diff --git a/.github/workflows/audits.yml b/.github/workflows/audits.yml index 026128b..14e3961 100644 --- a/.github/workflows/audits.yml +++ b/.github/workflows/audits.yml @@ -57,6 +57,10 @@ jobs: python-version: '3.12' cache: 'pip' + - uses: actions/setup-node@v4 + with: + node-version: '20' + - name: Install faircode + pytest run: | python -m pip install --upgrade pip diff --git a/assets/profiler-engine.js b/assets/profiler-engine.js index ce2d560..bf021f1 100644 --- a/assets/profiler-engine.js +++ b/assets/profiler-engine.js @@ -52,7 +52,17 @@ var SCORE_DROP_FLAG = 5; // Pandas-style missing tokens, so JS null-handling matches read_csv defaults. - var NA_TOKENS = { '': 1, 'na': 1, 'n/a': 1, 'nan': 1, 'null': 1, 'none': 1 }; + var NA_TOKENS = { + '': 1, + 'na': 1, + 'n/a': 1, + 'nan': 1, + 'null': 1, + // Intentionally exclude "none" to match the Python profiler. + // In this project, pd.read_csv() preserves the literal string "none" + // as a categorical value, so treating it as missing breaks Python↔JS + // parity (see credit_customers.csv). +}; // ── Keyword lists - MUST mirror faircode/detect.py ───────────────────── var KEYWORDS = [ @@ -447,6 +457,12 @@ flags.push(d.name + ": '" + g.label + "' is under-represented (" + (g.share * 100).toFixed(1) + '%)'); } + if (g.small_group) { + flags.push( + d.name + ": '" + g.label + "' has only " + + g.count + " rows; fairness metrics may be unreliable" + ); + } }); if (d.imbalance_ratio !== null && d.imbalance_ratio >= imbalanceFlag) { flags.push(d.name + ': imbalance ratio ' + d.imbalance_ratio.toFixed(1) + diff --git a/scripts/profile-js.js b/scripts/profile-js.js new file mode 100644 index 0000000..1ebe23a --- /dev/null +++ b/scripts/profile-js.js @@ -0,0 +1,22 @@ +#!/usr/bin/env node + +const fs = require("fs"); +const path = require("path"); + +// Load the profiler engine. It registers itself on globalThis.FairCodeProfiler. +require(path.join(__dirname, "..", "assets", "profiler-engine.js")); + +const E = globalThis.FairCodeProfiler; + +if (process.argv.length !== 3) { + console.error("Usage: node scripts/profile-js.js "); + process.exit(1); +} + +const csvPath = process.argv[2]; +const text = fs.readFileSync(csvPath, "utf8"); + +const table = E.parseCSV(text); +const result = E.profile(table); + +process.stdout.write(JSON.stringify(result)); diff --git a/tests/fixtures/AI_Fair_Recruitment_Dataset.csv b/tests/fixtures/AI_Fair_Recruitment_Dataset.csv new file mode 100644 index 0000000..7cd54c7 --- /dev/null +++ b/tests/fixtures/AI_Fair_Recruitment_Dataset.csv @@ -0,0 +1,121201 @@ +Candidate_ID,Gender,Age,Education_Level,Experience_Years,Skill_Score,Aptitude_Test_Score,Technical_Test_Score,Communication_Score,Certifications_Count,Previous_Companies,Interview_Score,Location,Job_Role_Applied,Expected_Salary,Hiring_Decision +1,Male,50,Bachelors,19,48,75,70,65,2.0,5,92,Urban,HR Executive,22214,1 +2,Other,36,Bachelors,18,9,53,46,25,2.0,4,77,Semi-Urban,Data Analyst,130094,0 +3,Female,58,Masters,11,1,85,62,72,1.0,3,90,Urban,ML Engineer,78652,0 +4,Male,48,Masters,0,74,35,79,67,6.0,3,9,Urban,HR Executive,144618,0 +5,Male,37,Bachelors,0,64,99,25,38,7.0,5,24,Urban,Data Analyst,133865,0 +6,Male,59,High School,10,92,95,71,68,0.0,0,10,Urban,Software Engineer,26830,1 +7,Male,39,Masters,4,39,57,50,21,7.0,4,63,Rural,Manager,40257,0 +8,Female,27,Masters,2,83,20,0,51,7.0,6,11,Urban,ML Engineer,141090,0 +9,Female,38,Bachelors,3,53,13,60,33,1.0,1,26,Urban,Data Analyst,147003,0 +10,Female,58,Diploma,1,39,98,7,65,2.0,5,2,Rural,ML Engineer,71587,0 +11,Male,46,Masters,14,55,53,84,70,5.0,5,71,Urban,Software Engineer,143539,1 +12,Other,48,Bachelors,14,28,4,35,19,2.0,2,51,Semi-Urban,Software Engineer,130033,0 +13,Female,27,Masters,10,92,26,63,73,8.0,4,95,Urban,ML Engineer,25183,1 +14,Male,59,Diploma,14,12,20,79,72,8.0,7,83,Urban,Software Engineer,35669,0 +15,Male,46,Bachelors,13,85,18,14,69,9.0,3,95,Rural,Data Analyst,121951,0 +16,Male,55,Diploma,17,85,68,68,54,7.0,3,83,Rural,Software Engineer,78593,1 +17,Male,28,Bachelors,2,29,0,2,64,7.0,1,60,Semi-Urban,Software Engineer,72168,0 +18,Male,24,Masters,9,2,21,58,12,7.0,7,14,Urban,HR Executive,105695,0 +19,Male,37,Bachelors,7,46,25,55,81,3.0,1,59,Urban,Data Analyst,132104,0 +20,Male,41,PhD,0,49,31,50,9,4.0,7,21,Urban,Data Analyst,117143,0 +21,Female,47,Masters,3,58,23,80,73,6.0,5,88,Semi-Urban,Manager,98480,1 +22,Male,59,Bachelors,2,52,78,33,49,0.0,3,40,Urban,HR Executive,120461,0 +23,Male,42,PhD,15,68,68,97,4,4.0,3,3,Urban,Manager,75469,1 +24,Male,43,Bachelors,13,77,0,75,28,7.0,0,96,Urban,ML Engineer,25503,1 +25,Male,23,Diploma,0,68,31,34,63,8.0,7,94,Urban,HR Executive,126306,0 +26,Female,51,PhD,5,99,78,86,30,1.0,4,87,Rural,Software Engineer,27418,1 +27,Male,28,Bachelors,18,82,39,85,40,1.0,1,21,Rural,Software Engineer,37668,0 +28,Male,34,Bachelors,13,26,20,43,26,4.0,5,12,Semi-Urban,Software Engineer,64846,0 +29,Male,47,Bachelors,18,46,23,49,85,3.0,1,47,Semi-Urban,Data Analyst,148389,0 +30,Male,45,Diploma,9,87,29,70,53,1.0,5,14,Semi-Urban,ML Engineer,101811,0 +31,Female,21,Diploma,18,18,98,2,21,5.0,3,37,Rural,Manager,39247,0 +32,Male,56,Diploma,19,71,36,42,95,7.0,6,66,Urban,Data Analyst,23159,0 +33,Male,44,High School,5,46,96,3,43,7.0,6,27,Rural,Software Engineer,125450,0 +34,Female,46,Masters,12,7,7,35,46,8.0,7,15,Urban,Data Analyst,73902,0 +35,Other,51,High School,7,29,46,83,37,7.0,4,8,Urban,Manager,72239,0 +36,Female,47,Bachelors,15,3,36,11,35,9.0,3,53,Urban,Software Engineer,54044,0 +37,Male,48,Bachelors,11,66,30,79,59,2.0,6,76,Semi-Urban,HR Executive,59427,1 +38,Male,51,Diploma,2,75,82,81,81,2.0,0,40,Rural,Data Analyst,28613,1 +39,Female,31,Bachelors,11,14,22,98,39,8.0,0,44,Urban,Manager,135418,0 +40,Male,50,Bachelors,13,13,73,85,86,4.0,3,45,Urban,HR Executive,100863,0 +41,Male,33,Bachelors,0,0,79,64,26,0.0,2,23,Rural,Software Engineer,99294,0 +42,Male,32,Diploma,12,23,0,57,96,2.0,6,39,Urban,Software Engineer,87062,0 +43,Male,50,High School,9,38,34,62,1,2.0,7,25,Rural,Data Analyst,46921,0 +44,Female,29,Diploma,7,40,1,13,79,8.0,2,6,Semi-Urban,Manager,133236,0 +45,Male,59,Diploma,8,84,53,27,19,6.0,5,38,Semi-Urban,HR Executive,33095,0 +46,Female,24,Bachelors,10,96,52,99,48,8.0,3,6,Rural,ML Engineer,42773,1 +47,Male,33,Bachelors,0,23,90,35,66,9.0,6,17,Rural,Software Engineer,31560,0 +48,Male,37,Diploma,19,58,35,0,31,5.0,3,27,Semi-Urban,Data Analyst,93695,0 +49,Male,21,Masters,18,19,82,38,86,9.0,0,60,Rural,ML Engineer,147464,0 +50,Male,36,Bachelors,18,13,64,26,7,6.0,2,53,Urban,Software Engineer,126798,0 +51,Other,30,Masters,1,86,25,73,60,6.0,7,60,Urban,HR Executive,71770,1 +52,Female,22,Diploma,13,73,25,43,46,2.0,3,13,Rural,HR Executive,87625,0 +53,Female,31,Bachelors,17,93,80,97,37,3.0,0,55,Semi-Urban,ML Engineer,141457,1 +54,Female,23,Diploma,4,52,15,11,9,7.0,7,10,Urban,Manager,149712,0 +55,Male,28,Diploma,9,13,44,37,58,9.0,1,15,Urban,ML Engineer,147446,0 +56,Female,36,Bachelors,12,64,79,23,82,4.0,4,90,Semi-Urban,Manager,26552,1 +57,Male,29,Bachelors,17,25,77,91,31,8.0,0,39,Rural,Data Analyst,68259,0 +58,Male,47,Bachelors,4,30,25,72,83,8.0,5,10,Urban,Manager,127740,0 +59,Male,42,Masters,10,4,75,20,44,9.0,6,7,Rural,ML Engineer,76056,0 +60,Male,47,High School,13,56,79,19,36,9.0,3,12,Semi-Urban,HR Executive,61312,0 +61,Male,58,Masters,14,59,1,4,69,6.0,0,63,Rural,HR Executive,109326,0 +62,Male,26,Bachelors,18,21,15,68,52,4.0,1,6,Urban,ML Engineer,127167,0 +63,Female,41,High School,18,95,52,17,37,3.0,3,79,Rural,Manager,24417,1 +64,Male,54,Diploma,5,11,40,39,12,7.0,7,61,Semi-Urban,ML Engineer,79217,0 +65,Male,27,Masters,0,9,56,16,65,8.0,7,57,Urban,Manager,105603,0 +66,Male,30,Masters,17,63,94,79,97,4.0,3,19,Urban,ML Engineer,44757,1 +67,Male,36,Bachelors,16,7,91,89,37,9.0,7,14,Rural,Manager,36243,0 +68,Female,54,Diploma,0,68,21,96,51,1.0,0,3,Urban,Data Analyst,40152,0 +69,Male,48,Bachelors,3,13,7,31,16,3.0,6,61,Semi-Urban,Software Engineer,102828,0 +70,Other,54,Diploma,12,15,4,60,80,8.0,6,75,Semi-Urban,HR Executive,126867,0 +71,Female,27,Bachelors,16,34,21,60,40,4.0,0,3,Rural,Software Engineer,123352,0 +72,Male,29,Masters,6,1,77,81,16,3.0,4,4,Urban,Data Analyst,24063,0 +73,Male,46,High School,4,49,20,18,94,9.0,4,36,Urban,Software Engineer,97945,0 +74,Female,38,High School,8,48,76,19,50,0.0,0,98,Rural,Software Engineer,49330,1 +75,Female,30,Bachelors,6,28,25,87,15,6.0,7,91,Urban,Software Engineer,99903,0 +76,Female,49,Masters,9,16,7,52,32,8.0,0,0,Urban,HR Executive,46165,0 +77,Female,34,Bachelors,3,1,73,43,72,6.0,5,34,Rural,ML Engineer,54360,0 +78,Male,34,Bachelors,13,78,68,48,86,1.0,2,82,Semi-Urban,Manager,103369,1 +79,Male,58,Bachelors,0,96,48,67,5,2.0,4,84,Urban,Software Engineer,146330,1 +80,Male,28,Bachelors,1,27,55,20,38,9.0,1,74,Urban,Software Engineer,93079,0 +81,Female,30,Bachelors,12,92,81,76,27,9.0,0,18,Urban,Data Analyst,73570,1 +82,Female,49,Diploma,10,47,69,80,10,4.0,5,76,Semi-Urban,ML Engineer,119166,1 +83,Male,39,High School,9,18,10,51,47,2.0,4,37,Urban,HR Executive,117818,0 +84,Male,59,Diploma,5,97,99,77,21,4.0,2,18,Semi-Urban,Data Analyst,108624,1 +85,Male,56,Bachelors,12,96,83,90,87,2.0,7,65,Semi-Urban,ML Engineer,135243,1 +86,Male,38,Masters,7,26,32,57,26,0.0,4,43,Urban,ML Engineer,84050,0 +87,Female,51,Masters,13,13,57,90,30,4.0,1,1,Urban,Manager,113116,0 +88,Female,34,Masters,15,98,9,0,14,7.0,3,2,Urban,HR Executive,132543,0 +89,Female,44,Bachelors,2,14,51,99,36,7.0,7,49,Semi-Urban,HR Executive,72218,0 +90,Male,49,Masters,9,56,17,98,91,9.0,6,63,Rural,ML Engineer,98059,0 +91,Male,54,High School,4,27,28,48,14,8.0,0,71,Urban,Data Analyst,120958,0 +92,Female,25,Bachelors,10,56,24,30,10,0.0,7,41,Urban,Manager,134203,0 +93,Female,51,Bachelors,14,10,52,3,1,6.0,0,76,Rural,HR Executive,107409,0 +94,Male,27,PhD,0,11,47,25,15,3.0,2,3,Urban,ML Engineer,100395,0 +95,Female,42,Masters,6,86,45,78,80,7.0,3,98,Rural,ML Engineer,94625,1 +96,Male,37,Masters,14,23,79,82,67,7.0,7,60,Urban,Software Engineer,94330,1 +97,Male,21,Masters,4,65,50,79,71,2.0,5,7,Semi-Urban,Manager,65524,0 +98,Male,52,Masters,1,32,38,47,81,9.0,2,79,Semi-Urban,ML Engineer,137355,0 +99,Male,23,Bachelors,4,0,22,81,82,0.0,3,37,Urban,Manager,112174,0 +100,Male,48,Bachelors,17,48,3,29,99,5.0,5,0,Rural,Manager,24083,0 +101,Male,35,Bachelors,3,36,85,29,54,5.0,5,3,Urban,ML Engineer,85554,0 +102,Female,59,Bachelors,5,60,91,84,74,3.0,1,61,Rural,ML Engineer,89156,1 +103,Male,42,Masters,8,92,53,69,56,9.0,3,41,Urban,ML Engineer,137289,1 +104,Male,39,Diploma,2,85,42,43,23,8.0,7,28,Urban,Software Engineer,37811,0 +105,Female,48,Masters,9,68,37,42,30,7.0,6,4,Urban,ML Engineer,66318,0 +106,Male,38,Bachelors,16,61,21,43,15,7.0,3,15,Semi-Urban,ML Engineer,32188,0 +107,Male,31,Bachelors,18,5,73,91,10,7.0,7,72,Urban,Data Analyst,146986,1 +108,Female,33,Masters,6,93,27,88,29,9.0,3,6,Rural,Manager,29489,0 +109,Male,59,High School,12,74,96,93,91,9.0,2,92,Urban,Manager,93139,1 +110,Male,48,Masters,14,0,42,97,85,4.0,1,57,Urban,Manager,53256,0 +111,Male,22,High School,4,50,99,53,92,7.0,0,50,Urban,Data Analyst,21223,1 +112,Male,55,Diploma,4,51,55,29,6,4.0,5,9,Semi-Urban,Manager,70065,0 +113,Female,50,Bachelors,10,10,17,73,10,3.0,0,79,Urban,Data Analyst,129868,0 +114,Female,48,Bachelors,8,90,55,14,84,9.0,4,32,Urban,ML Engineer,142212,0 +115,Female,59,Bachelors,4,25,12,12,75,8.0,7,74,Urban,HR Executive,132358,0 +116,Female,53,Diploma,11,18,29,11,18,4.0,4,93,Semi-Urban,Data Analyst,128181,0 +117,Female,51,Bachelors,1,30,85,40,87,6.0,6,38,Urban,Manager,63119,0 +118,Male,51,Diploma,3,4,89,67,93,1.0,1,90,Rural,Software Engineer,139516,1 +119,Female,30,Bachelors,8,63,46,21,70,8.0,6,14,Urban,HR Executive,54632,0 +120,Male,38,Bachelors,1,98,69,33,17,5.0,5,69,Semi-Urban,HR Executive,55687,1 +121,Female,51,Bachelors,7,73,89,65,49,1.0,2,98,Urban,Manager,31498,1 +122,Female,21,Bachelors,5,48,12,0,52,5.0,6,44,Urban,Manager,102535,0 +123,Male,46,Bachelors,9,96,38,97,47,5.0,4,32,Urban,Software Engineer,118568,1 +124,Male,35,Masters,3,44,72,38,66,7.0,0,23,Urban,HR Executive,89925,0 +125,Male,27,Masters,4,97,0,11,83,5.0,6,47,Urban,Data Analyst,47705,0 +126,Male,40,PhD,13,3,81,54,55,1.0,6,47,Semi-Urban,HR Executive,78265,0 +127,Female,41,Masters,0,61,55,37,75,1.0,6,74,Rural,Manager,115544,0 +128,Female,32,Diploma,6,25,89,66,60,6.0,4,42,Rural,Data Analyst,28382,0 +129,Male,42,Bachelors,14,96,80,90,97,0.0,4,82,Semi-Urban,Data Analyst,55363,1 +130,Male,29,Bachelors,9,70,39,76,92,6.0,0,78,Semi-Urban,ML Engineer,53463,1 +131,Male,33,Masters,8,28,38,80,27,6.0,3,49,Rural,HR Executive,63925,0 +132,Male,55,Diploma,11,22,86,24,38,4.0,4,58,Urban,ML Engineer,117181,0 +133,Male,31,High School,13,37,71,47,50,6.0,2,92,Semi-Urban,Manager,146134,1 +134,Male,34,Diploma,0,33,34,78,62,8.0,5,61,Semi-Urban,HR Executive,83733,0 +135,Female,51,Diploma,2,95,91,13,21,8.0,6,25,Urban,Data Analyst,73797,0 +136,Male,23,Bachelors,13,83,49,50,33,7.0,5,78,Rural,Manager,73948,1 +137,Male,56,Bachelors,9,3,33,70,88,1.0,6,17,Semi-Urban,ML Engineer,110935,0 +138,Female,43,High School,18,70,19,32,59,9.0,2,51,Urban,ML Engineer,73998,0 +139,Male,42,Masters,3,82,47,88,52,7.0,3,36,Urban,ML Engineer,125113,1 +140,Other,35,Bachelors,7,29,29,12,2,3.0,0,91,Urban,Manager,40526,0 +141,Other,51,Bachelors,11,82,26,71,66,9.0,2,26,Semi-Urban,Manager,70376,0 +142,Male,34,Masters,2,93,36,5,84,6.0,2,38,Urban,HR Executive,128591,0 +143,Male,50,Masters,8,40,96,66,31,4.0,7,45,Urban,Software Engineer,25430,1 +144,Male,44,Bachelors,6,91,99,34,74,5.0,7,53,Urban,Software Engineer,61638,1 +145,Male,39,Bachelors,3,13,36,21,46,0.0,6,55,Urban,Software Engineer,88349,0 +146,Male,27,Diploma,3,98,71,56,96,6.0,2,27,Urban,Software Engineer,60928,1 +147,Female,38,Bachelors,7,67,94,50,51,1.0,7,55,Urban,Data Analyst,41434,1 +148,Male,31,Bachelors,2,31,6,66,52,0.0,2,45,Rural,Manager,75907,0 +149,Male,45,Masters,6,38,96,39,33,4.0,3,11,Urban,Data Analyst,57299,0 +150,Male,59,Masters,4,5,93,2,83,8.0,3,48,Semi-Urban,HR Executive,88131,0 +151,Female,50,Bachelors,19,56,67,96,39,3.0,4,81,Rural,HR Executive,113279,1 +152,Male,32,Masters,15,32,5,86,69,2.0,6,5,Urban,Data Analyst,133397,0 +153,Male,41,Bachelors,12,97,26,61,29,6.0,7,51,Urban,Software Engineer,26201,1 +154,Male,30,High School,18,18,88,53,64,5.0,4,72,Urban,HR Executive,45143,0 +155,Other,54,Masters,11,32,99,19,72,2.0,7,86,Urban,Software Engineer,108786,0 +156,Male,45,Diploma,17,61,36,54,12,6.0,3,36,Urban,Manager,127290,0 +157,Female,43,Diploma,19,38,6,80,70,4.0,0,1,Urban,Software Engineer,84330,0 +158,Female,31,Bachelors,13,31,79,15,63,9.0,3,36,Rural,HR Executive,94914,0 +159,Male,53,Bachelors,17,63,15,39,84,8.0,2,31,Semi-Urban,Data Analyst,37184,0 +160,Female,57,Bachelors,8,84,68,46,4,1.0,4,48,Rural,Data Analyst,24604,1 +161,Male,41,Masters,14,71,97,98,64,9.0,2,22,Rural,ML Engineer,114274,1 +162,Female,52,Diploma,6,93,14,38,33,1.0,1,44,Urban,HR Executive,26489,0 +163,Female,42,Diploma,2,47,45,76,78,2.0,6,98,Urban,Manager,43673,1 +164,Male,37,Masters,16,85,6,73,44,5.0,1,1,Urban,ML Engineer,120248,0 +165,Male,56,Diploma,18,84,13,2,51,8.0,0,67,Urban,HR Executive,39331,0 +166,Female,48,High School,2,12,2,40,53,5.0,7,1,Urban,HR Executive,129792,0 +167,Male,37,Masters,9,15,60,23,62,5.0,3,72,Urban,Software Engineer,34788,0 +168,Male,34,Bachelors,14,56,81,66,53,0.0,3,30,Urban,ML Engineer,134108,0 +169,Male,47,PhD,12,11,54,57,7,3.0,5,66,Urban,Data Analyst,52122,0 +170,Male,27,PhD,14,59,33,29,92,0.0,3,32,Urban,Manager,138742,0 +171,Female,51,Diploma,3,28,71,34,32,8.0,4,27,Urban,Data Analyst,109767,0 +172,Male,32,High School,6,61,74,60,56,2.0,4,80,Urban,Software Engineer,109641,1 +173,Male,22,Bachelors,4,64,94,9,45,1.0,0,76,Rural,ML Engineer,30404,1 +174,Male,42,Bachelors,8,75,6,66,58,2.0,6,94,Urban,ML Engineer,94000,1 +175,Female,28,Masters,1,78,80,56,10,3.0,7,37,Rural,HR Executive,25593,1 +176,Male,36,Bachelors,4,39,21,70,58,9.0,0,17,Urban,Software Engineer,127259,0 +177,Female,45,High School,15,8,35,43,95,7.0,1,91,Semi-Urban,Manager,113088,0 +178,Male,23,Masters,13,24,56,46,7,3.0,0,10,Rural,Data Analyst,61075,0 +179,Female,50,Bachelors,2,2,52,3,72,8.0,2,52,Semi-Urban,HR Executive,45530,0 +180,Male,39,High School,19,5,62,75,71,2.0,1,79,Semi-Urban,ML Engineer,69144,0 +181,Male,49,Bachelors,12,18,89,19,99,0.0,0,15,Rural,Data Analyst,47496,0 +182,Male,25,Diploma,3,73,76,5,44,4.0,1,67,Semi-Urban,HR Executive,76691,0 +183,Female,40,Diploma,6,3,64,69,67,9.0,2,38,Rural,Software Engineer,111087,0 +184,Female,53,Masters,13,19,8,59,97,6.0,5,65,Urban,Software Engineer,146964,0 +185,Male,21,High School,14,14,29,42,35,5.0,7,12,Rural,Software Engineer,111702,0 +186,Female,52,High School,19,12,32,99,9,4.0,2,66,Urban,Software Engineer,46292,0 +187,Female,49,Bachelors,19,22,83,6,35,2.0,7,87,Urban,Software Engineer,110537,0 +188,Male,58,Diploma,10,12,34,81,94,1.0,6,71,Rural,ML Engineer,98550,0 +189,Male,43,Bachelors,4,90,22,90,49,0.0,3,1,Semi-Urban,HR Executive,37348,0 +190,Male,30,Bachelors,2,29,40,68,58,7.0,0,37,Semi-Urban,ML Engineer,126553,0 +191,Male,32,PhD,3,80,60,50,61,8.0,1,41,Urban,Manager,23558,0 +192,Female,55,Bachelors,5,2,72,80,64,5.0,4,14,Urban,Manager,118881,0 +193,Female,29,Bachelors,18,87,38,26,86,3.0,4,76,Urban,Manager,46229,0 +194,Female,31,Diploma,8,52,63,2,84,7.0,7,68,Semi-Urban,Data Analyst,41702,0 +195,Male,31,Diploma,12,29,34,49,8,8.0,5,88,Rural,ML Engineer,66629,0 +196,Male,58,High School,11,95,90,22,4,0.0,1,83,Urban,ML Engineer,49748,1 +197,Female,24,High School,18,81,61,25,13,6.0,6,35,Urban,HR Executive,46061,0 +198,Female,39,High School,7,64,42,29,4,6.0,0,9,Urban,Software Engineer,112952,0 +199,Female,41,High School,0,19,14,79,64,8.0,2,45,Rural,Software Engineer,79833,0 +200,Female,26,Bachelors,5,23,43,3,68,8.0,6,87,Urban,HR Executive,40479,0 +201,Female,43,Diploma,1,5,86,70,55,6.0,4,66,Urban,Manager,93720,0 +202,Male,59,High School,13,61,99,65,40,2.0,7,98,Urban,Software Engineer,67482,1 +203,Male,27,Bachelors,14,54,83,17,2,2.0,5,37,Urban,ML Engineer,76934,0 +204,Female,56,Bachelors,1,82,8,55,92,9.0,3,42,Urban,Software Engineer,36784,0 +205,Female,59,Bachelors,15,73,61,80,81,9.0,5,24,Urban,ML Engineer,141577,0 +206,Male,35,Bachelors,0,81,85,43,97,7.0,1,98,Urban,Manager,103820,1 +207,Male,29,Bachelors,15,75,21,36,25,4.0,6,97,Urban,Software Engineer,23237,0 +208,Female,42,Diploma,11,23,34,82,42,7.0,1,21,Urban,HR Executive,115642,0 +209,Male,31,Bachelors,8,70,51,12,25,5.0,3,91,Urban,ML Engineer,35460,0 +210,Male,55,Masters,7,56,87,69,40,7.0,3,65,Urban,Manager,93086,1 +211,Male,37,Bachelors,1,17,85,72,69,1.0,6,68,Rural,Data Analyst,58605,1 +212,Female,29,PhD,4,86,71,84,43,5.0,3,13,Semi-Urban,Manager,134506,1 +213,Female,54,Diploma,18,18,14,6,13,1.0,2,60,Semi-Urban,Software Engineer,122305,0 +214,Male,39,Bachelors,6,38,84,66,23,9.0,3,0,Semi-Urban,ML Engineer,65289,0 +215,Female,50,Masters,10,51,25,64,49,1.0,1,51,Rural,Manager,75821,0 +216,Male,42,Diploma,6,45,93,35,70,8.0,6,71,Urban,HR Executive,113739,1 +217,Male,46,High School,14,75,27,23,12,7.0,3,3,Urban,HR Executive,84361,0 +218,Female,50,Masters,11,51,73,71,29,4.0,4,49,Rural,HR Executive,41844,1 +219,Female,32,Bachelors,8,54,28,45,10,0.0,7,21,Urban,Software Engineer,33731,0 +220,Female,56,Bachelors,0,55,19,55,53,5.0,3,36,Urban,Software Engineer,114751,0 +221,Female,27,Bachelors,15,42,47,56,59,2.0,5,14,Rural,Software Engineer,100898,0 +222,Male,22,Bachelors,0,29,96,26,92,4.0,2,53,Urban,Software Engineer,105892,0 +223,Male,41,Bachelors,12,34,20,39,98,0.0,6,43,Rural,Manager,108323,0 +224,Male,47,High School,12,97,86,79,84,1.0,4,66,Urban,ML Engineer,90185,1 +225,Male,21,PhD,19,44,46,46,66,6.0,3,99,Urban,Software Engineer,64830,1 +226,Male,34,Bachelors,19,45,44,7,60,1.0,2,82,Urban,Software Engineer,80110,0 +227,Other,22,Bachelors,2,61,5,20,70,7.0,6,18,Urban,ML Engineer,131508,0 +228,Male,43,High School,0,55,41,81,51,0.0,1,80,Urban,HR Executive,63559,1 +229,Female,46,Bachelors,12,21,47,37,0,9.0,5,96,Semi-Urban,Data Analyst,133672,0 +230,Female,45,Bachelors,8,5,93,65,0,6.0,4,63,Rural,HR Executive,107141,0 +231,Female,35,Bachelors,5,1,80,50,50,0.0,4,1,Semi-Urban,Manager,83110,0 +232,Male,49,Diploma,15,13,50,75,19,8.0,3,10,Urban,ML Engineer,90100,0 +233,Male,48,Diploma,10,15,53,32,38,6.0,0,6,Semi-Urban,ML Engineer,72397,0 +234,Male,59,Diploma,11,69,68,5,60,4.0,2,30,Semi-Urban,Manager,33225,0 +235,Male,24,Bachelors,12,29,53,72,13,8.0,2,21,Urban,Data Analyst,124929,0 +236,Female,50,Diploma,4,14,25,29,12,0.0,4,59,Urban,HR Executive,83599,0 +237,Male,30,Bachelors,15,38,52,25,60,8.0,0,48,Rural,HR Executive,136968,0 +238,Male,30,Bachelors,16,9,14,35,3,0.0,0,68,Semi-Urban,HR Executive,51924,0 +239,Female,42,Diploma,0,78,69,96,47,0.0,5,97,Urban,HR Executive,32289,1 +240,Male,36,Diploma,15,40,15,33,96,5.0,7,14,Urban,HR Executive,89594,0 +241,Female,59,Bachelors,15,49,61,6,54,7.0,3,1,Urban,Software Engineer,51818,0 +242,Other,33,Masters,5,83,61,36,59,8.0,6,41,Urban,Software Engineer,111900,0 +243,Female,59,Bachelors,9,2,98,35,55,3.0,3,83,Semi-Urban,ML Engineer,47927,0 +244,Male,50,Bachelors,10,32,79,62,99,2.0,2,11,Urban,HR Executive,138602,0 +245,Male,33,Bachelors,17,84,42,8,2,0.0,2,51,Urban,ML Engineer,81164,0 +246,Female,46,Bachelors,19,7,59,83,86,3.0,3,65,Urban,Software Engineer,116646,0 +247,Male,51,Bachelors,19,82,24,50,15,7.0,7,45,Urban,ML Engineer,22751,0 +248,Other,59,Bachelors,17,23,57,85,96,1.0,6,72,Semi-Urban,Manager,47078,0 +249,Other,47,Bachelors,15,9,18,11,67,5.0,7,29,Semi-Urban,Data Analyst,100288,0 +250,Female,24,Bachelors,15,40,6,39,13,5.0,4,81,Rural,Manager,51430,0 +251,Male,32,High School,1,1,18,2,69,5.0,5,79,Urban,Software Engineer,71773,0 +252,Male,55,Diploma,2,55,28,34,40,4.0,0,88,Urban,Software Engineer,70150,0 +253,Female,59,Bachelors,9,5,37,18,59,4.0,2,11,Urban,Manager,119954,0 +254,Male,21,Masters,1,21,96,64,75,9.0,6,29,Urban,Manager,112332,0 +255,Male,36,High School,18,51,76,52,48,9.0,6,22,Rural,Data Analyst,72631,0 +256,Male,42,Masters,1,65,33,77,88,8.0,5,60,Rural,HR Executive,115011,1 +257,Female,56,Bachelors,19,33,7,87,88,5.0,4,61,Urban,HR Executive,63624,0 +258,Female,54,Bachelors,14,79,84,44,58,6.0,4,89,Semi-Urban,Manager,70407,1 +259,Male,42,Bachelors,13,49,79,93,49,5.0,0,56,Semi-Urban,Manager,72466,1 +260,Male,34,Bachelors,9,99,10,10,53,4.0,7,12,Urban,Manager,143401,0 +261,Female,23,High School,3,9,67,26,56,5.0,1,46,Urban,ML Engineer,118119,0 +262,Other,58,Diploma,17,15,59,38,94,1.0,3,79,Urban,Software Engineer,32574,0 +263,Male,33,Bachelors,11,31,64,71,48,0.0,5,42,Urban,Data Analyst,129433,0 +264,Male,22,Bachelors,3,26,79,26,71,9.0,7,60,Semi-Urban,HR Executive,22235,0 +265,Female,29,Bachelors,6,77,52,35,99,3.0,0,37,Urban,ML Engineer,53402,0 +266,Female,55,Diploma,11,81,51,25,69,5.0,0,60,Rural,HR Executive,131761,0 +267,Female,47,Bachelors,11,36,52,35,63,9.0,2,10,Urban,HR Executive,95730,0 +268,Female,40,High School,7,83,33,97,31,5.0,7,49,Semi-Urban,ML Engineer,117147,1 +269,Male,41,High School,13,64,70,33,2,7.0,7,14,Urban,HR Executive,84219,0 +270,Male,26,Diploma,4,91,56,52,75,1.0,5,26,Urban,Data Analyst,141926,0 +271,Female,49,Bachelors,0,94,36,97,35,0.0,0,67,Urban,ML Engineer,46109,1 +272,Female,42,Masters,18,35,99,80,82,1.0,7,5,Rural,Data Analyst,72558,0 +273,Female,55,Masters,12,19,59,61,41,0.0,2,30,Semi-Urban,Manager,117810,0 +274,Female,57,High School,19,84,21,23,13,4.0,6,79,Semi-Urban,HR Executive,76610,0 +275,Male,43,Diploma,11,32,23,46,7,2.0,1,5,Urban,Software Engineer,139611,0 +276,Male,49,Bachelors,11,24,48,53,70,5.0,4,89,Urban,Software Engineer,78995,0 +277,Female,47,Masters,4,99,13,39,97,5.0,5,59,Urban,Software Engineer,94095,0 +278,Female,35,Bachelors,14,55,15,81,55,6.0,1,6,Urban,HR Executive,129492,0 +279,Female,55,Bachelors,17,94,91,97,21,3.0,2,4,Urban,ML Engineer,126554,1 +280,Female,47,Masters,3,93,97,63,53,3.0,4,77,Semi-Urban,HR Executive,28831,1 +281,Female,32,Diploma,1,12,68,75,64,1.0,0,7,Rural,Software Engineer,83243,0 +282,Male,28,Masters,8,73,80,81,42,7.0,0,66,Urban,Software Engineer,100435,1 +283,Male,54,Masters,16,69,81,22,6,2.0,1,13,Urban,ML Engineer,140810,0 +284,Male,36,Bachelors,4,28,50,94,37,0.0,7,34,Rural,ML Engineer,110786,0 +285,Male,56,Bachelors,4,18,84,50,24,1.0,7,59,Rural,Data Analyst,31188,0 +286,Male,37,Bachelors,2,20,36,42,9,1.0,0,47,Urban,ML Engineer,27332,0 +287,Male,45,Diploma,17,45,34,44,26,2.0,5,30,Semi-Urban,HR Executive,76322,0 +288,Male,46,Bachelors,18,14,61,49,36,2.0,0,21,Semi-Urban,Manager,112976,0 +289,Male,37,Bachelors,3,34,3,2,36,9.0,3,17,Rural,HR Executive,26311,0 +290,Male,58,Bachelors,6,53,74,66,23,1.0,3,76,Urban,Software Engineer,123183,1 +291,Male,58,Bachelors,15,90,91,26,8,2.0,6,15,Urban,Manager,22601,0 +292,Male,32,Masters,7,59,92,70,57,8.0,3,95,Rural,Manager,91108,1 +293,Female,33,High School,19,54,52,4,29,2.0,7,11,Rural,Manager,134521,0 +294,Male,26,Masters,9,22,14,41,82,7.0,2,55,Urban,Data Analyst,119150,0 +295,Male,29,Bachelors,11,42,47,20,73,7.0,3,72,Urban,HR Executive,43348,0 +296,Male,42,Masters,13,46,69,53,61,2.0,1,24,Urban,HR Executive,46544,0 +297,Female,23,Masters,5,16,55,4,69,8.0,1,1,Urban,ML Engineer,148495,0 +298,Male,46,High School,7,70,89,14,35,9.0,3,76,Urban,Software Engineer,62926,1 +299,Female,54,Bachelors,9,21,68,54,99,2.0,7,71,Urban,ML Engineer,124888,0 +300,Male,24,Diploma,11,1,40,53,41,9.0,6,90,Semi-Urban,HR Executive,33256,0 +301,Male,22,Bachelors,1,34,89,83,40,1.0,4,17,Urban,Manager,59888,0 +302,Male,56,Diploma,15,33,61,74,95,0.0,6,11,Urban,Software Engineer,90688,0 +303,Male,33,Bachelors,6,41,60,0,77,1.0,4,32,Urban,Manager,61415,0 +304,Female,57,High School,1,53,71,33,87,9.0,3,45,Urban,Data Analyst,134384,0 +305,Female,29,High School,4,22,42,18,59,9.0,1,46,Semi-Urban,HR Executive,32668,0 +306,Other,28,Bachelors,5,30,72,38,37,7.0,2,6,Urban,Manager,81406,0 +307,Male,53,Bachelors,15,14,84,82,60,5.0,0,80,Urban,ML Engineer,53066,1 +308,Male,50,Bachelors,13,8,67,32,93,9.0,4,30,Urban,Manager,26939,0 +309,Female,53,Bachelors,4,49,91,46,3,6.0,0,5,Urban,Software Engineer,110384,0 +310,Male,37,Diploma,0,53,92,59,48,6.0,5,22,Rural,ML Engineer,20979,0 +311,Male,55,Bachelors,4,81,92,61,50,3.0,1,61,Urban,Software Engineer,42621,1 +312,Male,44,Masters,16,58,74,11,56,5.0,0,69,Urban,Manager,26524,0 +313,Male,42,Masters,3,90,35,33,98,7.0,0,58,Rural,Software Engineer,134946,0 +314,Other,24,Bachelors,14,89,29,25,0,6.0,3,67,Semi-Urban,Software Engineer,109350,0 +315,Female,29,Bachelors,11,74,66,5,31,5.0,7,12,Semi-Urban,ML Engineer,147204,0 +316,Female,23,High School,17,62,64,87,90,4.0,1,24,Semi-Urban,HR Executive,57936,0 +317,Male,36,Bachelors,4,19,59,73,1,8.0,2,74,Urban,Data Analyst,36293,0 +318,Male,58,High School,9,3,17,17,11,5.0,3,31,Semi-Urban,Manager,97296,0 +319,Male,27,High School,13,12,99,14,42,8.0,0,97,Semi-Urban,ML Engineer,138541,0 +320,Male,40,Diploma,14,6,14,11,42,6.0,1,84,Urban,HR Executive,67952,0 +321,Male,38,High School,13,12,24,8,63,1.0,0,81,Semi-Urban,Software Engineer,73568,0 +322,Female,52,Diploma,15,60,12,61,92,1.0,6,36,Urban,Manager,142320,0 +323,Female,31,High School,15,75,89,60,80,4.0,6,9,Semi-Urban,HR Executive,80913,0 +324,Male,50,Masters,15,96,36,6,67,8.0,0,86,Urban,Data Analyst,27526,0 +325,Other,44,Bachelors,2,93,13,10,81,4.0,2,91,Semi-Urban,ML Engineer,26018,0 +326,Female,47,PhD,13,36,76,65,76,0.0,6,24,Rural,ML Engineer,68732,0 +327,Male,51,Bachelors,10,8,24,81,53,0.0,2,63,Urban,HR Executive,72587,0 +328,Female,26,Bachelors,18,42,58,98,47,9.0,6,45,Urban,Data Analyst,34084,1 +329,Male,47,Masters,0,94,52,69,90,9.0,0,72,Semi-Urban,Software Engineer,89629,1 +330,Male,35,Masters,8,16,45,20,78,0.0,4,12,Semi-Urban,ML Engineer,124863,0 +331,Male,33,High School,12,66,26,81,37,0.0,4,89,Semi-Urban,HR Executive,99105,1 +332,Female,27,Bachelors,19,78,56,22,83,3.0,4,80,Urban,Manager,74519,0 +333,Male,59,Bachelors,2,51,47,87,77,4.0,6,74,Semi-Urban,HR Executive,101104,1 +334,Male,52,Bachelors,7,87,7,28,43,5.0,0,96,Urban,ML Engineer,118951,0 +335,Male,40,PhD,3,13,8,82,51,6.0,7,34,Urban,Data Analyst,44096,0 +336,Male,32,Diploma,13,85,19,55,1,4.0,0,22,Urban,Manager,108973,0 +337,Female,38,Bachelors,11,84,80,36,6,2.0,1,37,Semi-Urban,Manager,142052,0 +338,Female,34,Masters,5,47,30,33,37,4.0,2,55,Semi-Urban,ML Engineer,47185,0 +339,Male,38,Diploma,15,31,34,38,18,6.0,0,14,Urban,Data Analyst,113867,0 +340,Male,41,Diploma,10,41,12,29,35,3.0,5,80,Urban,ML Engineer,31553,0 +341,Male,53,Bachelors,7,57,47,86,60,1.0,7,26,Urban,Software Engineer,144132,0 +342,Male,50,Bachelors,4,45,41,18,56,7.0,2,60,Rural,Data Analyst,32817,0 +343,Male,38,Diploma,4,17,98,84,79,4.0,6,47,Urban,Software Engineer,66743,1 +344,Male,23,Diploma,1,36,26,79,23,3.0,5,33,Urban,Software Engineer,90630,0 +345,Male,52,Bachelors,3,88,58,8,94,8.0,7,67,Urban,Software Engineer,90629,0 +346,Female,22,Bachelors,15,39,58,99,20,7.0,4,87,Urban,Manager,35745,1 +347,Female,31,Diploma,15,15,46,36,12,0.0,3,17,Semi-Urban,Data Analyst,66761,0 +348,Male,22,Diploma,5,8,59,86,76,2.0,1,70,Rural,ML Engineer,148731,0 +349,Male,51,Diploma,17,21,30,94,17,3.0,6,33,Semi-Urban,HR Executive,45130,0 +350,Female,55,Bachelors,14,93,68,14,73,1.0,5,13,Urban,Manager,140786,0 +351,Male,49,Diploma,14,91,91,57,35,5.0,2,83,Semi-Urban,HR Executive,82156,1 +352,Female,49,Diploma,13,6,21,94,95,1.0,0,22,Rural,Manager,136543,0 +353,Female,53,Diploma,17,59,12,26,90,5.0,4,48,Semi-Urban,Manager,114499,0 +354,Male,23,PhD,0,57,46,12,86,0.0,0,18,Urban,Manager,58651,0 +355,Male,21,High School,11,62,6,33,63,3.0,5,58,Urban,HR Executive,76145,0 +356,Female,32,Bachelors,9,48,86,83,21,1.0,7,45,Urban,ML Engineer,62359,1 +357,Male,25,High School,11,23,95,89,31,4.0,5,41,Urban,ML Engineer,115084,1 +358,Male,34,Bachelors,13,3,71,45,86,3.0,4,27,Semi-Urban,HR Executive,44346,0 +359,Female,53,High School,12,47,18,1,98,3.0,2,1,Urban,Software Engineer,71126,0 +360,Male,27,Masters,19,27,54,39,67,1.0,2,69,Urban,Manager,147816,0 +361,Male,57,PhD,0,99,98,21,77,2.0,3,80,Semi-Urban,ML Engineer,47167,1 +362,Female,50,Masters,12,19,60,53,51,1.0,2,59,Semi-Urban,ML Engineer,74606,0 +363,Male,38,Diploma,14,50,91,3,86,8.0,6,99,Urban,Software Engineer,77370,1 +364,Male,57,Diploma,12,4,65,6,66,6.0,1,51,Urban,ML Engineer,113769,0 +365,Female,38,PhD,16,86,76,3,43,5.0,3,54,Semi-Urban,Data Analyst,87678,0 +366,Male,56,PhD,11,32,65,0,3,4.0,6,48,Urban,Data Analyst,32671,0 +367,Other,30,High School,3,73,43,36,30,3.0,7,25,Rural,ML Engineer,141234,0 +368,Female,50,Diploma,2,21,55,73,97,4.0,7,60,Urban,Data Analyst,41961,0 +369,Male,34,High School,14,1,81,28,42,2.0,3,92,Urban,Manager,106514,0 +370,Male,41,Diploma,11,84,91,47,73,3.0,1,11,Urban,Manager,105283,0 +371,Male,43,Bachelors,18,59,77,77,29,6.0,7,0,Urban,HR Executive,120201,0 +372,Male,41,Bachelors,11,13,28,58,74,4.0,6,18,Semi-Urban,ML Engineer,81555,0 +373,Male,52,Bachelors,2,5,0,98,52,8.0,1,31,Rural,ML Engineer,80369,0 +374,Female,50,High School,14,87,17,74,1,8.0,2,79,Urban,HR Executive,59992,1 +375,Male,52,Diploma,15,23,26,62,60,5.0,6,88,Urban,ML Engineer,32386,0 +376,Male,32,Masters,9,68,52,55,39,0.0,4,3,Urban,HR Executive,107556,0 +377,Female,38,High School,7,75,74,75,12,1.0,1,51,Rural,HR Executive,76569,1 +378,Male,58,Bachelors,17,16,40,23,33,1.0,3,80,Urban,Data Analyst,72130,0 +379,Female,42,High School,8,88,78,85,38,5.0,5,78,Urban,Manager,72917,1 +380,Male,59,Diploma,4,16,68,54,64,2.0,1,46,Urban,HR Executive,95851,0 +381,Male,24,Bachelors,7,74,18,61,5,0.0,2,61,Rural,Manager,46565,0 +382,Female,30,Masters,15,43,92,5,92,9.0,6,15,Urban,Data Analyst,40221,0 +383,Female,49,High School,16,18,39,68,59,9.0,7,89,Rural,ML Engineer,105159,0 +384,Female,36,PhD,13,45,12,63,21,4.0,5,27,Semi-Urban,Manager,66592,0 +385,Female,54,PhD,17,88,71,55,18,3.0,2,63,Urban,Manager,66156,1 +386,Female,39,PhD,3,76,99,81,95,5.0,7,36,Semi-Urban,Software Engineer,131473,1 +387,Male,30,Diploma,15,41,73,38,71,6.0,6,59,Urban,ML Engineer,149600,0 +388,Male,32,Bachelors,3,15,76,89,78,5.0,4,20,Urban,Manager,99785,0 +389,Female,28,Masters,5,96,40,91,33,3.0,7,74,Urban,Data Analyst,49392,1 +390,Female,35,Diploma,0,88,35,77,34,5.0,6,34,Semi-Urban,Data Analyst,101710,0 +391,Other,55,Bachelors,19,81,78,30,63,2.0,0,4,Semi-Urban,Manager,25384,0 +392,Male,52,Masters,6,59,47,7,78,8.0,2,58,Urban,HR Executive,59598,0 +393,Male,45,PhD,6,26,0,6,58,0.0,0,28,Urban,ML Engineer,83194,0 +394,Female,42,Diploma,12,54,56,67,81,8.0,7,35,Semi-Urban,Manager,138599,0 +395,Male,36,Bachelors,8,93,11,25,32,3.0,0,51,Semi-Urban,Manager,44398,0 +396,Female,38,Diploma,17,59,16,48,10,2.0,1,71,Urban,HR Executive,45397,0 +397,Female,47,Bachelors,8,75,51,90,78,5.0,5,3,Rural,Data Analyst,26722,0 +398,Male,40,Masters,18,88,53,54,81,2.0,2,20,Urban,HR Executive,139998,0 +399,Female,39,Diploma,3,72,94,1,75,9.0,6,31,Semi-Urban,Data Analyst,67151,0 +400,Female,37,Diploma,9,98,11,10,8,4.0,5,42,Semi-Urban,Software Engineer,121921,0 +401,Male,51,Masters,5,92,18,47,60,1.0,1,87,Urban,Data Analyst,76454,1 +402,Female,28,Diploma,13,65,11,6,40,9.0,5,3,Urban,Data Analyst,36518,0 +403,Male,21,Masters,19,50,90,93,6,7.0,3,46,Rural,ML Engineer,134180,1 +404,Female,48,High School,14,12,4,75,1,0.0,0,67,Semi-Urban,HR Executive,108610,0 +405,Male,46,PhD,3,72,59,55,27,5.0,2,16,Urban,HR Executive,123585,0 +406,Female,21,Bachelors,16,26,74,5,83,0.0,2,8,Urban,Data Analyst,117607,0 +407,Male,49,Diploma,6,54,77,32,11,8.0,6,82,Urban,ML Engineer,98744,1 +408,Male,45,PhD,18,99,33,75,0,2.0,5,70,Semi-Urban,Manager,112781,1 +409,Female,53,Diploma,5,92,1,4,33,5.0,4,15,Urban,ML Engineer,34741,0 +410,Male,30,Masters,2,34,15,43,2,7.0,1,54,Rural,Manager,68518,0 +411,Male,55,Masters,12,45,93,77,24,1.0,0,88,Urban,Data Analyst,79689,1 +412,Other,57,High School,17,54,79,94,72,1.0,6,65,Rural,Data Analyst,55934,1 +413,Other,37,Bachelors,8,88,26,48,47,4.0,3,7,Semi-Urban,Software Engineer,75003,0 +414,Male,34,Bachelors,15,58,33,57,10,9.0,3,51,Semi-Urban,Manager,62119,0 +415,Female,40,Bachelors,17,25,28,49,39,8.0,0,29,Urban,HR Executive,54406,0 +416,Male,36,Diploma,4,22,69,42,46,6.0,5,58,Urban,Manager,103355,0 +417,Male,24,High School,14,2,28,46,57,7.0,1,44,Semi-Urban,Data Analyst,137608,0 +418,Male,38,Bachelors,4,73,78,44,37,2.0,1,73,Semi-Urban,Data Analyst,108691,1 +419,Female,59,Diploma,10,87,81,96,24,0.0,6,46,Urban,Manager,28358,1 +420,Female,24,Bachelors,8,98,29,92,85,7.0,5,78,Urban,Software Engineer,49166,1 +421,Female,46,Bachelors,9,80,35,15,71,2.0,6,30,Urban,HR Executive,98192,0 +422,Female,33,High School,0,13,23,16,0,3.0,1,94,Semi-Urban,Manager,51236,0 +423,Male,45,Bachelors,12,55,44,97,63,3.0,5,78,Urban,ML Engineer,75455,1 +424,Male,41,Bachelors,19,94,1,44,86,7.0,3,57,Semi-Urban,ML Engineer,82567,0 +425,Male,33,Masters,15,12,80,60,40,8.0,3,67,Urban,Software Engineer,53202,0 +426,Male,41,Bachelors,16,61,12,97,40,8.0,3,65,Urban,Data Analyst,119924,1 +427,Male,35,Bachelors,19,4,52,2,92,9.0,4,57,Urban,Software Engineer,64562,0 +428,Female,51,Masters,14,19,80,48,41,7.0,4,30,Semi-Urban,Data Analyst,34571,0 +429,Male,25,Bachelors,17,87,96,41,68,8.0,4,23,Urban,HR Executive,28847,1 +430,Male,41,Diploma,9,83,74,22,93,6.0,5,56,Rural,HR Executive,132844,1 +431,Male,41,Bachelors,15,65,85,83,88,9.0,6,47,Urban,HR Executive,112116,1 +432,Female,29,Masters,16,89,4,77,14,6.0,5,91,Urban,HR Executive,80270,1 +433,Female,29,Bachelors,8,99,49,33,38,5.0,2,1,Semi-Urban,Data Analyst,47760,0 +434,Male,29,Masters,16,37,85,42,23,9.0,3,17,Rural,Manager,61519,0 +435,Male,29,Bachelors,11,60,3,35,82,2.0,7,36,Rural,Manager,101021,0 +436,Female,34,Bachelors,1,38,6,1,15,9.0,4,41,Semi-Urban,ML Engineer,100668,0 +437,Male,42,High School,12,64,45,51,33,9.0,5,85,Rural,Manager,101193,1 +438,Female,24,Bachelors,16,48,69,11,74,6.0,6,14,Urban,ML Engineer,80894,0 +439,Female,50,PhD,19,14,90,19,47,1.0,2,99,Urban,Data Analyst,147338,0 +440,Male,32,Masters,14,94,93,28,53,9.0,1,73,Urban,HR Executive,66400,1 +441,Male,57,Masters,7,55,18,40,34,0.0,0,9,Semi-Urban,ML Engineer,69201,0 +442,Other,49,Masters,13,6,90,78,95,2.0,0,92,Urban,Software Engineer,98913,1 +443,Male,36,Bachelors,11,53,47,66,20,6.0,0,76,Semi-Urban,ML Engineer,30510,1 +444,Male,35,Bachelors,19,30,47,75,72,4.0,2,71,Semi-Urban,ML Engineer,143887,0 +445,Female,28,Masters,9,34,72,90,34,3.0,2,57,Semi-Urban,ML Engineer,32434,1 +446,Female,30,Diploma,19,68,55,81,72,6.0,1,8,Urban,HR Executive,124603,0 +447,Other,35,Bachelors,4,37,23,0,96,2.0,7,80,Urban,Manager,102748,0 +448,Female,53,Bachelors,1,43,63,82,55,1.0,2,64,Urban,Data Analyst,127618,1 +449,Male,28,Bachelors,18,40,26,58,95,0.0,1,51,Rural,Data Analyst,133763,0 +450,Male,48,Diploma,5,21,31,54,24,7.0,4,89,Rural,Data Analyst,105449,0 +451,Female,33,Masters,12,18,48,80,65,5.0,1,78,Urban,ML Engineer,122850,0 +452,Male,41,Diploma,3,94,31,23,20,7.0,5,17,Urban,Manager,100145,0 +453,Male,33,Masters,7,86,98,4,15,3.0,5,91,Urban,HR Executive,29823,1 +454,Female,53,Bachelors,5,16,21,71,52,3.0,5,77,Urban,HR Executive,54232,0 +455,Male,42,PhD,7,48,49,87,66,8.0,7,18,Urban,Data Analyst,131165,0 +456,Male,35,Bachelors,9,87,15,7,13,6.0,2,81,Urban,Manager,49274,0 +457,Male,42,Bachelors,14,37,95,63,58,0.0,7,62,Semi-Urban,Data Analyst,135249,1 +458,Male,39,Bachelors,10,23,81,57,22,1.0,2,38,Urban,Software Engineer,105804,0 +459,Male,32,High School,8,90,42,73,91,1.0,7,87,Urban,Manager,48276,1 +460,Male,45,Diploma,8,69,29,60,54,7.0,3,92,Semi-Urban,Software Engineer,49778,1 +461,Male,46,Bachelors,19,48,33,79,56,1.0,2,52,Urban,Manager,124043,0 +462,Female,45,Bachelors,19,2,3,95,39,7.0,4,83,Urban,Manager,33215,0 +463,Female,47,Bachelors,12,75,21,94,3,4.0,4,11,Urban,Manager,74920,0 +464,Male,59,Masters,18,9,87,19,25,0.0,3,46,Rural,Software Engineer,76925,0 +465,Other,49,Bachelors,5,58,47,75,56,4.0,5,97,Urban,HR Executive,97759,1 +466,Male,50,Bachelors,18,19,3,78,93,4.0,6,41,Semi-Urban,Software Engineer,132718,0 +467,Male,41,High School,4,60,60,53,2,8.0,0,19,Urban,HR Executive,28336,0 +468,Female,43,PhD,6,33,21,2,43,4.0,0,88,Rural,HR Executive,147333,0 +469,Male,30,Diploma,13,13,8,88,26,1.0,3,57,Urban,HR Executive,65232,0 +470,Other,51,Masters,5,47,55,24,11,2.0,5,57,Semi-Urban,Software Engineer,100687,0 +471,Male,22,High School,17,78,3,3,62,9.0,5,16,Urban,Software Engineer,62360,0 +472,Other,31,Diploma,13,10,30,40,26,9.0,2,40,Urban,Manager,55442,0 +473,Male,59,High School,6,65,73,26,70,8.0,6,99,Urban,Manager,43965,1 +474,Female,44,Bachelors,16,10,90,66,79,1.0,4,40,Urban,Manager,144347,0 +475,Male,26,Bachelors,8,99,1,25,73,5.0,5,99,Urban,Software Engineer,54781,0 +476,Other,48,Masters,16,78,20,71,10,5.0,4,99,Urban,Data Analyst,92809,1 +477,Male,32,Masters,10,8,28,50,7,3.0,1,82,Rural,Software Engineer,73755,0 +478,Male,49,Bachelors,11,60,80,6,6,3.0,2,15,Semi-Urban,Software Engineer,97872,0 +479,Other,54,Bachelors,12,57,70,91,34,3.0,6,68,Rural,Software Engineer,76795,1 +480,Male,38,High School,19,64,66,38,50,5.0,0,48,Urban,Manager,87803,0 +481,Female,53,Diploma,3,11,66,74,84,3.0,3,29,Urban,HR Executive,51257,0 +482,Female,30,Bachelors,2,43,24,66,38,2.0,5,85,Rural,Software Engineer,93975,0 +483,Male,29,Bachelors,1,84,38,90,8,1.0,4,78,Rural,Data Analyst,70981,1 +484,Female,58,High School,17,25,71,4,5,6.0,5,14,Semi-Urban,ML Engineer,47590,0 +485,Male,58,Diploma,9,73,50,35,49,0.0,4,59,Urban,Manager,70211,0 +486,Female,42,Masters,3,57,57,36,74,3.0,6,51,Urban,Manager,140116,0 +487,Male,33,Masters,3,22,91,51,97,3.0,1,43,Urban,Manager,36279,0 +488,Male,36,PhD,0,81,48,97,10,9.0,6,95,Urban,HR Executive,83102,1 +489,Other,56,Diploma,11,44,47,66,46,9.0,4,83,Semi-Urban,ML Engineer,122516,0 +490,Female,51,High School,7,38,53,58,77,4.0,4,1,Urban,Manager,111602,0 +491,Male,21,Bachelors,15,59,24,63,85,3.0,7,15,Rural,ML Engineer,94932,0 +492,Female,27,Diploma,7,22,32,64,45,3.0,1,89,Urban,Software Engineer,84340,0 +493,Male,42,Bachelors,13,90,88,32,86,6.0,1,14,Urban,Software Engineer,87716,0 +494,Male,50,Bachelors,13,38,20,43,14,6.0,4,53,Urban,Software Engineer,127855,0 +495,Male,41,High School,13,0,13,67,69,0.0,1,34,Urban,Manager,24387,0 +496,Male,52,Diploma,9,33,1,45,43,5.0,0,1,Rural,Software Engineer,88776,0 +497,Male,22,Bachelors,2,33,87,30,14,1.0,4,30,Rural,Manager,90816,0 +498,Male,49,Masters,10,16,98,55,21,3.0,6,37,Rural,HR Executive,77583,0 +499,Other,21,Diploma,3,44,88,46,25,0.0,2,95,Urban,Software Engineer,148072,1 +500,Other,49,Masters,11,56,81,6,60,7.0,7,54,Urban,ML Engineer,86136,0 +501,Female,41,High School,15,69,40,24,34,5.0,7,19,Semi-Urban,Data Analyst,84649,0 +502,Male,37,Diploma,15,28,76,80,17,7.0,7,40,Urban,Data Analyst,126396,0 +503,Male,43,Diploma,8,91,71,56,23,4.0,5,78,Semi-Urban,Manager,65869,1 +504,Female,36,Bachelors,11,33,51,17,57,1.0,6,69,Urban,Data Analyst,138596,0 +505,Female,25,Diploma,15,91,15,9,80,8.0,7,43,Semi-Urban,HR Executive,128086,0 +506,Male,33,Diploma,15,92,16,72,46,6.0,0,61,Urban,Manager,111700,1 +507,Female,37,Bachelors,1,97,27,53,95,3.0,0,43,Rural,Manager,55884,0 +508,Female,30,Bachelors,1,17,32,59,25,4.0,0,62,Urban,HR Executive,116031,0 +509,Female,40,Diploma,6,82,78,52,19,2.0,6,92,Urban,Software Engineer,103723,1 +510,Female,51,Diploma,16,21,69,30,66,0.0,3,41,Urban,HR Executive,103927,0 +511,Female,45,Bachelors,11,7,91,20,82,3.0,2,97,Urban,Manager,144534,0 +512,Male,40,PhD,3,79,80,57,67,0.0,4,42,Semi-Urban,Data Analyst,131676,1 +513,Female,58,High School,18,75,20,62,30,9.0,5,31,Urban,Manager,140497,0 +514,Female,53,Masters,7,66,2,24,41,8.0,3,76,Rural,ML Engineer,68053,0 +515,Male,25,High School,3,12,2,28,77,7.0,2,53,Rural,Manager,83606,0 +516,Male,41,Bachelors,16,26,78,31,41,2.0,5,98,Semi-Urban,Manager,124907,0 +517,Male,30,High School,17,54,47,73,31,4.0,3,73,Urban,Data Analyst,49133,1 +518,Female,40,Bachelors,2,67,2,87,23,9.0,6,38,Semi-Urban,HR Executive,95094,0 +519,Other,45,Bachelors,3,46,8,87,59,1.0,3,86,Rural,ML Engineer,122681,0 +520,Male,53,Bachelors,0,2,58,5,48,9.0,7,82,Semi-Urban,HR Executive,59336,0 +521,Male,34,Bachelors,12,88,86,28,58,6.0,2,63,Urban,ML Engineer,60312,1 +522,Male,50,Masters,18,62,32,54,16,3.0,2,32,Rural,HR Executive,45576,0 +523,Other,26,Masters,13,65,1,97,97,9.0,2,54,Semi-Urban,Manager,37355,0 +524,Female,32,Diploma,4,79,45,92,92,6.0,1,85,Semi-Urban,ML Engineer,74142,1 +525,Female,40,Bachelors,1,52,33,83,39,0.0,1,1,Rural,Manager,92745,0 +526,Male,33,Bachelors,1,71,42,24,80,0.0,0,49,Urban,Software Engineer,104446,0 +527,Male,55,Bachelors,0,60,80,33,57,4.0,0,9,Urban,ML Engineer,42218,0 +528,Male,48,Masters,2,30,14,0,15,3.0,5,37,Rural,Manager,47069,0 +529,Male,24,Masters,3,8,2,72,71,5.0,0,7,Urban,ML Engineer,48125,0 +530,Female,45,Masters,2,42,56,33,6,5.0,1,59,Urban,Manager,65316,0 +531,Female,31,Bachelors,15,42,45,87,54,9.0,4,61,Rural,Manager,147187,0 +532,Other,47,Bachelors,3,43,78,67,30,7.0,5,50,Urban,HR Executive,117260,0 +533,Other,59,Masters,0,57,29,4,53,0.0,2,80,Urban,Manager,30636,0 +534,Male,25,Masters,1,84,52,21,31,2.0,7,28,Semi-Urban,Software Engineer,45819,0 +535,Female,37,Bachelors,14,17,84,8,27,8.0,1,18,Semi-Urban,HR Executive,56180,0 +536,Female,56,Bachelors,2,98,15,98,27,6.0,1,87,Urban,Manager,68973,1 +537,Female,55,Bachelors,18,66,50,43,1,8.0,4,94,Urban,Manager,144455,1 +538,Male,49,Bachelors,8,1,15,0,50,1.0,3,3,Urban,Data Analyst,62121,0 +539,Male,37,Diploma,18,38,41,51,98,2.0,3,95,Rural,Manager,138155,0 +540,Male,41,Bachelors,1,58,7,2,51,5.0,4,40,Urban,ML Engineer,38940,0 +541,Other,23,Bachelors,18,38,97,55,1,9.0,0,19,Urban,HR Executive,84814,0 +542,Female,24,Masters,0,71,89,40,53,8.0,4,54,Rural,ML Engineer,51084,1 +543,Male,39,Bachelors,12,21,13,57,80,6.0,1,26,Urban,Software Engineer,56827,0 +544,Female,57,Bachelors,13,16,86,47,6,9.0,4,62,Urban,Manager,35267,0 +545,Female,33,Bachelors,10,49,72,16,23,4.0,4,2,Rural,Software Engineer,148167,0 +546,Male,23,High School,10,27,53,70,79,6.0,3,36,Urban,ML Engineer,138025,0 +547,Male,27,High School,17,89,33,55,8,9.0,7,94,Urban,HR Executive,54488,1 +548,Female,39,High School,0,26,60,94,37,9.0,5,62,Semi-Urban,Data Analyst,124743,1 +549,Male,57,Masters,8,1,36,4,21,0.0,1,62,Urban,HR Executive,39152,0 +550,Female,35,Masters,11,79,85,64,26,3.0,4,56,Urban,HR Executive,119289,1 +551,Male,52,Bachelors,10,31,42,33,18,2.0,2,69,Urban,Manager,72224,0 +552,Female,39,Masters,9,10,58,50,93,7.0,1,29,Urban,ML Engineer,109805,0 +553,Male,51,Diploma,12,33,50,71,43,8.0,6,47,Semi-Urban,ML Engineer,28491,0 +554,Male,35,Bachelors,19,8,94,13,21,1.0,5,5,Urban,HR Executive,86468,0 +555,Female,37,High School,11,23,90,35,49,1.0,5,17,Urban,HR Executive,133654,0 +556,Male,37,Bachelors,10,7,57,64,45,2.0,5,78,Urban,Software Engineer,59533,0 +557,Male,42,Diploma,15,46,74,33,17,9.0,5,49,Semi-Urban,Manager,95507,0 +558,Male,52,Bachelors,18,18,50,36,23,3.0,3,82,Semi-Urban,Manager,89833,0 +559,Female,55,Masters,13,56,94,67,58,4.0,0,33,Urban,ML Engineer,146123,1 +560,Female,51,Bachelors,15,54,58,29,6,1.0,5,47,Urban,HR Executive,41349,0 +561,Female,39,PhD,3,97,86,65,26,2.0,5,91,Urban,Data Analyst,70966,1 +562,Male,52,Bachelors,14,17,61,39,18,0.0,7,4,Rural,Manager,80607,0 +563,Male,40,Bachelors,0,29,61,38,77,1.0,4,70,Rural,ML Engineer,123118,0 +564,Male,29,Bachelors,1,72,7,89,32,6.0,4,68,Semi-Urban,Software Engineer,77995,1 +565,Male,24,Masters,4,96,75,9,65,4.0,4,75,Rural,ML Engineer,38085,1 +566,Male,29,Bachelors,17,99,36,69,67,6.0,7,94,Urban,HR Executive,81967,1 +567,Male,30,Masters,11,65,47,70,26,3.0,0,46,Rural,HR Executive,70705,0 +568,Male,51,Bachelors,0,27,20,28,5,3.0,0,19,Urban,ML Engineer,88747,0 +569,Female,56,Bachelors,10,86,85,46,97,8.0,0,37,Urban,HR Executive,70284,1 +570,Male,53,Bachelors,5,90,4,49,63,5.0,4,23,Urban,Manager,117544,0 +571,Male,43,Diploma,17,54,92,59,23,7.0,1,39,Urban,HR Executive,106130,1 +572,Female,33,Diploma,15,82,73,15,84,3.0,5,3,Rural,Software Engineer,28307,0 +573,Male,52,Bachelors,18,59,90,7,98,6.0,4,16,Rural,Manager,103894,0 +574,Female,45,Bachelors,13,83,76,10,55,3.0,3,69,Urban,Manager,73309,0 +575,Female,44,Diploma,4,23,93,93,31,3.0,5,15,Semi-Urban,Software Engineer,132777,0 +576,Female,56,Bachelors,1,8,39,47,21,8.0,7,64,Semi-Urban,Software Engineer,45194,0 +577,Male,46,Masters,1,16,15,69,80,3.0,7,15,Urban,Software Engineer,51267,0 +578,Female,47,Diploma,7,2,66,6,21,7.0,6,36,Urban,Software Engineer,137395,0 +579,Male,56,High School,10,83,13,93,88,3.0,4,59,Rural,HR Executive,54030,1 +580,Male,52,Bachelors,0,19,34,49,49,7.0,4,70,Rural,HR Executive,101674,0 +581,Male,47,Masters,8,64,92,14,88,4.0,2,71,Urban,ML Engineer,74629,1 +582,Other,34,Bachelors,16,53,93,52,48,9.0,6,12,Urban,Data Analyst,50487,0 +583,Male,35,Bachelors,2,9,1,67,28,8.0,5,43,Semi-Urban,Data Analyst,37488,0 +584,Male,58,Bachelors,1,42,0,6,21,4.0,4,72,Urban,Manager,56680,0 +585,Female,54,Diploma,15,84,37,52,60,0.0,7,68,Rural,Software Engineer,92964,1 +586,Male,47,Diploma,15,33,61,50,9,1.0,5,97,Semi-Urban,Data Analyst,117186,1 +587,Male,45,Bachelors,12,58,67,33,63,1.0,1,2,Urban,Manager,97239,0 +588,Male,50,Bachelors,12,54,98,23,70,2.0,5,37,Rural,Data Analyst,95877,0 +589,Male,53,Masters,14,69,78,20,80,1.0,1,34,Semi-Urban,Data Analyst,104155,0 +590,Male,28,High School,18,86,50,9,49,1.0,4,36,Urban,Data Analyst,92473,0 +591,Male,25,Diploma,11,76,64,82,79,9.0,6,81,Semi-Urban,Manager,62615,1 +592,Female,34,Bachelors,18,4,4,82,41,7.0,3,84,Urban,Manager,64153,0 +593,Male,53,PhD,2,57,90,20,52,0.0,3,53,Semi-Urban,HR Executive,137901,0 +594,Male,41,Masters,19,10,11,36,7,3.0,2,64,Urban,Software Engineer,97423,0 +595,Female,53,Bachelors,5,81,95,1,18,3.0,4,29,Rural,Manager,41404,0 +596,Male,49,High School,2,53,80,29,40,1.0,4,49,Rural,HR Executive,74429,0 +597,Female,29,Diploma,5,43,48,98,87,9.0,2,64,Rural,ML Engineer,141220,1 +598,Male,47,Masters,5,80,29,23,37,2.0,5,33,Urban,Manager,147508,0 +599,Male,50,High School,9,95,46,41,74,9.0,2,81,Urban,Data Analyst,80750,1 +600,Male,29,Bachelors,14,89,59,88,25,5.0,1,8,Rural,Software Engineer,78825,1 +601,Male,52,Masters,3,73,35,45,23,0.0,6,19,Urban,Software Engineer,67360,0 +602,Male,43,Diploma,9,95,94,54,82,4.0,6,59,Urban,ML Engineer,20674,1 +603,Male,30,Diploma,14,13,96,3,92,0.0,3,31,Urban,Data Analyst,82530,0 +604,Male,43,High School,10,51,15,51,43,8.0,2,13,Semi-Urban,Manager,77049,0 +605,Male,48,PhD,4,81,69,50,32,7.0,4,71,Urban,Manager,76296,1 +606,Male,49,Bachelors,8,10,66,63,0,4.0,6,95,Urban,Software Engineer,92166,0 +607,Male,46,High School,8,87,11,82,41,4.0,7,13,Urban,ML Engineer,37755,0 +608,Male,53,Bachelors,0,61,89,69,5,7.0,1,43,Semi-Urban,HR Executive,44569,1 +609,Male,39,Bachelors,13,96,98,26,67,0.0,4,79,Semi-Urban,Manager,60338,1 +610,Female,43,Diploma,1,15,99,34,82,6.0,6,91,Rural,HR Executive,112114,0 +611,Male,24,Bachelors,5,99,35,20,36,0.0,4,49,Rural,Data Analyst,134067,0 +612,Female,51,Masters,7,35,41,0,76,2.0,7,27,Rural,HR Executive,91500,0 +613,Female,48,Bachelors,11,55,49,26,78,7.0,5,6,Urban,Software Engineer,118499,0 +614,Male,30,Diploma,5,51,85,18,58,9.0,6,47,Rural,ML Engineer,86728,0 +615,Female,28,Diploma,9,14,58,79,70,0.0,0,28,Semi-Urban,HR Executive,128224,0 +616,Female,52,Masters,13,5,97,62,0,5.0,6,98,Rural,Manager,65372,1 +617,Male,54,Bachelors,3,99,71,30,17,8.0,5,58,Semi-Urban,HR Executive,47488,1 +618,Male,38,Diploma,6,20,69,79,63,4.0,7,53,Urban,Manager,95368,0 +619,Female,53,Bachelors,1,63,92,84,80,3.0,2,40,Urban,HR Executive,75621,1 +620,Female,38,Masters,5,79,38,35,91,5.0,5,60,Semi-Urban,HR Executive,66688,0 +621,Male,50,Masters,8,25,28,23,62,5.0,7,81,Semi-Urban,ML Engineer,135852,0 +622,Male,23,High School,0,91,1,28,52,1.0,3,69,Rural,Manager,138719,0 +623,Male,42,Diploma,19,50,77,21,97,5.0,2,68,Urban,Data Analyst,92517,0 +624,Male,36,Bachelors,17,89,3,20,46,5.0,3,30,Rural,HR Executive,95391,0 +625,Female,29,Bachelors,18,9,99,7,54,1.0,5,85,Rural,Data Analyst,123310,0 +626,Male,53,Bachelors,3,91,7,18,80,5.0,2,42,Semi-Urban,Data Analyst,82909,0 +627,Male,36,Bachelors,15,32,85,85,73,8.0,6,24,Semi-Urban,Manager,120439,0 +628,Female,48,Diploma,16,57,53,84,33,8.0,2,35,Urban,Software Engineer,43306,0 +629,Male,59,Diploma,11,48,1,43,57,8.0,1,58,Urban,Data Analyst,44023,0 +630,Male,39,High School,9,24,14,40,25,9.0,6,14,Semi-Urban,HR Executive,141970,0 +631,Female,56,Bachelors,2,74,35,44,15,2.0,2,39,Urban,ML Engineer,31608,0 +632,Female,57,Bachelors,18,99,95,24,95,9.0,1,56,Urban,ML Engineer,87830,1 +633,Male,53,Masters,2,94,12,74,96,1.0,4,47,Urban,Data Analyst,77968,0 +634,Male,35,High School,11,86,73,32,46,9.0,1,81,Semi-Urban,Data Analyst,116714,1 +635,Male,45,Bachelors,11,57,64,66,93,9.0,1,19,Rural,ML Engineer,145937,0 +636,Male,51,Bachelors,6,60,19,31,1,1.0,4,27,Semi-Urban,Software Engineer,114044,0 +637,Male,36,Masters,7,27,51,65,98,5.0,0,47,Urban,Software Engineer,113106,0 +638,Male,29,Bachelors,15,61,67,79,58,3.0,1,65,Urban,Data Analyst,86022,1 +639,Male,26,High School,13,33,38,61,67,2.0,5,1,Urban,HR Executive,68362,0 +640,Male,50,High School,19,36,62,29,24,8.0,4,62,Rural,Manager,98237,0 +641,Male,33,Diploma,3,64,48,72,91,9.0,7,91,Semi-Urban,ML Engineer,79709,1 +642,Male,21,High School,9,89,32,20,12,0.0,3,77,Urban,ML Engineer,99721,0 +643,Male,33,High School,19,77,33,35,21,4.0,7,2,Urban,Manager,118934,0 +644,Male,55,Masters,5,29,83,59,30,5.0,1,98,Rural,HR Executive,133106,1 +645,Male,53,Diploma,17,85,15,97,67,8.0,6,73,Semi-Urban,Manager,48664,1 +646,Female,51,High School,3,52,27,80,71,1.0,5,66,Semi-Urban,Software Engineer,35283,0 +647,Male,38,Diploma,17,98,33,46,11,0.0,0,32,Urban,Manager,38054,0 +648,Female,35,PhD,4,17,24,69,64,5.0,5,75,Semi-Urban,Software Engineer,105017,0 +649,Female,58,Masters,16,40,85,42,92,8.0,0,58,Rural,Manager,56355,0 +650,Male,35,Masters,13,29,20,45,3,0.0,4,41,Rural,Software Engineer,71740,0 +651,Male,28,Masters,7,42,19,61,25,4.0,5,94,Urban,Data Analyst,123205,0 +652,Male,51,Bachelors,10,51,19,12,35,6.0,2,25,Semi-Urban,Software Engineer,68644,0 +653,Male,34,Bachelors,17,64,78,99,83,1.0,1,21,Urban,Data Analyst,89071,1 +654,Female,41,Masters,9,27,23,11,98,8.0,7,25,Rural,HR Executive,75609,0 +655,Male,27,Bachelors,10,89,26,17,40,9.0,4,32,Urban,Manager,31466,0 +656,Male,56,Diploma,11,56,60,0,61,9.0,5,59,Urban,Data Analyst,97525,0 +657,Male,59,Masters,2,56,22,57,26,7.0,1,83,Semi-Urban,Data Analyst,22877,0 +658,Male,46,High School,11,22,30,19,76,9.0,6,64,Urban,HR Executive,77842,0 +659,Female,56,Masters,14,3,87,78,63,7.0,5,77,Semi-Urban,Data Analyst,54932,1 +660,Male,35,Diploma,12,62,49,83,8,0.0,0,55,Rural,ML Engineer,81781,1 +661,Male,56,Diploma,6,61,8,74,85,2.0,4,92,Urban,Software Engineer,52546,1 +662,Other,46,High School,13,75,27,69,90,1.0,1,19,Semi-Urban,Software Engineer,30732,0 +663,Female,53,Diploma,8,71,62,15,62,3.0,7,31,Urban,Data Analyst,66765,0 +664,Male,52,Masters,4,67,93,90,94,1.0,0,18,Urban,Data Analyst,128528,1 +665,Male,36,Masters,13,83,16,95,44,2.0,7,36,Urban,HR Executive,28099,0 +666,Male,21,Diploma,8,22,55,39,14,7.0,1,85,Rural,Software Engineer,42606,0 +667,Male,21,High School,6,81,89,78,87,4.0,5,69,Rural,ML Engineer,46277,1 +668,Male,41,Diploma,11,84,53,10,41,8.0,6,24,Semi-Urban,ML Engineer,147028,0 +669,Male,35,Masters,16,16,68,40,35,0.0,6,33,Rural,HR Executive,46109,0 +670,Male,48,Bachelors,18,93,54,32,88,8.0,3,61,Urban,HR Executive,118856,1 +671,Male,55,Bachelors,6,60,7,23,51,2.0,4,82,Urban,HR Executive,40039,0 +672,Female,26,Bachelors,5,16,64,60,79,1.0,2,59,Urban,Manager,100847,0 +673,Male,27,Bachelors,17,18,29,7,69,0.0,7,95,Semi-Urban,Software Engineer,149767,0 +674,Male,48,Bachelors,5,7,91,26,18,2.0,4,86,Semi-Urban,HR Executive,68485,0 +675,Male,38,Bachelors,11,98,91,42,8,7.0,3,41,Rural,Manager,59668,1 +676,Other,57,Masters,3,84,81,33,25,6.0,1,85,Semi-Urban,Software Engineer,88351,1 +677,Male,57,Bachelors,0,11,16,43,1,6.0,3,11,Urban,Data Analyst,117636,0 +678,Male,51,PhD,5,26,82,89,31,1.0,2,58,Rural,Manager,77435,1 +679,Other,27,Bachelors,13,79,10,39,37,7.0,7,50,Urban,HR Executive,113171,0 +680,Female,58,PhD,15,64,53,88,63,2.0,6,6,Rural,ML Engineer,127967,0 +681,Female,48,Bachelors,4,63,97,86,35,3.0,4,51,Urban,ML Engineer,62973,1 +682,Male,58,Bachelors,11,19,8,88,85,6.0,2,29,Urban,Software Engineer,98525,0 +683,Male,33,Masters,12,69,67,75,63,5.0,0,61,Semi-Urban,HR Executive,83802,1 +684,Female,32,Bachelors,10,91,90,78,44,9.0,2,43,Urban,Software Engineer,73311,1 +685,Female,46,Masters,9,1,71,31,20,4.0,5,44,Urban,Data Analyst,25536,0 +686,Male,35,Bachelors,0,26,90,10,26,5.0,4,37,Urban,Manager,87463,0 +687,Male,39,High School,16,51,14,36,12,4.0,3,89,Rural,Software Engineer,71297,0 +688,Male,54,High School,7,40,87,71,33,3.0,4,16,Urban,Manager,110018,0 +689,Female,51,PhD,2,12,75,78,57,8.0,1,94,Urban,Manager,32947,1 +690,Male,37,Bachelors,18,37,93,75,89,6.0,5,5,Urban,Manager,106075,0 +691,Male,55,Masters,15,73,60,64,88,7.0,5,48,Rural,Data Analyst,89397,1 +692,Male,37,Diploma,17,94,67,70,9,3.0,6,40,Rural,ML Engineer,28486,1 +693,Male,53,Bachelors,1,18,2,23,71,9.0,0,92,Urban,ML Engineer,36287,0 +694,Male,54,Diploma,0,40,49,80,71,3.0,5,33,Rural,ML Engineer,116679,0 +695,Male,38,Diploma,15,31,28,14,15,0.0,5,89,Urban,Data Analyst,64414,0 +696,Female,54,Diploma,17,95,31,75,60,9.0,7,9,Rural,ML Engineer,27365,0 +697,Male,54,Masters,11,72,21,83,77,9.0,7,76,Rural,ML Engineer,111683,1 +698,Male,45,Masters,2,6,53,99,38,4.0,0,16,Semi-Urban,HR Executive,64598,0 +699,Male,26,Bachelors,5,22,20,15,34,4.0,1,49,Urban,ML Engineer,149443,0 +700,Male,24,Bachelors,1,33,63,24,20,7.0,6,19,Urban,Data Analyst,86591,0 +701,Male,58,Masters,17,60,62,48,43,8.0,5,1,Urban,ML Engineer,103141,0 +702,Male,42,High School,4,45,10,5,58,3.0,2,19,Urban,ML Engineer,69799,0 +703,Male,40,High School,3,65,15,24,59,0.0,4,63,Urban,Data Analyst,79474,0 +704,Male,45,Bachelors,18,70,58,5,1,4.0,5,84,Rural,HR Executive,46120,0 +705,Male,30,Bachelors,14,15,85,43,63,6.0,0,23,Urban,HR Executive,76068,0 +706,Other,37,Bachelors,6,31,75,8,69,5.0,1,7,Rural,HR Executive,55374,0 +707,Male,36,High School,17,98,55,62,46,1.0,6,24,Urban,Manager,29068,1 +708,Female,55,Bachelors,13,32,1,96,90,5.0,0,36,Semi-Urban,Data Analyst,77667,0 +709,Male,21,Masters,19,61,81,21,72,9.0,4,74,Urban,Data Analyst,33345,1 +710,Female,40,Diploma,12,28,3,10,99,7.0,4,97,Urban,ML Engineer,55356,0 +711,Female,49,Bachelors,10,44,8,88,69,2.0,6,0,Semi-Urban,Data Analyst,64372,0 +712,Male,35,Masters,5,24,30,80,24,5.0,3,63,Urban,HR Executive,134497,0 +713,Male,38,Bachelors,17,5,68,99,63,5.0,5,98,Semi-Urban,HR Executive,90433,1 +714,Male,48,Bachelors,5,82,92,43,99,0.0,2,38,Urban,ML Engineer,85015,1 +715,Male,36,Bachelors,9,16,42,95,20,2.0,7,67,Urban,Manager,67115,0 +716,Female,36,High School,8,61,14,61,92,9.0,7,63,Semi-Urban,Software Engineer,55195,0 +717,Female,31,High School,16,49,3,60,44,7.0,2,77,Urban,HR Executive,135289,0 +718,Other,35,Bachelors,18,10,99,92,30,0.0,2,49,Rural,Software Engineer,140102,1 +719,Male,41,Masters,9,25,92,17,85,1.0,6,61,Urban,ML Engineer,55907,0 +720,Female,51,Masters,2,53,50,40,12,1.0,6,34,Semi-Urban,Manager,47439,0 +721,Female,57,Bachelors,17,40,99,59,27,1.0,7,12,Semi-Urban,Software Engineer,119105,0 +722,Male,52,High School,15,78,36,28,66,8.0,4,34,Urban,HR Executive,57949,0 +723,Male,34,Bachelors,9,91,51,32,40,5.0,0,5,Semi-Urban,Manager,114855,0 +724,Female,58,Bachelors,11,6,29,14,39,3.0,1,82,Urban,ML Engineer,112574,0 +725,Male,39,Diploma,17,69,33,91,76,7.0,4,27,Urban,Software Engineer,121317,0 +726,Female,43,Diploma,18,35,81,29,33,2.0,5,6,Rural,Manager,110446,0 +727,Male,57,Bachelors,5,36,13,69,50,5.0,1,74,Urban,ML Engineer,123258,0 +728,Female,34,PhD,4,67,40,61,67,4.0,7,89,Urban,Software Engineer,60653,1 +729,Male,26,Diploma,13,3,6,61,74,8.0,1,51,Urban,HR Executive,87147,0 +730,Male,32,PhD,10,98,43,2,15,3.0,5,12,Urban,Software Engineer,63682,0 +731,Male,52,Diploma,6,17,96,57,88,9.0,2,34,Urban,ML Engineer,146230,0 +732,Female,26,High School,7,6,20,34,54,1.0,0,67,Semi-Urban,Manager,102541,0 +733,Female,59,Masters,19,20,21,54,67,4.0,7,53,Urban,HR Executive,113084,0 +734,Male,27,Masters,8,8,68,9,40,1.0,7,77,Urban,Data Analyst,132322,0 +735,Male,40,Masters,7,4,12,77,93,5.0,2,47,Semi-Urban,Data Analyst,135591,0 +736,Female,37,PhD,3,47,93,32,15,3.0,0,20,Urban,ML Engineer,132397,0 +737,Male,53,Bachelors,18,84,29,45,20,5.0,3,99,Urban,Manager,124914,1 +738,Female,54,Diploma,4,82,39,88,65,4.0,5,79,Urban,Data Analyst,46972,1 +739,Male,33,Bachelors,11,78,21,78,0,0.0,5,17,Urban,Manager,94994,0 +740,Male,57,PhD,14,38,14,35,6,3.0,5,73,Urban,Manager,138204,0 +741,Male,57,Masters,16,74,2,62,45,9.0,7,69,Semi-Urban,Software Engineer,36144,0 +742,Male,23,Diploma,9,14,15,49,12,0.0,2,6,Urban,Manager,50658,0 +743,Female,24,Diploma,11,53,86,16,81,5.0,5,77,Urban,Data Analyst,51659,0 +744,Male,33,Bachelors,18,53,32,52,4,1.0,5,73,Urban,Data Analyst,141884,0 +745,Male,30,Bachelors,10,80,54,66,40,8.0,1,93,Urban,HR Executive,124846,1 +746,Female,41,Masters,15,73,6,81,85,6.0,3,89,Rural,HR Executive,23935,1 +747,Male,35,Bachelors,12,31,15,40,14,3.0,5,58,Urban,Data Analyst,45920,0 +748,Male,39,Bachelors,7,49,95,67,5,8.0,0,29,Urban,Data Analyst,36060,1 +749,Female,42,Bachelors,10,61,78,47,53,7.0,0,61,Semi-Urban,ML Engineer,114633,1 +750,Female,28,Bachelors,5,93,65,78,50,3.0,4,83,Urban,Software Engineer,28936,1 +751,Male,23,Bachelors,12,96,56,47,32,4.0,6,92,Urban,ML Engineer,99613,1 +752,Female,38,Bachelors,4,5,98,44,17,5.0,1,69,Semi-Urban,ML Engineer,92466,0 +753,Female,22,Masters,18,88,86,83,16,7.0,5,98,Urban,Data Analyst,51345,1 +754,Male,53,Diploma,0,70,63,19,76,2.0,2,41,Rural,Manager,96478,0 +755,Male,59,Bachelors,10,19,6,22,39,1.0,0,67,Urban,HR Executive,62311,0 +756,Female,21,Diploma,10,31,99,54,38,4.0,2,91,Urban,Manager,37829,1 +757,Female,21,High School,5,22,74,24,89,8.0,7,94,Urban,Software Engineer,50397,0 +758,Male,37,Masters,1,85,75,85,50,4.0,4,38,Semi-Urban,ML Engineer,109449,1 +759,Female,33,Masters,0,89,97,59,48,4.0,1,86,Semi-Urban,Software Engineer,86314,1 +760,Female,53,Bachelors,9,78,69,36,5,9.0,4,1,Urban,Manager,27746,0 +761,Male,47,Bachelors,19,56,70,80,9,0.0,6,81,Semi-Urban,Manager,100050,1 +762,Male,51,Masters,11,62,28,59,27,4.0,4,74,Urban,HR Executive,92641,0 +763,Male,52,Bachelors,10,34,71,98,71,3.0,1,49,Urban,Software Engineer,22455,1 +764,Female,26,Diploma,4,56,8,70,89,5.0,7,68,Semi-Urban,Data Analyst,65733,0 +765,Male,23,Bachelors,16,95,48,37,67,9.0,7,20,Rural,Software Engineer,64212,0 +766,Male,49,Bachelors,4,71,28,70,32,3.0,1,60,Rural,Software Engineer,30533,0 +767,Female,31,Masters,15,45,61,19,46,8.0,3,48,Semi-Urban,ML Engineer,102535,0 +768,Female,46,Bachelors,18,49,97,11,38,4.0,4,98,Urban,Manager,45128,1 +769,Male,56,Diploma,7,9,78,73,40,6.0,4,20,Rural,Data Analyst,34853,0 +770,Female,27,PhD,17,18,71,2,14,5.0,3,40,Semi-Urban,Software Engineer,96794,0 +771,Male,54,Masters,11,41,72,9,85,7.0,3,86,Urban,HR Executive,133993,0 +772,Female,27,Bachelors,12,88,95,42,80,3.0,4,56,Urban,Data Analyst,143468,1 +773,Male,22,High School,3,55,43,70,13,0.0,3,35,Urban,HR Executive,62914,0 +774,Male,55,Bachelors,10,17,88,8,36,0.0,4,73,Urban,HR Executive,123660,0 +775,Female,37,Bachelors,3,48,83,11,92,6.0,1,76,Rural,ML Engineer,56219,0 +776,Male,56,Diploma,7,64,22,61,66,4.0,0,95,Urban,Manager,63765,1 +777,Male,47,Diploma,18,58,24,48,1,6.0,7,4,Urban,HR Executive,83793,0 +778,Female,46,Bachelors,19,86,95,73,71,1.0,6,99,Semi-Urban,Manager,58071,1 +779,Female,26,PhD,0,21,63,77,62,0.0,4,64,Urban,HR Executive,130740,0 +780,Female,28,Bachelors,2,31,29,11,55,7.0,2,65,Urban,ML Engineer,136655,0 +781,Female,36,Bachelors,14,50,58,14,23,1.0,7,42,Rural,HR Executive,49391,0 +782,Male,27,Diploma,13,99,50,59,28,8.0,7,55,Urban,HR Executive,62036,1 +783,Male,28,High School,10,56,11,66,73,6.0,1,52,Semi-Urban,Manager,128705,0 +784,Male,21,Masters,7,21,80,46,59,1.0,0,42,Urban,HR Executive,136548,0 +785,Male,37,Masters,5,85,92,52,96,3.0,3,52,Rural,Software Engineer,103855,1 +786,Female,48,PhD,15,13,55,88,31,4.0,2,99,Urban,Manager,46650,1 +787,Male,30,Diploma,3,59,24,30,58,8.0,5,16,Urban,Data Analyst,121477,0 +788,Male,42,Bachelors,12,79,41,55,39,4.0,4,48,Urban,HR Executive,89659,0 +789,Male,52,Bachelors,10,59,60,24,97,4.0,3,71,Urban,HR Executive,107969,0 +790,Female,48,Masters,18,79,37,74,30,9.0,7,52,Urban,Data Analyst,131464,1 +791,Male,53,Bachelors,5,61,46,32,52,4.0,5,90,Urban,ML Engineer,144762,0 +792,Male,59,Bachelors,18,14,12,87,29,0.0,5,45,Semi-Urban,ML Engineer,25768,0 +793,Male,38,High School,3,82,63,70,45,9.0,0,30,Urban,Manager,139940,1 +794,Female,43,High School,19,74,3,16,42,8.0,2,72,Semi-Urban,Software Engineer,110528,0 +795,Male,49,Bachelors,3,96,89,64,41,7.0,3,22,Urban,Manager,50379,1 +796,Female,42,High School,12,64,31,51,28,9.0,3,22,Urban,Manager,96124,0 +797,Female,34,Bachelors,8,25,6,24,25,4.0,1,54,Rural,Data Analyst,86319,0 +798,Male,37,Masters,0,42,15,67,90,1.0,5,1,Rural,Software Engineer,53170,0 +799,Female,26,Masters,15,63,41,11,90,7.0,0,80,Rural,Data Analyst,105439,0 +800,Female,59,Bachelors,13,57,83,46,75,1.0,4,64,Urban,Manager,115780,1 +801,Female,34,Diploma,14,79,92,5,78,2.0,5,89,Urban,Software Engineer,118273,1 +802,Male,49,High School,8,40,32,92,20,8.0,7,92,Urban,ML Engineer,109179,1 +803,Male,33,PhD,5,51,24,98,67,1.0,1,87,Semi-Urban,Data Analyst,45927,1 +804,Female,56,Bachelors,17,15,65,19,91,5.0,6,87,Urban,Data Analyst,29024,0 +805,Male,50,Bachelors,9,40,44,5,77,6.0,6,61,Rural,Software Engineer,84528,0 +806,Female,42,PhD,10,80,92,17,55,9.0,1,40,Semi-Urban,ML Engineer,103906,0 +807,Female,39,Bachelors,3,22,11,48,3,6.0,5,79,Semi-Urban,Software Engineer,95196,0 +808,Female,22,Masters,4,59,41,72,54,7.0,6,67,Rural,Software Engineer,86282,0 +809,Male,40,Bachelors,19,33,10,71,64,0.0,4,94,Semi-Urban,Manager,51396,0 +810,Male,43,Bachelors,0,65,76,99,22,6.0,3,76,Urban,HR Executive,83650,1 +811,Other,43,Bachelors,9,34,44,47,26,7.0,7,68,Urban,Data Analyst,51827,0 +812,Female,43,Diploma,13,2,26,65,70,3.0,5,97,Semi-Urban,Software Engineer,108849,0 +813,Male,40,Diploma,19,29,81,3,25,4.0,2,11,Urban,Manager,30458,0 +814,Female,48,Diploma,15,27,75,40,66,1.0,6,56,Rural,HR Executive,146371,0 +815,Female,53,High School,17,81,87,95,4,6.0,5,84,Urban,Manager,38999,1 +816,Male,48,Masters,19,13,88,94,98,4.0,5,57,Urban,HR Executive,46341,1 +817,Male,33,Bachelors,12,0,36,33,35,1.0,7,67,Semi-Urban,Data Analyst,55738,0 +818,Male,23,Bachelors,17,52,8,93,39,0.0,7,66,Urban,HR Executive,113558,0 +819,Male,46,High School,3,52,26,98,46,7.0,6,49,Semi-Urban,Data Analyst,101920,0 +820,Male,24,High School,9,59,87,13,57,0.0,6,60,Rural,Manager,29429,0 +821,Female,38,Bachelors,9,3,48,34,34,9.0,1,5,Rural,Data Analyst,31613,0 +822,Male,31,Bachelors,3,65,61,26,7,2.0,6,18,Urban,Software Engineer,61576,0 +823,Male,28,PhD,7,38,41,16,88,4.0,7,60,Urban,Data Analyst,149063,0 +824,Male,24,High School,7,82,80,98,28,6.0,0,22,Rural,ML Engineer,46400,1 +825,Male,59,High School,4,24,25,31,33,0.0,0,98,Urban,Data Analyst,68692,0 +826,Female,37,Bachelors,9,54,1,54,38,8.0,6,20,Urban,HR Executive,92395,0 +827,Male,34,Bachelors,1,22,5,40,64,4.0,2,38,Rural,ML Engineer,41100,0 +828,Male,41,Masters,17,69,20,75,68,4.0,1,91,Urban,Data Analyst,86697,1 +829,Female,28,Masters,8,60,87,11,27,4.0,3,88,Rural,Software Engineer,34775,1 +830,Male,25,Masters,2,37,52,66,40,3.0,0,32,Urban,Manager,37408,0 +831,Male,52,Bachelors,1,12,53,18,29,8.0,2,27,Rural,Data Analyst,77825,0 +832,Male,37,High School,11,29,37,23,35,7.0,1,74,Urban,Manager,108719,0 +833,Male,28,High School,18,96,97,5,13,2.0,4,24,Urban,Software Engineer,122157,0 +834,Male,58,Bachelors,14,59,24,74,65,3.0,7,81,Urban,Data Analyst,34718,1 +835,Male,55,PhD,15,18,35,20,0,2.0,7,12,Urban,Manager,71578,0 +836,Male,23,Bachelors,10,3,24,91,47,4.0,5,75,Urban,Data Analyst,82492,0 +837,Female,40,Diploma,1,38,98,87,33,1.0,6,91,Rural,Software Engineer,90323,1 +838,Male,35,Bachelors,16,10,28,45,9,3.0,2,80,Rural,Data Analyst,59616,0 +839,Male,49,Diploma,2,83,80,20,62,7.0,3,15,Rural,Manager,38280,0 +840,Female,54,Bachelors,15,75,24,40,80,0.0,5,55,Semi-Urban,ML Engineer,48467,0 +841,Male,50,Masters,9,58,58,6,96,0.0,1,83,Semi-Urban,Manager,124774,0 +842,Female,36,PhD,14,45,84,56,41,5.0,1,60,Urban,Data Analyst,149792,1 +843,Male,37,Masters,18,25,65,25,16,4.0,1,93,Rural,HR Executive,81630,0 +844,Other,38,High School,12,59,27,39,82,6.0,6,1,Rural,Data Analyst,137629,0 +845,Male,46,Bachelors,0,53,55,63,26,0.0,2,56,Urban,ML Engineer,60355,0 +846,Male,24,Masters,4,47,55,18,24,4.0,2,40,Semi-Urban,HR Executive,58808,0 +847,Male,33,High School,3,65,91,85,70,1.0,2,45,Urban,Software Engineer,49233,1 +848,Other,31,Bachelors,15,2,49,1,0,3.0,6,34,Rural,Software Engineer,85075,0 +849,Male,44,Bachelors,11,11,52,93,64,1.0,6,36,Semi-Urban,Manager,26057,0 +850,Male,42,High School,6,65,62,52,88,9.0,0,98,Semi-Urban,Data Analyst,136495,1 +851,Male,46,High School,18,9,87,23,58,3.0,2,44,Rural,Data Analyst,78581,0 +852,Female,39,Masters,1,26,58,63,22,3.0,3,92,Urban,Manager,104058,0 +853,Male,50,Bachelors,13,88,80,36,40,4.0,4,56,Urban,Manager,138973,1 +854,Female,41,Diploma,6,18,91,40,92,6.0,0,33,Urban,Software Engineer,38839,0 +855,Male,52,Bachelors,2,87,98,72,2,9.0,0,62,Urban,Data Analyst,28625,1 +856,Male,55,Diploma,4,27,49,59,2,6.0,4,31,Semi-Urban,ML Engineer,46335,0 +857,Male,51,Diploma,16,44,24,70,9,2.0,5,59,Urban,ML Engineer,122241,0 +858,Male,57,Masters,8,83,53,43,73,6.0,5,42,Urban,Manager,117683,0 +859,Male,54,Bachelors,5,47,75,67,31,5.0,5,75,Rural,Data Analyst,49530,1 +860,Male,38,Bachelors,1,87,17,76,69,4.0,5,1,Rural,HR Executive,114376,0 +861,Female,30,Masters,12,73,46,82,92,5.0,1,93,Urban,Software Engineer,62850,1 +862,Male,54,High School,2,40,24,30,13,4.0,4,28,Semi-Urban,HR Executive,59117,0 +863,Male,38,High School,14,58,42,89,2,2.0,1,70,Urban,Data Analyst,21362,1 +864,Male,58,High School,14,64,28,79,73,1.0,4,36,Rural,Data Analyst,49296,0 +865,Male,41,Bachelors,1,61,63,51,71,5.0,4,34,Semi-Urban,Software Engineer,34191,0 +866,Male,24,Bachelors,8,31,67,72,39,6.0,3,98,Urban,Data Analyst,134580,1 +867,Male,46,Masters,7,22,25,15,36,4.0,5,1,Urban,Software Engineer,37449,0 +868,Male,44,Diploma,3,43,47,66,22,8.0,6,52,Urban,HR Executive,99600,0 +869,Female,22,Bachelors,6,66,27,20,97,9.0,4,19,Semi-Urban,Manager,26304,0 +870,Female,57,Masters,4,72,43,12,66,1.0,2,47,Urban,Data Analyst,143279,0 +871,Male,41,Bachelors,19,92,38,2,40,5.0,4,52,Semi-Urban,HR Executive,146321,0 +872,Male,32,Masters,11,64,45,83,33,4.0,1,43,Semi-Urban,ML Engineer,100881,1 +873,Female,48,Bachelors,10,56,63,73,16,0.0,1,68,Rural,ML Engineer,37306,1 +874,Male,52,Bachelors,9,3,50,82,83,8.0,7,88,Rural,ML Engineer,81514,0 +875,Male,25,Bachelors,3,17,6,49,94,0.0,3,28,Urban,ML Engineer,33270,0 +876,Male,21,Bachelors,7,81,68,38,77,2.0,6,89,Rural,HR Executive,21397,1 +877,Female,42,Bachelors,1,78,88,28,82,0.0,4,0,Semi-Urban,ML Engineer,109462,0 +878,Female,56,Masters,10,5,34,39,35,7.0,7,41,Urban,Manager,32039,0 +879,Male,51,Masters,16,14,85,14,71,9.0,4,3,Urban,Data Analyst,95523,0 +880,Male,36,Diploma,5,18,18,57,17,9.0,4,64,Rural,Software Engineer,77301,0 +881,Male,26,Bachelors,15,68,75,95,6,7.0,4,42,Urban,Software Engineer,102784,1 +882,Female,58,Masters,17,87,50,32,20,5.0,6,49,Semi-Urban,Data Analyst,57585,0 +883,Male,42,Bachelors,12,10,58,75,21,4.0,3,24,Rural,Software Engineer,68182,0 +884,Male,59,High School,10,90,82,99,58,9.0,2,87,Rural,HR Executive,106166,1 +885,Female,36,PhD,3,56,10,34,95,6.0,6,40,Urban,HR Executive,101749,0 +886,Male,53,Masters,9,63,68,0,46,3.0,1,37,Rural,ML Engineer,92717,0 +887,Female,30,Bachelors,8,99,72,19,70,8.0,1,29,Semi-Urban,Manager,125810,0 +888,Male,30,Diploma,9,47,93,23,51,2.0,0,90,Urban,Data Analyst,104225,1 +889,Male,43,PhD,6,49,21,70,90,2.0,0,44,Urban,ML Engineer,35865,0 +890,Male,58,Bachelors,12,32,82,50,86,8.0,1,87,Semi-Urban,Data Analyst,109869,1 +891,Female,29,Masters,3,20,21,71,28,8.0,7,55,Semi-Urban,Manager,83365,0 +892,Female,22,Masters,12,97,25,83,24,6.0,5,60,Semi-Urban,Data Analyst,26362,1 +893,Female,27,Bachelors,17,47,39,21,5,4.0,0,11,Urban,ML Engineer,42561,0 +894,Male,22,Masters,18,10,81,81,24,1.0,0,74,Urban,Manager,93642,1 +895,Female,44,High School,10,25,68,25,23,9.0,4,56,Rural,ML Engineer,29185,0 +896,Male,31,Masters,2,99,19,41,48,0.0,4,1,Rural,Data Analyst,121364,0 +897,Male,33,High School,2,55,66,11,86,7.0,4,87,Rural,Software Engineer,72741,0 +898,Female,40,Bachelors,0,28,85,55,54,1.0,1,61,Rural,Software Engineer,48277,0 +899,Male,36,High School,7,19,61,4,22,3.0,1,29,Urban,Software Engineer,37000,0 +900,Male,31,Bachelors,19,87,47,13,34,8.0,7,24,Rural,Software Engineer,78736,0 +901,Male,28,Bachelors,11,36,49,26,18,6.0,7,16,Urban,Software Engineer,108749,0 +902,Male,25,Bachelors,11,69,38,33,94,3.0,3,53,Semi-Urban,Data Analyst,124324,0 +903,Male,40,Diploma,10,99,27,35,22,9.0,1,28,Rural,ML Engineer,96735,0 +904,Male,35,Bachelors,18,79,45,13,24,6.0,0,62,Semi-Urban,Data Analyst,67698,0 +905,Male,37,Diploma,2,79,95,16,86,8.0,1,66,Rural,HR Executive,32793,1 +906,Female,52,Bachelors,1,30,38,14,98,9.0,3,95,Semi-Urban,Manager,135889,0 +907,Female,33,Masters,6,45,49,62,61,0.0,7,94,Urban,Manager,53921,1 +908,Male,34,Bachelors,1,75,67,99,41,5.0,5,95,Urban,Data Analyst,22040,1 +909,Male,42,Bachelors,19,50,98,94,60,1.0,4,32,Rural,HR Executive,44222,1 +910,Male,29,Diploma,14,73,98,20,14,1.0,0,86,Semi-Urban,HR Executive,29147,1 +911,Male,48,Masters,1,34,16,66,17,1.0,2,74,Semi-Urban,Manager,43523,0 +912,Male,42,Bachelors,5,75,99,35,41,4.0,7,78,Urban,Data Analyst,122071,1 +913,Female,33,High School,18,37,55,40,87,6.0,1,21,Semi-Urban,HR Executive,109682,0 +914,Male,54,Masters,19,2,60,20,94,4.0,4,9,Urban,Manager,124849,0 +915,Male,38,PhD,16,11,90,40,20,9.0,4,68,Rural,ML Engineer,82990,0 +916,Male,46,Masters,7,27,15,8,69,6.0,2,72,Urban,ML Engineer,116107,0 +917,Male,24,Bachelors,12,20,67,54,19,2.0,7,50,Urban,HR Executive,62806,0 +918,Female,48,Bachelors,8,64,1,98,68,0.0,4,18,Rural,HR Executive,107493,0 +919,Female,31,Bachelors,15,16,12,69,67,4.0,4,61,Rural,Data Analyst,116854,0 +920,Male,37,High School,9,82,46,3,85,9.0,1,40,Urban,Data Analyst,82043,0 +921,Female,27,Bachelors,14,3,60,12,33,0.0,0,2,Semi-Urban,Software Engineer,142131,0 +922,Male,28,Masters,12,55,24,6,65,5.0,4,48,Urban,Data Analyst,42790,0 +923,Female,33,Diploma,7,93,94,68,13,7.0,4,58,Semi-Urban,Data Analyst,74484,1 +924,Female,38,Bachelors,1,39,93,85,41,2.0,2,90,Rural,ML Engineer,112192,1 +925,Male,55,Bachelors,0,75,98,44,60,9.0,3,87,Semi-Urban,ML Engineer,137792,1 +926,Male,44,Masters,19,95,51,72,2,7.0,5,91,Urban,Manager,74312,1 +927,Male,34,Bachelors,3,78,5,92,63,7.0,4,16,Semi-Urban,Data Analyst,93224,0 +928,Male,38,Bachelors,2,55,62,87,0,6.0,3,12,Urban,Manager,128510,0 +929,Female,24,Bachelors,7,49,47,80,36,9.0,0,65,Urban,Manager,81890,1 +930,Male,26,Bachelors,18,59,65,21,82,4.0,6,41,Urban,ML Engineer,108770,0 +931,Male,54,PhD,6,1,43,41,54,9.0,1,74,Urban,HR Executive,37784,0 +932,Female,45,Masters,19,40,84,79,51,1.0,2,83,Urban,Software Engineer,109491,1 +933,Other,53,Diploma,17,68,17,83,59,1.0,3,36,Rural,Manager,143736,0 +934,Male,21,Bachelors,3,61,6,38,26,3.0,4,48,Rural,Manager,140672,0 +935,Male,45,Bachelors,10,93,32,23,95,2.0,0,77,Urban,HR Executive,106390,0 +936,Male,37,Diploma,3,6,99,82,60,6.0,6,78,Semi-Urban,Data Analyst,115668,1 +937,Male,47,Bachelors,16,9,48,14,96,9.0,7,22,Semi-Urban,Data Analyst,63275,0 +938,Female,57,Bachelors,17,1,35,50,34,1.0,5,64,Urban,Manager,86767,0 +939,Male,58,Bachelors,15,43,41,76,5,6.0,0,63,Semi-Urban,HR Executive,64596,0 +940,Male,40,Diploma,15,59,22,2,53,1.0,1,49,Urban,ML Engineer,124164,0 +941,Male,54,Masters,15,74,86,51,98,0.0,3,13,Urban,Manager,118686,0 +942,Male,23,High School,16,40,89,44,85,7.0,6,50,Rural,Software Engineer,91061,0 +943,Female,30,Bachelors,14,22,19,18,89,7.0,3,32,Rural,ML Engineer,51975,0 +944,Female,54,Bachelors,8,48,90,43,10,2.0,1,14,Semi-Urban,HR Executive,24851,0 +945,Male,43,Bachelors,1,49,62,77,22,3.0,0,55,Semi-Urban,ML Engineer,47232,1 +946,Male,32,Bachelors,4,58,4,98,1,9.0,3,72,Rural,ML Engineer,28746,0 +947,Male,39,Bachelors,1,14,25,83,78,2.0,4,92,Urban,HR Executive,97424,0 +948,Female,52,Masters,14,50,87,50,86,4.0,7,33,Urban,ML Engineer,136364,0 +949,Female,51,Bachelors,18,80,7,76,31,5.0,1,79,Semi-Urban,Manager,123341,1 +950,Male,22,Bachelors,2,17,16,54,77,5.0,2,98,Urban,Software Engineer,46208,0 +951,Female,49,Bachelors,3,74,4,35,27,5.0,7,43,Semi-Urban,Data Analyst,136109,0 +952,Female,59,High School,9,38,80,44,52,6.0,6,37,Semi-Urban,Software Engineer,48508,0 +953,Male,41,Bachelors,13,74,61,74,28,5.0,5,66,Urban,HR Executive,146345,1 +954,Female,37,High School,7,46,16,74,18,2.0,3,31,Rural,ML Engineer,55014,0 +955,Male,55,Bachelors,6,37,38,80,24,0.0,7,26,Urban,ML Engineer,105953,0 +956,Male,22,Bachelors,10,31,61,11,33,3.0,1,67,Rural,Manager,97278,0 +957,Male,38,Bachelors,6,88,34,68,41,6.0,7,98,Urban,Manager,75009,1 +958,Male,27,Bachelors,5,71,14,25,61,0.0,4,9,Rural,Software Engineer,43897,0 +959,Male,48,PhD,3,93,24,73,64,0.0,2,64,Urban,ML Engineer,95138,1 +960,Female,25,High School,11,99,88,74,43,6.0,3,72,Urban,Data Analyst,121577,1 +961,Male,54,Masters,16,54,37,36,54,9.0,7,75,Urban,ML Engineer,71190,0 +962,Female,47,Masters,15,46,8,24,96,3.0,7,73,Urban,HR Executive,97209,0 +963,Male,39,Bachelors,19,77,38,5,65,1.0,3,24,Rural,HR Executive,71355,0 +964,Male,48,Masters,15,48,98,77,58,0.0,4,10,Urban,ML Engineer,34216,0 +965,Male,54,Diploma,11,98,44,22,18,6.0,0,24,Urban,Data Analyst,65818,0 +966,Male,25,Masters,0,89,31,3,26,1.0,6,19,Urban,Manager,116662,0 +967,Female,57,Bachelors,15,82,73,86,50,4.0,3,52,Semi-Urban,Software Engineer,80397,1 +968,Male,50,High School,6,66,67,41,66,8.0,4,0,Semi-Urban,Manager,38693,0 +969,Male,44,Bachelors,15,95,11,48,66,1.0,3,25,Urban,ML Engineer,54715,0 +970,Male,57,Bachelors,8,69,81,63,95,3.0,0,41,Rural,Software Engineer,26523,1 +971,Female,39,Bachelors,7,84,63,29,70,0.0,7,12,Semi-Urban,ML Engineer,59439,0 +972,Female,39,Masters,4,45,51,14,15,2.0,2,12,Semi-Urban,Data Analyst,60821,0 +973,Female,40,Bachelors,14,98,57,50,36,9.0,6,69,Rural,ML Engineer,117520,1 +974,Male,52,High School,10,76,72,96,81,6.0,0,2,Urban,Manager,46265,1 +975,Male,33,Bachelors,1,54,49,4,24,2.0,2,10,Rural,HR Executive,147488,0 +976,Male,48,Masters,12,99,1,27,20,6.0,2,81,Semi-Urban,HR Executive,95336,0 +977,Male,39,Diploma,4,25,1,3,97,0.0,4,13,Semi-Urban,HR Executive,92375,0 +978,Male,37,Diploma,2,69,63,0,69,3.0,5,90,Semi-Urban,Software Engineer,29069,0 +979,Male,44,Bachelors,3,77,64,65,28,3.0,1,89,Urban,Manager,114574,1 +980,Male,36,Bachelors,18,66,46,69,75,2.0,4,36,Urban,Data Analyst,103373,0 +981,Male,37,Masters,2,76,33,38,46,6.0,0,27,Urban,Manager,121347,0 +982,Female,23,Bachelors,17,55,35,65,41,3.0,6,39,Urban,HR Executive,50799,0 +983,Male,38,PhD,16,61,32,70,26,5.0,2,89,Semi-Urban,HR Executive,124432,1 +984,Male,34,Bachelors,0,62,56,17,44,2.0,3,44,Rural,Software Engineer,28203,0 +985,Female,23,PhD,5,45,39,96,51,2.0,2,69,Rural,Software Engineer,79671,1 +986,Male,45,High School,3,48,32,3,59,1.0,3,42,Semi-Urban,ML Engineer,113844,0 +987,Female,27,Masters,16,14,8,86,20,5.0,2,16,Semi-Urban,Software Engineer,145245,0 +988,Male,59,High School,12,84,2,48,89,7.0,2,37,Urban,Software Engineer,44469,0 +989,Male,45,Masters,12,45,19,15,48,2.0,2,48,Rural,ML Engineer,96518,0 +990,Female,37,Masters,16,73,60,88,19,6.0,1,79,Semi-Urban,HR Executive,101698,1 +991,Female,32,High School,16,50,84,14,22,5.0,7,28,Semi-Urban,Data Analyst,145709,0 +992,Female,27,PhD,2,35,37,84,44,2.0,5,41,Urban,Software Engineer,62941,0 +993,Male,48,Bachelors,1,64,49,19,34,6.0,2,86,Urban,Software Engineer,128483,0 +994,Male,54,PhD,1,97,43,99,51,0.0,3,46,Urban,ML Engineer,103368,1 +995,Male,47,High School,10,33,28,69,37,4.0,4,41,Urban,Software Engineer,106083,0 +996,Male,47,Bachelors,4,83,16,1,97,2.0,4,74,Semi-Urban,Manager,34635,0 +997,Female,55,Bachelors,8,7,37,88,30,7.0,6,57,Rural,Manager,85441,0 +998,Male,25,Masters,0,0,86,37,71,1.0,2,12,Semi-Urban,HR Executive,50201,0 +999,Other,28,High School,6,67,73,13,24,5.0,5,33,Semi-Urban,ML Engineer,46166,0 +1000,Male,34,Bachelors,9,91,43,42,86,9.0,4,58,Urban,Data Analyst,90017,0 +1001,Male,37,Bachelors,11,76,12,38,85,7.0,6,43,Urban,Data Analyst,99292,0 +1002,Male,55,Masters,16,47,26,99,66,5.0,5,91,Urban,Software Engineer,83358,1 +1003,Female,42,Masters,9,88,53,7,43,1.0,6,35,Urban,Software Engineer,80558,0 +1004,Female,32,Bachelors,4,7,79,85,42,7.0,5,63,Rural,Data Analyst,55617,0 +1005,Female,24,Bachelors,14,65,13,46,53,5.0,6,75,Urban,HR Executive,133146,0 +1006,Female,32,Diploma,6,55,98,95,59,2.0,6,12,Semi-Urban,ML Engineer,76293,1 +1007,Female,46,Diploma,1,63,47,11,25,0.0,3,86,Rural,Software Engineer,109685,0 +1008,Female,54,Masters,1,54,66,36,65,6.0,5,95,Urban,Manager,57626,1 +1009,Male,55,Masters,18,19,51,45,29,3.0,3,69,Urban,HR Executive,44315,0 +1010,Male,49,Bachelors,0,49,60,3,52,9.0,6,27,Urban,Software Engineer,38241,0 +1011,Male,51,Diploma,9,20,61,27,70,7.0,0,5,Semi-Urban,Manager,90150,0 +1012,Other,22,High School,2,24,18,26,39,0.0,0,37,Urban,ML Engineer,86281,0 +1013,Female,54,Diploma,0,99,93,37,52,1.0,6,3,Rural,ML Engineer,48946,0 +1014,Male,47,Diploma,10,78,78,78,83,5.0,2,91,Urban,Software Engineer,58991,1 +1015,Female,33,Bachelors,18,17,98,6,24,9.0,5,82,Urban,ML Engineer,106623,0 +1016,Female,33,Bachelors,10,5,57,94,58,1.0,2,44,Urban,Manager,96589,0 +1017,Male,40,Bachelors,19,20,64,73,92,7.0,4,79,Urban,Manager,137188,1 +1018,Male,23,Diploma,3,1,89,61,2,2.0,5,40,Semi-Urban,Data Analyst,50118,0 +1019,Female,37,Masters,11,71,55,16,61,5.0,4,19,Urban,Data Analyst,66016,0 +1020,Male,36,Diploma,16,56,14,20,30,0.0,7,11,Urban,Software Engineer,59606,0 +1021,Female,58,High School,2,66,78,88,98,3.0,7,59,Rural,Manager,109261,1 +1022,Male,39,PhD,6,66,78,30,59,7.0,6,70,Semi-Urban,HR Executive,111216,1 +1023,Female,23,High School,3,46,31,12,10,9.0,0,73,Urban,Manager,36774,0 +1024,Other,56,Bachelors,16,48,56,88,50,0.0,7,66,Urban,Data Analyst,126661,1 +1025,Female,28,Diploma,1,91,57,14,36,5.0,4,48,Rural,Data Analyst,25047,0 +1026,Male,59,PhD,3,84,71,97,41,9.0,5,67,Urban,ML Engineer,110867,1 +1027,Female,49,Diploma,10,91,31,86,1,0.0,7,74,Urban,Software Engineer,41475,1 +1028,Female,23,Masters,10,65,3,53,82,8.0,7,18,Semi-Urban,Data Analyst,20229,0 +1029,Male,53,Diploma,13,82,15,14,3,8.0,7,72,Urban,Software Engineer,80169,0 +1030,Female,42,Bachelors,19,63,26,81,63,0.0,5,20,Urban,Software Engineer,120479,0 +1031,Male,53,Bachelors,12,98,80,87,91,5.0,0,14,Semi-Urban,HR Executive,90799,1 +1032,Male,36,Masters,8,6,77,79,86,9.0,2,12,Urban,Manager,125334,0 +1033,Male,57,Masters,5,97,15,4,35,7.0,6,34,Semi-Urban,HR Executive,75537,0 +1034,Male,49,Bachelors,1,67,48,28,34,3.0,7,81,Urban,ML Engineer,126343,0 +1035,Male,36,High School,14,50,42,69,21,4.0,4,91,Semi-Urban,Data Analyst,48708,1 +1036,Female,24,Diploma,3,12,77,73,97,3.0,6,12,Urban,HR Executive,69908,0 +1037,Male,58,High School,12,7,26,6,44,8.0,0,89,Urban,ML Engineer,57408,0 +1038,Female,48,Masters,15,97,34,66,51,0.0,3,57,Urban,Manager,88843,1 +1039,Male,25,Masters,18,49,56,68,22,7.0,1,6,Rural,ML Engineer,45330,0 +1040,Male,21,Bachelors,15,95,7,26,18,6.0,4,58,Urban,Manager,96835,0 +1041,Male,39,Masters,10,66,64,38,4,3.0,3,61,Rural,Manager,99014,0 +1042,Female,49,Bachelors,8,99,23,37,73,2.0,4,39,Urban,HR Executive,149265,0 +1043,Male,26,High School,7,92,59,89,10,6.0,0,21,Semi-Urban,Data Analyst,22392,1 +1044,Female,35,Diploma,12,68,35,35,33,6.0,5,32,Urban,Data Analyst,53322,0 +1045,Female,21,Diploma,18,47,43,52,1,0.0,4,93,Rural,Manager,54454,0 +1046,Female,52,Bachelors,6,99,58,35,23,5.0,0,1,Semi-Urban,Data Analyst,131825,0 +1047,Male,31,Bachelors,10,9,11,33,62,4.0,6,38,Urban,HR Executive,133105,0 +1048,Male,38,Bachelors,3,25,83,39,16,0.0,0,2,Urban,Data Analyst,121960,0 +1049,Female,38,High School,8,81,18,98,97,3.0,0,25,Urban,Software Engineer,59146,0 +1050,Male,34,Masters,8,61,41,23,54,1.0,4,56,Rural,Software Engineer,83076,0 +1051,Female,46,Bachelors,12,39,77,10,50,3.0,3,24,Urban,Software Engineer,87780,0 +1052,Male,29,Bachelors,12,50,7,31,16,3.0,5,88,Urban,HR Executive,106526,0 +1053,Female,22,Bachelors,6,36,52,42,18,3.0,1,3,Urban,ML Engineer,63960,0 +1054,Female,49,Bachelors,16,8,46,92,62,1.0,2,49,Urban,ML Engineer,144768,0 +1055,Other,37,Masters,1,61,23,15,6,5.0,3,22,Urban,Manager,108402,0 +1056,Male,49,Diploma,12,73,56,13,93,0.0,1,27,Urban,Manager,88684,0 +1057,Female,45,High School,7,14,10,46,99,0.0,1,0,Semi-Urban,Software Engineer,83515,0 +1058,Male,50,Diploma,1,71,1,57,48,3.0,4,22,Rural,Data Analyst,147830,0 +1059,Male,28,Bachelors,2,74,70,54,36,4.0,7,7,Urban,HR Executive,44695,0 +1060,Female,54,Diploma,13,77,24,32,88,1.0,0,44,Urban,ML Engineer,54568,0 +1061,Female,31,Bachelors,7,13,63,25,31,7.0,0,16,Urban,Software Engineer,36707,0 +1062,Other,52,High School,15,78,56,61,17,0.0,4,67,Urban,HR Executive,114871,1 +1063,Female,53,Bachelors,15,6,81,86,7,9.0,0,28,Rural,Data Analyst,112645,0 +1064,Male,48,High School,14,80,86,63,20,7.0,3,75,Semi-Urban,HR Executive,133084,1 +1065,Male,59,Bachelors,18,70,51,68,33,4.0,0,97,Urban,HR Executive,86060,1 +1066,Female,42,High School,2,57,93,97,1,3.0,2,20,Urban,Data Analyst,137165,1 +1067,Male,31,PhD,12,39,12,38,64,8.0,7,30,Semi-Urban,Manager,135940,0 +1068,Male,54,Bachelors,5,68,32,61,88,5.0,5,85,Rural,ML Engineer,134614,1 +1069,Male,23,Bachelors,11,71,31,4,79,2.0,6,43,Semi-Urban,Data Analyst,58320,0 +1070,Male,32,Diploma,9,88,72,76,18,3.0,1,78,Semi-Urban,HR Executive,144245,1 +1071,Male,32,Masters,11,27,30,68,86,6.0,5,56,Urban,Data Analyst,90323,0 +1072,Male,52,Bachelors,15,86,90,96,27,3.0,4,18,Urban,Data Analyst,20468,1 +1073,Male,25,High School,14,72,83,40,75,3.0,2,69,Rural,Software Engineer,137947,1 +1074,Male,30,Bachelors,0,76,13,87,44,4.0,5,10,Rural,ML Engineer,100639,0 +1075,Other,28,Bachelors,19,63,77,22,52,0.0,4,74,Semi-Urban,Manager,142183,0 +1076,Male,28,Masters,1,79,23,1,74,9.0,2,67,Urban,Data Analyst,141736,0 +1077,Male,45,Bachelors,2,57,29,20,76,7.0,6,50,Urban,Data Analyst,88515,0 +1078,Female,34,Diploma,18,68,43,90,47,7.0,5,15,Semi-Urban,HR Executive,149247,0 +1079,Male,41,Bachelors,2,98,9,63,95,0.0,6,17,Semi-Urban,Data Analyst,22113,0 +1080,Female,26,Bachelors,19,86,5,6,76,7.0,6,3,Urban,HR Executive,133466,0 +1081,Female,58,Diploma,16,62,60,95,2,4.0,3,73,Urban,Data Analyst,96709,1 +1082,Male,51,Bachelors,17,25,97,38,15,7.0,6,51,Urban,Manager,29586,0 +1083,Male,42,Masters,15,24,90,28,87,4.0,3,2,Urban,Software Engineer,50732,0 +1084,Female,55,High School,2,42,8,72,20,4.0,6,80,Urban,HR Executive,114967,0 +1085,Female,39,Diploma,16,33,50,54,31,3.0,2,77,Urban,Software Engineer,98091,0 +1086,Male,59,Bachelors,6,96,13,98,27,4.0,7,7,Urban,ML Engineer,77176,0 +1087,Female,33,Bachelors,4,33,53,27,28,8.0,0,36,Semi-Urban,HR Executive,54040,0 +1088,Male,42,Diploma,0,28,72,44,1,9.0,0,8,Urban,HR Executive,72232,0 +1089,Other,39,Masters,1,2,64,35,41,5.0,7,79,Urban,Manager,137158,0 +1090,Male,41,Diploma,6,43,30,61,17,4.0,7,4,Semi-Urban,HR Executive,58742,0 +1091,Female,23,Masters,11,15,29,4,56,8.0,5,10,Rural,Manager,135192,0 +1092,Female,30,Bachelors,10,28,29,61,91,6.0,1,86,Rural,Software Engineer,133008,0 +1093,Female,25,High School,9,87,8,90,60,8.0,5,96,Rural,Manager,113966,1 +1094,Male,45,Bachelors,7,36,49,37,45,0.0,7,92,Semi-Urban,ML Engineer,140756,0 +1095,Male,57,Bachelors,16,64,14,46,12,6.0,0,90,Urban,Manager,111151,0 +1096,Male,26,Bachelors,6,9,39,1,15,1.0,2,63,Urban,Software Engineer,56765,0 +1097,Male,49,High School,9,4,5,88,80,7.0,6,67,Rural,Data Analyst,43549,0 +1098,Male,32,High School,1,16,30,89,69,6.0,5,49,Semi-Urban,ML Engineer,145999,0 +1099,Female,21,Masters,16,29,50,16,17,8.0,5,10,Rural,HR Executive,127856,0 +1100,Male,28,Diploma,2,63,54,23,24,8.0,4,6,Semi-Urban,ML Engineer,143686,0 +1101,Male,22,Masters,11,30,95,29,89,6.0,5,38,Rural,Data Analyst,117301,0 +1102,Other,28,Masters,5,59,52,70,47,6.0,1,98,Rural,HR Executive,93807,1 +1103,Female,24,Diploma,15,71,33,95,46,1.0,1,76,Semi-Urban,HR Executive,21719,1 +1104,Female,33,Masters,16,44,34,92,16,4.0,0,30,Rural,Software Engineer,137923,0 +1105,Other,49,High School,11,86,55,96,34,6.0,6,21,Urban,Manager,103605,1 +1106,Male,56,Diploma,18,0,4,28,3,6.0,6,47,Urban,Manager,139256,0 +1107,Male,35,Masters,16,89,36,19,10,8.0,7,94,Urban,Manager,31587,1 +1108,Female,28,High School,14,43,28,68,42,3.0,6,55,Urban,Data Analyst,97831,0 +1109,Female,27,Diploma,8,13,0,84,7,1.0,3,88,Urban,HR Executive,144581,0 +1110,Male,44,Bachelors,16,7,86,23,75,3.0,0,50,Urban,Manager,106071,0 +1111,Female,37,Masters,6,26,3,60,98,8.0,4,48,Urban,Manager,39373,0 +1112,Male,51,Bachelors,2,62,7,42,39,3.0,5,72,Semi-Urban,Manager,61659,0 +1113,Male,48,Bachelors,12,18,74,61,5,7.0,2,86,Rural,Software Engineer,41630,1 +1114,Male,40,Diploma,17,18,13,57,81,1.0,3,56,Rural,Software Engineer,84313,0 +1115,Male,37,Masters,1,79,78,86,39,0.0,4,5,Semi-Urban,Software Engineer,116678,1 +1116,Male,32,Diploma,14,52,0,36,88,6.0,5,91,Urban,HR Executive,123218,0 +1117,Male,32,Bachelors,10,2,77,20,41,3.0,3,54,Semi-Urban,HR Executive,95185,0 +1118,Female,22,Masters,0,4,66,98,30,1.0,3,92,Rural,ML Engineer,34831,1 +1119,Male,47,Bachelors,4,95,69,72,50,6.0,3,81,Semi-Urban,Software Engineer,86902,1 +1120,Male,38,High School,14,32,45,62,49,7.0,0,91,Urban,Data Analyst,143893,0 +1121,Female,28,Diploma,4,18,23,35,63,1.0,7,29,Urban,Data Analyst,64485,0 +1122,Other,48,Diploma,13,82,13,44,92,8.0,2,56,Semi-Urban,ML Engineer,133191,0 +1123,Female,55,High School,0,62,27,78,31,1.0,4,93,Urban,Data Analyst,124345,1 +1124,Female,45,Bachelors,12,90,33,72,88,3.0,5,25,Urban,HR Executive,115477,0 +1125,Female,34,Bachelors,14,82,74,98,83,9.0,0,4,Semi-Urban,HR Executive,82592,1 +1126,Male,55,Diploma,5,71,72,88,34,3.0,4,18,Rural,Software Engineer,113345,1 +1127,Male,56,Bachelors,15,3,6,84,18,4.0,4,54,Rural,Manager,96002,0 +1128,Male,54,High School,8,20,82,75,99,0.0,6,5,Rural,HR Executive,138217,0 +1129,Male,38,PhD,7,61,79,62,12,0.0,2,17,Semi-Urban,Software Engineer,119951,0 +1130,Male,22,Bachelors,19,83,91,85,23,4.0,3,65,Urban,HR Executive,49883,1 +1131,Female,42,Diploma,6,14,48,94,46,5.0,5,70,Urban,HR Executive,101693,0 +1132,Male,57,Bachelors,16,46,0,20,49,3.0,6,11,Semi-Urban,Software Engineer,61648,0 +1133,Male,23,Bachelors,3,65,68,41,29,4.0,2,79,Rural,Data Analyst,57435,1 +1134,Male,58,High School,7,54,20,84,74,6.0,2,0,Rural,ML Engineer,72022,0 +1135,Female,23,PhD,5,81,63,53,95,8.0,0,69,Urban,ML Engineer,121215,1 +1136,Male,29,Bachelors,12,43,75,8,47,6.0,7,5,Urban,Data Analyst,85373,0 +1137,Female,41,Diploma,7,27,8,72,8,0.0,2,96,Rural,Manager,47311,0 +1138,Male,59,Masters,14,35,14,34,71,2.0,3,86,Rural,Data Analyst,123361,0 +1139,Male,42,Diploma,6,90,82,1,74,3.0,1,70,Semi-Urban,Data Analyst,79150,1 +1140,Male,48,Masters,0,96,99,2,75,7.0,7,44,Urban,Data Analyst,111019,1 +1141,Female,31,High School,6,49,5,83,67,9.0,4,89,Semi-Urban,HR Executive,39808,0 +1142,Male,33,PhD,12,63,48,26,98,0.0,0,73,Urban,Software Engineer,56539,0 +1143,Female,59,Bachelors,19,47,32,51,8,9.0,3,18,Rural,ML Engineer,135802,0 +1144,Male,37,High School,3,96,30,72,91,5.0,7,7,Urban,ML Engineer,103257,0 +1145,Male,48,Masters,18,94,81,91,99,2.0,0,76,Urban,Data Analyst,64746,1 +1146,Female,52,Bachelors,6,65,16,35,87,7.0,2,86,Urban,ML Engineer,146189,0 +1147,Female,24,Diploma,16,96,64,96,39,2.0,3,95,Urban,ML Engineer,55688,1 +1148,Female,41,Masters,16,80,66,37,40,9.0,3,2,Urban,Software Engineer,53471,0 +1149,Female,40,Bachelors,3,60,40,56,75,6.0,3,11,Urban,Manager,23251,0 +1150,Female,37,Bachelors,3,13,53,9,70,9.0,3,95,Urban,ML Engineer,104559,0 +1151,Female,50,Diploma,11,9,97,9,52,4.0,5,22,Urban,Manager,109660,0 +1152,Female,29,Masters,7,38,75,5,56,5.0,7,35,Urban,Data Analyst,82402,0 +1153,Female,41,Masters,19,64,53,57,60,4.0,6,19,Rural,Data Analyst,26027,0 +1154,Female,26,Bachelors,12,63,60,72,34,7.0,7,3,Urban,Software Engineer,58365,0 +1155,Female,52,Bachelors,2,27,5,58,22,8.0,0,13,Rural,Data Analyst,48553,0 +1156,Female,54,Masters,4,43,6,93,44,0.0,6,86,Urban,ML Engineer,65585,0 +1157,Male,21,Bachelors,15,18,27,64,18,9.0,6,9,Rural,ML Engineer,119744,0 +1158,Female,53,Bachelors,17,41,51,89,35,4.0,3,38,Rural,Software Engineer,25014,0 +1159,Female,51,Masters,0,4,15,19,9,6.0,3,58,Rural,Software Engineer,117356,0 +1160,Male,40,Masters,6,0,64,53,47,3.0,5,77,Semi-Urban,HR Executive,95817,0 +1161,Female,28,PhD,2,0,95,88,83,0.0,6,0,Urban,ML Engineer,33846,0 +1162,Male,58,Bachelors,13,88,30,13,27,2.0,2,58,Urban,Software Engineer,51826,0 +1163,Male,51,Bachelors,3,6,30,36,19,6.0,5,43,Rural,Manager,97685,0 +1164,Female,30,Masters,0,60,76,10,52,8.0,3,19,Semi-Urban,Software Engineer,54583,0 +1165,Male,58,Diploma,7,79,69,22,65,0.0,7,38,Rural,Data Analyst,73575,0 +1166,Female,50,Masters,5,79,85,8,11,0.0,7,23,Urban,Data Analyst,44447,0 +1167,Female,46,High School,17,29,32,67,58,8.0,7,58,Urban,Data Analyst,89012,0 +1168,Male,31,Diploma,4,74,3,62,58,2.0,6,26,Rural,HR Executive,85270,0 +1169,Male,42,Masters,11,49,91,76,74,5.0,7,5,Urban,Manager,54964,0 +1170,Male,34,Masters,13,56,38,1,24,8.0,6,96,Semi-Urban,Data Analyst,128508,0 +1171,Female,41,Diploma,7,61,32,7,9,9.0,6,15,Urban,HR Executive,45132,0 +1172,Other,45,Bachelors,10,83,90,64,89,5.0,5,7,Urban,Manager,124590,1 +1173,Female,43,Bachelors,9,7,15,84,7,2.0,1,67,Urban,Software Engineer,108370,0 +1174,Male,54,Bachelors,16,2,40,44,62,2.0,5,82,Rural,HR Executive,78563,0 +1175,Female,38,Masters,7,10,70,75,33,1.0,3,94,Semi-Urban,ML Engineer,108674,1 +1176,Male,39,Masters,6,93,11,69,32,6.0,5,8,Semi-Urban,Manager,126536,0 +1177,Female,30,Bachelors,6,85,9,46,67,1.0,5,37,Urban,HR Executive,67631,0 +1178,Male,45,Diploma,16,71,17,19,80,7.0,5,33,Rural,Manager,76316,0 +1179,Female,43,PhD,5,86,78,35,19,1.0,2,67,Urban,ML Engineer,79553,1 +1180,Male,36,Bachelors,16,11,51,61,37,2.0,2,62,Semi-Urban,ML Engineer,128703,0 +1181,Other,53,Diploma,8,66,25,61,21,2.0,4,70,Urban,Software Engineer,123799,0 +1182,Male,51,Bachelors,9,6,46,21,96,9.0,1,15,Semi-Urban,HR Executive,25307,0 +1183,Female,59,High School,12,11,96,87,96,2.0,0,46,Urban,Data Analyst,32782,0 +1184,Female,35,Bachelors,8,42,43,69,37,6.0,3,31,Urban,HR Executive,146463,0 +1185,Male,33,Diploma,12,21,49,94,95,4.0,3,24,Semi-Urban,ML Engineer,97440,0 +1186,Female,50,Bachelors,1,58,64,23,93,9.0,3,91,Semi-Urban,Manager,98775,0 +1187,Female,48,Masters,15,51,89,3,64,2.0,0,54,Urban,HR Executive,55676,0 +1188,Male,26,PhD,19,13,41,6,69,7.0,3,72,Urban,Manager,145462,0 +1189,Male,47,High School,17,70,31,51,38,7.0,4,4,Semi-Urban,HR Executive,71756,0 +1190,Female,33,Masters,8,59,50,31,37,5.0,0,86,Urban,Software Engineer,105962,0 +1191,Male,36,High School,10,83,90,80,17,5.0,4,49,Semi-Urban,ML Engineer,136275,1 +1192,Male,26,Bachelors,0,44,17,16,28,5.0,3,51,Semi-Urban,Manager,67561,0 +1193,Male,29,Bachelors,5,77,71,32,82,6.0,1,60,Rural,Software Engineer,67505,1 +1194,Female,22,Masters,1,17,21,32,6,3.0,0,92,Urban,Data Analyst,93087,0 +1195,Male,22,Masters,13,61,40,26,75,4.0,3,72,Urban,Data Analyst,81972,0 +1196,Female,57,PhD,7,34,15,64,96,4.0,2,70,Semi-Urban,Data Analyst,142567,0 +1197,Other,58,High School,19,77,93,19,0,7.0,2,33,Urban,ML Engineer,95992,0 +1198,Other,43,Masters,4,78,44,86,18,2.0,3,83,Urban,ML Engineer,97380,1 +1199,Female,27,Diploma,11,58,61,54,38,1.0,4,67,Urban,Manager,97707,0 +1200,Male,25,Masters,7,66,96,81,60,1.0,5,85,Rural,ML Engineer,61961,1 +1201,Female,31,Bachelors,10,79,67,92,49,4.0,0,54,Urban,ML Engineer,102029,1 +1202,Male,45,Bachelors,2,25,29,93,9,3.0,2,25,Rural,Software Engineer,81378,0 +1203,Male,23,Masters,8,44,86,84,57,4.0,6,18,Urban,HR Executive,92398,0 +1204,Male,54,Diploma,17,15,27,29,86,8.0,3,7,Urban,HR Executive,56922,0 +1205,Male,53,Bachelors,7,92,8,75,51,7.0,0,26,Urban,Manager,115626,0 +1206,Female,41,Diploma,11,36,82,26,81,4.0,1,7,Urban,ML Engineer,58623,0 +1207,Female,54,Masters,4,68,63,48,88,0.0,3,89,Semi-Urban,Manager,144144,1 +1208,Male,54,Bachelors,2,98,8,65,38,8.0,4,18,Urban,ML Engineer,103112,0 +1209,Male,39,PhD,8,41,65,61,62,9.0,7,7,Urban,ML Engineer,123638,0 +1210,Other,49,Bachelors,1,55,68,12,47,6.0,7,36,Semi-Urban,HR Executive,117575,0 +1211,Male,47,Masters,1,89,36,93,25,5.0,3,12,Rural,Manager,75276,0 +1212,Male,40,Bachelors,12,80,94,83,54,9.0,0,75,Urban,Software Engineer,46692,1 +1213,Male,55,Bachelors,19,9,64,12,54,8.0,3,87,Semi-Urban,ML Engineer,23027,0 +1214,Female,51,Masters,15,8,28,16,12,8.0,0,24,Urban,Software Engineer,45230,0 +1215,Female,32,Masters,13,33,37,19,65,4.0,5,6,Rural,Data Analyst,93257,0 +1216,Male,56,Diploma,18,73,21,42,36,5.0,3,29,Urban,Manager,32267,0 +1217,Male,33,PhD,12,51,47,69,55,3.0,5,93,Rural,ML Engineer,141265,1 +1218,Female,53,High School,11,39,84,35,2,4.0,1,23,Semi-Urban,Software Engineer,92090,0 +1219,Female,34,High School,13,86,11,42,4,6.0,7,12,Urban,Software Engineer,41821,0 +1220,Male,37,Diploma,14,97,83,59,82,7.0,7,40,Urban,Manager,33137,1 +1221,Other,36,Bachelors,6,64,49,49,48,7.0,5,35,Urban,Manager,131843,0 +1222,Male,31,Diploma,5,65,37,28,41,4.0,2,62,Urban,Software Engineer,23871,0 +1223,Male,57,Diploma,17,38,58,20,35,8.0,4,15,Urban,Software Engineer,89617,0 +1224,Female,32,Bachelors,1,52,30,77,26,4.0,0,23,Urban,HR Executive,133581,0 +1225,Male,32,Diploma,15,32,70,86,41,5.0,2,24,Urban,Manager,62277,0 +1226,Female,31,Masters,2,50,88,16,85,8.0,4,63,Urban,HR Executive,148176,0 +1227,Male,44,Diploma,8,40,4,96,94,2.0,5,45,Urban,Software Engineer,21421,0 +1228,Male,51,Masters,8,84,72,27,29,9.0,2,77,Urban,Software Engineer,21458,1 +1229,Other,51,Bachelors,8,21,49,38,16,8.0,7,0,Urban,ML Engineer,135180,0 +1230,Male,46,Bachelors,18,80,55,31,77,8.0,4,82,Urban,Manager,132038,1 +1231,Female,56,High School,2,48,46,14,62,7.0,1,25,Semi-Urban,ML Engineer,99871,0 +1232,Male,43,Diploma,16,12,1,58,92,9.0,5,27,Urban,Manager,140356,0 +1233,Male,36,Diploma,5,72,57,87,56,3.0,3,52,Urban,ML Engineer,105840,1 +1234,Male,28,Bachelors,15,40,23,52,62,0.0,1,35,Urban,ML Engineer,47513,0 +1235,Female,46,Masters,15,6,27,58,87,6.0,2,87,Rural,ML Engineer,140402,0 +1236,Male,51,Diploma,18,23,38,75,48,8.0,7,16,Urban,Software Engineer,28358,0 +1237,Female,40,Bachelors,0,49,28,37,60,3.0,1,86,Semi-Urban,Software Engineer,58653,0 +1238,Male,52,High School,15,32,95,30,65,2.0,5,67,Urban,Manager,72759,0 +1239,Other,43,Bachelors,3,70,89,18,86,0.0,1,50,Semi-Urban,Manager,143734,0 +1240,Male,52,High School,0,22,32,20,4,1.0,6,88,Urban,Manager,128874,0 +1241,Female,49,Masters,1,86,69,80,97,1.0,3,87,Urban,Software Engineer,122222,1 +1242,Female,32,Bachelors,4,95,18,29,87,4.0,7,65,Semi-Urban,Data Analyst,87745,0 +1243,Female,57,Masters,17,58,67,54,53,5.0,5,73,Urban,Software Engineer,46858,1 +1244,Female,37,Diploma,1,94,64,79,73,8.0,7,30,Semi-Urban,HR Executive,104584,1 +1245,Female,50,Masters,12,45,18,55,29,1.0,2,96,Semi-Urban,Data Analyst,130071,0 +1246,Female,23,Masters,12,64,45,26,15,0.0,4,12,Urban,Data Analyst,61968,0 +1247,Male,21,High School,0,15,40,89,83,6.0,6,53,Urban,Software Engineer,96437,0 +1248,Male,36,Bachelors,16,90,86,39,58,6.0,4,21,Rural,HR Executive,122499,1 +1249,Female,23,Masters,19,1,56,75,93,2.0,3,56,Rural,HR Executive,107463,0 +1250,Female,24,Bachelors,15,12,46,94,12,6.0,0,59,Urban,Data Analyst,93460,0 +1251,Female,55,Masters,19,66,8,82,8,1.0,1,0,Urban,Manager,77030,0 +1252,Male,21,High School,4,12,15,10,40,7.0,0,66,Rural,Data Analyst,104620,0 +1253,Male,26,Bachelors,8,40,74,37,93,1.0,6,78,Urban,HR Executive,21293,0 +1254,Male,50,Diploma,14,83,74,4,97,3.0,1,17,Rural,HR Executive,136715,0 +1255,Female,26,Bachelors,3,73,30,95,75,6.0,6,33,Urban,Manager,47936,0 +1256,Male,57,Bachelors,13,31,62,93,13,8.0,3,46,Urban,ML Engineer,121416,0 +1257,Male,57,High School,9,56,99,86,91,0.0,0,65,Urban,ML Engineer,132244,1 +1258,Male,45,Bachelors,17,51,51,82,95,9.0,1,62,Rural,Manager,44577,1 +1259,Male,43,High School,9,89,38,57,90,2.0,5,86,Semi-Urban,Data Analyst,99279,1 +1260,Male,35,Diploma,0,96,54,2,47,9.0,4,25,Urban,Manager,93344,0 +1261,Male,47,Bachelors,9,33,94,39,35,4.0,4,15,Semi-Urban,ML Engineer,81662,0 +1262,Female,25,High School,15,34,54,87,59,5.0,3,56,Rural,ML Engineer,131161,0 +1263,Male,22,Bachelors,15,57,64,35,82,9.0,7,26,Rural,Manager,57951,0 +1264,Male,58,Bachelors,15,4,85,2,89,5.0,6,72,Urban,Manager,148269,0 +1265,Male,51,Bachelors,4,72,54,30,62,2.0,4,40,Urban,Software Engineer,112459,0 +1266,Male,50,High School,0,37,57,88,38,8.0,1,3,Rural,HR Executive,31201,0 +1267,Male,59,Bachelors,8,96,23,83,49,4.0,0,6,Semi-Urban,ML Engineer,43879,0 +1268,Male,39,Bachelors,9,22,62,13,32,7.0,1,75,Semi-Urban,ML Engineer,128391,0 +1269,Female,24,High School,7,49,59,3,74,6.0,7,97,Semi-Urban,Software Engineer,66052,0 +1270,Male,47,Masters,14,3,22,89,30,5.0,2,53,Rural,Data Analyst,46445,0 +1271,Female,29,Masters,12,72,40,65,76,7.0,6,64,Urban,Software Engineer,55114,1 +1272,Female,49,Masters,12,69,36,96,88,3.0,6,47,Rural,Manager,118115,1 +1273,Female,27,High School,14,30,4,60,27,5.0,2,2,Semi-Urban,Software Engineer,24791,0 +1274,Male,25,Diploma,10,8,44,7,55,1.0,0,39,Rural,ML Engineer,94313,0 +1275,Male,51,Diploma,7,15,31,76,56,6.0,0,30,Rural,Software Engineer,26463,0 +1276,Male,59,High School,15,56,1,27,23,7.0,3,82,Semi-Urban,HR Executive,147151,0 +1277,Male,54,PhD,16,42,9,83,46,4.0,6,70,Rural,HR Executive,47820,0 +1278,Other,40,High School,7,20,50,92,26,0.0,4,89,Urban,ML Engineer,140930,1 +1279,Male,49,High School,17,68,29,76,65,5.0,7,23,Semi-Urban,HR Executive,136959,0 +1280,Male,32,Diploma,15,20,55,54,39,7.0,5,6,Urban,Manager,73363,0 +1281,Female,48,Bachelors,1,57,49,33,80,7.0,7,89,Urban,HR Executive,83278,0 +1282,Female,58,Masters,4,19,20,79,74,2.0,0,91,Urban,Manager,91192,0 +1283,Male,48,Bachelors,16,62,14,31,2,8.0,3,24,Rural,Manager,70761,0 +1284,Male,31,Bachelors,0,9,36,75,62,6.0,4,46,Semi-Urban,ML Engineer,48828,0 +1285,Male,29,High School,3,32,81,3,97,1.0,5,55,Urban,Manager,135941,0 +1286,Male,51,High School,18,87,61,38,58,1.0,1,21,Semi-Urban,Data Analyst,41108,0 +1287,Male,44,Bachelors,14,42,33,77,92,0.0,6,19,Urban,Data Analyst,93040,0 +1288,Male,58,PhD,8,21,15,59,8,8.0,0,75,Urban,ML Engineer,104701,0 +1289,Male,33,Diploma,1,0,62,75,46,2.0,4,75,Urban,Data Analyst,121278,0 +1290,Male,42,Masters,11,48,11,63,51,2.0,7,65,Rural,HR Executive,113950,0 +1291,Male,44,Diploma,14,55,63,63,7,5.0,2,68,Urban,Software Engineer,119596,1 +1292,Male,40,Bachelors,6,10,35,29,18,7.0,6,22,Semi-Urban,HR Executive,43008,0 +1293,Male,32,Bachelors,15,15,66,64,86,0.0,4,16,Semi-Urban,Software Engineer,81981,0 +1294,Female,57,High School,9,71,25,24,91,2.0,0,38,Urban,Data Analyst,62455,0 +1295,Female,49,Bachelors,7,52,6,24,89,6.0,3,96,Semi-Urban,Data Analyst,135148,0 +1296,Male,57,Bachelors,13,24,91,49,90,5.0,6,95,Urban,Manager,30251,1 +1297,Male,56,Bachelors,12,84,33,63,95,8.0,7,73,Urban,Data Analyst,68259,1 +1298,Male,31,Bachelors,10,4,36,84,67,2.0,1,6,Urban,ML Engineer,113017,0 +1299,Female,34,Bachelors,18,46,74,57,38,5.0,3,31,Rural,ML Engineer,149495,0 +1300,Female,50,Bachelors,0,88,18,1,38,1.0,7,71,Rural,Manager,80395,0 +1301,Male,43,Diploma,1,14,99,47,57,8.0,6,70,Urban,Manager,96411,0 +1302,Female,36,Bachelors,6,96,49,88,71,3.0,0,12,Semi-Urban,Manager,90966,1 +1303,Male,51,Diploma,1,7,69,93,68,8.0,1,67,Rural,HR Executive,96037,1 +1304,Male,41,Bachelors,10,86,67,7,7,2.0,0,28,Urban,HR Executive,99177,0 +1305,Female,41,Masters,13,31,33,79,47,6.0,5,58,Urban,Manager,39291,0 +1306,Female,41,Masters,9,15,26,16,14,2.0,4,76,Urban,Software Engineer,86945,0 +1307,Female,59,Bachelors,8,24,78,91,9,4.0,0,77,Urban,Manager,43017,1 +1308,Female,44,Masters,7,20,45,96,57,6.0,2,42,Rural,Software Engineer,24234,0 +1309,Male,37,High School,11,75,46,14,97,1.0,2,83,Urban,Data Analyst,111516,0 +1310,Female,47,Masters,15,37,12,72,81,8.0,0,62,Semi-Urban,ML Engineer,35936,0 +1311,Male,37,Diploma,3,44,96,3,97,8.0,4,56,Urban,HR Executive,30741,0 +1312,Female,58,High School,18,95,26,91,34,4.0,6,85,Rural,Data Analyst,36945,1 +1313,Male,29,Bachelors,11,79,83,86,7,1.0,5,2,Semi-Urban,HR Executive,100398,1 +1314,Female,52,Bachelors,6,82,37,5,41,8.0,4,33,Rural,HR Executive,144614,0 +1315,Male,26,Diploma,19,55,40,28,36,5.0,5,46,Urban,Manager,105834,0 +1316,Female,38,Masters,0,34,13,37,3,1.0,0,72,Semi-Urban,ML Engineer,90792,0 +1317,Male,42,PhD,17,59,1,56,94,0.0,6,29,Urban,Data Analyst,28249,0 +1318,Female,57,Diploma,14,46,96,47,17,2.0,5,5,Semi-Urban,Manager,127688,0 +1319,Male,49,Diploma,0,60,85,75,59,1.0,5,71,Semi-Urban,Data Analyst,43853,1 +1320,Male,44,High School,3,61,29,24,34,9.0,1,38,Urban,HR Executive,142182,0 +1321,Male,51,PhD,6,86,90,75,83,8.0,7,42,Urban,Data Analyst,71138,1 +1322,Male,22,Bachelors,9,62,55,15,64,2.0,0,5,Semi-Urban,Data Analyst,147773,0 +1323,Female,28,Diploma,10,42,13,3,55,7.0,1,22,Rural,Manager,41676,0 +1324,Male,26,Bachelors,2,93,26,17,31,7.0,6,2,Urban,ML Engineer,76341,0 +1325,Other,49,Masters,19,13,21,76,84,8.0,1,79,Rural,ML Engineer,31166,0 +1326,Male,56,Bachelors,11,83,8,21,97,1.0,4,6,Rural,Software Engineer,62573,0 +1327,Male,43,Bachelors,12,23,68,83,89,0.0,6,1,Urban,Manager,131383,0 +1328,Female,53,Masters,9,91,40,23,1,4.0,1,13,Semi-Urban,HR Executive,32697,0 +1329,Female,36,Masters,6,98,6,28,52,9.0,3,57,Semi-Urban,ML Engineer,26078,0 +1330,Male,56,Bachelors,18,97,27,75,55,2.0,2,43,Urban,HR Executive,66434,1 +1331,Male,48,Bachelors,3,79,98,23,15,8.0,2,38,Urban,Data Analyst,57350,1 +1332,Female,44,Bachelors,14,83,51,49,5,8.0,4,41,Rural,HR Executive,78040,0 +1333,Male,24,High School,15,78,11,25,96,9.0,2,67,Urban,Software Engineer,53081,0 +1334,Other,33,Bachelors,16,95,65,72,30,9.0,5,12,Rural,Manager,103662,1 +1335,Other,48,Diploma,16,66,22,29,8,6.0,3,11,Urban,Manager,31776,0 +1336,Female,50,Masters,2,94,30,26,81,4.0,3,18,Urban,Manager,46395,0 +1337,Male,42,Masters,5,66,48,44,97,1.0,7,54,Urban,HR Executive,114849,0 +1338,Female,51,Bachelors,14,88,11,43,79,7.0,6,14,Rural,Data Analyst,30074,0 +1339,Male,27,Bachelors,17,45,71,67,83,3.0,6,13,Urban,Software Engineer,136936,0 +1340,Male,33,High School,8,52,7,74,30,9.0,3,70,Urban,Data Analyst,146216,0 +1341,Male,59,Bachelors,19,46,30,87,62,1.0,1,9,Rural,Manager,62285,0 +1342,Male,49,Masters,1,65,78,35,46,2.0,6,48,Urban,Software Engineer,84461,0 +1343,Female,58,High School,9,57,65,48,34,5.0,2,60,Urban,Software Engineer,99373,0 +1344,Female,48,Bachelors,4,5,90,26,40,3.0,5,27,Semi-Urban,Software Engineer,39459,0 +1345,Female,37,High School,0,25,88,63,16,7.0,1,28,Urban,ML Engineer,113985,0 +1346,Male,44,Bachelors,8,50,62,84,83,1.0,0,31,Urban,Data Analyst,117140,0 +1347,Male,34,High School,3,0,40,99,50,7.0,7,81,Urban,HR Executive,50041,0 +1348,Male,27,Bachelors,5,44,80,32,82,3.0,0,2,Rural,Manager,114700,0 +1349,Other,21,PhD,5,80,61,85,79,9.0,3,96,Rural,Software Engineer,51294,1 +1350,Male,25,Bachelors,7,40,3,86,87,3.0,6,21,Urban,Data Analyst,61322,0 +1351,Female,31,Masters,15,39,11,50,66,9.0,6,65,Semi-Urban,ML Engineer,66259,0 +1352,Male,41,Masters,16,54,89,74,53,0.0,2,95,Semi-Urban,ML Engineer,63326,1 +1353,Male,48,Masters,19,34,52,21,21,5.0,5,80,Urban,Data Analyst,46159,0 +1354,Female,33,Diploma,10,48,0,64,80,7.0,4,0,Urban,Software Engineer,22684,0 +1355,Male,56,Diploma,16,73,19,55,94,0.0,2,21,Urban,Data Analyst,65538,0 +1356,Female,54,Bachelors,8,7,56,35,44,4.0,7,11,Urban,Manager,79248,0 +1357,Female,51,Diploma,8,70,93,31,36,1.0,4,44,Rural,Software Engineer,138673,0 +1358,Male,41,Bachelors,5,2,69,4,58,5.0,5,99,Rural,Data Analyst,80503,0 +1359,Male,27,Bachelors,12,65,29,76,39,5.0,5,3,Rural,Manager,121311,0 +1360,Male,50,Bachelors,7,90,13,50,2,7.0,6,22,Urban,ML Engineer,138918,0 +1361,Female,51,Bachelors,16,63,38,2,50,8.0,0,57,Urban,ML Engineer,63909,0 +1362,Male,46,Masters,1,89,79,72,12,8.0,6,93,Urban,ML Engineer,104281,1 +1363,Female,43,High School,17,9,26,32,13,0.0,1,39,Semi-Urban,Data Analyst,69471,0 +1364,Female,51,Masters,0,19,47,30,82,4.0,7,45,Urban,Manager,83768,0 +1365,Female,53,Masters,3,95,47,38,3,0.0,7,18,Semi-Urban,Manager,101673,0 +1366,Male,44,High School,5,85,92,13,48,6.0,0,14,Urban,ML Engineer,46660,0 +1367,Female,30,Diploma,3,41,49,4,78,6.0,6,89,Semi-Urban,HR Executive,131014,0 +1368,Female,24,Bachelors,8,27,9,26,14,2.0,1,21,Semi-Urban,HR Executive,24006,0 +1369,Male,55,Masters,2,52,48,79,77,0.0,3,53,Urban,Data Analyst,98618,0 +1370,Male,55,Diploma,10,69,43,31,76,7.0,0,76,Rural,Manager,140896,0 +1371,Other,30,Bachelors,10,81,0,24,51,1.0,4,91,Semi-Urban,Data Analyst,88415,0 +1372,Male,33,Masters,13,82,85,3,98,8.0,0,47,Semi-Urban,HR Executive,139512,0 +1373,Female,47,Diploma,5,56,72,5,26,2.0,6,18,Semi-Urban,HR Executive,130585,0 +1374,Male,39,Diploma,0,24,47,31,75,6.0,7,46,Urban,HR Executive,87519,0 +1375,Male,54,Bachelors,8,77,48,20,58,5.0,3,51,Urban,Software Engineer,145277,0 +1376,Female,59,Diploma,14,15,2,42,99,8.0,6,83,Semi-Urban,Manager,47471,0 +1377,Male,48,Diploma,3,38,69,5,33,8.0,1,42,Urban,Manager,66119,0 +1378,Male,52,Bachelors,6,93,44,11,65,3.0,0,36,Urban,Data Analyst,93265,0 +1379,Male,48,High School,10,61,92,93,61,3.0,6,7,Urban,Software Engineer,87832,1 +1380,Male,40,Bachelors,10,7,62,41,34,7.0,0,68,Urban,Manager,128433,0 +1381,Male,42,Masters,17,90,26,0,16,8.0,4,8,Semi-Urban,ML Engineer,37468,0 +1382,Male,46,Masters,5,51,46,38,34,1.0,1,77,Urban,HR Executive,91491,0 +1383,Other,44,Bachelors,17,17,69,15,18,7.0,0,94,Urban,Manager,86991,0 +1384,Male,22,Bachelors,5,34,90,29,64,4.0,2,46,Urban,Software Engineer,127897,0 +1385,Female,23,Diploma,1,43,61,65,69,7.0,7,93,Semi-Urban,ML Engineer,109067,1 +1386,Male,36,High School,14,81,94,31,18,9.0,5,58,Semi-Urban,Manager,114967,1 +1387,Female,47,Masters,9,47,20,98,60,0.0,7,49,Urban,HR Executive,79478,0 +1388,Male,36,High School,7,92,4,38,74,6.0,5,27,Urban,Software Engineer,71719,0 +1389,Other,29,Bachelors,3,4,49,19,65,2.0,2,60,Urban,Data Analyst,49820,0 +1390,Male,52,Diploma,15,4,16,22,85,2.0,7,40,Urban,Manager,122381,0 +1391,Male,39,Bachelors,11,49,50,47,42,4.0,0,51,Rural,ML Engineer,40334,0 +1392,Male,38,High School,6,48,48,5,28,6.0,4,1,Rural,ML Engineer,131416,0 +1393,Male,41,Bachelors,16,33,49,54,33,6.0,4,89,Semi-Urban,Manager,121499,0 +1394,Male,23,Masters,6,22,55,14,76,4.0,7,50,Urban,Data Analyst,127524,0 +1395,Male,44,Bachelors,9,39,6,49,3,9.0,7,75,Rural,Data Analyst,108693,0 +1396,Female,48,Diploma,17,0,2,95,90,4.0,1,9,Semi-Urban,Data Analyst,23946,0 +1397,Male,41,Bachelors,0,93,69,77,89,7.0,6,1,Urban,Software Engineer,141220,1 +1398,Male,24,Bachelors,15,83,19,59,48,4.0,4,71,Urban,HR Executive,35215,0 +1399,Female,21,Masters,10,43,77,20,27,3.0,7,90,Semi-Urban,ML Engineer,77637,0 +1400,Female,47,High School,10,36,85,38,6,0.0,0,11,Urban,ML Engineer,41601,0 +1401,Male,38,Bachelors,7,4,64,64,89,8.0,5,26,Rural,HR Executive,92802,0 +1402,Male,57,Bachelors,3,5,68,66,34,3.0,6,17,Rural,Software Engineer,126111,0 +1403,Male,40,Bachelors,6,97,36,75,56,6.0,7,61,Urban,Data Analyst,41548,1 +1404,Female,50,PhD,5,80,94,18,6,8.0,6,26,Rural,Data Analyst,79169,0 +1405,Female,54,Bachelors,19,80,67,47,62,4.0,2,10,Urban,Data Analyst,132842,0 +1406,Male,25,Bachelors,11,54,31,0,70,4.0,6,10,Urban,Manager,97216,0 +1407,Female,37,Diploma,5,46,23,54,30,0.0,6,0,Rural,Software Engineer,79419,0 +1408,Female,40,Bachelors,17,94,23,21,18,4.0,6,37,Semi-Urban,ML Engineer,61369,0 +1409,Male,58,Bachelors,2,64,54,1,93,3.0,7,85,Urban,Manager,101504,0 +1410,Female,37,PhD,1,0,36,36,78,2.0,4,68,Semi-Urban,HR Executive,65496,0 +1411,Male,32,Bachelors,6,13,56,36,20,0.0,7,54,Semi-Urban,Software Engineer,145909,0 +1412,Male,51,Diploma,14,90,27,61,74,9.0,4,47,Urban,Data Analyst,82406,0 +1413,Male,40,PhD,8,11,47,11,64,6.0,1,7,Rural,ML Engineer,69357,0 +1414,Male,31,Diploma,18,9,22,54,45,5.0,4,17,Rural,Data Analyst,147801,0 +1415,Male,51,Bachelors,14,2,90,99,98,7.0,2,31,Urban,ML Engineer,118622,0 +1416,Female,44,High School,12,35,73,32,15,4.0,1,17,Urban,HR Executive,93028,0 +1417,Male,46,Bachelors,18,52,2,21,7,0.0,3,93,Rural,ML Engineer,93397,0 +1418,Male,35,Masters,18,95,94,81,29,7.0,3,28,Urban,ML Engineer,45989,1 +1419,Male,31,High School,15,9,8,1,15,6.0,5,67,Urban,Manager,116991,0 +1420,Female,48,Diploma,2,33,8,21,98,8.0,4,76,Semi-Urban,HR Executive,122043,0 +1421,Male,55,Bachelors,7,47,31,8,58,6.0,1,53,Urban,Data Analyst,99068,0 +1422,Male,58,Bachelors,10,84,46,32,64,4.0,2,25,Semi-Urban,ML Engineer,142928,0 +1423,Male,32,Bachelors,15,42,88,73,64,4.0,2,59,Urban,ML Engineer,123544,1 +1424,Male,53,Masters,16,5,67,97,57,5.0,4,84,Urban,Software Engineer,119116,1 +1425,Other,36,Diploma,7,39,62,87,79,7.0,2,85,Semi-Urban,ML Engineer,41757,1 +1426,Other,33,Diploma,9,95,33,12,17,6.0,2,10,Urban,Data Analyst,141440,0 +1427,Male,41,Bachelors,12,11,67,21,36,4.0,7,12,Urban,Manager,36695,0 +1428,Other,38,Bachelors,12,89,83,85,77,6.0,1,55,Semi-Urban,Data Analyst,65132,1 +1429,Female,34,Diploma,2,86,96,94,61,5.0,0,1,Urban,Manager,97454,1 +1430,Female,39,High School,8,17,32,38,90,5.0,2,38,Rural,Software Engineer,107914,0 +1431,Male,28,High School,9,37,48,72,0,2.0,1,20,Urban,HR Executive,51828,0 +1432,Male,50,Bachelors,5,72,40,25,5,7.0,4,94,Urban,Manager,49362,0 +1433,Male,32,Diploma,15,31,5,20,2,6.0,5,14,Urban,Data Analyst,65486,0 +1434,Female,31,High School,5,55,4,30,88,5.0,3,1,Semi-Urban,Manager,136560,0 +1435,Male,25,Bachelors,15,4,39,18,98,9.0,7,42,Semi-Urban,Software Engineer,83525,0 +1436,Male,48,Bachelors,5,53,99,41,91,1.0,6,69,Urban,ML Engineer,114845,1 +1437,Male,58,Masters,17,79,65,58,60,1.0,6,6,Urban,Manager,56007,0 +1438,Female,29,Bachelors,6,52,73,0,86,1.0,4,77,Urban,Software Engineer,48621,0 +1439,Male,54,Masters,19,0,0,61,13,8.0,7,86,Urban,Manager,70816,0 +1440,Female,25,Bachelors,19,24,40,91,74,2.0,5,41,Rural,Data Analyst,58018,0 +1441,Other,31,Bachelors,19,24,72,48,49,2.0,4,85,Rural,HR Executive,34164,0 +1442,Male,44,Masters,8,13,64,86,55,3.0,5,99,Rural,Manager,58032,1 +1443,Female,42,Bachelors,10,93,65,57,11,6.0,0,44,Urban,ML Engineer,69497,1 +1444,Male,36,Bachelors,9,94,76,66,59,1.0,6,96,Urban,HR Executive,54553,1 +1445,Female,22,Bachelors,1,6,27,40,95,3.0,4,69,Urban,ML Engineer,111421,0 +1446,Male,41,Bachelors,3,19,25,95,1,6.0,5,58,Urban,Manager,28637,0 +1447,Female,21,Bachelors,16,5,21,7,61,2.0,7,95,Urban,ML Engineer,146092,0 +1448,Female,46,Bachelors,13,32,92,73,66,5.0,5,93,Rural,HR Executive,38841,1 +1449,Female,29,Bachelors,2,75,45,42,77,8.0,1,29,Urban,ML Engineer,64336,0 +1450,Female,40,Diploma,14,52,54,58,51,7.0,6,55,Semi-Urban,ML Engineer,38977,0 +1451,Male,27,Masters,6,31,88,5,21,0.0,5,45,Urban,HR Executive,147249,0 +1452,Female,51,Masters,0,51,40,14,44,9.0,6,73,Urban,ML Engineer,79414,0 +1453,Female,59,Bachelors,19,62,52,34,77,5.0,3,68,Semi-Urban,Software Engineer,123188,0 +1454,Male,29,Bachelors,11,65,65,35,56,4.0,7,38,Urban,Manager,121969,0 +1455,Male,33,Masters,12,30,80,91,85,6.0,4,54,Semi-Urban,Manager,132876,1 +1456,Female,25,Bachelors,17,47,64,50,67,1.0,2,42,Urban,Data Analyst,95297,0 +1457,Female,47,Masters,1,46,3,99,99,9.0,6,8,Semi-Urban,Software Engineer,28417,0 +1458,Female,39,Bachelors,4,56,8,95,49,8.0,5,68,Urban,Manager,70811,0 +1459,Male,35,Masters,6,17,45,17,35,4.0,3,86,Urban,Software Engineer,86218,0 +1460,Female,39,High School,17,72,2,14,7,2.0,4,84,Rural,ML Engineer,52939,0 +1461,Male,49,High School,13,63,81,5,52,7.0,5,9,Urban,Software Engineer,116390,0 +1462,Female,48,Masters,7,46,85,53,47,2.0,6,56,Rural,HR Executive,128118,0 +1463,Male,34,Bachelors,5,10,86,46,85,9.0,4,12,Urban,ML Engineer,113955,0 +1464,Female,34,PhD,16,71,81,74,96,7.0,7,63,Urban,HR Executive,92813,1 +1465,Other,35,Bachelors,2,57,53,78,21,7.0,4,62,Semi-Urban,Data Analyst,106784,1 +1466,Male,39,Bachelors,1,32,25,72,38,2.0,1,35,Urban,Manager,137041,0 +1467,Other,36,Bachelors,8,19,7,43,70,7.0,3,6,Rural,Manager,75126,0 +1468,Male,55,Masters,1,75,33,70,85,5.0,1,71,Urban,Manager,95324,1 +1469,Female,56,Masters,2,9,71,47,9,9.0,1,96,Semi-Urban,Data Analyst,26072,0 +1470,Female,53,Bachelors,8,37,68,43,12,9.0,6,99,Urban,Data Analyst,27847,1 +1471,Male,59,Diploma,17,82,77,91,11,3.0,7,99,Semi-Urban,Data Analyst,77542,1 +1472,Female,57,Bachelors,18,67,94,78,36,4.0,6,64,Rural,Data Analyst,116024,1 +1473,Female,40,Bachelors,1,64,81,54,25,9.0,4,52,Urban,Data Analyst,70967,1 +1474,Male,44,Bachelors,3,4,69,2,49,5.0,6,15,Rural,Software Engineer,86266,0 +1475,Male,59,Bachelors,6,24,37,96,45,5.0,2,90,Urban,ML Engineer,27014,1 +1476,Female,45,Diploma,17,74,95,69,38,4.0,6,21,Urban,HR Executive,110025,1 +1477,Female,54,Masters,2,31,7,97,84,5.0,5,14,Urban,HR Executive,82687,0 +1478,Female,30,Bachelors,0,38,93,78,6,7.0,1,53,Rural,Software Engineer,129713,1 +1479,Female,44,Diploma,1,49,38,58,33,6.0,0,5,Urban,Software Engineer,137752,0 +1480,Male,37,Bachelors,19,44,49,0,91,8.0,1,68,Urban,Manager,81944,0 +1481,Female,34,Masters,11,27,91,61,41,6.0,7,72,Urban,Data Analyst,132524,1 +1482,Male,36,Bachelors,4,66,9,30,84,7.0,2,80,Rural,HR Executive,47096,0 +1483,Male,46,Masters,1,94,98,95,77,8.0,2,74,Urban,ML Engineer,121095,1 +1484,Male,51,Bachelors,11,77,68,35,81,7.0,5,15,Urban,ML Engineer,96813,0 +1485,Male,21,Bachelors,12,65,35,90,11,0.0,6,43,Urban,Software Engineer,82320,0 +1486,Male,27,Diploma,4,18,53,63,24,8.0,6,76,Semi-Urban,Manager,85235,0 +1487,Male,51,Diploma,14,85,35,5,5,3.0,0,27,Urban,Software Engineer,56250,0 +1488,Female,47,Bachelors,12,90,13,72,68,6.0,5,72,Urban,Software Engineer,87168,1 +1489,Male,24,Bachelors,16,88,25,46,85,4.0,4,57,Rural,Software Engineer,73931,0 +1490,Male,45,Bachelors,2,36,16,14,24,1.0,6,94,Urban,HR Executive,89088,0 +1491,Male,50,Diploma,9,5,78,79,29,1.0,6,6,Rural,Software Engineer,141993,0 +1492,Male,22,High School,6,12,87,79,66,6.0,1,23,Rural,HR Executive,125596,0 +1493,Male,38,Bachelors,16,33,85,50,13,6.0,7,63,Urban,Data Analyst,138791,0 +1494,Male,59,Bachelors,19,2,69,47,31,7.0,7,95,Urban,ML Engineer,42917,0 +1495,Female,44,Bachelors,0,98,17,62,99,5.0,3,8,Urban,Manager,81247,0 +1496,Female,49,High School,10,13,46,19,77,7.0,0,55,Urban,Software Engineer,89477,0 +1497,Female,36,Masters,18,4,23,27,27,7.0,6,41,Rural,HR Executive,89415,0 +1498,Male,51,High School,13,6,36,68,70,8.0,4,31,Urban,HR Executive,102039,0 +1499,Male,48,Masters,8,54,86,90,32,4.0,2,87,Urban,Software Engineer,47762,1 +1500,Female,55,Diploma,9,43,30,47,10,5.0,6,10,Urban,Manager,144509,0 +1501,Male,36,Masters,14,81,72,60,6,6.0,4,41,Semi-Urban,HR Executive,109423,1 +1502,Male,43,Bachelors,16,18,72,55,61,7.0,1,7,Semi-Urban,HR Executive,139814,0 +1503,Male,34,Masters,0,19,23,67,6,7.0,7,21,Urban,ML Engineer,38918,0 +1504,Male,53,High School,0,20,59,89,24,0.0,5,51,Urban,HR Executive,67968,0 +1505,Male,30,Bachelors,6,83,23,13,80,7.0,2,44,Urban,Manager,144816,0 +1506,Male,31,Bachelors,18,24,95,49,52,1.0,1,3,Rural,Software Engineer,34916,0 +1507,Male,25,Bachelors,14,57,83,20,79,9.0,1,95,Urban,Manager,64720,1 +1508,Male,41,PhD,4,80,36,74,98,1.0,2,23,Rural,Data Analyst,101187,0 +1509,Female,48,Diploma,18,50,82,44,97,9.0,5,51,Semi-Urban,Software Engineer,42365,0 +1510,Female,24,Masters,10,30,63,52,83,0.0,2,26,Urban,Manager,107649,0 +1511,Female,28,Bachelors,9,30,8,87,68,5.0,0,79,Urban,HR Executive,130785,0 +1512,Female,50,Bachelors,8,93,13,92,8,5.0,6,0,Urban,ML Engineer,131117,0 +1513,Other,53,Diploma,3,26,71,56,95,8.0,0,97,Semi-Urban,HR Executive,142915,1 +1514,Male,52,High School,11,8,14,97,42,6.0,5,16,Urban,Software Engineer,68574,0 +1515,Male,55,PhD,4,63,79,63,72,2.0,7,87,Rural,ML Engineer,39230,1 +1516,Male,53,High School,18,9,87,52,85,4.0,6,20,Urban,Data Analyst,47699,0 +1517,Female,57,Diploma,6,41,61,82,33,2.0,2,78,Urban,HR Executive,101665,1 +1518,Female,38,Bachelors,18,28,13,95,84,9.0,7,65,Semi-Urban,Data Analyst,39916,0 +1519,Male,57,PhD,4,8,91,61,38,1.0,1,73,Urban,ML Engineer,145030,0 +1520,Female,38,Bachelors,19,98,69,72,58,7.0,0,63,Semi-Urban,Manager,110790,1 +1521,Male,49,High School,19,25,5,97,83,0.0,3,7,Rural,Data Analyst,136345,0 +1522,Female,29,Diploma,2,9,33,9,86,0.0,7,65,Semi-Urban,Data Analyst,126585,0 +1523,Male,23,Bachelors,12,22,68,84,10,5.0,1,66,Rural,Manager,73728,1 +1524,Male,52,PhD,15,66,49,15,4,9.0,0,1,Urban,Manager,24407,0 +1525,Male,32,High School,6,8,90,76,27,3.0,1,77,Rural,Software Engineer,124823,1 +1526,Male,51,Masters,3,55,23,57,85,6.0,3,40,Urban,HR Executive,49276,0 +1527,Male,53,Diploma,1,17,42,57,38,9.0,1,46,Semi-Urban,Manager,118242,0 +1528,Male,21,High School,8,28,90,94,44,9.0,3,18,Rural,HR Executive,116416,0 +1529,Female,52,High School,17,54,8,62,43,7.0,4,97,Urban,Manager,34977,0 +1530,Male,53,Bachelors,18,90,2,48,44,8.0,1,69,Urban,Data Analyst,89780,0 +1531,Male,44,PhD,11,15,79,90,67,8.0,0,55,Rural,ML Engineer,70992,1 +1532,Female,21,Bachelors,10,67,17,75,34,6.0,6,3,Urban,Manager,80232,0 +1533,Female,55,Bachelors,9,23,56,3,55,8.0,2,75,Urban,HR Executive,74713,0 +1534,Male,50,Masters,8,24,75,29,46,6.0,2,46,Semi-Urban,HR Executive,87248,0 +1535,Male,42,Bachelors,5,90,74,23,33,8.0,7,58,Semi-Urban,HR Executive,69186,1 +1536,Male,32,Masters,12,74,18,78,8,3.0,6,64,Urban,HR Executive,87187,0 +1537,Male,54,PhD,15,96,39,78,39,8.0,6,30,Semi-Urban,Software Engineer,33556,1 +1538,Female,30,Bachelors,17,18,27,45,82,5.0,4,1,Urban,HR Executive,22865,0 +1539,Male,47,High School,6,45,53,72,51,9.0,5,29,Urban,HR Executive,68186,0 +1540,Male,24,High School,7,36,7,76,83,7.0,3,73,Urban,ML Engineer,109405,0 +1541,Female,58,High School,7,49,39,10,21,3.0,4,85,Urban,ML Engineer,96339,0 +1542,Male,34,Bachelors,4,90,24,49,51,8.0,3,10,Urban,Data Analyst,47035,0 +1543,Male,50,Diploma,10,56,46,27,61,0.0,3,60,Semi-Urban,Software Engineer,116096,0 +1544,Male,24,Bachelors,7,42,26,67,99,0.0,3,30,Semi-Urban,Data Analyst,61425,0 +1545,Other,21,Diploma,5,86,6,72,62,5.0,1,25,Urban,HR Executive,110549,0 +1546,Male,50,Masters,1,97,16,33,36,8.0,6,57,Urban,ML Engineer,147514,0 +1547,Female,49,Bachelors,0,65,93,72,10,9.0,7,69,Semi-Urban,Manager,84142,1 +1548,Male,24,PhD,7,49,53,98,45,6.0,1,22,Semi-Urban,Software Engineer,41686,0 +1549,Male,34,Bachelors,6,32,62,80,30,9.0,0,60,Semi-Urban,Manager,106717,0 +1550,Female,25,Masters,17,91,42,89,80,7.0,3,28,Rural,Software Engineer,89898,1 +1551,Other,54,Bachelors,12,64,7,81,47,9.0,0,93,Rural,ML Engineer,53402,1 +1552,Female,34,Bachelors,7,9,70,29,2,2.0,3,44,Urban,Data Analyst,94004,0 +1553,Female,36,High School,1,56,52,15,95,4.0,0,48,Urban,Software Engineer,30333,0 +1554,Female,27,Bachelors,2,30,56,56,57,2.0,1,52,Urban,Data Analyst,87758,0 +1555,Male,29,Masters,11,97,79,12,12,8.0,4,36,Urban,Manager,80596,0 +1556,Male,29,Bachelors,2,90,18,89,90,1.0,5,33,Semi-Urban,Software Engineer,121912,0 +1557,Female,59,Diploma,3,11,21,10,38,5.0,2,90,Semi-Urban,ML Engineer,41749,0 +1558,Male,42,Bachelors,13,3,89,34,8,4.0,1,89,Semi-Urban,Software Engineer,99016,0 +1559,Female,23,Masters,18,23,65,33,32,3.0,5,6,Urban,Data Analyst,146210,0 +1560,Female,36,PhD,15,52,86,20,82,9.0,2,93,Semi-Urban,Software Engineer,31718,1 +1561,Male,29,Masters,15,62,66,12,72,0.0,4,29,Semi-Urban,Software Engineer,135864,0 +1562,Male,34,Bachelors,6,38,9,1,25,8.0,7,92,Urban,HR Executive,148631,0 +1563,Female,55,Bachelors,10,62,62,56,76,8.0,3,35,Semi-Urban,Manager,146418,0 +1564,Male,53,Bachelors,13,14,13,67,21,0.0,6,79,Urban,Software Engineer,21708,0 +1565,Female,46,Bachelors,18,85,63,71,51,0.0,3,93,Rural,Software Engineer,107053,1 +1566,Male,26,Masters,16,84,92,52,6,6.0,4,96,Urban,HR Executive,26991,1 +1567,Female,39,Bachelors,5,31,29,10,75,4.0,4,28,Urban,HR Executive,109917,0 +1568,Male,38,Diploma,7,28,45,73,69,0.0,3,99,Semi-Urban,ML Engineer,70141,1 +1569,Female,25,Masters,10,21,31,16,43,4.0,1,19,Semi-Urban,ML Engineer,45007,0 +1570,Male,41,Bachelors,8,21,52,40,58,6.0,0,90,Urban,HR Executive,139904,0 +1571,Male,55,Bachelors,7,19,69,47,69,2.0,6,94,Semi-Urban,HR Executive,149765,0 +1572,Male,38,Bachelors,18,85,92,73,42,1.0,6,36,Semi-Urban,Software Engineer,77369,1 +1573,Female,40,Bachelors,8,13,48,10,71,6.0,6,44,Urban,ML Engineer,131989,0 +1574,Female,55,High School,5,27,3,56,75,0.0,7,96,Urban,HR Executive,107029,0 +1575,Male,59,Bachelors,15,32,84,69,35,3.0,1,79,Urban,Manager,107536,1 +1576,Male,23,Bachelors,15,1,65,68,93,5.0,5,2,Urban,HR Executive,71736,0 +1577,Male,27,Bachelors,5,35,71,92,64,4.0,5,87,Semi-Urban,Software Engineer,50965,1 +1578,Female,29,Bachelors,0,79,7,2,96,4.0,4,45,Semi-Urban,ML Engineer,100639,0 +1579,Female,45,High School,8,83,78,94,13,5.0,0,89,Rural,HR Executive,143749,1 +1580,Male,40,Masters,16,47,99,24,70,2.0,1,74,Urban,HR Executive,51615,1 +1581,Male,29,Bachelors,9,17,80,11,46,0.0,1,0,Semi-Urban,Software Engineer,75683,0 +1582,Male,29,Bachelors,4,12,10,55,8,5.0,7,83,Urban,HR Executive,51405,0 +1583,Male,35,Bachelors,14,96,59,14,87,4.0,3,84,Semi-Urban,ML Engineer,57160,1 +1584,Male,50,Bachelors,0,41,97,46,49,3.0,0,27,Rural,HR Executive,111140,0 +1585,Other,36,High School,17,24,49,65,36,7.0,1,83,Rural,Software Engineer,149940,0 +1586,Male,56,Bachelors,14,50,76,76,99,6.0,7,61,Rural,ML Engineer,33887,1 +1587,Female,43,High School,1,6,28,49,32,9.0,0,58,Urban,ML Engineer,62830,0 +1588,Male,38,Masters,15,46,78,66,5,3.0,7,90,Urban,Software Engineer,149258,1 +1589,Male,39,Diploma,15,73,16,86,44,1.0,7,50,Rural,Manager,100318,0 +1590,Female,50,Diploma,16,82,88,44,77,6.0,1,3,Urban,ML Engineer,114659,0 +1591,Female,35,PhD,4,60,91,84,27,0.0,6,51,Semi-Urban,ML Engineer,133497,1 +1592,Other,51,High School,19,74,36,8,87,7.0,5,59,Urban,Software Engineer,74179,0 +1593,Male,33,Bachelors,17,85,76,22,76,7.0,6,42,Urban,Software Engineer,33470,0 +1594,Male,25,Bachelors,1,95,79,2,7,9.0,5,66,Semi-Urban,Manager,52888,1 +1595,Female,45,Bachelors,14,55,62,46,92,5.0,2,81,Urban,Manager,84918,1 +1596,Male,40,Bachelors,2,72,64,89,70,2.0,4,88,Semi-Urban,HR Executive,27875,1 +1597,Male,52,High School,1,36,73,41,96,7.0,4,88,Urban,Software Engineer,102939,1 +1598,Male,47,Bachelors,14,17,88,67,96,6.0,5,91,Urban,HR Executive,114188,1 +1599,Male,37,High School,5,6,70,56,5,9.0,6,54,Urban,HR Executive,100413,0 +1600,Female,43,PhD,4,43,89,8,82,9.0,4,96,Rural,Software Engineer,64007,0 +1601,Male,24,Diploma,14,30,43,45,2,4.0,0,57,Urban,Data Analyst,50839,0 +1602,Male,37,Diploma,2,95,24,34,95,8.0,0,6,Semi-Urban,Software Engineer,39208,0 +1603,Male,23,Bachelors,11,86,35,18,13,9.0,1,57,Semi-Urban,Manager,144357,0 +1604,Male,24,Masters,4,69,78,87,87,8.0,2,52,Urban,ML Engineer,30950,1 +1605,Male,35,Bachelors,3,65,85,48,99,6.0,0,1,Urban,Software Engineer,53958,0 +1606,Male,56,Masters,13,77,68,62,25,3.0,2,6,Urban,Manager,26581,0 +1607,Male,25,Bachelors,14,60,41,37,14,3.0,6,3,Semi-Urban,Data Analyst,131033,0 +1608,Female,32,Diploma,1,98,24,24,57,7.0,3,78,Semi-Urban,Manager,67052,0 +1609,Male,21,Masters,10,3,65,86,77,7.0,7,98,Urban,HR Executive,118205,1 +1610,Male,54,Masters,0,8,15,5,34,0.0,1,58,Rural,Software Engineer,77570,0 +1611,Female,31,Diploma,0,10,18,80,12,2.0,7,90,Urban,ML Engineer,122855,0 +1612,Female,44,Diploma,17,97,73,12,24,5.0,3,25,Urban,Manager,76776,0 +1613,Male,48,Bachelors,4,1,95,10,75,3.0,7,70,Semi-Urban,Data Analyst,137092,0 +1614,Male,51,Bachelors,13,75,65,75,0,4.0,5,8,Urban,ML Engineer,137505,0 +1615,Male,53,Masters,1,21,54,26,56,8.0,1,17,Urban,Manager,79281,0 +1616,Female,52,High School,16,12,58,74,83,1.0,5,57,Rural,Data Analyst,137765,0 +1617,Other,26,Bachelors,1,43,51,20,11,2.0,5,10,Urban,Software Engineer,40922,0 +1618,Female,57,High School,19,79,15,37,5,5.0,4,71,Rural,Software Engineer,133620,0 +1619,Male,48,Diploma,19,51,52,40,80,3.0,2,23,Urban,Software Engineer,139308,0 +1620,Female,55,Masters,0,31,30,78,6,2.0,2,26,Urban,ML Engineer,31525,0 +1621,Male,32,Masters,3,45,62,78,71,0.0,1,71,Rural,Software Engineer,81096,1 +1622,Male,55,Diploma,17,60,27,8,34,8.0,1,68,Semi-Urban,Data Analyst,50817,0 +1623,Male,58,Diploma,11,90,36,21,19,6.0,3,5,Urban,Manager,44961,0 +1624,Other,52,High School,11,98,98,13,84,1.0,6,42,Semi-Urban,ML Engineer,91333,1 +1625,Male,43,Bachelors,18,64,16,18,27,0.0,4,89,Urban,Manager,98663,0 +1626,Female,28,Diploma,1,77,23,43,44,7.0,1,32,Semi-Urban,Manager,100758,0 +1627,Male,59,Diploma,10,93,40,16,23,4.0,4,37,Semi-Urban,Software Engineer,49928,0 +1628,Male,34,Masters,17,9,52,14,18,4.0,1,75,Urban,HR Executive,51575,0 +1629,Male,28,Bachelors,14,15,97,66,77,2.0,7,20,Rural,HR Executive,62388,0 +1630,Male,23,High School,14,30,39,64,65,9.0,0,40,Rural,Manager,129254,0 +1631,Female,55,High School,0,82,66,88,32,6.0,4,95,Semi-Urban,Software Engineer,26968,1 +1632,Male,45,High School,12,17,51,7,59,4.0,5,10,Semi-Urban,Data Analyst,57773,0 +1633,Female,34,Masters,9,75,73,99,33,8.0,7,48,Semi-Urban,ML Engineer,136742,1 +1634,Female,48,Masters,12,42,21,79,28,0.0,2,6,Semi-Urban,Manager,119445,0 +1635,Female,37,Masters,2,24,39,54,8,2.0,0,43,Semi-Urban,ML Engineer,132934,0 +1636,Male,32,Bachelors,16,95,60,60,81,5.0,5,1,Urban,Manager,36284,0 +1637,Male,42,Masters,17,16,54,50,66,2.0,7,56,Semi-Urban,Manager,45471,0 +1638,Male,32,Bachelors,2,72,1,41,33,6.0,6,25,Rural,Manager,80362,0 +1639,Other,30,Bachelors,10,97,95,61,53,6.0,1,15,Semi-Urban,Data Analyst,70635,1 +1640,Female,23,Bachelors,11,92,73,38,74,9.0,5,80,Rural,Manager,65180,1 +1641,Male,48,Bachelors,6,54,82,77,92,9.0,5,75,Urban,Manager,102504,1 +1642,Female,51,Bachelors,0,59,5,3,78,1.0,1,14,Urban,ML Engineer,47144,0 +1643,Male,32,Diploma,13,84,85,39,46,7.0,1,16,Semi-Urban,Software Engineer,46317,0 +1644,Female,22,Bachelors,2,6,21,37,3,0.0,1,67,Urban,Data Analyst,85071,0 +1645,Male,34,Bachelors,4,2,64,84,93,7.0,2,37,Urban,Data Analyst,31131,0 +1646,Female,53,Diploma,6,14,78,35,86,1.0,4,70,Urban,Software Engineer,102588,0 +1647,Male,36,Masters,11,50,3,64,51,4.0,3,16,Rural,Software Engineer,61537,0 +1648,Female,30,Diploma,15,18,50,11,49,7.0,6,16,Semi-Urban,Data Analyst,70696,0 +1649,Female,27,Bachelors,12,60,35,22,71,0.0,3,21,Semi-Urban,Manager,125639,0 +1650,Female,37,Bachelors,16,54,33,52,72,0.0,0,6,Urban,Software Engineer,139620,0 +1651,Male,45,High School,6,22,28,37,47,3.0,5,53,Urban,Software Engineer,126727,0 +1652,Male,50,Masters,11,39,8,52,64,1.0,7,13,Urban,HR Executive,49044,0 +1653,Male,23,Bachelors,1,44,58,85,8,8.0,6,43,Rural,Data Analyst,60888,0 +1654,Male,22,Bachelors,11,45,29,55,85,6.0,4,15,Rural,Manager,146089,0 +1655,Male,45,Diploma,9,64,8,11,27,0.0,1,16,Urban,Software Engineer,129171,0 +1656,Female,44,Masters,5,46,92,38,95,0.0,7,67,Urban,Manager,62386,1 +1657,Male,55,High School,12,84,92,30,30,4.0,5,58,Urban,ML Engineer,81547,1 +1658,Male,55,PhD,10,37,76,69,12,5.0,7,4,Rural,Manager,78416,0 +1659,Male,27,High School,6,34,63,33,20,0.0,4,73,Urban,Software Engineer,72590,0 +1660,Male,22,Diploma,8,90,53,46,64,0.0,1,88,Rural,ML Engineer,139261,1 +1661,Female,42,Bachelors,16,99,63,80,69,4.0,1,4,Semi-Urban,Data Analyst,44442,1 +1662,Male,42,Bachelors,12,77,86,77,77,8.0,6,65,Urban,ML Engineer,62078,1 +1663,Female,47,Bachelors,11,26,69,43,61,5.0,4,54,Urban,Data Analyst,140105,0 +1664,Male,31,Masters,2,90,74,6,60,4.0,7,28,Urban,Software Engineer,32795,0 +1665,Other,33,Bachelors,5,14,46,22,62,8.0,0,66,Semi-Urban,Software Engineer,69671,0 +1666,Female,38,Diploma,3,36,42,78,91,8.0,6,91,Urban,ML Engineer,114775,1 +1667,Male,25,Bachelors,19,55,27,27,40,8.0,1,50,Urban,ML Engineer,126984,0 +1668,Female,46,Masters,15,38,77,33,34,8.0,5,36,Urban,Data Analyst,125105,0 +1669,Male,55,PhD,17,58,46,95,63,1.0,7,19,Rural,HR Executive,53673,0 +1670,Female,47,Masters,11,99,87,93,26,3.0,7,80,Semi-Urban,Manager,26952,1 +1671,Male,27,PhD,4,85,50,11,57,2.0,4,54,Urban,Manager,126227,0 +1672,Female,27,Bachelors,18,9,81,49,76,8.0,7,21,Semi-Urban,Manager,73331,0 +1673,Female,29,Bachelors,14,1,89,16,50,6.0,7,45,Urban,HR Executive,67415,0 +1674,Female,40,Masters,17,78,50,1,74,0.0,7,66,Semi-Urban,ML Engineer,29650,0 +1675,Female,31,High School,10,18,34,84,44,7.0,5,96,Rural,Data Analyst,131747,0 +1676,Male,31,PhD,0,16,1,59,2,6.0,3,30,Rural,HR Executive,145957,0 +1677,Male,47,Diploma,5,97,0,64,66,4.0,1,89,Semi-Urban,Manager,90198,1 +1678,Male,37,Bachelors,4,35,70,32,16,4.0,0,78,Urban,Software Engineer,109816,0 +1679,Male,56,Bachelors,1,91,93,53,35,2.0,0,25,Urban,Manager,122487,1 +1680,Female,23,Masters,1,41,2,81,65,5.0,3,93,Urban,ML Engineer,115194,0 +1681,Male,23,Bachelors,19,23,92,78,17,0.0,1,70,Urban,Data Analyst,93378,1 +1682,Other,32,Bachelors,19,95,9,53,82,0.0,3,71,Urban,Data Analyst,69888,0 +1683,Female,40,Masters,18,50,41,41,43,4.0,7,17,Semi-Urban,Software Engineer,50430,0 +1684,Female,46,Masters,14,75,89,59,30,0.0,3,20,Semi-Urban,Manager,62608,1 +1685,Male,50,Bachelors,2,42,31,43,38,8.0,5,63,Urban,Data Analyst,111339,0 +1686,Female,34,Bachelors,10,39,51,84,18,4.0,3,54,Rural,Data Analyst,78795,0 +1687,Female,30,Diploma,2,23,65,68,74,5.0,7,71,Urban,Manager,148300,0 +1688,Male,55,Bachelors,14,89,89,35,14,2.0,5,40,Urban,Manager,24042,1 +1689,Female,29,High School,18,46,64,41,32,9.0,1,45,Semi-Urban,Data Analyst,144946,0 +1690,Female,31,Masters,5,19,65,27,6,0.0,0,7,Rural,ML Engineer,121416,0 +1691,Male,27,Bachelors,19,49,39,45,35,4.0,6,67,Rural,Manager,70735,0 +1692,Male,28,Bachelors,14,26,9,87,69,7.0,2,8,Rural,Manager,92843,0 +1693,Male,43,Bachelors,17,6,43,54,17,8.0,4,73,Semi-Urban,Manager,98032,0 +1694,Male,27,Bachelors,1,3,86,66,70,9.0,0,6,Urban,Data Analyst,148995,0 +1695,Male,48,Masters,3,16,18,54,34,4.0,2,21,Urban,Data Analyst,114699,0 +1696,Male,49,Bachelors,18,12,43,21,96,6.0,5,60,Urban,HR Executive,142603,0 +1697,Male,54,Bachelors,18,0,17,54,21,3.0,3,16,Urban,Data Analyst,61790,0 +1698,Male,30,Bachelors,10,60,62,11,62,0.0,6,7,Rural,Data Analyst,95105,0 +1699,Other,32,Bachelors,14,51,86,90,22,2.0,3,86,Urban,Data Analyst,112694,1 +1700,Male,38,Diploma,13,44,71,58,35,7.0,2,41,Urban,Software Engineer,46362,0 +1701,Other,39,Masters,4,41,94,53,39,9.0,0,71,Semi-Urban,HR Executive,30710,1 +1702,Male,46,Bachelors,17,62,94,13,4,3.0,0,93,Urban,Manager,56191,1 +1703,Male,56,Masters,10,58,80,95,98,4.0,1,0,Semi-Urban,Data Analyst,149324,0 +1704,Male,27,Diploma,14,83,50,67,40,7.0,7,17,Urban,HR Executive,52231,0 +1705,Male,52,Bachelors,9,34,37,71,20,8.0,2,85,Rural,Manager,103030,0 +1706,Male,43,Masters,11,24,71,97,8,5.0,4,88,Semi-Urban,Manager,35079,1 +1707,Female,27,Bachelors,4,68,60,16,37,4.0,7,73,Rural,Data Analyst,78662,0 +1708,Male,36,Bachelors,18,43,28,69,51,0.0,7,3,Urban,Software Engineer,148639,0 +1709,Female,25,Bachelors,5,6,85,39,58,5.0,2,92,Urban,ML Engineer,56318,0 +1710,Female,37,High School,9,3,76,7,52,5.0,3,67,Rural,HR Executive,141646,0 +1711,Male,26,Bachelors,6,95,73,52,0,4.0,4,79,Rural,HR Executive,67699,1 +1712,Male,45,Bachelors,15,23,0,9,86,9.0,0,99,Urban,ML Engineer,122540,0 +1713,Female,52,High School,2,35,57,64,82,0.0,4,57,Urban,Manager,63774,0 +1714,Male,21,Masters,16,4,37,15,48,0.0,2,42,Urban,Software Engineer,141641,0 +1715,Male,27,Bachelors,5,98,31,42,10,9.0,6,70,Urban,Manager,64127,1 +1716,Other,27,Bachelors,4,34,2,53,51,8.0,0,9,Urban,HR Executive,66890,0 +1717,Male,36,Diploma,1,96,95,64,38,7.0,4,93,Urban,Software Engineer,76682,1 +1718,Female,26,Masters,11,19,13,88,61,2.0,2,92,Rural,ML Engineer,68472,0 +1719,Other,51,Masters,18,88,27,37,6,8.0,0,67,Urban,ML Engineer,35118,0 +1720,Male,57,Bachelors,6,57,39,54,44,7.0,5,84,Rural,Data Analyst,117689,0 +1721,Male,55,Bachelors,6,49,60,65,9,2.0,2,33,Urban,Manager,100433,0 +1722,Male,34,High School,10,44,34,20,58,5.0,1,64,Urban,ML Engineer,99138,0 +1723,Male,54,Masters,18,53,24,69,96,6.0,6,86,Rural,HR Executive,46919,0 +1724,Male,35,High School,5,51,26,29,69,9.0,0,28,Urban,Manager,122823,0 +1725,Female,58,Masters,5,43,6,24,72,4.0,5,62,Semi-Urban,Software Engineer,42425,0 +1726,Male,38,Diploma,11,23,78,18,99,3.0,3,59,Urban,Software Engineer,37921,0 +1727,Male,58,Bachelors,6,21,15,84,50,2.0,3,24,Urban,Data Analyst,99314,0 +1728,Other,51,High School,3,78,3,79,30,6.0,4,46,Urban,HR Executive,60729,0 +1729,Female,58,Bachelors,15,5,93,26,98,1.0,6,1,Rural,HR Executive,70667,0 +1730,Female,57,Bachelors,11,51,38,32,72,0.0,6,75,Urban,Software Engineer,140532,0 +1731,Male,24,Masters,16,94,75,9,8,9.0,3,30,Rural,Data Analyst,106318,0 +1732,Female,49,PhD,15,31,19,24,43,9.0,7,42,Semi-Urban,ML Engineer,71235,0 +1733,Male,33,Bachelors,3,96,97,8,10,1.0,3,40,Urban,HR Executive,42426,1 +1734,Male,30,Bachelors,7,18,19,17,9,7.0,5,71,Urban,HR Executive,29408,0 +1735,Male,54,Bachelors,15,62,9,49,87,1.0,7,35,Urban,Data Analyst,113099,0 +1736,Female,57,Bachelors,8,23,3,8,91,7.0,1,55,Urban,Data Analyst,98052,0 +1737,Male,54,Bachelors,7,71,15,70,28,0.0,7,25,Rural,HR Executive,124578,0 +1738,Male,33,Masters,17,11,92,40,31,3.0,5,4,Semi-Urban,HR Executive,25997,0 +1739,Male,52,Diploma,19,38,24,62,10,1.0,3,64,Rural,HR Executive,95780,0 +1740,Male,29,High School,8,68,65,50,20,0.0,1,23,Semi-Urban,Software Engineer,75494,0 +1741,Female,54,Diploma,6,18,97,72,90,4.0,0,12,Semi-Urban,Software Engineer,121794,0 +1742,Female,52,Bachelors,10,18,20,6,16,5.0,7,29,Urban,Manager,119337,0 +1743,Female,40,Masters,15,25,97,97,64,2.0,6,16,Urban,Manager,66553,0 +1744,Male,21,Masters,16,37,63,25,23,9.0,4,2,Urban,Data Analyst,20243,0 +1745,Male,37,Bachelors,17,94,46,42,3,1.0,1,55,Semi-Urban,ML Engineer,60790,1 +1746,Male,56,Masters,6,62,36,23,75,0.0,2,0,Urban,Manager,109739,0 +1747,Male,31,Bachelors,14,83,7,37,27,6.0,4,51,Rural,HR Executive,42825,0 +1748,Male,29,Bachelors,16,35,89,95,60,5.0,6,68,Rural,Data Analyst,62242,1 +1749,Female,22,Bachelors,9,72,96,53,76,7.0,3,10,Semi-Urban,HR Executive,60930,0 +1750,Male,47,High School,5,97,68,39,5,2.0,2,41,Urban,HR Executive,97627,1 +1751,Male,26,Bachelors,13,34,73,77,69,0.0,0,62,Rural,Manager,64071,1 +1752,Male,21,Bachelors,9,99,15,65,35,1.0,2,6,Urban,Manager,62288,0 +1753,Male,59,Bachelors,17,3,33,26,46,2.0,4,72,Urban,ML Engineer,63144,0 +1754,Male,38,Masters,8,2,72,46,2,5.0,5,6,Rural,HR Executive,61088,0 +1755,Other,58,Diploma,10,38,54,29,35,8.0,0,88,Urban,Manager,138995,0 +1756,Female,39,Diploma,4,71,15,7,22,8.0,5,94,Semi-Urban,ML Engineer,61436,0 +1757,Other,21,Bachelors,10,42,31,15,47,3.0,4,48,Urban,HR Executive,24014,0 +1758,Male,52,High School,4,43,1,31,98,6.0,6,24,Semi-Urban,HR Executive,146802,0 +1759,Male,21,Bachelors,19,45,49,50,15,6.0,4,32,Rural,Data Analyst,81716,0 +1760,Male,34,Bachelors,17,31,8,37,15,1.0,0,84,Urban,Manager,102154,0 +1761,Male,37,Bachelors,16,45,19,75,94,0.0,2,69,Rural,HR Executive,41035,0 +1762,Female,29,Bachelors,4,28,35,42,97,0.0,7,58,Urban,Data Analyst,41043,0 +1763,Male,59,Diploma,17,66,71,26,46,3.0,1,93,Urban,Software Engineer,21168,1 +1764,Male,29,Masters,11,1,45,36,30,2.0,0,45,Rural,HR Executive,40673,0 +1765,Male,31,High School,11,14,73,30,44,2.0,7,89,Urban,Manager,67638,0 +1766,Male,31,Diploma,15,60,87,11,33,1.0,5,92,Semi-Urban,ML Engineer,70688,1 +1767,Female,46,High School,4,87,14,89,40,7.0,3,24,Semi-Urban,Data Analyst,105974,0 +1768,Male,29,Diploma,4,52,51,55,92,4.0,7,45,Rural,HR Executive,94096,0 +1769,Male,55,Bachelors,5,30,96,16,96,5.0,2,46,Urban,ML Engineer,115528,0 +1770,Male,29,High School,13,56,78,64,38,3.0,6,52,Urban,Software Engineer,105738,1 +1771,Male,28,Bachelors,5,18,45,93,44,4.0,6,63,Urban,HR Executive,84978,0 +1772,Female,25,Bachelors,4,28,74,17,7,3.0,3,73,Semi-Urban,Software Engineer,76074,0 +1773,Female,25,Bachelors,15,65,50,60,31,2.0,4,67,Urban,ML Engineer,115005,1 +1774,Other,35,Bachelors,1,66,66,23,62,6.0,2,39,Urban,HR Executive,64762,0 +1775,Female,57,Masters,2,12,76,55,25,8.0,1,75,Rural,Data Analyst,136416,0 +1776,Male,46,Bachelors,15,12,58,86,10,8.0,4,50,Semi-Urban,Software Engineer,135539,0 +1777,Female,54,Bachelors,1,15,13,82,58,0.0,7,54,Semi-Urban,Data Analyst,112670,0 +1778,Male,33,PhD,15,67,81,84,57,2.0,1,3,Urban,Manager,27698,1 +1779,Male,48,Diploma,11,37,82,42,48,9.0,2,21,Semi-Urban,Software Engineer,115542,0 +1780,Female,34,Bachelors,19,69,87,2,34,6.0,4,24,Urban,Software Engineer,128988,0 +1781,Male,21,PhD,13,23,37,90,90,9.0,6,93,Urban,ML Engineer,113495,1 +1782,Female,38,Diploma,19,39,54,36,56,0.0,4,64,Rural,Data Analyst,27130,0 +1783,Male,23,Bachelors,12,38,49,11,44,6.0,2,82,Rural,Manager,124674,0 +1784,Female,34,Bachelors,3,94,14,23,23,1.0,5,67,Semi-Urban,HR Executive,102113,0 +1785,Female,47,PhD,14,13,37,87,22,7.0,3,28,Semi-Urban,Manager,111699,0 +1786,Female,27,Bachelors,6,79,67,53,35,3.0,3,66,Urban,Data Analyst,68458,1 +1787,Female,36,Diploma,13,48,73,11,23,9.0,5,89,Urban,ML Engineer,64744,0 +1788,Female,52,Diploma,6,23,66,76,37,8.0,2,68,Semi-Urban,ML Engineer,90968,0 +1789,Male,25,Diploma,6,79,56,87,14,2.0,4,56,Urban,Data Analyst,121085,1 +1790,Male,22,High School,16,13,74,59,45,1.0,0,95,Semi-Urban,Software Engineer,29766,1 +1791,Male,23,Bachelors,0,78,1,84,73,7.0,3,98,Urban,ML Engineer,36417,1 +1792,Female,27,High School,4,78,86,20,38,2.0,0,80,Rural,Software Engineer,20249,1 +1793,Male,22,Bachelors,14,18,56,68,47,3.0,7,50,Urban,Manager,61899,0 +1794,Female,55,Masters,15,77,39,41,43,2.0,5,98,Urban,Data Analyst,131469,1 +1795,Male,33,Masters,9,48,63,91,55,8.0,6,97,Urban,ML Engineer,112403,1 +1796,Male,26,Masters,16,11,98,24,81,1.0,5,51,Semi-Urban,Data Analyst,46116,0 +1797,Female,25,High School,16,77,56,59,29,8.0,5,80,Semi-Urban,ML Engineer,58621,1 +1798,Male,31,Masters,11,59,1,35,99,7.0,1,11,Urban,HR Executive,86204,0 +1799,Male,38,Bachelors,15,17,8,30,30,6.0,4,29,Semi-Urban,Manager,91335,0 +1800,Male,39,Bachelors,14,78,98,77,74,4.0,3,48,Urban,HR Executive,30799,1 +1801,Other,25,Bachelors,5,19,31,27,17,9.0,3,3,Urban,Software Engineer,77385,0 +1802,Female,28,Bachelors,17,43,42,38,60,1.0,2,70,Semi-Urban,HR Executive,140176,0 +1803,Male,47,Bachelors,6,24,36,5,51,6.0,4,39,Urban,Data Analyst,95504,0 +1804,Male,34,High School,10,93,92,43,19,6.0,0,28,Semi-Urban,Manager,93316,1 +1805,Male,23,Masters,18,67,97,65,14,0.0,0,76,Urban,Software Engineer,38945,1 +1806,Female,24,Masters,16,52,27,43,42,2.0,0,84,Urban,Manager,72297,0 +1807,Female,53,Bachelors,9,40,46,92,78,2.0,1,81,Rural,ML Engineer,136897,1 +1808,Male,57,Bachelors,18,37,73,45,26,5.0,4,14,Rural,Manager,104998,0 +1809,Male,54,High School,19,51,87,8,78,5.0,0,91,Urban,ML Engineer,63739,1 +1810,Male,46,Masters,19,92,13,50,8,9.0,1,81,Urban,Manager,145564,1 +1811,Female,32,Diploma,12,70,23,65,50,9.0,5,97,Urban,Manager,85637,1 +1812,Female,30,Masters,15,70,13,39,33,9.0,1,84,Rural,HR Executive,113286,0 +1813,Male,47,High School,19,76,55,4,77,8.0,5,87,Semi-Urban,HR Executive,42078,0 +1814,Male,57,Diploma,8,20,71,46,76,7.0,7,39,Urban,ML Engineer,60121,0 +1815,Male,21,High School,14,56,21,56,97,1.0,7,82,Urban,Manager,49634,0 +1816,Other,40,Masters,8,44,2,29,81,0.0,0,30,Semi-Urban,Manager,112484,0 +1817,Male,38,Masters,12,18,79,36,97,6.0,1,43,Urban,HR Executive,146024,0 +1818,Female,26,Bachelors,18,18,69,48,80,5.0,4,41,Urban,HR Executive,113801,0 +1819,Female,27,High School,8,25,39,20,39,8.0,7,30,Urban,Software Engineer,72698,0 +1820,Male,26,High School,5,15,52,61,56,6.0,3,53,Urban,Software Engineer,143279,0 +1821,Male,49,Bachelors,16,59,72,25,11,7.0,7,24,Urban,Software Engineer,106470,0 +1822,Male,25,Bachelors,19,64,95,77,67,9.0,2,20,Rural,ML Engineer,147012,1 +1823,Female,23,Bachelors,11,60,28,30,47,4.0,0,97,Semi-Urban,Data Analyst,70990,0 +1824,Female,40,Bachelors,7,53,26,99,79,3.0,7,94,Semi-Urban,Manager,107764,1 +1825,Female,25,Bachelors,7,78,68,96,81,7.0,7,77,Urban,Manager,43028,1 +1826,Male,28,Masters,13,10,37,61,64,7.0,2,75,Semi-Urban,Data Analyst,108137,0 +1827,Male,21,Bachelors,2,14,37,15,77,3.0,2,60,Urban,ML Engineer,120677,0 +1828,Other,58,Masters,11,63,77,8,73,8.0,5,44,Urban,HR Executive,114598,0 +1829,Female,55,High School,11,32,94,21,23,5.0,6,75,Semi-Urban,ML Engineer,63540,0 +1830,Male,24,Masters,12,3,9,1,89,9.0,1,35,Rural,Manager,131464,0 +1831,Other,25,Bachelors,11,97,14,70,85,8.0,1,98,Semi-Urban,HR Executive,33111,1 +1832,Female,29,Masters,3,97,74,23,31,5.0,3,36,Urban,HR Executive,50039,0 +1833,Male,28,Bachelors,18,88,38,16,54,3.0,0,24,Urban,Data Analyst,135164,0 +1834,Female,56,Bachelors,4,91,83,6,26,5.0,7,91,Urban,HR Executive,57984,1 +1835,Female,44,Bachelors,17,48,50,53,70,2.0,5,55,Semi-Urban,HR Executive,31275,0 +1836,Female,43,Bachelors,7,38,99,36,89,0.0,4,18,Rural,ML Engineer,134622,0 +1837,Male,30,Bachelors,5,0,43,84,36,8.0,1,95,Semi-Urban,Data Analyst,62232,0 +1838,Male,38,Bachelors,7,40,79,0,99,2.0,1,63,Urban,ML Engineer,140936,0 +1839,Female,31,Bachelors,10,48,10,40,77,8.0,1,82,Urban,Manager,54684,0 +1840,Male,41,Bachelors,9,69,74,63,7,1.0,4,79,Urban,Data Analyst,134021,1 +1841,Male,31,Bachelors,17,46,67,14,72,3.0,3,69,Rural,Software Engineer,143505,0 +1842,Male,50,Bachelors,18,87,79,60,20,9.0,6,53,Urban,Software Engineer,139297,1 +1843,Male,50,Diploma,1,15,43,88,40,3.0,1,24,Urban,Data Analyst,24275,0 +1844,Female,57,Diploma,19,25,22,85,43,3.0,7,1,Semi-Urban,Data Analyst,54849,0 +1845,Female,40,High School,6,26,24,26,51,7.0,4,81,Urban,HR Executive,41976,0 +1846,Male,39,Bachelors,10,92,85,80,79,7.0,4,60,Semi-Urban,HR Executive,85035,1 +1847,Male,28,PhD,1,30,64,54,12,3.0,7,52,Urban,Data Analyst,33663,0 +1848,Male,57,PhD,10,77,76,3,9,1.0,5,47,Urban,ML Engineer,115536,0 +1849,Female,29,Masters,7,84,75,64,99,0.0,1,90,Rural,Manager,53510,1 +1850,Female,45,High School,11,37,74,95,24,5.0,7,87,Rural,ML Engineer,149715,1 +1851,Male,24,Bachelors,18,96,13,70,69,5.0,5,27,Semi-Urban,Data Analyst,122674,0 +1852,Female,43,High School,17,44,91,87,60,2.0,5,91,Semi-Urban,Manager,25781,1 +1853,Female,45,Diploma,1,24,49,78,15,5.0,3,95,Semi-Urban,Manager,60018,1 +1854,Female,34,High School,8,56,77,28,57,3.0,3,52,Urban,HR Executive,90511,0 +1855,Female,35,Bachelors,11,86,47,31,23,1.0,3,94,Semi-Urban,Manager,39637,1 +1856,Male,59,Diploma,16,39,94,14,48,4.0,1,40,Semi-Urban,Data Analyst,108897,0 +1857,Female,41,Bachelors,3,18,63,18,52,3.0,3,19,Urban,Software Engineer,36327,0 +1858,Male,50,PhD,2,31,84,94,16,5.0,1,89,Urban,Software Engineer,42030,1 +1859,Female,46,Bachelors,9,27,4,14,95,3.0,3,20,Semi-Urban,HR Executive,132138,0 +1860,Female,43,Bachelors,13,99,19,56,46,4.0,4,27,Urban,ML Engineer,71743,0 +1861,Female,56,Masters,2,57,18,50,40,3.0,5,70,Rural,HR Executive,55566,0 +1862,Female,48,Bachelors,18,70,95,20,19,2.0,0,0,Rural,Data Analyst,38148,0 +1863,Male,58,PhD,18,69,54,40,41,3.0,2,10,Semi-Urban,HR Executive,36020,0 +1864,Male,44,Diploma,7,48,46,69,55,9.0,0,54,Urban,ML Engineer,88968,0 +1865,Other,32,High School,6,18,99,86,52,1.0,3,91,Urban,ML Engineer,50292,1 +1866,Female,55,Bachelors,4,23,88,85,55,0.0,4,74,Urban,Data Analyst,51342,1 +1867,Male,31,Bachelors,7,57,94,25,72,8.0,1,3,Urban,HR Executive,146620,0 +1868,Male,25,PhD,11,92,52,1,54,3.0,4,61,Semi-Urban,HR Executive,119607,0 +1869,Male,22,Masters,7,41,32,39,53,1.0,2,66,Semi-Urban,ML Engineer,56184,0 +1870,Female,54,Bachelors,18,99,55,78,86,7.0,0,15,Urban,Software Engineer,106146,1 +1871,Female,41,Bachelors,0,64,86,61,31,9.0,2,28,Urban,Manager,126086,0 +1872,Male,33,High School,5,65,78,9,28,5.0,4,92,Semi-Urban,Software Engineer,142947,1 +1873,Male,39,Bachelors,10,0,40,30,12,4.0,3,81,Urban,ML Engineer,139736,0 +1874,Female,53,Bachelors,15,29,41,40,19,4.0,0,71,Urban,ML Engineer,145212,0 +1875,Female,26,PhD,10,90,22,91,75,4.0,4,22,Semi-Urban,ML Engineer,76061,0 +1876,Male,56,Masters,2,54,13,47,21,5.0,6,38,Semi-Urban,ML Engineer,75680,0 +1877,Male,43,Diploma,14,14,64,13,17,1.0,4,69,Semi-Urban,Data Analyst,133724,0 +1878,Male,43,Diploma,7,62,88,84,43,2.0,6,97,Semi-Urban,Data Analyst,123373,1 +1879,Male,24,Diploma,15,12,99,35,30,5.0,0,91,Rural,ML Engineer,119836,1 +1880,Male,22,High School,9,34,14,4,88,1.0,3,31,Semi-Urban,HR Executive,95734,0 +1881,Female,46,Diploma,6,16,37,61,92,6.0,5,36,Urban,HR Executive,52591,0 +1882,Female,49,Bachelors,6,61,78,33,68,4.0,4,5,Rural,ML Engineer,139717,0 +1883,Female,45,Bachelors,16,58,52,62,12,2.0,2,82,Urban,HR Executive,130302,1 +1884,Female,26,Bachelors,17,66,10,25,75,1.0,5,56,Urban,ML Engineer,23897,0 +1885,Male,22,Bachelors,11,11,12,41,19,3.0,6,77,Rural,HR Executive,108299,0 +1886,Male,55,Bachelors,4,99,11,23,69,8.0,5,7,Rural,Data Analyst,123294,0 +1887,Male,32,High School,18,5,8,22,10,4.0,0,96,Semi-Urban,Manager,118743,0 +1888,Male,47,Masters,13,23,15,40,25,6.0,5,25,Urban,HR Executive,39106,0 +1889,Female,40,Masters,0,22,46,34,30,8.0,7,4,Semi-Urban,Software Engineer,82565,0 +1890,Other,59,Diploma,13,94,24,93,76,1.0,1,4,Semi-Urban,HR Executive,111505,0 +1891,Male,44,Masters,13,0,9,93,76,9.0,3,74,Urban,ML Engineer,64143,0 +1892,Male,27,Bachelors,15,48,13,14,8,0.0,2,47,Urban,Data Analyst,62292,0 +1893,Female,46,Bachelors,12,41,90,52,72,9.0,3,78,Semi-Urban,Manager,79979,1 +1894,Male,32,Bachelors,3,20,91,13,34,4.0,3,34,Urban,Data Analyst,116575,0 +1895,Male,44,Bachelors,8,10,35,70,83,1.0,5,35,Semi-Urban,HR Executive,148375,0 +1896,Female,53,Diploma,0,22,1,13,62,1.0,1,27,Urban,Manager,140629,0 +1897,Female,30,Diploma,16,88,11,63,12,3.0,6,12,Rural,Data Analyst,113284,0 +1898,Male,52,Bachelors,5,87,26,69,23,5.0,5,20,Urban,Data Analyst,132787,0 +1899,Male,44,Masters,9,26,24,30,54,5.0,7,79,Rural,HR Executive,107518,0 +1900,Female,45,Bachelors,11,32,17,85,62,9.0,4,57,Urban,Manager,48035,0 +1901,Male,41,Diploma,0,63,66,60,96,9.0,5,24,Rural,ML Engineer,112639,0 +1902,Male,41,Diploma,10,12,80,91,34,8.0,7,75,Urban,HR Executive,145882,1 +1903,Female,42,Bachelors,5,46,99,97,96,0.0,2,56,Urban,HR Executive,148956,1 +1904,Male,22,Bachelors,6,47,10,20,58,5.0,5,77,Urban,Data Analyst,112859,0 +1905,Female,57,Bachelors,10,55,72,88,35,8.0,3,52,Semi-Urban,HR Executive,53876,1 +1906,Male,48,Bachelors,8,52,28,44,34,4.0,5,25,Semi-Urban,HR Executive,122647,0 +1907,Other,56,Bachelors,5,69,40,39,59,8.0,5,78,Urban,Manager,94845,0 +1908,Male,21,Diploma,3,13,46,50,64,1.0,3,81,Semi-Urban,ML Engineer,30402,0 +1909,Male,46,Bachelors,18,30,91,42,77,4.0,7,45,Rural,Data Analyst,94447,0 +1910,Male,27,Bachelors,1,54,77,1,77,1.0,7,50,Urban,Manager,99923,0 +1911,Male,25,Bachelors,6,29,6,10,66,9.0,4,55,Urban,Manager,29123,0 +1912,Female,46,High School,0,84,10,50,57,2.0,2,99,Semi-Urban,Manager,87658,1 +1913,Other,33,Bachelors,7,23,33,17,3,5.0,0,66,Urban,Software Engineer,56959,0 +1914,Male,47,Masters,4,48,13,66,39,3.0,0,11,Semi-Urban,Manager,128396,0 +1915,Male,37,Bachelors,12,8,25,35,87,2.0,0,15,Urban,HR Executive,129987,0 +1916,Female,30,High School,10,77,0,37,44,6.0,5,45,Urban,Data Analyst,31938,0 +1917,Female,33,Masters,1,15,98,16,62,4.0,7,51,Urban,HR Executive,122323,0 +1918,Male,43,Masters,2,78,68,1,4,8.0,0,79,Semi-Urban,Manager,93524,0 +1919,Male,42,Masters,5,14,5,49,55,7.0,1,1,Semi-Urban,ML Engineer,110420,0 +1920,Male,54,Diploma,2,24,70,71,18,9.0,0,56,Urban,Manager,25292,0 +1921,Female,29,Bachelors,12,10,12,81,45,9.0,2,53,Rural,HR Executive,135363,0 +1922,Male,30,Diploma,17,73,60,27,13,9.0,0,2,Semi-Urban,Data Analyst,88344,0 +1923,Female,38,Bachelors,18,15,36,43,12,6.0,5,96,Rural,HR Executive,110749,0 +1924,Male,55,Bachelors,3,77,41,64,33,2.0,7,77,Semi-Urban,ML Engineer,125157,1 +1925,Female,56,Bachelors,6,46,68,59,73,9.0,5,70,Semi-Urban,ML Engineer,26420,1 +1926,Male,31,Diploma,5,83,8,97,66,6.0,2,28,Urban,HR Executive,38202,0 +1927,Male,25,Masters,13,62,79,2,82,6.0,5,21,Urban,HR Executive,52823,0 +1928,Male,30,Bachelors,0,65,42,84,68,6.0,2,70,Urban,HR Executive,142910,1 +1929,Female,34,Bachelors,3,86,20,75,7,9.0,0,3,Semi-Urban,Software Engineer,53354,0 +1930,Male,37,Bachelors,17,49,88,83,36,5.0,6,60,Urban,ML Engineer,23962,1 +1931,Male,57,Bachelors,12,94,72,71,33,1.0,5,35,Urban,Manager,133506,1 +1932,Male,42,Diploma,12,76,61,69,35,3.0,7,17,Semi-Urban,Manager,56343,0 +1933,Male,22,Masters,0,75,77,0,91,9.0,7,9,Semi-Urban,HR Executive,125845,0 +1934,Female,41,Masters,1,75,4,63,67,4.0,6,68,Urban,Manager,81297,0 +1935,Female,41,Masters,14,46,3,55,68,4.0,2,10,Urban,Software Engineer,121948,0 +1936,Female,40,Bachelors,11,30,11,68,52,0.0,2,13,Urban,Software Engineer,101928,0 +1937,Male,40,Bachelors,10,75,60,5,98,3.0,7,12,Urban,ML Engineer,118777,0 +1938,Female,46,High School,0,29,25,39,61,4.0,1,10,Semi-Urban,Data Analyst,55213,0 +1939,Male,45,Bachelors,10,68,12,15,61,0.0,7,47,Rural,Manager,35599,0 +1940,Male,29,Bachelors,2,29,70,85,45,4.0,0,49,Urban,Data Analyst,54238,0 +1941,Male,58,Masters,13,92,11,36,61,4.0,1,52,Urban,Manager,144790,0 +1942,Male,35,Bachelors,12,33,85,5,59,6.0,1,9,Urban,Manager,106338,0 +1943,Female,33,Bachelors,12,68,52,21,71,8.0,7,94,Urban,HR Executive,93114,0 +1944,Female,53,High School,13,30,73,51,98,9.0,7,69,Urban,Data Analyst,107087,0 +1945,Female,30,Masters,6,5,54,4,48,2.0,0,95,Rural,Manager,37084,0 +1946,Male,22,High School,12,62,24,54,52,0.0,1,98,Semi-Urban,ML Engineer,62502,1 +1947,Male,30,Diploma,9,62,16,79,66,2.0,0,75,Urban,Data Analyst,26575,0 +1948,Male,46,PhD,14,2,45,46,80,6.0,6,28,Urban,ML Engineer,45754,0 +1949,Male,59,Bachelors,17,50,94,89,65,2.0,5,82,Semi-Urban,Software Engineer,31152,1 +1950,Male,32,Diploma,0,46,63,44,28,0.0,1,77,Urban,HR Executive,113472,0 +1951,Male,49,Masters,10,17,13,55,68,7.0,3,45,Urban,Software Engineer,64248,0 +1952,Male,33,Bachelors,8,66,29,66,53,1.0,1,46,Urban,Data Analyst,72243,0 +1953,Male,44,Bachelors,13,0,4,15,0,1.0,7,8,Rural,HR Executive,80922,0 +1954,Female,51,Diploma,0,80,0,81,87,6.0,6,6,Urban,Software Engineer,109516,0 +1955,Other,40,Diploma,14,94,87,13,68,0.0,4,93,Semi-Urban,HR Executive,68446,1 +1956,Female,31,Bachelors,18,28,14,37,77,6.0,1,50,Rural,Data Analyst,63303,0 +1957,Female,49,Diploma,16,92,42,41,80,4.0,2,32,Semi-Urban,Manager,20989,0 +1958,Male,36,Bachelors,9,11,20,8,28,0.0,5,97,Rural,Data Analyst,34578,0 +1959,Female,56,Diploma,10,96,14,20,41,5.0,1,5,Urban,HR Executive,65360,0 +1960,Female,42,Bachelors,13,54,5,17,13,2.0,4,67,Semi-Urban,Data Analyst,132991,0 +1961,Male,28,High School,0,50,49,6,35,7.0,0,44,Urban,Manager,146873,0 +1962,Male,40,PhD,15,67,5,31,36,4.0,5,38,Semi-Urban,Data Analyst,36200,0 +1963,Female,59,Diploma,17,56,97,42,22,1.0,0,85,Rural,ML Engineer,68256,1 +1964,Male,41,Bachelors,7,22,20,35,3,1.0,2,4,Urban,Manager,92186,0 +1965,Male,59,Bachelors,19,99,34,48,58,1.0,5,86,Urban,Manager,85301,1 +1966,Male,50,PhD,14,4,66,51,10,6.0,1,58,Semi-Urban,Manager,55931,0 +1967,Male,31,PhD,8,16,2,12,46,1.0,4,34,Urban,Manager,139411,0 +1968,Male,44,Diploma,0,52,31,27,37,5.0,3,19,Urban,ML Engineer,106590,0 +1969,Male,44,Masters,6,10,71,79,61,4.0,2,21,Rural,Manager,35952,0 +1970,Male,59,Bachelors,17,8,46,31,84,4.0,3,16,Urban,Data Analyst,84859,0 +1971,Male,40,Masters,10,34,5,19,87,5.0,6,90,Urban,Software Engineer,93098,0 +1972,Female,34,High School,12,49,15,72,14,7.0,6,67,Urban,Data Analyst,130208,0 +1973,Male,43,Masters,17,59,48,26,70,1.0,3,43,Semi-Urban,Software Engineer,59171,0 +1974,Male,49,Bachelors,3,14,62,8,12,8.0,2,23,Urban,Data Analyst,140601,0 +1975,Male,35,Bachelors,3,90,13,3,48,5.0,1,41,Urban,HR Executive,77529,0 +1976,Female,40,Bachelors,9,88,74,38,48,8.0,7,75,Semi-Urban,Software Engineer,70865,1 +1977,Male,46,Bachelors,2,97,53,68,32,5.0,2,41,Urban,HR Executive,118929,1 +1978,Male,32,Bachelors,10,17,72,55,11,2.0,5,77,Semi-Urban,Data Analyst,126460,0 +1979,Female,43,Diploma,8,55,53,23,91,3.0,1,74,Semi-Urban,Software Engineer,111901,0 +1980,Female,39,High School,6,88,11,59,18,9.0,7,25,Semi-Urban,HR Executive,103719,0 +1981,Male,53,Bachelors,16,80,26,69,11,4.0,5,44,Urban,HR Executive,63011,0 +1982,Female,45,Diploma,14,82,63,96,90,3.0,0,4,Urban,Manager,140804,1 +1983,Male,37,Bachelors,10,58,44,57,2,8.0,1,92,Rural,HR Executive,34132,1 +1984,Male,52,Diploma,19,31,37,51,52,3.0,5,51,Urban,Data Analyst,45484,0 +1985,Male,42,High School,13,62,75,98,29,7.0,4,53,Urban,HR Executive,135319,1 +1986,Male,54,Masters,14,4,43,89,12,6.0,3,63,Rural,Manager,109908,0 +1987,Female,58,Masters,14,19,94,84,81,2.0,2,24,Urban,Software Engineer,65527,0 +1988,Male,32,High School,4,77,18,31,32,1.0,6,63,Urban,Software Engineer,83457,0 +1989,Male,21,Bachelors,3,84,6,19,23,4.0,5,90,Urban,Software Engineer,83110,0 +1990,Female,35,High School,2,98,29,4,47,3.0,4,48,Semi-Urban,Data Analyst,138409,0 +1991,Female,38,Masters,2,87,36,4,19,9.0,3,79,Urban,Data Analyst,63749,0 +1992,Male,57,Diploma,3,78,42,87,31,7.0,1,32,Urban,HR Executive,63452,1 +1993,Female,21,Diploma,8,10,90,86,69,2.0,7,36,Semi-Urban,Data Analyst,53478,0 +1994,Male,22,Bachelors,14,85,35,22,45,3.0,7,53,Urban,Manager,84774,0 +1995,Female,56,High School,1,83,74,42,61,5.0,7,96,Urban,HR Executive,63325,1 +1996,Female,36,Diploma,7,1,83,2,71,7.0,5,62,Rural,ML Engineer,23188,0 +1997,Other,45,High School,6,96,41,92,43,1.0,0,0,Urban,Software Engineer,44413,0 +1998,Male,40,Bachelors,18,84,22,40,91,0.0,6,77,Urban,Data Analyst,69778,0 +1999,Male,38,Diploma,8,4,38,81,72,2.0,2,34,Urban,ML Engineer,52883,0 +2000,Male,53,Bachelors,9,18,70,12,56,1.0,4,45,Rural,ML Engineer,72412,0 +2001,Male,46,Bachelors,5,9,43,6,71,1.0,6,14,Urban,Data Analyst,34189,0 +2002,Male,35,Bachelors,19,22,59,58,26,0.0,2,51,Rural,HR Executive,30633,0 +2003,Female,59,Bachelors,3,22,26,56,65,3.0,7,19,Urban,ML Engineer,50727,0 +2004,Male,47,Bachelors,15,27,85,63,35,8.0,2,84,Urban,Manager,60319,1 +2005,Male,21,Bachelors,3,37,81,26,56,8.0,1,59,Semi-Urban,ML Engineer,44261,0 +2006,Female,43,High School,9,54,98,66,25,4.0,6,27,Semi-Urban,Manager,94630,1 +2007,Male,46,Bachelors,19,72,47,13,9,3.0,3,29,Semi-Urban,Data Analyst,42707,0 +2008,Female,56,Diploma,2,8,72,17,31,0.0,3,22,Urban,Data Analyst,59337,0 +2009,Male,22,PhD,2,3,88,39,49,0.0,6,55,Rural,Data Analyst,78848,0 +2010,Male,42,Bachelors,0,19,91,90,84,3.0,0,34,Urban,HR Executive,30447,0 +2011,Male,42,High School,18,2,77,43,89,5.0,4,97,Semi-Urban,ML Engineer,147594,0 +2012,Male,58,Bachelors,16,22,24,9,17,4.0,7,8,Urban,HR Executive,65109,0 +2013,Female,44,Diploma,17,68,94,18,25,4.0,6,95,Rural,Data Analyst,82083,1 +2014,Male,47,Masters,8,74,17,77,85,0.0,0,53,Semi-Urban,HR Executive,91446,0 +2015,Male,28,Masters,6,41,27,17,97,6.0,3,59,Urban,Manager,35986,0 +2016,Male,33,Masters,16,44,79,16,61,3.0,1,30,Urban,ML Engineer,25084,0 +2017,Male,57,Bachelors,11,59,11,77,59,7.0,3,7,Urban,ML Engineer,29298,0 +2018,Female,33,Masters,5,48,34,46,74,5.0,3,82,Urban,Data Analyst,78715,0 +2019,Male,29,Masters,15,87,83,39,30,3.0,7,98,Urban,Manager,136709,1 +2020,Female,56,Diploma,14,63,63,59,11,4.0,4,45,Semi-Urban,Software Engineer,36795,0 +2021,Other,49,High School,14,91,12,61,66,3.0,5,87,Urban,Data Analyst,92936,1 +2022,Male,42,High School,10,65,79,36,71,4.0,7,6,Urban,ML Engineer,68158,0 +2023,Female,30,Bachelors,16,27,23,57,36,5.0,4,42,Urban,Manager,43476,0 +2024,Male,58,Bachelors,2,0,59,51,31,5.0,1,78,Urban,Manager,80053,0 +2025,Male,59,Bachelors,16,94,58,8,67,5.0,5,86,Rural,HR Executive,31470,1 +2026,Male,33,Bachelors,10,38,90,1,34,9.0,4,53,Urban,Data Analyst,54426,0 +2027,Female,56,Bachelors,17,17,57,91,64,2.0,7,55,Urban,Data Analyst,90515,0 +2028,Other,53,Bachelors,12,55,38,65,15,6.0,3,65,Rural,Data Analyst,125875,0 +2029,Male,55,Diploma,18,7,97,30,49,0.0,7,41,Urban,Data Analyst,128301,0 +2030,Female,41,Bachelors,8,92,34,54,88,9.0,3,75,Urban,Manager,114060,1 +2031,Male,23,High School,15,65,64,95,48,9.0,2,1,Urban,ML Engineer,82475,0 +2032,Male,24,Diploma,18,30,31,66,88,4.0,6,84,Urban,Data Analyst,65900,0 +2033,Male,30,Diploma,2,94,35,43,32,2.0,4,89,Urban,Data Analyst,26987,1 +2034,Other,38,High School,9,44,78,2,58,8.0,6,61,Semi-Urban,ML Engineer,145036,0 +2035,Female,23,Bachelors,12,42,69,16,9,4.0,1,87,Semi-Urban,ML Engineer,133970,0 +2036,Male,22,Diploma,7,67,82,77,95,8.0,2,3,Rural,Software Engineer,91603,0 +2037,Male,45,Diploma,16,23,1,42,32,0.0,2,31,Urban,Manager,118879,0 +2038,Male,25,Bachelors,10,84,19,41,83,1.0,3,29,Urban,Data Analyst,37879,0 +2039,Male,56,PhD,14,38,39,16,71,9.0,0,11,Semi-Urban,Manager,83736,0 +2040,Male,37,Masters,15,81,80,70,35,9.0,6,87,Semi-Urban,ML Engineer,130591,1 +2041,Female,41,Bachelors,6,52,11,95,36,5.0,3,71,Urban,ML Engineer,118856,0 +2042,Male,32,Bachelors,0,89,63,9,39,0.0,0,3,Rural,ML Engineer,23652,0 +2043,Male,51,Bachelors,16,5,31,86,1,1.0,0,29,Urban,Software Engineer,84573,0 +2044,Male,31,Diploma,2,74,5,8,67,5.0,7,14,Semi-Urban,ML Engineer,141896,0 +2045,Female,38,PhD,9,86,89,5,83,5.0,1,54,Urban,Manager,40179,0 +2046,Female,30,Bachelors,8,39,4,49,27,4.0,5,70,Urban,ML Engineer,123689,0 +2047,Male,54,Bachelors,6,38,82,64,36,3.0,6,78,Urban,Data Analyst,65427,1 +2048,Female,58,Masters,5,9,58,82,67,4.0,3,24,Urban,Manager,115176,0 +2049,Male,30,Bachelors,15,45,26,97,30,4.0,1,55,Semi-Urban,Data Analyst,84450,0 +2050,Male,26,Masters,9,12,19,78,29,6.0,3,68,Semi-Urban,Software Engineer,62842,0 +2051,Male,37,Masters,8,32,53,18,38,7.0,1,65,Semi-Urban,Manager,98984,0 +2052,Male,27,Masters,10,96,20,13,22,9.0,7,75,Semi-Urban,Software Engineer,138922,0 +2053,Male,33,Bachelors,2,68,84,46,84,7.0,1,44,Urban,Software Engineer,51782,1 +2054,Female,47,Diploma,4,97,47,4,41,7.0,5,88,Urban,Software Engineer,143553,0 +2055,Female,23,Masters,2,8,43,59,40,7.0,2,90,Rural,HR Executive,53115,0 +2056,Female,25,Diploma,7,79,4,91,0,3.0,2,41,Urban,Data Analyst,127703,0 +2057,Male,28,Bachelors,4,64,58,17,20,9.0,1,0,Rural,Manager,67458,0 +2058,Male,48,Diploma,2,26,10,82,7,4.0,7,42,Urban,Software Engineer,84305,0 +2059,Female,31,Masters,0,21,23,9,59,1.0,0,35,Semi-Urban,ML Engineer,114513,0 +2060,Male,23,PhD,10,24,36,60,60,5.0,5,96,Urban,Manager,60682,0 +2061,Male,44,PhD,7,2,35,45,99,1.0,0,85,Urban,Data Analyst,130838,0 +2062,Male,29,Bachelors,8,20,79,45,95,9.0,1,25,Urban,Data Analyst,99132,0 +2063,Female,35,Diploma,5,61,7,15,73,3.0,1,56,Urban,HR Executive,101549,0 +2064,Male,49,High School,10,70,10,24,72,6.0,5,12,Urban,ML Engineer,70460,0 +2065,Male,40,Masters,9,44,62,54,5,3.0,4,61,Semi-Urban,HR Executive,44346,0 +2066,Female,54,High School,18,32,18,50,72,8.0,0,20,Rural,Data Analyst,114314,0 +2067,Male,32,Diploma,17,14,78,19,18,2.0,0,17,Semi-Urban,Software Engineer,95558,0 +2068,Male,47,Diploma,15,83,97,92,78,9.0,1,43,Urban,Manager,140050,1 +2069,Male,44,Bachelors,2,45,23,96,0,9.0,3,91,Urban,Data Analyst,74800,1 +2070,Male,34,Bachelors,16,10,73,65,45,7.0,4,32,Urban,Manager,147216,0 +2071,Female,56,Diploma,14,92,13,30,62,2.0,0,2,Urban,Software Engineer,118021,0 +2072,Male,21,High School,16,57,69,97,92,4.0,6,54,Urban,Manager,25096,1 +2073,Male,27,Bachelors,6,29,68,52,66,6.0,2,86,Urban,HR Executive,30789,1 +2074,Female,28,Bachelors,1,76,90,62,77,2.0,7,33,Urban,ML Engineer,124681,1 +2075,Female,49,Diploma,0,67,78,65,20,7.0,2,69,Urban,ML Engineer,144110,1 +2076,Female,42,Bachelors,1,90,36,0,72,8.0,5,11,Semi-Urban,Software Engineer,107861,0 +2077,Male,32,Bachelors,17,39,43,71,0,4.0,1,62,Rural,HR Executive,29453,0 +2078,Male,47,Bachelors,3,5,1,48,13,8.0,5,4,Rural,HR Executive,149414,0 +2079,Other,49,Diploma,18,52,3,17,28,1.0,6,55,Semi-Urban,Software Engineer,109789,0 +2080,Female,27,High School,2,2,14,18,67,7.0,1,22,Urban,Manager,115376,0 +2081,Male,46,Bachelors,13,63,17,84,18,3.0,6,99,Urban,Software Engineer,144152,1 +2082,Male,50,High School,17,26,11,33,46,8.0,5,46,Urban,ML Engineer,35637,0 +2083,Male,38,High School,18,35,22,78,60,3.0,5,19,Urban,Manager,118923,0 +2084,Female,31,Diploma,2,76,54,38,15,1.0,3,37,Semi-Urban,Manager,36862,0 +2085,Male,58,PhD,5,75,79,74,0,8.0,6,44,Urban,HR Executive,82610,1 +2086,Male,30,Diploma,14,76,27,85,26,6.0,0,69,Urban,Software Engineer,43602,1 +2087,Male,47,Bachelors,14,69,20,72,71,3.0,3,15,Semi-Urban,Software Engineer,48113,0 +2088,Female,52,Masters,0,71,66,29,53,8.0,6,25,Rural,Manager,117833,0 +2089,Female,42,Masters,13,64,45,55,80,4.0,5,78,Rural,ML Engineer,91657,1 +2090,Male,33,Bachelors,16,48,67,83,54,4.0,5,97,Urban,HR Executive,86029,1 +2091,Female,58,Diploma,19,36,97,62,4,0.0,4,13,Semi-Urban,Data Analyst,67345,0 +2092,Other,34,Bachelors,0,47,8,92,47,1.0,2,0,Urban,Software Engineer,78346,0 +2093,Male,32,Masters,19,69,90,68,77,4.0,2,49,Rural,ML Engineer,26185,1 +2094,Male,47,Bachelors,3,90,60,4,11,3.0,7,61,Semi-Urban,HR Executive,63455,0 +2095,Male,43,PhD,12,46,54,21,39,4.0,1,63,Semi-Urban,ML Engineer,43189,0 +2096,Female,22,PhD,12,35,64,78,33,3.0,3,58,Rural,ML Engineer,124108,0 +2097,Male,59,Diploma,2,34,14,86,5,6.0,0,80,Urban,Data Analyst,73492,0 +2098,Female,36,Bachelors,12,43,81,45,24,0.0,6,96,Semi-Urban,ML Engineer,60448,1 +2099,Female,43,Masters,19,79,83,17,24,1.0,4,36,Urban,Data Analyst,35141,0 +2100,Male,47,Bachelors,2,29,69,78,85,3.0,4,21,Semi-Urban,ML Engineer,89231,0 +2101,Female,27,High School,17,17,70,5,80,8.0,2,86,Semi-Urban,Data Analyst,47504,0 +2102,Male,36,Bachelors,18,31,11,46,22,7.0,5,66,Urban,HR Executive,45023,0 +2103,Male,59,Bachelors,4,42,73,48,89,8.0,5,72,Semi-Urban,Software Engineer,121068,1 +2104,Female,31,High School,3,59,90,46,44,8.0,4,2,Urban,Data Analyst,142423,0 +2105,Female,34,Bachelors,7,71,46,96,75,9.0,5,90,Rural,HR Executive,39716,1 +2106,Male,27,Diploma,18,37,5,27,75,4.0,0,59,Rural,ML Engineer,138109,0 +2107,Female,45,Bachelors,5,53,42,71,33,7.0,5,51,Urban,Manager,119175,0 +2108,Female,31,Masters,6,96,14,89,81,8.0,6,37,Rural,HR Executive,63779,0 +2109,Male,53,Diploma,3,3,28,66,77,8.0,2,5,Semi-Urban,Manager,104082,0 +2110,Other,52,Diploma,5,5,92,74,18,0.0,7,50,Rural,Manager,78727,0 +2111,Male,40,Bachelors,7,12,41,96,11,7.0,7,21,Urban,HR Executive,98683,0 +2112,Male,24,Masters,17,9,66,87,77,6.0,3,79,Rural,Software Engineer,60856,1 +2113,Male,57,Bachelors,0,77,42,98,3,6.0,1,65,Urban,Data Analyst,94962,1 +2114,Female,53,Masters,11,41,86,7,91,6.0,3,71,Urban,Manager,136054,0 +2115,Female,42,High School,13,38,78,62,40,7.0,1,83,Rural,Manager,123581,1 +2116,Male,56,High School,6,43,99,25,78,4.0,7,23,Rural,HR Executive,26812,0 +2117,Male,21,Masters,5,14,82,45,71,9.0,6,12,Urban,ML Engineer,29106,0 +2118,Female,27,Bachelors,10,9,70,74,31,9.0,3,90,Urban,HR Executive,130536,1 +2119,Male,28,Bachelors,9,7,1,46,32,0.0,2,84,Urban,HR Executive,35532,0 +2120,Female,28,PhD,18,96,71,20,41,3.0,3,19,Semi-Urban,HR Executive,66020,0 +2121,Female,46,Masters,6,80,40,45,88,8.0,2,20,Urban,Data Analyst,65247,0 +2122,Male,44,High School,14,50,75,32,83,0.0,1,60,Urban,HR Executive,72604,0 +2123,Other,47,High School,17,90,17,65,14,6.0,4,39,Rural,Software Engineer,81530,0 +2124,Male,40,High School,13,34,54,78,68,0.0,7,12,Semi-Urban,HR Executive,95574,0 +2125,Other,23,Bachelors,18,8,60,86,6,7.0,3,14,Semi-Urban,Software Engineer,73179,0 +2126,Female,27,Bachelors,14,49,61,68,65,1.0,7,15,Urban,Data Analyst,21874,0 +2127,Female,31,Bachelors,11,79,67,41,88,6.0,3,36,Urban,Data Analyst,115618,0 +2128,Male,51,Masters,6,93,67,87,97,0.0,5,47,Semi-Urban,Manager,33794,1 +2129,Female,59,Bachelors,2,59,72,96,43,2.0,5,52,Urban,ML Engineer,68974,1 +2130,Male,58,Diploma,0,63,60,88,64,0.0,4,62,Semi-Urban,ML Engineer,28611,1 +2131,Male,38,Bachelors,9,99,58,48,5,5.0,6,98,Semi-Urban,Manager,135994,1 +2132,Male,39,Masters,5,57,16,47,58,7.0,0,21,Urban,Software Engineer,63538,0 +2133,Male,43,Diploma,7,87,45,92,10,5.0,4,28,Semi-Urban,Manager,99535,1 +2134,Male,46,Diploma,4,40,98,47,93,6.0,7,8,Rural,Manager,28461,0 +2135,Female,28,Bachelors,1,92,59,53,84,2.0,5,10,Semi-Urban,Manager,32853,0 +2136,Female,35,PhD,10,61,7,6,55,0.0,0,74,Rural,HR Executive,81578,0 +2137,Male,48,Bachelors,0,31,48,55,18,8.0,7,42,Urban,Manager,54751,0 +2138,Female,33,Diploma,15,76,64,66,41,2.0,2,87,Rural,HR Executive,43253,1 +2139,Male,23,Masters,9,55,34,48,99,1.0,3,50,Urban,Data Analyst,41033,0 +2140,Female,43,Masters,10,97,56,14,89,5.0,7,52,Semi-Urban,ML Engineer,67557,0 +2141,Female,32,Bachelors,17,7,50,60,2,3.0,7,15,Urban,ML Engineer,101632,0 +2142,Male,42,Diploma,15,10,64,73,86,5.0,6,58,Rural,ML Engineer,137709,0 +2143,Female,55,Diploma,7,39,57,93,67,2.0,3,93,Urban,ML Engineer,71900,1 +2144,Male,23,Bachelors,11,37,41,79,20,8.0,6,5,Rural,Data Analyst,127872,0 +2145,Male,53,Diploma,6,91,94,79,81,4.0,6,24,Urban,Data Analyst,62028,1 +2146,Female,47,Masters,14,89,29,71,93,4.0,0,81,Urban,Software Engineer,103744,1 +2147,Male,46,Masters,8,98,58,60,11,2.0,4,18,Urban,Manager,49028,0 +2148,Male,24,High School,17,99,54,69,87,3.0,1,66,Urban,HR Executive,22738,1 +2149,Male,30,High School,10,53,99,96,65,8.0,2,73,Rural,Software Engineer,138353,1 +2150,Female,50,Diploma,12,24,80,37,19,6.0,7,89,Rural,Software Engineer,138804,0 +2151,Male,50,Bachelors,14,71,15,19,52,9.0,7,21,Rural,HR Executive,102782,0 +2152,Male,48,High School,19,58,48,94,74,7.0,6,93,Rural,Software Engineer,137704,1 +2153,Female,35,Diploma,19,41,17,39,54,9.0,5,6,Urban,Software Engineer,101881,0 +2154,Female,57,Bachelors,16,80,19,51,30,1.0,5,46,Semi-Urban,Manager,130322,0 +2155,Male,39,Masters,10,42,56,1,47,1.0,0,40,Urban,Data Analyst,66412,0 +2156,Male,43,Masters,11,34,43,55,81,1.0,0,55,Urban,HR Executive,93324,0 +2157,Male,37,Bachelors,14,94,17,80,51,9.0,2,98,Urban,Data Analyst,32691,1 +2158,Male,24,Bachelors,8,73,36,90,68,9.0,7,6,Urban,ML Engineer,119326,0 +2159,Male,39,Masters,7,15,67,69,3,0.0,3,86,Semi-Urban,Data Analyst,107414,1 +2160,Female,21,Bachelors,9,5,18,55,62,8.0,4,13,Urban,Data Analyst,96769,0 +2161,Female,56,Bachelors,10,69,21,43,13,1.0,4,0,Urban,Manager,45975,0 +2162,Female,41,PhD,10,1,0,62,4,0.0,2,87,Urban,Data Analyst,126189,0 +2163,Male,27,Bachelors,4,34,28,23,27,2.0,5,70,Urban,HR Executive,137552,0 +2164,Female,46,High School,2,93,60,11,79,0.0,7,58,Semi-Urban,Software Engineer,126892,0 +2165,Male,40,Masters,11,23,48,71,10,9.0,5,97,Urban,Software Engineer,83001,1 +2166,Other,22,Bachelors,0,41,4,98,28,5.0,2,93,Urban,ML Engineer,89416,0 +2167,Female,45,Masters,10,37,99,12,86,8.0,7,62,Rural,Manager,82698,0 +2168,Male,26,Masters,19,97,69,51,50,3.0,5,31,Urban,Manager,65740,1 +2169,Female,50,High School,3,81,73,73,70,4.0,6,51,Rural,ML Engineer,74112,1 +2170,Male,57,Masters,13,61,66,11,95,4.0,4,3,Urban,Manager,127060,0 +2171,Female,53,Bachelors,12,98,3,43,66,5.0,1,7,Rural,Manager,125745,0 +2172,Male,57,Masters,19,25,40,11,75,7.0,1,10,Urban,Data Analyst,35224,0 +2173,Male,48,Masters,4,50,36,72,76,3.0,5,30,Rural,Data Analyst,118611,0 +2174,Female,50,Masters,5,58,0,32,45,9.0,7,39,Semi-Urban,Data Analyst,78731,0 +2175,Male,30,Bachelors,10,12,85,11,21,3.0,7,75,Rural,HR Executive,63175,0 +2176,Female,35,Bachelors,19,34,99,72,39,3.0,3,67,Semi-Urban,HR Executive,130746,1 +2177,Male,39,High School,5,13,90,19,17,1.0,7,61,Semi-Urban,ML Engineer,80454,0 +2178,Female,32,Bachelors,15,71,55,95,25,7.0,2,0,Urban,Manager,36092,0 +2179,Female,55,Bachelors,10,69,18,93,53,5.0,1,31,Semi-Urban,ML Engineer,113678,0 +2180,Male,51,Masters,17,62,63,84,29,2.0,6,42,Urban,HR Executive,77920,1 +2181,Male,32,Masters,4,60,51,28,66,5.0,7,42,Urban,Manager,21083,0 +2182,Male,32,Masters,18,0,33,98,72,2.0,4,64,Urban,HR Executive,33568,0 +2183,Male,42,Masters,5,80,93,54,94,7.0,1,22,Urban,HR Executive,140474,1 +2184,Male,46,High School,14,99,15,51,88,9.0,6,20,Urban,Software Engineer,94641,0 +2185,Female,27,Bachelors,7,95,45,17,74,0.0,2,92,Urban,Data Analyst,30726,1 +2186,Female,23,Masters,14,85,77,81,77,9.0,4,72,Urban,Software Engineer,126772,1 +2187,Female,56,High School,4,81,41,0,30,3.0,0,98,Urban,Data Analyst,120839,0 +2188,Female,52,Bachelors,15,69,83,36,3,3.0,3,34,Urban,ML Engineer,121996,0 +2189,Female,27,Diploma,16,53,97,29,37,1.0,5,53,Urban,ML Engineer,27702,0 +2190,Female,36,Bachelors,9,31,10,46,7,8.0,3,56,Urban,Manager,136154,0 +2191,Male,56,Bachelors,13,17,52,77,82,1.0,5,35,Urban,ML Engineer,77370,0 +2192,Female,43,High School,0,46,27,76,83,3.0,2,17,Urban,HR Executive,64430,0 +2193,Female,33,Masters,4,11,57,10,3,9.0,1,86,Urban,ML Engineer,67511,0 +2194,Male,28,Bachelors,9,99,34,28,31,1.0,7,59,Urban,Data Analyst,45813,0 +2195,Male,56,High School,2,78,78,93,10,7.0,3,44,Urban,ML Engineer,129984,1 +2196,Male,42,Bachelors,7,73,57,13,66,5.0,6,44,Semi-Urban,HR Executive,139852,0 +2197,Male,51,Bachelors,10,90,54,58,58,3.0,5,58,Semi-Urban,Manager,43709,1 +2198,Female,58,High School,19,97,25,70,20,1.0,3,54,Urban,Data Analyst,122187,1 +2199,Male,34,Bachelors,2,70,37,7,78,2.0,1,7,Urban,Manager,68895,0 +2200,Male,25,High School,12,48,11,81,33,2.0,3,55,Urban,Data Analyst,80640,0 +2201,Other,51,Bachelors,15,80,44,11,43,5.0,0,36,Semi-Urban,Software Engineer,59807,0 +2202,Male,29,Bachelors,7,24,97,2,55,9.0,6,75,Urban,ML Engineer,104922,0 +2203,Male,28,Masters,6,14,35,25,16,7.0,7,45,Urban,Data Analyst,78874,0 +2204,Male,32,Bachelors,5,75,61,51,31,2.0,6,80,Urban,ML Engineer,57967,1 +2205,Female,25,Diploma,10,87,6,25,83,2.0,6,35,Urban,Manager,62052,0 +2206,Female,52,Bachelors,3,36,92,5,34,0.0,4,47,Semi-Urban,ML Engineer,66165,0 +2207,Male,54,Masters,6,72,78,32,72,2.0,6,21,Urban,Manager,32414,0 +2208,Female,46,High School,15,9,24,53,47,0.0,6,36,Rural,Software Engineer,81807,0 +2209,Male,32,Bachelors,9,70,35,57,2,4.0,1,4,Urban,ML Engineer,106378,0 +2210,Female,53,Bachelors,8,29,34,34,21,5.0,1,38,Rural,ML Engineer,133730,0 +2211,Female,29,PhD,17,22,0,52,94,0.0,2,51,Urban,HR Executive,94265,0 +2212,Female,21,Bachelors,10,32,18,15,26,4.0,2,49,Semi-Urban,Manager,127805,0 +2213,Male,35,Bachelors,1,50,58,43,4,7.0,6,85,Semi-Urban,Data Analyst,100529,1 +2214,Other,54,Diploma,8,64,11,25,61,3.0,3,82,Urban,HR Executive,149590,0 +2215,Female,55,Masters,13,42,66,39,79,1.0,0,26,Semi-Urban,ML Engineer,111540,0 +2216,Male,47,Bachelors,11,18,73,21,98,0.0,6,84,Rural,ML Engineer,24392,0 +2217,Female,28,Bachelors,5,93,17,7,23,8.0,7,95,Rural,Data Analyst,126162,0 +2218,Male,26,PhD,2,28,28,60,17,5.0,4,44,Urban,ML Engineer,25012,0 +2219,Female,42,Masters,17,27,2,22,93,7.0,0,19,Urban,HR Executive,43604,0 +2220,Male,56,Bachelors,4,5,82,66,51,7.0,0,37,Urban,Manager,55310,0 +2221,Female,33,High School,19,93,33,55,58,5.0,2,97,Urban,Manager,36757,1 +2222,Male,31,Bachelors,3,14,81,20,28,2.0,3,75,Semi-Urban,ML Engineer,110102,0 +2223,Male,33,Diploma,19,28,98,42,33,9.0,5,5,Rural,Software Engineer,132257,0 +2224,Male,27,Bachelors,3,97,87,99,40,9.0,3,74,Semi-Urban,Manager,96292,1 +2225,Male,51,Bachelors,16,34,69,61,70,6.0,0,15,Urban,Manager,73780,0 +2226,Male,24,High School,8,82,64,67,36,4.0,5,63,Urban,Software Engineer,41650,1 +2227,Male,56,Diploma,0,42,26,66,60,6.0,3,81,Semi-Urban,Software Engineer,85554,0 +2228,Male,27,Masters,17,70,48,38,65,9.0,3,82,Urban,HR Executive,75329,1 +2229,Male,58,PhD,2,97,88,40,63,9.0,0,47,Urban,Manager,101403,1 +2230,Male,53,Bachelors,12,85,11,51,24,2.0,1,46,Semi-Urban,Software Engineer,50569,0 +2231,Female,31,High School,1,74,93,23,79,2.0,7,87,Semi-Urban,HR Executive,83702,1 +2232,Male,48,Diploma,18,86,26,84,41,5.0,0,0,Urban,HR Executive,144230,0 +2233,Female,36,Diploma,9,58,14,4,4,4.0,7,35,Urban,ML Engineer,122921,0 +2234,Female,44,Bachelors,3,81,53,89,3,5.0,6,88,Urban,Manager,109736,1 +2235,Female,45,Bachelors,18,78,9,20,71,4.0,3,34,Urban,Manager,132328,0 +2236,Male,46,Diploma,10,25,80,48,37,0.0,1,34,Urban,HR Executive,43629,0 +2237,Female,42,Bachelors,12,23,20,68,47,3.0,5,95,Urban,Software Engineer,87079,0 +2238,Male,36,Bachelors,4,85,76,53,53,4.0,1,79,Urban,Manager,108912,1 +2239,Male,39,Bachelors,18,4,14,52,64,8.0,7,37,Semi-Urban,Software Engineer,28675,0 +2240,Male,31,Bachelors,1,76,33,63,79,7.0,5,82,Semi-Urban,HR Executive,116491,1 +2241,Female,21,High School,5,81,75,84,43,6.0,3,99,Urban,ML Engineer,42612,1 +2242,Male,51,Bachelors,1,4,23,7,47,8.0,0,30,Urban,Software Engineer,37822,0 +2243,Male,55,Bachelors,19,39,11,41,94,2.0,0,10,Urban,Software Engineer,130687,0 +2244,Other,34,Bachelors,2,44,11,27,50,5.0,2,89,Semi-Urban,ML Engineer,144010,0 +2245,Female,30,Masters,2,28,24,0,87,4.0,4,97,Semi-Urban,Software Engineer,20713,0 +2246,Male,23,Masters,15,38,25,24,22,5.0,4,5,Urban,Software Engineer,76378,0 +2247,Male,48,Bachelors,18,45,39,12,13,8.0,7,89,Rural,ML Engineer,101744,0 +2248,Female,30,Bachelors,13,99,20,24,73,4.0,2,3,Urban,ML Engineer,96790,0 +2249,Male,46,Diploma,9,75,90,32,20,9.0,5,68,Urban,ML Engineer,91976,1 +2250,Male,42,High School,6,18,62,36,69,8.0,7,3,Urban,HR Executive,127712,0 +2251,Male,51,High School,13,69,81,42,43,9.0,0,42,Urban,HR Executive,77818,0 +2252,Female,52,Masters,8,94,95,76,7,8.0,5,87,Urban,Data Analyst,99427,1 +2253,Female,56,Diploma,19,39,36,30,2,4.0,2,82,Rural,ML Engineer,103558,0 +2254,Female,27,Masters,18,34,39,56,52,5.0,4,79,Urban,HR Executive,86835,0 +2255,Female,28,High School,18,14,86,7,71,2.0,3,28,Rural,Software Engineer,36329,0 +2256,Male,49,High School,17,75,89,84,78,0.0,1,51,Urban,Software Engineer,125057,1 +2257,Male,28,Diploma,5,60,32,19,1,4.0,3,32,Urban,HR Executive,137300,0 +2258,Male,26,Masters,9,43,75,45,7,9.0,2,56,Urban,ML Engineer,51036,0 +2259,Male,45,Bachelors,13,53,79,96,19,6.0,7,9,Rural,HR Executive,49453,1 +2260,Male,57,PhD,14,69,62,20,80,6.0,6,75,Semi-Urban,Manager,83122,0 +2261,Female,48,Bachelors,17,95,4,54,20,4.0,4,11,Urban,Data Analyst,66638,0 +2262,Female,52,Masters,6,62,56,68,71,3.0,1,89,Semi-Urban,Software Engineer,31340,1 +2263,Female,55,Bachelors,2,4,37,58,14,9.0,1,58,Rural,Software Engineer,90298,0 +2264,Male,33,Masters,14,46,80,97,86,3.0,1,40,Urban,ML Engineer,46119,1 +2265,Female,31,High School,1,89,87,72,88,5.0,2,96,Semi-Urban,Data Analyst,32244,1 +2266,Female,27,Masters,14,6,53,9,34,6.0,7,88,Urban,Data Analyst,91200,0 +2267,Male,30,Diploma,11,96,35,77,20,1.0,5,88,Urban,ML Engineer,65315,1 +2268,Female,47,Masters,1,82,90,6,50,5.0,7,29,Rural,ML Engineer,100374,0 +2269,Male,26,PhD,1,94,57,90,83,4.0,0,4,Urban,ML Engineer,62268,1 +2270,Male,27,Bachelors,10,6,69,57,57,5.0,2,83,Urban,Software Engineer,116471,0 +2271,Male,38,Bachelors,1,24,82,0,49,1.0,3,97,Semi-Urban,ML Engineer,36410,0 +2272,Male,33,High School,7,21,35,11,22,8.0,2,70,Urban,HR Executive,79648,0 +2273,Male,33,Bachelors,4,2,80,93,87,2.0,4,84,Urban,ML Engineer,46887,1 +2274,Female,34,Bachelors,12,14,61,41,54,4.0,6,26,Urban,ML Engineer,145128,0 +2275,Other,36,Bachelors,14,66,80,82,13,2.0,2,14,Urban,HR Executive,148250,1 +2276,Female,38,PhD,2,21,55,45,74,2.0,7,83,Urban,Data Analyst,138217,0 +2277,Female,50,Masters,6,75,5,67,46,2.0,4,95,Semi-Urban,HR Executive,110393,1 +2278,Male,33,High School,15,4,74,45,78,5.0,2,73,Semi-Urban,Data Analyst,41261,0 +2279,Female,58,Diploma,15,55,90,91,75,8.0,3,91,Urban,HR Executive,62220,1 +2280,Male,43,Masters,11,96,36,17,1,8.0,6,81,Urban,Software Engineer,30992,0 +2281,Male,39,High School,5,6,16,81,55,0.0,0,71,Semi-Urban,Data Analyst,78603,0 +2282,Male,28,Bachelors,2,78,78,36,31,3.0,6,72,Rural,ML Engineer,117401,1 +2283,Male,37,Diploma,7,8,66,13,73,3.0,5,8,Rural,Software Engineer,43419,0 +2284,Male,56,Diploma,6,8,80,83,43,2.0,2,31,Urban,Software Engineer,99665,0 +2285,Male,28,Diploma,5,67,71,25,55,1.0,7,52,Rural,ML Engineer,113056,0 +2286,Male,54,Masters,9,63,35,75,13,5.0,0,40,Urban,Software Engineer,96673,0 +2287,Other,50,Bachelors,4,15,86,60,19,1.0,7,58,Rural,Data Analyst,47823,0 +2288,Male,26,Bachelors,11,37,43,27,78,4.0,5,63,Urban,Data Analyst,136397,0 +2289,Male,23,Diploma,8,76,34,85,33,8.0,6,53,Urban,Software Engineer,146463,1 +2290,Male,44,High School,8,79,28,27,72,2.0,0,81,Semi-Urban,ML Engineer,49487,0 +2291,Female,48,Diploma,12,11,59,20,96,7.0,4,51,Urban,Data Analyst,38142,0 +2292,Male,44,Masters,4,94,26,0,35,5.0,2,11,Rural,ML Engineer,112984,0 +2293,Male,32,Bachelors,19,34,71,59,27,4.0,0,32,Semi-Urban,Manager,146392,0 +2294,Male,55,High School,9,64,42,62,3,1.0,2,24,Urban,Software Engineer,122320,0 +2295,Male,56,Bachelors,3,99,62,45,68,7.0,5,11,Semi-Urban,Software Engineer,51394,0 +2296,Male,39,PhD,15,5,72,25,7,5.0,0,4,Rural,Data Analyst,35800,0 +2297,Male,57,Masters,2,24,88,55,3,8.0,3,71,Rural,HR Executive,34867,1 +2298,Male,59,Bachelors,16,6,50,88,83,7.0,0,80,Urban,ML Engineer,89554,0 +2299,Male,38,Bachelors,9,68,52,15,84,1.0,3,90,Urban,HR Executive,98985,0 +2300,Male,23,PhD,10,49,17,21,50,2.0,3,18,Rural,HR Executive,34721,0 +2301,Female,29,High School,9,11,62,37,11,5.0,7,43,Urban,Software Engineer,139976,0 +2302,Male,58,Diploma,3,83,47,72,68,2.0,7,38,Semi-Urban,Software Engineer,75324,1 +2303,Male,42,Bachelors,12,41,44,82,14,7.0,7,6,Rural,Manager,135722,0 +2304,Male,41,Diploma,7,74,36,55,71,,0,0,Urban,HR Executive,74856,0 +2305,Female,35,High School,18,73,62,16,58,6.0,1,90,Urban,HR Executive,77095,1 +2306,Male,31,High School,11,35,59,54,2,9.0,7,38,Urban,Data Analyst,98485,0 +2307,Male,47,Bachelors,2,62,25,52,59,7.0,1,19,Urban,Manager,82426,0 +2308,Female,54,Bachelors,5,9,1,91,93,4.0,0,9,Urban,Data Analyst,145074,0 +2309,Male,50,High School,3,70,92,39,30,7.0,0,16,Urban,Data Analyst,90755,0 +2310,Male,56,Bachelors,19,14,94,75,53,9.0,6,58,Semi-Urban,HR Executive,78114,1 +2311,Male,26,Bachelors,10,21,9,65,77,6.0,7,32,Urban,ML Engineer,39852,0 +2312,Female,32,Bachelors,3,5,1,56,68,3.0,2,56,Semi-Urban,Manager,92181,0 +2313,Male,34,Masters,8,39,29,72,56,5.0,4,15,Urban,HR Executive,83534,0 +2314,Female,56,Bachelors,3,94,29,37,17,4.0,5,72,Semi-Urban,Data Analyst,137070,0 +2315,Other,42,Bachelors,10,59,86,5,87,0.0,1,31,Rural,Data Analyst,65087,0 +2316,Male,35,Diploma,1,79,25,79,15,7.0,0,68,Rural,Software Engineer,95988,1 +2317,Male,52,High School,19,4,67,70,14,6.0,1,11,Semi-Urban,ML Engineer,76646,0 +2318,Male,50,Diploma,14,89,23,71,3,3.0,0,41,Semi-Urban,HR Executive,21616,0 +2319,Male,43,Bachelors,10,30,50,22,59,0.0,4,47,Urban,Software Engineer,110901,0 +2320,Male,36,Diploma,15,48,20,44,17,7.0,1,49,Rural,HR Executive,120722,0 +2321,Female,59,Bachelors,15,31,23,61,59,2.0,5,91,Urban,ML Engineer,64517,0 +2322,Female,32,Bachelors,7,47,88,4,34,7.0,3,1,Rural,Manager,99670,0 +2323,Female,40,Diploma,6,97,31,97,91,8.0,3,3,Urban,Software Engineer,31167,0 +2324,Male,53,PhD,0,32,87,8,5,8.0,1,53,Urban,HR Executive,110451,0 +2325,Female,34,High School,15,55,54,29,13,8.0,4,4,Urban,Manager,65713,0 +2326,Other,51,Bachelors,13,42,76,30,99,7.0,2,43,Semi-Urban,Manager,64532,0 +2327,Female,57,High School,5,76,13,92,29,9.0,6,19,Urban,Data Analyst,85647,0 +2328,Male,50,Bachelors,18,68,88,4,68,8.0,0,54,Urban,Software Engineer,48627,0 +2329,Female,46,PhD,6,58,23,93,15,5.0,1,14,Urban,Data Analyst,90148,0 +2330,Male,57,Diploma,2,73,1,73,4,0.0,4,31,Semi-Urban,ML Engineer,134859,0 +2331,Male,38,Masters,0,10,71,89,2,7.0,5,29,Urban,Software Engineer,56046,0 +2332,Male,55,PhD,13,83,42,7,60,6.0,4,55,Rural,ML Engineer,87705,0 +2333,Female,30,PhD,17,91,29,84,91,8.0,3,53,Urban,Manager,52947,1 +2334,Female,38,Bachelors,0,73,83,70,98,3.0,0,27,Semi-Urban,Manager,68778,1 +2335,Male,21,Masters,17,7,9,69,26,7.0,1,97,Urban,Manager,99445,0 +2336,Male,23,Masters,18,32,53,93,40,2.0,4,36,Urban,Software Engineer,119644,0 +2337,Male,54,Bachelors,7,30,56,38,0,5.0,1,79,Urban,Data Analyst,121688,0 +2338,Male,26,Bachelors,8,60,68,55,22,0.0,1,22,Urban,Manager,68468,0 +2339,Male,46,Diploma,7,66,75,92,98,0.0,3,41,Semi-Urban,Data Analyst,132920,1 +2340,Male,42,Bachelors,18,47,54,94,64,6.0,7,73,Semi-Urban,ML Engineer,145375,1 +2341,Female,40,Bachelors,7,82,73,44,90,0.0,6,57,Urban,Software Engineer,35450,1 +2342,Male,49,Bachelors,8,65,51,30,60,5.0,7,49,Rural,Data Analyst,149023,0 +2343,Male,47,Diploma,6,53,90,63,40,0.0,5,27,Urban,Software Engineer,106214,0 +2344,Male,43,Bachelors,16,8,67,46,45,7.0,6,49,Semi-Urban,ML Engineer,71169,0 +2345,Female,22,Masters,2,52,45,71,43,9.0,0,23,Urban,Data Analyst,80731,0 +2346,Female,31,Diploma,18,52,73,37,82,4.0,5,81,Semi-Urban,HR Executive,44443,1 +2347,Female,37,PhD,1,3,36,84,73,9.0,1,27,Urban,Software Engineer,31320,0 +2348,Male,57,Masters,9,58,42,88,82,8.0,4,24,Urban,ML Engineer,118724,0 +2349,Male,58,Masters,13,82,2,70,24,4.0,7,3,Urban,Software Engineer,100951,0 +2350,Male,39,Bachelors,7,23,8,73,63,6.0,2,74,Urban,Manager,47592,0 +2351,Female,52,Diploma,18,69,84,67,91,4.0,0,60,Rural,ML Engineer,100016,1 +2352,Female,38,Bachelors,16,65,21,61,52,9.0,1,65,Urban,HR Executive,62821,0 +2353,Female,56,Diploma,11,39,68,43,13,5.0,4,97,Urban,Software Engineer,129558,1 +2354,Female,31,Masters,5,20,3,68,76,5.0,4,39,Urban,Software Engineer,35482,0 +2355,Female,44,Masters,10,46,98,76,69,2.0,3,99,Rural,Manager,50265,1 +2356,Male,34,Diploma,14,92,53,90,6,2.0,5,21,Urban,HR Executive,114183,1 +2357,Female,31,High School,9,56,76,80,60,9.0,7,60,Urban,HR Executive,81435,1 +2358,Male,59,Bachelors,1,79,49,19,63,4.0,0,9,Urban,Data Analyst,124581,0 +2359,Male,50,Bachelors,17,10,8,33,55,1.0,6,9,Rural,ML Engineer,48274,0 +2360,Male,22,Masters,3,12,28,95,61,0.0,0,79,Urban,Software Engineer,92306,0 +2361,Male,55,Bachelors,13,45,4,61,91,4.0,2,8,Rural,Data Analyst,69608,0 +2362,Male,49,Diploma,5,1,74,56,85,9.0,2,91,Urban,Manager,126503,0 +2363,Male,38,Masters,7,98,17,11,73,6.0,5,87,Urban,Manager,34507,0 +2364,Male,55,Bachelors,18,88,18,56,45,6.0,2,98,Urban,HR Executive,39398,1 +2365,Male,47,High School,11,83,64,76,15,4.0,3,84,Urban,Manager,110135,1 +2366,Male,25,High School,10,77,18,63,4,5.0,4,10,Semi-Urban,ML Engineer,124235,0 +2367,Male,25,Diploma,7,94,38,47,41,2.0,0,83,Rural,ML Engineer,93956,1 +2368,Male,43,Bachelors,19,66,35,12,47,7.0,1,59,Urban,Manager,130579,0 +2369,Male,42,Bachelors,14,81,45,12,58,0.0,0,9,Rural,Software Engineer,106689,0 +2370,Female,48,Masters,2,75,86,20,40,1.0,0,91,Semi-Urban,Software Engineer,44527,1 +2371,Female,45,Diploma,0,0,88,80,30,4.0,1,7,Urban,ML Engineer,92959,0 +2372,Female,24,High School,16,26,73,29,22,1.0,0,0,Semi-Urban,ML Engineer,147895,0 +2373,Female,53,High School,13,66,91,72,3,0.0,7,96,Urban,Data Analyst,37166,1 +2374,Male,47,Bachelors,0,56,37,93,69,4.0,5,86,Urban,Software Engineer,99059,1 +2375,Female,43,Bachelors,8,69,91,63,68,3.0,3,85,Semi-Urban,Software Engineer,85773,1 +2376,Male,58,Diploma,7,58,69,91,6,4.0,1,3,Urban,Software Engineer,30578,0 +2377,Male,24,Masters,15,15,61,21,81,8.0,5,58,Rural,Data Analyst,68302,0 +2378,Female,57,Bachelors,4,99,50,70,82,7.0,2,49,Semi-Urban,ML Engineer,112660,1 +2379,Male,49,Diploma,19,93,71,53,60,1.0,4,63,Urban,Manager,130049,1 +2380,Female,21,Masters,18,36,72,66,66,1.0,4,9,Semi-Urban,Data Analyst,85053,0 +2381,Female,23,Masters,10,26,98,87,18,5.0,2,32,Semi-Urban,Software Engineer,55434,1 +2382,Female,24,Diploma,0,0,59,35,39,5.0,7,16,Urban,Data Analyst,107834,0 +2383,Female,38,Bachelors,4,46,7,9,6,1.0,0,75,Urban,Software Engineer,36507,0 +2384,Male,27,Masters,7,45,8,27,70,6.0,2,78,Urban,Software Engineer,93728,0 +2385,Male,21,Diploma,15,90,14,91,80,9.0,0,39,Urban,Data Analyst,80697,0 +2386,Male,49,Bachelors,18,6,76,13,71,7.0,3,50,Urban,Data Analyst,84733,0 +2387,Male,33,Masters,14,44,24,84,36,4.0,5,3,Urban,ML Engineer,68357,0 +2388,Female,46,Bachelors,7,89,88,80,12,3.0,6,99,Urban,Data Analyst,62906,1 +2389,Female,44,Bachelors,16,4,11,0,40,5.0,7,59,Urban,HR Executive,108197,0 +2390,Female,48,High School,18,80,57,23,79,5.0,2,95,Urban,Software Engineer,58029,1 +2391,Male,26,Bachelors,17,83,24,26,32,2.0,0,43,Urban,ML Engineer,81951,0 +2392,Male,29,Masters,19,0,40,18,86,5.0,6,58,Urban,Manager,128636,0 +2393,Male,57,Diploma,0,13,46,78,53,6.0,2,89,Urban,HR Executive,25206,0 +2394,Male,47,Diploma,0,90,44,2,92,4.0,5,4,Urban,ML Engineer,42664,0 +2395,Female,57,Bachelors,6,51,46,1,39,2.0,3,12,Urban,Software Engineer,70804,0 +2396,Male,51,Masters,4,66,50,66,21,9.0,5,78,Semi-Urban,Manager,87614,1 +2397,Male,40,Bachelors,6,21,76,3,87,7.0,6,41,Semi-Urban,ML Engineer,20650,0 +2398,Male,41,PhD,18,94,48,18,9,1.0,3,61,Urban,HR Executive,54531,0 +2399,Female,49,High School,2,78,36,11,65,0.0,2,36,Rural,Software Engineer,38400,0 +2400,Female,44,Bachelors,7,80,97,73,65,1.0,2,72,Semi-Urban,Manager,106215,1 +2401,Male,24,Bachelors,5,79,10,42,3,2.0,2,57,Urban,ML Engineer,140291,0 +2402,Male,33,Bachelors,0,45,60,39,31,3.0,1,98,Rural,Software Engineer,36575,1 +2403,Male,56,Bachelors,15,36,22,6,47,8.0,1,63,Urban,ML Engineer,110815,0 +2404,Male,30,PhD,9,73,9,53,97,2.0,7,59,Urban,Manager,147693,0 +2405,Female,41,Masters,14,62,46,26,30,0.0,2,20,Rural,ML Engineer,93275,0 +2406,Female,36,Masters,8,18,44,70,68,0.0,7,18,Urban,ML Engineer,107185,0 +2407,Male,51,Bachelors,12,54,25,57,53,9.0,2,18,Urban,Manager,128889,0 +2408,Male,34,High School,18,70,31,35,56,8.0,6,75,Rural,ML Engineer,25451,0 +2409,Other,38,Diploma,3,68,27,99,69,2.0,1,4,Semi-Urban,Manager,135065,0 +2410,Male,35,Diploma,5,8,30,95,30,6.0,5,67,Urban,Manager,35688,0 +2411,Female,21,High School,9,76,47,40,52,8.0,2,41,Urban,HR Executive,111447,0 +2412,Male,53,Bachelors,7,4,44,32,35,7.0,6,25,Urban,Software Engineer,74664,0 +2413,Male,52,Masters,17,55,73,17,24,8.0,3,92,Urban,ML Engineer,94274,1 +2414,Male,31,Diploma,15,60,71,88,64,2.0,1,15,Urban,ML Engineer,83617,0 +2415,Male,58,Bachelors,9,27,72,64,84,5.0,3,7,Rural,Software Engineer,84463,0 +2416,Other,36,Bachelors,5,34,31,43,81,4.0,5,36,Urban,Software Engineer,107689,0 +2417,Male,24,PhD,8,41,95,43,60,6.0,7,68,Urban,Manager,25156,1 +2418,Male,34,PhD,14,91,40,17,37,8.0,7,41,Urban,Manager,28694,0 +2419,Male,55,Masters,1,79,97,75,50,7.0,6,48,Urban,ML Engineer,82238,1 +2420,Male,28,High School,18,44,22,51,27,6.0,3,17,Urban,Software Engineer,85713,0 +2421,Male,59,Diploma,2,63,23,1,82,0.0,0,52,Rural,Software Engineer,87576,0 +2422,Male,54,Bachelors,17,39,11,38,11,6.0,4,79,Rural,ML Engineer,89937,0 +2423,Female,21,Bachelors,16,98,78,87,49,6.0,2,51,Urban,Manager,38259,1 +2424,Male,32,Diploma,4,44,91,6,88,1.0,6,73,Urban,Software Engineer,83586,0 +2425,Male,51,Diploma,19,66,90,39,30,0.0,6,28,Urban,HR Executive,143431,0 +2426,Female,50,Bachelors,18,18,62,2,88,8.0,4,27,Semi-Urban,Data Analyst,53249,0 +2427,Male,59,Masters,19,10,62,36,74,5.0,4,77,Urban,HR Executive,113768,0 +2428,Other,36,Diploma,2,49,83,79,97,1.0,6,30,Rural,HR Executive,107307,1 +2429,Male,34,Bachelors,18,26,52,19,94,1.0,1,90,Semi-Urban,ML Engineer,82808,0 +2430,Female,41,PhD,6,88,8,7,90,4.0,7,94,Urban,HR Executive,65589,0 +2431,Female,44,Bachelors,11,98,65,10,89,8.0,7,56,Semi-Urban,Data Analyst,94328,0 +2432,Female,21,High School,4,90,94,63,83,8.0,1,63,Semi-Urban,HR Executive,134903,1 +2433,Other,56,High School,8,26,44,82,95,3.0,7,74,Urban,HR Executive,120687,0 +2434,Male,31,Bachelors,8,59,14,54,44,3.0,6,24,Semi-Urban,Manager,73109,0 +2435,Other,45,Diploma,7,76,85,47,35,0.0,3,84,Semi-Urban,Software Engineer,27550,1 +2436,Male,33,Bachelors,4,40,48,22,41,3.0,5,42,Semi-Urban,Software Engineer,98681,0 +2437,Male,36,Diploma,5,45,27,85,11,7.0,2,42,Rural,Data Analyst,96347,0 +2438,Male,49,Bachelors,7,39,79,11,70,2.0,4,28,Urban,ML Engineer,146277,0 +2439,Male,39,Bachelors,8,11,91,51,64,9.0,1,61,Urban,HR Executive,29703,0 +2440,Male,35,Masters,7,39,81,14,69,2.0,5,25,Urban,Software Engineer,102086,0 +2441,Male,39,Bachelors,16,22,67,15,18,3.0,2,24,Urban,Manager,127661,0 +2442,Male,51,Bachelors,2,58,88,17,24,3.0,1,0,Semi-Urban,HR Executive,78903,0 +2443,Female,32,Masters,4,47,65,58,63,2.0,2,17,Semi-Urban,ML Engineer,46803,0 +2444,Female,53,Bachelors,18,97,49,42,89,4.0,6,12,Semi-Urban,Data Analyst,123257,0 +2445,Male,26,Bachelors,15,45,8,71,25,1.0,7,45,Urban,ML Engineer,71442,0 +2446,Male,58,Masters,7,82,94,14,51,3.0,4,93,Urban,Data Analyst,40780,1 +2447,Male,43,Bachelors,9,40,66,39,16,0.0,4,90,Rural,Manager,131916,1 +2448,Male,36,Bachelors,0,43,97,41,34,6.0,1,13,Urban,Software Engineer,45441,0 +2449,Male,56,Diploma,16,88,36,70,52,4.0,0,74,Rural,ML Engineer,22557,1 +2450,Male,37,Masters,16,74,77,84,65,4.0,7,62,Urban,HR Executive,79645,1 +2451,Male,38,Masters,16,64,36,89,65,4.0,7,1,Urban,Software Engineer,148867,0 +2452,Other,24,Bachelors,14,37,20,72,61,5.0,6,17,Urban,Software Engineer,72220,0 +2453,Male,49,Diploma,3,76,99,17,64,1.0,0,72,Urban,ML Engineer,29336,1 +2454,Male,40,Masters,1,61,58,91,80,1.0,2,62,Semi-Urban,Software Engineer,92378,1 +2455,Male,23,Masters,15,71,71,6,13,9.0,7,13,Urban,Manager,20994,0 +2456,Male,34,Masters,8,94,73,86,99,9.0,4,16,Urban,Manager,28716,1 +2457,Male,48,Masters,15,89,16,38,79,1.0,0,54,Semi-Urban,Manager,25266,0 +2458,Female,45,PhD,18,76,9,94,40,7.0,1,69,Semi-Urban,HR Executive,91688,1 +2459,Male,22,Bachelors,15,43,93,78,78,0.0,6,79,Semi-Urban,Data Analyst,28039,1 +2460,Male,58,Bachelors,5,79,94,88,38,0.0,0,57,Urban,HR Executive,91739,1 +2461,Other,34,Masters,2,86,19,62,24,0.0,5,3,Urban,Manager,111620,0 +2462,Female,26,Bachelors,7,14,93,81,44,3.0,3,6,Urban,HR Executive,89829,0 +2463,Female,44,Masters,12,4,95,20,77,3.0,0,82,Rural,Data Analyst,132081,0 +2464,Male,56,High School,3,85,71,9,14,8.0,1,47,Urban,Software Engineer,119359,0 +2465,Female,37,Bachelors,15,12,10,56,69,7.0,7,66,Rural,Software Engineer,132853,0 +2466,Male,48,Diploma,8,66,10,79,96,5.0,7,73,Urban,Manager,104334,0 +2467,Male,55,PhD,8,14,95,62,89,1.0,7,45,Urban,HR Executive,58783,0 +2468,Male,22,Bachelors,18,51,57,80,37,0.0,5,22,Urban,Software Engineer,112721,0 +2469,Male,59,Masters,15,97,8,19,0,8.0,1,49,Rural,Manager,51343,0 +2470,Male,41,Diploma,18,6,10,0,81,9.0,2,62,Urban,Manager,72869,0 +2471,Male,23,Bachelors,19,96,34,92,65,7.0,2,44,Semi-Urban,Software Engineer,57846,1 +2472,Other,27,Bachelors,18,8,79,93,93,6.0,0,80,Semi-Urban,ML Engineer,53520,1 +2473,Female,21,Diploma,11,26,6,17,51,4.0,2,34,Urban,Manager,131046,0 +2474,Female,55,Diploma,14,63,7,18,72,0.0,4,89,Urban,Manager,79595,0 +2475,Male,55,Diploma,1,48,92,69,2,8.0,5,66,Rural,Manager,148738,1 +2476,Female,36,Masters,4,3,25,4,19,1.0,0,97,Urban,ML Engineer,92113,0 +2477,Male,21,Bachelors,5,63,72,83,49,9.0,3,28,Urban,Data Analyst,137852,1 +2478,Female,22,Bachelors,3,49,10,3,37,0.0,5,83,Semi-Urban,ML Engineer,66316,0 +2479,Male,22,Bachelors,12,64,29,79,32,1.0,1,94,Urban,Data Analyst,125640,1 +2480,Female,23,Masters,16,36,3,73,37,5.0,4,42,Urban,ML Engineer,71483,0 +2481,Male,55,Masters,6,63,87,68,68,8.0,6,36,Urban,ML Engineer,28444,1 +2482,Female,52,Bachelors,9,14,43,80,24,4.0,1,49,Urban,Software Engineer,34686,0 +2483,Female,36,Masters,11,1,78,67,58,7.0,0,51,Urban,ML Engineer,132798,0 +2484,Male,22,Diploma,16,85,68,59,4,6.0,3,20,Rural,ML Engineer,87663,0 +2485,Male,57,Bachelors,7,35,70,77,55,8.0,7,32,Urban,Manager,54612,0 +2486,Other,32,PhD,0,51,84,19,45,0.0,4,54,Urban,ML Engineer,143345,0 +2487,Male,22,Diploma,13,57,26,64,4,3.0,3,86,Urban,Software Engineer,69390,0 +2488,Female,44,High School,12,86,90,13,36,2.0,0,48,Semi-Urban,Software Engineer,108879,0 +2489,Male,22,Diploma,15,98,51,53,8,3.0,3,9,Rural,ML Engineer,94826,0 +2490,Male,22,Bachelors,15,70,49,96,89,7.0,2,39,Urban,Data Analyst,125329,1 +2491,Male,49,Bachelors,11,90,1,27,40,2.0,5,14,Urban,Manager,82396,0 +2492,Male,22,Masters,9,3,69,30,93,2.0,5,90,Urban,Data Analyst,61838,0 +2493,Female,35,Bachelors,15,62,29,44,37,7.0,6,89,Semi-Urban,HR Executive,89744,0 +2494,Male,58,Bachelors,2,59,40,36,22,5.0,7,35,Urban,ML Engineer,128206,0 +2495,Male,41,Diploma,8,62,0,0,20,5.0,0,31,Urban,Software Engineer,40338,0 +2496,Male,39,Masters,13,99,98,56,1,1.0,5,85,Urban,Data Analyst,48282,1 +2497,Male,36,Diploma,19,64,9,76,82,2.0,4,11,Urban,Software Engineer,52566,0 +2498,Female,27,Diploma,17,20,53,7,50,4.0,2,18,Rural,HR Executive,74179,0 +2499,Other,49,Bachelors,13,92,97,94,39,7.0,3,19,Urban,ML Engineer,98854,1 +2500,Male,39,Masters,18,87,24,89,53,3.0,5,23,Urban,ML Engineer,97186,0 +2501,Female,53,Masters,8,3,18,36,39,1.0,6,87,Urban,Data Analyst,64484,0 +2502,Female,44,Bachelors,3,7,51,67,1,6.0,1,75,Rural,Manager,39121,0 +2503,Male,39,Masters,16,34,53,72,78,1.0,5,45,Urban,Software Engineer,147181,0 +2504,Other,25,Diploma,1,91,32,34,71,1.0,0,42,Semi-Urban,Software Engineer,56908,0 +2505,Male,57,High School,9,95,33,69,75,2.0,5,84,Urban,Software Engineer,135418,1 +2506,Male,45,Bachelors,16,29,29,10,62,8.0,2,62,Urban,ML Engineer,75053,0 +2507,Female,23,High School,18,56,24,2,29,7.0,1,94,Semi-Urban,Data Analyst,44266,0 +2508,Male,48,Bachelors,13,0,81,7,94,6.0,4,78,Urban,Software Engineer,100089,0 +2509,Female,46,Diploma,18,30,27,80,81,1.0,7,24,Urban,Data Analyst,133611,0 +2510,Female,31,Bachelors,8,1,58,34,6,3.0,7,33,Urban,Manager,136250,0 +2511,Male,31,Bachelors,16,14,21,55,48,0.0,7,93,Urban,Manager,95702,0 +2512,Female,27,Bachelors,18,48,48,2,13,9.0,6,30,Semi-Urban,Manager,103200,0 +2513,Male,46,Bachelors,16,75,44,29,73,4.0,3,55,Urban,Data Analyst,76064,0 +2514,Male,24,Masters,0,0,38,81,92,5.0,5,51,Urban,Manager,31974,0 +2515,Female,39,PhD,19,97,9,77,51,0.0,6,35,Rural,Manager,69421,0 +2516,Female,54,Bachelors,19,99,40,51,14,2.0,0,30,Rural,Data Analyst,23374,0 +2517,Male,30,Masters,6,33,40,2,95,2.0,7,90,Urban,Software Engineer,93904,0 +2518,Male,22,Bachelors,18,28,42,17,85,0.0,4,63,Urban,Data Analyst,79357,0 +2519,Female,27,Bachelors,16,97,24,21,8,3.0,1,8,Semi-Urban,Manager,127316,0 +2520,Female,55,High School,4,34,90,9,41,0.0,7,41,Urban,ML Engineer,137286,0 +2521,Female,52,Bachelors,16,97,46,89,55,0.0,1,30,Urban,Software Engineer,114361,1 +2522,Male,35,Masters,15,18,40,85,66,0.0,3,72,Semi-Urban,ML Engineer,30278,0 +2523,Male,32,Masters,6,76,46,89,35,3.0,4,98,Semi-Urban,Data Analyst,109107,1 +2524,Male,33,Masters,13,3,65,74,90,9.0,7,98,Semi-Urban,ML Engineer,94139,1 +2525,Female,28,Bachelors,15,82,7,34,25,1.0,3,39,Semi-Urban,Data Analyst,79266,0 +2526,Male,59,Bachelors,19,68,26,1,87,5.0,4,86,Semi-Urban,Data Analyst,55293,0 +2527,Male,41,Bachelors,16,75,91,43,45,8.0,0,17,Rural,Data Analyst,109083,0 +2528,Other,47,Diploma,11,71,59,56,51,1.0,3,40,Semi-Urban,Data Analyst,68354,0 +2529,Male,37,PhD,13,6,37,74,79,3.0,0,96,Rural,ML Engineer,31890,0 +2530,Other,31,Bachelors,12,64,42,76,98,3.0,6,70,Semi-Urban,Data Analyst,23124,1 +2531,Female,28,PhD,7,28,21,46,96,4.0,0,82,Urban,Software Engineer,92770,0 +2532,Female,52,Diploma,12,64,21,40,72,6.0,1,88,Semi-Urban,Data Analyst,110791,0 +2533,Male,30,Diploma,6,44,9,29,71,5.0,6,91,Semi-Urban,Software Engineer,32315,0 +2534,Male,55,Bachelors,11,88,96,6,39,9.0,0,35,Urban,ML Engineer,144275,0 +2535,Female,48,Diploma,11,73,1,56,56,6.0,0,91,Urban,Manager,66162,0 +2536,Female,52,Diploma,7,75,90,7,61,7.0,3,64,Semi-Urban,HR Executive,127518,0 +2537,Female,24,Bachelors,5,70,17,80,39,3.0,6,46,Semi-Urban,HR Executive,47222,0 +2538,Male,47,Bachelors,1,90,44,69,66,9.0,4,89,Rural,ML Engineer,114817,1 +2539,Female,59,Bachelors,1,11,75,13,42,4.0,7,35,Rural,Manager,121192,0 +2540,Female,38,Bachelors,11,75,44,42,63,7.0,6,48,Semi-Urban,ML Engineer,137038,0 +2541,Female,52,Bachelors,16,98,89,68,4,5.0,5,3,Urban,Data Analyst,77328,1 +2542,Female,25,Diploma,17,65,16,85,70,2.0,0,29,Urban,Software Engineer,66410,0 +2543,Female,57,Bachelors,5,44,37,68,35,2.0,0,7,Rural,HR Executive,72644,0 +2544,Female,48,Bachelors,1,25,61,87,58,7.0,5,44,Urban,HR Executive,118510,0 +2545,Male,59,Diploma,17,10,70,16,53,8.0,6,47,Semi-Urban,Software Engineer,53482,0 +2546,Male,33,Diploma,4,33,69,6,30,6.0,6,20,Urban,HR Executive,20351,0 +2547,Male,42,Bachelors,12,78,61,32,67,6.0,7,34,Rural,Data Analyst,136421,0 +2548,Male,47,Diploma,13,85,9,28,67,3.0,6,94,Semi-Urban,HR Executive,29585,0 +2549,Male,29,Bachelors,11,36,36,26,93,3.0,5,64,Urban,HR Executive,74238,0 +2550,Male,47,Bachelors,6,63,67,82,81,9.0,5,36,Urban,Data Analyst,106631,1 +2551,Male,37,Bachelors,11,97,56,29,9,8.0,0,19,Urban,HR Executive,27750,0 +2552,Male,32,Bachelors,8,52,38,13,54,4.0,4,61,Urban,Data Analyst,38481,0 +2553,Female,32,Bachelors,8,90,80,45,58,0.0,3,91,Urban,Manager,103438,1 +2554,Female,55,Diploma,0,37,94,90,59,7.0,7,50,Urban,ML Engineer,36170,1 +2555,Male,48,PhD,10,92,12,18,45,3.0,2,73,Urban,Manager,27403,0 +2556,Other,50,High School,11,79,59,57,41,0.0,2,90,Urban,Software Engineer,39841,1 +2557,Male,47,Bachelors,4,84,79,90,30,0.0,5,51,Rural,Software Engineer,112482,1 +2558,Male,52,Bachelors,0,46,75,4,28,8.0,0,2,Urban,Data Analyst,55109,0 +2559,Male,58,Masters,1,71,28,82,19,1.0,6,21,Urban,Data Analyst,78229,0 +2560,Male,26,Masters,0,83,69,39,30,0.0,1,34,Urban,ML Engineer,64071,0 +2561,Female,51,Bachelors,12,53,32,12,99,6.0,5,83,Urban,ML Engineer,83967,0 +2562,Female,21,Diploma,1,30,48,20,45,7.0,5,80,Rural,ML Engineer,65321,0 +2563,Male,41,Bachelors,0,41,4,65,22,1.0,6,5,Urban,HR Executive,128695,0 +2564,Male,32,Diploma,1,48,67,14,25,3.0,4,68,Urban,Manager,51016,0 +2565,Male,32,High School,10,9,35,7,87,9.0,3,74,Semi-Urban,HR Executive,81996,0 +2566,Male,57,High School,15,30,3,18,46,7.0,5,37,Semi-Urban,Data Analyst,60764,0 +2567,Male,42,Diploma,6,82,89,7,71,7.0,6,44,Urban,Software Engineer,133902,0 +2568,Male,58,Masters,11,63,95,47,6,8.0,4,95,Semi-Urban,Manager,135143,1 +2569,Female,36,Bachelors,0,12,79,61,90,0.0,5,39,Semi-Urban,Manager,98194,0 +2570,Female,32,Masters,10,32,90,32,19,5.0,6,2,Urban,Manager,53238,0 +2571,Male,59,High School,9,71,78,93,8,9.0,4,90,Semi-Urban,HR Executive,28843,1 +2572,Female,34,Diploma,4,85,42,3,51,6.0,6,90,Urban,Manager,77131,0 +2573,Male,29,High School,9,43,25,93,96,7.0,3,94,Urban,Data Analyst,127285,1 +2574,Male,22,Bachelors,17,22,6,91,16,6.0,0,0,Rural,HR Executive,105955,0 +2575,Male,49,Masters,4,41,4,46,37,5.0,2,2,Urban,Software Engineer,123778,0 +2576,Female,55,Masters,14,31,16,58,87,1.0,5,34,Urban,Manager,54091,0 +2577,Other,42,Bachelors,11,64,57,20,58,1.0,7,4,Semi-Urban,HR Executive,110799,0 +2578,Female,25,High School,6,86,5,11,7,6.0,4,3,Semi-Urban,Manager,42344,0 +2579,Male,25,Bachelors,17,2,44,62,16,0.0,3,91,Urban,Software Engineer,51179,0 +2580,Female,40,High School,16,48,31,54,5,9.0,5,7,Urban,Manager,74187,0 +2581,Male,53,Bachelors,2,27,5,59,72,4.0,6,36,Rural,Manager,45388,0 +2582,Female,25,Diploma,8,58,5,95,75,0.0,7,76,Semi-Urban,Manager,126974,0 +2583,Male,27,Diploma,14,88,42,22,48,9.0,4,40,Urban,ML Engineer,120895,0 +2584,Male,25,Bachelors,15,70,36,68,53,0.0,5,39,Rural,HR Executive,127551,0 +2585,Male,21,Bachelors,19,24,60,43,33,5.0,6,8,Urban,HR Executive,57845,0 +2586,Female,39,Bachelors,19,32,44,50,75,4.0,3,98,Urban,Data Analyst,47805,0 +2587,Male,29,Bachelors,10,81,73,49,13,0.0,3,40,Semi-Urban,Software Engineer,24196,1 +2588,Female,37,High School,6,10,99,45,2,2.0,2,51,Semi-Urban,Software Engineer,114538,0 +2589,Male,59,Bachelors,3,41,51,79,76,3.0,7,66,Urban,Data Analyst,98619,1 +2590,Female,29,Bachelors,13,5,51,81,11,8.0,4,14,Urban,HR Executive,81642,0 +2591,Female,36,Bachelors,3,30,35,45,42,0.0,7,98,Urban,Data Analyst,114972,0 +2592,Female,39,Bachelors,16,36,60,18,94,0.0,4,95,Semi-Urban,Manager,116967,0 +2593,Male,34,High School,5,23,27,89,24,5.0,0,57,Urban,Software Engineer,52926,0 +2594,Male,56,Masters,15,5,0,92,38,6.0,4,15,Urban,HR Executive,86585,0 +2595,Male,56,Bachelors,15,50,85,0,93,5.0,2,16,Urban,Manager,91460,0 +2596,Female,23,Diploma,4,88,81,68,54,3.0,4,1,Urban,ML Engineer,89872,0 +2597,Male,46,Bachelors,17,31,91,77,4,1.0,7,84,Urban,ML Engineer,116994,1 +2598,Male,31,Diploma,10,75,1,23,9,2.0,3,10,Urban,Data Analyst,125327,0 +2599,Male,48,Bachelors,11,42,94,40,7,7.0,3,17,Urban,Software Engineer,36627,0 +2600,Male,31,Masters,9,18,79,90,23,1.0,3,38,Urban,Software Engineer,103507,0 +2601,Female,32,Masters,14,40,47,1,80,5.0,5,93,Rural,Software Engineer,35231,0 +2602,Male,47,Masters,5,42,48,16,35,2.0,7,96,Rural,ML Engineer,149781,0 +2603,Female,32,Masters,0,29,70,89,60,9.0,2,47,Urban,Data Analyst,57472,0 +2604,Male,53,Bachelors,5,7,65,10,60,8.0,7,62,Urban,Manager,144843,0 +2605,Male,25,High School,5,29,42,27,29,9.0,4,20,Urban,HR Executive,131365,0 +2606,Male,41,Diploma,10,80,77,2,89,8.0,5,42,Urban,Manager,36053,0 +2607,Male,50,Bachelors,9,56,26,18,17,6.0,5,27,Semi-Urban,ML Engineer,93480,0 +2608,Male,53,Diploma,16,3,96,40,59,8.0,1,2,Urban,ML Engineer,50083,0 +2609,Female,30,Bachelors,10,43,65,49,1,6.0,3,1,Rural,HR Executive,46380,0 +2610,Male,21,Bachelors,9,35,28,11,21,6.0,0,75,Semi-Urban,Software Engineer,29574,0 +2611,Female,49,Bachelors,15,8,20,49,46,9.0,2,18,Urban,Data Analyst,69516,0 +2612,Male,27,Diploma,5,37,32,98,5,8.0,5,67,Semi-Urban,ML Engineer,120806,0 +2613,Male,53,Diploma,15,37,95,84,63,6.0,6,16,Urban,HR Executive,22892,0 +2614,Female,21,Bachelors,13,74,75,9,72,2.0,3,83,Semi-Urban,Software Engineer,90280,1 +2615,Male,51,Bachelors,14,92,10,27,80,1.0,5,7,Urban,Data Analyst,92878,0 +2616,Male,53,High School,9,73,72,95,71,8.0,1,18,Urban,Manager,85078,1 +2617,Male,23,High School,19,71,54,49,23,7.0,7,68,Urban,ML Engineer,23246,1 +2618,Male,51,Diploma,9,78,35,35,63,2.0,4,29,Urban,Software Engineer,47159,0 +2619,Female,22,Bachelors,5,51,56,63,66,0.0,0,19,Semi-Urban,HR Executive,32323,0 +2620,Male,38,Bachelors,11,78,66,68,94,9.0,7,42,Urban,ML Engineer,86214,1 +2621,Female,38,Diploma,17,3,81,38,86,4.0,3,24,Semi-Urban,Data Analyst,28497,0 +2622,Female,44,Bachelors,7,32,72,71,27,3.0,0,78,Urban,ML Engineer,135369,1 +2623,Male,52,Bachelors,17,57,96,24,41,2.0,2,79,Urban,Software Engineer,107178,1 +2624,Female,44,Bachelors,11,26,86,80,10,8.0,6,14,Urban,HR Executive,134511,0 +2625,Male,29,PhD,13,40,40,68,3,0.0,2,66,Semi-Urban,HR Executive,139630,0 +2626,Other,32,Bachelors,9,25,18,26,78,5.0,7,44,Urban,Software Engineer,141072,0 +2627,Male,47,Bachelors,14,92,52,48,89,5.0,2,13,Urban,Software Engineer,66087,0 +2628,Female,59,PhD,5,9,55,7,59,6.0,0,48,Urban,ML Engineer,61248,0 +2629,Male,25,Diploma,10,98,67,27,35,0.0,5,77,Rural,Manager,81036,1 +2630,Male,55,Diploma,1,57,32,32,8,4.0,3,59,Urban,ML Engineer,77408,0 +2631,Female,46,Bachelors,13,87,56,49,92,6.0,1,11,Urban,Software Engineer,99704,0 +2632,Female,30,Diploma,14,46,66,19,43,3.0,0,7,Urban,Manager,125662,0 +2633,Male,30,Bachelors,7,62,48,51,83,3.0,4,74,Urban,ML Engineer,106533,1 +2634,Male,23,Masters,9,79,38,52,76,9.0,0,54,Urban,ML Engineer,137301,0 +2635,Female,33,High School,4,6,68,47,38,4.0,4,49,Semi-Urban,Software Engineer,135183,0 +2636,Female,42,Masters,7,79,51,4,72,0.0,4,90,Urban,ML Engineer,94120,0 +2637,Other,41,Bachelors,17,36,33,93,2,5.0,6,59,Urban,Data Analyst,142138,0 +2638,Female,54,High School,5,39,95,14,63,9.0,6,85,Urban,Data Analyst,124318,0 +2639,Other,46,Masters,16,69,65,68,0,4.0,2,26,Urban,Data Analyst,108824,0 +2640,Female,30,Diploma,14,66,89,82,19,9.0,2,45,Semi-Urban,ML Engineer,27963,1 +2641,Male,40,High School,6,77,85,91,72,7.0,2,70,Semi-Urban,Manager,115484,1 +2642,Male,37,Bachelors,3,81,78,21,31,0.0,3,18,Urban,Data Analyst,30163,0 +2643,Female,44,Masters,4,74,36,62,13,2.0,3,76,Rural,ML Engineer,142307,1 +2644,Female,53,PhD,3,51,22,99,4,5.0,0,14,Urban,Data Analyst,148927,0 +2645,Male,36,Diploma,3,22,81,7,61,7.0,1,58,Urban,ML Engineer,120648,0 +2646,Male,57,Bachelors,3,8,49,94,48,5.0,7,32,Urban,ML Engineer,73536,0 +2647,Other,54,Masters,5,44,43,13,6,5.0,4,10,Urban,Manager,108442,0 +2648,Male,28,High School,14,38,30,25,28,0.0,1,78,Urban,Manager,95851,0 +2649,Male,35,Bachelors,11,74,57,26,92,2.0,6,68,Semi-Urban,Manager,139637,0 +2650,Male,33,Diploma,10,36,77,30,82,2.0,6,67,Semi-Urban,ML Engineer,80535,0 +2651,Male,45,Bachelors,5,49,28,30,28,8.0,3,25,Urban,HR Executive,48661,0 +2652,Male,48,PhD,16,83,81,88,79,7.0,0,37,Urban,Manager,124699,1 +2653,Male,59,Bachelors,17,1,70,93,70,9.0,2,74,Urban,Manager,33363,1 +2654,Male,56,Diploma,17,11,67,21,89,1.0,1,17,Semi-Urban,HR Executive,104845,0 +2655,Female,58,Bachelors,13,20,37,73,90,7.0,5,50,Semi-Urban,HR Executive,43686,0 +2656,Male,30,Bachelors,6,54,42,1,64,9.0,3,86,Urban,Data Analyst,106905,0 +2657,Female,36,Masters,4,97,92,44,92,5.0,5,65,Semi-Urban,Software Engineer,87179,1 +2658,Female,33,PhD,14,65,44,29,58,3.0,3,62,Urban,ML Engineer,71426,0 +2659,Male,50,High School,5,72,91,84,47,6.0,3,47,Semi-Urban,Software Engineer,145233,1 +2660,Female,33,Bachelors,3,88,36,23,80,6.0,7,21,Urban,ML Engineer,101779,0 +2661,Male,45,Bachelors,14,25,74,73,91,6.0,4,26,Urban,ML Engineer,106005,0 +2662,Female,37,Bachelors,13,68,30,51,73,4.0,5,85,Urban,ML Engineer,138896,0 +2663,Male,26,Bachelors,3,50,22,98,98,0.0,1,64,Urban,Data Analyst,26439,0 +2664,Female,41,Bachelors,0,25,93,36,5,6.0,6,27,Urban,Data Analyst,60666,0 +2665,Female,41,Bachelors,11,44,14,27,3,5.0,7,71,Semi-Urban,Software Engineer,74846,0 +2666,Male,48,Bachelors,10,16,79,43,4,3.0,0,46,Semi-Urban,Manager,49833,0 +2667,Male,32,Masters,16,30,26,20,52,1.0,0,65,Urban,HR Executive,37764,0 +2668,Female,28,High School,7,76,54,60,15,0.0,0,55,Urban,Manager,94964,1 +2669,Female,57,Diploma,19,37,37,58,17,7.0,5,36,Semi-Urban,Software Engineer,71550,0 +2670,Male,39,Bachelors,11,48,47,30,82,4.0,0,19,Urban,HR Executive,145365,0 +2671,Female,38,Diploma,3,83,39,50,98,3.0,7,69,Urban,ML Engineer,94706,1 +2672,Male,40,Diploma,9,51,28,77,61,7.0,2,30,Rural,Data Analyst,99054,0 +2673,Female,32,Bachelors,10,97,38,46,36,1.0,1,63,Rural,Data Analyst,136513,1 +2674,Male,25,PhD,7,16,21,33,80,7.0,2,22,Semi-Urban,ML Engineer,63325,0 +2675,Female,43,Diploma,19,43,31,4,71,9.0,6,47,Urban,ML Engineer,121021,0 +2676,Male,40,Bachelors,13,8,54,8,1,8.0,0,49,Urban,HR Executive,118071,0 +2677,Male,29,Diploma,5,82,55,4,78,1.0,0,77,Rural,ML Engineer,93514,0 +2678,Male,43,Bachelors,19,54,9,58,1,7.0,3,88,Urban,ML Engineer,56083,0 +2679,Male,58,PhD,19,71,13,7,97,9.0,5,97,Urban,HR Executive,133833,0 +2680,Male,29,Diploma,19,35,5,90,69,8.0,0,52,Semi-Urban,ML Engineer,40054,0 +2681,Male,49,Bachelors,18,66,19,87,22,5.0,6,54,Urban,Software Engineer,75919,0 +2682,Female,57,Masters,13,99,58,10,58,8.0,6,72,Urban,Software Engineer,90947,0 +2683,Male,50,Diploma,5,32,79,25,77,3.0,5,18,Urban,Software Engineer,59406,0 +2684,Male,33,Bachelors,18,61,97,76,75,8.0,0,63,Semi-Urban,Software Engineer,51259,1 +2685,Male,47,Masters,2,55,77,69,52,2.0,1,76,Urban,Manager,23049,1 +2686,Male,37,Bachelors,18,20,88,8,53,0.0,1,96,Rural,Software Engineer,41970,0 +2687,Male,24,Bachelors,9,4,98,51,88,3.0,2,19,Urban,Data Analyst,49199,0 +2688,Male,23,Bachelors,4,51,3,45,17,1.0,7,9,Urban,HR Executive,114475,0 +2689,Male,39,High School,6,62,83,21,73,1.0,2,91,Urban,ML Engineer,83390,1 +2690,Male,21,Bachelors,8,17,93,42,97,8.0,6,72,Urban,Data Analyst,32553,0 +2691,Male,28,Masters,7,37,53,18,17,5.0,1,33,Urban,Manager,49671,0 +2692,Male,22,Bachelors,18,85,75,32,19,5.0,1,18,Rural,ML Engineer,21660,0 +2693,Male,55,High School,10,40,48,77,21,0.0,7,86,Urban,ML Engineer,20447,1 +2694,Male,23,Bachelors,10,39,71,95,54,6.0,3,85,Urban,ML Engineer,102652,1 +2695,Other,37,Bachelors,13,36,99,16,25,0.0,5,33,Semi-Urban,Manager,114628,0 +2696,Male,59,Bachelors,9,49,89,85,30,7.0,3,69,Rural,HR Executive,45068,1 +2697,Female,51,Bachelors,17,5,73,2,12,2.0,2,71,Urban,Software Engineer,55669,0 +2698,Male,30,High School,16,19,75,13,50,5.0,6,23,Urban,Data Analyst,30253,0 +2699,Female,30,Diploma,13,98,40,75,89,4.0,1,35,Rural,ML Engineer,118278,1 +2700,Female,38,Bachelors,13,58,39,27,94,3.0,3,95,Semi-Urban,Data Analyst,132348,0 +2701,Male,59,Diploma,0,33,33,87,80,5.0,4,89,Urban,HR Executive,101692,1 +2702,Other,25,Bachelors,12,29,39,90,12,9.0,6,93,Urban,ML Engineer,75179,1 +2703,Male,26,Masters,3,46,54,94,62,5.0,7,32,Semi-Urban,ML Engineer,134546,0 +2704,Male,51,High School,19,12,58,19,52,4.0,3,26,Urban,HR Executive,57796,0 +2705,Female,56,High School,3,31,63,6,61,1.0,6,37,Semi-Urban,Data Analyst,107387,0 +2706,Female,34,Diploma,2,20,86,41,35,3.0,7,83,Semi-Urban,ML Engineer,123507,0 +2707,Male,53,Bachelors,2,33,22,78,34,3.0,2,81,Urban,Data Analyst,37180,0 +2708,Male,49,High School,0,50,29,64,44,3.0,1,55,Rural,Data Analyst,21653,0 +2709,Male,39,Diploma,3,2,14,41,89,5.0,2,33,Urban,HR Executive,108804,0 +2710,Male,30,Bachelors,13,22,9,47,48,4.0,2,45,Rural,HR Executive,62762,0 +2711,Female,43,Diploma,10,42,64,87,54,2.0,1,29,Rural,Software Engineer,61250,0 +2712,Male,28,Masters,11,86,68,90,67,8.0,5,79,Semi-Urban,ML Engineer,78774,1 +2713,Male,44,Diploma,3,93,13,25,34,9.0,4,18,Rural,HR Executive,145421,0 +2714,Male,26,Diploma,7,86,31,21,2,2.0,0,56,Urban,ML Engineer,74304,0 +2715,Male,57,Diploma,12,45,79,49,39,8.0,4,59,Rural,Software Engineer,128822,0 +2716,Male,47,High School,6,59,92,44,83,9.0,4,24,Semi-Urban,HR Executive,84330,0 +2717,Female,52,Bachelors,5,64,33,45,65,5.0,6,62,Urban,HR Executive,96180,0 +2718,Other,50,Bachelors,15,80,12,87,40,5.0,0,54,Rural,Software Engineer,38692,0 +2719,Female,23,Bachelors,1,52,0,87,44,1.0,1,55,Urban,HR Executive,23128,0 +2720,Male,30,Bachelors,5,52,25,38,63,9.0,7,48,Urban,HR Executive,128060,0 +2721,Female,38,Diploma,13,19,68,56,2,3.0,3,38,Urban,Manager,103048,0 +2722,Female,33,Bachelors,11,34,57,60,69,7.0,4,45,Rural,HR Executive,109871,0 +2723,Female,37,Diploma,6,49,3,74,79,,1,78,Urban,Software Engineer,67889,0 +2724,Male,36,Masters,5,91,75,82,77,9.0,7,91,Urban,Software Engineer,147153,1 +2725,Male,41,High School,10,0,27,18,90,3.0,6,40,Urban,ML Engineer,77253,0 +2726,Male,32,High School,17,39,46,57,76,2.0,0,60,Semi-Urban,HR Executive,64852,0 +2727,Male,36,High School,5,92,67,41,85,7.0,1,29,Urban,Data Analyst,79041,0 +2728,Male,34,High School,3,91,5,72,53,4.0,0,99,Urban,ML Engineer,46797,1 +2729,Male,30,Diploma,5,71,67,3,59,8.0,5,77,Urban,HR Executive,36232,0 +2730,Male,37,Bachelors,0,51,48,64,38,5.0,2,56,Semi-Urban,Software Engineer,139784,0 +2731,Female,39,Masters,11,23,34,0,8,0.0,4,77,Urban,ML Engineer,64869,0 +2732,Male,29,Diploma,1,93,76,85,41,4.0,7,53,Urban,ML Engineer,61496,1 +2733,Male,26,High School,11,99,97,56,25,9.0,4,5,Urban,ML Engineer,132472,1 +2734,Other,38,Bachelors,17,55,26,95,19,8.0,5,0,Semi-Urban,Software Engineer,95508,0 +2735,Female,53,Bachelors,15,87,86,62,31,7.0,2,37,Rural,Manager,120684,1 +2736,Female,25,PhD,13,62,46,90,38,2.0,0,41,Semi-Urban,HR Executive,30329,0 +2737,Other,48,Bachelors,17,8,54,1,72,4.0,5,57,Rural,Manager,31168,0 +2738,Male,28,Diploma,5,92,35,83,23,8.0,1,90,Semi-Urban,Data Analyst,55822,1 +2739,Other,54,Bachelors,4,85,61,67,38,6.0,5,43,Urban,HR Executive,64895,1 +2740,Male,36,High School,19,34,7,95,73,0.0,3,83,Urban,Manager,40857,0 +2741,Male,34,High School,18,38,75,65,6,6.0,6,3,Urban,Software Engineer,82543,0 +2742,Male,37,Masters,3,54,32,63,84,1.0,2,26,Rural,Software Engineer,94121,0 +2743,Male,25,Bachelors,6,30,96,54,65,1.0,4,22,Urban,Manager,117062,0 +2744,Male,49,High School,1,33,58,51,26,2.0,4,36,Urban,Data Analyst,139321,0 +2745,Female,39,Bachelors,9,58,96,29,16,2.0,3,73,Urban,Data Analyst,108783,1 +2746,Female,46,Masters,0,88,47,46,92,4.0,4,49,Rural,Manager,121306,0 +2747,Male,49,Diploma,15,1,47,21,57,2.0,2,59,Rural,HR Executive,53559,0 +2748,Male,31,Bachelors,0,34,58,60,64,8.0,5,51,Rural,ML Engineer,80638,0 +2749,Female,45,Bachelors,16,53,85,90,37,1.0,2,44,Urban,Software Engineer,87957,1 +2750,Female,49,Masters,15,84,35,12,7,1.0,5,43,Rural,Data Analyst,117002,0 +2751,Male,38,Masters,8,25,70,86,32,8.0,4,58,Urban,ML Engineer,143930,1 +2752,Female,49,Diploma,3,20,96,61,64,0.0,6,21,Urban,Software Engineer,102683,0 +2753,Male,59,Bachelors,1,97,38,52,65,6.0,6,81,Urban,Manager,24751,1 +2754,Male,50,Bachelors,12,15,19,58,85,0.0,5,77,Semi-Urban,Manager,138078,0 +2755,Female,42,Bachelors,2,57,29,31,62,3.0,3,66,Urban,HR Executive,51872,0 +2756,Male,52,Bachelors,7,38,23,37,44,0.0,4,88,Urban,HR Executive,86980,0 +2757,Male,55,Masters,12,74,40,61,85,2.0,4,61,Urban,ML Engineer,25607,1 +2758,Female,57,Bachelors,12,99,71,98,18,7.0,0,45,Semi-Urban,Software Engineer,141999,1 +2759,Female,49,Diploma,5,0,95,10,61,3.0,7,55,Semi-Urban,HR Executive,82704,0 +2760,Male,42,Masters,13,52,51,49,71,8.0,0,78,Urban,ML Engineer,29227,0 +2761,Male,23,Masters,9,20,23,75,66,9.0,6,18,Semi-Urban,ML Engineer,95924,0 +2762,Male,33,Bachelors,14,89,7,4,27,2.0,0,74,Urban,Manager,100568,0 +2763,Female,22,PhD,5,96,62,66,17,5.0,5,65,Urban,Data Analyst,93192,1 +2764,Male,29,High School,14,49,12,46,13,1.0,6,96,Semi-Urban,HR Executive,129900,0 +2765,Male,59,Bachelors,15,71,47,10,22,2.0,6,55,Semi-Urban,Manager,105096,0 +2766,Other,21,Bachelors,7,57,30,38,15,8.0,3,69,Urban,Manager,135745,0 +2767,Male,57,Bachelors,6,66,11,58,70,3.0,2,25,Semi-Urban,ML Engineer,114988,0 +2768,Male,37,Masters,0,40,23,67,59,7.0,6,44,Semi-Urban,Manager,59530,0 +2769,Male,31,PhD,7,42,45,16,85,8.0,4,68,Urban,Data Analyst,149809,0 +2770,Female,31,Bachelors,15,10,30,19,27,4.0,1,85,Urban,Software Engineer,79895,0 +2771,Male,22,High School,7,9,67,73,42,5.0,2,62,Rural,ML Engineer,106564,0 +2772,Male,28,Diploma,14,28,56,56,28,0.0,4,44,Urban,ML Engineer,89491,0 +2773,Female,34,High School,12,84,60,71,77,3.0,5,93,Semi-Urban,ML Engineer,45599,1 +2774,Male,24,Diploma,2,59,10,9,55,5.0,1,52,Rural,HR Executive,147362,0 +2775,Male,36,Bachelors,7,17,61,1,42,3.0,7,71,Urban,Manager,70393,0 +2776,Male,27,Masters,5,40,37,20,25,9.0,5,80,Urban,ML Engineer,35752,0 +2777,Male,53,High School,1,67,78,55,76,4.0,3,53,Semi-Urban,HR Executive,128937,1 +2778,Male,45,Bachelors,5,14,54,98,55,0.0,6,29,Semi-Urban,HR Executive,27141,0 +2779,Male,26,Bachelors,5,82,22,0,24,8.0,7,18,Semi-Urban,Data Analyst,130986,0 +2780,Male,28,Diploma,16,44,51,70,92,9.0,4,33,Urban,Data Analyst,118907,0 +2781,Male,50,Bachelors,15,30,5,46,46,9.0,2,20,Semi-Urban,Data Analyst,94588,0 +2782,Female,27,High School,19,99,67,23,77,5.0,0,32,Rural,Software Engineer,135967,0 +2783,Other,39,Bachelors,9,80,70,1,99,9.0,6,3,Urban,HR Executive,74728,0 +2784,Female,23,Masters,18,83,84,89,83,5.0,6,2,Semi-Urban,Software Engineer,78078,1 +2785,Female,30,Bachelors,2,4,54,71,93,3.0,5,45,Urban,ML Engineer,55096,0 +2786,Male,51,Bachelors,13,77,42,89,75,1.0,1,92,Semi-Urban,ML Engineer,111110,1 +2787,Other,33,Bachelors,13,65,27,64,60,6.0,4,32,Urban,HR Executive,20515,0 +2788,Male,51,Diploma,14,8,77,80,57,1.0,5,99,Urban,Manager,124674,1 +2789,Other,29,Bachelors,11,87,55,40,3,4.0,2,99,Semi-Urban,Data Analyst,112931,1 +2790,Other,39,Bachelors,15,19,74,68,97,7.0,3,98,Rural,Manager,44462,1 +2791,Female,47,PhD,2,69,74,56,37,2.0,1,81,Semi-Urban,HR Executive,100709,1 +2792,Other,54,High School,18,59,28,79,91,3.0,7,67,Semi-Urban,Data Analyst,118019,0 +2793,Male,56,Bachelors,3,50,42,74,14,3.0,5,43,Urban,ML Engineer,84058,0 +2794,Male,39,Bachelors,13,10,71,87,19,9.0,4,1,Urban,Manager,103330,0 +2795,Male,38,Bachelors,16,27,97,28,95,2.0,0,0,Semi-Urban,Software Engineer,110937,0 +2796,Male,21,PhD,1,27,57,61,77,4.0,7,6,Urban,ML Engineer,119862,0 +2797,Male,49,High School,2,52,7,46,0,4.0,5,34,Rural,ML Engineer,74268,0 +2798,Female,32,Diploma,7,36,61,9,48,8.0,2,63,Semi-Urban,Data Analyst,102132,0 +2799,Other,26,Masters,4,40,54,19,86,1.0,6,45,Semi-Urban,Manager,100020,0 +2800,Male,39,Bachelors,1,85,27,57,9,9.0,7,81,Urban,ML Engineer,54886,1 +2801,Female,46,Masters,0,16,36,76,19,2.0,2,54,Urban,ML Engineer,57201,0 +2802,Female,58,Bachelors,10,61,41,16,46,3.0,1,87,Urban,ML Engineer,133122,0 +2803,Female,45,Masters,14,92,38,54,43,2.0,1,54,Rural,ML Engineer,103484,0 +2804,Other,37,Masters,9,49,43,22,78,3.0,2,18,Rural,Software Engineer,52999,0 +2805,Male,32,Diploma,14,28,84,61,86,6.0,6,83,Semi-Urban,Data Analyst,77907,1 +2806,Other,40,PhD,13,54,81,86,11,6.0,2,37,Rural,Software Engineer,49544,1 +2807,Female,48,PhD,16,57,49,88,89,5.0,5,14,Urban,Data Analyst,134397,0 +2808,Male,26,Bachelors,13,93,77,17,23,2.0,5,91,Semi-Urban,Software Engineer,24008,1 +2809,Male,43,Bachelors,19,89,63,49,99,5.0,2,74,Urban,Data Analyst,146257,1 +2810,Female,51,High School,15,99,85,83,13,1.0,2,97,Urban,Data Analyst,33881,1 +2811,Male,22,Masters,8,84,71,28,42,5.0,2,2,Urban,Data Analyst,113390,0 +2812,Female,53,High School,1,49,61,58,43,6.0,1,0,Rural,ML Engineer,72815,0 +2813,Female,29,Masters,1,12,48,22,29,8.0,5,85,Urban,Software Engineer,143373,0 +2814,Male,46,Diploma,1,59,25,9,4,5.0,7,67,Urban,HR Executive,43418,0 +2815,Male,37,PhD,18,5,96,41,83,8.0,4,56,Rural,Software Engineer,141261,0 +2816,Female,37,Diploma,5,50,7,99,15,6.0,5,6,Rural,ML Engineer,127164,0 +2817,Male,50,Diploma,18,47,65,11,77,5.0,5,41,Urban,HR Executive,72113,0 +2818,Male,57,Diploma,19,5,18,37,5,9.0,0,53,Urban,Data Analyst,103193,0 +2819,Male,50,Diploma,9,41,17,46,4,6.0,7,46,Urban,Software Engineer,31690,0 +2820,Male,36,Bachelors,18,58,45,80,98,4.0,6,10,Rural,Manager,137583,0 +2821,Female,41,Masters,8,14,82,86,20,3.0,2,37,Urban,Manager,25169,0 +2822,Male,38,Diploma,19,75,46,87,20,9.0,7,54,Urban,HR Executive,40709,1 +2823,Female,47,High School,3,41,27,10,44,3.0,7,67,Urban,HR Executive,74605,0 +2824,Male,25,Bachelors,4,89,47,94,11,0.0,6,31,Rural,ML Engineer,26998,1 +2825,Male,33,Bachelors,5,86,80,89,23,5.0,5,14,Urban,Manager,88794,1 +2826,Female,46,Bachelors,9,27,12,75,31,3.0,1,69,Urban,Manager,38388,0 +2827,Female,40,High School,11,7,64,14,66,3.0,2,0,Semi-Urban,Manager,88456,0 +2828,Male,25,Bachelors,11,91,98,50,23,6.0,5,44,Urban,Manager,108841,1 +2829,Male,33,Bachelors,0,89,45,56,7,5.0,1,82,Urban,Software Engineer,118877,1 +2830,Male,57,High School,3,50,46,86,28,1.0,7,38,Semi-Urban,Data Analyst,22693,0 +2831,Male,46,Bachelors,8,40,91,84,36,4.0,6,0,Rural,HR Executive,76720,0 +2832,Female,35,High School,1,29,10,34,51,1.0,3,98,Urban,ML Engineer,98031,0 +2833,Male,29,PhD,8,23,25,85,0,6.0,0,75,Semi-Urban,Manager,144740,0 +2834,Male,43,Bachelors,17,69,22,26,24,6.0,7,32,Semi-Urban,HR Executive,48151,0 +2835,Male,41,Diploma,9,19,11,73,90,3.0,1,36,Semi-Urban,Data Analyst,130952,0 +2836,Female,56,Diploma,0,11,25,21,61,4.0,4,0,Rural,HR Executive,99546,0 +2837,Other,54,PhD,8,44,62,18,73,5.0,6,47,Urban,ML Engineer,137073,0 +2838,Male,22,Masters,17,49,58,0,39,3.0,3,51,Urban,HR Executive,46549,0 +2839,Female,38,Diploma,13,20,43,25,33,2.0,2,50,Urban,Data Analyst,71788,0 +2840,Male,47,Bachelors,0,7,65,46,39,4.0,1,78,Urban,ML Engineer,59687,0 +2841,Male,21,Bachelors,0,89,51,3,99,2.0,5,16,Urban,Manager,86498,0 +2842,Female,40,Masters,0,0,73,20,61,4.0,7,99,Semi-Urban,HR Executive,36474,0 +2843,Female,43,Bachelors,10,72,3,45,9,5.0,1,51,Urban,HR Executive,147277,0 +2844,Other,58,Bachelors,3,94,77,16,3,8.0,3,17,Semi-Urban,Data Analyst,59759,0 +2845,Male,59,High School,19,71,70,92,89,4.0,4,93,Urban,Manager,73805,1 +2846,Male,48,High School,5,47,57,24,28,6.0,6,59,Rural,Data Analyst,108200,0 +2847,Female,49,Bachelors,18,71,9,29,8,2.0,2,94,Rural,Manager,117261,0 +2848,Male,53,Masters,14,22,65,5,78,8.0,4,15,Rural,Software Engineer,122953,0 +2849,Male,25,Diploma,17,67,84,29,92,1.0,2,53,Rural,ML Engineer,70310,0 +2850,Male,54,High School,1,67,10,93,93,8.0,7,50,Urban,ML Engineer,67193,0 +2851,Female,28,Masters,15,70,18,3,14,4.0,7,96,Semi-Urban,Software Engineer,74069,0 +2852,Male,55,Bachelors,19,76,63,43,40,8.0,2,88,Urban,Manager,71471,1 +2853,Male,39,PhD,10,17,92,20,32,7.0,2,98,Semi-Urban,Data Analyst,52515,0 +2854,Female,31,Bachelors,5,18,81,84,80,2.0,0,91,Urban,ML Engineer,43981,1 +2855,Male,50,Bachelors,19,49,68,79,1,7.0,0,69,Urban,Manager,33531,1 +2856,Male,21,Diploma,13,33,63,97,11,9.0,2,21,Urban,Software Engineer,40071,0 +2857,Male,37,High School,10,0,73,22,25,7.0,6,84,Urban,HR Executive,106104,0 +2858,Male,30,High School,0,19,77,19,79,0.0,6,75,Semi-Urban,Manager,96609,0 +2859,Male,32,High School,10,94,98,0,70,3.0,2,18,Semi-Urban,Data Analyst,53547,0 +2860,Male,56,Masters,2,3,26,42,58,1.0,6,14,Urban,Manager,29154,0 +2861,Female,50,Bachelors,18,88,55,39,21,3.0,0,91,Urban,Data Analyst,70764,1 +2862,Male,28,Diploma,19,22,42,56,99,1.0,6,25,Urban,Data Analyst,117694,0 +2863,Other,53,Bachelors,3,33,46,62,37,3.0,7,29,Urban,HR Executive,142155,0 +2864,Male,33,High School,7,14,11,17,61,3.0,6,43,Rural,ML Engineer,104911,0 +2865,Male,54,Masters,3,64,41,6,21,7.0,4,14,Rural,Data Analyst,100773,0 +2866,Male,42,Bachelors,9,12,98,67,13,3.0,0,5,Rural,Manager,71485,0 +2867,Male,36,Diploma,0,93,97,6,62,0.0,2,58,Urban,Manager,69198,1 +2868,Female,30,Diploma,2,74,34,1,95,8.0,7,54,Urban,HR Executive,103977,0 +2869,Male,46,Bachelors,0,54,88,11,94,1.0,7,65,Semi-Urban,ML Engineer,60064,0 +2870,Male,45,Bachelors,6,93,61,16,64,0.0,5,27,Urban,ML Engineer,63620,0 +2871,Female,57,Bachelors,13,37,38,24,99,8.0,4,47,Semi-Urban,Software Engineer,50844,0 +2872,Female,33,Masters,14,7,95,4,50,8.0,1,64,Semi-Urban,Manager,77009,0 +2873,Female,23,High School,8,34,36,52,46,6.0,1,63,Semi-Urban,HR Executive,79032,0 +2874,Male,49,Masters,13,2,28,19,53,1.0,7,65,Urban,Data Analyst,64895,0 +2875,Female,24,Diploma,0,39,13,66,79,8.0,1,69,Rural,Manager,90891,0 +2876,Male,58,Masters,14,8,30,89,39,8.0,0,62,Semi-Urban,Data Analyst,26971,0 +2877,Male,42,Bachelors,15,37,29,38,40,3.0,5,72,Urban,ML Engineer,40488,0 +2878,Male,34,Diploma,3,0,18,97,31,9.0,1,52,Rural,HR Executive,91030,0 +2879,Male,21,PhD,6,18,55,63,50,9.0,2,39,Urban,ML Engineer,103098,0 +2880,Male,56,Bachelors,7,10,36,74,27,7.0,7,22,Urban,HR Executive,72000,0 +2881,Male,44,Bachelors,5,56,62,90,58,8.0,7,62,Semi-Urban,Software Engineer,90674,1 +2882,Female,29,Bachelors,6,37,61,75,72,8.0,4,30,Urban,HR Executive,40390,0 +2883,Male,39,Bachelors,9,57,71,95,79,8.0,1,70,Urban,Data Analyst,59565,1 +2884,Male,28,PhD,15,11,10,83,14,1.0,1,44,Urban,ML Engineer,118091,0 +2885,Male,22,High School,0,4,0,53,72,9.0,1,31,Urban,Manager,21419,0 +2886,Female,50,Bachelors,13,50,58,73,10,0.0,6,94,Semi-Urban,HR Executive,137499,1 +2887,Male,50,High School,17,14,97,52,4,9.0,2,2,Semi-Urban,Manager,89550,0 +2888,Male,21,Masters,3,91,85,87,26,4.0,0,90,Urban,ML Engineer,30896,1 +2889,Female,47,Diploma,15,96,69,56,23,0.0,2,7,Urban,Data Analyst,37566,0 +2890,Female,58,PhD,6,28,33,33,75,6.0,1,39,Urban,Manager,93721,0 +2891,Male,21,Bachelors,14,28,45,5,46,9.0,0,19,Semi-Urban,Manager,68587,0 +2892,Female,51,Bachelors,0,62,78,18,81,0.0,7,38,Urban,Software Engineer,139066,0 +2893,Female,56,Bachelors,12,45,34,25,25,1.0,2,74,Semi-Urban,Software Engineer,73952,0 +2894,Female,29,Diploma,9,11,7,12,78,9.0,4,30,Urban,Data Analyst,58131,0 +2895,Male,23,Bachelors,4,87,13,89,44,7.0,0,7,Urban,Software Engineer,62356,0 +2896,Female,43,Diploma,4,17,33,25,83,3.0,5,89,Semi-Urban,Data Analyst,97614,0 +2897,Male,28,Bachelors,3,46,79,41,88,0.0,2,0,Semi-Urban,HR Executive,94066,0 +2898,Male,34,High School,7,54,11,53,94,4.0,5,77,Urban,Manager,92587,0 +2899,Male,58,Bachelors,2,2,42,60,18,2.0,7,11,Semi-Urban,ML Engineer,78395,0 +2900,Male,33,High School,4,10,54,88,27,9.0,3,6,Semi-Urban,Data Analyst,77304,0 +2901,Male,32,Bachelors,4,65,83,43,18,3.0,1,55,Semi-Urban,Manager,35732,1 +2902,Female,59,PhD,2,78,30,62,24,9.0,2,17,Urban,HR Executive,41435,0 +2903,Male,31,Diploma,14,79,92,60,7,1.0,3,0,Urban,Data Analyst,34738,0 +2904,Male,32,Diploma,0,27,64,63,71,7.0,0,98,Rural,Data Analyst,82883,1 +2905,Male,34,Masters,15,85,46,36,18,8.0,6,94,Rural,Manager,46628,1 +2906,Male,32,Bachelors,16,42,23,18,28,9.0,4,29,Urban,HR Executive,135729,0 +2907,Other,59,Bachelors,14,67,79,67,13,4.0,1,77,Urban,Data Analyst,21395,1 +2908,Male,29,Masters,12,39,90,5,66,6.0,2,16,Rural,ML Engineer,93490,0 +2909,Male,43,Masters,19,55,18,93,48,2.0,6,60,Semi-Urban,Data Analyst,88062,0 +2910,Male,40,Bachelors,8,36,80,55,86,6.0,5,11,Urban,Manager,109306,0 +2911,Male,55,Masters,14,14,39,81,47,4.0,5,82,Rural,HR Executive,89052,0 +2912,Male,47,Masters,4,93,5,9,28,5.0,0,75,Urban,Manager,103432,0 +2913,Female,54,High School,15,19,16,70,40,9.0,0,0,Semi-Urban,ML Engineer,82606,0 +2914,Other,56,Bachelors,8,97,88,9,66,1.0,4,60,Urban,Software Engineer,89842,1 +2915,Male,22,PhD,13,17,61,47,9,7.0,2,47,Semi-Urban,Manager,38420,0 +2916,Female,35,Bachelors,0,25,33,40,6,2.0,0,6,Urban,Data Analyst,45128,0 +2917,Female,41,Diploma,9,6,27,27,67,4.0,4,59,Urban,Data Analyst,134413,0 +2918,Female,55,Bachelors,11,64,7,89,7,5.0,7,55,Rural,ML Engineer,22621,0 +2919,Male,33,Masters,3,44,35,48,24,6.0,5,65,Rural,Data Analyst,45201,0 +2920,Male,54,Bachelors,1,28,22,70,48,6.0,1,99,Urban,ML Engineer,41620,0 +2921,Male,45,Diploma,6,50,96,64,76,6.0,5,87,Semi-Urban,Software Engineer,142129,1 +2922,Female,42,Bachelors,4,78,49,42,22,7.0,7,85,Urban,ML Engineer,86000,1 +2923,Female,49,Diploma,7,44,32,97,98,3.0,5,37,Urban,ML Engineer,124147,0 +2924,Male,24,Bachelors,12,98,90,19,90,7.0,1,41,Rural,Manager,57062,1 +2925,Male,36,Bachelors,10,6,22,45,85,5.0,1,94,Semi-Urban,Software Engineer,95131,0 +2926,Female,48,Masters,2,44,4,94,12,8.0,0,89,Urban,ML Engineer,137191,0 +2927,Female,42,Bachelors,0,24,23,64,2,1.0,0,28,Urban,Software Engineer,24220,0 +2928,Other,33,Bachelors,2,81,48,47,54,9.0,1,37,Rural,HR Executive,96001,0 +2929,Female,58,Bachelors,1,59,47,25,71,2.0,5,42,Urban,Software Engineer,140807,0 +2930,Male,38,Bachelors,6,48,19,46,45,9.0,2,14,Urban,ML Engineer,33191,0 +2931,Male,49,Bachelors,5,11,62,89,18,5.0,6,79,Rural,Software Engineer,107706,1 +2932,Female,41,Bachelors,9,67,96,24,31,0.0,6,27,Semi-Urban,HR Executive,64061,0 +2933,Male,33,Bachelors,9,50,80,77,40,0.0,1,87,Rural,HR Executive,147849,1 +2934,Male,47,Bachelors,15,93,19,71,34,5.0,7,20,Urban,Manager,111936,0 +2935,Female,25,Bachelors,15,36,92,13,19,5.0,5,74,Semi-Urban,HR Executive,28940,0 +2936,Male,29,Masters,3,26,13,30,66,6.0,7,67,Urban,Manager,72214,0 +2937,Female,36,Bachelors,15,66,67,53,21,8.0,5,18,Urban,ML Engineer,90533,0 +2938,Male,39,Bachelors,5,10,53,40,75,1.0,4,40,Urban,ML Engineer,118344,0 +2939,Other,43,PhD,5,78,14,47,43,5.0,2,17,Semi-Urban,Software Engineer,149385,0 +2940,Male,52,Diploma,6,31,0,15,84,1.0,2,99,Urban,ML Engineer,93570,0 +2941,Male,23,Masters,1,90,21,77,20,6.0,6,53,Urban,HR Executive,46795,1 +2942,Female,32,High School,7,76,21,57,84,6.0,5,42,Urban,Data Analyst,59285,0 +2943,Male,28,Diploma,13,34,79,25,82,0.0,2,74,Rural,Data Analyst,111606,0 +2944,Female,37,Diploma,10,9,73,92,63,2.0,1,49,Semi-Urban,Software Engineer,89183,0 +2945,Female,31,High School,4,2,94,28,14,2.0,2,55,Urban,ML Engineer,26842,0 +2946,Male,53,High School,5,45,14,1,85,2.0,4,94,Rural,HR Executive,36492,0 +2947,Male,56,Bachelors,6,88,0,46,73,3.0,7,19,Urban,Data Analyst,111159,0 +2948,Male,47,Diploma,4,58,59,48,24,1.0,7,19,Semi-Urban,Manager,96974,0 +2949,Male,51,Bachelors,18,99,93,51,16,9.0,7,52,Rural,Data Analyst,146120,1 +2950,Female,29,Bachelors,6,82,71,18,20,2.0,2,90,Urban,Software Engineer,116095,1 +2951,Female,39,Diploma,16,60,8,36,42,2.0,0,92,Urban,Software Engineer,46664,0 +2952,Female,45,Diploma,19,89,18,18,6,8.0,2,24,Urban,Manager,24822,0 +2953,Female,39,Bachelors,3,98,58,83,70,2.0,5,11,Rural,Data Analyst,37537,1 +2954,Male,58,Masters,17,50,57,10,74,7.0,3,14,Semi-Urban,Manager,122388,0 +2955,Female,30,Bachelors,10,2,39,16,23,9.0,7,44,Urban,HR Executive,20176,0 +2956,Female,58,Diploma,3,69,40,40,45,2.0,4,49,Rural,ML Engineer,112543,0 +2957,Female,29,Bachelors,11,26,95,42,76,5.0,7,87,Urban,Manager,137763,1 +2958,Female,28,Masters,17,0,21,0,87,7.0,4,97,Urban,ML Engineer,95190,0 +2959,Male,21,High School,3,55,87,84,22,9.0,1,35,Urban,Software Engineer,105187,1 +2960,Female,41,Bachelors,12,21,4,34,44,2.0,2,88,Urban,Manager,70181,0 +2961,Male,24,PhD,4,53,73,5,69,8.0,2,1,Urban,ML Engineer,124647,0 +2962,Male,38,Diploma,18,41,7,72,52,5.0,0,70,Urban,Software Engineer,141527,0 +2963,Male,34,Diploma,3,60,32,69,63,3.0,6,53,Semi-Urban,Software Engineer,97245,0 +2964,Other,40,Masters,19,18,20,5,18,7.0,5,39,Urban,ML Engineer,37070,0 +2965,Female,56,Diploma,5,46,4,29,47,0.0,4,10,Urban,HR Executive,83099,0 +2966,Female,22,Bachelors,16,33,16,62,61,4.0,6,87,Urban,ML Engineer,24384,0 +2967,Female,35,High School,17,2,52,5,83,5.0,0,5,Urban,Data Analyst,62489,0 +2968,Male,38,High School,16,12,47,58,89,0.0,2,30,Rural,Manager,33354,0 +2969,Female,45,Masters,13,86,44,72,17,0.0,7,73,Rural,Software Engineer,39645,1 +2970,Male,50,Diploma,3,87,30,28,68,7.0,5,35,Semi-Urban,ML Engineer,136501,0 +2971,Male,55,Masters,0,54,86,68,49,7.0,5,72,Urban,ML Engineer,71792,1 +2972,Male,28,Masters,5,93,77,94,97,2.0,0,51,Urban,HR Executive,53530,1 +2973,Female,50,Diploma,18,70,8,52,72,8.0,7,79,Urban,Manager,40545,0 +2974,Female,45,Bachelors,9,57,12,20,54,2.0,1,87,Semi-Urban,Data Analyst,137042,0 +2975,Male,27,Bachelors,9,64,62,45,27,9.0,1,39,Urban,ML Engineer,118969,0 +2976,Male,37,High School,9,74,38,1,80,8.0,2,10,Rural,Data Analyst,58178,0 +2977,Female,52,Diploma,7,51,48,50,38,8.0,7,72,Urban,HR Executive,129740,0 +2978,Male,45,Bachelors,10,36,87,42,59,4.0,4,32,Urban,Data Analyst,23911,0 +2979,Female,48,High School,10,66,86,27,97,4.0,6,96,Semi-Urban,Software Engineer,67920,1 +2980,Other,58,Masters,10,13,45,96,22,9.0,5,28,Urban,HR Executive,144993,0 +2981,Male,28,Bachelors,7,76,5,34,80,4.0,2,18,Urban,Software Engineer,31492,0 +2982,Male,42,High School,9,77,72,43,71,7.0,0,44,Urban,ML Engineer,131297,1 +2983,Female,58,Bachelors,7,65,85,84,17,7.0,6,75,Urban,Software Engineer,113487,1 +2984,Female,26,Bachelors,18,37,18,18,47,2.0,7,69,Semi-Urban,Data Analyst,120594,0 +2985,Male,32,Bachelors,14,89,64,99,1,7.0,7,80,Urban,Manager,137506,1 +2986,Other,49,Masters,1,52,25,25,17,8.0,4,91,Rural,ML Engineer,135254,0 +2987,Male,50,Bachelors,12,99,38,73,70,3.0,1,81,Semi-Urban,Data Analyst,44656,1 +2988,Male,52,Bachelors,8,58,28,76,2,2.0,1,42,Semi-Urban,Data Analyst,51545,0 +2989,Female,28,Diploma,8,42,29,70,33,4.0,1,51,Semi-Urban,Data Analyst,76988,0 +2990,Female,46,Masters,2,33,43,7,37,1.0,7,75,Urban,Manager,77824,0 +2991,Male,41,Masters,0,95,65,52,32,0.0,6,7,Urban,Manager,115137,0 +2992,Female,56,Bachelors,7,15,68,45,4,3.0,0,5,Urban,Manager,46195,0 +2993,Male,33,Masters,18,86,76,29,39,3.0,4,3,Urban,HR Executive,134455,0 +2994,Male,26,Diploma,5,64,20,62,85,0.0,0,54,Urban,HR Executive,65424,0 +2995,Male,42,Bachelors,11,16,57,1,95,7.0,0,23,Rural,ML Engineer,80973,0 +2996,Female,36,Bachelors,11,15,59,36,50,4.0,5,24,Urban,Data Analyst,120553,0 +2997,Male,38,Bachelors,19,13,15,48,37,5.0,1,3,Urban,Software Engineer,76965,0 +2998,Male,52,Bachelors,5,52,93,2,71,5.0,6,87,Urban,Software Engineer,31054,0 +2999,Male,37,Bachelors,9,79,31,64,45,2.0,2,8,Semi-Urban,Software Engineer,41231,0 +3000,Female,58,Bachelors,0,6,4,28,27,9.0,5,17,Urban,Data Analyst,33069,0 +3001,Female,34,Diploma,9,88,83,83,81,1.0,0,68,Semi-Urban,Data Analyst,50599,1 +3002,Female,37,Bachelors,6,64,64,67,70,8.0,7,37,Semi-Urban,HR Executive,48861,0 +3003,Male,37,Masters,17,75,92,94,71,1.0,4,39,Semi-Urban,ML Engineer,137868,1 +3004,Female,36,Diploma,12,67,9,21,52,2.0,1,44,Urban,Manager,88952,0 +3005,Male,37,High School,9,15,2,33,23,2.0,1,27,Urban,Data Analyst,142225,0 +3006,Female,42,Bachelors,1,82,61,31,9,7.0,7,10,Rural,Manager,97145,0 +3007,Female,48,Diploma,13,81,33,63,13,9.0,7,6,Semi-Urban,Software Engineer,138005,0 +3008,Male,35,Bachelors,0,51,18,60,14,6.0,5,52,Urban,Software Engineer,51716,0 +3009,Female,59,Masters,2,85,17,59,15,5.0,5,94,Urban,Data Analyst,37144,1 +3010,Male,42,PhD,18,14,18,36,89,6.0,6,30,Urban,Data Analyst,104407,0 +3011,Male,41,High School,1,44,11,99,29,2.0,2,92,Urban,ML Engineer,47076,1 +3012,Male,31,High School,17,86,60,57,53,1.0,6,24,Rural,HR Executive,141169,0 +3013,Male,33,Bachelors,7,11,29,21,12,1.0,4,25,Rural,HR Executive,123782,0 +3014,Male,56,Bachelors,7,13,68,79,5,9.0,0,38,Urban,Manager,58198,0 +3015,Female,40,Diploma,11,8,40,70,23,1.0,5,52,Semi-Urban,HR Executive,119563,0 +3016,Male,57,Bachelors,13,24,35,35,63,8.0,3,92,Urban,Software Engineer,140656,0 +3017,Female,26,High School,3,33,63,70,22,2.0,0,6,Rural,Manager,121033,0 +3018,Male,21,Bachelors,9,4,95,96,47,1.0,4,85,Urban,HR Executive,142018,1 +3019,Male,37,Masters,1,90,49,51,43,3.0,2,28,Semi-Urban,Data Analyst,82563,0 +3020,Female,42,Diploma,6,70,87,54,17,7.0,5,15,Urban,Software Engineer,67820,0 +3021,Male,43,Bachelors,17,82,83,90,30,1.0,0,50,Rural,Manager,64473,1 +3022,Male,26,Diploma,15,88,10,87,40,4.0,3,67,Rural,Software Engineer,97802,1 +3023,Female,39,Bachelors,0,66,4,74,20,4.0,5,17,Urban,ML Engineer,37550,0 +3024,Male,50,Bachelors,2,3,29,70,54,7.0,2,87,Urban,Software Engineer,34726,0 +3025,Male,31,Diploma,17,17,85,58,54,4.0,5,29,Semi-Urban,Software Engineer,87883,0 +3026,Male,37,Bachelors,11,28,21,3,39,3.0,3,62,Rural,HR Executive,82544,0 +3027,Female,49,Bachelors,4,35,33,98,13,9.0,5,47,Urban,ML Engineer,59508,0 +3028,Female,39,Bachelors,10,52,45,27,53,7.0,2,10,Urban,Manager,32891,0 +3029,Female,32,Bachelors,10,81,45,22,36,0.0,5,6,Urban,HR Executive,148299,0 +3030,Female,41,Bachelors,17,5,80,75,57,9.0,4,55,Urban,Manager,114580,0 +3031,Male,35,Diploma,5,68,52,80,56,0.0,7,20,Semi-Urban,Software Engineer,94572,0 +3032,Male,50,Bachelors,1,20,91,35,48,8.0,7,36,Urban,Manager,25240,0 +3033,Female,21,PhD,14,41,15,40,97,1.0,2,72,Urban,Data Analyst,146689,0 +3034,Male,37,Diploma,14,24,39,24,16,1.0,3,17,Rural,ML Engineer,103945,0 +3035,Male,50,Diploma,18,24,39,41,81,9.0,4,65,Semi-Urban,Software Engineer,64043,0 +3036,Male,41,Diploma,8,75,38,6,0,8.0,1,92,Urban,HR Executive,60042,0 +3037,Male,48,Bachelors,13,51,51,40,79,1.0,0,8,Urban,Manager,33188,0 +3038,Other,40,Bachelors,3,95,30,60,43,2.0,2,33,Rural,HR Executive,43375,0 +3039,Male,39,Bachelors,2,83,82,8,79,8.0,2,10,Urban,ML Engineer,130495,0 +3040,Male,44,Diploma,8,44,45,42,41,5.0,7,52,Rural,Software Engineer,133340,0 +3041,Male,31,High School,9,95,39,35,60,2.0,5,94,Urban,HR Executive,92395,1 +3042,Other,46,Bachelors,0,35,70,17,87,4.0,7,63,Urban,Manager,40435,0 +3043,Male,37,Diploma,9,59,25,57,70,0.0,3,39,Urban,Data Analyst,130981,0 +3044,Male,46,Bachelors,1,47,59,60,86,1.0,1,51,Rural,HR Executive,125127,0 +3045,Female,58,High School,8,87,11,93,86,8.0,6,77,Semi-Urban,HR Executive,23199,1 +3046,Female,35,Masters,12,58,53,87,46,4.0,4,62,Urban,ML Engineer,48393,1 +3047,Male,33,Bachelors,12,3,96,15,14,2.0,5,41,Urban,ML Engineer,39033,0 +3048,Male,37,Bachelors,4,0,58,53,14,7.0,7,35,Urban,ML Engineer,134743,0 +3049,Male,34,Masters,8,86,5,2,88,8.0,7,84,Urban,Manager,140225,0 +3050,Male,39,Diploma,13,90,12,70,37,7.0,4,35,Urban,Manager,38092,0 +3051,Male,47,Diploma,9,48,49,16,27,6.0,3,9,Urban,Data Analyst,22818,0 +3052,Male,34,Diploma,1,54,53,32,11,9.0,0,85,Urban,ML Engineer,144441,0 +3053,Male,22,Diploma,5,63,56,68,86,6.0,5,97,Semi-Urban,Manager,90434,1 +3054,Male,27,Bachelors,17,76,50,12,80,8.0,7,51,Semi-Urban,HR Executive,54936,0 +3055,Female,21,High School,16,15,19,86,27,3.0,5,9,Rural,Software Engineer,24034,0 +3056,Other,41,Bachelors,0,51,6,43,93,2.0,4,61,Urban,ML Engineer,35786,0 +3057,Female,52,Masters,11,35,24,92,76,9.0,3,89,Urban,HR Executive,117810,0 +3058,Male,59,High School,15,0,75,20,46,4.0,7,2,Urban,Software Engineer,107008,0 +3059,Male,25,Bachelors,1,7,6,14,70,1.0,5,67,Urban,Manager,139924,0 +3060,Other,48,High School,15,15,71,19,74,7.0,1,79,Urban,ML Engineer,98543,0 +3061,Male,58,Bachelors,12,49,31,48,48,2.0,6,93,Urban,HR Executive,26224,0 +3062,Male,31,Bachelors,8,93,11,23,65,1.0,1,27,Urban,ML Engineer,141042,0 +3063,Male,59,Bachelors,6,31,67,2,65,9.0,7,29,Urban,Manager,63634,0 +3064,Female,55,High School,5,62,23,84,4,9.0,0,77,Semi-Urban,Data Analyst,128919,1 +3065,Female,33,Masters,10,14,48,50,28,5.0,0,50,Urban,Software Engineer,33834,0 +3066,Male,47,Bachelors,19,27,94,3,78,8.0,7,63,Urban,Manager,26669,0 +3067,Male,21,Masters,13,21,66,90,8,5.0,7,26,Semi-Urban,Software Engineer,135752,0 +3068,Other,29,Bachelors,1,73,2,85,17,3.0,7,9,Urban,HR Executive,21703,0 +3069,Male,56,Bachelors,8,55,93,19,51,2.0,2,36,Urban,ML Engineer,95806,0 +3070,Female,26,PhD,1,24,76,83,79,8.0,0,69,Urban,Data Analyst,78229,1 +3071,Female,31,Bachelors,2,65,28,30,48,1.0,1,31,Urban,Manager,119556,0 +3072,Female,54,Diploma,13,29,91,32,63,8.0,5,26,Urban,Manager,61054,0 +3073,Male,59,Diploma,4,99,24,24,92,4.0,2,32,Urban,Manager,47461,0 +3074,Male,26,Masters,3,61,95,88,71,2.0,2,62,Urban,Manager,148201,1 +3075,Male,56,Bachelors,12,68,6,16,55,2.0,6,4,Semi-Urban,Manager,88111,0 +3076,Female,23,Masters,19,49,81,68,50,0.0,2,77,Urban,HR Executive,141522,1 +3077,Female,48,Diploma,1,53,83,46,88,3.0,4,33,Semi-Urban,Data Analyst,61080,0 +3078,Male,26,Bachelors,19,90,62,62,14,1.0,4,5,Urban,HR Executive,100794,0 +3079,Male,28,Diploma,17,11,81,41,45,4.0,2,92,Urban,ML Engineer,83751,0 +3080,Female,44,Bachelors,0,28,29,31,80,0.0,0,51,Semi-Urban,Data Analyst,107174,0 +3081,Female,35,Masters,2,60,43,86,0,0.0,1,86,Urban,Software Engineer,109537,1 +3082,Female,48,Bachelors,15,92,70,4,1,4.0,6,80,Semi-Urban,Software Engineer,25087,1 +3083,Male,29,Masters,5,48,30,86,88,4.0,4,83,Semi-Urban,HR Executive,55235,1 +3084,Male,53,Bachelors,0,85,22,4,85,5.0,4,57,Urban,HR Executive,107209,0 +3085,Female,48,Bachelors,7,91,70,18,8,8.0,2,47,Semi-Urban,Manager,55176,0 +3086,Female,30,Masters,7,3,59,29,57,3.0,4,41,Urban,Manager,28901,0 +3087,Male,45,High School,12,61,93,4,42,2.0,7,82,Rural,HR Executive,105100,1 +3088,Male,24,Bachelors,1,12,71,59,24,5.0,0,92,Semi-Urban,Software Engineer,25051,0 +3089,Male,51,Bachelors,15,64,16,73,4,8.0,0,34,Urban,Manager,144273,0 +3090,Male,33,Diploma,0,40,43,7,99,5.0,2,40,Urban,HR Executive,55168,0 +3091,Male,46,Diploma,15,79,35,32,72,8.0,2,67,Urban,HR Executive,41107,0 +3092,Other,55,PhD,4,57,45,43,65,5.0,3,8,Urban,ML Engineer,148439,0 +3093,Male,27,Masters,15,48,65,36,50,1.0,3,77,Urban,Data Analyst,21907,0 +3094,Female,22,Bachelors,17,84,38,87,90,7.0,7,41,Semi-Urban,HR Executive,22449,1 +3095,Male,29,Bachelors,2,23,72,93,39,0.0,3,84,Rural,Manager,94089,1 +3096,Female,58,Bachelors,4,73,26,18,86,5.0,3,7,Urban,Software Engineer,37903,0 +3097,Other,37,High School,9,62,72,3,36,6.0,1,39,Rural,Manager,30199,0 +3098,Male,41,Masters,16,54,56,83,36,9.0,0,18,Semi-Urban,ML Engineer,57088,0 +3099,Male,49,Bachelors,14,69,69,25,16,5.0,0,57,Urban,Manager,83775,0 +3100,Male,52,Masters,6,96,67,8,90,1.0,5,67,Rural,Software Engineer,67841,1 +3101,Male,59,High School,13,24,27,18,78,0.0,3,94,Urban,HR Executive,129468,0 +3102,Female,36,Bachelors,14,45,9,58,89,7.0,0,57,Semi-Urban,Manager,133739,0 +3103,Female,56,Masters,14,2,98,16,62,8.0,6,6,Urban,Data Analyst,110232,0 +3104,Male,28,PhD,17,3,14,28,33,1.0,2,50,Urban,ML Engineer,58003,0 +3105,Male,41,Bachelors,7,64,9,29,25,8.0,3,21,Semi-Urban,Manager,132388,0 +3106,Male,58,Masters,12,61,22,0,30,2.0,7,7,Urban,Manager,76943,0 +3107,Female,27,Bachelors,16,34,21,51,95,4.0,1,36,Urban,ML Engineer,120904,0 +3108,Male,33,High School,13,22,12,70,7,3.0,1,70,Urban,Data Analyst,121838,0 +3109,Male,41,Masters,18,17,49,27,76,6.0,3,65,Urban,Data Analyst,95931,0 +3110,Female,25,Bachelors,15,48,82,6,57,9.0,1,86,Urban,Data Analyst,100481,0 +3111,Female,25,Masters,2,5,21,59,1,3.0,5,45,Urban,Software Engineer,79690,0 +3112,Male,48,Masters,7,33,23,82,91,7.0,4,47,Urban,HR Executive,125151,0 +3113,Female,53,PhD,17,15,33,98,47,8.0,0,42,Semi-Urban,Data Analyst,20866,0 +3114,Male,24,Masters,17,27,8,85,55,4.0,3,93,Semi-Urban,HR Executive,143509,0 +3115,Male,40,Masters,10,43,15,89,49,8.0,2,86,Urban,HR Executive,141474,0 +3116,Female,57,Bachelors,6,81,19,42,66,2.0,5,17,Rural,ML Engineer,69205,0 +3117,Female,56,Bachelors,15,35,2,76,27,4.0,6,31,Urban,ML Engineer,24466,0 +3118,Male,57,Bachelors,10,15,56,0,43,7.0,6,93,Urban,ML Engineer,21293,0 +3119,Male,58,Bachelors,3,99,52,93,72,0.0,4,98,Urban,Manager,50372,1 +3120,Male,29,Bachelors,18,73,24,44,94,0.0,4,22,Urban,Data Analyst,56863,0 +3121,Male,55,High School,10,2,85,36,10,1.0,7,48,Semi-Urban,Manager,51009,0 +3122,Male,52,Diploma,3,63,47,98,65,0.0,1,77,Semi-Urban,Manager,99142,1 +3123,Male,53,Diploma,2,77,83,94,20,0.0,2,97,Semi-Urban,Data Analyst,29682,1 +3124,Male,47,High School,5,8,1,59,77,2.0,7,80,Rural,HR Executive,26824,0 +3125,Female,58,Masters,6,24,14,23,21,6.0,0,95,Urban,Software Engineer,110132,0 +3126,Female,53,Diploma,17,87,66,49,39,6.0,5,84,Semi-Urban,ML Engineer,68828,1 +3127,Female,56,Diploma,19,96,21,92,29,7.0,5,16,Urban,Manager,60127,0 +3128,Male,44,Diploma,10,83,78,71,58,8.0,7,50,Semi-Urban,ML Engineer,135550,1 +3129,Other,37,Bachelors,15,99,58,24,8,6.0,6,15,Semi-Urban,HR Executive,53189,0 +3130,Female,31,High School,0,40,6,24,98,3.0,1,9,Semi-Urban,ML Engineer,39695,0 +3131,Female,54,Masters,18,46,73,4,45,8.0,2,79,Urban,ML Engineer,101760,0 +3132,Female,38,Diploma,8,90,77,39,45,4.0,2,79,Urban,ML Engineer,86400,1 +3133,Female,41,Masters,8,82,10,62,66,9.0,5,16,Urban,Software Engineer,133285,0 +3134,Male,39,Bachelors,15,94,37,49,82,5.0,4,19,Urban,Software Engineer,86005,0 +3135,Male,55,Masters,14,23,56,87,92,1.0,5,99,Semi-Urban,Data Analyst,146708,1 +3136,Female,39,PhD,0,36,2,79,55,4.0,5,39,Urban,ML Engineer,55778,0 +3137,Female,59,Bachelors,13,51,64,51,40,8.0,6,12,Urban,HR Executive,46788,0 +3138,Female,54,Bachelors,6,64,27,49,73,1.0,7,1,Rural,Manager,132579,0 +3139,Male,23,Masters,0,38,87,47,19,1.0,6,75,Urban,HR Executive,109243,1 +3140,Male,46,Diploma,7,31,68,25,1,5.0,6,74,Urban,Software Engineer,44645,0 +3141,Male,47,Diploma,16,86,70,92,2,3.0,3,17,Urban,Manager,109300,1 +3142,Female,23,Diploma,15,6,73,43,55,4.0,6,82,Rural,HR Executive,87327,0 +3143,Male,27,Masters,11,21,69,18,56,0.0,7,93,Urban,HR Executive,31255,0 +3144,Male,23,PhD,4,55,54,38,57,6.0,2,48,Urban,Software Engineer,118563,0 +3145,Male,41,Bachelors,19,48,96,88,20,1.0,1,5,Urban,HR Executive,43197,1 +3146,Male,57,Diploma,9,11,23,98,94,8.0,2,7,Urban,ML Engineer,24767,0 +3147,Female,38,Bachelors,13,78,89,22,64,6.0,1,2,Semi-Urban,HR Executive,26197,0 +3148,Female,47,PhD,14,57,43,20,78,7.0,6,99,Semi-Urban,Data Analyst,53495,0 +3149,Female,30,Bachelors,2,15,60,80,30,5.0,1,56,Rural,ML Engineer,106912,0 +3150,Male,23,Diploma,1,36,68,29,70,1.0,7,32,Semi-Urban,Manager,29797,0 +3151,Female,45,Diploma,16,99,25,27,12,8.0,4,58,Urban,ML Engineer,147658,0 +3152,Male,51,Bachelors,16,8,43,22,36,2.0,7,68,Semi-Urban,Software Engineer,135513,0 +3153,Female,53,Bachelors,2,6,11,15,10,7.0,0,64,Semi-Urban,HR Executive,112976,0 +3154,Male,40,Bachelors,19,53,96,23,83,2.0,0,3,Urban,ML Engineer,68247,0 +3155,Male,32,High School,15,8,88,56,96,8.0,6,28,Urban,Software Engineer,103199,0 +3156,Female,50,Bachelors,14,48,80,16,96,8.0,7,34,Semi-Urban,Software Engineer,86085,0 +3157,Female,54,Masters,14,98,92,80,63,8.0,5,90,Urban,Data Analyst,142629,1 +3158,Male,54,Masters,8,17,59,41,9,1.0,7,85,Semi-Urban,Manager,143599,0 +3159,Female,29,Bachelors,17,87,78,68,42,0.0,2,91,Semi-Urban,HR Executive,140160,1 +3160,Male,25,Masters,9,97,83,7,77,7.0,3,67,Semi-Urban,Software Engineer,50921,1 +3161,Male,44,Masters,15,54,92,1,20,4.0,2,59,Rural,Manager,24272,0 +3162,Male,25,Diploma,17,34,12,70,34,4.0,2,90,Urban,ML Engineer,88487,0 +3163,Male,27,Bachelors,19,47,75,49,39,4.0,5,68,Rural,ML Engineer,84338,1 +3164,Male,53,Masters,13,29,16,85,3,3.0,4,23,Urban,Manager,146078,0 +3165,Male,27,Bachelors,11,0,80,98,11,5.0,0,77,Urban,Software Engineer,43099,1 +3166,Male,33,Diploma,1,29,91,9,0,7.0,3,68,Urban,Manager,133606,0 +3167,Female,24,Bachelors,19,52,83,17,4,2.0,4,65,Urban,Manager,102092,0 +3168,Male,38,Bachelors,8,82,84,8,26,1.0,5,74,Rural,ML Engineer,95060,1 +3169,Female,47,Bachelors,4,58,63,29,39,8.0,3,95,Urban,ML Engineer,79008,1 +3170,Male,48,Bachelors,14,77,0,64,59,6.0,2,69,Semi-Urban,Software Engineer,95666,0 +3171,Female,44,Diploma,2,89,66,42,26,7.0,0,13,Urban,Data Analyst,126104,0 +3172,Male,34,Masters,7,91,2,13,5,0.0,3,41,Urban,HR Executive,101680,0 +3173,Male,32,Bachelors,6,69,72,84,38,7.0,2,92,Urban,ML Engineer,120387,1 +3174,Male,29,Bachelors,7,5,40,32,55,8.0,3,90,Rural,HR Executive,63928,0 +3175,Male,33,Bachelors,16,87,66,64,77,9.0,0,69,Urban,HR Executive,131724,1 +3176,Male,47,PhD,18,11,86,26,92,5.0,0,85,Urban,HR Executive,103587,0 +3177,Female,28,Masters,19,9,97,48,53,5.0,0,65,Urban,Data Analyst,54980,0 +3178,Female,30,Masters,6,89,82,83,33,2.0,0,57,Rural,HR Executive,33749,1 +3179,Female,25,Bachelors,10,93,70,44,9,7.0,5,5,Urban,HR Executive,139476,0 +3180,Female,53,Bachelors,7,60,15,75,72,9.0,5,0,Urban,HR Executive,52938,0 +3181,Male,32,PhD,14,41,47,8,72,5.0,6,73,Rural,Software Engineer,101408,0 +3182,Male,52,Bachelors,4,1,66,38,15,2.0,5,9,Urban,HR Executive,132732,0 +3183,Male,24,Bachelors,4,4,53,2,46,7.0,6,2,Semi-Urban,HR Executive,22543,0 +3184,Male,29,High School,16,76,46,67,39,3.0,2,3,Urban,Software Engineer,33357,0 +3185,Male,29,Masters,9,34,78,90,50,1.0,0,55,Rural,Manager,98926,1 +3186,Male,29,Masters,9,24,10,87,96,1.0,0,75,Semi-Urban,Manager,70562,0 +3187,Male,27,Masters,9,54,91,97,85,0.0,2,5,Semi-Urban,Data Analyst,105437,1 +3188,Male,58,Masters,15,56,48,88,50,4.0,7,6,Urban,HR Executive,34735,0 +3189,Female,22,Bachelors,18,13,92,71,4,3.0,6,75,Urban,Data Analyst,137648,1 +3190,Female,30,Masters,14,73,63,32,62,6.0,4,34,Semi-Urban,Data Analyst,148525,0 +3191,Male,57,Bachelors,16,65,85,40,0,2.0,1,26,Semi-Urban,Manager,108308,0 +3192,Female,44,Masters,19,21,52,33,40,7.0,2,58,Rural,Data Analyst,115293,0 +3193,Other,59,Diploma,2,76,96,42,48,6.0,4,88,Urban,HR Executive,37527,1 +3194,Male,32,Masters,2,37,16,80,33,4.0,0,56,Semi-Urban,Software Engineer,97499,0 +3195,Male,59,High School,12,35,82,73,69,8.0,0,87,Semi-Urban,HR Executive,130028,1 +3196,Male,59,Bachelors,16,84,54,70,26,4.0,7,26,Urban,Manager,49764,0 +3197,Female,56,Bachelors,3,70,42,63,60,1.0,2,19,Urban,HR Executive,68047,0 +3198,Female,23,Bachelors,2,69,33,69,89,0.0,2,47,Urban,Manager,124423,0 +3199,Male,23,Diploma,11,96,28,51,13,4.0,5,14,Urban,Manager,48688,0 +3200,Male,36,High School,8,14,31,44,29,9.0,4,68,Urban,HR Executive,71540,0 +3201,Male,43,Bachelors,10,12,41,84,30,2.0,4,76,Urban,ML Engineer,103024,0 +3202,Male,21,Diploma,19,84,94,71,97,6.0,6,92,Semi-Urban,Data Analyst,55808,1 +3203,Male,50,Diploma,7,10,36,18,97,2.0,3,52,Urban,Software Engineer,30195,0 +3204,Female,52,Bachelors,8,45,5,51,23,8.0,2,13,Rural,ML Engineer,88551,0 +3205,Female,54,Bachelors,16,66,5,75,0,5.0,5,66,Semi-Urban,Software Engineer,107773,0 +3206,Female,55,Diploma,16,82,70,62,37,9.0,2,42,Urban,Software Engineer,128143,1 +3207,Female,50,Bachelors,15,78,47,31,41,4.0,6,64,Urban,Data Analyst,54341,0 +3208,Female,48,Diploma,19,4,61,68,1,7.0,0,10,Rural,Software Engineer,113575,0 +3209,Male,52,Masters,10,43,45,90,74,3.0,7,57,Urban,HR Executive,147277,1 +3210,Female,40,Bachelors,19,87,46,53,24,2.0,3,77,Urban,Manager,100658,1 +3211,Male,59,Diploma,2,35,48,38,0,6.0,5,58,Urban,Software Engineer,112662,0 +3212,Female,24,High School,19,97,25,86,72,6.0,5,26,Urban,HR Executive,50677,0 +3213,Male,52,Bachelors,18,21,73,5,38,4.0,0,61,Urban,ML Engineer,144753,0 +3214,Female,36,Bachelors,4,84,88,45,57,5.0,7,93,Urban,Data Analyst,149198,1 +3215,Male,55,Bachelors,13,11,77,24,39,0.0,2,90,Rural,ML Engineer,82859,0 +3216,Male,34,PhD,16,21,35,84,55,6.0,5,5,Urban,Data Analyst,83635,0 +3217,Male,40,High School,15,8,61,89,64,2.0,1,8,Urban,ML Engineer,118149,0 +3218,Male,56,PhD,15,53,87,25,25,4.0,0,96,Rural,Manager,82575,1 +3219,Female,58,High School,9,0,26,36,51,0.0,1,37,Rural,Software Engineer,50790,0 +3220,Female,48,PhD,14,99,89,5,98,3.0,0,47,Rural,Manager,117038,0 +3221,Male,34,Bachelors,4,53,64,19,21,8.0,1,55,Semi-Urban,ML Engineer,99568,0 +3222,Male,23,Bachelors,18,65,3,77,15,5.0,5,38,Urban,HR Executive,135783,0 +3223,Male,44,Diploma,3,89,86,68,55,2.0,3,67,Urban,ML Engineer,64274,1 +3224,Male,48,High School,5,32,74,43,38,1.0,4,14,Urban,Software Engineer,148242,0 +3225,Male,27,Masters,9,24,87,48,52,9.0,7,16,Semi-Urban,HR Executive,80261,0 +3226,Female,35,Bachelors,5,92,95,68,80,7.0,3,13,Urban,Manager,23603,1 +3227,Male,45,High School,15,34,81,77,49,3.0,2,61,Urban,Manager,47488,1 +3228,Male,27,Bachelors,19,84,5,23,8,6.0,3,75,Rural,Manager,40040,0 +3229,Male,44,Diploma,7,40,16,3,14,1.0,2,9,Urban,HR Executive,105135,0 +3230,Male,31,PhD,17,70,54,58,58,0.0,4,32,Semi-Urban,HR Executive,133415,0 +3231,Male,56,Bachelors,2,27,51,12,4,5.0,3,20,Semi-Urban,Software Engineer,24478,0 +3232,Female,35,High School,4,15,35,42,74,8.0,7,40,Urban,ML Engineer,49158,0 +3233,Male,30,Bachelors,19,40,64,10,41,4.0,5,77,Semi-Urban,Data Analyst,44731,0 +3234,Male,49,Bachelors,8,87,36,11,53,2.0,0,48,Urban,Data Analyst,69185,0 +3235,Male,32,Bachelors,19,71,16,94,71,8.0,2,45,Urban,ML Engineer,51848,0 +3236,Male,44,Bachelors,1,31,72,48,7,8.0,7,29,Semi-Urban,Data Analyst,56097,0 +3237,Male,27,Bachelors,19,36,53,76,61,4.0,3,40,Urban,ML Engineer,45961,0 +3238,Other,49,Bachelors,12,49,70,26,27,1.0,5,52,Rural,Data Analyst,68873,0 +3239,Female,41,Bachelors,15,81,97,19,17,7.0,2,4,Rural,Data Analyst,116309,0 +3240,Male,48,Diploma,8,22,13,5,77,9.0,4,15,Rural,Software Engineer,99112,0 +3241,Male,49,Diploma,1,53,48,87,29,9.0,4,60,Semi-Urban,Manager,60828,1 +3242,Male,57,High School,19,11,7,60,20,1.0,5,2,Semi-Urban,ML Engineer,122608,0 +3243,Male,39,Diploma,17,70,73,16,82,2.0,4,33,Rural,HR Executive,93106,0 +3244,Female,50,Bachelors,1,14,30,48,82,4.0,0,85,Semi-Urban,Manager,98215,0 +3245,Female,45,Bachelors,14,95,61,63,70,3.0,1,85,Semi-Urban,HR Executive,95310,1 +3246,Male,50,Bachelors,14,20,8,50,98,0.0,3,72,Urban,Manager,146120,0 +3247,Male,51,High School,13,45,89,95,74,3.0,1,84,Urban,Manager,111752,1 +3248,Male,43,Masters,14,86,94,42,9,2.0,0,66,Urban,Data Analyst,25025,1 +3249,Female,55,Diploma,9,63,37,38,84,0.0,2,82,Urban,Manager,143368,0 +3250,Female,30,High School,12,1,97,90,89,3.0,4,23,Rural,Software Engineer,39180,0 +3251,Male,28,Bachelors,14,36,14,7,77,7.0,7,73,Urban,Software Engineer,48561,0 +3252,Male,26,Bachelors,5,7,40,12,39,5.0,2,92,Urban,Data Analyst,122139,0 +3253,Female,22,High School,2,32,7,38,23,0.0,5,19,Urban,HR Executive,122844,0 +3254,Male,56,Masters,2,31,12,73,16,6.0,5,83,Semi-Urban,ML Engineer,121248,0 +3255,Male,35,Bachelors,5,25,52,34,5,0.0,7,98,Urban,Data Analyst,98453,0 +3256,Male,57,Diploma,1,84,25,45,11,2.0,0,85,Urban,Software Engineer,97190,1 +3257,Female,45,Diploma,12,52,62,78,14,3.0,0,80,Semi-Urban,Manager,132036,1 +3258,Male,35,High School,13,23,23,7,62,3.0,0,48,Urban,ML Engineer,99591,0 +3259,Male,28,Diploma,6,31,2,24,85,1.0,0,36,Urban,Manager,126929,0 +3260,Female,27,Masters,18,16,88,68,88,6.0,2,22,Urban,Manager,112937,0 +3261,Male,30,Bachelors,0,10,51,54,65,2.0,6,53,Semi-Urban,Software Engineer,32062,0 +3262,Male,36,Bachelors,6,9,45,38,47,6.0,3,75,Rural,Software Engineer,93165,0 +3263,Male,55,Bachelors,0,48,76,60,85,6.0,7,32,Urban,Data Analyst,68405,0 +3264,Male,43,High School,6,62,78,3,16,2.0,5,43,Urban,Manager,20469,0 +3265,Female,54,Diploma,4,57,57,74,10,2.0,5,14,Urban,Manager,144343,0 +3266,Male,23,Bachelors,17,97,30,28,49,1.0,4,97,Urban,Software Engineer,127371,1 +3267,Male,22,Diploma,12,88,75,17,17,1.0,2,19,Urban,Software Engineer,36199,0 +3268,Male,50,Bachelors,7,85,63,51,7,8.0,4,37,Urban,Data Analyst,93407,1 +3269,Female,49,Bachelors,19,25,98,35,82,0.0,7,91,Semi-Urban,HR Executive,47419,1 +3270,Female,29,Masters,17,97,90,63,92,8.0,7,79,Urban,ML Engineer,51302,1 +3271,Male,55,Masters,2,31,25,66,68,2.0,3,12,Rural,ML Engineer,134645,0 +3272,Male,44,Diploma,10,84,47,47,62,5.0,2,3,Urban,Software Engineer,139160,0 +3273,Female,22,Bachelors,1,0,57,78,20,2.0,4,68,Urban,Manager,132134,0 +3274,Male,22,Bachelors,7,88,17,68,74,4.0,2,34,Semi-Urban,Data Analyst,45930,0 +3275,Female,39,Masters,10,23,39,19,94,0.0,5,53,Semi-Urban,Manager,124422,0 +3276,Female,31,Masters,0,86,2,23,92,0.0,4,54,Urban,Software Engineer,56296,0 +3277,Female,44,Bachelors,12,18,52,44,13,4.0,5,71,Urban,Data Analyst,100049,0 +3278,Male,36,Bachelors,0,27,71,83,18,9.0,3,28,Urban,Manager,100205,0 +3279,Male,52,Bachelors,5,16,46,76,59,0.0,1,46,Urban,Data Analyst,26090,0 +3280,Female,45,Masters,0,56,19,33,11,3.0,4,29,Urban,Manager,20908,0 +3281,Male,27,Bachelors,5,63,64,37,9,1.0,6,13,Urban,Manager,119501,0 +3282,Male,38,Masters,4,99,77,71,87,8.0,5,93,Urban,Data Analyst,75500,1 +3283,Female,28,Bachelors,2,11,54,79,53,1.0,2,31,Urban,Data Analyst,133992,0 +3284,Female,52,High School,16,68,34,70,53,6.0,2,71,Urban,ML Engineer,98855,1 +3285,Male,24,High School,3,89,47,3,54,6.0,1,25,Urban,HR Executive,139745,0 +3286,Male,41,Diploma,10,18,56,35,5,2.0,0,72,Urban,HR Executive,37150,0 +3287,Male,33,PhD,2,80,70,82,12,7.0,2,16,Rural,Software Engineer,84561,1 +3288,Female,53,PhD,1,42,42,1,78,9.0,0,89,Urban,Data Analyst,110178,0 +3289,Female,44,Bachelors,14,69,73,97,27,9.0,7,87,Semi-Urban,ML Engineer,117925,1 +3290,Male,26,Bachelors,3,9,30,45,10,4.0,0,18,Urban,HR Executive,76037,0 +3291,Male,41,PhD,11,72,77,61,96,3.0,5,35,Urban,Software Engineer,125419,1 +3292,Female,51,Bachelors,13,59,45,59,5,1.0,3,59,Semi-Urban,Data Analyst,136684,0 +3293,Male,29,Bachelors,15,76,87,21,43,9.0,2,30,Semi-Urban,Software Engineer,33081,0 +3294,Male,54,Masters,14,78,90,31,40,2.0,7,70,Semi-Urban,ML Engineer,20977,1 +3295,Other,21,Diploma,16,93,69,87,41,1.0,4,96,Urban,Data Analyst,56915,1 +3296,Male,39,PhD,11,30,16,19,83,6.0,2,48,Urban,ML Engineer,100765,0 +3297,Female,22,High School,6,77,0,80,11,5.0,1,26,Urban,Manager,84449,0 +3298,Male,40,Bachelors,10,18,43,35,87,8.0,5,61,Urban,Software Engineer,138549,0 +3299,Male,25,Bachelors,9,66,31,6,91,2.0,2,78,Semi-Urban,Manager,33638,0 +3300,Female,56,Masters,2,51,13,80,45,5.0,4,55,Urban,Manager,78567,0 +3301,Male,37,Diploma,18,68,2,28,13,6.0,2,6,Urban,Data Analyst,24400,0 +3302,Other,32,Diploma,17,41,41,0,7,6.0,3,10,Urban,Manager,71083,0 +3303,Male,42,Bachelors,18,62,90,42,30,0.0,5,77,Rural,Manager,82905,1 +3304,Male,45,Bachelors,17,6,42,64,79,6.0,7,43,Semi-Urban,Data Analyst,44585,0 +3305,Male,57,Bachelors,10,20,30,28,8,1.0,5,1,Semi-Urban,Data Analyst,48715,0 +3306,Male,50,Masters,5,43,16,4,51,6.0,3,52,Urban,Manager,33834,0 +3307,Male,29,PhD,13,62,9,37,55,9.0,3,69,Semi-Urban,ML Engineer,25507,0 +3308,Male,39,Bachelors,5,69,93,76,30,1.0,6,67,Semi-Urban,Manager,110907,1 +3309,Male,27,Masters,4,53,19,68,98,6.0,5,38,Urban,ML Engineer,50063,0 +3310,Male,42,Bachelors,0,25,8,90,63,2.0,3,75,Urban,ML Engineer,92888,0 +3311,Female,41,Masters,18,32,31,66,49,1.0,2,15,Urban,Manager,140219,0 +3312,Female,48,Masters,11,37,75,72,24,3.0,6,80,Urban,HR Executive,105518,1 +3313,Female,46,Diploma,19,30,77,62,39,0.0,4,0,Urban,Software Engineer,140340,0 +3314,Male,59,Bachelors,12,12,86,48,20,6.0,6,3,Urban,Data Analyst,21023,0 +3315,Male,56,High School,13,17,4,64,49,5.0,7,91,Rural,HR Executive,66264,0 +3316,Female,46,PhD,3,94,8,5,46,9.0,1,35,Urban,ML Engineer,105903,0 +3317,Male,46,PhD,2,98,10,69,30,1.0,1,67,Semi-Urban,HR Executive,40482,1 +3318,Male,59,High School,8,22,53,43,97,8.0,1,38,Urban,ML Engineer,145481,0 +3319,Female,55,Bachelors,13,9,50,92,46,1.0,3,72,Urban,Software Engineer,120171,0 +3320,Female,38,Diploma,18,35,95,56,64,8.0,4,6,Rural,Software Engineer,130312,0 +3321,Male,38,Diploma,10,20,0,17,46,3.0,4,62,Urban,HR Executive,42346,0 +3322,Male,37,Masters,19,5,42,11,27,4.0,5,36,Semi-Urban,Software Engineer,147135,0 +3323,Female,46,Diploma,19,17,64,3,33,9.0,3,68,Urban,Manager,120962,0 +3324,Male,54,High School,17,44,10,87,38,4.0,4,29,Urban,Data Analyst,69902,0 +3325,Female,57,PhD,4,10,54,74,26,0.0,1,40,Rural,ML Engineer,69403,0 +3326,Female,55,Bachelors,11,51,18,65,34,9.0,5,32,Semi-Urban,Software Engineer,68623,0 +3327,Female,29,Bachelors,8,90,89,63,59,3.0,2,20,Urban,Software Engineer,146292,1 +3328,Male,36,Bachelors,2,89,34,98,50,8.0,7,46,Semi-Urban,Software Engineer,59859,1 +3329,Male,41,Bachelors,18,4,47,58,57,8.0,5,89,Urban,Software Engineer,53876,0 +3330,Female,37,Diploma,0,32,17,10,72,5.0,1,95,Semi-Urban,Software Engineer,73695,0 +3331,Female,34,Diploma,17,73,94,88,68,5.0,6,6,Semi-Urban,ML Engineer,141199,1 +3332,Female,21,Bachelors,4,2,9,34,74,2.0,6,56,Semi-Urban,ML Engineer,122121,0 +3333,Male,57,Bachelors,16,89,87,20,81,7.0,0,9,Urban,Data Analyst,103941,0 +3334,Male,41,High School,4,76,90,13,15,5.0,0,90,Urban,Data Analyst,126625,1 +3335,Female,24,Bachelors,14,54,22,80,89,5.0,5,94,Urban,ML Engineer,61207,1 +3336,Female,55,Bachelors,13,78,98,42,62,2.0,6,75,Rural,HR Executive,85713,1 +3337,Female,38,Diploma,9,78,15,90,24,9.0,6,40,Urban,Manager,131922,0 +3338,Female,30,Bachelors,3,7,4,2,6,2.0,4,64,Semi-Urban,ML Engineer,87337,0 +3339,Male,49,Diploma,11,93,56,95,99,3.0,5,10,Urban,ML Engineer,97641,1 +3340,Female,22,Diploma,17,53,18,76,63,7.0,3,23,Rural,Manager,98982,0 +3341,Female,28,Bachelors,8,70,27,17,94,2.0,2,18,Semi-Urban,Data Analyst,49349,0 +3342,Male,54,Masters,5,45,35,79,17,2.0,1,94,Urban,ML Engineer,37955,1 +3343,Female,31,High School,19,31,2,8,99,9.0,1,77,Semi-Urban,Data Analyst,107118,0 +3344,Male,30,Bachelors,16,13,64,63,40,8.0,1,31,Semi-Urban,HR Executive,35227,0 +3345,Male,53,High School,0,95,92,33,27,2.0,4,66,Semi-Urban,Manager,67142,1 +3346,Female,24,Bachelors,10,16,51,51,89,7.0,0,77,Urban,Manager,21003,0 +3347,Male,45,Bachelors,10,35,14,43,75,6.0,1,81,Urban,Data Analyst,139326,0 +3348,Male,42,High School,13,41,83,12,51,1.0,5,38,Rural,Software Engineer,109908,0 +3349,Male,25,Bachelors,2,33,82,42,86,9.0,0,20,Urban,Manager,51667,0 +3350,Male,48,Masters,12,54,80,45,88,2.0,6,91,Urban,HR Executive,98958,1 +3351,Male,32,Masters,19,61,4,40,30,8.0,6,79,Rural,Data Analyst,97210,0 +3352,Male,24,Bachelors,9,21,33,22,83,9.0,6,37,Urban,ML Engineer,29832,0 +3353,Female,39,High School,19,58,55,44,50,2.0,4,32,Urban,Manager,71034,0 +3354,Male,45,Bachelors,9,96,95,15,12,6.0,6,51,Urban,HR Executive,55055,1 +3355,Male,38,Bachelors,4,19,22,77,68,2.0,1,80,Urban,HR Executive,101404,0 +3356,Male,52,PhD,0,21,21,26,65,2.0,0,37,Urban,Data Analyst,47845,0 +3357,Female,37,PhD,16,31,65,58,80,8.0,1,5,Semi-Urban,Software Engineer,87441,0 +3358,Male,36,Masters,12,71,68,91,9,8.0,6,83,Rural,Data Analyst,87997,1 +3359,Female,38,Bachelors,8,32,16,61,38,4.0,1,28,Semi-Urban,ML Engineer,31413,0 +3360,Female,56,Diploma,8,32,56,43,77,2.0,0,64,Semi-Urban,Manager,126031,0 +3361,Female,54,Bachelors,3,66,4,63,86,3.0,3,17,Rural,Manager,137485,0 +3362,Male,54,Bachelors,1,21,87,54,52,8.0,0,40,Urban,Data Analyst,132430,0 +3363,Female,49,Bachelors,15,38,69,37,67,4.0,6,84,Urban,ML Engineer,56201,0 +3364,Male,45,Bachelors,0,94,54,31,2,3.0,3,57,Semi-Urban,HR Executive,54729,1 +3365,Female,30,Diploma,12,45,68,23,13,1.0,1,78,Rural,Manager,77829,0 +3366,Female,29,Masters,0,9,99,97,82,0.0,4,49,Urban,ML Engineer,140782,1 +3367,Male,38,Diploma,17,57,46,29,6,5.0,5,99,Semi-Urban,HR Executive,36096,0 +3368,Male,43,High School,18,41,79,18,28,1.0,7,79,Rural,Software Engineer,93944,0 +3369,Male,26,Bachelors,7,17,83,94,80,2.0,4,54,Rural,HR Executive,52396,1 +3370,Female,57,Bachelors,6,50,58,40,15,1.0,0,23,Rural,Data Analyst,62299,0 +3371,Male,42,Diploma,0,1,91,17,16,8.0,5,49,Urban,Data Analyst,115462,0 +3372,Male,48,Masters,6,94,62,63,86,9.0,7,74,Urban,Data Analyst,111954,1 +3373,Male,28,Masters,9,29,31,99,36,0.0,7,27,Urban,HR Executive,95316,0 +3374,Female,31,Bachelors,0,88,15,78,68,5.0,0,11,Semi-Urban,ML Engineer,24894,0 +3375,Female,56,Bachelors,16,42,47,53,52,6.0,7,62,Urban,Software Engineer,112754,0 +3376,Female,28,High School,17,89,2,95,19,6.0,4,95,Urban,Data Analyst,54777,1 +3377,Female,29,Diploma,11,88,32,55,72,3.0,4,93,Urban,Data Analyst,28358,1 +3378,Male,46,Bachelors,16,84,11,22,7,3.0,2,80,Rural,Software Engineer,30404,0 +3379,Male,50,Diploma,19,70,10,33,33,6.0,5,66,Rural,Software Engineer,42739,0 +3380,Female,55,Diploma,2,66,87,40,97,9.0,0,24,Rural,ML Engineer,138368,0 +3381,Male,47,Diploma,10,31,89,97,98,8.0,7,62,Semi-Urban,HR Executive,67462,1 +3382,Male,58,Bachelors,15,51,64,15,65,4.0,2,66,Rural,Data Analyst,39128,0 +3383,Male,28,Bachelors,12,90,1,75,25,8.0,6,5,Urban,Software Engineer,23877,0 +3384,Male,26,High School,8,20,23,62,4,5.0,7,1,Semi-Urban,Manager,80775,0 +3385,Male,58,High School,18,66,8,67,59,3.0,2,52,Semi-Urban,Data Analyst,51951,0 +3386,Female,38,Diploma,18,61,31,95,18,7.0,1,83,Urban,Manager,39667,1 +3387,Male,21,Bachelors,7,77,95,20,94,7.0,3,61,Rural,Manager,49841,1 +3388,Male,28,Bachelors,0,44,36,21,80,2.0,2,95,Urban,Software Engineer,128601,0 +3389,Male,32,Bachelors,11,24,37,75,3,6.0,2,45,Urban,ML Engineer,135424,0 +3390,Female,21,High School,14,99,12,40,51,0.0,7,4,Urban,HR Executive,39238,0 +3391,Male,49,Diploma,5,86,1,6,75,2.0,4,16,Semi-Urban,Data Analyst,68420,0 +3392,Female,55,Diploma,15,50,43,89,6,0.0,1,1,Rural,Data Analyst,123439,0 +3393,Female,37,Bachelors,7,18,25,40,47,5.0,4,66,Urban,Manager,57786,0 +3394,Male,26,Bachelors,8,83,80,16,14,3.0,6,17,Rural,Software Engineer,119798,0 +3395,Female,42,Bachelors,9,78,95,86,32,4.0,0,50,Rural,HR Executive,121391,1 +3396,Other,28,High School,1,13,44,17,45,4.0,1,8,Urban,Data Analyst,29569,0 +3397,Female,56,Masters,7,58,12,70,17,9.0,4,34,Urban,Manager,73345,0 +3398,Female,41,Bachelors,3,24,37,90,67,7.0,0,87,Rural,ML Engineer,42598,0 +3399,Male,25,High School,2,5,1,21,6,4.0,0,95,Urban,Data Analyst,28214,0 +3400,Male,51,Masters,14,37,32,14,5,6.0,6,12,Semi-Urban,HR Executive,57307,0 +3401,Male,48,Diploma,0,30,86,56,19,3.0,5,49,Urban,HR Executive,130093,0 +3402,Male,50,Masters,12,23,96,32,16,1.0,6,5,Urban,ML Engineer,74494,0 +3403,Other,33,High School,3,42,52,87,69,8.0,2,46,Semi-Urban,Data Analyst,43371,0 +3404,Male,49,Masters,12,49,36,54,20,6.0,0,35,Urban,Manager,92009,0 +3405,Female,53,Bachelors,19,25,69,82,95,9.0,4,91,Urban,HR Executive,146261,1 +3406,Female,30,Masters,4,54,48,19,96,5.0,6,38,Urban,Software Engineer,112280,0 +3407,Female,39,Bachelors,4,5,85,52,11,6.0,1,26,Semi-Urban,ML Engineer,96154,0 +3408,Other,29,Masters,9,77,36,85,12,3.0,1,5,Rural,Data Analyst,126001,0 +3409,Male,36,Diploma,16,73,26,41,70,2.0,2,18,Semi-Urban,Software Engineer,123339,0 +3410,Male,47,Diploma,8,65,82,49,99,6.0,1,45,Rural,Manager,135616,1 +3411,Male,59,Bachelors,0,74,44,6,13,3.0,6,8,Urban,ML Engineer,87401,0 +3412,Male,59,Masters,6,35,42,51,98,4.0,6,83,Rural,Software Engineer,126049,0 +3413,Male,26,PhD,6,16,5,84,70,9.0,7,11,Semi-Urban,Software Engineer,110073,0 +3414,Male,39,Diploma,18,87,13,80,47,2.0,1,99,Urban,Software Engineer,80793,1 +3415,Female,51,Bachelors,11,27,57,88,50,5.0,4,75,Urban,ML Engineer,141918,1 +3416,Male,39,Bachelors,5,85,36,60,61,9.0,4,10,Urban,Manager,129478,0 +3417,Male,52,Diploma,14,53,80,90,19,9.0,2,66,Semi-Urban,Software Engineer,124276,1 +3418,Female,23,Bachelors,3,0,40,99,76,8.0,1,11,Urban,Software Engineer,34395,0 +3419,Male,42,Bachelors,11,91,11,96,27,6.0,0,0,Semi-Urban,HR Executive,107976,0 +3420,Male,31,Masters,14,94,49,80,97,0.0,3,54,Urban,HR Executive,103853,1 +3421,Female,52,Bachelors,15,87,41,3,87,2.0,7,77,Semi-Urban,HR Executive,109483,0 +3422,Female,24,Masters,12,39,28,87,31,7.0,5,37,Semi-Urban,ML Engineer,103382,0 +3423,Female,32,Masters,16,40,71,79,19,5.0,1,8,Rural,Data Analyst,31144,0 +3424,Male,49,Diploma,4,64,17,32,17,2.0,2,51,Semi-Urban,Data Analyst,76332,0 +3425,Female,24,Diploma,6,7,92,62,87,7.0,6,69,Semi-Urban,Software Engineer,89930,0 +3426,Female,23,Diploma,17,5,69,14,94,6.0,5,20,Rural,Manager,107735,0 +3427,Male,43,Masters,2,77,74,68,71,1.0,4,21,Urban,Data Analyst,70793,1 +3428,Female,30,Diploma,11,84,37,97,41,4.0,3,98,Rural,Manager,109625,1 +3429,Female,37,Bachelors,1,91,88,21,0,2.0,4,17,Semi-Urban,ML Engineer,139841,0 +3430,Male,49,Diploma,14,52,38,44,18,7.0,2,13,Semi-Urban,Data Analyst,117943,0 +3431,Male,57,Bachelors,1,22,39,59,84,1.0,1,94,Semi-Urban,HR Executive,120572,0 +3432,Other,32,Bachelors,16,88,33,19,71,7.0,3,33,Semi-Urban,ML Engineer,49195,0 +3433,Female,59,Masters,5,73,60,20,33,6.0,3,86,Urban,HR Executive,34403,0 +3434,Male,38,Diploma,2,22,38,75,2,1.0,5,39,Rural,Data Analyst,97679,0 +3435,Female,42,Masters,10,62,76,94,83,0.0,6,96,Urban,HR Executive,59343,1 +3436,Male,39,Diploma,13,4,81,75,88,4.0,0,98,Urban,ML Engineer,47651,1 +3437,Male,37,Masters,15,62,0,31,70,4.0,4,1,Urban,HR Executive,114977,0 +3438,Male,25,Masters,17,96,40,4,85,6.0,7,53,Urban,Manager,146601,0 +3439,Female,35,Masters,1,98,3,83,73,1.0,3,17,Urban,ML Engineer,82129,0 +3440,Female,46,Bachelors,6,56,25,10,1,2.0,5,70,Urban,Software Engineer,75013,0 +3441,Male,44,Diploma,11,93,12,13,64,8.0,7,41,Semi-Urban,Data Analyst,102567,0 +3442,Male,40,Masters,11,51,2,64,62,6.0,0,35,Urban,Manager,48545,0 +3443,Male,41,Diploma,16,82,46,18,92,3.0,0,16,Urban,Manager,69913,0 +3444,Other,55,Diploma,18,82,68,29,13,5.0,4,21,Urban,Software Engineer,107606,0 +3445,Other,47,High School,15,13,30,70,1,1.0,1,93,Urban,HR Executive,81505,0 +3446,Female,56,High School,12,45,81,0,57,4.0,3,10,Semi-Urban,ML Engineer,99377,0 +3447,Female,30,High School,15,96,34,74,8,0.0,3,70,Rural,Data Analyst,144225,1 +3448,Female,57,PhD,4,49,9,99,43,2.0,6,38,Urban,Software Engineer,139057,0 +3449,Male,54,Masters,8,68,81,2,84,1.0,6,42,Semi-Urban,ML Engineer,130266,0 +3450,Male,46,Masters,2,69,3,96,19,2.0,2,50,Rural,HR Executive,30969,0 +3451,Male,31,Bachelors,8,50,0,89,50,4.0,5,27,Urban,ML Engineer,114733,0 +3452,Female,40,Bachelors,9,26,56,82,68,6.0,3,18,Semi-Urban,ML Engineer,82295,0 +3453,Female,53,Diploma,10,9,51,98,73,4.0,1,71,Urban,ML Engineer,139832,0 +3454,Male,26,High School,18,32,28,88,64,0.0,0,21,Urban,Manager,79580,0 +3455,Female,22,Bachelors,12,84,71,25,28,5.0,7,71,Urban,Software Engineer,35202,1 +3456,Male,29,High School,15,29,67,42,76,1.0,6,20,Urban,Data Analyst,67890,0 +3457,Male,52,Bachelors,3,15,23,54,0,4.0,4,51,Urban,HR Executive,61766,0 +3458,Female,39,PhD,1,52,22,27,46,2.0,6,61,Semi-Urban,Software Engineer,51700,0 +3459,Female,45,High School,16,20,64,78,47,3.0,3,19,Urban,ML Engineer,119454,0 +3460,Female,50,Bachelors,7,10,84,23,2,3.0,7,70,Rural,Manager,94798,0 +3461,Male,37,Diploma,2,59,72,32,52,9.0,1,64,Urban,ML Engineer,44358,0 +3462,Male,33,Bachelors,11,68,49,20,20,6.0,3,34,Urban,Software Engineer,72105,0 +3463,Female,45,PhD,5,44,74,73,15,2.0,0,69,Rural,HR Executive,79507,1 +3464,Male,34,Diploma,12,25,44,18,16,6.0,2,74,Semi-Urban,ML Engineer,109728,0 +3465,Male,38,Masters,6,39,8,38,35,8.0,6,90,Urban,Software Engineer,65200,0 +3466,Female,36,Diploma,10,59,16,63,18,7.0,0,82,Semi-Urban,HR Executive,29292,0 +3467,Male,28,Bachelors,1,22,37,87,85,2.0,3,14,Urban,Manager,38804,0 +3468,Female,41,Diploma,2,8,3,90,6,5.0,4,67,Urban,Software Engineer,124061,0 +3469,Female,35,Bachelors,7,45,77,66,97,3.0,5,77,Urban,ML Engineer,133114,1 +3470,Male,21,Bachelors,5,28,98,20,1,6.0,2,72,Semi-Urban,Data Analyst,134690,0 +3471,Male,35,Masters,0,51,30,75,6,7.0,4,48,Urban,HR Executive,64706,0 +3472,Female,37,Bachelors,11,73,5,51,74,8.0,6,92,Urban,Manager,103934,0 +3473,Female,58,Diploma,5,19,41,63,45,7.0,7,1,Urban,HR Executive,44682,0 +3474,Female,46,Diploma,12,74,22,55,79,6.0,6,81,Semi-Urban,ML Engineer,71436,0 +3475,Female,34,High School,2,10,10,52,50,4.0,5,68,Urban,ML Engineer,149176,0 +3476,Female,53,Bachelors,3,6,59,16,76,0.0,6,79,Urban,Manager,66218,0 +3477,Other,35,Bachelors,7,16,14,87,93,1.0,2,63,Rural,Manager,111574,0 +3478,Male,44,Bachelors,3,74,30,2,45,1.0,5,99,Urban,Data Analyst,146491,0 +3479,Male,41,High School,13,78,77,80,54,4.0,6,91,Urban,Software Engineer,117009,1 +3480,Male,38,Bachelors,12,17,74,69,95,3.0,0,14,Semi-Urban,Data Analyst,143422,0 +3481,Male,27,High School,1,60,80,99,82,1.0,3,17,Semi-Urban,Data Analyst,31518,1 +3482,Male,38,Bachelors,7,91,74,24,99,0.0,2,48,Urban,Software Engineer,45026,1 +3483,Male,38,Masters,12,9,40,49,42,6.0,5,94,Semi-Urban,HR Executive,103975,0 +3484,Female,21,Masters,0,95,16,33,52,5.0,5,6,Urban,Manager,62230,0 +3485,Male,43,Masters,1,1,49,0,91,8.0,7,54,Semi-Urban,HR Executive,68467,0 +3486,Male,27,Bachelors,6,16,82,40,25,1.0,4,76,Urban,Data Analyst,144734,0 +3487,Male,40,Bachelors,17,60,96,43,32,6.0,3,17,Urban,ML Engineer,80212,0 +3488,Male,52,Bachelors,15,98,60,65,40,2.0,4,13,Rural,HR Executive,126634,1 +3489,Male,25,Bachelors,13,30,39,90,20,9.0,7,52,Rural,Data Analyst,110669,0 +3490,Male,42,Bachelors,10,23,79,69,76,8.0,0,80,Rural,Manager,112935,1 +3491,Male,52,Bachelors,3,52,14,75,22,4.0,5,30,Urban,HR Executive,128696,0 +3492,Female,27,Bachelors,13,8,66,31,78,7.0,1,90,Urban,HR Executive,117904,0 +3493,Female,27,High School,8,75,84,7,95,7.0,5,99,Urban,Manager,135303,1 +3494,Female,41,High School,10,14,6,20,15,0.0,4,27,Urban,Software Engineer,135582,0 +3495,Female,29,Bachelors,16,37,85,68,86,4.0,6,77,Urban,Data Analyst,27149,1 +3496,Male,35,Bachelors,2,25,2,86,85,2.0,0,7,Rural,HR Executive,93073,0 +3497,Female,46,Bachelors,10,50,57,8,68,7.0,7,80,Rural,Data Analyst,108842,0 +3498,Female,28,Diploma,1,57,4,19,88,9.0,1,48,Urban,Data Analyst,73192,0 +3499,Male,22,Bachelors,5,41,43,18,3,8.0,6,16,Rural,ML Engineer,96889,0 +3500,Female,29,Bachelors,2,18,17,61,63,0.0,5,56,Urban,ML Engineer,35740,0 +3501,Male,56,Bachelors,3,97,61,31,0,1.0,1,49,Urban,ML Engineer,135302,1 +3502,Female,38,High School,7,20,95,61,62,8.0,0,46,Semi-Urban,Software Engineer,80267,0 +3503,Other,44,Masters,0,59,94,28,86,6.0,3,18,Urban,ML Engineer,144746,0 +3504,Male,23,Masters,6,38,50,13,41,4.0,6,8,Urban,Data Analyst,147896,0 +3505,Female,41,Bachelors,15,7,43,51,96,0.0,3,87,Urban,Data Analyst,40560,0 +3506,Female,31,Diploma,2,63,55,96,40,1.0,3,73,Rural,HR Executive,39953,1 +3507,Other,21,High School,3,64,4,76,64,3.0,6,36,Urban,Software Engineer,122464,0 +3508,Male,32,Bachelors,15,27,63,77,67,7.0,0,52,Rural,Software Engineer,35681,0 +3509,Female,26,Diploma,11,66,75,71,35,6.0,7,58,Rural,Manager,107844,1 +3510,Male,27,High School,5,35,13,64,50,2.0,4,9,Rural,Data Analyst,52439,0 +3511,Male,24,Diploma,10,54,69,29,79,5.0,4,99,Rural,Data Analyst,129485,1 +3512,Male,28,Diploma,10,39,74,50,43,9.0,6,68,Urban,Software Engineer,24743,0 +3513,Other,43,High School,18,19,86,22,44,2.0,0,5,Urban,Data Analyst,64364,0 +3514,Female,34,Bachelors,16,76,10,54,77,1.0,2,39,Urban,Manager,64606,0 +3515,Female,57,Diploma,11,51,65,30,70,8.0,7,71,Urban,Software Engineer,49426,0 +3516,Female,53,Bachelors,8,12,66,65,96,2.0,3,33,Urban,Software Engineer,43591,0 +3517,Male,25,Bachelors,2,20,66,97,29,8.0,7,32,Rural,Data Analyst,86087,0 +3518,Male,26,Bachelors,18,79,97,26,41,3.0,2,64,Urban,Data Analyst,26734,1 +3519,Male,43,Bachelors,7,63,49,59,0,8.0,0,67,Rural,Data Analyst,43235,1 +3520,Male,35,Diploma,15,16,31,94,55,8.0,7,28,Urban,Data Analyst,25342,0 +3521,Male,54,PhD,15,92,16,99,70,9.0,4,36,Urban,HR Executive,142592,1 +3522,Male,23,Diploma,5,39,75,70,49,3.0,5,21,Rural,Manager,36082,0 +3523,Male,50,Bachelors,12,12,75,92,45,5.0,6,64,Urban,Software Engineer,109530,1 +3524,Male,36,Masters,7,35,3,72,67,5.0,6,52,Semi-Urban,HR Executive,123626,0 +3525,Male,34,High School,11,5,37,55,1,2.0,7,59,Semi-Urban,Software Engineer,137598,0 +3526,Male,41,Diploma,13,88,39,68,7,4.0,1,65,Urban,Software Engineer,30639,1 +3527,Other,22,Masters,6,70,58,98,61,8.0,7,40,Semi-Urban,Manager,148638,1 +3528,Female,40,Diploma,14,87,72,91,61,7.0,4,29,Urban,ML Engineer,132305,1 +3529,Other,38,Bachelors,2,39,78,6,23,5.0,6,24,Semi-Urban,HR Executive,108651,0 +3530,Male,39,Bachelors,16,42,86,65,93,5.0,0,46,Urban,HR Executive,20235,1 +3531,Male,37,Bachelors,11,56,32,19,6,3.0,0,46,Urban,Data Analyst,118715,0 +3532,Female,34,Diploma,15,60,61,87,43,2.0,5,19,Semi-Urban,ML Engineer,30370,0 +3533,Male,33,Bachelors,3,33,63,91,60,4.0,3,22,Urban,Data Analyst,114703,0 +3534,Male,47,High School,0,97,30,20,1,0.0,2,1,Urban,HR Executive,138863,0 +3535,Male,26,High School,15,20,16,38,88,2.0,5,66,Semi-Urban,Data Analyst,81345,0 +3536,Male,55,Diploma,14,53,69,45,82,9.0,3,54,Semi-Urban,Software Engineer,127380,0 +3537,Male,55,Bachelors,13,1,10,87,83,5.0,3,65,Urban,Software Engineer,20699,0 +3538,Male,38,Bachelors,11,33,9,73,67,6.0,6,45,Semi-Urban,ML Engineer,47762,0 +3539,Female,54,Masters,0,45,38,67,83,9.0,5,18,Urban,Software Engineer,117151,0 +3540,Male,56,Bachelors,12,51,48,76,71,3.0,4,17,Urban,Manager,85670,0 +3541,Male,42,Diploma,7,99,19,27,45,3.0,3,98,Semi-Urban,ML Engineer,140859,1 +3542,Female,24,Diploma,0,23,33,54,53,0.0,5,38,Urban,Software Engineer,49411,0 +3543,Male,49,Masters,5,70,10,93,88,0.0,6,74,Rural,Software Engineer,36692,1 +3544,Male,52,Bachelors,15,27,21,87,27,0.0,1,11,Semi-Urban,HR Executive,85217,0 +3545,Female,33,Diploma,9,77,46,60,57,4.0,5,11,Semi-Urban,Software Engineer,126681,0 +3546,Male,44,High School,13,96,27,46,42,5.0,6,95,Urban,Manager,39156,1 +3547,Male,36,Masters,18,17,29,60,71,7.0,3,74,Rural,HR Executive,93367,0 +3548,Male,21,High School,3,77,11,11,61,9.0,0,33,Urban,Manager,110336,0 +3549,Male,46,Bachelors,7,75,98,65,65,9.0,2,33,Urban,Data Analyst,25324,1 +3550,Male,36,High School,9,45,43,26,1,9.0,7,63,Rural,Manager,146086,0 +3551,Female,48,High School,3,32,10,47,36,7.0,7,26,Urban,HR Executive,95889,0 +3552,Male,40,Masters,1,56,19,73,93,7.0,7,52,Semi-Urban,HR Executive,43473,0 +3553,Male,52,Bachelors,3,87,2,3,95,0.0,7,88,Urban,ML Engineer,68040,0 +3554,Male,27,High School,4,99,2,28,85,0.0,1,8,Rural,HR Executive,140424,0 +3555,Male,26,Bachelors,4,7,3,60,61,6.0,4,19,Urban,Software Engineer,63862,0 +3556,Female,39,Bachelors,5,54,46,10,23,0.0,3,77,Rural,Data Analyst,24951,0 +3557,Male,28,Bachelors,16,62,33,70,37,9.0,0,99,Rural,ML Engineer,49218,1 +3558,Male,37,Bachelors,14,54,11,80,39,1.0,6,52,Rural,HR Executive,141643,0 +3559,Male,39,Bachelors,18,57,84,42,21,1.0,6,49,Rural,Data Analyst,113067,0 +3560,Male,39,Bachelors,16,13,63,98,2,8.0,7,23,Urban,HR Executive,131591,0 +3561,Male,29,Diploma,6,71,81,21,93,3.0,7,79,Semi-Urban,Software Engineer,75039,1 +3562,Female,54,Diploma,17,62,75,8,75,3.0,4,61,Urban,Manager,37646,0 +3563,Male,54,Masters,1,90,37,70,27,8.0,4,6,Urban,HR Executive,119882,0 +3564,Male,54,Bachelors,16,77,82,94,95,1.0,2,76,Rural,Data Analyst,78062,1 +3565,Male,22,Bachelors,12,15,28,79,10,7.0,4,85,Urban,ML Engineer,66775,0 +3566,Female,37,Diploma,10,34,8,10,33,5.0,3,67,Semi-Urban,Data Analyst,112273,0 +3567,Male,30,Bachelors,11,5,69,21,73,3.0,4,76,Rural,HR Executive,119827,0 +3568,Female,24,Masters,14,21,7,62,15,4.0,4,56,Semi-Urban,Software Engineer,63495,0 +3569,Female,43,Bachelors,15,92,74,19,21,0.0,1,99,Urban,Manager,132076,1 +3570,Female,43,Diploma,5,63,38,59,30,9.0,6,44,Urban,HR Executive,140752,0 +3571,Male,29,Masters,3,81,54,64,20,1.0,3,91,Urban,HR Executive,52083,1 +3572,Male,28,Bachelors,0,68,66,40,1,3.0,7,74,Urban,HR Executive,53415,1 +3573,Female,59,Diploma,7,66,24,84,73,2.0,2,85,Rural,HR Executive,69863,1 +3574,Other,38,Bachelors,3,51,47,27,27,1.0,7,65,Rural,Manager,75574,0 +3575,Female,49,Diploma,8,14,88,53,53,8.0,6,73,Urban,ML Engineer,38199,0 +3576,Male,24,Diploma,4,31,27,58,87,0.0,3,39,Urban,Manager,84794,0 +3577,Male,37,Bachelors,0,5,50,51,57,4.0,6,10,Urban,Data Analyst,75898,0 +3578,Male,58,Diploma,19,61,86,57,39,1.0,0,49,Semi-Urban,ML Engineer,88362,1 +3579,Female,26,PhD,12,74,40,77,35,9.0,6,27,Urban,Manager,48729,0 +3580,Male,43,High School,5,97,55,11,68,8.0,5,50,Urban,Manager,72168,0 +3581,Male,28,Diploma,12,90,12,41,36,7.0,2,66,Urban,HR Executive,64716,0 +3582,Female,32,Diploma,4,39,99,20,56,9.0,5,18,Semi-Urban,HR Executive,58429,0 +3583,Male,37,Bachelors,0,74,26,30,38,7.0,6,64,Rural,HR Executive,95527,0 +3584,Female,35,Masters,11,6,46,26,30,7.0,5,82,Rural,HR Executive,75956,0 +3585,Male,24,Bachelors,16,73,46,78,36,0.0,7,58,Semi-Urban,Data Analyst,128326,1 +3586,Male,37,High School,5,23,74,20,26,5.0,1,69,Semi-Urban,Manager,22586,0 +3587,Male,47,Diploma,10,41,81,73,64,2.0,6,99,Urban,Data Analyst,85078,1 +3588,Female,40,Bachelors,17,39,46,38,66,4.0,0,64,Rural,Manager,68945,0 +3589,Male,55,High School,7,37,61,44,28,1.0,6,8,Urban,ML Engineer,127020,0 +3590,Male,49,High School,6,4,95,32,94,4.0,1,84,Urban,HR Executive,129162,0 +3591,Other,33,Diploma,11,16,33,90,83,8.0,4,62,Urban,HR Executive,111658,0 +3592,Male,44,Masters,2,35,73,77,82,4.0,3,67,Urban,Software Engineer,92206,1 +3593,Male,38,Masters,7,55,93,41,89,6.0,6,31,Urban,Data Analyst,78701,0 +3594,Male,55,Bachelors,8,62,67,51,77,6.0,6,84,Semi-Urban,HR Executive,130293,1 +3595,Male,47,High School,1,24,76,88,39,4.0,0,74,Urban,ML Engineer,33668,1 +3596,Female,34,Diploma,17,21,90,74,74,3.0,5,97,Urban,ML Engineer,56309,1 +3597,Male,35,High School,13,67,53,13,91,7.0,5,43,Urban,Manager,111184,0 +3598,Male,45,High School,0,41,21,66,7,5.0,6,26,Urban,HR Executive,78794,0 +3599,Male,29,Bachelors,14,45,72,77,8,6.0,0,90,Semi-Urban,HR Executive,72283,1 +3600,Female,49,Bachelors,6,1,77,93,11,7.0,6,43,Urban,ML Engineer,89609,0 +3601,Male,58,Masters,3,75,70,52,30,6.0,5,2,Urban,Data Analyst,34565,0 +3602,Male,39,Bachelors,11,71,85,46,39,1.0,2,66,Semi-Urban,HR Executive,127293,1 +3603,Male,33,Diploma,17,30,69,40,72,2.0,2,59,Semi-Urban,Data Analyst,30447,0 +3604,Male,31,Bachelors,15,31,47,7,64,7.0,3,32,Urban,ML Engineer,47104,0 +3605,Male,31,PhD,2,47,84,83,97,9.0,0,73,Rural,Manager,67696,1 +3606,Male,36,Bachelors,17,75,65,88,29,5.0,2,26,Semi-Urban,ML Engineer,149844,1 +3607,Female,36,Bachelors,9,86,14,40,87,3.0,6,18,Urban,HR Executive,91961,0 +3608,Male,47,PhD,11,70,66,63,24,3.0,0,27,Rural,Manager,144209,0 +3609,Female,26,Diploma,7,63,35,38,31,6.0,1,82,Urban,HR Executive,123794,0 +3610,Other,31,Diploma,13,46,42,51,86,6.0,1,26,Urban,ML Engineer,105360,0 +3611,Male,30,PhD,15,68,50,80,30,1.0,7,46,Semi-Urban,ML Engineer,147133,1 +3612,Male,55,Bachelors,1,51,86,1,66,3.0,0,13,Urban,Data Analyst,33343,0 +3613,Male,46,Bachelors,0,95,67,96,76,2.0,5,39,Rural,Manager,36878,1 +3614,Female,44,Masters,9,6,74,8,75,4.0,1,62,Urban,Software Engineer,43494,0 +3615,Male,49,Bachelors,6,37,32,33,59,4.0,4,17,Semi-Urban,Data Analyst,145780,0 +3616,Male,30,Masters,15,58,5,4,26,9.0,4,1,Semi-Urban,Manager,88126,0 +3617,Male,43,Diploma,8,22,65,35,81,7.0,0,45,Urban,Manager,48674,0 +3618,Female,48,Masters,13,15,98,16,12,1.0,5,31,Urban,Manager,66075,0 +3619,Female,56,Bachelors,18,87,49,21,2,0.0,7,39,Urban,Software Engineer,40589,0 +3620,Male,59,Masters,17,54,29,51,10,4.0,1,10,Urban,ML Engineer,115791,0 +3621,Female,29,Bachelors,17,91,90,12,74,8.0,0,42,Urban,ML Engineer,148201,0 +3622,Male,38,High School,11,36,88,95,28,4.0,7,61,Urban,Software Engineer,146636,1 +3623,Male,37,Bachelors,4,16,76,87,66,0.0,3,52,Urban,HR Executive,115217,0 +3624,Female,46,High School,4,63,75,96,99,6.0,7,7,Urban,HR Executive,88845,1 +3625,Male,49,High School,18,35,87,96,97,7.0,7,58,Semi-Urban,ML Engineer,98403,1 +3626,Male,42,Bachelors,13,44,79,23,52,5.0,6,38,Semi-Urban,Data Analyst,50642,0 +3627,Male,24,Bachelors,11,61,93,0,99,8.0,2,39,Rural,Software Engineer,91454,0 +3628,Female,37,High School,1,34,80,81,55,2.0,3,81,Rural,HR Executive,70580,1 +3629,Female,39,Bachelors,8,30,6,92,90,1.0,6,54,Urban,Data Analyst,94495,0 +3630,Female,55,Bachelors,7,69,16,19,92,1.0,3,57,Urban,ML Engineer,104485,0 +3631,Female,45,Bachelors,7,78,62,7,60,5.0,4,31,Semi-Urban,HR Executive,56488,0 +3632,Male,25,Bachelors,15,39,95,4,0,0.0,7,99,Semi-Urban,Software Engineer,21262,1 +3633,Male,23,High School,8,78,43,63,43,5.0,6,30,Urban,Manager,35043,0 +3634,Male,40,Bachelors,12,29,2,59,67,1.0,1,81,Rural,ML Engineer,44053,0 +3635,Male,37,Diploma,11,77,84,51,45,5.0,5,7,Urban,Software Engineer,90594,0 +3636,Male,48,Bachelors,9,48,80,48,78,6.0,3,34,Semi-Urban,Software Engineer,132797,0 +3637,Female,41,PhD,8,70,29,2,49,4.0,7,15,Urban,Data Analyst,50589,0 +3638,Male,36,Bachelors,11,5,46,36,82,4.0,5,94,Semi-Urban,Data Analyst,121321,0 +3639,Male,47,Bachelors,19,47,62,74,92,0.0,1,78,Rural,Software Engineer,32275,1 +3640,Male,21,Masters,5,79,90,2,82,9.0,5,39,Semi-Urban,Software Engineer,119932,0 +3641,Male,28,Diploma,14,22,15,22,31,3.0,7,76,Semi-Urban,ML Engineer,100955,0 +3642,Female,36,High School,14,60,42,93,19,8.0,1,74,Urban,HR Executive,111137,1 +3643,Male,42,Bachelors,3,2,10,45,14,2.0,4,27,Urban,ML Engineer,101142,0 +3644,Male,48,Masters,11,70,73,22,27,4.0,5,93,Urban,Data Analyst,86815,1 +3645,Female,47,Bachelors,1,66,26,24,20,2.0,6,72,Urban,ML Engineer,58486,0 +3646,Male,25,High School,17,91,53,85,2,2.0,0,25,Urban,ML Engineer,22054,1 +3647,Male,52,Bachelors,11,4,61,69,54,3.0,6,74,Urban,Manager,43154,0 +3648,Male,32,Diploma,2,63,38,74,2,1.0,6,92,Semi-Urban,ML Engineer,40571,1 +3649,Male,47,Masters,12,16,75,96,79,0.0,1,38,Urban,ML Engineer,73541,0 +3650,Other,39,Bachelors,11,83,76,21,45,3.0,3,45,Urban,ML Engineer,67519,0 +3651,Female,41,High School,6,86,84,93,84,1.0,0,61,Semi-Urban,Software Engineer,64271,1 +3652,Male,44,Diploma,15,1,87,77,84,4.0,6,88,Urban,Data Analyst,28201,1 +3653,Female,24,Masters,14,46,60,43,12,9.0,5,67,Rural,Manager,51190,0 +3654,Male,22,Masters,18,54,48,44,93,5.0,7,18,Urban,Manager,42772,0 +3655,Male,45,High School,12,6,44,20,59,6.0,6,74,Semi-Urban,ML Engineer,72926,0 +3656,Male,38,Masters,10,32,89,49,52,3.0,1,86,Urban,Data Analyst,59500,1 +3657,Male,46,Diploma,6,60,74,49,84,2.0,3,3,Urban,ML Engineer,61169,0 +3658,Male,55,Bachelors,5,86,64,44,36,8.0,7,80,Rural,ML Engineer,116697,1 +3659,Female,24,Bachelors,4,29,14,78,7,3.0,0,42,Urban,Software Engineer,146478,0 +3660,Female,23,Masters,16,37,13,16,18,6.0,0,10,Urban,HR Executive,26277,0 +3661,Male,50,High School,0,34,70,64,11,9.0,0,77,Semi-Urban,Data Analyst,61156,1 +3662,Male,27,Masters,16,41,43,10,74,9.0,1,22,Urban,HR Executive,55757,0 +3663,Male,33,Masters,14,75,4,11,43,8.0,6,47,Urban,Manager,20160,0 +3664,Male,44,Diploma,11,20,55,83,61,9.0,5,77,Semi-Urban,HR Executive,115598,1 +3665,Male,24,Bachelors,0,13,27,53,93,1.0,4,46,Rural,ML Engineer,79267,0 +3666,Male,29,Diploma,18,37,0,8,6,5.0,1,25,Urban,Software Engineer,84127,0 +3667,Female,38,Bachelors,5,12,79,13,21,5.0,2,93,Semi-Urban,HR Executive,117092,0 +3668,Male,43,High School,18,68,55,96,60,8.0,3,17,Urban,Data Analyst,46862,1 +3669,Male,51,Bachelors,7,90,21,99,11,9.0,5,68,Semi-Urban,Data Analyst,84238,1 +3670,Male,49,Diploma,11,53,37,93,21,9.0,2,48,Urban,Software Engineer,48493,0 +3671,Male,43,Bachelors,5,50,52,75,96,7.0,0,82,Urban,Software Engineer,146384,1 +3672,Male,22,Masters,3,98,4,63,12,3.0,5,87,Urban,Software Engineer,61152,1 +3673,Female,57,High School,19,74,5,22,96,2.0,3,6,Semi-Urban,Software Engineer,25329,0 +3674,Male,39,High School,2,17,51,16,17,4.0,1,29,Urban,Software Engineer,78577,0 +3675,Female,41,Diploma,12,74,1,52,18,7.0,0,5,Urban,Data Analyst,34095,0 +3676,Male,38,Bachelors,9,90,66,16,35,0.0,4,77,Semi-Urban,Manager,69918,1 +3677,Male,51,Masters,13,64,58,49,38,0.0,1,60,Semi-Urban,HR Executive,42513,0 +3678,Male,58,Bachelors,1,1,56,87,91,0.0,7,3,Urban,HR Executive,34982,0 +3679,Female,58,High School,6,59,14,14,25,3.0,4,78,Urban,Data Analyst,74749,0 +3680,Male,23,High School,0,67,97,43,68,2.0,3,42,Urban,Software Engineer,20844,1 +3681,Female,39,Diploma,1,4,84,60,77,9.0,5,48,Rural,Data Analyst,119313,0 +3682,Male,33,Diploma,10,42,51,25,33,2.0,3,1,Urban,ML Engineer,23685,0 +3683,Female,30,Bachelors,5,61,80,7,44,8.0,4,96,Urban,Manager,45925,1 +3684,Male,45,Masters,0,98,44,46,87,8.0,4,98,Urban,ML Engineer,21719,1 +3685,Female,37,Bachelors,0,5,22,81,80,4.0,7,48,Urban,Manager,149076,0 +3686,Male,31,High School,13,44,32,96,20,8.0,5,97,Semi-Urban,Software Engineer,128810,1 +3687,Female,25,Masters,11,95,97,98,26,6.0,4,27,Urban,Software Engineer,120605,1 +3688,Male,45,Bachelors,4,98,79,53,91,7.0,3,91,Rural,Manager,122801,1 +3689,Male,35,High School,18,56,88,75,58,4.0,1,49,Semi-Urban,HR Executive,74591,1 +3690,Male,30,Bachelors,2,89,8,1,32,8.0,5,68,Rural,Data Analyst,100729,0 +3691,Female,45,PhD,13,12,94,46,9,0.0,0,39,Semi-Urban,ML Engineer,26970,0 +3692,Male,30,Masters,17,58,37,6,1,2.0,7,36,Rural,Manager,52776,0 +3693,Female,34,Diploma,3,87,5,29,5,1.0,3,88,Semi-Urban,Data Analyst,37089,0 +3694,Male,34,Diploma,15,64,76,24,20,4.0,3,90,Urban,Data Analyst,63166,1 +3695,Male,48,Diploma,7,79,79,43,36,3.0,5,30,Urban,HR Executive,131523,0 +3696,Male,54,Bachelors,12,67,8,12,12,3.0,2,75,Rural,ML Engineer,53395,0 +3697,Other,45,High School,13,88,64,68,41,6.0,2,18,Rural,HR Executive,146822,0 +3698,Female,53,High School,19,66,39,32,75,6.0,2,78,Semi-Urban,Data Analyst,125438,0 +3699,Female,48,Bachelors,13,25,57,46,35,0.0,5,21,Urban,HR Executive,84966,0 +3700,Male,52,High School,5,35,47,24,14,6.0,0,75,Urban,Data Analyst,83986,0 +3701,Female,49,PhD,8,91,96,40,46,6.0,4,12,Urban,ML Engineer,37684,0 +3702,Female,53,Diploma,14,39,95,29,4,8.0,3,58,Urban,HR Executive,125431,0 +3703,Male,25,High School,2,49,24,90,74,2.0,2,50,Urban,Software Engineer,57219,0 +3704,Female,59,Diploma,15,68,23,46,34,9.0,3,77,Semi-Urban,Software Engineer,99288,0 +3705,Female,33,Bachelors,7,90,70,8,52,7.0,7,0,Urban,Data Analyst,84738,0 +3706,Female,57,Masters,18,21,20,83,51,7.0,2,99,Rural,HR Executive,139903,0 +3707,Female,50,Diploma,12,27,62,86,77,4.0,6,46,Rural,HR Executive,70804,0 +3708,Male,46,Bachelors,12,2,92,53,75,6.0,5,56,Semi-Urban,Manager,63303,0 +3709,Male,25,Diploma,2,7,25,19,32,1.0,0,54,Semi-Urban,Manager,117720,0 +3710,Other,54,Masters,3,99,78,68,65,3.0,7,82,Urban,ML Engineer,62511,1 +3711,Male,26,Diploma,17,36,0,19,80,2.0,1,28,Urban,Manager,52523,0 +3712,Female,57,Bachelors,6,45,40,15,26,7.0,3,36,Urban,HR Executive,136912,0 +3713,Female,52,Bachelors,2,58,92,16,72,3.0,7,56,Urban,Manager,127561,0 +3714,Female,38,High School,4,17,81,52,9,7.0,5,89,Urban,Data Analyst,55711,0 +3715,Other,21,High School,13,50,97,75,32,6.0,2,43,Urban,Manager,76411,1 +3716,Male,54,Bachelors,12,75,15,83,40,1.0,1,13,Urban,Manager,144324,0 +3717,Male,39,Bachelors,5,1,43,40,18,1.0,0,48,Urban,ML Engineer,24339,0 +3718,Male,30,Bachelors,19,46,89,22,9,3.0,1,27,Urban,ML Engineer,101098,0 +3719,Male,22,High School,13,36,0,15,52,9.0,1,43,Urban,ML Engineer,75581,0 +3720,Male,21,High School,2,78,42,17,13,7.0,0,87,Urban,ML Engineer,113950,0 +3721,Male,21,Masters,18,61,12,38,95,0.0,4,17,Urban,ML Engineer,71816,0 +3722,Female,50,Masters,12,47,65,94,93,4.0,7,58,Urban,Manager,87784,1 +3723,Female,27,Bachelors,16,7,51,16,40,9.0,5,79,Rural,ML Engineer,135560,0 +3724,Male,29,High School,14,40,93,9,19,1.0,3,16,Urban,ML Engineer,21179,0 +3725,Male,29,Diploma,13,80,57,69,93,5.0,1,39,Semi-Urban,Data Analyst,72050,1 +3726,Female,29,Masters,8,9,96,40,33,6.0,2,55,Urban,HR Executive,115206,0 +3727,Male,22,Diploma,16,69,27,98,87,6.0,3,84,Semi-Urban,ML Engineer,113186,1 +3728,Male,24,Bachelors,17,33,34,91,20,5.0,6,50,Urban,Manager,106558,0 +3729,Male,59,Bachelors,18,56,29,57,93,7.0,5,92,Urban,Data Analyst,56823,0 +3730,Male,53,Bachelors,15,59,99,94,54,7.0,5,78,Urban,Software Engineer,36763,1 +3731,Male,37,High School,12,49,15,34,59,7.0,3,84,Rural,Data Analyst,49574,0 +3732,Other,29,Bachelors,19,41,52,50,27,8.0,6,38,Urban,Manager,123283,0 +3733,Male,49,Bachelors,2,25,26,29,42,5.0,0,75,Urban,ML Engineer,135416,0 +3734,Male,57,Bachelors,15,46,74,40,37,2.0,6,87,Urban,Software Engineer,22380,1 +3735,Male,38,Diploma,2,20,4,57,39,0.0,7,25,Semi-Urban,Data Analyst,108302,0 +3736,Male,31,Diploma,12,10,80,21,82,9.0,7,96,Urban,Manager,107480,0 +3737,Female,30,Bachelors,9,60,19,50,42,3.0,0,23,Semi-Urban,ML Engineer,88035,0 +3738,Female,52,Masters,2,50,27,5,25,4.0,7,18,Semi-Urban,Manager,128535,0 +3739,Female,58,Bachelors,7,57,39,28,41,6.0,5,17,Urban,Software Engineer,136620,0 +3740,Male,25,Bachelors,16,74,38,66,52,4.0,5,1,Rural,ML Engineer,118443,0 +3741,Female,23,Bachelors,1,12,8,82,47,3.0,5,69,Semi-Urban,ML Engineer,90872,0 +3742,Female,31,Diploma,14,84,4,62,93,5.0,2,4,Urban,Data Analyst,102421,0 +3743,Female,39,Bachelors,3,34,30,47,22,3.0,6,28,Semi-Urban,Software Engineer,132342,0 +3744,Male,43,Bachelors,18,24,78,70,74,8.0,7,79,Rural,HR Executive,132609,1 +3745,Male,51,Masters,16,49,4,0,61,0.0,6,20,Urban,Software Engineer,34201,0 +3746,Male,53,High School,6,0,44,34,19,2.0,0,21,Urban,ML Engineer,49821,0 +3747,Female,42,Masters,15,54,29,0,2,5.0,0,66,Urban,Data Analyst,70177,0 +3748,Male,33,High School,18,62,66,34,50,2.0,2,42,Urban,Software Engineer,66728,0 +3749,Male,32,Diploma,18,46,37,30,3,9.0,1,72,Urban,HR Executive,35857,0 +3750,Female,39,Masters,13,20,52,50,95,6.0,0,89,Urban,Software Engineer,130971,0 +3751,Female,29,Diploma,1,51,90,92,32,5.0,4,52,Urban,ML Engineer,117608,1 +3752,Female,25,Bachelors,16,65,83,3,49,5.0,1,13,Urban,Manager,129483,0 +3753,Male,55,Bachelors,11,65,37,19,83,0.0,1,0,Urban,ML Engineer,64006,0 +3754,Female,24,Masters,10,82,27,63,81,0.0,4,86,Urban,Manager,93775,1 +3755,Male,46,Masters,18,18,76,50,84,1.0,5,39,Urban,HR Executive,142456,0 +3756,Male,28,Bachelors,19,82,14,68,93,0.0,3,46,Rural,ML Engineer,77785,0 +3757,Male,48,Bachelors,5,59,53,26,22,0.0,7,16,Urban,ML Engineer,44821,0 +3758,Male,48,Bachelors,6,62,14,33,3,4.0,0,88,Rural,Software Engineer,68529,0 +3759,Male,50,Diploma,10,44,29,1,62,7.0,7,52,Semi-Urban,ML Engineer,114555,0 +3760,Female,43,Bachelors,0,34,36,73,70,3.0,1,34,Semi-Urban,Manager,88615,0 +3761,Male,46,Masters,7,82,11,15,53,5.0,1,97,Semi-Urban,ML Engineer,69804,0 +3762,Female,27,Bachelors,13,1,8,37,2,5.0,1,62,Urban,Software Engineer,142651,0 +3763,Male,30,Bachelors,9,46,66,45,30,7.0,7,87,Semi-Urban,HR Executive,67675,1 +3764,Male,43,Bachelors,5,66,89,68,23,4.0,1,27,Semi-Urban,HR Executive,105141,1 +3765,Male,28,Masters,1,37,81,67,37,4.0,7,20,Rural,Manager,102851,0 +3766,Male,36,PhD,0,4,81,49,46,1.0,2,16,Urban,Manager,124588,0 +3767,Male,27,Diploma,17,35,1,62,32,8.0,4,97,Urban,Software Engineer,94700,0 +3768,Male,29,Bachelors,6,43,10,81,39,8.0,0,30,Urban,Manager,28634,0 +3769,Male,35,Bachelors,8,46,62,26,7,6.0,3,86,Urban,Manager,80418,0 +3770,Male,53,Masters,4,82,17,99,87,1.0,6,88,Semi-Urban,Software Engineer,119082,1 +3771,Male,30,Bachelors,17,44,15,99,33,6.0,1,40,Rural,Manager,89884,0 +3772,Female,22,Diploma,4,46,28,8,79,3.0,3,93,Urban,Data Analyst,55178,0 +3773,Male,43,Masters,11,5,36,75,54,0.0,6,82,Rural,Manager,28317,0 +3774,Female,39,Bachelors,17,9,18,41,1,8.0,0,5,Urban,HR Executive,141807,0 +3775,Female,23,Masters,9,95,97,92,73,6.0,4,34,Semi-Urban,HR Executive,46882,1 +3776,Female,38,PhD,14,2,81,99,1,5.0,5,61,Urban,Manager,32319,1 +3777,Female,25,Bachelors,8,85,8,18,22,3.0,4,43,Urban,HR Executive,45785,0 +3778,Male,26,Diploma,5,15,48,66,58,5.0,2,96,Rural,Data Analyst,20605,0 +3779,Female,21,Bachelors,11,92,99,96,81,5.0,7,46,Urban,Manager,69866,1 +3780,Female,26,Diploma,5,34,33,10,48,5.0,3,71,Urban,Software Engineer,35380,0 +3781,Male,30,Bachelors,1,53,62,17,74,0.0,7,68,Semi-Urban,Data Analyst,33848,0 +3782,Male,58,Masters,13,95,45,48,25,9.0,1,92,Urban,Software Engineer,30660,1 +3783,Male,41,High School,3,56,6,29,43,4.0,3,47,Rural,Software Engineer,108381,0 +3784,Female,30,Bachelors,2,92,18,21,15,1.0,6,63,Semi-Urban,Data Analyst,81509,0 +3785,Female,58,Diploma,10,58,51,78,72,5.0,5,90,Semi-Urban,ML Engineer,51245,1 +3786,Male,52,Bachelors,6,54,92,1,67,7.0,4,9,Semi-Urban,Software Engineer,40186,0 +3787,Male,45,High School,15,29,53,95,97,9.0,0,89,Rural,Manager,90468,1 +3788,Male,47,High School,17,56,75,25,54,9.0,2,83,Rural,Software Engineer,114290,1 +3789,Male,43,Bachelors,19,93,70,76,27,4.0,4,37,Semi-Urban,Software Engineer,105706,1 +3790,Other,34,Bachelors,0,59,66,27,23,2.0,6,6,Semi-Urban,Software Engineer,82873,0 +3791,Male,32,Masters,9,63,42,73,36,0.0,1,20,Rural,ML Engineer,149004,0 +3792,Male,37,Masters,5,14,68,58,34,1.0,7,76,Semi-Urban,Data Analyst,92947,0 +3793,Male,55,High School,8,84,49,72,80,3.0,3,26,Semi-Urban,Manager,87570,0 +3794,Female,52,Diploma,10,35,29,79,19,5.0,4,1,Semi-Urban,Data Analyst,133852,0 +3795,Male,46,Masters,15,61,21,35,77,9.0,7,28,Rural,Manager,28600,0 +3796,Female,29,Bachelors,11,32,47,37,63,7.0,1,59,Semi-Urban,ML Engineer,87374,0 +3797,Male,24,Bachelors,6,18,81,84,50,0.0,4,40,Semi-Urban,ML Engineer,35922,0 +3798,Male,53,Bachelors,19,87,19,50,59,6.0,6,21,Urban,Software Engineer,27118,0 +3799,Male,49,Masters,16,43,19,9,65,6.0,2,57,Urban,Data Analyst,136371,0 +3800,Male,37,Diploma,8,13,70,81,18,9.0,5,72,Urban,HR Executive,127340,1 +3801,Male,28,Masters,14,88,86,83,93,1.0,2,75,Urban,Manager,125913,1 +3802,Female,55,Diploma,8,72,73,76,52,1.0,2,28,Urban,Manager,42140,1 +3803,Female,33,Diploma,8,29,39,14,74,1.0,7,47,Rural,Data Analyst,142574,0 +3804,Other,24,Diploma,3,71,93,58,50,0.0,6,99,Semi-Urban,ML Engineer,134125,1 +3805,Male,44,High School,16,75,41,55,43,6.0,2,83,Semi-Urban,HR Executive,131371,1 +3806,Other,59,Bachelors,5,50,92,66,64,4.0,2,98,Urban,Software Engineer,26866,1 +3807,Male,58,High School,6,28,43,47,24,0.0,2,40,Urban,Data Analyst,112996,0 +3808,Male,26,High School,10,28,33,45,44,2.0,6,54,Urban,ML Engineer,23880,0 +3809,Male,32,Bachelors,11,25,44,72,77,9.0,3,84,Rural,HR Executive,136849,0 +3810,Male,49,High School,11,74,62,33,18,4.0,1,99,Urban,Data Analyst,106688,1 +3811,Female,58,Bachelors,14,85,65,24,42,1.0,5,42,Rural,HR Executive,84972,0 +3812,Male,55,Diploma,10,52,32,55,93,0.0,5,94,Urban,ML Engineer,82683,0 +3813,Male,52,High School,13,53,21,55,59,5.0,6,3,Urban,ML Engineer,146136,0 +3814,Female,29,Masters,5,71,79,64,0,5.0,5,76,Urban,Data Analyst,93052,1 +3815,Male,23,Masters,9,21,67,44,49,7.0,4,86,Urban,HR Executive,33424,0 +3816,Male,30,High School,10,79,57,95,12,4.0,5,62,Urban,ML Engineer,78607,1 +3817,Male,36,Bachelors,18,87,40,88,81,1.0,1,79,Urban,Manager,41137,1 +3818,Female,35,High School,5,14,70,2,93,3.0,1,66,Urban,Software Engineer,102093,0 +3819,Female,30,Bachelors,4,55,77,90,82,2.0,0,78,Urban,ML Engineer,68088,1 +3820,Male,58,High School,2,35,70,19,46,3.0,2,19,Rural,Manager,39117,0 +3821,Male,43,Bachelors,15,47,54,87,93,4.0,1,38,Rural,ML Engineer,116002,0 +3822,Male,57,Bachelors,8,16,39,96,76,2.0,4,74,Urban,HR Executive,144001,0 +3823,Female,29,Masters,15,8,93,81,29,9.0,1,32,Semi-Urban,Data Analyst,123283,0 +3824,Male,53,High School,16,30,58,16,94,5.0,2,52,Urban,ML Engineer,119677,0 +3825,Male,37,Masters,7,1,46,79,73,6.0,1,36,Urban,HR Executive,126818,0 +3826,Male,53,High School,1,70,32,82,83,1.0,2,33,Rural,ML Engineer,134779,0 +3827,Male,55,Bachelors,8,30,25,41,70,8.0,3,16,Rural,HR Executive,34327,0 +3828,Male,38,Masters,6,88,55,74,17,1.0,7,32,Semi-Urban,Manager,34684,1 +3829,Female,29,Diploma,2,6,89,96,47,6.0,6,89,Urban,Data Analyst,81613,1 +3830,Male,34,Bachelors,4,54,40,52,38,0.0,6,3,Urban,ML Engineer,132130,0 +3831,Male,38,Bachelors,7,51,79,80,51,7.0,4,25,Semi-Urban,HR Executive,84399,1 +3832,Female,41,Bachelors,2,21,79,46,46,7.0,1,77,Urban,Data Analyst,78577,0 +3833,Female,25,Bachelors,13,56,43,97,26,4.0,5,88,Semi-Urban,Data Analyst,139843,1 +3834,Male,26,High School,12,65,44,92,35,6.0,4,98,Semi-Urban,Software Engineer,23485,1 +3835,Male,49,Bachelors,14,28,86,44,93,8.0,5,86,Urban,Data Analyst,31424,1 +3836,Male,54,Diploma,14,12,46,46,31,6.0,5,87,Urban,Software Engineer,122562,0 +3837,Female,59,Diploma,17,98,50,90,15,9.0,3,68,Rural,Manager,132097,1 +3838,Male,21,Diploma,14,89,27,74,86,8.0,0,13,Rural,Manager,28981,0 +3839,Female,46,High School,0,40,38,66,65,6.0,6,18,Urban,Software Engineer,79483,0 +3840,Female,40,Diploma,19,68,49,78,73,4.0,0,30,Semi-Urban,HR Executive,148224,0 +3841,Male,28,Masters,14,16,40,82,99,8.0,0,46,Semi-Urban,Manager,99040,0 +3842,Male,32,Masters,11,58,16,47,60,2.0,4,40,Semi-Urban,Software Engineer,114995,0 +3843,Male,48,Bachelors,11,30,21,88,1,3.0,5,39,Semi-Urban,Manager,44687,0 +3844,Male,44,High School,9,16,4,89,95,0.0,0,66,Urban,ML Engineer,92251,0 +3845,Male,58,Diploma,12,28,38,40,21,5.0,5,64,Rural,HR Executive,116096,0 +3846,Female,29,High School,1,59,69,64,53,9.0,5,70,Urban,Software Engineer,129483,1 +3847,Other,23,Bachelors,18,83,27,84,64,4.0,1,32,Urban,Software Engineer,74239,0 +3848,Male,53,Bachelors,0,68,55,30,65,6.0,5,3,Rural,Software Engineer,65569,0 +3849,Female,24,Bachelors,7,12,6,94,96,8.0,6,21,Semi-Urban,ML Engineer,94701,0 +3850,Male,28,Diploma,12,95,74,7,67,1.0,5,5,Urban,Software Engineer,67052,0 +3851,Male,48,Bachelors,0,26,79,84,55,7.0,0,17,Urban,ML Engineer,145979,0 +3852,Male,57,Masters,6,79,19,20,86,1.0,6,78,Urban,ML Engineer,94798,0 +3853,Female,33,Masters,15,36,24,33,18,4.0,1,21,Urban,ML Engineer,20931,0 +3854,Female,36,High School,8,21,15,20,23,7.0,4,97,Rural,Manager,139126,0 +3855,Female,43,Bachelors,16,63,26,13,38,6.0,4,67,Rural,Software Engineer,110199,0 +3856,Male,24,Bachelors,14,97,48,22,10,9.0,3,39,Rural,ML Engineer,52389,0 +3857,Male,28,Bachelors,3,88,74,9,97,3.0,0,18,Semi-Urban,Software Engineer,33219,0 +3858,Male,39,Masters,7,50,23,36,13,8.0,0,22,Semi-Urban,Data Analyst,59629,0 +3859,Male,53,Bachelors,8,46,56,74,87,6.0,6,4,Semi-Urban,Software Engineer,132100,0 +3860,Female,57,Diploma,3,17,98,54,68,8.0,0,41,Urban,ML Engineer,49796,0 +3861,Female,32,High School,15,66,43,45,87,1.0,7,89,Urban,HR Executive,145210,1 +3862,Female,35,Bachelors,2,76,39,28,41,0.0,4,82,Urban,ML Engineer,43708,0 +3863,Male,26,Bachelors,14,62,19,7,57,6.0,3,98,Urban,Software Engineer,70025,0 +3864,Male,27,Diploma,3,98,26,65,28,0.0,3,81,Semi-Urban,ML Engineer,64514,1 +3865,Male,51,PhD,8,0,51,69,22,5.0,0,96,Rural,HR Executive,40702,0 +3866,Male,37,Bachelors,18,33,14,31,66,8.0,2,16,Rural,HR Executive,112368,0 +3867,Male,43,Masters,4,12,14,41,56,2.0,3,58,Urban,HR Executive,107604,0 +3868,Female,43,Diploma,6,63,72,43,51,1.0,2,80,Urban,ML Engineer,125714,1 +3869,Female,54,Bachelors,8,51,47,54,24,6.0,6,69,Urban,Manager,29463,0 +3870,Male,23,Bachelors,9,22,94,91,43,8.0,2,41,Urban,Software Engineer,117871,1 +3871,Male,57,Bachelors,16,87,67,59,28,0.0,1,18,Urban,Data Analyst,108135,0 +3872,Male,52,Masters,13,66,98,34,50,1.0,0,43,Rural,Software Engineer,109026,1 +3873,Male,23,High School,12,65,57,21,93,6.0,7,92,Urban,Manager,78116,1 +3874,Female,26,PhD,18,21,75,95,46,3.0,1,17,Semi-Urban,Manager,121761,0 +3875,Male,45,High School,11,19,24,50,3,7.0,1,6,Urban,Data Analyst,30497,0 +3876,Male,59,Diploma,8,27,4,10,29,4.0,0,78,Rural,ML Engineer,123796,0 +3877,Male,30,Masters,1,92,6,21,98,7.0,2,13,Urban,Data Analyst,58986,0 +3878,Female,39,Bachelors,12,91,82,18,75,2.0,0,43,Urban,HR Executive,140983,0 +3879,Male,30,Bachelors,2,88,18,78,92,7.0,3,32,Urban,Manager,93642,0 +3880,Male,35,Bachelors,17,11,0,94,57,4.0,7,35,Urban,Software Engineer,90779,0 +3881,Male,48,Bachelors,12,1,48,23,45,0.0,5,45,Semi-Urban,Manager,52913,0 +3882,Female,29,Bachelors,4,21,30,22,65,8.0,5,17,Semi-Urban,HR Executive,147850,0 +3883,Other,54,Diploma,10,44,38,5,10,8.0,6,89,Rural,ML Engineer,145887,0 +3884,Male,44,Masters,1,44,87,34,73,7.0,7,67,Urban,ML Engineer,66141,0 +3885,Female,25,Bachelors,9,24,58,2,79,1.0,4,77,Semi-Urban,ML Engineer,129314,0 +3886,Female,47,Bachelors,11,12,48,57,87,1.0,7,78,Semi-Urban,Software Engineer,56148,0 +3887,Female,45,Masters,10,51,0,83,99,0.0,0,56,Semi-Urban,Data Analyst,101468,0 +3888,Female,49,Bachelors,3,33,9,43,79,9.0,2,71,Urban,HR Executive,119247,0 +3889,Female,52,Masters,9,50,66,95,11,6.0,1,27,Semi-Urban,Software Engineer,145371,0 +3890,Male,38,Bachelors,15,36,14,23,27,9.0,2,21,Semi-Urban,ML Engineer,108821,0 +3891,Female,28,Bachelors,16,36,83,26,68,8.0,7,60,Urban,Manager,102497,0 +3892,Male,40,High School,3,50,75,64,32,2.0,2,37,Urban,Manager,95886,0 +3893,Female,50,Masters,7,52,4,87,94,7.0,6,81,Urban,Data Analyst,68036,0 +3894,Male,30,Bachelors,14,10,91,43,58,0.0,0,0,Urban,ML Engineer,110045,0 +3895,Female,48,Diploma,10,8,2,72,1,4.0,2,96,Semi-Urban,Data Analyst,69965,0 +3896,Female,40,Bachelors,14,55,0,14,43,9.0,4,56,Urban,Data Analyst,55515,0 +3897,Male,49,High School,0,79,26,87,9,9.0,3,32,Urban,Manager,119508,0 +3898,Female,46,Bachelors,4,73,10,52,8,4.0,7,23,Semi-Urban,Data Analyst,63245,0 +3899,Male,37,Bachelors,3,25,78,6,25,8.0,2,21,Urban,ML Engineer,70476,0 +3900,Female,28,Masters,13,22,9,29,92,4.0,2,52,Urban,Manager,30115,0 +3901,Male,52,Masters,0,71,22,16,99,3.0,7,34,Rural,Manager,61722,0 +3902,Male,42,High School,3,11,12,16,82,2.0,0,69,Rural,HR Executive,76234,0 +3903,Female,52,Bachelors,1,27,6,18,89,3.0,3,49,Urban,Data Analyst,124546,0 +3904,Male,56,High School,3,5,90,37,52,4.0,2,17,Urban,HR Executive,129793,0 +3905,Female,35,High School,7,58,90,89,10,9.0,4,87,Rural,HR Executive,74639,1 +3906,Male,39,High School,8,45,33,85,66,0.0,2,83,Urban,HR Executive,112595,1 +3907,Male,37,High School,6,40,1,60,54,4.0,1,60,Semi-Urban,Data Analyst,28279,0 +3908,Male,25,High School,5,30,17,12,99,3.0,7,88,Semi-Urban,HR Executive,89530,0 +3909,Male,56,Masters,2,65,83,62,97,8.0,1,65,Semi-Urban,HR Executive,140605,1 +3910,Male,58,High School,7,32,22,82,84,9.0,5,41,Rural,Data Analyst,48187,0 +3911,Male,47,Bachelors,18,57,71,65,57,9.0,4,96,Urban,HR Executive,99226,1 +3912,Male,26,Diploma,16,79,22,33,9,8.0,1,80,Urban,Manager,39834,0 +3913,Male,29,Diploma,17,95,57,33,99,5.0,4,94,Semi-Urban,Manager,97189,1 +3914,Other,22,Diploma,15,64,57,80,25,9.0,4,28,Urban,ML Engineer,139259,0 +3915,Other,40,Masters,6,51,31,26,69,6.0,3,2,Urban,Manager,120549,0 +3916,Male,23,Bachelors,19,57,45,50,59,5.0,0,92,Rural,Data Analyst,93050,1 +3917,Female,54,Bachelors,12,24,41,6,63,7.0,5,91,Rural,Data Analyst,59811,0 +3918,Male,50,Bachelors,13,24,15,7,82,0.0,3,97,Urban,Data Analyst,128622,0 +3919,Female,46,Bachelors,0,67,32,5,6,5.0,6,77,Semi-Urban,HR Executive,68240,0 +3920,Female,55,Bachelors,18,44,15,53,73,6.0,0,62,Urban,Software Engineer,51680,0 +3921,Female,21,Masters,2,2,1,84,55,8.0,7,46,Urban,Software Engineer,96958,0 +3922,Male,51,Bachelors,9,0,81,55,50,7.0,0,64,Semi-Urban,ML Engineer,137348,0 +3923,Female,50,Masters,11,77,96,74,44,9.0,2,72,Urban,Manager,144459,1 +3924,Male,39,Bachelors,6,53,6,86,21,6.0,5,19,Semi-Urban,Manager,143564,0 +3925,Other,49,Diploma,15,9,87,17,37,5.0,5,89,Semi-Urban,Software Engineer,105472,0 +3926,Male,46,Bachelors,13,16,71,53,49,1.0,3,72,Rural,Manager,88313,0 +3927,Female,43,Bachelors,6,94,3,80,50,2.0,5,81,Urban,Software Engineer,57136,1 +3928,Female,43,Masters,6,91,24,56,55,7.0,4,17,Urban,Software Engineer,40728,0 +3929,Female,57,Diploma,13,93,29,69,20,2.0,7,99,Semi-Urban,Manager,22124,1 +3930,Male,39,Diploma,4,65,54,10,48,4.0,3,77,Rural,Data Analyst,102578,0 +3931,Female,59,Diploma,10,5,40,99,73,6.0,7,53,Rural,HR Executive,72866,0 +3932,Male,52,Masters,9,81,33,63,53,5.0,3,68,Rural,Manager,73908,1 +3933,Female,48,Bachelors,3,44,81,5,55,5.0,0,16,Urban,Manager,57484,0 +3934,Male,23,Masters,10,95,48,46,34,1.0,6,49,Rural,Software Engineer,46224,1 +3935,Male,39,Masters,1,21,57,85,77,9.0,5,27,Semi-Urban,Software Engineer,44548,0 +3936,Male,44,PhD,18,29,82,29,8,2.0,1,32,Urban,Manager,108841,0 +3937,Male,47,Bachelors,14,9,58,73,28,4.0,5,11,Urban,ML Engineer,111567,0 +3938,Male,42,Diploma,4,36,7,49,50,3.0,2,9,Urban,ML Engineer,47970,0 +3939,Male,28,Bachelors,19,33,34,53,28,3.0,5,39,Semi-Urban,ML Engineer,46039,0 +3940,Male,37,PhD,6,83,43,77,23,9.0,6,69,Urban,Data Analyst,85754,1 +3941,Female,34,Masters,13,7,69,86,10,4.0,3,30,Urban,Manager,146009,0 +3942,Female,51,Diploma,15,83,18,48,44,4.0,6,94,Urban,Software Engineer,50899,1 +3943,Male,38,Bachelors,0,5,17,30,40,6.0,7,83,Urban,Data Analyst,22021,0 +3944,Male,42,Bachelors,5,29,68,5,55,8.0,5,20,Urban,HR Executive,84420,0 +3945,Male,27,PhD,0,88,27,74,12,5.0,0,30,Rural,ML Engineer,122940,0 +3946,Male,47,Bachelors,14,26,39,92,35,0.0,6,51,Urban,Manager,79234,0 +3947,Female,57,Bachelors,3,86,81,13,62,3.0,6,68,Rural,HR Executive,27901,1 +3948,Female,37,Bachelors,6,77,10,54,51,8.0,1,83,Urban,ML Engineer,124148,0 +3949,Male,55,Bachelors,2,63,8,1,5,7.0,4,54,Urban,Manager,29270,0 +3950,Male,23,Bachelors,16,51,33,81,44,0.0,1,9,Rural,Software Engineer,26200,0 +3951,Male,22,PhD,2,35,59,38,19,4.0,4,33,Urban,Data Analyst,68163,0 +3952,Female,23,High School,15,19,76,99,61,2.0,0,89,Semi-Urban,Software Engineer,60137,1 +3953,Other,41,PhD,6,42,19,75,31,7.0,2,91,Urban,Software Engineer,130138,0 +3954,Male,57,Masters,17,75,47,8,88,1.0,6,30,Rural,Data Analyst,31650,0 +3955,Male,31,Bachelors,9,73,4,87,4,2.0,2,93,Semi-Urban,Data Analyst,146478,1 +3956,Female,21,Bachelors,16,93,22,5,60,0.0,4,54,Rural,Software Engineer,37568,0 +3957,Female,39,Diploma,2,16,40,86,13,3.0,5,6,Rural,ML Engineer,81864,0 +3958,Male,41,PhD,16,6,8,93,31,1.0,5,25,Rural,Manager,47552,0 +3959,Male,48,Masters,9,42,24,17,8,4.0,5,68,Rural,Data Analyst,98597,0 +3960,Male,38,PhD,2,67,27,46,25,7.0,6,28,Urban,HR Executive,24580,0 +3961,Male,30,Bachelors,9,58,46,95,13,8.0,5,6,Rural,Manager,22624,0 +3962,Male,57,Bachelors,15,99,15,4,55,3.0,2,12,Urban,Software Engineer,148853,0 +3963,Male,39,PhD,0,73,30,35,56,9.0,5,95,Rural,HR Executive,131520,0 +3964,Male,34,Bachelors,6,26,76,79,70,7.0,0,65,Semi-Urban,Manager,135514,1 +3965,Male,21,High School,0,98,32,21,36,5.0,1,34,Semi-Urban,ML Engineer,65220,0 +3966,Female,47,PhD,0,42,2,7,24,8.0,0,22,Rural,Data Analyst,26172,0 +3967,Male,32,PhD,1,68,82,27,80,9.0,4,91,Semi-Urban,Manager,90564,1 +3968,Male,57,Bachelors,15,15,18,65,25,1.0,7,25,Rural,ML Engineer,78904,0 +3969,Male,45,Bachelors,17,15,39,50,7,9.0,6,98,Urban,Manager,116559,0 +3970,Male,27,High School,14,51,40,12,95,5.0,0,23,Rural,ML Engineer,44237,0 +3971,Other,50,High School,2,13,73,16,91,0.0,1,53,Urban,Manager,94393,0 +3972,Male,48,Bachelors,4,37,29,8,4,6.0,4,30,Semi-Urban,Manager,138877,0 +3973,Male,28,Masters,14,16,60,18,66,5.0,4,72,Urban,Data Analyst,52059,0 +3974,Female,43,Bachelors,12,78,10,89,13,8.0,3,77,Urban,Software Engineer,144144,1 +3975,Male,32,Bachelors,14,38,33,61,27,7.0,1,21,Urban,Software Engineer,43926,0 +3976,Female,45,Bachelors,18,29,95,92,84,7.0,4,94,Urban,Manager,121961,1 +3977,Male,29,Diploma,8,31,2,41,46,8.0,5,10,Urban,ML Engineer,60052,0 +3978,Male,52,Masters,9,43,32,6,45,3.0,1,24,Rural,Data Analyst,100916,0 +3979,Male,37,Diploma,19,28,6,82,99,9.0,1,61,Urban,Manager,50056,0 +3980,Male,58,PhD,15,57,42,22,81,7.0,7,41,Urban,Manager,138052,0 +3981,Female,24,Diploma,10,98,62,7,32,8.0,5,83,Urban,Data Analyst,22980,1 +3982,Female,58,Masters,19,73,27,94,6,3.0,7,83,Semi-Urban,HR Executive,102559,1 +3983,Male,50,Bachelors,12,72,0,41,81,4.0,4,40,Rural,Software Engineer,66611,0 +3984,Male,44,Masters,5,71,34,27,6,0.0,5,52,Urban,HR Executive,137657,0 +3985,Female,22,Bachelors,7,29,48,22,36,6.0,2,19,Urban,ML Engineer,138649,0 +3986,Female,59,Masters,12,71,69,55,16,1.0,0,67,Rural,Data Analyst,63314,1 +3987,Male,29,High School,18,20,91,38,90,2.0,6,90,Urban,Data Analyst,101179,1 +3988,Male,44,High School,8,75,20,34,62,7.0,1,43,Urban,HR Executive,123583,0 +3989,Male,44,Bachelors,1,74,47,1,21,0.0,2,20,Urban,Manager,126911,0 +3990,Female,35,Masters,9,35,87,13,20,7.0,1,10,Rural,Software Engineer,138144,0 +3991,Male,27,Bachelors,16,13,94,74,25,8.0,2,38,Urban,ML Engineer,59178,0 +3992,Male,40,Masters,19,64,38,81,74,7.0,4,19,Semi-Urban,ML Engineer,26193,0 +3993,Female,56,Bachelors,13,60,18,51,75,4.0,4,10,Urban,Software Engineer,63945,0 +3994,Male,35,Bachelors,13,48,75,99,38,7.0,4,37,Rural,HR Executive,132498,1 +3995,Male,43,Bachelors,2,5,95,67,89,9.0,0,37,Urban,HR Executive,69415,0 +3996,Male,25,High School,18,35,13,66,84,3.0,7,52,Rural,HR Executive,44905,0 +3997,Male,38,High School,5,3,95,45,17,8.0,0,87,Urban,HR Executive,134059,0 +3998,Male,29,Bachelors,10,47,99,13,66,2.0,5,57,Urban,Manager,50565,0 +3999,Male,42,Diploma,11,50,74,60,2,2.0,4,98,Urban,HR Executive,131297,1 +4000,Male,54,Diploma,2,73,64,43,62,1.0,0,89,Urban,ML Engineer,145586,1 +4001,Male,21,Bachelors,15,94,4,44,76,3.0,6,84,Urban,Data Analyst,31433,0 +4002,Female,50,High School,19,61,26,0,77,7.0,5,66,Semi-Urban,Data Analyst,146403,0 +4003,Female,39,Masters,13,70,1,17,23,3.0,7,0,Semi-Urban,Data Analyst,50323,0 +4004,Male,23,Bachelors,2,94,32,4,63,4.0,3,27,Rural,ML Engineer,63431,0 +4005,Male,48,High School,18,17,26,3,45,7.0,4,16,Urban,HR Executive,72122,0 +4006,Male,30,Bachelors,15,89,82,72,76,1.0,7,51,Semi-Urban,Software Engineer,62788,1 +4007,Male,29,Diploma,4,47,13,65,21,1.0,1,48,Rural,ML Engineer,73269,0 +4008,Male,48,Diploma,4,6,81,46,7,4.0,5,77,Urban,ML Engineer,27049,0 +4009,Female,31,Bachelors,15,88,99,49,29,5.0,1,85,Urban,ML Engineer,56458,1 +4010,Male,36,Bachelors,14,5,11,71,47,8.0,5,63,Semi-Urban,ML Engineer,124295,0 +4011,Male,43,High School,14,67,86,79,17,7.0,5,56,Urban,ML Engineer,29163,1 +4012,Male,55,Bachelors,15,38,69,9,86,0.0,0,70,Semi-Urban,ML Engineer,60621,0 +4013,Female,31,Bachelors,17,63,35,56,40,4.0,4,34,Urban,Software Engineer,23305,0 +4014,Male,44,High School,7,51,87,43,54,4.0,1,56,Semi-Urban,ML Engineer,127285,1 +4015,Female,55,High School,0,98,98,76,47,3.0,1,1,Rural,Manager,141550,1 +4016,Male,41,Bachelors,2,43,46,23,9,6.0,6,40,Urban,Manager,65062,0 +4017,Female,34,High School,18,91,68,39,51,1.0,5,90,Urban,Manager,27488,1 +4018,Female,47,Bachelors,10,54,57,78,95,9.0,6,36,Rural,HR Executive,63952,0 +4019,Male,21,Bachelors,12,72,75,15,14,1.0,3,49,Semi-Urban,Software Engineer,65331,0 +4020,Male,47,Bachelors,2,12,46,40,20,8.0,5,66,Urban,Software Engineer,84249,0 +4021,Male,57,High School,12,78,46,87,77,8.0,3,69,Semi-Urban,HR Executive,120050,1 +4022,Male,46,PhD,11,81,80,82,60,0.0,7,80,Urban,Software Engineer,107435,1 +4023,Female,58,Diploma,15,10,62,30,39,6.0,2,40,Semi-Urban,Data Analyst,75777,0 +4024,Female,31,Masters,15,11,31,78,5,8.0,5,78,Semi-Urban,Data Analyst,66782,0 +4025,Female,31,High School,0,61,63,9,38,6.0,5,62,Rural,ML Engineer,100182,0 +4026,Female,25,High School,4,39,27,2,72,9.0,1,9,Rural,Software Engineer,40261,0 +4027,Male,25,Diploma,18,21,58,19,28,7.0,1,75,Rural,HR Executive,66429,0 +4028,Male,36,Bachelors,13,65,59,43,46,7.0,2,31,Urban,Software Engineer,144967,0 +4029,Female,34,Masters,4,44,1,17,86,2.0,0,78,Urban,Software Engineer,45016,0 +4030,Male,53,Masters,18,53,80,54,94,1.0,4,26,Urban,Manager,148177,0 +4031,Female,44,PhD,10,41,88,64,9,6.0,6,10,Semi-Urban,Software Engineer,64606,0 +4032,Male,25,Masters,6,98,13,54,76,4.0,5,2,Urban,Manager,144349,0 +4033,Male,51,Diploma,5,23,38,19,19,5.0,0,62,Urban,HR Executive,89383,0 +4034,Other,55,Masters,7,94,95,42,51,2.0,7,14,Urban,Manager,22573,1 +4035,Male,37,Bachelors,2,76,28,77,49,7.0,6,5,Urban,ML Engineer,42552,0 +4036,Other,32,Masters,10,81,56,77,17,7.0,6,5,Urban,ML Engineer,34494,0 +4037,Other,56,PhD,8,50,67,0,88,1.0,2,8,Urban,ML Engineer,112605,0 +4038,Female,59,Bachelors,7,74,70,9,36,0.0,6,76,Urban,Software Engineer,47569,0 +4039,Female,27,Masters,0,34,26,54,14,3.0,6,58,Rural,ML Engineer,91935,0 +4040,Male,34,Bachelors,8,98,80,92,37,1.0,0,58,Rural,HR Executive,105500,1 +4041,Female,36,Bachelors,16,95,82,89,69,4.0,6,51,Urban,Software Engineer,138163,1 +4042,Male,51,Diploma,10,51,51,22,79,7.0,7,12,Urban,Data Analyst,89820,0 +4043,Male,41,High School,11,93,78,7,77,0.0,7,95,Urban,Software Engineer,37936,1 +4044,Female,56,Bachelors,17,86,84,58,26,8.0,7,53,Rural,HR Executive,31947,1 +4045,Male,42,Diploma,3,64,46,87,53,0.0,1,91,Semi-Urban,Data Analyst,104409,1 +4046,Male,46,High School,14,59,89,8,60,4.0,3,13,Urban,Data Analyst,110824,0 +4047,Male,33,Bachelors,3,68,68,95,44,9.0,1,53,Semi-Urban,Manager,142683,1 +4048,Male,32,Bachelors,6,85,24,91,69,3.0,3,53,Semi-Urban,ML Engineer,66908,1 +4049,Female,57,High School,13,65,93,81,35,4.0,5,10,Urban,ML Engineer,36059,1 +4050,Male,40,Diploma,15,44,75,69,67,1.0,0,23,Semi-Urban,ML Engineer,24498,0 +4051,Female,34,Bachelors,3,48,90,0,15,8.0,0,88,Rural,ML Engineer,48710,0 +4052,Female,44,Diploma,1,66,86,42,12,0.0,2,52,Rural,Data Analyst,134204,1 +4053,Female,33,Bachelors,16,99,49,79,26,1.0,4,28,Semi-Urban,Data Analyst,149422,1 +4054,Male,30,Bachelors,16,9,8,39,50,6.0,2,82,Urban,ML Engineer,148093,0 +4055,Female,28,Diploma,2,71,1,15,46,2.0,7,55,Urban,Manager,109768,0 +4056,Male,51,Bachelors,4,25,94,87,26,9.0,7,55,Urban,Data Analyst,105213,1 +4057,Female,47,Bachelors,3,64,43,11,80,1.0,4,76,Urban,ML Engineer,148903,0 +4058,Male,51,Bachelors,1,14,3,6,40,4.0,5,65,Semi-Urban,Data Analyst,113226,0 +4059,Female,21,High School,10,70,91,68,48,3.0,3,58,Urban,HR Executive,72242,1 +4060,Other,55,High School,4,24,83,78,88,5.0,2,77,Rural,ML Engineer,21179,1 +4061,Male,37,Masters,14,89,54,83,21,7.0,4,65,Semi-Urban,ML Engineer,149618,1 +4062,Male,42,Diploma,1,55,2,16,27,9.0,2,68,Urban,Data Analyst,86047,0 +4063,Female,51,Bachelors,11,62,80,50,23,6.0,1,35,Rural,HR Executive,117625,0 +4064,Male,49,Bachelors,19,88,31,39,28,9.0,0,30,Rural,Software Engineer,124405,0 +4065,Female,32,PhD,7,26,44,69,56,0.0,5,11,Urban,Software Engineer,96692,0 +4066,Male,44,High School,18,75,85,42,44,4.0,3,67,Semi-Urban,HR Executive,99884,1 +4067,Male,25,High School,10,69,16,10,12,0.0,5,74,Urban,Data Analyst,90701,0 +4068,Other,27,Diploma,15,99,44,88,58,9.0,6,31,Urban,Data Analyst,21271,1 +4069,Female,38,Diploma,12,45,83,3,77,6.0,4,99,Urban,Data Analyst,129681,0 +4070,Female,46,Bachelors,14,66,88,27,31,7.0,6,66,Semi-Urban,Manager,47460,1 +4071,Male,36,Bachelors,6,60,42,49,76,3.0,1,72,Semi-Urban,Software Engineer,54234,0 +4072,Female,27,Bachelors,19,19,98,67,65,7.0,3,5,Urban,Data Analyst,143989,0 +4073,Male,39,Masters,3,68,62,96,1,5.0,7,12,Urban,Data Analyst,97365,1 +4074,Female,35,Masters,6,64,63,24,39,8.0,1,97,Semi-Urban,Manager,104560,1 +4075,Female,25,High School,0,95,18,26,10,2.0,5,70,Urban,Software Engineer,66964,0 +4076,Male,29,High School,8,19,90,59,48,4.0,6,77,Urban,Data Analyst,75345,1 +4077,Male,41,High School,11,10,31,56,19,6.0,2,41,Urban,Manager,64466,0 +4078,Male,54,Bachelors,9,16,41,75,25,9.0,6,81,Urban,HR Executive,94102,0 +4079,Female,42,Bachelors,17,1,75,88,99,9.0,1,82,Semi-Urban,ML Engineer,90579,1 +4080,Male,45,PhD,1,7,36,28,10,0.0,5,34,Urban,Data Analyst,146987,0 +4081,Female,22,Masters,7,16,40,63,96,3.0,2,50,Semi-Urban,ML Engineer,22564,0 +4082,Male,33,PhD,10,36,40,62,22,0.0,5,85,Rural,Data Analyst,99259,0 +4083,Female,34,Bachelors,8,49,33,64,0,7.0,1,28,Semi-Urban,HR Executive,85512,0 +4084,Female,22,Bachelors,2,18,87,76,41,4.0,5,53,Urban,Software Engineer,94412,0 +4085,Male,53,Bachelors,0,30,47,5,96,6.0,4,60,Semi-Urban,Software Engineer,136683,0 +4086,Male,38,Bachelors,16,31,37,90,25,7.0,6,57,Urban,ML Engineer,22460,0 +4087,Male,31,Masters,11,35,63,77,46,1.0,5,98,Urban,Software Engineer,86971,1 +4088,Female,35,Bachelors,13,26,66,95,79,9.0,6,77,Urban,Manager,60055,1 +4089,Female,57,Masters,9,58,63,43,29,6.0,5,92,Semi-Urban,Software Engineer,145718,1 +4090,Male,56,PhD,1,87,4,98,6,3.0,2,51,Urban,Software Engineer,109428,1 +4091,Female,38,Masters,16,21,74,90,4,0.0,4,88,Rural,ML Engineer,80957,1 +4092,Male,33,Bachelors,9,73,23,27,65,3.0,1,52,Rural,Data Analyst,133767,0 +4093,Male,38,Masters,1,51,26,61,45,2.0,0,0,Urban,Data Analyst,59544,0 +4094,Female,49,Diploma,7,29,35,89,79,2.0,0,19,Semi-Urban,Manager,31231,0 +4095,Male,43,Bachelors,13,86,49,3,36,2.0,3,54,Semi-Urban,Data Analyst,75589,0 +4096,Male,23,Masters,10,10,5,88,54,4.0,2,16,Urban,Manager,110509,0 +4097,Male,42,Bachelors,5,15,73,61,16,5.0,5,70,Urban,Data Analyst,114647,0 +4098,Male,29,PhD,13,38,34,4,73,8.0,3,85,Urban,Manager,30236,0 +4099,Male,49,High School,11,83,11,27,46,0.0,3,9,Semi-Urban,Data Analyst,112547,0 +4100,Male,42,Bachelors,6,78,49,12,81,6.0,5,11,Urban,Manager,91284,0 +4101,Female,59,Masters,13,2,3,48,48,9.0,6,7,Semi-Urban,HR Executive,78446,0 +4102,Male,24,Diploma,10,9,45,83,82,2.0,4,1,Urban,Manager,25780,0 +4103,Male,52,Masters,16,90,4,90,68,5.0,1,78,Semi-Urban,Data Analyst,101879,1 +4104,Male,51,Bachelors,15,4,5,66,82,3.0,3,33,Semi-Urban,Software Engineer,136085,0 +4105,Male,49,PhD,7,0,38,85,58,7.0,5,23,Urban,HR Executive,39678,0 +4106,Female,34,Bachelors,19,30,17,19,4,9.0,5,37,Urban,Data Analyst,33657,0 +4107,Other,27,Diploma,14,71,31,68,90,0.0,6,90,Semi-Urban,ML Engineer,135322,1 +4108,Male,30,Diploma,17,97,13,81,99,0.0,5,89,Semi-Urban,Software Engineer,35502,1 +4109,Female,51,Diploma,7,5,85,60,66,2.0,7,37,Semi-Urban,Manager,117094,0 +4110,Male,54,Masters,16,12,74,72,1,8.0,6,96,Rural,Software Engineer,138353,1 +4111,Male,33,Diploma,10,0,60,74,78,5.0,3,34,Rural,ML Engineer,148671,0 +4112,Male,41,Masters,11,57,21,39,71,7.0,4,74,Rural,Software Engineer,35651,0 +4113,Male,24,Bachelors,2,95,87,13,20,9.0,7,77,Rural,Manager,83959,1 +4114,Male,24,Bachelors,6,83,57,10,87,8.0,0,23,Urban,ML Engineer,35247,0 +4115,Female,42,Diploma,14,14,20,29,90,3.0,5,62,Urban,HR Executive,95160,0 +4116,Male,35,Bachelors,12,11,95,0,38,4.0,6,20,Semi-Urban,Data Analyst,89105,0 +4117,Female,25,Bachelors,2,88,28,60,16,5.0,5,86,Urban,Manager,102071,1 +4118,Male,38,Masters,8,86,97,73,54,7.0,2,60,Semi-Urban,ML Engineer,72509,1 +4119,Male,23,Diploma,0,34,72,52,82,2.0,5,66,Urban,ML Engineer,54044,0 +4120,Female,56,Bachelors,8,61,22,34,11,9.0,7,56,Semi-Urban,ML Engineer,84603,0 +4121,Male,42,High School,7,19,32,23,20,0.0,4,8,Urban,Data Analyst,45648,0 +4122,Male,33,Bachelors,16,44,75,21,40,6.0,6,99,Semi-Urban,Software Engineer,35847,1 +4123,Female,53,Bachelors,17,49,35,56,62,3.0,1,40,Urban,Software Engineer,107984,0 +4124,Female,45,Bachelors,9,1,41,64,48,9.0,4,66,Urban,Manager,140688,0 +4125,Female,40,Bachelors,16,53,5,69,38,0.0,2,67,Rural,HR Executive,60978,0 +4126,Female,34,Masters,16,96,75,11,99,0.0,1,15,Urban,HR Executive,149754,0 +4127,Female,29,Masters,7,90,51,15,79,1.0,5,17,Urban,Manager,100616,0 +4128,Female,32,Bachelors,18,13,12,72,62,0.0,6,16,Urban,Software Engineer,41231,0 +4129,Male,28,Diploma,7,52,3,34,44,7.0,3,87,Urban,HR Executive,88861,0 +4130,Male,40,Diploma,4,99,64,85,47,3.0,2,85,Urban,ML Engineer,41108,1 +4131,Male,24,Bachelors,14,49,71,73,94,4.0,2,63,Semi-Urban,HR Executive,22738,1 +4132,Male,56,Masters,14,61,70,64,62,8.0,1,29,Rural,Software Engineer,89861,0 +4133,Female,48,Bachelors,6,57,27,12,56,5.0,4,53,Semi-Urban,Data Analyst,118121,0 +4134,Female,38,Bachelors,17,59,15,97,12,4.0,7,62,Urban,Data Analyst,108752,0 +4135,Male,31,Bachelors,12,21,35,23,91,3.0,0,50,Rural,Manager,106229,0 +4136,Male,21,Bachelors,19,33,92,15,23,9.0,7,80,Semi-Urban,ML Engineer,89948,0 +4137,Female,23,Bachelors,10,97,37,58,60,3.0,7,23,Urban,HR Executive,53235,0 +4138,Male,24,Masters,11,32,55,53,42,4.0,4,13,Urban,HR Executive,62267,0 +4139,Female,33,High School,6,16,59,31,85,5.0,4,45,Urban,Manager,147647,0 +4140,Male,58,Diploma,16,76,41,28,33,6.0,4,53,Semi-Urban,ML Engineer,45453,0 +4141,Male,39,Diploma,18,82,20,44,5,7.0,0,44,Rural,HR Executive,56828,0 +4142,Male,29,High School,0,25,61,56,46,7.0,0,73,Urban,HR Executive,135546,0 +4143,Male,50,Bachelors,14,26,35,87,54,4.0,4,81,Urban,Manager,92593,0 +4144,Female,54,Diploma,0,8,47,28,40,3.0,7,76,Urban,HR Executive,125828,0 +4145,Female,44,Bachelors,15,80,90,28,51,2.0,0,22,Rural,Manager,79856,0 +4146,Female,57,High School,12,11,79,23,28,5.0,3,67,Urban,Manager,71071,0 +4147,Male,51,Bachelors,13,72,97,69,54,0.0,3,84,Rural,HR Executive,132255,1 +4148,Male,43,Diploma,11,3,45,61,19,0.0,7,41,Urban,HR Executive,143388,0 +4149,Female,36,Masters,6,52,26,32,95,6.0,7,59,Rural,Manager,113900,0 +4150,Female,37,High School,10,59,39,42,7,4.0,6,69,Urban,Software Engineer,83825,0 +4151,Male,28,Bachelors,12,49,60,30,46,1.0,3,3,Rural,Data Analyst,54514,0 +4152,Male,28,Bachelors,11,60,29,13,27,2.0,7,0,Urban,Software Engineer,33601,0 +4153,Female,54,Bachelors,5,60,29,85,6,8.0,0,94,Urban,HR Executive,68919,1 +4154,Male,32,Masters,11,95,61,36,85,4.0,2,5,Urban,ML Engineer,28041,0 +4155,Male,38,Masters,8,19,74,72,1,1.0,7,19,Semi-Urban,ML Engineer,67305,0 +4156,Male,56,Bachelors,3,58,64,16,73,1.0,5,50,Urban,Software Engineer,31967,0 +4157,Male,52,High School,13,45,20,48,29,5.0,0,6,Urban,Manager,74335,0 +4158,Female,50,Diploma,11,74,12,39,48,3.0,6,71,Rural,ML Engineer,61191,0 +4159,Other,41,High School,12,4,34,94,15,9.0,1,54,Semi-Urban,Data Analyst,41222,0 +4160,Male,48,Masters,10,44,49,17,89,7.0,5,33,Urban,ML Engineer,40451,0 +4161,Male,30,High School,4,59,40,30,19,4.0,4,84,Semi-Urban,Data Analyst,61128,0 +4162,Male,38,Masters,16,20,8,33,74,1.0,7,55,Urban,Data Analyst,26606,0 +4163,Male,23,Bachelors,1,67,38,20,54,3.0,7,1,Urban,Data Analyst,65086,0 +4164,Male,41,Bachelors,1,80,25,18,81,0.0,4,42,Rural,HR Executive,79306,0 +4165,Female,51,Bachelors,10,35,50,69,93,5.0,1,99,Semi-Urban,ML Engineer,42602,1 +4166,Male,55,High School,11,4,21,48,97,5.0,6,97,Semi-Urban,Software Engineer,101879,0 +4167,Male,23,Bachelors,8,94,0,85,74,8.0,7,24,Urban,Data Analyst,75499,0 +4168,Male,40,High School,11,28,23,58,32,7.0,4,71,Semi-Urban,Software Engineer,74973,0 +4169,Male,57,Masters,11,43,17,65,47,0.0,0,32,Urban,Manager,95686,0 +4170,Male,23,Diploma,9,27,43,4,67,4.0,3,60,Rural,Data Analyst,111193,0 +4171,Male,53,Bachelors,6,84,70,53,65,4.0,4,20,Urban,ML Engineer,54595,0 +4172,Other,51,Bachelors,8,35,19,45,36,5.0,5,67,Rural,Data Analyst,95560,0 +4173,Male,32,PhD,8,21,74,58,82,4.0,0,7,Urban,Data Analyst,41224,0 +4174,Male,23,Bachelors,0,21,55,0,67,7.0,3,89,Urban,Software Engineer,78473,0 +4175,Female,25,Diploma,15,66,81,76,73,9.0,4,58,Urban,Data Analyst,110425,1 +4176,Other,31,Bachelors,9,27,85,41,50,0.0,7,79,Semi-Urban,Data Analyst,129058,0 +4177,Male,26,Masters,9,65,54,73,49,7.0,7,79,Semi-Urban,HR Executive,133720,1 +4178,Female,28,Bachelors,5,37,78,45,96,8.0,2,47,Semi-Urban,ML Engineer,121718,0 +4179,Male,59,Bachelors,19,4,94,26,62,1.0,0,95,Urban,HR Executive,136444,0 +4180,Male,38,High School,5,0,60,60,13,9.0,1,24,Rural,ML Engineer,82176,0 +4181,Male,41,Bachelors,6,7,55,54,45,2.0,5,81,Urban,Software Engineer,62963,0 +4182,Female,52,Diploma,2,55,10,68,58,4.0,7,18,Urban,HR Executive,106918,0 +4183,Female,23,Diploma,15,39,20,98,31,8.0,0,50,Semi-Urban,Software Engineer,52541,0 +4184,Male,32,Bachelors,5,34,24,32,81,4.0,5,76,Urban,Data Analyst,117958,0 +4185,Male,44,Masters,5,45,26,23,5,2.0,3,41,Urban,HR Executive,72730,0 +4186,Female,39,Diploma,15,44,77,73,15,6.0,4,41,Urban,Software Engineer,48664,0 +4187,Male,43,Masters,16,77,60,96,87,5.0,2,53,Urban,Software Engineer,137756,1 +4188,Male,27,Bachelors,2,16,8,95,29,9.0,7,58,Urban,Manager,93155,0 +4189,Female,44,Diploma,2,48,89,71,39,5.0,6,56,Urban,HR Executive,115305,1 +4190,Female,40,Bachelors,14,74,66,20,60,3.0,1,97,Rural,Software Engineer,38933,1 +4191,Female,50,Diploma,19,6,11,15,89,5.0,4,49,Rural,HR Executive,32765,0 +4192,Female,47,Diploma,10,69,91,50,13,7.0,2,13,Urban,HR Executive,116587,0 +4193,Male,47,Bachelors,2,27,25,45,17,3.0,3,62,Urban,ML Engineer,107664,0 +4194,Female,21,Bachelors,6,5,91,44,47,9.0,0,95,Urban,Manager,131747,0 +4195,Female,27,Bachelors,6,84,64,9,29,2.0,4,58,Rural,Software Engineer,72055,0 +4196,Male,37,Bachelors,19,6,28,8,44,7.0,1,89,Semi-Urban,ML Engineer,93987,0 +4197,Male,51,High School,16,51,46,17,6,8.0,1,38,Rural,HR Executive,128013,0 +4198,Male,57,Bachelors,12,26,54,74,72,0.0,2,54,Urban,HR Executive,31127,0 +4199,Male,33,Diploma,3,58,40,34,45,8.0,1,30,Urban,Data Analyst,136142,0 +4200,Female,31,Diploma,12,34,26,48,22,4.0,1,55,Urban,ML Engineer,95726,0 +4201,Female,48,High School,3,12,94,35,83,9.0,1,81,Urban,HR Executive,82601,0 +4202,Male,28,Bachelors,1,39,82,21,82,2.0,2,80,Urban,ML Engineer,30831,0 +4203,Male,35,Masters,8,75,69,65,67,4.0,2,56,Urban,ML Engineer,78190,1 +4204,Other,38,High School,11,70,66,66,26,4.0,4,87,Urban,HR Executive,73212,1 +4205,Male,24,Bachelors,16,93,43,77,67,9.0,1,92,Urban,Software Engineer,38913,1 +4206,Male,35,PhD,4,82,65,0,42,1.0,5,31,Urban,Manager,147126,0 +4207,Male,27,Bachelors,18,54,77,11,69,7.0,7,87,Semi-Urban,ML Engineer,63241,0 +4208,Male,44,Bachelors,5,23,67,97,24,7.0,4,8,Urban,ML Engineer,68740,0 +4209,Male,35,High School,5,37,25,15,9,8.0,1,22,Urban,ML Engineer,147387,0 +4210,Male,23,High School,6,3,92,61,15,0.0,7,52,Rural,Software Engineer,79642,0 +4211,Male,43,High School,19,73,25,95,19,9.0,6,52,Semi-Urban,ML Engineer,120159,1 +4212,Male,27,Diploma,3,69,56,37,80,4.0,6,66,Urban,Software Engineer,53740,0 +4213,Male,22,Diploma,18,91,63,92,51,7.0,2,54,Rural,Data Analyst,104011,1 +4214,Male,53,High School,5,15,67,80,55,4.0,5,87,Urban,Manager,88886,1 +4215,Female,38,Bachelors,11,52,92,56,91,9.0,1,25,Semi-Urban,ML Engineer,32886,0 +4216,Female,55,Bachelors,11,45,49,70,87,4.0,3,17,Urban,Manager,139407,0 +4217,Male,59,Bachelors,3,68,97,93,96,8.0,0,49,Rural,ML Engineer,94342,1 +4218,Male,35,Masters,16,94,92,73,76,5.0,1,4,Semi-Urban,Manager,44493,1 +4219,Female,21,Diploma,3,28,19,29,17,1.0,6,6,Semi-Urban,ML Engineer,78653,0 +4220,Male,46,High School,9,35,87,49,26,6.0,3,24,Rural,ML Engineer,141586,0 +4221,Male,53,Bachelors,18,57,24,39,19,1.0,2,47,Urban,Software Engineer,64322,0 +4222,Female,25,Bachelors,19,6,48,90,21,9.0,0,16,Semi-Urban,Manager,71830,0 +4223,Female,45,Bachelors,13,42,19,34,50,0.0,3,31,Urban,Manager,124842,0 +4224,Female,44,Bachelors,3,85,50,66,0,1.0,7,0,Rural,ML Engineer,65412,0 +4225,Male,52,Bachelors,3,32,59,66,14,5.0,6,55,Rural,HR Executive,96378,0 +4226,Female,29,Bachelors,13,3,92,74,99,1.0,2,32,Rural,ML Engineer,30643,0 +4227,Male,45,Diploma,18,11,45,13,46,8.0,7,82,Rural,Manager,106736,0 +4228,Female,57,Bachelors,10,4,3,34,44,0.0,6,65,Urban,ML Engineer,93130,0 +4229,Male,46,PhD,16,56,40,42,33,2.0,0,37,Urban,HR Executive,20574,0 +4230,Male,21,Bachelors,15,88,59,58,49,0.0,1,80,Rural,Manager,136454,1 +4231,Female,34,Masters,4,21,18,23,44,1.0,7,97,Semi-Urban,HR Executive,124993,0 +4232,Male,50,Diploma,18,43,1,34,64,2.0,2,17,Urban,Software Engineer,45928,0 +4233,Male,48,Bachelors,18,6,66,52,55,5.0,0,57,Urban,Data Analyst,133964,0 +4234,Female,59,Diploma,13,15,40,56,71,4.0,5,74,Semi-Urban,Data Analyst,43350,0 +4235,Male,47,High School,3,87,89,51,19,5.0,2,36,Semi-Urban,ML Engineer,49524,1 +4236,Male,29,Bachelors,1,23,19,13,78,2.0,1,92,Urban,ML Engineer,135508,0 +4237,Male,52,Bachelors,1,14,19,51,53,1.0,4,15,Semi-Urban,Software Engineer,93820,0 +4238,Female,54,High School,7,84,31,10,5,6.0,3,96,Urban,HR Executive,30130,0 +4239,Female,24,High School,12,0,97,18,31,4.0,1,63,Rural,Manager,52777,0 +4240,Male,38,Diploma,17,11,37,31,94,9.0,6,90,Semi-Urban,ML Engineer,71119,0 +4241,Female,36,Diploma,8,38,19,0,18,0.0,0,71,Urban,HR Executive,59079,0 +4242,Male,26,PhD,17,46,63,33,37,5.0,4,99,Rural,Software Engineer,144021,1 +4243,Female,50,Bachelors,18,59,79,19,93,1.0,1,57,Semi-Urban,HR Executive,132015,0 +4244,Male,31,Diploma,2,46,50,62,66,3.0,7,33,Urban,Data Analyst,52273,0 +4245,Male,59,Bachelors,0,72,46,36,54,6.0,7,90,Urban,HR Executive,126206,1 +4246,Female,23,Bachelors,12,62,54,26,91,2.0,2,0,Urban,Software Engineer,105943,0 +4247,Male,57,Masters,19,54,51,59,87,3.0,0,24,Urban,ML Engineer,107632,0 +4248,Male,22,Diploma,0,3,35,15,32,5.0,0,89,Semi-Urban,Manager,62799,0 +4249,Male,27,Masters,11,97,48,73,61,7.0,6,9,Urban,Data Analyst,125528,0 +4250,Other,28,High School,8,91,83,60,10,1.0,1,6,Urban,HR Executive,111166,0 +4251,Male,51,High School,7,87,24,70,88,1.0,3,73,Semi-Urban,Software Engineer,116299,1 +4252,Male,21,Masters,6,76,26,43,74,2.0,1,20,Urban,Software Engineer,98185,0 +4253,Male,31,Masters,10,33,42,91,64,1.0,4,59,Semi-Urban,Data Analyst,126816,0 +4254,Male,58,Bachelors,5,24,60,13,9,1.0,6,22,Semi-Urban,HR Executive,70226,0 +4255,Male,25,High School,4,29,92,30,53,5.0,1,28,Urban,ML Engineer,116039,0 +4256,Female,51,Masters,10,59,42,94,66,4.0,1,18,Urban,Manager,142090,0 +4257,Other,39,PhD,6,60,7,47,79,6.0,5,87,Urban,Data Analyst,62854,0 +4258,Male,54,High School,5,83,18,92,81,6.0,6,16,Semi-Urban,Software Engineer,80090,0 +4259,Male,31,Bachelors,15,86,0,35,14,9.0,3,41,Urban,Manager,120797,0 +4260,Male,31,Diploma,17,3,34,81,75,5.0,4,15,Urban,Software Engineer,80173,0 +4261,Male,57,Bachelors,18,14,60,21,84,9.0,5,87,Semi-Urban,HR Executive,95172,0 +4262,Female,28,Bachelors,1,72,73,51,54,0.0,1,2,Urban,ML Engineer,21444,0 +4263,Male,46,Masters,13,76,59,94,28,9.0,3,26,Semi-Urban,Software Engineer,24202,1 +4264,Male,26,High School,4,73,13,3,36,5.0,1,2,Urban,HR Executive,31663,0 +4265,Female,52,Masters,3,88,16,82,33,1.0,4,21,Urban,Data Analyst,102338,0 +4266,Male,49,Masters,12,54,50,91,47,3.0,4,59,Urban,HR Executive,35440,1 +4267,Female,39,Diploma,10,35,21,43,72,2.0,0,33,Urban,Data Analyst,115504,0 +4268,Male,36,Bachelors,1,42,5,88,21,1.0,2,88,Rural,Data Analyst,76636,0 +4269,Female,44,High School,5,69,50,75,60,5.0,7,11,Semi-Urban,ML Engineer,70631,0 +4270,Female,49,Masters,16,63,73,8,28,2.0,7,11,Rural,Data Analyst,132826,0 +4271,Female,39,Bachelors,6,8,50,77,50,5.0,6,32,Rural,ML Engineer,142269,0 +4272,Other,24,Bachelors,19,62,62,4,98,9.0,5,64,Urban,Software Engineer,61994,0 +4273,Male,45,Bachelors,2,74,60,65,67,9.0,2,34,Rural,ML Engineer,107732,0 +4274,Male,51,Bachelors,10,77,24,79,79,8.0,7,74,Urban,Manager,107622,1 +4275,Female,21,Masters,0,28,94,98,86,0.0,0,45,Semi-Urban,Data Analyst,62371,1 +4276,Male,37,Bachelors,9,23,70,97,48,3.0,6,73,Urban,HR Executive,138929,1 +4277,Male,22,Masters,0,74,0,98,12,1.0,6,50,Semi-Urban,HR Executive,38833,0 +4278,Male,52,Bachelors,1,4,16,96,56,0.0,7,78,Semi-Urban,Software Engineer,23720,0 +4279,Male,59,High School,9,66,25,86,84,9.0,3,38,Urban,Data Analyst,53902,0 +4280,Male,28,Diploma,4,89,50,79,94,6.0,0,18,Urban,Software Engineer,102105,1 +4281,Male,39,Bachelors,9,26,27,72,77,1.0,1,92,Urban,ML Engineer,43231,0 +4282,Female,55,Bachelors,16,6,3,41,67,7.0,1,90,Urban,Software Engineer,91447,0 +4283,Male,49,Bachelors,18,25,81,89,59,0.0,2,88,Urban,Manager,41109,1 +4284,Male,23,Bachelors,19,61,7,55,54,8.0,7,27,Urban,HR Executive,81453,0 +4285,Male,22,Bachelors,18,49,8,88,25,8.0,3,58,Urban,ML Engineer,51788,0 +4286,Male,52,Bachelors,19,6,91,58,40,5.0,1,71,Urban,ML Engineer,112676,0 +4287,Female,35,Bachelors,7,46,30,4,41,5.0,2,83,Urban,Data Analyst,133959,0 +4288,Male,41,High School,4,22,38,61,23,0.0,6,90,Urban,HR Executive,133873,0 +4289,Male,33,Masters,14,12,22,83,14,0.0,7,5,Urban,ML Engineer,40515,0 +4290,Female,42,Bachelors,9,16,4,83,18,4.0,5,9,Semi-Urban,Manager,133962,0 +4291,Male,51,Bachelors,1,68,10,38,15,9.0,1,4,Rural,Software Engineer,111024,0 +4292,Male,33,Diploma,14,7,81,38,61,4.0,2,63,Urban,Data Analyst,35713,0 +4293,Male,42,Bachelors,18,33,40,78,5,3.0,3,10,Urban,Manager,34036,0 +4294,Female,28,Bachelors,19,33,66,7,16,8.0,2,96,Rural,Manager,138719,0 +4295,Male,51,Bachelors,17,70,81,4,38,4.0,5,80,Rural,HR Executive,40428,1 +4296,Male,47,Masters,10,5,0,45,47,0.0,1,10,Semi-Urban,Software Engineer,59644,0 +4297,Male,45,PhD,16,89,65,68,16,2.0,1,52,Urban,HR Executive,74488,1 +4298,Male,57,Masters,2,16,72,30,56,8.0,7,25,Urban,Data Analyst,115639,0 +4299,Male,38,Bachelors,5,26,76,41,7,6.0,2,89,Urban,HR Executive,91518,0 +4300,Male,52,Diploma,5,1,55,89,88,6.0,5,69,Semi-Urban,Data Analyst,143579,0 +4301,Male,57,Bachelors,7,32,67,54,17,4.0,3,7,Urban,Data Analyst,26138,0 +4302,Female,39,Bachelors,7,75,41,53,75,6.0,6,81,Urban,ML Engineer,69412,1 +4303,Female,26,Masters,15,76,35,52,7,0.0,5,61,Semi-Urban,Data Analyst,113760,0 +4304,Male,25,Bachelors,12,87,3,19,93,5.0,5,74,Semi-Urban,ML Engineer,111344,0 +4305,Female,46,Bachelors,16,15,67,60,55,6.0,0,27,Semi-Urban,ML Engineer,148278,0 +4306,Male,39,Diploma,14,39,59,10,53,9.0,1,39,Rural,HR Executive,149530,0 +4307,Male,27,Bachelors,15,99,5,92,83,6.0,7,15,Urban,ML Engineer,67431,0 +4308,Female,49,Bachelors,10,0,50,69,47,9.0,3,79,Semi-Urban,Data Analyst,28216,0 +4309,Female,26,Masters,11,60,45,83,30,9.0,6,51,Semi-Urban,Manager,49500,0 +4310,Female,25,Bachelors,12,22,67,82,85,9.0,1,70,Urban,ML Engineer,100622,1 +4311,Male,31,Masters,8,30,76,24,60,0.0,3,17,Urban,HR Executive,73954,0 +4312,Female,24,Masters,12,40,69,58,64,7.0,5,21,Urban,Software Engineer,109755,0 +4313,Male,53,Bachelors,8,91,94,26,31,4.0,4,89,Urban,ML Engineer,128998,1 +4314,Female,45,Bachelors,9,58,83,64,88,2.0,7,75,Urban,ML Engineer,96761,1 +4315,Other,49,High School,1,90,26,37,19,6.0,2,74,Semi-Urban,ML Engineer,56831,0 +4316,Male,35,High School,0,83,13,26,52,3.0,0,75,Urban,Manager,56965,0 +4317,Female,21,Bachelors,8,32,3,79,19,6.0,0,29,Semi-Urban,ML Engineer,48202,0 +4318,Male,41,Bachelors,13,95,29,38,93,8.0,1,40,Urban,Manager,70738,0 +4319,Male,35,Diploma,5,23,1,5,54,0.0,2,31,Urban,Manager,55616,0 +4320,Male,30,Bachelors,5,41,49,17,33,4.0,3,32,Urban,Software Engineer,69948,0 +4321,Male,37,Masters,3,51,38,52,37,3.0,5,92,Urban,Software Engineer,113013,0 +4322,Female,45,Bachelors,10,81,53,94,55,0.0,7,99,Semi-Urban,Manager,149982,1 +4323,Female,21,High School,7,42,14,57,39,4.0,3,29,Urban,ML Engineer,32552,0 +4324,Male,50,Bachelors,11,5,10,13,65,6.0,3,60,Rural,HR Executive,76671,0 +4325,Female,39,Diploma,18,52,65,99,39,1.0,4,53,Urban,Manager,115857,1 +4326,Other,21,High School,19,79,94,42,45,8.0,7,5,Urban,Software Engineer,73704,0 +4327,Male,26,Bachelors,18,11,62,62,7,7.0,7,40,Urban,HR Executive,112551,0 +4328,Other,52,Diploma,15,67,51,41,52,3.0,7,42,Urban,HR Executive,48466,0 +4329,Male,56,Masters,4,15,81,71,60,5.0,7,51,Urban,Manager,55168,0 +4330,Female,54,Diploma,10,73,40,83,18,0.0,0,45,Semi-Urban,Software Engineer,57043,1 +4331,Male,25,Masters,17,39,91,6,17,1.0,0,44,Urban,ML Engineer,99946,0 +4332,Male,53,Diploma,12,18,68,57,4,3.0,3,78,Semi-Urban,ML Engineer,25401,0 +4333,Male,27,Bachelors,5,15,72,50,24,7.0,1,24,Urban,ML Engineer,26919,0 +4334,Female,34,Masters,4,69,5,78,44,5.0,1,33,Rural,ML Engineer,73272,0 +4335,Male,54,High School,7,0,40,4,36,6.0,3,17,Semi-Urban,ML Engineer,130079,0 +4336,Male,52,Bachelors,3,63,63,51,0,4.0,0,33,Urban,HR Executive,42480,0 +4337,Male,47,Bachelors,12,73,21,18,35,9.0,2,27,Semi-Urban,HR Executive,34969,0 +4338,Female,43,Bachelors,8,95,52,33,76,9.0,2,6,Urban,ML Engineer,114462,0 +4339,Male,32,Masters,17,36,45,83,71,3.0,4,59,Rural,ML Engineer,145957,0 +4340,Male,50,Diploma,4,98,40,23,74,8.0,2,79,Urban,Software Engineer,96164,1 +4341,Male,44,High School,15,24,23,39,94,5.0,6,42,Urban,Manager,117840,0 +4342,Male,27,Bachelors,3,79,64,66,79,0.0,5,58,Semi-Urban,HR Executive,86395,1 +4343,Female,24,High School,3,83,60,67,89,1.0,4,1,Rural,Software Engineer,29573,0 +4344,Female,28,Masters,12,25,37,95,67,1.0,1,18,Urban,ML Engineer,22373,0 +4345,Male,51,Masters,6,3,76,43,78,0.0,0,16,Urban,Software Engineer,108172,0 +4346,Male,47,High School,16,55,39,41,19,5.0,0,97,Semi-Urban,HR Executive,109304,0 +4347,Female,45,Bachelors,4,85,60,30,70,5.0,0,95,Urban,Software Engineer,102994,1 +4348,Male,55,Bachelors,4,2,88,68,26,3.0,2,42,Urban,Data Analyst,94881,0 +4349,Female,54,Diploma,15,0,74,36,84,1.0,2,58,Urban,ML Engineer,81164,0 +4350,Female,25,Bachelors,7,80,15,28,51,7.0,4,54,Semi-Urban,Data Analyst,131969,0 +4351,Female,34,Bachelors,11,64,22,62,50,6.0,2,18,Rural,Software Engineer,90861,0 +4352,Male,24,Bachelors,13,34,93,18,74,9.0,6,44,Urban,Data Analyst,42507,0 +4353,Male,47,Diploma,16,74,35,21,17,8.0,6,43,Urban,Data Analyst,121622,0 +4354,Other,42,Bachelors,12,22,50,22,12,2.0,7,28,Urban,ML Engineer,27570,0 +4355,Male,23,Bachelors,0,47,55,61,85,4.0,0,69,Semi-Urban,ML Engineer,77374,0 +4356,Female,41,High School,14,43,24,4,14,4.0,4,42,Urban,Software Engineer,70658,0 +4357,Male,57,Bachelors,15,1,84,8,30,3.0,6,76,Urban,ML Engineer,30726,0 +4358,Female,27,High School,0,22,39,88,8,3.0,1,17,Urban,Software Engineer,141652,0 +4359,Male,27,High School,3,85,93,58,91,0.0,7,86,Urban,Manager,121445,1 +4360,Male,49,Bachelors,19,74,1,58,60,7.0,0,12,Urban,Manager,41129,0 +4361,Male,41,Bachelors,13,86,69,15,54,1.0,2,35,Rural,ML Engineer,146732,0 +4362,Female,57,Bachelors,3,85,94,20,88,1.0,2,86,Urban,Manager,38952,1 +4363,Female,40,Bachelors,4,49,8,89,90,9.0,4,4,Rural,Software Engineer,49690,0 +4364,Male,26,Bachelors,14,0,1,3,39,7.0,0,71,Urban,Manager,117008,0 +4365,Male,51,Bachelors,18,46,93,56,55,6.0,0,11,Urban,ML Engineer,104566,0 +4366,Female,27,Masters,7,42,10,19,27,1.0,0,83,Urban,Manager,125834,0 +4367,Male,55,Bachelors,3,1,76,55,91,2.0,5,94,Urban,Software Engineer,32543,0 +4368,Male,47,Diploma,17,42,39,71,14,4.0,7,47,Rural,Data Analyst,111362,0 +4369,Male,22,Diploma,16,17,12,83,52,2.0,1,46,Urban,Data Analyst,26535,0 +4370,Male,55,Bachelors,16,58,71,51,75,1.0,4,12,Urban,HR Executive,64010,0 +4371,Male,49,Diploma,2,80,4,9,5,3.0,0,54,Semi-Urban,Data Analyst,93840,0 +4372,Male,43,Bachelors,0,87,10,43,92,6.0,1,26,Urban,Data Analyst,75426,0 +4373,Male,49,Masters,15,70,38,3,82,2.0,1,33,Urban,Software Engineer,124348,0 +4374,Male,54,High School,12,69,15,87,2,8.0,4,16,Urban,HR Executive,107914,0 +4375,Male,38,Bachelors,7,91,47,8,28,0.0,0,50,Rural,Manager,133522,0 +4376,Male,48,Masters,18,58,11,99,94,0.0,5,81,Semi-Urban,Software Engineer,115364,1 +4377,Male,50,Bachelors,5,46,85,54,51,2.0,6,25,Urban,HR Executive,54728,0 +4378,Female,49,PhD,6,93,71,78,7,1.0,0,45,Urban,Software Engineer,52104,1 +4379,Male,42,PhD,17,60,93,40,0,8.0,4,89,Semi-Urban,HR Executive,65647,1 +4380,Male,23,Bachelors,12,24,3,99,30,2.0,3,47,Semi-Urban,Data Analyst,104753,0 +4381,Male,56,Diploma,5,3,80,27,58,9.0,4,92,Urban,ML Engineer,41012,0 +4382,Male,57,Bachelors,18,3,43,92,8,5.0,2,97,Semi-Urban,ML Engineer,87885,1 +4383,Male,45,Bachelors,1,77,34,19,72,2.0,4,89,Semi-Urban,HR Executive,34722,0 +4384,Male,43,PhD,14,61,6,29,35,4.0,4,21,Urban,ML Engineer,113368,0 +4385,Female,21,High School,7,29,4,63,39,0.0,5,8,Semi-Urban,Data Analyst,28143,0 +4386,Male,57,Diploma,12,62,95,2,67,2.0,2,53,Semi-Urban,ML Engineer,62748,0 +4387,Other,41,Bachelors,15,21,58,75,61,4.0,1,42,Urban,Software Engineer,129202,0 +4388,Male,50,Bachelors,1,20,3,22,77,5.0,1,70,Urban,HR Executive,80294,0 +4389,Male,52,Bachelors,5,62,22,19,17,8.0,6,58,Urban,Software Engineer,126248,0 +4390,Male,44,Bachelors,3,55,30,48,15,7.0,3,49,Rural,ML Engineer,108676,0 +4391,Male,57,Bachelors,3,57,19,53,0,8.0,1,64,Semi-Urban,ML Engineer,52128,0 +4392,Male,47,Diploma,19,32,21,56,9,8.0,4,17,Semi-Urban,HR Executive,94466,0 +4393,Female,58,Bachelors,15,52,42,14,82,1.0,7,84,Urban,HR Executive,83434,0 +4394,Male,55,Bachelors,13,71,79,71,89,2.0,5,32,Urban,ML Engineer,62120,1 +4395,Female,36,Masters,9,5,39,67,74,8.0,0,68,Semi-Urban,Data Analyst,33448,0 +4396,Female,24,Diploma,18,62,61,27,77,2.0,6,89,Urban,Manager,147137,0 +4397,Male,50,Bachelors,3,44,39,95,29,2.0,0,90,Semi-Urban,Data Analyst,33545,1 +4398,Male,38,Masters,2,73,96,34,15,5.0,1,63,Rural,Manager,110521,1 +4399,Male,26,Diploma,8,5,92,81,84,4.0,2,1,Urban,ML Engineer,33062,0 +4400,Male,35,Bachelors,11,30,57,44,25,1.0,5,69,Urban,ML Engineer,87414,0 +4401,Male,27,Masters,17,48,81,42,5,4.0,3,92,Urban,ML Engineer,73122,1 +4402,Male,59,High School,6,99,27,59,42,9.0,1,12,Urban,Manager,56214,0 +4403,Male,57,Diploma,15,48,23,67,22,3.0,2,95,Rural,Software Engineer,24595,0 +4404,Male,46,Bachelors,5,10,48,43,35,9.0,0,91,Rural,Data Analyst,139028,0 +4405,Other,59,Bachelors,13,42,38,0,90,5.0,6,81,Urban,Manager,83097,0 +4406,Female,21,Bachelors,19,26,47,28,39,0.0,2,38,Urban,Software Engineer,85214,0 +4407,Female,46,Diploma,6,83,77,23,72,2.0,3,7,Urban,Software Engineer,138503,0 +4408,Male,50,Masters,0,70,61,84,64,5.0,5,53,Semi-Urban,Software Engineer,82524,1 +4409,Male,43,Diploma,10,22,30,80,43,8.0,4,69,Urban,ML Engineer,91075,0 +4410,Male,54,High School,18,57,54,84,66,5.0,1,69,Urban,HR Executive,72593,1 +4411,Male,23,Bachelors,10,43,22,18,91,6.0,2,29,Semi-Urban,HR Executive,118441,0 +4412,Male,39,PhD,7,90,14,34,24,8.0,6,6,Urban,Software Engineer,91092,0 +4413,Female,51,Bachelors,17,40,24,14,30,4.0,0,58,Semi-Urban,ML Engineer,81270,0 +4414,Female,59,Bachelors,8,37,7,9,92,3.0,6,50,Urban,Data Analyst,91860,0 +4415,Male,33,Masters,4,50,35,93,77,1.0,6,48,Urban,Manager,53600,0 +4416,Male,49,Bachelors,14,38,1,68,96,6.0,1,88,Urban,Software Engineer,59580,0 +4417,Male,30,Diploma,2,56,4,40,3,9.0,7,28,Semi-Urban,Software Engineer,81028,0 +4418,Male,37,High School,8,82,9,67,54,0.0,6,54,Urban,HR Executive,129258,0 +4419,Male,51,Masters,5,82,29,2,73,3.0,6,98,Urban,Manager,60439,0 +4420,Male,48,Masters,13,67,62,45,12,6.0,2,84,Urban,Manager,88085,1 +4421,Male,28,High School,10,0,38,20,91,4.0,7,79,Urban,Software Engineer,47151,0 +4422,Other,50,Masters,14,1,34,34,80,4.0,6,79,Urban,Software Engineer,127579,0 +4423,Male,59,Masters,3,8,96,41,91,8.0,6,56,Urban,Manager,105361,0 +4424,Female,49,Bachelors,6,47,0,72,5,7.0,2,39,Urban,Manager,29361,0 +4425,Male,33,Bachelors,14,40,93,11,25,0.0,6,86,Rural,ML Engineer,142395,0 +4426,Male,47,Masters,5,74,56,23,23,6.0,1,70,Urban,Data Analyst,90580,0 +4427,Male,23,Diploma,19,30,90,70,98,9.0,6,88,Semi-Urban,ML Engineer,122070,1 +4428,Male,46,Diploma,12,36,7,10,10,3.0,2,83,Semi-Urban,HR Executive,85462,0 +4429,Male,48,Bachelors,12,92,31,4,60,1.0,2,2,Semi-Urban,Software Engineer,109491,0 +4430,Female,30,Bachelors,2,62,38,8,64,5.0,5,9,Urban,HR Executive,40616,0 +4431,Female,39,High School,15,87,94,56,9,6.0,4,75,Semi-Urban,Manager,22893,1 +4432,Male,36,Bachelors,4,79,10,19,88,0.0,2,48,Urban,Software Engineer,40094,0 +4433,Male,49,Diploma,17,95,55,87,70,6.0,5,93,Urban,Manager,136809,1 +4434,Female,53,Masters,5,45,49,49,15,6.0,5,19,Semi-Urban,Software Engineer,115738,0 +4435,Male,46,Masters,16,13,23,47,56,3.0,4,3,Urban,Manager,104880,0 +4436,Male,41,High School,15,67,77,7,42,7.0,4,64,Urban,ML Engineer,140877,0 +4437,Male,58,Masters,5,42,73,80,69,9.0,5,51,Urban,Software Engineer,105742,1 +4438,Female,45,High School,17,85,65,24,62,2.0,2,20,Urban,ML Engineer,92216,0 +4439,Other,36,Diploma,0,24,8,39,22,8.0,2,8,Urban,Software Engineer,131027,0 +4440,Male,59,Diploma,10,67,63,78,95,4.0,6,46,Semi-Urban,Software Engineer,80270,1 +4441,Female,22,Masters,7,41,25,99,18,2.0,1,29,Urban,Software Engineer,107141,0 +4442,Female,42,Diploma,14,12,21,88,14,1.0,2,64,Semi-Urban,Software Engineer,56645,0 +4443,Male,22,Masters,18,37,26,57,2,7.0,2,85,Urban,Manager,83015,0 +4444,Male,31,Diploma,3,12,37,73,43,3.0,6,94,Urban,ML Engineer,68891,0 +4445,Male,37,High School,13,84,6,2,41,8.0,2,74,Urban,Software Engineer,93119,0 +4446,Other,48,Bachelors,13,18,74,24,99,6.0,2,3,Semi-Urban,Data Analyst,103788,0 +4447,Male,24,Bachelors,17,94,2,11,31,1.0,1,5,Urban,HR Executive,122718,0 +4448,Female,47,Masters,0,47,92,28,97,0.0,6,6,Urban,HR Executive,137486,0 +4449,Male,22,Masters,18,15,31,11,0,1.0,2,53,Urban,Software Engineer,103281,0 +4450,Female,56,Bachelors,16,64,4,10,69,8.0,6,5,Rural,ML Engineer,28578,0 +4451,Male,58,Bachelors,0,78,40,96,62,6.0,2,76,Rural,ML Engineer,51719,1 +4452,Male,56,Bachelors,0,91,15,88,46,8.0,2,3,Semi-Urban,Software Engineer,26103,0 +4453,Female,25,High School,13,82,23,40,9,5.0,4,78,Urban,Data Analyst,106637,0 +4454,Female,48,High School,9,22,61,16,67,1.0,2,90,Urban,Software Engineer,114581,0 +4455,Female,29,Bachelors,11,84,81,96,7,3.0,4,60,Urban,Data Analyst,23384,1 +4456,Male,34,Bachelors,7,98,10,46,98,9.0,6,14,Urban,Software Engineer,134109,0 +4457,Female,41,Masters,6,63,49,81,17,5.0,1,47,Urban,ML Engineer,136626,0 +4458,Male,32,Bachelors,0,45,34,35,53,1.0,0,63,Urban,HR Executive,63678,0 +4459,Male,35,Diploma,8,7,66,40,66,2.0,7,23,Semi-Urban,Data Analyst,50710,0 +4460,Male,48,Masters,1,48,68,26,72,9.0,6,71,Urban,Manager,148171,0 +4461,Male,31,Bachelors,8,16,14,8,10,1.0,7,78,Urban,Data Analyst,46876,0 +4462,Male,40,High School,7,91,81,4,37,6.0,5,1,Rural,Software Engineer,143084,0 +4463,Other,47,Masters,6,43,26,41,94,4.0,7,18,Urban,Software Engineer,35909,0 +4464,Male,52,Bachelors,2,23,80,52,42,5.0,4,54,Urban,Manager,122226,0 +4465,Female,33,Masters,11,91,60,51,62,6.0,2,87,Semi-Urban,Data Analyst,135449,1 +4466,Male,24,Bachelors,11,68,26,14,34,9.0,0,83,Urban,Manager,35308,0 +4467,Male,34,Bachelors,5,61,40,2,12,9.0,4,78,Urban,Manager,111681,0 +4468,Male,26,Masters,17,62,33,23,95,9.0,2,47,Rural,Software Engineer,45298,0 +4469,Female,23,Bachelors,6,1,54,37,15,1.0,4,85,Semi-Urban,HR Executive,110919,0 +4470,Female,50,Masters,14,95,82,3,39,1.0,5,63,Urban,ML Engineer,123583,1 +4471,Female,32,Diploma,11,27,97,78,48,4.0,7,92,Rural,ML Engineer,52458,1 +4472,Other,26,Diploma,5,80,32,29,22,8.0,6,67,Urban,ML Engineer,139426,0 +4473,Male,45,High School,14,34,10,99,80,4.0,3,59,Rural,Software Engineer,81576,0 +4474,Male,47,Masters,14,42,29,36,95,0.0,6,25,Urban,HR Executive,66459,0 +4475,Female,55,Diploma,12,72,22,38,17,9.0,4,24,Semi-Urban,Manager,129782,0 +4476,Male,55,High School,12,35,1,74,99,0.0,5,45,Rural,Software Engineer,47534,0 +4477,Male,27,Diploma,12,91,20,24,31,0.0,3,81,Rural,Software Engineer,27071,0 +4478,Male,40,Bachelors,5,10,90,95,8,2.0,4,42,Rural,HR Executive,49534,1 +4479,Male,30,High School,13,30,28,54,58,5.0,1,90,Rural,HR Executive,99137,0 +4480,Male,31,Masters,17,48,61,78,24,6.0,3,79,Rural,Software Engineer,53668,1 +4481,Male,27,Masters,5,3,19,59,91,9.0,6,21,Rural,Manager,111098,0 +4482,Male,36,PhD,3,29,20,16,16,0.0,4,0,Rural,ML Engineer,72222,0 +4483,Male,23,Bachelors,10,95,59,33,12,5.0,6,44,Urban,HR Executive,124667,0 +4484,Male,45,High School,3,83,7,62,83,9.0,1,23,Semi-Urban,Data Analyst,40891,0 +4485,Male,43,Diploma,13,70,61,69,15,3.0,7,75,Urban,ML Engineer,135383,1 +4486,Female,48,Diploma,9,40,85,6,49,1.0,5,64,Semi-Urban,Manager,25048,0 +4487,Male,41,Masters,10,16,6,89,32,9.0,7,35,Semi-Urban,ML Engineer,32264,0 +4488,Male,24,Bachelors,18,89,29,65,52,6.0,2,89,Rural,Software Engineer,84876,1 +4489,Female,28,Diploma,3,71,56,56,86,4.0,7,47,Semi-Urban,Manager,62191,0 +4490,Male,50,Bachelors,7,45,46,36,14,3.0,2,35,Urban,ML Engineer,65607,0 +4491,Male,56,PhD,12,85,59,11,25,1.0,4,68,Rural,Software Engineer,52200,0 +4492,Female,51,Bachelors,3,29,73,89,33,5.0,4,50,Urban,Data Analyst,51499,1 +4493,Male,52,Masters,7,59,39,50,36,6.0,5,7,Urban,Manager,88070,0 +4494,Female,57,Bachelors,2,66,15,92,78,2.0,7,34,Urban,Data Analyst,40824,0 +4495,Female,56,Bachelors,18,78,39,1,58,4.0,3,95,Rural,HR Executive,66689,0 +4496,Female,56,Diploma,14,65,81,30,1,1.0,5,37,Rural,HR Executive,127807,0 +4497,Male,58,Masters,8,42,40,78,4,7.0,1,87,Semi-Urban,HR Executive,142779,1 +4498,Male,54,High School,19,87,13,66,62,3.0,5,99,Rural,HR Executive,120820,1 +4499,Male,50,Bachelors,2,62,85,9,55,4.0,1,10,Rural,Manager,70275,0 +4500,Male,47,High School,3,79,14,37,35,8.0,2,4,Semi-Urban,ML Engineer,139671,0 +4501,Male,28,Diploma,2,50,75,0,67,9.0,2,90,Semi-Urban,ML Engineer,64545,0 +4502,Male,54,Bachelors,1,30,65,29,75,2.0,2,25,Rural,Software Engineer,142789,0 +4503,Male,35,High School,14,46,19,31,41,8.0,3,86,Rural,Software Engineer,102618,0 +4504,Male,49,Diploma,15,8,18,74,79,5.0,6,82,Semi-Urban,ML Engineer,97182,0 +4505,Male,27,Diploma,2,12,81,31,17,8.0,7,60,Semi-Urban,ML Engineer,139682,0 +4506,Male,24,High School,9,66,46,15,24,4.0,0,10,Urban,HR Executive,102317,0 +4507,Female,55,Bachelors,5,15,53,65,23,4.0,6,40,Rural,Data Analyst,29943,0 +4508,Male,28,Masters,16,70,36,81,22,8.0,6,48,Urban,Manager,58672,1 +4509,Male,43,Diploma,3,95,55,17,61,0.0,0,14,Urban,Software Engineer,76178,0 +4510,Female,51,Masters,10,80,60,14,6,1.0,3,63,Rural,ML Engineer,148294,0 +4511,Male,46,Bachelors,18,15,95,36,74,0.0,4,95,Semi-Urban,Software Engineer,115711,1 +4512,Male,36,Bachelors,14,95,35,93,69,2.0,2,3,Urban,HR Executive,126080,0 +4513,Male,41,Bachelors,10,11,87,33,71,9.0,3,0,Urban,Manager,135217,0 +4514,Female,33,High School,16,25,75,10,61,5.0,4,4,Urban,HR Executive,138757,0 +4515,Male,25,High School,2,11,86,27,78,4.0,2,42,Urban,Software Engineer,49518,0 +4516,Male,31,High School,13,63,8,39,7,6.0,6,39,Urban,Manager,76757,0 +4517,Male,21,Masters,19,19,2,9,69,9.0,4,90,Semi-Urban,Manager,79506,0 +4518,Female,30,Bachelors,18,44,10,38,66,8.0,7,74,Semi-Urban,Software Engineer,106137,0 +4519,Male,38,Masters,3,36,1,11,90,4.0,5,13,Urban,ML Engineer,58667,0 +4520,Male,34,High School,15,23,50,19,1,0.0,0,39,Urban,HR Executive,56607,0 +4521,Female,26,Bachelors,9,40,76,76,78,5.0,2,43,Urban,Software Engineer,130287,0 +4522,Male,43,Masters,15,56,79,98,12,5.0,0,10,Semi-Urban,Software Engineer,37976,1 +4523,Female,47,Bachelors,11,46,55,73,1,3.0,3,71,Urban,ML Engineer,109403,1 +4524,Male,22,Diploma,6,83,31,81,95,4.0,6,81,Urban,Manager,94000,1 +4525,Female,37,Bachelors,1,30,3,43,62,2.0,3,27,Semi-Urban,ML Engineer,28700,0 +4526,Male,45,Bachelors,14,30,19,14,76,0.0,5,86,Rural,Data Analyst,145131,0 +4527,Female,49,Diploma,7,58,5,25,84,6.0,2,83,Semi-Urban,Software Engineer,123025,0 +4528,Female,22,Masters,14,43,92,46,91,3.0,7,62,Urban,HR Executive,100724,1 +4529,Male,31,Masters,10,70,28,40,85,7.0,0,41,Urban,Manager,44827,0 +4530,Male,33,Diploma,0,60,20,77,49,9.0,2,99,Urban,Manager,31069,1 +4531,Male,35,Masters,4,15,91,9,11,0.0,5,18,Rural,Software Engineer,114120,0 +4532,Male,24,High School,18,24,89,54,56,9.0,2,95,Urban,Data Analyst,131133,1 +4533,Male,29,Diploma,19,53,77,96,71,5.0,3,79,Urban,HR Executive,114293,1 +4534,Male,54,Bachelors,10,33,85,24,28,9.0,2,64,Urban,Data Analyst,126800,0 +4535,Male,54,Bachelors,7,7,47,57,60,5.0,2,86,Urban,ML Engineer,112847,0 +4536,Male,55,High School,15,80,0,44,51,2.0,5,35,Semi-Urban,Data Analyst,140912,0 +4537,Male,51,Diploma,1,75,61,7,76,3.0,7,45,Urban,Manager,25113,0 +4538,Female,53,Bachelors,13,27,74,6,28,7.0,4,89,Urban,Manager,53061,0 +4539,Male,54,Diploma,5,3,72,61,83,3.0,4,47,Urban,ML Engineer,139735,0 +4540,Male,43,Bachelors,6,63,17,23,52,9.0,3,30,Urban,Software Engineer,146906,0 +4541,Male,47,High School,4,51,55,89,32,7.0,7,64,Rural,ML Engineer,45391,1 +4542,Male,58,Diploma,7,52,33,1,9,3.0,4,72,Urban,Software Engineer,77381,0 +4543,Male,21,Masters,16,52,24,55,37,5.0,3,72,Semi-Urban,HR Executive,66166,0 +4544,Male,44,Masters,8,1,16,30,85,6.0,7,29,Rural,Software Engineer,79626,0 +4545,Male,38,Bachelors,11,6,96,28,92,3.0,7,88,Rural,Data Analyst,103585,0 +4546,Female,34,Masters,1,53,69,38,83,7.0,5,77,Urban,ML Engineer,71428,0 +4547,Male,55,Bachelors,5,75,79,14,60,8.0,1,14,Rural,ML Engineer,141832,0 +4548,Female,26,PhD,7,18,19,68,49,3.0,1,10,Semi-Urban,Software Engineer,123966,0 +4549,Female,23,High School,18,74,8,76,21,4.0,6,53,Urban,Data Analyst,45427,0 +4550,Female,52,Bachelors,9,63,34,56,82,3.0,2,66,Urban,Software Engineer,131550,0 +4551,Female,24,Masters,2,74,92,32,59,6.0,7,2,Semi-Urban,ML Engineer,137010,0 +4552,Male,27,Diploma,18,31,71,35,51,4.0,2,71,Semi-Urban,Manager,141694,0 +4553,Male,23,Bachelors,9,16,18,76,71,8.0,7,45,Rural,Data Analyst,105669,0 +4554,Female,23,Masters,14,16,90,3,32,0.0,7,23,Urban,ML Engineer,132305,0 +4555,Male,37,Diploma,8,32,25,40,71,5.0,3,63,Urban,HR Executive,130285,0 +4556,Male,58,Diploma,2,89,70,7,21,6.0,2,41,Urban,HR Executive,78975,0 +4557,Female,21,Diploma,0,33,10,3,52,1.0,7,68,Urban,Data Analyst,81478,0 +4558,Female,22,Bachelors,19,77,67,20,36,5.0,7,29,Urban,Manager,72620,0 +4559,Female,21,Bachelors,10,23,31,2,50,8.0,5,69,Semi-Urban,ML Engineer,35173,0 +4560,Other,31,Diploma,4,89,72,63,30,3.0,0,24,Urban,HR Executive,103027,1 +4561,Female,29,Bachelors,1,66,35,0,33,3.0,1,16,Urban,Software Engineer,106124,0 +4562,Male,25,Diploma,15,15,56,21,99,1.0,1,48,Urban,Data Analyst,116615,0 +4563,Female,53,Diploma,2,89,63,84,0,7.0,5,93,Rural,HR Executive,52372,1 +4564,Male,58,High School,3,1,21,78,74,7.0,3,73,Rural,Manager,93258,0 +4565,Male,58,High School,7,49,71,56,67,4.0,3,19,Urban,Manager,22349,0 +4566,Female,39,Bachelors,11,39,72,37,89,6.0,6,58,Urban,Manager,98237,0 +4567,Male,50,Diploma,7,71,52,22,17,8.0,0,62,Semi-Urban,ML Engineer,20431,0 +4568,Male,53,Bachelors,17,99,13,81,62,5.0,5,16,Rural,Manager,97150,0 +4569,Male,58,Bachelors,17,46,27,52,87,5.0,2,70,Semi-Urban,Data Analyst,58076,0 +4570,Female,41,Diploma,15,96,6,88,61,5.0,3,58,Rural,Data Analyst,57420,1 +4571,Male,24,Bachelors,18,38,90,93,37,1.0,0,71,Urban,ML Engineer,88006,1 +4572,Female,42,Bachelors,17,93,6,39,78,2.0,1,0,Semi-Urban,ML Engineer,107829,0 +4573,Male,42,Bachelors,8,25,38,97,27,0.0,4,94,Urban,Software Engineer,38145,1 +4574,Female,43,Bachelors,2,19,56,7,43,1.0,5,77,Semi-Urban,Data Analyst,21452,0 +4575,Female,57,PhD,5,38,3,99,2,3.0,2,70,Rural,Manager,85791,0 +4576,Male,29,Masters,4,88,18,27,16,7.0,6,36,Urban,ML Engineer,149598,0 +4577,Male,42,Masters,4,89,96,92,50,1.0,1,21,Urban,Data Analyst,78259,1 +4578,Male,56,Bachelors,9,41,29,10,54,5.0,1,51,Urban,ML Engineer,55503,0 +4579,Other,21,Bachelors,10,8,86,41,63,8.0,1,20,Urban,Software Engineer,88738,0 +4580,Female,32,Diploma,13,59,47,39,40,5.0,3,73,Urban,Data Analyst,35282,0 +4581,Female,52,Masters,19,50,15,81,12,2.0,5,64,Semi-Urban,ML Engineer,22099,0 +4582,Male,23,Masters,18,78,80,56,60,8.0,5,86,Rural,Software Engineer,120299,1 +4583,Female,45,Masters,15,30,28,70,83,0.0,0,56,Semi-Urban,Manager,80975,0 +4584,Female,39,High School,12,45,70,28,25,3.0,3,11,Urban,HR Executive,115321,0 +4585,Female,25,Masters,15,6,77,41,39,1.0,5,55,Urban,ML Engineer,74049,0 +4586,Other,49,Bachelors,4,4,17,97,84,3.0,0,15,Urban,ML Engineer,54344,0 +4587,Male,37,High School,0,56,11,85,79,9.0,4,92,Semi-Urban,Software Engineer,99321,1 +4588,Male,42,High School,18,56,1,82,71,1.0,1,46,Semi-Urban,HR Executive,103333,0 +4589,Female,28,Bachelors,0,25,24,37,75,9.0,6,88,Rural,Manager,131598,0 +4590,Female,50,Bachelors,14,49,92,60,75,2.0,0,17,Semi-Urban,ML Engineer,71776,0 +4591,Male,41,Diploma,18,24,15,13,87,5.0,2,95,Semi-Urban,HR Executive,69339,0 +4592,Male,27,Bachelors,9,35,59,14,87,0.0,3,84,Urban,HR Executive,87987,0 +4593,Male,40,High School,1,43,7,16,80,3.0,2,56,Semi-Urban,Data Analyst,140832,0 +4594,Male,33,Masters,3,24,16,84,57,6.0,6,58,Rural,ML Engineer,148756,0 +4595,Male,56,Masters,1,84,11,79,4,9.0,0,12,Urban,Software Engineer,108448,0 +4596,Female,29,Diploma,5,32,28,82,61,1.0,2,74,Urban,ML Engineer,98305,0 +4597,Female,34,Bachelors,18,87,74,94,86,0.0,3,66,Rural,Software Engineer,22382,1 +4598,Male,36,Diploma,5,59,7,91,0,9.0,7,37,Urban,Data Analyst,120235,0 +4599,Male,36,Masters,16,4,77,25,98,6.0,4,21,Urban,Manager,118570,0 +4600,Male,35,Bachelors,6,97,33,49,18,9.0,4,46,Semi-Urban,ML Engineer,37073,0 +4601,Male,23,Masters,0,96,15,5,86,1.0,6,3,Rural,ML Engineer,119667,0 +4602,Female,25,Bachelors,11,17,63,34,33,1.0,2,7,Urban,Manager,85374,0 +4603,Female,25,Diploma,11,78,84,13,96,9.0,5,13,Semi-Urban,Software Engineer,142105,0 +4604,Male,45,Diploma,9,14,37,47,84,6.0,4,4,Rural,Software Engineer,97470,0 +4605,Female,56,Diploma,8,64,12,19,30,7.0,1,57,Semi-Urban,Data Analyst,21913,0 +4606,Female,47,High School,0,55,39,68,1,5.0,7,70,Urban,Software Engineer,58086,0 +4607,Female,47,Bachelors,14,15,47,65,77,1.0,0,20,Rural,Software Engineer,133761,0 +4608,Male,46,Bachelors,13,39,14,8,69,4.0,4,18,Semi-Urban,ML Engineer,29314,0 +4609,Other,34,Masters,16,0,46,28,26,2.0,5,27,Semi-Urban,Manager,56688,0 +4610,Male,21,Bachelors,9,47,40,10,15,3.0,4,72,Urban,ML Engineer,92768,0 +4611,Male,46,High School,13,68,51,65,64,6.0,1,95,Rural,Manager,39837,1 +4612,Male,56,Diploma,4,6,54,40,42,1.0,7,41,Urban,HR Executive,134191,0 +4613,Male,38,Masters,19,70,74,77,88,0.0,3,8,Urban,Data Analyst,21664,0 +4614,Male,43,Bachelors,17,77,69,96,22,9.0,0,11,Semi-Urban,HR Executive,66336,1 +4615,Male,28,High School,12,64,65,49,33,6.0,6,85,Rural,ML Engineer,54196,1 +4616,Male,49,Bachelors,4,74,96,41,63,2.0,5,16,Semi-Urban,Software Engineer,97203,0 +4617,Female,40,Diploma,2,4,54,90,14,4.0,1,58,Semi-Urban,HR Executive,23559,0 +4618,Female,37,Bachelors,7,65,64,89,56,3.0,5,15,Urban,ML Engineer,118859,0 +4619,Male,21,Bachelors,5,32,9,0,52,4.0,1,34,Semi-Urban,HR Executive,38362,0 +4620,Female,35,High School,16,43,1,62,66,1.0,2,53,Rural,HR Executive,36430,0 +4621,Female,27,High School,5,3,85,77,94,2.0,7,36,Urban,Data Analyst,36444,0 +4622,Female,34,Bachelors,19,41,92,40,94,6.0,7,19,Semi-Urban,Data Analyst,74214,0 +4623,Male,22,Diploma,18,99,68,89,15,2.0,7,72,Urban,Manager,66362,1 +4624,Female,28,Masters,14,43,10,91,99,7.0,0,24,Rural,Manager,34901,0 +4625,Female,48,Bachelors,19,8,77,83,11,4.0,2,88,Rural,Manager,23485,1 +4626,Female,30,Diploma,17,93,23,90,16,8.0,3,27,Rural,Manager,130487,0 +4627,Male,29,Bachelors,8,33,60,69,57,3.0,3,47,Urban,HR Executive,47364,0 +4628,Male,27,Bachelors,18,35,31,73,0,1.0,0,80,Semi-Urban,Manager,55080,0 +4629,Female,55,Diploma,0,42,65,87,39,1.0,6,71,Urban,Manager,95294,1 +4630,Male,56,Diploma,4,32,28,28,16,5.0,5,41,Semi-Urban,Manager,55347,0 +4631,Male,28,Bachelors,16,31,77,55,14,9.0,0,9,Semi-Urban,ML Engineer,57196,0 +4632,Male,30,Bachelors,15,34,43,42,46,5.0,3,87,Urban,HR Executive,21619,0 +4633,Female,22,High School,14,58,31,0,89,2.0,5,41,Urban,ML Engineer,47572,0 +4634,Female,43,Bachelors,9,90,18,0,31,7.0,6,99,Urban,HR Executive,135814,0 +4635,Male,40,Masters,16,71,2,96,1,0.0,7,32,Rural,Software Engineer,93874,0 +4636,Other,43,Bachelors,9,13,94,15,34,7.0,1,56,Urban,Software Engineer,135565,0 +4637,Male,42,Masters,1,17,15,67,23,4.0,4,35,Rural,ML Engineer,98356,0 +4638,Female,41,Bachelors,1,55,45,73,56,8.0,5,56,Urban,Software Engineer,68130,0 +4639,Female,46,Bachelors,6,8,8,16,21,8.0,7,89,Urban,ML Engineer,43762,0 +4640,Female,52,Bachelors,6,79,87,16,16,5.0,1,13,Urban,Data Analyst,137467,0 +4641,Female,43,High School,11,30,70,17,58,6.0,2,64,Semi-Urban,Software Engineer,148430,0 +4642,Male,34,Diploma,14,23,87,30,84,3.0,1,92,Semi-Urban,Manager,101446,0 +4643,Female,57,Diploma,6,11,40,44,68,5.0,7,32,Urban,HR Executive,95283,0 +4644,Male,50,Bachelors,8,99,81,26,3,8.0,1,44,Urban,ML Engineer,88181,1 +4645,Female,51,High School,2,84,56,53,86,0.0,6,66,Semi-Urban,HR Executive,33421,1 +4646,Female,29,High School,16,38,90,80,14,3.0,0,76,Semi-Urban,HR Executive,45972,1 +4647,Female,39,High School,19,73,43,24,79,1.0,4,51,Rural,HR Executive,145809,0 +4648,Male,44,Bachelors,12,74,9,15,91,3.0,6,53,Urban,HR Executive,27027,0 +4649,Female,56,Diploma,1,49,68,49,12,6.0,7,99,Urban,Software Engineer,39126,1 +4650,Male,52,Masters,9,80,34,99,5,7.0,1,83,Urban,Data Analyst,58635,1 +4651,Male,21,Bachelors,3,16,41,25,98,1.0,6,78,Urban,HR Executive,40297,0 +4652,Female,31,High School,7,67,33,76,53,9.0,0,72,Rural,Software Engineer,141370,1 +4653,Male,48,Diploma,10,48,23,42,55,7.0,1,71,Urban,HR Executive,94362,0 +4654,Female,50,Bachelors,19,11,92,19,94,6.0,4,18,Rural,ML Engineer,30740,0 +4655,Male,45,Bachelors,2,55,82,3,75,7.0,4,6,Urban,Software Engineer,39788,0 +4656,Male,46,High School,1,39,58,94,80,1.0,6,61,Urban,Software Engineer,128359,1 +4657,Female,46,Bachelors,17,66,85,82,76,6.0,2,48,Rural,HR Executive,30005,1 +4658,Male,28,Bachelors,8,53,40,53,91,3.0,1,29,Urban,Software Engineer,21676,0 +4659,Male,24,PhD,19,29,10,51,49,5.0,5,74,Urban,HR Executive,32491,0 +4660,Female,23,Bachelors,14,15,33,53,42,7.0,4,59,Semi-Urban,Manager,70471,0 +4661,Male,34,Diploma,6,73,61,74,69,9.0,3,35,Urban,Data Analyst,130446,1 +4662,Female,28,Diploma,4,50,9,19,81,3.0,3,29,Urban,HR Executive,30097,0 +4663,Male,23,High School,9,52,11,32,27,1.0,4,84,Rural,ML Engineer,37147,0 +4664,Female,43,High School,1,43,98,85,18,1.0,1,3,Urban,Manager,42205,0 +4665,Female,37,Diploma,6,46,73,75,90,7.0,7,30,Rural,HR Executive,67526,0 +4666,Female,55,Diploma,13,46,15,62,10,6.0,2,25,Rural,ML Engineer,47174,0 +4667,Male,55,Masters,13,71,43,0,75,2.0,7,25,Semi-Urban,HR Executive,110011,0 +4668,Female,38,Bachelors,16,50,99,21,43,6.0,6,1,Rural,Manager,49713,0 +4669,Female,22,Masters,5,83,41,19,65,2.0,5,48,Urban,Manager,99357,0 +4670,Female,33,Masters,14,85,63,68,52,7.0,4,51,Urban,Data Analyst,32563,1 +4671,Male,21,Diploma,6,41,71,93,87,9.0,0,23,Semi-Urban,Manager,31412,0 +4672,Female,27,Bachelors,10,19,69,28,42,1.0,6,74,Urban,HR Executive,120035,0 +4673,Female,29,Diploma,17,0,15,21,35,9.0,2,54,Urban,HR Executive,64018,0 +4674,Male,31,High School,5,56,73,49,47,3.0,6,25,Semi-Urban,Manager,59825,0 +4675,Male,58,Bachelors,17,73,0,85,74,1.0,0,73,Urban,HR Executive,94503,0 +4676,Female,27,High School,10,2,27,81,18,4.0,6,13,Semi-Urban,HR Executive,136900,0 +4677,Male,23,High School,18,38,79,36,66,3.0,7,38,Urban,HR Executive,67970,0 +4678,Other,25,PhD,13,84,63,39,3,8.0,6,82,Urban,Software Engineer,123717,1 +4679,Female,45,High School,8,96,16,17,6,5.0,7,79,Semi-Urban,ML Engineer,94302,0 +4680,Female,53,Diploma,1,26,26,69,15,9.0,3,98,Urban,Data Analyst,143726,0 +4681,Male,32,Bachelors,7,90,41,51,14,4.0,6,59,Rural,HR Executive,55522,1 +4682,Male,30,Diploma,16,32,67,64,69,1.0,7,64,Semi-Urban,Manager,129368,0 +4683,Female,38,High School,19,44,49,13,54,8.0,6,65,Semi-Urban,Data Analyst,122811,0 +4684,Male,56,Diploma,14,22,67,79,16,9.0,5,46,Semi-Urban,Data Analyst,23308,0 +4685,Female,46,Bachelors,4,95,9,93,54,5.0,5,40,Urban,Data Analyst,130333,0 +4686,Male,50,Bachelors,13,39,26,68,66,2.0,3,18,Rural,Software Engineer,98789,0 +4687,Male,39,Bachelors,8,22,59,4,69,0.0,1,22,Urban,ML Engineer,38667,0 +4688,Male,54,Masters,5,28,55,31,52,6.0,7,60,Rural,Manager,146764,0 +4689,Male,48,Bachelors,14,7,30,83,32,3.0,2,23,Rural,Manager,77308,0 +4690,Other,44,Masters,2,9,21,31,52,5.0,0,16,Semi-Urban,HR Executive,120434,0 +4691,Male,36,High School,13,42,35,6,94,4.0,4,16,Rural,ML Engineer,99218,0 +4692,Male,45,Diploma,12,38,45,63,31,8.0,0,44,Rural,Manager,141712,0 +4693,Male,57,Bachelors,5,24,32,16,87,8.0,4,90,Urban,Software Engineer,101066,0 +4694,Male,28,Bachelors,3,73,34,10,32,4.0,4,55,Urban,Software Engineer,47712,0 +4695,Male,49,Diploma,10,62,43,72,2,2.0,0,26,Semi-Urban,HR Executive,95123,0 +4696,Female,59,Bachelors,6,11,13,59,40,3.0,1,91,Urban,HR Executive,72586,0 +4697,Male,40,Bachelors,15,58,64,17,3,1.0,5,73,Urban,Software Engineer,148142,0 +4698,Male,23,Bachelors,3,80,54,57,84,3.0,5,73,Semi-Urban,Software Engineer,83807,1 +4699,Male,22,Bachelors,12,36,16,13,16,0.0,3,96,Urban,ML Engineer,105991,0 +4700,Other,59,Diploma,5,27,80,89,74,1.0,3,34,Rural,ML Engineer,62278,0 +4701,Male,34,Diploma,6,19,5,35,20,1.0,0,87,Semi-Urban,Software Engineer,31392,0 +4702,Male,43,Bachelors,18,62,46,63,7,9.0,3,39,Urban,ML Engineer,132895,0 +4703,Female,40,Bachelors,9,64,53,29,58,5.0,2,78,Urban,Manager,105087,0 +4704,Male,54,Bachelors,15,57,55,38,6,8.0,5,22,Urban,ML Engineer,78528,0 +4705,Male,52,PhD,0,86,12,99,79,1.0,1,36,Urban,Manager,22368,0 +4706,Male,47,Masters,10,6,5,43,52,8.0,5,34,Urban,ML Engineer,67963,0 +4707,Female,37,Bachelors,4,98,80,67,2,8.0,4,66,Rural,Software Engineer,95638,1 +4708,Male,30,Bachelors,13,51,3,31,10,7.0,4,3,Semi-Urban,Data Analyst,85572,0 +4709,Female,54,Bachelors,18,52,15,51,90,4.0,3,15,Semi-Urban,ML Engineer,101381,0 +4710,Female,52,Diploma,14,57,72,53,30,8.0,6,89,Urban,Software Engineer,65464,1 +4711,Male,29,Masters,19,69,48,63,16,8.0,7,13,Semi-Urban,Data Analyst,129149,0 +4712,Male,29,Bachelors,16,12,55,98,21,0.0,1,4,Urban,Data Analyst,65922,0 +4713,Male,33,PhD,15,23,81,93,47,9.0,6,77,Semi-Urban,HR Executive,53381,1 +4714,Female,48,Diploma,15,43,93,96,95,3.0,5,17,Rural,ML Engineer,24199,1 +4715,Male,51,High School,14,25,34,36,89,4.0,2,7,Urban,Manager,135981,0 +4716,Male,28,Diploma,3,43,19,22,50,9.0,4,62,Urban,Software Engineer,70927,0 +4717,Male,44,High School,4,80,16,47,85,0.0,3,18,Urban,Manager,91876,0 +4718,Other,32,Diploma,19,64,74,19,99,1.0,7,6,Urban,HR Executive,122099,0 +4719,Male,54,Diploma,4,41,4,73,78,7.0,4,5,Urban,Data Analyst,56538,0 +4720,Female,27,Bachelors,8,54,12,65,59,4.0,3,68,Semi-Urban,Software Engineer,90300,0 +4721,Male,55,Diploma,14,56,48,59,42,0.0,7,9,Semi-Urban,Data Analyst,132244,0 +4722,Male,50,Diploma,1,27,75,2,20,8.0,3,41,Urban,HR Executive,136335,0 +4723,Male,56,Diploma,19,9,22,62,93,3.0,3,28,Semi-Urban,ML Engineer,55583,0 +4724,Male,41,Bachelors,8,69,84,89,19,6.0,3,0,Semi-Urban,Software Engineer,30717,1 +4725,Male,35,Bachelors,0,11,24,30,24,2.0,7,16,Rural,Data Analyst,72045,0 +4726,Male,26,High School,16,60,87,79,77,8.0,7,80,Urban,Data Analyst,45006,1 +4727,Female,36,Diploma,1,97,84,72,97,6.0,2,62,Semi-Urban,Data Analyst,82324,1 +4728,Female,34,Diploma,18,80,54,67,11,0.0,2,58,Semi-Urban,ML Engineer,68328,1 +4729,Female,32,Diploma,12,2,30,69,62,7.0,3,70,Semi-Urban,HR Executive,135709,0 +4730,Male,53,Masters,4,51,42,60,80,8.0,4,61,Urban,Data Analyst,42093,0 +4731,Male,37,Masters,17,9,68,98,71,2.0,7,9,Urban,HR Executive,114139,0 +4732,Male,53,Masters,15,58,42,66,1,9.0,7,47,Semi-Urban,Software Engineer,115449,0 +4733,Female,58,Diploma,1,68,35,89,64,8.0,5,68,Urban,Software Engineer,140374,1 +4734,Female,48,High School,8,30,65,77,81,4.0,4,83,Urban,HR Executive,118613,1 +4735,Male,41,High School,3,22,94,73,71,8.0,5,1,Urban,ML Engineer,93310,0 +4736,Male,52,Bachelors,0,89,46,26,45,6.0,4,55,Urban,Data Analyst,21965,0 +4737,Male,35,Masters,16,18,38,40,41,4.0,2,78,Urban,Manager,78233,0 +4738,Male,45,Masters,9,10,34,33,76,5.0,0,97,Semi-Urban,Software Engineer,61200,0 +4739,Male,56,Bachelors,16,69,75,10,2,4.0,0,10,Urban,Software Engineer,128572,0 +4740,Female,43,Bachelors,8,13,46,91,51,7.0,6,76,Urban,HR Executive,126512,0 +4741,Female,54,Bachelors,15,70,7,74,61,3.0,5,21,Urban,Manager,29246,0 +4742,Male,32,Bachelors,12,36,85,47,99,4.0,0,55,Urban,HR Executive,124789,0 +4743,Male,27,Bachelors,15,1,7,76,69,2.0,7,98,Semi-Urban,Manager,107959,0 +4744,Other,52,Bachelors,0,82,80,56,6,2.0,0,87,Urban,Manager,125937,1 +4745,Male,44,High School,6,66,16,71,84,5.0,2,26,Urban,HR Executive,113803,0 +4746,Male,43,Bachelors,7,85,27,94,88,5.0,2,19,Urban,Software Engineer,49230,0 +4747,Male,59,Bachelors,0,18,8,26,75,4.0,4,56,Semi-Urban,Data Analyst,62971,0 +4748,Male,54,Diploma,4,58,89,21,22,4.0,6,73,Semi-Urban,Manager,62411,1 +4749,Male,25,Masters,5,47,36,46,64,1.0,3,93,Rural,Data Analyst,126166,0 +4750,Female,52,Diploma,8,62,87,83,66,5.0,0,17,Rural,Manager,56794,1 +4751,Male,33,Bachelors,1,30,75,11,1,1.0,6,56,Urban,Software Engineer,32803,0 +4752,Male,52,Bachelors,11,4,93,89,50,3.0,7,73,Semi-Urban,Manager,85912,1 +4753,Female,31,Diploma,4,91,50,91,66,6.0,6,90,Rural,HR Executive,112903,1 +4754,Male,28,Bachelors,1,36,45,4,43,1.0,3,37,Rural,ML Engineer,137680,0 +4755,Female,52,High School,14,85,59,30,17,0.0,7,96,Urban,Software Engineer,27779,1 +4756,Female,38,PhD,11,26,17,96,96,8.0,3,36,Semi-Urban,ML Engineer,38235,0 +4757,Male,39,High School,1,60,78,77,26,2.0,3,28,Urban,HR Executive,35243,1 +4758,Female,27,Diploma,11,59,18,91,30,6.0,1,56,Urban,Data Analyst,139532,0 +4759,Male,38,Diploma,3,33,59,11,60,7.0,6,99,Urban,Manager,57541,0 +4760,Other,58,Masters,18,1,90,42,99,5.0,0,11,Semi-Urban,Software Engineer,108016,0 +4761,Male,37,Masters,19,84,70,83,90,6.0,7,12,Rural,Data Analyst,93538,1 +4762,Other,55,High School,18,35,53,1,91,6.0,6,48,Rural,Data Analyst,141939,0 +4763,Female,29,Bachelors,6,60,99,46,24,3.0,0,4,Semi-Urban,Software Engineer,102730,0 +4764,Male,57,Masters,16,6,91,80,85,0.0,7,80,Urban,ML Engineer,123309,1 +4765,Male,29,Masters,17,27,91,82,9,3.0,1,87,Urban,HR Executive,54325,1 +4766,Other,35,Diploma,18,59,43,50,52,2.0,4,44,Semi-Urban,HR Executive,98171,0 +4767,Female,42,High School,12,59,7,92,21,4.0,4,28,Rural,ML Engineer,96520,0 +4768,Male,53,Bachelors,10,44,0,59,99,0.0,5,31,Rural,HR Executive,133278,0 +4769,Female,53,Diploma,14,69,98,21,75,1.0,7,4,Semi-Urban,ML Engineer,127243,0 +4770,Male,47,Masters,5,65,45,46,50,6.0,3,59,Rural,ML Engineer,21397,0 +4771,Male,52,Diploma,6,87,81,54,55,3.0,2,4,Urban,Manager,126724,0 +4772,Male,53,Diploma,0,54,39,44,10,3.0,3,80,Rural,Software Engineer,38084,0 +4773,Male,53,Masters,7,47,30,81,39,6.0,6,9,Semi-Urban,ML Engineer,121157,0 +4774,Female,44,Bachelors,19,30,15,89,5,4.0,1,20,Urban,Data Analyst,36685,0 +4775,Male,26,PhD,13,6,60,21,76,1.0,5,48,Rural,Data Analyst,22143,0 +4776,Female,21,High School,16,12,1,41,18,4.0,2,57,Urban,ML Engineer,146778,0 +4777,Male,29,PhD,8,83,35,19,65,8.0,4,90,Semi-Urban,Software Engineer,80189,0 +4778,Male,43,Bachelors,4,31,66,70,4,9.0,0,94,Rural,Manager,145077,1 +4779,Male,28,Bachelors,12,1,58,36,37,9.0,7,67,Urban,HR Executive,24905,0 +4780,Male,49,Masters,1,21,84,5,24,6.0,2,60,Urban,ML Engineer,127878,0 +4781,Male,38,PhD,3,57,51,68,71,2.0,7,53,Rural,HR Executive,99610,0 +4782,Male,54,Bachelors,8,26,51,15,82,0.0,5,79,Urban,Software Engineer,45936,0 +4783,Male,28,Diploma,9,28,10,99,57,7.0,3,80,Semi-Urban,ML Engineer,52483,0 +4784,Male,30,Masters,3,28,0,98,15,0.0,0,85,Urban,Data Analyst,149245,0 +4785,Male,55,High School,18,89,92,86,22,0.0,7,30,Urban,Software Engineer,32295,1 +4786,Male,36,Masters,0,36,33,85,7,6.0,5,42,Urban,HR Executive,119202,0 +4787,Female,44,High School,5,60,11,4,75,6.0,1,14,Urban,Software Engineer,28651,0 +4788,Female,28,Bachelors,1,89,51,77,80,9.0,2,97,Semi-Urban,Data Analyst,74603,1 +4789,Male,31,High School,12,88,92,17,23,1.0,3,56,Urban,Software Engineer,40809,1 +4790,Male,25,High School,5,44,47,39,37,6.0,7,98,Semi-Urban,Software Engineer,68435,0 +4791,Male,44,Bachelors,7,91,62,75,34,5.0,4,14,Urban,Manager,60755,1 +4792,Other,56,Bachelors,18,28,93,4,34,0.0,3,95,Semi-Urban,Data Analyst,32554,0 +4793,Male,25,Diploma,4,70,35,41,31,4.0,1,76,Semi-Urban,Data Analyst,120366,0 +4794,Male,58,Bachelors,3,8,96,9,87,2.0,1,84,Urban,Manager,24773,0 +4795,Male,50,PhD,7,94,33,76,43,9.0,2,85,Semi-Urban,Manager,68411,1 +4796,Male,31,Bachelors,15,72,78,13,95,4.0,1,67,Rural,Software Engineer,96992,0 +4797,Male,58,Diploma,2,70,14,76,6,9.0,7,69,Urban,HR Executive,83739,0 +4798,Female,46,Diploma,1,51,36,24,60,4.0,0,59,Rural,HR Executive,47196,0 +4799,Male,59,High School,4,99,69,63,61,3.0,6,86,Rural,Software Engineer,81055,1 +4800,Female,23,Bachelors,16,63,91,85,22,0.0,4,27,Semi-Urban,ML Engineer,39988,1 +4801,Male,57,Bachelors,6,95,45,47,88,9.0,0,1,Semi-Urban,HR Executive,28854,0 +4802,Male,33,Bachelors,1,81,25,83,76,6.0,5,16,Urban,Software Engineer,51552,0 +4803,Female,34,Masters,16,89,91,27,89,8.0,5,66,Urban,Software Engineer,38294,1 +4804,Male,46,Masters,14,13,36,87,78,2.0,4,18,Urban,HR Executive,136317,0 +4805,Female,30,Bachelors,1,38,56,90,92,8.0,6,43,Urban,ML Engineer,142788,0 +4806,Male,43,Bachelors,15,3,58,68,17,0.0,3,47,Urban,HR Executive,126825,0 +4807,Male,31,Diploma,11,8,64,91,42,9.0,0,95,Rural,ML Engineer,57463,1 +4808,Other,24,High School,14,79,36,23,0,7.0,7,10,Urban,Manager,76750,0 +4809,Male,33,High School,15,25,81,80,67,0.0,1,49,Semi-Urban,Manager,111656,1 +4810,Female,51,Bachelors,1,92,56,32,10,7.0,1,26,Urban,HR Executive,111945,0 +4811,Male,38,Masters,16,71,79,24,73,1.0,7,2,Rural,Software Engineer,28236,0 +4812,Female,54,Masters,12,57,52,17,51,2.0,4,90,Semi-Urban,HR Executive,92290,0 +4813,Male,34,Bachelors,10,71,81,11,34,5.0,1,85,Urban,Data Analyst,41807,1 +4814,Male,45,Bachelors,2,68,44,7,63,5.0,4,52,Rural,HR Executive,115699,0 +4815,Female,45,Diploma,19,67,43,71,38,1.0,3,54,Urban,Software Engineer,72683,0 +4816,Female,22,Diploma,3,55,93,55,63,3.0,2,51,Semi-Urban,Data Analyst,101745,1 +4817,Female,38,Masters,5,42,85,37,85,6.0,4,34,Urban,Software Engineer,141670,0 +4818,Female,38,High School,3,3,82,94,92,8.0,7,16,Semi-Urban,Software Engineer,147676,0 +4819,Female,43,Diploma,2,91,2,69,50,0.0,1,37,Semi-Urban,Data Analyst,130717,0 +4820,Male,22,Masters,13,43,8,97,16,8.0,4,73,Rural,Manager,47116,0 +4821,Male,41,Masters,17,87,1,89,1,1.0,5,6,Semi-Urban,ML Engineer,138673,0 +4822,Male,21,Bachelors,13,39,17,59,35,5.0,0,14,Urban,Software Engineer,138673,0 +4823,Male,49,Bachelors,13,49,24,19,86,3.0,5,28,Urban,Data Analyst,83665,0 +4824,Male,52,High School,12,4,83,81,76,2.0,3,78,Rural,Manager,68683,1 +4825,Male,56,Bachelors,19,50,60,7,47,1.0,3,17,Urban,Manager,27417,0 +4826,Male,33,Diploma,19,60,94,71,78,7.0,1,37,Urban,Data Analyst,21176,1 +4827,Female,33,Bachelors,3,62,77,36,54,8.0,4,36,Semi-Urban,Software Engineer,88355,0 +4828,Male,23,High School,17,10,24,75,29,7.0,5,65,Semi-Urban,Manager,140904,0 +4829,Male,50,Masters,6,92,15,2,27,8.0,0,57,Urban,ML Engineer,98873,0 +4830,Male,58,Masters,3,84,25,66,19,9.0,7,73,Semi-Urban,HR Executive,83002,1 +4831,Female,45,Diploma,1,49,34,49,11,5.0,7,45,Rural,HR Executive,81322,0 +4832,Female,56,Masters,15,25,76,39,8,1.0,3,89,Rural,Software Engineer,127306,0 +4833,Female,34,Bachelors,16,15,29,31,48,7.0,7,69,Semi-Urban,Software Engineer,146317,0 +4834,Male,54,Bachelors,0,82,76,41,26,4.0,6,6,Semi-Urban,Software Engineer,41353,0 +4835,Male,42,Diploma,12,65,64,63,2,2.0,5,69,Rural,Manager,138984,1 +4836,Male,21,Bachelors,3,75,81,42,59,5.0,1,55,Semi-Urban,Software Engineer,102275,1 +4837,Male,43,Bachelors,18,84,81,88,53,7.0,2,82,Urban,HR Executive,85289,1 +4838,Male,46,Bachelors,10,69,27,18,13,3.0,4,37,Urban,Data Analyst,88625,0 +4839,Male,41,Bachelors,7,95,65,59,30,7.0,2,59,Urban,ML Engineer,136464,1 +4840,Male,25,Bachelors,0,37,25,37,79,8.0,1,36,Urban,ML Engineer,64156,0 +4841,Other,26,High School,5,2,33,84,7,7.0,0,1,Urban,Manager,80137,0 +4842,Other,40,Bachelors,3,41,63,10,41,1.0,3,98,Rural,ML Engineer,30438,0 +4843,Male,56,Diploma,8,49,57,27,36,9.0,1,40,Urban,ML Engineer,67775,0 +4844,Male,41,Diploma,17,3,7,76,96,3.0,5,53,Rural,Data Analyst,63169,0 +4845,Male,55,Bachelors,2,66,70,25,96,6.0,6,61,Urban,HR Executive,100237,0 +4846,Male,34,Diploma,11,22,61,61,76,3.0,7,85,Semi-Urban,Manager,119481,0 +4847,Female,45,Bachelors,16,71,22,45,84,7.0,0,89,Rural,Manager,89740,0 +4848,Male,37,High School,9,35,29,33,82,9.0,0,2,Semi-Urban,ML Engineer,50508,0 +4849,Female,59,Bachelors,10,89,98,58,10,3.0,1,64,Semi-Urban,ML Engineer,54330,1 +4850,Male,23,Bachelors,3,35,21,45,80,0.0,7,28,Semi-Urban,HR Executive,61797,0 +4851,Other,59,Bachelors,16,69,61,91,39,3.0,1,10,Semi-Urban,Software Engineer,116251,0 +4852,Male,30,Masters,18,15,95,52,2,5.0,7,96,Urban,Data Analyst,135185,1 +4853,Female,26,Bachelors,0,29,48,60,48,2.0,7,65,Semi-Urban,Manager,71064,0 +4854,Male,32,Masters,8,28,88,58,19,0.0,5,91,Semi-Urban,HR Executive,31983,1 +4855,Female,57,Diploma,13,78,71,61,80,0.0,6,25,Urban,ML Engineer,135196,0 +4856,Male,48,Bachelors,9,19,4,42,67,1.0,2,42,Urban,Data Analyst,144112,0 +4857,Male,56,High School,3,53,39,76,76,7.0,6,79,Urban,Software Engineer,127617,1 +4858,Female,21,Bachelors,2,77,77,76,1,4.0,4,79,Urban,ML Engineer,90354,1 +4859,Female,58,Diploma,14,96,30,99,44,9.0,7,67,Urban,ML Engineer,56687,1 +4860,Female,51,PhD,6,51,3,57,65,3.0,3,1,Urban,HR Executive,103675,0 +4861,Female,37,Bachelors,14,63,20,79,69,9.0,6,78,Semi-Urban,ML Engineer,53811,0 +4862,Female,42,Diploma,0,85,60,54,41,0.0,7,65,Urban,ML Engineer,65267,1 +4863,Male,54,Bachelors,12,67,4,58,82,6.0,5,40,Urban,ML Engineer,54420,0 +4864,Male,54,Masters,2,74,44,54,45,6.0,1,8,Urban,Data Analyst,26325,0 +4865,Male,49,Bachelors,7,23,18,88,8,1.0,4,67,Urban,Software Engineer,79804,0 +4866,Female,42,Bachelors,7,73,13,72,75,2.0,5,99,Urban,HR Executive,36268,1 +4867,Male,55,Bachelors,4,3,5,21,5,5.0,0,90,Rural,Manager,73571,0 +4868,Male,58,Bachelors,9,86,88,75,17,1.0,1,37,Rural,HR Executive,95235,1 +4869,Male,36,High School,3,39,84,77,83,3.0,3,18,Urban,ML Engineer,139850,0 +4870,Female,51,Bachelors,18,91,31,57,45,6.0,1,58,Rural,HR Executive,142459,0 +4871,Male,55,Masters,8,49,78,94,88,1.0,5,49,Rural,HR Executive,82639,1 +4872,Male,30,Bachelors,18,24,68,25,85,5.0,7,61,Urban,ML Engineer,145563,0 +4873,Male,26,Bachelors,7,77,11,75,61,2.0,1,26,Urban,Software Engineer,44460,0 +4874,Male,39,Bachelors,2,19,0,73,35,9.0,3,68,Semi-Urban,ML Engineer,39120,0 +4875,Male,32,Bachelors,10,97,0,87,47,0.0,6,20,Semi-Urban,Manager,95282,0 +4876,Female,47,Bachelors,10,12,97,62,64,9.0,4,30,Rural,Software Engineer,75210,0 +4877,Female,53,Masters,2,20,47,82,15,9.0,0,66,Rural,Software Engineer,131623,0 +4878,Female,46,Masters,8,8,97,18,70,8.0,1,10,Urban,ML Engineer,104639,0 +4879,Male,57,High School,1,83,16,64,25,0.0,4,88,Urban,Software Engineer,32758,1 +4880,Female,44,Bachelors,9,63,55,97,53,2.0,3,39,Semi-Urban,ML Engineer,35159,1 +4881,Male,51,High School,7,62,26,26,2,8.0,0,68,Rural,Software Engineer,136958,0 +4882,Male,22,Bachelors,7,33,91,45,43,6.0,6,77,Rural,HR Executive,20226,1 +4883,Female,42,Diploma,16,2,4,58,13,3.0,5,41,Rural,Manager,103114,0 +4884,Male,38,High School,18,98,26,10,46,1.0,7,89,Urban,ML Engineer,89594,0 +4885,Male,40,Diploma,1,1,24,40,70,6.0,7,82,Semi-Urban,Data Analyst,144371,0 +4886,Female,38,Bachelors,13,15,62,90,9,7.0,3,81,Urban,ML Engineer,89361,1 +4887,Male,49,Bachelors,6,41,37,32,86,3.0,3,38,Urban,Data Analyst,39348,0 +4888,Female,45,Bachelors,19,28,93,43,62,3.0,1,69,Urban,Data Analyst,130712,0 +4889,Male,31,Diploma,6,70,53,4,67,0.0,7,57,Urban,Software Engineer,95230,0 +4890,Female,56,Bachelors,4,30,1,31,56,9.0,6,63,Rural,Software Engineer,143050,0 +4891,Male,32,Bachelors,7,82,90,48,53,6.0,6,34,Urban,HR Executive,67594,1 +4892,Male,28,Diploma,1,82,67,58,13,2.0,1,86,Rural,Data Analyst,59483,1 +4893,Female,48,High School,12,29,19,48,89,1.0,5,14,Rural,Data Analyst,114778,0 +4894,Male,23,High School,19,16,54,58,48,0.0,3,89,Rural,ML Engineer,31595,0 +4895,Male,53,Masters,7,17,38,73,92,3.0,1,46,Urban,Software Engineer,50174,0 +4896,Male,31,Diploma,17,16,47,6,21,2.0,5,69,Semi-Urban,HR Executive,102777,0 +4897,Male,40,Masters,13,30,8,93,55,9.0,4,93,Urban,Software Engineer,93271,0 +4898,Male,50,PhD,3,79,45,91,43,2.0,4,80,Urban,Software Engineer,65650,1 +4899,Male,48,Masters,14,67,99,36,75,5.0,5,46,Rural,Manager,86657,1 +4900,Female,52,Masters,10,29,89,70,77,5.0,6,23,Urban,Data Analyst,78708,0 +4901,Male,35,Masters,11,99,28,77,9,8.0,4,63,Urban,HR Executive,88817,1 +4902,Male,36,Masters,15,25,83,10,30,0.0,4,92,Rural,ML Engineer,123087,0 +4903,Male,25,Masters,18,45,5,83,79,7.0,5,1,Urban,Manager,100369,0 +4904,Male,24,Diploma,19,9,6,77,58,5.0,0,49,Urban,Software Engineer,80326,0 +4905,Female,47,Diploma,9,89,62,39,15,9.0,5,24,Urban,Manager,74185,0 +4906,Male,24,High School,8,31,17,1,86,9.0,1,49,Urban,Software Engineer,44019,0 +4907,Other,37,High School,14,98,56,80,66,1.0,6,90,Semi-Urban,Manager,90220,1 +4908,Male,34,Bachelors,5,46,83,53,26,3.0,0,71,Urban,HR Executive,139908,1 +4909,Female,21,Bachelors,15,90,39,74,24,1.0,7,47,Urban,Software Engineer,31171,1 +4910,Male,29,Diploma,19,53,25,15,50,1.0,4,59,Urban,ML Engineer,57516,0 +4911,Female,51,Bachelors,2,60,10,86,6,1.0,2,93,Rural,Data Analyst,104125,1 +4912,Male,32,Masters,2,53,30,15,92,1.0,2,83,Semi-Urban,ML Engineer,96206,0 +4913,Male,28,Masters,14,11,57,36,32,7.0,2,56,Semi-Urban,Data Analyst,123237,0 +4914,Male,55,Bachelors,5,37,86,33,89,9.0,0,65,Urban,Data Analyst,127567,0 +4915,Male,59,Bachelors,18,3,9,14,5,9.0,0,30,Urban,Software Engineer,137249,0 +4916,Female,43,Masters,8,73,74,97,62,4.0,6,28,Rural,Software Engineer,78791,1 +4917,Male,21,Masters,0,81,44,16,67,3.0,1,7,Urban,Software Engineer,22619,0 +4918,Male,21,High School,4,18,71,46,80,5.0,2,56,Semi-Urban,HR Executive,70795,0 +4919,Female,34,Masters,12,30,64,60,28,0.0,2,52,Semi-Urban,HR Executive,55541,0 +4920,Male,59,Masters,6,62,60,44,8,8.0,3,29,Rural,Manager,138097,0 +4921,Other,59,Masters,13,9,46,51,43,9.0,5,37,Urban,Manager,50512,0 +4922,Female,52,Masters,6,56,39,96,90,0.0,1,62,Urban,ML Engineer,110223,1 +4923,Male,57,Masters,14,75,42,66,93,9.0,2,53,Urban,Manager,52839,1 +4924,Female,48,Diploma,9,2,9,86,96,4.0,0,88,Semi-Urban,Software Engineer,145247,0 +4925,Male,56,High School,19,63,3,31,11,7.0,5,83,Urban,Data Analyst,55444,0 +4926,Male,53,Diploma,18,65,40,64,55,3.0,6,42,Semi-Urban,ML Engineer,65573,0 +4927,Male,47,High School,7,80,39,70,97,5.0,2,75,Urban,ML Engineer,73237,1 +4928,Male,53,Bachelors,1,59,75,17,76,0.0,2,12,Semi-Urban,HR Executive,124273,0 +4929,Female,23,Masters,17,37,25,76,54,2.0,1,92,Urban,Data Analyst,108476,0 +4930,Female,40,Bachelors,19,51,47,44,5,3.0,6,81,Urban,Data Analyst,142478,0 +4931,Male,55,Diploma,10,75,88,22,97,2.0,1,33,Urban,ML Engineer,136093,0 +4932,Male,57,Bachelors,9,78,23,49,65,4.0,6,59,Urban,Data Analyst,39662,0 +4933,Other,34,Bachelors,16,10,99,82,86,9.0,6,95,Urban,Data Analyst,54019,1 +4934,Male,31,Bachelors,5,72,92,59,26,2.0,2,43,Rural,ML Engineer,53859,1 +4935,Male,22,Bachelors,7,69,60,71,76,4.0,2,98,Urban,ML Engineer,53212,1 +4936,Male,24,Diploma,6,39,11,5,47,0.0,1,55,Urban,HR Executive,32424,0 +4937,Female,30,High School,3,77,55,38,14,6.0,3,68,Urban,Software Engineer,41023,0 +4938,Male,27,Masters,16,87,59,19,45,3.0,2,71,Urban,Software Engineer,92042,1 +4939,Female,39,Bachelors,19,13,97,69,9,8.0,1,61,Semi-Urban,Manager,101569,0 +4940,Female,27,High School,10,34,30,60,80,9.0,4,77,Rural,Software Engineer,94093,0 +4941,Male,47,Masters,14,90,1,69,42,9.0,4,28,Urban,HR Executive,101719,0 +4942,Male,54,Diploma,1,25,28,44,29,9.0,7,21,Urban,ML Engineer,28010,0 +4943,Female,25,High School,6,60,3,14,59,2.0,6,2,Urban,HR Executive,62925,0 +4944,Male,50,High School,1,45,64,50,14,0.0,0,27,Urban,Manager,53241,0 +4945,Female,46,Bachelors,14,40,95,55,96,0.0,0,85,Urban,Software Engineer,77693,1 +4946,Female,29,Bachelors,3,65,31,96,24,0.0,5,12,Urban,ML Engineer,55719,0 +4947,Female,55,Masters,11,39,20,99,45,6.0,2,62,Urban,HR Executive,117730,0 +4948,Female,26,High School,18,62,82,56,96,7.0,4,34,Rural,Software Engineer,117192,0 +4949,Female,45,Bachelors,9,67,26,57,9,5.0,0,27,Rural,Data Analyst,76139,0 +4950,Female,30,Diploma,18,97,13,25,52,7.0,2,36,Semi-Urban,Software Engineer,111188,0 +4951,Male,39,Bachelors,11,10,16,25,69,5.0,0,54,Urban,HR Executive,71612,0 +4952,Male,55,Bachelors,14,14,2,22,64,4.0,2,64,Rural,HR Executive,23159,0 +4953,Male,59,Bachelors,13,50,52,37,97,1.0,1,20,Urban,HR Executive,125159,0 +4954,Female,46,Masters,10,62,7,85,84,7.0,2,12,Urban,Manager,82304,0 +4955,Male,55,Bachelors,18,38,80,93,22,8.0,7,28,Semi-Urban,Software Engineer,118242,1 +4956,Female,23,Bachelors,15,67,90,56,23,5.0,0,76,Urban,Software Engineer,58952,1 +4957,Male,25,Diploma,12,24,92,12,37,1.0,1,63,Urban,Manager,147658,0 +4958,Female,29,Bachelors,1,56,63,88,43,7.0,5,30,Rural,ML Engineer,111799,0 +4959,Male,49,Bachelors,11,26,43,42,40,1.0,0,13,Urban,ML Engineer,68619,0 +4960,Female,54,High School,0,33,40,30,30,3.0,1,41,Semi-Urban,HR Executive,97396,0 +4961,Male,40,Masters,12,29,90,4,62,0.0,5,96,Rural,Software Engineer,149594,0 +4962,Male,36,Bachelors,13,73,2,37,43,2.0,1,5,Semi-Urban,Software Engineer,142044,0 +4963,Male,53,Bachelors,0,88,4,68,81,0.0,5,62,Semi-Urban,Data Analyst,136073,0 +4964,Female,42,Bachelors,14,69,98,16,0,9.0,1,79,Semi-Urban,ML Engineer,51271,1 +4965,Male,35,PhD,14,70,80,98,12,6.0,3,45,Rural,Manager,30623,1 +4966,Male,56,Diploma,13,57,0,37,5,7.0,3,98,Urban,ML Engineer,93124,0 +4967,Other,42,Masters,19,18,2,88,29,6.0,3,9,Urban,Software Engineer,25832,0 +4968,Female,54,Diploma,12,42,21,31,58,4.0,0,6,Urban,HR Executive,57462,0 +4969,Other,45,Masters,6,66,94,34,97,7.0,0,72,Semi-Urban,Data Analyst,99739,1 +4970,Male,48,Bachelors,14,39,34,83,93,5.0,2,38,Urban,Software Engineer,28774,0 +4971,Male,54,Bachelors,15,43,72,71,82,1.0,6,22,Rural,ML Engineer,131181,0 +4972,Female,41,Masters,16,97,56,62,66,8.0,6,12,Urban,HR Executive,91160,0 +4973,Male,47,Bachelors,11,89,13,0,99,5.0,2,21,Rural,ML Engineer,50579,0 +4974,Female,21,Bachelors,16,64,15,31,69,7.0,2,60,Urban,HR Executive,112116,0 +4975,Male,49,PhD,13,85,74,42,51,5.0,3,34,Urban,Software Engineer,119744,1 +4976,Male,52,Bachelors,17,26,42,8,86,3.0,6,27,Semi-Urban,Software Engineer,37190,0 +4977,Male,33,Bachelors,11,5,25,40,3,9.0,7,38,Semi-Urban,Manager,90684,0 +4978,Male,33,Diploma,10,80,74,85,22,4.0,2,94,Rural,ML Engineer,140598,1 +4979,Male,56,Bachelors,4,29,76,65,24,6.0,3,7,Urban,HR Executive,103128,0 +4980,Male,33,Masters,9,99,23,61,39,2.0,2,60,Semi-Urban,Software Engineer,55115,1 +4981,Other,25,High School,11,21,75,71,29,8.0,3,6,Urban,Software Engineer,146205,0 +4982,Male,30,Diploma,10,85,11,36,59,8.0,5,90,Semi-Urban,HR Executive,85231,0 +4983,Female,34,PhD,14,65,29,43,54,4.0,2,42,Rural,ML Engineer,111854,0 +4984,Female,37,Diploma,4,52,83,20,98,6.0,6,52,Urban,HR Executive,137560,0 +4985,Male,22,Bachelors,3,3,53,86,16,4.0,3,98,Rural,Software Engineer,38220,1 +4986,Male,54,High School,5,97,88,32,37,1.0,6,30,Semi-Urban,Data Analyst,126968,1 +4987,Female,36,High School,14,40,71,98,69,4.0,1,77,Rural,Manager,104110,1 +4988,Female,45,Bachelors,17,94,28,29,29,5.0,7,3,Urban,Software Engineer,55094,0 +4989,Female,27,Diploma,1,2,91,35,57,9.0,4,49,Rural,Software Engineer,127762,0 +4990,Female,54,Bachelors,0,75,47,95,11,2.0,3,72,Urban,HR Executive,34534,1 +4991,Other,42,Bachelors,10,44,47,58,6,5.0,0,60,Semi-Urban,Manager,139487,0 +4992,Male,46,Bachelors,3,77,88,29,98,3.0,4,84,Urban,HR Executive,147240,1 +4993,Male,40,Bachelors,7,73,86,55,10,0.0,2,4,Urban,Manager,131921,0 +4994,Female,21,Diploma,12,40,44,29,60,0.0,3,39,Semi-Urban,Data Analyst,95371,0 +4995,Male,29,High School,17,84,43,88,54,5.0,1,3,Urban,Software Engineer,106218,0 +4996,Female,42,Bachelors,5,21,18,35,71,5.0,0,81,Urban,Manager,81383,0 +4997,Male,51,Diploma,13,90,3,10,53,4.0,7,68,Urban,ML Engineer,55473,0 +4998,Male,37,Bachelors,15,11,27,77,10,2.0,1,81,Urban,ML Engineer,115820,0 +4999,Female,22,Masters,19,48,44,15,61,3.0,1,83,Urban,ML Engineer,54272,0 +5000,Male,36,Masters,0,30,25,96,41,9.0,7,70,Urban,Software Engineer,115642,0 +5001,Male,30,Masters,8,5,18,66,76,9.0,7,85,Urban,Data Analyst,31107,0 +5002,Male,30,Masters,1,64,47,0,96,1.0,0,37,Urban,Software Engineer,70809,0 +5003,Female,45,Bachelors,19,42,24,12,50,1.0,6,75,Rural,HR Executive,45834,0 +5004,Male,55,Bachelors,8,64,69,88,72,9.0,7,10,Urban,Software Engineer,37420,0 +5005,Female,35,Diploma,13,71,38,82,3,9.0,4,41,Urban,HR Executive,34597,0 +5006,Male,39,High School,17,79,16,91,66,5.0,1,1,Urban,Manager,68701,0 +5007,Female,24,Bachelors,0,67,4,85,89,5.0,4,54,Urban,Data Analyst,29936,0 +5008,Female,42,Masters,9,46,26,38,74,1.0,6,23,Urban,Data Analyst,44088,0 +5009,Male,56,PhD,9,76,48,0,76,6.0,0,36,Urban,ML Engineer,99624,0 +5010,Male,42,Bachelors,10,90,29,40,18,3.0,4,53,Rural,Software Engineer,114436,0 +5011,Male,39,Diploma,11,89,62,77,30,0.0,3,57,Urban,HR Executive,102297,1 +5012,Female,29,Bachelors,6,61,27,79,21,1.0,3,2,Rural,Manager,79989,0 +5013,Male,31,PhD,1,0,97,46,61,6.0,3,56,Urban,Software Engineer,74480,0 +5014,Female,28,Diploma,8,80,52,35,77,0.0,7,82,Urban,Manager,58860,1 +5015,Male,21,Bachelors,9,3,77,45,27,9.0,0,58,Urban,Software Engineer,32404,0 +5016,Male,42,Bachelors,12,4,99,78,65,9.0,5,62,Urban,HR Executive,141167,1 +5017,Male,22,Bachelors,19,95,70,39,65,7.0,2,47,Urban,ML Engineer,66994,1 +5018,Male,35,Masters,0,16,7,47,18,8.0,1,76,Semi-Urban,Data Analyst,140718,0 +5019,Male,49,Bachelors,4,90,30,39,98,0.0,7,31,Urban,Data Analyst,25939,0 +5020,Female,35,Bachelors,16,30,89,98,98,7.0,4,41,Rural,HR Executive,86541,1 +5021,Female,38,Masters,9,21,44,12,46,0.0,6,48,Urban,Data Analyst,134710,0 +5022,Male,30,Diploma,4,81,82,41,9,7.0,6,98,Semi-Urban,Data Analyst,111269,1 +5023,Other,39,Bachelors,17,29,98,71,98,5.0,7,21,Urban,HR Executive,125852,0 +5024,Female,30,Masters,3,30,62,65,69,3.0,7,13,Urban,Data Analyst,66395,0 +5025,Female,47,Bachelors,6,62,27,70,58,5.0,0,29,Semi-Urban,Software Engineer,58357,0 +5026,Male,42,Bachelors,0,96,33,56,58,1.0,4,30,Semi-Urban,Manager,122185,0 +5027,Male,50,Bachelors,4,34,46,51,64,3.0,6,27,Urban,Manager,54213,0 +5028,Male,45,High School,16,44,66,60,22,0.0,5,17,Rural,Manager,75477,0 +5029,Female,35,Masters,11,61,9,91,57,7.0,5,8,Urban,Software Engineer,23160,0 +5030,Male,23,Masters,10,48,88,62,65,0.0,7,96,Semi-Urban,Manager,79145,1 +5031,Male,29,Diploma,17,20,39,66,3,2.0,1,95,Rural,HR Executive,26286,0 +5032,Male,54,Bachelors,4,60,37,36,38,3.0,5,55,Rural,Software Engineer,141188,0 +5033,Male,53,Bachelors,3,5,4,67,20,0.0,0,19,Semi-Urban,Data Analyst,30889,0 +5034,Female,43,Bachelors,7,46,93,28,65,4.0,7,29,Urban,ML Engineer,86569,0 +5035,Male,30,Diploma,1,56,16,66,26,2.0,4,45,Urban,Software Engineer,110705,0 +5036,Male,54,Bachelors,17,24,3,12,31,5.0,6,83,Urban,Software Engineer,23685,0 +5037,Female,59,High School,0,52,70,98,57,4.0,7,96,Urban,Manager,45998,1 +5038,Other,21,Diploma,18,41,83,10,95,6.0,0,65,Semi-Urban,Data Analyst,139743,0 +5039,Female,28,High School,0,51,35,69,3,5.0,7,21,Urban,HR Executive,40285,0 +5040,Female,59,PhD,11,84,26,61,10,8.0,5,24,Rural,Manager,42729,0 +5041,Female,34,Diploma,16,20,69,64,1,6.0,3,3,Urban,ML Engineer,63799,0 +5042,Male,23,Diploma,3,34,42,21,62,0.0,4,47,Semi-Urban,ML Engineer,125019,0 +5043,Male,32,Masters,10,55,92,71,27,5.0,1,80,Rural,Software Engineer,119691,1 +5044,Female,34,Bachelors,17,31,12,51,29,5.0,3,46,Urban,HR Executive,143801,0 +5045,Female,38,High School,8,78,44,68,39,0.0,5,5,Urban,Software Engineer,146367,0 +5046,Female,54,Bachelors,9,3,2,22,72,4.0,1,10,Semi-Urban,Data Analyst,108946,0 +5047,Male,29,High School,19,64,29,73,67,1.0,7,36,Urban,Data Analyst,29051,0 +5048,Male,22,Bachelors,14,57,93,37,69,6.0,7,16,Semi-Urban,Software Engineer,142680,0 +5049,Male,35,Diploma,19,82,31,43,27,0.0,3,65,Urban,Data Analyst,139824,0 +5050,Male,29,Diploma,16,67,18,25,25,3.0,1,93,Semi-Urban,Data Analyst,35785,0 +5051,Male,31,Diploma,19,97,12,27,43,6.0,0,22,Urban,ML Engineer,128824,0 +5052,Female,41,Masters,13,67,72,5,45,4.0,4,37,Urban,Software Engineer,104469,0 +5053,Male,21,Diploma,18,4,19,60,22,7.0,3,25,Rural,ML Engineer,90729,0 +5054,Male,40,PhD,10,11,25,38,25,6.0,1,12,Rural,Data Analyst,59637,0 +5055,Male,46,Masters,9,71,43,61,81,6.0,2,69,Urban,Data Analyst,143352,1 +5056,Female,29,Diploma,9,99,89,83,27,1.0,0,1,Rural,HR Executive,21070,1 +5057,Male,36,Bachelors,14,66,5,34,84,4.0,7,8,Urban,Software Engineer,73584,0 +5058,Male,46,Bachelors,5,50,22,87,16,7.0,7,72,Urban,ML Engineer,123178,0 +5059,Male,28,Bachelors,5,83,87,88,30,8.0,1,51,Urban,Data Analyst,22661,1 +5060,Male,47,Diploma,1,66,41,28,66,2.0,6,66,Urban,Software Engineer,134664,0 +5061,Female,30,Diploma,15,66,58,99,6,0.0,2,47,Urban,Software Engineer,61900,1 +5062,Female,35,Masters,19,49,55,64,4,2.0,5,78,Rural,ML Engineer,138754,1 +5063,Male,39,Diploma,2,20,43,88,94,4.0,1,15,Semi-Urban,ML Engineer,77747,0 +5064,Male,44,Masters,7,81,94,99,53,5.0,1,52,Urban,Software Engineer,63124,1 +5065,Female,33,Bachelors,19,30,44,54,35,5.0,2,70,Semi-Urban,HR Executive,92228,0 +5066,Male,27,Bachelors,3,76,93,82,31,9.0,3,33,Urban,Manager,135381,1 +5067,Male,27,Masters,7,51,15,49,96,8.0,7,58,Urban,Manager,82800,0 +5068,Male,56,Masters,10,24,63,9,17,0.0,2,28,Urban,HR Executive,108502,0 +5069,Female,48,Bachelors,2,46,90,57,90,9.0,7,90,Urban,Manager,61852,1 +5070,Male,56,Masters,9,19,20,55,1,0.0,6,76,Urban,HR Executive,141442,0 +5071,Male,35,High School,7,52,38,92,28,9.0,1,50,Semi-Urban,Manager,42006,0 +5072,Female,55,Diploma,13,79,21,48,61,5.0,0,50,Urban,HR Executive,91317,0 +5073,Male,32,Bachelors,3,68,96,96,41,6.0,6,40,Rural,Data Analyst,72702,1 +5074,Male,48,High School,11,53,13,96,96,5.0,5,71,Semi-Urban,Manager,110315,0 +5075,Other,51,Diploma,8,58,46,80,23,2.0,5,96,Urban,ML Engineer,119713,1 +5076,Male,51,Diploma,7,8,16,36,57,6.0,6,16,Urban,ML Engineer,123114,0 +5077,Female,32,Diploma,17,84,43,77,41,7.0,2,39,Urban,Data Analyst,92571,1 +5078,Male,37,Masters,4,91,58,71,75,1.0,1,24,Semi-Urban,Data Analyst,20473,1 +5079,Male,24,Bachelors,3,69,46,44,58,7.0,5,6,Semi-Urban,Software Engineer,29190,0 +5080,Male,31,Masters,14,28,79,96,88,1.0,7,17,Urban,ML Engineer,134690,0 +5081,Male,53,Bachelors,18,7,38,85,77,3.0,2,98,Urban,Data Analyst,112172,0 +5082,Male,43,Diploma,12,38,2,95,31,4.0,7,90,Urban,Manager,137076,0 +5083,Female,34,Masters,14,87,73,25,18,4.0,6,61,Semi-Urban,Manager,51972,1 +5084,Male,31,Diploma,11,83,49,76,53,4.0,4,25,Semi-Urban,Software Engineer,76479,0 +5085,Male,42,Bachelors,4,26,42,42,44,7.0,1,84,Urban,HR Executive,126608,0 +5086,Male,29,Bachelors,10,89,17,59,98,9.0,4,42,Semi-Urban,ML Engineer,118948,0 +5087,Female,56,Diploma,7,22,47,34,33,9.0,5,9,Semi-Urban,Data Analyst,136986,0 +5088,Male,42,Bachelors,8,40,41,63,58,6.0,6,68,Urban,Data Analyst,24968,0 +5089,Male,51,Bachelors,17,73,35,33,5,0.0,2,50,Semi-Urban,HR Executive,96810,0 +5090,Male,51,Bachelors,6,93,62,77,62,7.0,2,40,Semi-Urban,ML Engineer,145648,1 +5091,Male,26,Bachelors,13,81,73,98,60,0.0,0,99,Urban,Data Analyst,29244,1 +5092,Male,40,Bachelors,8,10,16,19,49,9.0,2,45,Semi-Urban,HR Executive,99072,0 +5093,Female,29,Bachelors,12,83,25,45,53,4.0,0,12,Urban,Manager,91324,0 +5094,Male,40,High School,4,77,6,4,75,8.0,2,1,Urban,ML Engineer,128462,0 +5095,Male,40,Bachelors,1,12,84,32,44,2.0,5,55,Urban,Manager,119523,0 +5096,Male,56,Masters,6,53,32,80,73,3.0,1,25,Semi-Urban,ML Engineer,91512,0 +5097,Female,21,Bachelors,13,35,24,15,33,5.0,4,90,Urban,Software Engineer,41040,0 +5098,Male,55,High School,15,23,96,76,76,0.0,4,48,Semi-Urban,ML Engineer,105218,1 +5099,Male,31,Bachelors,15,72,41,19,53,2.0,6,72,Urban,Manager,20276,0 +5100,Male,23,Diploma,19,30,49,8,52,9.0,1,73,Urban,Software Engineer,74162,0 +5101,Male,26,Diploma,14,1,58,54,30,2.0,0,18,Urban,ML Engineer,143196,0 +5102,Male,41,Diploma,16,71,31,85,39,5.0,6,82,Rural,Data Analyst,143764,1 +5103,Male,29,Masters,0,82,99,75,65,9.0,6,71,Rural,Manager,110383,1 +5104,Male,40,Bachelors,10,86,25,35,48,1.0,5,42,Urban,Data Analyst,121851,0 +5105,Male,39,High School,15,14,87,56,91,7.0,7,14,Rural,HR Executive,55764,0 +5106,Male,46,Bachelors,5,86,94,56,64,5.0,4,58,Urban,HR Executive,104205,1 +5107,Male,34,Bachelors,15,38,26,63,12,8.0,3,43,Urban,Software Engineer,97760,0 +5108,Male,44,Masters,4,17,40,11,3,8.0,6,8,Semi-Urban,ML Engineer,66995,0 +5109,Female,23,Masters,18,99,93,97,87,1.0,1,92,Urban,Data Analyst,99004,1 +5110,Other,48,Masters,16,81,7,63,51,4.0,5,28,Urban,Software Engineer,65915,0 +5111,Other,59,Bachelors,10,44,77,10,7,5.0,5,97,Rural,ML Engineer,130616,0 +5112,Female,21,Masters,16,29,67,32,34,2.0,2,94,Semi-Urban,Software Engineer,114525,0 +5113,Female,29,Bachelors,12,35,41,7,69,0.0,2,24,Urban,HR Executive,119716,0 +5114,Female,21,Bachelors,12,5,70,31,99,9.0,2,76,Urban,ML Engineer,37690,0 +5115,Male,51,Masters,5,8,58,24,66,5.0,6,92,Urban,HR Executive,76003,0 +5116,Female,31,Diploma,6,64,51,25,69,5.0,4,18,Urban,HR Executive,61528,0 +5117,Male,56,Diploma,2,71,70,91,44,5.0,3,69,Semi-Urban,ML Engineer,143685,1 +5118,Male,50,Masters,13,45,17,86,69,2.0,2,76,Urban,Manager,72955,0 +5119,Female,44,Masters,13,99,61,32,84,0.0,5,35,Semi-Urban,Manager,61006,0 +5120,Male,58,Bachelors,17,17,91,32,39,4.0,6,6,Urban,Data Analyst,42759,0 +5121,Male,47,Diploma,19,97,44,97,68,3.0,6,16,Rural,ML Engineer,131675,1 +5122,Female,43,Masters,7,24,38,75,43,4.0,5,46,Urban,ML Engineer,133778,0 +5123,Male,54,High School,4,88,71,99,27,7.0,3,87,Semi-Urban,Manager,37440,1 +5124,Male,55,High School,16,26,5,8,22,8.0,3,1,Semi-Urban,Data Analyst,36342,0 +5125,Female,27,Bachelors,4,8,84,61,83,6.0,5,46,Urban,HR Executive,63072,0 +5126,Female,28,High School,4,59,61,81,54,9.0,3,19,Urban,Software Engineer,101275,0 +5127,Male,47,Masters,18,52,44,40,41,1.0,2,54,Urban,Data Analyst,69223,0 +5128,Male,47,Bachelors,15,57,56,83,61,0.0,0,90,Semi-Urban,ML Engineer,131716,1 +5129,Male,29,Bachelors,16,8,44,79,98,5.0,4,58,Urban,Data Analyst,42661,0 +5130,Female,26,Bachelors,9,34,51,80,5,8.0,2,78,Urban,Manager,21989,1 +5131,Male,22,Bachelors,15,6,18,61,20,5.0,0,11,Urban,ML Engineer,46989,0 +5132,Male,29,Bachelors,3,15,44,52,82,1.0,7,66,Rural,Data Analyst,96006,0 +5133,Male,26,High School,17,55,79,35,50,4.0,2,7,Semi-Urban,Software Engineer,80210,0 +5134,Male,31,Masters,18,33,25,48,27,7.0,7,16,Semi-Urban,HR Executive,98286,0 +5135,Other,21,Masters,3,82,14,32,7,4.0,3,77,Urban,ML Engineer,95921,0 +5136,Male,55,Diploma,2,66,0,26,1,4.0,5,27,Rural,Manager,74387,0 +5137,Female,30,Bachelors,7,21,11,50,11,9.0,5,13,Urban,HR Executive,49407,0 +5138,Male,40,Diploma,2,8,5,79,98,2.0,4,39,Urban,Software Engineer,21705,0 +5139,Female,39,Bachelors,16,43,60,19,76,1.0,5,40,Rural,ML Engineer,136782,0 +5140,Female,31,Masters,15,9,44,43,48,2.0,2,35,Rural,Manager,80422,0 +5141,Male,47,Bachelors,10,73,24,46,56,7.0,1,19,Urban,ML Engineer,141409,0 +5142,Male,49,Bachelors,19,65,71,25,60,2.0,0,60,Semi-Urban,Data Analyst,82066,0 +5143,Male,40,Masters,11,4,53,13,49,6.0,6,59,Urban,Software Engineer,144104,0 +5144,Female,28,Masters,11,40,55,28,99,2.0,2,22,Urban,Manager,81986,0 +5145,Male,33,High School,3,58,75,51,94,8.0,4,46,Urban,Data Analyst,148903,0 +5146,Female,28,Bachelors,8,60,49,18,38,4.0,1,1,Urban,Manager,81175,0 +5147,Female,39,High School,16,11,73,49,10,3.0,3,45,Urban,Software Engineer,102897,0 +5148,Female,53,Bachelors,7,28,17,20,70,6.0,7,62,Urban,ML Engineer,70736,0 +5149,Female,59,Bachelors,5,81,83,43,57,7.0,7,8,Urban,Software Engineer,114641,0 +5150,Male,44,High School,19,41,46,66,81,7.0,3,9,Semi-Urban,Data Analyst,108360,0 +5151,Male,53,Bachelors,11,25,53,86,20,5.0,4,68,Urban,Manager,100702,0 +5152,Male,56,Masters,13,47,97,70,73,6.0,3,63,Rural,Software Engineer,133166,1 +5153,Female,23,Diploma,19,60,12,21,10,9.0,3,48,Semi-Urban,Manager,71509,0 +5154,Female,23,Masters,0,44,90,83,39,6.0,5,19,Urban,Manager,27792,0 +5155,Female,21,High School,16,37,16,77,6,8.0,6,70,Urban,ML Engineer,139799,0 +5156,Male,47,Diploma,18,41,68,55,28,5.0,0,57,Rural,Software Engineer,71088,0 +5157,Male,59,High School,6,82,93,29,29,3.0,5,37,Rural,Manager,75664,1 +5158,Female,55,Masters,18,84,60,43,80,4.0,4,68,Urban,HR Executive,115467,1 +5159,Male,54,Bachelors,1,60,46,28,99,6.0,2,66,Urban,Software Engineer,85624,0 +5160,Male,46,PhD,9,38,25,86,1,4.0,4,92,Rural,Software Engineer,93565,1 +5161,Female,51,High School,5,84,5,63,15,5.0,0,13,Urban,HR Executive,64464,0 +5162,Male,48,Masters,7,16,61,52,77,9.0,5,30,Urban,Software Engineer,118397,0 +5163,Male,56,Bachelors,0,64,40,89,93,0.0,0,16,Urban,Software Engineer,145124,0 +5164,Male,36,Diploma,16,86,88,93,52,8.0,6,23,Urban,Manager,94499,1 +5165,Male,40,Bachelors,12,22,68,97,48,9.0,7,77,Urban,ML Engineer,138665,1 +5166,Other,29,High School,19,8,75,64,55,9.0,3,87,Rural,Manager,25050,0 +5167,Male,52,Masters,14,88,13,74,82,1.0,0,1,Urban,Data Analyst,41261,0 +5168,Male,21,Bachelors,6,50,76,22,41,7.0,4,79,Urban,Manager,47054,0 +5169,Male,21,PhD,3,53,14,74,3,0.0,5,53,Urban,Data Analyst,130342,0 +5170,Female,53,Bachelors,13,24,56,61,72,0.0,6,41,Semi-Urban,Manager,73025,0 +5171,Male,44,Bachelors,11,89,20,75,28,6.0,3,26,Urban,Software Engineer,130539,0 +5172,Male,57,Bachelors,12,77,9,40,15,4.0,7,55,Semi-Urban,Software Engineer,74104,0 +5173,Male,22,Diploma,13,36,3,4,2,1.0,1,28,Rural,Manager,143467,0 +5174,Male,50,Masters,6,83,60,51,39,3.0,1,44,Urban,Data Analyst,106600,1 +5175,Male,38,Bachelors,4,98,16,30,25,6.0,5,14,Urban,Manager,77536,0 +5176,Female,48,Bachelors,3,7,70,1,32,0.0,2,49,Rural,Manager,38503,0 +5177,Female,35,Masters,14,30,33,83,56,6.0,1,91,Semi-Urban,Data Analyst,81368,0 +5178,Male,55,Diploma,1,37,67,2,69,2.0,1,30,Rural,Software Engineer,27023,0 +5179,Male,34,Bachelors,4,97,46,55,37,3.0,6,9,Urban,Data Analyst,103599,0 +5180,Female,22,Diploma,7,12,48,5,96,8.0,4,33,Urban,Manager,122635,0 +5181,Male,22,PhD,0,46,36,74,44,3.0,1,3,Urban,HR Executive,47041,0 +5182,Female,44,Masters,0,89,65,39,39,5.0,7,47,Urban,ML Engineer,69724,0 +5183,Male,31,Diploma,13,10,68,44,87,9.0,2,91,Urban,Software Engineer,120714,0 +5184,Female,39,High School,3,77,99,70,95,4.0,0,37,Urban,Software Engineer,120983,1 +5185,Female,21,Bachelors,11,59,64,59,20,4.0,1,60,Urban,HR Executive,90438,1 +5186,Female,48,Diploma,1,82,99,43,44,6.0,2,79,Urban,Data Analyst,58880,1 +5187,Female,47,Diploma,6,15,85,96,7,3.0,7,89,Urban,Data Analyst,85479,1 +5188,Male,32,Bachelors,10,46,11,87,45,6.0,1,99,Urban,ML Engineer,62609,1 +5189,Female,53,Bachelors,13,23,55,46,67,3.0,6,20,Urban,ML Engineer,51065,0 +5190,Male,59,Masters,7,15,14,41,22,5.0,4,61,Urban,HR Executive,87939,0 +5191,Male,37,Bachelors,15,6,78,20,95,2.0,3,34,Urban,Software Engineer,22597,0 +5192,Female,34,Bachelors,0,85,66,21,50,6.0,2,59,Semi-Urban,Manager,113934,0 +5193,Female,50,High School,18,58,35,38,56,1.0,3,59,Rural,HR Executive,30188,0 +5194,Female,46,Masters,19,71,41,29,26,8.0,5,57,Urban,ML Engineer,22615,0 +5195,Male,36,Diploma,2,18,50,97,39,6.0,1,95,Semi-Urban,Data Analyst,147754,1 +5196,Female,52,Diploma,2,60,93,34,33,5.0,6,60,Urban,Data Analyst,78041,1 +5197,Female,27,High School,8,55,59,10,54,0.0,7,9,Semi-Urban,Manager,87244,0 +5198,Male,44,Diploma,15,47,35,5,45,7.0,4,93,Semi-Urban,Software Engineer,84408,0 +5199,Male,21,Bachelors,11,77,50,3,25,9.0,5,47,Urban,ML Engineer,37821,0 +5200,Male,41,Bachelors,17,26,63,93,64,7.0,6,60,Rural,Manager,95027,1 +5201,Male,46,PhD,11,74,39,55,55,8.0,4,85,Semi-Urban,HR Executive,47171,1 +5202,Other,50,High School,15,43,45,26,89,3.0,2,23,Rural,Software Engineer,27787,0 +5203,Female,46,Bachelors,13,12,69,19,14,6.0,7,55,Urban,Manager,136587,0 +5204,Female,55,Bachelors,9,73,46,64,84,5.0,4,7,Rural,ML Engineer,48146,0 +5205,Other,50,Bachelors,11,92,32,60,58,9.0,6,94,Semi-Urban,Manager,147605,1 +5206,Male,58,Masters,0,88,33,31,67,7.0,3,47,Rural,Software Engineer,69203,0 +5207,Female,59,Bachelors,10,86,15,54,77,8.0,2,64,Urban,Data Analyst,142447,0 +5208,Male,43,Bachelors,9,27,62,31,64,1.0,1,5,Semi-Urban,Manager,121134,0 +5209,Female,56,High School,6,71,37,88,75,8.0,6,54,Urban,Manager,60437,1 +5210,Male,31,Bachelors,8,69,97,51,53,4.0,5,76,Urban,Manager,129147,1 +5211,Female,34,Bachelors,3,28,84,74,55,4.0,1,18,Semi-Urban,Data Analyst,148210,0 +5212,Male,32,Bachelors,13,19,15,31,95,6.0,0,59,Urban,HR Executive,47201,0 +5213,Male,50,High School,5,38,30,32,87,4.0,4,74,Urban,HR Executive,138948,0 +5214,Female,35,Bachelors,6,78,70,27,35,0.0,4,47,Semi-Urban,Manager,123092,0 +5215,Male,58,Diploma,11,75,94,52,65,5.0,6,72,Semi-Urban,Manager,67225,1 +5216,Female,45,Masters,14,84,76,13,28,3.0,2,59,Urban,HR Executive,40185,0 +5217,Male,23,Diploma,11,36,11,63,62,8.0,1,18,Rural,Manager,42636,0 +5218,Female,23,Diploma,4,96,99,5,41,3.0,6,93,Urban,ML Engineer,142006,1 +5219,Male,43,High School,1,36,12,94,77,9.0,1,18,Rural,Manager,28887,0 +5220,Male,30,PhD,17,65,67,40,37,6.0,4,55,Urban,HR Executive,25487,0 +5221,Male,46,Bachelors,11,62,47,90,51,2.0,4,78,Semi-Urban,Software Engineer,77590,1 +5222,Male,53,High School,10,48,65,7,12,0.0,0,29,Urban,Software Engineer,71531,0 +5223,Male,49,Masters,11,48,78,93,31,5.0,5,6,Urban,Data Analyst,114604,0 +5224,Male,21,Masters,13,33,91,48,69,3.0,7,16,Urban,ML Engineer,109541,0 +5225,Male,40,Bachelors,5,45,68,39,35,3.0,3,58,Urban,HR Executive,110822,0 +5226,Male,28,Bachelors,11,49,21,17,40,0.0,5,61,Urban,Manager,22428,0 +5227,Male,48,Masters,9,53,94,84,35,4.0,5,13,Urban,ML Engineer,110079,1 +5228,Female,51,Bachelors,0,93,62,39,73,6.0,5,26,Semi-Urban,Manager,67498,0 +5229,Male,35,High School,14,54,24,89,69,3.0,5,21,Urban,Data Analyst,134652,0 +5230,Male,32,Masters,11,38,11,7,59,9.0,1,97,Semi-Urban,HR Executive,96793,0 +5231,Female,55,Diploma,0,78,42,80,6,7.0,7,9,Urban,ML Engineer,122895,0 +5232,Male,25,Diploma,14,90,29,58,10,8.0,0,85,Urban,Data Analyst,135299,1 +5233,Female,21,Bachelors,5,68,32,44,90,3.0,1,90,Urban,HR Executive,81756,0 +5234,Male,50,Masters,19,37,10,9,56,2.0,5,32,Urban,Data Analyst,36717,0 +5235,Male,55,Masters,0,18,9,5,62,7.0,1,70,Urban,ML Engineer,28100,0 +5236,Male,23,High School,18,86,89,10,40,8.0,4,47,Semi-Urban,Manager,73416,0 +5237,Female,39,High School,15,96,22,57,21,6.0,5,30,Rural,ML Engineer,46100,0 +5238,Female,25,Diploma,1,71,76,3,31,6.0,5,80,Urban,ML Engineer,28823,0 +5239,Male,33,Diploma,9,76,43,26,31,2.0,2,17,Urban,Manager,71645,0 +5240,Male,25,Masters,9,58,48,63,98,3.0,4,29,Semi-Urban,Manager,117841,0 +5241,Other,25,Bachelors,13,52,98,46,67,1.0,1,34,Urban,Data Analyst,75428,0 +5242,Male,58,High School,7,77,85,28,35,2.0,4,68,Semi-Urban,HR Executive,135246,1 +5243,Male,24,Masters,12,32,79,0,71,6.0,0,31,Semi-Urban,HR Executive,65836,0 +5244,Female,34,Diploma,8,25,2,25,76,7.0,5,45,Urban,ML Engineer,125757,0 +5245,Female,36,Diploma,6,4,13,25,33,8.0,3,95,Rural,ML Engineer,57248,0 +5246,Male,21,Bachelors,18,19,48,3,74,8.0,1,59,Urban,Manager,105320,0 +5247,Female,30,Masters,12,26,22,89,15,9.0,0,58,Urban,HR Executive,94916,0 +5248,Female,59,Bachelors,3,32,60,10,52,3.0,6,0,Urban,ML Engineer,94863,0 +5249,Male,38,Masters,7,15,40,30,42,3.0,6,75,Urban,Software Engineer,120310,0 +5250,Male,36,Masters,13,62,70,26,71,4.0,1,42,Urban,Software Engineer,44831,0 +5251,Male,51,Bachelors,11,94,64,54,80,6.0,1,94,Rural,ML Engineer,42897,1 +5252,Other,32,Bachelors,12,54,26,86,49,0.0,6,53,Rural,Manager,101521,0 +5253,Female,36,Masters,11,75,24,86,97,3.0,3,10,Urban,Manager,110802,0 +5254,Male,44,PhD,10,97,67,65,70,1.0,6,10,Semi-Urban,HR Executive,30298,1 +5255,Female,41,PhD,4,73,63,11,27,0.0,2,25,Semi-Urban,Software Engineer,42033,0 +5256,Male,36,Bachelors,12,65,1,62,40,2.0,6,56,Urban,ML Engineer,104992,0 +5257,Male,45,Bachelors,8,83,92,29,81,1.0,3,1,Urban,ML Engineer,45369,0 +5258,Male,41,Masters,9,39,7,74,10,2.0,5,61,Urban,HR Executive,37319,0 +5259,Male,24,Bachelors,3,99,90,52,35,2.0,1,53,Rural,ML Engineer,27800,1 +5260,Female,58,Masters,19,79,42,74,28,5.0,2,97,Urban,HR Executive,58438,1 +5261,Male,44,Bachelors,15,78,11,76,53,3.0,3,3,Urban,ML Engineer,82818,0 +5262,Female,26,Masters,11,46,97,79,89,9.0,1,63,Semi-Urban,HR Executive,41607,1 +5263,Male,27,Bachelors,17,38,57,92,32,8.0,0,7,Urban,Software Engineer,117479,0 +5264,Male,24,Bachelors,13,95,8,1,76,9.0,2,93,Rural,Manager,132728,0 +5265,Other,56,PhD,16,52,47,42,65,5.0,7,38,Urban,Data Analyst,138830,0 +5266,Male,51,High School,19,8,30,35,61,4.0,1,98,Semi-Urban,HR Executive,66374,0 +5267,Male,45,Diploma,9,3,39,82,76,4.0,2,61,Urban,Data Analyst,102368,0 +5268,Male,34,Masters,12,47,60,44,88,0.0,3,57,Rural,Software Engineer,36180,0 +5269,Female,56,Diploma,18,28,24,14,9,9.0,4,24,Urban,HR Executive,147879,0 +5270,Male,25,Bachelors,10,54,92,45,49,1.0,7,88,Urban,ML Engineer,138808,1 +5271,Male,32,Masters,8,81,76,37,37,7.0,3,22,Urban,HR Executive,112037,0 +5272,Male,24,Diploma,1,50,91,27,85,2.0,6,45,Urban,ML Engineer,58723,0 +5273,Male,50,Bachelors,18,89,56,85,35,9.0,0,98,Urban,HR Executive,31562,1 +5274,Female,49,High School,16,26,76,90,62,8.0,3,35,Urban,ML Engineer,142959,0 +5275,Male,49,High School,18,41,11,38,94,3.0,5,23,Semi-Urban,Manager,115421,0 +5276,Male,42,Bachelors,14,93,45,74,10,9.0,1,10,Semi-Urban,HR Executive,54002,0 +5277,Male,56,Bachelors,16,55,58,61,18,5.0,2,30,Rural,Software Engineer,43723,0 +5278,Male,46,Bachelors,6,41,91,83,86,2.0,3,4,Urban,Software Engineer,86889,0 +5279,Female,42,Masters,18,26,73,67,36,6.0,5,46,Rural,Software Engineer,69103,0 +5280,Male,21,Diploma,7,33,75,35,19,4.0,5,5,Rural,Data Analyst,74236,0 +5281,Other,53,High School,17,76,50,66,70,1.0,5,45,Semi-Urban,Manager,110723,0 +5282,Male,59,High School,9,43,60,62,78,9.0,1,10,Urban,Manager,128485,0 +5283,Male,55,Bachelors,15,55,46,65,4,8.0,2,10,Urban,Data Analyst,133767,0 +5284,Female,46,Bachelors,18,28,97,96,10,4.0,0,59,Urban,HR Executive,138315,1 +5285,Male,53,High School,19,31,71,40,53,6.0,0,59,Urban,Data Analyst,49840,0 +5286,Female,47,Bachelors,3,0,10,59,39,3.0,4,97,Urban,Manager,126951,0 +5287,Other,29,Masters,17,99,24,0,76,8.0,6,69,Urban,Data Analyst,35788,0 +5288,Male,28,Bachelors,2,60,12,26,82,7.0,7,8,Urban,Data Analyst,145240,0 +5289,Male,23,Bachelors,17,84,58,52,40,0.0,3,3,Rural,Manager,114303,0 +5290,Female,46,Diploma,1,94,93,42,88,2.0,1,28,Semi-Urban,Data Analyst,47316,1 +5291,Male,28,Masters,16,43,3,53,96,2.0,5,81,Urban,Software Engineer,33942,0 +5292,Male,35,Masters,7,54,1,68,2,0.0,7,99,Rural,ML Engineer,129388,0 +5293,Male,28,High School,8,83,12,58,21,1.0,0,57,Rural,Manager,142794,0 +5294,Male,22,Bachelors,10,96,29,32,18,8.0,3,79,Urban,Software Engineer,22909,1 +5295,Female,50,Masters,5,81,13,12,29,3.0,2,88,Semi-Urban,HR Executive,123825,0 +5296,Male,57,Diploma,6,36,0,47,39,4.0,2,31,Semi-Urban,Manager,55857,0 +5297,Male,47,Bachelors,19,13,33,81,84,1.0,0,1,Rural,Manager,75895,0 +5298,Female,47,Bachelors,18,23,32,66,2,2.0,0,1,Rural,HR Executive,104685,0 +5299,Male,26,Bachelors,3,57,27,16,86,2.0,7,38,Urban,HR Executive,141262,0 +5300,Male,29,Bachelors,12,93,24,51,95,8.0,1,35,Rural,Manager,20065,0 +5301,Female,49,PhD,18,86,13,14,32,0.0,6,13,Rural,HR Executive,29266,0 +5302,Male,39,High School,16,46,70,31,13,1.0,5,6,Urban,HR Executive,129377,0 +5303,Female,44,Bachelors,10,35,26,37,27,5.0,7,90,Rural,Data Analyst,60127,0 +5304,Female,40,Bachelors,8,82,33,93,41,8.0,2,75,Urban,HR Executive,93359,1 +5305,Male,52,Bachelors,15,64,83,28,14,4.0,3,42,Urban,ML Engineer,35417,0 +5306,Male,55,Bachelors,12,79,24,36,46,6.0,0,63,Rural,ML Engineer,149336,0 +5307,Male,24,Masters,10,69,75,99,63,7.0,5,67,Semi-Urban,Data Analyst,79343,1 +5308,Male,33,Bachelors,15,23,92,82,25,6.0,5,40,Urban,ML Engineer,144602,1 +5309,Female,25,Bachelors,5,29,19,7,49,7.0,3,18,Rural,ML Engineer,65761,0 +5310,Female,57,Masters,19,9,6,37,68,4.0,6,80,Urban,Data Analyst,62850,0 +5311,Male,31,Bachelors,14,61,69,76,74,7.0,2,91,Urban,Manager,109845,1 +5312,Female,36,Diploma,19,86,55,87,0,0.0,4,61,Rural,HR Executive,93005,1 +5313,Female,47,Diploma,15,75,31,55,54,4.0,5,95,Urban,Data Analyst,131200,1 +5314,Other,39,Masters,16,69,42,34,22,9.0,2,49,Urban,Software Engineer,91400,0 +5315,Male,46,Bachelors,13,57,64,68,22,2.0,0,90,Urban,ML Engineer,53301,1 +5316,Male,55,Diploma,6,90,17,87,56,1.0,3,21,Rural,HR Executive,106656,0 +5317,Male,23,Bachelors,0,86,37,84,60,3.0,2,72,Urban,ML Engineer,45651,1 +5318,Other,49,Diploma,16,52,92,39,3,2.0,6,29,Semi-Urban,Manager,98087,0 +5319,Male,41,Bachelors,1,30,5,54,73,5.0,0,89,Semi-Urban,Manager,137200,0 +5320,Male,52,Masters,14,83,72,93,26,5.0,7,89,Urban,Manager,138965,1 +5321,Male,42,Diploma,11,0,40,47,72,9.0,2,42,Urban,Data Analyst,45943,0 +5322,Male,24,PhD,18,23,45,48,92,3.0,3,97,Rural,Software Engineer,136776,0 +5323,Male,36,Diploma,0,41,36,76,3,0.0,1,74,Rural,Manager,76322,0 +5324,Other,21,Diploma,16,46,45,53,73,8.0,7,11,Urban,ML Engineer,60813,0 +5325,Male,54,Diploma,11,93,13,6,56,5.0,5,81,Semi-Urban,HR Executive,66676,0 +5326,Male,48,Diploma,1,4,18,51,77,1.0,5,93,Urban,HR Executive,23086,0 +5327,Male,31,Bachelors,13,12,75,72,79,3.0,4,1,Urban,ML Engineer,82287,0 +5328,Male,23,Diploma,8,38,25,17,35,3.0,7,44,Urban,Software Engineer,72208,0 +5329,Male,57,Bachelors,7,83,41,1,88,0.0,3,10,Urban,ML Engineer,62690,0 +5330,Male,30,Masters,13,94,86,42,42,8.0,2,98,Urban,HR Executive,92652,1 +5331,Male,36,Diploma,3,32,22,36,82,8.0,5,15,Semi-Urban,Manager,93763,0 +5332,Male,48,Bachelors,17,65,72,62,91,9.0,4,63,Rural,Manager,48067,1 +5333,Male,49,Masters,4,46,61,58,45,2.0,2,35,Rural,Software Engineer,117238,0 +5334,Male,42,Bachelors,3,2,72,36,58,4.0,1,47,Urban,Software Engineer,110875,0 +5335,Other,29,Bachelors,12,12,95,81,12,2.0,6,76,Urban,Manager,48809,1 +5336,Female,58,Bachelors,1,48,4,35,69,3.0,4,24,Semi-Urban,Data Analyst,62728,0 +5337,Male,32,High School,12,5,68,40,49,2.0,0,65,Semi-Urban,HR Executive,61496,0 +5338,Male,48,Masters,15,93,44,87,20,0.0,4,29,Urban,Software Engineer,31438,1 +5339,Female,25,PhD,12,34,7,22,16,6.0,1,22,Rural,Manager,64666,0 +5340,Male,39,Bachelors,10,35,0,77,25,0.0,5,60,Urban,HR Executive,23486,0 +5341,Female,32,Bachelors,1,5,92,97,2,9.0,6,39,Rural,HR Executive,85551,0 +5342,Female,32,Bachelors,6,62,49,95,26,9.0,5,67,Urban,HR Executive,144375,1 +5343,Male,21,Masters,1,43,7,24,68,6.0,7,67,Urban,Data Analyst,62186,0 +5344,Male,22,Bachelors,8,68,10,81,24,3.0,7,26,Rural,HR Executive,85173,0 +5345,Other,48,Masters,14,28,23,38,34,3.0,2,14,Urban,ML Engineer,110006,0 +5346,Male,39,Bachelors,7,27,69,67,92,7.0,3,19,Urban,ML Engineer,118199,0 +5347,Male,51,Bachelors,11,43,31,18,70,7.0,6,4,Urban,Software Engineer,109928,0 +5348,Male,30,Diploma,4,96,71,58,87,9.0,6,80,Urban,ML Engineer,80873,1 +5349,Male,21,Bachelors,3,91,28,92,69,2.0,5,79,Semi-Urban,HR Executive,93034,1 +5350,Female,32,Masters,5,36,10,61,73,7.0,2,62,Urban,HR Executive,119695,0 +5351,Female,52,Bachelors,2,84,63,5,84,0.0,1,92,Urban,ML Engineer,25060,1 +5352,Other,33,Diploma,7,33,59,11,47,6.0,7,22,Semi-Urban,Data Analyst,37144,0 +5353,Male,44,Bachelors,6,66,16,96,11,5.0,6,25,Urban,Software Engineer,85234,0 +5354,Male,50,Bachelors,11,52,98,13,48,3.0,1,32,Urban,HR Executive,136489,0 +5355,Male,26,Bachelors,11,88,2,75,31,7.0,7,74,Urban,Data Analyst,144033,1 +5356,Male,50,Diploma,15,49,88,35,32,6.0,2,23,Semi-Urban,Software Engineer,71624,0 +5357,Male,55,High School,12,35,53,75,6,6.0,2,53,Urban,Manager,22271,0 +5358,Other,57,Diploma,6,85,36,51,5,7.0,4,8,Urban,HR Executive,62844,0 +5359,Female,48,Masters,3,27,16,62,56,7.0,6,90,Urban,ML Engineer,78952,0 +5360,Male,52,High School,8,32,6,19,95,6.0,6,49,Urban,Data Analyst,55678,0 +5361,Female,57,Bachelors,4,81,76,92,81,4.0,5,62,Urban,ML Engineer,50055,1 +5362,Male,25,Masters,1,25,98,56,41,5.0,6,13,Rural,Manager,118258,0 +5363,Male,44,Masters,16,60,97,10,56,6.0,6,84,Urban,Data Analyst,83100,1 +5364,Female,25,Bachelors,10,86,3,39,38,2.0,6,54,Urban,ML Engineer,108746,0 +5365,Male,52,Bachelors,8,76,4,8,43,4.0,2,58,Rural,Data Analyst,68600,0 +5366,Other,38,Diploma,13,52,57,14,88,1.0,6,81,Rural,ML Engineer,21375,0 +5367,Female,51,Masters,13,43,81,87,6,4.0,5,77,Urban,Data Analyst,44395,1 +5368,Male,22,Bachelors,15,56,73,21,76,7.0,5,88,Urban,Software Engineer,65689,1 +5369,Female,55,Diploma,13,64,86,72,47,6.0,4,1,Urban,Data Analyst,148873,0 +5370,Male,47,Diploma,7,41,73,54,63,8.0,1,71,Urban,Manager,31271,1 +5371,Male,48,Bachelors,8,46,2,88,15,5.0,0,47,Urban,HR Executive,111776,0 +5372,Male,32,High School,15,23,11,73,81,8.0,2,72,Urban,HR Executive,135344,0 +5373,Male,22,Diploma,16,43,14,11,97,5.0,4,55,Urban,Data Analyst,51622,0 +5374,Female,27,High School,0,80,99,53,31,4.0,1,47,Rural,Software Engineer,41617,1 +5375,Male,40,High School,12,86,15,46,51,3.0,3,72,Urban,Manager,141354,0 +5376,Female,22,High School,15,33,38,91,60,9.0,7,63,Semi-Urban,Software Engineer,91724,0 +5377,Male,30,Bachelors,10,65,1,34,6,6.0,6,50,Urban,Manager,107537,0 +5378,Male,33,Bachelors,11,51,72,55,73,8.0,2,78,Urban,Software Engineer,146414,1 +5379,Female,36,Diploma,14,93,92,56,16,7.0,5,46,Semi-Urban,Manager,149024,1 +5380,Male,48,High School,13,53,38,80,58,1.0,1,63,Urban,Software Engineer,80344,0 +5381,Male,49,Bachelors,5,1,53,84,82,7.0,7,15,Semi-Urban,HR Executive,66903,0 +5382,Male,31,Diploma,6,18,66,78,64,6.0,1,74,Rural,Software Engineer,37380,1 +5383,Male,36,Bachelors,13,84,57,13,13,4.0,1,7,Semi-Urban,Software Engineer,49722,0 +5384,Male,28,Diploma,15,71,87,48,86,5.0,7,99,Semi-Urban,Software Engineer,101943,1 +5385,Female,41,Masters,12,85,52,11,10,4.0,2,6,Semi-Urban,Software Engineer,34609,0 +5386,Male,26,Diploma,7,34,81,89,80,4.0,0,47,Urban,HR Executive,89279,1 +5387,Male,31,Masters,18,91,93,94,11,1.0,5,36,Urban,Data Analyst,80244,1 +5388,Other,46,Masters,9,21,24,75,49,9.0,2,97,Rural,Software Engineer,73095,0 +5389,Male,32,Bachelors,2,35,27,66,14,0.0,5,95,Urban,Data Analyst,119290,0 +5390,Female,22,Bachelors,12,58,38,26,67,2.0,1,15,Semi-Urban,HR Executive,30299,0 +5391,Male,40,Masters,13,73,82,55,14,7.0,2,44,Semi-Urban,Data Analyst,93929,1 +5392,Male,59,Diploma,9,26,28,23,12,0.0,7,4,Rural,Data Analyst,149941,0 +5393,Female,48,Masters,11,58,57,61,4,6.0,2,5,Urban,Software Engineer,115277,0 +5394,Male,59,Diploma,11,68,39,83,85,6.0,1,64,Rural,Data Analyst,120815,1 +5395,Female,27,Bachelors,1,50,48,11,53,1.0,6,21,Urban,Software Engineer,100137,0 +5396,Male,36,High School,6,91,36,87,83,7.0,3,41,Urban,Manager,131795,1 +5397,Male,33,Masters,3,10,10,33,98,8.0,4,42,Semi-Urban,Manager,34684,0 +5398,Male,49,Diploma,14,89,83,12,47,2.0,3,58,Urban,Manager,65148,1 +5399,Male,42,Masters,4,79,20,88,5,0.0,5,17,Rural,Data Analyst,50404,0 +5400,Female,58,Bachelors,19,9,23,47,83,1.0,4,16,Urban,Software Engineer,129937,0 +5401,Male,56,Diploma,13,61,18,72,39,5.0,5,47,Semi-Urban,Manager,101536,0 +5402,Other,22,PhD,3,26,38,57,44,7.0,1,68,Urban,Software Engineer,117446,0 +5403,Other,56,Bachelors,15,73,69,1,10,4.0,3,5,Urban,Software Engineer,69532,0 +5404,Male,34,Masters,14,36,17,12,16,8.0,2,36,Rural,Manager,42560,0 +5405,Male,48,Bachelors,15,53,6,67,57,8.0,1,81,Semi-Urban,Software Engineer,56794,0 +5406,Female,33,Bachelors,9,10,52,35,80,6.0,3,18,Semi-Urban,Data Analyst,38800,0 +5407,Other,24,Bachelors,19,15,88,55,65,8.0,2,2,Urban,ML Engineer,96644,0 +5408,Male,36,Bachelors,3,7,82,18,55,0.0,2,44,Rural,ML Engineer,86593,0 +5409,Male,22,Bachelors,4,18,29,62,46,3.0,1,27,Urban,ML Engineer,119960,0 +5410,Male,55,Masters,9,42,35,71,92,5.0,6,76,Urban,Manager,149597,0 +5411,Female,40,Bachelors,14,15,42,19,19,2.0,0,84,Semi-Urban,HR Executive,44555,0 +5412,Male,38,Bachelors,11,24,84,17,91,6.0,0,62,Rural,ML Engineer,33105,0 +5413,Female,28,Masters,18,27,42,89,52,3.0,7,33,Semi-Urban,Data Analyst,73470,0 +5414,Male,43,Bachelors,9,63,89,89,29,4.0,2,58,Urban,ML Engineer,71993,1 +5415,Male,43,High School,0,63,49,52,73,9.0,4,60,Urban,HR Executive,22332,0 +5416,Male,45,High School,1,31,21,64,65,0.0,0,99,Urban,Software Engineer,51136,0 +5417,Male,56,High School,4,2,4,87,24,7.0,3,49,Urban,ML Engineer,50058,0 +5418,Male,23,Diploma,12,77,63,5,27,5.0,0,54,Urban,HR Executive,80041,0 +5419,Male,38,Diploma,7,27,59,69,60,9.0,0,63,Urban,Software Engineer,65078,0 +5420,Male,49,Masters,4,88,17,43,57,0.0,5,88,Urban,HR Executive,30349,1 +5421,Male,44,Diploma,7,73,99,86,56,2.0,3,6,Semi-Urban,Manager,70710,1 +5422,Male,49,Masters,9,54,61,58,50,1.0,5,67,Urban,ML Engineer,84345,1 +5423,Other,32,High School,2,47,79,63,76,4.0,1,51,Urban,Data Analyst,100655,0 +5424,Male,53,Bachelors,13,53,36,46,16,7.0,3,92,Urban,Manager,72944,0 +5425,Male,33,High School,13,52,7,79,31,8.0,5,88,Urban,ML Engineer,101199,0 +5426,Male,34,Bachelors,18,11,83,22,16,7.0,3,30,Urban,HR Executive,52313,0 +5427,Other,54,High School,18,51,3,22,84,7.0,0,82,Rural,Manager,125285,0 +5428,Male,46,Bachelors,9,0,66,67,65,7.0,5,34,Semi-Urban,HR Executive,90263,0 +5429,Female,28,PhD,2,69,46,97,65,8.0,7,64,Urban,HR Executive,118022,1 +5430,Female,48,Masters,1,27,73,6,35,2.0,0,86,Urban,HR Executive,106900,0 +5431,Female,58,High School,1,62,44,3,82,8.0,4,21,Urban,Software Engineer,35903,0 +5432,Male,27,Masters,0,38,73,73,93,4.0,2,76,Semi-Urban,Manager,48136,1 +5433,Female,49,Masters,18,89,34,96,75,2.0,2,46,Rural,Software Engineer,42667,1 +5434,Male,49,PhD,1,4,10,90,96,4.0,3,26,Semi-Urban,HR Executive,121923,0 +5435,Male,50,Bachelors,8,43,89,71,92,3.0,3,89,Rural,Manager,40944,1 +5436,Female,52,Masters,5,47,63,21,4,1.0,1,83,Semi-Urban,ML Engineer,129157,0 +5437,Male,39,Bachelors,12,95,31,3,87,1.0,0,35,Urban,Manager,116651,0 +5438,Female,26,High School,6,89,78,0,20,3.0,4,33,Rural,Manager,118708,0 +5439,Male,58,High School,12,36,41,60,77,0.0,0,30,Urban,HR Executive,97341,0 +5440,Female,27,Bachelors,19,30,73,59,36,7.0,6,47,Rural,Data Analyst,104036,0 +5441,Male,38,Bachelors,13,71,8,62,73,7.0,7,78,Urban,Manager,54954,0 +5442,Male,51,Masters,13,95,40,85,29,5.0,6,25,Urban,HR Executive,121395,1 +5443,Male,25,Bachelors,3,42,6,11,27,2.0,0,23,Urban,Data Analyst,49724,0 +5444,Other,26,Bachelors,9,43,61,49,25,9.0,6,56,Urban,ML Engineer,108978,0 +5445,Male,39,Bachelors,5,4,84,64,71,7.0,5,11,Urban,ML Engineer,76885,0 +5446,Male,56,Bachelors,0,62,42,58,57,1.0,3,76,Semi-Urban,ML Engineer,122412,1 +5447,Male,34,Masters,17,36,16,75,13,9.0,5,89,Urban,HR Executive,35604,0 +5448,Female,30,Bachelors,7,10,67,2,91,4.0,7,7,Urban,HR Executive,149261,0 +5449,Male,48,PhD,8,2,14,44,4,2.0,1,42,Semi-Urban,Manager,77929,0 +5450,Male,30,High School,12,14,47,3,67,7.0,6,85,Semi-Urban,ML Engineer,111702,0 +5451,Male,41,Bachelors,9,17,78,94,33,1.0,6,50,Urban,HR Executive,137971,1 +5452,Male,23,Masters,12,24,23,91,19,3.0,1,68,Urban,Manager,25566,0 +5453,Male,32,Masters,13,14,36,82,28,7.0,5,96,Urban,Software Engineer,23632,0 +5454,Male,25,Bachelors,7,79,13,11,52,9.0,1,72,Urban,Manager,105250,0 +5455,Female,46,Bachelors,18,56,98,8,97,7.0,2,57,Urban,ML Engineer,96104,0 +5456,Male,47,Bachelors,17,42,52,56,66,5.0,0,47,Rural,ML Engineer,102686,0 +5457,Male,30,Bachelors,5,45,67,16,2,9.0,4,90,Urban,Manager,139196,0 +5458,Male,58,Bachelors,3,64,86,96,52,5.0,4,64,Urban,Data Analyst,72146,1 +5459,Other,33,High School,4,76,26,98,85,5.0,1,39,Urban,Manager,36726,0 +5460,Other,46,Bachelors,10,50,99,78,3,4.0,4,36,Semi-Urban,Data Analyst,50130,1 +5461,Female,47,Bachelors,12,98,91,36,66,6.0,0,23,Semi-Urban,ML Engineer,89780,1 +5462,Male,28,Bachelors,7,91,74,91,95,4.0,5,17,Urban,HR Executive,149922,1 +5463,Male,43,High School,0,48,34,91,59,0.0,5,36,Semi-Urban,Manager,42772,0 +5464,Male,41,Bachelors,12,21,40,98,3,9.0,4,32,Rural,HR Executive,51286,0 +5465,Male,21,Bachelors,18,66,65,42,13,8.0,4,3,Urban,HR Executive,136968,0 +5466,Male,22,Bachelors,19,22,68,84,35,3.0,7,15,Rural,Manager,146671,0 +5467,Female,45,Bachelors,0,74,13,55,85,0.0,4,52,Urban,Manager,42782,0 +5468,Female,32,High School,4,34,63,38,14,0.0,2,89,Urban,HR Executive,97499,0 +5469,Female,57,Diploma,11,14,40,94,22,0.0,1,93,Semi-Urban,Manager,86620,1 +5470,Male,36,Bachelors,12,0,7,72,14,5.0,0,38,Semi-Urban,Manager,77186,0 +5471,Female,32,Masters,5,60,49,80,27,0.0,3,0,Urban,Manager,120206,0 +5472,Male,32,Bachelors,19,94,43,1,49,4.0,0,10,Semi-Urban,Data Analyst,140174,0 +5473,Male,27,High School,5,62,10,5,99,3.0,4,39,Rural,ML Engineer,113556,0 +5474,Female,58,Bachelors,2,0,79,33,42,0.0,5,46,Urban,ML Engineer,134794,0 +5475,Male,29,Masters,1,82,11,5,50,0.0,5,44,Rural,HR Executive,23167,0 +5476,Male,46,Masters,0,53,91,74,48,6.0,5,34,Urban,HR Executive,37023,1 +5477,Male,58,Bachelors,10,54,67,5,89,8.0,6,72,Rural,Manager,57397,0 +5478,Female,36,High School,9,36,70,78,51,4.0,1,4,Urban,Data Analyst,115675,0 +5479,Female,37,Diploma,17,12,82,64,14,2.0,5,81,Rural,Manager,50979,0 +5480,Male,42,Masters,3,98,22,38,5,6.0,5,1,Urban,Software Engineer,28800,0 +5481,Female,57,Masters,16,34,84,84,92,8.0,3,78,Urban,HR Executive,40946,1 +5482,Male,59,Bachelors,19,46,34,24,7,9.0,4,65,Urban,HR Executive,23590,0 +5483,Male,22,High School,6,92,12,41,96,0.0,6,17,Rural,HR Executive,107512,0 +5484,Female,59,Bachelors,4,63,76,15,67,3.0,3,25,Urban,Manager,60961,0 +5485,Female,39,High School,18,49,78,91,92,3.0,1,8,Urban,Data Analyst,125594,0 +5486,Other,43,Bachelors,17,49,32,95,16,0.0,6,85,Urban,HR Executive,33424,1 +5487,Male,58,Bachelors,14,64,73,37,26,3.0,2,85,Rural,Software Engineer,118292,1 +5488,Female,23,Diploma,9,62,68,54,71,6.0,7,24,Urban,Software Engineer,21451,0 +5489,Female,42,Masters,17,36,92,63,69,9.0,0,42,Urban,Data Analyst,91180,0 +5490,Female,28,Diploma,12,44,11,72,47,7.0,3,52,Urban,HR Executive,111869,0 +5491,Male,58,Masters,7,52,54,99,92,4.0,5,49,Urban,HR Executive,64557,1 +5492,Female,38,Masters,17,32,97,8,86,0.0,5,4,Urban,Data Analyst,85915,0 +5493,Male,49,Bachelors,6,70,54,41,10,5.0,3,98,Urban,Software Engineer,49609,1 +5494,Male,49,High School,8,49,19,1,94,0.0,0,98,Semi-Urban,Data Analyst,119551,0 +5495,Male,51,Bachelors,17,3,6,50,7,5.0,1,61,Rural,Data Analyst,114586,0 +5496,Male,55,Bachelors,6,35,69,15,20,9.0,5,60,Rural,Software Engineer,111800,0 +5497,Male,51,Diploma,14,59,41,33,16,8.0,5,96,Rural,HR Executive,67647,0 +5498,Female,57,Diploma,9,36,63,37,48,6.0,2,74,Urban,HR Executive,135519,0 +5499,Male,49,Diploma,16,25,66,52,14,8.0,1,97,Urban,Manager,65948,1 +5500,Female,58,Bachelors,6,67,76,12,15,3.0,5,50,Urban,ML Engineer,56095,0 +5501,Male,38,High School,7,98,38,94,2,6.0,2,94,Semi-Urban,ML Engineer,145080,1 +5502,Male,48,Diploma,2,57,27,84,16,9.0,7,15,Semi-Urban,HR Executive,115780,0 +5503,Male,46,Bachelors,3,59,48,25,88,4.0,5,3,Urban,Manager,96877,0 +5504,Male,58,PhD,15,6,0,33,56,1.0,6,6,Urban,HR Executive,84540,0 +5505,Male,58,Masters,7,65,2,58,36,1.0,2,99,Urban,HR Executive,35167,0 +5506,Male,34,Bachelors,7,0,0,23,36,7.0,0,26,Semi-Urban,HR Executive,82884,0 +5507,Male,58,High School,9,6,81,73,31,2.0,0,60,Urban,Data Analyst,27520,0 +5508,Male,58,Bachelors,9,92,19,42,99,6.0,4,59,Urban,Software Engineer,148268,0 +5509,Male,50,Bachelors,4,47,45,32,13,2.0,5,19,Semi-Urban,ML Engineer,23608,0 +5510,Male,47,Bachelors,3,10,6,30,3,7.0,7,30,Urban,ML Engineer,87351,0 +5511,Male,34,Bachelors,12,38,80,38,52,3.0,4,1,Semi-Urban,Data Analyst,127539,0 +5512,Female,30,Bachelors,14,41,61,25,57,0.0,2,78,Urban,Data Analyst,107877,0 +5513,Female,53,Bachelors,1,22,2,60,12,9.0,6,75,Semi-Urban,Software Engineer,144763,0 +5514,Female,50,High School,16,79,91,33,23,6.0,4,14,Urban,Manager,136306,0 +5515,Male,21,Bachelors,16,87,72,29,55,2.0,2,20,Rural,Software Engineer,98582,0 +5516,Female,39,Bachelors,7,30,91,46,8,4.0,6,51,Rural,ML Engineer,135409,0 +5517,Female,39,Bachelors,8,49,41,89,41,8.0,4,50,Semi-Urban,ML Engineer,100218,0 +5518,Female,25,Bachelors,15,51,64,32,80,4.0,4,63,Urban,Manager,117881,0 +5519,Male,45,PhD,14,61,96,50,2,7.0,0,41,Rural,ML Engineer,76617,1 +5520,Female,53,Diploma,6,27,14,52,32,5.0,0,61,Urban,ML Engineer,39984,0 +5521,Female,41,Bachelors,16,43,34,83,23,6.0,7,2,Semi-Urban,Data Analyst,46390,0 +5522,Male,51,Masters,19,49,64,62,72,7.0,7,51,Urban,Software Engineer,22411,0 +5523,Female,34,Bachelors,17,29,62,94,43,3.0,1,6,Urban,Manager,36099,0 +5524,Male,51,Bachelors,8,92,77,19,63,1.0,7,53,Urban,Software Engineer,118581,1 +5525,Male,36,High School,18,4,79,9,4,6.0,4,84,Urban,Manager,101613,0 +5526,Male,45,Bachelors,3,97,8,75,31,2.0,1,44,Rural,ML Engineer,136562,0 +5527,Female,25,Masters,12,56,60,22,14,7.0,4,67,Urban,Software Engineer,134072,0 +5528,Male,45,High School,8,96,26,97,88,2.0,0,89,Urban,Data Analyst,142433,1 +5529,Male,51,High School,13,42,20,91,85,5.0,2,75,Urban,Data Analyst,149039,0 +5530,Male,35,Bachelors,10,73,41,1,91,9.0,0,0,Semi-Urban,Data Analyst,135528,0 +5531,Male,30,Diploma,12,95,77,83,88,2.0,0,56,Urban,Data Analyst,126424,1 +5532,Male,59,Masters,15,22,48,99,27,1.0,3,89,Urban,Software Engineer,40173,1 +5533,Female,32,Bachelors,13,29,57,0,55,8.0,6,70,Rural,Manager,21589,0 +5534,Female,34,Masters,13,39,43,41,42,0.0,0,86,Urban,Manager,21957,0 +5535,Male,46,Bachelors,12,60,66,47,32,7.0,2,95,Urban,Data Analyst,115595,1 +5536,Male,27,High School,10,87,77,61,19,2.0,1,59,Semi-Urban,ML Engineer,83397,1 +5537,Male,23,Bachelors,1,26,56,17,31,4.0,1,89,Urban,HR Executive,102405,0 +5538,Female,46,Masters,2,8,87,9,34,4.0,6,66,Urban,Manager,137146,0 +5539,Male,22,Diploma,12,89,87,79,49,5.0,2,57,Urban,HR Executive,23308,1 +5540,Male,52,Masters,11,90,56,56,36,2.0,6,0,Urban,Software Engineer,71314,0 +5541,Male,59,Masters,15,60,96,59,21,2.0,4,74,Urban,Software Engineer,132415,1 +5542,Female,33,Bachelors,19,7,17,33,29,0.0,7,29,Urban,Manager,42789,0 +5543,Female,22,PhD,11,77,53,93,79,4.0,7,20,Semi-Urban,Manager,122493,1 +5544,Female,31,Masters,17,5,23,29,8,4.0,3,19,Rural,ML Engineer,120038,0 +5545,Female,57,Diploma,18,25,4,20,13,9.0,2,30,Semi-Urban,Software Engineer,76620,0 +5546,Male,56,Masters,0,38,82,61,22,2.0,5,73,Semi-Urban,Manager,51008,1 +5547,Male,38,PhD,8,9,44,51,23,9.0,7,48,Urban,ML Engineer,129532,0 +5548,Male,35,High School,9,31,88,99,85,8.0,1,65,Urban,HR Executive,60525,1 +5549,Male,43,Masters,18,23,46,67,36,7.0,4,25,Urban,HR Executive,30077,0 +5550,Male,34,Masters,14,4,1,80,89,4.0,6,26,Semi-Urban,Data Analyst,70956,0 +5551,Male,50,Bachelors,6,56,99,92,56,6.0,2,94,Urban,HR Executive,133699,1 +5552,Male,29,Bachelors,0,56,24,36,34,1.0,1,22,Urban,ML Engineer,26006,0 +5553,Female,54,Diploma,9,8,63,92,22,7.0,7,40,Urban,Software Engineer,28763,0 +5554,Female,45,Masters,2,43,29,68,95,6.0,4,63,Rural,Manager,23917,0 +5555,Female,43,High School,6,19,99,71,81,7.0,0,85,Urban,ML Engineer,63707,1 +5556,Female,31,PhD,9,75,66,3,19,6.0,6,92,Urban,Data Analyst,40866,0 +5557,Male,26,Masters,16,78,15,82,7,5.0,6,49,Urban,Data Analyst,65689,0 +5558,Female,31,PhD,18,48,18,17,52,6.0,2,48,Semi-Urban,Manager,28745,0 +5559,Male,32,Bachelors,13,96,5,94,12,5.0,1,12,Rural,Data Analyst,116832,0 +5560,Female,52,Masters,16,83,58,24,93,6.0,2,55,Rural,Software Engineer,74728,0 +5561,Male,32,Bachelors,11,40,4,56,47,2.0,6,20,Rural,HR Executive,147361,0 +5562,Other,37,Diploma,10,6,71,80,0,6.0,4,94,Urban,HR Executive,120483,1 +5563,Male,47,Diploma,1,52,63,57,6,3.0,3,34,Rural,HR Executive,149330,0 +5564,Male,50,Masters,2,12,17,67,93,3.0,5,54,Semi-Urban,HR Executive,64128,0 +5565,Female,29,Bachelors,6,21,97,71,98,3.0,7,5,Rural,HR Executive,20241,0 +5566,Male,22,Bachelors,9,0,34,65,67,9.0,7,50,Rural,Software Engineer,77951,0 +5567,Female,45,High School,19,66,24,60,77,9.0,6,42,Rural,Manager,104745,0 +5568,Female,42,Bachelors,5,98,89,83,66,8.0,2,90,Semi-Urban,Data Analyst,92407,1 +5569,Female,37,Bachelors,18,7,42,44,62,1.0,4,8,Urban,HR Executive,80172,0 +5570,Other,48,Bachelors,12,95,44,42,57,3.0,6,26,Urban,Manager,20579,0 +5571,Other,56,High School,15,19,6,91,18,2.0,6,50,Semi-Urban,ML Engineer,46343,0 +5572,Male,58,High School,7,77,20,24,30,7.0,7,12,Semi-Urban,ML Engineer,140379,0 +5573,Female,51,Diploma,17,80,90,52,62,6.0,4,44,Urban,HR Executive,123170,1 +5574,Female,32,Bachelors,1,37,68,92,70,9.0,3,2,Urban,Manager,59818,0 +5575,Female,32,High School,16,49,47,74,1,4.0,4,74,Rural,ML Engineer,20904,1 +5576,Male,40,Bachelors,5,3,84,28,20,0.0,2,35,Rural,Data Analyst,142658,0 +5577,Female,33,Bachelors,4,74,8,89,96,2.0,3,95,Urban,Data Analyst,145655,1 +5578,Other,32,Bachelors,3,47,59,73,9,4.0,6,75,Urban,Manager,32415,1 +5579,Female,57,Masters,12,87,76,2,89,1.0,4,8,Rural,Manager,121127,0 +5580,Male,56,Diploma,12,97,94,98,7,3.0,7,10,Urban,Software Engineer,28988,1 +5581,Male,53,Diploma,1,68,56,38,14,7.0,4,4,Urban,Data Analyst,37788,0 +5582,Male,47,Masters,1,98,27,63,71,5.0,0,45,Urban,Manager,51830,0 +5583,Female,30,Masters,13,71,88,72,82,2.0,5,73,Semi-Urban,Software Engineer,93528,1 +5584,Female,33,Bachelors,5,1,77,55,15,4.0,7,48,Semi-Urban,Software Engineer,29707,0 +5585,Male,58,Masters,4,78,52,10,44,9.0,3,58,Urban,Manager,49899,0 +5586,Male,24,Diploma,16,68,68,78,49,6.0,2,31,Urban,Software Engineer,57409,1 +5587,Male,31,Diploma,15,88,45,96,23,5.0,0,23,Urban,Data Analyst,98242,1 +5588,Male,24,Masters,9,81,84,5,33,0.0,5,18,Semi-Urban,ML Engineer,48511,0 +5589,Female,51,Masters,14,19,97,61,54,2.0,6,95,Urban,ML Engineer,42321,1 +5590,Female,51,Bachelors,15,85,81,58,56,5.0,2,44,Urban,Manager,117588,1 +5591,Male,29,High School,0,63,27,16,38,7.0,1,50,Urban,ML Engineer,110222,0 +5592,Male,25,Masters,0,43,47,64,76,3.0,7,25,Urban,Manager,33295,0 +5593,Male,44,High School,7,35,1,5,56,7.0,1,35,Semi-Urban,ML Engineer,24188,0 +5594,Other,23,PhD,2,45,92,21,75,8.0,2,9,Urban,Manager,57703,0 +5595,Male,56,Bachelors,7,17,5,84,46,6.0,0,61,Urban,Data Analyst,124786,0 +5596,Male,56,Bachelors,10,21,35,67,10,8.0,5,61,Urban,Data Analyst,48970,0 +5597,Male,31,PhD,13,2,2,22,88,9.0,2,55,Urban,Data Analyst,145432,0 +5598,Female,25,Bachelors,6,53,49,34,64,1.0,0,60,Semi-Urban,ML Engineer,82789,0 +5599,Female,22,Bachelors,9,31,21,56,68,4.0,4,66,Rural,Data Analyst,105571,0 +5600,Female,58,Diploma,0,66,85,70,97,9.0,3,85,Urban,Manager,42573,1 +5601,Male,33,Bachelors,9,3,45,90,70,9.0,7,96,Urban,Data Analyst,65857,0 +5602,Male,32,Bachelors,0,58,91,30,0,3.0,0,30,Urban,ML Engineer,75373,0 +5603,Male,36,Bachelors,7,21,24,96,99,0.0,3,92,Semi-Urban,HR Executive,110016,0 +5604,Female,58,Diploma,16,71,15,88,83,4.0,1,31,Urban,HR Executive,76634,0 +5605,Male,36,PhD,9,83,76,46,51,3.0,6,0,Urban,Manager,82841,0 +5606,Male,31,Masters,5,72,93,74,31,9.0,2,13,Urban,Software Engineer,129472,1 +5607,Female,29,Diploma,17,88,51,32,40,9.0,4,24,Urban,Software Engineer,72697,0 +5608,Female,44,High School,15,54,81,54,83,9.0,1,23,Urban,Data Analyst,54597,0 +5609,Male,55,Bachelors,7,51,36,31,19,2.0,1,29,Semi-Urban,Data Analyst,51675,0 +5610,Male,58,Masters,15,17,46,75,68,7.0,6,0,Rural,HR Executive,20150,0 +5611,Male,44,Bachelors,15,65,77,9,72,9.0,3,43,Rural,ML Engineer,133219,0 +5612,Female,58,Diploma,11,65,53,17,91,0.0,5,6,Urban,Software Engineer,76778,0 +5613,Female,50,Diploma,9,62,85,33,46,9.0,7,97,Urban,Data Analyst,42567,1 +5614,Male,55,Bachelors,18,38,94,47,78,0.0,4,55,Urban,HR Executive,138138,0 +5615,Male,41,Masters,7,81,28,71,47,9.0,7,67,Urban,Software Engineer,33101,1 +5616,Female,37,Bachelors,14,36,24,46,48,0.0,7,52,Urban,ML Engineer,103259,0 +5617,Female,44,Bachelors,1,14,0,84,12,2.0,3,58,Urban,Data Analyst,102794,0 +5618,Male,47,High School,10,61,68,47,64,5.0,1,29,Semi-Urban,Software Engineer,132044,0 +5619,Male,50,Masters,7,11,19,63,62,0.0,2,89,Urban,Manager,30167,0 +5620,Male,33,Diploma,2,43,82,52,20,9.0,1,78,Semi-Urban,Data Analyst,110657,1 +5621,Male,23,High School,11,58,53,30,27,4.0,4,21,Urban,Software Engineer,94955,0 +5622,Female,48,Bachelors,15,77,60,21,83,7.0,5,87,Urban,HR Executive,85181,1 +5623,Female,42,Bachelors,11,70,2,84,87,0.0,7,57,Urban,HR Executive,113451,0 +5624,Female,38,Bachelors,8,71,85,26,45,6.0,4,74,Urban,Software Engineer,81282,1 +5625,Male,54,Bachelors,2,88,28,17,0,4.0,0,17,Urban,HR Executive,116609,0 +5626,Female,30,Bachelors,2,40,47,36,59,1.0,1,71,Urban,ML Engineer,35478,0 +5627,Male,58,Bachelors,12,6,23,58,72,6.0,7,29,Rural,Manager,69578,0 +5628,Male,41,High School,19,79,94,25,93,9.0,0,13,Rural,Software Engineer,60352,0 +5629,Male,53,Masters,5,56,63,21,87,6.0,5,45,Urban,Data Analyst,88462,0 +5630,Male,44,Bachelors,13,24,25,88,2,6.0,5,26,Urban,Data Analyst,94944,0 +5631,Female,33,Masters,16,88,60,94,82,0.0,3,5,Urban,HR Executive,88760,1 +5632,Male,59,Diploma,18,48,54,94,51,4.0,3,49,Semi-Urban,HR Executive,47309,1 +5633,Male,43,High School,11,48,99,12,68,4.0,1,60,Urban,ML Engineer,28045,0 +5634,Male,51,Masters,0,3,33,78,83,8.0,6,41,Urban,Manager,74473,0 +5635,Male,30,Masters,1,19,22,77,40,8.0,6,66,Rural,HR Executive,65589,0 +5636,Male,21,Diploma,12,66,16,89,68,8.0,0,9,Urban,Software Engineer,135682,0 +5637,Male,22,Masters,0,66,12,12,18,8.0,1,17,Urban,Data Analyst,62912,0 +5638,Female,22,Masters,19,12,17,71,55,6.0,3,44,Urban,ML Engineer,136541,0 +5639,Male,45,Bachelors,9,60,22,48,41,1.0,5,88,Urban,ML Engineer,32990,0 +5640,Male,50,Masters,12,68,57,16,20,7.0,2,44,Urban,ML Engineer,144448,0 +5641,Male,36,Masters,0,48,98,99,82,5.0,5,28,Rural,Data Analyst,62318,1 +5642,Female,40,Bachelors,7,44,20,79,15,0.0,6,96,Rural,Manager,38731,0 +5643,Male,37,Masters,12,24,29,90,94,4.0,6,30,Rural,Data Analyst,60216,0 +5644,Male,26,High School,3,25,15,97,77,6.0,6,60,Semi-Urban,Software Engineer,62354,0 +5645,Male,48,Bachelors,6,27,99,65,44,6.0,5,3,Semi-Urban,Manager,96206,0 +5646,Male,26,High School,13,50,52,15,53,7.0,1,85,Urban,ML Engineer,71539,0 +5647,Male,21,Bachelors,1,59,44,28,83,3.0,1,65,Urban,HR Executive,45125,0 +5648,Female,44,PhD,17,2,31,40,60,2.0,1,75,Urban,Software Engineer,103224,0 +5649,Female,34,PhD,5,96,37,88,29,4.0,4,30,Rural,ML Engineer,28539,1 +5650,Male,47,Diploma,9,37,68,78,58,5.0,3,26,Rural,HR Executive,43214,0 +5651,Female,33,Masters,11,44,30,7,47,4.0,5,8,Urban,Data Analyst,74804,0 +5652,Female,59,Diploma,3,88,95,84,6,3.0,7,72,Urban,Manager,137988,1 +5653,Male,34,High School,5,31,65,83,53,8.0,2,93,Rural,Manager,123847,1 +5654,Male,44,Bachelors,17,31,75,92,39,5.0,1,34,Urban,Manager,93159,0 +5655,Male,29,Bachelors,9,63,67,18,28,1.0,1,95,Semi-Urban,Manager,36481,1 +5656,Male,42,Bachelors,11,69,16,57,71,3.0,7,16,Urban,Manager,23477,0 +5657,Female,25,Bachelors,9,89,31,87,35,8.0,6,71,Urban,Manager,67641,1 +5658,Female,55,Diploma,17,63,0,3,2,6.0,4,1,Urban,HR Executive,95793,0 +5659,Other,48,Masters,3,99,48,40,3,2.0,0,93,Semi-Urban,Manager,100756,1 +5660,Female,57,Bachelors,3,70,50,87,46,0.0,7,24,Rural,Software Engineer,27927,0 +5661,Male,50,Bachelors,9,33,39,34,98,7.0,2,56,Urban,ML Engineer,56979,0 +5662,Male,29,Bachelors,9,30,2,3,27,2.0,3,76,Urban,ML Engineer,37719,0 +5663,Female,46,Diploma,6,8,34,75,24,6.0,5,2,Semi-Urban,Software Engineer,111401,0 +5664,Male,41,Bachelors,11,29,48,62,1,7.0,4,80,Urban,Manager,57478,0 +5665,Female,24,PhD,7,2,57,6,64,9.0,4,65,Urban,HR Executive,90024,0 +5666,Female,37,Diploma,0,41,97,21,73,6.0,3,41,Rural,Data Analyst,65363,0 +5667,Female,54,Diploma,11,13,12,53,24,4.0,1,56,Semi-Urban,Software Engineer,35522,0 +5668,Female,49,Diploma,5,19,2,54,7,4.0,0,9,Urban,HR Executive,26964,0 +5669,Male,39,Diploma,18,37,70,86,52,8.0,7,29,Urban,ML Engineer,94719,0 +5670,Female,54,Bachelors,1,83,11,33,45,7.0,1,8,Rural,Data Analyst,115452,0 +5671,Female,29,Bachelors,3,30,12,3,5,5.0,1,41,Urban,Manager,53615,0 +5672,Male,31,Bachelors,4,81,62,48,65,6.0,4,96,Rural,Manager,124487,1 +5673,Female,34,Bachelors,14,93,16,76,83,7.0,1,0,Urban,Software Engineer,143982,0 +5674,Male,48,Bachelors,10,31,25,3,85,0.0,7,21,Rural,HR Executive,132823,0 +5675,Other,57,PhD,15,73,19,89,27,7.0,3,23,Rural,HR Executive,94831,0 +5676,Male,39,Bachelors,15,97,29,27,86,9.0,0,49,Urban,HR Executive,116451,0 +5677,Male,30,Bachelors,3,57,3,45,87,9.0,0,37,Urban,Data Analyst,79532,0 +5678,Male,56,Bachelors,4,87,74,0,90,8.0,6,16,Urban,HR Executive,92398,0 +5679,Female,36,Diploma,17,58,45,97,60,8.0,2,25,Urban,Manager,119613,0 +5680,Male,35,Bachelors,10,31,77,27,36,8.0,6,64,Urban,Software Engineer,22737,0 +5681,Male,38,Bachelors,18,29,97,69,0,3.0,1,93,Urban,Software Engineer,22408,1 +5682,Male,26,PhD,8,93,27,70,10,5.0,4,71,Semi-Urban,Software Engineer,38370,1 +5683,Female,44,Diploma,5,22,16,41,29,8.0,3,88,Rural,Manager,28774,0 +5684,Male,43,High School,11,79,89,63,12,1.0,1,88,Urban,Data Analyst,99849,1 +5685,Male,49,Bachelors,13,59,6,55,88,7.0,7,16,Urban,ML Engineer,141784,0 +5686,Female,43,Diploma,7,34,33,50,69,9.0,1,82,Semi-Urban,Manager,125996,0 +5687,Male,51,Bachelors,14,38,39,42,23,9.0,3,19,Urban,Software Engineer,143705,0 +5688,Female,47,Bachelors,15,14,93,79,62,3.0,6,47,Urban,ML Engineer,45286,0 +5689,Male,55,Bachelors,13,13,17,97,64,4.0,0,44,Rural,Software Engineer,93535,0 +5690,Female,47,Masters,5,43,55,74,83,6.0,7,80,Urban,Manager,84545,1 +5691,Male,54,PhD,12,28,13,13,74,2.0,0,31,Urban,ML Engineer,120153,0 +5692,Male,45,Diploma,8,77,45,53,42,7.0,3,30,Urban,Data Analyst,47070,0 +5693,Female,25,High School,13,76,21,33,59,8.0,1,66,Urban,ML Engineer,75546,0 +5694,Male,41,Masters,8,84,33,28,97,7.0,6,70,Urban,Data Analyst,22731,0 +5695,Female,31,Diploma,0,42,15,53,94,3.0,5,36,Semi-Urban,Data Analyst,98855,0 +5696,Male,39,Diploma,17,51,15,54,79,2.0,1,7,Urban,Data Analyst,118213,0 +5697,Male,36,Bachelors,16,17,81,77,4,2.0,3,77,Rural,Data Analyst,74114,1 +5698,Male,26,Bachelors,10,66,65,67,20,2.0,5,76,Semi-Urban,Data Analyst,101142,1 +5699,Other,58,Masters,6,78,80,35,22,3.0,5,68,Urban,Manager,123596,1 +5700,Male,46,High School,11,35,87,51,34,2.0,3,74,Rural,Manager,134215,1 +5701,Male,58,PhD,7,85,93,8,91,0.0,3,36,Semi-Urban,HR Executive,63811,0 +5702,Male,48,Diploma,1,25,15,39,58,3.0,6,91,Semi-Urban,Software Engineer,114080,0 +5703,Male,42,Bachelors,1,34,39,94,30,2.0,7,63,Urban,HR Executive,90683,0 +5704,Male,27,Masters,6,88,5,83,6,6.0,0,43,Urban,Software Engineer,54774,0 +5705,Female,21,High School,16,72,62,74,95,9.0,0,22,Rural,HR Executive,59839,0 +5706,Male,33,Diploma,2,16,36,51,2,7.0,5,86,Semi-Urban,ML Engineer,29375,0 +5707,Female,37,Masters,1,71,55,21,83,0.0,5,63,Urban,Data Analyst,113418,0 +5708,Male,41,Masters,15,56,43,38,94,8.0,5,93,Urban,Software Engineer,88157,0 +5709,Female,21,Bachelors,1,85,24,71,67,2.0,7,73,Rural,Data Analyst,91724,1 +5710,Female,37,Diploma,11,87,74,70,27,3.0,6,94,Urban,Manager,135854,1 +5711,Male,40,Bachelors,13,85,7,45,76,9.0,7,56,Semi-Urban,Software Engineer,60689,0 +5712,Other,50,High School,14,99,86,23,18,9.0,1,87,Urban,Manager,69421,1 +5713,Male,37,Bachelors,3,18,26,34,16,4.0,6,45,Semi-Urban,HR Executive,96349,0 +5714,Female,47,Bachelors,13,47,76,38,38,5.0,0,5,Semi-Urban,Manager,85910,0 +5715,Female,47,High School,10,70,29,16,8,9.0,0,15,Urban,Data Analyst,31903,0 +5716,Male,24,Masters,4,98,98,89,56,2.0,3,73,Urban,Manager,123089,1 +5717,Male,53,Bachelors,10,28,81,50,14,0.0,1,53,Urban,ML Engineer,142790,0 +5718,Male,21,High School,3,80,68,9,54,7.0,0,74,Semi-Urban,Software Engineer,107662,0 +5719,Male,31,Bachelors,0,40,28,49,83,8.0,0,64,Semi-Urban,HR Executive,94300,0 +5720,Male,28,Masters,15,98,10,14,16,6.0,3,5,Rural,ML Engineer,121290,0 +5721,Male,55,Bachelors,10,93,57,10,5,2.0,5,86,Urban,ML Engineer,36410,1 +5722,Male,50,Diploma,3,92,59,88,26,3.0,6,41,Rural,Software Engineer,78618,1 +5723,Female,57,Diploma,17,80,3,58,68,6.0,4,52,Semi-Urban,Manager,31833,0 +5724,Male,44,Bachelors,4,87,8,34,10,4.0,6,86,Semi-Urban,Manager,20639,0 +5725,Male,23,Diploma,3,9,91,81,4,4.0,6,67,Urban,Software Engineer,102079,1 +5726,Female,51,Bachelors,11,27,24,60,17,0.0,3,65,Urban,Manager,93578,0 +5727,Male,58,Masters,7,96,13,79,50,6.0,0,60,Urban,Manager,52477,1 +5728,Male,24,Bachelors,17,3,42,87,17,9.0,6,97,Rural,Manager,34988,0 +5729,Male,24,Diploma,17,38,40,8,77,7.0,2,48,Rural,Software Engineer,80255,0 +5730,Female,28,Bachelors,9,22,53,19,64,2.0,3,84,Semi-Urban,Software Engineer,53502,0 +5731,Female,56,Masters,9,12,93,59,63,7.0,4,69,Urban,Manager,49031,0 +5732,Male,22,Bachelors,19,46,84,14,85,1.0,4,26,Rural,HR Executive,100220,0 +5733,Female,23,Diploma,15,64,34,55,50,0.0,6,98,Urban,ML Engineer,141958,1 +5734,Male,51,Bachelors,2,99,42,8,13,7.0,6,66,Urban,ML Engineer,53262,0 +5735,Female,30,Bachelors,7,36,87,71,20,5.0,1,50,Urban,HR Executive,64104,1 +5736,Female,46,Masters,17,45,19,72,55,7.0,1,96,Semi-Urban,Manager,116811,0 +5737,Female,22,High School,9,72,5,65,13,7.0,2,27,Semi-Urban,Data Analyst,99180,0 +5738,Male,34,Bachelors,4,75,5,60,44,6.0,1,94,Urban,Manager,127895,0 +5739,Male,22,Bachelors,14,15,87,11,45,7.0,4,17,Urban,Manager,35350,0 +5740,Male,38,Masters,15,78,78,62,30,1.0,5,72,Urban,HR Executive,135670,1 +5741,Female,47,Masters,2,29,25,42,68,7.0,3,64,Urban,Software Engineer,52936,0 +5742,Male,29,Masters,8,37,23,20,0,4.0,7,67,Rural,Software Engineer,30231,0 +5743,Female,52,Bachelors,7,75,28,86,13,2.0,4,31,Urban,Manager,60556,0 +5744,Other,31,Bachelors,11,26,96,13,38,9.0,7,60,Rural,HR Executive,67337,0 +5745,Male,41,Bachelors,1,52,36,22,61,7.0,3,93,Rural,ML Engineer,138220,0 +5746,Female,53,Bachelors,4,38,1,5,4,6.0,1,81,Urban,Manager,54655,0 +5747,Female,53,High School,9,35,49,36,72,3.0,3,48,Urban,Manager,37429,0 +5748,Other,38,Bachelors,17,24,95,23,27,1.0,5,65,Semi-Urban,Software Engineer,81988,0 +5749,Other,44,Bachelors,2,75,26,13,71,1.0,0,68,Rural,HR Executive,117754,0 +5750,Female,32,Diploma,17,41,67,44,68,8.0,5,78,Semi-Urban,ML Engineer,56833,0 +5751,Male,35,Masters,16,93,80,32,18,5.0,7,79,Rural,Manager,121972,1 +5752,Female,41,High School,7,49,81,84,72,5.0,7,13,Semi-Urban,Software Engineer,119767,0 +5753,Male,26,Bachelors,8,89,26,65,59,3.0,4,34,Urban,ML Engineer,82206,0 +5754,Female,58,High School,18,61,93,23,45,2.0,5,24,Urban,Manager,37024,0 +5755,Female,27,Diploma,10,11,22,37,40,5.0,1,59,Rural,HR Executive,111355,0 +5756,Male,38,High School,7,69,26,22,60,7.0,4,85,Rural,Data Analyst,104842,0 +5757,Female,42,High School,11,6,36,36,89,9.0,4,44,Urban,ML Engineer,101685,0 +5758,Male,52,Bachelors,9,93,65,39,73,7.0,0,94,Urban,HR Executive,71502,1 +5759,Male,57,Bachelors,9,34,13,53,67,8.0,1,31,Rural,ML Engineer,147241,0 +5760,Male,27,High School,9,97,81,78,64,7.0,3,28,Rural,Data Analyst,132457,1 +5761,Female,40,Diploma,7,66,28,89,84,3.0,6,93,Urban,Manager,121433,1 +5762,Female,33,High School,3,43,54,13,76,7.0,7,99,Rural,Manager,102893,0 +5763,Female,56,Bachelors,2,87,28,12,57,8.0,7,5,Rural,HR Executive,63788,0 +5764,Male,49,Masters,18,40,18,47,47,0.0,7,62,Urban,Software Engineer,73450,0 +5765,Female,41,Bachelors,1,37,27,41,18,3.0,5,65,Semi-Urban,ML Engineer,117368,0 +5766,Female,22,Masters,5,27,38,99,21,4.0,7,37,Rural,Software Engineer,52398,0 +5767,Male,49,High School,12,94,86,39,32,3.0,4,74,Rural,Software Engineer,58125,1 +5768,Male,39,Bachelors,12,24,66,79,82,4.0,4,88,Urban,Manager,96398,1 +5769,Male,54,Bachelors,13,86,48,50,22,1.0,5,94,Urban,Manager,68863,1 +5770,Female,28,Bachelors,15,11,71,76,77,3.0,5,47,Urban,Data Analyst,54871,0 +5771,Female,52,Bachelors,4,46,58,46,64,0.0,2,8,Rural,HR Executive,127401,0 +5772,Female,33,Bachelors,17,46,3,37,18,7.0,7,18,Rural,Data Analyst,99626,0 +5773,Male,38,Bachelors,7,28,38,86,74,1.0,0,32,Urban,ML Engineer,139201,0 +5774,Female,24,Bachelors,5,68,18,88,28,9.0,4,84,Urban,Software Engineer,140028,1 +5775,Male,38,Bachelors,18,73,15,30,76,8.0,4,84,Rural,ML Engineer,97074,0 +5776,Male,34,Diploma,18,64,7,96,31,2.0,1,39,Urban,Manager,101186,0 +5777,Female,28,Masters,18,68,31,3,26,7.0,0,33,Urban,ML Engineer,93813,0 +5778,Male,39,Masters,13,23,78,53,38,7.0,1,74,Urban,Data Analyst,84878,0 +5779,Female,44,Bachelors,4,31,63,1,93,7.0,0,62,Urban,HR Executive,112698,0 +5780,Male,36,Masters,19,12,56,47,0,2.0,5,92,Rural,Software Engineer,149911,0 +5781,Female,57,Masters,14,56,41,28,43,6.0,2,49,Urban,Data Analyst,105786,0 +5782,Male,21,Bachelors,10,50,55,59,31,7.0,2,85,Urban,Software Engineer,95772,1 +5783,Male,35,Bachelors,16,87,46,85,23,8.0,1,58,Urban,Software Engineer,135220,1 +5784,Male,29,Masters,3,87,6,87,33,6.0,1,53,Urban,Data Analyst,101329,0 +5785,Male,38,PhD,3,49,53,9,24,8.0,7,64,Urban,Data Analyst,125898,0 +5786,Female,24,Bachelors,10,70,10,88,5,1.0,2,75,Urban,Software Engineer,115525,1 +5787,Male,25,High School,7,59,75,42,47,1.0,0,47,Urban,Software Engineer,133890,0 +5788,Female,27,Bachelors,7,17,13,42,75,2.0,6,79,Urban,ML Engineer,76027,0 +5789,Other,22,Masters,10,99,12,79,24,2.0,4,60,Urban,Manager,99588,1 +5790,Male,23,High School,3,56,39,76,19,0.0,4,86,Urban,HR Executive,146968,1 +5791,Male,21,High School,4,64,3,81,78,7.0,3,18,Semi-Urban,Software Engineer,101374,0 +5792,Female,38,Diploma,9,27,96,83,20,7.0,4,25,Urban,Software Engineer,124457,0 +5793,Other,27,High School,4,35,40,83,48,7.0,0,59,Urban,Software Engineer,39907,0 +5794,Female,26,High School,9,66,83,54,28,3.0,6,15,Semi-Urban,Data Analyst,59202,0 +5795,Male,54,High School,15,11,71,46,50,6.0,1,24,Urban,Data Analyst,116037,0 +5796,Female,56,Diploma,7,68,97,15,35,1.0,4,38,Urban,ML Engineer,59342,0 +5797,Male,25,Bachelors,18,53,92,91,14,4.0,4,51,Semi-Urban,Software Engineer,72444,1 +5798,Other,41,PhD,18,99,97,10,68,6.0,5,15,Urban,HR Executive,48051,0 +5799,Other,43,Diploma,10,65,21,67,18,9.0,2,40,Rural,Software Engineer,39926,0 +5800,Male,55,Diploma,16,22,71,36,82,4.0,4,27,Urban,Manager,112959,0 +5801,Male,21,Bachelors,13,48,98,90,61,3.0,4,25,Semi-Urban,Data Analyst,32106,1 +5802,Male,55,Bachelors,0,62,54,6,27,8.0,7,22,Urban,Manager,135772,0 +5803,Male,39,Diploma,1,72,48,43,75,3.0,2,22,Rural,HR Executive,25422,0 +5804,Female,50,Bachelors,15,86,32,94,34,2.0,7,79,Urban,ML Engineer,118348,1 +5805,Male,26,Bachelors,6,32,29,48,76,2.0,2,36,Rural,HR Executive,89484,0 +5806,Male,51,Bachelors,17,72,5,65,20,3.0,7,78,Rural,Software Engineer,94284,0 +5807,Male,34,Bachelors,18,32,30,30,9,6.0,1,73,Rural,Software Engineer,56051,0 +5808,Other,36,Diploma,0,65,30,14,36,0.0,3,78,Urban,Manager,94736,0 +5809,Female,49,Masters,5,72,23,37,75,7.0,5,3,Urban,Software Engineer,142590,0 +5810,Male,59,Bachelors,17,54,97,30,62,3.0,7,7,Rural,Data Analyst,56923,0 +5811,Male,39,Diploma,8,62,37,33,80,7.0,0,3,Urban,HR Executive,120656,0 +5812,Other,41,PhD,0,94,89,52,61,6.0,1,14,Urban,ML Engineer,68804,1 +5813,Female,53,Masters,16,38,47,4,64,7.0,3,26,Semi-Urban,Data Analyst,46511,0 +5814,Male,50,High School,2,59,78,40,83,6.0,7,31,Semi-Urban,Manager,79589,0 +5815,Male,34,High School,9,5,13,4,98,5.0,2,80,Urban,Data Analyst,148727,0 +5816,Male,51,Bachelors,4,41,75,58,93,2.0,4,63,Urban,HR Executive,82300,1 +5817,Male,46,Bachelors,17,45,22,7,83,7.0,3,7,Rural,Manager,72289,0 +5818,Male,38,Bachelors,10,76,33,32,26,4.0,7,11,Urban,HR Executive,38145,0 +5819,Female,24,Bachelors,13,76,14,46,34,2.0,1,63,Rural,Manager,98691,0 +5820,Male,56,Bachelors,11,32,46,54,28,0.0,5,47,Urban,ML Engineer,73549,0 +5821,Female,33,High School,14,24,51,6,74,2.0,4,67,Urban,Manager,58271,0 +5822,Male,57,Masters,13,70,52,31,78,0.0,3,86,Urban,Software Engineer,37901,1 +5823,Female,30,PhD,14,21,10,58,16,9.0,1,5,Rural,Manager,129097,0 +5824,Female,57,Masters,0,30,50,85,74,2.0,0,61,Rural,ML Engineer,46488,0 +5825,Male,50,Bachelors,2,90,6,40,33,9.0,4,40,Semi-Urban,HR Executive,125584,0 +5826,Male,24,Masters,9,5,31,44,46,2.0,2,67,Urban,Software Engineer,35490,0 +5827,Female,30,Bachelors,9,33,49,53,74,1.0,0,28,Rural,Software Engineer,85060,0 +5828,Male,48,Masters,10,43,16,31,59,3.0,5,91,Rural,Data Analyst,131270,0 +5829,Male,22,Bachelors,17,21,10,32,8,0.0,2,68,Semi-Urban,Manager,53145,0 +5830,Male,47,Bachelors,8,87,74,66,20,1.0,6,39,Semi-Urban,Software Engineer,48696,1 +5831,Other,49,Bachelors,9,13,55,47,74,7.0,5,40,Semi-Urban,Data Analyst,102059,0 +5832,Male,26,Bachelors,8,3,80,15,11,4.0,4,36,Semi-Urban,Data Analyst,28924,0 +5833,Female,43,Bachelors,7,15,56,3,85,6.0,1,88,Rural,Manager,80398,0 +5834,Male,32,High School,18,61,61,46,67,8.0,5,96,Semi-Urban,ML Engineer,131520,1 +5835,Female,28,Masters,4,17,53,69,55,4.0,7,88,Urban,Manager,124434,0 +5836,Male,30,Diploma,16,40,30,63,95,2.0,0,2,Rural,Manager,67681,0 +5837,Female,37,Diploma,1,12,83,97,90,7.0,0,17,Rural,Software Engineer,35035,0 +5838,Male,21,Bachelors,11,89,8,10,43,2.0,5,17,Urban,Manager,100719,0 +5839,Female,23,Bachelors,7,96,35,2,4,3.0,1,6,Urban,HR Executive,49497,0 +5840,Female,48,High School,17,45,18,95,26,5.0,3,70,Urban,ML Engineer,126637,0 +5841,Male,56,Diploma,7,2,61,59,50,4.0,7,91,Urban,Software Engineer,111047,0 +5842,Male,46,Masters,4,60,35,65,48,0.0,6,18,Urban,Manager,62528,0 +5843,Male,45,High School,4,32,31,89,80,7.0,7,23,Urban,Manager,97195,0 +5844,Male,54,PhD,15,51,99,47,12,6.0,1,94,Rural,Data Analyst,134462,1 +5845,Female,23,PhD,14,67,89,21,66,2.0,4,1,Urban,ML Engineer,126393,0 +5846,Male,48,High School,12,39,35,6,25,3.0,6,59,Urban,Software Engineer,40515,0 +5847,Male,49,PhD,6,39,15,89,3,1.0,5,76,Semi-Urban,Manager,28747,0 +5848,Female,33,High School,3,2,6,51,59,5.0,5,30,Urban,Manager,62891,0 +5849,Male,59,Bachelors,8,29,27,51,52,2.0,3,49,Urban,Software Engineer,140023,0 +5850,Male,40,Bachelors,0,75,90,83,17,0.0,2,72,Urban,Software Engineer,76273,1 +5851,Male,42,Masters,4,68,12,13,98,5.0,5,95,Rural,Software Engineer,115455,0 +5852,Other,33,High School,2,37,41,71,16,9.0,6,63,Urban,HR Executive,142119,0 +5853,Female,28,Masters,12,19,34,51,27,5.0,7,15,Urban,Manager,37242,0 +5854,Female,39,Diploma,10,23,11,15,21,2.0,0,66,Semi-Urban,HR Executive,22765,0 +5855,Male,25,Bachelors,17,6,95,35,20,1.0,1,38,Urban,ML Engineer,141576,0 +5856,Female,25,Bachelors,2,74,52,33,2,8.0,5,41,Urban,Manager,22137,0 +5857,Male,54,Masters,11,20,42,15,97,2.0,0,0,Urban,Data Analyst,82122,0 +5858,Male,54,Diploma,18,74,73,2,17,5.0,6,9,Urban,HR Executive,23651,0 +5859,Male,31,Bachelors,15,5,2,66,94,7.0,5,16,Rural,ML Engineer,110740,0 +5860,Male,58,Bachelors,16,15,31,95,31,4.0,7,26,Urban,Manager,74692,0 +5861,Male,27,Diploma,13,94,90,50,82,0.0,7,12,Urban,Software Engineer,51218,1 +5862,Male,36,Diploma,18,21,25,93,12,1.0,2,92,Urban,Software Engineer,85950,0 +5863,Male,38,PhD,3,65,4,63,75,2.0,0,69,Rural,ML Engineer,85172,0 +5864,Male,26,Bachelors,18,72,49,66,31,4.0,2,67,Rural,ML Engineer,34453,1 +5865,Female,21,High School,13,14,11,86,71,3.0,1,7,Urban,ML Engineer,47475,0 +5866,Male,43,Diploma,16,35,66,21,21,3.0,0,29,Urban,Manager,39485,0 +5867,Female,58,Bachelors,9,52,20,89,24,8.0,0,34,Semi-Urban,Data Analyst,74664,0 +5868,Male,28,Masters,9,97,60,44,38,7.0,3,59,Rural,Software Engineer,116559,1 +5869,Female,32,High School,3,57,47,67,14,3.0,4,73,Semi-Urban,Software Engineer,130545,1 +5870,Male,25,Masters,3,58,87,93,18,6.0,0,34,Urban,HR Executive,55379,1 +5871,Male,47,PhD,6,22,5,33,27,5.0,5,57,Semi-Urban,HR Executive,85590,0 +5872,Male,41,Masters,1,84,7,48,59,6.0,6,58,Urban,HR Executive,61653,0 +5873,Female,57,Bachelors,3,98,66,11,66,0.0,3,6,Urban,Data Analyst,33291,0 +5874,Female,33,Masters,1,17,79,68,1,2.0,3,39,Urban,Manager,44933,0 +5875,Male,39,Masters,12,7,22,10,62,0.0,3,73,Urban,Manager,146685,0 +5876,Male,33,High School,3,90,7,5,1,9.0,0,11,Rural,Manager,76315,0 +5877,Female,42,Bachelors,13,25,87,75,92,3.0,7,47,Semi-Urban,Data Analyst,38622,0 +5878,Female,52,Masters,15,93,63,40,37,4.0,1,68,Rural,ML Engineer,104964,1 +5879,Male,23,Masters,3,67,24,56,83,4.0,2,34,Rural,Data Analyst,61927,0 +5880,Male,29,Masters,17,17,0,81,59,6.0,4,37,Semi-Urban,Manager,52942,0 +5881,Male,58,Bachelors,5,36,47,21,40,7.0,2,30,Urban,HR Executive,27286,0 +5882,Female,43,Bachelors,9,29,92,60,26,6.0,0,26,Semi-Urban,Software Engineer,120083,0 +5883,Male,46,Bachelors,17,66,48,11,9,4.0,5,90,Rural,Data Analyst,74378,0 +5884,Other,27,Bachelors,11,31,56,4,23,6.0,7,9,Rural,Data Analyst,33629,0 +5885,Male,30,Bachelors,14,45,12,17,76,5.0,0,95,Urban,Manager,133495,0 +5886,Male,25,Masters,13,18,55,80,27,9.0,0,33,Rural,ML Engineer,24451,0 +5887,Male,36,Masters,5,16,41,50,23,2.0,2,69,Semi-Urban,ML Engineer,121289,0 +5888,Female,29,Diploma,2,55,45,50,38,1.0,4,22,Rural,HR Executive,104158,0 +5889,Female,45,Masters,7,5,69,7,71,3.0,1,3,Urban,Manager,106619,0 +5890,Male,59,Bachelors,1,87,30,29,81,5.0,6,27,Urban,Software Engineer,131858,0 +5891,Female,58,Bachelors,8,33,34,97,82,7.0,1,9,Semi-Urban,Data Analyst,64771,0 +5892,Male,35,Bachelors,6,76,63,90,14,3.0,5,86,Semi-Urban,Manager,62844,1 +5893,Male,52,Bachelors,6,8,23,29,58,0.0,6,85,Urban,Data Analyst,139343,0 +5894,Male,55,Masters,18,77,68,60,0,9.0,1,35,Urban,ML Engineer,111917,1 +5895,Male,44,Diploma,2,40,19,42,36,6.0,6,72,Semi-Urban,Manager,145391,0 +5896,Male,56,Masters,6,52,52,60,73,6.0,0,60,Urban,ML Engineer,135468,0 +5897,Female,46,Bachelors,13,66,96,77,63,8.0,4,76,Rural,Manager,126241,1 +5898,Male,57,Bachelors,5,11,98,27,26,9.0,0,98,Urban,Data Analyst,47453,0 +5899,Other,43,Diploma,19,54,38,31,15,9.0,3,42,Urban,Software Engineer,123642,0 +5900,Male,39,Diploma,8,50,82,87,31,7.0,4,45,Urban,HR Executive,117737,1 +5901,Female,31,Bachelors,0,43,68,81,66,1.0,5,16,Semi-Urban,ML Engineer,84492,0 +5902,Male,38,Bachelors,19,54,34,41,31,3.0,3,93,Urban,Manager,109232,0 +5903,Male,48,Diploma,6,12,3,59,10,0.0,0,84,Rural,ML Engineer,38410,0 +5904,Male,35,Masters,19,32,37,55,91,3.0,0,37,Semi-Urban,ML Engineer,139288,0 +5905,Male,52,Bachelors,18,78,54,95,74,8.0,2,40,Urban,Software Engineer,73940,1 +5906,Female,35,Diploma,10,71,98,4,88,0.0,7,55,Urban,Data Analyst,142260,0 +5907,Male,57,Bachelors,17,58,15,16,10,7.0,3,47,Rural,Data Analyst,144381,0 +5908,Female,23,Masters,18,88,29,96,1,2.0,7,40,Urban,Software Engineer,44718,1 +5909,Male,32,Bachelors,10,6,63,52,24,9.0,6,0,Rural,Manager,79456,0 +5910,Male,36,Diploma,3,70,63,24,86,5.0,1,64,Urban,ML Engineer,57288,0 +5911,Male,25,Bachelors,1,19,64,79,46,7.0,0,96,Urban,Manager,21043,1 +5912,Female,25,Masters,15,88,17,80,13,0.0,1,56,Urban,Manager,31508,1 +5913,Female,45,Bachelors,16,94,63,29,46,2.0,6,26,Urban,HR Executive,141817,0 +5914,Male,31,High School,18,80,46,12,5,0.0,1,59,Rural,Data Analyst,64734,0 +5915,Male,30,Masters,2,96,48,80,8,8.0,1,9,Rural,HR Executive,23287,0 +5916,Male,57,Bachelors,2,90,2,7,75,3.0,2,9,Urban,Software Engineer,42383,0 +5917,Other,28,Bachelors,10,63,13,86,32,8.0,0,78,Urban,HR Executive,129886,0 +5918,Female,40,Masters,6,3,24,17,32,5.0,6,88,Urban,Software Engineer,82475,0 +5919,Male,57,Bachelors,8,79,43,79,44,8.0,4,7,Semi-Urban,HR Executive,118604,0 +5920,Male,55,Diploma,16,91,8,78,73,7.0,4,7,Urban,Manager,87501,0 +5921,Male,49,High School,6,50,43,11,60,3.0,5,43,Rural,HR Executive,99477,0 +5922,Other,53,Masters,15,30,76,12,75,6.0,1,32,Semi-Urban,Data Analyst,31508,0 +5923,Male,47,High School,15,42,50,37,36,9.0,1,94,Semi-Urban,Data Analyst,147272,0 +5924,Female,27,Masters,15,24,39,27,87,1.0,2,62,Semi-Urban,HR Executive,141425,0 +5925,Male,43,Diploma,19,64,59,37,60,9.0,6,65,Urban,HR Executive,47259,0 +5926,Female,47,PhD,9,64,86,73,42,5.0,3,27,Semi-Urban,Manager,130206,1 +5927,Female,25,Bachelors,10,46,76,8,29,2.0,4,20,Urban,Data Analyst,26865,0 +5928,Female,31,Diploma,11,20,43,66,75,9.0,6,53,Semi-Urban,Data Analyst,20233,0 +5929,Female,29,Bachelors,6,86,20,16,14,7.0,4,38,Semi-Urban,Software Engineer,104651,0 +5930,Female,21,Diploma,1,67,13,37,94,3.0,0,39,Semi-Urban,Manager,80263,0 +5931,Male,49,Bachelors,16,36,30,26,87,0.0,6,93,Semi-Urban,Data Analyst,109225,0 +5932,Male,25,Bachelors,3,48,95,22,76,0.0,4,49,Urban,Software Engineer,127604,0 +5933,Male,36,Masters,9,18,89,48,18,9.0,7,65,Urban,Software Engineer,135787,0 +5934,Other,34,High School,1,69,15,24,48,5.0,4,39,Semi-Urban,Software Engineer,24672,0 +5935,Male,37,Masters,0,51,48,84,30,5.0,5,13,Rural,Data Analyst,116573,0 +5936,Female,29,Bachelors,15,22,84,35,68,3.0,5,70,Semi-Urban,HR Executive,91193,0 +5937,Female,52,Bachelors,19,75,72,93,8,6.0,4,48,Rural,ML Engineer,29264,1 +5938,Male,53,Diploma,0,34,36,65,36,1.0,0,97,Urban,Data Analyst,82645,0 +5939,Male,27,High School,9,82,94,9,7,6.0,1,68,Rural,Data Analyst,95895,1 +5940,Male,59,Masters,0,24,50,69,10,7.0,4,13,Rural,Data Analyst,74458,0 +5941,Male,41,Masters,6,28,33,72,85,3.0,4,99,Rural,Software Engineer,83691,0 +5942,Male,35,High School,13,2,20,90,48,7.0,3,0,Urban,Software Engineer,79267,0 +5943,Male,54,Bachelors,8,29,90,32,15,2.0,5,28,Rural,Data Analyst,62837,0 +5944,Female,24,Masters,1,44,57,69,46,9.0,2,56,Semi-Urban,Data Analyst,113113,0 +5945,Other,32,Diploma,7,50,49,31,54,5.0,5,86,Urban,Software Engineer,125543,0 +5946,Male,54,High School,1,56,38,58,80,3.0,6,37,Rural,Software Engineer,59230,0 +5947,Male,44,Diploma,13,90,62,48,97,3.0,7,18,Rural,Manager,83462,0 +5948,Male,41,Bachelors,7,44,79,59,37,1.0,6,72,Urban,Data Analyst,111630,1 +5949,Female,58,High School,18,0,71,28,96,5.0,5,78,Urban,ML Engineer,63980,0 +5950,Female,48,High School,14,71,54,54,35,8.0,0,11,Urban,ML Engineer,123130,0 +5951,Male,23,Masters,2,61,9,67,19,7.0,4,43,Semi-Urban,Data Analyst,90900,0 +5952,Male,21,PhD,17,96,16,6,0,0.0,5,11,Semi-Urban,Software Engineer,27750,0 +5953,Female,31,Masters,17,18,7,63,63,2.0,4,46,Urban,Data Analyst,41173,0 +5954,Female,40,PhD,11,75,32,72,54,0.0,6,86,Urban,HR Executive,67144,1 +5955,Male,26,High School,12,3,65,0,70,7.0,5,68,Urban,Data Analyst,22792,0 +5956,Female,59,Bachelors,12,92,18,7,42,3.0,1,9,Urban,Manager,90317,0 +5957,Male,56,Bachelors,7,47,4,29,5,3.0,4,14,Semi-Urban,HR Executive,125710,0 +5958,Male,44,Masters,18,56,75,43,54,9.0,2,96,Rural,ML Engineer,82553,1 +5959,Female,50,Bachelors,13,33,83,40,85,4.0,1,27,Urban,Manager,72023,0 +5960,Female,21,Bachelors,6,90,84,31,71,8.0,1,56,Urban,Software Engineer,34306,1 +5961,Male,46,Bachelors,4,27,73,3,96,8.0,5,69,Urban,HR Executive,143353,0 +5962,Female,30,High School,19,56,75,91,17,0.0,0,31,Urban,Software Engineer,124936,1 +5963,Male,40,Diploma,17,37,39,16,22,1.0,2,29,Urban,Software Engineer,77457,0 +5964,Female,37,Masters,19,29,68,52,17,2.0,2,27,Rural,Manager,93838,0 +5965,Male,36,Bachelors,13,70,83,45,73,8.0,4,12,Urban,Software Engineer,25936,0 +5966,Female,52,Bachelors,7,9,62,86,72,7.0,5,64,Rural,ML Engineer,20512,0 +5967,Female,29,Masters,18,52,1,90,13,5.0,7,29,Urban,Data Analyst,42484,0 +5968,Male,51,Bachelors,1,69,79,12,99,0.0,4,61,Urban,HR Executive,127624,0 +5969,Female,47,Bachelors,19,97,67,23,32,9.0,4,4,Semi-Urban,Manager,109315,0 +5970,Female,42,Diploma,0,44,49,22,15,2.0,0,99,Urban,ML Engineer,45426,0 +5971,Female,41,Bachelors,18,83,4,81,43,2.0,4,86,Rural,ML Engineer,113079,1 +5972,Male,57,Bachelors,2,13,3,5,59,6.0,1,64,Urban,HR Executive,137810,0 +5973,Female,45,Bachelors,10,90,91,54,62,1.0,5,19,Urban,HR Executive,107790,1 +5974,Female,23,Masters,15,37,98,5,43,1.0,4,97,Urban,Software Engineer,147500,0 +5975,Male,23,Bachelors,6,29,92,8,22,1.0,4,20,Semi-Urban,Data Analyst,58876,0 +5976,Other,24,Masters,18,61,42,10,88,9.0,2,48,Semi-Urban,HR Executive,22127,0 +5977,Male,57,Diploma,10,93,46,70,46,8.0,3,39,Urban,Manager,33826,1 +5978,Male,54,Diploma,16,80,87,50,45,1.0,7,16,Rural,Software Engineer,88745,0 +5979,Male,30,Bachelors,18,91,62,16,81,8.0,0,31,Rural,Manager,47605,0 +5980,Male,51,Bachelors,11,78,91,69,97,3.0,5,57,Urban,HR Executive,55696,1 +5981,Female,45,Bachelors,6,97,77,52,96,8.0,4,44,Rural,Data Analyst,119596,1 +5982,Male,22,Masters,17,46,88,50,10,2.0,2,26,Urban,ML Engineer,53058,0 +5983,Other,29,Masters,15,18,2,74,45,8.0,7,24,Rural,Data Analyst,140952,0 +5984,Male,50,Diploma,0,78,22,58,95,2.0,3,18,Rural,Manager,57455,0 +5985,Male,45,High School,4,24,76,65,17,7.0,6,72,Semi-Urban,ML Engineer,141631,1 +5986,Male,51,Bachelors,18,3,75,19,3,4.0,2,83,Semi-Urban,Software Engineer,28080,0 +5987,Male,49,Bachelors,9,50,5,60,11,7.0,1,72,Rural,HR Executive,63578,0 +5988,Female,34,Bachelors,19,56,78,28,46,7.0,0,5,Urban,Software Engineer,34154,0 +5989,Female,48,Diploma,12,13,53,46,4,1.0,1,72,Urban,HR Executive,63478,0 +5990,Female,28,Masters,15,87,55,87,74,8.0,5,53,Semi-Urban,HR Executive,72293,1 +5991,Male,59,Diploma,2,6,35,64,28,8.0,3,49,Urban,Software Engineer,46288,0 +5992,Male,57,Bachelors,6,19,17,3,73,6.0,7,62,Rural,Manager,50787,0 +5993,Male,47,Bachelors,11,98,5,48,85,9.0,5,45,Semi-Urban,Software Engineer,56855,0 +5994,Male,29,Bachelors,5,86,33,93,51,9.0,5,12,Rural,ML Engineer,58011,0 +5995,Male,33,PhD,4,37,55,38,39,5.0,0,88,Rural,ML Engineer,78778,0 +5996,Female,40,Diploma,0,20,34,92,62,2.0,3,50,Urban,HR Executive,59120,0 +5997,Male,36,Masters,1,63,74,65,7,7.0,5,76,Urban,Manager,59181,1 +5998,Female,30,Masters,19,72,50,4,35,2.0,2,71,Urban,HR Executive,100210,0 +5999,Male,45,Masters,11,50,98,28,35,1.0,5,23,Rural,Data Analyst,123907,0 +6000,Male,23,High School,8,19,20,92,40,1.0,2,75,Semi-Urban,ML Engineer,116960,0 +6001,Female,35,Diploma,13,87,1,32,87,9.0,5,69,Urban,ML Engineer,128830,0 +6002,Male,21,High School,15,71,9,64,38,2.0,0,51,Urban,HR Executive,60676,0 +6003,Female,35,Diploma,3,87,34,10,50,9.0,7,47,Semi-Urban,Data Analyst,80268,0 +6004,Female,36,High School,1,62,54,79,80,0.0,2,45,Rural,Software Engineer,42832,0 +6005,Male,31,Masters,7,92,23,9,52,5.0,6,45,Urban,Manager,118835,0 +6006,Other,21,Diploma,17,95,8,99,12,7.0,3,27,Urban,ML Engineer,129531,0 +6007,Male,39,Bachelors,18,84,96,13,50,1.0,7,45,Urban,Data Analyst,111460,1 +6008,Male,30,Masters,13,66,13,21,0,4.0,4,25,Urban,Software Engineer,25548,0 +6009,Female,28,Diploma,16,5,35,36,86,5.0,3,10,Urban,Software Engineer,143869,0 +6010,Male,40,Masters,19,49,49,21,5,1.0,2,7,Rural,Software Engineer,53710,0 +6011,Female,29,Diploma,18,35,35,81,17,6.0,6,25,Urban,Manager,99717,0 +6012,Female,27,Bachelors,16,28,89,85,25,2.0,0,24,Rural,ML Engineer,48133,0 +6013,Other,32,Masters,8,99,18,92,98,4.0,6,98,Urban,Data Analyst,62394,1 +6014,Male,43,Bachelors,18,94,25,72,72,2.0,2,79,Semi-Urban,ML Engineer,36056,1 +6015,Male,59,Masters,5,96,68,34,66,2.0,0,85,Urban,ML Engineer,49939,1 +6016,Female,56,High School,8,37,64,15,29,9.0,2,30,Urban,Manager,31496,0 +6017,Male,46,Masters,9,12,23,55,68,2.0,4,7,Urban,HR Executive,36116,0 +6018,Male,30,Diploma,2,6,12,40,14,3.0,3,51,Urban,Software Engineer,147396,0 +6019,Male,45,Bachelors,15,59,57,0,57,8.0,1,89,Rural,HR Executive,142629,0 +6020,Male,50,Bachelors,7,56,14,15,33,8.0,5,33,Urban,Software Engineer,91527,0 +6021,Male,57,High School,12,97,13,56,71,8.0,6,34,Urban,HR Executive,35062,0 +6022,Female,53,Diploma,9,52,58,50,2,2.0,6,73,Semi-Urban,HR Executive,33774,0 +6023,Female,56,High School,3,39,59,53,40,5.0,6,93,Urban,Manager,120870,1 +6024,Male,23,Bachelors,18,8,16,45,73,9.0,3,1,Rural,Data Analyst,86250,0 +6025,Male,52,Diploma,13,0,63,68,95,3.0,4,54,Urban,Data Analyst,57249,0 +6026,Male,55,High School,17,7,66,10,2,8.0,5,58,Urban,Data Analyst,107621,0 +6027,Female,38,Masters,10,64,37,62,97,8.0,6,51,Urban,ML Engineer,79589,0 +6028,Male,50,Bachelors,9,92,87,25,49,7.0,2,15,Urban,ML Engineer,94254,0 +6029,Female,39,High School,17,21,7,43,51,1.0,3,85,Semi-Urban,HR Executive,67854,0 +6030,Male,32,Bachelors,11,5,35,79,70,7.0,7,88,Urban,HR Executive,71385,0 +6031,Female,54,Bachelors,19,19,83,98,39,5.0,3,5,Urban,ML Engineer,141277,0 +6032,Male,24,PhD,12,46,47,3,66,8.0,2,68,Urban,Manager,118502,0 +6033,Female,44,Diploma,17,77,29,29,31,6.0,6,1,Urban,HR Executive,127976,0 +6034,Male,27,Bachelors,16,8,28,67,81,3.0,2,20,Urban,HR Executive,99463,0 +6035,Female,37,High School,2,46,70,58,21,6.0,6,64,Urban,HR Executive,60877,0 +6036,Male,59,Bachelors,4,34,93,57,63,6.0,4,63,Urban,Data Analyst,79119,1 +6037,Female,44,High School,2,16,6,65,88,0.0,4,55,Urban,HR Executive,59802,0 +6038,Female,36,Diploma,18,3,96,56,16,9.0,5,79,Urban,HR Executive,39494,0 +6039,Male,45,Bachelors,12,61,95,85,4,1.0,6,16,Semi-Urban,HR Executive,77585,1 +6040,Female,39,Masters,5,14,70,71,75,1.0,1,65,Urban,ML Engineer,72239,0 +6041,Male,46,Bachelors,19,29,17,0,17,8.0,7,1,Urban,Data Analyst,94758,0 +6042,Male,53,High School,14,89,11,7,66,3.0,3,65,Urban,HR Executive,148595,0 +6043,Male,34,High School,18,18,60,61,40,7.0,6,70,Urban,Software Engineer,67249,0 +6044,Male,43,Bachelors,13,85,90,19,84,7.0,4,85,Semi-Urban,Software Engineer,110006,1 +6045,Female,51,Diploma,3,41,85,41,23,2.0,1,36,Rural,Manager,63736,0 +6046,Female,39,PhD,3,76,60,11,54,9.0,0,95,Semi-Urban,ML Engineer,39342,1 +6047,Male,50,Bachelors,4,90,5,57,90,5.0,2,76,Semi-Urban,Software Engineer,97015,0 +6048,Male,46,Masters,4,10,55,48,98,7.0,2,48,Semi-Urban,Data Analyst,141829,0 +6049,Female,28,Diploma,4,32,19,82,2,9.0,0,31,Urban,Software Engineer,33746,0 +6050,Female,42,Diploma,9,41,68,41,87,4.0,6,48,Urban,Data Analyst,42898,0 +6051,Male,47,Bachelors,12,85,1,26,61,1.0,3,81,Rural,ML Engineer,80616,0 +6052,Other,50,Bachelors,5,25,46,38,46,6.0,6,27,Urban,Manager,21780,0 +6053,Male,54,Diploma,19,77,46,24,75,3.0,4,15,Urban,ML Engineer,147578,0 +6054,Male,22,Bachelors,18,94,98,47,57,8.0,4,30,Urban,Manager,53595,1 +6055,Female,33,Bachelors,10,49,9,54,15,3.0,1,16,Urban,Manager,43547,0 +6056,Male,30,Diploma,6,64,60,0,68,1.0,6,86,Rural,Data Analyst,74899,0 +6057,Male,45,Bachelors,19,12,46,53,66,7.0,3,0,Rural,ML Engineer,47857,0 +6058,Male,53,Bachelors,15,65,40,31,64,4.0,0,79,Semi-Urban,Data Analyst,51878,0 +6059,Female,47,High School,7,6,16,66,53,2.0,2,1,Semi-Urban,Data Analyst,140902,0 +6060,Female,49,Bachelors,10,71,72,38,30,3.0,0,56,Urban,Data Analyst,39176,0 +6061,Male,47,Diploma,15,72,19,27,70,9.0,0,93,Urban,HR Executive,44035,0 +6062,Male,59,Bachelors,5,70,38,2,18,4.0,0,28,Urban,ML Engineer,147645,0 +6063,Male,36,Masters,5,25,53,19,20,0.0,1,19,Urban,Data Analyst,34802,0 +6064,Male,49,Bachelors,5,0,50,75,63,6.0,4,61,Semi-Urban,Data Analyst,103308,0 +6065,Male,55,Bachelors,9,25,28,3,92,1.0,6,74,Rural,HR Executive,32208,0 +6066,Female,36,Bachelors,4,27,79,16,71,6.0,0,29,Rural,ML Engineer,64153,0 +6067,Male,35,Masters,10,22,79,82,49,7.0,5,30,Urban,Manager,55150,0 +6068,Male,47,Bachelors,18,93,90,91,66,7.0,3,12,Urban,Software Engineer,31865,1 +6069,Male,53,High School,10,51,7,22,66,2.0,3,51,Rural,Manager,47313,0 +6070,Male,45,Masters,8,62,13,27,3,4.0,2,38,Urban,Data Analyst,137880,0 +6071,Female,53,Masters,12,95,16,7,62,6.0,6,83,Rural,HR Executive,128157,0 +6072,Male,32,Bachelors,18,66,51,0,85,9.0,4,28,Rural,HR Executive,117113,0 +6073,Male,34,Bachelors,12,13,69,19,21,4.0,4,33,Urban,ML Engineer,48834,0 +6074,Male,30,Diploma,9,46,25,84,39,9.0,6,71,Urban,Software Engineer,76509,0 +6075,Male,57,Diploma,13,25,26,23,15,5.0,7,47,Urban,ML Engineer,104582,0 +6076,Male,32,Bachelors,5,61,38,9,65,7.0,4,68,Urban,Software Engineer,128131,0 +6077,Male,41,Diploma,1,70,44,70,8,7.0,3,5,Urban,Data Analyst,58494,0 +6078,Male,56,PhD,5,47,42,57,84,4.0,6,66,Urban,Data Analyst,39812,0 +6079,Male,27,Masters,11,71,18,81,89,9.0,6,62,Urban,ML Engineer,50140,0 +6080,Male,32,Diploma,19,25,17,98,97,7.0,5,12,Semi-Urban,Data Analyst,100502,0 +6081,Male,40,Bachelors,19,40,29,33,48,8.0,5,67,Urban,Data Analyst,60740,0 +6082,Other,54,Bachelors,18,32,80,36,35,8.0,4,49,Urban,Software Engineer,132897,0 +6083,Male,51,PhD,0,83,70,70,93,6.0,2,25,Urban,ML Engineer,84431,1 +6084,Male,26,Diploma,5,90,13,78,49,7.0,1,96,Rural,Software Engineer,94665,1 +6085,Male,24,Bachelors,15,72,50,98,19,7.0,3,88,Urban,Manager,28143,1 +6086,Male,36,Bachelors,11,6,74,4,22,0.0,3,32,Urban,HR Executive,91518,0 +6087,Female,50,Bachelors,5,95,40,30,15,9.0,4,88,Semi-Urban,Manager,32139,1 +6088,Male,52,Bachelors,14,53,59,63,76,1.0,3,49,Semi-Urban,Software Engineer,116915,0 +6089,Female,48,Diploma,8,34,2,9,6,1.0,5,51,Semi-Urban,Data Analyst,81210,0 +6090,Male,23,Bachelors,14,98,92,23,39,6.0,0,70,Rural,Data Analyst,89795,1 +6091,Male,23,Diploma,5,25,29,68,85,4.0,6,45,Semi-Urban,HR Executive,103316,0 +6092,Female,47,Bachelors,12,37,7,49,61,8.0,2,34,Urban,Manager,33477,0 +6093,Male,49,High School,12,13,66,29,20,4.0,6,57,Urban,ML Engineer,63773,0 +6094,Male,33,Diploma,19,73,99,86,98,7.0,3,35,Urban,HR Executive,102405,1 +6095,Male,31,Bachelors,18,70,40,80,62,2.0,7,55,Urban,Software Engineer,27733,1 +6096,Female,28,Masters,16,83,27,84,33,5.0,6,21,Urban,Data Analyst,98069,0 +6097,Male,57,Bachelors,9,93,66,16,6,2.0,0,27,Rural,Manager,86133,0 +6098,Female,49,Masters,17,36,33,62,88,6.0,3,59,Urban,ML Engineer,21424,0 +6099,Male,30,Bachelors,3,25,37,94,41,0.0,1,46,Urban,HR Executive,77225,0 +6100,Female,59,Bachelors,16,39,24,76,51,3.0,4,87,Urban,HR Executive,68189,0 +6101,Male,27,Masters,3,23,98,40,66,7.0,5,49,Urban,Manager,33248,0 +6102,Female,28,High School,15,75,1,37,93,4.0,3,50,Semi-Urban,Data Analyst,67370,0 +6103,Male,58,Masters,17,96,25,79,17,7.0,6,15,Urban,ML Engineer,113225,0 +6104,Female,46,High School,4,19,57,45,31,4.0,4,69,Urban,HR Executive,113364,0 +6105,Male,22,Bachelors,9,49,31,9,99,9.0,3,11,Urban,Data Analyst,80699,0 +6106,Male,56,PhD,11,23,40,17,23,6.0,6,2,Rural,Software Engineer,82766,0 +6107,Male,55,Masters,19,88,50,26,69,3.0,1,86,Urban,Software Engineer,129902,1 +6108,Male,31,Bachelors,14,51,48,31,14,9.0,5,16,Urban,Software Engineer,77362,0 +6109,Male,44,Bachelors,11,95,42,28,12,4.0,7,22,Urban,Manager,92527,0 +6110,Female,49,Bachelors,18,33,81,86,83,3.0,7,85,Rural,Manager,142194,1 +6111,Other,43,Diploma,6,67,78,39,38,2.0,7,97,Semi-Urban,HR Executive,145296,1 +6112,Male,25,Diploma,12,6,19,53,16,8.0,6,21,Urban,Data Analyst,138949,0 +6113,Female,44,Diploma,10,83,1,57,26,4.0,2,33,Urban,Manager,51402,0 +6114,Male,34,Diploma,15,33,95,97,32,6.0,1,70,Rural,Data Analyst,25907,1 +6115,Male,37,Bachelors,8,85,80,95,56,9.0,3,54,Semi-Urban,HR Executive,101546,1 +6116,Female,59,Masters,0,55,52,24,44,1.0,1,53,Rural,HR Executive,149482,0 +6117,Female,21,Diploma,10,79,80,72,37,5.0,3,64,Rural,Manager,29916,1 +6118,Other,32,Diploma,19,2,89,3,79,2.0,3,53,Urban,ML Engineer,80017,0 +6119,Male,58,Bachelors,13,31,60,34,53,2.0,5,34,Urban,Data Analyst,35786,0 +6120,Female,36,Diploma,10,60,3,57,1,9.0,6,63,Semi-Urban,Data Analyst,30407,0 +6121,Male,56,Masters,9,86,65,54,90,0.0,6,72,Semi-Urban,Manager,97485,1 +6122,Male,23,Bachelors,19,6,92,3,22,1.0,1,33,Urban,Manager,72967,0 +6123,Male,25,Bachelors,7,11,55,63,76,8.0,4,35,Rural,HR Executive,89225,0 +6124,Other,52,High School,13,66,3,44,1,6.0,5,79,Rural,Software Engineer,61721,0 +6125,Female,37,Diploma,17,12,63,19,45,9.0,2,35,Semi-Urban,Manager,70964,0 +6126,Female,28,Diploma,3,12,21,48,15,2.0,6,9,Rural,ML Engineer,110137,0 +6127,Male,23,Bachelors,4,24,95,89,80,6.0,5,76,Urban,Manager,88730,1 +6128,Male,53,Bachelors,6,27,98,84,86,2.0,7,20,Semi-Urban,Manager,44906,0 +6129,Male,39,Masters,4,72,94,86,17,9.0,4,29,Semi-Urban,Manager,56267,1 +6130,Male,36,Diploma,1,67,23,97,38,8.0,7,65,Urban,HR Executive,138282,1 +6131,Male,23,Bachelors,19,13,11,82,79,0.0,3,39,Semi-Urban,HR Executive,120763,0 +6132,Female,44,High School,1,90,89,2,32,2.0,4,95,Urban,Manager,34094,1 +6133,Male,46,Diploma,18,7,61,60,62,2.0,7,44,Semi-Urban,Data Analyst,119177,0 +6134,Male,31,High School,11,60,37,75,17,5.0,0,33,Urban,ML Engineer,121843,0 +6135,Male,47,Bachelors,7,92,89,66,90,3.0,4,53,Semi-Urban,HR Executive,99383,1 +6136,Male,57,Masters,17,74,96,28,25,5.0,1,61,Urban,Software Engineer,71049,1 +6137,Male,31,Diploma,4,15,95,91,34,8.0,6,62,Semi-Urban,Software Engineer,138515,1 +6138,Female,54,Bachelors,9,68,96,87,18,1.0,7,20,Urban,Data Analyst,149169,1 +6139,Female,26,Bachelors,6,90,2,43,19,0.0,1,47,Semi-Urban,Software Engineer,29441,0 +6140,Female,59,Bachelors,19,67,12,54,42,8.0,4,99,Urban,Software Engineer,79992,0 +6141,Male,23,Diploma,6,55,31,71,54,4.0,0,85,Semi-Urban,HR Executive,97606,1 +6142,Male,56,Diploma,5,18,27,97,82,2.0,2,93,Semi-Urban,HR Executive,48664,1 +6143,Male,54,Bachelors,7,87,45,10,75,6.0,1,38,Rural,Software Engineer,36586,0 +6144,Female,56,Masters,8,21,94,9,62,1.0,3,92,Rural,ML Engineer,131182,0 +6145,Female,35,Masters,6,64,0,85,73,4.0,3,43,Urban,Software Engineer,28648,0 +6146,Male,53,High School,11,7,52,21,81,0.0,5,37,Urban,Software Engineer,86714,0 +6147,Male,53,High School,9,8,6,66,79,5.0,3,53,Semi-Urban,Data Analyst,61107,0 +6148,Male,25,Diploma,16,75,57,80,28,1.0,3,36,Rural,ML Engineer,77977,1 +6149,Female,25,Masters,9,22,88,44,93,7.0,6,39,Urban,Data Analyst,149694,0 +6150,Female,23,Masters,12,67,41,98,97,4.0,6,2,Urban,ML Engineer,22642,0 +6151,Male,51,Masters,2,38,27,61,86,5.0,1,50,Semi-Urban,Software Engineer,89917,0 +6152,Male,48,High School,17,55,11,21,56,5.0,6,18,Urban,Software Engineer,36058,0 +6153,Male,25,PhD,1,73,28,16,40,4.0,1,95,Urban,Software Engineer,41134,0 +6154,Male,50,Bachelors,17,88,2,23,49,4.0,7,57,Semi-Urban,Manager,127025,0 +6155,Male,37,Bachelors,19,25,29,48,23,2.0,2,77,Rural,Manager,57346,0 +6156,Male,36,Bachelors,18,59,5,30,50,6.0,6,68,Urban,Software Engineer,89263,0 +6157,Female,28,Masters,19,13,32,0,17,8.0,3,96,Rural,Manager,76961,0 +6158,Female,52,Masters,15,50,49,90,88,5.0,1,22,Rural,Software Engineer,107960,0 +6159,Male,35,Masters,17,78,6,44,73,4.0,5,21,Urban,ML Engineer,109923,0 +6160,Female,35,Masters,9,60,61,42,44,5.0,4,67,Urban,ML Engineer,119104,0 +6161,Male,50,High School,14,12,29,81,52,3.0,1,87,Urban,Software Engineer,96597,0 +6162,Male,57,Bachelors,15,72,24,48,9,1.0,4,10,Rural,Manager,114284,0 +6163,Male,53,Bachelors,18,89,57,37,85,6.0,5,96,Semi-Urban,HR Executive,22435,1 +6164,Male,45,Bachelors,11,40,42,93,71,7.0,1,76,Urban,Data Analyst,135092,1 +6165,Male,37,Bachelors,13,23,14,29,16,0.0,6,51,Urban,Manager,81863,0 +6166,Male,23,Bachelors,13,97,2,3,92,1.0,5,89,Semi-Urban,ML Engineer,105414,0 +6167,Male,38,Bachelors,19,65,68,0,23,4.0,6,93,Urban,Software Engineer,98276,0 +6168,Other,27,Bachelors,1,84,3,39,12,6.0,5,47,Urban,Data Analyst,113078,0 +6169,Male,45,Bachelors,0,25,20,31,44,9.0,5,62,Semi-Urban,Data Analyst,114086,0 +6170,Male,35,Bachelors,4,76,1,34,32,4.0,2,86,Rural,Data Analyst,21575,0 +6171,Male,30,Bachelors,3,29,37,15,75,4.0,4,10,Semi-Urban,Data Analyst,131750,0 +6172,Female,36,Diploma,16,27,16,98,17,5.0,1,26,Rural,Manager,57674,0 +6173,Male,46,Masters,1,44,35,95,77,4.0,5,3,Rural,ML Engineer,145983,0 +6174,Female,41,High School,8,91,65,2,4,1.0,6,34,Semi-Urban,Software Engineer,49174,0 +6175,Male,30,Masters,19,47,57,96,25,2.0,0,55,Rural,Data Analyst,20843,1 +6176,Male,31,High School,1,28,60,98,60,3.0,3,24,Urban,ML Engineer,44835,0 +6177,Male,40,Bachelors,8,72,19,52,99,7.0,5,18,Urban,Data Analyst,50910,0 +6178,Male,54,Masters,14,81,39,55,95,0.0,2,23,Semi-Urban,HR Executive,66122,0 +6179,Male,59,Diploma,9,32,18,68,23,3.0,4,33,Urban,Software Engineer,59903,0 +6180,Male,40,Bachelors,16,33,38,41,25,1.0,7,84,Semi-Urban,ML Engineer,37421,0 +6181,Male,33,High School,3,74,17,54,52,7.0,5,10,Urban,HR Executive,65567,0 +6182,Male,43,Masters,17,41,82,23,60,5.0,2,1,Urban,Manager,146235,0 +6183,Male,34,High School,17,23,89,20,45,6.0,2,64,Urban,Software Engineer,78539,0 +6184,Other,48,Bachelors,4,31,62,95,39,0.0,3,99,Semi-Urban,Software Engineer,106094,1 +6185,Male,43,Bachelors,17,76,43,8,17,3.0,5,90,Urban,Data Analyst,135446,0 +6186,Female,24,Masters,8,23,23,0,20,3.0,0,33,Urban,Software Engineer,78558,0 +6187,Female,54,Bachelors,12,52,86,44,78,4.0,2,78,Urban,Software Engineer,149288,1 +6188,Male,54,Bachelors,12,9,36,60,19,9.0,0,42,Urban,ML Engineer,128176,0 +6189,Male,39,Diploma,15,93,34,0,93,9.0,2,41,Urban,ML Engineer,66298,0 +6190,Male,46,Diploma,12,29,5,51,27,9.0,2,24,Rural,Software Engineer,43567,0 +6191,Female,31,Diploma,8,60,77,9,9,4.0,6,25,Urban,ML Engineer,68344,0 +6192,Female,50,High School,9,83,56,60,98,7.0,3,79,Urban,ML Engineer,98781,1 +6193,Female,38,PhD,8,37,78,52,37,3.0,5,79,Semi-Urban,Data Analyst,57715,1 +6194,Female,50,Bachelors,3,83,55,32,11,9.0,7,13,Semi-Urban,Data Analyst,109255,0 +6195,Female,38,High School,5,55,46,36,60,1.0,2,96,Rural,Data Analyst,143354,0 +6196,Male,31,High School,12,50,52,84,90,2.0,0,94,Urban,HR Executive,149612,1 +6197,Male,22,Masters,19,45,37,62,19,7.0,3,69,Rural,ML Engineer,101009,0 +6198,Female,39,Bachelors,8,69,25,66,97,5.0,1,59,Semi-Urban,HR Executive,132815,0 +6199,Male,41,Bachelors,17,27,77,52,53,5.0,3,51,Semi-Urban,Data Analyst,144372,0 +6200,Male,37,PhD,3,51,96,43,15,7.0,1,28,Urban,Software Engineer,32115,0 +6201,Female,54,Diploma,7,33,33,8,79,2.0,6,64,Semi-Urban,ML Engineer,80405,0 +6202,Male,35,Masters,15,56,94,26,25,9.0,7,29,Urban,ML Engineer,149358,0 +6203,Female,59,Diploma,19,8,30,62,97,5.0,6,72,Urban,Manager,30282,0 +6204,Female,57,Diploma,5,27,91,90,68,4.0,7,22,Urban,Data Analyst,126448,0 +6205,Male,40,High School,16,19,82,4,73,5.0,6,77,Urban,Software Engineer,68108,0 +6206,Female,24,Masters,1,99,72,77,16,0.0,2,73,Rural,HR Executive,60157,1 +6207,Male,37,Masters,8,51,30,47,10,2.0,3,29,Rural,Data Analyst,132059,0 +6208,Male,45,Bachelors,19,99,72,65,62,9.0,6,15,Urban,ML Engineer,112252,1 +6209,Male,28,Bachelors,1,25,91,11,39,0.0,4,9,Urban,Software Engineer,134356,0 +6210,Male,47,Bachelors,13,81,24,38,15,3.0,2,46,Urban,Manager,79370,0 +6211,Male,51,Bachelors,16,35,36,15,16,7.0,1,74,Urban,ML Engineer,36435,0 +6212,Male,28,Bachelors,4,0,36,34,63,6.0,7,78,Rural,HR Executive,35039,0 +6213,Male,45,Bachelors,9,81,23,79,93,0.0,2,0,Rural,ML Engineer,50297,0 +6214,Male,29,High School,15,89,52,8,27,5.0,5,93,Semi-Urban,ML Engineer,52578,1 +6215,Female,21,Bachelors,6,60,61,89,42,7.0,4,85,Urban,Manager,99393,1 +6216,Female,56,PhD,19,90,30,0,47,4.0,2,84,Urban,Manager,145144,0 +6217,Male,50,Bachelors,9,84,83,6,3,8.0,7,70,Urban,Data Analyst,45778,1 +6218,Male,34,High School,11,49,74,71,35,0.0,5,94,Rural,HR Executive,93755,1 +6219,Male,24,Masters,3,24,26,26,73,8.0,2,37,Urban,Manager,131891,0 +6220,Male,46,PhD,0,67,95,16,19,6.0,4,69,Urban,Data Analyst,78884,1 +6221,Female,34,High School,8,31,49,19,38,2.0,6,49,Semi-Urban,Software Engineer,75329,0 +6222,Female,56,Bachelors,17,10,74,77,22,0.0,7,17,Urban,Manager,137568,0 +6223,Male,23,Diploma,18,41,7,27,56,1.0,1,12,Urban,Manager,130227,0 +6224,Male,40,Diploma,10,24,51,5,62,7.0,4,79,Rural,HR Executive,113922,0 +6225,Male,26,High School,11,19,35,47,31,2.0,1,79,Semi-Urban,HR Executive,130175,0 +6226,Female,41,Bachelors,8,91,94,17,32,7.0,0,76,Urban,ML Engineer,107202,1 +6227,Male,31,Bachelors,11,69,80,83,80,3.0,3,88,Urban,ML Engineer,94878,1 +6228,Other,47,Diploma,3,45,74,47,82,4.0,1,82,Semi-Urban,Data Analyst,103643,1 +6229,Female,50,Bachelors,17,30,69,56,84,5.0,2,82,Urban,Data Analyst,116513,0 +6230,Male,34,Diploma,8,6,67,98,26,5.0,6,31,Urban,Manager,56317,0 +6231,Male,38,Bachelors,9,55,98,7,70,7.0,5,16,Urban,Manager,139885,0 +6232,Female,26,Bachelors,0,85,94,90,34,6.0,3,16,Semi-Urban,Software Engineer,77965,1 +6233,Male,52,High School,15,55,54,59,59,5.0,1,70,Urban,Data Analyst,110227,1 +6234,Male,53,Diploma,18,2,39,41,78,0.0,6,11,Semi-Urban,Manager,129039,0 +6235,Male,32,Bachelors,0,75,28,15,41,6.0,5,87,Rural,Software Engineer,115765,0 +6236,Female,24,Diploma,9,13,98,4,57,8.0,2,31,Urban,HR Executive,136472,0 +6237,Female,56,Bachelors,17,69,68,47,22,8.0,1,14,Semi-Urban,Data Analyst,68187,0 +6238,Female,31,Masters,18,70,18,55,37,3.0,3,30,Urban,ML Engineer,29336,0 +6239,Female,56,Bachelors,13,6,70,99,3,0.0,6,91,Rural,HR Executive,143690,1 +6240,Female,35,Bachelors,14,72,36,53,74,6.0,2,99,Semi-Urban,ML Engineer,85775,1 +6241,Female,44,Diploma,6,72,59,76,11,6.0,2,44,Rural,HR Executive,117738,1 +6242,Male,53,Masters,16,44,67,0,1,6.0,1,21,Rural,Manager,146016,0 +6243,Male,48,Diploma,12,31,53,37,61,4.0,4,74,Urban,Data Analyst,43003,0 +6244,Female,24,High School,16,13,67,10,71,5.0,3,30,Rural,Data Analyst,87649,0 +6245,Female,32,Bachelors,1,2,63,90,33,5.0,4,99,Urban,Data Analyst,67279,1 +6246,Female,36,Masters,0,44,85,6,62,6.0,0,38,Rural,Data Analyst,130876,0 +6247,Male,32,Bachelors,9,83,90,22,23,9.0,0,20,Urban,Software Engineer,50910,0 +6248,Female,41,Diploma,6,92,42,14,78,3.0,0,38,Rural,Software Engineer,129118,0 +6249,Female,46,Masters,18,67,16,99,4,3.0,2,52,Urban,Manager,144511,0 +6250,Male,29,Bachelors,12,91,24,31,48,4.0,3,93,Rural,Manager,64652,1 +6251,Male,40,Bachelors,6,56,62,13,77,3.0,3,83,Urban,Software Engineer,149657,0 +6252,Male,41,High School,7,51,65,62,26,3.0,3,56,Semi-Urban,Data Analyst,143682,0 +6253,Male,25,High School,11,92,71,85,1,9.0,6,37,Urban,HR Executive,32460,1 +6254,Male,31,Bachelors,4,41,72,81,41,6.0,1,69,Urban,Manager,108382,1 +6255,Male,25,High School,7,31,85,29,28,9.0,3,80,Semi-Urban,ML Engineer,60264,0 +6256,Male,36,Diploma,1,34,6,46,84,4.0,6,78,Semi-Urban,Data Analyst,39535,0 +6257,Female,32,Bachelors,0,77,12,57,56,9.0,4,11,Semi-Urban,Manager,54494,0 +6258,Female,57,Bachelors,18,11,41,96,25,0.0,4,2,Semi-Urban,HR Executive,115710,0 +6259,Female,54,Diploma,10,66,14,70,97,8.0,7,59,Urban,Software Engineer,96402,0 +6260,Male,42,Masters,1,23,60,37,57,0.0,1,0,Urban,Manager,35443,0 +6261,Male,35,Diploma,3,40,94,54,23,7.0,3,98,Urban,Software Engineer,141309,1 +6262,Female,52,Bachelors,18,71,71,39,66,9.0,3,79,Semi-Urban,Software Engineer,76470,1 +6263,Male,53,High School,17,85,33,54,94,8.0,5,62,Urban,ML Engineer,110749,0 +6264,Other,55,High School,5,64,86,83,97,2.0,1,90,Urban,HR Executive,103083,1 +6265,Female,24,Bachelors,0,71,7,64,27,5.0,4,11,Rural,ML Engineer,52814,0 +6266,Male,36,Bachelors,7,24,51,92,91,4.0,1,95,Urban,ML Engineer,50331,1 +6267,Other,30,Bachelors,7,73,77,23,43,9.0,3,34,Urban,ML Engineer,87786,0 +6268,Male,53,High School,8,34,38,2,21,7.0,6,13,Rural,HR Executive,58552,0 +6269,Male,32,Diploma,14,46,99,1,0,4.0,0,29,Rural,ML Engineer,148854,0 +6270,Female,35,PhD,6,20,80,4,71,5.0,4,26,Urban,Manager,27511,0 +6271,Male,51,Bachelors,14,45,33,57,72,9.0,6,15,Rural,ML Engineer,98712,0 +6272,Female,55,High School,18,58,48,51,21,3.0,4,34,Rural,HR Executive,25637,0 +6273,Male,43,Bachelors,7,90,12,14,1,1.0,4,28,Urban,Data Analyst,63377,0 +6274,Male,52,High School,5,65,54,34,8,8.0,4,11,Urban,Data Analyst,24425,0 +6275,Male,45,Diploma,14,74,0,80,45,5.0,6,75,Semi-Urban,HR Executive,30487,0 +6276,Female,25,Masters,18,92,11,70,57,9.0,0,4,Urban,Software Engineer,95510,0 +6277,Male,34,Bachelors,12,63,67,51,54,8.0,2,2,Urban,Data Analyst,46623,0 +6278,Male,51,Bachelors,9,3,31,16,0,4.0,2,44,Urban,HR Executive,93134,0 +6279,Female,34,Bachelors,7,70,74,8,24,0.0,5,30,Semi-Urban,HR Executive,90235,0 +6280,Male,34,PhD,5,18,81,31,48,6.0,4,68,Urban,Software Engineer,70709,0 +6281,Female,26,Bachelors,1,81,61,55,16,2.0,6,89,Semi-Urban,ML Engineer,71811,1 +6282,Male,45,Masters,7,38,86,47,3,2.0,7,72,Urban,Software Engineer,48128,1 +6283,Female,48,Diploma,18,45,49,45,3,5.0,4,30,Rural,Software Engineer,56451,0 +6284,Female,37,Masters,18,91,91,50,53,6.0,4,5,Urban,Software Engineer,72519,0 +6285,Male,24,PhD,12,97,1,0,20,4.0,5,88,Semi-Urban,HR Executive,122327,0 +6286,Male,48,High School,3,98,67,88,58,3.0,1,66,Semi-Urban,Manager,42075,1 +6287,Female,27,Masters,10,14,14,33,95,9.0,6,86,Semi-Urban,Manager,81553,0 +6288,Male,26,Bachelors,7,94,0,17,87,5.0,7,26,Urban,Data Analyst,27808,0 +6289,Other,57,Diploma,15,26,90,64,3,1.0,2,97,Urban,HR Executive,78482,1 +6290,Male,49,Masters,15,58,91,16,81,5.0,3,52,Rural,Manager,89370,0 +6291,Male,48,High School,14,62,10,77,0,9.0,0,93,Rural,ML Engineer,123734,1 +6292,Male,39,PhD,6,16,40,84,66,9.0,1,16,Urban,Software Engineer,53555,0 +6293,Other,34,Diploma,18,40,12,29,91,1.0,0,32,Urban,ML Engineer,46083,0 +6294,Male,33,PhD,17,26,79,35,62,1.0,7,89,Urban,Software Engineer,149007,0 +6295,Female,49,Diploma,19,16,48,13,14,2.0,4,42,Urban,Data Analyst,78883,0 +6296,Female,55,Bachelors,4,85,52,74,35,2.0,7,60,Urban,ML Engineer,141245,1 +6297,Male,22,PhD,6,10,15,53,14,0.0,6,94,Rural,HR Executive,122913,0 +6298,Male,22,PhD,14,38,82,32,58,5.0,5,42,Semi-Urban,HR Executive,45191,0 +6299,Female,46,Bachelors,4,90,31,46,8,2.0,5,74,Urban,Manager,24690,1 +6300,Male,21,Masters,3,66,89,6,47,6.0,3,25,Semi-Urban,Software Engineer,64380,0 +6301,Female,48,Bachelors,18,34,42,74,4,9.0,0,66,Urban,Data Analyst,125737,0 +6302,Male,57,High School,11,25,53,58,37,3.0,2,17,Urban,Data Analyst,121836,0 +6303,Male,54,High School,14,99,19,51,29,4.0,2,68,Urban,Software Engineer,81769,1 +6304,Female,44,Bachelors,0,95,32,31,64,0.0,2,66,Urban,ML Engineer,64149,0 +6305,Male,49,High School,16,77,17,73,9,4.0,1,24,Rural,HR Executive,91107,0 +6306,Male,48,High School,5,20,89,77,61,1.0,6,27,Semi-Urban,Software Engineer,20991,0 +6307,Male,54,Bachelors,10,78,50,57,86,2.0,5,94,Semi-Urban,Software Engineer,79983,1 +6308,Male,53,Diploma,4,90,19,67,13,8.0,2,84,Rural,Data Analyst,54940,1 +6309,Male,58,Masters,10,44,49,72,84,6.0,0,28,Semi-Urban,HR Executive,132195,0 +6310,Female,54,Diploma,1,83,43,79,4,1.0,0,77,Rural,ML Engineer,105100,1 +6311,Male,25,High School,3,65,22,38,54,1.0,4,62,Rural,Manager,114104,0 +6312,Male,50,High School,13,78,30,19,82,0.0,6,41,Urban,Software Engineer,107007,0 +6313,Female,42,High School,18,77,28,7,85,4.0,0,58,Urban,Manager,86917,0 +6314,Male,23,Masters,8,34,89,53,90,5.0,6,4,Urban,ML Engineer,46692,0 +6315,Male,49,High School,3,13,21,32,93,5.0,7,53,Semi-Urban,Software Engineer,118594,0 +6316,Female,51,Masters,8,88,12,51,53,7.0,1,94,Rural,ML Engineer,130898,1 +6317,Female,50,High School,12,99,77,98,32,1.0,4,3,Semi-Urban,ML Engineer,38958,1 +6318,Male,49,Diploma,4,29,4,2,53,6.0,0,84,Rural,Software Engineer,145262,0 +6319,Female,51,Diploma,0,71,94,96,77,2.0,2,4,Urban,ML Engineer,31114,1 +6320,Male,44,High School,11,27,4,32,43,5.0,6,58,Semi-Urban,Software Engineer,62744,0 +6321,Female,43,Diploma,6,30,73,24,72,8.0,7,38,Urban,HR Executive,23860,0 +6322,Male,58,Diploma,3,34,37,15,93,4.0,4,55,Urban,Software Engineer,120104,0 +6323,Male,54,Masters,19,57,34,20,89,7.0,5,16,Urban,Software Engineer,146103,0 +6324,Male,44,Diploma,0,8,9,34,31,0.0,6,56,Urban,Software Engineer,95834,0 +6325,Male,45,Diploma,4,60,46,80,66,1.0,7,51,Rural,Software Engineer,61062,1 +6326,Male,22,Masters,14,84,38,40,74,0.0,5,54,Rural,Software Engineer,72765,0 +6327,Other,26,Masters,3,88,23,86,25,1.0,0,22,Semi-Urban,Software Engineer,34710,0 +6328,Male,52,Bachelors,11,57,43,6,16,6.0,7,16,Urban,ML Engineer,46378,0 +6329,Male,33,Bachelors,10,2,58,93,18,8.0,4,10,Rural,Manager,90937,0 +6330,Male,36,High School,3,17,43,75,6,1.0,5,6,Rural,ML Engineer,100915,0 +6331,Male,46,High School,15,16,38,44,7,9.0,1,48,Rural,Data Analyst,36114,0 +6332,Female,30,Masters,19,69,29,72,44,7.0,1,38,Rural,Manager,125140,0 +6333,Male,24,Diploma,19,21,39,88,79,5.0,6,89,Rural,HR Executive,66516,1 +6334,Male,34,Diploma,17,54,18,15,13,0.0,5,15,Urban,ML Engineer,42271,0 +6335,Male,44,Bachelors,13,62,76,67,77,2.0,4,93,Urban,ML Engineer,26997,1 +6336,Female,58,Diploma,8,23,63,5,85,3.0,4,68,Rural,Software Engineer,25702,0 +6337,Male,57,Diploma,18,41,54,67,37,5.0,3,83,Urban,Manager,38261,1 +6338,Male,59,Masters,5,85,67,97,49,7.0,0,64,Semi-Urban,ML Engineer,121780,1 +6339,Male,43,Bachelors,19,5,89,71,20,9.0,5,89,Semi-Urban,ML Engineer,62630,1 +6340,Male,31,Diploma,15,29,54,92,41,8.0,3,87,Semi-Urban,Manager,50944,1 +6341,Male,28,Bachelors,16,26,38,23,59,4.0,5,15,Urban,Manager,106769,0 +6342,Female,26,Diploma,12,9,73,37,84,4.0,0,27,Urban,Software Engineer,95734,0 +6343,Female,54,High School,13,97,56,69,40,5.0,1,63,Urban,HR Executive,136229,1 +6344,Female,57,High School,0,27,31,18,57,6.0,5,40,Semi-Urban,Manager,83506,0 +6345,Male,53,Bachelors,16,82,9,76,10,5.0,3,33,Semi-Urban,ML Engineer,121475,0 +6346,Male,30,Bachelors,14,18,84,48,70,9.0,0,71,Rural,Data Analyst,48219,0 +6347,Male,56,Bachelors,17,31,30,72,34,2.0,6,15,Semi-Urban,Manager,85183,0 +6348,Other,27,PhD,5,69,15,71,20,4.0,5,53,Semi-Urban,ML Engineer,108190,0 +6349,Male,37,Bachelors,17,93,34,46,1,6.0,4,35,Urban,ML Engineer,111462,0 +6350,Female,40,High School,13,92,11,94,83,4.0,7,6,Semi-Urban,HR Executive,58354,0 +6351,Male,48,Bachelors,13,12,40,46,51,6.0,5,72,Rural,ML Engineer,80119,0 +6352,Male,44,Bachelors,15,92,70,51,87,6.0,0,39,Urban,Manager,26971,1 +6353,Male,58,High School,3,26,97,79,14,4.0,0,57,Rural,Software Engineer,90061,1 +6354,Male,29,High School,9,64,37,23,32,4.0,4,46,Semi-Urban,Manager,26883,0 +6355,Female,50,Bachelors,2,8,3,60,62,5.0,0,76,Rural,Manager,89715,0 +6356,Other,59,PhD,17,98,3,32,57,3.0,1,70,Urban,Data Analyst,123616,0 +6357,Male,56,Diploma,18,91,61,10,26,3.0,0,40,Rural,Manager,34889,0 +6358,Male,37,Bachelors,7,63,78,81,11,3.0,1,90,Semi-Urban,Software Engineer,73713,1 +6359,Female,36,Bachelors,15,5,74,64,25,0.0,4,92,Urban,ML Engineer,47592,0 +6360,Female,54,Masters,9,9,54,13,86,2.0,5,98,Urban,Software Engineer,107841,0 +6361,Male,27,High School,17,20,6,89,57,6.0,4,68,Semi-Urban,Data Analyst,142591,0 +6362,Male,47,High School,9,72,32,87,99,6.0,3,10,Urban,HR Executive,31583,0 +6363,Male,27,Bachelors,1,56,80,54,1,5.0,0,79,Rural,Software Engineer,74212,1 +6364,Male,52,Masters,19,66,62,27,77,9.0,4,5,Urban,HR Executive,68259,0 +6365,Male,36,Bachelors,17,89,55,30,77,8.0,2,2,Urban,Data Analyst,47598,0 +6366,Male,39,Diploma,16,91,56,90,30,2.0,0,11,Urban,Software Engineer,33938,1 +6367,Male,46,Bachelors,4,33,6,57,57,8.0,4,58,Urban,Software Engineer,80682,0 +6368,Male,21,High School,7,52,7,89,7,6.0,5,59,Semi-Urban,HR Executive,35521,0 +6369,Male,50,Bachelors,9,73,36,84,76,8.0,6,3,Urban,ML Engineer,98510,0 +6370,Female,35,Bachelors,7,41,77,59,22,7.0,0,2,Rural,HR Executive,140444,0 +6371,Female,23,Bachelors,4,64,64,54,67,4.0,6,51,Urban,Manager,125119,0 +6372,Male,40,Diploma,17,38,53,31,10,3.0,4,8,Semi-Urban,Data Analyst,144975,0 +6373,Female,39,Masters,9,29,34,92,26,6.0,1,38,Urban,HR Executive,99400,0 +6374,Female,47,Masters,3,80,67,56,83,8.0,4,85,Rural,Data Analyst,146533,1 +6375,Male,21,Bachelors,5,7,95,17,56,3.0,4,9,Urban,HR Executive,143211,0 +6376,Male,33,Masters,3,13,69,98,13,9.0,1,75,Rural,Software Engineer,103125,1 +6377,Female,53,High School,13,47,3,67,91,5.0,3,20,Semi-Urban,Data Analyst,25749,0 +6378,Female,44,High School,16,65,46,32,54,6.0,1,28,Urban,ML Engineer,96196,0 +6379,Other,31,PhD,9,69,46,49,19,2.0,0,21,Urban,Data Analyst,80303,0 +6380,Female,25,Bachelors,8,28,96,33,76,5.0,7,63,Rural,Software Engineer,96608,0 +6381,Female,52,Masters,18,63,84,23,55,3.0,6,2,Rural,Manager,74911,0 +6382,Male,55,Bachelors,0,90,11,16,1,0.0,3,69,Urban,ML Engineer,116133,0 +6383,Male,39,High School,18,47,11,89,71,2.0,7,44,Urban,Software Engineer,106371,0 +6384,Male,21,Diploma,19,10,74,48,82,3.0,5,82,Urban,HR Executive,48525,0 +6385,Male,35,High School,17,31,41,3,27,5.0,4,28,Semi-Urban,HR Executive,33195,0 +6386,Female,39,Bachelors,5,54,20,14,71,2.0,1,43,Semi-Urban,ML Engineer,135729,0 +6387,Male,24,Bachelors,2,4,11,96,64,8.0,5,78,Urban,HR Executive,59699,0 +6388,Female,45,Diploma,6,11,91,50,14,5.0,4,23,Urban,ML Engineer,86664,0 +6389,Male,56,High School,4,84,35,10,68,8.0,3,22,Semi-Urban,Manager,86879,0 +6390,Male,28,Bachelors,8,56,65,53,72,8.0,0,45,Urban,Software Engineer,106536,0 +6391,Male,46,Bachelors,8,68,16,29,3,6.0,7,94,Semi-Urban,HR Executive,58517,0 +6392,Male,56,High School,15,98,90,43,86,0.0,2,99,Rural,Manager,23217,1 +6393,Female,38,Masters,14,58,10,12,60,6.0,2,30,Rural,ML Engineer,78402,0 +6394,Female,48,Masters,19,53,23,81,17,6.0,5,5,Urban,HR Executive,71207,0 +6395,Other,53,Bachelors,18,25,16,10,62,6.0,7,67,Urban,Data Analyst,63239,0 +6396,Male,56,Masters,18,88,67,95,86,3.0,0,58,Urban,Data Analyst,73080,1 +6397,Male,25,Masters,15,61,89,98,43,5.0,3,42,Semi-Urban,Data Analyst,136126,1 +6398,Male,56,Masters,5,98,31,84,64,5.0,4,66,Urban,Manager,62625,1 +6399,Male,48,High School,8,12,15,35,65,8.0,7,13,Semi-Urban,Software Engineer,92710,0 +6400,Female,37,Masters,15,51,33,89,26,8.0,2,15,Urban,ML Engineer,83065,0 +6401,Female,34,High School,4,29,14,81,2,5.0,7,22,Rural,HR Executive,115292,0 +6402,Female,49,Diploma,15,27,31,37,51,6.0,4,70,Semi-Urban,HR Executive,26992,0 +6403,Male,35,PhD,0,70,32,42,19,5.0,0,18,Urban,HR Executive,68136,0 +6404,Female,23,High School,5,12,41,43,96,2.0,6,94,Semi-Urban,HR Executive,100459,0 +6405,Male,23,Bachelors,15,76,49,30,64,9.0,2,8,Urban,Manager,127291,0 +6406,Female,39,Diploma,17,76,50,72,86,3.0,0,75,Urban,Software Engineer,148733,1 +6407,Male,53,Bachelors,3,62,24,71,97,8.0,4,62,Urban,Software Engineer,28666,0 +6408,Male,56,Bachelors,6,39,90,98,9,2.0,6,40,Urban,HR Executive,137988,1 +6409,Male,46,Diploma,4,80,28,35,1,4.0,3,8,Urban,Software Engineer,127504,0 +6410,Female,59,Masters,17,39,52,36,26,7.0,5,15,Urban,ML Engineer,146739,0 +6411,Male,36,Bachelors,7,23,61,1,21,8.0,0,20,Semi-Urban,Manager,140817,0 +6412,Male,44,Bachelors,12,30,2,84,51,3.0,0,11,Urban,Data Analyst,56143,0 +6413,Female,49,Bachelors,15,34,18,40,49,1.0,4,35,Rural,HR Executive,51242,0 +6414,Male,47,Masters,19,52,2,34,67,9.0,6,88,Semi-Urban,Data Analyst,124189,0 +6415,Male,27,Bachelors,3,76,51,28,6,9.0,0,1,Rural,Manager,60169,0 +6416,Male,29,Masters,2,0,78,69,87,1.0,0,75,Semi-Urban,Manager,21292,0 +6417,Male,59,Bachelors,1,24,76,43,59,4.0,3,91,Rural,Manager,130450,0 +6418,Female,24,High School,15,85,30,13,73,9.0,5,32,Urban,HR Executive,146745,0 +6419,Female,57,Bachelors,0,14,44,78,10,1.0,3,38,Urban,Data Analyst,24305,0 +6420,Male,54,High School,0,54,23,16,60,8.0,0,1,Urban,ML Engineer,64561,0 +6421,Other,27,Bachelors,8,42,44,51,84,2.0,5,6,Urban,ML Engineer,92380,0 +6422,Male,24,Bachelors,10,2,88,66,70,9.0,1,40,Rural,ML Engineer,145441,0 +6423,Male,29,Masters,4,53,87,69,31,5.0,2,2,Urban,Data Analyst,75169,0 +6424,Male,22,Diploma,19,85,59,61,77,8.0,2,78,Semi-Urban,ML Engineer,133278,1 +6425,Male,47,High School,8,76,62,43,72,4.0,6,90,Rural,Data Analyst,78036,1 +6426,Male,52,Diploma,7,69,98,36,25,5.0,7,98,Rural,Software Engineer,26619,1 +6427,Female,40,Diploma,0,46,76,1,75,7.0,0,62,Urban,Software Engineer,41678,0 +6428,Female,41,Bachelors,7,50,9,91,98,4.0,2,23,Urban,Manager,76373,0 +6429,Male,37,Bachelors,10,30,61,18,89,4.0,0,80,Urban,HR Executive,140376,0 +6430,Male,33,Bachelors,17,23,19,82,33,0.0,5,99,Rural,ML Engineer,144421,0 +6431,Female,44,Diploma,4,18,64,34,52,2.0,1,29,Rural,HR Executive,22055,0 +6432,Female,26,Masters,16,82,39,71,12,1.0,4,4,Urban,Manager,123414,0 +6433,Female,46,Bachelors,13,12,99,97,51,2.0,1,52,Rural,Data Analyst,124109,1 +6434,Male,52,Bachelors,0,93,37,2,77,4.0,3,13,Rural,Manager,113044,0 +6435,Female,22,Bachelors,7,68,46,91,73,1.0,2,4,Urban,Manager,66552,0 +6436,Male,25,Bachelors,1,65,69,15,38,4.0,6,37,Urban,ML Engineer,92281,0 +6437,Male,25,PhD,11,41,55,17,85,3.0,0,21,Semi-Urban,Data Analyst,84469,0 +6438,Male,34,Bachelors,2,34,82,84,97,7.0,1,34,Urban,HR Executive,137560,0 +6439,Male,26,PhD,2,3,48,78,28,9.0,2,71,Urban,Data Analyst,136338,0 +6440,Male,40,Masters,7,82,79,52,92,7.0,3,29,Semi-Urban,Software Engineer,62397,1 +6441,Male,54,Bachelors,14,22,33,45,71,7.0,1,1,Rural,Manager,85780,0 +6442,Male,37,Bachelors,15,24,50,99,20,1.0,1,69,Rural,Data Analyst,124419,1 +6443,Female,23,Diploma,7,82,13,60,79,3.0,1,94,Semi-Urban,Data Analyst,108777,1 +6444,Male,53,Bachelors,17,55,55,30,69,3.0,1,27,Semi-Urban,HR Executive,132439,0 +6445,Male,29,Bachelors,4,81,97,72,88,1.0,7,58,Urban,Manager,72602,1 +6446,Male,26,High School,1,17,82,28,51,4.0,5,73,Urban,Software Engineer,102709,0 +6447,Other,29,Masters,7,77,34,73,85,4.0,7,25,Semi-Urban,Data Analyst,136237,0 +6448,Male,38,Bachelors,5,86,2,73,18,3.0,0,76,Urban,Manager,110427,1 +6449,Male,28,Diploma,17,86,92,49,3,0.0,4,16,Semi-Urban,Software Engineer,108074,1 +6450,Male,37,Diploma,4,16,2,2,81,0.0,4,50,Semi-Urban,Data Analyst,69040,0 +6451,Female,45,Bachelors,10,97,34,74,30,9.0,3,36,Semi-Urban,ML Engineer,102037,1 +6452,Other,45,High School,17,78,37,39,44,7.0,1,19,Rural,Manager,92452,0 +6453,Male,29,Bachelors,5,88,89,91,99,9.0,7,84,Urban,ML Engineer,48315,1 +6454,Male,29,Diploma,19,51,81,16,3,4.0,4,31,Semi-Urban,Software Engineer,105515,0 +6455,Female,24,PhD,10,59,28,37,72,4.0,7,49,Urban,ML Engineer,108328,0 +6456,Male,35,Bachelors,15,18,86,22,5,3.0,1,55,Semi-Urban,Software Engineer,57303,0 +6457,Female,30,Bachelors,12,14,77,44,6,4.0,2,56,Semi-Urban,ML Engineer,55672,0 +6458,Male,35,Masters,1,54,76,60,51,7.0,1,41,Rural,HR Executive,97630,0 +6459,Male,37,Masters,11,83,87,8,34,0.0,1,77,Urban,Data Analyst,146465,1 +6460,Male,58,Diploma,7,11,87,84,88,7.0,6,3,Semi-Urban,HR Executive,104636,0 +6461,Male,57,High School,6,84,74,44,90,3.0,5,76,Semi-Urban,Manager,47489,1 +6462,Female,23,Masters,5,97,77,8,68,8.0,2,50,Rural,ML Engineer,70700,0 +6463,Female,39,Diploma,15,4,36,34,91,4.0,0,52,Semi-Urban,ML Engineer,26096,0 +6464,Male,41,Bachelors,5,15,74,46,10,2.0,3,81,Rural,Manager,124625,0 +6465,Female,59,Diploma,10,80,71,40,49,1.0,2,35,Urban,HR Executive,81713,0 +6466,Male,21,Masters,14,94,86,8,24,1.0,3,96,Rural,Data Analyst,34131,1 +6467,Male,44,Bachelors,16,32,92,74,44,4.0,4,61,Semi-Urban,Software Engineer,88551,1 +6468,Male,38,Masters,6,57,84,82,74,6.0,6,15,Urban,ML Engineer,25276,1 +6469,Female,37,Diploma,4,31,28,9,78,7.0,6,96,Urban,Data Analyst,74949,0 +6470,Female,52,PhD,10,40,96,21,90,9.0,6,35,Urban,HR Executive,81783,0 +6471,Female,49,PhD,1,44,27,21,66,0.0,1,26,Urban,Software Engineer,40141,0 +6472,Female,22,PhD,4,68,78,34,67,1.0,0,93,Urban,HR Executive,55821,1 +6473,Female,23,High School,12,85,64,41,12,1.0,5,42,Urban,HR Executive,100466,0 +6474,Other,27,Masters,14,67,7,90,91,5.0,4,9,Semi-Urban,Data Analyst,88395,0 +6475,Female,42,High School,14,68,36,14,38,6.0,1,25,Urban,ML Engineer,33921,0 +6476,Female,58,Bachelors,0,90,68,61,93,8.0,0,75,Urban,ML Engineer,149942,1 +6477,Male,28,Bachelors,16,69,11,86,19,9.0,2,1,Rural,Software Engineer,131459,0 +6478,Male,55,Bachelors,7,47,50,17,65,9.0,3,39,Urban,Manager,123690,0 +6479,Male,24,High School,2,98,18,79,93,1.0,6,65,Urban,Software Engineer,87664,1 +6480,Male,41,Masters,10,53,69,68,54,6.0,2,28,Semi-Urban,Data Analyst,105939,0 +6481,Male,57,Diploma,13,59,85,55,53,5.0,7,15,Semi-Urban,HR Executive,78204,0 +6482,Male,35,Masters,12,47,39,33,61,0.0,5,31,Semi-Urban,Manager,148160,0 +6483,Female,48,Diploma,8,26,32,89,48,7.0,3,63,Urban,HR Executive,133182,0 +6484,Male,25,Masters,19,24,74,36,22,4.0,0,28,Urban,ML Engineer,94839,0 +6485,Male,53,Masters,2,37,49,15,74,4.0,7,58,Urban,ML Engineer,55767,0 +6486,Male,24,Diploma,13,6,16,78,48,8.0,1,78,Urban,HR Executive,32585,0 +6487,Other,25,Bachelors,19,64,88,53,43,0.0,6,3,Urban,Manager,84555,0 +6488,Male,23,Bachelors,6,94,24,29,91,8.0,3,29,Rural,Data Analyst,120465,0 +6489,Male,41,Bachelors,4,12,74,64,55,6.0,2,85,Semi-Urban,ML Engineer,89900,1 +6490,Female,26,High School,0,99,77,48,13,8.0,1,51,Urban,ML Engineer,100033,1 +6491,Female,31,Bachelors,6,56,16,4,39,5.0,4,50,Semi-Urban,Manager,139517,0 +6492,Male,45,PhD,4,23,18,41,70,6.0,6,5,Semi-Urban,Software Engineer,112571,0 +6493,Male,28,Masters,16,2,32,42,88,4.0,3,74,Semi-Urban,Data Analyst,75587,0 +6494,Male,48,High School,17,76,79,38,31,1.0,1,0,Urban,Data Analyst,39148,0 +6495,Other,21,High School,11,50,7,62,52,0.0,3,81,Urban,Data Analyst,73517,0 +6496,Male,46,High School,19,97,0,25,55,5.0,3,61,Urban,Data Analyst,62082,0 +6497,Male,52,PhD,19,67,42,93,78,8.0,5,72,Urban,Software Engineer,117138,1 +6498,Male,24,Bachelors,9,84,10,75,44,5.0,6,47,Semi-Urban,Data Analyst,138497,0 +6499,Male,44,Bachelors,4,28,81,92,80,0.0,3,77,Urban,Data Analyst,108628,1 +6500,Female,54,Bachelors,12,54,31,20,22,7.0,2,20,Rural,Manager,121205,0 +6501,Male,44,Diploma,1,49,63,38,16,6.0,0,87,Semi-Urban,ML Engineer,72219,1 +6502,Male,51,High School,16,38,48,48,16,3.0,2,33,Rural,Manager,126801,0 +6503,Male,29,Diploma,1,63,21,98,87,7.0,2,46,Urban,Software Engineer,145426,0 +6504,Male,35,Masters,18,78,50,0,61,9.0,3,55,Urban,ML Engineer,92967,0 +6505,Male,49,Masters,9,46,71,55,79,9.0,3,87,Urban,Data Analyst,76960,1 +6506,Female,30,High School,14,10,30,93,68,4.0,6,47,Semi-Urban,Manager,132930,0 +6507,Female,33,Bachelors,0,62,30,66,45,9.0,1,35,Urban,HR Executive,96240,0 +6508,Female,22,Bachelors,3,57,31,25,25,9.0,5,96,Semi-Urban,Data Analyst,48741,0 +6509,Female,34,Diploma,14,96,54,87,60,8.0,1,81,Urban,HR Executive,80130,1 +6510,Female,36,Masters,0,91,30,28,40,3.0,3,78,Semi-Urban,Data Analyst,142944,0 +6511,Male,24,Masters,1,43,52,18,3,8.0,7,76,Urban,ML Engineer,86440,0 +6512,Female,42,PhD,13,0,40,9,1,9.0,1,42,Urban,ML Engineer,75244,0 +6513,Female,50,Masters,5,55,23,69,48,1.0,1,16,Semi-Urban,HR Executive,58590,0 +6514,Female,41,Masters,9,53,85,49,97,2.0,4,23,Rural,Manager,90708,0 +6515,Male,28,Bachelors,7,23,87,78,91,8.0,0,51,Urban,ML Engineer,137113,1 +6516,Male,56,Bachelors,7,41,43,73,8,7.0,5,56,Semi-Urban,Data Analyst,133458,0 +6517,Female,35,Masters,16,31,64,22,25,7.0,2,67,Semi-Urban,Software Engineer,49867,0 +6518,Female,30,Masters,8,48,25,54,18,8.0,7,45,Semi-Urban,Data Analyst,21227,0 +6519,Other,52,Bachelors,17,44,86,11,90,6.0,5,75,Rural,ML Engineer,27892,0 +6520,Male,36,Diploma,4,6,44,13,6,4.0,3,58,Semi-Urban,HR Executive,121608,0 +6521,Male,35,PhD,12,5,49,29,13,5.0,7,41,Urban,Manager,122231,0 +6522,Male,59,Masters,5,49,95,57,59,6.0,7,64,Semi-Urban,ML Engineer,140626,1 +6523,Female,59,High School,14,65,73,92,72,6.0,5,7,Semi-Urban,Data Analyst,48061,0 +6524,Male,21,High School,18,57,64,13,33,4.0,5,12,Semi-Urban,Manager,25722,0 +6525,Male,23,PhD,7,32,58,96,96,3.0,0,72,Urban,HR Executive,35216,1 +6526,Other,37,Bachelors,17,11,98,58,75,5.0,2,83,Urban,Data Analyst,140736,1 +6527,Male,32,Bachelors,2,56,73,49,17,5.0,0,2,Urban,Manager,46326,0 +6528,Female,55,Masters,9,95,99,73,3,9.0,3,6,Urban,Software Engineer,34175,1 +6529,Male,22,High School,16,51,47,88,74,6.0,4,5,Urban,ML Engineer,83012,0 +6530,Female,55,Bachelors,8,1,85,69,1,3.0,6,44,Rural,Data Analyst,75249,0 +6531,Male,31,Bachelors,3,31,8,82,70,8.0,2,80,Rural,HR Executive,101571,0 +6532,Female,47,High School,15,87,97,22,21,6.0,2,65,Semi-Urban,Manager,73007,1 +6533,Female,39,Diploma,3,5,18,44,2,2.0,2,87,Semi-Urban,HR Executive,58253,0 +6534,Male,40,Bachelors,10,4,37,11,80,0.0,5,24,Urban,Software Engineer,133729,0 +6535,Male,31,High School,7,17,53,85,20,0.0,0,90,Urban,ML Engineer,47732,1 +6536,Male,48,Masters,14,54,76,9,26,7.0,0,51,Rural,Data Analyst,51770,0 +6537,Female,37,Masters,16,93,43,54,45,4.0,5,45,Urban,HR Executive,140415,0 +6538,Female,32,Masters,12,12,95,62,1,8.0,3,8,Urban,Data Analyst,58545,0 +6539,Male,25,High School,1,28,2,75,15,0.0,3,35,Urban,HR Executive,38980,0 +6540,Female,59,Bachelors,1,86,93,35,58,7.0,5,79,Urban,Software Engineer,111171,1 +6541,Male,46,Masters,6,24,36,0,1,3.0,3,50,Semi-Urban,ML Engineer,51803,0 +6542,Female,43,Bachelors,3,36,98,37,55,2.0,0,77,Semi-Urban,Data Analyst,132384,1 +6543,Other,32,High School,1,97,23,88,88,1.0,5,66,Semi-Urban,Manager,100938,1 +6544,Male,22,Bachelors,0,25,52,81,65,1.0,7,1,Rural,ML Engineer,139781,0 +6545,Male,27,Bachelors,5,98,88,0,24,3.0,3,34,Urban,Data Analyst,50154,0 +6546,Male,32,Bachelors,7,38,38,44,42,6.0,6,76,Urban,Data Analyst,110985,0 +6547,Male,31,Masters,17,4,74,23,16,3.0,1,86,Urban,Data Analyst,139324,0 +6548,Male,44,Diploma,0,33,61,75,18,4.0,2,2,Semi-Urban,Manager,62520,0 +6549,Male,41,Bachelors,10,30,90,91,65,9.0,3,32,Rural,HR Executive,41042,1 +6550,Male,43,Bachelors,11,15,51,99,67,2.0,1,44,Urban,ML Engineer,53438,0 +6551,Male,32,Bachelors,0,25,31,0,99,5.0,5,34,Urban,HR Executive,102025,0 +6552,Male,48,High School,10,2,22,11,56,9.0,1,96,Rural,HR Executive,50006,0 +6553,Male,54,Bachelors,12,47,11,61,28,7.0,3,33,Semi-Urban,HR Executive,43357,0 +6554,Male,57,Masters,16,61,94,79,10,0.0,1,34,Urban,HR Executive,140799,1 +6555,Female,21,High School,2,24,99,61,39,7.0,4,64,Urban,Software Engineer,124549,1 +6556,Female,26,Diploma,9,20,7,67,34,0.0,2,32,Urban,HR Executive,72433,0 +6557,Male,24,Masters,3,42,33,79,25,4.0,1,88,Urban,Data Analyst,100619,1 +6558,Male,33,Bachelors,7,91,70,46,6,1.0,4,36,Semi-Urban,HR Executive,114470,1 +6559,Female,39,Bachelors,17,18,71,54,29,0.0,3,85,Rural,ML Engineer,46869,0 +6560,Other,41,High School,3,48,57,71,81,5.0,2,99,Urban,Manager,20096,1 +6561,Male,54,Bachelors,16,61,64,31,69,2.0,5,21,Semi-Urban,Manager,60963,0 +6562,Male,45,Masters,0,51,67,46,41,8.0,0,4,Urban,Software Engineer,53926,0 +6563,Male,43,Diploma,19,4,60,72,13,4.0,0,7,Rural,ML Engineer,99938,0 +6564,Male,43,Bachelors,19,67,13,85,42,1.0,7,92,Urban,Software Engineer,70661,1 +6565,Male,26,Diploma,16,62,25,83,85,6.0,2,89,Semi-Urban,Manager,36703,1 +6566,Male,38,Masters,6,40,14,32,5,7.0,5,39,Urban,ML Engineer,131244,0 +6567,Female,23,Bachelors,5,19,54,98,80,8.0,4,31,Semi-Urban,Manager,60597,0 +6568,Male,54,Diploma,10,19,79,10,17,0.0,0,41,Rural,Data Analyst,37003,0 +6569,Male,26,Diploma,7,86,49,9,25,9.0,4,74,Semi-Urban,HR Executive,34290,0 +6570,Male,54,Masters,11,97,34,83,52,2.0,1,95,Urban,HR Executive,57184,1 +6571,Male,22,Diploma,4,24,37,17,99,2.0,1,18,Semi-Urban,Data Analyst,52922,0 +6572,Male,35,Bachelors,11,98,21,22,19,0.0,5,22,Urban,HR Executive,42489,0 +6573,Male,51,Diploma,7,54,92,1,56,8.0,4,12,Rural,Software Engineer,91277,0 +6574,Female,53,PhD,15,66,97,87,78,4.0,1,85,Semi-Urban,Software Engineer,140053,1 +6575,Male,22,Bachelors,4,13,23,58,64,4.0,0,36,Rural,HR Executive,44965,0 +6576,Female,49,Bachelors,13,25,7,51,15,5.0,5,54,Rural,Software Engineer,32180,0 +6577,Female,28,Diploma,6,96,81,5,84,7.0,5,76,Rural,Manager,58439,1 +6578,Male,24,Bachelors,9,19,24,5,33,3.0,3,21,Urban,HR Executive,105106,0 +6579,Male,21,Diploma,3,21,90,78,69,7.0,6,44,Urban,Software Engineer,95257,0 +6580,Male,21,Masters,9,17,11,64,15,8.0,4,35,Urban,Manager,128788,0 +6581,Female,49,Bachelors,16,52,46,51,45,2.0,0,18,Semi-Urban,Data Analyst,83339,0 +6582,Female,58,High School,7,79,3,29,47,8.0,5,21,Urban,Data Analyst,106152,0 +6583,Female,45,High School,18,12,12,52,83,5.0,2,3,Rural,Data Analyst,97005,0 +6584,Male,38,Masters,10,97,74,5,56,5.0,5,51,Urban,HR Executive,99255,0 +6585,Female,32,Masters,9,99,23,37,17,1.0,1,17,Urban,Data Analyst,142214,0 +6586,Male,31,Masters,17,19,4,29,75,1.0,5,61,Semi-Urban,Software Engineer,27843,0 +6587,Male,25,High School,2,14,77,11,61,0.0,7,37,Rural,ML Engineer,47040,0 +6588,Male,27,Masters,17,39,93,67,9,6.0,3,88,Rural,ML Engineer,35407,1 +6589,Male,57,Masters,11,69,35,82,74,8.0,7,70,Urban,HR Executive,67270,1 +6590,Female,55,Diploma,11,49,84,83,27,0.0,3,69,Semi-Urban,Software Engineer,29305,1 +6591,Male,53,High School,15,3,51,41,81,9.0,4,46,Semi-Urban,ML Engineer,39528,0 +6592,Male,29,Bachelors,13,23,40,36,50,2.0,0,50,Urban,Data Analyst,97215,0 +6593,Male,37,High School,0,54,40,30,55,3.0,5,60,Semi-Urban,Data Analyst,23235,0 +6594,Female,23,Bachelors,17,24,25,75,52,8.0,3,83,Urban,HR Executive,66621,0 +6595,Female,37,Bachelors,10,71,26,72,20,3.0,2,55,Urban,Manager,102531,0 +6596,Male,59,Bachelors,3,46,41,19,69,0.0,3,89,Rural,Software Engineer,76448,0 +6597,Male,33,High School,18,89,37,42,54,0.0,0,73,Semi-Urban,Software Engineer,45574,1 +6598,Male,23,Bachelors,9,21,6,34,99,1.0,2,90,Rural,Software Engineer,79640,0 +6599,Female,39,Masters,14,60,29,83,7,1.0,1,53,Rural,Software Engineer,48510,0 +6600,Male,57,Bachelors,0,96,39,83,40,1.0,3,9,Urban,HR Executive,24139,0 +6601,Male,26,Diploma,19,52,24,36,24,5.0,2,57,Urban,Data Analyst,81508,0 +6602,Male,54,PhD,5,81,64,80,38,4.0,0,15,Semi-Urban,HR Executive,96068,1 +6603,Male,55,High School,12,66,60,17,51,4.0,3,48,Urban,Software Engineer,30740,0 +6604,Female,59,High School,13,55,91,50,64,8.0,7,53,Urban,Manager,146216,1 +6605,Male,34,High School,9,58,83,84,98,5.0,0,50,Rural,Manager,107880,1 +6606,Male,32,Masters,12,33,33,17,33,4.0,5,42,Rural,Data Analyst,85005,0 +6607,Male,48,Bachelors,10,73,22,44,27,9.0,1,58,Semi-Urban,Manager,40582,0 +6608,Male,59,High School,18,11,58,47,26,2.0,6,16,Urban,Manager,25892,0 +6609,Female,22,Bachelors,9,61,50,41,79,1.0,7,16,Rural,ML Engineer,90225,0 +6610,Male,59,Bachelors,6,32,18,71,32,3.0,0,92,Urban,Software Engineer,143650,0 +6611,Female,58,Bachelors,5,55,22,65,2,0.0,2,77,Urban,HR Executive,23623,0 +6612,Female,45,High School,11,47,98,18,77,3.0,4,15,Urban,Manager,66077,0 +6613,Male,47,Diploma,13,56,34,16,84,1.0,1,82,Urban,ML Engineer,47824,0 +6614,Male,54,PhD,9,37,83,90,72,5.0,7,91,Semi-Urban,ML Engineer,80964,1 +6615,Male,48,High School,9,72,17,77,1,7.0,7,35,Urban,ML Engineer,54695,0 +6616,Female,47,Bachelors,7,55,43,90,18,6.0,0,86,Rural,ML Engineer,69801,1 +6617,Male,29,Bachelors,7,94,12,3,67,9.0,0,8,Urban,Manager,92136,0 +6618,Male,49,Diploma,16,65,46,43,40,3.0,6,49,Rural,ML Engineer,103994,0 +6619,Male,28,Bachelors,0,17,62,13,60,1.0,5,73,Rural,HR Executive,24701,0 +6620,Female,59,Masters,12,36,79,95,0,9.0,1,1,Urban,Software Engineer,137058,0 +6621,Male,22,Bachelors,15,54,4,93,10,0.0,4,12,Urban,Software Engineer,62798,0 +6622,Male,37,Diploma,9,55,96,24,14,6.0,5,43,Urban,Software Engineer,82287,0 +6623,Male,59,Bachelors,11,97,73,92,60,9.0,0,46,Semi-Urban,Manager,64459,1 +6624,Male,58,Diploma,5,1,53,79,34,7.0,4,32,Rural,HR Executive,31168,0 +6625,Female,56,Diploma,1,12,34,30,32,4.0,1,43,Urban,HR Executive,52047,0 +6626,Male,34,Masters,2,67,83,31,86,0.0,1,8,Urban,ML Engineer,97116,0 +6627,Female,43,Bachelors,16,26,46,9,35,5.0,1,81,Urban,Manager,48134,0 +6628,Female,21,Bachelors,8,58,30,30,14,6.0,5,3,Semi-Urban,Data Analyst,114061,0 +6629,Male,21,Diploma,10,69,80,39,37,9.0,0,95,Urban,ML Engineer,149677,1 +6630,Female,23,Bachelors,18,72,10,27,7,0.0,4,36,Semi-Urban,ML Engineer,102098,0 +6631,Male,43,High School,15,80,10,94,37,9.0,6,85,Urban,Data Analyst,86095,1 +6632,Male,48,Bachelors,2,8,53,65,84,2.0,1,26,Rural,Data Analyst,32995,0 +6633,Female,36,Bachelors,1,38,43,74,79,7.0,1,19,Urban,ML Engineer,34251,0 +6634,Male,49,Diploma,9,38,5,42,98,2.0,1,59,Semi-Urban,Software Engineer,123851,0 +6635,Female,53,Bachelors,18,54,91,79,68,5.0,4,9,Urban,HR Executive,50162,0 +6636,Male,52,Diploma,18,52,56,31,83,8.0,4,5,Semi-Urban,ML Engineer,121564,0 +6637,Female,43,Diploma,2,32,64,0,84,7.0,7,83,Urban,Data Analyst,32680,0 +6638,Male,53,Masters,15,96,72,71,51,3.0,7,94,Urban,Manager,45922,1 +6639,Male,53,Bachelors,16,82,48,10,16,9.0,3,89,Urban,Software Engineer,45460,0 +6640,Male,58,High School,4,93,47,48,51,1.0,4,47,Urban,ML Engineer,22979,1 +6641,Female,23,High School,11,10,95,24,92,2.0,5,82,Semi-Urban,HR Executive,60800,0 +6642,Female,54,Masters,10,97,70,15,62,1.0,7,93,Urban,Data Analyst,58437,1 +6643,Male,48,Bachelors,9,51,30,69,93,7.0,3,45,Rural,Data Analyst,86249,0 +6644,Female,28,Bachelors,15,10,28,97,0,5.0,7,67,Urban,Manager,107977,0 +6645,Male,29,Bachelors,7,24,30,31,99,4.0,3,92,Urban,HR Executive,107577,0 +6646,Male,25,Bachelors,10,9,88,68,62,4.0,1,27,Urban,Manager,106191,0 +6647,Female,51,Masters,3,57,21,36,20,5.0,2,25,Urban,Software Engineer,86673,0 +6648,Female,55,High School,6,62,96,45,7,3.0,1,54,Rural,ML Engineer,112730,1 +6649,Female,55,Bachelors,12,51,0,48,51,3.0,7,51,Rural,Data Analyst,28141,0 +6650,Female,25,Masters,14,86,96,47,90,0.0,6,46,Rural,Manager,97040,1 +6651,Male,53,PhD,12,17,33,33,15,3.0,1,97,Urban,HR Executive,87044,0 +6652,Female,33,Masters,6,24,51,34,48,4.0,2,82,Semi-Urban,HR Executive,119548,0 +6653,Male,45,Masters,13,90,5,28,1,0.0,3,4,Urban,Data Analyst,79184,0 +6654,Male,44,Bachelors,0,23,44,61,9,6.0,3,3,Rural,Data Analyst,40312,0 +6655,Male,31,Bachelors,15,16,1,22,66,0.0,6,78,Urban,Data Analyst,67857,0 +6656,Male,39,Bachelors,16,99,65,65,14,3.0,3,74,Urban,ML Engineer,51355,1 +6657,Male,31,Bachelors,9,52,8,98,92,3.0,0,1,Urban,Software Engineer,60204,0 +6658,Male,53,Masters,17,4,83,40,19,9.0,0,22,Rural,Manager,60224,0 +6659,Male,50,Bachelors,18,11,48,2,9,9.0,0,75,Rural,Software Engineer,82114,0 +6660,Male,34,Diploma,3,40,26,93,20,1.0,4,44,Semi-Urban,Software Engineer,102073,0 +6661,Male,21,Diploma,3,58,20,86,73,0.0,4,8,Semi-Urban,Data Analyst,72590,0 +6662,Male,51,Bachelors,7,41,49,71,54,2.0,6,51,Urban,Manager,53125,0 +6663,Male,23,Diploma,13,81,73,67,1,5.0,4,74,Urban,ML Engineer,83810,1 +6664,Female,45,Masters,3,28,8,3,53,9.0,7,15,Semi-Urban,ML Engineer,64070,0 +6665,Female,45,Bachelors,3,86,47,6,96,8.0,1,22,Rural,HR Executive,99336,0 +6666,Female,38,PhD,19,97,21,96,69,0.0,6,54,Rural,Software Engineer,64941,1 +6667,Male,54,High School,6,54,56,28,97,9.0,6,44,Urban,HR Executive,23618,0 +6668,Female,34,Bachelors,6,24,43,38,59,2.0,2,86,Urban,Data Analyst,138925,0 +6669,Male,47,Bachelors,7,76,66,41,71,5.0,1,72,Semi-Urban,Manager,59848,1 +6670,Male,51,Masters,10,24,54,41,26,7.0,3,52,Urban,ML Engineer,85693,0 +6671,Male,22,Diploma,16,33,56,2,54,2.0,2,37,Rural,Data Analyst,75895,0 +6672,Female,52,Masters,15,30,57,88,77,8.0,4,91,Rural,ML Engineer,73204,1 +6673,Male,57,Masters,18,9,69,57,23,4.0,2,70,Rural,Manager,98993,0 +6674,Male,54,Masters,8,14,84,68,62,3.0,3,73,Rural,Manager,53587,1 +6675,Male,54,High School,9,89,19,8,72,5.0,1,69,Urban,Manager,21078,0 +6676,Female,50,High School,7,93,21,78,0,7.0,3,56,Urban,Data Analyst,138828,1 +6677,Female,53,High School,8,10,33,14,97,3.0,3,12,Urban,HR Executive,76079,0 +6678,Male,44,Masters,12,63,84,41,11,0.0,4,32,Urban,ML Engineer,39656,0 +6679,Male,53,Bachelors,1,76,61,47,69,9.0,3,75,Urban,Manager,123966,1 +6680,Male,46,High School,19,18,69,53,27,9.0,0,70,Rural,Data Analyst,142928,0 +6681,Female,56,Masters,6,24,14,78,28,7.0,1,33,Semi-Urban,HR Executive,90222,0 +6682,Male,26,Masters,16,15,61,42,17,2.0,1,33,Urban,Data Analyst,43755,0 +6683,Female,37,Diploma,9,50,60,65,55,1.0,0,50,Urban,HR Executive,118905,0 +6684,Male,44,Masters,3,95,90,9,70,4.0,0,15,Urban,Data Analyst,89517,0 +6685,Female,36,High School,13,18,50,63,22,0.0,6,71,Urban,Software Engineer,51567,0 +6686,Male,44,Diploma,6,88,62,6,39,3.0,6,27,Urban,HR Executive,23334,0 +6687,Male,25,Bachelors,11,92,77,28,53,0.0,4,1,Rural,Data Analyst,89160,0 +6688,Male,44,Bachelors,14,18,2,0,90,4.0,7,98,Urban,Manager,101264,0 +6689,Male,46,Masters,10,51,0,78,36,7.0,4,90,Semi-Urban,Manager,49366,0 +6690,Male,40,Masters,14,43,43,71,75,7.0,1,68,Semi-Urban,Data Analyst,96842,0 +6691,Female,48,Bachelors,16,56,52,46,31,5.0,1,7,Urban,Software Engineer,116059,0 +6692,Male,40,High School,7,7,28,55,48,9.0,3,87,Rural,Data Analyst,127601,0 +6693,Female,49,Bachelors,2,85,63,67,82,3.0,2,22,Rural,HR Executive,130468,0 +6694,Female,54,High School,14,58,14,37,80,3.0,1,49,Semi-Urban,Software Engineer,146367,0 +6695,Male,48,High School,14,28,2,47,55,7.0,7,81,Urban,Software Engineer,83104,0 +6696,Female,46,High School,7,21,95,23,6,3.0,5,57,Urban,Manager,91290,0 +6697,Female,52,High School,15,47,72,50,42,1.0,1,56,Urban,ML Engineer,41806,0 +6698,Male,41,High School,11,66,54,99,21,1.0,7,5,Urban,Data Analyst,112549,0 +6699,Female,38,High School,4,56,53,80,61,2.0,7,23,Semi-Urban,ML Engineer,129980,0 +6700,Male,32,Masters,10,96,37,50,95,2.0,3,74,Rural,ML Engineer,30122,1 +6701,Male,55,Masters,13,55,20,23,91,4.0,1,79,Urban,ML Engineer,71870,0 +6702,Female,42,High School,8,77,34,35,67,1.0,6,28,Urban,ML Engineer,138470,0 +6703,Male,49,Diploma,8,39,60,62,3,7.0,6,32,Urban,Manager,75657,0 +6704,Male,39,Bachelors,9,94,94,81,32,7.0,4,48,Urban,HR Executive,108083,1 +6705,Male,38,Masters,17,32,75,41,12,3.0,5,80,Urban,Software Engineer,106216,0 +6706,Female,38,Masters,16,62,11,77,55,5.0,0,63,Semi-Urban,Manager,127920,0 +6707,Female,36,Bachelors,12,5,3,27,44,0.0,5,71,Urban,Data Analyst,122365,0 +6708,Male,39,Masters,18,33,69,71,56,1.0,5,17,Urban,ML Engineer,44062,0 +6709,Female,29,High School,14,4,89,20,1,2.0,3,87,Rural,ML Engineer,133856,0 +6710,Female,53,Bachelors,10,88,78,74,69,2.0,1,3,Urban,ML Engineer,87302,1 +6711,Male,33,Bachelors,11,34,88,47,34,5.0,4,99,Urban,Software Engineer,127657,1 +6712,Male,31,PhD,4,96,78,90,23,1.0,0,95,Urban,Manager,111356,1 +6713,Female,53,Masters,18,40,47,12,19,3.0,7,38,Semi-Urban,Software Engineer,123779,0 +6714,Female,57,Bachelors,16,46,20,22,74,0.0,7,23,Rural,Data Analyst,49931,0 +6715,Female,50,Diploma,3,86,54,39,74,4.0,6,68,Urban,HR Executive,58509,1 +6716,Male,59,Bachelors,18,94,71,17,19,2.0,5,92,Urban,ML Engineer,106888,1 +6717,Male,29,Diploma,16,0,99,66,95,8.0,2,25,Urban,Data Analyst,124505,0 +6718,Male,43,PhD,15,61,51,56,90,9.0,2,79,Rural,ML Engineer,48294,1 +6719,Male,44,Bachelors,10,63,62,87,74,4.0,0,33,Semi-Urban,ML Engineer,53510,1 +6720,Male,52,Bachelors,19,83,60,10,28,3.0,7,29,Semi-Urban,Manager,89701,0 +6721,Female,58,High School,18,1,72,58,77,3.0,1,31,Urban,Manager,70634,0 +6722,Male,24,High School,7,4,95,63,22,8.0,7,61,Urban,ML Engineer,39858,0 +6723,Female,47,Bachelors,3,17,44,52,38,8.0,4,75,Urban,ML Engineer,145449,0 +6724,Male,31,Diploma,16,80,83,24,91,9.0,4,84,Urban,Manager,44889,1 +6725,Male,41,Bachelors,11,10,12,54,28,4.0,7,35,Urban,HR Executive,57895,0 +6726,Male,34,Diploma,12,47,67,90,94,6.0,4,70,Urban,Data Analyst,67926,1 +6727,Male,38,Bachelors,11,40,6,22,2,2.0,7,74,Semi-Urban,HR Executive,103704,0 +6728,Male,44,Diploma,5,1,20,8,57,2.0,2,16,Urban,Data Analyst,75680,0 +6729,Other,40,Diploma,1,90,47,75,10,0.0,4,53,Urban,Software Engineer,129104,1 +6730,Female,46,Bachelors,14,46,22,0,27,0.0,4,35,Urban,Manager,52318,0 +6731,Male,51,High School,3,20,23,98,40,5.0,6,64,Urban,Manager,112196,0 +6732,Male,36,Bachelors,15,13,41,77,39,7.0,7,74,Urban,Manager,21408,0 +6733,Female,59,Masters,14,36,35,16,33,4.0,0,78,Urban,Software Engineer,54926,0 +6734,Male,39,Bachelors,1,64,16,45,34,4.0,3,97,Urban,ML Engineer,51252,0 +6735,Male,27,Bachelors,19,86,9,75,24,6.0,4,59,Urban,Data Analyst,59992,0 +6736,Male,36,High School,11,80,12,33,62,8.0,7,1,Urban,Software Engineer,79993,0 +6737,Female,44,Diploma,16,89,6,33,75,7.0,6,86,Rural,Software Engineer,62643,0 +6738,Male,26,Masters,12,22,9,37,84,7.0,0,32,Urban,HR Executive,132826,0 +6739,Male,36,Bachelors,16,49,79,15,11,6.0,4,12,Urban,Manager,123579,0 +6740,Female,56,Masters,7,25,11,2,79,1.0,3,82,Urban,HR Executive,63352,0 +6741,Male,59,Bachelors,16,22,5,11,50,4.0,0,37,Semi-Urban,ML Engineer,87619,0 +6742,Male,35,Bachelors,8,98,54,18,71,0.0,3,27,Semi-Urban,ML Engineer,124069,0 +6743,Male,24,Bachelors,9,50,14,56,73,2.0,3,15,Urban,Data Analyst,116190,0 +6744,Female,22,Masters,7,23,90,24,40,1.0,6,21,Urban,HR Executive,72009,0 +6745,Male,34,Bachelors,8,99,60,73,63,6.0,3,47,Urban,Software Engineer,124139,1 +6746,Other,42,Diploma,16,88,28,21,18,9.0,7,95,Urban,Software Engineer,38801,0 +6747,Female,22,Masters,8,96,78,58,94,9.0,2,96,Rural,Manager,59324,1 +6748,Male,40,High School,15,3,21,2,46,3.0,7,19,Semi-Urban,HR Executive,68788,0 +6749,Other,24,Diploma,8,21,62,53,3,9.0,0,51,Urban,HR Executive,103269,0 +6750,Male,54,Bachelors,13,15,15,33,82,2.0,6,65,Urban,Data Analyst,92369,0 +6751,Male,38,Bachelors,4,97,45,68,30,3.0,6,1,Urban,ML Engineer,43044,0 +6752,Male,40,Masters,3,1,33,6,75,4.0,6,25,Urban,ML Engineer,54441,0 +6753,Male,46,Diploma,3,49,0,39,21,2.0,0,70,Urban,Data Analyst,128519,0 +6754,Male,27,High School,1,49,90,83,73,0.0,6,51,Semi-Urban,ML Engineer,103630,1 +6755,Male,39,PhD,15,45,24,97,28,1.0,5,96,Urban,Manager,148512,1 +6756,Male,44,Bachelors,8,66,96,61,0,0.0,0,75,Urban,Manager,106429,1 +6757,Female,31,Diploma,12,16,44,94,99,1.0,0,58,Semi-Urban,ML Engineer,120875,0 +6758,Male,36,Bachelors,11,46,46,1,61,5.0,3,67,Urban,HR Executive,68818,0 +6759,Other,21,Masters,10,46,45,12,72,6.0,0,81,Urban,HR Executive,125675,0 +6760,Male,56,Masters,3,81,34,26,32,9.0,4,45,Semi-Urban,Software Engineer,105441,0 +6761,Male,48,Bachelors,17,35,94,67,99,0.0,3,60,Urban,Data Analyst,149779,1 +6762,Male,33,Diploma,6,12,76,76,56,5.0,1,53,Rural,ML Engineer,39557,0 +6763,Male,31,Masters,14,20,32,33,90,2.0,3,76,Urban,HR Executive,113550,0 +6764,Male,26,Diploma,16,25,72,68,34,4.0,6,35,Urban,Data Analyst,61353,0 +6765,Female,50,Masters,15,44,71,42,59,2.0,2,11,Urban,Manager,45368,0 +6766,Female,57,Bachelors,3,7,65,63,17,8.0,1,66,Urban,Manager,85956,0 +6767,Other,54,Bachelors,17,5,68,74,70,5.0,0,67,Urban,Data Analyst,27102,0 +6768,Male,48,Bachelors,7,3,70,59,97,9.0,0,18,Urban,Software Engineer,71151,0 +6769,Female,29,Bachelors,7,71,79,26,54,5.0,5,90,Urban,ML Engineer,139638,1 +6770,Male,51,Diploma,5,76,74,46,87,9.0,5,30,Rural,Manager,35067,0 +6771,Male,26,Masters,9,72,19,50,50,9.0,1,92,Urban,Software Engineer,102612,0 +6772,Female,26,Bachelors,3,28,11,97,98,1.0,1,29,Urban,ML Engineer,109818,0 +6773,Female,56,Bachelors,1,61,69,50,4,6.0,4,78,Semi-Urban,Manager,48759,1 +6774,Male,40,Bachelors,14,92,36,68,46,4.0,6,86,Urban,ML Engineer,38914,1 +6775,Male,52,Bachelors,3,7,22,86,74,7.0,5,61,Rural,ML Engineer,111163,0 +6776,Male,52,PhD,6,67,42,44,4,2.0,1,53,Urban,HR Executive,144388,0 +6777,Female,25,High School,5,72,58,21,20,8.0,0,70,Semi-Urban,HR Executive,119672,0 +6778,Male,58,Bachelors,10,82,41,86,71,0.0,7,63,Rural,ML Engineer,55980,1 +6779,Other,57,Bachelors,15,4,56,12,13,4.0,5,72,Semi-Urban,HR Executive,137681,0 +6780,Male,30,Bachelors,9,5,83,30,45,8.0,1,50,Urban,Manager,52596,0 +6781,Male,57,Masters,0,78,26,44,15,5.0,5,18,Semi-Urban,ML Engineer,96972,0 +6782,Male,22,Diploma,13,56,37,89,17,2.0,0,55,Urban,Manager,131163,1 +6783,Male,27,Diploma,17,30,67,41,27,6.0,3,20,Urban,Manager,141275,0 +6784,Male,31,Masters,0,75,55,77,79,1.0,3,64,Urban,HR Executive,137116,1 +6785,Female,21,PhD,19,48,69,99,48,2.0,1,62,Rural,Software Engineer,108159,1 +6786,Female,34,High School,2,43,34,83,95,5.0,1,46,Urban,ML Engineer,21315,0 +6787,Female,41,High School,19,38,28,9,66,7.0,3,80,Urban,Software Engineer,54833,0 +6788,Female,26,Masters,9,43,12,49,9,8.0,7,29,Rural,Software Engineer,116457,0 +6789,Female,46,High School,11,20,25,19,77,7.0,6,80,Urban,Manager,140806,0 +6790,Male,37,Bachelors,18,33,8,83,62,0.0,0,36,Rural,Software Engineer,84715,0 +6791,Female,46,Bachelors,9,61,0,73,40,2.0,5,82,Urban,ML Engineer,93826,0 +6792,Male,27,High School,2,68,42,23,88,0.0,4,59,Urban,Data Analyst,120050,0 +6793,Male,21,Masters,4,61,14,8,43,2.0,0,25,Urban,Data Analyst,96662,0 +6794,Male,35,High School,17,55,25,1,59,5.0,2,78,Rural,Software Engineer,98430,0 +6795,Male,51,Bachelors,1,34,5,46,79,0.0,4,28,Semi-Urban,Software Engineer,69732,0 +6796,Male,56,Bachelors,5,10,77,43,22,5.0,2,85,Urban,ML Engineer,115854,0 +6797,Other,26,Diploma,0,27,5,59,67,1.0,5,19,Urban,Software Engineer,94572,0 +6798,Male,39,Bachelors,18,86,91,69,63,5.0,7,33,Urban,HR Executive,35954,1 +6799,Male,26,Bachelors,3,42,77,49,71,7.0,2,75,Rural,Manager,123392,1 +6800,Male,50,Diploma,3,77,5,64,5,8.0,4,75,Rural,Software Engineer,46915,0 +6801,Male,55,Diploma,10,80,22,18,25,3.0,3,12,Rural,Software Engineer,62180,0 +6802,Male,37,Bachelors,5,17,91,36,81,9.0,3,21,Semi-Urban,Manager,37850,0 +6803,Male,36,Bachelors,11,54,66,22,25,2.0,5,26,Rural,Software Engineer,147231,0 +6804,Male,30,Bachelors,8,68,5,42,91,7.0,5,55,Urban,Software Engineer,25208,0 +6805,Male,56,Diploma,13,24,21,64,30,1.0,4,19,Urban,Software Engineer,85501,0 +6806,Female,38,Bachelors,3,65,68,6,19,1.0,3,42,Rural,ML Engineer,32171,0 +6807,Female,30,Bachelors,2,39,5,93,29,2.0,3,98,Rural,Software Engineer,133356,0 +6808,Male,57,Bachelors,11,84,73,63,3,3.0,1,59,Urban,ML Engineer,147698,1 +6809,Male,24,Bachelors,15,69,22,77,87,8.0,5,88,Rural,Manager,70234,1 +6810,Male,28,Bachelors,12,5,76,49,22,1.0,7,81,Urban,Manager,129457,0 +6811,Female,44,Bachelors,12,9,80,79,80,9.0,1,25,Semi-Urban,ML Engineer,141336,0 +6812,Male,54,Diploma,11,41,98,43,95,6.0,2,22,Rural,Software Engineer,50161,0 +6813,Male,32,High School,12,70,25,49,84,5.0,1,26,Rural,Software Engineer,55234,0 +6814,Female,44,Bachelors,3,31,68,80,45,4.0,0,30,Urban,Software Engineer,136820,0 +6815,Male,47,Bachelors,9,90,48,38,70,2.0,6,51,Semi-Urban,Software Engineer,131453,0 +6816,Male,58,Diploma,10,56,71,59,58,6.0,3,10,Semi-Urban,Software Engineer,109094,0 +6817,Male,37,Bachelors,5,28,25,58,88,5.0,5,58,Urban,Manager,30971,0 +6818,Female,36,Masters,19,95,0,7,86,5.0,6,45,Urban,Software Engineer,128801,0 +6819,Female,47,Bachelors,2,9,77,18,2,5.0,2,61,Urban,Manager,31764,0 +6820,Female,55,Diploma,14,53,18,69,33,8.0,6,26,Rural,Software Engineer,108484,0 +6821,Male,46,Bachelors,0,35,21,58,88,7.0,2,24,Semi-Urban,Software Engineer,144686,0 +6822,Male,26,Diploma,14,18,94,65,46,0.0,0,99,Semi-Urban,Manager,138946,1 +6823,Other,21,Diploma,4,21,32,59,83,4.0,1,6,Rural,Manager,24795,0 +6824,Other,56,High School,15,46,81,99,35,1.0,1,66,Urban,Manager,26260,1 +6825,Male,39,Diploma,5,97,17,12,16,7.0,5,79,Rural,Manager,26180,0 +6826,Female,54,Bachelors,0,92,20,89,58,0.0,5,52,Urban,Software Engineer,107049,1 +6827,Male,26,PhD,19,62,15,99,58,8.0,2,21,Semi-Urban,Data Analyst,77759,0 +6828,Male,25,Diploma,3,19,91,13,23,3.0,1,60,Urban,Software Engineer,127847,0 +6829,Female,59,PhD,1,11,14,66,62,0.0,6,17,Rural,Software Engineer,147789,0 +6830,Male,51,Diploma,9,95,35,59,57,9.0,7,59,Semi-Urban,Data Analyst,45433,1 +6831,Female,59,Diploma,4,91,94,83,66,0.0,4,60,Rural,ML Engineer,80853,1 +6832,Male,27,High School,7,78,81,17,95,9.0,0,61,Semi-Urban,ML Engineer,86234,1 +6833,Male,25,PhD,3,51,88,46,29,8.0,4,0,Urban,Data Analyst,39114,0 +6834,Female,55,Bachelors,4,24,28,78,9,0.0,0,88,Rural,Manager,67415,0 +6835,Female,48,Diploma,13,10,49,11,40,8.0,2,57,Rural,HR Executive,69070,0 +6836,Male,47,Bachelors,1,2,34,46,57,4.0,5,79,Urban,HR Executive,42129,0 +6837,Male,26,Bachelors,13,16,55,39,92,2.0,7,14,Semi-Urban,HR Executive,148086,0 +6838,Female,38,Bachelors,1,10,47,1,93,7.0,5,97,Urban,Data Analyst,76208,0 +6839,Male,37,Diploma,12,90,13,46,59,6.0,7,30,Urban,HR Executive,82759,0 +6840,Other,21,Diploma,13,13,55,65,24,7.0,6,89,Rural,ML Engineer,116563,0 +6841,Female,39,Bachelors,5,70,87,55,77,6.0,3,93,Urban,Manager,106468,1 +6842,Male,25,Bachelors,12,66,1,74,72,4.0,1,89,Urban,Software Engineer,36970,0 +6843,Male,30,Bachelors,13,47,49,29,62,0.0,1,75,Urban,HR Executive,111844,0 +6844,Male,30,PhD,1,54,45,42,81,9.0,1,23,Semi-Urban,Software Engineer,82184,0 +6845,Female,44,Bachelors,18,83,98,71,75,9.0,2,85,Urban,HR Executive,47681,1 +6846,Male,22,Bachelors,2,74,78,79,25,5.0,1,89,Rural,Data Analyst,120734,1 +6847,Male,31,High School,19,13,15,29,83,1.0,7,69,Urban,HR Executive,56061,0 +6848,Male,24,Bachelors,8,47,3,23,10,5.0,3,70,Rural,Data Analyst,47254,0 +6849,Male,43,Bachelors,0,8,55,79,1,6.0,6,25,Rural,Manager,102519,0 +6850,Male,27,Bachelors,12,67,84,43,64,3.0,1,46,Semi-Urban,Manager,32127,1 +6851,Male,35,Bachelors,0,80,30,44,68,2.0,1,43,Urban,HR Executive,47833,0 +6852,Female,43,High School,13,9,74,62,76,6.0,5,83,Urban,Data Analyst,48264,0 +6853,Female,55,Bachelors,5,69,90,22,7,6.0,6,3,Urban,Manager,51272,0 +6854,Female,31,Diploma,14,88,30,73,49,6.0,6,84,Urban,HR Executive,122377,1 +6855,Male,59,Bachelors,5,76,25,63,93,1.0,3,81,Urban,Software Engineer,25509,1 +6856,Male,51,Bachelors,0,68,39,61,43,9.0,3,71,Urban,Manager,76801,1 +6857,Female,22,Diploma,3,3,79,59,48,8.0,7,54,Semi-Urban,Manager,84646,0 +6858,Male,30,Bachelors,13,6,87,52,45,5.0,6,63,Semi-Urban,Data Analyst,78075,0 +6859,Female,25,Diploma,3,7,15,14,16,0.0,0,53,Urban,ML Engineer,60399,0 +6860,Female,32,Bachelors,12,23,81,91,8,8.0,2,6,Urban,ML Engineer,118208,0 +6861,Male,38,Bachelors,0,51,48,34,63,2.0,1,94,Urban,HR Executive,47326,0 +6862,Female,48,Bachelors,12,24,21,4,82,3.0,3,13,Semi-Urban,HR Executive,105908,0 +6863,Other,28,Diploma,9,83,47,98,62,8.0,3,70,Semi-Urban,HR Executive,137994,1 +6864,Male,24,Bachelors,1,94,7,6,34,0.0,2,76,Urban,Manager,141522,0 +6865,Male,37,Bachelors,19,35,70,67,18,6.0,2,11,Urban,Manager,84180,0 +6866,Male,49,Bachelors,5,4,30,3,89,4.0,5,3,Rural,Manager,101259,0 +6867,Male,29,PhD,0,48,60,22,59,8.0,2,88,Urban,ML Engineer,114504,0 +6868,Male,34,Diploma,12,16,89,71,58,9.0,4,52,Urban,ML Engineer,147795,0 +6869,Male,29,Bachelors,5,51,99,43,73,0.0,2,58,Semi-Urban,Software Engineer,96340,1 +6870,Other,58,Bachelors,2,74,21,30,37,3.0,5,64,Semi-Urban,ML Engineer,47327,0 +6871,Male,29,Bachelors,8,10,38,70,7,9.0,6,3,Urban,Manager,144554,0 +6872,Male,31,High School,19,18,1,27,57,9.0,1,6,Urban,Manager,82899,0 +6873,Female,42,Bachelors,17,54,73,54,73,1.0,3,91,Urban,Software Engineer,126003,1 +6874,Male,47,Diploma,2,31,50,9,22,8.0,7,19,Urban,Software Engineer,142880,0 +6875,Female,50,Bachelors,8,73,44,36,30,5.0,1,2,Semi-Urban,HR Executive,40114,0 +6876,Male,26,Bachelors,18,0,85,88,8,4.0,4,73,Rural,Software Engineer,88315,1 +6877,Male,53,Masters,7,73,28,66,16,5.0,4,62,Semi-Urban,Manager,83422,0 +6878,Male,42,Diploma,12,1,72,29,20,7.0,5,34,Urban,HR Executive,81456,0 +6879,Female,46,Bachelors,10,98,26,25,33,2.0,5,0,Semi-Urban,Software Engineer,138579,0 +6880,Male,26,High School,11,79,23,59,95,3.0,6,1,Urban,ML Engineer,81626,0 +6881,Female,53,Diploma,13,75,85,15,42,3.0,4,27,Semi-Urban,Software Engineer,55712,0 +6882,Male,30,Bachelors,18,47,23,19,65,3.0,5,14,Urban,Software Engineer,92492,0 +6883,Male,57,High School,18,32,66,79,21,5.0,5,59,Urban,Data Analyst,100521,1 +6884,Male,21,PhD,9,86,21,91,53,1.0,2,5,Semi-Urban,HR Executive,110197,0 +6885,Female,35,High School,6,36,49,89,22,4.0,3,51,Semi-Urban,Manager,71814,0 +6886,Female,43,High School,8,33,98,54,43,8.0,7,65,Rural,HR Executive,116362,1 +6887,Male,32,Bachelors,2,81,20,84,67,7.0,6,1,Rural,Manager,67535,0 +6888,Male,38,High School,4,29,57,74,63,9.0,2,84,Semi-Urban,Data Analyst,68866,1 +6889,Male,36,Diploma,10,35,97,4,22,4.0,0,20,Rural,Manager,37944,0 +6890,Male,47,Masters,12,66,30,81,38,4.0,3,52,Urban,ML Engineer,124588,0 +6891,Male,48,High School,10,3,52,9,7,9.0,6,49,Urban,Software Engineer,21454,0 +6892,Female,29,High School,17,8,43,10,93,7.0,5,24,Urban,HR Executive,37351,0 +6893,Female,40,Masters,13,35,24,52,21,9.0,4,51,Urban,ML Engineer,92964,0 +6894,Male,53,Diploma,16,41,7,87,94,3.0,7,11,Semi-Urban,Data Analyst,93080,0 +6895,Male,46,Masters,10,70,68,90,79,3.0,2,32,Urban,Data Analyst,124466,1 +6896,Female,49,Bachelors,2,6,61,99,36,7.0,4,43,Rural,Manager,128945,0 +6897,Female,49,Masters,11,85,25,66,92,1.0,1,66,Rural,Data Analyst,88631,1 +6898,Male,21,Diploma,3,55,15,73,61,3.0,1,70,Urban,Manager,100450,0 +6899,Male,37,Bachelors,13,63,20,24,10,4.0,3,95,Urban,Data Analyst,31207,0 +6900,Male,37,High School,14,72,38,14,18,3.0,6,8,Urban,Manager,31370,0 +6901,Male,52,Bachelors,1,25,73,14,18,2.0,5,41,Urban,Manager,103217,0 +6902,Male,37,High School,13,90,35,26,40,7.0,6,30,Urban,ML Engineer,36309,0 +6903,Male,57,Bachelors,6,74,1,74,61,9.0,7,35,Rural,Data Analyst,96585,0 +6904,Female,32,Bachelors,12,27,0,91,20,9.0,4,0,Semi-Urban,Software Engineer,115971,0 +6905,Male,31,Bachelors,6,11,43,20,0,4.0,0,0,Rural,HR Executive,20874,0 +6906,Male,48,Masters,15,77,89,48,33,6.0,7,52,Semi-Urban,Manager,108106,1 +6907,Male,41,High School,3,94,45,90,24,0.0,0,64,Semi-Urban,Manager,59164,1 +6908,Female,22,Bachelors,18,75,0,74,40,1.0,5,74,Semi-Urban,HR Executive,145604,0 +6909,Female,40,Diploma,1,22,76,82,71,3.0,2,81,Urban,Manager,122001,1 +6910,Male,40,Masters,5,13,5,87,80,8.0,6,48,Urban,HR Executive,20224,0 +6911,Male,56,High School,9,61,68,59,42,7.0,6,21,Urban,Data Analyst,98510,0 +6912,Other,53,PhD,9,89,67,60,59,4.0,6,20,Urban,Data Analyst,29742,0 +6913,Male,37,High School,8,93,27,6,85,6.0,5,2,Semi-Urban,Software Engineer,129904,0 +6914,Male,37,Bachelors,18,98,36,26,81,8.0,2,49,Urban,ML Engineer,108192,0 +6915,Male,39,Bachelors,6,59,82,25,99,6.0,6,97,Urban,Data Analyst,144681,1 +6916,Male,25,Masters,3,25,60,93,43,7.0,4,14,Semi-Urban,HR Executive,122603,0 +6917,Male,34,Diploma,12,71,95,72,29,1.0,3,50,Urban,Data Analyst,63670,1 +6918,Female,34,Masters,9,28,21,86,73,9.0,5,49,Semi-Urban,Data Analyst,148246,0 +6919,Female,59,Bachelors,3,60,91,15,16,6.0,7,66,Semi-Urban,Manager,88763,0 +6920,Male,36,Masters,1,58,58,62,55,9.0,7,62,Semi-Urban,Software Engineer,113553,1 +6921,Female,24,Masters,2,96,34,66,14,7.0,0,14,Semi-Urban,Data Analyst,96304,0 +6922,Male,30,Masters,7,40,34,83,15,9.0,7,13,Urban,Manager,68403,0 +6923,Male,44,Bachelors,14,92,52,22,13,5.0,6,52,Semi-Urban,Data Analyst,31577,0 +6924,Male,50,Masters,9,31,81,92,84,8.0,0,51,Urban,Manager,98538,1 +6925,Female,51,Masters,3,37,70,0,51,0.0,2,15,Urban,Manager,113480,0 +6926,Male,44,Masters,7,85,4,2,36,2.0,2,92,Rural,ML Engineer,83550,0 +6927,Male,47,Diploma,2,52,0,53,71,0.0,1,82,Urban,Data Analyst,49120,0 +6928,Female,52,Bachelors,5,4,38,44,57,6.0,7,8,Urban,Software Engineer,143822,0 +6929,Female,28,Masters,16,90,20,93,50,9.0,1,3,Rural,HR Executive,45987,0 +6930,Female,49,Masters,11,31,8,57,66,4.0,2,69,Urban,Data Analyst,49454,0 +6931,Male,36,Bachelors,4,33,89,55,37,1.0,7,22,Urban,HR Executive,108260,0 +6932,Male,25,Bachelors,13,57,68,0,21,2.0,2,9,Semi-Urban,HR Executive,63231,0 +6933,Male,40,Bachelors,18,35,26,83,10,0.0,5,16,Urban,Software Engineer,45727,0 +6934,Male,35,Bachelors,19,14,28,66,68,5.0,4,4,Urban,ML Engineer,76413,0 +6935,Female,35,Masters,13,28,51,94,93,5.0,7,33,Urban,Manager,42992,0 +6936,Male,40,PhD,15,43,73,73,14,0.0,2,38,Urban,ML Engineer,117516,0 +6937,Male,29,Bachelors,8,49,26,71,80,7.0,3,57,Urban,ML Engineer,91887,0 +6938,Female,48,Masters,1,73,57,85,28,1.0,6,41,Urban,ML Engineer,57448,1 +6939,Male,59,High School,3,79,2,98,95,3.0,7,21,Urban,Manager,149447,0 +6940,Male,27,High School,2,72,8,90,40,7.0,0,58,Urban,Data Analyst,68380,0 +6941,Female,43,High School,6,76,0,62,35,5.0,6,10,Semi-Urban,Data Analyst,92112,0 +6942,Female,44,Masters,10,24,33,67,1,3.0,0,99,Urban,HR Executive,132584,0 +6943,Female,36,Bachelors,10,82,26,56,97,1.0,7,67,Semi-Urban,HR Executive,118645,0 +6944,Male,42,High School,12,27,64,12,40,2.0,0,74,Urban,Manager,113845,0 +6945,Male,43,Diploma,14,38,4,83,1,2.0,0,33,Urban,ML Engineer,91941,0 +6946,Female,39,Diploma,1,17,92,84,63,2.0,5,30,Semi-Urban,Manager,34185,0 +6947,Male,32,Diploma,6,45,36,89,47,1.0,7,51,Semi-Urban,Software Engineer,144063,0 +6948,Male,46,Bachelors,2,76,39,49,19,1.0,7,71,Semi-Urban,HR Executive,62148,1 +6949,Female,53,Bachelors,8,12,36,75,70,9.0,4,80,Semi-Urban,Manager,41353,0 +6950,Male,59,Masters,4,35,87,93,7,5.0,4,5,Urban,HR Executive,72735,0 +6951,Female,22,Bachelors,11,34,23,46,63,9.0,3,22,Urban,ML Engineer,21288,0 +6952,Male,37,Bachelors,0,3,11,91,92,0.0,6,83,Semi-Urban,Software Engineer,57314,0 +6953,Male,31,High School,18,36,47,25,74,0.0,4,3,Semi-Urban,Manager,61849,0 +6954,Male,25,Bachelors,8,10,28,5,7,2.0,4,19,Rural,ML Engineer,42671,0 +6955,Female,28,Masters,14,26,54,78,2,0.0,4,37,Urban,ML Engineer,29985,0 +6956,Male,40,Bachelors,11,12,21,6,78,9.0,2,24,Urban,Manager,127164,0 +6957,Male,47,High School,14,31,3,36,98,3.0,7,5,Semi-Urban,Manager,96109,0 +6958,Female,47,High School,1,1,42,35,7,9.0,7,54,Semi-Urban,ML Engineer,143041,0 +6959,Female,50,Diploma,6,71,54,36,66,3.0,0,64,Urban,Software Engineer,144041,0 +6960,Other,54,High School,14,7,39,13,17,1.0,1,85,Urban,Manager,132390,0 +6961,Male,44,Masters,1,42,61,24,6,5.0,0,74,Semi-Urban,Manager,122287,0 +6962,Male,32,PhD,11,28,95,14,18,5.0,4,17,Urban,Data Analyst,90087,0 +6963,Other,49,Diploma,6,15,80,45,10,3.0,5,16,Semi-Urban,ML Engineer,68617,0 +6964,Female,29,Masters,4,18,94,21,9,0.0,5,35,Urban,Data Analyst,72813,0 +6965,Male,34,Masters,5,11,43,67,32,3.0,1,11,Semi-Urban,Manager,105438,0 +6966,Male,39,High School,6,84,50,54,94,0.0,3,1,Urban,Data Analyst,123145,0 +6967,Female,50,Masters,16,95,29,17,81,8.0,6,39,Rural,Manager,101169,0 +6968,Male,31,Masters,8,64,61,74,25,7.0,4,89,Urban,Software Engineer,143884,1 +6969,Female,42,Bachelors,5,1,18,76,85,9.0,6,32,Urban,ML Engineer,42741,0 +6970,Male,52,Bachelors,17,0,14,48,55,6.0,2,31,Urban,Software Engineer,27034,0 +6971,Male,56,PhD,14,70,63,50,19,4.0,0,4,Urban,Data Analyst,43021,0 +6972,Female,57,PhD,6,13,79,53,90,7.0,5,3,Urban,ML Engineer,72243,0 +6973,Male,25,PhD,5,57,60,90,6,7.0,7,73,Rural,Data Analyst,91951,1 +6974,Male,39,Bachelors,6,77,27,42,68,9.0,4,20,Urban,Software Engineer,40860,0 +6975,Male,57,Bachelors,11,36,66,53,90,6.0,2,75,Urban,Manager,117001,0 +6976,Male,40,High School,16,2,68,63,37,4.0,6,7,Rural,Software Engineer,134312,0 +6977,Female,43,Diploma,1,57,80,98,96,3.0,6,55,Urban,HR Executive,86561,1 +6978,Female,35,PhD,13,1,28,68,71,8.0,0,96,Urban,Data Analyst,129432,0 +6979,Female,53,Bachelors,4,26,61,56,3,1.0,2,60,Urban,Data Analyst,60981,0 +6980,Male,23,Bachelors,7,48,53,91,32,8.0,2,79,Urban,Software Engineer,100580,1 +6981,Male,40,Bachelors,19,6,28,94,71,7.0,1,70,Urban,Software Engineer,127257,0 +6982,Male,25,Bachelors,6,2,69,58,79,2.0,4,58,Urban,Software Engineer,131203,0 +6983,Female,56,High School,9,64,82,55,15,2.0,5,57,Urban,Manager,73600,1 +6984,Female,42,High School,5,86,12,39,34,6.0,5,45,Rural,ML Engineer,98464,0 +6985,Female,37,High School,13,73,31,23,70,1.0,2,97,Rural,Data Analyst,134764,0 +6986,Male,59,Bachelors,1,6,73,85,27,4.0,2,71,Urban,ML Engineer,131220,1 +6987,Male,37,Bachelors,7,4,75,28,87,7.0,4,53,Urban,Manager,122007,0 +6988,Male,26,Diploma,17,24,48,24,44,9.0,3,55,Urban,HR Executive,42549,0 +6989,Male,36,Bachelors,6,74,12,0,3,9.0,7,50,Urban,ML Engineer,63693,0 +6990,Male,22,Bachelors,18,79,10,82,3,8.0,6,6,Rural,Manager,86626,0 +6991,Female,35,Diploma,13,8,65,72,56,6.0,0,51,Urban,Data Analyst,148072,0 +6992,Male,26,Bachelors,13,44,72,25,95,5.0,1,92,Urban,ML Engineer,135651,0 +6993,Male,22,Masters,17,24,79,94,66,5.0,7,40,Urban,Manager,137287,1 +6994,Male,23,Masters,10,74,92,52,98,7.0,6,49,Rural,ML Engineer,89424,1 +6995,Female,25,Bachelors,13,7,93,45,28,5.0,2,0,Urban,ML Engineer,85192,0 +6996,Male,46,High School,17,87,33,20,28,0.0,0,25,Rural,ML Engineer,114691,0 +6997,Female,42,Bachelors,19,8,76,13,53,1.0,7,62,Urban,Data Analyst,98847,0 +6998,Female,57,Bachelors,9,50,22,77,6,6.0,3,36,Semi-Urban,Manager,141853,0 +6999,Male,30,Bachelors,0,14,50,29,48,6.0,0,47,Rural,HR Executive,46662,0 +7000,Female,44,Bachelors,1,91,21,63,37,2.0,2,76,Rural,Data Analyst,51715,1 +7001,Male,58,High School,2,29,37,36,49,8.0,2,27,Semi-Urban,Manager,88424,0 +7002,Male,35,Bachelors,8,97,46,32,7,2.0,0,99,Semi-Urban,Manager,88797,1 +7003,Female,58,High School,11,19,56,30,77,8.0,4,75,Rural,Manager,30774,0 +7004,Female,33,Masters,7,32,35,9,20,7.0,2,85,Urban,ML Engineer,44113,0 +7005,Male,52,Bachelors,2,29,33,51,40,9.0,2,28,Semi-Urban,Software Engineer,58267,0 +7006,Male,25,Bachelors,11,82,90,5,17,3.0,4,34,Rural,HR Executive,121883,0 +7007,Male,33,High School,18,67,34,44,48,4.0,6,25,Semi-Urban,Software Engineer,92949,0 +7008,Male,31,Bachelors,18,98,40,9,56,3.0,7,43,Urban,Software Engineer,117795,0 +7009,Male,54,Diploma,15,70,86,77,81,4.0,2,83,Urban,HR Executive,62261,1 +7010,Male,54,Bachelors,9,29,64,52,98,2.0,1,25,Urban,HR Executive,38308,0 +7011,Male,29,Diploma,3,63,65,2,96,3.0,4,50,Urban,Data Analyst,83911,0 +7012,Female,47,Diploma,16,69,97,7,59,6.0,2,56,Rural,Manager,71827,0 +7013,Male,50,High School,9,22,19,94,9,7.0,6,21,Urban,HR Executive,56486,0 +7014,Male,55,High School,3,95,43,31,61,9.0,4,48,Urban,ML Engineer,20245,0 +7015,Male,23,Diploma,9,86,90,12,36,7.0,0,59,Urban,Software Engineer,114908,1 +7016,Female,44,Bachelors,19,0,40,16,97,7.0,5,85,Rural,Software Engineer,77988,0 +7017,Male,49,Masters,6,99,31,96,19,4.0,0,9,Rural,HR Executive,106381,1 +7018,Male,32,Bachelors,17,71,76,88,40,8.0,5,98,Urban,ML Engineer,95818,1 +7019,Male,57,Bachelors,9,83,43,39,6,1.0,2,67,Urban,Software Engineer,35215,0 +7020,Female,40,Masters,6,59,88,90,22,7.0,4,7,Rural,HR Executive,74363,1 +7021,Male,22,Diploma,10,55,19,46,25,6.0,7,1,Urban,HR Executive,127012,0 +7022,Female,28,High School,17,31,81,51,95,7.0,3,18,Urban,HR Executive,131140,0 +7023,Other,36,Bachelors,13,18,49,24,49,3.0,1,1,Semi-Urban,HR Executive,97224,0 +7024,Female,47,Masters,14,7,17,45,93,5.0,2,8,Urban,Data Analyst,144900,0 +7025,Female,53,Bachelors,1,80,1,25,18,5.0,3,4,Urban,Data Analyst,48354,0 +7026,Male,44,High School,9,90,28,24,60,9.0,3,26,Urban,Data Analyst,94234,0 +7027,Male,33,Diploma,15,86,94,5,43,0.0,5,65,Urban,Manager,138970,1 +7028,Other,43,Bachelors,17,96,1,39,39,2.0,5,70,Semi-Urban,HR Executive,125461,0 +7029,Male,48,Diploma,18,17,98,60,97,8.0,6,67,Rural,Manager,109449,1 +7030,Male,32,Bachelors,19,25,30,31,31,6.0,1,87,Semi-Urban,HR Executive,45392,0 +7031,Female,22,Diploma,19,2,15,89,98,3.0,1,5,Semi-Urban,Software Engineer,78821,0 +7032,Male,33,High School,1,73,55,40,37,0.0,5,54,Rural,ML Engineer,89427,0 +7033,Male,34,Bachelors,17,29,58,68,58,9.0,5,84,Urban,Software Engineer,89105,1 +7034,Male,46,High School,7,66,63,10,1,4.0,6,99,Urban,Data Analyst,84945,1 +7035,Male,42,Bachelors,9,90,88,5,68,4.0,4,26,Semi-Urban,Manager,86008,0 +7036,Female,54,Bachelors,2,28,49,81,94,3.0,6,8,Semi-Urban,ML Engineer,43829,0 +7037,Male,21,Bachelors,10,88,31,80,15,9.0,1,88,Rural,ML Engineer,77324,1 +7038,Male,24,High School,9,34,83,78,20,0.0,4,54,Urban,Data Analyst,85302,1 +7039,Male,36,High School,4,67,63,59,2,7.0,4,56,Rural,HR Executive,110193,1 +7040,Female,29,Masters,2,91,46,90,49,6.0,5,88,Urban,Software Engineer,120775,1 +7041,Female,58,Bachelors,14,11,3,15,54,3.0,6,68,Urban,Software Engineer,76181,0 +7042,Male,51,Bachelors,1,47,61,64,42,0.0,5,46,Rural,ML Engineer,36947,0 +7043,Female,42,Bachelors,9,90,8,89,13,9.0,1,95,Rural,ML Engineer,67282,1 +7044,Male,22,Bachelors,15,30,73,55,67,6.0,0,31,Urban,Software Engineer,95605,0 +7045,Female,26,Bachelors,0,95,78,19,28,3.0,4,15,Rural,Data Analyst,136839,0 +7046,Male,35,Bachelors,13,22,11,35,57,0.0,3,64,Urban,ML Engineer,141499,0 +7047,Female,38,Masters,3,77,43,63,97,5.0,2,30,Urban,Software Engineer,28340,0 +7048,Male,28,Bachelors,13,27,86,70,82,7.0,5,75,Urban,HR Executive,127212,1 +7049,Male,48,Diploma,5,10,30,51,52,2.0,3,89,Urban,Software Engineer,39364,0 +7050,Male,47,Bachelors,0,37,93,67,41,9.0,3,56,Urban,Software Engineer,138620,1 +7051,Female,47,Diploma,18,94,50,52,88,5.0,3,38,Urban,Software Engineer,79541,0 +7052,Male,47,Bachelors,8,5,42,96,13,7.0,3,52,Semi-Urban,Manager,73151,0 +7053,Female,30,Bachelors,1,63,31,49,82,3.0,6,35,Urban,ML Engineer,85076,0 +7054,Male,54,Bachelors,12,22,29,72,89,3.0,6,72,Semi-Urban,Manager,48786,0 +7055,Male,52,High School,4,24,87,30,78,2.0,1,3,Rural,Manager,140328,0 +7056,Male,32,Bachelors,7,79,70,9,70,1.0,6,10,Urban,Manager,25899,0 +7057,Female,46,Masters,2,59,90,61,56,9.0,6,97,Semi-Urban,HR Executive,137779,1 +7058,Male,47,Masters,0,89,67,47,11,7.0,1,45,Rural,Software Engineer,127543,1 +7059,Female,32,Masters,2,53,29,28,19,7.0,1,38,Urban,Data Analyst,68332,0 +7060,Female,57,Bachelors,15,74,96,87,27,0.0,2,18,Urban,Software Engineer,110531,1 +7061,Female,51,High School,3,9,13,25,67,1.0,2,93,Urban,Manager,27274,0 +7062,Male,53,Bachelors,2,32,73,54,48,9.0,5,1,Urban,Manager,142869,0 +7063,Female,21,Bachelors,0,13,12,84,63,4.0,3,24,Urban,Manager,56421,0 +7064,Female,33,Bachelors,16,42,13,13,47,6.0,2,71,Rural,Manager,140640,0 +7065,Male,50,Diploma,10,96,27,66,0,9.0,5,49,Urban,ML Engineer,23435,1 +7066,Female,42,Masters,6,69,42,19,10,4.0,0,77,Rural,HR Executive,26017,0 +7067,Male,30,Masters,6,64,24,54,95,7.0,1,65,Semi-Urban,Data Analyst,24092,0 +7068,Male,35,PhD,12,33,24,9,20,4.0,3,82,Urban,HR Executive,118475,0 +7069,Male,27,Masters,19,52,89,66,11,0.0,1,39,Rural,Software Engineer,22794,1 +7070,Male,22,Masters,4,45,79,97,63,7.0,7,88,Rural,HR Executive,148861,1 +7071,Male,22,Bachelors,1,83,79,71,14,3.0,0,83,Rural,Software Engineer,128598,1 +7072,Male,40,Masters,12,20,41,78,42,4.0,4,25,Semi-Urban,Software Engineer,118143,0 +7073,Female,27,Diploma,12,23,37,98,38,5.0,0,34,Rural,HR Executive,86269,0 +7074,Male,49,PhD,10,74,1,69,36,1.0,4,38,Urban,Software Engineer,135305,0 +7075,Male,25,Bachelors,14,22,11,28,39,9.0,7,95,Rural,HR Executive,98236,0 +7076,Male,24,Diploma,19,97,86,50,86,2.0,1,77,Urban,Manager,141459,1 +7077,Male,34,Diploma,5,55,31,58,78,2.0,6,8,Urban,ML Engineer,99175,0 +7078,Female,21,Masters,10,64,82,30,25,4.0,5,5,Semi-Urban,Data Analyst,62485,0 +7079,Male,36,High School,5,69,98,89,43,7.0,5,19,Urban,HR Executive,40860,1 +7080,Female,44,Bachelors,12,84,55,69,61,7.0,2,42,Rural,ML Engineer,133934,1 +7081,Male,44,Bachelors,9,20,24,99,66,7.0,2,1,Semi-Urban,ML Engineer,98276,0 +7082,Female,22,High School,17,33,36,71,93,2.0,5,92,Urban,Manager,101515,0 +7083,Male,34,Bachelors,13,41,86,38,83,8.0,0,66,Rural,HR Executive,70737,0 +7084,Male,24,Masters,3,13,87,59,9,4.0,3,62,Semi-Urban,Manager,75514,0 +7085,Female,35,Masters,8,91,43,20,2,8.0,7,11,Urban,Software Engineer,124003,0 +7086,Male,22,Diploma,10,44,30,12,32,8.0,5,47,Rural,Data Analyst,127346,0 +7087,Female,45,Masters,8,52,50,88,64,4.0,6,36,Urban,ML Engineer,48292,0 +7088,Female,56,Diploma,15,96,65,87,74,8.0,1,65,Urban,Manager,114431,1 +7089,Male,53,High School,4,34,13,58,18,7.0,2,69,Semi-Urban,HR Executive,36050,0 +7090,Male,22,High School,17,20,7,34,53,0.0,5,38,Urban,Software Engineer,89539,0 +7091,Male,47,Bachelors,13,79,24,30,51,9.0,3,48,Rural,ML Engineer,142766,0 +7092,Female,29,Bachelors,18,93,17,79,81,6.0,4,3,Semi-Urban,HR Executive,30663,0 +7093,Female,21,Bachelors,13,0,91,4,3,9.0,5,65,Urban,Manager,49696,0 +7094,Male,30,Diploma,4,58,15,56,70,7.0,0,2,Urban,ML Engineer,101360,0 +7095,Male,35,Bachelors,8,98,66,96,17,4.0,1,8,Urban,HR Executive,131484,1 +7096,Male,59,High School,6,38,48,81,0,7.0,5,82,Semi-Urban,ML Engineer,108171,1 +7097,Female,27,Diploma,15,39,31,37,34,1.0,4,19,Urban,Software Engineer,28986,0 +7098,Male,21,Bachelors,9,30,10,87,77,7.0,5,43,Urban,HR Executive,48742,0 +7099,Male,35,Masters,11,54,73,92,92,7.0,3,52,Urban,HR Executive,62192,1 +7100,Female,21,Masters,17,82,74,54,17,7.0,6,44,Urban,Software Engineer,130189,1 +7101,Male,26,Diploma,2,31,40,44,39,0.0,5,92,Urban,Data Analyst,89614,0 +7102,Male,41,Bachelors,6,38,44,67,53,5.0,7,82,Urban,Manager,42876,0 +7103,Other,46,Diploma,11,30,34,74,52,7.0,7,59,Urban,HR Executive,127049,0 +7104,Female,27,Diploma,6,25,75,67,51,8.0,6,59,Urban,Data Analyst,84140,0 +7105,Male,50,Masters,3,16,64,72,66,6.0,0,0,Semi-Urban,Software Engineer,131821,0 +7106,Male,53,Masters,9,31,13,29,2,4.0,4,70,Semi-Urban,ML Engineer,142339,0 +7107,Male,37,Bachelors,6,74,15,68,15,4.0,1,54,Urban,HR Executive,66638,0 +7108,Male,59,Bachelors,3,18,24,9,33,4.0,5,56,Urban,HR Executive,141320,0 +7109,Female,57,Bachelors,14,89,22,10,86,3.0,3,0,Urban,Manager,72216,0 +7110,Male,59,Bachelors,19,19,72,51,1,7.0,5,8,Urban,Data Analyst,58996,0 +7111,Female,29,Masters,17,72,1,3,24,7.0,6,29,Urban,ML Engineer,125544,0 +7112,Female,24,Diploma,2,30,15,63,76,3.0,5,99,Semi-Urban,Data Analyst,99103,0 +7113,Male,37,High School,1,72,58,41,98,2.0,5,52,Urban,Data Analyst,83989,0 +7114,Male,24,Masters,17,47,19,55,97,2.0,2,80,Semi-Urban,ML Engineer,53765,0 +7115,Male,21,Bachelors,16,10,40,84,31,8.0,0,51,Urban,Manager,34127,0 +7116,Female,30,High School,3,12,70,85,65,5.0,7,44,Semi-Urban,Manager,115510,0 +7117,Female,41,Masters,10,50,51,23,81,7.0,7,34,Urban,HR Executive,77973,0 +7118,Male,52,High School,2,51,29,99,82,8.0,4,13,Semi-Urban,HR Executive,32906,0 +7119,Female,50,Bachelors,6,30,2,16,39,6.0,0,48,Urban,Manager,115177,0 +7120,Male,31,PhD,13,47,65,33,86,9.0,6,77,Semi-Urban,Manager,87829,0 +7121,Female,40,Diploma,19,74,98,31,9,4.0,4,38,Semi-Urban,ML Engineer,134656,1 +7122,Male,48,Bachelors,16,69,70,59,65,6.0,0,10,Rural,ML Engineer,92559,0 +7123,Male,29,High School,4,46,57,1,10,0.0,4,37,Semi-Urban,ML Engineer,119490,0 +7124,Female,40,PhD,12,67,44,59,95,1.0,0,86,Urban,ML Engineer,52876,1 +7125,Male,26,Bachelors,0,69,71,43,1,6.0,5,1,Semi-Urban,Data Analyst,125982,0 +7126,Male,45,Masters,19,28,78,2,72,0.0,5,46,Urban,Manager,51442,0 +7127,Male,57,Bachelors,0,9,55,47,35,8.0,0,34,Rural,Manager,71545,0 +7128,Male,27,Bachelors,17,95,11,48,8,2.0,7,0,Urban,ML Engineer,85479,0 +7129,Male,28,Bachelors,6,30,40,33,95,2.0,4,75,Urban,Manager,21855,0 +7130,Female,56,Diploma,1,73,73,83,31,5.0,4,2,Urban,Manager,117289,0 +7131,Male,27,Diploma,13,42,19,57,80,6.0,6,30,Semi-Urban,HR Executive,57643,0 +7132,Male,40,Diploma,5,2,64,66,86,6.0,4,43,Semi-Urban,Software Engineer,73608,0 +7133,Female,25,Bachelors,7,31,39,25,73,4.0,3,79,Urban,Manager,147301,0 +7134,Male,57,Bachelors,16,1,7,17,82,0.0,3,9,Urban,ML Engineer,28624,0 +7135,Male,21,Bachelors,4,68,33,24,93,2.0,7,22,Rural,HR Executive,118442,0 +7136,Female,27,High School,13,37,77,22,86,6.0,7,31,Rural,Data Analyst,80670,0 +7137,Female,43,Masters,1,13,73,30,66,6.0,1,52,Rural,ML Engineer,47303,0 +7138,Female,57,Masters,8,50,90,71,39,3.0,7,91,Urban,ML Engineer,118950,1 +7139,Female,48,Bachelors,3,15,36,44,71,4.0,7,79,Urban,Manager,127119,0 +7140,Male,57,Bachelors,0,49,86,84,42,4.0,1,29,Semi-Urban,Software Engineer,67908,1 +7141,Female,26,Bachelors,3,86,56,80,71,5.0,1,39,Semi-Urban,Software Engineer,137372,1 +7142,Male,47,Masters,11,33,72,25,45,9.0,6,50,Semi-Urban,Software Engineer,46896,0 +7143,Female,28,Masters,18,62,70,79,29,2.0,1,75,Semi-Urban,Data Analyst,146468,1 +7144,Male,54,Bachelors,18,9,39,12,65,3.0,0,26,Semi-Urban,HR Executive,125310,0 +7145,Female,57,Diploma,16,90,2,55,53,0.0,2,72,Urban,Software Engineer,88672,0 +7146,Female,46,Diploma,19,9,55,26,27,1.0,3,45,Urban,Data Analyst,129315,0 +7147,Female,25,Bachelors,2,14,9,58,63,4.0,0,82,Urban,HR Executive,100956,0 +7148,Male,40,Masters,10,8,21,15,6,4.0,7,31,Urban,ML Engineer,86592,0 +7149,Male,24,Bachelors,11,68,55,76,50,6.0,5,72,Rural,HR Executive,100868,1 +7150,Female,39,Diploma,4,42,86,17,26,9.0,4,66,Rural,Manager,36659,0 +7151,Female,25,Bachelors,10,45,37,67,16,8.0,4,63,Urban,HR Executive,121007,0 +7152,Male,57,Diploma,3,80,12,3,92,2.0,5,37,Urban,ML Engineer,65687,0 +7153,Other,21,Masters,3,82,35,2,91,5.0,0,24,Urban,Data Analyst,124797,0 +7154,Female,30,Masters,10,1,54,47,53,6.0,2,76,Rural,ML Engineer,49478,0 +7155,Male,28,High School,6,10,15,71,2,0.0,3,77,Urban,Data Analyst,110726,0 +7156,Female,31,Bachelors,0,23,38,46,1,6.0,5,71,Urban,HR Executive,95161,0 +7157,Male,25,Bachelors,12,56,1,1,5,3.0,1,50,Urban,HR Executive,89623,0 +7158,Male,37,Bachelors,7,60,52,17,83,2.0,4,82,Urban,Software Engineer,65912,0 +7159,Male,44,Bachelors,17,99,29,16,40,1.0,7,27,Urban,ML Engineer,57641,0 +7160,Male,26,Bachelors,13,86,66,2,59,7.0,1,38,Urban,Data Analyst,28993,0 +7161,Female,46,Masters,2,67,56,83,80,8.0,5,30,Semi-Urban,Software Engineer,87490,0 +7162,Male,23,Bachelors,2,72,97,86,23,0.0,5,82,Urban,HR Executive,134860,1 +7163,Female,37,Bachelors,17,78,94,55,40,7.0,0,51,Urban,Data Analyst,103217,1 +7164,Female,56,Masters,12,49,49,46,99,4.0,6,57,Urban,Manager,145903,0 +7165,Female,28,Diploma,16,90,17,53,14,9.0,1,52,Semi-Urban,Software Engineer,112543,0 +7166,Male,29,Bachelors,13,57,59,68,87,7.0,6,58,Urban,ML Engineer,35888,1 +7167,Female,43,Diploma,1,78,53,26,61,4.0,2,29,Semi-Urban,HR Executive,91112,0 +7168,Male,40,Masters,12,16,15,48,48,7.0,1,8,Urban,HR Executive,69193,0 +7169,Male,57,Diploma,1,16,66,29,14,4.0,2,91,Rural,Manager,95703,0 +7170,Male,35,Bachelors,0,70,75,76,69,9.0,6,89,Semi-Urban,Software Engineer,83698,1 +7171,Male,34,Diploma,2,1,92,47,46,9.0,6,61,Urban,HR Executive,122997,0 +7172,Female,42,Bachelors,13,10,16,94,99,2.0,4,94,Rural,Data Analyst,133011,0 +7173,Male,35,Masters,11,22,31,77,98,6.0,0,0,Rural,Data Analyst,143556,0 +7174,Female,57,Masters,0,54,34,75,41,0.0,1,12,Rural,Data Analyst,106641,0 +7175,Male,32,Bachelors,11,53,82,84,56,8.0,0,10,Semi-Urban,Software Engineer,45227,0 +7176,Male,41,High School,3,33,8,39,27,1.0,7,64,Rural,HR Executive,42631,0 +7177,Other,28,High School,4,64,3,53,95,0.0,0,59,Rural,Manager,59356,0 +7178,Female,42,Masters,14,49,89,36,2,4.0,5,66,Rural,ML Engineer,144300,0 +7179,Male,27,Masters,9,62,51,0,73,1.0,3,45,Urban,Data Analyst,114552,0 +7180,Male,58,Bachelors,3,8,32,33,1,4.0,0,27,Urban,Software Engineer,63163,0 +7181,Male,24,Masters,15,42,14,67,96,6.0,7,70,Urban,Software Engineer,71992,0 +7182,Male,26,Bachelors,16,7,51,61,53,3.0,0,24,Urban,HR Executive,51136,0 +7183,Female,50,High School,18,56,35,22,6,6.0,3,72,Rural,ML Engineer,21248,0 +7184,Female,21,Diploma,7,51,32,8,18,4.0,0,46,Rural,Data Analyst,31468,0 +7185,Male,44,Masters,1,40,38,4,3,4.0,0,62,Urban,Software Engineer,21914,0 +7186,Female,52,Masters,6,61,84,18,45,2.0,5,30,Urban,HR Executive,127907,0 +7187,Male,42,High School,3,25,95,83,27,1.0,6,64,Semi-Urban,ML Engineer,127138,1 +7188,Male,33,High School,6,53,45,42,87,7.0,4,73,Rural,Manager,60336,0 +7189,Male,57,Bachelors,12,12,86,62,89,8.0,1,72,Urban,ML Engineer,67741,0 +7190,Female,48,Diploma,19,14,25,55,86,9.0,6,27,Urban,Data Analyst,106076,0 +7191,Male,23,Bachelors,17,28,1,56,96,6.0,7,4,Rural,Manager,127574,0 +7192,Male,26,PhD,17,41,49,6,2,7.0,7,94,Semi-Urban,Software Engineer,47166,0 +7193,Male,22,Bachelors,3,80,79,68,76,3.0,3,16,Rural,Software Engineer,39035,1 +7194,Male,55,High School,9,20,51,64,58,8.0,6,58,Urban,Software Engineer,61306,0 +7195,Female,41,Masters,1,66,95,68,93,3.0,5,20,Urban,Manager,55724,1 +7196,Male,41,Masters,15,66,39,17,59,7.0,1,85,Urban,Software Engineer,69461,0 +7197,Male,51,Masters,19,89,34,75,51,8.0,5,52,Semi-Urban,Manager,70451,1 +7198,Female,34,PhD,18,15,1,65,45,5.0,7,29,Urban,Manager,92763,0 +7199,Female,28,Diploma,3,29,20,4,52,1.0,0,31,Urban,Manager,93034,0 +7200,Female,48,Masters,13,61,81,8,24,0.0,4,49,Urban,ML Engineer,68122,0 +7201,Male,52,Bachelors,0,60,95,34,95,3.0,6,49,Rural,Data Analyst,99859,1 +7202,Male,36,Diploma,9,34,46,50,41,7.0,2,74,Urban,Data Analyst,89438,0 +7203,Male,57,High School,10,26,98,33,16,8.0,1,22,Urban,ML Engineer,148079,0 +7204,Male,51,High School,15,33,78,41,38,8.0,2,27,Urban,ML Engineer,116924,0 +7205,Female,58,Masters,18,62,52,43,98,9.0,1,95,Rural,HR Executive,142101,1 +7206,Male,31,Bachelors,0,88,30,26,90,8.0,4,52,Urban,HR Executive,52506,0 +7207,Male,21,PhD,8,95,83,46,3,8.0,0,0,Urban,HR Executive,21588,0 +7208,Male,21,Diploma,9,24,25,83,31,8.0,1,34,Urban,Manager,114990,0 +7209,Male,59,Masters,10,55,30,17,1,1.0,2,9,Urban,HR Executive,28992,0 +7210,Female,47,Masters,12,60,64,38,93,3.0,1,81,Urban,HR Executive,33924,1 +7211,Male,37,High School,4,25,38,52,75,9.0,4,80,Urban,Data Analyst,119664,0 +7212,Male,35,Bachelors,4,52,3,31,93,5.0,1,66,Semi-Urban,ML Engineer,124826,0 +7213,Male,35,Bachelors,17,4,15,41,99,9.0,4,20,Rural,Data Analyst,91869,0 +7214,Male,22,Diploma,18,85,41,89,67,3.0,7,32,Rural,HR Executive,70109,1 +7215,Male,34,Bachelors,4,39,94,56,17,6.0,4,35,Urban,Data Analyst,92635,0 +7216,Female,44,Bachelors,14,13,63,98,88,9.0,6,35,Urban,HR Executive,104950,0 +7217,Male,58,Masters,5,99,73,26,18,8.0,3,43,Semi-Urban,ML Engineer,88243,1 +7218,Female,57,High School,11,62,69,4,58,1.0,4,43,Urban,HR Executive,43269,0 +7219,Female,44,Masters,15,73,16,63,68,8.0,6,17,Urban,Data Analyst,62824,0 +7220,Female,52,Diploma,0,35,26,41,66,3.0,4,41,Urban,Software Engineer,34641,0 +7221,Female,42,Bachelors,3,88,34,34,77,1.0,1,88,Rural,Software Engineer,37475,1 +7222,Male,32,Masters,6,50,93,17,33,4.0,0,84,Rural,Software Engineer,93288,1 +7223,Male,31,Masters,5,12,31,69,86,0.0,2,89,Rural,Data Analyst,31585,0 +7224,Male,49,Bachelors,6,11,61,39,45,6.0,0,36,Urban,Data Analyst,141513,0 +7225,Female,23,Bachelors,10,25,22,85,73,6.0,4,1,Urban,Data Analyst,46211,0 +7226,Other,24,Masters,16,0,92,99,27,2.0,3,23,Urban,ML Engineer,21301,0 +7227,Female,39,Masters,13,66,84,3,85,1.0,4,72,Urban,Manager,43910,0 +7228,Male,55,Bachelors,18,24,91,11,5,7.0,5,71,Urban,Data Analyst,131774,0 +7229,Female,32,Diploma,12,12,19,3,52,4.0,7,69,Rural,Data Analyst,144337,0 +7230,Male,30,Bachelors,2,18,83,12,76,0.0,0,25,Rural,Software Engineer,104883,0 +7231,Male,30,Diploma,1,28,14,80,65,5.0,3,10,Semi-Urban,Data Analyst,76592,0 +7232,Male,30,Diploma,10,77,29,64,68,0.0,4,34,Urban,Software Engineer,149805,0 +7233,Male,37,Bachelors,12,29,94,71,60,0.0,2,7,Urban,Software Engineer,44913,0 +7234,Male,43,Bachelors,13,15,9,41,83,2.0,1,73,Rural,HR Executive,75152,0 +7235,Male,35,High School,14,17,1,10,69,8.0,2,4,Urban,Manager,24340,0 +7236,Male,33,Bachelors,0,57,79,32,46,8.0,0,65,Semi-Urban,Software Engineer,51066,0 +7237,Female,35,Bachelors,6,11,31,9,8,5.0,1,43,Urban,Software Engineer,51773,0 +7238,Female,28,Bachelors,18,34,46,69,97,3.0,3,37,Semi-Urban,HR Executive,83893,0 +7239,Female,27,Bachelors,9,92,42,26,83,5.0,6,82,Semi-Urban,Software Engineer,101778,1 +7240,Male,36,Bachelors,18,20,6,9,91,6.0,4,32,Urban,Software Engineer,80049,0 +7241,Female,58,Diploma,5,26,50,71,89,9.0,0,52,Semi-Urban,Data Analyst,79627,0 +7242,Female,45,High School,12,77,83,7,53,3.0,5,22,Urban,Software Engineer,144539,0 +7243,Male,21,Bachelors,4,26,4,8,17,3.0,0,86,Semi-Urban,ML Engineer,62172,0 +7244,Male,49,Masters,16,56,41,3,17,0.0,1,94,Semi-Urban,Software Engineer,70194,0 +7245,Male,23,Bachelors,17,22,86,0,69,5.0,0,23,Urban,Data Analyst,26298,0 +7246,Male,48,Bachelors,13,48,92,38,84,4.0,5,94,Urban,Software Engineer,114393,1 +7247,Female,43,Bachelors,4,12,10,77,44,5.0,7,18,Urban,HR Executive,137161,0 +7248,Female,35,High School,18,51,46,55,52,0.0,3,41,Urban,ML Engineer,35751,0 +7249,Male,52,Bachelors,7,15,89,58,98,5.0,6,12,Urban,Data Analyst,39016,0 +7250,Female,45,High School,14,27,4,57,82,2.0,1,82,Rural,ML Engineer,108171,0 +7251,Female,40,Diploma,3,45,38,23,36,2.0,6,26,Urban,Manager,143702,0 +7252,Female,28,Bachelors,16,9,46,98,75,8.0,7,45,Semi-Urban,Manager,41568,0 +7253,Male,42,Bachelors,14,75,57,35,13,5.0,7,23,Semi-Urban,ML Engineer,81453,0 +7254,Female,45,Masters,16,52,7,85,69,1.0,1,40,Semi-Urban,Software Engineer,43346,0 +7255,Male,57,Masters,13,23,97,31,90,4.0,6,32,Semi-Urban,Software Engineer,71206,0 +7256,Male,30,PhD,15,66,46,38,49,5.0,1,61,Rural,Manager,103916,0 +7257,Male,36,Bachelors,3,56,20,27,25,4.0,2,49,Urban,Software Engineer,74181,0 +7258,Male,23,Bachelors,17,70,29,9,3,1.0,1,37,Urban,ML Engineer,108925,0 +7259,Female,47,High School,4,88,91,23,35,0.0,2,50,Urban,Software Engineer,44157,1 +7260,Male,51,Bachelors,4,1,9,84,78,7.0,1,88,Rural,HR Executive,88310,0 +7261,Male,38,Diploma,4,48,21,83,31,1.0,5,94,Urban,Manager,79289,1 +7262,Male,39,Bachelors,8,74,53,41,92,4.0,0,46,Rural,ML Engineer,145829,0 +7263,Female,22,Bachelors,1,17,68,29,13,8.0,0,44,Urban,Data Analyst,130916,0 +7264,Male,41,Masters,6,93,33,82,13,3.0,2,32,Urban,Data Analyst,36039,1 +7265,Female,35,Bachelors,11,82,34,87,39,3.0,1,62,Urban,HR Executive,33087,1 +7266,Male,31,High School,6,42,31,80,61,5.0,5,90,Urban,Manager,20199,1 +7267,Male,27,Diploma,17,51,83,36,63,4.0,5,59,Rural,Data Analyst,103471,0 +7268,Male,35,Bachelors,16,16,16,7,0,9.0,1,45,Urban,HR Executive,116073,0 +7269,Male,53,Bachelors,15,40,84,28,2,9.0,4,31,Urban,Software Engineer,120602,0 +7270,Male,55,High School,9,10,28,84,43,1.0,3,45,Urban,Data Analyst,20512,0 +7271,Male,58,Bachelors,1,40,63,98,9,3.0,1,73,Urban,HR Executive,125723,1 +7272,Other,31,Diploma,17,31,60,64,70,0.0,6,56,Urban,HR Executive,144743,0 +7273,Female,21,High School,1,22,63,86,45,1.0,7,62,Semi-Urban,Software Engineer,107263,0 +7274,Male,41,Bachelors,10,60,43,55,73,2.0,5,81,Urban,ML Engineer,47413,1 +7275,Male,50,Diploma,18,67,60,15,9,4.0,0,63,Semi-Urban,Data Analyst,105747,0 +7276,Female,47,Masters,6,13,25,47,68,4.0,4,71,Rural,HR Executive,96947,0 +7277,Male,38,Masters,14,97,33,4,92,1.0,7,58,Semi-Urban,ML Engineer,121706,0 +7278,Male,53,High School,15,49,49,5,13,3.0,2,21,Rural,Manager,74295,0 +7279,Female,21,Masters,12,8,59,24,47,6.0,1,16,Rural,HR Executive,45237,0 +7280,Female,40,Bachelors,14,78,78,99,97,3.0,0,30,Rural,Manager,149601,1 +7281,Male,49,Masters,19,38,60,15,57,1.0,5,39,Urban,Data Analyst,81697,0 +7282,Male,33,Bachelors,6,98,62,73,94,0.0,7,97,Urban,Manager,109346,1 +7283,Male,59,Bachelors,19,91,41,80,42,0.0,1,61,Urban,HR Executive,29249,1 +7284,Female,59,High School,1,27,6,92,28,8.0,0,13,Urban,HR Executive,121736,0 +7285,Male,54,Diploma,14,35,1,75,78,3.0,4,50,Semi-Urban,Software Engineer,42908,0 +7286,Male,43,Bachelors,11,54,36,4,85,7.0,0,55,Urban,Software Engineer,82484,0 +7287,Male,33,High School,13,96,75,68,86,5.0,1,74,Semi-Urban,HR Executive,109490,1 +7288,Male,22,Diploma,18,34,39,79,27,0.0,4,8,Urban,ML Engineer,75874,0 +7289,Female,48,Masters,11,16,71,46,16,2.0,3,54,Urban,Data Analyst,101311,0 +7290,Female,24,Masters,13,29,17,79,34,4.0,3,47,Urban,ML Engineer,104841,0 +7291,Female,59,Masters,5,89,58,13,25,7.0,1,99,Urban,HR Executive,143941,1 +7292,Male,52,Bachelors,18,3,98,8,46,4.0,7,68,Urban,ML Engineer,77004,0 +7293,Male,31,Bachelors,1,13,60,89,90,8.0,1,67,Urban,Software Engineer,93649,0 +7294,Male,52,Masters,8,25,57,62,17,5.0,5,90,Semi-Urban,Software Engineer,46759,0 +7295,Male,45,High School,19,90,94,80,21,8.0,4,33,Urban,ML Engineer,121595,1 +7296,Other,25,Bachelors,17,38,79,74,24,3.0,4,40,Rural,Software Engineer,114469,0 +7297,Male,35,Bachelors,2,75,72,23,22,8.0,1,19,Urban,Software Engineer,119902,0 +7298,Male,57,Bachelors,3,34,78,76,95,1.0,3,60,Rural,HR Executive,82263,1 +7299,Male,50,Bachelors,15,99,68,42,11,5.0,1,6,Rural,HR Executive,63144,0 +7300,Female,24,Bachelors,13,67,13,58,91,2.0,4,78,Urban,Data Analyst,34978,0 +7301,Male,24,Diploma,18,59,2,36,82,0.0,2,49,Urban,Manager,149130,0 +7302,Male,28,Masters,16,26,9,28,96,9.0,1,72,Semi-Urban,ML Engineer,112255,0 +7303,Male,34,Diploma,13,85,49,70,88,8.0,2,65,Urban,HR Executive,145708,1 +7304,Female,37,Diploma,12,69,61,42,55,7.0,7,34,Rural,Manager,42230,0 +7305,Male,31,Bachelors,4,78,76,48,21,8.0,4,25,Urban,HR Executive,126754,0 +7306,Female,26,Bachelors,11,88,78,32,58,3.0,7,22,Semi-Urban,ML Engineer,71603,0 +7307,Female,51,High School,16,29,18,16,26,2.0,6,58,Rural,HR Executive,31011,0 +7308,Male,32,Bachelors,0,11,61,39,55,7.0,3,59,Rural,Manager,48679,0 +7309,Female,58,Masters,9,59,20,88,7,8.0,5,82,Rural,Data Analyst,23652,1 +7310,Male,47,Bachelors,4,32,52,62,26,3.0,7,12,Rural,HR Executive,39885,0 +7311,Other,25,Bachelors,6,39,53,48,92,6.0,2,20,Rural,Software Engineer,149457,0 +7312,Male,49,Bachelors,1,23,79,34,37,2.0,4,7,Urban,Software Engineer,84893,0 +7313,Male,50,Bachelors,3,66,86,22,12,3.0,4,30,Urban,Data Analyst,72804,0 +7314,Male,33,Masters,7,63,17,51,94,3.0,6,63,Semi-Urban,HR Executive,39053,0 +7315,Male,33,Masters,14,99,8,46,13,0.0,5,28,Urban,Software Engineer,131624,0 +7316,Other,49,Masters,5,30,85,66,6,9.0,2,25,Urban,HR Executive,46754,0 +7317,Male,25,Masters,14,8,48,21,69,9.0,2,51,Rural,Software Engineer,124884,0 +7318,Female,34,Bachelors,9,81,0,1,86,4.0,2,91,Urban,Manager,94783,0 +7319,Male,42,Masters,14,49,93,86,98,8.0,7,98,Urban,Manager,21948,1 +7320,Female,37,Diploma,9,41,48,48,78,0.0,1,45,Urban,Manager,39855,0 +7321,Male,39,High School,1,38,58,32,39,6.0,7,42,Urban,Manager,63868,0 +7322,Male,56,High School,17,65,15,77,41,5.0,2,2,Semi-Urban,Data Analyst,114165,0 +7323,Male,32,Bachelors,1,29,12,96,7,7.0,1,14,Urban,Manager,117813,0 +7324,Female,45,Diploma,15,53,26,86,82,8.0,0,93,Urban,ML Engineer,34347,1 +7325,Male,43,Masters,5,66,23,24,53,6.0,4,24,Rural,Software Engineer,35275,0 +7326,Male,37,Bachelors,14,11,22,81,75,0.0,4,1,Semi-Urban,Data Analyst,43126,0 +7327,Male,55,Diploma,19,6,68,54,36,9.0,5,26,Urban,Manager,117324,0 +7328,Female,59,High School,0,87,77,26,40,9.0,3,99,Semi-Urban,Manager,71092,1 +7329,Male,44,Bachelors,12,43,28,82,57,2.0,7,8,Urban,HR Executive,90736,0 +7330,Male,58,Bachelors,5,10,29,48,19,4.0,3,55,Rural,Manager,21448,0 +7331,Male,32,High School,6,97,27,58,51,2.0,1,3,Semi-Urban,HR Executive,48254,0 +7332,Female,58,Diploma,7,37,41,66,19,3.0,3,66,Urban,HR Executive,95250,0 +7333,Female,34,Masters,17,83,79,67,62,7.0,4,89,Urban,ML Engineer,28141,1 +7334,Male,34,Masters,18,12,56,48,11,3.0,1,88,Semi-Urban,HR Executive,25730,0 +7335,Male,30,Bachelors,13,1,91,71,80,3.0,4,72,Urban,HR Executive,105769,1 +7336,Male,21,Bachelors,10,20,40,54,49,0.0,4,42,Semi-Urban,Software Engineer,94282,0 +7337,Male,43,Diploma,2,46,68,36,28,8.0,6,17,Semi-Urban,HR Executive,88394,0 +7338,Male,48,Bachelors,0,62,12,41,35,4.0,2,40,Urban,Data Analyst,90728,0 +7339,Female,27,Masters,11,17,30,52,19,5.0,4,51,Semi-Urban,Data Analyst,123238,0 +7340,Male,52,Diploma,8,58,87,42,33,9.0,1,20,Semi-Urban,Manager,112419,0 +7341,Female,31,Bachelors,9,70,3,58,91,3.0,2,94,Semi-Urban,Software Engineer,76167,0 +7342,Male,29,Diploma,10,43,6,20,86,6.0,7,71,Semi-Urban,Manager,60426,0 +7343,Female,44,Bachelors,12,23,53,29,57,7.0,1,87,Semi-Urban,Software Engineer,61708,0 +7344,Male,24,Masters,0,60,29,19,76,1.0,7,69,Urban,Manager,113818,0 +7345,Male,37,High School,16,22,44,64,5,9.0,2,50,Rural,Software Engineer,42775,0 +7346,Male,41,Bachelors,16,12,77,89,45,6.0,5,27,Urban,Software Engineer,42205,0 +7347,Male,45,High School,13,36,42,75,78,4.0,2,68,Rural,HR Executive,62201,0 +7348,Male,53,High School,5,55,15,13,68,7.0,1,55,Rural,Data Analyst,81108,0 +7349,Female,23,Masters,16,22,41,93,46,7.0,4,60,Semi-Urban,HR Executive,111615,0 +7350,Female,24,Bachelors,1,74,97,77,90,5.0,2,63,Urban,Software Engineer,93678,1 +7351,Male,33,Bachelors,10,83,94,80,32,1.0,6,72,Semi-Urban,Manager,107429,1 +7352,Male,49,Bachelors,12,20,93,78,0,7.0,7,74,Rural,HR Executive,46206,1 +7353,Male,56,Bachelors,1,10,68,64,38,4.0,5,46,Rural,ML Engineer,38663,0 +7354,Male,26,Diploma,2,78,92,68,20,7.0,0,53,Urban,Data Analyst,113766,1 +7355,Male,55,Masters,17,64,59,73,96,4.0,1,71,Semi-Urban,Manager,114872,1 +7356,Female,34,Bachelors,13,64,0,95,94,4.0,5,0,Urban,Software Engineer,114991,0 +7357,Other,21,Diploma,13,18,61,72,71,4.0,5,3,Semi-Urban,Software Engineer,30582,0 +7358,Female,27,Diploma,13,43,49,39,32,4.0,0,18,Urban,Data Analyst,97107,0 +7359,Male,51,Masters,12,56,36,99,74,6.0,3,20,Semi-Urban,ML Engineer,60496,0 +7360,Female,58,Diploma,1,19,79,57,20,9.0,4,21,Rural,HR Executive,27513,0 +7361,Female,40,Bachelors,14,29,81,91,19,9.0,4,69,Urban,Data Analyst,102559,1 +7362,Male,49,High School,7,26,61,48,1,5.0,7,21,Urban,HR Executive,141299,0 +7363,Male,47,Diploma,16,78,52,88,6,9.0,2,99,Urban,Software Engineer,20586,1 +7364,Female,42,High School,7,25,67,2,87,5.0,7,33,Rural,Software Engineer,125002,0 +7365,Male,35,High School,18,74,20,66,60,9.0,4,64,Semi-Urban,Data Analyst,131095,0 +7366,Male,23,Bachelors,11,59,89,73,88,5.0,5,20,Urban,Data Analyst,148004,1 +7367,Male,33,Masters,8,82,29,92,92,5.0,5,63,Semi-Urban,ML Engineer,69418,1 +7368,Male,51,Bachelors,5,36,47,84,54,1.0,0,86,Urban,HR Executive,87874,1 +7369,Male,31,Diploma,2,15,32,34,10,0.0,6,55,Urban,HR Executive,81643,0 +7370,Female,51,Bachelors,1,63,3,95,74,5.0,1,51,Rural,HR Executive,43222,0 +7371,Female,55,Bachelors,6,22,58,45,87,1.0,0,64,Urban,Software Engineer,58605,0 +7372,Female,50,Diploma,13,55,0,63,31,1.0,3,4,Urban,Data Analyst,80983,0 +7373,Male,56,Masters,18,72,56,99,73,7.0,5,26,Semi-Urban,Software Engineer,111627,1 +7374,Female,43,Bachelors,17,2,36,10,74,0.0,1,22,Urban,Manager,39535,0 +7375,Male,35,Bachelors,4,90,72,62,25,5.0,1,47,Urban,Manager,79639,1 +7376,Male,58,Masters,14,85,92,60,65,9.0,5,11,Urban,ML Engineer,88163,1 +7377,Male,58,Bachelors,15,6,94,69,10,0.0,6,71,Urban,Manager,57497,1 +7378,Male,23,High School,0,26,19,52,57,6.0,2,82,Urban,Software Engineer,69479,0 +7379,Male,43,Bachelors,12,50,53,51,48,5.0,1,41,Urban,Data Analyst,116886,0 +7380,Male,41,Bachelors,17,85,22,66,3,4.0,3,58,Semi-Urban,Manager,88178,0 +7381,Male,25,Diploma,2,29,24,76,69,8.0,5,46,Urban,HR Executive,38751,0 +7382,Male,45,Diploma,7,3,10,87,1,3.0,2,17,Urban,ML Engineer,30977,0 +7383,Other,30,PhD,2,92,94,98,3,0.0,7,30,Rural,HR Executive,91219,1 +7384,Male,32,Bachelors,10,72,3,36,29,2.0,0,19,Semi-Urban,Software Engineer,73085,0 +7385,Female,52,Masters,18,54,32,12,17,3.0,0,62,Semi-Urban,Data Analyst,63734,0 +7386,Male,42,Bachelors,10,79,40,34,12,0.0,6,34,Semi-Urban,ML Engineer,33244,0 +7387,Male,51,Bachelors,0,68,72,39,57,7.0,0,82,Urban,ML Engineer,68937,1 +7388,Other,54,High School,2,34,6,48,33,0.0,6,81,Semi-Urban,HR Executive,109886,0 +7389,Male,50,Diploma,6,57,71,43,26,0.0,7,99,Semi-Urban,Software Engineer,75679,1 +7390,Male,38,Masters,19,11,21,22,1,3.0,4,75,Urban,Manager,47882,0 +7391,Female,31,Bachelors,0,28,67,66,20,8.0,4,77,Urban,HR Executive,82599,0 +7392,Male,55,Bachelors,2,66,24,25,75,6.0,5,95,Urban,Manager,140807,0 +7393,Female,48,Diploma,6,12,76,74,63,4.0,4,91,Rural,ML Engineer,99021,1 +7394,Male,38,Masters,6,28,45,92,96,7.0,2,26,Semi-Urban,Software Engineer,118429,0 +7395,Male,21,High School,4,26,60,51,98,4.0,0,77,Urban,Software Engineer,142977,0 +7396,Male,54,Masters,14,96,89,30,73,2.0,3,22,Urban,ML Engineer,38984,1 +7397,Male,22,High School,5,31,77,79,47,4.0,3,47,Semi-Urban,Data Analyst,34132,0 +7398,Female,25,Bachelors,15,79,91,71,80,0.0,5,54,Urban,Manager,111512,1 +7399,Female,27,Bachelors,3,28,70,10,1,7.0,7,48,Semi-Urban,Data Analyst,97899,0 +7400,Male,38,Bachelors,5,14,9,27,75,0.0,2,68,Urban,Data Analyst,93841,0 +7401,Male,42,Masters,10,1,87,33,74,5.0,5,69,Urban,Data Analyst,123857,0 +7402,Female,49,High School,14,39,23,1,13,7.0,7,57,Urban,Software Engineer,86323,0 +7403,Male,48,Bachelors,11,82,19,86,72,3.0,6,49,Urban,HR Executive,68974,1 +7404,Male,59,High School,19,37,53,95,88,4.0,1,93,Urban,Software Engineer,54167,1 +7405,Male,41,Bachelors,2,70,88,43,56,6.0,4,22,Semi-Urban,Data Analyst,45812,0 +7406,Male,34,High School,5,87,89,75,71,1.0,2,93,Semi-Urban,Data Analyst,33310,1 +7407,Female,45,Diploma,18,60,34,56,31,7.0,3,83,Urban,Software Engineer,131260,0 +7408,Other,21,Bachelors,16,79,83,82,1,0.0,3,87,Urban,Data Analyst,20539,1 +7409,Male,41,High School,14,10,84,60,22,6.0,3,84,Rural,Data Analyst,68775,1 +7410,Male,52,Diploma,12,51,73,57,28,5.0,3,80,Semi-Urban,HR Executive,147263,1 +7411,Male,50,Bachelors,4,79,14,24,63,9.0,7,23,Urban,Manager,84851,0 +7412,Male,28,Masters,14,64,24,97,33,2.0,7,24,Rural,ML Engineer,109389,0 +7413,Male,58,Bachelors,5,32,25,99,76,8.0,1,9,Urban,Manager,31819,0 +7414,Female,56,High School,3,52,89,13,78,4.0,7,92,Urban,HR Executive,57807,1 +7415,Male,24,Masters,7,10,51,49,24,3.0,5,88,Urban,HR Executive,62232,0 +7416,Male,44,Bachelors,17,12,88,8,97,6.0,4,36,Urban,HR Executive,142057,0 +7417,Male,29,High School,6,8,1,44,63,6.0,1,35,Urban,Software Engineer,51777,0 +7418,Male,21,Masters,8,59,97,32,64,2.0,2,64,Rural,ML Engineer,77702,1 +7419,Male,47,Bachelors,0,78,83,75,90,0.0,2,72,Urban,Manager,44307,1 +7420,Female,53,Bachelors,8,25,17,89,19,3.0,5,59,Urban,Manager,26577,0 +7421,Male,49,Bachelors,8,13,91,44,90,8.0,0,42,Urban,Manager,68993,0 +7422,Female,56,Bachelors,10,17,66,97,24,7.0,1,98,Urban,Manager,128109,1 +7423,Male,25,High School,3,40,8,9,91,7.0,0,58,Semi-Urban,ML Engineer,42320,0 +7424,Male,49,Diploma,5,73,71,4,67,4.0,0,14,Urban,HR Executive,80144,0 +7425,Male,29,High School,10,12,30,33,94,1.0,7,0,Urban,Manager,80822,0 +7426,Male,55,Bachelors,14,93,19,88,54,7.0,1,36,Semi-Urban,ML Engineer,110743,1 +7427,Male,25,Masters,1,6,97,28,37,3.0,2,61,Urban,HR Executive,99260,0 +7428,Male,56,Bachelors,10,92,27,95,74,3.0,2,38,Urban,Data Analyst,121721,1 +7429,Female,59,Diploma,3,88,91,47,41,3.0,3,72,Semi-Urban,HR Executive,141510,1 +7430,Female,55,Bachelors,7,70,70,19,38,1.0,5,31,Semi-Urban,HR Executive,121215,0 +7431,Male,34,High School,1,97,3,32,29,2.0,1,97,Rural,HR Executive,60235,0 +7432,Male,22,Bachelors,3,50,67,65,0,0.0,2,23,Urban,Manager,32778,0 +7433,Male,27,High School,1,38,63,15,65,2.0,1,47,Semi-Urban,Data Analyst,52484,0 +7434,Male,35,Bachelors,19,75,2,48,71,1.0,3,47,Urban,ML Engineer,63578,0 +7435,Male,32,High School,4,98,36,97,33,7.0,3,61,Semi-Urban,Manager,115229,1 +7436,Female,58,Diploma,8,16,50,90,71,0.0,4,93,Rural,Data Analyst,137104,1 +7437,Male,51,Diploma,7,34,2,20,98,8.0,1,59,Urban,Software Engineer,94368,0 +7438,Male,29,Masters,6,61,77,75,38,4.0,2,71,Urban,HR Executive,110080,1 +7439,Male,42,Diploma,13,76,79,55,82,0.0,1,98,Urban,HR Executive,49740,1 +7440,Male,50,High School,19,10,16,71,3,1.0,5,70,Semi-Urban,HR Executive,43188,0 +7441,Female,58,Masters,15,95,97,73,97,9.0,2,45,Urban,ML Engineer,111444,1 +7442,Male,44,PhD,4,49,50,2,94,7.0,4,30,Urban,Manager,33443,0 +7443,Male,48,High School,18,29,80,67,84,9.0,4,4,Semi-Urban,ML Engineer,21524,0 +7444,Female,36,High School,14,75,68,78,24,9.0,7,97,Urban,ML Engineer,108946,1 +7445,Male,37,High School,15,30,46,13,14,6.0,7,20,Semi-Urban,Data Analyst,107143,0 +7446,Female,35,Bachelors,13,59,43,90,50,6.0,2,16,Semi-Urban,ML Engineer,79908,0 +7447,Male,32,Masters,12,40,58,1,24,4.0,4,27,Rural,Manager,118380,0 +7448,Male,53,Bachelors,0,43,89,66,95,0.0,4,37,Urban,Manager,136732,1 +7449,Female,48,Diploma,1,23,89,53,17,5.0,0,76,Urban,HR Executive,65119,1 +7450,Male,24,Bachelors,13,43,7,46,64,1.0,2,18,Urban,Software Engineer,45197,0 +7451,Male,41,Bachelors,8,55,42,46,73,4.0,3,29,Semi-Urban,ML Engineer,117021,0 +7452,Male,41,Masters,10,56,10,4,38,3.0,5,34,Rural,HR Executive,21314,0 +7453,Male,25,PhD,8,55,28,78,97,0.0,0,92,Semi-Urban,HR Executive,116522,1 +7454,Female,32,Bachelors,1,93,11,14,63,7.0,0,74,Semi-Urban,Data Analyst,139089,0 +7455,Female,28,Bachelors,17,35,88,83,83,1.0,4,29,Urban,Manager,126967,0 +7456,Other,32,Bachelors,4,99,84,76,18,7.0,4,49,Rural,Software Engineer,110658,1 +7457,Female,31,High School,2,9,35,47,55,3.0,6,53,Urban,ML Engineer,128300,0 +7458,Male,51,Bachelors,0,2,25,99,8,3.0,1,14,Urban,HR Executive,23116,0 +7459,Male,33,Masters,1,8,20,38,28,8.0,4,53,Semi-Urban,HR Executive,85327,0 +7460,Male,52,Diploma,0,30,94,92,76,5.0,2,69,Urban,ML Engineer,78395,1 +7461,Male,35,Bachelors,10,48,99,64,86,8.0,6,21,Semi-Urban,ML Engineer,68261,0 +7462,Male,50,Bachelors,4,50,7,54,15,8.0,2,9,Urban,Data Analyst,123009,0 +7463,Female,26,Bachelors,14,61,90,45,10,1.0,4,48,Rural,HR Executive,123356,1 +7464,Male,28,Bachelors,8,65,68,51,5,0.0,0,62,Semi-Urban,HR Executive,51034,1 +7465,Male,35,Masters,15,23,54,86,59,1.0,0,41,Semi-Urban,Software Engineer,43818,0 +7466,Male,51,High School,2,51,55,78,44,5.0,0,47,Urban,HR Executive,104365,0 +7467,Female,34,Bachelors,11,4,80,93,25,5.0,4,62,Rural,ML Engineer,75095,0 +7468,Female,29,Diploma,12,37,78,83,91,5.0,5,18,Rural,HR Executive,80545,0 +7469,Female,48,High School,13,25,87,13,96,9.0,1,61,Urban,Manager,127317,0 +7470,Male,39,High School,5,0,10,23,30,0.0,5,61,Rural,HR Executive,64492,0 +7471,Female,29,Masters,12,14,74,61,83,8.0,7,59,Urban,ML Engineer,132223,0 +7472,Male,34,Bachelors,2,28,67,30,15,0.0,3,5,Urban,Manager,103806,0 +7473,Female,55,Bachelors,15,46,10,81,23,7.0,2,85,Semi-Urban,Manager,105565,0 +7474,Male,48,Masters,11,57,66,61,79,2.0,1,70,Semi-Urban,HR Executive,129026,1 +7475,Male,55,Bachelors,1,29,76,26,80,1.0,7,70,Urban,Software Engineer,41102,0 +7476,Male,41,Bachelors,10,82,75,68,30,9.0,5,55,Urban,HR Executive,21603,1 +7477,Female,23,High School,14,93,8,51,43,6.0,0,45,Urban,Manager,48819,0 +7478,Male,37,Diploma,10,8,14,83,64,7.0,7,20,Rural,Manager,136746,0 +7479,Female,21,Masters,10,29,82,29,85,0.0,5,23,Urban,Manager,99875,0 +7480,Male,29,High School,5,12,52,51,31,6.0,0,94,Urban,Software Engineer,126120,0 +7481,Male,51,Masters,9,48,52,60,62,5.0,4,21,Rural,Software Engineer,39737,0 +7482,Male,54,High School,6,62,65,45,83,0.0,7,54,Urban,HR Executive,126734,0 +7483,Male,47,High School,10,37,64,10,39,5.0,5,29,Semi-Urban,Data Analyst,66887,0 +7484,Male,51,Masters,3,28,13,50,89,1.0,1,75,Rural,Manager,89984,0 +7485,Male,56,High School,15,71,91,38,76,1.0,7,42,Urban,Manager,40210,1 +7486,Female,54,Masters,0,55,30,48,95,6.0,3,99,Urban,Data Analyst,135156,0 +7487,Male,36,Diploma,2,46,49,92,56,7.0,2,6,Urban,HR Executive,119017,0 +7488,Other,43,Bachelors,4,66,90,57,46,9.0,1,7,Urban,Manager,82087,0 +7489,Male,42,PhD,9,72,25,56,49,2.0,6,80,Urban,HR Executive,53234,0 +7490,Female,24,Bachelors,14,68,99,70,38,1.0,2,28,Semi-Urban,ML Engineer,22761,1 +7491,Male,23,Bachelors,4,76,10,55,84,3.0,0,12,Semi-Urban,Manager,107517,0 +7492,Male,35,Bachelors,2,91,4,67,17,6.0,1,82,Rural,HR Executive,149117,1 +7493,Male,53,Diploma,8,60,89,2,72,0.0,1,38,Urban,Data Analyst,124157,0 +7494,Male,28,PhD,14,61,34,72,23,7.0,2,84,Urban,HR Executive,130320,1 +7495,Female,34,High School,5,18,25,45,42,3.0,0,10,Urban,Data Analyst,22423,0 +7496,Male,56,PhD,7,51,80,20,47,6.0,6,20,Urban,Software Engineer,135824,0 +7497,Male,58,High School,17,42,65,57,59,2.0,4,79,Urban,ML Engineer,57620,1 +7498,Female,34,High School,16,77,18,61,15,6.0,5,26,Urban,Data Analyst,132299,0 +7499,Male,56,High School,19,52,61,47,73,5.0,3,77,Urban,Data Analyst,27942,1 +7500,Female,48,Masters,16,34,42,74,1,4.0,5,97,Semi-Urban,Manager,49097,1 +7501,Male,51,Diploma,14,62,72,24,45,5.0,0,10,Urban,Software Engineer,80701,0 +7502,Female,21,Diploma,11,54,13,71,47,6.0,5,64,Urban,ML Engineer,24383,0 +7503,Male,51,High School,8,41,59,19,6,2.0,2,21,Urban,Manager,89392,0 +7504,Male,50,Bachelors,10,49,78,95,12,6.0,5,13,Urban,ML Engineer,47553,1 +7505,Male,32,Bachelors,10,73,26,84,26,4.0,2,10,Urban,Manager,44442,0 +7506,Female,34,Masters,2,50,37,0,89,1.0,3,46,Semi-Urban,Data Analyst,148874,0 +7507,Male,57,High School,3,66,48,40,91,6.0,6,98,Urban,HR Executive,143432,1 +7508,Male,26,High School,0,80,7,59,0,5.0,0,46,Urban,ML Engineer,98081,0 +7509,Female,50,Bachelors,0,18,7,7,53,2.0,6,98,Urban,Data Analyst,73462,0 +7510,Female,37,Diploma,17,31,57,2,37,7.0,3,23,Semi-Urban,Manager,100820,0 +7511,Female,33,Bachelors,18,37,31,66,38,0.0,5,97,Urban,Data Analyst,143744,0 +7512,Other,58,High School,8,98,81,27,33,0.0,7,53,Urban,Manager,82112,1 +7513,Male,36,Masters,0,19,43,8,12,7.0,3,69,Semi-Urban,Manager,52205,0 +7514,Male,48,High School,14,53,2,61,70,0.0,6,80,Semi-Urban,ML Engineer,70901,0 +7515,Female,32,Masters,4,78,20,32,66,4.0,1,66,Urban,Software Engineer,91592,0 +7516,Female,56,Bachelors,5,75,77,41,69,4.0,4,73,Rural,Data Analyst,83882,1 +7517,Male,36,Diploma,7,68,83,82,98,1.0,2,1,Urban,ML Engineer,93894,0 +7518,Male,32,Masters,11,73,53,11,10,1.0,3,48,Rural,Manager,54907,0 +7519,Female,21,Bachelors,13,96,97,41,64,0.0,6,36,Urban,Data Analyst,26793,1 +7520,Male,39,Masters,19,21,14,2,17,5.0,3,49,Urban,Manager,124819,0 +7521,Male,26,High School,9,30,22,96,59,1.0,1,8,Urban,Data Analyst,118773,0 +7522,Male,26,Bachelors,17,39,28,2,78,0.0,6,3,Rural,Data Analyst,50575,0 +7523,Male,38,High School,19,19,37,12,26,9.0,4,32,Urban,HR Executive,116359,0 +7524,Female,48,Bachelors,4,95,11,53,91,3.0,3,83,Urban,Software Engineer,130859,1 +7525,Male,32,High School,6,74,61,25,13,4.0,7,92,Urban,ML Engineer,85217,1 +7526,Female,51,Bachelors,5,74,90,25,70,2.0,0,87,Urban,Manager,141309,1 +7527,Male,47,Bachelors,17,95,31,34,71,5.0,3,0,Rural,Software Engineer,103506,0 +7528,Male,28,Masters,17,7,17,88,72,8.0,2,71,Urban,Manager,34375,0 +7529,Female,31,Bachelors,1,37,33,43,68,3.0,2,86,Rural,ML Engineer,118503,0 +7530,Male,27,Masters,7,39,25,57,17,0.0,4,49,Rural,HR Executive,34327,0 +7531,Male,42,Masters,9,91,61,53,47,9.0,3,31,Urban,HR Executive,120047,1 +7532,Male,40,Bachelors,14,97,86,77,8,2.0,3,7,Urban,Data Analyst,128259,1 +7533,Male,39,Masters,8,94,72,67,2,1.0,7,86,Urban,ML Engineer,135941,1 +7534,Male,22,High School,1,0,18,95,84,5.0,2,35,Urban,Manager,94077,0 +7535,Female,47,Masters,9,2,42,43,77,6.0,0,87,Urban,ML Engineer,62942,0 +7536,Female,45,Masters,14,34,68,62,52,8.0,3,92,Rural,Software Engineer,65925,1 +7537,Female,31,Bachelors,14,5,32,78,66,9.0,4,69,Urban,Software Engineer,41524,0 +7538,Male,29,Bachelors,0,39,39,25,17,0.0,2,3,Urban,ML Engineer,29035,0 +7539,Male,46,Masters,18,61,56,51,55,9.0,5,16,Rural,Software Engineer,146119,0 +7540,Male,51,Diploma,6,52,72,35,18,5.0,5,27,Urban,Manager,64216,0 +7541,Male,31,Bachelors,14,44,0,52,10,5.0,0,30,Rural,ML Engineer,114939,0 +7542,Male,32,Diploma,0,4,86,12,5,4.0,6,94,Rural,Data Analyst,59239,0 +7543,Male,30,PhD,6,56,81,10,14,6.0,2,91,Rural,ML Engineer,77006,1 +7544,Other,46,Masters,2,92,14,87,14,8.0,4,14,Rural,ML Engineer,83963,0 +7545,Male,29,Bachelors,7,43,94,91,62,5.0,6,16,Rural,Data Analyst,119488,1 +7546,Male,38,High School,13,40,80,0,86,9.0,3,2,Rural,Software Engineer,79818,0 +7547,Female,45,Bachelors,18,64,67,82,38,3.0,5,8,Semi-Urban,Software Engineer,22022,0 +7548,Male,38,Bachelors,3,93,88,14,29,4.0,5,38,Semi-Urban,ML Engineer,51182,0 +7549,Female,34,High School,19,68,86,67,44,0.0,3,3,Urban,Data Analyst,45734,0 +7550,Female,47,Masters,4,52,12,75,90,2.0,2,66,Semi-Urban,Manager,31726,0 +7551,Female,42,High School,4,92,12,46,40,2.0,0,8,Rural,ML Engineer,105005,0 +7552,Male,56,Bachelors,17,46,26,3,34,3.0,5,13,Semi-Urban,HR Executive,145885,0 +7553,Female,37,Diploma,6,74,26,28,1,4.0,5,40,Urban,Manager,73735,0 +7554,Male,32,Bachelors,4,5,63,92,93,8.0,4,71,Urban,ML Engineer,64637,0 +7555,Female,34,Masters,10,33,68,29,38,3.0,2,41,Urban,HR Executive,126130,0 +7556,Male,26,Diploma,19,92,1,22,36,7.0,5,83,Urban,HR Executive,121806,0 +7557,Male,30,Masters,9,58,96,81,14,8.0,4,96,Semi-Urban,Data Analyst,76207,1 +7558,Male,34,Masters,13,91,9,15,22,4.0,0,25,Semi-Urban,Data Analyst,118533,0 +7559,Male,42,High School,10,76,32,92,56,7.0,6,45,Urban,Manager,22215,1 +7560,Female,23,High School,15,31,76,60,53,7.0,1,78,Urban,ML Engineer,39712,1 +7561,Female,28,High School,4,13,2,86,17,3.0,0,87,Urban,HR Executive,42997,0 +7562,Female,58,Bachelors,14,35,3,77,7,7.0,6,9,Rural,HR Executive,36675,0 +7563,Male,56,Bachelors,7,32,91,77,80,2.0,1,0,Urban,ML Engineer,114606,0 +7564,Female,25,Masters,12,96,20,16,93,0.0,2,52,Urban,Software Engineer,49977,0 +7565,Male,54,Diploma,17,60,1,64,20,6.0,5,71,Urban,Data Analyst,128243,0 +7566,Female,21,Bachelors,3,94,75,63,47,0.0,7,73,Urban,ML Engineer,89135,1 +7567,Female,25,Masters,15,43,11,9,12,6.0,0,68,Urban,HR Executive,38543,0 +7568,Male,33,Diploma,9,48,35,3,0,9.0,7,28,Urban,ML Engineer,132806,0 +7569,Female,46,Bachelors,6,89,69,30,30,8.0,4,23,Urban,ML Engineer,135373,0 +7570,Male,54,Diploma,9,55,2,56,84,1.0,6,21,Urban,Data Analyst,61402,0 +7571,Male,51,Bachelors,3,47,94,26,1,5.0,6,16,Semi-Urban,HR Executive,28473,0 +7572,Male,58,Bachelors,8,21,7,52,85,1.0,1,19,Urban,HR Executive,44945,0 +7573,Male,42,Bachelors,8,85,68,43,53,9.0,7,40,Urban,Data Analyst,84112,1 +7574,Female,48,Diploma,8,96,29,44,61,1.0,1,7,Semi-Urban,Software Engineer,40696,0 +7575,Male,30,Bachelors,5,82,68,55,35,1.0,6,3,Rural,Software Engineer,141585,0 +7576,Male,40,Masters,18,32,13,71,34,4.0,6,80,Urban,ML Engineer,112735,0 +7577,Male,32,Bachelors,14,57,29,54,46,3.0,3,77,Urban,Manager,110038,0 +7578,Female,38,PhD,6,56,12,67,32,2.0,6,39,Urban,Manager,81718,0 +7579,Female,57,Bachelors,3,10,33,62,1,3.0,7,25,Urban,Manager,103801,0 +7580,Female,57,High School,15,89,85,53,65,8.0,1,43,Urban,Software Engineer,111014,1 +7581,Female,29,Masters,12,61,38,59,26,4.0,7,4,Semi-Urban,Manager,74437,0 +7582,Male,47,Masters,19,26,17,96,5,9.0,4,87,Semi-Urban,Manager,27618,0 +7583,Male,37,Masters,5,73,13,33,74,2.0,0,9,Urban,ML Engineer,33067,0 +7584,Male,22,Masters,17,30,77,9,12,8.0,4,19,Urban,ML Engineer,73222,0 +7585,Male,21,Bachelors,8,92,13,94,35,2.0,1,23,Urban,Data Analyst,107770,0 +7586,Female,35,Bachelors,6,49,97,86,58,5.0,1,88,Urban,ML Engineer,47354,1 +7587,Male,32,Bachelors,5,6,84,42,89,7.0,4,66,Urban,HR Executive,77727,0 +7588,Female,38,High School,1,97,84,25,34,6.0,0,74,Urban,ML Engineer,28240,1 +7589,Male,44,Bachelors,2,23,82,6,52,3.0,4,42,Urban,Data Analyst,60311,0 +7590,Male,53,Diploma,11,13,28,34,49,3.0,2,32,Urban,HR Executive,79958,0 +7591,Male,56,Bachelors,9,58,32,94,29,2.0,3,29,Semi-Urban,Manager,112360,0 +7592,Female,51,Bachelors,11,1,77,1,67,2.0,0,32,Urban,Software Engineer,53838,0 +7593,Female,40,Bachelors,7,4,94,35,36,2.0,0,75,Rural,Software Engineer,22879,0 +7594,Female,58,Diploma,18,40,80,49,84,1.0,1,86,Urban,Manager,128504,1 +7595,Male,48,Diploma,12,53,85,88,46,1.0,5,81,Semi-Urban,Manager,57634,1 +7596,Other,31,Bachelors,4,40,87,31,43,9.0,5,98,Urban,Manager,145806,1 +7597,Male,47,Masters,14,89,49,24,52,5.0,1,19,Urban,HR Executive,31106,0 +7598,Male,28,Diploma,14,41,85,94,55,5.0,1,34,Urban,HR Executive,127212,1 +7599,Other,33,Masters,14,7,1,21,23,0.0,6,53,Urban,Software Engineer,64149,0 +7600,Male,41,Diploma,0,65,83,80,10,9.0,5,48,Urban,Manager,107842,1 +7601,Female,23,Masters,12,64,38,66,0,5.0,5,90,Rural,HR Executive,24902,1 +7602,Male,57,Masters,6,81,45,25,75,2.0,6,22,Rural,Data Analyst,140954,0 +7603,Male,27,Masters,13,34,97,76,44,0.0,2,19,Semi-Urban,ML Engineer,22672,0 +7604,Female,35,Bachelors,16,43,22,77,71,7.0,7,18,Urban,HR Executive,101162,0 +7605,Male,25,Masters,17,95,7,69,4,1.0,1,77,Urban,Data Analyst,56551,1 +7606,Female,54,Bachelors,10,42,31,21,82,9.0,5,41,Urban,Manager,85514,0 +7607,Male,39,Bachelors,10,99,68,78,97,6.0,3,44,Semi-Urban,Data Analyst,69836,1 +7608,Female,53,Masters,11,10,45,66,67,6.0,7,96,Rural,Manager,147715,0 +7609,Male,23,Diploma,19,34,97,81,48,6.0,6,88,Urban,Software Engineer,125562,1 +7610,Male,25,Masters,4,73,40,63,27,0.0,3,98,Urban,HR Executive,67545,1 +7611,Male,39,Diploma,15,45,73,73,52,3.0,2,49,Urban,Manager,146713,1 +7612,Male,22,Masters,13,44,18,75,54,7.0,7,45,Urban,Manager,122656,0 +7613,Female,26,Diploma,4,89,39,37,76,3.0,2,41,Urban,Manager,53969,0 +7614,Male,59,Masters,9,40,29,53,42,5.0,6,77,Urban,HR Executive,130857,0 +7615,Male,34,Diploma,4,78,50,52,2,6.0,2,32,Semi-Urban,ML Engineer,110917,0 +7616,Male,24,Diploma,19,30,32,25,47,6.0,5,60,Urban,ML Engineer,80121,0 +7617,Male,40,Bachelors,5,27,31,17,73,2.0,1,63,Semi-Urban,Manager,123000,0 +7618,Female,21,Bachelors,7,48,28,32,46,7.0,0,65,Urban,Manager,89430,0 +7619,Other,54,Masters,1,68,77,50,34,2.0,7,10,Semi-Urban,ML Engineer,30181,0 +7620,Male,49,Diploma,5,10,7,33,69,1.0,2,65,Urban,Software Engineer,99176,0 +7621,Female,59,Masters,10,25,59,93,65,2.0,1,50,Semi-Urban,Software Engineer,44171,0 +7622,Male,50,Masters,9,97,4,12,18,9.0,3,68,Urban,ML Engineer,108926,0 +7623,Male,31,Masters,13,82,92,33,4,4.0,5,42,Urban,Manager,147476,1 +7624,Female,40,Diploma,3,83,38,61,34,8.0,5,58,Urban,Software Engineer,80432,0 +7625,Male,57,PhD,14,8,88,61,77,9.0,4,86,Semi-Urban,Data Analyst,36717,1 +7626,Female,41,Masters,13,39,32,26,89,2.0,1,5,Urban,ML Engineer,138919,0 +7627,Female,45,Masters,13,81,33,82,87,2.0,7,19,Urban,Software Engineer,84989,0 +7628,Male,56,Masters,15,44,92,91,21,8.0,2,11,Urban,HR Executive,143233,1 +7629,Female,24,Bachelors,1,29,69,85,30,8.0,0,0,Semi-Urban,HR Executive,112244,0 +7630,Female,43,Bachelors,9,10,91,19,75,2.0,6,8,Semi-Urban,Data Analyst,112018,0 +7631,Male,26,Bachelors,17,93,65,94,72,5.0,4,29,Urban,Data Analyst,148380,1 +7632,Female,46,Bachelors,12,36,56,78,65,4.0,2,44,Urban,HR Executive,30185,0 +7633,Male,48,High School,1,97,2,37,66,0.0,2,37,Urban,HR Executive,21716,0 +7634,Other,44,Bachelors,7,25,53,22,35,8.0,3,66,Urban,Data Analyst,37732,0 +7635,Female,53,PhD,16,58,0,85,27,0.0,5,27,Rural,Software Engineer,53310,0 +7636,Male,46,Bachelors,14,76,34,60,15,1.0,5,16,Semi-Urban,HR Executive,141708,0 +7637,Male,46,Diploma,10,70,26,34,93,0.0,0,13,Semi-Urban,Data Analyst,75387,0 +7638,Female,45,Bachelors,3,56,78,87,66,1.0,6,76,Semi-Urban,HR Executive,134551,1 +7639,Male,50,Bachelors,10,18,18,3,91,2.0,7,73,Urban,Data Analyst,98946,0 +7640,Male,58,Bachelors,3,46,55,84,82,0.0,4,93,Rural,Data Analyst,26911,1 +7641,Male,56,Diploma,16,27,82,4,47,1.0,0,88,Urban,ML Engineer,45440,0 +7642,Male,40,Bachelors,16,99,15,68,23,5.0,4,13,Urban,Manager,100069,0 +7643,Male,56,Bachelors,7,83,5,80,91,9.0,6,94,Urban,Data Analyst,68369,1 +7644,Male,25,High School,15,13,91,97,35,1.0,3,64,Urban,Manager,127520,1 +7645,Male,52,Masters,11,69,8,7,42,1.0,6,84,Semi-Urban,Software Engineer,37405,0 +7646,Female,50,Bachelors,13,83,75,22,11,1.0,2,72,Urban,Manager,145987,1 +7647,Male,47,Masters,3,51,96,2,7,1.0,7,49,Urban,HR Executive,149922,0 +7648,Male,44,High School,17,33,38,0,36,4.0,7,59,Urban,ML Engineer,135107,0 +7649,Male,41,Bachelors,2,23,18,82,50,5.0,0,51,Urban,ML Engineer,74222,0 +7650,Male,21,Masters,11,72,13,68,73,5.0,4,60,Urban,HR Executive,49340,0 +7651,Male,36,High School,5,74,82,62,58,2.0,1,67,Urban,Software Engineer,81578,1 +7652,Male,34,Bachelors,0,32,20,23,28,6.0,7,69,Rural,Manager,64360,0 +7653,Male,30,Bachelors,14,1,53,70,3,7.0,0,35,Urban,ML Engineer,118379,0 +7654,Female,48,Bachelors,8,40,15,66,56,9.0,2,40,Urban,HR Executive,76116,0 +7655,Female,56,High School,5,59,16,94,44,6.0,1,29,Semi-Urban,Manager,35491,0 +7656,Female,39,Bachelors,8,52,63,89,99,5.0,7,73,Urban,HR Executive,79127,1 +7657,Female,32,High School,17,87,33,87,74,1.0,4,4,Rural,Manager,90355,0 +7658,Female,38,Diploma,10,12,65,41,56,3.0,6,84,Urban,Data Analyst,97524,0 +7659,Male,35,Bachelors,7,15,97,55,72,3.0,5,3,Urban,Software Engineer,110649,0 +7660,Female,39,Bachelors,16,55,86,39,60,2.0,0,89,Semi-Urban,Manager,72022,1 +7661,Male,38,High School,15,18,10,18,65,6.0,4,23,Rural,Data Analyst,94712,0 +7662,Female,48,Diploma,10,97,24,27,28,7.0,5,26,Urban,Data Analyst,132512,0 +7663,Female,37,Bachelors,7,89,68,60,16,0.0,4,55,Urban,Software Engineer,94474,1 +7664,Male,41,Bachelors,6,1,21,74,82,2.0,5,66,Urban,Software Engineer,47788,0 +7665,Male,48,Diploma,15,71,66,76,51,2.0,6,13,Urban,Software Engineer,145132,0 +7666,Male,36,High School,12,70,18,34,87,3.0,5,98,Rural,ML Engineer,116494,0 +7667,Female,46,PhD,15,2,79,53,56,0.0,1,86,Rural,Manager,128517,0 +7668,Female,39,Diploma,2,95,3,22,47,1.0,0,17,Rural,Data Analyst,111320,0 +7669,Female,21,Masters,7,21,78,27,1,3.0,0,88,Semi-Urban,HR Executive,40683,0 +7670,Male,49,Diploma,10,89,38,87,58,8.0,2,14,Semi-Urban,Manager,87034,0 +7671,Female,42,Bachelors,15,8,86,52,39,3.0,0,7,Rural,HR Executive,140372,0 +7672,Male,52,Bachelors,3,6,85,35,87,9.0,1,41,Semi-Urban,ML Engineer,83609,0 +7673,Female,38,Bachelors,1,46,94,77,25,9.0,2,42,Semi-Urban,ML Engineer,142575,1 +7674,Male,56,Bachelors,10,84,76,66,58,1.0,7,7,Urban,Data Analyst,123989,0 +7675,Male,27,Bachelors,0,65,12,94,94,3.0,5,20,Urban,HR Executive,128220,0 +7676,Male,28,Diploma,4,76,14,87,46,5.0,6,73,Urban,Manager,91759,1 +7677,Female,33,Masters,17,70,18,11,9,5.0,5,13,Rural,HR Executive,37725,0 +7678,Other,26,Masters,0,25,46,15,65,4.0,5,10,Semi-Urban,Data Analyst,23122,0 +7679,Male,34,Bachelors,11,51,20,61,24,4.0,6,94,Urban,Manager,145430,0 +7680,Male,21,Masters,5,20,76,6,1,9.0,0,63,Semi-Urban,Manager,96995,0 +7681,Female,40,Masters,3,5,11,32,98,6.0,6,68,Semi-Urban,Manager,54271,0 +7682,Male,39,Diploma,4,84,56,30,53,7.0,5,27,Urban,Software Engineer,95140,0 +7683,Female,43,Masters,10,97,7,25,32,4.0,7,69,Rural,Manager,71112,0 +7684,Male,27,Bachelors,4,64,95,42,33,6.0,2,84,Urban,ML Engineer,29513,1 +7685,Male,43,Diploma,6,9,6,67,1,1.0,4,58,Urban,Data Analyst,40808,0 +7686,Female,45,Diploma,5,86,46,88,68,0.0,0,13,Semi-Urban,Software Engineer,135407,0 +7687,Female,59,Masters,0,28,19,13,80,7.0,5,1,Semi-Urban,ML Engineer,75365,0 +7688,Male,27,Diploma,14,67,7,11,61,0.0,6,36,Semi-Urban,Manager,140741,0 +7689,Male,53,Diploma,3,0,75,4,48,6.0,7,77,Rural,Data Analyst,26237,0 +7690,Female,32,Bachelors,3,17,57,4,19,5.0,2,27,Urban,ML Engineer,26547,0 +7691,Male,38,Bachelors,3,88,7,80,61,7.0,2,39,Semi-Urban,Software Engineer,35816,0 +7692,Female,53,Bachelors,3,81,42,66,78,0.0,1,82,Urban,ML Engineer,147815,1 +7693,Male,24,Bachelors,16,80,0,88,97,7.0,3,0,Urban,HR Executive,113961,0 +7694,Male,46,High School,11,23,90,21,24,7.0,1,93,Semi-Urban,Manager,109624,0 +7695,Female,55,Bachelors,7,10,64,17,38,8.0,1,15,Rural,Software Engineer,25027,0 +7696,Female,43,Masters,6,85,88,81,20,6.0,0,0,Urban,Manager,133407,1 +7697,Male,48,Masters,8,33,35,37,19,2.0,4,16,Rural,Data Analyst,110306,0 +7698,Female,55,Bachelors,18,72,80,80,57,4.0,5,45,Urban,HR Executive,114886,1 +7699,Male,42,Bachelors,18,91,5,22,64,9.0,7,28,Rural,Data Analyst,120102,0 +7700,Male,56,Diploma,4,57,38,92,24,4.0,0,52,Semi-Urban,ML Engineer,132217,1 +7701,Other,28,High School,3,99,79,16,65,1.0,5,59,Urban,HR Executive,54378,1 +7702,Female,26,Bachelors,17,17,72,26,41,2.0,0,26,Urban,Manager,136464,0 +7703,Female,22,Bachelors,9,45,41,43,11,6.0,2,69,Semi-Urban,Manager,132730,0 +7704,Male,32,Masters,13,27,25,87,89,4.0,2,35,Rural,Data Analyst,108732,0 +7705,Male,49,Masters,13,3,13,24,88,8.0,1,61,Urban,Software Engineer,129674,0 +7706,Male,31,Masters,14,70,92,17,83,8.0,7,9,Urban,Manager,21210,0 +7707,Male,39,Bachelors,0,54,21,76,6,4.0,5,5,Semi-Urban,Software Engineer,106031,0 +7708,Female,23,Bachelors,2,51,59,35,84,0.0,5,90,Urban,HR Executive,33017,0 +7709,Male,41,Diploma,19,1,18,17,22,4.0,6,28,Semi-Urban,ML Engineer,52809,0 +7710,Female,46,Masters,15,91,87,34,24,6.0,6,64,Urban,Data Analyst,55330,1 +7711,Male,47,Bachelors,15,54,65,34,9,3.0,5,51,Urban,Data Analyst,70977,0 +7712,Male,49,Masters,5,16,73,63,98,5.0,2,71,Urban,Data Analyst,59738,0 +7713,Male,34,High School,13,0,43,26,52,4.0,4,60,Urban,ML Engineer,67631,0 +7714,Male,21,Diploma,9,7,13,68,14,7.0,0,87,Urban,ML Engineer,144849,0 +7715,Male,39,Bachelors,18,58,45,86,37,2.0,0,2,Rural,Data Analyst,70229,0 +7716,Other,56,Bachelors,4,25,18,19,27,7.0,0,25,Urban,ML Engineer,25274,0 +7717,Male,26,Masters,15,12,83,55,50,3.0,3,58,Rural,Manager,139827,0 +7718,Female,33,Diploma,3,30,82,76,47,0.0,7,23,Urban,ML Engineer,101560,0 +7719,Male,39,High School,19,95,43,66,98,2.0,7,39,Rural,HR Executive,98294,1 +7720,Other,24,High School,5,34,81,41,74,3.0,6,51,Semi-Urban,HR Executive,137808,0 +7721,Male,44,Bachelors,12,9,59,51,52,5.0,6,12,Rural,HR Executive,59693,0 +7722,Female,57,Bachelors,16,55,40,24,65,5.0,2,6,Urban,HR Executive,86010,0 +7723,Male,52,Bachelors,14,46,65,13,6,3.0,2,47,Rural,HR Executive,135184,0 +7724,Female,42,Bachelors,7,47,3,69,86,8.0,0,9,Urban,Software Engineer,70517,0 +7725,Female,52,Bachelors,5,64,1,19,1,3.0,7,43,Urban,Data Analyst,32409,0 +7726,Male,37,Bachelors,9,5,90,61,59,9.0,5,19,Urban,ML Engineer,93130,0 +7727,Male,58,Bachelors,13,71,40,86,1,5.0,0,46,Rural,Data Analyst,41705,1 +7728,Male,34,High School,2,77,91,20,49,9.0,5,52,Urban,Data Analyst,31529,1 +7729,Female,33,Bachelors,17,69,51,51,16,2.0,6,16,Urban,Manager,133735,0 +7730,Male,43,Masters,2,36,64,98,96,0.0,7,38,Rural,HR Executive,95640,1 +7731,Male,41,PhD,6,7,4,27,61,4.0,5,96,Urban,Manager,50755,0 +7732,Male,47,Diploma,6,42,56,11,86,9.0,5,9,Semi-Urban,HR Executive,90784,0 +7733,Male,26,Bachelors,10,20,86,46,73,0.0,7,94,Semi-Urban,Software Engineer,46316,1 +7734,Female,32,High School,15,82,5,82,91,1.0,6,38,Semi-Urban,Data Analyst,40413,0 +7735,Male,30,Masters,4,12,64,79,49,6.0,1,28,Urban,Software Engineer,104697,0 +7736,Female,39,Bachelors,3,92,6,55,65,6.0,7,10,Semi-Urban,HR Executive,105176,0 +7737,Female,32,Masters,9,6,59,67,16,1.0,7,42,Semi-Urban,Software Engineer,79268,0 +7738,Male,57,PhD,11,1,48,93,41,6.0,5,84,Rural,HR Executive,58124,0 +7739,Female,31,Bachelors,19,88,88,91,49,2.0,4,75,Urban,Data Analyst,94487,1 +7740,Male,32,Bachelors,15,96,98,59,53,5.0,7,0,Urban,HR Executive,34349,1 +7741,Female,26,Diploma,13,13,78,52,3,5.0,1,52,Semi-Urban,HR Executive,138573,0 +7742,Male,46,Diploma,4,59,12,83,67,0.0,6,30,Urban,HR Executive,67609,0 +7743,Female,32,High School,0,47,29,64,33,6.0,6,49,Semi-Urban,Data Analyst,72945,0 +7744,Male,23,Masters,1,3,35,38,60,1.0,2,34,Urban,Software Engineer,30049,0 +7745,Male,45,High School,7,49,48,90,36,2.0,0,44,Urban,ML Engineer,97784,0 +7746,Male,24,Bachelors,9,41,58,5,81,7.0,3,55,Urban,Data Analyst,113068,0 +7747,Male,43,PhD,5,84,33,69,70,3.0,7,26,Urban,Software Engineer,97549,0 +7748,Female,21,Diploma,12,57,30,41,2,1.0,1,15,Rural,HR Executive,24542,0 +7749,Male,24,Diploma,4,42,98,29,16,5.0,0,25,Urban,HR Executive,138357,0 +7750,Female,37,Masters,6,56,67,79,9,2.0,3,89,Urban,Manager,90902,1 +7751,Male,29,Masters,8,78,43,21,17,4.0,1,86,Semi-Urban,Manager,109533,0 +7752,Female,38,Bachelors,18,48,18,85,15,9.0,4,86,Semi-Urban,ML Engineer,105720,0 +7753,Male,37,Bachelors,10,25,86,44,44,9.0,5,7,Rural,Manager,21965,0 +7754,Male,37,Bachelors,12,15,56,95,31,8.0,7,37,Urban,Software Engineer,33755,0 +7755,Male,39,Masters,14,46,96,54,16,7.0,4,35,Urban,ML Engineer,55541,0 +7756,Female,41,Diploma,6,20,95,62,98,8.0,0,65,Urban,ML Engineer,68990,1 +7757,Male,54,Masters,11,26,54,23,94,5.0,7,27,Rural,Data Analyst,49387,0 +7758,Female,51,Diploma,11,70,59,53,94,9.0,3,34,Rural,ML Engineer,120767,0 +7759,Female,48,Diploma,3,56,35,65,77,1.0,3,35,Rural,ML Engineer,109025,0 +7760,Male,42,Diploma,1,28,9,59,89,4.0,5,2,Rural,ML Engineer,106028,0 +7761,Female,56,Bachelors,9,96,5,60,37,9.0,6,63,Urban,Data Analyst,128403,0 +7762,Male,54,Diploma,6,12,28,32,63,5.0,2,36,Semi-Urban,HR Executive,33571,0 +7763,Male,31,Diploma,11,23,44,8,25,1.0,1,28,Rural,Software Engineer,122022,0 +7764,Female,27,PhD,12,14,37,63,45,1.0,7,6,Urban,HR Executive,43309,0 +7765,Female,42,PhD,0,69,12,34,94,5.0,3,89,Urban,Data Analyst,144949,0 +7766,Female,41,Masters,12,6,31,61,84,4.0,7,23,Urban,HR Executive,138264,0 +7767,Male,59,Diploma,10,13,16,88,84,9.0,1,66,Semi-Urban,Manager,139115,0 +7768,Male,31,Masters,5,53,69,81,55,2.0,4,73,Urban,Manager,103549,1 +7769,Male,27,Bachelors,3,21,18,62,38,0.0,2,66,Rural,Software Engineer,96942,0 +7770,Female,23,Bachelors,9,33,26,92,80,1.0,5,58,Semi-Urban,HR Executive,73182,0 +7771,Male,59,Bachelors,13,60,40,75,83,4.0,7,35,Semi-Urban,Data Analyst,117415,0 +7772,Female,56,High School,4,90,17,16,98,8.0,6,61,Rural,HR Executive,28089,0 +7773,Male,38,High School,1,50,5,73,98,0.0,7,63,Urban,HR Executive,45140,0 +7774,Male,27,Bachelors,16,87,81,6,70,8.0,6,71,Urban,HR Executive,142814,1 +7775,Male,50,Bachelors,13,51,76,55,22,4.0,6,64,Urban,Data Analyst,62278,1 +7776,Male,47,Masters,6,39,27,98,9,1.0,2,42,Semi-Urban,Data Analyst,28636,0 +7777,Male,22,Bachelors,1,27,0,85,2,7.0,7,49,Urban,ML Engineer,131438,0 +7778,Female,38,Bachelors,15,59,59,87,46,9.0,5,29,Urban,HR Executive,122376,0 +7779,Female,41,Bachelors,14,93,68,21,99,7.0,1,3,Rural,HR Executive,127555,0 +7780,Male,50,Diploma,12,19,91,50,41,0.0,1,52,Urban,Data Analyst,107571,0 +7781,Male,30,PhD,9,20,70,92,73,2.0,2,35,Rural,Manager,38981,0 +7782,Male,45,Diploma,16,84,48,76,10,8.0,4,2,Semi-Urban,ML Engineer,52191,0 +7783,Female,58,Bachelors,6,68,99,32,75,1.0,6,57,Semi-Urban,ML Engineer,127758,1 +7784,Male,39,Bachelors,8,80,41,92,62,5.0,3,72,Semi-Urban,HR Executive,118120,1 +7785,Female,33,Masters,7,34,70,85,93,2.0,1,62,Urban,HR Executive,49330,1 +7786,Male,57,High School,9,7,51,57,9,9.0,3,63,Semi-Urban,Manager,94305,0 +7787,Male,45,Masters,17,69,14,74,33,0.0,2,83,Rural,ML Engineer,143526,1 +7788,Female,25,Bachelors,13,32,78,51,93,3.0,2,37,Urban,Software Engineer,145018,0 +7789,Male,24,Bachelors,4,99,77,90,35,4.0,1,39,Rural,HR Executive,149400,1 +7790,Male,38,High School,11,81,18,35,95,8.0,7,93,Urban,Manager,126676,0 +7791,Male,56,Bachelors,14,91,10,24,58,4.0,0,76,Urban,Data Analyst,105482,0 +7792,Male,32,Bachelors,7,12,14,34,89,6.0,3,89,Urban,HR Executive,63600,0 +7793,Male,37,PhD,1,23,93,41,52,1.0,7,42,Urban,ML Engineer,134491,0 +7794,Female,58,High School,16,72,32,9,0,0.0,7,10,Urban,Data Analyst,55622,0 +7795,Female,41,Masters,9,84,94,36,45,6.0,0,4,Semi-Urban,ML Engineer,119500,0 +7796,Male,35,Bachelors,4,74,67,55,12,2.0,7,37,Urban,Manager,125080,0 +7797,Female,37,Bachelors,4,39,15,84,20,9.0,4,77,Urban,ML Engineer,107217,0 +7798,Male,37,Masters,19,5,28,90,52,7.0,3,5,Semi-Urban,ML Engineer,73068,0 +7799,Male,34,Bachelors,13,94,78,46,12,7.0,0,17,Urban,Manager,24269,1 +7800,Male,49,Diploma,17,92,89,36,54,4.0,2,28,Rural,Data Analyst,134248,1 +7801,Male,53,Bachelors,19,94,96,94,53,0.0,6,42,Urban,HR Executive,56068,1 +7802,Male,55,Masters,9,89,87,18,29,3.0,2,28,Rural,Manager,129095,0 +7803,Other,35,High School,13,72,81,94,9,8.0,5,77,Semi-Urban,Data Analyst,58159,1 +7804,Male,37,Masters,9,84,90,29,4,7.0,2,95,Semi-Urban,HR Executive,110066,1 +7805,Male,32,Diploma,15,51,27,26,43,1.0,5,4,Urban,Manager,136547,0 +7806,Male,25,Masters,14,46,26,76,88,2.0,7,60,Semi-Urban,ML Engineer,107466,0 +7807,Female,35,Masters,9,16,52,17,50,7.0,7,34,Rural,ML Engineer,104545,0 +7808,Female,55,High School,15,34,91,54,19,2.0,7,30,Semi-Urban,HR Executive,120562,0 +7809,Male,54,Masters,14,52,75,15,75,2.0,1,40,Rural,Data Analyst,110065,0 +7810,Male,40,Diploma,4,66,65,13,85,9.0,7,53,Urban,ML Engineer,76449,0 +7811,Male,22,Masters,13,16,62,45,4,1.0,7,94,Urban,HR Executive,111360,0 +7812,Male,46,Bachelors,18,34,70,19,54,0.0,0,13,Semi-Urban,Software Engineer,93398,0 +7813,Male,21,Bachelors,15,95,99,72,49,4.0,5,57,Urban,Data Analyst,101288,1 +7814,Male,25,Bachelors,9,9,44,71,12,1.0,1,49,Urban,HR Executive,32882,0 +7815,Male,52,Masters,0,19,40,25,57,9.0,6,83,Semi-Urban,Data Analyst,66224,0 +7816,Male,22,Bachelors,19,9,75,74,21,2.0,1,20,Semi-Urban,HR Executive,82908,0 +7817,Male,46,Diploma,6,52,17,21,68,1.0,6,78,Semi-Urban,HR Executive,35780,0 +7818,Female,30,High School,5,83,10,63,7,9.0,4,72,Urban,Software Engineer,111063,0 +7819,Female,36,Diploma,0,48,49,24,26,7.0,3,68,Urban,Data Analyst,20781,0 +7820,Male,47,Masters,14,28,46,1,79,2.0,2,35,Rural,Data Analyst,67024,0 +7821,Male,33,Bachelors,3,3,43,48,12,4.0,2,21,Semi-Urban,Manager,81931,0 +7822,Male,44,Masters,11,20,36,91,37,7.0,7,35,Urban,HR Executive,84677,0 +7823,Male,41,Masters,17,38,94,26,11,2.0,6,42,Urban,HR Executive,147324,0 +7824,Female,25,High School,19,53,75,18,66,1.0,2,21,Semi-Urban,Data Analyst,141952,0 +7825,Male,34,Bachelors,0,20,93,63,92,0.0,6,69,Semi-Urban,Manager,70234,1 +7826,Female,38,Diploma,12,45,0,65,2,4.0,4,64,Semi-Urban,Data Analyst,32025,0 +7827,Female,59,High School,1,32,77,77,91,9.0,3,89,Urban,Manager,119895,1 +7828,Male,49,Diploma,10,47,99,81,59,6.0,6,96,Urban,Data Analyst,127392,1 +7829,Male,38,Diploma,10,18,31,32,54,1.0,5,23,Urban,Data Analyst,77386,0 +7830,Male,29,Bachelors,19,1,12,14,50,4.0,3,49,Urban,Software Engineer,100643,0 +7831,Male,35,Diploma,17,65,62,74,40,2.0,4,5,Rural,Data Analyst,20890,0 +7832,Male,21,Bachelors,18,58,89,26,26,3.0,1,53,Semi-Urban,ML Engineer,75602,0 +7833,Male,36,Bachelors,17,80,18,58,69,2.0,1,1,Urban,Software Engineer,134382,0 +7834,Female,55,Bachelors,3,20,80,33,40,9.0,2,23,Urban,HR Executive,67446,0 +7835,Male,35,Bachelors,8,60,82,25,34,6.0,2,1,Rural,Manager,130154,0 +7836,Male,38,Diploma,7,37,80,91,79,0.0,6,73,Urban,HR Executive,21755,1 +7837,Female,56,High School,16,7,30,82,57,7.0,2,44,Semi-Urban,HR Executive,24595,0 +7838,Female,58,High School,17,4,17,97,68,0.0,0,33,Urban,ML Engineer,140662,0 +7839,Male,40,Bachelors,11,55,36,57,0,5.0,6,12,Urban,Software Engineer,47514,0 +7840,Female,32,Diploma,7,88,56,86,98,1.0,7,93,Rural,ML Engineer,81593,1 +7841,Male,55,High School,9,59,19,58,64,5.0,2,58,Urban,Manager,146893,0 +7842,Male,31,Bachelors,10,27,6,2,25,9.0,1,84,Semi-Urban,HR Executive,69868,0 +7843,Male,41,High School,6,1,2,53,46,3.0,2,26,Urban,Data Analyst,142285,0 +7844,Male,36,Bachelors,12,34,55,60,65,0.0,5,17,Urban,Data Analyst,102653,0 +7845,Female,23,Bachelors,3,22,79,97,2,1.0,3,72,Rural,ML Engineer,34275,1 +7846,Female,54,Bachelors,19,13,4,31,81,0.0,2,40,Urban,Data Analyst,122866,0 +7847,Female,44,Bachelors,4,25,65,8,9,3.0,3,70,Rural,ML Engineer,75175,0 +7848,Male,36,Bachelors,7,14,15,17,39,9.0,2,97,Rural,Data Analyst,72165,0 +7849,Male,57,Bachelors,16,14,26,94,1,4.0,6,58,Rural,HR Executive,118596,0 +7850,Male,56,Bachelors,17,38,87,88,7,7.0,7,23,Urban,Data Analyst,66778,1 +7851,Male,21,Bachelors,3,23,91,48,76,0.0,6,9,Rural,ML Engineer,108219,0 +7852,Female,44,PhD,4,96,49,41,70,7.0,3,23,Urban,Software Engineer,51482,0 +7853,Female,44,Diploma,12,83,5,41,25,1.0,3,38,Urban,Data Analyst,29527,0 +7854,Male,59,Bachelors,8,79,32,42,95,6.0,5,79,Urban,ML Engineer,97913,0 +7855,Male,34,High School,12,33,52,26,37,7.0,2,93,Rural,Data Analyst,55206,0 +7856,Male,54,High School,7,85,89,74,56,9.0,4,7,Urban,Software Engineer,58214,1 +7857,Male,57,Bachelors,18,30,27,50,87,9.0,2,36,Urban,ML Engineer,22473,0 +7858,Male,31,PhD,19,5,45,61,21,7.0,6,40,Semi-Urban,ML Engineer,25455,0 +7859,Male,23,Bachelors,12,76,62,75,17,4.0,7,77,Urban,HR Executive,66914,1 +7860,Male,47,PhD,14,66,76,39,74,8.0,5,48,Urban,ML Engineer,64209,0 +7861,Male,49,Bachelors,18,79,15,1,97,1.0,6,29,Urban,ML Engineer,47084,0 +7862,Male,43,Bachelors,12,15,95,85,8,3.0,5,27,Rural,Manager,96192,0 +7863,Male,41,Bachelors,18,30,90,98,59,1.0,3,70,Semi-Urban,Data Analyst,144726,1 +7864,Female,28,Masters,10,7,30,45,77,0.0,6,69,Rural,ML Engineer,71946,0 +7865,Male,56,Masters,3,40,84,28,40,2.0,2,28,Urban,ML Engineer,39607,0 +7866,Other,41,Bachelors,6,63,65,38,28,4.0,1,42,Urban,Manager,88239,0 +7867,Male,44,Masters,14,47,94,48,71,8.0,5,90,Semi-Urban,Data Analyst,91653,1 +7868,Male,32,Masters,10,7,40,34,23,7.0,2,55,Urban,Data Analyst,32525,0 +7869,Male,39,Bachelors,13,75,64,36,49,0.0,6,50,Rural,Data Analyst,64011,0 +7870,Male,59,Bachelors,11,14,96,14,46,4.0,3,46,Urban,Software Engineer,98397,0 +7871,Female,39,PhD,16,51,98,8,78,8.0,1,20,Semi-Urban,Software Engineer,99998,0 +7872,Male,55,Bachelors,5,60,34,52,91,5.0,3,56,Urban,ML Engineer,91235,0 +7873,Female,56,Bachelors,3,7,96,73,29,8.0,5,68,Urban,Software Engineer,111525,1 +7874,Female,25,High School,7,80,42,49,2,3.0,5,27,Rural,ML Engineer,130106,0 +7875,Male,31,Bachelors,10,7,56,63,35,9.0,7,67,Urban,Manager,107476,0 +7876,Male,26,High School,18,31,25,11,83,0.0,1,77,Urban,HR Executive,52459,0 +7877,Female,45,Bachelors,18,48,65,97,12,9.0,1,37,Urban,Manager,141797,1 +7878,Male,32,Bachelors,19,45,87,84,97,5.0,3,30,Urban,ML Engineer,42188,1 +7879,Female,36,High School,8,23,8,35,81,6.0,2,34,Urban,HR Executive,84501,0 +7880,Male,35,Masters,3,53,95,43,59,7.0,3,32,Rural,HR Executive,23628,0 +7881,Male,21,Bachelors,10,57,40,76,94,0.0,6,54,Semi-Urban,ML Engineer,143661,0 +7882,Male,54,Bachelors,1,75,96,42,36,1.0,4,17,Urban,Manager,98112,0 +7883,Male,54,Diploma,9,61,75,15,66,4.0,3,87,Urban,HR Executive,140074,1 +7884,Female,51,Bachelors,16,95,16,68,44,9.0,6,14,Semi-Urban,ML Engineer,129141,0 +7885,Male,30,Masters,19,14,97,44,33,4.0,2,68,Urban,Manager,63437,0 +7886,Female,29,Diploma,15,50,51,67,22,7.0,0,6,Urban,HR Executive,24157,0 +7887,Male,26,Masters,18,30,30,67,61,3.0,4,50,Rural,Software Engineer,26984,0 +7888,Male,50,High School,19,76,73,75,75,6.0,1,74,Semi-Urban,Software Engineer,119799,1 +7889,Male,41,Masters,1,32,59,64,3,2.0,3,7,Urban,HR Executive,120799,0 +7890,Male,49,Diploma,1,90,39,36,99,7.0,5,63,Rural,Software Engineer,70679,0 +7891,Male,46,High School,19,18,51,83,39,3.0,3,5,Rural,Data Analyst,20839,0 +7892,Male,55,Diploma,15,49,78,93,89,0.0,5,83,Urban,ML Engineer,85250,1 +7893,Female,43,Bachelors,0,7,80,62,3,7.0,7,99,Semi-Urban,Manager,102477,1 +7894,Male,45,Bachelors,6,62,59,23,10,2.0,1,78,Urban,Manager,27926,0 +7895,Male,54,Diploma,18,42,73,32,64,8.0,5,22,Semi-Urban,HR Executive,138158,0 +7896,Female,29,PhD,10,3,21,65,14,2.0,6,61,Rural,ML Engineer,112935,0 +7897,Female,28,Bachelors,11,9,47,11,7,1.0,2,9,Rural,Manager,126453,0 +7898,Male,53,Masters,9,88,17,4,89,9.0,5,70,Rural,ML Engineer,61323,0 +7899,Male,40,Masters,8,82,45,71,52,5.0,1,51,Semi-Urban,Data Analyst,98096,1 +7900,Female,37,Diploma,5,91,64,62,76,9.0,1,76,Urban,Data Analyst,112502,1 +7901,Male,36,Bachelors,14,73,83,98,15,6.0,3,27,Rural,Software Engineer,91318,1 +7902,Male,35,Bachelors,2,21,98,45,55,7.0,5,15,Urban,Software Engineer,20578,0 +7903,Male,33,High School,2,52,32,97,96,6.0,5,5,Urban,ML Engineer,115105,0 +7904,Female,25,Masters,17,31,47,93,23,7.0,5,23,Urban,Data Analyst,85681,0 +7905,Male,58,Bachelors,8,95,65,9,6,4.0,5,40,Rural,ML Engineer,36402,0 +7906,Other,34,Diploma,12,38,33,73,35,8.0,1,84,Semi-Urban,Data Analyst,92798,0 +7907,Male,38,Bachelors,10,85,56,50,31,2.0,3,51,Urban,Data Analyst,64455,1 +7908,Female,54,Bachelors,19,63,83,93,32,6.0,4,76,Semi-Urban,ML Engineer,60886,1 +7909,Male,31,Bachelors,13,69,68,66,15,2.0,0,99,Semi-Urban,ML Engineer,28908,1 +7910,Male,54,High School,5,1,90,19,31,3.0,6,43,Urban,HR Executive,119411,0 +7911,Female,36,Diploma,9,84,16,86,55,6.0,5,91,Urban,Software Engineer,60292,1 +7912,Male,42,Diploma,15,78,53,37,48,1.0,2,24,Semi-Urban,Manager,72518,0 +7913,Male,55,High School,19,94,34,26,84,0.0,0,92,Urban,ML Engineer,41526,1 +7914,Male,44,High School,12,38,64,84,29,7.0,1,44,Semi-Urban,HR Executive,141878,0 +7915,Male,38,Bachelors,16,20,98,31,21,3.0,0,62,Rural,ML Engineer,96122,0 +7916,Male,22,Diploma,16,27,27,97,62,5.0,6,93,Semi-Urban,Software Engineer,110970,1 +7917,Female,37,Masters,1,77,76,57,85,7.0,7,4,Semi-Urban,Software Engineer,58954,0 +7918,Male,54,Bachelors,7,8,60,67,41,4.0,0,57,Semi-Urban,Software Engineer,88240,0 +7919,Male,21,Diploma,13,80,77,25,31,5.0,7,11,Rural,Manager,135730,0 +7920,Male,44,Bachelors,1,96,97,70,21,8.0,5,70,Urban,Data Analyst,45165,1 +7921,Female,47,Diploma,12,59,59,79,93,6.0,2,98,Urban,HR Executive,50983,1 +7922,Female,34,Masters,0,76,92,57,46,9.0,6,13,Urban,Manager,82654,0 +7923,Male,22,Bachelors,9,29,89,72,63,3.0,6,73,Urban,HR Executive,90790,1 +7924,Male,31,Bachelors,6,42,56,6,15,5.0,6,18,Urban,Software Engineer,84131,0 +7925,Female,52,PhD,11,92,46,99,74,6.0,5,21,Urban,Software Engineer,61479,1 +7926,Male,25,Masters,3,49,64,60,44,5.0,3,76,Urban,Data Analyst,67635,1 +7927,Female,46,Bachelors,2,95,63,75,64,6.0,5,75,Semi-Urban,ML Engineer,20937,1 +7928,Female,58,PhD,1,2,51,3,31,9.0,4,6,Rural,ML Engineer,130092,0 +7929,Female,27,Diploma,15,52,79,3,96,3.0,2,14,Rural,Manager,141175,0 +7930,Male,55,Diploma,4,31,28,32,55,3.0,1,59,Urban,HR Executive,83876,0 +7931,Female,48,Bachelors,17,7,2,75,91,9.0,0,27,Urban,HR Executive,45006,0 +7932,Female,32,Diploma,10,73,69,35,98,7.0,0,52,Urban,Data Analyst,110160,0 +7933,Male,45,Bachelors,12,79,17,14,72,2.0,5,0,Urban,Software Engineer,76056,0 +7934,Male,55,High School,15,46,7,32,28,0.0,1,36,Semi-Urban,Software Engineer,32977,0 +7935,Male,51,Diploma,0,27,77,24,54,7.0,0,39,Urban,ML Engineer,95100,0 +7936,Male,34,High School,3,50,32,81,19,2.0,6,28,Rural,Manager,134347,0 +7937,Male,50,Bachelors,2,43,30,7,96,4.0,0,18,Urban,HR Executive,78029,0 +7938,Male,59,Masters,13,55,48,58,34,7.0,3,83,Urban,HR Executive,86883,1 +7939,Male,42,Bachelors,9,21,57,78,39,8.0,5,55,Urban,Software Engineer,137871,0 +7940,Male,53,Diploma,16,1,75,92,11,6.0,2,3,Urban,ML Engineer,115763,0 +7941,Male,50,Masters,0,83,62,86,24,1.0,1,55,Urban,HR Executive,127235,1 +7942,Female,44,Bachelors,14,23,46,30,18,3.0,0,51,Urban,ML Engineer,139845,0 +7943,Female,43,Diploma,6,60,43,45,77,8.0,7,61,Semi-Urban,ML Engineer,135700,0 +7944,Male,28,Bachelors,1,77,94,93,86,8.0,3,6,Urban,Software Engineer,71289,1 +7945,Male,21,High School,5,31,28,48,49,4.0,2,88,Rural,Manager,31509,0 +7946,Male,25,Bachelors,5,65,68,90,16,0.0,6,23,Semi-Urban,Manager,149212,1 +7947,Female,33,Masters,6,98,38,90,70,7.0,3,45,Rural,Software Engineer,42472,1 +7948,Female,52,Bachelors,1,18,17,2,94,3.0,2,85,Urban,Software Engineer,46622,0 +7949,Female,45,Masters,13,5,35,87,78,7.0,7,88,Urban,ML Engineer,135677,0 +7950,Male,45,Masters,17,50,2,10,3,4.0,7,78,Urban,Data Analyst,43313,0 +7951,Other,26,Masters,13,82,48,64,52,9.0,5,50,Rural,ML Engineer,137711,1 +7952,Male,32,Bachelors,14,65,43,68,4,3.0,0,39,Urban,Manager,57812,0 +7953,Female,36,Diploma,6,5,1,0,87,4.0,3,50,Rural,Data Analyst,120442,0 +7954,Male,46,Diploma,6,76,83,49,32,3.0,5,61,Urban,Software Engineer,119363,1 +7955,Female,46,Diploma,5,30,18,32,30,5.0,4,46,Urban,Data Analyst,24319,0 +7956,Male,42,Bachelors,11,72,19,14,60,7.0,4,37,Urban,Software Engineer,79630,0 +7957,Female,47,Bachelors,13,41,23,79,84,4.0,6,77,Urban,Software Engineer,90853,0 +7958,Female,36,PhD,6,72,48,59,64,3.0,4,19,Rural,Data Analyst,85365,0 +7959,Male,29,Bachelors,1,3,76,19,82,5.0,0,54,Semi-Urban,Software Engineer,118220,0 +7960,Male,32,Masters,13,83,3,43,86,0.0,1,88,Rural,Manager,140532,0 +7961,Female,23,Bachelors,5,97,24,78,59,1.0,2,13,Semi-Urban,Software Engineer,144941,0 +7962,Male,34,Diploma,8,74,75,85,17,7.0,6,61,Urban,HR Executive,104222,1 +7963,Male,34,Bachelors,14,94,64,19,28,7.0,3,87,Urban,ML Engineer,48298,1 +7964,Male,39,Diploma,7,28,44,7,65,5.0,6,13,Semi-Urban,Software Engineer,122553,0 +7965,Male,43,Bachelors,10,77,40,28,30,9.0,2,15,Urban,Software Engineer,97913,0 +7966,Male,45,Bachelors,8,81,23,89,29,2.0,5,17,Semi-Urban,Software Engineer,120016,0 +7967,Male,40,Masters,9,34,88,32,49,9.0,6,21,Rural,Data Analyst,39904,0 +7968,Male,30,Masters,12,16,19,33,73,8.0,4,37,Rural,HR Executive,94615,0 +7969,Male,41,High School,7,63,90,10,70,1.0,4,37,Semi-Urban,Data Analyst,59065,0 +7970,Female,27,Bachelors,2,51,39,79,14,6.0,2,99,Urban,Software Engineer,123064,1 +7971,Other,34,High School,7,85,29,11,9,5.0,4,45,Urban,Data Analyst,109997,0 +7972,Female,29,Masters,11,30,0,69,20,6.0,5,80,Semi-Urban,Software Engineer,69406,0 +7973,Male,53,Bachelors,14,25,69,79,10,4.0,6,89,Urban,Software Engineer,55417,1 +7974,Female,21,Masters,4,38,71,17,12,1.0,3,69,Urban,Software Engineer,21108,0 +7975,Male,36,Bachelors,1,81,6,7,20,3.0,1,14,Semi-Urban,Software Engineer,67936,0 +7976,Male,56,PhD,13,54,76,62,8,8.0,7,24,Urban,HR Executive,78621,0 +7977,Female,31,High School,18,44,90,82,37,9.0,5,85,Urban,ML Engineer,78754,1 +7978,Female,44,Bachelors,17,46,94,55,7,0.0,2,89,Urban,Software Engineer,120581,1 +7979,Female,25,PhD,1,22,0,24,55,8.0,6,8,Urban,ML Engineer,23084,0 +7980,Female,25,Bachelors,19,84,56,16,48,1.0,1,61,Semi-Urban,ML Engineer,40380,0 +7981,Male,46,Masters,8,5,24,60,18,5.0,7,0,Urban,Software Engineer,97095,0 +7982,Male,30,Bachelors,0,41,52,45,21,2.0,3,94,Semi-Urban,HR Executive,122306,0 +7983,Female,36,Masters,4,80,38,50,82,9.0,6,33,Semi-Urban,Software Engineer,36369,0 +7984,Male,50,High School,3,95,10,54,14,2.0,7,21,Urban,Data Analyst,111814,0 +7985,Male,26,Masters,10,59,39,42,1,8.0,6,38,Semi-Urban,Manager,49013,0 +7986,Female,42,Bachelors,4,15,99,21,14,9.0,6,53,Semi-Urban,Data Analyst,127928,0 +7987,Female,21,PhD,16,42,53,39,88,1.0,4,43,Urban,Software Engineer,145867,0 +7988,Male,38,Masters,8,41,59,91,48,3.0,1,53,Rural,ML Engineer,111602,1 +7989,Female,37,Bachelors,9,47,59,77,24,9.0,5,10,Rural,Software Engineer,142269,0 +7990,Female,38,Diploma,5,1,79,12,38,3.0,1,79,Urban,ML Engineer,93499,0 +7991,Female,55,PhD,2,27,78,68,4,5.0,2,18,Semi-Urban,HR Executive,138223,0 +7992,Male,39,Masters,1,37,61,47,37,6.0,4,74,Urban,Software Engineer,55137,0 +7993,Male,29,Masters,14,3,28,22,44,2.0,7,55,Urban,Manager,88511,0 +7994,Male,34,Bachelors,7,47,67,50,71,1.0,3,19,Semi-Urban,ML Engineer,97259,0 +7995,Male,59,Masters,9,55,94,5,66,0.0,1,54,Urban,Data Analyst,131839,0 +7996,Male,29,Diploma,9,29,90,28,74,9.0,2,22,Urban,Software Engineer,97884,0 +7997,Male,27,Masters,3,81,82,98,24,5.0,1,86,Semi-Urban,Manager,29679,1 +7998,Male,37,High School,7,97,40,25,89,8.0,4,98,Urban,Manager,53560,1 +7999,Female,24,Diploma,0,67,15,38,28,9.0,2,62,Rural,ML Engineer,147085,0 +8000,Male,24,Masters,17,10,37,66,7,0.0,4,77,Rural,HR Executive,76850,0 +8001,Female,45,Masters,4,65,23,35,86,3.0,3,61,Urban,Data Analyst,42909,0 +8002,Female,59,High School,10,28,74,35,24,2.0,2,57,Rural,Data Analyst,104356,0 +8003,Male,33,High School,8,10,43,6,12,3.0,3,39,Rural,HR Executive,134856,0 +8004,Female,34,Bachelors,15,14,48,84,27,6.0,6,87,Rural,Data Analyst,99797,0 +8005,Male,58,Diploma,2,77,62,50,80,6.0,2,15,Semi-Urban,Manager,31819,0 +8006,Male,47,High School,13,38,33,52,21,7.0,7,23,Urban,Manager,42948,0 +8007,Female,31,Bachelors,2,53,10,21,74,9.0,2,12,Rural,Data Analyst,127726,0 +8008,Male,27,Masters,0,35,28,47,34,0.0,2,24,Rural,Software Engineer,118411,0 +8009,Female,48,High School,6,21,33,89,73,1.0,6,89,Urban,Data Analyst,143669,0 +8010,Male,36,Bachelors,0,43,66,90,40,1.0,1,2,Urban,ML Engineer,35327,0 +8011,Female,48,Bachelors,18,5,69,83,39,0.0,6,95,Urban,Software Engineer,98490,1 +8012,Male,51,Bachelors,15,1,85,82,55,3.0,0,72,Urban,HR Executive,90776,1 +8013,Female,42,Diploma,18,70,95,43,97,9.0,2,80,Semi-Urban,HR Executive,134418,1 +8014,Male,29,Diploma,13,73,71,30,67,2.0,4,54,Urban,ML Engineer,75122,0 +8015,Female,57,High School,11,37,43,40,60,7.0,5,62,Semi-Urban,ML Engineer,40093,0 +8016,Female,51,Masters,2,13,50,94,99,7.0,4,41,Rural,Data Analyst,104300,0 +8017,Male,51,Bachelors,5,44,98,22,39,4.0,4,55,Urban,Data Analyst,77269,0 +8018,Female,41,Diploma,11,97,13,37,53,6.0,1,22,Urban,Software Engineer,26678,0 +8019,Male,25,Bachelors,19,20,19,94,49,6.0,5,32,Urban,ML Engineer,86454,0 +8020,Female,39,Bachelors,0,83,42,55,99,1.0,6,94,Semi-Urban,Manager,92366,1 +8021,Male,41,Bachelors,15,54,65,48,15,0.0,0,44,Urban,Data Analyst,72152,0 +8022,Female,50,Bachelors,12,96,15,91,2,0.0,7,29,Urban,HR Executive,86699,0 +8023,Female,57,Bachelors,14,44,33,6,20,9.0,7,10,Urban,Data Analyst,116915,0 +8024,Male,33,Masters,17,27,27,27,33,7.0,2,6,Urban,Manager,126275,0 +8025,Male,21,Diploma,3,66,41,21,4,3.0,5,10,Urban,Data Analyst,100301,0 +8026,Male,26,Bachelors,8,22,40,70,91,2.0,5,92,Semi-Urban,Manager,40860,0 +8027,Female,39,Bachelors,16,67,25,79,24,7.0,2,39,Urban,ML Engineer,49967,0 +8028,Male,43,Bachelors,19,54,49,86,93,3.0,5,47,Rural,ML Engineer,100525,1 +8029,Male,50,Bachelors,15,57,66,6,34,1.0,3,98,Urban,Data Analyst,30123,0 +8030,Female,39,Bachelors,7,63,47,93,8,3.0,1,94,Rural,Data Analyst,93879,1 +8031,Male,34,Diploma,1,48,51,5,24,4.0,3,58,Urban,ML Engineer,146747,0 +8032,Female,27,PhD,1,44,99,32,70,5.0,7,42,Semi-Urban,ML Engineer,103798,0 +8033,Male,30,Masters,13,84,9,35,41,8.0,5,57,Rural,Data Analyst,95143,0 +8034,Male,52,Masters,19,75,54,45,78,4.0,6,78,Semi-Urban,ML Engineer,78662,1 +8035,Female,34,Bachelors,4,84,13,36,6,0.0,5,69,Urban,Software Engineer,88426,0 +8036,Male,37,Bachelors,15,98,75,81,73,1.0,3,27,Rural,ML Engineer,141707,1 +8037,Male,59,Bachelors,15,73,58,79,60,8.0,3,84,Rural,HR Executive,59078,1 +8038,Female,34,Diploma,6,76,49,70,47,7.0,2,7,Rural,Software Engineer,112348,0 +8039,Male,22,Bachelors,11,20,11,80,92,8.0,4,96,Urban,Data Analyst,97287,0 +8040,Other,33,Bachelors,3,88,29,61,48,2.0,0,22,Urban,HR Executive,64774,0 +8041,Other,33,Bachelors,15,71,98,59,35,0.0,0,83,Urban,HR Executive,51301,1 +8042,Male,41,Masters,13,59,55,82,12,5.0,7,68,Rural,Data Analyst,146279,1 +8043,Male,47,Bachelors,2,92,29,43,5,2.0,0,78,Semi-Urban,Software Engineer,117266,1 +8044,Female,50,Bachelors,7,2,29,47,47,8.0,6,1,Rural,ML Engineer,148204,0 +8045,Male,51,Bachelors,14,60,62,20,66,2.0,7,77,Urban,ML Engineer,33844,0 +8046,Male,44,Bachelors,10,72,24,98,22,8.0,1,57,Semi-Urban,Software Engineer,127349,1 +8047,Female,48,Masters,15,88,91,59,47,1.0,5,92,Urban,Manager,137685,1 +8048,Male,30,High School,16,14,18,80,81,8.0,3,94,Urban,Data Analyst,125438,0 +8049,Female,49,Bachelors,6,79,80,28,45,4.0,7,2,Semi-Urban,Manager,122334,0 +8050,Male,54,Bachelors,18,34,38,2,45,6.0,2,89,Urban,Manager,110963,0 +8051,Male,39,Masters,5,50,26,74,21,0.0,6,60,Semi-Urban,HR Executive,111706,0 +8052,Male,37,Bachelors,10,8,42,25,82,1.0,0,84,Urban,HR Executive,31585,0 +8053,Other,54,Masters,2,64,12,4,10,5.0,6,22,Rural,ML Engineer,147038,0 +8054,Female,34,Bachelors,11,99,20,81,81,6.0,5,52,Urban,ML Engineer,113468,1 +8055,Female,48,Masters,5,23,43,88,73,3.0,3,22,Semi-Urban,Software Engineer,78856,0 +8056,Male,31,Bachelors,5,70,10,16,73,5.0,4,99,Urban,Data Analyst,116430,0 +8057,Male,58,High School,12,49,14,90,91,3.0,3,41,Urban,Software Engineer,42327,0 +8058,Male,27,Bachelors,1,88,22,30,56,6.0,1,6,Urban,Data Analyst,45855,0 +8059,Male,38,Bachelors,5,97,34,28,29,5.0,1,55,Rural,Data Analyst,135768,0 +8060,Male,53,Bachelors,2,19,14,1,72,1.0,3,0,Semi-Urban,Manager,122675,0 +8061,Female,31,Diploma,0,64,39,44,17,5.0,5,24,Rural,Manager,112378,0 +8062,Male,40,Bachelors,16,20,84,47,3,1.0,5,85,Rural,Manager,112558,1 +8063,Female,59,Bachelors,6,32,22,98,30,6.0,5,26,Rural,ML Engineer,117157,0 +8064,Male,38,Masters,6,88,85,62,91,5.0,0,36,Semi-Urban,Software Engineer,33408,1 +8065,Other,35,Bachelors,8,84,25,43,48,4.0,2,22,Urban,Software Engineer,37166,0 +8066,Male,55,High School,19,0,60,43,14,3.0,7,57,Rural,ML Engineer,89283,0 +8067,Male,24,PhD,7,7,70,10,54,5.0,3,34,Urban,ML Engineer,89338,0 +8068,Male,58,PhD,3,17,0,51,98,6.0,5,44,Rural,Data Analyst,97267,0 +8069,Male,55,High School,0,77,50,58,16,5.0,6,40,Rural,Data Analyst,91595,0 +8070,Male,59,Masters,17,11,70,90,86,7.0,7,93,Semi-Urban,Data Analyst,37083,1 +8071,Male,48,Masters,2,27,96,93,32,0.0,0,31,Semi-Urban,ML Engineer,28727,1 +8072,Male,58,High School,17,33,35,15,52,0.0,3,88,Urban,Manager,83057,0 +8073,Female,44,High School,1,46,42,64,90,0.0,0,82,Rural,Software Engineer,42663,0 +8074,Female,26,Bachelors,7,98,68,0,94,5.0,3,14,Urban,Manager,51704,0 +8075,Female,50,Bachelors,14,57,95,70,55,4.0,5,32,Rural,Data Analyst,92174,1 +8076,Male,54,Diploma,18,77,3,63,98,4.0,5,5,Urban,ML Engineer,99640,0 +8077,Female,25,PhD,17,14,27,74,55,2.0,5,0,Urban,Software Engineer,24308,0 +8078,Male,31,Diploma,13,11,64,52,83,7.0,6,14,Urban,Manager,130598,0 +8079,Male,29,Bachelors,15,60,16,7,92,2.0,7,47,Urban,ML Engineer,54010,0 +8080,Male,33,Bachelors,17,98,60,16,60,9.0,7,2,Urban,Data Analyst,114634,0 +8081,Male,37,PhD,17,48,7,11,47,2.0,1,3,Urban,Manager,63909,0 +8082,Male,28,Diploma,17,59,14,41,40,2.0,5,11,Urban,Manager,105226,0 +8083,Male,47,Masters,14,28,60,65,61,8.0,7,10,Semi-Urban,HR Executive,85471,0 +8084,Male,22,Bachelors,1,83,4,48,67,8.0,7,34,Urban,ML Engineer,120386,0 +8085,Female,39,Masters,14,49,16,4,77,7.0,4,25,Urban,Manager,54678,0 +8086,Female,59,Diploma,14,75,1,0,1,1.0,1,13,Urban,Software Engineer,59252,0 +8087,Other,51,High School,19,61,51,69,11,9.0,1,92,Urban,HR Executive,113826,1 +8088,Female,42,Diploma,13,43,43,11,63,3.0,1,17,Urban,Data Analyst,101359,0 +8089,Male,31,Bachelors,8,49,45,17,39,6.0,1,68,Urban,Software Engineer,110224,0 +8090,Female,34,Masters,8,18,80,86,20,3.0,1,9,Rural,Data Analyst,56793,0 +8091,Female,36,Bachelors,0,15,56,50,81,1.0,6,59,Rural,Manager,118189,0 +8092,Male,50,High School,3,25,95,52,59,2.0,6,84,Urban,HR Executive,135070,1 +8093,Male,54,PhD,15,30,6,41,31,3.0,6,33,Urban,Data Analyst,139402,0 +8094,Other,34,Diploma,12,12,8,23,10,2.0,0,4,Rural,Manager,57325,0 +8095,Male,52,Bachelors,6,56,10,35,9,0.0,2,86,Semi-Urban,Manager,125114,0 +8096,Female,55,Masters,0,81,22,75,28,3.0,4,10,Rural,Manager,49055,0 +8097,Male,56,Bachelors,6,25,91,58,44,2.0,4,55,Urban,Data Analyst,71602,0 +8098,Male,46,Bachelors,2,66,71,19,94,5.0,1,22,Semi-Urban,ML Engineer,94641,0 +8099,Male,32,Bachelors,17,2,16,91,29,8.0,1,93,Urban,Data Analyst,126676,0 +8100,Male,28,Bachelors,4,70,68,58,72,6.0,5,68,Urban,ML Engineer,145046,1 +8101,Female,45,Bachelors,15,33,9,52,66,8.0,1,1,Rural,ML Engineer,98232,0 +8102,Other,43,Bachelors,4,14,67,66,19,7.0,2,63,Semi-Urban,HR Executive,81301,0 +8103,Male,25,High School,1,36,20,4,26,5.0,0,96,Urban,Software Engineer,50234,0 +8104,Male,33,Bachelors,19,53,35,55,45,7.0,7,37,Urban,Software Engineer,80535,0 +8105,Female,36,High School,14,70,98,85,35,4.0,0,73,Urban,Data Analyst,26076,1 +8106,Female,51,Masters,18,89,40,58,22,5.0,1,1,Urban,ML Engineer,28626,0 +8107,Male,27,Bachelors,15,91,69,0,39,2.0,3,40,Urban,Data Analyst,127961,0 +8108,Male,59,Diploma,7,35,24,75,83,2.0,0,72,Urban,Software Engineer,26916,0 +8109,Female,52,High School,18,52,5,22,57,5.0,2,46,Urban,HR Executive,85787,0 +8110,Female,59,Masters,8,65,32,29,20,2.0,3,48,Semi-Urban,Software Engineer,93416,0 +8111,Male,53,Bachelors,3,91,41,77,69,2.0,3,16,Rural,Data Analyst,30824,0 +8112,Male,50,Diploma,15,22,27,92,42,0.0,4,6,Urban,Software Engineer,123470,0 +8113,Other,36,Bachelors,2,14,96,83,15,3.0,0,12,Urban,HR Executive,102702,0 +8114,Female,58,Bachelors,4,56,1,75,63,3.0,3,0,Rural,Software Engineer,90424,0 +8115,Male,45,Bachelors,16,62,33,41,91,7.0,7,98,Rural,ML Engineer,103408,0 +8116,Male,52,High School,4,43,33,38,28,5.0,1,82,Rural,Data Analyst,133494,0 +8117,Female,45,Masters,15,26,39,22,80,9.0,2,60,Urban,Software Engineer,110119,0 +8118,Male,56,Bachelors,8,50,69,97,25,6.0,6,54,Urban,ML Engineer,64564,1 +8119,Male,56,Bachelors,8,60,20,82,61,9.0,0,88,Urban,Manager,142359,1 +8120,Male,23,Bachelors,3,85,40,65,98,4.0,4,15,Urban,Data Analyst,138754,0 +8121,Male,56,Bachelors,9,32,87,10,39,9.0,2,77,Rural,Software Engineer,58723,0 +8122,Female,29,Diploma,11,3,53,99,7,0.0,6,43,Urban,Manager,127419,0 +8123,Male,38,High School,15,49,49,18,91,6.0,4,53,Semi-Urban,Software Engineer,31838,0 +8124,Female,59,PhD,14,21,63,14,70,9.0,5,21,Urban,Data Analyst,112850,0 +8125,Male,53,Bachelors,14,61,11,26,93,5.0,6,48,Rural,Manager,140605,0 +8126,Male,33,Masters,6,97,59,74,27,9.0,3,57,Semi-Urban,ML Engineer,143342,1 +8127,Male,32,Diploma,0,21,90,45,6,7.0,0,61,Rural,Data Analyst,119855,0 +8128,Female,23,Bachelors,9,27,32,63,84,6.0,7,52,Rural,ML Engineer,117468,0 +8129,Female,36,Bachelors,4,34,50,84,80,4.0,1,98,Rural,Manager,66694,1 +8130,Male,52,Diploma,3,79,69,28,86,6.0,5,34,Urban,ML Engineer,33456,0 +8131,Female,40,Bachelors,2,54,90,57,12,7.0,3,82,Urban,HR Executive,98354,1 +8132,Female,55,High School,15,17,17,58,58,2.0,5,28,Semi-Urban,Software Engineer,125055,0 +8133,Other,40,Bachelors,13,35,89,93,50,0.0,2,18,Rural,ML Engineer,47121,0 +8134,Male,50,Diploma,0,45,28,14,66,8.0,7,95,Urban,HR Executive,105499,0 +8135,Female,36,Diploma,12,32,42,12,38,0.0,4,38,Semi-Urban,HR Executive,44069,0 +8136,Male,57,Bachelors,0,67,19,39,41,4.0,5,59,Urban,HR Executive,96900,0 +8137,Male,53,Bachelors,12,53,25,55,19,8.0,3,5,Semi-Urban,Manager,55166,0 +8138,Other,46,Diploma,18,74,77,72,49,4.0,7,33,Rural,ML Engineer,65704,1 +8139,Male,36,Bachelors,0,99,83,15,60,6.0,7,66,Urban,HR Executive,31815,1 +8140,Male,49,Bachelors,13,5,49,61,73,0.0,0,42,Rural,ML Engineer,48551,0 +8141,Male,55,Bachelors,13,21,65,79,43,3.0,2,28,Semi-Urban,HR Executive,97387,0 +8142,Female,51,High School,5,46,14,75,80,8.0,1,45,Rural,HR Executive,70253,0 +8143,Female,47,Bachelors,5,41,91,98,61,5.0,0,2,Semi-Urban,HR Executive,142482,0 +8144,Male,48,Bachelors,13,32,12,74,52,0.0,1,80,Rural,HR Executive,140933,0 +8145,Other,46,Masters,0,48,71,88,54,0.0,6,77,Urban,HR Executive,103779,1 +8146,Male,46,Bachelors,6,0,61,6,37,4.0,2,79,Rural,Data Analyst,103688,0 +8147,Male,38,PhD,8,27,46,85,72,0.0,4,38,Urban,Software Engineer,88973,0 +8148,Female,25,Bachelors,7,47,12,57,14,9.0,6,85,Urban,Data Analyst,45750,0 +8149,Male,25,Bachelors,18,2,64,56,33,0.0,0,77,Rural,Software Engineer,92040,0 +8150,Male,50,Diploma,9,21,85,7,91,9.0,1,20,Rural,HR Executive,89414,0 +8151,Male,27,Diploma,13,25,12,9,25,8.0,7,84,Urban,Manager,91721,0 +8152,Female,29,Diploma,16,34,56,40,85,7.0,5,76,Urban,Manager,82869,0 +8153,Male,31,Diploma,10,41,15,90,0,3.0,2,46,Rural,Manager,145772,0 +8154,Female,49,Masters,12,83,32,89,40,3.0,3,20,Semi-Urban,Software Engineer,27787,0 +8155,Female,56,Bachelors,5,98,4,45,14,9.0,1,1,Rural,HR Executive,80630,0 +8156,Male,55,Bachelors,7,12,58,8,5,4.0,7,39,Semi-Urban,ML Engineer,95355,0 +8157,Female,54,Masters,9,70,96,72,99,4.0,3,48,Semi-Urban,HR Executive,35550,1 +8158,Male,59,Masters,19,58,68,73,41,7.0,5,59,Semi-Urban,Data Analyst,97244,1 +8159,Male,46,Masters,18,16,71,68,67,5.0,2,85,Urban,Manager,126729,1 +8160,Female,33,High School,4,59,42,76,87,4.0,5,23,Urban,HR Executive,38487,0 +8161,Other,39,Bachelors,6,46,78,77,28,4.0,5,75,Semi-Urban,ML Engineer,64414,1 +8162,Male,30,Bachelors,10,43,25,24,39,1.0,7,89,Rural,Data Analyst,149316,0 +8163,Male,31,Masters,13,7,36,24,61,2.0,3,84,Semi-Urban,Software Engineer,25421,0 +8164,Male,50,Masters,4,55,62,50,97,9.0,0,22,Rural,HR Executive,30634,0 +8165,Male,56,Bachelors,1,66,90,11,37,0.0,7,32,Semi-Urban,HR Executive,32207,0 +8166,Male,24,High School,14,9,21,57,52,8.0,5,96,Urban,ML Engineer,119887,0 +8167,Male,57,Bachelors,11,16,25,12,79,8.0,5,18,Urban,Software Engineer,37380,0 +8168,Female,50,High School,15,25,74,20,28,1.0,4,5,Urban,HR Executive,125941,0 +8169,Male,52,Bachelors,4,24,2,58,91,8.0,2,21,Semi-Urban,Manager,133672,0 +8170,Male,30,High School,15,30,48,47,76,8.0,4,90,Urban,HR Executive,73223,0 +8171,Female,50,High School,10,77,51,20,59,1.0,7,52,Urban,ML Engineer,47537,0 +8172,Female,51,Diploma,17,0,19,25,72,2.0,2,9,Urban,Data Analyst,120182,0 +8173,Male,43,Bachelors,5,49,33,93,52,6.0,7,30,Urban,ML Engineer,90860,0 +8174,Male,31,Masters,0,0,83,58,66,0.0,1,72,Urban,ML Engineer,23731,0 +8175,Female,33,High School,16,14,14,1,62,4.0,2,18,Urban,Software Engineer,113315,0 +8176,Male,59,Masters,10,51,51,15,59,4.0,7,71,Rural,HR Executive,111250,0 +8177,Male,44,High School,1,57,24,46,89,5.0,7,64,Urban,Software Engineer,133270,0 +8178,Female,43,Bachelors,2,21,43,84,80,8.0,1,1,Urban,Software Engineer,25841,0 +8179,Male,53,Diploma,5,41,94,75,90,7.0,0,70,Urban,Data Analyst,22960,1 +8180,Male,46,Masters,13,87,87,8,94,4.0,5,83,Urban,HR Executive,28162,1 +8181,Male,39,Bachelors,17,61,2,11,96,0.0,3,64,Urban,Software Engineer,102474,0 +8182,Male,59,Masters,11,94,23,58,39,8.0,0,70,Urban,HR Executive,134479,1 +8183,Male,41,Masters,1,5,69,76,77,6.0,5,93,Semi-Urban,Data Analyst,132691,1 +8184,Other,30,High School,19,24,31,78,89,2.0,3,39,Semi-Urban,ML Engineer,73420,0 +8185,Male,49,Masters,15,19,99,95,10,1.0,6,45,Urban,Software Engineer,32563,1 +8186,Male,55,Diploma,18,53,73,34,64,0.0,3,72,Semi-Urban,Manager,103342,0 +8187,Male,36,Diploma,15,20,47,17,8,5.0,4,89,Semi-Urban,ML Engineer,94048,0 +8188,Female,55,Diploma,9,47,33,67,37,3.0,4,10,Rural,Software Engineer,95377,0 +8189,Male,54,Diploma,11,88,47,64,11,4.0,5,60,Urban,Software Engineer,41034,1 +8190,Male,54,Bachelors,11,68,44,93,34,9.0,7,77,Urban,HR Executive,126270,1 +8191,Female,57,Masters,18,44,85,65,68,8.0,3,21,Urban,Data Analyst,116054,0 +8192,,41,Bachelors,3,70,58,4,17,0.0,5,79,Urban,Manager,134840,0 +8193,Male,34,Diploma,14,85,50,0,91,8.0,5,49,Rural,Manager,72267,0 +8194,Male,26,Diploma,13,91,67,84,11,8.0,6,26,Urban,ML Engineer,131734,1 +8195,Male,41,High School,19,89,12,29,76,1.0,0,94,Urban,Manager,53687,0 +8196,Male,38,Bachelors,0,31,56,38,36,3.0,1,83,Urban,Software Engineer,34687,0 +8197,Female,27,Bachelors,5,47,62,0,66,9.0,1,30,Urban,Data Analyst,48837,0 +8198,Male,59,Bachelors,11,71,53,87,24,6.0,7,22,Semi-Urban,Software Engineer,104528,0 +8199,Male,58,Masters,7,74,45,2,74,6.0,3,75,Urban,HR Executive,108312,0 +8200,Male,45,Masters,18,71,87,93,8,9.0,5,80,Urban,Data Analyst,41356,1 +8201,Male,39,Bachelors,0,33,2,78,9,7.0,7,45,Urban,Manager,131471,0 +8202,Male,51,Bachelors,3,95,23,57,43,1.0,4,44,Semi-Urban,ML Engineer,34468,0 +8203,Female,44,PhD,14,91,50,32,59,3.0,7,77,Urban,ML Engineer,137097,1 +8204,Male,52,High School,2,25,76,91,90,6.0,7,90,Urban,Data Analyst,92052,1 +8205,Female,51,Bachelors,18,94,37,19,51,0.0,6,78,Rural,Software Engineer,56020,0 +8206,Male,49,High School,9,71,13,51,97,8.0,7,10,Urban,Manager,106303,0 +8207,Male,54,Bachelors,10,87,57,74,34,6.0,6,19,Urban,Data Analyst,49283,1 +8208,Male,24,High School,15,74,86,49,60,9.0,0,7,Semi-Urban,HR Executive,149537,0 +8209,Male,48,Diploma,16,19,97,29,53,4.0,6,25,Semi-Urban,HR Executive,50492,0 +8210,Male,41,Bachelors,14,83,7,90,42,7.0,3,47,Urban,ML Engineer,34649,0 +8211,Male,22,Diploma,7,4,3,45,84,9.0,7,92,Rural,ML Engineer,21149,0 +8212,Female,42,PhD,14,65,15,1,20,3.0,5,39,Urban,ML Engineer,80068,0 +8213,Male,36,Bachelors,3,16,20,97,27,8.0,1,37,Rural,Data Analyst,132691,0 +8214,Male,58,Bachelors,7,93,35,74,74,5.0,7,25,Semi-Urban,ML Engineer,137464,0 +8215,Male,26,Bachelors,8,32,75,21,52,3.0,4,64,Semi-Urban,HR Executive,94920,0 +8216,Male,37,Diploma,9,6,75,38,76,7.0,4,58,Urban,Manager,67867,0 +8217,Male,37,Bachelors,17,33,40,71,16,2.0,5,62,Urban,HR Executive,87159,0 +8218,Male,47,Diploma,19,23,29,57,0,6.0,6,66,Semi-Urban,Data Analyst,91300,0 +8219,Male,26,Bachelors,3,9,23,12,26,7.0,4,76,Rural,Manager,57868,0 +8220,Female,24,Bachelors,4,19,0,30,43,0.0,7,29,Semi-Urban,Data Analyst,134361,0 +8221,Female,24,High School,4,47,28,0,82,2.0,0,81,Rural,Software Engineer,23254,0 +8222,Male,43,Bachelors,19,41,36,50,58,3.0,1,51,Semi-Urban,Data Analyst,94832,0 +8223,Male,42,PhD,5,71,19,27,28,2.0,4,99,Urban,HR Executive,69014,0 +8224,Female,44,Diploma,11,3,32,48,2,3.0,0,86,Urban,Data Analyst,38753,0 +8225,Male,25,High School,7,5,46,65,4,5.0,2,39,Semi-Urban,HR Executive,143716,0 +8226,Male,56,Bachelors,13,28,43,12,81,7.0,7,53,Urban,HR Executive,112623,0 +8227,Male,23,Bachelors,19,19,86,32,85,5.0,4,22,Semi-Urban,Data Analyst,57445,0 +8228,Male,57,Bachelors,10,10,78,82,86,2.0,0,86,Urban,Manager,126612,1 +8229,Male,32,High School,5,58,70,63,39,6.0,0,17,Semi-Urban,Manager,69037,0 +8230,Male,43,High School,2,86,31,1,97,7.0,1,26,Urban,Manager,121957,0 +8231,Male,36,Diploma,8,5,65,49,39,9.0,5,54,Urban,Data Analyst,29391,0 +8232,Male,56,Diploma,19,28,12,82,50,6.0,6,13,Urban,ML Engineer,121306,0 +8233,Female,28,Bachelors,8,68,9,76,56,0.0,5,10,Rural,Software Engineer,65740,0 +8234,Male,22,Masters,12,80,16,93,48,5.0,6,85,Rural,HR Executive,89444,1 +8235,Male,49,Bachelors,3,14,15,41,36,7.0,4,22,Urban,HR Executive,79012,0 +8236,Male,44,Masters,11,26,17,14,76,4.0,5,92,Urban,Manager,81214,0 +8237,Female,54,Bachelors,14,68,37,12,69,7.0,4,13,Urban,ML Engineer,122409,0 +8238,Female,56,High School,6,31,97,55,2,4.0,3,56,Semi-Urban,ML Engineer,129432,0 +8239,Female,27,Bachelors,11,63,9,39,29,9.0,6,80,Rural,Data Analyst,56154,0 +8240,Male,34,High School,14,80,84,10,65,0.0,4,58,Semi-Urban,HR Executive,112646,0 +8241,Female,43,Bachelors,11,61,56,7,25,5.0,5,40,Semi-Urban,Data Analyst,58535,0 +8242,Female,26,Bachelors,12,68,17,51,9,5.0,4,36,Urban,ML Engineer,27175,0 +8243,Male,21,Masters,16,18,83,79,43,6.0,7,38,Urban,ML Engineer,129612,0 +8244,Male,57,Bachelors,1,90,18,28,58,8.0,3,82,Semi-Urban,Data Analyst,94820,0 +8245,Male,38,Masters,2,55,14,19,63,9.0,4,14,Rural,Software Engineer,90118,0 +8246,Female,56,Bachelors,15,99,33,20,87,0.0,7,81,Rural,Software Engineer,82472,0 +8247,Male,47,Bachelors,18,79,85,79,16,6.0,3,20,Rural,Manager,89738,1 +8248,Male,48,PhD,13,31,88,81,90,9.0,7,62,Urban,HR Executive,27100,1 +8249,Female,35,Bachelors,3,12,68,0,84,2.0,4,81,Urban,ML Engineer,70448,0 +8250,Female,27,Diploma,2,52,72,93,18,2.0,6,19,Urban,HR Executive,125146,0 +8251,Female,21,High School,5,93,4,48,70,5.0,7,91,Semi-Urban,ML Engineer,86281,0 +8252,Other,54,Bachelors,15,87,3,80,67,0.0,1,18,Semi-Urban,ML Engineer,25903,0 +8253,Male,24,Diploma,12,61,44,45,44,2.0,0,36,Urban,Manager,144247,0 +8254,Female,52,Masters,18,95,90,44,19,0.0,7,46,Urban,Manager,37162,1 +8255,Male,40,Bachelors,12,98,89,37,26,7.0,7,39,Urban,Data Analyst,90894,1 +8256,Female,29,Bachelors,0,88,10,10,87,5.0,2,71,Urban,Software Engineer,21116,0 +8257,Male,26,Bachelors,15,12,29,50,17,1.0,4,58,Urban,Manager,61084,0 +8258,Other,41,Masters,13,53,34,8,82,2.0,6,50,Urban,Manager,44740,0 +8259,Female,36,Bachelors,18,27,86,30,78,8.0,1,52,Semi-Urban,Data Analyst,104366,0 +8260,Female,21,Diploma,11,23,70,41,95,0.0,1,91,Semi-Urban,ML Engineer,123476,0 +8261,Male,56,Masters,15,72,64,27,57,3.0,5,2,Urban,ML Engineer,61402,0 +8262,Male,38,Masters,16,79,46,79,6,8.0,4,20,Urban,HR Executive,54331,0 +8263,Female,29,Masters,1,74,92,70,75,4.0,1,80,Rural,ML Engineer,80446,1 +8264,Male,41,Bachelors,0,45,49,88,95,4.0,5,28,Semi-Urban,HR Executive,48236,0 +8265,Female,29,Diploma,15,38,19,44,41,9.0,2,47,Rural,Manager,91259,0 +8266,Male,32,High School,14,99,29,12,84,6.0,5,96,Urban,ML Engineer,94545,1 +8267,Female,57,Bachelors,11,82,2,49,64,3.0,4,58,Urban,Software Engineer,51423,0 +8268,Male,44,PhD,13,76,36,46,35,3.0,1,9,Urban,Software Engineer,22884,0 +8269,Female,25,Diploma,6,71,17,61,18,9.0,3,73,Urban,Software Engineer,94825,0 +8270,Female,33,Bachelors,4,25,0,13,21,9.0,5,10,Semi-Urban,Software Engineer,126296,0 +8271,Male,55,High School,19,23,20,84,37,6.0,0,36,Urban,HR Executive,35957,0 +8272,Male,56,Bachelors,18,55,63,62,90,7.0,0,48,Urban,Manager,147461,0 +8273,Male,46,Bachelors,17,92,29,26,8,9.0,6,94,Urban,HR Executive,121056,1 +8274,Male,51,Bachelors,6,81,64,10,2,2.0,3,87,Urban,ML Engineer,149419,1 +8275,Male,41,Diploma,4,81,50,51,92,4.0,0,84,Semi-Urban,HR Executive,20340,1 +8276,Female,43,Masters,4,29,3,44,74,9.0,6,5,Urban,Software Engineer,26798,0 +8277,Male,31,Masters,17,96,10,20,62,0.0,0,25,Urban,ML Engineer,115335,0 +8278,Male,27,Bachelors,5,65,20,98,5,9.0,5,75,Urban,HR Executive,34484,1 +8279,Male,56,Masters,18,55,48,84,24,3.0,3,32,Rural,Software Engineer,72050,0 +8280,Male,39,Bachelors,0,21,64,68,74,9.0,5,47,Urban,HR Executive,51526,0 +8281,Male,41,Bachelors,4,19,17,50,68,2.0,0,71,Urban,Manager,99846,0 +8282,Other,50,High School,15,21,29,31,51,3.0,7,49,Urban,Software Engineer,101723,0 +8283,Female,27,Diploma,0,8,0,46,25,4.0,6,81,Urban,ML Engineer,120957,0 +8284,Male,30,Bachelors,9,40,3,30,28,3.0,6,22,Urban,ML Engineer,91490,0 +8285,Male,41,Bachelors,2,3,71,23,78,8.0,0,56,Urban,Manager,49553,0 +8286,Female,43,Bachelors,8,58,49,40,95,7.0,2,88,Rural,Manager,147908,0 +8287,Male,47,Bachelors,15,18,72,27,12,4.0,6,56,Urban,Manager,65590,0 +8288,Male,35,Diploma,3,80,92,56,16,9.0,4,72,Urban,Data Analyst,86118,1 +8289,Male,59,Diploma,5,78,20,56,56,1.0,7,53,Urban,HR Executive,30183,0 +8290,Male,49,Bachelors,10,91,71,67,33,9.0,7,1,Rural,Manager,38753,0 +8291,Other,49,Masters,18,73,63,11,67,0.0,0,11,Rural,Data Analyst,86671,0 +8292,Female,36,Bachelors,12,5,83,95,63,4.0,6,82,Rural,Manager,148188,1 +8293,Male,50,Masters,1,71,79,46,24,4.0,2,77,Urban,Data Analyst,140243,1 +8294,Male,27,Diploma,2,28,45,76,6,9.0,1,55,Semi-Urban,Manager,149381,0 +8295,Female,48,Bachelors,6,33,30,11,38,8.0,2,22,Urban,Data Analyst,144039,0 +8296,Female,41,High School,9,3,46,91,57,9.0,2,18,Urban,Data Analyst,126626,0 +8297,Female,50,Bachelors,19,17,56,38,5,9.0,1,7,Urban,Data Analyst,86529,0 +8298,Female,22,High School,8,25,13,38,65,9.0,4,38,Urban,ML Engineer,114934,0 +8299,Male,34,Masters,14,22,64,73,32,3.0,2,25,Urban,ML Engineer,57013,0 +8300,Female,56,Diploma,0,80,34,39,74,8.0,7,90,Rural,Software Engineer,65816,1 +8301,Female,24,Bachelors,11,17,15,3,57,9.0,6,82,Urban,Data Analyst,119769,0 +8302,Male,55,High School,7,40,86,39,97,3.0,4,70,Urban,Manager,88148,1 +8303,Female,57,Bachelors,11,25,35,9,20,6.0,2,38,Rural,Data Analyst,32714,0 +8304,Male,22,Bachelors,4,90,49,1,91,4.0,4,80,Urban,ML Engineer,62595,0 +8305,Male,40,Bachelors,12,6,69,36,45,3.0,4,32,Urban,Manager,89528,0 +8306,Male,26,High School,19,14,36,41,22,3.0,0,54,Rural,ML Engineer,69711,0 +8307,Male,52,High School,5,68,89,13,82,1.0,5,35,Urban,Data Analyst,108618,0 +8308,Male,59,Bachelors,18,26,51,16,95,3.0,3,28,Urban,HR Executive,53970,0 +8309,Male,38,Masters,17,73,68,99,33,1.0,2,43,Urban,ML Engineer,135354,1 +8310,Male,51,High School,13,71,98,71,48,4.0,7,51,Semi-Urban,Data Analyst,98653,1 +8311,Male,25,Diploma,4,7,1,6,51,0.0,0,59,Urban,Manager,120180,0 +8312,Male,33,High School,6,89,39,23,87,8.0,4,39,Urban,Manager,110263,0 +8313,Male,21,Bachelors,10,92,96,12,73,1.0,7,7,Urban,Software Engineer,96300,0 +8314,Female,26,High School,19,61,47,23,86,6.0,4,11,Semi-Urban,ML Engineer,36806,0 +8315,Male,59,High School,9,30,97,60,62,9.0,4,41,Urban,ML Engineer,124122,0 +8316,Male,54,PhD,12,0,48,31,57,6.0,6,27,Urban,Manager,88930,0 +8317,Female,36,Bachelors,16,33,1,67,16,5.0,7,62,Urban,Software Engineer,97388,0 +8318,Female,46,Masters,2,62,94,66,83,1.0,2,10,Urban,HR Executive,146326,0 +8319,Female,33,Masters,17,92,67,86,3,2.0,4,29,Urban,Manager,95021,1 +8320,Male,24,Masters,14,54,91,50,46,1.0,4,74,Semi-Urban,Data Analyst,144858,1 +8321,Male,56,High School,17,25,84,71,16,1.0,3,44,Semi-Urban,HR Executive,80876,0 +8322,Female,30,Masters,6,82,53,69,13,6.0,6,21,Rural,ML Engineer,122210,0 +8323,Male,30,Bachelors,9,77,66,48,12,3.0,1,87,Rural,ML Engineer,86532,1 +8324,Male,47,High School,19,3,3,11,78,5.0,0,5,Urban,Manager,58120,0 +8325,Male,35,Diploma,17,85,26,42,27,3.0,6,61,Urban,HR Executive,131447,0 +8326,Female,55,High School,15,14,15,63,55,3.0,1,81,Semi-Urban,HR Executive,116087,0 +8327,Male,46,Masters,12,35,52,97,16,1.0,1,54,Urban,Software Engineer,44813,1 +8328,Female,54,High School,18,32,99,35,83,9.0,1,81,Urban,Data Analyst,73510,1 +8329,Female,47,Masters,0,1,55,32,17,3.0,4,45,Rural,Manager,27419,0 +8330,Male,24,Diploma,12,82,91,7,69,1.0,1,15,Urban,HR Executive,137562,0 +8331,Female,32,Bachelors,4,32,98,16,47,7.0,2,28,Rural,HR Executive,38480,0 +8332,Female,43,High School,14,45,1,54,52,4.0,4,62,Urban,Data Analyst,52444,0 +8333,Female,50,PhD,18,14,32,91,87,6.0,1,61,Rural,ML Engineer,21065,0 +8334,Male,53,Bachelors,0,33,64,24,71,6.0,3,80,Urban,HR Executive,106517,0 +8335,Female,36,Masters,13,12,84,32,16,9.0,4,67,Urban,Manager,53651,0 +8336,Male,48,Masters,14,14,31,6,48,4.0,4,15,Urban,Software Engineer,87092,0 +8337,Female,24,Masters,1,19,48,25,63,0.0,4,53,Urban,HR Executive,123219,0 +8338,Male,43,Bachelors,8,50,72,30,68,3.0,2,15,Urban,ML Engineer,75919,0 +8339,Male,26,High School,16,68,3,32,81,3.0,2,48,Urban,Data Analyst,21446,0 +8340,Female,37,Bachelors,11,44,8,75,1,7.0,2,53,Urban,ML Engineer,94088,0 +8341,Female,53,Bachelors,6,57,29,71,29,5.0,3,68,Urban,HR Executive,43377,0 +8342,Male,27,Masters,4,80,46,26,3,5.0,4,40,Semi-Urban,ML Engineer,31630,0 +8343,Male,57,Masters,9,4,19,52,52,1.0,6,1,Semi-Urban,Manager,138631,0 +8344,Male,49,Masters,16,49,98,33,13,8.0,3,88,Urban,Software Engineer,20245,1 +8345,Other,23,Bachelors,1,39,32,52,37,3.0,6,32,Semi-Urban,Manager,57657,0 +8346,Female,39,High School,9,78,90,0,73,8.0,6,62,Rural,ML Engineer,66590,0 +8347,Female,50,Masters,11,71,69,75,27,4.0,7,84,Rural,Manager,50291,1 +8348,Male,58,Masters,12,41,85,92,74,5.0,7,15,Urban,ML Engineer,129025,0 +8349,Male,52,Diploma,2,29,51,62,95,1.0,4,92,Urban,ML Engineer,96446,0 +8350,Female,25,Bachelors,7,75,8,72,18,7.0,3,93,Semi-Urban,Data Analyst,93272,1 +8351,Female,38,Bachelors,9,98,12,11,37,1.0,1,1,Urban,HR Executive,69565,0 +8352,Male,41,Diploma,4,42,47,85,27,3.0,4,21,Rural,Data Analyst,52915,0 +8353,Female,38,Bachelors,7,9,57,57,0,0.0,1,35,Semi-Urban,Data Analyst,128807,0 +8354,Male,21,Diploma,18,98,33,28,33,2.0,0,80,Rural,Manager,84814,1 +8355,Male,33,Bachelors,1,54,12,77,62,3.0,1,52,Urban,HR Executive,82400,0 +8356,Male,32,Bachelors,7,62,34,25,65,1.0,1,22,Urban,HR Executive,82716,0 +8357,Male,46,Masters,9,75,89,51,22,6.0,4,88,Urban,Manager,85166,1 +8358,Male,56,High School,4,7,91,46,30,9.0,2,14,Rural,Data Analyst,77241,0 +8359,Male,40,Bachelors,13,95,21,47,46,8.0,7,31,Urban,ML Engineer,66639,0 +8360,Male,35,High School,15,61,46,27,5,8.0,4,86,Urban,HR Executive,68212,0 +8361,Female,21,Masters,17,36,12,23,44,1.0,6,49,Semi-Urban,Data Analyst,33318,0 +8362,Male,33,High School,12,66,79,86,8,0.0,0,66,Urban,ML Engineer,99323,1 +8363,Male,45,PhD,18,50,33,68,6,7.0,1,35,Semi-Urban,Data Analyst,127389,0 +8364,Male,31,Bachelors,5,68,88,24,87,9.0,7,38,Semi-Urban,ML Engineer,71576,0 +8365,Male,47,Masters,19,57,81,38,89,5.0,3,66,Urban,Data Analyst,94940,1 +8366,Female,37,Bachelors,1,56,37,78,12,4.0,1,74,Urban,HR Executive,119898,1 +8367,Male,42,Bachelors,10,91,88,79,95,6.0,7,22,Urban,ML Engineer,128113,1 +8368,Female,49,Bachelors,7,85,69,70,94,0.0,2,13,Urban,ML Engineer,137966,0 +8369,Female,58,High School,8,96,48,45,48,0.0,0,43,Urban,Software Engineer,121378,0 +8370,Male,32,Bachelors,19,84,28,44,31,6.0,7,28,Rural,HR Executive,124068,0 +8371,Male,59,High School,0,47,28,64,87,2.0,5,92,Urban,ML Engineer,32384,0 +8372,Male,30,Diploma,4,23,55,56,78,9.0,4,55,Semi-Urban,ML Engineer,97631,0 +8373,Male,52,Bachelors,7,29,11,42,73,2.0,1,21,Urban,ML Engineer,42815,0 +8374,Female,32,Masters,18,30,46,46,26,6.0,4,28,Semi-Urban,Software Engineer,23415,0 +8375,Male,22,Diploma,7,86,68,8,62,2.0,5,96,Urban,ML Engineer,144086,1 +8376,Male,22,Bachelors,19,30,62,81,57,3.0,4,70,Urban,HR Executive,28807,1 +8377,Male,39,Bachelors,6,32,41,54,90,7.0,2,42,Rural,Manager,67910,0 +8378,Male,56,High School,2,67,78,2,20,8.0,2,71,Urban,ML Engineer,107342,0 +8379,Male,26,PhD,15,96,45,62,5,5.0,1,73,Urban,ML Engineer,77723,1 +8380,Male,35,Bachelors,11,34,72,73,73,1.0,7,7,Urban,Manager,71903,0 +8381,Male,26,Bachelors,6,81,93,77,88,5.0,0,91,Urban,HR Executive,149426,1 +8382,Male,22,Bachelors,4,30,65,94,58,0.0,4,39,Rural,Data Analyst,82934,0 +8383,Female,58,PhD,0,64,36,54,94,8.0,3,99,Rural,Software Engineer,89943,1 +8384,Female,33,Bachelors,0,74,93,73,83,9.0,6,17,Urban,HR Executive,86455,1 +8385,Male,42,Bachelors,14,89,46,18,87,0.0,1,33,Semi-Urban,ML Engineer,98078,0 +8386,Male,33,Bachelors,17,5,22,5,20,3.0,2,77,Semi-Urban,ML Engineer,91027,0 +8387,Other,58,Diploma,9,54,9,73,82,9.0,0,78,Semi-Urban,Manager,23296,0 +8388,Male,34,Bachelors,0,85,96,59,29,6.0,0,92,Urban,Data Analyst,21143,1 +8389,Male,34,Bachelors,18,21,78,11,22,2.0,3,62,Urban,HR Executive,51713,0 +8390,Male,37,Diploma,1,29,63,99,44,7.0,4,78,Urban,Data Analyst,43049,1 +8391,Female,40,High School,2,68,73,66,94,9.0,5,43,Urban,ML Engineer,140321,1 +8392,Male,23,PhD,0,97,5,52,6,3.0,2,34,Semi-Urban,Data Analyst,41127,0 +8393,Other,47,Bachelors,19,6,26,5,57,5.0,2,71,Urban,Software Engineer,83907,0 +8394,Female,25,Bachelors,16,88,23,7,29,3.0,4,87,Rural,Data Analyst,149589,0 +8395,Female,47,High School,4,63,92,69,44,0.0,0,82,Urban,HR Executive,108564,1 +8396,Female,57,Diploma,8,48,48,90,60,6.0,6,39,Urban,Manager,75543,0 +8397,Male,45,Bachelors,12,28,92,81,36,6.0,1,88,Semi-Urban,HR Executive,57244,1 +8398,Male,26,Masters,6,93,60,34,52,3.0,6,65,Urban,ML Engineer,122409,1 +8399,Female,22,Diploma,8,29,93,74,66,8.0,0,65,Urban,Software Engineer,46130,1 +8400,Other,57,Bachelors,11,4,11,47,64,0.0,3,53,Urban,HR Executive,25910,0 +8401,Male,35,High School,12,78,9,5,89,6.0,4,55,Rural,Data Analyst,66842,0 +8402,Female,30,High School,18,10,55,9,20,9.0,7,43,Rural,Manager,99439,0 +8403,Male,42,Masters,0,44,16,49,73,5.0,3,61,Semi-Urban,ML Engineer,50041,0 +8404,Male,30,Diploma,11,41,63,71,72,1.0,1,71,Semi-Urban,Manager,22139,1 +8405,Male,56,Masters,11,52,26,70,29,5.0,7,99,Urban,Data Analyst,36285,1 +8406,Male,50,Bachelors,16,87,81,58,24,3.0,7,93,Rural,ML Engineer,46637,1 +8407,Male,42,PhD,2,85,85,67,34,5.0,1,78,Semi-Urban,ML Engineer,74069,1 +8408,Male,22,Masters,6,55,68,5,1,2.0,0,78,Semi-Urban,Software Engineer,115781,0 +8409,Male,54,Bachelors,6,83,45,63,12,8.0,7,23,Urban,HR Executive,31345,0 +8410,Male,48,High School,6,50,3,50,10,3.0,4,54,Urban,Software Engineer,61647,0 +8411,Male,24,High School,10,45,39,51,57,8.0,4,71,Rural,Manager,137155,0 +8412,Other,41,Bachelors,0,98,4,33,53,8.0,3,36,Urban,HR Executive,45446,0 +8413,Male,37,Bachelors,18,83,88,25,51,0.0,6,26,Urban,Manager,146792,0 +8414,Male,40,Masters,7,42,84,20,88,5.0,0,54,Urban,Data Analyst,67804,0 +8415,Male,52,Masters,5,60,22,61,31,5.0,0,15,Urban,HR Executive,117765,0 +8416,Male,29,Masters,13,10,85,9,3,5.0,1,57,Semi-Urban,Manager,37110,0 +8417,Female,23,Bachelors,10,25,81,6,22,2.0,3,82,Urban,Data Analyst,76235,0 +8418,Male,53,Bachelors,4,4,80,59,78,1.0,5,1,Rural,ML Engineer,77301,0 +8419,Female,59,Diploma,8,24,83,42,71,6.0,5,43,Urban,Data Analyst,116880,0 +8420,Male,56,Masters,13,26,38,35,74,7.0,0,97,Urban,Data Analyst,112867,0 +8421,Male,34,Diploma,18,39,90,76,36,3.0,3,87,Urban,Manager,98874,1 +8422,Male,27,Masters,0,54,57,13,24,8.0,0,20,Urban,ML Engineer,41130,0 +8423,Male,48,Bachelors,7,45,38,46,75,9.0,5,78,Urban,Software Engineer,73680,0 +8424,Male,35,Diploma,16,8,6,64,7,2.0,7,39,Urban,HR Executive,76712,0 +8425,Male,50,High School,14,44,76,17,42,6.0,2,90,Urban,ML Engineer,67390,0 +8426,Male,47,Masters,14,92,26,88,46,8.0,5,51,Urban,ML Engineer,131948,1 +8427,Male,23,Bachelors,17,14,43,2,12,5.0,6,93,Urban,ML Engineer,78001,0 +8428,Other,30,Diploma,11,4,96,16,47,7.0,1,83,Semi-Urban,Software Engineer,108474,0 +8429,Male,58,Masters,13,18,56,19,57,4.0,6,33,Semi-Urban,Data Analyst,30550,0 +8430,Male,37,Bachelors,6,71,25,9,64,4.0,3,46,Urban,ML Engineer,106786,0 +8431,Male,42,High School,8,15,93,6,72,9.0,4,73,Semi-Urban,Software Engineer,68923,0 +8432,Male,37,High School,13,57,11,56,92,2.0,0,46,Urban,Data Analyst,45536,0 +8433,Male,49,Diploma,19,54,77,6,35,1.0,2,39,Urban,Software Engineer,127326,0 +8434,Female,56,High School,11,79,15,7,54,0.0,3,87,Urban,HR Executive,72343,0 +8435,Other,50,Bachelors,2,30,22,1,88,6.0,2,95,Semi-Urban,Data Analyst,131196,0 +8436,Male,52,Diploma,18,77,94,87,56,8.0,3,8,Rural,Manager,139224,1 +8437,Male,44,Diploma,5,62,39,22,17,9.0,3,87,Urban,HR Executive,148425,0 +8438,Male,22,Bachelors,0,44,93,55,11,3.0,2,57,Semi-Urban,Software Engineer,72498,1 +8439,Female,58,Diploma,0,58,2,83,44,7.0,3,49,Urban,ML Engineer,143097,0 +8440,Male,27,Bachelors,15,42,50,75,23,3.0,1,57,Semi-Urban,Software Engineer,122736,0 +8441,Male,32,PhD,1,11,43,61,78,8.0,6,70,Urban,Manager,95819,0 +8442,Male,40,High School,5,57,85,5,26,2.0,3,9,Semi-Urban,Software Engineer,125191,0 +8443,Female,24,PhD,14,80,68,5,62,0.0,7,25,Rural,Manager,140396,0 +8444,Male,22,Diploma,5,90,19,96,87,7.0,2,43,Semi-Urban,HR Executive,117529,1 +8445,Male,58,Masters,14,53,98,42,98,5.0,7,33,Urban,HR Executive,97004,0 +8446,Female,50,PhD,15,14,23,22,27,5.0,5,99,Urban,ML Engineer,47653,0 +8447,Male,24,High School,6,11,30,6,21,2.0,2,57,Urban,ML Engineer,94638,0 +8448,Female,40,Diploma,19,4,48,51,28,1.0,4,98,Urban,Data Analyst,114371,0 +8449,Male,45,Bachelors,10,62,96,34,30,3.0,0,29,Rural,HR Executive,130038,0 +8450,Female,57,Bachelors,15,43,66,4,11,6.0,3,48,Semi-Urban,Software Engineer,21655,0 +8451,Female,50,Masters,8,91,77,34,48,5.0,5,4,Semi-Urban,Data Analyst,82381,0 +8452,Male,55,High School,1,61,94,90,80,0.0,7,2,Rural,HR Executive,70126,1 +8453,Female,30,Bachelors,5,23,72,25,25,5.0,1,81,Semi-Urban,Software Engineer,75115,0 +8454,Male,33,Bachelors,13,13,52,59,26,7.0,7,88,Urban,Software Engineer,79547,0 +8455,Female,24,Masters,17,52,48,56,8,2.0,4,9,Urban,Software Engineer,129051,0 +8456,Male,42,Diploma,10,41,64,33,88,1.0,3,39,Urban,Data Analyst,68519,0 +8457,Female,31,Bachelors,8,24,1,47,50,2.0,5,93,Semi-Urban,HR Executive,43343,0 +8458,Male,57,Masters,0,29,11,68,43,0.0,1,4,Semi-Urban,HR Executive,124588,0 +8459,Other,34,Bachelors,12,22,1,17,1,4.0,3,89,Semi-Urban,ML Engineer,76129,0 +8460,Male,30,Diploma,0,26,11,72,88,8.0,4,43,Urban,ML Engineer,35451,0 +8461,Other,44,Bachelors,10,60,65,40,63,5.0,7,6,Urban,ML Engineer,30511,0 +8462,Female,51,Bachelors,9,84,83,57,67,2.0,4,96,Urban,ML Engineer,117453,1 +8463,Male,49,High School,8,78,81,5,87,8.0,7,93,Semi-Urban,Manager,144359,1 +8464,Female,39,Diploma,3,40,33,64,54,1.0,4,1,Rural,ML Engineer,100488,0 +8465,Other,58,Masters,9,57,47,77,34,2.0,5,37,Urban,Manager,89959,0 +8466,Male,22,Diploma,5,41,85,72,97,7.0,4,40,Semi-Urban,ML Engineer,107449,1 +8467,Male,45,Bachelors,6,10,18,3,74,2.0,1,87,Urban,ML Engineer,90176,0 +8468,Male,42,Masters,14,53,78,22,61,2.0,6,25,Semi-Urban,Software Engineer,45872,0 +8469,Male,21,High School,18,15,59,27,39,6.0,0,23,Semi-Urban,ML Engineer,23210,0 +8470,Male,28,Bachelors,14,68,7,63,78,9.0,4,79,Urban,Software Engineer,93008,0 +8471,Male,59,Masters,17,5,49,65,28,3.0,1,44,Urban,Data Analyst,57960,0 +8472,Male,22,Bachelors,2,41,1,63,80,9.0,2,32,Rural,HR Executive,85758,0 +8473,Male,56,Bachelors,1,68,84,14,38,6.0,3,73,Urban,Manager,116273,1 +8474,Male,29,Bachelors,19,83,38,36,86,0.0,0,47,Urban,Data Analyst,136678,0 +8475,Female,48,High School,13,33,21,33,37,1.0,0,48,Urban,Data Analyst,101392,0 +8476,Female,27,Bachelors,8,98,84,5,7,4.0,1,80,Urban,Manager,62950,1 +8477,Male,34,Bachelors,8,50,12,73,69,0.0,4,79,Rural,Manager,48725,0 +8478,Female,38,Diploma,18,66,4,12,60,1.0,3,76,Urban,Manager,124300,0 +8479,Female,52,Masters,4,71,6,62,13,5.0,6,58,Urban,HR Executive,80652,0 +8480,Other,21,Masters,0,78,42,5,40,6.0,4,23,Semi-Urban,Data Analyst,103112,0 +8481,Male,43,Bachelors,4,32,90,45,9,0.0,4,28,Urban,HR Executive,89958,0 +8482,Male,31,High School,0,54,4,66,5,6.0,3,8,Urban,ML Engineer,48657,0 +8483,Female,52,Masters,9,49,69,3,11,6.0,1,4,Urban,ML Engineer,25876,0 +8484,Female,44,High School,18,68,17,75,54,6.0,1,71,Semi-Urban,HR Executive,70619,0 +8485,Female,25,Masters,1,40,96,89,52,0.0,6,94,Urban,Manager,109512,1 +8486,Female,55,Bachelors,12,13,47,25,82,2.0,1,12,Rural,ML Engineer,112841,0 +8487,Male,41,Bachelors,5,52,22,17,30,1.0,0,75,Semi-Urban,Manager,121040,0 +8488,Male,40,Masters,14,20,25,24,67,8.0,5,85,Semi-Urban,HR Executive,81508,0 +8489,Male,50,Bachelors,15,48,83,13,56,6.0,0,35,Urban,Data Analyst,101947,0 +8490,Male,42,High School,7,80,54,95,70,9.0,0,70,Semi-Urban,Data Analyst,46378,1 +8491,Female,30,Diploma,2,40,97,5,69,9.0,7,76,Rural,Data Analyst,52725,0 +8492,Male,26,High School,12,94,77,15,30,2.0,1,87,Urban,HR Executive,28398,1 +8493,Male,33,High School,17,24,49,0,58,4.0,5,71,Urban,Data Analyst,83763,0 +8494,Female,56,Bachelors,4,99,63,76,3,8.0,4,78,Urban,HR Executive,81349,1 +8495,Male,32,Bachelors,13,53,6,36,17,3.0,2,92,Urban,Data Analyst,98253,0 +8496,Other,27,Bachelors,2,19,57,28,88,1.0,1,21,Urban,ML Engineer,144331,0 +8497,Other,39,Diploma,2,40,59,9,48,8.0,1,33,Urban,HR Executive,137828,0 +8498,Male,42,Diploma,19,91,65,14,57,1.0,1,31,Rural,ML Engineer,39110,0 +8499,Male,25,Diploma,6,26,62,62,76,4.0,4,9,Rural,ML Engineer,114684,0 +8500,Male,22,Bachelors,0,97,44,60,65,7.0,0,90,Urban,Software Engineer,130917,1 +8501,Male,31,Diploma,5,38,19,62,12,9.0,3,42,Semi-Urban,Software Engineer,55911,0 +8502,Male,25,PhD,11,30,7,97,57,1.0,4,93,Urban,Data Analyst,81674,0 +8503,Male,25,High School,13,46,49,12,97,4.0,2,83,Urban,Software Engineer,113605,0 +8504,Other,28,Masters,11,29,53,17,93,3.0,3,91,Urban,Data Analyst,24911,0 +8505,Male,23,High School,14,32,54,82,97,5.0,5,29,Urban,HR Executive,45914,0 +8506,Female,33,Bachelors,3,11,54,54,81,3.0,6,58,Urban,Manager,23113,0 +8507,Male,39,High School,0,86,16,61,67,5.0,7,66,Urban,Manager,118730,0 +8508,Male,22,Bachelors,1,39,28,59,89,3.0,5,60,Urban,Manager,97360,0 +8509,Female,22,Bachelors,19,18,86,83,37,0.0,1,2,Semi-Urban,Software Engineer,20268,0 +8510,Male,54,Diploma,10,9,61,98,73,3.0,0,18,Semi-Urban,Data Analyst,111327,0 +8511,Male,56,Masters,5,67,18,22,91,3.0,6,43,Urban,Manager,119973,0 +8512,Female,35,Masters,0,57,70,20,3,1.0,7,58,Urban,Manager,129411,0 +8513,Female,25,High School,2,42,90,98,57,5.0,0,72,Semi-Urban,Data Analyst,47052,1 +8514,Female,53,Bachelors,9,99,5,54,88,9.0,5,80,Urban,ML Engineer,141025,0 +8515,Male,30,Masters,9,80,68,13,64,1.0,7,68,Rural,ML Engineer,51894,0 +8516,Male,48,Bachelors,19,98,30,50,73,4.0,1,3,Semi-Urban,Software Engineer,94899,0 +8517,Other,22,Bachelors,19,73,84,8,39,6.0,4,76,Urban,Manager,50686,1 +8518,Female,58,PhD,9,65,83,9,49,1.0,1,98,Urban,HR Executive,46288,1 +8519,Male,32,Bachelors,14,92,27,11,35,8.0,5,76,Urban,Software Engineer,73327,0 +8520,Female,26,Bachelors,16,97,27,83,92,1.0,3,24,Urban,Manager,46261,0 +8521,Male,52,Masters,0,46,15,76,83,8.0,4,62,Semi-Urban,Data Analyst,142135,0 +8522,Male,24,Bachelors,17,63,78,7,2,3.0,1,71,Urban,ML Engineer,41003,0 +8523,Male,30,High School,2,4,80,89,39,4.0,4,24,Urban,Data Analyst,71814,0 +8524,Male,43,Masters,4,50,67,25,96,4.0,2,80,Semi-Urban,Software Engineer,134622,0 +8525,Male,25,Diploma,2,88,78,97,39,3.0,6,44,Urban,HR Executive,141250,1 +8526,Male,30,Diploma,8,81,38,12,83,4.0,7,74,Urban,Software Engineer,55752,0 +8527,Male,34,Masters,4,69,63,99,49,0.0,7,10,Semi-Urban,ML Engineer,148908,1 +8528,Female,25,Masters,17,64,9,25,30,8.0,2,14,Urban,ML Engineer,38078,0 +8529,Female,25,Masters,13,12,65,14,59,0.0,0,23,Semi-Urban,ML Engineer,97171,0 +8530,Female,56,High School,3,47,37,20,20,4.0,0,18,Semi-Urban,Manager,101263,0 +8531,Female,30,Masters,9,50,96,88,62,4.0,7,26,Semi-Urban,Software Engineer,55478,1 +8532,Male,54,Bachelors,11,4,59,46,51,8.0,1,7,Rural,ML Engineer,109956,0 +8533,Male,34,High School,1,28,64,93,56,3.0,1,77,Semi-Urban,HR Executive,41294,1 +8534,Female,55,Bachelors,13,64,95,51,64,0.0,0,46,Urban,ML Engineer,135085,1 +8535,Male,44,Diploma,11,65,51,82,29,3.0,1,82,Urban,HR Executive,52063,1 +8536,Male,48,Diploma,4,27,38,41,22,0.0,5,66,Semi-Urban,Data Analyst,60713,0 +8537,Male,48,Masters,19,47,98,70,35,3.0,2,9,Semi-Urban,Software Engineer,136551,0 +8538,Female,40,Diploma,10,60,12,50,73,7.0,6,3,Urban,Software Engineer,109505,0 +8539,Male,25,Diploma,11,63,78,72,92,3.0,6,62,Urban,ML Engineer,42758,1 +8540,Female,25,Masters,13,97,83,68,31,9.0,2,19,Urban,ML Engineer,88322,1 +8541,Male,55,Masters,4,23,58,69,16,4.0,2,54,Urban,ML Engineer,90251,0 +8542,Female,28,High School,18,75,40,75,80,7.0,0,9,Semi-Urban,HR Executive,114204,0 +8543,Female,50,Masters,13,34,10,69,8,3.0,1,40,Urban,Software Engineer,130237,0 +8544,Female,57,Bachelors,19,45,69,91,94,4.0,3,42,Urban,HR Executive,63504,1 +8545,Male,50,Bachelors,12,60,39,0,91,0.0,7,74,Rural,Data Analyst,43060,0 +8546,Male,53,Masters,3,38,66,21,14,4.0,6,96,Semi-Urban,Data Analyst,144992,0 +8547,Female,50,High School,4,11,90,77,80,3.0,4,96,Rural,Manager,103628,1 +8548,Male,53,Bachelors,8,44,63,11,73,0.0,7,6,Urban,ML Engineer,146307,0 +8549,Male,43,Diploma,2,30,85,26,8,9.0,7,96,Rural,Manager,97884,1 +8550,Male,47,Masters,10,97,39,14,94,7.0,6,76,Rural,ML Engineer,39169,0 +8551,Female,55,Masters,11,27,33,36,70,8.0,3,23,Semi-Urban,Software Engineer,120996,0 +8552,Male,31,Bachelors,14,96,37,72,71,9.0,3,92,Urban,Manager,35562,1 +8553,Female,40,Diploma,9,90,47,87,10,8.0,3,99,Semi-Urban,HR Executive,53946,1 +8554,Male,27,Bachelors,15,32,43,3,26,5.0,2,83,Semi-Urban,ML Engineer,109029,0 +8555,Male,26,Masters,14,23,1,41,45,8.0,0,81,Urban,HR Executive,95042,0 +8556,Female,49,High School,6,57,95,58,47,8.0,2,98,Urban,Data Analyst,121036,1 +8557,Male,53,High School,6,74,72,73,18,0.0,1,76,Urban,Software Engineer,141393,1 +8558,Male,28,Masters,6,32,63,60,86,6.0,1,42,Urban,ML Engineer,132386,0 +8559,Female,44,Diploma,6,66,1,99,12,7.0,6,19,Urban,ML Engineer,95829,0 +8560,Female,42,Diploma,15,97,19,47,34,9.0,0,19,Urban,Manager,74581,0 +8561,Male,42,Diploma,14,38,79,65,64,6.0,5,3,Urban,Data Analyst,52282,0 +8562,Female,41,High School,13,42,73,98,87,6.0,5,89,Urban,ML Engineer,95048,1 +8563,Female,41,Bachelors,8,72,73,96,91,2.0,3,41,Rural,ML Engineer,120702,1 +8564,Female,26,Masters,15,62,79,9,75,8.0,5,63,Semi-Urban,HR Executive,21125,0 +8565,Male,45,Masters,9,20,45,42,3,5.0,5,57,Semi-Urban,ML Engineer,92802,0 +8566,Male,52,Masters,18,37,57,39,35,8.0,4,12,Rural,Data Analyst,32546,0 +8567,Female,55,Masters,16,65,58,36,30,2.0,7,83,Urban,ML Engineer,84731,1 +8568,Female,29,Masters,14,20,27,41,36,8.0,3,65,Rural,Software Engineer,20399,0 +8569,Male,45,Diploma,2,18,46,49,40,7.0,0,99,Semi-Urban,HR Executive,58675,0 +8570,Male,59,Diploma,11,65,94,42,20,3.0,3,22,Semi-Urban,Software Engineer,108549,0 +8571,Male,45,High School,1,43,31,69,17,5.0,7,99,Urban,Manager,29889,1 +8572,Male,58,Masters,14,83,96,86,82,4.0,6,78,Urban,Manager,79737,1 +8573,Male,28,Bachelors,13,25,3,67,48,7.0,5,41,Urban,HR Executive,38389,0 +8574,Male,59,Bachelors,17,68,95,74,35,8.0,7,48,Urban,ML Engineer,109525,1 +8575,Female,59,High School,11,92,6,56,51,7.0,1,23,Urban,Manager,93439,0 +8576,Male,54,Masters,15,51,88,82,26,1.0,4,3,Urban,Data Analyst,75587,0 +8577,Female,49,High School,7,54,26,31,39,8.0,4,31,Semi-Urban,Software Engineer,82527,0 +8578,Male,22,Bachelors,10,36,54,43,51,9.0,6,97,Urban,ML Engineer,72871,0 +8579,Male,40,Diploma,2,24,5,84,95,0.0,4,40,Semi-Urban,Data Analyst,130514,0 +8580,Male,43,Bachelors,14,1,14,52,97,9.0,3,56,Rural,Manager,135047,0 +8581,Male,51,Bachelors,0,79,97,92,87,2.0,4,87,Urban,Software Engineer,23707,1 +8582,Female,47,High School,11,83,55,42,97,5.0,5,57,Urban,Software Engineer,61635,0 +8583,Female,41,Masters,3,94,49,36,15,2.0,2,10,Urban,Software Engineer,21415,0 +8584,Male,24,Bachelors,8,16,99,84,51,9.0,3,71,Rural,HR Executive,51881,1 +8585,Male,36,Diploma,19,4,68,22,45,4.0,7,20,Semi-Urban,Data Analyst,106221,0 +8586,Male,29,Bachelors,16,82,83,90,75,9.0,2,25,Urban,HR Executive,101019,1 +8587,Female,58,Diploma,19,91,48,11,5,4.0,7,99,Semi-Urban,Software Engineer,63530,1 +8588,Female,51,High School,9,41,18,78,88,2.0,5,80,Semi-Urban,HR Executive,53228,0 +8589,Male,43,PhD,16,86,1,44,55,2.0,5,10,Urban,Manager,106010,0 +8590,Female,32,High School,10,19,31,82,73,4.0,5,9,Urban,Software Engineer,76731,0 +8591,Female,22,Masters,2,14,28,57,62,1.0,7,27,Rural,HR Executive,79631,0 +8592,Male,49,High School,15,30,7,27,7,3.0,5,62,Urban,Data Analyst,45840,0 +8593,Male,39,Bachelors,3,24,76,10,75,9.0,4,1,Rural,Manager,102021,0 +8594,Female,34,Bachelors,4,18,98,18,31,5.0,2,77,Urban,HR Executive,129674,0 +8595,Female,43,Diploma,13,26,49,83,49,5.0,0,11,Urban,HR Executive,94414,0 +8596,Male,25,Bachelors,8,50,90,31,89,8.0,2,50,Rural,Data Analyst,81657,0 +8597,Male,48,Diploma,16,23,97,65,32,9.0,3,81,Urban,ML Engineer,55123,1 +8598,Male,40,High School,19,19,16,27,75,8.0,2,88,Semi-Urban,Data Analyst,41113,0 +8599,Male,30,Bachelors,1,47,39,20,52,2.0,3,64,Urban,ML Engineer,139678,0 +8600,Female,31,Bachelors,19,81,9,64,48,3.0,5,98,Urban,HR Executive,117179,1 +8601,Male,32,Bachelors,4,75,20,14,18,7.0,6,11,Urban,Manager,72752,0 +8602,Female,27,Diploma,10,35,51,42,4,9.0,2,98,Urban,Manager,64281,0 +8603,Female,44,Bachelors,15,10,20,16,34,8.0,5,28,Urban,Software Engineer,40803,0 +8604,Male,25,Masters,0,91,62,31,80,1.0,4,23,Urban,Manager,27691,0 +8605,Male,43,Bachelors,19,6,6,16,50,8.0,5,12,Rural,Manager,87465,0 +8606,Male,43,High School,10,41,53,46,32,7.0,4,54,Urban,HR Executive,30137,0 +8607,Female,28,High School,11,71,81,74,4,4.0,6,12,Rural,HR Executive,29062,0 +8608,Male,54,Bachelors,7,23,29,9,25,2.0,4,61,Semi-Urban,HR Executive,63365,0 +8609,Female,54,Bachelors,6,72,81,74,10,3.0,7,22,Urban,Data Analyst,91343,1 +8610,Female,58,Masters,14,98,79,27,24,5.0,3,46,Urban,Manager,48299,1 +8611,Male,22,Bachelors,19,65,41,49,46,9.0,2,35,Urban,HR Executive,122920,0 +8612,Female,22,Diploma,3,54,76,74,6,1.0,1,22,Semi-Urban,HR Executive,30698,0 +8613,Other,22,Bachelors,15,21,28,14,70,2.0,6,57,Urban,Manager,136365,0 +8614,Male,51,Diploma,4,21,6,98,51,8.0,1,22,Semi-Urban,Software Engineer,42845,0 +8615,Male,56,Bachelors,9,85,56,31,84,5.0,0,22,Urban,ML Engineer,65611,0 +8616,Other,28,High School,2,1,25,13,82,0.0,6,60,Rural,ML Engineer,89545,0 +8617,Other,28,High School,10,72,39,87,61,1.0,1,71,Urban,Data Analyst,65656,1 +8618,Male,54,Masters,14,73,28,82,21,5.0,1,99,Urban,ML Engineer,44305,1 +8619,Male,41,High School,3,72,47,94,55,9.0,6,85,Urban,HR Executive,47654,1 +8620,Male,35,Bachelors,2,27,32,14,28,5.0,7,43,Urban,Software Engineer,68761,0 +8621,Other,40,Bachelors,10,54,99,42,42,2.0,0,43,Urban,Data Analyst,142119,0 +8622,Male,25,Masters,8,58,23,9,53,2.0,7,72,Urban,Manager,38558,0 +8623,Male,33,PhD,18,86,12,79,5,6.0,1,85,Semi-Urban,Data Analyst,41535,1 +8624,Female,36,High School,10,72,60,91,60,5.0,7,39,Urban,Data Analyst,50087,1 +8625,Male,58,Diploma,0,11,54,25,83,0.0,6,21,Semi-Urban,HR Executive,35833,0 +8626,Female,23,Diploma,5,60,24,17,81,2.0,3,60,Semi-Urban,HR Executive,70298,0 +8627,Male,21,Bachelors,14,99,74,14,6,1.0,4,65,Rural,Manager,77955,1 +8628,Female,26,Masters,12,3,8,60,56,4.0,2,3,Semi-Urban,ML Engineer,20368,0 +8629,Male,59,Masters,6,74,15,86,55,0.0,4,70,Urban,Manager,96946,1 +8630,Female,47,Diploma,10,60,20,92,79,8.0,3,32,Semi-Urban,Manager,119437,0 +8631,Female,21,Masters,3,0,32,82,76,0.0,6,51,Urban,Data Analyst,127781,0 +8632,Male,44,Diploma,12,42,20,81,14,1.0,6,83,Semi-Urban,ML Engineer,138425,0 +8633,Male,33,Bachelors,7,70,58,55,32,7.0,7,29,Urban,Manager,114715,0 +8634,Male,50,Bachelors,14,29,13,75,39,0.0,2,74,Urban,Data Analyst,107862,0 +8635,Male,42,Bachelors,17,3,46,98,26,7.0,6,16,Urban,HR Executive,73995,0 +8636,Female,21,High School,6,12,93,59,54,6.0,3,77,Semi-Urban,HR Executive,67877,1 +8637,Female,49,Bachelors,13,26,51,68,7,3.0,0,66,Urban,ML Engineer,137783,0 +8638,Male,46,Masters,19,44,80,29,52,0.0,1,45,Urban,Data Analyst,49524,0 +8639,Female,28,Masters,19,31,51,80,14,7.0,2,95,Urban,Manager,144609,1 +8640,Female,57,Masters,14,26,10,90,72,2.0,6,21,Urban,Manager,66394,0 +8641,Female,43,Diploma,10,17,55,64,61,0.0,4,7,Rural,Software Engineer,134857,0 +8642,Male,43,Bachelors,18,30,19,80,10,2.0,0,73,Rural,HR Executive,42198,0 +8643,Male,54,Masters,13,69,80,6,68,1.0,3,59,Semi-Urban,Manager,149886,0 +8644,Male,22,High School,18,1,52,70,36,1.0,6,81,Rural,Manager,82969,0 +8645,Male,57,Diploma,16,43,20,72,18,1.0,5,79,Urban,HR Executive,130585,0 +8646,Male,38,Masters,15,46,34,89,39,2.0,5,77,Urban,Manager,47408,1 +8647,Male,39,High School,18,18,71,4,46,3.0,0,60,Urban,Data Analyst,60215,0 +8648,Male,33,Bachelors,15,60,76,57,59,5.0,5,97,Urban,HR Executive,104049,1 +8649,Female,49,Diploma,5,58,33,10,92,5.0,4,19,Urban,HR Executive,64442,0 +8650,Male,22,PhD,8,85,83,76,78,8.0,4,22,Semi-Urban,ML Engineer,97236,1 +8651,Male,28,Masters,17,8,44,81,25,4.0,5,35,Urban,HR Executive,109443,0 +8652,Male,40,Bachelors,18,48,30,0,97,4.0,7,94,Semi-Urban,HR Executive,62508,0 +8653,Male,30,Bachelors,0,5,23,13,52,6.0,6,46,Urban,Software Engineer,58930,0 +8654,Male,44,Bachelors,19,56,83,95,76,4.0,2,72,Semi-Urban,Manager,41847,1 +8655,Male,44,High School,18,81,20,64,76,7.0,2,60,Rural,Software Engineer,44980,0 +8656,Male,47,PhD,5,31,50,54,93,2.0,0,38,Semi-Urban,HR Executive,96335,0 +8657,Male,40,Bachelors,6,59,11,71,96,3.0,2,67,Urban,Software Engineer,134303,0 +8658,Male,39,Masters,3,22,37,54,17,2.0,1,0,Rural,Software Engineer,45110,0 +8659,Male,39,Bachelors,10,41,84,76,56,1.0,1,93,Urban,HR Executive,120828,1 +8660,Female,39,Masters,15,5,10,86,96,7.0,7,27,Semi-Urban,Software Engineer,60097,0 +8661,Male,23,Masters,14,68,1,23,92,1.0,4,33,Urban,Manager,108664,0 +8662,Male,21,High School,13,54,64,49,35,7.0,5,48,Urban,ML Engineer,48597,0 +8663,Male,52,High School,14,11,38,60,66,1.0,5,58,Rural,HR Executive,51614,0 +8664,Male,57,Bachelors,5,35,5,71,59,1.0,5,15,Urban,ML Engineer,146950,0 +8665,Male,50,Bachelors,10,6,7,31,18,8.0,6,93,Semi-Urban,HR Executive,93017,0 +8666,Male,59,Bachelors,12,12,4,40,60,0.0,2,4,Urban,Manager,55386,0 +8667,Female,57,Bachelors,1,36,4,59,24,4.0,6,91,Urban,Data Analyst,66919,0 +8668,Male,44,Diploma,10,54,55,32,22,1.0,2,83,Rural,ML Engineer,97619,0 +8669,Male,43,High School,2,73,4,80,51,9.0,5,56,Semi-Urban,Manager,48728,0 +8670,Female,30,High School,2,6,37,33,74,3.0,3,13,Urban,ML Engineer,113654,0 +8671,Female,46,High School,9,16,8,95,35,3.0,5,7,Urban,ML Engineer,23589,0 +8672,Male,36,High School,12,17,93,87,44,0.0,5,63,Rural,Software Engineer,87210,1 +8673,Male,21,Bachelors,6,76,84,15,11,3.0,7,38,Rural,Data Analyst,59696,0 +8674,Male,27,High School,8,10,73,84,77,0.0,6,48,Urban,Software Engineer,33165,0 +8675,Male,33,High School,3,31,0,4,56,5.0,0,83,Urban,Data Analyst,35684,0 +8676,Male,56,Diploma,4,41,28,67,81,9.0,6,82,Urban,Manager,97128,0 +8677,Male,59,High School,10,47,3,68,71,6.0,4,70,Urban,Data Analyst,146330,0 +8678,Female,41,Bachelors,17,82,99,33,51,1.0,5,65,Semi-Urban,Data Analyst,129030,1 +8679,Male,40,Diploma,17,59,28,83,40,9.0,4,34,Rural,HR Executive,72860,0 +8680,Male,40,High School,19,45,10,37,84,9.0,5,45,Urban,HR Executive,104238,0 +8681,Male,30,Masters,18,27,17,94,78,6.0,2,76,Rural,HR Executive,142981,0 +8682,Female,21,Bachelors,17,20,5,79,45,3.0,0,73,Urban,Data Analyst,47437,0 +8683,Male,47,Bachelors,12,98,95,24,55,7.0,3,60,Rural,Software Engineer,99476,1 +8684,Female,53,High School,10,91,91,86,33,3.0,6,89,Urban,Manager,50824,1 +8685,Male,34,Diploma,19,56,2,38,74,7.0,7,61,Urban,HR Executive,141098,0 +8686,Male,39,Bachelors,8,28,60,20,0,8.0,3,12,Urban,Data Analyst,44795,0 +8687,Male,47,PhD,8,66,34,49,88,4.0,4,23,Semi-Urban,HR Executive,82129,0 +8688,Male,44,Bachelors,8,24,84,22,6,4.0,3,13,Rural,ML Engineer,60077,0 +8689,Male,31,Bachelors,7,76,50,25,74,7.0,5,38,Urban,Manager,102301,0 +8690,Male,51,PhD,2,8,87,1,53,3.0,1,68,Semi-Urban,Data Analyst,105276,0 +8691,Male,32,Bachelors,0,40,18,37,40,6.0,0,96,Semi-Urban,Data Analyst,121553,0 +8692,Female,46,Bachelors,17,75,53,22,82,9.0,3,11,Rural,HR Executive,94659,0 +8693,Male,41,Bachelors,2,20,66,44,98,4.0,3,57,Urban,ML Engineer,38083,0 +8694,Male,54,Masters,14,14,73,32,76,8.0,0,87,Rural,Data Analyst,81055,0 +8695,Male,58,Diploma,1,42,49,21,27,6.0,0,69,Urban,ML Engineer,144479,0 +8696,Female,57,Masters,14,73,9,42,96,8.0,6,28,Urban,HR Executive,112379,0 +8697,Other,23,Masters,3,0,85,2,50,5.0,4,82,Semi-Urban,Manager,51648,0 +8698,Male,45,Bachelors,17,11,44,90,97,1.0,2,29,Urban,Software Engineer,61661,0 +8699,Male,26,Diploma,13,36,44,42,54,8.0,0,3,Semi-Urban,Software Engineer,25216,0 +8700,Male,43,Masters,18,40,39,61,70,4.0,1,37,Urban,Manager,87710,0 +8701,Female,59,Bachelors,10,33,32,63,68,2.0,1,15,Urban,Manager,33343,0 +8702,Female,28,Bachelors,1,52,2,30,6,2.0,2,89,Rural,HR Executive,110055,0 +8703,Male,25,Masters,15,23,1,66,32,8.0,2,78,Semi-Urban,Data Analyst,75702,0 +8704,Male,56,Diploma,12,6,97,51,19,3.0,7,86,Urban,Software Engineer,102985,1 +8705,Male,39,High School,18,15,7,74,17,6.0,7,35,Urban,ML Engineer,24744,0 +8706,Male,46,Bachelors,11,43,78,53,22,7.0,7,19,Urban,Data Analyst,30714,0 +8707,Female,58,Bachelors,3,9,91,54,52,8.0,3,46,Semi-Urban,Data Analyst,149140,0 +8708,Male,57,Bachelors,5,58,59,16,55,6.0,4,82,Urban,Manager,117618,0 +8709,Male,38,High School,4,44,79,36,93,2.0,3,11,Rural,ML Engineer,125321,0 +8710,Female,29,Masters,2,37,30,30,6,2.0,0,72,Urban,HR Executive,99800,0 +8711,Female,52,PhD,19,53,16,11,72,6.0,4,49,Semi-Urban,Data Analyst,24640,0 +8712,Male,43,Bachelors,14,31,60,27,18,5.0,7,37,Rural,ML Engineer,119489,0 +8713,Female,59,High School,6,18,18,96,45,6.0,1,63,Urban,Software Engineer,98250,0 +8714,Male,36,Diploma,11,87,45,37,62,8.0,5,41,Semi-Urban,ML Engineer,105838,0 +8715,Female,22,High School,3,54,29,64,68,6.0,6,42,Rural,HR Executive,120700,0 +8716,Female,27,Diploma,18,32,66,9,7,9.0,0,61,Urban,Software Engineer,62348,0 +8717,Male,26,High School,6,90,53,87,0,3.0,4,2,Semi-Urban,Software Engineer,104534,0 +8718,Female,46,High School,5,9,18,11,13,9.0,7,21,Semi-Urban,HR Executive,72009,0 +8719,Female,24,Bachelors,10,92,40,2,23,8.0,0,9,Urban,Data Analyst,115704,0 +8720,Male,50,High School,17,26,90,70,83,5.0,6,69,Urban,ML Engineer,37400,1 +8721,Male,49,Bachelors,3,64,95,52,78,5.0,4,40,Semi-Urban,Manager,83295,1 +8722,Female,58,High School,1,8,9,61,37,9.0,5,15,Urban,Data Analyst,31050,0 +8723,Male,59,Bachelors,17,50,86,84,36,5.0,6,45,Urban,HR Executive,140857,1 +8724,Male,21,High School,13,54,60,8,72,4.0,5,2,Urban,HR Executive,137834,0 +8725,Female,53,Bachelors,11,18,96,1,31,6.0,5,5,Urban,Data Analyst,25705,0 +8726,Female,46,Bachelors,7,25,41,49,99,8.0,5,43,Semi-Urban,Manager,40244,0 +8727,Male,48,Masters,18,86,97,31,29,8.0,4,39,Semi-Urban,HR Executive,142047,1 +8728,Male,49,High School,18,17,49,73,2,0.0,4,45,Urban,HR Executive,125794,0 +8729,Male,56,Masters,4,94,22,45,51,3.0,4,67,Semi-Urban,HR Executive,142503,0 +8730,Male,23,Bachelors,12,61,91,52,81,9.0,3,65,Urban,ML Engineer,52745,1 +8731,Male,59,Masters,7,70,1,26,75,5.0,4,65,Urban,Manager,46208,0 +8732,Female,33,Masters,11,50,45,18,68,1.0,0,6,Urban,Software Engineer,26776,0 +8733,Male,22,Bachelors,3,70,68,32,37,9.0,0,67,Rural,Manager,41529,1 +8734,Male,29,Diploma,11,74,32,42,32,3.0,6,6,Urban,HR Executive,90603,0 +8735,Male,25,Masters,12,93,36,21,87,1.0,5,11,Urban,Data Analyst,63894,0 +8736,Other,22,Bachelors,16,46,50,43,74,6.0,1,77,Urban,HR Executive,77954,0 +8737,Male,44,Diploma,11,26,5,40,48,5.0,0,7,Semi-Urban,HR Executive,71674,0 +8738,Male,45,Bachelors,15,3,40,1,50,3.0,7,77,Urban,Manager,62989,0 +8739,Male,25,Bachelors,13,10,43,89,96,9.0,2,69,Semi-Urban,ML Engineer,36731,0 +8740,Male,52,Diploma,1,89,43,14,59,4.0,2,25,Rural,Data Analyst,66851,0 +8741,Male,50,Bachelors,17,33,71,63,25,6.0,3,10,Urban,ML Engineer,80703,0 +8742,Male,34,Bachelors,17,17,29,75,78,9.0,3,25,Rural,ML Engineer,110057,0 +8743,Male,37,Diploma,8,53,95,16,0,8.0,2,53,Urban,Manager,121621,0 +8744,Male,30,High School,5,17,43,86,38,8.0,0,66,Urban,Data Analyst,149307,0 +8745,Male,54,Bachelors,19,51,53,4,64,2.0,4,36,Semi-Urban,Data Analyst,42045,0 +8746,Male,39,Masters,12,91,71,74,41,4.0,5,21,Urban,Data Analyst,58895,1 +8747,Male,40,Masters,11,10,66,49,27,3.0,1,93,Semi-Urban,HR Executive,82774,0 +8748,Male,32,Bachelors,15,58,0,99,26,8.0,1,1,Rural,HR Executive,92351,0 +8749,Male,57,Diploma,18,89,23,45,86,5.0,3,29,Rural,HR Executive,122092,0 +8750,Male,46,Diploma,1,3,19,62,52,2.0,2,84,Urban,Manager,58700,0 +8751,Female,31,Diploma,11,49,93,18,96,5.0,2,25,Urban,ML Engineer,118131,0 +8752,Male,30,High School,4,9,48,47,26,6.0,0,7,Semi-Urban,HR Executive,110641,0 +8753,Male,29,Diploma,17,98,35,44,42,7.0,4,49,Urban,HR Executive,120870,0 +8754,Male,47,Bachelors,2,95,73,23,69,5.0,1,68,Urban,ML Engineer,85280,1 +8755,Other,30,PhD,16,68,65,72,90,0.0,4,41,Semi-Urban,ML Engineer,125453,1 +8756,Female,52,Masters,16,36,41,66,27,9.0,5,61,Rural,Data Analyst,136310,0 +8757,Male,25,Masters,14,80,29,54,59,1.0,2,40,Rural,Software Engineer,36519,0 +8758,Male,48,Bachelors,18,82,27,78,19,6.0,3,78,Rural,ML Engineer,27429,1 +8759,Male,48,Bachelors,1,70,98,5,83,0.0,6,19,Semi-Urban,HR Executive,115028,0 +8760,Male,30,Diploma,18,40,37,85,13,8.0,5,57,Urban,ML Engineer,32363,0 +8761,Male,30,High School,1,45,31,50,43,5.0,0,87,Urban,ML Engineer,100547,0 +8762,Female,56,Diploma,12,41,46,60,77,3.0,1,25,Urban,Software Engineer,122032,0 +8763,Male,28,Bachelors,16,96,69,98,33,5.0,3,96,Semi-Urban,ML Engineer,28456,1 +8764,Female,35,Diploma,12,65,66,5,75,3.0,3,74,Urban,ML Engineer,142636,0 +8765,Male,27,Bachelors,7,71,38,39,82,6.0,3,31,Urban,Software Engineer,44295,0 +8766,Female,31,Bachelors,15,21,33,38,36,0.0,5,62,Urban,Manager,29970,0 +8767,Female,52,Masters,2,27,86,76,96,7.0,7,92,Urban,ML Engineer,116169,1 +8768,Male,49,Bachelors,9,28,51,2,1,5.0,6,21,Urban,ML Engineer,109574,0 +8769,Male,27,Bachelors,6,39,46,58,75,1.0,4,30,Semi-Urban,Manager,147039,0 +8770,Male,33,Masters,2,18,34,85,71,6.0,7,37,Semi-Urban,Data Analyst,65110,0 +8771,Male,59,High School,2,81,1,86,65,5.0,6,90,Urban,ML Engineer,66079,1 +8772,Male,55,Masters,0,33,98,85,44,0.0,4,29,Urban,ML Engineer,25168,1 +8773,Male,46,Masters,17,50,34,20,84,3.0,4,1,Urban,Data Analyst,130356,0 +8774,Male,45,Bachelors,11,10,77,51,33,4.0,1,70,Semi-Urban,Data Analyst,58659,0 +8775,Female,33,Diploma,11,81,22,87,51,1.0,1,89,Urban,ML Engineer,62750,1 +8776,Male,33,Masters,5,86,79,52,10,0.0,5,2,Semi-Urban,Manager,41122,0 +8777,Other,29,High School,5,69,92,23,2,9.0,2,75,Urban,Manager,49433,1 +8778,Male,59,High School,5,35,88,41,47,4.0,0,59,Urban,HR Executive,29385,0 +8779,Female,50,Bachelors,9,75,54,59,27,4.0,6,58,Rural,Software Engineer,70843,1 +8780,Male,43,High School,11,37,59,50,29,5.0,6,51,Urban,Manager,64232,0 +8781,Male,45,High School,4,0,22,76,72,7.0,7,55,Urban,HR Executive,78130,0 +8782,Female,47,High School,19,97,22,83,57,2.0,6,41,Semi-Urban,Manager,116073,1 +8783,Male,26,High School,16,19,32,36,49,6.0,1,79,Urban,Software Engineer,126460,0 +8784,Female,28,Bachelors,8,12,26,33,28,3.0,2,52,Urban,HR Executive,88126,0 +8785,Male,59,Bachelors,6,81,53,32,94,4.0,1,97,Semi-Urban,ML Engineer,127316,1 +8786,Male,55,Masters,19,74,58,79,1,3.0,1,6,Semi-Urban,Data Analyst,110657,0 +8787,Male,53,Bachelors,6,91,3,21,94,1.0,0,44,Urban,Data Analyst,136413,0 +8788,Female,43,High School,15,36,8,41,71,4.0,4,24,Urban,Software Engineer,99532,0 +8789,Male,55,Masters,14,7,4,19,13,4.0,7,73,Urban,HR Executive,25432,0 +8790,Female,24,Bachelors,9,76,18,38,2,4.0,2,4,Urban,ML Engineer,60759,0 +8791,Female,33,Bachelors,9,83,16,10,91,5.0,2,51,Urban,HR Executive,45561,0 +8792,Male,37,High School,12,75,4,60,11,7.0,5,44,Semi-Urban,Data Analyst,141936,0 +8793,Male,32,Bachelors,10,95,95,25,45,6.0,2,69,Urban,Manager,53786,1 +8794,Female,34,PhD,9,57,73,98,72,1.0,6,18,Rural,Software Engineer,28512,1 +8795,Male,58,Masters,1,45,99,90,7,7.0,3,48,Semi-Urban,Software Engineer,113883,1 +8796,Male,52,Bachelors,6,45,53,85,47,0.0,7,20,Rural,Manager,76967,0 +8797,Male,21,Bachelors,13,54,95,48,89,5.0,2,79,Urban,Manager,40501,1 +8798,Male,55,High School,8,8,83,44,4,8.0,1,68,Rural,Software Engineer,87782,0 +8799,Male,53,Masters,6,59,0,30,79,3.0,4,73,Semi-Urban,Software Engineer,81851,0 +8800,Male,30,Masters,13,33,74,38,3,0.0,6,47,Rural,Software Engineer,43189,0 +8801,Female,34,Diploma,8,20,24,85,30,4.0,6,49,Urban,Manager,82132,0 +8802,Male,30,Bachelors,12,95,77,15,40,9.0,5,80,Urban,Software Engineer,98575,1 +8803,Male,21,Bachelors,15,33,38,8,66,1.0,0,23,Urban,HR Executive,142560,0 +8804,Other,44,Bachelors,12,67,74,58,66,3.0,2,9,Rural,Data Analyst,137439,0 +8805,Female,28,Masters,2,95,76,76,41,4.0,0,77,Urban,Manager,85049,1 +8806,Female,58,Bachelors,16,13,74,27,26,7.0,5,68,Rural,Data Analyst,45745,0 +8807,Male,38,Masters,7,94,14,36,65,3.0,1,78,Rural,HR Executive,109687,0 +8808,Female,25,PhD,4,25,49,88,93,4.0,3,13,Rural,HR Executive,140491,0 +8809,Male,35,Diploma,8,7,32,94,93,7.0,6,65,Urban,Data Analyst,107293,0 +8810,Male,25,Diploma,3,72,0,83,24,9.0,3,36,Urban,Data Analyst,45416,0 +8811,Male,42,PhD,15,90,21,46,87,9.0,7,42,Urban,Software Engineer,128975,0 +8812,Male,47,Masters,10,63,67,57,46,6.0,4,84,Rural,HR Executive,126267,1 +8813,Female,54,Masters,1,71,56,76,10,1.0,3,78,Semi-Urban,Manager,50015,1 +8814,Male,55,Bachelors,4,2,46,41,33,6.0,0,6,Urban,Data Analyst,99333,0 +8815,Female,45,Diploma,2,50,33,99,6,1.0,5,33,Semi-Urban,Manager,111547,0 +8816,Female,22,Diploma,2,53,49,15,58,6.0,6,77,Rural,HR Executive,38149,0 +8817,Male,43,Masters,9,27,67,98,93,7.0,1,29,Semi-Urban,Software Engineer,131912,0 +8818,Male,41,Bachelors,0,96,40,67,81,0.0,1,91,Urban,Software Engineer,74334,1 +8819,Male,25,Diploma,11,56,28,0,30,6.0,1,61,Urban,Data Analyst,103011,0 +8820,Male,47,Masters,4,50,98,73,1,8.0,3,79,Rural,Data Analyst,147406,1 +8821,Male,38,Bachelors,3,59,74,37,30,2.0,0,26,Urban,Data Analyst,60810,0 +8822,Other,54,High School,11,96,76,9,28,5.0,6,33,Urban,Data Analyst,71495,0 +8823,Male,56,Bachelors,11,83,22,42,52,6.0,6,88,Urban,Manager,141845,1 +8824,Male,58,PhD,7,96,93,67,38,5.0,7,88,Semi-Urban,Manager,57141,1 +8825,Female,47,Bachelors,15,44,38,67,82,1.0,0,16,Semi-Urban,Manager,65968,0 +8826,Male,48,Masters,19,1,4,97,13,4.0,5,59,Semi-Urban,Data Analyst,30487,0 +8827,Female,35,Diploma,15,19,87,56,5,2.0,5,33,Rural,Software Engineer,29638,0 +8828,Male,45,Bachelors,13,1,85,67,61,9.0,4,98,Urban,Data Analyst,126752,1 +8829,Male,39,Bachelors,4,85,81,70,49,3.0,1,91,Semi-Urban,Data Analyst,109522,1 +8830,Male,37,Bachelors,13,4,24,97,31,4.0,6,71,Semi-Urban,Data Analyst,131625,0 +8831,Male,53,Bachelors,13,67,54,60,87,4.0,4,73,Urban,Data Analyst,85044,1 +8832,Male,21,Bachelors,10,76,30,76,39,2.0,3,51,Urban,Data Analyst,130768,0 +8833,Female,47,High School,17,8,61,67,37,9.0,1,76,Urban,Data Analyst,141923,0 +8834,Male,30,Diploma,5,58,54,41,31,4.0,3,16,Urban,ML Engineer,131778,0 +8835,Female,59,Bachelors,0,17,52,82,60,6.0,6,52,Rural,Manager,128421,0 +8836,Male,30,Bachelors,12,56,90,74,5,6.0,1,18,Semi-Urban,Manager,124381,1 +8837,Male,52,Bachelors,8,32,38,42,31,3.0,0,78,Semi-Urban,Software Engineer,27362,0 +8838,Male,41,Diploma,9,87,72,98,26,6.0,1,76,Urban,Software Engineer,36902,1 +8839,Female,28,Diploma,18,12,85,79,43,9.0,5,63,Semi-Urban,HR Executive,110475,0 +8840,Male,29,Bachelors,0,87,83,1,44,1.0,0,8,Urban,Manager,64579,0 +8841,Male,56,High School,0,54,50,88,61,3.0,6,84,Semi-Urban,Manager,41141,1 +8842,Female,38,High School,12,69,21,11,81,1.0,0,54,Rural,Data Analyst,101041,0 +8843,Male,25,High School,8,57,86,33,6,9.0,4,0,Rural,HR Executive,104623,0 +8844,Female,42,Diploma,7,9,70,15,50,8.0,1,64,Semi-Urban,Manager,55274,0 +8845,Male,34,Bachelors,14,13,61,30,45,9.0,0,99,Urban,ML Engineer,28820,0 +8846,Female,52,Diploma,16,90,11,79,79,6.0,2,50,Urban,Software Engineer,40076,0 +8847,Female,52,Bachelors,17,54,22,78,17,1.0,6,53,Urban,Data Analyst,92116,0 +8848,Female,32,Diploma,8,41,78,93,45,1.0,5,68,Urban,ML Engineer,93677,1 +8849,Male,25,Diploma,15,76,38,37,13,0.0,0,58,Semi-Urban,HR Executive,83440,0 +8850,Male,48,Masters,5,46,5,83,54,0.0,2,8,Semi-Urban,Data Analyst,51133,0 +8851,Female,48,Bachelors,5,98,2,79,65,3.0,6,2,Urban,ML Engineer,101177,0 +8852,Male,49,Bachelors,8,59,74,52,60,4.0,7,19,Rural,HR Executive,137847,0 +8853,Male,54,Diploma,19,81,45,60,11,7.0,1,82,Urban,Manager,43880,1 +8854,Female,37,Bachelors,1,26,8,36,54,5.0,1,86,Urban,HR Executive,107034,0 +8855,Male,34,Masters,6,68,46,72,24,3.0,2,47,Urban,Manager,89305,0 +8856,Male,36,Masters,13,30,28,56,64,4.0,6,3,Rural,Data Analyst,106415,0 +8857,Male,41,Bachelors,5,88,34,88,57,2.0,4,85,Urban,Data Analyst,50629,1 +8858,Male,47,Bachelors,1,75,99,60,1,2.0,1,66,Rural,Manager,40503,1 +8859,Male,34,High School,16,82,16,73,48,9.0,0,88,Semi-Urban,ML Engineer,88126,1 +8860,Female,22,Bachelors,6,36,1,3,39,5.0,6,95,Rural,ML Engineer,53995,0 +8861,Male,27,Bachelors,8,73,23,69,69,4.0,5,16,Rural,Manager,105369,0 +8862,Female,39,Diploma,4,18,60,87,35,3.0,5,35,Semi-Urban,Manager,131617,0 +8863,Female,42,Masters,7,50,38,27,51,1.0,4,38,Rural,Data Analyst,130595,0 +8864,Female,38,Masters,2,8,42,90,17,6.0,4,44,Urban,Manager,105201,0 +8865,Male,49,Masters,15,87,42,40,41,2.0,0,98,Rural,HR Executive,147158,1 +8866,Female,44,Diploma,0,94,8,27,15,4.0,2,7,Semi-Urban,ML Engineer,87166,0 +8867,Male,28,Diploma,18,22,14,56,36,9.0,2,55,Urban,ML Engineer,107665,0 +8868,Male,55,Bachelors,19,55,30,43,39,1.0,2,91,Urban,ML Engineer,129266,0 +8869,Female,55,Bachelors,10,42,60,72,5,8.0,1,62,Urban,ML Engineer,39262,0 +8870,Male,56,Masters,0,65,46,50,36,7.0,3,80,Semi-Urban,Manager,75260,1 +8871,Female,58,Diploma,18,54,82,66,85,0.0,0,6,Urban,HR Executive,52053,0 +8872,Male,30,Bachelors,4,98,72,47,62,8.0,5,74,Urban,ML Engineer,93226,1 +8873,Female,52,Bachelors,13,14,35,22,54,5.0,7,31,Urban,HR Executive,141563,0 +8874,Male,56,Diploma,7,96,1,47,68,5.0,4,9,Semi-Urban,Data Analyst,96032,0 +8875,Female,50,Masters,19,26,3,85,0,4.0,1,70,Semi-Urban,Manager,68623,0 +8876,Male,35,Bachelors,4,46,68,28,36,6.0,0,81,Semi-Urban,HR Executive,129529,0 +8877,Male,36,Bachelors,4,6,51,68,56,0.0,5,96,Urban,Software Engineer,74665,0 +8878,Male,58,Bachelors,2,88,70,82,48,9.0,3,91,Urban,Manager,97530,1 +8879,Male,43,Diploma,14,9,65,32,31,7.0,6,64,Urban,Manager,65905,0 +8880,Male,35,Masters,3,90,44,35,67,5.0,7,22,Rural,Manager,72728,0 +8881,Male,26,Diploma,0,81,9,20,42,6.0,7,21,Urban,Software Engineer,132078,0 +8882,Male,27,High School,17,80,39,56,78,0.0,1,46,Rural,ML Engineer,74944,0 +8883,Male,35,Masters,14,40,35,36,15,0.0,5,69,Urban,HR Executive,43770,0 +8884,Male,44,Bachelors,11,60,57,39,59,7.0,3,78,Semi-Urban,Manager,84626,0 +8885,Female,23,Diploma,18,8,11,84,2,9.0,6,56,Urban,ML Engineer,82108,0 +8886,Female,34,Bachelors,19,25,84,7,5,5.0,6,80,Urban,Data Analyst,125010,0 +8887,Female,41,Bachelors,2,0,58,83,13,9.0,6,64,Rural,Data Analyst,97121,0 +8888,Female,29,Bachelors,15,26,16,75,53,6.0,2,49,Rural,Data Analyst,100383,0 +8889,Male,32,Bachelors,1,35,60,53,50,0.0,5,92,Urban,Manager,77711,1 +8890,Male,44,PhD,17,79,98,95,92,8.0,3,27,Semi-Urban,ML Engineer,149798,1 +8891,Male,40,Bachelors,5,12,42,63,89,7.0,5,25,Semi-Urban,Manager,81402,0 +8892,Female,55,Bachelors,4,78,23,19,79,6.0,0,46,Urban,Data Analyst,123257,0 +8893,Other,55,PhD,13,65,29,92,10,0.0,5,87,Urban,Data Analyst,84309,1 +8894,Male,54,Diploma,8,96,17,12,94,7.0,6,69,Urban,HR Executive,75102,0 +8895,Male,48,High School,13,73,80,37,40,8.0,6,2,Rural,ML Engineer,86795,0 +8896,Male,25,Diploma,0,2,72,81,76,4.0,3,71,Urban,ML Engineer,100570,0 +8897,Male,38,Bachelors,9,60,13,82,48,3.0,2,56,Rural,HR Executive,21698,0 +8898,Male,29,Diploma,18,74,91,41,29,3.0,0,54,Urban,Data Analyst,108056,1 +8899,Male,26,PhD,17,14,90,21,25,1.0,4,59,Rural,Manager,128393,0 +8900,Female,27,High School,0,76,16,7,59,5.0,5,3,Urban,ML Engineer,21246,0 +8901,Male,21,Diploma,5,33,7,7,57,3.0,6,55,Urban,ML Engineer,114983,0 +8902,Female,50,Masters,5,87,50,62,54,1.0,4,96,Urban,HR Executive,101096,1 +8903,Female,42,Bachelors,17,86,36,95,57,9.0,3,88,Urban,ML Engineer,134632,1 +8904,Female,53,Bachelors,12,53,53,2,29,5.0,3,40,Semi-Urban,Software Engineer,96105,0 +8905,Female,56,Masters,0,66,46,28,25,5.0,5,59,Rural,Software Engineer,36449,0 +8906,Female,25,Bachelors,2,81,12,89,25,5.0,2,16,Urban,Software Engineer,79898,0 +8907,Female,47,Diploma,5,33,34,2,92,1.0,2,57,Urban,Software Engineer,147831,0 +8908,Female,40,Diploma,14,70,32,53,54,7.0,5,91,Urban,Data Analyst,94408,1 +8909,Male,54,Bachelors,19,27,88,67,78,5.0,5,66,Urban,Manager,126167,1 +8910,Other,56,Bachelors,0,79,75,16,49,6.0,2,45,Rural,Data Analyst,132693,0 +8911,Female,41,Bachelors,11,43,8,1,68,8.0,2,88,Urban,Software Engineer,118386,0 +8912,Female,35,Masters,11,35,85,30,82,8.0,1,2,Urban,Manager,45517,0 +8913,Female,38,Bachelors,2,98,90,24,54,8.0,5,34,Urban,Manager,71356,1 +8914,Male,42,Masters,9,84,49,11,28,5.0,0,17,Urban,HR Executive,89270,0 +8915,Male,59,Masters,7,75,41,52,40,6.0,6,97,Rural,ML Engineer,137279,1 +8916,Male,26,Diploma,15,69,92,93,3,9.0,4,1,Urban,ML Engineer,68716,1 +8917,Male,36,Diploma,17,83,53,82,99,8.0,4,52,Rural,ML Engineer,91946,1 +8918,Female,48,PhD,18,37,84,30,5,2.0,7,3,Semi-Urban,Manager,76410,0 +8919,Male,50,Diploma,3,96,54,23,52,8.0,5,11,Urban,ML Engineer,137031,0 +8920,Male,58,High School,10,52,53,76,7,8.0,3,29,Rural,Manager,59971,0 +8921,Male,30,High School,6,14,79,72,19,3.0,5,38,Urban,Manager,95673,0 +8922,Male,30,Bachelors,8,30,0,54,77,7.0,2,3,Semi-Urban,ML Engineer,92508,0 +8923,Female,23,PhD,6,97,70,61,51,1.0,1,28,Rural,Software Engineer,108407,1 +8924,Female,38,Masters,18,68,91,18,32,9.0,4,68,Urban,Data Analyst,85140,1 +8925,Male,42,Bachelors,0,52,40,36,32,5.0,6,66,Urban,ML Engineer,98826,0 +8926,Male,49,Bachelors,1,66,31,6,48,9.0,7,34,Urban,ML Engineer,39051,0 +8927,Male,28,Masters,18,7,55,50,49,7.0,2,43,Rural,Data Analyst,141965,0 +8928,Male,28,High School,15,62,42,44,20,5.0,6,47,Urban,ML Engineer,42979,0 +8929,Male,23,Bachelors,4,59,68,46,66,3.0,4,37,Rural,Manager,139812,0 +8930,Other,50,Masters,10,87,16,66,24,8.0,5,6,Urban,HR Executive,33574,0 +8931,Male,30,Bachelors,12,44,10,66,4,9.0,1,19,Urban,ML Engineer,121594,0 +8932,Male,28,High School,13,20,8,41,31,2.0,4,47,Semi-Urban,ML Engineer,49728,0 +8933,Male,27,Masters,11,95,49,91,99,6.0,4,28,Urban,Manager,72423,1 +8934,Female,58,High School,9,42,90,10,18,2.0,7,93,Semi-Urban,ML Engineer,82572,0 +8935,Female,59,Masters,12,12,26,62,28,4.0,7,90,Urban,Software Engineer,46435,0 +8936,Female,39,Masters,3,82,75,52,27,3.0,7,9,Rural,Manager,123998,0 +8937,Male,34,Bachelors,16,30,11,99,41,6.0,2,43,Urban,HR Executive,129698,0 +8938,Female,53,Bachelors,13,55,70,55,14,4.0,1,81,Urban,ML Engineer,90411,1 +8939,Male,48,Bachelors,17,9,83,18,68,7.0,3,95,Semi-Urban,Data Analyst,73861,0 +8940,Male,40,Bachelors,11,81,99,95,65,1.0,4,70,Urban,ML Engineer,84952,1 +8941,Male,21,Bachelors,12,53,60,34,58,4.0,6,35,Urban,Software Engineer,108419,0 +8942,Male,46,High School,15,3,32,70,30,2.0,5,30,Urban,Data Analyst,104779,0 +8943,Female,30,Bachelors,15,37,80,68,94,9.0,2,63,Urban,Manager,102304,1 +8944,Female,52,Diploma,0,96,87,17,57,3.0,3,29,Urban,Software Engineer,29901,0 +8945,Male,52,Diploma,2,35,33,69,45,7.0,4,39,Urban,ML Engineer,137399,0 +8946,Female,40,Masters,18,61,68,6,24,3.0,1,99,Rural,HR Executive,28054,0 +8947,Female,56,Bachelors,15,69,23,53,41,9.0,0,48,Urban,ML Engineer,123174,0 +8948,Female,50,Bachelors,14,17,8,50,96,1.0,3,11,Semi-Urban,Software Engineer,136214,0 +8949,Male,54,High School,13,38,92,76,70,5.0,1,95,Semi-Urban,ML Engineer,50263,1 +8950,Male,53,Bachelors,18,23,3,3,12,7.0,0,23,Semi-Urban,Manager,30302,0 +8951,Male,34,Bachelors,6,49,74,7,80,2.0,1,37,Urban,ML Engineer,138016,0 +8952,Female,42,Bachelors,5,53,43,35,37,5.0,3,44,Urban,Manager,143335,0 +8953,Male,48,High School,15,3,82,56,21,5.0,5,63,Rural,Software Engineer,38052,0 +8954,Male,50,Diploma,12,61,12,2,28,7.0,5,31,Urban,ML Engineer,111672,0 +8955,Male,28,Diploma,4,97,66,18,17,3.0,4,68,Semi-Urban,HR Executive,149328,1 +8956,Male,48,High School,6,98,45,13,75,0.0,0,5,Urban,Manager,47147,0 +8957,Female,41,Bachelors,18,39,95,70,63,7.0,3,4,Semi-Urban,Software Engineer,58004,0 +8958,Female,29,Bachelors,12,76,35,66,61,4.0,1,75,Rural,Data Analyst,28757,1 +8959,Female,36,PhD,13,6,97,40,65,0.0,4,16,Semi-Urban,ML Engineer,94839,0 +8960,Female,48,Bachelors,7,43,92,60,89,2.0,5,61,Rural,Software Engineer,28156,1 +8961,Male,21,Diploma,10,45,16,51,33,3.0,4,70,Urban,ML Engineer,127552,0 +8962,Male,57,Diploma,6,90,6,38,86,4.0,0,80,Urban,Software Engineer,54993,0 +8963,Male,25,Bachelors,17,22,25,12,61,3.0,4,34,Rural,HR Executive,47585,0 +8964,Male,32,Diploma,5,26,42,20,51,1.0,6,32,Urban,Software Engineer,88818,0 +8965,Male,30,Bachelors,11,65,26,65,86,4.0,4,36,Semi-Urban,Data Analyst,45559,0 +8966,Female,38,Masters,17,80,34,12,84,9.0,2,56,Urban,HR Executive,83386,0 +8967,Male,35,Bachelors,2,42,46,29,2,9.0,3,63,Urban,Data Analyst,76568,0 +8968,Female,22,Bachelors,11,79,60,63,54,1.0,7,46,Semi-Urban,Data Analyst,62328,1 +8969,Male,36,Diploma,9,18,58,54,55,4.0,4,53,Semi-Urban,Manager,67264,0 +8970,Male,29,Bachelors,16,38,32,2,9,7.0,5,37,Urban,HR Executive,137068,0 +8971,Male,49,High School,5,65,1,38,14,4.0,6,32,Urban,HR Executive,136732,0 +8972,Male,36,Bachelors,11,59,75,20,89,2.0,3,91,Urban,Manager,137350,1 +8973,Male,32,Bachelors,11,96,47,87,14,8.0,2,41,Urban,Software Engineer,34946,1 +8974,Male,34,Diploma,15,18,75,15,56,4.0,1,42,Semi-Urban,HR Executive,50060,0 +8975,Male,58,Diploma,7,13,20,37,97,5.0,4,59,Rural,HR Executive,44419,0 +8976,Male,53,Diploma,12,8,89,25,35,1.0,2,34,Semi-Urban,Software Engineer,93932,0 +8977,Male,45,Bachelors,2,7,86,15,87,3.0,6,2,Semi-Urban,Software Engineer,87510,0 +8978,Female,43,High School,10,17,95,3,31,0.0,5,48,Semi-Urban,Software Engineer,134042,0 +8979,Female,27,Bachelors,8,84,64,17,88,1.0,6,98,Rural,Data Analyst,73210,1 +8980,Male,53,High School,10,67,39,15,4,1.0,0,16,Urban,HR Executive,75826,0 +8981,Female,27,Bachelors,19,22,91,12,28,6.0,4,85,Semi-Urban,ML Engineer,102017,0 +8982,Female,41,Bachelors,12,61,83,56,97,6.0,3,81,Semi-Urban,Manager,136988,1 +8983,Female,31,PhD,10,32,72,33,2,7.0,0,59,Urban,ML Engineer,98383,0 +8984,Male,38,High School,5,40,20,50,22,3.0,7,90,Semi-Urban,Manager,129616,0 +8985,Male,31,Bachelors,18,21,62,49,45,2.0,6,58,Urban,Manager,87368,0 +8986,Female,41,Masters,5,56,54,23,91,9.0,3,97,Rural,HR Executive,43222,0 +8987,Male,39,High School,11,60,78,14,69,0.0,2,45,Urban,Data Analyst,66133,0 +8988,Female,47,Diploma,11,73,4,60,80,0.0,6,60,Urban,Data Analyst,84941,0 +8989,Female,32,Bachelors,1,75,78,40,69,6.0,7,20,Rural,HR Executive,56808,0 +8990,Male,22,Bachelors,13,2,28,35,5,2.0,7,2,Semi-Urban,ML Engineer,40566,0 +8991,Male,26,Bachelors,2,23,46,93,7,4.0,6,1,Urban,Manager,39431,0 +8992,Male,59,Diploma,5,75,56,81,1,3.0,5,91,Urban,Manager,29833,1 +8993,Male,34,High School,1,83,15,28,45,3.0,1,84,Urban,Data Analyst,40894,0 +8994,Male,45,Diploma,15,46,8,21,68,0.0,5,15,Urban,Data Analyst,45477,0 +8995,Male,59,Diploma,16,25,22,58,88,8.0,4,68,Rural,Software Engineer,38874,0 +8996,Male,35,PhD,19,79,69,27,61,1.0,6,64,Rural,HR Executive,75605,1 +8997,Male,44,Masters,12,40,29,72,76,3.0,3,39,Urban,HR Executive,145732,0 +8998,Other,41,Bachelors,19,82,93,68,21,0.0,1,23,Rural,Software Engineer,127211,1 +8999,Male,53,High School,9,13,94,24,62,2.0,1,88,Urban,HR Executive,22729,0 +9000,Female,40,Diploma,0,76,21,82,24,6.0,5,25,Semi-Urban,ML Engineer,54786,0 +9001,Female,26,Bachelors,15,40,68,15,31,6.0,3,44,Urban,Manager,62543,0 +9002,Male,28,High School,10,29,46,70,45,2.0,0,80,Urban,Software Engineer,57455,0 +9003,Female,51,PhD,19,17,20,76,45,2.0,3,47,Semi-Urban,HR Executive,84019,0 +9004,Male,27,Bachelors,6,10,55,14,93,1.0,0,85,Urban,Software Engineer,69203,0 +9005,Female,56,Bachelors,12,52,12,70,73,3.0,5,12,Urban,ML Engineer,40587,0 +9006,Male,48,High School,0,31,58,50,18,0.0,4,76,Semi-Urban,Manager,67536,0 +9007,Male,57,Bachelors,6,70,98,21,87,6.0,1,80,Semi-Urban,ML Engineer,78257,1 +9008,Male,54,High School,10,26,60,18,70,8.0,0,14,Semi-Urban,HR Executive,32917,0 +9009,Male,44,Masters,13,53,99,65,27,4.0,6,4,Rural,Manager,56503,0 +9010,Male,56,Diploma,15,38,39,37,3,1.0,5,57,Urban,Manager,103381,0 +9011,Male,26,Bachelors,10,27,77,38,87,3.0,2,63,Urban,HR Executive,57378,0 +9012,Male,44,Diploma,13,60,33,61,22,8.0,1,66,Urban,Manager,148848,0 +9013,Male,32,High School,3,3,95,98,64,3.0,0,27,Urban,Manager,118070,0 +9014,Male,51,Diploma,6,37,69,3,32,7.0,5,75,Rural,HR Executive,110044,0 +9015,Male,50,Bachelors,12,75,79,58,0,2.0,7,8,Rural,Data Analyst,56899,0 +9016,Male,39,Bachelors,5,39,80,34,87,4.0,5,6,Semi-Urban,Software Engineer,115328,0 +9017,Male,42,Diploma,8,4,33,3,84,2.0,5,56,Urban,Data Analyst,45323,0 +9018,Female,49,High School,9,69,7,13,43,7.0,1,71,Urban,ML Engineer,73715,0 +9019,Male,39,Masters,16,17,98,16,12,5.0,3,1,Semi-Urban,HR Executive,68021,0 +9020,Female,42,Masters,2,29,51,0,45,4.0,0,64,Semi-Urban,Manager,125412,0 +9021,Male,31,Bachelors,3,51,93,73,32,4.0,0,55,Urban,HR Executive,72827,1 +9022,Female,56,Masters,4,83,51,33,31,0.0,1,18,Urban,Manager,91734,0 +9023,Male,39,Bachelors,5,35,12,89,57,9.0,0,47,Urban,Software Engineer,75598,0 +9024,Male,24,Bachelors,19,80,33,20,68,2.0,5,80,Urban,Software Engineer,53689,0 +9025,Male,35,PhD,18,68,95,47,48,1.0,0,65,Rural,ML Engineer,107093,1 +9026,Male,26,PhD,4,72,54,14,80,2.0,6,85,Urban,Software Engineer,25991,0 +9027,Male,41,High School,17,41,12,5,0,7.0,7,10,Urban,Manager,85038,0 +9028,Male,21,Bachelors,6,30,79,6,0,4.0,1,53,Urban,Data Analyst,107434,0 +9029,Other,24,Bachelors,4,13,20,41,59,0.0,0,70,Urban,ML Engineer,86604,0 +9030,Male,36,Masters,19,19,80,58,90,0.0,3,34,Urban,HR Executive,47056,0 +9031,Male,49,Masters,8,18,81,12,99,8.0,3,5,Urban,HR Executive,88420,0 +9032,Female,46,Diploma,18,9,57,89,46,9.0,6,71,Rural,Manager,138176,0 +9033,Male,52,High School,18,68,91,21,30,1.0,5,87,Urban,Manager,140857,1 +9034,Female,40,Diploma,2,50,93,82,7,8.0,1,93,Urban,HR Executive,136818,1 +9035,Male,21,Masters,17,68,2,76,36,1.0,2,77,Urban,Software Engineer,80205,0 +9036,Female,37,Bachelors,3,43,47,85,22,9.0,4,25,Urban,Software Engineer,23812,0 +9037,Male,24,Bachelors,17,92,68,17,47,5.0,7,21,Urban,Manager,127955,0 +9038,Female,56,Bachelors,8,56,16,6,20,0.0,7,80,Semi-Urban,ML Engineer,93146,0 +9039,Female,56,Masters,5,60,94,61,88,2.0,0,21,Urban,Software Engineer,31930,0 +9040,Male,40,Bachelors,8,7,0,46,95,5.0,5,7,Semi-Urban,HR Executive,139803,0 +9041,Male,38,Diploma,3,63,66,93,76,2.0,1,26,Semi-Urban,HR Executive,33114,1 +9042,Male,59,Masters,7,8,10,72,59,2.0,6,91,Rural,Data Analyst,117574,0 +9043,Other,24,Bachelors,10,76,36,65,30,8.0,2,25,Urban,Software Engineer,102610,0 +9044,Male,33,Bachelors,12,4,24,76,39,4.0,1,42,Urban,HR Executive,26422,0 +9045,Male,46,Bachelors,3,52,65,38,31,5.0,0,98,Semi-Urban,HR Executive,50724,1 +9046,Male,29,High School,11,84,63,44,54,8.0,6,83,Rural,Software Engineer,89540,1 +9047,Male,41,High School,3,27,97,22,61,6.0,6,92,Rural,Software Engineer,23436,1 +9048,Male,36,PhD,5,91,47,54,60,3.0,4,11,Urban,Manager,137784,0 +9049,Other,46,Bachelors,19,71,31,24,49,1.0,0,63,Semi-Urban,Data Analyst,73773,0 +9050,Male,58,Diploma,16,16,57,88,26,3.0,4,9,Urban,ML Engineer,37373,0 +9051,Female,50,Diploma,10,73,57,3,9,4.0,7,37,Urban,Data Analyst,92126,0 +9052,Male,46,High School,8,86,49,72,50,1.0,0,15,Urban,Data Analyst,35042,0 +9053,Male,54,Diploma,3,51,47,20,64,5.0,6,91,Urban,HR Executive,41015,0 +9054,Male,40,Masters,10,64,47,20,70,3.0,3,98,Urban,Data Analyst,77266,0 +9055,Male,43,Bachelors,5,38,81,0,61,3.0,2,65,Urban,Manager,34607,0 +9056,Other,52,Diploma,11,68,51,8,55,8.0,5,86,Semi-Urban,HR Executive,130671,0 +9057,Female,50,Bachelors,8,99,4,8,72,1.0,4,75,Urban,Software Engineer,120149,0 +9058,Male,46,High School,14,80,66,87,16,3.0,5,71,Semi-Urban,Manager,66383,1 +9059,Male,44,PhD,0,9,54,2,39,6.0,1,6,Rural,Software Engineer,43954,0 +9060,Male,23,Diploma,8,48,93,26,14,0.0,0,90,Urban,HR Executive,83625,1 +9061,Female,44,Diploma,19,76,62,12,28,4.0,7,4,Rural,ML Engineer,76588,0 +9062,Female,51,Masters,15,26,60,64,4,9.0,6,92,Semi-Urban,Data Analyst,23819,1 +9063,Female,42,Bachelors,10,38,84,20,70,2.0,5,24,Urban,Manager,57769,0 +9064,Male,42,Bachelors,5,85,69,60,75,8.0,2,80,Urban,Software Engineer,25742,1 +9065,Male,29,Bachelors,16,63,55,40,49,1.0,4,73,Rural,Manager,70404,0 +9066,Male,43,Diploma,5,3,91,93,95,5.0,1,79,Semi-Urban,HR Executive,27919,1 +9067,Male,43,Bachelors,8,40,1,84,22,5.0,1,72,Rural,ML Engineer,148575,0 +9068,Male,40,Bachelors,2,69,48,25,22,7.0,0,78,Urban,ML Engineer,70748,0 +9069,Male,47,Bachelors,17,7,5,65,20,3.0,5,10,Urban,Manager,97280,0 +9070,Male,47,High School,2,87,16,55,49,1.0,0,97,Urban,Software Engineer,95378,1 +9071,Female,49,Masters,5,28,49,44,42,2.0,3,74,Urban,Manager,88421,0 +9072,Female,24,Bachelors,1,42,34,18,23,5.0,6,58,Urban,HR Executive,132889,0 +9073,Male,35,Bachelors,12,22,34,16,73,8.0,2,76,Semi-Urban,HR Executive,87912,0 +9074,Male,27,High School,9,2,88,31,17,2.0,7,65,Urban,ML Engineer,92139,0 +9075,Male,40,Diploma,5,0,13,83,78,4.0,1,43,Urban,ML Engineer,120702,0 +9076,Female,29,Bachelors,11,92,64,48,59,1.0,5,54,Semi-Urban,Manager,29463,1 +9077,Female,49,Diploma,8,59,27,7,68,6.0,0,21,Semi-Urban,Manager,71265,0 +9078,Female,31,Diploma,1,13,61,2,82,7.0,2,92,Urban,ML Engineer,24002,0 +9079,Female,22,Bachelors,7,11,5,28,57,3.0,6,46,Urban,Manager,138009,0 +9080,Male,44,Masters,16,51,75,6,1,4.0,1,61,Urban,Manager,40968,0 +9081,Male,22,Diploma,9,7,62,50,75,6.0,0,81,Semi-Urban,Manager,100601,0 +9082,Male,32,Bachelors,17,40,90,98,6,9.0,3,54,Urban,Manager,70724,1 +9083,Male,42,Bachelors,5,38,47,81,33,5.0,1,84,Rural,Data Analyst,78680,1 +9084,Female,25,Bachelors,6,29,5,51,27,4.0,3,40,Rural,Software Engineer,133577,0 +9085,Male,36,PhD,13,48,20,66,87,3.0,4,77,Rural,ML Engineer,125331,0 +9086,Male,27,High School,3,65,66,81,76,5.0,1,73,Rural,Data Analyst,102813,1 +9087,Male,28,Bachelors,5,91,45,41,47,1.0,2,30,Urban,Manager,116990,0 +9088,Other,40,Diploma,9,0,27,70,85,2.0,6,46,Urban,Software Engineer,111887,0 +9089,Male,47,High School,13,2,66,75,22,3.0,2,83,Semi-Urban,Software Engineer,89988,0 +9090,Female,37,PhD,11,96,22,73,38,6.0,4,28,Semi-Urban,Data Analyst,112427,0 +9091,Male,38,PhD,8,63,17,43,51,2.0,3,25,Urban,ML Engineer,144552,0 +9092,Male,37,Bachelors,7,76,64,59,64,0.0,6,42,Urban,Manager,52680,1 +9093,Male,32,Diploma,16,64,44,26,35,8.0,4,88,Urban,HR Executive,30176,0 +9094,Female,51,Bachelors,14,14,53,34,64,2.0,3,46,Semi-Urban,HR Executive,22046,0 +9095,Male,54,PhD,14,95,8,30,21,2.0,1,90,Rural,Manager,120549,0 +9096,Female,23,Bachelors,14,18,96,82,81,9.0,5,57,Rural,Manager,138307,1 +9097,Male,26,Bachelors,2,3,67,91,32,1.0,6,34,Rural,Manager,38679,0 +9098,Male,28,Bachelors,19,83,55,94,90,9.0,6,89,Urban,ML Engineer,146705,1 +9099,Female,36,Masters,18,4,44,14,46,2.0,3,62,Urban,Data Analyst,49981,0 +9100,Male,36,Diploma,18,6,44,4,45,0.0,3,24,Urban,HR Executive,89530,0 +9101,Male,49,Bachelors,8,93,27,58,62,0.0,2,57,Urban,Software Engineer,31955,1 +9102,Female,40,Diploma,2,96,41,31,49,4.0,3,82,Semi-Urban,HR Executive,131355,1 +9103,Male,36,Bachelors,2,75,95,66,66,2.0,3,44,Rural,ML Engineer,136464,1 +9104,Female,30,Bachelors,2,70,29,86,90,1.0,0,11,Urban,Software Engineer,67552,0 +9105,Male,43,Bachelors,1,24,27,63,7,1.0,3,91,Urban,ML Engineer,132926,0 +9106,Male,53,High School,1,79,39,17,46,5.0,6,9,Semi-Urban,HR Executive,114495,0 +9107,Male,50,Bachelors,5,99,18,51,13,3.0,5,73,Urban,ML Engineer,46319,1 +9108,Female,39,Bachelors,19,87,25,26,64,3.0,7,87,Urban,Manager,40181,0 +9109,Male,29,Bachelors,18,76,10,86,63,7.0,1,38,Urban,ML Engineer,80520,0 +9110,Female,53,Diploma,13,26,32,96,22,0.0,7,82,Urban,Software Engineer,42764,0 +9111,Female,45,PhD,18,68,9,0,74,9.0,5,45,Semi-Urban,Data Analyst,66785,0 +9112,Male,24,High School,13,6,52,15,62,1.0,3,21,Rural,Manager,45811,0 +9113,Male,57,High School,0,34,77,46,42,7.0,4,80,Urban,Manager,142010,1 +9114,Male,40,Bachelors,6,99,60,94,95,4.0,4,17,Rural,Manager,138959,1 +9115,Male,59,High School,9,40,20,71,3,9.0,7,4,Urban,HR Executive,106634,0 +9116,Male,27,High School,11,4,61,11,59,8.0,5,46,Urban,Manager,50493,0 +9117,Female,59,Bachelors,1,1,93,33,89,1.0,4,69,Urban,Manager,69156,0 +9118,Other,26,PhD,13,4,43,87,91,3.0,3,88,Urban,Data Analyst,103109,0 +9119,Female,27,Bachelors,9,16,56,76,20,5.0,1,80,Urban,ML Engineer,73231,0 +9120,Female,26,Bachelors,11,89,22,49,32,5.0,7,64,Rural,HR Executive,86416,0 +9121,Female,22,Bachelors,13,82,19,34,69,0.0,7,40,Urban,Manager,96838,0 +9122,Male,31,High School,0,13,11,65,25,0.0,4,84,Urban,Data Analyst,60444,0 +9123,Female,44,Bachelors,13,87,85,12,16,3.0,0,19,Urban,Software Engineer,23587,0 +9124,Female,26,PhD,17,31,81,20,59,6.0,1,34,Urban,Manager,128086,0 +9125,Male,44,Diploma,9,40,53,89,5,9.0,5,48,Urban,HR Executive,21605,0 +9126,Other,22,Diploma,12,32,90,14,58,5.0,5,20,Urban,ML Engineer,65403,0 +9127,Male,35,PhD,6,45,62,17,50,7.0,3,2,Rural,Software Engineer,33231,0 +9128,Female,27,Masters,10,61,25,26,35,4.0,0,71,Urban,ML Engineer,47396,0 +9129,Female,46,Bachelors,10,75,15,17,37,0.0,7,36,Urban,Software Engineer,20379,0 +9130,Other,53,Bachelors,13,5,51,69,12,6.0,2,56,Urban,HR Executive,62536,0 +9131,Male,54,High School,7,58,44,15,0,4.0,7,31,Rural,Data Analyst,76938,0 +9132,Female,31,High School,6,20,94,71,44,8.0,5,57,Urban,HR Executive,136300,1 +9133,Male,43,Masters,17,44,96,89,7,0.0,6,69,Urban,ML Engineer,133244,1 +9134,Male,45,Diploma,10,0,47,62,36,4.0,1,32,Rural,Software Engineer,49595,0 +9135,Female,32,High School,1,3,62,64,53,5.0,4,32,Urban,HR Executive,49259,0 +9136,Male,43,High School,9,92,23,86,41,8.0,1,1,Urban,ML Engineer,101520,0 +9137,Female,53,Bachelors,13,53,8,92,41,1.0,7,42,Semi-Urban,HR Executive,53609,0 +9138,Male,41,Bachelors,7,18,93,16,14,8.0,2,96,Rural,ML Engineer,108865,0 +9139,Male,29,Masters,8,99,75,0,93,4.0,1,27,Rural,Data Analyst,130589,0 +9140,Female,34,Diploma,6,76,30,39,87,2.0,0,76,Rural,HR Executive,106767,0 +9141,Male,47,Masters,16,91,98,75,84,4.0,3,87,Semi-Urban,Manager,73449,1 +9142,Male,29,Diploma,6,38,76,17,9,3.0,2,74,Rural,Data Analyst,56498,0 +9143,Other,47,Bachelors,10,85,56,8,95,6.0,1,57,Urban,Software Engineer,48816,0 +9144,Male,30,Bachelors,19,66,30,53,0,8.0,6,76,Semi-Urban,Manager,46519,0 +9145,Female,24,Bachelors,0,79,30,22,26,0.0,6,28,Urban,Manager,136931,0 +9146,Male,59,Bachelors,13,36,84,97,54,7.0,2,34,Urban,Software Engineer,108500,1 +9147,Male,22,Bachelors,7,37,51,70,12,6.0,6,45,Urban,Software Engineer,28202,0 +9148,Male,44,Diploma,12,25,5,59,66,5.0,3,21,Urban,Manager,84248,0 +9149,Male,56,Bachelors,13,47,2,77,51,6.0,2,33,Semi-Urban,Data Analyst,77636,0 +9150,Male,30,High School,15,31,66,36,2,0.0,5,43,Urban,HR Executive,131927,0 +9151,Male,57,Bachelors,19,48,5,99,73,9.0,6,34,Urban,Data Analyst,140296,0 +9152,Male,42,Diploma,18,11,83,1,66,3.0,0,81,Urban,Manager,57737,0 +9153,Male,39,Bachelors,13,53,3,63,37,8.0,1,61,Urban,Software Engineer,95037,0 +9154,Male,25,Bachelors,7,76,41,37,16,5.0,2,2,Urban,Software Engineer,33417,0 +9155,Male,49,Bachelors,15,51,29,0,15,9.0,2,45,Rural,Software Engineer,50557,0 +9156,Male,52,Masters,12,79,35,67,83,8.0,0,84,Rural,HR Executive,135984,1 +9157,Female,36,Bachelors,9,97,51,59,7,5.0,1,43,Rural,Software Engineer,77235,1 +9158,Female,23,Bachelors,4,50,1,17,54,0.0,5,6,Urban,Manager,79056,0 +9159,Female,53,Diploma,19,86,43,15,6,3.0,0,14,Semi-Urban,Data Analyst,60818,0 +9160,Male,31,Bachelors,9,33,20,29,67,5.0,2,95,Urban,HR Executive,78504,0 +9161,Female,29,High School,8,60,11,85,30,5.0,1,68,Urban,HR Executive,42862,0 +9162,Female,48,Masters,9,83,30,79,99,7.0,1,78,Rural,ML Engineer,132219,1 +9163,Female,49,Bachelors,16,16,67,68,91,9.0,0,55,Urban,HR Executive,32759,0 +9164,Male,49,Diploma,4,6,88,91,64,6.0,3,9,Urban,Data Analyst,20420,0 +9165,Other,59,Bachelors,12,60,40,61,78,7.0,5,1,Urban,ML Engineer,138298,0 +9166,Female,57,PhD,10,3,72,94,9,2.0,4,87,Urban,Software Engineer,41090,1 +9167,Female,56,PhD,11,43,24,47,58,5.0,7,98,Urban,HR Executive,93522,0 +9168,Male,36,High School,5,68,18,68,39,0.0,1,29,Urban,ML Engineer,68104,0 +9169,Male,57,Masters,15,11,3,69,43,7.0,2,89,Semi-Urban,ML Engineer,67184,0 +9170,Male,54,High School,0,89,17,43,98,8.0,4,28,Urban,Software Engineer,41669,0 +9171,Male,57,High School,7,27,10,84,38,5.0,4,71,Urban,Manager,88085,0 +9172,Female,49,Diploma,18,29,67,63,20,9.0,5,88,Semi-Urban,ML Engineer,46455,1 +9173,Male,43,Bachelors,6,18,63,10,52,4.0,4,13,Semi-Urban,Data Analyst,21668,0 +9174,Male,43,High School,7,49,78,80,54,7.0,0,86,Semi-Urban,Manager,86501,1 +9175,Male,56,Diploma,1,89,25,88,51,1.0,1,24,Urban,HR Executive,121737,0 +9176,Male,33,Masters,19,62,78,5,54,8.0,7,81,Rural,ML Engineer,118501,0 +9177,Male,35,Masters,5,68,5,86,84,6.0,2,65,Semi-Urban,Software Engineer,118305,0 +9178,Female,47,Diploma,10,83,64,59,30,0.0,6,88,Urban,Software Engineer,85223,1 +9179,Male,26,Masters,7,62,76,39,38,9.0,0,41,Urban,Manager,55319,0 +9180,Male,21,Bachelors,3,83,65,76,35,8.0,1,92,Semi-Urban,HR Executive,33882,1 +9181,Male,21,Masters,16,77,54,75,39,5.0,1,12,Semi-Urban,HR Executive,119757,0 +9182,Male,23,Bachelors,14,68,89,40,0,9.0,4,23,Urban,HR Executive,72915,0 +9183,Male,28,Masters,19,1,94,71,26,0.0,0,61,Urban,Data Analyst,146752,0 +9184,Female,51,High School,0,82,80,88,70,5.0,3,34,Urban,HR Executive,80098,1 +9185,Female,52,Diploma,19,25,75,56,8,6.0,0,79,Rural,HR Executive,120164,0 +9186,Female,47,Bachelors,19,70,19,76,82,8.0,6,49,Urban,Manager,105496,0 +9187,Female,36,Diploma,7,89,67,69,13,1.0,1,85,Semi-Urban,Data Analyst,56862,1 +9188,Male,36,Diploma,19,61,75,82,32,5.0,0,47,Rural,Manager,62516,1 +9189,Other,53,Bachelors,9,47,9,75,23,5.0,2,17,Semi-Urban,Software Engineer,22265,0 +9190,Female,36,Bachelors,3,48,98,1,3,6.0,6,88,Urban,Software Engineer,63938,0 +9191,Female,56,High School,0,26,41,95,17,9.0,5,2,Urban,Manager,138282,0 +9192,Male,27,Bachelors,11,80,77,35,97,7.0,1,68,Urban,Software Engineer,43470,1 +9193,Female,49,Bachelors,7,38,24,14,8,6.0,5,93,Urban,Manager,84206,0 +9194,Female,48,Diploma,19,64,47,44,49,1.0,2,76,Semi-Urban,HR Executive,117519,0 +9195,Female,59,Bachelors,14,47,68,86,20,0.0,2,93,Urban,HR Executive,109760,1 +9196,Male,36,Diploma,0,60,67,92,45,8.0,2,20,Rural,Manager,62593,1 +9197,Female,22,High School,8,9,92,61,8,1.0,0,56,Rural,HR Executive,42416,0 +9198,Other,49,Bachelors,11,72,63,79,75,6.0,0,40,Rural,ML Engineer,116804,1 +9199,Female,56,Diploma,2,63,14,87,25,5.0,7,99,Urban,Manager,66773,1 +9200,Male,25,High School,17,64,22,12,2,4.0,5,40,Rural,Manager,129029,0 +9201,Female,33,High School,2,21,61,4,42,4.0,7,55,Rural,Software Engineer,45828,0 +9202,Male,26,Bachelors,1,56,33,13,78,4.0,4,61,Semi-Urban,HR Executive,53614,0 +9203,Male,28,Diploma,13,61,25,88,34,3.0,7,32,Rural,ML Engineer,57067,0 +9204,Male,29,High School,14,90,31,10,76,8.0,7,50,Urban,Manager,116998,0 +9205,Female,37,Diploma,1,59,69,50,91,6.0,1,91,Rural,HR Executive,90081,1 +9206,Male,22,Masters,8,67,51,96,2,1.0,5,68,Rural,ML Engineer,51863,1 +9207,Male,55,High School,19,16,38,10,99,2.0,1,53,Urban,Data Analyst,23516,0 +9208,Female,30,Diploma,3,63,12,52,11,8.0,1,20,Urban,ML Engineer,129311,0 +9209,Female,54,Bachelors,12,69,7,23,59,4.0,3,71,Urban,ML Engineer,106315,0 +9210,Male,24,Bachelors,9,6,19,44,32,5.0,0,18,Urban,Data Analyst,45173,0 +9211,Female,55,PhD,11,13,70,58,20,6.0,4,26,Urban,Software Engineer,116642,0 +9212,Female,59,Diploma,17,42,82,59,98,8.0,6,91,Semi-Urban,HR Executive,148605,1 +9213,Male,44,Masters,13,5,5,73,32,6.0,2,7,Urban,Software Engineer,104898,0 +9214,Male,39,Bachelors,7,51,75,40,51,0.0,3,0,Urban,HR Executive,130418,0 +9215,Male,27,Masters,1,57,30,13,15,7.0,5,58,Semi-Urban,Data Analyst,29760,0 +9216,Male,50,High School,15,10,74,11,69,0.0,3,24,Urban,Software Engineer,142486,0 +9217,Male,43,Masters,9,18,59,0,24,7.0,6,50,Urban,ML Engineer,96785,0 +9218,Female,26,Diploma,4,68,13,40,65,9.0,4,61,Semi-Urban,ML Engineer,81970,0 +9219,Female,25,Bachelors,11,86,51,99,1,2.0,7,88,Rural,HR Executive,147027,1 +9220,Male,47,PhD,15,91,10,85,82,0.0,4,64,Rural,ML Engineer,40167,1 +9221,Male,42,Diploma,6,20,17,60,23,1.0,5,11,Rural,Data Analyst,138030,0 +9222,Male,33,Diploma,2,22,85,27,44,4.0,4,16,Urban,Software Engineer,95744,0 +9223,Male,31,Bachelors,0,39,0,82,11,7.0,5,94,Urban,Software Engineer,127332,0 +9224,Male,41,High School,14,80,25,27,56,8.0,2,38,Semi-Urban,Software Engineer,23880,0 +9225,Female,52,Masters,12,94,61,71,65,5.0,5,12,Rural,Data Analyst,54875,0 +9226,Female,26,Bachelors,15,28,50,42,30,1.0,1,67,Urban,Manager,53025,0 +9227,Male,32,Masters,12,21,93,73,96,6.0,3,49,Semi-Urban,ML Engineer,68894,1 +9228,Female,58,High School,2,25,1,8,84,3.0,5,41,Urban,Software Engineer,141118,0 +9229,Male,27,Diploma,6,99,92,10,49,0.0,6,99,Urban,Manager,125643,1 +9230,Female,31,Bachelors,15,69,60,55,64,4.0,2,78,Urban,Data Analyst,107801,1 +9231,Male,48,Bachelors,17,56,7,81,4,9.0,3,3,Rural,HR Executive,120708,0 +9232,Male,49,High School,4,21,40,48,84,6.0,1,89,Rural,Software Engineer,72849,0 +9233,Female,47,Diploma,4,42,1,69,65,4.0,4,18,Rural,Data Analyst,25993,0 +9234,Male,52,Masters,5,8,42,80,63,0.0,0,73,Urban,HR Executive,21585,0 +9235,Female,29,Bachelors,12,23,64,70,33,1.0,4,21,Rural,ML Engineer,70969,0 +9236,Male,40,PhD,3,79,64,15,84,8.0,6,4,Rural,Software Engineer,131963,0 +9237,Male,43,Bachelors,8,11,73,3,71,9.0,7,55,Urban,Data Analyst,32074,0 +9238,Male,57,High School,2,54,49,43,84,9.0,1,84,Urban,ML Engineer,147970,0 +9239,Male,52,Diploma,18,19,96,11,77,3.0,4,47,Semi-Urban,ML Engineer,119302,0 +9240,Female,22,High School,6,48,5,31,84,1.0,1,58,Urban,ML Engineer,38671,0 +9241,Male,29,Masters,17,6,6,83,1,0.0,1,93,Semi-Urban,Data Analyst,144976,0 +9242,Female,32,Bachelors,8,89,71,92,0,8.0,4,79,Semi-Urban,Manager,64556,1 +9243,Female,54,PhD,12,8,34,0,97,5.0,2,60,Semi-Urban,ML Engineer,57042,0 +9244,Female,39,Diploma,3,71,45,60,38,3.0,7,18,Urban,Software Engineer,119626,0 +9245,Male,47,Bachelors,12,77,17,11,11,1.0,3,66,Rural,Data Analyst,25266,0 +9246,Female,23,Masters,7,12,73,72,85,3.0,3,28,Urban,Manager,68967,0 +9247,Male,58,Bachelors,0,61,23,1,95,0.0,7,2,Rural,Software Engineer,143646,0 +9248,Male,39,Diploma,10,66,65,2,1,6.0,2,64,Urban,ML Engineer,83755,0 +9249,Male,21,High School,4,84,53,47,69,4.0,0,11,Rural,ML Engineer,88711,0 +9250,Male,51,Bachelors,13,93,59,88,6,6.0,5,30,Urban,ML Engineer,146142,1 +9251,Male,34,Diploma,9,11,8,76,45,6.0,7,43,Urban,Manager,138716,0 +9252,Female,53,Bachelors,12,66,31,64,73,2.0,7,16,Urban,Data Analyst,67683,0 +9253,Male,49,Diploma,4,93,17,59,4,8.0,3,13,Urban,Manager,149120,0 +9254,Male,31,High School,4,99,5,8,61,7.0,6,80,Urban,HR Executive,98009,0 +9255,Female,57,Bachelors,19,17,54,60,15,1.0,3,86,Urban,HR Executive,57591,0 +9256,Male,41,Masters,13,74,36,30,95,9.0,6,41,Semi-Urban,Software Engineer,131569,0 +9257,Male,26,Diploma,11,76,77,74,14,7.0,0,69,Rural,ML Engineer,129638,1 +9258,Male,39,Bachelors,0,76,35,3,78,8.0,2,0,Urban,HR Executive,115931,0 +9259,Female,34,High School,11,84,55,71,31,9.0,3,9,Urban,Manager,124831,0 +9260,Male,59,Bachelors,5,53,99,41,12,2.0,3,70,Urban,HR Executive,44316,1 +9261,Male,38,Masters,7,43,51,35,95,3.0,3,5,Semi-Urban,Data Analyst,98426,0 +9262,Male,22,Masters,7,30,11,72,52,1.0,7,12,Urban,Software Engineer,73097,0 +9263,Female,58,Masters,2,24,25,96,9,4.0,7,66,Urban,Software Engineer,61339,0 +9264,Female,40,Masters,6,31,74,9,3,5.0,6,59,Urban,Software Engineer,122242,0 +9265,Female,22,Masters,14,81,68,18,40,1.0,1,94,Urban,HR Executive,35490,1 +9266,Male,23,Masters,3,88,94,33,14,2.0,3,28,Rural,Data Analyst,40028,1 +9267,Male,59,Bachelors,9,28,33,49,69,1.0,1,60,Semi-Urban,HR Executive,86615,0 +9268,Male,38,Bachelors,7,41,56,21,28,7.0,5,58,Rural,Data Analyst,52599,0 +9269,Male,41,Bachelors,16,92,89,80,67,7.0,3,81,Urban,ML Engineer,57600,1 +9270,Male,50,Bachelors,16,54,39,28,20,0.0,7,80,Urban,Data Analyst,44492,0 +9271,Male,43,Bachelors,12,10,17,54,89,1.0,7,2,Urban,Software Engineer,94984,0 +9272,Male,29,Bachelors,5,33,79,48,46,4.0,3,28,Urban,Data Analyst,59377,0 +9273,Female,23,Masters,9,53,70,84,57,7.0,3,64,Urban,Data Analyst,48424,1 +9274,Male,46,High School,13,77,17,86,21,9.0,6,90,Semi-Urban,HR Executive,83912,1 +9275,Female,40,Bachelors,12,13,88,72,56,8.0,4,61,Urban,HR Executive,98407,0 +9276,Male,43,Bachelors,11,91,74,95,80,9.0,7,31,Urban,HR Executive,110872,1 +9277,Male,53,High School,9,34,9,2,64,9.0,6,7,Rural,HR Executive,119799,0 +9278,Male,57,Bachelors,9,6,28,23,88,0.0,7,56,Urban,Manager,117095,0 +9279,Male,43,Bachelors,17,33,16,95,74,4.0,1,76,Urban,Software Engineer,147673,0 +9280,Male,58,Bachelors,4,30,86,43,76,5.0,5,44,Semi-Urban,ML Engineer,100427,0 +9281,Male,57,Bachelors,16,6,95,25,61,9.0,6,34,Urban,Manager,91948,0 +9282,Female,25,Bachelors,3,49,83,67,12,0.0,3,45,Urban,Data Analyst,45444,1 +9283,Female,34,Bachelors,3,17,31,50,13,3.0,7,3,Urban,Manager,123037,0 +9284,Male,58,Bachelors,11,82,3,93,77,2.0,0,52,Urban,Manager,123575,0 +9285,Female,43,Bachelors,11,13,85,40,22,1.0,3,93,Urban,Software Engineer,90175,0 +9286,Female,59,Bachelors,15,13,5,56,52,8.0,2,57,Rural,Manager,142084,0 +9287,Female,32,Bachelors,18,34,30,72,11,6.0,4,52,Semi-Urban,ML Engineer,99567,0 +9288,Female,37,Diploma,16,85,36,19,85,8.0,5,25,Urban,Manager,110167,0 +9289,Male,33,Bachelors,14,1,91,37,90,1.0,7,25,Urban,ML Engineer,47581,0 +9290,Male,36,Bachelors,3,28,72,25,86,4.0,3,97,Rural,Software Engineer,124387,0 +9291,Male,47,Diploma,1,46,89,94,33,0.0,7,8,Rural,ML Engineer,88134,1 +9292,Male,44,Bachelors,14,29,21,85,25,3.0,1,8,Semi-Urban,Data Analyst,47215,0 +9293,Male,57,Masters,16,24,44,68,53,6.0,6,76,Urban,Manager,39395,0 +9294,Male,29,Bachelors,2,92,91,65,48,1.0,5,51,Urban,ML Engineer,109279,1 +9295,Female,37,Bachelors,12,18,98,58,7,4.0,7,88,Urban,Manager,104245,1 +9296,Female,43,Bachelors,11,46,43,58,11,6.0,2,43,Urban,Data Analyst,35984,0 +9297,Female,32,Diploma,13,3,38,44,46,9.0,2,57,Urban,HR Executive,72930,0 +9298,Female,24,Masters,17,81,55,46,16,3.0,7,82,Urban,Manager,66630,1 +9299,Female,25,High School,6,7,13,32,21,0.0,4,68,Urban,Software Engineer,110170,0 +9300,Male,51,High School,14,94,16,98,92,6.0,7,90,Urban,ML Engineer,78174,1 +9301,Male,27,Bachelors,1,38,48,99,17,3.0,0,74,Semi-Urban,HR Executive,64517,1 +9302,Male,31,Bachelors,10,93,29,57,32,0.0,7,12,Urban,Data Analyst,89475,0 +9303,Female,32,Masters,10,33,32,11,46,6.0,7,26,Urban,Data Analyst,92947,0 +9304,Male,58,Masters,16,56,61,96,92,9.0,1,60,Semi-Urban,ML Engineer,66398,1 +9305,Female,21,Bachelors,4,33,68,82,22,0.0,6,78,Urban,Manager,34280,1 +9306,Male,28,Bachelors,7,69,89,38,66,4.0,7,72,Urban,Manager,123086,1 +9307,Male,37,Bachelors,1,35,63,14,95,8.0,3,46,Urban,Data Analyst,49845,0 +9308,Female,41,High School,9,9,42,24,3,6.0,2,80,Urban,Data Analyst,22917,0 +9309,Male,24,Masters,18,86,77,41,84,8.0,6,29,Urban,Software Engineer,65554,0 +9310,Male,48,Diploma,1,88,65,97,99,4.0,6,16,Urban,Manager,83031,1 +9311,Male,57,Masters,3,66,65,4,33,5.0,5,49,Urban,Software Engineer,97226,0 +9312,Male,51,Masters,3,32,36,34,73,8.0,6,67,Urban,Data Analyst,46051,0 +9313,Female,42,Diploma,2,15,4,96,81,6.0,7,61,Urban,Software Engineer,136161,0 +9314,Male,29,High School,8,89,0,93,47,7.0,3,51,Urban,Data Analyst,32300,0 +9315,Male,46,Bachelors,11,8,47,14,61,2.0,4,95,Urban,HR Executive,62796,0 +9316,Male,53,High School,0,23,61,90,28,1.0,4,61,Rural,Manager,104569,1 +9317,Female,56,Bachelors,5,8,27,76,59,5.0,6,81,Urban,Data Analyst,105647,0 +9318,Male,57,High School,14,36,7,84,33,0.0,2,54,Semi-Urban,HR Executive,35796,0 +9319,Female,44,Masters,2,12,15,29,38,4.0,0,92,Urban,Data Analyst,122837,0 +9320,Female,24,Bachelors,9,50,91,57,74,5.0,6,40,Semi-Urban,Manager,28962,0 +9321,Male,29,Bachelors,5,49,56,59,76,8.0,2,43,Urban,Software Engineer,148449,0 +9322,Female,35,Bachelors,10,94,9,39,14,4.0,3,41,Rural,ML Engineer,115839,0 +9323,Female,53,Masters,3,25,55,15,14,6.0,4,47,Rural,Software Engineer,119405,0 +9324,Male,25,Bachelors,16,76,67,65,44,5.0,1,62,Urban,HR Executive,64593,1 +9325,Male,46,Bachelors,3,44,65,68,95,7.0,1,99,Urban,Data Analyst,33133,1 +9326,Female,23,Bachelors,7,85,22,57,22,1.0,6,52,Urban,Software Engineer,53005,0 +9327,Female,52,Bachelors,11,33,94,84,67,2.0,2,1,Urban,Software Engineer,77586,0 +9328,Male,41,High School,14,18,51,12,21,6.0,0,46,Urban,Software Engineer,124033,0 +9329,Male,21,Diploma,19,87,7,99,73,9.0,0,29,Urban,Data Analyst,23797,0 +9330,Female,46,High School,13,11,98,54,88,7.0,5,89,Urban,Manager,53302,1 +9331,Female,47,High School,15,2,44,43,29,3.0,6,11,Rural,HR Executive,43318,0 +9332,Female,56,Diploma,2,41,27,94,98,6.0,2,72,Urban,ML Engineer,45304,0 +9333,Male,53,Masters,7,13,37,30,20,3.0,0,10,Urban,ML Engineer,29274,0 +9334,Female,41,Masters,8,27,2,14,94,9.0,0,70,Urban,HR Executive,56656,0 +9335,Male,50,Diploma,7,85,93,20,1,5.0,7,69,Urban,ML Engineer,21615,1 +9336,Male,41,Bachelors,0,40,69,49,76,9.0,3,1,Semi-Urban,Manager,126374,0 +9337,Female,36,Diploma,2,98,75,6,17,7.0,3,44,Semi-Urban,Software Engineer,24005,0 +9338,Other,57,Bachelors,0,73,56,54,45,8.0,7,72,Urban,ML Engineer,105646,1 +9339,Male,29,Masters,6,77,45,24,78,5.0,3,17,Urban,Software Engineer,120921,0 +9340,Male,49,Masters,16,20,20,58,61,7.0,3,82,Rural,Software Engineer,29720,0 +9341,Female,40,Bachelors,19,98,60,60,59,7.0,7,57,Rural,Manager,143612,1 +9342,Male,28,Diploma,0,61,61,85,81,5.0,3,64,Urban,HR Executive,22184,1 +9343,Female,34,Bachelors,4,5,65,66,15,1.0,7,6,Urban,ML Engineer,83451,0 +9344,Female,58,PhD,8,14,9,33,26,1.0,0,56,Urban,Software Engineer,24269,0 +9345,Male,27,Diploma,3,77,85,64,75,6.0,4,57,Urban,HR Executive,45983,1 +9346,Other,37,Diploma,2,43,77,14,55,9.0,4,47,Semi-Urban,Data Analyst,119666,0 +9347,Female,30,Diploma,11,15,88,50,46,9.0,6,69,Rural,Manager,116508,0 +9348,Female,57,Masters,5,89,94,61,18,4.0,1,28,Urban,HR Executive,67414,1 +9349,Female,45,Diploma,14,53,61,99,46,7.0,5,70,Semi-Urban,Software Engineer,85807,1 +9350,Female,43,Bachelors,8,73,29,65,10,1.0,6,14,Urban,Manager,117158,0 +9351,Male,56,Bachelors,18,25,87,15,71,1.0,7,89,Urban,HR Executive,142537,0 +9352,Male,38,Bachelors,2,35,1,16,13,9.0,6,53,Semi-Urban,Manager,128483,0 +9353,Female,50,Bachelors,17,39,90,23,93,7.0,4,93,Urban,Manager,118042,1 +9354,Male,59,Bachelors,0,18,46,80,29,6.0,0,92,Semi-Urban,ML Engineer,137993,1 +9355,Male,26,Diploma,14,12,53,17,47,3.0,2,62,Semi-Urban,ML Engineer,61791,0 +9356,Female,35,PhD,2,89,19,33,59,9.0,3,7,Rural,HR Executive,144145,0 +9357,Female,44,Bachelors,15,5,65,58,37,8.0,7,62,Urban,Software Engineer,130576,0 +9358,Male,49,Masters,13,52,3,41,93,7.0,1,71,Rural,Data Analyst,95699,0 +9359,Female,36,Bachelors,7,91,70,88,73,8.0,7,59,Urban,HR Executive,144803,1 +9360,Female,29,High School,16,64,41,47,84,5.0,7,3,Urban,Manager,49335,0 +9361,Male,26,Bachelors,8,40,34,61,75,8.0,2,87,Urban,ML Engineer,82040,0 +9362,Female,34,Masters,0,89,94,37,12,0.0,6,32,Rural,ML Engineer,75726,1 +9363,Male,37,Masters,7,38,70,4,59,2.0,6,42,Urban,HR Executive,67313,0 +9364,Male,31,Bachelors,4,30,38,20,86,1.0,3,27,Semi-Urban,Data Analyst,113518,0 +9365,Male,48,Bachelors,5,38,9,87,19,9.0,1,76,Urban,ML Engineer,29378,0 +9366,Male,27,High School,8,72,14,83,45,5.0,0,24,Urban,HR Executive,64150,0 +9367,Male,53,Bachelors,10,15,26,81,60,3.0,2,4,Urban,Software Engineer,62396,0 +9368,Female,49,Bachelors,11,62,31,57,22,6.0,2,42,Urban,Software Engineer,56348,0 +9369,Female,49,High School,3,51,36,81,63,5.0,2,35,Rural,HR Executive,21054,0 +9370,Male,22,Bachelors,17,44,12,85,84,1.0,4,33,Urban,Manager,93462,0 +9371,Female,50,Bachelors,1,41,61,50,59,7.0,5,67,Urban,HR Executive,59490,0 +9372,Male,39,Bachelors,19,76,40,62,34,2.0,0,27,Urban,Manager,56263,0 +9373,Male,30,High School,12,70,96,8,19,0.0,6,7,Urban,HR Executive,53807,0 +9374,Female,21,Bachelors,14,34,57,90,0,6.0,6,33,Semi-Urban,HR Executive,98128,0 +9375,Male,55,Diploma,12,88,20,47,61,9.0,1,49,Rural,Data Analyst,72779,0 +9376,Male,37,Bachelors,7,55,4,7,63,2.0,1,21,Rural,ML Engineer,120767,0 +9377,Female,54,Diploma,18,12,13,28,54,3.0,5,43,Urban,HR Executive,128824,0 +9378,Male,54,PhD,6,71,99,50,52,0.0,3,60,Urban,Software Engineer,89324,1 +9379,Female,57,Diploma,12,15,49,97,60,7.0,1,80,Rural,ML Engineer,35948,1 +9380,Male,36,Diploma,19,20,55,11,9,0.0,3,65,Urban,Manager,49273,0 +9381,Male,25,PhD,1,93,25,13,68,6.0,2,56,Rural,Data Analyst,109449,0 +9382,Male,33,Masters,17,80,96,75,1,1.0,5,61,Urban,HR Executive,35060,1 +9383,Male,21,High School,15,49,19,95,83,6.0,0,51,Semi-Urban,HR Executive,35105,0 +9384,Male,36,Bachelors,9,46,76,87,97,1.0,6,34,Urban,Data Analyst,81415,1 +9385,Male,28,Bachelors,16,69,79,6,66,1.0,6,60,Rural,Manager,114394,0 +9386,Female,26,PhD,0,95,96,61,41,3.0,3,29,Urban,Data Analyst,107468,1 +9387,Female,33,Bachelors,9,79,99,16,90,8.0,3,89,Urban,Data Analyst,65994,1 +9388,Male,29,Diploma,13,88,73,76,63,7.0,2,71,Semi-Urban,Manager,33825,1 +9389,Male,59,Bachelors,5,92,19,60,96,2.0,3,88,Semi-Urban,ML Engineer,112619,1 +9390,Male,54,Bachelors,0,31,24,84,7,1.0,6,26,Urban,Software Engineer,34649,0 +9391,Female,29,Bachelors,3,25,20,91,98,0.0,7,7,Semi-Urban,ML Engineer,38621,0 +9392,Other,22,Masters,1,73,37,13,49,0.0,3,6,Urban,Manager,50916,0 +9393,Male,32,Diploma,18,53,18,82,45,4.0,6,22,Urban,Manager,148600,0 +9394,Female,25,Bachelors,18,59,74,31,45,0.0,7,99,Semi-Urban,Manager,123066,1 +9395,Male,43,Bachelors,17,27,70,6,88,3.0,2,96,Urban,Data Analyst,142182,0 +9396,Male,28,Bachelors,15,37,28,53,52,1.0,7,28,Rural,Manager,38058,0 +9397,Male,50,Masters,11,12,11,11,90,9.0,0,2,Urban,ML Engineer,64201,0 +9398,Male,32,Diploma,8,74,1,42,74,4.0,6,69,Urban,ML Engineer,62332,0 +9399,Male,23,High School,19,55,80,87,80,6.0,2,90,Urban,Manager,31045,1 +9400,Male,50,Bachelors,2,48,18,42,15,2.0,1,46,Urban,Software Engineer,35522,0 +9401,Female,40,Diploma,19,60,77,86,49,2.0,2,66,Rural,HR Executive,116786,1 +9402,Male,59,Masters,19,86,71,76,27,3.0,0,19,Urban,Data Analyst,37050,1 +9403,Male,52,Masters,16,22,53,4,8,5.0,1,96,Rural,ML Engineer,31563,0 +9404,Male,59,Bachelors,2,51,79,57,85,9.0,3,53,Urban,ML Engineer,41606,1 +9405,Male,45,Bachelors,15,28,17,19,87,3.0,4,13,Urban,ML Engineer,111701,0 +9406,Male,54,High School,16,38,53,67,50,7.0,5,36,Semi-Urban,Data Analyst,78334,0 +9407,Male,34,Masters,18,29,83,77,90,7.0,3,73,Urban,Manager,118011,1 +9408,Male,56,Diploma,12,53,71,37,83,8.0,1,16,Urban,HR Executive,119761,0 +9409,Male,52,Bachelors,9,8,63,2,98,5.0,0,2,Urban,ML Engineer,143295,0 +9410,Male,58,Bachelors,0,69,54,48,1,0.0,5,99,Urban,ML Engineer,147915,1 +9411,Male,33,Bachelors,15,50,84,47,18,5.0,5,72,Urban,Software Engineer,126121,1 +9412,Female,32,Diploma,16,19,61,15,77,2.0,4,35,Urban,ML Engineer,109361,0 +9413,Female,53,High School,4,92,30,82,57,4.0,7,48,Urban,HR Executive,92514,1 +9414,Male,53,Bachelors,19,8,65,31,79,6.0,1,26,Urban,ML Engineer,91647,0 +9415,Male,57,Bachelors,16,0,15,74,40,8.0,7,62,Urban,Data Analyst,36705,0 +9416,Male,24,High School,4,65,93,33,53,1.0,3,16,Urban,Software Engineer,89241,0 +9417,Male,36,High School,3,73,35,8,51,1.0,7,56,Urban,Manager,129158,0 +9418,Male,38,Diploma,16,12,37,62,19,8.0,2,55,Urban,Software Engineer,102839,0 +9419,Male,48,Bachelors,15,34,14,0,95,6.0,2,62,Urban,Data Analyst,36769,0 +9420,Male,25,Bachelors,19,18,17,43,88,4.0,5,16,Semi-Urban,Software Engineer,126389,0 +9421,Female,28,Diploma,5,19,74,49,57,3.0,4,19,Urban,Software Engineer,147819,0 +9422,Male,58,High School,3,82,34,43,87,1.0,5,0,Rural,Data Analyst,73723,0 +9423,Male,37,Bachelors,8,9,81,67,47,5.0,7,46,Urban,Data Analyst,21043,0 +9424,Male,39,Bachelors,14,43,76,4,75,4.0,7,66,Urban,Manager,87430,0 +9425,Female,53,Bachelors,15,60,46,69,93,0.0,2,42,Urban,Software Engineer,128153,0 +9426,Female,42,Bachelors,8,21,58,9,43,6.0,3,74,Urban,Software Engineer,64455,0 +9427,Male,46,Bachelors,17,67,34,70,70,8.0,5,81,Urban,ML Engineer,93277,1 +9428,Female,35,Bachelors,0,19,34,83,45,6.0,5,67,Semi-Urban,ML Engineer,36255,0 +9429,Male,53,Bachelors,6,16,18,70,82,3.0,3,93,Urban,Manager,29799,0 +9430,Female,30,High School,4,48,44,8,27,7.0,7,7,Semi-Urban,Data Analyst,68700,0 +9431,Female,25,Bachelors,4,84,96,79,56,1.0,1,66,Semi-Urban,Software Engineer,131982,1 +9432,Male,36,Bachelors,15,12,22,11,51,0.0,2,25,Urban,Software Engineer,145896,0 +9433,Female,29,Bachelors,13,61,38,72,96,4.0,1,44,Urban,HR Executive,50760,0 +9434,Male,50,Masters,3,23,5,80,9,9.0,1,20,Urban,HR Executive,127634,0 +9435,Male,35,High School,10,34,97,80,1,9.0,3,25,Urban,ML Engineer,108528,1 +9436,Male,58,Bachelors,3,1,60,18,38,8.0,1,85,Urban,ML Engineer,146450,0 +9437,Female,42,Bachelors,18,87,62,74,26,0.0,5,36,Rural,HR Executive,106405,1 +9438,Male,23,Masters,15,0,3,53,8,0.0,7,11,Urban,ML Engineer,23571,0 +9439,Male,38,Diploma,19,90,29,14,13,3.0,5,46,Rural,Data Analyst,62026,0 +9440,Female,42,Bachelors,7,95,11,6,26,6.0,0,3,Urban,HR Executive,144406,0 +9441,Male,52,Bachelors,11,19,72,91,5,2.0,3,39,Urban,Software Engineer,146722,0 +9442,Male,56,Bachelors,14,43,67,85,86,2.0,2,64,Rural,Software Engineer,81822,1 +9443,Male,25,Bachelors,19,18,64,15,42,7.0,4,70,Semi-Urban,Data Analyst,108992,0 +9444,Male,21,Bachelors,10,30,61,97,69,7.0,7,60,Semi-Urban,ML Engineer,83487,1 +9445,Male,48,Bachelors,8,57,23,66,12,0.0,6,82,Rural,ML Engineer,145353,0 +9446,Male,26,Bachelors,11,47,49,92,7,2.0,0,58,Rural,Software Engineer,98426,1 +9447,Other,43,Bachelors,11,1,70,39,97,2.0,3,47,Rural,Software Engineer,135588,0 +9448,Female,43,High School,11,71,77,75,62,6.0,3,53,Urban,HR Executive,137799,1 +9449,Male,21,Diploma,7,43,84,37,93,7.0,6,66,Urban,Software Engineer,111300,0 +9450,Male,35,Bachelors,15,27,28,10,87,5.0,2,1,Semi-Urban,Data Analyst,134646,0 +9451,Male,29,PhD,8,87,40,5,51,1.0,0,91,Urban,HR Executive,102896,0 +9452,Female,34,PhD,3,10,68,81,84,8.0,2,69,Rural,Software Engineer,121909,0 +9453,Male,46,Masters,11,69,69,33,75,2.0,7,38,Urban,Software Engineer,42681,0 +9454,Male,37,PhD,13,17,61,79,66,3.0,4,8,Urban,Manager,88769,0 +9455,Female,40,Bachelors,13,40,28,99,17,2.0,2,6,Semi-Urban,Data Analyst,109930,0 +9456,Male,58,Diploma,1,42,61,48,50,6.0,3,23,Semi-Urban,Data Analyst,123974,0 +9457,Male,57,Bachelors,2,75,30,18,53,4.0,2,48,Semi-Urban,ML Engineer,132522,0 +9458,Female,27,Diploma,6,75,2,0,16,6.0,1,68,Urban,Software Engineer,26103,0 +9459,Female,48,High School,2,3,63,16,94,4.0,3,21,Urban,HR Executive,95113,0 +9460,Male,51,Masters,4,44,68,28,89,7.0,4,78,Rural,Data Analyst,91917,0 +9461,Female,56,High School,5,98,60,81,50,9.0,2,68,Urban,Manager,93345,1 +9462,Male,23,High School,16,69,45,97,71,9.0,1,41,Semi-Urban,Manager,97005,1 +9463,Female,54,Diploma,9,34,65,40,63,7.0,2,21,Rural,HR Executive,108344,0 +9464,Male,25,Masters,8,34,49,73,38,1.0,1,57,Semi-Urban,ML Engineer,110089,0 +9465,Female,50,Masters,2,89,16,25,83,2.0,1,27,Urban,Data Analyst,120721,0 +9466,Other,28,Bachelors,11,54,14,7,67,0.0,4,17,Rural,ML Engineer,70653,0 +9467,Female,27,Bachelors,2,8,85,82,79,9.0,1,40,Rural,HR Executive,84731,0 +9468,Female,34,Diploma,14,96,83,14,1,5.0,7,12,Rural,HR Executive,32728,0 +9469,Male,37,High School,3,35,86,77,71,5.0,6,34,Rural,Data Analyst,85486,0 +9470,Male,35,Masters,0,34,23,61,58,9.0,3,16,Semi-Urban,Manager,75195,0 +9471,Male,27,Diploma,10,65,80,96,47,9.0,4,73,Semi-Urban,Data Analyst,76393,1 +9472,Female,29,Diploma,10,6,22,2,23,8.0,0,27,Semi-Urban,ML Engineer,48406,0 +9473,Female,25,Bachelors,13,38,70,44,17,6.0,1,5,Urban,Data Analyst,42609,0 +9474,Male,54,High School,8,44,30,90,42,9.0,5,38,Urban,ML Engineer,91455,0 +9475,Female,51,Masters,10,8,12,77,26,2.0,0,63,Semi-Urban,Manager,34439,0 +9476,Female,57,Diploma,4,90,71,71,87,2.0,5,60,Urban,Software Engineer,56582,1 +9477,Other,43,Bachelors,1,86,57,23,32,8.0,7,19,Urban,Manager,22755,0 +9478,Female,56,Diploma,1,61,18,66,95,3.0,0,76,Urban,Manager,26071,0 +9479,Male,51,Bachelors,6,44,28,12,61,5.0,2,93,Urban,HR Executive,130875,0 +9480,Male,40,Diploma,9,87,27,69,53,9.0,3,93,Urban,ML Engineer,78347,1 +9481,Male,40,Diploma,12,5,39,8,71,6.0,6,58,Urban,Data Analyst,73940,0 +9482,Male,27,Diploma,16,88,13,32,57,4.0,3,36,Urban,Manager,76653,0 +9483,Female,50,PhD,11,15,47,91,94,6.0,1,6,Urban,Manager,123635,0 +9484,Female,31,Diploma,6,55,99,86,81,2.0,4,58,Urban,HR Executive,124267,1 +9485,Female,54,High School,5,36,47,99,0,6.0,2,11,Urban,Data Analyst,25457,0 +9486,Female,57,Masters,6,92,80,16,3,4.0,6,54,Semi-Urban,Software Engineer,42833,1 +9487,Male,21,Masters,10,18,3,26,57,8.0,4,22,Urban,Software Engineer,35778,0 +9488,Male,58,Bachelors,0,94,51,95,49,5.0,4,7,Urban,HR Executive,80103,1 +9489,Male,53,Bachelors,3,29,87,44,67,2.0,5,47,Semi-Urban,HR Executive,113719,0 +9490,Male,40,Bachelors,14,0,53,40,42,0.0,1,57,Urban,Software Engineer,71240,0 +9491,Male,31,High School,16,71,55,13,27,7.0,2,57,Urban,ML Engineer,107562,0 +9492,Male,22,PhD,5,2,9,40,50,7.0,4,66,Semi-Urban,Software Engineer,106939,0 +9493,Male,24,Bachelors,9,31,11,64,35,4.0,5,44,Semi-Urban,Software Engineer,128327,0 +9494,Male,54,Masters,15,94,57,40,88,7.0,3,96,Rural,Manager,135234,1 +9495,Female,58,Diploma,9,73,54,73,4,4.0,2,17,Semi-Urban,HR Executive,123082,0 +9496,Male,42,Bachelors,14,46,6,49,83,1.0,0,42,Semi-Urban,Manager,74003,0 +9497,Male,52,Diploma,2,64,65,10,13,3.0,3,49,Urban,HR Executive,124165,0 +9498,Male,52,Bachelors,0,59,14,7,51,7.0,3,67,Urban,Manager,38926,0 +9499,Other,42,Masters,4,6,72,29,91,2.0,3,36,Urban,HR Executive,69503,0 +9500,Male,25,Bachelors,4,63,21,66,46,2.0,7,23,Urban,ML Engineer,73336,0 +9501,Male,25,PhD,15,30,1,24,21,3.0,4,78,Urban,HR Executive,106976,0 +9502,Female,48,PhD,16,13,19,23,21,7.0,2,21,Rural,Software Engineer,67260,0 +9503,Male,34,Diploma,14,11,26,7,15,1.0,7,16,Urban,HR Executive,42597,0 +9504,Female,25,Masters,13,31,56,59,78,6.0,6,62,Semi-Urban,ML Engineer,34220,0 +9505,Male,41,PhD,1,54,55,10,15,7.0,5,89,Urban,Software Engineer,82307,0 +9506,Male,23,High School,8,46,55,22,31,8.0,5,54,Rural,HR Executive,125418,0 +9507,Male,32,Masters,6,73,30,56,98,4.0,5,89,Urban,Software Engineer,82952,1 +9508,Female,53,Bachelors,15,14,8,14,86,2.0,6,0,Urban,Data Analyst,91816,0 +9509,Male,39,Diploma,18,56,54,27,84,5.0,6,74,Rural,Manager,120910,0 +9510,Male,27,High School,2,16,56,39,71,1.0,1,61,Urban,ML Engineer,136599,0 +9511,Male,32,High School,3,97,69,18,94,7.0,1,4,Urban,Software Engineer,44985,0 +9512,Male,31,High School,3,0,19,38,50,7.0,1,88,Semi-Urban,ML Engineer,97885,0 +9513,Male,35,Masters,10,32,90,7,52,3.0,3,6,Semi-Urban,Data Analyst,98830,0 +9514,Female,57,Bachelors,4,85,18,19,34,4.0,0,81,Urban,ML Engineer,54177,0 +9515,Female,42,Diploma,4,25,0,76,60,4.0,1,86,Urban,Manager,49449,0 +9516,Male,51,Bachelors,6,41,88,66,48,9.0,2,52,Semi-Urban,Manager,23510,1 +9517,Male,23,High School,17,74,57,15,54,0.0,7,95,Semi-Urban,Manager,65353,1 +9518,Female,25,Diploma,19,79,75,23,65,3.0,3,20,Urban,Software Engineer,28916,0 +9519,Male,53,Bachelors,2,11,54,16,45,0.0,4,51,Rural,Software Engineer,72618,0 +9520,Male,34,High School,19,0,66,80,75,9.0,4,46,Rural,Data Analyst,47237,0 +9521,Male,31,Bachelors,12,89,81,53,97,2.0,0,1,Semi-Urban,ML Engineer,22964,0 +9522,Female,40,Diploma,12,15,30,66,32,3.0,1,19,Rural,Software Engineer,104736,0 +9523,Female,51,Bachelors,2,42,39,40,3,4.0,4,50,Semi-Urban,Data Analyst,41787,0 +9524,Female,36,PhD,1,8,1,28,45,5.0,2,30,Rural,Software Engineer,122620,0 +9525,Male,29,High School,15,61,67,86,23,3.0,2,72,Urban,Software Engineer,39247,1 +9526,Male,25,Masters,2,59,30,65,66,4.0,0,93,Rural,HR Executive,138922,1 +9527,Female,38,Diploma,7,83,33,6,14,6.0,4,52,Rural,Manager,69335,0 +9528,Male,40,Bachelors,15,22,63,42,99,0.0,0,87,Urban,Software Engineer,47325,0 +9529,Other,48,Masters,1,18,1,96,29,5.0,6,5,Semi-Urban,HR Executive,29887,0 +9530,Female,39,Diploma,2,64,68,45,21,4.0,1,25,Rural,Software Engineer,62384,0 +9531,Male,33,High School,2,70,14,79,3,8.0,2,46,Urban,ML Engineer,51390,0 +9532,Female,38,Bachelors,3,58,94,96,10,1.0,5,83,Urban,Manager,141929,1 +9533,Male,38,Diploma,8,15,44,78,31,7.0,2,90,Rural,ML Engineer,116051,0 +9534,Female,33,High School,15,81,17,8,8,2.0,0,65,Urban,ML Engineer,82539,0 +9535,Male,31,Masters,13,1,11,74,60,1.0,5,84,Semi-Urban,ML Engineer,120215,0 +9536,Male,25,Diploma,16,42,12,41,8,0.0,7,59,Semi-Urban,Data Analyst,142284,0 +9537,Female,56,Bachelors,2,86,43,27,45,5.0,7,77,Urban,Software Engineer,39317,0 +9538,Female,32,Diploma,0,76,27,61,17,6.0,6,11,Urban,HR Executive,38666,0 +9539,Male,39,Bachelors,6,1,25,32,79,2.0,2,47,Semi-Urban,Software Engineer,48180,0 +9540,Male,41,Diploma,13,72,22,94,88,0.0,5,1,Urban,Manager,41394,0 +9541,Male,25,Masters,16,55,87,32,38,5.0,4,56,Semi-Urban,HR Executive,33405,0 +9542,Male,53,Masters,19,59,10,85,75,0.0,0,97,Urban,ML Engineer,47782,1 +9543,Male,21,PhD,12,58,53,87,48,8.0,3,99,Semi-Urban,HR Executive,82296,1 +9544,Male,31,Bachelors,9,66,49,7,17,9.0,3,41,Rural,ML Engineer,84467,0 +9545,Male,55,Masters,10,75,49,97,44,8.0,3,26,Urban,HR Executive,81011,1 +9546,Male,25,Bachelors,1,6,88,78,46,3.0,2,94,Semi-Urban,Data Analyst,109457,1 +9547,Male,45,High School,7,32,35,12,19,1.0,4,85,Semi-Urban,Data Analyst,46330,0 +9548,Male,31,High School,1,27,52,14,39,6.0,6,52,Urban,ML Engineer,125843,0 +9549,Male,42,High School,12,63,98,61,66,6.0,3,34,Semi-Urban,Data Analyst,104396,1 +9550,Other,26,Bachelors,3,76,7,12,0,0.0,6,72,Semi-Urban,ML Engineer,111508,0 +9551,Male,21,Masters,6,75,79,23,29,0.0,5,92,Rural,ML Engineer,149607,1 +9552,Female,33,PhD,1,74,79,64,31,0.0,6,62,Urban,HR Executive,50334,1 +9553,Female,39,Bachelors,9,41,50,96,46,1.0,3,68,Urban,HR Executive,31228,1 +9554,Female,42,Bachelors,8,51,73,29,54,6.0,4,17,Rural,Software Engineer,124518,0 +9555,Female,49,Diploma,14,86,1,84,47,2.0,3,7,Urban,HR Executive,21019,0 +9556,Female,50,Bachelors,4,55,35,50,90,6.0,4,32,Rural,Software Engineer,58648,0 +9557,Male,23,Bachelors,16,68,10,6,50,2.0,2,40,Semi-Urban,HR Executive,149966,0 +9558,Male,27,Masters,15,63,11,57,20,9.0,6,15,Urban,Data Analyst,29511,0 +9559,Female,49,PhD,16,86,21,78,84,7.0,3,55,Urban,Manager,80199,0 +9560,Male,26,Bachelors,18,12,36,52,85,8.0,2,51,Rural,Data Analyst,49161,0 +9561,Female,30,Bachelors,12,58,19,67,81,2.0,5,0,Urban,ML Engineer,92703,0 +9562,Male,51,High School,0,65,74,31,59,9.0,0,88,Semi-Urban,Software Engineer,32809,1 +9563,Female,28,Masters,13,34,71,25,93,5.0,3,17,Urban,HR Executive,90055,0 +9564,Male,26,Diploma,1,28,66,21,30,1.0,1,49,Urban,Software Engineer,119281,0 +9565,Male,27,Masters,10,78,4,93,90,4.0,1,29,Urban,Manager,126895,0 +9566,Male,26,Bachelors,2,16,89,45,97,3.0,4,73,Urban,HR Executive,50599,0 +9567,Female,39,Bachelors,1,25,34,58,70,3.0,3,49,Urban,HR Executive,41530,0 +9568,Female,47,Masters,14,32,0,49,18,8.0,1,98,Rural,Software Engineer,136285,0 +9569,Male,22,Bachelors,0,47,80,42,93,1.0,3,72,Urban,Data Analyst,118796,1 +9570,Female,42,Diploma,11,40,67,7,15,0.0,7,36,Rural,ML Engineer,88176,0 +9571,Male,59,High School,15,54,26,1,15,8.0,7,59,Urban,Software Engineer,142267,0 +9572,Male,56,High School,17,40,13,84,29,8.0,7,41,Semi-Urban,Software Engineer,75317,0 +9573,Male,53,Bachelors,3,25,2,97,11,2.0,2,63,Rural,ML Engineer,56043,0 +9574,Male,32,Bachelors,16,76,35,88,22,4.0,4,45,Urban,Data Analyst,149970,1 +9575,Male,49,Masters,2,4,47,0,37,2.0,7,86,Urban,Data Analyst,128583,0 +9576,Male,29,Bachelors,4,78,93,41,37,1.0,5,57,Urban,Data Analyst,131523,1 +9577,Female,43,Diploma,15,66,43,63,72,4.0,6,0,Urban,HR Executive,81462,0 +9578,Female,46,Bachelors,11,16,36,78,6,8.0,7,13,Rural,ML Engineer,81161,0 +9579,Male,48,Bachelors,15,74,69,86,49,1.0,0,34,Urban,Data Analyst,37841,1 +9580,Male,28,Bachelors,7,12,79,89,57,0.0,5,10,Urban,Data Analyst,24815,0 +9581,Male,31,Diploma,4,37,60,41,58,9.0,4,15,Rural,ML Engineer,129527,0 +9582,Male,31,Diploma,3,91,85,24,12,2.0,6,90,Rural,Manager,58037,1 +9583,Male,51,Bachelors,9,15,9,11,63,3.0,6,19,Semi-Urban,Data Analyst,83515,0 +9584,Male,33,Masters,8,95,16,40,24,4.0,5,54,Semi-Urban,Data Analyst,105594,0 +9585,Female,36,Masters,4,17,97,58,33,6.0,1,18,Urban,Manager,32056,0 +9586,Female,31,High School,2,80,53,43,57,0.0,0,35,Urban,Manager,20309,0 +9587,Male,58,Diploma,7,67,88,7,9,3.0,0,59,Urban,Data Analyst,32826,0 +9588,Male,53,Diploma,13,77,86,39,87,3.0,5,12,Semi-Urban,Manager,94446,0 +9589,Male,55,Diploma,13,17,83,64,77,7.0,5,53,Rural,Software Engineer,147869,0 +9590,Female,38,PhD,8,40,10,45,80,9.0,2,16,Urban,Software Engineer,136012,0 +9591,Male,51,High School,11,96,54,54,87,5.0,5,84,Semi-Urban,Data Analyst,132605,1 +9592,Male,51,Diploma,14,55,2,56,33,4.0,7,25,Urban,Manager,100380,0 +9593,Female,31,Bachelors,7,62,51,56,66,4.0,6,40,Urban,Manager,133823,0 +9594,Male,58,PhD,19,7,3,75,45,2.0,3,82,Urban,Manager,23148,0 +9595,Male,27,Masters,10,81,89,27,66,6.0,2,86,Urban,Software Engineer,101507,1 +9596,Male,50,Masters,14,74,97,92,88,9.0,1,5,Urban,Data Analyst,123125,1 +9597,Male,38,High School,10,93,30,13,49,4.0,3,74,Semi-Urban,Data Analyst,44572,0 +9598,Male,58,Bachelors,17,41,19,23,86,4.0,4,56,Urban,Manager,60609,0 +9599,Male,39,Diploma,2,16,61,25,61,4.0,4,74,Urban,Data Analyst,118326,0 +9600,Male,37,Diploma,3,75,70,86,4,3.0,3,64,Urban,Manager,42694,1 +9601,Male,46,Bachelors,4,10,57,53,95,5.0,4,94,Urban,Software Engineer,57384,0 +9602,Female,40,PhD,9,3,57,86,30,3.0,7,67,Semi-Urban,Software Engineer,56794,0 +9603,Male,23,Bachelors,8,85,5,32,89,5.0,4,42,Semi-Urban,Manager,61998,0 +9604,Male,29,Masters,17,62,91,63,31,5.0,6,47,Urban,HR Executive,24312,1 +9605,Female,42,Masters,12,62,4,98,87,2.0,4,21,Rural,Manager,129993,0 +9606,Female,54,Masters,9,48,98,64,20,0.0,0,14,Rural,ML Engineer,146486,0 +9607,Female,54,Masters,19,16,98,40,21,9.0,7,41,Rural,HR Executive,79386,0 +9608,Male,39,Diploma,16,0,71,77,98,3.0,1,72,Rural,ML Engineer,60517,0 +9609,Male,58,High School,10,97,39,61,85,8.0,1,84,Urban,Manager,22989,1 +9610,Female,24,High School,16,43,81,59,37,2.0,1,73,Urban,HR Executive,71719,1 +9611,Female,23,Bachelors,14,43,53,68,89,8.0,2,3,Urban,HR Executive,144511,0 +9612,Male,46,Masters,4,24,22,86,37,2.0,3,93,Rural,Manager,50925,0 +9613,Female,22,PhD,9,91,18,74,48,3.0,0,72,Urban,Manager,24588,1 +9614,Male,39,Diploma,12,17,84,24,36,1.0,5,33,Rural,Software Engineer,97772,0 +9615,Other,42,Bachelors,6,98,90,4,60,6.0,2,65,Semi-Urban,Data Analyst,23974,1 +9616,Female,26,Masters,7,41,61,18,76,8.0,2,56,Semi-Urban,HR Executive,102714,0 +9617,Female,52,Bachelors,1,15,97,9,0,9.0,6,2,Semi-Urban,ML Engineer,115255,0 +9618,Female,58,Diploma,13,47,61,33,44,2.0,5,91,Semi-Urban,HR Executive,111784,0 +9619,Female,25,Bachelors,16,86,71,99,83,4.0,2,67,Urban,Data Analyst,47648,1 +9620,Male,38,Diploma,0,41,92,15,90,6.0,5,97,Semi-Urban,HR Executive,42716,1 +9621,Male,58,Diploma,14,20,73,4,19,6.0,1,94,Urban,ML Engineer,107392,0 +9622,Male,55,Bachelors,2,54,54,50,40,4.0,5,70,Urban,Software Engineer,149861,0 +9623,Male,59,High School,15,54,57,14,21,4.0,2,11,Semi-Urban,Manager,20180,0 +9624,Female,59,Bachelors,4,11,46,77,40,0.0,7,48,Urban,ML Engineer,62753,0 +9625,Male,40,Bachelors,12,26,87,73,72,2.0,2,14,Urban,Software Engineer,72117,0 +9626,Male,36,Diploma,10,42,22,0,91,4.0,7,30,Semi-Urban,HR Executive,139197,0 +9627,Male,34,Bachelors,19,40,59,68,99,1.0,1,5,Urban,Manager,56031,0 +9628,Female,59,Bachelors,1,46,39,99,77,6.0,0,65,Rural,Data Analyst,27244,1 +9629,Male,59,Bachelors,11,96,91,69,12,6.0,7,53,Urban,Manager,72274,1 +9630,Male,44,Bachelors,17,28,0,37,75,2.0,7,81,Rural,Data Analyst,56422,0 +9631,Male,28,High School,19,52,44,43,26,5.0,5,68,Urban,HR Executive,45242,0 +9632,Female,42,High School,11,67,61,26,46,7.0,1,76,Urban,Software Engineer,96173,0 +9633,Male,55,Masters,0,45,91,3,90,8.0,4,40,Semi-Urban,ML Engineer,69859,0 +9634,Female,26,Bachelors,5,28,54,87,21,1.0,2,55,Rural,ML Engineer,147579,0 +9635,Male,22,Masters,8,77,70,73,41,3.0,6,0,Semi-Urban,Software Engineer,38150,0 +9636,Male,21,Bachelors,7,69,66,79,53,2.0,5,53,Urban,Data Analyst,61120,1 +9637,Female,35,High School,18,45,5,44,51,3.0,7,0,Semi-Urban,HR Executive,41506,0 +9638,Male,49,Bachelors,14,39,5,94,22,9.0,7,95,Rural,Manager,33889,0 +9639,Male,28,High School,1,7,58,68,61,1.0,3,28,Urban,Data Analyst,78922,0 +9640,Male,54,Masters,6,64,71,18,42,9.0,4,47,Urban,Data Analyst,21499,0 +9641,Male,32,High School,0,96,81,93,1,0.0,0,38,Semi-Urban,Manager,142408,1 +9642,Male,46,PhD,14,66,43,68,26,2.0,1,37,Semi-Urban,Manager,53145,0 +9643,Male,38,Bachelors,6,39,50,18,45,8.0,1,23,Urban,Manager,99595,0 +9644,Male,28,Bachelors,3,0,66,43,18,7.0,7,26,Semi-Urban,ML Engineer,61167,0 +9645,Male,59,Bachelors,8,35,40,12,15,4.0,1,46,Urban,Manager,27650,0 +9646,Female,58,High School,9,74,42,16,99,5.0,2,94,Rural,Manager,35059,0 +9647,Female,29,Masters,3,71,88,6,30,2.0,0,8,Urban,ML Engineer,118166,0 +9648,Male,59,High School,12,36,27,28,83,0.0,1,74,Urban,Manager,114767,0 +9649,Male,52,Masters,14,55,8,70,82,9.0,5,47,Rural,ML Engineer,79050,0 +9650,Male,30,Masters,14,62,83,76,47,3.0,6,60,Semi-Urban,ML Engineer,62489,1 +9651,Male,56,Masters,19,10,87,38,22,3.0,5,30,Rural,Manager,133952,0 +9652,Male,44,High School,4,66,38,17,60,6.0,4,12,Semi-Urban,Data Analyst,136310,0 +9653,Male,28,High School,8,67,17,23,69,1.0,4,56,Rural,Manager,84411,0 +9654,Male,45,Diploma,8,79,20,22,10,2.0,6,39,Semi-Urban,HR Executive,71026,0 +9655,Male,46,Diploma,3,38,69,96,79,7.0,7,92,Rural,ML Engineer,128664,1 +9656,Male,32,High School,18,41,18,30,97,0.0,1,65,Semi-Urban,Manager,72587,0 +9657,Female,46,PhD,12,5,25,95,49,2.0,4,57,Semi-Urban,Manager,48679,0 +9658,Male,55,Diploma,5,57,43,87,20,3.0,3,11,Semi-Urban,Software Engineer,37738,0 +9659,Female,44,Bachelors,10,35,68,99,27,8.0,6,91,Urban,Data Analyst,26557,1 +9660,Female,36,Masters,12,85,8,90,25,7.0,5,72,Semi-Urban,HR Executive,26547,1 +9661,Male,58,Masters,16,48,19,4,50,4.0,4,88,Urban,Data Analyst,52343,0 +9662,Male,26,Bachelors,6,47,15,6,89,4.0,7,64,Urban,Data Analyst,30995,0 +9663,Male,59,Bachelors,11,96,90,0,33,5.0,1,80,Urban,HR Executive,45645,1 +9664,Male,38,Masters,4,58,25,55,87,4.0,7,25,Semi-Urban,Manager,137823,0 +9665,Male,56,Masters,2,86,21,24,67,3.0,3,41,Urban,Data Analyst,113385,0 +9666,Female,33,Bachelors,19,57,42,43,13,8.0,2,34,Urban,Software Engineer,122994,0 +9667,Male,54,Bachelors,18,75,67,87,16,4.0,7,61,Semi-Urban,HR Executive,131423,1 +9668,Male,59,Masters,4,91,50,66,50,7.0,6,43,Urban,HR Executive,35802,1 +9669,Female,42,Masters,16,6,88,42,79,0.0,2,12,Semi-Urban,ML Engineer,97354,0 +9670,Female,27,Bachelors,2,93,8,7,13,4.0,0,91,Semi-Urban,HR Executive,89416,0 +9671,Male,38,Diploma,14,18,70,27,25,0.0,3,43,Semi-Urban,HR Executive,145566,0 +9672,Female,41,Masters,19,24,57,18,74,1.0,7,86,Urban,Data Analyst,81328,0 +9673,Male,47,High School,15,47,30,8,19,7.0,0,32,Urban,Software Engineer,26667,0 +9674,Male,28,Bachelors,10,71,93,53,33,2.0,7,49,Rural,ML Engineer,99464,1 +9675,Male,52,Bachelors,0,73,21,12,90,5.0,4,40,Semi-Urban,HR Executive,21883,0 +9676,Male,25,Bachelors,7,41,50,18,83,5.0,1,87,Urban,Software Engineer,86070,0 +9677,Female,34,Diploma,19,23,27,77,93,2.0,6,52,Urban,HR Executive,144895,0 +9678,Male,22,Bachelors,16,27,86,38,81,5.0,0,11,Rural,Software Engineer,147300,0 +9679,Male,59,Bachelors,10,14,23,53,14,6.0,2,96,Semi-Urban,Manager,42520,0 +9680,Male,44,Bachelors,2,44,1,31,84,6.0,3,71,Urban,Software Engineer,46564,0 +9681,Male,33,Masters,14,15,72,5,24,6.0,4,18,Urban,HR Executive,95785,0 +9682,Male,42,Bachelors,11,49,95,44,86,2.0,6,48,Rural,Manager,59706,1 +9683,Male,31,Masters,7,18,76,31,13,7.0,5,14,Rural,Manager,55524,0 +9684,Female,39,Bachelors,9,65,77,56,40,9.0,1,2,Urban,Manager,33326,0 +9685,Male,50,Masters,7,45,30,51,63,0.0,5,84,Rural,Software Engineer,28866,0 +9686,Male,24,Bachelors,7,83,93,56,66,1.0,0,33,Urban,HR Executive,30915,1 +9687,Male,48,Masters,6,2,69,54,78,3.0,3,17,Rural,Software Engineer,71993,0 +9688,Male,31,Masters,7,34,66,98,68,5.0,2,87,Urban,Data Analyst,84847,1 +9689,Male,24,Diploma,14,93,13,47,40,4.0,5,5,Urban,ML Engineer,123334,0 +9690,Female,36,Diploma,14,57,53,43,82,6.0,7,6,Urban,Data Analyst,126237,0 +9691,Other,46,Bachelors,18,55,78,4,9,2.0,6,34,Urban,ML Engineer,61769,0 +9692,Male,48,Masters,10,56,42,7,42,0.0,2,33,Semi-Urban,HR Executive,28587,0 +9693,Male,51,Bachelors,18,37,67,47,41,0.0,2,68,Semi-Urban,Manager,46387,0 +9694,Female,27,High School,7,17,96,27,23,9.0,5,39,Rural,Software Engineer,108229,0 +9695,Male,36,Bachelors,17,12,66,45,77,8.0,7,91,Urban,HR Executive,126186,0 +9696,Male,47,Masters,15,16,4,91,48,4.0,3,98,Semi-Urban,Manager,57972,0 +9697,Male,58,Masters,6,41,28,58,71,4.0,3,77,Urban,HR Executive,62597,0 +9698,Female,33,Bachelors,5,17,89,15,33,6.0,1,66,Urban,HR Executive,48378,0 +9699,Male,42,High School,11,74,43,71,57,2.0,5,96,Urban,HR Executive,22719,1 +9700,Female,57,Bachelors,12,61,28,25,44,7.0,6,10,Semi-Urban,HR Executive,86055,0 +9701,Female,43,PhD,13,37,46,64,20,4.0,4,20,Urban,HR Executive,65928,0 +9702,Male,39,Diploma,1,79,88,48,59,4.0,1,40,Rural,Software Engineer,30615,1 +9703,Female,26,Bachelors,4,18,0,75,64,1.0,0,20,Urban,Data Analyst,63165,0 +9704,Female,32,Masters,8,81,66,67,59,0.0,6,44,Urban,HR Executive,48565,1 +9705,Male,31,High School,10,69,5,84,75,0.0,7,92,Urban,Data Analyst,71933,1 +9706,Male,32,Diploma,10,87,49,80,25,9.0,5,4,Semi-Urban,Software Engineer,101582,0 +9707,Male,28,Masters,9,50,11,6,98,6.0,7,37,Rural,Software Engineer,137363,0 +9708,Male,31,Bachelors,11,37,94,40,55,3.0,7,65,Semi-Urban,Data Analyst,139820,1 +9709,Male,30,Diploma,7,33,69,50,51,2.0,3,46,Urban,Software Engineer,140144,0 +9710,Male,49,Bachelors,4,70,81,44,68,0.0,4,61,Urban,ML Engineer,113358,1 +9711,Male,35,Bachelors,15,81,62,53,23,9.0,1,26,Urban,Data Analyst,52973,0 +9712,Female,54,Diploma,7,18,58,85,66,0.0,5,93,Rural,Software Engineer,77746,1 +9713,Male,21,Bachelors,10,44,7,35,71,0.0,6,55,Urban,ML Engineer,48229,0 +9714,Male,59,Diploma,3,47,85,13,36,3.0,0,51,Urban,Manager,32567,0 +9715,Male,26,Masters,11,7,89,68,4,1.0,4,15,Urban,Software Engineer,77917,0 +9716,Male,49,Bachelors,16,14,60,11,91,0.0,5,58,Urban,Manager,96391,0 +9717,Male,47,Bachelors,10,8,52,18,55,3.0,4,83,Urban,Data Analyst,81778,0 +9718,Male,54,PhD,1,47,49,88,99,0.0,2,48,Semi-Urban,HR Executive,119271,0 +9719,Male,33,Diploma,2,46,57,95,55,1.0,6,90,Urban,Software Engineer,55364,1 +9720,Female,59,Diploma,18,75,47,56,18,3.0,2,6,Urban,Manager,131584,0 +9721,Female,38,Bachelors,14,76,20,54,69,3.0,0,13,Urban,Software Engineer,42485,0 +9722,Male,34,Diploma,3,27,55,43,90,4.0,6,39,Urban,Software Engineer,71315,0 +9723,Female,41,Masters,15,38,35,85,92,5.0,0,75,Urban,Data Analyst,126381,0 +9724,Female,52,Bachelors,4,69,64,69,85,3.0,0,96,Urban,Manager,46953,1 +9725,Male,51,High School,3,97,57,59,50,3.0,4,78,Semi-Urban,HR Executive,38448,1 +9726,Other,56,Bachelors,11,99,5,65,87,9.0,1,53,Urban,Software Engineer,140733,0 +9727,Female,49,Masters,6,69,49,36,33,9.0,6,63,Urban,Software Engineer,140512,0 +9728,Male,44,Diploma,14,17,17,4,27,9.0,6,23,Semi-Urban,Data Analyst,106168,0 +9729,Male,49,Bachelors,18,55,39,54,75,4.0,4,5,Urban,Software Engineer,54197,0 +9730,Male,30,PhD,14,64,45,91,48,2.0,3,21,Urban,Software Engineer,77752,0 +9731,Male,56,Diploma,10,2,33,46,74,2.0,0,3,Urban,Software Engineer,115927,0 +9732,Female,23,Diploma,9,64,2,27,81,7.0,6,26,Urban,ML Engineer,94024,0 +9733,Male,44,Masters,11,52,11,22,44,5.0,4,54,Urban,ML Engineer,66405,0 +9734,Female,57,PhD,6,67,66,78,29,3.0,3,19,Urban,HR Executive,147067,0 +9735,Female,42,Bachelors,16,90,83,65,92,9.0,5,0,Urban,HR Executive,69113,0 +9736,Female,34,Bachelors,4,37,8,0,99,2.0,5,44,Urban,Software Engineer,67431,0 +9737,Female,22,Bachelors,18,79,61,39,29,3.0,4,25,Urban,ML Engineer,119486,0 +9738,Male,42,Bachelors,13,17,68,82,40,1.0,1,17,Semi-Urban,Data Analyst,67850,0 +9739,Male,44,Bachelors,4,90,22,21,3,1.0,4,55,Rural,Data Analyst,144377,0 +9740,Female,38,Bachelors,4,44,49,15,5,5.0,7,24,Urban,ML Engineer,73910,0 +9741,Male,38,High School,15,56,20,37,45,9.0,5,12,Urban,Software Engineer,24847,0 +9742,Male,56,Bachelors,17,62,89,91,2,4.0,6,81,Urban,HR Executive,69154,1 +9743,Female,50,Diploma,1,19,74,6,0,6.0,1,10,Semi-Urban,ML Engineer,81350,0 +9744,Female,57,Bachelors,3,86,39,88,43,1.0,4,75,Rural,Data Analyst,76763,1 +9745,Male,22,Masters,11,15,12,67,75,2.0,1,10,Semi-Urban,Software Engineer,96966,0 +9746,Female,39,Bachelors,11,39,5,38,85,5.0,3,63,Semi-Urban,ML Engineer,26643,0 +9747,Female,56,Diploma,16,73,60,25,50,2.0,4,8,Urban,Software Engineer,123744,0 +9748,Male,58,Diploma,8,56,31,19,63,8.0,4,21,Urban,Manager,27544,0 +9749,Male,33,High School,17,18,30,92,62,6.0,4,38,Rural,Software Engineer,43762,0 +9750,Female,35,Bachelors,19,0,70,89,94,0.0,7,19,Urban,HR Executive,128712,0 +9751,Male,46,High School,15,79,69,76,9,3.0,2,66,Urban,Software Engineer,113813,1 +9752,Male,44,Diploma,3,54,77,72,69,9.0,1,1,Semi-Urban,Data Analyst,67611,0 +9753,Male,53,Bachelors,7,84,55,6,57,0.0,2,39,Urban,ML Engineer,63279,0 +9754,Female,23,Bachelors,8,82,90,10,47,8.0,3,32,Urban,HR Executive,123935,0 +9755,Male,57,Bachelors,11,44,59,61,57,6.0,4,96,Urban,HR Executive,133401,1 +9756,Male,29,Masters,10,27,47,25,75,9.0,2,86,Semi-Urban,Data Analyst,76772,0 +9757,Male,35,Bachelors,13,89,41,47,79,5.0,6,80,Rural,Manager,67272,1 +9758,Other,45,High School,0,31,94,11,83,8.0,4,98,Rural,HR Executive,50297,0 +9759,Male,59,Bachelors,5,46,29,27,93,4.0,1,27,Urban,HR Executive,87287,0 +9760,Male,51,Bachelors,17,29,21,47,16,0.0,7,43,Urban,ML Engineer,138576,0 +9761,Female,37,High School,12,17,79,83,82,9.0,7,68,Semi-Urban,Software Engineer,25085,1 +9762,Male,46,High School,15,23,14,97,75,9.0,1,35,Semi-Urban,Software Engineer,77862,0 +9763,Other,58,High School,2,5,61,30,11,0.0,3,26,Urban,ML Engineer,95103,0 +9764,Female,51,Bachelors,10,13,37,77,50,3.0,1,69,Rural,ML Engineer,110064,0 +9765,Female,35,Bachelors,15,35,62,48,3,5.0,7,46,Rural,ML Engineer,117750,0 +9766,Male,27,Bachelors,11,11,41,98,18,1.0,4,66,Urban,Software Engineer,141486,0 +9767,Female,40,Bachelors,7,16,38,67,82,9.0,7,31,Rural,Data Analyst,29756,0 +9768,Female,30,High School,16,50,27,75,32,8.0,4,49,Urban,Software Engineer,57324,0 +9769,Other,25,Bachelors,19,67,68,30,36,7.0,4,7,Rural,Manager,144381,0 +9770,Male,36,High School,9,83,70,64,9,4.0,5,50,Urban,Software Engineer,119902,1 +9771,Female,29,Bachelors,19,81,29,10,29,6.0,7,68,Urban,ML Engineer,124971,0 +9772,Male,51,Bachelors,1,78,47,22,72,1.0,7,63,Rural,ML Engineer,90091,0 +9773,Male,23,Bachelors,13,30,66,48,64,5.0,4,56,Urban,Software Engineer,111897,0 +9774,Male,21,Bachelors,8,27,8,99,54,9.0,4,93,Urban,Software Engineer,55547,0 +9775,Female,46,Bachelors,3,61,32,16,80,8.0,2,15,Semi-Urban,Software Engineer,116390,0 +9776,Male,47,High School,6,33,73,7,67,9.0,7,83,Semi-Urban,Manager,133746,0 +9777,Male,49,Bachelors,3,47,94,37,75,3.0,6,23,Semi-Urban,ML Engineer,46184,0 +9778,Other,52,Bachelors,0,24,94,47,88,2.0,4,66,Urban,Software Engineer,55313,0 +9779,Male,48,Diploma,6,12,71,5,64,3.0,3,90,Semi-Urban,Software Engineer,65651,0 +9780,Female,50,Masters,13,7,34,90,74,1.0,3,25,Urban,HR Executive,33277,0 +9781,Male,46,High School,16,74,8,47,84,0.0,3,72,Urban,Manager,117973,0 +9782,Male,42,Diploma,13,34,14,63,3,5.0,4,7,Urban,Data Analyst,26008,0 +9783,Female,44,Bachelors,4,25,53,56,15,8.0,3,47,Urban,Data Analyst,83840,0 +9784,Female,46,Masters,12,50,97,95,41,0.0,6,29,Rural,Data Analyst,51098,1 +9785,Male,27,High School,6,16,6,35,93,9.0,7,97,Rural,Data Analyst,119575,0 +9786,Female,21,Bachelors,11,98,2,27,68,2.0,5,10,Rural,ML Engineer,48262,0 +9787,Male,43,Masters,13,10,78,15,18,9.0,1,10,Urban,Manager,21684,0 +9788,Male,22,Diploma,12,11,18,96,21,0.0,5,28,Urban,ML Engineer,120905,0 +9789,Male,31,Bachelors,10,34,87,91,47,3.0,5,38,Semi-Urban,HR Executive,117544,1 +9790,Male,27,Diploma,7,63,61,75,64,1.0,6,16,Urban,Software Engineer,101675,0 +9791,Male,34,High School,7,44,31,76,73,6.0,2,72,Urban,Data Analyst,64029,0 +9792,Male,33,Masters,14,79,54,30,55,6.0,5,95,Urban,Software Engineer,36387,1 +9793,Male,21,High School,9,42,50,75,77,2.0,6,99,Urban,Software Engineer,56244,1 +9794,Male,47,Masters,7,49,31,5,24,3.0,7,47,Urban,HR Executive,117181,0 +9795,Male,23,High School,12,46,16,81,2,4.0,4,82,Urban,Manager,118030,0 +9796,Male,57,Bachelors,9,93,63,98,43,5.0,6,35,Rural,Data Analyst,92741,1 +9797,Female,47,Masters,2,75,1,44,89,6.0,2,21,Semi-Urban,Software Engineer,32983,0 +9798,Female,34,Bachelors,4,59,20,20,64,4.0,4,1,Rural,ML Engineer,69153,0 +9799,Male,49,Masters,10,40,38,89,91,1.0,6,21,Rural,ML Engineer,129239,0 +9800,Female,40,Bachelors,3,55,88,88,55,7.0,5,98,Rural,ML Engineer,78969,1 +9801,Female,57,High School,9,67,70,34,49,4.0,1,63,Semi-Urban,HR Executive,111125,0 +9802,Male,38,Diploma,3,34,95,16,12,5.0,1,58,Urban,HR Executive,41842,0 +9803,Male,42,Bachelors,8,86,71,1,72,9.0,3,64,Rural,Manager,20896,0 +9804,Female,50,Bachelors,9,47,94,67,74,2.0,1,93,Semi-Urban,Software Engineer,120817,1 +9805,Male,32,Bachelors,2,51,16,34,15,0.0,7,51,Semi-Urban,Software Engineer,120939,0 +9806,Female,54,Bachelors,18,49,40,27,37,3.0,7,48,Semi-Urban,Manager,46274,0 +9807,Female,46,Bachelors,10,52,69,42,83,6.0,2,45,Urban,Data Analyst,83278,0 +9808,Female,56,Diploma,1,17,44,64,97,0.0,6,86,Urban,Data Analyst,119485,0 +9809,Other,56,Diploma,5,78,62,66,10,6.0,0,45,Urban,ML Engineer,88633,1 +9810,Male,38,Bachelors,11,64,57,7,66,6.0,1,45,Urban,ML Engineer,107854,0 +9811,Male,45,Bachelors,5,52,59,84,16,9.0,3,99,Rural,ML Engineer,60262,1 +9812,Female,25,Bachelors,13,31,89,86,66,5.0,2,57,Rural,ML Engineer,131765,1 +9813,Male,47,Bachelors,16,6,52,4,20,2.0,5,80,Urban,Data Analyst,137824,0 +9814,Female,57,High School,1,70,63,19,64,1.0,5,14,Urban,ML Engineer,103915,0 +9815,Other,32,Masters,0,56,63,78,3,9.0,2,8,Urban,Manager,149453,0 +9816,Female,59,Bachelors,7,36,88,2,81,7.0,3,63,Urban,HR Executive,31928,0 +9817,Male,42,High School,18,18,2,38,58,4.0,6,29,Semi-Urban,Manager,21886,0 +9818,Male,31,High School,18,3,51,78,5,4.0,2,58,Urban,Data Analyst,84515,0 +9819,Male,30,Bachelors,9,23,39,41,72,7.0,5,86,Urban,Data Analyst,148714,0 +9820,Male,56,Masters,3,49,96,91,12,3.0,2,13,Urban,Software Engineer,116951,1 +9821,Female,58,Masters,2,27,4,71,61,9.0,6,83,Urban,Data Analyst,147980,0 +9822,Female,38,High School,17,35,30,60,52,3.0,2,5,Urban,Data Analyst,58717,0 +9823,Female,31,Masters,9,72,86,84,89,0.0,2,8,Urban,Software Engineer,41923,1 +9824,Male,36,Bachelors,16,79,86,21,60,8.0,2,83,Urban,Manager,87103,1 +9825,Male,45,Masters,17,28,27,76,24,4.0,5,71,Urban,ML Engineer,71183,0 +9826,Female,23,Bachelors,10,88,91,56,75,6.0,1,12,Semi-Urban,Software Engineer,137050,1 +9827,Male,22,High School,10,36,33,76,61,0.0,5,92,Urban,Manager,28866,1 +9828,Male,47,High School,17,1,95,16,30,4.0,6,6,Rural,ML Engineer,103597,0 +9829,Female,31,High School,2,61,3,46,72,3.0,1,41,Urban,Data Analyst,96251,0 +9830,Female,26,Bachelors,6,10,5,43,51,7.0,2,53,Rural,Software Engineer,28643,0 +9831,Male,48,High School,19,9,1,23,77,1.0,7,73,Rural,ML Engineer,138393,0 +9832,Female,23,Masters,15,20,41,73,29,4.0,0,6,Rural,HR Executive,44467,0 +9833,Male,35,Masters,10,76,28,65,35,2.0,3,99,Urban,HR Executive,44270,1 +9834,Other,26,Bachelors,8,16,74,83,35,8.0,4,12,Urban,Software Engineer,39878,0 +9835,Male,35,Masters,18,88,97,37,31,6.0,6,42,Rural,HR Executive,74506,1 +9836,Male,56,PhD,19,23,65,5,51,4.0,6,93,Urban,Data Analyst,20544,0 +9837,Female,37,Bachelors,8,71,23,52,56,6.0,3,26,Semi-Urban,Data Analyst,106589,0 +9838,Male,50,Bachelors,18,17,98,84,88,4.0,7,75,Semi-Urban,Software Engineer,26908,1 +9839,Female,26,Diploma,12,56,59,91,53,6.0,2,61,Urban,HR Executive,122945,1 +9840,Female,31,Masters,11,23,68,95,13,8.0,0,64,Urban,Data Analyst,99738,1 +9841,Female,57,Bachelors,0,48,68,0,27,8.0,4,14,Semi-Urban,Data Analyst,46992,0 +9842,Other,28,Bachelors,12,84,25,99,79,8.0,4,85,Semi-Urban,Manager,128583,1 +9843,Male,37,Diploma,3,2,11,29,55,3.0,6,24,Urban,Data Analyst,113755,0 +9844,Female,21,Diploma,13,93,7,94,99,6.0,5,32,Semi-Urban,ML Engineer,79859,0 +9845,Male,21,Bachelors,9,47,0,43,79,3.0,6,6,Urban,Software Engineer,37428,0 +9846,Male,59,High School,7,96,77,87,26,5.0,2,57,Rural,Software Engineer,101605,1 +9847,Female,50,Masters,17,46,3,11,39,0.0,5,9,Semi-Urban,Software Engineer,101416,0 +9848,Male,40,High School,4,42,47,0,90,6.0,4,56,Rural,HR Executive,45230,0 +9849,Male,43,High School,19,9,44,66,77,7.0,5,55,Urban,ML Engineer,147734,0 +9850,Male,51,Masters,11,77,16,94,2,0.0,0,3,Urban,Software Engineer,66314,0 +9851,Female,43,High School,0,3,25,3,43,5.0,3,75,Urban,Data Analyst,128103,0 +9852,Other,25,High School,9,32,64,83,66,7.0,1,50,Urban,Data Analyst,39501,0 +9853,Male,26,Diploma,12,99,70,64,35,3.0,2,26,Urban,Manager,91770,1 +9854,Male,56,Diploma,13,35,87,4,75,4.0,0,26,Urban,Software Engineer,143462,0 +9855,Female,37,Diploma,4,71,19,47,44,8.0,1,24,Urban,Software Engineer,137940,0 +9856,Male,57,Bachelors,12,6,20,96,68,2.0,4,45,Rural,Manager,40818,0 +9857,Male,47,Bachelors,9,78,54,53,7,2.0,6,69,Semi-Urban,Data Analyst,115674,1 +9858,Male,30,Bachelors,5,82,4,28,21,4.0,5,54,Urban,Software Engineer,137390,0 +9859,Male,48,Bachelors,18,50,18,73,52,2.0,7,68,Urban,HR Executive,70272,0 +9860,Male,22,Bachelors,3,86,89,67,25,8.0,7,10,Urban,ML Engineer,107732,1 +9861,Female,27,Bachelors,3,40,6,89,70,6.0,3,37,Urban,Manager,72946,0 +9862,Male,28,Diploma,8,67,21,2,60,0.0,4,95,Rural,HR Executive,43847,0 +9863,Female,56,High School,18,25,3,55,89,9.0,7,92,Semi-Urban,Data Analyst,101346,0 +9864,Female,53,Masters,10,20,84,18,12,2.0,2,10,Semi-Urban,Software Engineer,132032,0 +9865,Female,21,Bachelors,17,3,39,11,20,1.0,4,35,Rural,Data Analyst,91329,0 +9866,Male,51,Bachelors,0,22,69,23,89,2.0,3,7,Urban,Software Engineer,137890,0 +9867,Male,32,Diploma,12,85,10,51,7,1.0,6,91,Urban,HR Executive,59497,1 +9868,Male,44,High School,13,91,97,85,20,5.0,2,23,Urban,Manager,146235,1 +9869,Female,36,Bachelors,19,75,78,0,74,4.0,4,27,Urban,Software Engineer,30850,0 +9870,Male,37,Masters,19,39,26,42,82,3.0,2,92,Urban,ML Engineer,35487,0 +9871,Male,31,Bachelors,7,91,97,8,24,0.0,6,62,Urban,ML Engineer,141903,1 +9872,Male,55,Bachelors,15,4,75,94,41,6.0,2,43,Urban,ML Engineer,98276,0 +9873,Male,45,Bachelors,5,15,96,60,94,4.0,7,57,Urban,ML Engineer,92492,0 +9874,Male,56,High School,1,33,30,99,12,2.0,0,64,Rural,Data Analyst,57321,0 +9875,Male,24,Masters,10,56,36,37,91,9.0,1,20,Rural,Software Engineer,128953,0 +9876,Male,33,Diploma,12,59,72,85,89,3.0,1,7,Urban,HR Executive,43989,0 +9877,Male,57,High School,15,70,5,70,60,6.0,4,1,Urban,HR Executive,78681,0 +9878,Male,59,Bachelors,7,87,72,73,48,6.0,3,90,Semi-Urban,Manager,144453,1 +9879,Female,24,Bachelors,9,24,70,33,25,5.0,6,13,Urban,Manager,131267,0 +9880,Male,24,High School,18,39,33,64,29,2.0,7,26,Urban,Data Analyst,67753,0 +9881,Male,28,Masters,4,28,24,21,85,0.0,7,63,Urban,Software Engineer,124266,0 +9882,Male,29,Masters,6,94,44,14,60,6.0,4,75,Rural,Manager,89099,0 +9883,Male,34,High School,4,39,17,17,61,5.0,5,76,Urban,Manager,125816,0 +9884,Female,24,Bachelors,3,55,98,77,42,8.0,3,5,Semi-Urban,Data Analyst,91442,0 +9885,Male,56,Diploma,7,78,28,49,79,8.0,4,8,Urban,Data Analyst,128403,0 +9886,Female,43,Bachelors,16,17,84,45,82,5.0,7,58,Rural,HR Executive,147258,0 +9887,Female,58,Diploma,5,60,70,65,23,1.0,1,69,Urban,Data Analyst,138230,1 +9888,Female,40,Masters,13,11,22,72,42,2.0,7,64,Semi-Urban,ML Engineer,33865,0 +9889,Male,50,Bachelors,10,66,79,36,15,0.0,5,2,Semi-Urban,HR Executive,79103,0 +9890,Male,51,High School,8,4,40,57,8,9.0,0,19,Urban,Data Analyst,72590,0 +9891,Female,22,Bachelors,16,32,68,18,83,1.0,7,91,Rural,Manager,37731,0 +9892,Male,36,Masters,9,36,4,16,18,3.0,2,86,Urban,ML Engineer,141092,0 +9893,Female,31,High School,4,0,98,98,69,9.0,6,6,Rural,Manager,25275,0 +9894,Female,40,High School,0,27,15,25,98,2.0,3,19,Semi-Urban,HR Executive,42341,0 +9895,Female,26,Bachelors,4,79,99,35,57,2.0,1,15,Rural,Data Analyst,28952,0 +9896,Male,58,High School,13,82,35,13,5,9.0,6,21,Semi-Urban,Software Engineer,78346,0 +9897,Female,46,PhD,1,76,15,64,88,7.0,0,40,Urban,HR Executive,144080,0 +9898,Female,42,Bachelors,4,18,71,77,72,9.0,2,43,Rural,HR Executive,94506,0 +9899,Female,35,High School,15,90,66,46,26,3.0,7,60,Rural,Software Engineer,133374,1 +9900,Male,25,Masters,4,82,39,88,52,9.0,2,27,Urban,Software Engineer,144017,1 +9901,Male,25,Bachelors,7,36,68,37,78,3.0,3,46,Urban,Software Engineer,39302,0 +9902,Male,59,High School,6,39,2,57,73,1.0,6,50,Urban,ML Engineer,48519,0 +9903,Male,28,Diploma,11,89,50,44,37,5.0,7,67,Semi-Urban,Manager,94415,1 +9904,Male,29,Bachelors,15,70,65,14,97,1.0,1,6,Urban,Software Engineer,117717,0 +9905,Female,48,High School,2,90,36,83,59,5.0,3,97,Semi-Urban,HR Executive,79064,1 +9906,Male,44,PhD,7,85,94,3,50,7.0,7,32,Urban,ML Engineer,118326,0 +9907,Female,36,Masters,3,54,96,16,72,2.0,7,77,Semi-Urban,Data Analyst,140117,1 +9908,Male,40,High School,7,62,31,89,71,8.0,6,78,Urban,Manager,134177,1 +9909,Male,32,Bachelors,14,99,2,95,17,0.0,5,47,Urban,ML Engineer,102125,1 +9910,Male,32,High School,17,38,52,77,79,2.0,4,56,Rural,ML Engineer,46759,0 +9911,Male,47,Bachelors,11,85,37,50,32,3.0,2,77,Urban,Software Engineer,148548,1 +9912,Female,54,Bachelors,19,9,55,1,14,6.0,2,65,Urban,Software Engineer,105226,0 +9913,Male,46,Diploma,15,2,51,42,37,0.0,0,95,Urban,Software Engineer,143096,0 +9914,Female,58,Bachelors,1,87,79,58,74,0.0,2,20,Urban,Data Analyst,37347,1 +9915,Male,51,High School,1,30,83,30,9,1.0,0,95,Semi-Urban,HR Executive,90698,1 +9916,Female,49,Masters,5,45,81,3,71,2.0,5,31,Semi-Urban,Software Engineer,136050,0 +9917,Male,37,Bachelors,4,17,19,19,3,3.0,5,5,Urban,HR Executive,81957,0 +9918,Male,33,Diploma,6,47,13,13,44,3.0,5,83,Urban,Data Analyst,23934,0 +9919,Male,49,Masters,19,44,22,39,30,0.0,6,56,Semi-Urban,ML Engineer,63271,0 +9920,Male,38,Diploma,4,54,44,19,4,6.0,5,81,Rural,Software Engineer,20592,0 +9921,Male,59,Bachelors,9,57,17,37,47,6.0,7,94,Semi-Urban,Manager,111399,0 +9922,Female,29,Diploma,4,72,25,61,26,5.0,7,98,Semi-Urban,Data Analyst,41111,1 +9923,Female,39,Bachelors,12,93,5,20,15,2.0,5,4,Urban,Manager,104038,0 +9924,Female,50,Bachelors,13,5,79,94,23,7.0,7,3,Urban,Software Engineer,32214,0 +9925,Male,25,Masters,0,46,73,58,86,5.0,2,87,Urban,ML Engineer,46878,1 +9926,Male,28,Masters,3,38,81,70,46,2.0,0,61,Urban,Software Engineer,64612,1 +9927,Male,31,Masters,11,11,49,61,20,6.0,3,58,Semi-Urban,ML Engineer,118950,0 +9928,Other,29,High School,1,12,36,83,35,2.0,6,92,Urban,Data Analyst,86759,0 +9929,Female,47,High School,8,58,62,63,13,8.0,1,71,Urban,HR Executive,102778,1 +9930,Female,33,Diploma,17,65,86,9,91,8.0,2,18,Urban,Software Engineer,110988,0 +9931,Female,42,Bachelors,11,53,65,18,32,0.0,5,96,Urban,Software Engineer,100438,0 +9932,Male,31,Masters,2,99,3,56,60,5.0,5,43,Semi-Urban,HR Executive,144998,0 +9933,Male,39,Masters,10,37,51,99,5,4.0,3,69,Urban,Software Engineer,86632,1 +9934,Male,44,Masters,7,74,91,39,73,7.0,0,18,Rural,HR Executive,113632,0 +9935,Male,49,Bachelors,9,45,52,21,75,6.0,7,53,Urban,Data Analyst,92334,0 +9936,Male,45,Diploma,12,31,41,50,12,3.0,0,80,Urban,Data Analyst,85577,0 +9937,Male,49,Bachelors,16,81,64,48,64,0.0,4,59,Urban,Software Engineer,145584,1 +9938,Female,28,Bachelors,18,71,21,60,9,5.0,0,7,Rural,ML Engineer,137550,0 +9939,Female,33,Bachelors,12,13,35,80,38,9.0,2,14,Semi-Urban,HR Executive,126823,0 +9940,Female,30,High School,13,69,6,3,73,7.0,6,82,Urban,ML Engineer,44548,0 +9941,Female,34,Diploma,2,81,15,69,88,3.0,5,45,Urban,HR Executive,108658,0 +9942,Male,44,Masters,9,16,16,84,78,8.0,6,94,Semi-Urban,Software Engineer,52389,0 +9943,Male,36,Diploma,2,62,21,46,41,6.0,7,75,Urban,ML Engineer,81623,0 +9944,Female,31,Masters,14,62,58,15,81,2.0,7,77,Urban,HR Executive,59687,0 +9945,Male,50,Masters,9,27,24,86,63,8.0,6,47,Semi-Urban,Software Engineer,62482,0 +9946,Male,22,Bachelors,0,35,69,25,39,5.0,7,76,Urban,ML Engineer,40557,0 +9947,Male,54,Diploma,5,86,9,33,14,7.0,7,98,Rural,Software Engineer,119079,0 +9948,Male,35,Bachelors,19,21,50,54,3,5.0,1,16,Urban,Manager,104611,0 +9949,Male,56,Masters,9,95,78,64,88,1.0,4,97,Rural,Manager,114057,1 +9950,Male,33,High School,18,40,62,82,5,6.0,5,60,Rural,ML Engineer,114357,1 +9951,Male,25,Bachelors,15,64,82,88,25,7.0,3,73,Semi-Urban,HR Executive,108948,1 +9952,Female,55,Bachelors,10,58,65,1,21,6.0,1,64,Semi-Urban,ML Engineer,146212,0 +9953,Male,50,High School,0,19,13,64,3,4.0,3,76,Rural,Data Analyst,32680,0 +9954,Male,41,High School,18,91,0,55,40,1.0,4,26,Rural,ML Engineer,116928,0 +9955,Male,28,PhD,18,8,83,56,98,7.0,3,96,Urban,Data Analyst,120388,1 +9956,Male,27,Diploma,1,72,36,10,46,7.0,4,10,Urban,Data Analyst,136615,0 +9957,Female,32,Masters,16,95,36,53,45,8.0,3,24,Semi-Urban,Manager,32028,0 +9958,Female,35,Masters,18,81,22,6,89,6.0,3,43,Rural,HR Executive,125801,0 +9959,Female,39,Bachelors,2,65,72,89,32,0.0,0,25,Urban,HR Executive,120685,1 +9960,Male,59,Bachelors,7,40,36,50,50,6.0,5,53,Urban,ML Engineer,100482,0 +9961,Male,21,High School,11,5,3,19,62,9.0,7,30,Semi-Urban,Software Engineer,33655,0 +9962,Male,50,Bachelors,5,84,98,28,23,7.0,2,69,Urban,ML Engineer,135657,1 +9963,Male,37,Bachelors,6,23,96,29,58,0.0,4,28,Urban,Manager,69405,0 +9964,Male,44,High School,16,17,62,14,72,7.0,6,79,Urban,Manager,102494,0 +9965,Male,57,Masters,15,44,64,60,87,9.0,3,87,Urban,Manager,20935,1 +9966,Male,49,High School,4,70,56,9,92,3.0,0,61,Rural,Software Engineer,98078,0 +9967,Female,47,High School,15,63,68,64,15,6.0,4,75,Urban,Manager,131430,1 +9968,Male,48,Bachelors,5,61,38,34,27,9.0,4,59,Rural,Data Analyst,103530,0 +9969,Female,31,High School,14,71,28,37,41,5.0,1,66,Urban,HR Executive,64927,0 +9970,Male,25,Bachelors,3,60,90,36,30,0.0,1,36,Rural,ML Engineer,130747,0 +9971,Male,39,High School,15,27,67,79,8,5.0,2,30,Rural,Data Analyst,115084,0 +9972,Other,48,Bachelors,13,25,24,32,45,5.0,0,99,Semi-Urban,Data Analyst,64663,0 +9973,Other,48,Diploma,0,68,83,72,41,7.0,6,36,Semi-Urban,Manager,25836,1 +9974,Male,27,Bachelors,11,36,81,97,78,4.0,1,7,Semi-Urban,Software Engineer,117728,0 +9975,Male,56,High School,12,61,83,56,67,2.0,3,94,Urban,Software Engineer,73172,1 +9976,Male,47,High School,13,0,88,99,0,3.0,6,2,Urban,ML Engineer,76415,0 +9977,Male,42,PhD,18,90,58,34,54,6.0,6,53,Urban,HR Executive,45576,1 +9978,Female,31,Masters,10,69,17,79,28,9.0,1,57,Urban,Data Analyst,132814,0 +9979,Other,30,Bachelors,15,58,76,48,84,3.0,7,70,Urban,HR Executive,143231,1 +9980,Female,44,Bachelors,16,42,28,97,30,5.0,4,42,Urban,ML Engineer,50673,0 +9981,Male,57,Bachelors,7,71,56,19,93,5.0,3,20,Urban,HR Executive,106513,0 +9982,Female,44,Masters,9,22,39,4,12,2.0,6,55,Urban,ML Engineer,49135,0 +9983,Male,53,Bachelors,6,10,77,45,44,2.0,6,67,Urban,Data Analyst,130556,0 +9984,Female,33,Bachelors,10,14,34,30,28,3.0,3,2,Urban,Data Analyst,83057,0 +9985,Female,57,Diploma,8,99,22,80,9,1.0,6,23,Urban,Manager,65725,0 +9986,Male,27,Masters,14,43,90,68,66,8.0,1,44,Urban,Manager,112989,1 +9987,Male,40,Bachelors,8,17,25,9,86,5.0,3,23,Urban,ML Engineer,58896,0 +9988,Male,46,Masters,7,23,70,12,16,5.0,2,56,Semi-Urban,Manager,95607,0 +9989,Male,44,Diploma,3,13,18,70,72,0.0,2,12,Urban,Data Analyst,144655,0 +9990,Female,49,Diploma,14,80,98,1,88,2.0,0,11,Urban,ML Engineer,41460,0 +9991,Male,46,Bachelors,14,45,11,98,12,1.0,3,31,Rural,HR Executive,81407,0 +9992,Male,52,High School,5,75,90,58,18,9.0,2,48,Rural,Data Analyst,146970,1 +9993,Male,37,High School,19,68,48,64,73,1.0,6,13,Urban,Manager,35791,0 +9994,Female,53,High School,6,51,70,74,44,6.0,1,30,Urban,ML Engineer,94647,0 +9995,Male,55,Bachelors,17,98,48,59,68,7.0,0,52,Rural,Data Analyst,77537,1 +9996,Female,59,PhD,9,51,76,11,11,1.0,1,38,Urban,HR Executive,149190,0 +9997,Female,51,Masters,11,86,66,3,5,1.0,1,49,Rural,Software Engineer,121363,0 +9998,Female,40,Bachelors,13,25,13,90,74,1.0,6,6,Urban,Manager,77927,0 +9999,Male,36,Bachelors,18,29,31,15,47,9.0,1,60,Urban,HR Executive,127677,0 +10000,Male,26,High School,3,3,99,27,92,8.0,2,56,Rural,Software Engineer,101031,0 +10001,Male,32,Bachelors,15,43,66,30,29,2.0,1,17,Urban,Software Engineer,40975,0 +10002,Male,59,Bachelors,12,6,68,15,26,3.0,2,1,Rural,HR Executive,66371,0 +10003,Male,37,Masters,13,11,88,25,18,7.0,0,69,Urban,Data Analyst,140408,0 +10004,Female,21,Masters,14,26,17,43,44,5.0,6,48,Urban,Software Engineer,50390,0 +10005,Male,28,Bachelors,2,13,44,8,22,0.0,3,72,Semi-Urban,ML Engineer,59688,0 +10006,Female,27,Bachelors,3,46,47,34,1,8.0,2,24,Urban,Data Analyst,29125,0 +10007,Male,30,High School,10,41,29,75,72,7.0,5,40,Rural,HR Executive,131084,0 +10008,Female,44,High School,14,17,47,32,53,5.0,1,63,Rural,Manager,55098,0 +10009,Female,46,Diploma,13,67,51,99,73,0.0,2,7,Rural,Software Engineer,91498,0 +10010,Female,23,Bachelors,13,32,62,0,13,5.0,7,48,Semi-Urban,Manager,68489,0 +10011,Female,54,Bachelors,0,56,2,42,91,0.0,0,2,Semi-Urban,HR Executive,105546,0 +10012,Female,54,Masters,15,45,13,50,16,0.0,0,64,Urban,ML Engineer,51806,0 +10013,Female,43,PhD,18,80,57,8,70,3.0,2,56,Urban,HR Executive,118614,0 +10014,Male,55,Bachelors,1,57,10,44,84,3.0,0,99,Semi-Urban,Software Engineer,43109,0 +10015,Male,35,Bachelors,9,63,86,65,24,1.0,0,22,Urban,Manager,85007,1 +10016,Male,21,Bachelors,15,85,31,39,24,2.0,7,13,Semi-Urban,Data Analyst,76943,0 +10017,Male,29,Diploma,14,56,43,28,61,4.0,7,29,Rural,ML Engineer,96642,0 +10018,Male,29,Masters,19,37,29,13,46,9.0,3,3,Urban,ML Engineer,88591,0 +10019,Male,52,Diploma,3,20,8,21,77,5.0,7,76,Semi-Urban,HR Executive,130273,0 +10020,Male,39,Masters,6,10,59,57,92,3.0,0,16,Urban,Data Analyst,124949,0 +10021,Male,47,Masters,10,4,98,83,43,5.0,3,46,Semi-Urban,Manager,140067,0 +10022,Male,47,High School,14,80,82,1,65,4.0,4,15,Urban,Software Engineer,23777,0 +10023,Female,31,Bachelors,15,2,33,15,87,6.0,3,98,Urban,ML Engineer,40702,0 +10024,Male,47,Bachelors,8,50,44,93,28,3.0,2,33,Semi-Urban,ML Engineer,78034,0 +10025,Female,42,Bachelors,4,92,68,56,71,6.0,5,1,Urban,ML Engineer,55928,0 +10026,Male,34,High School,5,14,31,41,3,9.0,0,77,Urban,ML Engineer,112526,0 +10027,Female,42,Bachelors,8,82,80,24,51,0.0,0,56,Rural,Data Analyst,29801,1 +10028,Female,26,Bachelors,7,89,36,72,95,1.0,2,13,Urban,ML Engineer,109267,0 +10029,Female,46,High School,15,33,47,52,52,5.0,7,39,Urban,Manager,33785,0 +10030,Female,23,Bachelors,19,23,6,8,70,0.0,6,29,Urban,Manager,62591,0 +10031,Male,22,Bachelors,5,26,96,24,67,0.0,7,74,Urban,Data Analyst,111881,0 +10032,Other,58,Masters,4,67,5,10,3,1.0,4,55,Rural,Software Engineer,57297,0 +10033,Female,55,Bachelors,17,73,56,85,90,3.0,7,73,Urban,HR Executive,109043,1 +10034,Female,44,Masters,11,36,82,8,17,6.0,3,63,Rural,ML Engineer,36958,0 +10035,Female,43,Bachelors,10,73,35,10,87,5.0,5,43,Rural,Data Analyst,119937,0 +10036,Male,32,Masters,15,12,93,26,22,7.0,4,88,Urban,HR Executive,126489,0 +10037,Female,24,Bachelors,15,75,18,26,30,6.0,2,41,Urban,ML Engineer,20573,0 +10038,Male,50,Bachelors,11,7,99,86,20,3.0,0,36,Rural,Software Engineer,128315,0 +10039,Male,32,Bachelors,3,21,57,80,59,0.0,5,5,Rural,ML Engineer,128213,0 +10040,Male,51,Masters,14,45,89,6,81,8.0,2,43,Semi-Urban,Software Engineer,57946,0 +10041,Female,34,Bachelors,0,1,82,4,10,2.0,1,3,Semi-Urban,Software Engineer,94772,0 +10042,Male,52,Bachelors,2,76,88,47,70,2.0,6,95,Urban,Manager,55243,1 +10043,Male,51,High School,5,79,93,28,16,5.0,7,65,Urban,ML Engineer,108677,1 +10044,Male,21,High School,18,97,68,98,22,1.0,6,67,Semi-Urban,Data Analyst,33868,1 +10045,Female,57,Bachelors,5,26,75,49,95,2.0,3,20,Semi-Urban,Manager,100539,0 +10046,Female,41,Diploma,8,50,1,75,98,3.0,3,19,Urban,Data Analyst,126955,0 +10047,Male,27,Bachelors,5,89,73,84,49,7.0,1,47,Semi-Urban,HR Executive,115941,1 +10048,Male,36,Diploma,18,31,98,93,13,1.0,0,9,Semi-Urban,Data Analyst,87958,0 +10049,Female,38,Diploma,6,14,97,33,3,9.0,7,92,Semi-Urban,ML Engineer,103084,0 +10050,Other,41,PhD,14,72,18,41,58,2.0,7,77,Rural,HR Executive,117295,0 +10051,Female,28,Diploma,12,86,58,94,34,5.0,1,36,Rural,Manager,41382,1 +10052,Male,57,Bachelors,0,70,66,66,36,8.0,6,29,Semi-Urban,Software Engineer,132731,0 +10053,Female,41,Bachelors,5,5,20,53,2,7.0,2,67,Urban,Manager,108668,0 +10054,Male,30,Masters,12,92,64,37,33,9.0,5,23,Rural,HR Executive,26482,0 +10055,Male,27,Masters,7,17,44,57,93,2.0,7,91,Semi-Urban,Data Analyst,112872,0 +10056,Male,56,High School,10,31,62,91,33,0.0,4,52,Urban,Data Analyst,123387,1 +10057,Male,55,Bachelors,15,69,0,70,3,6.0,4,99,Urban,ML Engineer,106365,1 +10058,Female,26,Masters,15,90,73,29,22,9.0,4,47,Urban,HR Executive,34012,0 +10059,Male,49,Bachelors,6,81,1,77,58,6.0,6,48,Urban,HR Executive,80109,0 +10060,Male,56,High School,1,68,51,15,55,7.0,3,74,Rural,Data Analyst,35020,0 +10061,Male,21,Bachelors,7,69,95,30,10,1.0,4,23,Urban,Data Analyst,139235,0 +10062,Male,35,Diploma,5,20,67,9,31,5.0,0,94,Semi-Urban,HR Executive,55045,0 +10063,Male,33,PhD,10,95,67,65,28,6.0,0,10,Urban,HR Executive,38327,1 +10064,Male,29,Bachelors,14,27,31,48,14,5.0,0,65,Urban,ML Engineer,30179,0 +10065,Male,56,Diploma,17,89,33,82,24,2.0,2,68,Urban,Software Engineer,93879,1 +10066,Female,32,Bachelors,2,20,14,68,4,8.0,0,43,Urban,Software Engineer,41561,0 +10067,Female,29,High School,17,89,80,41,59,9.0,7,83,Rural,Software Engineer,86804,1 +10068,Female,27,Masters,19,6,99,66,28,7.0,0,35,Semi-Urban,Software Engineer,79235,0 +10069,Male,33,High School,3,84,20,94,57,9.0,6,10,Semi-Urban,Software Engineer,113662,0 +10070,Female,37,Masters,3,85,20,77,45,5.0,1,92,Urban,Software Engineer,86108,1 +10071,Female,25,Bachelors,12,6,7,99,12,2.0,2,10,Urban,HR Executive,35047,0 +10072,Female,26,Masters,8,38,92,14,66,1.0,5,7,Semi-Urban,Data Analyst,111136,0 +10073,Female,47,Diploma,17,32,0,18,77,3.0,4,71,Rural,ML Engineer,112389,0 +10074,Male,58,Diploma,13,13,97,33,90,5.0,2,64,Semi-Urban,Data Analyst,122553,0 +10075,Other,28,Diploma,6,47,41,53,5,2.0,5,42,Semi-Urban,HR Executive,59304,0 +10076,Male,21,High School,1,55,98,72,65,1.0,2,91,Semi-Urban,Manager,131329,1 +10077,Male,55,High School,13,97,17,40,27,2.0,2,51,Urban,Software Engineer,90968,0 +10078,Male,21,Bachelors,6,65,98,17,62,7.0,0,35,Urban,HR Executive,56910,0 +10079,Male,34,Bachelors,4,49,30,43,88,1.0,5,40,Urban,HR Executive,76112,0 +10080,Other,41,Bachelors,15,15,25,13,74,4.0,0,76,Urban,ML Engineer,81144,0 +10081,Male,38,Masters,7,35,4,78,71,6.0,2,45,Urban,Data Analyst,117150,0 +10082,Male,47,Bachelors,6,0,98,49,39,9.0,0,57,Semi-Urban,ML Engineer,69170,0 +10083,Female,32,High School,12,41,23,53,91,4.0,4,73,Rural,Data Analyst,102894,0 +10084,Male,55,Masters,5,60,38,14,12,0.0,5,32,Semi-Urban,Manager,40842,0 +10085,Male,58,Bachelors,4,33,32,42,7,6.0,0,18,Semi-Urban,Data Analyst,20133,0 +10086,Female,56,High School,7,24,79,1,93,5.0,1,73,Semi-Urban,ML Engineer,103972,0 +10087,Female,28,Bachelors,6,48,2,29,93,3.0,0,93,Urban,ML Engineer,97859,0 +10088,Male,59,Bachelors,0,58,56,99,52,9.0,0,67,Rural,Manager,102879,1 +10089,Female,27,Bachelors,17,8,18,89,50,7.0,4,76,Urban,Data Analyst,84268,0 +10090,Male,23,Bachelors,0,48,12,4,70,5.0,1,29,Urban,ML Engineer,132963,0 +10091,Male,28,Masters,17,78,48,88,98,7.0,1,7,Semi-Urban,Data Analyst,57759,0 +10092,Male,50,Diploma,6,85,64,65,6,3.0,3,37,Urban,HR Executive,29278,1 +10093,Male,48,Bachelors,2,45,48,96,93,0.0,2,55,Urban,Manager,95473,1 +10094,Female,24,Diploma,17,33,72,50,59,0.0,4,92,Urban,Software Engineer,124535,1 +10095,Female,23,Bachelors,15,34,75,81,20,3.0,2,1,Urban,Data Analyst,137689,0 +10096,Male,39,Bachelors,5,26,39,53,54,4.0,5,56,Urban,Software Engineer,44860,0 +10097,Male,39,Bachelors,19,70,71,4,99,1.0,0,93,Semi-Urban,HR Executive,77332,1 +10098,Female,41,Bachelors,10,67,40,2,0,0.0,7,66,Urban,Manager,100303,0 +10099,Male,25,Diploma,8,2,5,44,63,4.0,2,5,Urban,Software Engineer,50990,0 +10100,Male,51,PhD,18,39,43,23,8,2.0,7,35,Semi-Urban,HR Executive,129579,0 +10101,Other,45,Bachelors,14,92,66,13,86,4.0,4,18,Semi-Urban,ML Engineer,89906,0 +10102,Female,49,Bachelors,17,12,5,87,37,7.0,2,57,Rural,ML Engineer,54520,0 +10103,Other,37,PhD,13,42,41,8,23,6.0,3,54,Semi-Urban,Data Analyst,74699,0 +10104,Male,41,Diploma,8,54,61,7,80,2.0,5,99,Semi-Urban,Manager,23372,0 +10105,Female,22,Diploma,8,18,71,0,25,0.0,2,27,Urban,Data Analyst,29506,0 +10106,Male,32,Bachelors,4,9,1,97,52,7.0,1,80,Urban,HR Executive,75625,0 +10107,Male,23,Masters,4,14,11,34,61,7.0,1,85,Semi-Urban,Manager,94029,0 +10108,Male,56,PhD,14,56,19,13,68,9.0,4,44,Semi-Urban,Software Engineer,103323,0 +10109,Male,49,Bachelors,18,46,7,62,98,5.0,3,9,Urban,Software Engineer,133668,0 +10110,Male,47,Bachelors,18,87,58,47,6,8.0,4,92,Semi-Urban,HR Executive,128868,1 +10111,Male,35,Masters,17,33,22,66,77,8.0,1,76,Urban,Software Engineer,28758,0 +10112,Male,32,Masters,13,77,78,47,9,3.0,3,36,Urban,HR Executive,32811,1 +10113,Female,54,Masters,15,5,98,22,73,6.0,3,39,Urban,HR Executive,42969,0 +10114,Male,24,Masters,4,40,78,70,77,2.0,1,74,Urban,Software Engineer,107264,1 +10115,Male,36,PhD,2,31,84,20,69,9.0,0,20,Rural,ML Engineer,97668,0 +10116,Male,57,Bachelors,19,71,60,26,73,0.0,7,58,Semi-Urban,Data Analyst,130600,0 +10117,Male,57,Masters,6,17,57,30,3,9.0,3,60,Urban,HR Executive,46183,0 +10118,Female,30,Bachelors,2,58,61,25,31,4.0,5,3,Urban,Data Analyst,138671,0 +10119,Male,38,Diploma,0,86,60,7,84,2.0,4,31,Semi-Urban,HR Executive,90215,0 +10120,Female,37,Bachelors,7,19,38,22,32,9.0,3,89,Urban,Data Analyst,24869,0 +10121,Male,27,Bachelors,16,31,86,95,0,1.0,3,48,Semi-Urban,HR Executive,110959,1 +10122,Male,23,High School,5,15,38,35,38,1.0,1,10,Urban,ML Engineer,55702,0 +10123,Female,57,Bachelors,12,82,73,78,4,7.0,2,34,Urban,Software Engineer,52332,1 +10124,Female,54,High School,15,15,35,2,52,0.0,4,38,Rural,ML Engineer,33420,0 +10125,Male,41,Bachelors,17,6,69,57,41,2.0,7,48,Rural,ML Engineer,28803,0 +10126,Female,27,Bachelors,2,84,29,86,24,5.0,1,64,Semi-Urban,ML Engineer,114059,1 +10127,Male,43,High School,15,76,42,74,84,3.0,2,13,Urban,Manager,33125,0 +10128,Female,24,Masters,4,7,19,17,21,9.0,2,16,Urban,Data Analyst,60545,0 +10129,Female,43,Masters,5,14,51,45,49,6.0,2,89,Semi-Urban,Manager,51759,0 +10130,Female,50,Bachelors,2,54,53,22,67,0.0,7,81,Semi-Urban,HR Executive,89332,0 +10131,Other,31,Bachelors,7,35,49,42,59,1.0,5,14,Rural,Manager,20095,0 +10132,Male,45,Masters,8,30,80,3,59,0.0,1,40,Urban,Manager,110405,0 +10133,Female,31,Bachelors,17,94,97,75,22,0.0,4,75,Semi-Urban,HR Executive,51005,1 +10134,Male,30,Bachelors,11,80,41,97,37,9.0,5,49,Urban,HR Executive,140417,1 +10135,Male,24,Masters,11,41,61,80,95,6.0,2,85,Semi-Urban,HR Executive,141682,1 +10136,Male,26,Masters,11,22,73,57,30,5.0,4,28,Semi-Urban,ML Engineer,93734,0 +10137,Male,52,High School,19,91,60,66,3,1.0,4,87,Semi-Urban,Manager,30938,1 +10138,Female,24,Bachelors,2,73,9,71,4,5.0,2,34,Semi-Urban,HR Executive,74527,0 +10139,Male,29,Masters,14,36,10,99,68,5.0,4,2,Urban,Data Analyst,106568,0 +10140,Male,30,High School,8,5,29,67,51,2.0,0,86,Semi-Urban,ML Engineer,90604,0 +10141,Male,48,Bachelors,7,73,26,3,20,7.0,2,36,Semi-Urban,Manager,138841,0 +10142,Male,33,Bachelors,10,65,28,28,17,4.0,7,15,Urban,Software Engineer,92614,0 +10143,Female,52,Bachelors,7,91,47,52,50,5.0,6,91,Urban,Manager,53563,1 +10144,Male,58,PhD,6,48,80,9,11,8.0,3,29,Rural,Data Analyst,29131,0 +10145,Female,37,Masters,14,44,27,91,39,0.0,6,0,Urban,ML Engineer,141953,0 +10146,Female,38,Bachelors,0,94,41,72,81,0.0,4,72,Urban,Manager,79735,1 +10147,Female,27,Diploma,16,50,0,41,38,8.0,6,24,Rural,Manager,39591,0 +10148,Male,34,Bachelors,12,27,13,31,37,9.0,5,7,Semi-Urban,Software Engineer,33377,0 +10149,Female,52,Diploma,11,51,84,34,33,6.0,4,89,Urban,Data Analyst,24167,1 +10150,Male,30,Bachelors,11,80,86,85,75,7.0,3,66,Semi-Urban,ML Engineer,121127,1 +10151,Female,47,Bachelors,11,98,63,48,69,2.0,0,38,Semi-Urban,Data Analyst,79520,1 +10152,Male,26,Bachelors,8,8,35,3,94,0.0,1,5,Rural,Manager,81778,0 +10153,Male,21,Masters,4,26,61,54,97,0.0,6,43,Rural,Data Analyst,145554,0 +10154,Male,53,Bachelors,2,77,96,32,52,4.0,1,36,Rural,Software Engineer,55926,1 +10155,Female,30,Masters,17,14,59,13,15,7.0,2,21,Rural,HR Executive,109827,0 +10156,Male,38,Bachelors,15,56,41,8,32,8.0,7,42,Urban,Software Engineer,93572,0 +10157,Male,36,Bachelors,11,38,36,19,34,1.0,7,41,Semi-Urban,HR Executive,149028,0 +10158,Male,31,High School,8,15,3,28,13,0.0,4,39,Rural,Data Analyst,70364,0 +10159,Female,39,Bachelors,0,20,46,91,81,1.0,6,64,Urban,Data Analyst,127334,0 +10160,Female,48,Bachelors,12,37,56,79,74,5.0,4,86,Urban,HR Executive,125889,1 +10161,Male,21,High School,0,99,58,21,27,9.0,4,22,Urban,Data Analyst,74635,0 +10162,Female,58,Bachelors,12,53,29,10,91,9.0,0,96,Urban,Software Engineer,137627,0 +10163,Male,44,High School,11,1,78,42,64,0.0,6,9,Urban,HR Executive,105670,0 +10164,Male,51,Diploma,10,40,31,4,25,1.0,5,24,Semi-Urban,ML Engineer,89579,0 +10165,Female,51,Diploma,8,90,59,49,83,8.0,4,29,Urban,ML Engineer,47811,0 +10166,Male,31,Bachelors,7,14,61,39,36,9.0,1,61,Urban,Software Engineer,50064,0 +10167,Male,33,High School,1,9,95,92,79,5.0,5,47,Semi-Urban,HR Executive,114858,1 +10168,Male,58,Bachelors,6,33,49,78,38,7.0,2,20,Rural,HR Executive,37707,0 +10169,Male,24,Diploma,0,84,74,35,11,8.0,7,55,Urban,Software Engineer,77052,1 +10170,Male,45,Masters,12,80,60,37,58,7.0,7,19,Rural,HR Executive,77593,0 +10171,Male,37,Bachelors,17,67,91,35,66,3.0,4,83,Urban,HR Executive,35990,1 +10172,Male,26,Masters,11,18,20,1,10,3.0,7,4,Urban,Software Engineer,104200,0 +10173,Male,44,Masters,5,82,2,2,82,1.0,1,28,Urban,Manager,130480,0 +10174,Male,56,High School,3,22,41,23,63,4.0,1,36,Urban,Data Analyst,86001,0 +10175,Male,47,PhD,19,86,38,74,50,5.0,6,26,Rural,Data Analyst,54639,0 +10176,Male,29,High School,14,14,94,45,61,4.0,1,98,Urban,ML Engineer,25376,1 +10177,Female,35,Bachelors,5,32,26,62,34,1.0,4,22,Urban,Manager,125724,0 +10178,Male,38,Bachelors,14,43,0,39,99,5.0,1,86,Urban,ML Engineer,54454,0 +10179,Female,45,Bachelors,4,80,44,94,26,8.0,6,64,Urban,ML Engineer,97791,1 +10180,Female,34,Bachelors,10,34,19,13,29,3.0,7,92,Urban,Manager,40704,0 +10181,Female,27,High School,9,90,74,84,19,5.0,6,27,Urban,ML Engineer,85575,1 +10182,Male,49,Diploma,16,31,64,90,86,4.0,1,18,Semi-Urban,ML Engineer,108161,0 +10183,Male,22,Masters,15,35,57,77,67,2.0,1,61,Rural,Manager,147573,0 +10184,Male,59,Masters,4,15,39,68,70,1.0,6,39,Rural,HR Executive,120518,0 +10185,Female,24,Bachelors,14,97,51,84,45,7.0,7,80,Rural,HR Executive,126353,1 +10186,Male,28,Diploma,6,45,99,14,98,6.0,0,86,Urban,Manager,40491,1 +10187,Female,28,Bachelors,7,79,7,44,62,6.0,4,59,Urban,Manager,79768,0 +10188,Female,43,Bachelors,12,41,28,78,68,8.0,6,15,Semi-Urban,HR Executive,66440,0 +10189,Male,48,Masters,9,16,55,23,14,3.0,0,1,Urban,Manager,107363,0 +10190,Male,54,High School,12,26,24,94,81,0.0,4,14,Urban,Data Analyst,20352,0 +10191,Female,24,High School,19,91,70,63,48,6.0,3,30,Rural,Software Engineer,60658,1 +10192,Male,44,High School,8,10,31,80,41,8.0,1,34,Semi-Urban,ML Engineer,84098,0 +10193,Male,28,Masters,14,65,30,85,68,3.0,1,33,Urban,ML Engineer,143984,0 +10194,Female,21,Bachelors,2,88,31,16,69,6.0,7,54,Urban,Manager,128860,0 +10195,Male,36,Bachelors,13,99,98,86,43,9.0,5,15,Urban,HR Executive,86175,1 +10196,Female,51,High School,12,85,48,88,20,7.0,1,80,Urban,HR Executive,69415,1 +10197,Female,44,Diploma,1,75,59,95,74,5.0,4,47,Urban,Manager,96121,1 +10198,Female,46,Bachelors,14,47,52,59,64,8.0,4,23,Rural,HR Executive,137916,0 +10199,Male,32,Masters,8,48,1,38,64,8.0,5,11,Urban,Manager,72768,0 +10200,Male,38,Bachelors,17,84,10,1,61,3.0,1,28,Rural,HR Executive,121837,0 +10201,Male,35,Bachelors,19,45,99,63,94,1.0,7,24,Urban,Data Analyst,44127,0 +10202,Male,56,Diploma,11,30,61,18,71,3.0,2,8,Urban,HR Executive,130805,0 +10203,Male,46,Masters,13,3,66,57,93,2.0,1,28,Urban,Software Engineer,115722,0 +10204,Male,58,Bachelors,14,46,93,7,61,8.0,3,39,Urban,Software Engineer,116318,0 +10205,Male,30,Diploma,1,40,49,9,82,2.0,3,73,Urban,Manager,84222,0 +10206,Male,44,Masters,18,65,86,91,36,2.0,0,67,Semi-Urban,Data Analyst,46115,1 +10207,Female,41,High School,11,64,49,51,8,9.0,3,29,Rural,Data Analyst,75841,0 +10208,Male,27,Bachelors,18,4,45,29,38,3.0,4,75,Rural,HR Executive,91634,0 +10209,Male,26,Diploma,3,19,6,75,51,9.0,7,70,Urban,Manager,61171,0 +10210,Female,53,Bachelors,4,62,15,62,97,7.0,1,13,Urban,Data Analyst,91431,0 +10211,Other,41,Masters,8,35,28,55,34,8.0,6,5,Rural,Data Analyst,94344,0 +10212,Male,41,Diploma,3,53,98,91,40,9.0,7,68,Urban,Manager,144594,1 +10213,Male,29,Diploma,10,67,36,83,45,1.0,4,55,Urban,Software Engineer,76556,1 +10214,Male,50,Bachelors,18,7,92,20,63,7.0,7,97,Semi-Urban,HR Executive,59623,0 +10215,Female,48,Masters,12,75,14,72,91,0.0,6,8,Semi-Urban,HR Executive,126766,0 +10216,Female,41,Bachelors,19,53,33,40,6,4.0,7,24,Semi-Urban,HR Executive,121200,0 +10217,Female,30,High School,16,7,8,17,2,1.0,4,94,Urban,ML Engineer,137926,0 +10218,Male,27,Masters,9,20,88,26,13,1.0,3,79,Semi-Urban,Software Engineer,77387,0 +10219,Male,43,Diploma,11,15,72,39,39,4.0,1,24,Urban,ML Engineer,34894,0 +10220,Male,58,Bachelors,7,84,78,68,33,6.0,7,61,Urban,ML Engineer,44213,1 +10221,Female,45,Bachelors,17,43,91,92,43,4.0,3,77,Urban,Manager,44009,1 +10222,Female,35,High School,3,75,51,23,59,8.0,0,4,Urban,Data Analyst,90720,0 +10223,Other,47,Diploma,19,43,19,86,49,0.0,0,60,Rural,ML Engineer,117257,0 +10224,Male,23,Masters,8,64,4,42,73,8.0,0,32,Urban,HR Executive,49438,0 +10225,Male,59,Masters,6,64,23,28,71,1.0,6,31,Semi-Urban,ML Engineer,107811,0 +10226,Male,38,Bachelors,16,53,10,0,17,2.0,3,81,Rural,ML Engineer,29631,0 +10227,Female,29,Bachelors,4,35,60,94,65,9.0,1,89,Semi-Urban,HR Executive,127541,1 +10228,Female,25,Bachelors,16,77,81,0,3,4.0,4,34,Semi-Urban,Data Analyst,58768,0 +10229,Male,45,High School,16,3,75,74,2,2.0,6,35,Rural,ML Engineer,97597,0 +10230,Male,35,Bachelors,2,89,28,70,16,6.0,2,99,Urban,Data Analyst,105950,1 +10231,Male,35,High School,13,46,71,65,97,7.0,1,91,Urban,ML Engineer,59000,1 +10232,Male,36,Diploma,4,31,37,64,22,9.0,0,98,Semi-Urban,Data Analyst,112960,0 +10233,Female,58,Masters,12,29,42,74,56,6.0,0,4,Semi-Urban,Data Analyst,131774,0 +10234,Male,44,Diploma,7,33,80,99,66,9.0,0,84,Semi-Urban,Data Analyst,116850,1 +10235,Female,57,Diploma,0,1,9,84,69,5.0,1,32,Rural,ML Engineer,119358,0 +10236,Male,34,Diploma,2,72,38,64,94,3.0,2,72,Urban,Software Engineer,106017,1 +10237,Female,51,Bachelors,10,58,66,31,86,8.0,5,22,Urban,Data Analyst,26993,0 +10238,Male,51,Masters,14,17,33,38,68,7.0,6,53,Urban,HR Executive,121441,0 +10239,Female,41,Bachelors,14,37,91,86,67,5.0,0,14,Urban,ML Engineer,79632,0 +10240,Male,42,Diploma,7,84,25,22,12,6.0,5,82,Urban,Software Engineer,118409,0 +10241,Male,41,High School,17,22,2,1,29,6.0,0,31,Semi-Urban,HR Executive,128560,0 +10242,Male,53,Diploma,7,54,58,55,40,8.0,0,91,Urban,Manager,78579,1 +10243,Male,53,Diploma,17,55,45,90,78,0.0,5,64,Urban,Manager,28474,1 +10244,Male,56,Diploma,3,28,0,55,55,3.0,5,39,Semi-Urban,Software Engineer,149885,0 +10245,Male,51,High School,11,41,35,97,48,5.0,4,82,Urban,HR Executive,59918,1 +10246,Other,36,Masters,10,44,33,76,2,2.0,2,39,Urban,HR Executive,77560,0 +10247,Male,50,Diploma,10,83,19,36,95,3.0,0,64,Rural,ML Engineer,146798,0 +10248,Female,36,Bachelors,0,5,82,65,47,1.0,1,64,Urban,HR Executive,57748,0 +10249,Other,31,Diploma,9,68,43,6,62,6.0,1,79,Semi-Urban,Data Analyst,60016,0 +10250,Male,56,Diploma,17,70,14,77,62,2.0,7,71,Urban,Software Engineer,87902,0 +10251,Female,57,Masters,13,49,46,87,4,4.0,1,46,Rural,HR Executive,68652,0 +10252,Male,46,Diploma,18,54,0,29,77,8.0,5,34,Semi-Urban,Software Engineer,55197,0 +10253,Male,57,PhD,11,6,7,23,59,6.0,1,52,Rural,Data Analyst,104957,0 +10254,Male,32,High School,11,82,23,54,81,9.0,6,28,Rural,Data Analyst,35264,0 +10255,Female,24,Bachelors,11,37,57,13,47,8.0,4,67,Semi-Urban,Manager,49938,0 +10256,Male,43,Diploma,3,54,93,73,56,5.0,3,47,Urban,Manager,139142,1 +10257,Male,53,Bachelors,11,56,21,98,73,8.0,6,60,Semi-Urban,Manager,96825,1 +10258,Male,57,Bachelors,10,6,18,72,37,7.0,7,14,Urban,HR Executive,94870,0 +10259,Female,43,Bachelors,10,37,51,45,86,8.0,0,69,Urban,HR Executive,71375,0 +10260,Male,52,Bachelors,18,83,57,47,85,5.0,4,29,Rural,HR Executive,43647,0 +10261,Female,39,Diploma,6,51,62,27,88,0.0,0,25,Urban,ML Engineer,117525,0 +10262,Female,40,Masters,13,49,51,6,26,2.0,1,22,Semi-Urban,Manager,94907,0 +10263,Female,27,Masters,19,77,3,81,10,0.0,6,99,Semi-Urban,Data Analyst,81302,1 +10264,Female,52,Diploma,9,55,62,27,20,7.0,2,45,Urban,ML Engineer,64244,0 +10265,Female,27,Bachelors,13,63,81,29,61,0.0,4,19,Urban,ML Engineer,33987,0 +10266,Male,26,Masters,18,59,87,81,72,7.0,4,23,Semi-Urban,Data Analyst,129099,1 +10267,Male,52,Bachelors,5,92,31,18,73,8.0,0,47,Rural,Software Engineer,111206,0 +10268,Male,29,High School,3,56,97,27,27,4.0,4,51,Urban,Software Engineer,95518,0 +10269,Male,46,High School,5,9,22,4,1,2.0,0,41,Urban,ML Engineer,132265,0 +10270,Male,47,Bachelors,10,95,57,38,0,4.0,1,98,Urban,Manager,26889,1 +10271,Male,38,Bachelors,12,72,4,34,65,3.0,6,53,Urban,ML Engineer,44749,0 +10272,Male,44,Masters,4,19,21,12,92,2.0,3,15,Rural,Software Engineer,42573,0 +10273,Other,55,PhD,17,50,62,42,66,9.0,1,76,Rural,Manager,63317,0 +10274,Male,44,Bachelors,10,47,18,58,80,5.0,4,27,Rural,Data Analyst,39866,0 +10275,Female,40,Masters,3,42,41,24,94,5.0,3,1,Rural,Software Engineer,55587,0 +10276,Male,36,Bachelors,3,26,22,67,11,9.0,5,66,Rural,Manager,122156,0 +10277,Female,39,Masters,12,94,30,63,16,6.0,5,91,Rural,Data Analyst,46667,1 +10278,Female,29,High School,3,6,1,58,33,1.0,4,73,Urban,Software Engineer,99684,0 +10279,Male,37,Masters,12,80,76,33,53,4.0,2,59,Urban,Software Engineer,64818,1 +10280,Male,30,Bachelors,14,30,63,20,12,9.0,6,24,Semi-Urban,Manager,122636,0 +10281,Male,23,Bachelors,11,49,0,43,79,4.0,6,83,Semi-Urban,Software Engineer,118513,0 +10282,Male,38,Masters,18,79,15,7,53,4.0,1,68,Rural,HR Executive,59095,0 +10283,Female,31,Bachelors,4,24,82,43,26,8.0,7,12,Urban,Manager,105282,0 +10284,Female,47,Bachelors,13,53,15,16,29,2.0,1,84,Urban,Data Analyst,117396,0 +10285,Male,24,Diploma,8,70,1,34,48,9.0,4,8,Rural,Software Engineer,149662,0 +10286,Male,55,Masters,10,65,41,29,72,9.0,3,4,Rural,HR Executive,122285,0 +10287,Male,22,Diploma,19,30,97,42,30,8.0,6,80,Semi-Urban,HR Executive,63638,1 +10288,Male,30,Diploma,17,44,12,65,57,2.0,1,79,Rural,Manager,70665,0 +10289,Female,40,Masters,0,98,71,29,2,5.0,4,57,Rural,ML Engineer,71151,1 +10290,Male,51,Bachelors,1,51,88,51,60,9.0,1,85,Semi-Urban,Software Engineer,35950,1 +10291,Male,57,High School,14,58,7,98,20,9.0,2,63,Urban,Software Engineer,66546,0 +10292,Male,37,Bachelors,19,79,46,79,78,8.0,4,69,Rural,Software Engineer,60283,1 +10293,Male,47,High School,18,42,30,2,1,5.0,7,32,Urban,Data Analyst,42640,0 +10294,Female,25,Masters,6,53,75,48,65,0.0,3,53,Semi-Urban,Data Analyst,124509,0 +10295,Male,38,PhD,5,79,47,40,15,6.0,3,69,Semi-Urban,Manager,96652,1 +10296,Other,40,High School,3,2,64,37,94,4.0,3,13,Urban,Software Engineer,29616,0 +10297,Female,25,Bachelors,15,75,68,36,91,3.0,0,80,Urban,Manager,81822,1 +10298,Male,58,Bachelors,16,92,15,68,20,2.0,4,31,Urban,Manager,26316,0 +10299,Male,39,Masters,17,68,48,24,80,5.0,6,70,Rural,HR Executive,94552,0 +10300,Female,29,Masters,18,55,13,77,5,7.0,0,42,Rural,HR Executive,122390,0 +10301,Female,38,Diploma,16,53,10,51,43,3.0,7,39,Urban,Manager,82202,0 +10302,Female,57,Bachelors,3,20,50,42,91,6.0,5,48,Urban,HR Executive,93936,0 +10303,Male,23,Masters,15,44,12,45,19,1.0,3,95,Urban,Data Analyst,124837,0 +10304,Other,48,Bachelors,18,13,44,57,66,2.0,5,39,Semi-Urban,Manager,108683,0 +10305,Male,23,Masters,19,66,10,9,35,7.0,2,37,Rural,Software Engineer,101282,0 +10306,Female,33,Diploma,9,94,51,19,34,1.0,5,94,Urban,HR Executive,89717,1 +10307,Female,32,Bachelors,4,9,1,49,81,2.0,6,29,Semi-Urban,Data Analyst,135091,0 +10308,Male,25,Diploma,13,62,48,78,18,2.0,7,67,Urban,Manager,98832,1 +10309,Female,36,Bachelors,8,22,64,19,85,5.0,3,18,Urban,Data Analyst,98625,0 +10310,Male,39,Masters,18,53,73,47,21,1.0,0,6,Urban,Data Analyst,90606,0 +10311,Other,29,Bachelors,13,27,93,22,93,4.0,1,73,Semi-Urban,Software Engineer,61532,0 +10312,Male,47,High School,1,28,36,17,48,6.0,3,9,Rural,Data Analyst,75970,0 +10313,Other,30,Bachelors,18,89,12,29,95,7.0,7,17,Semi-Urban,Data Analyst,144620,0 +10314,Male,45,Bachelors,19,8,8,22,48,0.0,4,59,Urban,Software Engineer,81084,0 +10315,Female,32,Bachelors,1,50,32,93,31,0.0,0,54,Semi-Urban,Data Analyst,69595,0 +10316,Male,29,Bachelors,12,59,73,77,45,7.0,4,72,Semi-Urban,ML Engineer,40502,1 +10317,Male,47,Diploma,12,11,0,9,31,0.0,4,13,Semi-Urban,HR Executive,96545,0 +10318,Male,58,Bachelors,10,43,98,28,68,0.0,3,30,Urban,Software Engineer,70525,0 +10319,Female,46,Bachelors,19,9,95,44,62,4.0,3,49,Urban,Manager,46209,0 +10320,Male,53,High School,2,24,72,98,22,5.0,0,32,Semi-Urban,Manager,53908,0 +10321,Male,48,PhD,5,74,23,8,23,5.0,7,25,Semi-Urban,ML Engineer,32457,0 +10322,Male,37,High School,11,9,92,91,67,4.0,6,74,Semi-Urban,Manager,136549,1 +10323,Other,39,Masters,7,77,28,36,24,0.0,1,0,Semi-Urban,Software Engineer,93470,0 +10324,Male,45,Bachelors,1,2,25,16,55,8.0,3,57,Urban,Software Engineer,79233,0 +10325,Male,43,Masters,13,8,87,95,85,0.0,4,92,Urban,Manager,33022,1 +10326,Male,39,High School,15,55,70,83,91,0.0,4,62,Rural,HR Executive,91466,1 +10327,Male,36,High School,13,29,39,18,46,0.0,7,8,Semi-Urban,HR Executive,139005,0 +10328,Male,45,Bachelors,4,45,58,48,13,5.0,4,43,Urban,HR Executive,126929,0 +10329,Male,37,High School,1,17,15,1,29,2.0,4,70,Rural,HR Executive,119910,0 +10330,Female,33,Diploma,2,55,22,9,83,2.0,3,50,Semi-Urban,ML Engineer,141843,0 +10331,Female,29,Masters,10,85,35,3,79,4.0,5,38,Urban,Data Analyst,92895,0 +10332,Male,48,Diploma,16,34,91,76,44,5.0,5,63,Urban,Manager,147172,1 +10333,Male,51,Bachelors,7,2,0,55,68,9.0,3,21,Urban,Manager,78486,0 +10334,Female,27,Diploma,6,5,69,81,53,5.0,5,8,Urban,Software Engineer,99780,0 +10335,Male,27,PhD,4,83,96,87,9,3.0,3,98,Urban,Software Engineer,96954,1 +10336,Female,56,Bachelors,13,32,23,80,10,8.0,4,76,Rural,Data Analyst,22741,0 +10337,Male,29,Bachelors,19,74,24,13,99,5.0,0,74,Semi-Urban,Software Engineer,64457,0 +10338,Male,39,High School,15,81,92,29,11,9.0,2,91,Semi-Urban,Data Analyst,47366,1 +10339,Male,32,Bachelors,19,85,80,10,47,1.0,5,74,Urban,HR Executive,46572,1 +10340,Female,56,Bachelors,10,87,83,2,83,5.0,5,99,Urban,HR Executive,93322,1 +10341,Male,47,Bachelors,2,5,33,54,43,5.0,5,43,Semi-Urban,Manager,142181,0 +10342,Male,54,Diploma,12,23,2,50,70,7.0,0,77,Semi-Urban,Software Engineer,118688,0 +10343,Male,46,Diploma,4,38,75,55,79,0.0,2,75,Urban,HR Executive,63513,1 +10344,Female,58,Masters,19,83,61,71,27,0.0,3,27,Urban,ML Engineer,133343,1 +10345,Female,42,Masters,10,84,46,18,32,5.0,3,80,Rural,Data Analyst,77046,0 +10346,Male,41,Masters,7,9,13,72,0,5.0,2,63,Semi-Urban,HR Executive,29640,0 +10347,Male,27,Diploma,6,8,9,57,60,8.0,1,54,Urban,HR Executive,146031,0 +10348,Female,58,Diploma,12,5,24,78,45,4.0,5,40,Semi-Urban,ML Engineer,101905,0 +10349,Male,27,Bachelors,6,80,33,26,96,3.0,3,87,Urban,Software Engineer,124770,0 +10350,Male,51,Bachelors,10,3,23,38,38,2.0,6,46,Urban,Manager,108204,0 +10351,Male,57,High School,13,13,63,24,96,8.0,0,51,Urban,HR Executive,136605,0 +10352,Female,34,Diploma,17,15,48,76,74,3.0,1,88,Urban,Data Analyst,120496,0 +10353,Male,52,Bachelors,7,53,70,62,82,0.0,0,43,Urban,Software Engineer,76819,0 +10354,Female,46,High School,11,73,45,93,82,0.0,4,92,Semi-Urban,Manager,32469,1 +10355,Male,28,Bachelors,12,60,93,56,53,6.0,2,91,Urban,HR Executive,70171,1 +10356,Male,34,Bachelors,18,95,43,39,47,3.0,1,22,Urban,ML Engineer,123292,0 +10357,Female,35,Diploma,15,44,7,96,97,0.0,3,35,Urban,Manager,119766,0 +10358,Male,37,Bachelors,19,11,36,52,33,4.0,6,71,Semi-Urban,Manager,20074,0 +10359,Male,38,High School,8,73,43,98,66,6.0,2,22,Urban,Software Engineer,62034,1 +10360,Female,46,Masters,9,49,86,26,95,1.0,1,41,Urban,Manager,55687,0 +10361,Female,36,Bachelors,15,34,18,74,15,4.0,7,71,Urban,HR Executive,59104,0 +10362,Female,58,Masters,13,86,88,52,19,8.0,4,62,Urban,ML Engineer,95194,1 +10363,Other,58,Masters,16,95,8,84,23,2.0,5,80,Urban,Manager,117982,1 +10364,Female,25,High School,6,89,84,70,38,7.0,7,32,Urban,Software Engineer,119813,1 +10365,Male,57,Masters,1,94,85,93,85,9.0,0,89,Urban,HR Executive,84782,1 +10366,Male,38,Masters,0,52,66,96,7,0.0,6,18,Urban,HR Executive,110095,0 +10367,Female,52,High School,3,12,26,80,70,5.0,1,14,Urban,Manager,32991,0 +10368,Male,35,Diploma,5,16,78,22,99,8.0,7,38,Urban,Software Engineer,55666,0 +10369,Female,46,Bachelors,13,54,13,80,78,9.0,4,37,Semi-Urban,ML Engineer,53110,0 +10370,Female,23,Bachelors,17,46,29,53,74,4.0,3,91,Urban,Manager,132550,0 +10371,Male,21,Bachelors,17,61,26,84,17,7.0,3,72,Urban,Software Engineer,57698,1 +10372,Female,37,Bachelors,1,48,28,11,80,7.0,0,28,Semi-Urban,Manager,148950,0 +10373,Male,30,Bachelors,8,82,2,58,53,4.0,4,14,Urban,HR Executive,82848,0 +10374,Male,35,Masters,2,53,40,92,44,3.0,1,30,Urban,HR Executive,121794,0 +10375,Other,58,Diploma,18,77,32,28,63,6.0,2,51,Semi-Urban,ML Engineer,85800,0 +10376,Male,23,Masters,10,70,3,94,65,2.0,6,0,Urban,HR Executive,26188,0 +10377,Male,37,Masters,18,12,78,29,35,7.0,0,68,Urban,Data Analyst,134438,0 +10378,Male,25,High School,7,67,77,72,67,2.0,5,91,Urban,Manager,66588,1 +10379,Female,50,High School,8,19,79,66,46,5.0,6,22,Rural,Software Engineer,144527,0 +10380,Female,40,Diploma,18,79,15,30,77,7.0,1,44,Rural,Software Engineer,83971,0 +10381,Female,37,Bachelors,8,63,11,11,30,4.0,5,46,Urban,Software Engineer,37568,0 +10382,Female,30,High School,18,88,12,93,53,8.0,3,50,Rural,ML Engineer,32707,1 +10383,Male,25,Diploma,6,48,73,7,1,8.0,2,9,Urban,ML Engineer,80314,0 +10384,Female,26,Bachelors,4,99,18,30,94,8.0,5,90,Rural,HR Executive,42325,0 +10385,Female,47,Bachelors,19,1,52,56,78,2.0,7,53,Semi-Urban,HR Executive,115383,0 +10386,Male,43,Bachelors,19,63,10,33,83,1.0,7,87,Urban,Manager,122697,0 +10387,Male,51,High School,7,3,89,27,20,5.0,2,61,Semi-Urban,Software Engineer,104520,0 +10388,Other,37,Bachelors,5,49,58,40,85,3.0,6,67,Semi-Urban,Manager,129026,0 +10389,Female,26,Masters,7,92,41,56,35,5.0,0,69,Semi-Urban,HR Executive,143967,1 +10390,Female,58,Bachelors,0,55,95,18,78,9.0,6,2,Semi-Urban,ML Engineer,95354,0 +10391,Female,59,Diploma,5,9,92,68,67,0.0,7,13,Rural,HR Executive,40688,0 +10392,Male,21,Bachelors,7,19,46,45,65,9.0,2,67,Semi-Urban,Software Engineer,93143,0 +10393,Female,57,Bachelors,3,2,64,98,62,6.0,4,7,Rural,Data Analyst,119086,0 +10394,Male,32,High School,9,2,10,58,66,4.0,7,83,Semi-Urban,ML Engineer,148368,0 +10395,Male,25,Bachelors,2,76,31,17,93,9.0,3,22,Urban,Manager,45295,0 +10396,Female,23,Bachelors,9,96,10,15,32,0.0,5,62,Urban,HR Executive,73890,0 +10397,Male,59,Diploma,5,41,53,38,32,0.0,1,68,Rural,Data Analyst,20125,0 +10398,Female,23,Bachelors,11,43,31,24,7,7.0,5,38,Urban,Software Engineer,75477,0 +10399,Male,24,Diploma,7,44,32,37,52,0.0,2,34,Urban,Data Analyst,49157,0 +10400,Male,25,Diploma,1,90,3,53,98,6.0,0,81,Rural,Software Engineer,122241,0 +10401,Male,43,Diploma,10,25,6,21,83,1.0,7,8,Urban,Software Engineer,51926,0 +10402,Male,56,Bachelors,13,78,32,38,21,6.0,7,54,Urban,Software Engineer,43765,0 +10403,Male,29,Diploma,13,65,96,17,94,1.0,5,18,Semi-Urban,ML Engineer,123565,0 +10404,Male,36,Bachelors,8,79,96,81,51,3.0,2,20,Rural,HR Executive,52854,1 +10405,Other,51,Diploma,11,64,79,23,33,7.0,5,75,Urban,Manager,121244,1 +10406,Male,40,Bachelors,8,29,44,15,66,6.0,6,48,Urban,ML Engineer,134460,0 +10407,Male,52,High School,7,82,91,21,80,0.0,2,54,Urban,ML Engineer,131072,1 +10408,Male,49,Diploma,7,42,56,56,69,0.0,0,49,Urban,Manager,83075,0 +10409,Female,30,Bachelors,11,44,27,66,26,7.0,3,16,Semi-Urban,Data Analyst,142868,0 +10410,Male,57,Diploma,18,54,36,75,41,8.0,5,72,Rural,Data Analyst,138198,1 +10411,Female,46,High School,0,20,84,28,97,9.0,1,11,Urban,HR Executive,77765,0 +10412,Female,26,Bachelors,15,61,36,27,14,7.0,7,7,Semi-Urban,HR Executive,21911,0 +10413,Male,30,Bachelors,8,23,5,20,3,5.0,5,16,Urban,Software Engineer,138690,0 +10414,Male,38,High School,1,22,4,83,39,6.0,2,0,Semi-Urban,Software Engineer,83330,0 +10415,Female,35,Diploma,14,60,40,93,3,7.0,5,39,Urban,Data Analyst,138056,0 +10416,Female,41,Masters,14,83,29,27,86,3.0,6,58,Semi-Urban,ML Engineer,126216,0 +10417,Female,32,Masters,15,76,24,50,60,9.0,1,0,Urban,HR Executive,87365,0 +10418,Male,34,Bachelors,7,55,6,26,40,0.0,1,46,Urban,ML Engineer,122540,0 +10419,Male,54,High School,4,34,92,41,51,6.0,0,8,Urban,Software Engineer,146761,0 +10420,Male,42,Masters,7,7,19,5,55,5.0,6,61,Urban,HR Executive,72329,0 +10421,Male,45,Masters,6,40,70,21,58,2.0,3,67,Urban,Data Analyst,47266,0 +10422,Male,53,Masters,9,46,39,20,82,8.0,2,2,Urban,ML Engineer,108916,0 +10423,Female,56,Bachelors,13,1,89,4,98,6.0,2,55,Semi-Urban,Software Engineer,114915,0 +10424,Male,21,Bachelors,16,21,13,85,34,8.0,1,7,Urban,Software Engineer,135956,0 +10425,Female,26,Bachelors,10,81,98,26,44,0.0,2,25,Rural,Data Analyst,55267,0 +10426,Female,40,Bachelors,9,26,22,92,55,4.0,4,1,Semi-Urban,HR Executive,119307,0 +10427,Male,26,Bachelors,8,39,45,28,85,1.0,0,21,Semi-Urban,Software Engineer,144793,0 +10428,Female,47,Bachelors,12,88,18,9,96,7.0,2,33,Urban,Data Analyst,119277,0 +10429,Male,31,High School,7,68,35,45,57,8.0,2,77,Rural,ML Engineer,33729,0 +10430,Female,44,Diploma,4,10,35,70,3,1.0,6,25,Semi-Urban,Software Engineer,114983,0 +10431,Male,40,Diploma,3,54,94,16,45,6.0,4,55,Urban,HR Executive,94703,0 +10432,Male,43,Bachelors,15,8,12,3,59,5.0,6,61,Rural,Software Engineer,70512,0 +10433,Female,25,Masters,8,55,63,77,31,6.0,7,86,Semi-Urban,Manager,60285,1 +10434,Male,51,High School,4,42,26,31,7,0.0,2,92,Urban,HR Executive,44645,0 +10435,Female,23,Diploma,13,84,51,74,77,3.0,1,88,Rural,Data Analyst,51247,1 +10436,Male,51,Masters,7,37,52,35,52,8.0,5,43,Urban,HR Executive,89197,0 +10437,Male,49,High School,5,90,87,87,56,5.0,3,4,Urban,Software Engineer,36802,1 +10438,Male,54,Masters,3,18,80,24,64,4.0,6,49,Semi-Urban,Software Engineer,103947,0 +10439,Male,51,Masters,2,44,6,61,21,4.0,1,85,Urban,Software Engineer,130887,0 +10440,Male,33,Diploma,4,62,49,86,18,5.0,2,8,Urban,ML Engineer,141548,0 +10441,Female,43,Bachelors,13,29,93,76,78,5.0,5,97,Rural,HR Executive,110966,1 +10442,Female,31,High School,7,16,72,19,93,8.0,1,88,Rural,Manager,101507,0 +10443,Female,45,Bachelors,11,74,40,60,79,7.0,3,54,Rural,Manager,135011,0 +10444,Other,50,Diploma,11,23,6,59,71,6.0,1,52,Urban,HR Executive,62838,0 +10445,Male,37,PhD,8,35,9,22,79,8.0,1,7,Urban,Data Analyst,45056,0 +10446,Female,41,High School,0,72,92,96,19,6.0,5,75,Urban,ML Engineer,135602,1 +10447,Male,22,Bachelors,12,57,47,69,2,0.0,5,5,Urban,Data Analyst,115136,0 +10448,Female,36,Bachelors,1,22,75,64,27,0.0,6,44,Rural,Software Engineer,68797,0 +10449,Male,42,Bachelors,17,94,69,41,19,2.0,5,52,Urban,Manager,85071,1 +10450,Other,37,High School,7,13,64,12,89,1.0,3,3,Urban,ML Engineer,98928,0 +10451,Female,55,Masters,4,95,25,44,79,2.0,2,26,Semi-Urban,ML Engineer,141526,0 +10452,Other,22,Masters,16,14,23,92,85,4.0,2,70,Urban,ML Engineer,136578,0 +10453,Female,45,Bachelors,12,4,80,18,38,5.0,6,94,Semi-Urban,HR Executive,101956,0 +10454,Female,46,Masters,18,25,31,97,62,3.0,4,48,Semi-Urban,HR Executive,74822,0 +10455,Female,51,Diploma,8,74,56,33,80,1.0,0,73,Urban,Data Analyst,80863,0 +10456,Male,53,Diploma,16,23,85,46,84,3.0,6,18,Urban,ML Engineer,31896,0 +10457,Male,38,Masters,18,75,72,85,0,1.0,5,52,Urban,Manager,62234,1 +10458,Male,44,Diploma,7,79,50,82,67,4.0,0,79,Urban,Data Analyst,85539,1 +10459,Male,34,Bachelors,8,0,48,36,65,5.0,7,71,Urban,HR Executive,79137,0 +10460,Male,44,Diploma,19,39,0,83,14,6.0,4,79,Urban,Software Engineer,36987,0 +10461,Male,25,High School,19,0,52,20,28,1.0,7,37,Urban,Software Engineer,66531,0 +10462,Male,46,Bachelors,6,3,4,20,14,6.0,5,69,Urban,HR Executive,98264,0 +10463,Other,22,High School,5,20,72,23,69,6.0,1,27,Urban,HR Executive,135840,0 +10464,Female,32,Bachelors,12,41,54,40,65,9.0,5,1,Rural,HR Executive,69486,0 +10465,Male,55,High School,13,13,84,33,91,4.0,6,7,Rural,Data Analyst,25109,0 +10466,Male,55,Bachelors,14,7,4,60,78,2.0,5,58,Semi-Urban,ML Engineer,123791,0 +10467,Male,49,Bachelors,14,71,51,61,97,1.0,1,25,Urban,Data Analyst,81062,0 +10468,Male,52,Masters,7,14,12,77,49,2.0,1,80,Urban,Data Analyst,30061,0 +10469,Female,50,Masters,2,72,63,62,72,0.0,0,57,Urban,HR Executive,84341,1 +10470,Male,36,Bachelors,1,8,99,94,48,5.0,1,18,Semi-Urban,HR Executive,45107,0 +10471,Male,58,PhD,1,95,12,25,21,3.0,2,60,Urban,Data Analyst,29668,0 +10472,Female,22,Diploma,11,9,1,50,79,8.0,7,64,Semi-Urban,Manager,132652,0 +10473,Female,38,Diploma,16,35,89,31,3,0.0,6,63,Urban,Data Analyst,93763,0 +10474,Male,29,Masters,4,92,89,17,36,1.0,7,8,Semi-Urban,Manager,111269,0 +10475,Female,21,High School,9,0,57,18,15,0.0,0,55,Semi-Urban,ML Engineer,60517,0 +10476,Male,42,Bachelors,9,39,30,19,18,2.0,5,58,Semi-Urban,Manager,133724,0 +10477,Male,41,Bachelors,12,5,71,53,78,7.0,5,69,Semi-Urban,ML Engineer,141976,0 +10478,Male,38,Masters,2,92,41,79,88,9.0,6,55,Urban,HR Executive,22829,1 +10479,Male,47,Bachelors,3,34,50,82,49,1.0,4,75,Urban,Data Analyst,48293,1 +10480,Male,37,High School,10,2,99,16,89,9.0,5,95,Urban,ML Engineer,71470,0 +10481,Male,30,Bachelors,7,7,20,68,45,2.0,6,47,Urban,ML Engineer,45035,0 +10482,Female,51,Masters,6,11,38,10,18,4.0,5,95,Urban,Data Analyst,74062,0 +10483,Female,46,Diploma,6,99,46,49,10,9.0,1,20,Urban,ML Engineer,78043,0 +10484,Male,24,Bachelors,14,70,13,32,2,8.0,7,74,Urban,Software Engineer,99441,0 +10485,Male,36,Bachelors,14,83,19,8,50,4.0,0,54,Urban,HR Executive,90087,0 +10486,Female,31,Bachelors,13,87,63,8,86,5.0,4,27,Urban,Data Analyst,31076,0 +10487,Male,21,Masters,9,87,84,21,10,6.0,1,20,Rural,Data Analyst,89721,0 +10488,Female,55,Diploma,6,35,88,81,67,8.0,2,66,Urban,Data Analyst,104547,1 +10489,Female,35,High School,1,45,54,70,84,3.0,5,33,Urban,Manager,101815,0 +10490,Male,52,PhD,15,78,19,7,22,2.0,6,7,Semi-Urban,Software Engineer,42809,0 +10491,Male,30,Bachelors,11,6,28,59,99,3.0,3,16,Urban,Data Analyst,20940,0 +10492,Male,26,Bachelors,13,17,7,32,14,4.0,2,25,Semi-Urban,Software Engineer,87263,0 +10493,Male,43,Masters,5,36,99,97,71,1.0,0,31,Urban,Software Engineer,62912,1 +10494,Male,46,Diploma,14,77,73,88,15,5.0,0,74,Rural,Manager,40354,1 +10495,Female,25,Bachelors,15,63,85,41,82,9.0,6,13,Semi-Urban,Manager,20965,0 +10496,Male,44,Masters,4,50,7,37,17,6.0,0,62,Semi-Urban,Software Engineer,95616,0 +10497,Male,33,Masters,10,14,5,87,87,4.0,1,47,Urban,Software Engineer,67235,0 +10498,Male,34,Masters,1,25,48,88,26,1.0,0,69,Urban,HR Executive,140976,0 +10499,Male,39,Bachelors,19,33,18,20,56,3.0,7,18,Semi-Urban,ML Engineer,92005,0 +10500,Male,22,Bachelors,7,8,60,10,84,0.0,3,63,Urban,HR Executive,51602,0 +10501,Male,46,Bachelors,4,50,73,18,16,2.0,3,24,Rural,ML Engineer,97890,0 +10502,Male,51,Bachelors,15,87,67,97,65,4.0,4,31,Urban,HR Executive,146168,1 +10503,Female,51,Bachelors,5,47,7,41,32,3.0,1,81,Rural,ML Engineer,60946,0 +10504,Male,40,Bachelors,0,79,54,35,37,9.0,5,22,Semi-Urban,Data Analyst,33673,0 +10505,Female,47,Diploma,10,23,65,16,6,6.0,3,71,Semi-Urban,HR Executive,62021,0 +10506,Male,39,Bachelors,6,90,72,38,64,4.0,5,14,Rural,Software Engineer,105607,0 +10507,Male,48,Masters,1,96,50,80,20,1.0,1,66,Semi-Urban,Software Engineer,134353,1 +10508,Male,34,Bachelors,1,8,65,23,73,9.0,3,22,Urban,Data Analyst,44746,0 +10509,Female,26,Masters,8,61,39,31,83,8.0,6,77,Semi-Urban,ML Engineer,28994,0 +10510,Male,32,High School,10,22,73,50,14,9.0,0,88,Semi-Urban,Software Engineer,129892,0 +10511,Male,27,Diploma,12,52,45,49,44,2.0,2,82,Semi-Urban,Data Analyst,49065,0 +10512,Male,36,Bachelors,14,89,34,99,23,5.0,7,75,Urban,HR Executive,28554,1 +10513,Male,59,Bachelors,19,3,4,90,98,7.0,3,83,Urban,HR Executive,82836,0 +10514,Male,39,Masters,14,26,93,83,52,0.0,1,27,Rural,Software Engineer,98173,0 +10515,Female,55,Masters,12,87,8,34,17,0.0,3,19,Urban,Data Analyst,129981,0 +10516,Male,51,Bachelors,17,29,55,58,10,0.0,3,61,Rural,Software Engineer,73237,0 +10517,Female,58,Diploma,19,33,52,12,7,6.0,4,24,Semi-Urban,Manager,97214,0 +10518,Male,28,Masters,7,57,33,85,55,8.0,6,10,Rural,Software Engineer,141974,0 +10519,Female,30,Masters,11,36,50,49,10,4.0,0,30,Semi-Urban,ML Engineer,54132,0 +10520,Female,37,Masters,11,45,58,90,45,3.0,7,1,Semi-Urban,Data Analyst,64311,0 +10521,Male,58,High School,16,38,5,27,48,6.0,1,50,Rural,Data Analyst,118747,0 +10522,Female,50,Diploma,9,19,0,31,15,1.0,7,65,Urban,HR Executive,97999,0 +10523,Female,40,High School,16,59,87,23,16,0.0,4,97,Urban,ML Engineer,71355,1 +10524,Male,57,High School,3,8,47,24,19,4.0,3,14,Semi-Urban,Manager,114396,0 +10525,Male,47,High School,16,52,50,72,9,0.0,4,16,Rural,HR Executive,25517,0 +10526,Female,48,Masters,3,66,85,1,90,3.0,4,29,Urban,Software Engineer,134423,0 +10527,Male,22,Bachelors,10,67,40,51,68,6.0,4,14,Semi-Urban,Software Engineer,25883,0 +10528,Male,44,Masters,0,60,58,52,51,0.0,4,39,Urban,Manager,118287,0 +10529,Female,51,Masters,14,16,11,13,82,0.0,6,8,Rural,Data Analyst,95834,0 +10530,Male,22,High School,10,19,46,20,9,8.0,3,15,Urban,HR Executive,85044,0 +10531,Female,48,Bachelors,19,26,83,87,72,2.0,5,39,Urban,Data Analyst,49610,0 +10532,Female,57,Diploma,15,50,74,93,57,6.0,2,89,Semi-Urban,HR Executive,140802,1 +10533,Other,52,PhD,0,45,68,9,87,9.0,5,7,Urban,Data Analyst,138567,0 +10534,Male,27,Masters,9,34,96,76,47,0.0,7,2,Rural,Data Analyst,44576,0 +10535,Male,30,Bachelors,3,83,43,14,96,2.0,4,1,Urban,Data Analyst,96854,0 +10536,Male,24,PhD,10,61,49,36,93,0.0,3,94,Semi-Urban,Data Analyst,124817,1 +10537,Male,39,Bachelors,17,82,22,11,40,9.0,1,82,Urban,Data Analyst,95481,0 +10538,Male,33,Diploma,7,25,8,61,60,6.0,4,72,Semi-Urban,HR Executive,26907,0 +10539,Male,51,Masters,6,77,68,24,1,0.0,5,74,Semi-Urban,HR Executive,59687,1 +10540,Male,56,Masters,12,30,81,83,34,3.0,1,71,Urban,Manager,98645,1 +10541,Male,51,Bachelors,19,34,9,80,23,3.0,5,97,Urban,HR Executive,146733,0 +10542,Female,43,High School,19,29,16,5,2,2.0,2,45,Urban,Software Engineer,81322,0 +10543,Female,51,Bachelors,12,23,9,62,91,0.0,7,17,Urban,ML Engineer,139864,0 +10544,Female,36,Masters,6,26,17,2,61,3.0,4,28,Urban,HR Executive,43482,0 +10545,Female,42,Diploma,17,30,86,51,42,9.0,0,64,Urban,Manager,131686,0 +10546,Male,29,Masters,17,75,88,2,46,8.0,1,77,Semi-Urban,HR Executive,110030,1 +10547,Other,41,High School,1,71,31,23,53,5.0,7,87,Semi-Urban,Software Engineer,108997,0 +10548,Female,21,Bachelors,8,33,98,71,57,2.0,0,47,Rural,HR Executive,108501,1 +10549,Male,35,Diploma,15,83,25,10,51,9.0,4,38,Urban,HR Executive,37192,0 +10550,Male,27,Bachelors,10,68,34,93,37,8.0,1,35,Rural,Software Engineer,95567,0 +10551,Male,47,High School,18,29,52,0,43,8.0,0,95,Urban,Manager,86275,0 +10552,Male,53,Diploma,6,16,52,63,42,9.0,4,18,Semi-Urban,Data Analyst,29932,0 +10553,Male,38,Bachelors,15,59,79,82,60,8.0,0,44,Urban,HR Executive,124377,1 +10554,Male,26,High School,0,57,69,0,22,0.0,5,34,Urban,ML Engineer,34485,0 +10555,Female,44,Bachelors,10,74,65,84,88,4.0,3,31,Semi-Urban,ML Engineer,47858,1 +10556,Male,46,Bachelors,16,94,14,37,38,5.0,4,50,Semi-Urban,Software Engineer,141338,0 +10557,Male,28,Bachelors,5,45,3,20,16,3.0,3,30,Urban,HR Executive,96991,0 +10558,Female,27,Diploma,0,12,93,11,22,6.0,3,0,Urban,Software Engineer,91214,0 +10559,Male,54,High School,5,2,54,75,79,4.0,6,33,Semi-Urban,Software Engineer,128116,0 +10560,Other,50,Diploma,5,53,45,96,92,5.0,4,46,Rural,Manager,102874,0 +10561,Male,41,PhD,10,50,22,1,72,1.0,5,43,Urban,Data Analyst,41084,0 +10562,Other,32,High School,16,37,51,75,75,1.0,6,83,Semi-Urban,HR Executive,94746,1 +10563,Male,35,Masters,6,74,57,37,95,1.0,2,73,Urban,Software Engineer,149853,1 +10564,Male,40,Diploma,11,1,53,17,19,9.0,3,46,Urban,Software Engineer,59730,0 +10565,Male,54,Diploma,18,1,27,54,46,1.0,1,62,Urban,HR Executive,135003,0 +10566,Female,32,Masters,18,47,89,98,43,9.0,7,41,Urban,Software Engineer,131668,1 +10567,Female,26,Bachelors,5,18,14,51,45,2.0,4,71,Urban,HR Executive,31536,0 +10568,Male,55,High School,10,44,67,29,25,6.0,3,77,Urban,Software Engineer,148710,0 +10569,Female,48,High School,19,74,67,78,82,2.0,2,30,Semi-Urban,ML Engineer,137563,1 +10570,Male,45,High School,6,72,12,37,58,4.0,6,56,Semi-Urban,ML Engineer,59439,0 +10571,Female,59,Bachelors,4,9,2,4,2,6.0,5,21,Urban,ML Engineer,131829,0 +10572,Female,25,Bachelors,9,68,58,30,81,9.0,4,7,Urban,HR Executive,37104,0 +10573,Male,44,Masters,2,74,17,26,96,8.0,6,82,Urban,Data Analyst,122132,0 +10574,Male,49,Bachelors,12,50,16,81,92,3.0,2,95,Urban,Manager,34719,1 +10575,Female,49,Bachelors,2,33,26,40,4,8.0,7,9,Urban,HR Executive,25632,0 +10576,Female,32,PhD,2,9,49,97,0,0.0,4,21,Urban,Manager,137909,0 +10577,Other,28,High School,2,20,22,62,97,2.0,7,81,Rural,Manager,60421,0 +10578,Female,22,Diploma,15,28,7,81,48,0.0,3,55,Semi-Urban,Data Analyst,101715,0 +10579,Male,51,High School,0,26,57,51,66,3.0,3,65,Semi-Urban,Data Analyst,36434,0 +10580,Female,22,Bachelors,2,13,5,96,15,9.0,4,90,Urban,ML Engineer,148510,0 +10581,Male,37,PhD,13,89,32,77,1,1.0,5,38,Urban,Software Engineer,96178,1 +10582,Other,41,High School,9,71,37,28,79,8.0,0,14,Urban,Manager,46058,0 +10583,Male,32,Masters,12,54,95,16,48,5.0,7,76,Semi-Urban,Software Engineer,114065,1 +10584,Male,23,Diploma,6,15,91,47,69,7.0,6,83,Urban,Manager,39496,1 +10585,Male,23,Masters,15,17,80,23,20,9.0,6,32,Urban,Data Analyst,118940,0 +10586,Male,45,Diploma,7,81,17,74,24,8.0,3,64,Urban,Manager,65722,1 +10587,Male,44,Masters,0,81,81,99,95,8.0,5,64,Urban,Data Analyst,96493,1 +10588,Female,51,Masters,11,29,41,30,65,3.0,5,20,Semi-Urban,ML Engineer,78142,0 +10589,Female,23,High School,10,88,73,3,79,5.0,0,86,Semi-Urban,Data Analyst,125514,1 +10590,Male,30,Diploma,8,5,54,17,13,4.0,2,98,Urban,HR Executive,120649,0 +10591,Female,48,Bachelors,16,32,55,49,92,9.0,2,21,Urban,ML Engineer,20487,0 +10592,Female,53,Diploma,1,47,86,99,45,0.0,2,35,Semi-Urban,HR Executive,50814,1 +10593,Male,42,Diploma,2,16,1,58,78,1.0,7,14,Rural,Software Engineer,87781,0 +10594,Male,37,PhD,6,25,86,23,71,9.0,1,63,Urban,HR Executive,128641,0 +10595,Female,24,Bachelors,17,57,87,52,77,8.0,1,81,Rural,Data Analyst,48684,1 +10596,Female,38,Bachelors,19,61,31,11,86,0.0,6,63,Urban,Software Engineer,103392,0 +10597,Male,42,Bachelors,17,12,37,86,63,0.0,3,61,Rural,ML Engineer,22159,0 +10598,Female,25,Bachelors,6,53,79,86,14,9.0,3,1,Semi-Urban,Software Engineer,103934,0 +10599,Male,36,High School,6,82,16,9,20,3.0,7,13,Semi-Urban,Data Analyst,38021,0 +10600,Male,32,PhD,10,95,89,34,50,6.0,5,34,Rural,ML Engineer,88998,1 +10601,Male,54,PhD,1,58,29,40,96,1.0,6,42,Rural,ML Engineer,135261,0 +10602,Male,25,Bachelors,8,31,44,1,48,1.0,7,48,Semi-Urban,Data Analyst,133439,0 +10603,Female,23,Masters,17,8,4,47,94,5.0,3,10,Urban,ML Engineer,130767,0 +10604,Female,52,Bachelors,1,61,14,54,76,4.0,6,14,Urban,HR Executive,131413,0 +10605,Male,21,Bachelors,19,93,1,58,17,3.0,7,40,Semi-Urban,Manager,75987,0 +10606,Male,22,Bachelors,15,6,66,35,38,2.0,4,72,Urban,HR Executive,96695,0 +10607,Female,55,Bachelors,0,14,49,50,58,4.0,2,15,Urban,Software Engineer,119000,0 +10608,Female,28,Masters,16,23,7,74,77,5.0,2,67,Semi-Urban,Data Analyst,82800,0 +10609,Female,23,Masters,19,0,99,82,75,0.0,3,1,Semi-Urban,Data Analyst,58449,0 +10610,Female,44,Diploma,11,35,19,22,97,2.0,1,26,Urban,Data Analyst,46854,0 +10611,Male,57,Masters,2,83,41,10,24,7.0,5,57,Rural,Software Engineer,47681,0 +10612,Female,44,Diploma,9,7,36,77,45,5.0,6,6,Rural,Manager,41202,0 +10613,Male,43,High School,4,83,68,7,92,9.0,2,92,Urban,Data Analyst,84569,1 +10614,Male,42,Bachelors,6,59,85,4,9,2.0,3,38,Urban,Data Analyst,111070,0 +10615,Male,22,Masters,8,75,73,46,82,5.0,3,56,Semi-Urban,Manager,56642,1 +10616,Male,33,PhD,5,50,84,17,13,9.0,3,3,Urban,Manager,70711,0 +10617,Female,29,High School,11,75,95,50,15,0.0,6,0,Urban,HR Executive,99401,0 +10618,Female,43,Diploma,17,96,77,65,59,9.0,4,15,Urban,Software Engineer,71785,1 +10619,Male,45,Diploma,8,46,88,2,64,6.0,4,56,Urban,Software Engineer,57130,0 +10620,Male,42,Diploma,8,7,90,19,44,0.0,6,92,Urban,ML Engineer,103195,0 +10621,Male,54,Bachelors,18,46,10,13,88,4.0,1,77,Semi-Urban,Manager,82609,0 +10622,Male,40,High School,2,99,66,66,27,2.0,0,97,Semi-Urban,ML Engineer,68471,1 +10623,Female,37,Masters,2,31,64,18,33,3.0,2,35,Urban,Software Engineer,73335,0 +10624,Female,48,Bachelors,6,0,58,97,71,5.0,7,99,Semi-Urban,Data Analyst,21731,1 +10625,Other,35,High School,14,89,15,35,33,9.0,1,21,Rural,Data Analyst,46060,0 +10626,Female,34,Bachelors,18,26,23,21,25,2.0,6,27,Urban,Data Analyst,22799,0 +10627,Female,29,High School,13,1,84,75,70,8.0,2,80,Semi-Urban,HR Executive,134899,0 +10628,Male,26,Bachelors,3,97,48,77,98,6.0,2,59,Semi-Urban,Manager,86063,1 +10629,Male,42,Masters,3,51,42,89,64,5.0,5,74,Urban,Data Analyst,112017,1 +10630,Male,21,Bachelors,10,57,60,95,31,3.0,7,41,Urban,Data Analyst,29120,1 +10631,Male,58,Masters,14,7,81,85,41,3.0,2,58,Semi-Urban,Manager,58021,0 +10632,Female,52,Bachelors,11,5,81,66,73,0.0,6,38,Urban,ML Engineer,134445,0 +10633,Male,45,Masters,18,47,68,83,4,3.0,2,77,Urban,ML Engineer,139840,1 +10634,Male,47,High School,3,33,91,59,23,0.0,1,16,Urban,ML Engineer,133652,0 +10635,Male,35,High School,19,68,43,23,59,4.0,7,8,Semi-Urban,ML Engineer,125927,0 +10636,Other,53,High School,19,29,91,39,97,7.0,6,92,Semi-Urban,Data Analyst,58040,1 +10637,Male,51,High School,7,86,28,27,11,5.0,1,13,Rural,Manager,118460,0 +10638,Female,25,High School,10,94,68,8,27,2.0,3,22,Urban,HR Executive,102757,0 +10639,Female,53,Diploma,10,62,16,55,62,9.0,0,90,Semi-Urban,ML Engineer,103613,0 +10640,Male,35,Bachelors,15,39,13,80,28,8.0,1,82,Urban,ML Engineer,66476,0 +10641,Male,49,Diploma,0,77,44,83,33,0.0,1,88,Urban,Software Engineer,28682,1 +10642,Female,56,Masters,4,7,30,44,17,0.0,7,13,Urban,ML Engineer,134992,0 +10643,Male,34,Bachelors,4,67,29,55,94,7.0,1,12,Urban,HR Executive,117574,0 +10644,Female,40,Diploma,8,16,73,94,3,2.0,0,50,Urban,Manager,117418,0 +10645,Male,49,Diploma,6,37,31,58,19,7.0,4,23,Urban,ML Engineer,21504,0 +10646,Male,27,Masters,17,26,71,16,3,5.0,7,45,Urban,Manager,73136,0 +10647,Female,23,Bachelors,4,56,98,42,30,6.0,5,37,Rural,ML Engineer,85826,0 +10648,Female,30,Diploma,19,10,32,59,50,9.0,3,80,Urban,Software Engineer,50204,0 +10649,Other,43,Bachelors,11,69,25,68,59,2.0,4,71,Urban,Software Engineer,93640,0 +10650,Female,56,Bachelors,7,1,3,11,22,5.0,1,59,Urban,Manager,75718,0 +10651,Female,45,High School,7,99,66,21,15,6.0,1,90,Semi-Urban,Manager,79270,1 +10652,Female,52,Masters,5,42,85,73,28,1.0,6,87,Urban,Data Analyst,48898,1 +10653,Female,36,Bachelors,2,51,58,41,9,3.0,0,40,Rural,Software Engineer,26801,0 +10654,Male,32,Bachelors,7,61,98,91,86,6.0,2,74,Urban,Software Engineer,59150,1 +10655,Male,39,PhD,7,21,91,7,16,7.0,4,35,Urban,Data Analyst,51006,0 +10656,Female,28,Bachelors,0,4,73,87,59,0.0,7,98,Rural,Manager,132812,1 +10657,Male,22,Masters,15,67,30,10,23,4.0,3,42,Urban,HR Executive,88521,0 +10658,Male,26,High School,0,22,63,88,1,1.0,7,2,Urban,Software Engineer,39937,0 +10659,Male,56,High School,7,20,23,21,88,7.0,3,76,Urban,HR Executive,111926,0 +10660,Male,46,High School,10,76,97,37,54,7.0,3,54,Urban,Data Analyst,21852,1 +10661,Male,49,Diploma,12,72,18,25,21,8.0,6,32,Semi-Urban,ML Engineer,58870,0 +10662,Male,24,PhD,17,15,37,60,7,8.0,6,52,Urban,ML Engineer,94843,0 +10663,Female,54,Bachelors,14,74,81,39,95,9.0,1,42,Urban,ML Engineer,115273,0 +10664,Male,47,Bachelors,14,99,97,92,9,1.0,0,47,Urban,Software Engineer,60104,1 +10665,Male,56,Diploma,3,90,44,88,25,4.0,1,11,Semi-Urban,HR Executive,29081,0 +10666,Male,24,Bachelors,5,24,56,31,80,6.0,0,93,Urban,Software Engineer,91984,0 +10667,Male,53,Diploma,17,40,50,91,13,8.0,5,24,Urban,ML Engineer,130320,0 +10668,Male,49,Diploma,19,58,42,88,17,3.0,0,47,Urban,Software Engineer,129247,1 +10669,Female,45,Bachelors,16,6,84,67,77,7.0,5,8,Semi-Urban,ML Engineer,85298,0 +10670,Male,46,Bachelors,8,13,35,34,11,7.0,6,81,Rural,Manager,137475,0 +10671,Female,29,Masters,2,31,65,17,36,9.0,0,60,Urban,ML Engineer,122053,0 +10672,Male,47,Diploma,1,69,58,1,53,2.0,1,83,Semi-Urban,HR Executive,132340,0 +10673,Male,53,PhD,3,97,54,63,61,2.0,5,81,Urban,Software Engineer,145224,1 +10674,Male,27,Bachelors,11,3,27,11,84,7.0,2,42,Urban,HR Executive,84098,0 +10675,Male,52,Diploma,19,20,16,64,54,0.0,2,33,Semi-Urban,Manager,118411,0 +10676,Female,37,Diploma,8,4,64,79,78,2.0,0,10,Urban,Manager,140103,0 +10677,Female,22,Bachelors,5,60,86,25,80,0.0,1,22,Rural,Software Engineer,75148,0 +10678,Female,22,Bachelors,13,87,57,60,84,7.0,0,46,Semi-Urban,Software Engineer,68743,1 +10679,Male,48,Bachelors,18,43,91,43,60,8.0,0,83,Urban,ML Engineer,128565,1 +10680,Male,55,Diploma,0,45,29,40,57,2.0,3,3,Urban,HR Executive,125753,0 +10681,Male,39,Masters,14,14,83,8,51,1.0,5,85,Urban,Data Analyst,138729,0 +10682,Other,56,Bachelors,19,62,93,51,38,1.0,7,76,Urban,Manager,110432,1 +10683,Male,58,Masters,16,38,3,19,60,5.0,4,59,Semi-Urban,Software Engineer,83282,0 +10684,Female,43,Diploma,13,44,90,18,75,3.0,4,86,Semi-Urban,Data Analyst,85292,0 +10685,Male,24,Bachelors,14,48,39,57,73,2.0,2,21,Urban,Manager,31820,0 +10686,Male,46,High School,19,91,97,21,36,1.0,3,49,Semi-Urban,HR Executive,133487,1 +10687,Male,35,Bachelors,11,15,28,69,42,2.0,3,67,Urban,ML Engineer,41926,0 +10688,Male,29,Masters,11,21,41,2,41,9.0,6,68,Urban,HR Executive,61092,0 +10689,Female,54,Masters,7,80,34,27,24,0.0,1,14,Urban,ML Engineer,68580,0 +10690,Male,53,Diploma,10,51,63,72,75,4.0,0,79,Rural,Data Analyst,51040,1 +10691,Female,33,Masters,13,51,35,13,49,8.0,5,28,Urban,Software Engineer,130556,0 +10692,Male,27,High School,19,78,29,72,44,6.0,1,93,Semi-Urban,Data Analyst,126547,1 +10693,Other,27,Bachelors,17,43,39,48,71,0.0,3,15,Urban,Data Analyst,76560,0 +10694,Male,37,Bachelors,16,63,29,84,19,2.0,3,28,Rural,ML Engineer,120757,0 +10695,Female,46,Bachelors,7,87,94,57,55,4.0,5,12,Urban,HR Executive,42195,1 +10696,Female,58,Diploma,8,57,90,98,27,1.0,1,97,Rural,ML Engineer,111157,1 +10697,Other,55,High School,3,78,75,45,9,0.0,2,15,Urban,HR Executive,25771,0 +10698,Male,24,Masters,5,9,93,40,50,9.0,7,21,Semi-Urban,HR Executive,87378,0 +10699,Female,36,Masters,3,66,29,64,82,5.0,4,77,Urban,Data Analyst,29657,0 +10700,Male,52,Diploma,19,29,79,65,3,6.0,6,67,Urban,HR Executive,128046,1 +10701,Male,44,PhD,6,43,64,19,57,7.0,4,60,Semi-Urban,Manager,87476,0 +10702,Male,40,Bachelors,2,40,53,29,27,0.0,5,53,Semi-Urban,Software Engineer,89873,0 +10703,Male,28,Diploma,10,70,1,8,15,6.0,7,66,Urban,Manager,76046,0 +10704,Other,59,Masters,17,96,82,34,84,7.0,0,48,Semi-Urban,HR Executive,122552,1 +10705,Male,23,High School,17,17,1,57,56,9.0,0,12,Urban,HR Executive,60187,0 +10706,Male,28,Masters,7,97,35,43,17,0.0,5,11,Urban,Manager,128908,0 +10707,Female,54,Bachelors,3,72,21,33,6,3.0,1,6,Semi-Urban,HR Executive,148112,0 +10708,Male,34,Diploma,0,61,42,77,33,4.0,3,55,Urban,Manager,55933,1 +10709,Female,40,Masters,15,42,87,46,57,0.0,3,96,Urban,Manager,68700,1 +10710,Male,41,Bachelors,13,99,3,30,2,3.0,1,63,Rural,ML Engineer,49221,0 +10711,Male,57,Bachelors,4,94,77,71,22,0.0,4,82,Urban,ML Engineer,75551,1 +10712,Male,23,Masters,11,71,78,70,4,0.0,3,75,Urban,Manager,104510,1 +10713,Female,29,Bachelors,1,72,81,88,18,5.0,3,47,Urban,ML Engineer,97554,1 +10714,Female,46,Bachelors,0,12,19,99,3,0.0,3,98,Rural,Software Engineer,114816,0 +10715,Other,39,High School,1,22,4,53,44,3.0,2,49,Rural,Software Engineer,148707,0 +10716,Male,37,Bachelors,13,69,62,32,40,8.0,1,40,Urban,Manager,96857,0 +10717,Male,52,High School,8,27,81,72,34,1.0,7,79,Urban,ML Engineer,64417,1 +10718,Male,23,Bachelors,17,24,48,94,16,8.0,6,93,Semi-Urban,Software Engineer,80136,1 +10719,Male,44,PhD,14,89,76,87,97,7.0,0,1,Urban,Software Engineer,66259,1 +10720,Male,32,Bachelors,0,46,37,51,56,0.0,4,4,Urban,HR Executive,75649,0 +10721,Female,36,Bachelors,0,99,76,87,52,1.0,0,99,Urban,Data Analyst,92792,1 +10722,Male,33,High School,15,80,26,67,84,4.0,0,44,Rural,Data Analyst,80549,0 +10723,Male,45,High School,3,74,27,55,11,3.0,6,54,Rural,Manager,108799,0 +10724,Female,50,High School,14,29,46,20,87,3.0,0,75,Urban,ML Engineer,134818,0 +10725,Female,59,Masters,9,11,49,87,53,7.0,7,12,Rural,Data Analyst,102575,0 +10726,Male,33,Bachelors,8,45,9,89,72,1.0,1,81,Urban,Software Engineer,24068,0 +10727,Male,52,Masters,9,57,18,81,98,2.0,3,22,Semi-Urban,Data Analyst,98745,0 +10728,Male,24,Bachelors,0,52,8,80,68,7.0,4,70,Urban,ML Engineer,66533,0 +10729,Male,58,Bachelors,14,80,66,76,85,1.0,0,16,Rural,ML Engineer,53640,1 +10730,Female,25,Masters,6,87,8,3,46,0.0,1,43,Semi-Urban,Data Analyst,87717,0 +10731,Male,47,High School,17,54,81,62,78,7.0,4,66,Urban,HR Executive,27746,1 +10732,Female,30,Bachelors,1,61,0,32,25,4.0,0,81,Urban,Data Analyst,82335,0 +10733,Female,40,Bachelors,17,16,57,40,77,6.0,0,15,Urban,ML Engineer,24251,0 +10734,Female,24,High School,0,65,10,95,69,4.0,4,27,Urban,Software Engineer,95815,0 +10735,Male,30,Bachelors,12,49,90,97,91,3.0,4,56,Urban,HR Executive,106871,1 +10736,Male,21,Bachelors,18,81,82,77,24,0.0,3,56,Urban,Data Analyst,142589,1 +10737,Female,23,PhD,3,22,76,21,17,9.0,7,27,Semi-Urban,ML Engineer,50288,0 +10738,Male,41,High School,18,92,79,48,7,1.0,6,57,Urban,ML Engineer,33658,1 +10739,Male,31,Bachelors,1,19,29,29,74,5.0,4,76,Semi-Urban,Data Analyst,76088,0 +10740,Male,54,Bachelors,15,73,71,68,76,3.0,1,67,Urban,ML Engineer,83960,1 +10741,Male,57,Masters,3,47,53,54,76,9.0,6,14,Semi-Urban,HR Executive,24443,0 +10742,Female,45,Bachelors,16,45,88,40,73,7.0,3,19,Urban,Data Analyst,124648,0 +10743,Male,26,Bachelors,18,30,6,29,2,7.0,1,62,Semi-Urban,Software Engineer,64817,0 +10744,Male,40,Bachelors,8,8,5,0,91,7.0,6,66,Urban,Software Engineer,24141,0 +10745,Male,40,High School,6,47,32,39,85,4.0,0,36,Rural,Data Analyst,120303,0 +10746,Male,58,PhD,4,60,20,57,10,4.0,7,2,Semi-Urban,Data Analyst,56820,0 +10747,Female,54,Diploma,13,0,78,60,68,1.0,7,59,Semi-Urban,HR Executive,36563,0 +10748,Female,27,Bachelors,17,74,30,57,20,7.0,1,70,Urban,Software Engineer,33241,0 +10749,Male,49,Bachelors,4,19,98,4,92,0.0,1,22,Urban,Manager,51072,0 +10750,Male,22,Bachelors,0,61,3,22,33,4.0,1,9,Rural,Software Engineer,54424,0 +10751,Male,24,Bachelors,13,94,36,13,20,2.0,5,14,Rural,Manager,95259,0 +10752,Female,37,Masters,17,37,84,19,60,5.0,0,17,Urban,Data Analyst,37026,0 +10753,Male,41,Diploma,8,83,72,35,38,4.0,3,27,Semi-Urban,Software Engineer,27638,0 +10754,Female,23,Bachelors,5,54,30,24,48,2.0,6,74,Rural,HR Executive,25124,0 +10755,Male,46,Bachelors,8,30,31,9,32,1.0,2,73,Urban,ML Engineer,146269,0 +10756,Female,41,PhD,7,94,83,85,3,8.0,2,51,Semi-Urban,ML Engineer,134404,1 +10757,Male,40,Diploma,0,37,34,57,71,6.0,0,7,Rural,HR Executive,66722,0 +10758,Female,48,Bachelors,16,68,28,95,24,0.0,6,70,Semi-Urban,Manager,67157,1 +10759,Male,27,Bachelors,11,8,81,4,4,4.0,7,28,Semi-Urban,ML Engineer,135970,0 +10760,Female,43,Diploma,7,87,13,67,41,6.0,0,42,Urban,Software Engineer,100516,0 +10761,Male,37,Bachelors,5,39,50,85,71,4.0,1,78,Rural,ML Engineer,141202,1 +10762,Male,51,Masters,12,60,11,42,87,8.0,6,63,Urban,Software Engineer,23578,0 +10763,Female,28,Bachelors,10,80,4,44,78,1.0,2,99,Semi-Urban,ML Engineer,78558,0 +10764,Male,57,Diploma,16,6,14,74,43,8.0,4,23,Rural,ML Engineer,115742,0 +10765,Female,28,Masters,17,76,49,11,89,1.0,7,62,Urban,Manager,131100,0 +10766,Female,33,Diploma,16,53,87,14,90,7.0,2,32,Semi-Urban,ML Engineer,149779,0 +10767,Male,43,Masters,8,37,90,26,91,6.0,6,13,Urban,ML Engineer,129113,0 +10768,Male,35,Diploma,3,53,81,8,17,5.0,4,23,Rural,ML Engineer,44186,0 +10769,Male,45,PhD,17,87,15,23,61,7.0,3,55,Urban,Data Analyst,35311,0 +10770,Male,41,Bachelors,1,73,97,58,96,4.0,5,81,Semi-Urban,Data Analyst,60756,1 +10771,Male,48,Bachelors,6,95,22,40,96,4.0,2,65,Urban,Data Analyst,79509,0 +10772,Female,27,High School,19,36,57,92,36,1.0,3,0,Urban,ML Engineer,56970,0 +10773,Male,45,Masters,14,59,85,54,45,1.0,1,12,Urban,ML Engineer,75432,0 +10774,Male,30,Diploma,15,52,90,80,24,1.0,6,23,Semi-Urban,ML Engineer,121009,1 +10775,Male,47,Bachelors,13,40,29,4,9,5.0,0,87,Urban,HR Executive,24703,0 +10776,Male,38,Masters,19,66,80,5,60,6.0,0,55,Semi-Urban,ML Engineer,82382,0 +10777,Male,50,Bachelors,12,24,6,89,58,1.0,0,12,Urban,ML Engineer,72848,0 +10778,Female,51,PhD,9,81,72,60,67,7.0,2,37,Urban,Software Engineer,49492,1 +10779,Female,35,Masters,0,85,66,76,9,4.0,6,25,Rural,Data Analyst,52632,1 +10780,Male,35,Masters,7,46,46,96,18,8.0,4,20,Urban,HR Executive,100297,0 +10781,Other,24,High School,4,24,9,11,31,3.0,7,83,Semi-Urban,Software Engineer,91675,0 +10782,Male,56,Masters,12,69,49,3,45,2.0,7,71,Urban,Manager,45010,0 +10783,Female,26,Bachelors,14,90,42,28,32,2.0,6,82,Urban,Data Analyst,91579,1 +10784,Female,42,Bachelors,4,50,30,56,68,9.0,6,29,Urban,HR Executive,145172,0 +10785,Female,24,Bachelors,16,45,18,16,9,3.0,5,81,Urban,Software Engineer,32397,0 +10786,Male,43,Bachelors,14,75,1,72,65,0.0,3,37,Semi-Urban,Data Analyst,146100,0 +10787,Male,51,High School,11,66,21,77,66,4.0,1,71,Semi-Urban,Software Engineer,49071,1 +10788,Male,46,Bachelors,15,46,84,76,30,0.0,2,61,Urban,ML Engineer,114132,1 +10789,Female,31,Diploma,1,31,55,55,6,5.0,6,68,Semi-Urban,Manager,145835,0 +10790,Male,41,Bachelors,7,66,55,22,9,5.0,6,14,Urban,ML Engineer,51255,0 +10791,Female,34,Bachelors,19,64,99,44,11,7.0,2,95,Semi-Urban,ML Engineer,144680,1 +10792,Male,47,Bachelors,3,4,23,39,56,2.0,4,64,Urban,HR Executive,113525,0 +10793,Female,30,Bachelors,5,38,51,69,65,6.0,5,93,Rural,Software Engineer,118939,1 +10794,Male,28,Bachelors,11,26,31,77,64,1.0,5,20,Semi-Urban,ML Engineer,46182,0 +10795,Male,24,High School,12,12,89,23,65,1.0,4,56,Rural,ML Engineer,74399,0 +10796,Male,27,Masters,13,41,46,65,67,6.0,4,88,Urban,Manager,90303,1 +10797,Male,49,Bachelors,1,56,28,6,50,1.0,1,77,Rural,ML Engineer,145968,0 +10798,Male,45,Masters,18,1,23,4,9,9.0,4,92,Urban,Manager,108917,0 +10799,Female,58,Diploma,17,20,79,46,66,5.0,5,59,Urban,Manager,71525,0 +10800,Male,21,Bachelors,0,7,46,46,72,7.0,7,74,Urban,Software Engineer,77166,0 +10801,Male,36,Bachelors,19,6,10,53,86,7.0,5,88,Urban,Manager,136817,0 +10802,Female,23,Bachelors,15,11,93,77,21,0.0,6,30,Urban,ML Engineer,31857,0 +10803,Male,53,Bachelors,6,67,54,74,18,5.0,1,83,Rural,HR Executive,112851,1 +10804,Female,27,Masters,12,3,4,88,56,2.0,1,70,Semi-Urban,ML Engineer,54385,0 +10805,Other,35,Masters,5,14,12,29,24,2.0,1,51,Urban,Data Analyst,90612,0 +10806,Male,28,Bachelors,16,82,41,6,81,4.0,7,4,Urban,Data Analyst,83005,0 +10807,Male,45,Diploma,13,91,89,94,99,2.0,7,9,Urban,Manager,103350,1 +10808,Male,21,Bachelors,3,62,76,69,26,7.0,7,11,Urban,ML Engineer,113793,0 +10809,Female,30,Bachelors,1,37,66,43,81,7.0,4,26,Urban,Software Engineer,128774,0 +10810,Male,36,Bachelors,5,63,34,60,25,2.0,5,25,Urban,HR Executive,108961,0 +10811,Female,32,Diploma,17,75,51,11,39,4.0,5,44,Urban,Software Engineer,74315,0 +10812,Female,45,Diploma,12,88,53,72,37,9.0,2,44,Semi-Urban,ML Engineer,52834,1 +10813,Male,43,Bachelors,19,3,39,82,94,0.0,6,17,Urban,Software Engineer,81215,0 +10814,Female,34,Bachelors,9,44,7,40,25,3.0,0,22,Urban,Software Engineer,75654,0 +10815,Female,28,Bachelors,2,78,80,51,2,6.0,0,78,Semi-Urban,Software Engineer,102005,1 +10816,Male,28,Bachelors,3,64,67,60,93,8.0,7,58,Rural,HR Executive,43859,1 +10817,Female,46,Diploma,10,87,29,66,38,7.0,6,55,Rural,HR Executive,128985,0 +10818,Female,22,Diploma,19,5,79,22,65,5.0,2,26,Urban,Data Analyst,130904,0 +10819,Male,29,PhD,12,21,36,54,15,5.0,0,41,Urban,Manager,132246,0 +10820,Male,40,High School,7,51,88,12,11,5.0,4,44,Urban,Data Analyst,96156,0 +10821,Male,58,Diploma,6,76,84,93,26,9.0,3,84,Semi-Urban,HR Executive,117437,1 +10822,Male,43,Bachelors,6,1,13,82,36,4.0,4,72,Urban,Software Engineer,89470,0 +10823,Other,34,Bachelors,13,35,66,74,9,4.0,7,89,Urban,Manager,67494,1 +10824,Male,58,Masters,6,1,52,30,2,9.0,5,86,Urban,HR Executive,109524,0 +10825,Female,48,Bachelors,15,31,44,10,59,4.0,0,32,Rural,ML Engineer,77134,0 +10826,Male,51,Diploma,6,13,70,49,86,9.0,0,14,Urban,ML Engineer,28043,0 +10827,Male,48,Bachelors,17,28,9,28,35,8.0,4,19,Urban,Data Analyst,88640,0 +10828,Female,54,High School,3,50,41,25,38,2.0,7,88,Urban,HR Executive,55692,0 +10829,Female,22,Bachelors,5,63,18,55,17,7.0,3,93,Urban,Software Engineer,51310,0 +10830,Male,23,Masters,17,19,2,29,24,6.0,5,98,Urban,Data Analyst,60067,0 +10831,Male,57,Masters,17,38,19,17,51,9.0,2,52,Urban,Software Engineer,34855,0 +10832,Male,51,High School,8,23,35,11,63,9.0,5,13,Urban,Data Analyst,30362,0 +10833,Male,36,Bachelors,12,83,18,25,91,3.0,1,40,Urban,Data Analyst,58189,0 +10834,Male,49,Bachelors,13,85,84,95,79,3.0,3,30,Semi-Urban,Manager,136066,1 +10835,Male,27,Masters,2,63,99,85,37,6.0,2,66,Urban,Manager,93845,1 +10836,Other,58,Bachelors,18,93,4,28,98,7.0,4,73,Urban,Data Analyst,147919,0 +10837,Male,31,Diploma,8,44,96,25,4,7.0,2,81,Urban,HR Executive,77101,1 +10838,Female,38,Masters,1,15,43,28,62,4.0,4,91,Urban,Software Engineer,46378,0 +10839,Female,46,Bachelors,15,59,91,93,18,7.0,0,11,Urban,Manager,86572,1 +10840,Male,33,Masters,1,52,99,25,20,6.0,4,53,Urban,Manager,138179,0 +10841,Female,56,Masters,6,98,5,75,34,6.0,1,10,Urban,Manager,148815,0 +10842,Male,22,Bachelors,6,46,51,50,23,9.0,5,41,Rural,Manager,88799,0 +10843,Female,53,Bachelors,4,95,98,34,95,3.0,0,79,Rural,Software Engineer,69004,1 +10844,Male,48,Masters,14,26,26,64,9,3.0,2,18,Semi-Urban,Manager,110769,0 +10845,Male,42,High School,16,84,82,21,32,4.0,3,76,Urban,Software Engineer,78254,1 +10846,Female,43,Bachelors,16,26,65,9,70,6.0,0,75,Semi-Urban,HR Executive,110504,0 +10847,Male,43,Masters,0,87,17,97,26,7.0,4,85,Urban,Manager,134603,1 +10848,Female,57,Bachelors,14,73,41,85,61,0.0,3,81,Urban,Manager,145825,1 +10849,Female,59,Diploma,6,60,27,22,54,2.0,5,35,Semi-Urban,ML Engineer,49308,0 +10850,Male,51,Bachelors,17,29,12,66,60,2.0,3,51,Rural,ML Engineer,35646,0 +10851,Male,43,Bachelors,13,22,32,6,37,7.0,2,94,Urban,HR Executive,56739,0 +10852,Male,28,Masters,10,22,83,84,81,5.0,0,60,Rural,Software Engineer,52839,1 +10853,Female,51,Diploma,8,91,78,47,84,1.0,3,82,Rural,HR Executive,54546,1 +10854,Female,37,Bachelors,15,88,71,64,32,0.0,7,58,Semi-Urban,HR Executive,124622,1 +10855,Male,54,Masters,9,81,39,79,18,9.0,4,1,Urban,HR Executive,126701,0 +10856,Male,43,Bachelors,8,47,57,44,23,0.0,1,94,Urban,HR Executive,103651,1 +10857,Female,59,Bachelors,18,57,74,49,83,8.0,4,73,Urban,Software Engineer,65292,1 +10858,Male,45,High School,6,90,54,34,3,9.0,4,84,Rural,ML Engineer,122204,1 +10859,Female,48,Diploma,2,6,45,42,13,3.0,0,48,Rural,ML Engineer,149931,0 +10860,Female,35,Bachelors,9,82,13,43,59,8.0,4,27,Rural,Data Analyst,137192,0 +10861,Female,41,Masters,12,93,90,87,51,1.0,2,84,Semi-Urban,ML Engineer,59253,1 +10862,Male,26,Bachelors,5,97,28,90,36,3.0,2,56,Urban,Data Analyst,28205,1 +10863,Male,28,Masters,11,32,42,82,35,1.0,0,28,Rural,Data Analyst,55217,0 +10864,Male,53,Bachelors,4,84,83,35,18,1.0,4,94,Urban,Data Analyst,34808,1 +10865,Male,41,Bachelors,18,75,59,46,33,8.0,0,69,Semi-Urban,Data Analyst,95744,1 +10866,Other,41,Bachelors,11,8,90,26,85,6.0,3,6,Semi-Urban,HR Executive,90104,0 +10867,Male,30,Diploma,5,6,12,99,3,0.0,6,40,Rural,ML Engineer,120638,0 +10868,Female,24,Bachelors,8,61,47,67,32,1.0,6,73,Urban,Manager,126329,1 +10869,Male,29,Masters,7,23,95,83,55,6.0,0,54,Urban,ML Engineer,73571,1 +10870,Male,50,Bachelors,17,56,0,28,19,6.0,6,8,Urban,Manager,36232,0 +10871,Male,48,Masters,3,61,28,42,33,6.0,1,33,Rural,ML Engineer,22970,0 +10872,Female,50,Diploma,3,28,21,19,41,5.0,6,66,Urban,Software Engineer,116629,0 +10873,Male,43,Diploma,13,4,42,50,27,5.0,3,96,Semi-Urban,Data Analyst,149115,0 +10874,Male,44,Diploma,5,41,47,37,62,8.0,1,47,Semi-Urban,HR Executive,43132,0 +10875,Female,30,Bachelors,1,79,25,18,57,8.0,1,5,Rural,Manager,107216,0 +10876,Male,58,High School,17,86,34,12,78,3.0,5,9,Semi-Urban,Manager,20714,0 +10877,Male,39,Diploma,11,93,70,61,47,9.0,0,66,Urban,Software Engineer,106266,1 +10878,Male,53,Bachelors,11,30,47,19,19,5.0,4,26,Rural,ML Engineer,110529,0 +10879,Male,45,Bachelors,17,11,26,6,22,8.0,7,43,Urban,Manager,124228,0 +10880,Female,41,Bachelors,15,57,54,36,4,5.0,1,27,Rural,Software Engineer,79957,0 +10881,Male,40,Bachelors,12,80,27,20,32,4.0,3,80,Urban,Manager,26386,0 +10882,Male,36,Bachelors,17,17,74,12,92,1.0,4,16,Semi-Urban,HR Executive,54359,0 +10883,Male,22,High School,5,5,46,56,62,1.0,5,29,Urban,Software Engineer,50957,0 +10884,Female,56,Bachelors,12,1,20,22,70,8.0,7,4,Urban,ML Engineer,76841,0 +10885,Male,57,Bachelors,5,95,34,57,13,0.0,1,11,Rural,Data Analyst,40415,0 +10886,Female,31,Diploma,9,93,72,20,38,1.0,3,9,Rural,Data Analyst,117794,0 +10887,Male,27,Diploma,6,66,35,13,28,1.0,4,74,Urban,Manager,100487,0 +10888,Male,40,Masters,10,91,81,17,74,2.0,6,20,Semi-Urban,Data Analyst,34840,0 +10889,Female,27,Bachelors,14,33,27,93,30,2.0,1,22,Rural,HR Executive,94083,0 +10890,Male,31,Bachelors,17,98,86,67,92,4.0,0,51,Semi-Urban,Software Engineer,138315,1 +10891,Female,47,Bachelors,8,2,14,70,14,7.0,7,44,Urban,Manager,131237,0 +10892,Male,53,Diploma,7,32,9,72,6,9.0,7,91,Urban,Manager,55053,0 +10893,Female,28,Diploma,14,8,65,50,2,2.0,2,22,Urban,Data Analyst,49399,0 +10894,Male,28,High School,3,31,32,1,99,1.0,3,1,Rural,Data Analyst,81121,0 +10895,Female,21,High School,12,48,61,17,56,6.0,2,76,Rural,Software Engineer,73216,0 +10896,Male,52,Diploma,7,95,12,49,60,0.0,4,58,Semi-Urban,ML Engineer,73843,0 +10897,Male,51,Bachelors,12,80,27,45,43,6.0,6,57,Urban,HR Executive,146641,0 +10898,Male,23,Bachelors,12,35,70,3,20,0.0,5,98,Urban,ML Engineer,20180,0 +10899,Male,41,High School,12,0,80,71,67,5.0,5,34,Urban,Software Engineer,135032,0 +10900,Male,25,PhD,1,47,21,38,6,0.0,0,8,Semi-Urban,Data Analyst,81231,0 +10901,Male,58,Diploma,11,40,50,49,62,8.0,3,61,Urban,HR Executive,148810,0 +10902,Male,34,Bachelors,16,16,37,10,60,1.0,7,72,Urban,HR Executive,54924,0 +10903,Female,44,PhD,14,72,29,32,21,3.0,2,62,Rural,Software Engineer,138786,0 +10904,Female,52,Masters,2,50,8,42,30,3.0,7,45,Urban,ML Engineer,112979,0 +10905,Female,36,Diploma,19,76,38,73,70,4.0,0,22,Rural,Software Engineer,89976,0 +10906,Male,33,Bachelors,19,89,31,45,42,9.0,5,98,Urban,Data Analyst,148089,1 +10907,Male,44,High School,12,71,94,92,6,8.0,1,90,Semi-Urban,HR Executive,130342,1 +10908,Male,29,PhD,2,70,90,96,81,3.0,3,92,Urban,Manager,90919,1 +10909,Female,36,Masters,4,7,94,15,28,2.0,4,49,Rural,Software Engineer,50808,0 +10910,Male,45,High School,15,32,13,17,27,5.0,5,70,Urban,Software Engineer,148600,0 +10911,Male,35,Masters,11,92,83,65,9,4.0,4,51,Urban,Data Analyst,59585,1 +10912,Female,50,Diploma,18,6,10,75,76,8.0,3,58,Urban,Data Analyst,78853,0 +10913,Male,33,PhD,11,74,80,41,97,0.0,3,57,Urban,ML Engineer,74622,1 +10914,Female,41,Bachelors,15,4,88,29,0,1.0,3,27,Semi-Urban,Manager,118501,0 +10915,Female,58,Masters,2,87,17,24,54,3.0,5,32,Rural,Software Engineer,83075,0 +10916,Male,35,Bachelors,3,61,96,66,5,9.0,1,36,Semi-Urban,Software Engineer,34433,1 +10917,Male,21,Bachelors,8,4,73,91,83,5.0,0,1,Urban,HR Executive,124057,0 +10918,Male,36,High School,17,70,7,82,38,3.0,7,5,Urban,Manager,113101,0 +10919,Female,49,Masters,7,43,81,92,7,0.0,7,68,Rural,HR Executive,135955,1 +10920,Male,43,Diploma,5,18,14,77,20,3.0,5,31,Semi-Urban,Data Analyst,134221,0 +10921,Female,39,Bachelors,4,87,49,80,50,4.0,7,59,Rural,HR Executive,102533,1 +10922,Male,55,Masters,16,89,34,11,15,3.0,1,67,Semi-Urban,HR Executive,133128,0 +10923,Male,47,Masters,6,28,0,54,54,5.0,3,34,Semi-Urban,ML Engineer,128641,0 +10924,Male,54,Bachelors,7,33,74,28,94,8.0,4,52,Urban,Data Analyst,36808,0 +10925,Female,27,High School,17,73,75,15,38,3.0,6,33,Rural,ML Engineer,63380,0 +10926,Male,32,Bachelors,12,87,77,27,45,0.0,1,19,Semi-Urban,HR Executive,50703,0 +10927,Female,30,Masters,12,51,59,24,60,0.0,0,90,Semi-Urban,Software Engineer,124176,0 +10928,Male,42,Bachelors,14,83,34,40,68,5.0,0,59,Semi-Urban,Software Engineer,144233,0 +10929,Male,53,Masters,4,24,55,26,83,1.0,4,84,Urban,HR Executive,40698,0 +10930,Female,32,Diploma,4,40,40,46,20,1.0,1,37,Rural,Software Engineer,58473,0 +10931,Female,48,PhD,5,57,3,58,16,3.0,7,98,Urban,Software Engineer,98428,0 +10932,Male,41,Bachelors,4,94,81,76,41,5.0,6,80,Semi-Urban,ML Engineer,125105,1 +10933,Male,58,Bachelors,13,79,99,12,20,0.0,4,59,Semi-Urban,ML Engineer,58010,1 +10934,Female,35,Bachelors,0,77,45,49,90,7.0,3,83,Urban,Software Engineer,108944,1 +10935,Male,52,High School,9,72,24,86,4,5.0,6,22,Urban,ML Engineer,83935,0 +10936,Male,26,Diploma,6,33,44,15,44,5.0,1,94,Urban,Manager,107054,0 +10937,Female,53,Diploma,6,34,88,79,82,4.0,3,5,Urban,HR Executive,122193,0 +10938,Male,39,Bachelors,19,1,49,55,18,1.0,1,61,Semi-Urban,HR Executive,118896,0 +10939,Male,54,PhD,6,58,80,89,31,2.0,0,94,Urban,Software Engineer,114461,1 +10940,Male,50,Bachelors,7,42,90,15,26,6.0,5,8,Semi-Urban,Manager,113636,0 +10941,Female,47,Masters,7,39,32,72,71,3.0,7,70,Urban,Software Engineer,73962,0 +10942,Female,46,Masters,6,43,3,24,23,1.0,2,1,Urban,ML Engineer,147735,0 +10943,Male,43,Bachelors,18,1,20,65,82,7.0,4,54,Urban,ML Engineer,130653,0 +10944,Male,48,Diploma,0,17,62,26,25,0.0,6,61,Urban,Software Engineer,82556,0 +10945,Male,24,PhD,3,49,1,49,81,9.0,0,50,Urban,Software Engineer,123775,0 +10946,Female,31,High School,18,20,33,43,63,7.0,0,70,Urban,HR Executive,145850,0 +10947,Male,41,Diploma,13,99,25,49,81,0.0,5,82,Urban,Manager,37762,1 +10948,Female,29,High School,10,63,84,21,97,3.0,5,74,Urban,Software Engineer,20311,1 +10949,Male,32,Bachelors,8,42,24,50,81,4.0,3,12,Rural,ML Engineer,71000,0 +10950,Other,58,Diploma,16,1,26,37,34,3.0,4,73,Semi-Urban,HR Executive,140785,0 +10951,Male,21,High School,18,41,19,90,71,6.0,7,7,Rural,Software Engineer,38140,0 +10952,Female,32,Bachelors,3,92,47,18,75,3.0,0,70,Urban,ML Engineer,74928,0 +10953,Male,43,Masters,2,22,97,28,10,2.0,5,79,Semi-Urban,ML Engineer,52250,0 +10954,Male,26,Diploma,8,23,75,13,15,6.0,0,19,Urban,Data Analyst,45433,0 +10955,Female,52,Masters,1,13,1,87,93,9.0,4,74,Rural,Manager,125585,0 +10956,Female,59,High School,13,91,24,22,78,4.0,5,15,Rural,Software Engineer,146706,0 +10957,Male,48,Masters,17,70,77,87,97,0.0,3,82,Semi-Urban,ML Engineer,118793,1 +10958,Female,30,Bachelors,1,23,17,81,26,8.0,4,96,Rural,HR Executive,128470,0 +10959,Male,36,Masters,13,38,42,99,51,6.0,7,37,Urban,Manager,78218,0 +10960,Female,40,Bachelors,16,18,96,42,91,0.0,7,35,Urban,Manager,50877,0 +10961,Male,42,Masters,16,42,64,18,67,8.0,6,78,Urban,Data Analyst,66720,0 +10962,Male,44,Bachelors,5,58,60,40,8,3.0,2,1,Semi-Urban,HR Executive,125545,0 +10963,Male,50,Bachelors,4,34,1,63,21,9.0,5,69,Urban,Manager,101269,0 +10964,Male,34,Masters,16,41,1,5,13,3.0,6,54,Semi-Urban,Manager,144222,0 +10965,Female,46,Masters,8,55,88,53,7,3.0,5,90,Semi-Urban,Software Engineer,72466,1 +10966,Male,28,Masters,4,1,99,44,51,8.0,4,56,Urban,ML Engineer,83881,0 +10967,Male,46,Bachelors,13,52,15,17,27,0.0,2,4,Urban,Data Analyst,74769,0 +10968,Male,42,Masters,0,19,15,88,78,1.0,7,12,Semi-Urban,HR Executive,37390,0 +10969,Female,32,Bachelors,13,38,64,87,56,2.0,4,70,Urban,Manager,78094,1 +10970,Male,29,Masters,18,40,89,9,87,8.0,4,46,Urban,ML Engineer,144028,0 +10971,Male,50,Bachelors,5,35,5,15,93,5.0,6,96,Urban,HR Executive,141870,0 +10972,Female,57,Bachelors,12,4,95,22,94,0.0,4,62,Semi-Urban,Data Analyst,138065,0 +10973,Male,38,Bachelors,9,92,53,20,80,4.0,4,54,Urban,HR Executive,20904,0 +10974,Female,55,Masters,6,81,26,79,16,9.0,3,66,Urban,HR Executive,76861,1 +10975,Female,40,Bachelors,17,94,43,21,37,5.0,3,77,Semi-Urban,ML Engineer,116769,0 +10976,Male,32,Bachelors,0,77,45,18,83,8.0,1,56,Urban,Manager,58389,0 +10977,Female,57,Masters,0,32,13,98,92,2.0,6,82,Rural,Manager,108943,0 +10978,Female,59,Masters,4,90,65,34,21,8.0,4,85,Rural,Software Engineer,129535,1 +10979,Male,50,Masters,10,35,45,28,57,1.0,1,49,Urban,Manager,58574,0 +10980,Male,23,Diploma,0,71,23,5,9,1.0,4,15,Urban,Software Engineer,146777,0 +10981,Female,28,Masters,13,17,84,27,87,2.0,1,82,Urban,Manager,40591,0 +10982,Male,48,Masters,19,65,65,81,65,9.0,7,34,Urban,Manager,41560,1 +10983,Female,59,Masters,15,25,76,65,94,7.0,6,24,Rural,Data Analyst,121018,0 +10984,Male,21,Diploma,1,12,49,50,27,1.0,1,49,Urban,ML Engineer,54537,0 +10985,Male,37,Diploma,0,2,5,88,26,3.0,6,20,Rural,HR Executive,41255,0 +10986,Male,35,Bachelors,16,58,45,97,73,1.0,1,0,Urban,Data Analyst,51392,0 +10987,Male,37,Bachelors,1,9,97,12,30,4.0,3,13,Rural,Manager,59141,0 +10988,Male,32,Bachelors,2,56,92,79,17,7.0,0,56,Urban,ML Engineer,106582,1 +10989,Female,39,Masters,0,30,40,54,67,8.0,4,0,Semi-Urban,Software Engineer,57778,0 +10990,Female,45,Bachelors,10,0,7,10,48,3.0,3,29,Urban,HR Executive,138779,0 +10991,Female,58,Bachelors,5,55,93,3,34,2.0,1,47,Rural,Software Engineer,147263,0 +10992,Female,23,Diploma,4,30,57,57,75,5.0,3,15,Rural,Data Analyst,81463,0 +10993,Female,44,Bachelors,2,92,93,57,34,9.0,3,68,Urban,Data Analyst,90173,1 +10994,Male,23,Bachelors,6,5,92,99,34,6.0,5,72,Semi-Urban,Manager,126724,1 +10995,Female,32,Diploma,15,42,70,58,66,0.0,0,93,Semi-Urban,Data Analyst,118450,1 +10996,Male,28,PhD,9,4,68,13,57,0.0,5,39,Urban,ML Engineer,63551,0 +10997,Female,52,Bachelors,7,66,79,67,34,1.0,5,48,Urban,HR Executive,69624,1 +10998,Female,42,Masters,17,44,38,19,44,0.0,2,71,Semi-Urban,Manager,84662,0 +10999,Male,34,Bachelors,18,68,0,62,75,3.0,4,75,Urban,Software Engineer,132698,0 +11000,Male,36,Diploma,14,24,88,70,88,6.0,2,68,Urban,Manager,101802,1 +11001,Male,43,Diploma,4,41,38,43,64,7.0,1,45,Semi-Urban,Manager,123964,0 +11002,Male,34,PhD,14,68,38,38,79,3.0,2,50,Urban,Software Engineer,114055,0 +11003,Male,36,PhD,4,89,20,41,97,2.0,7,8,Semi-Urban,ML Engineer,50647,0 +11004,Male,54,High School,15,21,92,25,54,9.0,5,18,Urban,Manager,86487,0 +11005,Male,38,Bachelors,12,26,52,27,6,1.0,3,11,Semi-Urban,HR Executive,69115,0 +11006,Female,55,Diploma,19,39,84,29,42,8.0,6,28,Rural,Data Analyst,45321,0 +11007,Female,45,Bachelors,16,21,1,51,15,0.0,4,95,Urban,Data Analyst,67332,0 +11008,Female,34,Bachelors,5,10,40,79,40,4.0,3,12,Urban,Software Engineer,148865,0 +11009,Female,56,Diploma,16,3,74,74,8,7.0,5,50,Urban,Manager,133603,0 +11010,Male,23,Masters,14,45,78,85,96,0.0,0,58,Semi-Urban,Software Engineer,27624,1 +11011,Male,22,Bachelors,4,96,94,27,12,0.0,1,83,Urban,Data Analyst,117892,1 +11012,Female,58,Bachelors,10,36,44,53,24,1.0,6,5,Urban,Data Analyst,118126,0 +11013,Other,42,High School,11,37,89,76,49,2.0,4,72,Rural,ML Engineer,116665,1 +11014,Male,45,Diploma,3,33,78,76,44,9.0,7,61,Urban,ML Engineer,22086,1 +11015,Female,46,PhD,6,4,63,31,14,4.0,1,82,Urban,Data Analyst,25997,0 +11016,Female,28,PhD,2,39,60,48,91,0.0,0,62,Semi-Urban,Data Analyst,111127,0 +11017,Female,47,Diploma,12,54,32,44,74,1.0,6,48,Semi-Urban,HR Executive,23355,0 +11018,Female,45,Diploma,16,52,39,46,43,0.0,0,29,Semi-Urban,Software Engineer,68411,0 +11019,Male,58,Diploma,7,70,59,37,73,3.0,3,49,Urban,Manager,77602,0 +11020,Other,49,Diploma,3,46,65,96,45,1.0,5,61,Urban,Software Engineer,29735,1 +11021,Female,39,Bachelors,19,95,80,17,17,3.0,2,16,Urban,HR Executive,106031,0 +11022,Male,26,Diploma,10,40,20,55,97,0.0,7,82,Semi-Urban,Software Engineer,126257,0 +11023,Female,21,Diploma,13,90,79,6,62,4.0,5,30,Urban,Data Analyst,21528,0 +11024,Male,53,Masters,15,0,39,49,74,3.0,0,71,Semi-Urban,Software Engineer,136866,0 +11025,Male,50,Bachelors,4,97,35,32,35,9.0,4,90,Urban,ML Engineer,41827,1 +11026,Male,36,Masters,8,71,90,11,98,6.0,3,11,Semi-Urban,HR Executive,36918,0 +11027,Male,38,Bachelors,19,49,46,44,29,0.0,1,53,Urban,HR Executive,118497,0 +11028,Male,35,High School,8,72,49,52,47,0.0,6,45,Rural,ML Engineer,65470,0 +11029,Female,57,High School,17,23,21,77,1,6.0,5,62,Rural,Software Engineer,68269,0 +11030,Male,49,PhD,11,92,44,35,74,4.0,2,99,Urban,Software Engineer,148323,1 +11031,Male,36,Bachelors,5,74,35,73,8,4.0,6,47,Urban,ML Engineer,91224,0 +11032,Male,36,Masters,17,83,95,31,51,1.0,7,45,Urban,HR Executive,32578,1 +11033,Male,41,Bachelors,9,94,91,95,87,1.0,2,79,Urban,HR Executive,45888,1 +11034,Female,44,Masters,12,79,27,66,87,7.0,6,88,Rural,Software Engineer,68416,1 +11035,Female,55,High School,13,38,19,21,74,7.0,5,73,Urban,Manager,31748,0 +11036,Female,35,Bachelors,2,0,34,6,47,9.0,5,58,Urban,Software Engineer,70586,0 +11037,Female,56,Bachelors,5,27,36,9,52,1.0,3,78,Semi-Urban,Manager,105202,0 +11038,Male,35,Bachelors,1,26,52,45,39,2.0,2,34,Urban,HR Executive,105235,0 +11039,Female,35,Masters,1,11,38,63,45,7.0,5,83,Semi-Urban,HR Executive,94727,0 +11040,Female,58,Diploma,9,74,33,76,25,5.0,3,64,Urban,ML Engineer,29130,1 +11041,Male,41,Diploma,9,76,29,34,16,7.0,5,38,Urban,Software Engineer,63081,0 +11042,Female,21,Diploma,6,73,27,63,14,8.0,6,84,Urban,Software Engineer,137155,1 +11043,Female,45,Bachelors,10,75,57,45,5,0.0,6,30,Urban,ML Engineer,64607,0 +11044,Female,45,Masters,18,34,71,1,98,4.0,2,76,Semi-Urban,ML Engineer,34172,0 +11045,Male,38,Bachelors,0,93,55,42,8,6.0,7,86,Rural,Data Analyst,97486,1 +11046,Female,24,Masters,8,24,30,63,97,5.0,0,2,Urban,HR Executive,27517,0 +11047,Male,43,Bachelors,5,1,27,65,27,7.0,3,62,Semi-Urban,Software Engineer,23013,0 +11048,Male,45,Diploma,6,43,97,73,76,0.0,7,38,Urban,ML Engineer,50738,1 +11049,Male,50,Masters,2,78,40,91,55,9.0,6,1,Semi-Urban,Data Analyst,38608,0 +11050,Male,51,Masters,17,19,7,85,75,8.0,2,95,Urban,Software Engineer,79796,0 +11051,Male,42,Diploma,1,5,23,6,65,4.0,4,47,Urban,Software Engineer,62650,0 +11052,Male,34,Masters,0,95,97,69,0,4.0,5,75,Urban,Software Engineer,32385,1 +11053,Female,48,Bachelors,8,94,49,89,31,8.0,4,13,Rural,Software Engineer,135726,1 +11054,Female,58,High School,5,37,93,22,14,6.0,1,97,Semi-Urban,ML Engineer,52058,1 +11055,Other,54,Bachelors,10,4,6,94,48,4.0,0,93,Urban,Data Analyst,148102,0 +11056,Male,37,High School,8,37,44,9,98,5.0,1,3,Urban,HR Executive,70987,0 +11057,Male,32,Masters,6,24,43,14,61,1.0,6,40,Urban,ML Engineer,42514,0 +11058,Female,56,Bachelors,4,26,44,51,38,2.0,7,75,Semi-Urban,ML Engineer,51774,0 +11059,Male,57,Masters,4,85,29,65,90,2.0,5,16,Urban,HR Executive,44098,0 +11060,Female,53,Bachelors,9,53,61,95,35,5.0,5,81,Semi-Urban,ML Engineer,22011,1 +11061,Female,23,Bachelors,16,45,76,51,75,3.0,6,12,Semi-Urban,Software Engineer,117235,0 +11062,Male,50,Bachelors,12,5,25,20,88,3.0,7,50,Semi-Urban,HR Executive,60238,0 +11063,Female,45,Masters,10,6,14,53,84,0.0,5,86,Urban,HR Executive,107791,0 +11064,Female,29,Diploma,18,34,65,59,61,8.0,6,66,Rural,Manager,118814,0 +11065,Male,22,Masters,19,67,23,7,95,4.0,5,8,Urban,ML Engineer,108268,0 +11066,Male,34,Bachelors,18,13,63,34,91,0.0,0,75,Semi-Urban,Manager,102022,0 +11067,Male,44,Diploma,18,93,77,43,77,9.0,4,94,Semi-Urban,HR Executive,45423,1 +11068,Male,49,Bachelors,5,47,64,92,76,5.0,1,91,Semi-Urban,Manager,99158,1 +11069,Male,43,Diploma,10,7,42,24,78,1.0,5,38,Rural,Software Engineer,63243,0 +11070,Male,33,High School,3,8,52,73,89,9.0,4,21,Urban,Software Engineer,109002,0 +11071,Male,46,Bachelors,6,45,16,66,53,6.0,4,77,Rural,Data Analyst,116392,0 +11072,Female,42,Diploma,11,39,16,25,74,5.0,2,51,Semi-Urban,ML Engineer,120690,0 +11073,Male,43,Bachelors,18,39,86,25,11,7.0,0,44,Urban,ML Engineer,102837,0 +11074,Male,51,High School,17,44,58,89,96,7.0,0,32,Urban,HR Executive,123844,0 +11075,Male,50,Masters,5,91,76,8,9,1.0,0,19,Rural,Software Engineer,97938,0 +11076,Male,46,Diploma,16,60,72,43,58,1.0,0,97,Urban,Manager,44450,1 +11077,Male,58,Masters,6,25,91,99,21,2.0,7,26,Urban,Software Engineer,62887,1 +11078,Male,25,Bachelors,2,0,94,26,35,8.0,4,76,Urban,HR Executive,124676,0 +11079,Male,26,Diploma,1,13,82,48,83,7.0,2,77,Urban,HR Executive,143642,0 +11080,Female,21,Bachelors,6,36,63,31,43,7.0,6,79,Semi-Urban,ML Engineer,75213,0 +11081,Other,40,Diploma,8,44,64,15,20,9.0,7,46,Urban,Software Engineer,67609,0 +11082,Male,47,Bachelors,0,34,48,37,89,1.0,5,49,Urban,HR Executive,109471,0 +11083,Male,53,Masters,12,90,33,91,59,9.0,0,69,Urban,HR Executive,40906,1 +11084,Female,41,Diploma,4,17,92,3,95,2.0,0,9,Semi-Urban,ML Engineer,29989,0 +11085,Female,31,High School,14,25,2,60,27,8.0,4,83,Urban,HR Executive,116297,0 +11086,Male,21,High School,12,61,29,26,12,8.0,3,47,Urban,Data Analyst,123254,0 +11087,Female,34,Bachelors,17,71,26,87,73,0.0,1,45,Urban,ML Engineer,116265,0 +11088,Male,39,Diploma,19,50,67,9,31,2.0,5,21,Semi-Urban,HR Executive,50695,0 +11089,Male,23,Bachelors,10,72,49,36,42,1.0,5,63,Urban,Software Engineer,123696,0 +11090,Female,35,High School,9,19,94,86,4,3.0,3,73,Urban,Data Analyst,119142,1 +11091,Other,49,Masters,7,11,31,8,2,3.0,7,99,Urban,ML Engineer,48025,0 +11092,Female,21,Masters,6,31,17,44,0,7.0,3,78,Urban,Software Engineer,102553,0 +11093,Male,38,Masters,8,47,79,72,24,8.0,1,1,Rural,HR Executive,78905,0 +11094,Male,50,Masters,11,2,86,14,28,4.0,4,22,Semi-Urban,Manager,40852,0 +11095,Male,30,Bachelors,15,56,80,72,54,5.0,2,30,Urban,Software Engineer,75989,1 +11096,Male,47,High School,0,0,36,44,32,5.0,1,80,Urban,Manager,38269,0 +11097,Female,23,Diploma,18,52,98,72,13,0.0,2,43,Semi-Urban,Software Engineer,91596,1 +11098,Female,36,Masters,19,79,85,13,15,7.0,2,55,Rural,Software Engineer,27982,0 +11099,Female,30,PhD,12,52,14,32,68,0.0,6,77,Urban,Manager,65905,0 +11100,Other,28,Bachelors,16,44,92,88,91,1.0,2,66,Urban,Manager,107309,1 +11101,Male,48,High School,0,54,37,91,99,2.0,4,28,Rural,Manager,101131,0 +11102,Female,59,Diploma,8,61,10,88,80,9.0,3,63,Urban,Manager,125372,0 +11103,Female,49,Masters,2,89,41,79,38,4.0,4,34,Urban,Manager,102554,1 +11104,Male,33,Masters,4,38,5,27,78,5.0,5,59,Urban,ML Engineer,135938,0 +11105,Female,46,Masters,5,38,16,60,25,4.0,1,8,Semi-Urban,ML Engineer,135717,0 +11106,Male,24,Bachelors,10,35,30,32,90,5.0,3,83,Urban,ML Engineer,136680,0 +11107,Female,54,Diploma,4,35,35,99,44,2.0,3,95,Urban,Manager,120100,1 +11108,Male,38,Diploma,11,6,53,35,81,7.0,7,72,Urban,HR Executive,65020,0 +11109,Male,42,High School,18,25,33,19,46,8.0,2,77,Urban,Software Engineer,75528,0 +11110,Female,31,Masters,17,83,51,39,77,3.0,0,90,Urban,ML Engineer,133733,1 +11111,Female,29,Bachelors,8,47,23,20,9,3.0,0,89,Rural,HR Executive,72617,0 +11112,Male,54,Bachelors,16,31,54,89,67,0.0,7,32,Semi-Urban,HR Executive,49017,0 +11113,Male,38,Bachelors,0,27,51,61,99,9.0,4,13,Urban,HR Executive,88621,0 +11114,Male,42,High School,17,13,6,10,77,1.0,5,85,Urban,HR Executive,39121,0 +11115,Male,30,Diploma,17,72,40,86,67,2.0,7,85,Urban,ML Engineer,26355,1 +11116,Female,48,High School,6,48,6,77,13,7.0,2,95,Semi-Urban,Software Engineer,68872,0 +11117,Female,43,Diploma,1,47,18,56,40,9.0,7,75,Rural,HR Executive,130866,0 +11118,Male,23,Masters,10,63,58,27,21,3.0,0,17,Urban,Data Analyst,131126,0 +11119,Female,27,Masters,10,30,51,8,85,0.0,5,39,Urban,ML Engineer,141090,0 +11120,Male,28,Masters,10,90,24,38,11,7.0,3,34,Rural,Data Analyst,42789,0 +11121,Female,52,Bachelors,13,38,99,61,64,0.0,7,88,Urban,ML Engineer,49910,1 +11122,Male,21,Masters,5,17,80,19,54,7.0,4,87,Semi-Urban,Manager,48601,0 +11123,Male,45,Diploma,2,37,35,26,18,0.0,3,96,Urban,ML Engineer,95354,0 +11124,Female,46,Bachelors,9,77,84,81,97,2.0,5,85,Urban,Manager,134171,1 +11125,Male,55,PhD,17,0,15,71,2,8.0,3,97,Urban,Manager,112892,0 +11126,Female,33,High School,0,58,15,84,61,8.0,4,38,Rural,HR Executive,124136,0 +11127,Female,48,Masters,1,53,30,52,99,4.0,2,63,Semi-Urban,Data Analyst,71539,0 +11128,Male,31,Diploma,0,55,80,87,74,8.0,2,80,Urban,Manager,140285,1 +11129,Male,32,Bachelors,1,81,16,34,54,1.0,5,55,Semi-Urban,Data Analyst,83168,0 +11130,Female,48,Masters,5,83,18,47,35,7.0,4,17,Urban,Manager,119233,0 +11131,Female,45,Bachelors,11,55,73,38,18,3.0,1,48,Semi-Urban,Manager,37066,0 +11132,Male,49,Diploma,2,20,18,90,7,1.0,1,25,Semi-Urban,Data Analyst,100856,0 +11133,Male,21,Bachelors,3,2,80,15,52,2.0,6,42,Semi-Urban,Data Analyst,46680,0 +11134,Female,43,Diploma,19,9,38,72,89,6.0,1,56,Semi-Urban,ML Engineer,121579,0 +11135,Male,45,PhD,19,18,35,15,9,8.0,0,15,Urban,ML Engineer,94490,0 +11136,Male,37,Bachelors,1,16,72,87,79,2.0,5,9,Urban,Manager,132829,0 +11137,Male,27,Diploma,3,29,30,98,45,7.0,7,0,Rural,HR Executive,39483,0 +11138,Female,50,Diploma,6,28,8,21,94,0.0,4,47,Urban,Software Engineer,80757,0 +11139,Female,26,Diploma,3,7,76,2,49,5.0,3,18,Urban,ML Engineer,65505,0 +11140,Other,51,Diploma,2,41,16,86,98,6.0,2,18,Urban,HR Executive,107413,0 +11141,Female,28,Masters,19,80,69,59,70,0.0,2,89,Urban,Software Engineer,101238,1 +11142,Female,49,Bachelors,3,48,82,91,56,1.0,0,95,Urban,HR Executive,147355,1 +11143,Male,45,PhD,13,58,47,62,87,4.0,3,27,Semi-Urban,Software Engineer,107533,0 +11144,Female,29,High School,6,94,33,19,85,2.0,5,12,Semi-Urban,Data Analyst,76209,0 +11145,Male,51,Bachelors,4,19,91,84,36,7.0,3,56,Urban,Manager,30477,1 +11146,Female,58,Diploma,19,92,3,15,44,0.0,2,70,Urban,Manager,46622,0 +11147,Male,49,High School,19,7,88,76,46,6.0,6,62,Semi-Urban,ML Engineer,66312,0 +11148,Male,36,High School,12,98,14,26,2,6.0,6,56,Urban,Manager,80804,0 +11149,Female,57,PhD,18,1,37,88,35,1.0,6,23,Urban,Data Analyst,147423,0 +11150,Female,28,Masters,16,65,48,25,72,2.0,7,44,Urban,Manager,119369,0 +11151,Male,25,Diploma,18,32,28,20,10,8.0,0,80,Rural,Manager,70046,0 +11152,Female,56,Bachelors,10,45,18,8,85,2.0,4,11,Urban,Data Analyst,50808,0 +11153,Male,38,PhD,13,76,46,99,44,3.0,2,14,Urban,Manager,37618,1 +11154,Male,23,Bachelors,6,96,36,50,35,1.0,1,64,Urban,Software Engineer,20380,1 +11155,Female,54,Bachelors,6,93,67,77,62,5.0,2,46,Rural,Software Engineer,128452,1 +11156,Male,25,Bachelors,1,1,13,53,47,2.0,3,43,Urban,Data Analyst,23632,0 +11157,Female,28,Diploma,19,19,46,94,95,8.0,6,57,Urban,Data Analyst,147336,0 +11158,Male,57,Diploma,10,63,60,62,31,7.0,5,80,Semi-Urban,HR Executive,134038,1 +11159,Female,32,Bachelors,13,61,25,24,7,6.0,2,0,Urban,Data Analyst,149283,0 +11160,Female,38,Bachelors,19,95,21,68,49,9.0,7,18,Urban,Data Analyst,76582,0 +11161,Male,47,Bachelors,6,23,97,36,64,4.0,3,84,Rural,HR Executive,73862,1 +11162,Male,27,Bachelors,8,51,32,17,69,2.0,0,50,Urban,Manager,87109,0 +11163,Female,39,Masters,18,99,10,51,19,2.0,2,84,Semi-Urban,HR Executive,96946,1 +11164,Female,38,Diploma,16,36,84,85,29,6.0,7,96,Urban,Data Analyst,47235,1 +11165,Male,56,Bachelors,4,42,54,74,5,4.0,1,39,Urban,ML Engineer,32997,0 +11166,Male,28,Diploma,3,65,18,70,31,6.0,2,63,Semi-Urban,HR Executive,32881,0 +11167,Male,49,Bachelors,3,70,14,52,15,3.0,6,36,Rural,HR Executive,59247,0 +11168,Male,38,Bachelors,11,15,18,54,94,5.0,3,17,Urban,ML Engineer,26191,0 +11169,Male,25,Masters,3,49,78,41,23,1.0,2,78,Urban,ML Engineer,119578,1 +11170,Male,25,Masters,9,37,37,22,7,5.0,1,71,Urban,Manager,99913,0 +11171,Female,45,Masters,14,35,8,63,13,2.0,1,4,Rural,Manager,125395,0 +11172,Female,21,Masters,1,6,59,27,56,4.0,5,24,Urban,ML Engineer,94739,0 +11173,Female,31,Bachelors,16,11,40,0,88,9.0,0,66,Rural,Manager,31565,0 +11174,Female,34,Bachelors,9,18,34,41,57,9.0,3,23,Urban,Data Analyst,42301,0 +11175,Female,29,Masters,13,91,13,63,86,4.0,1,60,Semi-Urban,ML Engineer,70926,0 +11176,Male,25,High School,3,89,10,99,64,3.0,3,7,Urban,Manager,77846,0 +11177,Female,44,Masters,16,42,80,69,59,3.0,2,63,Urban,Software Engineer,50469,1 +11178,Other,26,Bachelors,19,40,76,89,86,5.0,4,2,Rural,Manager,32009,0 +11179,Female,37,Diploma,6,60,73,58,78,4.0,7,17,Rural,Data Analyst,33657,0 +11180,Male,31,Masters,14,13,46,53,55,0.0,0,43,Urban,ML Engineer,72402,0 +11181,Female,50,Bachelors,15,74,77,41,84,5.0,1,23,Urban,Manager,123277,0 +11182,Female,32,Diploma,11,63,72,88,20,1.0,7,23,Urban,Manager,78653,1 +11183,Female,35,Masters,2,27,41,15,89,1.0,2,39,Urban,Data Analyst,112187,0 +11184,Male,34,High School,10,17,58,76,50,5.0,7,70,Urban,Manager,41203,0 +11185,Female,28,Masters,14,58,81,92,82,7.0,3,30,Urban,Data Analyst,75501,1 +11186,Other,33,Bachelors,5,79,79,85,94,6.0,5,71,Semi-Urban,HR Executive,30527,1 +11187,Male,48,Masters,3,54,87,98,18,6.0,3,72,Urban,Software Engineer,140300,1 +11188,Female,40,Bachelors,14,13,93,36,19,4.0,4,24,Urban,Software Engineer,23492,0 +11189,Male,46,Bachelors,1,0,43,86,39,4.0,7,52,Urban,Data Analyst,142144,0 +11190,Female,43,Bachelors,19,60,77,34,8,2.0,2,9,Rural,Manager,96755,0 +11191,Female,35,Diploma,11,13,15,30,76,9.0,0,44,Semi-Urban,ML Engineer,76105,0 +11192,Male,48,Diploma,2,5,8,32,78,5.0,2,2,Semi-Urban,Manager,104641,0 +11193,Male,21,High School,18,97,88,25,33,5.0,2,38,Urban,Software Engineer,118349,1 +11194,Female,38,Diploma,4,15,41,7,45,0.0,3,16,Rural,ML Engineer,61714,0 +11195,Male,29,Bachelors,11,77,35,43,87,8.0,1,97,Rural,Manager,104447,1 +11196,Male,22,Masters,10,5,69,29,70,1.0,1,15,Urban,Data Analyst,90582,0 +11197,Female,33,Masters,18,82,40,74,99,6.0,0,82,Urban,Manager,110989,1 +11198,Male,34,Bachelors,14,39,48,35,19,0.0,4,52,Rural,ML Engineer,114990,0 +11199,Male,29,Masters,6,63,93,29,62,9.0,6,50,Semi-Urban,Data Analyst,40152,1 +11200,Female,46,High School,7,83,65,0,36,9.0,0,6,Rural,HR Executive,69443,0 +11201,Male,52,Masters,2,29,66,86,28,6.0,5,12,Rural,HR Executive,64868,0 +11202,Male,23,Bachelors,9,55,68,61,18,4.0,6,35,Urban,Data Analyst,60266,0 +11203,Female,38,Masters,10,9,16,86,38,9.0,3,4,Urban,ML Engineer,124331,0 +11204,Female,41,Diploma,7,27,95,21,78,8.0,7,92,Semi-Urban,Manager,44382,0 +11205,Female,51,Bachelors,10,95,56,72,14,2.0,4,47,Semi-Urban,Data Analyst,127972,1 +11206,Female,44,Diploma,16,25,69,6,99,4.0,2,20,Urban,Data Analyst,53759,0 +11207,Female,54,Bachelors,9,22,79,46,41,3.0,3,50,Urban,Manager,28495,0 +11208,Male,25,Bachelors,13,70,6,95,99,3.0,6,19,Urban,HR Executive,139470,0 +11209,Male,52,Bachelors,14,25,75,32,97,3.0,0,74,Semi-Urban,HR Executive,148977,0 +11210,Male,41,Bachelors,8,51,22,45,82,7.0,6,49,Urban,Manager,64071,0 +11211,Male,47,Bachelors,1,0,69,90,15,7.0,3,19,Urban,ML Engineer,110005,0 +11212,Female,53,Bachelors,4,85,75,67,84,6.0,0,95,Urban,HR Executive,130858,1 +11213,Female,23,Bachelors,19,89,15,52,59,8.0,1,66,Rural,Manager,22837,0 +11214,Male,39,Masters,18,96,29,23,15,4.0,0,6,Urban,HR Executive,131226,0 +11215,Female,21,Masters,3,30,90,32,41,6.0,2,92,Urban,HR Executive,87516,1 +11216,Male,24,Diploma,13,16,85,67,78,3.0,2,22,Urban,ML Engineer,47988,0 +11217,Male,47,Bachelors,6,76,16,74,39,9.0,2,65,Semi-Urban,Data Analyst,78846,0 +11218,Female,43,PhD,7,47,33,86,79,0.0,4,74,Rural,Software Engineer,98566,0 +11219,Male,24,Masters,8,32,88,64,40,7.0,5,78,Urban,Manager,143504,1 +11220,Male,40,High School,7,24,71,32,42,6.0,2,11,Urban,Software Engineer,91720,0 +11221,Male,32,Masters,4,0,88,75,82,1.0,6,23,Urban,HR Executive,123343,0 +11222,Male,51,Bachelors,11,21,81,62,75,4.0,1,52,Semi-Urban,HR Executive,91103,0 +11223,Female,29,Diploma,12,93,93,91,91,3.0,4,7,Urban,Software Engineer,32629,1 +11224,Female,33,Diploma,5,77,25,20,51,2.0,2,15,Urban,Software Engineer,117864,0 +11225,Male,54,Masters,15,6,9,30,6,6.0,6,6,Urban,Data Analyst,52612,0 +11226,Male,53,Bachelors,19,9,60,19,33,2.0,1,58,Semi-Urban,Manager,51008,0 +11227,Female,50,Bachelors,2,66,20,36,96,8.0,2,36,Rural,Data Analyst,54251,0 +11228,Female,42,Masters,12,28,1,69,85,8.0,0,58,Rural,HR Executive,129135,0 +11229,Male,27,Bachelors,18,14,40,85,75,6.0,6,80,Urban,Manager,97294,0 +11230,Male,56,Bachelors,6,82,1,93,6,5.0,5,31,Rural,Manager,87529,0 +11231,Female,37,Masters,3,48,54,85,80,8.0,4,8,Urban,Software Engineer,123867,0 +11232,Female,29,High School,2,83,73,62,70,4.0,3,26,Rural,Data Analyst,94285,1 +11233,Male,24,Bachelors,19,80,79,47,69,7.0,3,35,Urban,Data Analyst,50335,1 +11234,Female,58,High School,14,94,87,30,5,0.0,0,76,Rural,Data Analyst,122455,1 +11235,Male,48,Bachelors,16,88,64,50,84,9.0,1,86,Urban,ML Engineer,51983,1 +11236,Male,52,PhD,17,85,28,9,68,9.0,3,60,Semi-Urban,Software Engineer,86780,0 +11237,Male,38,Masters,7,96,71,12,14,3.0,0,59,Urban,Software Engineer,121496,1 +11238,Female,25,Diploma,12,1,71,80,95,0.0,3,84,Rural,Software Engineer,76564,0 +11239,Male,22,Masters,9,62,56,99,62,9.0,0,91,Urban,Software Engineer,64007,1 +11240,Male,31,High School,4,3,34,48,98,6.0,5,69,Rural,Software Engineer,28545,0 +11241,Male,50,Bachelors,15,83,23,38,3,2.0,1,11,Semi-Urban,ML Engineer,87865,0 +11242,Female,47,PhD,1,97,34,11,57,5.0,6,77,Rural,Software Engineer,99703,0 +11243,Male,35,Diploma,5,40,43,88,41,8.0,6,14,Semi-Urban,ML Engineer,114680,0 +11244,Male,44,High School,5,21,80,95,98,6.0,2,42,Urban,Manager,116190,1 +11245,Male,39,Masters,17,46,58,72,25,1.0,4,92,Urban,Software Engineer,137981,1 +11246,Female,21,Masters,7,95,45,14,63,3.0,1,55,Semi-Urban,Software Engineer,43894,0 +11247,Male,48,Diploma,7,43,77,67,65,1.0,2,11,Urban,Manager,98854,0 +11248,Male,28,Bachelors,14,5,13,79,38,3.0,2,96,Urban,Software Engineer,40927,0 +11249,Male,42,Bachelors,6,78,55,64,67,1.0,7,57,Rural,Data Analyst,26789,1 +11250,Female,45,Masters,13,29,24,10,5,8.0,4,2,Urban,Manager,95353,0 +11251,Male,38,High School,3,67,23,64,34,8.0,0,87,Urban,ML Engineer,33746,1 +11252,Female,29,PhD,7,41,48,77,52,0.0,4,74,Semi-Urban,ML Engineer,134727,0 +11253,Female,28,Diploma,13,83,12,96,55,7.0,0,86,Urban,Manager,119671,1 +11254,Female,42,Masters,18,59,52,27,81,0.0,4,11,Urban,ML Engineer,104526,0 +11255,Male,22,Bachelors,5,11,59,9,26,5.0,2,97,Urban,Manager,135806,0 +11256,Other,57,High School,13,52,44,47,63,1.0,2,10,Rural,Manager,69256,0 +11257,Male,55,Bachelors,17,28,82,83,91,6.0,2,18,Semi-Urban,Software Engineer,75225,0 +11258,Male,26,Diploma,8,50,40,34,86,8.0,2,95,Rural,Manager,115736,0 +11259,Female,31,Masters,4,1,50,70,0,0.0,2,42,Urban,HR Executive,117364,0 +11260,Male,43,Masters,12,84,86,42,9,2.0,4,28,Urban,Data Analyst,132787,1 +11261,Male,35,Bachelors,13,34,34,91,58,5.0,1,43,Rural,Data Analyst,99277,0 +11262,Male,39,Bachelors,16,3,33,44,66,7.0,4,25,Urban,Data Analyst,35141,0 +11263,Female,44,Diploma,1,25,2,38,14,8.0,5,18,Urban,Manager,41898,0 +11264,Male,30,Masters,5,78,98,44,76,7.0,0,77,Urban,Software Engineer,101759,1 +11265,Female,53,Bachelors,6,91,90,91,15,5.0,5,21,Urban,HR Executive,82028,1 +11266,Female,38,Bachelors,9,56,64,1,38,4.0,5,93,Urban,ML Engineer,108437,0 +11267,Female,38,Bachelors,11,33,31,30,73,2.0,0,45,Rural,Data Analyst,44624,0 +11268,Male,39,Bachelors,4,28,23,73,5,0.0,0,79,Urban,ML Engineer,140893,0 +11269,Female,44,High School,4,45,66,27,20,7.0,4,95,Urban,Data Analyst,28529,0 +11270,Male,45,High School,17,43,27,66,95,4.0,6,71,Urban,Data Analyst,141241,0 +11271,Male,29,Masters,1,47,52,53,35,1.0,5,33,Urban,Software Engineer,95184,0 +11272,Male,55,Diploma,13,59,35,96,71,0.0,2,42,Urban,ML Engineer,125000,0 +11273,Male,48,Diploma,4,53,67,22,6,0.0,2,11,Semi-Urban,Manager,79175,0 +11274,Male,48,Masters,4,38,57,89,95,8.0,4,27,Urban,ML Engineer,140402,0 +11275,Male,33,Bachelors,12,98,21,45,28,5.0,4,56,Semi-Urban,ML Engineer,66409,0 +11276,Male,52,High School,6,25,34,24,8,5.0,2,38,Urban,Data Analyst,128163,0 +11277,Male,43,Masters,8,85,95,13,60,1.0,4,36,Urban,Manager,43467,0 +11278,Female,38,Bachelors,14,24,85,84,72,8.0,3,70,Rural,Data Analyst,102348,1 +11279,Female,32,Bachelors,12,3,41,63,9,9.0,2,7,Rural,ML Engineer,56032,0 +11280,Female,46,Diploma,7,23,81,45,50,5.0,3,16,Urban,Data Analyst,132843,0 +11281,Male,41,Masters,6,5,36,40,11,3.0,6,88,Urban,Software Engineer,105635,0 +11282,Male,29,Diploma,12,98,41,70,95,4.0,7,37,Rural,Data Analyst,140597,1 +11283,Other,41,Bachelors,7,64,53,72,47,8.0,5,37,Semi-Urban,Software Engineer,44797,0 +11284,Male,43,Bachelors,7,13,88,40,21,3.0,0,52,Urban,Data Analyst,111674,0 +11285,Female,26,Bachelors,6,32,17,69,88,4.0,2,57,Urban,HR Executive,32088,0 +11286,Male,49,Bachelors,7,44,91,8,85,2.0,5,46,Urban,HR Executive,25782,0 +11287,Female,21,Bachelors,14,85,8,90,85,6.0,0,41,Rural,Manager,25985,0 +11288,Male,29,Masters,3,83,17,21,99,1.0,7,37,Urban,HR Executive,145851,0 +11289,Male,23,Bachelors,8,65,48,77,91,7.0,1,96,Rural,ML Engineer,111840,1 +11290,Female,29,Masters,16,57,88,3,24,1.0,0,64,Urban,Software Engineer,92344,0 +11291,Male,44,Bachelors,16,65,0,47,68,2.0,2,9,Semi-Urban,Data Analyst,97703,0 +11292,Male,48,Diploma,3,35,43,83,25,0.0,3,30,Urban,Software Engineer,133079,0 +11293,Male,46,Bachelors,17,52,57,51,24,4.0,2,85,Urban,HR Executive,71797,1 +11294,Female,36,Diploma,9,45,8,13,20,9.0,5,1,Urban,Data Analyst,122720,0 +11295,Male,27,Bachelors,1,96,20,28,74,9.0,2,53,Urban,ML Engineer,98904,0 +11296,Male,37,Diploma,7,7,21,49,65,2.0,7,51,Urban,Data Analyst,120643,0 +11297,Male,57,High School,0,71,25,15,90,2.0,7,37,Urban,Software Engineer,44070,0 +11298,Male,58,Diploma,9,14,56,80,32,0.0,5,58,Urban,ML Engineer,48521,0 +11299,Female,54,Bachelors,7,94,97,48,54,8.0,3,53,Rural,Data Analyst,122855,1 +11300,Male,39,Bachelors,11,58,88,79,29,2.0,0,69,Semi-Urban,Data Analyst,132221,1 +11301,Male,28,High School,1,7,28,70,34,5.0,5,79,Urban,ML Engineer,99940,0 +11302,Male,43,Masters,1,19,42,82,10,3.0,3,86,Semi-Urban,Software Engineer,60765,0 +11303,Male,36,High School,18,75,35,53,65,9.0,7,94,Urban,ML Engineer,129701,1 +11304,Male,34,Masters,9,90,47,69,33,0.0,1,4,Urban,Manager,32919,0 +11305,Male,38,PhD,0,72,11,27,50,2.0,3,46,Semi-Urban,HR Executive,110731,0 +11306,Male,45,High School,1,66,12,2,51,7.0,4,35,Semi-Urban,Software Engineer,110636,0 +11307,Other,36,Bachelors,16,81,2,90,83,9.0,5,58,Rural,Software Engineer,47568,0 +11308,Male,35,Masters,6,20,52,46,42,5.0,3,17,Urban,Data Analyst,82944,0 +11309,Female,45,Bachelors,7,63,50,1,89,8.0,2,80,Urban,Data Analyst,28435,0 +11310,Male,52,Masters,7,65,90,58,81,5.0,2,24,Rural,Software Engineer,87733,1 +11311,Male,45,Bachelors,16,36,46,58,35,6.0,1,29,Urban,ML Engineer,53414,0 +11312,Male,45,Bachelors,12,54,67,20,97,5.0,3,38,Semi-Urban,ML Engineer,92205,0 +11313,Male,56,High School,7,25,29,66,93,6.0,2,92,Rural,Software Engineer,130909,0 +11314,Other,28,Bachelors,9,4,62,84,30,1.0,5,78,Urban,HR Executive,94556,0 +11315,Female,56,High School,9,37,28,51,32,6.0,5,83,Urban,Manager,131663,0 +11316,Female,36,Bachelors,17,16,86,17,48,1.0,0,93,Urban,Software Engineer,118649,0 +11317,Female,36,PhD,3,71,63,95,42,1.0,5,19,Rural,Manager,39442,1 +11318,Male,26,Bachelors,7,99,67,79,82,8.0,1,95,Rural,HR Executive,117545,1 +11319,Male,58,High School,9,10,4,31,81,8.0,2,31,Urban,HR Executive,64522,0 +11320,Female,34,Masters,8,20,58,93,94,3.0,1,14,Semi-Urban,HR Executive,84273,0 +11321,Female,41,Masters,6,53,62,2,36,5.0,4,42,Urban,Data Analyst,90335,0 +11322,Male,45,High School,5,79,14,92,57,4.0,2,44,Semi-Urban,ML Engineer,145791,0 +11323,Male,48,PhD,16,3,0,58,11,6.0,0,23,Urban,Software Engineer,121079,0 +11324,Male,26,Diploma,2,55,15,33,63,4.0,0,19,Semi-Urban,ML Engineer,96412,0 +11325,Female,57,High School,15,67,28,67,90,3.0,3,36,Urban,HR Executive,61105,0 +11326,Male,30,High School,17,93,5,36,33,4.0,6,99,Rural,Software Engineer,106394,0 +11327,Male,27,Bachelors,8,34,32,18,4,4.0,1,99,Semi-Urban,Software Engineer,130267,0 +11328,Male,31,Bachelors,6,70,13,81,25,1.0,2,98,Urban,Software Engineer,74804,1 +11329,Female,32,Bachelors,14,42,99,34,15,1.0,2,48,Urban,ML Engineer,38700,0 +11330,Male,29,Masters,6,67,98,68,26,8.0,0,39,Urban,Software Engineer,48664,1 +11331,Female,25,PhD,19,71,70,96,48,0.0,5,11,Urban,Manager,44498,1 +11332,Male,46,Bachelors,4,30,39,83,45,5.0,4,38,Rural,Manager,61429,0 +11333,Female,47,High School,15,51,52,24,23,5.0,0,54,Semi-Urban,HR Executive,23157,0 +11334,Female,34,Bachelors,14,40,72,72,11,4.0,5,44,Urban,Data Analyst,101223,0 +11335,Male,37,High School,19,46,93,61,37,2.0,5,84,Urban,HR Executive,65023,1 +11336,Male,28,Masters,19,42,36,65,58,7.0,6,95,Semi-Urban,Data Analyst,97795,1 +11337,Male,21,High School,19,26,76,86,82,9.0,4,0,Urban,HR Executive,88829,0 +11338,Male,52,Diploma,12,46,7,14,20,4.0,3,86,Rural,HR Executive,70415,0 +11339,Female,26,Bachelors,7,84,0,6,51,6.0,4,10,Urban,Software Engineer,35411,0 +11340,Male,52,Bachelors,1,72,2,96,79,1.0,2,41,Urban,ML Engineer,42961,0 +11341,Male,25,Diploma,5,81,57,62,87,4.0,6,74,Semi-Urban,Software Engineer,121006,1 +11342,Male,41,Masters,9,23,99,68,75,4.0,2,96,Urban,Software Engineer,100736,1 +11343,Male,49,Masters,3,3,7,10,12,1.0,0,98,Semi-Urban,HR Executive,109803,0 +11344,Female,47,High School,15,47,93,88,63,7.0,6,3,Rural,HR Executive,72796,0 +11345,Male,34,Bachelors,9,20,18,3,50,9.0,2,97,Rural,Software Engineer,66360,0 +11346,Other,57,Bachelors,17,11,50,45,42,5.0,3,0,Semi-Urban,ML Engineer,147729,0 +11347,Female,55,Bachelors,3,48,69,82,5,1.0,2,46,Rural,ML Engineer,79311,1 +11348,Male,45,Diploma,6,65,39,14,57,0.0,6,65,Urban,HR Executive,99892,0 +11349,Male,44,Diploma,18,17,48,69,92,1.0,5,80,Rural,HR Executive,114684,0 +11350,Female,47,Diploma,15,57,95,83,51,6.0,2,89,Urban,Data Analyst,100077,1 +11351,Male,27,High School,9,91,71,2,73,5.0,4,6,Urban,Manager,113347,0 +11352,Male,46,Diploma,17,48,78,92,82,2.0,3,53,Semi-Urban,Data Analyst,113080,1 +11353,Male,21,High School,8,8,85,13,44,3.0,2,39,Rural,Software Engineer,97584,0 +11354,Male,48,Bachelors,0,21,64,26,65,6.0,2,96,Semi-Urban,ML Engineer,147015,0 +11355,Female,41,Bachelors,5,98,58,83,54,2.0,0,58,Semi-Urban,ML Engineer,67139,1 +11356,Male,57,Bachelors,5,42,30,16,32,2.0,0,60,Semi-Urban,Software Engineer,22709,0 +11357,Male,36,Diploma,18,88,48,50,18,0.0,6,8,Urban,HR Executive,81658,0 +11358,Female,26,PhD,15,5,94,41,0,0.0,6,96,Semi-Urban,HR Executive,147825,0 +11359,Female,41,PhD,4,0,21,76,4,1.0,7,82,Urban,Manager,94991,0 +11360,Male,22,Diploma,6,10,78,88,18,5.0,4,90,Urban,ML Engineer,86708,1 +11361,Female,36,Diploma,15,54,87,68,81,2.0,2,92,Urban,Software Engineer,90922,1 +11362,Male,35,Diploma,17,5,51,91,41,8.0,0,67,Urban,Software Engineer,140160,0 +11363,Female,36,Bachelors,11,80,21,22,49,4.0,2,86,Urban,Manager,45393,0 +11364,Male,52,Diploma,2,90,3,6,81,8.0,1,84,Rural,Software Engineer,142585,0 +11365,Male,57,Bachelors,11,21,29,36,96,7.0,0,20,Urban,HR Executive,90359,0 +11366,Female,24,Masters,13,79,94,35,99,8.0,7,2,Rural,Software Engineer,110857,0 +11367,Male,41,High School,6,32,60,49,18,6.0,4,61,Semi-Urban,Data Analyst,134036,0 +11368,Other,47,Diploma,16,55,62,10,72,9.0,7,46,Semi-Urban,ML Engineer,51338,0 +11369,Male,44,High School,16,25,20,59,1,3.0,2,51,Urban,Manager,55562,0 +11370,Female,26,High School,15,51,87,38,69,0.0,1,72,Rural,ML Engineer,23529,1 +11371,Female,54,High School,6,39,45,15,85,6.0,7,66,Urban,Manager,53152,0 +11372,Male,58,Diploma,6,39,31,59,74,0.0,7,75,Urban,Manager,46728,0 +11373,Female,38,Bachelors,3,30,8,5,87,8.0,7,38,Urban,Manager,109999,0 +11374,Male,41,Diploma,9,70,56,83,66,2.0,3,50,Rural,Manager,37018,1 +11375,Female,35,Bachelors,7,90,19,29,96,2.0,5,25,Semi-Urban,Manager,86650,0 +11376,Male,50,Masters,7,13,88,39,86,8.0,1,94,Semi-Urban,Data Analyst,146880,0 +11377,Female,26,Masters,6,88,46,95,50,5.0,2,66,Urban,HR Executive,39487,1 +11378,Male,57,Diploma,16,42,96,54,76,0.0,7,62,Urban,Software Engineer,84340,1 +11379,Male,35,Bachelors,9,7,96,91,42,7.0,7,1,Urban,HR Executive,112112,0 +11380,Male,38,High School,4,58,67,83,28,2.0,6,10,Urban,Manager,144575,0 +11381,Male,30,Diploma,16,5,5,23,37,1.0,3,97,Urban,HR Executive,128932,0 +11382,Female,23,Diploma,11,19,20,40,57,5.0,5,80,Urban,Software Engineer,110276,0 +11383,Female,47,Bachelors,8,93,42,25,66,0.0,4,10,Urban,Data Analyst,105369,0 +11384,Female,44,Bachelors,5,1,6,17,93,7.0,0,60,Semi-Urban,HR Executive,111570,0 +11385,Male,24,Masters,8,31,35,7,1,8.0,3,41,Urban,Software Engineer,110475,0 +11386,Male,31,Bachelors,8,77,79,27,93,3.0,2,96,Rural,Software Engineer,51824,1 +11387,Male,50,Bachelors,18,6,40,34,56,6.0,6,10,Rural,HR Executive,127747,0 +11388,Female,21,High School,4,47,1,25,26,7.0,1,33,Semi-Urban,Manager,93755,0 +11389,Other,28,Bachelors,16,66,67,41,84,6.0,7,50,Semi-Urban,HR Executive,59313,0 +11390,Male,31,Masters,9,54,97,57,32,1.0,6,86,Rural,Software Engineer,62794,1 +11391,Male,55,High School,8,54,88,84,21,7.0,2,14,Urban,HR Executive,105698,1 +11392,Male,35,Bachelors,13,91,39,42,97,2.0,0,38,Urban,Data Analyst,79039,0 +11393,Female,29,Masters,14,8,55,27,58,8.0,1,16,Semi-Urban,ML Engineer,46064,0 +11394,Female,32,Diploma,14,69,3,44,66,2.0,7,47,Semi-Urban,HR Executive,77293,0 +11395,Female,34,Diploma,14,46,88,37,20,0.0,1,78,Rural,Manager,93809,1 +11396,Male,26,Bachelors,9,37,69,21,97,3.0,6,93,Urban,Data Analyst,127325,0 +11397,Female,33,High School,17,3,40,54,86,4.0,5,12,Urban,Data Analyst,88874,0 +11398,Female,39,Masters,16,42,78,77,73,9.0,6,70,Urban,Software Engineer,85335,1 +11399,Male,27,High School,16,23,46,98,91,3.0,5,55,Urban,HR Executive,73493,0 +11400,Male,36,Bachelors,10,78,77,26,44,7.0,5,38,Semi-Urban,Manager,80266,0 +11401,Male,49,Bachelors,16,65,92,40,46,9.0,3,7,Urban,Software Engineer,138875,0 +11402,Male,56,Bachelors,6,79,47,30,85,5.0,2,92,Rural,HR Executive,95718,1 +11403,Female,22,High School,2,34,61,23,99,1.0,0,33,Rural,Data Analyst,22163,0 +11404,Male,53,Masters,4,52,9,32,76,2.0,6,53,Urban,HR Executive,69106,0 +11405,Female,52,Diploma,11,7,66,99,98,2.0,7,81,Urban,Data Analyst,86626,1 +11406,Male,21,Bachelors,9,58,48,37,66,7.0,3,26,Urban,Data Analyst,43405,0 +11407,Male,22,Diploma,16,58,21,84,48,2.0,2,29,Urban,Data Analyst,130045,0 +11408,Male,58,High School,9,32,36,91,15,2.0,2,98,Semi-Urban,Data Analyst,141655,1 +11409,Male,50,Diploma,12,5,21,21,89,0.0,3,85,Rural,Manager,37702,0 +11410,Male,47,Bachelors,18,58,96,95,9,5.0,7,18,Semi-Urban,Data Analyst,100665,1 +11411,Male,38,Bachelors,19,68,77,74,80,5.0,6,62,Rural,Software Engineer,68876,1 +11412,Male,24,Masters,16,30,97,96,69,7.0,3,65,Rural,ML Engineer,40982,1 +11413,Male,36,Masters,12,15,36,27,25,3.0,2,7,Urban,Data Analyst,98525,0 +11414,Male,52,Diploma,10,31,17,25,94,9.0,1,76,Urban,Software Engineer,132590,0 +11415,Male,42,Bachelors,10,62,11,73,43,5.0,3,24,Urban,Data Analyst,110582,0 +11416,Male,51,Diploma,13,21,65,47,93,6.0,2,77,Rural,Manager,23143,0 +11417,Female,35,Masters,12,42,54,85,92,3.0,7,96,Semi-Urban,ML Engineer,62795,1 +11418,Male,44,Bachelors,0,1,39,67,99,9.0,4,86,Urban,HR Executive,25520,0 +11419,Female,29,Bachelors,16,41,52,82,11,3.0,4,43,Semi-Urban,HR Executive,121501,0 +11420,Male,23,Bachelors,11,38,58,74,46,0.0,7,10,Urban,Data Analyst,82214,0 +11421,Female,23,Masters,1,59,19,0,41,6.0,4,34,Semi-Urban,HR Executive,132982,0 +11422,Male,54,Bachelors,7,32,64,8,46,8.0,5,33,Semi-Urban,Manager,124767,0 +11423,Female,22,Masters,14,83,22,99,90,1.0,6,79,Urban,Software Engineer,49805,1 +11424,Male,51,Diploma,12,86,86,73,66,8.0,4,11,Semi-Urban,ML Engineer,87382,1 +11425,Female,47,Diploma,15,4,25,51,73,7.0,4,86,Urban,Data Analyst,95685,0 +11426,Male,37,Diploma,13,21,26,80,45,0.0,1,95,Urban,Data Analyst,32642,0 +11427,Male,30,Bachelors,7,98,64,87,41,2.0,5,8,Semi-Urban,Data Analyst,40314,1 +11428,Female,58,Diploma,18,93,76,44,96,8.0,1,43,Semi-Urban,Data Analyst,132715,1 +11429,Male,45,Bachelors,11,85,94,84,26,2.0,1,24,Semi-Urban,Software Engineer,78655,1 +11430,Male,31,Bachelors,9,21,50,26,7,6.0,5,80,Rural,Data Analyst,69341,0 +11431,Male,57,Diploma,13,6,20,66,58,1.0,5,81,Semi-Urban,HR Executive,98314,0 +11432,Female,49,Bachelors,3,3,48,62,21,1.0,4,47,Semi-Urban,Software Engineer,98772,0 +11433,Other,31,High School,13,33,57,72,74,3.0,7,1,Semi-Urban,ML Engineer,126139,0 +11434,Male,55,Bachelors,4,66,82,61,41,3.0,6,42,Semi-Urban,ML Engineer,105960,1 +11435,Female,51,Bachelors,10,47,72,57,7,7.0,3,81,Urban,HR Executive,139052,1 +11436,Male,48,High School,18,19,21,94,49,0.0,1,15,Semi-Urban,Data Analyst,98448,0 +11437,Male,33,Diploma,0,79,90,3,4,5.0,4,69,Semi-Urban,ML Engineer,108147,1 +11438,Female,53,High School,11,79,34,1,43,4.0,4,56,Rural,Manager,26738,0 +11439,Female,34,High School,7,12,95,54,97,6.0,1,13,Rural,Manager,82677,0 +11440,Female,51,Bachelors,9,51,47,19,1,3.0,5,58,Urban,ML Engineer,32574,0 +11441,Male,47,Masters,2,46,70,36,19,6.0,0,5,Urban,Data Analyst,59680,0 +11442,Male,51,Bachelors,6,10,96,34,15,7.0,7,2,Urban,Manager,141095,0 +11443,Male,56,Masters,14,83,40,38,80,0.0,1,1,Urban,Data Analyst,62699,0 +11444,Male,32,Diploma,4,43,87,61,47,9.0,4,25,Urban,Software Engineer,143272,0 +11445,Male,51,Bachelors,10,19,4,70,7,6.0,2,32,Rural,Data Analyst,29188,0 +11446,Female,22,Bachelors,6,4,33,54,65,8.0,3,97,Rural,HR Executive,76024,0 +11447,Female,23,Diploma,5,44,91,74,76,5.0,3,52,Rural,HR Executive,23823,1 +11448,Male,51,Bachelors,19,3,70,63,73,6.0,5,4,Rural,Manager,48820,0 +11449,Male,48,Bachelors,6,77,78,93,44,0.0,0,23,Urban,ML Engineer,99710,1 +11450,Female,54,Diploma,10,24,88,69,12,2.0,3,74,Rural,Software Engineer,44979,1 +11451,Male,52,Bachelors,2,57,57,17,44,4.0,0,77,Rural,Manager,143170,0 +11452,Female,36,Bachelors,16,14,76,10,21,5.0,1,84,Semi-Urban,Data Analyst,91005,0 +11453,Male,37,Diploma,10,27,96,12,14,3.0,4,3,Urban,Data Analyst,94698,0 +11454,Male,39,Bachelors,12,95,99,46,26,2.0,6,64,Urban,ML Engineer,124624,1 +11455,Other,57,Bachelors,13,43,27,20,2,4.0,5,50,Rural,ML Engineer,35780,0 +11456,Male,48,Bachelors,11,46,25,50,84,8.0,4,95,Semi-Urban,ML Engineer,63500,0 +11457,Male,52,Bachelors,3,77,79,53,41,1.0,1,34,Rural,Data Analyst,116548,1 +11458,Male,23,High School,2,28,38,64,10,5.0,4,72,Urban,Data Analyst,56998,0 +11459,Female,53,Masters,3,70,91,78,30,1.0,0,81,Semi-Urban,HR Executive,117873,1 +11460,Female,40,Diploma,8,10,49,8,22,2.0,3,71,Urban,Software Engineer,149824,0 +11461,Male,55,Bachelors,2,98,79,7,93,3.0,5,45,Urban,ML Engineer,144102,0 +11462,Male,55,Bachelors,9,49,51,81,46,4.0,3,23,Semi-Urban,HR Executive,37160,0 +11463,Female,45,Bachelors,2,39,61,47,9,2.0,1,92,Rural,ML Engineer,61963,0 +11464,Male,46,Bachelors,2,39,36,12,79,8.0,0,60,Urban,Data Analyst,129171,0 +11465,Female,58,Bachelors,3,24,66,45,45,0.0,4,14,Urban,Software Engineer,106610,0 +11466,Male,47,Bachelors,10,32,18,72,90,4.0,1,38,Urban,ML Engineer,96451,0 +11467,Male,38,High School,14,14,18,78,52,0.0,3,16,Urban,Data Analyst,132172,0 +11468,Female,46,Diploma,18,96,83,39,46,3.0,3,69,Rural,Data Analyst,48043,1 +11469,Male,34,Diploma,9,76,13,72,55,8.0,5,98,Urban,ML Engineer,63127,1 +11470,Female,27,Diploma,19,78,5,47,89,3.0,0,35,Urban,Data Analyst,131426,0 +11471,Male,37,Bachelors,19,78,21,45,39,9.0,2,25,Urban,ML Engineer,126559,0 +11472,Male,30,Masters,15,66,30,80,78,6.0,3,1,Semi-Urban,Software Engineer,84799,0 +11473,Other,30,Diploma,7,96,31,34,17,8.0,7,9,Semi-Urban,Data Analyst,35771,0 +11474,Male,31,PhD,3,16,16,66,21,0.0,0,23,Semi-Urban,HR Executive,104458,0 +11475,Female,36,PhD,7,47,89,21,95,4.0,0,98,Semi-Urban,HR Executive,98597,1 +11476,Male,26,Diploma,13,96,35,94,82,8.0,7,66,Rural,ML Engineer,32431,1 +11477,Female,56,Diploma,8,0,21,86,34,2.0,7,89,Urban,ML Engineer,72883,0 +11478,Female,58,Bachelors,13,21,32,49,66,2.0,4,43,Urban,ML Engineer,32539,0 +11479,Male,48,Bachelors,8,43,88,82,64,5.0,1,20,Urban,Software Engineer,118892,0 +11480,Female,57,Bachelors,19,94,89,71,90,2.0,1,14,Urban,HR Executive,142537,1 +11481,Female,45,Diploma,4,70,72,72,10,2.0,4,27,Urban,Manager,148061,1 +11482,Male,54,Masters,6,56,52,40,88,7.0,2,10,Rural,ML Engineer,89244,0 +11483,Male,45,Diploma,0,53,44,20,10,8.0,5,79,Urban,Manager,77264,0 +11484,Male,21,Masters,1,86,51,35,73,1.0,3,69,Rural,Software Engineer,82384,1 +11485,Male,55,Diploma,3,81,85,9,98,7.0,1,79,Semi-Urban,ML Engineer,148851,1 +11486,Male,57,Masters,17,99,74,79,91,7.0,1,23,Semi-Urban,Manager,67259,1 +11487,Male,31,Diploma,1,25,27,22,33,8.0,6,32,Rural,ML Engineer,67472,0 +11488,Male,54,Diploma,11,29,9,57,92,7.0,0,52,Urban,Software Engineer,111515,0 +11489,Female,50,Masters,5,88,88,23,2,3.0,3,66,Semi-Urban,Manager,35985,1 +11490,Male,21,High School,0,23,99,3,44,1.0,7,77,Semi-Urban,Software Engineer,65860,0 +11491,Female,49,High School,1,83,61,78,96,4.0,7,35,Urban,HR Executive,146526,1 +11492,Male,49,High School,6,65,72,63,25,0.0,2,2,Semi-Urban,ML Engineer,142369,0 +11493,Male,29,Diploma,8,75,11,39,25,9.0,6,84,Urban,HR Executive,89242,0 +11494,Female,39,Bachelors,12,66,58,9,77,3.0,5,31,Rural,HR Executive,76643,0 +11495,Male,42,Bachelors,1,0,86,29,57,9.0,7,22,Urban,Software Engineer,121382,0 +11496,Male,36,Diploma,19,92,29,22,57,7.0,3,3,Semi-Urban,ML Engineer,64960,0 +11497,Male,42,Bachelors,11,44,53,39,99,9.0,4,78,Semi-Urban,Manager,86424,0 +11498,Male,56,Bachelors,13,80,32,4,93,0.0,4,76,Urban,HR Executive,104042,0 +11499,Male,22,Bachelors,11,3,63,51,12,9.0,5,55,Semi-Urban,HR Executive,21590,0 +11500,Other,40,Bachelors,4,87,43,37,56,4.0,3,59,Urban,Software Engineer,74357,0 +11501,Male,25,Bachelors,18,78,12,24,92,4.0,5,2,Rural,HR Executive,34624,0 +11502,Female,48,Masters,1,63,57,66,72,0.0,1,43,Rural,Data Analyst,115804,0 +11503,Female,40,Diploma,7,18,46,9,82,0.0,5,92,Urban,ML Engineer,36183,0 +11504,Male,47,High School,13,16,34,87,93,0.0,1,85,Urban,Manager,121702,0 +11505,Male,36,High School,0,77,95,64,86,0.0,6,4,Semi-Urban,Manager,91737,1 +11506,Female,59,Masters,9,24,35,54,52,1.0,7,32,Urban,ML Engineer,38475,0 +11507,Female,58,Diploma,9,37,36,48,2,8.0,3,20,Semi-Urban,HR Executive,28909,0 +11508,Male,41,Masters,10,4,75,87,6,5.0,0,97,Urban,Software Engineer,106513,1 +11509,Male,56,PhD,4,73,61,7,51,2.0,3,87,Semi-Urban,HR Executive,47617,0 +11510,Male,51,Masters,6,25,39,73,87,4.0,1,57,Rural,Data Analyst,34333,0 +11511,Male,55,Bachelors,14,99,55,49,46,9.0,6,14,Urban,HR Executive,75001,0 +11512,Male,48,Masters,17,43,98,1,74,6.0,7,56,Urban,Manager,59341,0 +11513,Female,31,Bachelors,2,87,60,27,48,4.0,2,45,Semi-Urban,HR Executive,95411,0 +11514,Male,53,High School,14,52,20,56,88,3.0,4,48,Urban,Data Analyst,110515,0 +11515,Female,27,High School,13,92,48,71,40,0.0,2,4,Urban,HR Executive,98766,0 +11516,Female,24,PhD,13,53,94,69,61,3.0,7,74,Semi-Urban,HR Executive,131606,1 +11517,Male,33,Masters,14,48,97,97,80,5.0,4,95,Rural,HR Executive,66827,1 +11518,Male,53,Masters,12,28,2,18,84,9.0,7,62,Rural,HR Executive,28530,0 +11519,Female,41,Bachelors,0,65,44,90,34,9.0,0,38,Urban,Software Engineer,112160,0 +11520,Female,29,Bachelors,2,51,74,40,47,2.0,1,80,Rural,Data Analyst,85788,1 +11521,Female,59,Masters,9,11,21,57,24,6.0,5,74,Urban,HR Executive,38926,0 +11522,Male,45,Masters,14,34,44,7,84,4.0,4,67,Semi-Urban,Software Engineer,24259,0 +11523,Male,54,Diploma,3,43,36,52,97,6.0,0,9,Rural,ML Engineer,109236,0 +11524,Male,31,Bachelors,4,49,31,86,32,5.0,6,22,Urban,HR Executive,90183,0 +11525,Male,43,High School,19,77,1,98,84,9.0,5,81,Semi-Urban,Software Engineer,76486,1 +11526,Female,49,High School,4,81,96,53,15,5.0,3,45,Urban,ML Engineer,55960,1 +11527,Male,56,Diploma,16,1,69,25,50,6.0,3,29,Rural,Software Engineer,127856,0 +11528,Female,45,Bachelors,12,85,16,55,1,9.0,2,13,Rural,HR Executive,65406,0 +11529,Male,45,Bachelors,3,1,91,30,58,8.0,6,53,Semi-Urban,Data Analyst,94447,0 +11530,Female,33,Diploma,9,91,19,37,96,8.0,1,17,Urban,Data Analyst,49002,0 +11531,Other,26,Bachelors,14,70,45,93,10,3.0,1,94,Urban,ML Engineer,141204,1 +11532,Male,27,Bachelors,3,44,27,26,65,1.0,6,38,Rural,HR Executive,121462,0 +11533,Female,40,Bachelors,8,31,14,28,1,8.0,2,38,Urban,ML Engineer,149514,0 +11534,Male,26,High School,16,71,35,58,27,6.0,0,54,Urban,Manager,84090,0 +11535,Male,27,High School,9,30,38,67,97,3.0,3,26,Urban,Manager,146237,0 +11536,Female,23,High School,10,92,42,38,41,3.0,1,94,Rural,ML Engineer,135440,1 +11537,Female,53,Bachelors,3,17,74,73,25,8.0,7,92,Urban,Manager,49541,1 +11538,Male,37,Bachelors,10,51,48,89,45,7.0,3,94,Semi-Urban,HR Executive,65669,1 +11539,Male,55,High School,2,62,55,26,85,7.0,5,28,Urban,Data Analyst,130140,0 +11540,Female,59,Diploma,6,17,13,7,26,0.0,6,91,Urban,HR Executive,30151,0 +11541,Female,25,Bachelors,4,76,61,57,49,4.0,4,26,Urban,Data Analyst,110695,0 +11542,Male,55,High School,6,25,96,25,6,7.0,0,14,Urban,Data Analyst,43039,0 +11543,Female,28,High School,9,46,33,58,40,6.0,7,11,Rural,Software Engineer,41939,0 +11544,Male,58,Bachelors,15,56,10,66,58,3.0,4,2,Semi-Urban,Data Analyst,26040,0 +11545,Male,58,Diploma,9,57,61,23,82,6.0,7,94,Urban,ML Engineer,113404,1 +11546,Male,41,High School,2,7,68,6,56,3.0,4,33,Urban,Manager,104573,0 +11547,Male,56,Masters,3,35,89,45,39,5.0,3,24,Rural,HR Executive,130437,0 +11548,Female,55,Bachelors,6,50,60,79,77,9.0,4,90,Urban,HR Executive,91855,1 +11549,Male,40,Bachelors,1,32,71,85,40,2.0,0,59,Rural,Data Analyst,71407,1 +11550,Other,34,Bachelors,8,40,94,3,30,0.0,7,98,Semi-Urban,Data Analyst,67944,0 +11551,Male,58,Masters,4,21,10,49,41,6.0,3,46,Rural,HR Executive,54242,0 +11552,Female,34,Diploma,18,12,80,31,54,2.0,1,34,Semi-Urban,HR Executive,66275,0 +11553,Female,39,Bachelors,18,59,99,75,11,1.0,5,77,Rural,ML Engineer,59657,1 +11554,Female,26,Masters,12,7,3,54,58,1.0,6,63,Semi-Urban,HR Executive,81195,0 +11555,Female,50,Bachelors,11,53,43,90,53,3.0,3,39,Urban,HR Executive,59348,0 +11556,Male,23,Diploma,19,18,22,54,7,3.0,7,6,Semi-Urban,Software Engineer,135568,0 +11557,Female,23,High School,15,89,38,81,22,6.0,0,65,Semi-Urban,Manager,81940,1 +11558,Female,54,PhD,0,26,18,50,15,9.0,7,87,Urban,Data Analyst,115713,0 +11559,Male,23,Bachelors,4,74,77,40,94,0.0,2,0,Semi-Urban,Manager,128052,0 +11560,Female,49,Masters,9,10,56,77,21,8.0,1,14,Urban,Software Engineer,22972,0 +11561,Male,41,Diploma,13,87,10,62,19,8.0,1,80,Rural,Manager,41579,1 +11562,Male,41,Bachelors,10,53,31,57,7,8.0,5,4,Rural,Data Analyst,43909,0 +11563,Female,23,High School,19,53,0,24,76,2.0,2,75,Semi-Urban,Manager,117704,0 +11564,Male,57,Masters,11,59,66,58,5,6.0,4,95,Rural,Data Analyst,133694,1 +11565,Female,37,High School,10,85,54,55,86,9.0,5,22,Urban,ML Engineer,146875,0 +11566,Male,42,Bachelors,14,3,14,3,19,8.0,4,89,Semi-Urban,HR Executive,97699,0 +11567,Male,30,Masters,7,27,15,39,2,8.0,3,22,Urban,ML Engineer,119458,0 +11568,Male,28,High School,19,31,56,40,56,1.0,1,79,Urban,Data Analyst,25516,0 +11569,Male,32,Bachelors,19,24,6,65,61,4.0,7,83,Urban,HR Executive,119993,0 +11570,Female,32,Bachelors,9,31,74,53,72,4.0,5,73,Urban,HR Executive,78028,0 +11571,Male,34,Bachelors,16,19,92,78,27,4.0,3,5,Urban,ML Engineer,106361,0 +11572,Male,37,Diploma,4,23,29,19,64,8.0,3,31,Urban,Manager,50128,0 +11573,Male,37,High School,13,78,67,71,20,2.0,1,40,Rural,Manager,77567,1 +11574,Male,50,Bachelors,13,5,15,72,72,4.0,2,34,Urban,Data Analyst,137042,0 +11575,Female,33,Bachelors,10,32,49,44,10,6.0,6,10,Urban,ML Engineer,52773,0 +11576,Male,26,High School,18,12,64,20,72,4.0,1,45,Semi-Urban,ML Engineer,27049,0 +11577,Female,39,Bachelors,1,36,61,9,91,3.0,3,26,Urban,Manager,119139,0 +11578,Female,46,Bachelors,8,10,17,81,31,5.0,7,75,Semi-Urban,ML Engineer,117906,0 +11579,Female,33,Bachelors,13,35,4,35,32,0.0,5,31,Semi-Urban,HR Executive,47164,0 +11580,Female,50,Bachelors,10,59,91,81,18,2.0,4,20,Rural,ML Engineer,57501,1 +11581,Male,58,Diploma,17,93,0,94,81,6.0,3,81,Urban,Software Engineer,37882,1 +11582,Male,43,Bachelors,0,77,39,18,29,1.0,2,52,Semi-Urban,ML Engineer,143656,0 +11583,Female,25,Diploma,5,71,16,58,15,1.0,7,65,Urban,Software Engineer,109473,0 +11584,Female,31,High School,11,86,7,8,56,5.0,6,69,Urban,Software Engineer,114946,0 +11585,Female,43,Bachelors,9,41,6,16,61,2.0,4,49,Urban,Manager,38873,0 +11586,Female,37,Bachelors,15,38,43,69,3,2.0,2,74,Urban,Data Analyst,77225,0 +11587,Male,40,Masters,11,32,71,77,24,8.0,7,7,Urban,Manager,29543,0 +11588,Male,50,High School,16,20,55,48,17,2.0,7,95,Urban,ML Engineer,25900,0 +11589,Female,33,Bachelors,0,21,27,20,39,3.0,4,21,Semi-Urban,Manager,52417,0 +11590,Female,39,Bachelors,5,95,90,27,29,6.0,7,49,Urban,Manager,20024,1 +11591,Male,51,Bachelors,9,30,89,36,92,1.0,5,2,Urban,Data Analyst,68368,0 +11592,Female,27,Masters,8,0,77,53,23,7.0,6,48,Urban,Manager,80132,0 +11593,Male,24,Bachelors,8,34,47,22,88,8.0,5,92,Urban,ML Engineer,52081,0 +11594,Male,28,Diploma,0,33,95,49,55,1.0,0,15,Rural,Data Analyst,140050,0 +11595,Female,32,Bachelors,0,60,39,58,91,6.0,1,39,Urban,Software Engineer,145077,0 +11596,Female,36,Bachelors,15,75,40,24,34,7.0,4,55,Urban,Manager,85786,0 +11597,Male,29,Bachelors,1,10,35,59,13,0.0,7,75,Rural,Data Analyst,94069,0 +11598,Male,29,Bachelors,19,1,54,43,37,0.0,1,95,Semi-Urban,Software Engineer,105322,0 +11599,Male,42,High School,12,96,15,3,95,6.0,5,11,Semi-Urban,Manager,51351,0 +11600,Female,48,Diploma,15,15,39,27,12,0.0,5,15,Semi-Urban,Data Analyst,126035,0 +11601,Male,33,Bachelors,16,53,23,79,31,2.0,6,17,Urban,ML Engineer,66475,0 +11602,Female,21,Bachelors,15,62,0,21,40,2.0,7,43,Urban,Data Analyst,118103,0 +11603,Female,55,High School,5,94,38,97,2,3.0,7,61,Urban,ML Engineer,114052,1 +11604,Female,44,Bachelors,16,46,8,56,83,8.0,4,5,Urban,ML Engineer,49865,0 +11605,Male,47,PhD,2,93,81,10,20,3.0,2,13,Semi-Urban,Manager,49484,0 +11606,Female,47,Bachelors,9,74,98,21,89,1.0,7,36,Rural,Manager,87143,0 +11607,Male,57,Bachelors,11,95,55,99,90,2.0,2,88,Semi-Urban,Manager,105315,1 +11608,Male,47,Diploma,0,74,42,5,22,4.0,2,50,Urban,HR Executive,101779,0 +11609,Male,54,Masters,13,69,63,5,99,0.0,7,88,Urban,Data Analyst,82057,0 +11610,Male,28,Bachelors,12,19,57,22,84,1.0,1,23,Semi-Urban,Manager,32853,0 +11611,Female,54,Bachelors,9,20,82,41,86,9.0,1,41,Rural,Manager,53121,0 +11612,Male,41,Masters,19,39,17,1,39,6.0,3,14,Rural,ML Engineer,26967,0 +11613,Male,55,Diploma,13,58,34,43,37,5.0,2,65,Rural,Software Engineer,20820,0 +11614,Other,37,Masters,7,24,93,58,52,6.0,0,83,Semi-Urban,HR Executive,34051,1 +11615,Male,43,Diploma,19,38,86,70,70,9.0,3,67,Urban,Manager,33702,1 +11616,Female,28,Bachelors,8,60,55,25,25,7.0,7,8,Urban,Manager,116036,0 +11617,Male,36,High School,3,58,37,49,17,5.0,6,82,Urban,ML Engineer,33976,0 +11618,Male,51,Diploma,14,70,33,46,1,9.0,3,66,Rural,Manager,37222,0 +11619,Female,32,Bachelors,5,24,68,62,84,5.0,0,69,Rural,HR Executive,55009,0 +11620,Male,50,High School,8,30,29,41,38,6.0,0,68,Rural,Software Engineer,55139,0 +11621,Male,44,Masters,16,53,62,74,11,0.0,7,8,Rural,HR Executive,57024,0 +11622,Male,51,Bachelors,14,45,78,51,0,4.0,5,96,Urban,Manager,112335,1 +11623,Male,32,Diploma,17,19,70,60,64,7.0,0,32,Semi-Urban,ML Engineer,78927,0 +11624,Male,42,Diploma,14,2,78,96,30,3.0,7,65,Urban,HR Executive,121145,1 +11625,Male,37,Bachelors,11,97,70,42,6,7.0,5,39,Rural,ML Engineer,134905,1 +11626,Male,24,Bachelors,0,97,19,85,93,1.0,4,87,Urban,Data Analyst,35451,1 +11627,Female,53,Diploma,11,57,70,3,17,9.0,5,73,Urban,Data Analyst,124724,0 +11628,Male,45,Bachelors,4,0,32,51,26,0.0,0,55,Urban,Manager,102901,0 +11629,Male,35,Bachelors,2,44,33,12,10,7.0,7,54,Urban,Software Engineer,100524,0 +11630,Male,39,Diploma,3,88,85,43,67,0.0,6,11,Urban,ML Engineer,66796,0 +11631,Female,36,Bachelors,16,44,62,89,14,6.0,2,6,Urban,HR Executive,85090,0 +11632,Female,50,Bachelors,4,72,24,85,35,0.0,7,43,Rural,Manager,116465,0 +11633,Female,29,Bachelors,16,72,72,43,36,6.0,5,24,Urban,HR Executive,29650,0 +11634,Female,42,Bachelors,10,24,73,29,67,1.0,5,28,Urban,ML Engineer,98537,0 +11635,Male,53,Masters,5,32,14,85,13,3.0,5,21,Rural,Data Analyst,29996,0 +11636,Male,55,PhD,8,53,96,81,98,9.0,2,2,Semi-Urban,ML Engineer,68618,0 +11637,Female,28,Bachelors,10,80,91,99,39,4.0,6,79,Rural,Manager,136530,1 +11638,Female,59,Bachelors,9,8,71,86,50,4.0,4,40,Urban,Manager,145713,0 +11639,Male,58,Masters,1,95,29,95,0,0.0,7,99,Rural,HR Executive,45499,1 +11640,Male,36,Bachelors,7,19,77,9,19,5.0,2,81,Rural,Manager,74649,0 +11641,Other,58,Bachelors,11,16,68,14,81,4.0,2,61,Semi-Urban,ML Engineer,105938,0 +11642,Female,27,Bachelors,14,44,16,65,48,1.0,2,47,Rural,HR Executive,92964,0 +11643,Male,35,High School,17,44,7,80,35,2.0,7,41,Semi-Urban,Data Analyst,117545,0 +11644,Female,57,Bachelors,11,38,19,80,23,2.0,0,49,Urban,Manager,114230,0 +11645,Male,45,Bachelors,3,60,30,94,60,3.0,0,17,Urban,ML Engineer,139798,0 +11646,Male,29,Bachelors,16,64,78,77,98,5.0,3,26,Urban,Manager,89102,1 +11647,Male,48,High School,13,60,42,4,20,1.0,7,20,Semi-Urban,Software Engineer,133713,0 +11648,Male,32,Diploma,9,34,80,81,57,0.0,5,94,Urban,Manager,92572,1 +11649,Male,36,Bachelors,16,46,53,58,77,2.0,1,25,Semi-Urban,HR Executive,123101,0 +11650,Female,40,High School,11,25,88,39,13,7.0,6,58,Urban,HR Executive,41814,0 +11651,Male,48,Diploma,16,35,81,28,19,9.0,7,54,Urban,Data Analyst,107223,0 +11652,Male,24,Masters,10,55,57,55,3,5.0,3,56,Semi-Urban,ML Engineer,82630,0 +11653,Male,38,Diploma,16,27,52,66,37,4.0,3,39,Urban,Data Analyst,60367,0 +11654,Male,37,Masters,4,23,49,2,60,6.0,6,67,Urban,HR Executive,24155,0 +11655,Female,54,Bachelors,18,15,53,74,88,5.0,7,53,Rural,ML Engineer,94412,0 +11656,Female,30,High School,17,10,91,95,53,9.0,4,21,Semi-Urban,Manager,62614,0 +11657,Other,50,Bachelors,17,80,69,72,44,9.0,1,37,Urban,HR Executive,55948,1 +11658,Other,52,High School,3,2,65,62,48,4.0,3,0,Urban,Manager,51129,0 +11659,Male,49,Bachelors,2,72,56,13,27,9.0,7,30,Urban,Manager,131176,0 +11660,Male,33,Diploma,0,46,40,88,90,0.0,6,29,Semi-Urban,HR Executive,101084,0 +11661,Female,29,Diploma,4,45,95,74,12,0.0,2,76,Urban,Manager,116722,1 +11662,Other,26,Diploma,8,61,42,86,46,8.0,5,55,Urban,Software Engineer,32901,1 +11663,Female,40,Masters,12,60,4,38,81,6.0,2,51,Rural,Manager,95244,0 +11664,Female,43,Bachelors,14,19,52,32,92,2.0,4,23,Urban,Software Engineer,134900,0 +11665,Female,24,High School,8,14,92,98,82,0.0,3,31,Urban,Data Analyst,138370,0 +11666,Male,31,High School,19,29,12,80,13,0.0,4,44,Rural,Data Analyst,94559,0 +11667,Male,53,Diploma,2,47,44,49,55,5.0,0,60,Urban,Data Analyst,25936,0 +11668,Female,40,Bachelors,14,33,85,29,24,2.0,5,90,Semi-Urban,Manager,88874,0 +11669,Female,44,Bachelors,1,99,40,63,83,0.0,5,39,Urban,Software Engineer,122900,1 +11670,Male,22,Bachelors,3,24,67,87,26,3.0,2,83,Urban,ML Engineer,136212,1 +11671,Male,31,Bachelors,8,82,50,55,80,6.0,3,56,Semi-Urban,ML Engineer,123864,1 +11672,Male,40,High School,13,15,66,78,86,5.0,1,46,Urban,HR Executive,106982,0 +11673,Male,53,Bachelors,9,40,8,12,16,0.0,4,20,Urban,Software Engineer,147445,0 +11674,Female,22,Bachelors,2,19,54,47,21,8.0,5,13,Semi-Urban,Software Engineer,125877,0 +11675,Male,59,Masters,11,11,95,61,24,8.0,6,30,Urban,Data Analyst,136120,0 +11676,Male,39,Masters,10,80,28,24,72,5.0,2,76,Urban,Software Engineer,51404,0 +11677,Male,33,Masters,3,81,15,59,55,3.0,0,81,Semi-Urban,Software Engineer,71738,1 +11678,Female,33,Bachelors,18,13,37,47,75,7.0,3,40,Rural,Manager,138335,0 +11679,Male,25,Bachelors,4,10,46,90,78,4.0,5,98,Rural,Software Engineer,136357,1 +11680,Male,54,Bachelors,5,36,13,49,18,9.0,1,62,Urban,Software Engineer,69751,0 +11681,Male,58,Diploma,16,74,10,14,5,7.0,5,5,Semi-Urban,Manager,64030,0 +11682,Male,48,Bachelors,5,28,51,84,17,5.0,0,66,Urban,ML Engineer,45012,0 +11683,Male,29,High School,16,62,81,84,67,3.0,5,97,Urban,HR Executive,107274,1 +11684,Male,23,Masters,9,18,70,37,46,4.0,6,19,Urban,Data Analyst,90168,0 +11685,Female,43,Diploma,17,10,86,76,89,7.0,4,75,Urban,Data Analyst,137563,1 +11686,Male,31,Bachelors,15,51,30,97,87,4.0,2,66,Semi-Urban,Data Analyst,112988,1 +11687,Male,48,Masters,17,10,34,28,19,3.0,0,3,Semi-Urban,Manager,71971,0 +11688,Female,35,Masters,14,7,94,22,56,2.0,4,20,Urban,Software Engineer,24619,0 +11689,Male,54,Bachelors,14,21,85,34,24,4.0,0,73,Urban,ML Engineer,58099,0 +11690,Female,41,High School,8,58,39,7,19,8.0,3,88,Rural,HR Executive,138765,0 +11691,Male,29,Masters,13,95,11,18,63,4.0,5,96,Urban,Manager,141256,0 +11692,Male,38,Diploma,1,31,99,4,92,4.0,3,42,Semi-Urban,ML Engineer,37409,0 +11693,Female,35,Masters,18,87,52,1,67,1.0,4,6,Urban,HR Executive,91787,0 +11694,Female,55,Bachelors,14,79,86,93,22,1.0,2,53,Urban,ML Engineer,119832,1 +11695,Male,30,Masters,13,54,42,83,28,0.0,2,92,Semi-Urban,ML Engineer,128481,1 +11696,Male,27,Diploma,12,80,3,59,38,0.0,3,17,Urban,Data Analyst,89427,0 +11697,Male,43,Diploma,9,68,7,99,49,2.0,2,37,Urban,HR Executive,141529,0 +11698,Female,53,Bachelors,0,23,12,60,59,5.0,6,98,Rural,ML Engineer,72400,0 +11699,Female,33,Bachelors,5,13,18,3,74,5.0,0,83,Urban,Manager,105680,0 +11700,Male,21,Masters,2,64,27,48,12,0.0,3,97,Semi-Urban,Software Engineer,77872,1 +11701,Male,37,Bachelors,1,80,44,31,93,1.0,5,93,Rural,ML Engineer,53277,1 +11702,Male,42,Bachelors,18,45,6,1,8,5.0,7,0,Urban,HR Executive,95257,0 +11703,Male,43,Bachelors,14,98,76,53,91,6.0,2,52,Urban,Data Analyst,125474,1 +11704,Male,47,Masters,7,51,40,95,64,2.0,1,34,Semi-Urban,Manager,131258,0 +11705,Male,23,High School,4,36,70,11,30,6.0,6,59,Rural,ML Engineer,109077,0 +11706,Female,41,Bachelors,19,93,2,68,70,7.0,4,0,Urban,Software Engineer,63598,0 +11707,Female,39,Bachelors,14,80,97,16,71,8.0,1,46,Urban,ML Engineer,55451,0 +11708,Other,51,PhD,12,61,42,63,70,5.0,1,82,Semi-Urban,Software Engineer,30673,1 +11709,Male,38,Bachelors,8,2,32,30,57,8.0,4,17,Urban,Software Engineer,22986,0 +11710,Male,55,Bachelors,8,80,39,48,21,5.0,7,6,Semi-Urban,Data Analyst,87229,0 +11711,Female,58,Bachelors,18,34,0,91,80,0.0,4,46,Semi-Urban,HR Executive,59433,0 +11712,Male,47,Masters,15,78,39,45,32,5.0,3,75,Urban,HR Executive,54499,1 +11713,Female,55,Diploma,13,45,97,98,75,9.0,0,45,Rural,Software Engineer,66957,1 +11714,Male,51,Diploma,0,78,47,72,26,8.0,7,92,Urban,Data Analyst,120457,1 +11715,Male,53,Bachelors,8,25,18,6,7,6.0,1,1,Urban,Data Analyst,140790,0 +11716,Male,40,Diploma,6,63,17,17,99,9.0,3,87,Semi-Urban,Data Analyst,134626,0 +11717,Male,45,Bachelors,3,93,2,12,14,0.0,6,71,Urban,Software Engineer,145555,0 +11718,Female,40,Masters,4,97,52,2,49,0.0,1,52,Rural,ML Engineer,146771,0 +11719,Male,33,Bachelors,0,69,25,13,59,0.0,3,25,Rural,Data Analyst,28615,0 +11720,Male,43,Bachelors,9,38,94,48,60,9.0,6,55,Urban,HR Executive,136272,1 +11721,Male,48,Bachelors,10,21,24,62,47,8.0,7,64,Rural,ML Engineer,106576,0 +11722,Female,40,Bachelors,6,7,67,99,4,0.0,1,83,Rural,Software Engineer,20228,1 +11723,Male,41,PhD,9,1,58,62,93,7.0,7,94,Urban,HR Executive,77656,0 +11724,Male,58,High School,11,94,25,25,64,3.0,1,93,Urban,Manager,21576,1 +11725,Male,23,Bachelors,3,46,71,42,12,5.0,6,64,Urban,Manager,119446,0 +11726,Male,42,Bachelors,3,10,66,98,20,1.0,4,32,Semi-Urban,Software Engineer,57434,0 +11727,Male,54,Bachelors,2,26,33,39,69,6.0,7,93,Semi-Urban,ML Engineer,98745,0 +11728,Female,30,Bachelors,18,66,53,26,54,4.0,3,81,Urban,Software Engineer,149662,0 +11729,Male,37,Diploma,19,67,65,41,1,9.0,7,50,Urban,Software Engineer,88886,0 +11730,Male,39,Bachelors,16,5,26,18,61,4.0,4,60,Urban,Manager,104196,0 +11731,Female,25,Masters,14,66,68,89,35,5.0,7,29,Urban,Manager,96349,1 +11732,Male,25,Bachelors,0,92,27,21,83,7.0,6,11,Urban,Manager,20973,0 +11733,Male,54,Masters,1,19,80,91,7,0.0,1,49,Urban,Data Analyst,127993,1 +11734,Male,53,Bachelors,7,75,10,86,93,5.0,0,94,Semi-Urban,ML Engineer,128244,1 +11735,Male,35,Diploma,11,21,16,28,35,5.0,0,40,Urban,HR Executive,142958,0 +11736,Female,22,Bachelors,3,30,1,92,98,1.0,6,58,Rural,Data Analyst,135303,0 +11737,Female,56,Diploma,0,40,58,94,87,0.0,4,95,Urban,ML Engineer,125568,1 +11738,Female,42,Bachelors,2,66,56,74,66,0.0,2,51,Semi-Urban,HR Executive,58703,1 +11739,Female,26,Diploma,14,17,50,36,50,4.0,5,49,Semi-Urban,Software Engineer,52800,0 +11740,Male,47,Bachelors,3,68,28,65,17,1.0,0,71,Urban,HR Executive,123994,0 +11741,Male,58,Bachelors,16,14,3,94,6,1.0,6,47,Urban,Data Analyst,61868,0 +11742,Male,49,Diploma,13,84,40,0,12,1.0,2,89,Urban,Data Analyst,81912,0 +11743,Male,36,High School,13,65,66,64,88,1.0,0,57,Urban,ML Engineer,112539,1 +11744,Other,55,Bachelors,3,53,1,28,42,5.0,4,24,Urban,Manager,42689,0 +11745,Female,26,PhD,8,28,68,32,95,8.0,3,50,Urban,ML Engineer,98549,0 +11746,Male,54,Bachelors,9,40,67,68,90,5.0,4,85,Urban,Software Engineer,69772,1 +11747,Male,54,Bachelors,9,47,65,43,36,1.0,0,8,Semi-Urban,Data Analyst,45662,0 +11748,Male,45,Bachelors,3,64,75,25,73,0.0,0,86,Rural,HR Executive,123931,1 +11749,Male,48,Bachelors,11,28,3,7,5,9.0,7,17,Urban,ML Engineer,114199,0 +11750,Male,58,Bachelors,6,44,21,54,8,4.0,6,28,Rural,Software Engineer,84363,0 +11751,Male,33,Masters,8,50,96,51,94,5.0,2,3,Semi-Urban,ML Engineer,41065,0 +11752,Female,33,Diploma,11,47,51,65,96,1.0,3,50,Rural,Manager,124759,0 +11753,Female,59,Masters,14,3,67,38,55,3.0,2,33,Urban,Manager,109873,0 +11754,Male,55,Bachelors,7,57,36,94,62,9.0,7,45,Urban,Data Analyst,148050,0 +11755,Male,23,PhD,11,72,66,35,96,7.0,0,99,Urban,Data Analyst,59654,1 +11756,Male,56,Bachelors,5,12,80,13,8,6.0,5,90,Rural,HR Executive,76384,0 +11757,Female,49,Masters,2,90,65,95,25,8.0,5,33,Semi-Urban,ML Engineer,133393,1 +11758,Female,42,Bachelors,11,67,88,14,33,7.0,2,81,Rural,Data Analyst,20849,1 +11759,Female,27,Diploma,13,67,2,52,35,2.0,4,43,Urban,HR Executive,60311,0 +11760,Male,25,Bachelors,9,38,2,17,34,2.0,4,19,Urban,Software Engineer,128499,0 +11761,Female,58,Bachelors,12,45,67,87,26,0.0,0,71,Urban,Data Analyst,78398,1 +11762,Male,30,Bachelors,14,31,13,49,59,8.0,7,32,Urban,Software Engineer,37591,0 +11763,Male,21,Bachelors,11,2,39,64,20,6.0,1,28,Rural,Software Engineer,45331,0 +11764,Male,28,Bachelors,18,48,99,90,38,8.0,5,15,Urban,Data Analyst,58401,1 +11765,Male,42,Masters,18,1,50,72,68,6.0,1,24,Semi-Urban,ML Engineer,65823,0 +11766,Female,42,Diploma,1,78,18,93,92,4.0,3,82,Urban,Data Analyst,37343,1 +11767,Male,35,Bachelors,7,6,22,75,74,2.0,5,59,Urban,ML Engineer,23514,0 +11768,Male,59,Diploma,13,74,91,24,71,4.0,6,49,Semi-Urban,ML Engineer,132107,1 +11769,Male,50,Bachelors,13,91,36,55,63,5.0,0,81,Rural,HR Executive,29816,1 +11770,Male,38,Masters,13,27,68,30,5,0.0,0,12,Semi-Urban,Data Analyst,95390,0 +11771,Male,26,PhD,9,87,66,40,15,7.0,4,37,Urban,ML Engineer,88080,0 +11772,Male,32,High School,5,87,99,84,8,6.0,4,4,Urban,ML Engineer,36804,1 +11773,Male,59,Masters,7,8,55,44,29,5.0,4,25,Semi-Urban,HR Executive,64748,0 +11774,Male,22,Masters,6,19,60,39,80,2.0,5,5,Urban,HR Executive,59285,0 +11775,Other,26,Bachelors,3,87,50,82,87,8.0,6,77,Rural,ML Engineer,136790,1 +11776,Male,42,Bachelors,1,28,38,92,62,9.0,1,35,Urban,Software Engineer,85244,0 +11777,Male,24,Diploma,0,66,83,11,56,9.0,0,20,Semi-Urban,Software Engineer,28771,0 +11778,Male,35,Bachelors,19,82,67,78,24,5.0,5,15,Semi-Urban,ML Engineer,26622,1 +11779,Female,57,Diploma,2,53,34,42,20,1.0,0,15,Semi-Urban,Data Analyst,34622,0 +11780,Female,53,Masters,10,8,7,43,44,6.0,1,6,Semi-Urban,Data Analyst,106275,0 +11781,Male,50,Diploma,4,0,91,75,98,3.0,6,89,Rural,Data Analyst,87834,1 +11782,Male,38,Bachelors,12,15,23,19,23,0.0,6,55,Rural,Manager,104301,0 +11783,Female,34,Masters,6,2,96,48,29,9.0,7,20,Urban,ML Engineer,140996,0 +11784,Female,40,Diploma,9,42,65,39,38,2.0,7,89,Semi-Urban,Data Analyst,90579,0 +11785,Female,56,Bachelors,12,33,3,74,92,7.0,4,74,Rural,Manager,143731,0 +11786,Female,41,Masters,17,40,75,30,50,2.0,7,38,Urban,HR Executive,122753,0 +11787,Female,57,Masters,14,72,94,52,74,8.0,7,23,Semi-Urban,Manager,64783,1 +11788,Male,48,High School,15,83,51,84,35,7.0,3,67,Urban,Data Analyst,60661,1 +11789,Male,37,Masters,9,33,73,47,94,2.0,3,83,Urban,Data Analyst,99034,1 +11790,Female,55,Diploma,15,1,29,97,14,0.0,7,36,Urban,Manager,88895,0 +11791,Female,38,Masters,6,33,19,84,84,5.0,5,41,Urban,HR Executive,39999,0 +11792,Male,46,PhD,14,73,1,57,85,8.0,4,20,Urban,Software Engineer,104441,0 +11793,Other,50,Bachelors,3,10,75,17,20,1.0,0,47,Rural,Software Engineer,88417,0 +11794,Male,23,Bachelors,14,64,88,74,70,2.0,0,42,Rural,HR Executive,122187,1 +11795,Male,52,High School,16,50,86,83,50,0.0,1,83,Semi-Urban,HR Executive,50246,1 +11796,Female,35,Bachelors,11,67,63,59,20,1.0,6,90,Urban,Manager,106356,1 +11797,Male,25,Bachelors,6,43,62,46,88,1.0,4,95,Urban,Manager,43664,1 +11798,Male,46,Bachelors,17,28,1,99,22,8.0,3,20,Urban,Data Analyst,76164,0 +11799,Male,52,Diploma,16,48,31,3,63,9.0,2,64,Urban,HR Executive,110429,0 +11800,Male,44,High School,10,98,99,92,99,0.0,1,71,Urban,Manager,142090,1 +11801,Male,41,Diploma,0,38,78,42,23,0.0,6,16,Rural,ML Engineer,111056,0 +11802,Male,29,Masters,8,45,60,67,11,6.0,7,78,Urban,Software Engineer,127605,1 +11803,Male,46,High School,7,46,9,64,26,9.0,2,97,Rural,Software Engineer,47158,0 +11804,Other,43,Bachelors,16,85,51,73,74,0.0,3,30,Rural,Manager,126304,0 +11805,Other,46,Bachelors,15,93,36,60,9,6.0,3,59,Rural,Manager,94280,1 +11806,Male,49,High School,12,93,51,47,54,2.0,5,54,Rural,Software Engineer,130903,1 +11807,Female,32,Bachelors,4,92,4,64,24,6.0,2,9,Urban,Data Analyst,104833,0 +11808,Male,41,Masters,5,76,79,28,15,8.0,3,34,Urban,Software Engineer,137901,0 +11809,Male,24,Diploma,14,27,91,67,22,0.0,0,62,Urban,HR Executive,145367,1 +11810,Male,57,High School,16,10,22,11,37,9.0,2,17,Urban,ML Engineer,69758,0 +11811,Other,26,Diploma,12,26,93,26,69,9.0,5,31,Semi-Urban,Data Analyst,74877,0 +11812,Female,39,Diploma,12,12,65,15,30,2.0,7,77,Rural,HR Executive,149610,0 +11813,Male,57,High School,16,60,27,99,89,2.0,0,98,Semi-Urban,Manager,104185,1 +11814,Male,25,High School,16,4,73,80,81,9.0,0,75,Rural,ML Engineer,61165,0 +11815,Male,49,Masters,10,5,16,68,97,8.0,6,84,Urban,Software Engineer,115197,0 +11816,Male,39,PhD,3,30,50,22,6,0.0,5,66,Rural,Data Analyst,125197,0 +11817,Male,28,High School,4,40,21,94,67,0.0,0,60,Urban,Manager,107219,0 +11818,Male,27,Bachelors,7,50,29,23,93,7.0,5,40,Rural,Software Engineer,142072,0 +11819,Female,33,Masters,6,23,99,87,94,4.0,4,25,Urban,Software Engineer,22784,0 +11820,Male,48,Masters,13,44,62,2,41,7.0,4,71,Urban,Data Analyst,87596,0 +11821,Female,50,Diploma,12,60,7,75,68,0.0,4,35,Rural,Data Analyst,20731,0 +11822,Female,54,Diploma,3,93,93,51,56,2.0,2,17,Rural,Data Analyst,106646,1 +11823,Male,39,Bachelors,2,1,42,86,99,0.0,3,99,Urban,Software Engineer,66737,0 +11824,Female,35,Bachelors,7,2,19,63,22,0.0,0,33,Urban,Manager,144763,0 +11825,Female,25,Bachelors,14,50,50,41,5,6.0,5,88,Semi-Urban,Manager,132037,0 +11826,Male,25,PhD,15,63,62,60,66,0.0,5,0,Urban,Data Analyst,141624,0 +11827,Male,33,Bachelors,0,7,78,31,67,7.0,1,84,Urban,Software Engineer,105435,0 +11828,Female,58,Masters,6,35,11,35,50,4.0,5,0,Urban,Software Engineer,119784,0 +11829,Male,58,High School,6,90,78,54,14,7.0,7,42,Urban,ML Engineer,46437,1 +11830,Male,32,Bachelors,1,77,61,83,64,6.0,4,28,Semi-Urban,ML Engineer,88569,1 +11831,Male,21,Masters,14,40,73,51,77,1.0,6,64,Urban,Data Analyst,27977,0 +11832,Female,53,High School,18,28,91,62,67,8.0,3,32,Urban,Manager,102141,0 +11833,Female,41,Diploma,0,81,87,13,26,8.0,6,46,Urban,Data Analyst,106373,0 +11834,Female,24,Bachelors,9,72,96,36,50,5.0,3,87,Urban,Data Analyst,89482,1 +11835,Male,21,Bachelors,9,43,47,55,1,6.0,7,0,Urban,ML Engineer,91713,0 +11836,Male,55,Diploma,2,29,67,53,6,6.0,2,86,Urban,Manager,48666,1 +11837,Male,44,Bachelors,16,0,54,9,8,7.0,2,57,Urban,HR Executive,49779,0 +11838,Female,41,High School,1,96,73,14,65,4.0,3,89,Rural,ML Engineer,69578,1 +11839,Male,57,Bachelors,3,26,10,91,5,4.0,6,66,Urban,HR Executive,67319,0 +11840,Male,38,Bachelors,14,41,56,60,92,6.0,3,38,Rural,Software Engineer,127876,0 +11841,Male,23,PhD,1,68,78,98,58,5.0,6,79,Rural,Software Engineer,79336,1 +11842,Male,49,High School,1,91,1,61,16,0.0,7,34,Rural,HR Executive,27655,0 +11843,Female,22,Masters,13,54,92,74,78,4.0,5,81,Urban,HR Executive,75497,1 +11844,Female,44,Bachelors,19,48,23,93,16,5.0,2,29,Semi-Urban,ML Engineer,33178,0 +11845,Other,26,Masters,17,15,60,37,11,2.0,5,5,Semi-Urban,Software Engineer,65784,0 +11846,Male,46,High School,18,34,61,83,39,0.0,1,66,Semi-Urban,Manager,87373,1 +11847,Female,54,Bachelors,6,82,60,43,8,3.0,4,1,Semi-Urban,Software Engineer,117477,0 +11848,Female,43,High School,2,51,40,92,94,5.0,0,67,Semi-Urban,HR Executive,138241,1 +11849,Male,59,High School,16,35,45,88,56,3.0,2,77,Semi-Urban,Data Analyst,41121,1 +11850,Other,54,Masters,1,43,86,26,17,6.0,3,13,Semi-Urban,Software Engineer,68333,0 +11851,Male,58,Masters,11,46,54,64,88,9.0,5,77,Semi-Urban,Manager,94344,1 +11852,Female,40,Diploma,14,88,34,10,37,1.0,1,66,Urban,Data Analyst,114080,0 +11853,Female,49,High School,15,37,56,32,17,3.0,5,87,Urban,Software Engineer,46041,0 +11854,Female,52,Masters,4,90,0,93,43,0.0,7,31,Semi-Urban,ML Engineer,21662,0 +11855,Male,40,Bachelors,13,99,53,54,88,2.0,6,91,Rural,Software Engineer,111325,1 +11856,Male,28,Diploma,11,15,81,75,34,9.0,4,61,Rural,Manager,98853,0 +11857,Male,44,Masters,10,9,70,34,76,4.0,0,2,Urban,Manager,108387,0 +11858,Male,27,Masters,16,28,6,54,85,6.0,7,86,Semi-Urban,Data Analyst,67311,0 +11859,Female,46,Bachelors,17,90,34,73,10,3.0,6,46,Semi-Urban,Software Engineer,142040,1 +11860,Female,38,High School,5,26,31,3,92,9.0,3,65,Urban,Data Analyst,128697,0 +11861,Female,58,High School,13,91,6,79,68,1.0,1,94,Urban,HR Executive,56245,1 +11862,Male,32,Bachelors,12,8,45,45,25,4.0,3,35,Urban,Data Analyst,124496,0 +11863,Female,44,Bachelors,17,37,6,2,53,8.0,0,64,Urban,HR Executive,144882,0 +11864,Female,28,Diploma,19,4,22,10,17,8.0,1,48,Urban,Software Engineer,86111,0 +11865,Female,29,,6,29,23,16,6,0.0,3,30,Semi-Urban,Data Analyst,30731,0 +11866,Male,29,High School,18,94,85,86,15,1.0,0,51,Urban,Manager,139326,1 +11867,Male,39,Bachelors,11,26,23,43,54,3.0,2,63,Urban,HR Executive,145039,0 +11868,Male,36,Bachelors,18,64,52,94,14,5.0,1,51,Urban,Software Engineer,121569,1 +11869,Female,54,Diploma,18,9,59,29,59,4.0,4,29,Urban,Software Engineer,74232,0 +11870,Female,21,High School,5,40,66,65,32,5.0,5,44,Urban,Data Analyst,69321,0 +11871,Other,40,Bachelors,8,18,13,35,61,8.0,7,34,Urban,Software Engineer,28184,0 +11872,Male,48,High School,3,76,92,12,83,8.0,4,0,Urban,Manager,110479,0 +11873,Male,48,Masters,13,33,44,69,17,1.0,5,1,Urban,ML Engineer,100327,0 +11874,Female,41,Masters,9,42,90,51,8,4.0,0,81,Semi-Urban,Software Engineer,103321,1 +11875,Female,58,Bachelors,8,1,41,57,89,4.0,5,83,Urban,Data Analyst,111782,0 +11876,Female,31,Masters,3,76,90,39,9,5.0,0,57,Semi-Urban,ML Engineer,47419,1 +11877,Female,44,Masters,15,98,90,74,19,0.0,5,81,Urban,Manager,139818,1 +11878,Male,32,Bachelors,6,56,92,99,22,4.0,2,33,Urban,Software Engineer,51074,1 +11879,Female,46,Diploma,12,3,4,2,40,2.0,3,99,Rural,ML Engineer,111432,0 +11880,Female,58,Bachelors,1,56,64,62,55,4.0,1,81,Urban,ML Engineer,125355,1 +11881,Male,29,Diploma,19,48,53,57,96,9.0,1,83,Urban,Manager,30282,1 +11882,Male,24,High School,6,84,69,7,84,9.0,0,18,Urban,ML Engineer,23954,0 +11883,Male,24,Bachelors,7,90,94,20,73,9.0,5,80,Urban,Software Engineer,55349,1 +11884,Male,35,Diploma,11,37,72,99,42,3.0,5,77,Urban,Manager,89046,1 +11885,Female,56,Bachelors,2,85,54,50,99,3.0,7,58,Urban,HR Executive,93127,1 +11886,Male,30,Bachelors,14,16,69,42,6,2.0,7,81,Urban,Data Analyst,27079,0 +11887,Male,48,Masters,16,93,76,85,97,9.0,6,91,Urban,Software Engineer,43361,1 +11888,Male,59,Bachelors,19,69,44,93,42,6.0,1,82,Rural,Manager,148853,1 +11889,Male,30,Bachelors,3,71,2,70,73,4.0,3,39,Rural,ML Engineer,121696,0 +11890,Male,36,Bachelors,13,98,33,68,2,0.0,5,32,Urban,HR Executive,33926,0 +11891,Female,34,PhD,4,96,12,97,78,3.0,6,71,Rural,ML Engineer,25717,1 +11892,Male,24,Bachelors,19,24,62,24,98,1.0,1,36,Urban,Data Analyst,128529,0 +11893,Male,56,High School,7,28,84,44,78,5.0,1,49,Rural,ML Engineer,39969,0 +11894,Male,59,High School,2,90,42,76,97,3.0,6,0,Semi-Urban,Data Analyst,99040,0 +11895,Male,28,Bachelors,3,62,47,77,92,1.0,4,1,Semi-Urban,HR Executive,123295,0 +11896,Male,43,High School,6,4,83,70,64,7.0,2,37,Urban,Manager,77208,0 +11897,Male,58,Masters,0,42,17,89,81,6.0,1,73,Rural,Manager,92165,0 +11898,Female,36,Bachelors,13,95,51,93,59,8.0,4,47,Semi-Urban,Data Analyst,28992,1 +11899,Female,47,Bachelors,14,99,62,46,36,4.0,7,99,Semi-Urban,Software Engineer,138570,1 +11900,Male,44,Masters,10,82,80,20,13,7.0,1,9,Semi-Urban,Manager,139295,0 +11901,Male,42,Masters,7,96,90,21,78,4.0,3,69,Rural,Data Analyst,57037,1 +11902,Other,47,Diploma,9,77,74,45,17,5.0,2,99,Semi-Urban,Software Engineer,146694,1 +11903,Female,44,Bachelors,0,68,75,16,13,8.0,7,33,Urban,Software Engineer,88311,0 +11904,Male,31,Bachelors,18,53,98,60,42,6.0,4,4,Urban,ML Engineer,72011,0 +11905,Female,36,PhD,15,59,55,28,46,2.0,2,26,Urban,Software Engineer,122298,0 +11906,Female,48,Bachelors,7,43,8,27,92,8.0,3,64,Urban,Data Analyst,42478,0 +11907,Female,31,Masters,6,23,80,80,30,9.0,7,59,Rural,HR Executive,68528,1 +11908,Male,40,Masters,17,77,98,96,36,3.0,6,3,Urban,HR Executive,83218,1 +11909,Male,53,Bachelors,5,83,0,92,9,2.0,1,77,Urban,Software Engineer,21431,1 +11910,Male,27,Masters,12,14,8,35,42,2.0,1,93,Urban,Data Analyst,24712,0 +11911,Female,30,Masters,14,33,24,71,59,9.0,6,20,Urban,Data Analyst,101097,0 +11912,Female,59,Masters,4,94,64,52,50,3.0,4,84,Urban,ML Engineer,144678,1 +11913,Male,41,Bachelors,4,1,42,0,2,0.0,3,79,Rural,Software Engineer,97318,0 +11914,Female,23,Bachelors,5,59,52,69,24,1.0,6,11,Semi-Urban,Manager,65875,0 +11915,Female,25,Bachelors,14,81,95,87,32,3.0,7,31,Urban,HR Executive,39678,1 +11916,Other,58,Bachelors,17,2,87,57,56,6.0,4,21,Urban,HR Executive,36751,0 +11917,Female,21,Diploma,6,31,51,93,48,2.0,5,56,Rural,HR Executive,99076,0 +11918,Other,56,Masters,8,90,61,77,89,9.0,0,55,Urban,Software Engineer,32507,1 +11919,Male,32,PhD,6,29,63,79,76,6.0,1,0,Semi-Urban,Software Engineer,100801,0 +11920,Female,51,High School,9,87,39,5,33,5.0,6,95,Semi-Urban,HR Executive,94942,0 +11921,Female,46,Diploma,4,87,5,21,33,2.0,4,41,Urban,HR Executive,131858,0 +11922,Male,54,Diploma,12,76,53,52,37,0.0,1,94,Urban,ML Engineer,147833,1 +11923,Male,59,High School,8,21,91,70,98,6.0,5,13,Urban,ML Engineer,30923,0 +11924,Other,36,Bachelors,8,31,19,67,72,5.0,1,61,Semi-Urban,ML Engineer,117745,0 +11925,Male,44,Bachelors,18,58,92,95,42,4.0,3,72,Urban,HR Executive,23996,1 +11926,Female,56,Masters,14,82,46,61,41,5.0,6,87,Urban,ML Engineer,144501,1 +11927,Male,25,Diploma,15,89,26,20,0,7.0,3,25,Urban,Data Analyst,76433,0 +11928,Male,21,Diploma,11,12,28,7,26,1.0,0,52,Urban,Software Engineer,142136,0 +11929,Male,41,Bachelors,10,45,68,69,52,9.0,6,78,Urban,Data Analyst,111277,1 +11930,Male,30,Masters,5,27,67,50,81,5.0,6,95,Semi-Urban,HR Executive,62752,1 +11931,Female,28,Bachelors,15,93,15,75,12,7.0,2,55,Urban,Data Analyst,44786,0 +11932,Male,40,Bachelors,16,33,25,87,65,8.0,6,98,Rural,Manager,100030,1 +11933,Male,55,High School,7,42,35,28,77,3.0,3,59,Urban,Software Engineer,136141,0 +11934,Male,50,Bachelors,10,66,44,50,21,8.0,0,76,Rural,ML Engineer,51111,1 +11935,Male,38,Bachelors,4,21,41,34,74,3.0,4,29,Semi-Urban,ML Engineer,89861,0 +11936,Male,48,Masters,10,8,88,76,69,2.0,2,58,Rural,ML Engineer,78989,0 +11937,Female,47,PhD,0,30,55,1,39,2.0,0,79,Urban,HR Executive,131887,0 +11938,Male,50,Diploma,16,39,19,92,29,1.0,2,62,Urban,Data Analyst,100139,0 +11939,Male,57,Bachelors,5,79,33,4,6,2.0,3,45,Rural,Manager,140153,0 +11940,Male,55,Bachelors,18,44,48,63,98,5.0,3,10,Semi-Urban,Data Analyst,57942,0 +11941,Male,39,Bachelors,19,87,87,36,53,2.0,1,98,Semi-Urban,Manager,57209,1 +11942,Male,58,High School,13,12,40,96,35,7.0,2,7,Urban,Software Engineer,110011,0 +11943,Male,24,High School,12,2,64,36,59,8.0,3,88,Semi-Urban,Software Engineer,89505,0 +11944,Female,23,Bachelors,14,85,96,1,58,4.0,3,86,Urban,Manager,63975,1 +11945,Female,30,Diploma,18,91,70,98,27,1.0,2,50,Semi-Urban,HR Executive,46484,1 +11946,Female,31,Bachelors,6,8,58,47,72,6.0,5,34,Semi-Urban,Software Engineer,59928,0 +11947,Male,48,Bachelors,3,90,64,90,44,2.0,3,72,Rural,ML Engineer,102851,1 +11948,Male,24,Masters,7,37,66,33,34,9.0,5,71,Urban,ML Engineer,67389,0 +11949,Male,59,High School,12,31,54,44,49,3.0,5,88,Rural,Data Analyst,63215,0 +11950,Female,23,Bachelors,10,87,65,87,7,7.0,6,14,Rural,Software Engineer,81020,1 +11951,Other,54,Masters,16,77,71,14,81,4.0,4,10,Semi-Urban,Software Engineer,39178,0 +11952,Male,41,Bachelors,14,81,65,3,0,2.0,0,76,Semi-Urban,Manager,68036,0 +11953,Male,45,Diploma,5,81,76,64,89,4.0,3,27,Urban,Data Analyst,121460,1 +11954,Female,23,Masters,9,88,1,53,37,3.0,0,68,Rural,Data Analyst,58701,0 +11955,Female,37,Bachelors,3,61,83,90,26,5.0,7,99,Rural,ML Engineer,139084,1 +11956,Female,37,High School,0,11,76,62,67,6.0,5,40,Urban,Data Analyst,47685,0 +11957,Female,43,PhD,3,2,27,77,83,2.0,7,79,Urban,Software Engineer,112448,0 +11958,Other,37,Bachelors,7,74,15,15,43,9.0,0,83,Rural,Manager,73085,0 +11959,Male,41,Masters,18,19,99,79,4,5.0,6,81,Semi-Urban,ML Engineer,29958,1 +11960,Female,35,High School,16,68,33,72,24,8.0,3,98,Rural,Data Analyst,41430,1 +11961,Other,38,Diploma,3,54,49,41,81,5.0,3,4,Urban,HR Executive,38853,0 +11962,Female,43,Bachelors,8,75,97,48,74,5.0,6,57,Urban,Software Engineer,68280,1 +11963,Male,37,Masters,16,30,80,73,10,2.0,2,42,Semi-Urban,Software Engineer,78598,0 +11964,Male,33,Bachelors,16,86,45,39,22,6.0,0,15,Rural,Manager,30404,0 +11965,Male,35,Bachelors,10,96,34,81,31,3.0,6,51,Urban,Software Engineer,38559,1 +11966,Male,39,Bachelors,17,55,30,60,46,6.0,4,35,Rural,HR Executive,92874,0 +11967,Female,32,Bachelors,11,57,73,74,73,5.0,0,20,Urban,Data Analyst,65025,0 +11968,Male,45,PhD,14,97,87,38,61,1.0,7,40,Urban,Data Analyst,139619,1 +11969,Male,30,Diploma,0,16,90,22,46,0.0,6,22,Semi-Urban,Manager,97871,0 +11970,Female,33,Diploma,8,53,33,22,76,5.0,4,65,Urban,Software Engineer,145584,0 +11971,Male,22,Bachelors,7,53,68,52,71,3.0,1,4,Urban,ML Engineer,41268,0 +11972,Male,38,Masters,12,61,1,45,71,5.0,1,81,Semi-Urban,Manager,98351,0 +11973,Male,54,Bachelors,0,55,14,87,66,5.0,1,80,Urban,ML Engineer,128727,1 +11974,Female,54,Masters,13,20,77,92,85,8.0,5,99,Urban,Data Analyst,63752,1 +11975,Male,41,Diploma,9,33,92,85,61,2.0,7,82,Urban,Data Analyst,96129,1 +11976,Female,29,PhD,8,0,65,82,54,8.0,5,9,Urban,HR Executive,133872,0 +11977,Male,39,Bachelors,2,37,61,94,25,9.0,5,63,Urban,Software Engineer,33562,1 +11978,Female,30,Bachelors,11,33,42,83,0,9.0,7,35,Semi-Urban,Software Engineer,91460,0 +11979,Male,54,High School,13,58,87,19,95,5.0,5,40,Rural,HR Executive,78912,0 +11980,Male,34,Bachelors,11,37,84,67,69,2.0,5,80,Semi-Urban,ML Engineer,67714,1 +11981,Male,28,Masters,1,81,43,42,31,8.0,6,78,Urban,Software Engineer,60443,1 +11982,Male,57,High School,8,26,84,52,54,4.0,6,65,Urban,HR Executive,89318,0 +11983,Male,53,High School,18,34,83,10,5,6.0,3,93,Semi-Urban,Software Engineer,133020,0 +11984,Male,54,Bachelors,2,95,34,36,23,1.0,4,68,Rural,ML Engineer,60329,0 +11985,Male,36,Diploma,19,77,85,89,12,7.0,1,91,Urban,Data Analyst,58619,1 +11986,Male,33,Bachelors,1,61,25,12,64,4.0,3,26,Semi-Urban,Data Analyst,96219,0 +11987,Male,59,High School,8,4,67,13,20,5.0,4,49,Rural,Data Analyst,124967,0 +11988,Male,47,High School,16,51,68,84,55,7.0,3,39,Urban,ML Engineer,59713,1 +11989,Female,59,Bachelors,1,11,18,78,36,0.0,0,82,Urban,ML Engineer,48300,0 +11990,Female,53,Diploma,12,77,19,32,70,7.0,5,96,Semi-Urban,ML Engineer,59263,0 +11991,Male,53,Masters,14,42,53,50,73,5.0,3,10,Urban,Software Engineer,102815,0 +11992,Male,24,Diploma,16,17,15,79,18,4.0,7,33,Urban,Software Engineer,89150,0 +11993,Other,57,Bachelors,16,63,67,38,50,7.0,3,27,Urban,ML Engineer,140970,0 +11994,Male,45,Diploma,1,62,18,3,15,1.0,7,57,Urban,Software Engineer,56308,0 +11995,Other,31,Diploma,8,39,95,14,65,1.0,0,7,Urban,Manager,83418,0 +11996,Male,31,High School,10,77,14,56,85,9.0,7,88,Rural,Data Analyst,40580,1 +11997,Female,42,Bachelors,14,81,97,12,39,0.0,3,62,Rural,HR Executive,56407,1 +11998,Male,34,Bachelors,19,71,94,89,25,3.0,1,67,Urban,ML Engineer,140148,1 +11999,Female,59,Bachelors,0,54,81,75,17,6.0,7,4,Urban,Manager,52401,0 +12000,Male,22,Bachelors,3,52,24,79,50,1.0,2,85,Semi-Urban,Software Engineer,87100,1 +12001,Female,54,High School,7,37,54,20,56,2.0,7,52,Urban,ML Engineer,112850,0 +12002,Male,31,Diploma,6,26,55,4,46,8.0,5,26,Rural,HR Executive,39731,0 +12003,Male,25,Diploma,11,42,13,50,2,7.0,7,60,Urban,Data Analyst,61040,0 +12004,Female,47,Diploma,7,84,14,30,24,0.0,4,34,Semi-Urban,Manager,83140,0 +12005,Male,38,High School,18,85,28,5,69,2.0,3,99,Urban,Data Analyst,101599,0 +12006,Female,52,Bachelors,15,45,51,98,14,8.0,2,61,Urban,HR Executive,109861,1 +12007,Male,23,Bachelors,0,6,70,27,57,3.0,2,38,Urban,Data Analyst,42640,0 +12008,Female,43,Bachelors,14,91,31,37,66,2.0,5,87,Urban,Software Engineer,82765,1 +12009,Male,28,Diploma,17,87,86,80,26,7.0,3,47,Urban,Data Analyst,28081,1 +12010,Other,30,Bachelors,6,34,21,43,73,8.0,0,53,Urban,ML Engineer,69563,0 +12011,Other,27,Bachelors,9,43,74,73,54,7.0,4,67,Urban,Software Engineer,43030,1 +12012,Male,48,Masters,16,73,30,27,42,6.0,3,38,Semi-Urban,Data Analyst,22584,0 +12013,Female,58,Bachelors,4,29,35,76,39,5.0,2,20,Urban,Software Engineer,136339,0 +12014,Female,44,High School,14,25,29,44,85,5.0,6,52,Urban,Manager,60485,0 +12015,Male,44,Diploma,6,83,67,31,9,1.0,4,88,Urban,HR Executive,128832,1 +12016,Female,44,Bachelors,18,82,88,67,97,5.0,3,18,Semi-Urban,ML Engineer,85785,1 +12017,Male,49,Bachelors,7,14,0,92,72,5.0,4,49,Semi-Urban,Data Analyst,119913,0 +12018,Female,44,High School,3,63,36,67,88,6.0,0,53,Urban,ML Engineer,118826,0 +12019,Male,59,Masters,9,51,67,41,55,3.0,1,14,Urban,Manager,56103,0 +12020,Male,23,Bachelors,10,49,75,96,29,9.0,2,46,Urban,Manager,80585,1 +12021,Male,56,Masters,13,75,32,32,45,1.0,4,94,Rural,Manager,53981,0 +12022,Male,58,Bachelors,9,67,4,56,90,2.0,6,63,Urban,Manager,40932,0 +12023,Female,46,Masters,16,58,63,61,36,0.0,1,77,Semi-Urban,Data Analyst,49672,1 +12024,Other,35,Bachelors,17,74,92,50,65,0.0,4,57,Semi-Urban,Manager,99034,1 +12025,Male,24,Bachelors,14,62,72,39,77,6.0,6,13,Urban,ML Engineer,30190,0 +12026,Male,32,High School,8,92,97,43,87,0.0,7,38,Semi-Urban,HR Executive,98634,1 +12027,Female,25,Masters,8,93,6,13,22,7.0,1,46,Urban,Software Engineer,21629,0 +12028,Male,38,Bachelors,10,99,42,7,15,1.0,2,50,Semi-Urban,Manager,129134,0 +12029,Male,24,Masters,12,90,8,24,81,6.0,1,97,Rural,Manager,39864,0 +12030,Male,23,Bachelors,18,98,92,82,67,8.0,2,81,Urban,Software Engineer,124571,1 +12031,Male,58,Masters,15,78,3,89,89,9.0,4,58,Urban,Manager,140942,0 +12032,Male,37,Diploma,4,73,81,75,40,9.0,3,48,Urban,ML Engineer,61858,1 +12033,Female,45,Diploma,11,74,36,56,62,2.0,7,50,Rural,Software Engineer,24757,0 +12034,Male,43,Diploma,5,32,63,47,16,9.0,6,48,Semi-Urban,Manager,124185,0 +12035,Female,29,Bachelors,2,33,76,68,16,8.0,5,91,Semi-Urban,Software Engineer,109569,1 +12036,Male,24,Diploma,9,92,71,98,29,6.0,5,24,Semi-Urban,Manager,105441,1 +12037,Male,42,Masters,15,76,32,20,92,0.0,5,72,Urban,ML Engineer,129934,0 +12038,Female,59,High School,3,13,65,83,63,5.0,0,94,Rural,ML Engineer,138652,1 +12039,Male,49,Masters,16,98,13,58,21,1.0,3,72,Urban,Manager,31251,1 +12040,Male,32,Bachelors,5,79,83,15,94,5.0,5,92,Semi-Urban,HR Executive,52848,1 +12041,Female,50,PhD,7,52,70,97,9,2.0,6,36,Urban,Manager,137708,1 +12042,Male,38,High School,14,0,98,99,56,6.0,5,28,Semi-Urban,Manager,49833,0 +12043,Female,36,Bachelors,3,15,95,34,84,1.0,7,99,Urban,Manager,133112,1 +12044,Male,59,Diploma,12,22,3,64,54,1.0,0,17,Urban,Manager,100960,0 +12045,Female,50,High School,17,2,75,19,93,2.0,5,18,Urban,Software Engineer,125418,0 +12046,Male,41,Masters,12,81,28,73,47,4.0,6,88,Urban,Software Engineer,103551,1 +12047,Male,42,Diploma,15,82,60,38,59,6.0,0,20,Rural,ML Engineer,111837,0 +12048,Other,45,Diploma,0,45,87,80,67,4.0,3,50,Semi-Urban,Data Analyst,108726,1 +12049,Female,50,Diploma,13,22,31,77,58,7.0,4,20,Rural,Data Analyst,36843,0 +12050,Male,26,Bachelors,16,13,58,79,95,7.0,0,93,Rural,Manager,22715,1 +12051,Male,49,Bachelors,9,10,70,42,14,2.0,6,59,Semi-Urban,Software Engineer,121030,0 +12052,Male,27,Diploma,19,72,23,89,26,2.0,7,18,Rural,Manager,70736,0 +12053,Female,49,Diploma,14,69,46,70,75,3.0,2,85,Rural,HR Executive,136578,1 +12054,Female,55,Bachelors,16,70,99,81,23,1.0,0,58,Semi-Urban,HR Executive,70624,1 +12055,Female,29,Diploma,6,41,87,19,44,1.0,3,10,Rural,Manager,57526,0 +12056,Male,37,Bachelors,4,52,89,51,61,9.0,7,37,Urban,HR Executive,142351,0 +12057,Female,41,Masters,10,98,50,27,96,0.0,7,75,Rural,ML Engineer,43175,1 +12058,Male,41,Diploma,12,96,66,45,22,0.0,7,61,Semi-Urban,Software Engineer,55320,1 +12059,Male,37,Bachelors,9,49,2,20,58,6.0,7,15,Rural,Manager,61292,0 +12060,Male,39,Masters,2,67,87,46,30,1.0,7,18,Semi-Urban,Data Analyst,70968,0 +12061,Other,45,Bachelors,10,37,29,86,84,1.0,0,84,Semi-Urban,Software Engineer,87765,0 +12062,Female,53,Bachelors,10,7,60,91,18,0.0,7,12,Rural,HR Executive,74202,0 +12063,Male,49,High School,11,42,4,7,12,9.0,3,78,Semi-Urban,Manager,65338,0 +12064,Female,45,High School,0,66,14,64,14,3.0,7,82,Semi-Urban,HR Executive,26958,0 +12065,Female,50,Bachelors,13,96,20,23,36,7.0,4,90,Urban,HR Executive,130194,0 +12066,Male,27,High School,8,28,68,87,51,3.0,0,48,Urban,ML Engineer,60209,0 +12067,Male,54,Bachelors,2,39,70,53,11,7.0,6,2,Urban,HR Executive,136267,0 +12068,Other,49,Masters,12,25,43,29,38,6.0,3,47,Semi-Urban,ML Engineer,29739,0 +12069,Female,29,Bachelors,0,42,52,46,13,3.0,0,2,Semi-Urban,ML Engineer,66170,0 +12070,Male,53,Bachelors,7,34,93,90,6,8.0,5,76,Rural,HR Executive,72342,1 +12071,Male,57,Diploma,14,89,47,52,16,7.0,4,41,Semi-Urban,Software Engineer,82520,0 +12072,Male,25,Diploma,14,25,4,38,34,4.0,5,22,Urban,Data Analyst,140937,0 +12073,Male,57,Masters,18,39,1,71,35,2.0,2,84,Urban,Manager,99323,0 +12074,Other,50,Bachelors,13,52,92,23,88,8.0,5,13,Urban,Software Engineer,82928,0 +12075,Male,35,Masters,0,32,44,1,25,4.0,4,15,Urban,Data Analyst,64432,0 +12076,Female,55,Bachelors,3,51,13,97,7,6.0,7,19,Urban,Data Analyst,129070,0 +12077,Male,52,PhD,11,28,97,45,26,4.0,7,84,Urban,Data Analyst,84910,1 +12078,Male,53,Bachelors,16,63,28,47,74,7.0,4,10,Semi-Urban,HR Executive,84590,0 +12079,Male,35,PhD,16,95,4,88,85,1.0,0,88,Urban,HR Executive,80471,1 +12080,Female,42,Bachelors,2,46,15,46,28,3.0,4,31,Urban,Software Engineer,69971,0 +12081,Male,21,Bachelors,4,6,60,12,11,7.0,4,7,Semi-Urban,Data Analyst,53859,0 +12082,Female,54,Masters,19,43,9,41,72,3.0,7,96,Urban,Data Analyst,120599,0 +12083,Male,57,Diploma,0,91,84,83,18,0.0,0,50,Semi-Urban,ML Engineer,132391,1 +12084,Male,30,Diploma,17,91,66,59,14,5.0,0,1,Urban,Manager,73063,0 +12085,Male,24,PhD,8,59,8,47,64,1.0,7,69,Rural,Software Engineer,33333,0 +12086,Male,37,Masters,16,21,43,4,85,7.0,5,46,Urban,ML Engineer,33884,0 +12087,Female,23,High School,18,36,29,21,31,3.0,0,60,Urban,Software Engineer,121468,0 +12088,Male,21,Masters,12,85,70,56,49,9.0,2,76,Urban,Data Analyst,30580,1 +12089,Female,40,Masters,3,40,51,53,4,9.0,2,84,Semi-Urban,HR Executive,91618,0 +12090,Male,36,Bachelors,15,94,65,4,78,9.0,0,74,Urban,Software Engineer,73462,1 +12091,Male,40,Diploma,3,25,3,71,13,5.0,3,87,Semi-Urban,Manager,34211,0 +12092,Male,25,Bachelors,18,51,17,49,50,1.0,3,88,Rural,Software Engineer,90752,0 +12093,Male,59,Diploma,14,77,90,81,11,7.0,4,81,Rural,Software Engineer,52205,1 +12094,Female,31,High School,13,51,26,50,25,2.0,7,76,Urban,Data Analyst,38172,0 +12095,Female,44,High School,13,11,5,70,83,3.0,3,26,Semi-Urban,ML Engineer,93538,0 +12096,Male,30,Bachelors,19,25,48,58,68,1.0,6,84,Semi-Urban,Data Analyst,69649,0 +12097,Male,57,Masters,5,39,6,32,33,2.0,5,58,Urban,HR Executive,108008,0 +12098,Female,36,High School,5,25,9,81,44,3.0,1,81,Urban,Manager,38850,0 +12099,Female,34,Bachelors,1,63,38,74,94,9.0,4,22,Urban,Data Analyst,110271,0 +12100,Female,29,Masters,14,64,27,22,97,0.0,4,7,Urban,Data Analyst,56893,0 +12101,Male,51,Masters,12,43,44,30,77,3.0,6,42,Urban,Software Engineer,27740,0 +12102,Male,44,Diploma,9,24,91,95,55,5.0,2,24,Semi-Urban,Manager,84154,0 +12103,Other,57,Diploma,15,64,54,35,35,9.0,3,85,Urban,Software Engineer,69805,0 +12104,Female,30,Bachelors,14,25,12,45,32,6.0,1,2,Urban,Manager,146656,0 +12105,Male,43,PhD,7,39,54,90,86,1.0,2,75,Urban,Manager,81174,1 +12106,Female,23,High School,12,51,41,43,65,9.0,4,17,Semi-Urban,Software Engineer,35510,0 +12107,Female,22,Diploma,7,35,69,55,79,7.0,5,0,Semi-Urban,Manager,126268,0 +12108,Male,46,High School,7,76,3,72,73,4.0,6,58,Urban,ML Engineer,57042,0 +12109,Male,59,Masters,8,56,43,41,47,3.0,3,61,Urban,Manager,44970,0 +12110,Male,25,PhD,6,28,81,54,21,2.0,3,64,Urban,Software Engineer,53381,0 +12111,Male,41,High School,16,73,11,78,23,5.0,4,34,Urban,HR Executive,72960,0 +12112,Female,59,Bachelors,8,7,17,94,72,6.0,0,82,Rural,Data Analyst,40734,0 +12113,Male,30,Masters,16,71,16,56,45,9.0,7,65,Urban,Software Engineer,20141,0 +12114,Female,27,Bachelors,13,71,77,3,89,4.0,3,13,Semi-Urban,ML Engineer,20513,0 +12115,Other,35,PhD,5,89,58,54,90,9.0,3,56,Rural,Manager,54130,1 +12116,Male,32,Bachelors,13,89,47,59,34,8.0,3,92,Rural,Data Analyst,74956,1 +12117,Male,45,Masters,15,93,42,69,33,3.0,6,79,Rural,Data Analyst,138259,1 +12118,Female,38,High School,10,56,83,2,64,0.0,4,53,Semi-Urban,Data Analyst,60804,0 +12119,Female,27,High School,15,11,40,6,86,1.0,1,67,Urban,Data Analyst,134563,0 +12120,Female,23,Bachelors,0,86,85,51,92,9.0,2,67,Urban,HR Executive,144425,1 +12121,Male,38,Bachelors,11,88,48,53,72,2.0,0,42,Rural,ML Engineer,34451,0 +12122,Male,49,Diploma,8,16,35,3,31,6.0,3,26,Semi-Urban,Data Analyst,126044,0 +12123,Male,59,Diploma,17,40,7,63,95,2.0,6,84,Rural,Software Engineer,126128,0 +12124,Other,33,Masters,1,75,10,41,51,8.0,2,53,Urban,HR Executive,61386,0 +12125,Male,33,Bachelors,11,42,43,81,40,3.0,6,80,Urban,Data Analyst,78063,1 +12126,Female,25,Masters,17,6,11,15,65,2.0,2,10,Urban,HR Executive,30804,0 +12127,Male,43,PhD,12,56,58,93,79,8.0,3,24,Semi-Urban,Manager,137084,0 +12128,Other,26,High School,15,97,46,59,68,6.0,6,1,Rural,Software Engineer,73281,0 +12129,Female,45,Diploma,14,69,39,52,99,6.0,7,32,Urban,Software Engineer,66445,0 +12130,Male,34,Masters,12,73,48,52,24,5.0,0,97,Semi-Urban,Software Engineer,127118,1 +12131,Female,48,Bachelors,8,91,43,97,29,7.0,3,85,Rural,Data Analyst,64538,1 +12132,Male,39,PhD,5,37,67,87,53,5.0,6,10,Urban,Software Engineer,136152,0 +12133,Male,34,Bachelors,14,26,19,41,7,2.0,3,80,Urban,HR Executive,34630,0 +12134,Male,35,High School,18,72,48,19,92,2.0,3,58,Urban,HR Executive,122990,0 +12135,Male,41,Masters,13,99,19,69,97,6.0,7,65,Urban,ML Engineer,93792,1 +12136,Male,35,Diploma,0,23,77,67,7,2.0,4,15,Semi-Urban,HR Executive,105255,0 +12137,Female,46,Diploma,17,69,21,89,30,0.0,4,20,Semi-Urban,Manager,63351,0 +12138,Female,37,High School,5,66,59,71,31,1.0,1,3,Urban,Manager,92207,0 +12139,Male,38,Bachelors,8,74,67,38,29,2.0,5,10,Semi-Urban,HR Executive,139314,0 +12140,Female,56,Diploma,6,18,88,31,58,2.0,4,46,Rural,Manager,68788,0 +12141,Female,49,Bachelors,13,19,78,10,88,4.0,5,6,Urban,Manager,137792,0 +12142,Other,49,Bachelors,19,16,39,65,21,6.0,6,25,Urban,Data Analyst,28907,0 +12143,Female,39,Masters,18,17,36,32,21,4.0,4,63,Semi-Urban,Software Engineer,136593,0 +12144,Male,54,High School,2,65,28,2,37,9.0,7,23,Urban,Manager,98266,0 +12145,Male,51,Diploma,3,45,8,57,83,3.0,1,46,Urban,Data Analyst,22843,0 +12146,Female,30,Masters,14,53,11,27,64,2.0,4,43,Urban,Data Analyst,47718,0 +12147,Male,36,Masters,12,46,9,94,98,6.0,2,68,Semi-Urban,Manager,23776,0 +12148,Male,56,Diploma,6,81,31,97,86,1.0,1,82,Semi-Urban,Manager,28340,1 +12149,Male,26,Bachelors,3,88,24,25,87,1.0,2,96,Semi-Urban,Data Analyst,101406,0 +12150,Male,48,High School,10,37,63,42,31,3.0,4,22,Urban,Data Analyst,132399,0 +12151,Male,24,Bachelors,1,71,62,78,52,3.0,7,43,Rural,Data Analyst,116216,1 +12152,Male,54,Bachelors,11,35,75,37,57,6.0,5,41,Semi-Urban,HR Executive,146706,0 +12153,Male,41,High School,19,52,47,95,9,8.0,3,80,Urban,ML Engineer,91109,1 +12154,Female,21,Bachelors,3,73,2,38,29,0.0,3,98,Urban,Manager,85640,0 +12155,Male,56,Masters,7,36,57,55,86,1.0,1,8,Rural,HR Executive,69846,0 +12156,Male,36,Bachelors,9,41,74,3,91,2.0,3,44,Urban,Data Analyst,78230,0 +12157,Male,52,Bachelors,11,24,75,46,94,8.0,2,28,Urban,Manager,106235,0 +12158,Male,25,Diploma,16,79,45,22,14,8.0,4,35,Urban,Software Engineer,125241,0 +12159,Male,36,Bachelors,11,42,12,32,84,2.0,2,45,Urban,Manager,104206,0 +12160,Male,57,Bachelors,1,80,40,96,55,9.0,4,38,Urban,Software Engineer,138946,1 +12161,Male,52,Diploma,4,94,75,47,74,4.0,2,33,Semi-Urban,Manager,29806,1 +12162,Female,26,Diploma,14,31,23,33,44,4.0,1,52,Semi-Urban,Data Analyst,71759,0 +12163,Male,49,Bachelors,16,82,35,32,73,1.0,3,38,Semi-Urban,Software Engineer,64805,0 +12164,Male,23,Bachelors,15,83,61,68,57,4.0,3,75,Rural,Data Analyst,57688,1 +12165,Male,40,Bachelors,8,36,75,80,21,3.0,7,49,Urban,Manager,48370,1 +12166,Female,59,Masters,11,20,8,24,60,7.0,1,11,Rural,HR Executive,42456,0 +12167,Female,25,Masters,18,99,38,94,96,1.0,6,6,Urban,Data Analyst,32482,0 +12168,Female,34,Masters,19,52,76,28,95,0.0,4,21,Semi-Urban,ML Engineer,71582,0 +12169,Male,31,Diploma,5,54,67,91,75,6.0,6,97,Urban,Manager,29330,1 +12170,Male,58,Bachelors,5,42,9,57,90,7.0,3,52,Urban,Software Engineer,124252,0 +12171,Male,23,Bachelors,5,9,39,82,89,8.0,7,8,Rural,ML Engineer,81518,0 +12172,Female,58,High School,18,94,76,5,68,1.0,5,61,Urban,ML Engineer,74444,0 +12173,Male,45,PhD,18,4,69,69,61,6.0,6,49,Rural,Manager,130289,0 +12174,Other,55,High School,14,34,13,90,94,1.0,6,84,Semi-Urban,ML Engineer,38524,0 +12175,Female,37,High School,3,43,46,32,93,1.0,4,2,Urban,Software Engineer,68991,0 +12176,Female,55,Bachelors,15,46,76,68,50,2.0,2,76,Urban,Software Engineer,132434,1 +12177,Male,32,Bachelors,5,42,49,78,90,2.0,0,36,Urban,HR Executive,78506,0 +12178,Female,45,Bachelors,1,92,50,99,55,9.0,2,93,Urban,Software Engineer,46700,1 +12179,Male,22,Bachelors,7,77,69,6,74,1.0,6,67,Urban,Data Analyst,78877,0 +12180,Male,48,Masters,15,35,0,84,61,9.0,7,5,Urban,ML Engineer,29759,0 +12181,Male,41,Diploma,14,39,19,88,88,6.0,2,10,Urban,ML Engineer,68501,0 +12182,Female,24,Bachelors,19,10,39,58,33,0.0,5,55,Semi-Urban,Data Analyst,20377,0 +12183,Male,24,High School,10,4,16,52,91,0.0,5,52,Urban,HR Executive,78489,0 +12184,Male,39,Bachelors,4,10,22,28,75,0.0,0,82,Urban,ML Engineer,128368,0 +12185,Male,32,Bachelors,6,23,25,79,64,1.0,4,96,Urban,Manager,81722,0 +12186,Female,47,Bachelors,8,50,73,32,51,9.0,1,79,Urban,Manager,20799,0 +12187,Female,36,High School,18,56,15,4,39,5.0,6,42,Semi-Urban,HR Executive,81206,0 +12188,Female,33,Masters,7,9,48,25,7,3.0,4,66,Semi-Urban,Data Analyst,94473,0 +12189,Male,54,PhD,3,52,50,17,55,4.0,3,68,Semi-Urban,Manager,126218,0 +12190,Male,33,PhD,2,49,98,56,31,5.0,5,34,Semi-Urban,HR Executive,28308,1 +12191,Male,33,Diploma,8,17,73,86,87,0.0,5,13,Rural,HR Executive,140980,0 +12192,Male,49,High School,15,27,19,11,50,2.0,6,36,Rural,Manager,81364,0 +12193,Female,39,High School,11,20,31,41,47,3.0,6,88,Rural,Manager,146442,0 +12194,Male,30,Diploma,11,89,40,27,85,5.0,7,81,Urban,Manager,22631,1 +12195,Male,38,High School,8,56,89,20,82,4.0,1,59,Urban,Software Engineer,137150,0 +12196,Male,28,PhD,6,7,19,98,22,6.0,6,13,Urban,Data Analyst,81710,0 +12197,Female,54,Masters,14,18,34,43,80,7.0,4,46,Semi-Urban,Data Analyst,52109,0 +12198,Male,28,Masters,9,63,52,32,7,7.0,3,88,Semi-Urban,Software Engineer,75130,1 +12199,Male,34,PhD,1,2,15,28,49,2.0,1,0,Rural,ML Engineer,44080,0 +12200,Female,56,Bachelors,5,67,77,32,59,9.0,0,48,Urban,HR Executive,50429,0 +12201,Male,47,High School,5,89,34,20,89,8.0,1,89,Urban,Software Engineer,112610,0 +12202,Female,42,Masters,3,41,47,85,78,8.0,7,88,Semi-Urban,HR Executive,120025,1 +12203,Male,24,Bachelors,11,2,62,52,64,7.0,0,24,Rural,HR Executive,112798,0 +12204,Female,46,Bachelors,3,38,48,31,90,7.0,3,79,Urban,Data Analyst,64128,0 +12205,Male,34,Diploma,5,98,87,85,4,3.0,1,19,Urban,Software Engineer,73212,1 +12206,Male,28,Bachelors,14,52,99,29,67,3.0,5,70,Urban,Software Engineer,111117,1 +12207,Female,48,High School,14,37,36,78,9,9.0,0,40,Urban,HR Executive,113312,0 +12208,Male,53,Diploma,8,72,29,9,71,4.0,0,74,Urban,HR Executive,26080,0 +12209,Male,42,Diploma,8,1,48,71,88,5.0,0,80,Urban,HR Executive,138250,0 +12210,Male,34,Diploma,18,4,81,81,16,4.0,6,77,Semi-Urban,Data Analyst,40736,1 +12211,Female,29,Bachelors,19,82,38,1,38,0.0,4,86,Urban,Software Engineer,68543,0 +12212,Male,44,Diploma,4,7,45,43,16,4.0,1,20,Semi-Urban,Manager,82896,0 +12213,Other,52,Bachelors,1,54,84,38,62,0.0,5,56,Semi-Urban,ML Engineer,32900,0 +12214,Other,31,Diploma,11,94,66,80,90,6.0,3,18,Semi-Urban,Data Analyst,63588,1 +12215,Female,58,Bachelors,11,27,2,62,52,9.0,2,40,Urban,ML Engineer,58340,0 +12216,Male,35,Masters,6,66,91,49,70,6.0,2,12,Semi-Urban,Manager,72159,0 +12217,Male,26,Bachelors,12,30,77,34,62,3.0,1,14,Urban,Manager,60574,0 +12218,Female,38,Masters,1,51,13,71,14,8.0,5,0,Urban,HR Executive,73264,0 +12219,Male,28,Masters,9,5,16,15,57,1.0,7,75,Semi-Urban,Manager,83260,0 +12220,Male,54,Bachelors,1,15,3,73,27,6.0,4,63,Semi-Urban,Software Engineer,61048,0 +12221,Male,58,Diploma,9,8,71,13,6,5.0,2,55,Urban,HR Executive,52471,0 +12222,Male,45,High School,14,66,56,41,57,9.0,5,21,Urban,Data Analyst,83861,0 +12223,Male,31,Masters,13,21,45,43,21,1.0,5,37,Rural,Software Engineer,116178,0 +12224,Male,49,Bachelors,11,67,81,62,78,3.0,1,16,Rural,Software Engineer,55827,0 +12225,Female,47,Bachelors,10,91,18,50,34,2.0,6,54,Urban,Software Engineer,57278,0 +12226,Male,25,Bachelors,5,63,65,26,31,7.0,6,72,Semi-Urban,Data Analyst,33137,0 +12227,Male,29,Masters,11,62,95,60,82,4.0,1,13,Urban,HR Executive,67404,0 +12228,Male,56,Diploma,4,79,27,66,7,3.0,4,95,Urban,Data Analyst,142547,1 +12229,Male,43,Bachelors,10,13,49,16,68,6.0,7,65,Semi-Urban,Manager,34337,0 +12230,Male,33,Masters,9,63,39,86,49,2.0,2,17,Semi-Urban,Software Engineer,96519,0 +12231,Female,56,High School,0,97,85,16,32,3.0,1,43,Urban,ML Engineer,88832,1 +12232,Other,41,Masters,9,6,78,87,74,6.0,7,25,Urban,Software Engineer,42597,0 +12233,Male,29,Bachelors,13,99,26,64,39,3.0,2,6,Urban,Software Engineer,31020,0 +12234,Male,22,Bachelors,6,98,67,81,74,4.0,6,83,Urban,Manager,63385,1 +12235,Male,45,Masters,15,78,79,36,60,6.0,3,87,Urban,HR Executive,27502,1 +12236,Other,21,Masters,14,72,38,7,64,7.0,3,52,Semi-Urban,ML Engineer,27593,0 +12237,Female,28,Masters,18,29,51,9,37,6.0,3,12,Semi-Urban,Data Analyst,22071,0 +12238,Female,52,Diploma,2,12,40,52,43,7.0,5,5,Urban,Manager,40506,0 +12239,Male,52,Masters,7,38,68,2,91,2.0,4,62,Urban,Manager,105897,0 +12240,Other,41,Bachelors,6,38,78,74,53,8.0,4,22,Urban,Software Engineer,75581,0 +12241,Male,42,Bachelors,11,87,30,72,68,3.0,0,39,Urban,HR Executive,64759,0 +12242,Male,22,High School,0,6,59,29,56,6.0,4,89,Semi-Urban,ML Engineer,99676,0 +12243,Female,30,Bachelors,19,60,95,5,53,0.0,0,6,Urban,HR Executive,107380,0 +12244,Female,21,Bachelors,1,49,93,99,90,9.0,6,96,Urban,Manager,123476,1 +12245,Male,30,Diploma,5,80,7,5,27,4.0,4,81,Semi-Urban,Data Analyst,92476,0 +12246,Male,57,High School,4,67,29,91,16,1.0,0,3,Semi-Urban,Software Engineer,114565,0 +12247,Male,28,Bachelors,5,52,8,15,26,4.0,3,86,Rural,Data Analyst,60276,0 +12248,Male,24,Bachelors,19,55,8,91,67,5.0,1,50,Urban,Data Analyst,57503,0 +12249,Male,54,Masters,3,53,92,9,14,2.0,7,0,Rural,ML Engineer,21635,0 +12250,Other,46,Bachelors,18,21,94,93,96,3.0,4,55,Rural,Data Analyst,140593,1 +12251,Female,49,PhD,4,65,78,42,50,3.0,2,98,Urban,ML Engineer,111675,1 +12252,Female,28,Diploma,14,67,19,91,69,6.0,7,25,Urban,HR Executive,119559,0 +12253,Female,39,Masters,10,18,35,39,91,0.0,2,74,Urban,ML Engineer,133519,0 +12254,Male,28,PhD,18,87,99,56,42,2.0,6,28,Semi-Urban,ML Engineer,33273,1 +12255,Female,32,PhD,1,29,43,70,56,7.0,4,28,Semi-Urban,HR Executive,32693,0 +12256,Male,38,Diploma,8,72,62,92,59,8.0,5,36,Semi-Urban,Software Engineer,42941,1 +12257,Male,33,Diploma,9,93,17,27,72,5.0,7,51,Rural,HR Executive,115004,0 +12258,Male,22,Masters,3,76,59,23,63,2.0,1,59,Urban,Data Analyst,50004,0 +12259,Male,39,Bachelors,13,14,38,97,22,3.0,6,16,Semi-Urban,ML Engineer,95855,0 +12260,Female,43,PhD,14,49,26,66,96,3.0,0,19,Urban,HR Executive,26160,0 +12261,Other,34,PhD,9,72,25,37,60,9.0,4,79,Urban,Manager,49323,0 +12262,Male,52,Bachelors,18,51,76,10,0,4.0,4,38,Rural,Manager,106322,0 +12263,Female,44,Diploma,15,46,46,3,55,4.0,0,3,Urban,Manager,30921,0 +12264,Male,29,Diploma,6,39,10,26,78,7.0,0,73,Semi-Urban,Manager,130232,0 +12265,Female,30,Diploma,2,14,23,35,79,2.0,6,97,Urban,Manager,97057,0 +12266,Male,54,High School,11,48,31,1,90,2.0,3,13,Semi-Urban,Software Engineer,137147,0 +12267,Male,32,Masters,11,46,85,18,5,6.0,1,35,Urban,Data Analyst,80133,0 +12268,Male,34,Bachelors,16,19,1,50,7,7.0,3,89,Urban,Software Engineer,130193,0 +12269,Female,41,Masters,1,48,54,90,80,8.0,3,65,Urban,HR Executive,106861,1 +12270,Male,43,PhD,0,26,87,77,38,1.0,4,35,Semi-Urban,HR Executive,119505,0 +12271,Female,21,Bachelors,19,92,96,61,59,4.0,7,51,Urban,Software Engineer,99952,1 +12272,Male,59,Diploma,9,76,32,9,85,2.0,6,13,Urban,Manager,86706,0 +12273,Female,37,Bachelors,4,73,30,33,87,2.0,2,57,Urban,Software Engineer,20831,0 +12274,Female,53,Masters,17,88,37,67,19,8.0,3,44,Urban,HR Executive,32192,0 +12275,Male,35,Bachelors,4,86,3,37,10,0.0,6,17,Urban,Software Engineer,116906,0 +12276,Male,23,Masters,10,10,52,33,37,6.0,4,49,Rural,Manager,53378,0 +12277,Female,44,High School,6,35,27,4,38,0.0,3,72,Urban,Manager,71567,0 +12278,Female,37,Bachelors,11,85,99,15,29,3.0,4,28,Urban,Manager,110795,0 +12279,Female,58,Bachelors,12,73,81,35,53,4.0,2,10,Semi-Urban,Software Engineer,76851,0 +12280,Male,31,Bachelors,17,61,87,16,34,4.0,2,53,Semi-Urban,Manager,65791,0 +12281,Male,46,Masters,18,8,86,63,92,3.0,3,91,Urban,ML Engineer,30416,1 +12282,Other,33,Masters,9,82,98,0,49,8.0,4,94,Rural,Data Analyst,147017,1 +12283,Male,32,Masters,17,75,63,1,66,9.0,2,29,Rural,Data Analyst,45873,0 +12284,Male,36,Bachelors,16,35,8,65,84,0.0,6,4,Rural,HR Executive,126226,0 +12285,Male,35,Bachelors,2,89,31,72,22,3.0,6,5,Semi-Urban,Data Analyst,20392,0 +12286,Female,39,Bachelors,9,39,64,93,28,9.0,6,53,Urban,HR Executive,69919,1 +12287,Female,39,High School,17,31,61,5,58,5.0,3,49,Urban,ML Engineer,119270,0 +12288,Male,57,Bachelors,10,76,77,69,36,8.0,1,41,Urban,Software Engineer,42154,1 +12289,Male,27,Bachelors,10,4,89,25,45,6.0,5,81,Semi-Urban,Manager,109105,0 +12290,Male,33,Bachelors,17,85,36,33,55,1.0,6,80,Urban,HR Executive,88676,0 +12291,Male,25,Masters,2,67,94,14,50,5.0,3,36,Urban,Data Analyst,75144,0 +12292,Male,37,Bachelors,5,27,0,59,70,3.0,2,16,Semi-Urban,Software Engineer,33191,0 +12293,Other,52,Bachelors,17,57,46,73,91,6.0,2,20,Semi-Urban,Manager,147887,0 +12294,Male,31,Bachelors,6,95,37,80,26,5.0,1,18,Rural,Data Analyst,90986,0 +12295,Male,55,High School,0,17,49,29,16,4.0,0,78,Rural,HR Executive,31861,0 +12296,Female,27,Bachelors,16,74,83,40,35,3.0,5,67,Semi-Urban,ML Engineer,89526,1 +12297,Male,42,Bachelors,5,32,71,78,34,1.0,2,40,Semi-Urban,ML Engineer,111872,0 +12298,Male,25,Diploma,3,61,83,64,96,3.0,5,62,Rural,Data Analyst,69437,1 +12299,Male,28,Diploma,12,18,0,58,64,7.0,4,96,Urban,Manager,127789,0 +12300,Male,34,PhD,9,85,45,59,65,6.0,6,77,Urban,Software Engineer,26272,1 +12301,Female,49,Diploma,18,97,43,83,28,1.0,0,12,Urban,Data Analyst,135408,0 +12302,Male,49,Diploma,5,73,91,93,65,4.0,6,48,Urban,HR Executive,54176,1 +12303,Male,50,Bachelors,8,24,32,7,39,7.0,5,62,Semi-Urban,Software Engineer,56535,0 +12304,Female,48,Bachelors,18,53,0,6,62,9.0,3,75,Urban,Software Engineer,74338,0 +12305,Female,42,Bachelors,17,76,75,21,19,7.0,7,18,Urban,Data Analyst,57096,0 +12306,Male,44,Diploma,6,84,63,8,29,0.0,0,41,Urban,Manager,55833,0 +12307,Male,56,Masters,16,84,59,42,0,5.0,6,95,Urban,ML Engineer,102288,1 +12308,Other,44,Bachelors,16,28,33,93,83,8.0,2,38,Urban,Data Analyst,128188,0 +12309,Male,55,Masters,13,86,70,37,65,7.0,2,2,Urban,ML Engineer,82148,0 +12310,Female,22,Bachelors,2,13,83,73,71,9.0,1,47,Urban,Software Engineer,130353,0 +12311,Female,29,Bachelors,8,23,2,17,71,7.0,0,8,Urban,Manager,54731,0 +12312,Female,40,Masters,13,68,38,86,32,8.0,1,76,Urban,HR Executive,30866,1 +12313,Male,33,Bachelors,17,41,80,37,72,5.0,2,33,Rural,Data Analyst,86598,0 +12314,Male,25,Bachelors,11,88,82,75,88,6.0,7,95,Urban,Software Engineer,66853,1 +12315,Female,32,Bachelors,9,18,90,32,57,1.0,4,79,Urban,Software Engineer,64598,0 +12316,Male,40,Diploma,6,19,16,63,32,1.0,2,86,Semi-Urban,ML Engineer,42866,0 +12317,Male,36,High School,12,82,81,54,98,0.0,0,7,Urban,Manager,112715,0 +12318,Male,58,Diploma,10,65,57,75,20,0.0,5,24,Urban,Data Analyst,148658,0 +12319,Male,23,Bachelors,17,86,6,30,30,9.0,5,18,Semi-Urban,Software Engineer,135435,0 +12320,Other,39,Bachelors,17,21,53,65,35,6.0,0,94,Urban,Data Analyst,141361,0 +12321,Male,47,Masters,11,75,33,25,15,4.0,1,8,Rural,Data Analyst,130081,0 +12322,Other,37,Bachelors,10,12,50,96,40,5.0,6,22,Urban,Data Analyst,38754,0 +12323,Male,43,Bachelors,2,70,3,20,54,1.0,7,12,Rural,Manager,115211,0 +12324,Male,31,Masters,14,5,41,23,57,7.0,5,76,Urban,Software Engineer,91936,0 +12325,Male,56,Bachelors,14,66,74,43,63,3.0,1,1,Urban,ML Engineer,44954,0 +12326,Female,41,High School,12,81,22,77,18,0.0,7,37,Urban,Manager,48524,0 +12327,Female,41,Bachelors,5,80,94,71,95,8.0,2,8,Rural,Manager,24314,1 +12328,Male,51,Bachelors,12,1,95,42,90,3.0,3,36,Semi-Urban,ML Engineer,24076,0 +12329,Female,21,Diploma,17,75,57,34,70,3.0,0,39,Semi-Urban,Manager,91057,0 +12330,Male,58,Bachelors,15,7,99,13,2,3.0,7,81,Rural,ML Engineer,119419,0 +12331,Female,54,Diploma,16,96,73,47,13,3.0,6,90,Urban,Manager,86850,1 +12332,Other,41,High School,15,80,38,84,51,3.0,0,11,Urban,ML Engineer,51815,0 +12333,Female,35,High School,14,55,54,75,12,6.0,1,75,Rural,Manager,74961,1 +12334,Other,46,High School,12,92,48,74,32,8.0,2,86,Rural,Data Analyst,136903,1 +12335,Male,25,PhD,8,85,74,11,36,0.0,4,32,Urban,Manager,70637,0 +12336,Male,57,Bachelors,14,3,25,34,37,3.0,3,49,Semi-Urban,HR Executive,125264,0 +12337,Male,30,PhD,17,49,1,6,75,1.0,4,52,Semi-Urban,Data Analyst,38506,0 +12338,Male,41,High School,2,45,76,3,89,3.0,2,25,Rural,Software Engineer,51517,0 +12339,Female,27,Masters,2,49,29,60,3,1.0,0,23,Rural,ML Engineer,98558,0 +12340,Male,49,Bachelors,5,81,28,77,14,7.0,7,81,Semi-Urban,ML Engineer,63760,1 +12341,Female,30,PhD,18,8,76,48,95,2.0,6,50,Urban,Data Analyst,148480,0 +12342,Male,32,Bachelors,17,52,92,87,30,7.0,1,48,Urban,Data Analyst,21519,1 +12343,Male,50,Masters,13,9,24,36,49,6.0,4,14,Urban,ML Engineer,52594,0 +12344,Female,23,Bachelors,16,43,36,63,43,3.0,2,32,Semi-Urban,Software Engineer,49625,0 +12345,Male,30,Diploma,4,72,80,91,58,6.0,0,74,Urban,Data Analyst,90094,1 +12346,Female,21,Diploma,19,77,53,30,59,7.0,2,59,Urban,Software Engineer,102065,0 +12347,Male,41,Masters,14,4,20,21,52,4.0,1,29,Rural,HR Executive,147942,0 +12348,Female,21,Diploma,14,46,9,52,63,9.0,5,77,Urban,Data Analyst,127088,0 +12349,Male,43,Bachelors,17,76,67,21,63,8.0,5,14,Urban,Manager,102104,0 +12350,Male,46,Bachelors,3,98,5,34,20,8.0,1,52,Urban,Manager,74869,0 +12351,Female,40,Bachelors,19,91,33,41,2,8.0,0,40,Urban,Software Engineer,144273,0 +12352,Female,34,PhD,9,77,31,6,52,6.0,4,71,Urban,Data Analyst,66310,0 +12353,Male,36,Masters,10,98,42,95,41,0.0,5,59,Urban,HR Executive,46437,1 +12354,Male,37,Masters,5,59,21,77,10,5.0,4,54,Urban,Manager,37146,0 +12355,Male,33,Bachelors,15,65,9,37,70,7.0,6,19,Rural,Data Analyst,146500,0 +12356,Male,41,Bachelors,9,96,62,56,24,2.0,0,36,Urban,Software Engineer,40821,1 +12357,Female,45,PhD,18,21,92,96,94,6.0,6,99,Urban,HR Executive,57847,1 +12358,Female,50,Bachelors,12,69,4,20,24,6.0,0,87,Urban,Software Engineer,146394,0 +12359,Male,26,Bachelors,2,69,23,86,88,7.0,4,83,Semi-Urban,ML Engineer,84346,1 +12360,Male,37,Bachelors,7,97,55,56,40,6.0,2,28,Semi-Urban,Data Analyst,141968,1 +12361,Female,42,Bachelors,13,41,14,70,16,0.0,5,53,Rural,Data Analyst,115809,0 +12362,Male,44,High School,11,58,45,6,4,0.0,0,99,Urban,Manager,38335,0 +12363,Female,25,Bachelors,1,83,85,40,30,1.0,6,82,Urban,Software Engineer,126621,1 +12364,Male,44,Bachelors,6,13,54,81,51,1.0,3,89,Urban,Manager,27504,1 +12365,Female,36,Bachelors,6,43,21,75,96,0.0,3,66,Semi-Urban,HR Executive,144738,0 +12366,Male,55,High School,19,14,74,81,58,3.0,5,82,Rural,ML Engineer,61490,1 +12367,Female,53,Bachelors,0,23,78,54,85,1.0,5,47,Semi-Urban,ML Engineer,149601,0 +12368,Male,38,Masters,15,27,51,58,33,7.0,3,46,Urban,Manager,53687,0 +12369,Male,43,Diploma,6,28,34,79,96,0.0,3,5,Semi-Urban,Manager,103867,0 +12370,Female,43,Diploma,11,15,5,50,1,5.0,5,6,Urban,ML Engineer,148216,0 +12371,Male,30,Bachelors,5,36,43,35,12,2.0,1,37,Urban,Software Engineer,138323,0 +12372,Male,36,High School,5,7,8,51,38,4.0,0,82,Urban,ML Engineer,66737,0 +12373,Male,50,Bachelors,2,79,16,85,67,4.0,0,9,Rural,Data Analyst,100379,0 +12374,Male,52,Bachelors,13,58,52,34,46,2.0,0,23,Urban,Manager,85252,0 +12375,Female,30,Bachelors,8,36,77,92,68,1.0,2,14,Rural,HR Executive,26892,0 +12376,Female,33,Bachelors,13,62,44,55,9,4.0,2,16,Urban,Data Analyst,144080,0 +12377,Male,28,Masters,18,52,45,3,58,3.0,0,5,Rural,Software Engineer,65569,0 +12378,Female,35,Bachelors,13,94,9,28,66,8.0,1,54,Rural,Manager,30124,0 +12379,Male,38,Diploma,0,17,36,19,65,9.0,1,1,Urban,Data Analyst,101628,0 +12380,Female,44,Diploma,10,42,31,53,72,2.0,4,63,Urban,Software Engineer,20354,0 +12381,Male,42,Masters,2,99,39,69,63,2.0,7,24,Urban,Software Engineer,35998,0 +12382,Male,41,PhD,17,59,6,4,71,6.0,7,54,Urban,HR Executive,82271,0 +12383,Male,43,Masters,7,63,81,25,29,9.0,7,71,Urban,Manager,122240,1 +12384,Male,53,Masters,14,48,70,19,38,5.0,5,47,Rural,HR Executive,133082,0 +12385,Male,30,Masters,4,22,99,75,47,9.0,3,36,Semi-Urban,Data Analyst,91616,0 +12386,Male,51,Diploma,3,81,63,66,81,0.0,4,49,Semi-Urban,Data Analyst,49337,1 +12387,Female,49,Bachelors,6,5,52,96,69,7.0,1,58,Urban,HR Executive,133882,0 +12388,Male,45,Masters,4,47,6,57,55,3.0,0,1,Urban,Manager,87833,0 +12389,Other,24,High School,3,96,86,37,43,9.0,5,79,Rural,Manager,45142,1 +12390,Male,38,Masters,5,53,64,25,8,0.0,1,60,Urban,Manager,147895,0 +12391,Female,41,Diploma,1,25,2,60,45,5.0,6,60,Semi-Urban,ML Engineer,91432,0 +12392,Female,49,High School,2,31,76,19,34,9.0,5,55,Semi-Urban,Software Engineer,68253,0 +12393,Female,29,Masters,17,17,74,31,73,4.0,1,1,Semi-Urban,Manager,135417,0 +12394,Female,34,PhD,0,52,24,72,45,4.0,1,42,Urban,Data Analyst,71198,0 +12395,Female,38,Bachelors,16,25,45,58,21,4.0,0,62,Urban,ML Engineer,86829,0 +12396,Male,39,Bachelors,18,26,19,29,40,2.0,6,42,Urban,HR Executive,56181,0 +12397,Female,29,Diploma,15,40,84,42,65,2.0,5,45,Rural,HR Executive,136199,0 +12398,Male,38,Bachelors,6,2,58,94,27,7.0,7,75,Urban,ML Engineer,53784,0 +12399,Male,54,Bachelors,16,84,57,34,34,4.0,6,99,Rural,Data Analyst,126126,1 +12400,Male,30,Masters,2,17,23,59,70,5.0,3,49,Urban,HR Executive,128302,0 +12401,Female,57,Masters,17,96,99,21,48,8.0,0,72,Rural,ML Engineer,31928,1 +12402,Male,32,Bachelors,9,77,21,48,48,3.0,1,9,Urban,ML Engineer,103397,0 +12403,Male,52,Bachelors,7,91,60,18,93,4.0,0,77,Rural,Data Analyst,117281,1 +12404,Male,49,Masters,13,97,4,70,75,0.0,4,27,Rural,Software Engineer,45648,0 +12405,Other,26,Diploma,11,99,46,64,26,1.0,1,99,Urban,Data Analyst,54718,1 +12406,Male,21,Bachelors,2,18,89,83,75,6.0,2,88,Rural,ML Engineer,28200,1 +12407,Male,39,Diploma,7,90,50,30,90,6.0,3,7,Urban,Software Engineer,31577,0 +12408,Male,30,Masters,0,85,45,8,60,0.0,1,85,Urban,ML Engineer,59398,0 +12409,Other,21,PhD,5,38,80,18,57,4.0,4,77,Rural,Data Analyst,95080,0 +12410,Other,50,Bachelors,15,59,35,51,69,3.0,6,36,Urban,Manager,29338,0 +12411,Female,25,Bachelors,19,4,59,1,70,6.0,3,65,Rural,ML Engineer,35920,0 +12412,Female,56,Bachelors,17,49,29,24,71,5.0,1,15,Urban,HR Executive,82076,0 +12413,Male,37,Diploma,6,61,29,99,46,6.0,1,96,Rural,Software Engineer,117142,1 +12414,Other,21,Bachelors,6,3,61,55,11,6.0,1,36,Urban,Data Analyst,113558,0 +12415,Male,32,Bachelors,16,98,29,72,15,4.0,1,5,Urban,Data Analyst,110110,0 +12416,Male,34,Bachelors,9,27,14,97,44,6.0,2,69,Urban,Manager,100176,0 +12417,Male,54,Bachelors,2,99,0,88,2,3.0,2,83,Rural,Manager,87155,1 +12418,Male,37,Bachelors,1,67,95,75,46,8.0,0,97,Urban,Software Engineer,96533,1 +12419,Female,29,Diploma,16,57,33,71,94,4.0,7,93,Semi-Urban,HR Executive,97949,1 +12420,Male,25,Bachelors,16,33,7,6,85,6.0,1,15,Urban,Data Analyst,78450,0 +12421,Other,29,Bachelors,5,51,37,70,17,5.0,4,59,Rural,Software Engineer,33383,0 +12422,Male,50,Bachelors,9,68,97,49,47,6.0,7,10,Rural,Data Analyst,118723,0 +12423,Male,55,Masters,14,33,85,61,28,4.0,3,32,Urban,Software Engineer,95938,0 +12424,Male,38,Bachelors,18,48,81,24,68,8.0,7,40,Urban,Data Analyst,64387,0 +12425,Female,41,Diploma,7,26,23,34,68,4.0,3,13,Semi-Urban,Data Analyst,72145,0 +12426,Female,23,Bachelors,12,52,15,24,57,4.0,4,24,Urban,Software Engineer,84759,0 +12427,Male,34,High School,5,20,29,39,56,4.0,5,33,Urban,Data Analyst,27403,0 +12428,Male,31,High School,9,10,50,16,75,0.0,2,29,Urban,Software Engineer,38420,0 +12429,Male,45,Masters,10,18,77,36,16,3.0,1,10,Semi-Urban,Data Analyst,103427,0 +12430,Female,57,High School,1,93,79,54,99,5.0,2,57,Semi-Urban,Data Analyst,39776,1 +12431,Other,30,Bachelors,16,14,23,98,92,0.0,2,33,Semi-Urban,HR Executive,47169,0 +12432,Male,41,PhD,10,37,20,66,52,7.0,5,82,Urban,Data Analyst,39568,0 +12433,Female,36,Bachelors,3,5,88,12,29,2.0,0,47,Urban,Software Engineer,45463,0 +12434,Male,58,Diploma,10,77,3,79,72,7.0,3,1,Semi-Urban,Manager,118180,0 +12435,Male,52,High School,18,32,11,8,83,0.0,0,62,Semi-Urban,HR Executive,89850,0 +12436,Other,24,Diploma,3,98,13,59,23,9.0,5,13,Urban,Software Engineer,110909,0 +12437,Male,21,High School,8,38,88,19,72,5.0,3,56,Urban,Software Engineer,39402,0 +12438,Male,30,PhD,9,98,46,26,35,3.0,4,17,Semi-Urban,Data Analyst,22419,0 +12439,Male,28,Bachelors,6,25,67,10,1,3.0,7,69,Rural,Data Analyst,36140,0 +12440,Male,52,Bachelors,13,56,39,99,88,0.0,1,19,Rural,Data Analyst,117512,0 +12441,Female,23,Bachelors,13,13,90,86,72,6.0,6,37,Semi-Urban,Manager,142521,0 +12442,Female,51,Bachelors,16,32,79,68,84,5.0,3,91,Rural,Software Engineer,98583,1 +12443,Female,43,Bachelors,9,21,32,56,87,0.0,2,82,Semi-Urban,Data Analyst,125481,0 +12444,Male,57,Bachelors,9,21,33,82,37,3.0,0,21,Semi-Urban,Manager,136824,0 +12445,Male,28,Bachelors,8,82,1,79,69,6.0,3,1,Urban,Software Engineer,21235,0 +12446,Male,49,Diploma,8,96,36,23,42,2.0,7,21,Urban,ML Engineer,80405,0 +12447,Male,53,Bachelors,14,62,93,60,23,5.0,0,36,Urban,Manager,103316,1 +12448,Other,45,High School,7,36,99,98,26,8.0,1,6,Urban,ML Engineer,36961,0 +12449,Female,22,Masters,12,96,87,38,70,5.0,5,93,Urban,HR Executive,103810,1 +12450,Male,25,Diploma,10,49,58,23,1,7.0,6,87,Urban,HR Executive,32920,0 +12451,Female,34,Bachelors,4,8,34,62,35,6.0,5,67,Semi-Urban,HR Executive,129847,0 +12452,Female,55,Bachelors,11,77,47,32,49,3.0,4,84,Urban,ML Engineer,49650,0 +12453,Male,34,Masters,6,78,76,3,46,8.0,0,65,Urban,Software Engineer,144227,0 +12454,Female,59,Diploma,13,34,40,2,58,8.0,0,55,Semi-Urban,Manager,143493,0 +12455,Male,39,Masters,1,68,37,27,83,4.0,7,72,Urban,Data Analyst,46725,0 +12456,Male,36,Diploma,3,80,94,69,43,5.0,7,93,Urban,Manager,114480,1 +12457,Male,38,Masters,19,28,7,27,27,9.0,1,47,Semi-Urban,Manager,28539,0 +12458,Male,22,Masters,19,10,55,76,88,4.0,4,26,Semi-Urban,Software Engineer,85205,0 +12459,Male,23,Bachelors,14,90,61,15,74,2.0,4,2,Urban,Software Engineer,31932,0 +12460,Male,27,Bachelors,13,24,41,15,3,0.0,7,44,Semi-Urban,ML Engineer,96462,0 +12461,Male,32,Bachelors,11,34,71,56,53,5.0,5,17,Urban,ML Engineer,99448,0 +12462,Female,36,Bachelors,2,32,50,5,3,1.0,2,55,Semi-Urban,HR Executive,137731,0 +12463,Other,38,High School,10,93,25,4,65,2.0,0,80,Urban,ML Engineer,66395,0 +12464,Female,55,Bachelors,18,80,42,59,73,6.0,6,93,Semi-Urban,Manager,124036,1 +12465,Male,52,Bachelors,19,68,97,32,33,7.0,2,49,Urban,Data Analyst,105097,1 +12466,Male,30,Bachelors,15,72,54,73,42,3.0,3,63,Urban,Data Analyst,146556,1 +12467,Male,53,Masters,16,13,25,0,52,2.0,1,92,Semi-Urban,Data Analyst,38191,0 +12468,Male,36,Bachelors,11,52,78,86,64,7.0,2,43,Semi-Urban,Data Analyst,42240,1 +12469,Male,43,Bachelors,12,80,83,48,3,2.0,2,47,Rural,Data Analyst,88099,1 +12470,Female,50,Masters,1,1,81,62,16,6.0,0,6,Semi-Urban,Software Engineer,145604,0 +12471,Female,28,Masters,13,38,10,77,73,4.0,3,92,Urban,Data Analyst,45635,0 +12472,Female,21,Bachelors,5,39,39,94,46,4.0,6,92,Urban,Data Analyst,31609,1 +12473,Male,29,Diploma,6,56,55,9,41,1.0,3,55,Urban,Software Engineer,147860,0 +12474,Male,53,Bachelors,3,16,71,72,15,7.0,5,58,Urban,HR Executive,113667,0 +12475,Female,36,Bachelors,12,28,92,14,28,2.0,2,98,Urban,Software Engineer,21200,0 +12476,Male,24,High School,18,39,44,66,98,3.0,3,53,Rural,ML Engineer,129083,0 +12477,Male,27,Diploma,16,36,15,57,56,5.0,3,61,Semi-Urban,ML Engineer,116146,0 +12478,Male,50,Masters,18,70,89,69,86,6.0,1,47,Urban,ML Engineer,106211,1 +12479,Male,23,High School,8,89,16,55,95,0.0,2,25,Semi-Urban,Data Analyst,59604,0 +12480,Male,27,Diploma,7,35,91,93,8,5.0,5,63,Semi-Urban,Manager,43693,1 +12481,Female,46,Bachelors,1,87,32,12,21,3.0,6,39,Urban,Data Analyst,118629,0 +12482,Female,44,Bachelors,7,63,26,73,82,7.0,5,73,Urban,Software Engineer,20660,0 +12483,Male,36,PhD,7,91,36,3,98,4.0,0,0,Rural,Manager,148116,0 +12484,Male,54,Bachelors,10,99,86,9,40,0.0,3,72,Urban,HR Executive,104184,1 +12485,Female,28,Diploma,3,48,49,35,31,6.0,7,65,Urban,Data Analyst,81754,0 +12486,Male,51,Masters,2,82,24,17,76,5.0,1,82,Urban,ML Engineer,79349,0 +12487,Male,41,Masters,11,74,74,70,15,4.0,7,14,Urban,Data Analyst,62717,0 +12488,Male,31,High School,19,15,34,22,89,7.0,6,66,Rural,Data Analyst,143448,0 +12489,Male,50,High School,9,1,3,70,68,2.0,0,47,Urban,Manager,134582,0 +12490,Female,50,Bachelors,16,57,85,2,12,3.0,5,19,Rural,ML Engineer,88510,0 +12491,Female,31,Masters,12,36,5,3,34,0.0,0,73,Semi-Urban,Manager,118402,0 +12492,Male,58,Bachelors,7,2,9,39,75,6.0,0,7,Rural,ML Engineer,85008,0 +12493,Male,32,Diploma,7,5,50,92,35,0.0,5,65,Rural,Software Engineer,138621,0 +12494,Male,46,Bachelors,17,40,16,83,33,5.0,5,87,Urban,HR Executive,55954,0 +12495,Male,48,Bachelors,1,66,74,97,77,8.0,3,52,Urban,Manager,43331,1 +12496,Other,29,Bachelors,12,62,38,80,31,0.0,1,9,Semi-Urban,Data Analyst,31821,0 +12497,Female,30,Bachelors,11,60,35,39,60,5.0,6,75,Rural,ML Engineer,29224,0 +12498,Male,35,Bachelors,15,27,13,62,61,7.0,6,18,Rural,ML Engineer,143514,0 +12499,Female,52,Diploma,17,27,66,92,82,7.0,4,92,Rural,HR Executive,80414,1 +12500,Female,32,Masters,9,88,66,0,30,5.0,7,95,Semi-Urban,Data Analyst,131259,1 +12501,Female,37,High School,13,71,85,29,26,6.0,6,41,Urban,HR Executive,61284,0 +12502,Male,29,PhD,2,81,16,25,46,0.0,1,94,Semi-Urban,ML Engineer,102365,0 +12503,Male,38,Bachelors,17,96,13,74,7,8.0,5,35,Urban,HR Executive,147357,0 +12504,Female,49,Diploma,5,56,47,40,91,5.0,5,87,Urban,Software Engineer,114997,0 +12505,Male,27,Diploma,10,87,6,64,18,0.0,3,70,Urban,Software Engineer,65242,0 +12506,Other,45,High School,9,36,50,39,38,4.0,4,63,Urban,HR Executive,97553,0 +12507,Female,33,High School,15,85,64,34,10,8.0,1,58,Urban,ML Engineer,88587,1 +12508,Other,57,Masters,11,90,40,46,67,1.0,3,15,Semi-Urban,Software Engineer,145732,0 +12509,Male,32,Bachelors,14,46,27,31,38,3.0,4,63,Rural,ML Engineer,127556,0 +12510,Female,55,Masters,4,11,37,63,28,9.0,5,53,Urban,Data Analyst,75542,0 +12511,Male,42,Bachelors,19,5,5,79,56,9.0,0,42,Urban,Manager,121692,0 +12512,Other,35,Bachelors,9,35,83,97,1,9.0,3,63,Urban,ML Engineer,79261,1 +12513,Male,27,Masters,1,45,46,99,15,0.0,7,46,Semi-Urban,Software Engineer,39648,1 +12514,Male,58,Diploma,14,34,47,68,48,2.0,2,11,Urban,Data Analyst,31128,0 +12515,Female,26,Bachelors,19,24,42,96,56,7.0,6,71,Semi-Urban,ML Engineer,33277,0 +12516,Male,57,High School,12,23,81,7,77,2.0,5,97,Rural,ML Engineer,81877,0 +12517,Male,26,Diploma,3,58,2,50,95,2.0,5,42,Urban,Manager,76588,0 +12518,Other,39,Masters,11,14,58,25,77,3.0,5,7,Semi-Urban,Manager,125503,0 +12519,Male,53,Masters,7,74,14,58,22,4.0,4,75,Rural,Manager,124682,0 +12520,Female,25,Diploma,7,90,97,3,19,9.0,7,22,Urban,Data Analyst,33655,0 +12521,Male,53,Bachelors,16,74,24,3,87,5.0,3,34,Urban,Software Engineer,134893,0 +12522,Female,41,Diploma,6,67,69,38,50,9.0,7,7,Urban,HR Executive,78449,0 +12523,Female,35,Masters,12,73,25,24,77,7.0,7,36,Urban,HR Executive,111050,0 +12524,Male,47,High School,15,81,81,11,4,8.0,1,1,Rural,Data Analyst,118983,0 +12525,Male,50,Bachelors,1,75,80,48,35,0.0,3,27,Urban,ML Engineer,39951,0 +12526,Male,25,Diploma,12,53,45,84,5,0.0,5,44,Urban,Software Engineer,104461,0 +12527,Male,43,Masters,19,88,51,86,99,4.0,3,63,Urban,ML Engineer,56245,1 +12528,Male,41,Bachelors,3,17,89,30,78,3.0,6,95,Semi-Urban,ML Engineer,30806,0 +12529,Female,21,Bachelors,0,84,55,65,32,2.0,0,77,Rural,HR Executive,99118,1 +12530,Male,29,Masters,4,54,40,90,96,3.0,4,73,Urban,Software Engineer,22795,1 +12531,Male,54,Diploma,3,79,21,81,85,8.0,5,25,Rural,Software Engineer,74563,0 +12532,Female,52,Bachelors,11,1,5,83,82,1.0,3,8,Urban,Manager,30431,0 +12533,Male,26,High School,15,80,34,24,71,0.0,5,6,Urban,HR Executive,59408,0 +12534,Male,43,Bachelors,7,25,72,25,98,4.0,4,1,Semi-Urban,Software Engineer,109592,0 +12535,Male,59,Diploma,16,63,42,56,39,2.0,2,47,Urban,Software Engineer,22267,0 +12536,Male,36,Masters,18,71,18,83,50,7.0,0,1,Rural,Data Analyst,83359,0 +12537,Female,37,Diploma,8,68,24,10,99,6.0,5,89,Semi-Urban,ML Engineer,21659,0 +12538,Female,34,Bachelors,5,9,52,94,59,9.0,0,27,Semi-Urban,Manager,119134,0 +12539,Male,35,Bachelors,11,85,95,83,22,9.0,7,31,Urban,HR Executive,73262,1 +12540,Male,24,Bachelors,18,94,49,16,85,0.0,2,53,Rural,HR Executive,134757,0 +12541,Male,58,Diploma,17,8,4,70,24,0.0,1,84,Urban,HR Executive,60014,0 +12542,Male,46,Bachelors,1,28,62,37,59,3.0,5,99,Rural,Data Analyst,90356,0 +12543,Female,26,Bachelors,9,66,3,63,65,5.0,0,54,Rural,Data Analyst,78395,0 +12544,Male,46,Masters,2,10,27,97,28,4.0,1,95,Urban,HR Executive,125642,0 +12545,Male,52,Bachelors,3,99,82,95,46,6.0,0,68,Urban,Manager,20371,1 +12546,Male,39,High School,15,91,96,37,31,9.0,4,54,Urban,Manager,27354,1 +12547,Female,58,Diploma,1,60,39,7,12,3.0,6,7,Urban,HR Executive,48492,0 +12548,Female,43,Masters,16,29,63,77,33,9.0,5,82,Urban,Software Engineer,75235,1 +12549,Female,30,Diploma,7,39,85,75,53,6.0,3,26,Urban,Software Engineer,54852,0 +12550,Female,34,Diploma,8,98,97,69,49,6.0,5,74,Rural,Data Analyst,112409,1 +12551,Male,30,Masters,1,15,50,71,54,2.0,1,68,Urban,HR Executive,111238,0 +12552,Male,49,High School,0,94,58,62,61,5.0,7,3,Urban,Manager,44023,0 +12553,Male,29,Diploma,5,90,41,89,56,8.0,2,42,Urban,Software Engineer,82387,1 +12554,Female,42,Bachelors,9,73,40,36,21,9.0,0,24,Urban,HR Executive,54815,0 +12555,Female,24,Masters,12,12,47,63,25,7.0,2,18,Urban,Software Engineer,126949,0 +12556,Male,45,PhD,2,46,24,97,44,3.0,5,80,Urban,HR Executive,37889,1 +12557,Female,37,Bachelors,6,95,73,14,39,6.0,2,30,Semi-Urban,ML Engineer,146290,0 +12558,Female,54,Bachelors,13,72,72,39,40,4.0,7,83,Semi-Urban,Data Analyst,92542,1 +12559,Female,25,Diploma,8,89,14,62,58,2.0,5,84,Rural,Data Analyst,85910,1 +12560,Male,37,Masters,8,38,23,96,63,3.0,6,71,Urban,Software Engineer,21898,0 +12561,Female,34,Diploma,17,22,46,95,28,7.0,3,5,Urban,Manager,91803,0 +12562,Male,29,Bachelors,19,90,19,10,90,8.0,1,44,Semi-Urban,Software Engineer,48779,0 +12563,Female,59,Diploma,19,23,47,64,56,7.0,0,30,Urban,HR Executive,40413,0 +12564,Female,45,Diploma,10,30,17,87,40,3.0,0,31,Urban,HR Executive,146446,0 +12565,Male,48,Diploma,14,68,5,63,57,5.0,3,13,Rural,ML Engineer,76213,0 +12566,Female,21,Diploma,0,15,21,59,73,3.0,0,47,Urban,HR Executive,73855,0 +12567,Female,58,Bachelors,15,27,44,47,65,0.0,6,58,Semi-Urban,Software Engineer,121275,0 +12568,Male,26,Diploma,7,86,2,30,84,9.0,5,5,Urban,Manager,44270,0 +12569,Male,24,High School,11,67,80,49,20,7.0,5,25,Urban,HR Executive,124011,0 +12570,Male,38,Bachelors,9,89,53,23,17,3.0,3,23,Urban,ML Engineer,147430,0 +12571,Other,55,Bachelors,5,80,59,30,58,1.0,0,25,Urban,ML Engineer,106652,0 +12572,Female,36,High School,18,96,29,63,68,4.0,7,61,Semi-Urban,HR Executive,101741,1 +12573,Male,25,Bachelors,18,21,55,69,12,9.0,1,70,Semi-Urban,ML Engineer,117356,0 +12574,Male,24,Bachelors,7,21,24,2,46,5.0,6,4,Semi-Urban,HR Executive,113861,0 +12575,Male,57,Bachelors,13,68,60,70,90,7.0,4,93,Semi-Urban,HR Executive,30843,1 +12576,Male,31,Masters,2,62,19,97,74,3.0,6,36,Rural,HR Executive,66453,0 +12577,Male,36,Masters,7,26,64,51,16,9.0,7,88,Semi-Urban,Manager,58769,0 +12578,Male,43,Bachelors,2,45,33,0,4,9.0,2,22,Rural,Manager,72571,0 +12579,Male,24,Bachelors,16,5,38,73,62,9.0,4,63,Semi-Urban,ML Engineer,26674,0 +12580,Male,41,Bachelors,11,50,7,11,54,3.0,3,38,Urban,Software Engineer,124558,0 +12581,Female,54,Masters,2,80,6,33,21,4.0,4,10,Urban,Manager,91327,0 +12582,Female,46,Masters,8,62,41,3,66,0.0,5,22,Urban,HR Executive,26053,0 +12583,Female,59,Masters,3,67,65,28,75,6.0,2,65,Urban,Software Engineer,88387,0 +12584,Female,47,Bachelors,7,48,62,55,2,6.0,4,33,Rural,Manager,98609,0 +12585,Male,32,Masters,7,16,83,35,32,5.0,5,99,Urban,ML Engineer,105310,0 +12586,Male,40,Bachelors,7,81,72,27,13,3.0,1,59,Semi-Urban,Data Analyst,52753,1 +12587,Male,56,Diploma,19,9,14,30,40,0.0,6,20,Urban,Software Engineer,54923,0 +12588,Female,57,Bachelors,1,55,44,72,28,4.0,1,54,Urban,ML Engineer,134971,0 +12589,Female,44,High School,12,80,86,44,17,7.0,5,21,Rural,HR Executive,119642,0 +12590,Female,39,Diploma,14,6,7,32,65,8.0,1,87,Urban,Manager,138129,0 +12591,Female,38,Bachelors,14,96,79,1,25,2.0,7,34,Semi-Urban,ML Engineer,124484,0 +12592,Female,26,High School,17,35,19,65,25,7.0,3,67,Urban,HR Executive,105472,0 +12593,Male,35,Diploma,2,32,55,42,51,7.0,7,13,Rural,Software Engineer,73825,0 +12594,Male,58,High School,5,64,41,75,30,2.0,7,98,Urban,Manager,85451,1 +12595,Male,57,Bachelors,18,68,61,6,19,9.0,1,69,Urban,HR Executive,119309,0 +12596,Male,45,PhD,16,35,16,35,17,2.0,7,95,Urban,Manager,149238,0 +12597,Female,54,Bachelors,9,95,98,33,8,9.0,1,30,Semi-Urban,Software Engineer,130047,1 +12598,Male,53,Diploma,15,76,54,47,45,3.0,5,11,Urban,Manager,126574,0 +12599,Male,47,Diploma,11,2,25,23,66,3.0,2,14,Rural,HR Executive,57527,0 +12600,Male,29,Bachelors,17,56,15,0,84,1.0,2,56,Semi-Urban,Manager,54165,0 +12601,Male,53,Masters,19,99,85,18,20,2.0,5,51,Urban,Data Analyst,92778,1 +12602,Male,37,Masters,16,43,54,56,69,1.0,5,64,Urban,ML Engineer,48542,0 +12603,Male,56,High School,9,99,90,50,66,5.0,3,10,Rural,Software Engineer,20814,1 +12604,Male,23,Bachelors,8,22,96,18,44,4.0,5,74,Urban,Software Engineer,87778,0 +12605,Female,50,Masters,5,52,0,8,8,4.0,2,58,Rural,Data Analyst,36622,0 +12606,Male,36,Bachelors,0,87,23,41,11,2.0,3,31,Urban,Manager,59000,0 +12607,Female,41,Bachelors,15,57,89,7,93,7.0,1,97,Semi-Urban,HR Executive,144293,1 +12608,Female,59,Diploma,7,5,91,63,58,6.0,1,22,Semi-Urban,Data Analyst,107674,0 +12609,Female,29,Bachelors,10,81,12,92,36,2.0,1,90,Semi-Urban,Manager,132983,1 +12610,Female,26,Bachelors,8,94,85,33,83,3.0,5,73,Rural,HR Executive,95221,1 +12611,Male,50,Bachelors,16,46,22,21,78,3.0,1,93,Rural,ML Engineer,115478,0 +12612,Male,44,Diploma,10,34,92,32,56,0.0,6,20,Semi-Urban,Software Engineer,109588,0 +12613,Male,30,Diploma,8,55,14,57,24,6.0,2,41,Semi-Urban,Manager,103180,0 +12614,Male,54,Diploma,7,33,3,48,91,0.0,5,13,Rural,HR Executive,100179,0 +12615,Female,59,Masters,16,12,93,96,54,6.0,6,67,Semi-Urban,ML Engineer,135480,1 +12616,Female,52,Bachelors,7,95,47,66,3,7.0,1,73,Urban,Software Engineer,59661,1 +12617,Male,46,High School,16,87,44,7,17,1.0,1,45,Semi-Urban,Software Engineer,145515,0 +12618,Male,48,Bachelors,11,89,91,52,22,7.0,5,18,Urban,HR Executive,106116,1 +12619,Male,25,Bachelors,12,4,90,71,5,8.0,3,88,Semi-Urban,HR Executive,43974,1 +12620,Female,23,Bachelors,17,61,92,79,3,8.0,4,29,Semi-Urban,ML Engineer,91471,1 +12621,Female,27,Diploma,9,68,32,97,32,2.0,3,5,Semi-Urban,ML Engineer,97287,0 +12622,Female,42,Diploma,14,58,52,69,14,4.0,5,90,Semi-Urban,HR Executive,117216,1 +12623,Female,50,Bachelors,16,76,90,4,87,2.0,1,74,Urban,Manager,79398,1 +12624,Male,48,Masters,8,7,57,55,63,7.0,7,1,Urban,Data Analyst,81851,0 +12625,Male,44,Bachelors,17,60,17,8,32,6.0,7,52,Semi-Urban,HR Executive,62955,0 +12626,Male,45,Diploma,11,64,4,68,58,0.0,6,48,Urban,ML Engineer,38073,0 +12627,Male,54,Bachelors,0,43,71,20,98,4.0,2,93,Rural,Data Analyst,78280,0 +12628,Female,47,Bachelors,17,58,69,90,80,0.0,7,60,Urban,ML Engineer,76744,1 +12629,Male,28,Diploma,17,35,52,16,27,6.0,1,84,Semi-Urban,Software Engineer,61107,0 +12630,Female,52,Masters,6,77,86,10,48,7.0,4,13,Rural,Manager,76867,0 +12631,Male,34,Masters,11,81,97,15,1,1.0,2,94,Semi-Urban,Manager,70641,1 +12632,Male,22,Bachelors,2,67,89,90,16,1.0,5,40,Semi-Urban,Data Analyst,31370,1 +12633,Male,44,Diploma,18,0,47,73,7,2.0,7,32,Urban,Software Engineer,41581,0 +12634,Male,23,High School,3,43,8,81,14,1.0,0,11,Urban,ML Engineer,78343,0 +12635,Female,21,Bachelors,4,3,89,13,75,1.0,5,46,Semi-Urban,Software Engineer,31822,0 +12636,Male,48,Masters,11,18,70,43,81,4.0,7,3,Rural,ML Engineer,54735,0 +12637,Female,46,Masters,7,76,0,51,70,8.0,3,14,Urban,HR Executive,82881,0 +12638,Female,45,Masters,19,47,51,63,48,1.0,4,12,Urban,Software Engineer,126999,0 +12639,Male,47,Masters,0,59,81,34,12,5.0,7,29,Urban,Manager,113499,0 +12640,Female,30,High School,12,47,54,15,79,8.0,5,0,Urban,Manager,143537,0 +12641,Male,44,Masters,8,25,37,82,1,0.0,6,17,Urban,Data Analyst,89043,0 +12642,Female,52,High School,15,45,36,84,11,6.0,3,39,Urban,Software Engineer,92455,0 +12643,Female,31,Diploma,18,88,11,84,14,3.0,1,58,Rural,ML Engineer,34372,1 +12644,Other,21,Bachelors,10,32,71,6,13,6.0,5,29,Urban,ML Engineer,134437,0 +12645,Male,22,PhD,16,7,47,68,9,0.0,1,65,Urban,Software Engineer,120495,0 +12646,Male,35,Masters,7,11,66,52,91,3.0,4,43,Semi-Urban,HR Executive,114691,0 +12647,Male,28,Bachelors,13,83,92,81,83,8.0,1,82,Rural,Software Engineer,66019,1 +12648,Male,33,Masters,10,14,74,79,60,1.0,0,43,Urban,HR Executive,136999,0 +12649,Female,46,Masters,2,6,68,43,0,9.0,6,5,Semi-Urban,Software Engineer,20359,0 +12650,Female,54,PhD,19,93,51,27,20,8.0,7,62,Rural,Data Analyst,143989,0 +12651,Male,44,Bachelors,3,7,39,74,35,6.0,1,69,Semi-Urban,Manager,54102,0 +12652,Male,21,High School,1,39,78,27,91,7.0,3,93,Urban,HR Executive,85779,1 +12653,Male,25,Bachelors,19,14,37,22,90,2.0,1,23,Semi-Urban,HR Executive,103053,0 +12654,Male,39,Bachelors,6,27,82,0,16,5.0,7,73,Urban,Software Engineer,100166,0 +12655,Male,32,Diploma,4,5,70,58,25,9.0,4,62,Semi-Urban,HR Executive,144708,0 +12656,Male,29,Diploma,9,57,29,26,42,5.0,1,51,Semi-Urban,Manager,133150,0 +12657,Female,22,Bachelors,4,32,46,40,62,6.0,4,32,Urban,Software Engineer,81660,0 +12658,Male,28,Masters,9,21,14,7,25,2.0,4,6,Semi-Urban,ML Engineer,27424,0 +12659,Male,30,Bachelors,9,34,2,50,23,5.0,2,72,Urban,Data Analyst,43812,0 +12660,Female,49,High School,15,17,9,49,54,7.0,2,94,Urban,ML Engineer,90747,0 +12661,Male,43,High School,13,20,90,37,49,4.0,5,27,Rural,Data Analyst,131149,0 +12662,Female,47,PhD,17,8,81,12,15,8.0,4,47,Urban,Software Engineer,93543,0 +12663,Female,57,Bachelors,15,15,72,10,38,0.0,1,54,Urban,Software Engineer,31703,0 +12664,Female,36,Bachelors,16,82,94,27,89,8.0,2,68,Urban,ML Engineer,111663,1 +12665,Male,52,Diploma,13,91,69,95,29,9.0,3,55,Urban,Data Analyst,68306,1 +12666,Male,33,Bachelors,11,77,91,93,69,9.0,2,64,Semi-Urban,HR Executive,21276,1 +12667,Female,26,Diploma,18,11,76,11,72,0.0,1,4,Rural,ML Engineer,101122,0 +12668,Female,43,Masters,5,2,70,59,98,5.0,0,80,Urban,Manager,143020,0 +12669,Male,56,Masters,2,14,61,24,96,8.0,4,13,Urban,Manager,47371,0 +12670,Male,44,High School,8,12,27,50,86,0.0,2,22,Urban,HR Executive,72395,0 +12671,Male,31,PhD,19,42,0,49,38,3.0,1,55,Urban,Software Engineer,23130,0 +12672,Male,50,Bachelors,17,72,78,24,20,1.0,6,32,Semi-Urban,Software Engineer,139506,0 +12673,Male,35,Bachelors,16,81,70,55,41,2.0,3,73,Rural,ML Engineer,135040,1 +12674,Male,37,Masters,4,22,19,65,90,8.0,2,85,Semi-Urban,Manager,102060,0 +12675,Male,50,Diploma,10,19,65,59,91,5.0,7,61,Urban,ML Engineer,103810,0 +12676,Female,42,Masters,17,35,68,27,83,0.0,4,19,Semi-Urban,Software Engineer,57807,0 +12677,Male,35,Bachelors,10,18,99,82,49,4.0,1,79,Urban,Data Analyst,135074,1 +12678,Female,23,Diploma,13,88,33,94,99,7.0,5,99,Urban,Manager,105183,1 +12679,Female,41,Diploma,1,29,78,65,90,3.0,0,37,Urban,HR Executive,116591,0 +12680,Male,58,PhD,17,34,62,94,0,3.0,3,55,Rural,HR Executive,87035,1 +12681,Female,29,High School,15,17,93,59,81,8.0,2,59,Urban,ML Engineer,92124,0 +12682,Female,35,Bachelors,1,62,72,51,90,0.0,1,93,Semi-Urban,ML Engineer,118574,1 +12683,Male,42,Bachelors,3,86,36,0,74,1.0,4,39,Urban,Software Engineer,81179,0 +12684,Male,56,Masters,16,29,14,94,28,2.0,7,44,Rural,Manager,37174,0 +12685,Male,53,Diploma,12,21,92,14,17,4.0,7,54,Semi-Urban,Manager,144837,0 +12686,Female,41,High School,8,28,0,16,58,9.0,2,89,Urban,Data Analyst,90435,0 +12687,Female,42,PhD,19,17,16,60,37,5.0,7,24,Semi-Urban,ML Engineer,32657,0 +12688,Male,27,High School,19,11,71,54,20,2.0,3,76,Semi-Urban,Data Analyst,91142,0 +12689,Female,47,Bachelors,6,64,38,22,78,3.0,6,12,Rural,Data Analyst,126567,0 +12690,Male,25,Bachelors,6,74,11,99,27,0.0,2,42,Urban,HR Executive,74965,0 +12691,Male,44,Masters,4,58,62,46,17,0.0,4,72,Rural,Data Analyst,107007,1 +12692,Female,22,Diploma,15,46,5,7,77,3.0,2,87,Rural,Manager,33700,0 +12693,Male,42,Masters,15,45,65,3,98,1.0,1,99,Rural,HR Executive,83341,0 +12694,Female,26,Diploma,2,98,24,79,47,8.0,3,50,Urban,ML Engineer,122390,1 +12695,Female,46,PhD,19,82,31,30,48,0.0,4,37,Semi-Urban,ML Engineer,48833,0 +12696,Female,23,Bachelors,17,6,39,62,60,5.0,2,78,Rural,Software Engineer,80173,0 +12697,Male,24,Bachelors,3,61,0,52,47,7.0,0,76,Semi-Urban,Data Analyst,55159,0 +12698,Female,33,Diploma,4,52,35,56,22,1.0,3,45,Urban,Software Engineer,114168,0 +12699,Female,57,Masters,3,78,3,80,74,0.0,0,13,Rural,HR Executive,93521,0 +12700,Male,39,Bachelors,18,86,7,35,96,3.0,2,12,Urban,HR Executive,39871,0 +12701,Male,54,Bachelors,13,90,20,86,57,1.0,6,91,Semi-Urban,Manager,80511,1 +12702,Male,58,Masters,18,59,0,14,23,9.0,7,63,Urban,ML Engineer,39491,0 +12703,Female,28,High School,8,46,92,87,63,1.0,7,63,Rural,Software Engineer,139079,1 +12704,Female,30,Bachelors,6,66,7,77,23,1.0,1,20,Urban,Manager,115295,0 +12705,Male,41,High School,4,73,72,19,44,2.0,6,36,Semi-Urban,Manager,27866,0 +12706,Female,39,PhD,19,56,27,85,71,2.0,4,33,Urban,Manager,145978,0 +12707,Male,31,Masters,19,44,62,36,4,6.0,6,32,Semi-Urban,Data Analyst,70526,0 +12708,Female,29,Masters,8,27,93,69,86,2.0,0,95,Rural,Data Analyst,73361,1 +12709,Male,40,High School,17,93,65,5,34,2.0,4,3,Urban,ML Engineer,111768,0 +12710,Male,58,Masters,1,38,68,17,77,5.0,6,8,Urban,ML Engineer,126643,0 +12711,Male,30,Bachelors,14,69,58,32,25,8.0,4,16,Semi-Urban,Manager,30489,0 +12712,Male,21,High School,18,2,17,57,77,5.0,5,98,Urban,Manager,136228,0 +12713,Female,49,Diploma,11,88,54,11,5,6.0,7,61,Urban,Manager,113620,0 +12714,Male,51,PhD,7,43,65,95,80,3.0,6,51,Urban,Data Analyst,125848,1 +12715,Male,46,Masters,16,39,86,85,43,5.0,5,67,Rural,Manager,108184,1 +12716,Male,40,Masters,11,12,7,93,80,5.0,3,92,Urban,HR Executive,131177,0 +12717,Male,26,Diploma,6,74,74,53,43,7.0,7,21,Urban,Manager,68638,0 +12718,Female,51,High School,6,53,3,28,41,9.0,6,96,Rural,HR Executive,46628,0 +12719,Female,32,Bachelors,8,0,26,78,74,1.0,5,98,Urban,ML Engineer,39149,0 +12720,Male,37,Bachelors,17,3,29,70,28,8.0,7,5,Urban,Software Engineer,76273,0 +12721,Male,44,High School,13,20,76,15,9,9.0,7,95,Urban,ML Engineer,146996,0 +12722,Male,26,Bachelors,5,24,55,70,91,6.0,3,27,Urban,Manager,31223,0 +12723,Female,39,Bachelors,3,31,0,16,35,4.0,2,34,Urban,Data Analyst,26228,0 +12724,Female,54,Bachelors,7,52,19,39,67,9.0,1,70,Semi-Urban,Manager,44687,0 +12725,Female,23,Diploma,18,68,61,90,86,6.0,5,31,Rural,Manager,90566,1 +12726,Female,58,Diploma,19,98,56,83,47,9.0,6,34,Semi-Urban,ML Engineer,148067,1 +12727,Female,37,Bachelors,19,0,95,12,41,5.0,0,84,Semi-Urban,HR Executive,67104,0 +12728,Female,39,Masters,1,76,24,95,5,2.0,2,11,Semi-Urban,Software Engineer,108283,0 +12729,Male,24,PhD,18,99,90,27,50,6.0,1,82,Urban,Software Engineer,101330,1 +12730,Male,33,Masters,11,31,98,15,91,3.0,1,77,Semi-Urban,Software Engineer,62151,0 +12731,Male,29,Diploma,15,50,10,72,77,0.0,4,49,Semi-Urban,Data Analyst,59903,0 +12732,Male,50,Masters,10,21,22,8,71,6.0,0,88,Urban,Manager,57608,0 +12733,Female,24,PhD,15,14,84,29,30,7.0,0,44,Rural,HR Executive,51593,0 +12734,Male,44,Masters,6,93,60,45,37,7.0,7,60,Urban,ML Engineer,24841,1 +12735,Male,35,High School,7,50,2,45,6,0.0,5,80,Urban,ML Engineer,72765,0 +12736,Male,29,Diploma,10,24,98,29,3,8.0,6,62,Semi-Urban,ML Engineer,62493,0 +12737,Male,40,Masters,3,60,3,43,9,8.0,5,28,Urban,HR Executive,54399,0 +12738,Male,51,Masters,1,42,44,13,83,3.0,3,3,Urban,HR Executive,48689,0 +12739,Female,52,Masters,5,66,92,38,20,9.0,2,95,Urban,HR Executive,74628,1 +12740,Female,27,Masters,19,96,36,22,38,1.0,5,48,Semi-Urban,Software Engineer,140939,0 +12741,Female,56,Masters,8,78,40,3,83,0.0,3,65,Urban,Software Engineer,41188,0 +12742,Male,25,Diploma,0,92,58,52,33,8.0,0,7,Rural,Manager,101368,0 +12743,Male,22,Diploma,7,40,42,45,55,4.0,3,43,Semi-Urban,HR Executive,147679,0 +12744,Male,29,Masters,15,75,44,98,16,1.0,6,52,Urban,HR Executive,89513,1 +12745,Female,46,High School,4,33,90,80,66,5.0,2,78,Urban,HR Executive,82207,1 +12746,Male,37,High School,9,93,49,86,53,1.0,2,74,Urban,HR Executive,94549,1 +12747,Male,52,High School,0,56,40,30,46,2.0,5,99,Semi-Urban,Software Engineer,122779,0 +12748,Female,50,Bachelors,11,62,16,80,68,9.0,0,99,Semi-Urban,ML Engineer,79709,1 +12749,Male,25,High School,18,97,61,26,25,7.0,2,64,Rural,Data Analyst,66173,1 +12750,Male,40,Bachelors,14,51,71,96,59,4.0,6,95,Semi-Urban,Manager,109901,1 +12751,Male,26,Diploma,14,61,49,72,56,3.0,1,28,Semi-Urban,Manager,120862,0 +12752,Male,28,Bachelors,16,95,43,10,2,2.0,2,74,Semi-Urban,Manager,77842,0 +12753,Male,52,Masters,17,6,69,13,10,4.0,4,65,Urban,HR Executive,107083,0 +12754,Male,32,Masters,13,62,39,31,41,3.0,1,79,Urban,ML Engineer,90249,0 +12755,Female,46,High School,6,43,23,5,2,9.0,1,64,Urban,Data Analyst,139195,0 +12756,Female,40,Bachelors,15,54,86,48,31,3.0,3,27,Urban,ML Engineer,24275,0 +12757,Male,33,Bachelors,16,42,7,8,24,7.0,7,14,Rural,Software Engineer,58574,0 +12758,Female,44,Diploma,8,35,53,45,50,1.0,4,70,Urban,Data Analyst,57230,0 +12759,Male,54,Bachelors,12,65,88,3,26,7.0,2,14,Urban,Data Analyst,108708,0 +12760,Male,28,High School,6,34,63,5,58,8.0,5,21,Rural,HR Executive,62845,0 +12761,Male,36,Diploma,11,13,48,46,57,3.0,5,19,Semi-Urban,Data Analyst,27666,0 +12762,Female,41,High School,19,23,44,95,49,3.0,1,61,Rural,ML Engineer,104399,0 +12763,Male,42,High School,7,39,74,53,42,4.0,7,63,Urban,ML Engineer,94552,0 +12764,Female,51,Diploma,5,25,4,65,29,7.0,4,23,Urban,Software Engineer,137318,0 +12765,Female,41,Diploma,16,15,88,34,53,7.0,3,55,Semi-Urban,ML Engineer,35601,0 +12766,Male,31,High School,2,66,91,72,59,3.0,7,80,Urban,HR Executive,89481,1 +12767,Female,41,Bachelors,16,18,92,76,77,5.0,5,36,Urban,Manager,52232,0 +12768,Female,44,Masters,10,30,52,87,52,4.0,3,61,Urban,HR Executive,122771,0 +12769,Male,37,Masters,14,85,24,8,26,5.0,5,43,Urban,Data Analyst,144347,0 +12770,Male,25,Masters,18,63,11,41,25,0.0,1,81,Urban,HR Executive,48803,0 +12771,Female,31,Bachelors,4,92,12,35,46,0.0,4,39,Semi-Urban,HR Executive,145721,0 +12772,Female,28,Bachelors,12,84,77,56,66,6.0,1,31,Urban,Software Engineer,89556,1 +12773,Male,26,Masters,0,85,9,53,85,8.0,0,85,Urban,Data Analyst,85227,0 +12774,Male,29,Bachelors,0,65,29,43,60,9.0,1,50,Urban,Software Engineer,28589,0 +12775,Male,49,Bachelors,9,23,5,10,99,8.0,4,84,Semi-Urban,Software Engineer,144622,0 +12776,Male,59,Bachelors,7,72,17,95,3,7.0,0,84,Urban,Software Engineer,54299,1 +12777,Male,26,Bachelors,19,85,62,64,32,0.0,1,29,Urban,Data Analyst,96337,1 +12778,Female,26,Bachelors,3,44,83,46,82,3.0,3,29,Urban,ML Engineer,23498,0 +12779,Female,40,Bachelors,8,98,86,42,86,0.0,0,24,Urban,Data Analyst,122055,1 +12780,Male,47,Bachelors,13,24,5,2,83,6.0,7,6,Rural,Software Engineer,146333,0 +12781,Female,35,PhD,11,97,78,87,46,6.0,3,59,Urban,Data Analyst,146849,1 +12782,Female,44,Bachelors,19,37,5,66,29,2.0,3,9,Rural,Data Analyst,83142,0 +12783,Male,28,Bachelors,18,56,53,83,32,0.0,1,61,Urban,HR Executive,83477,1 +12784,Male,54,Bachelors,2,40,44,61,11,9.0,6,79,Semi-Urban,Software Engineer,68951,0 +12785,Male,45,Diploma,11,5,15,61,12,2.0,5,6,Urban,Data Analyst,31457,0 +12786,Female,23,Masters,15,31,91,69,84,2.0,2,97,Rural,ML Engineer,137393,1 +12787,Male,32,Diploma,1,20,43,5,35,8.0,6,5,Urban,HR Executive,88731,0 +12788,Other,49,Bachelors,17,26,29,68,41,0.0,0,29,Semi-Urban,Data Analyst,122639,0 +12789,Male,29,Masters,5,25,77,86,12,2.0,0,52,Urban,Manager,100172,1 +12790,Male,39,Bachelors,10,49,38,84,13,4.0,4,17,Semi-Urban,ML Engineer,136268,0 +12791,Male,45,Masters,0,58,86,60,50,8.0,0,53,Urban,Data Analyst,71159,1 +12792,Male,54,Bachelors,17,80,70,90,40,0.0,0,82,Urban,HR Executive,93408,1 +12793,Female,49,High School,19,59,89,77,51,5.0,0,42,Urban,HR Executive,45507,1 +12794,Other,43,Bachelors,19,55,37,0,78,5.0,1,68,Semi-Urban,Software Engineer,77241,0 +12795,Male,58,Bachelors,19,43,53,40,5,9.0,2,13,Urban,HR Executive,144444,0 +12796,Other,39,High School,14,90,7,38,3,1.0,5,36,Urban,Manager,62975,0 +12797,Female,35,Diploma,1,94,52,67,26,7.0,7,74,Rural,HR Executive,50267,1 +12798,Male,30,Masters,2,72,66,62,23,1.0,2,20,Urban,HR Executive,87681,0 +12799,Female,33,Diploma,2,35,91,21,7,0.0,0,32,Semi-Urban,ML Engineer,89489,0 +12800,Male,58,Diploma,6,42,48,40,26,2.0,2,64,Rural,HR Executive,71653,0 +12801,Male,25,Bachelors,10,50,4,53,12,1.0,0,72,Urban,Data Analyst,127121,0 +12802,Male,36,Bachelors,4,81,47,56,30,7.0,5,77,Semi-Urban,Data Analyst,90147,1 +12803,Female,48,Bachelors,11,60,46,71,19,6.0,3,81,Semi-Urban,Manager,63806,1 +12804,Male,50,Bachelors,3,0,23,34,14,9.0,6,65,Urban,ML Engineer,35291,0 +12805,Female,29,High School,15,20,27,98,83,0.0,6,72,Semi-Urban,Manager,62179,0 +12806,Female,31,Bachelors,16,35,88,11,26,4.0,0,72,Urban,Software Engineer,47053,0 +12807,Male,45,Bachelors,4,74,9,82,85,3.0,0,12,Urban,ML Engineer,22153,0 +12808,Male,57,Bachelors,14,53,47,41,27,7.0,6,79,Urban,ML Engineer,93628,0 +12809,Male,38,Masters,1,17,1,79,55,2.0,5,91,Urban,Data Analyst,123053,0 +12810,Male,32,Diploma,6,8,15,33,67,5.0,0,8,Rural,Manager,25030,0 +12811,Male,22,High School,4,9,35,70,42,4.0,6,16,Urban,HR Executive,126738,0 +12812,Male,21,High School,6,66,21,21,49,6.0,5,14,Urban,Manager,103170,0 +12813,Male,37,Masters,7,53,94,88,85,7.0,6,2,Urban,Software Engineer,105972,1 +12814,Male,44,PhD,19,6,2,50,76,4.0,5,26,Semi-Urban,Software Engineer,113866,0 +12815,Male,57,Bachelors,12,71,17,71,82,9.0,7,66,Semi-Urban,HR Executive,131459,0 +12816,Male,56,Bachelors,4,72,90,82,9,9.0,1,88,Rural,Manager,31422,1 +12817,Female,49,Bachelors,12,44,99,85,63,4.0,0,75,Urban,ML Engineer,103809,1 +12818,Other,40,Masters,3,17,35,25,29,8.0,7,69,Urban,Manager,64777,0 +12819,Male,28,Masters,17,26,47,4,35,2.0,6,49,Semi-Urban,HR Executive,36344,0 +12820,Male,28,Bachelors,7,28,44,62,17,0.0,3,4,Urban,ML Engineer,60947,0 +12821,Male,42,Masters,2,17,52,17,3,3.0,2,57,Urban,HR Executive,48302,0 +12822,Male,45,Diploma,0,33,21,69,19,5.0,4,66,Urban,ML Engineer,104834,0 +12823,Male,29,Masters,3,88,3,9,96,1.0,6,89,Urban,HR Executive,77212,0 +12824,Female,37,PhD,5,2,51,3,66,8.0,5,16,Urban,HR Executive,85805,0 +12825,Female,37,Masters,4,73,5,26,2,7.0,5,49,Semi-Urban,Data Analyst,34395,0 +12826,Male,43,PhD,2,0,33,84,62,7.0,4,47,Urban,HR Executive,118242,0 +12827,Female,44,High School,0,32,25,20,19,2.0,5,99,Semi-Urban,HR Executive,112449,0 +12828,Male,23,Diploma,2,20,83,62,98,5.0,0,92,Rural,Data Analyst,44267,1 +12829,Male,35,High School,19,4,33,43,86,3.0,4,42,Urban,ML Engineer,95628,0 +12830,Male,22,Bachelors,14,86,43,8,81,7.0,1,17,Rural,Manager,138007,0 +12831,Male,57,Diploma,3,28,45,27,36,0.0,2,53,Semi-Urban,Manager,98009,0 +12832,Male,30,Diploma,14,38,98,77,81,2.0,3,37,Urban,Manager,48136,1 +12833,Male,51,Masters,9,14,24,71,23,7.0,5,8,Semi-Urban,Software Engineer,140535,0 +12834,Male,33,Bachelors,12,42,84,82,3,1.0,5,55,Semi-Urban,Manager,88299,1 +12835,Male,33,PhD,15,22,93,26,87,9.0,3,27,Urban,Software Engineer,110481,0 +12836,Female,47,Bachelors,10,83,94,72,77,2.0,7,37,Rural,HR Executive,100843,1 +12837,Female,24,Diploma,10,74,99,48,41,5.0,0,98,Urban,HR Executive,49133,1 +12838,Male,40,Bachelors,13,36,16,94,46,8.0,4,45,Urban,Software Engineer,33447,0 +12839,Male,38,Diploma,5,89,60,7,10,7.0,5,91,Urban,Data Analyst,23767,1 +12840,Male,21,Diploma,14,67,92,53,7,1.0,3,10,Rural,Manager,137308,0 +12841,Female,53,High School,12,72,96,80,19,1.0,4,36,Urban,Software Engineer,126676,1 +12842,Male,38,Bachelors,4,87,38,4,19,0.0,2,70,Urban,Software Engineer,134246,0 +12843,Male,46,Bachelors,13,92,92,17,34,2.0,7,46,Rural,Manager,144000,1 +12844,Male,36,Diploma,2,18,57,20,89,8.0,4,26,Semi-Urban,Data Analyst,75861,0 +12845,Male,54,Diploma,14,32,87,32,41,1.0,5,97,Urban,HR Executive,119711,1 +12846,Male,33,Diploma,6,42,19,65,97,2.0,5,9,Urban,HR Executive,147212,0 +12847,Female,21,High School,10,62,88,96,26,0.0,1,94,Rural,Software Engineer,64377,1 +12848,Female,58,Bachelors,17,69,17,50,77,9.0,1,20,Semi-Urban,Manager,109108,0 +12849,Male,28,Bachelors,16,51,35,5,76,0.0,7,86,Urban,Manager,55335,0 +12850,Male,57,Bachelors,7,92,40,8,58,2.0,6,51,Semi-Urban,ML Engineer,75270,0 +12851,Male,48,PhD,7,86,9,11,85,7.0,5,84,Semi-Urban,HR Executive,21251,0 +12852,Male,39,Bachelors,19,84,36,74,12,0.0,0,44,Urban,Software Engineer,111729,1 +12853,Female,45,Masters,16,31,57,24,50,7.0,7,21,Urban,Manager,124639,0 +12854,Male,41,PhD,3,57,86,20,20,3.0,0,23,Urban,Manager,59834,0 +12855,Male,58,Masters,10,54,29,73,24,2.0,1,2,Semi-Urban,Manager,146991,0 +12856,Male,39,Bachelors,5,79,60,39,88,3.0,2,86,Urban,HR Executive,54815,1 +12857,Female,35,Masters,15,8,96,64,79,0.0,1,71,Urban,HR Executive,40050,0 +12858,Female,43,Bachelors,8,97,5,56,16,1.0,4,10,Urban,Manager,122851,0 +12859,Male,51,Bachelors,4,34,74,61,77,7.0,5,24,Urban,Software Engineer,104958,0 +12860,Male,55,Masters,11,78,81,26,76,7.0,4,89,Urban,HR Executive,99365,1 +12861,Male,55,PhD,2,77,68,15,21,8.0,7,53,Urban,Data Analyst,33257,0 +12862,Other,28,Bachelors,3,22,1,42,98,3.0,1,45,Rural,Software Engineer,79958,0 +12863,Male,32,Bachelors,7,42,30,4,94,1.0,0,35,Semi-Urban,Manager,55000,0 +12864,Male,50,PhD,18,96,87,34,71,6.0,0,75,Urban,Data Analyst,83750,1 +12865,Male,38,Bachelors,7,54,82,44,17,7.0,2,80,Urban,Data Analyst,72469,1 +12866,Female,51,Diploma,15,8,77,71,94,7.0,1,65,Semi-Urban,HR Executive,122756,0 +12867,Male,51,Diploma,12,9,46,53,55,8.0,3,62,Urban,ML Engineer,139368,0 +12868,Male,31,High School,10,29,47,23,33,0.0,5,13,Rural,HR Executive,85872,0 +12869,Male,45,Bachelors,5,13,7,47,93,4.0,0,19,Urban,Data Analyst,98447,0 +12870,Female,38,Bachelors,3,15,67,0,89,0.0,6,48,Semi-Urban,HR Executive,109101,0 +12871,Female,36,Masters,18,53,62,66,44,9.0,0,3,Semi-Urban,Manager,43431,0 +12872,Female,27,Diploma,5,68,97,12,19,3.0,0,0,Urban,ML Engineer,79359,0 +12873,Male,35,Bachelors,16,24,50,30,12,3.0,6,3,Rural,ML Engineer,137446,0 +12874,Male,37,High School,13,11,10,80,55,9.0,7,11,Semi-Urban,ML Engineer,26557,0 +12875,Other,32,Masters,17,66,90,19,71,0.0,1,88,Urban,Software Engineer,57884,1 +12876,Male,31,Bachelors,5,50,73,14,25,7.0,0,1,Semi-Urban,HR Executive,146357,0 +12877,Female,30,Masters,1,16,54,57,64,1.0,7,85,Rural,HR Executive,130108,0 +12878,Female,49,High School,12,34,90,43,38,5.0,7,91,Urban,Manager,79468,1 +12879,Male,52,Masters,1,62,10,75,54,1.0,7,86,Rural,HR Executive,122758,0 +12880,Male,38,Bachelors,16,17,48,58,37,8.0,4,10,Urban,Software Engineer,29680,0 +12881,Female,41,Bachelors,6,21,57,86,53,0.0,2,15,Semi-Urban,ML Engineer,110578,0 +12882,Female,48,Diploma,8,66,56,29,94,5.0,3,8,Semi-Urban,Software Engineer,68330,0 +12883,Male,34,Bachelors,9,2,88,14,98,7.0,2,85,Semi-Urban,Manager,77097,0 +12884,Male,48,High School,14,23,18,76,27,6.0,0,23,Urban,ML Engineer,49337,0 +12885,Male,36,PhD,19,26,27,6,5,3.0,2,92,Semi-Urban,Data Analyst,87691,0 +12886,Male,33,Masters,2,81,50,27,39,0.0,2,19,Urban,Software Engineer,31860,0 +12887,Male,50,,18,56,96,24,58,3.0,5,67,Urban,HR Executive,100058,1 +12888,Male,57,Masters,13,3,81,16,5,1.0,2,40,Semi-Urban,Data Analyst,53964,0 +12889,Other,39,Bachelors,19,21,23,71,77,2.0,6,0,Urban,HR Executive,64509,0 +12890,Female,38,High School,2,75,42,36,20,5.0,2,19,Rural,Software Engineer,148998,0 +12891,Female,26,Diploma,18,16,46,41,22,7.0,6,9,Rural,Data Analyst,97446,0 +12892,Male,46,Masters,12,96,99,87,0,9.0,4,93,Urban,Manager,139038,1 +12893,Male,49,High School,4,53,99,50,48,6.0,7,39,Semi-Urban,ML Engineer,93005,1 +12894,Other,40,Bachelors,13,53,75,73,54,5.0,5,62,Urban,Data Analyst,116147,1 +12895,Male,57,Bachelors,7,34,21,92,57,9.0,7,52,Semi-Urban,ML Engineer,97439,0 +12896,Male,32,Bachelors,16,18,81,38,70,0.0,6,90,Semi-Urban,Software Engineer,137370,0 +12897,Male,48,Bachelors,6,10,77,70,10,8.0,2,87,Semi-Urban,HR Executive,127306,1 +12898,Female,38,Bachelors,3,9,28,76,29,4.0,7,27,Rural,Software Engineer,146817,0 +12899,Female,26,Diploma,1,41,62,36,3,9.0,3,53,Rural,Manager,133211,0 +12900,Male,22,High School,13,98,54,74,93,6.0,1,51,Urban,ML Engineer,57801,1 +12901,Female,29,Bachelors,1,60,56,29,54,5.0,5,68,Rural,Software Engineer,66353,0 +12902,Male,50,Masters,7,73,5,99,41,1.0,0,69,Urban,Manager,136473,1 +12903,Male,32,Bachelors,16,73,21,33,97,3.0,2,43,Rural,ML Engineer,23011,0 +12904,Female,25,Bachelors,6,73,15,10,35,7.0,6,80,Semi-Urban,Manager,97196,0 +12905,Female,59,Bachelors,11,7,51,26,20,2.0,1,6,Rural,Software Engineer,140168,0 +12906,Male,22,PhD,5,73,92,86,74,5.0,3,82,Semi-Urban,Manager,50537,1 +12907,Male,58,Bachelors,12,84,68,47,51,4.0,2,34,Semi-Urban,Software Engineer,94357,0 +12908,Female,28,Diploma,13,40,7,66,88,4.0,1,3,Semi-Urban,ML Engineer,107282,0 +12909,Female,26,Bachelors,7,30,30,98,55,5.0,5,94,Semi-Urban,HR Executive,51374,1 +12910,Female,31,High School,9,2,16,57,41,2.0,6,74,Semi-Urban,ML Engineer,98100,0 +12911,Male,51,Bachelors,2,83,3,60,48,3.0,5,72,Semi-Urban,Manager,60694,0 +12912,Other,30,High School,12,45,71,1,53,1.0,4,29,Urban,HR Executive,38310,0 +12913,Other,57,Masters,17,72,69,58,61,5.0,0,72,Urban,Data Analyst,86334,1 +12914,Male,42,High School,18,38,10,60,54,5.0,2,34,Urban,HR Executive,70534,0 +12915,Female,53,Bachelors,4,63,91,8,73,3.0,7,27,Urban,ML Engineer,75988,0 +12916,Male,29,Bachelors,3,71,77,51,9,2.0,6,74,Semi-Urban,HR Executive,93548,1 +12917,Male,56,Bachelors,5,27,14,3,35,4.0,7,38,Urban,ML Engineer,63284,0 +12918,Female,43,High School,8,82,52,42,21,0.0,3,40,Urban,Manager,95590,0 +12919,Male,51,Bachelors,1,97,0,34,63,0.0,3,1,Rural,Manager,123637,0 +12920,Male,41,Masters,16,26,91,84,1,4.0,1,0,Urban,HR Executive,110236,0 +12921,Female,23,Diploma,8,63,28,62,80,5.0,2,85,Urban,HR Executive,93757,0 +12922,Male,31,Bachelors,3,6,51,72,57,3.0,0,6,Urban,Manager,35630,0 +12923,Male,50,PhD,8,94,54,62,75,2.0,7,80,Urban,HR Executive,48627,1 +12924,Female,45,Bachelors,1,36,12,46,30,6.0,4,53,Semi-Urban,Manager,50262,0 +12925,Male,48,Diploma,3,9,82,5,73,2.0,6,26,Semi-Urban,Software Engineer,136734,0 +12926,Male,45,Masters,14,37,82,92,30,8.0,4,79,Urban,Data Analyst,89627,1 +12927,Male,37,Bachelors,10,76,9,56,45,6.0,3,78,Semi-Urban,ML Engineer,29181,0 +12928,Male,43,Bachelors,2,31,66,12,49,5.0,0,15,Urban,Software Engineer,120200,0 +12929,Female,56,Bachelors,3,68,60,93,69,6.0,4,1,Urban,HR Executive,100356,0 +12930,Female,59,Bachelors,4,71,94,72,25,7.0,6,40,Semi-Urban,Data Analyst,93984,1 +12931,Male,22,Bachelors,11,61,2,67,21,2.0,4,77,Urban,Manager,61872,0 +12932,Female,31,Bachelors,14,95,76,47,27,2.0,5,95,Urban,Software Engineer,98767,1 +12933,Male,32,Diploma,9,4,92,13,13,2.0,1,94,Urban,Data Analyst,36219,0 +12934,Male,24,Bachelors,14,80,17,7,76,8.0,4,26,Urban,Software Engineer,113376,0 +12935,Female,41,PhD,1,33,87,24,45,4.0,7,97,Semi-Urban,Manager,110971,1 +12936,Female,58,PhD,3,95,44,45,53,6.0,4,88,Urban,Data Analyst,48843,1 +12937,Male,25,PhD,10,79,62,15,73,9.0,5,53,Semi-Urban,ML Engineer,141226,0 +12938,Male,22,Diploma,3,24,77,15,19,8.0,4,60,Rural,Manager,87681,0 +12939,Male,55,Bachelors,19,37,72,59,18,6.0,2,19,Rural,Software Engineer,81190,0 +12940,Male,55,High School,1,15,94,68,68,5.0,7,43,Rural,HR Executive,144352,0 +12941,Male,46,Diploma,17,73,97,9,14,4.0,3,56,Semi-Urban,Manager,108762,1 +12942,Female,34,High School,1,78,49,62,30,3.0,5,11,Semi-Urban,Manager,51402,0 +12943,Male,43,Masters,4,4,8,82,20,9.0,4,49,Urban,Software Engineer,127145,0 +12944,Female,53,Masters,0,15,1,88,18,9.0,1,91,Urban,HR Executive,136272,0 +12945,Male,33,Bachelors,11,22,76,48,69,3.0,2,93,Urban,Software Engineer,76676,1 +12946,Male,45,Bachelors,16,52,38,97,53,8.0,6,81,Urban,ML Engineer,114792,1 +12947,Male,38,Diploma,13,13,86,91,39,5.0,2,65,Urban,ML Engineer,53135,1 +12948,Male,41,Diploma,17,12,34,95,82,1.0,6,39,Semi-Urban,Manager,39172,0 +12949,Female,58,Bachelors,19,98,5,99,37,6.0,5,17,Semi-Urban,Manager,95798,0 +12950,Male,45,PhD,18,12,90,14,19,2.0,6,86,Semi-Urban,HR Executive,136680,0 +12951,Male,32,Bachelors,16,69,54,35,45,6.0,2,54,Rural,Manager,39971,0 +12952,Female,51,Bachelors,14,98,19,83,54,1.0,4,33,Urban,Data Analyst,120537,0 +12953,Female,32,Bachelors,16,40,60,76,36,1.0,1,40,Urban,ML Engineer,89292,0 +12954,Male,51,Bachelors,18,1,64,64,74,0.0,3,86,Urban,ML Engineer,146878,0 +12955,Male,23,High School,8,83,56,16,50,1.0,5,15,Urban,HR Executive,23822,0 +12956,Female,54,Bachelors,2,47,2,94,80,3.0,7,83,Urban,HR Executive,142843,0 +12957,Other,47,Masters,7,78,2,19,55,8.0,2,34,Urban,Manager,57972,0 +12958,Female,41,Masters,3,82,3,83,1,9.0,5,38,Urban,HR Executive,123379,0 +12959,Male,41,Bachelors,19,35,4,38,35,6.0,1,25,Semi-Urban,ML Engineer,124940,0 +12960,Other,21,Bachelors,14,15,71,19,15,0.0,0,92,Urban,HR Executive,23512,0 +12961,Male,49,Bachelors,6,31,38,29,4,9.0,4,83,Semi-Urban,ML Engineer,64744,0 +12962,Male,35,Bachelors,4,85,48,90,37,3.0,5,41,Urban,Manager,46561,1 +12963,Female,50,Bachelors,15,32,32,15,83,5.0,6,58,Urban,Software Engineer,130114,0 +12964,Male,25,High School,7,76,1,57,95,8.0,1,20,Rural,Software Engineer,36544,0 +12965,Male,43,High School,1,85,72,64,70,8.0,0,99,Semi-Urban,Manager,131611,1 +12966,Male,58,Bachelors,5,14,22,44,8,4.0,5,36,Semi-Urban,Software Engineer,27957,0 +12967,Male,22,Masters,19,54,30,43,99,2.0,3,81,Rural,ML Engineer,77791,0 +12968,Female,24,Bachelors,3,72,57,74,59,8.0,7,43,Urban,ML Engineer,141759,1 +12969,Female,22,Bachelors,7,1,70,69,67,2.0,7,54,Urban,ML Engineer,20294,0 +12970,Male,46,Bachelors,5,44,12,64,4,0.0,4,93,Urban,HR Executive,58776,0 +12971,Male,53,Bachelors,3,4,93,4,9,9.0,5,52,Urban,Manager,124496,0 +12972,Female,48,Bachelors,1,99,15,21,38,4.0,5,97,Urban,Manager,29066,0 +12973,Female,23,Bachelors,12,84,23,21,24,5.0,7,36,Urban,Manager,33858,0 +12974,Male,50,Masters,2,23,61,23,0,0.0,3,41,Rural,Software Engineer,48092,0 +12975,Other,59,High School,16,50,30,93,63,1.0,0,77,Urban,ML Engineer,21923,1 +12976,Female,29,PhD,4,38,97,62,96,8.0,5,11,Urban,ML Engineer,69208,0 +12977,Male,40,PhD,13,64,26,7,54,9.0,4,52,Semi-Urban,Software Engineer,55384,0 +12978,Male,37,High School,4,43,6,57,26,4.0,6,94,Urban,Manager,30332,0 +12979,Male,40,Masters,3,13,37,14,5,5.0,4,3,Urban,Software Engineer,99731,0 +12980,Female,34,PhD,12,10,77,2,60,8.0,2,9,Urban,ML Engineer,89610,0 +12981,Male,34,Masters,9,85,33,31,52,0.0,4,0,Rural,ML Engineer,57083,0 +12982,Male,23,Diploma,5,70,65,32,33,1.0,3,64,Rural,Software Engineer,136531,0 +12983,Male,30,High School,2,68,67,6,12,9.0,6,48,Rural,Data Analyst,59765,0 +12984,Female,23,Diploma,11,81,45,33,83,8.0,5,60,Semi-Urban,Manager,139927,0 +12985,Male,34,High School,0,19,48,39,97,9.0,1,43,Urban,Data Analyst,144057,0 +12986,Female,29,Masters,9,84,50,69,30,9.0,3,13,Semi-Urban,ML Engineer,115743,0 +12987,Female,53,Bachelors,8,30,4,82,97,7.0,0,19,Rural,HR Executive,84918,0 +12988,Male,53,Diploma,1,25,60,74,76,8.0,3,54,Semi-Urban,Software Engineer,108053,0 +12989,Male,36,Masters,18,35,51,45,3,9.0,1,46,Rural,Manager,84095,0 +12990,Male,27,Bachelors,15,29,34,5,61,2.0,3,54,Rural,ML Engineer,88725,0 +12991,Female,40,Masters,16,34,90,81,72,8.0,2,96,Urban,Data Analyst,112042,1 +12992,Male,48,Bachelors,16,41,24,30,67,5.0,7,69,Rural,HR Executive,115180,0 +12993,Male,50,Masters,17,99,8,26,63,9.0,5,26,Urban,Data Analyst,123899,0 +12994,Male,46,Masters,8,75,16,90,20,5.0,7,67,Semi-Urban,Software Engineer,40719,1 +12995,Male,59,High School,3,12,6,75,98,0.0,4,66,Urban,ML Engineer,113224,0 +12996,Female,46,Masters,4,76,54,56,22,2.0,2,63,Urban,HR Executive,116041,1 +12997,Female,59,Diploma,13,56,45,48,8,3.0,7,5,Urban,Data Analyst,20179,0 +12998,Female,30,Diploma,0,44,53,90,12,1.0,6,18,Rural,Manager,120247,0 +12999,Male,58,Bachelors,14,82,37,22,17,6.0,3,6,Urban,Software Engineer,76055,0 +13000,Male,38,Masters,7,99,48,79,10,6.0,3,30,Semi-Urban,HR Executive,52267,1 +13001,Other,48,Bachelors,13,61,7,92,6,5.0,2,18,Urban,Data Analyst,89376,0 +13002,Male,28,Diploma,10,95,6,92,62,4.0,6,95,Urban,HR Executive,101274,1 +13003,Female,24,Masters,13,14,22,57,12,6.0,0,70,Urban,Software Engineer,30500,0 +13004,Male,35,Diploma,18,76,74,63,78,6.0,1,11,Rural,Manager,108378,0 +13005,Male,41,Bachelors,8,87,99,88,16,9.0,3,18,Urban,Software Engineer,85791,1 +13006,Female,35,Bachelors,18,68,77,99,16,0.0,1,35,Semi-Urban,ML Engineer,75651,1 +13007,Other,32,Diploma,7,16,38,53,45,2.0,2,62,Urban,Data Analyst,128299,0 +13008,Other,25,Diploma,10,49,45,98,79,8.0,1,41,Rural,HR Executive,91030,0 +13009,Male,23,High School,16,45,18,60,26,6.0,1,43,Urban,Data Analyst,104995,0 +13010,Male,27,Masters,18,86,49,60,23,9.0,4,11,Urban,Manager,65905,0 +13011,Male,30,Diploma,6,98,24,42,32,5.0,4,45,Urban,ML Engineer,70336,0 +13012,Female,22,Masters,5,94,33,36,51,8.0,4,65,Urban,Data Analyst,92729,0 +13013,Female,31,Bachelors,10,41,45,77,19,9.0,4,77,Urban,Software Engineer,122692,0 +13014,Male,54,Bachelors,7,98,26,79,68,8.0,0,33,Urban,Software Engineer,118752,1 +13015,Other,41,Diploma,8,85,60,14,36,4.0,4,1,Urban,HR Executive,136256,0 +13016,Female,23,Bachelors,14,39,16,32,89,7.0,1,8,Urban,Software Engineer,34287,0 +13017,Female,43,Bachelors,1,6,2,49,29,1.0,5,31,Urban,Software Engineer,91000,0 +13018,Male,32,Diploma,16,30,1,34,32,2.0,7,42,Urban,HR Executive,111454,0 +13019,Male,53,Bachelors,5,52,84,15,86,2.0,0,63,Rural,Software Engineer,66630,0 +13020,Other,24,Bachelors,0,43,78,43,31,5.0,4,41,Urban,Data Analyst,112213,0 +13021,Male,26,Bachelors,8,88,47,51,77,1.0,5,67,Urban,Manager,141739,1 +13022,Female,42,High School,1,84,14,16,66,1.0,4,67,Rural,Manager,54363,0 +13023,Other,29,High School,15,57,1,94,68,8.0,2,35,Urban,HR Executive,45752,0 +13024,Female,52,Bachelors,10,17,66,36,29,1.0,1,97,Urban,Manager,116319,0 +13025,Male,21,Bachelors,9,82,9,84,89,2.0,6,12,Semi-Urban,Manager,97848,0 +13026,Male,58,Masters,3,53,36,76,91,3.0,6,47,Urban,Manager,136152,0 +13027,Male,56,PhD,4,45,23,28,94,3.0,6,93,Semi-Urban,ML Engineer,123877,0 +13028,Male,25,Bachelors,12,44,75,79,23,1.0,5,54,Rural,Data Analyst,77617,1 +13029,Male,55,Masters,3,31,11,4,42,7.0,0,22,Urban,Data Analyst,127800,0 +13030,Male,40,Masters,1,57,72,49,4,2.0,3,49,Urban,HR Executive,54000,0 +13031,Male,50,Bachelors,7,71,97,3,51,1.0,5,60,Urban,ML Engineer,137337,0 +13032,Male,21,Bachelors,5,56,98,29,20,2.0,0,70,Urban,Software Engineer,122911,1 +13033,Male,56,Bachelors,2,80,50,17,56,1.0,7,53,Urban,ML Engineer,46885,0 +13034,Male,47,Diploma,6,56,39,12,25,9.0,1,15,Semi-Urban,Software Engineer,54215,0 +13035,Male,35,Masters,10,78,6,62,59,2.0,1,81,Rural,Manager,107032,0 +13036,Female,22,Masters,19,15,14,16,12,9.0,0,85,Urban,HR Executive,97118,0 +13037,Male,29,Bachelors,13,15,70,55,88,8.0,0,47,Urban,Software Engineer,117924,0 +13038,Male,52,Bachelors,19,4,11,35,3,6.0,3,60,Urban,Data Analyst,134727,0 +13039,Female,25,Diploma,5,35,19,9,61,3.0,6,90,Semi-Urban,Manager,117677,0 +13040,Female,55,High School,0,87,7,50,10,0.0,4,11,Urban,Software Engineer,137443,0 +13041,Male,29,Bachelors,1,78,49,15,8,8.0,5,0,Urban,HR Executive,39345,0 +13042,Female,28,Bachelors,11,61,43,41,45,5.0,3,39,Urban,Software Engineer,127945,0 +13043,Other,23,Masters,10,12,78,60,93,4.0,3,58,Urban,HR Executive,147599,0 +13044,Female,23,Bachelors,10,70,26,34,44,0.0,2,18,Rural,Data Analyst,31990,0 +13045,Male,23,Bachelors,1,74,17,96,15,2.0,0,21,Urban,HR Executive,110245,0 +13046,Female,53,Bachelors,6,41,84,7,10,0.0,0,23,Urban,ML Engineer,137832,0 +13047,Male,39,High School,11,78,73,3,38,4.0,2,58,Rural,ML Engineer,81637,0 +13048,Male,52,Bachelors,9,58,82,98,55,7.0,3,55,Rural,Manager,147170,1 +13049,Other,50,Bachelors,13,11,5,37,10,7.0,4,56,Semi-Urban,ML Engineer,62855,0 +13050,Male,35,Masters,15,68,14,64,68,4.0,3,16,Rural,Data Analyst,128526,0 +13051,Female,50,Bachelors,12,70,3,99,99,8.0,0,69,Semi-Urban,ML Engineer,146997,1 +13052,Male,28,High School,3,77,64,25,8,9.0,7,97,Urban,ML Engineer,133399,1 +13053,Other,24,Bachelors,12,60,29,74,18,2.0,3,20,Rural,HR Executive,109369,0 +13054,Male,23,Diploma,10,66,89,64,70,5.0,3,24,Urban,HR Executive,114973,1 +13055,Male,49,Diploma,2,90,73,66,77,3.0,4,38,Rural,HR Executive,53966,1 +13056,Male,42,High School,14,38,87,50,14,0.0,7,6,Rural,Manager,126466,0 +13057,Male,44,Diploma,18,26,89,93,29,8.0,5,95,Urban,ML Engineer,47137,1 +13058,Male,27,Masters,1,73,74,88,40,7.0,3,26,Urban,Software Engineer,40821,1 +13059,Female,32,Bachelors,17,14,70,91,49,6.0,5,29,Urban,Data Analyst,88962,0 +13060,Male,56,Bachelors,6,67,94,7,75,4.0,5,0,Rural,Manager,132250,0 +13061,Female,23,PhD,0,95,18,72,55,3.0,2,85,Rural,Manager,91935,1 +13062,Male,33,PhD,15,99,4,82,29,9.0,4,7,Urban,Manager,60937,0 +13063,Male,52,Diploma,4,37,56,53,32,8.0,2,88,Urban,Software Engineer,52302,0 +13064,Other,29,Masters,4,77,31,97,95,3.0,0,48,Rural,Software Engineer,43087,1 +13065,Male,50,Diploma,15,26,79,36,13,6.0,6,89,Urban,Manager,63905,0 +13066,Female,51,Masters,4,29,38,42,38,8.0,2,6,Semi-Urban,ML Engineer,51440,0 +13067,Female,26,Bachelors,10,43,84,69,7,2.0,0,19,Rural,Manager,106133,0 +13068,Male,32,Diploma,0,27,42,17,13,9.0,5,28,Rural,Manager,31836,0 +13069,Female,43,High School,16,3,19,15,29,5.0,7,26,Rural,Software Engineer,45785,0 +13070,Female,36,High School,7,28,19,98,73,2.0,6,93,Semi-Urban,Manager,28848,0 +13071,Male,36,Masters,9,9,93,6,17,3.0,6,24,Semi-Urban,Manager,44527,0 +13072,Female,41,High School,15,8,82,77,95,5.0,0,84,Rural,Software Engineer,52333,1 +13073,Male,56,Bachelors,6,26,25,23,40,7.0,3,87,Urban,HR Executive,88742,0 +13074,Male,34,Diploma,11,10,65,89,66,8.0,2,65,Rural,Manager,106038,0 +13075,Other,26,Diploma,17,79,10,13,91,4.0,0,32,Urban,Software Engineer,80034,0 +13076,Female,28,Bachelors,0,33,23,26,92,9.0,1,65,Semi-Urban,Data Analyst,22655,0 +13077,Female,21,Diploma,18,19,7,17,6,1.0,0,28,Rural,ML Engineer,40498,0 +13078,Female,40,Masters,16,88,97,63,60,1.0,0,98,Semi-Urban,Manager,142038,1 +13079,Female,46,Masters,2,64,89,16,36,2.0,0,39,Urban,HR Executive,90018,0 +13080,Female,28,High School,11,41,91,71,41,6.0,0,79,Urban,ML Engineer,131019,1 +13081,Male,26,Diploma,14,10,4,99,30,8.0,1,42,Rural,Software Engineer,90913,0 +13082,Male,26,High School,5,97,96,76,66,5.0,5,38,Rural,HR Executive,36529,1 +13083,Male,47,Bachelors,14,71,2,15,93,1.0,5,32,Semi-Urban,HR Executive,119558,0 +13084,Female,37,High School,6,42,41,2,33,9.0,3,26,Semi-Urban,HR Executive,111380,0 +13085,Male,49,Masters,1,35,87,43,93,1.0,1,3,Semi-Urban,Software Engineer,127099,0 +13086,Male,41,Masters,4,11,88,77,16,8.0,3,59,Semi-Urban,HR Executive,121438,1 +13087,Male,24,Masters,10,57,40,44,62,4.0,5,5,Urban,Software Engineer,36057,0 +13088,Other,22,PhD,18,62,70,36,33,8.0,4,77,Rural,Manager,107791,1 +13089,Female,57,Bachelors,15,70,66,4,57,9.0,2,7,Urban,ML Engineer,115840,0 +13090,Male,40,Bachelors,10,45,4,45,59,2.0,1,32,Rural,Manager,76513,0 +13091,Male,21,Masters,5,71,83,13,35,5.0,0,67,Rural,HR Executive,57052,0 +13092,Male,29,Diploma,17,41,19,84,43,2.0,1,73,Urban,Software Engineer,50953,0 +13093,Male,51,Bachelors,1,60,74,68,0,7.0,0,71,Rural,HR Executive,83598,1 +13094,Male,24,Diploma,9,94,35,68,5,0.0,0,37,Urban,Software Engineer,116888,0 +13095,Female,24,Bachelors,3,36,33,37,60,6.0,0,36,Urban,HR Executive,101464,0 +13096,Other,27,Diploma,15,8,19,71,12,5.0,7,29,Rural,HR Executive,149131,0 +13097,Male,59,Bachelors,9,94,30,34,73,9.0,1,26,Semi-Urban,Software Engineer,107560,0 +13098,Male,44,Diploma,13,85,15,73,58,9.0,7,52,Urban,HR Executive,128905,0 +13099,Male,35,Bachelors,7,98,85,20,70,8.0,3,75,Urban,ML Engineer,23444,1 +13100,Male,37,Bachelors,2,85,99,46,64,2.0,5,67,Urban,Data Analyst,70268,1 +13101,Male,54,Diploma,6,75,88,77,20,2.0,3,60,Urban,Software Engineer,37655,1 +13102,Male,51,Diploma,0,20,52,89,20,5.0,6,31,Urban,Manager,79997,0 +13103,Male,29,Bachelors,0,62,46,21,71,1.0,0,38,Urban,Software Engineer,49563,0 +13104,Female,48,Diploma,6,51,56,71,19,1.0,7,64,Rural,Manager,125744,1 +13105,Female,25,Bachelors,11,12,26,33,40,1.0,7,75,Semi-Urban,HR Executive,39152,0 +13106,Female,59,Bachelors,0,85,46,0,36,1.0,4,54,Urban,Software Engineer,26283,0 +13107,Male,53,High School,4,30,92,2,25,5.0,1,71,Urban,HR Executive,43248,0 +13108,Female,51,Bachelors,8,24,58,75,7,0.0,3,23,Urban,ML Engineer,89704,0 +13109,Other,23,Bachelors,10,13,65,90,17,5.0,4,61,Urban,Manager,119006,0 +13110,Male,23,Diploma,9,83,39,4,93,6.0,4,55,Urban,ML Engineer,33857,0 +13111,Male,58,PhD,4,71,17,77,80,9.0,7,37,Semi-Urban,Data Analyst,27129,0 +13112,Male,21,Masters,19,70,68,38,42,5.0,5,83,Urban,Software Engineer,37871,1 +13113,Male,33,High School,3,61,35,48,52,1.0,3,76,Rural,Data Analyst,114537,0 +13114,Male,29,Bachelors,14,7,97,57,44,6.0,2,70,Urban,Software Engineer,46716,0 +13115,Male,25,High School,4,67,98,90,32,6.0,1,73,Semi-Urban,Manager,36473,1 +13116,Male,27,High School,12,7,80,19,50,0.0,0,24,Rural,Data Analyst,126521,0 +13117,Male,27,Diploma,17,12,15,25,93,4.0,5,45,Semi-Urban,ML Engineer,145050,0 +13118,Male,22,Bachelors,12,54,60,3,54,3.0,2,54,Urban,HR Executive,20375,0 +13119,Other,21,Bachelors,14,86,38,78,46,2.0,5,47,Urban,Software Engineer,24990,1 +13120,Male,22,Diploma,16,57,98,7,70,5.0,1,67,Urban,HR Executive,29152,0 +13121,Female,59,Bachelors,0,98,70,41,59,1.0,2,65,Semi-Urban,HR Executive,133746,1 +13122,Male,50,Bachelors,13,44,72,98,77,2.0,6,89,Urban,Manager,138709,1 +13123,Male,45,Bachelors,1,56,34,93,95,8.0,3,33,Urban,ML Engineer,53014,0 +13124,Male,37,Bachelors,17,33,46,47,26,6.0,3,49,Urban,Data Analyst,98228,0 +13125,Male,57,Diploma,14,43,61,36,0,1.0,7,76,Semi-Urban,Data Analyst,39843,0 +13126,Male,25,Bachelors,4,20,79,72,54,8.0,0,98,Semi-Urban,HR Executive,143756,1 +13127,Male,25,PhD,9,82,0,9,54,8.0,7,74,Semi-Urban,Software Engineer,69964,0 +13128,Male,59,Diploma,0,46,48,19,45,0.0,5,9,Semi-Urban,Software Engineer,43997,0 +13129,Female,43,PhD,8,20,53,98,27,9.0,3,57,Urban,HR Executive,138819,0 +13130,Male,37,High School,7,48,34,65,48,9.0,1,50,Urban,Data Analyst,93905,0 +13131,Female,37,Diploma,12,42,38,16,36,2.0,3,77,Semi-Urban,ML Engineer,67068,0 +13132,Male,25,High School,6,9,54,23,2,0.0,5,14,Semi-Urban,Software Engineer,39009,0 +13133,Female,47,Diploma,8,61,6,83,77,8.0,7,21,Urban,Manager,122811,0 +13134,Male,59,Bachelors,14,1,5,25,94,8.0,7,19,Semi-Urban,HR Executive,84800,0 +13135,Female,36,Masters,4,82,84,70,97,8.0,4,69,Urban,Manager,28610,1 +13136,Other,22,Bachelors,13,84,83,59,81,3.0,7,57,Urban,Manager,54312,1 +13137,Female,59,High School,17,25,99,71,5,1.0,5,32,Urban,HR Executive,128465,0 +13138,Male,25,PhD,19,78,10,57,53,3.0,6,20,Semi-Urban,ML Engineer,20056,0 +13139,Female,31,Masters,3,88,50,1,88,3.0,4,7,Urban,ML Engineer,41677,0 +13140,Male,22,High School,4,45,37,81,44,5.0,0,20,Urban,Software Engineer,111181,0 +13141,Other,51,Bachelors,8,80,3,39,85,4.0,0,85,Urban,Software Engineer,111806,0 +13142,Male,21,Bachelors,7,90,71,84,74,7.0,1,31,Urban,Software Engineer,106211,1 +13143,Male,36,Bachelors,14,54,9,75,14,5.0,1,22,Urban,Software Engineer,43360,0 +13144,Male,53,High School,16,9,32,71,44,9.0,3,64,Rural,Software Engineer,128221,0 +13145,Male,38,Diploma,19,15,64,16,3,3.0,0,84,Urban,HR Executive,134851,0 +13146,Female,48,Diploma,7,92,63,70,83,1.0,3,12,Rural,ML Engineer,144885,0 +13147,Female,54,Diploma,19,37,31,31,32,3.0,6,40,Urban,ML Engineer,28191,0 +13148,Female,43,High School,10,69,15,28,38,3.0,5,26,Rural,ML Engineer,44793,0 +13149,Female,53,Diploma,16,6,98,7,69,9.0,7,27,Semi-Urban,HR Executive,86106,0 +13150,Female,31,High School,14,6,8,90,42,5.0,5,36,Urban,ML Engineer,96660,0 +13151,Male,54,High School,6,44,35,95,28,1.0,4,81,Urban,HR Executive,68721,1 +13152,Male,24,High School,5,62,58,92,86,9.0,7,9,Semi-Urban,Software Engineer,113940,0 +13153,Male,35,High School,9,31,56,56,70,4.0,6,26,Rural,Data Analyst,28744,0 +13154,Male,39,Bachelors,12,73,78,83,23,4.0,1,34,Semi-Urban,Data Analyst,147124,1 +13155,Male,48,PhD,17,78,74,3,58,3.0,0,26,Rural,Software Engineer,26864,0 +13156,Male,48,Diploma,15,9,9,58,2,2.0,3,22,Rural,ML Engineer,143557,0 +13157,Male,31,Bachelors,8,41,61,5,10,3.0,0,84,Semi-Urban,Software Engineer,106833,0 +13158,Male,27,Bachelors,11,70,46,74,5,0.0,4,65,Urban,Manager,63991,1 +13159,Female,57,High School,14,78,82,82,67,1.0,7,90,Urban,HR Executive,127154,1 +13160,Male,38,High School,5,45,86,32,96,7.0,4,17,Semi-Urban,Manager,35046,0 +13161,Male,35,Diploma,19,25,0,67,36,9.0,1,12,Urban,HR Executive,104723,0 +13162,Male,38,High School,7,72,10,98,85,8.0,0,15,Urban,ML Engineer,65108,0 +13163,Male,30,Masters,7,97,60,85,25,9.0,5,68,Semi-Urban,ML Engineer,57922,1 +13164,Male,48,Diploma,18,48,93,16,3,3.0,1,4,Rural,Data Analyst,61963,0 +13165,Male,32,High School,1,46,42,54,69,3.0,4,36,Urban,ML Engineer,129928,0 +13166,Male,36,Diploma,6,42,2,90,58,4.0,4,39,Rural,Manager,78599,0 +13167,Male,50,High School,16,83,68,92,59,7.0,5,72,Semi-Urban,Manager,106121,1 +13168,Male,55,Bachelors,18,87,81,18,97,7.0,6,26,Semi-Urban,ML Engineer,98011,0 +13169,Male,23,Diploma,6,7,86,7,15,9.0,6,43,Semi-Urban,Data Analyst,120611,0 +13170,Female,38,Diploma,1,69,68,0,75,7.0,4,35,Urban,Data Analyst,82951,0 +13171,Male,31,High School,19,17,10,17,53,5.0,7,47,Semi-Urban,Data Analyst,53963,0 +13172,Male,56,Masters,18,30,31,20,52,6.0,1,79,Urban,HR Executive,22865,0 +13173,Male,23,Bachelors,18,44,56,60,74,6.0,7,92,Urban,Manager,31778,1 +13174,Female,28,Bachelors,12,28,23,39,44,8.0,2,73,Semi-Urban,Manager,75437,0 +13175,Male,22,Bachelors,13,76,97,89,46,4.0,1,55,Urban,HR Executive,70906,1 +13176,Female,37,Bachelors,14,27,50,66,75,0.0,4,40,Rural,Software Engineer,137018,0 +13177,Female,21,Diploma,13,3,72,75,10,8.0,3,44,Semi-Urban,Software Engineer,105449,0 +13178,Male,35,High School,19,60,8,29,8,6.0,2,41,Semi-Urban,Software Engineer,134507,0 +13179,Male,30,Masters,16,80,48,57,90,4.0,4,99,Urban,ML Engineer,98163,1 +13180,Male,37,Bachelors,6,12,15,17,2,3.0,3,86,Urban,ML Engineer,49083,0 +13181,Male,23,Diploma,10,95,54,62,48,0.0,6,11,Urban,Software Engineer,125313,0 +13182,Male,48,Diploma,15,42,81,67,81,6.0,3,5,Urban,HR Executive,32374,0 +13183,Male,37,Masters,17,27,20,0,96,0.0,3,39,Urban,ML Engineer,77090,0 +13184,Male,54,Diploma,2,41,48,74,74,1.0,2,47,Rural,HR Executive,65567,0 +13185,Male,24,Bachelors,16,5,51,96,93,9.0,4,36,Rural,ML Engineer,87949,0 +13186,Female,39,Diploma,7,48,99,8,33,5.0,5,26,Rural,Data Analyst,112655,0 +13187,Male,35,Bachelors,17,56,62,59,45,2.0,2,4,Semi-Urban,Software Engineer,44092,0 +13188,Female,45,Diploma,1,11,5,76,51,8.0,4,5,Urban,Manager,50187,0 +13189,Other,36,Masters,6,52,76,62,7,9.0,5,51,Semi-Urban,Software Engineer,53156,1 +13190,Other,50,Masters,13,63,34,79,3,7.0,5,22,Urban,Data Analyst,140051,0 +13191,Female,55,High School,2,12,2,70,7,8.0,1,23,Urban,Manager,36984,0 +13192,Male,43,Masters,14,42,84,82,51,8.0,5,94,Semi-Urban,Data Analyst,73646,1 +13193,Male,34,Bachelors,4,51,43,97,99,9.0,0,58,Urban,Data Analyst,148205,1 +13194,Male,33,Bachelors,7,97,20,37,48,7.0,3,79,Urban,ML Engineer,84939,0 +13195,Male,49,High School,14,65,73,15,53,0.0,3,34,Urban,Software Engineer,85440,0 +13196,Female,44,Bachelors,18,58,92,40,29,3.0,3,95,Urban,Manager,146891,1 +13197,Other,45,High School,10,28,79,89,53,5.0,2,13,Urban,Software Engineer,130097,0 +13198,Male,38,Masters,0,67,72,49,14,8.0,4,25,Semi-Urban,Data Analyst,147486,0 +13199,Male,24,Diploma,18,71,97,21,19,6.0,7,2,Urban,HR Executive,68127,0 +13200,Male,50,Diploma,1,7,4,31,45,0.0,0,8,Semi-Urban,Manager,69010,0 +13201,Male,32,Diploma,19,77,9,56,31,7.0,7,94,Urban,HR Executive,127011,1 +13202,Male,48,Diploma,0,70,66,49,0,0.0,0,86,Semi-Urban,ML Engineer,47031,1 +13203,Male,41,PhD,11,26,45,85,46,9.0,1,88,Rural,Data Analyst,70959,1 +13204,Female,46,Bachelors,4,34,68,78,50,8.0,1,26,Rural,HR Executive,75816,0 +13205,Male,42,Masters,12,22,91,59,68,4.0,6,4,Semi-Urban,Software Engineer,62510,0 +13206,Female,38,Bachelors,17,74,67,72,22,5.0,4,76,Semi-Urban,Manager,141039,1 +13207,Female,50,Bachelors,1,23,30,25,34,5.0,0,63,Semi-Urban,Data Analyst,20089,0 +13208,Female,29,Bachelors,13,77,85,84,46,3.0,6,8,Urban,Manager,74880,1 +13209,Male,41,Diploma,17,70,67,10,63,3.0,2,19,Urban,Manager,140544,0 +13210,Female,49,High School,10,1,87,11,81,3.0,4,15,Urban,Data Analyst,89953,0 +13211,Female,57,High School,18,97,87,65,72,7.0,5,81,Rural,Manager,49478,1 +13212,Male,54,Diploma,0,34,88,81,4,3.0,5,17,Rural,HR Executive,137652,0 +13213,Male,55,Bachelors,19,25,32,58,24,0.0,6,7,Semi-Urban,HR Executive,137140,0 +13214,Female,40,Masters,7,17,29,96,79,8.0,0,6,Urban,HR Executive,33812,0 +13215,Male,21,Bachelors,19,69,13,3,53,9.0,7,15,Semi-Urban,Software Engineer,46943,0 +13216,Male,52,High School,3,27,84,36,17,9.0,3,93,Urban,Software Engineer,116943,1 +13217,Male,37,Diploma,3,59,13,38,58,9.0,0,36,Rural,ML Engineer,92140,0 +13218,Female,41,Bachelors,5,46,70,61,18,6.0,5,21,Urban,Software Engineer,72370,0 +13219,Female,46,PhD,14,96,56,62,60,8.0,2,3,Urban,HR Executive,52922,0 +13220,Male,53,Bachelors,12,31,3,11,17,6.0,0,10,Urban,Software Engineer,20750,0 +13221,Male,57,Masters,13,73,17,30,61,2.0,7,88,Rural,Data Analyst,31802,0 +13222,Other,48,High School,0,78,13,46,57,7.0,6,26,Urban,Manager,127804,0 +13223,Female,48,High School,7,54,87,8,9,3.0,7,5,Urban,Data Analyst,29011,0 +13224,Female,34,High School,10,74,15,85,95,5.0,5,4,Semi-Urban,Manager,123304,0 +13225,Male,53,Bachelors,9,48,73,84,40,0.0,2,17,Urban,Software Engineer,40823,0 +13226,Male,47,Masters,4,63,94,11,27,9.0,4,29,Urban,ML Engineer,61223,0 +13227,Male,52,Masters,9,84,52,85,90,8.0,3,44,Urban,HR Executive,26377,1 +13228,Female,40,Diploma,1,16,59,46,90,1.0,6,79,Urban,Software Engineer,101026,0 +13229,Male,32,Bachelors,11,65,45,82,61,3.0,5,71,Urban,HR Executive,90376,1 +13230,Male,25,Diploma,11,87,14,23,80,7.0,6,6,Semi-Urban,Data Analyst,98497,0 +13231,Male,50,Bachelors,19,58,50,82,69,4.0,0,52,Urban,Manager,79693,1 +13232,Male,59,Masters,12,84,49,17,58,8.0,7,77,Rural,Data Analyst,20785,0 +13233,Female,47,Bachelors,6,43,3,60,13,3.0,2,28,Urban,Data Analyst,136047,0 +13234,Male,42,Diploma,17,58,51,59,49,7.0,7,95,Urban,HR Executive,63853,1 +13235,Female,29,Diploma,4,49,58,43,68,7.0,4,68,Urban,Software Engineer,23986,0 +13236,Female,50,High School,12,57,77,60,32,1.0,2,30,Urban,Manager,57783,0 +13237,Male,50,Bachelors,1,44,96,11,4,6.0,0,66,Semi-Urban,Manager,67931,0 +13238,Female,51,Masters,6,6,87,22,62,2.0,4,13,Urban,HR Executive,29741,0 +13239,Other,26,High School,8,87,81,76,73,4.0,5,13,Urban,Software Engineer,86146,1 +13240,Other,56,Diploma,0,73,68,78,69,7.0,6,46,Urban,ML Engineer,34382,1 +13241,Male,23,Masters,10,71,56,52,40,7.0,1,31,Rural,Software Engineer,132742,0 +13242,Male,33,Bachelors,6,70,37,88,34,9.0,4,34,Urban,Software Engineer,99961,0 +13243,Male,29,PhD,4,95,21,69,37,6.0,1,44,Urban,Software Engineer,101467,0 +13244,Female,26,Masters,11,68,97,28,73,7.0,1,6,Rural,HR Executive,89526,0 +13245,Female,52,Bachelors,13,16,48,28,94,7.0,4,84,Urban,ML Engineer,123759,0 +13246,Female,51,High School,9,18,44,95,53,0.0,1,42,Semi-Urban,Software Engineer,125715,0 +13247,Male,42,Bachelors,16,54,4,31,52,8.0,5,86,Rural,Manager,117796,0 +13248,Male,51,High School,16,98,60,77,46,3.0,2,35,Urban,Manager,126807,1 +13249,Male,45,Bachelors,6,88,85,81,2,6.0,4,78,Semi-Urban,Data Analyst,36937,1 +13250,Male,51,Bachelors,16,78,88,9,49,6.0,5,66,Rural,Data Analyst,29734,1 +13251,Female,38,Bachelors,17,7,79,36,15,5.0,7,29,Rural,Data Analyst,56772,0 +13252,Male,55,Masters,16,81,70,51,10,1.0,5,85,Urban,Software Engineer,107085,1 +13253,Male,41,Masters,11,99,7,72,8,8.0,2,37,Rural,Manager,142253,0 +13254,Male,52,High School,16,11,29,96,56,7.0,2,89,Rural,HR Executive,96652,0 +13255,Male,22,Bachelors,7,16,0,5,30,6.0,7,23,Urban,Data Analyst,121841,0 +13256,Male,42,Masters,3,53,36,28,3,9.0,2,94,Urban,Manager,64525,0 +13257,Male,50,Diploma,10,22,49,15,73,5.0,0,85,Semi-Urban,Software Engineer,118148,0 +13258,Male,37,Bachelors,12,53,94,41,35,2.0,6,17,Semi-Urban,Data Analyst,29018,0 +13259,Male,36,PhD,8,77,61,48,47,5.0,7,0,Rural,Software Engineer,55594,0 +13260,Male,51,Bachelors,18,1,44,58,81,5.0,0,72,Semi-Urban,Data Analyst,38786,0 +13261,Female,57,Diploma,4,42,6,45,86,5.0,4,58,Rural,HR Executive,57732,0 +13262,Male,30,Bachelors,14,73,52,81,90,3.0,3,65,Urban,HR Executive,140421,1 +13263,Female,39,High School,7,73,56,90,51,1.0,1,4,Urban,Data Analyst,83413,0 +13264,Female,23,Diploma,4,13,96,20,45,3.0,5,90,Semi-Urban,Manager,105572,0 +13265,Male,32,PhD,7,54,84,92,75,4.0,3,49,Rural,Software Engineer,44978,1 +13266,Other,54,Diploma,18,53,41,92,77,3.0,3,23,Rural,Manager,40164,0 +13267,Male,39,Bachelors,15,5,74,29,24,0.0,2,82,Urban,Manager,67258,0 +13268,Female,47,Masters,0,63,90,77,34,5.0,7,73,Urban,Manager,56548,1 +13269,Other,43,Bachelors,8,29,85,58,40,8.0,5,54,Semi-Urban,Data Analyst,135455,0 +13270,Female,22,Bachelors,17,84,84,9,94,7.0,3,53,Rural,Software Engineer,138373,0 +13271,Male,52,Bachelors,6,81,47,24,23,2.0,1,96,Semi-Urban,Data Analyst,92254,1 +13272,Male,21,Bachelors,13,85,16,10,8,5.0,1,75,Urban,ML Engineer,142553,0 +13273,Male,55,Masters,0,72,27,48,67,3.0,2,21,Rural,ML Engineer,98513,0 +13274,Female,49,Bachelors,9,70,35,47,52,8.0,1,20,Rural,Data Analyst,118296,0 +13275,Female,25,Bachelors,0,30,67,22,77,5.0,0,64,Urban,ML Engineer,136489,0 +13276,Male,27,Bachelors,14,59,3,50,38,5.0,2,17,Urban,Software Engineer,65980,0 +13277,Male,40,Bachelors,0,2,12,55,65,8.0,1,58,Urban,ML Engineer,49520,0 +13278,Female,21,Bachelors,2,18,44,86,88,8.0,3,55,Urban,Manager,61486,0 +13279,Male,22,Bachelors,13,67,82,84,4,4.0,1,95,Urban,HR Executive,29254,1 +13280,Female,27,High School,12,83,63,17,81,7.0,6,10,Semi-Urban,Data Analyst,72824,0 +13281,Female,37,Masters,14,27,18,21,11,1.0,4,1,Urban,Software Engineer,34858,0 +13282,Male,52,Bachelors,8,69,27,93,71,1.0,7,41,Urban,HR Executive,66182,0 +13283,Female,32,Bachelors,11,47,65,44,69,8.0,1,97,Urban,Data Analyst,71455,1 +13284,Male,39,Masters,7,90,50,84,68,2.0,2,71,Rural,Data Analyst,110131,1 +13285,Male,57,PhD,2,15,56,18,27,7.0,2,42,Semi-Urban,Data Analyst,34637,0 +13286,Other,30,Bachelors,1,91,5,93,5,7.0,2,38,Semi-Urban,Software Engineer,46245,0 +13287,Female,51,Masters,11,48,18,13,44,6.0,7,33,Semi-Urban,ML Engineer,80295,0 +13288,Male,27,Bachelors,10,69,36,57,18,6.0,5,97,Urban,Data Analyst,89142,1 +13289,Male,26,Masters,12,39,64,80,77,7.0,0,5,Urban,Manager,117410,0 +13290,Male,59,Bachelors,1,98,99,24,98,7.0,6,20,Semi-Urban,HR Executive,83373,1 +13291,Male,28,Diploma,2,99,43,67,26,9.0,4,72,Urban,Manager,96317,1 +13292,Male,35,Masters,9,96,86,40,71,6.0,5,53,Urban,HR Executive,58626,1 +13293,Male,23,Diploma,15,47,71,16,94,5.0,5,11,Urban,HR Executive,80712,0 +13294,Male,47,Masters,2,59,45,71,10,5.0,2,9,Urban,Software Engineer,38956,0 +13295,Male,53,Diploma,18,60,87,90,24,9.0,6,42,Semi-Urban,Manager,141286,1 +13296,Male,49,Bachelors,16,80,55,0,38,3.0,4,81,Rural,Software Engineer,63359,0 +13297,Other,43,Diploma,5,73,16,96,65,5.0,4,90,Urban,Software Engineer,49855,1 +13298,Female,56,Diploma,19,56,30,7,90,6.0,7,4,Urban,Data Analyst,88855,0 +13299,Male,55,Diploma,5,54,38,56,71,6.0,6,65,Semi-Urban,HR Executive,138012,0 +13300,Male,59,Diploma,15,97,57,38,42,9.0,7,94,Rural,ML Engineer,112104,1 +13301,Male,48,PhD,5,18,0,66,44,4.0,1,89,Urban,Manager,50387,0 +13302,Male,44,High School,4,48,93,5,44,5.0,2,12,Semi-Urban,HR Executive,106851,0 +13303,Male,36,PhD,2,27,34,76,48,7.0,7,3,Urban,ML Engineer,137669,0 +13304,Female,55,High School,19,25,53,0,33,6.0,6,16,Rural,Data Analyst,60785,0 +13305,Female,22,Masters,2,47,14,32,27,8.0,5,20,Urban,ML Engineer,63509,0 +13306,Female,53,Masters,13,68,44,67,57,6.0,3,28,Urban,HR Executive,33362,0 +13307,Male,40,High School,3,14,88,41,15,2.0,7,39,Urban,HR Executive,121405,0 +13308,Female,57,Bachelors,6,5,31,95,91,0.0,6,85,Urban,Manager,149469,0 +13309,Female,26,Diploma,3,92,16,85,62,2.0,0,76,Semi-Urban,ML Engineer,139812,1 +13310,Male,23,Bachelors,2,16,35,36,78,0.0,7,78,Urban,Data Analyst,116479,0 +13311,Male,46,Diploma,8,46,77,80,18,2.0,0,18,Urban,Manager,84522,0 +13312,Male,52,High School,18,60,9,81,69,0.0,2,48,Rural,Software Engineer,129116,0 +13313,Male,50,Bachelors,1,82,28,43,79,8.0,7,6,Rural,HR Executive,29762,0 +13314,Female,42,Diploma,10,61,26,69,62,8.0,7,99,Urban,Data Analyst,53438,1 +13315,Male,46,Bachelors,4,49,59,89,69,5.0,4,33,Urban,ML Engineer,135007,0 +13316,Male,25,High School,7,31,63,11,74,6.0,6,52,Urban,Manager,28661,0 +13317,Male,44,High School,11,96,50,18,63,4.0,3,24,Semi-Urban,Manager,110124,0 +13318,Male,44,Masters,12,69,60,68,92,5.0,1,8,Semi-Urban,HR Executive,75180,0 +13319,Female,46,High School,1,58,18,32,66,5.0,3,89,Rural,HR Executive,123980,0 +13320,Male,35,Bachelors,1,49,5,95,31,8.0,5,65,Rural,Software Engineer,94090,0 +13321,Female,27,Masters,17,53,52,81,10,3.0,3,48,Urban,Software Engineer,34891,0 +13322,Male,50,Bachelors,0,59,37,12,65,0.0,3,66,Urban,Software Engineer,46976,0 +13323,Male,40,Masters,16,93,78,16,62,6.0,6,32,Urban,Software Engineer,72311,0 +13324,Male,27,Bachelors,14,70,64,46,36,3.0,0,49,Rural,Software Engineer,50258,0 +13325,Female,57,Masters,14,15,32,82,42,6.0,6,71,Urban,Software Engineer,26631,0 +13326,Male,22,Bachelors,5,98,13,43,94,0.0,5,99,Urban,HR Executive,65163,1 +13327,Male,51,Bachelors,8,60,18,1,28,5.0,1,26,Rural,HR Executive,98557,0 +13328,Male,25,Bachelors,16,84,91,23,86,7.0,4,88,Urban,Software Engineer,78334,1 +13329,Male,29,Bachelors,12,68,24,64,4,0.0,3,17,Urban,HR Executive,100561,0 +13330,Other,58,Masters,15,81,4,62,41,4.0,6,50,Urban,HR Executive,57335,0 +13331,Male,44,Diploma,0,73,7,46,30,1.0,6,30,Rural,Manager,120443,0 +13332,Male,24,PhD,13,69,52,29,58,3.0,6,63,Rural,Data Analyst,142418,0 +13333,Male,58,Diploma,10,98,59,71,10,9.0,4,65,Urban,Manager,110349,1 +13334,Female,57,Diploma,13,78,84,14,95,0.0,3,84,Rural,ML Engineer,53633,1 +13335,Male,26,Diploma,9,17,93,16,33,2.0,3,85,Semi-Urban,ML Engineer,99508,0 +13336,Female,42,Diploma,8,94,76,7,11,7.0,6,41,Urban,HR Executive,112031,0 +13337,Female,21,High School,0,9,52,72,46,0.0,4,56,Semi-Urban,Software Engineer,114913,0 +13338,Male,50,PhD,11,4,80,42,2,6.0,1,99,Urban,Software Engineer,20290,0 +13339,Male,28,Bachelors,0,33,53,71,72,2.0,6,76,Semi-Urban,Software Engineer,92682,0 +13340,Male,44,Bachelors,9,70,66,11,88,7.0,6,67,Urban,ML Engineer,53332,0 +13341,Female,47,Masters,18,54,47,2,39,5.0,1,64,Urban,HR Executive,55239,0 +13342,Male,54,Diploma,2,55,55,81,22,2.0,1,64,Urban,Software Engineer,134171,1 +13343,Male,44,Bachelors,11,47,48,81,34,5.0,0,54,Semi-Urban,HR Executive,134395,0 +13344,Female,47,Diploma,3,25,15,28,34,1.0,7,55,Urban,Manager,135319,0 +13345,Male,24,Bachelors,12,68,0,6,70,4.0,4,54,Semi-Urban,HR Executive,25513,0 +13346,Male,43,Bachelors,16,26,84,97,2,5.0,2,20,Semi-Urban,HR Executive,37037,0 +13347,Male,46,Bachelors,17,1,5,37,29,2.0,5,98,Semi-Urban,Software Engineer,110893,0 +13348,Male,52,High School,19,17,54,54,72,1.0,2,48,Urban,HR Executive,92094,0 +13349,Male,56,Masters,3,50,97,30,3,6.0,7,22,Semi-Urban,Software Engineer,116066,0 +13350,Male,59,Bachelors,3,97,61,87,58,0.0,0,54,Urban,Manager,25856,1 +13351,Female,25,Bachelors,11,23,35,89,20,2.0,7,79,Urban,ML Engineer,89345,0 +13352,Male,58,Masters,13,37,3,88,33,5.0,4,37,Urban,ML Engineer,147472,0 +13353,Female,44,Masters,16,3,6,0,28,4.0,0,32,Urban,Manager,57004,0 +13354,Female,50,PhD,7,46,63,1,52,6.0,0,54,Urban,Manager,149440,0 +13355,Male,31,Diploma,11,2,68,24,88,3.0,3,37,Semi-Urban,Software Engineer,38701,0 +13356,Female,50,Bachelors,5,21,36,35,53,7.0,1,27,Semi-Urban,HR Executive,139304,0 +13357,Male,24,Bachelors,1,63,31,64,88,3.0,0,76,Rural,ML Engineer,72897,0 +13358,Other,54,High School,5,23,4,86,89,5.0,4,21,Urban,Manager,121960,0 +13359,Female,21,Bachelors,18,37,83,20,48,2.0,3,60,Urban,Data Analyst,103511,0 +13360,Male,41,Bachelors,10,98,13,50,57,4.0,1,42,Urban,Data Analyst,148476,0 +13361,Male,34,Diploma,19,89,24,67,74,3.0,5,35,Urban,HR Executive,27259,0 +13362,Male,27,Bachelors,11,88,8,31,66,6.0,0,8,Urban,ML Engineer,93474,0 +13363,Male,56,High School,17,94,85,35,67,6.0,2,52,Rural,HR Executive,55604,1 +13364,Male,27,Bachelors,6,41,84,28,21,0.0,4,12,Rural,Data Analyst,79399,0 +13365,Male,54,Bachelors,0,36,29,36,73,6.0,4,61,Urban,Data Analyst,53509,0 +13366,Female,56,Bachelors,7,51,81,82,36,6.0,7,4,Urban,Manager,44704,0 +13367,Male,43,Diploma,10,76,98,93,69,3.0,7,64,Urban,Data Analyst,56193,1 +13368,Female,24,Bachelors,19,12,91,13,70,7.0,3,2,Urban,ML Engineer,118208,0 +13369,Female,44,Masters,7,42,31,69,85,6.0,6,63,Semi-Urban,Software Engineer,115384,0 +13370,Male,37,PhD,19,9,42,26,11,4.0,1,97,Rural,Manager,53022,0 +13371,Female,43,Diploma,0,62,78,32,24,0.0,7,27,Urban,HR Executive,42978,0 +13372,Male,39,Diploma,15,77,57,33,84,1.0,4,64,Urban,ML Engineer,50193,0 +13373,Male,48,Bachelors,6,71,74,88,38,4.0,5,12,Urban,Data Analyst,149431,1 +13374,Female,56,PhD,3,63,89,42,83,9.0,0,2,Urban,Software Engineer,86173,0 +13375,Male,54,Masters,2,51,99,5,30,8.0,1,50,Urban,ML Engineer,108648,0 +13376,Male,43,Bachelors,5,37,48,10,21,3.0,7,55,Rural,ML Engineer,20552,0 +13377,Female,40,Bachelors,2,62,53,95,58,6.0,2,92,Urban,ML Engineer,96392,1 +13378,Other,56,Masters,13,98,94,21,95,7.0,5,69,Urban,HR Executive,142474,1 +13379,Female,22,Bachelors,3,41,75,4,84,3.0,7,30,Urban,ML Engineer,50931,0 +13380,Female,35,High School,18,89,79,80,35,0.0,3,92,Urban,Data Analyst,72593,1 +13381,Male,32,High School,15,99,61,25,47,7.0,0,36,Rural,Software Engineer,149474,0 +13382,Male,49,Masters,3,11,0,5,80,2.0,6,63,Rural,Software Engineer,21225,0 +13383,Female,56,Bachelors,1,12,16,64,26,7.0,6,35,Urban,HR Executive,100574,0 +13384,Male,48,Bachelors,2,79,0,39,94,8.0,7,97,Rural,ML Engineer,53339,0 +13385,Male,30,Masters,13,64,63,4,18,1.0,2,1,Semi-Urban,Manager,112047,0 +13386,Male,29,High School,10,12,5,38,67,0.0,7,19,Semi-Urban,Manager,61804,0 +13387,Female,36,Diploma,11,43,63,18,75,3.0,3,80,Semi-Urban,ML Engineer,124200,0 +13388,Male,30,Masters,15,56,97,95,93,1.0,6,70,Urban,Data Analyst,142264,1 +13389,Female,56,Diploma,19,63,2,4,87,4.0,5,12,Urban,ML Engineer,66613,0 +13390,Male,36,Bachelors,2,72,68,62,55,7.0,4,55,Urban,HR Executive,141832,1 +13391,Male,49,Bachelors,9,43,17,5,3,4.0,1,94,Urban,HR Executive,97453,0 +13392,Male,25,Diploma,2,35,99,56,31,5.0,4,21,Semi-Urban,Software Engineer,49114,0 +13393,Male,44,Masters,19,64,68,64,87,8.0,7,82,Semi-Urban,Data Analyst,92935,1 +13394,Female,43,Bachelors,15,65,93,84,50,4.0,7,15,Semi-Urban,ML Engineer,99762,1 +13395,Male,54,High School,9,89,46,92,43,2.0,7,83,Urban,Data Analyst,33503,1 +13396,Male,24,Bachelors,4,26,11,32,96,4.0,0,50,Rural,Data Analyst,76235,0 +13397,Male,48,High School,3,59,97,53,35,9.0,6,76,Urban,ML Engineer,27691,1 +13398,Male,25,Masters,16,38,35,68,12,8.0,4,76,Urban,Manager,48512,0 +13399,Male,56,Bachelors,6,14,58,64,49,3.0,7,87,Urban,Software Engineer,65590,0 +13400,Male,29,Masters,10,94,30,74,20,9.0,4,97,Semi-Urban,ML Engineer,88543,1 +13401,Other,37,Masters,5,49,42,78,40,4.0,5,73,Urban,Manager,123069,1 +13402,Female,23,Masters,11,29,36,16,91,8.0,3,32,Rural,HR Executive,58054,0 +13403,Male,22,Diploma,17,65,34,90,13,4.0,3,38,Semi-Urban,Software Engineer,99678,0 +13404,Male,37,Bachelors,17,58,96,85,31,8.0,4,42,Rural,Software Engineer,119965,1 +13405,Male,31,Diploma,4,4,72,73,44,4.0,1,68,Semi-Urban,Manager,110274,0 +13406,Male,30,High School,14,21,81,22,84,6.0,0,4,Urban,Software Engineer,30051,0 +13407,Female,47,Masters,2,3,58,86,36,5.0,0,18,Semi-Urban,Manager,87199,0 +13408,Female,46,Diploma,0,98,84,54,80,3.0,7,7,Urban,Data Analyst,76287,1 +13409,Male,49,Bachelors,14,18,60,39,94,2.0,6,8,Urban,HR Executive,63194,0 +13410,Female,41,High School,3,83,0,78,45,5.0,6,3,Semi-Urban,Software Engineer,147833,0 +13411,Male,31,High School,6,38,75,13,85,9.0,6,40,Semi-Urban,Software Engineer,37019,0 +13412,Male,24,Diploma,16,31,36,52,78,8.0,3,58,Urban,Data Analyst,84267,0 +13413,Male,50,Bachelors,10,41,66,28,66,3.0,6,64,Urban,HR Executive,101210,0 +13414,Male,58,Masters,8,0,38,24,21,8.0,0,88,Urban,Manager,135128,0 +13415,Female,24,Masters,19,14,60,70,4,6.0,7,59,Rural,Software Engineer,49238,0 +13416,Male,23,High School,6,33,69,77,45,9.0,6,17,Urban,Data Analyst,66281,0 +13417,Male,45,Masters,16,4,82,88,97,4.0,5,47,Rural,Data Analyst,132229,0 +13418,Other,24,Bachelors,1,39,13,75,34,6.0,6,69,Urban,ML Engineer,57762,0 +13419,Female,37,Bachelors,12,93,16,82,17,4.0,4,91,Urban,Manager,63068,1 +13420,Female,23,High School,7,7,92,98,64,2.0,0,56,Urban,Manager,122437,1 +13421,Female,37,Bachelors,8,43,91,81,22,8.0,0,19,Urban,HR Executive,127665,0 +13422,Male,24,Bachelors,15,30,55,17,82,2.0,0,36,Semi-Urban,Software Engineer,27692,0 +13423,Female,26,Bachelors,13,25,30,16,14,0.0,4,11,Urban,Data Analyst,78360,0 +13424,Female,49,Bachelors,6,82,63,26,90,4.0,0,26,Urban,Data Analyst,93524,0 +13425,Female,56,Bachelors,15,75,19,45,75,3.0,6,21,Semi-Urban,Data Analyst,89209,0 +13426,Female,34,Masters,18,64,44,6,96,2.0,4,49,Urban,ML Engineer,95047,0 +13427,Male,52,Bachelors,5,67,34,50,29,1.0,5,98,Urban,Software Engineer,103037,1 +13428,Female,25,Bachelors,4,51,10,95,33,5.0,0,24,Urban,HR Executive,56596,0 +13429,Male,21,High School,18,48,87,92,75,8.0,7,17,Urban,Manager,52152,1 +13430,Male,42,Bachelors,19,13,80,18,61,8.0,5,72,Rural,Data Analyst,141469,0 +13431,Male,40,PhD,1,52,86,3,50,9.0,0,5,Semi-Urban,ML Engineer,80590,0 +13432,Female,45,Bachelors,11,53,99,24,30,4.0,5,34,Semi-Urban,Manager,92936,0 +13433,Male,44,Bachelors,1,18,61,69,1,9.0,0,53,Semi-Urban,Software Engineer,52033,0 +13434,Male,23,Diploma,1,97,17,47,31,0.0,2,72,Urban,Data Analyst,131354,0 +13435,Male,42,Bachelors,3,53,49,82,58,6.0,3,58,Rural,ML Engineer,108861,1 +13436,Other,31,High School,6,86,95,39,82,8.0,6,43,Semi-Urban,Software Engineer,51197,1 +13437,Male,55,Bachelors,7,14,39,15,92,0.0,5,19,Urban,Data Analyst,71357,0 +13438,Female,32,Bachelors,2,32,16,67,80,1.0,0,29,Urban,Software Engineer,77575,0 +13439,Female,39,High School,9,0,23,31,9,8.0,1,29,Rural,Data Analyst,59556,0 +13440,Male,29,Bachelors,14,4,83,18,87,8.0,5,93,Urban,Manager,46024,0 +13441,Male,48,Diploma,15,7,32,8,47,3.0,5,12,Semi-Urban,Data Analyst,111300,0 +13442,Female,36,Masters,7,70,65,34,67,3.0,7,42,Urban,Data Analyst,78017,0 +13443,Female,37,PhD,16,48,10,42,78,0.0,4,2,Semi-Urban,HR Executive,106520,0 +13444,Female,56,Masters,11,26,88,54,76,8.0,6,40,Semi-Urban,ML Engineer,80161,0 +13445,Male,52,Diploma,10,89,91,69,94,2.0,1,53,Urban,ML Engineer,27977,1 +13446,Female,59,Bachelors,16,96,21,94,66,6.0,3,56,Urban,Manager,83830,1 +13447,Male,31,Masters,17,55,74,55,12,8.0,3,52,Semi-Urban,Data Analyst,77945,1 +13448,Male,33,Diploma,18,81,36,17,17,2.0,2,28,Urban,HR Executive,124056,0 +13449,Female,56,Diploma,13,87,52,95,26,3.0,7,7,Urban,Manager,70816,1 +13450,Male,29,Bachelors,16,65,47,78,14,4.0,1,40,Rural,Manager,101765,0 +13451,Female,26,High School,10,3,15,40,9,9.0,7,65,Urban,Software Engineer,46876,0 +13452,Male,39,Masters,19,47,24,92,21,6.0,5,5,Urban,Manager,78805,0 +13453,Female,44,Bachelors,7,59,37,49,46,4.0,3,7,Urban,Software Engineer,93648,0 +13454,Male,55,High School,4,13,72,39,79,5.0,4,45,Rural,Software Engineer,78120,0 +13455,Male,57,Bachelors,18,52,37,56,11,6.0,1,60,Urban,Software Engineer,20912,0 +13456,Female,50,Masters,2,32,26,23,9,5.0,5,84,Urban,Data Analyst,65784,0 +13457,Male,32,Bachelors,18,6,67,33,8,9.0,6,32,Urban,ML Engineer,124182,0 +13458,Male,42,High School,15,90,19,6,33,8.0,2,11,Urban,Data Analyst,136688,0 +13459,Other,38,High School,13,30,10,10,59,2.0,5,88,Urban,HR Executive,103928,0 +13460,Male,43,Masters,4,38,74,46,61,1.0,2,34,Urban,ML Engineer,119026,0 +13461,Other,44,Diploma,10,13,7,12,25,4.0,3,33,Urban,Software Engineer,51558,0 +13462,Male,32,Bachelors,8,29,84,26,23,9.0,2,99,Rural,Data Analyst,131640,1 +13463,Male,38,Bachelors,0,84,85,31,30,8.0,3,58,Urban,HR Executive,79398,1 +13464,Female,39,High School,1,31,27,39,11,5.0,4,50,Urban,HR Executive,44539,0 +13465,Female,36,High School,13,22,71,78,58,4.0,6,50,Semi-Urban,Software Engineer,124707,0 +13466,Male,25,Bachelors,6,99,60,90,51,8.0,7,3,Urban,Software Engineer,85984,1 +13467,Male,59,Masters,5,66,18,26,88,2.0,2,27,Urban,Data Analyst,87576,0 +13468,Female,27,Masters,8,98,43,0,64,0.0,5,39,Semi-Urban,ML Engineer,60117,0 +13469,Male,44,Bachelors,1,35,2,85,89,9.0,3,11,Urban,Manager,42055,0 +13470,Male,51,Masters,17,35,76,86,61,0.0,6,95,Semi-Urban,Software Engineer,101180,1 +13471,Male,27,Bachelors,1,84,35,49,43,0.0,0,43,Semi-Urban,HR Executive,109346,0 +13472,Male,25,Masters,9,67,14,88,79,5.0,4,52,Urban,HR Executive,35199,0 +13473,Male,49,Masters,16,37,48,44,93,0.0,2,86,Semi-Urban,ML Engineer,26677,0 +13474,Male,40,Masters,10,2,28,20,58,1.0,6,24,Urban,Data Analyst,70639,0 +13475,Male,57,Masters,14,2,86,88,88,3.0,3,89,Semi-Urban,Manager,144137,1 +13476,Male,25,Masters,14,8,5,39,49,9.0,5,57,Rural,HR Executive,83288,0 +13477,Male,42,Masters,9,89,5,7,47,7.0,0,15,Semi-Urban,Data Analyst,87575,0 +13478,Female,59,Bachelors,10,82,67,18,51,4.0,0,58,Semi-Urban,ML Engineer,94104,0 +13479,Male,32,Bachelors,14,83,95,21,38,4.0,4,86,Urban,ML Engineer,38735,1 +13480,Female,36,Masters,18,42,73,2,44,8.0,5,73,Urban,Manager,103325,0 +13481,Female,21,Bachelors,3,93,37,35,50,4.0,5,99,Semi-Urban,Software Engineer,61457,1 +13482,Male,25,High School,1,92,69,5,12,9.0,5,45,Urban,Manager,116770,0 +13483,Female,27,Diploma,19,95,69,2,82,2.0,0,21,Urban,Data Analyst,106609,0 +13484,Male,54,Bachelors,4,31,30,40,45,4.0,0,60,Urban,Software Engineer,26232,0 +13485,Female,21,Bachelors,19,13,21,61,67,5.0,5,17,Rural,Manager,147149,0 +13486,Other,50,Bachelors,0,54,85,6,21,8.0,1,67,Urban,Data Analyst,60353,0 +13487,Male,30,High School,18,73,17,98,60,0.0,5,17,Urban,ML Engineer,41637,0 +13488,Female,23,Bachelors,10,57,63,41,11,8.0,1,8,Rural,Manager,64402,0 +13489,Male,35,Diploma,6,19,12,78,6,5.0,6,30,Urban,ML Engineer,142715,0 +13490,Male,29,Diploma,13,92,14,90,58,0.0,1,10,Urban,Manager,99720,0 +13491,Female,24,Bachelors,6,68,51,74,49,5.0,7,67,Urban,ML Engineer,32803,1 +13492,Male,23,PhD,16,27,51,42,1,3.0,5,54,Urban,Software Engineer,98583,0 +13493,Male,23,Bachelors,9,12,23,90,38,7.0,3,16,Urban,Data Analyst,116290,0 +13494,Male,43,Bachelors,0,46,17,98,16,4.0,1,1,Urban,ML Engineer,134558,0 +13495,Female,25,Bachelors,9,99,76,4,22,9.0,7,41,Urban,ML Engineer,117234,0 +13496,Male,23,Bachelors,7,1,44,8,41,8.0,4,17,Semi-Urban,Manager,74177,0 +13497,Female,58,High School,13,73,40,86,29,8.0,4,98,Urban,Data Analyst,148347,1 +13498,Male,48,Diploma,16,83,73,0,20,4.0,0,97,Urban,Data Analyst,111330,1 +13499,Male,49,High School,10,47,87,73,52,2.0,5,87,Semi-Urban,Manager,40419,1 +13500,Female,53,Bachelors,6,80,81,37,29,2.0,4,48,Rural,HR Executive,100790,1 +13501,Male,41,Bachelors,8,83,5,42,23,2.0,7,11,Rural,Data Analyst,133518,0 +13502,Female,50,Diploma,9,12,46,54,74,8.0,3,86,Urban,ML Engineer,129635,0 +13503,Male,32,High School,6,29,17,35,46,5.0,1,22,Semi-Urban,HR Executive,29309,0 +13504,Male,51,Masters,4,97,20,0,54,0.0,2,83,Urban,Manager,43967,0 +13505,Male,51,Diploma,18,12,96,85,51,0.0,7,63,Semi-Urban,Manager,49672,1 +13506,Female,28,Masters,15,65,75,99,20,4.0,7,23,Urban,ML Engineer,107021,1 +13507,Male,57,Bachelors,15,65,71,66,73,6.0,5,34,Urban,Manager,59839,1 +13508,Female,23,Bachelors,14,90,71,38,76,9.0,5,53,Rural,Software Engineer,95362,1 +13509,Male,29,Bachelors,18,83,43,99,90,9.0,0,16,Rural,HR Executive,116733,1 +13510,Male,43,Masters,8,23,90,28,68,3.0,4,77,Urban,Data Analyst,136467,0 +13511,Male,34,Bachelors,6,51,67,85,19,6.0,7,9,Semi-Urban,Data Analyst,119822,0 +13512,Female,59,Bachelors,15,62,19,81,43,9.0,6,21,Urban,ML Engineer,138989,0 +13513,Female,38,Bachelors,17,97,71,99,46,5.0,1,99,Semi-Urban,Data Analyst,87754,1 +13514,Female,32,High School,5,70,67,64,65,1.0,3,33,Urban,Software Engineer,64140,0 +13515,Male,34,Bachelors,10,70,61,68,67,5.0,1,49,Urban,Software Engineer,63491,1 +13516,Male,47,Bachelors,16,74,53,11,61,0.0,5,14,Urban,HR Executive,39302,0 +13517,Male,53,Diploma,1,70,49,14,63,8.0,4,37,Rural,HR Executive,141731,0 +13518,Female,38,High School,5,43,13,47,68,8.0,0,2,Urban,Manager,119221,0 +13519,Male,21,Diploma,17,14,77,3,83,7.0,2,6,Urban,Software Engineer,48335,0 +13520,Male,52,Masters,17,85,39,2,55,9.0,5,14,Urban,Software Engineer,136584,0 +13521,Male,40,High School,13,15,81,84,74,5.0,2,58,Urban,Software Engineer,100424,1 +13522,Male,56,Masters,9,84,1,11,75,6.0,5,84,Urban,ML Engineer,66871,0 +13523,Male,49,Masters,7,91,20,23,63,8.0,0,97,Semi-Urban,Manager,94021,0 +13524,Female,45,High School,12,55,53,35,27,6.0,3,15,Rural,Software Engineer,71136,0 +13525,Male,40,Diploma,15,17,8,88,80,2.0,7,61,Semi-Urban,ML Engineer,75373,0 +13526,Female,50,Diploma,2,14,16,81,71,7.0,3,50,Urban,HR Executive,42829,0 +13527,Female,48,Diploma,18,95,86,9,92,1.0,7,67,Urban,Data Analyst,105211,1 +13528,Male,44,Bachelors,13,99,85,40,41,2.0,2,51,Urban,Data Analyst,71802,1 +13529,Male,44,Bachelors,17,72,52,2,18,4.0,7,50,Semi-Urban,HR Executive,124302,0 +13530,Male,43,Diploma,5,62,87,58,34,6.0,1,59,Urban,Manager,84364,1 +13531,Female,59,Diploma,11,8,75,10,34,1.0,3,97,Urban,Data Analyst,70847,0 +13532,Male,21,Bachelors,9,36,76,37,56,7.0,3,98,Urban,HR Executive,96818,1 +13533,Male,52,High School,8,8,95,97,20,7.0,5,75,Rural,HR Executive,77341,1 +13534,Male,25,Diploma,6,41,93,37,11,7.0,6,55,Rural,Data Analyst,41101,0 +13535,Male,35,Bachelors,16,13,40,67,12,7.0,0,21,Urban,ML Engineer,58695,0 +13536,Male,30,Masters,8,14,4,10,27,8.0,4,76,Urban,HR Executive,91989,0 +13537,Male,53,Masters,13,37,61,0,84,1.0,0,56,Semi-Urban,HR Executive,74080,0 +13538,Female,43,High School,9,77,52,27,61,0.0,0,70,Semi-Urban,HR Executive,46241,0 +13539,Female,58,Bachelors,1,33,80,63,20,6.0,0,11,Urban,Software Engineer,27485,0 +13540,Male,32,Masters,2,98,86,79,8,6.0,7,95,Urban,Manager,21656,1 +13541,Male,50,Diploma,9,90,4,93,61,6.0,6,93,Urban,HR Executive,127389,1 +13542,Female,31,Masters,15,18,71,28,28,5.0,1,90,Rural,Software Engineer,137777,0 +13543,Male,40,Bachelors,17,41,6,88,59,1.0,3,43,Rural,ML Engineer,79506,0 +13544,Female,58,Bachelors,13,34,24,63,26,3.0,6,18,Rural,HR Executive,140610,0 +13545,Male,24,Diploma,19,11,33,77,44,5.0,2,9,Urban,Software Engineer,143406,0 +13546,Female,35,Bachelors,19,82,91,58,51,3.0,1,42,Urban,Software Engineer,140435,1 +13547,Male,37,High School,19,1,87,51,40,9.0,0,96,Semi-Urban,Software Engineer,26903,1 +13548,Male,40,Diploma,13,12,16,10,7,7.0,4,57,Urban,Manager,125933,0 +13549,Female,32,Masters,8,62,26,28,44,8.0,5,95,Urban,HR Executive,112372,0 +13550,Male,58,High School,17,66,20,64,87,1.0,6,13,Urban,Manager,126869,0 +13551,Male,27,Bachelors,18,20,53,87,5,1.0,5,86,Rural,ML Engineer,66902,1 +13552,Male,30,Bachelors,2,68,27,55,2,6.0,0,12,Rural,Data Analyst,124516,0 +13553,Female,59,Masters,0,70,91,86,6,1.0,2,35,Urban,HR Executive,24458,1 +13554,Male,57,Diploma,9,25,77,62,5,8.0,3,20,Urban,HR Executive,54856,0 +13555,Female,23,Bachelors,4,33,8,54,12,7.0,1,48,Urban,Manager,139514,0 +13556,Male,49,Masters,16,24,94,33,47,3.0,4,10,Urban,ML Engineer,137089,0 +13557,Male,58,Diploma,7,12,57,52,94,8.0,5,41,Urban,ML Engineer,72813,0 +13558,Female,44,Bachelors,9,21,49,82,25,6.0,1,66,Rural,Data Analyst,35701,0 +13559,Male,37,Bachelors,6,63,56,73,38,5.0,1,83,Urban,Software Engineer,109618,1 +13560,Male,23,Bachelors,6,97,81,8,2,9.0,2,45,Semi-Urban,ML Engineer,84408,0 +13561,Male,29,Diploma,17,70,61,74,91,3.0,3,92,Urban,ML Engineer,147733,1 +13562,Male,46,Diploma,8,18,11,30,48,4.0,4,5,Semi-Urban,Software Engineer,89685,0 +13563,Female,34,High School,19,36,90,29,26,6.0,5,73,Semi-Urban,Manager,104740,0 +13564,Male,27,Diploma,3,56,44,14,93,7.0,1,79,Urban,Data Analyst,44704,0 +13565,Male,33,Bachelors,18,32,13,74,15,9.0,4,33,Semi-Urban,Manager,110758,0 +13566,Male,43,Diploma,2,47,97,68,92,8.0,1,11,Urban,Manager,54137,0 +13567,Male,24,Diploma,6,42,74,98,6,3.0,1,19,Urban,Data Analyst,145294,0 +13568,Male,57,Masters,17,93,57,23,15,5.0,6,8,Semi-Urban,ML Engineer,142830,0 +13569,Other,49,High School,7,91,26,37,6,9.0,4,97,Rural,HR Executive,102204,1 +13570,Female,53,Masters,13,71,33,17,36,5.0,3,9,Urban,Software Engineer,65536,0 +13571,Male,41,Masters,17,94,31,30,6,6.0,0,25,Urban,Manager,35892,0 +13572,Male,39,Bachelors,9,60,7,15,26,9.0,4,79,Rural,Data Analyst,34046,0 +13573,Female,25,Bachelors,19,67,42,26,8,9.0,4,36,Semi-Urban,Data Analyst,37243,0 +13574,Male,35,Bachelors,0,49,40,85,63,3.0,7,47,Urban,ML Engineer,146969,0 +13575,Male,59,High School,8,28,57,54,30,7.0,5,16,Urban,Software Engineer,107885,0 +13576,Female,24,Bachelors,19,9,76,47,90,5.0,6,61,Urban,Software Engineer,32606,0 +13577,Male,44,Bachelors,16,34,94,35,28,4.0,6,78,Semi-Urban,ML Engineer,31040,1 +13578,Male,54,Bachelors,7,93,47,18,39,3.0,2,8,Urban,Data Analyst,61774,0 +13579,Other,40,Bachelors,14,9,62,34,2,0.0,7,60,Urban,Software Engineer,107031,0 +13580,Female,37,Diploma,14,64,11,53,9,5.0,0,25,Semi-Urban,Software Engineer,148566,0 +13581,Male,33,Bachelors,2,32,3,74,64,5.0,1,61,Semi-Urban,HR Executive,94984,0 +13582,Male,50,Bachelors,4,57,8,67,51,4.0,4,97,Rural,Data Analyst,146538,0 +13583,Male,21,Bachelors,16,20,22,94,82,1.0,7,37,Semi-Urban,Data Analyst,139132,0 +13584,Female,28,High School,9,84,75,12,98,6.0,2,49,Semi-Urban,Software Engineer,116672,0 +13585,Male,38,Bachelors,0,69,52,5,29,5.0,4,57,Rural,HR Executive,68632,0 +13586,Male,21,Bachelors,10,63,31,58,45,5.0,6,65,Urban,Data Analyst,149042,0 +13587,Female,40,Diploma,2,26,53,27,10,8.0,6,68,Rural,Manager,20044,0 +13588,Male,57,Masters,9,27,83,50,18,0.0,6,5,Urban,Manager,83145,0 +13589,Male,59,Masters,12,9,78,52,5,2.0,5,9,Semi-Urban,Software Engineer,77776,0 +13590,Male,57,Bachelors,9,95,36,1,46,1.0,7,0,Rural,Software Engineer,143400,0 +13591,Male,25,Diploma,16,24,43,87,8,9.0,5,25,Urban,HR Executive,137491,0 +13592,Male,46,Bachelors,12,65,29,19,17,5.0,2,53,Rural,Data Analyst,83561,0 +13593,Female,42,Diploma,2,73,91,19,46,1.0,4,53,Semi-Urban,Manager,64362,0 +13594,Female,46,Bachelors,10,97,52,96,69,1.0,7,32,Urban,Manager,91000,1 +13595,Male,26,Bachelors,1,95,88,95,91,3.0,1,32,Urban,HR Executive,146145,1 +13596,Male,28,Masters,1,41,94,53,79,6.0,6,90,Rural,ML Engineer,101208,1 +13597,Male,59,Diploma,17,99,7,5,65,5.0,1,6,Urban,HR Executive,80879,0 +13598,Male,29,Diploma,19,98,78,48,6,5.0,3,98,Urban,Software Engineer,56432,1 +13599,Male,27,High School,7,63,94,90,98,3.0,5,82,Rural,Software Engineer,43154,1 +13600,Female,46,Bachelors,18,13,47,23,87,7.0,1,7,Semi-Urban,ML Engineer,71207,0 +13601,Male,38,High School,19,85,2,7,95,0.0,1,49,Semi-Urban,HR Executive,138725,0 +13602,Male,54,Masters,17,36,9,57,59,1.0,7,32,Urban,Data Analyst,65896,0 +13603,Male,44,Bachelors,11,75,81,29,90,2.0,7,54,Urban,ML Engineer,138475,1 +13604,Male,21,Bachelors,12,30,0,87,62,9.0,4,44,Urban,ML Engineer,104110,0 +13605,Male,25,PhD,9,87,76,7,20,3.0,4,72,Semi-Urban,HR Executive,82959,1 +13606,Male,53,Masters,18,83,98,72,91,5.0,5,42,Semi-Urban,HR Executive,134540,1 +13607,Male,36,Bachelors,13,78,22,78,11,5.0,7,44,Rural,Software Engineer,68103,0 +13608,Female,53,Masters,14,10,60,11,80,8.0,4,48,Rural,Data Analyst,69890,0 +13609,Male,45,Masters,12,81,32,61,1,1.0,7,99,Rural,HR Executive,148703,1 +13610,Male,43,Bachelors,14,4,1,60,87,4.0,3,26,Urban,ML Engineer,37238,0 +13611,Male,26,Bachelors,14,38,34,82,41,7.0,2,20,Urban,HR Executive,42509,0 +13612,Female,50,Bachelors,3,80,42,90,15,1.0,1,10,Urban,HR Executive,68798,0 +13613,Male,23,Masters,9,45,35,39,42,8.0,6,99,Semi-Urban,Software Engineer,45422,0 +13614,Male,39,Diploma,13,43,79,36,48,8.0,1,82,Urban,ML Engineer,31319,1 +13615,Male,50,Masters,10,68,6,70,25,2.0,4,29,Semi-Urban,Manager,98919,0 +13616,Female,44,Diploma,0,62,3,58,58,5.0,3,30,Urban,Data Analyst,60773,0 +13617,Male,49,High School,16,10,54,89,82,8.0,6,96,Urban,Data Analyst,74318,1 +13618,Male,37,PhD,1,10,3,28,96,4.0,6,85,Urban,HR Executive,38815,0 +13619,Male,58,Bachelors,4,76,19,47,37,3.0,7,97,Rural,HR Executive,112821,1 +13620,Male,45,PhD,13,62,22,40,63,5.0,5,24,Urban,ML Engineer,85686,0 +13621,Male,21,Bachelors,12,76,64,15,22,4.0,7,58,Semi-Urban,Software Engineer,119322,0 +13622,Male,36,Diploma,16,15,59,37,67,8.0,2,94,Rural,HR Executive,63358,0 +13623,Female,32,Diploma,1,15,94,90,25,8.0,7,58,Semi-Urban,Data Analyst,111611,1 +13624,Female,31,Masters,14,50,45,44,52,7.0,2,18,Rural,Manager,26327,0 +13625,Male,30,Diploma,8,72,63,16,39,9.0,1,14,Urban,Software Engineer,45853,0 +13626,Male,23,Diploma,0,63,26,41,4,5.0,5,26,Urban,Manager,121625,0 +13627,Male,49,PhD,5,18,29,87,70,0.0,2,46,Urban,Manager,103023,0 +13628,Male,54,Bachelors,8,23,31,10,22,8.0,7,50,Urban,HR Executive,57670,0 +13629,Female,51,Bachelors,11,98,79,88,76,6.0,2,47,Rural,Data Analyst,144656,1 +13630,Other,24,Diploma,10,74,67,77,85,7.0,1,98,Urban,Data Analyst,113617,1 +13631,Male,52,Bachelors,12,19,30,34,43,0.0,3,95,Semi-Urban,Manager,128042,0 +13632,Male,23,Masters,10,33,44,22,23,7.0,2,67,Urban,ML Engineer,128718,0 +13633,Male,56,PhD,12,95,49,51,32,2.0,3,42,Urban,Manager,125927,1 +13634,Female,38,Bachelors,2,22,77,90,4,2.0,7,94,Semi-Urban,Data Analyst,106720,1 +13635,Female,58,Bachelors,12,17,30,86,98,0.0,3,19,Urban,Software Engineer,51778,0 +13636,Female,42,Bachelors,10,65,58,11,93,2.0,0,32,Rural,Manager,40556,0 +13637,Female,25,Bachelors,8,55,17,53,64,8.0,3,34,Rural,HR Executive,72351,0 +13638,Male,41,Bachelors,15,40,2,66,78,6.0,1,8,Urban,HR Executive,71356,0 +13639,Female,25,Bachelors,14,84,84,95,64,9.0,6,15,Urban,Manager,23953,1 +13640,Female,46,Bachelors,2,89,63,3,16,4.0,7,76,Urban,Manager,72575,0 +13641,Male,42,Masters,19,79,52,23,83,8.0,7,44,Semi-Urban,ML Engineer,148014,0 +13642,Male,29,High School,14,36,48,26,99,7.0,3,76,Urban,ML Engineer,49972,0 +13643,Female,42,Bachelors,8,40,72,49,65,5.0,5,45,Urban,ML Engineer,123149,0 +13644,Male,32,Bachelors,3,37,7,40,36,5.0,6,91,Rural,HR Executive,148696,0 +13645,Female,33,Bachelors,4,77,36,54,50,4.0,7,90,Rural,ML Engineer,74593,1 +13646,Female,59,Bachelors,2,90,99,8,73,3.0,0,78,Semi-Urban,Manager,144270,1 +13647,Female,40,Bachelors,11,36,65,41,65,0.0,5,69,Urban,Software Engineer,97147,0 +13648,Female,25,Masters,15,3,67,11,88,8.0,6,27,Rural,HR Executive,25948,0 +13649,Male,23,Bachelors,4,79,52,39,61,7.0,1,29,Urban,HR Executive,42925,0 +13650,Female,40,High School,16,70,81,21,23,0.0,0,28,Urban,ML Engineer,132897,0 +13651,Male,35,Bachelors,12,9,61,89,60,4.0,1,8,Urban,Software Engineer,142511,0 +13652,Male,48,Diploma,19,43,35,41,2,1.0,2,86,Urban,Manager,100771,0 +13653,Male,25,Diploma,0,71,97,15,73,2.0,4,29,Semi-Urban,Manager,104002,0 +13654,Male,50,Diploma,3,10,94,72,73,5.0,3,16,Rural,ML Engineer,48117,0 +13655,Male,34,Diploma,8,42,26,81,96,5.0,7,47,Semi-Urban,Manager,60115,0 +13656,Other,21,Diploma,6,49,93,69,91,1.0,3,92,Urban,HR Executive,123597,1 +13657,Male,27,High School,3,82,79,12,97,7.0,1,11,Rural,HR Executive,51022,0 +13658,Male,48,Masters,16,42,43,4,72,2.0,7,38,Rural,HR Executive,22562,0 +13659,Male,49,Bachelors,1,97,62,0,77,4.0,5,82,Rural,HR Executive,149301,1 +13660,Male,28,Masters,17,72,59,9,44,5.0,5,96,Semi-Urban,Software Engineer,48178,1 +13661,Female,41,Bachelors,3,7,43,13,2,2.0,1,7,Semi-Urban,ML Engineer,98251,0 +13662,Male,58,Bachelors,11,41,98,41,0,3.0,0,69,Urban,HR Executive,119394,1 +13663,Female,55,Diploma,0,21,83,62,93,2.0,7,55,Urban,Software Engineer,102094,0 +13664,Female,47,Diploma,6,38,81,11,68,7.0,0,85,Rural,Software Engineer,74964,0 +13665,Male,32,Bachelors,19,67,74,22,85,7.0,1,91,Urban,Manager,37505,1 +13666,Female,40,Diploma,19,85,20,25,11,7.0,4,38,Semi-Urban,ML Engineer,62096,0 +13667,Male,59,High School,14,31,32,23,48,3.0,7,41,Urban,Manager,135219,0 +13668,Male,41,High School,15,20,60,75,48,7.0,6,95,Urban,HR Executive,46061,1 +13669,Female,39,Diploma,19,28,38,60,10,1.0,6,25,Semi-Urban,Data Analyst,76852,0 +13670,Female,33,Diploma,8,84,70,30,70,1.0,7,67,Urban,Software Engineer,112115,1 +13671,Male,23,Bachelors,18,37,7,55,63,6.0,1,47,Urban,ML Engineer,20715,0 +13672,Male,54,Bachelors,11,77,94,24,22,7.0,5,78,Rural,ML Engineer,144852,1 +13673,Male,47,Diploma,5,45,20,97,2,0.0,5,17,Urban,Data Analyst,135427,0 +13674,Male,38,Masters,18,80,16,28,25,3.0,2,44,Rural,Manager,88319,0 +13675,Other,23,Bachelors,3,32,54,40,68,7.0,4,93,Rural,HR Executive,105077,0 +13676,Male,57,Masters,9,62,58,47,11,9.0,6,87,Urban,Manager,78613,1 +13677,Male,23,Diploma,4,66,99,7,29,8.0,3,78,Urban,Data Analyst,99780,1 +13678,Female,58,High School,2,67,96,50,50,9.0,3,17,Rural,Software Engineer,66446,0 +13679,Male,56,Bachelors,19,59,85,75,76,6.0,2,53,Urban,Manager,29873,1 +13680,Male,37,Masters,18,51,80,32,17,6.0,3,85,Urban,ML Engineer,33078,1 +13681,Female,46,Diploma,7,27,28,68,60,0.0,5,76,Rural,Manager,79881,0 +13682,Female,38,Bachelors,0,10,73,26,72,1.0,6,1,Urban,Software Engineer,94562,0 +13683,Female,41,Bachelors,15,71,37,15,24,0.0,0,76,Urban,Software Engineer,71950,0 +13684,Male,45,Diploma,4,16,39,76,14,6.0,6,66,Urban,Software Engineer,92470,0 +13685,Female,56,Bachelors,10,56,42,20,81,7.0,4,91,Rural,Data Analyst,137567,0 +13686,Male,53,Diploma,15,55,69,29,60,2.0,5,61,Urban,Manager,31917,0 +13687,Male,51,Bachelors,18,24,19,58,54,6.0,4,15,Urban,HR Executive,102766,0 +13688,Other,28,Bachelors,16,36,39,66,19,2.0,1,13,Semi-Urban,ML Engineer,119058,0 +13689,Male,54,Masters,0,76,94,37,70,4.0,3,62,Urban,Software Engineer,93390,1 +13690,Female,40,Bachelors,18,84,95,42,96,7.0,5,7,Urban,Software Engineer,78080,0 +13691,Male,57,Bachelors,12,99,80,16,23,2.0,7,84,Urban,HR Executive,146432,1 +13692,Male,46,Diploma,9,45,81,10,10,2.0,4,68,Semi-Urban,ML Engineer,145442,0 +13693,Female,45,Bachelors,15,87,28,74,30,5.0,0,38,Urban,Software Engineer,116355,0 +13694,Male,49,Diploma,14,41,2,42,98,7.0,0,67,Urban,Software Engineer,57467,0 +13695,Female,44,Diploma,13,27,69,57,39,1.0,7,58,Urban,ML Engineer,28051,0 +13696,Male,31,Bachelors,6,49,57,60,64,5.0,7,56,Semi-Urban,Manager,25356,0 +13697,Female,27,Masters,18,22,45,12,47,8.0,4,18,Semi-Urban,Manager,128641,0 +13698,Male,26,Bachelors,5,46,61,60,79,7.0,4,10,Urban,Manager,41910,0 +13699,Male,44,Masters,6,43,15,51,49,9.0,5,55,Urban,Manager,32691,0 +13700,Male,59,Bachelors,2,86,76,65,2,5.0,0,23,Semi-Urban,Data Analyst,58662,1 +13701,Female,30,Masters,6,46,45,65,3,5.0,5,47,Urban,ML Engineer,31047,0 +13702,Female,49,High School,13,10,88,69,15,6.0,0,31,Rural,Software Engineer,81376,0 +13703,Female,30,High School,1,48,51,26,1,9.0,0,45,Urban,Manager,121599,0 +13704,Male,25,Diploma,10,50,89,39,23,7.0,2,66,Urban,Data Analyst,118177,1 +13705,Male,56,Bachelors,9,94,12,23,69,8.0,4,39,Semi-Urban,HR Executive,124884,0 +13706,Male,33,Bachelors,15,61,91,30,1,1.0,3,72,Semi-Urban,ML Engineer,96321,1 +13707,Male,45,Bachelors,3,27,18,75,37,3.0,4,40,Semi-Urban,Manager,37114,0 +13708,Male,31,Diploma,2,7,24,24,68,8.0,6,51,Urban,HR Executive,100265,0 +13709,Other,24,Bachelors,7,69,35,17,6,8.0,7,0,Rural,HR Executive,84834,0 +13710,Female,53,Bachelors,9,49,6,59,97,4.0,7,52,Urban,Data Analyst,21926,0 +13711,Male,36,Diploma,2,98,9,14,88,2.0,5,99,Rural,ML Engineer,118665,0 +13712,Male,59,Diploma,12,21,24,4,11,1.0,0,46,Urban,Software Engineer,111390,0 +13713,Female,53,Bachelors,16,95,52,81,87,5.0,5,57,Urban,Manager,91302,1 +13714,Male,36,Bachelors,10,59,87,36,0,8.0,5,26,Semi-Urban,Manager,99434,0 +13715,Male,34,Bachelors,3,35,48,84,26,7.0,0,84,Rural,Manager,81221,1 +13716,Male,35,High School,5,56,90,31,73,3.0,1,33,Semi-Urban,Manager,121009,0 +13717,Male,56,Diploma,5,26,30,32,44,4.0,3,30,Urban,Manager,119648,0 +13718,Female,56,Bachelors,6,15,27,31,37,0.0,5,73,Urban,HR Executive,86397,0 +13719,Male,52,Diploma,1,33,84,34,2,0.0,3,50,Rural,HR Executive,117889,0 +13720,Male,42,Masters,0,70,56,69,35,1.0,1,16,Rural,HR Executive,91658,0 +13721,Male,22,Diploma,18,28,48,99,18,5.0,5,9,Semi-Urban,Data Analyst,98321,0 +13722,Female,29,Diploma,12,66,83,48,57,6.0,1,2,Rural,HR Executive,53848,0 +13723,Male,48,Diploma,12,26,61,50,99,0.0,3,96,Urban,Manager,57245,0 +13724,Male,29,Bachelors,13,96,57,1,60,7.0,2,10,Urban,HR Executive,60003,0 +13725,Female,54,Bachelors,19,73,33,50,52,4.0,7,25,Urban,Manager,63156,0 +13726,Other,21,Bachelors,5,88,12,88,26,7.0,3,3,Urban,Manager,118799,0 +13727,Other,47,PhD,10,55,98,11,78,2.0,0,6,Urban,Manager,112901,0 +13728,Female,30,High School,1,12,52,2,78,9.0,6,65,Urban,Software Engineer,58047,0 +13729,Male,37,Diploma,14,8,74,27,87,4.0,3,54,Urban,ML Engineer,60309,0 +13730,Male,23,High School,1,95,17,99,21,1.0,7,34,Urban,Manager,40898,1 +13731,Male,36,Bachelors,17,5,77,79,56,7.0,5,65,Semi-Urban,Manager,57901,0 +13732,Male,38,Bachelors,3,30,75,12,53,6.0,5,7,Semi-Urban,ML Engineer,120068,0 +13733,Other,46,Bachelors,7,36,76,79,68,8.0,7,61,Urban,HR Executive,136769,1 +13734,Female,36,Bachelors,5,28,79,19,63,2.0,0,97,Semi-Urban,Manager,137500,0 +13735,Female,38,High School,17,71,97,59,38,4.0,3,94,Urban,Data Analyst,37395,1 +13736,Male,29,Bachelors,12,77,83,87,17,5.0,1,4,Urban,Software Engineer,139476,1 +13737,Female,33,Bachelors,14,12,18,3,40,6.0,0,66,Urban,Data Analyst,61806,0 +13738,Female,47,Masters,4,68,86,23,91,8.0,3,51,Rural,HR Executive,82405,0 +13739,Male,32,Diploma,12,21,56,18,15,3.0,7,77,Semi-Urban,Manager,102006,0 +13740,Female,50,Bachelors,12,97,70,56,16,5.0,3,93,Semi-Urban,Data Analyst,110719,1 +13741,Male,52,Diploma,4,7,73,55,10,8.0,1,4,Urban,Manager,109078,0 +13742,Male,25,PhD,11,45,47,79,31,6.0,6,30,Rural,Software Engineer,113681,0 +13743,Female,54,Diploma,0,34,61,73,5,3.0,0,69,Urban,Data Analyst,121708,0 +13744,Female,32,PhD,15,57,6,71,69,7.0,5,28,Urban,HR Executive,54790,0 +13745,Male,44,Diploma,8,37,7,56,32,6.0,1,23,Rural,Manager,40279,0 +13746,Male,53,Bachelors,5,73,64,42,0,3.0,6,59,Urban,HR Executive,134205,1 +13747,Other,22,Diploma,2,59,41,39,62,9.0,2,32,Rural,Manager,127142,0 +13748,Female,56,Bachelors,4,51,55,85,28,1.0,7,18,Semi-Urban,Manager,35005,0 +13749,Female,26,High School,18,47,3,72,78,2.0,3,11,Semi-Urban,Software Engineer,86367,0 +13750,Male,52,Masters,1,80,15,94,48,3.0,0,54,Urban,Data Analyst,84815,1 +13751,Male,54,Bachelors,0,19,60,85,72,4.0,6,54,Urban,Software Engineer,56495,0 +13752,Male,46,High School,14,62,41,76,77,6.0,2,56,Urban,Manager,100871,1 +13753,Male,53,Bachelors,12,22,95,93,16,3.0,6,79,Urban,Software Engineer,54188,1 +13754,Male,22,Masters,5,78,12,28,80,1.0,4,32,Urban,Data Analyst,85615,0 +13755,Male,34,Bachelors,19,8,76,44,65,3.0,7,20,Rural,HR Executive,106192,0 +13756,Male,57,Bachelors,17,97,36,30,96,7.0,0,81,Urban,Manager,114787,1 +13757,Male,35,Bachelors,6,52,80,96,49,7.0,4,87,Urban,HR Executive,52856,1 +13758,Female,37,Masters,3,9,79,28,22,8.0,3,68,Rural,Data Analyst,34521,0 +13759,Male,48,Masters,4,29,27,13,48,9.0,2,88,Urban,ML Engineer,24560,0 +13760,Male,42,High School,10,37,26,89,70,6.0,2,91,Urban,Manager,65456,1 +13761,Male,40,Masters,5,80,64,6,21,1.0,0,28,Urban,ML Engineer,86964,0 +13762,Male,48,High School,17,40,6,0,87,2.0,7,51,Semi-Urban,Software Engineer,136131,0 +13763,Male,39,Diploma,2,46,40,0,41,1.0,1,45,Rural,Manager,40252,0 +13764,Other,39,Diploma,12,41,58,92,10,7.0,4,57,Semi-Urban,Software Engineer,92601,1 +13765,Female,24,Masters,3,15,55,30,68,8.0,5,8,Rural,Software Engineer,75608,0 +13766,Male,27,High School,6,73,15,89,64,2.0,5,17,Semi-Urban,Data Analyst,91104,0 +13767,Male,33,High School,13,79,25,34,82,7.0,3,2,Urban,ML Engineer,43570,0 +13768,Male,32,PhD,2,64,54,91,81,6.0,0,19,Urban,ML Engineer,54170,0 +13769,Female,30,High School,1,87,43,43,66,5.0,7,98,Urban,ML Engineer,37653,1 +13770,Male,36,Bachelors,7,32,74,98,11,6.0,1,48,Rural,HR Executive,83667,1 +13771,Male,35,High School,11,86,96,21,68,4.0,4,91,Urban,Data Analyst,53975,1 +13772,Female,59,Bachelors,18,32,24,89,55,6.0,4,2,Urban,Data Analyst,102825,0 +13773,Female,50,PhD,8,26,64,87,15,5.0,5,3,Semi-Urban,Manager,69784,0 +13774,Female,53,Bachelors,13,11,75,89,75,3.0,0,97,Urban,Software Engineer,104990,1 +13775,Female,41,Bachelors,15,44,52,55,25,8.0,6,47,Urban,Manager,47706,0 +13776,Female,33,Bachelors,1,16,19,21,21,9.0,5,28,Urban,HR Executive,134993,0 +13777,Male,54,Diploma,2,79,77,56,55,4.0,4,68,Rural,Data Analyst,84310,1 +13778,Male,22,Bachelors,12,64,24,88,2,2.0,4,10,Rural,ML Engineer,114919,0 +13779,Female,39,Masters,3,73,58,12,40,7.0,7,6,Semi-Urban,Software Engineer,38937,0 +13780,Female,47,PhD,16,76,60,78,99,4.0,1,39,Urban,HR Executive,46427,1 +13781,Other,27,Bachelors,6,81,28,71,27,9.0,4,31,Rural,ML Engineer,114319,0 +13782,Male,21,Bachelors,12,85,80,7,49,9.0,3,86,Urban,Data Analyst,147287,1 +13783,Male,24,Bachelors,11,18,34,22,0,8.0,3,28,Urban,Data Analyst,113960,0 +13784,Male,36,Bachelors,19,3,14,59,6,1.0,6,97,Semi-Urban,Manager,70138,0 +13785,Male,47,Masters,13,77,77,37,32,9.0,7,10,Urban,ML Engineer,55179,0 +13786,Male,27,Masters,2,85,40,96,47,3.0,1,80,Semi-Urban,Software Engineer,125136,1 +13787,Female,38,High School,15,10,43,25,62,7.0,6,64,Urban,Software Engineer,97467,0 +13788,Male,21,Bachelors,3,5,30,91,19,4.0,3,53,Urban,Software Engineer,80203,0 +13789,Female,21,Bachelors,18,12,32,27,2,2.0,1,66,Semi-Urban,ML Engineer,47116,0 +13790,Female,32,Diploma,13,45,38,9,41,8.0,3,13,Rural,HR Executive,78265,0 +13791,Male,31,PhD,17,32,92,92,49,4.0,2,27,Urban,Manager,55364,1 +13792,Male,26,Bachelors,17,32,25,3,13,0.0,4,76,Rural,HR Executive,136239,0 +13793,Female,43,High School,17,17,66,5,57,1.0,6,19,Semi-Urban,HR Executive,81383,0 +13794,Female,27,Diploma,16,28,45,67,75,3.0,4,15,Urban,Data Analyst,61974,0 +13795,Female,56,Diploma,19,94,87,14,62,2.0,4,67,Urban,Data Analyst,136584,1 +13796,Female,31,Diploma,14,11,58,50,75,7.0,1,94,Rural,Manager,35841,0 +13797,Other,21,Diploma,4,41,90,61,63,4.0,4,76,Urban,Manager,42960,1 +13798,Male,42,Bachelors,0,34,6,83,94,0.0,1,22,Rural,ML Engineer,36235,0 +13799,Female,51,Bachelors,0,24,18,42,62,5.0,4,44,Semi-Urban,HR Executive,89426,0 +13800,Female,34,High School,9,35,96,88,31,2.0,6,2,Rural,Software Engineer,44219,0 +13801,Female,30,Bachelors,6,28,53,96,89,8.0,2,93,Semi-Urban,HR Executive,112566,1 +13802,Male,56,Bachelors,9,16,97,36,67,9.0,5,58,Urban,Manager,77818,0 +13803,Other,53,Masters,19,44,14,80,92,1.0,4,12,Urban,Software Engineer,130796,0 +13804,Male,22,Bachelors,0,34,97,89,85,4.0,2,35,Semi-Urban,Data Analyst,89555,1 +13805,Female,35,Bachelors,4,43,58,65,90,5.0,5,21,Semi-Urban,Data Analyst,54359,0 +13806,Male,32,Diploma,8,0,72,87,84,8.0,6,38,Semi-Urban,HR Executive,139076,0 +13807,Male,28,Diploma,2,75,81,30,89,4.0,7,2,Urban,Data Analyst,95384,0 +13808,Male,58,Bachelors,0,4,9,63,98,5.0,0,51,Urban,Software Engineer,40906,0 +13809,Male,38,High School,3,58,42,72,41,8.0,1,87,Urban,Software Engineer,36983,1 +13810,Male,33,Bachelors,1,50,51,57,92,1.0,0,53,Urban,Software Engineer,77556,0 +13811,Female,47,Diploma,18,13,5,53,4,2.0,4,42,Urban,Manager,132105,0 +13812,Male,48,Bachelors,15,87,71,43,53,8.0,3,69,Rural,Software Engineer,33492,1 +13813,Male,23,Diploma,4,93,69,92,5,5.0,6,28,Urban,Manager,25074,1 +13814,Male,50,Bachelors,13,7,32,86,63,8.0,3,6,Urban,HR Executive,51928,0 +13815,Male,45,Masters,16,30,43,86,64,9.0,0,12,Urban,Manager,137513,0 +13816,Male,57,Diploma,7,94,64,87,12,9.0,5,8,Semi-Urban,Data Analyst,131125,1 +13817,Male,47,Bachelors,15,54,59,56,96,4.0,0,24,Urban,Software Engineer,42210,0 +13818,Male,35,Diploma,10,52,33,39,10,7.0,0,66,Urban,Software Engineer,95225,0 +13819,Female,58,Bachelors,9,38,14,40,23,4.0,1,91,Urban,ML Engineer,33336,0 +13820,Male,31,High School,5,14,39,62,93,6.0,4,43,Rural,HR Executive,22716,0 +13821,Male,52,Bachelors,15,95,60,35,65,4.0,1,65,Semi-Urban,HR Executive,62118,1 +13822,Male,27,High School,11,25,87,88,17,6.0,3,57,Rural,ML Engineer,137002,1 +13823,Other,37,High School,14,54,88,34,66,4.0,3,80,Urban,Software Engineer,27626,1 +13824,Male,29,Bachelors,14,75,58,49,47,6.0,6,51,Semi-Urban,Manager,53535,0 +13825,Male,59,Bachelors,10,73,46,67,69,5.0,2,11,Semi-Urban,Software Engineer,114683,0 +13826,Male,50,High School,10,40,75,96,62,2.0,0,65,Urban,HR Executive,128500,1 +13827,Male,54,Masters,0,86,23,68,61,1.0,2,70,Rural,Software Engineer,64346,1 +13828,Male,23,Bachelors,16,32,86,36,67,4.0,1,6,Urban,HR Executive,127891,0 +13829,Male,49,Diploma,8,15,84,79,24,6.0,7,64,Urban,Data Analyst,145234,1 +13830,Male,24,PhD,18,4,63,10,58,6.0,7,25,Rural,ML Engineer,134480,0 +13831,Male,44,Bachelors,19,22,32,32,20,2.0,1,60,Urban,Data Analyst,86016,0 +13832,Male,49,Bachelors,1,38,21,62,29,0.0,3,8,Urban,Manager,144489,0 +13833,Female,38,Bachelors,12,63,86,38,98,8.0,6,8,Urban,Manager,105092,0 +13834,Other,57,Bachelors,15,10,9,56,12,3.0,1,93,Urban,HR Executive,93648,0 +13835,Male,59,Diploma,3,76,65,99,4,0.0,1,58,Urban,ML Engineer,24314,1 +13836,Female,37,Bachelors,17,60,77,50,93,1.0,0,70,Semi-Urban,Software Engineer,84993,1 +13837,Other,59,Bachelors,10,75,34,72,17,5.0,3,55,Semi-Urban,Software Engineer,69626,0 +13838,Female,23,Masters,0,43,35,5,57,3.0,4,74,Urban,Software Engineer,74083,0 +13839,Male,35,Bachelors,8,14,74,33,63,6.0,0,7,Semi-Urban,ML Engineer,96423,0 +13840,Female,30,Bachelors,8,27,67,27,21,6.0,2,90,Urban,HR Executive,23007,0 +13841,Male,46,Masters,9,23,91,89,81,4.0,1,7,Urban,Manager,42109,0 +13842,Male,35,Bachelors,3,73,25,22,91,3.0,3,26,Semi-Urban,Software Engineer,71605,0 +13843,Male,56,Bachelors,10,17,27,14,43,4.0,1,54,Urban,Data Analyst,34468,0 +13844,Male,32,High School,4,39,31,21,27,8.0,1,25,Semi-Urban,HR Executive,59159,0 +13845,Male,48,Masters,3,12,40,25,18,0.0,6,34,Rural,HR Executive,32090,0 +13846,Male,38,Diploma,14,64,81,89,15,2.0,5,4,Rural,Software Engineer,109440,1 +13847,Female,23,Bachelors,10,58,69,80,8,9.0,0,11,Urban,Data Analyst,149923,0 +13848,Male,46,Bachelors,18,87,55,20,35,2.0,3,84,Urban,ML Engineer,126004,1 +13849,Male,47,Bachelors,2,38,7,73,2,0.0,4,72,Rural,Data Analyst,82082,0 +13850,Male,36,PhD,18,5,20,10,5,3.0,5,88,Urban,Manager,102220,0 +13851,Male,40,Masters,7,63,4,66,5,3.0,1,97,Urban,Software Engineer,118001,0 +13852,Male,47,Masters,5,70,80,97,93,6.0,5,32,Urban,Manager,113854,1 +13853,Other,39,High School,14,33,90,66,14,8.0,6,3,Urban,Manager,140471,0 +13854,Male,24,Bachelors,17,0,54,38,93,4.0,6,7,Urban,ML Engineer,98565,0 +13855,Male,59,Bachelors,5,17,17,12,40,4.0,5,59,Semi-Urban,Data Analyst,106099,0 +13856,Female,59,Masters,8,27,72,59,1,0.0,0,25,Rural,ML Engineer,80938,0 +13857,Male,57,Masters,14,59,43,36,4,9.0,7,69,Urban,ML Engineer,79021,0 +13858,Female,53,Bachelors,3,26,1,18,19,9.0,2,34,Rural,Software Engineer,94170,0 +13859,Male,21,Bachelors,6,97,63,5,19,5.0,4,35,Rural,Manager,26222,0 +13860,Male,22,High School,8,25,16,23,30,8.0,6,51,Rural,Data Analyst,38552,0 +13861,Male,52,Masters,1,22,73,2,8,0.0,4,70,Rural,Manager,125363,0 +13862,Male,45,Masters,13,36,9,97,53,0.0,3,63,Urban,Data Analyst,100730,0 +13863,Male,35,High School,17,64,26,2,1,3.0,3,58,Rural,Software Engineer,38198,0 +13864,Female,58,High School,16,28,40,89,14,0.0,0,43,Rural,HR Executive,20024,0 +13865,Female,54,High School,17,96,55,14,86,0.0,2,73,Urban,ML Engineer,120208,0 +13866,Female,34,PhD,16,78,61,50,72,0.0,5,57,Urban,Software Engineer,33125,1 +13867,Female,55,Bachelors,6,20,32,23,13,0.0,2,79,Rural,Manager,85029,0 +13868,Male,59,Bachelors,10,22,19,48,94,6.0,6,97,Urban,Manager,110411,0 +13869,Female,29,Masters,9,74,68,47,72,5.0,4,93,Urban,Software Engineer,32998,1 +13870,Male,58,Bachelors,19,52,2,18,8,3.0,1,35,Rural,Manager,83946,0 +13871,Female,51,Diploma,2,32,75,72,15,8.0,4,16,Urban,Software Engineer,46925,0 +13872,Male,36,Diploma,12,27,37,57,75,3.0,6,17,Semi-Urban,Manager,116966,0 +13873,Female,54,Bachelors,10,24,28,56,89,1.0,6,2,Semi-Urban,HR Executive,58829,0 +13874,Female,43,Diploma,7,16,31,13,37,4.0,3,74,Semi-Urban,Software Engineer,45235,0 +13875,Male,38,Masters,11,42,29,21,8,6.0,2,84,Urban,Software Engineer,84925,0 +13876,Male,30,Diploma,16,1,15,87,64,1.0,3,0,Semi-Urban,Data Analyst,117084,0 +13877,Male,29,High School,10,86,25,1,29,8.0,7,15,Semi-Urban,ML Engineer,120491,0 +13878,Male,41,Diploma,12,51,3,81,18,6.0,0,40,Urban,HR Executive,142875,0 +13879,Female,39,Bachelors,6,6,8,68,11,2.0,2,60,Urban,ML Engineer,74090,0 +13880,Other,31,Bachelors,17,77,96,75,98,8.0,3,39,Urban,Data Analyst,35172,1 +13881,Male,27,Diploma,1,26,58,2,76,5.0,6,81,Urban,Software Engineer,38041,0 +13882,Male,24,Bachelors,19,2,81,98,81,1.0,6,16,Rural,Manager,43634,0 +13883,Female,38,Diploma,13,37,9,2,68,5.0,7,62,Urban,Data Analyst,90771,0 +13884,Male,37,PhD,1,9,46,31,3,4.0,1,63,Semi-Urban,Data Analyst,39297,0 +13885,Male,49,Diploma,4,78,55,72,14,5.0,3,75,Rural,Manager,45750,1 +13886,Female,48,Masters,16,66,82,87,44,6.0,2,69,Semi-Urban,Data Analyst,38664,1 +13887,Female,55,PhD,15,61,31,19,46,3.0,2,66,Semi-Urban,ML Engineer,96617,0 +13888,Male,48,Bachelors,18,9,68,97,38,5.0,5,88,Rural,ML Engineer,41767,1 +13889,Male,24,Diploma,3,83,29,49,85,6.0,5,73,Urban,Manager,105093,0 +13890,Female,32,PhD,9,31,76,56,15,2.0,4,90,Rural,Data Analyst,108607,1 +13891,Female,47,Diploma,8,94,57,37,16,8.0,6,68,Semi-Urban,Software Engineer,29961,1 +13892,Female,50,Bachelors,1,62,8,97,37,7.0,2,24,Urban,Software Engineer,127060,0 +13893,Male,24,Bachelors,0,58,5,48,53,7.0,3,12,Urban,Manager,27265,0 +13894,Female,57,Masters,11,7,6,65,35,2.0,2,95,Semi-Urban,Manager,39663,0 +13895,Male,31,High School,13,80,97,9,10,8.0,7,87,Urban,Software Engineer,102874,1 +13896,Female,21,Masters,17,66,16,49,92,8.0,6,57,Semi-Urban,Data Analyst,99902,0 +13897,Male,47,Masters,3,36,85,35,98,3.0,2,13,Rural,ML Engineer,141022,0 +13898,Male,56,Diploma,5,15,52,78,13,6.0,3,79,Semi-Urban,Manager,35015,0 +13899,Other,34,Bachelors,16,98,7,93,98,7.0,3,78,Semi-Urban,Software Engineer,44347,1 +13900,Male,43,Masters,12,48,61,85,30,6.0,0,58,Semi-Urban,Software Engineer,92810,1 +13901,Male,46,Bachelors,6,79,94,31,66,6.0,2,20,Urban,Data Analyst,20482,0 +13902,Female,35,Bachelors,17,50,0,39,92,1.0,7,53,Semi-Urban,HR Executive,108851,0 +13903,Female,23,Diploma,13,64,41,30,91,1.0,6,87,Urban,ML Engineer,120884,0 +13904,Female,51,High School,6,20,50,51,35,4.0,7,33,Urban,Data Analyst,116443,0 +13905,Male,44,Masters,13,82,79,72,98,1.0,4,37,Semi-Urban,Manager,109695,1 +13906,Male,53,PhD,11,6,87,83,43,1.0,1,79,Rural,Data Analyst,128035,1 +13907,Female,47,Masters,14,91,1,41,82,6.0,4,41,Urban,Data Analyst,120062,0 +13908,Male,45,Bachelors,6,59,4,52,45,9.0,6,94,Urban,ML Engineer,94862,0 +13909,Female,59,Bachelors,19,73,79,72,74,9.0,7,91,Rural,Manager,105589,1 +13910,Male,36,Diploma,1,98,13,77,46,0.0,2,23,Rural,Data Analyst,45928,0 +13911,Female,26,Bachelors,4,27,74,81,93,1.0,4,36,Urban,HR Executive,147832,0 +13912,Male,30,Masters,5,81,24,39,57,6.0,0,6,Rural,ML Engineer,75927,0 +13913,Male,46,PhD,8,54,64,2,62,5.0,0,31,Semi-Urban,ML Engineer,76698,0 +13914,Female,26,Bachelors,18,77,20,32,94,3.0,6,71,Rural,Data Analyst,54237,0 +13915,Male,41,Diploma,0,70,9,87,13,5.0,7,8,Semi-Urban,HR Executive,112489,0 +13916,Female,42,Masters,2,59,77,56,39,3.0,0,56,Urban,Manager,63323,1 +13917,Female,29,Bachelors,15,40,24,12,62,0.0,7,35,Rural,ML Engineer,28246,0 +13918,Female,39,Masters,3,81,38,93,97,7.0,0,23,Semi-Urban,HR Executive,117326,0 +13919,Female,58,Masters,13,44,96,73,0,2.0,7,63,Rural,ML Engineer,27798,1 +13920,Male,48,Masters,5,65,84,51,85,0.0,1,93,Rural,HR Executive,47823,1 +13921,Male,33,Masters,7,45,20,81,75,7.0,0,37,Semi-Urban,Software Engineer,102653,0 +13922,Male,43,Diploma,17,4,95,52,34,1.0,7,31,Urban,Manager,32796,0 +13923,Male,49,Masters,15,91,9,82,6,8.0,7,85,Urban,Manager,129560,1 +13924,Male,32,Masters,19,48,61,29,66,3.0,5,20,Urban,Manager,133982,0 +13925,Male,44,Diploma,1,56,86,78,76,0.0,6,97,Rural,ML Engineer,28001,1 +13926,Male,44,High School,13,15,86,5,44,6.0,2,65,Urban,ML Engineer,90019,0 +13927,Male,25,Bachelors,5,48,85,54,41,7.0,7,90,Rural,HR Executive,139700,1 +13928,Male,29,Bachelors,9,39,5,15,6,8.0,7,5,Urban,Data Analyst,107052,0 +13929,Female,53,Bachelors,13,76,21,43,16,5.0,4,76,Rural,Manager,103008,0 +13930,Male,55,Bachelors,10,39,59,64,32,0.0,0,95,Rural,ML Engineer,95307,1 +13931,Male,39,Diploma,12,43,15,7,75,8.0,7,33,Rural,Software Engineer,27290,0 +13932,Female,48,Masters,19,46,1,50,50,1.0,4,85,Urban,Software Engineer,76400,0 +13933,Male,21,Diploma,13,51,81,29,68,7.0,2,78,Urban,Software Engineer,80929,1 +13934,Other,58,Bachelors,10,57,42,82,65,4.0,1,20,Urban,Software Engineer,77104,0 +13935,Female,48,Diploma,12,32,6,33,83,1.0,7,14,Semi-Urban,HR Executive,115305,0 +13936,Male,31,Bachelors,14,2,41,81,78,5.0,2,80,Rural,ML Engineer,39624,0 +13937,Female,41,Bachelors,8,26,30,26,8,6.0,0,76,Rural,Software Engineer,93667,0 +13938,Female,40,Bachelors,2,36,25,95,70,1.0,4,21,Urban,ML Engineer,117436,0 +13939,Male,27,High School,10,37,23,23,80,7.0,4,10,Urban,ML Engineer,58660,0 +13940,Female,21,Bachelors,10,55,81,91,80,4.0,0,21,Urban,Software Engineer,104577,1 +13941,Male,41,Bachelors,9,2,79,41,18,4.0,2,74,Urban,Software Engineer,99344,0 +13942,Male,27,Bachelors,6,31,28,27,63,8.0,6,82,Rural,Software Engineer,25231,0 +13943,Male,36,Bachelors,11,6,49,61,44,3.0,3,11,Urban,HR Executive,56677,0 +13944,Male,31,Bachelors,10,16,55,86,10,9.0,1,41,Urban,HR Executive,110828,0 +13945,Male,42,High School,9,42,67,49,35,4.0,0,87,Urban,HR Executive,137342,1 +13946,Female,34,Bachelors,3,34,15,39,47,5.0,1,58,Rural,Software Engineer,76561,0 +13947,Male,58,Bachelors,17,78,50,67,66,1.0,6,49,Semi-Urban,Software Engineer,99860,1 +13948,Male,22,High School,16,65,36,25,11,9.0,5,85,Semi-Urban,HR Executive,45629,0 +13949,Male,40,High School,10,49,17,63,26,7.0,4,79,Rural,Software Engineer,97670,0 +13950,Female,24,Bachelors,16,62,86,85,57,7.0,7,95,Rural,Data Analyst,98175,1 +13951,Other,50,Bachelors,10,96,14,11,16,3.0,4,65,Semi-Urban,ML Engineer,68296,0 +13952,Female,58,Bachelors,16,11,91,86,50,6.0,6,33,Urban,ML Engineer,30765,0 +13953,Other,48,Bachelors,13,15,97,55,74,4.0,4,41,Urban,Data Analyst,136799,0 +13954,Female,41,Diploma,9,95,68,60,24,4.0,5,74,Semi-Urban,Software Engineer,134570,1 +13955,Other,32,Diploma,17,76,56,63,13,0.0,5,54,Rural,HR Executive,49261,1 +13956,Female,53,Bachelors,1,30,28,50,75,8.0,4,42,Rural,Manager,35306,0 +13957,Male,23,Masters,9,91,81,62,56,7.0,4,35,Rural,ML Engineer,80319,1 +13958,Male,55,Bachelors,14,95,64,75,2,5.0,2,35,Rural,Manager,73266,1 +13959,Female,39,Masters,7,16,14,35,63,2.0,2,86,Rural,ML Engineer,108753,0 +13960,Male,21,Diploma,8,94,70,43,41,9.0,3,29,Urban,Manager,56092,1 +13961,Male,53,Diploma,8,21,13,44,23,8.0,3,19,Urban,HR Executive,131155,0 +13962,Male,50,Bachelors,3,59,95,43,71,4.0,0,75,Urban,HR Executive,99615,1 +13963,Female,21,Diploma,5,80,51,4,0,1.0,0,5,Urban,Data Analyst,34627,0 +13964,Male,24,Bachelors,5,80,71,30,14,7.0,5,24,Urban,Manager,64318,0 +13965,Female,24,Diploma,4,80,72,45,92,8.0,4,17,Urban,Manager,106853,0 +13966,Female,31,Bachelors,15,70,27,4,62,5.0,3,99,Semi-Urban,Data Analyst,77887,0 +13967,Other,24,High School,18,65,43,25,66,7.0,0,47,Urban,ML Engineer,148369,0 +13968,Female,36,Bachelors,9,15,79,65,39,1.0,0,4,Semi-Urban,ML Engineer,88812,0 +13969,Female,37,Bachelors,3,42,24,85,58,8.0,0,23,Urban,Data Analyst,140027,0 +13970,Male,52,Bachelors,2,94,25,21,36,1.0,6,25,Rural,Manager,72211,0 +13971,Male,41,Bachelors,15,88,15,80,9,6.0,3,90,Semi-Urban,Data Analyst,60486,1 +13972,Male,54,Masters,8,64,81,20,53,6.0,3,35,Urban,Data Analyst,133346,0 +13973,Female,21,High School,11,37,89,93,4,6.0,1,23,Semi-Urban,Data Analyst,35980,1 +13974,Female,40,High School,15,53,28,69,37,5.0,1,69,Urban,Manager,44755,0 +13975,Female,43,Masters,8,67,96,74,50,0.0,5,20,Semi-Urban,Manager,58506,1 +13976,Male,28,Diploma,13,34,77,39,49,5.0,5,16,Semi-Urban,Software Engineer,49690,0 +13977,Male,34,Masters,7,49,94,43,22,6.0,5,66,Urban,HR Executive,134845,1 +13978,Male,59,High School,13,48,92,15,97,8.0,3,19,Urban,HR Executive,21997,0 +13979,Male,29,PhD,7,50,80,23,45,3.0,2,37,Urban,Data Analyst,58539,0 +13980,Male,30,Bachelors,15,99,15,58,13,1.0,3,21,Semi-Urban,Manager,89853,0 +13981,Male,29,Bachelors,11,80,66,38,50,0.0,2,69,Rural,ML Engineer,76045,1 +13982,Female,56,PhD,17,57,15,2,60,4.0,3,80,Semi-Urban,HR Executive,75243,0 +13983,Male,41,Diploma,11,12,90,52,86,7.0,1,73,Urban,Software Engineer,99908,0 +13984,Male,36,Masters,4,95,50,39,7,6.0,6,33,Urban,Data Analyst,101548,0 +13985,Other,43,PhD,3,4,68,39,15,4.0,2,77,Urban,HR Executive,30341,0 +13986,Male,55,High School,8,58,36,73,51,3.0,2,2,Semi-Urban,Manager,126141,0 +13987,Male,49,Bachelors,0,61,78,6,90,8.0,5,45,Rural,Data Analyst,49667,0 +13988,Male,39,High School,12,96,56,60,81,0.0,7,47,Urban,ML Engineer,73828,1 +13989,Male,51,High School,0,6,40,46,55,1.0,2,68,Urban,Software Engineer,57669,0 +13990,Male,51,Bachelors,18,76,78,67,46,6.0,3,82,Rural,ML Engineer,55004,1 +13991,Male,37,High School,11,17,21,73,96,1.0,2,22,Semi-Urban,ML Engineer,94324,0 +13992,Male,46,Bachelors,1,87,86,20,76,1.0,2,18,Semi-Urban,HR Executive,63374,0 +13993,Male,37,Bachelors,13,55,59,27,33,2.0,6,72,Semi-Urban,ML Engineer,145516,0 +13994,Male,31,Masters,0,6,32,15,44,7.0,1,82,Semi-Urban,Software Engineer,99766,0 +13995,Female,33,Bachelors,15,22,29,54,71,4.0,7,10,Urban,Data Analyst,38929,0 +13996,Male,23,Bachelors,18,66,85,66,66,1.0,3,80,Urban,ML Engineer,71291,1 +13997,Female,38,Diploma,4,97,34,84,32,2.0,7,40,Urban,Manager,50326,1 +13998,Male,57,Diploma,0,34,49,42,30,8.0,6,78,Semi-Urban,Manager,88434,0 +13999,Male,49,Bachelors,9,53,38,78,96,5.0,2,39,Semi-Urban,ML Engineer,122594,0 +14000,Female,48,Bachelors,3,85,16,32,40,0.0,5,67,Urban,Software Engineer,94038,0 +14001,Male,46,Bachelors,8,74,4,60,31,0.0,5,14,Urban,HR Executive,95612,0 +14002,Male,55,Masters,14,58,63,70,32,0.0,6,70,Semi-Urban,Data Analyst,99452,1 +14003,Female,46,Masters,0,9,97,84,3,1.0,1,66,Urban,Data Analyst,128726,1 +14004,Male,55,Bachelors,10,35,47,33,71,0.0,5,66,Urban,Software Engineer,34959,0 +14005,Female,55,Bachelors,12,27,2,93,3,6.0,1,28,Urban,HR Executive,59825,0 +14006,Female,49,Masters,16,41,6,87,21,7.0,0,33,Urban,Data Analyst,31301,0 +14007,Male,25,Bachelors,6,41,2,30,98,1.0,7,35,Semi-Urban,Manager,110779,0 +14008,Male,49,Bachelors,16,18,39,93,14,2.0,0,74,Urban,Software Engineer,66300,0 +14009,Male,45,PhD,0,76,19,13,46,9.0,1,19,Semi-Urban,Software Engineer,40278,0 +14010,Other,52,Bachelors,14,44,44,30,74,6.0,1,94,Urban,Data Analyst,128121,0 +14011,Female,39,Bachelors,15,53,99,19,91,1.0,2,88,Urban,Manager,136292,1 +14012,Female,58,Bachelors,1,94,4,33,31,2.0,4,73,Rural,HR Executive,82804,0 +14013,Male,45,Bachelors,17,46,33,46,49,2.0,4,35,Semi-Urban,Software Engineer,26295,0 +14014,Female,51,Diploma,1,65,50,43,71,8.0,2,3,Semi-Urban,ML Engineer,62448,0 +14015,Male,45,Masters,13,33,85,99,35,4.0,6,31,Urban,Manager,97887,1 +14016,Male,30,Masters,8,13,46,57,49,9.0,6,32,Urban,Manager,43856,0 +14017,Female,57,Masters,11,92,65,36,7,1.0,3,93,Urban,HR Executive,50177,1 +14018,Male,41,Masters,16,45,31,75,73,4.0,4,8,Semi-Urban,Software Engineer,27126,0 +14019,Other,28,Masters,0,31,81,67,89,8.0,0,23,Semi-Urban,Software Engineer,135604,0 +14020,Male,26,High School,8,65,22,35,2,5.0,2,72,Urban,Data Analyst,72984,0 +14021,Female,27,Masters,2,35,2,47,18,5.0,4,24,Semi-Urban,HR Executive,71472,0 +14022,Male,50,High School,13,9,70,71,13,9.0,3,16,Urban,ML Engineer,96505,0 +14023,Male,44,Bachelors,17,71,2,23,7,0.0,2,57,Semi-Urban,HR Executive,28497,0 +14024,Male,28,High School,6,24,44,84,89,9.0,5,20,Urban,ML Engineer,127598,0 +14025,Male,28,High School,7,50,78,89,62,3.0,0,70,Urban,Software Engineer,125022,1 +14026,Male,51,Masters,10,93,82,67,83,3.0,0,92,Semi-Urban,Manager,81231,1 +14027,Female,24,Bachelors,10,4,7,95,79,6.0,2,31,Semi-Urban,Manager,44946,0 +14028,Male,56,Masters,12,16,4,31,38,9.0,4,99,Rural,ML Engineer,98881,0 +14029,Male,22,Diploma,14,4,2,26,99,3.0,5,48,Urban,Software Engineer,124042,0 +14030,Male,42,Masters,10,80,34,46,33,6.0,7,79,Urban,ML Engineer,80173,1 +14031,Male,41,Diploma,13,65,86,13,88,2.0,3,56,Urban,ML Engineer,101416,0 +14032,Female,55,Bachelors,11,39,21,17,2,2.0,3,0,Urban,Data Analyst,148570,0 +14033,Female,59,Diploma,14,73,50,82,34,6.0,7,13,Semi-Urban,Software Engineer,112678,0 +14034,Male,52,Bachelors,12,67,54,31,15,4.0,0,78,Urban,Data Analyst,131231,0 +14035,Male,25,Bachelors,8,99,85,40,22,3.0,0,6,Urban,ML Engineer,52204,0 +14036,Female,21,Masters,18,27,56,0,93,8.0,7,89,Semi-Urban,Software Engineer,136458,0 +14037,Male,51,Bachelors,0,77,75,94,66,6.0,0,33,Urban,HR Executive,70496,1 +14038,Male,46,Bachelors,0,41,31,10,79,0.0,7,97,Semi-Urban,Software Engineer,134138,0 +14039,Male,46,Diploma,14,16,79,33,81,7.0,3,22,Urban,Data Analyst,90534,0 +14040,Male,43,Bachelors,16,19,55,82,16,7.0,6,65,Urban,Software Engineer,84109,0 +14041,Male,37,Masters,13,3,47,62,35,9.0,7,42,Semi-Urban,HR Executive,97677,0 +14042,Male,55,Diploma,6,58,57,41,0,3.0,4,54,Urban,Software Engineer,80399,0 +14043,Female,39,Masters,12,21,10,46,75,9.0,6,94,Rural,ML Engineer,28247,0 +14044,Male,23,Diploma,3,87,65,21,39,3.0,6,86,Urban,HR Executive,116971,1 +14045,Male,25,Bachelors,0,56,72,40,80,6.0,0,87,Rural,Data Analyst,50681,1 +14046,Male,49,Bachelors,2,19,67,52,57,0.0,2,4,Urban,ML Engineer,141371,0 +14047,Male,45,Diploma,11,48,92,44,94,1.0,2,59,Urban,Data Analyst,115154,1 +14048,Male,48,Bachelors,11,86,66,94,49,0.0,3,82,Urban,Manager,43819,1 +14049,Female,49,Diploma,6,12,91,31,75,3.0,0,51,Urban,HR Executive,25549,0 +14050,Male,55,Masters,4,94,70,63,29,8.0,6,92,Urban,Data Analyst,83660,1 +14051,Female,29,High School,8,4,72,7,75,0.0,2,72,Rural,HR Executive,81850,0 +14052,Male,30,Bachelors,4,64,10,13,40,2.0,6,7,Rural,HR Executive,136860,0 +14053,Female,36,Diploma,2,76,85,81,75,9.0,4,64,Semi-Urban,Software Engineer,51249,1 +14054,Male,51,Diploma,12,41,0,63,65,2.0,2,90,Semi-Urban,Manager,38968,0 +14055,Male,35,PhD,7,43,48,5,18,3.0,3,86,Semi-Urban,Software Engineer,146919,0 +14056,Female,39,Diploma,1,39,26,14,46,3.0,2,31,Urban,Software Engineer,99259,0 +14057,Male,40,Bachelors,12,10,93,90,56,7.0,6,55,Urban,Software Engineer,24917,1 +14058,Female,59,Bachelors,1,44,91,52,9,3.0,5,36,Semi-Urban,HR Executive,101012,0 +14059,Male,37,Bachelors,3,52,2,85,97,0.0,1,21,Urban,Manager,132428,0 +14060,Other,39,PhD,8,62,51,10,8,4.0,2,38,Semi-Urban,Data Analyst,60960,0 +14061,Female,55,Diploma,6,2,0,22,41,6.0,1,95,Urban,ML Engineer,99903,0 +14062,Other,56,Masters,17,25,60,23,66,2.0,3,46,Semi-Urban,HR Executive,68339,0 +14063,Male,57,Bachelors,12,60,64,30,83,2.0,3,36,Urban,Data Analyst,149231,0 +14064,Male,57,PhD,8,48,40,59,29,0.0,7,29,Semi-Urban,Manager,100132,0 +14065,Female,50,Diploma,0,55,60,0,62,7.0,6,50,Urban,Manager,128235,0 +14066,Female,38,Masters,5,15,30,28,73,8.0,1,8,Rural,ML Engineer,144965,0 +14067,Other,49,Bachelors,7,4,90,27,88,2.0,4,90,Semi-Urban,ML Engineer,73672,0 +14068,Male,45,Masters,8,38,93,7,78,2.0,6,52,Urban,Data Analyst,95219,0 +14069,Female,29,Bachelors,15,2,25,2,32,0.0,0,30,Urban,HR Executive,139557,0 +14070,Male,56,Diploma,15,2,19,46,49,9.0,3,14,Urban,Data Analyst,113138,0 +14071,Male,55,Masters,17,99,54,62,86,8.0,2,2,Urban,HR Executive,140364,0 +14072,Male,53,Bachelors,2,44,32,32,31,3.0,0,12,Semi-Urban,Software Engineer,143924,0 +14073,Male,24,Masters,19,16,94,71,35,0.0,6,5,Urban,ML Engineer,113447,0 +14074,Female,45,Bachelors,11,80,56,31,29,0.0,5,58,Urban,Data Analyst,61045,0 +14075,Male,59,Bachelors,11,39,97,35,30,6.0,6,72,Urban,ML Engineer,84929,1 +14076,Female,29,Masters,11,86,14,11,97,5.0,7,85,Urban,ML Engineer,103859,0 +14077,Male,22,Bachelors,12,4,31,44,20,3.0,5,49,Rural,Manager,38621,0 +14078,Male,45,High School,19,76,94,59,78,2.0,4,32,Urban,Software Engineer,31565,1 +14079,Male,58,Bachelors,13,23,76,2,55,6.0,0,52,Urban,Manager,46673,0 +14080,Male,34,Diploma,5,94,12,45,93,8.0,1,56,Rural,Manager,41931,0 +14081,Male,39,High School,2,74,24,12,48,2.0,1,61,Rural,HR Executive,106462,0 +14082,Female,45,High School,11,79,46,35,96,5.0,7,77,Urban,ML Engineer,134975,0 +14083,Other,59,Bachelors,9,54,47,44,2,1.0,7,76,Rural,Software Engineer,90319,0 +14084,Male,22,Diploma,4,77,22,16,62,4.0,5,15,Urban,HR Executive,107539,0 +14085,Male,30,Diploma,0,99,50,83,28,1.0,3,66,Semi-Urban,Software Engineer,75490,1 +14086,Male,23,Diploma,3,33,88,39,6,3.0,6,40,Urban,Software Engineer,53991,0 +14087,Female,47,Diploma,5,75,87,40,80,0.0,4,72,Semi-Urban,Software Engineer,70186,1 +14088,Male,50,PhD,3,43,20,44,46,2.0,6,84,Rural,Data Analyst,138387,0 +14089,Male,55,Bachelors,5,7,51,83,24,5.0,4,68,Urban,Manager,95003,0 +14090,Male,38,Diploma,14,82,87,28,89,8.0,7,33,Rural,HR Executive,46833,0 +14091,Other,47,Bachelors,18,8,19,82,35,5.0,0,11,Rural,Data Analyst,21671,0 +14092,Male,39,Diploma,10,66,81,38,39,6.0,3,26,Urban,HR Executive,61376,0 +14093,Male,37,Diploma,6,61,97,69,76,4.0,5,99,Urban,Data Analyst,149102,1 +14094,Other,24,Masters,4,45,1,82,64,0.0,0,47,Urban,Software Engineer,73380,0 +14095,Female,56,High School,0,19,33,89,27,6.0,7,44,Urban,ML Engineer,75503,0 +14096,Female,41,Bachelors,18,39,72,24,37,2.0,2,25,Urban,Manager,32022,0 +14097,Male,31,Bachelors,8,2,11,10,39,9.0,5,55,Semi-Urban,ML Engineer,51552,0 +14098,Other,36,High School,7,89,72,90,56,5.0,0,1,Urban,HR Executive,98336,1 +14099,Female,38,High School,3,27,78,32,4,2.0,7,96,Urban,HR Executive,102852,0 +14100,Female,37,High School,9,57,30,68,26,3.0,4,0,Urban,ML Engineer,25853,0 +14101,Female,34,Diploma,2,7,62,36,33,8.0,3,54,Rural,Software Engineer,143296,0 +14102,Female,34,Bachelors,2,22,53,58,73,1.0,2,98,Urban,Software Engineer,29332,0 +14103,Male,54,Bachelors,8,91,1,29,32,3.0,3,57,Semi-Urban,Manager,62300,0 +14104,Male,22,Bachelors,13,47,3,63,73,9.0,5,74,Urban,ML Engineer,125414,0 +14105,Female,55,Bachelors,3,31,77,1,81,4.0,2,0,Urban,Manager,110356,0 +14106,Male,36,Masters,3,5,42,47,25,1.0,5,24,Urban,Software Engineer,141337,0 +14107,Male,56,Diploma,13,48,32,31,77,5.0,5,9,Rural,Software Engineer,127756,0 +14108,Male,48,Bachelors,13,34,44,91,45,8.0,2,98,Semi-Urban,Data Analyst,54365,1 +14109,Female,32,High School,5,59,52,65,27,0.0,7,23,Urban,HR Executive,60251,0 +14110,Male,49,Diploma,9,98,30,56,20,7.0,7,14,Urban,HR Executive,57657,0 +14111,Female,29,Masters,15,88,58,42,11,3.0,1,70,Urban,Data Analyst,61454,1 +14112,Female,39,Masters,2,11,34,65,14,5.0,4,39,Rural,Software Engineer,122692,0 +14113,Male,24,Masters,16,90,90,55,9,2.0,5,62,Urban,Software Engineer,104002,1 +14114,Male,30,Bachelors,5,25,97,76,20,8.0,6,15,Semi-Urban,Manager,60216,0 +14115,Male,29,High School,3,72,39,69,50,0.0,6,86,Urban,Manager,117578,1 +14116,Male,49,Diploma,9,35,56,39,85,4.0,4,50,Urban,ML Engineer,120080,0 +14117,Male,46,High School,9,64,46,47,37,1.0,4,16,Urban,HR Executive,101921,0 +14118,Male,48,High School,7,95,6,59,9,0.0,6,39,Semi-Urban,ML Engineer,27459,0 +14119,Other,44,Diploma,5,15,78,58,2,4.0,2,41,Urban,Manager,123345,0 +14120,Male,51,Masters,3,63,1,85,88,1.0,2,60,Urban,Software Engineer,50773,0 +14121,Female,26,Bachelors,14,75,61,85,47,6.0,6,5,Semi-Urban,Manager,149416,0 +14122,Male,55,Diploma,0,77,13,23,19,8.0,5,17,Urban,Software Engineer,138853,0 +14123,Female,33,PhD,5,18,7,74,77,2.0,0,86,Urban,Manager,83036,0 +14124,Male,56,PhD,4,25,96,91,51,0.0,1,61,Rural,Manager,90584,1 +14125,Female,49,Diploma,11,37,59,83,17,3.0,3,23,Semi-Urban,Manager,114732,0 +14126,Female,50,Bachelors,15,73,24,17,19,5.0,3,65,Rural,ML Engineer,67263,0 +14127,Female,34,Diploma,15,93,93,84,50,6.0,4,49,Urban,ML Engineer,144833,1 +14128,Male,42,Bachelors,19,21,5,26,93,9.0,0,13,Rural,Data Analyst,81162,0 +14129,Female,48,Masters,13,1,96,67,47,9.0,7,87,Urban,Software Engineer,41079,1 +14130,Male,35,Bachelors,12,40,3,50,44,5.0,4,51,Urban,Software Engineer,62909,0 +14131,Male,26,Masters,19,15,98,0,82,8.0,4,22,Semi-Urban,HR Executive,95208,0 +14132,Male,34,High School,3,1,0,89,44,9.0,5,93,Urban,Data Analyst,55812,0 +14133,Male,48,High School,8,56,77,18,39,8.0,2,59,Urban,Data Analyst,29936,0 +14134,Male,50,Bachelors,15,52,74,68,97,3.0,3,4,Urban,Software Engineer,26478,0 +14135,Female,50,Diploma,3,2,13,50,36,9.0,2,23,Urban,Data Analyst,40020,0 +14136,Male,21,Masters,17,62,50,13,68,1.0,2,62,Urban,Data Analyst,67424,0 +14137,Male,28,Diploma,19,28,3,69,81,6.0,0,47,Semi-Urban,HR Executive,57389,0 +14138,Male,43,Bachelors,13,11,76,36,55,9.0,5,52,Semi-Urban,ML Engineer,68851,0 +14139,Female,57,High School,5,98,84,40,7,6.0,4,66,Semi-Urban,Manager,76936,1 +14140,Male,33,Bachelors,16,20,96,17,11,1.0,5,86,Urban,Software Engineer,143895,0 +14141,Male,44,Bachelors,7,25,97,71,74,1.0,3,74,Urban,HR Executive,118081,1 +14142,Female,42,PhD,10,2,23,92,72,4.0,4,13,Urban,Software Engineer,26248,0 +14143,Male,21,Diploma,9,34,78,68,39,6.0,7,10,Urban,Manager,39453,0 +14144,Male,24,Masters,1,95,86,10,63,7.0,2,75,Semi-Urban,Data Analyst,116469,1 +14145,Male,40,Bachelors,17,83,77,26,49,4.0,0,17,Semi-Urban,Data Analyst,102894,0 +14146,Female,37,Bachelors,8,47,47,47,49,1.0,2,78,Semi-Urban,ML Engineer,82430,0 +14147,Female,30,Bachelors,6,60,13,13,49,6.0,7,37,Rural,Manager,108819,0 +14148,Male,37,Bachelors,11,74,41,14,45,1.0,4,87,Urban,HR Executive,97261,0 +14149,Male,38,Diploma,13,7,52,60,32,0.0,2,82,Semi-Urban,HR Executive,51480,0 +14150,Male,55,Masters,2,85,81,55,80,8.0,5,41,Urban,HR Executive,130645,1 +14151,Female,40,Bachelors,18,96,15,56,25,8.0,6,59,Urban,Data Analyst,22192,0 +14152,Female,33,Masters,4,25,78,50,50,5.0,4,47,Urban,Manager,96751,0 +14153,Male,28,High School,14,39,97,14,75,1.0,4,19,Urban,Manager,33911,0 +14154,Male,55,Diploma,13,81,49,6,69,8.0,7,77,Semi-Urban,Data Analyst,54983,0 +14155,Female,53,Bachelors,10,32,91,49,83,4.0,5,43,Urban,HR Executive,45707,0 +14156,Female,39,Bachelors,17,11,18,31,46,0.0,0,72,Urban,HR Executive,51805,0 +14157,Female,45,Bachelors,15,18,68,75,60,3.0,0,46,Rural,ML Engineer,90616,0 +14158,Female,22,High School,18,84,48,91,4,2.0,1,81,Urban,HR Executive,63653,1 +14159,Female,26,High School,16,28,91,79,28,5.0,3,23,Semi-Urban,Software Engineer,43495,0 +14160,Male,55,Bachelors,19,64,62,99,82,2.0,0,77,Urban,Data Analyst,25060,1 +14161,Male,22,Bachelors,16,44,87,7,56,2.0,1,56,Rural,Data Analyst,141536,0 +14162,Male,28,High School,11,78,31,88,9,6.0,4,27,Urban,Data Analyst,53540,0 +14163,Female,28,Bachelors,2,70,10,43,35,3.0,5,15,Rural,Software Engineer,52216,0 +14164,Male,56,Bachelors,1,54,90,66,74,2.0,3,49,Urban,HR Executive,99847,1 +14165,Male,59,Diploma,2,66,17,18,42,1.0,4,34,Urban,ML Engineer,33599,0 +14166,Male,56,Masters,11,1,25,49,55,0.0,6,37,Urban,Software Engineer,47295,0 +14167,Male,41,Bachelors,13,66,24,51,48,0.0,0,48,Urban,Data Analyst,92770,0 +14168,Female,45,High School,18,72,43,49,13,5.0,4,23,Rural,Data Analyst,37219,0 +14169,Male,54,Bachelors,19,62,3,44,39,2.0,3,70,Urban,Manager,90855,0 +14170,Male,51,Diploma,18,69,82,13,2,1.0,4,36,Urban,Software Engineer,109254,0 +14171,Female,37,Bachelors,0,23,48,98,27,5.0,0,12,Urban,Manager,137420,0 +14172,Male,50,High School,13,5,55,43,1,7.0,1,64,Urban,Software Engineer,94296,0 +14173,Female,38,High School,16,32,7,93,21,6.0,4,43,Urban,ML Engineer,22770,0 +14174,Female,49,Bachelors,15,17,55,16,10,7.0,5,11,Urban,Data Analyst,62960,0 +14175,Female,42,Bachelors,13,93,63,75,73,3.0,7,88,Rural,ML Engineer,65037,1 +14176,Female,57,Bachelors,18,91,10,17,4,4.0,4,14,Urban,Data Analyst,36861,0 +14177,Male,39,High School,3,85,52,22,71,3.0,0,19,Semi-Urban,HR Executive,24941,0 +14178,Male,36,High School,13,14,76,80,84,1.0,4,40,Urban,ML Engineer,48287,0 +14179,Male,24,Diploma,18,40,66,61,32,6.0,4,53,Semi-Urban,Data Analyst,105872,0 +14180,Male,58,PhD,18,25,33,29,64,6.0,4,4,Urban,Manager,110360,0 +14181,Male,56,Bachelors,18,35,47,10,44,0.0,6,20,Urban,Data Analyst,47092,0 +14182,Male,21,Diploma,4,15,70,79,56,3.0,5,7,Urban,HR Executive,92763,0 +14183,Female,54,Diploma,14,54,86,8,71,3.0,7,94,Urban,Data Analyst,88670,1 +14184,Male,51,Bachelors,1,67,4,59,58,2.0,3,55,Semi-Urban,HR Executive,88708,0 +14185,Male,55,PhD,16,99,37,21,96,3.0,7,95,Urban,Manager,44739,1 +14186,Male,31,Bachelors,0,49,27,12,66,1.0,0,41,Semi-Urban,Data Analyst,95994,0 +14187,Male,38,Diploma,1,94,97,99,19,6.0,5,60,Semi-Urban,ML Engineer,28243,1 +14188,Other,26,Bachelors,13,32,40,76,39,2.0,6,28,Urban,Manager,56062,0 +14189,Male,45,Bachelors,11,7,39,90,62,1.0,6,73,Semi-Urban,Software Engineer,84290,0 +14190,Female,31,High School,3,9,34,51,2,2.0,7,5,Semi-Urban,Manager,79624,0 +14191,Male,55,Bachelors,6,13,3,14,74,7.0,3,97,Urban,Software Engineer,133855,0 +14192,Male,34,Bachelors,14,24,49,71,58,7.0,2,75,Urban,HR Executive,40772,0 +14193,Male,51,Masters,14,53,97,19,53,5.0,7,68,Urban,Data Analyst,107237,1 +14194,Female,50,Diploma,12,11,77,76,39,1.0,3,2,Semi-Urban,Software Engineer,118003,0 +14195,Male,41,High School,2,42,75,57,92,0.0,3,72,Urban,ML Engineer,69025,1 +14196,Male,23,Diploma,6,77,23,28,86,8.0,3,67,Semi-Urban,Data Analyst,125097,0 +14197,Male,41,Bachelors,4,39,7,69,70,9.0,2,15,Urban,HR Executive,39809,0 +14198,Female,43,Bachelors,19,59,85,52,8,2.0,7,30,Urban,Manager,51297,0 +14199,Female,30,High School,6,63,83,31,96,2.0,4,89,Semi-Urban,HR Executive,98521,1 +14200,Male,52,Bachelors,15,42,75,83,8,4.0,6,79,Semi-Urban,Manager,143607,1 +14201,Male,54,High School,13,40,98,50,31,9.0,0,88,Urban,ML Engineer,53169,1 +14202,Female,31,Masters,2,37,4,40,92,1.0,5,26,Semi-Urban,ML Engineer,64109,0 +14203,Female,47,Diploma,3,58,15,59,21,2.0,6,99,Urban,Manager,29325,0 +14204,Female,49,Masters,18,73,83,94,33,9.0,6,22,Semi-Urban,Software Engineer,57915,1 +14205,Female,23,Diploma,11,83,51,96,42,1.0,4,72,Urban,HR Executive,148612,1 +14206,Female,44,Bachelors,17,12,38,2,64,0.0,1,89,Urban,ML Engineer,52878,0 +14207,Male,47,Diploma,17,61,29,60,5,6.0,2,30,Rural,HR Executive,136198,0 +14208,Female,36,High School,10,94,63,91,29,0.0,2,29,Rural,Manager,55785,1 +14209,Female,35,Bachelors,18,4,98,28,31,3.0,5,3,Semi-Urban,HR Executive,64174,0 +14210,Male,39,Bachelors,2,76,33,9,36,1.0,2,64,Urban,HR Executive,81394,0 +14211,Male,48,High School,16,86,15,47,0,3.0,6,55,Rural,ML Engineer,29726,0 +14212,Other,26,Diploma,9,98,43,50,68,2.0,3,2,Urban,Data Analyst,80191,0 +14213,Male,21,Diploma,8,72,63,68,41,5.0,0,10,Urban,ML Engineer,52987,0 +14214,Female,21,Diploma,10,76,35,6,64,0.0,2,30,Urban,Data Analyst,113420,0 +14215,Male,58,Bachelors,12,57,45,25,85,6.0,2,24,Rural,HR Executive,71439,0 +14216,Male,40,High School,4,32,9,44,4,5.0,4,29,Urban,HR Executive,72506,0 +14217,Male,27,Bachelors,4,89,79,0,81,1.0,7,27,Urban,ML Engineer,94237,0 +14218,Male,48,Bachelors,13,30,85,78,79,8.0,2,83,Urban,Software Engineer,54116,1 +14219,Male,22,Masters,14,4,62,41,74,8.0,1,55,Rural,Software Engineer,34339,0 +14220,Male,25,Bachelors,7,43,81,31,55,6.0,3,43,Semi-Urban,Manager,127663,0 +14221,Female,27,PhD,14,24,24,11,22,4.0,2,46,Rural,Data Analyst,85242,0 +14222,Other,28,Diploma,10,67,63,19,95,3.0,5,12,Urban,ML Engineer,71706,0 +14223,Male,48,Bachelors,14,91,80,58,87,1.0,7,60,Rural,HR Executive,120400,1 +14224,Male,45,Masters,5,38,25,64,5,4.0,7,81,Semi-Urban,Manager,58781,0 +14225,Male,43,High School,9,5,77,72,16,1.0,4,52,Urban,Software Engineer,106537,0 +14226,Male,42,High School,10,74,39,78,41,7.0,3,50,Urban,Software Engineer,87253,1 +14227,Male,45,Bachelors,8,15,28,85,44,9.0,3,40,Urban,Data Analyst,35952,0 +14228,Male,21,Masters,15,97,98,55,85,9.0,1,98,Rural,ML Engineer,52639,1 +14229,Male,53,Masters,12,16,49,75,18,5.0,1,32,Semi-Urban,Data Analyst,42055,0 +14230,Male,53,Bachelors,7,39,46,3,81,4.0,1,11,Urban,ML Engineer,134363,0 +14231,Male,34,Masters,10,54,28,10,50,8.0,5,85,Semi-Urban,HR Executive,46713,0 +14232,Female,21,Diploma,4,61,79,4,13,7.0,5,81,Urban,Manager,75200,0 +14233,Male,59,Diploma,19,85,38,49,13,7.0,0,46,Semi-Urban,Manager,143037,0 +14234,Female,44,Bachelors,18,67,76,76,70,1.0,2,42,Rural,HR Executive,78774,1 +14235,Female,32,Diploma,9,76,21,3,14,8.0,3,15,Urban,ML Engineer,118692,0 +14236,Other,33,Bachelors,12,21,40,76,1,2.0,2,51,Urban,Software Engineer,81663,0 +14237,Female,43,Bachelors,3,66,22,25,3,7.0,3,12,Urban,ML Engineer,137151,0 +14238,Male,24,Masters,10,52,60,97,76,4.0,7,8,Urban,Software Engineer,110363,0 +14239,Male,54,Masters,18,16,93,96,33,6.0,4,2,Semi-Urban,HR Executive,127760,0 +14240,Male,58,Masters,15,22,83,74,76,3.0,6,33,Urban,ML Engineer,112596,0 +14241,Female,47,Masters,7,69,65,94,38,8.0,5,76,Rural,HR Executive,132545,1 +14242,Female,52,Bachelors,6,99,28,11,29,3.0,7,90,Urban,HR Executive,21112,0 +14243,Female,47,Bachelors,13,30,71,4,55,5.0,1,97,Urban,Manager,118683,0 +14244,Male,21,Diploma,11,37,91,43,21,7.0,1,40,Urban,Manager,80357,0 +14245,Female,32,Masters,19,31,96,18,0,0.0,4,77,Semi-Urban,Software Engineer,66549,0 +14246,Male,27,Bachelors,13,10,36,84,78,5.0,1,47,Urban,ML Engineer,138903,0 +14247,Male,59,Bachelors,3,13,43,17,24,8.0,5,12,Urban,ML Engineer,42505,0 +14248,Female,27,Masters,7,63,12,89,50,8.0,4,89,Urban,HR Executive,46557,1 +14249,Male,36,High School,10,65,56,66,60,7.0,7,56,Urban,Data Analyst,38579,1 +14250,Other,48,Masters,9,29,39,50,96,0.0,3,97,Rural,HR Executive,96503,0 +14251,Male,54,Masters,6,30,79,70,94,8.0,6,83,Urban,Software Engineer,86777,1 +14252,Female,29,PhD,8,86,88,49,98,1.0,7,81,Semi-Urban,Manager,65346,1 +14253,Male,57,High School,5,67,89,6,44,1.0,1,13,Urban,Manager,66816,0 +14254,Female,42,Bachelors,1,82,14,9,13,6.0,1,0,Urban,Software Engineer,145930,0 +14255,Female,32,Bachelors,1,35,16,25,96,2.0,2,62,Urban,Manager,148018,0 +14256,Female,27,High School,8,45,41,15,44,0.0,2,67,Urban,HR Executive,39755,0 +14257,Male,46,Diploma,19,62,0,41,46,8.0,7,90,Semi-Urban,Software Engineer,57578,0 +14258,Female,57,Masters,11,29,57,27,81,6.0,4,29,Rural,ML Engineer,36518,0 +14259,Male,26,Masters,19,49,3,24,14,5.0,1,13,Urban,Software Engineer,136549,0 +14260,Male,47,High School,0,99,14,65,56,8.0,0,21,Semi-Urban,HR Executive,136223,0 +14261,Male,47,Masters,18,19,73,74,53,9.0,4,65,Urban,Manager,125408,0 +14262,Female,49,Masters,5,16,52,22,56,6.0,5,16,Urban,ML Engineer,33150,0 +14263,Male,54,Masters,11,61,17,17,30,4.0,5,14,Urban,HR Executive,28720,0 +14264,Female,56,High School,12,58,61,29,77,0.0,4,63,Semi-Urban,Software Engineer,79417,0 +14265,Female,51,Masters,10,11,40,98,30,2.0,6,36,Urban,Software Engineer,31565,0 +14266,Male,49,High School,8,46,39,46,68,2.0,0,56,Urban,Manager,62281,0 +14267,Female,42,Bachelors,5,45,2,45,91,4.0,2,32,Rural,ML Engineer,61256,0 +14268,Male,27,Diploma,7,78,46,94,62,8.0,5,16,Rural,Software Engineer,49892,0 +14269,Female,29,Bachelors,0,67,80,87,91,8.0,0,85,Urban,ML Engineer,70142,1 +14270,Male,38,Masters,14,24,53,48,48,5.0,5,17,Urban,HR Executive,81416,0 +14271,Male,32,Diploma,12,5,65,45,1,5.0,0,52,Rural,ML Engineer,50637,0 +14272,Male,39,High School,13,39,64,91,97,8.0,2,44,Semi-Urban,Data Analyst,109347,1 +14273,Male,55,PhD,13,46,80,38,9,3.0,2,79,Semi-Urban,Manager,87621,1 +14274,Male,23,Masters,18,82,84,63,94,5.0,2,73,Semi-Urban,Manager,148021,1 +14275,Male,52,Masters,0,16,49,89,88,8.0,1,40,Urban,ML Engineer,38416,0 +14276,Male,28,Bachelors,9,9,25,52,83,1.0,7,79,Urban,Data Analyst,97065,0 +14277,Male,22,Bachelors,8,81,82,9,56,4.0,1,55,Urban,HR Executive,108464,0 +14278,Male,30,High School,10,41,55,90,99,3.0,1,36,Urban,Software Engineer,130370,0 +14279,Female,55,Bachelors,5,54,1,51,2,2.0,2,29,Urban,Software Engineer,69963,0 +14280,Male,31,Masters,15,30,66,63,89,3.0,5,46,Rural,Manager,57789,0 +14281,Female,48,Diploma,8,46,78,44,42,4.0,1,63,Urban,Data Analyst,142071,0 +14282,Female,36,Bachelors,18,19,80,93,40,6.0,2,17,Semi-Urban,Data Analyst,39248,0 +14283,Female,57,Bachelors,3,53,17,10,89,3.0,6,52,Urban,Data Analyst,135207,0 +14284,Female,51,Masters,9,91,23,21,70,0.0,7,57,Urban,Manager,134930,0 +14285,Male,47,Bachelors,1,73,95,18,32,3.0,2,78,Urban,HR Executive,30460,1 +14286,Female,52,High School,5,6,79,1,41,0.0,5,64,Semi-Urban,Manager,46325,0 +14287,Male,52,Masters,8,40,84,46,54,9.0,2,62,Urban,Data Analyst,61276,0 +14288,Female,28,Bachelors,2,65,3,60,26,6.0,7,91,Rural,Manager,105600,0 +14289,Female,23,Masters,16,55,49,5,65,6.0,0,97,Semi-Urban,Data Analyst,107376,0 +14290,Male,57,Bachelors,15,11,1,89,97,7.0,1,62,Urban,HR Executive,95364,0 +14291,Female,34,Masters,17,88,99,32,78,2.0,7,32,Semi-Urban,HR Executive,49507,1 +14292,Male,33,Bachelors,11,42,92,80,61,4.0,3,41,Urban,Software Engineer,146378,1 +14293,Male,32,Diploma,6,73,59,12,92,3.0,3,83,Urban,HR Executive,29531,0 +14294,Male,58,Masters,19,29,56,19,3,9.0,7,99,Urban,Data Analyst,78931,0 +14295,Female,38,Bachelors,12,81,79,75,23,8.0,1,34,Urban,Software Engineer,119973,1 +14296,Female,23,Diploma,4,94,2,48,23,7.0,2,54,Semi-Urban,Data Analyst,108533,0 +14297,Female,25,Bachelors,9,94,52,46,13,3.0,2,1,Rural,Manager,81613,0 +14298,Male,29,PhD,2,1,72,70,95,8.0,1,68,Semi-Urban,ML Engineer,102256,0 +14299,Male,25,Bachelors,1,0,85,54,48,8.0,2,51,Urban,Manager,59260,0 +14300,Female,59,Bachelors,8,10,69,0,92,3.0,6,43,Urban,Software Engineer,29074,0 +14301,Male,35,Bachelors,4,99,12,50,83,9.0,2,70,Rural,Software Engineer,114581,0 +14302,Female,59,Bachelors,1,69,1,16,27,0.0,2,13,Urban,Data Analyst,137490,0 +14303,Male,42,Masters,0,21,18,90,0,1.0,6,69,Urban,ML Engineer,22195,0 +14304,Male,51,Diploma,0,75,47,97,63,4.0,2,13,Urban,Manager,26782,0 +14305,Male,41,Bachelors,1,36,64,96,55,3.0,7,51,Urban,Manager,149571,1 +14306,Female,25,High School,18,1,19,22,43,3.0,1,22,Urban,Data Analyst,67325,0 +14307,Male,52,Bachelors,0,17,69,46,84,0.0,1,98,Urban,Software Engineer,22510,0 +14308,Male,31,High School,0,43,47,95,98,5.0,4,48,Urban,Software Engineer,77242,0 +14309,Male,36,Bachelors,13,1,88,65,40,2.0,1,53,Rural,Manager,117274,0 +14310,Male,46,High School,4,77,10,93,79,6.0,4,11,Urban,ML Engineer,112223,0 +14311,Male,52,Masters,16,29,81,18,81,4.0,0,79,Semi-Urban,Manager,50130,0 +14312,Male,51,Masters,9,28,82,21,45,0.0,7,75,Urban,HR Executive,48012,0 +14313,Female,36,Masters,19,43,53,31,39,4.0,5,69,Semi-Urban,Data Analyst,91666,0 +14314,Male,52,Diploma,17,25,57,31,19,6.0,5,4,Semi-Urban,Software Engineer,149355,0 +14315,Female,48,Diploma,13,4,27,42,81,5.0,2,94,Rural,ML Engineer,20251,0 +14316,Female,23,Diploma,17,6,4,47,83,8.0,2,40,Semi-Urban,ML Engineer,107136,0 +14317,Male,40,Bachelors,1,26,53,42,51,0.0,5,89,Urban,ML Engineer,102004,0 +14318,Male,22,Bachelors,15,11,20,61,2,9.0,0,7,Urban,Software Engineer,142828,0 +14319,Female,36,Masters,18,0,64,92,93,7.0,6,22,Urban,Data Analyst,91008,0 +14320,Male,29,Bachelors,19,11,20,87,1,1.0,3,0,Semi-Urban,HR Executive,68406,0 +14321,Male,51,PhD,3,35,14,96,94,6.0,2,74,Rural,Manager,55145,0 +14322,Male,24,Masters,0,21,71,89,38,4.0,2,33,Urban,Data Analyst,73094,0 +14323,Female,41,High School,11,54,23,35,26,7.0,6,47,Urban,Manager,83023,0 +14324,Male,27,Bachelors,5,1,82,31,39,1.0,2,45,Urban,Software Engineer,64632,0 +14325,Other,31,Bachelors,5,68,86,19,74,1.0,4,76,Semi-Urban,HR Executive,132738,1 +14326,Female,47,Bachelors,7,30,22,63,38,7.0,1,47,Urban,Data Analyst,22394,0 +14327,Male,22,Bachelors,9,33,46,68,79,2.0,2,51,Urban,HR Executive,35331,0 +14328,Male,58,Diploma,18,50,84,31,77,2.0,3,2,Urban,HR Executive,59330,0 +14329,Male,51,Bachelors,18,17,31,86,1,9.0,6,59,Urban,Manager,52520,0 +14330,Male,29,Bachelors,6,80,7,79,5,9.0,6,35,Rural,Data Analyst,120513,0 +14331,Male,42,Bachelors,19,3,2,97,56,7.0,4,59,Semi-Urban,Data Analyst,83926,0 +14332,Male,59,Masters,0,13,25,89,9,2.0,6,28,Rural,Data Analyst,91438,0 +14333,Male,41,High School,11,71,40,88,14,9.0,7,30,Semi-Urban,Software Engineer,92671,0 +14334,Male,49,Bachelors,3,57,85,81,84,4.0,4,73,Urban,Manager,27457,1 +14335,Male,59,Bachelors,13,29,81,74,46,0.0,4,13,Semi-Urban,ML Engineer,76534,0 +14336,Other,28,Bachelors,10,24,44,38,85,8.0,3,3,Semi-Urban,HR Executive,131678,0 +14337,Male,54,Masters,4,9,79,40,42,5.0,3,49,Urban,Data Analyst,36648,0 +14338,Other,22,Bachelors,5,30,75,23,30,3.0,4,64,Urban,HR Executive,73546,0 +14339,Male,44,Bachelors,19,34,92,47,44,2.0,3,92,Urban,Data Analyst,55113,1 +14340,Male,46,Diploma,17,11,15,7,23,7.0,4,85,Semi-Urban,Data Analyst,114031,0 +14341,Male,54,Diploma,3,45,92,33,5,3.0,3,57,Rural,Manager,23668,0 +14342,Male,59,Bachelors,10,72,97,19,55,2.0,0,54,Urban,Software Engineer,99190,1 +14343,Male,23,Masters,17,99,8,73,69,6.0,6,39,Semi-Urban,HR Executive,25539,0 +14344,Female,38,PhD,14,52,97,58,81,2.0,0,0,Urban,Software Engineer,112965,0 +14345,Other,56,Masters,5,43,92,94,11,9.0,3,91,Urban,Manager,143936,1 +14346,Male,25,Bachelors,14,15,2,53,71,2.0,1,58,Semi-Urban,Software Engineer,49173,0 +14347,Male,54,Bachelors,18,85,76,59,64,6.0,5,17,Urban,Data Analyst,29512,1 +14348,Male,42,Masters,18,6,25,39,84,4.0,7,19,Urban,ML Engineer,40875,0 +14349,Male,22,Bachelors,12,61,80,20,59,0.0,5,48,Rural,HR Executive,73545,0 +14350,Male,27,Masters,18,92,96,27,21,7.0,2,9,Urban,Manager,98036,0 +14351,Male,50,Diploma,6,83,3,91,40,7.0,1,72,Urban,ML Engineer,146043,1 +14352,Male,41,Bachelors,15,77,30,4,60,6.0,5,8,Urban,HR Executive,104316,0 +14353,Male,48,Diploma,8,77,22,40,89,6.0,1,73,Urban,ML Engineer,40144,0 +14354,Male,54,Bachelors,9,90,41,56,31,8.0,3,61,Semi-Urban,Software Engineer,130575,1 +14355,Male,25,High School,13,34,45,1,99,3.0,2,41,Urban,HR Executive,35855,0 +14356,Male,52,Bachelors,5,46,54,52,44,5.0,3,43,Urban,Manager,78034,0 +14357,Other,40,Masters,8,53,26,59,40,7.0,1,12,Semi-Urban,Data Analyst,98620,0 +14358,Male,36,Masters,13,91,49,56,91,7.0,3,82,Urban,HR Executive,34269,1 +14359,Female,49,Masters,3,39,70,53,67,6.0,2,9,Urban,ML Engineer,100161,0 +14360,Female,52,Diploma,12,39,5,64,61,6.0,4,43,Urban,HR Executive,94136,0 +14361,Other,25,Bachelors,7,39,49,58,28,8.0,0,67,Urban,Software Engineer,52304,0 +14362,Female,25,Bachelors,14,57,43,13,30,5.0,0,52,Rural,Software Engineer,140867,0 +14363,Female,25,High School,16,85,24,73,91,0.0,7,80,Urban,Data Analyst,51180,1 +14364,Female,56,High School,17,55,54,83,41,6.0,1,34,Urban,Data Analyst,92333,0 +14365,Male,36,Bachelors,19,9,42,83,39,5.0,1,35,Rural,Manager,142194,0 +14366,Male,51,High School,5,34,69,72,54,8.0,0,58,Semi-Urban,Manager,120005,0 +14367,Other,25,Masters,14,41,91,8,40,1.0,7,51,Rural,Software Engineer,29990,0 +14368,Female,44,Masters,5,34,10,40,5,9.0,5,53,Urban,HR Executive,97888,0 +14369,Other,49,Bachelors,0,27,51,29,4,2.0,7,21,Rural,ML Engineer,65264,0 +14370,Female,50,Diploma,19,54,37,41,58,3.0,4,94,Semi-Urban,Manager,37473,0 +14371,Female,58,PhD,14,57,81,24,64,3.0,1,65,Semi-Urban,HR Executive,118202,0 +14372,Female,33,Diploma,14,75,92,25,51,9.0,1,12,Urban,ML Engineer,46375,0 +14373,Female,53,Diploma,2,81,13,96,76,3.0,0,35,Urban,Data Analyst,105052,0 +14374,Male,28,Diploma,15,93,86,7,17,2.0,2,46,Rural,HR Executive,148625,0 +14375,Female,58,Diploma,12,11,20,99,80,4.0,0,86,Urban,Software Engineer,135164,0 +14376,Female,59,Bachelors,17,14,39,21,28,5.0,0,94,Semi-Urban,Software Engineer,98968,0 +14377,Female,31,High School,3,54,24,80,34,2.0,1,85,Semi-Urban,Data Analyst,41410,1 +14378,Female,55,Diploma,11,83,88,37,32,1.0,5,8,Urban,Software Engineer,50337,0 +14379,Male,40,Bachelors,5,63,91,32,1,2.0,6,59,Urban,Software Engineer,116868,1 +14380,Male,21,PhD,16,73,53,86,80,7.0,6,35,Semi-Urban,ML Engineer,74965,1 +14381,Female,38,High School,3,89,99,16,46,2.0,5,88,Semi-Urban,Data Analyst,46617,1 +14382,Male,58,High School,11,42,31,46,23,9.0,0,2,Semi-Urban,Software Engineer,144994,0 +14383,Male,49,Masters,19,55,85,72,30,4.0,5,99,Semi-Urban,HR Executive,126654,1 +14384,Male,51,Masters,16,10,58,4,33,8.0,4,96,Semi-Urban,Software Engineer,24980,0 +14385,Female,45,Masters,1,45,2,15,92,9.0,4,53,Urban,ML Engineer,128466,0 +14386,Female,21,High School,10,22,77,19,99,7.0,0,30,Rural,Manager,33298,0 +14387,Female,26,Bachelors,9,74,83,22,71,7.0,4,38,Urban,Data Analyst,55512,0 +14388,Female,37,Bachelors,8,58,3,3,57,3.0,6,22,Semi-Urban,Manager,79465,0 +14389,Male,29,Bachelors,15,57,41,60,7,5.0,7,94,Semi-Urban,HR Executive,60528,1 +14390,Male,21,Masters,6,74,46,37,24,6.0,2,7,Urban,HR Executive,93068,0 +14391,Male,35,Bachelors,14,84,22,97,53,8.0,2,22,Urban,Manager,136047,0 +14392,Female,37,Bachelors,11,9,81,74,93,1.0,3,96,Urban,Manager,64084,1 +14393,Male,21,Diploma,13,42,79,86,80,6.0,6,6,Semi-Urban,ML Engineer,54694,0 +14394,Female,47,High School,19,13,56,51,10,2.0,7,78,Rural,Data Analyst,102433,0 +14395,Male,26,Bachelors,11,45,58,3,79,0.0,4,26,Urban,HR Executive,112636,0 +14396,Male,40,Bachelors,18,39,15,39,70,3.0,6,23,Semi-Urban,Manager,68240,0 +14397,Female,38,Masters,15,26,22,63,51,5.0,4,78,Semi-Urban,Data Analyst,34283,0 +14398,Male,25,High School,2,90,20,2,7,9.0,3,56,Urban,ML Engineer,89500,0 +14399,Female,34,Bachelors,8,15,68,88,42,3.0,0,20,Urban,Manager,55461,0 +14400,Male,51,Diploma,1,82,13,55,69,5.0,2,45,Rural,Software Engineer,39806,0 +14401,Male,38,Masters,10,80,7,16,96,5.0,6,72,Urban,HR Executive,22667,0 +14402,Male,38,Diploma,4,2,72,58,5,8.0,6,40,Urban,ML Engineer,72786,0 +14403,Male,59,Masters,6,89,86,24,39,6.0,1,48,Urban,HR Executive,84470,1 +14404,Female,26,Bachelors,0,68,87,95,5,5.0,1,27,Urban,HR Executive,50468,1 +14405,Male,55,Bachelors,8,71,63,32,49,7.0,0,88,Urban,HR Executive,58113,1 +14406,Male,58,Diploma,6,39,48,87,86,0.0,4,12,Urban,Data Analyst,25510,0 +14407,Male,23,High School,17,74,76,11,64,9.0,5,79,Semi-Urban,Manager,90672,1 +14408,Female,49,Bachelors,9,2,61,58,49,7.0,1,1,Urban,Data Analyst,79011,0 +14409,Female,59,Masters,14,49,58,53,21,0.0,0,52,Urban,ML Engineer,121892,0 +14410,Male,59,Diploma,5,14,12,90,1,9.0,2,16,Rural,HR Executive,105865,0 +14411,Male,56,High School,4,81,10,48,4,8.0,4,44,Urban,ML Engineer,114494,0 +14412,Female,41,Bachelors,12,70,56,44,94,2.0,4,16,Semi-Urban,Data Analyst,103037,0 +14413,Female,24,High School,1,59,30,30,9,7.0,6,9,Rural,Software Engineer,125021,0 +14414,Male,57,Bachelors,19,2,14,3,0,0.0,3,79,Semi-Urban,Software Engineer,71420,0 +14415,Female,21,Masters,9,36,62,85,2,4.0,1,26,Urban,HR Executive,149809,0 +14416,Female,35,Bachelors,10,57,22,67,38,3.0,2,10,Urban,HR Executive,74977,0 +14417,Female,40,Diploma,4,57,31,37,59,8.0,6,44,Urban,Software Engineer,53950,0 +14418,Female,30,Bachelors,18,92,1,93,29,8.0,6,68,Urban,Data Analyst,87107,1 +14419,Other,40,Masters,2,83,43,31,87,0.0,1,41,Urban,Software Engineer,86798,0 +14420,Male,57,Bachelors,18,88,53,90,35,3.0,2,82,Semi-Urban,Software Engineer,27438,1 +14421,Other,41,Masters,7,42,80,75,92,5.0,3,61,Semi-Urban,Software Engineer,67611,1 +14422,Male,40,Masters,15,88,28,54,88,6.0,1,49,Urban,Software Engineer,113094,0 +14423,Female,51,Diploma,0,15,7,16,60,9.0,3,27,Semi-Urban,Data Analyst,149258,0 +14424,Male,51,Masters,15,11,54,26,8,9.0,4,64,Rural,Data Analyst,139089,0 +14425,Male,58,Diploma,2,65,46,82,89,3.0,2,97,Urban,HR Executive,101733,1 +14426,Female,33,High School,11,76,67,79,94,3.0,1,42,Semi-Urban,ML Engineer,40773,1 +14427,Female,30,Bachelors,19,76,13,27,22,7.0,3,26,Rural,Software Engineer,81755,0 +14428,Male,48,High School,11,27,54,20,74,4.0,4,49,Urban,HR Executive,25973,0 +14429,Male,35,Bachelors,4,81,54,26,96,5.0,1,16,Urban,HR Executive,92892,0 +14430,Male,48,Masters,10,29,39,84,39,6.0,6,70,Rural,Manager,112601,0 +14431,Other,49,Bachelors,17,2,57,56,38,8.0,6,38,Semi-Urban,Software Engineer,75693,0 +14432,Female,56,Bachelors,1,67,95,32,55,8.0,0,17,Urban,Software Engineer,118797,0 +14433,Male,21,Bachelors,16,66,17,8,11,5.0,5,75,Semi-Urban,Manager,122340,0 +14434,Female,43,High School,19,11,32,12,29,6.0,5,92,Urban,Manager,72875,0 +14435,Female,56,High School,17,8,86,18,8,1.0,2,71,Urban,Manager,136710,0 +14436,Male,45,Diploma,10,13,0,61,28,1.0,4,11,Semi-Urban,ML Engineer,65689,0 +14437,Female,58,Bachelors,6,8,58,64,90,4.0,4,27,Rural,Data Analyst,140083,0 +14438,Male,37,Diploma,11,80,61,46,81,0.0,3,94,Urban,ML Engineer,84355,1 +14439,Female,28,Bachelors,4,78,35,22,59,0.0,3,10,Urban,Manager,127964,0 +14440,Male,23,Diploma,5,93,91,55,32,9.0,6,27,Urban,ML Engineer,137530,1 +14441,Male,29,Masters,2,42,74,36,30,2.0,1,34,Urban,Software Engineer,90750,0 +14442,Male,58,Bachelors,19,57,9,58,56,5.0,2,1,Urban,Data Analyst,47854,0 +14443,Male,45,Bachelors,11,35,38,24,42,2.0,5,88,Semi-Urban,Data Analyst,138877,0 +14444,Female,48,Bachelors,11,84,44,50,46,8.0,4,88,Urban,Data Analyst,119740,1 +14445,Male,56,Bachelors,6,88,73,42,12,5.0,0,25,Urban,Data Analyst,98214,0 +14446,Male,56,Bachelors,1,84,73,95,11,2.0,1,65,Semi-Urban,Data Analyst,82116,1 +14447,Female,37,High School,13,65,15,93,39,8.0,6,51,Rural,HR Executive,51344,0 +14448,Male,24,PhD,5,67,98,27,39,9.0,1,42,Urban,HR Executive,61764,0 +14449,Male,47,High School,5,21,92,0,46,7.0,6,89,Urban,Software Engineer,102379,0 +14450,Other,40,Bachelors,12,48,73,16,75,4.0,7,36,Semi-Urban,Software Engineer,66035,0 +14451,Female,36,Bachelors,0,48,13,72,1,9.0,1,46,Urban,ML Engineer,71324,0 +14452,Male,52,Masters,19,39,27,33,39,5.0,6,51,Semi-Urban,ML Engineer,99204,0 +14453,Male,37,Diploma,10,53,68,16,38,9.0,0,39,Urban,Software Engineer,125082,0 +14454,Other,54,High School,1,18,27,93,83,5.0,6,26,Urban,HR Executive,55442,0 +14455,Male,38,High School,0,32,22,62,10,3.0,2,10,Rural,ML Engineer,136742,0 +14456,Male,23,PhD,5,80,58,29,19,6.0,2,20,Urban,Software Engineer,34308,0 +14457,Male,31,PhD,1,18,93,58,3,2.0,5,26,Semi-Urban,HR Executive,132564,0 +14458,Male,32,Diploma,6,27,37,81,89,5.0,4,52,Rural,Data Analyst,110323,0 +14459,Female,45,Bachelors,14,59,53,25,78,2.0,5,73,Semi-Urban,HR Executive,70953,0 +14460,Female,57,Bachelors,14,62,78,70,16,5.0,5,50,Semi-Urban,Data Analyst,109862,1 +14461,Other,37,Bachelors,15,50,88,27,78,8.0,5,79,Urban,Manager,28410,1 +14462,Female,54,Masters,5,60,84,54,58,7.0,1,57,Urban,Software Engineer,115514,1 +14463,Male,40,Bachelors,6,32,38,11,27,0.0,6,11,Semi-Urban,Data Analyst,72540,0 +14464,Male,37,Bachelors,1,0,48,16,52,2.0,2,70,Urban,Software Engineer,60787,0 +14465,Other,40,Masters,0,56,93,2,4,2.0,3,65,Semi-Urban,Manager,89478,0 +14466,Male,23,Bachelors,4,76,79,10,97,0.0,3,66,Semi-Urban,Manager,34162,0 +14467,Male,21,Masters,14,90,47,38,51,8.0,6,36,Urban,Software Engineer,77519,0 +14468,Female,48,High School,19,56,33,6,96,0.0,5,11,Rural,HR Executive,35790,0 +14469,Male,58,Masters,3,90,99,27,83,1.0,4,54,Urban,Data Analyst,58791,1 +14470,Male,26,PhD,8,68,62,24,60,8.0,6,75,Urban,HR Executive,104154,0 +14471,Female,42,Bachelors,0,97,81,15,2,4.0,7,21,Urban,Manager,68361,0 +14472,Other,33,Bachelors,8,63,46,55,66,5.0,7,92,Urban,ML Engineer,142444,1 +14473,Male,24,Diploma,16,60,50,92,68,8.0,0,60,Urban,ML Engineer,54095,1 +14474,Female,44,Bachelors,15,55,59,27,7,0.0,0,0,Urban,ML Engineer,101728,0 +14475,Male,30,Bachelors,18,24,67,3,75,7.0,2,92,Urban,HR Executive,110903,0 +14476,Male,22,Diploma,9,4,78,87,93,3.0,3,74,Semi-Urban,Software Engineer,132872,1 +14477,Female,36,Bachelors,0,33,22,98,48,8.0,1,39,Semi-Urban,Software Engineer,54544,0 +14478,Other,30,PhD,18,12,96,1,97,6.0,2,42,Urban,HR Executive,56510,0 +14479,Male,29,Bachelors,13,30,21,95,21,7.0,4,88,Urban,HR Executive,98735,0 +14480,Male,46,Bachelors,2,54,53,40,40,1.0,5,10,Urban,HR Executive,123569,0 +14481,Male,27,Bachelors,9,29,52,68,45,4.0,7,26,Rural,Manager,75066,0 +14482,Male,36,High School,15,94,39,29,15,4.0,3,97,Rural,ML Engineer,40962,1 +14483,Male,22,Bachelors,11,84,1,28,92,1.0,4,11,Urban,ML Engineer,41682,0 +14484,Male,58,Diploma,4,33,24,34,52,5.0,0,4,Urban,Manager,66601,0 +14485,Male,48,Masters,17,36,64,9,8,7.0,1,49,Rural,Software Engineer,131641,0 +14486,Male,46,Bachelors,5,4,68,60,22,2.0,6,41,Semi-Urban,Manager,33331,0 +14487,Male,34,Diploma,4,29,85,29,15,1.0,0,6,Urban,Software Engineer,108232,0 +14488,Female,28,Bachelors,4,80,44,88,48,5.0,3,63,Rural,ML Engineer,126255,1 +14489,Male,31,Diploma,0,91,55,17,74,3.0,4,6,Urban,HR Executive,71544,0 +14490,Male,53,High School,14,84,4,78,22,2.0,4,66,Rural,Manager,62911,0 +14491,Female,33,Bachelors,17,2,23,9,33,6.0,4,77,Urban,Data Analyst,92537,0 +14492,Female,59,Masters,19,73,35,53,23,3.0,5,5,Urban,Data Analyst,85084,0 +14493,Male,26,Bachelors,8,14,35,83,10,3.0,3,92,Semi-Urban,ML Engineer,83933,0 +14494,Male,39,Bachelors,2,91,81,18,27,3.0,7,97,Urban,Manager,140283,1 +14495,Female,48,High School,12,24,2,69,76,1.0,3,38,Rural,HR Executive,29204,0 +14496,Male,44,Masters,14,22,53,92,91,6.0,2,18,Urban,HR Executive,138782,0 +14497,Female,44,Diploma,4,32,32,40,95,0.0,6,83,Rural,HR Executive,147823,0 +14498,Male,55,Bachelors,2,88,17,60,91,0.0,4,66,Semi-Urban,Data Analyst,87258,0 +14499,Male,27,Bachelors,7,83,32,77,42,0.0,4,63,Semi-Urban,Data Analyst,91988,1 +14500,Male,29,Diploma,14,88,27,70,75,2.0,1,72,Rural,Software Engineer,20195,1 +14501,Female,21,Bachelors,5,62,28,41,70,3.0,7,82,Urban,Software Engineer,148509,0 +14502,Female,26,Bachelors,3,15,17,50,24,3.0,7,8,Rural,Data Analyst,28483,0 +14503,Male,32,Diploma,4,58,18,33,8,1.0,3,93,Urban,ML Engineer,105873,0 +14504,Male,48,Bachelors,1,30,83,91,19,0.0,0,23,Urban,HR Executive,30062,0 +14505,Male,58,Bachelors,17,97,66,85,52,2.0,5,47,Rural,Data Analyst,23634,1 +14506,Male,48,Bachelors,9,29,32,58,14,3.0,1,77,Semi-Urban,Data Analyst,43171,0 +14507,Female,46,Masters,1,25,38,68,33,7.0,0,35,Semi-Urban,HR Executive,42727,0 +14508,Male,55,High School,7,76,49,12,48,7.0,4,83,Rural,HR Executive,87417,0 +14509,Female,38,Bachelors,12,54,61,60,98,4.0,7,3,Urban,HR Executive,94338,0 +14510,Female,47,Bachelors,18,34,29,23,47,1.0,4,73,Urban,ML Engineer,25148,0 +14511,Female,30,Bachelors,5,19,45,46,1,2.0,0,94,Rural,HR Executive,34304,0 +14512,Female,36,Masters,13,9,40,88,47,7.0,1,23,Rural,ML Engineer,106692,0 +14513,Male,28,High School,9,64,50,90,69,6.0,7,40,Urban,Software Engineer,58163,1 +14514,Male,27,Diploma,14,1,24,67,21,7.0,3,75,Urban,HR Executive,141573,0 +14515,Male,33,Diploma,2,17,8,22,53,8.0,6,13,Rural,HR Executive,69714,0 +14516,Male,31,High School,11,73,16,61,44,6.0,5,90,Urban,ML Engineer,123511,1 +14517,Male,55,Diploma,3,29,59,75,42,7.0,0,1,Urban,Software Engineer,90111,0 +14518,Male,25,Bachelors,9,34,16,49,94,0.0,7,80,Rural,Data Analyst,37292,0 +14519,Other,49,Bachelors,8,8,13,25,72,0.0,5,3,Urban,HR Executive,135663,0 +14520,Male,43,Masters,10,50,91,66,87,9.0,5,97,Rural,ML Engineer,56308,1 +14521,Female,57,PhD,9,13,20,62,67,4.0,5,85,Semi-Urban,ML Engineer,78982,0 +14522,Female,41,Bachelors,16,76,79,99,83,1.0,0,34,Semi-Urban,Manager,91349,1 +14523,Female,54,Bachelors,16,46,1,56,23,9.0,1,51,Urban,HR Executive,70135,0 +14524,Male,54,Bachelors,15,39,32,73,95,7.0,2,47,Urban,Software Engineer,105666,0 +14525,Male,37,Masters,6,47,23,61,28,9.0,2,96,Semi-Urban,ML Engineer,109700,0 +14526,Male,33,High School,5,3,42,94,51,1.0,4,11,Urban,Software Engineer,133502,0 +14527,Male,25,Bachelors,16,17,96,0,50,4.0,6,95,Semi-Urban,Software Engineer,103812,0 +14528,Male,51,Bachelors,8,52,15,72,38,3.0,4,80,Urban,Manager,97250,0 +14529,Female,37,Bachelors,9,30,40,63,21,6.0,3,8,Semi-Urban,Manager,62337,0 +14530,Male,44,Bachelors,7,59,85,95,12,3.0,6,54,Semi-Urban,Data Analyst,84689,1 +14531,Male,37,Bachelors,16,73,10,85,93,5.0,4,89,Urban,Data Analyst,69762,1 +14532,Other,36,Diploma,18,71,90,21,81,5.0,1,58,Urban,Software Engineer,37298,0 +14533,Male,46,Bachelors,4,9,43,35,32,5.0,1,91,Semi-Urban,HR Executive,97820,0 +14534,Male,41,Bachelors,1,1,64,55,85,7.0,6,65,Urban,Data Analyst,60023,0 +14535,Female,31,Diploma,2,27,51,76,4,3.0,7,50,Urban,HR Executive,91464,0 +14536,Male,44,Diploma,3,90,89,32,7,3.0,3,67,Semi-Urban,Data Analyst,139361,1 +14537,Female,51,High School,11,79,29,10,27,2.0,4,48,Urban,ML Engineer,65454,0 +14538,Male,58,Bachelors,8,65,95,59,16,1.0,3,92,Urban,Manager,24785,1 +14539,Female,24,Masters,10,34,13,70,97,3.0,2,7,Urban,Data Analyst,129977,0 +14540,Male,26,PhD,15,79,99,86,45,6.0,6,79,Rural,Manager,24217,1 +14541,Male,54,Diploma,4,1,27,61,41,1.0,4,24,Semi-Urban,Manager,102638,0 +14542,Male,43,Bachelors,12,3,67,40,78,4.0,1,12,Semi-Urban,Data Analyst,92824,0 +14543,Male,38,High School,10,31,68,86,8,2.0,6,37,Urban,Manager,126130,0 +14544,Male,58,Masters,13,37,91,40,28,0.0,4,1,Urban,ML Engineer,85143,0 +14545,Male,57,Bachelors,10,7,90,33,85,2.0,7,12,Rural,Manager,44180,0 +14546,Male,37,High School,11,9,85,52,42,3.0,1,75,Urban,Data Analyst,88918,0 +14547,Male,52,Diploma,9,76,78,52,21,2.0,0,80,Urban,Manager,21189,1 +14548,Male,42,Masters,17,20,88,86,34,1.0,4,56,Semi-Urban,HR Executive,98493,1 +14549,Male,31,PhD,3,80,28,32,93,8.0,3,30,Semi-Urban,HR Executive,37371,0 +14550,Female,55,Bachelors,16,93,41,75,53,4.0,7,56,Urban,Data Analyst,90750,1 +14551,Male,31,PhD,2,56,2,4,26,1.0,4,21,Semi-Urban,Manager,124943,0 +14552,Male,40,Masters,12,82,34,43,85,9.0,3,11,Semi-Urban,Data Analyst,37686,0 +14553,Female,30,Diploma,1,46,48,86,32,5.0,4,48,Urban,Manager,93419,0 +14554,Female,48,Bachelors,3,8,17,44,95,2.0,5,69,Urban,HR Executive,110681,0 +14555,Male,59,Bachelors,1,68,44,36,87,1.0,3,30,Urban,Software Engineer,63235,0 +14556,Male,52,PhD,4,59,9,84,40,0.0,7,69,Urban,ML Engineer,70511,0 +14557,Male,27,Masters,3,95,72,26,99,8.0,7,91,Urban,Software Engineer,59916,1 +14558,Male,23,High School,6,14,61,89,32,0.0,4,19,Urban,ML Engineer,42788,0 +14559,Female,44,Diploma,13,70,99,17,34,7.0,5,9,Semi-Urban,Manager,136193,0 +14560,Male,27,Masters,3,7,59,64,5,9.0,3,77,Urban,ML Engineer,28716,0 +14561,Female,25,Diploma,5,88,89,36,95,2.0,3,91,Semi-Urban,HR Executive,113337,1 +14562,Male,30,Masters,17,18,51,89,31,9.0,7,69,Urban,HR Executive,23959,0 +14563,Male,41,Masters,16,90,7,31,56,8.0,1,33,Rural,Data Analyst,21259,0 +14564,Female,37,Diploma,12,3,30,96,77,3.0,3,62,Urban,HR Executive,61130,0 +14565,Male,34,Masters,2,67,91,4,94,5.0,1,88,Semi-Urban,Manager,42566,1 +14566,Male,50,Masters,18,86,19,80,19,6.0,7,67,Rural,HR Executive,143630,1 +14567,Other,26,High School,7,44,17,42,82,8.0,6,91,Urban,HR Executive,104512,0 +14568,Female,47,Bachelors,6,85,33,73,83,3.0,6,99,Semi-Urban,Software Engineer,141985,1 +14569,Female,24,Diploma,2,71,4,68,68,4.0,0,27,Rural,Manager,23834,0 +14570,Male,46,Masters,10,20,14,17,19,9.0,5,75,Semi-Urban,HR Executive,133616,0 +14571,Male,21,Masters,6,40,7,29,85,8.0,6,23,Rural,ML Engineer,59017,0 +14572,Female,28,Bachelors,17,47,72,28,5,6.0,6,15,Semi-Urban,Manager,141346,0 +14573,Male,47,Masters,7,99,19,71,84,3.0,7,62,Urban,ML Engineer,125983,1 +14574,Female,24,Bachelors,1,93,39,17,25,3.0,4,80,Semi-Urban,Software Engineer,114667,0 +14575,Male,55,Masters,3,56,60,27,17,4.0,0,41,Semi-Urban,HR Executive,51692,0 +14576,Male,29,Diploma,7,28,79,89,14,4.0,1,69,Urban,ML Engineer,114400,1 +14577,Other,39,PhD,18,13,50,30,57,5.0,2,32,Urban,Manager,119272,0 +14578,Male,59,Masters,4,76,94,9,73,2.0,5,7,Semi-Urban,ML Engineer,128660,0 +14579,Male,24,Diploma,3,23,72,24,15,8.0,6,33,Urban,ML Engineer,87780,0 +14580,Male,47,Masters,13,78,37,77,32,1.0,5,71,Rural,Manager,129371,1 +14581,Male,28,Bachelors,3,31,29,35,86,3.0,3,2,Urban,Software Engineer,26203,0 +14582,Male,57,Diploma,19,42,20,68,52,3.0,2,58,Urban,Software Engineer,33372,0 +14583,Male,49,Diploma,1,85,68,70,35,5.0,4,70,Semi-Urban,Data Analyst,110019,1 +14584,Male,52,Masters,12,40,51,64,65,9.0,3,93,Semi-Urban,Manager,98631,1 +14585,Female,30,Masters,10,87,37,8,87,1.0,0,34,Rural,Data Analyst,22509,0 +14586,Male,39,Bachelors,12,48,67,49,21,9.0,1,3,Urban,HR Executive,61219,0 +14587,Other,38,PhD,4,56,76,57,31,7.0,6,44,Urban,ML Engineer,39849,0 +14588,Male,46,Bachelors,5,87,3,94,78,0.0,6,97,Urban,ML Engineer,23973,1 +14589,Male,50,Bachelors,5,59,37,73,22,2.0,7,53,Rural,Data Analyst,87890,0 +14590,Male,49,PhD,1,23,5,34,18,5.0,4,2,Semi-Urban,Software Engineer,104397,0 +14591,Female,42,Masters,19,64,34,94,43,6.0,1,0,Rural,Data Analyst,24129,0 +14592,Other,32,Masters,14,12,76,35,99,1.0,2,20,Rural,Manager,102852,0 +14593,Female,43,Bachelors,5,82,61,75,72,5.0,2,9,Semi-Urban,ML Engineer,133348,0 +14594,Male,29,Bachelors,14,2,13,54,90,2.0,6,21,Urban,Data Analyst,54954,0 +14595,Male,31,High School,6,96,80,6,61,7.0,3,64,Urban,HR Executive,33691,1 +14596,Female,41,Masters,14,47,77,34,91,2.0,5,4,Urban,HR Executive,36921,0 +14597,Female,31,High School,10,48,55,43,37,4.0,1,31,Urban,Data Analyst,78916,0 +14598,Other,51,High School,19,86,3,24,83,6.0,0,20,Semi-Urban,HR Executive,86292,0 +14599,Male,52,Diploma,10,5,34,28,14,3.0,3,36,Rural,Data Analyst,95009,0 +14600,Other,36,Bachelors,19,40,84,91,61,5.0,3,43,Urban,Manager,126344,1 +14601,Male,32,Bachelors,9,68,67,85,60,4.0,5,84,Urban,Manager,49274,1 +14602,Male,30,High School,8,70,40,33,33,1.0,3,48,Urban,Manager,78518,0 +14603,Male,26,High School,6,80,11,72,97,2.0,6,37,Urban,Manager,71937,0 +14604,Male,57,Diploma,16,49,55,75,40,1.0,0,46,Semi-Urban,HR Executive,102117,0 +14605,Female,40,Diploma,1,50,52,64,12,5.0,4,42,Urban,ML Engineer,146540,0 +14606,Female,55,PhD,11,68,7,61,61,1.0,1,37,Semi-Urban,Manager,46439,0 +14607,Female,59,High School,17,35,28,35,6,0.0,7,64,Semi-Urban,Manager,72155,0 +14608,Female,31,Bachelors,2,67,1,16,25,1.0,6,65,Rural,Software Engineer,138550,0 +14609,Male,22,PhD,19,67,14,78,86,8.0,0,37,Semi-Urban,HR Executive,94110,0 +14610,Female,39,Diploma,10,88,98,11,40,1.0,2,69,Semi-Urban,HR Executive,35175,1 +14611,Male,46,Masters,11,95,65,55,89,6.0,7,14,Rural,Data Analyst,66362,0 +14612,Female,55,Bachelors,14,70,76,5,71,7.0,4,80,Urban,HR Executive,31189,0 +14613,Female,22,Masters,2,88,79,89,83,4.0,0,91,Rural,Manager,40381,1 +14614,Female,38,Bachelors,16,30,40,97,4,2.0,2,51,Urban,Data Analyst,41162,0 +14615,Male,50,Diploma,18,30,20,86,45,0.0,6,66,Urban,HR Executive,122134,0 +14616,Female,41,Bachelors,15,50,61,78,11,8.0,1,65,Semi-Urban,Software Engineer,120940,1 +14617,Male,33,Diploma,5,0,48,96,83,8.0,7,3,Urban,ML Engineer,93716,0 +14618,Male,47,Bachelors,16,80,18,31,25,1.0,4,18,Urban,Manager,93199,0 +14619,Female,22,Bachelors,6,54,42,56,84,1.0,5,67,Urban,Manager,116369,0 +14620,Male,49,Bachelors,5,51,93,38,28,6.0,0,76,Semi-Urban,Data Analyst,134730,1 +14621,Female,47,Masters,3,22,55,4,4,3.0,3,17,Semi-Urban,HR Executive,133428,0 +14622,Male,42,Diploma,13,69,37,74,46,0.0,0,27,Rural,Data Analyst,42177,0 +14623,Male,51,Masters,18,61,5,21,19,7.0,3,88,Semi-Urban,Software Engineer,78672,0 +14624,Female,36,Bachelors,6,11,74,65,72,3.0,7,37,Rural,Data Analyst,64994,0 +14625,Male,38,Bachelors,14,68,39,52,11,6.0,5,19,Urban,Manager,67432,0 +14626,Male,21,PhD,18,85,48,22,90,7.0,3,43,Urban,Manager,72784,0 +14627,Male,57,High School,19,10,12,5,83,4.0,3,83,Urban,HR Executive,111967,0 +14628,Male,23,Diploma,13,53,81,79,5,9.0,7,41,Semi-Urban,ML Engineer,146696,1 +14629,Female,23,Masters,11,12,26,61,87,0.0,2,12,Urban,HR Executive,131224,0 +14630,Male,29,High School,5,94,21,50,49,9.0,6,49,Semi-Urban,Software Engineer,23453,0 +14631,Female,32,Diploma,9,48,62,24,84,1.0,0,57,Semi-Urban,Manager,30641,0 +14632,Female,58,Bachelors,16,51,95,32,48,1.0,3,30,Urban,Data Analyst,58339,0 +14633,Male,55,High School,17,39,3,75,80,8.0,5,87,Urban,Data Analyst,111765,0 +14634,Female,44,Diploma,10,87,27,44,72,0.0,1,63,Urban,Software Engineer,81781,0 +14635,Female,54,Bachelors,0,74,98,78,40,4.0,5,24,Urban,HR Executive,135840,1 +14636,Male,23,Bachelors,15,92,54,47,46,3.0,0,78,Urban,Software Engineer,111992,1 +14637,Male,54,Diploma,16,50,1,80,7,4.0,4,80,Semi-Urban,Manager,38163,0 +14638,Male,47,Masters,8,94,6,47,84,6.0,4,54,Urban,HR Executive,52961,0 +14639,Female,25,Bachelors,0,75,74,42,57,5.0,5,11,Urban,HR Executive,115303,0 +14640,Female,46,High School,4,64,57,79,3,1.0,7,49,Urban,ML Engineer,124163,1 +14641,Male,36,Bachelors,3,79,89,97,98,8.0,5,85,Semi-Urban,Manager,29407,1 +14642,Female,33,Bachelors,1,73,38,18,82,2.0,7,94,Urban,Data Analyst,108001,0 +14643,Female,27,PhD,10,35,44,89,23,4.0,6,71,Urban,Data Analyst,111415,0 +14644,Female,47,Bachelors,0,39,86,7,3,3.0,6,42,Urban,HR Executive,80828,0 +14645,Female,46,Bachelors,4,92,33,99,77,4.0,7,1,Urban,HR Executive,24156,0 +14646,Male,23,High School,15,46,59,76,83,8.0,0,37,Urban,HR Executive,133788,0 +14647,Female,31,Bachelors,3,0,19,68,67,7.0,5,10,Urban,ML Engineer,67894,0 +14648,Female,25,PhD,12,0,53,14,46,2.0,0,34,Urban,HR Executive,136452,0 +14649,Female,32,Diploma,15,74,4,64,71,7.0,7,25,Semi-Urban,Manager,89066,0 +14650,Male,54,Bachelors,12,52,65,56,32,9.0,5,53,Rural,Software Engineer,61956,0 +14651,Male,45,Masters,19,25,33,45,46,6.0,5,97,Rural,Software Engineer,60440,0 +14652,Male,51,High School,1,68,58,89,13,4.0,1,87,Rural,ML Engineer,118499,1 +14653,Male,36,Bachelors,15,14,28,39,89,7.0,6,0,Urban,HR Executive,81889,0 +14654,Female,40,Bachelors,2,3,31,37,84,2.0,6,29,Urban,Software Engineer,50104,0 +14655,Male,51,PhD,6,91,53,18,12,9.0,1,49,Semi-Urban,ML Engineer,76855,0 +14656,Female,57,PhD,6,93,3,9,49,5.0,2,62,Rural,ML Engineer,100926,0 +14657,Female,38,Bachelors,7,57,37,84,88,4.0,2,23,Urban,HR Executive,93174,0 +14658,Female,36,Masters,11,49,64,78,73,0.0,5,89,Urban,ML Engineer,122330,1 +14659,Male,25,Diploma,11,27,50,94,78,7.0,4,87,Rural,HR Executive,43720,1 +14660,Other,43,Bachelors,4,12,86,10,18,2.0,7,60,Urban,Software Engineer,59881,0 +14661,Female,52,Masters,14,58,9,23,69,8.0,7,93,Urban,Manager,101327,0 +14662,Female,39,Bachelors,18,63,16,20,82,1.0,2,96,Urban,Software Engineer,148919,0 +14663,Male,43,Bachelors,0,33,15,20,86,6.0,7,47,Urban,Manager,103064,0 +14664,Male,25,Bachelors,14,2,38,61,11,9.0,7,34,Urban,Data Analyst,46158,0 +14665,Male,50,Diploma,16,81,34,98,67,0.0,1,70,Urban,HR Executive,118795,1 +14666,Male,24,Bachelors,9,88,66,15,30,5.0,7,31,Urban,ML Engineer,146053,0 +14667,Male,59,Diploma,5,62,41,55,84,7.0,4,5,Urban,Manager,31304,0 +14668,Male,23,Bachelors,14,15,24,74,44,1.0,6,32,Urban,Software Engineer,129734,0 +14669,Female,43,Diploma,8,61,82,61,88,5.0,7,0,Rural,Manager,27062,0 +14670,Male,33,Diploma,16,66,20,91,59,6.0,0,40,Urban,Manager,146815,0 +14671,Male,50,High School,4,9,97,50,44,2.0,7,28,Semi-Urban,Software Engineer,45267,0 +14672,Female,42,Masters,6,92,42,72,66,2.0,2,64,Semi-Urban,Data Analyst,94141,1 +14673,Male,29,PhD,2,1,42,79,72,5.0,2,65,Semi-Urban,Manager,36357,0 +14674,Female,30,Bachelors,15,55,47,0,43,6.0,4,52,Urban,HR Executive,60000,0 +14675,Male,37,Bachelors,8,43,75,44,65,3.0,7,46,Semi-Urban,Data Analyst,107931,0 +14676,Male,28,Bachelors,8,82,36,71,37,1.0,7,37,Urban,ML Engineer,142160,0 +14677,Male,53,Bachelors,11,76,17,16,51,2.0,0,28,Urban,Data Analyst,123854,0 +14678,Female,36,Diploma,4,4,84,31,83,7.0,3,42,Semi-Urban,HR Executive,132072,0 +14679,Male,49,Masters,19,1,27,9,17,6.0,1,6,Semi-Urban,Data Analyst,37340,0 +14680,Female,40,Masters,2,73,8,1,74,0.0,4,87,Urban,ML Engineer,22038,0 +14681,Male,38,Masters,17,3,6,50,96,5.0,2,65,Urban,HR Executive,142459,0 +14682,Male,26,Bachelors,5,36,59,19,29,0.0,2,92,Urban,HR Executive,112455,0 +14683,Female,48,Bachelors,7,37,95,90,18,8.0,3,24,Rural,ML Engineer,105594,1 +14684,Male,36,Diploma,9,25,79,84,88,2.0,3,65,Urban,Data Analyst,24751,1 +14685,Female,32,Masters,14,2,44,90,43,6.0,7,96,Semi-Urban,ML Engineer,75039,0 +14686,Male,39,Bachelors,19,26,29,93,65,2.0,2,23,Semi-Urban,HR Executive,131825,0 +14687,Male,28,Masters,13,78,80,55,3,5.0,2,11,Rural,Software Engineer,47033,0 +14688,Female,57,Masters,19,37,10,10,44,4.0,2,79,Semi-Urban,Manager,144986,0 +14689,Other,29,Diploma,1,81,1,46,6,1.0,6,5,Urban,Software Engineer,57350,0 +14690,Male,59,Diploma,15,28,77,28,69,8.0,4,58,Urban,Data Analyst,64161,0 +14691,Female,37,Bachelors,13,85,29,47,38,7.0,5,15,Urban,ML Engineer,124815,0 +14692,Male,36,Masters,0,50,1,87,39,9.0,7,50,Rural,Software Engineer,113959,0 +14693,Female,56,Bachelors,6,79,48,84,31,0.0,4,30,Semi-Urban,Software Engineer,88061,1 +14694,Female,41,Bachelors,17,90,99,4,76,2.0,5,47,Urban,Data Analyst,115848,0 +14695,Male,38,High School,19,56,93,78,70,1.0,2,77,Urban,ML Engineer,60616,1 +14696,Male,47,High School,3,49,73,15,13,5.0,5,85,Semi-Urban,ML Engineer,36422,0 +14697,Male,39,Masters,1,29,25,2,72,4.0,7,49,Semi-Urban,ML Engineer,51512,0 +14698,Male,50,High School,5,69,69,84,2,0.0,6,38,Urban,Software Engineer,128665,1 +14699,Male,48,Bachelors,19,52,45,17,53,7.0,2,37,Urban,Manager,113038,0 +14700,Female,57,Masters,0,36,87,28,38,8.0,3,84,Urban,Manager,119689,0 +14701,Other,25,Bachelors,5,90,82,6,26,5.0,5,85,Urban,Manager,135171,1 +14702,Male,56,Diploma,1,48,3,58,30,3.0,5,86,Urban,HR Executive,20996,0 +14703,Male,58,Bachelors,17,60,86,8,81,2.0,7,42,Rural,ML Engineer,145246,0 +14704,Male,49,Bachelors,16,52,56,24,39,8.0,7,31,Rural,HR Executive,59738,0 +14705,Female,29,Diploma,4,59,16,34,38,6.0,2,87,Urban,Software Engineer,74742,0 +14706,Male,45,Bachelors,13,18,29,18,5,9.0,1,11,Urban,Software Engineer,73989,0 +14707,Male,26,High School,7,28,70,31,42,1.0,3,26,Rural,ML Engineer,61713,0 +14708,Male,32,Masters,13,19,40,73,86,7.0,5,92,Urban,HR Executive,96057,0 +14709,Male,50,Masters,5,62,79,48,64,2.0,6,64,Urban,Software Engineer,74844,1 +14710,Male,29,Bachelors,14,79,13,64,54,7.0,1,54,Urban,HR Executive,68341,0 +14711,Male,42,Bachelors,15,89,58,85,1,2.0,3,29,Rural,Manager,146536,1 +14712,Male,47,High School,12,74,81,86,22,1.0,1,62,Urban,Manager,88088,1 +14713,Male,30,Bachelors,5,21,63,63,16,0.0,1,93,Rural,ML Engineer,69930,1 +14714,Male,33,Bachelors,3,65,0,97,21,5.0,2,78,Urban,Manager,33399,1 +14715,Male,32,Diploma,19,31,22,53,86,4.0,1,64,Rural,HR Executive,56475,0 +14716,Male,32,Bachelors,6,64,27,83,91,4.0,4,68,Urban,ML Engineer,144836,1 +14717,Female,48,Diploma,18,4,51,2,47,9.0,1,57,Urban,ML Engineer,31392,0 +14718,Female,56,Masters,19,45,90,37,51,1.0,1,99,Urban,Data Analyst,116756,1 +14719,Male,35,High School,11,93,40,85,3,4.0,6,3,Urban,Manager,112610,0 +14720,Male,29,Bachelors,18,16,69,50,46,2.0,2,63,Rural,Data Analyst,146533,0 +14721,Female,38,High School,1,43,31,95,29,0.0,6,69,Urban,Software Engineer,101074,0 +14722,Male,47,Bachelors,18,1,38,43,62,7.0,0,84,Urban,ML Engineer,126340,0 +14723,Male,44,Bachelors,8,49,65,84,29,6.0,7,61,Semi-Urban,HR Executive,95004,1 +14724,Male,54,Diploma,9,22,46,43,58,9.0,4,95,Rural,HR Executive,126484,0 +14725,Female,29,Bachelors,2,91,73,64,0,4.0,0,96,Semi-Urban,Manager,62048,1 +14726,Female,49,Diploma,5,48,11,45,79,4.0,5,97,Urban,Software Engineer,87225,0 +14727,Male,38,Bachelors,18,15,29,89,64,4.0,4,94,Urban,Data Analyst,87636,0 +14728,Male,48,Masters,2,9,65,51,38,9.0,3,99,Urban,Data Analyst,86493,0 +14729,Female,41,Bachelors,6,71,78,82,76,8.0,5,81,Urban,HR Executive,40401,1 +14730,Female,55,High School,12,70,25,32,73,1.0,2,35,Urban,Software Engineer,28113,0 +14731,Other,43,PhD,11,36,10,90,95,3.0,3,25,Rural,Manager,140451,0 +14732,Male,49,Bachelors,1,90,21,71,59,9.0,6,27,Urban,ML Engineer,115521,0 +14733,Male,57,Masters,0,6,75,11,55,1.0,4,19,Rural,Software Engineer,46645,0 +14734,Female,56,High School,7,8,32,13,93,0.0,3,61,Semi-Urban,Software Engineer,57162,0 +14735,Male,30,Masters,11,74,58,39,89,7.0,1,83,Semi-Urban,Software Engineer,76742,1 +14736,Male,40,Masters,7,96,35,76,24,7.0,2,51,Urban,Manager,78266,1 +14737,Male,31,Diploma,18,37,66,75,72,9.0,3,70,Urban,Data Analyst,86911,1 +14738,Female,58,Masters,18,68,10,24,76,0.0,0,38,Urban,Data Analyst,30135,0 +14739,Female,41,Diploma,17,87,93,81,70,3.0,2,77,Semi-Urban,ML Engineer,126717,1 +14740,Male,51,Masters,2,50,17,86,20,7.0,4,28,Rural,Data Analyst,107965,0 +14741,Female,33,Diploma,11,31,48,25,80,8.0,1,91,Semi-Urban,Manager,111089,0 +14742,Male,38,Bachelors,5,78,41,14,74,3.0,7,51,Urban,Software Engineer,63827,0 +14743,Female,48,Masters,0,26,87,21,90,9.0,0,23,Rural,Data Analyst,129482,0 +14744,Male,26,High School,9,3,96,71,10,2.0,1,91,Urban,ML Engineer,134633,1 +14745,Male,46,Masters,6,19,85,1,47,9.0,3,13,Semi-Urban,HR Executive,103456,0 +14746,Male,56,Bachelors,3,16,56,82,93,1.0,5,47,Rural,Data Analyst,107373,0 +14747,Male,24,Diploma,3,66,71,22,80,4.0,7,44,Semi-Urban,Data Analyst,94053,0 +14748,Male,52,Bachelors,9,98,21,31,38,7.0,2,82,Rural,Manager,136037,0 +14749,Male,22,Bachelors,5,52,10,81,17,5.0,1,63,Urban,Software Engineer,50907,0 +14750,Other,42,Masters,7,69,12,42,81,2.0,2,38,Rural,ML Engineer,108117,0 +14751,Male,33,Bachelors,4,91,75,40,42,0.0,2,68,Urban,Manager,33436,1 +14752,Male,32,Bachelors,19,34,61,51,60,1.0,6,2,Urban,Data Analyst,60120,0 +14753,Male,23,Masters,15,10,58,2,72,5.0,6,80,Urban,Manager,140295,0 +14754,Male,28,High School,9,66,5,62,81,2.0,7,90,Semi-Urban,Data Analyst,128541,0 +14755,Male,49,Bachelors,10,50,45,2,97,8.0,4,89,Urban,Data Analyst,117975,0 +14756,Female,42,High School,6,39,75,19,3,3.0,7,19,Urban,ML Engineer,75263,0 +14757,Male,45,Bachelors,7,83,0,39,42,9.0,0,46,Urban,Manager,104299,0 +14758,Female,28,High School,19,81,93,60,61,3.0,5,16,Urban,ML Engineer,67617,1 +14759,Female,29,Bachelors,0,70,57,97,61,5.0,4,89,Semi-Urban,Manager,95232,1 +14760,Male,52,High School,17,85,91,10,28,3.0,5,27,Urban,Software Engineer,89605,0 +14761,Male,46,Diploma,17,11,96,3,17,3.0,4,56,Urban,Software Engineer,102170,0 +14762,Female,53,Bachelors,0,38,98,74,31,6.0,3,69,Semi-Urban,HR Executive,47773,1 +14763,Male,33,Bachelors,0,58,77,33,73,1.0,6,95,Urban,Software Engineer,108555,1 +14764,Male,52,Bachelors,8,16,30,30,67,9.0,5,43,Semi-Urban,Manager,78642,0 +14765,Female,34,Bachelors,18,21,20,56,40,2.0,7,83,Rural,Software Engineer,122042,0 +14766,Male,32,Diploma,15,85,98,81,41,1.0,5,86,Semi-Urban,Manager,132987,1 +14767,Male,59,Bachelors,9,77,93,22,45,5.0,5,71,Urban,Manager,75251,1 +14768,Other,57,Diploma,3,22,27,79,39,8.0,1,39,Rural,HR Executive,30399,0 +14769,Male,53,Bachelors,5,98,95,30,1,7.0,2,24,Urban,ML Engineer,114477,1 +14770,Male,39,Bachelors,10,47,37,10,63,6.0,1,99,Rural,ML Engineer,81084,0 +14771,Female,40,Bachelors,1,59,57,67,64,1.0,3,9,Urban,Software Engineer,91862,0 +14772,Female,29,Bachelors,19,87,44,25,78,4.0,0,45,Urban,Software Engineer,124981,0 +14773,Male,46,Bachelors,15,93,9,34,45,3.0,1,69,Urban,ML Engineer,78392,0 +14774,Male,53,Diploma,10,16,77,15,46,9.0,0,93,Rural,Software Engineer,43611,0 +14775,Female,27,Bachelors,0,77,81,22,29,3.0,6,38,Rural,Manager,130221,0 +14776,Female,30,Bachelors,18,29,15,89,70,6.0,6,10,Urban,HR Executive,75094,0 +14777,Male,48,Bachelors,5,37,20,2,20,5.0,4,61,Semi-Urban,ML Engineer,146490,0 +14778,Male,25,Masters,7,6,56,61,79,7.0,6,24,Urban,Data Analyst,22327,0 +14779,Male,56,Masters,10,68,58,15,64,5.0,4,19,Urban,ML Engineer,29954,0 +14780,Female,37,Bachelors,4,38,2,11,98,2.0,6,49,Urban,HR Executive,64572,0 +14781,Female,48,Bachelors,4,5,91,63,59,8.0,7,89,Semi-Urban,ML Engineer,83105,1 +14782,Other,22,Masters,8,87,43,92,15,9.0,7,23,Urban,Manager,146455,1 +14783,Female,42,Masters,11,76,66,92,56,0.0,1,76,Urban,Software Engineer,61488,1 +14784,Male,53,Bachelors,5,28,75,54,11,1.0,5,61,Urban,Manager,34243,0 +14785,Male,38,PhD,5,30,93,20,54,3.0,6,27,Semi-Urban,Manager,111662,0 +14786,Female,37,Bachelors,9,16,49,26,65,0.0,0,47,Urban,Manager,112681,0 +14787,Female,27,Masters,11,81,99,10,23,1.0,5,62,Urban,Manager,92496,1 +14788,Male,52,Masters,16,76,21,12,47,4.0,7,43,Semi-Urban,Manager,147506,0 +14789,Male,59,Diploma,13,4,63,4,21,0.0,2,34,Semi-Urban,HR Executive,29697,0 +14790,Female,57,Bachelors,11,98,96,88,40,6.0,3,25,Urban,HR Executive,89646,1 +14791,Male,58,Bachelors,5,73,66,33,72,0.0,2,35,Urban,Software Engineer,47965,0 +14792,Male,49,PhD,4,78,91,33,87,6.0,4,59,Urban,Software Engineer,122851,1 +14793,Female,24,Diploma,6,92,89,11,76,0.0,2,55,Rural,ML Engineer,68762,1 +14794,Female,43,Masters,4,26,84,92,22,7.0,2,28,Urban,Manager,95755,0 +14795,Male,35,Bachelors,6,45,41,2,75,5.0,0,81,Urban,ML Engineer,147784,0 +14796,Female,37,High School,18,20,50,40,87,9.0,2,35,Semi-Urban,Data Analyst,94998,0 +14797,Male,44,Bachelors,14,6,65,35,57,0.0,1,68,Semi-Urban,Manager,21126,0 +14798,Male,52,High School,10,46,4,19,9,9.0,5,58,Semi-Urban,Software Engineer,141766,0 +14799,Male,23,Bachelors,12,27,23,3,97,8.0,4,96,Urban,Manager,24487,0 +14800,Female,53,Bachelors,6,35,48,20,79,6.0,3,57,Urban,Manager,118748,0 +14801,Other,37,Bachelors,16,1,36,54,20,0.0,7,49,Urban,ML Engineer,96529,0 +14802,Female,57,Bachelors,1,57,70,66,36,2.0,0,92,Urban,HR Executive,95783,1 +14803,Female,45,Diploma,8,50,60,95,1,9.0,1,86,Urban,HR Executive,111689,1 +14804,Male,34,High School,12,27,61,96,67,9.0,1,65,Rural,HR Executive,96045,1 +14805,Male,48,Bachelors,8,84,19,76,49,2.0,4,42,Rural,ML Engineer,144573,0 +14806,Male,58,High School,5,91,79,92,27,0.0,4,32,Rural,Software Engineer,58688,1 +14807,Male,50,Masters,11,78,12,6,87,5.0,0,66,Semi-Urban,Software Engineer,28843,0 +14808,Female,42,Diploma,9,81,89,99,41,4.0,4,21,Urban,Data Analyst,32108,1 +14809,Female,44,Bachelors,13,61,32,23,56,5.0,3,20,Rural,Manager,110399,0 +14810,Other,51,Masters,13,48,31,45,80,0.0,2,16,Urban,Manager,82208,0 +14811,Male,22,Diploma,3,22,89,43,46,4.0,0,24,Urban,Manager,97189,0 +14812,Male,36,Diploma,8,25,30,33,7,0.0,5,21,Semi-Urban,Data Analyst,74360,0 +14813,Male,51,Bachelors,12,82,61,46,9,3.0,0,27,Semi-Urban,Manager,103936,0 +14814,Male,25,Masters,8,98,49,81,50,2.0,3,57,Urban,Manager,35482,1 +14815,Male,48,Bachelors,4,1,75,84,2,4.0,3,29,Urban,Software Engineer,34569,0 +14816,Male,53,PhD,4,22,3,33,87,8.0,6,11,Urban,ML Engineer,70551,0 +14817,Male,28,Diploma,12,44,55,84,81,8.0,7,82,Urban,ML Engineer,60957,1 +14818,Male,58,Diploma,2,37,44,6,68,7.0,2,80,Urban,Manager,147614,0 +14819,Male,32,High School,10,28,39,59,87,4.0,5,42,Semi-Urban,Software Engineer,78096,0 +14820,Male,31,Diploma,7,47,0,24,68,3.0,7,31,Urban,HR Executive,132559,0 +14821,Male,28,Masters,2,12,75,81,60,1.0,0,56,Semi-Urban,Software Engineer,123220,0 +14822,Male,34,Bachelors,14,96,18,75,54,1.0,7,35,Semi-Urban,Data Analyst,36011,0 +14823,Male,45,Bachelors,16,80,29,38,73,2.0,7,55,Semi-Urban,Software Engineer,80499,0 +14824,Male,52,Bachelors,16,48,52,21,25,8.0,3,27,Urban,Manager,52007,0 +14825,Male,21,Diploma,19,45,80,28,8,2.0,7,16,Rural,Software Engineer,101678,0 +14826,Male,51,Bachelors,13,88,11,8,80,4.0,0,25,Rural,ML Engineer,45981,0 +14827,Male,39,Masters,18,80,82,92,87,8.0,0,33,Rural,Manager,97628,1 +14828,Female,57,Diploma,10,5,9,75,91,9.0,4,46,Urban,ML Engineer,106032,0 +14829,Female,42,Bachelors,12,71,19,6,90,5.0,3,82,Rural,ML Engineer,142956,0 +14830,Female,36,Bachelors,5,27,92,52,6,2.0,7,98,Rural,HR Executive,71365,1 +14831,Male,32,High School,15,52,17,30,40,3.0,2,66,Semi-Urban,Data Analyst,119270,0 +14832,Male,34,High School,14,33,18,15,38,9.0,7,10,Urban,Manager,26182,0 +14833,Female,45,High School,9,32,86,54,78,7.0,4,22,Rural,Manager,27096,0 +14834,Male,30,High School,7,47,91,46,15,3.0,1,10,Rural,ML Engineer,49979,0 +14835,Female,31,Bachelors,13,86,91,29,23,7.0,2,7,Urban,Data Analyst,23571,0 +14836,Male,27,Bachelors,7,48,59,99,10,4.0,0,25,Urban,ML Engineer,122463,0 +14837,Male,57,PhD,10,77,61,62,12,4.0,7,99,Urban,Software Engineer,91761,1 +14838,Female,27,Masters,16,70,54,95,40,0.0,4,46,Urban,Manager,144702,1 +14839,Male,28,Diploma,9,20,51,83,41,7.0,5,27,Urban,HR Executive,81744,0 +14840,Male,32,Diploma,10,64,24,88,72,6.0,2,35,Rural,Data Analyst,65741,0 +14841,Male,25,Bachelors,12,15,87,10,55,2.0,5,96,Rural,Manager,88729,0 +14842,Male,52,Bachelors,18,88,66,6,53,3.0,3,36,Semi-Urban,Manager,91351,0 +14843,Male,39,Masters,14,5,20,62,60,2.0,6,64,Semi-Urban,Manager,82118,0 +14844,Male,50,Diploma,4,44,51,35,73,6.0,0,82,Rural,Data Analyst,29021,0 +14845,Female,46,Masters,14,48,64,76,2,8.0,2,48,Rural,HR Executive,92453,0 +14846,Female,52,Masters,4,86,88,64,48,1.0,5,10,Rural,HR Executive,85122,1 +14847,Male,44,PhD,0,84,83,30,95,0.0,4,9,Urban,ML Engineer,92372,0 +14848,Other,42,Bachelors,7,72,82,93,16,0.0,5,49,Semi-Urban,Manager,56244,1 +14849,Male,50,Bachelors,5,98,8,99,35,5.0,5,18,Semi-Urban,ML Engineer,47305,0 +14850,Male,52,Masters,6,79,42,11,42,9.0,3,72,Urban,ML Engineer,113631,0 +14851,Female,30,Bachelors,14,77,49,85,70,2.0,4,32,Urban,Software Engineer,25134,1 +14852,Female,57,Diploma,10,96,31,48,49,5.0,4,58,Semi-Urban,ML Engineer,148799,0 +14853,Female,51,Bachelors,5,48,36,91,7,3.0,0,21,Semi-Urban,Manager,121890,0 +14854,Male,52,Masters,17,62,50,33,74,1.0,1,36,Urban,HR Executive,34106,0 +14855,Male,45,PhD,11,33,32,40,52,0.0,5,69,Urban,ML Engineer,63769,0 +14856,Female,27,Masters,7,63,48,61,31,7.0,0,71,Semi-Urban,Software Engineer,67022,1 +14857,Male,33,Diploma,3,2,0,69,96,6.0,5,76,Rural,Data Analyst,143685,0 +14858,Female,52,PhD,7,33,74,65,4,5.0,1,2,Urban,Manager,24573,0 +14859,Male,31,Bachelors,12,2,70,70,8,1.0,1,33,Semi-Urban,HR Executive,120478,0 +14860,Female,28,PhD,5,60,77,40,83,5.0,4,3,Semi-Urban,HR Executive,42400,0 +14861,Male,27,Masters,14,97,38,43,98,1.0,0,50,Urban,Data Analyst,34466,0 +14862,Male,54,High School,0,24,35,74,0,6.0,1,43,Rural,HR Executive,64996,0 +14863,Male,41,Bachelors,19,76,48,8,43,4.0,1,22,Urban,Data Analyst,103258,0 +14864,Female,24,Bachelors,11,52,16,26,10,7.0,7,58,Urban,Data Analyst,146284,0 +14865,Female,21,Bachelors,2,15,52,28,80,6.0,3,44,Rural,ML Engineer,129452,0 +14866,Male,40,Diploma,0,6,65,48,59,8.0,0,14,Semi-Urban,ML Engineer,146650,0 +14867,Female,34,Masters,4,68,91,11,12,1.0,5,87,Urban,Data Analyst,87812,1 +14868,Male,27,Diploma,3,37,70,55,65,3.0,0,94,Semi-Urban,HR Executive,23880,1 +14869,Male,30,Diploma,7,25,4,88,69,1.0,0,89,Urban,Software Engineer,127341,0 +14870,Male,32,Bachelors,1,45,58,16,54,2.0,3,47,Urban,Software Engineer,76167,0 +14871,Male,36,Masters,13,62,48,63,19,3.0,3,3,Semi-Urban,HR Executive,39073,0 +14872,Male,53,Bachelors,3,99,84,42,68,3.0,0,49,Urban,Data Analyst,28198,1 +14873,Male,21,Bachelors,6,63,87,13,37,1.0,3,17,Urban,ML Engineer,51277,0 +14874,Female,33,Bachelors,2,97,66,19,59,9.0,5,62,Urban,ML Engineer,103327,1 +14875,Female,41,Diploma,18,74,16,69,9,9.0,1,37,Urban,Data Analyst,52831,0 +14876,Female,50,PhD,17,2,46,74,82,3.0,1,69,Rural,ML Engineer,106245,0 +14877,Male,34,Bachelors,2,84,73,6,21,3.0,2,65,Semi-Urban,Manager,117340,0 +14878,Female,52,Bachelors,7,53,9,77,21,5.0,0,11,Urban,Data Analyst,25837,0 +14879,Female,39,Bachelors,0,22,90,94,69,8.0,5,89,Rural,Manager,131162,1 +14880,Male,36,High School,4,75,27,22,77,1.0,6,48,Urban,Data Analyst,42521,0 +14881,Female,40,Masters,12,44,10,66,30,3.0,5,5,Rural,Data Analyst,32790,0 +14882,Male,24,Diploma,5,72,21,10,21,2.0,4,21,Rural,HR Executive,56162,0 +14883,Male,54,High School,8,28,22,83,95,7.0,0,21,Urban,Software Engineer,25955,0 +14884,Male,37,High School,14,98,6,54,47,1.0,1,76,Urban,Software Engineer,61637,0 +14885,Male,28,Bachelors,8,43,6,62,10,9.0,1,9,Semi-Urban,Manager,101228,0 +14886,Female,42,Bachelors,16,81,11,61,4,1.0,1,73,Rural,Software Engineer,52392,0 +14887,Male,34,Diploma,13,13,32,35,12,1.0,4,22,Semi-Urban,Data Analyst,41497,0 +14888,Male,48,Bachelors,3,14,69,27,47,2.0,6,3,Urban,ML Engineer,97073,0 +14889,Female,45,Diploma,5,7,16,66,10,9.0,5,65,Urban,HR Executive,38326,0 +14890,Female,58,High School,4,85,44,17,84,7.0,4,50,Urban,Manager,51217,0 +14891,Female,39,Bachelors,18,34,76,61,14,2.0,0,88,Semi-Urban,Software Engineer,120849,1 +14892,Male,27,Bachelors,12,8,90,15,87,6.0,1,31,Semi-Urban,HR Executive,26940,0 +14893,Male,51,Diploma,4,57,94,6,32,1.0,6,46,Semi-Urban,HR Executive,112727,0 +14894,Female,26,Bachelors,17,80,25,95,16,5.0,4,93,Urban,HR Executive,20280,1 +14895,Male,32,Bachelors,0,61,52,21,48,2.0,3,91,Rural,Data Analyst,98952,0 +14896,Male,42,Diploma,4,47,71,77,0,8.0,4,34,Rural,Manager,64337,0 +14897,Male,38,Masters,5,16,52,0,6,7.0,3,28,Rural,HR Executive,128558,0 +14898,Male,48,High School,16,53,68,72,30,4.0,6,2,Semi-Urban,Manager,24269,0 +14899,Male,54,Bachelors,14,60,93,13,73,0.0,3,67,Urban,ML Engineer,78752,0 +14900,Male,50,Diploma,1,10,21,4,79,7.0,6,31,Urban,Manager,71586,0 +14901,Male,59,Diploma,5,55,88,44,69,3.0,3,89,Urban,ML Engineer,80064,1 +14902,Male,30,Diploma,5,39,97,40,22,8.0,4,31,Rural,Software Engineer,34171,0 +14903,Male,59,Diploma,12,27,33,65,9,6.0,4,43,Semi-Urban,Software Engineer,25979,0 +14904,Male,45,Masters,7,53,91,23,14,0.0,7,47,Urban,HR Executive,70420,0 +14905,Female,39,Masters,3,76,5,23,99,5.0,2,56,Urban,ML Engineer,101769,0 +14906,Female,58,High School,16,43,61,21,63,1.0,3,39,Urban,Data Analyst,118119,0 +14907,Male,57,Diploma,12,56,43,37,36,5.0,7,57,Urban,ML Engineer,145543,0 +14908,Male,36,Masters,5,99,2,9,48,6.0,4,4,Rural,Data Analyst,24366,0 +14909,Male,54,High School,18,39,25,89,45,9.0,5,76,Semi-Urban,Data Analyst,147478,0 +14910,Male,55,Bachelors,4,36,25,83,22,7.0,5,16,Urban,ML Engineer,92350,0 +14911,Male,55,High School,4,57,74,19,30,2.0,4,88,Urban,Data Analyst,149932,1 +14912,Male,36,High School,3,35,33,3,32,5.0,7,24,Rural,HR Executive,43502,0 +14913,Female,25,Bachelors,15,93,84,36,0,6.0,6,42,Urban,HR Executive,63557,1 +14914,Female,32,High School,16,25,38,79,66,9.0,6,55,Urban,HR Executive,139765,0 +14915,Male,34,Masters,10,9,88,0,45,3.0,5,43,Semi-Urban,Data Analyst,65597,0 +14916,Male,21,Bachelors,10,26,16,23,14,8.0,1,97,Urban,HR Executive,147213,0 +14917,Female,58,Masters,10,18,95,71,19,1.0,4,54,Semi-Urban,Manager,78397,0 +14918,Male,35,High School,8,19,91,64,33,9.0,4,95,Urban,Data Analyst,109385,1 +14919,Female,51,Diploma,14,34,74,3,20,3.0,6,35,Urban,Data Analyst,55119,0 +14920,Male,54,Diploma,11,36,10,38,10,5.0,7,31,Urban,Data Analyst,144976,0 +14921,Female,43,Diploma,5,75,78,79,69,5.0,3,23,Urban,Manager,108744,1 +14922,Female,31,Bachelors,10,31,72,84,31,7.0,0,19,Urban,Data Analyst,133325,0 +14923,Female,57,Diploma,2,78,92,13,57,6.0,0,10,Urban,Software Engineer,54807,0 +14924,Male,34,High School,6,4,7,49,71,7.0,1,34,Urban,ML Engineer,105546,0 +14925,Male,30,Bachelors,13,67,54,19,67,3.0,1,90,Urban,ML Engineer,33142,0 +14926,Male,36,High School,9,68,3,18,85,8.0,3,59,Rural,HR Executive,111366,0 +14927,Female,42,Bachelors,8,72,22,29,18,9.0,4,75,Urban,Data Analyst,36050,0 +14928,Male,28,Bachelors,16,87,76,87,59,6.0,7,79,Urban,Manager,98807,1 +14929,Male,51,Bachelors,3,88,56,18,63,9.0,4,29,Rural,Data Analyst,146367,0 +14930,Male,30,Bachelors,11,75,73,7,3,2.0,6,63,Rural,HR Executive,131835,0 +14931,Male,50,PhD,0,14,83,31,52,7.0,0,80,Semi-Urban,Data Analyst,147745,0 +14932,Male,34,Masters,12,52,91,66,38,2.0,5,55,Urban,Data Analyst,41843,1 +14933,Male,24,Bachelors,12,62,5,56,53,1.0,0,49,Semi-Urban,ML Engineer,127044,0 +14934,Male,30,Masters,6,83,55,88,79,2.0,7,19,Urban,ML Engineer,21566,1 +14935,Male,25,Bachelors,7,76,18,47,9,0.0,1,13,Urban,Data Analyst,57327,0 +14936,Female,58,Diploma,18,44,16,58,58,6.0,7,46,Urban,Software Engineer,130572,0 +14937,Female,50,High School,13,45,37,86,60,3.0,1,90,Semi-Urban,ML Engineer,90890,1 +14938,Female,31,Diploma,10,5,58,19,55,1.0,2,0,Semi-Urban,Software Engineer,34353,0 +14939,Male,24,Bachelors,18,28,55,66,19,5.0,3,49,Urban,Software Engineer,137457,0 +14940,Female,49,High School,3,49,60,5,45,1.0,5,7,Urban,HR Executive,66099,0 +14941,Male,47,Diploma,13,28,96,36,78,1.0,2,45,Rural,Software Engineer,56448,0 +14942,Male,44,High School,13,16,64,32,10,6.0,5,3,Urban,Data Analyst,147892,0 +14943,Male,57,Bachelors,5,70,24,74,75,7.0,5,65,Urban,Data Analyst,100364,0 +14944,Male,35,Bachelors,16,20,28,54,43,8.0,4,32,Semi-Urban,Manager,137400,0 +14945,Male,24,PhD,3,67,2,28,35,8.0,2,99,Urban,ML Engineer,88936,0 +14946,Other,34,Bachelors,13,14,58,57,8,6.0,7,98,Rural,Data Analyst,69972,0 +14947,Male,33,High School,13,39,87,18,80,1.0,3,50,Semi-Urban,Data Analyst,34719,0 +14948,Male,58,Masters,19,53,46,85,45,7.0,4,53,Urban,Manager,36126,1 +14949,Male,54,Diploma,12,38,25,74,19,9.0,2,44,Semi-Urban,Data Analyst,144586,0 +14950,Male,25,Bachelors,15,23,15,20,22,5.0,5,54,Rural,HR Executive,25639,0 +14951,Male,26,Bachelors,18,18,73,41,73,7.0,5,72,Urban,Manager,32597,0 +14952,Male,59,Bachelors,8,49,67,56,30,2.0,3,58,Urban,Manager,132877,0 +14953,Female,22,Diploma,7,76,10,58,94,2.0,2,78,Rural,Data Analyst,50533,0 +14954,Male,57,High School,16,30,75,37,22,2.0,6,37,Urban,Software Engineer,85448,0 +14955,Male,32,Diploma,0,28,99,94,60,4.0,3,38,Urban,Data Analyst,88105,1 +14956,Female,42,Bachelors,0,7,8,41,33,3.0,7,11,Rural,HR Executive,43864,0 +14957,Female,24,Bachelors,19,99,87,87,61,4.0,0,50,Semi-Urban,Data Analyst,74613,1 +14958,Female,35,Masters,12,19,50,38,36,5.0,4,7,Urban,HR Executive,60029,0 +14959,Female,40,Diploma,12,99,27,48,21,3.0,0,78,Rural,Data Analyst,125079,1 +14960,Male,52,Masters,5,89,44,27,70,5.0,1,67,Urban,Software Engineer,91202,0 +14961,Male,51,Bachelors,18,29,93,85,86,3.0,3,13,Rural,ML Engineer,148284,0 +14962,Female,55,Bachelors,1,0,78,71,96,9.0,4,95,Rural,Data Analyst,20922,1 +14963,Female,44,PhD,16,62,77,81,85,8.0,7,14,Rural,HR Executive,109291,0 +14964,Male,48,Masters,1,46,49,44,29,7.0,2,64,Rural,ML Engineer,130427,0 +14965,Male,40,Diploma,16,6,19,96,57,4.0,3,16,Semi-Urban,HR Executive,43096,0 +14966,Female,49,Bachelors,16,22,64,11,51,4.0,1,47,Urban,ML Engineer,120720,0 +14967,Male,26,Bachelors,18,82,33,20,25,0.0,5,18,Semi-Urban,ML Engineer,149509,0 +14968,Male,46,Masters,12,38,72,2,0,8.0,6,31,Rural,ML Engineer,116640,0 +14969,Male,36,Bachelors,6,65,64,83,49,6.0,2,52,Urban,Data Analyst,23510,1 +14970,Female,34,High School,17,35,4,65,86,6.0,4,0,Rural,ML Engineer,131878,0 +14971,Other,49,Masters,6,72,7,23,30,3.0,0,55,Urban,ML Engineer,136852,0 +14972,Male,43,Diploma,6,25,39,59,78,2.0,7,71,Urban,HR Executive,102477,0 +14973,Male,31,Bachelors,11,33,75,53,80,8.0,3,12,Rural,Manager,135580,0 +14974,Male,52,Masters,2,97,2,97,14,6.0,7,21,Urban,Manager,87300,0 +14975,Male,55,Bachelors,16,36,11,1,98,9.0,0,61,Urban,ML Engineer,135446,0 +14976,Male,21,Masters,18,76,16,75,54,4.0,6,6,Rural,Manager,30305,0 +14977,Male,33,High School,15,92,19,26,0,3.0,2,82,Semi-Urban,ML Engineer,115398,0 +14978,Male,27,High School,17,57,7,6,10,2.0,2,24,Urban,Manager,48167,0 +14979,Female,27,Masters,3,83,56,36,2,5.0,2,43,Semi-Urban,Software Engineer,22972,0 +14980,Female,34,Bachelors,4,93,93,28,79,0.0,3,22,Urban,ML Engineer,50019,0 +14981,Male,46,Masters,19,46,88,53,54,3.0,4,60,Urban,Software Engineer,66282,1 +14982,Male,37,PhD,1,25,32,32,99,5.0,1,41,Urban,ML Engineer,49527,0 +14983,Other,49,Diploma,12,92,8,17,28,0.0,4,18,Urban,Software Engineer,135402,0 +14984,Male,31,Bachelors,10,49,92,50,74,3.0,6,47,Urban,ML Engineer,21852,1 +14985,Female,30,PhD,16,30,69,30,77,0.0,4,50,Semi-Urban,HR Executive,46162,0 +14986,Male,27,Masters,2,21,80,49,21,7.0,0,57,Rural,Data Analyst,84505,0 +14987,Female,40,Masters,16,68,69,14,2,5.0,4,55,Urban,HR Executive,46481,0 +14988,Female,35,Diploma,6,15,55,84,55,5.0,3,36,Urban,Manager,144959,0 +14989,Female,22,Masters,0,83,65,33,83,0.0,1,61,Semi-Urban,Manager,51178,1 +14990,Female,24,Masters,19,35,71,47,29,1.0,3,64,Semi-Urban,Data Analyst,48482,0 +14991,Female,47,Bachelors,4,89,80,59,57,8.0,4,96,Urban,Data Analyst,133247,1 +14992,Male,23,PhD,15,6,73,54,55,0.0,0,33,Urban,Data Analyst,110110,0 +14993,Male,21,Diploma,18,81,31,95,29,3.0,6,6,Rural,ML Engineer,86590,0 +14994,Male,27,Bachelors,13,22,70,98,76,5.0,7,17,Urban,Data Analyst,62091,0 +14995,Female,47,Masters,7,15,71,72,27,1.0,4,49,Rural,Manager,106605,0 +14996,Female,54,Diploma,14,73,2,45,54,6.0,2,88,Urban,HR Executive,87726,0 +14997,Male,23,Bachelors,2,96,80,63,46,6.0,5,73,Rural,Manager,64889,1 +14998,Male,39,Diploma,9,95,69,56,54,0.0,2,14,Urban,Manager,29455,0 +14999,Female,26,Diploma,6,48,21,86,20,5.0,0,9,Urban,Data Analyst,27488,0 +15000,Male,53,Bachelors,5,54,81,66,99,4.0,1,99,Urban,Software Engineer,89891,1 +15001,Male,32,Bachelors,11,44,1,68,5,1.0,3,97,Rural,Software Engineer,41164,0 +15002,Female,44,Bachelors,14,45,74,92,35,6.0,1,46,Rural,Manager,91962,1 +15003,Male,34,Diploma,16,89,17,39,12,9.0,1,63,Urban,Data Analyst,24685,0 +15004,Male,37,Bachelors,1,90,89,38,48,3.0,1,80,Semi-Urban,Software Engineer,71005,1 +15005,Male,56,Diploma,19,95,28,68,86,8.0,6,13,Urban,HR Executive,60997,0 +15006,Male,40,High School,15,81,47,33,21,7.0,2,49,Urban,HR Executive,59659,0 +15007,Male,28,Bachelors,6,24,92,86,13,4.0,7,36,Semi-Urban,ML Engineer,51254,1 +15008,Male,58,High School,17,18,26,94,61,1.0,7,64,Urban,Manager,128896,0 +15009,Male,45,Bachelors,19,37,18,50,29,3.0,6,58,Urban,Data Analyst,55299,0 +15010,Male,24,Bachelors,0,31,98,39,28,0.0,0,63,Urban,Software Engineer,96045,0 +15011,Male,49,Masters,1,76,26,47,31,7.0,0,37,Urban,ML Engineer,66549,0 +15012,Male,23,Bachelors,10,12,74,34,90,9.0,0,93,Urban,HR Executive,71204,0 +15013,Other,51,Bachelors,16,7,27,27,7,7.0,6,15,Urban,ML Engineer,109573,0 +15014,Male,57,High School,7,94,14,92,12,3.0,1,86,Urban,HR Executive,79194,1 +15015,Female,30,High School,3,82,0,22,21,3.0,4,21,Urban,ML Engineer,107094,0 +15016,Female,32,Diploma,11,56,25,65,35,0.0,0,96,Urban,Manager,131322,1 +15017,Male,23,Diploma,18,27,81,68,91,1.0,6,98,Semi-Urban,Manager,117056,1 +15018,Female,29,Diploma,7,47,58,48,47,9.0,5,57,Urban,HR Executive,130721,0 +15019,Male,34,Bachelors,11,41,51,84,81,2.0,5,40,Semi-Urban,ML Engineer,56574,0 +15020,Female,34,PhD,19,37,63,63,69,5.0,0,35,Urban,Software Engineer,108316,0 +15021,Male,39,Masters,3,4,69,11,12,7.0,2,95,Semi-Urban,ML Engineer,84588,0 +15022,Female,37,Diploma,14,79,76,90,45,1.0,4,21,Urban,HR Executive,48678,1 +15023,Male,57,Masters,5,48,19,55,69,2.0,6,27,Urban,HR Executive,74356,0 +15024,Female,42,Bachelors,3,67,22,33,98,3.0,3,71,Urban,Software Engineer,128143,0 +15025,Male,41,Bachelors,15,64,46,60,53,0.0,4,78,Urban,Software Engineer,131444,1 +15026,Female,51,Masters,1,41,80,80,56,6.0,4,90,Urban,Data Analyst,124655,1 +15027,Male,59,Bachelors,7,21,81,17,90,8.0,5,56,Urban,Manager,89634,0 +15028,Female,32,Diploma,2,8,32,6,70,5.0,7,85,Urban,Manager,101985,0 +15029,Male,54,Diploma,9,80,36,80,16,8.0,1,75,Semi-Urban,Data Analyst,141322,1 +15030,Male,34,PhD,12,24,65,28,30,8.0,3,89,Semi-Urban,Software Engineer,64866,0 +15031,Female,38,High School,5,71,66,29,68,9.0,1,78,Urban,HR Executive,129541,1 +15032,Female,30,PhD,16,91,77,52,65,6.0,6,98,Urban,Data Analyst,129270,1 +15033,Male,52,PhD,8,63,19,38,88,0.0,7,92,Urban,Software Engineer,29484,0 +15034,Female,43,Bachelors,2,40,40,57,49,0.0,4,23,Semi-Urban,Manager,79314,0 +15035,Female,58,Masters,14,66,25,61,92,2.0,6,12,Semi-Urban,ML Engineer,71340,0 +15036,Female,30,Bachelors,12,52,5,28,93,2.0,7,0,Semi-Urban,Manager,63968,0 +15037,Male,38,Bachelors,6,94,42,77,81,9.0,3,51,Urban,Data Analyst,83092,1 +15038,Male,24,High School,13,53,85,53,61,4.0,5,15,Urban,Data Analyst,75625,0 +15039,Female,23,Diploma,9,55,95,52,63,1.0,0,68,Urban,Manager,101597,1 +15040,Male,49,Masters,6,92,71,34,5,7.0,3,95,Semi-Urban,Software Engineer,124525,1 +15041,Male,32,Masters,18,50,63,96,86,4.0,6,99,Urban,Software Engineer,25418,1 +15042,Male,26,Diploma,19,51,26,11,0,9.0,3,32,Semi-Urban,HR Executive,146064,0 +15043,Male,58,Bachelors,4,86,94,48,16,2.0,7,1,Urban,Software Engineer,96045,0 +15044,Female,44,Diploma,3,38,24,99,89,7.0,1,78,Semi-Urban,Manager,39421,0 +15045,Female,48,Masters,3,33,51,69,19,3.0,0,17,Rural,ML Engineer,147503,0 +15046,Male,57,High School,8,18,52,57,87,4.0,7,77,Urban,Data Analyst,129851,0 +15047,Male,52,Bachelors,6,74,80,23,99,0.0,7,37,Rural,Software Engineer,145530,0 +15048,Male,39,Diploma,10,87,95,92,36,7.0,1,63,Urban,Manager,60197,1 +15049,Male,25,High School,13,64,22,87,68,9.0,5,36,Rural,HR Executive,21826,0 +15050,Male,24,Masters,4,54,95,97,73,0.0,2,33,Urban,ML Engineer,55351,1 +15051,Female,50,High School,19,71,77,13,84,2.0,5,11,Urban,ML Engineer,85423,0 +15052,Female,47,Bachelors,3,10,26,40,84,2.0,3,26,Semi-Urban,Software Engineer,69329,0 +15053,Male,54,High School,7,83,13,33,87,5.0,2,42,Urban,ML Engineer,87992,0 +15054,Female,26,Bachelors,1,78,77,11,47,9.0,5,60,Semi-Urban,Software Engineer,95141,0 +15055,Male,35,Bachelors,9,54,20,94,78,8.0,1,7,Semi-Urban,Manager,118117,0 +15056,Female,41,Bachelors,11,28,99,96,47,0.0,6,40,Semi-Urban,HR Executive,70020,1 +15057,Male,54,Diploma,6,49,86,28,44,7.0,7,23,Rural,ML Engineer,108605,0 +15058,Female,50,Bachelors,7,27,53,94,94,7.0,2,69,Urban,Software Engineer,48256,1 +15059,Male,25,High School,10,83,92,79,54,6.0,2,55,Rural,ML Engineer,92092,1 +15060,Male,34,Bachelors,1,80,59,28,99,8.0,4,43,Rural,Data Analyst,104620,0 +15061,Male,44,Bachelors,19,13,53,17,92,5.0,6,70,Semi-Urban,Data Analyst,64027,0 +15062,Male,56,High School,18,14,28,26,86,8.0,5,58,Semi-Urban,Manager,139332,0 +15063,Male,35,Bachelors,13,33,9,47,8,1.0,3,70,Urban,Software Engineer,60246,0 +15064,Male,44,Diploma,0,51,60,99,20,6.0,7,22,Urban,ML Engineer,89309,0 +15065,Male,48,Bachelors,3,53,6,23,1,3.0,3,17,Urban,ML Engineer,107186,0 +15066,Female,44,Masters,18,0,87,66,80,7.0,4,14,Rural,Manager,27605,0 +15067,Male,43,High School,16,15,89,60,7,8.0,6,78,Urban,Software Engineer,97243,1 +15068,Female,27,Diploma,12,64,75,48,47,8.0,1,26,Urban,Manager,111774,0 +15069,Male,30,High School,11,53,22,95,15,6.0,3,52,Urban,Data Analyst,105411,0 +15070,Female,53,Masters,1,70,80,33,50,7.0,4,31,Urban,ML Engineer,66964,0 +15071,Female,58,Bachelors,4,14,17,22,74,0.0,2,64,Urban,Software Engineer,49332,0 +15072,Male,29,Bachelors,14,39,71,0,50,3.0,6,35,Urban,ML Engineer,51089,0 +15073,Female,59,High School,4,52,78,94,58,1.0,2,70,Urban,HR Executive,84792,1 +15074,Male,41,Masters,18,34,3,49,98,5.0,3,79,Urban,Manager,25500,0 +15075,Female,49,PhD,15,61,45,85,48,0.0,1,44,Semi-Urban,Software Engineer,91908,0 +15076,Male,49,Masters,2,83,9,94,12,4.0,7,45,Urban,Software Engineer,32981,0 +15077,Male,26,Diploma,19,80,5,52,53,1.0,0,77,Semi-Urban,Manager,35025,0 +15078,Male,24,Bachelors,3,84,62,20,31,6.0,0,60,Rural,Data Analyst,61630,0 +15079,Male,39,PhD,2,27,12,46,41,0.0,0,81,Urban,Data Analyst,115840,0 +15080,Male,31,Bachelors,9,89,28,54,54,8.0,6,49,Urban,Manager,108399,0 +15081,Female,39,Bachelors,5,73,68,93,40,3.0,1,28,Urban,ML Engineer,80113,1 +15082,Male,27,High School,7,96,98,24,10,2.0,1,38,Semi-Urban,HR Executive,88591,1 +15083,Male,40,Diploma,11,63,69,2,38,4.0,1,88,Semi-Urban,ML Engineer,146675,0 +15084,Male,27,High School,4,2,78,50,62,3.0,2,64,Semi-Urban,ML Engineer,116658,0 +15085,Male,32,Bachelors,13,6,33,87,6,6.0,1,85,Urban,Data Analyst,42558,0 +15086,Male,35,Diploma,1,37,11,63,20,0.0,4,0,Urban,ML Engineer,141702,0 +15087,Female,36,Bachelors,11,15,81,20,14,2.0,6,51,Rural,HR Executive,47510,0 +15088,Male,30,Bachelors,8,64,66,2,23,4.0,1,32,Rural,Data Analyst,40696,0 +15089,Male,36,High School,6,22,1,54,12,8.0,6,95,Rural,Software Engineer,52119,0 +15090,Male,45,PhD,0,23,15,46,63,3.0,1,99,Urban,Data Analyst,64125,0 +15091,Male,29,Bachelors,10,65,26,77,43,8.0,0,31,Urban,Manager,122540,0 +15092,Female,21,Diploma,7,86,96,33,61,0.0,2,50,Urban,Software Engineer,116197,1 +15093,Male,33,Bachelors,7,76,66,43,89,7.0,1,66,Urban,Data Analyst,135935,1 +15094,Male,41,Masters,12,90,19,41,97,6.0,4,50,Urban,Data Analyst,27270,0 +15095,Male,46,Bachelors,7,31,12,64,64,2.0,5,79,Urban,Software Engineer,96513,0 +15096,Male,36,High School,3,81,99,70,25,0.0,1,54,Urban,HR Executive,64809,1 +15097,Male,21,Masters,15,59,92,92,50,4.0,5,54,Urban,ML Engineer,111953,1 +15098,Male,54,Masters,11,43,89,73,15,4.0,3,88,Semi-Urban,HR Executive,123111,1 +15099,Female,35,Masters,15,83,83,18,47,4.0,4,88,Urban,ML Engineer,87835,1 +15100,Male,23,Bachelors,11,74,25,30,16,1.0,3,16,Semi-Urban,ML Engineer,63385,0 +15101,Male,34,Bachelors,7,26,88,75,1,1.0,6,73,Rural,HR Executive,70659,1 +15102,Male,55,Masters,10,34,18,88,90,0.0,7,42,Semi-Urban,HR Executive,115527,0 +15103,Male,40,Bachelors,3,58,0,67,88,7.0,2,83,Urban,HR Executive,91505,0 +15104,Male,54,High School,17,29,27,31,76,0.0,7,77,Rural,Data Analyst,105349,0 +15105,Female,47,Diploma,2,23,27,56,6,1.0,5,43,Semi-Urban,Manager,118820,0 +15106,Female,56,Bachelors,19,71,95,30,11,4.0,2,75,Urban,Data Analyst,131313,1 +15107,Male,52,Masters,18,31,2,88,94,3.0,7,79,Urban,ML Engineer,128698,0 +15108,Male,51,Bachelors,8,86,6,2,57,4.0,2,15,Urban,HR Executive,85129,0 +15109,Male,26,Masters,6,21,31,19,48,6.0,2,70,Urban,ML Engineer,46481,0 +15110,Male,53,Bachelors,18,2,55,15,53,3.0,0,40,Semi-Urban,ML Engineer,100441,0 +15111,Female,58,High School,4,6,91,41,58,0.0,6,24,Urban,Manager,41509,0 +15112,Female,49,Bachelors,7,86,4,45,43,1.0,1,13,Urban,Data Analyst,136384,0 +15113,Female,41,Bachelors,12,13,75,75,93,6.0,7,71,Rural,Data Analyst,96253,0 +15114,Male,45,PhD,19,10,70,49,43,8.0,1,35,Rural,ML Engineer,89853,0 +15115,Male,35,Diploma,12,30,28,5,47,6.0,7,92,Urban,ML Engineer,33843,0 +15116,Female,44,Bachelors,4,14,16,72,24,2.0,4,92,Urban,HR Executive,53172,0 +15117,Female,28,Diploma,17,82,93,82,91,3.0,7,36,Urban,Manager,105744,1 +15118,Female,34,Masters,6,75,87,18,76,5.0,4,62,Semi-Urban,ML Engineer,20298,1 +15119,Male,40,Masters,7,14,82,96,4,7.0,2,34,Urban,Data Analyst,63598,0 +15120,Male,53,Diploma,15,52,99,5,86,3.0,0,23,Urban,HR Executive,41275,0 +15121,Male,56,High School,8,59,67,96,93,2.0,0,39,Urban,Data Analyst,26325,1 +15122,Male,55,Diploma,17,55,14,52,31,3.0,2,55,Rural,Data Analyst,102004,0 +15123,Male,58,Bachelors,19,80,13,89,36,0.0,3,48,Urban,Software Engineer,57387,0 +15124,Female,27,High School,3,15,32,81,89,6.0,3,47,Urban,ML Engineer,124036,0 +15125,Male,44,High School,12,26,96,73,57,3.0,5,47,Urban,ML Engineer,63289,1 +15126,Male,32,Bachelors,11,71,17,22,42,7.0,4,93,Urban,Data Analyst,141388,0 +15127,Female,36,Masters,16,89,75,10,51,2.0,2,2,Urban,ML Engineer,45178,0 +15128,Male,37,High School,7,88,58,17,62,3.0,2,86,Semi-Urban,Manager,24006,1 +15129,Female,55,Bachelors,4,61,37,66,62,6.0,3,31,Urban,ML Engineer,140127,0 +15130,Male,43,Masters,17,17,82,25,67,4.0,7,13,Urban,Manager,74568,0 +15131,Male,42,Bachelors,6,35,37,43,19,7.0,3,69,Semi-Urban,Software Engineer,87209,0 +15132,Other,35,Masters,15,35,92,7,44,4.0,7,50,Urban,Manager,83838,0 +15133,Female,45,PhD,12,13,26,71,76,5.0,7,13,Urban,ML Engineer,99174,0 +15134,Male,40,Bachelors,2,92,10,78,35,5.0,1,76,Urban,ML Engineer,113431,1 +15135,Female,25,Diploma,0,64,16,81,12,9.0,5,6,Urban,ML Engineer,52080,0 +15136,Male,49,PhD,12,23,79,28,38,1.0,0,45,Semi-Urban,ML Engineer,53340,0 +15137,Male,24,Bachelors,9,40,25,13,88,8.0,7,76,Rural,Software Engineer,97909,0 +15138,Male,52,Bachelors,14,99,27,23,53,5.0,2,95,Urban,Software Engineer,124412,1 +15139,Male,45,Diploma,18,32,34,84,8,3.0,1,59,Urban,HR Executive,98071,0 +15140,Female,57,Bachelors,17,78,52,86,83,9.0,3,99,Semi-Urban,Software Engineer,124275,1 +15141,Female,45,Bachelors,17,45,87,38,21,3.0,4,87,Semi-Urban,HR Executive,139878,1 +15142,Other,28,Diploma,10,25,9,31,95,1.0,0,79,Urban,Software Engineer,130388,0 +15143,Female,54,Bachelors,2,81,8,36,60,0.0,3,49,Urban,Software Engineer,106455,0 +15144,Male,42,Diploma,9,2,74,34,65,0.0,3,72,Urban,ML Engineer,48302,0 +15145,Female,59,Bachelors,17,44,35,4,31,6.0,6,7,Urban,Data Analyst,54680,0 +15146,Other,39,Diploma,13,1,31,2,49,3.0,3,83,Rural,HR Executive,67755,0 +15147,Female,45,Masters,0,28,4,34,35,1.0,5,24,Rural,Manager,92923,0 +15148,Female,24,Bachelors,6,99,54,41,0,9.0,3,93,Semi-Urban,Manager,84313,1 +15149,Female,52,Bachelors,2,49,0,53,20,4.0,6,12,Semi-Urban,Data Analyst,85030,0 +15150,Male,56,PhD,17,37,60,85,99,1.0,6,54,Urban,Data Analyst,101205,1 +15151,Female,55,Bachelors,18,73,23,63,20,7.0,0,49,Semi-Urban,Data Analyst,66250,0 +15152,Female,52,Bachelors,1,3,50,90,92,7.0,3,14,Semi-Urban,ML Engineer,103930,0 +15153,Other,36,Bachelors,18,7,72,79,95,9.0,6,21,Semi-Urban,HR Executive,52470,0 +15154,Male,45,Bachelors,1,17,60,15,18,6.0,5,11,Rural,Software Engineer,103878,0 +15155,Male,49,Diploma,11,15,65,46,37,9.0,1,57,Urban,HR Executive,30021,0 +15156,Female,26,Bachelors,15,75,20,36,60,0.0,5,24,Urban,Data Analyst,46858,0 +15157,Male,35,Masters,6,30,38,48,99,0.0,4,76,Rural,HR Executive,55281,0 +15158,Female,27,Diploma,17,26,42,82,71,3.0,3,42,Urban,Data Analyst,20116,0 +15159,Male,39,Masters,10,25,64,29,51,3.0,5,54,Urban,Data Analyst,62390,0 +15160,Male,45,High School,9,58,77,7,51,7.0,0,4,Urban,HR Executive,135972,0 +15161,Male,42,Bachelors,11,45,21,59,80,0.0,0,95,Rural,Manager,108505,0 +15162,Male,36,Bachelors,14,60,38,52,88,1.0,4,79,Urban,Data Analyst,87303,0 +15163,Male,27,Bachelors,3,44,96,54,60,8.0,3,89,Urban,Data Analyst,116307,1 +15164,Male,47,Masters,9,58,26,47,51,3.0,0,91,Semi-Urban,HR Executive,101419,0 +15165,Male,23,Bachelors,9,64,5,93,40,8.0,5,24,Rural,HR Executive,139451,0 +15166,Male,54,Bachelors,15,36,49,34,95,9.0,3,95,Urban,Manager,139862,0 +15167,Male,48,Bachelors,5,58,6,31,9,0.0,2,42,Urban,Software Engineer,54840,0 +15168,Male,34,Diploma,15,67,40,77,35,4.0,0,88,Rural,Software Engineer,60585,1 +15169,Male,45,PhD,10,21,12,97,38,2.0,4,19,Rural,ML Engineer,125173,0 +15170,Female,23,Bachelors,13,98,81,2,86,7.0,0,18,Urban,Data Analyst,77551,0 +15171,Male,36,Masters,18,73,90,49,49,4.0,5,13,Semi-Urban,ML Engineer,139258,0 +15172,Male,31,Masters,16,98,50,17,42,8.0,5,2,Urban,ML Engineer,146282,0 +15173,Female,27,Masters,1,92,1,22,40,7.0,0,60,Urban,Software Engineer,127488,0 +15174,Male,39,High School,14,68,19,30,41,7.0,7,20,Semi-Urban,ML Engineer,96043,0 +15175,Other,22,Masters,9,87,61,39,45,3.0,4,95,Semi-Urban,HR Executive,25765,1 +15176,Female,29,High School,6,90,97,47,34,2.0,2,78,Urban,Data Analyst,105993,1 +15177,Male,55,Bachelors,13,62,78,3,41,2.0,2,84,Urban,Software Engineer,115618,0 +15178,Male,50,Bachelors,0,19,86,28,17,9.0,1,96,Urban,Data Analyst,117478,0 +15179,Male,53,Bachelors,9,49,0,54,28,6.0,6,26,Urban,Data Analyst,130115,0 +15180,Male,29,Bachelors,16,59,0,42,29,3.0,5,69,Semi-Urban,Data Analyst,98131,0 +15181,Male,55,Diploma,17,92,64,87,55,0.0,3,10,Urban,Software Engineer,64964,1 +15182,Male,33,Bachelors,18,87,33,84,13,7.0,0,80,Semi-Urban,Data Analyst,129451,1 +15183,Female,56,Bachelors,19,88,74,99,98,8.0,1,55,Urban,HR Executive,119355,1 +15184,Male,23,Diploma,7,70,77,23,61,8.0,1,34,Rural,Software Engineer,66890,0 +15185,Male,38,Bachelors,14,23,60,80,1,0.0,1,46,Urban,Manager,107048,0 +15186,Female,29,PhD,15,15,35,77,67,1.0,6,66,Rural,Data Analyst,30438,0 +15187,Male,21,Bachelors,5,78,2,86,70,5.0,7,28,Urban,Data Analyst,95314,0 +15188,Male,21,Bachelors,9,10,63,6,72,1.0,5,78,Semi-Urban,Software Engineer,26408,0 +15189,Male,54,Diploma,2,88,83,71,32,3.0,5,31,Semi-Urban,ML Engineer,50147,1 +15190,Male,56,Bachelors,10,50,48,4,55,9.0,1,31,Semi-Urban,ML Engineer,124050,0 +15191,Other,23,Diploma,14,37,30,20,12,8.0,0,72,Urban,ML Engineer,113030,0 +15192,Male,25,Diploma,17,45,22,12,71,0.0,4,2,Semi-Urban,Software Engineer,51366,0 +15193,Male,30,Bachelors,9,8,18,9,81,3.0,7,65,Semi-Urban,Data Analyst,25607,0 +15194,Male,51,PhD,14,87,91,86,74,7.0,5,26,Urban,ML Engineer,37702,1 +15195,Male,48,Bachelors,0,18,45,5,18,7.0,7,96,Urban,Software Engineer,67373,0 +15196,Male,48,Masters,17,68,64,34,77,4.0,7,58,Semi-Urban,Software Engineer,98266,0 +15197,Female,28,Masters,14,52,77,17,88,1.0,3,28,Rural,Manager,144148,0 +15198,Female,31,Bachelors,7,3,75,23,32,4.0,3,12,Urban,HR Executive,63676,0 +15199,Male,37,High School,12,64,24,81,48,6.0,2,59,Rural,HR Executive,65024,0 +15200,Male,44,Bachelors,18,83,35,38,84,0.0,2,28,Urban,Software Engineer,147530,0 +15201,Female,52,Bachelors,18,98,18,73,10,3.0,3,78,Semi-Urban,Data Analyst,146410,1 +15202,Male,56,Diploma,7,15,8,50,97,2.0,5,82,Rural,Software Engineer,36961,0 +15203,Male,49,Masters,7,53,69,71,40,0.0,6,91,Urban,Manager,26097,1 +15204,Male,27,Diploma,6,61,4,59,14,2.0,4,44,Urban,Software Engineer,118307,0 +15205,Male,43,Bachelors,16,32,86,86,12,3.0,3,87,Semi-Urban,Software Engineer,96760,1 +15206,Male,36,PhD,2,32,36,70,22,1.0,5,7,Semi-Urban,Manager,47819,0 +15207,Female,48,Bachelors,4,81,33,44,24,5.0,1,32,Rural,ML Engineer,30496,0 +15208,Female,58,High School,16,47,7,76,6,2.0,4,82,Urban,Software Engineer,95610,0 +15209,Male,35,Bachelors,3,48,14,27,81,8.0,0,21,Urban,Manager,146049,0 +15210,Male,24,Bachelors,9,21,96,72,91,6.0,1,50,Urban,Software Engineer,93984,1 +15211,Female,35,Masters,5,34,5,34,81,9.0,3,20,Urban,Data Analyst,26033,0 +15212,Male,47,Diploma,0,95,10,83,33,9.0,4,17,Semi-Urban,Data Analyst,24774,0 +15213,Female,45,Bachelors,11,54,54,97,1,3.0,5,48,Urban,Data Analyst,130003,1 +15214,Male,21,Diploma,11,19,21,2,58,9.0,4,39,Rural,Data Analyst,60374,0 +15215,Male,48,Masters,8,93,36,6,52,9.0,1,8,Semi-Urban,Software Engineer,114909,0 +15216,Male,32,Bachelors,0,51,74,78,59,7.0,1,44,Urban,Software Engineer,71627,1 +15217,Female,23,Masters,17,56,77,1,50,0.0,1,39,Semi-Urban,Manager,22003,0 +15218,Male,41,Bachelors,2,94,15,74,46,1.0,2,40,Rural,Data Analyst,111061,0 +15219,Male,47,PhD,2,27,80,1,50,3.0,3,28,Urban,HR Executive,81334,0 +15220,Male,45,Diploma,2,22,38,63,65,4.0,5,4,Urban,ML Engineer,44420,0 +15221,Female,49,Bachelors,11,51,83,84,27,9.0,2,96,Urban,Manager,62442,1 +15222,Female,47,Bachelors,7,47,81,69,68,3.0,7,17,Rural,Data Analyst,55895,0 +15223,Other,51,Masters,11,36,84,19,83,4.0,0,1,Urban,ML Engineer,23780,0 +15224,Other,34,High School,5,56,4,37,11,2.0,5,19,Urban,ML Engineer,51493,0 +15225,Male,32,Bachelors,16,48,65,16,57,2.0,2,21,Urban,Software Engineer,86946,0 +15226,Male,26,High School,6,49,63,55,45,4.0,3,90,Rural,Software Engineer,135370,1 +15227,Male,35,Diploma,15,90,44,51,41,0.0,1,99,Urban,HR Executive,54401,1 +15228,Male,21,Bachelors,15,54,60,58,17,7.0,4,30,Semi-Urban,Manager,66869,0 +15229,Female,35,Bachelors,8,36,41,39,40,3.0,2,13,Rural,ML Engineer,134674,0 +15230,Female,48,High School,14,22,83,19,60,8.0,6,15,Rural,Data Analyst,72403,0 +15231,Male,34,Diploma,16,4,70,32,12,5.0,0,82,Semi-Urban,Data Analyst,112278,0 +15232,Female,43,Bachelors,4,44,59,60,42,8.0,5,62,Urban,HR Executive,50220,0 +15233,Female,25,High School,18,54,8,13,69,8.0,6,89,Urban,Data Analyst,121955,0 +15234,Male,59,Diploma,3,52,51,17,6,4.0,7,61,Urban,ML Engineer,101285,0 +15235,Male,56,Bachelors,1,55,79,42,65,4.0,1,83,Urban,Manager,143668,1 +15236,Male,57,Bachelors,18,10,30,94,85,5.0,4,60,Rural,Software Engineer,121438,0 +15237,Male,48,High School,16,91,34,74,36,4.0,4,41,Urban,ML Engineer,128963,1 +15238,Male,57,Bachelors,5,75,84,46,20,7.0,3,66,Urban,Data Analyst,38134,1 +15239,Male,39,High School,4,7,7,23,9,6.0,1,73,Urban,Manager,38246,0 +15240,Male,57,Bachelors,18,64,33,89,80,1.0,1,16,Rural,Software Engineer,145311,0 +15241,Other,42,Bachelors,17,59,48,35,74,2.0,1,17,Urban,Software Engineer,61844,0 +15242,Male,27,Masters,2,26,4,6,47,2.0,5,66,Semi-Urban,Manager,94313,0 +15243,Male,40,Bachelors,4,9,85,83,55,4.0,6,58,Urban,Data Analyst,66057,1 +15244,Other,31,Masters,13,74,26,57,18,4.0,6,50,Urban,Software Engineer,78977,0 +15245,Male,23,Diploma,5,98,63,58,2,6.0,4,81,Urban,Software Engineer,130328,1 +15246,Male,44,Masters,12,70,42,80,47,1.0,3,61,Rural,HR Executive,145929,1 +15247,Female,41,Diploma,18,15,6,27,32,7.0,2,26,Urban,Data Analyst,134665,0 +15248,Male,49,Bachelors,1,66,31,30,8,5.0,2,68,Urban,Software Engineer,101919,0 +15249,Female,27,Bachelors,0,24,59,7,58,7.0,7,20,Urban,Software Engineer,88829,0 +15250,Male,31,High School,15,69,28,59,6,9.0,6,4,Rural,Data Analyst,35681,0 +15251,Male,35,Diploma,2,91,72,31,51,3.0,6,7,Semi-Urban,HR Executive,91473,0 +15252,Male,44,Bachelors,15,75,93,24,61,5.0,1,41,Urban,Data Analyst,70736,0 +15253,Male,32,High School,4,55,52,57,12,2.0,1,16,Urban,Data Analyst,67078,0 +15254,Female,42,Diploma,13,92,19,36,54,6.0,3,42,Urban,HR Executive,145393,0 +15255,Female,46,Diploma,17,54,75,54,78,3.0,6,38,Rural,Data Analyst,56216,0 +15256,Female,30,Bachelors,2,11,19,19,68,0.0,5,78,Urban,Manager,20867,0 +15257,Female,43,Bachelors,1,79,79,67,80,3.0,6,61,Urban,Software Engineer,131769,1 +15258,Male,42,High School,3,55,83,22,16,4.0,2,45,Urban,HR Executive,133614,0 +15259,Female,38,Masters,9,35,1,96,1,8.0,5,16,Rural,HR Executive,68125,0 +15260,Female,46,Bachelors,11,82,51,29,11,1.0,3,58,Rural,Data Analyst,32596,0 +15261,Female,25,Diploma,2,13,96,99,44,1.0,4,31,Urban,Manager,144748,0 +15262,Female,50,High School,18,15,82,34,71,7.0,3,16,Rural,Manager,111881,0 +15263,Male,47,Diploma,4,11,54,35,8,2.0,3,94,Semi-Urban,Data Analyst,96431,0 +15264,Male,23,High School,18,69,81,17,2,6.0,6,52,Semi-Urban,ML Engineer,20179,0 +15265,Female,22,High School,13,54,88,98,23,8.0,4,72,Urban,ML Engineer,129639,1 +15266,Male,57,High School,6,92,20,45,28,5.0,2,67,Urban,Manager,114953,0 +15267,Male,42,Masters,10,27,73,25,80,6.0,3,23,Rural,ML Engineer,59432,0 +15268,Female,43,High School,5,83,70,1,17,8.0,3,9,Urban,ML Engineer,59090,0 +15269,Male,23,Bachelors,9,27,9,27,64,1.0,5,19,Urban,Data Analyst,105698,0 +15270,Male,39,Masters,3,48,28,74,47,9.0,1,72,Urban,Data Analyst,41999,0 +15271,Male,26,Bachelors,17,65,58,10,90,0.0,1,41,Rural,Data Analyst,47403,0 +15272,Female,52,Diploma,19,14,17,56,50,4.0,0,52,Rural,ML Engineer,118359,0 +15273,Male,22,Diploma,0,48,95,26,13,4.0,5,31,Urban,Software Engineer,122512,0 +15274,Female,31,Bachelors,16,97,10,4,47,4.0,7,48,Rural,ML Engineer,125073,0 +15275,Male,46,Bachelors,18,81,78,19,47,8.0,2,87,Semi-Urban,ML Engineer,46580,1 +15276,Male,41,PhD,18,77,29,11,65,4.0,5,40,Urban,Manager,118664,0 +15277,Male,50,PhD,17,36,76,32,97,7.0,0,61,Urban,HR Executive,58237,0 +15278,Female,30,High School,6,60,55,36,67,7.0,4,74,Urban,Software Engineer,131071,0 +15279,Male,32,Bachelors,8,54,84,31,61,8.0,6,82,Urban,ML Engineer,144555,1 +15280,Other,44,Bachelors,16,80,37,22,95,1.0,4,12,Urban,ML Engineer,29378,0 +15281,Female,39,Bachelors,16,88,22,30,32,8.0,0,3,Urban,ML Engineer,69162,0 +15282,Female,56,Masters,15,8,73,40,70,1.0,5,51,Urban,Software Engineer,52799,0 +15283,Female,51,Bachelors,19,4,23,36,22,3.0,7,61,Urban,ML Engineer,49600,0 +15284,Male,29,Masters,17,30,72,83,4,3.0,0,51,Semi-Urban,ML Engineer,44662,1 +15285,Male,42,Bachelors,3,3,77,79,60,1.0,2,37,Urban,Manager,61469,0 +15286,Female,46,Diploma,12,40,5,17,70,9.0,6,15,Rural,Data Analyst,23398,0 +15287,Female,23,High School,18,78,61,3,50,6.0,2,81,Urban,Manager,75147,0 +15288,Female,59,Bachelors,19,55,61,61,61,9.0,6,50,Semi-Urban,Software Engineer,138620,0 +15289,Female,32,Diploma,18,92,46,82,35,4.0,0,61,Urban,Manager,26232,1 +15290,Other,54,Bachelors,0,30,21,72,38,4.0,3,30,Urban,Data Analyst,37281,0 +15291,Male,26,Masters,14,15,25,4,61,5.0,0,0,Urban,ML Engineer,132824,0 +15292,Female,43,Bachelors,15,29,57,34,37,5.0,4,44,Semi-Urban,Data Analyst,139364,0 +15293,Female,34,Masters,6,15,31,85,52,9.0,1,98,Semi-Urban,HR Executive,26216,0 +15294,Female,44,Bachelors,6,11,42,36,84,6.0,2,30,Urban,Manager,35676,0 +15295,Male,57,Bachelors,14,97,43,69,39,3.0,6,79,Urban,Manager,131953,1 +15296,Female,28,Masters,3,15,70,35,18,6.0,0,38,Urban,Software Engineer,39465,0 +15297,Female,40,Bachelors,16,41,48,82,12,7.0,3,50,Urban,Manager,99917,0 +15298,Male,42,High School,3,60,92,94,71,7.0,5,45,Urban,HR Executive,83333,1 +15299,Female,51,Bachelors,10,37,48,37,45,2.0,5,28,Urban,Data Analyst,64352,0 +15300,Male,27,Masters,5,37,37,40,93,4.0,4,60,Urban,Software Engineer,37485,0 +15301,Other,57,Diploma,5,52,81,90,20,3.0,0,44,Urban,ML Engineer,63022,1 +15302,Male,29,PhD,5,98,33,93,7,7.0,4,33,Rural,HR Executive,37650,1 +15303,Male,49,Masters,13,8,49,25,4,0.0,3,42,Rural,Data Analyst,64227,0 +15304,Male,37,Bachelors,10,76,53,10,7,6.0,1,91,Rural,Data Analyst,25331,0 +15305,Female,44,Bachelors,4,9,58,56,53,4.0,1,8,Semi-Urban,ML Engineer,125728,0 +15306,Male,36,Bachelors,15,72,23,21,40,8.0,6,54,Semi-Urban,Data Analyst,121914,0 +15307,Female,55,Masters,5,49,59,65,59,6.0,4,68,Urban,Data Analyst,62903,1 +15308,Female,53,Diploma,11,49,45,13,95,8.0,1,83,Urban,Manager,100282,0 +15309,Female,37,High School,13,24,15,43,4,8.0,2,15,Urban,Manager,35702,0 +15310,Male,53,Diploma,15,31,17,24,59,1.0,4,77,Rural,Software Engineer,70163,0 +15311,Other,45,Masters,12,81,13,22,1,6.0,6,98,Semi-Urban,ML Engineer,105622,0 +15312,Female,47,High School,3,45,66,70,15,3.0,0,91,Semi-Urban,HR Executive,35157,1 +15313,Male,57,PhD,6,86,16,15,94,6.0,4,68,Urban,HR Executive,38169,0 +15314,Male,37,Bachelors,6,28,29,48,4,0.0,4,54,Urban,Data Analyst,48109,0 +15315,Male,53,Bachelors,9,52,96,60,70,0.0,0,92,Semi-Urban,Data Analyst,89766,1 +15316,Female,51,Diploma,2,58,17,45,12,9.0,3,84,Urban,ML Engineer,45650,0 +15317,Male,26,Bachelors,8,0,88,46,69,7.0,4,29,Urban,HR Executive,110018,0 +15318,Male,49,Bachelors,4,20,15,71,3,5.0,6,16,Semi-Urban,Manager,46561,0 +15319,Female,24,Bachelors,3,56,47,67,61,8.0,2,95,Semi-Urban,Software Engineer,52127,1 +15320,Male,54,Diploma,10,34,92,37,75,0.0,1,16,Urban,Manager,52021,0 +15321,Female,38,Bachelors,12,88,47,48,9,1.0,0,37,Rural,ML Engineer,40935,0 +15322,Female,44,Bachelors,2,49,55,37,50,4.0,7,10,Urban,Software Engineer,128094,0 +15323,Male,42,Bachelors,7,32,53,87,13,8.0,2,56,Urban,Data Analyst,116332,0 +15324,Female,22,High School,12,47,44,1,87,4.0,0,62,Urban,HR Executive,88128,0 +15325,Male,45,Bachelors,14,57,50,51,50,5.0,7,56,Urban,Software Engineer,148358,0 +15326,Male,34,Diploma,9,95,92,43,77,2.0,3,19,Rural,ML Engineer,137951,1 +15327,Female,59,PhD,18,34,47,67,94,6.0,0,12,Urban,Manager,41907,0 +15328,Male,39,Diploma,17,67,39,16,15,1.0,5,41,Semi-Urban,Data Analyst,136495,0 +15329,Other,45,Bachelors,19,35,29,5,76,4.0,7,18,Urban,ML Engineer,121296,0 +15330,Male,56,Masters,10,32,49,86,28,3.0,2,15,Urban,Data Analyst,59882,0 +15331,Male,21,Masters,1,11,27,97,7,5.0,1,64,Urban,HR Executive,107972,0 +15332,Female,35,Bachelors,18,26,59,10,78,7.0,4,34,Rural,HR Executive,99943,0 +15333,Male,45,Diploma,19,17,38,8,60,7.0,2,49,Urban,Manager,80591,0 +15334,Female,30,High School,4,63,22,79,75,1.0,4,36,Urban,ML Engineer,65818,0 +15335,Male,38,High School,17,64,89,30,24,6.0,3,48,Urban,HR Executive,102995,0 +15336,Female,29,Bachelors,6,64,83,68,32,4.0,2,77,Urban,Data Analyst,113678,1 +15337,Male,22,Masters,3,86,45,56,73,3.0,0,15,Semi-Urban,Data Analyst,120617,0 +15338,Male,43,Bachelors,13,45,25,93,2,7.0,5,69,Urban,HR Executive,112518,0 +15339,Male,28,Diploma,4,50,91,90,76,4.0,6,30,Urban,ML Engineer,116189,1 +15340,Male,26,Diploma,7,15,74,44,2,6.0,1,97,Semi-Urban,ML Engineer,92065,0 +15341,Female,41,Bachelors,4,96,30,77,69,0.0,3,12,Urban,HR Executive,65579,0 +15342,Male,27,Bachelors,6,92,14,3,2,4.0,3,12,Urban,HR Executive,130851,0 +15343,Male,46,High School,0,42,40,25,90,6.0,1,20,Urban,Software Engineer,35991,0 +15344,Male,57,Bachelors,7,50,58,48,49,5.0,1,67,Urban,Software Engineer,109286,0 +15345,Female,24,Bachelors,6,14,71,88,51,6.0,1,1,Urban,Software Engineer,96519,0 +15346,Female,38,Masters,13,32,63,82,20,7.0,1,1,Rural,Data Analyst,100125,0 +15347,Male,30,Bachelors,7,12,83,36,51,0.0,0,81,Semi-Urban,HR Executive,81838,0 +15348,Male,53,Bachelors,17,95,7,43,98,6.0,1,33,Urban,HR Executive,114310,0 +15349,Male,43,Bachelors,13,38,19,8,90,4.0,0,82,Urban,Data Analyst,28667,0 +15350,Female,26,Diploma,15,88,92,30,78,8.0,0,15,Urban,Manager,72963,0 +15351,Male,27,Bachelors,1,77,76,33,49,8.0,1,78,Urban,ML Engineer,70932,1 +15352,Male,46,High School,5,24,36,71,73,8.0,3,16,Urban,Data Analyst,54330,0 +15353,Female,24,Masters,10,44,86,80,31,5.0,2,53,Urban,ML Engineer,24783,1 +15354,Female,24,Masters,17,5,89,48,93,1.0,7,42,Urban,Manager,130442,0 +15355,Male,53,Masters,17,63,86,68,20,9.0,4,69,Semi-Urban,HR Executive,89975,1 +15356,Female,57,Bachelors,14,53,95,89,98,2.0,5,63,Rural,Manager,83158,1 +15357,Male,56,High School,19,53,8,6,91,2.0,2,59,Urban,ML Engineer,42854,0 +15358,Female,25,Masters,5,34,9,60,86,1.0,7,41,Rural,Manager,130455,0 +15359,Male,49,Diploma,7,32,93,9,16,8.0,5,1,Urban,ML Engineer,138029,0 +15360,Male,31,High School,13,82,4,48,9,0.0,7,71,Urban,Software Engineer,41095,0 +15361,Female,46,Diploma,16,61,55,73,23,6.0,3,58,Urban,Data Analyst,24202,1 +15362,Male,33,Bachelors,13,15,25,5,69,6.0,3,66,Urban,Data Analyst,121621,0 +15363,Male,49,Masters,12,52,54,58,9,4.0,5,56,Urban,Manager,37912,0 +15364,Male,35,PhD,9,37,57,62,68,8.0,0,27,Rural,HR Executive,82017,0 +15365,Female,28,Bachelors,4,69,63,33,92,9.0,4,2,Rural,Software Engineer,25705,0 +15366,Male,47,Masters,11,80,36,65,51,8.0,4,74,Rural,Software Engineer,40626,1 +15367,Female,59,Diploma,13,41,19,54,73,6.0,2,62,Semi-Urban,Manager,79066,0 +15368,Male,25,Bachelors,9,88,7,43,24,1.0,6,26,Semi-Urban,Data Analyst,71770,0 +15369,Male,39,Diploma,15,62,17,57,77,5.0,4,17,Urban,ML Engineer,42432,0 +15370,Male,25,Bachelors,12,50,43,26,56,1.0,3,29,Urban,ML Engineer,117259,0 +15371,Male,22,Diploma,8,21,25,22,16,6.0,5,26,Urban,Software Engineer,147537,0 +15372,Female,43,Bachelors,2,82,95,56,94,3.0,5,38,Semi-Urban,Data Analyst,104276,1 +15373,Female,58,Bachelors,18,54,36,48,58,0.0,4,83,Semi-Urban,Software Engineer,34715,0 +15374,Male,47,Masters,13,42,97,5,19,0.0,3,29,Semi-Urban,ML Engineer,114304,0 +15375,Male,46,Diploma,12,53,58,24,5,8.0,4,92,Urban,HR Executive,63477,0 +15376,Female,56,Bachelors,10,10,10,74,96,8.0,0,68,Rural,HR Executive,120233,0 +15377,Female,41,Bachelors,16,92,30,76,22,5.0,2,87,Urban,HR Executive,121967,1 +15378,Female,28,Masters,5,70,12,74,68,0.0,5,27,Urban,Software Engineer,58590,0 +15379,Female,58,Bachelors,13,77,90,18,81,7.0,0,88,Urban,Data Analyst,147469,1 +15380,Male,45,Bachelors,4,43,27,65,6,8.0,4,96,Urban,Software Engineer,39090,0 +15381,Female,28,Masters,14,71,47,28,87,8.0,3,80,Rural,Software Engineer,142344,0 +15382,Male,41,Bachelors,16,14,22,75,34,0.0,2,73,Rural,ML Engineer,73972,0 +15383,Male,50,Diploma,17,30,15,8,77,4.0,7,71,Urban,Manager,141402,0 +15384,Female,38,Bachelors,9,54,38,35,62,2.0,1,28,Urban,Data Analyst,112916,0 +15385,Female,48,Bachelors,18,27,78,50,66,3.0,0,16,Urban,Manager,96440,0 +15386,Female,47,Diploma,13,40,33,48,13,7.0,6,99,Rural,Data Analyst,53229,0 +15387,Male,29,High School,17,78,55,70,29,7.0,7,59,Rural,HR Executive,22437,1 +15388,Male,30,Bachelors,8,63,22,39,82,6.0,7,71,Urban,ML Engineer,111777,0 +15389,Male,53,Bachelors,7,26,83,59,27,1.0,2,74,Urban,ML Engineer,73356,1 +15390,Female,30,Diploma,5,53,52,16,48,1.0,2,83,Semi-Urban,ML Engineer,115214,0 +15391,Male,52,High School,6,22,87,12,31,4.0,2,51,Semi-Urban,Manager,67995,0 +15392,Female,34,Bachelors,18,20,0,5,79,6.0,4,20,Urban,Data Analyst,144530,0 +15393,Male,38,Bachelors,3,0,8,69,79,1.0,2,82,Rural,ML Engineer,79178,0 +15394,Female,22,Bachelors,3,57,0,5,82,0.0,5,2,Urban,Manager,99204,0 +15395,Female,56,Bachelors,15,13,30,43,30,8.0,7,6,Urban,ML Engineer,149536,0 +15396,Male,31,Bachelors,10,0,13,85,95,4.0,4,64,Semi-Urban,Data Analyst,107998,0 +15397,Male,39,Bachelors,6,69,86,2,49,4.0,2,46,Urban,Software Engineer,63242,0 +15398,Female,49,High School,16,85,35,67,96,1.0,4,0,Rural,Data Analyst,44538,0 +15399,Male,39,Diploma,12,14,74,38,52,8.0,3,60,Urban,Data Analyst,99092,0 +15400,Female,34,Bachelors,6,23,32,70,49,9.0,6,80,Urban,HR Executive,147364,0 +15401,Female,57,PhD,10,80,59,40,76,8.0,1,94,Urban,HR Executive,139103,1 +15402,Male,43,Diploma,9,15,75,70,32,2.0,0,6,Urban,Data Analyst,71933,0 +15403,Female,44,PhD,3,72,70,31,80,6.0,1,32,Urban,Data Analyst,74170,0 +15404,Male,49,Masters,8,65,16,68,97,8.0,7,51,Rural,ML Engineer,81748,0 +15405,Female,29,Diploma,18,82,25,7,81,3.0,0,48,Rural,Software Engineer,62220,0 +15406,Male,38,Bachelors,9,14,59,66,44,1.0,0,94,Urban,HR Executive,108598,0 +15407,Female,21,Diploma,0,22,16,70,15,3.0,7,24,Urban,Software Engineer,74324,0 +15408,Male,44,High School,5,68,75,15,99,9.0,7,27,Urban,Data Analyst,67967,0 +15409,Male,40,High School,13,99,44,71,21,0.0,7,27,Semi-Urban,Data Analyst,112708,1 +15410,Male,24,Bachelors,0,56,50,24,89,1.0,7,10,Urban,ML Engineer,88262,0 +15411,Female,33,Diploma,0,59,77,52,0,5.0,4,59,Urban,HR Executive,95855,1 +15412,Male,34,Bachelors,16,93,74,39,92,0.0,0,73,Urban,Manager,101706,1 +15413,Female,34,Bachelors,2,45,56,3,12,1.0,2,78,Semi-Urban,HR Executive,67585,0 +15414,Male,46,Bachelors,10,20,0,27,85,8.0,1,7,Urban,HR Executive,67522,0 +15415,Female,46,Bachelors,18,97,56,11,19,8.0,7,52,Urban,HR Executive,143746,0 +15416,Female,58,Bachelors,13,24,94,25,99,7.0,0,43,Urban,ML Engineer,96675,0 +15417,Male,25,Bachelors,4,7,67,2,31,4.0,0,94,Semi-Urban,ML Engineer,68501,0 +15418,Male,25,High School,13,91,82,5,71,4.0,6,60,Urban,Data Analyst,55513,1 +15419,Male,25,High School,10,51,71,58,8,0.0,3,46,Urban,Software Engineer,133574,0 +15420,Male,38,Masters,13,66,54,51,63,7.0,7,32,Urban,Software Engineer,66789,0 +15421,Male,41,High School,9,74,0,39,77,4.0,1,63,Urban,Manager,129249,0 +15422,Female,45,Bachelors,0,60,37,9,27,0.0,6,56,Semi-Urban,Manager,58632,0 +15423,Male,58,Bachelors,5,10,31,90,41,2.0,7,11,Rural,Data Analyst,37231,0 +15424,Female,34,Diploma,7,25,33,0,26,9.0,7,73,Semi-Urban,Software Engineer,85650,0 +15425,Female,50,Bachelors,1,34,24,31,11,8.0,3,26,Urban,HR Executive,41853,0 +15426,Male,42,Bachelors,13,80,66,82,68,4.0,1,99,Urban,Manager,129050,1 +15427,Female,38,Bachelors,2,37,46,70,17,1.0,5,73,Semi-Urban,HR Executive,125884,0 +15428,Male,30,Bachelors,11,42,16,25,77,0.0,5,88,Urban,ML Engineer,139277,0 +15429,Female,44,Diploma,7,50,49,44,78,4.0,2,34,Urban,Data Analyst,85558,0 +15430,Male,48,Masters,0,98,46,44,73,7.0,2,27,Urban,Manager,26709,0 +15431,Female,29,Bachelors,10,22,90,98,53,3.0,4,82,Urban,Data Analyst,118197,1 +15432,Other,45,Diploma,2,15,79,98,72,8.0,6,6,Semi-Urban,HR Executive,116168,0 +15433,Male,36,Masters,14,6,0,18,8,8.0,4,83,Urban,Software Engineer,138650,0 +15434,Female,31,Masters,8,15,45,12,22,1.0,3,30,Rural,Data Analyst,70850,0 +15435,Male,29,Bachelors,1,73,79,47,83,1.0,0,13,Urban,Data Analyst,123589,0 +15436,Male,29,PhD,6,99,48,20,36,4.0,5,63,Rural,HR Executive,117517,0 +15437,Female,53,Bachelors,8,83,51,96,33,5.0,6,18,Semi-Urban,Manager,50204,1 +15438,Male,23,PhD,11,87,60,1,8,7.0,1,99,Semi-Urban,ML Engineer,80715,1 +15439,Female,21,Diploma,15,9,87,41,19,5.0,5,14,Urban,HR Executive,25498,0 +15440,Male,56,Bachelors,2,97,5,4,0,8.0,2,52,Rural,HR Executive,99244,0 +15441,Female,40,Bachelors,14,18,58,50,32,3.0,3,11,Urban,Manager,69800,0 +15442,Male,44,Diploma,13,22,15,96,69,7.0,7,43,Urban,ML Engineer,123462,0 +15443,Male,49,Bachelors,17,52,21,96,88,2.0,5,80,Urban,HR Executive,127233,1 +15444,Male,54,Bachelors,8,11,40,28,89,8.0,1,9,Semi-Urban,HR Executive,63973,0 +15445,Male,25,Diploma,16,46,44,42,82,4.0,4,90,Urban,Software Engineer,42811,0 +15446,Male,39,Masters,6,46,28,70,72,0.0,0,58,Urban,ML Engineer,47112,0 +15447,Male,54,Diploma,5,65,35,21,34,8.0,7,12,Urban,ML Engineer,86713,0 +15448,Male,22,Masters,13,56,51,97,58,7.0,2,87,Semi-Urban,Software Engineer,146363,1 +15449,Male,32,Diploma,1,29,43,1,65,0.0,3,2,Urban,ML Engineer,147321,0 +15450,Male,31,PhD,5,62,41,21,2,4.0,6,85,Semi-Urban,HR Executive,119106,0 +15451,Male,42,Bachelors,9,69,25,26,51,8.0,5,68,Urban,Manager,55556,0 +15452,Male,43,Masters,12,99,37,76,86,2.0,7,46,Semi-Urban,Manager,41378,1 +15453,Other,37,Bachelors,16,6,81,48,63,1.0,1,53,Urban,Manager,41450,0 +15454,Male,55,Masters,16,79,39,73,88,4.0,0,16,Rural,Data Analyst,69240,0 +15455,Male,30,Masters,16,25,58,19,2,2.0,4,1,Urban,Manager,94346,0 +15456,Male,47,Masters,18,68,61,62,64,0.0,1,13,Semi-Urban,HR Executive,113726,0 +15457,Female,31,Bachelors,19,80,72,9,67,9.0,3,96,Urban,HR Executive,31815,1 +15458,Male,26,High School,8,39,62,92,24,3.0,0,14,Urban,Manager,85860,0 +15459,Female,28,Diploma,10,15,86,61,26,9.0,1,36,Semi-Urban,Data Analyst,44207,0 +15460,Male,35,Masters,7,30,28,68,53,9.0,4,16,Semi-Urban,HR Executive,144778,0 +15461,Male,37,High School,6,73,67,92,57,6.0,7,65,Semi-Urban,ML Engineer,70387,1 +15462,Female,21,High School,14,49,73,65,83,9.0,5,27,Rural,Software Engineer,35745,0 +15463,Male,31,Diploma,13,49,56,70,15,6.0,0,79,Urban,Data Analyst,46385,1 +15464,Male,48,Bachelors,15,63,38,39,16,9.0,4,95,Semi-Urban,Manager,110744,1 +15465,Female,29,High School,6,92,26,45,91,0.0,6,97,Rural,Software Engineer,110914,1 +15466,Female,38,Bachelors,19,21,63,76,96,6.0,5,19,Urban,Software Engineer,128830,0 +15467,Female,32,High School,1,44,59,75,16,3.0,7,91,Urban,Manager,100081,1 +15468,Female,33,High School,18,68,71,33,51,3.0,7,7,Semi-Urban,Data Analyst,145277,0 +15469,Female,56,Diploma,15,89,97,46,16,9.0,6,92,Rural,ML Engineer,56768,1 +15470,Female,42,Masters,16,42,27,48,44,1.0,1,33,Urban,Data Analyst,121751,0 +15471,Male,49,Bachelors,17,69,22,41,35,5.0,2,54,Semi-Urban,Manager,139662,0 +15472,Female,55,Diploma,0,51,49,1,13,3.0,1,62,Semi-Urban,Data Analyst,23414,0 +15473,Female,50,Bachelors,1,89,52,40,10,7.0,4,38,Urban,ML Engineer,73360,0 +15474,Male,32,High School,5,89,5,93,67,7.0,6,90,Urban,HR Executive,48968,1 +15475,Male,21,Bachelors,15,10,87,1,72,0.0,6,74,Semi-Urban,HR Executive,144008,0 +15476,Male,38,Diploma,17,71,13,16,58,6.0,4,87,Urban,ML Engineer,57242,0 +15477,Female,36,Masters,7,83,28,54,75,6.0,4,19,Rural,Manager,88604,0 +15478,Male,45,Bachelors,10,91,86,25,37,4.0,1,2,Urban,Manager,134551,0 +15479,Other,47,Bachelors,2,13,85,83,9,1.0,1,16,Urban,Manager,60165,0 +15480,Male,33,Bachelors,7,19,57,23,87,0.0,7,3,Semi-Urban,Software Engineer,34709,0 +15481,Female,56,Masters,16,56,90,34,39,2.0,5,47,Semi-Urban,ML Engineer,25124,0 +15482,Male,41,Masters,3,58,94,12,58,8.0,7,86,Urban,Data Analyst,113041,1 +15483,Female,27,Masters,5,8,63,71,84,2.0,0,62,Urban,ML Engineer,99690,0 +15484,Female,25,High School,17,83,3,59,78,2.0,6,97,Urban,ML Engineer,113601,1 +15485,Female,40,High School,1,66,62,84,73,6.0,7,73,Semi-Urban,ML Engineer,67194,1 +15486,Female,29,Bachelors,10,58,34,77,47,8.0,4,89,Semi-Urban,Manager,79447,1 +15487,Female,27,Masters,7,69,6,89,19,0.0,0,58,Urban,Software Engineer,116853,0 +15488,Male,22,Diploma,19,52,86,12,31,1.0,5,79,Rural,Manager,48625,0 +15489,Male,37,Bachelors,16,77,61,71,6,6.0,0,26,Urban,Software Engineer,136977,1 +15490,Female,23,Bachelors,11,22,11,84,58,0.0,2,62,Semi-Urban,Manager,37705,0 +15491,Male,52,Masters,17,20,47,52,77,7.0,4,31,Urban,ML Engineer,65836,0 +15492,Male,46,High School,4,97,80,75,50,4.0,7,74,Urban,HR Executive,45383,1 +15493,Male,29,Bachelors,18,77,43,56,57,7.0,1,85,Semi-Urban,ML Engineer,29427,1 +15494,Male,58,Masters,8,17,52,89,67,8.0,0,98,Rural,HR Executive,52126,1 +15495,Male,38,Bachelors,12,68,21,54,96,0.0,6,55,Urban,Data Analyst,65482,0 +15496,Female,25,Masters,14,43,96,71,41,7.0,1,18,Urban,Software Engineer,71735,0 +15497,Male,58,Masters,6,26,25,81,11,3.0,7,99,Urban,Software Engineer,39080,0 +15498,Male,59,Bachelors,16,99,78,21,4,1.0,5,45,Urban,Software Engineer,138773,1 +15499,Male,40,Masters,16,71,81,66,26,9.0,3,55,Semi-Urban,Software Engineer,133591,1 +15500,Female,48,High School,0,87,40,41,2,9.0,1,92,Urban,Data Analyst,50548,1 +15501,Other,48,Diploma,15,5,41,29,81,2.0,5,68,Semi-Urban,Data Analyst,66682,0 +15502,Female,45,Bachelors,4,43,0,80,67,1.0,7,22,Rural,ML Engineer,21536,0 +15503,Male,46,Diploma,6,89,3,44,63,8.0,7,99,Semi-Urban,Manager,67524,1 +15504,Female,40,Bachelors,9,1,32,80,72,5.0,6,89,Semi-Urban,HR Executive,86171,0 +15505,Female,43,Masters,13,55,39,41,55,8.0,1,13,Semi-Urban,HR Executive,91984,0 +15506,Female,34,Bachelors,5,17,49,54,29,5.0,7,98,Semi-Urban,ML Engineer,37082,0 +15507,Female,53,Masters,11,5,66,45,95,5.0,0,12,Urban,Manager,49343,0 +15508,Male,44,Diploma,2,88,77,88,75,8.0,7,19,Urban,Manager,136909,1 +15509,Male,24,Diploma,4,48,13,15,37,7.0,1,35,Rural,Data Analyst,67005,0 +15510,Male,35,Bachelors,11,11,6,44,43,4.0,1,25,Urban,Data Analyst,75594,0 +15511,Male,39,Diploma,3,15,41,53,68,1.0,5,88,Urban,Software Engineer,116598,0 +15512,Female,43,Bachelors,2,33,64,24,91,5.0,5,57,Urban,Manager,65954,0 +15513,Female,26,Masters,9,47,66,70,3,2.0,4,80,Semi-Urban,Data Analyst,66245,1 +15514,Female,57,Bachelors,5,25,35,14,70,1.0,3,11,Urban,Software Engineer,32474,0 +15515,Male,35,Bachelors,0,78,90,42,90,2.0,6,57,Semi-Urban,Data Analyst,83646,1 +15516,Male,37,Bachelors,4,80,99,66,5,6.0,3,37,Rural,Manager,63072,1 +15517,Male,35,Diploma,1,47,59,18,39,9.0,6,55,Urban,Software Engineer,131413,0 +15518,Male,47,High School,2,60,60,97,84,8.0,3,74,Semi-Urban,HR Executive,41790,1 +15519,Male,28,Bachelors,19,55,57,14,26,9.0,4,8,Semi-Urban,Data Analyst,124802,0 +15520,Female,51,Diploma,0,13,35,10,52,4.0,4,4,Urban,HR Executive,133064,0 +15521,Male,59,Masters,18,94,40,0,51,3.0,5,90,Semi-Urban,HR Executive,147445,0 +15522,Other,37,High School,5,94,8,27,78,0.0,4,37,Urban,Software Engineer,40602,0 +15523,Male,43,High School,0,76,16,22,44,7.0,0,52,Semi-Urban,Manager,140391,0 +15524,Female,25,Masters,6,61,36,88,7,3.0,3,54,Semi-Urban,Data Analyst,142070,0 +15525,Male,56,Masters,4,44,67,43,16,1.0,2,24,Urban,Manager,90550,0 +15526,Male,48,High School,7,7,89,37,72,2.0,1,30,Urban,ML Engineer,91819,0 +15527,Female,37,Bachelors,14,12,55,53,22,4.0,0,91,Urban,Manager,38527,0 +15528,Female,58,Masters,0,78,5,23,50,2.0,4,49,Rural,Manager,110720,0 +15529,Male,55,High School,13,97,59,11,29,7.0,4,48,Urban,Manager,35002,0 +15530,Male,57,High School,18,35,85,48,62,8.0,1,84,Semi-Urban,HR Executive,50274,1 +15531,Male,49,Bachelors,14,3,33,80,9,4.0,4,69,Urban,Manager,79737,0 +15532,Female,48,Diploma,10,40,98,53,87,8.0,5,41,Urban,ML Engineer,82030,0 +15533,Female,53,Bachelors,17,94,29,23,69,2.0,0,66,Semi-Urban,HR Executive,71269,0 +15534,Male,45,Diploma,3,84,72,67,79,3.0,2,89,Rural,Software Engineer,144349,1 +15535,Male,36,High School,5,19,58,31,59,3.0,5,54,Semi-Urban,HR Executive,76710,0 +15536,Female,23,Bachelors,15,85,28,57,81,2.0,7,31,Semi-Urban,Manager,145607,0 +15537,Male,50,Diploma,12,88,2,39,57,5.0,4,46,Rural,Software Engineer,105011,0 +15538,Female,48,Masters,0,54,20,18,7,0.0,5,13,Urban,Software Engineer,32037,0 +15539,Male,57,Diploma,19,70,43,21,21,9.0,7,19,Semi-Urban,ML Engineer,94593,0 +15540,Male,21,High School,11,48,80,2,9,1.0,7,73,Semi-Urban,Data Analyst,132073,0 +15541,Male,35,Diploma,15,40,26,69,14,3.0,3,67,Urban,HR Executive,27453,0 +15542,Male,45,PhD,6,30,29,10,75,2.0,3,94,Urban,HR Executive,35111,0 +15543,Male,23,Bachelors,19,41,87,98,11,6.0,0,69,Semi-Urban,Data Analyst,42379,1 +15544,Female,40,PhD,9,58,45,99,15,5.0,3,14,Urban,Software Engineer,95041,0 +15545,Female,33,High School,4,6,20,16,24,4.0,4,54,Urban,Data Analyst,129520,0 +15546,Female,23,Masters,15,69,79,23,80,4.0,7,2,Urban,Data Analyst,144551,0 +15547,Female,51,Bachelors,16,26,82,95,73,1.0,4,64,Urban,Manager,64796,1 +15548,Male,29,PhD,17,30,52,15,42,7.0,0,6,Urban,Software Engineer,93989,0 +15549,Male,47,High School,5,82,46,54,2,0.0,6,74,Rural,ML Engineer,93835,1 +15550,Female,38,Masters,0,59,66,26,21,4.0,0,84,Urban,Data Analyst,51753,0 +15551,Male,51,Masters,5,41,13,45,80,0.0,0,47,Urban,HR Executive,95001,0 +15552,Male,56,High School,19,73,4,12,78,8.0,1,33,Urban,Data Analyst,110578,0 +15553,Male,21,Bachelors,0,13,88,90,99,1.0,5,68,Semi-Urban,HR Executive,96638,1 +15554,Male,50,Bachelors,18,18,87,59,53,5.0,1,40,Urban,Data Analyst,70554,0 +15555,Male,26,Diploma,13,56,7,40,76,8.0,0,16,Urban,HR Executive,143110,0 +15556,Female,53,Bachelors,2,20,40,34,94,2.0,6,49,Urban,Data Analyst,48214,0 +15557,Female,47,Masters,0,84,11,91,6,7.0,2,96,Urban,Manager,119531,1 +15558,Female,57,High School,7,76,85,28,50,7.0,3,17,Semi-Urban,Data Analyst,99258,0 +15559,Female,25,Diploma,2,93,8,45,15,5.0,6,89,Semi-Urban,Manager,36681,0 +15560,Female,24,Masters,17,29,14,15,68,7.0,1,9,Semi-Urban,Data Analyst,25258,0 +15561,Male,35,High School,5,2,10,76,23,0.0,7,35,Rural,Software Engineer,80641,0 +15562,Male,34,Masters,7,51,5,26,87,0.0,7,53,Urban,HR Executive,65222,0 +15563,Female,56,Bachelors,12,79,38,57,19,4.0,7,99,Semi-Urban,Manager,66911,1 +15564,Male,22,Bachelors,19,41,52,63,64,0.0,4,43,Urban,ML Engineer,126253,0 +15565,Male,39,Bachelors,15,30,39,48,63,5.0,6,80,Urban,Data Analyst,39189,0 +15566,Male,53,Bachelors,3,0,95,42,3,5.0,4,73,Urban,Data Analyst,135637,0 +15567,Male,28,High School,19,14,85,38,79,0.0,7,15,Urban,Data Analyst,133551,0 +15568,Male,21,Bachelors,5,26,86,84,43,5.0,5,47,Urban,ML Engineer,58738,1 +15569,Male,30,Diploma,2,82,19,16,16,2.0,6,47,Urban,Software Engineer,53479,0 +15570,Male,33,Masters,12,70,94,76,85,2.0,5,75,Urban,ML Engineer,58636,1 +15571,Female,43,High School,18,62,45,5,98,1.0,5,84,Semi-Urban,Manager,36125,0 +15572,Male,22,High School,15,67,22,19,38,7.0,0,4,Rural,Data Analyst,135339,0 +15573,Female,24,High School,4,77,36,33,55,9.0,5,29,Rural,Manager,124833,0 +15574,Male,21,Bachelors,14,47,57,25,90,7.0,1,61,Semi-Urban,ML Engineer,39161,0 +15575,Male,39,Masters,8,65,17,72,5,1.0,4,1,Urban,ML Engineer,27135,0 +15576,Male,27,Masters,19,64,75,67,39,5.0,4,23,Urban,HR Executive,21477,0 +15577,Male,29,PhD,11,26,79,55,50,0.0,2,25,Urban,Manager,70320,0 +15578,Female,45,High School,19,28,14,64,86,8.0,1,37,Urban,Software Engineer,42863,0 +15579,Female,24,Bachelors,10,13,30,92,39,1.0,6,60,Urban,Software Engineer,139372,0 +15580,Female,57,Diploma,14,71,40,29,12,7.0,3,41,Urban,HR Executive,143473,0 +15581,Female,34,Diploma,16,57,33,16,25,3.0,2,55,Rural,Data Analyst,47913,0 +15582,Male,42,Diploma,19,51,27,19,54,3.0,2,2,Urban,Manager,49113,0 +15583,Male,32,Diploma,3,61,45,99,29,3.0,6,34,Urban,ML Engineer,45040,1 +15584,Male,30,Bachelors,19,1,2,26,40,7.0,3,25,Urban,Manager,95086,0 +15585,Male,48,High School,13,2,34,67,17,0.0,4,46,Semi-Urban,HR Executive,47224,0 +15586,Male,30,Bachelors,9,19,62,53,55,6.0,6,92,Semi-Urban,Manager,52369,0 +15587,Male,54,Masters,5,73,91,79,6,8.0,0,6,Semi-Urban,Data Analyst,148724,1 +15588,Male,27,Bachelors,7,1,33,99,21,5.0,2,38,Urban,Manager,60944,0 +15589,Male,25,Masters,19,47,60,85,20,4.0,6,6,Semi-Urban,ML Engineer,89875,0 +15590,Male,41,Bachelors,14,75,6,13,71,0.0,4,67,Urban,Data Analyst,108077,0 +15591,Female,27,PhD,19,52,46,85,0,2.0,5,73,Urban,Software Engineer,21104,1 +15592,Female,21,Masters,5,16,86,16,76,2.0,5,86,Urban,HR Executive,135117,0 +15593,Female,53,Masters,4,93,65,18,95,3.0,4,74,Semi-Urban,Manager,140772,1 +15594,Female,45,Masters,19,20,41,40,1,0.0,4,76,Urban,HR Executive,73271,0 +15595,Male,44,PhD,16,15,9,79,37,2.0,2,11,Rural,HR Executive,79047,0 +15596,Male,28,Diploma,9,74,25,56,63,6.0,4,15,Semi-Urban,ML Engineer,115123,0 +15597,Male,50,Masters,13,66,81,86,24,8.0,6,61,Semi-Urban,HR Executive,111037,1 +15598,Female,34,PhD,13,50,13,92,6,0.0,0,46,Urban,HR Executive,68276,0 +15599,Female,50,Diploma,14,43,95,71,15,2.0,4,18,Semi-Urban,ML Engineer,149749,0 +15600,Male,29,Bachelors,6,70,22,2,86,0.0,1,72,Urban,Data Analyst,113907,0 +15601,Male,44,PhD,2,64,41,98,4,6.0,6,9,Urban,ML Engineer,50249,0 +15602,Other,21,Diploma,16,81,19,68,39,1.0,2,44,Urban,Software Engineer,87845,0 +15603,Male,40,Masters,3,97,85,48,86,2.0,0,13,Rural,ML Engineer,141467,1 +15604,Female,57,High School,7,49,18,21,38,1.0,6,54,Urban,Software Engineer,102291,0 +15605,Male,50,Diploma,5,7,44,42,65,5.0,0,48,Rural,ML Engineer,141001,0 +15606,Male,56,Masters,15,10,10,47,40,1.0,4,90,Semi-Urban,Software Engineer,127508,0 +15607,Female,46,Masters,16,79,79,37,40,8.0,0,65,Semi-Urban,ML Engineer,116092,1 +15608,Female,34,PhD,15,40,47,92,73,2.0,1,67,Rural,Software Engineer,27317,1 +15609,Female,58,Bachelors,9,58,62,7,95,0.0,7,81,Urban,Data Analyst,110669,0 +15610,Male,26,Diploma,1,23,55,87,79,3.0,6,22,Rural,Manager,93909,0 +15611,Male,36,Bachelors,12,93,50,80,2,8.0,6,79,Urban,ML Engineer,41887,1 +15612,Female,44,Diploma,14,40,71,18,59,2.0,3,4,Rural,Data Analyst,146405,0 +15613,Male,59,Bachelors,12,74,42,8,54,3.0,5,28,Rural,Software Engineer,133188,0 +15614,Male,23,Masters,17,77,54,27,28,7.0,3,48,Semi-Urban,HR Executive,129100,0 +15615,Female,35,High School,16,76,31,7,39,9.0,7,0,Semi-Urban,Data Analyst,23486,0 +15616,Male,53,Masters,15,33,24,87,90,0.0,7,4,Rural,Software Engineer,149175,0 +15617,Male,45,Bachelors,4,24,72,67,20,6.0,4,55,Urban,Manager,47683,0 +15618,Female,26,Bachelors,6,73,22,34,42,3.0,2,40,Urban,HR Executive,68573,0 +15619,Other,47,Masters,7,68,11,73,50,7.0,7,88,Urban,Data Analyst,92348,0 +15620,Male,54,Masters,2,38,7,72,64,8.0,2,35,Rural,Software Engineer,95554,0 +15621,Male,49,High School,8,17,19,23,64,5.0,0,61,Semi-Urban,HR Executive,98143,0 +15622,Female,38,Diploma,13,94,55,28,34,1.0,5,37,Urban,ML Engineer,58956,0 +15623,Female,26,Bachelors,17,81,60,23,40,3.0,2,38,Urban,Software Engineer,97826,0 +15624,Female,53,High School,19,69,35,66,46,8.0,2,79,Urban,Software Engineer,60054,1 +15625,Male,24,Bachelors,8,60,68,16,8,2.0,6,56,Semi-Urban,Data Analyst,72525,0 +15626,Male,49,Diploma,3,90,26,41,18,6.0,0,85,Semi-Urban,HR Executive,74484,1 +15627,Female,27,Masters,5,95,29,47,6,0.0,4,86,Semi-Urban,ML Engineer,128043,1 +15628,Female,30,Diploma,18,9,64,27,43,0.0,7,51,Urban,Manager,63874,0 +15629,Female,34,Masters,0,15,47,94,58,3.0,6,77,Rural,ML Engineer,101597,0 +15630,Male,40,Bachelors,6,99,34,4,84,7.0,3,58,Urban,Manager,76132,0 +15631,Male,53,Masters,1,23,15,71,99,9.0,4,94,Rural,Manager,132831,0 +15632,Male,30,Bachelors,7,77,88,58,31,8.0,5,5,Urban,ML Engineer,84805,0 +15633,Other,31,Diploma,14,19,58,30,97,9.0,7,51,Semi-Urban,Manager,116299,0 +15634,Female,55,Masters,5,59,3,14,77,5.0,3,42,Semi-Urban,Manager,114609,0 +15635,Male,58,PhD,6,78,6,38,12,1.0,6,77,Semi-Urban,Software Engineer,26277,0 +15636,Male,55,High School,19,17,48,0,40,1.0,7,40,Urban,ML Engineer,56968,0 +15637,Male,47,High School,14,63,67,41,35,8.0,0,23,Urban,Manager,100863,0 +15638,Male,34,High School,10,21,28,54,93,7.0,2,44,Urban,Data Analyst,98278,0 +15639,Female,23,Masters,2,48,75,37,75,3.0,6,21,Rural,Data Analyst,26669,0 +15640,Female,41,Bachelors,6,39,2,61,24,9.0,1,69,Rural,HR Executive,35621,0 +15641,Male,38,Bachelors,13,24,69,32,71,4.0,1,74,Urban,ML Engineer,58115,0 +15642,Male,51,High School,2,1,69,87,72,4.0,2,59,Urban,HR Executive,131141,0 +15643,Female,45,Masters,17,49,73,22,83,6.0,2,70,Semi-Urban,Data Analyst,35568,0 +15644,Male,47,Diploma,6,52,14,70,12,3.0,5,6,Semi-Urban,Manager,142283,0 +15645,Male,22,Bachelors,18,47,83,58,85,8.0,4,13,Urban,ML Engineer,80983,0 +15646,Female,47,High School,16,3,54,33,12,9.0,4,8,Urban,Manager,68329,0 +15647,Female,40,Masters,9,89,36,15,24,5.0,6,29,Rural,Data Analyst,44316,0 +15648,Female,31,Diploma,18,74,12,88,79,0.0,5,33,Urban,ML Engineer,134368,0 +15649,Male,32,Masters,9,95,72,45,74,7.0,4,13,Urban,ML Engineer,132874,0 +15650,Male,44,High School,0,81,39,74,32,1.0,6,87,Semi-Urban,Data Analyst,105341,1 +15651,Male,34,Masters,17,95,43,97,15,8.0,0,24,Rural,HR Executive,97814,1 +15652,Male,31,Diploma,7,32,24,67,53,8.0,6,56,Semi-Urban,Software Engineer,98270,0 +15653,Female,40,Diploma,5,62,87,83,51,4.0,0,27,Rural,HR Executive,31805,1 +15654,Male,56,Bachelors,9,75,61,12,19,2.0,5,22,Urban,ML Engineer,119595,0 +15655,Female,52,High School,15,22,81,89,27,9.0,2,27,Urban,Software Engineer,42367,0 +15656,Male,47,Diploma,3,55,38,27,57,7.0,5,84,Urban,ML Engineer,98162,0 +15657,Male,43,PhD,19,44,47,75,92,6.0,1,16,Urban,HR Executive,74092,0 +15658,Other,42,Bachelors,10,42,15,47,2,0.0,5,73,Semi-Urban,Manager,130316,0 +15659,Male,42,Masters,18,46,58,6,77,2.0,1,26,Urban,Manager,46523,0 +15660,Male,31,Bachelors,8,13,98,89,45,1.0,0,92,Urban,Data Analyst,62293,1 +15661,Male,32,High School,11,57,5,30,45,7.0,7,47,Urban,ML Engineer,36398,0 +15662,Male,56,Bachelors,1,80,92,41,34,6.0,0,32,Semi-Urban,Data Analyst,115361,1 +15663,Male,56,Diploma,4,65,85,1,1,7.0,2,73,Urban,ML Engineer,94851,0 +15664,Male,24,Masters,0,51,27,74,63,8.0,2,48,Urban,Manager,35008,0 +15665,Female,33,Masters,13,90,90,44,91,4.0,4,9,Urban,Data Analyst,123808,0 +15666,Female,41,PhD,11,58,96,22,21,7.0,3,80,Urban,Data Analyst,31949,1 +15667,Male,58,Bachelors,10,5,78,1,47,1.0,3,91,Semi-Urban,Software Engineer,70313,0 +15668,Male,39,Masters,4,76,45,83,88,8.0,7,57,Semi-Urban,Software Engineer,138917,1 +15669,Female,42,Bachelors,6,25,8,37,30,5.0,7,95,Urban,Data Analyst,94249,0 +15670,Male,57,Bachelors,19,69,19,41,67,5.0,0,38,Urban,Manager,30595,0 +15671,Female,58,Bachelors,0,42,37,4,39,5.0,3,60,Semi-Urban,Manager,46506,0 +15672,Female,36,Masters,13,78,78,24,97,9.0,5,74,Urban,Data Analyst,143288,1 +15673,Male,42,PhD,12,66,11,12,51,9.0,7,89,Urban,HR Executive,48476,0 +15674,Female,53,Bachelors,4,64,21,11,85,8.0,0,36,Rural,HR Executive,145306,0 +15675,Female,34,Bachelors,6,98,55,47,59,3.0,5,28,Urban,HR Executive,38905,0 +15676,Female,30,Bachelors,4,95,13,78,8,7.0,3,29,Urban,ML Engineer,26592,0 +15677,Male,38,High School,10,42,39,13,97,7.0,6,31,Urban,Manager,60439,0 +15678,Male,36,High School,13,80,87,79,53,8.0,1,8,Urban,Manager,129535,1 +15679,Female,46,Diploma,17,13,37,31,73,4.0,1,25,Urban,Software Engineer,75417,0 +15680,Male,54,Diploma,13,72,7,22,32,2.0,7,44,Urban,ML Engineer,122677,0 +15681,Female,34,Bachelors,7,20,88,51,11,2.0,7,2,Urban,ML Engineer,31918,0 +15682,Male,57,High School,0,24,31,0,48,9.0,6,12,Semi-Urban,HR Executive,83642,0 +15683,Male,55,Bachelors,8,37,26,32,62,3.0,2,98,Semi-Urban,Data Analyst,76389,0 +15684,Female,53,Diploma,14,85,18,85,97,3.0,2,37,Rural,Data Analyst,33928,0 +15685,Female,25,Masters,16,90,17,10,13,6.0,6,91,Urban,Software Engineer,73789,0 +15686,Female,58,Diploma,9,56,0,33,44,7.0,4,13,Semi-Urban,Software Engineer,85098,0 +15687,Female,31,Diploma,18,40,20,86,59,3.0,0,25,Urban,HR Executive,89955,0 +15688,Male,39,Bachelors,19,42,47,53,50,6.0,1,84,Urban,Manager,96541,0 +15689,Male,26,Masters,12,50,16,99,67,9.0,2,33,Semi-Urban,Manager,75220,0 +15690,Female,51,Masters,19,32,18,14,19,6.0,7,61,Rural,HR Executive,77063,0 +15691,Male,37,Masters,18,59,79,82,8,2.0,5,41,Semi-Urban,HR Executive,125290,1 +15692,Female,57,Bachelors,5,64,41,29,3,5.0,1,84,Urban,Software Engineer,145069,0 +15693,Male,31,Diploma,9,10,65,0,90,2.0,0,98,Rural,Data Analyst,70794,0 +15694,Male,36,Bachelors,9,37,36,84,90,6.0,5,63,Urban,ML Engineer,99916,0 +15695,Male,27,Bachelors,16,61,14,68,88,9.0,1,61,Semi-Urban,Manager,117786,0 +15696,Male,53,Masters,17,75,68,81,10,2.0,5,43,Urban,Data Analyst,34910,1 +15697,Female,59,Bachelors,15,0,32,86,49,9.0,3,38,Rural,ML Engineer,74822,0 +15698,Female,55,Diploma,14,24,5,2,19,5.0,0,16,Semi-Urban,Software Engineer,41194,0 +15699,Female,38,Masters,17,47,86,55,74,4.0,7,16,Rural,ML Engineer,113909,0 +15700,Male,23,Masters,18,59,34,46,63,8.0,2,23,Urban,Software Engineer,132614,0 +15701,Male,52,High School,7,80,65,26,41,8.0,6,4,Urban,ML Engineer,34656,0 +15702,Male,49,Diploma,8,41,4,61,60,8.0,2,85,Rural,ML Engineer,138251,0 +15703,Male,51,Bachelors,1,47,36,51,35,6.0,4,81,Urban,ML Engineer,46673,0 +15704,Male,55,Masters,9,81,59,50,78,7.0,5,44,Rural,Manager,42465,0 +15705,Male,33,Masters,16,61,4,5,93,8.0,7,57,Urban,Manager,78950,0 +15706,Male,24,Masters,4,5,6,83,81,0.0,0,85,Semi-Urban,Data Analyst,138839,0 +15707,Male,30,Bachelors,16,34,57,73,83,1.0,1,21,Urban,ML Engineer,39948,0 +15708,Male,40,Bachelors,9,62,22,77,78,3.0,1,44,Urban,Data Analyst,82743,0 +15709,Male,50,High School,15,44,52,14,12,0.0,2,82,Rural,Manager,77841,0 +15710,Male,46,PhD,0,24,72,17,54,2.0,4,86,Semi-Urban,Data Analyst,113222,0 +15711,Male,49,Bachelors,7,76,98,31,21,6.0,4,51,Semi-Urban,Software Engineer,122331,1 +15712,Female,54,Bachelors,12,11,60,50,9,9.0,3,10,Semi-Urban,Manager,122998,0 +15713,Male,45,High School,18,66,3,26,43,5.0,0,24,Semi-Urban,Data Analyst,140480,0 +15714,Female,53,Diploma,10,23,37,20,4,8.0,5,15,Urban,HR Executive,31569,0 +15715,Male,29,Masters,5,41,11,73,83,0.0,2,23,Urban,Data Analyst,29506,0 +15716,Female,36,Bachelors,18,91,9,58,42,6.0,6,81,Urban,Software Engineer,23592,0 +15717,Male,29,High School,10,58,34,74,10,0.0,0,92,Urban,HR Executive,70230,1 +15718,Female,35,Masters,11,73,39,6,46,8.0,0,10,Semi-Urban,Manager,121701,0 +15719,Male,29,Masters,6,25,33,52,75,1.0,6,99,Urban,Software Engineer,44338,0 +15720,Female,42,Diploma,10,79,66,57,16,8.0,0,34,Semi-Urban,Data Analyst,55961,0 +15721,Male,35,Masters,14,87,25,15,78,8.0,5,32,Rural,ML Engineer,95271,0 +15722,Male,47,High School,5,57,55,41,7,6.0,0,26,Urban,Data Analyst,73396,0 +15723,Female,21,Bachelors,14,23,80,2,50,2.0,1,83,Semi-Urban,HR Executive,92669,0 +15724,Male,27,Diploma,13,30,26,64,42,1.0,6,69,Urban,Data Analyst,91170,0 +15725,Female,30,Diploma,4,48,39,79,4,6.0,1,25,Urban,Manager,103822,0 +15726,Male,44,PhD,15,17,2,68,80,6.0,4,49,Rural,Data Analyst,57065,0 +15727,Male,55,Bachelors,17,51,96,53,65,9.0,6,54,Semi-Urban,Data Analyst,121094,1 +15728,Female,59,Bachelors,13,91,33,89,12,0.0,6,81,Rural,Manager,31770,1 +15729,Male,46,Masters,14,10,72,65,59,6.0,4,63,Urban,ML Engineer,72374,0 +15730,Male,29,Diploma,7,27,22,45,22,3.0,2,81,Rural,HR Executive,120120,0 +15731,Female,55,Bachelors,6,84,49,41,47,7.0,7,42,Urban,Data Analyst,60488,0 +15732,Female,56,Diploma,1,63,25,93,73,8.0,2,46,Urban,Data Analyst,122302,0 +15733,Female,26,Diploma,3,83,15,27,66,8.0,6,43,Urban,HR Executive,56308,0 +15734,Male,29,Bachelors,15,86,84,95,19,6.0,3,6,Semi-Urban,ML Engineer,110968,1 +15735,Male,42,Diploma,11,60,44,22,93,0.0,4,82,Semi-Urban,Software Engineer,133463,0 +15736,Male,42,Bachelors,7,79,80,27,73,8.0,2,70,Rural,Software Engineer,116324,1 +15737,Male,30,Bachelors,8,4,22,86,39,5.0,5,19,Semi-Urban,Software Engineer,78102,0 +15738,Female,28,Diploma,4,73,72,33,61,8.0,6,42,Urban,Data Analyst,109520,0 +15739,Male,53,Diploma,10,60,71,70,91,2.0,0,34,Urban,Manager,109771,1 +15740,Male,53,High School,15,48,51,44,79,8.0,5,61,Urban,Manager,68528,0 +15741,Male,46,PhD,11,35,50,89,74,8.0,5,32,Urban,Manager,107196,0 +15742,Female,45,Bachelors,9,43,16,2,10,5.0,2,19,Urban,ML Engineer,95724,0 +15743,Female,51,Bachelors,18,52,67,46,22,8.0,4,63,Rural,Software Engineer,134335,0 +15744,Female,38,Bachelors,8,44,74,85,10,3.0,2,72,Semi-Urban,Manager,101042,1 +15745,Male,52,Diploma,3,83,50,93,88,9.0,4,73,Urban,Software Engineer,101287,1 +15746,Female,34,PhD,14,47,44,7,25,0.0,6,99,Semi-Urban,ML Engineer,112468,0 +15747,Female,29,High School,6,12,72,45,52,0.0,5,18,Urban,Manager,94187,0 +15748,Male,57,High School,9,72,94,64,65,0.0,3,26,Rural,ML Engineer,123485,1 +15749,Male,27,Diploma,8,82,47,90,58,2.0,7,57,Rural,Manager,74418,1 +15750,Male,34,High School,5,6,52,50,40,1.0,1,21,Urban,HR Executive,125463,0 +15751,Male,39,Masters,13,89,69,2,58,8.0,2,61,Urban,Software Engineer,128057,0 +15752,Female,37,Bachelors,15,30,40,82,11,5.0,4,66,Urban,HR Executive,123627,0 +15753,Male,42,Bachelors,4,33,64,9,59,1.0,4,69,Rural,Manager,120514,0 +15754,Male,54,Bachelors,3,87,46,59,54,6.0,0,28,Urban,HR Executive,36189,0 +15755,Female,28,Diploma,3,69,45,20,22,1.0,2,75,Semi-Urban,HR Executive,76664,0 +15756,Female,55,Diploma,14,20,42,7,63,3.0,1,69,Urban,Data Analyst,29287,0 +15757,Female,30,Bachelors,18,83,78,71,68,6.0,0,37,Urban,Software Engineer,69005,1 +15758,Male,30,Diploma,9,48,28,88,55,9.0,4,34,Urban,Data Analyst,64019,0 +15759,Male,22,Bachelors,6,85,49,1,3,5.0,7,15,Urban,HR Executive,128843,0 +15760,Male,26,Masters,4,50,3,9,72,3.0,6,49,Rural,ML Engineer,106977,0 +15761,Male,48,Masters,0,31,5,22,21,0.0,3,54,Rural,Data Analyst,99926,0 +15762,Male,37,Bachelors,0,78,75,10,10,4.0,1,14,Rural,Manager,70360,0 +15763,Male,53,High School,6,18,64,39,44,3.0,7,8,Urban,HR Executive,71186,0 +15764,Male,33,Bachelors,16,99,15,85,62,3.0,6,72,Urban,HR Executive,40618,1 +15765,Male,49,PhD,15,58,12,27,59,6.0,3,22,Urban,ML Engineer,129359,0 +15766,Male,58,Bachelors,3,53,84,52,64,9.0,4,94,Urban,Software Engineer,60709,1 +15767,Female,26,Diploma,13,7,42,88,97,4.0,7,39,Urban,Manager,129267,0 +15768,Female,39,Bachelors,17,48,30,99,19,6.0,3,1,Urban,Software Engineer,48143,0 +15769,Male,40,Bachelors,2,55,13,98,68,7.0,6,72,Rural,Manager,127950,1 +15770,Male,53,Diploma,7,40,80,68,66,4.0,5,63,Rural,Data Analyst,40539,1 +15771,Male,42,Masters,0,16,89,83,79,8.0,1,79,Semi-Urban,ML Engineer,74284,1 +15772,Male,28,Bachelors,0,88,23,54,20,8.0,1,92,Urban,Data Analyst,28758,1 +15773,Male,22,Masters,14,55,86,84,71,2.0,0,6,Urban,Software Engineer,124237,0 +15774,Female,40,High School,14,53,39,28,79,9.0,5,63,Urban,Software Engineer,131872,0 +15775,Other,30,High School,3,83,24,54,81,1.0,1,74,Rural,Manager,108408,0 +15776,Female,50,Masters,10,78,87,86,75,9.0,1,55,Semi-Urban,Manager,26307,1 +15777,Female,52,Diploma,19,40,82,44,51,5.0,6,5,Urban,ML Engineer,140102,0 +15778,Female,24,High School,4,37,82,94,51,8.0,3,36,Semi-Urban,Data Analyst,143493,1 +15779,Male,51,Bachelors,8,92,11,5,34,6.0,0,18,Urban,Manager,72088,0 +15780,Other,31,Masters,4,56,46,53,88,9.0,7,12,Rural,Manager,106343,0 +15781,Male,33,Masters,3,73,62,24,2,9.0,0,30,Semi-Urban,Data Analyst,67661,0 +15782,Female,24,Diploma,3,14,32,89,42,7.0,5,42,Rural,Software Engineer,74901,0 +15783,Male,54,High School,5,97,80,79,67,8.0,3,84,Urban,Data Analyst,109890,1 +15784,Male,42,Bachelors,17,62,11,69,49,8.0,7,58,Semi-Urban,HR Executive,71297,0 +15785,Female,29,Bachelors,5,75,68,68,89,7.0,2,59,Rural,Manager,97598,1 +15786,Male,39,Bachelors,17,68,86,11,93,3.0,6,21,Urban,HR Executive,60935,0 +15787,Male,50,Bachelors,1,28,51,34,27,8.0,2,37,Rural,HR Executive,108854,0 +15788,Male,24,Bachelors,0,84,0,62,82,9.0,0,68,Semi-Urban,Data Analyst,120101,0 +15789,Male,42,High School,11,46,96,94,42,4.0,6,83,Urban,Software Engineer,29270,1 +15790,Other,55,Bachelors,9,80,4,40,48,0.0,6,14,Semi-Urban,ML Engineer,70354,0 +15791,Female,45,Diploma,9,64,49,92,71,0.0,7,74,Semi-Urban,ML Engineer,145627,1 +15792,Male,39,Masters,10,58,89,3,48,3.0,4,91,Urban,ML Engineer,69175,1 +15793,Male,55,Bachelors,1,70,84,58,87,6.0,6,76,Urban,Software Engineer,64802,1 +15794,Female,22,Diploma,5,91,86,69,10,9.0,6,43,Rural,HR Executive,137467,1 +15795,Male,39,Bachelors,9,5,88,91,75,2.0,0,51,Semi-Urban,Data Analyst,146160,1 +15796,Male,58,Diploma,4,66,81,11,71,4.0,5,70,Urban,Manager,114299,0 +15797,Male,55,High School,7,59,17,30,52,6.0,7,88,Urban,Manager,62504,0 +15798,Female,39,High School,2,21,38,55,6,2.0,3,10,Urban,Software Engineer,137733,0 +15799,Male,23,Masters,10,58,13,69,50,1.0,5,47,Semi-Urban,Data Analyst,137710,0 +15800,Male,44,Masters,18,43,91,96,80,4.0,3,80,Rural,Software Engineer,70857,1 +15801,Male,45,Bachelors,1,71,4,47,21,0.0,1,47,Semi-Urban,Data Analyst,118143,0 +15802,Male,33,Bachelors,11,85,87,61,64,9.0,4,25,Semi-Urban,Data Analyst,120612,1 +15803,Male,23,High School,18,44,51,50,58,6.0,6,16,Urban,HR Executive,55976,0 +15804,Male,26,Bachelors,0,86,34,46,8,6.0,6,53,Urban,ML Engineer,94823,0 +15805,Male,53,High School,0,77,83,31,73,6.0,1,53,Urban,ML Engineer,22190,1 +15806,Male,24,PhD,2,67,1,77,33,9.0,4,0,Urban,HR Executive,121167,0 +15807,Male,47,Bachelors,12,84,8,47,84,4.0,4,52,Rural,ML Engineer,112648,0 +15808,Female,51,High School,12,85,15,82,53,5.0,7,98,Urban,Manager,24518,1 +15809,Female,31,Bachelors,18,31,58,75,56,6.0,5,50,Urban,Manager,117391,0 +15810,Male,51,Diploma,6,35,35,88,33,2.0,7,52,Semi-Urban,Manager,77878,0 +15811,Male,52,High School,3,4,10,41,59,9.0,6,23,Urban,Data Analyst,68399,0 +15812,Male,47,Bachelors,12,83,99,30,84,7.0,6,39,Rural,Manager,143859,1 +15813,Female,30,Bachelors,10,16,86,51,60,2.0,1,31,Semi-Urban,ML Engineer,32396,0 +15814,Female,22,Bachelors,11,17,87,83,80,0.0,7,29,Urban,Software Engineer,90799,0 +15815,Male,59,Bachelors,3,32,43,99,0,7.0,7,77,Urban,HR Executive,93092,1 +15816,Female,48,Bachelors,3,62,89,94,91,4.0,5,87,Urban,Manager,119198,1 +15817,Female,27,High School,7,89,28,80,91,0.0,7,72,Urban,ML Engineer,124608,1 +15818,Female,35,Diploma,10,97,85,60,63,8.0,1,99,Urban,Manager,143288,1 +15819,Male,58,High School,4,28,23,37,65,2.0,0,49,Urban,Data Analyst,21072,0 +15820,Male,24,Bachelors,11,2,95,96,19,1.0,6,9,Semi-Urban,HR Executive,114618,0 +15821,Male,42,Bachelors,3,26,42,9,10,4.0,4,18,Semi-Urban,HR Executive,93669,0 +15822,Female,32,Diploma,0,15,47,83,60,1.0,7,83,Rural,ML Engineer,23582,0 +15823,Female,30,PhD,5,87,75,11,48,7.0,3,86,Rural,Manager,133440,1 +15824,Male,38,Masters,0,53,19,88,3,5.0,3,19,Semi-Urban,Software Engineer,95100,0 +15825,Male,32,Bachelors,2,57,48,70,21,6.0,4,22,Semi-Urban,HR Executive,30032,0 +15826,Male,55,High School,5,22,74,28,2,3.0,1,4,Semi-Urban,Software Engineer,59657,0 +15827,Male,51,Diploma,18,2,71,92,44,6.0,4,22,Urban,ML Engineer,31574,0 +15828,Male,48,High School,18,87,94,83,34,9.0,1,45,Semi-Urban,HR Executive,32254,1 +15829,Male,57,Bachelors,13,61,80,22,6,0.0,3,51,Urban,Manager,76635,0 +15830,Male,36,Masters,10,96,95,36,64,0.0,3,91,Urban,HR Executive,84726,1 +15831,Female,23,Bachelors,8,54,24,61,79,4.0,0,57,Urban,Manager,100320,0 +15832,Male,56,High School,15,66,84,21,13,2.0,7,42,Urban,Data Analyst,82348,0 +15833,Male,26,Diploma,11,88,67,4,96,4.0,5,24,Semi-Urban,ML Engineer,48527,0 +15834,Male,44,Masters,9,34,4,59,63,3.0,6,67,Urban,Manager,120207,0 +15835,Female,54,Bachelors,10,49,19,41,84,5.0,0,10,Semi-Urban,Data Analyst,81108,0 +15836,Male,31,Diploma,8,23,33,66,27,4.0,7,91,Urban,Manager,99243,0 +15837,Female,33,Bachelors,4,89,44,60,16,3.0,3,93,Urban,Software Engineer,34645,1 +15838,Male,33,High School,10,98,58,40,63,5.0,4,45,Semi-Urban,Data Analyst,115699,1 +15839,Female,45,Bachelors,19,20,36,78,35,5.0,3,93,Rural,Data Analyst,135367,0 +15840,Female,54,Masters,1,95,4,4,75,7.0,7,7,Urban,Data Analyst,70930,0 +15841,Male,27,Bachelors,11,55,7,20,88,4.0,3,86,Urban,Data Analyst,65899,0 +15842,Female,47,Diploma,8,62,71,97,51,9.0,3,37,Rural,Software Engineer,81407,1 +15843,Male,33,High School,17,81,69,2,72,8.0,0,21,Semi-Urban,HR Executive,131213,0 +15844,Male,47,Diploma,13,93,83,84,36,9.0,1,21,Semi-Urban,Manager,56215,1 +15845,Male,53,Diploma,14,88,76,97,8,7.0,3,70,Urban,Data Analyst,123538,1 +15846,Male,42,Bachelors,12,36,78,3,85,9.0,5,31,Urban,Manager,91211,0 +15847,Female,55,High School,14,54,69,69,39,8.0,3,43,Urban,ML Engineer,59585,0 +15848,Female,42,Bachelors,14,91,59,86,86,5.0,4,59,Semi-Urban,HR Executive,112459,1 +15849,Male,39,High School,1,66,87,29,11,9.0,0,10,Rural,HR Executive,20845,0 +15850,Male,33,Bachelors,5,77,54,26,96,5.0,4,6,Semi-Urban,Data Analyst,21994,0 +15851,Male,21,Masters,8,45,65,14,47,6.0,3,68,Semi-Urban,Data Analyst,83070,0 +15852,Female,34,Bachelors,11,34,27,62,67,7.0,0,3,Semi-Urban,Data Analyst,93317,0 +15853,Male,27,Bachelors,18,72,18,43,19,2.0,6,92,Semi-Urban,HR Executive,109903,0 +15854,Female,48,Bachelors,3,73,45,90,69,4.0,1,12,Urban,Manager,31891,0 +15855,Male,39,Masters,19,59,16,80,21,8.0,5,33,Semi-Urban,HR Executive,54243,0 +15856,Male,26,High School,15,62,94,91,61,8.0,2,90,Rural,Software Engineer,88916,1 +15857,Female,50,Diploma,12,10,75,13,83,3.0,4,46,Urban,ML Engineer,79488,0 +15858,Male,50,Diploma,19,97,63,76,94,2.0,6,58,Urban,Software Engineer,109814,1 +15859,Male,55,Masters,10,71,30,16,82,2.0,5,84,Semi-Urban,Manager,132363,0 +15860,Male,55,Masters,19,95,88,92,93,1.0,1,9,Urban,ML Engineer,46246,1 +15861,Male,31,Bachelors,10,27,6,24,7,6.0,5,92,Rural,ML Engineer,111521,0 +15862,Other,23,Bachelors,1,6,88,66,94,1.0,1,87,Rural,Manager,55169,1 +15863,Male,43,Masters,18,61,25,20,72,2.0,6,88,Urban,Manager,90880,0 +15864,Male,39,Masters,17,20,14,56,56,5.0,0,26,Semi-Urban,Data Analyst,123433,0 +15865,Male,58,Bachelors,17,1,9,35,48,7.0,5,75,Urban,Manager,128860,0 +15866,Male,38,Bachelors,18,6,63,95,29,5.0,2,54,Semi-Urban,Data Analyst,59310,0 +15867,Female,36,Bachelors,0,43,45,76,73,9.0,0,94,Urban,HR Executive,135758,1 +15868,Female,46,Diploma,0,0,79,19,96,1.0,4,17,Urban,ML Engineer,47185,0 +15869,Female,45,Bachelors,1,58,35,39,88,8.0,4,42,Semi-Urban,Manager,99742,0 +15870,Male,44,Diploma,16,18,94,88,86,4.0,2,47,Urban,Manager,56676,1 +15871,Male,27,PhD,12,16,52,91,95,9.0,4,31,Urban,ML Engineer,61374,0 +15872,Male,39,Bachelors,10,98,87,68,65,5.0,2,8,Urban,HR Executive,110437,1 +15873,Female,31,High School,11,58,65,50,79,4.0,0,23,Urban,HR Executive,68291,0 +15874,Male,39,Masters,16,66,22,57,0,2.0,0,86,Urban,ML Engineer,131953,0 +15875,Male,27,Bachelors,8,53,64,82,76,1.0,1,48,Rural,Manager,70156,1 +15876,Female,21,Bachelors,2,94,64,24,75,0.0,7,16,Semi-Urban,ML Engineer,134213,0 +15877,Male,31,Bachelors,10,89,33,48,59,1.0,0,5,Urban,ML Engineer,69862,0 +15878,Male,54,Bachelors,14,43,37,35,53,3.0,1,29,Semi-Urban,Data Analyst,108710,0 +15879,Male,56,Bachelors,1,77,31,46,43,8.0,6,56,Semi-Urban,ML Engineer,38708,0 +15880,Male,29,Bachelors,3,18,80,10,10,8.0,5,99,Rural,Data Analyst,26405,0 +15881,Male,26,High School,19,67,67,56,7,8.0,5,29,Urban,Data Analyst,133167,0 +15882,Male,27,Bachelors,14,3,16,53,66,1.0,5,22,Rural,Data Analyst,136724,0 +15883,Male,49,Bachelors,15,70,77,33,2,1.0,1,80,Urban,Software Engineer,117835,1 +15884,Male,32,Bachelors,2,22,95,71,28,0.0,6,31,Rural,Software Engineer,146420,0 +15885,Female,50,High School,18,85,39,86,8,0.0,7,28,Urban,HR Executive,132655,0 +15886,Male,32,Bachelors,16,5,94,65,17,3.0,7,69,Rural,HR Executive,94803,0 +15887,Female,38,Diploma,8,96,65,54,49,5.0,5,33,Urban,Data Analyst,25498,1 +15888,Male,21,Masters,3,26,5,62,25,7.0,7,45,Urban,Manager,92291,0 +15889,Male,35,Bachelors,1,32,33,10,56,6.0,4,90,Urban,Manager,123733,0 +15890,Female,25,High School,6,19,64,82,0,3.0,7,93,Urban,Manager,122359,1 +15891,Male,53,Diploma,3,90,65,54,9,8.0,2,18,Urban,Software Engineer,96676,0 +15892,Male,21,High School,11,77,26,77,40,8.0,2,67,Semi-Urban,HR Executive,69416,1 +15893,Female,42,Masters,10,0,80,14,27,1.0,3,3,Semi-Urban,HR Executive,50540,0 +15894,Male,45,Bachelors,14,54,3,84,92,3.0,1,57,Urban,Manager,49356,0 +15895,Male,41,Bachelors,17,68,4,57,74,5.0,7,13,Urban,Software Engineer,148541,0 +15896,Male,26,Masters,17,27,40,98,85,7.0,6,28,Rural,Manager,89391,0 +15897,Female,23,High School,5,63,40,95,98,8.0,5,73,Rural,Manager,124945,1 +15898,Female,26,Bachelors,18,98,54,86,49,5.0,1,63,Urban,Data Analyst,72373,1 +15899,Male,29,Diploma,10,32,57,37,11,8.0,7,61,Urban,Software Engineer,58261,0 +15900,Male,32,Masters,9,50,79,18,78,5.0,5,31,Urban,Data Analyst,64273,0 +15901,Male,24,Bachelors,9,40,29,99,33,7.0,5,78,Urban,Manager,148284,1 +15902,Male,21,High School,5,67,65,15,60,2.0,6,94,Semi-Urban,Software Engineer,38937,1 +15903,Male,47,Diploma,5,60,5,34,81,3.0,2,69,Urban,HR Executive,27699,0 +15904,Male,41,Bachelors,17,68,79,67,33,6.0,2,72,Urban,HR Executive,63282,1 +15905,Male,52,High School,11,65,8,22,82,0.0,4,67,Semi-Urban,HR Executive,64426,0 +15906,Male,33,High School,19,2,87,88,78,8.0,3,67,Urban,Manager,96036,1 +15907,Female,21,Diploma,17,38,74,77,44,1.0,3,93,Semi-Urban,Data Analyst,142526,1 +15908,Male,22,High School,2,83,92,86,30,8.0,1,37,Urban,ML Engineer,20347,1 +15909,Male,44,Masters,17,96,8,27,69,7.0,1,32,Urban,Data Analyst,104266,0 +15910,Male,33,Bachelors,14,14,25,74,31,0.0,4,82,Semi-Urban,Manager,87248,0 +15911,Female,21,Diploma,13,47,15,3,85,3.0,4,72,Urban,HR Executive,70076,0 +15912,Female,57,Bachelors,7,25,99,22,41,0.0,3,72,Urban,Software Engineer,62363,0 +15913,Female,24,Diploma,19,87,28,63,13,6.0,5,51,Semi-Urban,Manager,79263,0 +15914,Male,29,Bachelors,9,73,66,62,65,8.0,1,57,Semi-Urban,Software Engineer,126100,1 +15915,Female,58,Masters,7,50,51,16,78,6.0,5,63,Urban,Data Analyst,130633,0 +15916,Male,54,Bachelors,19,9,49,17,73,2.0,4,53,Semi-Urban,Software Engineer,68107,0 +15917,Male,41,High School,14,44,98,89,48,3.0,6,27,Urban,Manager,28772,1 +15918,Male,54,Diploma,9,2,95,80,64,2.0,0,16,Rural,HR Executive,48427,0 +15919,Female,31,Bachelors,18,57,10,69,77,8.0,7,68,Urban,Software Engineer,63201,0 +15920,Female,29,Diploma,6,33,47,27,57,8.0,7,58,Semi-Urban,HR Executive,82437,0 +15921,Female,24,High School,4,71,76,12,65,4.0,5,38,Urban,HR Executive,103813,0 +15922,Female,23,Bachelors,9,68,66,30,78,9.0,4,57,Semi-Urban,Data Analyst,28432,0 +15923,Male,50,Masters,7,99,78,15,83,6.0,3,70,Urban,Software Engineer,127433,1 +15924,Male,36,Bachelors,15,95,4,88,24,5.0,1,36,Urban,ML Engineer,99341,0 +15925,Male,41,Bachelors,5,97,31,35,90,8.0,6,71,Semi-Urban,Software Engineer,54820,0 +15926,Female,23,High School,19,93,7,86,34,5.0,6,49,Urban,Software Engineer,53468,0 +15927,Male,44,Masters,11,15,55,81,32,4.0,7,56,Semi-Urban,Data Analyst,107053,0 +15928,Female,42,Bachelors,11,74,16,77,27,2.0,2,32,Rural,Software Engineer,129404,0 +15929,Male,46,Bachelors,16,58,36,19,83,8.0,5,54,Semi-Urban,HR Executive,87856,0 +15930,Male,42,Masters,10,37,58,42,57,5.0,7,99,Semi-Urban,Data Analyst,136366,1 +15931,Male,34,Diploma,17,29,97,95,22,4.0,5,8,Rural,Manager,76784,0 +15932,Male,22,Bachelors,10,28,44,16,9,8.0,6,91,Urban,Software Engineer,121080,0 +15933,Female,25,Bachelors,17,85,48,13,59,5.0,3,97,Semi-Urban,Data Analyst,65000,1 +15934,Male,59,PhD,13,0,27,60,64,6.0,7,3,Urban,ML Engineer,121444,0 +15935,Male,25,PhD,19,37,79,32,66,9.0,3,75,Urban,Software Engineer,136100,0 +15936,Male,50,Bachelors,18,53,11,4,28,7.0,1,7,Semi-Urban,Data Analyst,93689,0 +15937,Male,38,Diploma,15,70,48,8,11,1.0,3,20,Urban,Software Engineer,31415,0 +15938,Male,45,High School,2,4,87,88,8,1.0,4,24,Urban,Data Analyst,142272,0 +15939,Male,29,Diploma,17,54,35,14,25,9.0,0,83,Urban,ML Engineer,146455,0 +15940,Female,51,High School,4,68,17,75,53,5.0,4,19,Semi-Urban,HR Executive,36179,0 +15941,Male,22,Diploma,15,42,99,8,96,1.0,5,77,Rural,Software Engineer,95749,0 +15942,Male,55,Diploma,17,16,21,99,55,5.0,3,60,Urban,HR Executive,108132,0 +15943,Male,32,Bachelors,12,20,21,58,67,8.0,7,65,Urban,Manager,85710,0 +15944,Male,52,Diploma,17,61,35,3,58,0.0,0,60,Urban,Manager,41798,0 +15945,Male,48,High School,9,27,26,88,93,3.0,5,37,Urban,Manager,84073,0 +15946,Male,52,Bachelors,7,66,72,93,36,0.0,3,87,Rural,HR Executive,20307,1 +15947,Male,21,Bachelors,5,53,6,10,9,6.0,7,6,Semi-Urban,ML Engineer,115503,0 +15948,Female,31,Bachelors,10,83,62,61,9,3.0,4,18,Urban,Data Analyst,91805,0 +15949,Male,36,Bachelors,15,25,84,46,1,8.0,4,67,Urban,Data Analyst,95030,0 +15950,Female,44,Bachelors,2,60,97,99,96,3.0,3,96,Urban,Software Engineer,30200,1 +15951,Female,52,High School,13,42,86,76,79,3.0,6,72,Urban,Software Engineer,56856,1 +15952,Male,21,Diploma,2,90,90,57,77,0.0,0,99,Urban,ML Engineer,106322,1 +15953,Male,55,Bachelors,15,81,94,42,6,6.0,7,44,Semi-Urban,ML Engineer,123972,1 +15954,Male,37,Bachelors,17,90,12,36,99,7.0,1,21,Semi-Urban,Data Analyst,145123,0 +15955,Male,42,High School,1,13,12,27,83,2.0,7,84,Urban,Software Engineer,45255,0 +15956,Female,21,Masters,4,85,75,15,44,2.0,7,92,Semi-Urban,Software Engineer,78531,1 +15957,Female,59,Diploma,1,22,17,10,39,7.0,5,20,Urban,ML Engineer,125688,0 +15958,Male,23,Bachelors,1,29,35,96,0,9.0,5,39,Semi-Urban,ML Engineer,64401,0 +15959,Male,24,Bachelors,4,11,99,1,13,2.0,1,40,Urban,HR Executive,38040,0 +15960,Male,40,Bachelors,2,53,85,63,8,5.0,2,76,Urban,ML Engineer,120517,1 +15961,Male,48,PhD,4,19,25,43,46,8.0,4,63,Urban,Manager,115584,0 +15962,Female,21,Bachelors,16,78,12,30,30,2.0,4,33,Urban,ML Engineer,25031,0 +15963,Male,27,PhD,15,11,16,29,24,7.0,6,54,Urban,Data Analyst,135431,0 +15964,Male,58,Bachelors,0,61,67,6,38,7.0,7,7,Urban,Data Analyst,51822,0 +15965,Female,50,High School,8,42,57,51,19,6.0,3,52,Urban,ML Engineer,88435,0 +15966,Male,27,Diploma,16,36,41,39,7,5.0,6,82,Urban,ML Engineer,121831,0 +15967,Male,40,Bachelors,17,50,37,67,5,1.0,2,33,Urban,Data Analyst,80694,0 +15968,Male,43,Diploma,18,34,99,58,95,9.0,5,91,Urban,ML Engineer,111048,1 +15969,Male,36,Diploma,8,89,8,30,72,4.0,1,3,Semi-Urban,Software Engineer,64193,0 +15970,Female,41,Masters,14,58,41,46,36,3.0,4,21,Urban,ML Engineer,42433,0 +15971,Female,21,Diploma,11,95,89,60,16,3.0,2,9,Urban,Data Analyst,30635,1 +15972,Male,37,High School,12,95,13,9,9,1.0,3,4,Semi-Urban,ML Engineer,107588,0 +15973,Female,56,Diploma,7,94,73,32,35,3.0,6,83,Urban,ML Engineer,38599,1 +15974,Male,22,Masters,4,92,37,18,73,8.0,4,83,Urban,Software Engineer,29893,0 +15975,Female,43,High School,9,59,63,83,90,9.0,6,7,Urban,Manager,37033,0 +15976,Female,25,Diploma,2,84,14,3,89,9.0,4,21,Rural,Data Analyst,132525,0 +15977,Male,32,Bachelors,5,61,15,39,21,4.0,5,25,Urban,ML Engineer,143943,0 +15978,Female,54,Bachelors,13,83,95,79,41,6.0,3,67,Urban,Data Analyst,131607,1 +15979,Male,37,Bachelors,2,97,7,67,52,9.0,7,62,Rural,Data Analyst,24936,0 +15980,Male,41,High School,17,55,34,23,32,6.0,0,43,Rural,ML Engineer,130061,0 +15981,Female,24,High School,13,76,11,56,1,0.0,7,11,Semi-Urban,HR Executive,111816,0 +15982,Female,46,Bachelors,7,2,26,8,28,7.0,7,44,Urban,HR Executive,108210,0 +15983,Female,45,Masters,16,83,80,61,44,2.0,1,61,Urban,Manager,57902,1 +15984,Female,46,Bachelors,18,42,20,41,51,2.0,1,71,Rural,HR Executive,65740,0 +15985,Male,44,Bachelors,7,45,31,30,28,6.0,6,48,Semi-Urban,Data Analyst,43921,0 +15986,Male,47,Bachelors,17,60,81,53,50,9.0,2,81,Rural,Manager,138386,1 +15987,Other,33,Diploma,19,33,94,42,7,4.0,0,46,Urban,HR Executive,34478,0 +15988,Male,41,Bachelors,12,59,80,37,87,5.0,2,82,Rural,Software Engineer,95022,1 +15989,Female,57,Masters,3,90,52,85,67,8.0,4,37,Rural,Data Analyst,102202,1 +15990,Male,37,Bachelors,13,43,75,38,56,3.0,0,6,Urban,Manager,39948,0 +15991,Female,45,PhD,16,32,71,83,60,7.0,6,16,Urban,Manager,67087,0 +15992,Male,30,Masters,8,28,15,71,37,1.0,7,80,Urban,HR Executive,43517,0 +15993,Other,52,Masters,19,69,8,56,15,3.0,0,22,Urban,ML Engineer,144893,0 +15994,Male,35,Bachelors,18,84,15,79,78,3.0,6,74,Semi-Urban,ML Engineer,43593,1 +15995,Female,49,Masters,1,47,60,20,45,8.0,7,93,Urban,Data Analyst,43500,0 +15996,Male,27,Bachelors,10,16,0,44,63,4.0,3,64,Semi-Urban,Data Analyst,91642,0 +15997,Male,46,Bachelors,7,26,35,35,21,1.0,3,0,Urban,Data Analyst,86845,0 +15998,Female,55,Masters,3,7,70,8,19,,3,44,Rural,Manager,25067,0 +15999,Female,38,Bachelors,8,87,27,25,11,9.0,7,67,Urban,Data Analyst,90127,0 +16000,Female,46,Bachelors,7,27,64,93,13,4.0,3,11,Urban,ML Engineer,36614,0 +16001,Male,54,Masters,1,58,1,56,7,5.0,7,68,Urban,Data Analyst,141507,0 +16002,Male,22,PhD,17,61,12,70,66,7.0,1,78,Urban,HR Executive,89512,0 +16003,Male,46,Diploma,4,38,88,24,2,9.0,7,88,Urban,Software Engineer,28134,1 +16004,Male,48,Bachelors,1,15,50,78,73,3.0,7,83,Semi-Urban,Data Analyst,54539,0 +16005,Other,46,Diploma,14,97,58,55,95,9.0,2,49,Urban,ML Engineer,149760,1 +16006,Male,54,PhD,8,59,48,57,36,6.0,3,54,Urban,ML Engineer,131885,0 +16007,Male,27,PhD,18,79,22,4,41,7.0,1,43,Rural,Data Analyst,120195,0 +16008,Male,57,Bachelors,2,99,40,84,53,0.0,0,77,Urban,Manager,91877,1 +16009,Male,42,Bachelors,12,79,93,4,25,0.0,6,92,Urban,ML Engineer,63174,1 +16010,Male,58,PhD,15,31,78,62,13,3.0,3,75,Urban,ML Engineer,137412,1 +16011,Male,49,Diploma,2,54,94,54,24,3.0,4,69,Rural,Software Engineer,129442,1 +16012,Male,44,High School,13,34,86,17,97,2.0,4,6,Urban,Manager,63117,0 +16013,Male,55,Diploma,2,50,44,36,58,4.0,6,44,Urban,HR Executive,20844,0 +16014,Other,24,Masters,11,71,14,99,14,5.0,5,65,Urban,Data Analyst,46414,1 +16015,Male,53,High School,19,1,2,11,1,3.0,6,53,Urban,Software Engineer,31331,0 +16016,Male,52,Bachelors,6,82,25,75,45,9.0,3,13,Semi-Urban,Software Engineer,99754,0 +16017,Other,36,Bachelors,3,16,67,15,21,1.0,5,43,Urban,Manager,92326,0 +16018,Female,44,Masters,4,83,3,87,87,9.0,6,91,Urban,Data Analyst,143806,1 +16019,Other,46,Bachelors,12,29,2,86,58,1.0,1,34,Urban,Manager,50534,0 +16020,Other,52,Diploma,17,71,12,73,54,2.0,0,64,Rural,Manager,91364,0 +16021,Male,32,Diploma,1,99,39,82,36,7.0,6,74,Urban,Software Engineer,132634,1 +16022,Female,34,Masters,5,91,73,9,5,9.0,4,4,Urban,Data Analyst,33212,0 +16023,Male,39,Bachelors,13,5,16,22,74,3.0,3,96,Urban,Software Engineer,116633,0 +16024,Male,38,High School,5,77,46,32,75,0.0,1,75,Urban,Data Analyst,76026,0 +16025,Female,54,Bachelors,1,46,75,69,97,4.0,0,90,Urban,Data Analyst,50829,1 +16026,Male,52,Bachelors,11,9,83,72,16,5.0,4,17,Urban,HR Executive,35557,0 +16027,Female,53,Diploma,6,69,1,8,45,9.0,0,16,Urban,Data Analyst,24567,0 +16028,Female,28,Masters,4,31,96,65,90,8.0,4,19,Urban,ML Engineer,31802,0 +16029,Male,57,Masters,15,64,41,53,9,7.0,6,28,Rural,Software Engineer,88043,0 +16030,Female,45,Bachelors,18,63,13,27,34,6.0,1,60,Urban,Manager,146522,0 +16031,Male,53,High School,6,45,51,3,94,5.0,1,61,Semi-Urban,ML Engineer,134382,0 +16032,Male,24,Bachelors,3,78,80,59,40,9.0,3,29,Urban,Manager,114093,1 +16033,Female,31,Bachelors,3,15,17,44,91,1.0,2,77,Urban,Manager,43437,0 +16034,Male,31,Bachelors,3,52,44,39,43,3.0,4,1,Urban,Manager,89832,0 +16035,Female,41,Bachelors,6,28,92,5,34,7.0,7,56,Urban,Software Engineer,86337,0 +16036,Male,41,Bachelors,10,61,37,19,87,0.0,5,97,Urban,Data Analyst,148638,0 +16037,Male,34,Bachelors,17,67,55,26,32,1.0,4,24,Rural,ML Engineer,35414,0 +16038,Female,33,Diploma,2,17,68,26,60,6.0,4,46,Semi-Urban,Manager,96710,0 +16039,Male,54,Masters,17,13,81,58,78,9.0,2,13,Urban,HR Executive,118587,0 +16040,Male,53,Masters,15,79,64,43,14,3.0,3,60,Rural,Manager,136076,1 +16041,Male,37,Bachelors,8,1,83,40,20,3.0,0,19,Rural,Software Engineer,82496,0 +16042,Female,28,Bachelors,3,11,48,1,91,7.0,3,97,Urban,Software Engineer,23780,0 +16043,Male,45,Bachelors,2,22,71,87,85,5.0,1,52,Urban,Data Analyst,106304,0 +16044,Female,37,Diploma,4,84,34,4,8,5.0,0,18,Rural,Data Analyst,24033,0 +16045,Male,46,Masters,3,29,13,25,74,4.0,1,88,Rural,HR Executive,42346,0 +16046,Female,25,Diploma,18,53,3,21,53,1.0,4,85,Urban,ML Engineer,58531,0 +16047,Female,41,Bachelors,12,72,35,75,26,4.0,0,68,Rural,ML Engineer,47075,1 +16048,Male,36,Bachelors,3,48,60,56,99,0.0,2,73,Semi-Urban,Manager,32117,1 +16049,Male,38,Diploma,10,87,94,4,74,6.0,1,42,Urban,Manager,55990,0 +16050,Female,24,Masters,17,46,20,54,2,2.0,3,38,Urban,Manager,60398,0 +16051,Female,31,High School,17,15,23,79,56,5.0,5,66,Semi-Urban,Software Engineer,106003,0 +16052,Male,32,High School,16,94,37,14,85,6.0,3,83,Urban,Software Engineer,144433,0 +16053,Female,45,Bachelors,3,61,93,54,64,0.0,3,63,Semi-Urban,HR Executive,85613,1 +16054,Female,58,Bachelors,4,97,98,72,76,8.0,6,19,Rural,Data Analyst,126573,1 +16055,Female,46,PhD,19,73,78,7,12,9.0,5,76,Semi-Urban,ML Engineer,57465,0 +16056,Female,53,Masters,5,61,30,82,32,3.0,6,30,Urban,ML Engineer,40575,0 +16057,Male,52,High School,6,4,93,2,90,4.0,6,4,Rural,Software Engineer,77272,0 +16058,Other,47,Bachelors,10,45,44,36,25,9.0,1,88,Rural,HR Executive,20802,0 +16059,Male,29,Diploma,19,1,98,91,30,1.0,0,42,Rural,HR Executive,149601,0 +16060,Male,46,Bachelors,6,99,64,75,84,4.0,2,20,Rural,Data Analyst,70239,1 +16061,Male,31,Masters,5,21,47,76,11,1.0,6,52,Rural,Software Engineer,44061,0 +16062,Male,21,Bachelors,0,11,83,59,11,0.0,5,75,Semi-Urban,Manager,122575,0 +16063,Male,43,Diploma,1,73,40,74,16,6.0,4,94,Urban,Data Analyst,60816,1 +16064,Male,22,High School,18,6,8,83,98,4.0,3,13,Urban,ML Engineer,112488,0 +16065,Male,48,Masters,1,44,45,84,9,7.0,7,28,Urban,Software Engineer,43003,0 +16066,Female,42,PhD,5,99,70,13,62,9.0,4,58,Urban,Data Analyst,24278,0 +16067,Male,46,High School,5,5,87,32,18,5.0,4,77,Semi-Urban,HR Executive,22694,0 +16068,Male,42,Bachelors,18,8,90,52,30,8.0,5,58,Urban,HR Executive,118308,0 +16069,Male,49,Masters,14,29,67,48,47,8.0,2,77,Rural,Software Engineer,141696,0 +16070,Male,25,High School,1,23,70,6,46,8.0,7,24,Urban,Software Engineer,92289,0 +16071,Male,34,Bachelors,19,10,35,87,54,6.0,6,68,Urban,ML Engineer,38941,0 +16072,Male,26,Diploma,0,3,3,25,95,9.0,0,23,Rural,HR Executive,122405,0 +16073,Other,59,Diploma,15,65,47,6,52,1.0,6,50,Rural,ML Engineer,80122,0 +16074,Female,55,PhD,18,50,34,1,25,7.0,3,12,Semi-Urban,Manager,112739,0 +16075,Female,34,Bachelors,5,10,55,35,9,8.0,5,69,Rural,Manager,142086,0 +16076,Male,38,High School,15,48,53,47,2,6.0,3,26,Urban,Software Engineer,101230,0 +16077,Male,32,PhD,9,77,68,9,16,1.0,5,35,Rural,ML Engineer,68922,0 +16078,Male,54,Bachelors,17,52,81,15,18,7.0,0,8,Urban,HR Executive,57999,0 +16079,Female,53,Bachelors,9,37,88,21,1,3.0,4,86,Semi-Urban,ML Engineer,108161,0 +16080,Male,34,Bachelors,0,50,93,69,29,6.0,1,40,Semi-Urban,HR Executive,118315,1 +16081,Male,47,PhD,13,87,17,12,75,4.0,2,8,Rural,Manager,119305,0 +16082,Male,38,Masters,4,17,8,67,16,0.0,1,32,Urban,Data Analyst,74524,0 +16083,Male,23,High School,18,38,54,92,55,4.0,1,38,Urban,Software Engineer,122094,0 +16084,Other,34,High School,5,44,10,29,63,0.0,6,0,Urban,ML Engineer,37975,0 +16085,Female,27,Diploma,11,44,19,72,50,8.0,7,87,Urban,HR Executive,110115,0 +16086,Female,44,High School,0,14,36,19,82,1.0,1,57,Urban,ML Engineer,106314,0 +16087,Male,21,Diploma,11,37,67,40,99,8.0,2,61,Semi-Urban,HR Executive,34408,0 +16088,Female,50,Bachelors,8,30,44,39,81,7.0,4,47,Rural,Data Analyst,75214,0 +16089,Female,24,Masters,11,55,38,30,94,5.0,3,35,Urban,HR Executive,54385,0 +16090,Female,48,Masters,0,59,49,64,5,0.0,1,10,Urban,Software Engineer,76357,0 +16091,Male,30,Masters,11,63,0,13,59,0.0,4,96,Urban,Software Engineer,57660,0 +16092,Male,50,Masters,14,34,74,30,16,5.0,0,9,Urban,ML Engineer,55754,0 +16093,Female,40,High School,6,99,77,12,24,2.0,0,90,Urban,HR Executive,68681,1 +16094,Male,53,Diploma,2,26,84,50,56,8.0,4,17,Rural,Data Analyst,85602,0 +16095,Female,42,High School,19,97,24,28,7,0.0,6,70,Urban,HR Executive,148827,0 +16096,Other,41,High School,17,75,40,65,86,9.0,5,98,Urban,Manager,78929,1 +16097,Male,24,Bachelors,4,89,24,45,57,2.0,1,66,Urban,HR Executive,90252,0 +16098,Male,28,Masters,7,45,55,67,43,4.0,2,47,Urban,Manager,136860,0 +16099,Male,37,Masters,18,32,75,72,49,7.0,0,97,Semi-Urban,Manager,57504,1 +16100,Female,21,Diploma,12,40,42,43,66,1.0,1,26,Rural,Data Analyst,143274,0 +16101,Female,44,High School,6,53,19,14,30,6.0,1,32,Urban,Software Engineer,86370,0 +16102,Male,37,Masters,17,75,4,72,20,8.0,5,42,Urban,ML Engineer,50907,0 +16103,Male,49,Masters,13,87,46,34,42,9.0,7,38,Urban,Software Engineer,140526,0 +16104,Male,27,Bachelors,19,29,50,28,14,0.0,5,41,Semi-Urban,Software Engineer,64599,0 +16105,Female,42,Masters,16,57,87,32,45,2.0,1,32,Urban,ML Engineer,91323,0 +16106,Male,33,Bachelors,9,45,67,38,63,7.0,0,17,Semi-Urban,Software Engineer,69521,0 +16107,Male,34,Masters,5,45,58,63,59,6.0,0,68,Urban,Manager,23793,0 +16108,Female,31,High School,17,77,63,35,19,7.0,7,73,Urban,HR Executive,46768,1 +16109,Male,35,High School,1,14,6,6,67,1.0,4,46,Urban,Manager,22224,0 +16110,Male,46,Bachelors,18,29,29,39,57,1.0,7,50,Semi-Urban,Manager,41954,0 +16111,Male,46,Bachelors,11,55,24,91,30,7.0,4,68,Semi-Urban,Manager,22733,1 +16112,Male,25,Masters,7,70,62,95,17,4.0,4,35,Urban,Data Analyst,60939,1 +16113,Male,38,Bachelors,3,3,17,79,56,0.0,4,55,Urban,HR Executive,142351,0 +16114,Other,21,Masters,16,3,34,55,89,0.0,7,80,Semi-Urban,ML Engineer,141806,0 +16115,Female,22,Masters,12,64,68,53,34,8.0,5,88,Rural,Manager,117715,1 +16116,Female,23,Bachelors,8,9,19,24,1,1.0,6,31,Urban,HR Executive,82039,0 +16117,Female,57,Bachelors,19,90,38,10,25,9.0,0,58,Semi-Urban,ML Engineer,62114,0 +16118,Male,59,Diploma,11,24,24,26,88,5.0,2,42,Urban,HR Executive,67918,0 +16119,Male,36,Bachelors,8,31,76,36,13,6.0,3,96,Urban,HR Executive,141427,1 +16120,Male,54,Bachelors,6,55,57,92,41,2.0,1,64,Rural,Software Engineer,74020,1 +16121,Female,37,Bachelors,17,92,41,97,76,2.0,1,73,Rural,Data Analyst,45743,1 +16122,Female,41,Diploma,5,50,92,97,84,6.0,7,60,Urban,Manager,145571,1 +16123,Male,49,Masters,11,5,85,20,71,7.0,4,91,Urban,Manager,126718,0 +16124,Male,40,Bachelors,17,22,65,37,16,2.0,7,3,Urban,HR Executive,36772,0 +16125,Male,51,Diploma,18,63,18,77,28,0.0,4,74,Urban,Data Analyst,33375,0 +16126,Male,27,Bachelors,16,39,23,11,20,0.0,0,4,Urban,Data Analyst,37911,0 +16127,Female,37,Masters,15,9,63,20,13,0.0,0,2,Urban,HR Executive,138142,0 +16128,Male,36,Masters,7,79,26,94,54,1.0,6,73,Urban,Software Engineer,84503,1 +16129,Female,45,Bachelors,4,96,65,2,83,3.0,2,11,Urban,ML Engineer,20486,0 +16130,Male,54,Bachelors,16,3,39,49,51,4.0,1,84,Urban,HR Executive,23391,0 +16131,Female,43,High School,14,17,21,85,57,1.0,1,87,Urban,Software Engineer,32679,0 +16132,Female,56,High School,19,68,60,12,44,1.0,7,92,Rural,ML Engineer,48093,0 +16133,Female,44,Bachelors,7,67,1,13,8,6.0,1,45,Rural,Software Engineer,32483,0 +16134,Male,31,PhD,9,86,90,40,6,5.0,1,26,Urban,ML Engineer,68850,1 +16135,Male,22,Diploma,8,42,94,55,2,5.0,1,78,Urban,Software Engineer,76878,1 +16136,Male,48,Bachelors,1,48,40,60,68,6.0,2,36,Semi-Urban,Data Analyst,120195,0 +16137,Male,56,Masters,2,41,19,6,20,2.0,5,0,Semi-Urban,HR Executive,72346,0 +16138,Female,52,Bachelors,0,17,21,1,22,3.0,5,23,Semi-Urban,ML Engineer,112074,0 +16139,Female,26,Bachelors,11,15,1,94,78,6.0,4,61,Semi-Urban,Software Engineer,27963,0 +16140,Male,42,Diploma,5,68,99,26,25,8.0,5,41,Semi-Urban,HR Executive,42566,0 +16141,Male,36,High School,12,44,82,70,99,9.0,7,41,Urban,Data Analyst,23634,1 +16142,Male,32,High School,11,42,41,5,96,4.0,2,74,Rural,Manager,127624,0 +16143,Female,33,Bachelors,16,70,30,51,97,6.0,7,51,Semi-Urban,Data Analyst,133169,0 +16144,Other,22,Bachelors,0,57,42,85,55,8.0,5,45,Semi-Urban,Data Analyst,96735,0 +16145,Male,35,Masters,12,24,86,89,11,2.0,5,87,Urban,Software Engineer,117498,1 +16146,Male,22,Bachelors,7,79,41,59,94,5.0,4,28,Urban,Manager,126634,0 +16147,Female,42,Bachelors,3,26,78,40,9,5.0,5,62,Urban,Manager,108173,0 +16148,Female,34,Bachelors,2,19,40,42,3,7.0,1,43,Urban,Software Engineer,30183,0 +16149,Male,50,Masters,2,13,40,98,73,0.0,2,70,Urban,HR Executive,87664,0 +16150,Female,42,Bachelors,8,44,95,81,41,5.0,2,0,Rural,ML Engineer,51117,0 +16151,Other,33,Bachelors,17,66,17,83,82,6.0,4,4,Rural,Software Engineer,71511,0 +16152,Male,29,Bachelors,16,74,34,77,97,6.0,7,20,Urban,Data Analyst,56708,0 +16153,Male,57,High School,18,58,44,15,70,5.0,3,30,Rural,Manager,114327,0 +16154,Male,45,PhD,8,88,35,72,54,6.0,5,71,Urban,HR Executive,122788,1 +16155,Male,40,PhD,10,83,74,57,63,7.0,3,38,Semi-Urban,Software Engineer,103399,1 +16156,Male,35,Diploma,2,3,54,85,89,1.0,7,99,Urban,Software Engineer,88508,1 +16157,Male,44,Bachelors,17,87,46,54,64,5.0,1,43,Urban,ML Engineer,74588,0 +16158,Male,45,Masters,3,4,38,32,92,3.0,0,45,Semi-Urban,HR Executive,144538,0 +16159,Male,21,High School,14,6,92,34,87,7.0,2,77,Urban,Data Analyst,46019,0 +16160,Male,58,Diploma,18,50,71,70,56,3.0,5,63,Urban,Data Analyst,146053,1 +16161,Male,26,Masters,11,98,54,67,58,6.0,1,73,Urban,Manager,143921,1 +16162,Female,30,Bachelors,16,50,89,44,9,9.0,7,44,Urban,Manager,130739,0 +16163,Female,56,PhD,18,4,55,44,76,2.0,7,3,Urban,Software Engineer,33639,0 +16164,Male,29,Bachelors,15,84,75,91,54,3.0,7,83,Urban,Manager,146802,1 +16165,Male,51,Bachelors,4,15,3,76,6,3.0,5,22,Rural,Data Analyst,36620,0 +16166,Female,55,Bachelors,2,45,50,43,20,8.0,5,65,Urban,Manager,35842,0 +16167,Male,22,Masters,18,21,70,38,22,0.0,1,24,Urban,HR Executive,60338,0 +16168,Other,46,Bachelors,9,49,33,88,49,2.0,6,97,Semi-Urban,HR Executive,118741,1 +16169,Male,59,Diploma,14,79,42,51,61,5.0,5,10,Rural,ML Engineer,76470,0 +16170,Female,40,Bachelors,9,97,50,62,68,5.0,3,35,Urban,Manager,109362,1 +16171,Male,22,Masters,10,47,28,22,26,5.0,5,75,Urban,ML Engineer,32086,0 +16172,Female,46,Masters,18,14,69,69,8,8.0,3,9,Rural,ML Engineer,52780,0 +16173,Female,39,Masters,19,84,97,30,49,5.0,3,34,Urban,HR Executive,27402,1 +16174,Female,26,Diploma,4,2,60,84,21,1.0,4,62,Urban,Data Analyst,91737,0 +16175,Other,49,Masters,16,64,78,68,88,2.0,3,68,Urban,ML Engineer,71290,1 +16176,Male,42,Diploma,19,74,4,15,85,9.0,6,7,Urban,Software Engineer,103741,0 +16177,Male,34,Masters,17,25,39,48,76,7.0,1,91,Urban,HR Executive,21792,0 +16178,Male,34,Bachelors,1,99,60,89,80,7.0,6,13,Urban,ML Engineer,118163,1 +16179,Male,59,PhD,13,94,97,80,78,7.0,4,22,Urban,Manager,88313,1 +16180,Male,56,Bachelors,13,71,54,61,19,0.0,4,74,Semi-Urban,ML Engineer,28504,1 +16181,Female,56,Bachelors,4,99,3,93,34,4.0,7,4,Semi-Urban,Manager,42114,0 +16182,Female,34,Masters,1,82,99,76,73,2.0,2,0,Urban,Software Engineer,68071,1 +16183,Male,56,Masters,16,46,35,35,31,3.0,1,17,Rural,HR Executive,134611,0 +16184,Male,25,Masters,5,66,35,97,24,5.0,4,40,Rural,Software Engineer,105713,1 +16185,Male,45,PhD,1,17,89,60,66,9.0,1,20,Urban,Data Analyst,131320,0 +16186,Female,29,High School,14,77,67,45,50,6.0,4,55,Semi-Urban,Software Engineer,128116,1 +16187,Male,26,Bachelors,10,74,85,39,94,4.0,2,98,Semi-Urban,ML Engineer,112578,1 +16188,Female,43,Bachelors,6,65,48,61,11,3.0,2,92,Rural,Manager,26975,1 +16189,Female,52,Bachelors,2,90,65,29,89,9.0,5,85,Rural,ML Engineer,134149,1 +16190,Female,35,Diploma,1,25,26,3,57,7.0,0,74,Urban,Manager,92478,0 +16191,Male,30,Bachelors,11,40,80,80,22,0.0,7,56,Urban,Software Engineer,82130,1 +16192,Male,28,Diploma,0,72,20,35,18,4.0,0,76,Rural,ML Engineer,140152,0 +16193,Female,57,High School,8,28,59,64,27,3.0,4,54,Urban,HR Executive,132945,0 +16194,Female,56,Bachelors,9,50,60,18,69,3.0,1,3,Semi-Urban,ML Engineer,68776,0 +16195,Other,48,Diploma,5,83,65,28,47,6.0,2,11,Rural,ML Engineer,93411,0 +16196,Male,51,Diploma,9,20,0,80,59,3.0,0,20,Semi-Urban,Data Analyst,67971,0 +16197,Female,47,High School,16,99,48,48,51,3.0,0,56,Semi-Urban,Manager,46974,1 +16198,Male,32,Bachelors,16,80,28,44,52,3.0,7,56,Semi-Urban,Software Engineer,76879,0 +16199,Female,41,PhD,19,93,4,29,48,9.0,1,2,Rural,Data Analyst,52035,0 +16200,Female,47,Bachelors,15,64,54,10,69,3.0,7,30,Urban,HR Executive,96611,0 +16201,Female,48,Bachelors,19,32,84,78,92,3.0,4,35,Urban,HR Executive,60728,0 +16202,Female,52,High School,7,63,76,55,62,8.0,7,28,Urban,ML Engineer,80834,0 +16203,Male,28,Bachelors,19,8,33,27,55,9.0,0,70,Rural,ML Engineer,69920,0 +16204,Other,58,Masters,6,95,47,84,28,1.0,2,90,Urban,ML Engineer,85186,1 +16205,Other,39,Bachelors,7,46,11,61,82,9.0,2,98,Urban,Data Analyst,36209,0 +16206,Male,40,High School,6,16,0,35,91,5.0,3,73,Semi-Urban,ML Engineer,55121,0 +16207,Female,55,Diploma,6,37,56,37,36,9.0,5,42,Urban,Manager,69116,0 +16208,Male,32,Masters,14,51,64,65,5,5.0,2,44,Semi-Urban,HR Executive,34221,0 +16209,Female,52,Masters,9,64,44,80,96,3.0,3,88,Rural,Data Analyst,143640,1 +16210,Male,28,Bachelors,18,59,44,36,96,1.0,6,61,Semi-Urban,Software Engineer,47811,0 +16211,Other,24,Bachelors,5,49,80,83,84,2.0,0,97,Semi-Urban,Software Engineer,61573,1 +16212,Male,21,Masters,5,84,93,16,79,3.0,3,36,Urban,Data Analyst,83874,0 +16213,Male,59,Masters,17,38,2,50,61,1.0,7,28,Urban,Data Analyst,103087,0 +16214,Male,48,Masters,2,29,12,54,66,5.0,6,95,Urban,Manager,76251,0 +16215,Male,35,Diploma,4,51,8,38,55,7.0,4,41,Urban,Software Engineer,125835,0 +16216,Female,31,Bachelors,0,90,91,90,91,1.0,2,27,Urban,Manager,97112,1 +16217,Male,56,Masters,3,79,71,83,60,8.0,5,70,Urban,HR Executive,149590,1 +16218,Female,39,PhD,8,73,78,71,76,1.0,4,0,Semi-Urban,ML Engineer,43101,0 +16219,Other,47,High School,0,77,53,35,19,4.0,5,59,Urban,HR Executive,79495,0 +16220,Female,32,Diploma,12,64,28,95,92,1.0,0,12,Urban,Data Analyst,127677,0 +16221,Female,31,High School,2,73,16,10,67,7.0,0,42,Urban,HR Executive,103197,0 +16222,Male,39,Masters,15,40,40,39,1,9.0,4,13,Urban,Software Engineer,72262,0 +16223,Male,59,PhD,12,29,83,59,81,4.0,0,18,Rural,ML Engineer,37838,0 +16224,Male,21,Bachelors,17,66,10,43,10,1.0,7,70,Urban,HR Executive,35860,0 +16225,Male,30,Bachelors,16,99,70,18,32,6.0,1,60,Urban,ML Engineer,69287,1 +16226,Female,46,Diploma,0,11,33,43,30,7.0,4,19,Semi-Urban,Manager,114962,0 +16227,Male,51,Masters,1,32,68,23,18,0.0,0,98,Rural,HR Executive,146490,0 +16228,Female,34,Diploma,0,34,0,88,45,1.0,0,26,Rural,HR Executive,66156,0 +16229,Male,56,Bachelors,14,91,68,20,56,3.0,4,84,Semi-Urban,HR Executive,45829,1 +16230,Female,24,High School,16,78,10,33,57,5.0,2,16,Rural,ML Engineer,140661,0 +16231,Male,39,High School,4,33,70,4,68,0.0,5,18,Urban,Software Engineer,92103,0 +16232,Male,56,Masters,5,86,92,11,11,3.0,5,10,Urban,Manager,63540,0 +16233,Female,50,Bachelors,2,9,30,64,56,5.0,2,1,Urban,Data Analyst,111606,0 +16234,Male,54,Diploma,7,4,46,59,53,1.0,5,13,Urban,ML Engineer,68249,0 +16235,Female,58,Bachelors,9,75,13,57,79,2.0,7,10,Urban,Manager,77803,0 +16236,Male,46,Diploma,17,11,27,25,39,6.0,1,73,Semi-Urban,Software Engineer,103669,0 +16237,Male,41,Masters,13,57,53,11,11,3.0,1,58,Urban,ML Engineer,22442,0 +16238,Female,39,PhD,3,29,99,29,15,0.0,0,4,Semi-Urban,Data Analyst,44299,0 +16239,Male,32,Diploma,3,70,46,79,40,7.0,3,92,Urban,ML Engineer,21058,1 +16240,Female,47,PhD,8,14,25,60,9,8.0,0,36,Semi-Urban,ML Engineer,21927,0 +16241,Male,55,Bachelors,14,99,18,17,26,0.0,2,63,Rural,ML Engineer,118008,0 +16242,Female,32,Bachelors,12,79,90,5,48,1.0,1,91,Urban,HR Executive,130053,1 +16243,Male,27,Diploma,6,70,96,25,80,7.0,4,53,Urban,Software Engineer,87398,1 +16244,Male,37,Diploma,12,10,3,17,21,3.0,5,86,Semi-Urban,ML Engineer,60854,0 +16245,Male,29,Bachelors,9,26,21,25,34,5.0,4,84,Rural,Software Engineer,106242,0 +16246,Male,37,Diploma,19,43,63,14,36,2.0,5,25,Rural,HR Executive,29956,0 +16247,Male,34,High School,8,91,22,90,83,6.0,1,11,Semi-Urban,Software Engineer,136187,0 +16248,Female,53,Diploma,9,78,66,7,82,7.0,4,89,Urban,Software Engineer,55222,0 +16249,Female,31,Masters,10,56,61,23,50,0.0,6,66,Urban,HR Executive,62057,0 +16250,Male,42,Diploma,13,80,36,50,87,9.0,6,52,Urban,Software Engineer,107074,0 +16251,Male,43,Bachelors,19,81,78,39,77,4.0,3,42,Semi-Urban,Manager,115758,1 +16252,Male,45,Masters,14,81,61,30,2,1.0,2,52,Urban,Software Engineer,108786,0 +16253,Male,42,Bachelors,19,15,31,88,83,4.0,6,0,Urban,ML Engineer,104809,0 +16254,Male,57,Masters,5,67,26,73,71,1.0,3,72,Urban,Manager,60769,1 +16255,Male,33,Diploma,11,28,9,63,88,0.0,3,7,Urban,HR Executive,129256,0 +16256,Other,43,Masters,9,26,69,42,46,6.0,2,72,Semi-Urban,ML Engineer,103400,0 +16257,Female,37,Bachelors,6,22,73,66,76,2.0,4,80,Urban,HR Executive,93072,1 +16258,Male,58,Bachelors,14,46,18,36,15,2.0,2,57,Semi-Urban,ML Engineer,106558,0 +16259,Male,21,Masters,8,50,87,11,97,6.0,2,44,Semi-Urban,Data Analyst,26579,0 +16260,Female,34,Bachelors,2,77,67,5,24,2.0,1,51,Urban,Software Engineer,74786,0 +16261,Male,29,Diploma,6,58,37,66,59,8.0,6,24,Urban,Manager,86886,0 +16262,Female,50,Diploma,0,12,30,2,47,2.0,1,8,Semi-Urban,Software Engineer,48529,0 +16263,Female,45,High School,7,6,28,89,33,8.0,0,59,Rural,HR Executive,81312,0 +16264,Male,52,Bachelors,10,41,11,42,43,8.0,5,97,Urban,HR Executive,78502,0 +16265,Male,44,High School,18,71,29,12,80,0.0,3,30,Semi-Urban,HR Executive,87833,0 +16266,Female,52,Masters,13,3,25,34,82,9.0,6,56,Urban,Data Analyst,49128,0 +16267,Other,34,Diploma,12,93,23,80,44,3.0,7,14,Urban,Data Analyst,123101,0 +16268,Male,27,Masters,5,86,78,70,11,9.0,3,87,Urban,HR Executive,139706,1 +16269,Female,49,Diploma,11,59,24,75,61,6.0,1,23,Urban,Data Analyst,36651,0 +16270,Male,30,Bachelors,8,5,94,60,65,8.0,3,39,Urban,HR Executive,107950,0 +16271,Male,39,Bachelors,8,48,42,31,6,3.0,0,62,Urban,Software Engineer,136215,0 +16272,Female,34,Bachelors,11,40,1,89,47,8.0,4,60,Urban,HR Executive,60489,0 +16273,Female,38,Masters,1,99,3,15,65,1.0,5,89,Urban,Software Engineer,34087,0 +16274,Female,31,Diploma,1,26,98,70,38,2.0,7,81,Semi-Urban,Manager,59978,1 +16275,Female,59,High School,2,93,44,14,93,5.0,4,78,Urban,Software Engineer,115680,0 +16276,Male,46,Bachelors,19,92,79,30,14,4.0,5,87,Urban,Software Engineer,55661,1 +16277,Male,59,High School,18,28,26,19,48,4.0,5,91,Rural,Data Analyst,142761,0 +16278,Male,34,Masters,11,10,7,5,52,3.0,7,91,Urban,Data Analyst,86834,0 +16279,Male,44,Diploma,4,88,63,37,92,5.0,6,37,Semi-Urban,Software Engineer,126230,0 +16280,Female,29,Diploma,4,73,76,46,68,5.0,1,34,Urban,Data Analyst,97648,0 +16281,Male,59,Bachelors,11,17,56,9,53,7.0,3,61,Urban,Software Engineer,136801,0 +16282,Female,46,Masters,12,54,54,39,93,5.0,5,34,Rural,Manager,48199,0 +16283,Female,33,Masters,12,76,70,70,4,1.0,3,56,Urban,ML Engineer,22277,1 +16284,Male,28,Diploma,9,10,66,93,94,1.0,6,58,Urban,ML Engineer,35016,0 +16285,Male,35,Diploma,16,3,50,32,46,0.0,2,86,Urban,ML Engineer,51811,0 +16286,Female,59,Masters,9,48,41,57,31,2.0,5,68,Urban,Manager,93892,0 +16287,Other,47,Bachelors,14,70,57,54,33,0.0,1,60,Urban,ML Engineer,24548,1 +16288,Female,23,Bachelors,13,31,69,5,68,8.0,2,92,Semi-Urban,Manager,103495,0 +16289,Male,46,Bachelors,9,47,4,64,25,0.0,5,68,Semi-Urban,Software Engineer,103718,0 +16290,Male,45,Bachelors,10,14,99,41,24,1.0,4,80,Urban,Data Analyst,143386,0 +16291,Male,50,Bachelors,5,82,61,79,85,2.0,3,85,Urban,Software Engineer,132988,1 +16292,Male,50,PhD,13,82,54,46,8,1.0,4,25,Urban,Manager,28556,0 +16293,Female,46,Bachelors,18,31,19,26,74,9.0,5,56,Urban,HR Executive,126310,0 +16294,Female,39,High School,4,80,60,67,29,6.0,3,33,Urban,Manager,135123,0 +16295,Male,47,PhD,8,79,46,18,62,4.0,7,55,Urban,HR Executive,100745,0 +16296,Male,25,Bachelors,14,68,65,96,69,2.0,0,19,Urban,HR Executive,120583,1 +16297,Male,59,Bachelors,12,85,79,78,60,4.0,4,42,Rural,ML Engineer,99556,1 +16298,Female,53,Diploma,15,20,69,31,69,6.0,2,0,Urban,Software Engineer,22980,0 +16299,Male,36,Masters,13,40,23,78,89,9.0,3,52,Urban,Data Analyst,92526,0 +16300,Female,45,Bachelors,17,71,55,99,41,3.0,5,34,Urban,Data Analyst,66950,1 +16301,Male,58,Bachelors,5,86,21,92,5,4.0,1,67,Rural,Manager,68251,1 +16302,Female,23,Masters,4,3,57,40,78,3.0,4,10,Urban,ML Engineer,23019,0 +16303,Male,43,Bachelors,6,61,62,20,56,2.0,4,25,Rural,ML Engineer,24062,0 +16304,Male,33,Bachelors,11,20,60,67,5,2.0,7,14,Urban,Manager,131301,0 +16305,Female,42,Masters,13,38,40,16,71,3.0,5,10,Urban,Manager,142006,0 +16306,Male,22,Diploma,15,33,19,1,93,1.0,6,16,Rural,Manager,31164,0 +16307,Male,58,Bachelors,8,4,96,89,41,5.0,3,26,Urban,Data Analyst,95822,0 +16308,Male,36,High School,11,48,46,70,9,7.0,3,85,Urban,HR Executive,111430,1 +16309,Male,53,Bachelors,8,88,10,12,78,8.0,1,69,Urban,Software Engineer,74894,0 +16310,Male,21,Bachelors,6,46,65,77,65,4.0,3,77,Semi-Urban,Software Engineer,25192,1 +16311,Female,28,Diploma,9,67,40,29,15,7.0,3,37,Urban,Manager,107937,0 +16312,Female,39,High School,14,38,16,68,96,6.0,0,12,Rural,Data Analyst,136061,0 +16313,Male,33,Bachelors,8,62,92,14,78,0.0,7,92,Semi-Urban,Manager,127738,1 +16314,Male,48,Masters,18,64,24,88,41,3.0,1,39,Urban,Software Engineer,29427,0 +16315,Male,28,High School,0,12,23,97,89,3.0,5,92,Urban,Data Analyst,84067,0 +16316,Male,42,Masters,3,74,16,12,40,4.0,0,71,Urban,HR Executive,92688,0 +16317,Male,43,Diploma,1,15,11,78,1,7.0,3,92,Rural,Software Engineer,99845,0 +16318,Female,31,Diploma,0,88,32,94,98,7.0,4,39,Urban,ML Engineer,80610,1 +16319,Male,31,PhD,4,66,61,30,85,2.0,4,31,Rural,ML Engineer,57257,0 +16320,Male,41,High School,8,92,85,90,50,7.0,7,12,Semi-Urban,Manager,35316,1 +16321,Female,53,Bachelors,8,91,47,77,70,3.0,7,90,Urban,ML Engineer,36264,1 +16322,Female,36,Bachelors,6,23,67,27,44,6.0,6,97,Urban,Data Analyst,33540,0 +16323,Other,25,PhD,17,37,35,70,30,5.0,4,50,Semi-Urban,Software Engineer,41195,0 +16324,Female,51,Bachelors,0,45,35,74,6,2.0,3,31,Urban,Data Analyst,109879,0 +16325,Female,34,Bachelors,2,74,38,52,87,1.0,2,61,Urban,ML Engineer,79018,0 +16326,Male,26,Diploma,19,23,81,29,21,9.0,7,69,Rural,ML Engineer,116256,0 +16327,Male,48,Masters,17,48,6,17,66,7.0,1,51,Urban,HR Executive,130025,0 +16328,Male,38,Bachelors,4,58,65,48,25,5.0,5,49,Urban,ML Engineer,75778,0 +16329,Female,42,High School,9,77,4,95,81,0.0,4,93,Urban,HR Executive,105317,1 +16330,Female,26,Diploma,2,72,47,41,28,6.0,6,22,Urban,ML Engineer,107873,0 +16331,Male,32,Masters,17,24,26,37,19,9.0,4,24,Rural,ML Engineer,111184,0 +16332,Female,59,Bachelors,16,66,8,72,0,3.0,3,71,Urban,HR Executive,43977,0 +16333,Female,24,Masters,10,88,55,2,75,9.0,2,75,Urban,HR Executive,87592,0 +16334,Female,35,High School,19,1,5,88,51,4.0,3,99,Urban,Software Engineer,146775,0 +16335,Female,44,Diploma,13,91,60,67,7,9.0,5,54,Urban,Software Engineer,129149,1 +16336,Other,36,Bachelors,12,9,90,99,36,9.0,6,73,Urban,Data Analyst,142797,1 +16337,Male,23,Bachelors,19,28,97,7,17,2.0,7,75,Urban,ML Engineer,79599,0 +16338,Male,44,Diploma,3,26,73,58,38,6.0,3,3,Semi-Urban,Data Analyst,100216,0 +16339,Male,36,High School,19,32,60,1,72,9.0,7,1,Rural,Manager,122277,0 +16340,Male,38,Bachelors,3,20,62,86,87,0.0,2,69,Urban,Software Engineer,90827,1 +16341,Male,50,Masters,14,36,97,57,50,1.0,6,50,Urban,HR Executive,53488,1 +16342,Female,21,Masters,8,1,95,3,18,6.0,3,96,Rural,HR Executive,51928,0 +16343,Female,32,Bachelors,19,82,56,97,75,4.0,2,72,Urban,ML Engineer,114984,1 +16344,Female,23,Diploma,14,35,62,46,10,8.0,6,4,Urban,ML Engineer,129266,0 +16345,Male,26,Bachelors,6,76,84,77,54,7.0,1,32,Urban,Manager,130391,1 +16346,Male,49,PhD,16,23,22,49,24,0.0,1,92,Semi-Urban,Data Analyst,86932,0 +16347,Male,56,Bachelors,17,73,70,48,35,1.0,3,64,Urban,Manager,67418,1 +16348,Male,23,Bachelors,18,26,43,18,82,0.0,7,0,Rural,ML Engineer,47018,0 +16349,Male,49,Bachelors,17,70,3,93,97,1.0,3,69,Urban,HR Executive,121192,1 +16350,Male,21,High School,12,29,45,48,79,5.0,5,59,Urban,Software Engineer,36154,0 +16351,Male,31,Bachelors,7,49,86,32,25,8.0,3,3,Urban,HR Executive,142592,0 +16352,Female,59,Diploma,1,0,76,41,17,4.0,2,34,Urban,HR Executive,120563,0 +16353,Male,33,Masters,10,27,49,2,52,3.0,2,25,Rural,ML Engineer,60655,0 +16354,Other,55,Bachelors,9,84,13,98,36,1.0,5,54,Urban,ML Engineer,89899,1 +16355,Male,41,Masters,13,53,31,18,80,1.0,6,64,Rural,Software Engineer,28085,0 +16356,Other,50,High School,9,35,6,32,64,5.0,5,22,Semi-Urban,Manager,63726,0 +16357,Male,41,Bachelors,1,83,39,5,89,8.0,4,91,Urban,ML Engineer,74115,0 +16358,Male,31,Bachelors,8,0,83,7,38,1.0,4,29,Urban,Manager,25100,0 +16359,Male,21,Masters,4,45,84,76,18,1.0,1,75,Urban,ML Engineer,62949,1 +16360,Female,30,Masters,3,71,45,65,93,7.0,0,93,Urban,Software Engineer,31587,1 +16361,Male,22,Masters,5,63,84,11,62,7.0,2,98,Semi-Urban,ML Engineer,25571,1 +16362,Male,52,Diploma,13,48,39,7,19,6.0,7,3,Urban,HR Executive,132906,0 +16363,Female,38,Bachelors,13,91,13,80,66,8.0,0,52,Semi-Urban,Software Engineer,83314,0 +16364,Male,37,Bachelors,5,27,49,39,57,4.0,6,65,Semi-Urban,Data Analyst,31221,0 +16365,Male,55,Masters,14,44,33,1,39,1.0,3,38,Urban,Manager,36179,0 +16366,Male,52,PhD,0,31,85,62,77,9.0,3,59,Semi-Urban,HR Executive,83768,1 +16367,Female,27,Bachelors,10,97,77,31,41,3.0,1,73,Urban,ML Engineer,104782,1 +16368,Male,56,Bachelors,17,89,89,34,28,2.0,6,99,Urban,Data Analyst,106569,1 +16369,Male,56,Bachelors,17,55,87,1,64,3.0,2,84,Urban,HR Executive,122462,0 +16370,Male,58,Masters,4,88,50,27,40,2.0,5,19,Urban,Data Analyst,117791,0 +16371,Male,27,Masters,12,88,4,14,74,6.0,1,4,Urban,ML Engineer,56343,0 +16372,Female,58,Masters,19,55,39,45,91,8.0,6,28,Semi-Urban,Manager,124272,0 +16373,Male,52,Diploma,6,99,66,30,84,6.0,2,41,Urban,ML Engineer,90888,1 +16374,Male,25,High School,4,21,9,83,66,1.0,0,69,Urban,ML Engineer,109360,0 +16375,Male,40,Bachelors,13,25,72,99,63,3.0,1,29,Semi-Urban,Manager,109462,0 +16376,Male,39,Bachelors,6,84,4,52,3,2.0,1,57,Rural,ML Engineer,147442,0 +16377,Male,46,Bachelors,4,78,88,26,49,7.0,1,76,Rural,Software Engineer,40917,1 +16378,Male,49,Masters,12,29,16,63,50,0.0,7,77,Semi-Urban,ML Engineer,126142,0 +16379,Male,44,Diploma,5,99,69,68,6,0.0,3,80,Rural,ML Engineer,73431,1 +16380,Female,26,Bachelors,14,91,71,40,71,9.0,5,78,Urban,Software Engineer,80552,1 +16381,Male,50,Masters,7,21,75,0,84,4.0,4,40,Semi-Urban,ML Engineer,118516,0 +16382,Male,48,Diploma,1,18,99,97,45,7.0,7,1,Urban,Data Analyst,148186,0 +16383,Male,31,Diploma,15,22,69,9,78,9.0,6,72,Urban,Manager,65177,0 +16384,Male,39,Masters,0,93,87,92,59,5.0,0,31,Semi-Urban,HR Executive,55607,1 +16385,Female,27,Bachelors,16,42,76,69,70,6.0,0,60,Rural,Manager,31031,1 +16386,Male,37,Bachelors,13,30,20,47,92,6.0,0,62,Urban,Data Analyst,133681,0 +16387,Male,32,Masters,7,80,54,66,54,7.0,3,9,Urban,ML Engineer,36151,0 +16388,Female,40,Bachelors,13,59,61,94,72,2.0,1,2,Urban,ML Engineer,149962,0 +16389,Male,27,Bachelors,3,98,68,60,3,1.0,7,81,Urban,Software Engineer,133000,1 +16390,Male,56,Bachelors,12,97,98,90,97,4.0,0,33,Semi-Urban,Software Engineer,100280,1 +16391,Male,27,Bachelors,1,77,45,27,37,1.0,5,5,Urban,Software Engineer,57738,0 +16392,Male,40,Bachelors,5,11,88,78,83,2.0,0,27,Rural,Software Engineer,107216,0 +16393,Female,48,Bachelors,15,65,36,69,33,5.0,0,65,Semi-Urban,Software Engineer,108702,0 +16394,Male,24,Bachelors,18,96,64,5,83,9.0,1,42,Urban,HR Executive,24248,0 +16395,Male,58,Bachelors,11,17,92,73,63,0.0,4,27,Urban,ML Engineer,141304,0 +16396,Male,54,Diploma,1,18,66,66,46,6.0,0,7,Urban,ML Engineer,65471,0 +16397,Male,29,High School,13,5,56,46,82,4.0,3,83,Urban,Software Engineer,142897,0 +16398,Other,56,High School,6,58,96,99,8,1.0,1,5,Semi-Urban,Data Analyst,87868,1 +16399,Male,52,Diploma,1,79,83,11,11,0.0,6,22,Semi-Urban,Data Analyst,123498,0 +16400,Other,53,Masters,4,91,58,24,24,4.0,7,19,Rural,HR Executive,63931,0 +16401,Male,56,Masters,19,75,7,79,69,1.0,3,34,Urban,ML Engineer,56663,0 +16402,Female,48,Diploma,12,82,79,16,14,8.0,7,27,Urban,ML Engineer,121343,0 +16403,Male,37,Masters,9,95,39,35,37,1.0,2,66,Semi-Urban,Software Engineer,108645,1 +16404,Male,36,Bachelors,1,38,67,48,37,8.0,3,94,Urban,Software Engineer,65021,1 +16405,Female,51,Bachelors,14,58,14,22,85,6.0,1,53,Urban,Manager,31591,0 +16406,Female,26,High School,10,65,91,98,78,9.0,2,49,Semi-Urban,Software Engineer,48726,1 +16407,Male,30,Bachelors,6,91,72,14,83,9.0,2,56,Urban,HR Executive,93188,0 +16408,Male,39,Bachelors,17,31,53,87,25,2.0,2,70,Semi-Urban,HR Executive,64097,1 +16409,Male,45,Masters,17,42,12,35,38,4.0,0,77,Rural,HR Executive,70164,0 +16410,Female,22,Bachelors,2,46,51,33,70,9.0,0,8,Urban,Software Engineer,106932,0 +16411,Male,42,Bachelors,13,23,96,77,10,6.0,1,61,Rural,Data Analyst,80805,1 +16412,Female,41,Diploma,14,12,94,67,88,9.0,0,9,Urban,ML Engineer,61244,0 +16413,Female,51,PhD,1,46,30,12,49,6.0,4,49,Urban,Manager,74616,0 +16414,Female,34,Diploma,19,72,65,84,78,3.0,0,85,Urban,Software Engineer,85056,1 +16415,Male,35,Bachelors,4,69,91,45,5,0.0,5,26,Urban,Manager,40209,0 +16416,Male,51,Masters,16,94,68,43,99,3.0,4,96,Urban,Manager,83239,1 +16417,Other,34,Masters,11,55,9,82,76,3.0,1,73,Rural,Manager,140590,0 +16418,Female,40,PhD,19,57,83,54,85,6.0,4,5,Urban,Data Analyst,81145,0 +16419,Female,42,PhD,6,34,47,12,23,1.0,1,68,Urban,Manager,23022,0 +16420,Male,21,Diploma,12,22,26,65,2,3.0,1,9,Urban,Data Analyst,58609,0 +16421,Female,52,Masters,15,51,53,43,33,0.0,6,45,Semi-Urban,Software Engineer,91417,0 +16422,Male,33,Bachelors,5,57,1,9,63,4.0,4,53,Urban,Software Engineer,88897,0 +16423,Male,42,Bachelors,10,38,33,98,45,5.0,6,16,Semi-Urban,HR Executive,97791,0 +16424,Female,22,PhD,4,17,70,51,41,2.0,7,50,Semi-Urban,HR Executive,116544,0 +16425,Male,49,Diploma,0,15,17,32,4,7.0,0,73,Semi-Urban,HR Executive,127398,0 +16426,Female,47,High School,5,99,7,30,5,8.0,7,56,Urban,HR Executive,71608,0 +16427,Male,29,High School,19,0,19,50,76,1.0,4,22,Urban,Software Engineer,129648,0 +16428,Male,42,High School,16,28,4,73,84,3.0,4,3,Rural,Data Analyst,103343,0 +16429,Male,38,High School,0,16,76,44,35,8.0,1,87,Urban,Manager,40440,0 +16430,Male,37,High School,16,51,45,30,32,9.0,6,16,Rural,Manager,43745,0 +16431,Male,44,Diploma,0,96,16,97,17,1.0,5,23,Urban,Data Analyst,133578,0 +16432,Female,40,Diploma,9,66,76,94,67,4.0,2,52,Urban,HR Executive,121791,1 +16433,Female,25,Bachelors,7,91,19,76,87,8.0,6,59,Semi-Urban,ML Engineer,56746,1 +16434,Male,22,Masters,12,72,69,1,39,1.0,5,36,Rural,ML Engineer,122479,0 +16435,Male,34,Bachelors,0,44,20,55,4,9.0,0,56,Urban,Data Analyst,44502,0 +16436,Female,31,Diploma,1,70,11,79,64,4.0,0,21,Urban,Software Engineer,132847,0 +16437,Female,34,Bachelors,19,18,67,95,93,9.0,4,43,Urban,Software Engineer,101161,0 +16438,Female,22,Masters,19,56,36,69,52,2.0,5,69,Urban,Manager,26293,0 +16439,Female,42,Diploma,1,70,57,27,63,5.0,0,44,Rural,ML Engineer,38593,0 +16440,Male,42,Masters,6,31,59,12,98,0.0,0,31,Semi-Urban,ML Engineer,141267,0 +16441,Male,45,Masters,5,94,71,30,98,3.0,0,83,Rural,ML Engineer,119043,1 +16442,Male,30,Bachelors,4,80,52,50,62,4.0,7,35,Semi-Urban,ML Engineer,142694,0 +16443,Male,52,Masters,9,34,27,28,67,4.0,6,46,Semi-Urban,Data Analyst,31518,0 +16444,Female,25,High School,17,31,37,74,58,9.0,0,1,Semi-Urban,ML Engineer,24207,0 +16445,Male,35,Bachelors,6,77,70,79,66,3.0,1,38,Urban,HR Executive,36923,1 +16446,Female,59,Bachelors,16,28,32,15,10,5.0,5,41,Rural,Manager,141845,0 +16447,Female,27,Bachelors,2,40,7,63,58,5.0,6,15,Rural,HR Executive,124464,0 +16448,Female,35,Bachelors,7,61,7,34,1,8.0,3,64,Urban,Data Analyst,83559,0 +16449,Female,55,Bachelors,4,64,75,73,43,1.0,7,24,Rural,ML Engineer,137753,0 +16450,Male,22,Diploma,15,96,32,8,10,9.0,5,87,Semi-Urban,ML Engineer,122693,0 +16451,Female,33,High School,6,72,97,66,71,0.0,0,84,Rural,Manager,43704,1 +16452,Male,31,Masters,3,58,57,64,3,0.0,5,91,Urban,Manager,148441,1 +16453,Male,33,Bachelors,0,74,95,26,34,2.0,6,83,Rural,ML Engineer,119775,1 +16454,Female,47,PhD,4,20,17,5,6,6.0,1,18,Semi-Urban,Data Analyst,119732,0 +16455,Male,25,Diploma,0,59,12,86,77,4.0,5,11,Urban,Software Engineer,68220,0 +16456,Other,25,Bachelors,11,62,38,97,29,7.0,7,38,Rural,HR Executive,99809,0 +16457,Female,38,Bachelors,5,2,62,39,19,9.0,3,16,Semi-Urban,HR Executive,54978,0 +16458,Female,36,Diploma,18,66,43,28,61,9.0,2,25,Semi-Urban,Manager,103517,0 +16459,Male,33,Masters,14,39,22,28,37,5.0,1,51,Urban,Manager,140254,0 +16460,Female,46,Bachelors,0,99,82,94,17,0.0,5,47,Urban,Manager,139663,1 +16461,Male,38,Bachelors,14,90,92,82,27,6.0,2,5,Urban,Software Engineer,64102,1 +16462,Female,50,Diploma,10,28,68,64,65,6.0,3,27,Urban,ML Engineer,23371,0 +16463,Male,46,High School,19,90,87,93,7,3.0,7,39,Urban,Data Analyst,125402,1 +16464,Female,42,Diploma,6,56,26,55,92,8.0,4,6,Rural,Manager,59668,0 +16465,Male,26,Bachelors,12,93,65,64,50,6.0,3,75,Rural,HR Executive,51163,1 +16466,Male,45,Masters,18,99,51,54,47,6.0,3,52,Rural,Data Analyst,57089,1 +16467,Male,28,Diploma,19,31,46,90,65,6.0,2,94,Urban,Software Engineer,129214,1 +16468,Male,59,Bachelors,5,86,21,4,71,3.0,1,14,Semi-Urban,ML Engineer,52045,0 +16469,Female,41,Diploma,5,5,25,58,75,3.0,7,43,Rural,ML Engineer,98278,0 +16470,Male,23,Diploma,8,21,21,35,4,9.0,7,86,Urban,Data Analyst,132064,0 +16471,Male,55,Bachelors,1,70,13,16,25,2.0,7,7,Urban,HR Executive,115542,0 +16472,Male,56,PhD,15,80,56,22,7,4.0,7,52,Rural,Data Analyst,28313,0 +16473,Male,55,Bachelors,14,24,45,90,60,9.0,6,34,Semi-Urban,ML Engineer,83236,0 +16474,Male,22,Bachelors,8,39,58,42,13,0.0,1,12,Urban,HR Executive,126115,0 +16475,Female,26,Masters,6,29,46,85,59,9.0,5,4,Semi-Urban,Manager,40944,0 +16476,Male,48,Bachelors,11,4,11,60,24,9.0,0,8,Urban,ML Engineer,144310,0 +16477,Male,53,High School,18,34,91,97,18,0.0,3,42,Urban,Data Analyst,93015,1 +16478,Male,56,Bachelors,14,42,75,24,77,0.0,2,32,Urban,Data Analyst,66144,0 +16479,Male,56,Bachelors,1,56,82,51,73,7.0,7,90,Urban,Manager,118349,1 +16480,Male,29,Bachelors,16,18,22,56,36,8.0,6,21,Semi-Urban,Software Engineer,135670,0 +16481,Male,51,High School,12,31,57,44,58,3.0,6,36,Semi-Urban,Manager,132991,0 +16482,Female,58,High School,4,1,69,76,84,1.0,1,11,Rural,HR Executive,65216,0 +16483,Male,57,Bachelors,7,91,98,8,52,1.0,2,6,Urban,HR Executive,145053,0 +16484,Male,21,Masters,7,81,75,92,46,0.0,5,3,Semi-Urban,Data Analyst,130145,1 +16485,Male,40,PhD,19,98,10,74,91,9.0,1,2,Semi-Urban,Manager,129506,0 +16486,Female,56,Bachelors,2,15,59,0,67,8.0,2,99,Urban,ML Engineer,82491,0 +16487,Other,54,High School,5,87,6,14,90,9.0,5,54,Urban,HR Executive,125130,0 +16488,Male,28,Diploma,12,74,65,51,78,0.0,3,70,Rural,ML Engineer,105772,1 +16489,Other,34,High School,2,59,54,60,35,1.0,3,41,Urban,Software Engineer,39215,0 +16490,Male,24,Masters,14,47,77,33,90,4.0,2,2,Urban,Data Analyst,133270,0 +16491,Male,58,Diploma,16,97,18,11,91,0.0,3,20,Semi-Urban,Data Analyst,22388,0 +16492,Male,34,Masters,3,32,69,81,18,2.0,0,38,Rural,Manager,86048,0 +16493,Male,37,Diploma,9,5,62,74,61,9.0,5,0,Urban,Manager,81280,0 +16494,Male,45,High School,17,55,19,37,29,3.0,5,56,Urban,Data Analyst,132656,0 +16495,Male,39,Bachelors,16,68,49,41,86,9.0,0,28,Urban,ML Engineer,115834,0 +16496,Male,26,Bachelors,19,28,91,62,81,0.0,3,32,Urban,HR Executive,122769,0 +16497,Male,35,High School,17,24,65,21,5,0.0,1,37,Rural,Manager,34824,0 +16498,Male,29,Bachelors,9,28,57,53,19,6.0,7,89,Semi-Urban,Software Engineer,113496,0 +16499,Male,34,Bachelors,5,42,29,42,54,1.0,6,63,Urban,ML Engineer,130207,0 +16500,Female,32,High School,16,1,2,64,90,1.0,1,25,Urban,Manager,30469,0 +16501,Male,25,Bachelors,1,19,93,14,48,8.0,1,15,Rural,Manager,31023,0 +16502,Female,52,Bachelors,12,11,0,60,69,2.0,4,69,Urban,Manager,81839,0 +16503,Female,22,Masters,12,31,82,86,2,6.0,4,11,Semi-Urban,Manager,78156,0 +16504,Male,44,Masters,0,22,5,74,84,7.0,4,15,Urban,Data Analyst,28550,0 +16505,Male,48,Masters,18,23,67,22,20,6.0,1,7,Semi-Urban,Software Engineer,132955,0 +16506,Male,41,Bachelors,6,72,98,35,74,6.0,3,91,Urban,Data Analyst,78028,1 +16507,Male,25,Masters,9,42,69,62,44,0.0,4,24,Urban,HR Executive,54043,0 +16508,Male,51,Masters,13,57,32,94,62,3.0,6,29,Semi-Urban,Software Engineer,35436,0 +16509,Male,54,Bachelors,9,87,98,79,1,0.0,6,92,Rural,Software Engineer,124689,1 +16510,Male,29,Bachelors,9,3,83,7,65,8.0,1,31,Rural,Data Analyst,132718,0 +16511,Female,51,Bachelors,10,11,17,23,54,8.0,4,15,Urban,ML Engineer,75961,0 +16512,Male,55,High School,12,2,85,59,45,4.0,7,74,Semi-Urban,ML Engineer,32579,0 +16513,Female,37,Bachelors,3,55,14,94,95,9.0,3,85,Urban,HR Executive,27977,1 +16514,Male,31,Masters,3,82,23,36,20,7.0,5,98,Urban,Data Analyst,104308,1 +16515,Female,31,Diploma,2,61,79,92,75,4.0,1,64,Rural,HR Executive,50533,1 +16516,Male,53,Bachelors,6,70,40,23,36,8.0,2,70,Urban,Software Engineer,120279,0 +16517,Male,35,Bachelors,0,16,61,39,37,4.0,5,35,Urban,ML Engineer,138771,0 +16518,Female,25,High School,7,35,83,96,46,6.0,5,60,Rural,HR Executive,129156,1 +16519,Female,31,High School,9,96,11,55,37,3.0,1,38,Semi-Urban,Data Analyst,51124,0 +16520,Male,39,Masters,8,95,85,80,51,9.0,7,8,Urban,HR Executive,22414,1 +16521,Male,51,Diploma,6,5,87,81,88,4.0,3,61,Urban,Software Engineer,84918,0 +16522,Female,50,Bachelors,2,32,93,24,19,7.0,5,14,Semi-Urban,ML Engineer,148495,0 +16523,Female,39,Diploma,17,87,37,40,64,7.0,7,71,Urban,HR Executive,128424,0 +16524,Male,36,Diploma,17,69,62,58,38,4.0,6,28,Urban,Software Engineer,76068,0 +16525,Male,41,High School,10,70,59,53,19,2.0,0,29,Urban,Manager,56513,0 +16526,Female,25,Diploma,11,92,87,97,93,3.0,6,38,Semi-Urban,Manager,137992,1 +16527,Male,47,Diploma,12,0,13,25,48,1.0,0,3,Semi-Urban,Data Analyst,92867,0 +16528,Female,51,PhD,9,78,92,83,11,6.0,0,62,Urban,Software Engineer,68503,1 +16529,Male,46,Diploma,8,48,59,43,22,4.0,3,15,Semi-Urban,Software Engineer,73174,0 +16530,Other,28,Bachelors,1,89,29,84,81,2.0,2,39,Urban,Data Analyst,29830,1 +16531,Female,27,High School,9,63,5,11,31,2.0,7,22,Urban,ML Engineer,81112,0 +16532,Female,38,Bachelors,18,83,30,24,68,9.0,6,37,Semi-Urban,ML Engineer,47574,0 +16533,Male,57,Bachelors,19,21,79,38,12,6.0,0,63,Semi-Urban,HR Executive,36051,0 +16534,Male,43,Masters,9,83,21,48,62,2.0,6,40,Urban,Manager,28532,0 +16535,Male,53,Bachelors,5,44,3,73,79,3.0,6,87,Semi-Urban,Manager,63945,0 +16536,Female,44,PhD,12,26,0,43,36,1.0,0,99,Urban,Manager,139461,0 +16537,Female,53,Bachelors,2,75,81,79,98,9.0,1,93,Urban,Manager,109191,1 +16538,Male,53,Masters,9,82,96,66,92,9.0,2,81,Urban,Manager,78357,1 +16539,Female,48,Bachelors,12,94,17,53,82,9.0,0,56,Semi-Urban,Data Analyst,81019,0 +16540,Female,22,Masters,5,17,93,34,2,5.0,5,13,Semi-Urban,HR Executive,86015,0 +16541,Male,53,PhD,2,84,19,90,77,8.0,1,20,Semi-Urban,HR Executive,133867,0 +16542,Male,56,Bachelors,16,16,95,44,85,1.0,7,25,Rural,ML Engineer,79205,0 +16543,Female,58,Bachelors,17,0,66,29,30,7.0,7,17,Rural,Manager,121496,0 +16544,Male,38,Masters,18,51,41,0,46,0.0,0,27,Urban,ML Engineer,102702,0 +16545,Female,29,High School,1,19,14,17,12,4.0,4,27,Urban,Data Analyst,30673,0 +16546,Male,45,Diploma,18,75,99,75,14,2.0,2,90,Urban,Software Engineer,32665,1 +16547,Other,54,Diploma,9,32,7,86,0,6.0,2,93,Semi-Urban,Data Analyst,44556,0 +16548,Male,48,Masters,18,19,59,39,30,2.0,6,0,Rural,Software Engineer,99210,0 +16549,Male,56,Diploma,19,23,91,84,6,5.0,0,4,Semi-Urban,HR Executive,119354,0 +16550,Male,34,Masters,10,17,41,79,60,2.0,4,91,Urban,Manager,84659,0 +16551,Male,56,Bachelors,19,68,82,96,47,6.0,1,86,Semi-Urban,Data Analyst,69932,1 +16552,Male,30,Diploma,15,99,54,94,69,9.0,2,64,Urban,HR Executive,44165,1 +16553,Male,29,Bachelors,12,0,75,91,94,3.0,3,52,Urban,HR Executive,51389,0 +16554,Other,23,Bachelors,18,14,28,48,16,8.0,0,84,Urban,Software Engineer,23804,0 +16555,Female,23,High School,4,30,61,40,35,6.0,4,80,Urban,HR Executive,74294,0 +16556,Male,30,Bachelors,10,35,70,9,20,1.0,5,78,Urban,Data Analyst,43274,0 +16557,Female,45,Masters,7,66,1,56,47,2.0,4,5,Urban,HR Executive,31801,0 +16558,Male,43,Bachelors,16,64,73,62,6,1.0,7,82,Urban,Data Analyst,143871,1 +16559,Female,31,Bachelors,2,17,41,0,58,3.0,2,89,Urban,HR Executive,66489,0 +16560,Female,42,Diploma,0,97,79,55,52,9.0,7,6,Semi-Urban,Manager,110940,0 +16561,Male,47,Bachelors,4,20,70,82,75,0.0,5,18,Rural,Software Engineer,28162,0 +16562,Female,23,Diploma,7,86,25,6,24,4.0,1,27,Urban,Manager,145215,0 +16563,Female,33,Bachelors,8,70,75,8,41,4.0,6,72,Urban,Manager,87839,0 +16564,Male,50,Bachelors,11,24,92,97,28,1.0,2,18,Semi-Urban,HR Executive,36077,0 +16565,Female,54,Diploma,9,18,35,67,52,8.0,2,21,Urban,Software Engineer,108488,0 +16566,Female,50,Bachelors,15,0,91,70,47,4.0,5,21,Semi-Urban,HR Executive,23272,0 +16567,Male,44,High School,16,93,74,62,66,6.0,1,99,Rural,Manager,34701,1 +16568,Female,21,PhD,18,77,53,89,60,9.0,5,42,Urban,Data Analyst,31248,1 +16569,Other,56,Bachelors,1,11,38,93,97,9.0,4,79,Urban,Manager,125167,0 +16570,Male,32,Bachelors,10,7,78,88,89,1.0,4,56,Semi-Urban,ML Engineer,29392,0 +16571,Male,40,Bachelors,9,85,29,23,29,9.0,4,99,Semi-Urban,HR Executive,115468,1 +16572,Male,22,High School,1,9,58,41,49,8.0,0,72,Rural,ML Engineer,131805,0 +16573,Female,45,Diploma,7,65,60,49,63,6.0,2,82,Urban,ML Engineer,149721,1 +16574,Female,52,Bachelors,15,96,71,77,66,4.0,3,68,Urban,Data Analyst,49340,1 +16575,Male,53,PhD,17,81,89,93,10,4.0,2,18,Rural,Data Analyst,62653,1 +16576,Other,51,Diploma,5,94,2,33,42,8.0,6,44,Semi-Urban,Software Engineer,123182,0 +16577,Female,56,Bachelors,3,65,20,5,77,6.0,2,79,Urban,HR Executive,142619,0 +16578,Female,40,Bachelors,9,40,2,11,1,9.0,1,73,Rural,HR Executive,45017,0 +16579,Male,44,High School,12,62,57,6,86,2.0,5,24,Urban,ML Engineer,132615,0 +16580,Male,49,Diploma,0,23,81,73,57,8.0,2,41,Urban,Data Analyst,59055,0 +16581,Female,23,Masters,3,95,88,6,89,0.0,3,91,Urban,HR Executive,35973,1 +16582,Male,24,High School,7,52,55,30,28,4.0,0,16,Rural,HR Executive,71291,0 +16583,Female,24,Bachelors,15,30,94,49,4,6.0,4,86,Urban,Data Analyst,70625,1 +16584,Female,33,PhD,13,55,49,29,28,9.0,4,38,Semi-Urban,Manager,133408,0 +16585,Male,35,High School,0,85,36,97,46,8.0,6,79,Semi-Urban,Data Analyst,77283,1 +16586,Female,27,Bachelors,12,98,37,1,19,8.0,4,76,Semi-Urban,ML Engineer,148048,0 +16587,Male,56,Bachelors,1,0,51,56,81,5.0,4,45,Rural,HR Executive,105336,0 +16588,Male,31,Bachelors,6,45,57,62,18,0.0,3,89,Semi-Urban,HR Executive,107629,1 +16589,Male,41,PhD,9,86,70,51,52,2.0,7,68,Semi-Urban,HR Executive,88064,1 +16590,Male,59,Masters,6,84,38,91,75,7.0,3,43,Semi-Urban,HR Executive,47225,1 +16591,Male,32,Bachelors,4,96,65,18,89,5.0,0,11,Urban,HR Executive,23673,0 +16592,Female,37,Bachelors,9,92,38,2,71,5.0,5,49,Semi-Urban,ML Engineer,61593,0 +16593,Female,42,Masters,11,7,48,71,83,3.0,0,3,Rural,ML Engineer,51434,0 +16594,Male,38,High School,16,13,29,61,78,4.0,5,7,Urban,Software Engineer,59750,0 +16595,Female,24,Bachelors,8,27,29,26,94,7.0,7,96,Urban,ML Engineer,115977,0 +16596,Male,26,PhD,13,91,98,57,28,2.0,0,49,Urban,Manager,107542,1 +16597,Male,36,Bachelors,15,35,91,98,41,8.0,0,82,Semi-Urban,ML Engineer,120261,1 +16598,Female,59,Diploma,15,74,20,52,48,9.0,3,40,Urban,Data Analyst,87293,0 +16599,Female,29,Masters,17,16,84,39,57,7.0,1,63,Semi-Urban,Software Engineer,140274,0 +16600,Female,34,Masters,18,37,14,5,79,8.0,7,44,Semi-Urban,ML Engineer,99008,0 +16601,Male,59,Bachelors,0,61,26,30,46,1.0,3,19,Urban,Data Analyst,71679,0 +16602,Female,52,Bachelors,13,80,73,40,37,7.0,1,86,Semi-Urban,HR Executive,39571,1 +16603,Female,32,Masters,0,98,7,85,3,7.0,3,30,Urban,HR Executive,121556,0 +16604,Other,27,Bachelors,11,37,44,40,12,2.0,5,39,Semi-Urban,HR Executive,64920,0 +16605,Male,26,Bachelors,0,35,11,29,94,9.0,6,45,Rural,ML Engineer,139982,0 +16606,Male,46,Bachelors,14,41,22,36,92,8.0,1,26,Semi-Urban,ML Engineer,81549,0 +16607,Female,48,Diploma,2,99,67,18,10,8.0,4,16,Semi-Urban,Software Engineer,56769,0 +16608,Other,29,Diploma,19,62,13,39,16,0.0,5,17,Rural,Manager,130739,0 +16609,Male,42,Masters,19,80,35,32,96,3.0,5,89,Urban,HR Executive,80611,1 +16610,Male,23,Bachelors,15,29,10,33,18,2.0,5,31,Semi-Urban,ML Engineer,22742,0 +16611,Male,43,Diploma,3,1,18,65,35,7.0,2,86,Urban,Data Analyst,40169,0 +16612,Male,38,Masters,2,56,94,41,61,0.0,4,64,Rural,Manager,111233,1 +16613,Male,25,Diploma,15,47,67,18,72,9.0,3,15,Urban,Data Analyst,112217,0 +16614,Male,58,PhD,10,85,34,11,71,4.0,1,17,Urban,Software Engineer,101324,0 +16615,Male,42,Bachelors,11,44,6,21,11,4.0,3,67,Semi-Urban,Software Engineer,28974,0 +16616,Male,54,Bachelors,9,96,22,35,28,5.0,5,57,Urban,ML Engineer,53535,0 +16617,Male,34,Bachelors,10,35,27,76,62,3.0,5,5,Rural,ML Engineer,128682,0 +16618,Male,48,Diploma,15,66,96,70,68,9.0,1,70,Urban,Manager,135551,1 +16619,Male,46,Masters,4,94,24,45,5,7.0,7,18,Semi-Urban,ML Engineer,82109,0 +16620,Other,22,Diploma,9,10,41,87,77,3.0,4,69,Urban,HR Executive,101539,0 +16621,Male,52,Bachelors,17,88,54,90,63,6.0,4,81,Semi-Urban,ML Engineer,90087,1 +16622,Female,35,Diploma,17,24,91,40,68,1.0,0,57,Urban,ML Engineer,76732,0 +16623,Male,34,Bachelors,19,69,19,18,97,0.0,1,75,Rural,Data Analyst,89018,0 +16624,Female,34,Masters,18,57,67,55,1,2.0,5,73,Semi-Urban,Data Analyst,92687,1 +16625,Male,41,Bachelors,0,16,9,37,83,0.0,3,29,Urban,Software Engineer,21397,0 +16626,Male,53,Bachelors,7,47,22,31,7,7.0,7,19,Urban,Data Analyst,113124,0 +16627,Male,56,Bachelors,19,47,8,0,46,3.0,5,53,Rural,Data Analyst,105885,0 +16628,Female,58,Diploma,14,24,87,53,82,8.0,7,65,Urban,ML Engineer,98020,0 +16629,Male,55,Diploma,2,70,75,97,0,5.0,0,51,Semi-Urban,Software Engineer,81333,1 +16630,Male,56,Bachelors,2,50,92,94,75,6.0,0,96,Urban,Data Analyst,51392,1 +16631,Male,49,High School,11,57,90,94,69,4.0,1,26,Rural,Software Engineer,49082,1 +16632,Female,21,Bachelors,12,86,61,97,60,4.0,4,91,Urban,Software Engineer,106754,1 +16633,Male,43,Masters,18,50,87,23,9,2.0,7,43,Rural,Data Analyst,103261,0 +16634,Male,52,Masters,16,14,61,40,59,5.0,4,99,Urban,Data Analyst,149777,0 +16635,Male,25,Masters,0,86,43,79,77,2.0,5,24,Urban,ML Engineer,141241,0 +16636,Male,45,Diploma,3,58,5,41,57,9.0,1,55,Rural,HR Executive,37768,0 +16637,Female,42,Bachelors,8,95,88,91,62,1.0,1,86,Semi-Urban,Software Engineer,52051,1 +16638,Male,59,High School,11,55,11,15,27,2.0,3,72,Rural,Data Analyst,135072,0 +16639,Male,21,Masters,15,84,10,32,72,3.0,1,25,Urban,Data Analyst,135760,0 +16640,Female,43,Bachelors,18,14,20,8,48,6.0,5,0,Urban,Software Engineer,21339,0 +16641,Female,39,Masters,13,16,60,60,35,2.0,6,93,Semi-Urban,ML Engineer,68200,0 +16642,Male,28,PhD,7,8,52,57,56,3.0,7,98,Urban,Data Analyst,22478,0 +16643,Female,30,High School,6,80,52,74,26,9.0,0,23,Urban,Software Engineer,51800,0 +16644,Male,58,Bachelors,3,37,36,17,44,5.0,0,17,Urban,Software Engineer,81637,0 +16645,Male,33,Bachelors,7,36,55,71,86,8.0,1,27,Urban,ML Engineer,117516,0 +16646,Other,57,PhD,13,46,6,20,44,9.0,0,93,Semi-Urban,Data Analyst,123875,0 +16647,Female,32,Bachelors,9,20,57,14,5,0.0,5,24,Semi-Urban,ML Engineer,66138,0 +16648,Male,48,Bachelors,1,8,93,61,18,8.0,6,32,Urban,ML Engineer,98851,0 +16649,Male,39,Bachelors,16,81,50,35,5,8.0,5,55,Urban,Software Engineer,114581,0 +16650,Male,21,Diploma,5,67,17,32,41,3.0,1,41,Urban,Data Analyst,77904,0 +16651,Male,57,Masters,13,80,19,68,61,1.0,7,33,Urban,HR Executive,93407,0 +16652,Male,40,Bachelors,2,79,41,96,55,9.0,2,99,Rural,Software Engineer,134082,1 +16653,Male,50,Bachelors,1,67,62,35,59,9.0,7,36,Urban,Manager,116522,0 +16654,Female,28,Bachelors,18,75,18,93,26,7.0,3,7,Urban,ML Engineer,96235,0 +16655,Female,59,PhD,16,60,96,88,66,8.0,6,78,Urban,Data Analyst,52224,1 +16656,Male,59,Masters,14,14,62,52,11,7.0,7,21,Urban,Manager,78206,0 +16657,Male,46,Bachelors,18,17,66,74,20,1.0,0,28,Urban,Software Engineer,101435,0 +16658,Male,56,Bachelors,19,63,57,58,83,7.0,0,78,Urban,ML Engineer,52177,1 +16659,Male,28,High School,14,30,75,62,97,4.0,2,88,Semi-Urban,Data Analyst,88434,1 +16660,Male,47,Bachelors,9,76,16,73,87,0.0,0,9,Urban,Manager,87702,0 +16661,Female,48,High School,16,43,62,19,72,8.0,0,54,Urban,Manager,29291,0 +16662,Male,43,Bachelors,13,57,46,48,52,1.0,0,38,Urban,Software Engineer,139711,0 +16663,Female,45,Bachelors,7,74,15,33,66,4.0,7,15,Semi-Urban,Data Analyst,113101,0 +16664,Female,29,Masters,1,93,6,33,55,4.0,3,92,Semi-Urban,Data Analyst,53234,0 +16665,Male,38,Diploma,5,60,30,30,13,5.0,1,79,Urban,ML Engineer,115618,0 +16666,Male,26,Bachelors,14,55,0,17,98,0.0,1,18,Urban,Data Analyst,143105,0 +16667,Female,23,Masters,12,95,26,14,56,2.0,3,86,Rural,ML Engineer,71547,0 +16668,Female,47,Diploma,4,28,4,2,25,3.0,2,11,Semi-Urban,Software Engineer,83456,0 +16669,Female,51,Diploma,17,95,35,95,61,4.0,4,16,Rural,Manager,42312,1 +16670,Male,47,Bachelors,1,50,13,15,67,7.0,7,70,Urban,Software Engineer,44029,0 +16671,Male,45,Bachelors,11,49,14,33,15,0.0,4,90,Semi-Urban,HR Executive,62448,0 +16672,Male,35,Bachelors,15,65,17,26,66,7.0,4,21,Rural,Software Engineer,114882,0 +16673,Other,29,Bachelors,5,58,58,41,24,2.0,7,50,Urban,HR Executive,122838,0 +16674,Female,38,Masters,16,35,6,83,21,8.0,1,42,Rural,Data Analyst,126616,0 +16675,Female,21,Diploma,15,29,24,35,43,8.0,7,88,Urban,Software Engineer,113000,0 +16676,Male,32,Masters,11,79,92,87,45,8.0,5,59,Urban,HR Executive,78611,1 +16677,Female,47,Bachelors,14,82,65,99,57,1.0,3,30,Urban,Software Engineer,97895,1 +16678,Male,27,Bachelors,18,86,55,78,39,5.0,6,54,Urban,Manager,111622,1 +16679,Male,38,Masters,9,36,82,68,63,2.0,6,41,Urban,Manager,65494,0 +16680,Male,54,High School,16,30,55,85,27,2.0,0,66,Urban,Manager,96877,1 +16681,Female,37,Bachelors,8,28,64,87,72,5.0,6,68,Rural,Data Analyst,82920,1 +16682,Female,56,PhD,2,14,48,91,4,1.0,4,64,Semi-Urban,Data Analyst,53654,0 +16683,Male,57,Diploma,18,65,95,24,19,9.0,3,60,Urban,Manager,70769,1 +16684,Female,22,Diploma,6,74,7,79,95,9.0,4,71,Semi-Urban,Manager,122585,0 +16685,Male,58,Masters,13,83,57,49,31,1.0,5,19,Semi-Urban,Data Analyst,132641,0 +16686,Male,33,Masters,18,96,1,68,35,2.0,2,11,Rural,ML Engineer,49352,0 +16687,Male,55,High School,6,82,69,90,87,6.0,5,30,Urban,HR Executive,66678,1 +16688,Male,31,Masters,2,11,28,72,85,9.0,5,59,Urban,Data Analyst,44348,0 +16689,Male,53,Bachelors,3,31,58,26,23,5.0,6,44,Urban,Data Analyst,27641,0 +16690,Male,47,High School,0,18,84,35,37,1.0,0,46,Semi-Urban,Manager,90413,0 +16691,Female,25,Bachelors,14,76,55,31,66,2.0,2,5,Urban,Data Analyst,111767,0 +16692,Male,59,Bachelors,18,93,64,55,31,6.0,3,31,Rural,HR Executive,110739,1 +16693,Female,35,Diploma,4,25,2,7,21,9.0,5,71,Semi-Urban,ML Engineer,55649,0 +16694,Male,57,Masters,7,73,17,30,96,1.0,3,84,Semi-Urban,Manager,117864,0 +16695,Female,26,Bachelors,16,90,80,3,29,3.0,1,95,Urban,Data Analyst,45646,1 +16696,Female,52,Bachelors,17,41,89,75,53,4.0,1,75,Urban,HR Executive,51899,1 +16697,Female,47,Bachelors,17,23,84,45,31,0.0,1,55,Urban,Software Engineer,68802,0 +16698,Male,22,High School,16,51,20,15,41,4.0,0,36,Urban,Manager,127373,0 +16699,Female,59,PhD,11,23,46,77,41,8.0,0,46,Semi-Urban,Software Engineer,33374,0 +16700,Male,42,Bachelors,6,1,59,28,12,0.0,3,32,Urban,Data Analyst,76544,0 +16701,Female,42,Bachelors,2,7,46,52,38,6.0,4,13,Urban,ML Engineer,20409,0 +16702,Male,39,Masters,3,6,32,59,55,2.0,0,47,Urban,Data Analyst,45138,0 +16703,Male,26,Masters,16,58,34,88,38,9.0,3,27,Semi-Urban,ML Engineer,44367,0 +16704,Male,41,Bachelors,7,40,91,23,39,3.0,4,75,Urban,HR Executive,46463,0 +16705,Female,51,High School,0,28,27,89,2,5.0,2,11,Urban,Data Analyst,54098,0 +16706,Male,27,Bachelors,11,58,48,82,90,7.0,5,78,Semi-Urban,HR Executive,48726,1 +16707,Female,48,Bachelors,16,21,86,1,45,3.0,4,31,Urban,Software Engineer,99214,0 +16708,Other,24,Bachelors,8,40,48,32,9,0.0,7,47,Rural,Software Engineer,87510,0 +16709,Female,21,Masters,9,51,28,64,60,4.0,4,67,Urban,ML Engineer,87743,0 +16710,Male,29,Diploma,7,57,6,96,90,7.0,1,78,Urban,Data Analyst,134379,1 +16711,Female,27,Bachelors,1,0,16,87,57,1.0,2,91,Rural,ML Engineer,40972,0 +16712,Male,26,Diploma,19,43,77,88,75,8.0,4,80,Urban,ML Engineer,25699,1 +16713,Male,24,PhD,2,56,52,63,11,6.0,3,83,Urban,Data Analyst,39970,1 +16714,Female,50,Diploma,16,54,58,43,45,4.0,3,13,Semi-Urban,Data Analyst,20170,0 +16715,Other,52,Masters,5,71,8,43,48,4.0,0,59,Urban,Manager,107452,0 +16716,Female,43,High School,14,49,9,25,19,9.0,1,91,Semi-Urban,Data Analyst,40233,0 +16717,Male,33,High School,8,60,66,49,66,5.0,7,96,Urban,ML Engineer,149617,1 +16718,Male,51,Masters,10,78,45,83,40,7.0,6,40,Urban,HR Executive,132553,1 +16719,Male,42,Bachelors,12,72,57,46,67,1.0,3,34,Rural,Data Analyst,114662,0 +16720,Male,21,High School,18,97,56,59,24,0.0,4,86,Urban,HR Executive,96990,1 +16721,Male,35,Masters,0,27,10,86,35,0.0,3,69,Urban,HR Executive,76961,0 +16722,Male,34,Diploma,13,5,13,54,70,4.0,4,42,Urban,Software Engineer,137027,0 +16723,Female,36,Diploma,14,49,96,29,26,0.0,0,44,Urban,Software Engineer,96951,0 +16724,Female,46,Masters,2,60,88,46,83,2.0,2,55,Urban,Software Engineer,42082,1 +16725,Female,45,High School,8,76,12,35,45,8.0,2,90,Rural,Data Analyst,102939,0 +16726,Female,35,Bachelors,3,65,75,62,70,9.0,0,41,Urban,Data Analyst,56271,1 +16727,Male,59,Masters,16,55,77,91,3,8.0,3,83,Urban,Data Analyst,71266,1 +16728,Male,32,High School,15,16,45,46,8,0.0,4,18,Urban,Manager,138541,0 +16729,Female,28,Masters,0,52,95,27,9,9.0,7,32,Rural,Manager,76489,0 +16730,Male,47,Bachelors,4,40,56,10,47,6.0,6,29,Urban,Data Analyst,59530,0 +16731,Male,49,Bachelors,1,77,77,97,84,8.0,0,3,Semi-Urban,ML Engineer,57437,1 +16732,Male,43,Bachelors,18,6,13,95,3,2.0,3,1,Urban,HR Executive,63430,0 +16733,Male,42,Diploma,8,76,3,13,4,8.0,2,27,Urban,ML Engineer,51688,0 +16734,Female,28,Bachelors,12,61,65,85,3,1.0,1,80,Urban,HR Executive,77341,1 +16735,Female,33,PhD,18,54,2,30,79,7.0,3,64,Semi-Urban,HR Executive,34588,0 +16736,Female,45,Diploma,17,10,36,7,21,8.0,6,7,Urban,Data Analyst,53356,0 +16737,Male,53,High School,19,10,45,62,34,4.0,5,4,Urban,Software Engineer,125148,0 +16738,Male,25,High School,13,42,16,77,60,1.0,2,29,Semi-Urban,HR Executive,84188,0 +16739,Female,45,Masters,9,39,85,26,27,6.0,7,57,Urban,Software Engineer,51163,0 +16740,Male,25,Bachelors,15,51,37,9,75,2.0,7,10,Urban,ML Engineer,47826,0 +16741,Male,52,Bachelors,1,12,67,18,62,5.0,3,83,Rural,Software Engineer,102613,0 +16742,Female,34,Diploma,18,56,7,61,29,3.0,4,41,Semi-Urban,Software Engineer,86440,0 +16743,Female,47,Bachelors,0,83,47,34,20,5.0,0,92,Urban,Software Engineer,142794,1 +16744,Female,51,High School,3,62,15,78,3,5.0,3,1,Urban,Software Engineer,134929,0 +16745,Male,55,Bachelors,0,31,56,59,5,6.0,0,41,Semi-Urban,Software Engineer,39224,0 +16746,Male,29,Masters,17,3,88,69,17,0.0,3,58,Rural,ML Engineer,106972,0 +16747,Female,50,PhD,5,86,69,74,29,0.0,3,19,Urban,Manager,80713,1 +16748,Male,57,Bachelors,1,56,8,45,68,2.0,1,52,Urban,ML Engineer,100134,0 +16749,Female,57,Masters,8,98,44,99,59,9.0,3,76,Semi-Urban,Manager,23094,1 +16750,Male,21,Diploma,4,98,57,71,50,4.0,0,81,Urban,HR Executive,40046,1 +16751,Female,35,Bachelors,14,99,77,88,27,0.0,3,95,Semi-Urban,Data Analyst,59747,1 +16752,Female,44,Diploma,10,7,52,67,95,5.0,0,56,Semi-Urban,Software Engineer,30300,0 +16753,Male,27,Masters,9,15,41,20,2,7.0,1,65,Urban,Software Engineer,56913,0 +16754,Male,54,Masters,18,90,64,53,39,7.0,1,59,Rural,ML Engineer,53989,1 +16755,Female,48,Diploma,8,48,61,95,61,3.0,0,1,Urban,Software Engineer,135192,0 +16756,Female,35,Bachelors,19,37,33,51,18,6.0,6,78,Semi-Urban,Manager,45135,0 +16757,Male,38,Bachelors,15,30,12,20,92,9.0,2,7,Urban,ML Engineer,85932,0 +16758,Female,55,PhD,11,53,60,31,4,9.0,0,41,Urban,Manager,147025,0 +16759,Male,31,Bachelors,14,62,42,78,87,5.0,0,30,Urban,Software Engineer,103633,0 +16760,Male,26,Bachelors,11,29,48,0,19,0.0,7,12,Urban,Software Engineer,118300,0 +16761,Male,34,Bachelors,18,97,67,52,89,1.0,1,19,Semi-Urban,ML Engineer,127177,1 +16762,Female,49,Diploma,7,74,92,4,26,3.0,2,39,Semi-Urban,Software Engineer,129217,0 +16763,Male,36,Bachelors,2,4,14,83,6,7.0,4,18,Urban,Data Analyst,122039,0 +16764,Male,24,Diploma,17,17,39,19,22,0.0,5,90,Semi-Urban,ML Engineer,82793,0 +16765,Female,26,Masters,18,56,11,96,60,7.0,4,43,Rural,Data Analyst,29155,0 +16766,Male,40,Bachelors,11,53,7,0,80,6.0,3,91,Semi-Urban,HR Executive,76293,0 +16767,Male,22,Diploma,5,12,29,8,51,9.0,4,58,Urban,Data Analyst,96989,0 +16768,Male,39,Bachelors,19,11,31,66,49,0.0,2,50,Urban,Manager,40048,0 +16769,Female,31,Masters,18,93,70,43,74,2.0,2,74,Rural,ML Engineer,78720,1 +16770,Male,51,High School,1,89,60,57,77,7.0,3,72,Rural,Data Analyst,50488,1 +16771,Female,40,Bachelors,0,15,19,48,28,4.0,0,64,Rural,Manager,135542,0 +16772,Female,50,Masters,0,75,2,82,76,5.0,3,19,Urban,Software Engineer,54710,0 +16773,Female,29,Bachelors,14,77,40,24,0,1.0,2,14,Semi-Urban,HR Executive,131496,0 +16774,Female,27,High School,17,48,53,24,94,7.0,6,54,Urban,ML Engineer,62639,0 +16775,Male,37,Diploma,2,78,42,67,96,3.0,2,48,Semi-Urban,Software Engineer,85831,1 +16776,Male,43,Masters,12,82,28,83,36,4.0,3,14,Urban,HR Executive,53976,0 +16777,Female,30,Masters,7,28,15,86,31,7.0,3,66,Urban,HR Executive,39027,0 +16778,Female,42,Bachelors,10,86,80,29,32,1.0,1,95,Urban,Data Analyst,101478,1 +16779,Male,43,Masters,15,89,19,79,68,1.0,2,99,Urban,Data Analyst,148990,1 +16780,Male,53,Bachelors,5,94,50,96,29,6.0,5,33,Rural,HR Executive,42476,1 +16781,Male,30,Bachelors,10,89,69,27,32,9.0,7,98,Urban,Data Analyst,38456,1 +16782,Male,33,Bachelors,0,80,16,4,74,5.0,7,55,Urban,Software Engineer,42462,0 +16783,Male,59,High School,11,96,83,80,16,7.0,6,4,Urban,Data Analyst,52616,1 +16784,Male,47,Bachelors,11,55,97,1,24,1.0,2,69,Semi-Urban,Manager,73682,0 +16785,Male,26,PhD,18,28,84,13,99,7.0,1,78,Urban,Software Engineer,26858,0 +16786,Male,44,Bachelors,11,25,98,27,21,4.0,6,18,Urban,Manager,95875,0 +16787,Male,27,Bachelors,15,87,30,18,29,8.0,4,23,Semi-Urban,ML Engineer,34881,0 +16788,Female,48,Bachelors,0,88,12,96,2,1.0,0,64,Rural,HR Executive,117414,1 +16789,Female,26,Diploma,18,30,3,59,82,5.0,2,59,Urban,ML Engineer,120571,0 +16790,Other,51,Masters,17,8,96,93,92,6.0,7,80,Urban,Manager,135770,1 +16791,Male,58,Diploma,10,91,18,98,21,9.0,2,81,Urban,ML Engineer,121246,1 +16792,Male,32,Masters,2,2,72,10,42,5.0,7,17,Semi-Urban,Manager,133889,0 +16793,Other,38,High School,0,22,98,59,36,4.0,7,13,Urban,HR Executive,27461,0 +16794,Female,37,Masters,7,83,97,20,65,0.0,0,73,Urban,Data Analyst,95107,1 +16795,Male,23,Masters,8,38,78,65,35,3.0,3,98,Semi-Urban,Manager,103369,1 +16796,Male,22,Masters,12,91,89,13,81,7.0,2,87,Semi-Urban,HR Executive,68978,1 +16797,Male,58,Bachelors,9,73,35,78,67,2.0,4,86,Semi-Urban,ML Engineer,138551,1 +16798,Male,27,Masters,15,13,10,33,6,8.0,5,53,Semi-Urban,Manager,84054,0 +16799,Male,50,Bachelors,8,86,34,55,8,3.0,4,31,Rural,Manager,63935,0 +16800,Female,36,Bachelors,11,27,83,36,44,6.0,0,2,Rural,Software Engineer,42646,0 +16801,Male,21,Bachelors,5,26,38,54,35,9.0,3,61,Urban,HR Executive,115439,0 +16802,Female,22,Bachelors,15,90,69,21,44,8.0,6,10,Urban,ML Engineer,58752,0 +16803,Female,41,Bachelors,18,59,88,18,80,5.0,3,88,Semi-Urban,HR Executive,87022,1 +16804,Female,39,Bachelors,13,75,60,66,56,9.0,2,54,Semi-Urban,HR Executive,36933,1 +16805,Female,42,High School,11,59,80,84,36,5.0,3,19,Rural,Manager,147197,1 +16806,Other,46,Bachelors,8,36,34,66,81,8.0,0,97,Urban,Software Engineer,26425,0 +16807,Male,59,Diploma,12,49,32,5,99,1.0,0,17,Urban,Manager,106651,0 +16808,Other,40,High School,16,51,49,90,18,2.0,5,12,Semi-Urban,Data Analyst,71683,0 +16809,Female,40,Masters,6,24,0,7,72,3.0,1,75,Urban,HR Executive,143498,0 +16810,Male,43,PhD,7,88,1,65,6,8.0,1,1,Urban,HR Executive,123335,0 +16811,Female,27,Masters,2,99,96,89,94,8.0,3,58,Semi-Urban,Manager,146301,1 +16812,Female,51,Bachelors,1,25,54,77,64,1.0,3,25,Semi-Urban,Data Analyst,100770,0 +16813,Female,47,Diploma,4,18,4,97,8,1.0,7,43,Urban,ML Engineer,119006,0 +16814,Male,31,Diploma,7,24,88,66,74,4.0,7,28,Urban,ML Engineer,30798,0 +16815,Male,21,Diploma,1,5,33,92,17,6.0,2,65,Semi-Urban,Data Analyst,141785,0 +16816,Male,33,Bachelors,18,7,60,40,43,8.0,2,67,Rural,Software Engineer,80307,0 +16817,Male,56,Bachelors,11,33,34,49,23,9.0,5,23,Urban,ML Engineer,65782,0 +16818,Male,58,PhD,11,54,33,82,56,9.0,4,11,Rural,ML Engineer,109922,0 +16819,Male,31,Bachelors,10,48,53,6,97,7.0,3,85,Urban,Manager,129206,0 +16820,Female,28,Diploma,3,71,54,80,4,1.0,6,99,Semi-Urban,Software Engineer,146923,1 +16821,Male,48,Bachelors,19,28,86,74,45,9.0,4,13,Semi-Urban,Manager,31606,0 +16822,Male,40,Masters,4,65,28,94,84,3.0,4,91,Urban,Software Engineer,142110,1 +16823,Male,21,Bachelors,16,14,10,80,95,6.0,1,63,Urban,Software Engineer,82033,0 +16824,Male,21,Masters,6,17,21,75,15,0.0,2,32,Urban,Manager,106865,0 +16825,Male,48,Bachelors,6,25,9,17,44,3.0,1,89,Urban,ML Engineer,41782,0 +16826,Male,41,Bachelors,0,86,73,14,66,8.0,4,26,Semi-Urban,ML Engineer,119735,0 +16827,Male,31,High School,13,17,57,6,15,8.0,0,84,Rural,Data Analyst,57116,0 +16828,Male,32,Bachelors,5,55,53,80,16,9.0,7,99,Urban,Software Engineer,34742,1 +16829,Male,35,Bachelors,0,56,61,93,66,2.0,6,84,Rural,Software Engineer,23198,1 +16830,Male,50,Bachelors,0,24,50,22,30,1.0,1,94,Rural,HR Executive,107786,0 +16831,Male,41,Bachelors,17,6,10,12,50,0.0,7,76,Urban,Software Engineer,63210,0 +16832,Male,59,Bachelors,1,89,55,20,88,6.0,2,62,Urban,ML Engineer,103938,0 +16833,Male,43,Diploma,0,8,43,81,8,5.0,0,15,Urban,ML Engineer,130517,0 +16834,Female,57,Bachelors,4,86,16,81,4,5.0,7,12,Urban,HR Executive,68903,0 +16835,Female,55,High School,17,24,2,60,80,4.0,5,98,Semi-Urban,HR Executive,20035,0 +16836,Male,34,Masters,3,48,72,27,64,0.0,4,62,Urban,Manager,36153,0 +16837,Male,46,Bachelors,9,39,44,45,6,5.0,5,36,Rural,HR Executive,143389,0 +16838,Female,39,Bachelors,16,58,3,61,50,4.0,2,6,Urban,ML Engineer,104921,0 +16839,Male,27,High School,16,62,38,71,61,8.0,6,81,Urban,Manager,100496,1 +16840,Female,52,Bachelors,18,35,39,28,55,1.0,3,46,Semi-Urban,Data Analyst,21180,0 +16841,Female,32,Masters,10,51,94,71,95,3.0,5,97,Rural,Manager,48370,1 +16842,Female,50,Diploma,11,17,97,61,92,6.0,7,59,Semi-Urban,Manager,105872,0 +16843,Female,32,Diploma,18,31,85,65,75,1.0,6,7,Urban,ML Engineer,45677,0 +16844,Female,33,High School,13,25,15,34,53,9.0,1,38,Semi-Urban,Data Analyst,34175,0 +16845,Female,58,Bachelors,2,46,1,33,69,8.0,2,11,Semi-Urban,HR Executive,48197,0 +16846,Female,45,High School,1,57,29,62,63,6.0,6,97,Urban,HR Executive,112778,1 +16847,Female,38,Bachelors,12,17,90,96,37,2.0,5,86,Urban,Data Analyst,105530,1 +16848,Female,43,Diploma,12,75,28,4,94,6.0,2,26,Semi-Urban,HR Executive,73443,0 +16849,Male,23,Masters,7,45,34,47,94,8.0,2,20,Semi-Urban,HR Executive,48909,0 +16850,Male,39,Diploma,18,62,6,91,66,3.0,1,24,Semi-Urban,Manager,65444,0 +16851,Female,46,Masters,4,34,6,33,58,5.0,0,45,Urban,Software Engineer,59516,0 +16852,Male,57,Masters,1,36,20,35,83,0.0,1,64,Semi-Urban,Software Engineer,49740,0 +16853,Female,46,Bachelors,1,34,66,24,31,1.0,6,75,Urban,ML Engineer,31389,0 +16854,Other,46,Masters,7,89,62,4,49,6.0,3,13,Rural,Software Engineer,20608,0 +16855,Female,33,PhD,8,58,93,21,22,5.0,5,53,Urban,Data Analyst,123789,0 +16856,Other,41,Diploma,17,46,72,36,37,4.0,0,94,Semi-Urban,ML Engineer,87627,1 +16857,Female,43,High School,18,21,95,19,57,3.0,5,69,Semi-Urban,HR Executive,27450,0 +16858,Male,37,Diploma,5,6,16,85,37,4.0,3,38,Urban,HR Executive,44363,0 +16859,Female,31,Diploma,6,88,80,80,71,2.0,2,66,Semi-Urban,Manager,107740,1 +16860,Male,37,Masters,8,35,22,35,57,0.0,3,46,Semi-Urban,HR Executive,120628,0 +16861,Male,36,Diploma,4,55,16,61,32,5.0,1,2,Semi-Urban,Software Engineer,24734,0 +16862,Male,57,Diploma,14,93,49,95,60,2.0,2,66,Rural,HR Executive,96399,1 +16863,Male,39,High School,13,10,64,44,67,0.0,0,48,Urban,HR Executive,36843,0 +16864,Male,40,Bachelors,16,11,3,72,97,3.0,6,63,Urban,ML Engineer,147384,0 +16865,Male,58,Masters,4,78,18,67,33,1.0,5,80,Rural,Data Analyst,62126,1 +16866,Female,33,Diploma,14,28,9,50,2,1.0,1,93,Urban,HR Executive,136366,0 +16867,Female,34,Diploma,16,28,44,44,94,7.0,6,76,Urban,HR Executive,77298,0 +16868,Male,34,High School,5,22,69,39,33,2.0,5,44,Urban,ML Engineer,93799,0 +16869,Male,30,Bachelors,11,66,75,52,87,2.0,3,76,Semi-Urban,HR Executive,101605,1 +16870,Female,30,High School,15,27,80,52,88,1.0,7,95,Rural,Data Analyst,139792,1 +16871,Female,50,Diploma,12,36,27,96,20,1.0,5,13,Urban,ML Engineer,137091,0 +16872,Female,24,Bachelors,11,27,96,81,40,1.0,5,4,Rural,ML Engineer,41751,0 +16873,Male,37,High School,2,15,54,84,7,8.0,3,32,Urban,ML Engineer,122829,0 +16874,Female,34,Diploma,2,1,69,39,48,2.0,2,13,Rural,Data Analyst,144551,0 +16875,Male,42,Masters,8,43,37,30,24,7.0,3,51,Urban,HR Executive,44860,0 +16876,Female,31,Masters,19,78,1,53,88,2.0,5,59,Semi-Urban,ML Engineer,116659,0 +16877,Male,26,Diploma,1,50,39,61,90,8.0,4,51,Semi-Urban,Manager,132917,0 +16878,Male,55,Bachelors,10,37,66,83,98,3.0,7,6,Urban,HR Executive,112557,0 +16879,Male,45,Bachelors,19,57,35,27,86,4.0,4,89,Urban,ML Engineer,91352,0 +16880,Male,47,Diploma,14,69,32,49,34,4.0,3,23,Semi-Urban,Data Analyst,42764,0 +16881,Male,25,Diploma,11,74,5,47,70,1.0,2,28,Urban,Software Engineer,88472,0 +16882,Female,57,Diploma,15,88,84,91,24,5.0,0,87,Urban,ML Engineer,56210,1 +16883,Female,42,Bachelors,19,96,24,81,6,3.0,2,24,Semi-Urban,Data Analyst,46390,0 +16884,Male,45,Diploma,6,31,77,84,74,9.0,3,88,Urban,Manager,123754,1 +16885,Male,36,Bachelors,2,79,91,6,68,7.0,5,78,Urban,Data Analyst,105003,1 +16886,Male,22,Diploma,13,0,64,40,17,1.0,5,14,Semi-Urban,Manager,48403,0 +16887,Other,22,Bachelors,19,78,22,59,30,5.0,0,50,Urban,ML Engineer,74536,0 +16888,Male,47,Bachelors,15,58,6,80,14,8.0,6,93,Urban,HR Executive,142156,1 +16889,Male,30,Diploma,6,47,93,67,38,5.0,4,92,Urban,Software Engineer,66195,1 +16890,Male,59,Bachelors,6,65,17,40,20,2.0,1,62,Urban,Software Engineer,130267,0 +16891,Female,43,Masters,12,36,3,4,41,3.0,7,39,Rural,Manager,113645,0 +16892,Male,35,High School,0,92,1,37,43,9.0,3,54,Urban,Manager,136000,0 +16893,Male,58,Masters,14,91,52,73,27,4.0,5,56,Rural,Data Analyst,77960,1 +16894,Female,33,Masters,1,49,30,41,50,2.0,4,12,Urban,ML Engineer,85718,0 +16895,Female,25,Diploma,17,91,57,21,1,1.0,5,43,Semi-Urban,Data Analyst,81474,0 +16896,Female,22,Masters,3,83,97,75,59,5.0,4,77,Urban,Manager,58931,1 +16897,Male,56,Bachelors,8,63,17,38,21,5.0,7,60,Rural,Manager,35326,0 +16898,Male,47,Diploma,5,17,45,54,68,1.0,6,94,Semi-Urban,Manager,105531,0 +16899,Female,47,PhD,2,35,15,24,67,0.0,4,57,Urban,ML Engineer,134933,0 +16900,Female,25,Bachelors,18,87,16,86,40,5.0,3,36,Urban,Manager,64954,0 +16901,Male,25,High School,10,59,91,13,14,0.0,7,97,Semi-Urban,HR Executive,132345,1 +16902,Male,27,High School,10,16,79,23,22,5.0,4,53,Urban,Manager,113004,0 +16903,Male,33,High School,9,37,91,47,27,6.0,3,49,Urban,ML Engineer,39689,0 +16904,Male,37,Bachelors,2,81,42,26,16,7.0,5,91,Urban,Software Engineer,89305,1 +16905,Female,54,Diploma,8,60,69,17,7,4.0,0,72,Urban,ML Engineer,71701,0 +16906,Other,53,Diploma,16,38,49,10,39,9.0,0,54,Urban,Data Analyst,72050,0 +16907,Male,59,High School,1,6,79,17,25,4.0,4,81,Urban,Manager,107542,0 +16908,Male,28,Bachelors,19,35,12,54,52,1.0,0,69,Urban,Manager,127461,0 +16909,Female,58,Bachelors,10,95,85,60,56,3.0,1,21,Rural,HR Executive,72606,1 +16910,Male,24,Diploma,11,38,27,37,69,4.0,3,62,Urban,Software Engineer,59643,0 +16911,Other,24,Bachelors,3,81,43,45,23,4.0,3,96,Urban,HR Executive,32927,1 +16912,Female,21,High School,8,59,98,2,40,4.0,0,75,Urban,HR Executive,59898,0 +16913,Female,23,Bachelors,12,78,50,36,13,5.0,0,30,Urban,Manager,123624,0 +16914,Male,46,Diploma,6,17,18,41,6,4.0,4,94,Urban,HR Executive,148626,0 +16915,Male,58,Bachelors,18,76,68,24,82,1.0,7,13,Urban,Data Analyst,55197,0 +16916,Male,41,Masters,12,70,81,72,48,3.0,0,70,Semi-Urban,Manager,96878,1 +16917,Male,23,Bachelors,9,62,3,43,76,6.0,7,88,Urban,Software Engineer,30528,0 +16918,Male,47,Bachelors,6,20,20,76,29,8.0,7,40,Semi-Urban,Software Engineer,97694,0 +16919,Other,47,Bachelors,5,67,73,40,79,7.0,2,40,Rural,Software Engineer,36276,0 +16920,Female,23,Diploma,4,62,5,5,56,4.0,6,81,Urban,HR Executive,34256,0 +16921,Female,34,High School,18,5,89,5,54,3.0,7,52,Urban,Data Analyst,124986,0 +16922,Male,50,Diploma,10,42,91,93,61,3.0,6,25,Urban,ML Engineer,136986,1 +16923,Female,28,Bachelors,7,21,78,89,30,1.0,7,88,Urban,Data Analyst,26920,1 +16924,Female,29,Masters,14,83,76,82,58,3.0,3,0,Rural,HR Executive,28628,1 +16925,Male,46,Bachelors,7,89,86,94,6,5.0,1,8,Urban,HR Executive,121623,1 +16926,Female,37,Bachelors,9,3,56,96,58,6.0,7,14,Semi-Urban,Data Analyst,88586,0 +16927,Male,37,Bachelors,17,48,70,5,79,7.0,0,47,Rural,ML Engineer,72675,0 +16928,Male,25,Bachelors,16,79,72,13,93,3.0,2,39,Urban,Software Engineer,142866,0 +16929,Male,41,Diploma,9,75,69,28,7,0.0,0,30,Rural,Software Engineer,112195,0 +16930,Female,55,Masters,13,22,64,16,37,5.0,2,45,Urban,Data Analyst,85755,0 +16931,Female,44,Diploma,18,34,86,34,45,2.0,4,73,Semi-Urban,ML Engineer,136907,0 +16932,Male,59,Bachelors,8,40,22,16,20,2.0,0,27,Urban,Manager,117532,0 +16933,Male,38,Masters,4,94,56,8,81,4.0,3,36,Urban,ML Engineer,39547,0 +16934,Male,36,Bachelors,0,13,76,3,6,1.0,6,50,Urban,Data Analyst,28112,0 +16935,Male,40,Bachelors,6,33,85,1,14,2.0,5,99,Urban,ML Engineer,104199,0 +16936,Male,35,Bachelors,18,79,81,71,39,4.0,7,72,Urban,Software Engineer,45345,1 +16937,Male,52,Bachelors,4,0,55,69,33,9.0,4,16,Urban,Software Engineer,108769,0 +16938,Male,56,Bachelors,7,44,88,37,32,8.0,1,51,Rural,HR Executive,56352,0 +16939,Female,51,Diploma,4,16,67,31,78,8.0,7,78,Semi-Urban,Manager,71090,0 +16940,Male,47,Diploma,5,68,1,79,41,4.0,0,81,Semi-Urban,Manager,148006,0 +16941,Female,27,Diploma,14,88,33,59,75,4.0,3,16,Urban,Data Analyst,26937,0 +16942,Male,29,Masters,8,97,46,92,16,8.0,0,70,Rural,ML Engineer,95370,1 +16943,Male,54,Masters,8,10,67,81,74,4.0,3,45,Urban,Software Engineer,110302,0 +16944,Male,40,Masters,5,11,87,43,35,9.0,2,58,Rural,Data Analyst,149633,0 +16945,Male,36,Bachelors,7,97,31,0,96,4.0,3,71,Urban,Manager,144270,0 +16946,Male,24,Bachelors,4,4,73,59,32,3.0,1,47,Urban,HR Executive,89011,0 +16947,Female,46,Diploma,19,39,90,46,80,9.0,0,97,Urban,Manager,91132,1 +16948,Female,21,Diploma,6,95,51,24,35,2.0,4,93,Semi-Urban,Software Engineer,114779,1 +16949,Male,50,Diploma,19,80,95,42,14,3.0,0,46,Urban,Data Analyst,44697,1 +16950,Male,43,Diploma,15,63,12,4,24,1.0,2,18,Urban,Data Analyst,79272,0 +16951,Other,22,Bachelors,6,41,82,20,82,3.0,0,81,Urban,Data Analyst,95060,0 +16952,Male,51,Bachelors,3,92,82,30,56,4.0,1,99,Urban,Software Engineer,91935,1 +16953,Female,33,Diploma,11,27,99,28,18,3.0,0,41,Semi-Urban,ML Engineer,75613,0 +16954,Other,58,Diploma,13,44,96,19,94,7.0,3,38,Urban,Software Engineer,45716,0 +16955,Other,57,Diploma,6,60,61,98,46,4.0,4,71,Urban,Manager,147045,1 +16956,Male,56,Bachelors,16,45,80,78,43,5.0,6,49,Rural,ML Engineer,140135,1 +16957,Male,33,Bachelors,16,72,33,20,72,3.0,7,47,Urban,Manager,44046,0 +16958,Male,40,Masters,1,44,35,72,64,0.0,6,40,Urban,Software Engineer,62340,0 +16959,Female,29,Masters,15,25,70,62,28,8.0,1,38,Rural,ML Engineer,115707,0 +16960,Female,58,Bachelors,0,18,26,45,8,7.0,0,8,Urban,Software Engineer,148024,0 +16961,Female,38,High School,3,18,1,30,93,5.0,5,17,Rural,HR Executive,111753,0 +16962,Female,45,Bachelors,9,49,14,83,68,1.0,1,74,Urban,Manager,26488,0 +16963,Female,35,High School,16,96,15,29,68,6.0,0,4,Rural,Data Analyst,142060,0 +16964,Female,59,High School,17,13,79,0,21,0.0,3,11,Urban,Software Engineer,138613,0 +16965,Female,32,Bachelors,14,43,71,26,0,0.0,3,91,Semi-Urban,Manager,82368,0 +16966,Female,34,Diploma,14,95,66,3,28,8.0,6,11,Rural,HR Executive,73646,0 +16967,Male,27,Masters,5,99,34,76,88,0.0,1,75,Rural,Software Engineer,53894,1 +16968,Male,44,Masters,1,39,97,22,32,6.0,0,61,Semi-Urban,HR Executive,88815,0 +16969,Female,27,Diploma,11,82,36,42,91,5.0,3,18,Urban,Manager,120707,0 +16970,Male,59,Masters,5,1,95,35,98,9.0,1,4,Urban,Software Engineer,72274,0 +16971,Male,51,High School,1,57,80,79,9,5.0,1,64,Urban,Software Engineer,116301,1 +16972,Female,57,Masters,19,46,70,26,62,8.0,1,43,Urban,Software Engineer,129049,0 +16973,Female,53,Bachelors,6,31,26,89,16,9.0,5,92,Urban,ML Engineer,42906,0 +16974,Female,26,Diploma,7,63,30,19,61,7.0,5,24,Rural,HR Executive,86042,0 +16975,Male,53,High School,1,30,71,87,20,4.0,3,72,Urban,ML Engineer,113194,1 +16976,Female,58,Bachelors,12,55,76,40,40,2.0,2,97,Urban,Manager,105666,1 +16977,Male,42,High School,19,66,2,65,82,1.0,3,34,Urban,HR Executive,73057,0 +16978,Female,38,Bachelors,19,91,75,33,74,5.0,1,94,Rural,Data Analyst,146481,1 +16979,Male,31,Bachelors,6,36,82,82,45,2.0,3,18,Urban,HR Executive,42396,0 +16980,Female,34,Bachelors,15,70,83,91,57,9.0,1,10,Semi-Urban,HR Executive,45717,1 +16981,Female,46,Bachelors,17,21,1,28,46,1.0,7,32,Urban,Manager,146251,0 +16982,Male,30,Bachelors,18,28,20,71,4,1.0,7,2,Rural,HR Executive,34234,0 +16983,Other,58,High School,11,50,91,80,16,9.0,0,45,Urban,ML Engineer,105432,1 +16984,Female,52,High School,7,69,48,78,46,4.0,1,33,Semi-Urban,Software Engineer,83884,0 +16985,Male,32,High School,14,74,82,22,37,6.0,7,66,Urban,HR Executive,129582,1 +16986,Male,52,Bachelors,15,97,64,69,86,4.0,0,38,Semi-Urban,Software Engineer,69125,1 +16987,Male,59,Masters,10,45,70,42,20,4.0,7,73,Urban,Software Engineer,127348,0 +16988,Male,56,Diploma,17,62,71,45,20,6.0,0,20,Urban,Software Engineer,73298,0 +16989,Female,53,Bachelors,12,71,79,27,32,3.0,3,31,Urban,Manager,133046,0 +16990,Other,33,Bachelors,7,57,96,78,16,7.0,2,24,Rural,Manager,68560,1 +16991,Male,51,Bachelors,1,17,99,15,42,6.0,4,31,Urban,Data Analyst,69945,0 +16992,Male,35,Bachelors,13,43,86,54,58,7.0,4,8,Semi-Urban,Software Engineer,141746,0 +16993,Male,37,Bachelors,14,32,53,4,98,0.0,5,94,Semi-Urban,Data Analyst,68305,0 +16994,Male,44,High School,0,32,34,42,76,6.0,4,69,Urban,Software Engineer,35717,0 +16995,Male,34,Diploma,18,8,30,15,52,3.0,1,37,Semi-Urban,Data Analyst,24460,0 +16996,Male,34,High School,7,0,50,99,47,4.0,2,48,Semi-Urban,Manager,48600,0 +16997,Male,45,Bachelors,5,60,56,50,52,3.0,3,71,Rural,HR Executive,109325,1 +16998,Female,56,Masters,13,69,34,12,25,9.0,5,36,Rural,HR Executive,95469,0 +16999,Female,30,Masters,12,60,50,43,3,5.0,5,20,Rural,HR Executive,100482,0 +17000,Male,35,Bachelors,0,71,80,63,60,5.0,4,32,Semi-Urban,Data Analyst,83301,1 +17001,Female,27,Diploma,8,99,16,7,57,5.0,4,57,Urban,Data Analyst,147033,0 +17002,Female,37,High School,5,29,38,11,22,0.0,2,15,Urban,Manager,91850,0 +17003,Female,35,Masters,16,42,63,56,81,6.0,7,21,Semi-Urban,ML Engineer,29412,0 +17004,Male,24,Masters,0,81,46,50,2,2.0,5,68,Rural,Software Engineer,57547,1 +17005,Female,57,Bachelors,5,92,97,41,36,4.0,0,82,Semi-Urban,ML Engineer,41293,1 +17006,Female,30,High School,9,54,87,66,70,5.0,1,86,Urban,Software Engineer,147807,1 +17007,Male,39,Bachelors,2,7,35,81,11,7.0,2,92,Rural,Data Analyst,106962,0 +17008,Male,39,Masters,11,47,21,78,37,0.0,3,50,Urban,HR Executive,89294,0 +17009,Female,30,Diploma,1,78,62,58,29,0.0,5,60,Urban,Data Analyst,110144,1 +17010,Female,28,Bachelors,7,43,67,46,14,3.0,0,28,Urban,ML Engineer,145501,0 +17011,Female,52,Diploma,0,48,85,78,7,3.0,5,37,Urban,Software Engineer,43177,1 +17012,Female,42,Diploma,3,46,35,74,36,8.0,6,62,Rural,ML Engineer,94490,0 +17013,Female,59,High School,5,16,58,52,55,0.0,4,46,Urban,ML Engineer,134661,0 +17014,Male,29,Bachelors,4,66,40,8,83,0.0,7,83,Rural,HR Executive,78829,0 +17015,Male,27,Diploma,16,97,70,99,15,1.0,3,68,Semi-Urban,ML Engineer,148783,1 +17016,Other,56,Diploma,13,44,27,59,19,8.0,7,72,Urban,Software Engineer,109028,0 +17017,Male,33,Masters,14,98,9,12,90,6.0,4,94,Urban,Software Engineer,110821,0 +17018,Male,41,Diploma,1,57,38,97,70,5.0,0,59,Semi-Urban,ML Engineer,142053,1 +17019,Female,44,High School,0,68,11,83,61,3.0,4,61,Urban,Data Analyst,108172,0 +17020,Female,34,Bachelors,5,2,91,36,72,1.0,7,77,Urban,Manager,107893,0 +17021,Male,45,Masters,10,68,24,46,76,3.0,7,4,Rural,Software Engineer,119515,0 +17022,Male,33,Bachelors,15,71,48,39,5,1.0,0,6,Urban,HR Executive,97381,0 +17023,Male,21,High School,12,60,15,46,82,4.0,4,20,Urban,Data Analyst,137743,0 +17024,Male,37,High School,1,34,54,33,39,7.0,1,20,Urban,Manager,77120,0 +17025,Female,23,Bachelors,5,23,61,68,63,4.0,5,30,Rural,Software Engineer,63316,0 +17026,Male,46,Masters,3,4,4,91,30,4.0,4,72,Semi-Urban,ML Engineer,35672,0 +17027,Female,34,Bachelors,6,33,93,55,18,0.0,2,96,Urban,Software Engineer,104770,1 +17028,Female,24,Diploma,1,7,5,18,41,5.0,3,51,Urban,Software Engineer,48865,0 +17029,Female,32,Diploma,5,51,47,88,57,8.0,5,41,Urban,ML Engineer,133671,0 +17030,Male,30,Diploma,10,6,33,70,54,3.0,2,11,Urban,Manager,51418,0 +17031,Male,59,Bachelors,15,95,30,89,4,7.0,3,69,Semi-Urban,ML Engineer,35257,1 +17032,Male,31,Bachelors,4,32,98,81,57,4.0,3,45,Semi-Urban,Manager,135175,1 +17033,Male,24,High School,6,28,33,34,2,2.0,7,11,Rural,HR Executive,126209,0 +17034,Female,35,Bachelors,5,26,66,99,23,3.0,7,15,Semi-Urban,Manager,117285,0 +17035,Male,24,Bachelors,3,59,14,29,89,8.0,1,37,Semi-Urban,ML Engineer,22658,0 +17036,Female,37,Bachelors,15,95,51,21,72,4.0,6,66,Semi-Urban,Manager,117152,0 +17037,Male,55,Diploma,3,12,39,78,65,1.0,7,85,Urban,ML Engineer,45756,0 +17038,Male,49,High School,4,41,24,8,95,9.0,2,23,Urban,Software Engineer,78277,0 +17039,Other,58,Bachelors,11,16,19,66,84,0.0,2,55,Semi-Urban,HR Executive,85513,0 +17040,Male,23,Bachelors,7,49,92,70,20,4.0,0,89,Rural,Software Engineer,67112,1 +17041,Male,32,High School,9,76,0,1,90,7.0,0,55,Rural,Software Engineer,73514,0 +17042,Male,58,Bachelors,3,9,23,46,10,9.0,7,8,Urban,Software Engineer,114744,0 +17043,Male,31,Bachelors,0,33,14,11,15,1.0,0,21,Rural,Data Analyst,110933,0 +17044,Female,56,Masters,8,8,26,39,67,7.0,7,53,Urban,Data Analyst,148910,0 +17045,Male,22,Diploma,18,35,63,33,20,5.0,7,67,Urban,Software Engineer,51697,0 +17046,Male,54,Diploma,7,82,97,88,59,2.0,4,28,Rural,Software Engineer,149914,1 +17047,Male,25,Masters,19,41,43,39,68,0.0,7,34,Urban,ML Engineer,41404,0 +17048,Female,50,Masters,3,31,43,25,70,0.0,7,40,Urban,Software Engineer,56557,0 +17049,Male,39,Bachelors,5,43,27,81,90,8.0,3,66,Semi-Urban,HR Executive,106648,0 +17050,Male,40,Bachelors,15,74,5,72,73,1.0,2,67,Semi-Urban,HR Executive,122270,0 +17051,Male,22,Masters,13,42,47,73,70,1.0,3,34,Urban,Software Engineer,147336,0 +17052,Male,51,Bachelors,2,18,88,1,51,9.0,0,6,Urban,HR Executive,23736,0 +17053,Male,58,PhD,4,43,70,16,55,9.0,4,9,Urban,HR Executive,26898,0 +17054,Male,37,High School,13,41,84,14,54,4.0,6,71,Semi-Urban,Manager,143625,0 +17055,Male,52,High School,10,57,91,73,10,5.0,5,82,Rural,HR Executive,109282,1 +17056,Male,45,Bachelors,5,98,27,95,86,0.0,4,11,Urban,Data Analyst,71963,0 +17057,Male,21,Bachelors,5,48,88,93,49,6.0,1,44,Urban,ML Engineer,45304,1 +17058,Female,36,Bachelors,5,89,70,86,28,9.0,6,93,Urban,HR Executive,28003,1 +17059,Female,40,Masters,1,50,44,44,9,8.0,2,1,Rural,HR Executive,103499,0 +17060,Male,23,Masters,5,86,51,34,19,3.0,7,86,Semi-Urban,HR Executive,142943,1 +17061,Male,33,Diploma,18,82,71,67,97,5.0,5,37,Urban,ML Engineer,38008,1 +17062,Female,42,Masters,16,58,98,78,0,4.0,1,10,Urban,Data Analyst,113049,1 +17063,Female,48,PhD,4,13,27,39,81,6.0,0,66,Semi-Urban,Data Analyst,61419,0 +17064,Male,51,Diploma,0,18,58,4,77,8.0,1,55,Urban,ML Engineer,52761,0 +17065,Female,27,High School,14,61,79,56,68,3.0,3,70,Semi-Urban,Software Engineer,59791,1 +17066,Male,54,Masters,16,25,8,14,40,9.0,4,26,Urban,HR Executive,55238,0 +17067,Male,50,Bachelors,17,99,73,79,11,3.0,4,43,Semi-Urban,HR Executive,63164,1 +17068,Other,45,Bachelors,18,3,76,63,30,0.0,0,81,Urban,Manager,71525,0 +17069,Female,23,Masters,13,83,40,44,61,9.0,7,4,Semi-Urban,Manager,33628,0 +17070,Female,55,Bachelors,11,36,19,80,70,8.0,7,36,Urban,ML Engineer,118569,0 +17071,Male,22,Diploma,13,18,88,68,65,7.0,6,54,Semi-Urban,Software Engineer,97305,0 +17072,Male,47,Diploma,0,28,94,6,37,9.0,0,34,Rural,HR Executive,107141,0 +17073,Female,23,Bachelors,15,15,72,86,33,5.0,1,93,Rural,ML Engineer,84174,1 +17074,Male,48,Bachelors,5,32,65,65,81,3.0,2,7,Urban,HR Executive,107043,0 +17075,Male,31,Bachelors,4,32,85,47,72,9.0,1,78,Urban,HR Executive,129384,1 +17076,Male,25,Diploma,12,6,43,34,55,7.0,7,23,Urban,Software Engineer,121153,0 +17077,Male,37,Masters,2,60,84,6,22,5.0,4,97,Rural,ML Engineer,142114,1 +17078,Male,47,Diploma,15,80,46,21,98,9.0,3,78,Urban,Software Engineer,54440,0 +17079,Female,29,Bachelors,14,48,11,17,48,4.0,4,77,Semi-Urban,HR Executive,85647,0 +17080,Female,53,PhD,9,57,88,98,35,9.0,5,8,Urban,HR Executive,135230,1 +17081,Male,23,Bachelors,5,11,9,55,22,3.0,0,88,Urban,Data Analyst,66097,0 +17082,Female,48,Diploma,19,1,45,53,40,1.0,5,33,Rural,Manager,46929,0 +17083,Male,40,Bachelors,10,98,62,71,84,9.0,5,84,Urban,Manager,69339,1 +17084,Female,51,Masters,3,14,85,88,59,1.0,3,82,Urban,ML Engineer,111631,1 +17085,Male,49,PhD,16,35,58,9,37,2.0,2,67,Urban,Software Engineer,114316,0 +17086,Female,55,Diploma,4,15,95,38,24,4.0,6,68,Rural,HR Executive,34612,0 +17087,Female,48,Diploma,8,73,70,33,51,3.0,3,73,Rural,Data Analyst,59351,1 +17088,Male,26,Bachelors,16,12,59,32,1,7.0,1,94,Semi-Urban,Manager,62450,0 +17089,Male,48,Bachelors,8,87,80,46,63,2.0,5,47,Urban,ML Engineer,119736,1 +17090,Other,56,Diploma,7,41,8,26,97,1.0,2,67,Urban,HR Executive,138968,0 +17091,Male,56,Masters,2,84,75,14,59,4.0,5,41,Semi-Urban,Data Analyst,82098,0 +17092,Female,59,Bachelors,14,66,66,63,11,0.0,6,61,Semi-Urban,HR Executive,82178,1 +17093,Other,31,Bachelors,12,53,63,94,10,3.0,3,87,Rural,ML Engineer,120448,1 +17094,Male,44,Bachelors,3,29,95,51,34,6.0,5,19,Urban,HR Executive,30584,0 +17095,Female,59,Diploma,17,95,75,86,46,9.0,7,65,Urban,Software Engineer,107757,1 +17096,Female,45,High School,5,12,14,12,80,4.0,6,99,Urban,Data Analyst,86960,0 +17097,Female,54,Bachelors,0,68,11,99,48,6.0,0,61,Semi-Urban,ML Engineer,57642,0 +17098,Male,25,Diploma,1,52,3,70,53,9.0,6,3,Rural,HR Executive,132157,0 +17099,Male,57,Diploma,17,52,38,66,56,4.0,4,76,Rural,HR Executive,114796,0 +17100,Male,42,High School,7,16,14,65,82,2.0,3,93,Semi-Urban,Manager,136376,0 +17101,Female,56,Bachelors,17,98,12,81,26,9.0,6,21,Rural,Software Engineer,126520,0 +17102,Female,21,Masters,5,6,28,40,43,6.0,7,41,Semi-Urban,HR Executive,53792,0 +17103,Female,36,Bachelors,10,37,31,72,85,8.0,4,92,Semi-Urban,Manager,135065,0 +17104,Male,57,Diploma,2,10,64,78,6,6.0,7,26,Urban,HR Executive,122909,0 +17105,Male,59,Bachelors,10,48,87,54,15,2.0,4,90,Urban,Data Analyst,24598,1 +17106,Female,50,Masters,8,97,82,67,51,7.0,6,36,Urban,Manager,31837,1 +17107,Female,31,PhD,0,37,81,14,52,4.0,3,66,Urban,Data Analyst,41218,0 +17108,Female,32,High School,2,74,31,86,27,7.0,4,93,Semi-Urban,Software Engineer,128035,1 +17109,Female,51,Masters,18,38,4,59,91,0.0,6,46,Urban,Data Analyst,87241,0 +17110,Female,39,Diploma,13,85,62,77,33,1.0,2,46,Urban,Data Analyst,109075,1 +17111,Female,44,High School,12,56,61,48,1,8.0,2,34,Rural,ML Engineer,33258,0 +17112,Female,45,Masters,18,88,37,10,60,0.0,7,20,Semi-Urban,Software Engineer,57691,0 +17113,Male,36,Bachelors,0,55,57,45,29,9.0,2,34,Urban,Manager,126874,0 +17114,Female,54,PhD,19,43,51,49,27,4.0,1,12,Urban,ML Engineer,59830,0 +17115,Female,38,Bachelors,7,54,44,46,9,2.0,2,76,Semi-Urban,Data Analyst,116154,0 +17116,Male,49,High School,17,28,88,78,31,2.0,1,76,Rural,Manager,70513,1 +17117,Male,26,Bachelors,15,84,84,52,80,2.0,1,80,Rural,Data Analyst,53691,1 +17118,Male,36,Bachelors,14,54,60,53,94,1.0,1,43,Rural,Manager,131013,0 +17119,Male,31,Bachelors,0,48,0,67,56,4.0,2,77,Rural,Data Analyst,102297,0 +17120,Male,51,Diploma,3,70,34,3,50,3.0,6,72,Urban,Data Analyst,81571,0 +17121,Male,31,Bachelors,11,3,25,64,65,5.0,7,60,Urban,ML Engineer,39708,0 +17122,Male,57,High School,5,26,59,25,6,2.0,3,18,Semi-Urban,HR Executive,34381,0 +17123,Male,30,Bachelors,6,43,90,28,74,9.0,2,70,Urban,ML Engineer,147558,0 +17124,Female,22,Diploma,2,14,25,87,41,3.0,4,81,Urban,Software Engineer,114189,0 +17125,Male,45,Masters,4,33,88,37,13,4.0,2,55,Urban,Software Engineer,29565,0 +17126,Male,34,Bachelors,15,88,12,27,72,6.0,2,95,Urban,Manager,136164,0 +17127,Male,22,High School,2,60,16,6,7,0.0,7,32,Rural,Manager,124573,0 +17128,Male,49,Masters,12,90,37,30,12,3.0,0,69,Urban,Data Analyst,82094,0 +17129,Male,35,Bachelors,0,14,38,66,50,5.0,0,14,Urban,Manager,111298,0 +17130,Female,50,Diploma,11,94,17,6,77,5.0,2,61,Urban,Manager,130607,0 +17131,Female,54,High School,13,87,10,67,91,0.0,3,43,Semi-Urban,Data Analyst,140906,0 +17132,Male,32,Masters,11,64,97,88,44,5.0,0,28,Urban,Manager,116433,1 +17133,Female,49,Diploma,14,71,15,8,38,3.0,0,66,Rural,Data Analyst,20514,0 +17134,Male,26,Masters,5,60,23,53,38,9.0,5,65,Semi-Urban,Software Engineer,88123,0 +17135,Other,46,Diploma,10,84,51,47,46,8.0,7,26,Semi-Urban,Manager,44322,0 +17136,Other,22,High School,18,70,4,3,67,3.0,1,96,Urban,Manager,29892,0 +17137,Male,24,High School,15,51,94,9,12,9.0,4,19,Rural,ML Engineer,58462,0 +17138,Female,38,Masters,9,23,93,35,98,1.0,1,93,Rural,Manager,107190,1 +17139,Female,40,Masters,0,41,68,8,91,6.0,2,73,Rural,Manager,31562,0 +17140,Female,32,Bachelors,10,33,40,50,78,1.0,6,23,Semi-Urban,Data Analyst,145045,0 +17141,Female,29,Bachelors,6,45,92,35,62,5.0,3,71,Urban,ML Engineer,115437,1 +17142,Other,49,Bachelors,13,33,51,98,27,6.0,0,23,Urban,ML Engineer,132960,0 +17143,Male,39,Masters,7,29,56,54,31,4.0,3,95,Semi-Urban,ML Engineer,139564,0 +17144,Female,53,Masters,1,8,33,64,16,7.0,5,29,Rural,Manager,32852,0 +17145,Female,26,Bachelors,6,82,42,0,98,6.0,6,29,Rural,Data Analyst,146686,0 +17146,Female,32,Masters,0,78,27,75,81,0.0,5,17,Urban,Software Engineer,98703,0 +17147,Female,52,PhD,16,30,5,32,99,6.0,3,87,Semi-Urban,ML Engineer,59831,0 +17148,Male,37,Masters,13,90,24,21,29,7.0,3,44,Urban,ML Engineer,135003,0 +17149,Male,38,Bachelors,8,0,43,72,96,7.0,1,30,Urban,ML Engineer,123431,0 +17150,Male,45,Diploma,15,26,36,0,98,7.0,4,91,Rural,Data Analyst,108026,0 +17151,Male,25,Masters,13,34,15,29,22,7.0,0,95,Urban,Data Analyst,73315,0 +17152,Male,58,Bachelors,13,8,39,34,92,4.0,5,21,Urban,Manager,96425,0 +17153,Other,55,Masters,9,42,34,28,37,7.0,1,49,Urban,HR Executive,97309,0 +17154,Female,49,Diploma,0,67,60,66,46,3.0,5,63,Semi-Urban,ML Engineer,68080,1 +17155,Female,44,Bachelors,3,42,49,40,79,9.0,0,47,Rural,ML Engineer,30863,0 +17156,Male,56,Masters,4,65,56,65,57,7.0,4,37,Semi-Urban,ML Engineer,103332,0 +17157,Female,58,Bachelors,8,18,29,87,37,3.0,5,42,Rural,Software Engineer,88287,0 +17158,Female,27,Bachelors,7,66,78,42,15,8.0,3,39,Semi-Urban,Manager,82478,0 +17159,Female,58,Diploma,16,72,46,75,44,1.0,2,32,Urban,ML Engineer,52439,0 +17160,Male,47,High School,16,10,63,39,29,3.0,7,44,Urban,HR Executive,93521,0 +17161,Male,26,High School,10,50,27,86,57,8.0,1,64,Rural,Manager,85711,0 +17162,Female,54,Diploma,18,52,53,89,8,3.0,6,58,Semi-Urban,Data Analyst,127274,1 +17163,Male,50,Bachelors,5,25,63,50,62,4.0,6,7,Urban,ML Engineer,135463,0 +17164,Female,49,Bachelors,9,52,97,4,71,6.0,6,9,Semi-Urban,ML Engineer,141102,0 +17165,Female,45,Diploma,17,11,26,7,84,6.0,4,90,Urban,Manager,21288,0 +17166,Other,49,High School,4,72,43,44,69,0.0,7,30,Rural,Software Engineer,89008,0 +17167,Female,35,Bachelors,10,10,47,28,25,3.0,6,98,Urban,Data Analyst,70586,0 +17168,Other,54,Masters,5,56,37,41,58,0.0,1,45,Urban,Software Engineer,112600,0 +17169,Female,47,PhD,9,9,79,57,56,9.0,2,60,Rural,Software Engineer,141089,0 +17170,Male,42,Bachelors,4,96,80,41,56,8.0,2,29,Urban,HR Executive,99670,1 +17171,Male,22,Bachelors,1,79,87,96,15,4.0,7,78,Urban,Data Analyst,30998,1 +17172,Male,46,Bachelors,8,73,89,34,0,4.0,4,91,Urban,Manager,102454,1 +17173,Male,31,Bachelors,14,7,39,29,86,0.0,3,1,Rural,Software Engineer,121656,0 +17174,Male,58,Bachelors,19,77,69,34,34,2.0,2,7,Semi-Urban,ML Engineer,149756,0 +17175,Male,23,Diploma,17,82,41,24,91,8.0,5,62,Urban,Software Engineer,79047,0 +17176,Female,52,Masters,12,69,59,37,96,6.0,4,2,Urban,Software Engineer,137391,0 +17177,Male,40,Bachelors,15,57,87,2,24,9.0,6,74,Rural,Data Analyst,115939,0 +17178,Male,59,Bachelors,16,56,96,3,90,7.0,0,17,Urban,Software Engineer,28362,0 +17179,Female,40,Bachelors,13,70,13,87,44,9.0,1,1,Urban,HR Executive,123313,0 +17180,Female,28,High School,17,97,3,42,58,1.0,6,16,Urban,Data Analyst,131743,0 +17181,Other,43,Bachelors,10,42,40,54,96,0.0,0,87,Semi-Urban,Data Analyst,123816,0 +17182,Female,42,Bachelors,15,10,16,5,32,0.0,7,40,Urban,Manager,44889,0 +17183,Male,50,Bachelors,0,71,32,15,99,7.0,2,37,Urban,HR Executive,106398,0 +17184,Male,45,Bachelors,9,14,35,94,12,8.0,2,64,Rural,Manager,77779,0 +17185,Male,41,Bachelors,2,21,33,29,33,0.0,3,29,Urban,Manager,44674,0 +17186,Male,57,PhD,2,38,31,80,52,4.0,3,66,Semi-Urban,Manager,148687,0 +17187,Male,23,Masters,5,2,9,58,65,9.0,0,20,Urban,Data Analyst,81586,0 +17188,Other,44,Masters,19,18,36,4,41,7.0,4,14,Rural,Data Analyst,83748,0 +17189,Male,42,High School,6,40,47,36,23,0.0,2,84,Urban,ML Engineer,52764,0 +17190,Male,40,Bachelors,2,50,46,12,71,1.0,6,15,Urban,ML Engineer,143846,0 +17191,Male,22,Bachelors,18,44,31,60,74,1.0,5,14,Urban,Software Engineer,59950,0 +17192,Female,24,Bachelors,15,30,20,36,12,9.0,4,44,Semi-Urban,Data Analyst,147507,0 +17193,Male,37,Bachelors,7,73,17,86,48,5.0,3,99,Rural,HR Executive,81202,1 +17194,Male,48,Bachelors,1,10,74,25,91,7.0,0,96,Urban,Data Analyst,55744,0 +17195,Male,40,Masters,7,19,7,41,92,3.0,1,97,Urban,Data Analyst,92606,0 +17196,Male,26,Bachelors,7,49,17,82,91,8.0,7,15,Urban,ML Engineer,47261,0 +17197,Male,46,High School,4,46,51,26,4,9.0,1,6,Urban,Software Engineer,98133,0 +17198,Male,29,Diploma,12,25,20,75,63,8.0,7,62,Urban,Manager,74075,0 +17199,Male,51,Bachelors,2,56,72,56,31,7.0,0,40,Semi-Urban,Manager,123064,0 +17200,Female,51,High School,13,10,24,11,66,8.0,2,56,Urban,Data Analyst,102322,0 +17201,Male,24,Bachelors,3,79,24,98,75,9.0,7,49,Urban,Manager,98727,1 +17202,Female,48,Bachelors,4,80,79,0,83,0.0,0,64,Urban,Software Engineer,126851,0 +17203,Male,43,Masters,1,18,31,36,57,0.0,0,75,Rural,Software Engineer,97919,0 +17204,Male,23,Bachelors,19,80,9,62,97,2.0,2,9,Urban,HR Executive,138137,0 +17205,Male,47,Bachelors,15,13,23,70,85,3.0,5,53,Rural,Manager,98495,0 +17206,Male,58,Diploma,18,8,0,79,19,5.0,5,61,Semi-Urban,HR Executive,61619,0 +17207,Male,24,PhD,18,57,88,1,79,1.0,4,19,Urban,ML Engineer,70598,0 +17208,Male,40,Bachelors,0,45,6,53,21,1.0,7,79,Rural,Manager,49274,0 +17209,Female,24,Masters,17,65,41,85,81,4.0,5,12,Urban,Software Engineer,112888,0 +17210,Female,38,Masters,1,49,85,75,0,5.0,6,75,Urban,Software Engineer,37130,1 +17211,Female,40,Bachelors,16,64,84,48,94,1.0,5,84,Urban,Software Engineer,74340,1 +17212,Male,38,Bachelors,11,56,72,50,83,6.0,7,82,Urban,Software Engineer,35636,1 +17213,Female,51,Bachelors,5,10,11,95,30,6.0,5,84,Urban,Manager,41405,0 +17214,Male,33,Bachelors,12,80,19,66,31,1.0,4,12,Urban,ML Engineer,22654,0 +17215,Female,26,Bachelors,17,62,19,76,5,8.0,5,34,Urban,Software Engineer,99135,0 +17216,Male,40,Diploma,14,60,0,86,70,1.0,3,83,Rural,ML Engineer,80244,0 +17217,Male,36,Bachelors,16,24,73,3,90,2.0,3,57,Urban,Manager,61518,0 +17218,Female,23,Masters,12,57,76,94,53,8.0,7,93,Semi-Urban,Manager,88187,1 +17219,Female,56,Masters,19,95,3,40,0,4.0,6,96,Rural,Data Analyst,113310,0 +17220,Male,43,Masters,9,35,23,36,25,7.0,0,94,Rural,Software Engineer,144696,0 +17221,Male,55,High School,1,12,73,21,76,7.0,1,98,Rural,Data Analyst,44889,0 +17222,Male,47,High School,3,9,7,23,58,0.0,6,58,Urban,Software Engineer,93943,0 +17223,Female,45,Bachelors,17,39,0,68,8,2.0,2,54,Urban,HR Executive,73069,0 +17224,Male,46,Bachelors,10,91,8,2,49,7.0,0,94,Urban,Manager,59343,0 +17225,Other,55,Diploma,6,21,54,79,86,1.0,1,73,Semi-Urban,Software Engineer,113072,0 +17226,Male,49,Diploma,1,75,59,15,57,8.0,7,49,Semi-Urban,Software Engineer,100145,0 +17227,Male,58,Masters,14,94,8,76,40,2.0,0,1,Urban,Software Engineer,39366,0 +17228,Female,50,Masters,19,78,48,35,67,3.0,5,91,Urban,Manager,120956,1 +17229,Male,33,Bachelors,0,88,4,91,28,6.0,0,21,Rural,Software Engineer,66627,0 +17230,Male,58,Diploma,4,34,1,49,25,4.0,0,80,Urban,Data Analyst,122239,0 +17231,Male,27,Bachelors,13,97,62,75,0,6.0,3,75,Semi-Urban,Data Analyst,103939,1 +17232,Female,33,Bachelors,3,39,10,68,32,0.0,1,16,Rural,Manager,149577,0 +17233,Female,59,PhD,3,96,36,10,40,5.0,6,43,Urban,Manager,138971,0 +17234,Female,21,High School,11,60,40,16,66,9.0,7,84,Semi-Urban,HR Executive,112222,0 +17235,Female,52,Masters,9,3,99,77,98,9.0,2,46,Urban,Data Analyst,95152,0 +17236,Female,43,Diploma,1,89,97,24,32,0.0,1,65,Semi-Urban,Software Engineer,117596,1 +17237,Male,37,Bachelors,14,18,48,44,88,8.0,6,27,Urban,ML Engineer,68363,0 +17238,Male,40,Bachelors,8,43,76,27,19,2.0,3,36,Urban,HR Executive,100727,0 +17239,Female,52,Bachelors,9,7,11,33,40,0.0,1,63,Urban,Software Engineer,112163,0 +17240,Other,31,Bachelors,9,40,91,8,95,0.0,4,82,Urban,Software Engineer,70947,0 +17241,Male,40,Masters,4,6,13,95,48,9.0,2,57,Urban,Data Analyst,125632,0 +17242,Male,48,Diploma,14,22,55,98,62,7.0,4,80,Urban,HR Executive,52205,1 +17243,Male,51,Diploma,9,40,49,84,42,9.0,6,43,Urban,HR Executive,106384,0 +17244,Male,24,Bachelors,11,62,92,87,40,9.0,2,20,Urban,Data Analyst,111912,1 +17245,Male,42,Masters,5,53,33,60,85,1.0,3,51,Semi-Urban,ML Engineer,93258,0 +17246,Female,24,Diploma,6,95,40,19,98,0.0,1,76,Semi-Urban,ML Engineer,52392,0 +17247,Male,58,Masters,15,15,73,58,53,4.0,1,10,Urban,Software Engineer,29933,0 +17248,Female,46,Diploma,8,9,79,72,13,1.0,5,8,Rural,Software Engineer,111027,0 +17249,Female,23,Bachelors,8,11,70,28,63,3.0,1,2,Rural,ML Engineer,141933,0 +17250,Other,54,High School,1,97,53,96,72,5.0,2,19,Urban,Data Analyst,65073,1 +17251,Male,41,Bachelors,8,20,46,42,11,6.0,4,94,Urban,Manager,145148,0 +17252,Male,35,Bachelors,10,56,44,84,14,4.0,6,34,Urban,ML Engineer,120102,0 +17253,Male,46,Masters,8,57,46,8,49,1.0,7,10,Rural,Manager,75026,0 +17254,Male,47,Masters,11,35,23,50,70,3.0,6,47,Semi-Urban,HR Executive,130609,0 +17255,Male,58,Bachelors,11,12,99,61,4,6.0,5,71,Urban,Manager,146541,1 +17256,Female,48,Bachelors,13,86,7,1,85,9.0,0,50,Urban,HR Executive,51441,0 +17257,Male,50,Masters,18,36,0,56,73,5.0,2,19,Urban,Manager,134228,0 +17258,Other,43,Diploma,8,59,87,23,74,9.0,7,19,Urban,Data Analyst,130022,0 +17259,Female,59,Bachelors,4,20,44,70,43,0.0,0,68,Rural,Data Analyst,83437,0 +17260,Female,57,Bachelors,12,17,42,60,3,5.0,0,41,Urban,Data Analyst,36827,0 +17261,Female,58,Diploma,15,87,2,71,52,5.0,1,3,Semi-Urban,Data Analyst,95593,0 +17262,Male,24,High School,4,22,25,63,68,4.0,7,2,Urban,Manager,48333,0 +17263,Female,53,Bachelors,8,55,96,40,73,6.0,6,11,Urban,HR Executive,86119,0 +17264,Male,37,Diploma,12,33,44,94,19,3.0,4,89,Urban,Manager,81650,1 +17265,Female,58,Masters,11,24,39,83,88,8.0,7,80,Rural,Manager,40049,0 +17266,Male,41,Masters,15,10,69,13,60,4.0,6,55,Urban,Software Engineer,26893,0 +17267,Male,39,Bachelors,4,35,23,0,49,2.0,5,2,Urban,ML Engineer,32991,0 +17268,Male,32,Diploma,18,7,99,7,91,9.0,3,9,Semi-Urban,Manager,83871,0 +17269,Male,52,Diploma,8,58,49,17,90,0.0,1,59,Semi-Urban,Software Engineer,112909,0 +17270,Male,57,Diploma,4,14,96,61,0,5.0,3,40,Urban,ML Engineer,55109,0 +17271,Male,24,Masters,5,28,15,55,50,2.0,1,16,Rural,Software Engineer,136060,0 +17272,Female,28,Bachelors,0,79,71,0,33,1.0,0,38,Urban,Manager,133362,0 +17273,Male,24,High School,13,8,32,46,6,0.0,7,94,Urban,Manager,94698,0 +17274,Male,42,Diploma,12,34,36,71,54,4.0,4,3,Semi-Urban,Software Engineer,148606,0 +17275,Male,30,Masters,16,5,46,59,51,8.0,6,18,Urban,Software Engineer,39859,0 +17276,Male,41,Masters,8,3,2,33,59,1.0,1,35,Urban,HR Executive,39425,0 +17277,Male,53,Masters,12,57,66,49,85,5.0,5,87,Semi-Urban,Manager,146864,1 +17278,Female,43,Masters,3,40,9,86,60,7.0,4,83,Semi-Urban,Data Analyst,51313,0 +17279,Male,36,Bachelors,5,99,99,56,50,3.0,6,91,Rural,Manager,31496,1 +17280,Male,50,Bachelors,2,80,18,60,91,5.0,3,50,Urban,ML Engineer,143739,0 +17281,Male,39,Masters,0,65,29,26,67,0.0,0,12,Urban,Software Engineer,113457,0 +17282,Male,27,Bachelors,7,43,77,27,32,6.0,7,27,Semi-Urban,Data Analyst,96533,0 +17283,Male,29,Diploma,12,55,75,39,97,1.0,6,15,Semi-Urban,ML Engineer,46512,0 +17284,Female,49,Diploma,18,62,39,3,63,2.0,6,18,Semi-Urban,ML Engineer,98569,0 +17285,Male,25,Masters,17,21,86,49,50,8.0,1,24,Urban,Data Analyst,45291,0 +17286,Male,38,Bachelors,16,75,26,51,8,8.0,0,64,Urban,Data Analyst,81950,0 +17287,Female,57,Bachelors,17,95,5,3,12,1.0,1,83,Rural,Software Engineer,58338,0 +17288,Male,57,High School,1,40,36,25,6,0.0,3,97,Urban,Data Analyst,113480,0 +17289,Female,22,High School,2,35,60,15,8,1.0,3,86,Urban,Data Analyst,48498,0 +17290,Male,57,Bachelors,18,45,92,71,8,4.0,1,79,Urban,Manager,140038,1 +17291,Male,47,PhD,16,89,82,83,28,0.0,2,94,Semi-Urban,Data Analyst,65383,1 +17292,Female,28,Masters,19,81,59,15,86,4.0,3,49,Rural,Data Analyst,146867,0 +17293,Male,45,PhD,14,21,22,8,15,5.0,6,16,Rural,Data Analyst,145071,0 +17294,Female,42,Diploma,0,75,48,21,69,5.0,1,68,Rural,Manager,123697,0 +17295,Male,44,Diploma,0,64,3,8,51,8.0,6,18,Urban,Software Engineer,38150,0 +17296,Female,55,Diploma,19,33,93,25,45,5.0,6,9,Rural,HR Executive,73944,0 +17297,Female,23,High School,15,34,22,12,4,3.0,0,52,Urban,ML Engineer,110293,0 +17298,Female,30,PhD,16,67,99,59,19,1.0,2,10,Urban,Data Analyst,79464,0 +17299,Female,35,Bachelors,13,98,7,56,45,2.0,4,75,Urban,Software Engineer,116619,0 +17300,Female,41,Diploma,12,85,43,52,63,8.0,5,75,Urban,Manager,127850,1 +17301,Male,39,Bachelors,16,23,78,6,22,4.0,0,66,Semi-Urban,HR Executive,129109,0 +17302,Male,41,High School,17,16,55,29,2,4.0,5,99,Urban,Data Analyst,146052,0 +17303,Male,57,Bachelors,8,15,69,82,5,9.0,5,54,Urban,HR Executive,119814,0 +17304,Male,28,Diploma,9,35,19,86,90,3.0,0,62,Semi-Urban,Software Engineer,47008,0 +17305,Female,37,High School,8,91,37,4,45,9.0,6,44,Rural,ML Engineer,62890,0 +17306,Male,48,Masters,19,7,68,96,53,9.0,7,23,Semi-Urban,Software Engineer,113111,0 +17307,Male,41,PhD,19,30,12,77,15,8.0,2,88,Rural,Software Engineer,70761,0 +17308,Female,28,Bachelors,8,40,31,1,9,4.0,1,30,Semi-Urban,Manager,69589,0 +17309,Male,31,High School,3,12,34,13,77,9.0,1,39,Urban,Manager,69816,0 +17310,Male,33,High School,15,40,26,33,83,9.0,7,83,Semi-Urban,Manager,93013,0 +17311,Male,35,High School,2,27,79,12,41,3.0,7,63,Semi-Urban,Software Engineer,102971,0 +17312,Male,48,PhD,2,58,57,8,10,9.0,2,23,Urban,Data Analyst,33372,0 +17313,Female,22,Diploma,13,50,93,31,53,9.0,4,16,Urban,Software Engineer,83467,0 +17314,Male,41,Bachelors,16,0,96,96,56,5.0,2,85,Urban,Manager,132410,1 +17315,Male,41,Bachelors,15,97,73,19,90,7.0,3,68,Semi-Urban,Data Analyst,128600,1 +17316,Female,47,Bachelors,3,37,87,6,15,5.0,6,8,Urban,HR Executive,51405,0 +17317,Male,35,Diploma,17,75,13,59,89,5.0,7,62,Urban,Software Engineer,61844,0 +17318,Female,48,Bachelors,6,11,65,44,69,7.0,2,77,Semi-Urban,ML Engineer,65366,0 +17319,Female,53,Bachelors,8,54,64,12,9,7.0,7,77,Rural,ML Engineer,29040,0 +17320,Male,27,Masters,17,31,49,81,16,3.0,6,42,Urban,ML Engineer,108608,0 +17321,Male,52,Diploma,12,88,75,78,62,9.0,7,38,Semi-Urban,ML Engineer,43104,1 +17322,Male,23,Bachelors,18,34,54,69,50,6.0,0,8,Urban,Data Analyst,134374,0 +17323,Female,23,Bachelors,15,62,69,60,78,8.0,0,98,Semi-Urban,HR Executive,49184,1 +17324,Male,36,Bachelors,12,71,92,99,38,6.0,3,76,Rural,Software Engineer,47399,1 +17325,Male,41,Diploma,11,60,52,47,47,0.0,1,7,Urban,Manager,60369,0 +17326,Female,29,Bachelors,19,43,29,39,18,7.0,2,55,Urban,Software Engineer,149078,0 +17327,Male,23,Bachelors,1,41,1,59,48,4.0,7,22,Urban,Data Analyst,55124,0 +17328,Male,50,Masters,5,56,59,58,67,8.0,0,91,Semi-Urban,Manager,49232,1 +17329,Female,28,Bachelors,3,93,64,81,94,8.0,2,29,Urban,ML Engineer,117100,1 +17330,Male,49,Diploma,5,0,23,99,70,9.0,5,42,Urban,Manager,69587,0 +17331,Female,58,Diploma,19,38,79,92,87,8.0,0,56,Urban,ML Engineer,92847,1 +17332,Female,34,High School,19,47,72,9,20,2.0,1,74,Semi-Urban,Data Analyst,41807,0 +17333,Male,43,Bachelors,7,57,83,15,60,2.0,4,4,Urban,Manager,110353,0 +17334,Female,58,Masters,0,49,94,54,21,7.0,3,44,Semi-Urban,HR Executive,81156,1 +17335,Male,48,Bachelors,0,19,48,96,55,1.0,2,59,Rural,Manager,97908,0 +17336,Other,48,Diploma,4,59,31,43,3,8.0,5,35,Urban,Manager,136897,0 +17337,Male,49,Bachelors,10,33,54,57,95,3.0,6,92,Urban,Data Analyst,85606,1 +17338,Male,36,High School,2,97,69,68,74,4.0,3,17,Urban,Manager,71483,1 +17339,Male,42,Masters,18,48,16,35,73,1.0,4,27,Urban,HR Executive,39747,0 +17340,Male,22,Masters,16,35,25,44,60,9.0,3,24,Urban,Manager,69617,0 +17341,Female,29,Diploma,10,40,95,82,49,5.0,7,26,Semi-Urban,HR Executive,71261,1 +17342,Female,24,Masters,5,69,19,91,18,5.0,4,40,Semi-Urban,ML Engineer,63038,0 +17343,Female,43,Diploma,16,64,35,46,79,5.0,6,35,Urban,Data Analyst,111658,0 +17344,Male,44,Bachelors,16,30,1,20,94,1.0,7,68,Semi-Urban,Data Analyst,104143,0 +17345,Male,23,Bachelors,5,92,88,93,13,9.0,6,60,Urban,ML Engineer,144232,1 +17346,Female,32,Bachelors,16,36,48,70,47,5.0,5,16,Urban,ML Engineer,125013,0 +17347,Male,49,Bachelors,10,93,82,47,21,8.0,6,83,Urban,Manager,41730,1 +17348,Female,42,Diploma,16,98,66,28,88,2.0,3,43,Urban,Software Engineer,119828,0 +17349,Female,39,High School,14,98,41,56,42,6.0,4,49,Semi-Urban,ML Engineer,59738,1 +17350,Male,36,Bachelors,19,48,50,84,53,1.0,2,34,Semi-Urban,Software Engineer,86540,0 +17351,Female,47,High School,1,75,70,88,43,1.0,6,57,Urban,ML Engineer,83140,1 +17352,Female,34,Diploma,11,99,10,4,61,6.0,6,40,Urban,Manager,68432,0 +17353,Female,49,Bachelors,14,10,60,60,31,9.0,2,61,Semi-Urban,Software Engineer,142998,0 +17354,Male,23,Diploma,12,79,77,69,64,4.0,4,93,Urban,Data Analyst,22908,1 +17355,Male,50,Diploma,7,72,16,33,52,2.0,3,22,Urban,Software Engineer,26309,0 +17356,Male,53,Bachelors,15,5,77,20,76,4.0,6,38,Urban,Data Analyst,111893,0 +17357,Male,46,Diploma,5,20,93,91,85,8.0,4,47,Semi-Urban,Software Engineer,137584,1 +17358,Male,23,Bachelors,8,26,67,47,8,0.0,3,72,Urban,Data Analyst,24583,0 +17359,Female,50,Diploma,11,56,88,22,33,6.0,3,79,Semi-Urban,HR Executive,123327,1 +17360,Female,36,Masters,4,22,44,64,28,8.0,2,53,Urban,Manager,125624,0 +17361,Male,25,Bachelors,13,64,74,64,99,2.0,1,74,Urban,Data Analyst,103231,1 +17362,Male,51,Masters,8,30,69,3,2,6.0,0,81,Urban,HR Executive,146238,0 +17363,Female,56,Bachelors,11,52,0,50,61,4.0,1,37,Urban,Manager,119990,0 +17364,Male,46,Bachelors,1,62,70,13,96,7.0,6,48,Urban,HR Executive,86595,0 +17365,Female,50,Diploma,15,40,68,41,71,5.0,5,18,Urban,Manager,25866,0 +17366,Other,47,High School,15,98,19,29,72,0.0,3,89,Urban,ML Engineer,125492,0 +17367,Female,33,Bachelors,13,55,4,55,71,5.0,1,31,Urban,Manager,82835,0 +17368,Other,31,Bachelors,18,56,30,93,8,9.0,1,71,Semi-Urban,Data Analyst,20101,1 +17369,Female,46,Bachelors,10,45,43,56,70,1.0,3,23,Semi-Urban,Manager,116388,0 +17370,Male,58,PhD,10,28,56,92,61,4.0,4,46,Rural,HR Executive,21821,0 +17371,Male,53,Diploma,5,39,6,89,95,7.0,1,93,Urban,Manager,134973,0 +17372,Male,49,Masters,19,43,75,17,30,1.0,4,57,Urban,HR Executive,104694,0 +17373,Male,42,Masters,5,25,28,8,12,7.0,4,18,Semi-Urban,ML Engineer,39106,0 +17374,Female,47,Bachelors,7,18,81,60,20,2.0,6,23,Rural,Data Analyst,62207,0 +17375,Male,53,Bachelors,4,84,45,41,72,4.0,6,86,Rural,HR Executive,149060,1 +17376,Female,36,Masters,4,93,19,0,25,8.0,2,79,Semi-Urban,Software Engineer,140074,0 +17377,Male,36,Bachelors,1,95,72,51,8,0.0,6,64,Urban,HR Executive,51527,1 +17378,Male,28,Diploma,9,78,53,92,24,3.0,6,9,Urban,HR Executive,54137,0 +17379,Other,24,Bachelors,11,11,25,15,57,5.0,2,22,Semi-Urban,Manager,36037,0 +17380,Male,57,Bachelors,4,1,46,81,50,4.0,6,1,Urban,ML Engineer,146459,0 +17381,Female,30,Diploma,2,58,78,56,65,4.0,4,64,Rural,Data Analyst,27691,1 +17382,Female,52,Bachelors,11,7,92,38,1,5.0,0,69,Urban,ML Engineer,89717,0 +17383,Male,27,High School,18,70,98,62,36,4.0,6,2,Urban,HR Executive,103362,0 +17384,Male,37,Diploma,11,95,3,95,76,1.0,5,8,Semi-Urban,Software Engineer,52309,0 +17385,Male,36,Diploma,2,42,39,26,28,4.0,7,35,Semi-Urban,ML Engineer,21049,0 +17386,Female,55,Diploma,15,8,8,20,19,6.0,5,97,Urban,Software Engineer,36856,0 +17387,Female,31,Bachelors,13,27,35,54,98,6.0,1,95,Rural,Manager,44181,0 +17388,Male,30,PhD,16,88,60,90,47,1.0,7,93,Rural,HR Executive,64051,1 +17389,Female,48,Bachelors,16,72,64,7,62,6.0,4,36,Rural,Data Analyst,113434,0 +17390,Male,37,Bachelors,2,45,82,12,62,0.0,1,80,Urban,Data Analyst,44845,0 +17391,Female,58,Masters,9,49,47,17,12,0.0,2,12,Urban,HR Executive,72987,0 +17392,Female,36,Diploma,2,49,16,48,52,6.0,0,50,Semi-Urban,HR Executive,72415,0 +17393,Female,41,Bachelors,1,11,16,59,15,0.0,5,89,Semi-Urban,Manager,109839,0 +17394,Female,58,Bachelors,8,5,18,64,32,5.0,2,87,Rural,Software Engineer,54102,0 +17395,Male,38,Bachelors,6,11,47,27,60,7.0,4,6,Urban,Software Engineer,131654,0 +17396,Other,24,Masters,2,29,65,13,51,5.0,4,30,Urban,Manager,77322,0 +17397,Male,59,High School,17,66,55,20,54,2.0,4,49,Urban,Manager,92495,0 +17398,Female,25,High School,3,34,36,1,89,4.0,0,14,Urban,Data Analyst,117505,0 +17399,Male,48,Bachelors,18,80,90,48,29,1.0,2,62,Urban,Software Engineer,131185,1 +17400,Other,59,Bachelors,18,72,55,4,45,2.0,6,24,Urban,HR Executive,41387,0 +17401,Female,57,Bachelors,17,3,59,18,45,7.0,0,75,Semi-Urban,ML Engineer,128489,0 +17402,Female,40,High School,8,83,34,33,62,1.0,1,99,Urban,Data Analyst,45885,1 +17403,Male,30,Bachelors,1,65,43,78,2,7.0,3,75,Urban,Software Engineer,73257,1 +17404,Female,30,Diploma,5,86,31,25,12,2.0,7,9,Urban,Software Engineer,72196,0 +17405,Female,38,Diploma,15,6,44,27,85,2.0,6,9,Urban,ML Engineer,144565,0 +17406,Female,21,High School,2,28,45,74,81,4.0,3,21,Urban,ML Engineer,41814,0 +17407,Male,57,Bachelors,1,14,73,2,64,1.0,0,82,Urban,Data Analyst,125712,0 +17408,Male,51,Bachelors,13,45,11,81,57,5.0,6,73,Urban,Software Engineer,93778,0 +17409,Male,59,Masters,9,13,92,0,54,7.0,6,96,Urban,Data Analyst,44236,0 +17410,Male,38,Bachelors,6,56,88,70,44,4.0,7,68,Urban,Data Analyst,106608,1 +17411,Male,43,Diploma,18,5,90,61,85,6.0,1,67,Rural,HR Executive,119955,0 +17412,Male,36,Bachelors,15,9,3,40,47,1.0,2,26,Urban,Software Engineer,73285,0 +17413,Male,46,Diploma,5,19,26,66,6,6.0,2,22,Semi-Urban,Manager,131619,0 +17414,Male,55,Diploma,10,68,41,61,42,2.0,3,32,Urban,Manager,91597,0 +17415,Male,35,Bachelors,16,19,17,78,40,7.0,1,82,Urban,HR Executive,127854,0 +17416,Female,55,Bachelors,6,36,63,74,95,0.0,5,45,Rural,HR Executive,26800,0 +17417,Male,34,Bachelors,10,91,79,50,96,2.0,0,7,Urban,ML Engineer,142781,0 +17418,Male,52,Bachelors,3,70,81,44,8,0.0,5,51,Urban,ML Engineer,132322,1 +17419,Male,36,High School,16,16,75,39,45,3.0,6,79,Urban,Software Engineer,143933,0 +17420,Female,25,Bachelors,1,87,76,31,25,0.0,3,85,Urban,ML Engineer,46915,1 +17421,Female,50,Bachelors,11,25,7,9,99,1.0,4,83,Rural,Software Engineer,125804,0 +17422,Male,36,High School,10,10,84,32,54,6.0,1,37,Semi-Urban,HR Executive,50347,0 +17423,Male,56,Masters,6,0,60,11,12,3.0,5,77,Rural,Data Analyst,25599,0 +17424,Other,23,Bachelors,1,70,61,87,1,7.0,5,52,Semi-Urban,ML Engineer,63489,1 +17425,Male,52,Diploma,13,7,49,25,92,5.0,4,95,Urban,Manager,122502,0 +17426,Male,21,High School,6,23,42,21,59,3.0,3,95,Semi-Urban,HR Executive,139189,0 +17427,Male,40,Bachelors,13,66,59,16,48,7.0,6,56,Urban,Software Engineer,81025,0 +17428,Male,53,Masters,6,14,4,7,67,8.0,0,59,Semi-Urban,ML Engineer,104893,0 +17429,Other,51,High School,17,4,64,93,90,7.0,6,31,Urban,Data Analyst,116978,0 +17430,Male,40,Bachelors,4,31,49,74,11,3.0,1,33,Urban,HR Executive,64335,0 +17431,Female,27,Masters,8,7,92,97,10,3.0,7,63,Semi-Urban,ML Engineer,62174,1 +17432,Other,41,Bachelors,10,50,55,24,25,8.0,7,53,Semi-Urban,Data Analyst,32214,0 +17433,Male,27,Bachelors,18,95,85,90,1,6.0,5,21,Urban,ML Engineer,22970,1 +17434,Male,59,Diploma,1,48,17,73,69,0.0,2,61,Rural,HR Executive,93574,0 +17435,Male,49,Bachelors,10,67,23,49,85,6.0,4,3,Urban,ML Engineer,40991,0 +17436,Male,38,Bachelors,16,20,92,38,41,4.0,4,94,Urban,ML Engineer,25513,1 +17437,Male,35,Diploma,11,34,57,2,45,3.0,3,42,Semi-Urban,Manager,88455,0 +17438,Female,43,Bachelors,3,9,28,37,24,1.0,6,46,Semi-Urban,ML Engineer,53918,0 +17439,Male,39,Bachelors,19,89,11,91,65,4.0,3,90,Urban,Data Analyst,101418,1 +17440,Female,35,Bachelors,10,16,45,23,87,3.0,3,86,Urban,Data Analyst,24859,0 +17441,Male,38,Diploma,6,3,33,95,43,3.0,5,13,Rural,ML Engineer,79789,0 +17442,Female,27,High School,14,66,62,57,72,5.0,1,47,Rural,Manager,120889,0 +17443,Female,55,Masters,4,77,3,59,51,1.0,2,45,Rural,Manager,114069,0 +17444,Male,38,Masters,0,16,98,3,5,4.0,1,16,Urban,Data Analyst,148532,0 +17445,Male,58,Bachelors,0,22,21,84,37,7.0,2,90,Urban,ML Engineer,89717,0 +17446,Male,36,Diploma,8,24,48,50,62,2.0,7,12,Rural,Data Analyst,104086,0 +17447,Male,45,Bachelors,3,33,31,78,94,8.0,0,60,Urban,Manager,81426,0 +17448,Male,47,Bachelors,9,38,4,11,13,4.0,4,63,Rural,ML Engineer,110029,0 +17449,Male,43,Bachelors,12,58,55,57,35,1.0,1,17,Rural,ML Engineer,67159,0 +17450,Male,38,Bachelors,11,8,86,82,28,2.0,1,10,Semi-Urban,ML Engineer,148431,0 +17451,Other,33,Bachelors,9,44,16,92,21,3.0,2,72,Rural,Manager,102915,0 +17452,Male,23,Bachelors,12,93,70,2,22,4.0,0,64,Urban,Manager,83653,0 +17453,Male,49,High School,4,98,68,22,98,2.0,5,13,Semi-Urban,Manager,81839,0 +17454,Male,31,Bachelors,12,93,98,65,16,8.0,1,85,Semi-Urban,ML Engineer,49771,1 +17455,Male,50,High School,12,52,27,15,64,4.0,1,71,Urban,Manager,91495,0 +17456,Male,22,Bachelors,4,52,47,49,29,7.0,2,71,Urban,HR Executive,140368,0 +17457,Female,44,Masters,17,14,16,31,0,9.0,4,74,Rural,Software Engineer,124730,0 +17458,Male,58,Masters,5,29,97,73,77,2.0,3,77,Urban,HR Executive,129258,1 +17459,Male,25,Diploma,10,69,89,80,73,8.0,7,61,Urban,Manager,89224,1 +17460,Male,46,High School,3,60,26,52,98,5.0,3,28,Semi-Urban,ML Engineer,29958,0 +17461,Male,33,Masters,9,40,74,74,6,0.0,0,93,Rural,Data Analyst,30662,1 +17462,Male,38,Bachelors,2,32,22,55,68,0.0,7,91,Urban,Data Analyst,149367,0 +17463,Female,36,Bachelors,8,72,61,81,33,6.0,3,43,Urban,Data Analyst,103617,1 +17464,Male,48,Bachelors,11,88,85,7,20,2.0,4,0,Urban,Data Analyst,21690,0 +17465,Male,34,Bachelors,0,94,14,95,57,9.0,5,12,Rural,Manager,84573,0 +17466,Female,22,Bachelors,15,33,69,32,98,0.0,3,75,Urban,Manager,37926,0 +17467,Male,26,Bachelors,8,63,47,42,38,6.0,2,6,Urban,HR Executive,85794,0 +17468,Male,25,High School,4,17,85,48,45,2.0,2,59,Urban,HR Executive,54173,0 +17469,Other,35,Masters,19,76,21,87,51,7.0,4,64,Semi-Urban,ML Engineer,60330,1 +17470,Male,38,PhD,11,58,26,64,99,5.0,7,0,Urban,HR Executive,38695,0 +17471,Female,53,Bachelors,19,18,99,74,92,2.0,0,11,Urban,Software Engineer,137522,0 +17472,Male,55,Masters,15,16,38,23,79,8.0,2,43,Urban,Software Engineer,138717,0 +17473,Male,45,High School,4,46,99,29,20,0.0,3,5,Urban,Manager,24917,0 +17474,Male,46,Masters,12,45,80,88,52,6.0,6,56,Semi-Urban,Manager,134813,1 +17475,Male,42,Bachelors,16,74,76,3,49,5.0,3,87,Urban,ML Engineer,54797,1 +17476,Male,56,Masters,10,17,5,10,23,4.0,7,8,Urban,Manager,141260,0 +17477,Male,31,Bachelors,5,8,2,29,32,0.0,2,88,Urban,Software Engineer,102756,0 +17478,Female,31,Diploma,12,31,71,26,91,6.0,7,63,Rural,ML Engineer,123856,0 +17479,Female,59,Bachelors,1,86,23,6,14,7.0,0,92,Urban,Manager,29841,0 +17480,Male,41,Diploma,14,82,74,52,93,8.0,1,13,Rural,Manager,92697,0 +17481,Male,45,High School,12,51,46,54,57,1.0,5,11,Rural,Manager,109797,0 +17482,Female,46,Diploma,5,19,16,38,60,9.0,2,42,Urban,ML Engineer,66237,0 +17483,Female,48,Masters,5,34,28,36,14,8.0,6,39,Semi-Urban,Software Engineer,47703,0 +17484,Male,33,Diploma,2,86,68,64,12,6.0,7,42,Urban,Data Analyst,120790,1 +17485,Female,43,Bachelors,7,91,14,85,22,4.0,4,81,Urban,Manager,114173,1 +17486,Male,38,Bachelors,16,42,14,40,47,3.0,3,35,Urban,Software Engineer,98544,0 +17487,Male,52,Bachelors,13,98,49,62,16,8.0,4,58,Semi-Urban,HR Executive,50674,1 +17488,Male,45,Bachelors,4,1,29,36,20,5.0,6,43,Semi-Urban,Software Engineer,57229,0 +17489,Female,51,Masters,0,68,82,61,4,1.0,7,5,Urban,Manager,33589,0 +17490,Female,32,Bachelors,11,5,10,21,32,6.0,5,20,Urban,Software Engineer,68315,0 +17491,Female,25,Bachelors,3,9,6,78,16,1.0,2,90,Urban,Software Engineer,114327,0 +17492,Male,33,PhD,15,11,58,92,7,4.0,0,97,Rural,HR Executive,29590,1 +17493,Female,45,Masters,0,11,6,45,86,3.0,6,80,Semi-Urban,ML Engineer,55215,0 +17494,Male,59,High School,7,70,11,53,33,9.0,4,37,Urban,Data Analyst,48224,0 +17495,Male,29,Bachelors,0,22,81,57,97,1.0,6,44,Urban,Data Analyst,81928,0 +17496,Male,59,PhD,9,99,44,11,67,8.0,0,15,Urban,HR Executive,71159,0 +17497,Male,58,Diploma,0,92,75,49,64,5.0,6,47,Urban,Manager,87131,1 +17498,Female,24,High School,9,19,8,92,17,1.0,6,52,Semi-Urban,Software Engineer,63048,0 +17499,Male,46,High School,8,92,47,78,44,3.0,4,10,Urban,Software Engineer,110495,0 +17500,Female,36,High School,10,95,97,13,37,7.0,0,10,Semi-Urban,Manager,37600,0 +17501,Male,47,Masters,7,65,48,93,11,1.0,1,58,Urban,HR Executive,23685,1 +17502,Male,24,Bachelors,19,58,28,33,99,9.0,6,80,Urban,HR Executive,124344,0 +17503,Female,49,Masters,19,54,65,53,81,5.0,2,14,Rural,Data Analyst,142400,0 +17504,Male,28,Bachelors,12,3,2,28,98,4.0,2,48,Urban,ML Engineer,99795,0 +17505,Female,38,High School,11,58,52,41,59,2.0,3,20,Rural,Manager,134529,0 +17506,Female,53,Bachelors,4,59,36,20,57,6.0,5,61,Urban,Software Engineer,56147,0 +17507,Male,51,High School,1,77,12,29,79,8.0,1,67,Rural,Manager,139728,0 +17508,Female,44,Bachelors,10,47,71,21,27,6.0,6,66,Urban,Software Engineer,46021,0 +17509,Male,59,Bachelors,8,82,57,72,50,1.0,1,22,Urban,Manager,91973,0 +17510,Female,58,High School,3,62,36,39,20,5.0,4,16,Rural,Manager,47976,0 +17511,Male,56,Diploma,9,72,86,48,97,8.0,5,35,Rural,Software Engineer,127411,1 +17512,Male,24,Bachelors,4,78,54,58,84,9.0,1,61,Urban,Manager,47428,1 +17513,Male,52,Bachelors,14,20,47,48,29,4.0,7,54,Urban,Manager,146270,0 +17514,Male,52,Diploma,17,50,20,50,73,8.0,7,38,Rural,Manager,35323,0 +17515,Female,45,Masters,4,55,4,51,35,4.0,2,70,Semi-Urban,ML Engineer,82501,0 +17516,Female,40,Masters,13,16,19,65,57,2.0,1,10,Urban,Manager,93195,0 +17517,Female,44,Bachelors,18,13,98,31,19,8.0,6,47,Urban,HR Executive,138976,0 +17518,Male,41,High School,6,34,80,40,52,6.0,3,14,Semi-Urban,HR Executive,46500,0 +17519,Female,36,Bachelors,7,58,38,72,42,5.0,3,99,Urban,HR Executive,88842,1 +17520,Male,49,Bachelors,13,7,80,65,89,6.0,6,45,Urban,Manager,130599,0 +17521,Male,31,Bachelors,8,73,11,46,33,0.0,4,6,Rural,Manager,72066,0 +17522,Male,29,High School,18,45,14,50,57,3.0,2,57,Rural,ML Engineer,66436,0 +17523,Male,37,Bachelors,9,69,93,79,2,4.0,4,23,Urban,Data Analyst,147839,1 +17524,Female,58,Masters,18,81,91,24,87,1.0,7,69,Rural,Software Engineer,33094,1 +17525,Male,28,Bachelors,1,33,28,46,36,8.0,0,92,Urban,HR Executive,32454,0 +17526,Male,21,Bachelors,9,96,15,82,67,7.0,1,53,Urban,HR Executive,65857,1 +17527,Female,24,Bachelors,3,21,43,85,41,8.0,0,25,Urban,Manager,136304,0 +17528,Female,39,Bachelors,4,82,78,39,67,0.0,1,35,Urban,Manager,137312,0 +17529,Female,32,Masters,12,6,31,48,29,8.0,3,46,Urban,ML Engineer,63998,0 +17530,Male,54,Bachelors,0,93,67,62,90,0.0,0,69,Rural,HR Executive,76055,1 +17531,Female,28,High School,11,99,2,63,16,4.0,1,2,Urban,HR Executive,42950,0 +17532,Male,42,PhD,17,72,20,27,75,4.0,3,65,Urban,Manager,93553,0 +17533,Male,44,Bachelors,18,44,50,95,82,3.0,5,76,Rural,Manager,102210,1 +17534,Female,29,Masters,11,49,41,27,28,1.0,5,40,Semi-Urban,Data Analyst,22646,0 +17535,Female,46,High School,0,74,23,60,88,5.0,6,16,Urban,HR Executive,24537,0 +17536,Female,32,High School,17,86,10,92,49,5.0,7,17,Urban,HR Executive,28162,0 +17537,Male,42,Diploma,12,37,84,50,77,8.0,0,40,Urban,ML Engineer,71659,0 +17538,Female,34,Bachelors,1,62,46,89,17,4.0,0,93,Urban,Manager,120461,1 +17539,Female,28,Diploma,9,98,55,47,88,4.0,0,46,Rural,Manager,20779,1 +17540,Male,48,High School,10,4,87,96,80,1.0,6,99,Rural,Manager,48856,1 +17541,Male,29,Bachelors,7,2,73,66,45,9.0,7,77,Semi-Urban,HR Executive,122045,0 +17542,Female,59,High School,9,40,93,99,73,2.0,5,43,Urban,Manager,53811,1 +17543,Male,59,Bachelors,15,39,84,70,46,4.0,2,54,Urban,Software Engineer,145189,1 +17544,Other,21,Diploma,5,19,17,54,43,0.0,0,13,Semi-Urban,ML Engineer,52930,0 +17545,Male,54,Masters,13,26,82,1,74,5.0,3,38,Urban,Data Analyst,136809,0 +17546,Female,46,Bachelors,7,30,46,81,67,1.0,0,60,Urban,HR Executive,115586,0 +17547,Female,25,High School,14,85,20,28,57,2.0,1,29,Semi-Urban,Software Engineer,93842,0 +17548,Male,43,Masters,7,21,62,0,16,1.0,2,8,Semi-Urban,Manager,122317,0 +17549,Female,30,Masters,13,56,35,6,52,8.0,5,71,Urban,Software Engineer,37537,0 +17550,Male,27,Diploma,6,0,28,86,79,7.0,0,21,Urban,ML Engineer,99770,0 +17551,Male,53,Bachelors,5,53,2,17,59,8.0,7,62,Semi-Urban,Manager,21581,0 +17552,Male,30,High School,3,50,89,97,50,4.0,6,66,Rural,ML Engineer,113952,1 +17553,Male,30,Diploma,7,49,47,96,67,8.0,1,66,Urban,Data Analyst,110589,1 +17554,Female,26,Bachelors,19,96,21,34,95,8.0,5,5,Urban,Software Engineer,72899,0 +17555,Female,52,High School,7,1,26,54,76,0.0,5,13,Urban,HR Executive,30191,0 +17556,Male,22,Bachelors,2,13,51,18,77,6.0,3,41,Semi-Urban,HR Executive,148490,0 +17557,Male,34,Diploma,2,17,94,78,72,4.0,1,88,Urban,Manager,130455,1 +17558,Male,29,Diploma,13,63,43,13,55,6.0,3,73,Urban,Data Analyst,63727,0 +17559,Female,38,Masters,13,86,10,54,35,5.0,6,77,Urban,Data Analyst,113495,0 +17560,Other,31,High School,9,96,81,1,7,4.0,6,9,Semi-Urban,Manager,35275,0 +17561,Female,37,Bachelors,3,10,99,80,74,4.0,7,60,Urban,Manager,80642,1 +17562,Female,47,Bachelors,17,47,58,90,82,9.0,2,88,Semi-Urban,ML Engineer,33008,1 +17563,Male,25,Bachelors,12,76,30,83,68,7.0,1,32,Urban,HR Executive,136369,0 +17564,Male,56,Bachelors,0,72,62,81,34,1.0,2,87,Urban,Software Engineer,76169,1 +17565,Female,54,Masters,16,55,77,5,90,2.0,2,35,Rural,HR Executive,71766,0 +17566,Female,47,Masters,16,12,37,20,26,5.0,7,29,Rural,Data Analyst,104522,0 +17567,Female,38,High School,7,53,82,20,73,1.0,0,89,Urban,HR Executive,38946,1 +17568,Female,21,Bachelors,4,20,40,21,19,7.0,0,71,Urban,ML Engineer,112462,0 +17569,Female,36,Masters,3,67,43,49,52,2.0,6,63,Urban,HR Executive,46637,0 +17570,Female,59,Bachelors,7,44,49,7,33,1.0,5,16,Rural,Data Analyst,27263,0 +17571,Female,39,Bachelors,13,80,2,91,67,2.0,3,56,Urban,Manager,122284,0 +17572,Other,53,Diploma,2,27,55,4,14,6.0,4,32,Urban,Manager,130602,0 +17573,Male,50,Masters,8,45,44,88,15,4.0,6,10,Semi-Urban,Software Engineer,74383,0 +17574,Male,47,Bachelors,12,82,51,34,45,4.0,2,79,Semi-Urban,Manager,115383,1 +17575,Male,52,Bachelors,15,28,15,70,21,5.0,6,1,Semi-Urban,Software Engineer,143530,0 +17576,Female,49,Diploma,3,19,39,7,45,9.0,5,98,Rural,HR Executive,132891,0 +17577,Male,28,Masters,2,26,93,34,52,1.0,4,9,Semi-Urban,Data Analyst,37863,0 +17578,Male,55,Masters,19,46,50,10,86,5.0,5,63,Semi-Urban,ML Engineer,93712,0 +17579,Male,55,Bachelors,0,61,20,1,28,4.0,6,38,Urban,HR Executive,41535,0 +17580,Female,34,Diploma,5,86,57,64,70,2.0,4,4,Urban,HR Executive,101662,0 +17581,Male,57,Masters,5,44,72,63,45,1.0,0,34,Urban,Software Engineer,120230,0 +17582,Male,58,Diploma,1,9,9,29,8,2.0,5,61,Urban,Manager,132411,0 +17583,Male,58,Diploma,5,96,28,28,30,6.0,6,63,Urban,Software Engineer,148758,0 +17584,Female,52,Diploma,12,48,71,36,12,2.0,7,75,Rural,HR Executive,59240,0 +17585,Male,30,Bachelors,10,78,6,69,63,9.0,3,26,Semi-Urban,ML Engineer,144878,0 +17586,Male,49,Bachelors,16,40,97,5,45,6.0,4,0,Urban,Manager,138882,0 +17587,Female,51,Diploma,5,62,27,34,47,5.0,7,51,Rural,Data Analyst,51086,0 +17588,Male,28,High School,1,36,89,37,15,7.0,3,93,Rural,Software Engineer,29541,1 +17589,Male,43,Bachelors,18,49,67,46,56,0.0,2,44,Rural,Data Analyst,112868,0 +17590,Female,26,Masters,0,92,20,66,90,1.0,4,36,Urban,Software Engineer,72825,0 +17591,Male,41,PhD,8,37,21,37,30,7.0,6,32,Urban,Manager,72875,0 +17592,Female,25,Diploma,3,62,93,60,11,5.0,5,70,Rural,ML Engineer,99711,1 +17593,Male,57,PhD,19,22,39,42,33,5.0,6,53,Urban,ML Engineer,102570,0 +17594,Male,25,Diploma,12,44,45,79,2,6.0,4,94,Semi-Urban,Software Engineer,100264,1 +17595,Female,26,Diploma,8,70,44,43,79,2.0,1,72,Urban,Manager,49178,0 +17596,Female,25,High School,14,4,16,11,35,3.0,7,95,Urban,Software Engineer,64876,0 +17597,Male,21,Bachelors,5,33,77,17,23,3.0,7,14,Urban,Manager,123653,0 +17598,Male,47,Bachelors,8,57,96,4,40,2.0,6,64,Urban,Software Engineer,64139,0 +17599,Female,32,Diploma,1,65,83,84,67,0.0,3,44,Urban,HR Executive,113931,1 +17600,Female,23,PhD,11,34,92,80,90,8.0,3,95,Semi-Urban,ML Engineer,110922,1 +17601,Male,26,Masters,12,9,33,14,18,2.0,1,13,Urban,Data Analyst,58329,0 +17602,Female,21,Bachelors,2,45,24,22,25,7.0,0,4,Semi-Urban,Data Analyst,64079,0 +17603,Male,30,Diploma,18,13,55,18,75,0.0,2,51,Urban,Manager,121648,0 +17604,Male,30,High School,17,64,68,2,50,9.0,6,81,Urban,HR Executive,126649,0 +17605,Male,28,Bachelors,12,96,39,95,47,1.0,0,41,Urban,ML Engineer,81098,1 +17606,Male,32,Bachelors,15,10,23,31,82,9.0,3,77,Semi-Urban,Data Analyst,85730,0 +17607,Male,45,Bachelors,0,31,6,71,11,9.0,2,45,Urban,Software Engineer,53613,0 +17608,Male,54,Bachelors,1,49,76,40,81,6.0,2,80,Rural,Data Analyst,31929,1 +17609,Male,44,Bachelors,16,23,58,64,85,7.0,7,15,Urban,Data Analyst,52086,0 +17610,Male,21,Bachelors,2,75,75,12,50,8.0,3,88,Urban,Data Analyst,55565,1 +17611,Male,24,Bachelors,5,52,51,16,21,5.0,5,27,Urban,Data Analyst,66170,0 +17612,Male,33,Masters,3,40,1,19,97,6.0,5,5,Semi-Urban,Data Analyst,42359,0 +17613,Female,43,Masters,5,61,94,96,43,6.0,0,14,Rural,Data Analyst,59158,1 +17614,Male,31,Bachelors,2,86,19,97,63,0.0,0,42,Urban,ML Engineer,91083,1 +17615,Female,56,Diploma,9,69,49,80,30,5.0,6,22,Urban,Manager,118480,0 +17616,Male,39,Masters,5,2,1,42,99,3.0,4,39,Urban,Data Analyst,63963,0 +17617,Male,25,Masters,12,92,57,84,71,5.0,2,9,Semi-Urban,Manager,61080,1 +17618,Male,39,Diploma,18,97,19,5,66,0.0,3,66,Semi-Urban,HR Executive,110722,0 +17619,Other,23,Bachelors,4,68,13,29,95,9.0,2,57,Urban,Manager,116357,0 +17620,Male,26,High School,7,16,64,0,32,1.0,3,10,Urban,Software Engineer,75215,0 +17621,Male,25,Diploma,11,9,68,33,11,1.0,6,69,Semi-Urban,ML Engineer,32776,0 +17622,Female,57,High School,7,18,77,97,83,3.0,2,58,Urban,Data Analyst,21127,1 +17623,Female,50,High School,6,4,6,94,97,7.0,4,93,Urban,HR Executive,34915,0 +17624,Other,53,Bachelors,11,42,51,32,24,1.0,1,10,Urban,Manager,33170,0 +17625,Male,58,Masters,1,4,64,91,71,3.0,1,83,Semi-Urban,Software Engineer,84807,1 +17626,Male,30,PhD,18,36,5,23,1,2.0,2,16,Semi-Urban,Software Engineer,75208,0 +17627,Female,47,Diploma,9,60,50,63,77,2.0,7,44,Rural,Software Engineer,149010,0 +17628,Male,59,High School,11,11,80,46,91,0.0,4,0,Semi-Urban,Manager,45585,0 +17629,Female,26,Diploma,13,56,72,98,35,6.0,5,42,Rural,HR Executive,26639,1 +17630,Female,42,High School,6,36,92,21,68,2.0,1,94,Urban,Data Analyst,135375,1 +17631,Female,43,Masters,18,27,17,97,85,5.0,1,50,Semi-Urban,HR Executive,122277,0 +17632,Male,35,Diploma,17,11,54,26,63,7.0,3,11,Urban,ML Engineer,143522,0 +17633,Male,27,High School,19,20,46,80,43,8.0,4,95,Urban,Data Analyst,23976,1 +17634,Female,24,Diploma,8,53,54,19,51,5.0,4,29,Semi-Urban,Software Engineer,134771,0 +17635,Male,21,Bachelors,1,57,25,91,67,2.0,1,50,Semi-Urban,Manager,55603,0 +17636,Male,40,Bachelors,7,58,60,21,30,9.0,5,33,Urban,ML Engineer,21624,0 +17637,Male,22,Bachelors,4,55,58,56,85,5.0,5,70,Semi-Urban,HR Executive,116925,1 +17638,Male,23,Bachelors,18,48,17,38,29,9.0,3,31,Urban,Manager,108575,0 +17639,Male,57,Diploma,6,3,63,72,92,8.0,5,81,Urban,HR Executive,149343,0 +17640,Female,36,Diploma,19,20,35,6,86,3.0,2,39,Semi-Urban,Manager,84955,0 +17641,Male,32,Bachelors,1,33,24,60,28,5.0,0,2,Urban,ML Engineer,115832,0 +17642,Male,46,Masters,10,87,96,30,82,0.0,3,92,Urban,Manager,23697,1 +17643,Male,55,Masters,15,75,48,81,67,7.0,7,68,Rural,Software Engineer,95475,1 +17644,Male,58,Masters,9,86,37,69,76,5.0,5,89,Urban,Data Analyst,98851,1 +17645,Other,42,Masters,13,70,49,96,30,1.0,6,44,Rural,HR Executive,114774,1 +17646,Female,50,Diploma,0,53,79,96,89,9.0,3,0,Urban,HR Executive,101186,0 +17647,Male,50,Bachelors,15,38,44,24,35,1.0,1,1,Rural,HR Executive,56799,0 +17648,Female,37,Bachelors,10,42,46,72,5,0.0,4,49,Rural,HR Executive,145264,0 +17649,Male,26,Diploma,13,79,0,85,1,0.0,2,27,Semi-Urban,HR Executive,76864,0 +17650,Other,50,High School,18,25,38,61,11,3.0,2,38,Semi-Urban,Software Engineer,25849,0 +17651,Male,32,Diploma,13,37,39,28,7,7.0,5,36,Semi-Urban,ML Engineer,149365,0 +17652,Male,39,Masters,17,63,46,4,43,0.0,4,83,Urban,Data Analyst,65100,0 +17653,Male,43,Bachelors,7,66,73,79,21,7.0,1,44,Rural,ML Engineer,21105,1 +17654,Female,28,Bachelors,13,28,41,67,22,7.0,0,67,Urban,HR Executive,98770,0 +17655,Male,59,Masters,1,51,40,87,81,4.0,7,49,Urban,HR Executive,106039,0 +17656,Female,28,High School,0,75,16,3,61,9.0,1,22,Semi-Urban,HR Executive,77846,0 +17657,Male,43,Bachelors,7,24,81,87,84,5.0,4,62,Semi-Urban,ML Engineer,102260,1 +17658,Female,58,High School,1,38,49,36,14,4.0,3,25,Rural,HR Executive,112920,0 +17659,Male,54,PhD,11,79,49,71,42,3.0,5,91,Urban,Data Analyst,76554,1 +17660,Female,46,Bachelors,9,80,8,50,84,3.0,7,28,Semi-Urban,HR Executive,138676,0 +17661,Male,29,Bachelors,0,30,14,0,57,1.0,2,79,Urban,Data Analyst,56339,0 +17662,Male,23,Diploma,9,45,28,76,38,3.0,3,95,Urban,Software Engineer,44232,1 +17663,Other,25,Bachelors,15,98,59,11,62,9.0,7,13,Urban,HR Executive,38159,0 +17664,Other,42,High School,13,88,41,0,89,7.0,3,0,Urban,HR Executive,49546,0 +17665,Female,51,Masters,4,98,62,44,64,0.0,0,61,Rural,Software Engineer,114587,1 +17666,Male,36,Bachelors,7,4,5,63,87,2.0,5,81,Urban,Manager,31483,0 +17667,Male,55,Masters,4,75,74,5,42,7.0,0,55,Rural,HR Executive,60445,0 +17668,Male,44,PhD,7,40,58,11,77,0.0,2,69,Urban,ML Engineer,125839,0 +17669,Male,38,Masters,10,60,13,52,98,1.0,1,43,Semi-Urban,HR Executive,85001,0 +17670,Male,33,High School,3,49,61,69,46,1.0,2,40,Semi-Urban,HR Executive,72101,0 +17671,Male,46,Bachelors,13,82,28,85,50,4.0,6,51,Urban,HR Executive,134248,1 +17672,Female,54,PhD,16,13,76,60,37,6.0,7,91,Semi-Urban,HR Executive,82925,0 +17673,Female,46,Bachelors,12,37,83,49,49,8.0,4,79,Urban,Manager,82014,1 +17674,Male,29,Bachelors,1,41,58,65,70,5.0,5,44,Urban,Manager,53593,0 +17675,Male,55,High School,19,35,9,26,14,7.0,0,7,Urban,Software Engineer,63687,0 +17676,Male,53,Masters,17,33,49,76,94,2.0,0,25,Semi-Urban,ML Engineer,26702,0 +17677,Female,36,Diploma,3,18,16,69,63,2.0,3,13,Semi-Urban,HR Executive,80924,0 +17678,Male,30,Bachelors,4,38,80,2,80,0.0,6,47,Semi-Urban,ML Engineer,30667,0 +17679,Female,28,Bachelors,6,71,8,49,55,2.0,2,42,Rural,Manager,24970,0 +17680,Male,29,Bachelors,15,41,50,0,15,0.0,2,86,Urban,Manager,48770,0 +17681,Male,48,Diploma,10,35,61,83,93,9.0,7,1,Semi-Urban,ML Engineer,98364,0 +17682,Female,24,Bachelors,10,83,31,65,75,3.0,1,7,Urban,Manager,128433,0 +17683,Female,48,Bachelors,19,94,32,41,14,6.0,2,14,Rural,Data Analyst,91712,0 +17684,Male,39,PhD,6,4,56,13,76,4.0,0,85,Rural,Software Engineer,108535,0 +17685,Male,47,PhD,6,17,7,67,50,2.0,5,49,Urban,HR Executive,45326,0 +17686,Other,59,Diploma,1,26,66,22,28,6.0,3,59,Urban,Software Engineer,27761,0 +17687,Male,25,Bachelors,16,69,82,53,5,0.0,1,20,Semi-Urban,Data Analyst,79765,0 +17688,Female,41,Masters,5,91,24,49,6,0.0,6,79,Rural,ML Engineer,146999,1 +17689,Female,32,Diploma,5,20,1,66,73,1.0,0,66,Urban,HR Executive,41706,0 +17690,Female,33,PhD,18,49,2,22,0,0.0,3,87,Rural,ML Engineer,93802,0 +17691,Male,38,Diploma,15,95,37,80,47,0.0,3,62,Semi-Urban,HR Executive,127032,1 +17692,Male,30,Diploma,5,40,29,75,52,7.0,0,65,Urban,Manager,74882,0 +17693,Female,40,Bachelors,5,36,75,41,70,2.0,0,55,Urban,Manager,98626,0 +17694,Male,56,Masters,13,54,21,57,46,1.0,0,26,Urban,HR Executive,97736,0 +17695,Male,54,Bachelors,11,47,34,28,7,5.0,4,9,Urban,Software Engineer,142134,0 +17696,Female,54,Diploma,17,81,16,70,47,3.0,5,97,Urban,Manager,58851,1 +17697,Male,24,Bachelors,6,13,26,20,34,7.0,1,82,Urban,Manager,32266,0 +17698,Female,21,Bachelors,0,80,80,29,5,7.0,1,53,Urban,ML Engineer,58190,1 +17699,Female,37,Masters,4,58,58,30,76,3.0,4,46,Urban,ML Engineer,144815,0 +17700,Female,47,High School,5,53,69,79,83,9.0,7,8,Semi-Urban,Manager,43263,0 +17701,Female,56,Bachelors,19,61,50,16,99,8.0,4,25,Urban,Data Analyst,32803,0 +17702,Male,50,Bachelors,5,27,53,65,54,6.0,5,45,Rural,ML Engineer,100484,0 +17703,Male,27,Bachelors,1,38,9,28,57,4.0,4,62,Urban,Software Engineer,95614,0 +17704,Female,39,Bachelors,10,25,92,10,77,9.0,3,97,Rural,Software Engineer,36933,0 +17705,Male,32,Diploma,5,5,23,10,58,1.0,6,7,Urban,Data Analyst,30275,0 +17706,Other,48,High School,12,29,80,14,58,4.0,2,54,Urban,Data Analyst,119581,0 +17707,Female,44,Diploma,10,13,86,79,97,3.0,5,8,Rural,Manager,35705,0 +17708,Male,35,Masters,18,95,18,96,1,7.0,2,79,Semi-Urban,Data Analyst,40671,1 +17709,Female,23,Masters,18,52,20,75,88,3.0,5,88,Urban,Software Engineer,106965,0 +17710,Male,48,PhD,5,81,80,15,65,3.0,1,96,Semi-Urban,Software Engineer,63239,1 +17711,Male,39,Bachelors,7,57,68,44,13,8.0,0,24,Urban,ML Engineer,98754,0 +17712,Female,45,Diploma,17,7,70,37,84,3.0,4,22,Rural,Manager,52840,0 +17713,Female,28,Bachelors,18,58,24,98,96,5.0,7,90,Urban,Software Engineer,98957,1 +17714,Male,52,Masters,9,12,59,84,90,6.0,1,54,Semi-Urban,ML Engineer,55582,0 +17715,Male,59,Diploma,18,47,19,48,42,0.0,7,56,Urban,HR Executive,99150,0 +17716,Male,28,Bachelors,8,97,8,56,44,5.0,0,40,Semi-Urban,HR Executive,73085,0 +17717,Male,59,Diploma,5,40,63,83,31,6.0,4,86,Rural,Manager,80032,1 +17718,Male,53,Bachelors,0,65,58,92,81,9.0,4,14,Urban,Software Engineer,97408,0 +17719,Male,26,Bachelors,19,8,27,39,87,0.0,5,21,Urban,HR Executive,123945,0 +17720,Female,56,High School,13,94,74,16,36,7.0,7,52,Urban,ML Engineer,76860,0 +17721,Female,42,Bachelors,9,63,97,26,72,6.0,5,82,Urban,Data Analyst,93487,1 +17722,Male,30,High School,12,58,36,15,74,2.0,4,98,Rural,Software Engineer,132069,0 +17723,Male,24,High School,16,25,3,88,17,5.0,5,53,Urban,Software Engineer,68385,0 +17724,Female,49,Bachelors,8,50,96,16,39,2.0,0,65,Urban,HR Executive,125703,0 +17725,Female,45,Masters,14,33,32,97,48,5.0,6,62,Semi-Urban,Software Engineer,139490,0 +17726,Female,40,Bachelors,8,21,0,61,97,6.0,7,7,Semi-Urban,Software Engineer,97357,0 +17727,Male,39,High School,9,51,65,5,53,3.0,1,45,Semi-Urban,HR Executive,146638,0 +17728,Male,32,Bachelors,8,12,96,92,54,7.0,4,58,Urban,HR Executive,137667,1 +17729,Male,54,Bachelors,5,89,14,42,34,0.0,6,9,Urban,HR Executive,50515,0 +17730,Female,41,Bachelors,10,30,1,72,65,2.0,0,10,Urban,Software Engineer,124713,0 +17731,Male,21,Diploma,3,9,21,64,23,2.0,4,75,Urban,ML Engineer,145940,0 +17732,Male,44,Bachelors,2,8,54,11,2,6.0,7,97,Urban,ML Engineer,145526,0 +17733,Male,48,High School,12,23,39,69,12,4.0,0,54,Semi-Urban,ML Engineer,126271,0 +17734,Male,28,Bachelors,14,37,95,69,68,9.0,2,49,Urban,Manager,114198,1 +17735,Female,42,Masters,6,5,14,26,10,4.0,5,95,Rural,Software Engineer,68726,0 +17736,Male,40,Bachelors,6,78,8,34,32,4.0,3,75,Urban,HR Executive,45326,0 +17737,Female,40,Masters,11,95,8,53,36,2.0,4,5,Urban,HR Executive,21995,0 +17738,Male,50,Bachelors,8,82,39,91,5,1.0,5,98,Semi-Urban,Data Analyst,32023,1 +17739,Male,55,High School,8,99,33,18,10,9.0,7,25,Semi-Urban,Data Analyst,113912,0 +17740,Male,22,High School,0,49,16,44,88,5.0,3,87,Semi-Urban,HR Executive,92708,0 +17741,Male,55,Bachelors,11,52,3,14,14,1.0,5,52,Semi-Urban,Data Analyst,77849,0 +17742,Male,58,High School,12,91,50,67,70,7.0,2,11,Rural,Manager,46085,0 +17743,Female,56,Bachelors,0,10,48,10,74,5.0,5,18,Semi-Urban,Manager,82321,0 +17744,Female,33,Bachelors,9,84,33,21,68,7.0,6,40,Urban,ML Engineer,44155,0 +17745,Male,56,Diploma,14,55,65,71,21,0.0,7,99,Rural,Manager,73424,1 +17746,Male,36,Bachelors,1,7,96,70,26,1.0,1,91,Urban,Software Engineer,102211,1 +17747,Other,32,Bachelors,0,33,27,79,23,5.0,4,70,Rural,ML Engineer,123521,0 +17748,Male,33,Bachelors,11,45,63,85,37,1.0,2,28,Semi-Urban,Software Engineer,109915,0 +17749,Male,37,Masters,0,45,64,31,80,7.0,7,94,Urban,Software Engineer,121807,0 +17750,Male,44,Masters,7,13,91,2,94,4.0,3,42,Urban,Data Analyst,29213,0 +17751,Female,48,High School,11,81,55,98,37,9.0,0,41,Urban,Data Analyst,118637,1 +17752,Male,37,Bachelors,5,16,73,76,4,0.0,3,31,Semi-Urban,HR Executive,77183,0 +17753,Male,47,Masters,3,75,47,30,86,5.0,1,60,Urban,Data Analyst,144213,0 +17754,Male,42,High School,10,19,42,94,53,9.0,5,35,Semi-Urban,HR Executive,79819,0 +17755,Male,53,Bachelors,16,17,16,7,1,9.0,6,87,Rural,ML Engineer,27519,0 +17756,Male,32,Diploma,18,57,81,5,80,8.0,1,50,Urban,Software Engineer,63195,0 +17757,Female,27,Bachelors,14,45,7,34,74,5.0,2,73,Rural,ML Engineer,26565,0 +17758,Female,48,Masters,5,22,20,33,21,1.0,4,24,Semi-Urban,Manager,96133,0 +17759,Male,33,Bachelors,1,68,38,53,62,7.0,7,60,Urban,Data Analyst,84560,0 +17760,Male,48,Bachelors,17,79,82,3,61,7.0,3,4,Semi-Urban,ML Engineer,132128,0 +17761,Female,30,Masters,6,89,34,34,42,4.0,3,26,Semi-Urban,ML Engineer,60885,0 +17762,Female,46,Bachelors,18,70,41,69,61,1.0,2,69,Urban,Manager,67320,1 +17763,Male,28,PhD,10,73,36,70,46,3.0,7,79,Rural,Data Analyst,121943,1 +17764,Male,49,Masters,5,32,63,5,28,0.0,4,36,Semi-Urban,Software Engineer,77349,0 +17765,Male,46,High School,7,74,33,37,72,7.0,1,46,Semi-Urban,Software Engineer,83992,0 +17766,Male,49,PhD,5,91,41,34,65,1.0,3,55,Semi-Urban,Software Engineer,57707,0 +17767,Male,47,Diploma,17,46,58,70,36,1.0,7,95,Urban,Software Engineer,128268,1 +17768,Female,32,High School,8,62,44,78,52,7.0,3,91,Urban,Data Analyst,141217,1 +17769,Male,46,Masters,19,5,60,38,49,1.0,6,26,Urban,Data Analyst,100561,0 +17770,Female,21,Bachelors,0,27,54,94,7,3.0,3,24,Urban,Data Analyst,34327,0 +17771,Female,38,Bachelors,3,85,92,58,39,4.0,2,80,Urban,HR Executive,51088,1 +17772,Female,24,Diploma,18,41,93,45,65,2.0,5,54,Rural,ML Engineer,82318,0 +17773,Male,35,Masters,12,82,28,42,42,7.0,2,89,Urban,Software Engineer,63088,1 +17774,Male,53,Bachelors,4,34,19,9,62,5.0,6,6,Rural,HR Executive,134023,0 +17775,Other,50,High School,6,30,95,41,82,8.0,4,40,Urban,Manager,115518,0 +17776,Female,53,Masters,4,48,76,51,23,6.0,6,74,Semi-Urban,HR Executive,91946,1 +17777,Female,46,Bachelors,9,66,65,50,49,1.0,3,39,Urban,Manager,103699,0 +17778,Male,40,Diploma,16,14,21,40,29,8.0,2,61,Semi-Urban,Manager,38527,0 +17779,Male,33,Diploma,2,71,15,37,48,0.0,0,62,Urban,Software Engineer,106855,0 +17780,Female,22,Diploma,11,19,31,7,54,8.0,1,2,Semi-Urban,HR Executive,102791,0 +17781,Male,27,Bachelors,14,91,4,53,49,9.0,2,49,Urban,HR Executive,67722,0 +17782,Male,23,Diploma,10,49,44,50,65,0.0,0,24,Rural,Data Analyst,69994,0 +17783,Male,59,Masters,15,93,62,49,21,9.0,6,43,Rural,Software Engineer,93136,1 +17784,Male,37,Bachelors,8,36,98,92,17,1.0,0,29,Urban,Software Engineer,130998,1 +17785,Male,56,High School,7,64,50,54,70,2.0,0,51,Semi-Urban,ML Engineer,23721,0 +17786,Male,51,Masters,18,98,6,97,94,3.0,7,60,Urban,Manager,94283,1 +17787,Male,32,High School,12,69,15,95,35,3.0,7,87,Urban,Data Analyst,99342,1 +17788,Female,40,Masters,10,30,97,57,30,3.0,4,25,Rural,ML Engineer,118881,0 +17789,Male,53,Diploma,11,4,71,84,22,5.0,7,47,Urban,Software Engineer,63517,0 +17790,Male,39,High School,9,77,69,61,46,3.0,5,52,Urban,Manager,134173,1 +17791,Female,28,Bachelors,19,78,0,37,77,2.0,5,19,Urban,HR Executive,121932,0 +17792,Male,22,Bachelors,3,21,74,76,86,3.0,7,13,Urban,HR Executive,76443,0 +17793,Male,29,Bachelors,17,36,42,71,31,7.0,5,15,Urban,HR Executive,141747,0 +17794,Female,53,Bachelors,8,66,15,90,27,8.0,1,5,Semi-Urban,ML Engineer,104613,0 +17795,Female,48,High School,3,75,49,10,44,8.0,6,87,Urban,Software Engineer,54169,0 +17796,Male,24,Bachelors,3,78,55,39,77,1.0,1,24,Urban,HR Executive,122652,0 +17797,Male,51,Diploma,2,72,70,1,38,7.0,1,97,Semi-Urban,Data Analyst,67844,1 +17798,Female,40,Masters,15,42,23,62,64,8.0,3,21,Semi-Urban,HR Executive,63620,0 +17799,Male,46,Bachelors,5,91,4,16,99,9.0,5,23,Rural,Software Engineer,124925,0 +17800,Female,34,High School,17,17,45,15,80,8.0,0,25,Urban,HR Executive,51467,0 +17801,Other,22,Masters,3,33,69,22,99,6.0,7,29,Urban,HR Executive,110300,0 +17802,Female,24,Diploma,14,21,93,99,4,9.0,6,8,Urban,HR Executive,133239,0 +17803,Male,37,Bachelors,10,87,99,79,98,1.0,1,65,Semi-Urban,Software Engineer,106367,1 +17804,Male,24,Bachelors,13,84,82,30,3,2.0,5,38,Urban,ML Engineer,88976,0 +17805,Other,59,Bachelors,18,40,69,15,0,7.0,5,87,Urban,ML Engineer,76252,0 +17806,Male,24,Bachelors,17,64,14,37,98,8.0,4,71,Urban,Manager,135609,0 +17807,Male,30,Masters,0,38,87,54,70,2.0,0,81,Urban,HR Executive,43507,1 +17808,Female,48,Diploma,15,29,19,5,38,8.0,5,17,Urban,Manager,21920,0 +17809,Male,30,Diploma,14,45,75,62,30,9.0,3,37,Semi-Urban,Software Engineer,41373,0 +17810,Male,55,Bachelors,11,70,67,7,27,3.0,2,53,Semi-Urban,HR Executive,149865,0 +17811,Female,45,Diploma,9,42,99,83,38,3.0,1,17,Urban,Software Engineer,139561,1 +17812,Male,26,Diploma,17,35,45,77,83,1.0,5,60,Urban,Manager,114873,0 +17813,Male,34,Masters,9,47,66,85,96,2.0,6,65,Rural,Data Analyst,39514,1 +17814,Male,44,Diploma,18,55,60,91,31,5.0,0,69,Urban,Data Analyst,145252,1 +17815,Female,50,Masters,16,36,27,84,46,2.0,5,93,Urban,ML Engineer,149629,0 +17816,Male,24,Bachelors,1,58,56,72,43,7.0,2,90,Semi-Urban,Software Engineer,149577,1 +17817,Male,45,Masters,12,10,72,88,82,8.0,2,97,Rural,Manager,67989,1 +17818,Female,55,Diploma,19,80,90,36,46,6.0,5,25,Urban,ML Engineer,106398,0 +17819,Female,59,Bachelors,15,63,59,57,95,6.0,4,95,Urban,ML Engineer,147325,1 +17820,Male,49,Masters,6,27,69,63,65,2.0,6,14,Urban,Software Engineer,141558,0 +17821,Female,28,Masters,15,25,74,98,45,4.0,7,38,Semi-Urban,Manager,101655,0 +17822,Male,37,Bachelors,16,85,41,28,93,0.0,1,45,Urban,HR Executive,112005,0 +17823,Female,55,Diploma,3,40,89,28,22,0.0,5,65,Semi-Urban,ML Engineer,140884,0 +17824,Male,49,Masters,15,39,9,41,36,6.0,5,36,Urban,ML Engineer,73126,0 +17825,Male,31,Diploma,12,88,56,99,44,7.0,2,63,Urban,Data Analyst,77399,1 +17826,Female,28,High School,6,35,90,53,67,1.0,6,26,Urban,Software Engineer,88190,0 +17827,Male,48,Diploma,16,12,32,21,88,4.0,3,32,Urban,Data Analyst,133996,0 +17828,Male,57,Diploma,17,76,19,8,1,3.0,2,41,Urban,Data Analyst,76525,0 +17829,Male,55,Diploma,19,81,82,71,20,3.0,7,53,Urban,Manager,53668,1 +17830,Female,46,Masters,3,84,34,77,18,1.0,5,15,Semi-Urban,Data Analyst,148077,0 +17831,Male,47,Bachelors,18,54,18,46,17,7.0,6,41,Urban,ML Engineer,85771,0 +17832,Male,35,Masters,4,29,21,26,76,6.0,0,11,Rural,Software Engineer,55372,0 +17833,Male,40,Masters,14,94,15,21,71,9.0,6,53,Urban,Manager,123818,0 +17834,Male,30,Bachelors,1,38,6,36,0,0.0,5,4,Rural,Software Engineer,72690,0 +17835,Male,25,High School,0,23,18,45,26,1.0,1,75,Urban,ML Engineer,130691,0 +17836,Male,47,Bachelors,6,80,58,40,32,0.0,7,64,Urban,ML Engineer,142908,1 +17837,Male,46,Masters,13,40,48,78,25,9.0,3,33,Urban,HR Executive,134363,0 +17838,Male,35,Bachelors,13,25,14,33,29,8.0,0,28,Rural,ML Engineer,110211,0 +17839,Female,45,Masters,6,10,61,83,13,3.0,6,68,Rural,ML Engineer,106991,0 +17840,Female,38,Bachelors,1,35,19,73,60,1.0,6,70,Urban,Manager,134693,0 +17841,Female,43,Masters,13,8,84,29,88,9.0,0,0,Urban,Manager,129485,0 +17842,Male,57,Diploma,0,67,5,78,1,3.0,5,31,Semi-Urban,ML Engineer,25504,0 +17843,Other,51,Bachelors,19,4,51,85,11,1.0,7,41,Urban,Software Engineer,144396,0 +17844,Male,21,High School,3,18,77,18,14,0.0,1,46,Semi-Urban,ML Engineer,89802,0 +17845,Other,47,Diploma,12,13,55,41,17,9.0,3,35,Semi-Urban,Manager,66930,0 +17846,Male,35,Diploma,11,26,86,55,2,4.0,0,97,Urban,Data Analyst,68665,1 +17847,Male,21,Diploma,0,7,48,71,27,2.0,0,43,Urban,Manager,114936,0 +17848,Male,34,Diploma,5,50,3,93,79,3.0,6,33,Semi-Urban,Manager,32205,0 +17849,Male,58,Diploma,1,90,77,67,81,9.0,6,16,Rural,Data Analyst,70766,1 +17850,Female,53,Diploma,5,89,58,76,80,8.0,2,83,Urban,Data Analyst,126011,1 +17851,Female,22,Masters,18,74,92,93,93,9.0,5,28,Rural,Data Analyst,78840,1 +17852,Other,56,Diploma,14,95,23,4,72,4.0,4,81,Urban,Data Analyst,22947,0 +17853,Female,40,Bachelors,1,52,59,46,91,0.0,5,87,Urban,ML Engineer,26535,1 +17854,Male,39,High School,7,90,53,91,26,2.0,3,91,Rural,HR Executive,103286,1 +17855,Male,31,Bachelors,0,42,29,54,99,3.0,6,94,Semi-Urban,HR Executive,132319,0 +17856,Other,21,Diploma,8,48,84,35,78,8.0,0,50,Urban,Manager,149270,0 +17857,Male,35,Bachelors,6,16,27,53,50,6.0,3,18,Semi-Urban,Manager,139359,0 +17858,Female,22,Diploma,15,30,98,76,4,2.0,4,47,Urban,Manager,47381,1 +17859,Male,22,High School,4,72,73,26,94,1.0,5,14,Urban,Manager,82494,0 +17860,Male,26,Bachelors,14,85,71,65,65,7.0,2,87,Urban,Manager,37460,1 +17861,Female,52,Masters,2,13,38,79,98,3.0,2,42,Urban,ML Engineer,53276,0 +17862,Male,29,Masters,17,41,39,85,86,5.0,7,26,Urban,Data Analyst,22092,0 +17863,Male,38,Masters,11,57,93,3,25,3.0,3,95,Semi-Urban,Data Analyst,34980,1 +17864,Male,25,Bachelors,19,74,44,67,64,0.0,6,25,Rural,Software Engineer,65617,0 +17865,Female,42,PhD,0,26,37,19,42,6.0,4,77,Urban,ML Engineer,144795,0 +17866,Male,28,Diploma,10,3,83,42,89,3.0,2,40,Urban,HR Executive,77389,0 +17867,Male,34,Masters,0,54,24,59,97,4.0,5,88,Urban,ML Engineer,131866,0 +17868,Male,23,Diploma,3,44,13,15,95,9.0,5,62,Rural,HR Executive,55288,0 +17869,Male,45,High School,10,62,91,68,70,6.0,4,55,Urban,Data Analyst,88140,1 +17870,Male,45,Masters,2,90,36,92,39,1.0,7,8,Urban,HR Executive,81161,0 +17871,Male,25,Bachelors,12,37,26,94,15,3.0,0,42,Urban,ML Engineer,49209,0 +17872,Other,49,PhD,11,41,5,37,84,8.0,6,2,Rural,Software Engineer,79564,0 +17873,Other,43,High School,9,98,9,41,89,9.0,1,67,Urban,Software Engineer,47071,0 +17874,Male,53,Masters,14,81,40,45,33,4.0,5,25,Urban,Software Engineer,141736,0 +17875,Female,33,Bachelors,9,70,55,58,92,0.0,2,65,Urban,Manager,138038,1 +17876,Male,56,Bachelors,12,58,49,62,78,3.0,5,92,Urban,ML Engineer,77594,1 +17877,Male,31,Bachelors,9,25,7,99,90,7.0,4,78,Rural,Manager,141928,0 +17878,Male,37,Bachelors,4,63,93,16,46,1.0,2,74,Urban,Software Engineer,140387,1 +17879,Male,53,PhD,11,40,74,62,16,9.0,1,25,Urban,HR Executive,69309,0 +17880,Male,47,PhD,0,53,55,5,64,3.0,2,23,Urban,Software Engineer,107626,0 +17881,Male,25,Bachelors,17,14,41,85,13,3.0,0,94,Rural,Data Analyst,26895,0 +17882,Female,54,Bachelors,17,57,48,79,73,6.0,6,52,Semi-Urban,Manager,47773,0 +17883,Male,25,Bachelors,9,90,74,16,33,6.0,3,55,Rural,Manager,21740,1 +17884,Female,36,Masters,18,79,93,18,66,9.0,2,11,Urban,HR Executive,72212,0 +17885,Male,27,Bachelors,14,33,84,88,75,1.0,2,39,Urban,Software Engineer,109107,1 +17886,Male,21,Masters,2,47,79,97,42,7.0,1,42,Rural,Data Analyst,93647,1 +17887,Male,46,Bachelors,14,9,16,3,67,7.0,0,14,Urban,Data Analyst,92176,0 +17888,Male,34,Masters,16,41,64,39,4,8.0,5,20,Urban,Manager,96936,0 +17889,Female,57,High School,1,2,70,8,12,1.0,7,75,Semi-Urban,Manager,132252,0 +17890,Female,25,Bachelors,6,60,27,73,53,0.0,0,74,Rural,HR Executive,25321,0 +17891,Male,57,Diploma,16,31,40,77,50,8.0,6,87,Semi-Urban,Data Analyst,125548,1 +17892,Female,41,Bachelors,2,96,86,82,45,5.0,3,37,Urban,HR Executive,119401,1 +17893,Female,54,Masters,5,50,35,67,39,7.0,3,25,Urban,Data Analyst,28733,0 +17894,Female,53,Masters,13,36,84,9,13,5.0,4,27,Urban,Data Analyst,33862,0 +17895,Male,43,Bachelors,17,28,4,16,70,1.0,2,99,Urban,ML Engineer,86761,0 +17896,Female,26,Masters,7,70,78,34,91,7.0,6,21,Rural,Software Engineer,75382,0 +17897,Male,46,Diploma,1,70,65,86,53,4.0,3,39,Semi-Urban,Data Analyst,26360,1 +17898,Female,53,High School,19,99,51,95,16,4.0,3,9,Urban,Manager,114414,1 +17899,Male,33,High School,5,11,92,54,70,8.0,1,33,Urban,Data Analyst,116088,0 +17900,Male,43,Diploma,15,39,4,89,58,6.0,0,39,Urban,Data Analyst,62674,0 +17901,Male,55,Masters,17,35,76,19,72,2.0,3,74,Urban,Manager,50882,0 +17902,Male,54,Bachelors,18,5,85,79,8,3.0,7,1,Urban,ML Engineer,45372,0 +17903,Female,41,Bachelors,10,1,92,73,18,5.0,4,60,Urban,Software Engineer,90303,0 +17904,Male,24,Bachelors,4,90,56,16,3,8.0,2,61,Urban,Software Engineer,43736,0 +17905,Male,42,High School,13,61,63,74,44,7.0,7,51,Semi-Urban,HR Executive,46316,1 +17906,Female,40,Masters,18,86,79,33,47,1.0,5,93,Urban,Data Analyst,134619,1 +17907,Male,38,High School,1,91,95,6,99,5.0,1,87,Urban,Software Engineer,94887,1 +17908,Male,27,Bachelors,16,0,68,21,55,5.0,2,51,Urban,HR Executive,131143,0 +17909,Male,38,Bachelors,5,13,66,58,6,9.0,2,16,Urban,Manager,97607,0 +17910,Male,51,Diploma,19,52,65,79,50,8.0,6,24,Urban,ML Engineer,101236,0 +17911,Male,24,PhD,8,7,89,2,69,9.0,4,74,Urban,Software Engineer,111754,0 +17912,Male,29,Diploma,4,18,10,53,43,1.0,3,77,Urban,Software Engineer,47806,0 +17913,Female,52,Diploma,3,99,63,31,34,5.0,7,80,Urban,Manager,85433,1 +17914,Female,27,Masters,19,98,4,91,95,3.0,3,55,Semi-Urban,Software Engineer,91741,1 +17915,Male,38,Bachelors,5,52,37,38,62,6.0,2,42,Urban,Software Engineer,78263,0 +17916,Male,52,Bachelors,0,4,43,69,86,5.0,3,53,Urban,Manager,55816,0 +17917,Male,34,Diploma,2,7,17,91,41,1.0,0,70,Semi-Urban,Data Analyst,112283,0 +17918,Female,46,Masters,12,19,86,95,30,0.0,0,23,Semi-Urban,Software Engineer,42280,0 +17919,Male,22,Diploma,14,75,68,81,14,0.0,4,27,Semi-Urban,Manager,97985,1 +17920,Female,54,Diploma,13,97,41,86,67,1.0,3,26,Urban,HR Executive,90729,1 +17921,Male,39,Bachelors,12,56,7,94,36,5.0,7,88,Semi-Urban,Manager,46524,1 +17922,Female,54,Masters,12,79,99,94,44,0.0,3,5,Urban,Manager,67467,1 +17923,Male,58,Bachelors,16,93,76,89,31,3.0,0,2,Urban,HR Executive,31477,1 +17924,Female,58,Bachelors,18,88,27,57,86,3.0,0,98,Rural,Data Analyst,109516,1 +17925,Male,52,Masters,10,25,50,32,28,2.0,3,34,Rural,ML Engineer,148967,0 +17926,Female,44,High School,1,81,92,88,86,5.0,4,3,Urban,Software Engineer,131404,1 +17927,Male,45,Masters,8,47,80,64,32,7.0,1,10,Urban,Data Analyst,46143,0 +17928,Male,45,High School,7,50,5,69,15,7.0,5,50,Urban,Manager,38342,0 +17929,Male,59,Diploma,16,27,73,55,64,5.0,7,75,Semi-Urban,ML Engineer,20226,0 +17930,Female,49,High School,1,66,64,46,92,5.0,5,5,Semi-Urban,Manager,79359,0 +17931,Female,53,Bachelors,18,7,38,26,35,8.0,5,63,Urban,ML Engineer,143415,0 +17932,Male,42,Bachelors,9,95,3,70,12,3.0,3,9,Urban,HR Executive,121549,0 +17933,Male,47,PhD,0,59,38,51,15,4.0,3,62,Urban,HR Executive,48513,0 +17934,Male,47,Masters,0,40,54,50,70,4.0,3,27,Urban,HR Executive,51077,0 +17935,Female,54,Bachelors,16,45,50,50,85,9.0,1,46,Urban,HR Executive,44643,0 +17936,Female,49,Masters,8,87,74,72,72,5.0,2,39,Urban,Software Engineer,77066,1 +17937,Female,38,Diploma,3,31,80,33,4,9.0,3,92,Semi-Urban,ML Engineer,36041,0 +17938,Male,30,High School,16,10,2,18,91,5.0,5,3,Semi-Urban,Manager,117573,0 +17939,Other,57,Diploma,0,16,36,92,63,6.0,2,9,Semi-Urban,Software Engineer,70840,0 +17940,Female,57,Diploma,2,68,91,29,73,1.0,4,91,Urban,Manager,88201,1 +17941,Female,25,Bachelors,8,45,6,6,18,7.0,3,50,Urban,Software Engineer,52982,0 +17942,Male,36,Bachelors,6,78,92,41,16,4.0,3,60,Urban,HR Executive,108190,1 +17943,Female,57,Bachelors,2,40,93,32,28,7.0,1,3,Urban,ML Engineer,123915,0 +17944,Male,49,PhD,16,66,32,12,47,4.0,4,13,Semi-Urban,Software Engineer,55847,0 +17945,Male,52,Bachelors,1,52,22,32,67,4.0,7,65,Urban,HR Executive,138089,0 +17946,Male,48,Bachelors,14,79,90,44,50,4.0,2,60,Urban,Manager,145338,1 +17947,Male,54,Diploma,19,64,19,1,39,3.0,3,0,Urban,Data Analyst,39409,0 +17948,Male,47,Masters,7,82,31,1,59,4.0,5,55,Rural,HR Executive,49764,0 +17949,Male,53,PhD,16,44,18,63,93,8.0,7,15,Urban,ML Engineer,82699,0 +17950,Male,24,Bachelors,3,33,40,0,70,4.0,2,66,Semi-Urban,Data Analyst,36813,0 +17951,Female,39,Bachelors,17,87,10,23,48,3.0,2,98,Urban,Data Analyst,71243,0 +17952,Male,42,Masters,2,51,59,43,97,6.0,4,54,Semi-Urban,Manager,93270,0 +17953,Male,43,Diploma,17,68,71,7,45,7.0,3,39,Semi-Urban,ML Engineer,97531,0 +17954,Male,44,Masters,15,67,67,39,47,4.0,7,75,Urban,Data Analyst,74814,1 +17955,Female,56,Bachelors,17,54,59,51,4,2.0,6,32,Urban,Manager,21621,0 +17956,Female,23,Bachelors,13,44,2,86,55,8.0,2,90,Semi-Urban,ML Engineer,27568,0 +17957,Male,25,Diploma,16,75,88,89,71,4.0,5,88,Urban,ML Engineer,103688,1 +17958,Female,50,High School,6,7,67,17,60,9.0,5,54,Urban,ML Engineer,41294,0 +17959,Male,29,High School,10,23,77,76,16,0.0,3,79,Urban,Data Analyst,90487,1 +17960,Other,34,Masters,12,3,37,44,4,9.0,7,97,Urban,Data Analyst,51983,0 +17961,Male,21,Bachelors,4,30,14,20,82,4.0,6,38,Rural,ML Engineer,22712,0 +17962,Male,53,Diploma,7,96,38,74,88,7.0,2,98,Urban,ML Engineer,66162,1 +17963,Male,31,Diploma,2,51,72,90,90,8.0,6,52,Urban,Manager,144607,1 +17964,Male,40,Bachelors,16,76,1,12,70,9.0,3,53,Semi-Urban,ML Engineer,109669,0 +17965,Male,35,Diploma,13,74,20,84,99,8.0,7,3,Urban,ML Engineer,39597,0 +17966,Female,54,Bachelors,13,6,7,31,95,9.0,3,39,Rural,Data Analyst,107106,0 +17967,Female,47,Masters,18,64,89,30,70,2.0,4,23,Rural,Software Engineer,123328,0 +17968,Male,39,Masters,18,79,23,61,22,0.0,7,42,Urban,ML Engineer,106383,0 +17969,Male,55,Bachelors,6,68,14,34,12,1.0,2,18,Rural,Software Engineer,138684,0 +17970,Male,40,Masters,0,62,63,46,38,3.0,5,32,Urban,Data Analyst,99644,0 +17971,Male,47,Diploma,5,42,17,42,98,0.0,1,41,Rural,ML Engineer,116032,0 +17972,Female,28,Diploma,8,53,18,79,83,6.0,5,18,Urban,ML Engineer,26673,0 +17973,Male,58,High School,10,72,97,82,88,6.0,7,92,Semi-Urban,Data Analyst,20293,1 +17974,Female,28,Bachelors,18,45,91,51,71,9.0,4,96,Semi-Urban,Software Engineer,57396,1 +17975,Male,51,Masters,3,41,40,50,4,4.0,4,66,Urban,ML Engineer,104797,0 +17976,Male,33,Masters,15,58,15,61,47,3.0,7,54,Semi-Urban,Software Engineer,63795,0 +17977,Male,42,High School,18,36,70,71,68,5.0,2,69,Urban,Data Analyst,53299,1 +17978,Male,44,High School,15,98,19,34,14,1.0,7,96,Semi-Urban,Software Engineer,83107,1 +17979,Male,52,Bachelors,0,79,69,65,41,9.0,6,66,Urban,Manager,114206,1 +17980,Female,27,High School,10,27,27,89,11,3.0,1,18,Urban,Software Engineer,32943,0 +17981,Male,34,Diploma,13,2,79,30,30,2.0,2,99,Semi-Urban,ML Engineer,132767,0 +17982,Male,38,High School,0,35,26,90,60,1.0,3,5,Urban,Software Engineer,104398,0 +17983,Female,35,High School,0,38,90,17,91,9.0,3,43,Urban,Software Engineer,84202,0 +17984,Male,47,Diploma,9,1,91,7,23,6.0,3,89,Semi-Urban,Manager,99972,0 +17985,Female,57,Bachelors,2,5,52,91,16,0.0,2,80,Semi-Urban,HR Executive,62107,0 +17986,Male,21,High School,5,42,24,99,71,7.0,5,32,Urban,Data Analyst,101373,0 +17987,Male,35,Bachelors,1,29,22,30,49,6.0,6,41,Semi-Urban,Manager,85611,0 +17988,Female,42,PhD,8,96,78,43,23,0.0,6,23,Urban,Data Analyst,78415,0 +17989,Female,30,High School,7,1,27,36,2,0.0,5,4,Urban,Manager,54816,0 +17990,Male,46,Bachelors,2,14,14,13,61,1.0,7,78,Rural,HR Executive,127029,0 +17991,Male,44,Bachelors,2,71,46,53,96,1.0,4,18,Semi-Urban,Manager,53970,0 +17992,Female,35,Bachelors,11,43,98,69,70,0.0,6,20,Semi-Urban,HR Executive,102691,0 +17993,Male,35,Bachelors,14,85,47,56,28,0.0,0,32,Urban,ML Engineer,134191,0 +17994,Male,34,High School,8,36,31,90,28,9.0,2,68,Semi-Urban,HR Executive,69844,0 +17995,Female,30,Bachelors,8,9,56,49,90,8.0,0,99,Urban,HR Executive,121509,0 +17996,Female,53,Bachelors,0,54,3,15,66,0.0,0,53,Semi-Urban,Data Analyst,125475,0 +17997,Female,46,PhD,6,35,71,6,60,3.0,6,62,Semi-Urban,Manager,46830,0 +17998,Female,37,Diploma,1,56,27,87,58,1.0,3,25,Semi-Urban,HR Executive,23087,0 +17999,Female,36,Bachelors,12,24,51,70,61,7.0,2,42,Urban,HR Executive,123654,0 +18000,Female,37,Masters,5,46,28,20,27,9.0,3,93,Urban,HR Executive,124117,0 +18001,Female,31,Bachelors,1,40,59,33,1,5.0,7,13,Urban,Data Analyst,30619,0 +18002,Male,50,Diploma,12,15,7,43,65,7.0,5,10,Urban,ML Engineer,62147,0 +18003,Male,32,Bachelors,3,37,69,68,83,6.0,1,26,Rural,Data Analyst,124896,0 +18004,Female,34,Bachelors,1,0,32,9,9,0.0,1,9,Urban,Data Analyst,129551,0 +18005,Female,36,Diploma,11,69,79,41,59,5.0,0,12,Urban,Data Analyst,25248,0 +18006,Male,36,Bachelors,16,89,76,67,94,5.0,1,11,Urban,ML Engineer,132636,1 +18007,Male,31,Bachelors,2,6,33,22,31,4.0,6,92,Urban,HR Executive,68555,0 +18008,Female,54,Bachelors,17,73,76,53,77,3.0,2,23,Rural,HR Executive,88195,0 +18009,Male,23,Masters,9,62,63,70,89,9.0,7,11,Urban,Manager,133973,0 +18010,Male,57,Diploma,13,40,90,68,70,5.0,0,56,Semi-Urban,Data Analyst,106620,1 +18011,Female,52,Diploma,8,41,68,86,34,5.0,5,86,Rural,ML Engineer,26776,1 +18012,Other,43,Bachelors,13,11,25,99,11,0.0,6,66,Rural,ML Engineer,101590,0 +18013,Female,37,Bachelors,2,27,66,9,91,4.0,3,59,Urban,Software Engineer,44729,0 +18014,Female,32,Bachelors,16,75,54,21,99,1.0,0,62,Rural,Data Analyst,127030,0 +18015,Male,55,High School,13,64,91,23,48,5.0,7,87,Rural,Data Analyst,52531,1 +18016,Female,50,Bachelors,15,37,12,65,22,7.0,6,6,Urban,HR Executive,39127,0 +18017,Male,52,High School,17,35,91,91,71,8.0,5,94,Urban,Manager,118947,1 +18018,Female,22,Bachelors,1,41,29,30,36,2.0,3,1,Semi-Urban,HR Executive,101726,0 +18019,Male,54,Bachelors,18,90,49,39,24,3.0,5,95,Urban,Manager,142516,1 +18020,Male,40,Diploma,8,5,16,50,11,7.0,3,13,Urban,Manager,126420,0 +18021,Male,29,Bachelors,7,97,67,69,32,6.0,4,96,Urban,Software Engineer,94887,1 +18022,Male,55,PhD,1,13,17,26,57,2.0,7,89,Semi-Urban,Software Engineer,98533,0 +18023,Female,42,Bachelors,8,8,61,80,71,8.0,4,25,Urban,ML Engineer,107418,0 +18024,Other,50,Bachelors,6,24,78,39,30,2.0,3,75,Semi-Urban,HR Executive,106314,0 +18025,Female,48,High School,18,23,94,96,10,9.0,2,76,Urban,Data Analyst,87105,1 +18026,Female,24,Masters,10,9,50,99,61,1.0,7,65,Urban,Manager,123267,0 +18027,Male,48,Bachelors,10,14,66,39,9,7.0,5,99,Urban,ML Engineer,38584,0 +18028,Female,54,Bachelors,0,5,46,83,59,2.0,3,61,Urban,ML Engineer,39904,0 +18029,Female,39,Bachelors,4,7,49,59,60,3.0,5,62,Rural,HR Executive,73590,0 +18030,Female,53,Masters,13,80,59,79,53,7.0,2,95,Rural,ML Engineer,82118,1 +18031,Male,56,High School,19,74,38,64,38,1.0,7,82,Urban,Data Analyst,143560,1 +18032,Female,39,Masters,6,22,80,56,75,0.0,7,56,Urban,HR Executive,63365,0 +18033,Female,42,PhD,3,23,98,8,0,7.0,7,70,Semi-Urban,Manager,49765,0 +18034,Male,57,Diploma,7,8,30,52,44,7.0,5,84,Urban,HR Executive,66065,0 +18035,Female,52,Bachelors,15,12,83,95,33,3.0,7,19,Urban,HR Executive,27300,0 +18036,Other,43,Masters,9,53,11,80,62,5.0,4,39,Urban,Data Analyst,34935,0 +18037,Male,49,Diploma,16,32,11,29,41,7.0,5,38,Urban,Software Engineer,87652,0 +18038,Female,50,Bachelors,0,77,6,17,86,0.0,2,20,Rural,HR Executive,23750,0 +18039,Female,34,Masters,6,43,28,54,91,0.0,1,87,Semi-Urban,Data Analyst,68714,0 +18040,Female,47,Bachelors,16,38,89,4,47,5.0,2,72,Urban,Manager,88272,0 +18041,Male,43,Masters,0,53,21,30,74,7.0,0,19,Urban,Data Analyst,148534,0 +18042,Female,21,PhD,17,48,35,59,69,0.0,7,27,Rural,Software Engineer,81770,0 +18043,Male,55,Diploma,7,2,91,0,69,9.0,3,89,Urban,ML Engineer,26759,0 +18044,Male,52,PhD,19,74,79,41,99,5.0,3,49,Semi-Urban,Software Engineer,135854,1 +18045,Female,56,High School,18,16,46,76,20,0.0,6,4,Rural,Software Engineer,139035,0 +18046,Female,33,Bachelors,19,10,33,10,72,1.0,0,73,Semi-Urban,Manager,28952,0 +18047,Female,49,High School,12,82,48,70,38,5.0,1,77,Semi-Urban,Software Engineer,125385,1 +18048,Male,36,High School,15,29,30,80,92,8.0,7,6,Urban,Manager,43897,0 +18049,Male,40,High School,8,97,41,97,3,0.0,3,62,Semi-Urban,Data Analyst,35906,1 +18050,Female,59,Masters,15,72,96,20,19,7.0,2,11,Rural,Manager,132679,0 +18051,Male,57,Diploma,13,53,85,69,82,5.0,2,7,Semi-Urban,Data Analyst,108655,0 +18052,Female,47,Bachelors,11,27,57,69,73,6.0,6,44,Semi-Urban,ML Engineer,35719,0 +18053,Female,52,PhD,14,54,42,88,20,2.0,2,11,Urban,ML Engineer,40633,0 +18054,Female,31,Diploma,17,88,60,42,37,9.0,3,92,Urban,Software Engineer,55487,1 +18055,Male,40,Masters,16,43,50,41,17,5.0,5,24,Urban,HR Executive,75952,0 +18056,Female,43,Diploma,5,12,85,96,40,4.0,0,36,Rural,Software Engineer,59536,0 +18057,Female,54,Masters,13,25,53,73,67,8.0,1,80,Rural,ML Engineer,118991,0 +18058,Male,40,PhD,1,50,21,53,94,0.0,6,52,Urban,Data Analyst,26154,0 +18059,Male,27,High School,4,66,21,33,7,9.0,6,25,Rural,Data Analyst,59885,0 +18060,Male,27,Bachelors,8,48,24,12,21,9.0,7,24,Urban,Manager,92381,0 +18061,Male,38,Bachelors,1,48,83,63,74,8.0,6,75,Urban,Manager,141660,1 +18062,Female,36,Masters,12,3,28,79,55,4.0,6,84,Urban,Software Engineer,77559,0 +18063,Female,47,Diploma,4,40,31,27,28,5.0,2,67,Urban,Manager,32903,0 +18064,Other,31,High School,7,61,94,6,68,2.0,0,41,Semi-Urban,HR Executive,123532,0 +18065,Male,49,High School,6,5,86,66,24,3.0,7,46,Urban,Data Analyst,62684,0 +18066,Female,23,Diploma,12,57,84,95,41,3.0,6,17,Semi-Urban,Manager,31673,1 +18067,Male,26,PhD,10,90,89,78,12,4.0,1,65,Urban,ML Engineer,141987,1 +18068,Female,41,High School,1,97,89,6,3,9.0,5,0,Urban,ML Engineer,99351,0 +18069,Female,53,Bachelors,18,9,41,25,30,1.0,7,77,Urban,Software Engineer,146231,0 +18070,Female,50,Masters,11,74,58,59,16,1.0,2,71,Rural,Manager,121453,1 +18071,Female,37,Bachelors,11,24,92,44,60,3.0,4,19,Urban,ML Engineer,149140,0 +18072,Female,57,PhD,8,93,1,74,67,3.0,4,60,Semi-Urban,Data Analyst,112126,0 +18073,Female,40,Bachelors,13,38,0,48,95,4.0,0,55,Rural,Software Engineer,47490,0 +18074,Female,39,Bachelors,5,51,90,58,98,2.0,3,9,Urban,Manager,116199,0 +18075,Male,58,Bachelors,16,28,62,44,72,5.0,3,85,Urban,HR Executive,70641,0 +18076,Female,34,Diploma,10,15,2,14,56,1.0,3,14,Semi-Urban,ML Engineer,33687,0 +18077,Female,22,Bachelors,13,31,10,10,57,1.0,2,54,Urban,Data Analyst,25619,0 +18078,Male,27,Bachelors,10,72,9,2,80,0.0,0,21,Rural,ML Engineer,121903,0 +18079,Male,31,Bachelors,7,49,66,44,17,6.0,0,48,Urban,Data Analyst,123642,0 +18080,Female,21,Bachelors,7,24,27,35,92,7.0,0,33,Urban,ML Engineer,117577,0 +18081,Male,27,Diploma,1,65,50,29,91,7.0,3,3,Urban,Data Analyst,57041,0 +18082,Male,48,Diploma,16,32,4,22,25,6.0,1,1,Semi-Urban,Software Engineer,104003,0 +18083,Female,53,Bachelors,14,83,46,87,73,3.0,5,34,Semi-Urban,Data Analyst,48981,1 +18084,Female,35,Diploma,5,87,99,27,70,2.0,4,25,Urban,Manager,144367,0 +18085,Female,29,Diploma,12,59,88,80,8,7.0,3,8,Urban,Software Engineer,59077,0 +18086,Male,49,Masters,0,26,88,84,78,4.0,3,52,Semi-Urban,ML Engineer,120046,1 +18087,Male,34,Bachelors,11,98,24,8,77,8.0,6,6,Urban,ML Engineer,99995,0 +18088,Male,46,Bachelors,16,18,57,23,93,1.0,5,20,Rural,Software Engineer,91765,0 +18089,Male,41,High School,2,19,62,1,75,9.0,2,67,Urban,Manager,56031,0 +18090,Male,50,Masters,2,37,54,53,33,4.0,4,22,Semi-Urban,HR Executive,104166,0 +18091,Other,59,High School,6,23,38,54,94,1.0,0,80,Urban,HR Executive,55910,0 +18092,Male,39,Bachelors,13,16,12,94,4,3.0,5,95,Rural,Data Analyst,149801,0 +18093,Male,55,Diploma,5,49,99,90,11,4.0,2,19,Urban,HR Executive,143822,1 +18094,Male,49,Bachelors,19,22,2,67,2,0.0,7,33,Rural,ML Engineer,50733,0 +18095,Male,54,Masters,5,13,69,83,18,4.0,2,23,Urban,Manager,28982,0 +18096,Male,49,Diploma,15,2,51,68,32,2.0,3,87,Semi-Urban,HR Executive,77921,0 +18097,Male,26,PhD,5,57,89,99,77,2.0,3,87,Semi-Urban,HR Executive,59265,1 +18098,Other,29,Bachelors,19,10,81,51,95,1.0,5,75,Semi-Urban,Manager,50280,0 +18099,Male,28,PhD,11,53,48,30,1,8.0,2,91,Urban,ML Engineer,99858,0 +18100,Male,36,Masters,8,52,32,51,74,2.0,5,75,Semi-Urban,Data Analyst,20937,0 +18101,Male,54,Masters,9,28,91,23,29,9.0,7,57,Urban,HR Executive,25590,0 +18102,Male,26,Bachelors,8,30,13,87,69,3.0,7,74,Urban,HR Executive,24858,0 +18103,Male,31,Diploma,10,8,20,59,44,9.0,7,90,Urban,Software Engineer,104189,0 +18104,Male,21,Diploma,18,20,37,9,45,8.0,0,4,Urban,Software Engineer,82614,0 +18105,Male,26,Masters,19,11,2,96,82,2.0,5,3,Urban,Manager,80520,0 +18106,Female,55,High School,17,16,88,16,83,2.0,1,80,Semi-Urban,Data Analyst,93627,0 +18107,Male,44,Diploma,6,59,12,34,87,8.0,1,9,Urban,Manager,115143,0 +18108,Male,37,High School,17,11,93,14,24,1.0,5,20,Urban,Software Engineer,131539,0 +18109,Male,40,High School,3,90,49,86,70,0.0,2,51,Urban,Manager,111948,1 +18110,Male,45,Bachelors,4,83,11,74,52,5.0,0,90,Urban,Software Engineer,62354,1 +18111,Male,43,Masters,4,49,95,84,6,1.0,4,22,Urban,HR Executive,121204,1 +18112,Male,39,Masters,0,34,7,97,88,5.0,2,90,Semi-Urban,ML Engineer,63090,0 +18113,Male,33,Masters,5,85,71,51,88,7.0,3,30,Semi-Urban,Manager,98626,1 +18114,Male,34,Bachelors,0,19,30,51,30,5.0,4,87,Semi-Urban,Manager,108138,0 +18115,Male,29,Diploma,4,17,96,63,48,1.0,7,59,Urban,HR Executive,84077,1 +18116,Male,50,PhD,15,37,45,23,47,1.0,4,6,Rural,ML Engineer,37195,0 +18117,Male,31,Bachelors,6,19,55,50,87,6.0,4,42,Urban,Data Analyst,127254,0 +18118,Female,26,Bachelors,11,3,49,62,47,8.0,2,26,Urban,Manager,50398,0 +18119,Female,24,High School,1,23,37,19,86,6.0,2,55,Urban,HR Executive,138009,0 +18120,Female,41,Bachelors,15,81,76,15,39,3.0,2,87,Rural,Data Analyst,104957,1 +18121,Female,38,Diploma,5,22,97,9,71,7.0,6,23,Urban,Software Engineer,148629,0 +18122,Other,38,Masters,13,71,43,9,48,6.0,6,42,Urban,ML Engineer,142383,0 +18123,Female,33,Bachelors,9,57,52,66,84,5.0,2,79,Semi-Urban,Software Engineer,69570,1 +18124,Female,26,Bachelors,14,95,21,13,40,1.0,6,58,Semi-Urban,ML Engineer,27386,0 +18125,Male,41,Bachelors,4,1,66,63,98,2.0,1,55,Urban,ML Engineer,85031,0 +18126,Male,22,Bachelors,2,38,26,96,82,4.0,3,82,Semi-Urban,Software Engineer,57956,1 +18127,Female,41,High School,17,34,85,60,1,0.0,3,90,Urban,ML Engineer,41594,1 +18128,Other,32,Diploma,3,68,1,73,63,6.0,3,2,Rural,HR Executive,73503,0 +18129,Male,38,Bachelors,2,56,81,83,18,7.0,3,62,Rural,Software Engineer,43604,1 +18130,Female,21,Diploma,8,83,8,22,57,1.0,5,31,Semi-Urban,HR Executive,61394,0 +18131,Male,35,PhD,2,7,74,24,98,1.0,7,6,Semi-Urban,HR Executive,129843,0 +18132,Male,43,Diploma,17,74,89,9,53,0.0,1,74,Rural,Data Analyst,99220,1 +18133,Male,45,Bachelors,16,83,50,58,30,1.0,7,80,Urban,Software Engineer,89489,1 +18134,Male,40,Bachelors,16,62,2,76,44,6.0,1,72,Urban,ML Engineer,106557,0 +18135,Male,35,Bachelors,1,24,82,81,7,3.0,2,48,Urban,HR Executive,48870,1 +18136,Female,23,High School,3,81,3,39,22,4.0,4,6,Rural,HR Executive,119226,0 +18137,Female,27,Bachelors,10,8,68,31,24,4.0,6,46,Urban,Software Engineer,67038,0 +18138,Female,21,High School,16,63,23,25,72,4.0,3,2,Urban,Software Engineer,134264,0 +18139,Male,33,Bachelors,13,72,81,32,56,7.0,6,19,Urban,ML Engineer,127403,0 +18140,Female,33,PhD,7,31,30,64,19,0.0,5,60,Semi-Urban,Software Engineer,107272,0 +18141,Male,36,Masters,14,37,80,65,47,1.0,5,49,Semi-Urban,ML Engineer,79941,0 +18142,Male,56,Bachelors,13,81,46,29,25,9.0,0,34,Urban,HR Executive,22919,0 +18143,Female,58,High School,11,34,58,78,0,8.0,7,49,Urban,Data Analyst,46950,0 +18144,Male,47,Bachelors,16,96,65,23,32,8.0,0,96,Semi-Urban,Manager,65792,1 +18145,Male,42,Bachelors,9,37,36,71,97,6.0,0,70,Urban,Manager,32467,0 +18146,Male,28,Masters,1,2,38,36,66,3.0,7,40,Rural,HR Executive,77300,0 +18147,Female,36,Diploma,10,24,72,25,61,8.0,0,99,Semi-Urban,Manager,130363,0 +18148,Male,52,Bachelors,13,84,7,14,8,6.0,6,14,Semi-Urban,ML Engineer,108929,0 +18149,Female,36,PhD,0,88,27,37,58,6.0,7,64,Semi-Urban,ML Engineer,104025,0 +18150,Female,57,Bachelors,2,58,65,77,39,2.0,4,98,Urban,HR Executive,83662,1 +18151,Female,26,Bachelors,2,28,19,12,92,9.0,6,49,Urban,ML Engineer,110270,0 +18152,Female,45,Masters,10,39,35,27,40,5.0,1,47,Semi-Urban,Manager,109567,0 +18153,Male,43,Masters,5,82,5,1,6,2.0,1,71,Urban,Manager,93983,0 +18154,Male,39,Bachelors,15,2,50,98,95,8.0,4,28,Rural,Software Engineer,35528,0 +18155,Male,45,Bachelors,19,47,14,16,53,4.0,3,93,Rural,Software Engineer,124187,0 +18156,Male,21,Bachelors,5,61,89,44,65,4.0,2,21,Urban,Manager,70824,0 +18157,Female,29,Diploma,0,77,37,20,57,2.0,2,89,Semi-Urban,Data Analyst,50697,0 +18158,Male,52,Bachelors,12,67,64,24,66,8.0,5,80,Urban,Software Engineer,24757,1 +18159,Male,37,Masters,14,76,90,28,96,3.0,0,9,Semi-Urban,Software Engineer,139387,0 +18160,Female,33,Bachelors,13,41,15,83,56,8.0,7,91,Urban,ML Engineer,51062,0 +18161,Female,44,Diploma,19,4,47,58,44,6.0,5,74,Urban,HR Executive,100766,0 +18162,Female,50,Bachelors,14,43,73,54,77,8.0,4,63,Urban,Data Analyst,53950,0 +18163,Female,41,High School,1,93,13,96,57,8.0,2,28,Urban,Data Analyst,82656,0 +18164,Female,56,Masters,10,77,99,19,52,1.0,1,72,Rural,ML Engineer,27311,1 +18165,Female,34,Diploma,3,55,46,87,6,5.0,3,89,Semi-Urban,ML Engineer,93694,1 +18166,Male,43,Bachelors,2,86,3,70,95,1.0,4,52,Semi-Urban,ML Engineer,117483,0 +18167,Other,36,Masters,16,89,23,99,46,1.0,1,81,Urban,HR Executive,115417,1 +18168,Male,44,Bachelors,17,8,29,34,67,9.0,3,25,Urban,Software Engineer,54734,0 +18169,Male,34,Bachelors,18,39,29,44,13,8.0,0,66,Urban,Manager,85634,0 +18170,Male,53,Bachelors,1,13,94,88,57,4.0,3,59,Semi-Urban,Manager,98499,1 +18171,Female,37,Masters,4,92,41,12,98,0.0,0,43,Semi-Urban,Data Analyst,81994,0 +18172,Female,55,Bachelors,6,38,48,62,89,8.0,3,69,Rural,Data Analyst,43012,0 +18173,Male,23,Bachelors,17,78,37,0,71,9.0,0,47,Urban,Data Analyst,100158,0 +18174,Male,53,Masters,18,29,14,64,24,0.0,0,47,Urban,ML Engineer,124602,0 +18175,Female,48,PhD,9,10,70,57,46,8.0,7,75,Urban,Software Engineer,118256,0 +18176,Female,48,High School,3,15,75,13,53,5.0,4,41,Rural,HR Executive,65114,0 +18177,Male,25,Bachelors,12,72,79,70,39,6.0,6,61,Urban,Software Engineer,33113,1 +18178,Male,28,High School,4,87,63,9,31,7.0,2,24,Rural,HR Executive,104896,0 +18179,Female,27,Diploma,9,27,1,29,22,7.0,5,6,Urban,Data Analyst,41518,0 +18180,Male,55,High School,11,34,58,34,0,9.0,6,21,Urban,Data Analyst,26915,0 +18181,Female,30,Masters,12,43,62,8,7,4.0,5,64,Urban,Manager,104224,0 +18182,Male,38,Diploma,4,27,92,15,28,4.0,6,12,Rural,HR Executive,35314,0 +18183,Male,26,Bachelors,6,38,51,69,94,5.0,5,21,Urban,Manager,93655,0 +18184,Male,57,Diploma,4,58,68,30,31,6.0,3,99,Urban,Manager,34360,1 +18185,Male,36,PhD,18,83,92,58,41,1.0,1,46,Urban,ML Engineer,113569,1 +18186,Male,59,Masters,11,39,70,96,19,7.0,2,54,Urban,ML Engineer,70448,1 +18187,Male,51,Masters,10,39,7,46,6,6.0,5,13,Urban,ML Engineer,83474,0 +18188,Female,58,Bachelors,17,85,47,41,83,9.0,3,72,Rural,HR Executive,126913,1 +18189,Male,57,PhD,9,93,22,79,30,9.0,5,71,Urban,ML Engineer,102222,1 +18190,Female,41,Bachelors,6,27,45,51,74,7.0,7,47,Semi-Urban,HR Executive,28369,0 +18191,Male,33,Bachelors,5,18,84,86,20,4.0,7,11,Urban,Manager,137385,0 +18192,Female,54,Masters,8,8,82,31,6,0.0,0,22,Urban,HR Executive,105711,0 +18193,Male,29,Diploma,9,73,31,19,19,6.0,5,76,Urban,Software Engineer,126861,0 +18194,Male,54,Diploma,9,20,28,47,67,4.0,0,29,Rural,HR Executive,117227,0 +18195,Male,53,Bachelors,14,9,17,21,78,0.0,2,38,Urban,Data Analyst,134559,0 +18196,Male,30,Diploma,17,25,85,64,76,0.0,7,70,Urban,HR Executive,28618,1 +18197,Female,50,Bachelors,9,10,40,10,95,6.0,6,89,Rural,Data Analyst,89684,0 +18198,Female,35,Masters,0,81,66,0,89,3.0,2,25,Rural,HR Executive,112354,0 +18199,Female,27,Bachelors,10,34,28,60,57,3.0,0,37,Semi-Urban,Software Engineer,125069,0 +18200,Male,27,Bachelors,1,77,58,47,81,5.0,7,80,Urban,Manager,129769,1 +18201,Female,35,Masters,7,97,96,8,26,4.0,0,58,Urban,Software Engineer,133386,1 +18202,Female,46,PhD,8,60,0,78,90,4.0,2,90,Semi-Urban,Manager,102082,0 +18203,Other,39,Bachelors,16,55,87,68,13,9.0,0,3,Urban,Data Analyst,127697,0 +18204,Female,39,Bachelors,8,88,14,92,48,8.0,4,22,Urban,ML Engineer,26343,0 +18205,Male,58,Bachelors,8,66,15,83,87,4.0,2,64,Urban,Manager,53599,0 +18206,Male,59,Diploma,13,47,14,70,61,2.0,3,51,Semi-Urban,Manager,106045,0 +18207,Male,38,Bachelors,8,59,23,74,38,4.0,5,1,Urban,Software Engineer,107530,0 +18208,Female,21,Bachelors,15,39,94,94,1,2.0,0,70,Urban,HR Executive,96717,1 +18209,Male,26,Bachelors,3,93,53,38,3,2.0,4,4,Urban,Manager,31868,0 +18210,Female,40,High School,0,1,66,70,55,5.0,7,7,Rural,Manager,20265,0 +18211,Male,51,Bachelors,8,89,99,6,80,7.0,4,69,Urban,Manager,89331,1 +18212,Male,38,High School,1,45,49,45,57,1.0,6,93,Semi-Urban,Software Engineer,95871,0 +18213,Male,37,Bachelors,19,12,19,41,47,2.0,2,7,Semi-Urban,Data Analyst,93143,0 +18214,Male,52,Masters,0,98,38,49,93,6.0,2,88,Rural,HR Executive,46879,1 +18215,Female,45,Diploma,7,72,14,77,15,0.0,0,35,Urban,ML Engineer,66742,0 +18216,Male,34,Diploma,14,33,12,12,43,8.0,6,40,Urban,HR Executive,131682,0 +18217,Female,25,Bachelors,14,17,51,77,16,3.0,2,3,Rural,Software Engineer,125691,0 +18218,Male,27,Masters,5,36,47,45,51,1.0,3,97,Urban,HR Executive,95266,0 +18219,Male,36,Diploma,17,50,89,49,87,5.0,6,32,Rural,Software Engineer,149194,0 +18220,Female,27,Bachelors,12,82,76,98,53,4.0,7,91,Urban,Data Analyst,55845,1 +18221,Male,40,High School,2,34,21,36,94,9.0,7,32,Semi-Urban,ML Engineer,120724,0 +18222,Female,28,Masters,11,0,78,65,97,2.0,2,49,Urban,Software Engineer,142146,0 +18223,Female,37,Bachelors,19,9,35,75,7,8.0,2,41,Rural,Data Analyst,136718,0 +18224,Female,29,Masters,10,91,89,27,90,0.0,5,68,Urban,Software Engineer,104508,1 +18225,Male,35,Diploma,5,87,84,47,46,8.0,0,71,Urban,HR Executive,54389,1 +18226,Male,31,Bachelors,14,14,46,79,43,5.0,3,74,Semi-Urban,Manager,84552,0 +18227,Female,33,Bachelors,18,37,75,51,78,9.0,0,14,Urban,Manager,77745,0 +18228,Female,56,Masters,11,67,50,17,84,2.0,6,58,Urban,Data Analyst,97019,0 +18229,Female,44,Bachelors,8,53,59,66,13,4.0,0,16,Rural,Data Analyst,115486,0 +18230,Male,25,Diploma,17,3,42,51,20,9.0,3,22,Urban,Manager,61112,0 +18231,Male,48,Bachelors,15,97,65,35,25,0.0,7,60,Semi-Urban,HR Executive,135121,1 +18232,Male,43,Bachelors,0,73,5,69,7,6.0,0,57,Semi-Urban,Software Engineer,75538,0 +18233,Female,22,Diploma,9,11,48,87,94,0.0,7,2,Rural,HR Executive,107265,0 +18234,Male,53,Bachelors,1,71,53,99,7,7.0,6,51,Urban,HR Executive,52492,1 +18235,Male,33,Bachelors,14,7,32,46,88,5.0,2,48,Urban,Software Engineer,134990,0 +18236,Female,34,High School,4,49,28,36,40,6.0,2,17,Urban,Software Engineer,56442,0 +18237,Male,43,Masters,4,75,17,91,55,4.0,4,75,Urban,ML Engineer,87462,1 +18238,Male,44,Bachelors,7,74,67,96,73,6.0,3,5,Urban,ML Engineer,142408,1 +18239,Male,28,Masters,14,71,42,64,86,1.0,7,16,Urban,Manager,106531,0 +18240,Male,21,Masters,9,72,68,23,99,3.0,1,76,Semi-Urban,ML Engineer,105319,1 +18241,Male,24,Masters,9,59,56,76,17,9.0,6,7,Urban,ML Engineer,121285,0 +18242,Male,43,Bachelors,17,81,77,75,6,2.0,4,25,Urban,Manager,23107,1 +18243,Male,34,Diploma,6,0,63,90,20,0.0,1,72,Urban,Manager,50342,0 +18244,Male,46,Bachelors,7,22,88,48,40,5.0,5,3,Urban,Manager,49697,0 +18245,Male,40,Masters,12,62,84,84,52,7.0,2,52,Urban,Data Analyst,52214,1 +18246,Female,37,Diploma,9,21,93,67,37,4.0,7,89,Rural,Data Analyst,126746,1 +18247,Male,50,High School,2,64,39,66,31,2.0,4,0,Urban,ML Engineer,88335,0 +18248,Male,59,Diploma,10,24,29,9,76,7.0,0,10,Rural,HR Executive,42621,0 +18249,Male,35,High School,16,62,35,93,98,4.0,0,43,Rural,HR Executive,30676,0 +18250,Male,49,Masters,6,47,15,25,80,7.0,7,3,Rural,ML Engineer,75993,0 +18251,Male,26,Diploma,12,36,86,72,92,6.0,5,99,Urban,Data Analyst,54748,1 +18252,Male,38,Bachelors,9,4,86,85,72,1.0,1,91,Urban,Manager,122998,1 +18253,Female,52,Diploma,19,94,50,63,67,6.0,0,56,Urban,Data Analyst,147614,1 +18254,Male,40,Diploma,0,46,7,71,55,7.0,1,12,Urban,Data Analyst,27407,0 +18255,Female,21,Bachelors,19,28,57,22,74,3.0,7,54,Rural,ML Engineer,86720,0 +18256,Male,49,PhD,2,74,33,8,40,1.0,5,52,Urban,Software Engineer,69890,0 +18257,Male,25,Diploma,1,99,84,13,54,7.0,6,48,Urban,HR Executive,93913,1 +18258,Male,56,High School,14,70,7,13,5,4.0,1,8,Urban,Manager,131904,0 +18259,Female,24,Diploma,14,45,60,66,0,9.0,0,34,Urban,Data Analyst,97301,0 +18260,Male,57,Diploma,1,30,38,15,90,7.0,1,26,Rural,ML Engineer,89612,0 +18261,Male,51,Bachelors,3,83,74,11,55,4.0,5,52,Rural,Manager,82388,0 +18262,Male,58,Masters,15,32,3,76,55,0.0,0,37,Urban,HR Executive,143224,0 +18263,Male,42,Bachelors,10,32,24,52,97,1.0,3,6,Semi-Urban,HR Executive,119287,0 +18264,Female,22,High School,15,56,53,6,34,5.0,2,32,Semi-Urban,ML Engineer,142881,0 +18265,Male,55,High School,12,82,82,46,13,5.0,2,71,Semi-Urban,HR Executive,93167,1 +18266,Female,39,Diploma,15,41,82,70,68,1.0,7,4,Urban,Data Analyst,130239,0 +18267,Female,31,High School,18,14,75,41,55,7.0,7,69,Semi-Urban,Software Engineer,139097,0 +18268,Male,45,Bachelors,17,33,67,79,7,5.0,7,24,Urban,ML Engineer,118110,0 +18269,Male,21,Masters,14,7,41,86,53,9.0,3,76,Rural,Data Analyst,127874,0 +18270,Female,52,Diploma,5,67,31,61,6,5.0,4,76,Urban,Manager,53467,0 +18271,Male,27,Bachelors,8,72,20,17,40,1.0,6,27,Rural,Manager,149771,0 +18272,Male,32,High School,15,13,43,43,62,5.0,5,0,Urban,ML Engineer,106774,0 +18273,Female,55,High School,5,30,74,8,82,1.0,2,50,Urban,ML Engineer,20279,0 +18274,Female,22,High School,16,0,14,11,81,3.0,7,70,Semi-Urban,Manager,116591,0 +18275,Female,54,Diploma,15,69,56,52,11,3.0,7,11,Urban,ML Engineer,97273,0 +18276,Female,38,Bachelors,0,10,82,41,10,2.0,4,61,Urban,Data Analyst,131336,0 +18277,Male,29,High School,19,68,41,15,2,1.0,1,66,Urban,ML Engineer,68395,0 +18278,Male,23,Masters,18,67,79,83,0,5.0,4,65,Semi-Urban,HR Executive,149616,1 +18279,Male,47,Diploma,10,92,83,36,71,4.0,4,36,Semi-Urban,Manager,96814,1 +18280,Female,49,Bachelors,9,56,56,4,5,3.0,0,21,Urban,Manager,81249,0 +18281,Other,34,Diploma,1,89,24,30,34,5.0,5,7,Semi-Urban,Data Analyst,122554,0 +18282,Male,28,Bachelors,18,67,19,79,33,1.0,0,57,Urban,ML Engineer,118618,0 +18283,Male,52,Bachelors,9,61,4,49,72,8.0,4,61,Rural,Data Analyst,41408,0 +18284,Male,44,Diploma,11,59,5,39,6,6.0,2,52,Urban,Manager,104518,0 +18285,Female,46,Diploma,8,70,9,27,31,8.0,0,32,Rural,Manager,33804,0 +18286,Male,31,Bachelors,15,25,6,93,83,8.0,7,85,Rural,ML Engineer,121967,0 +18287,Male,25,High School,3,61,58,26,31,0.0,7,57,Semi-Urban,ML Engineer,113807,0 +18288,Other,54,Masters,1,92,76,91,43,9.0,0,30,Urban,Data Analyst,122416,1 +18289,Female,59,Diploma,15,99,77,35,35,5.0,6,95,Semi-Urban,HR Executive,103361,1 +18290,Male,28,Masters,11,0,91,58,34,4.0,6,0,Urban,Manager,51706,0 +18291,Female,35,Masters,4,50,70,34,36,5.0,3,53,Urban,ML Engineer,106248,0 +18292,Male,35,PhD,14,13,19,76,29,0.0,7,80,Urban,Manager,92359,0 +18293,Male,56,Bachelors,10,14,4,30,23,4.0,5,83,Rural,HR Executive,53199,0 +18294,Male,45,Bachelors,9,53,75,43,70,8.0,0,95,Urban,Software Engineer,43556,1 +18295,Female,57,Bachelors,5,43,27,21,45,4.0,5,52,Rural,Data Analyst,139843,0 +18296,Female,41,High School,15,15,18,86,81,7.0,0,41,Semi-Urban,Manager,45925,0 +18297,Male,26,Diploma,4,9,21,20,94,4.0,7,34,Rural,Data Analyst,136574,0 +18298,Other,53,Bachelors,17,57,41,91,74,8.0,2,38,Semi-Urban,ML Engineer,35208,0 +18299,Male,38,Diploma,13,98,63,20,4,7.0,2,55,Urban,Manager,70300,1 +18300,Female,27,Bachelors,3,48,60,2,13,0.0,4,31,Semi-Urban,HR Executive,83709,0 +18301,Female,47,Diploma,11,36,37,62,25,8.0,6,3,Rural,HR Executive,129904,0 +18302,Male,44,High School,10,2,31,16,20,4.0,6,9,Rural,Software Engineer,127354,0 +18303,Male,56,PhD,5,50,21,72,37,1.0,1,90,Rural,Manager,27711,0 +18304,Female,38,High School,3,63,99,26,83,8.0,1,23,Urban,ML Engineer,102884,0 +18305,Male,43,Bachelors,13,28,89,5,81,6.0,2,74,Urban,Data Analyst,60365,0 +18306,Female,22,Diploma,14,72,83,45,17,3.0,0,98,Semi-Urban,Data Analyst,60129,1 +18307,Male,27,Bachelors,9,52,41,94,73,3.0,6,34,Urban,HR Executive,46581,0 +18308,Female,57,Diploma,2,36,43,9,78,4.0,0,33,Urban,ML Engineer,70496,0 +18309,Male,40,Bachelors,0,22,16,10,74,8.0,3,8,Urban,HR Executive,61377,0 +18310,Male,58,Bachelors,12,29,54,50,56,9.0,4,26,Urban,Software Engineer,44475,0 +18311,Male,30,Bachelors,7,52,98,23,76,9.0,5,30,Rural,Manager,70734,0 +18312,Female,21,PhD,4,47,61,81,75,2.0,0,29,Urban,ML Engineer,55264,0 +18313,Male,29,Diploma,12,6,60,2,7,6.0,3,49,Urban,Data Analyst,27051,0 +18314,Male,55,Masters,10,46,13,36,6,8.0,0,1,Rural,HR Executive,125894,0 +18315,Female,21,Diploma,1,64,73,79,88,3.0,2,40,Semi-Urban,HR Executive,103846,1 +18316,Female,53,PhD,7,5,55,15,29,0.0,7,80,Urban,Software Engineer,42384,0 +18317,Male,56,Bachelors,16,1,8,72,71,1.0,2,11,Urban,ML Engineer,134746,0 +18318,Other,54,Masters,15,58,33,61,6,4.0,1,95,Urban,Software Engineer,110549,1 +18319,Female,27,High School,19,12,67,48,10,8.0,3,46,Urban,Data Analyst,110670,0 +18320,Male,43,High School,19,43,92,54,2,4.0,1,91,Urban,Software Engineer,136556,1 +18321,Male,38,Bachelors,1,2,6,85,96,4.0,0,53,Urban,HR Executive,118856,0 +18322,Female,21,Bachelors,19,37,7,54,11,3.0,6,58,Urban,Manager,149733,0 +18323,Female,31,Bachelors,8,81,97,49,49,9.0,2,51,Rural,Manager,142302,1 +18324,Male,40,High School,1,7,1,6,18,5.0,7,23,Urban,HR Executive,86395,0 +18325,Male,40,Diploma,8,82,47,56,22,1.0,7,37,Urban,Manager,33759,0 +18326,Male,52,High School,7,96,93,53,10,4.0,1,25,Urban,Software Engineer,44378,1 +18327,Male,52,Bachelors,12,94,5,59,16,3.0,7,44,Urban,Software Engineer,63205,0 +18328,Male,40,Masters,9,95,69,75,76,7.0,7,73,Urban,Data Analyst,132347,1 +18329,Male,47,PhD,5,37,14,12,25,2.0,0,33,Urban,ML Engineer,48579,0 +18330,Female,24,High School,4,95,27,99,68,0.0,4,29,Rural,ML Engineer,42612,1 +18331,Female,53,Bachelors,5,28,9,47,17,7.0,5,77,Urban,Data Analyst,132015,0 +18332,Male,41,Diploma,17,95,50,43,55,1.0,2,50,Urban,ML Engineer,61834,1 +18333,Male,43,Bachelors,10,66,37,17,15,7.0,4,50,Urban,Software Engineer,96580,0 +18334,Male,55,PhD,9,83,34,69,77,2.0,2,75,Urban,HR Executive,71397,1 +18335,Male,25,Bachelors,13,93,51,54,79,6.0,4,95,Semi-Urban,Software Engineer,87463,1 +18336,Other,26,Bachelors,15,29,6,36,9,8.0,0,87,Urban,HR Executive,68004,0 +18337,Female,52,Bachelors,5,96,10,12,83,3.0,5,63,Semi-Urban,Software Engineer,139653,0 +18338,Male,26,Bachelors,2,1,45,44,48,8.0,5,2,Semi-Urban,Data Analyst,58232,0 +18339,Male,46,Diploma,18,50,30,68,81,3.0,2,30,Semi-Urban,Manager,149377,0 +18340,Male,29,Bachelors,13,63,86,9,56,5.0,0,51,Urban,Software Engineer,111178,0 +18341,Female,21,Diploma,10,85,16,77,62,1.0,0,0,Urban,ML Engineer,132647,0 +18342,Male,41,Bachelors,12,13,15,81,93,9.0,1,31,Semi-Urban,ML Engineer,133003,0 +18343,Female,42,Diploma,13,13,2,10,91,9.0,5,8,Urban,Software Engineer,74590,0 +18344,Female,44,High School,10,17,86,64,58,7.0,7,1,Urban,Software Engineer,70186,0 +18345,Male,57,Bachelors,12,83,42,54,29,3.0,3,78,Semi-Urban,Manager,94633,1 +18346,Female,41,High School,4,52,73,17,35,4.0,7,63,Urban,Data Analyst,27320,0 +18347,Female,35,High School,14,87,75,27,48,9.0,6,40,Semi-Urban,Data Analyst,144594,0 +18348,Female,30,PhD,1,81,87,8,75,9.0,4,72,Semi-Urban,Software Engineer,55611,1 +18349,Other,46,Bachelors,15,8,91,19,34,7.0,5,51,Semi-Urban,Data Analyst,68437,0 +18350,Male,30,Bachelors,2,78,47,5,75,5.0,7,78,Semi-Urban,Data Analyst,143648,0 +18351,Male,46,Bachelors,2,41,35,43,86,9.0,6,31,Urban,HR Executive,126837,0 +18352,Female,27,Masters,10,51,62,16,73,3.0,2,1,Semi-Urban,ML Engineer,139726,0 +18353,Female,29,Bachelors,14,88,48,49,94,7.0,3,38,Urban,HR Executive,112031,0 +18354,Female,33,Bachelors,18,84,23,69,99,3.0,7,26,Urban,ML Engineer,104766,0 +18355,Male,52,Bachelors,11,45,28,26,23,8.0,3,9,Semi-Urban,HR Executive,111923,0 +18356,Female,56,High School,16,21,63,60,71,2.0,5,6,Semi-Urban,Software Engineer,145085,0 +18357,Male,44,High School,12,86,16,20,51,7.0,5,72,Rural,Data Analyst,60955,0 +18358,Male,37,Bachelors,6,85,62,12,82,5.0,5,66,Rural,Software Engineer,135026,0 +18359,Male,59,High School,13,11,96,11,74,7.0,6,22,Semi-Urban,Data Analyst,58196,0 +18360,Male,22,Masters,16,52,21,88,40,2.0,0,75,Urban,Data Analyst,26039,1 +18361,Male,52,Masters,7,25,77,32,76,1.0,5,65,Urban,Manager,42288,0 +18362,Female,26,Diploma,7,8,38,44,88,7.0,6,51,Urban,HR Executive,43044,0 +18363,Male,46,Bachelors,19,93,16,23,95,8.0,0,52,Urban,ML Engineer,93456,0 +18364,Male,38,Bachelors,18,50,43,99,82,8.0,5,19,Urban,Manager,141293,0 +18365,Male,36,Diploma,14,48,97,82,98,5.0,4,4,Urban,Manager,61531,0 +18366,Male,25,Masters,13,92,58,7,82,7.0,0,8,Urban,Data Analyst,54515,0 +18367,Female,55,Masters,19,14,88,21,19,0.0,0,83,Urban,Software Engineer,124946,0 +18368,Male,53,Masters,19,87,18,9,29,6.0,4,9,Rural,Software Engineer,142323,0 +18369,Male,40,Bachelors,0,69,27,52,27,9.0,2,33,Urban,Manager,141025,0 +18370,Female,24,Bachelors,9,53,70,20,24,2.0,4,91,Semi-Urban,ML Engineer,77815,0 +18371,Female,54,High School,2,84,94,70,97,5.0,6,7,Rural,Software Engineer,97264,1 +18372,Female,54,Bachelors,3,49,78,17,83,0.0,6,7,Urban,Software Engineer,23806,0 +18373,Female,27,High School,0,30,46,69,46,2.0,2,14,Urban,Manager,41795,0 +18374,Female,54,Diploma,12,52,95,11,5,2.0,4,21,Rural,ML Engineer,25796,0 +18375,Male,52,Masters,19,59,97,40,29,1.0,2,28,Semi-Urban,HR Executive,125962,0 +18376,Other,46,Bachelors,9,74,8,41,7,1.0,4,76,Urban,Data Analyst,34895,0 +18377,Female,49,Bachelors,10,20,70,80,55,2.0,1,20,Rural,ML Engineer,37274,0 +18378,Male,38,Masters,2,99,38,67,17,0.0,1,10,Urban,Software Engineer,55913,0 +18379,Female,58,Bachelors,0,4,7,74,0,2.0,6,67,Urban,HR Executive,30275,0 +18380,Female,45,Masters,0,36,20,9,69,5.0,1,69,Urban,HR Executive,59397,0 +18381,Male,48,Diploma,18,24,84,50,68,2.0,0,84,Rural,Manager,105115,1 +18382,Male,21,Masters,16,55,25,85,67,8.0,0,72,Urban,Software Engineer,59007,1 +18383,Other,24,Bachelors,2,5,95,61,93,5.0,4,98,Semi-Urban,HR Executive,63413,1 +18384,Male,36,Bachelors,7,26,23,0,7,1.0,4,52,Urban,HR Executive,54255,0 +18385,Male,27,Bachelors,3,18,97,77,59,6.0,3,18,Urban,Data Analyst,38960,0 +18386,Female,34,Masters,3,40,73,81,99,2.0,6,60,Urban,Software Engineer,91720,1 +18387,Male,22,Diploma,17,11,20,39,17,9.0,3,31,Urban,Data Analyst,58861,0 +18388,Male,39,Diploma,14,94,25,71,42,5.0,3,62,Urban,Software Engineer,117902,1 +18389,Female,33,Masters,5,48,9,53,34,3.0,0,25,Urban,Manager,99662,0 +18390,Female,31,Masters,17,99,31,6,10,9.0,3,91,Semi-Urban,Manager,148631,0 +18391,Male,21,Bachelors,16,48,68,23,36,8.0,6,54,Urban,HR Executive,123429,0 +18392,Other,55,High School,13,2,86,33,72,4.0,5,99,Urban,ML Engineer,71313,0 +18393,Male,40,PhD,13,60,34,94,48,2.0,4,74,Urban,Manager,107332,1 +18394,Male,49,Masters,1,42,29,50,68,7.0,3,54,Rural,HR Executive,28802,0 +18395,Male,52,High School,9,64,11,63,99,2.0,1,40,Urban,ML Engineer,35887,0 +18396,Female,54,Diploma,2,56,1,1,25,2.0,6,71,Semi-Urban,Software Engineer,57389,0 +18397,Male,33,Masters,0,34,15,15,16,6.0,6,86,Semi-Urban,Data Analyst,119052,0 +18398,Male,59,Bachelors,17,87,9,77,5,9.0,7,21,Urban,HR Executive,119422,0 +18399,Female,35,High School,13,55,62,63,36,1.0,2,22,Urban,ML Engineer,47994,0 +18400,Male,48,Diploma,17,52,61,30,47,6.0,6,16,Rural,HR Executive,63203,0 +18401,Female,33,Diploma,11,7,25,38,49,9.0,4,35,Urban,HR Executive,118093,0 +18402,Male,25,Diploma,19,92,96,44,17,2.0,0,54,Urban,HR Executive,62559,1 +18403,Other,45,Masters,10,48,45,14,76,7.0,1,27,Urban,ML Engineer,126026,0 +18404,Male,45,High School,14,6,45,22,59,4.0,7,89,Rural,Software Engineer,25280,0 +18405,Male,56,Masters,11,51,52,34,14,8.0,7,41,Rural,Manager,149204,0 +18406,Male,50,Bachelors,6,18,32,89,46,8.0,7,31,Urban,HR Executive,63240,0 +18407,Female,57,Bachelors,11,80,30,10,94,0.0,7,78,Rural,Software Engineer,38694,0 +18408,Female,29,High School,17,79,67,12,45,8.0,2,5,Semi-Urban,Data Analyst,82756,0 +18409,Male,22,Diploma,8,56,13,0,51,1.0,5,45,Rural,HR Executive,21689,0 +18410,Female,28,Diploma,15,51,93,14,24,7.0,1,89,Rural,ML Engineer,101373,1 +18411,Male,47,Bachelors,12,60,38,16,74,1.0,5,83,Rural,Data Analyst,37267,0 +18412,Other,26,Diploma,15,65,48,17,56,6.0,2,2,Urban,Manager,86093,0 +18413,Female,27,PhD,0,0,59,53,64,5.0,6,48,Urban,Data Analyst,35608,0 +18414,Other,51,Diploma,18,6,74,41,83,6.0,3,28,Urban,Manager,125078,0 +18415,Female,25,Bachelors,15,34,93,23,28,6.0,0,88,Urban,Data Analyst,94604,0 +18416,Female,22,Bachelors,7,39,83,1,28,3.0,2,84,Urban,Software Engineer,110436,0 +18417,Male,56,Diploma,12,13,16,3,70,6.0,4,55,Urban,Manager,45549,0 +18418,Female,42,High School,17,64,42,82,98,3.0,4,74,Rural,Data Analyst,139069,1 +18419,Female,46,Masters,12,6,45,88,27,3.0,6,33,Urban,Software Engineer,99975,0 +18420,Other,51,Bachelors,19,74,21,71,24,8.0,1,93,Urban,Manager,75546,1 +18421,Male,58,Bachelors,3,83,84,46,2,2.0,6,98,Semi-Urban,Software Engineer,129142,1 +18422,Male,56,Masters,6,31,35,41,4,3.0,0,97,Urban,Data Analyst,67399,0 +18423,Male,44,Masters,6,78,41,39,23,9.0,0,71,Urban,ML Engineer,22190,0 +18424,Female,48,Masters,4,97,66,13,93,8.0,6,88,Semi-Urban,Software Engineer,124237,1 +18425,Male,31,Masters,7,35,5,62,28,8.0,7,18,Urban,HR Executive,79122,0 +18426,Male,52,Bachelors,3,77,8,95,40,2.0,6,51,Rural,Manager,137059,0 +18427,Male,52,Bachelors,9,2,31,3,38,1.0,2,67,Urban,ML Engineer,128768,0 +18428,Male,37,Bachelors,0,20,94,21,45,4.0,6,62,Semi-Urban,HR Executive,60593,0 +18429,Male,43,Bachelors,9,97,60,73,21,0.0,7,26,Rural,Software Engineer,115228,1 +18430,Male,40,High School,0,45,71,11,81,4.0,6,34,Urban,Software Engineer,89224,0 +18431,Female,38,High School,18,72,76,99,34,6.0,1,2,Semi-Urban,HR Executive,99357,1 +18432,Female,33,Bachelors,2,70,76,5,73,1.0,3,99,Urban,ML Engineer,37427,1 +18433,Male,57,Diploma,6,82,46,89,36,8.0,3,18,Semi-Urban,ML Engineer,94418,1 +18434,Female,31,Masters,4,92,88,69,40,5.0,5,89,Semi-Urban,Manager,113067,1 +18435,Female,30,Bachelors,3,89,83,42,72,4.0,1,1,Semi-Urban,Data Analyst,98417,0 +18436,Male,51,High School,14,43,7,79,51,0.0,1,26,Semi-Urban,ML Engineer,46550,0 +18437,Male,36,High School,6,92,35,15,81,5.0,6,10,Rural,Software Engineer,138250,0 +18438,Female,39,Diploma,15,3,74,51,7,7.0,6,58,Rural,Data Analyst,116922,0 +18439,Male,38,Diploma,9,16,5,9,74,0.0,2,89,Urban,Software Engineer,38274,0 +18440,Female,52,PhD,5,91,90,33,58,4.0,4,10,Urban,Manager,134747,0 +18441,Male,47,Diploma,17,47,44,7,82,9.0,6,27,Rural,Software Engineer,78150,0 +18442,Male,55,Bachelors,19,39,44,94,20,4.0,1,41,Semi-Urban,Data Analyst,39112,0 +18443,Other,27,Bachelors,2,60,83,80,31,3.0,2,80,Urban,Manager,60749,1 +18444,Male,42,Masters,19,89,6,89,85,6.0,4,8,Urban,ML Engineer,133323,0 +18445,Female,41,High School,14,43,84,2,33,0.0,4,82,Semi-Urban,HR Executive,84958,0 +18446,Male,46,High School,13,10,95,34,52,1.0,3,69,Urban,HR Executive,119326,0 +18447,Male,58,High School,6,98,22,17,13,5.0,6,79,Rural,ML Engineer,45842,0 +18448,Male,30,Bachelors,17,68,44,86,87,6.0,2,8,Urban,HR Executive,60183,0 +18449,Male,46,Bachelors,16,43,21,53,25,7.0,3,66,Semi-Urban,Software Engineer,20804,0 +18450,Male,38,High School,6,34,66,58,96,3.0,6,12,Urban,Manager,52350,0 +18451,Male,28,High School,4,29,95,20,98,8.0,5,35,Rural,HR Executive,39258,0 +18452,Male,25,Bachelors,19,84,7,53,80,3.0,6,61,Urban,HR Executive,134888,0 +18453,Female,56,Diploma,9,15,14,91,86,0.0,2,78,Urban,Data Analyst,142991,0 +18454,Male,58,Bachelors,5,51,21,72,70,0.0,1,98,Urban,HR Executive,148460,1 +18455,Female,59,Bachelors,18,96,74,73,4,5.0,5,31,Semi-Urban,ML Engineer,148392,1 +18456,Male,48,Masters,9,57,25,92,77,9.0,2,56,Urban,HR Executive,33458,0 +18457,Male,59,Bachelors,8,61,52,45,90,4.0,7,55,Urban,Manager,48873,0 +18458,Female,24,Bachelors,0,52,34,55,50,4.0,4,90,Urban,ML Engineer,23629,0 +18459,Male,25,Bachelors,8,6,6,22,70,5.0,1,85,Urban,ML Engineer,119934,0 +18460,Male,27,Masters,2,91,25,97,24,7.0,5,85,Semi-Urban,Manager,98466,1 +18461,Male,43,Bachelors,0,52,5,36,68,2.0,3,87,Rural,HR Executive,64386,0 +18462,Female,43,Bachelors,17,7,56,64,79,3.0,7,31,Urban,HR Executive,94433,0 +18463,Female,40,Diploma,16,95,13,85,39,0.0,3,9,Semi-Urban,Data Analyst,47854,0 +18464,Male,47,Masters,10,0,89,11,44,5.0,3,42,Semi-Urban,HR Executive,101339,0 +18465,Male,21,Masters,3,64,0,84,44,6.0,0,44,Urban,Manager,89590,0 +18466,Female,33,High School,13,88,83,41,66,4.0,5,94,Urban,ML Engineer,94889,1 +18467,Male,31,Diploma,13,43,17,80,21,3.0,6,54,Urban,ML Engineer,113408,0 +18468,Male,21,Bachelors,8,98,34,28,37,0.0,0,50,Urban,Software Engineer,128018,0 +18469,Male,33,Bachelors,2,13,65,90,32,4.0,5,61,Urban,Manager,32380,0 +18470,Male,28,Bachelors,9,49,46,3,36,5.0,4,93,Semi-Urban,HR Executive,61176,0 +18471,Male,54,High School,0,37,41,19,90,9.0,7,35,Urban,Software Engineer,130827,0 +18472,Female,55,High School,16,92,94,64,81,9.0,3,89,Semi-Urban,ML Engineer,72736,1 +18473,Male,44,Bachelors,19,48,9,85,78,3.0,7,29,Rural,ML Engineer,48353,0 +18474,Male,23,Bachelors,4,45,83,18,80,0.0,2,39,Urban,Manager,25630,0 +18475,Female,30,Bachelors,6,97,79,18,17,9.0,6,43,Urban,ML Engineer,25229,0 +18476,Male,55,High School,3,97,22,23,52,9.0,0,72,Rural,Software Engineer,57439,0 +18477,Male,56,High School,3,18,34,36,68,2.0,7,36,Semi-Urban,ML Engineer,79081,0 +18478,Male,34,High School,1,78,20,23,31,5.0,6,20,Urban,HR Executive,111917,0 +18479,Female,56,Diploma,10,85,70,68,50,8.0,4,55,Semi-Urban,Manager,120388,1 +18480,Male,44,Diploma,17,42,38,10,82,7.0,5,68,Semi-Urban,Data Analyst,120306,0 +18481,Male,59,Diploma,11,65,8,30,11,4.0,1,46,Rural,HR Executive,44333,0 +18482,Other,29,Diploma,13,75,37,80,40,0.0,3,57,Rural,Manager,72389,1 +18483,Female,27,Bachelors,0,44,39,70,13,6.0,7,69,Rural,Manager,30476,0 +18484,Female,59,Bachelors,11,90,21,43,28,5.0,7,36,Rural,ML Engineer,43818,0 +18485,Male,55,Bachelors,0,10,64,80,12,5.0,5,17,Rural,Software Engineer,119382,0 +18486,Male,33,PhD,13,60,27,51,44,9.0,4,19,Rural,Software Engineer,77194,0 +18487,Male,46,Bachelors,5,89,29,69,33,5.0,3,49,Urban,HR Executive,43472,1 +18488,Male,25,Masters,11,87,44,88,16,6.0,1,14,Rural,Manager,89162,0 +18489,Female,37,Diploma,11,42,83,2,81,1.0,3,18,Urban,Software Engineer,83696,0 +18490,Male,31,Masters,2,53,69,53,29,2.0,6,26,Rural,Data Analyst,54307,0 +18491,Female,42,Masters,8,59,58,34,50,4.0,5,45,Urban,ML Engineer,86435,0 +18492,Male,37,Diploma,19,40,28,24,42,5.0,6,40,Rural,Manager,67960,0 +18493,Male,21,Masters,16,33,96,97,62,7.0,1,38,Rural,HR Executive,52111,1 +18494,Female,52,Masters,8,28,77,20,82,5.0,2,94,Semi-Urban,HR Executive,84413,0 +18495,Male,35,Diploma,13,85,11,36,38,3.0,0,14,Urban,Data Analyst,109101,0 +18496,Female,36,Bachelors,3,42,10,82,78,0.0,1,83,Rural,Software Engineer,73507,0 +18497,Other,33,Bachelors,1,29,89,75,43,2.0,7,40,Semi-Urban,HR Executive,27110,0 +18498,Male,44,Bachelors,13,99,53,49,74,4.0,7,28,Semi-Urban,Data Analyst,33273,0 +18499,Male,55,Bachelors,18,88,39,16,93,0.0,4,37,Urban,Manager,51727,0 +18500,Male,29,Bachelors,2,56,87,54,65,8.0,1,44,Urban,ML Engineer,145913,1 +18501,Female,34,Bachelors,14,21,70,64,51,2.0,3,37,Urban,Manager,127026,0 +18502,Male,24,Bachelors,14,88,86,68,82,5.0,5,70,Rural,Software Engineer,75849,1 +18503,Female,54,Bachelors,9,34,15,76,75,2.0,7,54,Semi-Urban,HR Executive,35064,0 +18504,Male,22,Masters,10,32,72,40,49,4.0,1,3,Urban,Software Engineer,42511,0 +18505,Female,44,Bachelors,7,87,80,45,87,2.0,7,35,Urban,Data Analyst,56086,1 +18506,Female,55,Bachelors,18,89,64,12,89,4.0,4,23,Urban,HR Executive,136368,0 +18507,Male,34,Bachelors,7,21,86,12,73,0.0,7,52,Urban,Data Analyst,141922,0 +18508,Male,44,Masters,6,83,25,88,20,5.0,4,47,Urban,ML Engineer,45462,1 +18509,Male,21,Bachelors,1,49,94,83,46,0.0,0,14,Rural,ML Engineer,44668,1 +18510,Male,36,Bachelors,4,83,97,9,7,3.0,1,92,Urban,HR Executive,84432,1 +18511,Male,21,PhD,15,28,95,61,53,9.0,1,87,Semi-Urban,HR Executive,131390,1 +18512,Male,48,High School,10,60,26,11,9,7.0,5,7,Semi-Urban,Software Engineer,22318,0 +18513,Female,24,Bachelors,2,89,33,79,48,4.0,7,51,Semi-Urban,Software Engineer,119361,1 +18514,Female,44,Bachelors,18,41,76,56,26,4.0,4,14,Semi-Urban,Manager,100192,0 +18515,Female,35,High School,8,76,97,51,67,1.0,2,47,Semi-Urban,HR Executive,112978,1 +18516,Male,44,Bachelors,17,17,13,66,97,7.0,5,49,Urban,Software Engineer,113263,0 +18517,Female,21,High School,16,60,20,36,15,8.0,0,67,Semi-Urban,Data Analyst,108802,0 +18518,Male,59,Bachelors,3,97,31,16,8,1.0,2,84,Rural,Data Analyst,114309,0 +18519,Male,51,Diploma,2,81,27,54,28,1.0,7,2,Urban,Data Analyst,39900,0 +18520,Male,27,Diploma,8,46,62,41,90,5.0,7,99,Urban,Software Engineer,85574,1 +18521,Male,31,Bachelors,11,7,48,48,88,3.0,0,23,Urban,Data Analyst,114675,0 +18522,Male,25,Diploma,13,22,15,50,73,0.0,1,55,Urban,HR Executive,139960,0 +18523,Male,50,Bachelors,4,86,70,77,82,2.0,4,25,Urban,ML Engineer,68040,1 +18524,Other,57,Bachelors,19,69,94,91,18,5.0,3,42,Urban,ML Engineer,54250,1 +18525,Male,31,High School,4,95,62,5,44,4.0,3,7,Urban,Manager,34179,0 +18526,Female,54,Bachelors,6,44,3,10,27,4.0,5,7,Urban,HR Executive,100199,0 +18527,Male,52,PhD,8,64,1,0,5,3.0,2,6,Rural,Manager,107673,0 +18528,Male,43,High School,1,66,93,87,84,3.0,4,68,Urban,HR Executive,83497,1 +18529,Male,22,Diploma,13,44,28,66,69,7.0,4,69,Urban,Software Engineer,134041,0 +18530,Female,29,Masters,5,78,40,54,96,2.0,0,71,Urban,Software Engineer,27640,1 +18531,Male,56,Masters,8,58,72,35,11,6.0,4,9,Rural,HR Executive,120442,0 +18532,Male,38,Bachelors,18,24,14,62,13,2.0,4,42,Urban,HR Executive,134215,0 +18533,Male,32,Diploma,3,92,61,42,74,4.0,6,41,Urban,ML Engineer,134238,1 +18534,Male,21,Bachelors,8,10,49,73,49,0.0,1,65,Urban,Software Engineer,133224,0 +18535,Female,54,Bachelors,8,24,61,57,50,6.0,1,22,Urban,HR Executive,76107,0 +18536,Male,24,Diploma,13,90,66,29,73,1.0,1,8,Rural,ML Engineer,128272,0 +18537,Male,26,High School,0,69,66,83,35,6.0,6,74,Rural,ML Engineer,96181,1 +18538,Female,44,Diploma,8,31,23,36,15,7.0,5,65,Urban,HR Executive,39087,0 +18539,Male,52,Bachelors,13,67,74,29,21,2.0,3,88,Urban,Software Engineer,51329,1 +18540,Female,57,Bachelors,13,84,96,78,13,5.0,1,39,Rural,Data Analyst,94716,1 +18541,Female,48,Bachelors,5,13,19,89,84,7.0,4,66,Urban,HR Executive,124248,0 +18542,Other,30,Bachelors,15,64,81,13,84,5.0,0,36,Semi-Urban,Data Analyst,95574,0 +18543,Male,34,Bachelors,15,54,78,31,76,3.0,2,1,Rural,Software Engineer,116235,0 +18544,Female,43,Bachelors,16,81,3,6,63,0.0,5,19,Semi-Urban,Manager,134360,0 +18545,Male,59,Bachelors,2,95,61,68,16,0.0,1,98,Urban,Software Engineer,78638,1 +18546,Female,58,Diploma,18,29,72,18,11,0.0,3,39,Rural,Manager,87485,0 +18547,Male,48,Masters,0,53,56,37,77,9.0,7,41,Urban,Manager,67825,0 +18548,Male,21,Bachelors,0,46,75,12,96,4.0,4,82,Semi-Urban,HR Executive,93248,0 +18549,Female,56,Diploma,15,4,33,10,65,2.0,3,45,Rural,Data Analyst,103701,0 +18550,Male,50,Bachelors,14,18,32,77,38,3.0,7,31,Urban,HR Executive,119268,0 +18551,Female,48,High School,9,45,32,3,65,7.0,0,87,Urban,Software Engineer,82652,0 +18552,Female,35,Diploma,11,48,33,89,20,6.0,4,27,Semi-Urban,Data Analyst,93713,0 +18553,Male,49,High School,2,72,6,24,85,7.0,0,62,Rural,HR Executive,148625,0 +18554,Male,59,Masters,14,87,57,57,7,1.0,7,93,Rural,Software Engineer,121056,1 +18555,Male,59,High School,3,63,69,36,42,0.0,5,20,Semi-Urban,ML Engineer,96501,0 +18556,Other,41,Bachelors,10,61,93,90,57,0.0,0,78,Urban,HR Executive,138159,1 +18557,Male,53,Masters,12,14,53,16,36,7.0,1,22,Semi-Urban,Data Analyst,89514,0 +18558,Male,37,Bachelors,4,14,86,70,38,7.0,2,64,Semi-Urban,Software Engineer,22939,0 +18559,Female,47,PhD,9,15,5,51,10,3.0,4,14,Urban,HR Executive,132925,0 +18560,Female,45,Bachelors,2,92,5,79,26,9.0,4,38,Rural,ML Engineer,89624,0 +18561,Female,52,High School,7,99,78,48,39,0.0,6,28,Urban,HR Executive,132660,1 +18562,Female,35,High School,19,44,76,87,36,0.0,3,1,Rural,Manager,119851,0 +18563,Male,22,Masters,15,65,12,35,61,3.0,6,54,Rural,Manager,88281,0 +18564,Male,31,Bachelors,7,2,75,71,91,7.0,4,11,Rural,Software Engineer,136229,0 +18565,Male,23,High School,12,11,11,10,33,3.0,3,82,Semi-Urban,ML Engineer,53317,0 +18566,Female,37,Masters,0,61,37,37,7,3.0,3,75,Urban,HR Executive,109764,0 +18567,Female,45,Masters,11,4,77,3,74,5.0,0,26,Urban,HR Executive,58136,0 +18568,Female,45,Bachelors,14,31,72,56,15,2.0,0,54,Urban,ML Engineer,50934,0 +18569,Female,56,Diploma,8,21,75,87,89,7.0,7,33,Urban,Manager,146868,0 +18570,Male,35,Bachelors,8,19,64,1,71,0.0,0,54,Semi-Urban,Manager,44063,0 +18571,Male,51,Diploma,18,59,24,59,16,7.0,4,49,Urban,Data Analyst,68679,0 +18572,Male,43,Diploma,3,57,33,38,53,8.0,2,77,Urban,Software Engineer,98198,0 +18573,Male,45,Diploma,18,10,55,52,61,0.0,4,13,Urban,ML Engineer,22534,0 +18574,Female,39,Masters,17,87,39,80,79,8.0,3,76,Urban,HR Executive,113764,1 +18575,Male,56,High School,6,70,22,71,82,1.0,1,4,Urban,Data Analyst,44046,0 +18576,Female,21,Masters,5,63,77,70,33,3.0,0,13,Urban,Manager,41988,0 +18577,Female,36,Masters,3,89,63,47,26,7.0,5,12,Urban,HR Executive,67579,0 +18578,Male,28,Diploma,12,9,43,13,68,0.0,0,91,Urban,HR Executive,101227,0 +18579,Male,48,High School,18,16,63,36,55,4.0,5,79,Urban,ML Engineer,57116,0 +18580,Male,44,Masters,10,6,61,71,83,8.0,6,4,Rural,Software Engineer,89869,0 +18581,Male,24,Bachelors,15,26,44,7,97,8.0,0,28,Urban,Data Analyst,53291,0 +18582,Female,43,Bachelors,12,37,61,56,13,7.0,0,32,Urban,Manager,133012,0 +18583,Male,38,Diploma,16,11,42,95,93,8.0,3,50,Urban,ML Engineer,44918,0 +18584,Female,35,Diploma,15,4,61,44,42,1.0,1,39,Semi-Urban,Data Analyst,140363,0 +18585,Female,38,Masters,16,85,47,38,73,8.0,4,31,Rural,ML Engineer,46829,0 +18586,Male,54,High School,6,83,1,99,78,6.0,3,36,Urban,Manager,29784,0 +18587,Female,28,High School,2,39,78,97,72,0.0,4,76,Urban,Data Analyst,81947,1 +18588,Female,32,Bachelors,6,90,97,70,24,1.0,3,97,Urban,ML Engineer,68193,1 +18589,Female,33,Bachelors,4,70,27,38,18,0.0,0,84,Urban,Software Engineer,141961,0 +18590,Male,44,PhD,19,92,16,53,7,6.0,1,94,Urban,Manager,99181,1 +18591,Male,21,Diploma,7,27,40,77,68,7.0,1,89,Urban,HR Executive,63048,0 +18592,Male,31,Diploma,11,95,46,85,32,5.0,0,18,Urban,Software Engineer,29620,1 +18593,Male,32,Diploma,17,18,60,69,23,5.0,2,55,Urban,Software Engineer,87056,0 +18594,Female,36,Bachelors,7,32,75,65,63,9.0,4,95,Urban,Manager,143003,1 +18595,Female,54,Diploma,17,63,81,17,22,2.0,0,85,Urban,Manager,99840,1 +18596,Female,36,Bachelors,18,20,4,90,37,9.0,0,87,Semi-Urban,Manager,28588,0 +18597,Male,41,Bachelors,9,59,73,80,29,1.0,5,43,Semi-Urban,Software Engineer,38080,1 +18598,Male,58,Bachelors,13,39,3,85,44,0.0,1,27,Urban,HR Executive,119824,0 +18599,Female,47,Bachelors,13,70,79,48,99,9.0,7,5,Urban,ML Engineer,81594,0 +18600,Male,35,Diploma,5,88,50,54,37,5.0,4,44,Semi-Urban,HR Executive,114008,1 +18601,Male,36,Masters,8,48,21,78,9,3.0,7,12,Urban,ML Engineer,138012,0 +18602,Male,43,Masters,2,67,44,78,18,5.0,3,5,Urban,Manager,127937,0 +18603,Male,55,Bachelors,4,11,90,97,52,4.0,1,54,Urban,Manager,78236,1 +18604,Female,45,Bachelors,9,5,74,41,80,5.0,5,61,Urban,Data Analyst,56642,0 +18605,Male,48,Bachelors,17,70,90,64,86,0.0,0,46,Urban,HR Executive,148384,1 +18606,Female,44,Masters,19,98,92,76,65,2.0,5,52,Urban,HR Executive,90763,1 +18607,Female,24,Bachelors,13,66,41,27,68,0.0,0,52,Urban,Data Analyst,44954,0 +18608,Male,26,Bachelors,4,52,44,88,33,8.0,3,43,Urban,Data Analyst,50559,0 +18609,Female,34,High School,7,21,68,7,55,4.0,5,52,Rural,ML Engineer,25566,0 +18610,Male,23,PhD,15,33,97,54,65,2.0,4,22,Urban,HR Executive,119767,0 +18611,Female,41,Bachelors,19,73,75,65,48,0.0,2,0,Urban,Manager,36921,0 +18612,Male,54,Diploma,9,54,73,15,11,0.0,3,19,Semi-Urban,Data Analyst,47259,0 +18613,Female,58,Masters,14,62,82,2,87,8.0,4,91,Urban,Manager,95654,0 +18614,Male,22,PhD,9,48,16,58,39,6.0,0,26,Urban,ML Engineer,31580,0 +18615,Female,27,Masters,19,58,29,37,9,1.0,3,34,Urban,HR Executive,78489,0 +18616,Female,55,Bachelors,11,94,87,62,92,3.0,1,21,Urban,Manager,67796,1 +18617,Male,43,Masters,4,53,52,83,54,8.0,1,46,Semi-Urban,ML Engineer,126473,0 +18618,Female,40,Diploma,2,77,24,63,6,1.0,3,91,Semi-Urban,ML Engineer,53042,1 +18619,Male,53,Diploma,19,16,34,62,24,6.0,1,96,Urban,Data Analyst,105380,0 +18620,Male,45,Diploma,9,71,18,59,48,2.0,1,76,Urban,Data Analyst,132641,0 +18621,Female,57,High School,13,89,25,56,24,7.0,1,21,Rural,Manager,66443,0 +18622,Female,24,Bachelors,3,63,98,63,38,8.0,7,60,Urban,ML Engineer,48922,1 +18623,Male,56,Masters,10,87,58,75,91,7.0,1,52,Semi-Urban,Manager,21258,1 +18624,Male,27,Bachelors,1,67,92,72,2,5.0,6,18,Rural,HR Executive,54947,1 +18625,Other,38,Diploma,6,87,65,2,34,8.0,3,98,Urban,Software Engineer,88464,1 +18626,Female,36,Diploma,12,16,32,67,2,7.0,2,68,Rural,Data Analyst,83046,0 +18627,Male,31,Bachelors,19,35,52,53,25,0.0,5,59,Urban,ML Engineer,46387,0 +18628,Male,33,Bachelors,2,74,90,72,78,3.0,1,2,Urban,Data Analyst,99198,1 +18629,Other,22,High School,13,13,39,99,17,7.0,6,8,Urban,HR Executive,27186,0 +18630,Female,44,Bachelors,5,52,33,43,93,8.0,1,52,Urban,ML Engineer,60094,0 +18631,Female,56,Diploma,5,59,79,42,71,8.0,7,84,Semi-Urban,HR Executive,111483,1 +18632,Male,26,Diploma,4,26,52,59,63,5.0,0,93,Urban,ML Engineer,67805,0 +18633,Female,48,Bachelors,18,35,61,78,17,6.0,3,54,Urban,Manager,72967,0 +18634,Female,45,Bachelors,15,14,76,96,18,5.0,2,67,Semi-Urban,Software Engineer,100772,1 +18635,Male,41,Bachelors,15,53,27,79,90,9.0,3,73,Semi-Urban,Manager,133565,0 +18636,Male,32,Bachelors,3,7,72,47,55,1.0,0,13,Urban,ML Engineer,146270,0 +18637,Female,34,Masters,5,96,54,43,42,9.0,5,34,Urban,ML Engineer,112718,0 +18638,Male,41,Bachelors,7,30,5,74,46,6.0,7,84,Urban,Manager,142177,0 +18639,Female,41,Diploma,15,72,96,10,44,0.0,6,45,Urban,ML Engineer,27866,0 +18640,Female,47,Bachelors,17,70,93,63,7,8.0,3,53,Urban,ML Engineer,21374,1 +18641,Female,58,Bachelors,14,12,42,9,24,1.0,7,54,Urban,HR Executive,78144,0 +18642,Female,45,Bachelors,7,47,39,31,36,9.0,7,85,Urban,ML Engineer,96981,0 +18643,Male,27,Diploma,18,80,7,45,65,1.0,6,44,Urban,Software Engineer,73784,0 +18644,Male,31,High School,5,94,94,92,32,1.0,4,75,Urban,ML Engineer,61546,1 +18645,Female,31,Diploma,12,83,98,24,52,3.0,1,50,Urban,Manager,65507,1 +18646,Male,46,Masters,8,83,66,13,51,0.0,4,30,Rural,HR Executive,65783,0 +18647,Male,45,Diploma,1,74,68,18,4,8.0,1,24,Urban,ML Engineer,146271,0 +18648,Male,28,Diploma,13,93,55,32,29,8.0,5,59,Urban,HR Executive,111031,1 +18649,Male,46,High School,12,97,76,54,9,3.0,5,62,Semi-Urban,Manager,76518,1 +18650,Female,28,Bachelors,5,42,8,77,87,2.0,4,88,Rural,Data Analyst,116136,0 +18651,Male,34,High School,1,73,77,49,97,3.0,5,85,Urban,ML Engineer,138417,1 +18652,Male,44,High School,8,15,57,35,58,1.0,4,6,Rural,Data Analyst,78840,0 +18653,Other,30,Diploma,1,76,12,73,55,7.0,4,79,Rural,Data Analyst,92068,0 +18654,Female,42,Masters,5,75,90,67,56,5.0,7,69,Urban,Data Analyst,82867,1 +18655,Female,35,Bachelors,5,82,12,79,66,6.0,6,47,Semi-Urban,Data Analyst,36959,0 +18656,Female,23,Diploma,4,46,20,34,68,9.0,7,4,Semi-Urban,HR Executive,78034,0 +18657,Female,55,Bachelors,14,89,93,67,93,0.0,3,83,Urban,Software Engineer,47506,1 +18658,Female,57,Bachelors,10,38,83,43,42,4.0,0,85,Urban,ML Engineer,135067,1 +18659,Male,49,Bachelors,0,41,29,25,72,9.0,7,37,Semi-Urban,HR Executive,25111,0 +18660,Other,25,Bachelors,18,85,84,11,43,9.0,1,2,Semi-Urban,Manager,41806,0 +18661,Male,47,Bachelors,14,77,63,85,31,5.0,5,22,Urban,HR Executive,129236,1 +18662,Female,22,High School,4,44,45,73,58,7.0,5,58,Rural,ML Engineer,51041,0 +18663,Male,42,Bachelors,17,30,53,53,96,4.0,0,62,Urban,HR Executive,24394,0 +18664,Male,41,High School,18,26,29,87,80,2.0,4,26,Urban,Data Analyst,65688,0 +18665,Male,30,Diploma,16,9,65,56,85,5.0,3,98,Rural,Data Analyst,53924,0 +18666,Male,36,Diploma,7,13,41,6,66,1.0,6,98,Urban,Software Engineer,34631,0 +18667,Female,26,Masters,0,75,79,58,92,2.0,1,85,Semi-Urban,Data Analyst,55260,1 +18668,Other,58,Masters,7,46,55,17,5,7.0,7,44,Semi-Urban,ML Engineer,60915,0 +18669,Other,59,Masters,16,44,89,13,69,0.0,4,1,Semi-Urban,HR Executive,41151,0 +18670,Other,28,Diploma,17,3,89,52,47,4.0,1,39,Semi-Urban,Manager,125633,0 +18671,Male,51,Bachelors,6,14,82,21,80,0.0,3,93,Urban,Software Engineer,36871,0 +18672,Other,21,High School,7,35,77,35,31,9.0,2,36,Urban,HR Executive,120193,0 +18673,Male,46,Diploma,8,63,83,5,13,3.0,7,96,Urban,Software Engineer,45835,1 +18674,Female,53,Masters,5,90,9,61,79,9.0,1,54,Urban,Manager,96627,0 +18675,Male,46,Bachelors,14,51,13,7,60,9.0,2,58,Urban,Software Engineer,67953,0 +18676,Male,28,Bachelors,19,99,52,40,11,9.0,2,15,Urban,HR Executive,30920,0 +18677,Other,32,Bachelors,8,80,66,11,95,9.0,3,18,Urban,ML Engineer,33771,0 +18678,Female,26,High School,4,9,19,79,44,3.0,5,69,Urban,Data Analyst,58339,0 +18679,Female,38,Diploma,10,34,21,15,92,4.0,0,13,Semi-Urban,Software Engineer,25941,0 +18680,Female,40,Bachelors,2,88,71,11,74,9.0,7,61,Urban,Data Analyst,61046,0 +18681,Male,55,Bachelors,12,12,13,10,71,5.0,0,57,Urban,Manager,111760,0 +18682,Female,47,Diploma,5,15,94,23,12,5.0,3,50,Rural,Manager,115470,0 +18683,Female,59,Diploma,11,52,34,90,28,0.0,3,8,Urban,ML Engineer,20797,0 +18684,Male,34,Bachelors,7,37,71,44,66,6.0,7,60,Urban,Data Analyst,35600,0 +18685,Male,52,Bachelors,3,35,39,39,25,3.0,5,27,Semi-Urban,Software Engineer,21249,0 +18686,Male,50,PhD,12,17,54,82,23,2.0,5,74,Urban,Manager,37108,0 +18687,Female,57,High School,19,14,54,18,43,1.0,2,66,Urban,Data Analyst,87656,0 +18688,Male,44,PhD,7,77,53,73,4,2.0,2,85,Semi-Urban,Software Engineer,29184,1 +18689,Male,37,High School,18,41,25,97,54,5.0,4,76,Semi-Urban,Data Analyst,37839,1 +18690,Male,45,Masters,9,51,18,44,92,1.0,6,92,Rural,HR Executive,42419,0 +18691,Male,23,High School,17,33,35,28,96,3.0,2,0,Urban,Data Analyst,25148,0 +18692,Female,58,Masters,0,84,95,27,70,5.0,6,9,Urban,Data Analyst,113843,0 +18693,Female,36,Masters,8,10,76,59,88,2.0,7,2,Urban,Data Analyst,99215,0 +18694,Male,25,Masters,2,53,56,49,49,2.0,3,14,Urban,Data Analyst,46517,0 +18695,Male,58,High School,2,96,56,95,70,8.0,6,70,Urban,HR Executive,23972,1 +18696,Male,25,Bachelors,5,29,13,85,70,1.0,5,27,Urban,Manager,93640,0 +18697,Female,21,High School,8,35,19,27,44,3.0,4,36,Semi-Urban,ML Engineer,145137,0 +18698,Male,45,Diploma,1,16,9,96,37,2.0,4,64,Semi-Urban,ML Engineer,29897,0 +18699,Male,53,Bachelors,4,90,58,66,16,3.0,5,85,Rural,HR Executive,124528,1 +18700,Female,23,Bachelors,5,44,11,24,83,8.0,4,82,Urban,Software Engineer,27083,0 +18701,Male,27,Masters,3,38,73,98,61,2.0,5,12,Urban,Software Engineer,129462,0 +18702,Female,25,Bachelors,17,27,23,15,81,5.0,6,30,Semi-Urban,Manager,28038,0 +18703,Male,57,Bachelors,13,4,30,70,46,1.0,6,76,Semi-Urban,Manager,99563,0 +18704,Female,48,Diploma,10,72,75,39,36,9.0,0,78,Semi-Urban,HR Executive,106910,1 +18705,Male,45,Masters,4,25,8,19,46,3.0,7,46,Semi-Urban,Software Engineer,146576,0 +18706,Male,35,PhD,17,78,69,38,46,5.0,5,70,Urban,Manager,133612,1 +18707,Male,51,Masters,19,34,27,59,93,8.0,3,7,Urban,Manager,142216,0 +18708,Female,55,PhD,4,13,4,37,30,4.0,4,80,Urban,Data Analyst,134527,0 +18709,Other,33,High School,18,74,92,83,26,4.0,3,75,Urban,Software Engineer,65164,1 +18710,Male,39,Bachelors,13,84,6,15,36,3.0,6,60,Urban,HR Executive,48863,0 +18711,Female,34,Bachelors,16,65,31,4,76,7.0,6,34,Urban,Data Analyst,54011,0 +18712,Female,40,Diploma,11,82,33,97,25,3.0,6,80,Urban,Manager,146000,1 +18713,Other,58,Masters,15,39,48,16,52,3.0,1,17,Rural,Manager,64767,0 +18714,Female,41,Diploma,13,30,77,17,15,7.0,0,10,Urban,Data Analyst,135197,0 +18715,Male,35,Diploma,11,52,43,74,89,4.0,4,4,Urban,HR Executive,45492,0 +18716,Female,49,Bachelors,16,5,5,85,39,5.0,7,43,Urban,ML Engineer,51534,0 +18717,Male,47,High School,15,50,56,61,73,5.0,7,40,Semi-Urban,ML Engineer,67866,0 +18718,Male,47,Bachelors,2,42,41,25,53,9.0,3,77,Semi-Urban,Software Engineer,47330,0 +18719,Male,27,Diploma,15,67,53,9,75,4.0,6,10,Urban,Software Engineer,127368,0 +18720,Female,57,Bachelors,18,73,75,5,10,0.0,4,0,Urban,Manager,58206,0 +18721,Female,52,Bachelors,14,33,61,63,65,8.0,1,41,Urban,Data Analyst,69058,0 +18722,Female,56,Bachelors,10,14,72,94,82,3.0,7,82,Urban,Software Engineer,79380,1 +18723,Other,55,Bachelors,10,83,77,6,46,6.0,1,34,Semi-Urban,ML Engineer,61423,0 +18724,Female,39,PhD,18,27,91,87,38,4.0,4,43,Urban,ML Engineer,120643,1 +18725,Male,48,Bachelors,16,50,31,57,39,3.0,1,52,Urban,HR Executive,87057,0 +18726,Male,27,Bachelors,18,21,91,16,95,8.0,6,8,Rural,Software Engineer,102433,0 +18727,Male,40,Masters,13,85,19,74,22,3.0,4,22,Urban,Manager,136385,0 +18728,Male,44,Masters,14,28,85,67,53,5.0,4,7,Urban,HR Executive,137431,0 +18729,Male,49,Diploma,0,75,26,9,15,6.0,1,70,Urban,Software Engineer,59809,0 +18730,Male,34,Masters,2,31,65,19,73,0.0,2,30,Urban,Data Analyst,81371,0 +18731,Female,47,High School,8,14,41,11,81,6.0,1,72,Urban,HR Executive,88024,0 +18732,Female,55,Masters,5,25,39,88,74,9.0,1,79,Urban,ML Engineer,74922,0 +18733,Female,58,Bachelors,14,86,83,34,74,1.0,6,41,Rural,Software Engineer,45732,1 +18734,Female,25,Diploma,18,70,6,94,60,1.0,6,9,Urban,Manager,27855,0 +18735,Male,37,Diploma,8,4,18,73,42,1.0,5,45,Urban,Manager,119023,0 +18736,Female,58,Diploma,5,96,78,35,6,3.0,5,38,Semi-Urban,HR Executive,143011,1 +18737,Male,32,Bachelors,9,89,53,43,22,6.0,6,84,Semi-Urban,ML Engineer,56569,1 +18738,Male,24,Diploma,1,41,88,45,58,4.0,7,2,Urban,Data Analyst,35691,0 +18739,Female,33,High School,1,14,23,77,53,4.0,3,71,Rural,Manager,28404,0 +18740,Male,27,Bachelors,6,15,60,7,96,2.0,1,61,Urban,ML Engineer,44414,0 +18741,Male,57,High School,4,31,35,38,28,6.0,2,48,Urban,Manager,76393,0 +18742,Male,57,Diploma,5,13,38,0,3,0.0,1,69,Urban,HR Executive,44564,0 +18743,Female,53,Bachelors,5,50,28,90,96,8.0,2,11,Urban,Software Engineer,84762,0 +18744,Other,35,Diploma,11,22,55,15,7,0.0,6,6,Urban,Manager,125092,0 +18745,Male,39,Bachelors,18,70,25,23,70,4.0,5,25,Urban,ML Engineer,91640,0 +18746,Female,45,High School,5,33,38,46,58,5.0,6,9,Rural,Software Engineer,129067,0 +18747,Male,38,Bachelors,5,73,16,3,11,0.0,1,4,Urban,Software Engineer,127788,0 +18748,Male,38,Masters,17,6,84,5,85,6.0,5,72,Urban,Manager,31093,0 +18749,Male,51,Masters,3,49,52,98,0,0.0,5,80,Rural,Software Engineer,51826,1 +18750,Female,53,Diploma,17,66,73,76,11,6.0,2,38,Urban,HR Executive,118064,1 +18751,Male,23,High School,13,82,71,88,71,0.0,5,79,Urban,Software Engineer,103617,1 +18752,Male,23,Diploma,0,81,90,14,47,2.0,0,33,Urban,ML Engineer,85113,0 +18753,Male,22,Bachelors,3,74,24,88,71,5.0,3,73,Urban,Software Engineer,25178,1 +18754,Male,24,PhD,14,24,5,25,20,2.0,4,14,Urban,HR Executive,143424,0 +18755,Female,32,Diploma,4,84,13,13,68,5.0,6,15,Semi-Urban,ML Engineer,82540,0 +18756,Male,27,Diploma,1,11,25,28,10,0.0,6,77,Urban,Data Analyst,121152,0 +18757,Male,47,Bachelors,12,87,91,48,76,7.0,7,41,Urban,Manager,143194,1 +18758,Male,55,Bachelors,13,16,56,3,25,5.0,3,37,Urban,Data Analyst,102418,0 +18759,Male,30,Masters,16,86,31,50,44,2.0,0,0,Urban,ML Engineer,100614,0 +18760,Female,21,Diploma,7,66,54,0,52,3.0,2,48,Urban,ML Engineer,89015,0 +18761,Male,51,Diploma,12,57,96,46,84,8.0,7,70,Rural,ML Engineer,103644,1 +18762,Male,29,Bachelors,19,1,6,74,52,4.0,2,61,Urban,ML Engineer,42420,0 +18763,Male,45,Masters,18,79,95,0,88,9.0,4,45,Semi-Urban,Software Engineer,55471,0 +18764,Male,49,Bachelors,19,5,19,88,52,3.0,7,43,Semi-Urban,HR Executive,104807,0 +18765,Female,54,Bachelors,16,65,93,42,77,0.0,0,35,Urban,ML Engineer,87013,0 +18766,Female,24,Masters,1,49,35,80,79,7.0,0,66,Urban,HR Executive,35659,0 +18767,Female,59,Diploma,11,25,1,87,31,5.0,6,71,Semi-Urban,Manager,93212,0 +18768,Male,47,Bachelors,13,7,49,35,48,7.0,2,9,Urban,Software Engineer,116234,0 +18769,Female,54,High School,13,80,61,58,98,2.0,0,70,Semi-Urban,Data Analyst,148502,1 +18770,Female,41,Masters,13,38,83,89,77,8.0,6,65,Semi-Urban,Manager,30400,1 +18771,Male,21,Diploma,14,90,49,40,54,7.0,1,15,Semi-Urban,Manager,54758,0 +18772,Female,41,PhD,3,6,65,86,11,9.0,7,57,Semi-Urban,HR Executive,145015,0 +18773,Female,55,High School,5,75,74,56,27,5.0,0,48,Rural,Manager,23701,1 +18774,Male,53,Bachelors,0,35,0,57,46,5.0,7,19,Urban,Data Analyst,142996,0 +18775,Male,28,Bachelors,10,24,17,49,4,2.0,5,64,Urban,Manager,128289,0 +18776,Female,54,Bachelors,8,57,40,16,42,8.0,2,12,Semi-Urban,Software Engineer,142122,0 +18777,Male,52,High School,3,68,99,15,51,7.0,2,6,Rural,Manager,79344,0 +18778,Female,44,Masters,14,14,47,50,76,5.0,7,13,Semi-Urban,Data Analyst,130429,0 +18779,Female,47,Bachelors,7,39,71,23,53,9.0,6,43,Urban,ML Engineer,85620,0 +18780,Female,23,Bachelors,17,30,60,28,5,5.0,1,40,Semi-Urban,Data Analyst,85319,0 +18781,Male,52,Bachelors,12,20,85,37,88,3.0,6,42,Urban,Manager,66800,0 +18782,Male,25,Bachelors,11,26,21,64,72,2.0,1,17,Urban,Software Engineer,44582,0 +18783,Male,57,High School,5,2,53,42,81,9.0,3,14,Urban,ML Engineer,54512,0 +18784,Female,25,PhD,11,33,5,0,43,5.0,7,74,Rural,ML Engineer,90529,0 +18785,Female,46,Diploma,9,87,70,3,69,2.0,3,80,Urban,Software Engineer,36316,0 +18786,Female,44,High School,11,33,45,56,71,8.0,2,34,Urban,Manager,44246,0 +18787,Male,41,Diploma,18,87,91,54,92,2.0,0,24,Urban,ML Engineer,50983,1 +18788,Female,40,PhD,10,11,67,21,43,7.0,3,31,Urban,ML Engineer,84223,0 +18789,Other,29,Masters,16,18,58,56,30,8.0,3,53,Semi-Urban,Software Engineer,117748,0 +18790,Male,35,High School,19,84,50,96,78,0.0,0,74,Urban,HR Executive,87809,1 +18791,Male,23,Bachelors,12,68,88,12,17,4.0,6,13,Semi-Urban,ML Engineer,134219,0 +18792,Female,47,Masters,11,28,30,4,52,9.0,7,14,Urban,ML Engineer,27753,0 +18793,Female,24,PhD,10,9,57,39,66,1.0,0,67,Urban,Data Analyst,41045,0 +18794,Other,38,Masters,16,79,77,37,15,9.0,6,51,Semi-Urban,ML Engineer,119040,1 +18795,Male,51,Bachelors,7,9,81,86,43,9.0,6,78,Urban,Manager,76903,1 +18796,Male,46,Masters,9,16,83,82,1,4.0,0,92,Urban,Software Engineer,148396,1 +18797,Female,41,Bachelors,15,73,57,51,78,1.0,2,77,Semi-Urban,ML Engineer,102877,1 +18798,Female,41,Masters,10,37,53,24,7,9.0,5,18,Semi-Urban,Manager,33463,0 +18799,Female,55,Diploma,7,8,25,20,65,7.0,2,4,Urban,Software Engineer,72601,0 +18800,Other,46,Bachelors,10,38,5,81,69,8.0,7,2,Urban,Data Analyst,54129,0 +18801,Male,52,Masters,5,88,54,47,3,5.0,7,56,Urban,Software Engineer,54607,1 +18802,Female,35,Bachelors,4,41,97,67,59,7.0,4,46,Semi-Urban,ML Engineer,130398,1 +18803,Male,48,Masters,17,37,13,25,36,3.0,4,89,Rural,ML Engineer,25993,0 +18804,Male,29,Masters,16,25,89,49,96,0.0,0,61,Urban,HR Executive,139927,0 +18805,Male,25,Bachelors,2,26,23,44,14,0.0,7,87,Urban,Data Analyst,71598,0 +18806,Female,27,Diploma,1,49,35,12,96,8.0,5,90,Urban,ML Engineer,132843,0 +18807,Other,42,High School,5,47,15,73,70,9.0,2,27,Urban,Manager,37081,0 +18808,Male,41,Masters,7,14,73,42,45,9.0,3,14,Semi-Urban,ML Engineer,51111,0 +18809,Male,39,Bachelors,15,94,84,58,37,3.0,3,19,Urban,HR Executive,71863,1 +18810,Female,37,Masters,8,29,55,56,30,4.0,2,28,Semi-Urban,Data Analyst,107673,0 +18811,Female,31,Diploma,10,9,75,25,3,1.0,4,84,Urban,HR Executive,65928,0 +18812,Other,51,Masters,8,35,73,28,84,2.0,0,16,Urban,ML Engineer,41416,0 +18813,Male,28,High School,1,83,99,47,3,9.0,1,78,Urban,Software Engineer,23350,1 +18814,Male,54,Bachelors,4,6,48,85,83,8.0,0,72,Urban,HR Executive,115827,0 +18815,Male,23,Bachelors,2,76,23,44,33,8.0,7,89,Urban,HR Executive,70124,0 +18816,Male,38,High School,19,66,50,21,0,7.0,6,93,Rural,ML Engineer,101389,0 +18817,Male,56,Bachelors,13,95,12,54,49,2.0,1,67,Semi-Urban,Data Analyst,92078,0 +18818,Male,59,PhD,3,33,23,59,46,3.0,5,21,Urban,HR Executive,67637,0 +18819,Male,41,High School,5,41,61,11,37,8.0,2,97,Semi-Urban,Data Analyst,27882,0 +18820,Male,24,High School,17,6,85,34,18,3.0,2,33,Rural,Software Engineer,84108,0 +18821,Other,48,Diploma,19,19,5,74,54,8.0,7,10,Semi-Urban,ML Engineer,41360,0 +18822,Male,56,Bachelors,7,85,68,14,16,5.0,3,21,Urban,Manager,46911,0 +18823,Male,47,Bachelors,4,91,19,90,84,1.0,1,15,Urban,Manager,44351,0 +18824,Female,29,PhD,1,19,26,67,29,5.0,7,46,Urban,Data Analyst,48219,0 +18825,Female,29,Masters,5,63,27,31,64,8.0,2,85,Rural,Manager,98514,0 +18826,Female,48,Diploma,0,80,91,75,37,1.0,5,25,Urban,Data Analyst,44522,1 +18827,Female,39,Masters,17,15,64,27,7,3.0,0,78,Rural,Manager,87840,0 +18828,Female,58,Masters,19,53,33,82,12,9.0,6,45,Urban,ML Engineer,68388,0 +18829,Female,26,Bachelors,14,45,28,70,75,9.0,2,54,Rural,HR Executive,43629,0 +18830,Female,42,Masters,11,40,97,18,32,5.0,3,14,Urban,Software Engineer,42205,0 +18831,Female,55,Diploma,8,67,83,62,13,7.0,6,63,Semi-Urban,HR Executive,35351,1 +18832,Male,51,Bachelors,17,58,81,79,96,1.0,7,69,Rural,Data Analyst,67579,1 +18833,Male,46,Masters,14,43,56,26,84,1.0,5,35,Semi-Urban,HR Executive,144900,0 +18834,Female,44,Bachelors,1,27,12,81,28,9.0,2,57,Rural,Software Engineer,61080,0 +18835,Male,25,Bachelors,16,95,87,37,45,9.0,5,38,Semi-Urban,HR Executive,88863,1 +18836,Female,41,Bachelors,3,93,70,40,14,0.0,7,53,Semi-Urban,Data Analyst,21016,1 +18837,Male,42,Masters,14,50,66,95,45,6.0,0,85,Semi-Urban,Software Engineer,57316,1 +18838,Male,44,High School,3,78,3,40,43,9.0,6,23,Rural,ML Engineer,28382,0 +18839,Female,55,Diploma,18,43,39,83,86,8.0,5,98,Rural,Data Analyst,121467,1 +18840,Male,25,Bachelors,14,55,63,19,71,7.0,1,5,Semi-Urban,HR Executive,107850,0 +18841,Female,35,Diploma,17,21,9,24,62,5.0,6,98,Urban,HR Executive,70807,0 +18842,Other,59,Bachelors,9,62,32,8,88,8.0,3,25,Rural,Data Analyst,149230,0 +18843,Female,58,Bachelors,14,6,38,50,54,7.0,1,91,Rural,HR Executive,137244,0 +18844,Male,26,Masters,0,85,97,32,40,1.0,6,58,Rural,HR Executive,113387,1 +18845,Female,39,Bachelors,12,66,26,81,27,0.0,3,75,Urban,Manager,123921,1 +18846,Female,37,Diploma,4,4,97,52,52,8.0,3,28,Rural,ML Engineer,87675,0 +18847,Female,22,Bachelors,5,62,54,97,87,1.0,3,77,Rural,Software Engineer,52661,1 +18848,Female,49,Bachelors,12,40,8,46,6,7.0,0,65,Semi-Urban,HR Executive,102334,0 +18849,Other,45,High School,14,5,90,83,69,7.0,4,93,Urban,Manager,98231,1 +18850,Female,55,High School,13,72,74,66,87,3.0,0,57,Urban,Manager,34778,1 +18851,Other,57,Bachelors,11,72,37,60,88,7.0,3,70,Urban,Manager,100103,0 +18852,Male,40,Diploma,4,62,73,40,52,2.0,4,21,Urban,HR Executive,48819,0 +18853,Male,35,Bachelors,17,23,77,28,4,1.0,4,80,Rural,Data Analyst,55678,0 +18854,Male,30,Masters,1,11,85,94,43,6.0,5,50,Urban,Manager,126938,1 +18855,Male,52,Masters,10,41,29,32,69,9.0,3,12,Rural,HR Executive,122731,0 +18856,Female,28,Bachelors,16,75,6,33,3,8.0,4,82,Rural,Manager,136972,0 +18857,Male,53,Diploma,17,51,91,71,89,3.0,3,53,Urban,ML Engineer,130221,1 +18858,Other,21,Bachelors,14,22,82,21,84,5.0,6,85,Urban,Software Engineer,89532,0 +18859,Male,46,Masters,3,18,18,11,7,3.0,0,61,Semi-Urban,Data Analyst,67683,0 +18860,Male,25,Diploma,0,98,74,39,2,1.0,4,64,Rural,ML Engineer,75813,1 +18861,Male,22,Bachelors,9,42,11,51,69,6.0,1,97,Urban,Data Analyst,41860,0 +18862,Male,38,High School,5,7,66,79,87,3.0,6,90,Rural,HR Executive,127505,1 +18863,Male,53,High School,9,27,30,16,61,9.0,3,86,Urban,HR Executive,121894,0 +18864,Male,30,Bachelors,0,68,60,29,14,5.0,6,39,Semi-Urban,Manager,23221,0 +18865,Female,26,Diploma,2,88,74,79,8,0.0,5,21,Rural,Data Analyst,76319,1 +18866,Male,59,Bachelors,6,42,10,80,32,5.0,2,35,Urban,Manager,148961,0 +18867,Male,59,High School,10,2,71,57,89,0.0,5,64,Urban,HR Executive,23519,0 +18868,Female,33,Bachelors,18,18,37,64,25,7.0,5,38,Urban,Manager,54736,0 +18869,Male,32,Bachelors,14,96,64,72,41,3.0,5,68,Urban,Manager,75992,1 +18870,Male,45,Bachelors,0,22,5,44,70,5.0,4,24,Rural,HR Executive,54367,0 +18871,Male,22,Diploma,10,98,82,18,38,3.0,3,12,Urban,ML Engineer,81497,0 +18872,Male,23,Masters,9,53,28,15,72,1.0,7,78,Urban,ML Engineer,99691,0 +18873,Female,25,Masters,3,80,42,74,71,5.0,3,51,Urban,Software Engineer,129048,1 +18874,Male,39,Bachelors,16,71,75,31,41,6.0,2,52,Semi-Urban,Manager,145112,0 +18875,Female,22,Masters,1,26,93,66,70,5.0,1,9,Urban,Software Engineer,35774,0 +18876,Female,41,Bachelors,8,45,41,19,9,9.0,2,68,Urban,ML Engineer,44700,0 +18877,Male,33,Masters,2,62,36,90,8,3.0,6,50,Urban,Manager,45218,1 +18878,Other,42,Masters,11,41,87,72,37,1.0,7,23,Urban,Software Engineer,26165,0 +18879,Male,37,High School,5,28,69,79,23,2.0,5,1,Urban,Software Engineer,141489,0 +18880,Male,46,Masters,5,39,85,14,32,3.0,5,97,Urban,Software Engineer,38302,1 +18881,Male,56,Diploma,1,80,23,63,15,4.0,0,77,Semi-Urban,Manager,66793,1 +18882,Male,24,Bachelors,5,60,61,32,96,8.0,5,69,Rural,ML Engineer,111233,0 +18883,Female,52,High School,16,0,33,11,64,0.0,3,14,Semi-Urban,Manager,100165,0 +18884,Male,55,Bachelors,15,23,43,84,52,1.0,2,77,Rural,Data Analyst,112418,0 +18885,Female,55,Diploma,18,60,36,73,32,8.0,2,7,Urban,HR Executive,37505,0 +18886,Female,33,Bachelors,14,59,41,72,66,8.0,1,17,Urban,HR Executive,45055,0 +18887,Male,44,Masters,6,62,45,25,79,5.0,2,38,Semi-Urban,Software Engineer,50291,0 +18888,Female,37,Bachelors,0,43,33,40,23,9.0,6,70,Rural,Software Engineer,62382,0 +18889,Female,33,Bachelors,5,11,22,76,7,3.0,4,68,Rural,Data Analyst,109315,0 +18890,Male,23,Bachelors,13,63,31,12,34,1.0,0,40,Urban,Data Analyst,20046,0 +18891,Male,57,Bachelors,10,6,54,25,89,2.0,7,93,Urban,Manager,89830,0 +18892,Male,32,Bachelors,6,51,1,85,7,2.0,1,20,Urban,Software Engineer,76355,0 +18893,Male,37,Bachelors,19,77,4,39,94,1.0,2,92,Rural,Software Engineer,68975,0 +18894,Male,37,Bachelors,9,88,69,61,50,6.0,3,8,Rural,HR Executive,103517,0 +18895,Male,28,Diploma,10,23,29,13,42,1.0,0,18,Semi-Urban,ML Engineer,41598,0 +18896,Female,34,Bachelors,0,79,45,87,45,0.0,3,98,Urban,Manager,93636,1 +18897,Female,34,Bachelors,10,48,39,22,50,8.0,0,9,Urban,HR Executive,76754,0 +18898,Male,38,Bachelors,13,4,64,81,91,3.0,2,68,Rural,ML Engineer,143851,0 +18899,Male,52,Bachelors,1,31,90,38,67,1.0,5,60,Semi-Urban,Software Engineer,129446,0 +18900,Male,42,Bachelors,18,18,3,31,24,5.0,2,31,Urban,Manager,28152,0 +18901,Male,35,Bachelors,17,70,6,66,33,8.0,0,65,Urban,Data Analyst,30871,0 +18902,Male,36,High School,5,29,73,1,34,8.0,0,14,Urban,Manager,28995,0 +18903,Female,49,Masters,1,61,45,2,21,9.0,1,87,Urban,HR Executive,89212,0 +18904,Male,23,High School,9,94,11,69,23,9.0,1,98,Urban,ML Engineer,40869,1 +18905,Male,40,Diploma,16,82,29,58,82,4.0,3,78,Urban,HR Executive,61331,1 +18906,Male,58,Diploma,1,33,21,67,98,2.0,4,4,Rural,HR Executive,79896,0 +18907,Female,32,Bachelors,19,31,0,98,36,8.0,0,98,Urban,Software Engineer,81953,0 +18908,Female,55,Bachelors,12,27,90,47,56,2.0,7,92,Urban,Manager,77325,1 +18909,Male,38,Bachelors,11,82,88,83,68,0.0,7,81,Urban,ML Engineer,135048,1 +18910,Male,47,High School,10,54,87,25,69,5.0,7,27,Urban,HR Executive,77776,0 +18911,Male,40,Diploma,5,1,96,66,5,7.0,3,58,Urban,ML Engineer,98078,0 +18912,Male,26,High School,4,29,5,55,29,5.0,0,46,Urban,Software Engineer,87891,0 +18913,Other,43,High School,13,56,5,5,76,2.0,6,29,Rural,ML Engineer,110438,0 +18914,Female,51,High School,13,18,10,77,70,7.0,1,73,Urban,Data Analyst,26980,0 +18915,Female,27,Diploma,10,21,32,5,86,7.0,7,70,Urban,ML Engineer,145220,0 +18916,Male,24,Bachelors,5,79,13,77,41,3.0,7,43,Urban,ML Engineer,136492,0 +18917,Male,39,Masters,15,65,67,43,33,9.0,0,67,Urban,HR Executive,38515,1 +18918,Female,48,Bachelors,4,95,23,8,40,9.0,2,98,Rural,Software Engineer,136763,0 +18919,Male,43,Diploma,0,11,50,93,86,4.0,6,30,Rural,Data Analyst,59816,0 +18920,Other,43,Diploma,15,77,79,15,47,2.0,4,28,Semi-Urban,Manager,92345,0 +18921,Male,24,Diploma,17,24,50,54,98,9.0,7,63,Urban,Manager,102366,0 +18922,Male,52,Bachelors,2,88,72,38,36,4.0,2,56,Semi-Urban,ML Engineer,84823,1 +18923,Female,30,Bachelors,3,6,69,55,14,3.0,2,80,Urban,ML Engineer,94972,0 +18924,Male,59,Bachelors,19,45,14,87,80,5.0,3,33,Semi-Urban,Data Analyst,51103,0 +18925,Male,48,Bachelors,16,84,71,29,23,6.0,1,97,Urban,HR Executive,147103,1 +18926,Male,53,High School,9,50,55,39,75,9.0,3,33,Rural,ML Engineer,110888,0 +18927,Female,28,Bachelors,15,23,97,56,16,0.0,1,61,Semi-Urban,Data Analyst,73659,0 +18928,Male,37,High School,11,80,44,54,62,4.0,4,87,Urban,Manager,88136,1 +18929,Male,55,High School,13,64,81,23,47,0.0,2,19,Rural,Software Engineer,97498,0 +18930,Female,42,High School,10,66,83,89,26,1.0,6,9,Semi-Urban,Software Engineer,82747,1 +18931,Male,55,Masters,11,35,4,89,77,5.0,1,20,Urban,ML Engineer,26779,0 +18932,Female,57,Masters,0,69,54,48,6,3.0,4,81,Urban,ML Engineer,28207,1 +18933,Male,38,High School,4,85,56,46,16,8.0,3,19,Urban,Data Analyst,22542,0 +18934,Female,44,Masters,8,91,14,17,64,7.0,5,74,Urban,ML Engineer,73678,0 +18935,Male,42,PhD,6,95,3,24,28,4.0,6,12,Semi-Urban,ML Engineer,39001,0 +18936,Female,57,Masters,10,49,83,23,60,5.0,0,96,Urban,Data Analyst,57650,1 +18937,Female,24,Diploma,12,7,51,52,20,8.0,5,80,Urban,Manager,30281,0 +18938,Female,29,Bachelors,18,44,19,49,31,7.0,6,12,Urban,Manager,75700,0 +18939,Male,21,Bachelors,10,29,93,81,64,4.0,2,80,Semi-Urban,ML Engineer,139170,1 +18940,Male,32,PhD,2,63,70,33,28,0.0,1,16,Urban,ML Engineer,59741,0 +18941,Female,24,Bachelors,9,93,29,46,23,8.0,6,58,Semi-Urban,Software Engineer,29994,0 +18942,Male,24,Diploma,11,78,20,56,46,9.0,0,98,Urban,Data Analyst,22198,1 +18943,Male,29,High School,13,60,58,85,67,8.0,6,80,Urban,Manager,141503,1 +18944,Female,38,Masters,13,60,24,24,77,8.0,1,76,Urban,Software Engineer,22803,0 +18945,Male,34,Masters,11,2,11,72,74,3.0,6,59,Rural,Manager,70470,0 +18946,Other,30,Bachelors,0,19,21,91,18,8.0,1,71,Semi-Urban,HR Executive,127073,0 +18947,Male,38,Masters,14,38,58,22,8,1.0,6,90,Rural,Software Engineer,72899,0 +18948,Female,46,High School,11,33,37,55,93,0.0,6,36,Rural,Software Engineer,77784,0 +18949,Male,47,Bachelors,16,9,14,89,72,1.0,5,20,Urban,Software Engineer,126522,0 +18950,Male,39,Masters,2,49,65,51,64,8.0,4,91,Urban,ML Engineer,36319,1 +18951,Other,43,High School,4,49,52,67,25,6.0,4,13,Semi-Urban,HR Executive,22862,0 +18952,Male,34,Bachelors,2,42,80,2,98,9.0,7,51,Rural,Manager,77151,0 +18953,Female,27,Bachelors,16,84,49,15,25,3.0,4,32,Rural,Software Engineer,37229,0 +18954,Female,21,PhD,4,33,44,72,5,2.0,0,29,Urban,Data Analyst,80359,0 +18955,Male,51,Bachelors,16,66,27,28,43,1.0,4,96,Semi-Urban,Manager,48265,0 +18956,Female,40,High School,7,82,23,25,42,7.0,1,15,Semi-Urban,Manager,118202,0 +18957,Male,43,Bachelors,9,17,35,74,94,9.0,4,34,Semi-Urban,Manager,107766,0 +18958,Female,47,Bachelors,19,97,35,82,73,0.0,4,58,Semi-Urban,Software Engineer,115380,1 +18959,Male,51,Bachelors,12,90,37,92,63,7.0,0,84,Urban,Software Engineer,33202,1 +18960,Female,46,High School,17,47,33,18,29,1.0,2,11,Urban,Manager,45069,0 +18961,Female,24,High School,3,37,18,30,14,1.0,0,41,Urban,Data Analyst,105770,0 +18962,Male,50,Bachelors,4,97,91,0,37,7.0,4,3,Semi-Urban,Manager,124334,0 +18963,Female,39,Diploma,4,20,44,15,32,9.0,3,53,Semi-Urban,Software Engineer,22359,0 +18964,Male,51,Bachelors,4,4,70,17,96,5.0,5,18,Rural,Manager,123277,0 +18965,Male,34,Masters,2,16,70,90,93,6.0,7,72,Urban,Data Analyst,23314,1 +18966,Male,59,High School,5,81,93,31,14,4.0,2,98,Urban,HR Executive,128852,1 +18967,Male,55,Masters,9,70,74,0,25,7.0,3,0,Semi-Urban,Software Engineer,145025,0 +18968,Male,38,Bachelors,13,67,81,77,57,6.0,7,34,Urban,Software Engineer,39634,1 +18969,Male,25,Bachelors,7,45,70,96,81,7.0,6,30,Semi-Urban,Software Engineer,101971,1 +18970,Male,38,Bachelors,11,71,22,89,28,8.0,1,7,Urban,Software Engineer,78635,0 +18971,Male,42,Bachelors,7,23,31,27,43,6.0,7,63,Urban,Manager,41340,0 +18972,Male,55,Bachelors,10,46,8,82,35,4.0,0,1,Semi-Urban,Data Analyst,69960,0 +18973,Female,36,Masters,18,85,14,40,90,8.0,1,53,Semi-Urban,Software Engineer,147581,0 +18974,Female,33,Diploma,14,3,14,30,98,4.0,3,13,Urban,ML Engineer,149770,0 +18975,Male,41,High School,12,73,92,91,95,9.0,3,74,Semi-Urban,Data Analyst,117712,1 +18976,Female,53,Diploma,17,87,32,43,8,1.0,0,98,Semi-Urban,Data Analyst,92950,1 +18977,Female,38,Diploma,6,49,20,72,24,0.0,4,69,Semi-Urban,HR Executive,149181,0 +18978,Female,49,Bachelors,8,92,67,79,20,3.0,4,1,Urban,Software Engineer,85157,0 +18979,Male,43,Diploma,15,45,31,1,86,0.0,3,0,Urban,HR Executive,40121,0 +18980,Male,59,Diploma,12,3,24,60,93,5.0,2,83,Semi-Urban,Software Engineer,121715,0 +18981,Female,58,Diploma,4,44,96,12,23,1.0,7,23,Urban,Data Analyst,32953,0 +18982,Female,58,Masters,7,14,71,1,81,8.0,5,47,Urban,HR Executive,53558,0 +18983,Male,58,Bachelors,1,10,50,56,89,3.0,2,13,Urban,Data Analyst,93277,0 +18984,Male,52,Bachelors,4,7,19,92,93,5.0,5,16,Urban,Manager,115585,0 +18985,Female,40,Masters,1,42,16,53,6,5.0,0,9,Urban,Manager,59348,0 +18986,Female,27,PhD,10,22,87,95,94,1.0,1,50,Rural,Manager,90421,1 +18987,Female,54,Diploma,15,52,88,65,40,8.0,3,54,Rural,ML Engineer,132749,1 +18988,Male,39,Diploma,7,43,24,85,69,4.0,7,75,Urban,Software Engineer,114333,0 +18989,Male,23,Diploma,12,27,58,94,19,5.0,4,36,Urban,Software Engineer,82412,0 +18990,Male,26,High School,1,86,24,45,17,8.0,3,47,Semi-Urban,Software Engineer,90197,0 +18991,Male,55,Bachelors,5,90,79,36,91,1.0,4,56,Rural,HR Executive,56406,1 +18992,Male,37,Bachelors,9,8,77,17,30,0.0,5,45,Semi-Urban,ML Engineer,113841,0 +18993,Female,56,Bachelors,6,87,53,70,98,7.0,7,4,Urban,ML Engineer,93859,0 +18994,Male,55,Diploma,6,87,81,15,63,5.0,2,61,Semi-Urban,Manager,67206,1 +18995,Female,52,Diploma,17,16,37,63,33,2.0,7,0,Urban,Data Analyst,149091,0 +18996,Male,59,Bachelors,5,43,45,0,35,3.0,3,92,Urban,Software Engineer,88591,0 +18997,Male,27,Bachelors,14,3,75,78,1,9.0,1,20,Urban,Manager,25818,0 +18998,Male,57,PhD,17,6,10,26,18,1.0,1,7,Semi-Urban,HR Executive,97212,0 +18999,Male,38,Bachelors,8,80,9,32,18,7.0,6,36,Urban,ML Engineer,121175,0 +19000,Female,37,Bachelors,0,78,65,71,5,7.0,2,78,Semi-Urban,Software Engineer,78141,1 +19001,Male,53,High School,4,92,21,54,78,3.0,6,45,Urban,Software Engineer,36721,0 +19002,Male,25,Bachelors,7,39,0,16,45,1.0,7,36,Urban,ML Engineer,67761,0 +19003,Male,54,Bachelors,2,40,31,38,96,3.0,1,72,Semi-Urban,Software Engineer,116793,0 +19004,Male,42,Bachelors,8,20,92,69,43,9.0,4,56,Semi-Urban,HR Executive,143683,1 +19005,Female,31,Bachelors,1,66,66,85,88,3.0,7,6,Urban,HR Executive,64982,0 +19006,Male,37,Diploma,5,16,31,9,23,3.0,5,59,Semi-Urban,HR Executive,71586,0 +19007,Female,59,Bachelors,18,97,70,56,38,1.0,2,29,Urban,Data Analyst,27734,1 +19008,Female,43,High School,3,85,72,2,73,5.0,6,32,Semi-Urban,HR Executive,68585,0 +19009,Male,22,Bachelors,18,44,74,8,22,0.0,3,42,Urban,HR Executive,114064,0 +19010,Male,52,Diploma,15,26,49,78,64,8.0,5,31,Semi-Urban,Manager,73125,0 +19011,Female,27,Bachelors,5,82,66,98,45,7.0,1,32,Urban,HR Executive,25814,1 +19012,Female,35,Bachelors,13,30,26,79,23,9.0,7,65,Urban,ML Engineer,40227,0 +19013,Male,36,Diploma,7,80,48,87,71,0.0,0,31,Semi-Urban,ML Engineer,140291,1 +19014,Male,34,Bachelors,3,17,40,62,53,8.0,7,81,Urban,ML Engineer,143424,0 +19015,Male,58,High School,13,73,1,88,88,2.0,2,10,Semi-Urban,Software Engineer,72205,0 +19016,Male,42,High School,19,21,99,52,78,6.0,6,46,Semi-Urban,Data Analyst,80364,0 +19017,Male,43,High School,6,49,55,98,5,3.0,7,40,Semi-Urban,ML Engineer,59828,1 +19018,Male,42,PhD,17,7,28,53,68,3.0,3,51,Urban,ML Engineer,89895,0 +19019,Male,39,Bachelors,14,2,80,37,90,5.0,2,87,Urban,ML Engineer,101853,0 +19020,Male,21,Bachelors,16,9,65,61,0,5.0,4,39,Semi-Urban,Manager,26272,0 +19021,Male,55,High School,14,79,88,98,35,4.0,5,80,Rural,ML Engineer,142897,1 +19022,Female,42,Bachelors,9,80,82,91,32,1.0,7,24,Semi-Urban,Software Engineer,85745,1 +19023,Male,52,Masters,15,3,45,97,47,1.0,6,65,Urban,HR Executive,101619,0 +19024,Female,38,Bachelors,2,93,74,81,19,2.0,2,89,Rural,HR Executive,27682,1 +19025,Male,55,Bachelors,9,80,79,81,6,7.0,6,49,Rural,Data Analyst,51934,1 +19026,Female,55,Masters,4,97,54,15,4,8.0,5,97,Urban,ML Engineer,147715,1 +19027,Male,35,Bachelors,11,23,40,58,30,3.0,7,19,Urban,HR Executive,47904,0 +19028,Female,59,Diploma,3,6,82,40,63,2.0,3,29,Urban,Data Analyst,93245,0 +19029,Male,53,Diploma,13,19,89,9,45,0.0,7,29,Urban,ML Engineer,48498,0 +19030,Male,47,Bachelors,7,69,37,76,96,3.0,4,76,Urban,Data Analyst,107923,1 +19031,Female,25,PhD,15,45,0,58,10,3.0,0,72,Urban,Software Engineer,107858,0 +19032,Male,26,Bachelors,0,37,53,23,47,2.0,1,32,Urban,Software Engineer,90449,0 +19033,Female,28,Diploma,10,13,73,77,55,2.0,0,39,Urban,ML Engineer,42649,0 +19034,Male,47,Diploma,9,44,66,24,64,7.0,2,86,Urban,HR Executive,120980,0 +19035,Male,57,Masters,14,41,71,67,96,1.0,3,6,Urban,Software Engineer,114813,0 +19036,Male,58,Bachelors,19,92,9,31,55,1.0,0,18,Urban,HR Executive,26940,0 +19037,Female,55,Bachelors,18,40,32,80,2,5.0,5,82,Urban,HR Executive,79781,0 +19038,Male,28,Bachelors,10,73,85,48,69,2.0,7,73,Rural,HR Executive,108144,1 +19039,Female,37,High School,10,41,49,59,14,8.0,7,21,Urban,HR Executive,77220,0 +19040,Male,50,Bachelors,13,88,19,60,55,8.0,3,25,Urban,Software Engineer,119798,0 +19041,Female,42,Bachelors,14,12,75,14,0,6.0,6,61,Urban,Software Engineer,67319,0 +19042,Male,41,High School,7,60,69,80,72,0.0,3,11,Urban,HR Executive,113287,0 +19043,Male,46,High School,16,13,59,4,94,9.0,0,69,Urban,ML Engineer,103172,0 +19044,Male,41,Diploma,11,50,54,29,8,0.0,2,34,Semi-Urban,HR Executive,46488,0 +19045,Male,38,High School,12,50,39,8,50,3.0,3,74,Urban,HR Executive,92238,0 +19046,Male,34,Bachelors,4,57,18,11,39,2.0,6,56,Semi-Urban,ML Engineer,129496,0 +19047,Male,35,Bachelors,7,32,14,39,88,7.0,3,75,Semi-Urban,Data Analyst,52935,0 +19048,Male,23,Bachelors,6,55,23,60,22,7.0,1,24,Semi-Urban,Manager,77042,0 +19049,Male,51,Diploma,19,71,49,40,85,1.0,7,54,Urban,ML Engineer,62201,0 +19050,Male,26,Diploma,17,1,88,76,19,5.0,4,46,Urban,HR Executive,103602,0 +19051,Male,37,Bachelors,19,25,19,2,7,9.0,7,10,Urban,Software Engineer,95855,0 +19052,Male,22,Masters,8,32,64,34,32,4.0,2,37,Rural,Data Analyst,92604,0 +19053,Other,25,Diploma,18,39,65,40,16,7.0,6,91,Semi-Urban,ML Engineer,112927,0 +19054,Female,44,PhD,0,77,88,14,23,5.0,7,59,Semi-Urban,HR Executive,72990,0 +19055,Male,50,PhD,7,50,85,19,36,7.0,6,28,Rural,Manager,89485,0 +19056,Other,55,Diploma,1,7,58,74,31,6.0,7,47,Urban,HR Executive,149823,0 +19057,Female,54,Bachelors,0,64,57,77,1,8.0,0,46,Semi-Urban,Data Analyst,23792,1 +19058,Male,57,Bachelors,11,61,85,7,91,1.0,0,95,Urban,ML Engineer,39068,1 +19059,Male,35,Masters,9,35,98,50,12,7.0,4,45,Urban,Manager,120137,0 +19060,Female,54,Bachelors,15,84,52,65,54,5.0,7,85,Rural,Data Analyst,22437,1 +19061,Female,39,Bachelors,9,84,58,12,39,8.0,5,24,Urban,HR Executive,104047,0 +19062,Female,28,Bachelors,15,0,77,0,55,6.0,0,85,Urban,Data Analyst,73473,0 +19063,Female,34,Masters,16,54,97,78,67,3.0,0,38,Urban,Manager,35658,1 +19064,Male,58,Bachelors,15,26,32,23,78,6.0,7,48,Semi-Urban,Manager,87939,0 +19065,Male,32,Masters,15,19,90,47,6,0.0,0,86,Rural,Software Engineer,138610,1 +19066,Male,53,Diploma,5,38,83,36,59,1.0,2,34,Urban,Manager,28364,0 +19067,Male,53,Diploma,0,67,97,68,79,7.0,2,35,Urban,HR Executive,135709,1 +19068,Male,39,High School,11,91,10,93,37,5.0,3,63,Urban,Manager,62516,1 +19069,Male,41,Diploma,10,94,32,55,50,1.0,5,58,Urban,Manager,118253,1 +19070,Male,35,Masters,10,61,89,76,24,6.0,3,94,Semi-Urban,Software Engineer,25371,1 +19071,Male,39,Masters,17,25,70,63,61,1.0,4,38,Urban,Software Engineer,22049,0 +19072,Male,52,Masters,15,37,50,53,92,6.0,4,11,Urban,ML Engineer,142741,0 +19073,Male,34,Bachelors,9,97,61,63,94,4.0,3,30,Urban,Manager,104385,1 +19074,Male,51,Bachelors,12,14,7,39,91,9.0,6,75,Semi-Urban,Software Engineer,99809,0 +19075,Male,40,High School,3,77,15,62,91,4.0,5,40,Urban,Data Analyst,33228,0 +19076,Female,54,High School,7,74,58,54,49,1.0,7,38,Semi-Urban,HR Executive,93008,0 +19077,Female,40,Bachelors,3,16,30,17,28,6.0,1,10,Urban,Software Engineer,92997,0 +19078,Male,30,High School,14,53,50,38,98,7.0,6,91,Urban,HR Executive,114738,0 +19079,Male,27,Diploma,1,9,45,18,69,3.0,0,60,Urban,Data Analyst,98175,0 +19080,Female,23,Bachelors,14,91,15,36,22,3.0,4,3,Rural,Data Analyst,145643,0 +19081,Male,43,High School,4,98,44,29,68,0.0,0,25,Urban,HR Executive,140702,0 +19082,Female,30,Diploma,5,93,34,13,17,4.0,2,5,Semi-Urban,HR Executive,31793,0 +19083,Male,55,High School,18,5,24,14,65,3.0,7,38,Rural,HR Executive,91547,0 +19084,Female,37,Bachelors,18,15,6,8,1,3.0,0,14,Semi-Urban,Data Analyst,92835,0 +19085,Female,41,High School,5,4,23,84,12,0.0,6,97,Urban,HR Executive,102022,0 +19086,Female,50,High School,10,8,72,95,52,6.0,5,38,Semi-Urban,HR Executive,144289,0 +19087,Male,23,Bachelors,18,54,24,88,21,1.0,4,20,Urban,ML Engineer,30050,0 +19088,Female,22,Bachelors,19,92,85,25,32,2.0,0,94,Urban,Software Engineer,24672,1 +19089,Female,45,High School,17,4,47,6,20,5.0,0,98,Urban,HR Executive,130799,0 +19090,Female,25,Bachelors,11,13,69,74,73,8.0,5,6,Urban,HR Executive,46473,0 +19091,Male,27,Bachelors,15,78,46,49,40,1.0,7,34,Semi-Urban,Data Analyst,101929,0 +19092,Female,21,Bachelors,0,5,90,88,51,3.0,5,96,Rural,Manager,33024,1 +19093,Male,52,Diploma,16,44,95,72,59,8.0,4,9,Urban,Data Analyst,93732,0 +19094,Male,53,Bachelors,8,81,14,17,0,5.0,6,52,Rural,ML Engineer,102371,0 +19095,Male,57,High School,3,10,38,83,2,5.0,6,16,Semi-Urban,ML Engineer,68567,0 +19096,Male,32,High School,5,24,8,65,53,0.0,7,39,Semi-Urban,Manager,74720,0 +19097,Female,23,Masters,0,6,40,98,69,4.0,1,33,Semi-Urban,Data Analyst,123276,0 +19098,Female,39,Diploma,12,14,19,15,84,7.0,4,35,Urban,Manager,125188,0 +19099,Male,44,Masters,2,42,5,5,62,6.0,6,97,Urban,HR Executive,96199,0 +19100,Female,43,Diploma,13,18,38,47,5,9.0,7,98,Semi-Urban,Manager,111739,0 +19101,Female,43,High School,1,1,79,6,31,7.0,5,35,Urban,ML Engineer,86777,0 +19102,Male,58,Bachelors,5,13,87,85,80,2.0,2,53,Semi-Urban,Manager,54619,1 +19103,Male,28,Diploma,10,82,6,28,83,8.0,7,25,Rural,Data Analyst,136892,0 +19104,Male,44,Diploma,3,46,15,24,57,5.0,2,88,Urban,Data Analyst,133913,0 +19105,Male,30,Bachelors,6,63,26,51,98,9.0,2,21,Semi-Urban,Software Engineer,123184,0 +19106,Male,24,Bachelors,19,56,82,35,39,1.0,6,38,Rural,Data Analyst,39163,0 +19107,Male,33,Bachelors,17,38,5,93,85,6.0,6,6,Urban,Manager,138271,0 +19108,Male,48,Diploma,14,94,28,59,40,4.0,4,90,Semi-Urban,ML Engineer,51526,1 +19109,Other,44,Bachelors,12,72,56,73,78,9.0,5,17,Urban,Data Analyst,119759,0 +19110,Female,47,PhD,12,33,82,30,18,2.0,4,46,Urban,Software Engineer,68263,0 +19111,Male,52,High School,18,40,70,92,57,4.0,6,76,Urban,ML Engineer,90257,1 +19112,Male,38,Bachelors,1,72,21,56,98,2.0,4,87,Urban,Manager,69394,1 +19113,Male,26,Diploma,18,56,90,44,16,4.0,3,80,Urban,Software Engineer,143649,1 +19114,Male,49,Bachelors,15,53,63,50,74,2.0,5,38,Urban,Data Analyst,138003,0 +19115,Male,47,Masters,12,17,90,52,84,2.0,3,77,Urban,HR Executive,95069,1 +19116,Male,47,Diploma,12,75,64,32,67,9.0,7,71,Urban,ML Engineer,51836,1 +19117,Male,55,Masters,14,42,46,14,37,7.0,4,66,Urban,ML Engineer,83050,0 +19118,Male,21,Masters,3,15,44,23,76,6.0,3,68,Semi-Urban,Manager,45225,0 +19119,Male,24,High School,7,24,78,51,38,6.0,0,97,Urban,Manager,89501,1 +19120,Female,52,High School,13,15,66,66,1,1.0,5,60,Semi-Urban,Manager,38413,0 +19121,Male,51,Masters,11,30,19,25,82,0.0,3,13,Urban,HR Executive,21588,0 +19122,Male,25,Bachelors,0,47,16,27,70,5.0,0,38,Urban,Software Engineer,82924,0 +19123,Male,23,Masters,4,15,37,68,33,6.0,4,70,Semi-Urban,HR Executive,66783,0 +19124,Other,33,Masters,13,36,52,30,81,6.0,2,52,Semi-Urban,Data Analyst,140516,0 +19125,Female,33,Bachelors,19,19,66,23,40,0.0,3,59,Urban,HR Executive,126639,0 +19126,Male,42,Diploma,2,69,62,91,25,0.0,1,48,Urban,ML Engineer,48247,1 +19127,Female,41,Bachelors,8,50,72,23,58,6.0,2,42,Urban,Data Analyst,123985,0 +19128,Male,39,Bachelors,14,65,0,35,91,2.0,5,6,Urban,Software Engineer,35430,0 +19129,Other,35,Bachelors,1,81,78,89,83,5.0,6,5,Rural,HR Executive,29684,1 +19130,Male,36,Diploma,15,72,53,86,89,3.0,3,18,Semi-Urban,ML Engineer,86698,0 +19131,Male,26,Diploma,15,12,4,6,1,2.0,7,50,Semi-Urban,ML Engineer,115869,0 +19132,Female,42,PhD,19,79,76,69,41,0.0,5,4,Urban,Software Engineer,27721,0 +19133,Male,37,Bachelors,16,30,58,38,48,9.0,4,82,Urban,Manager,66125,0 +19134,Female,25,Bachelors,14,27,98,41,55,8.0,3,16,Semi-Urban,ML Engineer,48898,0 +19135,Male,28,Bachelors,11,71,29,78,40,3.0,7,6,Urban,ML Engineer,111786,0 +19136,Female,53,High School,8,11,92,92,11,9.0,5,62,Rural,HR Executive,67434,1 +19137,Male,22,Diploma,19,21,75,38,25,5.0,6,80,Semi-Urban,Software Engineer,67940,0 +19138,Male,39,Bachelors,6,43,32,32,0,8.0,0,98,Urban,Data Analyst,60256,0 +19139,Female,25,Diploma,11,19,79,22,42,6.0,2,5,Semi-Urban,Data Analyst,148341,0 +19140,Female,26,Bachelors,15,89,43,65,5,0.0,2,96,Urban,Software Engineer,82200,1 +19141,Other,56,Diploma,17,61,68,39,10,4.0,5,9,Rural,Data Analyst,56172,0 +19142,Female,40,Masters,12,49,3,19,14,9.0,6,28,Urban,Data Analyst,30988,0 +19143,Female,43,High School,16,99,46,40,64,3.0,4,90,Urban,Software Engineer,59752,1 +19144,Male,22,Masters,10,38,80,30,20,2.0,0,78,Rural,Manager,44308,0 +19145,Male,41,High School,8,31,78,53,45,6.0,5,29,Rural,Manager,92249,0 +19146,Male,38,Diploma,18,94,87,0,65,7.0,7,77,Urban,Data Analyst,96476,1 +19147,Male,30,Bachelors,10,12,32,97,43,8.0,1,28,Rural,HR Executive,86289,0 +19148,Female,49,Bachelors,9,78,3,35,53,0.0,4,77,Urban,HR Executive,40970,0 +19149,Male,53,Masters,4,39,0,2,77,5.0,4,34,Rural,Data Analyst,59519,0 +19150,Female,29,Masters,3,62,89,97,80,9.0,5,55,Urban,Software Engineer,67425,1 +19151,Male,43,Bachelors,17,84,81,61,16,5.0,4,70,Semi-Urban,Manager,50433,1 +19152,Female,40,Bachelors,4,9,46,29,4,1.0,6,54,Semi-Urban,ML Engineer,62483,0 +19153,Male,56,High School,9,4,52,12,10,8.0,6,4,Urban,Data Analyst,65185,0 +19154,Male,39,Masters,3,68,59,13,16,1.0,0,83,Rural,ML Engineer,90021,0 +19155,Other,29,Diploma,8,61,73,58,12,3.0,3,84,Urban,Data Analyst,63574,1 +19156,Male,53,Diploma,11,65,7,52,8,4.0,1,82,Rural,Manager,130510,0 +19157,Male,24,Bachelors,17,44,43,17,98,9.0,2,57,Urban,Manager,120264,0 +19158,Male,36,High School,0,60,26,6,27,8.0,7,34,Urban,Data Analyst,114248,0 +19159,Male,36,Masters,6,78,17,8,2,4.0,5,64,Rural,Data Analyst,114330,0 +19160,Male,24,Bachelors,11,0,56,32,65,9.0,2,14,Urban,Data Analyst,62808,0 +19161,Female,41,Bachelors,0,91,55,74,86,8.0,5,48,Rural,ML Engineer,84340,1 +19162,Male,51,High School,2,38,84,95,75,2.0,5,81,Rural,Software Engineer,56952,1 +19163,Male,45,Diploma,17,72,93,89,12,1.0,5,67,Semi-Urban,ML Engineer,35457,1 +19164,Male,37,Bachelors,2,13,96,22,99,2.0,5,21,Urban,Manager,146804,0 +19165,Female,30,Diploma,4,75,82,84,95,8.0,2,26,Urban,Software Engineer,44455,1 +19166,Female,56,Bachelors,9,50,95,72,76,5.0,7,89,Urban,Software Engineer,138393,1 +19167,Male,55,Bachelors,19,55,50,57,61,7.0,1,58,Semi-Urban,HR Executive,95774,0 +19168,Male,27,Bachelors,16,76,84,20,35,1.0,6,87,Urban,Software Engineer,86165,1 +19169,Male,35,Masters,11,20,31,89,97,7.0,2,23,Rural,ML Engineer,55151,0 +19170,Female,31,Bachelors,6,60,59,12,29,5.0,5,63,Urban,Manager,87262,0 +19171,Female,54,Masters,18,70,29,63,91,3.0,7,84,Semi-Urban,Software Engineer,59932,1 +19172,Female,30,High School,2,17,81,0,71,4.0,7,7,Semi-Urban,ML Engineer,59235,0 +19173,Male,24,Diploma,13,17,6,64,97,3.0,5,41,Urban,Software Engineer,42112,0 +19174,Male,28,Bachelors,8,95,55,79,29,6.0,7,21,Rural,Data Analyst,113081,1 +19175,Male,37,Bachelors,12,86,89,34,53,9.0,7,20,Urban,Software Engineer,72674,0 +19176,Male,49,Diploma,10,22,61,47,23,0.0,0,31,Urban,ML Engineer,40280,0 +19177,Male,51,Bachelors,15,95,20,34,78,5.0,5,26,Semi-Urban,Software Engineer,143413,0 +19178,Male,53,High School,15,77,6,71,18,7.0,0,72,Urban,Data Analyst,32191,0 +19179,Female,46,High School,12,93,19,90,9,1.0,3,39,Semi-Urban,HR Executive,131480,1 +19180,Male,26,Masters,5,96,55,89,99,8.0,0,98,Urban,ML Engineer,93426,1 +19181,Female,41,Bachelors,3,22,2,50,20,2.0,5,83,Semi-Urban,Software Engineer,54903,0 +19182,Male,29,Bachelors,8,86,40,41,74,5.0,2,93,Urban,Software Engineer,39077,1 +19183,Female,37,Bachelors,0,72,30,6,7,8.0,3,99,Rural,HR Executive,148142,0 +19184,Other,28,Bachelors,5,90,4,45,43,4.0,2,17,Urban,Software Engineer,126568,0 +19185,Female,23,Bachelors,4,49,93,7,82,6.0,1,28,Urban,Software Engineer,121092,0 +19186,Female,28,High School,13,26,87,86,13,9.0,7,33,Semi-Urban,HR Executive,26258,0 +19187,Female,45,Bachelors,9,7,15,31,10,2.0,0,54,Semi-Urban,Software Engineer,120627,0 +19188,Male,46,Masters,14,56,76,92,98,2.0,7,59,Rural,Data Analyst,39744,1 +19189,Male,53,Diploma,9,8,83,44,32,2.0,0,74,Urban,HR Executive,131952,0 +19190,Female,22,Bachelors,4,64,43,36,87,2.0,6,62,Semi-Urban,ML Engineer,138812,0 +19191,Female,54,Diploma,18,41,71,32,50,5.0,3,61,Urban,Software Engineer,69831,0 +19192,Other,55,Bachelors,18,30,65,53,12,2.0,7,50,Urban,Software Engineer,148885,0 +19193,Male,27,Bachelors,16,23,22,49,76,8.0,4,19,Semi-Urban,Manager,57567,0 +19194,Male,46,Bachelors,12,15,88,77,35,9.0,4,63,Semi-Urban,HR Executive,142474,1 +19195,Female,41,PhD,12,77,28,13,92,4.0,7,38,Rural,Software Engineer,48197,0 +19196,Other,55,Diploma,9,8,48,6,68,2.0,0,35,Rural,Software Engineer,120286,0 +19197,Male,57,Diploma,12,21,27,50,83,8.0,0,26,Urban,Manager,76534,0 +19198,Male,31,Masters,12,6,30,51,66,5.0,6,21,Urban,HR Executive,101384,0 +19199,Male,27,Masters,18,60,68,72,38,5.0,6,95,Urban,Software Engineer,85221,1 +19200,Male,56,Masters,4,27,6,23,64,5.0,7,20,Rural,Software Engineer,137333,0 +19201,Male,34,Bachelors,19,10,45,93,52,4.0,1,66,Urban,HR Executive,35255,0 +19202,Male,23,Diploma,2,18,33,17,71,5.0,2,86,Urban,ML Engineer,66916,0 +19203,Female,51,High School,13,65,24,60,87,2.0,6,89,Rural,Software Engineer,80004,0 +19204,Male,33,High School,2,94,37,74,34,8.0,3,87,Semi-Urban,Software Engineer,105476,1 +19205,Male,30,Diploma,5,25,59,38,6,7.0,1,22,Urban,HR Executive,80907,0 +19206,Female,54,Diploma,0,62,94,22,89,1.0,1,75,Rural,HR Executive,111930,1 +19207,Other,44,High School,15,12,41,25,43,7.0,2,93,Semi-Urban,Manager,118853,0 +19208,Other,56,Masters,6,20,62,94,82,9.0,7,8,Rural,Manager,21204,0 +19209,Male,56,Diploma,8,86,96,18,11,3.0,4,52,Semi-Urban,HR Executive,51462,1 +19210,Other,34,Bachelors,1,45,94,56,45,6.0,7,87,Urban,Data Analyst,23332,1 +19211,Male,59,Bachelors,17,16,2,28,45,9.0,3,4,Urban,HR Executive,132923,0 +19212,Female,47,High School,18,39,85,61,56,3.0,1,17,Rural,Data Analyst,37344,0 +19213,Female,53,Bachelors,19,66,0,17,69,7.0,6,49,Urban,Manager,89611,0 +19214,Male,58,Masters,6,97,79,93,19,3.0,7,46,Urban,Software Engineer,118461,1 +19215,Male,23,Bachelors,4,28,69,82,25,0.0,1,8,Urban,HR Executive,137944,0 +19216,Male,47,High School,6,93,43,85,27,2.0,7,41,Urban,Manager,123366,1 +19217,Female,56,Diploma,17,33,42,18,76,2.0,1,40,Rural,Data Analyst,37399,0 +19218,Male,52,Bachelors,12,9,32,11,21,5.0,7,68,Semi-Urban,Data Analyst,120071,0 +19219,Female,48,High School,12,15,95,79,88,8.0,7,72,Semi-Urban,ML Engineer,54098,1 +19220,Male,35,Bachelors,14,67,79,50,55,5.0,2,40,Urban,HR Executive,137200,1 +19221,Male,49,High School,18,14,55,26,22,0.0,4,7,Urban,Data Analyst,137438,0 +19222,Other,37,PhD,5,59,28,5,64,1.0,6,54,Urban,Data Analyst,24301,0 +19223,Female,30,Diploma,0,97,35,66,38,1.0,6,76,Urban,Manager,100676,1 +19224,Other,37,Bachelors,12,32,95,65,77,2.0,0,24,Rural,ML Engineer,48589,0 +19225,Male,45,Diploma,5,23,59,84,88,3.0,0,56,Urban,Software Engineer,83906,0 +19226,Male,30,Bachelors,13,12,53,77,68,1.0,2,72,Semi-Urban,Data Analyst,92505,0 +19227,Male,36,Bachelors,7,78,19,29,82,3.0,6,12,Urban,HR Executive,75411,0 +19228,Male,25,Bachelors,16,59,47,94,44,7.0,7,94,Urban,Manager,87084,1 +19229,Male,50,Diploma,19,17,81,35,48,6.0,5,67,Rural,Manager,24816,0 +19230,Female,52,Masters,19,68,47,59,17,8.0,0,41,Urban,Manager,76794,0 +19231,Male,38,Bachelors,6,61,13,4,54,5.0,4,84,Rural,Manager,83640,0 +19232,Male,32,Masters,13,99,47,34,78,0.0,3,14,Semi-Urban,Software Engineer,98439,0 +19233,Male,47,Bachelors,4,64,4,67,20,2.0,4,87,Urban,ML Engineer,62219,0 +19234,Male,48,PhD,9,48,65,23,73,4.0,6,9,Semi-Urban,HR Executive,143016,0 +19235,Female,40,Bachelors,3,46,12,33,55,8.0,5,46,Urban,ML Engineer,78641,0 +19236,Male,52,Bachelors,3,63,80,77,77,1.0,2,94,Urban,Manager,32464,1 +19237,Male,43,Diploma,9,62,26,95,70,0.0,7,92,Rural,Manager,46889,1 +19238,Male,23,Masters,8,27,5,60,8,9.0,5,34,Semi-Urban,HR Executive,45300,0 +19239,Female,23,Masters,17,66,39,55,1,9.0,1,26,Semi-Urban,ML Engineer,61073,0 +19240,Female,39,Masters,2,34,54,50,33,1.0,6,23,Urban,Data Analyst,117124,0 +19241,Female,59,Bachelors,8,35,78,9,99,8.0,0,34,Semi-Urban,Software Engineer,125269,0 +19242,Male,37,High School,7,17,94,13,97,3.0,6,59,Rural,Data Analyst,140077,0 +19243,Male,52,Diploma,14,39,50,14,55,6.0,2,1,Urban,ML Engineer,63389,0 +19244,Female,51,Bachelors,4,7,47,92,2,4.0,0,39,Urban,Software Engineer,25533,0 +19245,Other,29,Bachelors,14,78,75,44,66,8.0,2,1,Urban,Software Engineer,20817,0 +19246,Other,55,Bachelors,15,9,95,10,36,0.0,3,71,Rural,Software Engineer,106417,0 +19247,Female,37,Diploma,2,58,58,70,77,1.0,1,43,Rural,HR Executive,116808,0 +19248,Male,36,Diploma,5,0,18,2,52,0.0,6,31,Urban,Software Engineer,86377,0 +19249,Other,36,Bachelors,18,40,81,57,7,6.0,7,52,Urban,ML Engineer,109183,0 +19250,Female,42,Diploma,11,84,95,25,25,4.0,6,97,Rural,HR Executive,129294,1 +19251,Female,49,High School,5,65,1,35,62,1.0,2,82,Rural,Software Engineer,93238,0 +19252,Male,31,Masters,2,34,57,36,19,4.0,6,85,Rural,ML Engineer,104033,0 +19253,Male,30,Masters,17,96,85,82,71,0.0,7,12,Urban,ML Engineer,121344,1 +19254,Male,55,Diploma,3,47,8,97,75,3.0,0,55,Semi-Urban,Manager,36823,0 +19255,Male,25,Diploma,16,2,76,82,59,5.0,7,99,Urban,Software Engineer,142022,1 +19256,Male,36,High School,19,63,33,14,50,0.0,6,3,Urban,Data Analyst,52075,0 +19257,Female,33,Bachelors,17,41,86,48,9,5.0,4,85,Rural,Manager,59107,1 +19258,Male,27,Bachelors,6,43,64,1,13,7.0,3,9,Semi-Urban,ML Engineer,136183,0 +19259,Male,45,High School,8,28,14,51,54,1.0,4,82,Semi-Urban,Software Engineer,20960,0 +19260,Male,54,High School,4,86,35,6,32,6.0,3,14,Semi-Urban,ML Engineer,36442,0 +19261,Male,44,Diploma,18,56,73,16,29,3.0,7,44,Urban,Data Analyst,42972,0 +19262,Other,23,Bachelors,14,54,27,50,22,8.0,6,55,Semi-Urban,Software Engineer,130692,0 +19263,Male,23,Bachelors,0,75,8,50,93,0.0,5,27,Urban,Manager,95013,0 +19264,Male,55,Diploma,14,39,56,92,29,9.0,7,53,Urban,Software Engineer,130704,1 +19265,Female,56,Bachelors,14,81,28,78,30,0.0,7,90,Rural,ML Engineer,117182,1 +19266,Female,41,Bachelors,9,63,39,34,84,0.0,4,48,Urban,Software Engineer,114877,0 +19267,Male,53,Diploma,2,53,98,93,92,2.0,1,84,Urban,Manager,102076,1 +19268,Female,43,Masters,19,8,57,24,65,7.0,0,51,Rural,Software Engineer,32431,0 +19269,Female,57,Diploma,7,60,10,87,97,1.0,7,99,Urban,Data Analyst,99149,1 +19270,Female,39,Masters,10,73,37,40,8,2.0,0,16,Urban,Software Engineer,75251,0 +19271,Male,42,Bachelors,13,69,90,93,37,8.0,0,6,Urban,HR Executive,77587,1 +19272,Other,32,Bachelors,10,38,85,66,1,0.0,2,39,Urban,Data Analyst,82577,0 +19273,Male,54,Bachelors,13,62,72,19,46,1.0,4,36,Urban,ML Engineer,54478,0 +19274,Male,35,Bachelors,17,6,66,31,34,0.0,7,84,Urban,Data Analyst,63898,0 +19275,Male,32,Bachelors,12,0,23,98,75,0.0,0,11,Urban,HR Executive,114727,0 +19276,Male,33,Bachelors,0,24,91,54,19,2.0,3,29,Urban,HR Executive,96460,0 +19277,Female,56,Masters,0,11,37,92,70,1.0,1,35,Semi-Urban,ML Engineer,39388,0 +19278,Male,44,Bachelors,2,17,15,64,29,9.0,6,70,Semi-Urban,HR Executive,86535,0 +19279,Male,26,High School,16,64,0,10,51,9.0,1,61,Rural,Data Analyst,140935,0 +19280,Male,42,Masters,13,58,25,41,38,7.0,3,66,Urban,Data Analyst,65660,0 +19281,Male,57,High School,18,6,90,3,83,8.0,0,8,Urban,Manager,132222,0 +19282,Other,33,Bachelors,17,36,31,11,47,5.0,1,44,Semi-Urban,Software Engineer,110546,0 +19283,Male,31,Diploma,14,73,87,38,92,1.0,1,43,Semi-Urban,Data Analyst,63829,1 +19284,Female,51,Diploma,8,60,22,44,86,2.0,0,51,Rural,ML Engineer,38154,0 +19285,Female,58,Diploma,13,6,12,56,80,8.0,2,42,Urban,Software Engineer,69979,0 +19286,Female,56,High School,11,99,81,86,98,2.0,5,8,Semi-Urban,Manager,108798,1 +19287,Female,39,Bachelors,16,2,50,76,38,3.0,3,8,Urban,Manager,26687,0 +19288,Male,54,Diploma,3,89,23,64,37,3.0,5,77,Semi-Urban,HR Executive,139866,1 +19289,Female,45,Masters,1,53,61,30,80,9.0,7,28,Urban,Software Engineer,33809,0 +19290,Female,43,High School,19,70,57,18,43,3.0,5,41,Rural,ML Engineer,84842,0 +19291,Female,30,Diploma,8,27,23,83,95,7.0,7,36,Urban,Manager,108020,0 +19292,Other,37,Bachelors,19,74,3,15,31,5.0,6,16,Urban,Manager,136077,0 +19293,Female,47,High School,3,52,67,87,80,0.0,2,5,Urban,ML Engineer,139412,0 +19294,Female,27,Bachelors,18,74,32,44,89,6.0,3,22,Semi-Urban,Data Analyst,51585,0 +19295,Other,48,Bachelors,12,43,32,28,21,7.0,1,37,Semi-Urban,Software Engineer,118986,0 +19296,Male,34,Diploma,16,51,93,51,46,1.0,6,28,Semi-Urban,Manager,61253,0 +19297,Male,35,Diploma,7,32,89,86,45,3.0,6,84,Urban,HR Executive,85152,1 +19298,Male,45,High School,13,70,7,86,91,0.0,5,40,Semi-Urban,ML Engineer,52870,0 +19299,Male,24,High School,5,9,5,4,14,2.0,5,18,Urban,ML Engineer,144988,0 +19300,Female,45,Bachelors,7,89,14,37,29,1.0,7,49,Rural,Data Analyst,107100,0 +19301,Female,34,High School,19,36,8,74,41,1.0,3,88,Rural,ML Engineer,50192,0 +19302,Female,29,Bachelors,12,21,17,61,76,0.0,2,56,Urban,Software Engineer,116607,0 +19303,Other,37,Diploma,5,93,45,15,91,5.0,4,96,Semi-Urban,Data Analyst,74428,1 +19304,Male,51,PhD,11,16,4,19,46,6.0,5,73,Semi-Urban,ML Engineer,78338,0 +19305,Female,38,Masters,11,7,31,7,59,3.0,4,25,Urban,ML Engineer,38778,0 +19306,Male,35,Bachelors,11,50,72,73,5,6.0,3,36,Urban,HR Executive,122757,0 +19307,Male,53,Diploma,6,82,73,75,92,7.0,3,77,Urban,ML Engineer,68926,1 +19308,Male,34,High School,3,91,20,68,29,9.0,1,46,Urban,HR Executive,91250,0 +19309,Female,58,Diploma,11,53,25,5,89,7.0,4,32,Semi-Urban,Data Analyst,80956,0 +19310,Male,26,Bachelors,14,94,57,42,21,3.0,5,56,Urban,Software Engineer,63853,1 +19311,Female,46,Masters,17,46,58,29,5,4.0,1,35,Semi-Urban,ML Engineer,114156,0 +19312,Male,52,Bachelors,9,37,46,98,1,9.0,4,35,Rural,Data Analyst,67510,0 +19313,Male,39,Masters,12,15,57,91,9,7.0,4,32,Rural,ML Engineer,81708,0 +19314,Male,43,High School,5,71,60,9,63,1.0,4,3,Urban,ML Engineer,141072,0 +19315,Male,46,Diploma,5,50,27,1,11,2.0,5,46,Semi-Urban,Manager,103959,0 +19316,Other,31,Bachelors,11,18,93,59,16,1.0,4,48,Urban,HR Executive,26789,0 +19317,Male,33,Diploma,18,88,14,55,17,5.0,7,89,Urban,Data Analyst,29426,1 +19318,Other,41,Bachelors,17,75,98,64,1,0.0,3,13,Semi-Urban,Software Engineer,89941,1 +19319,Other,43,High School,14,53,72,47,84,9.0,2,33,Rural,Manager,95460,0 +19320,Other,55,Bachelors,3,30,56,19,31,3.0,0,96,Semi-Urban,Data Analyst,80017,0 +19321,Male,50,Masters,2,48,21,39,15,3.0,0,80,Semi-Urban,Software Engineer,65329,0 +19322,Other,59,Diploma,6,17,84,65,69,9.0,4,2,Urban,Software Engineer,108126,0 +19323,Male,35,High School,4,28,14,7,25,5.0,6,51,Rural,Manager,25142,0 +19324,Male,23,High School,8,95,11,74,39,5.0,5,4,Urban,Data Analyst,51688,0 +19325,Male,28,Diploma,15,5,63,28,92,8.0,6,74,Rural,HR Executive,68040,0 +19326,Female,58,Bachelors,13,67,79,4,15,6.0,5,20,Urban,HR Executive,39438,0 +19327,Male,27,Masters,12,47,0,40,69,0.0,2,11,Semi-Urban,ML Engineer,23774,0 +19328,Male,43,Bachelors,3,52,33,46,50,0.0,0,39,Urban,HR Executive,139308,0 +19329,Male,55,Bachelors,9,80,81,5,18,2.0,4,50,Urban,Manager,75956,0 +19330,Male,39,Bachelors,2,83,92,58,41,6.0,3,12,Urban,Data Analyst,147151,1 +19331,Male,23,Diploma,19,95,82,66,64,7.0,6,91,Rural,Software Engineer,125433,1 +19332,Female,31,Bachelors,2,8,76,94,33,9.0,0,14,Urban,HR Executive,83797,0 +19333,Male,40,Bachelors,14,53,32,50,1,0.0,1,19,Semi-Urban,Software Engineer,40907,0 +19334,Female,54,Bachelors,19,98,77,54,91,4.0,7,12,Urban,ML Engineer,121364,1 +19335,Female,41,Masters,8,0,14,55,8,7.0,2,3,Urban,Software Engineer,65950,0 +19336,Other,37,Masters,13,56,96,45,53,2.0,4,99,Rural,Data Analyst,27838,1 +19337,Male,51,Bachelors,7,97,23,40,90,9.0,7,26,Rural,Manager,96812,0 +19338,Female,50,High School,6,50,8,60,50,7.0,3,18,Rural,Manager,67616,0 +19339,Male,36,Bachelors,15,39,48,8,53,2.0,3,34,Rural,ML Engineer,26318,0 +19340,Male,56,High School,17,43,5,31,10,0.0,5,64,Urban,HR Executive,95410,0 +19341,Female,57,Masters,3,3,0,93,33,1.0,7,45,Semi-Urban,Manager,79676,0 +19342,Female,28,Bachelors,9,55,41,98,8,9.0,5,3,Urban,HR Executive,139646,0 +19343,Female,44,Masters,15,30,83,59,54,2.0,2,82,Urban,Manager,59149,1 +19344,Female,45,High School,8,2,72,92,58,0.0,5,68,Urban,ML Engineer,126422,0 +19345,Male,29,Bachelors,16,7,94,93,76,9.0,2,83,Urban,Software Engineer,97152,1 +19346,Female,42,Masters,5,54,71,33,25,1.0,5,15,Urban,HR Executive,36155,0 +19347,Male,59,Diploma,14,90,18,55,16,6.0,6,32,Urban,Manager,101113,0 +19348,Male,52,Bachelors,4,37,29,19,53,9.0,4,9,Urban,ML Engineer,25714,0 +19349,Female,29,Masters,6,52,44,54,59,8.0,7,13,Urban,ML Engineer,39004,0 +19350,Other,54,Bachelors,19,14,25,72,29,1.0,0,13,Semi-Urban,Data Analyst,122916,0 +19351,Male,39,Diploma,0,8,78,33,25,5.0,5,77,Urban,Software Engineer,35706,0 +19352,Male,41,Diploma,14,67,80,2,45,6.0,2,43,Semi-Urban,Data Analyst,70268,0 +19353,Male,47,High School,11,24,53,42,42,7.0,6,30,Urban,Software Engineer,74969,0 +19354,Male,47,Diploma,4,68,14,74,60,2.0,7,36,Urban,Data Analyst,146115,0 +19355,Female,42,Masters,14,15,83,8,23,3.0,2,93,Urban,Data Analyst,92280,0 +19356,Female,25,High School,19,91,39,37,86,5.0,7,47,Urban,Manager,96094,0 +19357,Female,31,Masters,18,41,52,64,95,6.0,4,74,Semi-Urban,Data Analyst,128700,0 +19358,Female,55,Diploma,10,64,9,93,58,9.0,5,63,Urban,HR Executive,31923,0 +19359,Male,40,Diploma,19,0,52,73,82,0.0,0,98,Semi-Urban,Software Engineer,86265,0 +19360,Male,24,Diploma,17,28,61,99,0,8.0,2,54,Urban,Data Analyst,20465,1 +19361,Male,43,Bachelors,13,65,13,81,89,0.0,1,21,Urban,HR Executive,113590,0 +19362,Female,37,Bachelors,19,82,33,38,63,3.0,4,27,Urban,Manager,79077,0 +19363,Female,24,Bachelors,5,74,42,85,73,3.0,2,67,Semi-Urban,Manager,20759,1 +19364,Female,48,Bachelors,1,73,99,13,34,5.0,3,8,Urban,Manager,84307,0 +19365,Male,30,High School,15,66,20,46,61,6.0,5,32,Semi-Urban,ML Engineer,143912,0 +19366,Male,31,High School,16,86,6,6,48,1.0,2,82,Rural,Data Analyst,127976,0 +19367,Other,27,Bachelors,12,45,65,68,35,2.0,0,26,Semi-Urban,HR Executive,44619,0 +19368,Male,21,Diploma,5,6,78,60,79,2.0,0,93,Rural,Manager,143784,1 +19369,Female,54,Bachelors,7,12,27,99,85,4.0,2,33,Urban,Manager,72934,0 +19370,Male,53,High School,18,37,4,68,47,2.0,4,19,Urban,Software Engineer,102789,0 +19371,Male,54,Diploma,7,11,76,9,41,1.0,5,27,Semi-Urban,Manager,39782,0 +19372,Female,37,Masters,4,64,81,15,58,3.0,7,67,Semi-Urban,Manager,45661,0 +19373,Male,56,Masters,11,14,98,84,8,3.0,1,86,Urban,ML Engineer,55878,1 +19374,Female,41,Bachelors,9,90,23,22,61,3.0,7,61,Semi-Urban,Manager,79533,0 +19375,Female,48,PhD,16,20,40,37,39,3.0,4,23,Urban,Software Engineer,118603,0 +19376,Male,36,Bachelors,0,98,32,5,24,5.0,6,97,Semi-Urban,ML Engineer,134099,0 +19377,Female,36,Masters,17,56,51,3,32,4.0,5,96,Urban,Data Analyst,22263,0 +19378,Male,48,Bachelors,15,10,3,15,5,6.0,2,39,Rural,Software Engineer,136797,0 +19379,Male,49,Diploma,18,11,26,67,21,3.0,1,52,Urban,Software Engineer,99062,0 +19380,Female,22,Masters,11,32,63,74,51,6.0,4,73,Urban,Data Analyst,118459,1 +19381,Male,36,PhD,0,29,77,78,4,5.0,6,72,Semi-Urban,ML Engineer,146168,1 +19382,Male,39,Diploma,2,85,58,71,53,0.0,1,93,Semi-Urban,Software Engineer,39124,1 +19383,Female,47,Bachelors,16,39,18,2,62,6.0,5,21,Semi-Urban,HR Executive,28905,0 +19384,Male,59,Bachelors,7,86,9,32,61,8.0,3,22,Rural,Manager,117673,0 +19385,Female,22,High School,5,64,10,93,37,2.0,3,52,Urban,Manager,62481,0 +19386,Female,38,Bachelors,4,55,79,5,93,9.0,2,42,Semi-Urban,Data Analyst,68577,0 +19387,Male,43,Masters,6,12,27,58,57,8.0,3,16,Rural,ML Engineer,110168,0 +19388,Male,32,Bachelors,19,31,41,20,55,9.0,4,47,Urban,Manager,31061,0 +19389,Male,46,Masters,15,89,98,0,75,3.0,4,61,Urban,Manager,24743,1 +19390,Male,50,Bachelors,6,42,70,48,91,2.0,2,37,Semi-Urban,ML Engineer,76023,0 +19391,Female,34,Masters,3,4,27,83,7,7.0,0,61,Urban,ML Engineer,53661,0 +19392,Female,35,Masters,10,2,26,52,61,0.0,3,50,Semi-Urban,Software Engineer,58553,0 +19393,Male,21,Diploma,4,20,47,4,54,9.0,5,44,Rural,ML Engineer,99094,0 +19394,Female,37,Masters,7,16,26,89,19,3.0,5,44,Rural,Manager,138109,0 +19395,Other,28,Bachelors,19,10,96,34,36,3.0,4,76,Rural,Data Analyst,110371,0 +19396,Male,51,Diploma,4,26,99,11,60,4.0,0,72,Rural,Manager,60497,0 +19397,Female,46,Diploma,7,76,89,12,98,8.0,5,96,Rural,HR Executive,146324,1 +19398,Female,38,High School,3,8,77,82,50,6.0,7,52,Rural,Data Analyst,148630,0 +19399,Male,34,High School,14,9,78,85,7,0.0,7,39,Urban,Data Analyst,49207,0 +19400,Male,32,Bachelors,12,89,33,93,18,4.0,1,58,Urban,Data Analyst,25679,1 +19401,Female,26,High School,0,4,15,74,93,7.0,0,43,Semi-Urban,HR Executive,101911,0 +19402,Male,41,Bachelors,18,86,20,65,56,0.0,0,28,Semi-Urban,Manager,31495,0 +19403,Male,42,Diploma,2,31,75,96,63,1.0,7,77,Urban,ML Engineer,136227,1 +19404,Female,38,Bachelors,0,20,93,12,43,7.0,6,21,Semi-Urban,Software Engineer,56284,0 +19405,Female,33,High School,8,35,94,87,58,6.0,4,15,Rural,HR Executive,92944,0 +19406,Male,59,PhD,15,81,82,28,35,3.0,3,72,Urban,Manager,124624,1 +19407,Male,22,Bachelors,13,98,16,36,5,1.0,6,4,Urban,Data Analyst,57729,0 +19408,Male,44,Diploma,12,49,7,76,5,4.0,0,96,Urban,ML Engineer,106191,0 +19409,Male,53,Diploma,17,30,14,86,7,0.0,5,27,Semi-Urban,Data Analyst,101919,0 +19410,Male,41,Diploma,16,61,17,58,50,0.0,2,5,Urban,HR Executive,83785,0 +19411,Male,47,Masters,6,77,77,17,30,9.0,2,2,Urban,ML Engineer,69711,0 +19412,Male,56,Diploma,5,67,70,96,65,6.0,2,70,Urban,HR Executive,147860,1 +19413,Male,59,Bachelors,8,14,96,3,7,4.0,1,74,Urban,Software Engineer,111964,0 +19414,Male,39,Bachelors,4,62,44,5,52,3.0,2,18,Urban,ML Engineer,93073,0 +19415,Male,37,Diploma,0,9,49,37,37,6.0,6,25,Rural,Manager,46339,0 +19416,Male,40,Masters,12,22,89,31,39,6.0,2,99,Rural,Manager,24349,1 +19417,Male,45,Diploma,2,75,53,59,50,4.0,4,47,Urban,Manager,33536,0 +19418,Female,36,Diploma,13,62,63,62,18,5.0,6,44,Urban,HR Executive,29191,0 +19419,Male,50,Masters,6,35,2,48,37,9.0,4,85,Urban,Data Analyst,81797,0 +19420,Female,54,Diploma,14,8,67,21,77,0.0,2,19,Urban,Manager,43059,0 +19421,Female,59,High School,9,23,94,8,2,0.0,3,24,Urban,ML Engineer,130671,0 +19422,Male,41,Bachelors,18,63,77,28,63,0.0,0,31,Rural,ML Engineer,112689,0 +19423,Female,33,Bachelors,13,14,77,46,53,0.0,5,7,Urban,Software Engineer,38139,0 +19424,Male,21,Masters,9,73,89,83,4,4.0,6,37,Urban,Manager,83639,1 +19425,Male,30,Masters,5,23,2,34,82,8.0,3,83,Urban,Data Analyst,71164,0 +19426,Male,31,PhD,16,69,74,30,71,8.0,6,43,Urban,Data Analyst,81562,0 +19427,Male,57,Bachelors,1,2,94,37,58,2.0,6,8,Urban,Software Engineer,38442,0 +19428,Male,53,High School,11,87,35,79,35,7.0,6,53,Rural,Data Analyst,66486,1 +19429,Male,38,Masters,8,6,38,71,71,8.0,3,73,Urban,Data Analyst,23309,0 +19430,Female,47,Bachelors,12,47,48,22,79,7.0,5,2,Semi-Urban,Data Analyst,23575,0 +19431,Female,43,Bachelors,7,8,1,38,63,1.0,3,42,Urban,Manager,63321,0 +19432,Male,58,Masters,18,66,86,73,15,9.0,4,93,Urban,ML Engineer,128143,1 +19433,Male,51,Bachelors,10,34,41,4,41,4.0,5,16,Rural,Software Engineer,96676,0 +19434,Male,30,Masters,15,80,42,94,51,5.0,2,49,Rural,Data Analyst,143762,1 +19435,Male,46,Masters,6,81,25,2,15,5.0,3,23,Urban,Manager,117371,0 +19436,Female,35,High School,18,90,54,62,85,6.0,0,21,Urban,Software Engineer,108553,0 +19437,Male,39,Bachelors,13,67,83,18,79,8.0,0,12,Rural,Data Analyst,147660,0 +19438,Male,59,Masters,16,10,90,27,66,1.0,1,74,Rural,Software Engineer,107533,0 +19439,Female,28,Bachelors,5,16,20,61,48,9.0,6,0,Urban,Software Engineer,52176,0 +19440,Female,29,High School,15,27,96,25,88,0.0,3,69,Semi-Urban,Software Engineer,58813,0 +19441,Male,38,Diploma,0,59,11,56,63,3.0,1,2,Semi-Urban,Data Analyst,68789,0 +19442,Male,46,Masters,14,75,52,37,62,6.0,7,44,Urban,Software Engineer,50729,0 +19443,Male,24,Masters,17,14,31,74,14,5.0,2,44,Urban,Data Analyst,35328,0 +19444,Male,59,Diploma,4,70,29,79,74,1.0,0,51,Semi-Urban,Software Engineer,77374,0 +19445,Male,34,Bachelors,9,25,12,62,0,3.0,7,17,Urban,HR Executive,82437,0 +19446,Male,52,Masters,4,4,14,70,27,5.0,0,2,Urban,Manager,79636,0 +19447,Female,57,Bachelors,16,48,1,64,91,5.0,6,42,Rural,ML Engineer,112864,0 +19448,Male,48,PhD,6,94,51,34,69,9.0,0,40,Urban,HR Executive,145794,0 +19449,Male,51,Bachelors,13,23,97,87,53,5.0,4,89,Urban,Data Analyst,57988,1 +19450,Male,52,Bachelors,13,10,92,93,74,6.0,2,74,Urban,Software Engineer,42150,1 +19451,Male,54,High School,8,16,34,9,23,4.0,6,51,Rural,HR Executive,37089,0 +19452,Female,42,Bachelors,18,89,27,20,45,7.0,5,44,Urban,HR Executive,46561,0 +19453,Male,55,Masters,8,65,57,90,25,0.0,0,36,Urban,Manager,122921,1 +19454,Male,33,Bachelors,19,41,85,93,10,7.0,7,94,Urban,ML Engineer,139159,1 +19455,Male,29,Diploma,12,18,56,88,27,9.0,3,63,Semi-Urban,Software Engineer,53911,0 +19456,Male,59,High School,19,35,62,92,69,3.0,5,2,Semi-Urban,Data Analyst,135542,0 +19457,Male,40,Diploma,9,92,10,34,44,1.0,2,4,Semi-Urban,Software Engineer,75617,0 +19458,Male,26,Masters,1,60,99,14,8,3.0,0,45,Urban,Software Engineer,148134,0 +19459,Male,40,Bachelors,8,19,72,39,56,2.0,5,49,Urban,HR Executive,48140,0 +19460,Male,44,Diploma,5,35,59,62,46,3.0,4,5,Rural,Manager,116343,0 +19461,Male,42,Diploma,4,28,72,42,46,3.0,5,98,Rural,Manager,102195,1 +19462,Female,44,High School,9,8,24,59,16,7.0,2,11,Semi-Urban,ML Engineer,115690,0 +19463,Female,43,Bachelors,3,55,64,12,34,9.0,7,75,Urban,Data Analyst,24463,0 +19464,Female,41,Bachelors,10,63,38,54,8,1.0,0,85,Rural,Data Analyst,144504,0 +19465,Female,36,Bachelors,4,44,47,80,93,8.0,5,1,Semi-Urban,ML Engineer,81050,0 +19466,Male,47,Bachelors,12,64,30,85,98,1.0,1,34,Urban,Manager,75041,0 +19467,Female,45,Diploma,3,75,16,1,10,8.0,1,74,Urban,Software Engineer,40654,0 +19468,Male,55,PhD,14,86,22,20,2,1.0,5,17,Rural,ML Engineer,32006,0 +19469,Male,48,Bachelors,0,91,93,26,91,9.0,6,43,Urban,Manager,53834,1 +19470,Male,44,Diploma,9,11,9,30,6,5.0,7,50,Semi-Urban,Data Analyst,35051,0 +19471,Male,54,High School,16,17,96,45,87,4.0,6,11,Urban,Data Analyst,133403,0 +19472,Other,30,Bachelors,10,70,41,20,59,3.0,5,8,Semi-Urban,Manager,27718,0 +19473,Male,55,Diploma,8,75,44,15,0,7.0,6,96,Semi-Urban,Manager,28776,0 +19474,Male,44,Diploma,7,50,82,30,77,3.0,5,88,Urban,Manager,37391,1 +19475,Male,34,Diploma,8,21,74,38,62,3.0,2,86,Urban,Data Analyst,21688,0 +19476,Male,54,Masters,3,53,96,86,72,9.0,1,6,Rural,Software Engineer,25641,1 +19477,Male,57,Masters,4,63,95,27,3,4.0,7,69,Urban,Software Engineer,145693,1 +19478,Male,59,Bachelors,4,85,11,67,54,2.0,7,71,Urban,Data Analyst,64912,0 +19479,Male,50,Bachelors,16,79,94,88,57,7.0,6,88,Urban,ML Engineer,130300,1 +19480,Female,53,Bachelors,3,82,76,83,92,5.0,2,94,Urban,Software Engineer,78274,1 +19481,Male,25,Masters,19,80,47,4,5,6.0,5,62,Semi-Urban,HR Executive,74639,0 +19482,Male,32,High School,12,71,51,38,21,9.0,0,2,Semi-Urban,HR Executive,91862,0 +19483,Female,36,Diploma,1,76,57,99,86,6.0,0,13,Semi-Urban,Software Engineer,111391,1 +19484,Other,43,Bachelors,17,53,28,5,33,1.0,6,69,Urban,Software Engineer,43731,0 +19485,Male,37,Bachelors,8,83,66,59,64,1.0,6,25,Urban,Data Analyst,49847,0 +19486,Male,21,PhD,3,19,60,72,26,8.0,4,17,Urban,ML Engineer,116824,0 +19487,Other,26,Bachelors,16,52,43,94,66,2.0,2,73,Rural,HR Executive,142246,1 +19488,Male,48,High School,16,51,49,64,46,2.0,6,58,Urban,Software Engineer,68752,0 +19489,Male,25,Masters,11,29,18,34,59,6.0,3,35,Semi-Urban,Data Analyst,21547,0 +19490,Male,29,Bachelors,18,52,38,69,70,4.0,3,13,Urban,ML Engineer,149544,0 +19491,Female,21,Bachelors,6,10,16,91,77,4.0,7,81,Urban,HR Executive,37388,0 +19492,Other,23,Bachelors,9,0,92,54,87,0.0,2,3,Urban,HR Executive,87308,0 +19493,Female,50,Bachelors,2,66,4,84,85,9.0,2,57,Rural,ML Engineer,74837,0 +19494,Male,41,Bachelors,10,38,35,66,38,6.0,5,85,Semi-Urban,Software Engineer,96794,0 +19495,Male,37,Bachelors,17,99,8,45,15,6.0,0,80,Rural,Software Engineer,122892,0 +19496,Male,24,Diploma,7,91,29,4,49,3.0,2,94,Semi-Urban,ML Engineer,54190,0 +19497,Female,53,Diploma,0,81,63,50,47,0.0,2,0,Urban,Manager,96013,0 +19498,Female,50,Bachelors,17,13,85,32,49,6.0,2,74,Semi-Urban,HR Executive,60133,0 +19499,Male,48,Bachelors,3,15,7,41,36,2.0,5,58,Semi-Urban,HR Executive,97631,0 +19500,Female,44,Masters,2,4,5,28,12,8.0,0,79,Urban,Data Analyst,148560,0 +19501,Male,43,Diploma,6,82,3,72,71,4.0,1,7,Semi-Urban,HR Executive,107141,0 +19502,Male,37,Diploma,3,37,27,18,51,2.0,1,50,Rural,Software Engineer,76684,0 +19503,Female,48,Diploma,4,97,48,9,97,0.0,0,74,Semi-Urban,HR Executive,70884,0 +19504,Male,56,Masters,8,92,3,97,31,9.0,2,75,Rural,Manager,115904,1 +19505,Male,53,High School,2,86,88,34,98,8.0,4,72,Urban,Data Analyst,121712,1 +19506,Male,54,Bachelors,4,67,17,28,82,4.0,7,14,Semi-Urban,Manager,99223,0 +19507,Female,34,Bachelors,9,45,79,61,3,6.0,6,24,Rural,HR Executive,126086,0 +19508,Female,54,Diploma,13,1,86,78,80,7.0,3,48,Rural,Manager,57639,0 +19509,Other,48,Bachelors,3,93,96,13,85,0.0,2,76,Urban,HR Executive,112686,1 +19510,Female,22,Bachelors,10,48,17,38,70,7.0,1,76,Urban,HR Executive,42358,0 +19511,Male,35,Masters,10,73,36,14,29,3.0,2,9,Semi-Urban,Manager,137568,0 +19512,Male,42,Bachelors,11,45,75,9,18,5.0,1,57,Semi-Urban,ML Engineer,26170,0 +19513,Other,51,Bachelors,15,42,33,10,39,3.0,3,74,Urban,Manager,66925,0 +19514,Male,34,Bachelors,8,65,72,3,48,3.0,2,31,Urban,Manager,123827,0 +19515,Female,39,Diploma,2,78,34,30,40,7.0,7,20,Semi-Urban,Manager,21205,0 +19516,Female,54,Bachelors,5,74,58,56,88,3.0,3,92,Urban,HR Executive,65327,1 +19517,Female,51,Bachelors,14,77,43,58,44,7.0,7,36,Rural,HR Executive,30126,0 +19518,Male,57,Masters,0,19,88,43,38,6.0,0,88,Semi-Urban,ML Engineer,40529,1 +19519,Male,29,Bachelors,18,0,23,11,89,4.0,1,15,Urban,ML Engineer,35902,0 +19520,Female,41,Masters,12,88,14,63,20,8.0,4,42,Semi-Urban,Data Analyst,48841,0 +19521,Female,52,Bachelors,18,77,48,18,95,1.0,1,53,Rural,Software Engineer,137226,0 +19522,Female,40,High School,5,67,45,70,34,3.0,2,4,Urban,Manager,49925,0 +19523,Male,58,Diploma,9,16,21,28,32,4.0,6,51,Urban,Software Engineer,101748,0 +19524,Male,58,Bachelors,0,53,87,95,50,7.0,0,41,Urban,ML Engineer,21358,1 +19525,Female,25,PhD,0,71,11,55,50,1.0,4,15,Urban,Software Engineer,135697,0 +19526,Female,28,Diploma,2,40,20,49,69,8.0,4,77,Urban,Manager,96813,0 +19527,Female,43,Diploma,8,73,68,67,12,1.0,3,78,Urban,Manager,94743,1 +19528,Male,38,Masters,15,28,13,62,10,7.0,7,58,Urban,HR Executive,41410,0 +19529,Female,26,Bachelors,2,88,99,78,8,8.0,4,78,Rural,HR Executive,139189,1 +19530,Male,30,Bachelors,16,86,22,37,25,3.0,7,17,Urban,HR Executive,99275,0 +19531,Female,31,Diploma,5,20,69,83,37,2.0,1,99,Urban,HR Executive,132458,1 +19532,Male,46,PhD,3,33,45,32,8,2.0,6,97,Semi-Urban,Data Analyst,135511,0 +19533,Male,25,Masters,17,24,86,60,25,4.0,1,87,Semi-Urban,ML Engineer,96550,1 +19534,Female,22,Diploma,3,22,42,68,76,3.0,1,80,Rural,HR Executive,119963,0 +19535,Male,21,Bachelors,14,22,67,78,70,6.0,4,94,Urban,Data Analyst,29075,1 +19536,Male,54,Masters,3,31,74,45,9,6.0,6,39,Rural,ML Engineer,118297,0 +19537,Male,54,Diploma,2,61,83,45,21,3.0,5,81,Urban,ML Engineer,108292,1 +19538,Female,30,Bachelors,5,28,59,96,56,8.0,1,69,Rural,Data Analyst,87553,1 +19539,Male,22,Masters,12,42,99,33,72,9.0,6,2,Urban,Data Analyst,120697,0 +19540,Male,23,Masters,10,21,1,3,6,2.0,4,79,Urban,Manager,93804,0 +19541,Female,51,Bachelors,8,43,97,9,58,3.0,0,61,Urban,Data Analyst,35402,0 +19542,Male,51,Bachelors,2,58,99,32,4,5.0,0,0,Urban,Data Analyst,26066,0 +19543,Male,41,Masters,16,92,58,29,9,6.0,3,26,Urban,Software Engineer,85112,0 +19544,Male,47,Masters,0,48,92,21,42,6.0,1,50,Urban,ML Engineer,78214,0 +19545,Other,42,Diploma,15,5,26,44,20,3.0,5,91,Rural,Data Analyst,30463,0 +19546,Male,38,Masters,16,95,50,97,69,7.0,1,10,Semi-Urban,Data Analyst,145767,1 +19547,Female,26,Diploma,5,78,48,70,43,8.0,3,14,Urban,Data Analyst,143842,0 +19548,Male,36,PhD,9,58,41,2,77,4.0,0,52,Urban,Manager,99318,0 +19549,Female,52,Masters,12,91,12,36,31,2.0,5,29,Semi-Urban,ML Engineer,46118,0 +19550,Female,56,Diploma,18,65,52,34,68,7.0,5,53,Urban,Data Analyst,75557,0 +19551,Male,22,Diploma,18,62,48,31,13,4.0,2,65,Rural,Manager,60282,0 +19552,Male,21,Bachelors,13,26,1,42,8,1.0,2,70,Urban,HR Executive,112649,0 +19553,Female,53,Bachelors,3,32,83,47,78,7.0,3,35,Urban,HR Executive,80521,0 +19554,Male,39,Bachelors,15,6,85,4,9,7.0,5,54,Urban,ML Engineer,97626,0 +19555,Female,31,Bachelors,1,10,28,53,69,3.0,4,60,Semi-Urban,HR Executive,43671,0 +19556,Male,50,Masters,1,90,33,90,0,4.0,2,40,Rural,ML Engineer,110168,1 +19557,Female,49,Bachelors,14,48,15,7,34,8.0,0,98,Semi-Urban,Manager,112222,0 +19558,Male,31,Masters,7,4,58,33,97,5.0,6,52,Semi-Urban,Data Analyst,98448,0 +19559,Female,35,Bachelors,3,57,5,84,86,6.0,4,86,Semi-Urban,Data Analyst,27438,0 +19560,Male,47,Bachelors,0,15,18,41,82,5.0,4,56,Rural,ML Engineer,60872,0 +19561,Male,50,High School,4,84,70,3,53,2.0,2,70,Urban,Software Engineer,92003,0 +19562,Male,55,Diploma,9,85,85,85,3,5.0,4,96,Semi-Urban,Software Engineer,147890,1 +19563,Male,47,PhD,14,97,15,28,60,1.0,6,88,Rural,Manager,117613,0 +19564,Male,42,Diploma,11,55,33,77,91,8.0,1,16,Rural,ML Engineer,132304,0 +19565,Male,38,High School,2,14,33,69,95,6.0,4,14,Urban,Software Engineer,25504,0 +19566,Female,48,Diploma,3,32,92,48,67,5.0,2,77,Rural,Manager,47728,1 +19567,Male,46,High School,13,99,76,10,62,4.0,4,47,Urban,Software Engineer,102910,0 +19568,Female,58,High School,4,91,16,74,92,4.0,6,48,Urban,Software Engineer,54725,0 +19569,Male,43,High School,4,35,95,87,95,8.0,1,36,Urban,Manager,90812,1 +19570,Male,49,Bachelors,3,45,58,36,66,2.0,5,55,Urban,Data Analyst,60840,0 +19571,Male,24,Masters,7,11,86,15,74,3.0,7,48,Urban,Data Analyst,65931,0 +19572,Other,51,Bachelors,5,38,99,19,75,8.0,5,62,Urban,HR Executive,47530,0 +19573,Female,49,High School,12,94,99,90,56,8.0,5,19,Semi-Urban,ML Engineer,55882,1 +19574,Male,47,Diploma,12,68,19,65,61,8.0,7,49,Urban,Data Analyst,53404,0 +19575,Female,38,Bachelors,18,81,35,46,30,7.0,3,8,Urban,Manager,105250,0 +19576,Male,32,Bachelors,11,52,1,77,63,8.0,4,48,Urban,ML Engineer,51978,0 +19577,Male,37,Bachelors,1,9,37,58,75,5.0,6,11,Rural,ML Engineer,59548,0 +19578,Male,28,Bachelors,17,59,21,1,38,9.0,3,35,Urban,Data Analyst,114830,0 +19579,Male,28,Bachelors,10,51,82,35,33,8.0,7,43,Semi-Urban,HR Executive,37553,0 +19580,Male,28,Diploma,8,85,38,26,77,3.0,7,60,Urban,Software Engineer,101267,0 +19581,Female,50,High School,19,75,78,64,18,8.0,3,33,Semi-Urban,Software Engineer,28120,1 +19582,Male,22,Masters,1,17,81,44,89,1.0,5,99,Rural,Manager,137350,1 +19583,Female,33,Masters,0,28,24,29,0,4.0,6,57,Semi-Urban,HR Executive,49970,0 +19584,Male,56,Bachelors,10,79,87,68,84,3.0,3,33,Urban,HR Executive,83437,1 +19585,Male,58,Bachelors,18,87,83,42,15,2.0,5,86,Urban,HR Executive,59854,1 +19586,Female,58,Masters,9,70,82,97,53,0.0,4,99,Urban,ML Engineer,67155,1 +19587,Female,26,Diploma,7,35,18,62,33,0.0,7,77,Semi-Urban,Software Engineer,24861,0 +19588,Female,24,Masters,1,70,26,45,69,8.0,3,95,Urban,HR Executive,73679,0 +19589,Male,46,High School,16,52,94,35,45,0.0,5,54,Urban,Software Engineer,49268,1 +19590,Female,54,Masters,5,82,42,13,4,6.0,3,91,Semi-Urban,HR Executive,149668,0 +19591,Female,51,Bachelors,17,84,59,62,63,7.0,5,63,Semi-Urban,HR Executive,24704,1 +19592,Male,57,Diploma,11,24,67,13,71,7.0,5,24,Rural,Manager,99537,0 +19593,Male,31,Bachelors,17,48,55,84,60,7.0,4,27,Urban,Manager,65965,0 +19594,Male,23,Diploma,14,53,22,61,48,6.0,4,63,Rural,Manager,83546,0 +19595,Male,23,Bachelors,15,58,24,28,14,4.0,7,13,Rural,Software Engineer,20606,0 +19596,Male,21,Masters,16,68,95,63,13,6.0,1,92,Urban,ML Engineer,127908,1 +19597,Other,26,Bachelors,17,95,35,59,54,0.0,5,21,Semi-Urban,Manager,118533,0 +19598,Male,42,Masters,6,23,71,41,32,9.0,6,1,Rural,HR Executive,31100,0 +19599,Female,31,Bachelors,4,92,26,92,48,0.0,1,74,Rural,ML Engineer,54293,1 +19600,Female,46,Masters,8,34,52,58,16,5.0,0,53,Urban,Manager,73006,0 +19601,Male,43,Bachelors,0,45,97,83,16,6.0,1,0,Urban,HR Executive,52603,0 +19602,Male,58,Masters,3,28,90,86,77,2.0,5,1,Semi-Urban,Manager,105730,0 +19603,Male,26,Masters,6,56,84,51,84,6.0,2,25,Rural,ML Engineer,110076,0 +19604,Female,58,Bachelors,13,71,39,6,88,7.0,6,53,Semi-Urban,HR Executive,39865,0 +19605,Other,51,Bachelors,8,41,61,40,96,8.0,6,81,Urban,HR Executive,33293,0 +19606,Male,42,Diploma,19,14,1,77,92,3.0,1,58,Urban,ML Engineer,131447,0 +19607,Female,23,Masters,16,29,42,57,20,1.0,6,28,Urban,ML Engineer,145640,0 +19608,Male,46,Masters,14,30,72,53,87,1.0,7,21,Urban,Manager,41998,0 +19609,Female,22,Diploma,5,20,35,35,6,3.0,7,80,Semi-Urban,Software Engineer,95314,0 +19610,Male,42,Masters,19,65,26,4,40,2.0,0,30,Urban,Software Engineer,47641,0 +19611,Male,48,Masters,19,40,35,72,11,7.0,0,73,Urban,Software Engineer,22454,0 +19612,Male,35,High School,6,99,60,15,60,4.0,6,4,Urban,HR Executive,40495,0 +19613,Male,26,Diploma,6,3,8,74,58,9.0,0,97,Urban,Manager,59353,0 +19614,Male,52,Diploma,9,57,67,4,12,7.0,5,78,Urban,Data Analyst,87194,0 +19615,Female,41,Diploma,5,39,2,22,30,8.0,3,71,Semi-Urban,ML Engineer,133959,0 +19616,Male,45,Bachelors,11,87,25,83,55,8.0,1,26,Semi-Urban,ML Engineer,104379,0 +19617,Female,41,Masters,2,96,3,16,74,7.0,4,36,Urban,ML Engineer,86876,0 +19618,Male,39,Diploma,11,45,97,11,55,2.0,6,3,Semi-Urban,HR Executive,23347,0 +19619,Female,32,PhD,2,94,86,33,22,5.0,6,50,Urban,Data Analyst,106357,1 +19620,Female,30,PhD,9,79,56,65,5,1.0,1,3,Urban,Manager,77969,0 +19621,Female,58,Masters,3,45,92,40,3,6.0,5,89,Urban,ML Engineer,149734,1 +19622,Male,45,Masters,2,66,61,77,85,1.0,5,96,Semi-Urban,Data Analyst,135117,1 +19623,Male,36,Masters,14,40,18,61,63,8.0,0,23,Urban,ML Engineer,60314,0 +19624,Female,59,PhD,7,28,54,87,13,6.0,7,25,Semi-Urban,Data Analyst,142188,0 +19625,Male,48,Bachelors,3,76,8,57,31,4.0,3,63,Semi-Urban,ML Engineer,103647,0 +19626,Male,42,Diploma,1,45,87,55,14,5.0,6,74,Semi-Urban,Software Engineer,89031,1 +19627,Male,22,Bachelors,18,86,57,4,49,5.0,1,43,Rural,HR Executive,92829,0 +19628,Female,33,High School,9,27,60,18,43,3.0,7,86,Rural,ML Engineer,119994,0 +19629,Female,53,Bachelors,3,9,8,37,72,8.0,0,59,Urban,Software Engineer,122173,0 +19630,Female,22,Bachelors,7,29,95,88,63,5.0,1,60,Urban,HR Executive,84643,1 +19631,Male,30,PhD,3,58,29,69,57,0.0,7,78,Urban,Data Analyst,46405,0 +19632,Male,56,Masters,1,96,58,6,17,7.0,2,67,Rural,Data Analyst,118131,0 +19633,Female,29,Bachelors,2,82,69,59,84,9.0,4,29,Rural,ML Engineer,142448,0 +19634,Male,40,High School,13,20,98,55,85,9.0,7,80,Urban,Software Engineer,97148,1 +19635,Male,44,Masters,13,15,52,86,62,1.0,7,82,Urban,HR Executive,41620,1 +19636,Male,59,High School,11,83,62,59,41,0.0,5,58,Urban,Software Engineer,127332,1 +19637,Male,31,High School,9,47,27,60,8,1.0,5,3,Semi-Urban,Manager,20582,0 +19638,Male,30,Bachelors,12,16,75,29,28,1.0,5,48,Urban,Software Engineer,72566,0 +19639,Male,44,Bachelors,7,41,63,58,4,4.0,4,13,Urban,Software Engineer,49266,0 +19640,Male,35,Masters,13,25,45,95,33,7.0,7,1,Urban,Manager,47806,0 +19641,Male,43,Diploma,6,29,9,75,50,1.0,3,69,Rural,Manager,30887,0 +19642,Female,25,High School,0,50,22,57,23,4.0,2,89,Urban,Software Engineer,114547,0 +19643,Male,35,Diploma,8,44,51,7,9,0.0,1,12,Urban,Manager,124238,0 +19644,Male,21,Bachelors,5,84,83,2,3,5.0,4,14,Urban,Software Engineer,76614,0 +19645,Female,22,Bachelors,13,53,76,71,84,8.0,0,35,Urban,ML Engineer,25802,0 +19646,Other,57,Bachelors,5,52,27,51,22,0.0,2,9,Urban,Software Engineer,45961,0 +19647,Male,44,High School,3,84,91,14,94,1.0,4,95,Semi-Urban,ML Engineer,43986,1 +19648,Female,32,Bachelors,0,89,89,44,99,6.0,2,28,Urban,Software Engineer,22432,1 +19649,Male,36,Bachelors,9,35,32,85,9,2.0,6,60,Rural,HR Executive,56050,0 +19650,Male,56,Bachelors,14,22,63,42,36,4.0,3,75,Rural,ML Engineer,73539,0 +19651,Male,31,Diploma,5,41,33,94,26,4.0,7,41,Semi-Urban,Data Analyst,25520,0 +19652,Male,34,Masters,12,18,69,29,61,7.0,0,36,Semi-Urban,Manager,66978,0 +19653,Female,49,Masters,19,15,10,24,62,2.0,4,91,Semi-Urban,Manager,46552,0 +19654,Male,56,Masters,9,53,96,57,31,0.0,5,50,Semi-Urban,ML Engineer,60113,1 +19655,Male,22,Masters,19,14,4,97,0,9.0,4,9,Urban,HR Executive,38374,0 +19656,Female,55,Bachelors,7,74,47,93,62,6.0,4,83,Semi-Urban,ML Engineer,73112,1 +19657,Male,52,Masters,2,65,1,64,75,1.0,4,79,Urban,ML Engineer,76972,0 +19658,Female,44,PhD,16,67,71,54,96,1.0,7,98,Urban,Software Engineer,55938,1 +19659,Female,47,Diploma,5,7,60,39,88,0.0,2,7,Urban,Software Engineer,118471,0 +19660,Male,42,High School,1,33,35,43,90,6.0,0,39,Rural,Manager,60369,0 +19661,Other,46,Bachelors,18,91,79,81,56,1.0,6,72,Urban,Data Analyst,110642,1 +19662,Male,56,High School,1,92,39,69,6,7.0,2,57,Urban,HR Executive,145043,1 +19663,Male,34,Diploma,2,1,49,15,34,5.0,1,11,Urban,Software Engineer,42518,0 +19664,Male,39,High School,9,62,47,9,87,5.0,1,18,Urban,ML Engineer,37283,0 +19665,Female,21,Masters,17,8,93,38,32,8.0,2,28,Urban,HR Executive,83897,0 +19666,Female,54,High School,12,12,63,0,30,5.0,0,50,Rural,Manager,28346,0 +19667,Male,21,Bachelors,13,86,59,34,55,8.0,2,29,Urban,Manager,38952,0 +19668,Male,25,Bachelors,2,27,47,10,94,0.0,6,32,Urban,Data Analyst,114807,0 +19669,Male,34,Bachelors,15,15,78,78,33,5.0,2,23,Urban,HR Executive,40353,0 +19670,Female,47,Bachelors,7,27,74,97,21,3.0,0,97,Semi-Urban,HR Executive,128349,1 +19671,Female,22,Bachelors,11,3,76,95,76,4.0,0,25,Semi-Urban,HR Executive,66331,0 +19672,Female,42,Diploma,13,25,61,75,55,8.0,7,44,Rural,HR Executive,129445,0 +19673,Female,50,,9,39,32,16,26,0.0,2,41,Rural,ML Engineer,58834,0 +19674,Male,31,Bachelors,4,64,41,41,79,0.0,7,20,Urban,Manager,147882,0 +19675,Male,35,Diploma,4,56,21,36,65,1.0,7,99,Rural,Manager,140993,0 +19676,Male,57,PhD,7,11,77,41,62,0.0,4,61,Urban,Software Engineer,72763,0 +19677,Female,37,Diploma,12,91,31,57,7,4.0,4,76,Urban,HR Executive,22850,1 +19678,Male,59,Bachelors,16,89,98,93,21,2.0,1,63,Semi-Urban,Software Engineer,20919,1 +19679,Male,56,Masters,7,73,26,95,27,5.0,4,54,Urban,Manager,127954,1 +19680,Other,21,Bachelors,11,50,22,50,74,8.0,6,38,Urban,HR Executive,96541,0 +19681,Female,36,High School,12,38,75,28,82,5.0,5,50,Semi-Urban,Software Engineer,78306,0 +19682,Male,21,Bachelors,0,26,50,70,44,3.0,6,93,Urban,Manager,34121,1 +19683,Female,39,Bachelors,19,4,33,12,35,9.0,7,40,Semi-Urban,Manager,51451,0 +19684,Female,29,Diploma,16,17,53,31,29,1.0,1,72,Urban,HR Executive,63460,0 +19685,Male,55,High School,15,91,69,83,57,6.0,2,90,Urban,ML Engineer,76171,1 +19686,Male,39,Diploma,17,55,11,98,64,0.0,4,59,Rural,ML Engineer,27804,0 +19687,Male,54,High School,8,29,18,11,61,1.0,2,62,Rural,Manager,138309,0 +19688,Male,29,Masters,0,96,16,67,70,1.0,6,56,Rural,ML Engineer,97094,1 +19689,Female,54,High School,17,80,12,61,78,0.0,3,4,Rural,ML Engineer,116689,0 +19690,Male,33,Diploma,1,59,81,93,22,1.0,3,52,Urban,Data Analyst,123114,1 +19691,Male,34,High School,2,26,95,83,3,0.0,4,27,Rural,HR Executive,32750,0 +19692,Male,53,Bachelors,3,28,69,95,18,7.0,2,35,Urban,Software Engineer,125444,0 +19693,Male,44,Diploma,9,32,3,28,71,4.0,0,58,Urban,Manager,63668,0 +19694,Male,55,Masters,18,0,11,80,25,5.0,4,10,Semi-Urban,Manager,122687,0 +19695,Female,35,High School,12,81,4,7,59,5.0,2,31,Urban,Data Analyst,82104,0 +19696,Male,37,High School,0,2,10,86,55,9.0,5,18,Rural,Manager,63538,0 +19697,Female,41,Masters,13,2,22,51,35,8.0,5,17,Urban,Data Analyst,90339,0 +19698,Female,23,Diploma,19,62,22,75,96,1.0,7,22,Rural,Software Engineer,46958,0 +19699,Male,21,Masters,9,3,17,20,5,3.0,6,41,Urban,Software Engineer,36527,0 +19700,Female,34,Masters,6,92,92,25,5,8.0,1,31,Semi-Urban,Manager,120748,0 +19701,Female,49,High School,5,99,37,69,97,4.0,7,21,Urban,Software Engineer,149838,0 +19702,Male,27,Masters,11,33,68,99,71,0.0,5,45,Urban,ML Engineer,59542,1 +19703,Male,37,High School,8,44,42,51,89,7.0,1,14,Urban,ML Engineer,114622,0 +19704,Female,45,High School,9,37,80,71,94,0.0,6,86,Urban,ML Engineer,38208,1 +19705,Other,47,Masters,13,30,55,2,87,5.0,6,36,Urban,ML Engineer,28682,0 +19706,Male,31,Bachelors,14,69,69,52,84,4.0,0,22,Semi-Urban,Software Engineer,125933,0 +19707,Male,55,Bachelors,2,40,56,98,36,3.0,4,86,Urban,ML Engineer,90502,1 +19708,Male,31,Bachelors,1,25,77,1,29,9.0,7,9,Urban,Software Engineer,122311,0 +19709,Male,38,Masters,15,44,7,17,78,1.0,1,67,Urban,Manager,123212,0 +19710,Male,40,Diploma,5,24,65,92,70,0.0,2,41,Urban,Data Analyst,79446,0 +19711,Male,26,Bachelors,11,2,10,13,19,3.0,7,73,Urban,Data Analyst,131147,0 +19712,Male,36,High School,14,37,82,40,58,6.0,3,76,Urban,HR Executive,38633,1 +19713,Male,22,High School,17,49,31,35,48,9.0,4,22,Urban,Data Analyst,64928,0 +19714,Male,45,PhD,9,10,11,27,76,7.0,2,62,Urban,Software Engineer,116987,0 +19715,Male,21,Diploma,5,89,31,94,5,5.0,0,48,Urban,Data Analyst,121733,1 +19716,Male,22,PhD,8,91,73,76,17,5.0,7,33,Semi-Urban,ML Engineer,75976,1 +19717,Male,27,Bachelors,5,20,35,45,60,6.0,6,39,Urban,HR Executive,21639,0 +19718,Female,34,Diploma,19,62,67,94,4,9.0,6,67,Urban,Manager,28981,1 +19719,Female,38,PhD,5,58,95,97,81,8.0,4,76,Urban,ML Engineer,31700,1 +19720,Male,53,Diploma,3,61,26,35,50,5.0,0,97,Urban,ML Engineer,126283,0 +19721,Male,49,Masters,3,78,81,22,28,5.0,4,32,Urban,Data Analyst,99064,0 +19722,Male,59,Masters,1,43,76,1,87,6.0,0,99,Urban,Data Analyst,142065,0 +19723,Male,21,Diploma,1,48,50,9,57,2.0,1,17,Urban,Software Engineer,120004,0 +19724,Male,51,Masters,8,67,58,30,87,0.0,4,56,Semi-Urban,Manager,80995,0 +19725,Male,58,Diploma,2,11,71,38,91,3.0,0,74,Urban,HR Executive,98463,0 +19726,Female,47,PhD,12,77,69,13,27,9.0,5,9,Urban,Data Analyst,137482,0 +19727,Male,47,Bachelors,11,89,73,40,77,8.0,0,38,Urban,Manager,42516,1 +19728,Male,22,Diploma,18,4,82,98,40,3.0,5,39,Urban,ML Engineer,109423,0 +19729,Female,40,Bachelors,18,64,51,61,41,8.0,5,85,Urban,Manager,79670,1 +19730,Female,37,High School,2,90,19,25,57,5.0,5,6,Urban,Data Analyst,142498,0 +19731,Male,59,Bachelors,12,51,70,60,95,6.0,4,3,Semi-Urban,ML Engineer,146701,0 +19732,Male,59,Bachelors,14,28,99,82,25,6.0,0,37,Urban,Software Engineer,144061,1 +19733,Male,28,High School,12,56,45,85,49,7.0,2,13,Rural,Data Analyst,26284,0 +19734,Male,23,High School,14,63,68,50,5,2.0,6,70,Urban,ML Engineer,112827,1 +19735,Male,21,Bachelors,6,15,43,84,55,7.0,2,46,Urban,ML Engineer,38780,0 +19736,Male,49,Masters,9,39,99,79,65,5.0,2,3,Urban,Software Engineer,39917,0 +19737,Male,51,Bachelors,11,54,60,68,23,7.0,7,25,Semi-Urban,Data Analyst,41653,0 +19738,Female,27,Diploma,0,31,32,86,7,6.0,3,41,Urban,HR Executive,146831,0 +19739,Female,33,Diploma,7,35,71,90,53,3.0,0,24,Semi-Urban,Data Analyst,145128,0 +19740,Male,41,Masters,0,4,78,35,67,4.0,1,15,Rural,Manager,131170,0 +19741,Male,51,Diploma,12,51,52,55,70,1.0,1,47,Semi-Urban,ML Engineer,99808,0 +19742,Male,46,Diploma,2,94,10,26,56,9.0,1,30,Semi-Urban,Software Engineer,69671,0 +19743,Male,50,Diploma,2,16,84,58,7,9.0,2,87,Urban,ML Engineer,98246,1 +19744,Male,53,PhD,11,88,17,71,84,9.0,6,17,Urban,ML Engineer,70686,0 +19745,Female,54,Bachelors,15,18,17,80,10,2.0,1,79,Urban,Manager,50259,0 +19746,Female,22,Bachelors,8,87,93,79,76,1.0,4,91,Semi-Urban,Software Engineer,35185,1 +19747,Female,25,Masters,19,42,7,6,6,4.0,4,81,Urban,Manager,145699,0 +19748,Female,26,Masters,4,34,98,70,5,7.0,4,99,Semi-Urban,Software Engineer,107789,1 +19749,Other,48,Diploma,15,90,78,80,66,0.0,1,22,Semi-Urban,HR Executive,103752,1 +19750,Female,39,Diploma,0,93,26,14,39,5.0,7,40,Urban,Software Engineer,72955,0 +19751,Other,43,Bachelors,0,40,52,91,78,9.0,4,16,Urban,Data Analyst,52342,0 +19752,Male,53,Bachelors,1,16,99,94,79,2.0,6,33,Semi-Urban,HR Executive,71493,1 +19753,Male,48,Bachelors,5,84,17,27,20,5.0,2,64,Urban,Manager,79262,0 +19754,Male,34,Bachelors,17,13,80,45,76,2.0,2,54,Urban,Software Engineer,131771,0 +19755,Other,26,Masters,10,10,4,86,16,1.0,1,73,Urban,ML Engineer,107005,0 +19756,Male,39,Masters,15,63,67,54,73,7.0,3,10,Urban,ML Engineer,97833,0 +19757,Male,22,Masters,15,12,2,0,49,2.0,0,8,Semi-Urban,Data Analyst,56677,0 +19758,Male,27,High School,16,14,49,14,99,7.0,7,75,Rural,Data Analyst,97206,0 +19759,Female,50,High School,13,23,70,52,96,8.0,2,18,Semi-Urban,HR Executive,92141,0 +19760,Male,54,High School,2,74,50,80,97,2.0,0,15,Semi-Urban,Manager,135296,0 +19761,Female,30,Masters,17,6,56,8,95,2.0,7,32,Rural,ML Engineer,63397,0 +19762,Other,56,Diploma,2,12,65,75,10,1.0,1,48,Semi-Urban,Software Engineer,38335,0 +19763,Female,21,High School,16,9,97,47,12,3.0,4,85,Semi-Urban,ML Engineer,26633,0 +19764,Male,52,Diploma,11,62,5,26,41,0.0,7,20,Urban,Software Engineer,144912,0 +19765,Male,47,Bachelors,18,61,81,50,81,4.0,6,76,Rural,Software Engineer,88552,1 +19766,Male,58,Bachelors,3,42,94,35,78,5.0,3,29,Semi-Urban,ML Engineer,87451,0 +19767,Male,33,Diploma,0,53,86,77,82,2.0,1,91,Rural,Software Engineer,143456,1 +19768,Male,54,High School,3,24,19,38,6,3.0,1,68,Urban,Manager,115635,0 +19769,Female,33,Bachelors,3,79,10,37,3,4.0,0,53,Semi-Urban,Manager,83379,0 +19770,Male,46,Diploma,6,94,62,36,43,1.0,1,94,Urban,Software Engineer,103077,1 +19771,Female,31,Diploma,6,33,77,2,31,4.0,4,99,Urban,Software Engineer,56059,0 +19772,Female,21,Bachelors,16,1,69,91,21,8.0,4,71,Urban,ML Engineer,101326,0 +19773,Male,29,Bachelors,17,82,36,99,74,7.0,6,13,Urban,Data Analyst,92033,0 +19774,Other,44,Diploma,8,2,11,73,52,6.0,7,16,Semi-Urban,Manager,111455,0 +19775,Female,54,Diploma,0,57,56,88,49,3.0,0,48,Urban,ML Engineer,58019,1 +19776,Male,39,Diploma,15,73,66,54,22,8.0,4,2,Semi-Urban,ML Engineer,141766,0 +19777,Male,27,Bachelors,6,26,9,6,56,9.0,7,37,Urban,Software Engineer,88547,0 +19778,Male,43,Bachelors,6,12,48,99,16,4.0,5,49,Urban,Software Engineer,76958,0 +19779,Male,25,Masters,19,18,37,21,68,5.0,2,61,Urban,HR Executive,96344,0 +19780,Female,41,Bachelors,16,58,27,32,80,0.0,2,84,Urban,Manager,70207,0 +19781,Male,55,Masters,12,7,85,29,14,4.0,7,75,Semi-Urban,Software Engineer,122014,0 +19782,Female,37,Bachelors,12,93,6,7,7,5.0,7,13,Semi-Urban,ML Engineer,93840,0 +19783,Male,22,Bachelors,0,93,60,68,92,2.0,5,61,Urban,ML Engineer,53578,1 +19784,Male,48,Bachelors,18,19,49,92,27,3.0,2,54,Rural,HR Executive,96672,0 +19785,Male,25,High School,13,50,31,0,40,4.0,1,15,Rural,Manager,62597,0 +19786,Male,31,Diploma,5,6,67,85,48,4.0,0,28,Semi-Urban,Data Analyst,69015,0 +19787,Male,59,Masters,10,4,90,23,8,2.0,0,74,Urban,HR Executive,50597,0 +19788,Male,28,Masters,14,12,65,79,82,7.0,4,97,Rural,Data Analyst,84956,1 +19789,Female,32,Bachelors,15,77,56,98,75,8.0,4,73,Semi-Urban,Data Analyst,43043,1 +19790,Female,34,Bachelors,14,53,28,41,4,2.0,0,64,Urban,ML Engineer,37995,0 +19791,Male,23,Bachelors,8,21,1,62,26,5.0,1,72,Urban,Software Engineer,113858,0 +19792,Male,35,Diploma,5,55,63,67,50,9.0,2,95,Rural,HR Executive,90919,1 +19793,Male,52,Bachelors,14,91,64,36,38,5.0,7,14,Urban,Manager,143091,0 +19794,Male,39,PhD,7,69,14,97,78,9.0,7,90,Rural,ML Engineer,78946,1 +19795,Female,39,High School,19,13,15,75,51,4.0,1,72,Semi-Urban,Data Analyst,102714,0 +19796,Female,27,Masters,6,26,3,95,28,5.0,1,93,Urban,Data Analyst,40585,0 +19797,Female,32,Masters,19,5,6,63,33,4.0,3,65,Semi-Urban,Software Engineer,73211,0 +19798,Male,27,Masters,16,20,75,51,59,6.0,2,97,Rural,Manager,61109,1 +19799,Female,57,PhD,16,15,43,0,50,0.0,3,36,Urban,Manager,128228,0 +19800,Male,56,Bachelors,14,52,51,95,93,5.0,3,43,Rural,HR Executive,138884,1 +19801,Female,43,Bachelors,19,81,80,54,31,3.0,3,49,Urban,Manager,94517,1 +19802,Male,54,Diploma,4,15,88,87,95,9.0,3,54,Urban,Data Analyst,21076,1 +19803,Male,59,High School,13,84,2,26,10,9.0,7,90,Rural,Software Engineer,56986,0 +19804,Male,22,Masters,5,90,35,27,35,4.0,5,49,Urban,ML Engineer,79922,0 +19805,Male,36,Diploma,14,44,56,64,66,5.0,4,25,Rural,HR Executive,122740,0 +19806,Female,22,Bachelors,13,80,94,53,67,7.0,7,59,Urban,Manager,85216,1 +19807,Female,56,Bachelors,13,52,47,51,17,2.0,0,14,Semi-Urban,HR Executive,149101,0 +19808,Male,37,Masters,0,37,23,20,67,5.0,1,3,Rural,Data Analyst,42273,0 +19809,Female,59,Masters,5,32,88,40,11,2.0,5,13,Urban,Data Analyst,63216,0 +19810,Male,49,Bachelors,4,54,77,10,51,7.0,5,52,Urban,Data Analyst,67943,0 +19811,Male,44,Bachelors,15,86,86,29,43,5.0,7,51,Rural,ML Engineer,92001,1 +19812,Other,47,Bachelors,14,56,63,25,99,8.0,4,97,Urban,HR Executive,122841,1 +19813,Female,46,Diploma,9,76,11,27,25,5.0,5,71,Urban,Manager,138502,0 +19814,Male,27,Masters,6,49,99,71,24,7.0,0,63,Semi-Urban,HR Executive,119377,1 +19815,Male,21,Bachelors,9,1,77,88,22,3.0,2,43,Semi-Urban,ML Engineer,73139,0 +19816,Male,35,Masters,9,78,69,48,35,7.0,1,0,Semi-Urban,Data Analyst,92371,0 +19817,Female,29,High School,8,52,95,53,0,3.0,2,49,Semi-Urban,Manager,128447,1 +19818,Female,58,Bachelors,8,58,35,48,58,9.0,5,0,Urban,Software Engineer,101977,0 +19819,Male,33,Bachelors,5,60,42,62,40,6.0,6,45,Urban,Manager,131488,0 +19820,Female,53,Bachelors,11,98,20,31,63,9.0,5,97,Rural,Data Analyst,59079,1 +19821,Male,50,Diploma,0,20,64,95,0,5.0,6,19,Urban,ML Engineer,149913,0 +19822,Male,37,Masters,11,2,30,87,23,7.0,4,69,Semi-Urban,ML Engineer,56289,0 +19823,Female,38,Bachelors,8,93,57,73,92,4.0,5,88,Rural,ML Engineer,148312,1 +19824,Male,36,Bachelors,1,37,37,83,81,3.0,3,53,Rural,Data Analyst,73996,0 +19825,Male,42,Bachelors,18,62,95,69,44,2.0,0,95,Semi-Urban,HR Executive,28723,1 +19826,Female,31,Bachelors,2,97,43,49,84,5.0,0,1,Urban,Data Analyst,73099,0 +19827,Male,35,PhD,18,37,7,22,82,7.0,3,46,Rural,Software Engineer,37311,0 +19828,Male,47,Masters,16,39,78,8,91,7.0,7,0,Semi-Urban,Data Analyst,67323,0 +19829,Female,28,Masters,0,37,39,59,28,7.0,1,39,Rural,Manager,61766,0 +19830,Female,24,High School,2,46,71,54,86,6.0,4,30,Urban,HR Executive,120277,0 +19831,Female,52,Bachelors,1,21,29,39,5,7.0,3,64,Semi-Urban,Software Engineer,24443,0 +19832,Male,40,High School,6,19,5,96,94,5.0,5,48,Urban,Data Analyst,104406,0 +19833,Male,58,Bachelors,3,76,59,80,79,3.0,2,90,Rural,Software Engineer,61611,1 +19834,Other,50,Bachelors,0,74,63,74,55,1.0,6,1,Urban,Data Analyst,90229,0 +19835,Male,27,Diploma,9,86,79,22,39,1.0,3,53,Urban,Manager,117999,1 +19836,Male,57,Masters,8,64,66,67,34,2.0,6,54,Semi-Urban,ML Engineer,92267,1 +19837,Male,25,Bachelors,9,64,61,15,38,7.0,4,24,Urban,HR Executive,61719,0 +19838,Male,38,Bachelors,3,86,87,15,59,0.0,7,60,Urban,Data Analyst,25687,1 +19839,Male,44,Masters,14,7,34,59,67,3.0,0,33,Rural,Data Analyst,111054,0 +19840,Female,54,Masters,15,53,79,65,69,1.0,6,60,Urban,Manager,53463,1 +19841,Other,21,Diploma,10,57,55,7,57,5.0,1,26,Rural,ML Engineer,97455,0 +19842,Male,43,Diploma,1,8,41,79,83,7.0,4,64,Rural,ML Engineer,122637,0 +19843,Female,48,Masters,2,20,51,69,95,9.0,0,86,Rural,HR Executive,117114,0 +19844,Female,46,Diploma,13,64,1,81,80,8.0,3,7,Urban,HR Executive,132842,0 +19845,Female,24,Diploma,0,38,15,91,25,6.0,7,77,Rural,HR Executive,146713,0 +19846,Male,54,Diploma,13,86,55,97,44,7.0,3,74,Urban,ML Engineer,135850,1 +19847,Male,50,Bachelors,9,61,52,72,75,0.0,0,92,Urban,Data Analyst,56301,1 +19848,Male,36,Bachelors,2,8,64,51,27,6.0,7,4,Semi-Urban,Software Engineer,38768,0 +19849,Male,38,Masters,10,23,10,87,17,1.0,0,65,Semi-Urban,Manager,87838,0 +19850,Male,52,Bachelors,0,5,4,19,69,1.0,7,77,Rural,Software Engineer,141333,0 +19851,Male,57,Diploma,13,39,66,56,52,0.0,6,4,Urban,Data Analyst,45768,0 +19852,Male,33,High School,9,92,41,71,24,1.0,5,62,Urban,Data Analyst,103894,1 +19853,Male,37,PhD,11,14,31,53,47,6.0,0,16,Semi-Urban,Data Analyst,79526,0 +19854,Male,34,PhD,2,92,67,83,84,9.0,3,21,Semi-Urban,Software Engineer,76757,1 +19855,Male,21,Bachelors,4,65,9,20,65,2.0,3,13,Semi-Urban,Software Engineer,40794,0 +19856,Female,59,Bachelors,11,44,15,32,64,1.0,7,97,Semi-Urban,Data Analyst,124033,0 +19857,Male,59,Bachelors,19,68,6,34,84,8.0,3,82,Urban,Software Engineer,136983,0 +19858,Female,39,Bachelors,6,61,10,80,86,9.0,7,81,Rural,Software Engineer,113154,0 +19859,Other,53,Diploma,16,6,48,88,34,3.0,0,33,Semi-Urban,ML Engineer,132410,0 +19860,Female,32,Bachelors,9,97,97,78,88,5.0,3,15,Rural,HR Executive,103526,1 +19861,Female,30,Bachelors,15,24,5,73,44,2.0,2,64,Urban,HR Executive,68326,0 +19862,Female,49,Masters,7,17,77,88,86,7.0,7,95,Semi-Urban,Data Analyst,76736,1 +19863,Male,47,Bachelors,14,67,30,2,64,5.0,1,62,Urban,Manager,91388,0 +19864,Other,53,Bachelors,6,40,95,42,48,9.0,7,4,Rural,Software Engineer,37467,0 +19865,Female,36,High School,16,18,40,64,29,9.0,0,38,Urban,HR Executive,148228,0 +19866,Female,40,High School,13,16,5,52,10,3.0,5,46,Urban,Manager,108213,0 +19867,Male,34,Masters,1,47,18,39,64,6.0,4,12,Rural,Data Analyst,67540,0 +19868,Male,34,Bachelors,19,53,44,63,64,8.0,0,75,Urban,Software Engineer,57047,1 +19869,Female,34,High School,12,48,55,88,94,0.0,1,36,Urban,Manager,99195,0 +19870,Female,32,Masters,9,90,57,96,47,2.0,5,45,Rural,Data Analyst,118274,1 +19871,Female,40,Masters,18,43,68,73,18,7.0,3,73,Rural,Software Engineer,90713,1 +19872,Male,26,Diploma,2,48,80,71,69,7.0,5,90,Urban,Data Analyst,97488,1 +19873,Male,50,Bachelors,12,94,4,50,79,9.0,6,36,Urban,Data Analyst,38126,0 +19874,Male,57,Diploma,13,83,60,42,16,0.0,5,75,Urban,Data Analyst,109604,1 +19875,Male,37,Bachelors,16,36,7,62,51,7.0,1,26,Semi-Urban,HR Executive,135890,0 +19876,Male,51,Bachelors,5,77,47,99,74,7.0,6,13,Urban,Data Analyst,36601,1 +19877,Male,41,Diploma,13,2,63,57,78,2.0,5,32,Rural,ML Engineer,34921,0 +19878,Male,26,Bachelors,16,55,33,43,51,4.0,7,74,Rural,ML Engineer,145913,0 +19879,Male,31,Bachelors,2,43,92,88,36,2.0,6,0,Urban,ML Engineer,132538,0 +19880,Male,52,Bachelors,9,0,40,0,52,6.0,6,19,Urban,Manager,107901,0 +19881,Female,46,Masters,11,54,80,87,89,7.0,4,27,Urban,ML Engineer,23342,1 +19882,Female,24,Diploma,12,8,46,49,71,6.0,6,88,Urban,HR Executive,123233,0 +19883,Female,29,Masters,6,28,90,2,22,4.0,0,29,Urban,Data Analyst,40876,0 +19884,Male,22,Diploma,19,42,80,26,53,4.0,3,5,Urban,HR Executive,108313,0 +19885,Female,46,Bachelors,5,87,33,96,56,5.0,7,19,Urban,Manager,111633,0 +19886,Male,48,Masters,19,34,45,56,40,6.0,2,65,Semi-Urban,Data Analyst,51705,0 +19887,Other,47,Diploma,10,39,40,37,90,1.0,1,73,Rural,ML Engineer,37493,0 +19888,Female,29,Bachelors,15,16,98,62,25,2.0,2,94,Urban,HR Executive,36664,1 +19889,Male,54,Masters,12,18,19,73,58,8.0,6,57,Semi-Urban,Data Analyst,132690,0 +19890,Female,47,High School,15,63,41,23,98,2.0,5,76,Urban,Software Engineer,23774,0 +19891,Male,25,Bachelors,1,80,6,75,20,6.0,7,48,Urban,Manager,115460,0 +19892,Male,57,High School,1,11,7,42,26,5.0,4,96,Urban,Data Analyst,99766,0 +19893,Female,29,High School,15,63,84,50,10,2.0,2,48,Semi-Urban,Data Analyst,29508,1 +19894,Male,26,Bachelors,16,73,76,81,74,4.0,7,32,Urban,Data Analyst,84911,1 +19895,Male,48,Bachelors,19,81,78,43,79,8.0,7,12,Urban,ML Engineer,141220,0 +19896,Female,27,Masters,7,86,31,91,94,9.0,0,0,Semi-Urban,Software Engineer,69039,0 +19897,Male,39,Diploma,3,16,82,33,16,8.0,6,17,Urban,ML Engineer,105652,0 +19898,Female,48,Diploma,10,60,24,95,15,5.0,1,41,Semi-Urban,Software Engineer,63479,0 +19899,Female,47,High School,3,40,29,33,17,9.0,0,13,Semi-Urban,Manager,113073,0 +19900,Male,36,Masters,6,11,36,31,28,8.0,5,86,Semi-Urban,Software Engineer,66404,0 +19901,Male,47,Masters,7,6,7,24,71,7.0,2,8,Semi-Urban,Software Engineer,83655,0 +19902,Male,38,Diploma,14,99,85,18,67,4.0,6,94,Urban,Data Analyst,102773,1 +19903,Male,21,Masters,18,23,82,42,65,6.0,1,65,Semi-Urban,Software Engineer,80772,0 +19904,Male,29,Bachelors,6,77,12,23,35,4.0,2,69,Urban,HR Executive,119389,0 +19905,Male,33,PhD,1,92,42,79,85,2.0,2,88,Semi-Urban,Software Engineer,78542,1 +19906,Male,38,Masters,2,63,98,40,32,4.0,0,29,Urban,Data Analyst,32290,0 +19907,Male,36,High School,17,27,33,12,70,0.0,0,85,Rural,Manager,41256,0 +19908,Female,40,PhD,4,9,73,62,22,0.0,1,91,Semi-Urban,Data Analyst,78468,0 +19909,Female,52,Diploma,15,8,55,41,5,9.0,6,19,Urban,Software Engineer,46957,0 +19910,Female,54,Bachelors,9,7,19,21,45,2.0,4,58,Urban,Manager,142557,0 +19911,Male,54,Masters,16,9,92,29,50,6.0,3,89,Semi-Urban,Software Engineer,41743,0 +19912,Male,21,Bachelors,3,99,64,65,26,5.0,2,28,Rural,Software Engineer,36505,1 +19913,Female,55,Bachelors,13,55,91,12,66,3.0,5,10,Rural,Data Analyst,110708,0 +19914,Male,21,Bachelors,6,72,57,24,38,7.0,3,94,Urban,Manager,99807,1 +19915,Male,33,Diploma,7,39,90,8,22,0.0,2,17,Urban,ML Engineer,34721,0 +19916,Female,48,Bachelors,6,14,71,79,58,2.0,0,60,Urban,HR Executive,39899,0 +19917,Male,28,Bachelors,16,56,36,50,33,0.0,7,10,Urban,Data Analyst,91861,0 +19918,Male,23,Bachelors,18,70,9,9,62,2.0,1,89,Urban,ML Engineer,97829,0 +19919,Female,23,Bachelors,6,99,38,35,50,5.0,0,81,Semi-Urban,HR Executive,98955,1 +19920,Female,22,Diploma,11,64,6,26,8,3.0,6,57,Semi-Urban,Data Analyst,34964,0 +19921,Male,53,High School,19,32,28,69,49,8.0,0,2,Urban,Data Analyst,92054,0 +19922,Male,54,High School,19,76,68,3,20,2.0,0,13,Urban,ML Engineer,45130,0 +19923,Male,47,Bachelors,2,10,41,25,85,3.0,3,5,Urban,HR Executive,119770,0 +19924,Female,39,Diploma,6,96,27,49,84,5.0,3,85,Rural,ML Engineer,139107,1 +19925,Male,27,High School,9,64,77,39,69,4.0,7,98,Urban,HR Executive,63949,1 +19926,Male,54,Diploma,17,42,19,8,45,9.0,0,97,Rural,Data Analyst,89797,0 +19927,Other,53,Diploma,8,41,97,56,1,0.0,2,99,Rural,ML Engineer,57899,1 +19928,Male,54,Bachelors,1,64,5,40,71,5.0,6,77,Rural,Software Engineer,61371,0 +19929,Female,54,Bachelors,14,31,7,7,65,1.0,3,18,Rural,Software Engineer,98339,0 +19930,Other,37,Bachelors,7,20,1,95,22,5.0,7,75,Semi-Urban,HR Executive,96138,0 +19931,Male,27,Diploma,15,46,71,30,58,7.0,1,74,Urban,Data Analyst,42379,0 +19932,Female,58,Masters,2,73,11,67,47,6.0,7,98,Rural,Data Analyst,46622,1 +19933,Male,50,Bachelors,4,44,70,91,45,8.0,2,75,Urban,ML Engineer,87243,1 +19934,Female,57,Bachelors,5,78,33,21,43,3.0,4,11,Semi-Urban,Data Analyst,93419,0 +19935,Female,48,Bachelors,19,21,20,61,83,4.0,3,49,Semi-Urban,Manager,149808,0 +19936,Male,44,High School,14,14,59,7,34,8.0,6,39,Urban,ML Engineer,57782,0 +19937,Female,38,Masters,12,72,94,97,52,0.0,0,59,Urban,HR Executive,122899,1 +19938,Female,41,Masters,18,79,49,13,35,8.0,6,48,Urban,HR Executive,59442,0 +19939,Male,25,Bachelors,3,69,84,15,69,9.0,1,93,Semi-Urban,ML Engineer,29384,1 +19940,Male,56,Bachelors,8,60,88,47,49,0.0,5,15,Urban,ML Engineer,57170,0 +19941,Male,36,Diploma,17,67,51,35,43,7.0,7,0,Urban,ML Engineer,140367,0 +19942,Male,33,Diploma,10,59,68,14,14,2.0,5,34,Urban,Software Engineer,134403,0 +19943,Other,53,Masters,2,40,68,79,15,7.0,1,18,Semi-Urban,ML Engineer,137920,0 +19944,Female,33,Bachelors,18,70,3,74,91,9.0,5,87,Urban,Software Engineer,98267,0 +19945,Male,25,High School,5,49,79,23,24,2.0,4,75,Semi-Urban,HR Executive,94750,0 +19946,Male,48,Masters,18,93,3,41,36,1.0,6,49,Urban,HR Executive,85319,0 +19947,Male,29,Masters,8,70,12,42,18,5.0,5,28,Urban,Software Engineer,54414,0 +19948,Male,47,Bachelors,16,32,19,68,85,3.0,1,50,Urban,Data Analyst,33165,0 +19949,Male,38,Diploma,18,2,11,53,84,7.0,7,96,Urban,Manager,77257,0 +19950,Male,35,Masters,15,10,18,55,44,9.0,4,88,Urban,ML Engineer,84561,0 +19951,Male,40,Bachelors,1,65,47,74,68,4.0,3,37,Semi-Urban,Data Analyst,50022,0 +19952,Other,22,Bachelors,15,68,79,87,56,6.0,4,16,Urban,ML Engineer,70465,1 +19953,Female,30,Masters,12,53,54,99,95,2.0,5,73,Urban,Software Engineer,57301,1 +19954,Female,34,Diploma,16,82,22,58,98,8.0,5,75,Semi-Urban,Manager,119429,0 +19955,Male,36,High School,3,21,45,85,87,5.0,4,37,Rural,Software Engineer,40052,0 +19956,Other,40,PhD,18,56,46,18,33,3.0,0,88,Semi-Urban,Manager,133795,0 +19957,Female,28,Diploma,17,18,98,51,82,2.0,2,87,Urban,Software Engineer,74241,1 +19958,Female,37,Bachelors,8,99,27,83,5,7.0,2,87,Urban,Data Analyst,145250,1 +19959,Male,49,Diploma,16,40,22,81,9,2.0,2,49,Urban,HR Executive,96356,0 +19960,Male,46,Diploma,11,16,4,27,82,6.0,5,80,Semi-Urban,Software Engineer,94245,0 +19961,Male,53,Diploma,14,68,37,99,49,3.0,3,80,Semi-Urban,Manager,24540,1 +19962,Male,23,Diploma,19,14,70,28,61,0.0,3,53,Rural,HR Executive,93597,0 +19963,Female,27,Bachelors,15,52,37,11,32,5.0,2,45,Rural,ML Engineer,122804,0 +19964,Female,32,Masters,11,84,11,17,83,6.0,1,17,Semi-Urban,Software Engineer,146826,0 +19965,Male,40,Masters,15,13,34,29,40,9.0,7,56,Urban,Manager,80761,0 +19966,Male,30,High School,13,72,44,5,88,8.0,6,63,Rural,Software Engineer,55888,0 +19967,Female,59,High School,12,7,99,97,31,9.0,3,13,Urban,Manager,70415,0 +19968,Male,48,Bachelors,8,57,61,98,52,4.0,3,97,Semi-Urban,HR Executive,75884,1 +19969,Female,37,Masters,2,74,36,5,28,4.0,2,52,Rural,ML Engineer,49579,0 +19970,Female,58,Bachelors,2,6,26,36,65,4.0,7,72,Semi-Urban,Manager,40669,0 +19971,Male,35,Diploma,3,25,22,11,85,6.0,3,22,Rural,Manager,30081,0 +19972,Female,28,Diploma,11,69,13,94,53,8.0,7,47,Urban,Data Analyst,90787,0 +19973,Male,39,Bachelors,3,32,11,68,1,6.0,2,83,Urban,Manager,149081,0 +19974,Female,40,PhD,11,13,92,21,79,8.0,5,16,Rural,Data Analyst,75127,0 +19975,Female,39,High School,2,10,73,93,50,3.0,7,31,Semi-Urban,Data Analyst,87928,0 +19976,Female,40,Bachelors,15,49,60,79,29,6.0,3,70,Rural,Software Engineer,26664,1 +19977,Male,36,Masters,8,15,80,49,42,3.0,0,93,Semi-Urban,ML Engineer,62628,1 +19978,Male,58,Bachelors,1,4,61,51,63,0.0,4,41,Rural,Software Engineer,93017,0 +19979,Male,29,Masters,0,27,55,40,24,2.0,5,14,Urban,Data Analyst,21179,0 +19980,Male,42,Bachelors,13,76,55,32,94,4.0,1,17,Urban,Software Engineer,106267,0 +19981,Female,35,Diploma,13,29,85,71,35,2.0,1,23,Urban,ML Engineer,104418,0 +19982,Male,48,High School,10,46,56,46,77,1.0,3,30,Semi-Urban,ML Engineer,130547,0 +19983,Female,24,Diploma,9,83,12,51,48,2.0,4,73,Semi-Urban,ML Engineer,60668,0 +19984,Male,34,Diploma,7,92,13,16,86,7.0,7,92,Urban,Software Engineer,80281,0 +19985,Male,45,PhD,5,42,65,42,32,3.0,3,21,Urban,ML Engineer,54423,0 +19986,Female,58,Bachelors,3,5,57,27,0,8.0,0,7,Rural,Manager,116039,0 +19987,Male,57,PhD,15,65,35,7,79,7.0,1,0,Semi-Urban,ML Engineer,147667,0 +19988,Female,29,Bachelors,6,11,85,48,86,8.0,3,33,Urban,Manager,91293,0 +19989,Male,38,Masters,5,16,81,63,41,3.0,7,50,Rural,Manager,114523,0 +19990,Female,48,Diploma,13,50,66,41,69,8.0,2,4,Rural,Software Engineer,34229,0 +19991,Male,49,Masters,13,49,84,11,35,2.0,5,43,Urban,Data Analyst,128747,0 +19992,Female,57,PhD,7,80,89,67,8,7.0,2,35,Urban,Software Engineer,124616,1 +19993,Male,50,Masters,19,64,91,62,40,0.0,7,50,Urban,Data Analyst,67153,1 +19994,Male,50,Bachelors,5,55,48,41,39,3.0,6,56,Urban,Manager,50941,0 +19995,Female,48,Diploma,15,18,79,26,93,3.0,3,16,Urban,ML Engineer,69083,0 +19996,Female,58,Bachelors,1,99,79,87,83,2.0,1,94,Urban,HR Executive,23610,1 +19997,Male,38,Masters,3,17,19,56,26,2.0,6,43,Urban,ML Engineer,114971,0 +19998,Male,51,High School,19,62,14,86,93,8.0,3,89,Semi-Urban,Data Analyst,97256,1 +19999,Male,53,Masters,11,2,12,78,95,0.0,0,19,Rural,Manager,120108,0 +20000,Male,25,Bachelors,14,58,32,4,60,4.0,4,97,Urban,HR Executive,109211,0 +20001,Female,38,Diploma,19,86,9,91,5,2.0,2,77,Rural,Manager,131800,1 +20002,Male,54,PhD,12,54,34,65,3,3.0,2,72,Semi-Urban,Data Analyst,44154,0 +20003,Male,27,Diploma,10,23,44,85,87,5.0,7,8,Semi-Urban,Manager,46055,0 +20004,Female,42,High School,7,48,76,69,96,4.0,6,64,Urban,Data Analyst,133118,1 +20005,Male,26,Bachelors,3,0,81,43,4,9.0,5,92,Urban,Data Analyst,121667,0 +20006,Female,56,Bachelors,19,26,70,27,65,5.0,6,51,Semi-Urban,ML Engineer,23796,0 +20007,Other,32,High School,4,17,83,46,2,6.0,1,54,Semi-Urban,ML Engineer,112125,0 +20008,Male,51,High School,8,20,52,33,94,2.0,6,24,Urban,ML Engineer,114958,0 +20009,Female,56,Bachelors,8,43,43,66,28,8.0,7,67,Urban,Software Engineer,79854,0 +20010,Male,49,Bachelors,19,93,0,82,50,2.0,3,37,Urban,ML Engineer,58027,0 +20011,Male,37,Diploma,1,33,95,54,97,0.0,0,83,Semi-Urban,HR Executive,120946,1 +20012,Male,37,Masters,13,59,71,44,16,0.0,2,54,Urban,Manager,131019,0 +20013,Male,28,Masters,13,13,7,79,66,2.0,5,34,Urban,Software Engineer,87037,0 +20014,Male,57,Masters,14,42,40,4,39,0.0,7,14,Urban,Data Analyst,39695,0 +20015,Male,30,PhD,16,2,78,71,8,4.0,4,70,Semi-Urban,ML Engineer,129588,0 +20016,Female,58,Masters,14,14,84,74,67,0.0,4,17,Urban,Software Engineer,149088,0 +20017,Female,58,Diploma,2,35,94,58,25,2.0,1,49,Urban,Manager,94419,0 +20018,Other,34,High School,19,19,15,43,60,8.0,3,34,Semi-Urban,Manager,146281,0 +20019,Male,55,Diploma,18,12,53,40,20,7.0,1,85,Urban,Data Analyst,57238,0 +20020,Male,40,Bachelors,9,35,91,89,83,3.0,0,47,Urban,ML Engineer,142745,1 +20021,Male,28,Bachelors,1,6,69,41,65,8.0,4,73,Urban,HR Executive,91658,0 +20022,Male,22,Masters,1,18,8,73,79,5.0,6,26,Urban,Data Analyst,101851,0 +20023,Male,35,Diploma,6,67,21,80,19,5.0,0,88,Urban,Software Engineer,79502,1 +20024,Female,26,High School,9,95,94,60,34,0.0,3,24,Urban,ML Engineer,116776,1 +20025,Male,36,Bachelors,19,1,70,40,46,7.0,4,29,Semi-Urban,Data Analyst,81718,0 +20026,Male,35,High School,4,82,50,90,29,1.0,7,3,Urban,Data Analyst,94241,0 +20027,Male,32,Diploma,14,47,37,48,23,4.0,6,97,Urban,Data Analyst,75072,0 +20028,Male,49,Bachelors,0,19,5,83,0,3.0,3,46,Urban,ML Engineer,97569,0 +20029,Male,37,Bachelors,4,31,49,7,59,1.0,2,49,Urban,ML Engineer,28138,0 +20030,Male,43,Bachelors,19,87,45,75,42,3.0,0,14,Urban,Manager,117740,0 +20031,Female,30,Bachelors,8,38,90,87,90,9.0,0,21,Urban,HR Executive,46007,0 +20032,Male,58,Bachelors,3,44,77,16,65,5.0,2,2,Urban,Manager,45086,0 +20033,Female,42,Bachelors,4,19,72,97,84,8.0,4,4,Urban,Data Analyst,134380,0 +20034,Male,35,Masters,5,26,69,27,39,8.0,0,54,Urban,Data Analyst,109816,0 +20035,Male,51,Bachelors,14,56,95,73,39,4.0,6,95,Semi-Urban,Software Engineer,102032,1 +20036,Female,23,Bachelors,0,68,77,27,60,6.0,5,90,Semi-Urban,Data Analyst,54692,1 +20037,Male,22,Masters,8,22,37,96,53,6.0,7,52,Urban,Software Engineer,33770,0 +20038,Male,29,High School,15,34,36,37,43,4.0,4,35,Urban,Data Analyst,139496,0 +20039,Female,45,Bachelors,10,55,11,88,18,6.0,5,85,Urban,HR Executive,42950,0 +20040,Male,52,Bachelors,2,84,65,2,67,1.0,0,46,Semi-Urban,ML Engineer,112448,0 +20041,Male,45,Masters,3,47,36,70,5,4.0,6,9,Semi-Urban,Data Analyst,54116,0 +20042,Female,23,Diploma,15,41,38,69,50,8.0,6,80,Urban,Data Analyst,78898,0 +20043,Female,24,Masters,16,46,1,84,77,9.0,5,30,Urban,HR Executive,23167,0 +20044,Male,39,PhD,16,2,29,10,85,4.0,4,49,Semi-Urban,HR Executive,128615,0 +20045,Male,31,High School,8,77,97,74,58,9.0,7,48,Urban,Manager,91224,1 +20046,Female,23,Bachelors,1,84,80,46,8,4.0,5,17,Rural,Manager,144759,0 +20047,Male,45,Masters,5,92,42,46,31,8.0,2,72,Urban,ML Engineer,66884,1 +20048,Male,55,Bachelors,4,24,7,91,39,3.0,7,25,Urban,HR Executive,102313,0 +20049,Male,43,Bachelors,8,30,8,80,94,0.0,0,60,Semi-Urban,Manager,135509,0 +20050,Female,24,Diploma,10,53,89,12,35,8.0,7,86,Urban,Manager,124105,0 +20051,Male,52,PhD,3,78,89,38,83,1.0,0,91,Urban,ML Engineer,37728,1 +20052,Female,25,Bachelors,8,20,6,67,94,1.0,4,77,Rural,Software Engineer,83316,0 +20053,Male,33,Bachelors,15,56,21,62,60,9.0,4,46,Urban,Data Analyst,147607,0 +20054,Male,51,Bachelors,11,39,60,43,52,9.0,3,54,Urban,HR Executive,32251,0 +20055,Female,23,Bachelors,4,5,93,68,88,3.0,4,63,Urban,HR Executive,74241,0 +20056,Other,44,Masters,2,63,81,41,6,1.0,5,68,Semi-Urban,Manager,98861,1 +20057,Male,45,Bachelors,1,58,60,12,36,2.0,6,13,Urban,Software Engineer,67275,0 +20058,Male,29,Bachelors,8,92,46,24,71,3.0,6,93,Rural,Software Engineer,33860,1 +20059,Female,36,Bachelors,12,64,22,82,41,9.0,6,5,Rural,ML Engineer,47354,0 +20060,Female,59,Masters,2,38,67,75,25,6.0,0,81,Rural,HR Executive,91882,1 +20061,Male,31,Masters,7,53,81,96,77,5.0,4,15,Semi-Urban,Manager,129586,1 +20062,Male,33,Masters,14,47,60,93,6,3.0,0,38,Urban,Software Engineer,35956,1 +20063,Female,49,High School,2,56,56,93,44,2.0,6,83,Urban,Manager,94332,1 +20064,Female,23,Bachelors,19,13,85,79,51,6.0,0,42,Urban,HR Executive,148347,0 +20065,Female,56,Bachelors,5,90,19,55,89,1.0,2,33,Urban,ML Engineer,76810,0 +20066,Male,51,Masters,18,21,59,72,72,0.0,2,88,Rural,Software Engineer,54442,1 +20067,Male,27,Diploma,19,11,36,61,2,4.0,0,28,Rural,Data Analyst,105232,0 +20068,Female,25,Masters,5,74,80,11,52,4.0,4,43,Urban,Manager,53810,0 +20069,Male,43,Bachelors,15,85,29,96,89,5.0,5,26,Urban,ML Engineer,121440,1 +20070,Male,34,Bachelors,12,44,13,61,5,9.0,1,31,Semi-Urban,Data Analyst,129117,0 +20071,Male,29,Masters,7,29,1,20,82,4.0,2,70,Rural,Software Engineer,20646,0 +20072,Male,47,Masters,9,33,67,54,76,0.0,1,97,Urban,Manager,112088,1 +20073,Male,26,Masters,12,0,74,3,70,5.0,3,16,Urban,ML Engineer,78059,0 +20074,Female,58,Diploma,11,33,81,60,96,0.0,4,54,Urban,Manager,146287,0 +20075,Female,21,High School,8,84,10,74,34,5.0,4,12,Rural,ML Engineer,61035,0 +20076,Male,52,Bachelors,2,27,35,72,81,9.0,4,43,Semi-Urban,Manager,60904,0 +20077,Male,54,High School,13,95,67,87,89,3.0,4,2,Rural,Data Analyst,88833,1 +20078,Male,34,Masters,2,52,47,77,68,9.0,2,92,Rural,ML Engineer,82813,1 +20079,Female,39,Diploma,1,56,62,24,38,1.0,5,80,Urban,Data Analyst,131413,0 +20080,Male,32,Bachelors,19,20,96,59,24,8.0,6,34,Semi-Urban,Manager,141991,0 +20081,Female,40,Bachelors,9,58,33,87,30,8.0,6,46,Rural,Software Engineer,84701,0 +20082,Male,53,Bachelors,4,59,82,42,29,4.0,5,74,Urban,HR Executive,95219,1 +20083,Male,57,Diploma,2,81,83,79,89,3.0,3,12,Urban,Data Analyst,37549,1 +20084,Female,49,Bachelors,4,9,8,12,10,6.0,0,88,Urban,Manager,119285,0 +20085,Male,45,High School,2,56,72,62,90,7.0,7,42,Rural,Manager,89508,0 +20086,Male,41,Diploma,12,91,43,7,9,8.0,2,14,Urban,Manager,90801,0 +20087,Male,36,Bachelors,17,97,75,89,68,9.0,7,71,Semi-Urban,ML Engineer,33103,1 +20088,Male,50,Bachelors,19,95,87,47,96,7.0,7,6,Urban,Manager,140415,1 +20089,Male,49,Bachelors,12,12,50,33,56,8.0,5,33,Urban,ML Engineer,28571,0 +20090,Male,49,Diploma,17,32,18,43,6,5.0,2,54,Urban,HR Executive,86122,0 +20091,Female,41,Bachelors,4,58,10,1,90,1.0,2,59,Urban,Software Engineer,75840,0 +20092,Female,27,Masters,9,10,73,2,75,0.0,4,17,Semi-Urban,ML Engineer,100904,0 +20093,Female,29,Bachelors,6,7,78,39,5,1.0,7,64,Urban,ML Engineer,104195,0 +20094,Male,55,Masters,13,0,90,5,36,6.0,3,81,Urban,Data Analyst,121287,0 +20095,Female,22,Masters,4,64,34,49,7,0.0,5,95,Semi-Urban,Manager,91745,1 +20096,Male,53,High School,19,26,27,55,86,1.0,6,54,Urban,Data Analyst,51926,0 +20097,Male,41,Masters,2,97,82,1,80,7.0,1,13,Semi-Urban,Software Engineer,116874,0 +20098,Male,41,Bachelors,18,96,36,69,80,7.0,6,94,Semi-Urban,Software Engineer,85612,1 +20099,Female,49,High School,6,12,53,5,33,7.0,2,62,Semi-Urban,HR Executive,66480,0 +20100,Male,26,Masters,4,79,51,87,23,5.0,3,45,Rural,HR Executive,148847,1 +20101,Female,22,Bachelors,17,76,46,8,13,7.0,1,29,Semi-Urban,Manager,142603,0 +20102,Male,39,Masters,1,39,51,63,62,2.0,5,87,Urban,Data Analyst,108498,1 +20103,Male,51,Diploma,4,61,17,69,92,9.0,2,73,Rural,ML Engineer,88080,0 +20104,Male,45,Diploma,19,72,5,54,9,9.0,5,62,Semi-Urban,HR Executive,99963,0 +20105,Female,22,Masters,15,52,77,12,70,5.0,0,52,Urban,Software Engineer,42839,0 +20106,Male,56,Masters,17,98,91,33,36,7.0,3,28,Semi-Urban,ML Engineer,104190,1 +20107,Female,24,Masters,15,47,52,6,78,4.0,1,39,Urban,ML Engineer,123185,0 +20108,Female,35,Bachelors,10,21,13,48,81,6.0,6,71,Semi-Urban,Software Engineer,29991,0 +20109,Female,34,Bachelors,16,47,93,31,42,8.0,2,81,Urban,Manager,88798,1 +20110,Male,39,Diploma,3,3,86,60,17,0.0,3,33,Semi-Urban,HR Executive,109677,0 +20111,Female,24,High School,17,73,98,14,82,7.0,2,83,Semi-Urban,HR Executive,52987,1 +20112,Female,37,Masters,2,88,5,10,3,2.0,7,50,Rural,Manager,53109,0 +20113,Male,50,Diploma,15,57,77,12,11,4.0,7,16,Urban,ML Engineer,52934,0 +20114,Female,37,Bachelors,18,53,92,19,26,5.0,6,69,Urban,Data Analyst,44742,0 +20115,Male,52,Bachelors,14,74,77,94,0,1.0,7,92,Urban,Data Analyst,124458,1 +20116,Male,54,Bachelors,10,92,66,93,54,5.0,2,97,Semi-Urban,HR Executive,139900,1 +20117,Male,35,Masters,17,98,96,83,21,8.0,1,19,Urban,Manager,128561,1 +20118,Male,37,High School,0,3,60,46,8,7.0,7,60,Urban,Software Engineer,115933,0 +20119,Male,51,Bachelors,9,1,46,99,64,3.0,0,33,Urban,Manager,38702,0 +20120,Male,32,Masters,12,6,36,86,10,8.0,6,91,Rural,Software Engineer,111362,0 +20121,Female,53,Bachelors,2,85,16,76,90,2.0,4,36,Urban,Manager,53103,0 +20122,Other,34,Masters,6,73,63,88,74,5.0,1,38,Urban,ML Engineer,115684,1 +20123,Other,38,Diploma,16,86,52,16,6,2.0,4,0,Urban,HR Executive,38862,0 +20124,Male,35,Bachelors,12,3,30,92,95,2.0,2,79,Urban,Software Engineer,112572,0 +20125,Female,28,Bachelors,17,23,65,41,74,5.0,4,48,Urban,Manager,135945,0 +20126,Male,43,Diploma,6,78,9,44,20,9.0,4,31,Semi-Urban,ML Engineer,115711,0 +20127,Female,24,High School,6,64,45,43,53,6.0,7,77,Rural,Data Analyst,127914,0 +20128,Male,57,Bachelors,13,21,4,36,18,6.0,1,21,Urban,HR Executive,113037,0 +20129,Male,52,High School,18,34,12,21,74,7.0,0,65,Urban,Data Analyst,63981,0 +20130,Female,48,Diploma,1,41,57,21,24,3.0,4,95,Urban,ML Engineer,123919,0 +20131,Male,58,High School,8,17,93,18,42,8.0,0,88,Urban,HR Executive,141897,0 +20132,Male,38,Masters,1,24,53,70,18,0.0,1,97,Semi-Urban,Manager,23627,1 +20133,Female,22,Bachelors,5,17,54,33,26,5.0,6,60,Rural,Data Analyst,129193,0 +20134,Male,44,Diploma,4,65,92,38,76,0.0,1,56,Semi-Urban,Software Engineer,50953,1 +20135,Male,34,High School,1,87,87,17,2,5.0,4,16,Rural,Data Analyst,83013,0 +20136,Male,55,Masters,13,54,81,51,24,5.0,5,33,Rural,Software Engineer,97211,0 +20137,Male,51,High School,13,48,10,97,67,4.0,0,75,Semi-Urban,Software Engineer,30422,0 +20138,Male,21,Bachelors,9,13,82,75,97,1.0,3,55,Semi-Urban,Software Engineer,80872,0 +20139,Female,47,Diploma,2,54,90,88,24,8.0,0,37,Urban,Data Analyst,28558,1 +20140,Male,41,Diploma,4,16,89,80,31,1.0,3,5,Urban,ML Engineer,82314,0 +20141,Female,59,Diploma,2,36,24,27,86,2.0,2,33,Semi-Urban,Data Analyst,83633,0 +20142,Male,25,High School,10,59,43,63,51,7.0,4,35,Urban,HR Executive,54032,0 +20143,Male,38,Bachelors,8,12,58,97,76,9.0,0,65,Urban,Manager,136519,0 +20144,Female,38,Diploma,2,23,15,90,83,4.0,5,25,Semi-Urban,Software Engineer,140719,0 +20145,Female,27,Bachelors,10,91,53,9,52,9.0,1,59,Rural,HR Executive,53276,0 +20146,Female,55,Bachelors,7,51,34,22,29,7.0,3,13,Semi-Urban,Data Analyst,53232,0 +20147,Female,55,Bachelors,10,69,44,70,10,7.0,4,92,Urban,ML Engineer,121353,1 +20148,Male,39,Bachelors,17,98,24,36,98,7.0,4,17,Urban,Data Analyst,147485,0 +20149,Male,47,Diploma,3,95,22,32,58,8.0,3,71,Urban,HR Executive,134433,0 +20150,Female,23,PhD,9,8,17,52,77,0.0,6,36,Semi-Urban,Manager,124952,0 +20151,Male,36,PhD,6,74,18,89,98,4.0,2,34,Semi-Urban,Data Analyst,35730,0 +20152,Male,29,Masters,16,85,3,45,22,7.0,2,81,Semi-Urban,Manager,89553,0 +20153,Male,44,Bachelors,18,57,69,6,8,1.0,3,10,Urban,HR Executive,43477,0 +20154,Female,49,Masters,9,43,78,97,18,9.0,3,72,Rural,HR Executive,133990,1 +20155,Male,35,Bachelors,16,91,31,75,47,9.0,6,24,Urban,HR Executive,35727,0 +20156,Male,29,Masters,13,6,70,44,6,8.0,7,72,Urban,HR Executive,97120,0 +20157,Male,37,Diploma,5,92,2,66,89,7.0,5,83,Semi-Urban,Data Analyst,71066,1 +20158,Female,49,PhD,16,59,77,10,83,4.0,3,64,Urban,ML Engineer,122432,0 +20159,Male,46,Masters,8,11,92,18,78,2.0,2,3,Rural,Manager,40334,0 +20160,Male,58,Bachelors,12,57,14,31,2,8.0,0,79,Urban,HR Executive,127377,0 +20161,Female,50,Masters,18,29,41,7,2,2.0,1,91,Urban,Manager,83176,0 +20162,Female,47,High School,2,84,65,67,87,3.0,6,1,Urban,Data Analyst,103687,0 +20163,Female,54,Bachelors,6,3,55,3,85,8.0,5,82,Urban,Software Engineer,135696,0 +20164,Female,34,Diploma,13,59,35,90,59,2.0,0,38,Urban,Manager,144592,0 +20165,Male,25,Masters,15,15,65,13,62,0.0,5,88,Semi-Urban,Software Engineer,75333,0 +20166,Male,24,Bachelors,1,78,26,5,3,2.0,2,94,Rural,Software Engineer,93820,0 +20167,Male,53,Bachelors,2,76,9,70,76,3.0,4,92,Semi-Urban,HR Executive,74960,1 +20168,Female,54,Bachelors,1,61,25,10,21,5.0,6,78,Rural,Software Engineer,96351,0 +20169,Male,50,Diploma,16,43,13,53,71,3.0,4,79,Urban,HR Executive,39975,0 +20170,Female,43,High School,10,67,11,66,16,5.0,2,30,Semi-Urban,ML Engineer,46095,0 +20171,Other,35,PhD,16,6,38,96,22,3.0,1,62,Rural,Software Engineer,93701,0 +20172,Male,26,Masters,8,32,43,92,66,7.0,5,9,Urban,Manager,99718,0 +20173,Male,50,High School,10,1,43,4,17,2.0,1,96,Urban,Data Analyst,40528,0 +20174,Male,58,Bachelors,9,58,38,81,4,3.0,3,18,Urban,HR Executive,112998,0 +20175,Male,33,PhD,4,22,93,14,56,8.0,0,99,Urban,HR Executive,114350,0 +20176,Male,56,Diploma,15,86,88,7,64,5.0,5,19,Urban,Software Engineer,104737,0 +20177,Female,26,Diploma,7,49,27,88,54,7.0,4,5,Urban,Data Analyst,144970,0 +20178,Male,38,Masters,5,9,79,9,35,2.0,7,2,Rural,Manager,93491,0 +20179,Male,56,Masters,17,88,7,25,49,7.0,2,39,Urban,HR Executive,27932,0 +20180,Male,45,Bachelors,14,21,53,27,97,2.0,6,83,Urban,Data Analyst,116299,0 +20181,Female,24,Bachelors,9,9,41,64,35,5.0,7,4,Semi-Urban,ML Engineer,93402,0 +20182,Female,44,Masters,15,96,69,17,24,4.0,2,62,Semi-Urban,HR Executive,111580,1 +20183,Female,45,PhD,3,3,98,88,92,3.0,5,98,Urban,Software Engineer,103670,1 +20184,Other,42,Bachelors,1,89,10,85,32,6.0,5,93,Rural,Manager,121516,1 +20185,Male,21,High School,0,9,2,83,44,6.0,6,78,Rural,Manager,83125,0 +20186,Male,24,Masters,10,46,59,93,81,4.0,7,21,Urban,Software Engineer,126266,0 +20187,Male,57,Bachelors,4,8,28,69,84,9.0,4,11,Urban,Data Analyst,116028,0 +20188,Male,47,Bachelors,5,87,38,62,89,1.0,5,33,Rural,Software Engineer,68225,0 +20189,Female,58,Masters,19,25,62,82,94,6.0,5,88,Rural,ML Engineer,76552,1 +20190,Male,53,Masters,18,11,75,83,84,6.0,2,12,Rural,HR Executive,22588,0 +20191,Male,27,Masters,6,22,6,61,59,9.0,0,23,Semi-Urban,Manager,139583,0 +20192,Female,26,High School,2,9,7,8,94,3.0,3,6,Urban,Manager,125349,0 +20193,Female,33,Diploma,18,95,50,62,64,1.0,3,28,Semi-Urban,Manager,128741,0 +20194,Female,50,High School,18,93,9,61,14,2.0,5,39,Rural,ML Engineer,30907,0 +20195,Male,34,Bachelors,13,12,39,7,61,6.0,0,31,Rural,Manager,145860,0 +20196,Female,40,High School,11,79,24,45,31,2.0,1,66,Semi-Urban,HR Executive,109817,0 +20197,Male,33,Masters,14,58,42,90,18,7.0,3,92,Semi-Urban,ML Engineer,80175,1 +20198,Male,22,Bachelors,11,41,51,13,47,4.0,7,54,Urban,Manager,54995,0 +20199,Female,50,Masters,13,42,96,96,16,4.0,3,49,Urban,Manager,103120,1 +20200,Other,47,Bachelors,7,38,40,86,89,5.0,0,51,Urban,Manager,131535,0 +20201,Male,57,PhD,17,58,33,74,35,1.0,5,53,Urban,Data Analyst,98483,0 +20202,Male,27,Bachelors,16,24,44,40,28,5.0,1,11,Urban,ML Engineer,129694,0 +20203,Male,42,Bachelors,5,25,82,0,95,9.0,3,35,Semi-Urban,HR Executive,44997,0 +20204,Male,36,Bachelors,1,11,10,57,70,1.0,6,64,Urban,Software Engineer,121290,0 +20205,Female,57,Diploma,1,59,43,74,5,9.0,0,7,Urban,Manager,81042,0 +20206,Male,40,Diploma,13,73,89,8,30,0.0,5,48,Rural,Data Analyst,130225,0 +20207,Female,41,Masters,3,89,77,91,22,9.0,5,8,Urban,ML Engineer,142594,1 +20208,Female,33,Bachelors,11,69,11,64,37,9.0,6,65,Rural,HR Executive,140100,0 +20209,Male,55,High School,9,54,83,89,73,,3,98,Urban,Data Analyst,95907,1 +20210,Male,38,PhD,17,7,72,9,13,9.0,0,51,Rural,Manager,88587,0 +20211,Male,44,Diploma,8,72,0,18,16,3.0,2,54,Rural,Manager,39827,0 +20212,Male,36,Bachelors,6,16,39,29,40,3.0,3,60,Urban,Manager,136380,0 +20213,Male,51,High School,13,88,53,47,56,9.0,0,11,Urban,Data Analyst,54436,0 +20214,Male,49,High School,19,68,16,28,32,6.0,6,12,Semi-Urban,HR Executive,40584,0 +20215,Female,21,Bachelors,0,51,28,25,51,7.0,6,71,Urban,Data Analyst,29073,0 +20216,Male,54,Masters,0,61,71,24,65,0.0,3,11,Urban,Data Analyst,62983,0 +20217,Female,49,PhD,0,1,37,49,60,3.0,4,80,Rural,Data Analyst,140252,0 +20218,Male,35,Bachelors,19,78,19,94,15,8.0,3,86,Urban,Data Analyst,120157,1 +20219,Female,21,Masters,19,80,15,13,24,7.0,2,83,Urban,HR Executive,113983,0 +20220,Other,44,Masters,0,90,28,5,12,2.0,6,91,Semi-Urban,Data Analyst,48526,0 +20221,Male,38,High School,7,77,79,22,29,3.0,5,44,Urban,Software Engineer,140718,0 +20222,Female,53,Masters,16,10,21,96,18,4.0,5,76,Urban,HR Executive,63854,0 +20223,Female,25,Bachelors,16,25,0,20,50,6.0,3,98,Urban,ML Engineer,25622,0 +20224,Female,51,Bachelors,10,47,66,74,49,3.0,6,85,Urban,HR Executive,25206,1 +20225,Female,39,Bachelors,12,53,58,31,87,6.0,4,75,Urban,Data Analyst,126523,0 +20226,Male,42,Bachelors,8,0,12,45,79,7.0,3,83,Urban,HR Executive,44933,0 +20227,Male,46,Masters,0,44,57,63,4,9.0,4,3,Urban,Data Analyst,87284,0 +20228,Male,27,Masters,6,15,3,30,30,7.0,5,46,Rural,Software Engineer,127481,0 +20229,Male,50,Bachelors,13,70,63,29,89,4.0,1,24,Urban,ML Engineer,99404,0 +20230,Other,45,Masters,0,44,58,53,88,9.0,7,74,Urban,ML Engineer,132486,0 +20231,Female,57,Bachelors,6,83,38,49,19,9.0,3,47,Rural,Data Analyst,38825,0 +20232,Male,38,Diploma,18,18,69,85,41,6.0,2,40,Rural,HR Executive,75695,0 +20233,Female,22,Bachelors,7,35,7,8,10,5.0,3,1,Urban,Data Analyst,143013,0 +20234,Female,54,Bachelors,17,12,75,12,64,7.0,5,58,Urban,Software Engineer,79865,0 +20235,Male,44,Bachelors,3,48,14,16,52,7.0,0,14,Urban,ML Engineer,72091,0 +20236,Male,49,Bachelors,4,73,71,74,16,9.0,3,79,Semi-Urban,Software Engineer,146134,1 +20237,Male,30,Diploma,18,27,85,20,9,7.0,6,27,Urban,Manager,64176,0 +20238,Female,51,Bachelors,13,1,56,27,50,8.0,5,11,Urban,Manager,54992,0 +20239,Female,27,High School,19,17,89,69,51,1.0,3,45,Rural,ML Engineer,67480,0 +20240,Male,54,Bachelors,15,8,49,4,10,6.0,0,27,Rural,HR Executive,21137,0 +20241,Male,49,Bachelors,1,44,89,92,80,3.0,7,40,Semi-Urban,Software Engineer,45166,1 +20242,Female,58,Masters,6,9,50,50,28,0.0,1,95,Semi-Urban,ML Engineer,33349,0 +20243,Female,49,Masters,11,11,95,37,38,1.0,4,87,Semi-Urban,Data Analyst,28656,0 +20244,Female,43,High School,13,4,80,40,88,8.0,7,22,Urban,Manager,66154,0 +20245,Female,31,Bachelors,9,94,69,70,43,6.0,5,77,Urban,Data Analyst,96459,1 +20246,Male,42,Diploma,18,94,16,20,54,7.0,4,70,Rural,HR Executive,77913,0 +20247,Male,22,High School,4,87,59,94,71,4.0,5,51,Rural,Software Engineer,89117,1 +20248,Male,24,Bachelors,13,36,59,85,17,6.0,4,72,Rural,Data Analyst,146546,1 +20249,Female,53,Bachelors,8,52,32,19,37,4.0,2,86,Rural,ML Engineer,30320,0 +20250,Male,34,Bachelors,16,38,46,47,39,0.0,7,41,Urban,Data Analyst,99130,0 +20251,Female,33,Masters,17,63,23,97,5,0.0,5,90,Rural,Data Analyst,141147,1 +20252,Male,31,Bachelors,2,91,78,28,25,5.0,2,50,Semi-Urban,HR Executive,119809,1 +20253,Female,21,Masters,13,90,75,93,55,6.0,0,65,Rural,Data Analyst,110230,1 +20254,Male,41,Bachelors,14,14,11,16,89,8.0,7,89,Urban,Data Analyst,97113,0 +20255,Male,53,Bachelors,19,17,61,47,63,1.0,1,65,Urban,HR Executive,127331,0 +20256,Female,39,Bachelors,11,11,71,87,35,5.0,1,98,Urban,Software Engineer,123754,1 +20257,Male,22,Diploma,15,93,44,86,9,6.0,3,75,Urban,HR Executive,120199,1 +20258,Female,58,Diploma,2,58,17,56,15,2.0,5,64,Rural,HR Executive,37104,0 +20259,Male,41,Bachelors,10,53,83,86,91,1.0,5,19,Urban,Data Analyst,69399,1 +20260,Male,36,Bachelors,10,34,64,2,91,4.0,5,43,Semi-Urban,ML Engineer,73532,0 +20261,Female,55,Masters,8,17,86,77,85,7.0,0,4,Semi-Urban,Software Engineer,103218,0 +20262,Female,27,Masters,14,46,19,71,33,2.0,1,88,Urban,Manager,49791,0 +20263,Male,24,Diploma,12,31,77,70,23,5.0,7,82,Urban,Software Engineer,23366,1 +20264,Female,56,Masters,4,93,95,14,70,2.0,2,19,Rural,Manager,144594,0 +20265,Male,35,Diploma,4,6,43,38,15,8.0,3,65,Semi-Urban,Software Engineer,80721,0 +20266,Male,48,Bachelors,8,91,27,14,29,5.0,4,52,Urban,Data Analyst,122331,0 +20267,Male,51,Diploma,12,55,99,50,41,3.0,4,93,Rural,Data Analyst,24633,1 +20268,Male,40,Bachelors,14,52,17,77,29,5.0,1,57,Urban,Manager,128802,0 +20269,Male,47,Bachelors,19,83,47,22,45,7.0,0,67,Semi-Urban,Manager,35501,0 +20270,Male,40,High School,4,20,47,41,76,9.0,4,48,Urban,HR Executive,28912,0 +20271,Male,31,High School,1,0,79,69,15,0.0,3,30,Semi-Urban,ML Engineer,80170,0 +20272,Female,46,Bachelors,15,47,44,38,13,9.0,5,26,Semi-Urban,Software Engineer,40269,0 +20273,Male,21,High School,14,10,53,6,15,6.0,5,39,Urban,Software Engineer,20619,0 +20274,Other,48,Masters,18,28,34,74,18,3.0,7,65,Urban,Manager,88942,0 +20275,Female,40,Bachelors,17,10,64,87,35,3.0,6,0,Rural,Manager,128671,0 +20276,Male,56,PhD,12,47,18,12,46,8.0,2,6,Urban,Manager,57477,0 +20277,Male,21,Bachelors,15,80,11,16,62,5.0,4,8,Urban,Data Analyst,49600,0 +20278,Male,51,Masters,3,72,13,27,12,6.0,0,56,Urban,Data Analyst,115901,0 +20279,Female,23,Bachelors,18,0,3,61,80,4.0,3,49,Urban,Software Engineer,59874,0 +20280,Male,37,Masters,2,85,15,19,75,1.0,4,15,Semi-Urban,Software Engineer,80037,0 +20281,Male,57,Masters,3,58,32,0,13,6.0,5,97,Semi-Urban,HR Executive,85743,0 +20282,Female,31,High School,17,60,11,52,85,4.0,2,18,Urban,Manager,98057,0 +20283,Female,33,Masters,17,21,2,50,96,7.0,2,41,Urban,HR Executive,117926,0 +20284,Male,55,Bachelors,15,18,21,60,91,2.0,3,10,Rural,HR Executive,86466,0 +20285,Male,25,Diploma,0,10,15,3,50,6.0,1,77,Urban,Manager,33989,0 +20286,Female,38,High School,6,5,95,47,44,4.0,5,78,Rural,HR Executive,136179,0 +20287,Female,38,Bachelors,13,24,92,75,27,8.0,3,59,Semi-Urban,Manager,35298,1 +20288,Male,48,Bachelors,18,0,98,92,20,6.0,0,38,Urban,HR Executive,93373,0 +20289,Male,32,Masters,10,40,54,89,5,7.0,1,41,Urban,ML Engineer,82529,0 +20290,Female,46,High School,5,3,82,16,64,9.0,5,61,Rural,HR Executive,136523,0 +20291,Female,48,Masters,9,95,17,17,37,8.0,4,76,Urban,Manager,103362,0 +20292,Female,49,Diploma,9,63,62,95,60,2.0,5,0,Urban,HR Executive,55269,0 +20293,Male,57,Bachelors,9,18,75,1,12,3.0,7,69,Semi-Urban,Manager,99131,0 +20294,Female,51,Masters,3,80,22,26,95,6.0,1,42,Semi-Urban,Data Analyst,132611,0 +20295,Male,54,Bachelors,16,10,8,22,16,5.0,4,10,Semi-Urban,HR Executive,122384,0 +20296,Male,24,Masters,13,68,48,34,90,2.0,3,98,Urban,Software Engineer,139804,1 +20297,Female,26,High School,5,82,28,28,90,5.0,6,74,Urban,ML Engineer,129966,0 +20298,Male,48,Bachelors,3,14,23,39,66,2.0,2,28,Semi-Urban,ML Engineer,88263,0 +20299,Female,42,High School,1,74,26,86,68,5.0,2,1,Urban,Manager,85035,0 +20300,Male,37,High School,9,95,14,2,35,0.0,1,27,Semi-Urban,Data Analyst,37563,0 +20301,Female,56,Diploma,7,69,39,23,1,5.0,0,6,Rural,Manager,137936,0 +20302,Male,51,Bachelors,16,74,6,36,27,3.0,7,64,Rural,Software Engineer,60830,0 +20303,Female,51,Masters,2,44,43,52,12,1.0,3,10,Urban,ML Engineer,130224,0 +20304,Male,53,Diploma,13,72,55,46,17,3.0,1,46,Urban,ML Engineer,127177,0 +20305,Female,50,Diploma,17,16,29,21,33,6.0,4,72,Urban,HR Executive,122237,0 +20306,Female,40,Bachelors,6,79,4,35,1,5.0,1,3,Urban,Data Analyst,34343,0 +20307,Male,44,Bachelors,2,80,19,21,13,9.0,4,81,Rural,HR Executive,37360,0 +20308,Male,57,Bachelors,14,89,65,95,65,6.0,6,70,Semi-Urban,Software Engineer,53719,1 +20309,Male,46,Bachelors,3,33,22,30,37,7.0,2,84,Urban,HR Executive,148601,0 +20310,Female,44,Bachelors,15,3,42,59,58,6.0,6,11,Semi-Urban,Data Analyst,145025,0 +20311,Male,50,High School,15,98,97,28,72,5.0,0,47,Semi-Urban,Manager,24022,1 +20312,Male,47,Bachelors,0,19,71,33,70,3.0,6,45,Semi-Urban,Data Analyst,119330,0 +20313,Male,26,High School,1,46,30,60,81,6.0,0,47,Urban,Data Analyst,63957,0 +20314,Female,31,High School,12,93,73,66,3,0.0,5,98,Rural,HR Executive,56279,1 +20315,Male,35,Masters,15,20,49,2,29,4.0,2,54,Semi-Urban,ML Engineer,109591,0 +20316,Male,33,Masters,19,78,85,32,71,7.0,4,80,Semi-Urban,HR Executive,115961,1 +20317,Female,58,High School,8,18,44,2,74,0.0,4,73,Semi-Urban,HR Executive,126868,0 +20318,Female,54,Masters,16,20,78,0,42,6.0,0,65,Urban,HR Executive,72501,0 +20319,Male,37,High School,1,53,83,41,95,3.0,5,2,Rural,Software Engineer,33961,0 +20320,Other,41,Bachelors,8,93,46,94,50,7.0,3,71,Rural,ML Engineer,117147,1 +20321,Female,21,Masters,18,86,75,4,97,2.0,7,85,Urban,Manager,47461,1 +20322,Male,36,Bachelors,0,38,72,20,44,9.0,0,40,Urban,Data Analyst,91976,0 +20323,Male,43,Bachelors,13,19,49,40,74,6.0,6,57,Urban,Data Analyst,49993,0 +20324,Female,59,Bachelors,17,82,86,35,43,7.0,7,4,Rural,Data Analyst,60030,0 +20325,Male,23,Masters,0,63,88,62,35,4.0,7,42,Semi-Urban,HR Executive,33857,1 +20326,Male,32,Bachelors,3,12,8,11,16,3.0,5,53,Rural,Software Engineer,88733,0 +20327,Male,49,Bachelors,1,94,26,60,35,2.0,1,95,Urban,Software Engineer,84133,1 +20328,Female,29,Masters,10,81,5,60,50,7.0,1,0,Urban,Data Analyst,88193,0 +20329,Male,47,Bachelors,14,36,28,44,33,9.0,6,2,Rural,Data Analyst,28597,0 +20330,Female,40,Diploma,5,42,25,47,21,8.0,6,3,Urban,Software Engineer,134432,0 +20331,Male,52,Masters,12,6,49,30,27,4.0,2,49,Urban,Data Analyst,94401,0 +20332,Female,56,Bachelors,7,18,12,54,45,3.0,7,47,Urban,Data Analyst,89953,0 +20333,Female,52,High School,15,83,49,15,32,3.0,1,41,Rural,HR Executive,83475,0 +20334,Male,53,Bachelors,0,53,71,79,41,9.0,6,94,Urban,ML Engineer,121203,1 +20335,Female,35,Masters,6,3,82,78,38,4.0,7,78,Urban,ML Engineer,28853,1 +20336,Male,28,High School,7,52,51,45,46,4.0,2,12,Urban,Data Analyst,139342,0 +20337,Female,24,Bachelors,11,68,90,5,6,5.0,6,80,Rural,Data Analyst,90613,1 +20338,Male,52,Bachelors,19,58,41,54,74,6.0,4,78,Urban,Data Analyst,87294,0 +20339,Male,39,Bachelors,1,4,90,72,49,3.0,3,33,Urban,ML Engineer,95241,0 +20340,Other,46,High School,17,80,52,50,42,8.0,5,9,Urban,Manager,123527,0 +20341,Other,28,Masters,18,26,17,36,1,2.0,2,74,Rural,Data Analyst,36486,0 +20342,Male,57,Bachelors,4,14,59,97,14,8.0,7,32,Urban,Manager,130019,0 +20343,Male,57,Bachelors,13,87,60,97,2,9.0,5,33,Urban,HR Executive,85747,1 +20344,Male,40,Diploma,16,37,5,11,2,5.0,5,93,Semi-Urban,HR Executive,36847,0 +20345,Female,50,Bachelors,1,8,29,33,24,4.0,3,81,Urban,HR Executive,95719,0 +20346,Male,32,Masters,17,57,52,34,11,5.0,2,85,Urban,Manager,130332,0 +20347,Male,54,Bachelors,7,60,41,3,48,2.0,3,2,Semi-Urban,ML Engineer,64674,0 +20348,Male,50,Bachelors,4,17,1,34,41,4.0,1,28,Urban,Data Analyst,36871,0 +20349,Female,44,Bachelors,5,15,23,61,34,6.0,5,55,Urban,HR Executive,146351,0 +20350,Male,42,Diploma,17,43,76,60,98,6.0,4,60,Urban,HR Executive,58441,1 +20351,Male,34,Masters,19,75,23,21,42,1.0,2,62,Rural,ML Engineer,88855,0 +20352,Male,43,Bachelors,0,8,46,31,54,1.0,3,23,Rural,Manager,45729,0 +20353,Male,22,High School,6,32,96,40,99,4.0,0,47,Urban,Data Analyst,130645,0 +20354,Female,56,High School,9,26,99,9,51,7.0,6,98,Semi-Urban,Data Analyst,111732,0 +20355,Female,34,Bachelors,9,40,20,60,22,4.0,4,12,Urban,ML Engineer,96129,0 +20356,Female,52,Masters,10,97,97,35,13,2.0,6,52,Rural,Data Analyst,68509,1 +20357,Male,38,Diploma,4,56,16,37,7,1.0,0,43,Urban,Data Analyst,69795,0 +20358,Female,45,Diploma,17,76,83,18,58,3.0,1,45,Urban,HR Executive,134137,0 +20359,Male,45,High School,10,92,0,38,70,8.0,6,96,Urban,Software Engineer,67470,0 +20360,Male,22,PhD,13,99,8,34,40,0.0,6,39,Urban,HR Executive,108942,0 +20361,Other,24,Bachelors,11,48,19,28,40,6.0,4,15,Urban,ML Engineer,94612,0 +20362,Male,28,Diploma,0,75,98,15,72,3.0,6,32,Urban,HR Executive,107061,0 +20363,Male,21,Diploma,15,16,62,65,77,5.0,5,95,Urban,Data Analyst,56227,1 +20364,Other,29,Masters,16,69,98,87,24,1.0,1,18,Semi-Urban,Manager,26098,1 +20365,Male,47,High School,1,91,3,29,49,0.0,1,55,Urban,Software Engineer,140473,0 +20366,Female,48,Bachelors,1,75,12,87,7,9.0,5,52,Rural,Manager,139053,0 +20367,Female,21,Bachelors,18,62,45,75,85,9.0,7,1,Urban,Manager,106823,0 +20368,Male,26,Bachelors,18,17,47,92,69,5.0,0,89,Urban,Software Engineer,89576,1 +20369,Male,55,Bachelors,15,67,50,56,47,3.0,3,89,Semi-Urban,Manager,27638,1 +20370,Male,35,Diploma,13,71,84,80,59,2.0,1,16,Rural,Software Engineer,33896,1 +20371,Male,30,Bachelors,10,96,50,96,4,1.0,1,99,Semi-Urban,ML Engineer,83101,1 +20372,Male,44,Diploma,1,7,9,4,1,5.0,2,42,Semi-Urban,HR Executive,132005,0 +20373,Female,21,Diploma,15,29,60,35,55,7.0,6,81,Urban,ML Engineer,56342,0 +20374,Male,47,High School,13,3,53,22,22,6.0,5,89,Urban,Software Engineer,44438,0 +20375,Male,40,Bachelors,10,48,17,30,0,5.0,0,6,Rural,Software Engineer,41528,0 +20376,Male,59,Bachelors,1,14,76,84,73,7.0,4,73,Rural,ML Engineer,21209,1 +20377,Male,50,PhD,2,71,52,16,13,6.0,4,27,Urban,HR Executive,44049,0 +20378,Female,30,Diploma,9,52,71,66,66,9.0,3,83,Urban,ML Engineer,27301,1 +20379,Male,43,Bachelors,7,24,57,98,32,1.0,7,64,Urban,Data Analyst,63096,1 +20380,Female,44,Masters,18,34,7,88,79,1.0,2,66,Urban,Data Analyst,127852,0 +20381,Male,40,Masters,9,1,86,69,26,5.0,0,87,Rural,Manager,96936,1 +20382,Male,54,Masters,15,10,78,63,37,0.0,1,70,Urban,ML Engineer,25092,0 +20383,Male,38,PhD,9,19,82,89,2,0.0,1,84,Semi-Urban,Software Engineer,124240,1 +20384,Male,58,Bachelors,18,24,36,45,36,1.0,5,59,Urban,Manager,127110,0 +20385,Female,21,Bachelors,5,2,75,98,47,4.0,5,49,Semi-Urban,Data Analyst,97658,0 +20386,Male,39,Bachelors,12,37,39,2,45,5.0,7,64,Urban,Software Engineer,143136,0 +20387,Female,56,High School,1,62,90,82,27,3.0,0,3,Urban,ML Engineer,20557,0 +20388,Male,57,Masters,11,30,82,72,34,9.0,5,62,Urban,Data Analyst,54735,1 +20389,Female,37,Diploma,7,22,6,92,25,6.0,2,43,Urban,Manager,101033,0 +20390,Male,21,Bachelors,12,93,76,92,50,3.0,4,77,Rural,HR Executive,25848,1 +20391,Male,58,Bachelors,12,44,11,75,61,1.0,1,67,Semi-Urban,Manager,54488,0 +20392,Male,53,Bachelors,3,96,55,31,24,6.0,5,50,Rural,Manager,83502,0 +20393,Male,53,Bachelors,3,80,88,18,35,8.0,2,57,Semi-Urban,Data Analyst,99160,1 +20394,Female,50,Bachelors,19,79,19,7,20,4.0,7,3,Urban,ML Engineer,31299,0 +20395,Male,59,Bachelors,13,32,85,78,66,7.0,6,74,Semi-Urban,Data Analyst,131519,1 +20396,Male,34,Bachelors,12,15,65,10,72,8.0,6,1,Rural,Data Analyst,109352,0 +20397,Male,39,High School,6,74,80,23,16,3.0,4,99,Urban,Manager,21966,1 +20398,Male,27,Bachelors,13,66,67,88,82,9.0,5,98,Urban,Software Engineer,84603,1 +20399,Female,41,Bachelors,13,75,11,72,71,1.0,6,62,Semi-Urban,ML Engineer,143837,0 +20400,Female,38,Bachelors,6,70,46,84,21,8.0,6,75,Urban,HR Executive,143848,1 +20401,Female,32,Masters,14,45,16,82,72,5.0,5,67,Rural,HR Executive,99644,0 +20402,Male,32,Masters,2,65,89,97,19,1.0,4,17,Urban,Data Analyst,118996,1 +20403,Female,28,Masters,0,56,82,89,95,1.0,3,76,Rural,HR Executive,81850,1 +20404,Female,36,Bachelors,15,69,85,6,61,9.0,6,4,Urban,ML Engineer,21474,0 +20405,Male,47,High School,6,29,24,81,6,6.0,4,41,Urban,ML Engineer,112750,0 +20406,Male,59,Bachelors,3,1,20,49,16,7.0,4,37,Urban,Data Analyst,61257,0 +20407,Female,39,Bachelors,19,69,51,1,54,7.0,5,40,Rural,Software Engineer,84067,0 +20408,Male,35,Bachelors,15,42,90,23,74,7.0,1,55,Semi-Urban,Software Engineer,62729,0 +20409,Female,53,Diploma,19,5,3,59,14,0.0,2,54,Semi-Urban,HR Executive,123347,0 +20410,Male,52,Masters,2,73,4,1,47,8.0,7,36,Urban,Software Engineer,144617,0 +20411,Male,47,Diploma,11,46,26,29,3,7.0,3,82,Semi-Urban,Manager,25456,0 +20412,Female,35,Masters,11,93,98,26,92,1.0,6,2,Urban,HR Executive,40996,0 +20413,Female,45,Bachelors,1,11,51,28,95,4.0,7,73,Urban,HR Executive,112053,0 +20414,Male,54,High School,16,94,59,54,15,7.0,7,84,Urban,Data Analyst,134657,1 +20415,Female,52,PhD,18,89,85,86,72,6.0,0,99,Rural,ML Engineer,35534,1 +20416,Male,28,Masters,14,80,98,18,23,2.0,6,42,Urban,ML Engineer,51555,1 +20417,Female,30,Masters,11,19,1,87,98,7.0,5,77,Rural,Software Engineer,137487,0 +20418,Female,35,Diploma,3,95,52,52,36,6.0,4,50,Semi-Urban,HR Executive,41045,1 +20419,Female,46,Bachelors,18,10,59,55,0,7.0,2,2,Urban,ML Engineer,107689,0 +20420,Male,45,Diploma,14,48,40,56,32,2.0,1,20,Semi-Urban,Data Analyst,145558,0 +20421,Male,51,Bachelors,18,34,19,53,19,1.0,6,81,Semi-Urban,ML Engineer,99401,0 +20422,Female,33,Bachelors,8,63,43,34,45,6.0,4,71,Urban,HR Executive,45934,0 +20423,Male,27,Masters,9,16,36,43,76,9.0,3,28,Urban,ML Engineer,48435,0 +20424,Male,54,Masters,5,83,28,89,68,0.0,5,11,Rural,Manager,111830,0 +20425,Female,38,Bachelors,16,53,45,93,64,2.0,1,25,Urban,Data Analyst,87284,0 +20426,Male,22,Diploma,18,86,91,3,57,1.0,7,56,Urban,Software Engineer,50671,1 +20427,Male,58,Diploma,8,23,49,33,3,0.0,0,97,Rural,Software Engineer,110338,0 +20428,Male,32,Masters,4,46,55,18,13,8.0,0,85,Semi-Urban,HR Executive,73086,0 +20429,Male,21,Diploma,15,2,68,92,48,1.0,0,4,Rural,Software Engineer,101790,0 +20430,Male,59,PhD,9,51,75,0,44,0.0,3,11,Rural,Manager,68266,0 +20431,Female,24,Bachelors,1,63,12,31,16,4.0,2,54,Urban,ML Engineer,64611,0 +20432,Male,48,Bachelors,4,42,71,12,93,9.0,3,46,Urban,Software Engineer,24471,0 +20433,Male,27,Bachelors,10,71,31,9,2,9.0,0,0,Urban,HR Executive,147544,0 +20434,Female,44,Bachelors,10,67,94,73,91,1.0,0,88,Urban,HR Executive,91956,1 +20435,Female,50,PhD,18,81,38,81,28,5.0,1,33,Semi-Urban,Data Analyst,118699,0 +20436,Female,42,Diploma,2,23,63,94,73,7.0,4,2,Rural,HR Executive,136633,0 +20437,Male,42,Diploma,10,24,83,97,43,7.0,7,98,Urban,Software Engineer,57680,1 +20438,Female,48,Masters,9,66,19,28,33,8.0,4,74,Urban,HR Executive,102886,0 +20439,Male,40,Masters,11,60,38,8,82,4.0,2,73,Semi-Urban,Data Analyst,120431,0 +20440,Male,29,Diploma,17,57,68,21,89,5.0,1,35,Urban,HR Executive,76380,0 +20441,Male,48,PhD,9,95,3,95,57,0.0,4,76,Urban,ML Engineer,77257,1 +20442,Male,25,Bachelors,0,54,58,25,7,7.0,6,78,Rural,Data Analyst,54554,0 +20443,Male,42,Masters,2,21,59,67,1,5.0,3,3,Urban,Data Analyst,25971,0 +20444,Female,43,Bachelors,6,79,42,8,37,9.0,2,13,Semi-Urban,HR Executive,87942,0 +20445,Male,30,Bachelors,4,44,85,10,38,2.0,4,10,Urban,Manager,103532,0 +20446,Female,27,Bachelors,9,77,9,7,67,7.0,2,68,Rural,Software Engineer,132847,0 +20447,Male,54,Masters,3,95,91,38,57,4.0,0,48,Urban,ML Engineer,44695,1 +20448,Male,50,Diploma,2,24,3,40,71,9.0,5,43,Rural,Data Analyst,103281,0 +20449,Male,39,Masters,0,29,43,63,14,6.0,5,26,Urban,ML Engineer,42282,0 +20450,Female,35,Diploma,11,12,21,59,26,9.0,6,13,Urban,Software Engineer,98560,0 +20451,Female,56,Diploma,15,65,55,86,92,1.0,0,88,Rural,HR Executive,101839,1 +20452,Other,59,Diploma,11,58,38,44,44,4.0,2,17,Urban,ML Engineer,37033,0 +20453,Female,49,Diploma,9,40,38,15,6,5.0,3,67,Urban,Data Analyst,82810,0 +20454,Female,55,Masters,16,98,45,72,98,7.0,2,54,Urban,ML Engineer,112949,1 +20455,Female,22,PhD,12,2,52,17,88,3.0,7,92,Urban,ML Engineer,108830,0 +20456,Female,45,Bachelors,12,65,90,26,23,4.0,6,91,Rural,ML Engineer,91546,1 +20457,Male,55,Bachelors,19,25,9,82,83,0.0,7,99,Urban,Data Analyst,26603,0 +20458,Male,28,Bachelors,16,54,15,5,89,1.0,0,42,Rural,Software Engineer,23862,0 +20459,Male,56,Diploma,9,58,69,42,56,1.0,1,64,Rural,HR Executive,29055,0 +20460,Male,39,PhD,14,53,50,34,17,8.0,5,52,Semi-Urban,HR Executive,135601,0 +20461,Male,25,High School,8,82,80,95,24,8.0,7,46,Urban,Software Engineer,100670,1 +20462,Male,51,High School,13,58,59,44,74,6.0,7,22,Semi-Urban,Software Engineer,28194,0 +20463,Male,58,High School,10,29,6,52,27,4.0,2,2,Urban,Software Engineer,110579,0 +20464,Male,27,Diploma,19,37,89,48,60,9.0,7,88,Rural,HR Executive,46659,1 +20465,Other,48,Masters,14,53,34,71,20,5.0,3,98,Urban,Data Analyst,71297,1 +20466,Male,32,Bachelors,10,30,1,79,19,5.0,6,86,Urban,HR Executive,107120,0 +20467,Male,53,Diploma,2,84,0,64,98,4.0,6,97,Semi-Urban,ML Engineer,135233,1 +20468,Female,22,Bachelors,19,71,97,98,54,8.0,5,33,Urban,ML Engineer,25986,1 +20469,Male,35,Bachelors,2,83,22,24,27,9.0,1,97,Urban,HR Executive,24946,0 +20470,Male,33,Masters,14,1,28,87,50,1.0,5,32,Urban,Data Analyst,32766,0 +20471,Male,25,High School,1,29,58,31,58,6.0,2,1,Rural,Data Analyst,149325,0 +20472,Male,59,Bachelors,6,36,40,11,64,9.0,1,51,Urban,HR Executive,78032,0 +20473,Male,31,Diploma,12,66,19,15,8,7.0,4,22,Semi-Urban,HR Executive,111030,0 +20474,Male,24,Bachelors,10,81,31,79,43,2.0,4,51,Urban,HR Executive,32936,1 +20475,Male,53,Diploma,15,34,58,84,80,5.0,7,36,Rural,HR Executive,80789,0 +20476,Female,37,Diploma,15,87,21,10,53,4.0,5,95,Semi-Urban,Software Engineer,114608,0 +20477,Male,21,Masters,1,66,60,83,2,8.0,1,49,Semi-Urban,HR Executive,83530,1 +20478,Female,51,Diploma,19,79,21,52,81,0.0,0,33,Rural,HR Executive,47512,0 +20479,Male,33,High School,2,37,53,27,14,1.0,1,46,Semi-Urban,Data Analyst,51936,0 +20480,Male,48,Bachelors,11,23,22,24,75,0.0,4,99,Urban,Data Analyst,134141,0 +20481,Female,55,Bachelors,3,67,83,97,20,4.0,3,84,Urban,HR Executive,57029,1 +20482,Male,54,Masters,10,17,78,48,97,4.0,0,17,Semi-Urban,Data Analyst,116466,0 +20483,Female,57,Masters,6,16,9,35,78,7.0,5,41,Urban,Data Analyst,65908,0 +20484,Male,48,Masters,8,41,7,12,4,9.0,3,38,Urban,Data Analyst,83539,0 +20485,Female,29,High School,5,2,69,60,21,5.0,0,46,Rural,HR Executive,36115,0 +20486,Male,30,Bachelors,11,33,26,82,40,0.0,1,85,Rural,Software Engineer,46441,0 +20487,Male,29,Bachelors,18,62,68,15,99,1.0,1,42,Urban,ML Engineer,148540,0 +20488,Female,29,Bachelors,13,29,22,93,47,7.0,0,23,Semi-Urban,Software Engineer,41164,0 +20489,Female,56,Masters,16,94,2,52,49,5.0,4,56,Semi-Urban,ML Engineer,45210,0 +20490,Male,56,Bachelors,18,14,3,18,49,0.0,6,94,Urban,Software Engineer,24183,0 +20491,Other,58,High School,19,98,78,11,4,4.0,7,30,Urban,Software Engineer,149799,0 +20492,Male,41,PhD,14,75,6,92,95,0.0,2,94,Urban,Data Analyst,26448,1 +20493,Male,51,Diploma,1,60,1,20,78,8.0,6,29,Semi-Urban,Software Engineer,77425,0 +20494,Male,38,Diploma,14,99,46,91,29,7.0,0,87,Rural,Manager,68020,1 +20495,Female,54,Bachelors,17,51,54,20,76,8.0,6,93,Urban,HR Executive,43752,0 +20496,Other,33,High School,11,82,17,18,92,3.0,2,94,Rural,Software Engineer,47629,0 +20497,Male,56,Masters,3,34,25,62,28,8.0,0,2,Urban,HR Executive,136814,0 +20498,Male,46,High School,16,61,50,8,6,2.0,4,74,Urban,Manager,75444,0 +20499,Female,59,Bachelors,19,95,29,39,15,4.0,1,53,Rural,Data Analyst,124052,0 +20500,Male,57,Bachelors,13,93,0,29,80,4.0,5,3,Urban,Manager,58080,0 +20501,Male,45,Masters,1,1,11,93,95,9.0,5,32,Urban,Data Analyst,130247,0 +20502,Male,55,Bachelors,19,66,63,50,63,8.0,3,25,Urban,HR Executive,94960,0 +20503,Male,28,High School,10,65,55,35,26,4.0,3,43,Urban,ML Engineer,30669,0 +20504,Male,55,Masters,10,46,77,33,89,7.0,6,20,Semi-Urban,Data Analyst,124871,0 +20505,Male,55,Diploma,10,85,53,69,53,6.0,6,48,Semi-Urban,Manager,64438,1 +20506,Female,35,PhD,17,47,60,25,4,3.0,0,68,Semi-Urban,Manager,123391,0 +20507,Female,49,Diploma,11,20,35,54,56,9.0,2,59,Urban,Software Engineer,45635,0 +20508,Male,40,Diploma,17,34,60,10,49,5.0,0,71,Rural,ML Engineer,128531,0 +20509,Male,52,Bachelors,7,6,68,43,13,0.0,5,84,Semi-Urban,Manager,119029,0 +20510,Male,47,Diploma,13,57,90,39,85,9.0,4,36,Urban,Software Engineer,59808,0 +20511,Male,58,PhD,5,54,15,0,99,9.0,4,82,Urban,Software Engineer,29331,0 +20512,Female,33,Diploma,17,41,6,59,53,7.0,3,35,Urban,ML Engineer,71121,0 +20513,Other,25,Bachelors,9,49,37,65,31,9.0,0,12,Rural,Data Analyst,144634,0 +20514,Female,51,Diploma,18,73,19,97,4,0.0,1,46,Semi-Urban,ML Engineer,149049,0 +20515,Female,32,Bachelors,11,1,60,76,58,1.0,1,42,Urban,HR Executive,118736,0 +20516,Male,39,Bachelors,15,74,91,87,59,5.0,7,34,Semi-Urban,ML Engineer,58678,1 +20517,Male,41,High School,13,90,44,54,31,9.0,1,88,Semi-Urban,HR Executive,123616,1 +20518,Female,59,Diploma,8,17,74,92,14,4.0,4,87,Urban,Software Engineer,135319,1 +20519,Other,23,Bachelors,18,50,25,31,53,8.0,0,10,Semi-Urban,HR Executive,63795,0 +20520,Male,30,Diploma,0,85,82,14,81,5.0,5,14,Urban,Software Engineer,103131,0 +20521,Male,50,High School,9,27,4,79,21,9.0,2,33,Urban,Software Engineer,99754,0 +20522,Female,27,Diploma,13,94,84,80,35,1.0,2,12,Urban,Manager,126779,1 +20523,Male,53,Bachelors,8,82,26,50,98,0.0,1,25,Urban,Software Engineer,122373,0 +20524,Female,37,Diploma,16,44,38,23,94,1.0,1,68,Urban,Software Engineer,101453,0 +20525,Female,26,Bachelors,15,39,87,28,57,5.0,6,28,Semi-Urban,HR Executive,23632,0 +20526,Male,22,Bachelors,11,63,35,33,74,4.0,2,36,Semi-Urban,HR Executive,57324,0 +20527,Other,27,Masters,1,82,38,16,89,2.0,7,35,Urban,Data Analyst,42177,0 +20528,Other,57,Bachelors,17,99,82,19,66,4.0,5,46,Rural,ML Engineer,62257,1 +20529,Female,33,Bachelors,17,49,40,92,25,6.0,4,78,Urban,Data Analyst,132178,1 +20530,Male,36,Bachelors,10,22,55,86,68,5.0,2,54,Semi-Urban,Software Engineer,35879,0 +20531,Male,37,Bachelors,19,85,76,37,87,8.0,0,17,Urban,HR Executive,57096,0 +20532,Male,28,Diploma,3,63,38,84,37,7.0,0,67,Urban,Manager,96672,1 +20533,Male,55,Bachelors,11,19,68,81,54,8.0,6,41,Semi-Urban,Manager,119225,0 +20534,Male,48,High School,1,12,71,9,70,6.0,6,67,Rural,ML Engineer,117902,0 +20535,Male,32,Diploma,9,25,97,11,73,1.0,7,99,Urban,Data Analyst,83088,0 +20536,Female,43,Bachelors,13,60,38,4,91,7.0,0,36,Urban,ML Engineer,143596,0 +20537,Male,40,Bachelors,4,25,14,20,13,1.0,4,76,Urban,ML Engineer,135962,0 +20538,Male,21,Bachelors,14,75,28,15,34,2.0,4,85,Urban,Manager,40051,0 +20539,Male,25,Masters,6,42,68,9,49,3.0,2,76,Urban,Manager,113842,0 +20540,Female,30,Bachelors,17,72,63,11,89,3.0,0,14,Urban,ML Engineer,131855,0 +20541,Female,49,Bachelors,19,10,91,53,27,0.0,2,63,Urban,ML Engineer,65000,0 +20542,Male,38,Bachelors,7,34,95,54,82,5.0,3,16,Semi-Urban,HR Executive,72766,0 +20543,Other,59,Bachelors,6,62,48,46,27,3.0,0,90,Semi-Urban,Data Analyst,30912,1 +20544,Male,28,Masters,0,9,58,7,70,7.0,2,99,Urban,Manager,143073,0 +20545,Male,27,Masters,2,14,61,83,45,2.0,1,41,Urban,HR Executive,108845,0 +20546,Female,41,Bachelors,13,78,52,52,8,7.0,3,61,Urban,ML Engineer,20200,1 +20547,Female,21,Masters,2,33,81,85,8,1.0,4,37,Urban,Software Engineer,23427,0 +20548,Male,34,Masters,0,46,39,39,82,0.0,6,41,Urban,Data Analyst,29121,0 +20549,Female,31,Bachelors,14,89,36,19,42,0.0,5,86,Rural,Software Engineer,84036,0 +20550,Female,53,PhD,4,73,28,62,90,5.0,5,1,Semi-Urban,Manager,149685,0 +20551,Male,35,Bachelors,18,71,40,88,90,4.0,0,1,Urban,ML Engineer,120499,0 +20552,Male,33,Masters,14,8,68,2,85,4.0,2,23,Urban,HR Executive,54951,0 +20553,Male,38,Diploma,17,35,56,2,49,4.0,3,65,Urban,ML Engineer,108282,0 +20554,Male,53,PhD,6,73,62,48,82,7.0,0,99,Urban,HR Executive,76217,1 +20555,Male,22,Masters,2,62,94,29,42,9.0,4,80,Urban,Software Engineer,122589,1 +20556,Female,21,Diploma,4,95,20,35,15,6.0,6,28,Urban,Software Engineer,129626,0 +20557,Male,58,High School,16,41,21,75,12,2.0,5,12,Urban,Manager,27767,0 +20558,Female,54,Masters,7,23,88,17,30,1.0,7,73,Rural,HR Executive,31552,0 +20559,Male,45,Diploma,19,70,5,83,74,7.0,2,1,Urban,ML Engineer,148884,0 +20560,Male,42,Bachelors,0,63,19,90,84,6.0,0,61,Rural,Manager,107134,0 +20561,Male,21,High School,1,32,33,41,17,6.0,2,44,Semi-Urban,Manager,35294,0 +20562,Male,32,Diploma,17,10,63,59,68,3.0,7,64,Rural,ML Engineer,47843,0 +20563,Male,36,High School,6,83,40,23,49,2.0,0,8,Urban,ML Engineer,128947,0 +20564,Female,39,Masters,10,99,81,13,21,6.0,7,99,Semi-Urban,Data Analyst,134228,1 +20565,Female,54,Masters,10,94,97,9,16,0.0,0,83,Urban,ML Engineer,129557,1 +20566,Male,33,Masters,15,98,70,57,17,9.0,7,3,Rural,HR Executive,47746,0 +20567,Female,59,High School,0,7,38,49,71,4.0,4,36,Urban,Manager,127998,0 +20568,Male,35,Bachelors,0,41,48,6,82,1.0,0,25,Semi-Urban,HR Executive,97098,0 +20569,Male,48,Bachelors,6,86,29,55,6,9.0,1,48,Urban,Software Engineer,55414,0 +20570,Male,25,Diploma,1,11,19,30,35,2.0,4,47,Urban,Manager,133573,0 +20571,Female,56,Diploma,11,40,26,7,11,4.0,0,49,Semi-Urban,HR Executive,96205,0 +20572,Male,51,Bachelors,8,53,86,52,93,0.0,5,79,Rural,HR Executive,133583,1 +20573,Male,34,Bachelors,18,7,30,20,76,9.0,3,17,Urban,ML Engineer,137922,0 +20574,Male,45,Diploma,14,77,85,40,45,8.0,2,66,Rural,Data Analyst,74679,1 +20575,Female,24,Diploma,10,15,97,46,91,2.0,2,97,Urban,Software Engineer,36474,1 +20576,Female,58,Bachelors,11,27,61,89,70,3.0,5,8,Semi-Urban,Data Analyst,87390,0 +20577,Female,49,Diploma,14,98,43,88,0,9.0,5,16,Urban,HR Executive,28776,1 +20578,Female,23,Bachelors,18,8,47,84,64,0.0,0,44,Semi-Urban,Data Analyst,148267,0 +20579,Male,53,Bachelors,8,1,68,59,75,7.0,2,90,Urban,Software Engineer,112666,0 +20580,Female,27,PhD,12,80,35,28,77,7.0,6,51,Semi-Urban,Data Analyst,71204,0 +20581,Female,41,High School,16,91,61,16,93,1.0,1,59,Semi-Urban,Software Engineer,34440,0 +20582,Male,26,Bachelors,16,17,76,19,92,5.0,6,19,Semi-Urban,Data Analyst,24249,0 +20583,Male,29,Bachelors,6,78,21,72,78,0.0,7,45,Urban,Software Engineer,77240,0 +20584,Male,27,Masters,15,98,54,77,5,2.0,2,43,Urban,Data Analyst,113675,1 +20585,Male,27,Diploma,14,13,27,4,16,4.0,0,20,Rural,HR Executive,131647,0 +20586,Female,25,Masters,15,99,72,27,1,2.0,7,26,Urban,Data Analyst,61721,0 +20587,Male,22,High School,0,88,45,16,13,4.0,1,64,Urban,HR Executive,57624,0 +20588,Male,54,Bachelors,3,73,18,28,32,0.0,6,59,Urban,ML Engineer,129589,0 +20589,Female,59,Diploma,17,15,49,9,6,8.0,5,37,Urban,Data Analyst,37283,0 +20590,Male,27,Bachelors,12,28,87,43,80,3.0,2,37,Urban,Manager,31147,0 +20591,Male,52,Diploma,17,51,3,54,31,1.0,6,72,Semi-Urban,Data Analyst,133919,0 +20592,Female,27,Masters,14,90,96,93,49,7.0,4,45,Semi-Urban,Software Engineer,92901,1 +20593,Male,58,Diploma,17,30,63,16,35,2.0,5,48,Urban,HR Executive,125314,0 +20594,Female,28,Diploma,17,87,44,87,62,5.0,7,70,Semi-Urban,Software Engineer,122571,1 +20595,Male,26,Bachelors,12,32,7,41,21,8.0,1,65,Urban,Data Analyst,110488,0 +20596,Male,54,Bachelors,17,52,56,32,34,5.0,4,27,Urban,Data Analyst,104340,0 +20597,Male,38,Bachelors,13,28,87,80,43,3.0,0,22,Urban,Software Engineer,114836,0 +20598,Male,39,Diploma,19,90,96,52,10,3.0,1,9,Semi-Urban,HR Executive,112431,1 +20599,Other,23,High School,5,71,90,62,25,9.0,1,55,Rural,Software Engineer,81945,1 +20600,Other,43,Masters,8,2,62,60,40,5.0,7,36,Urban,Data Analyst,114849,0 +20601,Female,25,Bachelors,11,80,98,55,34,7.0,2,24,Urban,ML Engineer,37952,1 +20602,Male,39,Bachelors,2,65,47,85,45,0.0,0,65,Urban,HR Executive,35029,1 +20603,Other,36,High School,13,42,68,60,50,5.0,7,38,Urban,Manager,55956,0 +20604,Female,44,Bachelors,0,44,66,8,79,0.0,5,44,Rural,ML Engineer,42615,0 +20605,Male,24,Diploma,2,0,65,78,37,7.0,7,56,Semi-Urban,Software Engineer,133846,0 +20606,Female,56,Diploma,18,24,95,95,33,1.0,3,51,Semi-Urban,Software Engineer,145745,1 +20607,Male,59,Diploma,2,71,43,21,35,9.0,0,60,Rural,Data Analyst,89477,0 +20608,Male,41,Bachelors,3,1,65,43,75,1.0,3,90,Semi-Urban,Data Analyst,67876,0 +20609,Female,21,Masters,0,35,3,75,30,7.0,2,24,Urban,HR Executive,31518,0 +20610,Female,39,Bachelors,8,9,6,65,33,8.0,6,34,Urban,ML Engineer,84600,0 +20611,Male,43,High School,12,17,51,11,66,2.0,2,62,Rural,Software Engineer,83821,0 +20612,Male,51,Masters,6,62,26,7,83,6.0,5,53,Rural,Data Analyst,77252,0 +20613,Female,27,Diploma,6,41,66,99,97,6.0,1,88,Semi-Urban,HR Executive,63539,1 +20614,Female,43,Masters,5,63,5,36,72,3.0,3,0,Semi-Urban,ML Engineer,95511,0 +20615,Male,32,Bachelors,17,53,61,98,19,0.0,3,44,Semi-Urban,ML Engineer,51951,1 +20616,Male,50,High School,1,5,52,85,92,1.0,3,45,Semi-Urban,Data Analyst,137682,0 +20617,Male,59,Bachelors,12,20,72,5,75,1.0,5,42,Urban,HR Executive,144298,0 +20618,Other,56,Masters,12,67,37,79,46,2.0,5,49,Urban,Software Engineer,143019,0 +20619,Male,35,Masters,11,88,35,78,23,2.0,3,8,Urban,HR Executive,123044,0 +20620,Male,53,High School,0,4,32,66,17,6.0,6,90,Rural,HR Executive,72771,0 +20621,Male,55,High School,3,92,20,72,97,7.0,4,26,Urban,Software Engineer,41482,0 +20622,Female,50,Masters,11,96,96,27,67,1.0,5,65,Urban,Data Analyst,58316,1 +20623,Female,46,Diploma,8,10,17,90,49,0.0,5,12,Semi-Urban,Software Engineer,122375,0 +20624,Female,51,Diploma,13,16,72,6,8,1.0,1,17,Rural,Software Engineer,45007,0 +20625,Male,58,Masters,12,68,15,37,69,0.0,2,33,Rural,Manager,133721,0 +20626,Male,43,Diploma,15,53,75,7,5,7.0,3,48,Urban,Software Engineer,26133,0 +20627,Female,29,Diploma,19,9,80,39,16,5.0,2,12,Urban,Data Analyst,141254,0 +20628,Female,48,Masters,5,98,48,76,43,9.0,6,16,Urban,Software Engineer,110168,0 +20629,Female,42,Masters,6,8,60,8,90,4.0,5,56,Semi-Urban,Software Engineer,123678,0 +20630,Female,25,Diploma,7,6,69,44,67,8.0,1,48,Urban,ML Engineer,134572,0 +20631,Female,34,Diploma,16,31,77,45,57,1.0,0,54,Urban,Data Analyst,69419,0 +20632,Female,27,Masters,18,40,98,10,24,2.0,2,34,Urban,Data Analyst,103627,0 +20633,Female,55,Masters,3,76,47,60,62,5.0,1,4,Urban,Software Engineer,130688,0 +20634,Female,35,Masters,7,4,70,76,93,5.0,1,70,Urban,Manager,74565,0 +20635,Male,39,Bachelors,4,81,30,15,26,2.0,4,95,Urban,Software Engineer,88271,0 +20636,Male,23,Bachelors,3,4,61,20,5,8.0,2,93,Rural,Manager,87450,0 +20637,Other,38,High School,6,86,62,15,85,9.0,2,62,Semi-Urban,HR Executive,41911,0 +20638,Male,33,Bachelors,18,94,70,79,94,3.0,7,47,Rural,Manager,40890,1 +20639,Female,33,High School,12,34,91,81,87,9.0,4,55,Semi-Urban,Software Engineer,39491,1 +20640,Male,49,PhD,6,12,62,43,94,5.0,0,0,Urban,Data Analyst,71543,0 +20641,Male,23,High School,10,78,16,28,97,1.0,2,49,Rural,Manager,140316,0 +20642,Male,46,Masters,9,62,87,31,49,9.0,3,15,Rural,Manager,125160,0 +20643,Male,55,Bachelors,9,70,31,78,62,1.0,2,71,Rural,Manager,93787,1 +20644,Male,24,Bachelors,1,58,20,7,83,8.0,6,7,Semi-Urban,Software Engineer,98598,0 +20645,Male,44,Masters,18,96,16,84,49,0.0,7,28,Rural,ML Engineer,31948,0 +20646,Female,29,Diploma,3,15,52,56,32,9.0,4,33,Semi-Urban,HR Executive,124649,0 +20647,Male,33,Bachelors,17,20,21,41,57,9.0,4,54,Urban,Data Analyst,146265,0 +20648,Male,47,Masters,14,85,25,48,99,8.0,7,76,Rural,Manager,96127,0 +20649,Male,22,Masters,3,29,3,2,69,9.0,2,79,Urban,HR Executive,113156,0 +20650,Female,40,Bachelors,18,98,5,81,58,1.0,4,43,Urban,Data Analyst,98164,0 +20651,Female,35,Diploma,6,67,53,27,14,3.0,1,51,Semi-Urban,Software Engineer,120246,0 +20652,Female,32,Bachelors,1,33,96,3,73,3.0,1,16,Rural,ML Engineer,61598,0 +20653,Male,22,High School,3,59,52,83,69,7.0,5,78,Semi-Urban,ML Engineer,89298,1 +20654,Male,59,Diploma,5,21,54,34,78,8.0,0,5,Semi-Urban,HR Executive,120758,0 +20655,Female,36,Diploma,4,2,49,64,42,2.0,0,46,Urban,Data Analyst,129298,0 +20656,Female,48,Bachelors,17,47,69,47,40,1.0,2,24,Urban,ML Engineer,62283,0 +20657,Male,56,Bachelors,9,7,9,52,28,8.0,6,46,Urban,Manager,105794,0 +20658,Male,43,Bachelors,10,36,25,64,39,9.0,2,30,Urban,ML Engineer,112782,0 +20659,Male,27,Diploma,19,46,44,22,37,1.0,6,38,Urban,ML Engineer,40807,0 +20660,Male,35,Bachelors,5,9,41,69,79,3.0,5,77,Rural,Software Engineer,43198,0 +20661,Female,59,Masters,16,24,45,39,9,9.0,2,40,Urban,ML Engineer,148846,0 +20662,Male,55,Bachelors,5,30,94,76,31,3.0,2,97,Semi-Urban,Manager,22261,1 +20663,Male,23,Diploma,18,56,94,81,41,3.0,7,59,Rural,HR Executive,40582,1 +20664,Male,45,High School,8,77,8,89,47,2.0,5,84,Rural,Manager,140897,1 +20665,Other,56,Bachelors,19,31,42,11,7,2.0,3,31,Semi-Urban,ML Engineer,47982,0 +20666,Female,55,High School,17,22,38,95,97,8.0,2,33,Rural,HR Executive,129514,0 +20667,Female,30,Bachelors,9,85,17,28,2,5.0,4,88,Urban,Manager,96897,0 +20668,Male,33,Bachelors,1,43,63,93,51,4.0,1,83,Urban,Data Analyst,131325,1 +20669,Female,44,Masters,12,77,32,46,71,0.0,1,49,Rural,Software Engineer,115991,0 +20670,Male,25,High School,13,33,59,62,97,4.0,1,41,Urban,HR Executive,95003,0 +20671,Male,37,Bachelors,8,32,33,9,25,0.0,0,79,Urban,Software Engineer,65986,0 +20672,Male,45,Bachelors,16,39,0,13,49,6.0,3,52,Urban,ML Engineer,65778,0 +20673,Male,33,High School,18,59,11,19,59,1.0,6,61,Semi-Urban,Data Analyst,110482,0 +20674,Male,58,Bachelors,17,83,69,45,15,2.0,4,26,Urban,Software Engineer,127584,0 +20675,Female,33,High School,12,96,85,71,51,2.0,5,50,Urban,HR Executive,69419,1 +20676,Male,32,PhD,13,95,95,62,62,1.0,2,26,Semi-Urban,Manager,118187,1 +20677,Male,49,Diploma,14,43,90,22,9,9.0,4,97,Urban,ML Engineer,44046,1 +20678,Male,32,Bachelors,3,65,4,17,64,8.0,7,59,Urban,ML Engineer,92543,0 +20679,Male,45,Bachelors,13,38,88,1,71,7.0,1,20,Urban,Data Analyst,51666,0 +20680,Male,49,Masters,19,79,28,66,67,0.0,2,5,Urban,HR Executive,59397,0 +20681,Male,23,High School,8,44,71,34,73,6.0,0,67,Urban,HR Executive,85729,0 +20682,Male,52,Diploma,3,21,9,11,6,4.0,0,31,Urban,ML Engineer,120057,0 +20683,Male,41,Bachelors,14,76,19,76,4,2.0,5,7,Rural,Software Engineer,46662,0 +20684,Male,27,Masters,3,7,73,63,18,9.0,0,85,Urban,ML Engineer,102984,0 +20685,Male,23,High School,18,94,82,44,78,5.0,7,92,Semi-Urban,Software Engineer,31220,1 +20686,Male,28,Masters,4,92,76,94,99,5.0,1,96,Urban,HR Executive,93627,1 +20687,Male,27,Diploma,17,72,11,51,26,5.0,1,9,Semi-Urban,Software Engineer,75012,0 +20688,Male,36,PhD,0,76,62,25,59,1.0,7,93,Urban,Manager,77815,1 +20689,Female,41,Masters,5,35,12,48,60,3.0,3,53,Semi-Urban,ML Engineer,34421,0 +20690,Male,35,Masters,8,59,44,3,10,6.0,1,95,Urban,Data Analyst,134215,0 +20691,Male,57,Bachelors,15,25,72,77,63,0.0,0,35,Urban,ML Engineer,21267,0 +20692,Female,50,High School,10,31,24,10,13,3.0,3,73,Semi-Urban,HR Executive,106717,0 +20693,Female,48,Diploma,3,87,70,41,28,5.0,6,93,Urban,Data Analyst,142736,1 +20694,Other,27,High School,2,94,36,77,78,3.0,1,90,Urban,Software Engineer,38840,1 +20695,Female,49,Diploma,5,77,37,32,59,4.0,5,65,Semi-Urban,ML Engineer,27529,0 +20696,Male,52,Masters,14,41,42,1,39,1.0,2,37,Semi-Urban,Manager,24526,0 +20697,Male,41,Masters,2,64,67,81,30,9.0,0,49,Semi-Urban,Software Engineer,46268,1 +20698,Female,28,Diploma,3,26,48,90,85,8.0,5,83,Urban,Data Analyst,118549,1 +20699,Other,26,Bachelors,4,90,36,3,97,4.0,3,84,Urban,Software Engineer,103125,0 +20700,Female,50,Bachelors,12,18,57,81,61,0.0,1,17,Semi-Urban,Software Engineer,94626,0 +20701,Female,23,PhD,7,40,44,49,11,6.0,2,1,Urban,Data Analyst,20607,0 +20702,Male,35,Masters,3,86,59,34,13,7.0,0,87,Semi-Urban,ML Engineer,32886,1 +20703,Male,48,High School,13,95,5,9,49,7.0,7,36,Urban,Software Engineer,140290,0 +20704,Female,36,Bachelors,5,83,10,8,43,5.0,0,3,Urban,HR Executive,38201,0 +20705,Female,49,High School,9,59,63,4,10,6.0,7,58,Semi-Urban,ML Engineer,119353,0 +20706,Other,48,Masters,17,59,55,75,60,9.0,4,61,Urban,Manager,128213,1 +20707,Female,25,Bachelors,13,14,73,43,88,7.0,4,45,Urban,Software Engineer,122297,0 +20708,Male,50,High School,19,69,74,13,93,2.0,6,79,Rural,Manager,87755,1 +20709,Male,32,Bachelors,4,36,55,86,61,5.0,4,11,Urban,ML Engineer,148337,0 +20710,Female,22,Bachelors,18,55,56,3,0,4.0,1,44,Rural,Data Analyst,48681,0 +20711,Male,42,Bachelors,19,28,59,98,75,0.0,7,66,Rural,Data Analyst,142384,1 +20712,Male,57,Masters,16,86,96,47,85,0.0,4,70,Semi-Urban,Software Engineer,52337,1 +20713,Male,35,Bachelors,11,43,15,86,85,5.0,5,24,Urban,Manager,46952,0 +20714,Male,38,Masters,14,84,67,62,17,9.0,4,42,Urban,HR Executive,105777,1 +20715,Male,25,Bachelors,15,56,59,5,12,4.0,7,98,Semi-Urban,Manager,49621,0 +20716,Female,53,High School,0,19,55,11,36,3.0,1,24,Urban,ML Engineer,87757,0 +20717,Male,23,Diploma,11,60,54,80,30,7.0,6,66,Urban,HR Executive,21180,1 +20718,Male,49,Bachelors,4,12,16,7,65,7.0,0,20,Urban,Manager,75469,0 +20719,Female,54,Bachelors,12,34,86,31,98,4.0,4,9,Semi-Urban,Manager,63037,0 +20720,Male,28,Bachelors,2,60,64,32,98,6.0,4,41,Rural,HR Executive,65305,0 +20721,Female,47,Bachelors,7,24,31,67,2,7.0,2,81,Rural,HR Executive,100137,0 +20722,Male,48,Masters,8,62,65,64,37,9.0,3,15,Semi-Urban,ML Engineer,134761,0 +20723,Other,27,Masters,13,43,81,94,63,5.0,0,17,Semi-Urban,Data Analyst,149751,0 +20724,Male,26,Bachelors,4,39,85,9,71,0.0,7,3,Urban,HR Executive,77809,0 +20725,Male,26,Diploma,9,82,97,45,55,5.0,4,46,Rural,Manager,138928,1 +20726,Female,42,Bachelors,7,45,14,80,11,0.0,4,72,Urban,Data Analyst,95678,0 +20727,Female,43,Bachelors,1,60,32,67,4,0.0,6,5,Rural,Manager,54071,0 +20728,Male,48,Bachelors,13,89,56,73,3,4.0,5,77,Urban,Software Engineer,137297,1 +20729,Other,46,High School,17,84,2,11,44,1.0,7,79,Urban,HR Executive,129842,0 +20730,Male,53,Bachelors,0,2,72,50,9,2.0,2,38,Urban,Data Analyst,66967,0 +20731,Other,44,Masters,9,89,44,53,83,6.0,5,17,Semi-Urban,ML Engineer,44399,0 +20732,Male,35,Bachelors,18,38,89,58,79,1.0,7,42,Urban,Data Analyst,142521,0 +20733,Male,31,Bachelors,4,0,99,86,1,2.0,3,8,Urban,ML Engineer,97221,0 +20734,Male,41,Bachelors,10,20,81,20,8,8.0,6,25,Rural,Data Analyst,33271,0 +20735,Male,42,Diploma,16,95,32,17,38,4.0,2,86,Rural,ML Engineer,31145,0 +20736,Male,55,Masters,4,64,98,26,0,2.0,2,98,Urban,Manager,20443,1 +20737,Male,32,Diploma,7,2,43,25,45,5.0,2,61,Urban,Software Engineer,146237,0 +20738,Male,33,Bachelors,6,19,75,92,39,8.0,1,59,Semi-Urban,Data Analyst,30857,1 +20739,Male,55,Masters,6,45,49,17,20,6.0,5,82,Semi-Urban,Software Engineer,124580,0 +20740,Male,44,Masters,2,8,88,5,61,9.0,3,16,Urban,Manager,28542,0 +20741,Female,23,Bachelors,11,89,4,39,89,5.0,3,35,Urban,HR Executive,63805,0 +20742,Male,44,Diploma,15,43,6,26,25,1.0,6,63,Urban,ML Engineer,87004,0 +20743,Female,56,High School,4,49,63,54,7,2.0,7,92,Rural,Manager,148553,1 +20744,Other,33,Bachelors,14,71,43,2,22,2.0,7,38,Semi-Urban,HR Executive,85669,0 +20745,Female,47,Bachelors,5,21,27,77,13,5.0,7,4,Urban,Manager,75589,0 +20746,Other,30,Diploma,1,98,30,89,85,7.0,4,15,Semi-Urban,HR Executive,111979,0 +20747,Male,43,Diploma,15,71,69,55,65,5.0,6,28,Urban,Software Engineer,149167,0 +20748,Male,59,High School,16,59,15,43,17,0.0,5,72,Urban,Data Analyst,125744,0 +20749,Male,32,Diploma,12,72,45,99,36,9.0,7,92,Semi-Urban,HR Executive,22912,1 +20750,Male,38,High School,17,96,94,45,20,1.0,7,35,Urban,Data Analyst,148699,1 +20751,Female,39,Bachelors,0,35,63,55,25,0.0,6,38,Urban,Data Analyst,138623,0 +20752,Male,58,Bachelors,19,75,1,62,36,3.0,1,98,Rural,Manager,30701,1 +20753,Male,22,Bachelors,13,79,44,15,27,1.0,0,38,Semi-Urban,ML Engineer,52364,0 +20754,Female,24,Bachelors,17,71,87,40,54,7.0,2,32,Urban,Manager,82278,0 +20755,Male,52,Bachelors,1,89,85,12,43,7.0,6,17,Urban,HR Executive,144218,0 +20756,Male,39,Masters,13,38,17,24,71,0.0,7,5,Rural,HR Executive,64042,0 +20757,Male,53,Bachelors,0,51,90,57,84,2.0,7,68,Urban,Software Engineer,91504,1 +20758,Female,44,Bachelors,0,65,55,39,53,3.0,6,6,Rural,ML Engineer,147279,0 +20759,Female,45,Masters,0,61,9,93,3,5.0,1,68,Semi-Urban,Manager,92507,0 +20760,Male,21,Masters,8,5,13,85,74,6.0,1,58,Urban,Software Engineer,146426,0 +20761,Male,51,Bachelors,16,26,15,35,46,5.0,1,27,Urban,HR Executive,148941,0 +20762,Male,24,High School,0,1,2,77,41,3.0,7,15,Semi-Urban,Software Engineer,148431,0 +20763,Male,50,Masters,5,48,97,36,31,6.0,6,70,Rural,HR Executive,129806,1 +20764,Female,32,Diploma,18,91,50,32,50,5.0,7,79,Rural,ML Engineer,25594,1 +20765,Male,31,PhD,15,76,56,92,4,7.0,4,5,Rural,HR Executive,49138,0 +20766,Male,40,Diploma,11,38,29,58,10,0.0,0,49,Urban,ML Engineer,65467,0 +20767,Female,59,High School,5,52,80,33,1,2.0,7,4,Urban,Data Analyst,118623,0 +20768,Female,38,High School,2,75,97,68,72,1.0,5,79,Urban,ML Engineer,37535,1 +20769,Female,56,Bachelors,9,93,36,5,67,8.0,5,84,Urban,ML Engineer,60070,0 +20770,Male,31,Bachelors,16,48,36,28,40,3.0,7,3,Semi-Urban,HR Executive,39562,0 +20771,Male,22,Bachelors,0,97,42,58,47,0.0,1,61,Urban,Data Analyst,45131,1 +20772,Male,28,Masters,3,95,70,13,31,8.0,5,26,Rural,HR Executive,96656,0 +20773,Female,29,High School,4,56,87,99,90,3.0,7,71,Rural,Software Engineer,81786,1 +20774,Male,46,Diploma,18,3,22,99,24,0.0,6,65,Rural,ML Engineer,144587,0 +20775,Female,53,Diploma,12,86,52,6,88,5.0,5,0,Rural,Data Analyst,111226,0 +20776,Other,27,Bachelors,8,3,74,32,83,5.0,1,91,Semi-Urban,ML Engineer,92982,0 +20777,Male,50,PhD,5,42,58,44,65,8.0,6,66,Semi-Urban,HR Executive,42604,0 +20778,Male,30,Diploma,18,31,74,73,31,4.0,5,81,Semi-Urban,HR Executive,90675,1 +20779,Female,21,Diploma,18,64,44,81,55,1.0,2,19,Urban,ML Engineer,118695,0 +20780,Female,49,Bachelors,15,97,57,62,32,7.0,6,21,Semi-Urban,Data Analyst,121010,0 +20781,Female,23,Bachelors,4,24,56,39,78,7.0,6,27,Semi-Urban,ML Engineer,99609,0 +20782,Male,52,Bachelors,0,71,25,54,1,4.0,7,24,Semi-Urban,Manager,108791,0 +20783,Male,51,PhD,5,80,70,3,52,2.0,6,99,Rural,Manager,121697,1 +20784,Female,24,PhD,0,15,56,42,16,5.0,2,7,Urban,Data Analyst,131039,0 +20785,Female,50,Masters,8,27,61,49,81,8.0,3,85,Urban,HR Executive,136066,0 +20786,Male,36,Bachelors,5,33,31,87,1,5.0,4,52,Rural,Manager,56285,0 +20787,Male,39,Bachelors,2,78,6,82,67,6.0,1,18,Urban,HR Executive,30721,0 +20788,Female,42,High School,15,97,54,75,78,2.0,0,24,Urban,HR Executive,130756,1 +20789,Male,51,Masters,0,19,42,15,98,5.0,0,92,Semi-Urban,Software Engineer,114128,0 +20790,Female,25,Bachelors,19,90,87,47,70,6.0,7,24,Rural,Data Analyst,67979,1 +20791,Male,24,Bachelors,17,81,40,89,57,3.0,1,96,Semi-Urban,Data Analyst,112675,1 +20792,Female,22,Bachelors,6,55,68,18,61,4.0,5,91,Rural,Manager,84518,0 +20793,Female,40,Diploma,4,46,22,79,34,7.0,0,24,Rural,ML Engineer,148693,0 +20794,Male,21,Masters,8,7,12,86,50,5.0,3,2,Semi-Urban,HR Executive,145033,0 +20795,Female,38,Bachelors,16,75,54,23,19,4.0,5,14,Semi-Urban,Data Analyst,129512,0 +20796,Female,56,Masters,4,12,26,52,17,6.0,3,96,Urban,Manager,25702,0 +20797,Female,48,Masters,6,35,82,86,23,9.0,6,77,Semi-Urban,ML Engineer,90854,1 +20798,Male,41,Diploma,16,40,80,89,84,3.0,6,99,Urban,Data Analyst,132760,1 +20799,Female,28,Diploma,19,39,46,79,3,1.0,6,89,Urban,Manager,99961,1 +20800,Female,26,High School,11,78,88,39,11,2.0,7,69,Semi-Urban,ML Engineer,96207,1 +20801,Male,38,Bachelors,16,86,83,70,32,1.0,2,92,Semi-Urban,Software Engineer,136299,1 +20802,Female,57,Bachelors,13,46,32,97,53,9.0,5,78,Urban,ML Engineer,47800,1 +20803,Male,35,Diploma,17,44,28,24,87,4.0,6,29,Semi-Urban,Manager,123409,0 +20804,Male,27,Diploma,15,8,96,95,29,5.0,0,15,Urban,Data Analyst,69226,0 +20805,Male,53,Diploma,4,26,22,80,36,1.0,3,86,Urban,Data Analyst,138281,0 +20806,Male,54,Diploma,4,16,27,77,5,3.0,0,81,Rural,ML Engineer,83741,0 +20807,Female,59,Bachelors,1,2,85,18,67,3.0,7,66,Rural,Manager,30442,0 +20808,Female,24,High School,5,80,6,4,87,5.0,3,37,Rural,Software Engineer,101265,0 +20809,Male,32,Bachelors,2,68,92,92,67,1.0,6,91,Urban,ML Engineer,120004,1 +20810,Female,39,Bachelors,14,81,18,87,66,8.0,7,9,Semi-Urban,HR Executive,121095,0 +20811,Male,36,Bachelors,2,0,70,55,76,8.0,6,91,Semi-Urban,Data Analyst,137048,0 +20812,Male,49,Bachelors,8,23,49,91,49,3.0,1,15,Semi-Urban,HR Executive,144425,0 +20813,Male,29,Bachelors,9,96,67,40,95,1.0,7,79,Rural,HR Executive,123281,1 +20814,Male,55,High School,1,21,25,91,13,7.0,1,45,Semi-Urban,Software Engineer,66065,0 +20815,Male,35,Masters,15,4,35,62,65,8.0,7,76,Urban,ML Engineer,45609,0 +20816,Female,27,Diploma,10,72,17,60,71,7.0,4,4,Semi-Urban,HR Executive,146711,0 +20817,Male,26,Masters,19,28,13,81,10,6.0,2,61,Urban,Software Engineer,142822,0 +20818,Male,47,Bachelors,15,47,10,60,63,3.0,6,20,Rural,Manager,108571,0 +20819,Male,30,High School,18,70,17,62,37,4.0,6,62,Urban,HR Executive,56799,0 +20820,Male,41,High School,14,89,17,34,7,8.0,1,44,Rural,ML Engineer,42708,0 +20821,Female,28,Bachelors,11,94,34,56,83,8.0,4,75,Urban,Manager,76934,1 +20822,Male,39,Bachelors,9,66,57,18,27,7.0,3,4,Urban,Software Engineer,55848,0 +20823,Female,50,Masters,3,9,7,19,87,3.0,1,94,Semi-Urban,Data Analyst,82584,0 +20824,Male,52,Diploma,18,21,48,78,42,5.0,1,91,Urban,HR Executive,127719,1 +20825,Female,26,Bachelors,19,63,53,75,7,5.0,3,48,Semi-Urban,Data Analyst,69099,0 +20826,Male,59,Bachelors,16,4,16,28,23,8.0,4,14,Rural,HR Executive,46371,0 +20827,Other,58,Diploma,7,67,54,78,45,5.0,7,96,Rural,HR Executive,52535,1 +20828,Male,50,High School,12,72,43,98,21,0.0,0,49,Semi-Urban,Data Analyst,20121,1 +20829,Male,32,Masters,1,37,38,48,33,5.0,4,32,Semi-Urban,Manager,63131,0 +20830,Other,23,Diploma,14,72,79,79,6,0.0,4,60,Urban,ML Engineer,92129,1 +20831,Female,33,Diploma,3,45,7,35,36,3.0,3,44,Urban,Software Engineer,125939,0 +20832,Male,38,Bachelors,9,82,9,3,21,7.0,1,84,Semi-Urban,HR Executive,51092,0 +20833,Other,28,Bachelors,16,90,65,2,80,5.0,2,93,Semi-Urban,HR Executive,111693,1 +20834,Female,52,Bachelors,17,60,51,72,90,7.0,3,89,Semi-Urban,Software Engineer,144972,1 +20835,Male,24,Masters,14,69,3,45,69,9.0,0,46,Urban,HR Executive,52522,0 +20836,Male,39,Diploma,4,39,96,92,89,8.0,2,3,Urban,HR Executive,148102,0 +20837,Male,38,Bachelors,4,36,11,91,92,0.0,3,6,Urban,HR Executive,141266,0 +20838,Male,58,High School,3,67,53,42,62,0.0,5,99,Semi-Urban,Data Analyst,47136,1 +20839,Female,32,Bachelors,18,61,6,81,79,6.0,3,71,Urban,ML Engineer,137531,0 +20840,Male,33,Bachelors,0,61,32,47,47,3.0,2,89,Rural,Manager,99319,0 +20841,Male,57,Masters,11,12,84,6,64,3.0,4,40,Rural,Data Analyst,76214,0 +20842,Female,21,High School,15,95,16,24,84,1.0,4,0,Urban,Data Analyst,126517,0 +20843,Male,38,Bachelors,3,4,61,88,12,0.0,5,39,Urban,ML Engineer,102202,0 +20844,Other,55,PhD,3,77,48,85,22,4.0,2,93,Rural,Software Engineer,22549,1 +20845,Other,47,Bachelors,10,8,96,63,46,7.0,3,35,Urban,HR Executive,127077,0 +20846,Female,58,Bachelors,0,65,11,51,7,3.0,2,64,Urban,Data Analyst,132804,0 +20847,Female,44,Bachelors,12,38,19,39,36,7.0,2,51,Urban,ML Engineer,149117,0 +20848,Male,38,Diploma,4,30,54,52,81,0.0,2,19,Urban,Manager,134364,0 +20849,Male,56,Diploma,9,32,49,30,87,4.0,6,0,Urban,Manager,58351,0 +20850,Male,29,Bachelors,17,83,28,40,64,1.0,7,71,Rural,Data Analyst,42760,0 +20851,Male,21,Bachelors,3,16,72,69,68,8.0,1,34,Urban,HR Executive,96220,0 +20852,Female,24,Masters,18,72,27,80,68,1.0,6,81,Urban,Software Engineer,102566,1 +20853,Male,53,High School,10,0,9,13,89,8.0,6,37,Urban,HR Executive,139992,0 +20854,Other,47,Bachelors,11,50,42,17,35,1.0,3,44,Semi-Urban,Data Analyst,98070,0 +20855,Female,22,High School,7,40,3,72,0,7.0,4,16,Rural,Software Engineer,66999,0 +20856,Male,25,Bachelors,19,13,94,80,47,1.0,7,27,Semi-Urban,HR Executive,143035,0 +20857,Male,39,Diploma,6,62,21,21,16,8.0,1,29,Urban,Manager,124796,0 +20858,Male,58,Diploma,17,78,81,5,67,5.0,3,96,Urban,HR Executive,121908,1 +20859,Female,35,Masters,1,60,85,99,69,0.0,4,15,Urban,Manager,51470,1 +20860,Female,46,High School,13,82,70,80,80,3.0,3,53,Urban,Software Engineer,73127,1 +20861,Male,42,Diploma,13,29,77,38,36,5.0,7,20,Urban,Software Engineer,34797,0 +20862,Male,39,Masters,2,59,23,92,77,6.0,0,59,Rural,Manager,135428,0 +20863,Male,24,Diploma,15,99,94,85,99,5.0,5,16,Semi-Urban,HR Executive,21555,1 +20864,Other,40,Diploma,2,49,3,96,16,4.0,0,2,Urban,ML Engineer,141686,0 +20865,Male,43,Masters,14,9,17,89,35,3.0,1,3,Semi-Urban,ML Engineer,23437,0 +20866,Male,26,Diploma,10,64,39,3,18,4.0,0,78,Urban,HR Executive,23828,0 +20867,Female,58,Bachelors,11,40,0,63,51,6.0,7,18,Urban,Manager,43545,0 +20868,Female,41,High School,4,39,59,93,54,8.0,0,98,Semi-Urban,HR Executive,103401,1 +20869,Female,45,Bachelors,3,87,95,60,84,6.0,1,22,Semi-Urban,Manager,125106,1 +20870,Male,45,Masters,19,75,45,90,80,7.0,1,11,Urban,Software Engineer,74827,0 +20871,Female,46,Diploma,2,61,43,81,57,1.0,3,0,Rural,Manager,46068,0 +20872,Male,47,Bachelors,0,82,15,74,76,4.0,4,43,Rural,HR Executive,93178,0 +20873,Male,49,Bachelors,19,60,42,16,67,4.0,5,74,Urban,ML Engineer,70777,0 +20874,Male,42,Diploma,2,44,41,85,11,7.0,7,93,Rural,Manager,98573,1 +20875,Male,38,Masters,18,13,66,42,89,5.0,3,86,Urban,Software Engineer,55515,0 +20876,Male,44,Bachelors,19,74,6,49,91,0.0,7,72,Semi-Urban,Software Engineer,67356,0 +20877,Female,35,Diploma,16,25,96,53,61,1.0,0,11,Urban,HR Executive,27229,0 +20878,Male,26,Bachelors,6,70,30,24,97,5.0,2,53,Semi-Urban,Manager,118108,0 +20879,Female,27,Bachelors,15,21,66,37,48,6.0,0,1,Urban,Data Analyst,63305,0 +20880,Male,49,Bachelors,11,65,65,91,61,1.0,5,65,Semi-Urban,Software Engineer,86395,1 +20881,Male,22,Bachelors,13,3,35,90,49,2.0,7,98,Rural,HR Executive,48875,0 +20882,Female,34,High School,15,78,43,79,65,0.0,7,33,Urban,Software Engineer,107393,0 +20883,Female,42,Masters,2,53,49,10,9,9.0,0,0,Urban,HR Executive,129810,0 +20884,Male,35,High School,14,82,91,85,81,9.0,3,85,Semi-Urban,Data Analyst,143355,1 +20885,Female,33,Bachelors,3,51,65,99,39,1.0,7,60,Urban,Software Engineer,126480,1 +20886,Male,21,Masters,9,75,19,46,19,5.0,3,26,Semi-Urban,Software Engineer,67692,0 +20887,Female,36,Bachelors,15,85,59,74,56,4.0,3,12,Semi-Urban,HR Executive,82089,0 +20888,Male,33,High School,15,33,6,13,90,3.0,7,94,Semi-Urban,ML Engineer,63698,0 +20889,Female,32,Masters,2,46,72,60,47,9.0,6,78,Urban,Manager,75883,1 +20890,Male,58,Masters,16,2,13,83,69,6.0,6,42,Urban,Manager,59404,0 +20891,Female,59,Bachelors,5,63,39,3,28,9.0,3,8,Urban,Data Analyst,24895,0 +20892,Female,33,Bachelors,15,31,7,70,35,7.0,1,89,Urban,Data Analyst,86495,0 +20893,Male,38,Masters,1,12,6,42,54,3.0,6,42,Urban,Manager,117805,0 +20894,Female,28,PhD,12,86,47,34,66,4.0,6,39,Rural,Data Analyst,120867,0 +20895,Male,31,Bachelors,6,32,76,38,17,5.0,6,11,Semi-Urban,Manager,53090,0 +20896,Male,26,Bachelors,14,80,8,70,5,3.0,1,30,Semi-Urban,Data Analyst,141500,0 +20897,Female,24,Bachelors,6,79,38,35,61,7.0,7,58,Semi-Urban,Data Analyst,63645,0 +20898,Male,48,Bachelors,18,50,69,97,81,7.0,4,14,Urban,Manager,69784,0 +20899,Male,43,Bachelors,3,84,54,51,48,7.0,2,12,Semi-Urban,Data Analyst,111499,0 +20900,Male,44,Bachelors,2,36,33,76,4,4.0,4,5,Semi-Urban,Data Analyst,90122,0 +20901,Female,41,Diploma,16,53,47,96,71,8.0,0,25,Urban,Software Engineer,77847,0 +20902,Male,26,Masters,2,80,61,87,20,2.0,2,82,Rural,ML Engineer,26840,1 +20903,Male,45,High School,10,78,62,31,84,6.0,1,10,Semi-Urban,ML Engineer,95005,0 +20904,Female,33,High School,1,53,61,35,0,8.0,3,18,Semi-Urban,Data Analyst,97173,0 +20905,Female,59,High School,10,97,76,84,14,7.0,3,91,Urban,Software Engineer,101977,1 +20906,Female,37,Diploma,8,88,42,36,15,8.0,0,54,Urban,Manager,91398,0 +20907,Female,35,Bachelors,2,27,40,72,2,5.0,0,62,Urban,Data Analyst,99629,0 +20908,Female,33,High School,3,73,57,25,24,7.0,1,28,Rural,HR Executive,35707,0 +20909,Male,36,Bachelors,6,47,78,28,84,0.0,2,88,Urban,Software Engineer,148178,1 +20910,Male,28,Bachelors,13,84,87,17,65,7.0,0,0,Urban,Software Engineer,64761,0 +20911,Female,58,High School,9,17,46,24,66,7.0,5,75,Urban,Data Analyst,65099,0 +20912,Other,29,Masters,2,3,14,36,53,7.0,5,56,Rural,HR Executive,91336,0 +20913,Female,23,Masters,19,27,68,80,43,2.0,1,3,Urban,Software Engineer,65774,0 +20914,Male,33,Bachelors,6,40,11,82,15,1.0,7,85,Semi-Urban,ML Engineer,80300,0 +20915,Male,34,Bachelors,7,15,25,68,24,1.0,4,29,Urban,HR Executive,61585,0 +20916,Female,55,Bachelors,1,23,35,35,7,1.0,4,77,Semi-Urban,HR Executive,137985,0 +20917,Female,50,Bachelors,17,32,23,2,48,2.0,1,10,Urban,ML Engineer,106258,0 +20918,Female,41,Masters,12,2,15,28,35,3.0,6,21,Urban,HR Executive,25063,0 +20919,Male,32,Masters,5,39,9,90,39,2.0,1,18,Rural,ML Engineer,53209,0 +20920,Male,45,Bachelors,9,26,16,94,90,6.0,1,32,Urban,HR Executive,140185,0 +20921,Female,40,Diploma,0,22,45,64,44,0.0,6,41,Urban,Data Analyst,145232,0 +20922,Female,26,Bachelors,12,16,82,91,14,0.0,4,90,Urban,Software Engineer,53176,1 +20923,Male,43,Bachelors,1,0,7,64,59,1.0,0,10,Urban,ML Engineer,118778,0 +20924,Male,41,High School,0,54,69,45,53,4.0,4,31,Urban,Manager,21569,0 +20925,Female,52,High School,19,14,44,51,33,7.0,0,18,Urban,HR Executive,71476,0 +20926,Female,24,Masters,1,50,40,79,48,6.0,5,15,Urban,Manager,143499,0 +20927,Male,38,Bachelors,4,12,59,46,37,1.0,2,60,Urban,HR Executive,102809,0 +20928,Male,52,Bachelors,15,7,51,57,22,2.0,5,94,Urban,ML Engineer,107511,0 +20929,Male,37,Masters,19,92,31,20,1,1.0,7,87,Urban,HR Executive,66397,0 +20930,Male,48,Bachelors,18,69,94,62,2,2.0,4,74,Semi-Urban,Data Analyst,94687,1 +20931,Female,49,High School,11,85,93,87,53,7.0,6,98,Urban,ML Engineer,102638,1 +20932,Male,31,Bachelors,4,44,31,56,42,5.0,1,55,Urban,Data Analyst,81542,0 +20933,Female,33,Masters,16,96,78,92,69,7.0,5,2,Rural,Data Analyst,77396,1 +20934,Female,58,Bachelors,14,93,34,35,65,3.0,5,8,Urban,ML Engineer,89904,0 +20935,Male,42,Masters,10,57,95,57,72,0.0,3,96,Rural,HR Executive,110228,1 +20936,Male,37,Bachelors,7,48,5,58,17,4.0,1,66,Rural,Data Analyst,136247,0 +20937,Male,30,Masters,1,21,13,82,25,6.0,4,46,Urban,Data Analyst,81747,0 +20938,Male,24,Masters,12,15,13,96,13,3.0,7,41,Rural,HR Executive,76546,0 +20939,Male,54,High School,2,62,73,94,23,1.0,7,75,Semi-Urban,Software Engineer,85961,1 +20940,Female,21,Masters,15,99,44,7,47,3.0,3,44,Urban,Manager,143980,0 +20941,Female,52,Diploma,12,28,22,39,16,2.0,3,25,Semi-Urban,Data Analyst,101041,0 +20942,Female,58,Masters,16,39,39,74,54,1.0,3,36,Semi-Urban,Data Analyst,123616,0 +20943,Female,53,Bachelors,4,26,79,39,52,7.0,5,88,Semi-Urban,HR Executive,55319,0 +20944,Female,51,High School,7,38,72,99,75,2.0,3,5,Rural,HR Executive,107151,0 +20945,Female,25,Bachelors,19,10,54,76,67,2.0,4,13,Urban,Data Analyst,81342,0 +20946,Male,58,High School,12,83,99,58,1,3.0,7,99,Semi-Urban,Manager,100552,1 +20947,Other,25,Bachelors,0,9,61,64,93,8.0,4,3,Urban,Software Engineer,56538,0 +20948,Male,56,Bachelors,16,80,31,74,61,3.0,3,64,Semi-Urban,Data Analyst,106344,1 +20949,Male,29,Bachelors,16,10,60,10,24,0.0,0,22,Semi-Urban,ML Engineer,43526,0 +20950,Male,21,High School,12,61,96,95,31,2.0,1,9,Rural,HR Executive,38113,1 +20951,Other,38,Diploma,18,59,73,27,57,6.0,3,34,Urban,Data Analyst,149020,0 +20952,Other,57,High School,12,56,19,91,71,3.0,6,28,Urban,ML Engineer,146911,0 +20953,Female,34,Bachelors,8,12,1,23,14,0.0,0,26,Rural,Manager,105571,0 +20954,Female,38,Masters,15,52,23,12,12,4.0,6,67,Urban,HR Executive,53487,0 +20955,Male,38,Bachelors,6,59,16,69,77,2.0,5,9,Semi-Urban,Data Analyst,82669,0 +20956,Other,44,Bachelors,7,61,39,54,80,1.0,2,84,Semi-Urban,ML Engineer,103192,0 +20957,Female,59,Diploma,4,1,78,35,73,7.0,6,34,Semi-Urban,Data Analyst,29789,0 +20958,Female,44,Masters,0,69,60,87,35,0.0,0,50,Urban,Software Engineer,111415,1 +20959,Male,34,Bachelors,17,75,44,34,20,9.0,4,26,Urban,Software Engineer,120898,0 +20960,Male,38,Masters,7,96,27,56,49,7.0,1,82,Urban,Software Engineer,113661,1 +20961,Female,42,PhD,16,8,26,45,7,5.0,6,73,Urban,Data Analyst,149770,0 +20962,Male,21,Masters,10,75,96,6,17,8.0,2,42,Urban,Software Engineer,124911,0 +20963,Female,41,Bachelors,8,0,85,16,94,8.0,6,10,Semi-Urban,Manager,25499,0 +20964,Male,47,High School,9,26,39,15,56,8.0,0,63,Urban,HR Executive,117336,0 +20965,Female,33,Diploma,6,51,3,67,12,6.0,2,53,Urban,Software Engineer,121328,0 +20966,Male,31,Masters,7,69,61,27,46,8.0,6,33,Semi-Urban,ML Engineer,136327,0 +20967,Female,22,Masters,14,49,93,91,13,1.0,5,13,Urban,Manager,26784,1 +20968,Male,24,High School,16,51,80,47,19,5.0,0,83,Urban,Software Engineer,84041,1 +20969,Female,48,Bachelors,5,26,8,74,26,9.0,2,71,Rural,Software Engineer,121048,0 +20970,Male,50,High School,7,40,27,50,8,2.0,1,26,Rural,Manager,98241,0 +20971,Other,37,Bachelors,10,79,41,27,94,1.0,2,85,Rural,Data Analyst,80762,0 +20972,Female,53,Bachelors,4,4,81,14,72,8.0,5,98,Urban,HR Executive,47026,0 +20973,Male,43,Masters,9,90,29,3,13,7.0,0,77,Rural,HR Executive,110279,0 +20974,Female,49,Masters,17,31,21,71,22,1.0,0,41,Urban,HR Executive,48548,0 +20975,Male,41,Masters,13,83,60,15,67,5.0,6,6,Semi-Urban,ML Engineer,87594,0 +20976,Male,34,PhD,2,13,20,61,88,6.0,3,24,Rural,Data Analyst,49307,0 +20977,Male,23,Diploma,4,60,3,66,85,8.0,7,57,Urban,Manager,31987,0 +20978,Female,58,Bachelors,9,50,92,56,9,6.0,6,59,Urban,HR Executive,51400,1 +20979,Male,34,High School,2,81,2,9,0,5.0,7,92,Urban,Software Engineer,122827,0 +20980,Male,59,Diploma,11,41,32,83,36,8.0,6,41,Semi-Urban,Software Engineer,34303,0 +20981,Female,53,Diploma,2,77,29,90,15,9.0,4,75,Urban,Manager,76444,1 +20982,Female,54,Diploma,11,33,23,88,77,4.0,3,4,Semi-Urban,Manager,45849,0 +20983,Male,23,Diploma,3,79,77,98,34,8.0,1,97,Urban,HR Executive,128773,1 +20984,Female,36,Diploma,14,5,39,42,80,6.0,5,23,Rural,Manager,136343,0 +20985,Female,59,Bachelors,5,12,90,47,10,7.0,3,94,Urban,Manager,144118,1 +20986,Male,24,Bachelors,7,29,61,65,33,2.0,7,4,Urban,Software Engineer,24701,0 +20987,Female,29,Bachelors,9,19,68,79,83,1.0,1,58,Urban,Software Engineer,20488,0 +20988,Male,28,Masters,4,50,34,71,15,2.0,0,7,Semi-Urban,ML Engineer,76990,0 +20989,Female,23,High School,17,54,72,59,10,8.0,2,82,Urban,HR Executive,93781,1 +20990,Male,53,High School,7,33,25,65,33,1.0,6,46,Semi-Urban,Manager,95877,0 +20991,Female,58,Diploma,8,99,18,46,42,9.0,5,0,Rural,Manager,38397,0 +20992,Male,24,Masters,16,72,84,95,54,5.0,2,73,Rural,Software Engineer,45205,1 +20993,Female,44,Bachelors,7,28,34,34,94,6.0,5,54,Semi-Urban,Software Engineer,47170,0 +20994,Male,22,Bachelors,16,99,24,64,87,8.0,5,64,Rural,HR Executive,118915,1 +20995,Male,59,High School,14,63,58,32,91,5.0,1,13,Urban,Software Engineer,149826,0 +20996,Male,21,Bachelors,0,17,9,37,60,5.0,5,63,Urban,Software Engineer,97115,0 +20997,Female,40,Diploma,7,25,87,4,54,4.0,5,92,Urban,HR Executive,126072,0 +20998,Male,45,Diploma,10,27,35,72,3,5.0,6,39,Urban,Data Analyst,146122,0 +20999,Male,50,PhD,5,48,84,77,32,3.0,7,14,Semi-Urban,Data Analyst,48591,0 +21000,Male,57,Masters,13,55,99,10,14,0.0,3,3,Urban,Software Engineer,71004,0 +21001,Female,30,Diploma,4,43,44,90,47,8.0,7,93,Urban,Data Analyst,83228,1 +21002,Male,31,Masters,15,32,42,1,94,8.0,3,91,Rural,Data Analyst,111911,0 +21003,Female,33,Diploma,11,25,23,16,57,0.0,6,2,Urban,ML Engineer,148842,0 +21004,Male,33,High School,0,40,17,79,86,3.0,0,57,Urban,Data Analyst,96446,0 +21005,Male,57,Bachelors,5,94,39,79,52,0.0,1,80,Urban,ML Engineer,136254,1 +21006,Male,55,Masters,3,2,23,64,37,3.0,1,39,Semi-Urban,HR Executive,91970,0 +21007,Female,36,Bachelors,2,8,96,42,68,0.0,3,35,Semi-Urban,Data Analyst,148889,0 +21008,Male,55,Masters,13,1,74,93,74,3.0,5,3,Urban,Data Analyst,41531,0 +21009,Male,34,High School,5,30,50,5,75,6.0,1,33,Semi-Urban,Software Engineer,108064,0 +21010,Male,21,Diploma,8,28,88,81,1,8.0,7,51,Semi-Urban,ML Engineer,144326,1 +21011,Female,24,Masters,13,83,96,76,57,5.0,2,7,Rural,Manager,146638,1 +21012,Male,58,Bachelors,14,36,34,10,11,8.0,2,66,Rural,HR Executive,58374,0 +21013,Female,21,Bachelors,4,0,16,30,15,2.0,1,6,Urban,Software Engineer,74660,0 +21014,Male,51,Masters,1,38,29,80,94,0.0,3,55,Semi-Urban,HR Executive,45575,0 +21015,Male,21,Masters,0,1,89,70,32,7.0,3,62,Semi-Urban,HR Executive,43368,0 +21016,Male,50,Bachelors,15,89,98,12,24,9.0,6,16,Urban,HR Executive,34675,0 +21017,Female,54,High School,2,83,98,35,52,5.0,2,76,Urban,HR Executive,46019,1 +21018,Female,29,High School,1,47,56,20,88,5.0,6,66,Semi-Urban,ML Engineer,115004,0 +21019,Male,33,Diploma,4,72,84,0,87,5.0,4,39,Rural,HR Executive,130802,0 +21020,Female,32,Diploma,4,99,31,53,91,1.0,5,48,Urban,Data Analyst,109664,0 +21021,Male,29,High School,4,80,0,46,34,5.0,3,87,Semi-Urban,HR Executive,31781,0 +21022,Female,50,Bachelors,8,28,17,13,2,1.0,4,12,Semi-Urban,Manager,103927,0 +21023,Male,44,PhD,16,93,93,99,86,6.0,0,50,Semi-Urban,Software Engineer,68723,1 +21024,Male,36,Diploma,17,92,78,34,61,5.0,1,90,Urban,Software Engineer,95240,1 +21025,Female,24,High School,10,77,52,57,58,8.0,3,14,Urban,HR Executive,123682,0 +21026,Female,50,Bachelors,15,10,52,61,29,8.0,7,86,Urban,Manager,89698,0 +21027,Male,40,Masters,19,23,46,17,41,9.0,2,83,Semi-Urban,ML Engineer,142898,0 +21028,Male,46,Bachelors,16,76,96,66,20,0.0,7,49,Urban,Software Engineer,20380,1 +21029,Male,53,Bachelors,5,35,62,73,79,9.0,6,78,Urban,Manager,62315,1 +21030,Female,35,Masters,10,58,58,27,30,8.0,1,88,Semi-Urban,Manager,100298,0 +21031,Male,35,High School,13,14,52,95,13,4.0,0,15,Urban,Software Engineer,111684,0 +21032,Female,58,Bachelors,10,94,0,85,19,7.0,1,45,Urban,Data Analyst,48067,0 +21033,Male,56,Masters,7,15,60,64,83,1.0,3,66,Semi-Urban,Software Engineer,67900,0 +21034,Male,37,Diploma,3,12,59,80,35,6.0,2,49,Urban,Manager,116098,0 +21035,Male,43,Masters,11,1,97,46,90,7.0,7,39,Urban,Data Analyst,100463,0 +21036,Male,54,High School,8,94,56,27,81,8.0,4,30,Semi-Urban,Software Engineer,21752,0 +21037,Male,45,High School,12,20,89,26,5,8.0,4,34,Rural,Manager,80027,0 +21038,Male,55,Bachelors,1,7,56,87,6,1.0,7,98,Urban,Software Engineer,72635,1 +21039,Female,58,Bachelors,19,76,97,77,70,8.0,5,65,Urban,Software Engineer,22078,1 +21040,Male,25,PhD,15,71,76,69,11,0.0,4,57,Urban,HR Executive,54495,1 +21041,Female,31,Diploma,18,99,19,59,70,7.0,0,83,Urban,ML Engineer,54511,1 +21042,Male,34,PhD,9,77,0,18,76,6.0,5,90,Urban,Software Engineer,80056,0 +21043,Other,23,High School,15,24,15,18,83,2.0,4,2,Rural,Software Engineer,23022,0 +21044,Other,44,Masters,5,86,3,48,34,1.0,6,83,Rural,ML Engineer,64917,0 +21045,Female,53,Bachelors,11,96,40,65,25,8.0,1,2,Urban,HR Executive,39307,0 +21046,Female,47,High School,15,95,92,66,61,6.0,4,85,Rural,Manager,123603,1 +21047,Male,45,PhD,8,50,75,37,52,4.0,2,92,Urban,Data Analyst,97822,1 +21048,Female,40,Diploma,15,61,82,0,51,1.0,3,39,Semi-Urban,Manager,46826,0 +21049,Other,56,High School,1,18,50,9,64,6.0,3,71,Urban,Data Analyst,44412,0 +21050,Male,31,Bachelors,1,91,11,86,5,1.0,2,98,Urban,Data Analyst,61841,1 +21051,Male,33,Diploma,4,32,31,86,47,3.0,7,12,Urban,HR Executive,27032,0 +21052,Male,37,High School,17,66,24,36,78,4.0,2,60,Semi-Urban,ML Engineer,93894,0 +21053,Male,59,Masters,10,67,84,38,20,3.0,1,71,Urban,ML Engineer,46843,1 +21054,Male,26,PhD,4,66,21,73,13,8.0,6,55,Semi-Urban,Software Engineer,33817,0 +21055,Male,30,High School,7,92,24,1,11,8.0,6,47,Rural,Manager,115394,0 +21056,Male,45,PhD,19,59,71,18,63,9.0,3,14,Rural,ML Engineer,63394,0 +21057,Other,25,Bachelors,7,88,44,74,25,7.0,4,66,Urban,Software Engineer,47060,1 +21058,Male,27,Diploma,14,62,0,24,42,8.0,0,85,Urban,ML Engineer,118855,0 +21059,Female,39,Bachelors,7,77,85,57,11,2.0,4,21,Rural,Software Engineer,36809,0 +21060,Male,24,Bachelors,19,42,83,41,71,1.0,0,63,Semi-Urban,Software Engineer,66475,0 +21061,Male,30,Bachelors,3,99,79,47,37,9.0,6,70,Urban,Data Analyst,101136,1 +21062,Male,38,Diploma,8,53,8,81,10,2.0,2,12,Urban,HR Executive,98703,0 +21063,Male,45,High School,18,98,46,62,37,9.0,5,61,Rural,HR Executive,43947,1 +21064,Male,50,Bachelors,16,52,41,81,59,6.0,4,45,Urban,ML Engineer,110704,0 +21065,Male,48,Bachelors,13,33,1,49,51,3.0,7,90,Rural,Data Analyst,24435,0 +21066,Male,45,PhD,2,84,30,40,73,6.0,4,62,Semi-Urban,ML Engineer,143161,0 +21067,Female,50,Diploma,18,95,66,23,21,2.0,0,20,Urban,HR Executive,31808,0 +21068,Male,23,Masters,6,81,13,48,83,8.0,3,76,Semi-Urban,HR Executive,135484,0 +21069,Male,29,High School,14,1,48,60,77,1.0,4,24,Urban,ML Engineer,89347,0 +21070,Female,32,Diploma,13,10,8,22,47,3.0,0,49,Semi-Urban,Data Analyst,136060,0 +21071,Male,28,Bachelors,8,72,96,99,48,2.0,4,88,Urban,ML Engineer,111326,1 +21072,Male,26,Bachelors,15,69,66,15,28,7.0,2,3,Urban,Manager,49267,0 +21073,Male,27,Bachelors,5,72,30,40,96,5.0,1,47,Urban,Software Engineer,101004,0 +21074,Male,27,High School,1,86,53,92,80,2.0,6,43,Rural,Software Engineer,36967,1 +21075,Male,58,Bachelors,18,15,4,75,83,5.0,2,89,Urban,ML Engineer,143693,0 +21076,Male,29,Diploma,19,91,27,47,66,6.0,4,25,Urban,Data Analyst,135631,0 +21077,Male,21,PhD,9,28,96,20,16,9.0,3,74,Urban,Data Analyst,134029,0 +21078,Female,40,Bachelors,12,71,84,47,33,6.0,5,7,Urban,ML Engineer,102829,0 +21079,Male,36,Masters,7,21,23,79,48,4.0,2,66,Urban,ML Engineer,94887,0 +21080,Male,46,Bachelors,15,61,85,79,73,7.0,7,94,Semi-Urban,HR Executive,113027,1 +21081,Female,32,Bachelors,1,74,2,78,87,4.0,4,27,Urban,Data Analyst,104851,0 +21082,Female,40,Diploma,14,81,93,71,28,5.0,6,71,Semi-Urban,Software Engineer,82136,1 +21083,Male,50,Diploma,15,6,92,1,15,6.0,2,82,Semi-Urban,Data Analyst,139775,0 +21084,Female,43,Masters,10,72,55,68,73,2.0,6,64,Semi-Urban,Manager,58101,1 +21085,Male,57,Bachelors,13,97,61,19,71,7.0,6,18,Urban,HR Executive,41169,0 +21086,Male,50,Masters,3,16,33,17,70,9.0,3,9,Semi-Urban,Manager,132436,0 +21087,Other,35,Masters,2,95,32,80,50,0.0,0,34,Semi-Urban,ML Engineer,143431,1 +21088,Female,45,Masters,15,23,57,45,46,3.0,7,46,Urban,Data Analyst,92089,0 +21089,Male,56,Bachelors,0,36,9,86,42,0.0,1,49,Urban,HR Executive,22939,0 +21090,Female,48,Masters,9,94,44,61,27,4.0,6,97,Rural,Software Engineer,129649,1 +21091,Female,37,Bachelors,10,19,89,48,27,4.0,0,41,Urban,ML Engineer,51894,0 +21092,Male,34,High School,9,30,50,16,5,9.0,1,40,Semi-Urban,ML Engineer,101876,0 +21093,Male,55,Masters,2,3,99,97,71,4.0,0,64,Urban,Software Engineer,62981,1 +21094,Male,38,Diploma,18,19,74,20,29,7.0,1,10,Urban,Manager,123278,0 +21095,Female,29,Masters,1,55,12,41,42,6.0,6,58,Urban,Manager,32296,0 +21096,Male,46,Diploma,13,54,11,13,80,8.0,1,46,Urban,ML Engineer,82026,0 +21097,Female,57,Diploma,0,52,67,57,83,6.0,6,24,Rural,HR Executive,109566,0 +21098,Male,51,Masters,10,1,7,60,26,5.0,3,4,Semi-Urban,HR Executive,137300,0 +21099,Male,48,Bachelors,6,4,37,52,54,1.0,0,8,Urban,Software Engineer,113816,0 +21100,Female,36,Bachelors,13,95,86,57,82,8.0,7,44,Urban,ML Engineer,66959,1 +21101,Female,43,Bachelors,1,11,22,74,61,4.0,5,75,Urban,HR Executive,138137,0 +21102,Male,23,Bachelors,2,8,38,7,58,6.0,2,5,Urban,ML Engineer,142667,0 +21103,Male,57,Bachelors,2,38,72,72,56,4.0,0,0,Urban,HR Executive,60910,0 +21104,Male,44,PhD,11,40,89,8,69,6.0,5,39,Urban,Data Analyst,76716,0 +21105,Male,25,Masters,7,83,78,19,83,3.0,6,44,Urban,Manager,127776,0 +21106,Male,22,Bachelors,13,57,45,40,74,6.0,0,94,Rural,Manager,102657,1 +21107,Female,51,Masters,3,59,84,44,97,7.0,3,85,Urban,Data Analyst,134384,1 +21108,Male,50,Diploma,16,20,61,78,37,4.0,6,76,Urban,Data Analyst,70654,1 +21109,Male,47,Diploma,18,44,5,30,31,6.0,6,45,Urban,Manager,70154,0 +21110,Male,59,High School,13,91,75,69,87,3.0,7,11,Urban,Manager,53633,1 +21111,Female,29,Masters,12,21,80,3,80,0.0,1,44,Urban,ML Engineer,47091,0 +21112,Male,49,Bachelors,10,65,64,98,71,8.0,3,2,Urban,Software Engineer,98344,0 +21113,Female,57,High School,14,89,70,70,57,7.0,1,11,Urban,Manager,54145,0 +21114,Male,35,Masters,8,52,73,37,44,3.0,6,9,Urban,Manager,32349,0 +21115,Male,50,High School,3,54,57,5,68,5.0,4,79,Urban,Software Engineer,70513,0 +21116,Male,43,Bachelors,11,45,88,99,18,7.0,1,59,Semi-Urban,Manager,89666,1 +21117,Male,41,Bachelors,2,39,8,63,59,4.0,0,58,Semi-Urban,ML Engineer,135554,0 +21118,Female,39,Masters,15,6,81,86,90,1.0,0,91,Semi-Urban,Manager,100580,1 +21119,Male,34,Bachelors,7,3,31,87,88,7.0,5,9,Rural,Software Engineer,53877,0 +21120,Female,22,Bachelors,5,30,91,32,13,9.0,0,22,Urban,ML Engineer,107903,0 +21121,Male,31,Bachelors,15,94,13,30,82,1.0,6,59,Urban,ML Engineer,91052,0 +21122,Male,52,Masters,7,61,76,27,38,2.0,6,27,Semi-Urban,Software Engineer,52726,0 +21123,Male,29,Masters,6,55,21,46,24,4.0,3,63,Urban,Manager,64206,0 +21124,Female,50,Diploma,5,81,45,24,22,4.0,7,19,Urban,Data Analyst,102493,0 +21125,Female,54,PhD,4,5,54,9,28,7.0,4,0,Urban,ML Engineer,36994,0 +21126,Female,54,Bachelors,3,50,16,55,31,3.0,5,71,Semi-Urban,Software Engineer,104478,0 +21127,Male,54,Bachelors,18,62,46,17,81,4.0,0,76,Urban,ML Engineer,105963,0 +21128,Female,59,Masters,15,74,22,34,97,2.0,4,41,Urban,ML Engineer,56108,0 +21129,Male,22,Masters,15,65,5,9,21,8.0,3,89,Semi-Urban,ML Engineer,129970,0 +21130,Female,31,Diploma,12,24,47,55,71,0.0,4,36,Urban,Manager,68814,0 +21131,Female,35,Diploma,14,20,44,59,66,3.0,0,5,Urban,HR Executive,20878,0 +21132,Male,58,Bachelors,13,1,89,22,73,7.0,4,65,Urban,Manager,144124,0 +21133,Male,45,Masters,8,97,25,99,10,2.0,3,82,Semi-Urban,Manager,102541,1 +21134,Female,56,High School,7,37,63,96,91,5.0,0,33,Semi-Urban,Software Engineer,139390,0 +21135,Female,44,Bachelors,3,71,97,33,44,5.0,5,99,Urban,Data Analyst,20471,1 +21136,Male,35,High School,17,63,16,55,19,2.0,2,10,Urban,ML Engineer,146711,0 +21137,Other,35,Bachelors,0,99,92,48,50,8.0,1,88,Semi-Urban,Data Analyst,114839,1 +21138,Female,50,Bachelors,13,59,6,34,81,9.0,5,48,Semi-Urban,HR Executive,123499,0 +21139,Male,50,High School,6,74,93,88,60,8.0,4,44,Urban,HR Executive,77433,1 +21140,Male,23,Masters,5,97,50,30,92,6.0,6,33,Semi-Urban,Software Engineer,55385,0 +21141,Female,22,Bachelors,8,29,76,40,45,6.0,3,33,Urban,Manager,25160,0 +21142,Male,45,Diploma,4,89,48,29,81,8.0,1,47,Urban,Data Analyst,142804,0 +21143,Male,27,Bachelors,3,84,60,71,11,0.0,3,4,Urban,ML Engineer,61591,0 +21144,Male,56,Masters,3,15,67,51,83,5.0,7,75,Semi-Urban,Manager,95148,0 +21145,Female,47,Diploma,17,32,3,33,96,9.0,0,70,Semi-Urban,Software Engineer,95142,0 +21146,Female,27,High School,19,40,89,91,12,9.0,1,71,Semi-Urban,HR Executive,68833,1 +21147,Male,29,PhD,11,95,88,50,45,1.0,1,16,Urban,Data Analyst,40040,1 +21148,Female,25,Diploma,18,28,70,28,10,7.0,1,36,Urban,Data Analyst,23264,0 +21149,Other,50,Bachelors,0,35,73,16,74,7.0,0,95,Semi-Urban,Software Engineer,20929,0 +21150,Male,37,Bachelors,7,76,44,93,48,0.0,5,4,Urban,Software Engineer,56736,0 +21151,Female,48,Bachelors,16,77,60,9,3,4.0,2,87,Semi-Urban,HR Executive,125618,0 +21152,Female,30,Masters,1,56,34,49,37,0.0,3,82,Urban,ML Engineer,21608,0 +21153,Female,23,Diploma,11,86,40,58,95,5.0,3,48,Urban,Manager,56618,0 +21154,Female,31,Diploma,15,3,58,80,63,5.0,7,9,Urban,Data Analyst,54907,0 +21155,Male,45,High School,14,83,93,13,29,7.0,4,89,Urban,Manager,97778,1 +21156,Male,28,Bachelors,10,24,5,85,88,0.0,3,20,Urban,Manager,82535,0 +21157,Male,48,PhD,17,31,45,3,25,7.0,4,92,Urban,ML Engineer,60436,0 +21158,Female,33,Diploma,7,46,63,29,64,8.0,5,29,Urban,Manager,24875,0 +21159,Other,42,Masters,11,20,28,7,34,5.0,4,84,Semi-Urban,Data Analyst,69886,0 +21160,Male,25,High School,18,5,89,79,20,9.0,7,70,Semi-Urban,Software Engineer,69724,1 +21161,Male,53,Bachelors,7,88,77,34,33,0.0,3,55,Semi-Urban,Software Engineer,128208,1 +21162,Male,54,PhD,4,79,97,55,93,3.0,2,87,Urban,ML Engineer,28035,1 +21163,Female,25,Masters,8,43,9,44,44,6.0,1,13,Urban,Software Engineer,92386,0 +21164,Male,52,High School,5,22,34,34,29,5.0,2,8,Urban,Data Analyst,53748,0 +21165,Female,33,Diploma,5,30,31,26,3,3.0,6,0,Semi-Urban,ML Engineer,56832,0 +21166,Male,53,High School,6,99,62,93,65,8.0,1,76,Urban,Software Engineer,130044,1 +21167,Male,26,Bachelors,6,90,47,58,77,9.0,7,75,Urban,ML Engineer,23388,1 +21168,Male,22,High School,13,36,36,21,17,5.0,6,45,Semi-Urban,ML Engineer,120083,0 +21169,Female,35,Bachelors,10,28,6,9,67,9.0,2,40,Urban,Data Analyst,84042,0 +21170,Male,58,High School,9,27,82,36,68,7.0,2,63,Urban,ML Engineer,39482,0 +21171,Female,55,Diploma,14,51,3,42,11,1.0,7,98,Urban,Data Analyst,80131,0 +21172,Male,21,Bachelors,17,47,78,67,70,9.0,2,39,Urban,Data Analyst,90492,0 +21173,Male,57,Bachelors,8,63,41,97,29,5.0,7,73,Rural,HR Executive,85794,1 +21174,Male,23,Bachelors,8,75,47,42,79,8.0,1,99,Rural,Manager,116678,1 +21175,Other,58,High School,9,56,45,58,47,7.0,6,27,Rural,HR Executive,83905,0 +21176,Female,57,High School,11,57,75,86,69,2.0,6,79,Semi-Urban,Software Engineer,94463,1 +21177,Male,30,Bachelors,5,10,85,49,34,7.0,2,80,Urban,Software Engineer,116140,0 +21178,Female,54,Bachelors,0,32,1,87,91,5.0,0,51,Rural,Software Engineer,90808,0 +21179,Male,54,Masters,12,61,50,57,46,5.0,6,84,Urban,ML Engineer,64195,1 +21180,Male,30,High School,19,20,52,60,97,9.0,2,58,Urban,Data Analyst,85375,0 +21181,Male,42,Diploma,3,30,79,68,19,7.0,5,26,Urban,ML Engineer,54977,0 +21182,Female,54,Diploma,7,17,81,84,75,6.0,7,73,Rural,HR Executive,148460,1 +21183,Male,54,High School,1,92,69,30,0,3.0,7,49,Rural,Manager,120756,1 +21184,Male,34,Bachelors,14,62,37,4,56,2.0,2,71,Semi-Urban,Data Analyst,127386,0 +21185,Male,45,Bachelors,10,25,87,7,97,5.0,7,85,Urban,Software Engineer,53495,0 +21186,Male,43,High School,8,46,96,65,44,7.0,4,27,Rural,Manager,95257,0 +21187,Male,22,Diploma,17,70,80,42,83,1.0,6,55,Rural,Data Analyst,138814,1 +21188,Male,54,Diploma,0,58,67,36,5,0.0,5,84,Urban,Software Engineer,81694,1 +21189,Male,55,Bachelors,18,80,97,30,6,7.0,0,16,Urban,Software Engineer,126090,0 +21190,Female,44,Diploma,11,31,45,22,31,1.0,3,95,Rural,Software Engineer,124358,0 +21191,Male,36,Bachelors,3,74,21,26,86,2.0,4,1,Urban,HR Executive,149688,0 +21192,Male,41,Diploma,7,0,24,15,92,1.0,2,18,Semi-Urban,Manager,58643,0 +21193,Male,37,Masters,15,83,96,46,96,7.0,3,15,Semi-Urban,HR Executive,53308,1 +21194,Male,52,Bachelors,17,93,62,51,28,9.0,0,79,Semi-Urban,Software Engineer,148972,1 +21195,Female,34,Diploma,1,28,19,9,4,7.0,3,88,Rural,Manager,110620,0 +21196,Male,48,Masters,4,2,31,69,2,3.0,0,95,Rural,Manager,58100,0 +21197,Female,53,Bachelors,0,17,12,38,0,1.0,5,78,Urban,Software Engineer,146757,0 +21198,Female,27,Masters,15,37,26,62,65,1.0,7,66,Semi-Urban,Data Analyst,34197,0 +21199,Female,34,Bachelors,2,53,90,3,78,9.0,5,25,Urban,ML Engineer,97090,0 +21200,Male,26,Bachelors,12,4,5,50,75,2.0,1,93,Urban,ML Engineer,48848,0 +21201,Male,31,Bachelors,13,32,69,75,85,9.0,4,60,Semi-Urban,ML Engineer,35511,1 +21202,Male,47,Bachelors,8,5,2,56,22,3.0,6,24,Urban,Data Analyst,64816,0 +21203,Female,46,Bachelors,0,13,5,5,40,4.0,6,72,Semi-Urban,HR Executive,82742,0 +21204,Male,54,Diploma,6,38,28,1,40,4.0,1,66,Urban,HR Executive,129946,0 +21205,Male,45,Bachelors,6,8,82,98,68,2.0,6,30,Semi-Urban,ML Engineer,26344,0 +21206,Male,56,Bachelors,0,86,68,4,8,6.0,6,76,Rural,Manager,134056,0 +21207,Female,38,Bachelors,19,61,45,23,19,0.0,2,48,Semi-Urban,ML Engineer,39219,0 +21208,Female,48,Diploma,8,2,35,70,69,5.0,7,29,Rural,Manager,136009,0 +21209,Male,30,Bachelors,0,45,64,0,42,6.0,3,8,Urban,ML Engineer,142894,0 +21210,Male,56,Bachelors,16,27,70,11,72,0.0,4,48,Urban,ML Engineer,41989,0 +21211,Male,58,PhD,15,65,3,43,74,0.0,7,97,Semi-Urban,Software Engineer,85152,0 +21212,Male,29,Bachelors,6,82,49,50,53,3.0,4,10,Semi-Urban,Software Engineer,26532,0 +21213,Female,59,High School,13,9,26,58,97,7.0,5,28,Urban,HR Executive,85103,0 +21214,Female,41,Bachelors,19,26,51,86,28,1.0,0,9,Rural,HR Executive,121285,0 +21215,Female,46,Diploma,8,13,86,59,72,8.0,3,46,Urban,Software Engineer,56509,0 +21216,Male,55,Diploma,2,2,0,93,21,5.0,3,21,Rural,Software Engineer,110357,0 +21217,Female,53,Bachelors,13,29,51,13,34,0.0,2,89,Semi-Urban,ML Engineer,36587,0 +21218,Other,45,Diploma,5,7,92,66,89,0.0,4,58,Urban,Data Analyst,144000,0 +21219,Female,23,Bachelors,17,71,81,4,33,0.0,5,35,Urban,Manager,125325,0 +21220,Female,39,Diploma,13,19,11,48,86,2.0,0,39,Rural,Software Engineer,62967,0 +21221,Male,32,Masters,19,61,63,65,35,5.0,2,32,Urban,Software Engineer,96975,0 +21222,Female,50,Bachelors,16,89,52,32,71,3.0,1,19,Rural,Data Analyst,145467,0 +21223,Female,54,Masters,0,44,77,20,54,8.0,3,4,Urban,HR Executive,135041,0 +21224,Female,28,Diploma,17,16,58,52,95,5.0,0,70,Urban,ML Engineer,111423,0 +21225,Male,34,High School,14,65,65,12,95,5.0,7,68,Semi-Urban,HR Executive,147033,0 +21226,Other,31,Diploma,12,63,24,5,71,6.0,5,98,Urban,Software Engineer,70505,0 +21227,Male,28,Bachelors,14,31,39,91,30,5.0,7,72,Semi-Urban,ML Engineer,121933,0 +21228,Male,39,Bachelors,2,21,58,61,23,1.0,2,54,Semi-Urban,Manager,66883,0 +21229,Male,41,Bachelors,15,19,36,44,91,9.0,4,90,Urban,Manager,66695,0 +21230,Female,39,Diploma,10,16,4,52,82,1.0,4,67,Semi-Urban,Software Engineer,138144,0 +21231,Male,53,Bachelors,18,61,65,93,91,9.0,7,20,Urban,Data Analyst,58920,1 +21232,Male,42,Bachelors,15,12,74,80,85,4.0,1,49,Urban,ML Engineer,63980,0 +21233,Female,23,Bachelors,0,82,40,1,81,9.0,4,34,Semi-Urban,Data Analyst,109103,0 +21234,Female,58,Diploma,18,4,98,84,32,1.0,7,28,Rural,Software Engineer,90336,0 +21235,Female,29,Bachelors,19,93,91,2,60,8.0,2,46,Urban,ML Engineer,43982,0 +21236,Male,51,High School,13,14,69,48,16,0.0,6,15,Semi-Urban,HR Executive,135143,0 +21237,Female,47,Bachelors,7,47,74,67,98,4.0,3,38,Urban,HR Executive,58497,0 +21238,Male,40,High School,0,92,93,35,18,9.0,6,83,Urban,HR Executive,132560,1 +21239,Male,31,Masters,5,11,14,52,55,5.0,4,35,Urban,HR Executive,106957,0 +21240,Male,57,Bachelors,15,19,46,25,85,3.0,3,28,Urban,ML Engineer,128543,0 +21241,Female,37,Bachelors,10,36,37,14,94,6.0,1,78,Rural,Data Analyst,82383,0 +21242,Male,48,Masters,4,32,27,68,55,2.0,3,13,Semi-Urban,Software Engineer,36098,0 +21243,Male,23,High School,7,11,1,60,97,4.0,7,89,Rural,ML Engineer,136052,0 +21244,Male,23,Bachelors,16,56,20,74,9,2.0,2,6,Urban,HR Executive,103278,0 +21245,Male,42,Masters,10,67,73,71,76,4.0,6,7,Rural,HR Executive,36890,0 +21246,Female,36,Bachelors,6,29,10,78,16,0.0,7,53,Semi-Urban,HR Executive,117246,0 +21247,Female,30,Masters,1,80,42,76,86,9.0,1,53,Rural,Manager,68297,1 +21248,Male,22,Masters,0,39,17,92,25,4.0,0,83,Urban,HR Executive,65093,0 +21249,Male,32,Diploma,0,86,60,83,86,9.0,7,11,Semi-Urban,HR Executive,115508,1 +21250,Male,56,Bachelors,14,84,29,82,9,8.0,5,75,Urban,ML Engineer,132943,1 +21251,Female,34,High School,14,52,59,25,91,8.0,1,47,Urban,Manager,40189,0 +21252,Male,36,High School,18,45,22,26,45,1.0,7,65,Urban,ML Engineer,92486,0 +21253,Male,31,Bachelors,7,60,29,70,81,0.0,1,65,Rural,Data Analyst,95767,0 +21254,Male,59,Bachelors,0,54,29,96,34,7.0,2,32,Urban,Data Analyst,92685,0 +21255,Male,43,PhD,7,32,28,23,58,3.0,1,81,Rural,ML Engineer,82998,0 +21256,Male,49,Diploma,9,44,10,7,9,6.0,3,66,Urban,Software Engineer,42609,0 +21257,Male,31,Bachelors,2,33,79,87,50,9.0,4,16,Urban,Data Analyst,97989,0 +21258,Male,30,Bachelors,8,90,66,81,29,4.0,0,94,Urban,Software Engineer,68891,1 +21259,Male,57,High School,18,5,71,14,93,7.0,1,88,Semi-Urban,Software Engineer,119644,0 +21260,Other,36,Masters,3,49,41,72,56,1.0,1,2,Urban,ML Engineer,137370,0 +21261,Male,35,PhD,18,28,11,76,53,3.0,1,31,Semi-Urban,Software Engineer,65307,0 +21262,Male,45,Bachelors,12,11,44,50,49,8.0,3,34,Semi-Urban,Software Engineer,50294,0 +21263,Female,54,High School,9,39,63,23,19,4.0,0,86,Semi-Urban,HR Executive,113589,0 +21264,Female,24,Masters,2,52,23,30,34,4.0,2,12,Urban,HR Executive,32609,0 +21265,Male,32,Diploma,11,16,54,94,7,1.0,6,8,Urban,Manager,96000,0 +21266,Female,36,Masters,16,3,12,86,89,4.0,4,22,Rural,Data Analyst,106618,0 +21267,Male,42,Masters,16,16,92,74,65,8.0,0,36,Urban,ML Engineer,37295,0 +21268,Female,26,Bachelors,10,15,38,85,31,8.0,1,15,Urban,Software Engineer,100557,0 +21269,Other,53,Masters,4,50,95,0,61,4.0,7,56,Rural,HR Executive,55753,0 +21270,Male,39,High School,10,60,3,21,34,4.0,6,12,Urban,HR Executive,30091,0 +21271,Male,35,Masters,4,87,7,31,49,3.0,2,70,Semi-Urban,HR Executive,146753,0 +21272,Male,48,Bachelors,5,49,86,11,64,1.0,6,54,Rural,Manager,27887,0 +21273,Female,36,Bachelors,9,87,77,11,67,3.0,6,89,Urban,HR Executive,125930,1 +21274,Male,59,Bachelors,6,77,96,66,21,3.0,4,83,Urban,Software Engineer,61322,1 +21275,Female,27,Bachelors,11,98,31,69,50,0.0,4,61,Urban,ML Engineer,52099,1 +21276,Male,45,Diploma,8,73,49,2,21,3.0,7,64,Urban,Manager,42738,0 +21277,Male,56,Diploma,18,71,47,8,49,8.0,3,9,Urban,Data Analyst,68802,0 +21278,Male,32,Diploma,11,74,60,97,45,2.0,7,92,Urban,Manager,87043,1 +21279,Male,54,Bachelors,16,47,86,24,80,3.0,1,94,Urban,Software Engineer,39065,1 +21280,Male,56,Bachelors,9,61,6,30,86,7.0,1,57,Urban,HR Executive,24619,0 +21281,Male,23,Bachelors,5,1,77,75,34,0.0,1,7,Semi-Urban,HR Executive,76284,0 +21282,Female,32,Bachelors,15,67,92,6,92,6.0,6,53,Urban,HR Executive,69998,0 +21283,Female,40,PhD,15,76,43,2,2,4.0,6,19,Semi-Urban,ML Engineer,39152,0 +21284,Female,45,Masters,17,58,15,27,11,7.0,0,10,Rural,Data Analyst,83420,0 +21285,Male,49,Bachelors,19,57,87,70,88,2.0,3,62,Rural,Software Engineer,50457,1 +21286,Female,50,Bachelors,1,84,97,20,98,3.0,1,31,Semi-Urban,Manager,142651,0 +21287,Female,48,Masters,9,66,14,89,79,8.0,0,3,Urban,Software Engineer,101095,0 +21288,Male,39,High School,2,43,72,92,68,5.0,7,67,Semi-Urban,HR Executive,58075,1 +21289,Male,22,Masters,9,26,92,12,99,7.0,1,40,Urban,Software Engineer,122349,0 +21290,Male,41,High School,18,67,42,30,68,2.0,3,99,Rural,HR Executive,108825,1 +21291,Other,33,PhD,5,19,45,59,45,0.0,2,14,Urban,Manager,71472,0 +21292,Male,34,Masters,7,21,41,57,19,6.0,0,51,Rural,HR Executive,123134,0 +21293,Male,51,Bachelors,17,59,33,19,14,3.0,1,17,Rural,HR Executive,86107,0 +21294,Male,37,High School,2,94,0,35,78,6.0,0,17,Rural,Manager,140656,0 +21295,Female,32,High School,18,64,34,85,51,5.0,3,22,Rural,Software Engineer,149535,0 +21296,Male,36,Masters,19,5,78,83,71,4.0,6,93,Urban,Software Engineer,129314,1 +21297,Male,43,PhD,11,5,34,16,33,2.0,5,9,Urban,Software Engineer,65482,0 +21298,Male,36,High School,7,65,83,37,95,1.0,0,80,Urban,Software Engineer,145599,1 +21299,Male,41,Bachelors,6,83,59,67,11,3.0,0,3,Rural,Software Engineer,100308,0 +21300,Male,58,Masters,14,19,17,45,21,5.0,0,16,Rural,ML Engineer,66650,0 +21301,Male,31,Bachelors,8,69,78,17,9,5.0,0,43,Urban,HR Executive,27869,0 +21302,Female,32,Bachelors,11,23,16,10,16,3.0,4,40,Rural,ML Engineer,27111,0 +21303,Female,46,Bachelors,14,16,3,56,78,4.0,3,2,Semi-Urban,Manager,82324,0 +21304,Female,46,Bachelors,15,25,77,72,86,4.0,5,27,Semi-Urban,HR Executive,141292,0 +21305,Male,54,Masters,14,54,0,59,69,9.0,5,75,Urban,HR Executive,43860,0 +21306,Female,36,Masters,5,91,19,31,1,2.0,0,67,Urban,HR Executive,58609,0 +21307,Male,35,Diploma,11,31,63,98,11,9.0,2,0,Urban,Data Analyst,88401,0 +21308,Male,26,High School,0,41,89,47,58,1.0,4,47,Urban,Data Analyst,97221,0 +21309,Female,30,Bachelors,14,85,59,41,66,5.0,0,72,Rural,Software Engineer,137155,1 +21310,Female,39,Masters,0,77,0,49,85,0.0,3,63,Urban,HR Executive,25176,0 +21311,Male,26,Diploma,17,18,48,12,80,0.0,0,59,Urban,HR Executive,60438,0 +21312,Female,54,Bachelors,1,37,28,71,5,7.0,2,7,Semi-Urban,Data Analyst,79805,0 +21313,Other,31,Bachelors,13,9,40,46,37,7.0,2,82,Semi-Urban,Manager,104731,0 +21314,Female,23,Diploma,13,88,61,94,81,4.0,0,67,Urban,Software Engineer,27111,1 +21315,Female,32,Diploma,7,84,28,77,79,7.0,7,4,Urban,Software Engineer,91494,0 +21316,Female,53,Masters,6,78,5,73,73,6.0,1,22,Rural,HR Executive,75888,0 +21317,Male,51,Masters,9,66,4,81,36,1.0,7,20,Urban,ML Engineer,49829,0 +21318,Male,46,Diploma,5,75,68,42,31,7.0,6,75,Urban,HR Executive,117180,1 +21319,Female,53,High School,13,52,32,35,48,3.0,0,51,Semi-Urban,ML Engineer,53604,0 +21320,Male,29,Bachelors,4,71,63,83,51,0.0,5,21,Rural,Manager,128863,1 +21321,Male,50,Masters,9,80,9,37,45,8.0,0,91,Urban,ML Engineer,56616,0 +21322,Male,27,Bachelors,10,5,43,25,73,1.0,1,5,Urban,ML Engineer,25264,0 +21323,Male,30,Masters,11,12,34,13,42,2.0,1,36,Semi-Urban,Software Engineer,66048,0 +21324,Other,38,Masters,17,92,68,54,80,9.0,2,4,Rural,Data Analyst,62448,0 +21325,Female,37,Bachelors,5,75,89,64,2,9.0,7,37,Rural,ML Engineer,137754,1 +21326,Male,48,Bachelors,9,1,32,20,63,4.0,4,99,Urban,HR Executive,37703,0 +21327,Other,27,Masters,4,72,97,75,95,0.0,5,93,Rural,ML Engineer,144258,1 +21328,Female,46,Masters,6,3,10,7,34,3.0,4,87,Rural,Data Analyst,57247,0 +21329,Male,34,Bachelors,13,22,52,36,2,4.0,5,70,Urban,Data Analyst,89281,0 +21330,Female,23,Bachelors,9,4,11,8,53,8.0,0,85,Urban,Manager,48915,0 +21331,Male,53,Bachelors,19,51,23,55,84,6.0,4,0,Urban,HR Executive,107341,0 +21332,Male,28,Diploma,16,21,75,41,42,4.0,4,97,Rural,HR Executive,93265,0 +21333,Male,53,Bachelors,17,41,66,36,70,5.0,5,65,Urban,HR Executive,62052,0 +21334,Female,59,PhD,14,57,1,47,59,3.0,5,9,Semi-Urban,ML Engineer,49559,0 +21335,Male,49,High School,19,43,25,9,12,7.0,0,52,Urban,HR Executive,71488,0 +21336,Female,28,Diploma,13,38,72,25,47,0.0,5,50,Semi-Urban,ML Engineer,116209,0 +21337,Female,57,Bachelors,15,28,0,62,58,8.0,0,68,Urban,HR Executive,83988,0 +21338,Male,44,Masters,5,32,13,19,31,7.0,6,92,Semi-Urban,HR Executive,57541,0 +21339,Male,34,Bachelors,10,40,86,33,53,0.0,7,37,Semi-Urban,HR Executive,38356,0 +21340,Male,33,Bachelors,10,5,33,62,56,4.0,7,39,Semi-Urban,HR Executive,29569,0 +21341,Male,26,Bachelors,14,84,6,75,50,5.0,6,27,Urban,ML Engineer,112400,0 +21342,Female,27,Bachelors,9,97,12,17,76,0.0,1,8,Urban,Data Analyst,114463,0 +21343,Male,41,Bachelors,10,54,67,74,18,9.0,4,5,Urban,Data Analyst,84840,0 +21344,Male,23,High School,11,10,47,98,73,3.0,1,84,Semi-Urban,Manager,82406,1 +21345,Male,58,Bachelors,10,19,86,38,54,2.0,3,12,Semi-Urban,Software Engineer,63266,0 +21346,Female,42,Bachelors,4,72,13,56,49,6.0,0,35,Rural,ML Engineer,132211,0 +21347,Female,33,Masters,5,65,41,2,0,6.0,7,3,Urban,Software Engineer,116013,0 +21348,Other,56,Bachelors,19,30,73,32,53,8.0,5,34,Urban,ML Engineer,94858,0 +21349,Female,51,Diploma,6,83,76,41,77,7.0,2,15,Urban,ML Engineer,50210,0 +21350,Male,49,Masters,5,80,11,72,97,5.0,4,63,Urban,Manager,42705,0 +21351,Male,34,Diploma,10,78,96,72,5,7.0,6,18,Semi-Urban,Software Engineer,65508,1 +21352,Female,34,Bachelors,9,65,87,91,73,7.0,7,37,Urban,HR Executive,72168,1 +21353,Female,25,Masters,15,93,19,67,73,6.0,3,11,Rural,ML Engineer,73675,0 +21354,Male,22,Bachelors,15,76,93,95,72,4.0,4,78,Rural,Manager,104263,1 +21355,Male,38,Diploma,18,22,58,78,97,2.0,3,50,Urban,Manager,146218,0 +21356,Male,37,Masters,9,54,47,51,19,4.0,6,16,Urban,Data Analyst,144065,0 +21357,Female,26,Diploma,17,57,36,87,99,6.0,6,90,Urban,ML Engineer,84675,1 +21358,Male,48,Masters,9,6,96,98,61,5.0,4,56,Urban,Data Analyst,101185,1 +21359,Male,39,Diploma,13,72,29,89,17,2.0,6,47,Rural,Software Engineer,114340,1 +21360,Female,48,PhD,15,9,26,39,94,1.0,0,0,Semi-Urban,ML Engineer,23760,0 +21361,Male,46,Bachelors,4,70,62,56,69,0.0,1,91,Urban,Manager,122742,1 +21362,Male,24,PhD,2,85,89,28,44,6.0,6,27,Urban,Software Engineer,90302,0 +21363,Male,52,Diploma,14,2,91,31,9,6.0,7,11,Urban,Data Analyst,124895,0 +21364,Male,36,Diploma,5,32,82,74,96,2.0,0,72,Semi-Urban,Manager,128878,1 +21365,Male,26,Bachelors,9,51,89,45,67,9.0,7,68,Urban,HR Executive,60562,1 +21366,Male,39,High School,4,52,96,62,55,7.0,5,83,Urban,Data Analyst,92837,1 +21367,Male,36,Bachelors,16,99,66,59,88,7.0,0,54,Urban,HR Executive,30907,1 +21368,Female,43,Bachelors,5,98,94,50,75,0.0,2,61,Urban,Data Analyst,98133,1 +21369,Female,59,High School,18,87,91,85,86,7.0,3,37,Urban,Manager,123684,1 +21370,Male,30,Masters,18,10,95,79,18,8.0,1,73,Semi-Urban,HR Executive,60166,1 +21371,Male,41,Bachelors,18,98,80,8,88,5.0,3,38,Semi-Urban,HR Executive,140661,0 +21372,Female,37,Bachelors,13,52,76,68,76,3.0,6,89,Urban,Software Engineer,114229,1 +21373,Male,39,PhD,9,15,0,72,4,7.0,6,13,Urban,Software Engineer,68832,0 +21374,Male,47,PhD,9,67,27,42,64,1.0,3,3,Urban,Data Analyst,145180,0 +21375,Male,39,Bachelors,11,30,35,30,95,1.0,3,99,Urban,Software Engineer,113146,0 +21376,Female,34,High School,8,51,36,28,22,3.0,0,43,Rural,ML Engineer,76738,0 +21377,Male,24,Masters,6,82,86,84,80,8.0,3,72,Semi-Urban,HR Executive,113573,1 +21378,Female,48,Bachelors,12,56,35,28,2,1.0,5,11,Urban,HR Executive,23002,0 +21379,Female,29,Masters,7,64,83,26,82,8.0,1,45,Rural,Software Engineer,113262,0 +21380,Female,54,Masters,5,34,40,27,2,4.0,3,84,Rural,Data Analyst,98915,0 +21381,Male,44,Bachelors,4,68,79,50,95,2.0,3,92,Urban,Data Analyst,61354,1 +21382,Female,44,High School,1,65,17,29,76,3.0,3,25,Semi-Urban,Software Engineer,26934,0 +21383,Male,27,Bachelors,10,75,67,33,93,9.0,4,20,Urban,Manager,43988,0 +21384,Male,45,High School,12,4,65,84,51,1.0,7,98,Urban,HR Executive,78296,1 +21385,Male,59,Bachelors,15,12,33,30,23,8.0,5,51,Urban,Software Engineer,35457,0 +21386,Male,56,PhD,1,35,20,54,96,9.0,3,27,Urban,Software Engineer,129187,0 +21387,Female,38,Diploma,16,31,37,99,66,8.0,1,88,Rural,Manager,88243,1 +21388,Male,29,High School,12,10,30,7,13,2.0,3,21,Semi-Urban,HR Executive,115548,0 +21389,Male,38,PhD,7,67,62,92,0,4.0,7,95,Urban,Manager,69182,1 +21390,Male,45,High School,10,34,57,10,29,5.0,2,65,Urban,Manager,102961,0 +21391,Female,35,Diploma,0,52,7,35,77,0.0,5,91,Semi-Urban,ML Engineer,26715,0 +21392,Male,27,Bachelors,18,71,22,19,83,5.0,4,98,Urban,HR Executive,99275,0 +21393,Female,59,Bachelors,7,30,90,22,90,9.0,4,27,Urban,ML Engineer,81317,0 +21394,Female,28,Diploma,10,79,30,55,79,4.0,2,69,Urban,Manager,46463,0 +21395,Female,27,Bachelors,4,32,25,34,62,2.0,5,82,Urban,Manager,92564,0 +21396,Male,36,Masters,3,59,47,81,24,3.0,4,52,Urban,Data Analyst,140604,1 +21397,Female,43,Masters,4,44,99,79,95,9.0,2,34,Rural,Data Analyst,114571,1 +21398,Male,36,Bachelors,2,51,78,87,90,4.0,4,47,Semi-Urban,Data Analyst,82448,1 +21399,Female,57,Bachelors,3,68,11,88,28,1.0,3,84,Urban,Manager,73755,1 +21400,Female,55,Bachelors,2,99,60,79,53,9.0,1,58,Urban,Data Analyst,42494,1 +21401,Male,40,Diploma,3,33,88,0,46,0.0,5,90,Semi-Urban,Manager,57499,0 +21402,Female,45,High School,11,57,59,99,24,0.0,5,32,Urban,Software Engineer,119469,1 +21403,Male,36,Diploma,17,62,43,26,18,9.0,4,72,Urban,Software Engineer,117531,0 +21404,Male,44,Diploma,10,64,3,98,28,0.0,2,78,Urban,Data Analyst,26228,1 +21405,Male,59,Diploma,19,26,17,57,90,1.0,6,71,Urban,Software Engineer,98393,0 +21406,Other,55,Bachelors,11,81,78,79,52,8.0,2,32,Rural,HR Executive,36092,1 +21407,Female,24,Bachelors,14,36,39,73,86,9.0,1,92,Rural,Data Analyst,133319,0 +21408,Female,33,Bachelors,17,8,11,37,11,3.0,6,94,Semi-Urban,Software Engineer,96917,0 +21409,Female,36,Masters,9,17,55,1,77,6.0,4,95,Urban,Data Analyst,91692,0 +21410,Male,33,Diploma,19,52,99,0,62,6.0,0,75,Semi-Urban,Data Analyst,137547,0 +21411,Female,23,Bachelors,7,7,22,45,12,7.0,7,78,Urban,Software Engineer,131303,0 +21412,Male,29,Masters,12,13,24,76,96,5.0,3,71,Urban,HR Executive,122987,0 +21413,Female,43,Bachelors,6,12,56,92,6,5.0,7,17,Semi-Urban,HR Executive,47954,0 +21414,Female,44,Bachelors,3,37,72,60,97,1.0,2,58,Semi-Urban,ML Engineer,111018,0 +21415,Male,42,High School,9,35,35,10,92,1.0,4,4,Rural,Manager,99858,0 +21416,Male,48,Diploma,4,2,44,60,2,4.0,3,23,Urban,Manager,80602,0 +21417,Male,56,Diploma,9,39,40,41,69,8.0,4,15,Urban,Manager,86910,0 +21418,Other,36,Bachelors,8,90,11,4,85,3.0,7,40,Urban,ML Engineer,28209,0 +21419,Male,47,Masters,12,78,40,23,13,3.0,2,45,Urban,HR Executive,62966,0 +21420,Male,35,Masters,8,58,40,0,74,4.0,2,7,Semi-Urban,Software Engineer,42211,0 +21421,Female,46,High School,3,3,67,95,30,9.0,6,41,Urban,Manager,36611,0 +21422,Male,58,Bachelors,1,74,82,87,14,2.0,5,49,Urban,HR Executive,37805,1 +21423,Male,21,Masters,9,16,26,62,77,9.0,5,17,Urban,Software Engineer,67377,0 +21424,Female,34,High School,18,67,54,97,38,5.0,4,94,Urban,ML Engineer,39047,1 +21425,Male,58,Masters,12,74,41,80,7,4.0,0,60,Semi-Urban,HR Executive,108812,1 +21426,Female,42,Masters,18,42,35,94,53,6.0,2,14,Urban,Software Engineer,88965,0 +21427,Male,34,Diploma,9,57,44,65,94,1.0,2,34,Rural,Software Engineer,93501,0 +21428,Male,42,Diploma,9,61,53,22,26,4.0,6,51,Urban,Software Engineer,141008,0 +21429,Male,58,Bachelors,2,83,13,11,78,9.0,6,13,Urban,Software Engineer,70729,0 +21430,Male,38,Bachelors,15,97,73,92,5,1.0,6,34,Urban,ML Engineer,127416,1 +21431,Female,32,Bachelors,17,23,26,43,16,5.0,1,3,Urban,ML Engineer,21872,0 +21432,Female,46,Masters,10,14,85,44,87,7.0,1,40,Semi-Urban,HR Executive,115117,0 +21433,Male,59,Diploma,2,63,22,53,3,1.0,5,42,Semi-Urban,HR Executive,126749,0 +21434,Male,31,High School,14,31,14,66,20,8.0,1,59,Urban,Data Analyst,42721,0 +21435,Male,54,Diploma,16,91,14,66,30,3.0,3,3,Urban,Data Analyst,51609,0 +21436,Male,27,Bachelors,13,26,27,47,70,3.0,5,89,Urban,HR Executive,105235,0 +21437,Male,54,Diploma,8,21,91,24,27,1.0,6,74,Urban,Software Engineer,53033,0 +21438,Female,44,Bachelors,19,83,10,16,71,7.0,7,3,Urban,Manager,46357,0 +21439,Male,48,Masters,8,59,19,89,35,7.0,1,80,Rural,Software Engineer,121135,1 +21440,Male,53,Bachelors,14,34,40,84,48,0.0,2,85,Rural,Data Analyst,26555,1 +21441,Male,54,Bachelors,18,93,23,42,53,8.0,2,79,Semi-Urban,Data Analyst,141753,1 +21442,Male,56,Masters,2,42,28,61,21,5.0,6,14,Rural,Software Engineer,59856,0 +21443,Female,31,Masters,2,78,74,21,15,0.0,4,19,Urban,Manager,118217,0 +21444,Male,56,Bachelors,1,41,17,52,64,0.0,7,6,Semi-Urban,Software Engineer,137398,0 +21445,Male,22,Diploma,3,14,17,72,6,4.0,6,71,Urban,ML Engineer,34481,0 +21446,Male,22,Masters,17,70,56,91,94,0.0,0,70,Semi-Urban,Software Engineer,94117,1 +21447,Female,40,Bachelors,19,39,8,81,48,0.0,7,64,Urban,HR Executive,44980,0 +21448,Male,58,High School,7,30,70,32,71,5.0,0,62,Urban,Data Analyst,48016,0 +21449,Female,57,Diploma,11,9,25,13,82,0.0,2,48,Rural,Software Engineer,145680,0 +21450,Male,28,Diploma,1,90,59,84,52,8.0,3,85,Urban,Software Engineer,47572,1 +21451,Female,54,Bachelors,14,1,99,82,53,9.0,2,27,Rural,Manager,105233,0 +21452,Female,53,Diploma,16,39,26,99,93,3.0,5,56,Urban,HR Executive,67798,0 +21453,Male,27,Bachelors,13,29,30,98,2,3.0,6,5,Semi-Urban,HR Executive,126554,0 +21454,Female,25,PhD,6,99,52,74,10,7.0,3,61,Urban,Software Engineer,60999,1 +21455,Female,52,Bachelors,17,14,98,75,57,4.0,3,72,Rural,ML Engineer,140741,1 +21456,Male,24,PhD,11,87,29,4,23,6.0,3,24,Rural,Data Analyst,134131,0 +21457,Male,25,High School,8,43,74,17,56,7.0,1,45,Rural,HR Executive,138069,0 +21458,Female,40,Masters,18,4,15,2,85,0.0,5,37,Urban,Manager,49613,0 +21459,Female,21,Masters,16,48,19,59,65,3.0,2,57,Urban,ML Engineer,30361,0 +21460,Female,28,Bachelors,13,0,39,79,12,9.0,5,50,Urban,Software Engineer,32662,0 +21461,Female,25,Bachelors,5,14,76,63,44,1.0,2,54,Urban,HR Executive,42483,0 +21462,Female,28,High School,1,68,6,74,15,9.0,4,83,Urban,Data Analyst,98944,0 +21463,Female,31,Bachelors,5,59,91,37,25,2.0,7,15,Semi-Urban,Manager,92847,0 +21464,Male,52,Bachelors,8,66,64,82,20,1.0,2,47,Urban,Manager,137738,1 +21465,Male,40,Masters,7,90,88,21,63,7.0,1,77,Rural,Manager,142383,1 +21466,Female,59,Masters,18,91,46,91,48,9.0,2,49,Urban,ML Engineer,66126,1 +21467,Male,56,Diploma,13,29,9,98,89,8.0,4,28,Urban,HR Executive,103243,0 +21468,Male,58,Bachelors,3,86,13,4,22,8.0,2,15,Urban,Software Engineer,62033,0 +21469,Female,47,Bachelors,4,46,18,48,6,2.0,6,32,Rural,HR Executive,96988,0 +21470,Male,58,Bachelors,2,31,83,41,56,5.0,3,18,Urban,HR Executive,23110,0 +21471,Male,57,Diploma,3,97,18,78,77,5.0,5,24,Semi-Urban,Software Engineer,100352,0 +21472,Male,43,Bachelors,3,79,59,94,19,1.0,6,76,Urban,Manager,36174,1 +21473,Female,48,Bachelors,12,8,15,86,3,3.0,7,66,Urban,HR Executive,59038,0 +21474,Other,29,Diploma,0,12,69,26,57,0.0,4,36,Rural,Software Engineer,145453,0 +21475,Male,24,Bachelors,1,31,73,48,63,1.0,5,81,Urban,ML Engineer,133756,0 +21476,Male,39,Masters,10,71,60,28,71,5.0,4,29,Urban,ML Engineer,98252,0 +21477,Male,26,Diploma,13,73,11,76,93,5.0,2,38,Semi-Urban,Data Analyst,93876,0 +21478,Male,44,Masters,3,91,84,57,29,9.0,0,13,Urban,Software Engineer,74630,1 +21479,Male,45,Bachelors,17,10,71,1,48,2.0,3,72,Urban,Data Analyst,58133,0 +21480,Male,26,Bachelors,19,69,24,13,79,0.0,5,85,Urban,HR Executive,104185,0 +21481,Male,33,Masters,8,3,73,80,18,4.0,7,79,Urban,Manager,39720,1 +21482,Male,58,Bachelors,12,38,66,18,31,6.0,5,75,Urban,Data Analyst,64225,0 +21483,Male,57,High School,15,57,43,22,49,6.0,1,60,Urban,Software Engineer,59839,0 +21484,Female,44,Bachelors,6,55,69,88,28,9.0,4,40,Urban,HR Executive,84822,1 +21485,Female,43,Bachelors,17,62,53,4,45,9.0,5,18,Urban,Data Analyst,87160,0 +21486,Female,53,Bachelors,3,6,27,27,59,7.0,7,50,Rural,Manager,145627,0 +21487,Female,56,Diploma,19,18,67,30,90,4.0,1,35,Semi-Urban,Software Engineer,126148,0 +21488,Male,46,High School,10,73,94,65,0,6.0,4,77,Rural,Software Engineer,111926,1 +21489,Female,47,Masters,15,52,5,98,71,1.0,2,21,Rural,Data Analyst,113554,0 +21490,Male,54,Bachelors,2,80,78,72,34,1.0,6,45,Semi-Urban,HR Executive,28531,1 +21491,Female,57,Masters,13,1,87,64,21,1.0,1,84,Semi-Urban,HR Executive,64831,0 +21492,Female,44,High School,18,74,31,80,93,5.0,2,32,Urban,Data Analyst,82365,0 +21493,Female,46,Bachelors,15,45,64,75,81,1.0,0,75,Urban,Manager,80648,1 +21494,Other,26,High School,10,61,89,26,20,4.0,1,95,Urban,Data Analyst,106050,1 +21495,Female,48,Bachelors,14,85,52,8,4,0.0,5,26,Rural,Data Analyst,82811,0 +21496,Female,26,Bachelors,8,54,36,85,46,4.0,6,67,Urban,Manager,57999,1 +21497,Male,21,Bachelors,8,94,27,65,35,6.0,5,47,Semi-Urban,ML Engineer,104694,0 +21498,Female,46,Masters,8,23,69,19,68,2.0,1,89,Rural,Manager,34156,0 +21499,Male,54,Bachelors,16,64,52,76,65,0.0,3,73,Urban,Data Analyst,130042,1 +21500,Female,45,High School,11,74,12,0,21,0.0,0,70,Urban,Software Engineer,87078,0 +21501,Male,53,Masters,12,5,28,91,35,4.0,1,5,Urban,Software Engineer,64715,0 +21502,Male,54,Diploma,0,55,93,72,34,0.0,3,89,Urban,Software Engineer,115635,1 +21503,Female,49,Bachelors,18,22,21,23,46,0.0,0,50,Urban,HR Executive,66332,0 +21504,Male,41,High School,9,45,38,41,2,3.0,2,88,Semi-Urban,Data Analyst,75074,0 +21505,Female,28,Bachelors,14,65,6,91,89,3.0,2,25,Urban,HR Executive,103585,0 +21506,Male,33,High School,12,44,7,37,30,1.0,7,7,Urban,ML Engineer,50639,0 +21507,Female,59,Bachelors,8,2,87,71,81,4.0,7,6,Urban,Software Engineer,124621,0 +21508,Female,51,Masters,14,24,92,31,90,6.0,5,44,Semi-Urban,Data Analyst,43374,0 +21509,Female,22,PhD,12,66,30,92,59,9.0,4,1,Semi-Urban,Data Analyst,132159,0 +21510,Male,36,High School,6,67,60,61,77,4.0,1,73,Urban,HR Executive,119669,1 +21511,Male,47,Bachelors,10,66,50,80,97,1.0,5,78,Urban,ML Engineer,140295,1 +21512,Female,37,Bachelors,17,79,69,91,65,9.0,4,54,Semi-Urban,ML Engineer,102210,1 +21513,Male,32,Masters,12,58,14,53,25,9.0,0,77,Urban,HR Executive,47903,0 +21514,Male,44,Masters,9,83,23,55,2,4.0,7,40,Urban,Software Engineer,88684,0 +21515,Female,52,Diploma,10,19,80,29,90,0.0,2,47,Rural,Data Analyst,99125,0 +21516,Male,42,High School,13,16,25,6,75,4.0,1,72,Semi-Urban,Manager,126674,0 +21517,Male,29,Bachelors,12,13,62,83,13,6.0,0,89,Rural,Manager,118667,1 +21518,Male,52,PhD,9,5,17,16,18,7.0,3,97,Rural,HR Executive,115312,0 +21519,Male,38,Diploma,1,68,77,86,93,7.0,5,91,Semi-Urban,ML Engineer,71206,1 +21520,Female,43,Diploma,12,54,69,63,30,8.0,0,70,Semi-Urban,Software Engineer,69326,1 +21521,Male,58,Masters,19,21,24,67,20,3.0,3,9,Urban,HR Executive,44203,0 +21522,Other,36,Masters,8,73,11,96,23,2.0,2,34,Urban,Manager,118293,0 +21523,Male,48,Diploma,14,37,11,58,14,3.0,0,36,Urban,HR Executive,137641,0 +21524,Male,36,Bachelors,16,32,31,5,71,3.0,7,72,Semi-Urban,Data Analyst,28343,0 +21525,Male,23,Bachelors,8,53,43,16,94,8.0,5,2,Rural,ML Engineer,82045,0 +21526,Male,22,Bachelors,14,54,14,65,29,4.0,4,43,Urban,ML Engineer,105874,0 +21527,Female,58,High School,14,81,13,72,23,3.0,6,86,Semi-Urban,Data Analyst,128491,1 +21528,Female,48,Bachelors,0,28,64,3,83,7.0,7,31,Urban,Data Analyst,64150,0 +21529,Male,58,Diploma,0,34,8,36,78,8.0,7,99,Urban,HR Executive,47236,0 +21530,Female,26,High School,16,24,59,45,48,7.0,1,67,Rural,Software Engineer,129750,0 +21531,Male,40,High School,18,49,29,27,98,5.0,0,51,Semi-Urban,Manager,55075,0 +21532,Male,50,High School,16,64,80,24,3,4.0,5,7,Rural,HR Executive,136347,0 +21533,Male,52,Bachelors,15,60,80,56,80,7.0,0,15,Rural,Manager,102183,0 +21534,Female,26,Bachelors,13,26,54,20,83,8.0,1,41,Semi-Urban,Manager,51666,0 +21535,Male,57,Masters,10,98,47,49,60,5.0,5,58,Urban,Manager,94416,1 +21536,Female,45,Bachelors,17,27,23,84,48,5.0,5,71,Semi-Urban,Data Analyst,129343,0 +21537,Male,29,Diploma,1,0,84,59,95,5.0,5,85,Urban,Manager,109103,0 +21538,Male,31,High School,6,64,4,57,47,7.0,7,4,Rural,Software Engineer,62881,0 +21539,Male,58,High School,9,4,32,47,15,6.0,6,80,Semi-Urban,HR Executive,41261,0 +21540,Female,42,Diploma,1,66,56,12,41,2.0,2,43,Urban,Data Analyst,107557,0 +21541,Female,53,Bachelors,11,67,96,33,30,2.0,5,19,Semi-Urban,Manager,33186,0 +21542,Male,50,Diploma,14,44,50,36,15,0.0,6,47,Urban,Data Analyst,107636,0 +21543,Female,44,PhD,4,90,28,9,49,9.0,6,20,Urban,Software Engineer,22956,0 +21544,Male,36,High School,18,51,91,39,21,0.0,0,67,Urban,Software Engineer,46537,1 +21545,Female,31,Masters,0,3,94,71,52,8.0,1,28,Semi-Urban,Data Analyst,134426,0 +21546,Female,27,Masters,16,25,87,69,1,6.0,5,0,Semi-Urban,Software Engineer,119078,0 +21547,Female,29,Masters,5,79,6,60,64,3.0,7,68,Urban,ML Engineer,64335,0 +21548,Female,37,Diploma,19,97,41,3,83,5.0,5,90,Urban,HR Executive,130767,0 +21549,Male,32,Bachelors,19,77,97,76,39,0.0,5,9,Urban,Data Analyst,106212,1 +21550,Female,46,Diploma,0,95,94,45,41,6.0,3,31,Urban,Manager,99388,1 +21551,Male,29,Masters,15,53,97,11,30,2.0,4,14,Rural,Data Analyst,134969,0 +21552,Male,24,Bachelors,9,18,94,38,95,8.0,1,50,Urban,Data Analyst,36195,0 +21553,Male,35,Bachelors,7,13,33,36,66,4.0,5,37,Urban,HR Executive,42921,0 +21554,Male,44,Bachelors,0,61,78,79,10,6.0,1,95,Urban,Data Analyst,140293,1 +21555,Male,25,Bachelors,16,26,13,79,97,3.0,7,75,Urban,HR Executive,146069,0 +21556,Male,47,Diploma,11,73,43,88,63,0.0,3,84,Urban,Data Analyst,59903,1 +21557,Male,34,Bachelors,10,72,65,35,75,1.0,1,56,Urban,HR Executive,53477,0 +21558,Male,49,Bachelors,15,71,77,58,90,2.0,0,11,Semi-Urban,Data Analyst,71421,0 +21559,Female,31,Masters,11,71,81,21,95,2.0,0,60,Urban,HR Executive,53365,0 +21560,Male,57,PhD,4,67,20,57,83,5.0,0,58,Rural,Data Analyst,141534,0 +21561,Female,50,High School,19,1,59,51,48,6.0,0,87,Semi-Urban,Data Analyst,48422,0 +21562,Male,37,High School,12,11,48,8,95,3.0,3,67,Semi-Urban,Manager,86800,0 +21563,Male,38,Bachelors,16,93,68,22,69,0.0,4,16,Urban,HR Executive,27193,0 +21564,Male,53,Diploma,6,92,75,6,64,8.0,4,17,Urban,Manager,86265,0 +21565,Male,54,Bachelors,8,37,75,95,76,7.0,2,19,Urban,HR Executive,69613,0 +21566,Female,45,Diploma,5,40,93,77,69,2.0,6,57,Semi-Urban,ML Engineer,132408,1 +21567,Female,22,Masters,1,32,92,58,90,5.0,1,55,Rural,Software Engineer,57394,0 +21568,Male,44,Masters,8,80,14,20,43,4.0,7,2,Urban,Software Engineer,127845,0 +21569,Male,26,Bachelors,17,38,50,76,59,4.0,7,57,Urban,Manager,47284,0 +21570,Female,59,Bachelors,18,68,81,17,84,2.0,4,1,Semi-Urban,HR Executive,75155,0 +21571,Male,56,PhD,7,21,21,21,58,8.0,4,79,Urban,Data Analyst,59238,0 +21572,Male,23,Bachelors,7,79,21,76,50,7.0,7,97,Urban,Data Analyst,128330,1 +21573,Female,27,Masters,4,79,98,88,75,3.0,7,56,Semi-Urban,ML Engineer,124095,1 +21574,Male,42,Masters,7,34,43,38,70,0.0,7,20,Rural,Software Engineer,105850,0 +21575,Other,50,Masters,13,96,21,61,8,0.0,0,94,Rural,Manager,121137,1 +21576,Female,32,Masters,2,32,3,38,29,3.0,6,19,Urban,Software Engineer,107502,0 +21577,Male,53,Bachelors,7,98,15,16,67,9.0,4,92,Urban,Data Analyst,144619,0 +21578,Male,29,Bachelors,14,55,69,99,0,6.0,3,52,Urban,ML Engineer,146527,1 +21579,Male,47,Diploma,10,83,35,97,15,2.0,4,74,Rural,Manager,95158,1 +21580,Male,26,Bachelors,13,35,36,38,13,7.0,5,75,Urban,Software Engineer,28265,0 +21581,Female,41,Masters,17,81,61,15,70,7.0,2,6,Urban,HR Executive,91194,0 +21582,Female,36,Diploma,18,61,26,30,14,7.0,4,77,Semi-Urban,Software Engineer,92066,0 +21583,Male,40,Masters,4,96,18,34,88,0.0,7,74,Rural,Manager,146555,0 +21584,Male,23,High School,11,15,13,72,38,1.0,1,62,Urban,Manager,31220,0 +21585,Male,36,High School,7,47,33,68,10,1.0,6,69,Urban,Software Engineer,145949,0 +21586,Male,32,Diploma,0,58,22,25,6,5.0,5,63,Rural,HR Executive,45090,0 +21587,Female,38,Bachelors,11,91,50,2,96,5.0,0,5,Rural,Software Engineer,103216,0 +21588,Female,45,Diploma,13,50,4,56,58,1.0,3,20,Urban,Data Analyst,65093,0 +21589,Male,57,Bachelors,1,53,91,6,63,8.0,2,98,Urban,Software Engineer,147015,1 +21590,Male,38,Bachelors,4,15,9,77,34,4.0,3,68,Semi-Urban,Manager,72796,0 +21591,Female,44,Diploma,3,67,23,92,48,7.0,0,74,Urban,ML Engineer,97397,1 +21592,Male,40,Bachelors,6,69,8,22,18,4.0,3,36,Urban,Data Analyst,39153,0 +21593,Female,50,Bachelors,17,84,49,61,62,2.0,1,3,Urban,HR Executive,131583,0 +21594,Male,46,Bachelors,16,95,33,29,33,0.0,0,55,Rural,Manager,78380,0 +21595,Female,36,Masters,11,79,19,29,74,1.0,6,97,Semi-Urban,HR Executive,62107,0 +21596,Female,44,Masters,8,73,66,33,50,9.0,4,91,Urban,Software Engineer,72884,1 +21597,Female,21,High School,4,86,19,76,51,6.0,2,41,Semi-Urban,Software Engineer,44504,0 +21598,Other,59,PhD,5,73,67,96,55,9.0,2,93,Urban,Data Analyst,65534,1 +21599,Other,30,Bachelors,3,94,24,92,64,3.0,0,50,Urban,Data Analyst,22325,1 +21600,Female,55,High School,11,7,39,97,25,9.0,4,54,Urban,Software Engineer,115662,0 +21601,Other,57,Bachelors,7,25,65,68,53,2.0,1,59,Rural,ML Engineer,72018,0 +21602,Female,33,Masters,16,59,29,77,87,7.0,3,85,Urban,Data Analyst,32551,1 +21603,Female,25,Diploma,7,86,23,0,98,9.0,6,90,Semi-Urban,Software Engineer,51542,0 +21604,Male,45,Bachelors,17,33,76,76,85,1.0,7,24,Semi-Urban,HR Executive,125193,0 +21605,Male,56,PhD,3,21,21,32,97,6.0,0,66,Rural,HR Executive,102573,0 +21606,Female,28,Bachelors,2,85,31,87,76,5.0,4,16,Urban,HR Executive,64621,0 +21607,Male,59,Diploma,14,62,89,5,25,8.0,3,11,Rural,Software Engineer,42958,0 +21608,Female,34,PhD,15,48,0,45,69,3.0,5,50,Urban,Data Analyst,67120,0 +21609,Male,24,Bachelors,7,50,70,34,19,2.0,4,52,Urban,Manager,56398,0 +21610,Male,59,Bachelors,9,17,25,62,15,2.0,6,96,Semi-Urban,HR Executive,40076,0 +21611,Female,33,Diploma,17,52,33,77,93,8.0,7,34,Urban,Manager,99347,0 +21612,Female,22,Bachelors,15,90,53,58,38,4.0,2,69,Urban,ML Engineer,139231,1 +21613,Male,35,Bachelors,16,76,99,49,34,5.0,0,95,Urban,HR Executive,126085,1 +21614,Female,37,Masters,9,90,64,9,14,2.0,0,43,Semi-Urban,ML Engineer,46770,0 +21615,Female,47,Masters,7,80,63,58,16,8.0,1,50,Rural,Software Engineer,51716,1 +21616,Male,59,Bachelors,1,29,27,23,88,2.0,2,53,Urban,ML Engineer,97282,0 +21617,Male,37,Bachelors,13,26,17,84,38,5.0,5,41,Rural,Manager,85909,0 +21618,Male,21,Bachelors,9,29,6,38,84,0.0,6,50,Urban,Manager,68627,0 +21619,Male,26,Masters,14,51,49,30,20,4.0,4,16,Urban,HR Executive,91906,0 +21620,Male,42,Masters,17,4,98,60,69,6.0,2,67,Urban,HR Executive,144068,0 +21621,Male,23,Masters,8,96,1,0,39,8.0,3,6,Urban,ML Engineer,84674,0 +21622,Male,40,Diploma,14,58,46,30,82,6.0,7,19,Rural,Manager,76306,0 +21623,Female,39,Bachelors,8,23,96,1,63,7.0,2,7,Rural,Software Engineer,72711,0 +21624,Male,37,Bachelors,2,67,13,34,54,7.0,5,43,Urban,ML Engineer,52686,0 +21625,Female,24,High School,7,57,58,38,71,3.0,1,22,Rural,Software Engineer,56280,0 +21626,Male,56,PhD,19,62,6,18,70,3.0,0,81,Urban,Data Analyst,72670,0 +21627,Female,28,Masters,6,71,65,3,98,4.0,2,89,Rural,Software Engineer,64903,0 +21628,Female,23,Masters,16,38,80,59,73,9.0,5,64,Urban,ML Engineer,53335,1 +21629,Male,40,Diploma,12,84,5,16,34,0.0,0,33,Urban,Data Analyst,138561,0 +21630,Female,49,Masters,19,13,0,58,25,2.0,2,14,Rural,HR Executive,81981,0 +21631,Female,27,Diploma,5,8,33,72,80,1.0,5,56,Rural,ML Engineer,136907,0 +21632,Female,36,High School,4,33,21,96,78,8.0,1,8,Semi-Urban,Software Engineer,109977,0 +21633,Female,31,Bachelors,13,90,61,65,86,3.0,3,46,Rural,Data Analyst,26619,1 +21634,Male,27,Bachelors,12,82,97,20,77,4.0,1,17,Urban,Data Analyst,44553,0 +21635,Male,29,Bachelors,16,84,19,72,37,1.0,2,73,Urban,HR Executive,48036,1 +21636,Male,46,Bachelors,11,70,92,43,61,8.0,5,15,Semi-Urban,Software Engineer,62908,0 +21637,Male,53,Diploma,4,28,92,61,82,3.0,4,33,Urban,HR Executive,57892,0 +21638,Male,38,Bachelors,10,81,82,29,21,7.0,7,45,Urban,Software Engineer,44950,1 +21639,Female,28,Masters,2,95,31,90,7,7.0,3,38,Urban,ML Engineer,48235,1 +21640,Male,45,Bachelors,17,72,73,38,79,8.0,3,18,Urban,Manager,57059,0 +21641,Other,49,Bachelors,10,50,55,73,28,4.0,6,71,Urban,ML Engineer,112285,1 +21642,Male,58,Bachelors,4,0,34,11,64,0.0,5,2,Rural,ML Engineer,118212,0 +21643,Male,56,Bachelors,4,42,68,9,39,0.0,7,55,Urban,Software Engineer,94192,0 +21644,Male,45,Diploma,3,56,53,76,69,9.0,5,47,Urban,HR Executive,95443,0 +21645,Male,27,Masters,19,0,27,17,90,5.0,7,19,Semi-Urban,Data Analyst,51505,0 +21646,Other,39,Diploma,13,16,78,89,98,6.0,0,25,Rural,ML Engineer,101326,0 +21647,Female,29,Bachelors,5,43,27,96,34,4.0,0,46,Rural,Software Engineer,136219,0 +21648,Male,35,Bachelors,18,43,10,78,83,5.0,4,75,Semi-Urban,Data Analyst,73250,0 +21649,Female,27,High School,18,33,88,73,91,2.0,3,72,Urban,ML Engineer,62868,1 +21650,Female,32,Bachelors,0,97,58,48,37,9.0,2,55,Urban,HR Executive,53915,1 +21651,Male,33,Diploma,12,39,56,81,38,3.0,7,81,Rural,Software Engineer,33649,1 +21652,Female,39,Diploma,1,37,27,7,67,4.0,3,33,Rural,Software Engineer,118207,0 +21653,Female,58,Bachelors,11,27,41,20,27,0.0,1,89,Urban,HR Executive,79393,0 +21654,Male,53,Masters,14,46,66,42,16,4.0,0,84,Urban,ML Engineer,32735,1 +21655,Female,59,Diploma,9,61,98,47,23,1.0,3,70,Rural,Software Engineer,43357,1 +21656,Male,40,Masters,18,85,33,17,76,9.0,4,18,Urban,Software Engineer,21950,0 +21657,Male,22,Bachelors,1,79,75,45,27,0.0,0,95,Rural,ML Engineer,122084,1 +21658,Male,33,Diploma,13,14,15,57,67,8.0,0,9,Urban,ML Engineer,45326,0 +21659,Other,59,High School,17,45,33,90,4,6.0,5,32,Semi-Urban,Manager,146188,0 +21660,Female,53,Diploma,1,70,91,43,64,4.0,4,50,Urban,Data Analyst,133904,1 +21661,Male,57,Diploma,4,70,90,2,65,7.0,7,6,Rural,Software Engineer,136181,0 +21662,Male,30,Bachelors,13,35,27,53,17,9.0,3,69,Semi-Urban,Data Analyst,28123,0 +21663,Male,44,High School,5,49,4,91,16,5.0,2,22,Semi-Urban,Software Engineer,101495,0 +21664,Female,46,High School,14,29,39,75,9,7.0,5,76,Urban,Manager,68321,0 +21665,Male,51,Masters,13,92,95,6,97,0.0,7,8,Urban,Data Analyst,23985,0 +21666,Female,31,Bachelors,5,68,98,74,19,0.0,0,66,Urban,Data Analyst,81480,1 +21667,Female,33,Diploma,19,20,31,6,93,7.0,1,55,Urban,HR Executive,56856,0 +21668,Female,57,PhD,1,86,80,88,63,1.0,6,4,Urban,Software Engineer,27255,1 +21669,Male,34,Masters,7,32,42,49,99,2.0,7,54,Urban,HR Executive,92565,0 +21670,Male,42,Bachelors,19,59,92,48,57,9.0,4,34,Urban,Software Engineer,41665,0 +21671,Male,25,Bachelors,13,1,2,71,16,3.0,6,5,Semi-Urban,Manager,119745,0 +21672,Female,55,Bachelors,13,74,78,72,4,9.0,4,40,Urban,Manager,117234,1 +21673,Female,57,Diploma,8,83,18,26,56,9.0,5,38,Urban,ML Engineer,120303,0 +21674,Male,30,PhD,16,18,3,56,62,0.0,0,42,Rural,Data Analyst,62793,0 +21675,Male,48,Bachelors,2,90,6,35,49,8.0,4,25,Urban,Data Analyst,118029,0 +21676,Female,45,High School,4,89,19,32,57,1.0,7,2,Urban,ML Engineer,147504,0 +21677,Male,33,Diploma,8,57,41,20,65,7.0,3,45,Rural,HR Executive,142166,0 +21678,Male,47,PhD,18,74,40,64,57,0.0,7,47,Urban,HR Executive,56399,0 +21679,Female,33,High School,3,84,72,68,46,3.0,6,70,Urban,Manager,133819,1 +21680,Male,52,High School,9,92,74,53,75,2.0,5,11,Semi-Urban,Manager,23507,0 +21681,Female,48,Bachelors,4,17,57,90,65,4.0,4,87,Semi-Urban,Manager,149247,1 +21682,Female,47,Diploma,9,65,56,61,50,0.0,0,33,Rural,HR Executive,78672,0 +21683,Female,34,Masters,7,77,59,29,52,1.0,4,66,Urban,Data Analyst,44485,0 +21684,Male,48,Bachelors,13,67,14,18,52,3.0,7,54,Semi-Urban,Data Analyst,22722,0 +21685,Male,29,Bachelors,12,23,78,65,63,6.0,1,44,Semi-Urban,HR Executive,147271,0 +21686,Male,24,High School,6,47,95,18,86,3.0,1,86,Semi-Urban,Software Engineer,113737,1 +21687,Male,21,High School,5,87,10,99,17,3.0,4,73,Urban,HR Executive,137935,1 +21688,Other,53,Bachelors,5,32,78,44,23,9.0,2,59,Rural,HR Executive,99024,0 +21689,Female,46,High School,19,18,45,77,75,3.0,5,11,Urban,Software Engineer,80268,0 +21690,Male,21,Diploma,11,53,48,39,42,3.0,7,70,Semi-Urban,Data Analyst,113047,0 +21691,Female,25,Diploma,11,28,83,73,56,0.0,3,52,Urban,Software Engineer,49193,0 +21692,Female,50,High School,14,2,42,39,30,2.0,0,97,Urban,HR Executive,104796,0 +21693,Male,56,High School,11,53,49,92,45,6.0,0,57,Semi-Urban,Software Engineer,60538,1 +21694,Male,45,Bachelors,18,75,85,86,87,4.0,3,71,Semi-Urban,Data Analyst,101428,1 +21695,Male,56,Diploma,13,90,7,47,6,8.0,6,90,Semi-Urban,Software Engineer,63897,0 +21696,Other,50,Bachelors,18,10,84,66,76,6.0,7,7,Urban,ML Engineer,42030,0 +21697,Male,50,Bachelors,4,79,74,27,44,1.0,1,81,Urban,Manager,146734,1 +21698,Female,51,PhD,14,77,17,62,94,2.0,6,40,Urban,Data Analyst,140280,0 +21699,Male,59,Masters,2,51,14,1,42,4.0,1,84,Semi-Urban,Software Engineer,64477,0 +21700,Female,22,Diploma,1,8,55,71,78,6.0,4,85,Urban,HR Executive,34381,0 +21701,Male,52,High School,5,36,36,35,43,6.0,4,47,Urban,HR Executive,70198,0 +21702,Other,30,Bachelors,14,29,82,62,28,6.0,1,42,Urban,ML Engineer,51198,0 +21703,Female,30,Bachelors,11,65,77,68,50,1.0,1,61,Urban,Software Engineer,142880,1 +21704,Male,38,Bachelors,5,56,87,77,88,1.0,2,81,Urban,Manager,142389,1 +21705,Female,56,Bachelors,2,13,76,17,99,7.0,6,4,Urban,ML Engineer,123022,0 +21706,Female,56,Masters,17,76,98,90,86,4.0,4,30,Semi-Urban,Manager,56820,1 +21707,Female,45,High School,14,86,75,63,48,9.0,4,54,Urban,Manager,75147,1 +21708,Male,47,Bachelors,1,86,50,51,17,5.0,1,12,Rural,Software Engineer,73231,0 +21709,Male,25,Masters,2,18,44,87,77,4.0,2,10,Urban,Data Analyst,83025,0 +21710,Female,46,Diploma,15,41,63,16,5,9.0,3,87,Urban,HR Executive,124003,0 +21711,Female,57,Bachelors,18,94,94,10,54,9.0,4,76,Rural,Data Analyst,21767,1 +21712,Male,23,Masters,10,69,77,34,83,3.0,3,31,Urban,Data Analyst,32676,0 +21713,Female,50,Diploma,17,42,87,43,62,8.0,0,4,Semi-Urban,Software Engineer,124408,0 +21714,Male,41,Diploma,5,59,43,20,95,3.0,3,32,Rural,HR Executive,91298,0 +21715,Female,22,Masters,10,61,48,26,25,4.0,5,88,Urban,Software Engineer,72317,0 +21716,Male,36,Bachelors,0,42,17,45,76,0.0,5,12,Urban,Manager,107378,0 +21717,Male,49,Diploma,13,18,99,1,96,3.0,6,41,Urban,HR Executive,76829,0 +21718,Male,26,Diploma,2,82,86,50,72,9.0,2,70,Urban,HR Executive,111146,1 +21719,Male,48,Masters,16,45,52,30,46,1.0,6,11,Semi-Urban,HR Executive,52009,0 +21720,Male,32,Bachelors,19,88,50,88,16,1.0,4,52,Semi-Urban,ML Engineer,142029,1 +21721,Male,50,Masters,15,66,20,40,76,4.0,1,67,Semi-Urban,Data Analyst,112895,0 +21722,Male,58,Masters,11,3,49,6,8,2.0,0,15,Semi-Urban,Data Analyst,80305,0 +21723,Male,39,Bachelors,3,11,66,86,83,1.0,6,33,Urban,HR Executive,131485,0 +21724,Female,25,Masters,17,99,36,38,6,2.0,7,92,Rural,HR Executive,95995,1 +21725,Male,48,Masters,16,17,37,38,22,6.0,1,40,Rural,Manager,104002,0 +21726,Male,57,PhD,15,74,60,22,15,5.0,1,87,Urban,HR Executive,36762,1 +21727,Female,48,High School,4,57,23,8,51,4.0,7,49,Urban,Data Analyst,64399,0 +21728,Female,22,Masters,2,28,97,15,12,3.0,6,9,Rural,Data Analyst,27612,0 +21729,Female,22,Bachelors,0,29,86,11,77,2.0,1,86,Urban,Manager,101355,0 +21730,Male,21,Bachelors,0,88,28,87,55,4.0,2,38,Rural,Data Analyst,125811,1 +21731,Female,56,Masters,0,87,0,14,53,6.0,1,61,Urban,Manager,27458,0 +21732,Other,39,Diploma,0,77,97,54,19,0.0,6,48,Rural,Manager,125670,1 +21733,Male,59,Bachelors,12,49,61,99,50,8.0,5,20,Urban,Data Analyst,137897,0 +21734,Other,55,Masters,9,30,77,58,30,4.0,7,77,Semi-Urban,ML Engineer,20882,1 +21735,Male,26,Bachelors,19,5,83,88,65,5.0,6,87,Urban,ML Engineer,69617,1 +21736,Male,48,Diploma,19,46,31,25,53,7.0,0,28,Semi-Urban,Software Engineer,127859,0 +21737,Male,53,Masters,11,47,5,6,65,2.0,3,26,Urban,Manager,22827,0 +21738,Female,48,Diploma,13,46,95,51,8,2.0,6,81,Semi-Urban,Manager,118731,1 +21739,Male,32,High School,12,64,99,45,99,4.0,3,50,Semi-Urban,ML Engineer,144891,1 +21740,Male,23,Bachelors,16,26,65,62,87,7.0,5,57,Semi-Urban,Data Analyst,126740,0 +21741,Male,57,Bachelors,15,26,61,72,85,8.0,5,16,Rural,HR Executive,130267,0 +21742,Male,33,Bachelors,4,31,76,48,57,5.0,2,10,Semi-Urban,HR Executive,77422,0 +21743,Male,53,Diploma,11,76,15,81,8,4.0,2,74,Rural,Data Analyst,131970,1 +21744,Male,36,Diploma,9,37,51,39,25,2.0,4,14,Urban,HR Executive,113090,0 +21745,Male,35,High School,18,46,69,44,3,7.0,0,4,Semi-Urban,HR Executive,134124,0 +21746,Other,59,Bachelors,11,45,74,42,3,3.0,0,23,Urban,HR Executive,33137,0 +21747,Male,28,Masters,10,68,15,65,44,7.0,2,22,Urban,ML Engineer,67579,0 +21748,Male,32,Bachelors,10,82,84,97,72,9.0,0,18,Rural,Data Analyst,93766,1 +21749,Male,40,Bachelors,12,83,66,82,5,5.0,1,14,Urban,Manager,84694,1 +21750,Male,23,Diploma,18,17,85,97,3,1.0,2,35,Urban,Data Analyst,24383,0 +21751,Male,29,Bachelors,17,57,2,55,1,5.0,6,27,Urban,Data Analyst,128301,0 +21752,Male,30,High School,16,13,29,64,13,9.0,1,17,Semi-Urban,Data Analyst,44791,0 +21753,Female,27,Bachelors,7,27,72,79,62,7.0,5,36,Rural,HR Executive,104288,0 +21754,Male,30,Diploma,4,25,13,24,45,3.0,4,25,Rural,HR Executive,97308,0 +21755,Male,42,High School,1,74,50,46,39,3.0,0,94,Urban,Manager,136765,1 +21756,Male,23,Bachelors,8,73,10,97,3,6.0,5,42,Semi-Urban,HR Executive,54029,0 +21757,Female,39,Diploma,10,70,35,95,10,2.0,2,42,Rural,HR Executive,38164,1 +21758,Female,44,Diploma,14,72,7,94,33,6.0,6,35,Urban,Software Engineer,21198,0 +21759,Male,43,Diploma,10,97,59,31,6,5.0,4,53,Semi-Urban,ML Engineer,123022,1 +21760,Male,44,Bachelors,14,35,63,55,25,7.0,4,66,Urban,HR Executive,97567,0 +21761,Other,27,Bachelors,4,41,58,56,67,7.0,0,17,Rural,HR Executive,60764,0 +21762,Male,22,High School,10,11,48,18,12,9.0,3,86,Rural,Manager,77863,0 +21763,Male,24,Bachelors,3,24,1,50,41,0.0,0,57,Urban,HR Executive,106120,0 +21764,Male,59,Bachelors,11,92,16,56,67,8.0,6,34,Semi-Urban,HR Executive,100235,0 +21765,Male,27,Bachelors,0,35,13,93,62,4.0,4,68,Urban,Software Engineer,23767,0 +21766,Other,56,Bachelors,12,12,57,77,98,4.0,4,49,Semi-Urban,Software Engineer,58842,0 +21767,Other,36,Bachelors,7,65,14,49,25,3.0,6,92,Urban,ML Engineer,99570,0 +21768,Female,46,Diploma,14,57,44,54,65,2.0,0,59,Urban,Manager,63632,0 +21769,Male,55,Bachelors,12,85,86,4,41,8.0,4,46,Rural,ML Engineer,46728,0 +21770,Male,22,Bachelors,3,8,91,4,17,6.0,2,37,Semi-Urban,Manager,49327,0 +21771,Male,44,Bachelors,1,14,9,62,51,6.0,3,25,Urban,ML Engineer,101046,0 +21772,Other,25,High School,7,83,54,4,37,9.0,2,17,Semi-Urban,Data Analyst,60456,0 +21773,Female,37,High School,4,81,4,76,17,8.0,5,40,Urban,Data Analyst,89532,0 +21774,Male,54,Bachelors,14,78,37,50,64,6.0,6,52,Semi-Urban,HR Executive,37992,0 +21775,Male,52,Bachelors,11,21,37,28,28,7.0,7,65,Urban,Software Engineer,28498,0 +21776,Male,42,Diploma,18,68,96,93,50,2.0,2,20,Rural,Data Analyst,65031,1 +21777,Other,35,Diploma,12,30,13,36,13,4.0,4,89,Urban,Data Analyst,106248,0 +21778,Male,39,High School,9,58,57,37,73,2.0,4,20,Semi-Urban,Manager,144623,0 +21779,Male,34,High School,3,38,50,41,9,1.0,1,93,Urban,Software Engineer,39301,0 +21780,Male,22,Bachelors,9,55,34,69,14,4.0,0,14,Urban,HR Executive,44984,0 +21781,Male,37,Bachelors,12,20,97,35,67,6.0,4,23,Urban,HR Executive,105357,0 +21782,Female,38,Diploma,5,39,27,42,66,0.0,4,64,Rural,Manager,77471,0 +21783,Other,55,Bachelors,15,1,38,45,20,2.0,1,21,Urban,Software Engineer,137677,0 +21784,Female,27,Bachelors,13,10,43,82,36,9.0,7,15,Semi-Urban,Manager,104530,0 +21785,Female,34,Masters,13,14,60,21,52,6.0,7,98,Urban,HR Executive,96887,0 +21786,Male,46,Diploma,15,59,25,96,73,4.0,7,41,Urban,Manager,38373,0 +21787,Male,32,High School,3,49,95,73,13,8.0,2,43,Semi-Urban,HR Executive,23480,1 +21788,Male,59,Masters,3,55,43,87,78,0.0,2,98,Rural,ML Engineer,25668,1 +21789,Female,37,High School,7,54,2,43,59,9.0,6,12,Semi-Urban,Manager,104085,0 +21790,Male,34,Diploma,14,91,30,78,25,8.0,7,66,Semi-Urban,Data Analyst,20172,1 +21791,Female,24,Masters,3,0,79,72,78,7.0,2,52,Semi-Urban,Manager,107196,0 +21792,Male,33,Diploma,6,9,55,53,19,6.0,3,77,Urban,HR Executive,71745,0 +21793,Male,50,Diploma,3,80,40,2,14,0.0,5,19,Semi-Urban,HR Executive,131878,0 +21794,Female,37,Masters,4,94,81,97,6,1.0,7,14,Urban,Manager,28187,1 +21795,Female,53,High School,10,27,59,37,93,4.0,7,77,Urban,HR Executive,49665,0 +21796,Male,39,Masters,19,8,77,32,43,2.0,7,25,Semi-Urban,ML Engineer,57443,0 +21797,Male,27,Masters,5,48,19,48,84,9.0,3,94,Urban,ML Engineer,26832,0 +21798,Female,25,Masters,9,68,53,40,87,9.0,6,59,Urban,Software Engineer,78816,0 +21799,Female,31,Bachelors,14,99,11,13,84,0.0,6,1,Semi-Urban,HR Executive,70729,0 +21800,Male,44,Bachelors,12,58,1,34,49,7.0,5,66,Urban,Software Engineer,49295,0 +21801,Male,32,Masters,6,15,36,9,26,1.0,2,17,Semi-Urban,ML Engineer,35380,0 +21802,Male,25,High School,12,3,25,82,81,8.0,4,54,Semi-Urban,ML Engineer,97501,0 +21803,Male,23,Diploma,0,58,19,71,89,7.0,3,7,Urban,Software Engineer,71704,0 +21804,Female,34,High School,14,39,75,43,0,4.0,4,63,Urban,Manager,108834,0 +21805,Male,50,Masters,12,23,38,55,95,9.0,5,91,Urban,Data Analyst,142100,0 +21806,Male,51,Bachelors,15,56,6,99,89,3.0,7,52,Urban,Manager,87783,0 +21807,Male,57,Bachelors,0,3,77,26,70,0.0,6,46,Rural,Manager,81418,0 +21808,Male,44,Diploma,4,90,70,10,30,9.0,3,52,Urban,HR Executive,121106,0 +21809,Male,38,Diploma,11,58,12,77,2,4.0,0,64,Rural,Manager,117518,0 +21810,Male,57,Masters,10,49,39,16,94,2.0,6,11,Urban,Software Engineer,135947,0 +21811,Male,45,Bachelors,10,36,56,18,43,5.0,7,74,Urban,HR Executive,110154,0 +21812,Male,36,High School,0,30,66,86,51,4.0,1,31,Urban,ML Engineer,146077,0 +21813,Male,45,Bachelors,0,92,29,72,18,1.0,5,43,Semi-Urban,ML Engineer,111603,1 +21814,Male,30,Masters,13,32,93,49,43,2.0,0,15,Semi-Urban,Software Engineer,147157,0 +21815,Female,58,Diploma,9,74,53,79,90,9.0,7,31,Urban,Software Engineer,138592,0 +21816,Male,55,Diploma,2,42,45,49,95,9.0,2,85,Rural,Data Analyst,148367,0 +21817,Male,38,Masters,14,51,31,42,14,9.0,2,63,Semi-Urban,Manager,55248,0 +21818,Male,45,Masters,14,10,73,27,77,2.0,2,87,Urban,Data Analyst,79824,0 +21819,Other,49,Bachelors,3,55,90,74,62,5.0,1,88,Urban,Manager,73443,1 +21820,Female,55,Bachelors,3,52,87,10,2,8.0,5,12,Urban,Software Engineer,38419,0 +21821,Male,32,Bachelors,12,36,57,96,29,7.0,1,28,Urban,Manager,40649,0 +21822,Female,27,Bachelors,12,35,45,76,59,0.0,1,91,Urban,Manager,68525,1 +21823,Male,44,Masters,11,71,55,56,41,4.0,2,86,Urban,HR Executive,29639,1 +21824,Male,57,Bachelors,18,68,36,23,78,2.0,7,17,Semi-Urban,Manager,75243,0 +21825,Male,45,Masters,1,91,1,25,67,6.0,7,55,Urban,Manager,83828,0 +21826,Male,39,Diploma,6,48,56,93,46,4.0,0,0,Urban,ML Engineer,110949,0 +21827,Male,55,Masters,10,5,2,42,97,2.0,4,69,Semi-Urban,Software Engineer,83050,0 +21828,Female,52,Bachelors,9,30,83,75,54,1.0,0,89,Rural,Data Analyst,77807,1 +21829,Female,31,High School,11,13,16,69,80,7.0,4,70,Urban,Software Engineer,36006,0 +21830,Male,40,Bachelors,11,35,9,10,8,0.0,1,26,Rural,Manager,143283,0 +21831,Male,27,Masters,19,53,15,93,96,8.0,4,50,Urban,HR Executive,119705,0 +21832,Male,35,Diploma,13,15,41,57,53,4.0,5,12,Semi-Urban,ML Engineer,104678,0 +21833,Male,39,Masters,5,78,77,37,69,2.0,1,13,Rural,HR Executive,32964,0 +21834,Other,46,Diploma,18,27,60,84,89,3.0,0,29,Urban,ML Engineer,38845,0 +21835,Female,40,Bachelors,0,32,3,55,29,3.0,2,87,Urban,Data Analyst,133249,0 +21836,Other,55,Masters,19,29,6,83,23,9.0,1,1,Urban,HR Executive,34205,0 +21837,Female,44,Masters,9,75,12,94,69,4.0,5,39,Urban,Data Analyst,108329,0 +21838,Male,48,Bachelors,7,90,5,20,97,4.0,3,25,Rural,Software Engineer,34804,0 +21839,Male,38,High School,17,25,96,69,85,8.0,1,48,Urban,Manager,146731,1 +21840,Male,49,Masters,10,59,46,46,50,5.0,0,88,Urban,ML Engineer,86808,1 +21841,Male,32,Bachelors,12,28,46,69,98,6.0,7,68,Urban,HR Executive,103692,0 +21842,Female,42,Masters,11,97,5,14,0,3.0,6,44,Rural,HR Executive,47022,0 +21843,Male,39,High School,12,21,15,48,42,7.0,7,41,Urban,ML Engineer,140058,0 +21844,Male,50,Bachelors,14,45,26,47,93,1.0,7,56,Semi-Urban,ML Engineer,133142,0 +21845,Female,49,PhD,15,98,10,34,51,9.0,3,43,Urban,HR Executive,74549,0 +21846,Female,23,Bachelors,7,71,63,91,24,5.0,5,72,Rural,ML Engineer,71177,1 +21847,Male,52,PhD,0,91,40,96,70,0.0,7,76,Semi-Urban,Software Engineer,43387,1 +21848,Female,33,Bachelors,19,75,47,20,93,8.0,5,53,Rural,Software Engineer,96285,0 +21849,Male,29,Diploma,2,65,83,26,77,0.0,6,4,Urban,Manager,35289,0 +21850,Male,43,Bachelors,9,73,38,4,11,4.0,6,19,Urban,Manager,21551,0 +21851,Male,35,Diploma,6,29,98,64,31,6.0,5,65,Urban,Software Engineer,108739,1 +21852,Male,39,Diploma,19,83,81,69,72,3.0,5,30,Urban,HR Executive,38092,1 +21853,Female,27,Masters,9,76,75,84,20,0.0,4,72,Urban,HR Executive,108788,1 +21854,Male,45,Masters,14,7,66,6,97,2.0,0,90,Semi-Urban,HR Executive,73369,0 +21855,Female,36,High School,12,28,64,53,66,7.0,2,2,Urban,Manager,127890,0 +21856,Female,58,High School,7,13,15,31,2,5.0,5,2,Urban,ML Engineer,123788,0 +21857,Male,41,Bachelors,9,79,88,27,49,8.0,2,27,Urban,Software Engineer,39426,0 +21858,Female,34,High School,2,18,55,90,22,6.0,5,37,Urban,HR Executive,124911,0 +21859,Male,40,High School,18,9,5,55,11,2.0,1,33,Rural,Software Engineer,90019,0 +21860,Male,29,PhD,6,88,1,44,61,9.0,4,66,Urban,HR Executive,21777,0 +21861,Female,46,Diploma,4,23,93,12,10,0.0,0,93,Urban,Manager,77119,0 +21862,Female,21,Diploma,7,12,81,7,77,9.0,3,16,Semi-Urban,Manager,137182,0 +21863,Male,41,Bachelors,14,15,87,24,48,7.0,1,24,Urban,Data Analyst,41670,0 +21864,Female,26,Bachelors,18,64,17,11,74,3.0,0,63,Semi-Urban,Software Engineer,145633,0 +21865,Male,50,High School,12,14,0,76,42,7.0,7,66,Urban,HR Executive,75509,0 +21866,Other,30,Bachelors,9,84,47,93,38,4.0,4,82,Semi-Urban,ML Engineer,144866,1 +21867,Male,48,PhD,12,12,72,39,43,6.0,0,82,Rural,Manager,111768,0 +21868,Male,39,Bachelors,7,12,63,47,56,1.0,1,43,Urban,Data Analyst,99109,0 +21869,Male,42,Bachelors,16,20,45,73,75,9.0,2,64,Urban,HR Executive,136861,0 +21870,Male,43,Diploma,3,4,26,82,84,6.0,7,74,Urban,HR Executive,75852,0 +21871,Male,38,Masters,16,0,3,68,74,5.0,3,30,Rural,ML Engineer,52391,0 +21872,Female,48,PhD,11,67,60,5,98,1.0,2,9,Semi-Urban,HR Executive,135328,0 +21873,Male,52,Bachelors,1,82,87,88,38,2.0,5,55,Rural,ML Engineer,99134,1 +21874,Male,57,Bachelors,15,2,75,9,97,0.0,7,52,Semi-Urban,HR Executive,97424,0 +21875,Male,42,PhD,10,64,60,32,46,9.0,2,64,Rural,Software Engineer,69410,0 +21876,Male,37,Diploma,9,57,80,6,71,5.0,7,1,Urban,ML Engineer,32845,0 +21877,Female,52,Bachelors,0,8,68,4,20,0.0,0,55,Semi-Urban,Manager,49193,0 +21878,Female,36,Bachelors,16,48,36,0,91,3.0,6,80,Urban,Data Analyst,82539,0 +21879,Other,44,Diploma,7,71,43,55,35,3.0,5,92,Urban,ML Engineer,112742,1 +21880,Male,24,Masters,6,86,10,44,99,8.0,0,15,Rural,HR Executive,87735,0 +21881,Male,49,High School,5,78,0,15,56,9.0,2,78,Semi-Urban,Manager,60167,0 +21882,Male,55,Masters,1,33,98,47,46,8.0,2,58,Urban,Manager,143466,1 +21883,Female,46,Bachelors,5,63,81,55,49,1.0,1,18,Semi-Urban,Manager,35351,0 +21884,Female,52,Bachelors,17,93,46,83,97,9.0,7,66,Urban,Software Engineer,145100,1 +21885,Male,34,High School,12,35,48,79,18,1.0,1,66,Rural,Software Engineer,82213,0 +21886,Male,42,Bachelors,19,45,6,13,71,8.0,0,39,Rural,HR Executive,81726,0 +21887,Female,24,Bachelors,8,32,98,26,11,5.0,4,86,Urban,Manager,44380,1 +21888,Female,57,Masters,8,76,87,8,43,3.0,7,13,Semi-Urban,ML Engineer,120231,0 +21889,Female,42,High School,13,84,38,34,12,6.0,3,65,Urban,Data Analyst,45540,0 +21890,Male,43,Masters,16,38,91,90,45,6.0,6,24,Urban,Manager,22555,1 +21891,Other,56,Bachelors,1,15,31,74,92,6.0,3,5,Rural,Data Analyst,28952,0 +21892,Male,42,Bachelors,11,35,44,72,90,1.0,0,42,Rural,HR Executive,49854,0 +21893,Other,53,Masters,8,32,0,7,70,7.0,6,89,Urban,HR Executive,85356,0 +21894,Female,45,Masters,7,92,33,43,84,7.0,2,1,Semi-Urban,Software Engineer,116446,0 +21895,Female,25,PhD,11,72,17,42,7,2.0,7,51,Semi-Urban,ML Engineer,39936,0 +21896,Female,59,Masters,15,5,50,28,99,4.0,4,3,Rural,ML Engineer,132481,0 +21897,Male,49,Bachelors,10,52,76,45,33,5.0,2,96,Semi-Urban,ML Engineer,63564,1 +21898,Male,39,Masters,2,25,97,45,79,4.0,5,48,Urban,HR Executive,98695,0 +21899,Male,39,High School,8,20,73,96,30,7.0,1,29,Urban,HR Executive,118799,0 +21900,Male,28,Masters,11,89,21,48,11,3.0,6,88,Semi-Urban,Data Analyst,44346,1 +21901,Male,51,Diploma,6,97,13,39,30,0.0,0,80,Urban,ML Engineer,28811,0 +21902,Male,54,Masters,2,45,73,55,43,5.0,7,44,Semi-Urban,Data Analyst,45376,0 +21903,Female,24,Bachelors,6,0,52,60,57,0.0,3,83,Rural,Data Analyst,76349,0 +21904,Male,42,Diploma,11,37,59,80,88,9.0,5,87,Urban,Manager,104429,1 +21905,Female,51,Bachelors,1,89,49,61,61,9.0,5,2,Semi-Urban,Manager,115920,0 +21906,Female,24,PhD,19,84,54,24,95,1.0,3,42,Urban,Data Analyst,137746,0 +21907,Male,50,Masters,9,77,57,80,43,2.0,6,40,Semi-Urban,HR Executive,136778,1 +21908,Male,38,Bachelors,15,50,5,25,26,3.0,3,27,Urban,HR Executive,30681,0 +21909,Male,46,High School,3,59,94,31,46,0.0,1,94,Urban,Data Analyst,86456,1 +21910,Female,52,Masters,15,78,40,83,88,3.0,1,15,Urban,Data Analyst,31288,0 +21911,Male,51,Bachelors,10,65,19,51,57,5.0,0,49,Rural,Software Engineer,50755,0 +21912,Male,40,Masters,1,36,32,49,78,9.0,1,19,Urban,ML Engineer,70357,0 +21913,Female,29,High School,14,50,95,89,76,2.0,2,1,Urban,ML Engineer,124726,0 +21914,Male,50,Bachelors,17,5,19,20,37,7.0,5,48,Semi-Urban,ML Engineer,120138,0 +21915,Female,37,Masters,11,62,37,52,44,2.0,7,83,Urban,HR Executive,89049,0 +21916,Male,25,High School,15,11,82,85,37,7.0,3,42,Rural,ML Engineer,133412,0 +21917,Female,50,High School,13,15,86,0,77,2.0,7,20,Urban,Software Engineer,69535,0 +21918,Female,22,Diploma,18,2,81,75,6,0.0,5,1,Rural,HR Executive,56732,0 +21919,Female,54,Bachelors,17,10,58,9,39,6.0,1,98,Urban,Data Analyst,114078,0 +21920,Male,51,Bachelors,0,3,10,75,89,7.0,2,7,Urban,Manager,131698,0 +21921,Male,50,Bachelors,1,6,67,50,78,9.0,7,11,Urban,Manager,67592,0 +21922,Female,46,Masters,12,4,91,45,95,0.0,2,85,Urban,Manager,135546,0 +21923,Male,29,Bachelors,19,40,14,73,93,6.0,4,38,Semi-Urban,Data Analyst,35315,0 +21924,Male,34,Diploma,10,77,52,88,37,8.0,3,29,Urban,Manager,21682,1 +21925,Female,41,Bachelors,8,51,9,34,40,9.0,3,59,Urban,ML Engineer,83645,0 +21926,Male,51,Bachelors,2,35,64,84,42,9.0,1,46,Semi-Urban,ML Engineer,89366,0 +21927,Male,28,Masters,4,60,7,47,11,5.0,1,67,Urban,HR Executive,132381,0 +21928,Female,48,Diploma,7,46,80,17,89,5.0,5,69,Semi-Urban,Software Engineer,90375,0 +21929,Male,41,Bachelors,14,65,53,66,53,3.0,2,69,Urban,Data Analyst,143110,1 +21930,Male,53,Bachelors,18,80,93,93,16,9.0,0,54,Semi-Urban,Manager,99842,1 +21931,Female,43,Bachelors,7,56,70,15,90,8.0,3,41,Rural,ML Engineer,30101,0 +21932,Female,35,Bachelors,14,87,95,38,77,9.0,7,38,Rural,HR Executive,125424,1 +21933,Male,50,Bachelors,4,99,6,6,1,1.0,2,38,Rural,Data Analyst,113064,0 +21934,Female,43,Diploma,6,58,22,2,58,3.0,6,31,Rural,HR Executive,140019,0 +21935,Female,59,Bachelors,18,62,6,8,23,8.0,0,26,Semi-Urban,Software Engineer,130984,0 +21936,Male,42,Masters,14,6,19,43,68,1.0,7,62,Semi-Urban,ML Engineer,128523,0 +21937,Male,40,Bachelors,19,78,47,7,24,3.0,0,36,Urban,Software Engineer,124123,0 +21938,Male,54,Masters,4,40,71,60,69,0.0,1,7,Rural,ML Engineer,79217,0 +21939,Female,43,Diploma,8,68,72,79,0,7.0,7,65,Urban,Software Engineer,110585,1 +21940,Female,26,Diploma,4,61,21,65,26,1.0,6,11,Urban,ML Engineer,125642,0 +21941,Male,24,Masters,11,76,39,10,98,7.0,0,28,Urban,ML Engineer,138301,0 +21942,Female,30,Bachelors,16,98,96,46,67,7.0,5,3,Rural,Data Analyst,75086,1 +21943,Female,58,Diploma,1,76,67,88,30,7.0,2,83,Urban,Manager,87840,1 +21944,Male,56,Bachelors,13,95,47,78,82,1.0,2,19,Urban,Manager,52430,1 +21945,Female,32,Masters,15,76,13,60,89,1.0,5,68,Urban,Data Analyst,104343,0 +21946,Male,44,Bachelors,14,78,89,45,28,2.0,5,4,Rural,Software Engineer,67350,0 +21947,Female,25,High School,8,65,9,35,58,2.0,1,49,Urban,Software Engineer,35014,0 +21948,Male,58,Diploma,14,83,20,47,46,8.0,4,83,Rural,HR Executive,98403,0 +21949,Female,26,Bachelors,3,0,44,90,3,7.0,7,21,Semi-Urban,ML Engineer,78415,0 +21950,Female,55,Diploma,12,29,88,84,46,7.0,3,46,Semi-Urban,ML Engineer,20617,1 +21951,Male,45,Diploma,4,46,75,57,56,9.0,3,99,Urban,Software Engineer,55854,1 +21952,Female,25,Bachelors,5,19,45,42,29,6.0,1,63,Urban,HR Executive,81678,0 +21953,Female,59,Bachelors,8,39,36,88,69,1.0,3,24,Rural,Manager,65977,0 +21954,Female,28,Bachelors,10,1,61,47,84,6.0,7,71,Urban,Manager,59222,0 +21955,Male,36,Bachelors,10,37,6,87,26,9.0,3,58,Rural,ML Engineer,35156,0 +21956,Male,59,Diploma,15,81,47,41,65,7.0,5,9,Semi-Urban,HR Executive,120786,0 +21957,Female,51,High School,12,85,1,60,92,3.0,6,17,Rural,ML Engineer,37435,0 +21958,Female,36,PhD,7,12,59,43,54,0.0,6,45,Urban,Software Engineer,24039,0 +21959,Female,23,Diploma,16,47,98,80,74,2.0,6,69,Semi-Urban,Data Analyst,60894,1 +21960,Other,39,Bachelors,3,16,60,82,5,8.0,4,61,Urban,Data Analyst,108462,0 +21961,Male,33,Masters,7,65,34,65,17,0.0,1,53,Urban,Manager,42146,0 +21962,Male,33,Diploma,3,66,98,14,45,5.0,6,20,Urban,HR Executive,112540,0 +21963,Male,26,High School,2,1,46,48,40,0.0,5,23,Semi-Urban,ML Engineer,33024,0 +21964,Female,59,High School,12,73,82,77,19,6.0,0,6,Semi-Urban,Data Analyst,78698,0 +21965,Female,43,Diploma,17,37,23,99,35,8.0,4,84,Urban,Manager,123236,1 +21966,Other,26,Masters,6,35,82,56,87,0.0,5,38,Urban,HR Executive,75801,0 +21967,Male,24,Masters,3,5,23,9,48,5.0,2,10,Semi-Urban,Software Engineer,106191,0 +21968,Female,59,Bachelors,7,3,62,25,69,9.0,6,14,Rural,HR Executive,89686,0 +21969,Female,55,Masters,1,81,47,82,71,9.0,7,93,Urban,Software Engineer,120917,1 +21970,Female,55,Bachelors,14,50,28,19,8,0.0,5,4,Rural,HR Executive,45710,0 +21971,Male,37,Masters,9,82,8,9,96,2.0,1,39,Urban,ML Engineer,94114,0 +21972,Female,58,Bachelors,19,71,32,94,10,2.0,7,91,Urban,HR Executive,62330,1 +21973,Other,45,Diploma,12,32,32,92,6,8.0,0,81,Rural,Manager,118585,0 +21974,Other,49,Bachelors,1,79,19,13,86,5.0,4,81,Urban,ML Engineer,100671,0 +21975,Female,26,Diploma,4,77,9,72,16,6.0,4,90,Urban,Software Engineer,81379,1 +21976,Female,34,Masters,19,47,56,30,42,2.0,1,76,Urban,ML Engineer,48750,0 +21977,Male,47,Masters,14,82,2,66,9,9.0,6,3,Urban,Data Analyst,59969,0 +21978,Male,55,Masters,9,74,56,25,37,4.0,4,83,Urban,Data Analyst,120566,1 +21979,Other,26,Bachelors,0,10,3,68,50,2.0,1,21,Urban,ML Engineer,59500,0 +21980,Male,28,High School,7,75,52,40,1,4.0,7,48,Rural,Software Engineer,96221,0 +21981,Male,50,Masters,14,51,62,88,84,8.0,3,97,Urban,ML Engineer,103592,1 +21982,Male,48,Bachelors,3,70,36,60,87,3.0,2,48,Urban,HR Executive,67306,0 +21983,Male,47,Diploma,4,92,70,24,73,3.0,0,8,Rural,Data Analyst,70209,0 +21984,Female,53,Bachelors,7,88,61,24,72,8.0,7,64,Rural,Software Engineer,32794,0 +21985,Male,46,Bachelors,14,7,82,36,33,8.0,6,19,Urban,Manager,73934,0 +21986,Female,36,PhD,13,87,71,6,51,0.0,2,59,Urban,ML Engineer,30908,0 +21987,Female,34,Masters,9,1,9,63,46,4.0,3,44,Semi-Urban,HR Executive,56494,0 +21988,Male,44,Diploma,8,53,5,7,59,7.0,5,80,Semi-Urban,Software Engineer,136748,0 +21989,Male,51,Masters,18,33,0,22,75,4.0,3,63,Urban,HR Executive,98976,0 +21990,Female,21,Masters,18,97,96,74,71,9.0,3,89,Rural,Manager,135553,1 +21991,Female,40,High School,6,63,41,62,40,0.0,6,84,Urban,HR Executive,65127,1 +21992,Male,52,Masters,10,1,58,68,99,3.0,7,61,Urban,Data Analyst,132011,0 +21993,Male,42,Diploma,11,21,32,82,66,5.0,0,38,Urban,ML Engineer,89128,0 +21994,Male,44,High School,8,58,44,70,41,9.0,4,63,Urban,Data Analyst,140564,1 +21995,Male,55,Bachelors,18,44,55,41,93,8.0,2,97,Rural,ML Engineer,138433,1 +21996,Male,22,Bachelors,8,77,0,60,9,3.0,3,70,Semi-Urban,ML Engineer,124097,0 +21997,Female,26,Masters,0,85,0,14,64,5.0,5,7,Urban,Software Engineer,34176,0 +21998,Female,21,Masters,1,39,32,17,41,2.0,1,74,Urban,Data Analyst,141088,0 +21999,Female,57,Bachelors,8,38,88,38,10,2.0,2,45,Urban,Data Analyst,99915,0 +22000,Male,51,Bachelors,18,20,56,30,70,2.0,4,7,Semi-Urban,Software Engineer,90657,0 +22001,Female,21,High School,8,78,24,29,12,9.0,0,59,Urban,HR Executive,45161,0 +22002,Male,52,Diploma,10,88,39,32,73,1.0,7,14,Urban,ML Engineer,123784,0 +22003,Male,45,Diploma,15,80,79,65,55,9.0,1,1,Urban,ML Engineer,84288,0 +22004,Female,22,Bachelors,3,45,30,33,90,5.0,3,67,Urban,HR Executive,124135,0 +22005,Female,47,Bachelors,1,31,7,86,21,6.0,5,58,Rural,Data Analyst,131975,0 +22006,Male,26,High School,16,2,75,78,64,2.0,5,68,Urban,Manager,32466,0 +22007,Female,37,Bachelors,14,7,29,18,76,4.0,2,37,Urban,Software Engineer,97390,0 +22008,Female,24,Masters,11,21,59,57,65,3.0,0,70,Urban,HR Executive,132389,0 +22009,Male,58,High School,14,58,66,48,12,3.0,7,15,Urban,Manager,62130,0 +22010,Female,36,Diploma,8,74,18,2,5,2.0,7,76,Urban,Manager,117610,0 +22011,Other,40,Diploma,18,8,45,2,67,1.0,4,74,Urban,Manager,104856,0 +22012,Female,56,Masters,6,18,72,85,7,1.0,7,96,Urban,Software Engineer,127194,1 +22013,Male,51,High School,2,38,3,25,26,7.0,3,90,Urban,HR Executive,131937,0 +22014,Male,49,Bachelors,2,15,65,85,5,6.0,5,55,Semi-Urban,Manager,67481,0 +22015,Male,21,Masters,6,73,53,66,81,9.0,7,89,Urban,HR Executive,32369,1 +22016,Male,40,Diploma,14,16,52,19,29,5.0,7,57,Urban,ML Engineer,80320,0 +22017,Female,47,Masters,16,75,17,39,7,9.0,2,43,Urban,Data Analyst,68741,0 +22018,Male,23,Bachelors,12,25,48,27,72,3.0,1,38,Urban,Manager,79504,0 +22019,Other,52,Bachelors,3,10,19,4,36,1.0,3,61,Urban,Software Engineer,64125,0 +22020,Male,37,Masters,5,22,74,30,18,9.0,1,47,Urban,Software Engineer,68005,0 +22021,Female,27,Masters,3,11,74,80,27,4.0,7,7,Urban,Data Analyst,139397,0 +22022,Male,38,High School,12,61,86,32,29,6.0,3,93,Urban,ML Engineer,98524,1 +22023,Male,25,Masters,7,46,64,44,86,9.0,3,40,Urban,Data Analyst,47185,0 +22024,Female,23,Bachelors,9,62,67,93,54,8.0,0,55,Urban,Data Analyst,84138,1 +22025,Male,35,Bachelors,7,44,4,42,78,6.0,3,59,Semi-Urban,Software Engineer,73191,0 +22026,Male,32,Masters,9,32,32,76,89,8.0,6,78,Rural,Manager,96969,0 +22027,Male,54,Masters,17,27,55,17,90,8.0,3,22,Rural,HR Executive,41156,0 +22028,Male,23,Diploma,17,70,86,13,80,8.0,7,18,Urban,Manager,29499,0 +22029,Female,28,Diploma,11,38,46,78,45,3.0,5,93,Urban,Software Engineer,126390,1 +22030,Other,22,Diploma,1,54,47,29,66,2.0,1,43,Urban,Data Analyst,143660,0 +22031,Male,39,Bachelors,2,27,66,73,20,7.0,6,4,Semi-Urban,Software Engineer,147189,0 +22032,Male,57,Masters,3,59,26,78,92,6.0,6,42,Semi-Urban,HR Executive,29955,0 +22033,Female,52,Bachelors,15,50,1,51,51,4.0,1,45,Urban,Data Analyst,46841,0 +22034,Other,43,Bachelors,5,3,69,11,67,5.0,6,64,Semi-Urban,HR Executive,45428,0 +22035,Female,37,High School,18,48,53,52,55,5.0,0,30,Urban,Software Engineer,87797,0 +22036,Female,56,Bachelors,12,42,6,20,54,7.0,6,32,Urban,HR Executive,136283,0 +22037,Male,35,PhD,19,66,29,66,9,0.0,2,40,Rural,ML Engineer,84105,0 +22038,Male,46,Masters,11,0,18,43,17,9.0,3,57,Urban,Manager,73905,0 +22039,Male,25,High School,0,93,7,55,98,7.0,3,91,Urban,ML Engineer,79265,1 +22040,Male,48,Diploma,9,66,11,33,10,9.0,2,50,Semi-Urban,ML Engineer,31764,0 +22041,Female,45,Bachelors,10,21,17,12,5,7.0,6,49,Semi-Urban,Manager,71098,0 +22042,Female,34,Bachelors,9,82,51,20,22,0.0,5,24,Semi-Urban,ML Engineer,142550,0 +22043,Female,35,Bachelors,19,73,25,54,16,4.0,6,70,Semi-Urban,ML Engineer,73843,0 +22044,Male,36,Masters,0,42,25,3,86,7.0,3,97,Urban,Manager,138555,0 +22045,Female,42,High School,5,15,79,54,82,6.0,4,56,Urban,Data Analyst,72954,0 +22046,Male,39,Diploma,14,46,52,86,78,8.0,2,49,Urban,Software Engineer,72588,0 +22047,Male,34,Masters,15,64,12,41,63,2.0,1,55,Semi-Urban,Manager,78508,0 +22048,Male,55,Masters,12,85,69,56,81,7.0,3,26,Semi-Urban,Manager,136475,1 +22049,Female,47,Bachelors,18,25,59,31,91,7.0,2,30,Urban,Data Analyst,50233,0 +22050,Male,34,High School,14,53,22,87,75,6.0,6,35,Rural,HR Executive,95173,0 +22051,Female,50,High School,15,98,34,66,55,9.0,5,3,Urban,Software Engineer,62967,0 +22052,Male,22,Masters,18,15,94,87,91,4.0,2,87,Rural,Data Analyst,107830,1 +22053,Male,38,Bachelors,5,67,79,49,50,5.0,0,74,Semi-Urban,ML Engineer,128022,1 +22054,Female,34,Bachelors,5,50,88,40,87,8.0,5,70,Urban,ML Engineer,23015,1 +22055,Male,59,Masters,9,36,78,53,13,0.0,6,64,Semi-Urban,ML Engineer,60174,0 +22056,Male,29,Bachelors,6,42,62,16,61,5.0,5,98,Urban,ML Engineer,129886,0 +22057,Male,42,Bachelors,14,97,52,16,35,9.0,1,19,Urban,ML Engineer,53484,0 +22058,Female,32,Diploma,0,66,24,96,11,3.0,1,67,Urban,Manager,39053,1 +22059,Male,31,Diploma,18,37,60,37,53,8.0,3,80,Semi-Urban,Software Engineer,115576,0 +22060,Male,28,Bachelors,16,98,31,29,38,2.0,3,79,Urban,Software Engineer,100023,1 +22061,Male,52,Diploma,19,40,69,76,17,8.0,0,91,Urban,HR Executive,42429,1 +22062,Male,57,Bachelors,11,79,59,64,48,5.0,3,46,Rural,Software Engineer,131422,1 +22063,Male,43,Diploma,9,4,61,11,66,9.0,0,74,Urban,Manager,95669,0 +22064,Female,58,Diploma,12,68,77,85,30,3.0,5,80,Semi-Urban,Software Engineer,129329,1 +22065,Female,42,Masters,6,43,95,81,17,4.0,4,75,Urban,Software Engineer,42274,1 +22066,Male,46,Diploma,6,70,51,68,7,7.0,5,13,Urban,HR Executive,78462,0 +22067,Female,27,Bachelors,19,37,62,81,23,7.0,6,64,Urban,Software Engineer,131705,1 +22068,Female,49,Bachelors,8,83,41,78,42,3.0,4,75,Urban,Software Engineer,70186,1 +22069,Female,56,Masters,9,17,11,74,64,2.0,1,15,Urban,Data Analyst,130136,0 +22070,Male,52,Bachelors,6,98,12,94,19,6.0,3,94,Semi-Urban,HR Executive,51953,1 +22071,Male,39,High School,11,77,76,59,84,0.0,4,61,Semi-Urban,Software Engineer,123294,1 +22072,Female,32,Bachelors,14,34,50,35,92,9.0,6,71,Urban,HR Executive,22385,0 +22073,Male,58,Bachelors,7,49,35,82,30,1.0,0,30,Rural,ML Engineer,66972,0 +22074,Male,46,Masters,15,34,87,68,99,8.0,0,51,Urban,Software Engineer,89176,1 +22075,Female,51,Masters,3,94,30,36,61,3.0,0,39,Urban,HR Executive,115973,0 +22076,Male,33,Masters,0,13,5,8,21,5.0,2,21,Urban,HR Executive,65902,0 +22077,Male,23,Bachelors,19,72,94,92,61,0.0,0,53,Semi-Urban,Software Engineer,51631,1 +22078,Male,49,Bachelors,16,16,48,78,32,3.0,2,70,Urban,HR Executive,81413,0 +22079,Female,52,High School,5,49,47,16,56,1.0,3,47,Urban,Manager,44738,0 +22080,Male,48,Bachelors,14,99,69,90,5,1.0,5,63,Urban,Manager,32203,1 +22081,Female,32,High School,9,18,69,74,9,5.0,0,38,Rural,HR Executive,122795,0 +22082,Female,40,Masters,1,29,13,24,70,8.0,6,10,Urban,Manager,33374,0 +22083,Male,25,Bachelors,13,69,56,79,99,7.0,4,98,Rural,Manager,35813,1 +22084,Male,50,Bachelors,5,72,33,94,66,5.0,1,66,Semi-Urban,Software Engineer,127334,1 +22085,Male,57,Masters,15,26,41,38,2,4.0,6,15,Semi-Urban,HR Executive,106715,0 +22086,Female,31,High School,4,65,75,58,80,2.0,2,25,Urban,Data Analyst,120034,0 +22087,Male,27,Diploma,19,16,98,89,97,2.0,5,38,Urban,HR Executive,74970,1 +22088,Female,23,High School,2,52,43,81,5,6.0,4,58,Rural,ML Engineer,81877,0 +22089,Male,57,Bachelors,19,10,0,18,40,0.0,4,28,Rural,Data Analyst,27015,0 +22090,Male,45,High School,4,64,92,15,97,0.0,4,84,Semi-Urban,Software Engineer,57555,1 +22091,Male,57,Masters,5,6,34,95,99,5.0,1,40,Urban,Software Engineer,62335,0 +22092,Female,40,Bachelors,13,18,64,45,77,2.0,0,19,Urban,Manager,84783,0 +22093,Male,47,Bachelors,0,15,21,78,3,2.0,7,28,Urban,ML Engineer,48106,0 +22094,Male,28,PhD,5,62,70,51,16,9.0,0,65,Urban,Data Analyst,28585,1 +22095,Female,40,Bachelors,11,53,24,98,2,4.0,3,53,Semi-Urban,HR Executive,95302,0 +22096,Male,41,Bachelors,5,32,15,40,47,6.0,5,0,Rural,HR Executive,82044,0 +22097,Male,57,PhD,0,12,6,37,39,8.0,4,36,Rural,Manager,133318,0 +22098,Female,55,Diploma,8,74,12,20,37,2.0,0,40,Semi-Urban,Software Engineer,72285,0 +22099,Female,29,Diploma,6,75,40,97,88,4.0,1,45,Semi-Urban,Data Analyst,44909,1 +22100,Male,43,Bachelors,9,92,78,55,3,3.0,4,7,Urban,Manager,38328,0 +22101,Male,51,PhD,2,8,90,89,9,2.0,6,83,Semi-Urban,ML Engineer,106221,1 +22102,Female,50,Masters,17,55,24,56,65,8.0,1,40,Rural,Data Analyst,145453,0 +22103,Male,45,Bachelors,0,13,25,71,95,2.0,0,38,Urban,Data Analyst,81504,0 +22104,Female,50,Masters,14,1,73,47,59,2.0,7,19,Urban,ML Engineer,111323,0 +22105,Male,25,Masters,10,44,12,72,31,9.0,6,62,Urban,HR Executive,129495,0 +22106,Male,46,Diploma,13,48,82,12,69,2.0,6,95,Rural,ML Engineer,119907,1 +22107,Male,25,Masters,19,32,25,61,83,6.0,2,1,Urban,Data Analyst,114055,0 +22108,Male,37,Diploma,6,88,80,32,55,9.0,4,32,Semi-Urban,Manager,139132,0 +22109,Female,34,Masters,5,72,60,30,89,2.0,5,59,Urban,ML Engineer,92046,0 +22110,Male,44,Bachelors,1,93,44,37,6,2.0,2,21,Urban,Software Engineer,131728,0 +22111,Male,42,High School,4,52,37,17,82,7.0,5,31,Rural,Data Analyst,142839,0 +22112,Female,21,High School,13,9,24,42,51,9.0,7,63,Rural,Software Engineer,133195,0 +22113,Male,49,Bachelors,3,93,95,24,21,0.0,7,55,Urban,HR Executive,68565,1 +22114,Female,35,High School,6,99,98,61,86,4.0,5,82,Urban,ML Engineer,24599,1 +22115,Female,51,Bachelors,0,59,89,24,13,0.0,7,30,Urban,HR Executive,90890,0 +22116,Other,57,Diploma,6,54,21,86,21,3.0,5,17,Urban,Software Engineer,57149,0 +22117,Female,57,Masters,3,80,69,11,37,9.0,0,67,Semi-Urban,HR Executive,97669,0 +22118,Male,43,Diploma,0,94,39,80,31,8.0,3,96,Urban,Software Engineer,57306,1 +22119,Other,50,High School,18,48,6,56,92,0.0,4,45,Semi-Urban,ML Engineer,67954,0 +22120,Female,45,Masters,15,4,9,31,10,7.0,0,73,Urban,HR Executive,112501,0 +22121,Female,23,High School,1,68,62,98,70,5.0,0,22,Urban,Data Analyst,78576,1 +22122,Male,46,Bachelors,16,76,94,86,48,4.0,0,98,Urban,HR Executive,112877,1 +22123,Other,34,High School,8,91,75,36,56,0.0,3,23,Urban,ML Engineer,137083,0 +22124,Female,45,Bachelors,10,26,1,55,75,3.0,0,30,Urban,ML Engineer,121210,0 +22125,Female,59,Bachelors,10,89,81,39,6,2.0,0,27,Rural,ML Engineer,38974,0 +22126,Male,37,Diploma,3,63,2,41,18,3.0,6,35,Urban,Manager,100552,0 +22127,Male,44,Bachelors,1,50,18,0,73,5.0,6,26,Semi-Urban,Software Engineer,111110,0 +22128,Other,34,Bachelors,0,56,70,97,45,6.0,5,92,Urban,Data Analyst,31318,1 +22129,Male,47,Bachelors,5,58,89,10,24,7.0,4,60,Urban,ML Engineer,74928,0 +22130,Male,37,Bachelors,19,97,89,54,36,9.0,1,70,Urban,Software Engineer,80034,1 +22131,Female,31,Masters,14,62,26,54,16,7.0,2,91,Urban,Manager,82264,0 +22132,Male,34,Bachelors,9,62,84,34,3,9.0,1,80,Urban,HR Executive,141641,1 +22133,Male,32,Bachelors,19,83,21,70,97,4.0,2,76,Urban,Software Engineer,65721,1 +22134,Male,27,Diploma,18,96,17,36,39,4.0,7,62,Urban,Data Analyst,26421,0 +22135,Male,57,PhD,19,85,6,86,27,6.0,5,45,Urban,ML Engineer,26500,0 +22136,Male,53,Bachelors,3,11,50,3,35,2.0,1,13,Urban,HR Executive,34921,0 +22137,Male,37,Masters,4,48,88,35,88,9.0,3,84,Urban,HR Executive,141926,1 +22138,Male,38,Bachelors,15,79,29,83,9,8.0,4,95,Rural,ML Engineer,120941,1 +22139,Female,57,Masters,1,37,12,83,45,3.0,5,94,Urban,ML Engineer,75882,0 +22140,Female,24,Bachelors,1,66,79,25,4,4.0,5,41,Rural,Data Analyst,33333,0 +22141,Male,55,High School,15,39,77,63,71,1.0,5,66,Semi-Urban,HR Executive,128619,1 +22142,Male,37,Diploma,15,70,37,76,31,7.0,5,81,Urban,Manager,129443,1 +22143,Male,36,Bachelors,7,45,18,86,63,8.0,0,14,Urban,HR Executive,136368,0 +22144,Female,23,Bachelors,11,70,49,62,84,8.0,7,64,Urban,ML Engineer,92306,1 +22145,Other,39,Masters,5,34,5,10,48,9.0,7,50,Semi-Urban,HR Executive,138151,0 +22146,Male,39,Bachelors,16,86,58,13,60,7.0,1,37,Urban,Manager,59614,0 +22147,Male,26,Bachelors,2,50,85,37,61,7.0,6,9,Semi-Urban,ML Engineer,108629,0 +22148,Female,39,High School,14,22,26,63,70,7.0,4,14,Urban,HR Executive,28736,0 +22149,Female,34,Bachelors,19,13,32,77,11,1.0,3,86,Urban,HR Executive,123205,0 +22150,Male,43,Bachelors,14,3,17,16,57,4.0,2,79,Urban,Manager,134879,0 +22151,Female,33,High School,12,76,10,15,50,1.0,0,61,Urban,HR Executive,74869,0 +22152,Female,49,Bachelors,19,68,61,27,11,5.0,1,58,Urban,ML Engineer,38983,0 +22153,Other,31,High School,4,73,62,63,73,7.0,4,62,Urban,Software Engineer,136827,1 +22154,Male,29,Bachelors,17,54,31,51,83,9.0,3,41,Urban,Software Engineer,96438,0 +22155,Other,23,Diploma,13,31,75,74,66,0.0,3,47,Urban,ML Engineer,101225,0 +22156,Male,48,Masters,18,27,27,55,53,3.0,1,43,Rural,ML Engineer,93984,0 +22157,Female,30,Bachelors,15,88,31,64,50,5.0,4,8,Semi-Urban,Manager,45319,0 +22158,Male,49,Bachelors,12,91,70,7,30,7.0,6,57,Urban,ML Engineer,81240,0 +22159,Male,39,Bachelors,10,62,6,81,35,6.0,2,43,Urban,Software Engineer,73404,0 +22160,Female,24,High School,12,67,51,6,60,7.0,5,5,Urban,HR Executive,47719,0 +22161,Male,36,High School,1,55,68,25,3,3.0,6,27,Semi-Urban,Manager,70421,0 +22162,Male,45,High School,7,82,75,54,26,9.0,3,65,Urban,Data Analyst,149872,1 +22163,Male,55,High School,17,35,23,74,11,2.0,4,56,Urban,Data Analyst,149696,0 +22164,Male,58,Bachelors,18,36,52,29,50,7.0,5,87,Rural,Software Engineer,82080,0 +22165,Male,34,High School,7,80,99,39,63,9.0,6,85,Rural,Manager,26823,1 +22166,Female,26,Masters,4,2,90,87,27,5.0,7,47,Rural,HR Executive,131743,0 +22167,Male,33,Bachelors,9,0,29,69,96,0.0,3,37,Urban,Manager,35262,0 +22168,Male,41,Bachelors,19,64,63,97,34,6.0,5,27,Urban,Data Analyst,69384,1 +22169,Male,29,Bachelors,18,36,86,3,2,9.0,4,85,Semi-Urban,Manager,134812,0 +22170,Male,23,PhD,18,54,67,73,10,8.0,2,66,Semi-Urban,Manager,98399,1 +22171,Male,41,Bachelors,4,84,79,67,26,7.0,6,62,Urban,HR Executive,136191,1 +22172,Male,25,Bachelors,13,48,98,29,18,0.0,6,70,Rural,Software Engineer,82293,1 +22173,Male,24,Bachelors,18,54,57,0,37,8.0,0,63,Rural,Manager,111228,0 +22174,Male,25,Bachelors,9,78,8,34,84,1.0,6,73,Semi-Urban,ML Engineer,73087,0 +22175,Female,23,Bachelors,18,23,18,84,21,0.0,2,22,Semi-Urban,Data Analyst,77697,0 +22176,Female,40,Bachelors,11,51,61,93,77,5.0,4,78,Rural,Data Analyst,30417,1 +22177,Male,30,PhD,6,66,85,55,99,6.0,7,95,Urban,Manager,107633,1 +22178,Male,57,Bachelors,10,18,6,30,76,4.0,0,18,Urban,Data Analyst,68629,0 +22179,Female,24,Bachelors,12,78,83,81,23,2.0,5,84,Urban,ML Engineer,41112,1 +22180,Male,55,Masters,15,8,96,54,57,3.0,5,23,Urban,ML Engineer,92525,0 +22181,Female,38,Masters,10,91,48,83,11,5.0,4,56,Rural,Data Analyst,79141,1 +22182,Male,35,PhD,6,90,40,1,45,2.0,6,72,Urban,Software Engineer,31422,0 +22183,Male,22,High School,4,27,71,95,94,3.0,5,60,Rural,Data Analyst,67170,1 +22184,Female,56,Bachelors,7,69,86,34,21,6.0,1,6,Urban,HR Executive,63456,0 +22185,Female,43,Masters,17,21,77,13,90,8.0,4,95,Semi-Urban,Data Analyst,134151,0 +22186,Male,26,High School,13,60,38,25,39,6.0,0,87,Urban,HR Executive,78307,0 +22187,Male,29,Bachelors,12,94,96,85,35,3.0,0,67,Urban,Software Engineer,125309,1 +22188,Male,45,High School,12,8,51,9,49,0.0,7,54,Urban,HR Executive,51309,0 +22189,Female,56,Bachelors,5,10,64,64,55,3.0,6,13,Rural,Data Analyst,27507,0 +22190,Female,37,Bachelors,5,79,84,71,58,0.0,5,48,Urban,HR Executive,36168,1 +22191,Male,46,Bachelors,9,70,14,75,73,5.0,1,76,Urban,Data Analyst,137699,1 +22192,Male,30,Bachelors,3,82,55,0,36,6.0,6,42,Urban,ML Engineer,82923,0 +22193,Male,26,High School,13,70,4,8,63,4.0,7,83,Urban,Data Analyst,129403,0 +22194,Male,44,High School,13,77,56,0,88,0.0,5,27,Urban,HR Executive,49140,0 +22195,Male,56,Bachelors,16,43,97,82,57,0.0,0,14,Urban,HR Executive,99328,1 +22196,Female,36,High School,17,10,89,23,85,3.0,3,25,Urban,Data Analyst,124839,0 +22197,Male,32,Diploma,1,43,65,98,65,8.0,3,2,Urban,Data Analyst,93556,0 +22198,Male,29,PhD,12,77,36,16,56,9.0,6,83,Rural,HR Executive,52881,0 +22199,Female,22,Diploma,3,73,5,92,51,6.0,7,52,Semi-Urban,ML Engineer,43700,0 +22200,Male,42,Bachelors,19,91,69,28,92,9.0,3,98,Urban,ML Engineer,68461,1 +22201,Male,37,Bachelors,12,93,30,2,34,9.0,3,96,Urban,Data Analyst,124744,0 +22202,Male,27,High School,17,4,86,6,88,3.0,4,27,Urban,ML Engineer,53873,0 +22203,Male,40,Bachelors,11,63,37,70,27,1.0,5,83,Urban,ML Engineer,114386,1 +22204,Female,56,Masters,1,75,35,1,34,4.0,5,75,Rural,Software Engineer,145386,0 +22205,Female,37,Bachelors,1,26,70,57,90,1.0,1,89,Urban,ML Engineer,112515,1 +22206,Male,54,Bachelors,14,26,71,62,57,9.0,7,57,Urban,Data Analyst,31181,0 +22207,Male,30,Bachelors,16,86,57,51,1,3.0,2,21,Urban,HR Executive,60171,0 +22208,Male,30,Diploma,1,51,51,45,24,1.0,5,27,Urban,Manager,56191,0 +22209,Male,36,PhD,3,96,65,64,76,8.0,4,56,Urban,Data Analyst,56104,1 +22210,Male,59,Bachelors,13,24,77,42,73,3.0,6,85,Semi-Urban,HR Executive,129226,0 +22211,Male,37,Bachelors,0,87,11,41,55,6.0,5,65,Urban,Data Analyst,138864,0 +22212,Male,41,Bachelors,14,37,95,40,13,4.0,0,20,Semi-Urban,Manager,134695,0 +22213,Male,41,Masters,14,41,44,37,63,1.0,6,21,Semi-Urban,HR Executive,27041,0 +22214,Female,50,Masters,14,38,96,21,3,0.0,1,20,Urban,Manager,21271,0 +22215,Female,21,High School,16,89,77,52,63,2.0,0,61,Rural,Manager,85716,1 +22216,Female,31,Masters,19,52,21,31,52,6.0,0,16,Rural,ML Engineer,107162,0 +22217,Male,51,High School,8,13,49,73,94,9.0,2,38,Urban,Manager,46737,0 +22218,Female,47,Bachelors,14,69,14,45,86,3.0,6,30,Rural,Manager,129790,0 +22219,Female,38,PhD,0,58,34,40,21,1.0,3,18,Rural,HR Executive,91100,0 +22220,Female,21,Bachelors,9,27,79,71,98,4.0,7,87,Rural,Data Analyst,81138,1 +22221,Male,52,Bachelors,16,73,72,99,94,9.0,3,29,Urban,Software Engineer,20869,1 +22222,Female,27,High School,17,99,70,85,3,5.0,2,14,Rural,ML Engineer,89788,1 +22223,Male,29,Bachelors,4,43,48,91,91,6.0,2,42,Urban,Manager,114524,0 +22224,Female,46,High School,1,91,21,75,54,5.0,4,82,Semi-Urban,ML Engineer,118214,1 +22225,Male,53,Masters,11,21,30,75,26,3.0,3,38,Urban,ML Engineer,135903,0 +22226,Female,33,Diploma,9,34,64,30,39,3.0,7,67,Semi-Urban,HR Executive,67668,0 +22227,Female,27,Diploma,14,75,38,86,25,0.0,7,19,Rural,ML Engineer,142492,0 +22228,Male,56,Diploma,0,27,29,46,88,4.0,7,30,Semi-Urban,ML Engineer,129981,0 +22229,Male,44,Bachelors,6,68,46,18,23,1.0,4,67,Urban,Manager,131186,0 +22230,Male,34,High School,3,85,24,44,47,2.0,7,86,Rural,Manager,92819,1 +22231,Male,29,High School,4,77,0,24,27,4.0,7,29,Urban,Software Engineer,36486,0 +22232,Male,41,Diploma,9,46,48,66,39,6.0,3,16,Urban,Manager,73237,0 +22233,Male,25,High School,14,65,53,41,65,3.0,3,95,Semi-Urban,Data Analyst,137326,1 +22234,Female,27,High School,11,14,71,77,16,8.0,0,0,Rural,HR Executive,145220,0 +22235,Male,23,Bachelors,1,69,15,21,29,9.0,4,2,Urban,Data Analyst,34167,0 +22236,Female,44,PhD,4,90,34,75,45,7.0,6,62,Semi-Urban,Manager,40770,1 +22237,Female,45,Bachelors,0,89,31,14,46,0.0,7,3,Semi-Urban,Software Engineer,92789,0 +22238,Female,37,Diploma,15,8,3,12,40,1.0,2,65,Urban,HR Executive,123726,0 +22239,Female,31,Bachelors,19,23,83,32,57,5.0,7,85,Urban,Software Engineer,124481,0 +22240,Male,46,Diploma,2,83,78,94,31,6.0,1,44,Rural,HR Executive,136134,1 +22241,Female,22,Bachelors,19,4,56,57,91,8.0,3,28,Urban,Software Engineer,29352,0 +22242,Male,50,Bachelors,9,98,21,58,18,8.0,2,69,Urban,Manager,129280,1 +22243,Female,50,High School,15,71,9,35,10,6.0,1,78,Urban,ML Engineer,87306,0 +22244,Female,31,Masters,11,91,70,37,49,6.0,6,17,Semi-Urban,Software Engineer,94750,0 +22245,Female,23,Bachelors,15,86,90,33,70,6.0,0,7,Urban,Software Engineer,86639,0 +22246,Male,58,Masters,9,4,27,70,56,8.0,2,35,Urban,HR Executive,47862,0 +22247,Male,49,Diploma,2,90,20,73,68,3.0,0,5,Urban,ML Engineer,63624,0 +22248,Female,24,Bachelors,8,51,92,92,42,0.0,5,90,Urban,HR Executive,35253,1 +22249,Female,52,Diploma,6,34,3,62,72,3.0,0,70,Semi-Urban,Software Engineer,89154,0 +22250,Male,36,High School,5,68,32,24,3,5.0,5,48,Rural,HR Executive,41813,0 +22251,Female,42,Diploma,3,4,55,33,92,6.0,7,20,Semi-Urban,Software Engineer,115024,0 +22252,Male,38,Bachelors,1,41,37,19,18,7.0,1,22,Urban,Manager,120607,0 +22253,Female,31,High School,6,84,69,34,46,0.0,7,80,Semi-Urban,ML Engineer,122660,1 +22254,Female,55,Bachelors,0,30,98,65,86,7.0,3,63,Rural,Data Analyst,33224,1 +22255,Male,40,Bachelors,13,90,93,87,41,6.0,7,43,Urban,ML Engineer,34236,1 +22256,Male,28,Diploma,8,79,28,72,54,8.0,5,21,Rural,HR Executive,130317,0 +22257,Female,35,Bachelors,19,76,37,25,75,4.0,4,0,Urban,Manager,108042,0 +22258,Male,38,High School,8,73,72,37,37,6.0,1,34,Urban,Manager,94982,0 +22259,Male,29,Bachelors,16,71,35,57,87,3.0,1,99,Semi-Urban,Data Analyst,80731,1 +22260,Female,26,Diploma,10,53,53,54,12,4.0,5,74,Semi-Urban,Data Analyst,66311,0 +22261,Female,35,Masters,11,54,45,68,70,8.0,7,35,Semi-Urban,ML Engineer,121752,0 +22262,Male,41,PhD,12,90,61,9,69,7.0,6,66,Semi-Urban,Data Analyst,130344,0 +22263,Male,33,Bachelors,7,93,29,70,68,6.0,0,93,Urban,Manager,82893,1 +22264,Male,26,High School,5,41,62,87,0,6.0,1,95,Urban,Data Analyst,70776,1 +22265,Female,23,High School,3,90,81,24,0,6.0,1,46,Rural,Manager,29015,1 +22266,Male,25,Diploma,7,3,75,12,17,7.0,3,92,Urban,ML Engineer,113842,0 +22267,Female,51,Bachelors,16,17,92,40,59,9.0,2,63,Urban,ML Engineer,56494,0 +22268,Female,58,Masters,17,25,77,48,3,1.0,7,95,Rural,Software Engineer,98128,1 +22269,Male,38,Bachelors,1,10,45,52,30,8.0,4,92,Urban,Data Analyst,69512,0 +22270,Male,50,Masters,2,99,8,32,39,6.0,6,48,Urban,Manager,137747,0 +22271,Female,50,Bachelors,9,33,5,38,7,6.0,7,54,Urban,Software Engineer,93574,0 +22272,Male,28,Masters,2,90,47,0,29,5.0,7,33,Urban,ML Engineer,60828,0 +22273,Female,36,High School,10,56,82,60,37,7.0,7,64,Urban,HR Executive,83879,1 +22274,Female,32,High School,16,3,10,37,48,4.0,0,78,Urban,Data Analyst,143803,0 +22275,Female,44,Bachelors,0,2,32,27,85,1.0,0,65,Urban,Software Engineer,106214,0 +22276,Male,37,Diploma,0,19,70,69,79,3.0,5,14,Urban,ML Engineer,101594,0 +22277,Male,29,Bachelors,2,70,23,57,42,6.0,2,49,Semi-Urban,ML Engineer,112399,0 +22278,Other,55,Diploma,16,2,42,48,70,2.0,5,62,Semi-Urban,HR Executive,30082,0 +22279,Female,48,Masters,19,2,95,74,29,7.0,6,80,Semi-Urban,ML Engineer,24651,1 +22280,Male,39,Diploma,8,83,14,53,13,9.0,2,9,Semi-Urban,Manager,92977,0 +22281,Male,43,Diploma,2,92,68,54,3,2.0,1,56,Urban,Software Engineer,46792,1 +22282,Male,36,Bachelors,16,81,79,15,76,3.0,3,24,Urban,ML Engineer,37888,0 +22283,Female,48,Bachelors,1,49,40,23,87,6.0,3,99,Semi-Urban,HR Executive,95434,0 +22284,Male,32,Diploma,6,9,18,25,9,0.0,6,80,Rural,ML Engineer,102860,0 +22285,Female,41,Bachelors,7,81,66,22,8,9.0,2,67,Semi-Urban,Manager,55083,0 +22286,Female,51,Masters,0,70,80,11,94,1.0,4,28,Urban,Software Engineer,102221,0 +22287,Female,51,Masters,14,21,13,4,90,0.0,0,8,Rural,ML Engineer,122884,0 +22288,Female,46,Diploma,1,38,25,87,20,5.0,4,19,Semi-Urban,Software Engineer,88937,0 +22289,Female,33,Bachelors,2,46,72,1,83,5.0,3,28,Urban,Data Analyst,87934,0 +22290,Male,39,Diploma,14,26,84,12,79,8.0,4,40,Rural,Manager,54279,0 +22291,Male,38,Diploma,5,52,94,92,61,4.0,0,24,Urban,HR Executive,148806,1 +22292,Female,56,High School,11,51,40,93,5,7.0,3,37,Urban,ML Engineer,114293,0 +22293,Male,56,High School,3,8,0,44,65,4.0,4,99,Urban,Software Engineer,88122,0 +22294,Male,47,PhD,18,12,1,58,6,5.0,4,26,Rural,Manager,104584,0 +22295,Male,24,Bachelors,6,92,32,12,65,4.0,7,90,Urban,Software Engineer,46389,0 +22296,Male,50,Bachelors,6,19,6,28,87,8.0,7,4,Rural,Software Engineer,75985,0 +22297,Female,43,High School,0,26,14,0,63,3.0,6,90,Rural,Data Analyst,117825,0 +22298,Female,24,Masters,7,9,21,9,14,9.0,5,55,Semi-Urban,ML Engineer,110374,0 +22299,Male,39,Bachelors,13,35,0,36,8,2.0,0,14,Urban,Data Analyst,141846,0 +22300,Female,30,Bachelors,4,77,47,13,47,0.0,4,40,Rural,Manager,57306,0 +22301,Male,39,Bachelors,4,70,6,29,2,7.0,5,50,Semi-Urban,ML Engineer,77446,0 +22302,Female,54,Diploma,10,42,60,64,61,9.0,3,78,Rural,Data Analyst,80239,1 +22303,Male,49,Diploma,16,97,71,90,1,4.0,6,82,Urban,HR Executive,48351,1 +22304,Female,57,PhD,6,16,28,79,76,1.0,3,94,Urban,Software Engineer,137789,0 +22305,Male,22,Diploma,11,58,95,66,93,6.0,1,42,Urban,Software Engineer,32574,1 +22306,Male,47,Bachelors,0,40,90,27,19,0.0,2,87,Urban,Data Analyst,54072,1 +22307,Female,29,Masters,17,16,85,21,65,3.0,6,26,Urban,Manager,40744,0 +22308,Male,25,Masters,5,16,67,46,78,7.0,7,95,Rural,Manager,104291,0 +22309,Other,49,Bachelors,15,95,23,95,51,2.0,7,91,Urban,ML Engineer,55253,1 +22310,Female,49,Bachelors,7,66,40,37,29,9.0,0,41,Urban,Manager,72067,0 +22311,Male,40,Masters,13,97,8,59,63,7.0,5,88,Urban,Software Engineer,73752,1 +22312,Female,33,Bachelors,1,50,72,81,28,3.0,6,58,Rural,ML Engineer,28962,1 +22313,Male,52,Masters,9,33,5,74,79,9.0,4,80,Urban,Software Engineer,29745,0 +22314,Male,48,Masters,3,49,94,1,5,9.0,5,99,Urban,Data Analyst,122865,1 +22315,Other,58,Diploma,7,97,51,51,90,3.0,1,83,Urban,HR Executive,111945,1 +22316,Male,45,Diploma,18,53,21,48,72,3.0,7,31,Rural,Data Analyst,21956,0 +22317,Female,31,Masters,3,4,48,18,48,0.0,5,73,Semi-Urban,Software Engineer,136230,0 +22318,Male,39,Bachelors,3,75,98,43,38,5.0,3,72,Urban,HR Executive,138004,1 +22319,Female,43,High School,8,14,43,5,35,8.0,4,14,Urban,HR Executive,101158,0 +22320,Male,37,Bachelors,16,36,11,62,8,1.0,2,9,Urban,Software Engineer,36886,0 +22321,Male,25,Bachelors,15,88,61,92,75,6.0,5,28,Semi-Urban,Software Engineer,55172,1 +22322,Other,50,Bachelors,16,95,65,19,49,8.0,5,52,Rural,Software Engineer,73622,0 +22323,Male,57,Bachelors,14,74,88,56,73,6.0,2,69,Urban,Software Engineer,94645,1 +22324,Female,58,Bachelors,1,41,61,64,49,4.0,4,75,Semi-Urban,Data Analyst,98116,1 +22325,Male,48,Bachelors,6,82,70,11,33,2.0,4,9,Rural,Software Engineer,39418,0 +22326,Male,57,Bachelors,6,43,59,19,92,1.0,4,43,Urban,Manager,63390,0 +22327,Female,48,Bachelors,1,50,77,32,16,5.0,2,90,Semi-Urban,HR Executive,149158,1 +22328,Male,45,PhD,1,85,86,67,31,8.0,7,54,Semi-Urban,HR Executive,42281,1 +22329,Male,30,Diploma,9,73,75,15,84,1.0,0,58,Urban,HR Executive,40483,0 +22330,Female,39,Bachelors,7,76,17,83,3,3.0,0,92,Semi-Urban,Software Engineer,35958,1 +22331,Female,22,Bachelors,2,10,55,77,17,9.0,7,63,Urban,Manager,25332,0 +22332,Male,24,Masters,1,63,29,54,62,9.0,1,31,Semi-Urban,Manager,85293,0 +22333,Male,39,High School,5,9,68,21,76,9.0,0,28,Urban,Software Engineer,30228,0 +22334,Female,38,Bachelors,10,58,56,21,36,8.0,3,76,Semi-Urban,Data Analyst,45774,0 +22335,Other,32,Masters,9,4,96,72,20,2.0,0,65,Semi-Urban,Software Engineer,135448,0 +22336,Other,41,Diploma,3,29,82,9,47,6.0,4,3,Semi-Urban,Software Engineer,148223,0 +22337,Female,33,Bachelors,13,1,77,33,94,4.0,1,96,Urban,Software Engineer,70021,0 +22338,Male,50,Masters,6,27,59,88,37,8.0,7,93,Urban,Data Analyst,24197,1 +22339,Female,28,Diploma,2,88,43,83,70,3.0,3,1,Urban,Data Analyst,85776,0 +22340,Female,59,PhD,18,63,96,74,35,1.0,6,90,Semi-Urban,HR Executive,81006,1 +22341,Male,37,Bachelors,13,88,67,45,82,4.0,7,28,Semi-Urban,HR Executive,43317,0 +22342,Male,38,Diploma,15,24,9,93,75,0.0,0,29,Urban,Data Analyst,141892,0 +22343,Male,35,Masters,13,95,68,32,28,4.0,0,26,Rural,ML Engineer,112950,0 +22344,Female,40,Masters,18,48,92,7,7,1.0,1,90,Semi-Urban,Manager,116709,0 +22345,Male,52,Diploma,10,27,11,47,13,5.0,4,70,Rural,ML Engineer,125551,0 +22346,Male,51,High School,16,39,86,65,14,2.0,6,24,Semi-Urban,Manager,117155,0 +22347,Male,46,Diploma,4,93,17,26,63,8.0,4,98,Semi-Urban,Manager,21317,0 +22348,Male,32,Masters,16,41,88,61,45,6.0,1,80,Urban,ML Engineer,138924,1 +22349,Male,48,Bachelors,4,90,37,69,32,0.0,0,78,Semi-Urban,Software Engineer,98602,1 +22350,Female,43,Diploma,5,15,40,26,16,2.0,3,71,Urban,ML Engineer,117285,0 +22351,Male,24,Bachelors,8,29,92,40,13,7.0,2,0,Rural,Manager,114210,0 +22352,Female,24,High School,0,4,81,83,86,5.0,2,91,Rural,ML Engineer,31185,1 +22353,Female,50,High School,19,31,90,25,48,9.0,0,61,Urban,HR Executive,47657,0 +22354,Female,29,Masters,18,10,15,22,60,9.0,7,75,Rural,HR Executive,113211,0 +22355,Female,46,Masters,11,23,33,68,46,3.0,5,90,Rural,ML Engineer,54725,0 +22356,Male,53,Diploma,7,62,24,82,57,1.0,6,53,Urban,HR Executive,51640,0 +22357,Male,23,Bachelors,0,34,61,65,2,7.0,3,42,Rural,Data Analyst,77816,0 +22358,Male,56,Diploma,0,36,7,75,98,3.0,6,78,Urban,HR Executive,133895,0 +22359,Other,34,Bachelors,12,51,47,54,28,0.0,2,16,Urban,Software Engineer,30038,0 +22360,Male,22,Bachelors,8,41,8,68,84,0.0,2,85,Urban,Data Analyst,60773,0 +22361,Male,24,Diploma,18,33,19,36,7,9.0,4,76,Urban,Manager,91513,0 +22362,Female,57,Masters,9,74,66,7,29,8.0,5,84,Urban,Manager,122353,0 +22363,Female,43,Bachelors,18,95,28,49,61,7.0,0,15,Urban,Data Analyst,32728,0 +22364,Female,31,Bachelors,7,74,78,24,25,4.0,5,16,Semi-Urban,Manager,118956,0 +22365,Female,55,Masters,19,46,55,32,47,7.0,0,18,Urban,ML Engineer,110211,0 +22366,Male,54,Diploma,12,89,93,17,8,5.0,3,56,Urban,HR Executive,95233,1 +22367,Female,41,PhD,18,20,24,70,1,0.0,1,23,Semi-Urban,HR Executive,35491,0 +22368,Male,55,Diploma,12,63,55,19,52,1.0,2,63,Urban,Manager,137790,0 +22369,Female,29,Diploma,0,75,8,57,28,2.0,0,97,Rural,Data Analyst,36093,0 +22370,Male,34,Masters,5,97,62,65,67,6.0,2,63,Semi-Urban,Manager,109133,1 +22371,Male,50,Masters,16,60,15,45,41,9.0,3,90,Semi-Urban,HR Executive,133997,0 +22372,Female,22,Bachelors,5,52,30,15,54,3.0,7,36,Urban,Manager,23314,0 +22373,Male,37,Diploma,11,7,4,85,70,2.0,2,68,Semi-Urban,Manager,109381,0 +22374,Female,35,PhD,19,52,69,53,23,9.0,0,49,Semi-Urban,Manager,52316,0 +22375,Female,31,PhD,7,88,71,22,48,2.0,1,2,Urban,ML Engineer,100288,0 +22376,Female,49,High School,14,75,40,33,63,2.0,5,89,Urban,Software Engineer,44456,0 +22377,Male,31,Bachelors,1,92,64,42,53,5.0,2,19,Rural,HR Executive,147242,0 +22378,Male,40,Masters,17,78,52,30,73,3.0,3,23,Urban,Software Engineer,137737,0 +22379,Female,23,High School,17,65,90,10,90,5.0,3,41,Urban,Software Engineer,147917,0 +22380,Female,27,Bachelors,15,42,25,47,2,4.0,6,55,Urban,Software Engineer,56916,0 +22381,Male,21,Diploma,9,54,11,95,47,3.0,2,77,Urban,Manager,121404,1 +22382,Male,33,High School,3,83,24,86,75,9.0,7,44,Urban,Data Analyst,133161,1 +22383,Male,39,PhD,4,69,19,99,22,9.0,4,53,Semi-Urban,Software Engineer,56210,1 +22384,Other,50,PhD,1,11,12,70,10,1.0,6,40,Rural,ML Engineer,85818,0 +22385,Male,36,Diploma,18,11,76,10,88,3.0,1,64,Urban,HR Executive,75345,0 +22386,Male,38,Bachelors,19,1,20,16,5,0.0,7,9,Urban,ML Engineer,43402,0 +22387,Female,51,PhD,10,94,36,40,83,8.0,3,63,Rural,HR Executive,26381,0 +22388,Male,55,Bachelors,14,26,31,86,65,4.0,0,99,Urban,Data Analyst,59158,1 +22389,Female,48,Diploma,3,51,94,43,76,1.0,0,85,Urban,ML Engineer,130024,1 +22390,Male,45,Bachelors,16,48,43,7,11,7.0,1,36,Urban,ML Engineer,144143,0 +22391,Male,32,Diploma,2,25,34,32,39,7.0,7,45,Semi-Urban,HR Executive,43813,0 +22392,Male,44,Masters,11,24,63,75,30,3.0,0,61,Rural,HR Executive,131256,0 +22393,Male,52,Masters,16,47,36,66,45,4.0,6,3,Rural,Data Analyst,71601,0 +22394,Male,43,Bachelors,17,26,31,77,30,9.0,7,30,Rural,Data Analyst,84637,0 +22395,Male,46,Diploma,12,4,49,31,85,0.0,6,23,Rural,HR Executive,96003,0 +22396,Male,25,Masters,4,79,68,89,95,3.0,6,25,Semi-Urban,Data Analyst,28934,1 +22397,Female,33,Masters,9,39,72,76,10,8.0,3,49,Urban,ML Engineer,111059,0 +22398,Male,22,Bachelors,12,67,88,90,18,5.0,5,85,Rural,ML Engineer,21927,1 +22399,Other,47,Diploma,16,9,87,19,36,3.0,5,77,Semi-Urban,Software Engineer,135500,0 +22400,Female,44,Bachelors,11,80,77,37,41,2.0,1,56,Rural,Data Analyst,71742,1 +22401,Male,24,Bachelors,12,48,17,38,30,3.0,7,10,Rural,ML Engineer,90813,0 +22402,Male,40,High School,1,15,1,91,42,6.0,6,3,Rural,ML Engineer,94759,0 +22403,Male,29,PhD,2,95,44,28,10,6.0,3,43,Rural,Data Analyst,105175,0 +22404,Male,59,Masters,13,57,25,50,97,8.0,3,18,Urban,Data Analyst,123402,0 +22405,Male,45,Bachelors,4,67,99,77,37,1.0,4,48,Rural,Data Analyst,68305,1 +22406,Male,57,PhD,3,26,19,0,23,1.0,5,31,Urban,ML Engineer,114353,0 +22407,Female,23,Diploma,18,27,19,22,47,3.0,7,21,Urban,Data Analyst,122372,0 +22408,Male,41,Bachelors,18,19,60,43,31,3.0,2,28,Urban,Manager,74797,0 +22409,Male,29,Masters,2,88,29,78,84,2.0,5,45,Urban,Manager,121551,1 +22410,Male,43,Masters,17,40,52,29,50,0.0,7,5,Semi-Urban,ML Engineer,84658,0 +22411,Female,42,PhD,9,96,17,23,95,8.0,3,12,Urban,Data Analyst,68462,0 +22412,Male,37,Bachelors,11,35,67,76,79,1.0,5,57,Rural,ML Engineer,148454,1 +22413,Female,33,Bachelors,5,1,6,90,13,6.0,6,33,Urban,Software Engineer,66065,0 +22414,Male,29,Bachelors,11,20,32,99,64,4.0,3,25,Rural,Data Analyst,129544,0 +22415,Other,40,PhD,8,74,19,69,17,6.0,5,78,Urban,ML Engineer,147096,0 +22416,Male,43,Bachelors,19,33,70,54,97,2.0,0,90,Urban,HR Executive,104880,1 +22417,Other,39,High School,6,28,33,36,9,7.0,6,73,Urban,ML Engineer,76438,0 +22418,Female,38,Bachelors,17,38,86,84,62,9.0,2,49,Urban,HR Executive,98221,1 +22419,Male,37,Bachelors,8,67,42,0,89,7.0,2,69,Urban,Software Engineer,41690,0 +22420,Male,36,Bachelors,2,92,22,98,67,0.0,1,58,Urban,Data Analyst,138383,1 +22421,Male,33,Masters,13,34,87,38,54,7.0,3,46,Urban,Software Engineer,109296,0 +22422,Female,41,Bachelors,10,73,88,64,44,4.0,1,26,Urban,ML Engineer,143630,1 +22423,Female,56,Masters,4,67,15,87,93,8.0,2,77,Urban,Manager,114966,1 +22424,Male,56,Diploma,11,26,81,50,52,5.0,2,63,Urban,Software Engineer,73123,0 +22425,Male,36,Bachelors,12,18,99,73,32,2.0,7,90,Rural,Manager,29032,1 +22426,Male,24,Bachelors,17,86,89,79,13,4.0,6,69,Rural,Data Analyst,88797,1 +22427,Female,25,Bachelors,2,66,62,51,1,4.0,3,71,Urban,ML Engineer,33967,1 +22428,Female,39,Bachelors,8,69,11,85,81,5.0,1,47,Semi-Urban,Manager,74075,0 +22429,Male,49,High School,16,87,41,76,1,7.0,0,85,Semi-Urban,Manager,135156,1 +22430,Male,54,PhD,13,77,44,2,14,4.0,2,8,Urban,HR Executive,119420,0 +22431,Male,25,High School,16,5,9,48,30,9.0,7,13,Urban,Manager,68931,0 +22432,Male,34,Diploma,0,50,85,88,69,9.0,7,32,Urban,Software Engineer,34619,1 +22433,Male,35,Bachelors,19,60,70,6,28,5.0,6,68,Urban,Software Engineer,88719,0 +22434,Male,30,Diploma,15,31,32,84,10,1.0,1,77,Semi-Urban,ML Engineer,132391,0 +22435,Male,51,Bachelors,2,62,82,23,85,3.0,3,82,Urban,Data Analyst,58850,1 +22436,Female,47,Masters,15,31,49,54,52,6.0,5,56,Urban,Software Engineer,138561,0 +22437,Female,44,Bachelors,12,35,20,6,32,8.0,4,92,Urban,ML Engineer,95982,0 +22438,Other,41,Bachelors,6,44,72,63,87,1.0,1,66,Urban,ML Engineer,50966,1 +22439,Male,37,Masters,18,24,21,77,8,8.0,6,75,Urban,Manager,90526,0 +22440,Female,59,Masters,18,55,41,29,26,6.0,2,72,Urban,ML Engineer,100962,0 +22441,Female,48,Masters,4,1,49,92,47,2.0,6,42,Semi-Urban,Manager,143229,0 +22442,Male,40,Bachelors,11,96,26,66,83,0.0,6,82,Urban,ML Engineer,53911,1 +22443,Male,53,Masters,12,99,71,65,76,8.0,3,68,Semi-Urban,Data Analyst,40890,1 +22444,Female,33,Bachelors,13,51,18,44,4,4.0,3,16,Urban,Data Analyst,23415,0 +22445,Female,58,Bachelors,16,5,76,13,0,9.0,6,56,Urban,Software Engineer,69200,0 +22446,Male,26,Bachelors,4,72,11,33,60,3.0,5,10,Rural,ML Engineer,80238,0 +22447,Male,48,Diploma,4,93,9,79,41,4.0,4,25,Urban,Software Engineer,85910,0 +22448,Female,28,Diploma,16,81,54,61,62,4.0,7,63,Urban,Manager,118179,1 +22449,Other,30,Diploma,6,74,10,92,63,0.0,1,38,Rural,Data Analyst,114703,0 +22450,Female,43,Masters,8,39,12,50,92,9.0,3,55,Urban,Software Engineer,106373,0 +22451,Male,52,Masters,15,18,93,19,58,9.0,2,41,Urban,Data Analyst,143992,0 +22452,Male,46,Bachelors,5,64,16,18,19,4.0,3,15,Rural,ML Engineer,41871,0 +22453,Male,21,Diploma,9,5,26,71,45,7.0,1,72,Semi-Urban,HR Executive,146247,0 +22454,Female,54,High School,2,24,38,44,36,3.0,5,51,Urban,Software Engineer,130169,0 +22455,Female,24,Masters,5,48,56,23,59,2.0,2,96,Semi-Urban,ML Engineer,24405,0 +22456,Male,50,High School,18,83,51,0,39,9.0,4,82,Urban,HR Executive,92433,0 +22457,Male,23,Bachelors,7,73,39,28,84,5.0,1,68,Rural,Manager,143647,0 +22458,Female,52,Bachelors,15,86,8,70,44,9.0,4,52,Semi-Urban,Software Engineer,110586,0 +22459,Female,46,Diploma,12,84,95,40,56,9.0,7,30,Urban,Manager,104516,1 +22460,Other,34,Bachelors,10,88,82,1,64,8.0,0,79,Urban,ML Engineer,133634,1 +22461,Male,22,Bachelors,7,67,79,41,67,3.0,4,92,Rural,Manager,33416,1 +22462,Female,24,High School,0,92,65,78,10,3.0,1,51,Urban,Software Engineer,60669,1 +22463,Female,29,Bachelors,6,82,14,3,22,5.0,1,59,Rural,ML Engineer,29427,0 +22464,Male,30,Bachelors,14,71,53,39,64,6.0,5,26,Urban,ML Engineer,107898,0 +22465,Other,56,Diploma,14,75,98,4,3,5.0,4,79,Rural,ML Engineer,74434,1 +22466,Male,28,High School,18,27,1,33,95,0.0,5,13,Urban,Manager,92012,0 +22467,Female,37,Diploma,10,31,59,86,43,4.0,1,25,Rural,Software Engineer,43903,0 +22468,Other,39,Bachelors,4,29,54,84,20,9.0,2,9,Urban,Data Analyst,68573,0 +22469,Male,42,Masters,0,98,67,83,7,7.0,4,59,Urban,Manager,137507,1 +22470,Female,55,Masters,4,95,83,93,55,7.0,1,60,Urban,ML Engineer,119276,1 +22471,Male,45,High School,14,93,87,58,74,8.0,5,94,Rural,HR Executive,64074,1 +22472,Female,40,Diploma,5,69,76,48,50,2.0,1,41,Urban,HR Executive,40281,0 +22473,Female,45,Diploma,14,0,40,77,81,2.0,4,79,Semi-Urban,Software Engineer,42796,0 +22474,Female,35,Bachelors,6,93,40,8,59,6.0,5,41,Semi-Urban,HR Executive,96987,0 +22475,Female,24,Bachelors,9,67,25,67,65,1.0,0,70,Urban,ML Engineer,121061,0 +22476,Male,47,High School,16,53,99,43,47,7.0,7,51,Urban,ML Engineer,96252,1 +22477,Male,25,Bachelors,2,61,37,64,58,3.0,6,38,Rural,Manager,57209,0 +22478,Male,40,PhD,12,88,44,64,44,4.0,0,86,Semi-Urban,HR Executive,78624,1 +22479,Female,45,Bachelors,6,26,94,3,98,5.0,1,44,Semi-Urban,HR Executive,88462,0 +22480,Male,31,Diploma,12,89,96,45,50,5.0,5,3,Rural,HR Executive,23170,0 +22481,Female,41,High School,6,0,90,41,45,0.0,4,33,Semi-Urban,Software Engineer,95644,0 +22482,Male,36,Masters,1,31,90,13,19,8.0,2,80,Urban,Manager,107887,0 +22483,Female,59,Bachelors,1,35,43,86,49,5.0,1,73,Urban,Software Engineer,123263,0 +22484,Male,24,Diploma,12,64,4,27,89,2.0,3,52,Rural,Manager,83729,0 +22485,Female,43,Bachelors,3,16,80,63,2,7.0,1,10,Urban,HR Executive,44373,0 +22486,Female,51,Bachelors,2,6,96,92,98,2.0,5,20,Urban,ML Engineer,64830,0 +22487,Female,47,High School,9,51,35,90,74,7.0,3,25,Urban,Manager,60650,0 +22488,Female,58,Bachelors,7,19,83,58,44,2.0,2,68,Rural,HR Executive,72291,0 +22489,Female,29,Masters,2,32,42,37,79,4.0,2,74,Urban,Data Analyst,91886,0 +22490,Female,27,High School,3,47,89,31,5,3.0,5,41,Semi-Urban,Data Analyst,135883,0 +22491,Female,40,Diploma,2,35,76,10,35,6.0,4,83,Semi-Urban,Data Analyst,39123,0 +22492,Male,49,Diploma,16,15,59,69,44,9.0,7,90,Semi-Urban,Manager,94020,0 +22493,Female,40,High School,4,16,50,55,4,4.0,4,72,Semi-Urban,ML Engineer,80306,0 +22494,Female,47,High School,1,29,30,87,38,1.0,2,67,Semi-Urban,Data Analyst,118432,0 +22495,Male,54,Diploma,16,66,0,93,82,1.0,3,10,Semi-Urban,Data Analyst,89654,0 +22496,Female,35,Bachelors,5,26,60,86,85,1.0,1,35,Rural,Manager,68698,0 +22497,Female,36,Bachelors,16,98,80,44,27,0.0,7,95,Semi-Urban,Manager,108886,1 +22498,Other,56,Bachelors,6,31,91,5,46,5.0,4,31,Urban,HR Executive,118799,0 +22499,Other,55,Masters,6,52,88,51,77,6.0,2,46,Urban,Manager,80488,0 +22500,Male,52,Bachelors,3,63,0,56,58,8.0,1,73,Urban,Software Engineer,146165,0 +22501,Male,24,Masters,7,64,10,38,67,9.0,0,7,Urban,Software Engineer,47365,0 +22502,Male,35,Bachelors,5,32,3,41,15,1.0,3,50,Urban,ML Engineer,55496,0 +22503,Male,55,Masters,11,80,21,32,7,0.0,6,83,Semi-Urban,Manager,144185,0 +22504,Female,48,Bachelors,6,96,45,68,32,4.0,6,46,Urban,Software Engineer,30288,1 +22505,Male,53,Diploma,1,22,46,64,63,9.0,5,46,Urban,Data Analyst,145019,0 +22506,Female,54,Masters,0,11,88,28,31,8.0,7,94,Urban,ML Engineer,114054,0 +22507,Female,46,Bachelors,19,82,20,26,57,5.0,1,5,Semi-Urban,Data Analyst,32121,0 +22508,Female,26,High School,12,52,60,90,50,4.0,2,23,Urban,HR Executive,33401,0 +22509,Male,23,Masters,2,9,2,1,98,2.0,1,8,Urban,HR Executive,94805,0 +22510,Male,49,Bachelors,13,87,95,49,31,2.0,6,73,Rural,ML Engineer,117164,1 +22511,Male,43,Bachelors,9,83,30,70,67,3.0,2,94,Semi-Urban,ML Engineer,105752,1 +22512,Male,39,Masters,16,59,61,31,57,2.0,5,86,Urban,HR Executive,69632,1 +22513,Other,21,Diploma,6,27,27,74,10,8.0,6,91,Urban,HR Executive,23374,0 +22514,Female,54,Bachelors,2,19,12,70,46,1.0,7,98,Urban,Data Analyst,113008,0 +22515,Male,44,Diploma,16,89,5,98,85,9.0,0,18,Urban,Data Analyst,50826,0 +22516,Female,58,High School,18,44,21,28,88,3.0,2,13,Semi-Urban,ML Engineer,68706,0 +22517,Male,56,Bachelors,17,80,49,36,13,7.0,1,79,Rural,Data Analyst,71794,1 +22518,Female,21,Bachelors,5,93,49,31,63,9.0,6,45,Urban,ML Engineer,102361,0 +22519,Male,50,Bachelors,7,40,75,6,47,9.0,0,23,Urban,Manager,40138,0 +22520,Female,43,Diploma,2,50,28,25,66,1.0,2,81,Urban,Manager,72904,0 +22521,Male,34,Bachelors,6,90,98,11,97,7.0,6,38,Urban,HR Executive,113318,1 +22522,Male,59,Bachelors,10,10,65,81,53,6.0,6,85,Rural,ML Engineer,42436,1 +22523,Male,47,Bachelors,12,5,98,86,59,6.0,4,87,Rural,ML Engineer,75677,1 +22524,Male,38,Bachelors,17,47,17,78,93,4.0,5,82,Rural,HR Executive,63830,0 +22525,Female,41,PhD,2,58,65,27,37,6.0,0,89,Urban,ML Engineer,71295,0 +22526,Male,57,Diploma,10,8,20,58,36,8.0,4,87,Rural,Data Analyst,113434,0 +22527,Female,58,Bachelors,18,97,42,74,49,7.0,0,84,Urban,Data Analyst,145267,1 +22528,Female,39,Bachelors,19,11,60,67,95,6.0,6,41,Urban,Software Engineer,118101,0 +22529,Female,36,Bachelors,0,63,25,79,45,0.0,4,0,Semi-Urban,Manager,56627,0 +22530,Female,47,High School,18,55,99,26,10,5.0,3,64,Rural,Manager,46304,1 +22531,Male,32,Bachelors,10,9,89,4,98,6.0,6,22,Urban,ML Engineer,130514,0 +22532,Male,23,Bachelors,2,3,12,22,5,5.0,1,79,Urban,ML Engineer,73429,0 +22533,Female,21,High School,1,82,86,79,88,9.0,2,74,Urban,HR Executive,132091,1 +22534,Female,46,Bachelors,12,50,71,43,34,5.0,1,16,Urban,Data Analyst,92664,0 +22535,Female,50,Bachelors,11,26,34,41,13,2.0,3,53,Urban,HR Executive,27538,0 +22536,Female,37,Bachelors,1,0,14,9,96,4.0,5,52,Semi-Urban,ML Engineer,32365,0 +22537,Male,33,PhD,13,84,1,9,55,9.0,2,80,Urban,Data Analyst,26892,0 +22538,Female,46,Masters,0,32,29,12,45,0.0,3,28,Urban,Data Analyst,43906,0 +22539,Female,27,Masters,14,90,42,21,66,8.0,4,85,Rural,HR Executive,26724,0 +22540,Male,36,Masters,19,34,12,62,39,4.0,2,41,Semi-Urban,Software Engineer,95430,0 +22541,Female,44,High School,0,5,40,9,58,9.0,6,11,Urban,Manager,25646,0 +22542,Male,22,Bachelors,12,68,17,72,66,9.0,2,91,Semi-Urban,Software Engineer,27547,1 +22543,Male,33,Bachelors,15,14,14,48,32,6.0,5,78,Semi-Urban,Data Analyst,135284,0 +22544,Female,50,Diploma,17,68,19,71,50,4.0,5,43,Urban,HR Executive,45751,0 +22545,Female,55,Bachelors,7,26,97,6,65,5.0,1,0,Urban,Data Analyst,38847,0 +22546,Female,34,Bachelors,11,15,17,60,16,8.0,2,18,Semi-Urban,Manager,73000,0 +22547,Female,34,Masters,9,93,52,51,20,4.0,0,0,Urban,Manager,89384,0 +22548,Male,47,Bachelors,15,14,29,29,76,6.0,3,33,Urban,ML Engineer,75806,0 +22549,Female,27,Masters,19,54,91,18,58,6.0,7,21,Semi-Urban,HR Executive,32998,0 +22550,Male,25,Masters,0,49,55,95,19,6.0,1,17,Semi-Urban,HR Executive,97385,0 +22551,Male,57,Diploma,5,76,44,37,44,6.0,2,31,Rural,Software Engineer,76910,0 +22552,Male,50,High School,9,28,79,30,97,7.0,0,38,Urban,Manager,145402,0 +22553,Female,36,Bachelors,14,18,9,26,72,0.0,5,94,Rural,HR Executive,32208,0 +22554,Male,40,Bachelors,17,98,42,53,14,0.0,1,33,Rural,HR Executive,134202,0 +22555,Female,24,Bachelors,5,97,97,25,47,4.0,5,97,Semi-Urban,Software Engineer,140020,1 +22556,Female,36,PhD,4,74,99,84,10,1.0,6,33,Semi-Urban,Software Engineer,61602,1 +22557,Male,58,Diploma,6,67,4,94,36,3.0,5,13,Urban,Software Engineer,46682,0 +22558,Female,26,High School,14,65,61,60,96,3.0,1,47,Rural,Data Analyst,121184,0 +22559,Male,39,PhD,8,54,28,70,77,7.0,4,31,Rural,Manager,61434,0 +22560,Male,36,Bachelors,18,42,58,20,30,5.0,3,72,Urban,Software Engineer,21114,0 +22561,Female,45,Masters,2,0,1,9,94,1.0,5,63,Rural,ML Engineer,40372,0 +22562,Male,47,Diploma,2,22,35,99,11,9.0,4,71,Urban,Manager,109565,0 +22563,Female,46,Diploma,17,75,55,0,11,2.0,0,42,Urban,Software Engineer,134961,0 +22564,Female,27,Masters,15,59,51,0,43,9.0,6,59,Semi-Urban,Data Analyst,92688,0 +22565,Male,44,Bachelors,4,2,56,8,77,3.0,6,53,Urban,Software Engineer,31063,0 +22566,Female,49,Diploma,4,47,82,34,84,7.0,5,82,Rural,ML Engineer,68668,1 +22567,Male,41,Diploma,7,58,53,1,63,1.0,7,90,Urban,Manager,82996,0 +22568,Male,30,Bachelors,10,44,78,95,53,5.0,6,76,Urban,ML Engineer,115085,1 +22569,Male,51,High School,8,48,69,83,14,5.0,4,25,Urban,Software Engineer,42366,0 +22570,Male,54,Diploma,10,60,99,96,5,7.0,0,0,Urban,Data Analyst,122395,1 +22571,Male,26,Bachelors,7,26,87,20,52,3.0,5,13,Urban,ML Engineer,121734,0 +22572,Other,50,Bachelors,17,89,90,49,60,2.0,1,90,Urban,ML Engineer,32037,1 +22573,Male,44,Bachelors,4,10,87,93,19,9.0,1,14,Semi-Urban,ML Engineer,147919,0 +22574,Female,39,Bachelors,19,8,28,89,58,7.0,1,10,Urban,Manager,137812,0 +22575,Male,26,Bachelors,12,11,66,60,21,7.0,4,93,Urban,Software Engineer,85330,0 +22576,Male,35,High School,10,0,73,59,63,5.0,4,26,Urban,ML Engineer,139892,0 +22577,Male,22,Bachelors,4,63,77,94,69,0.0,4,70,Urban,ML Engineer,144569,1 +22578,Female,35,High School,12,3,11,70,39,0.0,3,87,Rural,HR Executive,70800,0 +22579,Male,42,Bachelors,6,31,34,41,77,3.0,7,1,Urban,Data Analyst,56646,0 +22580,Male,39,Bachelors,12,27,78,4,35,8.0,0,34,Urban,Software Engineer,131176,0 +22581,Male,43,Bachelors,17,25,5,70,13,1.0,1,68,Semi-Urban,HR Executive,105149,0 +22582,Female,56,Masters,13,94,78,82,83,8.0,5,12,Urban,ML Engineer,54861,1 +22583,Male,22,High School,6,46,92,8,67,2.0,5,50,Urban,ML Engineer,34218,0 +22584,Female,45,Bachelors,4,76,50,15,32,8.0,4,54,Rural,Manager,63346,0 +22585,Male,44,Bachelors,6,89,95,34,53,2.0,0,49,Semi-Urban,Data Analyst,117234,1 +22586,Female,39,Bachelors,1,49,72,42,92,3.0,3,4,Urban,HR Executive,83117,0 +22587,Male,25,High School,9,76,24,28,96,4.0,0,97,Urban,ML Engineer,127615,0 +22588,Male,29,Masters,4,86,83,22,52,6.0,2,77,Urban,Software Engineer,112128,1 +22589,Male,33,Bachelors,8,10,55,92,94,5.0,1,47,Urban,Data Analyst,25990,0 +22590,Other,28,Bachelors,17,45,2,70,95,3.0,0,92,Urban,ML Engineer,66149,0 +22591,Male,32,Bachelors,18,92,26,1,52,9.0,1,23,Semi-Urban,ML Engineer,20111,0 +22592,Other,48,Diploma,5,20,75,42,79,5.0,6,71,Urban,ML Engineer,128500,0 +22593,Male,39,Diploma,6,27,42,69,2,1.0,5,87,Urban,HR Executive,147664,0 +22594,Male,25,Bachelors,4,68,54,89,58,1.0,2,44,Semi-Urban,Data Analyst,137694,1 +22595,Male,41,Bachelors,17,71,16,33,79,8.0,3,19,Urban,ML Engineer,94625,0 +22596,Male,53,High School,17,93,43,97,72,5.0,2,28,Urban,ML Engineer,149628,1 +22597,Female,46,Masters,6,99,70,79,1,0.0,2,66,Urban,Data Analyst,38478,1 +22598,Female,53,Masters,16,21,83,0,53,0.0,7,50,Urban,ML Engineer,57670,0 +22599,Female,47,Diploma,17,72,68,89,45,1.0,2,48,Urban,ML Engineer,20412,1 +22600,Female,23,Masters,17,53,92,4,5,9.0,5,72,Rural,Manager,67012,0 +22601,Male,33,Diploma,9,33,92,4,88,6.0,6,43,Urban,Software Engineer,48772,0 +22602,Other,45,Bachelors,10,51,91,20,40,5.0,5,50,Semi-Urban,Software Engineer,93583,0 +22603,Male,23,PhD,1,61,93,48,21,0.0,5,80,Rural,HR Executive,131088,1 +22604,Female,40,Masters,2,19,71,30,31,5.0,4,84,Urban,Manager,129403,0 +22605,Male,30,Bachelors,19,52,97,37,35,4.0,4,97,Urban,Data Analyst,147163,1 +22606,Other,26,Diploma,2,89,43,82,88,2.0,0,83,Urban,HR Executive,100789,1 +22607,Female,23,Bachelors,13,17,40,84,25,7.0,1,59,Urban,Data Analyst,72261,0 +22608,Other,59,High School,2,95,30,30,54,5.0,6,90,Urban,Software Engineer,146235,1 +22609,Male,35,PhD,7,90,80,68,13,8.0,1,91,Urban,HR Executive,146098,1 +22610,Male,30,Diploma,18,6,21,62,58,2.0,6,73,Rural,Manager,121350,0 +22611,Male,57,Masters,9,81,58,44,41,5.0,0,66,Semi-Urban,Manager,63466,1 +22612,Female,41,Masters,12,34,84,99,80,7.0,2,93,Semi-Urban,Manager,98526,1 +22613,Female,34,Diploma,4,47,45,60,20,1.0,2,25,Urban,ML Engineer,94591,0 +22614,Male,28,Bachelors,15,85,88,3,62,2.0,2,60,Rural,ML Engineer,96367,1 +22615,Male,55,Masters,15,94,62,7,96,2.0,1,94,Urban,HR Executive,58121,1 +22616,Male,25,Masters,13,97,71,54,47,9.0,3,71,Urban,Manager,96965,1 +22617,Female,53,Bachelors,16,94,85,98,47,8.0,6,35,Urban,Data Analyst,26851,1 +22618,Male,57,Diploma,0,26,46,49,59,6.0,7,21,Urban,Software Engineer,99443,0 +22619,Female,55,Bachelors,19,82,18,59,3,4.0,5,24,Urban,HR Executive,26303,0 +22620,Male,31,High School,7,59,88,47,42,5.0,7,87,Urban,Data Analyst,53418,1 +22621,Male,49,Diploma,14,78,75,64,18,9.0,0,75,Urban,HR Executive,39140,1 +22622,Female,38,Bachelors,0,45,84,7,66,0.0,5,4,Urban,Software Engineer,50044,0 +22623,Male,57,Bachelors,12,11,50,56,25,7.0,4,59,Semi-Urban,Manager,92434,0 +22624,Male,52,High School,15,78,77,48,57,2.0,6,88,Semi-Urban,HR Executive,29748,1 +22625,Male,37,PhD,14,28,65,73,3,7.0,7,59,Rural,Data Analyst,38254,0 +22626,Male,22,High School,3,94,76,19,47,5.0,3,6,Urban,Manager,97031,0 +22627,Female,48,High School,18,2,43,2,66,5.0,4,44,Rural,Software Engineer,120644,0 +22628,Male,53,High School,9,10,9,14,40,4.0,3,64,Semi-Urban,ML Engineer,36771,0 +22629,Female,34,High School,12,80,16,46,87,8.0,6,77,Urban,Software Engineer,146463,0 +22630,Male,58,Bachelors,14,29,16,71,3,6.0,7,99,Urban,Manager,95798,0 +22631,Female,50,Bachelors,5,90,54,12,55,9.0,6,21,Rural,Data Analyst,66114,0 +22632,Female,27,Bachelors,7,71,33,59,86,6.0,7,19,Urban,Software Engineer,33500,0 +22633,Other,56,High School,17,28,67,93,76,9.0,5,8,Rural,Data Analyst,65652,0 +22634,Female,46,Bachelors,8,46,24,62,80,4.0,3,76,Urban,Data Analyst,30022,0 +22635,Male,44,Bachelors,10,59,99,67,0,0.0,3,92,Semi-Urban,Software Engineer,91764,1 +22636,Male,41,Bachelors,3,62,96,18,49,9.0,1,8,Semi-Urban,Data Analyst,36471,0 +22637,Female,34,Diploma,17,72,26,53,20,8.0,4,97,Rural,ML Engineer,99540,1 +22638,Male,35,Masters,18,40,53,72,20,1.0,0,48,Rural,Manager,102600,0 +22639,Male,52,Bachelors,0,84,26,54,46,8.0,0,93,Urban,ML Engineer,98355,1 +22640,Male,34,Bachelors,10,95,91,49,28,9.0,4,47,Rural,ML Engineer,64608,1 +22641,Male,52,Diploma,6,8,12,19,16,2.0,7,52,Urban,Software Engineer,92669,0 +22642,Male,46,Bachelors,17,91,32,18,55,8.0,1,9,Semi-Urban,HR Executive,135949,0 +22643,Male,38,Bachelors,15,64,41,83,91,6.0,4,73,Urban,Manager,130795,1 +22644,Male,22,Masters,13,0,79,70,62,6.0,1,28,Urban,Manager,146900,0 +22645,Female,39,High School,10,82,80,51,83,0.0,7,20,Urban,HR Executive,47871,0 +22646,Male,44,Masters,14,21,77,84,17,0.0,4,9,Rural,Software Engineer,75929,0 +22647,Other,45,Bachelors,19,74,96,95,6,9.0,5,32,Rural,Manager,97645,1 +22648,Male,22,Diploma,8,3,31,51,29,7.0,0,35,Urban,Manager,46893,0 +22649,Female,54,Masters,12,69,92,47,82,0.0,0,36,Semi-Urban,ML Engineer,122607,1 +22650,Male,29,Masters,0,46,26,61,51,7.0,5,40,Urban,ML Engineer,85089,0 +22651,Male,54,Diploma,16,55,71,2,40,5.0,1,5,Urban,Software Engineer,44216,0 +22652,Male,46,Bachelors,9,53,67,20,10,0.0,6,59,Semi-Urban,HR Executive,146756,0 +22653,Male,26,Masters,3,3,76,84,43,8.0,1,88,Urban,HR Executive,128380,1 +22654,Female,32,Bachelors,14,85,68,80,29,1.0,2,83,Urban,HR Executive,81231,1 +22655,Female,29,Bachelors,13,69,82,14,41,6.0,2,54,Semi-Urban,Data Analyst,31409,0 +22656,Male,30,Bachelors,17,50,0,38,10,8.0,6,27,Semi-Urban,Software Engineer,137668,0 +22657,Male,41,Masters,4,19,66,58,33,5.0,3,95,Urban,HR Executive,25916,1 +22658,Male,36,Bachelors,4,42,37,85,65,0.0,4,10,Urban,Manager,115871,0 +22659,Male,57,Masters,17,80,28,65,24,7.0,4,25,Urban,ML Engineer,95674,0 +22660,Male,37,Bachelors,15,82,26,78,17,0.0,2,46,Urban,ML Engineer,123972,0 +22661,Other,55,High School,2,77,54,66,62,9.0,7,93,Rural,ML Engineer,143226,1 +22662,Male,34,Diploma,17,23,28,99,36,2.0,0,47,Rural,Manager,78567,0 +22663,Female,49,Bachelors,5,19,63,45,3,0.0,3,87,Urban,Software Engineer,121571,0 +22664,Female,32,Masters,2,36,4,89,40,3.0,1,61,Rural,Data Analyst,102633,0 +22665,Female,53,Diploma,17,56,58,46,98,3.0,6,50,Urban,ML Engineer,121407,0 +22666,Male,43,PhD,13,13,45,74,45,4.0,6,15,Rural,Manager,54482,0 +22667,Female,24,Bachelors,12,1,11,46,59,9.0,4,8,Urban,ML Engineer,137285,0 +22668,Female,56,High School,12,69,96,8,93,6.0,7,57,Semi-Urban,HR Executive,134704,0 +22669,Male,31,High School,4,19,73,97,32,0.0,6,24,Semi-Urban,ML Engineer,82530,0 +22670,Male,51,Diploma,7,57,6,21,93,3.0,2,37,Urban,HR Executive,115411,0 +22671,Other,40,High School,7,94,50,61,29,4.0,0,98,Semi-Urban,Manager,144267,1 +22672,Female,32,Bachelors,11,87,10,22,60,0.0,0,57,Urban,ML Engineer,117616,0 +22673,Male,24,Masters,5,99,19,77,0,7.0,6,89,Rural,HR Executive,34679,1 +22674,Male,35,Diploma,4,3,40,74,71,3.0,2,8,Urban,HR Executive,67789,0 +22675,Male,31,PhD,9,15,60,92,35,2.0,6,75,Urban,Software Engineer,97133,1 +22676,Male,54,Bachelors,12,59,56,15,47,1.0,6,14,Rural,HR Executive,24806,0 +22677,Male,23,Masters,14,44,28,38,34,5.0,1,60,Semi-Urban,HR Executive,118373,0 +22678,Male,59,Bachelors,3,19,83,56,25,9.0,3,40,Urban,Manager,115487,0 +22679,Female,52,Masters,1,96,22,72,13,3.0,1,51,Urban,Software Engineer,50970,1 +22680,Female,49,Bachelors,6,65,68,62,92,8.0,3,84,Urban,HR Executive,70329,1 +22681,Female,41,Bachelors,16,10,62,30,40,8.0,2,52,Urban,ML Engineer,71507,0 +22682,Male,39,Masters,5,45,52,45,40,5.0,5,0,Urban,ML Engineer,25096,0 +22683,Female,54,Bachelors,4,46,44,61,6,4.0,5,8,Urban,Data Analyst,88838,0 +22684,Male,55,High School,4,68,42,74,58,3.0,5,46,Urban,Manager,42211,0 +22685,Male,38,Bachelors,11,27,43,1,1,8.0,6,74,Urban,Data Analyst,79818,0 +22686,Female,32,High School,9,91,56,38,85,6.0,4,13,Urban,ML Engineer,58126,0 +22687,Male,35,Bachelors,11,63,97,99,71,2.0,0,13,Urban,Data Analyst,93552,1 +22688,Male,30,Masters,19,41,43,44,34,5.0,2,48,Urban,Manager,104383,0 +22689,Male,41,Diploma,18,55,13,48,34,8.0,6,79,Urban,Data Analyst,85033,0 +22690,Male,22,Diploma,16,29,69,91,12,5.0,2,27,Urban,HR Executive,53867,0 +22691,Female,39,Masters,5,48,5,52,97,2.0,3,77,Semi-Urban,Manager,122865,0 +22692,Other,36,Masters,9,78,42,26,89,8.0,4,97,Urban,Software Engineer,120421,1 +22693,Female,58,Masters,12,61,45,51,21,3.0,0,69,Rural,ML Engineer,113945,0 +22694,Female,55,Diploma,9,9,72,44,36,0.0,4,16,Semi-Urban,Software Engineer,68735,0 +22695,Female,55,Masters,5,70,43,23,54,8.0,2,42,Urban,Data Analyst,105551,0 +22696,Female,25,Bachelors,0,15,4,89,58,5.0,2,32,Urban,Manager,52110,0 +22697,Male,26,Bachelors,3,27,7,3,96,5.0,0,54,Rural,HR Executive,40949,0 +22698,Female,59,Diploma,12,21,26,13,82,5.0,6,96,Urban,Software Engineer,20716,0 +22699,Male,34,Bachelors,3,14,10,49,4,1.0,1,1,Rural,Manager,102260,0 +22700,Female,48,Bachelors,9,62,45,32,78,4.0,1,6,Urban,HR Executive,82348,0 +22701,Male,29,Diploma,11,38,71,39,82,5.0,3,23,Urban,HR Executive,58778,0 +22702,Female,50,Bachelors,0,93,62,56,46,6.0,5,84,Semi-Urban,Data Analyst,54770,1 +22703,Female,58,Masters,2,61,56,53,40,5.0,6,59,Rural,Software Engineer,38074,0 +22704,Other,43,Bachelors,5,35,20,31,28,0.0,5,3,Semi-Urban,ML Engineer,147518,0 +22705,Female,24,Masters,11,90,76,3,71,7.0,1,27,Semi-Urban,Software Engineer,30539,0 +22706,Male,55,Bachelors,7,29,31,67,13,7.0,1,64,Urban,ML Engineer,135173,0 +22707,Male,45,Bachelors,13,24,20,89,29,2.0,0,6,Urban,Data Analyst,38837,0 +22708,Male,55,High School,1,27,48,80,86,5.0,1,53,Urban,Manager,77697,0 +22709,Male,54,Bachelors,4,3,44,32,88,0.0,6,37,Rural,ML Engineer,120848,0 +22710,Male,23,Masters,18,82,1,37,53,5.0,0,62,Urban,Software Engineer,53624,0 +22711,Male,59,Masters,0,82,45,5,79,8.0,7,90,Urban,Software Engineer,82567,0 +22712,Male,43,Bachelors,15,60,31,88,53,4.0,5,31,Semi-Urban,ML Engineer,79958,0 +22713,Female,29,Masters,12,14,74,98,6,8.0,2,64,Semi-Urban,Software Engineer,34875,1 +22714,Female,44,Masters,1,62,69,0,6,7.0,7,28,Urban,Software Engineer,142554,0 +22715,Male,41,High School,8,81,45,88,77,3.0,4,98,Urban,Data Analyst,131303,1 +22716,Male,45,Bachelors,17,70,95,53,99,3.0,1,29,Urban,ML Engineer,78350,1 +22717,Male,42,Masters,14,49,38,13,16,1.0,4,38,Urban,ML Engineer,125966,0 +22718,Male,27,Masters,1,61,82,1,19,0.0,6,77,Semi-Urban,Data Analyst,92606,0 +22719,Male,48,Masters,13,58,28,23,1,9.0,7,52,Urban,Software Engineer,63755,0 +22720,Male,27,Bachelors,0,10,85,62,28,1.0,0,89,Urban,Manager,33260,1 +22721,Male,55,Bachelors,19,36,11,16,75,4.0,2,74,Urban,ML Engineer,63689,0 +22722,Male,38,Diploma,17,61,93,1,82,0.0,0,79,Urban,Manager,108186,0 +22723,Male,45,Bachelors,13,27,0,82,73,5.0,0,5,Urban,Software Engineer,50604,0 +22724,Male,50,Bachelors,18,30,98,95,21,8.0,6,84,Semi-Urban,Data Analyst,65712,1 +22725,Female,29,Bachelors,10,63,13,10,2,4.0,7,82,Urban,Software Engineer,85274,0 +22726,Female,26,PhD,1,40,58,51,57,3.0,5,8,Urban,Software Engineer,72680,0 +22727,Male,40,Bachelors,4,47,31,58,7,0.0,7,93,Rural,Data Analyst,130395,0 +22728,Male,38,Masters,4,31,17,78,26,2.0,3,57,Rural,HR Executive,90745,0 +22729,Male,49,Masters,2,23,34,0,73,0.0,7,33,Rural,HR Executive,135203,0 +22730,Male,21,Masters,3,67,32,82,23,2.0,0,34,Rural,Data Analyst,61102,0 +22731,Male,58,Diploma,15,72,82,77,56,1.0,0,23,Urban,Manager,144239,1 +22732,Male,46,Diploma,19,20,34,94,98,7.0,5,83,Rural,Data Analyst,100014,0 +22733,Male,29,Bachelors,5,40,32,66,40,3.0,0,91,Urban,Data Analyst,61338,0 +22734,Male,24,Bachelors,15,97,28,37,63,0.0,4,67,Semi-Urban,Software Engineer,34210,0 +22735,Female,55,Bachelors,11,10,86,51,9,4.0,3,25,Urban,Data Analyst,42871,0 +22736,Male,53,High School,1,51,63,82,54,8.0,2,6,Rural,ML Engineer,133330,0 +22737,Male,37,Diploma,1,45,80,37,18,1.0,0,6,Urban,ML Engineer,116087,0 +22738,Male,22,High School,0,61,11,39,43,2.0,4,40,Urban,HR Executive,42940,0 +22739,Male,30,High School,12,18,55,72,79,0.0,4,0,Semi-Urban,Manager,120329,0 +22740,Female,43,Bachelors,11,41,15,41,34,6.0,2,54,Urban,ML Engineer,48913,0 +22741,Female,25,Bachelors,4,4,79,78,23,2.0,3,23,Semi-Urban,Software Engineer,107914,0 +22742,Male,38,Masters,1,31,95,20,15,4.0,2,26,Rural,ML Engineer,57533,0 +22743,Female,23,Bachelors,11,91,63,96,9,7.0,0,50,Urban,ML Engineer,72676,1 +22744,Female,42,High School,9,51,94,95,69,8.0,0,27,Urban,HR Executive,40048,1 +22745,Male,40,High School,18,71,9,25,69,1.0,0,61,Rural,Software Engineer,59882,0 +22746,Male,21,Diploma,14,71,3,15,77,6.0,5,44,Semi-Urban,Manager,35831,0 +22747,Female,53,Diploma,16,27,82,86,24,9.0,7,4,Rural,Manager,149934,0 +22748,Male,53,Bachelors,18,72,14,66,10,2.0,6,40,Semi-Urban,Data Analyst,73555,0 +22749,Male,36,Diploma,12,15,85,42,91,3.0,6,7,Urban,Data Analyst,108055,0 +22750,Male,23,Masters,19,34,6,40,84,2.0,2,15,Urban,Data Analyst,92474,0 +22751,Female,31,PhD,8,42,8,84,73,6.0,4,31,Urban,Software Engineer,28386,0 +22752,Female,31,Bachelors,10,43,5,78,32,5.0,6,11,Urban,Data Analyst,142024,0 +22753,Female,34,Diploma,0,56,69,38,20,2.0,5,68,Urban,ML Engineer,91579,0 +22754,Female,23,Masters,4,52,85,91,81,7.0,3,77,Rural,Manager,92211,1 +22755,Other,40,Bachelors,12,77,98,86,17,0.0,5,46,Urban,Data Analyst,21894,1 +22756,Female,57,Bachelors,3,3,7,83,49,2.0,0,10,Urban,Software Engineer,33180,0 +22757,Female,40,Bachelors,6,12,8,70,11,4.0,7,62,Urban,Data Analyst,94025,0 +22758,Other,31,Diploma,12,55,48,49,18,8.0,3,59,Urban,Software Engineer,24720,0 +22759,Male,51,Bachelors,16,48,46,77,61,5.0,2,97,Semi-Urban,Software Engineer,139139,1 +22760,Female,21,Bachelors,9,21,90,58,15,0.0,2,73,Semi-Urban,ML Engineer,49590,1 +22761,Female,26,Masters,6,48,67,98,10,7.0,6,70,Urban,HR Executive,140678,1 +22762,Female,56,Bachelors,14,62,60,30,79,6.0,5,21,Urban,Data Analyst,91658,0 +22763,Female,36,Bachelors,13,59,19,78,11,5.0,6,42,Urban,ML Engineer,141763,0 +22764,Female,27,Diploma,0,24,14,2,29,7.0,4,0,Urban,ML Engineer,143265,0 +22765,Female,22,PhD,18,6,61,2,97,9.0,6,57,Urban,HR Executive,59575,0 +22766,Male,27,High School,19,11,2,80,49,4.0,4,71,Semi-Urban,Data Analyst,57252,0 +22767,Male,58,High School,16,95,25,90,71,4.0,7,13,Semi-Urban,Manager,91107,0 +22768,Male,25,Bachelors,2,94,77,48,14,0.0,7,45,Semi-Urban,HR Executive,32551,1 +22769,Male,23,Diploma,13,12,10,60,83,6.0,6,31,Rural,ML Engineer,93634,0 +22770,Male,42,Masters,6,45,86,73,55,8.0,1,82,Urban,ML Engineer,109941,1 +22771,Male,29,High School,18,85,23,24,13,3.0,2,43,Urban,Software Engineer,133221,0 +22772,Male,25,Bachelors,18,48,56,88,9,1.0,0,6,Urban,Software Engineer,126738,0 +22773,Female,58,Bachelors,16,46,8,11,33,3.0,3,16,Rural,Software Engineer,49626,0 +22774,Male,52,Bachelors,2,58,10,18,10,9.0,6,84,Semi-Urban,HR Executive,128876,0 +22775,Female,34,Bachelors,17,86,97,95,17,7.0,0,85,Semi-Urban,Data Analyst,71223,1 +22776,Female,47,Bachelors,15,36,26,67,42,7.0,6,68,Rural,Data Analyst,129800,0 +22777,Male,29,Bachelors,8,42,75,71,8,7.0,0,9,Semi-Urban,Data Analyst,65254,0 +22778,Male,39,Diploma,19,70,8,29,54,9.0,0,35,Urban,ML Engineer,120578,0 +22779,Female,47,High School,18,2,37,26,73,8.0,1,32,Urban,ML Engineer,70228,0 +22780,Female,29,Bachelors,17,28,56,71,16,9.0,0,53,Urban,Software Engineer,58914,0 +22781,Male,53,Diploma,15,43,9,21,53,6.0,2,89,Semi-Urban,ML Engineer,105792,0 +22782,Male,58,Bachelors,1,99,54,46,13,5.0,5,72,Urban,Manager,28802,1 +22783,Male,44,Diploma,7,88,76,26,63,6.0,4,55,Semi-Urban,Manager,79473,1 +22784,Male,29,Masters,4,12,19,42,28,1.0,1,75,Urban,HR Executive,141118,0 +22785,Male,35,PhD,6,55,25,8,88,0.0,2,43,Urban,ML Engineer,73552,0 +22786,Male,40,Bachelors,8,67,99,20,56,3.0,7,42,Urban,Software Engineer,60558,0 +22787,Female,38,PhD,3,38,26,97,17,0.0,2,58,Urban,HR Executive,26544,0 +22788,Other,25,Bachelors,11,56,91,80,87,6.0,2,96,Urban,Software Engineer,43462,1 +22789,Female,33,Diploma,11,80,95,63,73,1.0,3,14,Urban,Data Analyst,126917,1 +22790,Female,34,Masters,19,34,4,16,80,8.0,0,64,Rural,Manager,135718,0 +22791,Female,45,High School,14,49,49,99,76,3.0,4,82,Semi-Urban,Data Analyst,35060,1 +22792,Female,47,PhD,1,44,48,17,89,8.0,1,87,Urban,HR Executive,91066,0 +22793,Male,34,Bachelors,19,84,15,91,37,3.0,1,6,Urban,ML Engineer,84363,0 +22794,Male,53,Bachelors,12,25,83,58,57,6.0,0,0,Semi-Urban,Software Engineer,36333,0 +22795,Female,53,Bachelors,14,48,18,96,70,5.0,2,19,Urban,ML Engineer,119023,0 +22796,Female,25,High School,2,91,98,53,2,7.0,7,28,Semi-Urban,HR Executive,46741,1 +22797,Male,56,Bachelors,2,2,19,13,37,0.0,1,93,Urban,Data Analyst,146687,0 +22798,Male,54,High School,5,27,12,31,1,0.0,0,51,Urban,Software Engineer,23154,0 +22799,Female,40,Bachelors,9,4,55,64,90,8.0,0,52,Rural,Data Analyst,29444,0 +22800,Male,37,Bachelors,18,95,39,97,17,3.0,7,44,Urban,Software Engineer,97453,1 +22801,Male,36,High School,10,98,17,47,9,4.0,2,54,Urban,HR Executive,61268,0 +22802,Female,52,Bachelors,5,36,70,38,16,8.0,4,8,Semi-Urban,ML Engineer,104100,0 +22803,Male,52,Bachelors,4,96,23,70,67,9.0,3,26,Semi-Urban,ML Engineer,78404,0 +22804,Female,26,PhD,11,0,30,24,83,8.0,5,73,Urban,ML Engineer,129518,0 +22805,Female,58,Masters,0,90,75,76,64,1.0,4,28,Urban,Data Analyst,107518,1 +22806,Male,39,Masters,2,30,37,89,27,3.0,4,66,Semi-Urban,ML Engineer,21810,0 +22807,Male,34,Bachelors,7,91,31,99,52,7.0,0,51,Urban,ML Engineer,57889,1 +22808,Male,56,Diploma,1,24,18,61,48,8.0,6,48,Urban,Data Analyst,25099,0 +22809,Male,38,High School,6,6,77,64,67,3.0,2,8,Rural,Software Engineer,93820,0 +22810,Female,29,Diploma,1,69,26,45,2,2.0,7,78,Urban,Software Engineer,126555,0 +22811,Male,50,Bachelors,13,9,93,64,61,5.0,5,35,Urban,HR Executive,92864,0 +22812,Male,35,High School,4,45,12,5,0,2.0,5,50,Semi-Urban,Software Engineer,109558,0 +22813,Male,41,Bachelors,4,7,78,5,6,4.0,1,55,Semi-Urban,Data Analyst,112821,0 +22814,Male,39,Masters,11,78,37,63,48,9.0,7,36,Urban,Manager,120289,0 +22815,Male,53,Masters,17,72,74,22,81,3.0,7,48,Urban,HR Executive,144677,0 +22816,Female,39,Masters,10,96,92,41,27,2.0,4,60,Urban,Software Engineer,80827,1 +22817,Male,26,Bachelors,3,45,23,59,37,1.0,3,22,Urban,ML Engineer,104362,0 +22818,Male,24,Bachelors,2,95,47,19,77,4.0,4,65,Rural,Data Analyst,73799,0 +22819,Male,30,Bachelors,15,43,89,21,56,1.0,2,23,Urban,Data Analyst,47553,0 +22820,Female,27,Diploma,2,34,80,91,90,5.0,1,75,Semi-Urban,HR Executive,128416,1 +22821,Male,22,Diploma,1,45,42,4,57,7.0,1,40,Urban,Data Analyst,20828,0 +22822,Female,22,Diploma,9,42,24,37,42,7.0,6,51,Urban,Manager,65087,0 +22823,Male,32,Diploma,3,82,32,24,45,7.0,6,0,Urban,Data Analyst,122985,0 +22824,Female,43,Diploma,6,99,68,33,44,9.0,6,7,Semi-Urban,Manager,47823,0 +22825,Male,44,High School,13,51,32,20,47,4.0,4,69,Urban,Software Engineer,139209,0 +22826,Female,49,High School,0,64,59,16,99,6.0,2,9,Semi-Urban,HR Executive,77703,0 +22827,Female,45,Bachelors,14,78,44,84,40,9.0,5,26,Urban,HR Executive,100276,0 +22828,Female,43,Bachelors,6,27,30,53,1,8.0,1,1,Rural,HR Executive,84852,0 +22829,Male,57,Masters,14,34,19,52,99,1.0,4,37,Urban,Software Engineer,98796,0 +22830,Female,23,Bachelors,1,95,39,53,30,2.0,7,56,Urban,Data Analyst,136041,1 +22831,Female,42,Bachelors,19,46,79,40,0,6.0,1,63,Urban,Software Engineer,63063,0 +22832,Male,29,Diploma,18,3,72,59,28,9.0,3,84,Semi-Urban,Manager,142654,0 +22833,Male,39,Bachelors,16,39,32,48,97,3.0,7,16,Urban,ML Engineer,43016,0 +22834,Female,43,Bachelors,16,35,39,19,0,0.0,4,80,Semi-Urban,Software Engineer,140067,0 +22835,Male,35,Bachelors,19,34,36,2,54,3.0,3,16,Urban,Data Analyst,36868,0 +22836,Female,32,Diploma,6,8,53,94,0,9.0,1,65,Urban,Data Analyst,96053,0 +22837,Male,57,Diploma,3,97,73,98,70,0.0,4,69,Urban,ML Engineer,112554,1 +22838,Male,33,Bachelors,10,89,22,61,10,4.0,2,95,Semi-Urban,Manager,58427,1 +22839,Female,29,High School,15,32,2,89,17,9.0,0,1,Rural,Data Analyst,30503,0 +22840,Male,32,Diploma,16,78,9,18,28,7.0,2,79,Urban,HR Executive,28307,0 +22841,Other,25,Masters,7,97,26,12,79,3.0,5,43,Urban,ML Engineer,89316,0 +22842,Female,39,Bachelors,0,65,89,34,97,9.0,3,4,Urban,HR Executive,95808,0 +22843,Female,32,Masters,10,45,82,30,26,0.0,0,56,Urban,HR Executive,114197,0 +22844,Female,49,Bachelors,11,72,19,38,24,3.0,6,45,Urban,Manager,127691,0 +22845,Female,57,High School,12,44,94,92,61,5.0,6,75,Urban,Software Engineer,117061,1 +22846,Male,53,Masters,15,31,1,45,23,1.0,7,82,Semi-Urban,Manager,95585,0 +22847,Female,26,Bachelors,5,53,54,69,28,3.0,2,98,Urban,ML Engineer,57535,1 +22848,Male,35,Bachelors,10,37,81,41,23,4.0,0,71,Urban,ML Engineer,84570,0 +22849,Male,54,High School,4,12,66,9,96,1.0,6,56,Urban,HR Executive,126470,0 +22850,Male,41,Diploma,3,93,17,69,79,4.0,5,51,Semi-Urban,ML Engineer,24272,0 +22851,Female,49,Masters,18,87,24,12,82,6.0,2,29,Rural,ML Engineer,106069,0 +22852,Male,58,PhD,13,19,27,98,45,8.0,1,66,Urban,Software Engineer,127041,0 +22853,Male,23,Diploma,17,1,4,26,86,3.0,3,12,Urban,ML Engineer,135838,0 +22854,Female,52,High School,10,6,95,66,53,1.0,1,76,Rural,Manager,53158,1 +22855,Male,22,Bachelors,4,39,16,46,70,7.0,1,16,Urban,Manager,57870,0 +22856,Female,28,Diploma,6,5,54,90,85,5.0,5,10,Rural,Software Engineer,51511,0 +22857,Female,47,Bachelors,7,78,72,33,22,8.0,2,36,Urban,Software Engineer,138086,0 +22858,Male,24,Diploma,14,22,55,42,65,8.0,7,83,Urban,Software Engineer,106053,0 +22859,Male,58,Masters,7,57,81,3,74,8.0,5,8,Rural,Manager,113176,0 +22860,Female,33,Masters,2,0,82,46,46,4.0,0,9,Urban,HR Executive,100451,0 +22861,Male,57,Bachelors,3,82,63,0,18,0.0,7,47,Urban,Data Analyst,82051,0 +22862,Male,45,Bachelors,8,44,50,28,47,2.0,3,77,Semi-Urban,Software Engineer,62687,0 +22863,Male,21,Bachelors,2,51,95,76,23,5.0,5,48,Semi-Urban,Manager,39909,1 +22864,Male,41,Masters,5,83,54,64,3,1.0,1,99,Urban,Software Engineer,78561,1 +22865,Male,29,Bachelors,3,41,68,72,79,8.0,3,86,Urban,Software Engineer,106593,1 +22866,Male,29,Bachelors,7,27,52,97,18,5.0,0,19,Semi-Urban,HR Executive,147599,0 +22867,Female,40,PhD,0,74,85,90,55,5.0,7,32,Urban,Data Analyst,122953,1 +22868,Male,49,Diploma,18,47,8,57,77,9.0,0,98,Semi-Urban,Software Engineer,149625,0 +22869,Female,22,Bachelors,2,33,88,3,71,7.0,2,23,Urban,ML Engineer,56026,0 +22870,Male,24,Masters,17,0,32,99,81,8.0,1,69,Urban,Software Engineer,69845,0 +22871,Male,48,High School,15,46,85,30,89,5.0,2,7,Urban,HR Executive,65035,0 +22872,Female,35,Masters,14,97,65,13,53,1.0,5,97,Urban,Data Analyst,139810,1 +22873,Female,40,Bachelors,18,34,7,12,89,7.0,0,10,Semi-Urban,ML Engineer,25417,0 +22874,Female,42,Masters,4,25,13,74,58,0.0,0,85,Urban,Manager,55429,0 +22875,Female,23,Bachelors,14,53,97,43,20,3.0,6,34,Urban,Software Engineer,139730,0 +22876,Female,41,Bachelors,3,4,73,7,37,2.0,1,62,Urban,Data Analyst,29229,0 +22877,Male,23,Bachelors,7,55,30,73,7,0.0,3,85,Urban,Software Engineer,26958,1 +22878,Female,30,Bachelors,1,26,67,97,54,1.0,1,78,Urban,ML Engineer,100398,1 +22879,Female,42,Bachelors,8,30,27,30,71,7.0,0,48,Semi-Urban,Data Analyst,149130,0 +22880,Other,28,Diploma,15,56,75,16,25,7.0,0,79,Urban,Manager,128876,0 +22881,Female,55,Masters,3,72,6,44,69,8.0,3,19,Urban,Manager,63735,0 +22882,Female,29,Diploma,18,1,82,33,29,3.0,1,79,Rural,Software Engineer,129167,0 +22883,Male,27,PhD,14,92,83,66,27,1.0,0,1,Semi-Urban,Software Engineer,145594,1 +22884,Female,40,Bachelors,3,27,51,30,34,1.0,2,75,Urban,Software Engineer,29305,0 +22885,Other,22,Bachelors,0,53,81,91,25,0.0,6,49,Urban,Data Analyst,93973,1 +22886,Female,56,Bachelors,6,50,27,52,74,2.0,2,79,Urban,Manager,41054,0 +22887,Female,30,Diploma,9,41,28,7,77,2.0,1,38,Rural,Data Analyst,61053,0 +22888,Male,41,Bachelors,13,15,95,15,11,0.0,4,87,Rural,ML Engineer,67847,0 +22889,Female,59,Bachelors,9,54,37,96,55,0.0,6,22,Rural,Data Analyst,82383,0 +22890,Female,57,Bachelors,4,42,71,96,22,6.0,7,68,Rural,Data Analyst,45924,1 +22891,Female,39,High School,17,79,97,50,89,7.0,2,89,Urban,HR Executive,103012,1 +22892,Male,29,Masters,3,13,54,62,92,6.0,5,64,Urban,Data Analyst,122811,0 +22893,Female,55,PhD,4,36,89,1,32,7.0,3,63,Semi-Urban,ML Engineer,30528,0 +22894,Male,47,Diploma,15,28,59,18,11,5.0,5,86,Urban,HR Executive,144545,0 +22895,Female,59,Bachelors,15,0,90,53,40,5.0,3,34,Rural,HR Executive,77694,0 +22896,Male,44,Bachelors,8,12,83,20,29,6.0,6,29,Urban,HR Executive,110087,0 +22897,Female,48,Bachelors,0,83,72,53,47,8.0,1,29,Urban,HR Executive,143179,0 +22898,Male,37,Bachelors,8,77,77,16,8,5.0,7,6,Urban,ML Engineer,111080,0 +22899,Male,42,Bachelors,17,26,23,59,97,2.0,3,11,Urban,HR Executive,22030,0 +22900,Female,43,High School,17,1,95,43,85,5.0,7,35,Urban,Manager,64694,0 +22901,Male,34,PhD,15,75,33,69,93,5.0,5,65,Urban,ML Engineer,67593,1 +22902,Female,38,Bachelors,13,9,91,32,55,5.0,1,47,Semi-Urban,Data Analyst,25124,0 +22903,Female,49,Diploma,8,60,46,35,17,2.0,6,12,Urban,HR Executive,97419,0 +22904,Other,54,Bachelors,13,22,84,91,44,1.0,3,13,Urban,Software Engineer,50963,0 +22905,Male,49,Masters,11,84,32,49,10,3.0,4,72,Urban,Data Analyst,39763,1 +22906,Female,58,Bachelors,18,5,41,22,87,0.0,6,34,Urban,Manager,130520,0 +22907,Male,38,Bachelors,4,35,58,68,78,2.0,5,81,Urban,HR Executive,53110,1 +22908,Female,21,Bachelors,2,53,64,96,27,5.0,0,29,Urban,HR Executive,126528,1 +22909,Female,45,Bachelors,0,38,84,33,11,6.0,1,41,Urban,Software Engineer,95636,0 +22910,Male,44,Bachelors,6,30,21,21,1,3.0,5,41,Rural,Manager,34802,0 +22911,Male,30,Bachelors,7,52,91,58,32,7.0,2,61,Urban,HR Executive,102907,1 +22912,Male,46,Diploma,11,22,42,59,98,7.0,5,88,Urban,Manager,53885,0 +22913,Female,54,Masters,3,12,22,64,69,6.0,4,21,Rural,ML Engineer,111493,0 +22914,Male,52,Diploma,2,22,6,89,4,7.0,7,70,Urban,ML Engineer,70690,0 +22915,Female,52,Bachelors,18,63,69,80,9,3.0,6,99,Rural,HR Executive,73961,1 +22916,Female,48,Bachelors,0,65,75,31,74,5.0,1,68,Semi-Urban,Manager,122327,0 +22917,Other,54,Bachelors,8,86,31,66,68,6.0,1,14,Urban,Manager,21578,0 +22918,Female,24,High School,6,45,72,52,67,6.0,6,61,Rural,ML Engineer,122248,0 +22919,Male,33,Bachelors,19,84,49,86,16,9.0,4,36,Urban,Data Analyst,69822,1 +22920,Female,25,Bachelors,14,70,86,66,74,0.0,4,34,Urban,Data Analyst,126213,1 +22921,Female,58,PhD,8,86,65,71,85,9.0,2,36,Rural,HR Executive,100972,1 +22922,Female,29,Diploma,10,95,42,95,65,9.0,6,72,Urban,Software Engineer,105664,1 +22923,Male,58,Bachelors,9,46,13,76,46,4.0,2,34,Urban,Data Analyst,93004,0 +22924,Male,36,High School,12,35,83,63,75,1.0,3,82,Semi-Urban,ML Engineer,107936,1 +22925,Male,43,Bachelors,13,14,86,7,72,2.0,0,77,Rural,ML Engineer,128534,0 +22926,Male,28,Masters,3,47,57,90,55,7.0,4,57,Urban,Manager,33718,1 +22927,Male,55,Bachelors,16,68,69,16,18,6.0,1,8,Urban,Software Engineer,70156,0 +22928,Male,59,Masters,15,52,52,58,37,0.0,5,18,Urban,Data Analyst,51050,0 +22929,Female,21,Bachelors,0,14,27,95,79,7.0,1,16,Urban,Software Engineer,149721,0 +22930,Male,46,Bachelors,5,95,31,63,99,1.0,5,63,Urban,Manager,116412,1 +22931,Female,49,Diploma,6,72,96,16,57,5.0,5,0,Urban,Manager,132645,0 +22932,Male,56,PhD,14,69,52,48,5,5.0,3,77,Semi-Urban,Manager,88364,1 +22933,Female,28,High School,5,57,37,15,14,6.0,5,67,Urban,Data Analyst,104976,0 +22934,Female,45,High School,2,22,47,12,89,4.0,2,2,Semi-Urban,HR Executive,35941,0 +22935,Female,40,High School,2,24,20,22,33,3.0,2,88,Urban,Manager,88676,0 +22936,Female,22,Bachelors,1,86,41,4,96,9.0,2,6,Urban,Data Analyst,73550,0 +22937,Male,52,Masters,12,95,61,80,88,5.0,1,25,Urban,ML Engineer,22711,1 +22938,Female,45,Masters,14,0,4,45,24,7.0,5,62,Urban,Software Engineer,54038,0 +22939,Male,30,Bachelors,18,84,84,84,17,8.0,3,93,Urban,Software Engineer,54173,1 +22940,Male,47,Masters,10,73,17,76,91,0.0,4,72,Semi-Urban,HR Executive,22698,1 +22941,Male,32,Masters,11,61,44,30,10,0.0,3,65,Urban,Manager,38871,0 +22942,Male,43,High School,18,51,27,93,97,4.0,6,88,Semi-Urban,HR Executive,106503,1 +22943,Male,57,Diploma,12,11,42,80,15,6.0,2,25,Urban,Manager,93441,0 +22944,Female,58,Diploma,0,4,29,31,38,1.0,5,27,Rural,ML Engineer,20226,0 +22945,Male,33,Masters,8,77,9,38,34,9.0,4,29,Semi-Urban,Manager,69351,0 +22946,Female,54,Bachelors,13,39,48,55,68,6.0,4,84,Semi-Urban,Data Analyst,80488,0 +22947,Female,57,Bachelors,9,33,4,73,41,6.0,4,58,Semi-Urban,ML Engineer,86123,0 +22948,Male,30,Diploma,19,47,45,79,3,7.0,6,67,Semi-Urban,Software Engineer,51261,1 +22949,Male,58,Diploma,16,58,41,91,21,8.0,2,77,Rural,HR Executive,88892,1 +22950,Female,41,High School,15,79,47,44,15,8.0,3,51,Semi-Urban,Manager,114470,0 +22951,Male,41,Diploma,4,59,95,6,53,6.0,0,72,Urban,Software Engineer,81275,0 +22952,Male,27,Diploma,2,76,88,5,76,6.0,1,47,Semi-Urban,HR Executive,117676,0 +22953,Female,36,Bachelors,4,7,89,73,5,4.0,1,77,Urban,HR Executive,98038,1 +22954,Male,24,High School,16,11,2,10,79,3.0,5,62,Urban,Data Analyst,129480,0 +22955,Male,39,Masters,9,17,22,61,42,9.0,2,37,Urban,Software Engineer,49400,0 +22956,Male,37,Bachelors,14,51,46,49,71,7.0,5,38,Semi-Urban,Manager,123051,0 +22957,Male,52,Bachelors,14,27,83,14,85,9.0,0,35,Urban,ML Engineer,48545,0 +22958,Male,51,Bachelors,5,9,54,14,27,1.0,6,57,Urban,ML Engineer,73962,0 +22959,Male,25,Bachelors,3,50,62,24,14,5.0,1,14,Urban,Data Analyst,42788,0 +22960,Male,50,Bachelors,4,53,62,11,2,1.0,5,42,Semi-Urban,ML Engineer,100574,0 +22961,Male,31,Diploma,10,77,65,92,92,5.0,4,46,Urban,HR Executive,144685,1 +22962,Other,30,Bachelors,1,17,90,95,97,7.0,3,20,Semi-Urban,Manager,124818,0 +22963,Male,39,Masters,10,65,21,26,76,5.0,4,70,Semi-Urban,ML Engineer,77566,0 +22964,Female,53,Bachelors,11,29,35,57,19,4.0,4,72,Semi-Urban,Manager,136987,0 +22965,Male,22,Diploma,4,91,51,11,44,9.0,3,13,Rural,Data Analyst,52375,0 +22966,Male,55,Diploma,7,53,28,66,33,2.0,5,48,Semi-Urban,ML Engineer,88676,0 +22967,Female,30,Diploma,13,64,97,29,15,5.0,3,68,Rural,Manager,54535,1 +22968,Female,52,Masters,0,61,25,36,40,1.0,6,6,Urban,HR Executive,56828,0 +22969,Male,49,Masters,17,54,58,67,47,0.0,7,10,Semi-Urban,ML Engineer,39447,0 +22970,Male,36,Bachelors,9,85,57,77,51,1.0,0,21,Semi-Urban,Data Analyst,138870,1 +22971,Male,44,High School,13,17,96,0,38,9.0,2,8,Semi-Urban,ML Engineer,110097,0 +22972,Female,30,High School,2,70,37,21,52,1.0,3,98,Semi-Urban,Data Analyst,66475,0 +22973,Male,32,Masters,10,43,50,84,33,5.0,4,34,Urban,HR Executive,130626,0 +22974,Male,23,High School,3,67,20,79,8,7.0,2,37,Urban,Data Analyst,50110,0 +22975,Female,48,Masters,13,55,80,81,56,3.0,2,25,Urban,Data Analyst,140550,1 +22976,Other,51,Masters,8,85,32,48,86,9.0,7,66,Semi-Urban,Software Engineer,137294,0 +22977,Female,35,Diploma,7,65,54,89,84,7.0,1,15,Semi-Urban,Software Engineer,67104,0 +22978,Male,40,Diploma,7,67,11,6,87,2.0,7,36,Semi-Urban,HR Executive,92702,0 +22979,Female,38,Masters,8,79,67,64,93,7.0,2,32,Urban,Software Engineer,50997,1 +22980,Female,39,Bachelors,0,59,9,98,13,6.0,0,18,Semi-Urban,Software Engineer,130915,0 +22981,Female,50,Diploma,16,90,94,92,79,9.0,3,3,Urban,Data Analyst,107132,1 +22982,Female,29,Diploma,1,12,75,13,81,3.0,1,45,Semi-Urban,HR Executive,138826,0 +22983,Female,32,Diploma,19,28,29,0,24,9.0,7,91,Rural,HR Executive,41008,0 +22984,Male,25,Masters,10,73,91,88,82,3.0,1,73,Semi-Urban,Software Engineer,134823,1 +22985,Male,58,High School,17,19,62,79,2,9.0,2,44,Urban,Software Engineer,83299,0 +22986,Female,55,Diploma,10,90,86,74,31,4.0,0,35,Urban,Data Analyst,38493,1 +22987,Male,48,Bachelors,9,36,22,96,24,7.0,0,55,Semi-Urban,Data Analyst,144027,0 +22988,Male,54,Bachelors,7,22,7,91,27,7.0,4,43,Semi-Urban,Software Engineer,136514,0 +22989,Male,40,Diploma,10,47,85,74,43,4.0,4,73,Urban,Data Analyst,100881,1 +22990,Female,41,Diploma,17,56,56,0,80,6.0,3,96,Urban,ML Engineer,111774,0 +22991,Male,33,Diploma,1,71,74,23,4,1.0,4,78,Urban,Data Analyst,64528,1 +22992,Female,29,Bachelors,7,90,81,74,69,1.0,6,86,Urban,Manager,45164,1 +22993,Male,57,Bachelors,18,5,50,67,17,1.0,3,33,Rural,Data Analyst,65911,0 +22994,Male,32,Bachelors,9,75,98,98,17,7.0,2,10,Rural,Software Engineer,43006,1 +22995,Male,44,Diploma,7,78,69,63,38,0.0,6,66,Urban,Data Analyst,95316,1 +22996,Male,46,PhD,7,25,46,68,55,1.0,0,96,Urban,Software Engineer,57215,1 +22997,Female,27,Bachelors,2,13,62,9,53,3.0,2,93,Urban,HR Executive,41147,0 +22998,Female,30,Masters,10,25,30,82,51,8.0,3,48,Urban,Data Analyst,21331,0 +22999,Female,56,Diploma,0,86,10,76,99,3.0,0,35,Urban,Data Analyst,100646,0 +23000,Male,32,Masters,3,72,23,74,27,5.0,3,49,Urban,Software Engineer,85907,0 +23001,Male,37,PhD,4,26,33,92,12,6.0,4,88,Urban,Manager,125195,1 +23002,Male,55,Bachelors,12,25,28,8,34,6.0,7,17,Semi-Urban,Software Engineer,134932,0 +23003,Male,27,Diploma,2,6,16,10,41,4.0,6,37,Rural,HR Executive,129392,0 +23004,Male,26,Diploma,2,56,20,90,69,4.0,3,40,Semi-Urban,Manager,65118,0 +23005,Female,54,PhD,17,1,95,50,23,4.0,4,12,Urban,Manager,21990,0 +23006,Male,54,PhD,15,8,68,12,31,7.0,4,24,Urban,ML Engineer,132075,0 +23007,Male,21,High School,8,10,83,82,34,6.0,7,15,Semi-Urban,HR Executive,143075,0 +23008,Female,45,Diploma,19,80,31,18,80,3.0,7,50,Urban,ML Engineer,144671,0 +23009,Male,41,Diploma,6,2,67,61,82,3.0,4,33,Semi-Urban,ML Engineer,101295,0 +23010,Female,47,Masters,11,78,81,47,70,5.0,7,98,Urban,HR Executive,137283,1 +23011,Other,49,High School,9,16,66,71,66,2.0,4,87,Semi-Urban,Data Analyst,91356,0 +23012,Male,56,Diploma,12,58,57,18,92,5.0,7,1,Semi-Urban,HR Executive,127188,0 +23013,Male,32,Bachelors,5,50,30,88,73,2.0,0,29,Rural,Data Analyst,24562,0 +23014,Female,50,Bachelors,7,90,99,10,12,7.0,1,45,Urban,ML Engineer,125053,1 +23015,Male,24,Bachelors,4,68,32,91,40,9.0,3,48,Semi-Urban,Data Analyst,109448,1 +23016,Male,29,Bachelors,19,87,19,46,40,9.0,5,0,Urban,Software Engineer,90565,0 +23017,Female,40,High School,19,37,75,93,16,1.0,2,32,Semi-Urban,Software Engineer,77439,0 +23018,Male,57,PhD,4,19,77,62,85,0.0,6,93,Semi-Urban,Manager,103872,1 +23019,Male,37,Bachelors,19,52,78,91,91,0.0,6,25,Rural,Data Analyst,37403,1 +23020,Female,55,Bachelors,4,68,29,41,80,4.0,2,91,Semi-Urban,Data Analyst,97219,0 +23021,Female,27,High School,19,75,44,69,8,6.0,5,38,Semi-Urban,HR Executive,62693,0 +23022,Male,58,Masters,4,25,63,82,7,3.0,7,96,Rural,HR Executive,40121,1 +23023,Male,56,High School,2,38,3,46,88,0.0,3,87,Rural,Manager,60761,0 +23024,Male,34,Bachelors,19,20,86,83,92,7.0,1,24,Urban,Data Analyst,98145,0 +23025,Male,37,Diploma,0,23,78,24,40,1.0,5,85,Urban,HR Executive,101602,0 +23026,Female,44,Masters,18,1,31,32,84,9.0,5,78,Semi-Urban,ML Engineer,80744,0 +23027,Female,26,High School,3,89,50,72,32,2.0,3,36,Urban,Software Engineer,128572,1 +23028,Female,45,Masters,4,98,42,2,32,4.0,7,32,Rural,HR Executive,67748,0 +23029,Male,42,Diploma,15,12,82,1,27,4.0,6,28,Urban,HR Executive,51908,0 +23030,Male,44,Bachelors,18,75,86,81,47,2.0,0,29,Urban,Manager,65639,1 +23031,Male,45,Masters,1,62,50,8,77,0.0,7,41,Urban,ML Engineer,139897,0 +23032,Male,54,Masters,14,60,28,65,80,0.0,6,61,Urban,Software Engineer,34914,0 +23033,Male,59,Masters,7,94,45,75,85,5.0,5,68,Urban,ML Engineer,40152,1 +23034,Male,33,Bachelors,19,27,57,22,63,4.0,1,2,Urban,ML Engineer,58779,0 +23035,Male,48,Diploma,15,11,53,46,5,7.0,5,54,Semi-Urban,ML Engineer,78219,0 +23036,Female,44,High School,6,85,39,46,11,1.0,3,25,Urban,Data Analyst,79919,0 +23037,Female,26,Masters,6,81,55,61,89,4.0,0,25,Semi-Urban,HR Executive,64905,0 +23038,Male,57,Bachelors,14,31,62,95,12,9.0,6,21,Semi-Urban,Manager,48874,0 +23039,Male,58,Bachelors,1,38,18,83,49,1.0,5,83,Rural,HR Executive,65855,0 +23040,Female,57,Bachelors,13,8,36,86,55,2.0,7,96,Rural,Software Engineer,51125,0 +23041,Other,29,Bachelors,19,56,96,77,79,6.0,6,63,Urban,HR Executive,21676,1 +23042,Male,43,Masters,19,36,85,40,16,0.0,5,67,Urban,Software Engineer,69314,0 +23043,Female,31,High School,13,42,24,81,63,4.0,6,63,Urban,Software Engineer,27653,0 +23044,Female,55,Masters,1,70,42,74,47,1.0,3,90,Urban,HR Executive,120240,1 +23045,Male,39,Diploma,15,66,96,83,17,7.0,2,24,Semi-Urban,Software Engineer,38889,1 +23046,Male,48,Bachelors,12,52,43,59,14,9.0,0,88,Urban,Manager,36271,1 +23047,Male,39,Diploma,4,92,9,51,32,8.0,2,31,Urban,ML Engineer,98391,0 +23048,Male,50,Bachelors,0,39,78,36,35,2.0,5,5,Semi-Urban,Data Analyst,70604,0 +23049,Male,28,Masters,7,55,80,58,56,0.0,6,74,Rural,Data Analyst,65294,1 +23050,Female,52,Diploma,17,39,25,80,80,8.0,7,90,Urban,HR Executive,113446,0 +23051,Female,25,Masters,13,25,35,71,33,5.0,2,26,Semi-Urban,Data Analyst,149603,0 +23052,Male,25,Bachelors,17,86,54,12,93,2.0,7,94,Urban,Data Analyst,109886,1 +23053,Male,54,Bachelors,1,14,64,42,7,2.0,7,23,Semi-Urban,ML Engineer,25716,0 +23054,Female,46,Bachelors,0,3,88,75,49,0.0,1,23,Urban,Manager,26901,0 +23055,Male,54,Masters,16,34,13,59,73,5.0,5,28,Urban,ML Engineer,133585,0 +23056,Male,33,Bachelors,18,16,88,46,27,5.0,3,83,Urban,HR Executive,79065,0 +23057,Female,41,Masters,10,37,75,61,52,2.0,2,34,Urban,Manager,127579,0 +23058,Male,57,Bachelors,6,75,23,21,30,6.0,4,44,Rural,Software Engineer,88047,0 +23059,Male,21,Bachelors,4,67,15,0,8,4.0,7,38,Urban,Software Engineer,91211,0 +23060,Male,36,Diploma,2,36,77,7,60,6.0,5,48,Rural,ML Engineer,46365,0 +23061,Male,56,High School,0,46,70,28,53,2.0,7,51,Urban,Software Engineer,121635,0 +23062,Male,21,Bachelors,0,90,53,53,58,9.0,2,90,Urban,HR Executive,69065,1 +23063,Male,31,Bachelors,18,63,28,30,35,5.0,3,45,Semi-Urban,ML Engineer,47770,0 +23064,Female,52,Bachelors,17,14,57,52,17,4.0,4,99,Urban,Manager,60115,0 +23065,Male,23,High School,12,95,21,67,41,3.0,4,20,Rural,Manager,57172,0 +23066,Male,43,Bachelors,0,91,50,30,45,1.0,2,23,Urban,HR Executive,119752,0 +23067,Male,41,Bachelors,0,45,4,42,1,0.0,3,22,Urban,Manager,142534,0 +23068,Male,47,Masters,2,77,36,40,50,8.0,1,34,Urban,Software Engineer,46772,0 +23069,Female,55,Masters,10,65,35,22,15,7.0,4,32,Semi-Urban,Manager,122397,0 +23070,Male,31,Bachelors,4,84,21,7,70,0.0,6,5,Urban,Data Analyst,112729,0 +23071,Female,22,High School,18,88,48,77,21,8.0,1,7,Urban,Data Analyst,32831,0 +23072,Male,28,High School,3,60,89,47,95,1.0,7,54,Semi-Urban,Manager,62866,1 +23073,Male,53,Diploma,16,34,24,46,74,2.0,0,98,Rural,Software Engineer,110417,0 +23074,Female,53,Bachelors,6,54,98,15,12,5.0,5,33,Urban,HR Executive,76154,0 +23075,Male,48,Bachelors,18,35,17,55,31,5.0,3,75,Semi-Urban,HR Executive,92248,0 +23076,Female,27,Bachelors,17,3,1,12,42,0.0,5,90,Urban,Data Analyst,61272,0 +23077,Male,58,Bachelors,18,78,54,97,74,6.0,0,53,Urban,HR Executive,109202,1 +23078,Male,52,Bachelors,7,99,44,73,38,6.0,1,75,Rural,Software Engineer,37994,1 +23079,Female,49,High School,16,43,71,88,51,4.0,5,50,Rural,ML Engineer,34630,1 +23080,Female,54,High School,11,84,98,80,29,1.0,7,25,Urban,Software Engineer,112186,1 +23081,Female,56,Diploma,13,79,25,85,93,5.0,3,44,Urban,Manager,32932,0 +23082,Female,26,Bachelors,17,27,5,76,74,3.0,1,94,Urban,ML Engineer,67606,0 +23083,Female,22,Bachelors,9,92,70,56,97,8.0,0,41,Rural,ML Engineer,59840,1 +23084,Male,41,High School,3,24,64,39,7,8.0,4,93,Semi-Urban,ML Engineer,25742,0 +23085,Male,33,Bachelors,17,91,61,49,91,6.0,6,14,Urban,ML Engineer,76250,0 +23086,Male,47,Masters,4,66,68,63,69,7.0,7,88,Urban,Data Analyst,43264,1 +23087,Male,44,Bachelors,10,62,36,1,14,7.0,7,97,Urban,ML Engineer,135857,0 +23088,Male,25,Bachelors,4,14,23,39,78,7.0,0,26,Urban,HR Executive,89892,0 +23089,Female,32,Bachelors,3,14,43,17,26,9.0,4,15,Rural,Manager,119074,0 +23090,Male,30,High School,9,6,49,98,87,4.0,7,84,Rural,Manager,29321,1 +23091,Female,40,High School,5,5,66,20,31,8.0,3,48,Urban,HR Executive,72500,0 +23092,Male,24,Bachelors,4,17,8,18,79,3.0,3,37,Semi-Urban,Software Engineer,68352,0 +23093,Male,39,Masters,8,91,9,52,58,7.0,2,1,Semi-Urban,Software Engineer,54023,0 +23094,Female,53,Bachelors,8,59,49,13,11,3.0,1,61,Urban,HR Executive,92100,0 +23095,Male,27,Bachelors,6,18,7,96,99,9.0,2,23,Urban,HR Executive,112823,0 +23096,Male,34,Diploma,2,42,39,67,15,2.0,4,50,Semi-Urban,Manager,95863,0 +23097,Male,37,Masters,3,0,66,37,20,0.0,3,21,Rural,Manager,107295,0 +23098,Female,37,Bachelors,1,17,71,40,4,5.0,3,70,Urban,HR Executive,72827,0 +23099,Male,28,High School,6,4,19,49,0,2.0,3,64,Urban,Manager,134846,0 +23100,Male,27,Bachelors,17,59,73,22,73,8.0,5,85,Semi-Urban,HR Executive,27197,1 +23101,Female,43,Diploma,6,19,83,80,49,6.0,3,47,Semi-Urban,Software Engineer,124369,0 +23102,Male,43,Masters,9,23,72,92,40,8.0,0,74,Rural,HR Executive,93284,1 +23103,Female,46,Bachelors,19,2,94,18,52,6.0,7,32,Urban,HR Executive,101233,0 +23104,Male,31,Masters,1,73,89,39,70,7.0,6,23,Urban,Software Engineer,66167,0 +23105,Male,36,Masters,8,2,18,62,29,3.0,6,8,Urban,HR Executive,83523,0 +23106,Female,40,Bachelors,3,99,57,54,77,1.0,6,55,Urban,ML Engineer,80501,1 +23107,Female,59,Bachelors,4,42,65,33,10,5.0,2,9,Rural,Manager,61742,0 +23108,Female,39,Masters,19,92,24,52,28,5.0,3,33,Urban,ML Engineer,82601,0 +23109,Female,54,Bachelors,18,61,81,39,23,2.0,3,52,Urban,Data Analyst,126235,0 +23110,Male,30,Diploma,14,87,43,71,94,2.0,0,9,Semi-Urban,Manager,43468,0 +23111,Male,45,Diploma,14,43,36,81,85,3.0,4,19,Semi-Urban,Software Engineer,138721,0 +23112,Male,48,Masters,19,81,98,12,29,3.0,0,49,Rural,HR Executive,37881,1 +23113,Female,26,Bachelors,12,98,88,14,38,0.0,1,56,Semi-Urban,ML Engineer,95683,1 +23114,Female,59,Diploma,19,31,83,33,15,9.0,2,10,Urban,HR Executive,88278,0 +23115,Other,45,Bachelors,17,78,36,65,43,6.0,7,82,Rural,Data Analyst,44252,1 +23116,Male,40,PhD,3,25,60,60,86,2.0,6,82,Urban,ML Engineer,62697,0 +23117,Male,57,Bachelors,11,71,54,40,19,4.0,7,2,Urban,Software Engineer,124428,0 +23118,Female,51,High School,7,74,44,95,11,6.0,7,97,Rural,Data Analyst,143468,1 +23119,Female,23,Bachelors,7,47,85,49,35,5.0,7,23,Urban,Data Analyst,58741,0 +23120,Female,58,Bachelors,9,76,94,5,47,9.0,7,79,Rural,ML Engineer,138397,1 +23121,Female,35,Diploma,16,81,86,48,68,0.0,4,51,Rural,HR Executive,25223,1 +23122,Male,30,Diploma,16,17,99,71,38,6.0,7,62,Rural,ML Engineer,138297,1 +23123,Male,26,Masters,3,68,81,98,26,2.0,6,28,Rural,Software Engineer,37327,1 +23124,Male,25,High School,16,53,55,29,51,8.0,6,79,Semi-Urban,Software Engineer,99780,0 +23125,Male,21,Bachelors,6,41,11,15,92,8.0,4,23,Urban,Data Analyst,104242,0 +23126,Male,52,Bachelors,2,46,89,68,85,4.0,7,80,Urban,Data Analyst,69414,1 +23127,Male,37,Masters,19,64,40,96,39,0.0,6,60,Urban,ML Engineer,36948,1 +23128,Male,25,High School,8,35,21,9,61,1.0,4,41,Semi-Urban,HR Executive,40282,0 +23129,Female,54,High School,14,76,37,73,86,1.0,1,34,Urban,ML Engineer,50130,0 +23130,Female,42,Bachelors,0,27,0,90,25,7.0,6,59,Urban,Software Engineer,131764,0 +23131,Female,29,Masters,2,26,80,17,13,5.0,1,72,Urban,Software Engineer,61919,0 +23132,Male,48,Diploma,1,87,66,34,92,0.0,4,18,Urban,Data Analyst,121092,0 +23133,Male,37,Bachelors,17,10,96,87,25,5.0,3,18,Urban,HR Executive,69555,0 +23134,Male,42,Bachelors,0,15,27,66,21,2.0,5,13,Urban,Data Analyst,125644,0 +23135,Other,34,Diploma,5,68,46,82,81,3.0,3,65,Rural,ML Engineer,38244,1 +23136,Male,47,Masters,7,9,85,91,89,8.0,5,26,Urban,Manager,104875,0 +23137,Male,40,Bachelors,6,84,69,18,17,6.0,3,98,Urban,HR Executive,73859,1 +23138,Female,57,High School,12,42,17,48,84,3.0,1,96,Semi-Urban,Manager,120217,0 +23139,Male,39,Diploma,6,92,87,3,17,8.0,7,42,Rural,HR Executive,85455,0 +23140,Female,33,High School,15,38,61,23,73,5.0,1,50,Urban,ML Engineer,143618,0 +23141,Male,33,High School,6,56,11,28,84,1.0,4,40,Semi-Urban,Software Engineer,100437,0 +23142,Male,24,Masters,15,69,22,75,91,3.0,1,19,Urban,Software Engineer,103987,0 +23143,Male,57,Bachelors,15,38,90,38,90,3.0,6,83,Rural,ML Engineer,32535,1 +23144,Female,32,High School,8,73,78,45,49,1.0,0,87,Urban,HR Executive,100055,1 +23145,Female,53,Bachelors,13,69,64,71,34,4.0,2,3,Rural,Manager,82213,0 +23146,Male,38,Diploma,18,68,48,28,77,2.0,0,29,Rural,Data Analyst,112314,0 +23147,Male,51,High School,8,15,79,53,50,0.0,5,17,Urban,Manager,149049,0 +23148,Male,40,Bachelors,19,93,47,67,97,5.0,1,68,Rural,Manager,36842,1 +23149,Other,49,Bachelors,11,87,20,54,55,8.0,7,40,Urban,Data Analyst,131418,0 +23150,Female,24,Bachelors,7,46,50,58,47,4.0,0,68,Urban,ML Engineer,111341,0 +23151,Female,27,Bachelors,10,16,25,18,15,1.0,7,35,Urban,HR Executive,95479,0 +23152,Male,57,Diploma,8,59,7,8,98,8.0,6,26,Rural,Data Analyst,55952,0 +23153,Male,26,Bachelors,19,74,49,1,31,0.0,5,51,Urban,Manager,79216,0 +23154,Male,54,High School,9,29,54,2,4,0.0,2,27,Urban,Software Engineer,33758,0 +23155,Female,41,High School,5,59,53,99,88,6.0,1,66,Semi-Urban,Data Analyst,98530,1 +23156,Female,45,Bachelors,1,60,75,45,31,5.0,5,78,Urban,Manager,65042,1 +23157,Male,22,Masters,2,32,13,57,70,9.0,1,45,Semi-Urban,ML Engineer,65680,0 +23158,Male,52,Bachelors,13,46,11,66,71,4.0,1,68,Semi-Urban,Manager,60168,0 +23159,Male,24,Diploma,16,61,82,65,80,6.0,1,77,Semi-Urban,Data Analyst,76184,1 +23160,Male,23,Bachelors,19,64,99,61,57,0.0,5,95,Rural,Software Engineer,110527,1 +23161,Female,35,Masters,9,18,53,40,88,0.0,1,25,Urban,Software Engineer,41467,0 +23162,Male,53,PhD,7,98,10,3,93,4.0,1,10,Semi-Urban,ML Engineer,126972,0 +23163,Female,27,Bachelors,4,2,45,80,60,1.0,4,52,Semi-Urban,ML Engineer,59071,0 +23164,Female,24,Masters,12,10,35,13,58,2.0,4,93,Rural,Software Engineer,47239,0 +23165,Female,53,Bachelors,0,90,86,9,28,2.0,7,31,Rural,Software Engineer,69811,0 +23166,Female,36,Diploma,15,73,10,64,73,6.0,5,67,Urban,Data Analyst,78316,0 +23167,Female,27,Bachelors,6,70,63,99,3,3.0,7,91,Urban,ML Engineer,21517,1 +23168,Female,45,High School,19,56,45,41,68,9.0,3,17,Urban,Software Engineer,67256,0 +23169,Male,36,Diploma,12,88,13,48,46,1.0,1,67,Semi-Urban,ML Engineer,119131,0 +23170,Female,30,Diploma,5,19,5,15,96,2.0,1,8,Semi-Urban,Manager,140234,0 +23171,Female,54,Masters,17,61,17,18,72,5.0,2,35,Semi-Urban,ML Engineer,139933,0 +23172,Male,42,Bachelors,17,64,67,52,43,9.0,6,14,Urban,ML Engineer,119759,0 +23173,Female,22,Bachelors,2,37,81,12,5,1.0,1,85,Urban,Software Engineer,90575,0 +23174,Female,47,Diploma,1,32,26,0,15,5.0,1,9,Semi-Urban,HR Executive,80160,0 +23175,Female,48,Diploma,13,10,80,86,33,4.0,3,47,Semi-Urban,Manager,102194,0 +23176,Male,32,Masters,11,35,44,29,78,7.0,3,93,Urban,Manager,122078,0 +23177,Female,45,Diploma,11,61,83,23,30,2.0,5,30,Urban,Manager,130612,0 +23178,Male,51,PhD,16,66,51,72,5,3.0,4,38,Urban,ML Engineer,92117,0 +23179,Female,53,Diploma,12,7,4,17,59,3.0,4,5,Urban,Software Engineer,42705,0 +23180,Male,44,Diploma,14,27,44,84,28,3.0,7,40,Semi-Urban,ML Engineer,113553,0 +23181,Male,23,Bachelors,16,8,94,66,27,9.0,5,20,Urban,Software Engineer,139655,0 +23182,Male,27,PhD,8,48,94,42,78,6.0,5,78,Urban,Data Analyst,134983,1 +23183,Male,39,Bachelors,14,58,1,31,67,8.0,3,72,Urban,Manager,73426,0 +23184,Male,52,Bachelors,11,15,20,84,16,4.0,6,58,Urban,HR Executive,117379,0 +23185,Male,27,Diploma,10,63,76,50,7,1.0,4,96,Urban,HR Executive,58572,1 +23186,Female,30,PhD,0,63,92,65,88,5.0,0,85,Urban,HR Executive,142230,1 +23187,Female,42,Diploma,8,9,7,68,38,2.0,4,6,Urban,ML Engineer,47742,0 +23188,Male,49,High School,3,31,67,54,47,0.0,1,13,Semi-Urban,ML Engineer,148509,0 +23189,Male,59,Bachelors,8,40,26,79,57,0.0,3,72,Semi-Urban,Software Engineer,51113,0 +23190,Male,39,Bachelors,0,27,97,8,46,6.0,2,6,Semi-Urban,Software Engineer,55527,0 +23191,Female,36,Bachelors,6,85,87,3,17,4.0,5,53,Urban,Manager,40774,0 +23192,Male,44,High School,10,26,80,63,12,2.0,0,12,Semi-Urban,Data Analyst,34786,0 +23193,Male,46,Diploma,15,39,90,39,14,3.0,1,9,Urban,Manager,31588,0 +23194,Male,44,Bachelors,4,4,31,28,34,8.0,4,74,Urban,Software Engineer,44746,0 +23195,Male,29,Bachelors,10,11,88,26,91,8.0,2,80,Urban,HR Executive,77967,0 +23196,Male,44,Diploma,7,56,86,66,12,5.0,6,13,Rural,Data Analyst,139504,0 +23197,Male,53,Bachelors,8,21,21,47,92,7.0,3,13,Rural,HR Executive,47741,0 +23198,Female,53,Masters,12,34,12,7,21,4.0,1,32,Urban,Software Engineer,147297,0 +23199,Female,22,Bachelors,17,18,29,2,77,1.0,5,94,Urban,HR Executive,41830,0 +23200,Male,29,High School,17,17,42,10,17,0.0,2,41,Rural,HR Executive,38792,0 +23201,Female,25,Diploma,16,39,66,8,56,1.0,6,98,Semi-Urban,ML Engineer,47666,0 +23202,Male,24,High School,17,60,24,69,78,7.0,4,99,Urban,Data Analyst,147161,1 +23203,Female,58,Masters,6,76,9,10,89,9.0,0,9,Urban,HR Executive,51632,0 +23204,Male,21,Masters,3,85,72,59,54,7.0,3,87,Semi-Urban,ML Engineer,73202,1 +23205,Female,37,High School,1,89,11,22,58,5.0,6,78,Urban,HR Executive,24088,0 +23206,Female,27,PhD,6,66,73,42,60,9.0,7,96,Urban,Manager,84341,1 +23207,Male,47,Bachelors,8,29,14,17,83,1.0,7,48,Urban,Manager,111609,0 +23208,Female,31,Bachelors,14,73,74,54,54,0.0,0,59,Urban,Software Engineer,68084,1 +23209,Male,32,Bachelors,8,86,7,86,13,7.0,6,40,Rural,Data Analyst,118628,0 +23210,Female,43,Bachelors,16,71,10,20,10,7.0,2,53,Urban,ML Engineer,115833,0 +23211,Male,27,Masters,15,97,32,75,59,0.0,2,88,Semi-Urban,ML Engineer,139738,1 +23212,Male,39,Diploma,3,46,90,57,40,9.0,1,91,Urban,HR Executive,73114,1 +23213,Male,50,Bachelors,2,72,15,33,35,9.0,6,93,Semi-Urban,Manager,104073,0 +23214,Male,46,Masters,16,16,40,51,59,0.0,5,12,Semi-Urban,Manager,44363,0 +23215,Male,56,High School,4,74,65,6,0,6.0,4,56,Rural,HR Executive,66676,0 +23216,Male,54,Masters,17,51,8,45,63,2.0,0,51,Rural,ML Engineer,59863,0 +23217,Female,27,High School,8,50,30,44,82,0.0,3,58,Rural,Data Analyst,77724,0 +23218,Male,37,Diploma,9,98,15,24,46,6.0,4,54,Rural,Software Engineer,91549,0 +23219,Male,58,Bachelors,14,8,90,5,55,8.0,6,5,Rural,HR Executive,128874,0 +23220,Female,26,Bachelors,0,46,73,15,77,0.0,7,80,Urban,Software Engineer,105357,0 +23221,Male,24,High School,5,20,27,46,98,9.0,6,1,Urban,Software Engineer,42600,0 +23222,Male,26,Bachelors,2,50,76,58,69,5.0,5,13,Semi-Urban,Manager,136400,0 +23223,Male,57,Diploma,0,48,99,77,75,3.0,7,9,Urban,Software Engineer,96637,0 +23224,Male,49,Bachelors,2,98,13,23,33,8.0,0,74,Urban,Data Analyst,114933,0 +23225,Male,42,PhD,14,9,15,74,77,0.0,1,81,Urban,ML Engineer,101438,0 +23226,Female,35,Bachelors,7,27,88,59,62,5.0,2,72,Urban,ML Engineer,81367,1 +23227,Male,27,Diploma,0,94,26,49,39,6.0,1,33,Rural,Software Engineer,98768,0 +23228,Male,41,High School,10,35,40,28,26,7.0,0,20,Semi-Urban,ML Engineer,98846,0 +23229,Male,29,Masters,10,95,81,13,17,7.0,5,37,Semi-Urban,Data Analyst,58725,0 +23230,Male,58,Bachelors,10,46,84,29,73,6.0,4,32,Urban,Software Engineer,118428,0 +23231,Male,49,Bachelors,17,9,95,64,91,9.0,3,99,Rural,Data Analyst,85827,1 +23232,Male,54,Bachelors,7,65,99,52,6,7.0,0,74,Urban,HR Executive,138153,1 +23233,Male,48,Diploma,19,72,87,87,22,6.0,2,18,Semi-Urban,Data Analyst,22934,1 +23234,Male,31,Masters,3,29,7,30,45,0.0,1,24,Urban,Manager,148136,0 +23235,Female,31,Masters,9,72,40,25,3,3.0,3,67,Urban,Software Engineer,121574,0 +23236,Male,59,Bachelors,8,37,0,7,36,6.0,0,86,Urban,Manager,125738,0 +23237,Male,25,Masters,1,36,31,3,97,7.0,7,30,Semi-Urban,Manager,144757,0 +23238,Female,44,Bachelors,14,85,33,91,34,8.0,2,17,Semi-Urban,Data Analyst,144240,0 +23239,Male,49,Diploma,16,47,91,90,48,2.0,2,71,Urban,ML Engineer,65242,1 +23240,Female,47,High School,7,64,1,13,23,3.0,1,19,Urban,Data Analyst,47487,0 +23241,Female,47,Bachelors,5,90,67,33,59,6.0,1,56,Semi-Urban,HR Executive,86825,1 +23242,Male,26,Bachelors,13,87,37,67,89,2.0,5,91,Semi-Urban,ML Engineer,85112,1 +23243,Male,33,High School,0,96,19,34,23,4.0,6,30,Urban,ML Engineer,50107,0 +23244,Other,55,PhD,1,7,22,49,95,6.0,6,51,Urban,Software Engineer,146553,0 +23245,Female,32,Masters,5,15,82,26,36,9.0,2,6,Semi-Urban,HR Executive,47451,0 +23246,Female,57,Bachelors,19,12,62,33,78,6.0,6,8,Urban,Data Analyst,114936,0 +23247,Male,57,Diploma,13,84,50,29,82,0.0,4,10,Urban,Manager,64144,0 +23248,Male,58,Masters,13,87,51,30,25,9.0,1,21,Urban,Data Analyst,108368,0 +23249,Female,57,Masters,13,5,8,55,75,0.0,1,3,Urban,Data Analyst,84828,0 +23250,Male,47,Bachelors,3,46,64,8,47,1.0,7,61,Semi-Urban,Data Analyst,48706,0 +23251,Other,42,High School,19,79,46,45,4,5.0,7,0,Urban,Data Analyst,57352,0 +23252,Male,47,Bachelors,1,78,75,96,23,5.0,6,86,Semi-Urban,Manager,36374,1 +23253,Female,41,Diploma,7,17,80,67,41,9.0,2,40,Urban,Manager,54521,0 +23254,Male,34,Diploma,12,27,84,9,62,2.0,3,14,Urban,Manager,113996,0 +23255,Male,47,Bachelors,11,32,24,7,60,8.0,1,65,Urban,Data Analyst,105585,0 +23256,Female,43,Diploma,15,92,74,59,0,9.0,5,91,Urban,HR Executive,71638,1 +23257,Male,31,Masters,3,59,2,17,93,4.0,2,15,Rural,Manager,29190,0 +23258,Male,50,Diploma,12,27,45,39,37,6.0,0,12,Rural,HR Executive,132414,0 +23259,Male,49,Bachelors,15,76,16,64,57,1.0,0,33,Semi-Urban,ML Engineer,24332,0 +23260,Female,37,Masters,2,0,6,86,53,0.0,3,71,Urban,HR Executive,87376,0 +23261,Other,29,Masters,14,53,52,22,35,5.0,1,64,Urban,Data Analyst,34079,0 +23262,Male,44,Bachelors,12,34,26,52,66,3.0,5,92,Semi-Urban,Data Analyst,74220,0 +23263,Male,47,High School,8,18,62,69,20,7.0,6,95,Urban,Software Engineer,102686,1 +23264,Male,26,High School,15,18,63,16,58,4.0,0,47,Urban,Manager,61948,0 +23265,Female,29,Diploma,11,90,66,83,65,5.0,5,89,Urban,Data Analyst,82072,1 +23266,Male,41,Diploma,13,97,68,3,62,1.0,0,94,Semi-Urban,Data Analyst,71621,1 +23267,Male,39,Bachelors,1,90,84,7,68,2.0,3,69,Urban,Software Engineer,83949,1 +23268,Male,25,Masters,16,54,27,97,44,7.0,6,74,Urban,ML Engineer,21458,1 +23269,Male,47,Bachelors,5,14,13,41,51,0.0,3,61,Urban,Manager,53827,0 +23270,Female,54,Bachelors,5,18,53,67,23,4.0,7,96,Urban,Data Analyst,143305,0 +23271,Male,35,Bachelors,17,63,15,56,82,8.0,5,22,Urban,ML Engineer,38210,0 +23272,Male,21,Bachelors,0,36,59,17,15,9.0,3,91,Semi-Urban,Manager,131350,0 +23273,Male,27,Bachelors,17,41,75,83,47,0.0,0,82,Rural,ML Engineer,31766,1 +23274,Female,38,Bachelors,11,2,23,21,64,7.0,2,17,Urban,Data Analyst,82765,0 +23275,Male,47,Bachelors,18,23,13,53,90,0.0,3,40,Urban,Data Analyst,73862,0 +23276,Male,44,High School,1,24,38,37,32,5.0,0,24,Semi-Urban,ML Engineer,41504,0 +23277,Male,43,Bachelors,14,6,70,11,49,8.0,5,92,Rural,HR Executive,80583,0 +23278,Female,52,Bachelors,0,40,97,37,12,0.0,1,72,Rural,ML Engineer,120041,1 +23279,Male,51,Bachelors,16,41,7,76,82,2.0,1,37,Semi-Urban,Manager,91969,0 +23280,Male,25,Diploma,16,11,58,12,50,3.0,2,51,Urban,HR Executive,115300,0 +23281,Male,34,High School,7,32,96,14,46,4.0,2,44,Urban,ML Engineer,131839,0 +23282,Male,38,Bachelors,1,97,36,65,64,6.0,7,64,Urban,Data Analyst,102814,1 +23283,Other,37,Diploma,7,56,58,16,65,9.0,7,28,Semi-Urban,Manager,124192,0 +23284,Male,32,Bachelors,17,28,30,2,53,2.0,5,33,Urban,HR Executive,94584,0 +23285,Female,26,High School,10,7,55,55,83,2.0,6,85,Semi-Urban,ML Engineer,90063,0 +23286,Male,59,Diploma,12,83,46,81,33,9.0,2,33,Urban,ML Engineer,114185,1 +23287,Male,50,Bachelors,8,45,57,67,38,4.0,0,96,Urban,Manager,93642,1 +23288,Male,55,Bachelors,14,1,59,99,89,2.0,1,39,Urban,Software Engineer,64701,0 +23289,Female,50,High School,13,79,66,44,13,8.0,0,86,Semi-Urban,Manager,125959,1 +23290,Male,37,Bachelors,19,15,8,78,26,6.0,6,16,Rural,Software Engineer,143803,0 +23291,Female,47,Diploma,14,88,81,35,2,5.0,2,37,Semi-Urban,Data Analyst,31364,1 +23292,Male,39,Masters,2,42,75,63,36,3.0,0,15,Urban,ML Engineer,106543,0 +23293,Male,32,Bachelors,7,15,26,20,0,7.0,6,54,Urban,HR Executive,54334,0 +23294,Female,41,Bachelors,17,42,19,0,31,9.0,1,12,Urban,Manager,87027,0 +23295,Female,41,Bachelors,16,63,29,37,15,3.0,4,5,Urban,ML Engineer,93065,0 +23296,Male,27,High School,2,30,7,50,74,9.0,2,11,Rural,Manager,140942,0 +23297,Female,50,High School,1,50,95,79,54,7.0,7,54,Semi-Urban,Software Engineer,48919,1 +23298,Male,51,Diploma,17,58,11,2,95,7.0,0,28,Urban,Data Analyst,115397,0 +23299,Male,48,Bachelors,14,59,25,15,78,5.0,3,22,Urban,Software Engineer,83736,0 +23300,Male,23,PhD,17,10,54,70,51,2.0,5,43,Urban,Software Engineer,92641,0 +23301,Male,28,High School,1,36,0,17,19,4.0,7,10,Rural,Data Analyst,111117,0 +23302,Male,36,Bachelors,19,44,14,28,16,7.0,2,1,Urban,ML Engineer,120184,0 +23303,Male,43,Bachelors,3,11,62,86,76,6.0,3,4,Urban,Data Analyst,80753,0 +23304,Other,37,Masters,17,15,25,39,73,4.0,0,26,Semi-Urban,HR Executive,122639,0 +23305,Female,49,Diploma,17,23,11,37,61,5.0,0,34,Urban,HR Executive,25193,0 +23306,Male,58,Masters,8,49,72,66,25,5.0,6,56,Urban,Data Analyst,138812,1 +23307,Other,48,Diploma,9,86,77,61,27,6.0,4,47,Rural,HR Executive,85435,1 +23308,Male,30,Masters,3,31,11,49,91,4.0,7,54,Semi-Urban,Software Engineer,105685,0 +23309,Male,25,PhD,7,50,24,26,25,0.0,5,26,Rural,Manager,92469,0 +23310,Female,50,PhD,0,15,97,16,19,3.0,1,34,Urban,Manager,126741,0 +23311,Male,59,PhD,14,46,68,25,90,3.0,3,14,Rural,Manager,123307,0 +23312,Female,57,PhD,19,12,7,33,80,6.0,4,55,Urban,ML Engineer,77770,0 +23313,Male,31,Bachelors,10,81,27,28,97,8.0,2,95,Semi-Urban,HR Executive,131590,0 +23314,Male,58,Bachelors,17,98,0,82,27,7.0,0,73,Semi-Urban,Manager,52515,1 +23315,Male,59,Diploma,3,1,78,91,79,7.0,1,3,Semi-Urban,Data Analyst,106744,0 +23316,Female,46,Masters,12,16,2,80,7,7.0,2,26,Rural,Data Analyst,78680,0 +23317,Female,53,Masters,17,27,58,77,34,8.0,1,54,Semi-Urban,ML Engineer,64814,0 +23318,Female,52,Diploma,19,49,98,8,53,1.0,4,37,Urban,Software Engineer,137268,0 +23319,Male,39,Bachelors,10,37,99,18,84,9.0,6,5,Urban,Manager,56324,0 +23320,Male,57,High School,19,6,9,48,27,9.0,7,79,Urban,Manager,103949,0 +23321,Female,30,High School,14,15,9,46,65,5.0,3,67,Semi-Urban,Manager,111660,0 +23322,Male,35,High School,7,33,10,62,96,1.0,6,48,Urban,Software Engineer,115229,0 +23323,Male,59,High School,3,24,55,3,49,7.0,0,80,Rural,Software Engineer,34248,0 +23324,Female,39,PhD,11,95,44,73,22,5.0,2,68,Urban,Software Engineer,47581,1 +23325,Male,38,Masters,5,82,74,13,41,9.0,1,14,Rural,Software Engineer,41689,0 +23326,Male,31,Bachelors,2,95,28,50,86,1.0,4,0,Urban,HR Executive,91897,0 +23327,Female,55,Masters,5,60,61,3,35,1.0,4,28,Semi-Urban,Software Engineer,68835,0 +23328,Female,26,Bachelors,1,28,47,15,17,1.0,2,53,Urban,Software Engineer,108971,0 +23329,Female,47,Diploma,7,34,56,65,33,2.0,1,45,Urban,Data Analyst,105441,0 +23330,Male,39,Diploma,2,69,50,85,34,1.0,6,37,Urban,HR Executive,117770,1 +23331,Male,36,Bachelors,16,0,34,0,84,1.0,6,60,Semi-Urban,Data Analyst,100286,0 +23332,Female,55,Diploma,15,69,43,64,52,7.0,0,8,Rural,ML Engineer,147908,0 +23333,Female,46,Diploma,13,63,3,7,43,7.0,1,70,Urban,Software Engineer,100380,0 +23334,Male,48,Diploma,6,44,22,72,68,8.0,6,20,Urban,HR Executive,126465,0 +23335,Other,55,Bachelors,6,26,94,94,77,7.0,4,63,Semi-Urban,Manager,63920,1 +23336,Other,52,Masters,0,21,0,22,2,8.0,0,32,Urban,ML Engineer,87425,0 +23337,Male,30,High School,12,8,94,93,75,3.0,1,97,Urban,Data Analyst,79802,1 +23338,Female,43,Masters,1,23,67,17,2,4.0,4,68,Urban,Software Engineer,21895,0 +23339,Male,44,Masters,14,8,52,31,6,5.0,7,19,Urban,Data Analyst,99286,0 +23340,Male,48,Masters,16,94,4,77,66,2.0,0,7,Rural,Software Engineer,136101,0 +23341,Male,44,High School,1,54,32,17,88,4.0,4,30,Semi-Urban,Manager,108062,0 +23342,Male,37,Bachelors,0,88,51,59,85,1.0,7,21,Semi-Urban,Manager,63830,0 +23343,Female,56,Diploma,2,33,90,55,27,5.0,2,36,Semi-Urban,Manager,99777,0 +23344,Female,28,Masters,17,49,45,46,8,9.0,1,63,Urban,Manager,52305,0 +23345,Female,55,High School,2,17,51,84,38,0.0,7,40,Urban,Manager,105852,0 +23346,Male,30,Bachelors,14,63,55,49,76,7.0,4,75,Semi-Urban,HR Executive,133884,1 +23347,Male,34,Bachelors,8,35,54,63,81,9.0,5,40,Urban,ML Engineer,31890,0 +23348,Male,53,Diploma,18,80,82,62,40,4.0,6,20,Rural,ML Engineer,49871,1 +23349,Male,30,PhD,12,44,57,6,12,7.0,5,42,Urban,HR Executive,135485,0 +23350,Male,49,Bachelors,9,50,95,18,91,6.0,2,73,Rural,Software Engineer,108685,1 +23351,Male,41,Diploma,11,82,58,83,24,2.0,5,92,Urban,Manager,42524,1 +23352,Male,59,Diploma,0,50,46,57,9,8.0,3,87,Rural,Data Analyst,63264,1 +23353,Male,49,Bachelors,12,14,54,5,76,4.0,7,95,Urban,HR Executive,58143,0 +23354,Male,52,Masters,5,13,72,86,16,0.0,3,58,Urban,Data Analyst,105923,0 +23355,Male,58,Bachelors,17,65,60,12,23,4.0,3,80,Urban,Software Engineer,112783,0 +23356,Female,58,PhD,1,1,29,73,42,1.0,3,5,Urban,Software Engineer,74180,0 +23357,Male,56,Masters,1,8,59,5,81,9.0,1,96,Semi-Urban,Manager,137155,0 +23358,Male,29,Bachelors,1,34,84,77,7,8.0,1,66,Urban,ML Engineer,49618,1 +23359,Female,54,Masters,4,73,29,51,81,5.0,4,26,Urban,Manager,93801,0 +23360,Other,49,Bachelors,12,69,86,68,47,6.0,1,28,Semi-Urban,Data Analyst,116052,1 +23361,Female,59,Bachelors,2,53,68,90,45,6.0,4,75,Urban,Manager,112701,1 +23362,Male,35,Bachelors,1,51,65,61,40,3.0,3,13,Semi-Urban,HR Executive,55060,0 +23363,Male,43,High School,16,71,73,33,85,0.0,2,88,Urban,HR Executive,135998,1 +23364,Other,40,Diploma,12,19,18,2,45,7.0,5,50,Urban,HR Executive,113702,0 +23365,Female,54,Bachelors,1,75,42,84,93,6.0,6,7,Urban,Data Analyst,126479,0 +23366,Male,33,Diploma,18,53,95,13,69,8.0,2,80,Rural,Software Engineer,40851,1 +23367,Male,27,Diploma,6,95,57,50,6,3.0,5,91,Urban,Manager,146098,1 +23368,Male,23,Masters,11,42,24,48,15,6.0,1,55,Urban,Data Analyst,111355,0 +23369,Male,44,PhD,18,33,3,38,99,5.0,0,78,Semi-Urban,HR Executive,84807,0 +23370,Female,25,Bachelors,9,36,24,40,45,3.0,1,17,Urban,ML Engineer,99137,0 +23371,Male,29,High School,9,85,6,15,28,6.0,7,83,Rural,ML Engineer,117038,0 +23372,Other,49,Bachelors,1,78,7,99,18,9.0,5,0,Urban,Software Engineer,63560,0 +23373,Male,56,Masters,15,71,16,82,60,3.0,2,70,Urban,ML Engineer,147153,1 +23374,Female,50,Masters,4,30,50,78,55,1.0,5,80,Semi-Urban,Data Analyst,70476,0 +23375,Male,28,Bachelors,12,61,75,90,63,0.0,6,64,Urban,Data Analyst,84135,1 +23376,Male,35,Diploma,6,75,85,20,15,7.0,3,75,Semi-Urban,Data Analyst,20569,1 +23377,Male,47,Bachelors,10,86,21,49,69,2.0,3,40,Urban,Data Analyst,57939,0 +23378,Female,43,Bachelors,13,16,10,27,82,0.0,7,56,Rural,Data Analyst,66763,0 +23379,Male,42,Bachelors,2,48,75,45,38,5.0,4,13,Urban,HR Executive,80128,0 +23380,Male,21,PhD,12,21,46,92,82,8.0,5,69,Urban,HR Executive,80806,0 +23381,Female,21,Masters,18,9,50,22,25,1.0,2,9,Rural,HR Executive,128334,0 +23382,Male,52,Diploma,19,76,52,26,17,1.0,7,34,Urban,HR Executive,133321,0 +23383,Female,53,Bachelors,6,43,8,2,33,1.0,0,70,Urban,Data Analyst,29006,0 +23384,Female,27,Bachelors,18,4,54,83,89,0.0,4,0,Urban,ML Engineer,138787,0 +23385,Female,31,High School,15,52,95,72,3,7.0,5,75,Urban,Manager,136147,1 +23386,Male,30,PhD,12,26,11,50,67,6.0,5,62,Urban,Data Analyst,51292,0 +23387,Male,53,High School,19,80,83,48,65,6.0,6,39,Semi-Urban,ML Engineer,110605,1 +23388,Other,38,Bachelors,13,87,31,10,92,1.0,7,5,Urban,ML Engineer,79052,0 +23389,Male,27,Bachelors,19,49,92,34,82,6.0,4,23,Rural,HR Executive,143322,0 +23390,Male,34,Bachelors,2,59,52,60,56,7.0,7,87,Urban,Manager,89849,1 +23391,Female,28,Diploma,11,13,17,84,48,0.0,5,25,Semi-Urban,ML Engineer,89840,0 +23392,Male,21,High School,0,58,63,43,32,5.0,1,15,Urban,Software Engineer,56499,0 +23393,Female,52,Masters,16,62,47,80,46,5.0,0,18,Semi-Urban,Manager,142667,0 +23394,Female,45,Masters,10,21,57,69,72,1.0,5,35,Urban,ML Engineer,46436,0 +23395,Female,49,Bachelors,15,85,9,3,40,2.0,3,4,Urban,Software Engineer,53039,0 +23396,Male,31,Masters,17,40,18,91,79,0.0,5,72,Urban,Manager,45762,0 +23397,Male,26,Diploma,0,24,69,10,90,8.0,2,24,Semi-Urban,Software Engineer,138632,0 +23398,Male,56,Masters,18,96,29,10,6,9.0,0,51,Urban,ML Engineer,80570,0 +23399,Male,50,Diploma,6,33,67,10,58,5.0,4,46,Rural,Manager,148539,0 +23400,Male,48,Bachelors,2,22,73,48,26,5.0,4,61,Urban,Software Engineer,25574,0 +23401,Male,34,High School,14,73,21,75,91,0.0,3,69,Urban,ML Engineer,20682,1 +23402,Male,56,Masters,4,72,55,43,80,9.0,4,52,Urban,Data Analyst,23191,0 +23403,Male,44,Diploma,3,89,21,28,16,8.0,4,4,Urban,ML Engineer,31524,0 +23404,Female,59,Masters,13,62,88,2,39,6.0,1,38,Urban,Manager,121355,0 +23405,Male,29,Masters,19,46,31,52,38,6.0,4,17,Urban,Manager,57927,0 +23406,Male,52,Bachelors,19,63,55,23,35,6.0,6,45,Semi-Urban,Software Engineer,120116,0 +23407,Female,59,Masters,4,12,14,95,20,1.0,7,82,Rural,ML Engineer,141456,0 +23408,Female,42,High School,1,15,23,81,31,7.0,3,24,Urban,Manager,141473,0 +23409,Male,29,High School,7,68,10,8,89,8.0,4,44,Urban,HR Executive,141124,0 +23410,Female,40,Bachelors,18,69,38,33,88,3.0,3,63,Rural,Manager,86864,0 +23411,Male,38,Diploma,13,30,17,49,45,5.0,2,65,Semi-Urban,HR Executive,105980,0 +23412,Male,31,Diploma,18,73,55,95,37,2.0,0,0,Semi-Urban,Manager,117133,0 +23413,Female,53,High School,12,20,73,63,83,6.0,4,5,Urban,ML Engineer,63592,0 +23414,Female,51,Masters,5,44,73,69,59,3.0,5,48,Urban,Software Engineer,78266,0 +23415,Male,48,High School,9,79,56,95,59,8.0,3,86,Urban,Data Analyst,25529,1 +23416,Female,56,Diploma,2,36,85,47,76,2.0,5,51,Urban,Software Engineer,87364,0 +23417,Female,56,Bachelors,7,77,82,84,31,9.0,6,79,Rural,Manager,75245,1 +23418,Other,22,Bachelors,12,33,32,91,89,4.0,1,81,Semi-Urban,Manager,126615,0 +23419,Male,22,Bachelors,11,17,78,63,30,7.0,4,67,Rural,ML Engineer,68601,0 +23420,Male,37,Bachelors,12,12,37,98,31,0.0,7,79,Urban,Data Analyst,28270,0 +23421,Male,33,Bachelors,5,39,65,4,55,5.0,7,96,Semi-Urban,Software Engineer,113204,0 +23422,Male,42,Bachelors,8,68,80,95,69,8.0,5,29,Semi-Urban,Manager,113255,1 +23423,Male,43,Diploma,12,85,42,12,10,7.0,0,98,Urban,Software Engineer,104541,1 +23424,Female,53,High School,4,96,44,71,68,8.0,3,36,Urban,Software Engineer,40864,1 +23425,Female,21,Masters,15,93,8,12,86,5.0,4,39,Urban,HR Executive,65545,0 +23426,Female,56,Masters,1,14,65,29,56,2.0,0,76,Urban,Software Engineer,123910,0 +23427,Male,59,PhD,1,68,46,8,56,0.0,1,55,Semi-Urban,HR Executive,119660,0 +23428,Male,56,Diploma,10,53,78,55,97,4.0,3,7,Urban,HR Executive,33861,0 +23429,Male,55,Masters,0,63,56,10,63,7.0,6,22,Semi-Urban,Data Analyst,36719,0 +23430,Male,33,PhD,15,70,43,32,71,0.0,2,72,Urban,ML Engineer,143757,0 +23431,Female,42,Masters,15,40,60,36,8,0.0,2,56,Urban,HR Executive,74425,0 +23432,Male,52,High School,1,27,68,62,30,7.0,1,25,Urban,Software Engineer,126558,0 +23433,Female,43,Diploma,17,96,54,69,7,1.0,7,18,Rural,HR Executive,64732,0 +23434,Male,23,Bachelors,2,71,22,58,47,7.0,3,92,Urban,Data Analyst,123192,1 +23435,Male,31,Diploma,0,72,48,71,47,0.0,2,21,Rural,Manager,123490,0 +23436,Female,49,Bachelors,11,71,55,74,70,1.0,4,61,Urban,ML Engineer,49996,1 +23437,Male,46,High School,8,21,43,86,98,1.0,3,30,Urban,Software Engineer,143560,0 +23438,Male,33,Diploma,11,94,78,21,78,6.0,4,42,Semi-Urban,HR Executive,76858,1 +23439,Male,58,High School,15,70,64,27,95,5.0,4,92,Rural,Data Analyst,113915,1 +23440,Female,36,High School,18,50,58,17,65,0.0,3,47,Urban,ML Engineer,41906,0 +23441,Other,23,Masters,12,76,1,80,7,5.0,5,66,Semi-Urban,Manager,30169,0 +23442,Female,41,Bachelors,6,54,98,10,70,4.0,3,39,Semi-Urban,Manager,39826,0 +23443,Other,26,PhD,4,7,34,39,21,6.0,0,63,Urban,Software Engineer,67769,0 +23444,Female,57,Bachelors,13,95,72,58,82,5.0,5,49,Semi-Urban,HR Executive,106933,1 +23445,Female,35,Bachelors,18,0,15,63,55,3.0,4,7,Semi-Urban,Data Analyst,125112,0 +23446,Male,45,Bachelors,2,15,42,54,70,1.0,4,22,Urban,ML Engineer,100599,0 +23447,Male,49,Bachelors,10,49,82,77,43,2.0,0,15,Semi-Urban,Data Analyst,36415,0 +23448,Male,51,Bachelors,8,4,80,28,33,8.0,0,57,Urban,ML Engineer,44195,0 +23449,Female,33,Bachelors,9,36,93,67,96,4.0,1,60,Urban,ML Engineer,101961,1 +23450,Male,59,Diploma,3,12,70,19,37,3.0,3,2,Rural,HR Executive,50310,0 +23451,Male,43,Masters,13,74,40,43,94,5.0,5,54,Semi-Urban,Manager,90174,0 +23452,Female,49,High School,18,62,48,25,13,0.0,0,79,Urban,Software Engineer,86208,0 +23453,Male,50,Bachelors,15,70,30,55,42,7.0,3,44,Urban,ML Engineer,96946,0 +23454,Other,50,Bachelors,7,45,70,65,52,7.0,3,26,Semi-Urban,Software Engineer,34721,0 +23455,Female,58,Bachelors,9,90,0,51,22,1.0,3,79,Urban,HR Executive,101093,0 +23456,Male,55,Masters,0,62,50,74,45,7.0,5,95,Urban,HR Executive,83737,1 +23457,Female,33,Masters,19,2,88,59,85,6.0,2,35,Semi-Urban,HR Executive,148950,0 +23458,Female,26,High School,11,70,55,33,47,0.0,7,73,Urban,HR Executive,29222,0 +23459,Male,46,Bachelors,16,69,89,48,39,7.0,4,30,Urban,Data Analyst,117708,1 +23460,Female,32,Bachelors,8,84,87,32,54,6.0,3,10,Urban,HR Executive,111889,0 +23461,Female,37,High School,3,42,94,8,58,4.0,5,2,Urban,Manager,64033,0 +23462,Male,40,Bachelors,11,66,84,50,98,3.0,6,85,Urban,ML Engineer,52392,1 +23463,Male,54,Masters,6,76,99,86,12,2.0,2,62,Urban,Manager,58832,1 +23464,Male,36,Diploma,1,12,27,31,65,9.0,1,14,Urban,ML Engineer,115045,0 +23465,Male,40,High School,14,99,13,87,81,9.0,3,40,Semi-Urban,Data Analyst,46722,1 +23466,Male,56,Diploma,15,9,59,64,48,4.0,2,87,Rural,ML Engineer,123934,0 +23467,Female,34,Diploma,13,99,35,44,23,8.0,4,31,Semi-Urban,Software Engineer,69435,0 +23468,Male,36,PhD,9,82,26,21,22,7.0,1,0,Urban,Manager,135718,0 +23469,Female,59,Bachelors,3,96,85,40,46,5.0,4,65,Urban,Data Analyst,80715,1 +23470,Male,26,Bachelors,1,69,62,24,29,7.0,2,90,Urban,Manager,93947,1 +23471,Male,59,Bachelors,10,0,3,92,99,2.0,0,57,Rural,Manager,90714,0 +23472,Female,43,Bachelors,17,47,40,12,42,8.0,0,41,Urban,ML Engineer,49495,0 +23473,Female,23,Bachelors,2,71,65,21,95,4.0,5,21,Urban,ML Engineer,140311,0 +23474,Male,46,Bachelors,12,34,2,74,60,6.0,4,16,Urban,Manager,140611,0 +23475,Male,32,Masters,2,9,90,3,40,5.0,7,43,Urban,Software Engineer,44694,0 +23476,Female,24,Bachelors,1,57,3,89,30,1.0,1,20,Urban,HR Executive,68194,0 +23477,Male,27,PhD,10,76,12,39,22,6.0,6,80,Semi-Urban,Manager,87755,0 +23478,Male,45,Bachelors,2,46,9,73,37,5.0,4,29,Urban,Manager,21821,0 +23479,Male,21,Masters,14,16,14,8,80,1.0,4,48,Urban,Data Analyst,55064,0 +23480,Female,28,High School,19,51,21,74,78,3.0,2,57,Urban,HR Executive,128979,0 +23481,Male,54,High School,17,70,86,91,60,7.0,5,79,Rural,HR Executive,52240,1 +23482,Male,24,High School,10,18,60,50,64,4.0,5,45,Urban,HR Executive,68916,0 +23483,Male,37,Masters,7,19,16,22,79,1.0,1,45,Urban,HR Executive,23525,0 +23484,Female,50,Bachelors,9,90,69,45,7,5.0,3,88,Urban,Software Engineer,78322,1 +23485,Male,39,Bachelors,4,89,24,90,64,2.0,1,73,Rural,Manager,101711,1 +23486,Male,25,High School,13,34,98,91,6,3.0,4,62,Semi-Urban,Data Analyst,100769,1 +23487,Male,29,High School,14,33,18,95,27,9.0,3,50,Urban,Manager,84014,0 +23488,Male,39,Bachelors,4,30,98,48,55,6.0,4,60,Urban,Data Analyst,88766,1 +23489,Female,50,Bachelors,15,11,45,80,61,4.0,4,15,Rural,Software Engineer,123476,0 +23490,Female,21,Masters,8,70,72,58,30,2.0,3,38,Semi-Urban,ML Engineer,43588,0 +23491,Female,42,Bachelors,15,72,46,12,71,1.0,2,76,Urban,Manager,107776,0 +23492,Female,24,Diploma,8,88,27,27,56,1.0,4,20,Rural,Software Engineer,78012,0 +23493,Female,56,High School,7,76,82,82,73,7.0,6,5,Urban,Data Analyst,41724,1 +23494,Male,53,Masters,14,32,91,92,74,5.0,0,48,Urban,ML Engineer,144147,1 +23495,Other,37,Bachelors,4,32,91,5,73,5.0,6,24,Urban,HR Executive,69861,0 +23496,Male,55,Bachelors,12,30,72,6,75,1.0,0,30,Urban,Data Analyst,113463,0 +23497,Female,50,High School,17,40,95,41,39,9.0,7,13,Urban,Software Engineer,48006,0 +23498,Male,28,Bachelors,15,16,84,69,25,7.0,1,62,Semi-Urban,ML Engineer,98067,0 +23499,Female,49,Bachelors,17,16,77,22,70,8.0,5,43,Rural,ML Engineer,99340,0 +23500,Male,24,High School,8,23,81,58,45,1.0,0,80,Urban,Manager,89038,1 +23501,Female,31,Bachelors,18,5,30,74,43,4.0,3,7,Rural,Data Analyst,81400,0 +23502,Female,38,Masters,13,55,22,9,97,9.0,7,97,Urban,HR Executive,24688,0 +23503,Female,52,Masters,6,24,7,30,48,4.0,6,90,Urban,HR Executive,106898,0 +23504,Female,35,Bachelors,18,18,87,49,2,4.0,7,85,Semi-Urban,HR Executive,76317,0 +23505,Male,57,Masters,13,64,12,82,26,6.0,2,26,Urban,Data Analyst,23685,0 +23506,Male,28,Bachelors,19,7,69,83,81,4.0,5,93,Urban,ML Engineer,88990,1 +23507,Other,29,Bachelors,6,33,21,62,70,1.0,3,11,Urban,HR Executive,75156,0 +23508,Female,57,High School,5,45,39,87,3,9.0,1,67,Semi-Urban,Software Engineer,40752,0 +23509,Male,23,Diploma,17,25,93,2,45,7.0,7,67,Urban,HR Executive,149225,0 +23510,Male,52,Bachelors,0,79,38,96,70,4.0,6,40,Urban,HR Executive,133734,1 +23511,Male,35,PhD,3,75,11,21,30,6.0,4,41,Urban,ML Engineer,136396,0 +23512,Male,42,Bachelors,6,80,62,30,11,3.0,2,39,Urban,Data Analyst,116726,0 +23513,Male,26,Bachelors,12,76,84,41,92,8.0,1,38,Urban,Software Engineer,20614,1 +23514,Male,31,Bachelors,14,98,95,41,91,6.0,1,80,Urban,Software Engineer,97584,1 +23515,Male,41,Masters,15,46,2,33,35,5.0,5,18,Urban,Manager,57725,0 +23516,Male,37,Bachelors,16,37,63,81,28,6.0,4,21,Semi-Urban,ML Engineer,128862,0 +23517,Male,35,Bachelors,5,65,28,31,62,8.0,1,51,Urban,ML Engineer,122982,0 +23518,Male,40,Bachelors,17,83,54,43,7,2.0,0,74,Urban,Data Analyst,74940,1 +23519,Male,24,Bachelors,18,16,11,84,33,9.0,6,46,Urban,Software Engineer,62789,0 +23520,Female,56,Bachelors,12,48,92,15,47,4.0,0,45,Rural,Software Engineer,95400,0 +23521,Male,24,PhD,7,78,76,65,9,5.0,0,4,Rural,Data Analyst,53117,0 +23522,Female,21,Bachelors,14,46,42,69,67,3.0,1,25,Semi-Urban,HR Executive,110668,0 +23523,Female,34,Diploma,16,52,58,67,71,6.0,3,17,Urban,Data Analyst,111239,0 +23524,Male,50,Bachelors,12,30,28,89,3,8.0,6,98,Rural,Data Analyst,54185,1 +23525,Male,26,Bachelors,8,16,63,52,54,3.0,7,41,Semi-Urban,HR Executive,67846,0 +23526,Male,35,High School,19,92,69,7,37,8.0,0,9,Semi-Urban,HR Executive,105482,0 +23527,Male,23,Bachelors,9,84,9,52,80,5.0,3,52,Urban,ML Engineer,111348,0 +23528,Male,51,Bachelors,16,48,88,20,57,1.0,2,15,Rural,Data Analyst,56747,0 +23529,Male,53,Diploma,17,38,35,35,48,6.0,0,61,Urban,Data Analyst,73131,0 +23530,Female,24,Masters,3,66,17,73,87,6.0,2,88,Rural,Software Engineer,142704,1 +23531,Male,31,Bachelors,17,8,71,19,95,5.0,7,29,Urban,Manager,52214,0 +23532,Other,43,Bachelors,10,35,30,45,88,3.0,1,88,Urban,Software Engineer,38030,0 +23533,Male,27,High School,10,15,43,61,20,0.0,4,44,Rural,Data Analyst,31823,0 +23534,Female,53,PhD,9,18,62,99,76,4.0,6,69,Urban,Software Engineer,62527,1 +23535,Male,30,High School,2,92,92,78,18,9.0,4,34,Rural,Software Engineer,27312,1 +23536,Male,58,Masters,2,90,86,18,21,0.0,4,56,Urban,Software Engineer,68086,1 +23537,Male,39,PhD,2,51,79,86,73,6.0,1,80,Urban,Software Engineer,148455,1 +23538,Other,48,High School,17,87,22,60,35,7.0,7,2,Semi-Urban,Software Engineer,91053,0 +23539,Male,43,Masters,10,50,93,25,65,0.0,4,42,Urban,Data Analyst,30511,0 +23540,Female,43,High School,8,24,92,71,28,8.0,5,85,Rural,ML Engineer,105280,1 +23541,Female,36,Masters,11,76,45,24,76,0.0,5,52,Urban,ML Engineer,57280,0 +23542,Female,35,Diploma,3,10,83,64,12,1.0,6,6,Rural,Manager,109589,0 +23543,Male,31,PhD,10,83,6,49,27,8.0,5,0,Urban,Software Engineer,84624,0 +23544,Other,54,High School,11,62,53,98,4,4.0,0,94,Urban,Manager,101705,1 +23545,Female,55,High School,0,89,30,54,73,2.0,1,84,Rural,Data Analyst,70069,1 +23546,Male,34,High School,5,9,10,0,99,9.0,2,68,Urban,HR Executive,94313,0 +23547,Male,45,Masters,15,95,28,84,58,7.0,0,47,Urban,Software Engineer,60271,1 +23548,Other,43,High School,17,31,77,87,98,4.0,3,22,Urban,Data Analyst,31160,0 +23549,Other,41,Masters,12,31,82,5,1,0.0,6,75,Rural,Data Analyst,133331,0 +23550,Male,54,PhD,3,38,64,22,9,3.0,2,14,Urban,Data Analyst,112818,0 +23551,Female,52,Bachelors,10,77,44,11,25,9.0,5,72,Semi-Urban,Manager,83543,0 +23552,Male,41,Diploma,8,82,58,72,27,0.0,5,5,Urban,Data Analyst,37421,0 +23553,Male,48,Bachelors,14,72,45,75,8,9.0,0,66,Rural,Manager,36887,1 +23554,Male,44,Bachelors,7,15,93,57,92,7.0,3,95,Semi-Urban,Data Analyst,146412,1 +23555,Male,53,Bachelors,16,7,84,98,38,5.0,0,25,Semi-Urban,ML Engineer,124870,0 +23556,Female,57,Bachelors,17,13,17,73,90,5.0,2,93,Urban,Data Analyst,100081,0 +23557,Male,34,Bachelors,3,94,12,9,93,0.0,4,54,Semi-Urban,ML Engineer,75878,0 +23558,Male,50,Masters,9,73,93,93,42,5.0,0,82,Urban,Data Analyst,55879,1 +23559,Male,38,Bachelors,18,61,85,28,50,3.0,0,32,Urban,HR Executive,124287,0 +23560,Male,29,Bachelors,7,71,83,97,36,7.0,7,96,Rural,Software Engineer,68332,1 +23561,Other,41,Masters,5,9,26,96,92,7.0,1,30,Urban,ML Engineer,135521,0 +23562,Female,48,Bachelors,7,49,73,57,60,1.0,7,73,Rural,HR Executive,140461,1 +23563,Male,41,Bachelors,2,33,25,28,30,7.0,2,21,Urban,Data Analyst,43561,0 +23564,Female,58,Bachelors,3,15,43,43,70,5.0,4,58,Urban,Manager,100836,0 +23565,Male,25,Bachelors,7,82,10,80,45,4.0,3,89,Urban,HR Executive,25818,1 +23566,Female,40,Bachelors,9,4,56,98,15,2.0,2,94,Semi-Urban,Software Engineer,92378,1 +23567,Other,46,Diploma,2,4,4,83,17,6.0,4,77,Semi-Urban,Manager,38215,0 +23568,Male,42,Masters,4,4,84,63,47,3.0,0,76,Urban,Software Engineer,92631,0 +23569,Female,30,Bachelors,9,62,82,53,69,1.0,2,51,Urban,Data Analyst,25958,1 +23570,Male,57,Bachelors,12,58,13,13,46,0.0,2,58,Urban,Data Analyst,91542,0 +23571,Male,57,Bachelors,0,1,25,11,14,9.0,4,94,Urban,ML Engineer,131419,0 +23572,Male,29,Diploma,13,66,63,48,22,0.0,1,23,Urban,HR Executive,116460,0 +23573,Other,46,Bachelors,8,97,38,25,35,9.0,6,79,Semi-Urban,Software Engineer,133679,0 +23574,Male,36,Bachelors,18,98,88,99,63,8.0,3,0,Urban,Software Engineer,96296,1 +23575,Female,26,PhD,9,36,83,2,56,5.0,3,89,Semi-Urban,Manager,140762,0 +23576,Female,39,High School,14,6,58,55,49,7.0,5,89,Urban,HR Executive,119080,0 +23577,Male,42,PhD,2,32,33,84,98,5.0,2,9,Urban,Data Analyst,102670,0 +23578,Male,25,Masters,6,65,15,61,85,3.0,6,70,Urban,Manager,23380,0 +23579,Female,36,Bachelors,6,92,85,86,31,5.0,0,40,Urban,HR Executive,143899,1 +23580,Male,26,Masters,15,40,18,24,28,4.0,1,19,Semi-Urban,HR Executive,28568,0 +23581,Male,30,Diploma,5,5,3,84,44,3.0,0,61,Semi-Urban,Software Engineer,37888,0 +23582,Other,54,Bachelors,12,80,46,23,49,2.0,3,24,Rural,Manager,61928,0 +23583,Female,39,Bachelors,10,2,53,12,76,8.0,1,39,Urban,Software Engineer,97951,0 +23584,Male,47,High School,19,66,71,25,94,3.0,5,69,Semi-Urban,Software Engineer,40410,0 +23585,Female,59,Bachelors,4,37,78,56,48,4.0,1,39,Urban,Data Analyst,137072,0 +23586,Male,33,Bachelors,15,89,4,60,51,2.0,4,25,Semi-Urban,Data Analyst,106013,0 +23587,Male,41,High School,9,81,63,90,4,0.0,6,84,Semi-Urban,ML Engineer,113694,1 +23588,Female,57,PhD,16,4,77,59,90,6.0,0,39,Semi-Urban,ML Engineer,82782,0 +23589,Female,48,Diploma,8,57,43,35,80,4.0,3,46,Urban,ML Engineer,91202,0 +23590,Male,51,High School,0,82,68,7,53,7.0,3,82,Urban,HR Executive,110664,1 +23591,Male,44,Bachelors,17,30,32,76,68,5.0,0,51,Semi-Urban,ML Engineer,48493,0 +23592,Female,40,Masters,11,0,93,97,76,7.0,0,96,Urban,Software Engineer,75547,1 +23593,Male,55,Bachelors,10,37,12,96,16,3.0,2,11,Semi-Urban,ML Engineer,46523,0 +23594,Male,24,High School,0,23,57,15,69,5.0,6,83,Urban,HR Executive,120154,0 +23595,Male,28,Masters,3,39,78,19,91,8.0,2,38,Urban,HR Executive,97176,0 +23596,Female,50,High School,19,89,20,83,5,2.0,5,62,Urban,Data Analyst,77918,1 +23597,Male,36,High School,10,17,33,38,24,6.0,7,53,Semi-Urban,Software Engineer,79316,0 +23598,Male,49,Diploma,10,78,84,34,76,0.0,0,84,Semi-Urban,HR Executive,36702,1 +23599,Male,31,Bachelors,8,25,74,69,7,7.0,7,36,Urban,ML Engineer,124873,0 +23600,Male,31,Bachelors,15,78,42,79,58,9.0,0,31,Urban,HR Executive,66110,0 +23601,Male,54,Bachelors,15,96,74,8,75,3.0,7,44,Rural,ML Engineer,50156,0 +23602,Male,58,PhD,5,5,87,72,15,3.0,6,19,Semi-Urban,ML Engineer,121166,0 +23603,Male,55,Masters,12,41,29,9,68,3.0,1,59,Urban,HR Executive,78100,0 +23604,Female,50,Bachelors,2,77,93,6,8,4.0,1,51,Urban,ML Engineer,140298,0 +23605,Male,51,High School,2,25,46,70,86,1.0,0,76,Urban,ML Engineer,132605,0 +23606,Male,56,High School,4,66,49,10,73,7.0,1,76,Urban,HR Executive,101288,0 +23607,Other,29,Masters,14,35,13,6,96,9.0,5,24,Urban,Manager,128338,0 +23608,Female,44,Diploma,9,9,72,76,25,1.0,2,77,Urban,Data Analyst,61432,0 +23609,Female,45,Diploma,16,58,81,0,40,1.0,4,98,Semi-Urban,ML Engineer,94627,0 +23610,Male,24,High School,5,50,42,90,62,5.0,4,96,Semi-Urban,Data Analyst,121674,1 +23611,Male,33,Bachelors,17,58,75,18,3,0.0,0,71,Urban,Manager,126248,0 +23612,Female,41,Diploma,13,48,7,81,79,0.0,1,59,Urban,Data Analyst,42370,0 +23613,Female,45,PhD,14,54,93,22,26,1.0,6,98,Urban,HR Executive,48806,1 +23614,Male,36,Bachelors,8,49,27,56,66,8.0,7,45,Urban,Software Engineer,37888,0 +23615,Male,49,Diploma,16,75,38,31,44,2.0,2,73,Semi-Urban,Manager,27614,0 +23616,Female,28,High School,7,13,40,31,16,0.0,1,86,Rural,ML Engineer,111827,0 +23617,Male,57,Diploma,10,30,68,62,72,7.0,0,93,Urban,Data Analyst,27639,1 +23618,Male,37,Diploma,8,69,18,20,54,2.0,0,87,Semi-Urban,Manager,85593,0 +23619,Male,56,Bachelors,1,75,12,58,0,8.0,6,92,Semi-Urban,Manager,41605,1 +23620,Female,44,Masters,15,71,93,92,8,4.0,6,11,Urban,ML Engineer,32731,1 +23621,Female,45,Diploma,15,7,30,89,20,9.0,4,25,Semi-Urban,Manager,49397,0 +23622,Female,27,Bachelors,10,18,11,31,56,7.0,0,77,Urban,Software Engineer,146607,0 +23623,Male,55,Bachelors,9,2,62,72,73,4.0,6,82,Semi-Urban,HR Executive,126992,0 +23624,Male,26,Bachelors,7,70,8,0,92,4.0,2,44,Urban,Manager,40429,0 +23625,Male,42,Diploma,1,49,63,12,35,8.0,0,29,Semi-Urban,Data Analyst,104680,0 +23626,Female,26,Bachelors,11,90,3,96,67,2.0,5,28,Semi-Urban,HR Executive,115729,0 +23627,Female,24,Masters,7,11,6,79,70,4.0,5,54,Urban,Software Engineer,43722,0 +23628,Other,31,Bachelors,18,8,75,26,95,6.0,1,97,Semi-Urban,Software Engineer,142742,0 +23629,Male,38,Diploma,10,46,60,63,36,4.0,4,60,Semi-Urban,Software Engineer,46260,0 +23630,Female,22,Diploma,3,18,83,25,94,0.0,6,38,Semi-Urban,Data Analyst,31272,0 +23631,Male,33,High School,7,84,91,52,94,4.0,2,12,Rural,Software Engineer,116404,1 +23632,Male,34,High School,14,50,87,8,58,9.0,3,10,Rural,Manager,116326,0 +23633,Male,34,Bachelors,17,64,44,0,64,6.0,0,80,Urban,ML Engineer,71666,0 +23634,Male,41,Masters,14,89,51,87,43,2.0,6,0,Semi-Urban,Software Engineer,70839,0 +23635,Other,30,Bachelors,13,15,21,19,79,7.0,5,17,Urban,Software Engineer,113844,0 +23636,Male,50,Masters,17,87,0,38,10,4.0,5,12,Semi-Urban,Manager,40775,0 +23637,Other,42,Bachelors,11,86,38,92,41,9.0,7,28,Urban,Manager,24368,1 +23638,Male,51,Masters,4,89,47,70,63,9.0,0,40,Urban,Manager,134064,1 +23639,Male,53,Diploma,0,72,2,68,67,1.0,0,45,Rural,Manager,91854,0 +23640,Male,27,Bachelors,9,33,61,18,38,0.0,1,85,Urban,Data Analyst,98840,0 +23641,Male,36,Bachelors,5,78,76,28,22,2.0,0,24,Urban,HR Executive,50196,0 +23642,Male,26,Bachelors,3,52,86,24,80,8.0,0,67,Urban,HR Executive,115730,0 +23643,Male,52,Bachelors,3,20,32,98,52,9.0,2,72,Urban,HR Executive,149720,0 +23644,Male,21,Bachelors,13,70,45,74,3,8.0,7,77,Urban,ML Engineer,110948,1 +23645,Other,48,Masters,1,30,62,49,34,0.0,3,3,Urban,Manager,39631,0 +23646,Female,53,Diploma,11,47,76,24,21,3.0,3,44,Semi-Urban,Data Analyst,129754,0 +23647,Female,45,Bachelors,16,38,83,79,86,4.0,5,54,Urban,Data Analyst,27917,1 +23648,Male,43,High School,7,1,7,54,10,6.0,4,2,Semi-Urban,Software Engineer,126865,0 +23649,Male,53,Bachelors,18,79,66,6,37,5.0,4,21,Urban,HR Executive,49828,0 +23650,Male,54,Diploma,0,37,47,98,88,9.0,1,23,Urban,Data Analyst,144646,0 +23651,Female,49,Diploma,3,16,1,14,4,4.0,1,26,Urban,Software Engineer,120674,0 +23652,Male,30,Bachelors,19,9,34,91,4,8.0,3,67,Urban,ML Engineer,108819,0 +23653,Male,26,Masters,11,79,60,70,30,0.0,0,74,Urban,Data Analyst,57058,1 +23654,Male,40,Bachelors,6,22,14,71,94,5.0,7,10,Semi-Urban,ML Engineer,107092,0 +23655,Male,37,Diploma,9,57,0,76,4,9.0,0,54,Urban,Manager,52715,0 +23656,Female,40,Bachelors,1,96,65,86,21,3.0,4,42,Semi-Urban,HR Executive,25183,1 +23657,Male,46,Bachelors,10,79,78,52,26,0.0,1,73,Urban,HR Executive,23211,1 +23658,Male,22,Diploma,1,38,93,80,73,9.0,3,98,Urban,Data Analyst,40210,1 +23659,Female,41,Masters,0,11,17,50,78,1.0,7,56,Urban,HR Executive,37224,0 +23660,Male,57,High School,14,15,62,10,68,4.0,5,44,Semi-Urban,HR Executive,39160,0 +23661,Male,45,Bachelors,8,80,0,22,7,6.0,3,47,Rural,Manager,51297,0 +23662,Male,29,Bachelors,15,59,14,66,26,3.0,2,85,Urban,Manager,97109,0 +23663,Female,29,Masters,17,69,38,88,45,6.0,1,20,Urban,Manager,41458,0 +23664,Other,38,High School,17,78,25,3,68,6.0,4,65,Rural,ML Engineer,26338,0 +23665,Female,43,Bachelors,3,91,87,50,43,6.0,5,47,Semi-Urban,ML Engineer,106673,1 +23666,Female,28,Bachelors,17,27,52,44,24,0.0,6,49,Semi-Urban,Data Analyst,147339,0 +23667,Male,24,Masters,4,46,70,44,57,7.0,5,13,Rural,ML Engineer,49950,0 +23668,Male,47,Masters,5,39,45,48,48,8.0,4,73,Semi-Urban,Software Engineer,91791,0 +23669,Male,41,High School,17,8,16,46,83,0.0,1,38,Semi-Urban,ML Engineer,33282,0 +23670,Female,42,High School,11,1,56,85,4,8.0,0,47,Urban,HR Executive,121231,0 +23671,Male,49,Bachelors,19,5,25,25,55,4.0,5,51,Urban,Data Analyst,94485,0 +23672,Female,55,Bachelors,0,76,45,9,83,9.0,5,95,Rural,Manager,22581,0 +23673,Female,43,Diploma,6,8,30,60,60,2.0,3,52,Urban,Data Analyst,64488,0 +23674,Other,26,Bachelors,4,98,63,50,24,0.0,7,35,Urban,Data Analyst,38204,1 +23675,Male,24,Diploma,9,45,15,51,27,3.0,4,12,Urban,Software Engineer,73640,0 +23676,Male,56,High School,5,78,57,34,89,1.0,0,0,Semi-Urban,Data Analyst,40814,0 +23677,Male,21,Bachelors,7,30,99,83,5,7.0,1,27,Semi-Urban,Manager,115963,1 +23678,Male,31,Bachelors,19,48,42,42,43,7.0,7,83,Urban,HR Executive,70064,0 +23679,Female,37,Bachelors,10,46,20,98,71,6.0,0,62,Urban,HR Executive,148010,0 +23680,Male,32,Diploma,9,39,0,1,10,2.0,2,81,Urban,ML Engineer,67668,0 +23681,Other,22,Bachelors,15,26,3,69,42,5.0,7,23,Rural,Software Engineer,20497,0 +23682,Other,29,PhD,5,21,44,62,84,8.0,7,9,Urban,HR Executive,71355,0 +23683,Male,42,Diploma,2,68,99,94,96,8.0,7,25,Urban,Manager,91509,1 +23684,Male,36,Masters,9,87,27,14,76,7.0,6,85,Rural,ML Engineer,122221,0 +23685,Male,38,High School,4,95,36,31,90,2.0,5,3,Urban,ML Engineer,103354,0 +23686,Male,58,High School,12,0,95,50,90,8.0,3,96,Semi-Urban,Data Analyst,29832,1 +23687,Male,53,High School,0,97,56,66,39,7.0,6,82,Rural,Data Analyst,140637,1 +23688,Male,51,High School,15,84,4,35,50,6.0,6,23,Rural,Software Engineer,64995,0 +23689,Male,41,Bachelors,1,16,13,46,44,5.0,2,5,Semi-Urban,Manager,108218,0 +23690,Female,37,Diploma,4,53,38,33,54,4.0,4,57,Semi-Urban,Software Engineer,38382,0 +23691,Male,54,Diploma,9,55,9,21,22,1.0,5,1,Urban,Software Engineer,130304,0 +23692,Male,58,Diploma,5,3,6,46,73,7.0,7,85,Semi-Urban,Software Engineer,131126,0 +23693,Male,21,Diploma,1,91,63,28,58,4.0,2,72,Urban,Software Engineer,50309,1 +23694,Other,46,Bachelors,5,91,30,28,93,1.0,1,76,Semi-Urban,Data Analyst,22410,0 +23695,Female,54,Bachelors,19,11,28,4,29,8.0,0,18,Semi-Urban,HR Executive,83250,0 +23696,Male,48,Bachelors,7,72,76,19,36,0.0,2,62,Urban,Data Analyst,118274,0 +23697,Female,28,Bachelors,18,8,61,22,84,9.0,6,93,Urban,Data Analyst,92678,0 +23698,Female,59,Bachelors,1,67,59,62,50,5.0,1,91,Semi-Urban,HR Executive,71535,1 +23699,Female,32,Bachelors,5,67,61,51,88,8.0,4,56,Rural,Manager,43173,0 +23700,Male,30,High School,2,18,64,18,17,8.0,5,14,Semi-Urban,Software Engineer,77008,0 +23701,Female,39,Diploma,11,71,25,31,50,8.0,4,26,Urban,Software Engineer,98959,0 +23702,Male,30,High School,16,23,84,64,90,4.0,0,92,Urban,HR Executive,23225,1 +23703,Female,30,Bachelors,10,35,28,18,44,9.0,0,37,Urban,ML Engineer,37642,0 +23704,Male,26,Bachelors,18,56,2,8,1,7.0,4,0,Urban,Data Analyst,79525,0 +23705,Female,48,PhD,17,88,50,5,47,0.0,4,70,Urban,Data Analyst,21886,0 +23706,Other,55,Bachelors,9,21,77,17,35,8.0,6,71,Urban,Software Engineer,50051,0 +23707,Male,42,Masters,0,99,75,42,68,1.0,4,95,Urban,ML Engineer,107420,1 +23708,Other,41,Bachelors,12,39,5,86,27,9.0,7,18,Semi-Urban,ML Engineer,67673,0 +23709,Male,41,Diploma,3,56,53,25,58,2.0,3,82,Urban,ML Engineer,130233,0 +23710,Male,57,PhD,18,23,68,62,17,3.0,2,47,Urban,Software Engineer,28936,0 +23711,Male,53,Bachelors,7,33,2,11,54,6.0,7,85,Urban,ML Engineer,50932,0 +23712,Other,35,Bachelors,7,93,10,60,81,1.0,7,6,Urban,ML Engineer,55650,0 +23713,Male,38,Bachelors,2,11,30,15,5,8.0,4,60,Semi-Urban,Manager,108806,0 +23714,Male,59,Bachelors,14,51,46,19,90,2.0,6,75,Urban,Data Analyst,74323,0 +23715,Female,25,Diploma,11,68,24,78,61,0.0,2,90,Urban,Software Engineer,143909,1 +23716,Other,41,Bachelors,17,56,86,4,54,9.0,0,5,Urban,Data Analyst,96661,0 +23717,Female,54,High School,6,70,22,20,2,7.0,6,10,Urban,HR Executive,141266,0 +23718,Male,48,Bachelors,13,56,3,75,6,6.0,1,5,Rural,ML Engineer,123606,0 +23719,Male,23,High School,0,37,88,97,77,9.0,4,56,Urban,Data Analyst,62688,1 +23720,Male,56,Bachelors,16,54,3,65,98,0.0,3,10,Rural,Data Analyst,125299,0 +23721,Female,23,Masters,0,68,51,31,22,2.0,7,1,Urban,Manager,25611,0 +23722,Male,36,High School,1,80,71,48,88,9.0,2,20,Urban,ML Engineer,142646,0 +23723,Male,53,Bachelors,4,44,35,77,75,0.0,4,76,Urban,ML Engineer,24202,0 +23724,Female,37,Bachelors,11,7,58,14,46,2.0,4,61,Semi-Urban,Software Engineer,54918,0 +23725,Male,38,High School,19,18,21,69,3,1.0,4,93,Rural,HR Executive,111438,0 +23726,Male,24,Bachelors,13,59,16,60,70,6.0,5,52,Semi-Urban,Manager,76600,0 +23727,Male,42,Diploma,10,25,32,60,26,6.0,6,60,Semi-Urban,Data Analyst,92788,0 +23728,Male,29,High School,16,0,44,11,16,1.0,4,25,Urban,ML Engineer,108932,0 +23729,Male,27,High School,11,79,60,65,37,6.0,7,80,Semi-Urban,Manager,126893,1 +23730,Male,50,Bachelors,11,85,60,70,42,0.0,7,21,Urban,ML Engineer,31567,1 +23731,Female,39,Masters,10,82,40,77,0,4.0,6,42,Urban,Manager,126364,1 +23732,Male,45,Masters,15,73,11,42,6,2.0,1,74,Semi-Urban,ML Engineer,130958,0 +23733,Male,57,Bachelors,8,97,6,58,1,5.0,1,17,Rural,Data Analyst,100724,0 +23734,Female,48,Bachelors,18,70,86,41,79,0.0,4,65,Semi-Urban,ML Engineer,59008,1 +23735,Female,46,Bachelors,0,30,19,80,88,3.0,1,60,Urban,HR Executive,144820,0 +23736,Female,28,Bachelors,2,24,82,18,25,1.0,6,1,Urban,Data Analyst,106533,0 +23737,Other,58,Bachelors,0,2,18,75,87,2.0,3,63,Semi-Urban,Data Analyst,137301,0 +23738,Female,55,High School,5,46,94,73,40,7.0,0,59,Rural,Data Analyst,81126,1 +23739,Male,36,Bachelors,16,29,30,31,36,4.0,0,50,Urban,HR Executive,64649,0 +23740,Female,31,Bachelors,1,9,28,24,62,7.0,1,23,Semi-Urban,Manager,70374,0 +23741,Male,54,Diploma,4,49,2,21,63,8.0,0,79,Rural,Data Analyst,142317,0 +23742,Male,38,Bachelors,1,60,21,28,28,7.0,3,58,Urban,Manager,144500,0 +23743,Male,39,Bachelors,0,4,98,64,9,0.0,7,91,Semi-Urban,Data Analyst,124655,1 +23744,Male,27,Bachelors,15,81,35,9,34,8.0,6,51,Semi-Urban,ML Engineer,117236,0 +23745,Male,43,Masters,6,34,87,13,59,1.0,2,61,Urban,HR Executive,116113,0 +23746,Male,23,Bachelors,10,22,34,51,64,9.0,3,25,Semi-Urban,Manager,104834,0 +23747,Male,23,High School,17,56,55,55,99,9.0,5,92,Urban,ML Engineer,107597,1 +23748,Female,49,Diploma,4,65,90,15,64,0.0,5,79,Rural,Data Analyst,44407,1 +23749,Female,53,Diploma,17,59,95,10,6,7.0,1,36,Urban,ML Engineer,101807,0 +23750,Male,43,Bachelors,7,44,46,65,59,0.0,6,20,Rural,Data Analyst,107917,0 +23751,Female,24,Masters,3,0,4,66,96,4.0,4,87,Semi-Urban,Manager,90228,0 +23752,Male,22,Bachelors,15,69,71,9,77,8.0,0,70,Urban,Data Analyst,148117,0 +23753,Female,35,Bachelors,10,96,73,34,13,7.0,3,70,Rural,ML Engineer,134676,1 +23754,Male,59,Masters,10,33,96,77,93,8.0,2,59,Semi-Urban,Data Analyst,73013,1 +23755,Male,51,Bachelors,14,10,0,52,43,5.0,4,43,Rural,HR Executive,128406,0 +23756,Male,33,Masters,7,41,33,22,92,9.0,2,84,Urban,HR Executive,28239,0 +23757,Male,58,Bachelors,11,67,71,93,39,3.0,3,2,Urban,ML Engineer,47246,0 +23758,Male,47,Diploma,5,59,98,37,76,8.0,2,36,Urban,Manager,49260,0 +23759,Male,56,Bachelors,10,69,17,78,5,8.0,2,28,Urban,Data Analyst,27494,0 +23760,Male,48,Masters,18,54,91,69,54,3.0,4,22,Urban,Data Analyst,110423,1 +23761,Male,55,Bachelors,1,94,60,20,62,8.0,0,15,Rural,Data Analyst,63330,0 +23762,Male,38,High School,14,18,70,85,68,5.0,1,64,Urban,Software Engineer,103358,1 +23763,Other,29,Bachelors,4,9,50,52,82,6.0,1,59,Urban,ML Engineer,128083,0 +23764,Male,49,Bachelors,13,0,82,29,69,6.0,7,99,Urban,Software Engineer,85843,0 +23765,Male,22,Bachelors,17,65,65,62,65,9.0,5,7,Urban,Data Analyst,83053,0 +23766,Female,58,Bachelors,16,11,52,76,36,2.0,0,23,Urban,Data Analyst,39446,0 +23767,Female,50,Bachelors,0,8,37,97,17,3.0,6,97,Urban,Software Engineer,49000,0 +23768,Male,48,Bachelors,3,4,38,0,22,1.0,0,37,Urban,Software Engineer,98894,0 +23769,Female,48,Diploma,15,72,4,4,85,3.0,2,48,Urban,ML Engineer,117361,0 +23770,Male,57,High School,12,97,40,73,4,3.0,1,26,Rural,Data Analyst,122869,1 +23771,Male,53,Bachelors,15,28,40,21,2,4.0,3,66,Rural,Software Engineer,63266,0 +23772,Male,57,Bachelors,9,82,44,56,27,6.0,4,95,Urban,HR Executive,83606,1 +23773,Female,27,Diploma,18,95,1,82,48,9.0,1,73,Rural,HR Executive,67392,1 +23774,Male,47,Masters,14,43,80,91,41,1.0,6,19,Urban,Data Analyst,88752,0 +23775,Female,29,Bachelors,19,69,61,24,75,9.0,7,40,Semi-Urban,Software Engineer,36723,0 +23776,Male,39,High School,14,25,36,56,21,2.0,3,22,Urban,Data Analyst,84610,0 +23777,Female,56,Bachelors,11,70,9,12,9,9.0,2,97,Rural,HR Executive,40499,0 +23778,Male,27,Bachelors,3,12,92,20,28,8.0,1,84,Urban,ML Engineer,69059,0 +23779,Male,55,Masters,11,68,92,92,91,5.0,0,48,Semi-Urban,Manager,54217,1 +23780,Male,25,Bachelors,11,47,6,64,43,5.0,6,92,Urban,Data Analyst,59009,0 +23781,Female,43,Masters,1,69,54,23,83,4.0,0,35,Rural,Data Analyst,123010,0 +23782,Male,28,Masters,7,96,15,39,83,3.0,3,62,Urban,Data Analyst,102033,0 +23783,Female,58,Diploma,0,3,44,45,14,8.0,3,24,Rural,HR Executive,48452,0 +23784,Female,49,Masters,13,82,98,3,3,2.0,6,67,Semi-Urban,Data Analyst,24245,1 +23785,Male,55,Masters,14,30,12,87,96,3.0,4,64,Rural,Software Engineer,67639,0 +23786,Other,44,Bachelors,11,54,37,6,4,0.0,4,77,Semi-Urban,Manager,32633,0 +23787,Female,55,Bachelors,4,49,94,53,96,3.0,0,44,Semi-Urban,Software Engineer,30829,0 +23788,Male,51,High School,5,4,69,50,65,9.0,5,86,Semi-Urban,Data Analyst,49916,0 +23789,Male,55,Bachelors,19,78,78,72,37,7.0,6,28,Semi-Urban,HR Executive,115230,1 +23790,Male,40,Masters,10,69,0,96,39,7.0,1,25,Urban,Manager,42235,0 +23791,Male,52,Bachelors,8,71,93,17,47,9.0,0,36,Semi-Urban,Manager,44714,0 +23792,Male,32,Bachelors,16,33,3,23,57,9.0,5,50,Urban,ML Engineer,83725,0 +23793,Male,25,PhD,14,93,19,11,44,2.0,2,57,Semi-Urban,ML Engineer,43555,0 +23794,Female,22,Bachelors,4,96,67,13,74,6.0,0,94,Urban,HR Executive,79905,1 +23795,Male,55,Masters,4,46,15,83,75,4.0,6,4,Urban,Software Engineer,96605,0 +23796,Female,56,Masters,2,83,7,7,23,9.0,6,19,Urban,HR Executive,101443,0 +23797,Male,30,Masters,4,12,92,50,28,6.0,7,52,Semi-Urban,ML Engineer,76327,0 +23798,Male,49,Masters,5,49,50,77,21,9.0,1,45,Urban,HR Executive,145032,0 +23799,Female,56,Diploma,13,36,90,17,87,6.0,6,48,Urban,HR Executive,100272,0 +23800,Female,36,PhD,12,42,86,47,67,6.0,3,4,Urban,ML Engineer,125160,0 +23801,Male,47,Diploma,0,16,4,60,90,4.0,0,36,Semi-Urban,Data Analyst,131642,0 +23802,Male,58,High School,19,68,73,21,98,1.0,2,71,Urban,ML Engineer,106725,0 +23803,Male,49,Masters,14,97,38,2,63,9.0,2,0,Rural,Manager,113524,0 +23804,Male,54,Bachelors,12,49,83,42,65,5.0,2,68,Urban,Data Analyst,110351,1 +23805,Male,31,Bachelors,13,17,65,57,97,9.0,6,46,Rural,HR Executive,95043,0 +23806,Female,51,Bachelors,18,65,87,31,2,8.0,5,85,Semi-Urban,Software Engineer,74161,1 +23807,Male,58,Diploma,11,99,57,79,91,6.0,4,62,Rural,Software Engineer,37033,1 +23808,Male,44,Bachelors,18,72,29,83,22,4.0,3,54,Urban,Software Engineer,123945,1 +23809,Male,44,Bachelors,4,99,52,24,71,4.0,7,37,Urban,Manager,116165,0 +23810,Male,54,Masters,17,56,32,3,53,3.0,7,57,Urban,Software Engineer,39201,0 +23811,Male,40,PhD,9,49,34,49,44,3.0,5,65,Urban,Data Analyst,92122,0 +23812,Male,21,Diploma,5,7,4,47,25,6.0,2,98,Urban,Software Engineer,28898,0 +23813,Male,35,Diploma,18,40,92,94,61,3.0,6,68,Semi-Urban,Manager,49929,1 +23814,Female,26,Diploma,13,59,40,37,81,2.0,7,56,Semi-Urban,ML Engineer,120223,0 +23815,Male,42,PhD,13,10,0,95,67,2.0,1,71,Rural,HR Executive,147622,0 +23816,Female,58,Masters,9,21,64,15,91,2.0,6,20,Rural,Manager,55711,0 +23817,Male,56,Bachelors,16,12,59,75,57,7.0,3,17,Urban,Software Engineer,29550,0 +23818,Male,51,Diploma,8,41,52,56,34,5.0,4,51,Semi-Urban,Software Engineer,148994,0 +23819,Female,33,High School,13,14,63,19,82,5.0,0,72,Urban,ML Engineer,126762,0 +23820,Female,47,Bachelors,7,46,8,29,20,3.0,6,6,Rural,ML Engineer,41358,0 +23821,Male,23,Bachelors,14,42,45,10,56,9.0,1,11,Rural,Data Analyst,149906,0 +23822,Female,22,PhD,9,41,87,59,4,3.0,3,73,Rural,Manager,111291,1 +23823,Female,21,Diploma,1,72,64,14,86,7.0,0,61,Urban,ML Engineer,55267,0 +23824,Female,55,Masters,5,54,40,98,56,3.0,6,80,Rural,Data Analyst,99859,1 +23825,Male,40,Diploma,7,19,26,63,56,5.0,3,15,Semi-Urban,ML Engineer,103758,0 +23826,Female,32,PhD,19,92,37,91,81,7.0,7,70,Rural,Data Analyst,76833,1 +23827,Female,48,Bachelors,17,43,61,99,80,9.0,2,4,Urban,Manager,114000,0 +23828,Female,43,Diploma,2,61,37,18,13,6.0,2,57,Urban,Software Engineer,113915,0 +23829,Female,36,Bachelors,7,4,56,39,49,4.0,4,77,Urban,Manager,118955,0 +23830,Other,22,Bachelors,19,48,72,38,92,7.0,7,57,Rural,Manager,70627,0 +23831,Male,22,Bachelors,3,64,99,96,34,2.0,6,67,Semi-Urban,Manager,99910,1 +23832,Male,58,Bachelors,5,67,46,14,23,2.0,2,42,Semi-Urban,Manager,133369,0 +23833,Male,27,PhD,18,3,20,24,75,8.0,5,27,Urban,Manager,99242,0 +23834,Male,28,High School,16,39,5,35,89,7.0,7,60,Semi-Urban,Data Analyst,143967,0 +23835,Male,41,Bachelors,3,86,76,27,32,7.0,5,41,Urban,HR Executive,37315,0 +23836,Male,26,Bachelors,4,18,64,22,58,2.0,1,11,Semi-Urban,HR Executive,70871,0 +23837,Male,33,Masters,11,19,25,41,93,1.0,5,73,Rural,HR Executive,146501,0 +23838,Female,35,Bachelors,15,72,36,99,56,9.0,1,66,Urban,ML Engineer,99304,1 +23839,Female,43,High School,17,60,33,98,30,2.0,0,22,Semi-Urban,Software Engineer,68026,0 +23840,Male,26,Diploma,8,61,3,27,24,7.0,5,71,Semi-Urban,Manager,47836,0 +23841,Female,41,Masters,12,88,63,78,59,1.0,4,49,Rural,ML Engineer,141022,1 +23842,Male,55,High School,14,93,76,4,81,9.0,0,74,Rural,HR Executive,35653,1 +23843,Female,55,Bachelors,7,51,31,56,9,9.0,7,73,Rural,Data Analyst,77681,0 +23844,Female,48,Masters,16,9,23,43,94,7.0,1,36,Urban,HR Executive,144546,0 +23845,Male,35,Bachelors,7,96,2,52,13,3.0,7,9,Rural,HR Executive,128247,0 +23846,Male,34,Diploma,15,27,10,81,24,5.0,4,18,Urban,Manager,142904,0 +23847,Male,36,Bachelors,8,21,30,64,32,9.0,5,76,Urban,Software Engineer,115972,0 +23848,Female,49,Masters,3,96,11,67,14,7.0,3,49,Urban,Software Engineer,127784,0 +23849,Female,31,Bachelors,1,44,57,52,19,5.0,0,64,Urban,HR Executive,41647,0 +23850,Male,59,Diploma,12,78,20,32,30,8.0,1,61,Urban,Software Engineer,127176,0 +23851,Male,45,Diploma,10,7,25,68,73,5.0,3,6,Semi-Urban,Software Engineer,85045,0 +23852,Male,26,High School,2,59,97,80,14,6.0,2,72,Rural,Data Analyst,123003,1 +23853,Male,36,Masters,4,13,62,55,67,9.0,1,25,Semi-Urban,HR Executive,64620,0 +23854,Other,51,Masters,5,98,21,7,50,3.0,1,12,Urban,Software Engineer,119251,0 +23855,Male,54,Bachelors,11,26,31,70,54,2.0,2,54,Urban,Data Analyst,118269,0 +23856,Female,39,Bachelors,3,6,48,97,76,2.0,5,23,Semi-Urban,Data Analyst,72510,0 +23857,Female,48,Bachelors,8,81,29,45,82,3.0,4,46,Semi-Urban,HR Executive,123254,0 +23858,Other,36,Diploma,6,23,47,66,28,4.0,6,88,Rural,Manager,44559,0 +23859,Male,41,Diploma,13,8,39,94,21,8.0,5,19,Semi-Urban,Software Engineer,141194,0 +23860,Male,54,Diploma,16,9,53,17,96,2.0,3,49,Urban,Data Analyst,41638,0 +23861,Male,42,High School,19,6,28,7,14,2.0,1,56,Urban,HR Executive,138595,0 +23862,Female,42,High School,15,4,38,48,34,1.0,5,18,Rural,Manager,49507,0 +23863,Female,24,PhD,19,45,43,54,96,7.0,6,11,Urban,Software Engineer,109306,0 +23864,Male,59,Diploma,5,98,60,51,2,8.0,4,86,Semi-Urban,Data Analyst,110882,1 +23865,Female,35,High School,7,59,86,13,54,3.0,5,93,Urban,Manager,130219,1 +23866,Male,50,Masters,2,6,96,14,72,7.0,2,69,Urban,Manager,31964,0 +23867,Male,41,Masters,11,18,80,88,13,0.0,3,98,Rural,ML Engineer,86098,1 +23868,Male,35,Diploma,2,99,30,34,72,8.0,4,23,Urban,Manager,147903,0 +23869,Male,23,Bachelors,13,41,75,19,82,9.0,1,27,Rural,Data Analyst,133171,0 +23870,Male,45,Masters,0,96,15,15,12,0.0,6,0,Rural,ML Engineer,80648,0 +23871,Male,58,High School,7,41,51,47,15,0.0,6,82,Urban,HR Executive,145999,0 +23872,Female,42,Bachelors,10,20,56,15,52,9.0,5,46,Urban,Software Engineer,141273,0 +23873,Female,48,Bachelors,10,68,80,29,73,8.0,6,42,Urban,Manager,51341,0 +23874,Male,25,Bachelors,1,12,81,26,85,2.0,6,30,Rural,ML Engineer,134955,0 +23875,Female,54,Bachelors,15,40,54,12,21,8.0,6,80,Urban,Data Analyst,102328,0 +23876,Male,32,Masters,9,75,71,27,14,2.0,5,36,Urban,Software Engineer,145592,0 +23877,Male,22,High School,9,52,47,81,96,0.0,5,61,Semi-Urban,Manager,77150,1 +23878,Female,40,Diploma,0,67,86,6,88,0.0,1,41,Rural,Manager,57187,0 +23879,Female,48,Bachelors,9,26,65,20,8,7.0,1,98,Semi-Urban,Data Analyst,82492,0 +23880,Female,45,PhD,0,48,95,47,55,2.0,0,6,Semi-Urban,Data Analyst,93254,0 +23881,Female,28,Diploma,4,16,0,56,16,0.0,3,26,Urban,HR Executive,87469,0 +23882,Female,27,Masters,9,37,3,54,70,3.0,7,74,Urban,ML Engineer,24364,0 +23883,Male,30,Diploma,2,64,76,38,12,2.0,2,4,Semi-Urban,Data Analyst,90050,0 +23884,Female,45,Diploma,15,35,30,89,27,7.0,2,71,Urban,HR Executive,42201,0 +23885,Male,52,Masters,11,90,55,69,71,1.0,2,53,Urban,Data Analyst,42315,1 +23886,Female,36,Bachelors,14,49,20,81,80,2.0,2,56,Semi-Urban,ML Engineer,76953,0 +23887,Male,22,Masters,8,1,22,24,32,0.0,4,37,Urban,Software Engineer,35424,0 +23888,Male,34,Masters,6,24,65,29,14,4.0,0,9,Urban,ML Engineer,131953,0 +23889,Female,23,High School,0,62,0,96,87,0.0,7,99,Rural,HR Executive,65478,1 +23890,Male,41,Bachelors,15,39,75,68,91,2.0,3,42,Semi-Urban,ML Engineer,110688,0 +23891,Female,35,Bachelors,4,57,51,71,2,4.0,4,86,Urban,Manager,36747,1 +23892,Male,36,Bachelors,9,65,99,46,86,5.0,3,34,Urban,Manager,76470,1 +23893,Female,54,Bachelors,3,16,44,55,83,3.0,7,48,Urban,Manager,131968,0 +23894,Male,46,Masters,18,60,46,52,92,0.0,0,0,Semi-Urban,HR Executive,79344,0 +23895,Male,51,High School,4,57,23,16,16,2.0,3,46,Urban,ML Engineer,85034,0 +23896,Male,42,Bachelors,19,86,28,41,75,6.0,6,67,Urban,Software Engineer,45933,0 +23897,Female,49,Bachelors,0,66,3,83,14,0.0,0,86,Urban,HR Executive,98103,0 +23898,Female,29,Bachelors,5,68,73,56,44,6.0,2,23,Semi-Urban,Software Engineer,123658,0 +23899,Male,48,PhD,1,43,62,28,2,8.0,1,60,Urban,HR Executive,112595,0 +23900,Other,37,High School,7,24,86,77,1,2.0,0,38,Urban,HR Executive,134228,0 +23901,Female,52,Bachelors,17,36,67,31,4,9.0,0,75,Semi-Urban,Data Analyst,40706,0 +23902,Female,26,PhD,2,44,90,98,16,6.0,6,17,Urban,Manager,129006,1 +23903,Male,40,High School,6,20,61,70,54,3.0,1,4,Semi-Urban,ML Engineer,145438,0 +23904,Male,24,Masters,5,49,23,11,21,6.0,0,92,Urban,ML Engineer,114752,0 +23905,Male,39,Masters,6,81,85,22,83,9.0,6,79,Urban,HR Executive,41452,1 +23906,Male,43,Bachelors,4,57,88,49,1,9.0,2,66,Rural,Software Engineer,143324,1 +23907,Male,27,Bachelors,18,0,30,41,77,6.0,2,65,Rural,Data Analyst,119852,0 +23908,Male,46,Masters,11,92,48,28,31,0.0,3,56,Rural,ML Engineer,133863,0 +23909,Male,22,Bachelors,11,78,11,61,35,3.0,1,80,Urban,ML Engineer,75851,0 +23910,Female,59,Bachelors,6,24,20,88,25,5.0,0,18,Semi-Urban,HR Executive,148870,0 +23911,Other,25,High School,7,73,93,36,79,4.0,7,92,Urban,Software Engineer,146926,1 +23912,Female,44,PhD,19,87,91,24,32,7.0,3,85,Rural,Data Analyst,123039,1 +23913,Male,27,Masters,7,19,90,50,5,7.0,6,73,Urban,ML Engineer,54021,0 +23914,Male,28,Bachelors,13,20,85,13,12,5.0,1,18,Rural,HR Executive,124837,0 +23915,Male,43,High School,11,71,96,52,48,4.0,5,56,Rural,ML Engineer,140524,1 +23916,Male,21,Diploma,19,86,68,6,38,9.0,1,80,Rural,Software Engineer,54920,1 +23917,Male,27,Bachelors,14,30,4,7,29,7.0,4,7,Semi-Urban,ML Engineer,142806,0 +23918,Male,26,Bachelors,1,19,79,59,84,7.0,3,76,Semi-Urban,Manager,117568,0 +23919,Male,45,High School,1,51,23,11,1,2.0,5,68,Urban,Data Analyst,134726,0 +23920,Female,21,PhD,5,0,46,24,43,5.0,4,27,Urban,Software Engineer,132353,0 +23921,Female,53,High School,14,14,49,78,86,4.0,7,87,Urban,HR Executive,146354,0 +23922,Male,41,Bachelors,8,97,80,28,47,1.0,6,79,Semi-Urban,Software Engineer,41880,1 +23923,Male,49,High School,18,16,43,44,71,0.0,5,7,Rural,Manager,60742,0 +23924,Female,35,Diploma,7,17,54,31,43,3.0,7,60,Urban,HR Executive,88237,0 +23925,Male,58,Diploma,16,92,22,73,58,3.0,0,72,Urban,Software Engineer,89527,1 +23926,Male,42,Bachelors,4,22,52,24,97,7.0,4,14,Urban,Software Engineer,118993,0 +23927,Male,52,Masters,16,28,64,68,96,8.0,4,85,Urban,Manager,45474,1 +23928,Male,58,Bachelors,11,95,34,72,54,5.0,4,13,Urban,ML Engineer,81238,0 +23929,Male,37,Bachelors,2,96,45,2,45,0.0,4,56,Urban,Manager,34760,0 +23930,Female,56,Bachelors,1,31,61,88,20,9.0,5,83,Rural,HR Executive,102647,1 +23931,Male,33,Diploma,6,53,5,46,1,8.0,5,26,Urban,ML Engineer,113651,0 +23932,Male,58,High School,0,94,60,76,5,4.0,6,10,Urban,ML Engineer,73659,1 +23933,Male,43,Masters,7,17,78,63,88,8.0,2,0,Semi-Urban,HR Executive,48443,0 +23934,Female,25,Masters,15,42,12,33,13,9.0,6,56,Semi-Urban,Software Engineer,71778,0 +23935,Male,39,Bachelors,0,98,91,31,17,7.0,5,20,Semi-Urban,Data Analyst,136043,1 +23936,Male,37,Diploma,14,92,67,7,23,6.0,5,50,Urban,HR Executive,47120,0 +23937,Male,38,Masters,6,39,20,63,44,2.0,4,68,Urban,Data Analyst,41468,0 +23938,Male,46,High School,17,80,72,9,63,1.0,2,59,Rural,Software Engineer,89955,0 +23939,Male,29,Masters,4,2,27,95,39,2.0,5,16,Urban,ML Engineer,126505,0 +23940,Male,47,Bachelors,16,50,14,16,3,6.0,4,63,Semi-Urban,Manager,64818,0 +23941,Female,41,Masters,6,23,19,37,70,6.0,4,77,Semi-Urban,HR Executive,21767,0 +23942,Other,46,Bachelors,5,78,51,45,18,3.0,3,64,Urban,Manager,138661,0 +23943,Male,45,High School,7,26,72,35,62,4.0,1,5,Urban,Data Analyst,127170,0 +23944,Male,34,Diploma,19,42,99,90,49,0.0,1,9,Semi-Urban,ML Engineer,89475,1 +23945,Male,30,Diploma,2,65,46,87,67,0.0,2,14,Urban,Data Analyst,118732,0 +23946,Female,25,Bachelors,15,65,59,74,35,3.0,7,63,Semi-Urban,Software Engineer,47275,1 +23947,Male,39,High School,14,45,98,47,83,4.0,2,45,Urban,ML Engineer,122527,1 +23948,Female,37,Diploma,3,71,81,81,25,0.0,3,74,Rural,Manager,80159,1 +23949,Female,26,Diploma,12,62,2,63,43,7.0,0,62,Urban,Software Engineer,144032,0 +23950,Female,31,Bachelors,9,40,62,4,84,0.0,6,79,Rural,HR Executive,51649,0 +23951,Female,49,Diploma,9,39,1,78,44,0.0,2,18,Urban,ML Engineer,46134,0 +23952,Female,52,Bachelors,12,94,85,47,5,6.0,3,90,Urban,Manager,120222,1 +23953,Male,54,Bachelors,5,11,47,22,23,0.0,6,70,Urban,Data Analyst,24711,0 +23954,Male,40,High School,19,33,96,95,0,9.0,3,92,Semi-Urban,Manager,116280,1 +23955,Male,21,Diploma,16,50,71,11,22,5.0,5,17,Urban,Software Engineer,35672,0 +23956,Male,38,Bachelors,8,90,26,99,53,0.0,2,27,Urban,HR Executive,70612,1 +23957,Female,42,Bachelors,9,17,60,38,57,1.0,4,68,Semi-Urban,HR Executive,114286,0 +23958,Male,31,Diploma,8,65,77,39,71,5.0,1,48,Rural,Software Engineer,21869,0 +23959,Female,35,High School,13,69,20,68,76,7.0,0,39,Semi-Urban,Software Engineer,50789,0 +23960,Male,37,High School,1,18,37,64,59,2.0,2,35,Semi-Urban,Data Analyst,42142,0 +23961,Female,43,Bachelors,3,94,85,87,42,4.0,6,97,Urban,HR Executive,107357,1 +23962,Male,34,High School,12,82,25,71,4,9.0,5,95,Semi-Urban,Manager,26389,1 +23963,Male,44,PhD,6,76,2,43,58,7.0,2,59,Semi-Urban,ML Engineer,125434,0 +23964,Male,38,PhD,0,14,26,53,94,4.0,6,67,Rural,HR Executive,141525,0 +23965,Female,23,Masters,5,84,95,0,23,3.0,3,97,Semi-Urban,ML Engineer,74339,1 +23966,Male,27,High School,19,77,97,94,28,3.0,0,95,Urban,HR Executive,60474,1 +23967,Male,38,Bachelors,14,16,10,38,50,2.0,6,64,Rural,Software Engineer,83555,0 +23968,Male,32,Bachelors,10,48,9,85,98,8.0,6,33,Urban,Software Engineer,148478,0 +23969,Female,46,Bachelors,15,17,1,74,8,8.0,2,57,Urban,ML Engineer,120765,0 +23970,Male,22,Masters,12,96,63,32,71,2.0,0,37,Rural,HR Executive,89638,0 +23971,Other,44,Bachelors,19,49,34,8,32,7.0,7,4,Rural,ML Engineer,120252,0 +23972,Male,28,Bachelors,9,80,51,11,2,6.0,5,73,Semi-Urban,Data Analyst,122604,0 +23973,Male,38,Bachelors,11,33,11,86,26,9.0,5,32,Urban,Software Engineer,127010,0 +23974,Female,40,Bachelors,1,18,42,35,6,0.0,6,59,Semi-Urban,Software Engineer,56768,0 +23975,Male,40,Bachelors,17,6,14,9,12,4.0,3,96,Semi-Urban,HR Executive,82949,0 +23976,Female,27,Masters,10,68,50,94,49,1.0,0,96,Rural,HR Executive,23892,1 +23977,Male,35,Bachelors,8,11,74,50,16,2.0,7,28,Rural,Data Analyst,39698,0 +23978,Other,59,Diploma,13,47,14,10,30,1.0,5,46,Urban,ML Engineer,145801,0 +23979,Female,38,High School,4,88,80,90,68,7.0,1,12,Rural,Manager,101365,1 +23980,Female,45,Bachelors,4,68,97,53,45,0.0,6,21,Urban,Software Engineer,68136,0 +23981,Male,56,Masters,4,29,76,81,17,5.0,1,58,Semi-Urban,Data Analyst,129293,1 +23982,Male,22,Bachelors,19,57,48,56,85,2.0,7,69,Semi-Urban,HR Executive,147052,0 +23983,Female,45,Masters,12,86,62,77,71,7.0,6,51,Rural,Software Engineer,119729,1 +23984,Female,25,Bachelors,15,73,38,18,46,3.0,6,87,Semi-Urban,HR Executive,107332,0 +23985,Male,58,High School,3,24,45,46,65,7.0,0,1,Urban,HR Executive,40372,0 +23986,Male,23,High School,10,14,30,45,57,3.0,5,41,Rural,Data Analyst,103326,0 +23987,Male,48,Bachelors,17,94,73,45,51,9.0,7,75,Rural,Manager,135491,1 +23988,Female,29,Bachelors,8,68,33,69,44,7.0,4,8,Rural,HR Executive,130645,0 +23989,Male,22,Masters,13,44,39,30,59,6.0,0,24,Urban,HR Executive,36381,0 +23990,Male,42,Diploma,7,70,82,27,92,4.0,0,25,Rural,ML Engineer,100740,0 +23991,Male,23,Masters,8,91,94,30,71,0.0,6,71,Urban,HR Executive,121227,1 +23992,Male,51,High School,18,15,17,51,5,2.0,3,47,Rural,Software Engineer,116529,0 +23993,Male,45,Masters,2,38,83,15,25,4.0,3,19,Rural,Software Engineer,133213,0 +23994,Other,54,Bachelors,7,8,30,41,51,9.0,0,9,Urban,ML Engineer,34425,0 +23995,Male,23,Diploma,16,80,70,62,21,2.0,4,36,Semi-Urban,Software Engineer,95501,1 +23996,Female,47,Bachelors,1,45,13,63,23,4.0,5,36,Urban,Manager,39855,0 +23997,Male,57,Masters,5,80,16,69,99,7.0,7,65,Urban,ML Engineer,141019,0 +23998,Male,31,Diploma,0,93,0,79,45,8.0,3,14,Urban,ML Engineer,126844,0 +23999,Male,39,Bachelors,19,25,89,76,85,6.0,5,90,Urban,Manager,106823,1 +24000,Female,57,Masters,15,82,26,82,46,2.0,5,97,Urban,HR Executive,72505,1 +24001,Female,58,Masters,12,7,45,36,15,4.0,2,99,Urban,Software Engineer,39044,0 +24002,Male,50,Masters,6,38,18,32,93,6.0,4,82,Semi-Urban,Manager,105492,0 +24003,Male,29,Bachelors,6,34,93,92,84,5.0,3,88,Semi-Urban,ML Engineer,99876,1 +24004,Female,57,Masters,15,66,55,49,8,3.0,7,91,Urban,HR Executive,136333,1 +24005,Other,46,Bachelors,7,31,0,43,98,8.0,3,7,Rural,ML Engineer,62814,0 +24006,Male,39,Bachelors,10,83,1,32,83,9.0,3,59,Urban,HR Executive,121604,0 +24007,Female,44,Masters,8,90,94,38,43,0.0,1,8,Semi-Urban,Data Analyst,113774,0 +24008,Male,33,Bachelors,2,77,72,35,88,3.0,2,90,Urban,Data Analyst,115491,1 +24009,Male,26,PhD,2,53,93,75,89,9.0,4,36,Urban,Manager,28110,1 +24010,Male,40,Bachelors,15,19,87,52,30,4.0,7,48,Semi-Urban,HR Executive,84453,0 +24011,Male,53,Masters,5,32,78,4,75,5.0,3,42,Urban,Manager,78665,0 +24012,Female,48,Masters,17,79,6,35,66,8.0,6,92,Urban,HR Executive,39522,0 +24013,Male,46,High School,4,9,31,65,6,9.0,3,96,Urban,Manager,112738,0 +24014,Male,51,Bachelors,16,22,74,90,63,9.0,4,3,Urban,ML Engineer,52627,0 +24015,Female,59,Masters,13,46,47,19,70,2.0,7,83,Rural,Data Analyst,99159,0 +24016,Male,40,High School,16,47,29,34,36,6.0,1,79,Rural,ML Engineer,119239,0 +24017,Male,36,High School,1,95,90,25,90,2.0,0,44,Rural,Software Engineer,106914,1 +24018,Female,50,Bachelors,15,85,92,12,20,4.0,5,34,Semi-Urban,Manager,25317,0 +24019,Male,49,Bachelors,2,18,58,45,9,9.0,7,49,Urban,HR Executive,98928,0 +24020,Male,59,Masters,5,97,43,80,41,2.0,4,88,Semi-Urban,Manager,62402,1 +24021,Male,41,Bachelors,8,31,95,23,65,7.0,2,77,Semi-Urban,Software Engineer,79713,0 +24022,Male,43,High School,3,79,36,43,8,2.0,5,32,Urban,ML Engineer,90347,0 +24023,Female,42,Diploma,15,34,86,56,58,1.0,2,73,Urban,HR Executive,101024,1 +24024,Female,27,Masters,0,90,68,18,97,8.0,2,2,Urban,Manager,103987,0 +24025,Male,34,Diploma,19,14,63,74,35,6.0,4,56,Urban,Data Analyst,84177,0 +24026,Male,21,Masters,9,49,30,67,0,6.0,0,39,Rural,Data Analyst,55893,0 +24027,Other,38,Bachelors,3,81,2,5,40,0.0,5,14,Urban,Manager,70701,0 +24028,Male,28,Bachelors,14,26,34,22,33,3.0,6,81,Urban,HR Executive,22453,0 +24029,Male,32,Bachelors,6,42,52,79,93,7.0,7,56,Semi-Urban,ML Engineer,39283,0 +24030,Other,26,Bachelors,16,74,32,52,2,1.0,1,78,Urban,HR Executive,31836,0 +24031,Other,38,High School,8,42,15,4,51,6.0,4,30,Urban,Software Engineer,91540,0 +24032,Male,25,Diploma,9,10,43,20,60,7.0,6,32,Urban,ML Engineer,99014,0 +24033,Male,25,Bachelors,2,6,49,78,90,2.0,7,96,Semi-Urban,HR Executive,85871,0 +24034,Male,36,Bachelors,3,12,87,28,26,6.0,6,27,Urban,ML Engineer,82584,0 +24035,Male,22,Bachelors,9,33,52,28,97,7.0,1,55,Urban,Manager,63555,0 +24036,Female,55,Bachelors,4,23,28,42,20,7.0,4,39,Urban,Software Engineer,54113,0 +24037,Male,38,Bachelors,5,29,89,27,98,9.0,2,29,Urban,ML Engineer,109210,0 +24038,Male,57,Diploma,12,23,4,87,55,8.0,5,47,Urban,Manager,39733,0 +24039,Male,23,Bachelors,14,76,31,99,50,3.0,4,27,Semi-Urban,HR Executive,30866,0 +24040,Other,53,Masters,9,78,95,85,55,2.0,2,13,Rural,ML Engineer,80067,1 +24041,Male,41,Diploma,0,74,85,15,19,3.0,3,51,Semi-Urban,ML Engineer,111409,0 +24042,Male,57,Diploma,5,9,4,61,4,8.0,3,75,Urban,Software Engineer,58079,0 +24043,Other,48,Bachelors,9,69,10,62,48,7.0,0,45,Urban,Data Analyst,125532,0 +24044,Male,35,High School,5,10,83,3,75,3.0,4,58,Semi-Urban,Data Analyst,101410,0 +24045,Male,54,Bachelors,15,37,60,96,11,3.0,6,61,Urban,ML Engineer,84464,1 +24046,Male,25,Bachelors,13,19,3,85,68,9.0,1,97,Rural,HR Executive,64625,0 +24047,Male,43,Masters,8,84,36,34,31,8.0,0,1,Urban,ML Engineer,25565,0 +24048,Male,53,High School,3,64,24,19,6,8.0,5,21,Rural,Manager,90792,0 +24049,Male,53,Masters,13,13,17,32,54,3.0,6,88,Urban,ML Engineer,55389,0 +24050,Male,27,Bachelors,13,69,98,62,31,1.0,6,11,Rural,Data Analyst,41608,1 +24051,Male,42,High School,5,43,37,91,29,2.0,3,77,Urban,HR Executive,100188,1 +24052,Male,35,Masters,17,32,17,65,92,3.0,3,51,Urban,Data Analyst,50758,0 +24053,Male,28,Masters,13,3,72,70,16,6.0,3,45,Semi-Urban,HR Executive,111288,0 +24054,Male,36,Diploma,15,82,10,78,92,6.0,0,85,Semi-Urban,ML Engineer,141827,1 +24055,Male,21,Masters,13,14,44,21,80,3.0,4,4,Urban,HR Executive,25814,0 +24056,Female,49,Diploma,8,97,60,87,3,7.0,2,94,Rural,ML Engineer,32315,1 +24057,Male,54,Bachelors,5,66,21,12,11,4.0,7,2,Urban,Manager,85855,0 +24058,Male,23,Bachelors,13,31,50,69,6,1.0,1,11,Semi-Urban,ML Engineer,83428,0 +24059,Female,47,High School,12,8,47,23,15,2.0,7,62,Urban,HR Executive,91113,0 +24060,Male,40,Bachelors,0,58,4,25,98,7.0,5,26,Urban,Data Analyst,32912,0 +24061,Female,21,Masters,19,53,75,32,7,0.0,7,89,Urban,ML Engineer,79314,1 +24062,Female,27,Bachelors,0,47,33,11,70,7.0,2,7,Urban,ML Engineer,76673,0 +24063,Female,32,Diploma,11,62,33,22,14,7.0,1,45,Urban,HR Executive,109552,0 +24064,Female,40,Bachelors,13,74,42,69,0,4.0,1,15,Urban,Data Analyst,73724,0 +24065,Male,45,Masters,13,95,1,38,56,7.0,3,0,Rural,ML Engineer,56431,0 +24066,Female,39,Masters,5,15,1,81,24,7.0,7,5,Rural,HR Executive,79496,0 +24067,Male,28,Bachelors,8,26,16,31,57,5.0,4,43,Urban,Software Engineer,106975,0 +24068,Male,27,High School,5,98,26,29,37,6.0,5,10,Semi-Urban,HR Executive,42475,0 +24069,Female,54,Diploma,13,54,65,39,19,6.0,1,6,Urban,Manager,88265,0 +24070,Male,21,Diploma,8,55,0,2,31,2.0,2,87,Urban,Data Analyst,61555,0 +24071,Other,30,Diploma,18,43,60,63,12,8.0,1,37,Urban,Software Engineer,38438,0 +24072,Male,38,Masters,19,6,70,80,4,0.0,1,83,Urban,ML Engineer,20246,1 +24073,Male,56,Bachelors,2,75,19,28,24,1.0,5,88,Urban,Software Engineer,33654,0 +24074,Male,29,Masters,19,99,55,6,80,0.0,1,57,Urban,Software Engineer,140814,0 +24075,Female,23,Masters,19,58,76,47,95,4.0,5,84,Rural,HR Executive,96488,1 +24076,Male,56,Bachelors,14,55,94,20,39,1.0,4,53,Semi-Urban,Manager,20691,0 +24077,Male,31,Bachelors,13,78,83,48,33,6.0,1,51,Rural,Data Analyst,122480,1 +24078,Male,28,Masters,15,5,62,48,29,5.0,7,44,Rural,Software Engineer,62827,0 +24079,Female,48,Diploma,0,63,57,46,32,1.0,1,14,Urban,Data Analyst,22461,0 +24080,Male,59,Diploma,8,10,41,11,8,6.0,6,69,Rural,Software Engineer,149482,0 +24081,Female,59,Masters,2,0,21,35,97,1.0,3,36,Semi-Urban,ML Engineer,38398,0 +24082,Male,53,High School,10,5,71,24,81,0.0,7,53,Urban,HR Executive,49323,0 +24083,Male,49,Bachelors,4,58,68,33,26,5.0,7,69,Rural,ML Engineer,77233,0 +24084,Male,26,High School,0,6,34,88,18,1.0,1,90,Rural,HR Executive,102128,0 +24085,Other,38,Masters,7,98,52,18,38,4.0,4,61,Urban,HR Executive,58979,0 +24086,Male,28,High School,13,20,50,27,56,0.0,2,25,Urban,Data Analyst,123137,0 +24087,Male,24,High School,14,31,20,33,96,9.0,3,94,Urban,HR Executive,26733,0 +24088,Female,35,Masters,13,37,64,31,76,5.0,2,80,Urban,HR Executive,74571,0 +24089,Male,23,Diploma,13,69,6,97,27,5.0,0,94,Rural,HR Executive,113476,1 +24090,Female,51,Diploma,1,99,1,59,97,6.0,5,43,Urban,Data Analyst,64368,0 +24091,Male,34,Bachelors,15,64,68,86,54,9.0,0,11,Urban,Data Analyst,57504,0 +24092,Male,42,Diploma,4,94,90,31,97,5.0,0,81,Rural,Manager,114889,1 +24093,Male,29,Bachelors,8,39,34,82,99,9.0,5,81,Urban,Software Engineer,103874,1 +24094,Male,42,Masters,6,63,14,85,77,9.0,5,94,Urban,ML Engineer,129185,1 +24095,Female,40,Diploma,18,63,74,71,23,0.0,0,60,Rural,HR Executive,139849,1 +24096,Female,41,Bachelors,11,13,20,53,64,7.0,6,51,Urban,ML Engineer,89491,0 +24097,Male,41,Bachelors,10,26,18,30,2,6.0,3,41,Urban,Data Analyst,60033,0 +24098,Female,29,Masters,3,65,29,62,82,7.0,3,30,Urban,Software Engineer,88435,0 +24099,Male,29,Bachelors,14,6,55,23,86,2.0,1,14,Urban,Manager,25979,0 +24100,Male,28,High School,15,82,52,78,7,4.0,4,65,Semi-Urban,Data Analyst,95651,1 +24101,Female,35,Bachelors,5,89,35,75,8,0.0,3,94,Urban,Data Analyst,73792,1 +24102,Female,35,Bachelors,10,67,76,1,63,2.0,0,42,Urban,ML Engineer,115637,0 +24103,Male,42,Bachelors,6,29,37,69,50,1.0,5,72,Urban,Manager,56285,0 +24104,Female,47,Bachelors,7,88,32,98,21,9.0,3,63,Urban,Software Engineer,26847,1 +24105,Male,55,Bachelors,15,94,75,54,4,8.0,7,92,Semi-Urban,ML Engineer,90017,1 +24106,Female,36,Bachelors,8,56,93,26,90,9.0,5,9,Semi-Urban,Manager,90991,0 +24107,Female,47,Bachelors,14,15,82,47,43,8.0,6,0,Semi-Urban,Data Analyst,41863,0 +24108,Male,50,Diploma,11,49,78,7,29,9.0,1,94,Semi-Urban,Data Analyst,22726,0 +24109,Male,53,Masters,1,66,16,61,15,5.0,5,23,Rural,HR Executive,143035,0 +24110,Female,35,Bachelors,13,1,42,7,95,1.0,1,95,Urban,Software Engineer,102049,0 +24111,Female,54,Diploma,15,45,41,9,87,2.0,4,61,Semi-Urban,Software Engineer,85031,0 +24112,Male,25,Masters,11,40,18,58,78,5.0,0,58,Urban,ML Engineer,104114,0 +24113,Male,32,Masters,3,49,77,37,1,7.0,6,26,Semi-Urban,ML Engineer,67046,0 +24114,Other,55,Masters,4,55,74,67,60,7.0,4,14,Urban,HR Executive,63338,0 +24115,Male,25,Bachelors,13,21,12,24,1,7.0,5,78,Urban,Software Engineer,94782,0 +24116,Male,23,Bachelors,2,69,90,36,70,5.0,6,94,Semi-Urban,Software Engineer,97947,1 +24117,Male,48,High School,7,78,74,88,2,2.0,0,84,Urban,Software Engineer,47443,1 +24118,Male,42,Masters,4,36,22,9,49,0.0,5,55,Rural,Manager,57328,0 +24119,Female,51,High School,2,51,54,69,3,3.0,7,8,Urban,Data Analyst,145763,0 +24120,Female,29,Bachelors,8,50,86,11,0,5.0,6,51,Urban,Manager,50397,0 +24121,Male,47,Bachelors,10,66,76,58,13,2.0,5,4,Urban,Manager,124818,0 +24122,Female,27,Masters,3,67,12,66,66,8.0,4,3,Urban,Data Analyst,105767,0 +24123,Female,41,Diploma,13,55,0,27,72,1.0,0,23,Urban,HR Executive,87887,0 +24124,Male,56,Bachelors,6,6,19,67,48,9.0,5,90,Urban,HR Executive,84046,0 +24125,Male,33,Bachelors,9,75,4,8,3,6.0,4,25,Semi-Urban,Data Analyst,120674,0 +24126,Female,36,Diploma,7,81,38,28,25,2.0,0,87,Urban,Manager,51669,0 +24127,Male,54,Bachelors,10,94,85,66,57,6.0,5,33,Urban,HR Executive,98520,1 +24128,Male,35,Diploma,6,38,79,71,25,5.0,1,51,Semi-Urban,HR Executive,121280,1 +24129,Male,32,High School,12,1,12,88,1,1.0,4,37,Rural,Data Analyst,40889,0 +24130,Other,52,Bachelors,14,96,20,7,35,4.0,2,84,Semi-Urban,Data Analyst,36620,0 +24131,Male,56,Bachelors,0,83,20,72,93,1.0,2,1,Rural,HR Executive,23263,0 +24132,Other,39,Bachelors,10,93,11,29,16,0.0,6,30,Semi-Urban,Manager,95308,0 +24133,Male,32,Masters,17,67,51,61,6,0.0,2,15,Urban,ML Engineer,112495,0 +24134,Female,24,Diploma,8,14,16,83,35,1.0,0,46,Urban,Data Analyst,129258,0 +24135,Male,33,High School,16,92,51,18,4,5.0,0,97,Rural,Manager,21325,1 +24136,Male,51,Bachelors,1,5,5,40,39,1.0,2,18,Urban,ML Engineer,87808,0 +24137,Male,51,Masters,8,2,31,96,78,4.0,6,85,Urban,Manager,45003,0 +24138,Male,27,Diploma,1,97,62,3,47,5.0,2,74,Rural,Software Engineer,26399,1 +24139,Female,32,Bachelors,15,34,16,16,6,1.0,7,14,Semi-Urban,Data Analyst,106122,0 +24140,Female,35,Diploma,17,30,80,21,17,9.0,6,36,Rural,Software Engineer,68623,0 +24141,Male,44,High School,0,77,7,48,54,1.0,0,64,Urban,HR Executive,64843,0 +24142,Female,28,Bachelors,18,78,21,22,9,4.0,5,94,Urban,Software Engineer,92905,0 +24143,Male,21,Diploma,11,42,53,36,5,7.0,2,89,Rural,ML Engineer,132277,0 +24144,Male,31,Masters,9,61,51,32,73,9.0,3,8,Urban,HR Executive,111233,0 +24145,Male,44,Masters,7,77,89,89,31,5.0,4,88,Rural,Manager,66640,1 +24146,Male,59,Bachelors,16,97,21,33,38,5.0,2,21,Semi-Urban,Manager,36490,0 +24147,Female,22,Bachelors,4,75,42,22,64,8.0,5,77,Rural,Data Analyst,30691,0 +24148,Male,42,Diploma,15,49,18,97,99,7.0,3,10,Urban,Software Engineer,74237,0 +24149,Male,53,Diploma,5,21,54,58,29,4.0,0,88,Rural,Data Analyst,56953,0 +24150,Male,37,Masters,19,94,56,18,10,4.0,1,15,Urban,Data Analyst,31595,0 +24151,Male,40,Bachelors,10,33,15,92,86,5.0,0,11,Urban,Software Engineer,28869,0 +24152,Male,22,Masters,6,79,66,51,20,2.0,4,60,Urban,Manager,27589,1 +24153,Male,58,Bachelors,18,50,53,56,49,1.0,6,78,Urban,Software Engineer,42551,1 +24154,Male,24,Masters,18,1,41,21,44,8.0,5,6,Rural,Software Engineer,43567,0 +24155,Female,21,Diploma,3,91,8,55,42,7.0,0,34,Rural,HR Executive,56025,0 +24156,Male,36,Diploma,6,1,72,30,48,8.0,0,76,Urban,ML Engineer,41270,0 +24157,Male,50,High School,17,16,99,86,78,8.0,7,86,Rural,Data Analyst,87328,1 +24158,Male,55,Diploma,17,21,39,30,46,3.0,4,59,Semi-Urban,Software Engineer,61153,0 +24159,Female,33,Masters,19,83,68,51,98,9.0,3,23,Urban,ML Engineer,68496,0 +24160,Male,32,Masters,1,60,37,23,30,4.0,1,40,Urban,ML Engineer,130888,0 +24161,Other,59,Bachelors,16,71,40,92,59,4.0,0,29,Urban,Manager,76355,0 +24162,Other,31,Masters,6,26,5,35,19,8.0,0,88,Semi-Urban,Data Analyst,70101,0 +24163,Female,21,Masters,7,43,25,55,89,1.0,6,15,Urban,HR Executive,71937,0 +24164,Male,42,Diploma,7,96,29,61,3,3.0,5,1,Urban,Manager,27739,0 +24165,Male,36,Bachelors,18,54,87,24,23,4.0,6,2,Rural,ML Engineer,147354,0 +24166,Male,23,Bachelors,10,89,76,38,9,4.0,6,41,Urban,ML Engineer,64203,1 +24167,Female,29,Bachelors,19,40,27,53,88,5.0,2,59,Rural,Manager,32678,0 +24168,Female,46,PhD,18,4,79,5,0,4.0,3,85,Urban,Data Analyst,132403,0 +24169,Other,31,Masters,15,86,69,26,84,2.0,0,22,Urban,Data Analyst,58887,0 +24170,Female,49,High School,12,73,4,40,36,6.0,6,1,Rural,HR Executive,41323,0 +24171,Male,42,Masters,12,99,54,24,90,0.0,7,47,Semi-Urban,ML Engineer,26568,0 +24172,Male,47,Diploma,6,72,11,79,75,2.0,0,44,Urban,Software Engineer,93363,0 +24173,Male,48,Masters,6,10,41,70,95,3.0,4,50,Semi-Urban,ML Engineer,81010,0 +24174,Male,35,Bachelors,14,96,98,30,83,1.0,2,94,Semi-Urban,Data Analyst,99746,1 +24175,Female,23,Bachelors,19,92,69,20,94,1.0,6,94,Rural,Data Analyst,54736,1 +24176,Female,41,Masters,9,65,60,73,94,0.0,1,73,Semi-Urban,Data Analyst,54748,1 +24177,Male,44,Masters,15,17,37,3,50,7.0,0,93,Semi-Urban,ML Engineer,82666,0 +24178,Female,52,Bachelors,14,82,23,36,76,8.0,1,51,Urban,HR Executive,76472,0 +24179,Female,24,Bachelors,1,9,70,44,73,3.0,7,18,Semi-Urban,Software Engineer,94856,0 +24180,Male,59,Diploma,12,49,79,75,76,5.0,6,48,Urban,Data Analyst,96888,1 +24181,Male,40,Masters,5,85,98,93,11,3.0,5,31,Urban,ML Engineer,114497,1 +24182,Female,50,Diploma,10,43,68,88,68,3.0,2,48,Urban,Data Analyst,105351,1 +24183,Male,27,Masters,6,56,79,81,77,4.0,2,9,Semi-Urban,Data Analyst,54518,0 +24184,Male,49,Masters,9,20,9,99,71,6.0,1,1,Semi-Urban,Software Engineer,145891,0 +24185,Male,48,High School,12,58,7,94,40,7.0,4,30,Urban,ML Engineer,124260,0 +24186,Other,30,PhD,19,80,94,60,57,3.0,1,25,Urban,Data Analyst,40768,1 +24187,Male,32,Masters,10,68,63,6,77,8.0,4,24,Urban,Software Engineer,133169,0 +24188,Female,25,Diploma,12,25,62,41,22,6.0,5,31,Rural,Manager,61054,0 +24189,Female,48,Bachelors,11,2,8,65,50,2.0,3,16,Urban,Manager,123084,0 +24190,Female,29,High School,0,41,54,45,14,5.0,3,92,Rural,Manager,57428,0 +24191,Male,23,Bachelors,12,43,56,81,3,8.0,0,62,Urban,HR Executive,82246,1 +24192,Female,27,Diploma,9,66,24,72,52,6.0,3,25,Semi-Urban,Software Engineer,110108,0 +24193,Male,40,Bachelors,16,27,31,63,36,1.0,3,88,Semi-Urban,Software Engineer,102408,0 +24194,Male,21,Bachelors,5,1,27,19,33,2.0,2,59,Urban,Manager,73173,0 +24195,Other,37,Diploma,14,69,65,22,3,9.0,2,3,Urban,Manager,66854,0 +24196,Male,42,Masters,6,78,4,36,93,1.0,1,54,Urban,Manager,69599,0 +24197,Female,49,Bachelors,10,89,36,99,1,9.0,5,84,Rural,HR Executive,146187,1 +24198,Male,55,Bachelors,7,97,21,91,99,3.0,6,54,Semi-Urban,HR Executive,85419,1 +24199,Male,47,Masters,13,44,74,55,74,2.0,6,90,Rural,Manager,51861,1 +24200,Other,44,Bachelors,4,35,0,64,26,0.0,2,30,Semi-Urban,ML Engineer,60671,0 +24201,Female,35,High School,1,31,27,12,51,4.0,6,26,Urban,ML Engineer,58583,0 +24202,Male,28,High School,11,45,83,21,61,7.0,0,64,Rural,Manager,115617,0 +24203,Other,56,High School,19,54,12,48,96,7.0,2,67,Urban,Manager,143128,0 +24204,Female,59,Bachelors,9,47,73,74,96,1.0,0,77,Rural,ML Engineer,101049,1 +24205,Male,56,PhD,2,63,95,58,94,7.0,0,60,Urban,ML Engineer,111043,1 +24206,Female,44,High School,11,30,12,51,20,6.0,7,52,Urban,HR Executive,27549,0 +24207,Male,45,Diploma,17,53,66,35,14,2.0,4,29,Urban,Manager,45578,0 +24208,Male,41,High School,14,92,79,18,70,5.0,0,65,Semi-Urban,Manager,74352,1 +24209,Male,23,Masters,16,63,7,10,70,8.0,5,73,Urban,ML Engineer,117394,0 +24210,Male,26,High School,11,49,15,93,93,3.0,4,54,Urban,HR Executive,85826,0 +24211,Male,30,Bachelors,8,84,95,79,90,4.0,2,98,Urban,Data Analyst,143287,1 +24212,Female,27,Diploma,19,74,57,86,71,0.0,1,16,Semi-Urban,HR Executive,146191,0 +24213,Female,50,Bachelors,1,40,41,69,17,1.0,4,18,Urban,HR Executive,95733,0 +24214,Male,36,Bachelors,1,73,80,34,24,6.0,6,12,Urban,ML Engineer,107225,0 +24215,Female,36,Bachelors,17,89,91,10,80,1.0,7,3,Urban,Manager,122666,0 +24216,Male,45,Diploma,10,77,19,27,49,6.0,5,73,Urban,Software Engineer,28827,0 +24217,Female,46,High School,19,94,91,37,0,0.0,5,86,Semi-Urban,ML Engineer,85419,1 +24218,Male,42,Masters,4,78,3,73,59,8.0,4,29,Semi-Urban,HR Executive,144111,0 +24219,Female,41,High School,14,19,3,25,38,9.0,4,73,Urban,ML Engineer,31487,0 +24220,Female,31,Bachelors,10,85,84,2,15,6.0,2,51,Rural,Manager,33316,0 +24221,Female,47,Diploma,6,69,54,96,20,7.0,6,13,Semi-Urban,ML Engineer,112582,0 +24222,Female,58,High School,5,38,92,40,83,4.0,5,28,Semi-Urban,Data Analyst,52611,0 +24223,Male,31,High School,19,14,30,58,87,5.0,0,80,Semi-Urban,Data Analyst,28467,0 +24224,Female,45,Masters,4,28,8,3,87,9.0,4,0,Urban,HR Executive,68163,0 +24225,Male,54,Masters,12,45,18,22,89,8.0,4,82,Rural,Manager,132919,0 +24226,Male,38,Masters,18,56,79,79,5,9.0,6,73,Rural,Manager,90834,1 +24227,Female,40,Masters,2,87,78,49,92,0.0,3,77,Urban,Manager,135764,1 +24228,Female,35,Bachelors,1,69,19,5,66,6.0,5,79,Urban,Software Engineer,38888,0 +24229,Male,34,Bachelors,8,7,8,90,54,7.0,2,67,Urban,Manager,141404,0 +24230,Male,30,Bachelors,9,61,84,72,92,6.0,3,28,Rural,ML Engineer,62192,1 +24231,Male,22,Bachelors,14,88,68,89,22,4.0,7,91,Urban,HR Executive,82890,1 +24232,Male,43,PhD,0,71,17,66,19,6.0,1,22,Urban,HR Executive,148207,0 +24233,Male,24,High School,9,30,91,97,80,7.0,4,15,Rural,Software Engineer,96212,0 +24234,Male,35,High School,17,6,15,50,85,0.0,7,95,Semi-Urban,Data Analyst,51204,0 +24235,Male,35,High School,10,43,39,10,50,1.0,4,21,Urban,Data Analyst,91197,0 +24236,Other,49,Bachelors,17,87,25,2,16,3.0,6,4,Urban,Software Engineer,102518,0 +24237,Female,53,High School,14,5,18,65,89,5.0,4,45,Semi-Urban,HR Executive,118088,0 +24238,Male,27,PhD,10,59,27,11,11,5.0,3,27,Semi-Urban,Software Engineer,98985,0 +24239,Other,38,Bachelors,11,48,62,94,54,0.0,6,56,Urban,ML Engineer,74185,1 +24240,Female,42,Diploma,8,92,69,77,13,7.0,1,66,Rural,Manager,146350,1 +24241,Male,45,Bachelors,3,67,33,98,82,7.0,5,80,Urban,Software Engineer,41183,1 +24242,Male,24,Masters,18,41,8,87,98,7.0,7,14,Urban,HR Executive,131794,0 +24243,Male,25,Diploma,2,98,57,32,11,9.0,0,43,Urban,Software Engineer,102481,0 +24244,Male,32,High School,1,3,94,60,23,6.0,2,21,Urban,HR Executive,120722,0 +24245,Male,42,PhD,12,51,0,1,53,3.0,6,4,Urban,Manager,71092,0 +24246,Male,43,Masters,9,82,71,70,74,2.0,4,77,Urban,Manager,61218,1 +24247,Male,24,Masters,4,92,85,8,55,0.0,4,51,Semi-Urban,ML Engineer,75448,1 +24248,Female,47,Bachelors,4,49,78,70,55,4.0,2,79,Urban,Software Engineer,77191,1 +24249,Male,22,Bachelors,16,26,17,52,10,6.0,0,36,Urban,Data Analyst,48910,0 +24250,Female,56,High School,3,54,4,83,75,4.0,2,39,Urban,Data Analyst,101613,0 +24251,Male,39,Bachelors,14,76,96,69,39,3.0,7,34,Semi-Urban,Data Analyst,137174,1 +24252,Other,28,Masters,19,24,39,13,39,9.0,4,84,Semi-Urban,ML Engineer,146907,0 +24253,Male,46,Masters,15,99,34,13,39,2.0,2,11,Urban,ML Engineer,44261,0 +24254,Female,35,Bachelors,1,10,32,3,53,1.0,1,64,Urban,Data Analyst,65713,0 +24255,Female,26,Diploma,2,64,75,79,25,0.0,3,33,Urban,Manager,106196,1 +24256,Female,36,Bachelors,12,42,35,95,18,3.0,1,46,Urban,Manager,132582,0 +24257,Female,44,PhD,8,74,14,18,87,5.0,1,23,Urban,Manager,117100,0 +24258,Male,26,Masters,19,24,71,51,97,4.0,6,11,Urban,HR Executive,130576,0 +24259,Other,35,Bachelors,15,14,76,41,98,3.0,1,14,Rural,Manager,47770,0 +24260,Male,23,Diploma,9,0,83,24,10,4.0,7,89,Semi-Urban,ML Engineer,118502,0 +24261,Male,47,Bachelors,8,45,1,60,88,3.0,2,59,Rural,Data Analyst,24689,0 +24262,Male,24,Diploma,19,60,81,49,2,1.0,2,73,Semi-Urban,ML Engineer,101743,1 +24263,Male,27,Bachelors,11,67,87,77,29,9.0,2,20,Urban,HR Executive,61158,1 +24264,Female,58,Diploma,5,28,82,78,32,5.0,6,70,Semi-Urban,Manager,123168,1 +24265,Female,57,Bachelors,3,76,79,79,96,3.0,3,90,Urban,HR Executive,118715,1 +24266,Male,46,Bachelors,16,77,84,66,48,5.0,2,32,Urban,ML Engineer,144473,1 +24267,Other,27,Diploma,6,75,51,46,14,3.0,2,79,Urban,Data Analyst,139695,1 +24268,Male,22,Masters,15,71,40,4,85,4.0,5,55,Urban,HR Executive,98721,0 +24269,Male,48,Bachelors,15,53,55,30,35,2.0,7,10,Urban,Manager,146192,0 +24270,Male,49,Masters,12,37,12,88,68,8.0,0,79,Urban,HR Executive,111613,0 +24271,Female,21,Bachelors,7,61,54,17,51,0.0,2,2,Urban,HR Executive,149525,0 +24272,Male,38,Bachelors,15,24,91,74,82,6.0,1,67,Urban,Data Analyst,22998,1 +24273,Male,39,Masters,13,44,90,16,57,4.0,2,86,Rural,HR Executive,22026,1 +24274,Male,40,Bachelors,6,8,27,64,8,6.0,7,88,Urban,ML Engineer,105373,0 +24275,Male,50,Bachelors,16,32,16,43,30,2.0,4,37,Semi-Urban,Software Engineer,148891,0 +24276,Female,50,Bachelors,17,25,76,48,9,2.0,6,45,Semi-Urban,Manager,96654,0 +24277,Male,27,Bachelors,16,62,17,24,12,7.0,7,8,Rural,Software Engineer,67555,0 +24278,Male,42,Bachelors,17,2,75,56,6,7.0,6,36,Urban,HR Executive,94101,0 +24279,Male,43,Masters,5,74,43,46,81,7.0,6,87,Urban,Software Engineer,43341,1 +24280,Male,55,Bachelors,14,16,82,57,0,3.0,0,23,Urban,HR Executive,22460,0 +24281,Male,35,Diploma,19,30,11,40,35,9.0,5,19,Semi-Urban,ML Engineer,117434,0 +24282,Male,55,Diploma,19,2,79,37,62,8.0,0,85,Urban,ML Engineer,64675,0 +24283,Female,30,Diploma,7,97,15,13,74,4.0,4,42,Urban,Software Engineer,47207,0 +24284,Male,44,Masters,17,18,68,91,38,0.0,0,25,Urban,Software Engineer,60744,0 +24285,Male,58,Bachelors,16,31,95,20,3,1.0,0,33,Semi-Urban,Manager,99301,0 +24286,Male,23,Bachelors,14,82,85,82,63,7.0,2,48,Rural,HR Executive,48175,1 +24287,Male,36,Bachelors,8,32,69,3,35,3.0,6,60,Urban,HR Executive,31770,0 +24288,Male,48,Bachelors,11,83,90,43,93,1.0,3,32,Semi-Urban,HR Executive,22758,1 +24289,Male,46,Bachelors,8,6,15,0,79,2.0,4,83,Semi-Urban,Data Analyst,98414,0 +24290,Male,28,Diploma,12,39,99,66,90,3.0,2,53,Urban,Manager,126780,1 +24291,Female,54,Bachelors,13,19,65,89,82,3.0,2,43,Semi-Urban,Software Engineer,134358,0 +24292,Male,46,Bachelors,1,98,45,78,16,9.0,0,35,Urban,ML Engineer,139279,1 +24293,Female,27,Bachelors,2,42,91,17,55,9.0,3,48,Semi-Urban,HR Executive,62737,0 +24294,Male,56,Bachelors,3,60,52,32,43,8.0,5,45,Urban,Software Engineer,74545,0 +24295,Male,51,Diploma,0,78,10,86,62,6.0,1,95,Urban,Software Engineer,57825,1 +24296,Female,50,Bachelors,15,14,74,40,93,9.0,7,46,Urban,HR Executive,137673,0 +24297,Male,59,Bachelors,16,63,16,49,61,7.0,6,24,Rural,ML Engineer,56479,0 +24298,Male,43,High School,17,81,2,63,35,5.0,4,89,Semi-Urban,Manager,108478,1 +24299,Female,36,High School,10,23,13,37,55,4.0,6,43,Urban,Software Engineer,51180,0 +24300,Female,46,Diploma,8,47,75,51,94,4.0,4,88,Urban,Software Engineer,50993,1 +24301,Other,41,Masters,15,36,69,76,52,4.0,6,22,Rural,Software Engineer,39526,0 +24302,Female,33,Diploma,2,28,45,62,79,5.0,6,6,Urban,Software Engineer,116673,0 +24303,Female,46,Masters,8,62,48,58,34,9.0,1,51,Urban,HR Executive,136651,0 +24304,Male,29,High School,15,8,98,45,92,8.0,4,80,Semi-Urban,HR Executive,136919,0 +24305,Male,26,Masters,0,46,37,50,18,1.0,6,63,Rural,Software Engineer,80699,0 +24306,Male,42,Diploma,9,1,62,48,48,0.0,7,99,Rural,HR Executive,41488,0 +24307,Male,40,Bachelors,10,75,76,13,8,4.0,3,82,Urban,Data Analyst,65102,1 +24308,Male,44,High School,9,20,82,65,55,4.0,5,11,Urban,Data Analyst,45193,0 +24309,Female,45,PhD,1,88,33,90,4,5.0,7,57,Urban,ML Engineer,114151,1 +24310,Male,53,Bachelors,1,92,92,72,34,4.0,1,77,Urban,HR Executive,87302,1 +24311,Female,39,Bachelors,11,23,79,27,39,5.0,0,96,Rural,Software Engineer,28898,0 +24312,Male,59,Diploma,9,81,15,52,43,3.0,4,99,Urban,Manager,25900,1 +24313,Male,28,Diploma,14,89,37,22,36,3.0,1,68,Semi-Urban,Manager,42466,0 +24314,Male,32,Masters,10,13,24,40,24,1.0,2,96,Semi-Urban,HR Executive,43494,0 +24315,Male,48,Bachelors,9,49,93,39,2,3.0,2,22,Urban,HR Executive,77532,0 +24316,Male,51,Diploma,18,62,77,10,31,6.0,2,69,Urban,Data Analyst,92305,0 +24317,Female,36,PhD,4,87,21,89,1,1.0,6,30,Urban,ML Engineer,94122,0 +24318,Male,57,Diploma,13,57,98,80,37,5.0,1,54,Urban,HR Executive,125179,1 +24319,Male,50,Bachelors,12,19,2,4,6,5.0,3,81,Semi-Urban,Software Engineer,35645,0 +24320,Female,26,PhD,14,54,85,10,7,2.0,3,93,Rural,ML Engineer,58545,1 +24321,Male,45,Masters,2,72,74,7,48,0.0,5,69,Urban,HR Executive,131358,0 +24322,Male,39,PhD,18,45,56,35,97,0.0,3,40,Urban,Manager,100669,0 +24323,Male,50,Bachelors,7,18,8,4,91,0.0,6,21,Rural,Data Analyst,36191,0 +24324,Male,57,High School,15,98,86,90,65,8.0,7,49,Urban,HR Executive,66670,1 +24325,Female,43,High School,15,83,77,82,25,5.0,3,68,Urban,Data Analyst,76988,1 +24326,Female,48,Diploma,8,8,30,82,85,3.0,0,74,Semi-Urban,HR Executive,139123,0 +24327,Female,46,Diploma,16,96,8,84,8,2.0,3,45,Semi-Urban,ML Engineer,133305,0 +24328,Male,22,Bachelors,15,19,64,99,16,4.0,6,38,Urban,Data Analyst,135978,0 +24329,Female,24,Bachelors,3,5,49,45,33,2.0,4,71,Urban,ML Engineer,66152,0 +24330,Male,40,Bachelors,10,92,46,80,35,3.0,0,79,Semi-Urban,Manager,63309,1 +24331,Male,59,Bachelors,12,4,25,12,72,1.0,3,57,Urban,Data Analyst,23066,0 +24332,Male,59,Bachelors,10,43,20,78,92,2.0,5,7,Rural,HR Executive,43273,0 +24333,Female,56,Bachelors,3,62,32,28,75,6.0,5,24,Semi-Urban,Data Analyst,25858,0 +24334,Female,42,Bachelors,18,87,29,9,62,6.0,2,12,Rural,ML Engineer,137336,0 +24335,Female,27,Diploma,8,46,91,8,27,6.0,6,50,Rural,ML Engineer,67806,0 +24336,Female,44,Bachelors,3,2,61,17,21,5.0,5,78,Semi-Urban,HR Executive,103625,0 +24337,Male,37,Masters,2,9,3,51,87,1.0,7,11,Rural,Data Analyst,84257,0 +24338,Male,51,Bachelors,6,42,71,74,4,6.0,5,12,Semi-Urban,ML Engineer,87219,0 +24339,Female,45,Masters,17,32,18,20,98,1.0,4,11,Urban,Software Engineer,98020,0 +24340,Female,56,Bachelors,15,23,37,57,47,0.0,1,65,Urban,Manager,93048,0 +24341,Female,25,Masters,14,69,48,24,26,4.0,5,50,Urban,ML Engineer,99180,0 +24342,Male,40,Bachelors,7,73,85,48,40,3.0,3,13,Semi-Urban,HR Executive,116397,0 +24343,Female,37,Masters,2,67,17,67,72,5.0,4,97,Semi-Urban,Manager,27560,1 +24344,Male,41,Bachelors,9,99,67,18,38,9.0,5,54,Urban,Manager,55454,1 +24345,Female,42,Diploma,1,82,54,87,53,1.0,2,39,Semi-Urban,HR Executive,64459,1 +24346,Male,51,Bachelors,13,75,60,1,3,2.0,6,97,Urban,ML Engineer,21796,0 +24347,Female,54,Bachelors,10,42,30,24,73,4.0,0,51,Urban,ML Engineer,135930,0 +24348,Male,48,Bachelors,1,48,46,7,30,9.0,5,29,Rural,ML Engineer,35041,0 +24349,Female,25,Bachelors,4,66,28,79,56,9.0,3,29,Rural,Software Engineer,116903,0 +24350,Male,45,Bachelors,19,47,65,44,92,2.0,3,94,Semi-Urban,HR Executive,55023,1 +24351,Male,57,High School,9,14,8,78,73,3.0,5,26,Semi-Urban,Data Analyst,111269,0 +24352,Male,44,Bachelors,12,50,20,63,25,0.0,0,53,Urban,HR Executive,80832,0 +24353,Female,28,High School,8,2,49,9,95,6.0,7,16,Semi-Urban,Data Analyst,123353,0 +24354,Male,53,Bachelors,12,76,81,41,94,6.0,1,81,Urban,Data Analyst,135855,1 +24355,Male,26,Diploma,8,78,34,62,49,9.0,7,72,Rural,Manager,145553,1 +24356,Other,34,Diploma,16,12,99,39,34,9.0,5,19,Urban,ML Engineer,44281,0 +24357,Female,53,Diploma,15,72,39,58,45,7.0,4,65,Urban,ML Engineer,94545,0 +24358,Male,26,Diploma,5,3,96,1,26,4.0,3,59,Semi-Urban,Manager,82821,0 +24359,Male,38,Masters,10,26,45,95,1,8.0,5,12,Urban,Software Engineer,147239,0 +24360,Male,34,Bachelors,3,98,38,45,98,5.0,2,28,Semi-Urban,ML Engineer,119010,0 +24361,Female,51,PhD,5,24,59,58,34,9.0,7,61,Semi-Urban,Data Analyst,148729,0 +24362,Female,38,Bachelors,12,18,25,36,81,5.0,6,54,Semi-Urban,Software Engineer,36825,0 +24363,Female,53,PhD,10,73,30,1,24,5.0,4,57,Semi-Urban,Software Engineer,52372,0 +24364,Male,43,High School,18,98,64,73,41,6.0,4,22,Semi-Urban,Data Analyst,65662,1 +24365,Female,44,Bachelors,5,9,18,22,90,9.0,0,8,Urban,Data Analyst,99650,0 +24366,Male,57,Masters,5,41,47,24,83,7.0,4,43,Semi-Urban,HR Executive,32761,0 +24367,Male,39,Bachelors,0,16,70,0,16,4.0,2,76,Semi-Urban,Data Analyst,59057,0 +24368,Female,55,High School,7,85,32,15,1,4.0,4,45,Semi-Urban,Software Engineer,131416,0 +24369,Male,44,Diploma,11,0,36,9,62,6.0,0,45,Semi-Urban,HR Executive,95168,0 +24370,Male,40,Masters,16,78,65,73,51,5.0,6,23,Rural,Software Engineer,94372,1 +24371,Female,52,PhD,1,72,71,75,97,9.0,7,97,Semi-Urban,HR Executive,85448,1 +24372,Male,37,Diploma,0,35,31,90,10,0.0,0,43,Urban,Software Engineer,63165,0 +24373,Male,52,Masters,10,23,35,4,68,8.0,5,60,Semi-Urban,Manager,98471,0 +24374,Female,48,Bachelors,2,22,55,90,34,0.0,5,69,Rural,Software Engineer,144725,0 +24375,Female,38,PhD,18,26,70,58,39,4.0,1,34,Semi-Urban,Manager,55908,0 +24376,Female,46,Bachelors,7,78,43,40,13,1.0,6,55,Rural,Software Engineer,54383,0 +24377,Male,28,Diploma,12,29,47,11,15,1.0,2,50,Urban,Data Analyst,76055,0 +24378,Male,45,PhD,16,35,85,55,91,5.0,5,74,Urban,Manager,132659,1 +24379,Male,53,Bachelors,2,28,95,22,4,3.0,0,20,Rural,Data Analyst,26273,0 +24380,Female,49,Bachelors,5,4,2,72,55,9.0,1,35,Urban,Software Engineer,148993,0 +24381,Male,57,Masters,17,92,73,93,44,8.0,3,72,Urban,ML Engineer,79762,1 +24382,Female,40,Bachelors,4,22,43,50,82,1.0,7,3,Rural,Manager,48354,0 +24383,Male,32,Bachelors,0,42,67,29,71,5.0,6,30,Urban,Manager,53030,0 +24384,Male,54,Diploma,3,8,82,88,24,2.0,3,51,Rural,Manager,95296,0 +24385,Female,39,High School,3,52,99,21,49,2.0,0,55,Semi-Urban,HR Executive,59383,0 +24386,Female,21,High School,0,8,62,6,27,6.0,5,78,Rural,Data Analyst,115214,0 +24387,Female,32,High School,13,35,59,71,80,5.0,0,76,Rural,Software Engineer,27685,1 +24388,Female,35,Bachelors,12,58,30,47,39,9.0,0,12,Urban,HR Executive,123378,0 +24389,Other,52,High School,15,8,63,91,27,5.0,6,92,Urban,Software Engineer,64138,1 +24390,Female,59,Bachelors,5,42,62,94,61,8.0,1,46,Urban,Manager,137126,1 +24391,Female,56,PhD,11,10,11,22,58,2.0,3,57,Urban,Manager,130437,0 +24392,Female,57,Diploma,9,21,19,28,85,0.0,2,90,Semi-Urban,ML Engineer,138621,0 +24393,Female,48,Bachelors,2,96,36,96,48,4.0,4,0,Semi-Urban,ML Engineer,143979,0 +24394,Male,57,Bachelors,14,3,8,42,81,2.0,6,55,Urban,HR Executive,108737,0 +24395,Male,48,Bachelors,7,62,65,94,80,5.0,5,73,Semi-Urban,ML Engineer,65815,1 +24396,Male,53,High School,17,40,41,86,46,9.0,2,75,Urban,HR Executive,80330,1 +24397,Male,47,Bachelors,12,83,70,26,72,1.0,4,21,Semi-Urban,ML Engineer,79155,0 +24398,Male,43,Masters,8,45,47,21,94,7.0,6,1,Urban,Manager,59427,0 +24399,Male,53,Diploma,10,43,38,11,37,9.0,5,86,Urban,Software Engineer,47486,0 +24400,Female,29,Diploma,2,64,64,82,97,0.0,0,36,Urban,HR Executive,139215,1 +24401,Female,46,High School,0,91,79,74,9,0.0,4,79,Urban,ML Engineer,111264,1 +24402,Male,21,Diploma,14,76,48,61,86,4.0,0,13,Urban,Manager,138672,0 +24403,Male,47,Bachelors,6,57,4,97,99,8.0,4,73,Urban,HR Executive,78875,0 +24404,Female,44,Masters,12,56,16,38,83,1.0,4,38,Semi-Urban,ML Engineer,57777,0 +24405,Female,54,Bachelors,15,8,26,27,9,5.0,0,65,Urban,Software Engineer,140438,0 +24406,Female,43,Masters,5,58,19,91,59,0.0,6,68,Rural,Software Engineer,76006,0 +24407,Other,53,Bachelors,13,59,22,61,70,8.0,4,59,Urban,HR Executive,56822,0 +24408,Other,42,Masters,2,43,63,72,4,4.0,5,79,Urban,HR Executive,85416,1 +24409,Male,38,Diploma,8,54,17,4,14,5.0,5,81,Urban,ML Engineer,114566,0 +24410,Male,42,Diploma,8,21,19,84,91,9.0,0,42,Urban,Software Engineer,54522,0 +24411,Female,32,Bachelors,16,35,73,14,39,0.0,6,26,Urban,Data Analyst,72130,0 +24412,Male,24,Bachelors,14,98,75,24,70,1.0,3,82,Rural,Data Analyst,124235,1 +24413,Female,26,Masters,14,40,91,99,29,0.0,5,96,Semi-Urban,ML Engineer,32961,1 +24414,Male,22,High School,4,49,85,70,10,2.0,5,77,Semi-Urban,Data Analyst,44311,1 +24415,Female,30,Bachelors,10,37,17,99,60,2.0,1,83,Urban,Software Engineer,118593,0 +24416,Male,43,Bachelors,16,64,41,35,11,8.0,6,44,Urban,ML Engineer,70629,0 +24417,Male,39,Bachelors,15,92,94,76,87,3.0,0,76,Urban,Manager,89206,1 +24418,Male,44,High School,3,95,28,19,95,1.0,1,60,Urban,ML Engineer,135863,0 +24419,Female,42,Bachelors,12,20,25,46,73,8.0,1,88,Urban,HR Executive,72110,0 +24420,Male,34,Diploma,5,96,16,33,71,0.0,4,83,Urban,ML Engineer,64395,0 +24421,Female,46,High School,4,89,4,53,99,9.0,1,7,Semi-Urban,Manager,132919,0 +24422,Female,42,Diploma,10,55,94,12,55,2.0,1,97,Urban,Manager,37880,1 +24423,Female,43,Masters,13,96,11,88,74,7.0,2,2,Urban,Software Engineer,76048,0 +24424,Female,21,High School,13,54,92,7,40,9.0,3,57,Semi-Urban,Data Analyst,138731,0 +24425,Female,59,Bachelors,16,87,43,5,11,2.0,3,40,Urban,Manager,45414,0 +24426,Male,53,Bachelors,13,45,65,68,52,4.0,0,29,Urban,ML Engineer,144780,0 +24427,Male,46,High School,4,79,95,99,88,4.0,4,72,Urban,Data Analyst,36275,1 +24428,Female,47,Bachelors,9,67,85,23,75,8.0,0,23,Urban,Software Engineer,63674,0 +24429,Female,52,Masters,8,93,6,72,6,8.0,1,31,Rural,ML Engineer,107511,0 +24430,Male,55,Bachelors,5,33,74,33,9,0.0,0,90,Urban,Data Analyst,44378,0 +24431,Female,44,Bachelors,14,78,43,79,37,1.0,5,62,Urban,ML Engineer,118993,1 +24432,Male,32,Masters,3,70,88,52,99,8.0,1,1,Urban,Software Engineer,78964,0 +24433,Male,32,Masters,7,29,38,70,68,7.0,7,16,Semi-Urban,Manager,86283,0 +24434,Male,56,Bachelors,17,62,43,46,61,3.0,3,39,Urban,Manager,139681,0 +24435,Male,26,High School,16,2,26,47,0,8.0,5,55,Urban,HR Executive,39608,0 +24436,Male,52,High School,2,98,15,58,71,1.0,7,32,Urban,Data Analyst,37382,0 +24437,Male,44,Masters,12,87,25,90,35,7.0,3,52,Rural,ML Engineer,139214,1 +24438,Male,47,High School,11,37,12,27,49,1.0,1,72,Urban,Manager,127004,0 +24439,Male,23,Bachelors,13,4,52,11,60,0.0,4,52,Urban,Software Engineer,99397,0 +24440,Male,52,PhD,16,51,30,23,19,0.0,6,30,Urban,Data Analyst,41971,0 +24441,Male,44,Diploma,12,25,18,45,72,9.0,3,84,Urban,HR Executive,81152,0 +24442,Male,27,Bachelors,8,33,6,2,1,0.0,1,23,Urban,Software Engineer,108746,0 +24443,Male,52,Bachelors,6,28,39,96,65,4.0,4,83,Semi-Urban,Software Engineer,105402,1 +24444,Male,48,Bachelors,2,20,32,44,39,1.0,2,82,Rural,HR Executive,47742,0 +24445,Male,29,High School,17,81,74,45,69,4.0,1,3,Urban,ML Engineer,103346,0 +24446,Female,29,High School,6,34,47,98,42,3.0,6,6,Rural,HR Executive,84889,0 +24447,Male,24,Masters,14,99,19,62,62,6.0,4,49,Urban,ML Engineer,130766,0 +24448,Male,58,PhD,18,95,19,67,86,8.0,2,72,Semi-Urban,Software Engineer,55586,1 +24449,Male,56,Bachelors,15,80,15,93,56,5.0,2,32,Urban,Software Engineer,76909,0 +24450,Male,23,Masters,11,16,13,39,72,9.0,0,86,Rural,Software Engineer,76130,0 +24451,Female,49,Bachelors,11,13,15,32,70,4.0,5,58,Semi-Urban,Software Engineer,63240,0 +24452,Male,27,Bachelors,4,67,39,89,65,2.0,5,10,Semi-Urban,Manager,77056,0 +24453,Male,27,Bachelors,10,27,2,39,39,1.0,5,30,Urban,Manager,110324,0 +24454,Male,30,Bachelors,19,30,18,81,82,4.0,3,2,Urban,Manager,57044,0 +24455,Male,24,Bachelors,7,84,45,4,86,8.0,6,81,Semi-Urban,HR Executive,21913,0 +24456,Male,46,Diploma,15,11,58,97,5,6.0,6,52,Semi-Urban,HR Executive,56158,0 +24457,Female,24,Bachelors,3,0,41,34,20,4.0,2,99,Semi-Urban,Data Analyst,133913,0 +24458,Male,45,PhD,13,6,94,63,66,7.0,7,30,Urban,Software Engineer,123592,0 +24459,Male,33,High School,11,66,38,77,81,0.0,5,76,Urban,ML Engineer,52142,1 +24460,Female,45,PhD,15,65,13,89,67,1.0,5,78,Urban,Software Engineer,96994,1 +24461,Female,47,Masters,12,49,20,52,33,7.0,0,3,Urban,Software Engineer,38249,0 +24462,Female,22,Bachelors,7,27,43,82,38,2.0,7,9,Rural,Software Engineer,44972,0 +24463,Male,47,Diploma,15,45,96,22,23,0.0,0,53,Rural,Software Engineer,63417,0 +24464,Male,22,Bachelors,5,48,3,10,66,5.0,7,89,Rural,Data Analyst,68777,0 +24465,Male,59,Bachelors,10,72,82,36,35,7.0,2,34,Rural,Software Engineer,126975,0 +24466,Female,34,Diploma,1,40,96,28,31,6.0,6,67,Urban,ML Engineer,112097,0 +24467,Male,54,High School,14,27,20,41,81,5.0,2,80,Urban,Software Engineer,121941,0 +24468,Male,42,Bachelors,2,25,96,6,63,3.0,7,38,Semi-Urban,Software Engineer,34705,0 +24469,Female,55,Bachelors,17,78,29,7,66,0.0,4,25,Urban,Data Analyst,93413,0 +24470,Female,38,PhD,15,60,68,9,54,6.0,1,24,Semi-Urban,Software Engineer,26616,0 +24471,Male,38,High School,14,7,54,54,15,9.0,7,65,Rural,HR Executive,94419,0 +24472,Female,26,High School,4,65,9,78,26,9.0,2,87,Semi-Urban,Software Engineer,68303,0 +24473,Female,34,Bachelors,19,46,63,26,40,8.0,1,5,Semi-Urban,Manager,66921,0 +24474,Male,27,Bachelors,2,79,84,65,72,7.0,7,70,Urban,HR Executive,90271,1 +24475,Female,46,Masters,14,94,42,64,0,8.0,6,63,Urban,Data Analyst,26876,1 +24476,Male,46,Masters,5,49,57,6,55,0.0,3,64,Urban,Data Analyst,135097,0 +24477,Female,41,Masters,1,48,80,96,36,9.0,1,30,Urban,HR Executive,28907,1 +24478,Female,40,Diploma,17,11,51,4,44,0.0,0,12,Urban,Software Engineer,58897,0 +24479,Male,25,High School,10,11,66,73,41,9.0,3,75,Urban,Data Analyst,27285,0 +24480,Male,22,Masters,18,35,53,67,33,8.0,1,97,Urban,Data Analyst,132810,1 +24481,Female,53,High School,13,41,60,95,27,3.0,5,78,Urban,Manager,50149,1 +24482,Male,45,Masters,8,79,65,79,9,7.0,6,77,Rural,HR Executive,88454,1 +24483,Male,41,Diploma,4,79,4,9,6,8.0,2,25,Semi-Urban,Software Engineer,46707,0 +24484,Male,55,Masters,1,94,85,29,50,5.0,0,34,Urban,HR Executive,138557,1 +24485,Female,30,Bachelors,6,85,19,84,4,1.0,3,77,Urban,HR Executive,144616,1 +24486,Female,30,High School,15,42,0,83,92,7.0,3,72,Urban,ML Engineer,94466,0 +24487,Male,37,Diploma,1,14,70,91,40,0.0,4,70,Rural,Software Engineer,58265,1 +24488,Female,56,Masters,15,73,40,18,72,9.0,5,69,Semi-Urban,Data Analyst,32986,0 +24489,Male,43,Masters,13,29,95,52,13,3.0,7,99,Urban,Manager,68696,1 +24490,Other,28,Bachelors,14,66,70,17,18,5.0,1,4,Urban,Manager,125238,0 +24491,Male,28,Bachelors,3,29,49,2,72,2.0,7,34,Semi-Urban,ML Engineer,68432,0 +24492,Male,50,Bachelors,18,44,88,57,8,7.0,5,89,Urban,ML Engineer,105530,1 +24493,Male,46,Bachelors,5,65,62,95,41,1.0,5,52,Urban,Manager,86227,1 +24494,Male,25,Bachelors,7,4,3,13,94,2.0,3,2,Urban,HR Executive,28946,0 +24495,Male,32,Bachelors,0,67,78,12,74,5.0,6,43,Urban,Data Analyst,81702,0 +24496,Female,53,Bachelors,2,49,24,92,26,6.0,5,19,Urban,Software Engineer,110888,0 +24497,Male,43,Masters,7,28,29,8,20,7.0,5,75,Urban,ML Engineer,94346,0 +24498,Other,47,Diploma,6,25,82,44,87,6.0,6,85,Semi-Urban,ML Engineer,23658,0 +24499,Female,35,PhD,7,56,10,17,30,7.0,1,23,Semi-Urban,Manager,120707,0 +24500,Female,37,Bachelors,12,5,98,5,80,8.0,1,77,Urban,HR Executive,91373,0 +24501,Male,56,Bachelors,2,87,25,39,26,5.0,4,51,Semi-Urban,Manager,43271,0 +24502,Female,32,Diploma,17,23,96,47,72,7.0,6,42,Urban,ML Engineer,127633,0 +24503,Female,33,Diploma,8,52,22,86,69,5.0,6,93,Rural,Data Analyst,78965,1 +24504,Female,53,Diploma,17,57,0,0,38,9.0,2,46,Urban,ML Engineer,109584,0 +24505,Other,22,Bachelors,6,32,42,98,54,6.0,5,9,Rural,ML Engineer,86049,0 +24506,Male,30,Bachelors,7,86,43,72,63,5.0,1,94,Urban,HR Executive,36728,1 +24507,Male,54,Bachelors,0,55,30,1,35,0.0,3,90,Rural,Software Engineer,59766,0 +24508,Female,46,Bachelors,9,48,18,60,16,8.0,3,87,Urban,HR Executive,84472,0 +24509,Female,26,Masters,19,65,92,96,82,3.0,4,70,Semi-Urban,ML Engineer,141095,1 +24510,Male,37,Masters,1,80,38,82,98,7.0,6,88,Rural,Manager,122778,1 +24511,Male,57,Bachelors,14,63,49,83,49,8.0,1,13,Urban,Data Analyst,64984,0 +24512,Female,37,Diploma,3,2,74,61,10,8.0,3,92,Urban,Software Engineer,96876,0 +24513,Male,49,Diploma,14,82,93,12,33,6.0,7,7,Urban,Data Analyst,23398,0 +24514,Male,47,Masters,8,65,38,89,10,9.0,2,88,Rural,Manager,107088,1 +24515,Male,27,Bachelors,15,86,92,36,10,3.0,1,85,Semi-Urban,Data Analyst,127196,1 +24516,Male,44,Diploma,2,95,50,58,73,9.0,0,33,Semi-Urban,ML Engineer,119394,1 +24517,Male,49,High School,16,16,97,73,2,9.0,4,15,Urban,HR Executive,91191,0 +24518,Other,28,High School,9,46,9,4,71,4.0,0,43,Urban,Software Engineer,127441,0 +24519,Female,58,Bachelors,0,67,61,50,83,5.0,1,1,Rural,ML Engineer,81209,0 +24520,Female,28,Bachelors,17,63,40,58,22,2.0,3,99,Urban,Data Analyst,130391,1 +24521,Female,36,High School,3,48,91,44,24,1.0,0,93,Urban,Software Engineer,120145,1 +24522,Male,30,Diploma,9,18,32,54,56,0.0,1,55,Urban,HR Executive,136431,0 +24523,Female,24,Bachelors,3,34,81,24,45,7.0,6,22,Semi-Urban,HR Executive,50140,0 +24524,Female,44,Bachelors,16,63,19,77,0,3.0,4,82,Urban,Manager,108131,1 +24525,Female,58,Bachelors,13,92,74,8,36,3.0,7,12,Urban,Data Analyst,87606,0 +24526,Female,22,Masters,5,1,41,48,53,1.0,6,57,Rural,Data Analyst,97424,0 +24527,Male,27,Diploma,12,10,84,89,95,8.0,2,59,Rural,ML Engineer,42376,1 +24528,Male,23,Masters,14,19,80,41,10,8.0,5,51,Urban,HR Executive,88743,0 +24529,Male,39,Bachelors,19,46,6,48,53,9.0,2,67,Urban,Software Engineer,58360,0 +24530,Other,29,Bachelors,15,83,30,74,67,5.0,7,84,Semi-Urban,ML Engineer,46895,1 +24531,Male,53,Bachelors,19,76,62,75,1,5.0,3,15,Semi-Urban,HR Executive,67991,0 +24532,Female,49,Bachelors,13,0,6,66,20,8.0,4,68,Rural,HR Executive,89625,0 +24533,Male,50,PhD,4,73,17,64,49,9.0,7,12,Urban,HR Executive,110507,0 +24534,Female,52,Diploma,10,15,21,23,41,4.0,3,72,Urban,Data Analyst,25779,0 +24535,Male,39,High School,11,11,62,69,33,7.0,2,71,Rural,ML Engineer,149541,0 +24536,Male,24,Bachelors,16,4,41,73,83,2.0,5,46,Urban,Software Engineer,63041,0 +24537,Male,41,High School,14,35,72,30,51,7.0,6,8,Rural,HR Executive,125800,0 +24538,Female,39,Masters,6,8,37,93,75,6.0,2,45,Semi-Urban,Software Engineer,85303,0 +24539,Male,43,Bachelors,5,30,4,8,36,3.0,7,51,Urban,HR Executive,83197,0 +24540,Female,51,Masters,7,90,4,59,40,8.0,5,57,Semi-Urban,HR Executive,128764,0 +24541,Male,32,Masters,17,49,69,12,84,6.0,0,1,Semi-Urban,Manager,53554,0 +24542,Female,23,Masters,18,60,33,98,92,6.0,0,84,Semi-Urban,ML Engineer,130294,1 +24543,Male,40,Bachelors,15,25,20,93,86,5.0,4,72,Urban,Manager,146886,0 +24544,Female,46,Bachelors,3,62,64,78,52,7.0,6,49,Semi-Urban,Manager,127949,1 +24545,Male,58,Diploma,9,12,83,79,85,8.0,0,22,Urban,HR Executive,75429,0 +24546,Female,26,Bachelors,1,19,76,3,47,1.0,5,60,Semi-Urban,ML Engineer,35078,0 +24547,Male,29,Bachelors,13,54,79,0,27,1.0,0,66,Rural,ML Engineer,95877,0 +24548,Female,54,Diploma,9,42,38,89,78,6.0,3,68,Semi-Urban,Software Engineer,38688,0 +24549,Female,45,Bachelors,13,9,68,44,27,2.0,2,92,Semi-Urban,ML Engineer,136044,0 +24550,Male,48,Diploma,19,65,36,39,72,1.0,0,90,Semi-Urban,Data Analyst,42373,0 +24551,Male,55,High School,12,7,42,78,50,9.0,2,17,Urban,Software Engineer,42844,0 +24552,Female,29,Diploma,5,42,35,13,19,4.0,0,52,Urban,Manager,22560,0 +24553,Female,38,Bachelors,19,7,63,13,70,8.0,1,17,Urban,Manager,54014,0 +24554,Male,48,Bachelors,19,48,13,58,67,5.0,6,89,Urban,HR Executive,136837,0 +24555,Male,32,Masters,6,81,6,38,75,4.0,5,80,Urban,Manager,48882,0 +24556,Male,42,Diploma,3,74,46,50,85,6.0,2,23,Urban,Data Analyst,61444,0 +24557,Male,45,Masters,11,75,68,31,46,6.0,5,71,Semi-Urban,Software Engineer,38048,1 +24558,Male,54,Bachelors,4,32,11,63,84,4.0,4,28,Urban,Manager,107274,0 +24559,Female,49,Diploma,8,41,33,44,42,5.0,3,55,Urban,HR Executive,86856,0 +24560,Male,29,Diploma,16,64,77,69,72,9.0,1,75,Semi-Urban,Software Engineer,104480,1 +24561,Male,49,Masters,18,84,19,9,61,6.0,4,60,Rural,ML Engineer,67601,0 +24562,Female,22,Bachelors,14,94,64,32,24,1.0,6,14,Urban,ML Engineer,37321,0 +24563,Male,41,Bachelors,2,3,35,28,62,4.0,5,14,Urban,Manager,74267,0 +24564,Female,48,Diploma,7,74,42,51,46,5.0,0,67,Rural,Data Analyst,86810,0 +24565,Female,25,Diploma,6,1,61,52,97,6.0,0,60,Urban,ML Engineer,97861,0 +24566,Male,46,Masters,12,51,71,97,23,9.0,0,75,Urban,Manager,65267,1 +24567,Male,21,Diploma,7,41,39,9,24,5.0,7,41,Urban,HR Executive,96692,0 +24568,Other,40,Bachelors,0,18,27,41,60,7.0,7,51,Urban,ML Engineer,95017,0 +24569,Other,41,Bachelors,11,54,6,31,59,5.0,7,41,Semi-Urban,HR Executive,110574,0 +24570,Male,22,Bachelors,14,27,24,89,55,5.0,6,19,Semi-Urban,Data Analyst,124902,0 +24571,Male,33,Bachelors,16,85,47,10,20,5.0,0,17,Urban,HR Executive,85197,0 +24572,Male,48,Bachelors,7,24,33,17,8,0.0,5,5,Urban,ML Engineer,61010,0 +24573,Male,36,Bachelors,0,56,90,14,18,2.0,4,42,Semi-Urban,Data Analyst,142820,0 +24574,Male,22,PhD,19,92,75,94,74,3.0,5,88,Semi-Urban,Manager,90786,1 +24575,Female,37,Bachelors,16,0,10,90,43,8.0,5,71,Urban,Manager,81787,0 +24576,Female,29,Masters,8,54,75,92,65,4.0,4,60,Urban,ML Engineer,59898,1 +24577,Male,26,Bachelors,3,75,84,28,90,0.0,5,55,Urban,ML Engineer,74076,1 +24578,Female,22,Masters,1,41,57,89,88,7.0,4,64,Semi-Urban,Data Analyst,138961,1 +24579,Male,52,Bachelors,19,18,72,66,85,0.0,6,43,Rural,ML Engineer,45357,0 +24580,Male,40,Diploma,18,53,87,45,27,3.0,3,39,Urban,Data Analyst,30330,0 +24581,Male,41,Bachelors,2,94,25,85,54,6.0,6,84,Urban,Data Analyst,89636,1 +24582,Male,44,Diploma,7,78,92,66,61,0.0,5,66,Semi-Urban,ML Engineer,69281,1 +24583,Male,52,Bachelors,3,59,67,69,6,7.0,2,21,Urban,HR Executive,87740,0 +24584,Female,35,High School,0,7,54,34,84,1.0,5,27,Semi-Urban,ML Engineer,117947,0 +24585,Male,59,High School,13,19,2,13,17,3.0,0,67,Urban,Software Engineer,36501,0 +24586,Female,42,High School,2,10,70,73,34,9.0,7,60,Semi-Urban,Data Analyst,70352,0 +24587,Male,58,Bachelors,0,27,66,3,84,8.0,2,45,Semi-Urban,HR Executive,93784,0 +24588,Male,56,Masters,19,44,15,86,43,0.0,4,41,Urban,Manager,80857,0 +24589,Male,36,Bachelors,12,37,40,57,91,6.0,7,47,Rural,Software Engineer,72828,0 +24590,Female,24,High School,13,92,91,97,64,0.0,1,73,Urban,Data Analyst,98928,1 +24591,Male,28,Diploma,14,5,67,86,17,1.0,4,99,Rural,ML Engineer,130065,1 +24592,Female,53,High School,3,67,55,15,3,7.0,6,90,Urban,HR Executive,46563,0 +24593,Female,44,Diploma,11,37,94,13,40,1.0,4,49,Semi-Urban,Manager,41340,0 +24594,Female,34,Diploma,19,39,68,77,15,7.0,1,19,Semi-Urban,Software Engineer,44336,0 +24595,Male,44,Bachelors,13,50,23,8,16,2.0,1,54,Urban,HR Executive,141759,0 +24596,Female,36,High School,12,60,82,84,48,8.0,3,76,Semi-Urban,Data Analyst,64263,1 +24597,Male,50,Bachelors,2,6,92,46,17,1.0,3,46,Urban,HR Executive,104036,0 +24598,Female,43,High School,1,52,26,46,97,8.0,6,10,Urban,HR Executive,135912,0 +24599,Male,35,Masters,14,70,0,46,88,3.0,1,39,Semi-Urban,ML Engineer,130515,0 +24600,Male,42,Bachelors,6,63,26,35,82,0.0,0,0,Semi-Urban,HR Executive,134379,0 +24601,Male,57,Bachelors,5,33,23,18,47,4.0,1,78,Urban,HR Executive,36733,0 +24602,Male,38,Bachelors,5,73,45,19,78,9.0,1,64,Urban,Manager,39578,0 +24603,Male,33,High School,9,74,61,21,32,3.0,4,15,Urban,Software Engineer,116725,0 +24604,Female,40,Masters,3,66,64,37,0,2.0,7,53,Semi-Urban,ML Engineer,97562,0 +24605,Female,54,Diploma,3,68,80,6,52,7.0,7,11,Urban,Software Engineer,101782,0 +24606,Male,57,Bachelors,0,85,77,98,88,8.0,4,8,Urban,Software Engineer,57711,1 +24607,Male,24,Masters,18,55,13,54,84,0.0,5,2,Rural,Data Analyst,24350,0 +24608,Male,24,Masters,18,99,86,26,67,3.0,2,69,Semi-Urban,Software Engineer,139273,1 +24609,Male,29,Bachelors,0,89,47,35,15,3.0,0,24,Rural,HR Executive,54050,0 +24610,Other,32,High School,16,64,10,10,71,4.0,5,11,Rural,ML Engineer,83330,0 +24611,Female,42,Bachelors,12,2,57,22,77,7.0,4,0,Rural,Manager,140804,0 +24612,Male,52,Bachelors,13,62,42,50,22,6.0,0,80,Urban,Manager,59103,0 +24613,Male,33,Masters,0,56,56,76,33,5.0,6,97,Urban,ML Engineer,56983,1 +24614,Female,59,High School,7,72,26,34,45,2.0,0,6,Urban,HR Executive,79517,0 +24615,Female,27,Masters,0,93,78,71,10,0.0,7,59,Urban,Data Analyst,72099,1 +24616,Male,43,Diploma,4,98,48,89,78,4.0,5,62,Semi-Urban,Manager,89111,1 +24617,Male,34,Diploma,15,82,96,77,68,7.0,4,0,Urban,HR Executive,83889,1 +24618,Male,59,Bachelors,5,96,4,6,77,9.0,3,62,Urban,Data Analyst,56603,0 +24619,Male,37,Masters,6,82,93,42,93,1.0,1,84,Semi-Urban,HR Executive,149719,1 +24620,Male,27,Bachelors,11,53,90,96,7,8.0,7,84,Urban,Manager,83027,1 +24621,Male,39,Bachelors,17,6,60,23,67,6.0,6,36,Semi-Urban,ML Engineer,147263,0 +24622,Female,29,Masters,7,55,48,62,99,5.0,3,81,Urban,Software Engineer,23897,1 +24623,Male,23,Diploma,8,61,47,14,73,7.0,7,73,Urban,HR Executive,25971,0 +24624,Female,41,High School,1,88,92,39,41,0.0,2,20,Urban,Software Engineer,57434,0 +24625,Male,58,Diploma,16,69,71,2,41,6.0,2,46,Urban,Software Engineer,41041,0 +24626,Male,33,Bachelors,15,90,76,92,93,5.0,5,5,Urban,Manager,125955,1 +24627,Male,31,Bachelors,10,56,68,38,31,3.0,2,22,Rural,Manager,129483,0 +24628,Male,43,Bachelors,2,75,90,73,61,2.0,7,11,Urban,Software Engineer,51600,1 +24629,Female,34,Bachelors,7,55,62,35,93,8.0,1,75,Urban,Software Engineer,41148,0 +24630,Male,38,Bachelors,13,51,55,13,60,1.0,2,23,Urban,Data Analyst,97138,0 +24631,Male,30,Masters,0,82,38,1,48,8.0,4,22,Urban,Manager,30988,0 +24632,Female,46,High School,2,2,84,99,36,0.0,5,22,Rural,Manager,116265,0 +24633,Male,26,Diploma,0,6,66,66,20,7.0,5,57,Urban,Manager,60682,0 +24634,Male,43,Diploma,3,24,35,23,29,2.0,7,55,Urban,Data Analyst,75192,0 +24635,Male,25,Bachelors,13,43,59,84,20,7.0,7,15,Urban,Data Analyst,117555,0 +24636,Male,59,Diploma,14,18,93,7,6,5.0,0,96,Semi-Urban,Manager,102477,0 +24637,Male,58,Diploma,17,47,76,88,76,8.0,4,81,Semi-Urban,Manager,35640,1 +24638,Male,48,Diploma,14,18,53,29,60,1.0,0,5,Urban,HR Executive,100209,0 +24639,Female,32,High School,9,27,19,59,36,3.0,1,15,Rural,Software Engineer,85146,0 +24640,Female,31,Bachelors,19,16,91,31,57,5.0,6,63,Rural,Manager,147440,0 +24641,Male,45,Diploma,10,39,34,49,4,6.0,6,61,Semi-Urban,HR Executive,66639,0 +24642,Male,52,Bachelors,15,81,11,38,19,5.0,4,37,Rural,Software Engineer,38129,0 +24643,Male,49,Bachelors,14,13,28,2,39,3.0,6,5,Semi-Urban,Data Analyst,139126,0 +24644,Male,29,Bachelors,14,88,23,57,51,3.0,4,92,Urban,ML Engineer,118880,1 +24645,Male,42,Bachelors,16,44,88,16,61,6.0,5,47,Semi-Urban,Manager,90139,0 +24646,Female,32,Diploma,3,28,90,65,17,2.0,1,68,Rural,HR Executive,88351,1 +24647,Female,24,Bachelors,1,93,25,96,90,4.0,3,33,Rural,Manager,40026,1 +24648,Male,27,Diploma,9,6,1,8,5,5.0,4,18,Urban,Data Analyst,53317,0 +24649,Female,45,Diploma,2,84,42,18,45,4.0,1,32,Urban,Data Analyst,115391,0 +24650,Male,24,High School,9,95,59,49,60,5.0,0,83,Rural,Manager,22014,1 +24651,Male,36,Bachelors,2,86,99,16,68,6.0,6,90,Rural,Software Engineer,74290,1 +24652,Male,53,Diploma,11,6,7,66,51,6.0,6,3,Urban,HR Executive,70475,0 +24653,Male,25,Bachelors,6,87,75,83,69,3.0,6,47,Urban,Data Analyst,123142,1 +24654,Female,24,Masters,10,0,20,58,29,9.0,1,15,Urban,Software Engineer,127703,0 +24655,Male,49,Diploma,4,92,62,38,67,7.0,4,30,Urban,Data Analyst,69260,0 +24656,Male,39,Diploma,18,19,21,37,58,8.0,2,91,Urban,HR Executive,110147,0 +24657,Other,54,Masters,6,69,69,96,56,3.0,0,27,Semi-Urban,HR Executive,129811,1 +24658,Male,36,Bachelors,1,60,60,88,38,2.0,3,78,Urban,Software Engineer,140512,1 +24659,Male,22,High School,2,74,6,18,74,0.0,5,2,Urban,Software Engineer,70892,0 +24660,Male,29,Diploma,7,3,46,26,93,8.0,7,44,Semi-Urban,Manager,105620,0 +24661,Male,53,Bachelors,17,99,48,61,37,2.0,4,90,Urban,Manager,28247,1 +24662,Other,39,Diploma,18,47,0,94,32,1.0,5,84,Semi-Urban,ML Engineer,76519,0 +24663,Male,49,Masters,9,64,62,86,85,7.0,6,56,Semi-Urban,Data Analyst,139235,1 +24664,Female,38,Diploma,3,58,61,16,73,7.0,4,40,Semi-Urban,Software Engineer,46509,0 +24665,Male,34,Diploma,15,94,51,92,61,4.0,3,68,Rural,Manager,78770,1 +24666,Male,27,Masters,15,94,10,8,83,7.0,3,30,Urban,Software Engineer,21730,0 +24667,Male,32,High School,16,49,94,33,13,0.0,6,36,Urban,HR Executive,145859,0 +24668,Female,28,Bachelors,1,18,85,73,20,7.0,3,10,Urban,Data Analyst,120293,0 +24669,Male,35,Masters,6,98,55,19,96,8.0,6,82,Rural,Software Engineer,70669,1 +24670,Female,35,High School,16,30,55,74,68,7.0,2,62,Urban,HR Executive,61302,0 +24671,Male,28,Bachelors,3,84,91,16,7,2.0,4,66,Urban,ML Engineer,47536,1 +24672,Male,40,Bachelors,16,37,56,76,87,8.0,5,98,Urban,HR Executive,54301,1 +24673,Male,23,Bachelors,6,20,17,70,14,5.0,6,11,Semi-Urban,Software Engineer,119791,0 +24674,Female,31,Masters,7,45,80,76,61,0.0,5,15,Rural,ML Engineer,120923,0 +24675,Male,47,Bachelors,13,77,6,8,23,7.0,0,39,Semi-Urban,Data Analyst,143053,0 +24676,Male,54,PhD,12,10,85,21,18,7.0,5,92,Rural,ML Engineer,85960,0 +24677,Male,50,Masters,6,17,42,79,10,8.0,5,36,Urban,Manager,138628,0 +24678,Female,56,Bachelors,14,46,47,53,46,9.0,6,48,Urban,Software Engineer,126741,0 +24679,Female,54,Masters,19,44,99,30,35,4.0,1,3,Urban,Manager,146121,0 +24680,Female,55,Bachelors,19,75,54,65,67,0.0,1,12,Urban,Manager,137496,0 +24681,Male,22,Diploma,8,28,96,16,75,9.0,3,13,Semi-Urban,Data Analyst,98868,0 +24682,Other,41,Masters,7,45,59,68,49,8.0,4,85,Rural,Manager,145287,1 +24683,Female,43,Bachelors,12,11,52,22,47,1.0,0,36,Rural,Manager,40778,0 +24684,Male,35,Bachelors,13,50,13,37,35,5.0,6,16,Urban,ML Engineer,120315,0 +24685,Male,28,Diploma,9,74,83,96,26,4.0,1,1,Urban,Manager,86659,1 +24686,Male,42,Diploma,12,48,8,89,93,1.0,1,22,Urban,ML Engineer,148542,0 +24687,Male,27,Bachelors,16,95,21,64,70,2.0,0,90,Urban,Data Analyst,140472,1 +24688,Female,42,Bachelors,12,85,18,84,31,0.0,5,78,Urban,ML Engineer,124791,1 +24689,Female,57,Masters,1,94,65,53,21,7.0,4,13,Urban,Manager,70108,0 +24690,Female,46,High School,9,22,30,32,72,0.0,7,82,Urban,HR Executive,117570,0 +24691,Male,30,Bachelors,7,25,60,73,56,5.0,2,76,Urban,Software Engineer,113237,0 +24692,Male,36,Bachelors,15,82,70,84,36,8.0,5,70,Urban,ML Engineer,108561,1 +24693,Male,21,Bachelors,2,65,49,82,15,8.0,4,84,Urban,Data Analyst,149300,1 +24694,Male,53,Bachelors,15,82,11,19,23,2.0,6,62,Rural,HR Executive,132982,0 +24695,Female,55,Masters,9,72,3,66,18,9.0,3,32,Urban,HR Executive,116650,0 +24696,Male,24,Diploma,4,4,30,23,8,4.0,3,49,Rural,ML Engineer,116153,0 +24697,Female,44,Masters,10,25,29,93,61,4.0,6,10,Rural,ML Engineer,71160,0 +24698,Female,35,Diploma,16,47,96,34,4,8.0,0,75,Urban,Manager,110092,1 +24699,Female,25,Bachelors,15,68,93,26,70,8.0,3,69,Urban,HR Executive,96036,1 +24700,Male,48,Bachelors,19,85,84,6,38,6.0,6,17,Semi-Urban,Data Analyst,117808,0 +24701,Female,45,Bachelors,13,27,73,14,31,3.0,3,43,Semi-Urban,Software Engineer,116226,0 +24702,Other,29,High School,0,28,24,3,50,8.0,1,36,Semi-Urban,Manager,22960,0 +24703,Female,21,Bachelors,16,76,16,31,95,7.0,0,77,Semi-Urban,Manager,137447,0 +24704,Female,39,Diploma,13,7,84,96,34,6.0,4,95,Semi-Urban,Data Analyst,135775,1 +24705,Female,36,High School,14,64,13,86,56,3.0,0,40,Semi-Urban,Software Engineer,110473,0 +24706,Male,37,Bachelors,14,14,53,7,31,4.0,3,56,Urban,ML Engineer,46206,0 +24707,Female,22,Diploma,7,42,6,26,56,9.0,3,25,Urban,Software Engineer,123017,0 +24708,Female,41,Diploma,17,30,32,87,62,2.0,2,26,Urban,HR Executive,94042,0 +24709,Female,44,Diploma,6,15,14,26,66,3.0,5,61,Semi-Urban,Manager,42580,0 +24710,Female,30,Diploma,9,65,65,93,28,7.0,6,95,Urban,ML Engineer,54146,1 +24711,Male,26,High School,17,15,31,16,46,7.0,6,78,Urban,Data Analyst,81564,0 +24712,Male,34,High School,12,70,1,13,75,4.0,5,55,Urban,HR Executive,39687,0 +24713,Male,40,High School,7,28,33,88,72,4.0,5,11,Semi-Urban,ML Engineer,106312,0 +24714,Male,35,Diploma,0,3,72,34,56,5.0,3,70,Semi-Urban,Manager,146406,0 +24715,Male,38,Bachelors,16,69,84,22,50,1.0,7,36,Urban,HR Executive,87067,0 +24716,Male,49,High School,5,51,7,75,4,4.0,3,54,Rural,HR Executive,56269,0 +24717,Male,36,Bachelors,17,32,97,12,4,0.0,0,86,Rural,Manager,130532,0 +24718,Female,36,PhD,0,17,50,24,24,0.0,1,15,Urban,Data Analyst,141845,0 +24719,Male,25,Bachelors,19,11,97,71,42,3.0,6,20,Urban,ML Engineer,86040,0 +24720,Male,47,High School,5,6,99,71,61,6.0,4,76,Rural,Manager,95035,1 +24721,Male,48,Masters,2,82,97,54,25,3.0,6,68,Urban,Software Engineer,24632,1 +24722,Male,52,Masters,13,74,5,72,92,1.0,2,22,Urban,HR Executive,50849,0 +24723,Male,26,Masters,10,29,20,68,25,6.0,3,34,Rural,Data Analyst,72083,0 +24724,Male,21,Bachelors,11,22,0,79,75,4.0,4,56,Rural,ML Engineer,79965,0 +24725,Female,31,Bachelors,7,27,68,4,54,2.0,4,30,Urban,Software Engineer,85148,0 +24726,Male,28,Masters,2,47,68,62,44,5.0,5,86,Urban,HR Executive,59346,1 +24727,Female,41,Diploma,3,24,11,92,65,4.0,3,27,Urban,Manager,44893,0 +24728,Female,34,Bachelors,9,60,67,82,93,3.0,5,43,Rural,Software Engineer,139670,1 +24729,Other,45,Diploma,4,14,68,83,68,9.0,7,41,Urban,ML Engineer,30216,0 +24730,Male,34,Masters,0,30,17,52,36,4.0,1,73,Urban,Software Engineer,22576,0 +24731,Male,48,Bachelors,11,58,0,22,97,1.0,1,43,Semi-Urban,Data Analyst,126568,0 +24732,Male,31,Masters,5,19,79,41,65,9.0,7,88,Urban,ML Engineer,74125,0 +24733,Male,29,Diploma,10,1,76,1,15,8.0,2,28,Semi-Urban,Data Analyst,67081,0 +24734,Male,39,Bachelors,14,96,31,7,40,8.0,3,68,Rural,HR Executive,70878,0 +24735,Female,44,High School,12,4,15,60,67,1.0,4,17,Urban,Data Analyst,67509,0 +24736,Male,41,High School,7,45,76,14,66,9.0,3,99,Urban,HR Executive,134463,0 +24737,Male,39,Diploma,5,95,18,98,40,9.0,2,75,Urban,HR Executive,63035,1 +24738,Male,41,Masters,10,50,50,97,69,2.0,1,16,Rural,HR Executive,134967,0 +24739,Other,58,Bachelors,10,11,51,10,96,5.0,7,98,Urban,HR Executive,52867,0 +24740,Female,33,Diploma,9,16,18,92,63,6.0,5,19,Rural,ML Engineer,137959,0 +24741,Male,42,PhD,5,9,40,16,37,2.0,2,10,Rural,ML Engineer,45711,0 +24742,Male,22,Diploma,7,30,5,48,70,7.0,5,96,Semi-Urban,HR Executive,87071,0 +24743,Male,40,Bachelors,9,11,19,91,94,0.0,0,16,Rural,ML Engineer,100779,0 +24744,Female,24,Masters,15,55,54,39,6,7.0,5,7,Urban,Manager,38651,0 +24745,Female,53,Diploma,13,40,99,97,46,0.0,5,35,Urban,Software Engineer,62794,1 +24746,Female,51,Masters,4,52,28,91,88,9.0,4,80,Rural,HR Executive,37328,1 +24747,Male,49,Masters,11,4,33,79,19,8.0,3,98,Urban,Software Engineer,111364,0 +24748,Female,25,Masters,13,24,70,33,67,4.0,5,8,Urban,ML Engineer,47665,0 +24749,Female,24,Bachelors,0,69,24,40,62,6.0,4,62,Urban,ML Engineer,79651,0 +24750,Other,23,Bachelors,0,53,66,70,1,8.0,7,20,Semi-Urban,Manager,52486,0 +24751,Male,54,Masters,16,67,81,56,61,7.0,3,43,Rural,Manager,131500,1 +24752,Male,26,Bachelors,12,94,7,58,12,4.0,0,85,Urban,Software Engineer,136023,1 +24753,Male,52,Diploma,18,63,37,60,81,9.0,7,47,Urban,ML Engineer,70428,0 +24754,Male,37,Masters,15,2,84,86,76,6.0,0,47,Semi-Urban,Manager,21322,0 +24755,Female,46,Bachelors,16,61,53,50,68,6.0,2,53,Semi-Urban,Software Engineer,31819,0 +24756,Female,40,Diploma,2,43,19,74,84,5.0,4,67,Urban,Software Engineer,51023,0 +24757,Male,36,Masters,5,81,50,22,90,4.0,7,80,Urban,ML Engineer,25132,0 +24758,Male,21,Diploma,3,36,95,90,67,4.0,7,32,Semi-Urban,Data Analyst,106475,1 +24759,Male,51,Diploma,18,82,58,18,8,3.0,6,3,Urban,ML Engineer,32670,0 +24760,Female,48,Masters,1,22,96,62,77,2.0,4,86,Semi-Urban,Software Engineer,127382,1 +24761,Male,46,Bachelors,10,65,50,91,46,4.0,4,29,Urban,Manager,64473,1 +24762,Male,51,Bachelors,16,67,82,83,56,8.0,5,11,Semi-Urban,ML Engineer,63965,1 +24763,Male,52,Masters,19,77,93,57,37,9.0,4,18,Semi-Urban,ML Engineer,97616,1 +24764,Male,58,Diploma,3,90,91,56,31,6.0,7,81,Semi-Urban,Software Engineer,117355,1 +24765,Female,57,Masters,5,46,36,88,59,6.0,7,69,Semi-Urban,HR Executive,42447,0 +24766,Female,42,High School,10,54,28,23,84,5.0,2,76,Urban,Manager,131969,0 +24767,Male,29,Diploma,15,72,97,67,47,2.0,3,24,Semi-Urban,Data Analyst,117799,1 +24768,Female,45,Diploma,8,60,61,47,72,9.0,7,88,Rural,Software Engineer,85090,1 +24769,Male,56,Masters,4,18,73,42,69,3.0,6,11,Urban,ML Engineer,47543,0 +24770,Other,33,Bachelors,6,18,90,79,96,7.0,6,5,Rural,Manager,63554,0 +24771,Male,50,Bachelors,18,0,10,94,20,6.0,4,82,Urban,ML Engineer,69807,0 +24772,Male,57,Diploma,7,90,93,67,79,2.0,0,28,Urban,ML Engineer,26951,1 +24773,Male,50,Bachelors,18,25,42,35,36,0.0,0,93,Semi-Urban,Data Analyst,96061,0 +24774,Male,33,Bachelors,13,38,48,87,72,0.0,3,80,Urban,Manager,49184,1 +24775,Male,23,High School,13,52,69,78,73,1.0,0,63,Urban,ML Engineer,136890,1 +24776,Female,37,Diploma,14,70,0,21,77,4.0,7,55,Rural,ML Engineer,79586,0 +24777,Female,21,Masters,16,38,51,92,54,6.0,7,19,Urban,Manager,136084,0 +24778,Male,31,Diploma,0,76,84,47,52,2.0,4,36,Semi-Urban,Data Analyst,106278,1 +24779,Female,24,High School,14,5,23,68,34,8.0,1,52,Semi-Urban,ML Engineer,104680,0 +24780,Male,33,Bachelors,3,62,40,85,64,4.0,2,2,Urban,Data Analyst,138491,0 +24781,Female,41,PhD,10,48,9,18,92,8.0,0,93,Urban,Manager,57002,0 +24782,Male,52,Bachelors,18,65,91,69,85,2.0,2,82,Urban,Data Analyst,95292,1 +24783,Female,46,Bachelors,7,61,37,31,11,4.0,2,64,Rural,Manager,123004,0 +24784,Male,21,PhD,4,18,77,65,2,2.0,4,26,Urban,HR Executive,103166,0 +24785,Male,41,High School,5,76,20,28,90,4.0,1,87,Urban,Software Engineer,115111,0 +24786,Male,32,High School,1,61,72,75,11,7.0,2,8,Rural,ML Engineer,131111,0 +24787,Male,29,Bachelors,0,48,33,20,11,6.0,7,11,Urban,HR Executive,107532,0 +24788,Female,56,Masters,7,98,16,93,57,0.0,0,86,Semi-Urban,Manager,75334,1 +24789,Male,29,High School,16,11,57,76,11,5.0,7,20,Semi-Urban,Manager,73129,0 +24790,Male,42,Bachelors,17,29,25,67,37,3.0,3,54,Urban,ML Engineer,31079,0 +24791,Male,23,Bachelors,1,46,35,73,29,1.0,5,74,Semi-Urban,Software Engineer,86896,0 +24792,Male,22,Bachelors,3,64,34,32,40,6.0,6,98,Semi-Urban,Data Analyst,23582,0 +24793,Female,52,Bachelors,18,12,38,94,55,5.0,3,11,Semi-Urban,Manager,135281,0 +24794,Male,30,High School,3,11,87,0,56,4.0,5,66,Urban,Data Analyst,90239,0 +24795,Female,55,Masters,2,21,8,40,56,6.0,1,77,Rural,Manager,106479,0 +24796,Male,48,Masters,10,64,61,12,99,4.0,6,98,Urban,Software Engineer,99502,1 +24797,Female,24,Bachelors,11,51,51,31,40,1.0,7,59,Urban,Data Analyst,92911,0 +24798,Other,57,Bachelors,4,20,18,41,98,9.0,3,46,Urban,Data Analyst,94362,0 +24799,Female,31,Diploma,17,24,91,98,24,7.0,5,65,Semi-Urban,Data Analyst,122410,1 +24800,Female,42,Masters,10,58,19,21,71,0.0,7,69,Urban,Software Engineer,80743,0 +24801,Male,51,Masters,2,48,92,7,92,6.0,4,42,Urban,Data Analyst,69158,0 +24802,Female,52,Bachelors,13,80,57,31,99,0.0,1,25,Semi-Urban,HR Executive,61068,0 +24803,Female,58,High School,8,7,35,39,82,6.0,7,22,Urban,HR Executive,119164,0 +24804,Other,54,Masters,14,56,88,46,95,7.0,1,17,Urban,Manager,116532,0 +24805,Female,31,Bachelors,19,30,64,75,54,5.0,1,47,Urban,ML Engineer,36820,0 +24806,Female,37,Bachelors,9,79,63,1,19,2.0,3,17,Urban,Software Engineer,45410,0 +24807,Male,57,Masters,12,64,58,44,49,7.0,3,86,Urban,ML Engineer,103580,1 +24808,Male,40,Masters,3,14,96,43,8,7.0,7,67,Urban,Software Engineer,149163,0 +24809,Male,55,High School,14,72,70,19,23,5.0,4,88,Urban,Data Analyst,85962,1 +24810,Female,33,Bachelors,2,44,96,56,86,9.0,5,43,Semi-Urban,ML Engineer,121612,0 +24811,Male,45,Masters,4,41,33,92,1,7.0,7,33,Urban,Data Analyst,43678,0 +24812,Male,51,Bachelors,1,2,18,64,85,5.0,7,23,Urban,Software Engineer,140590,0 +24813,Male,36,Diploma,18,11,41,83,18,3.0,1,92,Rural,Manager,111710,0 +24814,Male,41,Diploma,9,6,0,32,39,2.0,3,38,Rural,Data Analyst,63410,0 +24815,Female,30,PhD,10,35,36,76,42,1.0,7,84,Semi-Urban,Software Engineer,49615,0 +24816,Female,53,Masters,8,96,59,10,50,7.0,5,56,Semi-Urban,Data Analyst,106933,0 +24817,Male,59,Masters,11,89,57,72,90,2.0,3,77,Urban,HR Executive,24581,1 +24818,Male,51,Bachelors,8,91,96,92,82,5.0,3,49,Semi-Urban,Software Engineer,68796,1 +24819,Male,35,Bachelors,6,23,13,57,4,3.0,0,2,Urban,Data Analyst,113111,0 +24820,Male,29,Bachelors,17,95,20,4,99,4.0,0,89,Urban,Data Analyst,99186,0 +24821,Male,32,Bachelors,18,54,50,19,21,1.0,3,7,Semi-Urban,Manager,121545,0 +24822,Male,37,High School,3,15,80,6,28,6.0,4,87,Rural,HR Executive,47347,0 +24823,Male,43,Bachelors,11,61,65,39,1,6.0,2,24,Urban,HR Executive,42360,0 +24824,Male,55,Masters,11,68,28,7,34,2.0,0,46,Semi-Urban,Data Analyst,132926,0 +24825,Female,52,Masters,14,96,15,49,86,8.0,6,9,Urban,Manager,86237,0 +24826,Male,23,Bachelors,3,18,16,42,31,1.0,3,92,Rural,Manager,61440,0 +24827,Male,58,Bachelors,18,46,33,2,54,3.0,0,63,Urban,Software Engineer,25423,0 +24828,Male,44,High School,16,48,38,95,27,4.0,2,42,Urban,Software Engineer,58254,0 +24829,Other,32,Bachelors,0,88,85,48,9,1.0,0,48,Urban,HR Executive,130887,1 +24830,Male,45,High School,9,56,35,47,25,8.0,7,31,Semi-Urban,HR Executive,69498,0 +24831,Male,24,Bachelors,0,55,69,60,15,9.0,0,36,Rural,ML Engineer,91858,0 +24832,Male,53,Bachelors,15,63,93,64,3,6.0,6,86,Urban,Manager,127541,1 +24833,Female,21,PhD,6,41,0,11,77,5.0,6,47,Urban,Manager,127917,0 +24834,Female,57,PhD,0,13,5,57,88,6.0,0,75,Urban,Data Analyst,93038,0 +24835,Female,53,Bachelors,11,65,39,81,87,6.0,4,45,Urban,Manager,147255,0 +24836,Male,40,Diploma,5,19,33,98,78,5.0,3,61,Urban,ML Engineer,35458,0 +24837,Female,28,Diploma,8,77,60,84,13,1.0,4,91,Semi-Urban,Manager,46732,1 +24838,Female,40,Bachelors,0,66,34,61,96,6.0,0,40,Urban,HR Executive,22737,0 +24839,Male,24,Masters,14,43,57,10,78,2.0,0,18,Rural,Manager,149673,0 +24840,Female,51,Masters,19,83,88,18,96,4.0,4,42,Rural,HR Executive,89231,0 +24841,Male,23,Masters,1,30,90,35,49,2.0,2,90,Urban,ML Engineer,147122,1 +24842,Male,28,Bachelors,0,78,34,79,56,4.0,2,17,Rural,HR Executive,139156,0 +24843,Female,37,High School,18,82,98,59,53,5.0,5,11,Semi-Urban,Manager,142416,1 +24844,Female,58,Masters,19,45,34,20,28,4.0,6,14,Urban,ML Engineer,50899,0 +24845,Male,27,Masters,18,86,70,64,74,8.0,7,22,Urban,ML Engineer,113423,1 +24846,Male,30,Bachelors,9,20,29,41,6,1.0,1,36,Rural,ML Engineer,72173,0 +24847,Female,59,Masters,0,7,20,81,59,5.0,1,23,Semi-Urban,HR Executive,120108,0 +24848,Male,27,Diploma,5,60,81,86,45,0.0,0,0,Semi-Urban,Manager,28147,0 +24849,Male,24,Bachelors,3,66,72,86,78,1.0,3,82,Urban,Manager,61845,1 +24850,Male,21,Bachelors,8,2,75,13,78,1.0,0,24,Urban,Data Analyst,45723,0 +24851,Female,44,Bachelors,5,39,5,78,76,0.0,0,54,Semi-Urban,ML Engineer,39134,0 +24852,Female,41,High School,6,82,71,86,96,7.0,0,35,Semi-Urban,ML Engineer,26435,1 +24853,Male,58,Bachelors,8,20,82,15,96,9.0,1,27,Urban,HR Executive,77094,0 +24854,Male,26,Masters,18,39,49,73,94,0.0,4,70,Urban,Manager,31868,0 +24855,Male,49,High School,9,81,9,96,81,2.0,6,38,Urban,ML Engineer,34193,0 +24856,Male,22,Bachelors,7,54,15,24,52,1.0,3,21,Semi-Urban,ML Engineer,33263,0 +24857,Female,39,Masters,13,17,86,55,89,4.0,7,93,Rural,Data Analyst,28090,1 +24858,Male,58,Bachelors,11,77,99,97,78,0.0,7,61,Semi-Urban,HR Executive,40373,1 +24859,Male,32,Bachelors,8,79,60,85,90,8.0,3,34,Semi-Urban,Data Analyst,123238,1 +24860,Female,37,Bachelors,3,19,18,23,24,1.0,0,55,Urban,Software Engineer,58974,0 +24861,Male,46,High School,6,86,60,73,7,5.0,0,40,Semi-Urban,Data Analyst,38452,1 +24862,Male,41,Bachelors,2,35,46,49,88,0.0,3,33,Urban,HR Executive,47320,0 +24863,Male,46,Diploma,0,83,88,66,54,6.0,4,1,Urban,Data Analyst,37854,1 +24864,Female,41,Diploma,17,38,64,36,60,7.0,3,56,Urban,Data Analyst,90210,0 +24865,Male,41,Bachelors,9,84,95,30,14,4.0,2,32,Semi-Urban,Data Analyst,95209,1 +24866,Male,34,Bachelors,19,23,71,91,98,6.0,0,10,Rural,Data Analyst,41224,0 +24867,Male,55,Bachelors,6,5,50,29,73,4.0,5,55,Urban,Data Analyst,121090,0 +24868,Other,36,Diploma,9,67,53,51,85,9.0,4,53,Rural,ML Engineer,122534,0 +24869,Male,33,Bachelors,1,95,67,63,71,9.0,1,66,Urban,Data Analyst,22905,1 +24870,Other,57,Diploma,17,59,93,19,95,4.0,3,31,Urban,Software Engineer,96830,0 +24871,Female,27,High School,12,37,6,66,28,5.0,7,61,Urban,Data Analyst,94036,0 +24872,Female,52,Masters,4,54,93,11,58,4.0,4,14,Rural,Data Analyst,111811,0 +24873,Male,22,High School,17,40,40,57,83,0.0,2,19,Urban,HR Executive,149954,0 +24874,Male,21,Diploma,4,85,83,2,49,0.0,3,21,Urban,Manager,88870,0 +24875,Male,28,Bachelors,2,28,88,90,13,5.0,2,55,Rural,Data Analyst,128131,1 +24876,Male,55,Bachelors,15,75,34,86,74,0.0,3,27,Rural,Software Engineer,59061,0 +24877,Other,58,Diploma,1,51,23,65,68,8.0,3,30,Rural,Manager,93366,0 +24878,Male,50,Bachelors,19,50,31,66,3,5.0,5,35,Semi-Urban,Data Analyst,138304,0 +24879,Male,53,High School,9,41,44,7,52,4.0,3,81,Semi-Urban,ML Engineer,92601,0 +24880,Male,42,Bachelors,9,76,91,13,45,9.0,5,63,Rural,Manager,79286,1 +24881,Female,47,Bachelors,1,57,17,13,35,2.0,5,78,Rural,Manager,136970,0 +24882,Male,28,Bachelors,13,12,97,26,84,6.0,5,94,Urban,Data Analyst,72749,0 +24883,Male,42,Masters,9,5,91,77,77,5.0,3,44,Semi-Urban,HR Executive,63646,0 +24884,Male,27,Bachelors,16,66,52,54,35,3.0,6,27,Rural,Manager,56022,0 +24885,Female,51,Bachelors,16,9,67,46,40,6.0,4,42,Urban,Manager,29773,0 +24886,Male,53,Diploma,19,73,36,11,1,8.0,3,28,Urban,Software Engineer,98925,0 +24887,Male,27,Diploma,7,15,46,33,74,0.0,2,45,Urban,Software Engineer,119094,0 +24888,Male,35,Bachelors,6,13,83,18,8,8.0,2,57,Urban,Manager,126885,0 +24889,Other,24,Bachelors,18,51,40,55,38,5.0,2,0,Urban,HR Executive,118698,0 +24890,Male,31,Masters,16,57,1,99,91,2.0,2,38,Rural,Software Engineer,27451,0 +24891,Female,43,Masters,17,90,33,53,22,5.0,6,17,Urban,ML Engineer,48775,0 +24892,Female,27,High School,12,11,79,11,26,5.0,5,61,Semi-Urban,Data Analyst,136969,0 +24893,Male,48,Bachelors,1,71,10,45,11,0.0,4,55,Rural,Data Analyst,93897,0 +24894,Male,22,Diploma,11,68,22,0,51,2.0,7,75,Urban,Software Engineer,139940,0 +24895,Male,37,Bachelors,4,91,28,62,18,9.0,7,98,Semi-Urban,Data Analyst,78950,1 +24896,Male,44,Bachelors,4,2,46,33,71,2.0,1,48,Urban,Manager,113448,0 +24897,Male,52,Masters,12,86,63,37,33,2.0,4,74,Urban,HR Executive,52874,1 +24898,Male,55,Masters,19,81,56,16,78,1.0,5,88,Urban,Manager,67562,1 +24899,Male,21,Bachelors,0,93,1,97,27,3.0,4,61,Semi-Urban,Data Analyst,127811,1 +24900,Male,39,Diploma,10,28,8,77,72,6.0,5,16,Urban,Software Engineer,149763,0 +24901,Female,43,Masters,5,99,68,59,29,4.0,7,88,Rural,ML Engineer,64255,1 +24902,Female,36,Bachelors,17,82,95,31,93,9.0,5,80,Rural,HR Executive,35310,1 +24903,Male,52,Diploma,15,99,76,11,25,7.0,3,73,Urban,Manager,43724,1 +24904,Male,55,Bachelors,4,29,71,82,33,2.0,4,62,Urban,HR Executive,65911,1 +24905,Female,38,Diploma,19,95,64,12,99,2.0,0,78,Urban,Manager,108531,1 +24906,Female,28,PhD,15,24,68,98,85,3.0,1,71,Urban,ML Engineer,77524,1 +24907,Other,41,PhD,19,96,3,53,88,1.0,1,27,Urban,Data Analyst,93985,0 +24908,Male,32,Bachelors,6,39,63,16,65,4.0,4,54,Urban,ML Engineer,69900,0 +24909,Male,56,Bachelors,4,78,35,23,25,0.0,3,33,Rural,Manager,117833,0 +24910,Male,50,Masters,4,95,98,89,64,9.0,1,89,Semi-Urban,ML Engineer,143425,1 +24911,Female,56,Diploma,19,52,59,28,75,2.0,4,13,Rural,Data Analyst,60289,0 +24912,Male,56,High School,14,97,0,54,12,5.0,6,84,Semi-Urban,Data Analyst,52659,1 +24913,Male,26,Diploma,8,57,92,84,3,2.0,3,75,Urban,HR Executive,136958,1 +24914,Male,41,Masters,15,46,13,78,36,4.0,5,14,Urban,Software Engineer,43189,0 +24915,Female,33,Masters,15,8,66,55,25,0.0,4,84,Semi-Urban,HR Executive,77745,0 +24916,Male,32,Bachelors,17,54,69,64,14,3.0,7,59,Urban,ML Engineer,31277,1 +24917,Female,46,Diploma,3,81,27,44,64,7.0,1,0,Urban,ML Engineer,129752,0 +24918,Female,51,Bachelors,6,27,43,30,71,6.0,2,36,Urban,Software Engineer,55625,0 +24919,Female,49,Diploma,17,23,0,0,97,3.0,1,59,Urban,ML Engineer,107532,0 +24920,Male,46,Masters,5,50,98,65,87,0.0,6,20,Urban,Software Engineer,130023,0 +24921,Other,23,High School,3,99,21,65,52,9.0,0,49,Rural,Data Analyst,108437,0 +24922,Male,29,Bachelors,7,52,80,12,64,0.0,6,65,Urban,Data Analyst,56617,0 +24923,Male,27,Diploma,2,59,49,71,94,0.0,0,20,Semi-Urban,Data Analyst,53458,0 +24924,Other,35,Diploma,17,39,61,34,14,1.0,0,19,Urban,Manager,87810,0 +24925,Male,27,Bachelors,5,34,73,39,7,9.0,0,67,Urban,Software Engineer,96340,0 +24926,Male,28,Bachelors,15,90,71,46,87,4.0,0,25,Urban,Data Analyst,91110,0 +24927,Male,51,Bachelors,0,87,49,41,18,5.0,7,0,Semi-Urban,Software Engineer,21777,0 +24928,Male,59,High School,18,53,60,37,49,9.0,6,86,Semi-Urban,HR Executive,20191,1 +24929,Male,31,Bachelors,18,32,37,4,82,5.0,1,42,Rural,HR Executive,75009,0 +24930,Male,59,PhD,19,23,59,69,69,8.0,0,63,Rural,Data Analyst,55012,0 +24931,Male,32,PhD,3,90,44,98,14,0.0,2,81,Semi-Urban,Manager,121920,1 +24932,Female,46,Diploma,0,96,32,17,87,0.0,4,6,Urban,HR Executive,86513,0 +24933,Male,37,Bachelors,4,1,62,92,12,2.0,5,41,Urban,Software Engineer,127523,0 +24934,Male,51,Bachelors,18,92,46,1,29,6.0,1,62,Semi-Urban,HR Executive,78086,0 +24935,Male,44,High School,8,82,90,67,66,6.0,6,32,Urban,Software Engineer,67216,1 +24936,Female,28,Diploma,12,28,85,35,69,3.0,1,37,Rural,HR Executive,55493,0 +24937,Female,23,Masters,18,48,67,80,74,1.0,2,44,Urban,Data Analyst,149319,0 +24938,Female,39,High School,12,88,88,29,94,9.0,7,33,Semi-Urban,ML Engineer,114509,0 +24939,Male,57,Bachelors,7,14,33,90,70,8.0,6,12,Urban,HR Executive,76696,0 +24940,Male,36,Diploma,15,84,87,56,97,9.0,6,37,Rural,Data Analyst,80591,1 +24941,Male,31,Bachelors,19,3,30,83,35,9.0,0,65,Urban,Manager,115187,0 +24942,Male,39,Diploma,2,6,37,38,5,1.0,2,14,Urban,Data Analyst,108265,0 +24943,Male,48,Bachelors,3,45,46,38,76,6.0,6,70,Urban,ML Engineer,106081,0 +24944,Other,58,Bachelors,12,72,51,85,5,0.0,4,33,Urban,ML Engineer,75915,1 +24945,Male,43,Diploma,14,77,40,73,0,0.0,3,2,Urban,HR Executive,44859,0 +24946,Other,49,Bachelors,0,95,29,13,42,0.0,1,24,Rural,ML Engineer,149216,0 +24947,Male,30,Masters,16,35,24,47,34,2.0,5,52,Urban,ML Engineer,23905,0 +24948,Female,51,Bachelors,14,90,4,2,46,2.0,1,61,Urban,Software Engineer,147075,0 +24949,Male,41,Masters,1,23,84,90,82,0.0,3,8,Urban,Manager,133599,0 +24950,Female,40,Diploma,3,42,39,59,98,8.0,1,53,Urban,Software Engineer,76177,0 +24951,Male,31,Bachelors,0,29,42,91,30,8.0,0,81,Urban,Data Analyst,58253,1 +24952,Female,25,Bachelors,17,19,53,60,72,3.0,3,18,Urban,Software Engineer,106330,0 +24953,Male,26,Bachelors,12,86,43,49,17,0.0,4,4,Urban,Data Analyst,43871,0 +24954,Male,39,Bachelors,1,9,67,38,54,1.0,5,16,Semi-Urban,Software Engineer,134248,0 +24955,Male,43,Diploma,12,19,26,18,12,5.0,6,1,Rural,HR Executive,126770,0 +24956,Male,35,Masters,10,71,0,40,16,9.0,1,68,Urban,Data Analyst,56003,0 +24957,Female,55,High School,9,60,98,19,28,9.0,6,43,Urban,Manager,148221,0 +24958,Other,53,PhD,2,44,77,72,70,4.0,4,46,Urban,Manager,116106,0 +24959,Female,39,High School,5,65,73,21,74,4.0,1,13,Urban,Software Engineer,32186,0 +24960,Female,49,Bachelors,6,62,47,57,99,3.0,4,80,Semi-Urban,ML Engineer,105636,1 +24961,Male,35,Bachelors,1,80,92,8,50,4.0,1,18,Rural,ML Engineer,47406,0 +24962,Female,38,PhD,3,82,13,98,98,5.0,1,33,Rural,Software Engineer,113582,0 +24963,Male,58,Masters,12,30,40,5,50,9.0,4,38,Semi-Urban,HR Executive,120213,0 +24964,Female,46,Diploma,18,7,99,75,53,4.0,7,31,Semi-Urban,Data Analyst,34453,0 +24965,Male,38,Bachelors,12,7,43,16,55,8.0,1,8,Rural,Manager,149713,0 +24966,Female,42,Bachelors,2,36,8,0,1,5.0,7,79,Urban,Data Analyst,139438,0 +24967,Male,23,Diploma,1,42,1,85,68,4.0,3,12,Semi-Urban,ML Engineer,115951,0 +24968,Male,22,Bachelors,13,20,86,20,40,5.0,5,99,Rural,ML Engineer,59789,0 +24969,Male,29,Bachelors,10,1,10,71,26,0.0,7,30,Rural,ML Engineer,143184,0 +24970,Male,50,Masters,19,36,54,1,53,4.0,6,1,Urban,HR Executive,72341,0 +24971,Male,29,Bachelors,2,64,86,53,45,7.0,0,10,Rural,HR Executive,34549,0 +24972,Male,58,Diploma,5,98,12,84,58,5.0,7,9,Urban,Manager,31333,0 +24973,Female,37,Masters,13,98,26,73,68,9.0,5,9,Urban,Software Engineer,61503,0 +24974,Male,30,PhD,11,19,71,6,41,1.0,2,56,Urban,Data Analyst,63331,0 +24975,Female,30,High School,11,24,59,83,3,4.0,4,1,Semi-Urban,Data Analyst,77515,0 +24976,Male,44,Bachelors,12,26,17,29,91,4.0,2,80,Rural,Data Analyst,112992,0 +24977,Male,37,Diploma,10,30,27,20,33,5.0,0,78,Urban,HR Executive,32489,0 +24978,Male,28,Masters,13,98,3,21,52,7.0,1,56,Rural,HR Executive,66082,0 +24979,Male,39,Bachelors,2,78,70,71,57,0.0,7,64,Urban,Manager,20131,1 +24980,Male,35,Diploma,7,14,34,68,54,6.0,5,52,Urban,ML Engineer,113148,0 +24981,Male,42,Masters,12,75,65,48,1,0.0,7,83,Semi-Urban,Software Engineer,67353,1 +24982,Male,31,Masters,4,31,6,46,89,6.0,1,98,Rural,Manager,126150,0 +24983,Female,33,Bachelors,19,13,76,26,62,4.0,7,48,Semi-Urban,Data Analyst,136331,0 +24984,Male,36,High School,11,51,74,19,9,9.0,5,42,Rural,Data Analyst,91331,0 +24985,Male,50,Bachelors,14,84,62,95,45,8.0,3,31,Urban,Data Analyst,34736,1 +24986,Female,22,Masters,14,45,7,41,38,8.0,6,39,Urban,Software Engineer,138356,0 +24987,Female,23,High School,2,7,45,51,7,2.0,4,97,Semi-Urban,Manager,134234,0 +24988,Male,37,Diploma,1,51,65,74,16,9.0,5,1,Semi-Urban,Software Engineer,119121,0 +24989,Female,54,Bachelors,5,46,25,37,81,7.0,4,63,Urban,Manager,128223,0 +24990,Female,36,High School,4,28,25,40,4,0.0,2,29,Rural,ML Engineer,121612,0 +24991,Male,55,Bachelors,16,55,88,60,62,3.0,7,77,Semi-Urban,Software Engineer,91745,1 +24992,Male,41,Diploma,19,86,79,12,55,4.0,2,3,Semi-Urban,Software Engineer,86568,0 +24993,Female,44,Bachelors,7,44,2,36,86,6.0,4,89,Urban,Data Analyst,95504,0 +24994,Male,51,Masters,16,22,49,69,42,1.0,2,39,Rural,Manager,149746,0 +24995,Male,34,Masters,0,21,79,81,18,6.0,6,51,Rural,Software Engineer,99612,0 +24996,Male,36,High School,4,79,89,11,95,5.0,0,45,Urban,Manager,44244,0 +24997,Female,48,Diploma,10,50,52,76,0,3.0,2,46,Rural,Data Analyst,58568,0 +24998,Female,58,PhD,0,64,82,5,76,2.0,7,13,Semi-Urban,Manager,81039,0 +24999,Female,46,High School,3,28,27,50,11,9.0,0,28,Urban,HR Executive,95745,0 +25000,Other,42,Masters,1,87,5,64,82,5.0,1,99,Rural,HR Executive,74319,1 +25001,Male,44,Diploma,9,53,0,24,27,3.0,7,89,Rural,HR Executive,97836,0 +25002,Male,55,Bachelors,2,8,7,26,43,6.0,0,30,Semi-Urban,Manager,87531,0 +25003,Female,52,High School,18,88,13,50,68,0.0,6,28,Urban,Manager,25123,0 +25004,Other,21,High School,3,23,95,0,85,8.0,3,52,Semi-Urban,Software Engineer,39401,0 +25005,Male,50,Bachelors,0,96,1,58,89,8.0,6,15,Semi-Urban,Manager,135837,0 +25006,Male,33,Bachelors,14,29,36,99,32,8.0,6,69,Semi-Urban,HR Executive,58305,0 +25007,Male,32,Diploma,0,36,85,86,7,3.0,3,4,Semi-Urban,ML Engineer,57447,0 +25008,Male,56,Diploma,16,28,22,8,28,8.0,7,71,Semi-Urban,Software Engineer,40886,0 +25009,Male,55,PhD,17,88,94,10,60,4.0,7,24,Urban,Manager,55559,0 +25010,Male,44,High School,8,30,26,32,48,9.0,6,16,Urban,Data Analyst,83358,0 +25011,Female,21,Bachelors,16,64,86,73,83,9.0,7,9,Urban,Data Analyst,44706,0 +25012,Male,41,Masters,0,87,73,35,96,0.0,2,44,Semi-Urban,ML Engineer,86913,1 +25013,Female,35,High School,0,39,15,20,52,1.0,3,61,Urban,HR Executive,102472,0 +25014,Male,53,High School,8,47,44,48,45,2.0,5,79,Urban,ML Engineer,58152,0 +25015,Male,35,Bachelors,6,30,68,54,85,8.0,1,88,Semi-Urban,Software Engineer,124953,1 +25016,Male,35,High School,0,18,7,22,39,1.0,7,1,Semi-Urban,HR Executive,99278,0 +25017,Female,33,Bachelors,13,81,60,95,20,4.0,7,21,Semi-Urban,Software Engineer,25245,1 +25018,Male,51,Diploma,6,24,34,90,84,3.0,3,45,Semi-Urban,HR Executive,134221,0 +25019,Female,37,Bachelors,18,40,63,3,93,7.0,6,8,Urban,Manager,102221,0 +25020,Female,25,Diploma,16,85,28,28,18,8.0,4,55,Rural,Manager,96625,0 +25021,Male,21,Masters,9,0,47,14,51,2.0,6,51,Rural,HR Executive,111232,0 +25022,Male,45,Diploma,0,39,26,34,47,5.0,7,80,Urban,Software Engineer,45891,0 +25023,Female,27,Bachelors,10,97,37,85,59,8.0,1,1,Urban,Data Analyst,125690,0 +25024,Male,46,Diploma,1,11,16,67,9,8.0,6,61,Rural,HR Executive,119982,0 +25025,Male,56,Masters,18,75,51,94,44,7.0,4,69,Urban,Data Analyst,51107,1 +25026,Male,44,Masters,16,8,18,93,58,5.0,4,33,Urban,ML Engineer,87717,0 +25027,Male,35,High School,13,79,54,18,36,9.0,5,27,Rural,ML Engineer,34539,0 +25028,Female,53,Bachelors,17,22,72,87,49,7.0,6,12,Urban,Software Engineer,38104,0 +25029,Male,47,Bachelors,5,88,97,38,29,4.0,3,95,Urban,ML Engineer,143674,1 +25030,Male,31,High School,19,33,29,23,73,8.0,0,49,Urban,HR Executive,78870,0 +25031,Male,31,Masters,17,51,69,16,54,0.0,5,75,Urban,Manager,37455,0 +25032,Female,29,Bachelors,3,29,10,1,83,9.0,6,9,Semi-Urban,HR Executive,79238,0 +25033,Female,25,Diploma,2,51,12,53,1,8.0,3,91,Urban,Software Engineer,62262,0 +25034,Female,46,Bachelors,6,91,76,39,0,9.0,6,23,Urban,Data Analyst,96694,0 +25035,Female,55,High School,0,26,97,4,53,5.0,3,70,Semi-Urban,ML Engineer,141326,0 +25036,Male,35,Masters,9,9,85,66,41,9.0,3,76,Urban,Software Engineer,62037,1 +25037,Male,49,Bachelors,17,85,58,68,9,8.0,4,89,Rural,Software Engineer,147164,1 +25038,Male,42,Masters,7,64,80,76,48,1.0,0,64,Urban,ML Engineer,103556,1 +25039,Female,58,Diploma,14,3,14,95,68,0.0,5,63,Urban,Manager,139677,0 +25040,Female,25,Bachelors,9,4,65,92,11,5.0,1,95,Rural,ML Engineer,71218,1 +25041,Other,59,High School,5,21,42,45,95,2.0,2,34,Urban,ML Engineer,101463,0 +25042,Female,47,Masters,5,2,83,95,42,3.0,3,7,Urban,Software Engineer,23232,0 +25043,Male,33,Bachelors,13,91,89,76,69,6.0,3,25,Semi-Urban,Manager,100294,1 +25044,Male,29,Bachelors,11,9,48,43,59,6.0,3,85,Semi-Urban,Data Analyst,70325,0 +25045,Male,46,Masters,4,61,49,2,76,2.0,0,75,Urban,ML Engineer,88786,0 +25046,Male,53,Diploma,3,28,95,54,30,1.0,1,81,Rural,Software Engineer,52785,1 +25047,Male,37,Diploma,8,12,48,77,68,0.0,2,60,Urban,ML Engineer,116695,0 +25048,Male,52,Bachelors,8,96,5,34,30,0.0,6,31,Urban,Software Engineer,80328,0 +25049,Male,49,Masters,18,61,3,81,25,4.0,2,21,Rural,HR Executive,65392,0 +25050,Female,46,High School,7,84,79,30,72,4.0,7,61,Semi-Urban,HR Executive,139359,1 +25051,Male,32,Bachelors,6,17,83,48,45,1.0,1,81,Urban,ML Engineer,76670,0 +25052,Male,51,Masters,5,48,59,67,39,8.0,0,67,Urban,Software Engineer,61842,1 +25053,Male,42,Diploma,19,19,57,69,95,6.0,7,54,Semi-Urban,Software Engineer,24178,0 +25054,Male,46,Bachelors,0,59,14,49,72,4.0,0,7,Urban,Manager,56206,0 +25055,Other,53,Masters,17,11,82,64,21,7.0,2,12,Urban,HR Executive,49163,0 +25056,Male,36,Bachelors,19,2,92,8,88,6.0,5,14,Urban,Data Analyst,104456,0 +25057,Female,28,Diploma,6,44,94,38,26,6.0,0,86,Semi-Urban,ML Engineer,138345,1 +25058,Male,36,Diploma,4,69,90,98,78,1.0,3,41,Rural,Manager,20357,1 +25059,Male,50,Diploma,8,84,68,78,35,4.0,6,30,Semi-Urban,HR Executive,92146,1 +25060,Male,31,Bachelors,12,55,39,22,42,7.0,4,97,Urban,ML Engineer,27390,0 +25061,Male,36,Masters,12,37,94,3,1,5.0,0,57,Semi-Urban,Software Engineer,146909,0 +25062,Male,43,Masters,11,37,91,44,29,8.0,0,74,Rural,Data Analyst,143918,1 +25063,Female,22,Masters,5,10,15,78,52,0.0,1,77,Urban,Manager,112762,0 +25064,Male,34,Bachelors,13,20,87,83,52,1.0,6,34,Urban,Software Engineer,101834,0 +25065,Male,35,High School,10,3,91,4,20,3.0,3,1,Urban,ML Engineer,124023,0 +25066,Male,44,Bachelors,19,68,6,39,31,5.0,4,79,Rural,Data Analyst,31124,0 +25067,Male,56,Diploma,4,64,58,3,48,6.0,0,86,Semi-Urban,Manager,32469,0 +25068,Female,22,Diploma,6,69,32,5,85,3.0,5,37,Urban,HR Executive,101065,0 +25069,Female,54,Masters,9,50,57,93,10,6.0,2,17,Urban,Data Analyst,110728,0 +25070,Male,50,Diploma,13,95,80,17,39,0.0,2,24,Semi-Urban,HR Executive,56304,0 +25071,Male,57,Bachelors,2,4,66,1,63,1.0,5,57,Semi-Urban,HR Executive,140993,0 +25072,Male,30,Bachelors,13,40,43,53,59,9.0,7,96,Rural,Data Analyst,101098,0 +25073,Other,58,Diploma,1,31,43,39,32,2.0,3,88,Urban,ML Engineer,68938,0 +25074,Male,26,Bachelors,15,38,22,68,84,2.0,5,34,Semi-Urban,Manager,43786,0 +25075,Female,41,High School,4,88,94,40,19,9.0,6,81,Urban,Software Engineer,111796,1 +25076,Male,38,Diploma,12,95,3,85,21,3.0,4,47,Urban,Data Analyst,114095,0 +25077,Other,42,Diploma,0,44,98,84,47,4.0,2,20,Semi-Urban,Software Engineer,24624,1 +25078,Male,47,Diploma,19,24,12,58,55,9.0,0,43,Urban,Software Engineer,46063,0 +25079,Male,57,Diploma,19,39,17,89,93,2.0,4,32,Semi-Urban,Software Engineer,38540,0 +25080,Female,29,Masters,1,16,11,48,29,0.0,5,59,Urban,ML Engineer,25886,0 +25081,Other,40,High School,19,63,18,9,24,3.0,3,42,Rural,HR Executive,29480,0 +25082,Other,47,Bachelors,3,62,41,98,90,8.0,5,93,Semi-Urban,Data Analyst,99881,1 +25083,Female,52,Masters,12,84,0,50,40,3.0,0,14,Urban,Data Analyst,127492,0 +25084,Female,32,Bachelors,1,64,20,12,3,6.0,5,92,Semi-Urban,ML Engineer,23380,0 +25085,Male,39,High School,8,70,60,41,96,5.0,7,38,Urban,Data Analyst,141353,0 +25086,Female,54,Bachelors,6,41,82,35,51,8.0,5,1,Urban,ML Engineer,23255,0 +25087,Female,57,Bachelors,2,35,12,32,79,7.0,1,81,Urban,Data Analyst,132494,0 +25088,Male,33,Bachelors,19,21,18,80,81,6.0,4,88,Rural,HR Executive,134047,0 +25089,Female,51,Bachelors,0,65,60,60,32,1.0,7,63,Semi-Urban,Software Engineer,131223,1 +25090,Male,30,PhD,9,34,65,99,18,4.0,1,66,Urban,Software Engineer,48551,1 +25091,Male,34,Masters,14,99,85,40,10,5.0,6,75,Urban,ML Engineer,52321,1 +25092,Female,48,High School,13,29,86,36,18,5.0,0,22,Urban,Data Analyst,115100,0 +25093,Male,35,Bachelors,5,9,62,5,40,7.0,5,84,Rural,Manager,59724,0 +25094,Male,36,Diploma,2,31,64,91,84,0.0,1,83,Urban,ML Engineer,64122,1 +25095,Male,43,Masters,13,47,34,5,88,9.0,6,30,Urban,HR Executive,105308,0 +25096,Male,59,High School,8,33,70,79,99,8.0,5,12,Urban,HR Executive,90119,0 +25097,Male,21,Bachelors,9,6,72,65,65,2.0,6,71,Semi-Urban,Manager,50292,0 +25098,Female,51,Diploma,9,86,96,8,41,5.0,6,60,Semi-Urban,HR Executive,147025,1 +25099,Female,25,High School,11,27,69,97,10,0.0,2,51,Urban,Manager,23298,1 +25100,Female,24,Masters,1,88,2,4,99,2.0,1,87,Urban,Data Analyst,91137,0 +25101,Male,54,Bachelors,18,84,55,35,98,2.0,1,41,Urban,Manager,41307,0 +25102,Female,48,Masters,2,62,52,96,68,3.0,7,38,Urban,HR Executive,54574,1 +25103,Female,25,Masters,13,39,28,1,4,9.0,4,14,Rural,HR Executive,57773,0 +25104,Male,23,Bachelors,16,60,12,63,39,4.0,2,44,Urban,Manager,115818,0 +25105,Female,38,Bachelors,15,86,25,83,87,6.0,4,63,Urban,HR Executive,96113,1 +25106,Other,40,Bachelors,3,5,76,94,46,4.0,1,2,Semi-Urban,Software Engineer,72135,0 +25107,Male,41,Bachelors,8,68,16,9,65,7.0,1,30,Semi-Urban,ML Engineer,75843,0 +25108,Male,53,Bachelors,10,43,98,58,5,8.0,0,10,Urban,Software Engineer,43838,0 +25109,Female,51,Diploma,10,93,97,40,23,9.0,2,35,Semi-Urban,ML Engineer,105995,1 +25110,Male,31,Bachelors,5,65,21,76,64,4.0,2,68,Rural,Data Analyst,76363,0 +25111,Female,24,PhD,0,59,99,53,75,4.0,0,95,Semi-Urban,Software Engineer,33774,1 +25112,Male,36,Diploma,2,83,76,45,40,0.0,7,27,Rural,ML Engineer,101903,0 +25113,Male,21,Bachelors,13,63,63,91,29,7.0,1,30,Urban,Manager,50935,1 +25114,Female,43,Bachelors,3,37,62,80,69,4.0,0,59,Semi-Urban,ML Engineer,148384,0 +25115,Male,45,High School,0,91,85,31,76,5.0,2,4,Urban,HR Executive,87274,0 +25116,Female,23,Diploma,4,41,24,64,14,5.0,4,31,Semi-Urban,Manager,104783,0 +25117,Male,24,Bachelors,15,4,47,65,61,9.0,5,61,Urban,HR Executive,53125,0 +25118,Male,30,Diploma,13,4,8,72,82,2.0,7,2,Urban,Data Analyst,147707,0 +25119,Male,23,Diploma,14,31,49,19,48,9.0,6,35,Urban,Manager,31110,0 +25120,Male,55,Diploma,11,16,62,65,68,3.0,5,52,Urban,Manager,29857,0 +25121,Male,25,Diploma,7,14,60,8,29,5.0,5,11,Urban,Data Analyst,83037,0 +25122,Female,50,Bachelors,16,10,65,2,58,8.0,2,37,Urban,Manager,114285,0 +25123,Female,23,Diploma,17,27,1,13,28,2.0,1,32,Urban,Software Engineer,49044,0 +25124,Female,50,PhD,9,87,90,51,27,1.0,1,27,Rural,Data Analyst,117793,1 +25125,Male,23,Masters,7,19,56,96,40,7.0,3,33,Urban,Software Engineer,28229,0 +25126,Female,33,Bachelors,10,73,31,79,30,7.0,3,12,Urban,HR Executive,116826,0 +25127,Female,22,Masters,11,38,18,80,51,0.0,2,60,Rural,HR Executive,57121,0 +25128,Male,59,Diploma,12,4,2,77,55,7.0,2,6,Urban,Software Engineer,29808,0 +25129,Male,49,Bachelors,12,41,60,67,2,6.0,3,16,Urban,HR Executive,91983,0 +25130,Male,27,Bachelors,4,3,53,98,79,2.0,3,72,Urban,Data Analyst,105939,0 +25131,Male,56,Masters,0,68,12,44,17,0.0,7,93,Urban,Software Engineer,90716,0 +25132,Female,58,PhD,17,20,70,42,95,2.0,3,66,Urban,Data Analyst,62973,0 +25133,Male,55,Masters,4,0,7,39,47,2.0,1,21,Urban,ML Engineer,83515,0 +25134,Female,43,High School,14,28,19,87,73,5.0,4,28,Urban,Software Engineer,102360,0 +25135,Male,27,Bachelors,17,30,1,69,87,5.0,1,89,Semi-Urban,Data Analyst,61055,0 +25136,Male,23,Diploma,0,25,21,79,34,7.0,6,74,Semi-Urban,Manager,76768,0 +25137,Male,30,Masters,4,79,14,2,2,8.0,6,13,Urban,Data Analyst,122899,0 +25138,Other,38,High School,15,94,62,5,19,6.0,2,25,Rural,Data Analyst,22346,0 +25139,Male,54,Bachelors,13,43,53,76,41,2.0,3,87,Urban,HR Executive,62091,1 +25140,Female,50,PhD,3,45,18,12,5,2.0,1,5,Urban,HR Executive,96566,0 +25141,Male,29,Masters,3,32,59,1,76,7.0,3,57,Urban,Manager,93689,0 +25142,Female,52,High School,0,5,16,59,76,0.0,5,53,Semi-Urban,HR Executive,80101,0 +25143,Female,30,PhD,10,16,25,5,96,5.0,5,3,Urban,HR Executive,127159,0 +25144,Female,49,Bachelors,5,30,77,44,20,1.0,3,56,Semi-Urban,Software Engineer,131099,0 +25145,Male,34,Bachelors,7,32,25,79,38,2.0,2,13,Urban,Software Engineer,84455,0 +25146,Male,26,Bachelors,8,14,86,40,84,7.0,0,70,Semi-Urban,Manager,110759,0 +25147,Male,25,Bachelors,4,10,31,43,2,6.0,4,7,Urban,Manager,107587,0 +25148,Female,41,PhD,10,4,92,15,8,4.0,1,26,Urban,ML Engineer,45119,0 +25149,Male,24,Diploma,6,11,87,37,66,3.0,0,16,Urban,Manager,91429,0 +25150,Male,26,Diploma,13,58,23,42,50,0.0,4,5,Urban,Software Engineer,35216,0 +25151,Male,38,Bachelors,4,23,11,88,34,5.0,3,28,Semi-Urban,Software Engineer,135390,0 +25152,Male,28,Masters,1,62,56,16,48,5.0,6,65,Rural,HR Executive,90784,0 +25153,Female,23,Bachelors,12,67,49,0,79,6.0,6,93,Urban,Data Analyst,149969,0 +25154,Female,21,Diploma,3,30,42,55,19,4.0,4,62,Urban,ML Engineer,118705,0 +25155,Male,57,High School,9,20,65,37,1,3.0,0,21,Semi-Urban,HR Executive,149906,0 +25156,Female,43,Diploma,7,96,97,13,79,7.0,3,79,Urban,HR Executive,25420,1 +25157,Female,47,High School,0,61,32,17,12,5.0,5,31,Rural,HR Executive,139209,0 +25158,Male,56,High School,1,48,31,92,46,0.0,1,39,Urban,HR Executive,95493,0 +25159,Female,40,Masters,15,14,6,26,35,8.0,0,95,Rural,ML Engineer,77510,0 +25160,Female,32,Bachelors,14,9,69,49,86,3.0,6,9,Semi-Urban,Manager,130132,0 +25161,Male,55,PhD,12,39,99,0,57,2.0,5,1,Semi-Urban,ML Engineer,136317,0 +25162,Female,25,Diploma,3,55,33,51,60,3.0,6,8,Urban,ML Engineer,26888,0 +25163,Male,21,Masters,5,72,16,16,68,1.0,3,58,Urban,Data Analyst,137407,0 +25164,Male,37,High School,13,48,34,12,28,7.0,6,85,Urban,Manager,29978,0 +25165,Female,52,Masters,11,1,20,24,94,5.0,5,97,Urban,Software Engineer,34891,0 +25166,Female,24,Bachelors,3,88,40,5,27,5.0,5,36,Semi-Urban,Software Engineer,102284,0 +25167,Female,22,Masters,3,15,53,50,9,5.0,7,30,Semi-Urban,Software Engineer,138238,0 +25168,Male,45,Bachelors,8,70,54,15,86,1.0,1,71,Rural,ML Engineer,82235,0 +25169,Other,39,Masters,13,3,68,40,23,9.0,5,82,Urban,Software Engineer,140991,0 +25170,Male,39,Bachelors,5,1,87,89,34,6.0,5,59,Urban,Data Analyst,149264,1 +25171,Male,42,Bachelors,5,58,69,12,79,0.0,5,80,Semi-Urban,HR Executive,59214,0 +25172,Male,32,Bachelors,14,1,20,38,92,9.0,3,96,Urban,Data Analyst,58998,0 +25173,Male,57,Bachelors,0,54,28,6,8,8.0,3,43,Urban,Software Engineer,110900,0 +25174,Male,23,Diploma,6,1,47,65,25,8.0,1,90,Urban,HR Executive,144193,0 +25175,Female,28,Diploma,17,37,26,69,74,9.0,1,27,Urban,Data Analyst,33022,0 +25176,Female,49,Masters,5,54,54,54,15,8.0,7,58,Rural,ML Engineer,97887,0 +25177,Other,45,Masters,15,80,13,68,80,3.0,3,87,Urban,ML Engineer,37752,1 +25178,Female,39,Masters,0,26,59,28,20,4.0,3,95,Urban,ML Engineer,142355,0 +25179,Male,31,Bachelors,9,91,57,24,16,3.0,1,75,Semi-Urban,Manager,93308,1 +25180,Female,46,Diploma,5,0,47,31,16,4.0,7,96,Semi-Urban,Data Analyst,27562,0 +25181,Female,23,High School,14,48,6,72,60,3.0,4,33,Urban,ML Engineer,41556,0 +25182,Male,28,Bachelors,8,73,4,71,4,4.0,3,80,Urban,HR Executive,26995,0 +25183,Female,41,Masters,11,74,62,56,55,2.0,7,78,Semi-Urban,Software Engineer,58192,1 +25184,Male,21,Diploma,5,71,40,79,36,9.0,3,69,Semi-Urban,Software Engineer,67536,1 +25185,Male,51,Bachelors,12,4,16,58,63,4.0,3,67,Urban,Software Engineer,41779,0 +25186,Male,41,High School,17,47,37,52,40,1.0,7,51,Rural,HR Executive,22249,0 +25187,Female,58,Diploma,19,53,59,89,93,0.0,6,3,Urban,HR Executive,66369,0 +25188,Female,47,Bachelors,17,67,22,63,73,7.0,0,24,Semi-Urban,Manager,60534,0 +25189,Male,53,Bachelors,15,50,44,50,74,1.0,3,19,Urban,ML Engineer,48684,0 +25190,Male,26,Diploma,0,19,82,9,19,6.0,6,2,Rural,Data Analyst,108585,0 +25191,Female,23,Bachelors,0,81,94,76,18,8.0,1,43,Urban,Data Analyst,145368,1 +25192,Other,36,Masters,17,55,21,82,36,0.0,2,48,Semi-Urban,Data Analyst,123508,0 +25193,Male,23,Bachelors,9,57,79,4,14,9.0,6,92,Urban,ML Engineer,121024,0 +25194,Male,33,Bachelors,16,16,88,61,2,0.0,0,71,Urban,Data Analyst,136595,1 +25195,Female,57,Masters,2,80,82,46,43,2.0,3,27,Urban,Manager,103286,0 +25196,Male,23,Diploma,9,43,94,69,98,2.0,5,69,Semi-Urban,ML Engineer,88512,1 +25197,Male,37,Diploma,16,69,31,68,73,7.0,0,5,Urban,ML Engineer,138078,0 +25198,Male,32,Masters,4,68,60,54,49,9.0,4,47,Urban,HR Executive,93726,0 +25199,Female,53,PhD,18,95,47,90,22,2.0,7,62,Rural,HR Executive,101983,1 +25200,Female,43,Masters,9,73,85,7,70,4.0,0,28,Urban,HR Executive,91764,0 +25201,Male,51,Bachelors,7,61,17,64,14,8.0,3,48,Rural,Software Engineer,149419,0 +25202,Male,31,PhD,4,24,55,77,85,8.0,7,77,Rural,ML Engineer,144390,0 +25203,Male,38,Diploma,17,64,80,97,65,4.0,2,59,Rural,Data Analyst,98501,1 +25204,Male,31,Bachelors,14,68,10,71,2,3.0,2,26,Urban,HR Executive,66412,0 +25205,Male,49,Diploma,13,97,31,85,27,2.0,0,20,Urban,HR Executive,115263,0 +25206,Male,51,High School,4,47,20,13,72,6.0,6,24,Semi-Urban,Software Engineer,37273,0 +25207,Male,44,Bachelors,9,3,6,14,7,4.0,2,56,Urban,Manager,25970,0 +25208,Male,47,Bachelors,13,26,84,67,83,7.0,5,83,Rural,Manager,20051,1 +25209,Female,39,Bachelors,7,72,24,51,79,3.0,7,85,Urban,ML Engineer,34078,0 +25210,Female,40,Bachelors,14,21,46,44,95,0.0,4,39,Semi-Urban,Manager,80310,0 +25211,Male,37,Masters,2,43,12,53,96,5.0,0,59,Urban,HR Executive,57760,0 +25212,Male,32,Diploma,9,28,33,5,71,9.0,7,15,Rural,Data Analyst,112589,0 +25213,Male,52,Diploma,1,97,66,44,2,2.0,2,5,Urban,ML Engineer,55669,0 +25214,Female,22,Masters,8,20,34,99,17,0.0,6,61,Rural,Data Analyst,108301,0 +25215,Male,51,Masters,6,40,62,2,74,0.0,0,28,Rural,Data Analyst,53036,0 +25216,Male,59,Diploma,6,14,67,40,41,7.0,2,82,Urban,Data Analyst,119340,0 +25217,Female,55,Diploma,5,32,36,35,89,3.0,2,30,Urban,Software Engineer,48778,0 +25218,Female,22,Masters,10,35,57,60,1,0.0,5,47,Semi-Urban,ML Engineer,80788,0 +25219,Male,45,High School,1,71,61,28,32,4.0,5,64,Rural,ML Engineer,108869,0 +25220,Male,24,Bachelors,13,31,9,72,97,0.0,7,92,Urban,ML Engineer,149934,0 +25221,Female,57,Diploma,11,19,34,61,96,5.0,3,76,Urban,Software Engineer,116464,0 +25222,Female,59,High School,0,14,12,79,82,9.0,3,8,Semi-Urban,ML Engineer,131415,0 +25223,Male,56,Bachelors,0,34,74,86,89,6.0,2,16,Urban,Manager,72776,0 +25224,Female,22,Diploma,9,88,98,82,71,1.0,4,78,Semi-Urban,Data Analyst,72337,1 +25225,Male,41,Bachelors,4,97,93,61,78,5.0,7,66,Urban,Data Analyst,121266,1 +25226,Other,56,Bachelors,9,13,29,67,35,7.0,6,11,Rural,Software Engineer,41090,0 +25227,Male,53,Bachelors,10,26,86,3,25,6.0,6,68,Urban,Data Analyst,132622,0 +25228,Female,36,Bachelors,17,36,54,63,99,4.0,4,26,Urban,Data Analyst,134221,0 +25229,Female,59,Masters,11,91,25,11,19,1.0,7,16,Semi-Urban,Software Engineer,36883,0 +25230,Male,36,Bachelors,2,70,40,81,96,5.0,7,89,Rural,Data Analyst,119774,1 +25231,Female,33,Diploma,3,65,1,52,83,9.0,2,80,Urban,Data Analyst,26787,0 +25232,Male,33,PhD,8,67,42,45,71,0.0,5,66,Urban,ML Engineer,94524,0 +25233,Male,27,Bachelors,3,46,81,52,82,6.0,0,74,Rural,Manager,121533,1 +25234,Male,47,Diploma,2,87,71,51,3,4.0,1,35,Urban,HR Executive,22452,1 +25235,Female,45,Diploma,13,0,5,61,24,3.0,7,30,Rural,HR Executive,106356,0 +25236,Male,40,Diploma,4,3,2,97,27,1.0,4,31,Urban,Data Analyst,72424,0 +25237,Female,43,Masters,16,72,52,69,69,2.0,2,6,Urban,HR Executive,76973,0 +25238,Female,40,High School,16,64,95,35,64,7.0,7,85,Urban,Data Analyst,70404,1 +25239,Male,37,Bachelors,3,95,26,47,32,7.0,4,10,Urban,Data Analyst,98218,0 +25240,Male,26,Bachelors,19,85,12,60,90,9.0,1,24,Rural,Manager,75152,0 +25241,Female,28,Diploma,17,43,45,0,73,8.0,4,23,Rural,Manager,137816,0 +25242,Other,47,Diploma,9,28,59,29,46,5.0,4,59,Urban,Software Engineer,135909,0 +25243,Male,30,Bachelors,16,87,88,49,55,7.0,0,54,Semi-Urban,ML Engineer,61672,1 +25244,Male,57,High School,5,37,23,53,72,7.0,3,74,Semi-Urban,Software Engineer,139591,0 +25245,Male,23,Diploma,17,56,18,78,23,2.0,0,58,Semi-Urban,Software Engineer,40245,0 +25246,Male,39,High School,11,20,49,38,82,9.0,1,56,Urban,HR Executive,122261,0 +25247,Male,38,High School,18,80,75,73,21,9.0,2,50,Semi-Urban,ML Engineer,35228,1 +25248,Male,24,Bachelors,1,29,31,48,11,4.0,3,52,Urban,HR Executive,42774,0 +25249,Male,31,Diploma,0,84,23,90,46,6.0,3,55,Semi-Urban,ML Engineer,93836,1 +25250,Male,51,Diploma,7,50,28,78,17,8.0,5,21,Urban,Data Analyst,71720,0 +25251,Female,21,PhD,1,36,76,38,66,5.0,6,20,Urban,HR Executive,48719,0 +25252,Other,40,Bachelors,10,25,4,86,17,9.0,6,44,Semi-Urban,Manager,136835,0 +25253,Male,32,Bachelors,2,85,10,33,10,0.0,6,91,Semi-Urban,ML Engineer,96926,0 +25254,Female,42,Bachelors,2,85,3,63,10,0.0,6,9,Urban,HR Executive,57811,0 +25255,Male,41,Diploma,10,3,30,52,20,2.0,0,16,Urban,HR Executive,105918,0 +25256,Female,53,Diploma,17,0,51,71,40,2.0,6,92,Rural,Manager,103265,0 +25257,Female,27,Bachelors,3,86,10,49,5,3.0,0,24,Urban,Data Analyst,45957,0 +25258,Female,54,Bachelors,10,39,46,91,14,9.0,7,38,Urban,Manager,99763,0 +25259,Male,52,Diploma,0,60,72,49,79,0.0,5,52,Urban,ML Engineer,101218,0 +25260,Male,42,High School,13,19,54,11,28,6.0,7,64,Urban,Data Analyst,108137,0 +25261,Male,49,Bachelors,5,9,98,32,80,8.0,7,84,Urban,Manager,105677,0 +25262,Male,21,Bachelors,4,12,63,57,53,7.0,3,24,Urban,Manager,134086,0 +25263,Male,50,Bachelors,3,19,38,66,77,4.0,7,58,Urban,Software Engineer,140594,0 +25264,Male,39,Diploma,12,7,72,39,29,6.0,0,11,Urban,Software Engineer,128887,0 +25265,Female,32,Bachelors,9,85,46,65,17,8.0,4,30,Semi-Urban,HR Executive,55938,0 +25266,Male,47,Masters,14,12,69,54,12,8.0,0,66,Rural,HR Executive,50149,0 +25267,Male,54,Masters,10,91,62,74,20,6.0,6,60,Semi-Urban,Manager,80483,1 +25268,Male,42,Bachelors,1,97,87,83,38,0.0,6,25,Urban,Software Engineer,146403,1 +25269,Male,58,Diploma,8,39,25,65,68,5.0,4,25,Semi-Urban,Software Engineer,40719,0 +25270,Female,25,Masters,18,50,93,62,15,0.0,7,7,Semi-Urban,HR Executive,65734,0 +25271,Male,52,High School,3,24,65,56,57,3.0,1,2,Urban,HR Executive,42915,0 +25272,Male,47,Masters,17,48,58,16,84,8.0,6,0,Urban,Software Engineer,107582,0 +25273,Male,25,Bachelors,16,15,15,87,19,7.0,7,0,Rural,Manager,116135,0 +25274,Female,58,PhD,1,0,34,29,38,5.0,2,60,Rural,Manager,107793,0 +25275,Male,59,Diploma,7,88,88,64,84,6.0,0,74,Urban,Manager,127761,1 +25276,Other,47,Masters,13,45,7,6,71,7.0,1,13,Urban,ML Engineer,87788,0 +25277,Male,34,High School,13,3,41,71,64,9.0,1,61,Semi-Urban,Manager,119014,0 +25278,Female,46,Masters,11,19,11,83,39,6.0,0,44,Urban,Data Analyst,78071,0 +25279,Male,48,Diploma,12,83,59,1,67,0.0,5,36,Urban,Data Analyst,75123,0 +25280,Male,25,Bachelors,9,8,12,84,91,7.0,1,34,Semi-Urban,HR Executive,118717,0 +25281,Male,43,High School,4,72,65,46,49,8.0,7,66,Semi-Urban,HR Executive,38773,1 +25282,Male,55,Masters,5,38,39,1,76,6.0,4,40,Urban,HR Executive,142973,0 +25283,Male,46,Masters,0,89,56,99,5,6.0,5,50,Urban,Manager,49912,1 +25284,Male,45,Bachelors,0,13,98,59,36,3.0,6,88,Semi-Urban,HR Executive,53514,1 +25285,Male,55,Bachelors,10,51,44,72,32,4.0,3,42,Urban,ML Engineer,142238,0 +25286,Male,55,Diploma,8,46,83,35,93,8.0,7,0,Urban,ML Engineer,81776,0 +25287,Female,48,Bachelors,16,7,49,56,17,2.0,3,41,Semi-Urban,ML Engineer,141656,0 +25288,Female,46,Bachelors,16,11,11,78,29,4.0,1,35,Semi-Urban,Manager,45738,0 +25289,Male,54,High School,9,46,9,99,7,6.0,4,82,Rural,ML Engineer,130350,1 +25290,Male,51,Bachelors,4,59,51,24,70,6.0,2,47,Urban,Manager,70852,0 +25291,Male,46,Diploma,0,84,45,71,89,7.0,4,35,Semi-Urban,ML Engineer,117067,1 +25292,Male,33,Diploma,18,58,23,78,65,0.0,6,95,Rural,ML Engineer,37686,1 +25293,Female,38,Masters,18,43,7,24,2,3.0,3,67,Urban,Software Engineer,86872,0 +25294,Female,48,High School,3,49,57,99,41,9.0,4,60,Urban,HR Executive,147547,1 +25295,Male,41,Bachelors,2,64,83,16,71,2.0,1,50,Urban,ML Engineer,91834,0 +25296,Male,53,Diploma,8,18,45,38,68,7.0,1,2,Rural,HR Executive,46314,0 +25297,Female,51,Bachelors,15,41,37,60,27,9.0,6,37,Urban,Data Analyst,36847,0 +25298,Male,35,Diploma,13,36,99,75,63,6.0,2,32,Urban,Manager,45322,1 +25299,Male,41,Masters,9,84,85,60,16,3.0,1,27,Urban,Manager,33065,1 +25300,Female,21,High School,12,12,93,66,41,5.0,5,29,Urban,Data Analyst,136966,0 +25301,Male,23,Bachelors,0,0,16,33,0,0.0,5,16,Urban,Manager,76529,0 +25302,Male,45,Diploma,13,14,97,36,84,0.0,2,96,Urban,ML Engineer,79537,1 +25303,Female,59,Bachelors,4,65,8,55,94,3.0,5,35,Rural,ML Engineer,72752,0 +25304,Male,29,High School,1,38,30,5,97,6.0,6,21,Urban,ML Engineer,23203,0 +25305,Female,46,Masters,9,34,27,21,98,2.0,6,48,Urban,Software Engineer,62537,0 +25306,Male,36,Masters,5,32,78,55,6,4.0,1,83,Urban,Software Engineer,22237,1 +25307,Female,52,Diploma,10,52,70,49,3,5.0,0,14,Urban,Manager,125682,0 +25308,Female,49,Bachelors,6,29,63,36,65,5.0,4,86,Urban,Software Engineer,21037,0 +25309,Male,21,Masters,1,83,27,54,83,7.0,7,66,Rural,Software Engineer,63190,0 +25310,Female,46,Diploma,11,26,41,57,12,7.0,0,25,Rural,Software Engineer,57477,0 +25311,Female,51,Masters,18,2,44,20,73,6.0,3,24,Rural,Manager,49757,0 +25312,Male,37,Bachelors,3,55,0,12,38,0.0,5,59,Rural,ML Engineer,104199,0 +25313,Female,22,Bachelors,17,61,40,12,89,6.0,0,91,Urban,Software Engineer,53251,0 +25314,Female,45,Diploma,4,48,72,55,17,8.0,5,37,Urban,Data Analyst,49923,0 +25315,Male,46,Diploma,11,3,64,62,74,9.0,2,44,Urban,Data Analyst,66455,0 +25316,Male,59,Masters,1,86,94,41,82,7.0,6,9,Semi-Urban,Software Engineer,113554,0 +25317,Male,32,High School,6,39,14,76,46,3.0,0,24,Semi-Urban,ML Engineer,92897,0 +25318,Male,48,Diploma,13,44,75,36,32,7.0,0,91,Semi-Urban,Software Engineer,113573,1 +25319,Male,33,PhD,13,91,75,53,24,1.0,6,73,Urban,ML Engineer,123705,1 +25320,Male,23,Diploma,19,94,50,88,14,8.0,4,66,Semi-Urban,ML Engineer,112851,1 +25321,Male,52,High School,6,19,93,76,20,9.0,5,52,Urban,Software Engineer,137929,1 +25322,Male,34,High School,11,35,62,0,31,8.0,3,11,Rural,ML Engineer,109675,0 +25323,Male,35,High School,14,54,97,51,91,0.0,5,68,Semi-Urban,Manager,24748,1 +25324,Male,48,Masters,14,12,44,86,14,3.0,0,95,Semi-Urban,Data Analyst,23060,1 +25325,Male,32,Diploma,7,19,48,58,43,3.0,6,68,Semi-Urban,ML Engineer,56334,0 +25326,Female,33,Diploma,9,61,49,76,78,3.0,3,17,Urban,Software Engineer,42916,0 +25327,Male,54,Bachelors,6,57,45,59,19,5.0,3,94,Urban,HR Executive,128224,1 +25328,Male,33,PhD,13,95,41,24,30,7.0,5,50,Rural,HR Executive,78628,0 +25329,Male,32,Bachelors,18,61,32,66,96,6.0,5,92,Urban,Software Engineer,107781,1 +25330,Male,56,Bachelors,4,72,22,30,52,8.0,7,69,Urban,Manager,141871,0 +25331,Male,41,Bachelors,16,38,45,19,96,5.0,7,7,Urban,HR Executive,25992,0 +25332,Female,51,High School,9,61,85,92,65,2.0,1,27,Urban,ML Engineer,26456,1 +25333,Male,23,Bachelors,13,96,92,99,58,7.0,3,28,Semi-Urban,Manager,83150,1 +25334,Female,36,Bachelors,3,13,28,52,38,6.0,0,12,Rural,ML Engineer,116162,0 +25335,Male,22,Masters,14,32,23,55,16,1.0,6,52,Urban,HR Executive,103418,0 +25336,Male,22,Bachelors,15,54,91,18,70,0.0,7,87,Rural,HR Executive,146925,1 +25337,Female,54,Bachelors,15,49,42,43,82,7.0,6,49,Urban,Manager,30097,0 +25338,Female,47,Bachelors,7,58,56,97,3,2.0,1,16,Urban,ML Engineer,34976,0 +25339,Female,46,Bachelors,10,63,54,27,74,1.0,0,85,Urban,ML Engineer,55655,0 +25340,Female,31,Diploma,2,0,8,95,96,0.0,2,24,Urban,ML Engineer,127167,0 +25341,Male,42,Diploma,14,56,12,16,6,2.0,6,1,Urban,Software Engineer,24926,0 +25342,Female,23,Masters,15,52,5,49,65,0.0,0,1,Urban,HR Executive,26493,0 +25343,Male,30,Masters,1,3,28,62,12,2.0,0,13,Urban,Manager,23751,0 +25344,Female,53,Diploma,6,68,49,6,93,5.0,6,64,Urban,Data Analyst,27931,0 +25345,Male,21,Masters,11,45,65,25,12,7.0,1,59,Urban,Manager,83296,0 +25346,Male,53,Bachelors,1,38,85,60,4,3.0,5,3,Urban,HR Executive,141255,0 +25347,Female,35,Bachelors,14,18,74,79,96,6.0,3,76,Semi-Urban,ML Engineer,102073,1 +25348,Male,30,Bachelors,8,31,40,91,29,4.0,5,57,Urban,Data Analyst,34543,0 +25349,Male,50,Bachelors,1,93,75,10,74,2.0,2,85,Rural,Manager,113821,1 +25350,Male,33,High School,0,70,24,98,27,2.0,4,92,Rural,HR Executive,61359,1 +25351,Female,58,High School,8,16,41,73,13,2.0,3,35,Rural,Data Analyst,146812,0 +25352,Female,46,Bachelors,17,83,69,24,86,7.0,4,80,Urban,HR Executive,147846,1 +25353,Female,45,Masters,17,7,3,59,53,2.0,3,47,Urban,HR Executive,110243,0 +25354,Female,53,High School,19,52,47,61,18,3.0,1,45,Semi-Urban,Data Analyst,95137,0 +25355,Male,35,Bachelors,15,32,55,81,53,9.0,5,14,Urban,Software Engineer,140269,0 +25356,Male,46,PhD,9,85,8,34,3,1.0,0,84,Rural,ML Engineer,145163,0 +25357,Male,46,Bachelors,6,42,74,82,29,3.0,5,89,Urban,HR Executive,80837,1 +25358,Male,37,Bachelors,8,84,62,85,80,0.0,6,47,Urban,HR Executive,89813,1 +25359,Male,50,Diploma,0,47,87,29,16,5.0,6,36,Urban,Data Analyst,82037,0 +25360,Male,36,Bachelors,9,93,6,66,79,3.0,3,12,Urban,HR Executive,149948,0 +25361,Male,22,Diploma,19,28,69,71,14,8.0,2,73,Urban,Manager,41501,1 +25362,Female,32,Bachelors,3,9,99,0,40,3.0,4,13,Urban,ML Engineer,124459,0 +25363,Male,56,Diploma,1,4,27,6,32,5.0,0,96,Semi-Urban,Software Engineer,129958,0 +25364,Female,33,Bachelors,13,68,17,3,32,7.0,1,50,Semi-Urban,Manager,40460,0 +25365,Female,49,Bachelors,0,1,20,21,74,2.0,3,16,Urban,Software Engineer,41104,0 +25366,Female,25,Bachelors,8,95,22,54,53,0.0,1,26,Rural,Manager,65503,0 +25367,Other,49,Bachelors,12,16,10,14,95,8.0,3,61,Rural,ML Engineer,49499,0 +25368,Male,43,Diploma,3,22,38,91,82,4.0,1,97,Urban,Manager,114997,1 +25369,Female,58,Bachelors,19,49,45,55,63,1.0,3,50,Urban,Manager,126323,0 +25370,Female,44,Masters,4,69,0,59,69,8.0,4,73,Urban,Data Analyst,120292,0 +25371,Male,43,Masters,15,67,67,77,62,6.0,2,30,Semi-Urban,Manager,99998,1 +25372,Female,59,Bachelors,2,58,63,53,19,3.0,2,28,Urban,HR Executive,108629,0 +25373,Male,32,PhD,7,37,71,14,8,2.0,1,87,Urban,HR Executive,68460,0 +25374,Male,37,Masters,2,21,67,46,3,3.0,2,24,Rural,Manager,58021,0 +25375,Male,52,Diploma,19,84,53,31,68,8.0,3,89,Rural,Manager,143231,1 +25376,Other,43,High School,13,47,33,41,24,4.0,7,99,Rural,Data Analyst,36697,0 +25377,Female,26,Masters,8,90,97,36,43,8.0,0,99,Urban,ML Engineer,137618,1 +25378,Female,59,Masters,11,23,44,80,80,3.0,3,72,Rural,Software Engineer,130949,0 +25379,Female,22,Diploma,0,8,54,69,99,0.0,5,94,Semi-Urban,Manager,49975,0 +25380,Male,29,High School,14,87,50,87,19,9.0,5,56,Urban,Software Engineer,106502,1 +25381,Male,23,Bachelors,12,94,88,56,69,0.0,4,23,Urban,Data Analyst,58510,1 +25382,Female,42,High School,11,17,46,0,36,0.0,2,1,Urban,HR Executive,130068,0 +25383,Male,56,Masters,15,62,87,25,14,4.0,5,54,Urban,Data Analyst,60994,0 +25384,Male,31,Bachelors,10,64,20,69,75,8.0,1,88,Rural,HR Executive,107921,1 +25385,Male,59,Bachelors,2,35,24,77,52,8.0,3,17,Urban,HR Executive,60582,0 +25386,Male,59,Diploma,17,21,19,26,3,4.0,0,98,Urban,HR Executive,119645,0 +25387,Female,32,Bachelors,3,37,84,73,42,4.0,3,71,Urban,Software Engineer,106496,1 +25388,Male,24,Masters,13,84,11,82,93,8.0,0,79,Urban,ML Engineer,89794,1 +25389,Female,26,High School,11,80,2,40,90,1.0,2,38,Semi-Urban,Manager,107244,0 +25390,Female,56,Bachelors,1,42,20,82,53,3.0,4,87,Semi-Urban,ML Engineer,38003,0 +25391,Male,35,Diploma,15,34,45,96,91,6.0,7,22,Semi-Urban,Manager,104835,0 +25392,Male,35,Bachelors,2,55,85,43,7,1.0,2,37,Urban,Manager,101772,0 +25393,Male,41,PhD,11,48,33,78,19,1.0,5,62,Urban,Data Analyst,148126,0 +25394,Other,50,Masters,18,97,38,32,9,7.0,0,67,Urban,Software Engineer,50015,0 +25395,Male,37,PhD,18,84,13,60,79,4.0,7,58,Urban,Data Analyst,58466,0 +25396,Male,32,Bachelors,17,68,55,14,92,6.0,6,91,Urban,HR Executive,121603,0 +25397,Female,27,High School,8,79,51,37,40,3.0,2,82,Rural,Data Analyst,95471,1 +25398,Male,30,Bachelors,17,87,6,52,87,6.0,0,66,Semi-Urban,HR Executive,95715,0 +25399,Other,36,Masters,19,12,30,46,27,4.0,7,41,Urban,Software Engineer,70384,0 +25400,Female,26,Diploma,0,85,55,35,37,3.0,4,41,Rural,Software Engineer,99312,0 +25401,Male,41,Diploma,16,60,76,79,42,9.0,1,49,Rural,Data Analyst,127622,1 +25402,Female,42,Masters,12,54,51,68,37,2.0,7,49,Urban,Data Analyst,134464,0 +25403,Male,59,Bachelors,13,42,59,74,45,9.0,4,10,Rural,Software Engineer,55593,0 +25404,Female,33,Diploma,12,1,97,41,1,7.0,1,95,Urban,ML Engineer,77026,0 +25405,Female,25,Masters,11,31,3,91,37,9.0,5,10,Urban,Data Analyst,55613,0 +25406,Male,24,Bachelors,19,12,3,27,50,0.0,4,30,Urban,Data Analyst,138600,0 +25407,Male,40,Masters,0,93,57,33,88,8.0,0,12,Urban,Data Analyst,99073,0 +25408,Female,23,Masters,4,68,52,67,50,9.0,5,19,Urban,Software Engineer,43285,0 +25409,Male,44,High School,14,76,11,32,10,8.0,2,25,Urban,Software Engineer,110614,0 +25410,Female,42,Bachelors,18,27,81,1,44,4.0,6,22,Urban,Data Analyst,132229,0 +25411,Male,29,Masters,3,44,57,73,92,3.0,4,79,Urban,Data Analyst,42858,1 +25412,Male,51,High School,13,80,76,20,98,9.0,0,10,Rural,ML Engineer,100432,0 +25413,Female,35,Masters,7,82,1,33,36,5.0,1,86,Rural,ML Engineer,94258,0 +25414,Male,27,Bachelors,15,89,8,74,93,2.0,1,72,Urban,Manager,74749,1 +25415,Female,35,Bachelors,3,4,28,73,0,0.0,1,34,Semi-Urban,Software Engineer,110815,0 +25416,Male,36,Bachelors,0,50,67,58,79,0.0,4,68,Urban,HR Executive,44238,1 +25417,Male,58,Diploma,8,7,59,49,50,0.0,5,69,Semi-Urban,HR Executive,61989,0 +25418,Female,36,High School,4,65,8,63,38,2.0,2,85,Urban,Manager,85492,0 +25419,Male,24,Diploma,16,36,9,56,6,5.0,7,56,Urban,Data Analyst,38121,0 +25420,Female,53,Bachelors,18,19,50,41,43,9.0,5,3,Semi-Urban,Manager,140054,0 +25421,Female,45,Masters,2,63,60,36,87,3.0,5,21,Semi-Urban,ML Engineer,31743,0 +25422,Female,24,Bachelors,6,22,0,16,84,5.0,0,15,Rural,Manager,70507,0 +25423,Female,35,Bachelors,3,88,18,34,72,9.0,3,39,Urban,Data Analyst,67726,0 +25424,Male,32,Diploma,19,87,89,42,67,2.0,1,19,Urban,Manager,34252,1 +25425,Female,56,Bachelors,16,10,99,13,35,2.0,0,26,Urban,ML Engineer,103257,0 +25426,Male,30,Diploma,5,50,63,43,32,5.0,7,23,Rural,Software Engineer,43748,0 +25427,Male,22,Diploma,17,95,50,79,49,6.0,6,2,Urban,Software Engineer,24050,0 +25428,Male,28,PhD,6,14,69,75,7,5.0,2,1,Semi-Urban,Software Engineer,73812,0 +25429,Male,24,High School,17,73,25,2,43,5.0,6,59,Urban,HR Executive,97853,0 +25430,Female,44,Diploma,6,70,61,33,53,6.0,2,78,Urban,Software Engineer,94968,1 +25431,Male,24,High School,16,94,73,53,75,0.0,6,79,Semi-Urban,Data Analyst,52914,1 +25432,Male,32,High School,1,31,23,5,62,5.0,5,99,Rural,HR Executive,71865,0 +25433,Male,40,Masters,4,84,45,45,48,3.0,1,94,Semi-Urban,ML Engineer,149676,1 +25434,Male,55,Masters,2,40,37,40,57,2.0,0,0,Urban,ML Engineer,69579,0 +25435,Female,55,Masters,10,16,8,54,38,6.0,7,33,Urban,HR Executive,58221,0 +25436,Male,29,Bachelors,0,65,28,83,83,2.0,0,87,Urban,ML Engineer,39014,1 +25437,Male,31,High School,14,58,57,92,68,9.0,2,29,Urban,HR Executive,38250,1 +25438,Male,50,Diploma,16,70,16,2,10,1.0,2,16,Urban,Software Engineer,133828,0 +25439,Male,57,Diploma,9,8,42,79,52,8.0,0,59,Urban,Software Engineer,123455,0 +25440,Male,38,High School,7,24,87,99,4,8.0,3,4,Urban,ML Engineer,90265,0 +25441,Male,56,High School,9,98,42,61,10,2.0,4,3,Semi-Urban,HR Executive,71453,0 +25442,Male,34,Diploma,15,1,80,29,58,3.0,2,87,Urban,Data Analyst,135034,0 +25443,Male,42,Bachelors,8,23,74,35,14,9.0,0,78,Rural,ML Engineer,27670,0 +25444,Male,26,Bachelors,19,1,59,95,16,7.0,6,37,Rural,Software Engineer,109031,0 +25445,Other,55,Diploma,0,50,18,40,9,2.0,0,5,Urban,ML Engineer,129626,0 +25446,Male,24,Masters,19,94,74,22,24,9.0,6,10,Semi-Urban,Data Analyst,88792,0 +25447,Female,58,Masters,15,15,86,3,59,7.0,6,7,Semi-Urban,Data Analyst,35055,0 +25448,Female,29,Bachelors,3,61,18,86,52,2.0,6,59,Urban,Manager,100379,0 +25449,Male,48,Masters,14,57,76,71,26,1.0,1,27,Urban,Data Analyst,48185,0 +25450,Other,33,Diploma,12,37,73,18,13,2.0,4,5,Rural,ML Engineer,115098,0 +25451,Female,59,PhD,8,75,65,31,63,6.0,3,5,Semi-Urban,Manager,21311,0 +25452,Female,30,Diploma,10,15,87,43,39,3.0,0,36,Urban,HR Executive,74174,0 +25453,Male,50,Masters,6,85,9,88,66,5.0,0,45,Semi-Urban,ML Engineer,121520,0 +25454,Male,31,Masters,12,17,81,87,1,2.0,2,34,Urban,Manager,104322,0 +25455,Male,38,Diploma,12,57,89,8,10,1.0,4,2,Semi-Urban,Data Analyst,143771,0 +25456,Male,49,Masters,8,11,24,22,14,0.0,7,34,Urban,Software Engineer,75890,0 +25457,Female,30,Diploma,11,79,30,94,75,6.0,5,56,Semi-Urban,Data Analyst,116356,1 +25458,Female,26,Diploma,19,73,53,80,71,5.0,0,21,Urban,Software Engineer,131973,0 +25459,Male,32,Bachelors,12,65,31,84,46,4.0,3,51,Rural,ML Engineer,32454,0 +25460,Female,40,Bachelors,13,30,30,94,95,7.0,2,97,Urban,Data Analyst,136196,1 +25461,Female,30,Bachelors,3,98,51,8,28,1.0,0,27,Urban,Manager,133664,0 +25462,Male,36,Diploma,12,44,26,31,22,1.0,6,28,Urban,Software Engineer,124228,0 +25463,Male,21,Masters,6,63,82,44,26,7.0,5,67,Semi-Urban,HR Executive,115870,1 +25464,Male,54,Bachelors,15,41,69,13,0,7.0,0,6,Rural,Data Analyst,33359,0 +25465,Female,36,High School,8,53,53,29,55,0.0,0,52,Urban,HR Executive,97719,0 +25466,Female,57,Bachelors,2,45,63,79,30,4.0,5,3,Urban,Data Analyst,98507,0 +25467,Male,37,Bachelors,14,41,32,61,66,0.0,5,38,Urban,Data Analyst,83010,0 +25468,Male,37,Diploma,4,47,37,92,29,9.0,6,67,Rural,Manager,51934,1 +25469,Female,30,High School,12,37,76,30,22,1.0,2,35,Urban,ML Engineer,60296,0 +25470,Female,34,Masters,19,57,96,9,12,1.0,7,61,Semi-Urban,ML Engineer,102029,0 +25471,Male,59,Masters,7,62,99,83,2,7.0,5,79,Semi-Urban,HR Executive,145852,1 +25472,Male,43,Bachelors,15,42,70,75,0,3.0,3,55,Urban,HR Executive,54346,1 +25473,Female,55,Diploma,16,28,9,37,95,8.0,1,4,Urban,ML Engineer,90372,0 +25474,Male,26,Masters,9,37,71,77,71,9.0,6,36,Urban,Data Analyst,118831,0 +25475,Male,48,Masters,0,0,95,55,89,2.0,4,32,Semi-Urban,Software Engineer,72253,0 +25476,Female,38,Bachelors,19,26,95,55,59,9.0,5,37,Urban,ML Engineer,149568,0 +25477,Male,58,Masters,14,75,80,57,43,6.0,4,39,Urban,Manager,70732,1 +25478,Female,44,Masters,17,8,13,10,13,1.0,2,26,Urban,Manager,132060,0 +25479,Male,33,Bachelors,12,26,17,59,89,7.0,2,47,Urban,Software Engineer,99486,0 +25480,Male,23,High School,9,61,61,78,2,1.0,3,85,Urban,HR Executive,108922,1 +25481,Male,56,High School,17,62,77,47,61,1.0,6,18,Semi-Urban,ML Engineer,24787,0 +25482,Male,33,Diploma,19,16,61,22,97,2.0,2,34,Urban,Manager,143593,0 +25483,Male,35,Bachelors,8,29,29,36,17,9.0,3,78,Semi-Urban,Manager,98820,0 +25484,Female,52,Diploma,18,82,21,90,8,9.0,1,13,Urban,HR Executive,85682,0 +25485,Male,38,Masters,9,91,49,77,8,2.0,0,53,Urban,HR Executive,66387,1 +25486,Female,30,High School,14,85,97,11,66,5.0,6,78,Rural,Manager,28062,1 +25487,Male,29,Diploma,6,70,8,10,83,8.0,7,56,Urban,ML Engineer,95388,0 +25488,Male,23,Bachelors,8,81,41,87,41,1.0,6,41,Urban,Data Analyst,33099,1 +25489,Male,49,Bachelors,18,55,36,39,89,4.0,5,54,Urban,ML Engineer,34045,0 +25490,Female,35,Bachelors,5,85,0,88,95,2.0,0,0,Rural,ML Engineer,82562,0 +25491,Male,29,Bachelors,9,31,0,19,65,2.0,5,96,Semi-Urban,ML Engineer,106997,0 +25492,Male,51,Bachelors,5,43,64,81,91,3.0,0,60,Urban,Data Analyst,131442,1 +25493,Female,52,Bachelors,8,43,70,68,52,5.0,7,26,Rural,Data Analyst,114466,0 +25494,Male,25,High School,4,61,88,27,44,9.0,4,49,Urban,ML Engineer,24660,0 +25495,Male,41,Diploma,9,40,58,79,19,5.0,5,85,Semi-Urban,HR Executive,91914,1 +25496,Male,23,Diploma,15,23,19,74,10,8.0,1,44,Urban,Data Analyst,69187,0 +25497,Female,56,Bachelors,0,42,90,26,37,6.0,5,20,Semi-Urban,HR Executive,65067,0 +25498,Male,47,High School,6,66,1,64,20,7.0,4,50,Semi-Urban,Data Analyst,142595,0 +25499,Female,31,Diploma,13,36,43,3,75,2.0,5,8,Urban,Data Analyst,80405,0 +25500,Female,28,Masters,15,92,28,63,25,8.0,6,41,Urban,HR Executive,115622,0 +25501,Female,35,Masters,11,0,99,7,72,8.0,7,76,Semi-Urban,HR Executive,74399,0 +25502,Male,33,High School,0,97,49,86,39,9.0,7,12,Urban,ML Engineer,115213,1 +25503,Other,28,PhD,8,28,37,60,5,2.0,0,21,Semi-Urban,Software Engineer,143734,0 +25504,Male,55,Masters,14,73,11,44,22,8.0,7,99,Urban,Manager,23266,0 +25505,Male,24,Masters,4,32,33,65,85,7.0,7,12,Urban,Manager,113277,0 +25506,Male,29,Diploma,2,5,73,59,57,8.0,6,87,Semi-Urban,HR Executive,42398,0 +25507,Female,54,Diploma,13,73,8,94,45,8.0,1,16,Rural,HR Executive,130304,0 +25508,Male,21,Diploma,9,42,64,89,98,3.0,6,1,Rural,Software Engineer,35717,0 +25509,Male,46,Diploma,7,76,2,67,4,2.0,3,3,Rural,HR Executive,53363,0 +25510,Female,52,Bachelors,10,13,86,51,85,3.0,1,73,Semi-Urban,ML Engineer,100111,0 +25511,Male,54,Bachelors,13,40,48,33,14,5.0,3,27,Semi-Urban,Manager,60773,0 +25512,Male,48,High School,18,80,40,96,59,3.0,6,95,Urban,Data Analyst,141648,1 +25513,Female,35,Bachelors,12,33,81,12,30,7.0,1,92,Urban,ML Engineer,110179,0 +25514,Female,43,High School,7,75,10,80,70,0.0,5,51,Semi-Urban,ML Engineer,31631,0 +25515,Male,35,Bachelors,11,46,76,20,46,5.0,2,48,Semi-Urban,Data Analyst,130029,0 +25516,Male,37,Bachelors,2,68,56,91,87,4.0,1,36,Urban,ML Engineer,52486,1 +25517,Other,43,Masters,1,21,56,99,84,9.0,5,89,Semi-Urban,Manager,130265,1 +25518,Male,31,Bachelors,2,23,47,82,73,6.0,5,16,Urban,HR Executive,67791,0 +25519,Male,56,Masters,12,80,93,9,50,0.0,6,86,Semi-Urban,HR Executive,33143,1 +25520,Female,41,Masters,12,2,10,16,18,6.0,7,17,Urban,HR Executive,24373,0 +25521,Male,51,Diploma,18,79,3,95,25,9.0,4,60,Urban,ML Engineer,23534,1 +25522,Male,40,Diploma,8,25,28,85,21,5.0,3,84,Semi-Urban,ML Engineer,59273,0 +25523,Male,48,Diploma,8,63,52,94,40,2.0,2,16,Urban,HR Executive,70708,0 +25524,Male,42,Diploma,6,48,31,57,95,3.0,2,55,Urban,Software Engineer,130593,0 +25525,Female,41,High School,16,92,56,28,61,7.0,4,17,Urban,HR Executive,49393,0 +25526,Male,59,PhD,1,39,96,38,42,1.0,1,13,Urban,ML Engineer,44088,0 +25527,Male,58,High School,6,16,28,86,67,8.0,5,86,Urban,ML Engineer,76121,0 +25528,Female,38,Masters,12,72,65,79,84,9.0,3,90,Urban,Manager,99077,1 +25529,Male,44,Masters,11,75,73,15,52,4.0,4,66,Urban,Software Engineer,62974,0 +25530,Female,50,Bachelors,17,41,92,42,2,5.0,4,99,Rural,ML Engineer,80798,1 +25531,Male,58,Masters,8,77,45,80,54,0.0,5,45,Urban,Data Analyst,48450,1 +25532,Female,54,High School,16,7,94,10,34,9.0,4,29,Urban,Data Analyst,43966,0 +25533,Male,36,Diploma,1,95,16,80,83,3.0,4,25,Urban,Manager,94808,0 +25534,Male,59,PhD,1,1,41,51,66,3.0,4,35,Rural,ML Engineer,47511,0 +25535,Male,46,Masters,3,75,64,44,68,4.0,3,16,Semi-Urban,Data Analyst,77222,0 +25536,Female,27,PhD,12,69,42,97,27,7.0,6,7,Urban,HR Executive,143958,0 +25537,Female,22,Bachelors,7,8,16,49,82,4.0,1,5,Urban,HR Executive,21086,0 +25538,Female,24,Masters,16,39,10,24,33,4.0,0,28,Semi-Urban,Software Engineer,76725,0 +25539,Male,28,Diploma,16,70,5,11,46,3.0,2,3,Urban,Data Analyst,100561,0 +25540,Male,27,Bachelors,1,26,21,66,93,1.0,6,14,Rural,ML Engineer,49711,0 +25541,Female,25,Bachelors,9,3,30,45,29,1.0,6,18,Urban,ML Engineer,104708,0 +25542,Female,28,High School,10,87,88,73,47,4.0,1,87,Rural,Data Analyst,97223,1 +25543,Female,34,High School,4,59,41,62,56,1.0,5,22,Semi-Urban,Manager,116818,0 +25544,Male,22,Diploma,16,68,60,65,15,7.0,5,96,Semi-Urban,Data Analyst,23008,1 +25545,Male,43,High School,19,52,27,51,76,1.0,2,3,Urban,HR Executive,56780,0 +25546,Male,23,Masters,15,34,13,76,28,9.0,4,65,Rural,Software Engineer,22711,0 +25547,Male,38,Diploma,13,68,60,25,2,0.0,0,55,Rural,Software Engineer,58319,0 +25548,Female,38,High School,11,32,1,49,72,0.0,4,95,Urban,HR Executive,42037,0 +25549,Female,44,Bachelors,14,62,3,6,72,6.0,0,7,Urban,Manager,127840,0 +25550,Male,33,Bachelors,11,51,65,65,50,4.0,0,55,Urban,Data Analyst,23852,1 +25551,Male,30,High School,8,47,29,68,76,9.0,2,0,Urban,Manager,147963,0 +25552,Male,27,Masters,2,81,45,43,85,8.0,0,51,Urban,Software Engineer,90057,0 +25553,Female,39,High School,18,51,80,58,78,7.0,4,95,Urban,Manager,143485,1 +25554,Female,28,Bachelors,16,15,38,59,63,4.0,4,74,Rural,Manager,100329,0 +25555,Male,39,Masters,1,54,65,4,96,3.0,3,94,Urban,Data Analyst,119720,0 +25556,Female,59,Bachelors,1,99,79,4,38,4.0,7,28,Semi-Urban,HR Executive,56898,0 +25557,Male,42,Bachelors,2,95,49,67,50,2.0,1,70,Urban,Software Engineer,136781,1 +25558,Male,40,Diploma,15,69,66,23,71,1.0,7,91,Urban,ML Engineer,43226,1 +25559,Female,50,PhD,11,17,69,46,11,6.0,6,32,Semi-Urban,HR Executive,66041,0 +25560,Female,53,Bachelors,6,31,38,44,90,0.0,6,95,Urban,Manager,50440,0 +25561,Female,33,Bachelors,4,66,25,98,32,4.0,3,99,Semi-Urban,HR Executive,42981,1 +25562,Male,34,Bachelors,6,35,13,46,54,0.0,6,46,Urban,Software Engineer,54891,0 +25563,Male,59,Bachelors,13,3,42,24,94,1.0,6,73,Urban,Software Engineer,40445,0 +25564,Male,21,High School,17,69,40,20,37,6.0,0,35,Rural,HR Executive,99166,0 +25565,Male,33,Bachelors,12,21,33,44,46,7.0,2,98,Semi-Urban,Software Engineer,53059,0 +25566,Male,53,PhD,0,70,61,95,12,0.0,4,77,Semi-Urban,Software Engineer,29786,1 +25567,Male,44,High School,11,40,32,6,86,4.0,0,90,Urban,ML Engineer,28629,0 +25568,Male,37,Diploma,7,39,35,56,10,3.0,7,69,Rural,Data Analyst,65645,0 +25569,Male,29,Bachelors,7,64,18,11,97,2.0,7,97,Rural,Manager,95227,0 +25570,Female,45,Diploma,2,58,65,13,25,7.0,5,17,Urban,HR Executive,147818,0 +25571,Female,37,Diploma,5,58,90,27,20,4.0,3,36,Urban,Manager,148406,0 +25572,Female,23,Masters,11,7,41,57,35,5.0,3,3,Rural,HR Executive,119837,0 +25573,Male,48,High School,14,90,70,47,75,4.0,4,70,Urban,ML Engineer,142382,1 +25574,Male,41,Masters,8,62,16,28,99,9.0,3,9,Urban,Software Engineer,27712,0 +25575,Male,36,Masters,11,74,97,84,82,1.0,5,15,Semi-Urban,Manager,113063,1 +25576,Male,51,High School,8,98,54,83,39,9.0,2,28,Semi-Urban,HR Executive,137610,1 +25577,Male,21,PhD,2,57,51,95,69,0.0,7,99,Urban,ML Engineer,40784,1 +25578,Male,38,Masters,2,84,33,96,88,4.0,4,6,Semi-Urban,Manager,62067,0 +25579,Female,45,Bachelors,5,23,52,44,16,3.0,4,43,Rural,ML Engineer,108388,0 +25580,Other,46,Bachelors,12,33,57,44,74,4.0,0,21,Rural,ML Engineer,61997,0 +25581,Male,54,PhD,10,72,34,49,59,1.0,1,14,Urban,Manager,80750,0 +25582,Female,25,Masters,1,80,46,10,78,3.0,4,2,Semi-Urban,Manager,95197,0 +25583,Male,26,Bachelors,9,62,98,29,32,2.0,7,0,Urban,Manager,51449,0 +25584,Female,48,Diploma,15,41,96,12,19,8.0,7,91,Urban,Data Analyst,58108,0 +25585,Female,47,Masters,3,50,82,62,91,6.0,6,46,Semi-Urban,ML Engineer,59642,0 +25586,Female,42,Bachelors,19,88,55,62,59,2.0,0,12,Urban,Software Engineer,68807,0 +25587,Male,51,High School,8,41,52,76,75,6.0,0,91,Urban,ML Engineer,86816,1 +25588,Male,31,Bachelors,7,53,7,93,59,6.0,5,56,Urban,Manager,44560,0 +25589,Male,40,High School,11,3,6,52,77,8.0,3,1,Rural,HR Executive,125567,0 +25590,Male,45,Masters,1,97,62,41,10,5.0,5,84,Urban,Data Analyst,49716,1 +25591,Female,37,Diploma,5,25,43,26,18,6.0,3,2,Urban,Software Engineer,131032,0 +25592,Female,44,Bachelors,14,12,74,30,48,1.0,2,27,Semi-Urban,Software Engineer,59510,0 +25593,Female,27,Diploma,9,69,41,71,64,2.0,6,71,Urban,Software Engineer,81602,1 +25594,Male,24,Masters,0,74,75,32,17,2.0,6,42,Urban,Data Analyst,131649,0 +25595,Female,47,Masters,8,20,31,13,51,9.0,3,8,Urban,Data Analyst,134317,0 +25596,Male,45,Bachelors,17,97,18,56,68,5.0,4,97,Rural,Data Analyst,136882,1 +25597,Male,42,High School,16,81,62,51,66,7.0,4,11,Urban,Manager,139961,0 +25598,Female,39,Masters,10,60,94,49,58,1.0,7,65,Urban,Manager,100524,1 +25599,Male,38,High School,5,81,8,26,60,9.0,7,87,Urban,Data Analyst,117019,0 +25600,Male,59,Masters,0,1,75,63,88,8.0,7,43,Urban,ML Engineer,102300,0 +25601,Male,33,Masters,11,83,56,79,78,0.0,6,43,Semi-Urban,Data Analyst,120408,1 +25602,Female,34,High School,6,73,26,55,99,3.0,0,14,Rural,Data Analyst,140879,0 +25603,Female,58,Diploma,0,76,13,42,33,4.0,7,65,Urban,ML Engineer,53960,0 +25604,Male,25,Masters,19,79,51,8,69,9.0,0,68,Urban,Data Analyst,28807,0 +25605,Female,27,Masters,7,15,6,16,88,2.0,1,43,Urban,Software Engineer,143534,0 +25606,Female,24,High School,4,2,99,50,42,5.0,6,94,Rural,Data Analyst,62314,1 +25607,Female,54,Diploma,14,71,96,7,61,6.0,1,1,Semi-Urban,Software Engineer,20669,0 +25608,Male,28,Bachelors,0,86,40,76,44,6.0,5,42,Semi-Urban,Data Analyst,123610,1 +25609,Female,25,Masters,2,97,16,45,11,9.0,0,26,Urban,Manager,126116,0 +25610,Female,40,Bachelors,1,66,63,29,71,2.0,7,78,Urban,Software Engineer,84764,0 +25611,Male,54,Masters,17,77,47,16,71,6.0,2,59,Urban,ML Engineer,75134,0 +25612,Male,40,Diploma,9,53,89,42,57,5.0,0,95,Urban,Manager,69510,1 +25613,Male,26,High School,18,19,26,49,57,9.0,2,50,Urban,Data Analyst,145324,0 +25614,Male,50,Masters,2,55,67,13,32,8.0,0,23,Rural,ML Engineer,76246,0 +25615,Male,34,Bachelors,4,61,86,8,18,6.0,0,48,Rural,HR Executive,54694,0 +25616,Male,58,Masters,10,31,38,85,25,4.0,7,14,Urban,Manager,77828,0 +25617,Male,46,Bachelors,5,28,55,17,13,2.0,2,48,Urban,HR Executive,84934,0 +25618,Male,41,High School,9,15,45,1,30,4.0,7,87,Urban,Software Engineer,64144,0 +25619,Male,49,Bachelors,2,8,79,86,37,1.0,2,20,Urban,ML Engineer,92801,0 +25620,Female,57,Bachelors,11,68,5,84,82,9.0,7,51,Semi-Urban,Software Engineer,113174,0 +25621,Female,59,Bachelors,5,73,59,90,68,5.0,3,23,Semi-Urban,Software Engineer,90418,1 +25622,Male,50,Masters,17,86,69,26,76,8.0,2,9,Urban,Manager,44385,0 +25623,Male,54,Masters,13,70,14,69,10,0.0,3,70,Semi-Urban,Data Analyst,31565,0 +25624,Male,46,Bachelors,2,24,33,25,92,2.0,6,16,Rural,HR Executive,35128,0 +25625,Male,58,PhD,13,42,31,49,51,1.0,0,94,Urban,ML Engineer,140436,0 +25626,Male,38,Bachelors,5,90,92,58,26,5.0,3,29,Semi-Urban,ML Engineer,113983,1 +25627,Female,53,Diploma,0,42,74,82,53,4.0,7,37,Semi-Urban,Data Analyst,106054,0 +25628,Male,39,Masters,3,47,78,73,83,3.0,5,68,Urban,ML Engineer,149265,1 +25629,Female,29,High School,17,50,46,1,49,8.0,4,2,Urban,Manager,134094,0 +25630,Female,39,Masters,10,23,52,48,73,7.0,2,39,Rural,Software Engineer,45185,0 +25631,Male,49,High School,14,73,71,37,24,6.0,4,44,Semi-Urban,HR Executive,94453,0 +25632,Male,26,Bachelors,16,22,36,64,58,3.0,4,87,Urban,HR Executive,94007,0 +25633,Male,51,Diploma,9,44,81,56,52,5.0,4,57,Urban,ML Engineer,30197,1 +25634,Male,47,High School,0,60,90,19,51,5.0,3,34,Urban,Manager,37625,0 +25635,Male,50,Bachelors,14,62,40,16,15,7.0,0,52,Urban,ML Engineer,107810,0 +25636,Other,42,Masters,13,64,62,95,51,6.0,3,92,Urban,ML Engineer,68700,1 +25637,Female,42,Bachelors,8,71,19,86,34,7.0,2,77,Urban,Software Engineer,49787,1 +25638,Female,27,Diploma,2,28,33,8,81,9.0,4,26,Rural,Data Analyst,126256,0 +25639,Male,47,Bachelors,2,67,40,18,48,3.0,7,2,Urban,Data Analyst,45127,0 +25640,Male,25,Diploma,14,64,79,9,5,9.0,5,91,Semi-Urban,Data Analyst,74276,1 +25641,Male,28,Bachelors,14,54,88,57,67,0.0,0,53,Urban,Data Analyst,90484,1 +25642,Male,26,High School,4,12,18,60,53,9.0,6,50,Urban,ML Engineer,91005,0 +25643,Male,53,Masters,13,72,16,89,76,4.0,2,44,Urban,ML Engineer,87957,0 +25644,Female,50,Bachelors,13,63,44,75,90,4.0,6,33,Semi-Urban,HR Executive,83357,0 +25645,Male,29,Diploma,14,95,18,41,10,0.0,0,48,Rural,ML Engineer,20985,0 +25646,Female,46,Masters,2,39,76,79,1,9.0,6,62,Urban,HR Executive,90143,1 +25647,Female,21,Diploma,16,80,37,31,88,1.0,7,90,Urban,Manager,97220,0 +25648,Male,32,Masters,5,24,53,39,0,6.0,7,76,Urban,Manager,62968,0 +25649,Female,44,Bachelors,17,79,51,63,99,5.0,4,5,Urban,Software Engineer,33042,0 +25650,Male,44,Bachelors,9,49,0,35,57,2.0,2,98,Rural,HR Executive,137729,0 +25651,Male,52,Masters,8,70,20,54,83,5.0,2,61,Rural,Data Analyst,24840,0 +25652,Female,48,Bachelors,3,79,87,31,98,2.0,7,75,Urban,Software Engineer,68460,1 +25653,Male,28,High School,10,60,30,84,46,8.0,6,7,Urban,HR Executive,70998,0 +25654,Female,33,Diploma,2,67,50,23,34,4.0,3,21,Semi-Urban,Software Engineer,33385,0 +25655,Female,47,High School,6,42,58,97,7,5.0,5,14,Urban,ML Engineer,99818,0 +25656,Female,37,Bachelors,7,47,94,38,23,6.0,3,76,Rural,Manager,146000,1 +25657,Other,48,Bachelors,11,50,59,2,33,4.0,0,85,Semi-Urban,HR Executive,120172,0 +25658,Male,48,Bachelors,14,69,70,26,91,6.0,1,26,Urban,ML Engineer,85254,0 +25659,Male,31,High School,10,94,63,53,9,5.0,5,61,Semi-Urban,Data Analyst,107520,1 +25660,Male,51,Masters,3,72,99,92,67,9.0,3,73,Urban,Data Analyst,109728,1 +25661,Male,29,Masters,3,51,59,87,65,9.0,5,45,Urban,Manager,40221,1 +25662,Male,50,Bachelors,15,90,60,47,13,6.0,2,95,Urban,Data Analyst,82043,1 +25663,Female,22,Bachelors,19,20,54,4,4,5.0,6,74,Semi-Urban,Data Analyst,147013,0 +25664,Male,36,Masters,6,29,63,34,18,3.0,6,94,Semi-Urban,Manager,117564,0 +25665,Other,48,Masters,16,20,96,31,60,6.0,6,59,Urban,HR Executive,77266,0 +25666,Female,41,Diploma,8,32,11,75,8,2.0,5,26,Rural,Software Engineer,24968,0 +25667,Male,27,Diploma,16,70,92,54,66,8.0,5,35,Urban,HR Executive,58216,1 +25668,Male,28,Bachelors,19,40,66,87,46,8.0,7,60,Semi-Urban,HR Executive,117079,1 +25669,Male,56,Diploma,16,90,51,3,60,2.0,2,80,Semi-Urban,Manager,49017,0 +25670,Male,58,Masters,5,56,91,15,72,9.0,4,29,Urban,Manager,32362,0 +25671,Male,37,Bachelors,17,76,25,76,57,6.0,5,25,Urban,Manager,139290,0 +25672,Male,59,Diploma,8,31,69,57,98,7.0,7,57,Semi-Urban,HR Executive,136724,0 +25673,Female,26,Bachelors,4,70,72,29,13,2.0,7,53,Semi-Urban,HR Executive,42105,0 +25674,Male,55,Diploma,1,26,23,39,90,3.0,0,1,Urban,HR Executive,82024,0 +25675,Female,39,Masters,12,64,45,29,60,1.0,7,48,Rural,Data Analyst,29829,0 +25676,Female,51,Bachelors,3,85,97,82,44,3.0,1,37,Semi-Urban,Data Analyst,123132,1 +25677,Male,24,Diploma,18,95,65,64,66,9.0,7,28,Semi-Urban,Software Engineer,104538,1 +25678,Male,45,Masters,2,90,53,83,73,9.0,3,70,Urban,HR Executive,104739,1 +25679,Female,56,Bachelors,15,20,87,85,19,6.0,6,46,Urban,Data Analyst,60169,0 +25680,Other,52,Masters,4,19,60,76,18,6.0,0,62,Urban,Manager,117571,0 +25681,Male,26,Bachelors,13,71,65,80,62,4.0,4,28,Urban,HR Executive,54456,1 +25682,Male,32,Bachelors,7,61,30,38,48,8.0,6,26,Urban,Software Engineer,47659,0 +25683,Male,23,Bachelors,7,74,65,17,97,2.0,0,66,Urban,HR Executive,62521,0 +25684,Male,37,Diploma,4,86,55,77,86,5.0,1,2,Semi-Urban,Data Analyst,146742,0 +25685,Male,43,Bachelors,13,15,88,13,58,7.0,5,74,Urban,Data Analyst,46572,0 +25686,Male,46,Masters,4,34,92,23,79,2.0,4,53,Semi-Urban,Software Engineer,103066,0 +25687,Female,34,Masters,15,32,6,85,89,8.0,4,63,Rural,Software Engineer,105644,0 +25688,Male,29,Bachelors,14,51,51,85,39,4.0,4,83,Rural,Manager,137969,1 +25689,Male,44,Diploma,0,51,31,41,8,9.0,5,91,Semi-Urban,ML Engineer,25343,0 +25690,Male,24,Bachelors,14,38,66,85,1,5.0,3,51,Urban,ML Engineer,131903,1 +25691,Female,53,High School,5,60,62,0,67,5.0,7,71,Rural,Software Engineer,136867,0 +25692,Male,39,PhD,2,87,77,65,2,0.0,4,92,Semi-Urban,HR Executive,62145,1 +25693,Other,28,Bachelors,17,38,23,9,31,6.0,5,17,Rural,HR Executive,30831,0 +25694,Male,31,Masters,11,47,79,29,73,3.0,1,62,Urban,HR Executive,128414,0 +25695,Male,41,High School,9,65,95,4,53,5.0,1,52,Urban,Manager,77238,0 +25696,Male,26,Bachelors,1,85,12,1,58,2.0,7,72,Semi-Urban,Software Engineer,41947,0 +25697,Female,37,Bachelors,1,19,84,21,70,0.0,6,64,Urban,HR Executive,43290,0 +25698,Male,22,Bachelors,9,67,56,56,95,6.0,3,85,Urban,Manager,71517,1 +25699,Female,28,Diploma,17,10,53,6,0,7.0,7,31,Rural,Data Analyst,82580,0 +25700,Female,52,Masters,5,97,76,91,38,0.0,5,41,Urban,Manager,65891,1 +25701,Female,23,Diploma,0,73,68,54,92,7.0,1,61,Semi-Urban,HR Executive,59936,1 +25702,Male,54,High School,11,3,42,72,8,3.0,2,61,Semi-Urban,Software Engineer,39244,0 +25703,Female,33,Bachelors,18,36,73,84,82,3.0,7,53,Urban,HR Executive,62085,1 +25704,Male,43,Bachelors,4,69,91,33,77,5.0,5,63,Urban,ML Engineer,139580,1 +25705,Male,33,High School,13,71,44,86,99,4.0,2,25,Urban,ML Engineer,120323,0 +25706,Male,44,Masters,15,82,96,97,2,5.0,3,67,Urban,ML Engineer,24041,1 +25707,Female,30,Diploma,2,82,43,42,36,0.0,5,32,Semi-Urban,HR Executive,126036,0 +25708,Male,49,Masters,17,54,41,52,30,4.0,4,11,Urban,Data Analyst,79887,0 +25709,Male,48,Masters,15,79,36,42,14,5.0,4,37,Urban,Manager,113675,0 +25710,Male,56,Bachelors,15,73,25,51,50,2.0,6,75,Urban,Software Engineer,127713,0 +25711,Male,36,Masters,14,4,55,45,91,9.0,5,5,Semi-Urban,HR Executive,69711,0 +25712,Male,21,Masters,12,52,14,62,56,6.0,0,90,Urban,Manager,101652,0 +25713,Male,28,High School,17,32,74,48,25,4.0,2,80,Rural,HR Executive,50121,0 +25714,Male,22,Masters,16,54,75,41,44,4.0,3,99,Rural,Data Analyst,84749,1 +25715,Male,30,Masters,7,68,0,74,1,1.0,6,83,Urban,Software Engineer,115144,0 +25716,Female,57,Masters,1,58,54,29,24,9.0,2,7,Urban,ML Engineer,72498,0 +25717,Male,39,High School,7,77,83,33,21,4.0,4,6,Semi-Urban,Data Analyst,120374,0 +25718,Male,47,Masters,7,44,40,0,4,1.0,5,84,Semi-Urban,ML Engineer,47682,0 +25719,Male,30,Masters,8,63,78,34,32,0.0,4,77,Rural,Data Analyst,148244,1 +25720,Female,56,Diploma,15,11,21,87,66,1.0,1,91,Urban,HR Executive,94898,0 +25721,Male,41,Bachelors,11,49,33,12,97,5.0,5,84,Urban,Manager,46881,0 +25722,Male,28,Diploma,9,88,51,41,99,8.0,1,2,Semi-Urban,HR Executive,86506,0 +25723,Male,30,Bachelors,0,85,0,31,21,3.0,5,50,Semi-Urban,ML Engineer,130636,0 +25724,Other,25,Diploma,2,17,14,32,84,2.0,3,87,Urban,ML Engineer,38923,0 +25725,Male,26,High School,10,2,22,28,52,0.0,6,23,Rural,HR Executive,140260,0 +25726,Male,47,Bachelors,4,50,86,30,98,4.0,1,97,Urban,HR Executive,57385,1 +25727,Male,30,High School,7,86,22,6,11,0.0,0,49,Semi-Urban,HR Executive,21909,0 +25728,Male,54,Bachelors,18,94,74,93,44,8.0,3,53,Urban,Software Engineer,92169,1 +25729,Male,53,Bachelors,8,80,98,65,63,5.0,6,39,Rural,Data Analyst,79240,1 +25730,Female,26,Masters,8,5,4,21,28,8.0,2,85,Urban,HR Executive,30921,0 +25731,Male,24,Bachelors,3,9,78,67,55,6.0,0,23,Urban,Data Analyst,39936,0 +25732,Female,37,High School,19,20,35,88,18,4.0,4,90,Urban,Software Engineer,131626,0 +25733,Male,27,Bachelors,10,14,20,28,38,6.0,5,62,Rural,Manager,59179,0 +25734,Male,52,Diploma,19,99,2,3,79,2.0,6,87,Semi-Urban,Software Engineer,49351,0 +25735,Male,34,Diploma,18,40,43,95,82,7.0,4,73,Semi-Urban,Data Analyst,101213,1 +25736,Male,49,PhD,4,80,43,36,32,5.0,4,57,Semi-Urban,Software Engineer,35865,0 +25737,Female,57,Bachelors,13,1,49,70,87,9.0,5,1,Urban,Software Engineer,117536,0 +25738,Male,31,Bachelors,17,44,88,85,46,8.0,6,10,Urban,ML Engineer,126633,0 +25739,Female,52,Bachelors,3,75,45,77,41,7.0,4,70,Semi-Urban,HR Executive,110483,1 +25740,Female,24,Diploma,13,68,80,46,2,3.0,1,59,Urban,Data Analyst,76500,1 +25741,Male,34,Bachelors,0,75,58,77,25,6.0,6,5,Urban,Data Analyst,107015,0 +25742,Female,55,Bachelors,0,4,63,22,74,2.0,3,79,Rural,Data Analyst,130625,0 +25743,Male,29,PhD,13,42,29,54,95,9.0,6,26,Rural,Data Analyst,146766,0 +25744,Male,51,Masters,11,38,38,24,39,0.0,7,33,Semi-Urban,Manager,76792,0 +25745,Female,45,High School,5,86,18,53,53,9.0,5,46,Semi-Urban,Software Engineer,44836,0 +25746,Male,57,Diploma,7,4,1,31,20,5.0,3,46,Semi-Urban,Data Analyst,87308,0 +25747,Male,32,High School,19,94,37,2,37,0.0,3,61,Semi-Urban,HR Executive,96570,0 +25748,Female,46,Diploma,5,48,78,70,53,7.0,2,53,Semi-Urban,ML Engineer,108968,1 +25749,Other,45,Bachelors,16,17,76,4,91,0.0,4,37,Urban,Manager,120926,0 +25750,Male,51,Masters,16,42,0,7,65,8.0,5,18,Urban,Manager,104108,0 +25751,Female,31,Bachelors,0,86,93,64,44,1.0,7,27,Semi-Urban,Manager,86856,1 +25752,Male,22,Diploma,10,97,68,54,27,9.0,3,11,Urban,Data Analyst,58025,0 +25753,Female,29,Bachelors,14,11,46,83,82,9.0,0,47,Rural,Manager,97710,0 +25754,Male,28,Masters,0,54,35,97,8,0.0,5,65,Rural,HR Executive,97682,1 +25755,Female,37,Bachelors,12,93,25,41,1,2.0,1,26,Semi-Urban,Manager,38535,0 +25756,Male,39,Bachelors,12,93,47,82,77,2.0,3,39,Urban,Manager,37532,1 +25757,Female,29,Diploma,8,18,42,69,23,5.0,4,20,Urban,Data Analyst,90796,0 +25758,Female,56,Diploma,0,39,98,84,43,2.0,5,6,Urban,ML Engineer,80408,0 +25759,Male,35,Bachelors,1,35,10,7,28,0.0,4,42,Urban,Manager,126592,0 +25760,Male,49,High School,19,66,41,42,81,1.0,6,48,Semi-Urban,ML Engineer,20261,0 +25761,Female,32,Bachelors,10,56,3,10,98,9.0,6,88,Urban,Data Analyst,79967,0 +25762,Female,21,Bachelors,18,73,15,74,69,7.0,1,22,Urban,ML Engineer,97222,0 +25763,Male,23,Bachelors,19,43,45,70,19,8.0,3,57,Urban,HR Executive,107533,0 +25764,Male,48,High School,9,2,62,52,4,4.0,4,27,Urban,ML Engineer,35933,0 +25765,Female,49,Diploma,8,2,13,42,45,9.0,4,91,Urban,HR Executive,148604,0 +25766,Male,57,Masters,17,36,25,31,89,8.0,2,48,Urban,Data Analyst,65333,0 +25767,Male,54,Bachelors,12,67,3,52,2,5.0,6,83,Urban,Manager,72864,0 +25768,Female,55,Bachelors,8,71,82,47,76,9.0,7,48,Semi-Urban,Manager,52844,1 +25769,Male,32,High School,12,6,71,53,94,5.0,1,74,Semi-Urban,HR Executive,35893,0 +25770,Male,32,Bachelors,19,94,25,77,49,3.0,2,86,Urban,Software Engineer,71983,1 +25771,Male,53,Bachelors,10,9,48,33,20,6.0,5,68,Urban,ML Engineer,134901,0 +25772,Female,24,Bachelors,14,94,47,64,53,1.0,2,62,Rural,Manager,22051,1 +25773,Male,34,Bachelors,11,64,47,47,10,9.0,1,15,Urban,Manager,79243,0 +25774,Female,31,Masters,16,23,90,78,19,8.0,3,5,Semi-Urban,HR Executive,47428,0 +25775,Female,51,Masters,7,35,16,95,64,2.0,4,19,Urban,ML Engineer,134169,0 +25776,Male,55,Masters,7,8,37,28,56,8.0,6,59,Semi-Urban,HR Executive,27582,0 +25777,Female,22,PhD,7,68,56,16,92,4.0,1,89,Urban,Manager,112684,0 +25778,Male,37,Bachelors,15,13,60,61,92,1.0,1,27,Semi-Urban,Manager,27659,0 +25779,Female,40,Masters,7,21,35,68,93,2.0,1,5,Urban,Software Engineer,76749,0 +25780,Male,40,Masters,15,26,18,68,8,8.0,2,46,Rural,ML Engineer,53313,0 +25781,Female,56,PhD,18,18,8,24,93,1.0,7,87,Semi-Urban,Software Engineer,39246,0 +25782,Male,33,PhD,0,89,29,10,68,8.0,7,13,Urban,Data Analyst,106288,0 +25783,Male,32,Masters,4,69,67,78,47,9.0,6,72,Semi-Urban,Data Analyst,110596,1 +25784,Female,47,PhD,12,63,96,62,88,1.0,4,30,Rural,Software Engineer,41618,1 +25785,Male,43,Diploma,0,12,73,14,24,4.0,4,49,Urban,Software Engineer,129131,0 +25786,Female,25,Diploma,16,67,68,88,17,6.0,3,87,Urban,Data Analyst,100055,1 +25787,Male,28,Diploma,19,48,23,34,37,9.0,0,66,Urban,HR Executive,127638,0 +25788,Male,24,Masters,11,1,79,65,65,2.0,0,2,Urban,HR Executive,98182,0 +25789,Female,35,Masters,14,38,52,54,43,9.0,2,94,Urban,Software Engineer,52075,0 +25790,Male,36,Bachelors,4,67,94,40,42,6.0,3,81,Rural,ML Engineer,91276,1 +25791,Female,21,Diploma,17,6,79,28,80,9.0,3,73,Semi-Urban,Data Analyst,86343,0 +25792,Male,51,High School,7,54,22,85,57,1.0,4,78,Rural,HR Executive,28355,1 +25793,Male,37,Diploma,9,28,37,19,79,4.0,5,16,Urban,HR Executive,77905,0 +25794,Female,48,Masters,10,16,6,71,88,7.0,6,38,Urban,HR Executive,118528,0 +25795,Male,38,Bachelors,1,70,82,63,99,1.0,3,29,Semi-Urban,HR Executive,53274,1 +25796,Male,29,Masters,9,10,73,46,65,1.0,4,14,Semi-Urban,HR Executive,145984,0 +25797,Female,46,Bachelors,14,48,3,42,83,9.0,4,49,Semi-Urban,Manager,63952,0 +25798,Male,48,Bachelors,10,7,97,2,58,0.0,0,96,Semi-Urban,ML Engineer,83535,0 +25799,Male,21,Diploma,17,89,17,23,75,6.0,7,42,Urban,Software Engineer,125493,0 +25800,Female,24,High School,17,76,34,51,10,1.0,1,96,Semi-Urban,Data Analyst,28124,1 +25801,Female,42,Bachelors,14,22,13,11,85,3.0,3,61,Urban,Manager,28881,0 +25802,Male,26,Bachelors,4,48,51,73,21,9.0,4,86,Rural,Manager,122380,1 +25803,Male,23,Bachelors,16,79,76,83,60,7.0,4,4,Urban,Manager,125887,1 +25804,Female,47,Diploma,2,61,85,58,52,6.0,2,6,Urban,Software Engineer,140010,0 +25805,Male,59,High School,18,53,50,50,6,6.0,2,19,Urban,ML Engineer,87018,0 +25806,Male,26,Bachelors,17,31,44,99,41,9.0,7,51,Urban,HR Executive,104900,0 +25807,Other,47,Masters,14,87,2,27,12,1.0,5,40,Rural,HR Executive,37136,0 +25808,Male,37,Bachelors,0,69,25,23,25,8.0,3,45,Urban,Data Analyst,29800,0 +25809,Male,55,Bachelors,17,13,75,45,77,1.0,7,4,Semi-Urban,Data Analyst,122401,0 +25810,Female,41,High School,13,98,82,58,20,4.0,7,56,Urban,Data Analyst,103519,1 +25811,Female,38,Bachelors,6,99,36,8,17,0.0,5,69,Rural,ML Engineer,116927,0 +25812,Female,53,Masters,13,19,51,72,1,0.0,7,71,Semi-Urban,Manager,134702,0 +25813,Male,30,Bachelors,2,97,72,5,35,9.0,1,72,Urban,Software Engineer,107830,1 +25814,Male,40,High School,5,76,48,17,19,4.0,3,59,Urban,Data Analyst,66872,0 +25815,Female,32,Diploma,18,50,11,58,28,4.0,7,76,Urban,Software Engineer,127995,0 +25816,Male,52,Diploma,18,91,48,60,65,3.0,0,17,Urban,Software Engineer,109815,0 +25817,Female,43,Diploma,11,44,53,37,86,3.0,1,35,Urban,Manager,67913,0 +25818,Male,41,Masters,5,31,71,30,66,2.0,3,97,Urban,Software Engineer,41451,0 +25819,Female,47,Masters,10,95,31,46,12,6.0,6,10,Rural,HR Executive,115519,0 +25820,Male,36,Bachelors,14,12,60,45,98,5.0,0,11,Rural,HR Executive,29004,0 +25821,Male,57,Diploma,1,71,37,4,2,0.0,6,39,Rural,HR Executive,61467,0 +25822,Male,38,Masters,5,25,52,94,32,1.0,2,97,Urban,Manager,137379,1 +25823,Female,26,Bachelors,8,73,93,84,57,2.0,1,36,Semi-Urban,ML Engineer,52725,1 +25824,Male,38,High School,19,78,59,37,76,0.0,3,52,Urban,HR Executive,138177,0 +25825,Female,58,High School,9,85,99,51,8,6.0,2,2,Semi-Urban,Software Engineer,40649,0 +25826,Male,23,Bachelors,4,5,55,63,56,2.0,2,48,Urban,Manager,47481,0 +25827,Male,39,Bachelors,18,61,45,44,36,9.0,2,49,Urban,HR Executive,72912,0 +25828,Female,53,Bachelors,9,89,4,53,51,4.0,6,47,Urban,Software Engineer,75240,0 +25829,Male,31,PhD,1,95,70,20,24,2.0,2,28,Rural,HR Executive,136704,0 +25830,Male,23,Masters,10,24,60,4,15,5.0,4,13,Urban,ML Engineer,106558,0 +25831,Male,57,Diploma,17,58,96,59,28,6.0,3,51,Rural,Manager,68211,1 +25832,Female,38,PhD,11,57,82,31,3,2.0,3,86,Semi-Urban,Data Analyst,35740,1 +25833,Female,48,PhD,11,61,22,86,80,3.0,3,59,Urban,ML Engineer,72627,0 +25834,Male,59,Masters,14,29,57,77,39,0.0,2,10,Urban,Data Analyst,145426,0 +25835,Male,56,High School,16,6,71,96,65,2.0,2,52,Urban,Software Engineer,149604,0 +25836,Male,24,Masters,9,64,77,69,16,1.0,2,60,Rural,Data Analyst,88290,1 +25837,Female,36,Bachelors,15,21,21,71,65,5.0,7,12,Urban,Software Engineer,80925,0 +25838,Male,41,Masters,5,76,87,44,33,0.0,7,88,Semi-Urban,Data Analyst,115653,1 +25839,Female,47,High School,3,46,45,95,96,8.0,3,75,Urban,HR Executive,62185,1 +25840,Male,35,Bachelors,1,42,93,30,65,8.0,2,61,Semi-Urban,Manager,105249,0 +25841,Female,37,Diploma,6,42,1,31,48,8.0,2,96,Rural,ML Engineer,123911,0 +25842,Male,24,High School,6,98,53,51,37,2.0,0,62,Urban,Data Analyst,93381,1 +25843,Female,42,Diploma,19,41,47,98,66,2.0,5,1,Semi-Urban,ML Engineer,137488,0 +25844,Male,43,Bachelors,11,36,17,84,93,2.0,1,75,Semi-Urban,Manager,148412,0 +25845,Male,38,High School,6,89,47,74,98,5.0,7,25,Urban,Software Engineer,34016,1 +25846,Female,57,High School,0,27,74,47,36,9.0,2,38,Urban,ML Engineer,26133,0 +25847,Female,58,Diploma,9,3,3,38,69,2.0,5,6,Urban,Manager,116906,0 +25848,Male,31,Diploma,7,6,81,56,50,4.0,3,7,Rural,Data Analyst,27310,0 +25849,Other,24,Diploma,5,55,92,82,40,4.0,6,41,Semi-Urban,HR Executive,112074,1 +25850,Male,22,Diploma,8,71,74,52,66,5.0,6,77,Rural,Manager,135651,1 +25851,,23,Masters,7,6,80,15,4,2.0,4,91,Urban,Manager,80975,0 +25852,Male,49,Bachelors,7,45,2,4,14,0.0,7,65,Semi-Urban,Software Engineer,22735,0 +25853,Male,46,Masters,6,32,73,48,7,4.0,7,69,Rural,Manager,22765,0 +25854,Female,25,Bachelors,1,2,34,32,5,9.0,5,85,Urban,Manager,90130,0 +25855,Male,24,PhD,3,80,16,48,53,6.0,4,72,Urban,Software Engineer,139748,0 +25856,Male,53,Diploma,5,75,47,72,63,6.0,3,7,Urban,HR Executive,85217,0 +25857,Male,45,Bachelors,0,22,5,23,42,1.0,4,10,Urban,ML Engineer,132773,0 +25858,Male,51,Masters,4,99,3,60,10,2.0,5,86,Urban,ML Engineer,87126,1 +25859,Female,35,Diploma,6,73,97,62,65,1.0,2,96,Urban,Data Analyst,84330,1 +25860,Female,21,Masters,5,33,94,44,56,2.0,0,63,Urban,HR Executive,36046,0 +25861,Male,41,High School,13,50,99,82,93,7.0,5,39,Rural,Data Analyst,53199,1 +25862,Male,24,PhD,2,48,26,61,8,1.0,4,80,Urban,Software Engineer,125690,0 +25863,Female,38,Bachelors,10,40,41,52,77,6.0,7,5,Semi-Urban,HR Executive,28950,0 +25864,Male,38,Bachelors,13,17,26,56,30,9.0,1,2,Rural,ML Engineer,37863,0 +25865,Male,21,Diploma,7,3,2,92,16,9.0,1,79,Semi-Urban,Software Engineer,120372,0 +25866,Male,28,Diploma,6,30,79,31,57,5.0,2,47,Urban,Manager,100228,0 +25867,Male,31,Diploma,19,91,92,60,58,4.0,6,9,Semi-Urban,Data Analyst,56637,1 +25868,Female,30,High School,12,23,69,55,20,3.0,5,85,Urban,Manager,94237,0 +25869,Male,25,Diploma,10,78,27,23,81,1.0,4,55,Urban,Data Analyst,94893,0 +25870,Other,32,Bachelors,1,22,9,10,56,6.0,7,65,Urban,ML Engineer,89899,0 +25871,Male,21,Bachelors,1,57,40,68,24,8.0,5,53,Urban,Software Engineer,134361,0 +25872,Male,51,PhD,7,41,57,11,21,7.0,4,84,Semi-Urban,Software Engineer,95181,0 +25873,Other,58,Bachelors,17,25,54,19,51,1.0,5,17,Urban,ML Engineer,73930,0 +25874,Female,47,Diploma,15,87,37,21,96,0.0,2,3,Urban,Software Engineer,26597,0 +25875,Female,53,Diploma,19,71,59,95,37,5.0,5,49,Urban,Software Engineer,47399,1 +25876,Male,40,PhD,12,4,76,19,26,2.0,0,72,Semi-Urban,Software Engineer,67407,0 +25877,Female,55,Bachelors,11,49,66,62,60,6.0,5,61,Urban,Manager,85775,0 +25878,Male,28,High School,16,12,15,73,50,0.0,1,62,Urban,Manager,45150,0 +25879,Male,49,Bachelors,14,59,7,78,3,3.0,0,49,Rural,Manager,139205,0 +25880,Female,34,Bachelors,6,45,53,78,34,9.0,2,49,Urban,HR Executive,103042,0 +25881,Female,35,Masters,14,97,20,38,41,0.0,3,24,Semi-Urban,Manager,56869,0 +25882,Female,28,Masters,13,15,58,25,47,2.0,3,28,Rural,HR Executive,60772,0 +25883,Female,21,Bachelors,7,79,96,52,99,0.0,5,29,Semi-Urban,HR Executive,142645,1 +25884,Male,56,Masters,4,10,68,58,90,1.0,4,27,Urban,Software Engineer,83754,0 +25885,Male,58,Masters,17,58,52,64,89,1.0,6,6,Urban,Data Analyst,101924,0 +25886,Female,41,Diploma,6,1,90,85,8,1.0,2,41,Semi-Urban,ML Engineer,41332,0 +25887,Male,50,High School,2,76,95,99,4,2.0,4,82,Rural,Data Analyst,55729,1 +25888,Male,27,High School,15,91,71,3,73,1.0,4,32,Urban,Data Analyst,95989,0 +25889,Male,26,Bachelors,2,23,12,88,20,8.0,0,89,Semi-Urban,Manager,104544,0 +25890,Male,28,High School,11,36,69,72,84,2.0,1,74,Semi-Urban,HR Executive,139292,1 +25891,Other,50,Bachelors,10,4,14,68,97,5.0,5,98,Urban,Software Engineer,60587,0 +25892,Male,59,Bachelors,11,57,14,82,91,1.0,7,11,Rural,Manager,28526,0 +25893,Male,42,Bachelors,8,53,55,24,43,7.0,3,40,Urban,Manager,20979,0 +25894,Female,35,Bachelors,11,32,67,7,77,2.0,6,65,Urban,ML Engineer,134670,0 +25895,Male,21,Bachelors,15,97,7,71,10,8.0,5,98,Semi-Urban,HR Executive,41304,1 +25896,Female,33,Diploma,17,25,98,94,81,8.0,3,79,Urban,ML Engineer,97756,1 +25897,Male,21,Bachelors,1,90,21,14,15,9.0,7,34,Semi-Urban,Data Analyst,24535,0 +25898,Female,51,Bachelors,7,98,10,49,86,3.0,7,48,Urban,HR Executive,149385,0 +25899,Male,52,PhD,7,71,34,64,3,7.0,1,65,Rural,Manager,51619,0 +25900,Male,41,Bachelors,4,59,23,63,47,4.0,5,91,Semi-Urban,Software Engineer,100132,1 +25901,Male,29,PhD,15,86,65,71,76,8.0,3,55,Urban,Data Analyst,104028,1 +25902,Male,24,Masters,8,92,54,92,6,8.0,5,43,Urban,HR Executive,94846,1 +25903,Female,30,Bachelors,9,42,83,46,65,7.0,3,3,Semi-Urban,ML Engineer,58820,0 +25904,Male,34,Masters,5,50,82,98,96,5.0,5,88,Semi-Urban,Manager,57282,1 +25905,Female,45,Masters,1,78,70,14,12,7.0,7,49,Semi-Urban,HR Executive,83847,0 +25906,Male,32,High School,14,3,87,92,76,9.0,2,49,Semi-Urban,Manager,86696,0 +25907,Female,48,Diploma,19,74,62,68,75,1.0,4,76,Urban,Manager,100982,1 +25908,Female,29,Diploma,9,64,50,58,88,2.0,6,88,Urban,ML Engineer,132506,1 +25909,Male,52,High School,3,25,10,63,39,8.0,1,79,Semi-Urban,ML Engineer,133492,0 +25910,Male,34,Masters,11,96,8,2,99,8.0,0,20,Urban,Data Analyst,71064,0 +25911,Female,59,Diploma,7,71,73,88,60,7.0,4,9,Semi-Urban,HR Executive,116037,1 +25912,Male,30,High School,13,15,4,25,43,8.0,1,83,Urban,ML Engineer,85514,0 +25913,Male,30,Bachelors,19,70,99,67,53,5.0,2,31,Urban,ML Engineer,95693,1 +25914,Female,21,Bachelors,7,25,93,83,91,0.0,6,20,Semi-Urban,HR Executive,62008,0 +25915,Other,40,Bachelors,3,99,8,90,84,0.0,3,85,Urban,ML Engineer,118702,1 +25916,Female,38,High School,16,96,98,68,15,5.0,5,24,Urban,Manager,134799,1 +25917,Male,55,High School,16,56,11,51,30,1.0,0,66,Semi-Urban,HR Executive,139692,0 +25918,Male,28,High School,13,24,43,55,88,2.0,3,40,Semi-Urban,ML Engineer,21747,0 +25919,Other,32,Bachelors,17,39,36,40,52,5.0,7,75,Urban,Data Analyst,130357,0 +25920,Male,54,High School,19,90,19,29,93,5.0,1,86,Urban,Data Analyst,37337,0 +25921,Male,54,Diploma,18,18,68,49,31,8.0,5,98,Urban,HR Executive,66942,0 +25922,Female,53,Masters,14,28,68,5,45,1.0,6,36,Urban,HR Executive,87621,0 +25923,Male,41,Diploma,11,10,77,60,70,1.0,1,65,Urban,HR Executive,54270,0 +25924,Male,42,Diploma,11,67,26,34,79,9.0,2,65,Urban,Manager,71860,0 +25925,Female,25,Bachelors,8,58,3,26,11,6.0,7,68,Urban,Manager,110352,0 +25926,Male,44,Masters,15,99,86,52,13,1.0,7,50,Urban,Data Analyst,54791,1 +25927,Male,43,Masters,9,2,79,89,25,4.0,0,64,Semi-Urban,HR Executive,87107,0 +25928,Male,46,Masters,16,57,16,52,44,0.0,0,98,Rural,Data Analyst,44214,0 +25929,Male,34,Bachelors,4,76,94,36,18,3.0,4,47,Semi-Urban,HR Executive,61650,1 +25930,Other,49,Bachelors,1,68,34,63,67,5.0,7,35,Rural,HR Executive,110716,0 +25931,Male,31,High School,7,31,8,39,79,5.0,1,88,Urban,HR Executive,39588,0 +25932,Male,44,High School,19,29,70,34,88,1.0,2,28,Urban,Software Engineer,71221,0 +25933,Male,28,Bachelors,15,12,12,44,96,8.0,6,89,Semi-Urban,Software Engineer,112606,0 +25934,Female,25,Bachelors,10,25,50,20,66,1.0,2,73,Urban,HR Executive,57682,0 +25935,Female,45,Bachelors,1,42,40,86,88,0.0,2,65,Urban,Data Analyst,81216,0 +25936,Male,57,Diploma,17,98,79,35,99,9.0,4,55,Urban,Software Engineer,43391,1 +25937,Male,57,Bachelors,2,49,60,2,76,2.0,6,6,Urban,ML Engineer,50196,0 +25938,Female,57,Bachelors,3,59,86,26,49,9.0,3,39,Urban,ML Engineer,62168,0 +25939,Male,46,Bachelors,16,43,20,99,24,0.0,7,84,Urban,HR Executive,89440,1 +25940,Male,52,Diploma,12,55,53,23,8,2.0,6,90,Urban,Software Engineer,54825,0 +25941,Male,37,Masters,18,6,22,39,65,9.0,7,3,Urban,Manager,124431,0 +25942,Male,21,Masters,6,40,3,29,91,7.0,3,85,Urban,HR Executive,80607,0 +25943,Other,22,Masters,18,68,78,70,18,2.0,1,69,Rural,Data Analyst,58072,1 +25944,Female,27,Bachelors,19,2,9,25,73,0.0,2,47,Urban,Software Engineer,65783,0 +25945,Female,26,Diploma,12,48,66,34,19,6.0,1,45,Urban,ML Engineer,66487,0 +25946,Female,59,Diploma,2,16,4,1,28,5.0,2,81,Urban,Manager,75862,0 +25947,Female,45,Bachelors,16,74,21,10,75,0.0,2,6,Urban,Manager,147403,0 +25948,Female,29,Bachelors,19,80,0,72,11,2.0,0,34,Urban,Data Analyst,50889,0 +25949,Male,41,Bachelors,18,7,64,17,95,3.0,2,60,Urban,HR Executive,59955,0 +25950,Male,43,Bachelors,3,5,0,23,81,0.0,5,99,Urban,Data Analyst,124171,0 +25951,Female,49,Diploma,0,19,72,86,2,7.0,3,48,Semi-Urban,HR Executive,23970,0 +25952,Male,32,Bachelors,2,74,42,12,37,9.0,3,19,Rural,ML Engineer,71419,0 +25953,Male,35,Masters,0,6,34,74,28,3.0,4,43,Semi-Urban,HR Executive,73669,0 +25954,Male,42,Diploma,7,21,37,21,69,9.0,1,79,Urban,Data Analyst,57824,0 +25955,Male,46,Diploma,1,21,45,14,51,3.0,0,47,Rural,Software Engineer,71879,0 +25956,Male,24,Bachelors,6,77,46,87,18,2.0,2,59,Urban,Data Analyst,68142,1 +25957,Male,27,Masters,14,33,92,11,74,6.0,5,72,Urban,Data Analyst,55177,0 +25958,Male,59,Bachelors,5,48,47,4,30,7.0,1,1,Semi-Urban,Data Analyst,115100,0 +25959,Female,44,Diploma,5,34,31,86,57,6.0,1,99,Urban,HR Executive,23243,1 +25960,Female,25,High School,18,90,97,13,76,4.0,5,34,Rural,Data Analyst,125793,0 +25961,Female,51,PhD,16,78,38,22,87,0.0,6,29,Urban,HR Executive,139154,0 +25962,Female,38,Bachelors,0,66,91,10,85,5.0,0,30,Rural,ML Engineer,89677,0 +25963,Male,48,Diploma,9,71,12,51,22,2.0,0,11,Urban,Manager,54894,0 +25964,Male,55,Bachelors,6,5,42,89,50,8.0,6,34,Urban,Software Engineer,83349,0 +25965,Male,37,Diploma,4,62,28,61,6,4.0,3,24,Semi-Urban,Software Engineer,20787,0 +25966,Female,39,Bachelors,18,72,44,58,84,6.0,0,85,Rural,ML Engineer,86619,1 +25967,Male,45,Bachelors,12,76,9,96,92,9.0,1,99,Semi-Urban,ML Engineer,126349,1 +25968,Female,24,Diploma,4,91,13,96,95,1.0,5,32,Urban,Software Engineer,51729,0 +25969,Male,53,Bachelors,8,66,71,70,48,9.0,0,8,Semi-Urban,Data Analyst,125165,0 +25970,Female,54,Masters,7,58,56,85,45,3.0,4,49,Urban,Data Analyst,111394,1 +25971,Male,51,Masters,13,21,0,42,83,5.0,2,4,Urban,HR Executive,59009,0 +25972,Female,47,Bachelors,0,62,14,17,22,4.0,1,65,Urban,Software Engineer,79658,0 +25973,Male,51,Diploma,18,26,94,18,50,2.0,1,9,Urban,HR Executive,128941,0 +25974,Male,45,High School,18,81,5,8,17,4.0,7,4,Urban,Manager,81816,0 +25975,Male,45,High School,19,0,8,92,61,2.0,7,41,Urban,HR Executive,97805,0 +25976,Other,40,Masters,18,73,8,85,57,2.0,1,48,Urban,Data Analyst,65901,0 +25977,Male,43,Bachelors,10,76,57,6,26,2.0,0,6,Urban,Manager,141569,0 +25978,Female,31,Diploma,5,32,37,56,90,2.0,5,58,Rural,Data Analyst,52935,0 +25979,Female,24,Bachelors,6,85,7,45,42,0.0,2,91,Rural,Manager,63352,0 +25980,Female,23,High School,10,10,2,42,23,6.0,6,30,Urban,Data Analyst,143134,0 +25981,Male,23,Bachelors,6,92,5,58,11,9.0,2,50,Semi-Urban,Manager,138983,0 +25982,Male,53,Diploma,15,7,10,80,51,2.0,2,56,Urban,HR Executive,74685,0 +25983,Male,25,Bachelors,12,7,37,49,50,4.0,2,80,Urban,ML Engineer,86782,0 +25984,Other,57,High School,3,43,62,34,75,8.0,0,28,Urban,HR Executive,98762,0 +25985,Other,43,Bachelors,14,15,59,18,51,4.0,3,2,Semi-Urban,Data Analyst,131419,0 +25986,Female,23,High School,10,12,10,2,7,0.0,5,94,Urban,Manager,138030,0 +25987,Male,57,High School,1,83,98,88,0,9.0,4,64,Rural,Software Engineer,24658,1 +25988,Male,33,High School,6,60,48,67,79,3.0,1,93,Urban,ML Engineer,84426,1 +25989,Other,52,Bachelors,1,47,76,64,89,8.0,0,69,Urban,ML Engineer,63592,1 +25990,Male,29,Bachelors,0,65,30,69,49,1.0,1,70,Semi-Urban,HR Executive,88085,0 +25991,Female,25,High School,15,62,38,66,80,5.0,3,12,Urban,ML Engineer,105789,0 +25992,Male,58,Masters,12,96,12,74,74,0.0,5,54,Urban,Data Analyst,41974,1 +25993,Male,52,Diploma,11,56,95,97,14,9.0,7,90,Semi-Urban,Data Analyst,75132,1 +25994,Female,52,PhD,13,10,53,64,20,6.0,3,41,Urban,HR Executive,67794,0 +25995,Male,43,Bachelors,14,54,80,61,10,3.0,2,39,Rural,HR Executive,117978,0 +25996,Male,32,Bachelors,2,10,35,95,99,0.0,1,60,Semi-Urban,Data Analyst,109532,0 +25997,Other,41,Diploma,3,91,70,81,76,7.0,4,51,Semi-Urban,ML Engineer,101317,1 +25998,Female,56,Masters,1,7,64,21,9,8.0,2,18,Rural,Manager,53313,0 +25999,Female,47,High School,16,73,69,84,33,1.0,7,56,Urban,Software Engineer,72925,1 +26000,Female,44,Diploma,1,46,61,54,87,0.0,2,57,Urban,HR Executive,83668,0 +26001,Male,40,Bachelors,6,91,1,66,68,4.0,7,17,Urban,ML Engineer,73640,0 +26002,Male,34,Masters,18,55,24,78,48,2.0,6,4,Urban,Software Engineer,36507,0 +26003,Male,33,Bachelors,19,34,5,30,41,8.0,4,30,Urban,HR Executive,91476,0 +26004,Male,35,High School,5,12,23,23,60,3.0,4,83,Urban,Software Engineer,32516,0 +26005,Male,30,PhD,1,10,30,81,35,4.0,5,46,Urban,Manager,32332,0 +26006,Female,27,Diploma,2,16,53,74,98,8.0,2,9,Urban,HR Executive,106858,0 +26007,Male,35,High School,5,82,41,19,77,9.0,5,23,Urban,ML Engineer,75965,0 +26008,Female,26,Masters,2,67,20,66,55,4.0,6,20,Semi-Urban,Software Engineer,128958,0 +26009,Male,55,Bachelors,15,57,45,41,14,3.0,4,14,Urban,ML Engineer,88914,0 +26010,Male,39,PhD,3,32,85,7,70,8.0,2,29,Urban,Manager,54481,0 +26011,Male,32,High School,3,12,86,23,40,9.0,1,93,Urban,HR Executive,63049,0 +26012,Female,52,Masters,12,89,4,18,88,1.0,7,43,Urban,HR Executive,121656,0 +26013,Male,32,High School,7,60,19,68,74,9.0,1,24,Urban,Manager,82540,0 +26014,Male,44,Bachelors,10,95,17,15,23,2.0,4,13,Rural,ML Engineer,71911,0 +26015,Female,55,Bachelors,7,23,41,15,68,7.0,1,50,Urban,HR Executive,79413,0 +26016,Male,22,Masters,10,67,48,7,85,3.0,5,25,Urban,Software Engineer,40103,0 +26017,Male,27,High School,3,95,18,76,30,5.0,7,12,Urban,HR Executive,104107,0 +26018,Female,48,Bachelors,9,15,12,24,84,4.0,7,73,Urban,Software Engineer,52030,0 +26019,Male,33,Diploma,16,94,70,65,90,9.0,4,1,Urban,Software Engineer,48998,0 +26020,Male,36,High School,19,87,51,33,99,8.0,6,89,Rural,Data Analyst,121349,1 +26021,Female,55,Diploma,6,58,66,34,19,1.0,7,39,Urban,Manager,22362,0 +26022,Male,34,Diploma,5,16,15,47,3,1.0,6,6,Semi-Urban,Manager,134448,0 +26023,Male,34,Diploma,17,4,3,46,10,1.0,6,0,Urban,Software Engineer,55784,0 +26024,Male,21,Masters,11,40,23,91,77,5.0,3,65,Semi-Urban,ML Engineer,70773,0 +26025,Male,31,Bachelors,7,27,8,5,38,3.0,7,76,Urban,HR Executive,50143,0 +26026,Male,30,Bachelors,6,83,61,32,79,0.0,7,36,Urban,Manager,39246,0 +26027,Male,34,Diploma,16,36,26,63,60,0.0,1,7,Urban,Data Analyst,51252,0 +26028,Male,58,High School,9,76,31,39,80,2.0,2,34,Semi-Urban,HR Executive,130864,0 +26029,Male,53,High School,10,29,55,83,54,5.0,1,32,Rural,ML Engineer,110249,0 +26030,Female,49,Bachelors,9,91,71,66,2,6.0,4,99,Urban,Software Engineer,73358,1 +26031,Female,28,Bachelors,2,65,74,96,20,0.0,7,82,Semi-Urban,HR Executive,136886,1 +26032,Female,53,Bachelors,19,71,98,49,17,1.0,5,0,Urban,ML Engineer,45510,0 +26033,Male,23,High School,10,3,18,20,63,6.0,1,14,Urban,Manager,23503,0 +26034,Male,29,PhD,6,80,39,71,48,1.0,7,11,Semi-Urban,Data Analyst,77986,0 +26035,Male,33,Bachelors,8,23,46,24,49,0.0,4,41,Urban,Software Engineer,109232,0 +26036,Female,26,Bachelors,2,33,91,69,43,8.0,3,28,Urban,HR Executive,84139,0 +26037,Male,56,PhD,16,43,35,71,38,9.0,3,62,Urban,Data Analyst,127945,0 +26038,Male,58,Bachelors,2,7,48,24,32,4.0,4,32,Urban,Software Engineer,144210,0 +26039,Male,25,Bachelors,15,1,17,51,27,4.0,6,8,Rural,ML Engineer,131712,0 +26040,Male,26,High School,12,72,80,57,58,1.0,4,54,Urban,ML Engineer,112495,1 +26041,Male,35,High School,9,99,47,62,63,6.0,6,35,Semi-Urban,ML Engineer,99794,1 +26042,Male,51,High School,18,40,17,94,47,3.0,2,99,Rural,Manager,44477,1 +26043,Male,56,Diploma,2,66,39,84,47,1.0,7,64,Urban,ML Engineer,57810,1 +26044,Female,53,Diploma,11,63,81,47,66,9.0,2,16,Rural,ML Engineer,28336,0 +26045,Male,27,PhD,2,60,80,2,53,1.0,2,16,Rural,Software Engineer,27662,0 +26046,Female,39,Diploma,0,41,8,20,80,1.0,3,23,Rural,Software Engineer,59801,0 +26047,Male,22,Bachelors,8,84,78,0,71,9.0,4,48,Semi-Urban,ML Engineer,117205,0 +26048,Male,54,Bachelors,7,3,4,39,93,1.0,1,53,Urban,Data Analyst,99871,0 +26049,Male,56,High School,7,61,21,42,89,9.0,2,76,Urban,ML Engineer,48879,0 +26050,Male,55,Bachelors,18,41,78,71,40,9.0,4,47,Semi-Urban,HR Executive,47711,1 +26051,Male,57,Diploma,11,96,63,78,42,7.0,2,74,Urban,HR Executive,66666,1 +26052,Male,56,Bachelors,13,69,84,75,71,0.0,0,25,Semi-Urban,ML Engineer,108900,1 +26053,Male,25,Bachelors,7,44,32,28,82,5.0,5,89,Urban,Manager,38562,0 +26054,Male,46,Bachelors,16,12,92,8,55,3.0,0,72,Urban,HR Executive,25485,0 +26055,Male,41,Masters,14,90,19,33,23,0.0,7,80,Urban,ML Engineer,143694,0 +26056,Male,45,Masters,8,61,9,84,48,5.0,5,97,Semi-Urban,Manager,115859,1 +26057,Male,45,High School,0,10,3,50,92,1.0,2,55,Urban,Data Analyst,58673,0 +26058,Male,32,PhD,0,64,35,65,44,5.0,3,92,Urban,HR Executive,31728,1 +26059,Other,58,High School,8,83,44,52,50,8.0,5,80,Semi-Urban,HR Executive,71754,1 +26060,Male,26,Bachelors,11,20,94,66,71,4.0,6,68,Urban,Data Analyst,122488,1 +26061,Male,27,Bachelors,17,64,88,97,47,9.0,1,79,Urban,Data Analyst,95853,1 +26062,Female,28,Bachelors,0,21,89,82,77,1.0,3,96,Urban,Data Analyst,104378,1 +26063,Female,50,High School,6,71,30,51,66,4.0,4,73,Urban,ML Engineer,143641,0 +26064,Female,40,Bachelors,17,98,75,94,87,6.0,3,44,Semi-Urban,HR Executive,115969,1 +26065,Female,33,Masters,7,62,65,91,67,4.0,1,15,Urban,Data Analyst,123538,0 +26066,Female,36,Diploma,10,72,41,31,70,3.0,5,27,Rural,ML Engineer,85597,0 +26067,Other,44,Bachelors,8,5,69,83,4,7.0,7,7,Rural,Software Engineer,56069,0 +26068,Male,37,Bachelors,10,49,15,27,74,7.0,5,10,Semi-Urban,Software Engineer,25889,0 +26069,Female,33,Bachelors,10,33,34,20,5,6.0,7,37,Semi-Urban,Software Engineer,92682,0 +26070,Female,56,Masters,10,74,51,28,56,9.0,0,2,Rural,Manager,142718,0 +26071,Female,40,High School,5,39,47,65,50,0.0,3,32,Urban,Manager,118249,0 +26072,Other,32,Bachelors,7,45,66,78,40,5.0,4,34,Urban,HR Executive,130841,0 +26073,Male,41,Bachelors,19,74,26,20,64,5.0,0,72,Rural,Data Analyst,75205,0 +26074,Male,58,Bachelors,16,39,50,89,71,7.0,0,55,Semi-Urban,Data Analyst,149559,0 +26075,Other,57,Diploma,1,50,22,62,64,3.0,6,77,Rural,ML Engineer,37372,0 +26076,Male,41,Bachelors,15,36,59,11,92,7.0,3,82,Urban,Data Analyst,40538,0 +26077,Female,41,Bachelors,4,43,21,87,23,8.0,2,66,Semi-Urban,HR Executive,38651,0 +26078,Male,55,Diploma,13,35,1,53,47,6.0,2,91,Urban,Software Engineer,44414,0 +26079,Female,53,Masters,15,55,2,89,62,4.0,7,35,Urban,Software Engineer,76880,0 +26080,Female,26,Bachelors,9,58,42,65,81,4.0,3,97,Urban,Manager,57550,1 +26081,Male,25,Masters,7,85,67,36,1,5.0,3,92,Urban,Data Analyst,136300,1 +26082,Male,49,Bachelors,13,37,44,19,94,2.0,4,10,Urban,Manager,64563,0 +26083,Male,41,Bachelors,7,40,67,46,29,9.0,4,15,Urban,Manager,85145,0 +26084,Female,23,Masters,18,63,8,4,79,0.0,1,55,Semi-Urban,ML Engineer,84410,0 +26085,Female,32,Masters,19,24,15,98,59,3.0,5,80,Semi-Urban,Software Engineer,47222,0 +26086,Male,31,Masters,3,14,49,38,14,7.0,1,96,Urban,Data Analyst,27790,0 +26087,Male,33,High School,16,38,17,44,86,9.0,1,90,Urban,HR Executive,146567,0 +26088,Female,33,Bachelors,2,77,61,42,66,8.0,6,31,Urban,Data Analyst,126360,0 +26089,Female,34,Bachelors,3,38,75,10,29,2.0,4,29,Urban,Manager,121507,0 +26090,Male,35,Masters,0,46,2,57,22,5.0,4,26,Rural,Manager,24913,0 +26091,Male,45,Bachelors,18,29,95,57,76,4.0,4,95,Urban,HR Executive,53743,1 +26092,Female,42,Masters,8,90,55,72,60,8.0,4,74,Urban,Manager,99389,1 +26093,Male,36,Bachelors,19,22,7,66,18,6.0,6,92,Urban,Manager,54100,0 +26094,Other,29,Masters,17,87,94,22,78,8.0,7,56,Semi-Urban,Data Analyst,120832,1 +26095,Male,33,Masters,6,28,55,73,18,8.0,1,98,Rural,ML Engineer,49488,1 +26096,Female,29,High School,3,71,17,2,16,6.0,4,54,Rural,Manager,144014,0 +26097,Male,39,Masters,15,26,42,78,66,8.0,1,90,Semi-Urban,ML Engineer,21338,1 +26098,Female,39,Bachelors,12,90,23,0,69,1.0,4,79,Rural,Software Engineer,132120,0 +26099,Male,32,Bachelors,5,98,21,65,51,1.0,5,91,Urban,Manager,50220,1 +26100,Male,30,Diploma,10,11,9,67,21,0.0,0,81,Urban,Data Analyst,76112,0 +26101,Male,33,High School,18,27,7,77,80,7.0,1,38,Rural,HR Executive,109795,0 +26102,Female,24,Bachelors,6,91,75,4,23,0.0,0,30,Urban,Data Analyst,142172,0 +26103,Male,21,High School,7,96,29,38,23,9.0,0,57,Urban,Software Engineer,139368,0 +26104,Male,35,Bachelors,9,91,87,81,66,5.0,6,67,Rural,Software Engineer,59261,1 +26105,Male,22,PhD,6,1,73,76,80,4.0,6,3,Urban,ML Engineer,98695,0 +26106,Male,28,PhD,9,90,9,60,1,0.0,3,19,Urban,ML Engineer,23107,0 +26107,Male,21,High School,13,59,54,76,58,5.0,7,74,Semi-Urban,HR Executive,31556,1 +26108,Male,49,Diploma,8,96,4,13,22,1.0,0,3,Urban,HR Executive,71640,0 +26109,Female,43,Diploma,7,68,33,29,10,0.0,3,38,Semi-Urban,ML Engineer,103805,0 +26110,Female,59,Masters,5,90,76,71,66,9.0,4,0,Urban,Software Engineer,50328,0 +26111,Female,37,Bachelors,1,46,31,98,17,3.0,6,63,Urban,Manager,102453,0 +26112,Female,33,Diploma,15,74,85,85,19,5.0,0,13,Rural,Manager,139257,1 +26113,Male,35,Diploma,9,54,80,65,59,6.0,3,17,Urban,Manager,143331,0 +26114,Female,28,Diploma,5,6,54,52,80,6.0,1,15,Rural,HR Executive,71077,0 +26115,Male,52,Bachelors,14,17,39,67,7,3.0,5,44,Urban,Data Analyst,41407,0 +26116,Male,27,Diploma,11,30,89,48,62,3.0,5,26,Urban,Data Analyst,82140,0 +26117,Male,33,High School,6,91,18,86,4,5.0,1,71,Urban,ML Engineer,55560,1 +26118,Male,35,Diploma,1,88,16,61,98,1.0,1,53,Urban,Manager,124636,0 +26119,Male,38,Bachelors,13,38,5,2,5,4.0,6,77,Rural,ML Engineer,45273,0 +26120,Male,37,Bachelors,9,40,2,22,62,9.0,1,6,Rural,Manager,44545,0 +26121,Female,37,Masters,13,17,63,87,87,7.0,4,56,Semi-Urban,Data Analyst,43586,0 +26122,Male,24,Masters,18,83,32,79,65,1.0,7,47,Semi-Urban,Software Engineer,87915,1 +26123,Male,55,Bachelors,8,28,90,38,55,6.0,7,38,Urban,ML Engineer,67000,0 +26124,Male,34,Masters,8,3,27,25,95,5.0,5,91,Rural,ML Engineer,136713,0 +26125,Male,59,Bachelors,5,1,61,68,75,4.0,6,21,Rural,Software Engineer,112940,0 +26126,Male,35,Bachelors,18,10,75,1,45,5.0,6,32,Semi-Urban,Data Analyst,120113,0 +26127,Male,42,Bachelors,18,82,56,44,15,4.0,1,40,Urban,Manager,90823,0 +26128,Male,50,Masters,2,30,68,41,66,3.0,7,81,Semi-Urban,Manager,81465,0 +26129,Female,48,Bachelors,18,67,85,55,2,1.0,2,4,Urban,HR Executive,134691,0 +26130,Female,49,Masters,14,20,24,11,56,9.0,7,80,Urban,Data Analyst,103201,0 +26131,Male,48,Masters,15,21,5,76,23,6.0,2,70,Urban,Data Analyst,43475,0 +26132,Male,22,Diploma,14,87,56,56,58,5.0,1,19,Rural,Data Analyst,122161,0 +26133,Female,51,Bachelors,18,52,26,81,0,1.0,7,38,Urban,HR Executive,25042,0 +26134,Male,29,Bachelors,6,7,59,28,88,3.0,0,78,Urban,Manager,106140,0 +26135,Male,44,Bachelors,13,59,43,35,38,7.0,4,98,Urban,Manager,125404,1 +26136,Male,55,Bachelors,19,5,30,79,65,0.0,3,94,Urban,ML Engineer,20538,0 +26137,Female,36,High School,8,89,11,64,51,7.0,2,38,Semi-Urban,HR Executive,105666,0 +26138,Male,48,Diploma,10,68,31,44,91,1.0,4,25,Rural,HR Executive,71800,0 +26139,Female,44,PhD,15,86,30,26,39,3.0,5,47,Semi-Urban,Data Analyst,31868,0 +26140,Male,52,Bachelors,4,94,91,63,68,4.0,1,59,Urban,Data Analyst,94086,1 +26141,Male,39,Bachelors,6,87,50,98,29,8.0,5,7,Urban,Manager,128701,1 +26142,Male,30,Masters,5,89,71,53,79,3.0,4,54,Rural,ML Engineer,59676,1 +26143,Female,30,Bachelors,19,73,51,26,12,2.0,7,28,Rural,Data Analyst,138357,0 +26144,Female,25,PhD,4,22,90,21,52,0.0,7,58,Urban,ML Engineer,36865,0 +26145,Male,51,Diploma,10,9,53,62,65,7.0,3,74,Urban,HR Executive,39935,0 +26146,Male,50,Diploma,8,30,97,4,41,6.0,3,25,Urban,HR Executive,72076,0 +26147,Male,56,Bachelors,8,70,90,56,67,8.0,6,53,Urban,Data Analyst,45067,1 +26148,Male,48,High School,17,72,15,76,90,2.0,6,10,Urban,HR Executive,29499,0 +26149,Male,21,Bachelors,19,77,40,64,47,4.0,7,59,Semi-Urban,Software Engineer,148719,1 +26150,Male,44,Bachelors,1,58,43,64,40,3.0,0,46,Urban,ML Engineer,34173,0 +26151,Other,36,Bachelors,15,2,87,6,20,5.0,0,9,Urban,Manager,52979,0 +26152,Male,52,PhD,17,49,66,76,17,4.0,5,87,Semi-Urban,Data Analyst,126123,1 +26153,Male,27,Masters,0,89,97,53,49,7.0,6,17,Urban,Data Analyst,145985,1 +26154,Male,41,Bachelors,6,55,70,68,12,2.0,5,88,Semi-Urban,HR Executive,138336,1 +26155,Male,34,High School,6,86,59,98,43,2.0,2,68,Urban,Manager,119074,1 +26156,Male,22,Masters,9,4,68,63,55,9.0,2,93,Urban,Manager,30999,0 +26157,Female,59,Bachelors,11,97,89,93,64,1.0,2,13,Rural,Software Engineer,131538,1 +26158,Male,29,Diploma,8,34,70,19,10,9.0,3,87,Urban,ML Engineer,112387,0 +26159,Other,21,Diploma,15,3,65,53,16,8.0,5,25,Semi-Urban,Data Analyst,93261,0 +26160,Male,51,Bachelors,6,19,37,41,53,9.0,6,91,Urban,Data Analyst,126972,0 +26161,Male,55,Masters,3,1,81,30,24,9.0,0,3,Semi-Urban,Software Engineer,49675,0 +26162,Male,25,High School,8,74,59,17,24,3.0,4,38,Urban,Data Analyst,85794,0 +26163,Female,37,High School,6,80,65,83,47,3.0,5,20,Urban,Data Analyst,120553,1 +26164,Male,23,High School,8,66,19,81,59,6.0,0,13,Urban,HR Executive,77682,0 +26165,Male,23,High School,9,2,10,62,52,4.0,2,21,Semi-Urban,Manager,142504,0 +26166,Male,54,Diploma,17,12,92,82,11,9.0,3,32,Semi-Urban,Software Engineer,112884,0 +26167,Female,42,Bachelors,9,51,40,75,7,7.0,0,55,Rural,ML Engineer,78581,0 +26168,Male,43,PhD,5,16,23,83,4,2.0,1,87,Urban,HR Executive,98584,0 +26169,Male,26,PhD,1,19,19,39,57,5.0,6,98,Urban,Software Engineer,48104,0 +26170,Male,28,Diploma,11,36,60,5,24,1.0,6,76,Urban,Manager,133775,0 +26171,Male,27,Masters,5,55,55,77,42,9.0,6,31,Urban,HR Executive,90766,0 +26172,Male,24,Masters,10,36,57,96,90,9.0,2,62,Urban,Software Engineer,80402,1 +26173,Male,22,High School,10,69,40,31,93,5.0,0,51,Rural,Data Analyst,87946,0 +26174,Female,56,Bachelors,1,29,5,60,73,2.0,6,76,Urban,Data Analyst,54052,0 +26175,Male,52,Diploma,6,88,71,77,23,6.0,6,95,Semi-Urban,HR Executive,148342,1 +26176,Female,55,Diploma,6,37,73,76,43,5.0,2,22,Rural,HR Executive,141492,0 +26177,Female,25,Bachelors,2,45,79,74,87,1.0,6,40,Rural,ML Engineer,60723,0 +26178,Male,48,High School,16,94,42,10,35,9.0,4,51,Rural,HR Executive,23422,0 +26179,Male,31,High School,4,36,10,77,32,7.0,4,58,Urban,Manager,87085,0 +26180,Female,29,Masters,7,53,76,13,76,7.0,2,33,Urban,ML Engineer,20008,0 +26181,Female,56,Diploma,16,22,80,67,6,9.0,1,56,Rural,Data Analyst,32717,0 +26182,Female,59,Bachelors,13,26,26,57,59,4.0,7,46,Rural,ML Engineer,28091,0 +26183,Female,22,Bachelors,5,45,82,73,67,5.0,1,56,Rural,ML Engineer,81249,1 +26184,Male,26,High School,19,10,6,28,30,6.0,3,65,Semi-Urban,Data Analyst,35713,0 +26185,Female,42,High School,13,7,79,31,10,1.0,4,81,Urban,Data Analyst,66535,0 +26186,Male,50,Bachelors,17,33,0,18,79,8.0,3,77,Urban,Manager,24846,0 +26187,Male,25,Bachelors,8,87,31,35,62,3.0,6,96,Rural,Software Engineer,146823,1 +26188,Male,49,Diploma,10,94,14,69,44,1.0,2,20,Rural,Data Analyst,57008,0 +26189,Female,26,Masters,9,22,96,53,63,3.0,3,13,Semi-Urban,HR Executive,101333,0 +26190,Male,21,Bachelors,13,52,26,66,65,5.0,5,1,Semi-Urban,Manager,60936,0 +26191,Female,22,Masters,2,78,76,78,64,6.0,5,51,Urban,Manager,102422,1 +26192,Female,58,High School,4,16,91,3,63,4.0,6,69,Urban,HR Executive,99127,0 +26193,Female,24,High School,2,78,34,91,63,1.0,5,89,Semi-Urban,Software Engineer,114568,1 +26194,Female,28,High School,8,94,51,66,69,3.0,2,82,Urban,HR Executive,134255,1 +26195,Male,41,Masters,14,50,70,83,38,3.0,6,36,Rural,Manager,77083,1 +26196,Female,29,Diploma,7,79,27,87,41,9.0,1,60,Semi-Urban,Manager,112241,1 +26197,Female,58,Bachelors,1,12,71,8,9,6.0,7,92,Urban,Data Analyst,75767,0 +26198,Female,54,Bachelors,12,44,48,10,47,2.0,1,89,Semi-Urban,HR Executive,139478,0 +26199,Female,32,Bachelors,11,83,29,26,46,3.0,1,24,Semi-Urban,HR Executive,105666,0 +26200,Male,35,Bachelors,16,96,50,69,75,7.0,2,92,Urban,Manager,64953,1 +26201,Male,47,Bachelors,0,99,53,3,50,0.0,1,34,Semi-Urban,Manager,96880,0 +26202,Male,36,High School,8,33,89,95,74,9.0,3,40,Urban,Software Engineer,108638,1 +26203,Female,25,Masters,14,52,34,92,8,8.0,5,56,Rural,Manager,71901,0 +26204,Male,51,High School,10,79,51,26,69,2.0,7,52,Urban,Data Analyst,146946,0 +26205,Female,57,Bachelors,4,35,9,14,76,8.0,7,20,Semi-Urban,HR Executive,139294,0 +26206,Male,55,Bachelors,2,60,4,74,13,4.0,7,13,Urban,ML Engineer,118426,0 +26207,Female,56,Bachelors,18,76,14,60,85,4.0,2,11,Semi-Urban,HR Executive,116315,0 +26208,Female,42,High School,15,29,95,7,56,8.0,0,39,Urban,Manager,145542,0 +26209,Male,48,Bachelors,15,53,2,43,4,7.0,4,52,Urban,HR Executive,133717,0 +26210,Female,35,Masters,18,18,16,68,49,8.0,4,22,Urban,ML Engineer,90700,0 +26211,Female,35,Bachelors,0,9,64,6,59,0.0,1,14,Semi-Urban,HR Executive,78306,0 +26212,Male,45,Bachelors,5,35,79,9,86,1.0,1,18,Rural,Software Engineer,50740,0 +26213,Male,55,PhD,7,36,54,41,74,4.0,2,53,Rural,ML Engineer,127353,0 +26214,Male,37,Bachelors,11,5,0,99,70,7.0,5,90,Semi-Urban,ML Engineer,126280,0 +26215,Female,30,Bachelors,7,6,94,41,6,1.0,5,7,Rural,Software Engineer,38512,0 +26216,Male,50,Diploma,7,93,17,66,4,3.0,7,75,Rural,Software Engineer,51181,1 +26217,Male,50,PhD,5,37,1,70,47,2.0,3,98,Urban,Manager,66719,0 +26218,Male,56,High School,7,55,15,85,59,0.0,3,95,Urban,Manager,72031,1 +26219,Male,54,Bachelors,17,50,30,74,74,2.0,4,87,Urban,HR Executive,48990,1 +26220,Female,52,Masters,3,21,86,44,19,0.0,0,56,Urban,Manager,31712,0 +26221,Female,30,Bachelors,17,77,16,14,45,4.0,5,72,Urban,Data Analyst,137290,0 +26222,Male,59,Diploma,2,47,64,13,85,9.0,6,33,Semi-Urban,ML Engineer,65528,0 +26223,Female,27,Masters,15,6,86,8,91,4.0,5,99,Semi-Urban,HR Executive,122186,0 +26224,Female,47,Bachelors,9,45,99,14,44,5.0,1,63,Semi-Urban,ML Engineer,109548,0 +26225,Male,21,Diploma,16,38,22,77,55,7.0,7,92,Urban,HR Executive,83111,0 +26226,Male,24,Bachelors,15,42,47,12,41,6.0,2,55,Urban,Manager,26833,0 +26227,Female,24,Bachelors,16,37,94,78,57,7.0,0,76,Urban,Manager,130643,1 +26228,Female,29,Bachelors,15,55,53,22,30,3.0,7,83,Semi-Urban,Manager,52460,0 +26229,Female,35,Bachelors,6,47,13,34,1,7.0,0,45,Rural,ML Engineer,24055,0 +26230,Male,30,Diploma,16,62,91,58,95,5.0,1,19,Rural,ML Engineer,69135,0 +26231,Female,28,Bachelors,8,86,53,23,56,8.0,2,22,Semi-Urban,Data Analyst,46145,0 +26232,Male,45,Masters,12,25,41,98,36,7.0,6,18,Urban,ML Engineer,80870,0 +26233,Female,35,Masters,1,31,21,53,41,1.0,2,44,Urban,HR Executive,55072,0 +26234,Other,24,Masters,12,46,77,33,40,0.0,3,60,Urban,Manager,33816,0 +26235,Other,33,Bachelors,11,17,35,23,6,6.0,7,76,Semi-Urban,HR Executive,82960,0 +26236,Female,40,Bachelors,9,45,17,37,82,7.0,6,33,Urban,ML Engineer,125853,0 +26237,Male,21,Masters,4,29,30,60,90,7.0,6,92,Urban,ML Engineer,102127,0 +26238,Female,46,Masters,1,1,22,47,74,5.0,1,63,Semi-Urban,HR Executive,27763,0 +26239,Male,55,High School,7,59,35,25,68,8.0,6,99,Rural,HR Executive,94609,0 +26240,Female,37,Bachelors,15,61,42,78,72,9.0,0,93,Semi-Urban,Manager,46202,1 +26241,Male,48,Diploma,9,43,31,50,60,1.0,3,1,Semi-Urban,Software Engineer,27296,0 +26242,Female,43,Bachelors,10,22,81,83,82,7.0,7,41,Urban,Data Analyst,54677,0 +26243,Male,58,Masters,18,17,2,66,60,0.0,4,24,Semi-Urban,Manager,109331,0 +26244,Female,45,High School,8,42,24,35,71,5.0,0,65,Urban,Manager,74971,0 +26245,Male,34,Diploma,14,8,46,97,72,6.0,5,11,Urban,Manager,143739,0 +26246,Male,51,Masters,1,92,92,79,2,9.0,0,18,Rural,Data Analyst,147687,1 +26247,Female,33,Bachelors,13,66,6,8,37,6.0,6,27,Urban,Software Engineer,99711,0 +26248,Female,38,Diploma,18,26,6,62,53,8.0,6,23,Urban,ML Engineer,96285,0 +26249,Male,38,Bachelors,2,17,49,77,24,5.0,6,87,Semi-Urban,ML Engineer,122947,0 +26250,Male,31,Masters,10,41,64,26,65,0.0,6,76,Rural,Software Engineer,37019,0 +26251,Male,26,Diploma,1,10,21,13,56,9.0,4,69,Urban,HR Executive,133037,0 +26252,Female,25,High School,12,70,94,17,8,7.0,1,44,Urban,HR Executive,23640,0 +26253,Other,27,Diploma,9,67,86,96,97,8.0,3,63,Urban,Manager,87968,1 +26254,Female,55,PhD,2,97,58,78,41,4.0,0,88,Urban,Software Engineer,140153,1 +26255,Male,21,Bachelors,16,72,92,10,52,9.0,3,84,Semi-Urban,Manager,118432,1 +26256,Male,34,Diploma,10,12,12,24,24,2.0,6,98,Semi-Urban,Manager,64399,0 +26257,Other,34,Masters,18,37,0,30,24,0.0,5,41,Urban,Data Analyst,120570,0 +26258,Male,26,High School,12,84,12,75,63,5.0,4,79,Urban,Software Engineer,110589,1 +26259,Male,39,High School,15,61,4,75,34,6.0,5,71,Urban,HR Executive,118761,0 +26260,Male,29,Masters,18,97,18,21,53,0.0,7,60,Urban,Data Analyst,35867,0 +26261,Female,44,Diploma,3,67,26,46,17,3.0,0,38,Urban,ML Engineer,135208,0 +26262,Female,58,Diploma,2,22,88,92,97,5.0,6,4,Urban,Data Analyst,73324,0 +26263,Male,31,Diploma,10,97,25,85,77,5.0,2,96,Urban,Manager,85277,1 +26264,Female,50,Diploma,3,89,21,30,76,0.0,4,23,Urban,HR Executive,141954,0 +26265,Male,33,PhD,13,16,36,57,62,5.0,4,49,Urban,Software Engineer,147680,0 +26266,Male,50,Diploma,14,75,75,59,17,2.0,0,35,Semi-Urban,HR Executive,130589,1 +26267,Male,23,High School,7,54,29,54,29,0.0,5,12,Semi-Urban,ML Engineer,139923,0 +26268,Male,57,Masters,0,68,53,56,87,4.0,7,38,Urban,Manager,137433,0 +26269,Male,28,Masters,6,96,26,4,85,3.0,1,24,Semi-Urban,HR Executive,119599,0 +26270,Female,51,Bachelors,13,47,75,40,27,0.0,1,83,Urban,Data Analyst,66805,1 +26271,Male,36,Bachelors,12,39,59,39,18,3.0,6,81,Urban,Software Engineer,46645,0 +26272,Male,34,High School,0,60,38,90,88,9.0,2,42,Urban,Data Analyst,61599,0 +26273,Male,41,Masters,7,21,15,24,99,7.0,0,0,Urban,ML Engineer,126449,0 +26274,Male,36,Diploma,9,94,73,81,55,7.0,0,32,Rural,HR Executive,111878,1 +26275,Male,41,High School,16,33,37,58,25,6.0,6,91,Urban,HR Executive,78664,0 +26276,Male,54,PhD,6,26,96,23,71,3.0,3,29,Urban,ML Engineer,126558,0 +26277,Female,21,Bachelors,18,80,91,89,42,7.0,0,10,Urban,Manager,137677,1 +26278,Other,51,Masters,0,42,36,42,80,6.0,3,26,Urban,Manager,91407,0 +26279,Female,37,Bachelors,17,86,38,41,28,2.0,1,62,Semi-Urban,Data Analyst,148379,0 +26280,Male,54,High School,19,16,51,83,60,3.0,0,59,Semi-Urban,ML Engineer,108388,0 +26281,Female,39,Diploma,11,95,12,16,88,2.0,1,36,Urban,Data Analyst,100926,0 +26282,Male,55,Bachelors,2,43,60,72,84,4.0,5,76,Semi-Urban,Data Analyst,99066,1 +26283,Male,42,High School,0,42,42,19,45,0.0,6,35,Urban,Manager,87476,0 +26284,Male,36,Bachelors,19,82,1,51,88,2.0,6,24,Semi-Urban,Software Engineer,125669,0 +26285,Male,30,Bachelors,19,92,73,51,48,9.0,3,28,Urban,ML Engineer,105032,1 +26286,Female,35,Bachelors,6,93,96,47,64,7.0,4,44,Urban,Data Analyst,60700,1 +26287,Male,51,Masters,15,77,85,66,27,1.0,7,75,Semi-Urban,Manager,28515,1 +26288,Male,56,Masters,13,49,57,55,54,2.0,2,21,Urban,HR Executive,132483,0 +26289,Male,49,Masters,12,68,9,49,48,8.0,2,90,Urban,Software Engineer,47805,0 +26290,Female,54,Bachelors,3,57,33,93,74,3.0,5,4,Urban,Data Analyst,142581,0 +26291,Female,54,Diploma,11,65,35,5,21,8.0,4,17,Semi-Urban,HR Executive,37069,0 +26292,Male,24,High School,9,57,66,0,39,2.0,0,89,Semi-Urban,ML Engineer,55688,0 +26293,Female,52,Bachelors,13,86,86,81,12,1.0,1,83,Urban,ML Engineer,42111,1 +26294,Female,53,High School,7,32,28,81,73,1.0,1,64,Rural,ML Engineer,29197,0 +26295,Male,43,High School,14,29,92,96,76,1.0,5,65,Rural,ML Engineer,50872,1 +26296,Female,32,Diploma,10,92,82,79,93,1.0,2,30,Urban,Manager,99710,1 +26297,Male,23,Diploma,6,85,70,3,29,7.0,1,75,Urban,Data Analyst,101637,0 +26298,Male,38,Diploma,6,22,90,13,70,4.0,2,28,Urban,Data Analyst,73998,0 +26299,Female,22,Bachelors,12,73,97,44,68,2.0,5,48,Urban,Data Analyst,40213,1 +26300,Male,29,Bachelors,19,73,58,36,27,5.0,6,48,Semi-Urban,HR Executive,143756,0 +26301,Male,36,PhD,0,96,10,99,21,3.0,0,94,Urban,HR Executive,98949,1 +26302,Female,42,Bachelors,10,93,6,2,73,3.0,3,86,Urban,HR Executive,103725,0 +26303,Male,49,Masters,13,40,93,5,57,1.0,7,93,Urban,Manager,129010,0 +26304,Male,34,PhD,8,61,42,39,12,1.0,6,9,Rural,HR Executive,37494,0 +26305,Male,51,Diploma,1,57,71,74,41,0.0,5,39,Urban,ML Engineer,49010,1 +26306,Male,46,Diploma,13,63,86,49,74,7.0,4,37,Rural,ML Engineer,113955,1 +26307,Male,50,Bachelors,4,83,55,65,59,4.0,6,1,Semi-Urban,HR Executive,68142,0 +26308,Other,49,Bachelors,19,47,5,10,55,5.0,0,82,Urban,Data Analyst,128858,0 +26309,Male,49,Bachelors,8,56,93,86,78,4.0,3,60,Urban,Software Engineer,89992,1 +26310,Female,54,Bachelors,16,33,34,28,48,5.0,0,18,Rural,HR Executive,83535,0 +26311,Male,41,Diploma,6,65,97,93,84,5.0,0,6,Urban,HR Executive,29316,1 +26312,Female,26,Masters,11,38,85,98,14,0.0,7,97,Urban,HR Executive,143427,1 +26313,Other,36,Diploma,16,97,62,29,85,5.0,2,27,Rural,Software Engineer,122224,0 +26314,Male,48,Diploma,8,15,73,87,70,8.0,0,88,Urban,Software Engineer,46140,1 +26315,Female,29,Masters,0,0,73,59,44,3.0,2,80,Semi-Urban,Manager,29938,0 +26316,Other,26,Diploma,15,58,8,34,38,8.0,1,32,Semi-Urban,HR Executive,143738,0 +26317,Male,50,Bachelors,10,16,96,36,59,9.0,3,75,Urban,HR Executive,51240,0 +26318,Male,29,Bachelors,15,55,85,24,56,9.0,5,14,Semi-Urban,ML Engineer,78513,0 +26319,Female,52,High School,16,23,42,38,23,3.0,7,76,Urban,Data Analyst,128111,0 +26320,Female,48,PhD,15,81,87,21,89,0.0,3,17,Urban,Data Analyst,105186,0 +26321,Male,45,Bachelors,5,98,18,78,0,5.0,7,17,Urban,ML Engineer,25130,0 +26322,Male,48,High School,19,9,40,20,49,6.0,2,72,Semi-Urban,Software Engineer,32251,0 +26323,Male,36,Diploma,6,23,47,87,87,4.0,2,47,Urban,Manager,66479,0 +26324,Male,33,Bachelors,15,62,46,52,38,1.0,4,8,Urban,HR Executive,94335,0 +26325,Female,31,Bachelors,16,29,63,46,32,9.0,2,0,Urban,Manager,80018,0 +26326,Male,45,Bachelors,6,27,8,87,25,5.0,2,23,Semi-Urban,Manager,67047,0 +26327,Male,30,Diploma,15,9,57,52,5,1.0,6,42,Urban,Software Engineer,65899,0 +26328,Female,42,Diploma,11,15,34,34,87,6.0,4,2,Semi-Urban,Manager,138450,0 +26329,Male,31,High School,2,34,83,40,22,6.0,6,48,Urban,Manager,63450,0 +26330,Male,32,Masters,17,95,16,69,88,2.0,2,33,Urban,Data Analyst,52265,0 +26331,Male,43,High School,8,82,53,24,97,4.0,0,55,Semi-Urban,Data Analyst,146432,0 +26332,Male,53,Masters,12,39,66,22,34,3.0,6,57,Urban,HR Executive,21241,0 +26333,Male,45,Bachelors,10,91,23,32,26,1.0,1,79,Semi-Urban,Data Analyst,98222,0 +26334,Male,35,Bachelors,3,13,27,69,1,6.0,3,4,Urban,HR Executive,47714,0 +26335,Male,57,Masters,8,50,23,92,62,3.0,1,17,Semi-Urban,ML Engineer,129067,0 +26336,Female,54,Bachelors,15,13,70,44,38,2.0,2,48,Urban,Data Analyst,50179,0 +26337,Female,50,Bachelors,6,21,24,22,95,8.0,0,0,Urban,Software Engineer,75241,0 +26338,Male,56,Bachelors,15,48,8,5,22,8.0,2,8,Semi-Urban,Data Analyst,71900,0 +26339,Male,39,Masters,4,66,67,21,31,3.0,3,16,Urban,Software Engineer,43998,0 +26340,Female,39,Diploma,13,15,30,88,69,6.0,5,81,Semi-Urban,ML Engineer,138997,0 +26341,Male,28,High School,6,25,60,40,88,1.0,2,31,Urban,ML Engineer,89525,0 +26342,Female,37,Bachelors,2,69,96,85,29,5.0,4,49,Urban,HR Executive,133333,1 +26343,Female,46,PhD,18,7,68,59,10,6.0,4,23,Urban,ML Engineer,147844,0 +26344,Male,30,Bachelors,12,85,26,39,41,8.0,2,9,Urban,Data Analyst,97160,0 +26345,Male,28,Diploma,3,86,37,61,40,9.0,4,14,Rural,ML Engineer,121902,0 +26346,Male,47,Bachelors,1,38,29,60,35,7.0,5,23,Urban,Manager,73024,0 +26347,Male,32,Masters,11,44,82,26,9,5.0,5,55,Urban,Manager,145110,0 +26348,Female,44,High School,17,94,21,13,53,1.0,5,83,Urban,Data Analyst,97538,0 +26349,Female,55,Masters,7,4,33,97,33,3.0,5,21,Rural,Manager,40971,0 +26350,Male,54,Bachelors,19,8,22,54,7,1.0,7,28,Semi-Urban,Manager,141210,0 +26351,Male,29,Diploma,13,76,18,39,64,5.0,1,11,Urban,HR Executive,50847,0 +26352,Male,22,Bachelors,4,48,35,17,27,0.0,4,92,Rural,HR Executive,111424,0 +26353,Male,56,Bachelors,14,25,65,97,9,4.0,5,86,Urban,Software Engineer,88686,1 +26354,Female,26,Masters,0,16,86,13,2,5.0,2,52,Semi-Urban,ML Engineer,137103,0 +26355,Female,47,Diploma,8,87,91,18,49,9.0,7,61,Urban,ML Engineer,49393,1 +26356,Male,33,Diploma,9,7,99,27,8,7.0,5,15,Urban,Software Engineer,29450,0 +26357,Male,43,High School,17,64,59,97,66,5.0,3,46,Semi-Urban,ML Engineer,141035,1 +26358,Male,44,Bachelors,13,65,94,93,90,3.0,2,17,Semi-Urban,Data Analyst,78318,1 +26359,Male,22,High School,1,62,41,29,61,4.0,0,11,Urban,Manager,124051,0 +26360,Male,43,Masters,13,81,2,56,74,1.0,7,92,Urban,Software Engineer,104316,0 +26361,Male,39,Bachelors,19,62,23,94,69,0.0,1,45,Semi-Urban,HR Executive,28620,0 +26362,Male,42,Diploma,7,81,93,39,88,8.0,4,44,Semi-Urban,Manager,50491,1 +26363,Female,23,Masters,16,26,40,19,45,5.0,3,88,Urban,HR Executive,53951,0 +26364,Male,47,Bachelors,12,43,86,95,78,1.0,7,47,Urban,Manager,131433,1 +26365,Male,25,High School,1,4,41,53,85,8.0,3,23,Urban,HR Executive,50422,0 +26366,Female,33,High School,4,4,46,57,77,7.0,3,3,Urban,Software Engineer,88395,0 +26367,Female,44,Diploma,6,6,26,22,69,6.0,2,57,Rural,Data Analyst,84689,0 +26368,Male,51,Bachelors,19,87,38,65,90,7.0,4,68,Urban,Manager,106873,1 +26369,Male,52,Masters,4,87,89,21,35,3.0,7,89,Rural,Software Engineer,139703,1 +26370,Female,35,High School,9,13,5,82,46,9.0,1,35,Semi-Urban,HR Executive,119400,0 +26371,Male,56,High School,19,34,13,64,97,3.0,3,71,Urban,Data Analyst,115215,0 +26372,Male,48,Masters,13,10,83,82,76,5.0,0,7,Semi-Urban,Manager,68032,0 +26373,Male,52,Diploma,8,63,54,8,5,8.0,6,98,Urban,HR Executive,127846,0 +26374,Male,43,Masters,7,16,72,39,10,7.0,1,26,Semi-Urban,Software Engineer,66508,0 +26375,Male,55,Masters,0,68,49,87,69,9.0,6,37,Urban,Manager,68144,1 +26376,Male,47,Masters,4,63,35,61,37,1.0,5,68,Urban,ML Engineer,134277,0 +26377,Female,31,Masters,16,13,16,40,28,6.0,0,89,Urban,Manager,78081,0 +26378,Female,34,Diploma,19,97,51,68,89,6.0,7,88,Urban,HR Executive,20294,1 +26379,Other,47,Diploma,7,40,2,18,40,2.0,7,27,Urban,Software Engineer,141831,0 +26380,Male,40,Diploma,9,75,36,66,73,2.0,7,34,Semi-Urban,HR Executive,78996,0 +26381,Male,33,Diploma,10,24,89,9,47,3.0,7,29,Rural,HR Executive,69301,0 +26382,Female,37,Bachelors,19,86,35,24,60,8.0,3,33,Urban,Data Analyst,35291,0 +26383,Male,54,Masters,10,88,39,75,58,1.0,6,92,Semi-Urban,ML Engineer,53497,1 +26384,Male,52,Bachelors,3,98,95,69,7,6.0,1,79,Urban,Manager,73548,1 +26385,Male,51,Masters,16,58,30,89,83,1.0,5,96,Urban,HR Executive,23683,1 +26386,Male,41,Masters,17,85,96,72,44,8.0,4,26,Semi-Urban,HR Executive,91169,1 +26387,Male,54,Bachelors,4,66,67,76,93,6.0,2,59,Semi-Urban,Software Engineer,81857,1 +26388,Male,35,Diploma,5,70,76,95,62,9.0,0,52,Semi-Urban,Data Analyst,35496,1 +26389,Other,48,Diploma,2,66,29,36,89,2.0,3,54,Urban,Manager,109033,0 +26390,Male,41,Diploma,6,47,4,6,67,6.0,5,57,Urban,ML Engineer,120122,0 +26391,Other,27,PhD,12,79,46,53,51,4.0,6,28,Rural,ML Engineer,96085,0 +26392,Female,45,Diploma,0,0,75,24,41,8.0,0,67,Urban,Software Engineer,101499,0 +26393,Male,42,Masters,2,92,92,39,33,7.0,1,73,Urban,Data Analyst,94211,1 +26394,Female,35,High School,14,27,41,69,3,6.0,4,92,Urban,HR Executive,64976,0 +26395,Female,48,Diploma,4,29,6,24,12,7.0,3,23,Urban,HR Executive,90019,0 +26396,Male,44,Masters,18,96,44,79,15,5.0,4,20,Semi-Urban,HR Executive,139057,1 +26397,Male,29,High School,8,55,78,57,7,7.0,3,21,Urban,ML Engineer,73498,0 +26398,Male,52,Bachelors,8,9,49,21,94,8.0,5,56,Urban,Data Analyst,88785,0 +26399,Female,35,Bachelors,2,74,21,32,70,9.0,3,69,Urban,Data Analyst,24739,0 +26400,Male,31,Bachelors,7,51,17,53,50,5.0,1,59,Urban,ML Engineer,123131,0 +26401,Male,53,Bachelors,0,44,3,53,46,2.0,3,49,Urban,ML Engineer,131164,0 +26402,Male,32,Bachelors,4,61,18,90,46,4.0,2,71,Urban,Data Analyst,122006,1 +26403,Male,26,Masters,18,51,32,95,0,8.0,6,38,Urban,ML Engineer,21207,0 +26404,Male,47,Bachelors,0,45,84,15,27,9.0,6,75,Semi-Urban,Data Analyst,130185,0 +26405,Male,40,Masters,16,56,22,24,24,1.0,5,18,Urban,Manager,120469,0 +26406,Female,22,Masters,8,48,46,25,18,1.0,7,28,Urban,Manager,130231,0 +26407,Female,33,High School,0,98,28,16,53,3.0,1,99,Urban,Manager,133804,1 +26408,Female,29,Diploma,8,73,44,88,93,7.0,1,59,Semi-Urban,Software Engineer,133809,1 +26409,Male,31,Masters,19,19,12,89,25,9.0,5,79,Rural,ML Engineer,44282,0 +26410,Female,27,PhD,16,63,49,27,22,4.0,4,34,Urban,Data Analyst,140153,0 +26411,Male,45,High School,2,51,88,94,27,0.0,3,38,Rural,Software Engineer,52152,1 +26412,Male,27,Bachelors,8,91,78,13,91,4.0,4,18,Rural,HR Executive,124182,0 +26413,Other,42,High School,11,79,24,41,40,5.0,6,61,Urban,Software Engineer,68312,0 +26414,Male,47,Bachelors,5,45,77,30,13,3.0,2,97,Urban,ML Engineer,98151,1 +26415,Male,52,Masters,6,29,28,47,62,6.0,5,57,Rural,ML Engineer,118926,0 +26416,Male,32,Diploma,14,22,43,6,88,8.0,5,68,Urban,Software Engineer,88646,0 +26417,Male,39,Masters,16,42,73,52,60,7.0,1,80,Urban,HR Executive,32231,1 +26418,Female,48,Masters,19,66,42,44,41,3.0,3,12,Urban,ML Engineer,64299,0 +26419,Male,32,Masters,16,28,29,44,70,7.0,7,50,Semi-Urban,Manager,134224,0 +26420,Female,39,Bachelors,18,90,75,94,28,9.0,3,26,Urban,HR Executive,25041,1 +26421,Male,56,Masters,8,39,12,48,83,7.0,0,11,Urban,Software Engineer,112080,0 +26422,Male,34,Bachelors,0,24,27,39,41,5.0,4,19,Rural,HR Executive,126215,0 +26423,Male,39,Bachelors,13,50,77,35,0,7.0,5,46,Rural,ML Engineer,40526,0 +26424,Female,55,Diploma,6,11,89,81,97,3.0,4,36,Urban,ML Engineer,119197,0 +26425,Female,49,Bachelors,9,87,60,25,22,7.0,0,55,Urban,ML Engineer,22448,0 +26426,Male,57,Diploma,18,68,98,77,71,9.0,4,81,Urban,HR Executive,77579,1 +26427,Male,25,Bachelors,6,32,5,73,32,3.0,0,25,Semi-Urban,HR Executive,102656,0 +26428,Other,37,Bachelors,17,2,72,46,64,2.0,2,55,Urban,ML Engineer,72542,0 +26429,Male,48,Masters,5,82,61,67,36,4.0,2,99,Semi-Urban,Software Engineer,90475,1 +26430,Male,55,Masters,14,55,57,29,18,8.0,7,62,Urban,Data Analyst,92018,0 +26431,Male,30,Bachelors,17,91,9,89,40,8.0,2,37,Urban,Data Analyst,94428,0 +26432,Male,23,Bachelors,15,0,55,25,72,6.0,6,31,Urban,Manager,147190,0 +26433,Male,27,Bachelors,13,64,9,82,33,6.0,1,3,Urban,Manager,48993,0 +26434,Male,45,Masters,6,90,83,50,36,7.0,1,24,Rural,HR Executive,98192,1 +26435,Female,37,High School,5,29,97,5,99,4.0,2,63,Urban,HR Executive,73536,0 +26436,Female,44,Diploma,12,32,19,20,11,9.0,6,99,Urban,ML Engineer,123962,0 +26437,Female,40,PhD,12,12,2,28,52,0.0,2,71,Urban,Manager,30353,0 +26438,Male,51,Diploma,12,36,26,94,90,9.0,1,11,Urban,Data Analyst,119942,0 +26439,Male,39,High School,1,27,5,51,42,3.0,5,1,Semi-Urban,Software Engineer,123035,0 +26440,Female,50,Bachelors,3,20,33,22,84,5.0,4,88,Rural,Data Analyst,86655,0 +26441,Female,25,PhD,6,44,9,3,13,8.0,4,71,Semi-Urban,Manager,26406,0 +26442,Male,30,Bachelors,2,93,97,81,35,9.0,4,89,Rural,Manager,71029,1 +26443,Male,45,Bachelors,2,22,40,51,7,3.0,0,3,Urban,HR Executive,141153,0 +26444,Female,35,Bachelors,16,77,86,38,20,5.0,5,23,Urban,Manager,58189,0 +26445,Other,41,Bachelors,8,85,26,74,74,9.0,3,67,Urban,Data Analyst,26879,1 +26446,Other,36,Bachelors,2,85,98,3,47,4.0,7,54,Urban,Manager,22699,0 +26447,Female,49,PhD,8,48,30,27,64,4.0,0,34,Semi-Urban,Manager,137244,0 +26448,Male,58,Diploma,1,62,61,77,64,0.0,2,48,Urban,Data Analyst,140033,1 +26449,Male,48,Diploma,3,23,50,23,41,9.0,7,11,Urban,Manager,118772,0 +26450,Female,57,Bachelors,19,82,36,81,17,5.0,1,67,Semi-Urban,Software Engineer,90430,1 +26451,Male,28,Bachelors,14,98,29,67,85,6.0,1,33,Urban,HR Executive,79250,0 +26452,Male,35,Bachelors,16,18,97,22,72,0.0,4,31,Semi-Urban,Manager,112651,0 +26453,Female,52,Bachelors,9,27,95,0,98,7.0,3,4,Urban,ML Engineer,105510,0 +26454,Male,36,Bachelors,16,70,4,63,61,7.0,0,74,Urban,Software Engineer,23186,0 +26455,Female,44,Diploma,12,65,69,38,62,2.0,0,77,Rural,HR Executive,27140,1 +26456,Female,36,Bachelors,10,90,45,81,61,1.0,6,66,Semi-Urban,Software Engineer,141732,1 +26457,Male,28,High School,4,12,13,11,65,4.0,0,95,Semi-Urban,Software Engineer,49213,0 +26458,Male,35,Bachelors,18,30,88,66,33,9.0,2,88,Urban,Manager,142692,1 +26459,Male,35,Diploma,6,44,93,23,7,8.0,5,24,Rural,Data Analyst,99151,0 +26460,Female,26,Bachelors,14,52,93,46,41,0.0,4,35,Urban,Manager,67615,0 +26461,Male,36,Bachelors,18,78,55,23,85,5.0,4,69,Urban,Manager,121582,0 +26462,Male,31,Masters,7,67,61,99,12,9.0,1,43,Rural,Software Engineer,60242,1 +26463,Other,21,Diploma,19,47,6,95,84,3.0,1,74,Urban,ML Engineer,92788,0 +26464,Male,39,High School,17,68,62,89,26,5.0,3,27,Rural,HR Executive,44824,1 +26465,Male,34,High School,15,37,61,3,52,1.0,3,64,Urban,Manager,65118,0 +26466,Male,30,Bachelors,7,43,12,30,52,0.0,6,65,Rural,ML Engineer,88464,0 +26467,Male,27,Bachelors,13,87,96,19,40,0.0,0,6,Urban,Manager,58706,0 +26468,Other,38,Bachelors,14,34,1,79,58,3.0,2,98,Urban,ML Engineer,91416,0 +26469,Male,22,Diploma,14,67,37,83,18,1.0,5,10,Semi-Urban,Software Engineer,87399,0 +26470,Male,31,Bachelors,16,81,7,58,52,5.0,1,64,Urban,Data Analyst,149732,0 +26471,Female,57,Bachelors,13,68,41,40,30,8.0,4,55,Rural,Data Analyst,54721,0 +26472,Female,28,Bachelors,7,31,23,90,96,5.0,7,28,Urban,Data Analyst,72380,0 +26473,Male,26,Bachelors,16,57,41,25,53,9.0,0,30,Urban,ML Engineer,125510,0 +26474,Female,46,Diploma,5,84,39,56,47,8.0,5,15,Urban,Manager,85176,0 +26475,Female,58,Diploma,4,47,1,63,89,1.0,2,43,Semi-Urban,Manager,38238,0 +26476,Male,34,Masters,3,55,48,18,18,0.0,0,83,Urban,ML Engineer,95401,0 +26477,Female,48,High School,1,72,67,57,22,4.0,4,22,Semi-Urban,Software Engineer,115580,0 +26478,Female,54,Bachelors,13,65,17,22,33,7.0,4,36,Urban,HR Executive,123915,0 +26479,Male,37,Masters,12,70,47,74,2,6.0,7,67,Rural,HR Executive,81745,1 +26480,Female,33,Bachelors,2,36,21,17,59,2.0,5,72,Urban,ML Engineer,127171,0 +26481,Other,50,PhD,16,92,85,87,52,4.0,7,61,Urban,HR Executive,146837,1 +26482,Female,21,Bachelors,2,83,33,76,66,3.0,0,41,Urban,Data Analyst,35060,0 +26483,Male,58,Bachelors,11,87,90,34,90,8.0,7,4,Urban,Manager,148342,0 +26484,Male,27,Bachelors,14,58,15,21,19,3.0,4,7,Urban,ML Engineer,106630,0 +26485,Male,27,Diploma,0,19,27,68,59,3.0,0,69,Semi-Urban,HR Executive,54197,0 +26486,Male,58,Bachelors,14,28,77,51,37,2.0,2,70,Urban,Manager,65038,0 +26487,Other,30,Bachelors,14,6,39,78,48,7.0,7,16,Semi-Urban,Data Analyst,49590,0 +26488,Male,58,Bachelors,7,16,77,2,4,7.0,3,31,Urban,Manager,31999,0 +26489,Male,47,High School,1,83,44,4,19,2.0,7,16,Urban,ML Engineer,55073,0 +26490,Female,55,Bachelors,4,88,74,65,58,9.0,4,18,Urban,Software Engineer,44059,1 +26491,Male,23,Bachelors,1,10,95,22,79,6.0,6,28,Urban,ML Engineer,127312,0 +26492,Male,38,Masters,16,82,41,88,53,3.0,3,61,Urban,Manager,21244,1 +26493,Male,22,Bachelors,17,94,91,2,50,6.0,3,40,Urban,ML Engineer,113358,0 +26494,Male,40,Bachelors,14,27,78,91,19,1.0,2,39,Rural,Manager,139676,1 +26495,Female,44,Masters,0,48,67,91,87,9.0,2,8,Urban,HR Executive,138219,0 +26496,Female,47,Masters,0,69,29,79,94,9.0,0,44,Semi-Urban,Manager,75733,0 +26497,Male,30,Bachelors,10,0,15,56,76,5.0,0,2,Urban,Data Analyst,102379,0 +26498,Male,26,Bachelors,7,73,8,7,42,8.0,6,66,Urban,HR Executive,36650,0 +26499,Female,27,Diploma,0,83,28,75,45,7.0,1,18,Rural,Software Engineer,43654,0 +26500,Female,31,Masters,12,12,6,91,87,2.0,1,87,Urban,Manager,28574,0 +26501,Male,40,Bachelors,15,65,75,61,0,7.0,2,60,Rural,ML Engineer,60849,1 +26502,Female,45,Masters,15,38,12,53,80,2.0,4,23,Urban,Manager,26385,0 +26503,Male,22,Bachelors,10,49,99,6,23,8.0,1,29,Semi-Urban,Manager,148288,0 +26504,Male,26,Bachelors,14,90,29,34,94,3.0,7,10,Urban,Software Engineer,28813,0 +26505,Female,23,High School,12,42,97,46,11,7.0,0,60,Urban,Software Engineer,85916,1 +26506,Male,22,Bachelors,9,61,79,7,78,2.0,2,77,Urban,Data Analyst,149361,0 +26507,Male,44,Masters,0,82,92,28,38,6.0,2,30,Semi-Urban,Manager,88502,0 +26508,Male,33,High School,16,8,80,42,82,9.0,4,97,Semi-Urban,Manager,130547,0 +26509,Male,25,Bachelors,3,76,23,83,83,6.0,7,57,Urban,Data Analyst,33562,1 +26510,Female,25,High School,3,21,12,68,44,2.0,3,13,Urban,Software Engineer,109443,0 +26511,Male,23,Diploma,14,96,95,69,93,1.0,0,83,Urban,HR Executive,23341,1 +26512,Male,55,PhD,15,0,60,91,7,0.0,3,47,Semi-Urban,Manager,31908,0 +26513,Male,54,Bachelors,17,21,97,72,73,0.0,3,3,Urban,HR Executive,85956,0 +26514,Female,22,Bachelors,13,34,32,93,76,4.0,7,28,Rural,Manager,56859,0 +26515,Male,43,Diploma,17,81,83,48,2,0.0,0,68,Urban,ML Engineer,58948,1 +26516,Female,34,High School,12,75,85,49,49,6.0,4,76,Semi-Urban,HR Executive,112311,1 +26517,Female,37,Masters,13,60,89,15,87,9.0,3,66,Rural,ML Engineer,99412,0 +26518,Other,43,Bachelors,18,74,64,78,74,6.0,5,78,Semi-Urban,Data Analyst,20261,1 +26519,Female,28,Masters,10,31,86,83,75,1.0,4,61,Urban,HR Executive,105949,1 +26520,Male,59,Bachelors,0,19,76,97,89,3.0,6,92,Rural,Software Engineer,32809,1 +26521,Male,33,High School,4,46,34,57,24,3.0,5,93,Urban,ML Engineer,37011,0 +26522,Female,35,Diploma,13,12,69,79,10,2.0,5,15,Semi-Urban,ML Engineer,102767,0 +26523,Female,27,Masters,6,29,90,12,35,4.0,1,78,Rural,ML Engineer,89954,0 +26524,Male,45,Diploma,12,92,95,74,85,8.0,6,99,Urban,HR Executive,52865,1 +26525,Male,56,High School,5,85,52,19,48,4.0,1,35,Semi-Urban,ML Engineer,34075,0 +26526,Male,23,Bachelors,7,33,67,21,33,1.0,3,96,Rural,ML Engineer,32101,0 +26527,Female,30,Diploma,14,84,78,60,41,7.0,3,88,Urban,Software Engineer,147108,1 +26528,Female,53,Bachelors,13,14,88,60,94,4.0,5,60,Rural,Software Engineer,112576,0 +26529,Male,44,Bachelors,6,42,68,16,87,0.0,5,92,Urban,ML Engineer,71260,0 +26530,Male,56,Diploma,1,6,8,18,42,1.0,5,20,Rural,Data Analyst,88316,0 +26531,Male,34,Diploma,9,2,1,2,37,2.0,7,59,Urban,Data Analyst,142037,0 +26532,Male,29,Masters,9,20,60,12,12,7.0,3,40,Urban,Software Engineer,135615,0 +26533,Female,33,Bachelors,2,19,32,88,68,4.0,0,53,Rural,Software Engineer,38759,0 +26534,Female,28,Diploma,12,1,49,89,66,2.0,0,10,Urban,ML Engineer,28300,0 +26535,Male,55,Bachelors,0,99,71,33,21,7.0,2,3,Urban,ML Engineer,140585,0 +26536,Male,49,Bachelors,0,7,92,16,59,2.0,5,60,Urban,Software Engineer,71557,0 +26537,Male,54,Diploma,7,87,34,87,94,0.0,4,66,Urban,HR Executive,43044,1 +26538,Female,44,Diploma,14,38,20,95,42,0.0,3,97,Semi-Urban,HR Executive,109526,1 +26539,Male,57,Bachelors,6,80,88,79,24,0.0,5,70,Rural,Data Analyst,23825,1 +26540,Male,31,Masters,15,66,75,39,65,0.0,5,57,Urban,Software Engineer,24861,1 +26541,Female,56,Bachelors,18,95,80,90,21,8.0,3,59,Urban,Data Analyst,115913,1 +26542,Female,26,High School,18,3,24,49,90,8.0,5,82,Rural,Software Engineer,97923,0 +26543,Female,47,Bachelors,19,78,46,98,33,2.0,3,18,Urban,ML Engineer,23693,0 +26544,Male,25,Diploma,2,60,26,5,26,7.0,4,57,Urban,Software Engineer,100918,0 +26545,Male,54,Masters,8,56,66,52,60,9.0,7,74,Rural,Software Engineer,97976,1 +26546,Male,53,Bachelors,8,32,99,61,74,1.0,3,8,Semi-Urban,Software Engineer,97422,0 +26547,Female,46,Bachelors,1,78,31,44,75,9.0,7,5,Rural,ML Engineer,138056,0 +26548,Female,57,Masters,5,29,52,6,82,6.0,6,52,Urban,Manager,125391,0 +26549,Female,34,Bachelors,13,43,68,26,76,4.0,3,58,Urban,Manager,37288,0 +26550,Male,54,Bachelors,4,70,48,78,0,2.0,6,31,Semi-Urban,HR Executive,118004,0 +26551,Female,50,Masters,16,1,74,71,79,0.0,5,90,Urban,Manager,52400,0 +26552,Male,29,Diploma,11,1,52,67,51,2.0,6,62,Rural,Data Analyst,98443,0 +26553,Male,55,Masters,0,31,40,24,73,1.0,5,92,Urban,Software Engineer,81086,0 +26554,Male,51,Masters,16,74,86,13,70,3.0,4,95,Urban,HR Executive,68101,1 +26555,Female,34,Diploma,5,20,18,51,28,0.0,6,73,Urban,ML Engineer,25626,0 +26556,Male,35,Bachelors,0,3,80,35,47,8.0,1,83,Urban,Manager,68153,0 +26557,Female,54,Bachelors,16,79,81,15,45,8.0,3,39,Urban,Software Engineer,86184,0 +26558,Female,21,Bachelors,8,37,58,21,78,8.0,5,62,Rural,Manager,107622,0 +26559,Male,28,Bachelors,11,38,81,11,81,7.0,5,9,Urban,ML Engineer,104998,0 +26560,Female,58,PhD,8,66,78,88,73,1.0,5,39,Urban,Manager,53112,1 +26561,Male,53,Bachelors,17,75,46,20,52,5.0,2,51,Rural,ML Engineer,136874,0 +26562,Male,47,Bachelors,17,67,98,27,87,9.0,6,5,Urban,HR Executive,109818,0 +26563,Female,22,Diploma,11,0,60,37,60,5.0,2,21,Semi-Urban,Manager,42684,0 +26564,Female,48,Diploma,18,36,82,94,28,4.0,7,91,Urban,Data Analyst,35116,1 +26565,Male,22,Bachelors,13,97,29,7,93,1.0,6,67,Urban,ML Engineer,76533,0 +26566,Female,56,Masters,12,47,83,97,56,0.0,4,81,Urban,Software Engineer,144646,1 +26567,Female,58,Bachelors,15,0,26,68,65,4.0,7,49,Urban,Software Engineer,115990,0 +26568,Male,27,PhD,4,65,35,0,90,7.0,6,6,Urban,ML Engineer,132912,0 +26569,Male,59,Bachelors,16,59,33,89,80,0.0,6,86,Urban,Manager,107945,1 +26570,Female,23,High School,19,91,24,11,87,5.0,0,27,Urban,Manager,95756,0 +26571,Male,32,Bachelors,0,94,83,58,81,1.0,1,58,Semi-Urban,HR Executive,88820,1 +26572,Female,28,PhD,3,56,52,95,9,8.0,3,52,Urban,Manager,102793,1 +26573,Female,32,Bachelors,16,4,99,95,30,8.0,6,29,Rural,HR Executive,34625,0 +26574,Male,28,Bachelors,11,44,96,24,83,7.0,5,33,Urban,Data Analyst,138196,0 +26575,Other,31,High School,11,16,6,35,99,8.0,3,0,Urban,Data Analyst,83139,0 +26576,Male,49,Diploma,2,94,32,47,78,5.0,2,38,Urban,Data Analyst,118951,0 +26577,Female,22,Diploma,13,65,46,30,70,0.0,7,94,Urban,Software Engineer,120695,0 +26578,Male,54,Diploma,2,4,72,14,57,6.0,5,96,Semi-Urban,ML Engineer,41016,0 +26579,Female,48,High School,17,42,75,24,4,0.0,4,69,Urban,Data Analyst,33305,0 +26580,Male,43,Bachelors,13,55,94,86,23,9.0,7,52,Urban,Software Engineer,49257,1 +26581,Female,54,Diploma,3,26,17,49,86,6.0,0,16,Semi-Urban,ML Engineer,120372,0 +26582,Male,32,Masters,4,51,14,0,6,8.0,6,70,Rural,Manager,146310,0 +26583,Male,50,Bachelors,17,62,97,39,3,6.0,7,90,Semi-Urban,Manager,122096,1 +26584,Male,41,Bachelors,18,34,95,9,56,8.0,3,99,Rural,HR Executive,73704,1 +26585,Female,30,High School,16,86,2,59,80,1.0,4,70,Semi-Urban,Manager,95691,0 +26586,Male,30,PhD,4,35,46,15,68,3.0,5,10,Urban,ML Engineer,36802,0 +26587,Female,50,Diploma,7,68,54,71,67,5.0,6,50,Urban,Manager,70008,1 +26588,Female,25,Bachelors,6,20,45,0,53,7.0,3,31,Urban,Data Analyst,122033,0 +26589,Female,45,Masters,5,88,10,23,92,4.0,4,5,Urban,Software Engineer,146145,0 +26590,Male,45,Diploma,0,62,27,29,38,8.0,2,55,Urban,Manager,74284,0 +26591,Female,24,Diploma,9,30,91,65,91,2.0,6,46,Urban,Manager,63565,0 +26592,Male,44,Bachelors,7,91,0,25,74,8.0,1,1,Urban,Data Analyst,85903,0 +26593,Female,33,Bachelors,0,43,25,54,13,5.0,5,46,Urban,Software Engineer,143158,0 +26594,Female,43,Bachelors,6,34,48,91,28,7.0,7,44,Semi-Urban,HR Executive,28622,0 +26595,Male,37,Bachelors,1,74,40,23,48,5.0,6,20,Urban,Manager,68388,0 +26596,Male,50,High School,6,31,25,17,86,8.0,3,79,Urban,Data Analyst,41038,0 +26597,Male,24,Diploma,16,15,21,21,80,3.0,0,2,Urban,Software Engineer,65578,0 +26598,Male,55,Bachelors,14,83,4,80,95,1.0,3,91,Semi-Urban,ML Engineer,114139,1 +26599,Female,41,Bachelors,7,36,71,10,89,7.0,4,10,Urban,Manager,144272,0 +26600,Male,23,Bachelors,16,12,48,30,22,7.0,6,34,Urban,HR Executive,103586,0 +26601,Female,40,High School,15,41,28,12,4,5.0,0,1,Urban,ML Engineer,108422,0 +26602,Male,34,High School,9,98,43,27,19,0.0,4,89,Urban,ML Engineer,46790,1 +26603,Other,38,Diploma,16,82,70,33,58,9.0,3,48,Semi-Urban,Data Analyst,91123,0 +26604,Female,53,Masters,15,65,67,9,93,0.0,2,64,Urban,ML Engineer,138602,0 +26605,Female,38,Diploma,3,19,54,68,27,7.0,6,22,Urban,Data Analyst,83803,0 +26606,Male,51,PhD,17,31,91,90,63,3.0,6,39,Urban,HR Executive,120711,1 +26607,Male,48,Diploma,0,27,70,28,88,6.0,2,69,Urban,Manager,98987,0 +26608,Male,27,Diploma,18,24,31,37,37,5.0,6,33,Urban,Data Analyst,149402,0 +26609,Male,56,Diploma,0,59,43,4,29,6.0,7,27,Urban,Software Engineer,75577,0 +26610,Female,56,Bachelors,17,69,22,7,66,0.0,4,39,Urban,HR Executive,120717,0 +26611,Female,56,High School,13,78,80,60,48,0.0,6,75,Urban,Data Analyst,146295,1 +26612,Male,41,Masters,9,51,34,77,24,4.0,2,47,Urban,Software Engineer,81527,0 +26613,Male,58,Bachelors,12,31,25,26,49,1.0,1,47,Semi-Urban,Data Analyst,84788,0 +26614,Male,22,Masters,17,99,15,30,8,1.0,7,42,Rural,HR Executive,117498,0 +26615,Male,54,Diploma,9,16,11,26,81,7.0,5,75,Urban,Data Analyst,20165,0 +26616,Male,24,Diploma,0,22,28,38,79,2.0,4,54,Urban,HR Executive,56774,0 +26617,Female,28,High School,1,69,89,69,91,4.0,6,15,Semi-Urban,Manager,140617,1 +26618,Male,51,Bachelors,2,4,4,90,88,4.0,1,1,Urban,HR Executive,107911,0 +26619,Female,38,Masters,12,81,61,14,91,1.0,0,29,Urban,ML Engineer,61889,0 +26620,Male,39,Bachelors,11,42,62,3,21,8.0,6,20,Semi-Urban,Data Analyst,36531,0 +26621,Female,47,Bachelors,4,76,62,37,14,2.0,3,83,Semi-Urban,Software Engineer,65483,1 +26622,Male,41,Diploma,1,29,36,76,10,2.0,3,63,Urban,ML Engineer,91934,0 +26623,Female,46,Bachelors,13,74,49,7,50,3.0,0,14,Rural,Software Engineer,54184,0 +26624,Male,41,Diploma,1,30,91,0,60,3.0,7,31,Urban,Data Analyst,129909,0 +26625,Male,24,Bachelors,13,85,2,57,25,3.0,0,4,Urban,ML Engineer,21067,0 +26626,Male,29,Diploma,4,52,30,24,85,1.0,7,33,Urban,Software Engineer,118436,0 +26627,Female,24,High School,8,38,21,60,12,4.0,3,72,Semi-Urban,HR Executive,85676,0 +26628,Female,59,Masters,7,81,99,53,58,6.0,1,79,Rural,ML Engineer,29217,1 +26629,Male,55,Diploma,17,60,63,60,14,5.0,6,36,Urban,ML Engineer,94407,0 +26630,Male,36,Bachelors,6,44,52,5,58,8.0,3,59,Rural,ML Engineer,97040,0 +26631,Male,37,Diploma,10,99,61,60,61,8.0,6,80,Urban,Data Analyst,62360,1 +26632,Male,27,Masters,11,94,95,63,53,6.0,7,89,Urban,Manager,94835,1 +26633,Female,23,Bachelors,17,10,91,73,73,4.0,3,58,Rural,HR Executive,51941,0 +26634,Female,56,Masters,3,83,71,74,13,5.0,2,5,Urban,Manager,62637,0 +26635,Female,56,Bachelors,12,56,22,49,44,8.0,3,51,Urban,HR Executive,23398,0 +26636,Other,57,Diploma,11,27,17,28,24,0.0,2,73,Semi-Urban,Software Engineer,99479,0 +26637,Female,35,High School,12,57,37,28,22,6.0,6,42,Semi-Urban,ML Engineer,66260,0 +26638,Male,58,Diploma,9,72,86,43,50,1.0,5,88,Urban,HR Executive,35350,1 +26639,Male,37,Masters,11,40,64,91,38,3.0,7,59,Urban,Data Analyst,44343,1 +26640,Male,27,Bachelors,16,89,13,79,29,5.0,2,16,Urban,Data Analyst,54143,0 +26641,Male,24,Diploma,19,54,5,99,86,5.0,6,25,Urban,Software Engineer,108307,0 +26642,Female,30,Masters,4,15,81,82,56,8.0,6,60,Semi-Urban,ML Engineer,128848,0 +26643,Other,37,Bachelors,6,0,64,86,25,6.0,6,26,Urban,Data Analyst,129009,0 +26644,Female,35,Diploma,4,28,32,46,8,6.0,5,86,Semi-Urban,Manager,41937,0 +26645,Male,38,PhD,11,85,74,92,17,1.0,1,27,Semi-Urban,ML Engineer,20369,1 +26646,Male,43,Bachelors,6,68,38,91,45,4.0,4,8,Urban,Software Engineer,133692,0 +26647,Female,35,Bachelors,7,32,14,68,39,9.0,7,42,Urban,Data Analyst,148610,0 +26648,Female,48,Bachelors,1,20,46,85,34,6.0,7,58,Urban,Data Analyst,121319,0 +26649,Male,38,PhD,2,69,81,70,70,2.0,1,79,Semi-Urban,HR Executive,146855,1 +26650,Female,33,High School,13,27,95,0,62,1.0,1,97,Urban,ML Engineer,115532,0 +26651,Female,56,Masters,1,37,55,68,41,6.0,0,77,Semi-Urban,Software Engineer,119367,0 +26652,Male,46,Bachelors,13,64,86,27,89,3.0,4,18,Urban,ML Engineer,43306,0 +26653,Male,33,Bachelors,3,46,58,28,41,1.0,0,41,Urban,HR Executive,95890,0 +26654,Female,26,Diploma,19,91,13,64,84,3.0,2,49,Semi-Urban,Software Engineer,111971,0 +26655,Female,45,Bachelors,8,71,20,80,51,7.0,7,49,Rural,Data Analyst,20280,0 +26656,Male,49,Masters,18,18,61,86,71,4.0,2,4,Urban,HR Executive,27982,0 +26657,Female,56,Diploma,4,91,54,86,32,1.0,5,41,Urban,Data Analyst,149318,1 +26658,Female,50,High School,4,89,56,48,64,9.0,1,50,Urban,Manager,92010,1 +26659,Female,40,Diploma,19,13,40,73,25,6.0,0,91,Semi-Urban,ML Engineer,77405,0 +26660,Male,57,Bachelors,15,77,35,63,85,0.0,6,27,Semi-Urban,HR Executive,38333,0 +26661,Other,36,High School,19,53,90,83,24,8.0,4,6,Urban,ML Engineer,39397,0 +26662,Male,46,High School,2,85,4,57,73,6.0,4,30,Urban,Software Engineer,120002,0 +26663,Female,42,High School,13,20,32,86,39,7.0,4,48,Rural,Data Analyst,32195,0 +26664,Female,40,High School,14,55,20,65,53,4.0,2,62,Urban,ML Engineer,92245,0 +26665,Male,43,Bachelors,11,97,1,42,88,8.0,3,77,Urban,HR Executive,111813,0 +26666,Male,27,Bachelors,12,46,17,98,74,8.0,5,58,Urban,ML Engineer,88576,0 +26667,Female,39,PhD,14,97,28,30,59,1.0,1,57,Semi-Urban,Manager,96154,0 +26668,Female,46,Bachelors,7,72,90,43,3,9.0,7,16,Urban,ML Engineer,57578,0 +26669,Male,54,Masters,5,36,47,38,91,8.0,5,82,Semi-Urban,HR Executive,31140,0 +26670,Male,46,Bachelors,13,42,83,10,1,5.0,7,68,Rural,ML Engineer,95870,0 +26671,Male,44,Bachelors,1,10,28,53,31,3.0,6,7,Urban,ML Engineer,30609,0 +26672,Male,52,Bachelors,16,84,94,37,64,9.0,4,62,Urban,HR Executive,84375,1 +26673,Other,33,High School,0,28,66,21,73,5.0,4,69,Semi-Urban,HR Executive,128498,0 +26674,Female,23,Masters,12,18,60,53,37,0.0,2,90,Semi-Urban,HR Executive,83163,0 +26675,Other,34,Masters,3,51,70,81,4,0.0,5,11,Rural,HR Executive,26614,0 +26676,Male,27,Diploma,8,32,14,95,85,4.0,7,97,Urban,ML Engineer,122778,1 +26677,Female,31,High School,14,45,61,11,87,3.0,0,27,Rural,Manager,101256,0 +26678,Male,57,Bachelors,7,82,42,73,38,2.0,6,30,Semi-Urban,HR Executive,115946,0 +26679,Female,57,PhD,7,24,45,26,40,0.0,6,53,Urban,Software Engineer,25040,0 +26680,Male,45,Bachelors,19,31,90,80,66,0.0,7,21,Urban,ML Engineer,51447,0 +26681,Male,27,Bachelors,9,90,54,2,70,1.0,2,23,Semi-Urban,Software Engineer,144364,0 +26682,Male,57,Diploma,13,78,9,49,90,4.0,4,50,Urban,Software Engineer,69881,0 +26683,Male,59,Bachelors,17,1,7,11,2,4.0,7,29,Urban,ML Engineer,66941,0 +26684,Female,55,Diploma,7,62,63,42,87,9.0,1,58,Urban,Data Analyst,47818,0 +26685,Female,29,Diploma,16,7,44,2,22,4.0,1,98,Urban,Manager,87716,0 +26686,Female,29,Bachelors,0,40,43,9,67,0.0,5,50,Rural,Manager,77995,0 +26687,Other,21,High School,14,75,78,57,13,7.0,0,89,Semi-Urban,Data Analyst,52812,1 +26688,Male,46,High School,17,83,91,81,56,1.0,4,33,Urban,ML Engineer,63539,1 +26689,Male,48,Bachelors,5,88,8,55,13,3.0,7,32,Rural,ML Engineer,121679,0 +26690,Female,57,Masters,10,57,0,89,65,9.0,1,35,Urban,Software Engineer,25503,0 +26691,Male,44,Diploma,13,20,42,22,23,5.0,7,50,Urban,Manager,24036,0 +26692,Male,56,Diploma,9,71,40,64,58,9.0,2,21,Semi-Urban,Manager,24528,0 +26693,Female,21,Bachelors,15,6,29,65,21,1.0,7,92,Urban,Manager,108839,0 +26694,Male,37,Bachelors,4,82,55,35,27,0.0,2,85,Semi-Urban,Software Engineer,126168,1 +26695,Male,59,Bachelors,16,57,46,80,96,6.0,7,15,Semi-Urban,ML Engineer,93117,0 +26696,Male,32,Diploma,8,81,51,70,14,2.0,5,32,Semi-Urban,Data Analyst,66205,0 +26697,Male,58,Diploma,15,22,34,87,50,7.0,4,22,Rural,Software Engineer,59858,0 +26698,Male,57,Bachelors,17,33,25,8,12,0.0,6,94,Semi-Urban,Software Engineer,48477,0 +26699,Male,59,Bachelors,17,90,71,84,58,2.0,2,92,Semi-Urban,Data Analyst,95924,1 +26700,Male,49,Bachelors,6,41,42,52,63,6.0,7,60,Rural,Software Engineer,51465,0 +26701,Male,34,Masters,1,5,83,51,4,4.0,1,57,Semi-Urban,Data Analyst,43480,0 +26702,Male,58,Diploma,19,21,70,47,69,6.0,0,68,Urban,HR Executive,125590,0 +26703,Female,55,Masters,9,35,77,45,37,2.0,7,96,Urban,ML Engineer,35416,1 +26704,Male,31,Bachelors,10,23,12,4,83,4.0,7,65,Urban,Manager,87369,0 +26705,Male,38,Masters,12,85,11,95,57,8.0,4,53,Semi-Urban,Data Analyst,64588,1 +26706,Male,30,Bachelors,18,79,32,3,17,5.0,3,71,Semi-Urban,Software Engineer,76208,0 +26707,Male,29,Bachelors,6,51,67,70,1,2.0,1,7,Urban,ML Engineer,107786,0 +26708,Male,29,Diploma,5,84,58,17,13,1.0,0,5,Semi-Urban,Data Analyst,62108,0 +26709,Male,49,Bachelors,14,66,49,85,57,2.0,6,41,Urban,Software Engineer,26382,1 +26710,Female,32,High School,5,93,24,32,83,3.0,0,20,Semi-Urban,Data Analyst,111058,0 +26711,Female,59,Diploma,12,98,37,68,56,6.0,0,34,Urban,ML Engineer,21804,0 +26712,Female,36,High School,14,59,84,32,6,1.0,5,23,Urban,HR Executive,34555,0 +26713,Male,31,Bachelors,0,7,55,14,56,9.0,5,8,Rural,Software Engineer,69472,0 +26714,Male,22,Masters,1,91,72,91,96,0.0,2,90,Rural,HR Executive,73157,1 +26715,Male,38,High School,12,59,19,4,25,3.0,0,45,Semi-Urban,Data Analyst,57995,0 +26716,Female,23,High School,16,57,14,80,92,8.0,5,88,Urban,Software Engineer,41929,0 +26717,Male,52,Bachelors,10,89,29,0,88,9.0,7,18,Urban,Data Analyst,96739,0 +26718,Male,59,Bachelors,19,5,30,33,30,8.0,4,89,Urban,Manager,84902,0 +26719,Male,52,Masters,1,51,89,37,38,7.0,4,79,Rural,Data Analyst,103575,1 +26720,Female,27,Diploma,12,0,67,71,79,7.0,2,5,Urban,Data Analyst,32169,0 +26721,Female,55,Bachelors,15,48,98,40,36,7.0,0,43,Urban,Data Analyst,39918,0 +26722,Female,34,Masters,6,9,93,65,13,6.0,6,7,Urban,Software Engineer,145195,0 +26723,Male,21,High School,13,41,62,91,48,9.0,2,67,Rural,Manager,54199,1 +26724,Male,58,High School,15,76,2,51,46,2.0,0,68,Urban,Data Analyst,48483,0 +26725,Female,27,Diploma,19,93,6,24,99,5.0,3,92,Semi-Urban,Software Engineer,96165,0 +26726,Male,54,Masters,7,35,15,23,19,6.0,4,73,Urban,Software Engineer,142549,0 +26727,Male,21,Bachelors,8,18,15,44,52,8.0,0,48,Rural,Data Analyst,142330,0 +26728,Female,34,Diploma,12,47,13,78,98,9.0,5,36,Semi-Urban,Data Analyst,113065,0 +26729,Female,48,Bachelors,11,85,64,16,46,6.0,0,86,Urban,ML Engineer,93661,1 +26730,Other,41,Diploma,6,1,85,92,41,6.0,1,52,Urban,Manager,33659,0 +26731,Male,47,Bachelors,11,10,96,93,89,9.0,7,72,Semi-Urban,Software Engineer,98462,1 +26732,Male,47,Diploma,1,66,58,62,57,1.0,4,83,Semi-Urban,ML Engineer,77915,1 +26733,Male,28,Bachelors,17,86,92,42,65,3.0,2,27,Semi-Urban,HR Executive,69910,1 +26734,Female,33,Diploma,10,40,58,99,89,9.0,7,85,Urban,Software Engineer,117609,1 +26735,Female,57,Bachelors,2,38,93,71,19,3.0,5,10,Urban,ML Engineer,88832,0 +26736,Female,57,Bachelors,3,26,82,94,43,8.0,1,13,Rural,HR Executive,85961,0 +26737,Other,59,PhD,0,77,8,46,52,2.0,1,78,Urban,Data Analyst,94352,0 +26738,Female,44,Masters,9,33,80,25,42,0.0,2,90,Urban,HR Executive,138539,0 +26739,Male,33,Bachelors,10,58,34,37,85,0.0,6,85,Rural,Data Analyst,140476,0 +26740,Female,40,Bachelors,3,17,28,5,63,6.0,4,7,Semi-Urban,HR Executive,64672,0 +26741,Female,34,Masters,8,45,87,5,42,5.0,6,4,Urban,ML Engineer,75621,0 +26742,Male,24,Bachelors,14,27,21,19,7,4.0,3,72,Rural,ML Engineer,50302,0 +26743,Male,35,Diploma,19,57,41,40,30,1.0,7,97,Urban,ML Engineer,88774,1 +26744,Female,45,Bachelors,9,28,90,22,75,9.0,5,65,Semi-Urban,Manager,131430,0 +26745,Male,21,Masters,16,14,27,33,29,0.0,7,41,Urban,Manager,132722,0 +26746,Female,25,Diploma,8,62,49,60,79,2.0,2,51,Urban,ML Engineer,81363,0 +26747,Male,34,Diploma,9,52,27,47,86,3.0,2,58,Urban,HR Executive,148867,0 +26748,Other,57,Diploma,7,70,45,67,31,7.0,4,17,Semi-Urban,HR Executive,77641,0 +26749,Male,35,Bachelors,13,97,7,94,41,6.0,5,37,Urban,ML Engineer,56151,1 +26750,Male,27,Diploma,12,30,62,67,3,1.0,6,10,Rural,ML Engineer,118121,0 +26751,Male,32,Bachelors,8,76,76,45,49,2.0,6,77,Semi-Urban,Manager,36837,1 +26752,Male,23,Masters,18,82,55,25,93,0.0,0,59,Semi-Urban,ML Engineer,92009,0 +26753,Male,40,High School,1,79,75,23,63,3.0,6,50,Urban,HR Executive,125840,0 +26754,Male,31,Masters,7,42,73,30,39,7.0,3,1,Urban,Software Engineer,63468,0 +26755,Female,40,High School,3,41,72,64,69,4.0,3,3,Rural,Data Analyst,103659,0 +26756,Male,50,Diploma,5,9,30,12,63,7.0,4,64,Semi-Urban,Manager,115791,0 +26757,Female,59,Bachelors,12,37,3,46,74,4.0,1,29,Urban,Software Engineer,26534,0 +26758,Female,42,Diploma,12,7,93,1,58,4.0,0,36,Urban,HR Executive,88170,0 +26759,Female,51,Masters,3,84,12,3,63,1.0,6,77,Urban,Manager,72985,0 +26760,Male,51,Masters,14,2,36,35,94,8.0,7,79,Semi-Urban,Manager,20103,0 +26761,Male,57,High School,5,19,73,0,94,6.0,6,4,Semi-Urban,Software Engineer,99512,0 +26762,Male,27,Bachelors,13,99,1,27,39,3.0,0,83,Urban,Data Analyst,97893,0 +26763,Female,45,Diploma,10,46,91,3,67,1.0,3,76,Urban,Data Analyst,80152,0 +26764,Female,54,Bachelors,17,99,63,40,10,6.0,4,26,Urban,HR Executive,104521,0 +26765,Male,32,Bachelors,13,28,79,7,91,6.0,5,31,Urban,Software Engineer,144837,0 +26766,Male,51,Bachelors,8,44,55,1,82,0.0,6,19,Urban,HR Executive,126900,0 +26767,Male,58,Bachelors,12,78,59,78,11,0.0,7,42,Semi-Urban,HR Executive,98794,1 +26768,Male,35,Diploma,2,98,13,99,71,8.0,1,39,Urban,Manager,120534,1 +26769,Male,22,Bachelors,14,70,35,50,68,3.0,1,77,Urban,Data Analyst,52511,0 +26770,Female,52,Masters,12,71,41,59,21,4.0,0,70,Urban,Software Engineer,101103,1 +26771,Male,55,Diploma,15,95,46,43,78,3.0,6,66,Semi-Urban,HR Executive,111825,1 +26772,Female,45,Masters,3,6,79,84,37,5.0,5,91,Urban,HR Executive,41984,1 +26773,Female,42,Bachelors,19,55,39,2,26,2.0,7,30,Urban,Data Analyst,94133,0 +26774,Female,33,Bachelors,10,62,63,41,18,0.0,0,1,Urban,Manager,64548,0 +26775,Male,32,Bachelors,9,75,22,66,14,6.0,5,74,Urban,Manager,50681,1 +26776,Male,31,Diploma,14,55,27,74,18,3.0,3,87,Urban,ML Engineer,36411,1 +26777,Male,42,Bachelors,4,30,11,30,77,3.0,6,50,Urban,Software Engineer,119956,0 +26778,Female,54,Masters,7,22,4,53,67,2.0,4,98,Urban,Data Analyst,74099,0 +26779,Male,43,Diploma,16,57,25,13,14,1.0,0,51,Urban,Software Engineer,33058,0 +26780,Male,23,Bachelors,4,77,61,11,95,3.0,2,89,Urban,Manager,62266,1 +26781,Male,36,Bachelors,19,12,30,10,36,5.0,5,29,Urban,Data Analyst,51592,0 +26782,Male,23,Masters,3,77,33,98,87,2.0,7,93,Urban,HR Executive,125030,1 +26783,Female,38,Bachelors,2,90,68,48,29,4.0,2,25,Urban,HR Executive,105659,0 +26784,Male,25,Bachelors,14,26,91,88,78,7.0,5,30,Semi-Urban,ML Engineer,63994,1 +26785,Male,48,Bachelors,3,0,86,87,79,5.0,1,78,Urban,HR Executive,59120,1 +26786,Male,54,Bachelors,17,23,40,69,17,2.0,2,40,Urban,HR Executive,72985,0 +26787,Male,56,Masters,12,96,1,52,37,1.0,1,57,Urban,Software Engineer,147936,0 +26788,Female,38,Diploma,2,56,24,93,56,1.0,3,75,Urban,ML Engineer,33124,1 +26789,Male,48,Diploma,7,89,47,7,99,8.0,2,1,Urban,HR Executive,143488,0 +26790,Male,23,Bachelors,1,6,46,41,7,0.0,1,97,Urban,Data Analyst,26655,0 +26791,Female,32,Bachelors,3,87,71,28,28,4.0,1,57,Urban,Data Analyst,138847,1 +26792,Female,55,Masters,11,7,12,81,83,7.0,7,86,Urban,Manager,92488,0 +26793,Male,35,Bachelors,13,54,95,52,12,0.0,7,37,Urban,ML Engineer,141431,1 +26794,Male,50,Diploma,9,0,47,80,30,3.0,3,36,Urban,Software Engineer,122360,0 +26795,Male,54,Diploma,0,99,26,1,65,0.0,3,59,Urban,Software Engineer,33869,0 +26796,Male,36,Masters,3,72,76,52,57,9.0,6,46,Semi-Urban,Software Engineer,35587,1 +26797,Male,55,Bachelors,1,14,1,66,71,7.0,2,18,Urban,ML Engineer,78613,0 +26798,Male,46,Bachelors,11,42,12,86,60,7.0,3,69,Urban,Software Engineer,57830,0 +26799,Other,24,Bachelors,10,12,2,28,9,0.0,3,47,Rural,Data Analyst,50537,0 +26800,Male,23,Diploma,16,61,22,77,9,5.0,3,38,Semi-Urban,Data Analyst,119503,0 +26801,Female,49,Bachelors,1,77,33,9,90,1.0,0,91,Rural,Data Analyst,22549,0 +26802,Female,55,Diploma,16,75,59,50,94,5.0,2,48,Urban,Software Engineer,123879,0 +26803,Other,45,Bachelors,16,36,25,23,52,2.0,4,97,Urban,Manager,113838,0 +26804,Male,38,Bachelors,3,15,7,74,89,4.0,3,82,Rural,HR Executive,31576,0 +26805,Female,36,High School,6,5,52,70,42,1.0,1,20,Urban,Software Engineer,45710,0 +26806,Other,46,Masters,9,24,13,49,64,4.0,3,96,Semi-Urban,ML Engineer,40501,0 +26807,Male,29,Bachelors,14,32,37,46,34,3.0,6,76,Urban,Data Analyst,65348,0 +26808,Male,39,Diploma,2,82,28,5,56,6.0,3,84,Semi-Urban,Data Analyst,135255,0 +26809,Male,29,Bachelors,14,45,88,10,50,9.0,6,4,Urban,Manager,24379,0 +26810,Female,35,Masters,2,23,48,23,10,8.0,5,25,Urban,ML Engineer,32642,0 +26811,Male,57,Bachelors,18,99,37,98,49,5.0,5,1,Urban,Data Analyst,122163,1 +26812,Male,22,Diploma,10,69,51,90,87,6.0,4,23,Urban,Software Engineer,50158,0 +26813,Female,51,Bachelors,15,74,27,68,60,3.0,0,59,Urban,Manager,52896,0 +26814,Male,37,Bachelors,14,73,73,75,82,7.0,6,0,Rural,ML Engineer,23499,0 +26815,Female,31,Bachelors,2,8,23,28,19,1.0,1,86,Urban,Data Analyst,112378,0 +26816,Male,25,Bachelors,19,45,4,62,8,1.0,4,50,Semi-Urban,Manager,138477,0 +26817,Female,59,High School,9,16,24,11,56,8.0,1,16,Semi-Urban,Software Engineer,54598,0 +26818,Male,38,PhD,3,76,17,52,67,7.0,4,46,Urban,Data Analyst,140156,0 +26819,Male,54,Bachelors,3,66,81,19,17,9.0,1,83,Semi-Urban,Software Engineer,74661,1 +26820,Female,37,Diploma,7,52,97,92,90,1.0,7,89,Semi-Urban,Manager,128512,1 +26821,Male,56,Diploma,3,89,12,57,40,2.0,1,32,Urban,Software Engineer,139030,0 +26822,Male,39,Bachelors,0,48,52,38,77,0.0,4,15,Semi-Urban,Data Analyst,21661,0 +26823,Female,59,Bachelors,6,22,55,35,49,0.0,3,88,Semi-Urban,Software Engineer,148245,0 +26824,Male,58,Diploma,2,51,6,66,56,3.0,3,41,Urban,Data Analyst,28541,0 +26825,Female,26,Bachelors,0,9,45,28,13,6.0,2,3,Urban,Software Engineer,139240,0 +26826,Male,44,Diploma,19,13,20,56,8,3.0,1,58,Rural,ML Engineer,115780,0 +26827,Male,59,PhD,8,0,94,94,57,8.0,5,45,Semi-Urban,HR Executive,104185,0 +26828,Male,53,Bachelors,5,96,26,92,68,9.0,5,56,Urban,Data Analyst,65922,1 +26829,Other,34,Bachelors,3,3,43,1,13,0.0,7,69,Rural,HR Executive,73561,0 +26830,Male,24,Masters,16,83,28,16,44,1.0,1,15,Rural,ML Engineer,45155,0 +26831,Female,41,Bachelors,19,26,50,34,90,3.0,2,35,Urban,ML Engineer,53258,0 +26832,Other,34,Bachelors,17,79,66,21,14,1.0,3,43,Urban,Software Engineer,60913,0 +26833,Male,43,Bachelors,19,33,70,88,45,0.0,1,78,Urban,Software Engineer,58488,1 +26834,Female,37,Diploma,13,71,68,51,23,6.0,0,24,Urban,HR Executive,81774,0 +26835,Female,56,Bachelors,18,26,36,84,72,9.0,0,8,Urban,ML Engineer,51309,0 +26836,Male,33,Masters,17,28,67,34,46,0.0,2,68,Semi-Urban,Manager,67710,0 +26837,Male,38,Bachelors,10,84,71,98,46,0.0,0,99,Urban,HR Executive,62103,1 +26838,Male,26,Bachelors,6,29,54,59,37,9.0,5,84,Rural,Manager,145993,0 +26839,Female,54,High School,0,28,13,46,85,3.0,0,47,Urban,Manager,140466,0 +26840,Female,36,Bachelors,14,85,62,41,0,8.0,7,92,Semi-Urban,Software Engineer,57912,1 +26841,Male,30,Bachelors,13,93,92,44,79,5.0,2,48,Urban,Software Engineer,60282,1 +26842,Male,55,High School,12,72,58,2,11,1.0,4,19,Urban,Software Engineer,29243,0 +26843,Female,39,PhD,19,43,57,62,41,8.0,2,90,Urban,ML Engineer,126695,1 +26844,Male,41,Masters,14,41,18,44,53,5.0,4,99,Rural,Software Engineer,66421,0 +26845,Female,47,Bachelors,16,40,72,79,71,3.0,4,21,Semi-Urban,HR Executive,79380,0 +26846,Male,59,Bachelors,16,34,7,45,15,2.0,1,9,Semi-Urban,ML Engineer,62191,0 +26847,Female,59,Bachelors,19,25,88,12,41,8.0,2,26,Semi-Urban,ML Engineer,102893,0 +26848,Female,48,Diploma,6,36,99,34,4,6.0,2,96,Urban,HR Executive,65612,1 +26849,Male,43,Bachelors,16,33,9,81,55,4.0,2,30,Semi-Urban,ML Engineer,142254,0 +26850,Male,29,Diploma,7,18,47,49,24,0.0,4,95,Urban,HR Executive,38789,0 +26851,Male,47,Masters,5,54,20,91,58,9.0,7,78,Rural,HR Executive,117533,1 +26852,Male,25,Bachelors,16,27,85,20,88,7.0,3,57,Urban,ML Engineer,104665,0 +26853,Male,52,Diploma,10,47,43,4,70,2.0,0,21,Urban,Software Engineer,124478,0 +26854,Female,49,Bachelors,4,99,25,7,67,1.0,5,67,Urban,Software Engineer,92901,0 +26855,Male,57,Bachelors,11,71,95,58,48,6.0,5,48,Rural,Manager,91362,1 +26856,Male,22,Diploma,19,85,8,59,9,5.0,4,21,Rural,HR Executive,123765,0 +26857,Female,40,Bachelors,10,10,41,30,95,5.0,5,45,Rural,HR Executive,137677,0 +26858,Female,44,Masters,17,27,59,36,93,1.0,2,2,Urban,HR Executive,25159,0 +26859,Male,50,High School,5,78,90,28,45,0.0,4,20,Rural,Manager,144018,0 +26860,Female,26,Masters,14,85,89,32,14,3.0,5,17,Urban,Software Engineer,93272,0 +26861,Female,23,PhD,18,26,35,89,52,1.0,3,45,Semi-Urban,HR Executive,42807,0 +26862,Male,49,High School,0,2,28,1,27,8.0,6,50,Urban,HR Executive,37836,0 +26863,Male,55,PhD,9,49,97,86,33,2.0,2,68,Urban,Software Engineer,92227,1 +26864,Male,21,Bachelors,2,10,43,30,89,9.0,3,21,Urban,Manager,50531,0 +26865,Female,49,Masters,4,26,80,50,69,6.0,4,17,Urban,Manager,64512,0 +26866,Female,38,Bachelors,2,42,73,43,95,6.0,1,65,Urban,Manager,141772,0 +26867,Female,26,Bachelors,5,63,20,94,94,3.0,1,30,Urban,ML Engineer,65853,0 +26868,Male,49,PhD,17,5,38,21,28,1.0,5,90,Urban,Data Analyst,138834,0 +26869,Male,42,Diploma,17,82,17,86,46,7.0,5,78,Urban,Data Analyst,83033,1 +26870,Female,56,Bachelors,7,89,61,83,84,5.0,1,44,Urban,Manager,72199,1 +26871,Male,52,Masters,12,77,46,66,4,3.0,7,90,Semi-Urban,Software Engineer,137256,1 +26872,Male,52,Bachelors,2,17,84,56,87,1.0,5,86,Rural,HR Executive,32719,1 +26873,Male,21,High School,8,74,39,47,97,1.0,6,50,Urban,Data Analyst,81185,0 +26874,Female,58,Diploma,18,95,95,18,72,9.0,7,51,Rural,Data Analyst,114868,1 +26875,Male,24,High School,13,54,96,2,43,5.0,0,82,Semi-Urban,HR Executive,95336,0 +26876,Male,31,High School,16,86,24,83,44,9.0,2,51,Urban,ML Engineer,48248,1 +26877,Female,39,Bachelors,16,49,9,40,10,1.0,6,8,Rural,Software Engineer,54501,0 +26878,Female,26,Diploma,17,20,76,6,89,6.0,2,37,Semi-Urban,Manager,26478,0 +26879,Female,47,Masters,2,2,15,84,75,0.0,7,26,Urban,ML Engineer,60415,0 +26880,Female,44,Bachelors,4,89,23,24,94,5.0,2,20,Urban,ML Engineer,149518,0 +26881,Male,35,Diploma,11,24,28,14,54,1.0,1,73,Semi-Urban,Manager,144816,0 +26882,Male,58,PhD,3,70,55,90,79,4.0,7,41,Rural,ML Engineer,125952,1 +26883,Female,21,Bachelors,6,23,97,21,13,4.0,1,84,Urban,Manager,103898,0 +26884,Male,34,Bachelors,13,77,19,43,60,8.0,2,98,Rural,ML Engineer,44650,1 +26885,Female,21,Masters,17,75,16,94,85,0.0,3,96,Rural,Manager,39590,1 +26886,Female,28,Diploma,13,80,82,54,92,0.0,3,46,Urban,Software Engineer,78508,1 +26887,Male,43,High School,3,56,51,27,8,2.0,6,58,Urban,ML Engineer,130778,0 +26888,Male,51,Masters,5,31,90,11,53,0.0,7,74,Rural,Software Engineer,127041,0 +26889,Male,42,Bachelors,0,19,96,0,37,5.0,3,99,Semi-Urban,Software Engineer,26254,0 +26890,Male,45,Masters,11,17,96,17,78,8.0,5,24,Urban,Software Engineer,65347,0 +26891,Male,47,Masters,4,74,51,72,48,2.0,3,34,Urban,Manager,37923,0 +26892,Female,24,Bachelors,15,58,45,10,69,0.0,7,57,Urban,Software Engineer,123407,0 +26893,Male,21,Bachelors,4,35,51,9,70,4.0,5,87,Urban,Manager,117657,0 +26894,Female,57,Bachelors,4,81,22,20,84,0.0,1,36,Rural,Manager,140003,0 +26895,Male,41,Bachelors,5,71,4,48,61,7.0,2,23,Urban,Software Engineer,94300,0 +26896,Male,40,Masters,15,55,9,70,19,9.0,7,10,Rural,ML Engineer,119846,0 +26897,Male,36,PhD,14,99,76,74,1,8.0,1,97,Urban,Software Engineer,64864,1 +26898,Female,21,Bachelors,10,16,73,91,66,2.0,3,64,Urban,HR Executive,71955,1 +26899,Male,39,High School,3,6,63,85,35,2.0,3,8,Urban,HR Executive,38738,0 +26900,Male,59,Masters,6,63,62,22,72,8.0,6,95,Semi-Urban,Data Analyst,99176,1 +26901,Female,42,Masters,13,90,71,83,33,9.0,7,30,Urban,HR Executive,141745,1 +26902,Male,32,Diploma,8,13,81,28,87,3.0,3,14,Rural,ML Engineer,123378,0 +26903,Male,40,PhD,1,92,11,95,93,6.0,3,96,Semi-Urban,Manager,114526,1 +26904,Male,41,Masters,1,43,23,35,93,9.0,5,70,Semi-Urban,Manager,27926,0 +26905,Male,44,Diploma,4,83,31,23,61,1.0,0,57,Urban,Software Engineer,139049,0 +26906,Male,37,Masters,17,28,62,17,83,9.0,2,92,Urban,ML Engineer,105649,0 +26907,Male,52,Bachelors,7,10,60,90,12,5.0,1,47,Urban,Software Engineer,80236,0 +26908,Male,24,Diploma,14,21,63,20,43,1.0,5,21,Rural,Manager,119528,0 +26909,Female,26,Bachelors,5,57,85,31,13,9.0,0,37,Rural,Data Analyst,117074,0 +26910,Female,43,Bachelors,7,98,39,39,14,7.0,7,15,Urban,HR Executive,116766,0 +26911,Female,50,Masters,6,99,72,67,95,0.0,1,58,Semi-Urban,HR Executive,134528,1 +26912,Female,26,Diploma,8,88,29,99,69,2.0,1,83,Urban,HR Executive,88591,1 +26913,Male,49,Bachelors,7,97,59,3,37,6.0,6,29,Semi-Urban,Software Engineer,143270,0 +26914,Female,33,Masters,14,12,20,89,78,0.0,7,22,Rural,Manager,44890,0 +26915,Male,37,Bachelors,19,29,33,72,6,3.0,3,67,Urban,HR Executive,42586,0 +26916,Female,47,High School,2,65,40,4,90,3.0,6,40,Urban,Manager,40213,0 +26917,Male,41,Bachelors,9,44,52,10,32,2.0,6,82,Semi-Urban,HR Executive,123602,0 +26918,Male,37,Masters,17,56,80,76,10,4.0,5,70,Urban,Manager,94968,1 +26919,Female,52,Diploma,8,50,80,2,10,4.0,1,14,Urban,Manager,54272,0 +26920,Female,56,Diploma,12,49,42,94,68,2.0,1,9,Rural,HR Executive,138839,0 +26921,Female,48,PhD,1,18,2,42,26,5.0,6,6,Semi-Urban,Manager,26495,0 +26922,Male,42,Bachelors,19,68,69,43,24,9.0,3,60,Semi-Urban,Data Analyst,29028,1 +26923,Male,31,Diploma,15,68,96,49,46,1.0,2,23,Urban,Data Analyst,121329,1 +26924,Male,46,Masters,19,16,84,22,12,9.0,3,31,Semi-Urban,HR Executive,86854,0 +26925,Male,52,High School,16,29,80,20,19,1.0,0,70,Urban,Software Engineer,44708,0 +26926,Male,40,PhD,7,44,44,79,31,6.0,0,0,Urban,Data Analyst,65829,0 +26927,Male,44,Masters,15,40,28,74,32,7.0,5,6,Semi-Urban,ML Engineer,148857,0 +26928,Male,47,PhD,12,41,78,93,61,6.0,6,33,Semi-Urban,HR Executive,137849,1 +26929,Male,45,Diploma,3,24,43,81,86,8.0,4,94,Urban,Manager,83764,1 +26930,Female,50,Masters,1,72,37,46,39,7.0,3,24,Urban,Data Analyst,125773,0 +26931,Female,47,Diploma,19,46,12,52,80,0.0,3,10,Urban,HR Executive,64055,0 +26932,Male,24,Masters,13,12,46,25,46,1.0,2,77,Semi-Urban,Data Analyst,35361,0 +26933,Male,48,Diploma,14,10,95,12,27,5.0,7,2,Rural,Software Engineer,98272,0 +26934,Male,27,Diploma,4,57,80,28,21,7.0,5,39,Semi-Urban,Manager,76862,0 +26935,Male,33,Bachelors,15,8,68,77,87,0.0,6,49,Urban,Data Analyst,120316,0 +26936,Female,44,Bachelors,17,48,15,51,64,3.0,5,87,Urban,HR Executive,117326,0 +26937,Female,39,Bachelors,10,61,26,45,65,9.0,5,35,Urban,Data Analyst,33649,0 +26938,Female,28,Masters,19,31,11,93,86,8.0,3,79,Urban,HR Executive,145844,0 +26939,Male,56,Bachelors,8,3,7,86,78,3.0,4,43,Semi-Urban,Data Analyst,141093,0 +26940,Female,50,High School,19,64,76,74,62,1.0,4,93,Urban,Software Engineer,91711,1 +26941,Male,21,High School,7,41,28,19,2,5.0,7,15,Semi-Urban,HR Executive,79921,0 +26942,Male,49,High School,5,86,95,93,21,2.0,4,60,Urban,Software Engineer,55252,1 +26943,Male,30,Masters,16,60,54,38,68,9.0,4,47,Urban,Software Engineer,119486,0 +26944,Female,27,Bachelors,13,53,75,68,66,2.0,7,28,Urban,Data Analyst,53578,0 +26945,Male,34,Masters,19,7,79,23,10,6.0,2,70,Urban,ML Engineer,119468,0 +26946,Male,43,High School,15,43,23,41,58,2.0,7,80,Rural,ML Engineer,106940,0 +26947,Female,52,Bachelors,4,55,33,34,14,4.0,3,0,Urban,Software Engineer,88686,0 +26948,Male,56,Bachelors,2,67,92,58,89,2.0,2,58,Rural,Data Analyst,75237,1 +26949,Male,47,High School,7,85,69,91,51,7.0,2,90,Rural,Data Analyst,101638,1 +26950,Male,36,PhD,0,57,99,70,9,6.0,5,84,Semi-Urban,ML Engineer,103868,1 +26951,Male,52,Bachelors,8,13,42,11,83,2.0,3,69,Semi-Urban,ML Engineer,59293,0 +26952,Female,35,Masters,14,18,96,86,86,1.0,2,70,Semi-Urban,Manager,104227,1 +26953,Male,36,Masters,13,72,66,8,83,8.0,2,83,Urban,HR Executive,32224,0 +26954,Male,34,Bachelors,6,58,64,57,61,1.0,5,83,Rural,HR Executive,58344,1 +26955,Male,23,Diploma,17,84,41,34,24,8.0,4,86,Urban,Software Engineer,35397,1 +26956,Female,53,High School,6,68,81,74,11,0.0,4,71,Semi-Urban,ML Engineer,85325,1 +26957,Male,46,Masters,10,5,69,40,6,6.0,1,58,Semi-Urban,Software Engineer,35208,0 +26958,Female,57,Bachelors,15,59,93,48,83,5.0,6,27,Urban,Manager,56831,0 +26959,Male,40,High School,9,42,86,97,10,7.0,1,57,Urban,ML Engineer,22987,1 +26960,Male,53,Masters,4,65,84,40,53,5.0,2,92,Urban,Manager,77637,1 +26961,Other,46,PhD,12,16,56,76,0,1.0,5,17,Urban,Manager,66885,0 +26962,Male,32,Bachelors,4,26,35,86,69,4.0,6,53,Urban,Data Analyst,88644,0 +26963,Male,33,Bachelors,17,48,39,5,51,7.0,3,51,Rural,Software Engineer,46304,0 +26964,Male,27,High School,6,13,28,27,71,3.0,0,63,Urban,Data Analyst,149055,0 +26965,Male,26,High School,4,40,99,60,30,7.0,5,37,Urban,Data Analyst,119218,1 +26966,Male,42,Diploma,14,76,58,44,24,2.0,2,68,Urban,HR Executive,93903,1 +26967,Female,25,Masters,1,2,26,30,18,3.0,4,31,Urban,ML Engineer,59551,0 +26968,Female,23,Bachelors,12,0,52,50,62,7.0,5,56,Semi-Urban,HR Executive,102869,0 +26969,Male,46,Diploma,4,24,5,50,96,5.0,7,82,Urban,Software Engineer,147894,0 +26970,Male,30,PhD,4,39,25,63,52,9.0,2,34,Urban,Software Engineer,98777,0 +26971,Female,48,Bachelors,7,52,90,96,8,5.0,7,6,Semi-Urban,HR Executive,139972,1 +26972,Male,51,Diploma,1,62,73,59,83,4.0,3,73,Urban,Manager,89019,1 +26973,Male,48,High School,8,45,89,69,36,1.0,0,38,Semi-Urban,HR Executive,109256,1 +26974,Female,39,Diploma,4,88,94,48,7,5.0,0,57,Semi-Urban,Data Analyst,64875,1 +26975,Female,32,Bachelors,6,25,29,28,90,8.0,4,72,Urban,Software Engineer,80331,0 +26976,Female,46,Masters,3,80,15,16,65,0.0,4,38,Rural,ML Engineer,92372,0 +26977,Female,54,High School,6,0,27,21,69,8.0,7,93,Urban,HR Executive,127595,0 +26978,Other,31,High School,17,60,33,83,68,4.0,1,28,Semi-Urban,Manager,110104,0 +26979,Male,48,Bachelors,3,2,63,96,68,0.0,3,86,Urban,Data Analyst,101143,1 +26980,Female,56,Bachelors,15,68,79,6,56,6.0,4,19,Urban,Manager,82296,0 +26981,Male,51,Masters,10,67,71,12,69,0.0,3,18,Semi-Urban,Software Engineer,136139,0 +26982,Male,59,Diploma,6,19,27,80,54,7.0,6,21,Urban,ML Engineer,21846,0 +26983,Male,27,Bachelors,6,35,16,77,7,7.0,1,13,Urban,HR Executive,70476,0 +26984,Female,32,Bachelors,5,47,76,83,64,1.0,1,66,Urban,ML Engineer,108577,1 +26985,Male,59,Bachelors,3,38,42,26,2,1.0,4,9,Rural,Data Analyst,107009,0 +26986,Female,27,Masters,6,5,33,64,82,3.0,3,99,Urban,HR Executive,67764,0 +26987,Female,42,Bachelors,18,82,2,65,53,3.0,7,14,Rural,HR Executive,124326,0 +26988,Male,32,Diploma,12,4,31,70,99,8.0,5,62,Urban,Data Analyst,24986,0 +26989,Female,46,High School,6,72,55,37,26,7.0,0,83,Semi-Urban,HR Executive,37874,1 +26990,Female,39,Bachelors,8,30,8,84,44,8.0,0,57,Urban,ML Engineer,125892,0 +26991,Female,43,High School,19,48,82,74,9,3.0,6,48,Semi-Urban,Software Engineer,43229,1 +26992,Male,35,Bachelors,3,28,71,49,12,7.0,2,69,Urban,HR Executive,111632,0 +26993,Female,29,Masters,12,77,44,42,73,1.0,7,75,Urban,HR Executive,23865,0 +26994,Female,54,High School,2,73,0,95,27,6.0,0,2,Semi-Urban,Data Analyst,128605,0 +26995,Male,29,Masters,2,51,23,95,47,1.0,4,34,Rural,Software Engineer,118211,0 +26996,Male,48,Bachelors,14,46,31,71,7,6.0,0,63,Rural,ML Engineer,65394,0 +26997,Male,52,Diploma,13,88,49,73,82,4.0,2,16,Urban,Manager,137141,0 +26998,Female,32,High School,16,66,59,59,45,4.0,2,38,Rural,HR Executive,39030,0 +26999,Male,25,Bachelors,3,89,24,62,90,9.0,4,97,Semi-Urban,HR Executive,117184,1 +27000,Male,33,Masters,11,9,93,72,58,5.0,7,52,Urban,Data Analyst,115769,0 +27001,Female,52,Bachelors,17,35,4,52,82,0.0,7,2,Urban,HR Executive,108465,0 +27002,Male,43,Bachelors,14,93,83,4,80,8.0,2,6,Rural,ML Engineer,128271,0 +27003,Female,26,Masters,15,16,95,83,66,5.0,7,7,Rural,Manager,112651,0 +27004,Male,32,Masters,12,38,22,60,9,8.0,1,87,Urban,Software Engineer,28712,0 +27005,Male,29,Bachelors,1,32,85,93,73,2.0,7,20,Semi-Urban,Data Analyst,92985,0 +27006,Male,53,Diploma,9,65,1,64,73,9.0,0,20,Urban,Software Engineer,51797,0 +27007,Female,56,Diploma,17,63,68,22,98,9.0,4,87,Rural,Data Analyst,115756,0 +27008,Female,50,Bachelors,2,25,94,92,19,6.0,4,20,Urban,Data Analyst,130933,0 +27009,Female,54,Masters,18,47,36,26,95,8.0,6,23,Urban,HR Executive,81451,0 +27010,Female,49,High School,9,44,94,24,59,0.0,1,10,Urban,ML Engineer,142122,0 +27011,Male,57,Diploma,16,14,83,5,55,7.0,0,41,Semi-Urban,ML Engineer,43470,0 +27012,Male,22,Masters,17,55,49,9,34,6.0,5,87,Urban,Manager,73124,0 +27013,Male,47,Bachelors,16,59,50,60,8,6.0,6,22,Urban,Manager,106246,0 +27014,Female,49,Masters,9,57,89,39,43,3.0,6,61,Urban,HR Executive,78029,1 +27015,Female,50,Masters,1,91,0,73,14,2.0,1,40,Urban,ML Engineer,39332,0 +27016,Male,45,Diploma,14,8,82,90,6,6.0,0,98,Urban,Manager,35024,1 +27017,Female,27,PhD,9,77,60,85,59,9.0,7,30,Urban,Data Analyst,138056,1 +27018,Other,46,Bachelors,4,27,43,78,46,3.0,0,62,Urban,Manager,62824,0 +27019,Male,47,Bachelors,2,83,8,25,48,8.0,7,9,Urban,Manager,124412,0 +27020,Female,49,Bachelors,15,22,99,12,98,5.0,1,23,Urban,ML Engineer,21036,0 +27021,Male,45,Masters,16,23,56,45,39,5.0,0,1,Urban,ML Engineer,101896,0 +27022,Female,34,High School,3,56,60,63,57,4.0,7,69,Urban,Manager,33355,1 +27023,Male,55,High School,8,45,54,31,95,6.0,2,33,Rural,ML Engineer,135512,0 +27024,Male,32,Masters,2,31,27,60,70,9.0,3,42,Rural,Manager,115911,0 +27025,Male,47,Bachelors,2,80,68,67,20,4.0,3,19,Urban,Software Engineer,90084,0 +27026,Other,28,Bachelors,14,90,67,59,82,9.0,4,13,Urban,ML Engineer,32920,0 +27027,Female,59,Diploma,3,3,7,41,56,1.0,2,76,Semi-Urban,HR Executive,23495,0 +27028,Male,40,Bachelors,11,88,82,95,38,3.0,2,42,Semi-Urban,HR Executive,100817,1 +27029,Other,47,Bachelors,19,35,6,54,44,8.0,6,12,Urban,ML Engineer,97521,0 +27030,Female,21,Bachelors,6,78,96,53,39,6.0,0,63,Urban,Manager,131291,1 +27031,Female,54,Bachelors,9,97,87,9,30,1.0,3,58,Rural,HR Executive,142819,1 +27032,Male,47,PhD,15,38,68,15,2,8.0,5,20,Urban,ML Engineer,75968,0 +27033,Male,31,Masters,15,17,89,16,34,5.0,6,27,Rural,HR Executive,50159,0 +27034,Female,58,High School,18,81,54,80,12,0.0,3,73,Urban,Software Engineer,134184,1 +27035,Male,30,High School,0,47,27,27,92,3.0,1,19,Urban,Manager,121180,0 +27036,Male,23,Bachelors,14,98,46,46,9,6.0,3,13,Semi-Urban,ML Engineer,52166,0 +27037,Male,49,Diploma,3,48,84,45,1,9.0,1,47,Semi-Urban,HR Executive,136115,0 +27038,Male,57,Diploma,2,69,31,39,61,0.0,2,24,Urban,Manager,73800,0 +27039,Male,52,Diploma,8,29,28,33,18,8.0,5,91,Semi-Urban,HR Executive,57890,0 +27040,Other,31,High School,7,48,73,35,58,3.0,0,51,Rural,HR Executive,90552,0 +27041,Male,26,Masters,15,77,53,43,84,7.0,0,81,Urban,HR Executive,141037,1 +27042,Male,24,Bachelors,14,42,64,30,91,7.0,3,18,Rural,HR Executive,96412,0 +27043,Male,26,PhD,0,33,46,20,65,6.0,7,16,Urban,Software Engineer,103812,0 +27044,Female,51,PhD,18,50,51,17,14,7.0,7,16,Rural,Manager,70382,0 +27045,Female,32,Bachelors,8,3,28,99,72,0.0,2,6,Semi-Urban,ML Engineer,55663,0 +27046,Female,32,Diploma,7,4,42,28,25,0.0,1,35,Semi-Urban,Manager,148618,0 +27047,Male,23,Diploma,11,68,85,6,93,5.0,5,16,Urban,Data Analyst,128612,0 +27048,Male,29,Bachelors,0,58,49,26,16,4.0,7,49,Semi-Urban,Data Analyst,85196,0 +27049,Female,27,Masters,8,65,46,27,91,1.0,1,60,Semi-Urban,HR Executive,23382,0 +27050,Female,24,Masters,1,68,63,18,28,3.0,1,30,Semi-Urban,Software Engineer,149041,0 +27051,Female,47,Diploma,3,94,70,58,6,0.0,3,38,Urban,ML Engineer,21887,1 +27052,Male,39,Bachelors,0,73,89,63,32,2.0,7,82,Urban,Software Engineer,66325,1 +27053,Male,59,Masters,12,68,58,3,77,3.0,7,76,Urban,Manager,24581,0 +27054,Male,44,Masters,9,65,25,32,83,3.0,3,76,Rural,Manager,113677,0 +27055,Female,45,PhD,3,59,78,76,61,3.0,5,8,Urban,Software Engineer,21132,0 +27056,Male,43,Masters,4,96,18,47,26,6.0,0,41,Semi-Urban,Software Engineer,137399,0 +27057,Male,39,Diploma,12,67,25,59,53,1.0,0,84,Rural,ML Engineer,133373,1 +27058,Male,37,Bachelors,0,11,97,88,3,5.0,2,92,Rural,Data Analyst,97713,1 +27059,Male,45,Diploma,14,97,66,85,2,5.0,3,1,Semi-Urban,HR Executive,88960,1 +27060,Male,25,Bachelors,12,16,50,5,70,7.0,3,54,Urban,Software Engineer,94842,0 +27061,Male,33,Diploma,13,9,12,26,95,6.0,0,6,Urban,Manager,57023,0 +27062,Female,30,Masters,15,91,56,87,31,1.0,0,53,Urban,HR Executive,35752,1 +27063,Male,58,Diploma,18,12,5,39,33,1.0,1,23,Urban,ML Engineer,33173,0 +27064,Male,33,Masters,15,38,1,58,88,0.0,1,55,Semi-Urban,Software Engineer,113083,0 +27065,Male,37,Bachelors,6,78,83,28,68,7.0,2,2,Semi-Urban,Manager,116352,0 +27066,Male,58,High School,15,13,55,9,34,3.0,7,22,Semi-Urban,Manager,127490,0 +27067,Female,37,PhD,18,65,53,11,90,4.0,1,10,Semi-Urban,HR Executive,135537,0 +27068,Male,30,Masters,6,9,19,31,31,5.0,5,7,Urban,Manager,108783,0 +27069,Female,24,Bachelors,4,13,99,96,70,7.0,5,7,Rural,Manager,42573,0 +27070,Male,44,Bachelors,2,13,43,59,78,3.0,2,89,Urban,Software Engineer,35075,0 +27071,Female,21,Diploma,19,44,17,48,36,0.0,6,99,Urban,Data Analyst,91501,0 +27072,Male,22,Diploma,3,23,89,72,2,4.0,0,5,Urban,HR Executive,58667,0 +27073,Male,53,High School,3,94,78,19,30,5.0,0,84,Urban,Data Analyst,51303,1 +27074,Female,26,Diploma,8,66,9,32,9,2.0,5,10,Rural,Manager,48886,0 +27075,Male,53,Masters,11,1,81,24,76,1.0,0,98,Urban,Manager,44936,0 +27076,Male,34,Bachelors,1,96,18,63,84,5.0,5,45,Urban,Software Engineer,125869,0 +27077,Female,57,Diploma,12,56,82,14,69,7.0,4,94,Semi-Urban,Software Engineer,67607,1 +27078,Male,47,Bachelors,0,73,59,23,77,6.0,1,39,Urban,HR Executive,81210,0 +27079,Male,25,Bachelors,3,26,15,0,43,0.0,6,27,Urban,Manager,94133,0 +27080,Male,21,Masters,3,65,43,82,31,6.0,5,68,Urban,Data Analyst,125470,1 +27081,Other,41,Bachelors,16,88,27,51,98,4.0,6,86,Rural,Data Analyst,89655,1 +27082,Female,32,PhD,6,66,70,93,33,4.0,2,53,Semi-Urban,HR Executive,74136,1 +27083,Male,22,Bachelors,8,80,0,4,28,1.0,4,79,Urban,Manager,113266,0 +27084,Male,27,Masters,8,28,0,32,47,1.0,4,51,Semi-Urban,HR Executive,82297,0 +27085,Male,53,Masters,19,86,96,34,48,1.0,7,42,Rural,Software Engineer,101845,1 +27086,Male,55,Bachelors,9,6,36,39,13,4.0,2,88,Urban,Data Analyst,138042,0 +27087,Female,30,Masters,18,14,88,38,26,8.0,0,78,Urban,ML Engineer,20971,0 +27088,Male,38,Bachelors,11,9,58,79,0,6.0,3,95,Semi-Urban,ML Engineer,98617,1 +27089,Male,55,Diploma,18,5,15,45,67,3.0,6,40,Urban,HR Executive,147139,0 +27090,Female,59,Masters,14,51,23,43,95,4.0,7,59,Rural,HR Executive,30574,0 +27091,Female,59,PhD,0,57,12,90,87,0.0,5,64,Urban,HR Executive,21073,0 +27092,Female,24,Diploma,12,47,3,26,83,9.0,7,46,Urban,ML Engineer,123224,0 +27093,Female,39,High School,11,20,97,36,32,5.0,5,83,Urban,HR Executive,41754,0 +27094,Female,39,Bachelors,9,64,70,94,5,1.0,5,75,Urban,Software Engineer,40334,1 +27095,Male,22,Masters,3,60,90,65,27,3.0,2,34,Rural,ML Engineer,75772,1 +27096,Male,59,Masters,5,4,80,63,15,1.0,6,48,Rural,ML Engineer,140345,0 +27097,Male,30,Masters,3,54,91,10,86,4.0,4,27,Urban,HR Executive,119890,0 +27098,Male,37,High School,17,41,96,62,30,6.0,6,58,Semi-Urban,HR Executive,98288,1 +27099,Female,37,High School,6,61,6,13,74,3.0,4,41,Urban,Software Engineer,147499,0 +27100,Male,33,Bachelors,12,83,45,74,11,9.0,7,88,Urban,ML Engineer,21073,1 +27101,Male,46,High School,1,36,68,37,84,6.0,4,53,Semi-Urban,HR Executive,110344,0 +27102,Male,51,Masters,15,75,50,98,13,0.0,1,10,Semi-Urban,Software Engineer,137457,0 +27103,Male,50,Diploma,1,60,88,1,91,6.0,1,78,Urban,ML Engineer,74565,0 +27104,Female,50,Diploma,17,63,49,66,14,4.0,0,13,Semi-Urban,Manager,101897,0 +27105,Female,35,High School,6,99,22,56,11,6.0,2,79,Urban,Software Engineer,134864,1 +27106,Male,55,Masters,18,35,32,20,62,6.0,0,36,Urban,HR Executive,131916,0 +27107,Male,50,Bachelors,19,61,11,35,72,7.0,6,75,Urban,HR Executive,32690,0 +27108,Female,35,Bachelors,4,77,79,17,11,6.0,1,64,Urban,ML Engineer,52911,0 +27109,Female,43,Bachelors,18,50,9,12,37,7.0,6,78,Semi-Urban,Manager,55620,0 +27110,Male,30,Diploma,16,41,34,13,84,4.0,3,90,Rural,Data Analyst,47148,0 +27111,Female,21,PhD,14,29,91,62,82,1.0,5,74,Urban,Data Analyst,53243,1 +27112,Other,27,Bachelors,10,10,45,76,67,2.0,5,55,Semi-Urban,HR Executive,43110,0 +27113,Other,31,Bachelors,6,89,49,12,4,6.0,1,19,Semi-Urban,Data Analyst,23998,0 +27114,Female,35,High School,5,66,23,99,92,4.0,7,31,Urban,Manager,63934,0 +27115,Female,54,Bachelors,7,13,81,16,1,1.0,5,1,Urban,ML Engineer,111206,0 +27116,Male,21,Masters,6,11,45,28,59,6.0,0,63,Semi-Urban,ML Engineer,79843,0 +27117,Female,26,Bachelors,0,81,59,11,16,5.0,6,89,Urban,Data Analyst,132909,0 +27118,Female,39,PhD,18,70,64,37,40,0.0,7,53,Semi-Urban,Data Analyst,40768,0 +27119,Female,24,Bachelors,12,65,68,93,61,8.0,3,42,Rural,ML Engineer,135403,1 +27120,Female,31,Bachelors,5,32,66,46,81,5.0,2,67,Semi-Urban,HR Executive,132682,0 +27121,Male,46,Bachelors,11,52,55,89,51,5.0,1,90,Urban,Data Analyst,130582,1 +27122,Male,53,High School,8,15,91,47,78,3.0,3,32,Urban,Software Engineer,109810,0 +27123,Male,38,Bachelors,13,57,90,50,42,1.0,0,9,Semi-Urban,Data Analyst,70438,0 +27124,Female,45,High School,11,66,81,37,88,1.0,0,96,Urban,Manager,35838,1 +27125,Male,55,Bachelors,1,83,60,1,5,0.0,6,38,Urban,HR Executive,34662,0 +27126,Male,34,Masters,19,2,84,62,69,8.0,6,81,Urban,ML Engineer,21597,0 +27127,Male,50,Bachelors,18,34,11,2,76,3.0,3,17,Urban,ML Engineer,60199,0 +27128,Female,57,High School,18,0,2,44,84,0.0,5,26,Semi-Urban,ML Engineer,20809,0 +27129,Female,21,Bachelors,5,72,9,89,81,5.0,3,17,Urban,ML Engineer,66802,0 +27130,Female,24,Diploma,17,96,22,95,64,4.0,6,92,Urban,Software Engineer,62791,1 +27131,Female,24,Bachelors,19,14,48,85,22,2.0,5,85,Rural,Software Engineer,62797,0 +27132,Male,25,High School,9,7,92,80,59,6.0,6,33,Urban,Manager,81027,0 +27133,Female,30,High School,16,12,32,76,2,0.0,7,34,Semi-Urban,Software Engineer,36466,0 +27134,Male,35,Bachelors,2,9,67,14,30,8.0,3,49,Rural,Manager,70681,0 +27135,Male,58,Masters,15,70,9,36,57,3.0,2,91,Rural,ML Engineer,132935,0 +27136,Female,57,Masters,4,64,18,9,86,4.0,3,89,Urban,Software Engineer,117596,0 +27137,Female,26,Bachelors,15,61,41,3,67,8.0,7,95,Urban,HR Executive,84944,0 +27138,Female,42,Masters,4,32,71,60,97,5.0,7,14,Semi-Urban,Manager,113853,0 +27139,Male,39,Bachelors,7,27,31,76,14,7.0,4,22,Urban,Data Analyst,68602,0 +27140,Male,29,Masters,17,32,21,0,20,0.0,3,86,Semi-Urban,ML Engineer,57099,0 +27141,Male,43,Diploma,10,50,50,58,56,5.0,6,29,Semi-Urban,ML Engineer,149826,0 +27142,Male,46,Masters,0,18,29,27,77,9.0,5,31,Urban,ML Engineer,67790,0 +27143,Male,43,Masters,3,58,3,32,35,6.0,2,43,Urban,Manager,24600,0 +27144,Male,36,Bachelors,3,38,21,55,63,0.0,0,16,Semi-Urban,Data Analyst,81170,0 +27145,Male,48,Masters,0,46,16,52,86,1.0,5,2,Urban,ML Engineer,30478,0 +27146,Female,53,Bachelors,1,27,72,70,35,0.0,3,8,Urban,ML Engineer,58337,0 +27147,Other,28,Bachelors,17,95,2,39,95,6.0,7,65,Semi-Urban,ML Engineer,129830,0 +27148,Female,57,Masters,5,79,41,21,31,8.0,6,43,Urban,Manager,93976,0 +27149,Female,45,Bachelors,15,58,66,82,68,7.0,6,73,Urban,HR Executive,34617,1 +27150,Male,55,Bachelors,13,28,59,23,82,6.0,3,33,Urban,Data Analyst,96361,0 +27151,Female,54,Masters,6,40,54,27,52,2.0,3,70,Urban,Manager,32410,0 +27152,Male,23,Bachelors,15,81,93,31,20,6.0,5,9,Urban,Software Engineer,45781,0 +27153,Male,54,Bachelors,1,29,18,56,4,8.0,6,95,Urban,Manager,139205,0 +27154,Male,41,PhD,7,83,23,16,99,9.0,0,23,Urban,Manager,45204,0 +27155,Male,55,Diploma,12,81,20,82,64,0.0,2,22,Semi-Urban,ML Engineer,142911,0 +27156,Female,55,Bachelors,14,22,93,33,2,8.0,3,43,Urban,Manager,132960,0 +27157,Male,45,Diploma,0,83,80,43,19,0.0,3,18,Rural,Data Analyst,26383,0 +27158,Female,22,Diploma,14,38,87,66,52,4.0,3,17,Urban,Manager,34641,0 +27159,Other,26,Masters,19,14,99,22,15,1.0,2,44,Semi-Urban,Software Engineer,32979,0 +27160,Male,27,PhD,5,82,63,22,9,0.0,7,35,Rural,Manager,127788,0 +27161,Male,56,Bachelors,19,57,75,26,29,4.0,4,86,Rural,Software Engineer,48639,1 +27162,Female,59,Masters,12,74,68,86,44,2.0,2,13,Semi-Urban,HR Executive,22266,1 +27163,Male,26,Masters,19,31,8,76,60,2.0,2,39,Semi-Urban,ML Engineer,144335,0 +27164,Male,58,Bachelors,5,97,24,75,46,4.0,6,1,Semi-Urban,ML Engineer,21663,0 +27165,Female,46,Diploma,15,39,39,62,42,8.0,2,2,Urban,Data Analyst,72925,0 +27166,Other,51,Bachelors,19,7,55,29,21,3.0,0,16,Rural,HR Executive,128126,0 +27167,Female,41,Diploma,8,39,22,90,62,2.0,5,61,Urban,Manager,137237,0 +27168,Male,38,High School,6,39,47,76,28,2.0,1,17,Urban,HR Executive,97561,0 +27169,Male,37,Masters,7,75,12,24,97,1.0,3,73,Urban,Manager,112516,0 +27170,Male,52,Bachelors,1,13,93,91,29,6.0,5,51,Urban,Manager,54884,1 +27171,Male,25,Bachelors,16,45,49,89,40,6.0,4,54,Urban,ML Engineer,115215,1 +27172,Male,42,PhD,5,94,9,6,54,4.0,4,99,Urban,HR Executive,100274,0 +27173,Male,24,Bachelors,6,45,71,21,95,9.0,4,37,Semi-Urban,Software Engineer,106459,0 +27174,Female,49,Bachelors,11,2,19,13,83,0.0,6,89,Urban,ML Engineer,44059,0 +27175,Female,25,Bachelors,14,84,57,11,48,7.0,2,53,Urban,ML Engineer,51001,0 +27176,Female,25,High School,9,71,73,79,44,2.0,0,65,Rural,Software Engineer,94829,1 +27177,Female,33,Diploma,3,95,19,0,5,0.0,2,16,Urban,Manager,29282,0 +27178,Male,49,Bachelors,0,98,95,74,22,0.0,2,89,Urban,Data Analyst,30947,1 +27179,Male,51,Bachelors,12,86,38,73,12,9.0,5,67,Urban,Manager,146516,1 +27180,Female,33,Bachelors,6,84,82,85,25,8.0,6,22,Urban,Manager,148115,1 +27181,Other,22,High School,6,5,82,16,16,5.0,6,28,Rural,HR Executive,33447,0 +27182,Male,27,Bachelors,4,10,76,19,13,3.0,1,88,Semi-Urban,Manager,37382,0 +27183,Male,53,Bachelors,8,83,14,91,64,6.0,5,0,Urban,ML Engineer,128773,0 +27184,Female,41,High School,18,55,21,65,95,6.0,0,99,Rural,HR Executive,148208,0 +27185,Male,51,High School,12,0,8,92,31,4.0,2,13,Urban,Data Analyst,65212,0 +27186,Male,40,Diploma,13,98,5,14,64,2.0,4,0,Urban,ML Engineer,132875,0 +27187,Male,40,Bachelors,19,6,70,0,91,6.0,3,58,Rural,Software Engineer,105611,0 +27188,Female,54,Diploma,0,73,60,69,2,3.0,6,36,Urban,ML Engineer,73338,0 +27189,Male,22,Diploma,6,2,17,84,8,8.0,6,90,Semi-Urban,Manager,50449,0 +27190,Female,26,PhD,15,2,73,91,17,4.0,4,52,Rural,Manager,148318,0 +27191,Male,32,Bachelors,2,80,84,79,63,6.0,6,77,Urban,Data Analyst,72232,1 +27192,Male,48,High School,15,59,44,81,20,5.0,7,34,Urban,Data Analyst,102859,0 +27193,Female,58,Bachelors,5,55,9,40,10,6.0,7,75,Semi-Urban,Data Analyst,131089,0 +27194,Male,27,Diploma,5,32,85,12,8,2.0,5,81,Rural,Software Engineer,124087,0 +27195,Male,43,Bachelors,18,54,12,30,42,3.0,4,11,Urban,ML Engineer,84403,0 +27196,Male,28,Diploma,3,88,7,24,70,6.0,1,84,Rural,Software Engineer,67317,0 +27197,Female,40,PhD,10,49,63,89,28,3.0,0,66,Semi-Urban,ML Engineer,37479,1 +27198,Male,37,Bachelors,19,51,31,48,13,8.0,1,69,Semi-Urban,HR Executive,105136,0 +27199,Male,41,High School,18,21,98,13,53,3.0,7,23,Rural,ML Engineer,123304,0 +27200,Female,56,High School,0,81,48,50,45,1.0,3,71,Semi-Urban,ML Engineer,88291,1 +27201,Male,36,Masters,11,20,99,93,95,3.0,0,55,Urban,Software Engineer,140060,1 +27202,Male,57,Masters,19,1,56,49,78,1.0,6,14,Urban,Data Analyst,46206,0 +27203,Female,30,High School,13,60,38,67,13,5.0,6,36,Urban,ML Engineer,84544,0 +27204,Male,41,Bachelors,15,8,29,40,82,8.0,4,53,Rural,ML Engineer,87500,0 +27205,Male,50,Diploma,8,45,55,22,41,6.0,1,65,Urban,Software Engineer,117803,0 +27206,Female,50,PhD,12,15,80,46,56,3.0,4,26,Semi-Urban,Data Analyst,80279,0 +27207,Female,35,High School,15,90,87,69,40,9.0,2,92,Urban,Software Engineer,105173,1 +27208,Male,49,Diploma,15,61,55,3,48,3.0,5,67,Urban,ML Engineer,37898,0 +27209,Male,39,High School,14,63,22,49,5,5.0,3,2,Rural,Data Analyst,116492,0 +27210,Female,49,Bachelors,4,68,97,79,68,4.0,4,59,Semi-Urban,HR Executive,134890,1 +27211,Male,26,Bachelors,19,35,64,32,93,0.0,7,57,Urban,Software Engineer,79483,0 +27212,Male,43,Bachelors,1,34,42,38,23,2.0,1,79,Urban,Data Analyst,125920,0 +27213,Male,47,Bachelors,13,59,26,66,49,0.0,4,87,Rural,Data Analyst,33686,1 +27214,Female,32,PhD,16,62,51,36,65,6.0,1,72,Semi-Urban,ML Engineer,80601,0 +27215,Male,30,Diploma,4,63,17,73,72,3.0,1,9,Urban,Manager,106158,0 +27216,Female,46,Bachelors,5,11,94,20,88,9.0,1,72,Urban,Data Analyst,109033,0 +27217,Female,45,High School,11,21,77,23,64,4.0,0,87,Semi-Urban,Software Engineer,76791,0 +27218,Male,47,High School,14,47,26,33,27,0.0,2,63,Urban,Manager,94873,0 +27219,Male,43,Diploma,18,99,61,60,50,8.0,6,45,Urban,ML Engineer,80986,1 +27220,Other,42,Diploma,17,49,52,75,64,4.0,0,20,Rural,Data Analyst,135984,0 +27221,Male,59,Bachelors,19,30,61,47,89,1.0,3,65,Urban,Data Analyst,42217,0 +27222,Male,31,Diploma,1,59,77,4,21,7.0,4,3,Urban,Data Analyst,33193,0 +27223,Female,55,Bachelors,5,69,61,81,43,7.0,2,75,Urban,ML Engineer,68307,1 +27224,Male,21,Bachelors,5,50,24,28,98,8.0,4,30,Semi-Urban,Manager,120273,0 +27225,Male,46,Diploma,19,59,85,98,51,9.0,4,47,Semi-Urban,Data Analyst,56933,1 +27226,Male,32,Bachelors,4,69,98,4,55,7.0,7,90,Urban,ML Engineer,75051,1 +27227,Male,30,Diploma,12,29,9,90,58,3.0,3,77,Rural,ML Engineer,56236,0 +27228,Male,47,Bachelors,9,52,71,10,18,5.0,2,97,Semi-Urban,HR Executive,60414,0 +27229,Female,38,Bachelors,9,1,66,54,32,0.0,3,72,Urban,Manager,21934,0 +27230,Other,36,Masters,11,50,95,50,34,8.0,3,57,Semi-Urban,HR Executive,46931,1 +27231,Male,22,Masters,9,77,78,88,23,6.0,0,11,Rural,Data Analyst,21614,1 +27232,Male,59,High School,4,47,83,68,70,4.0,4,30,Urban,HR Executive,35413,0 +27233,Male,30,High School,17,89,23,27,76,3.0,4,99,Semi-Urban,Software Engineer,80431,1 +27234,Male,58,Bachelors,11,18,60,15,6,3.0,3,30,Urban,Data Analyst,115675,0 +27235,Male,47,Bachelors,4,25,58,23,97,0.0,0,2,Semi-Urban,Data Analyst,80460,0 +27236,Male,33,Bachelors,17,4,34,43,30,2.0,3,59,Urban,HR Executive,93369,0 +27237,Female,32,Masters,14,76,41,74,10,6.0,3,46,Urban,HR Executive,32576,0 +27238,Male,34,Bachelors,3,3,0,45,96,1.0,4,1,Semi-Urban,Software Engineer,30113,0 +27239,Male,21,Diploma,11,21,6,37,30,8.0,4,64,Urban,Data Analyst,56475,0 +27240,Male,30,Bachelors,18,63,56,92,67,4.0,4,39,Urban,Software Engineer,85305,1 +27241,Male,34,Bachelors,16,92,1,14,31,6.0,1,49,Semi-Urban,Manager,63786,0 +27242,Female,41,Bachelors,8,62,73,87,65,4.0,6,50,Semi-Urban,Manager,34120,1 +27243,Male,31,Masters,15,53,47,79,46,8.0,3,30,Rural,Data Analyst,146242,0 +27244,Other,38,Masters,9,97,64,57,64,0.0,1,93,Urban,HR Executive,36337,1 +27245,Male,54,Masters,2,61,59,54,76,1.0,5,6,Semi-Urban,ML Engineer,143499,0 +27246,Female,54,Bachelors,15,28,11,85,39,6.0,3,6,Rural,Manager,34048,0 +27247,Other,53,Bachelors,15,70,71,95,66,3.0,3,81,Urban,Manager,75284,1 +27248,Male,58,Masters,11,17,1,25,89,1.0,2,35,Urban,ML Engineer,114473,0 +27249,Male,33,Masters,4,31,75,71,19,4.0,2,27,Urban,HR Executive,83584,0 +27250,Female,29,Bachelors,19,21,20,35,46,1.0,2,60,Urban,ML Engineer,81682,0 +27251,Male,31,Bachelors,10,30,87,77,26,8.0,4,12,Urban,Data Analyst,49965,0 +27252,Female,53,Masters,16,68,81,77,12,6.0,0,96,Rural,Software Engineer,33601,1 +27253,Male,58,High School,17,13,34,96,70,7.0,7,50,Urban,Manager,51720,0 +27254,Male,56,Masters,0,62,0,23,81,4.0,5,70,Urban,Manager,64039,0 +27255,Male,48,Diploma,2,81,19,58,23,6.0,4,25,Rural,Software Engineer,70427,0 +27256,Female,47,Bachelors,19,53,98,7,19,1.0,0,39,Urban,Data Analyst,63781,0 +27257,Male,38,Diploma,12,58,81,95,91,8.0,7,57,Urban,Software Engineer,91004,1 +27258,Male,34,Bachelors,19,1,53,96,8,1.0,6,35,Urban,ML Engineer,43280,0 +27259,Male,53,Diploma,19,71,87,19,10,2.0,3,72,Urban,Manager,117711,1 +27260,Male,42,Masters,3,15,88,77,8,1.0,2,45,Rural,Software Engineer,22415,0 +27261,Male,49,Bachelors,1,15,85,88,27,0.0,5,58,Urban,HR Executive,123539,1 +27262,Male,36,Bachelors,17,83,83,48,92,9.0,5,59,Semi-Urban,ML Engineer,137188,1 +27263,Female,52,Diploma,1,35,12,95,58,3.0,2,32,Semi-Urban,HR Executive,43891,0 +27264,Female,30,Diploma,16,31,97,60,90,4.0,4,70,Semi-Urban,ML Engineer,96451,1 +27265,Male,57,Bachelors,19,44,85,41,31,7.0,5,86,Urban,ML Engineer,102391,1 +27266,Male,52,Bachelors,16,73,28,74,8,7.0,7,70,Urban,Manager,69145,1 +27267,Male,50,Diploma,14,86,49,8,57,2.0,1,39,Rural,ML Engineer,119536,0 +27268,Female,25,Masters,7,38,58,60,64,3.0,4,56,Urban,HR Executive,58747,0 +27269,Male,57,Masters,11,48,31,89,92,3.0,3,84,Semi-Urban,Manager,85773,1 +27270,Male,58,Bachelors,17,36,18,63,80,4.0,2,98,Urban,HR Executive,49720,0 +27271,Male,50,PhD,2,68,60,30,6,1.0,5,63,Rural,Manager,54852,0 +27272,Female,45,High School,14,80,38,79,88,4.0,7,80,Urban,Software Engineer,130282,1 +27273,Other,37,Bachelors,9,63,53,35,16,5.0,2,26,Urban,HR Executive,132919,0 +27274,Male,33,PhD,11,18,39,22,27,5.0,7,99,Urban,Manager,49580,0 +27275,Male,52,Masters,10,0,22,54,81,5.0,6,2,Urban,ML Engineer,102100,0 +27276,Male,34,Diploma,3,98,18,80,0,3.0,5,53,Urban,Software Engineer,56486,1 +27277,Male,50,Diploma,7,83,15,66,84,4.0,0,80,Semi-Urban,ML Engineer,120523,1 +27278,Male,49,PhD,12,0,16,25,77,3.0,0,95,Urban,ML Engineer,41025,0 +27279,Female,48,PhD,8,79,88,66,66,7.0,0,52,Urban,Manager,77575,1 +27280,Male,59,Diploma,7,53,8,31,48,0.0,2,16,Semi-Urban,HR Executive,124479,0 +27281,Female,48,Bachelors,17,36,66,83,97,3.0,1,97,Urban,HR Executive,65077,1 +27282,Male,40,High School,7,11,15,65,79,6.0,2,26,Rural,Software Engineer,111430,0 +27283,Female,31,Diploma,16,82,13,69,10,4.0,3,24,Semi-Urban,HR Executive,56347,0 +27284,Male,24,Bachelors,4,34,93,75,15,7.0,5,34,Semi-Urban,HR Executive,22246,1 +27285,Male,53,Diploma,15,47,75,70,78,1.0,6,53,Urban,HR Executive,114818,1 +27286,Female,34,Bachelors,0,76,30,70,43,2.0,4,0,Urban,HR Executive,20921,0 +27287,Male,26,Diploma,13,34,65,80,22,7.0,2,29,Semi-Urban,HR Executive,35857,0 +27288,Male,57,Masters,4,60,49,22,97,3.0,7,70,Urban,Manager,20170,0 +27289,Female,51,Masters,7,24,75,58,23,1.0,6,28,Urban,Software Engineer,106831,0 +27290,Male,47,Bachelors,2,33,94,90,26,8.0,2,17,Rural,Data Analyst,127034,0 +27291,Male,42,Bachelors,14,81,42,79,0,7.0,7,1,Urban,Software Engineer,40369,0 +27292,Female,29,Bachelors,15,75,68,46,55,3.0,5,74,Urban,ML Engineer,74316,1 +27293,Other,35,Bachelors,9,76,97,89,49,1.0,6,64,Urban,HR Executive,103311,1 +27294,Female,23,Bachelors,16,27,33,92,78,7.0,3,16,Urban,Data Analyst,87002,0 +27295,Male,25,Diploma,0,11,96,25,25,8.0,4,51,Semi-Urban,HR Executive,73865,0 +27296,Female,38,High School,12,33,4,49,29,8.0,0,68,Semi-Urban,HR Executive,129812,0 +27297,Female,22,Diploma,15,44,65,95,99,2.0,5,88,Urban,ML Engineer,79339,1 +27298,Female,39,Bachelors,10,89,21,17,85,6.0,3,40,Semi-Urban,Data Analyst,62608,0 +27299,Female,37,Bachelors,10,25,46,17,33,2.0,7,32,Urban,Manager,104472,0 +27300,Male,39,Masters,7,2,28,55,26,4.0,5,4,Urban,Software Engineer,109845,0 +27301,Male,23,Diploma,4,28,83,45,79,7.0,6,8,Semi-Urban,Data Analyst,125434,0 +27302,Female,43,Masters,18,72,23,83,6,5.0,3,48,Urban,Software Engineer,134585,0 +27303,Other,41,Bachelors,18,4,3,58,31,5.0,1,6,Urban,Manager,28066,0 +27304,Male,55,High School,15,54,33,37,67,5.0,0,13,Urban,Software Engineer,24596,0 +27305,Other,23,High School,0,86,41,94,4,3.0,0,99,Rural,Data Analyst,145542,1 +27306,Female,26,Diploma,5,78,1,70,90,7.0,1,50,Urban,Data Analyst,97629,0 +27307,Female,36,Masters,5,67,75,3,71,9.0,4,3,Urban,ML Engineer,60911,0 +27308,Female,35,PhD,16,37,24,28,43,0.0,6,1,Urban,Manager,92520,0 +27309,Female,57,Diploma,18,43,29,95,27,3.0,1,47,Semi-Urban,Data Analyst,20543,0 +27310,Female,50,Bachelors,14,97,41,73,90,6.0,0,20,Urban,Manager,20650,0 +27311,Female,29,Masters,7,33,10,54,3,8.0,3,23,Rural,HR Executive,40741,0 +27312,Male,30,Masters,1,25,87,19,57,4.0,1,76,Rural,ML Engineer,69999,0 +27313,Male,49,Bachelors,13,98,94,25,31,4.0,7,42,Urban,Manager,26492,1 +27314,Male,32,Masters,0,85,53,12,95,7.0,5,8,Rural,Manager,95873,0 +27315,Male,59,Diploma,1,34,91,70,57,9.0,0,0,Rural,Software Engineer,143858,0 +27316,Male,58,Bachelors,3,28,50,98,51,1.0,6,59,Urban,HR Executive,143966,1 +27317,Female,55,Diploma,5,91,48,34,81,7.0,4,95,Urban,Data Analyst,28073,1 +27318,Female,28,Bachelors,15,0,79,34,72,1.0,5,93,Urban,Data Analyst,22769,0 +27319,Male,21,High School,8,88,47,4,31,5.0,6,74,Urban,ML Engineer,117672,0 +27320,Female,59,Diploma,13,97,47,78,4,5.0,1,23,Urban,ML Engineer,62474,1 +27321,Male,29,Bachelors,4,47,51,26,17,2.0,3,61,Urban,HR Executive,138987,0 +27322,Male,59,Bachelors,4,93,93,18,58,3.0,3,48,Urban,ML Engineer,37808,1 +27323,Female,46,Masters,8,44,89,62,83,9.0,1,82,Urban,Manager,37502,1 +27324,Male,37,Diploma,9,35,95,93,71,2.0,2,32,Urban,Software Engineer,98351,1 +27325,Female,34,High School,0,78,0,7,42,3.0,6,62,Urban,Software Engineer,116212,0 +27326,Male,21,Bachelors,4,72,39,79,68,5.0,6,15,Semi-Urban,ML Engineer,149737,0 +27327,Male,30,High School,3,54,30,94,25,7.0,4,71,Urban,Manager,39929,1 +27328,Female,58,Bachelors,13,2,44,74,57,0.0,2,15,Urban,HR Executive,39948,0 +27329,Male,33,Bachelors,13,74,8,80,21,3.0,6,40,Semi-Urban,Software Engineer,134515,0 +27330,Other,47,Masters,19,22,33,27,67,2.0,7,11,Urban,Manager,72341,0 +27331,Male,52,Diploma,17,45,87,46,57,6.0,0,34,Urban,Software Engineer,140298,0 +27332,Male,58,Masters,4,8,92,90,34,3.0,6,71,Urban,ML Engineer,116506,1 +27333,Female,59,Bachelors,10,51,21,10,6,7.0,3,84,Urban,Data Analyst,90361,0 +27334,Female,35,Diploma,14,21,12,96,88,9.0,7,55,Urban,Software Engineer,70578,0 +27335,Male,50,Bachelors,11,75,81,87,60,6.0,6,67,Semi-Urban,ML Engineer,59604,1 +27336,Male,28,Diploma,18,76,91,24,19,1.0,3,7,Urban,Data Analyst,139884,0 +27337,Female,49,PhD,10,60,98,22,25,9.0,4,99,Semi-Urban,Software Engineer,28326,1 +27338,Male,48,Diploma,19,54,19,42,28,5.0,5,88,Semi-Urban,ML Engineer,75208,0 +27339,Male,26,Diploma,10,18,0,14,91,8.0,7,35,Urban,ML Engineer,20371,0 +27340,Female,33,Bachelors,14,69,44,64,24,8.0,4,71,Urban,ML Engineer,142216,1 +27341,Male,57,Bachelors,18,25,33,80,71,1.0,6,16,Urban,ML Engineer,37546,0 +27342,Male,59,PhD,11,56,7,28,98,5.0,6,6,Urban,HR Executive,111192,0 +27343,Male,32,Diploma,15,62,0,86,4,8.0,0,0,Semi-Urban,Software Engineer,147338,0 +27344,Female,59,Diploma,3,11,87,91,58,9.0,0,80,Rural,Data Analyst,137102,1 +27345,Female,59,Bachelors,3,28,65,49,2,6.0,5,64,Semi-Urban,ML Engineer,91925,0 +27346,Female,36,Masters,17,61,18,94,79,3.0,1,34,Semi-Urban,ML Engineer,69222,0 +27347,Male,22,High School,10,77,46,42,49,5.0,6,2,Rural,Manager,98428,0 +27348,Male,42,Bachelors,2,94,90,34,26,2.0,5,59,Urban,Data Analyst,65786,1 +27349,Male,40,Masters,11,15,91,95,60,9.0,1,10,Urban,Software Engineer,111286,0 +27350,Male,42,Masters,6,61,3,99,44,9.0,3,47,Rural,ML Engineer,121714,0 +27351,Male,39,Diploma,17,94,66,6,68,2.0,2,16,Urban,ML Engineer,128231,0 +27352,Male,22,High School,7,25,23,19,67,1.0,4,59,Urban,HR Executive,123248,0 +27353,Female,34,High School,19,6,66,16,85,1.0,7,97,Semi-Urban,Manager,45703,0 +27354,Female,24,Diploma,12,87,43,6,3,0.0,5,77,Urban,ML Engineer,144921,0 +27355,Male,27,Bachelors,18,9,68,43,74,4.0,0,81,Rural,Manager,137853,0 +27356,Female,42,Bachelors,4,83,18,32,72,7.0,6,63,Semi-Urban,HR Executive,146124,0 +27357,Female,56,Masters,4,52,29,26,94,8.0,0,52,Urban,ML Engineer,41648,0 +27358,Male,21,Diploma,9,39,34,56,83,0.0,6,49,Rural,ML Engineer,57891,0 +27359,Male,49,Bachelors,5,25,9,50,98,2.0,1,94,Rural,HR Executive,100020,0 +27360,Female,56,Bachelors,17,50,68,23,5,8.0,3,38,Rural,Data Analyst,84430,0 +27361,Male,47,Diploma,4,96,83,55,93,5.0,2,26,Urban,Data Analyst,136776,1 +27362,Male,39,PhD,17,45,73,95,58,1.0,1,20,Semi-Urban,ML Engineer,37661,0 +27363,Male,49,Masters,2,43,18,67,57,0.0,2,50,Urban,ML Engineer,118738,0 +27364,Male,33,Bachelors,12,89,21,66,75,9.0,6,69,Urban,Manager,66177,1 +27365,Other,23,Bachelors,8,56,67,60,72,5.0,5,35,Urban,Software Engineer,85135,0 +27366,Female,56,Bachelors,11,73,45,55,18,7.0,7,97,Urban,Manager,40262,1 +27367,Male,32,Masters,16,75,96,92,91,4.0,1,12,Urban,Software Engineer,109062,1 +27368,Female,45,Diploma,7,74,30,88,99,6.0,5,48,Urban,HR Executive,121893,0 +27369,Female,36,Diploma,14,29,33,34,23,0.0,0,25,Urban,ML Engineer,126832,0 +27370,Female,31,High School,15,45,81,54,69,4.0,7,96,Semi-Urban,ML Engineer,100351,1 +27371,Male,47,High School,6,45,2,87,83,8.0,5,77,Urban,HR Executive,37942,0 +27372,Male,53,High School,13,61,35,89,57,0.0,5,67,Urban,HR Executive,20421,1 +27373,Male,23,Diploma,9,40,4,97,37,1.0,1,23,Semi-Urban,Manager,26633,0 +27374,Male,42,Masters,7,93,6,34,91,4.0,6,85,Rural,HR Executive,106330,0 +27375,Male,51,Diploma,10,3,30,55,87,1.0,6,46,Urban,Manager,33298,0 +27376,Male,58,Diploma,7,73,77,1,44,8.0,5,6,Urban,ML Engineer,30798,0 +27377,Male,51,High School,5,36,51,17,29,9.0,3,88,Semi-Urban,Software Engineer,92403,0 +27378,Male,45,Bachelors,13,10,74,64,72,1.0,4,63,Semi-Urban,ML Engineer,113280,0 +27379,Female,58,Diploma,11,86,7,56,97,5.0,0,78,Rural,Software Engineer,120352,0 +27380,Male,46,Bachelors,11,75,41,13,23,4.0,5,30,Semi-Urban,ML Engineer,129159,0 +27381,Female,34,High School,13,80,17,1,91,4.0,1,75,Urban,Data Analyst,61919,0 +27382,Female,59,Bachelors,6,26,66,70,13,8.0,0,99,Urban,Data Analyst,148613,1 +27383,Male,45,Diploma,19,0,76,64,21,0.0,1,59,Urban,Manager,57091,0 +27384,Male,53,Diploma,6,76,25,31,77,5.0,5,71,Semi-Urban,Manager,34312,0 +27385,Female,40,High School,8,86,67,11,52,8.0,2,59,Semi-Urban,ML Engineer,58691,0 +27386,Male,30,High School,1,38,56,64,28,9.0,0,94,Urban,Manager,78023,1 +27387,Female,48,High School,7,41,79,39,86,8.0,4,33,Rural,HR Executive,81130,0 +27388,Female,38,Bachelors,1,16,55,9,54,1.0,6,75,Rural,ML Engineer,126383,0 +27389,Male,44,Bachelors,13,93,76,40,31,9.0,1,7,Urban,Data Analyst,92516,0 +27390,Male,37,Bachelors,11,89,13,99,12,7.0,5,57,Semi-Urban,ML Engineer,30565,1 +27391,Male,38,High School,5,18,32,80,52,0.0,7,95,Urban,Data Analyst,147449,0 +27392,Female,32,High School,16,32,71,31,48,4.0,4,97,Semi-Urban,Data Analyst,109924,0 +27393,Female,25,Bachelors,14,98,50,67,19,2.0,0,91,Urban,Data Analyst,40666,1 +27394,Female,43,Masters,13,99,94,50,42,5.0,7,11,Rural,Software Engineer,90966,1 +27395,Male,30,Bachelors,10,71,1,35,4,2.0,1,56,Rural,Data Analyst,97620,0 +27396,Male,35,Masters,13,11,44,18,53,4.0,6,68,Semi-Urban,Software Engineer,26318,0 +27397,Male,29,Bachelors,11,62,53,30,11,6.0,7,93,Urban,Software Engineer,137400,1 +27398,Female,58,Bachelors,2,40,33,3,24,6.0,5,31,Urban,ML Engineer,112871,0 +27399,Male,29,PhD,11,12,16,32,94,5.0,5,77,Semi-Urban,Manager,104241,0 +27400,Male,49,Masters,13,72,91,20,19,3.0,3,29,Semi-Urban,Data Analyst,54920,0 +27401,Female,35,Diploma,11,21,18,78,79,1.0,6,1,Urban,Data Analyst,136270,0 +27402,Male,58,High School,19,88,10,46,83,1.0,2,12,Semi-Urban,Software Engineer,20346,0 +27403,Male,56,Masters,2,90,6,19,10,0.0,0,22,Urban,Data Analyst,49771,0 +27404,Male,42,High School,19,78,77,47,90,6.0,4,5,Rural,Data Analyst,149297,0 +27405,Male,55,Bachelors,16,55,6,61,47,9.0,3,30,Rural,Manager,137409,0 +27406,Female,59,High School,10,76,93,51,78,5.0,5,79,Urban,Manager,25099,1 +27407,Male,43,Bachelors,8,2,37,68,2,4.0,3,11,Urban,HR Executive,54200,0 +27408,Male,39,Masters,9,42,48,99,47,6.0,6,59,Semi-Urban,Manager,22162,1 +27409,Male,37,Bachelors,5,16,25,5,36,2.0,7,9,Rural,Data Analyst,43256,0 +27410,Male,42,Bachelors,1,19,30,56,37,1.0,7,9,Semi-Urban,Software Engineer,60101,0 +27411,Male,58,High School,10,46,90,21,43,7.0,7,42,Urban,ML Engineer,101725,0 +27412,Male,22,Masters,17,61,94,57,0,5.0,2,8,Urban,ML Engineer,123994,0 +27413,Female,35,Bachelors,10,66,3,48,23,7.0,4,15,Urban,HR Executive,88304,0 +27414,Male,54,PhD,9,42,76,15,4,1.0,5,24,Rural,Software Engineer,145803,0 +27415,Female,51,Bachelors,8,38,65,58,51,2.0,0,65,Rural,ML Engineer,143912,0 +27416,Male,31,Diploma,18,27,42,46,77,1.0,0,20,Rural,Manager,80898,0 +27417,Female,30,High School,8,84,59,86,29,4.0,5,89,Urban,Software Engineer,20355,1 +27418,Male,24,Bachelors,19,41,61,52,11,3.0,5,77,Semi-Urban,Data Analyst,86785,0 +27419,Male,53,Bachelors,16,72,40,89,32,0.0,4,5,Urban,Manager,122350,0 +27420,Other,48,High School,4,69,41,15,40,2.0,4,23,Rural,Data Analyst,99686,0 +27421,Male,58,Bachelors,17,51,58,92,38,8.0,0,95,Rural,Data Analyst,63322,1 +27422,Male,28,Diploma,0,86,34,55,75,1.0,2,30,Urban,Data Analyst,123618,0 +27423,Male,52,Diploma,17,95,68,65,59,3.0,4,65,Semi-Urban,Software Engineer,75341,1 +27424,Male,22,Diploma,17,20,33,89,66,7.0,7,99,Rural,Data Analyst,133653,1 +27425,Male,56,Bachelors,0,73,51,38,19,5.0,6,49,Semi-Urban,Data Analyst,50481,0 +27426,Male,30,Bachelors,5,29,65,88,90,0.0,0,19,Semi-Urban,ML Engineer,73853,0 +27427,Female,45,High School,4,38,88,46,73,8.0,1,0,Semi-Urban,Data Analyst,29642,0 +27428,Female,58,Bachelors,14,56,79,89,20,0.0,2,31,Semi-Urban,ML Engineer,55924,1 +27429,Female,45,High School,13,18,58,24,38,4.0,0,52,Rural,ML Engineer,69267,0 +27430,Male,39,Bachelors,15,94,68,15,25,1.0,7,84,Urban,HR Executive,103922,1 +27431,Male,39,Masters,15,69,65,77,33,2.0,6,13,Urban,Software Engineer,120955,0 +27432,Female,42,Bachelors,3,49,88,17,45,5.0,2,19,Urban,ML Engineer,82897,0 +27433,Male,40,PhD,2,15,69,11,39,0.0,7,18,Semi-Urban,ML Engineer,38604,0 +27434,Female,55,Bachelors,15,34,82,44,18,9.0,0,47,Urban,ML Engineer,35762,0 +27435,Male,39,High School,16,29,81,95,94,1.0,1,35,Semi-Urban,Manager,85643,1 +27436,Male,21,Bachelors,8,22,71,54,72,5.0,3,66,Urban,HR Executive,41444,0 +27437,Female,34,PhD,11,14,80,77,59,1.0,3,9,Urban,Software Engineer,50338,0 +27438,Female,35,Masters,2,57,91,42,51,6.0,4,87,Rural,Software Engineer,110726,1 +27439,Female,35,Bachelors,3,96,64,65,28,4.0,7,23,Rural,Manager,59489,1 +27440,Female,31,Bachelors,15,48,25,32,36,6.0,6,63,Urban,Manager,32338,0 +27441,Female,43,PhD,2,92,36,40,76,6.0,0,69,Semi-Urban,Manager,74455,0 +27442,Male,43,Bachelors,6,34,13,83,96,2.0,2,71,Urban,Data Analyst,87631,0 +27443,Other,55,Bachelors,8,1,45,18,4,5.0,1,18,Rural,Software Engineer,75243,0 +27444,Female,21,Bachelors,12,8,1,91,37,7.0,0,76,Rural,ML Engineer,73286,0 +27445,Female,27,Diploma,18,49,80,24,69,1.0,2,4,Semi-Urban,Software Engineer,146074,0 +27446,Male,49,Masters,3,11,16,73,90,0.0,7,59,Rural,ML Engineer,56555,0 +27447,Female,54,Masters,12,79,26,51,61,4.0,5,89,Rural,Software Engineer,95040,1 +27448,Male,57,Bachelors,18,49,99,67,74,9.0,7,57,Semi-Urban,HR Executive,148623,1 +27449,Male,30,Bachelors,17,1,6,10,52,5.0,0,60,Urban,Software Engineer,35923,0 +27450,Male,42,Masters,4,4,37,4,72,7.0,0,18,Semi-Urban,Software Engineer,149996,0 +27451,Male,32,Bachelors,1,71,29,23,78,0.0,6,10,Semi-Urban,Manager,97299,0 +27452,Male,32,Bachelors,8,12,65,69,50,0.0,3,74,Urban,Manager,26000,0 +27453,Female,57,High School,19,79,69,25,58,2.0,7,3,Urban,Software Engineer,73471,0 +27454,Female,54,PhD,7,71,68,97,17,2.0,4,41,Semi-Urban,Data Analyst,56815,1 +27455,Male,55,Bachelors,4,5,99,86,56,3.0,6,38,Semi-Urban,Data Analyst,98954,0 +27456,Female,24,Bachelors,2,38,35,5,20,4.0,0,72,Urban,Data Analyst,107598,0 +27457,Male,56,Bachelors,1,80,52,45,6,7.0,2,76,Urban,ML Engineer,146567,1 +27458,Male,55,Bachelors,10,60,22,98,42,1.0,2,64,Urban,ML Engineer,148080,1 +27459,Male,25,Bachelors,13,9,41,71,55,2.0,1,95,Rural,Data Analyst,29263,0 +27460,Female,33,Bachelors,16,32,44,36,52,1.0,5,47,Urban,Software Engineer,33991,0 +27461,Male,26,Bachelors,18,6,67,2,23,7.0,2,78,Urban,Manager,33936,0 +27462,Male,38,Diploma,2,16,44,24,1,0.0,2,95,Urban,ML Engineer,77024,0 +27463,Male,55,Masters,4,2,4,1,19,2.0,6,49,Urban,ML Engineer,81155,0 +27464,Female,54,Diploma,13,18,43,52,5,5.0,7,71,Urban,Software Engineer,107697,0 +27465,Female,37,Bachelors,3,65,78,64,75,1.0,3,62,Urban,HR Executive,117577,1 +27466,Male,39,Bachelors,1,17,30,61,96,8.0,3,23,Semi-Urban,HR Executive,122084,0 +27467,Male,56,High School,18,82,52,75,60,3.0,7,29,Rural,Data Analyst,103738,1 +27468,Female,53,Bachelors,13,47,4,24,91,2.0,0,12,Semi-Urban,Data Analyst,79633,0 +27469,Female,50,Bachelors,8,58,74,87,26,1.0,3,51,Urban,Manager,129571,1 +27470,Male,58,Masters,15,7,6,36,38,4.0,0,92,Urban,Software Engineer,50517,0 +27471,Female,52,Diploma,16,36,8,36,71,3.0,6,24,Urban,Data Analyst,132396,0 +27472,Other,27,Diploma,13,16,70,89,18,5.0,2,69,Semi-Urban,ML Engineer,77377,1 +27473,Male,28,Masters,4,53,89,26,42,5.0,1,53,Urban,Software Engineer,113985,0 +27474,Male,46,Masters,15,21,91,74,94,3.0,2,73,Rural,Manager,113334,1 +27475,Male,53,Bachelors,1,83,29,77,89,7.0,1,12,Urban,Manager,86555,0 +27476,Female,52,Masters,1,25,55,55,84,2.0,6,36,Semi-Urban,HR Executive,62892,0 +27477,Male,33,Masters,8,78,97,41,81,2.0,1,28,Semi-Urban,ML Engineer,99332,1 +27478,Male,42,High School,18,21,6,43,79,9.0,2,42,Urban,Data Analyst,93804,0 +27479,Female,42,Bachelors,19,73,1,35,64,3.0,4,52,Urban,ML Engineer,133075,0 +27480,Female,39,Masters,3,74,35,15,98,0.0,5,84,Rural,Software Engineer,44227,0 +27481,Male,22,Bachelors,16,95,2,21,4,6.0,6,0,Rural,Software Engineer,55034,0 +27482,Male,54,Diploma,17,9,52,15,73,6.0,6,87,Urban,Software Engineer,116011,0 +27483,Male,56,Masters,12,6,30,77,19,2.0,1,10,Urban,ML Engineer,145103,0 +27484,Female,41,Bachelors,7,28,68,51,77,5.0,1,9,Urban,ML Engineer,123549,0 +27485,Female,42,Bachelors,2,34,4,28,37,7.0,6,23,Rural,Software Engineer,117288,0 +27486,Male,51,Masters,5,33,80,13,68,5.0,7,20,Urban,Software Engineer,67528,0 +27487,Male,33,Diploma,6,94,2,77,68,2.0,0,37,Urban,ML Engineer,83785,0 +27488,Female,35,Diploma,12,54,49,10,2,3.0,4,12,Rural,Manager,148617,0 +27489,Male,24,Masters,10,4,29,94,55,9.0,2,19,Urban,Data Analyst,117679,0 +27490,Female,46,Diploma,10,98,36,83,51,6.0,1,5,Semi-Urban,Manager,140781,0 +27491,Male,28,High School,10,33,23,64,57,1.0,3,86,Rural,Software Engineer,114664,0 +27492,Female,23,Bachelors,15,5,1,30,79,1.0,4,17,Semi-Urban,Manager,81698,0 +27493,Male,59,High School,17,16,16,71,58,5.0,2,47,Urban,Data Analyst,98168,0 +27494,Male,44,PhD,2,53,36,77,11,9.0,7,26,Urban,HR Executive,36932,0 +27495,Male,40,Bachelors,15,76,19,92,38,4.0,0,61,Urban,ML Engineer,36623,1 +27496,Female,40,High School,0,94,79,37,66,9.0,5,93,Urban,Software Engineer,138617,1 +27497,Male,47,Masters,6,93,79,22,77,3.0,0,75,Rural,ML Engineer,103538,1 +27498,Male,37,Bachelors,7,33,90,87,40,5.0,7,74,Rural,Software Engineer,72438,1 +27499,Other,53,Bachelors,0,39,7,55,4,2.0,7,71,Urban,Software Engineer,44170,0 +27500,Female,51,Diploma,8,78,98,26,22,9.0,5,4,Semi-Urban,HR Executive,77983,0 +27501,Other,37,Bachelors,18,93,9,27,99,0.0,3,31,Semi-Urban,HR Executive,83138,0 +27502,Male,27,Bachelors,4,15,29,81,94,9.0,4,94,Urban,Manager,50542,0 +27503,Female,36,High School,4,44,79,28,59,6.0,2,11,Urban,Software Engineer,78620,0 +27504,Male,55,Masters,15,48,77,25,25,4.0,0,87,Semi-Urban,Data Analyst,131930,1 +27505,Male,36,Bachelors,3,68,9,11,59,1.0,2,47,Urban,Software Engineer,80187,0 +27506,Male,36,Bachelors,4,86,93,95,7,7.0,2,10,Urban,Software Engineer,129724,1 +27507,Male,53,Bachelors,14,8,16,65,45,8.0,1,33,Rural,Data Analyst,59684,0 +27508,Male,25,Bachelors,7,2,60,25,44,9.0,2,48,Rural,ML Engineer,116276,0 +27509,Male,26,Diploma,0,52,66,15,86,1.0,2,0,Urban,Data Analyst,57880,0 +27510,Female,33,Diploma,13,36,2,37,99,4.0,5,3,Semi-Urban,Software Engineer,46906,0 +27511,Male,48,High School,6,97,78,10,68,1.0,5,24,Semi-Urban,Manager,73674,0 +27512,Male,38,High School,1,14,15,63,0,1.0,0,33,Rural,ML Engineer,60193,0 +27513,Male,55,Masters,19,4,91,32,98,3.0,1,94,Urban,Manager,128651,0 +27514,Female,36,Masters,8,71,44,39,84,7.0,0,83,Urban,Data Analyst,87670,0 +27515,Male,37,Diploma,16,95,46,88,76,7.0,3,15,Semi-Urban,Manager,137885,1 +27516,Male,37,Masters,11,50,88,35,12,0.0,7,15,Urban,Manager,84121,0 +27517,Male,56,Diploma,4,45,14,99,90,8.0,6,97,Rural,Data Analyst,55545,1 +27518,Female,47,Masters,12,73,8,86,34,2.0,4,71,Urban,Software Engineer,66141,0 +27519,Male,55,PhD,3,52,20,50,39,7.0,1,59,Urban,HR Executive,92510,0 +27520,Male,48,Diploma,19,96,78,28,14,7.0,5,34,Semi-Urban,Data Analyst,66011,1 +27521,Male,37,Bachelors,0,84,98,50,86,3.0,7,23,Urban,Manager,38595,1 +27522,Female,23,Diploma,4,82,56,59,73,3.0,0,92,Rural,Data Analyst,135920,1 +27523,Male,52,Diploma,15,47,20,14,44,9.0,7,28,Urban,ML Engineer,55211,0 +27524,Female,27,Bachelors,5,61,56,9,22,8.0,7,2,Semi-Urban,HR Executive,31051,0 +27525,Male,27,PhD,9,92,74,23,18,5.0,7,12,Urban,HR Executive,81549,0 +27526,Other,34,Diploma,10,58,86,98,24,4.0,6,44,Semi-Urban,ML Engineer,134811,1 +27527,Male,29,Bachelors,7,88,56,78,54,9.0,1,47,Urban,Software Engineer,136017,1 +27528,Female,25,Bachelors,6,28,23,28,26,8.0,1,85,Urban,ML Engineer,104599,0 +27529,Male,37,High School,4,93,20,51,11,0.0,4,66,Semi-Urban,ML Engineer,22898,0 +27530,Male,35,Bachelors,5,75,67,81,92,7.0,5,33,Urban,Data Analyst,132543,1 +27531,Male,33,Masters,16,3,59,36,16,9.0,7,44,Urban,Manager,63185,0 +27532,Female,21,Bachelors,17,71,11,5,46,8.0,7,63,Rural,ML Engineer,90651,0 +27533,Other,44,Diploma,17,21,60,74,11,4.0,6,12,Rural,Manager,55535,0 +27534,Male,35,Masters,10,47,73,92,34,1.0,5,8,Rural,Software Engineer,70927,0 +27535,Female,38,Diploma,0,42,36,85,42,0.0,4,85,Urban,HR Executive,149187,1 +27536,Male,37,Diploma,7,24,21,5,67,8.0,5,84,Urban,Data Analyst,139120,0 +27537,Female,32,Bachelors,3,29,56,88,68,2.0,2,46,Urban,Software Engineer,146413,0 +27538,Male,37,Masters,12,5,36,63,7,9.0,5,32,Semi-Urban,Manager,131105,0 +27539,Male,57,PhD,6,30,34,59,3,0.0,0,34,Urban,HR Executive,118923,0 +27540,Male,34,Bachelors,8,89,21,63,7,4.0,2,1,Semi-Urban,Software Engineer,143977,0 +27541,Female,56,Masters,13,84,87,12,2,6.0,3,69,Rural,Software Engineer,85915,1 +27542,Female,34,Bachelors,7,35,3,50,50,8.0,5,35,Urban,ML Engineer,123164,0 +27543,Male,35,PhD,2,49,28,40,6,0.0,2,14,Rural,Manager,33799,0 +27544,Male,28,Masters,12,3,68,28,93,4.0,5,97,Urban,Software Engineer,43863,0 +27545,Male,28,Masters,13,12,65,28,73,9.0,6,70,Rural,HR Executive,44782,0 +27546,Male,32,Masters,0,27,99,74,57,8.0,6,90,Rural,Software Engineer,123100,1 +27547,Male,48,High School,2,19,21,12,82,4.0,4,94,Urban,Software Engineer,57245,0 +27548,Male,26,Diploma,7,88,44,39,82,8.0,2,36,Rural,Data Analyst,140516,0 +27549,Male,57,High School,3,4,68,10,92,9.0,2,33,Urban,HR Executive,36086,0 +27550,Female,39,Masters,10,21,38,69,93,6.0,0,33,Urban,ML Engineer,93666,0 +27551,Female,21,Bachelors,1,61,2,59,77,9.0,2,8,Semi-Urban,Software Engineer,106135,0 +27552,Male,48,Bachelors,6,11,59,54,78,1.0,3,30,Urban,Manager,94896,0 +27553,Female,41,Masters,11,54,88,61,53,9.0,5,88,Rural,HR Executive,105318,1 +27554,Male,47,Masters,14,2,42,6,56,6.0,3,98,Semi-Urban,Manager,32880,0 +27555,Female,53,Diploma,14,72,0,26,87,2.0,7,23,Urban,HR Executive,124819,0 +27556,Male,33,Diploma,5,16,27,15,88,7.0,7,13,Urban,Software Engineer,75705,0 +27557,Female,44,Bachelors,7,88,62,49,47,9.0,5,23,Semi-Urban,Data Analyst,100586,0 +27558,Male,55,PhD,13,34,82,49,75,2.0,2,80,Rural,Manager,83192,1 +27559,Male,55,Diploma,2,98,66,26,66,3.0,2,81,Semi-Urban,HR Executive,92063,1 +27560,Female,42,Masters,1,92,66,84,64,5.0,6,81,Urban,ML Engineer,95997,1 +27561,Male,35,PhD,11,7,64,79,27,9.0,3,7,Urban,ML Engineer,43229,0 +27562,Male,29,Bachelors,16,68,9,64,65,9.0,0,44,Urban,Software Engineer,73491,0 +27563,Female,22,Bachelors,12,75,4,28,50,6.0,3,64,Rural,Manager,99520,0 +27564,Female,44,Masters,8,69,74,83,93,1.0,2,94,Urban,Data Analyst,35261,1 +27565,Male,23,PhD,17,82,47,42,47,6.0,4,32,Urban,Manager,85810,0 +27566,Male,49,Bachelors,5,62,36,17,90,4.0,3,90,Semi-Urban,Data Analyst,83022,0 +27567,Male,40,Masters,9,92,66,84,73,9.0,5,73,Urban,ML Engineer,143372,1 +27568,Female,53,Diploma,18,77,99,19,91,2.0,0,2,Rural,Data Analyst,124763,0 +27569,Male,28,Bachelors,7,8,52,34,68,3.0,7,31,Semi-Urban,HR Executive,149245,0 +27570,Female,48,Masters,18,62,64,90,58,0.0,6,34,Urban,Manager,121130,1 +27571,Male,47,Masters,1,23,22,2,61,6.0,1,50,Urban,Manager,48937,0 +27572,Male,38,Masters,8,87,23,47,12,7.0,5,60,Urban,HR Executive,144183,0 +27573,Male,34,Diploma,4,41,40,80,78,9.0,3,86,Urban,Software Engineer,23464,1 +27574,Male,24,Bachelors,13,81,63,28,4,6.0,4,76,Urban,HR Executive,132155,1 +27575,Female,25,Masters,18,52,2,63,34,5.0,3,86,Semi-Urban,ML Engineer,135449,0 +27576,Male,32,Bachelors,18,17,73,30,64,1.0,2,2,Rural,Data Analyst,44714,0 +27577,Other,52,Bachelors,18,61,23,19,26,4.0,1,3,Urban,HR Executive,89208,0 +27578,Male,59,Bachelors,9,49,61,51,8,4.0,3,13,Urban,ML Engineer,72583,0 +27579,Male,24,Diploma,4,60,62,0,10,7.0,4,85,Rural,ML Engineer,54203,0 +27580,Male,41,Masters,15,84,40,21,21,9.0,7,72,Urban,ML Engineer,105354,0 +27581,Female,35,Bachelors,12,99,18,67,65,9.0,0,50,Urban,Manager,105942,0 +27582,Female,52,PhD,5,36,97,43,70,2.0,2,97,Semi-Urban,ML Engineer,97577,1 +27583,Male,56,PhD,17,49,70,15,75,3.0,6,32,Urban,ML Engineer,65796,0 +27584,Female,31,Masters,19,21,31,47,54,6.0,6,60,Rural,Data Analyst,110057,0 +27585,Male,39,Bachelors,1,21,13,10,76,8.0,4,80,Semi-Urban,Software Engineer,45129,0 +27586,Female,43,Bachelors,9,59,47,70,34,0.0,1,78,Semi-Urban,ML Engineer,57567,1 +27587,Female,58,Diploma,10,9,87,75,63,2.0,4,19,Semi-Urban,Manager,136514,0 +27588,Female,32,Bachelors,19,13,55,28,70,5.0,6,32,Urban,Software Engineer,26987,0 +27589,Female,33,Bachelors,0,77,31,80,32,1.0,3,62,Semi-Urban,HR Executive,122508,1 +27590,Female,31,High School,9,45,9,9,31,6.0,4,79,Semi-Urban,Software Engineer,125252,0 +27591,Other,46,Bachelors,10,24,25,16,6,2.0,5,25,Urban,HR Executive,23827,0 +27592,Male,25,High School,3,33,77,39,57,7.0,1,80,Urban,HR Executive,25868,0 +27593,Male,55,Masters,15,82,77,72,14,1.0,1,99,Urban,Software Engineer,60987,1 +27594,Female,57,Bachelors,17,64,86,12,10,3.0,7,32,Urban,HR Executive,141235,0 +27595,Female,35,Bachelors,13,55,91,31,88,3.0,0,41,Semi-Urban,Data Analyst,63282,0 +27596,Male,44,Diploma,18,22,32,27,52,8.0,7,40,Semi-Urban,HR Executive,140127,0 +27597,Male,30,Bachelors,4,99,46,47,19,5.0,1,97,Urban,Software Engineer,127922,1 +27598,Female,31,Masters,9,70,85,66,92,6.0,7,59,Urban,Software Engineer,56837,1 +27599,Other,39,Diploma,14,58,45,10,34,4.0,6,24,Semi-Urban,Data Analyst,22703,0 +27600,Male,52,Masters,14,53,95,20,28,6.0,4,62,Semi-Urban,ML Engineer,23384,0 +27601,Male,38,Masters,0,27,51,41,96,1.0,3,41,Urban,HR Executive,57833,0 +27602,Male,26,High School,0,35,72,56,2,0.0,0,25,Urban,Software Engineer,112409,0 +27603,Male,36,Bachelors,14,89,8,55,69,0.0,6,62,Urban,Data Analyst,125456,0 +27604,Female,49,High School,2,65,66,77,51,7.0,5,74,Urban,ML Engineer,69393,1 +27605,Female,45,Diploma,13,72,78,32,77,1.0,7,57,Rural,Manager,86187,0 +27606,Male,26,Bachelors,9,50,56,65,64,8.0,6,17,Urban,Software Engineer,126535,0 +27607,Male,54,Bachelors,10,34,93,23,23,8.0,7,7,Rural,Data Analyst,129165,0 +27608,Female,40,Bachelors,17,9,44,77,81,6.0,1,37,Semi-Urban,Manager,93312,0 +27609,Male,25,Bachelors,0,52,10,18,13,9.0,6,8,Rural,HR Executive,62884,0 +27610,Male,33,Bachelors,16,78,16,23,19,2.0,2,82,Semi-Urban,Data Analyst,47205,0 +27611,Female,22,PhD,6,76,70,91,14,4.0,7,56,Rural,ML Engineer,22043,1 +27612,Female,49,Masters,7,63,20,72,98,0.0,5,7,Urban,HR Executive,34626,0 +27613,Male,27,Masters,1,53,85,80,99,2.0,0,19,Semi-Urban,Software Engineer,34848,1 +27614,Female,47,Masters,8,21,43,34,14,1.0,6,70,Semi-Urban,HR Executive,119100,0 +27615,Male,44,High School,10,53,77,93,93,7.0,4,76,Semi-Urban,HR Executive,94620,1 +27616,Male,57,Masters,4,34,47,46,81,7.0,5,21,Rural,ML Engineer,124458,0 +27617,Male,42,Diploma,5,98,18,98,66,5.0,7,13,Urban,Software Engineer,95417,0 +27618,Male,46,Bachelors,7,48,87,65,81,2.0,1,4,Urban,HR Executive,87579,0 +27619,Male,51,Diploma,14,6,36,41,32,4.0,3,68,Urban,Software Engineer,92234,0 +27620,Male,45,Bachelors,4,47,43,60,16,8.0,1,98,Urban,HR Executive,132731,1 +27621,Female,23,Bachelors,8,2,97,45,93,1.0,3,94,Urban,ML Engineer,24082,0 +27622,Female,40,Masters,2,7,53,79,26,8.0,2,30,Urban,ML Engineer,135356,0 +27623,Male,30,High School,16,56,43,98,48,1.0,5,73,Semi-Urban,HR Executive,31757,1 +27624,Male,38,Bachelors,14,87,65,4,39,7.0,0,35,Urban,HR Executive,32046,0 +27625,Male,53,Masters,1,69,46,20,6,9.0,1,40,Urban,Data Analyst,39675,0 +27626,Male,59,Diploma,7,44,7,28,89,6.0,6,92,Semi-Urban,Manager,135291,0 +27627,Male,51,Bachelors,18,53,50,80,8,2.0,5,66,Rural,ML Engineer,85593,1 +27628,Female,48,Bachelors,2,69,34,58,85,3.0,4,55,Urban,Data Analyst,26701,0 +27629,Male,31,High School,2,95,74,12,68,6.0,5,64,Urban,HR Executive,133181,1 +27630,Male,25,Masters,1,53,30,17,69,3.0,3,6,Urban,Data Analyst,44256,0 +27631,Male,40,Bachelors,1,46,33,58,76,0.0,6,51,Rural,Software Engineer,149822,0 +27632,Male,40,Diploma,14,17,36,73,98,4.0,6,47,Urban,HR Executive,125848,0 +27633,Other,53,Bachelors,15,57,55,75,93,2.0,4,38,Urban,Data Analyst,95351,0 +27634,Male,43,Bachelors,9,93,9,11,79,8.0,3,89,Urban,HR Executive,114723,0 +27635,Male,28,Diploma,18,95,49,22,94,5.0,6,35,Semi-Urban,Manager,140469,0 +27636,Female,51,Masters,3,43,66,60,87,5.0,5,29,Urban,Data Analyst,70871,0 +27637,Male,29,Masters,8,10,14,78,25,9.0,4,44,Rural,Manager,46359,0 +27638,Male,30,High School,1,73,19,48,48,3.0,0,81,Urban,Manager,133232,0 +27639,Female,44,Masters,18,29,43,41,48,6.0,7,23,Rural,HR Executive,49914,0 +27640,Female,56,Masters,19,65,56,46,65,1.0,1,83,Rural,ML Engineer,120699,1 +27641,Male,26,Bachelors,6,43,28,76,60,2.0,6,20,Rural,Software Engineer,117716,0 +27642,Male,46,High School,5,28,45,27,88,9.0,3,54,Urban,Data Analyst,75365,0 +27643,Female,59,Diploma,5,94,63,60,71,2.0,4,35,Urban,Manager,82465,1 +27644,Male,38,Bachelors,17,2,94,54,29,1.0,1,93,Urban,ML Engineer,103359,1 +27645,Male,58,Bachelors,0,35,51,57,11,9.0,7,70,Urban,HR Executive,110936,0 +27646,Male,54,Diploma,13,90,23,67,68,0.0,0,86,Semi-Urban,Software Engineer,24772,1 +27647,Male,30,Diploma,11,60,74,37,81,0.0,7,5,Urban,Manager,104870,0 +27648,Male,33,Masters,14,38,20,17,38,0.0,3,88,Semi-Urban,Manager,117961,0 +27649,Male,34,Masters,10,56,93,37,72,6.0,4,64,Semi-Urban,HR Executive,145864,1 +27650,Female,23,Bachelors,18,78,19,68,62,4.0,6,3,Rural,Software Engineer,25606,0 +27651,Male,43,Bachelors,0,79,69,21,9,6.0,6,72,Urban,ML Engineer,137761,1 +27652,Male,46,High School,4,33,50,66,87,4.0,2,1,Urban,Manager,87569,0 +27653,Male,43,Diploma,1,58,70,65,22,1.0,7,39,Urban,ML Engineer,115133,0 +27654,Female,34,High School,0,13,86,44,83,7.0,3,66,Urban,ML Engineer,113268,0 +27655,Male,59,Diploma,15,86,58,61,70,9.0,7,82,Semi-Urban,Data Analyst,30761,1 +27656,Male,50,High School,18,85,24,44,4,5.0,3,78,Urban,Data Analyst,62354,0 +27657,Male,55,Diploma,10,39,62,55,91,4.0,2,56,Urban,Software Engineer,31832,0 +27658,Male,35,High School,6,63,26,11,26,1.0,5,22,Urban,ML Engineer,39259,0 +27659,Female,39,Masters,10,97,74,28,18,6.0,5,48,Rural,Data Analyst,131437,1 +27660,Male,49,Bachelors,14,27,85,20,98,1.0,4,22,Urban,HR Executive,93138,0 +27661,Male,50,Masters,12,30,85,37,22,9.0,6,8,Urban,Software Engineer,89143,0 +27662,Female,55,Diploma,19,98,82,91,30,1.0,3,97,Urban,Manager,65346,1 +27663,Male,48,Masters,0,97,27,45,44,4.0,6,15,Urban,Data Analyst,132101,0 +27664,Male,32,Masters,12,29,10,17,3,9.0,7,17,Urban,Software Engineer,98393,0 +27665,Male,48,Masters,2,8,43,50,5,7.0,5,84,Rural,Manager,94945,0 +27666,Female,38,Bachelors,13,72,91,74,23,0.0,0,49,Semi-Urban,Manager,98098,1 +27667,Male,49,Bachelors,5,90,89,3,65,7.0,7,77,Urban,ML Engineer,63397,1 +27668,Male,47,Bachelors,18,82,68,75,8,9.0,1,22,Urban,Manager,52452,1 +27669,Male,50,Bachelors,17,24,97,43,50,9.0,1,86,Semi-Urban,Manager,135024,1 +27670,Male,23,Diploma,14,8,58,29,46,7.0,0,44,Urban,Software Engineer,46544,0 +27671,Female,35,Bachelors,13,44,7,89,89,2.0,0,80,Urban,Data Analyst,40095,0 +27672,Female,21,High School,18,55,66,50,28,7.0,4,20,Urban,Manager,39323,0 +27673,Female,59,High School,18,64,50,5,15,4.0,4,51,Urban,ML Engineer,55324,0 +27674,Female,33,Bachelors,12,68,31,88,1,7.0,1,87,Urban,Manager,52503,1 +27675,Female,35,High School,12,51,41,39,23,3.0,7,42,Urban,Software Engineer,70587,0 +27676,Male,49,Masters,18,65,93,53,22,7.0,1,27,Urban,Software Engineer,58496,1 +27677,Male,46,Diploma,11,24,43,60,55,3.0,3,61,Urban,Data Analyst,98722,0 +27678,Male,43,Diploma,0,15,80,98,82,3.0,6,86,Semi-Urban,HR Executive,146983,1 +27679,Male,50,Bachelors,0,94,59,2,96,4.0,2,11,Rural,HR Executive,63114,0 +27680,Male,48,Diploma,4,83,77,75,0,0.0,6,24,Semi-Urban,Manager,35378,1 +27681,Male,51,High School,0,77,63,49,41,0.0,6,98,Urban,ML Engineer,92451,1 +27682,Male,32,Diploma,10,45,64,51,55,0.0,7,79,Urban,ML Engineer,47992,1 +27683,Male,43,Masters,4,30,43,53,60,7.0,2,36,Urban,Data Analyst,51745,0 +27684,Female,31,High School,2,64,19,73,88,7.0,7,85,Urban,HR Executive,148671,1 +27685,Male,43,Diploma,1,46,64,3,21,6.0,3,32,Semi-Urban,ML Engineer,43999,0 +27686,Male,57,High School,7,84,63,12,91,0.0,4,89,Urban,Data Analyst,138348,1 +27687,Female,41,High School,14,60,35,29,34,2.0,6,80,Urban,Data Analyst,80789,0 +27688,Male,29,High School,0,35,68,81,76,5.0,6,10,Urban,HR Executive,91998,0 +27689,Male,44,Bachelors,4,43,47,49,9,2.0,4,78,Urban,Software Engineer,124720,0 +27690,Male,27,Bachelors,10,49,39,33,66,9.0,1,53,Semi-Urban,Manager,124832,0 +27691,Female,38,High School,18,41,62,47,96,9.0,1,82,Urban,Software Engineer,82038,0 +27692,Female,26,Bachelors,18,23,81,67,61,1.0,6,79,Urban,Manager,100620,1 +27693,Male,42,Masters,14,26,69,71,3,9.0,5,43,Rural,ML Engineer,79755,0 +27694,Male,44,Bachelors,5,45,96,8,88,7.0,3,16,Semi-Urban,ML Engineer,71426,0 +27695,Male,55,Diploma,2,33,40,96,80,6.0,7,8,Urban,HR Executive,73790,0 +27696,Male,52,Bachelors,17,69,65,22,87,6.0,6,87,Urban,Data Analyst,77408,1 +27697,Female,38,Bachelors,6,59,17,82,30,1.0,0,54,Urban,ML Engineer,119024,0 +27698,Female,42,High School,10,57,56,20,7,0.0,7,81,Urban,HR Executive,145064,0 +27699,Male,57,Masters,16,62,8,78,2,5.0,1,85,Rural,Data Analyst,33740,0 +27700,Female,50,Masters,7,4,22,0,61,4.0,5,35,Urban,HR Executive,138055,0 +27701,Male,53,Diploma,11,6,88,45,57,3.0,5,27,Rural,Software Engineer,66292,0 +27702,Other,59,Bachelors,17,83,94,28,25,9.0,6,25,Urban,Manager,42600,0 +27703,Female,43,Bachelors,14,31,34,43,20,5.0,4,14,Semi-Urban,Software Engineer,76580,0 +27704,Male,22,Masters,16,6,78,10,80,3.0,1,5,Urban,HR Executive,99047,0 +27705,Female,29,Masters,2,40,19,18,88,7.0,7,2,Semi-Urban,ML Engineer,102840,0 +27706,Male,42,Bachelors,14,61,33,82,41,3.0,3,54,Semi-Urban,HR Executive,33316,0 +27707,Male,21,Bachelors,12,71,79,75,52,1.0,5,66,Semi-Urban,HR Executive,46326,1 +27708,Female,30,Bachelors,10,55,21,32,86,1.0,3,66,Urban,ML Engineer,53379,0 +27709,Male,52,Diploma,4,62,59,7,32,0.0,5,23,Semi-Urban,Software Engineer,91854,0 +27710,Male,27,High School,8,94,90,78,31,8.0,7,81,Urban,Manager,63975,1 +27711,Female,30,PhD,14,32,78,23,72,2.0,0,61,Urban,ML Engineer,143945,0 +27712,Female,36,Bachelors,16,66,36,69,44,2.0,0,39,Semi-Urban,Data Analyst,148001,0 +27713,Male,44,Masters,6,93,53,26,38,8.0,6,0,Semi-Urban,Software Engineer,134104,0 +27714,Male,24,Diploma,4,94,53,15,77,5.0,6,69,Urban,HR Executive,67656,0 +27715,Male,57,Bachelors,9,52,40,40,43,9.0,4,38,Urban,HR Executive,23060,0 +27716,Male,39,Bachelors,1,38,8,62,60,7.0,2,72,Urban,ML Engineer,145191,0 +27717,Female,21,Masters,11,42,83,11,20,1.0,1,35,Urban,Manager,111398,0 +27718,Male,45,Bachelors,17,11,66,28,24,5.0,1,93,Rural,ML Engineer,96657,0 +27719,Male,39,Masters,2,98,5,26,22,2.0,5,95,Urban,ML Engineer,136039,0 +27720,Male,47,PhD,19,36,10,86,43,2.0,2,55,Urban,HR Executive,116458,0 +27721,Male,46,Diploma,17,46,6,71,42,2.0,3,19,Rural,Manager,87400,0 +27722,Female,55,Diploma,2,66,41,19,59,6.0,1,34,Urban,HR Executive,141397,0 +27723,Male,39,High School,1,78,65,2,95,1.0,6,82,Semi-Urban,HR Executive,145284,0 +27724,Male,36,Diploma,5,4,58,64,62,3.0,7,54,Semi-Urban,Manager,40857,0 +27725,Female,48,Diploma,7,86,91,59,40,2.0,7,2,Urban,HR Executive,59348,0 +27726,Male,29,Bachelors,0,94,19,91,72,3.0,2,62,Urban,ML Engineer,52603,1 +27727,Male,37,Masters,12,95,56,64,26,7.0,7,64,Urban,HR Executive,138240,1 +27728,Male,21,High School,7,77,25,22,10,4.0,7,59,Urban,Software Engineer,79178,0 +27729,Male,36,Bachelors,15,57,52,44,32,6.0,0,48,Semi-Urban,Manager,115352,0 +27730,Male,47,Bachelors,18,1,84,1,80,5.0,3,30,Semi-Urban,Data Analyst,64541,0 +27731,Male,21,Bachelors,3,77,88,61,87,4.0,1,79,Urban,Manager,106661,1 +27732,Male,27,Diploma,12,37,39,35,72,4.0,5,59,Urban,Software Engineer,144389,0 +27733,Female,45,Diploma,17,45,47,42,11,4.0,6,78,Semi-Urban,ML Engineer,116691,0 +27734,Male,53,Bachelors,10,57,6,69,64,7.0,1,65,Urban,HR Executive,129494,0 +27735,Female,24,Masters,5,66,90,16,60,1.0,7,96,Semi-Urban,ML Engineer,130050,1 +27736,Female,48,Bachelors,6,68,34,27,88,6.0,6,84,Urban,Software Engineer,60299,0 +27737,Male,59,Diploma,0,88,12,98,21,4.0,4,58,Urban,HR Executive,112439,1 +27738,Male,43,Bachelors,17,30,35,97,80,9.0,0,3,Urban,Data Analyst,125029,0 +27739,Male,49,Masters,19,39,86,95,19,3.0,5,61,Semi-Urban,Data Analyst,137869,1 +27740,Male,51,Masters,19,39,24,13,9,5.0,4,9,Rural,Software Engineer,53855,0 +27741,Female,57,Bachelors,9,94,66,2,23,3.0,2,57,Urban,Software Engineer,49879,0 +27742,Male,28,Bachelors,5,91,52,87,32,1.0,5,13,Urban,Data Analyst,85157,1 +27743,Female,41,Masters,3,53,26,15,23,3.0,4,63,Urban,HR Executive,95877,0 +27744,Female,22,Bachelors,1,34,51,1,4,9.0,2,41,Urban,HR Executive,28206,0 +27745,Male,44,Diploma,5,2,20,88,64,6.0,7,63,Urban,Software Engineer,142353,0 +27746,Male,22,Masters,2,69,33,55,16,3.0,0,99,Rural,Software Engineer,147669,1 +27747,Male,48,High School,4,42,42,79,65,3.0,3,67,Rural,HR Executive,134101,0 +27748,Female,38,Bachelors,7,40,88,95,19,4.0,1,77,Urban,Manager,61641,1 +27749,Female,46,Bachelors,1,10,41,49,65,8.0,0,77,Urban,Data Analyst,84406,0 +27750,Male,29,Masters,4,91,7,69,91,0.0,6,74,Semi-Urban,Manager,76520,1 +27751,Male,59,Diploma,5,84,25,92,79,5.0,1,2,Semi-Urban,Data Analyst,48011,0 +27752,Male,31,Bachelors,0,20,74,76,95,0.0,3,24,Rural,ML Engineer,28165,0 +27753,Female,57,Masters,4,12,20,46,44,8.0,4,98,Urban,Manager,113254,0 +27754,Female,26,High School,16,2,8,36,20,4.0,6,77,Urban,Data Analyst,130825,0 +27755,Male,57,High School,1,58,38,98,98,0.0,6,25,Urban,Manager,135768,0 +27756,Male,51,Masters,10,33,56,83,19,0.0,2,64,Urban,Data Analyst,121870,1 +27757,Male,28,Diploma,12,91,47,40,93,5.0,7,25,Rural,HR Executive,51555,0 +27758,Male,40,Diploma,11,65,4,94,54,5.0,7,24,Semi-Urban,Data Analyst,112896,0 +27759,Female,32,High School,5,75,24,45,66,5.0,6,8,Urban,ML Engineer,23052,0 +27760,Male,52,High School,10,92,58,5,96,1.0,7,82,Urban,HR Executive,132254,1 +27761,Female,55,High School,14,63,7,46,42,4.0,1,73,Rural,HR Executive,71556,0 +27762,Male,28,Bachelors,15,20,13,75,87,8.0,1,12,Urban,Manager,38890,0 +27763,Male,30,Masters,11,71,43,88,48,3.0,3,73,Urban,Data Analyst,31462,1 +27764,Male,21,Masters,6,36,81,39,43,3.0,3,45,Urban,HR Executive,97101,0 +27765,Female,28,Bachelors,9,77,88,74,46,5.0,2,87,Urban,ML Engineer,85749,1 +27766,Female,34,Bachelors,2,63,13,35,96,5.0,0,47,Urban,ML Engineer,123266,0 +27767,Male,52,Diploma,19,96,57,76,12,9.0,0,60,Rural,Software Engineer,52315,1 +27768,Male,35,Masters,2,23,68,20,88,5.0,0,98,Rural,Manager,87649,0 +27769,Male,36,Bachelors,19,30,26,88,79,9.0,6,94,Semi-Urban,ML Engineer,142588,1 +27770,Male,57,Bachelors,1,29,22,7,25,3.0,2,31,Rural,HR Executive,101217,0 +27771,Female,53,Masters,17,64,13,44,96,1.0,1,6,Rural,HR Executive,35064,0 +27772,Male,46,Masters,19,72,9,55,4,5.0,2,61,Urban,Manager,22995,0 +27773,Male,42,Bachelors,2,53,80,80,80,6.0,2,38,Semi-Urban,Software Engineer,57494,1 +27774,Female,42,Bachelors,11,56,31,71,61,7.0,7,9,Rural,Data Analyst,42616,0 +27775,Male,54,Bachelors,8,95,25,94,97,0.0,2,23,Urban,ML Engineer,22557,1 +27776,Male,48,Bachelors,2,97,39,76,63,9.0,5,50,Semi-Urban,Data Analyst,41691,1 +27777,Male,40,High School,1,75,85,20,54,4.0,2,25,Semi-Urban,Data Analyst,48458,0 +27778,Female,27,Bachelors,18,34,88,88,0,1.0,6,9,Urban,HR Executive,84384,0 +27779,Male,36,Bachelors,8,66,14,92,3,3.0,2,79,Semi-Urban,Manager,70383,1 +27780,Male,37,Masters,16,31,5,58,48,7.0,2,39,Rural,HR Executive,138851,0 +27781,Female,47,Bachelors,6,63,76,29,86,6.0,2,45,Rural,ML Engineer,111946,0 +27782,Male,35,Bachelors,10,45,75,83,80,1.0,3,13,Semi-Urban,Manager,36592,0 +27783,Female,34,Bachelors,10,89,68,67,49,9.0,4,55,Urban,Data Analyst,126348,1 +27784,Female,36,Bachelors,0,40,28,19,13,7.0,5,66,Urban,Software Engineer,31164,0 +27785,Female,40,Diploma,17,2,0,2,97,3.0,4,13,Rural,Manager,24720,0 +27786,Female,33,Masters,19,45,4,63,11,3.0,5,30,Urban,Manager,76345,0 +27787,Male,45,PhD,5,73,45,94,34,5.0,3,32,Rural,HR Executive,43718,1 +27788,Male,55,Bachelors,18,97,57,55,92,2.0,7,65,Urban,Software Engineer,139424,1 +27789,Female,35,Diploma,19,12,47,16,54,2.0,1,16,Urban,Manager,115567,0 +27790,Male,26,Bachelors,8,99,90,63,68,9.0,3,90,Semi-Urban,Data Analyst,147701,1 +27791,Male,40,Bachelors,8,21,82,82,30,7.0,3,64,Semi-Urban,Software Engineer,104911,1 +27792,Female,47,Bachelors,8,41,97,53,61,4.0,3,50,Semi-Urban,Software Engineer,72547,1 +27793,Male,44,PhD,15,95,82,19,91,3.0,2,93,Urban,HR Executive,60173,1 +27794,Male,51,High School,14,30,10,58,13,1.0,7,41,Semi-Urban,Data Analyst,142038,0 +27795,Female,53,Bachelors,18,77,86,54,0,6.0,5,46,Semi-Urban,HR Executive,46641,1 +27796,Female,35,Diploma,12,16,29,17,37,8.0,2,59,Semi-Urban,Manager,125773,0 +27797,Female,48,Bachelors,12,20,42,63,19,7.0,5,1,Urban,HR Executive,37612,0 +27798,Female,32,Masters,14,69,46,97,66,4.0,6,92,Semi-Urban,Software Engineer,38169,1 +27799,Female,32,Bachelors,12,73,78,50,91,7.0,5,1,Urban,HR Executive,108981,0 +27800,Female,23,Masters,14,35,35,79,2,5.0,6,88,Semi-Urban,ML Engineer,136479,0 +27801,Male,28,PhD,10,82,25,94,27,7.0,1,26,Rural,Software Engineer,115569,0 +27802,Female,27,Masters,9,37,55,70,65,7.0,6,69,Semi-Urban,Manager,110251,0 +27803,Male,33,High School,7,12,47,95,60,6.0,1,71,Urban,Manager,114373,0 +27804,Male,36,High School,2,4,71,46,65,8.0,3,84,Semi-Urban,HR Executive,28795,0 +27805,Male,23,Bachelors,14,16,7,18,26,8.0,0,66,Urban,ML Engineer,93184,0 +27806,Male,22,Bachelors,18,20,62,74,30,3.0,5,51,Rural,Software Engineer,112009,0 +27807,Male,52,Diploma,0,40,86,2,73,7.0,4,42,Rural,HR Executive,107191,0 +27808,Male,28,High School,1,24,12,61,51,0.0,4,1,Rural,Data Analyst,50244,0 +27809,Male,47,PhD,14,64,79,17,76,8.0,4,31,Semi-Urban,ML Engineer,104715,0 +27810,Male,53,Diploma,13,94,20,5,71,1.0,6,54,Semi-Urban,Software Engineer,26145,0 +27811,Male,43,Bachelors,15,87,46,74,71,9.0,1,89,Urban,HR Executive,113188,1 +27812,Female,27,High School,0,69,91,51,69,4.0,6,97,Rural,HR Executive,30317,1 +27813,Female,59,High School,11,41,94,3,89,0.0,0,78,Rural,Data Analyst,24977,0 +27814,Female,49,Bachelors,17,75,43,0,3,3.0,3,45,Semi-Urban,ML Engineer,49345,0 +27815,Male,23,High School,8,14,2,22,87,2.0,6,74,Semi-Urban,Data Analyst,87588,0 +27816,Female,54,Bachelors,16,67,87,52,87,0.0,4,72,Urban,Software Engineer,147790,1 +27817,Male,37,High School,10,8,30,25,17,7.0,1,17,Urban,Manager,61961,0 +27818,Male,35,High School,0,54,24,35,21,6.0,7,27,Urban,HR Executive,78784,0 +27819,Female,40,Diploma,14,64,18,40,21,7.0,7,39,Rural,HR Executive,117141,0 +27820,Female,56,Bachelors,5,52,49,64,39,3.0,4,2,Urban,ML Engineer,116047,0 +27821,Female,42,Bachelors,0,1,24,74,71,2.0,4,5,Semi-Urban,Software Engineer,116978,0 +27822,Female,23,Bachelors,1,85,72,96,43,1.0,1,35,Rural,ML Engineer,111122,1 +27823,Male,26,Bachelors,3,16,96,30,25,6.0,6,81,Urban,ML Engineer,94969,0 +27824,Female,22,Bachelors,18,96,6,43,40,8.0,2,10,Urban,HR Executive,46050,0 +27825,Female,30,Diploma,2,82,23,20,49,1.0,1,94,Urban,Manager,116778,0 +27826,Female,39,High School,15,77,27,73,37,1.0,1,62,Urban,Manager,139019,0 +27827,Female,33,Masters,17,56,4,98,21,6.0,6,45,Rural,HR Executive,115425,0 +27828,Male,58,High School,16,72,71,7,57,3.0,1,27,Urban,Software Engineer,131156,0 +27829,Male,51,PhD,6,92,48,49,20,5.0,6,76,Rural,Software Engineer,67880,1 +27830,Male,47,High School,4,36,11,92,12,2.0,1,21,Urban,ML Engineer,134005,0 +27831,Male,42,Bachelors,12,21,18,62,80,1.0,0,46,Urban,HR Executive,77073,0 +27832,Male,27,Diploma,13,21,88,71,5,5.0,6,69,Urban,Manager,125452,1 +27833,Male,34,High School,12,14,20,26,20,4.0,7,90,Rural,Software Engineer,75100,0 +27834,Female,55,High School,18,39,57,56,97,3.0,7,0,Semi-Urban,ML Engineer,49712,0 +27835,Female,28,Bachelors,12,88,48,8,33,3.0,7,82,Semi-Urban,HR Executive,57875,0 +27836,Female,59,High School,17,42,0,76,79,5.0,7,4,Urban,Data Analyst,50761,0 +27837,Male,52,Bachelors,5,99,7,75,44,8.0,3,52,Rural,HR Executive,27681,0 +27838,Male,28,High School,14,61,36,44,71,0.0,7,11,Urban,HR Executive,130158,0 +27839,Female,57,Diploma,19,67,13,60,89,3.0,2,23,Semi-Urban,Manager,135120,0 +27840,Male,30,Bachelors,16,8,0,26,9,8.0,3,44,Semi-Urban,ML Engineer,97474,0 +27841,Female,58,Diploma,15,70,60,21,16,7.0,4,57,Rural,Software Engineer,51240,0 +27842,Female,42,Masters,9,31,96,98,46,5.0,0,37,Rural,ML Engineer,86155,1 +27843,Male,39,High School,19,65,48,56,36,6.0,3,97,Rural,ML Engineer,42154,1 +27844,Female,36,Diploma,15,12,17,93,93,7.0,4,28,Rural,ML Engineer,46773,0 +27845,Male,38,Diploma,8,90,87,2,42,0.0,2,10,Urban,Data Analyst,146874,0 +27846,Female,33,Diploma,5,16,49,43,39,9.0,1,8,Urban,Data Analyst,130868,0 +27847,Male,27,Diploma,15,60,22,18,26,6.0,3,73,Urban,Manager,47980,0 +27848,Male,30,Bachelors,15,67,96,87,80,3.0,3,76,Urban,Data Analyst,126107,1 +27849,Female,26,Masters,2,79,55,6,37,4.0,2,68,Rural,ML Engineer,79578,0 +27850,Female,22,High School,19,54,84,49,83,6.0,6,76,Urban,HR Executive,108646,1 +27851,Female,36,High School,15,75,60,66,88,5.0,7,70,Urban,Software Engineer,111500,1 +27852,Male,56,Bachelors,5,10,53,29,42,0.0,6,48,Urban,ML Engineer,144298,0 +27853,Female,55,Masters,5,67,65,34,48,4.0,3,15,Semi-Urban,ML Engineer,58712,0 +27854,Female,55,Masters,13,95,91,25,89,7.0,2,38,Urban,ML Engineer,62587,1 +27855,Other,51,Bachelors,12,87,86,35,84,3.0,1,36,Urban,Software Engineer,100203,1 +27856,Female,28,High School,17,44,25,41,8,8.0,2,53,Urban,Manager,48595,0 +27857,Female,22,Masters,11,92,14,52,15,1.0,1,7,Semi-Urban,Data Analyst,54027,0 +27858,Female,34,Masters,5,60,55,3,92,6.0,3,75,Urban,Data Analyst,129498,0 +27859,Male,38,Bachelors,3,93,35,47,39,5.0,5,11,Urban,Data Analyst,77718,0 +27860,Male,27,High School,9,34,63,3,51,3.0,7,27,Urban,HR Executive,41277,0 +27861,Male,33,Bachelors,19,30,22,27,61,2.0,7,99,Rural,Data Analyst,109520,0 +27862,Female,29,Bachelors,15,14,88,63,27,7.0,7,54,Semi-Urban,Manager,138240,0 +27863,Female,35,Bachelors,5,20,70,59,0,4.0,4,74,Urban,Software Engineer,75326,0 +27864,Female,29,High School,14,0,29,57,87,0.0,2,7,Rural,Software Engineer,39259,0 +27865,Male,24,High School,10,52,22,60,36,0.0,7,62,Urban,Manager,129291,0 +27866,Male,25,Diploma,3,81,77,92,26,7.0,2,61,Rural,ML Engineer,46563,1 +27867,Male,30,Masters,4,92,41,90,37,1.0,3,28,Urban,Software Engineer,30484,1 +27868,Male,40,Bachelors,17,62,30,68,7,6.0,5,3,Urban,Data Analyst,71942,0 +27869,Male,38,Bachelors,12,28,54,66,46,9.0,5,15,Urban,Manager,141152,0 +27870,Female,45,Bachelors,18,47,92,21,87,6.0,1,5,Urban,Manager,100335,0 +27871,Male,38,High School,9,98,34,93,98,6.0,5,86,Urban,Data Analyst,28258,1 +27872,Male,49,Bachelors,12,40,21,57,25,5.0,5,62,Urban,HR Executive,104113,0 +27873,Male,26,Bachelors,17,15,25,91,4,3.0,3,5,Urban,ML Engineer,125113,0 +27874,Other,38,PhD,16,15,79,40,13,7.0,7,81,Urban,Software Engineer,115432,0 +27875,Female,55,Masters,3,4,86,4,59,4.0,5,44,Urban,Software Engineer,117251,0 +27876,Male,29,High School,19,64,8,71,93,2.0,3,82,Urban,Manager,28679,0 +27877,Other,51,Bachelors,8,93,23,29,69,2.0,3,19,Semi-Urban,Data Analyst,34827,0 +27878,Male,47,Diploma,13,34,49,54,16,2.0,1,28,Urban,Software Engineer,124980,0 +27879,Male,26,Diploma,4,2,75,59,77,4.0,6,43,Urban,ML Engineer,99222,0 +27880,Male,30,High School,5,54,99,62,83,9.0,6,11,Urban,ML Engineer,42237,0 +27881,Male,58,Bachelors,18,60,81,76,72,9.0,6,77,Urban,HR Executive,147162,1 +27882,Female,37,High School,2,90,63,78,92,2.0,1,12,Semi-Urban,Data Analyst,148810,1 +27883,Female,25,PhD,8,23,9,43,31,4.0,5,69,Semi-Urban,Data Analyst,130603,0 +27884,Female,59,Bachelors,17,18,63,93,17,8.0,6,10,Semi-Urban,Software Engineer,66196,0 +27885,Male,50,Masters,8,70,71,8,34,7.0,1,48,Urban,HR Executive,69782,0 +27886,Male,41,Masters,18,73,39,37,80,7.0,4,80,Urban,HR Executive,143176,0 +27887,Male,45,Bachelors,0,0,19,10,66,9.0,7,50,Semi-Urban,Manager,42937,0 +27888,Male,46,Bachelors,7,10,19,47,54,4.0,4,14,Urban,ML Engineer,39623,0 +27889,Male,32,High School,11,80,79,63,38,3.0,0,84,Semi-Urban,Data Analyst,86814,1 +27890,Male,35,Bachelors,15,92,33,20,77,1.0,1,53,Rural,Software Engineer,115635,0 +27891,Female,22,Bachelors,3,6,95,87,29,9.0,7,57,Semi-Urban,Data Analyst,67818,1 +27892,Female,40,Bachelors,8,67,49,22,71,9.0,0,97,Rural,HR Executive,97236,0 +27893,Male,48,Diploma,4,77,43,76,31,4.0,7,50,Urban,Software Engineer,129108,1 +27894,Male,36,Diploma,13,46,63,40,49,5.0,1,71,Semi-Urban,Software Engineer,109144,0 +27895,Male,22,Bachelors,17,49,70,63,82,9.0,2,52,Urban,ML Engineer,121210,0 +27896,Male,45,High School,1,11,37,97,62,2.0,1,68,Semi-Urban,Software Engineer,109925,0 +27897,Male,51,PhD,3,74,0,32,72,8.0,0,37,Urban,Manager,73536,0 +27898,Male,40,Masters,0,5,84,29,99,0.0,3,96,Semi-Urban,Data Analyst,141413,0 +27899,Female,22,Masters,4,41,74,69,4,7.0,1,41,Urban,Data Analyst,31578,0 +27900,Female,58,Diploma,16,62,64,37,22,7.0,0,61,Semi-Urban,Manager,66929,0 +27901,Male,57,Bachelors,5,76,29,13,49,5.0,7,68,Urban,Software Engineer,113646,0 +27902,Female,58,Bachelors,7,90,32,74,94,0.0,7,61,Semi-Urban,Manager,64917,1 +27903,Male,32,Bachelors,11,51,14,24,90,5.0,0,35,Urban,Manager,108820,0 +27904,Female,28,Bachelors,9,58,24,42,84,0.0,4,38,Semi-Urban,Data Analyst,146467,0 +27905,Male,44,Bachelors,11,4,44,48,55,7.0,4,38,Semi-Urban,HR Executive,110346,0 +27906,Male,26,Diploma,18,45,5,30,40,0.0,6,7,Semi-Urban,ML Engineer,40697,0 +27907,Male,52,Masters,0,54,75,5,55,0.0,5,14,Urban,Software Engineer,92978,0 +27908,Male,53,Bachelors,18,77,26,78,59,7.0,1,73,Urban,Manager,127760,1 +27909,Male,39,Bachelors,11,68,80,4,78,7.0,4,92,Rural,ML Engineer,57319,1 +27910,Other,33,High School,8,9,17,98,85,3.0,5,5,Semi-Urban,Manager,141996,0 +27911,Female,57,Diploma,5,52,80,73,61,7.0,6,29,Urban,Software Engineer,35381,0 +27912,Male,33,PhD,18,19,50,5,27,1.0,4,65,Rural,Manager,81024,0 +27913,Male,37,Bachelors,16,80,84,53,31,2.0,2,59,Semi-Urban,HR Executive,92807,1 +27914,Female,47,Masters,10,22,82,78,3,6.0,4,96,Rural,HR Executive,97661,1 +27915,Female,38,Masters,8,6,16,91,95,2.0,5,58,Rural,Manager,43071,0 +27916,Female,41,Diploma,10,56,78,51,29,4.0,7,27,Rural,HR Executive,101419,0 +27917,Male,34,Masters,9,79,96,79,55,5.0,5,43,Urban,Manager,28235,1 +27918,Female,56,Bachelors,19,70,44,76,75,3.0,1,15,Rural,Data Analyst,124751,0 +27919,Female,28,Bachelors,3,45,79,43,10,7.0,3,52,Rural,Data Analyst,127047,0 +27920,Male,47,Bachelors,17,37,1,83,0,2.0,4,43,Urban,Data Analyst,40144,0 +27921,Male,29,Masters,16,17,82,24,48,5.0,5,24,Urban,ML Engineer,38455,0 +27922,Female,56,Masters,5,78,54,86,66,7.0,6,18,Semi-Urban,Manager,89689,0 +27923,Female,38,Bachelors,9,38,63,90,53,6.0,4,79,Semi-Urban,Software Engineer,70076,1 +27924,Male,59,Bachelors,9,22,45,75,84,5.0,5,91,Urban,HR Executive,84330,0 +27925,Other,32,Bachelors,5,84,28,9,20,9.0,2,19,Rural,HR Executive,142537,0 +27926,Male,36,Diploma,13,18,38,33,39,5.0,0,53,Urban,ML Engineer,80786,0 +27927,Male,49,Masters,9,2,19,7,79,9.0,3,92,Rural,Software Engineer,46283,0 +27928,Male,26,Bachelors,19,98,2,10,31,5.0,7,35,Semi-Urban,Manager,119635,0 +27929,Female,44,Masters,3,81,58,22,54,5.0,7,19,Rural,ML Engineer,51261,0 +27930,Male,42,High School,4,61,5,81,98,6.0,7,69,Rural,HR Executive,26997,0 +27931,Male,45,Bachelors,12,6,14,18,16,8.0,1,4,Urban,ML Engineer,20700,0 +27932,Male,55,Diploma,17,87,6,6,10,3.0,6,32,Urban,Manager,22495,0 +27933,Male,45,Bachelors,6,13,48,13,73,8.0,3,59,Urban,Manager,140450,0 +27934,Female,40,Masters,15,87,42,99,74,3.0,5,13,Urban,Software Engineer,99620,1 +27935,Male,59,Bachelors,16,27,26,85,22,4.0,5,75,Rural,ML Engineer,61388,0 +27936,Female,23,Masters,3,56,99,99,24,0.0,2,37,Urban,ML Engineer,109494,1 +27937,Female,25,Bachelors,13,0,71,44,58,7.0,2,15,Urban,Manager,26709,0 +27938,Male,36,Bachelors,1,34,21,49,85,8.0,3,35,Semi-Urban,Manager,124069,0 +27939,Female,41,High School,9,33,75,10,52,6.0,0,76,Semi-Urban,ML Engineer,139539,0 +27940,Male,52,Diploma,10,48,18,29,68,1.0,7,26,Urban,ML Engineer,86482,0 +27941,Male,35,Bachelors,8,63,68,23,76,3.0,4,78,Urban,Data Analyst,125535,0 +27942,Female,59,Bachelors,4,15,86,42,91,3.0,0,12,Semi-Urban,Manager,81212,0 +27943,Female,40,Diploma,5,51,44,22,17,1.0,4,4,Semi-Urban,Manager,118379,0 +27944,Male,58,Masters,16,71,64,87,93,3.0,2,34,Urban,Software Engineer,28759,1 +27945,Male,40,Masters,3,44,38,97,21,8.0,2,88,Urban,Manager,47071,1 +27946,Female,57,Diploma,3,26,52,33,62,9.0,0,63,Semi-Urban,ML Engineer,49355,0 +27947,Female,58,Masters,10,74,55,16,71,6.0,7,78,Rural,HR Executive,73456,0 +27948,Male,47,Bachelors,15,6,73,88,95,8.0,7,89,Urban,Manager,63964,1 +27949,Male,36,Diploma,13,50,59,89,15,1.0,4,21,Rural,Data Analyst,132770,0 +27950,Male,24,Diploma,13,5,22,82,58,5.0,2,77,Rural,Manager,62142,0 +27951,Male,51,Masters,11,99,55,32,8,5.0,2,70,Urban,Manager,116533,1 +27952,Male,35,PhD,17,90,12,64,23,8.0,0,39,Urban,Manager,94710,0 +27953,Male,47,Masters,3,49,30,62,1,0.0,3,66,Urban,HR Executive,20447,0 +27954,Male,47,Masters,2,51,39,91,95,9.0,1,79,Semi-Urban,Manager,113478,1 +27955,Female,48,Bachelors,3,39,80,2,6,3.0,7,26,Urban,Manager,125129,0 +27956,Male,46,Bachelors,2,54,98,71,52,8.0,6,75,Urban,ML Engineer,97733,1 +27957,Male,37,Masters,5,51,86,99,70,2.0,3,16,Urban,ML Engineer,67778,1 +27958,Male,49,Bachelors,1,13,38,83,53,2.0,5,41,Urban,Manager,37839,0 +27959,Male,59,Diploma,11,88,47,89,75,5.0,6,0,Rural,Manager,54389,0 +27960,Male,50,Bachelors,14,99,44,91,50,0.0,6,82,Semi-Urban,HR Executive,96189,1 +27961,Female,46,Diploma,18,71,10,22,86,1.0,4,3,Urban,Manager,49589,0 +27962,Male,34,Bachelors,8,69,96,59,90,9.0,1,29,Rural,ML Engineer,122288,1 +27963,Male,31,Masters,2,21,7,83,8,1.0,1,16,Semi-Urban,Software Engineer,122828,0 +27964,Male,28,Masters,11,95,36,46,59,1.0,1,82,Urban,Software Engineer,73817,1 +27965,Male,33,PhD,8,1,39,77,35,6.0,3,27,Urban,Data Analyst,36032,0 +27966,Male,21,High School,15,88,75,77,29,0.0,0,82,Rural,HR Executive,37526,1 +27967,Male,21,High School,5,15,41,13,23,2.0,3,77,Urban,ML Engineer,114696,0 +27968,Male,58,High School,14,8,55,77,25,6.0,2,30,Urban,Data Analyst,86173,0 +27969,Female,28,Masters,9,59,61,38,22,7.0,6,80,Urban,Data Analyst,134917,0 +27970,Other,53,Bachelors,16,66,49,87,41,7.0,2,25,Rural,HR Executive,130586,0 +27971,Male,39,Masters,17,0,52,75,74,9.0,1,60,Urban,HR Executive,90632,0 +27972,Female,48,Masters,4,7,39,10,15,2.0,4,35,Rural,Manager,25552,0 +27973,Female,51,Bachelors,8,43,90,18,49,6.0,6,96,Semi-Urban,Data Analyst,51026,1 +27974,Female,41,Bachelors,1,35,97,71,24,3.0,3,65,Semi-Urban,ML Engineer,135313,1 +27975,Male,42,Masters,15,16,65,65,2,7.0,7,1,Urban,Software Engineer,132032,0 +27976,Female,42,Masters,4,66,41,88,61,0.0,3,20,Urban,ML Engineer,60392,0 +27977,Female,28,Masters,17,86,23,68,72,6.0,2,78,Urban,HR Executive,47962,1 +27978,Male,24,PhD,12,51,9,2,16,4.0,4,57,Semi-Urban,HR Executive,98181,0 +27979,Male,27,Diploma,18,69,67,9,83,8.0,4,18,Urban,Manager,90355,0 +27980,Other,57,Bachelors,12,84,97,89,62,7.0,3,19,Rural,Data Analyst,143231,1 +27981,Female,36,Masters,18,66,21,62,5,2.0,4,60,Urban,Manager,25047,0 +27982,Male,51,Bachelors,14,92,84,31,35,3.0,3,38,Urban,Manager,120190,1 +27983,Female,30,PhD,1,35,23,26,43,2.0,3,44,Urban,Data Analyst,140430,0 +27984,Male,42,High School,3,87,83,17,29,3.0,6,3,Semi-Urban,Software Engineer,110180,0 +27985,Male,34,Bachelors,8,78,34,60,12,4.0,0,79,Semi-Urban,ML Engineer,130198,1 +27986,Male,26,High School,11,14,84,43,48,1.0,5,95,Urban,Manager,28887,1 +27987,Male,31,Diploma,3,92,55,63,83,7.0,0,53,Urban,Software Engineer,20154,1 +27988,Female,56,High School,6,81,54,26,25,2.0,2,0,Rural,Data Analyst,87129,0 +27989,Male,58,Bachelors,1,91,11,70,9,2.0,2,28,Semi-Urban,Data Analyst,21116,0 +27990,Female,51,Bachelors,2,70,1,50,57,9.0,5,24,Urban,Data Analyst,77928,0 +27991,Male,42,High School,5,10,24,93,65,9.0,6,98,Urban,Manager,134630,0 +27992,Male,38,Bachelors,14,58,14,73,77,0.0,6,81,Urban,Manager,32337,0 +27993,Male,21,Bachelors,7,5,83,31,30,6.0,0,97,Urban,ML Engineer,127274,0 +27994,Male,21,Bachelors,11,29,75,76,53,3.0,0,73,Urban,ML Engineer,53138,1 +27995,Female,51,Bachelors,10,64,2,42,8,0.0,3,28,Urban,HR Executive,91268,0 +27996,Male,47,Diploma,17,52,14,14,62,7.0,3,33,Urban,ML Engineer,83504,0 +27997,Female,34,PhD,16,49,52,53,68,1.0,1,39,Semi-Urban,Software Engineer,62272,0 +27998,Male,22,Bachelors,14,72,45,69,95,1.0,1,62,Urban,Software Engineer,52526,1 +27999,Male,39,Diploma,13,91,7,77,7,5.0,2,81,Urban,ML Engineer,144421,1 +28000,Male,29,High School,7,57,41,70,82,4.0,5,80,Semi-Urban,Manager,68672,1 +28001,Female,31,Masters,11,45,85,43,12,6.0,1,50,Urban,Data Analyst,121841,0 +28002,Male,52,Masters,13,21,59,52,67,8.0,5,96,Rural,Manager,71607,0 +28003,Female,23,Masters,4,74,59,77,43,4.0,7,76,Semi-Urban,Manager,77309,1 +28004,Female,49,Diploma,17,60,73,72,66,1.0,6,59,Urban,Software Engineer,103738,1 +28005,Male,39,Masters,10,20,14,29,44,2.0,2,83,Semi-Urban,ML Engineer,41936,0 +28006,Male,51,Bachelors,4,15,14,96,31,3.0,1,94,Urban,Software Engineer,139434,0 +28007,Male,21,Bachelors,12,91,24,53,40,0.0,0,49,Urban,HR Executive,94778,0 +28008,Female,43,Diploma,18,23,94,44,82,1.0,7,7,Urban,Software Engineer,50957,0 +28009,Male,24,PhD,2,31,63,82,43,0.0,1,51,Urban,Software Engineer,97828,0 +28010,Male,27,Bachelors,5,16,91,10,89,8.0,1,9,Urban,Data Analyst,131772,0 +28011,Male,58,Masters,11,96,21,83,99,5.0,6,98,Urban,HR Executive,114146,1 +28012,Female,44,Masters,14,1,64,5,65,6.0,4,63,Urban,HR Executive,33405,0 +28013,Female,44,Bachelors,17,40,72,31,7,4.0,1,57,Semi-Urban,Manager,38610,0 +28014,Female,31,Bachelors,5,53,32,13,16,0.0,0,46,Rural,Manager,146485,0 +28015,Female,55,High School,14,47,32,64,56,6.0,6,23,Urban,ML Engineer,64440,0 +28016,Male,51,Masters,16,96,72,83,86,9.0,7,29,Urban,Manager,105697,1 +28017,Male,49,Bachelors,7,10,49,10,95,6.0,4,7,Urban,Manager,57241,0 +28018,Female,26,Bachelors,12,40,0,38,35,1.0,2,80,Rural,Data Analyst,133875,0 +28019,Female,33,Masters,12,97,72,54,7,3.0,2,3,Urban,Data Analyst,105322,0 +28020,Male,21,Bachelors,5,91,13,64,68,2.0,2,68,Semi-Urban,HR Executive,54382,1 +28021,Male,37,Bachelors,12,64,94,76,35,1.0,0,58,Urban,ML Engineer,50410,1 +28022,Female,46,Masters,17,36,42,73,69,0.0,7,63,Urban,Software Engineer,110419,0 +28023,Male,50,Bachelors,7,94,58,50,57,6.0,5,95,Urban,Data Analyst,70481,1 +28024,Male,40,Bachelors,18,20,91,69,31,7.0,3,33,Semi-Urban,Software Engineer,130709,0 +28025,Female,56,Masters,5,23,95,22,93,8.0,5,9,Rural,HR Executive,50220,0 +28026,Female,34,Bachelors,2,64,66,11,49,2.0,7,93,Semi-Urban,Software Engineer,47516,0 +28027,Male,43,Bachelors,1,85,93,18,68,5.0,5,29,Semi-Urban,HR Executive,78700,0 +28028,Male,57,Bachelors,6,65,88,30,76,3.0,6,33,Urban,Software Engineer,100292,0 +28029,Male,51,Bachelors,12,62,1,19,91,4.0,1,90,Urban,ML Engineer,80352,0 +28030,Female,45,Bachelors,18,19,57,8,85,1.0,4,33,Urban,HR Executive,84257,0 +28031,Other,57,Diploma,1,42,20,6,73,1.0,2,0,Urban,HR Executive,67297,0 +28032,Female,30,Bachelors,1,58,23,87,59,0.0,0,33,Urban,Software Engineer,45504,0 +28033,Male,33,Masters,5,45,67,76,4,8.0,6,85,Rural,Data Analyst,29301,1 +28034,Male,52,High School,5,85,8,38,54,5.0,2,96,Urban,ML Engineer,136864,0 +28035,Female,26,Bachelors,6,79,77,84,45,5.0,1,85,Urban,Software Engineer,48970,1 +28036,Male,39,High School,14,7,41,62,48,7.0,1,77,Urban,Manager,25022,0 +28037,Female,34,Bachelors,8,73,46,88,75,6.0,5,85,Urban,Data Analyst,75356,1 +28038,Female,57,Bachelors,18,6,20,19,61,2.0,7,54,Semi-Urban,HR Executive,86091,0 +28039,Male,59,Masters,16,3,92,88,4,4.0,7,64,Urban,ML Engineer,51420,1 +28040,Female,39,Masters,17,53,65,72,38,1.0,5,92,Urban,Data Analyst,146527,1 +28041,Male,43,High School,6,78,86,91,75,1.0,4,31,Urban,ML Engineer,71623,1 +28042,Female,42,Diploma,14,9,30,85,25,3.0,7,57,Urban,Data Analyst,52431,0 +28043,Male,46,Diploma,0,11,84,69,79,5.0,6,68,Semi-Urban,Manager,44629,0 +28044,Female,28,High School,12,33,60,10,21,3.0,2,10,Rural,Data Analyst,70303,0 +28045,Female,22,Bachelors,12,89,96,42,94,1.0,3,16,Rural,Software Engineer,98250,1 +28046,Male,30,Bachelors,11,43,86,25,59,7.0,7,74,Semi-Urban,Data Analyst,140234,0 +28047,Male,56,Bachelors,8,94,75,54,54,5.0,6,66,Urban,HR Executive,135906,1 +28048,Male,54,Diploma,12,12,42,62,43,1.0,2,57,Urban,Software Engineer,83674,0 +28049,Male,26,Bachelors,2,97,87,14,77,5.0,5,79,Urban,ML Engineer,51427,1 +28050,Female,49,Bachelors,15,38,87,4,90,8.0,3,24,Semi-Urban,HR Executive,35051,0 +28051,Male,47,PhD,6,11,12,31,21,8.0,2,33,Rural,Manager,131027,0 +28052,Male,59,PhD,9,10,77,70,29,9.0,6,83,Urban,Data Analyst,58815,1 +28053,Male,56,Masters,11,78,32,48,66,6.0,5,76,Urban,Manager,28687,0 +28054,Male,38,Bachelors,2,34,0,67,72,7.0,2,85,Semi-Urban,Manager,54993,0 +28055,Female,26,Bachelors,5,68,41,4,28,3.0,1,17,Semi-Urban,Software Engineer,78064,0 +28056,Male,37,Diploma,5,51,94,88,61,7.0,1,73,Urban,Manager,97691,1 +28057,Female,51,Bachelors,3,43,78,76,25,8.0,2,77,Urban,Data Analyst,30911,1 +28058,Female,34,Diploma,1,62,81,41,39,7.0,5,73,Urban,ML Engineer,131743,1 +28059,Male,44,Bachelors,0,15,66,76,82,2.0,3,26,Urban,Software Engineer,121969,0 +28060,Female,38,Bachelors,16,48,89,46,2,3.0,4,45,Urban,Manager,65447,0 +28061,Male,40,Masters,16,37,91,34,61,4.0,1,18,Urban,Data Analyst,31847,0 +28062,Male,31,High School,1,42,25,60,34,7.0,3,6,Semi-Urban,Data Analyst,107700,0 +28063,Male,52,Bachelors,9,47,51,80,46,7.0,5,39,Semi-Urban,ML Engineer,145537,0 +28064,Male,46,Bachelors,18,75,84,14,14,3.0,1,3,Urban,HR Executive,29536,0 +28065,Female,23,Masters,4,60,53,75,36,5.0,6,47,Semi-Urban,Software Engineer,131881,0 +28066,Male,50,High School,15,47,19,71,3,9.0,4,76,Urban,HR Executive,131414,0 +28067,Male,48,Diploma,13,34,88,47,84,0.0,1,93,Urban,ML Engineer,24536,1 +28068,Male,27,Masters,7,83,96,20,36,4.0,1,3,Semi-Urban,Data Analyst,149764,0 +28069,Male,34,Bachelors,1,10,32,77,40,9.0,2,4,Urban,Manager,58380,0 +28070,Female,24,Masters,8,61,80,81,17,6.0,5,87,Semi-Urban,Software Engineer,147307,1 +28071,Male,51,Bachelors,8,23,57,31,69,2.0,5,62,Urban,HR Executive,67302,0 +28072,Female,48,Masters,13,88,86,35,11,2.0,2,31,Semi-Urban,Software Engineer,71836,0 +28073,Other,57,Diploma,14,65,51,91,14,7.0,1,76,Rural,HR Executive,27751,1 +28074,Male,31,Masters,17,56,61,12,54,1.0,2,78,Rural,Software Engineer,118985,0 +28075,Female,38,Bachelors,0,37,85,35,43,1.0,5,20,Rural,ML Engineer,61563,0 +28076,Male,27,Masters,10,96,79,12,58,2.0,6,71,Semi-Urban,Software Engineer,104319,1 +28077,Male,51,Masters,15,48,41,6,37,9.0,2,11,Rural,Manager,20908,0 +28078,Male,33,Bachelors,11,46,94,73,94,1.0,4,35,Urban,HR Executive,136111,1 +28079,Male,27,Diploma,14,90,54,20,31,4.0,4,73,Urban,Software Engineer,132910,1 +28080,Other,57,Bachelors,16,8,2,14,18,4.0,6,19,Semi-Urban,HR Executive,77617,0 +28081,Male,50,Bachelors,12,38,69,75,25,3.0,7,77,Urban,HR Executive,94187,1 +28082,Female,54,Diploma,12,3,64,63,18,4.0,4,61,Rural,Manager,94757,0 +28083,Male,24,Bachelors,18,59,9,89,50,7.0,7,88,Urban,ML Engineer,83971,1 +28084,Female,55,High School,15,48,17,64,98,3.0,5,64,Urban,HR Executive,141612,0 +28085,Male,40,High School,17,6,47,32,40,7.0,6,67,Urban,Manager,98430,0 +28086,Female,51,Bachelors,11,25,65,47,63,5.0,7,10,Semi-Urban,Manager,33945,0 +28087,Male,21,Diploma,19,21,78,98,90,3.0,6,50,Urban,ML Engineer,49988,1 +28088,Female,45,Bachelors,15,22,98,47,50,8.0,3,81,Semi-Urban,Manager,116725,1 +28089,Female,27,Diploma,6,69,2,85,54,5.0,7,22,Semi-Urban,Software Engineer,50553,0 +28090,Female,35,Bachelors,14,77,62,33,25,2.0,0,24,Urban,Manager,39777,0 +28091,Male,29,Bachelors,9,78,35,0,67,3.0,4,84,Rural,HR Executive,78249,0 +28092,Male,41,Masters,9,57,54,9,3,8.0,0,53,Rural,HR Executive,106134,0 +28093,Female,27,High School,8,15,61,86,22,5.0,1,46,Urban,Software Engineer,137441,0 +28094,Male,25,Diploma,19,48,0,65,46,7.0,6,3,Rural,Software Engineer,123702,0 +28095,Male,47,Bachelors,12,41,31,49,3,6.0,0,5,Rural,Data Analyst,136625,0 +28096,Male,22,Diploma,18,65,62,86,80,5.0,6,81,Urban,Software Engineer,89063,1 +28097,Male,35,Bachelors,15,56,96,92,40,9.0,6,24,Urban,ML Engineer,46766,1 +28098,Male,24,Diploma,6,60,70,51,81,0.0,3,81,Rural,Software Engineer,81527,1 +28099,Male,29,High School,15,4,36,34,46,7.0,3,46,Urban,Manager,74301,0 +28100,Male,41,Bachelors,0,57,3,97,35,4.0,0,91,Semi-Urban,Software Engineer,42943,1 +28101,Male,39,Diploma,13,78,53,3,52,4.0,6,91,Urban,Software Engineer,38816,0 +28102,Male,51,Diploma,1,87,85,45,6,4.0,4,69,Urban,HR Executive,129950,1 +28103,Male,42,Masters,15,17,33,49,86,7.0,0,27,Urban,HR Executive,30064,0 +28104,Female,32,High School,11,7,42,88,16,3.0,5,60,Urban,HR Executive,56202,0 +28105,Male,55,Masters,6,82,87,81,84,0.0,4,16,Rural,Software Engineer,103034,1 +28106,Female,34,High School,13,77,49,14,99,4.0,0,33,Urban,HR Executive,87854,0 +28107,Male,49,Diploma,19,18,12,64,6,8.0,4,40,Urban,Manager,93109,0 +28108,Male,36,High School,6,55,7,10,3,9.0,1,74,Rural,Software Engineer,121471,0 +28109,Male,52,High School,2,53,80,59,24,0.0,4,93,Urban,Data Analyst,54219,1 +28110,Male,28,Bachelors,12,80,76,97,39,6.0,0,63,Urban,Software Engineer,23357,1 +28111,Female,56,Bachelors,16,56,16,94,80,0.0,6,70,Semi-Urban,Software Engineer,98569,0 +28112,Male,56,Diploma,9,84,40,9,34,9.0,0,34,Urban,HR Executive,79841,0 +28113,Female,29,High School,14,80,63,37,33,0.0,5,8,Semi-Urban,HR Executive,28441,0 +28114,Female,29,High School,19,40,40,95,43,2.0,2,37,Rural,Software Engineer,117891,0 +28115,Male,47,Diploma,0,90,80,75,95,2.0,4,77,Urban,HR Executive,116647,1 +28116,Male,41,Bachelors,16,18,75,83,72,7.0,7,99,Rural,HR Executive,131143,1 +28117,Male,51,Bachelors,1,77,84,88,65,9.0,5,31,Urban,HR Executive,65954,1 +28118,Female,34,Masters,19,49,15,34,80,7.0,5,56,Urban,Software Engineer,130028,0 +28119,Female,45,Bachelors,17,65,65,58,80,8.0,5,52,Semi-Urban,HR Executive,106809,0 +28120,Female,27,Bachelors,14,48,60,13,97,3.0,7,25,Urban,Manager,148470,0 +28121,Male,33,Bachelors,5,75,15,97,7,6.0,4,45,Rural,Software Engineer,142239,0 +28122,Female,22,High School,6,20,67,16,53,9.0,2,57,Rural,ML Engineer,61430,0 +28123,Female,55,Masters,10,26,82,86,42,5.0,0,59,Urban,Manager,123163,1 +28124,Male,29,Masters,15,52,76,76,38,8.0,7,98,Urban,Manager,103277,1 +28125,Male,32,Diploma,4,86,90,17,2,8.0,6,89,Urban,ML Engineer,82223,1 +28126,Male,31,Bachelors,8,50,59,46,57,9.0,3,2,Rural,ML Engineer,141025,0 +28127,Male,36,High School,5,92,24,28,64,0.0,0,99,Urban,HR Executive,56684,1 +28128,Female,22,Masters,4,72,52,73,25,5.0,7,78,Semi-Urban,ML Engineer,76090,1 +28129,Male,57,Bachelors,6,56,76,33,36,7.0,5,14,Urban,Software Engineer,120400,0 +28130,Male,26,Bachelors,6,97,34,85,72,0.0,5,65,Urban,HR Executive,64609,1 +28131,Male,31,Masters,18,97,52,46,35,2.0,1,94,Urban,Data Analyst,74183,1 +28132,Male,36,Bachelors,6,14,85,40,49,1.0,3,21,Urban,Manager,21748,0 +28133,Male,27,Masters,14,32,55,66,45,3.0,1,92,Urban,Data Analyst,79705,1 +28134,Other,55,High School,13,8,99,64,23,4.0,2,37,Urban,Data Analyst,110869,0 +28135,Male,42,Diploma,3,98,55,58,3,8.0,5,9,Semi-Urban,ML Engineer,141526,0 +28136,Male,28,Masters,10,86,30,29,13,4.0,7,66,Rural,ML Engineer,135960,0 +28137,Female,26,Diploma,4,85,97,0,39,1.0,4,7,Semi-Urban,Data Analyst,87191,0 +28138,Male,55,Masters,8,77,63,81,94,9.0,7,13,Urban,ML Engineer,30872,0 +28139,Male,40,Masters,5,62,31,92,79,3.0,3,74,Urban,Manager,110586,1 +28140,Male,56,Masters,6,46,39,85,56,6.0,2,78,Semi-Urban,Data Analyst,95789,1 +28141,Male,31,Bachelors,4,1,72,60,64,9.0,6,81,Rural,HR Executive,81386,0 +28142,Male,35,Masters,13,96,26,39,77,3.0,4,32,Semi-Urban,Manager,83888,0 +28143,Male,39,Bachelors,3,86,71,97,84,2.0,3,34,Rural,Software Engineer,83453,1 +28144,Male,56,Diploma,7,31,43,58,47,9.0,3,54,Rural,Software Engineer,44639,0 +28145,Female,35,Bachelors,3,53,69,28,3,4.0,7,71,Semi-Urban,Software Engineer,43461,0 +28146,Male,22,Bachelors,8,23,64,55,87,5.0,7,37,Semi-Urban,Data Analyst,46555,0 +28147,Female,26,Bachelors,17,11,35,65,79,2.0,3,48,Urban,Software Engineer,133765,0 +28148,Male,32,Bachelors,9,29,54,78,71,1.0,0,91,Urban,Manager,130008,1 +28149,Male,33,Masters,3,55,90,68,64,9.0,4,14,Urban,Manager,86579,0 +28150,Other,42,Masters,17,8,84,22,82,1.0,0,75,Semi-Urban,Data Analyst,95991,0 +28151,Male,32,Bachelors,19,80,64,55,96,1.0,7,78,Urban,Data Analyst,25195,1 +28152,Male,56,Bachelors,8,96,16,66,70,9.0,0,88,Rural,HR Executive,62273,1 +28153,Male,51,Diploma,7,86,96,14,52,8.0,6,69,Semi-Urban,HR Executive,127475,1 +28154,Female,26,High School,6,98,35,11,11,9.0,0,88,Semi-Urban,HR Executive,76972,0 +28155,Male,30,High School,14,99,26,33,40,2.0,5,41,Semi-Urban,Manager,137082,0 +28156,Male,26,Bachelors,6,14,98,51,12,2.0,6,68,Urban,ML Engineer,83969,0 +28157,Male,50,High School,3,26,9,85,75,7.0,6,25,Semi-Urban,Data Analyst,110534,0 +28158,Female,26,Diploma,0,83,56,15,0,8.0,5,87,Semi-Urban,HR Executive,127019,1 +28159,Male,49,Bachelors,13,74,39,2,66,0.0,0,24,Semi-Urban,HR Executive,27251,0 +28160,Male,35,Bachelors,1,81,46,95,26,8.0,0,69,Rural,HR Executive,45855,1 +28161,Male,26,Bachelors,19,25,62,40,55,6.0,4,14,Urban,Software Engineer,36817,0 +28162,Female,22,Bachelors,3,46,75,64,2,1.0,5,46,Urban,Data Analyst,136088,0 +28163,Male,55,Masters,17,84,6,95,39,2.0,2,53,Urban,Software Engineer,46394,1 +28164,Male,33,High School,1,76,31,50,13,9.0,0,33,Semi-Urban,HR Executive,116363,0 +28165,Female,54,Bachelors,6,63,3,72,89,2.0,6,31,Urban,Manager,44446,0 +28166,Male,40,Masters,14,43,92,73,11,4.0,1,32,Urban,ML Engineer,72024,1 +28167,Female,22,Bachelors,18,11,51,54,40,0.0,0,99,Semi-Urban,ML Engineer,65235,0 +28168,Other,48,Bachelors,6,47,33,74,21,9.0,7,26,Urban,Manager,135398,0 +28169,Female,59,Bachelors,1,23,40,69,97,1.0,7,14,Semi-Urban,ML Engineer,54040,0 +28170,Male,50,Diploma,8,17,29,99,1,5.0,1,15,Urban,Data Analyst,127485,0 +28171,Male,31,Bachelors,4,57,51,97,46,2.0,6,66,Urban,Manager,99137,1 +28172,Male,48,Diploma,8,92,69,65,54,2.0,7,87,Semi-Urban,HR Executive,83974,1 +28173,Female,56,Bachelors,12,20,51,42,64,1.0,1,86,Rural,ML Engineer,120881,0 +28174,Other,42,Bachelors,1,60,54,47,8,5.0,6,51,Rural,ML Engineer,107470,0 +28175,Male,37,Bachelors,1,42,72,18,43,6.0,4,51,Semi-Urban,Data Analyst,44435,0 +28176,Female,54,High School,14,66,35,15,68,9.0,0,89,Urban,HR Executive,45272,0 +28177,Female,52,Masters,19,76,32,24,15,7.0,7,52,Urban,Data Analyst,87887,0 +28178,Male,40,Bachelors,16,54,35,33,18,3.0,1,77,Rural,Software Engineer,24022,0 +28179,Male,23,Diploma,16,74,94,72,15,2.0,3,79,Rural,Data Analyst,70904,1 +28180,Male,31,PhD,5,99,44,66,93,0.0,1,39,Rural,ML Engineer,125921,1 +28181,Male,43,Diploma,4,7,72,0,52,4.0,2,36,Urban,HR Executive,24422,0 +28182,Female,29,Diploma,19,19,82,21,83,8.0,1,75,Urban,Software Engineer,94011,0 +28183,Female,41,Masters,18,58,3,42,18,0.0,5,60,Rural,ML Engineer,145621,0 +28184,Male,22,Diploma,6,64,13,21,2,4.0,4,38,Urban,Manager,119485,0 +28185,Male,53,Bachelors,10,88,93,70,93,1.0,4,18,Urban,Data Analyst,59184,1 +28186,Male,38,Bachelors,5,81,53,64,28,1.0,7,41,Urban,Manager,50477,1 +28187,Female,53,Bachelors,8,32,59,76,50,5.0,3,7,Urban,Data Analyst,25770,0 +28188,Female,49,Bachelors,4,81,51,7,5,8.0,2,52,Rural,Data Analyst,60136,0 +28189,Male,36,Bachelors,4,8,10,96,47,0.0,3,21,Urban,Data Analyst,147073,0 +28190,Male,46,Diploma,1,20,19,56,77,4.0,2,35,Urban,HR Executive,82031,0 +28191,Male,39,Bachelors,2,77,87,29,40,5.0,6,30,Urban,Manager,74416,0 +28192,Male,28,Bachelors,2,91,82,97,29,2.0,4,75,Rural,Data Analyst,142727,1 +28193,Other,40,High School,18,0,0,54,5,3.0,4,41,Rural,ML Engineer,117753,0 +28194,Male,43,Diploma,14,97,67,27,2,2.0,3,32,Semi-Urban,ML Engineer,79174,0 +28195,Male,34,Diploma,2,17,50,42,61,5.0,5,89,Urban,Data Analyst,101392,0 +28196,Male,47,Bachelors,16,18,69,87,34,0.0,1,57,Urban,Software Engineer,48173,0 +28197,Male,41,Diploma,3,95,41,88,14,7.0,3,61,Rural,ML Engineer,22196,1 +28198,Male,24,High School,1,99,21,51,18,3.0,3,43,Urban,Manager,123660,0 +28199,Male,35,High School,4,13,68,99,28,9.0,1,40,Rural,Software Engineer,50276,0 +28200,Female,29,Bachelors,16,85,94,60,2,0.0,1,80,Urban,HR Executive,136289,1 +28201,Male,57,Masters,5,2,6,97,91,3.0,5,40,Rural,Software Engineer,24860,0 +28202,Male,46,Diploma,3,38,9,88,55,1.0,3,65,Urban,Data Analyst,69327,0 +28203,Male,30,High School,18,27,72,72,22,5.0,3,46,Urban,ML Engineer,63742,0 +28204,Female,30,Bachelors,5,64,40,10,6,9.0,4,69,Semi-Urban,Data Analyst,43208,0 +28205,Male,45,Bachelors,7,68,75,82,14,0.0,2,52,Urban,Manager,107986,1 +28206,Female,30,High School,15,63,30,77,65,9.0,1,93,Semi-Urban,Data Analyst,57947,1 +28207,Male,59,Bachelors,0,34,66,53,42,0.0,3,84,Urban,HR Executive,59076,1 +28208,Male,34,Masters,19,29,69,80,63,1.0,7,43,Semi-Urban,ML Engineer,20486,0 +28209,Male,29,Diploma,10,91,44,15,54,6.0,0,22,Semi-Urban,HR Executive,105356,0 +28210,Other,27,Diploma,17,22,98,75,88,2.0,1,76,Urban,ML Engineer,71784,1 +28211,Male,55,Masters,12,55,87,83,29,4.0,5,18,Urban,ML Engineer,137043,1 +28212,Male,30,Masters,17,58,88,18,97,5.0,4,42,Semi-Urban,Data Analyst,95191,0 +28213,Male,47,PhD,11,27,52,82,15,6.0,3,37,Semi-Urban,Data Analyst,119530,0 +28214,Male,23,High School,10,97,0,84,51,7.0,5,58,Urban,HR Executive,140363,1 +28215,Male,30,Bachelors,10,41,32,42,17,7.0,3,84,Urban,Data Analyst,72871,0 +28216,Male,39,Bachelors,4,89,21,55,29,1.0,0,47,Rural,Software Engineer,112624,0 +28217,Male,39,PhD,3,17,82,30,56,1.0,2,80,Urban,Manager,27048,0 +28218,Male,32,High School,7,84,93,8,49,2.0,4,23,Semi-Urban,Software Engineer,134500,0 +28219,Male,48,Masters,19,56,13,53,23,5.0,3,5,Rural,ML Engineer,92779,0 +28220,Male,57,Diploma,15,53,70,34,11,4.0,6,10,Rural,ML Engineer,109758,0 +28221,Male,22,Bachelors,7,60,2,49,23,5.0,6,43,Semi-Urban,Manager,80966,0 +28222,Male,49,High School,4,38,76,51,93,3.0,3,75,Urban,HR Executive,91438,1 +28223,Male,35,Masters,13,20,50,6,59,5.0,2,54,Rural,Software Engineer,145157,0 +28224,Male,45,Bachelors,8,27,25,82,73,0.0,1,87,Rural,Software Engineer,92187,0 +28225,Male,40,Bachelors,13,13,12,0,83,7.0,3,36,Urban,Software Engineer,25110,0 +28226,Female,42,High School,4,90,58,4,25,0.0,7,26,Rural,Data Analyst,129692,0 +28227,Male,47,Diploma,4,64,94,60,71,5.0,5,93,Urban,Software Engineer,97434,1 +28228,Female,23,PhD,15,42,28,44,92,5.0,1,52,Rural,ML Engineer,34046,0 +28229,Male,22,Bachelors,12,88,42,32,45,3.0,2,84,Semi-Urban,Manager,48242,1 +28230,Male,31,Bachelors,19,59,75,2,89,1.0,3,10,Semi-Urban,Manager,85039,0 +28231,Male,29,Diploma,14,96,57,17,43,5.0,5,94,Semi-Urban,Software Engineer,78666,1 +28232,Male,33,Masters,15,17,67,49,59,3.0,0,84,Semi-Urban,Data Analyst,96923,0 +28233,Male,54,Bachelors,14,88,79,64,81,2.0,1,25,Rural,Software Engineer,124172,1 +28234,Male,41,Masters,15,87,98,89,24,4.0,3,35,Urban,Data Analyst,81885,1 +28235,Female,59,Bachelors,13,21,19,25,18,7.0,0,97,Semi-Urban,ML Engineer,32993,0 +28236,Male,59,Bachelors,8,95,63,66,24,4.0,1,80,Rural,ML Engineer,92615,1 +28237,Other,54,Bachelors,18,92,47,37,80,5.0,5,63,Semi-Urban,HR Executive,139872,0 +28238,Male,37,Bachelors,11,24,37,42,48,3.0,2,90,Urban,Data Analyst,34476,0 +28239,Female,28,Masters,16,72,43,24,56,8.0,1,40,Rural,Manager,127236,0 +28240,Male,22,Masters,18,6,51,16,57,6.0,6,65,Rural,HR Executive,124701,0 +28241,Female,46,Masters,3,32,66,23,16,7.0,7,67,Urban,Data Analyst,108513,0 +28242,Male,49,Bachelors,12,13,71,52,26,4.0,6,1,Urban,Data Analyst,27227,0 +28243,Male,59,Diploma,2,46,83,37,88,3.0,4,70,Urban,HR Executive,115178,1 +28244,Male,40,High School,13,2,19,1,67,3.0,7,78,Urban,Software Engineer,53748,0 +28245,Other,31,High School,12,55,9,3,79,6.0,4,73,Semi-Urban,Data Analyst,143445,0 +28246,Other,34,Masters,12,16,81,35,54,0.0,3,55,Urban,Manager,104360,0 +28247,Male,28,Bachelors,7,17,36,63,86,1.0,5,59,Rural,Data Analyst,92495,0 +28248,Female,56,Diploma,18,38,39,12,59,4.0,0,60,Urban,Manager,63539,0 +28249,Male,56,High School,14,35,2,62,21,1.0,2,94,Urban,ML Engineer,116098,0 +28250,Male,56,Masters,12,90,56,5,89,5.0,6,66,Semi-Urban,Software Engineer,138342,0 +28251,Male,36,Bachelors,18,54,83,72,84,6.0,4,7,Semi-Urban,Data Analyst,126958,0 +28252,Other,44,Bachelors,13,53,23,53,39,1.0,6,96,Urban,Manager,77429,0 +28253,Male,52,Bachelors,16,28,35,50,70,2.0,6,34,Urban,Software Engineer,42332,0 +28254,Male,21,Diploma,9,52,13,95,48,4.0,3,72,Rural,HR Executive,91221,0 +28255,Male,37,Bachelors,0,38,36,93,65,9.0,5,34,Urban,Data Analyst,64991,0 +28256,Male,52,Masters,16,68,89,47,56,8.0,2,51,Urban,ML Engineer,128167,1 +28257,Male,32,Diploma,2,43,78,57,97,8.0,7,24,Rural,Software Engineer,23108,0 +28258,Male,34,Masters,13,79,12,34,40,8.0,5,93,Semi-Urban,Manager,45957,0 +28259,Male,37,High School,5,60,37,97,55,0.0,3,8,Urban,Software Engineer,87653,0 +28260,Male,41,Diploma,10,60,82,43,47,0.0,6,73,Rural,Manager,92437,1 +28261,Male,44,Bachelors,2,75,53,80,12,4.0,4,15,Rural,Manager,90033,0 +28262,Male,47,Bachelors,19,83,81,89,97,5.0,6,30,Rural,HR Executive,82881,1 +28263,Female,34,Diploma,9,14,4,35,23,7.0,2,33,Rural,Manager,41160,0 +28264,Male,41,High School,8,98,93,43,43,4.0,4,69,Rural,ML Engineer,56426,1 +28265,Female,37,High School,0,61,44,70,2,4.0,6,42,Urban,HR Executive,29220,0 +28266,Male,39,Bachelors,2,70,23,83,43,5.0,6,54,Semi-Urban,Data Analyst,122335,0 +28267,Male,27,High School,19,91,94,15,8,7.0,6,24,Urban,Manager,113938,0 +28268,Male,55,Masters,5,90,43,15,56,7.0,1,7,Semi-Urban,Data Analyst,64860,0 +28269,Female,25,Masters,13,41,67,80,37,0.0,7,87,Urban,Manager,96318,1 +28270,Female,36,Bachelors,10,73,60,86,88,8.0,3,47,Urban,HR Executive,112511,1 +28271,Male,26,Bachelors,15,79,87,40,12,7.0,1,73,Semi-Urban,ML Engineer,79066,1 +28272,Male,34,Diploma,0,47,23,72,27,7.0,5,51,Rural,Manager,82558,0 +28273,Female,29,Bachelors,11,11,42,67,90,2.0,0,94,Urban,Manager,57518,0 +28274,Male,30,High School,4,55,89,23,87,1.0,3,5,Rural,Manager,95457,0 +28275,Female,47,Bachelors,12,57,74,96,79,9.0,3,80,Urban,Software Engineer,135626,1 +28276,Male,21,High School,3,82,56,93,36,1.0,5,61,Urban,Manager,144212,1 +28277,Female,52,Bachelors,18,87,97,19,47,0.0,5,87,Rural,Manager,70512,1 +28278,Male,42,Bachelors,14,36,54,50,76,1.0,6,22,Urban,HR Executive,89643,0 +28279,Male,40,PhD,11,82,42,16,85,5.0,0,10,Urban,HR Executive,76649,0 +28280,Female,51,Diploma,19,29,79,50,76,4.0,1,2,Rural,ML Engineer,28878,0 +28281,Male,38,Diploma,3,44,53,1,53,1.0,4,41,Urban,Data Analyst,79593,0 +28282,Male,45,Masters,9,37,87,98,10,5.0,0,95,Rural,Manager,116725,1 +28283,Male,57,Bachelors,9,25,59,69,15,1.0,0,93,Urban,HR Executive,110218,1 +28284,Male,24,Bachelors,1,46,74,46,56,6.0,6,69,Urban,ML Engineer,100093,1 +28285,Male,53,Bachelors,1,96,64,10,69,0.0,2,76,Urban,Software Engineer,49190,1 +28286,Other,48,Diploma,6,70,51,88,21,3.0,1,24,Semi-Urban,Manager,124952,0 +28287,Female,28,Masters,15,47,72,83,89,7.0,1,7,Rural,Software Engineer,108399,0 +28288,Male,26,Bachelors,18,91,85,92,35,2.0,6,45,Semi-Urban,Software Engineer,139591,1 +28289,Female,32,High School,5,74,70,48,75,0.0,5,52,Rural,Software Engineer,135877,1 +28290,Male,28,Bachelors,12,5,25,57,41,2.0,1,57,Urban,Software Engineer,121789,0 +28291,Male,24,Bachelors,12,53,44,29,42,7.0,2,21,Urban,HR Executive,127043,0 +28292,Male,27,Diploma,14,10,33,95,55,0.0,6,63,Semi-Urban,ML Engineer,116346,0 +28293,Female,26,Diploma,17,7,0,38,25,1.0,4,15,Urban,Software Engineer,148843,0 +28294,Female,41,Bachelors,10,98,44,47,16,9.0,0,9,Urban,HR Executive,114860,0 +28295,Male,56,Diploma,8,39,46,54,24,9.0,6,73,Urban,Manager,66926,0 +28296,Male,47,Bachelors,8,20,32,10,16,0.0,2,21,Rural,ML Engineer,85009,0 +28297,Male,38,Masters,13,52,76,51,19,3.0,7,49,Rural,Manager,40276,0 +28298,Male,28,Bachelors,13,88,0,27,20,4.0,5,27,Urban,HR Executive,59077,0 +28299,Male,44,Bachelors,17,94,28,48,55,7.0,4,42,Semi-Urban,HR Executive,42132,0 +28300,Male,43,Diploma,6,92,25,24,63,4.0,0,74,Urban,Manager,54611,0 +28301,Female,37,Bachelors,4,54,80,32,77,3.0,2,24,Semi-Urban,Manager,53934,0 +28302,Female,35,Diploma,13,71,3,37,66,0.0,4,71,Urban,Software Engineer,117780,0 +28303,Male,31,High School,2,70,94,58,75,2.0,7,46,Semi-Urban,Software Engineer,20354,1 +28304,Male,36,Masters,17,74,19,8,78,1.0,1,37,Urban,Software Engineer,96336,0 +28305,Female,41,Masters,4,36,84,16,78,2.0,7,10,Urban,Manager,34507,0 +28306,Female,45,Bachelors,0,88,58,41,77,3.0,0,32,Semi-Urban,ML Engineer,40801,0 +28307,Male,49,Masters,10,29,20,59,37,8.0,2,13,Urban,Data Analyst,97268,0 +28308,Male,52,Bachelors,2,60,78,94,55,7.0,1,58,Urban,HR Executive,58838,1 +28309,Female,30,Bachelors,11,58,60,44,76,8.0,6,38,Semi-Urban,ML Engineer,29333,0 +28310,Female,53,Bachelors,2,1,64,48,47,2.0,4,28,Semi-Urban,ML Engineer,31286,0 +28311,Male,26,Bachelors,11,30,32,40,44,8.0,1,64,Urban,HR Executive,92535,0 +28312,Male,45,Diploma,6,19,28,18,78,1.0,6,48,Urban,ML Engineer,138657,0 +28313,Male,30,Diploma,1,10,66,55,75,9.0,0,84,Urban,Data Analyst,71510,0 +28314,Male,41,Masters,17,6,84,48,29,2.0,7,91,Urban,Data Analyst,104231,0 +28315,Female,36,Bachelors,18,35,87,43,57,0.0,5,74,Rural,Software Engineer,53976,0 +28316,Male,59,PhD,17,61,48,66,9,4.0,1,9,Urban,Data Analyst,42752,0 +28317,Female,58,Masters,8,57,59,18,47,9.0,3,38,Semi-Urban,Data Analyst,63677,0 +28318,Male,21,Bachelors,3,82,29,21,52,5.0,1,87,Urban,HR Executive,110799,0 +28319,Male,47,Bachelors,1,35,12,78,62,2.0,0,3,Urban,ML Engineer,65279,0 +28320,Female,37,Bachelors,11,57,32,72,8,0.0,2,50,Rural,Data Analyst,130015,0 +28321,Female,41,Bachelors,7,54,80,66,77,8.0,2,28,Semi-Urban,Manager,72813,0 +28322,Other,25,Diploma,12,70,18,12,23,7.0,6,78,Urban,Software Engineer,135209,0 +28323,Male,31,Bachelors,11,22,89,85,16,4.0,5,47,Urban,Data Analyst,44520,1 +28324,Male,56,Bachelors,1,93,62,13,33,8.0,7,25,Rural,Software Engineer,70380,0 +28325,Other,34,Bachelors,19,4,28,65,71,6.0,0,26,Rural,Data Analyst,112538,0 +28326,Female,25,Bachelors,11,19,81,25,81,0.0,7,15,Semi-Urban,Manager,23124,0 +28327,Female,28,PhD,13,66,90,89,28,9.0,3,77,Semi-Urban,Software Engineer,77481,1 +28328,Male,55,Bachelors,15,10,25,86,77,3.0,6,31,Semi-Urban,ML Engineer,37118,0 +28329,Male,56,Bachelors,16,18,23,69,28,4.0,0,79,Urban,Software Engineer,101847,0 +28330,Male,31,Diploma,6,47,60,70,31,0.0,0,53,Urban,Software Engineer,65104,0 +28331,Female,25,Bachelors,9,96,21,4,66,8.0,4,28,Urban,HR Executive,123697,0 +28332,Female,35,High School,11,14,99,78,43,6.0,7,78,Urban,HR Executive,92257,1 +28333,Male,35,High School,4,13,99,51,94,3.0,5,20,Semi-Urban,HR Executive,130296,0 +28334,Male,27,Bachelors,15,80,95,40,71,6.0,5,85,Semi-Urban,HR Executive,55226,1 +28335,Male,58,Diploma,16,91,10,33,85,2.0,6,58,Semi-Urban,Data Analyst,130550,0 +28336,Male,47,Bachelors,2,22,87,65,52,3.0,2,22,Urban,HR Executive,137120,0 +28337,Male,41,Diploma,18,97,72,2,11,4.0,6,4,Urban,Data Analyst,52960,0 +28338,Female,54,Diploma,9,50,48,29,98,6.0,2,67,Urban,ML Engineer,29695,0 +28339,Male,31,Diploma,12,30,27,11,94,8.0,3,54,Rural,Manager,134225,0 +28340,Male,58,Diploma,3,85,35,77,92,5.0,0,10,Urban,ML Engineer,45680,0 +28341,Male,47,Masters,13,41,23,18,21,6.0,2,91,Rural,HR Executive,118981,0 +28342,Female,33,High School,1,72,24,92,45,9.0,2,96,Urban,Data Analyst,101076,1 +28343,Male,44,Diploma,15,76,24,35,3,0.0,6,7,Urban,ML Engineer,39378,0 +28344,Female,52,Diploma,1,12,5,40,41,9.0,1,61,Urban,HR Executive,120851,0 +28345,Female,39,Bachelors,8,25,53,54,6,5.0,6,36,Urban,Manager,40250,0 +28346,Male,55,Masters,19,56,93,4,54,7.0,3,79,Semi-Urban,Manager,122578,0 +28347,Male,55,Bachelors,5,59,40,31,46,5.0,4,11,Semi-Urban,ML Engineer,115751,0 +28348,Female,25,Bachelors,4,34,55,77,69,0.0,4,95,Rural,Data Analyst,112721,1 +28349,Male,58,Bachelors,2,78,46,96,34,5.0,4,84,Rural,Software Engineer,43376,1 +28350,Male,43,Bachelors,17,86,88,52,58,7.0,1,18,Semi-Urban,HR Executive,88974,1 +28351,Female,35,High School,5,60,19,72,98,8.0,3,49,Rural,Data Analyst,132681,0 +28352,Female,21,Bachelors,5,12,21,97,12,9.0,4,81,Semi-Urban,HR Executive,34807,0 +28353,Male,43,High School,3,52,1,25,16,2.0,6,89,Urban,ML Engineer,49956,0 +28354,Male,49,Bachelors,7,84,75,68,31,8.0,4,86,Semi-Urban,Manager,83443,1 +28355,Female,47,High School,14,67,43,51,48,6.0,3,33,Urban,Manager,123387,0 +28356,Male,26,Bachelors,18,97,88,71,40,9.0,0,43,Semi-Urban,HR Executive,76171,1 +28357,Male,36,Bachelors,12,75,93,41,10,5.0,0,39,Semi-Urban,HR Executive,23528,1 +28358,Male,43,Diploma,12,18,44,81,80,7.0,0,7,Semi-Urban,Data Analyst,134646,0 +28359,Male,47,Masters,2,2,65,81,42,1.0,0,92,Urban,Software Engineer,36794,1 +28360,Other,57,Bachelors,3,30,75,40,89,5.0,3,55,Urban,Data Analyst,64551,0 +28361,Female,53,Bachelors,5,99,44,6,85,9.0,3,18,Semi-Urban,ML Engineer,141306,0 +28362,Female,51,Bachelors,18,11,28,18,30,3.0,6,4,Rural,Manager,135742,0 +28363,Other,27,Bachelors,17,38,11,87,18,2.0,0,57,Rural,Manager,131962,0 +28364,Male,49,High School,10,75,16,9,28,3.0,5,83,Rural,ML Engineer,80146,0 +28365,Male,26,PhD,4,14,46,89,58,4.0,3,80,Urban,ML Engineer,88824,0 +28366,Male,22,Masters,13,49,54,84,23,1.0,2,19,Urban,Manager,108061,0 +28367,Male,43,Diploma,4,17,59,68,8,1.0,2,37,Semi-Urban,HR Executive,148416,0 +28368,Male,58,Diploma,15,79,96,17,94,1.0,7,29,Semi-Urban,Manager,51425,0 +28369,Male,23,High School,12,28,86,51,48,4.0,2,94,Urban,Data Analyst,126826,1 +28370,Male,46,Diploma,19,52,20,34,47,4.0,6,96,Rural,HR Executive,62546,0 +28371,Male,42,Bachelors,16,64,53,56,48,0.0,4,47,Urban,Manager,53026,0 +28372,Male,33,Bachelors,6,98,31,75,89,4.0,4,41,Urban,Data Analyst,102606,1 +28373,Male,25,High School,6,71,70,50,3,3.0,0,43,Semi-Urban,Data Analyst,45000,0 +28374,Male,56,Bachelors,16,88,0,93,41,2.0,7,1,Rural,Manager,68514,0 +28375,Male,37,Masters,10,12,77,10,59,4.0,5,94,Semi-Urban,ML Engineer,41342,0 +28376,Male,51,Masters,14,41,46,82,66,5.0,5,51,Urban,Manager,99658,0 +28377,Other,38,Diploma,1,78,5,84,15,2.0,6,75,Urban,Software Engineer,131962,1 +28378,Female,48,Diploma,17,39,36,43,21,9.0,2,68,Rural,Data Analyst,124113,0 +28379,Male,48,Diploma,19,85,39,25,99,3.0,2,25,Urban,Manager,32150,0 +28380,Other,25,Bachelors,5,76,80,5,16,8.0,6,68,Semi-Urban,Data Analyst,91997,0 +28381,Other,29,PhD,10,74,17,38,42,3.0,4,48,Semi-Urban,Data Analyst,44256,0 +28382,Male,45,Diploma,3,62,7,44,4,6.0,4,25,Semi-Urban,Software Engineer,68223,0 +28383,Male,39,Bachelors,12,34,74,4,74,5.0,6,90,Semi-Urban,Data Analyst,70140,0 +28384,Other,31,Bachelors,9,42,18,95,83,0.0,0,27,Urban,ML Engineer,85040,0 +28385,Female,46,Bachelors,10,59,52,7,0,6.0,7,21,Semi-Urban,Manager,34042,0 +28386,Male,32,Diploma,19,65,40,86,91,8.0,0,48,Rural,Software Engineer,21743,1 +28387,Female,56,High School,3,87,58,55,56,3.0,2,75,Urban,Manager,144751,1 +28388,Male,53,Masters,4,10,2,46,9,4.0,5,56,Semi-Urban,Data Analyst,39072,0 +28389,Male,27,Bachelors,16,4,99,62,7,7.0,6,75,Urban,ML Engineer,75957,1 +28390,Male,22,Bachelors,11,55,66,12,79,0.0,2,87,Semi-Urban,Data Analyst,126059,0 +28391,Male,24,Bachelors,7,30,40,73,26,8.0,0,10,Semi-Urban,ML Engineer,48055,0 +28392,Male,39,Bachelors,3,71,40,34,18,5.0,2,71,Urban,ML Engineer,98821,0 +28393,Female,25,Bachelors,7,87,27,65,51,6.0,1,56,Semi-Urban,HR Executive,101781,0 +28394,Male,22,High School,11,68,75,14,30,1.0,7,50,Urban,Software Engineer,42626,0 +28395,Male,48,Diploma,8,41,23,96,12,9.0,4,0,Semi-Urban,ML Engineer,123915,0 +28396,Male,51,Diploma,1,61,71,44,8,1.0,0,65,Rural,Data Analyst,66831,1 +28397,Male,47,PhD,14,65,73,86,40,6.0,1,10,Semi-Urban,Manager,66245,0 +28398,Other,39,Diploma,3,81,79,32,59,5.0,7,5,Urban,Manager,98123,0 +28399,Male,26,High School,9,43,44,88,92,9.0,1,92,Rural,ML Engineer,112650,1 +28400,Male,42,Bachelors,0,48,63,48,69,2.0,6,66,Semi-Urban,Data Analyst,39472,0 +28401,Male,52,Bachelors,18,29,55,53,79,7.0,6,14,Urban,Software Engineer,57438,0 +28402,Male,36,Bachelors,1,56,12,0,26,1.0,7,15,Semi-Urban,HR Executive,48526,0 +28403,Male,37,Masters,4,50,76,74,56,1.0,2,28,Urban,Software Engineer,87386,0 +28404,Male,36,High School,7,0,59,26,59,8.0,5,1,Semi-Urban,HR Executive,112972,0 +28405,Male,53,High School,5,11,96,69,78,5.0,2,75,Rural,ML Engineer,33380,1 +28406,Male,47,Bachelors,17,1,49,33,10,3.0,2,61,Semi-Urban,Data Analyst,88547,0 +28407,Female,52,Bachelors,17,43,77,68,56,3.0,1,2,Urban,Data Analyst,105036,0 +28408,Male,35,Bachelors,16,92,95,10,36,3.0,7,44,Urban,Software Engineer,60234,1 +28409,Male,27,Bachelors,6,77,77,20,83,3.0,5,53,Urban,ML Engineer,66615,0 +28410,Female,29,Bachelors,1,59,99,6,40,6.0,6,5,Urban,HR Executive,105884,0 +28411,Female,56,Diploma,16,82,57,85,4,1.0,0,53,Urban,ML Engineer,105378,1 +28412,Male,50,PhD,8,89,95,62,67,3.0,6,58,Urban,HR Executive,93343,1 +28413,Other,28,PhD,6,47,42,80,13,1.0,7,37,Urban,Data Analyst,146733,0 +28414,Female,32,High School,7,51,29,23,10,7.0,6,40,Semi-Urban,Manager,64735,0 +28415,Male,58,Bachelors,1,77,13,15,86,2.0,1,55,Urban,ML Engineer,99332,0 +28416,Male,24,Diploma,17,78,40,13,10,6.0,7,30,Urban,HR Executive,96967,0 +28417,Male,39,Diploma,13,79,37,78,85,1.0,4,54,Urban,HR Executive,28068,1 +28418,Male,32,Bachelors,4,14,66,60,55,9.0,7,83,Urban,Manager,39909,0 +28419,Male,55,Bachelors,18,67,98,42,90,5.0,7,88,Rural,Software Engineer,80888,1 +28420,Male,32,Diploma,16,73,10,98,20,5.0,6,64,Urban,HR Executive,58792,1 +28421,Female,50,PhD,17,99,95,92,73,2.0,3,1,Urban,Manager,92877,1 +28422,Male,34,Masters,6,36,51,98,18,5.0,1,77,Semi-Urban,Software Engineer,138018,1 +28423,Male,48,Diploma,17,34,3,50,33,1.0,1,86,Rural,HR Executive,57462,0 +28424,Male,50,Masters,1,36,28,5,13,6.0,7,61,Semi-Urban,HR Executive,129254,0 +28425,Female,29,Bachelors,1,63,21,19,48,4.0,3,73,Urban,Manager,71545,0 +28426,Female,52,Masters,5,38,56,58,35,9.0,1,99,Urban,Manager,98683,1 +28427,Male,50,Masters,11,13,2,73,5,5.0,1,14,Urban,Manager,46500,0 +28428,Male,34,PhD,1,40,44,91,96,3.0,3,78,Semi-Urban,Data Analyst,42699,1 +28429,Male,24,Diploma,4,12,13,52,14,2.0,4,13,Urban,Manager,53990,0 +28430,Female,54,Bachelors,7,40,75,15,17,6.0,1,28,Semi-Urban,Software Engineer,103096,0 +28431,Male,43,Masters,14,76,69,83,0,3.0,4,7,Urban,ML Engineer,103769,1 +28432,Male,21,Bachelors,10,61,37,4,39,2.0,1,4,Urban,ML Engineer,145056,0 +28433,Male,21,High School,2,33,92,33,33,6.0,5,17,Urban,Manager,122951,0 +28434,Female,37,Bachelors,4,66,4,52,88,7.0,7,28,Rural,Software Engineer,147707,0 +28435,Male,24,Bachelors,10,37,73,48,60,9.0,2,54,Urban,ML Engineer,56764,0 +28436,Other,30,Bachelors,15,55,49,25,18,7.0,1,11,Urban,ML Engineer,78175,0 +28437,Male,39,High School,1,7,17,19,20,3.0,5,1,Urban,HR Executive,140346,0 +28438,Male,21,Bachelors,11,24,16,43,9,5.0,6,83,Rural,Software Engineer,95756,0 +28439,Male,21,Bachelors,1,48,19,95,42,3.0,0,91,Urban,HR Executive,23990,1 +28440,Female,53,Masters,12,0,33,68,29,3.0,2,11,Urban,ML Engineer,44098,0 +28441,Female,39,Diploma,16,47,50,25,76,2.0,6,13,Urban,HR Executive,149230,0 +28442,Female,37,High School,17,31,68,62,87,0.0,0,12,Urban,ML Engineer,30500,0 +28443,Female,53,Masters,9,33,85,8,16,0.0,5,98,Urban,HR Executive,123880,0 +28444,Female,47,Bachelors,1,63,72,42,48,7.0,3,89,Rural,Data Analyst,136817,1 +28445,Female,31,Masters,17,92,47,89,47,0.0,3,31,Urban,HR Executive,65747,1 +28446,Male,33,Bachelors,11,26,36,49,60,3.0,4,92,Semi-Urban,ML Engineer,92182,0 +28447,Female,30,Bachelors,16,13,97,12,35,0.0,2,47,Urban,Data Analyst,32252,0 +28448,Female,57,Bachelors,0,70,96,16,56,2.0,7,2,Rural,Data Analyst,29066,0 +28449,Male,33,Diploma,16,40,46,22,46,5.0,3,19,Semi-Urban,HR Executive,69013,0 +28450,Female,30,Bachelors,6,30,32,44,94,3.0,3,20,Urban,Manager,47925,0 +28451,Male,30,Bachelors,3,36,76,45,76,7.0,7,67,Urban,HR Executive,74804,0 +28452,Male,34,Bachelors,4,15,5,36,16,3.0,5,52,Rural,ML Engineer,106580,0 +28453,Male,23,Diploma,11,55,91,98,1,1.0,1,81,Urban,ML Engineer,32876,1 +28454,Male,26,Masters,1,41,35,99,52,4.0,6,96,Urban,HR Executive,69448,1 +28455,Male,47,PhD,18,37,30,43,59,6.0,0,49,Urban,Manager,132705,0 +28456,Female,28,Masters,0,21,58,40,23,9.0,3,17,Semi-Urban,Manager,20165,0 +28457,Male,47,Bachelors,5,4,86,48,73,6.0,1,49,Semi-Urban,Manager,47465,0 +28458,Male,36,Bachelors,9,78,31,92,91,7.0,6,50,Urban,Data Analyst,123652,1 +28459,Female,53,Bachelors,5,72,34,48,88,8.0,7,49,Urban,HR Executive,40951,0 +28460,Male,32,Masters,12,85,79,3,59,4.0,5,49,Rural,Software Engineer,139053,0 +28461,Male,56,Bachelors,3,58,41,62,71,8.0,2,45,Urban,Data Analyst,62012,0 +28462,Male,36,Masters,0,84,32,78,81,1.0,0,71,Urban,Manager,56510,1 +28463,Male,45,Bachelors,13,63,4,57,94,0.0,6,18,Urban,Software Engineer,29826,0 +28464,Male,38,Diploma,8,73,8,6,41,1.0,7,49,Semi-Urban,Manager,46308,0 +28465,Female,32,High School,1,73,46,29,34,3.0,6,0,Urban,HR Executive,100209,0 +28466,Male,36,Masters,18,3,84,63,23,5.0,0,89,Urban,Data Analyst,35405,1 +28467,Male,28,Masters,19,21,18,11,79,4.0,1,49,Semi-Urban,HR Executive,117861,0 +28468,Other,37,Masters,19,70,5,88,88,9.0,5,32,Urban,Data Analyst,117609,0 +28469,Female,40,Bachelors,10,70,36,94,79,7.0,3,21,Urban,Manager,123019,0 +28470,Male,54,Diploma,11,93,93,62,12,1.0,1,73,Rural,Data Analyst,51597,1 +28471,Male,22,Bachelors,8,84,27,61,18,4.0,7,98,Urban,Manager,137626,1 +28472,Female,47,Masters,0,57,41,66,58,0.0,1,30,Urban,Manager,94131,0 +28473,Female,26,Bachelors,19,63,52,32,54,1.0,0,88,Urban,Data Analyst,72481,0 +28474,Female,55,Bachelors,3,50,96,24,65,1.0,6,83,Rural,Software Engineer,84064,1 +28475,Male,58,High School,11,49,97,56,12,0.0,7,35,Urban,Manager,42348,1 +28476,Male,48,Masters,3,5,90,4,50,8.0,3,46,Semi-Urban,Manager,128932,0 +28477,Male,27,Bachelors,3,63,37,80,56,6.0,2,33,Urban,Manager,62320,0 +28478,Female,31,Diploma,14,76,50,15,22,4.0,3,31,Semi-Urban,Data Analyst,108593,0 +28479,Female,23,Bachelors,3,86,72,0,96,3.0,1,28,Semi-Urban,Software Engineer,71791,0 +28480,Male,37,Diploma,15,20,74,95,99,0.0,6,95,Semi-Urban,HR Executive,73998,1 +28481,Male,27,Masters,16,75,78,24,19,4.0,3,44,Semi-Urban,Software Engineer,74095,0 +28482,Other,36,Bachelors,2,85,77,44,87,7.0,1,75,Urban,Manager,98115,1 +28483,Male,25,Diploma,17,10,35,47,12,6.0,0,48,Urban,ML Engineer,103976,0 +28484,Male,25,Bachelors,0,71,80,53,99,4.0,0,89,Semi-Urban,ML Engineer,60719,1 +28485,Female,21,Diploma,12,22,56,49,20,3.0,7,18,Semi-Urban,Manager,32023,0 +28486,Male,26,High School,7,94,33,1,34,5.0,5,40,Rural,HR Executive,129252,0 +28487,Male,33,Masters,11,31,39,46,74,4.0,5,30,Urban,Software Engineer,133785,0 +28488,Male,43,Masters,15,12,30,26,82,9.0,6,76,Urban,HR Executive,109093,0 +28489,Male,43,Masters,2,80,78,45,13,5.0,4,71,Semi-Urban,Software Engineer,71616,1 +28490,Male,54,PhD,15,66,46,99,54,0.0,5,85,Urban,HR Executive,127159,1 +28491,Female,48,Bachelors,8,91,74,43,10,7.0,5,60,Semi-Urban,Manager,92437,1 +28492,Male,28,Diploma,5,42,53,81,0,3.0,1,25,Semi-Urban,Software Engineer,31835,0 +28493,Female,34,Masters,6,70,84,23,26,6.0,7,2,Urban,Manager,141886,0 +28494,Male,24,PhD,10,1,54,96,11,1.0,3,31,Urban,ML Engineer,87293,0 +28495,Male,25,Diploma,14,12,58,64,4,7.0,1,43,Urban,ML Engineer,134489,0 +28496,Female,24,Masters,4,42,41,12,26,3.0,5,51,Rural,Software Engineer,137068,0 +28497,Male,58,Bachelors,19,99,71,79,9,3.0,2,8,Urban,Data Analyst,96756,1 +28498,Male,46,Bachelors,8,60,33,0,56,1.0,4,39,Urban,Software Engineer,22132,0 +28499,Male,55,Diploma,6,59,25,57,98,0.0,6,4,Urban,Manager,126693,0 +28500,Male,27,Diploma,19,13,65,2,30,9.0,1,8,Urban,Software Engineer,52511,0 +28501,Male,57,Masters,8,67,13,32,22,0.0,7,84,Rural,Manager,101824,0 +28502,Female,31,Bachelors,8,53,19,41,62,0.0,1,9,Rural,Manager,38962,0 +28503,Male,43,Bachelors,6,21,81,94,94,0.0,0,36,Urban,Data Analyst,138697,0 +28504,Female,49,Diploma,3,35,75,78,18,3.0,0,34,Urban,Manager,51048,0 +28505,Male,42,Bachelors,17,45,72,5,53,3.0,4,81,Rural,Data Analyst,21836,0 +28506,Male,33,High School,14,81,58,42,86,5.0,5,40,Urban,Software Engineer,80212,0 +28507,Male,47,Masters,9,70,51,89,9,1.0,3,41,Rural,Data Analyst,111803,1 +28508,Male,33,Diploma,16,39,65,41,57,1.0,5,64,Rural,HR Executive,114587,0 +28509,Male,43,Diploma,18,48,97,63,91,6.0,5,75,Rural,Manager,28971,1 +28510,Female,24,Bachelors,2,8,71,22,30,7.0,1,53,Rural,HR Executive,115906,0 +28511,Male,53,Diploma,3,32,35,18,68,3.0,3,12,Semi-Urban,HR Executive,102593,0 +28512,Male,35,Bachelors,18,23,98,75,66,7.0,0,12,Rural,Data Analyst,106972,0 +28513,Other,47,Bachelors,11,90,67,76,14,8.0,2,76,Urban,HR Executive,116850,1 +28514,Male,58,Bachelors,10,44,43,92,88,7.0,5,18,Urban,ML Engineer,88135,0 +28515,Male,46,Diploma,9,77,61,25,56,5.0,0,40,Semi-Urban,Software Engineer,44686,0 +28516,Male,59,Bachelors,16,23,42,15,11,5.0,5,34,Urban,Software Engineer,142433,0 +28517,Male,32,PhD,13,37,24,64,0,4.0,3,51,Urban,Manager,84701,0 +28518,Male,32,Bachelors,14,19,55,98,92,1.0,2,4,Urban,HR Executive,138486,0 +28519,Male,29,High School,9,25,69,25,77,2.0,4,3,Semi-Urban,ML Engineer,56580,0 +28520,Male,47,Diploma,15,18,81,98,71,7.0,2,37,Urban,ML Engineer,91926,0 +28521,Female,39,Diploma,11,72,59,8,60,5.0,5,86,Urban,ML Engineer,21795,0 +28522,Female,26,High School,17,17,20,31,26,4.0,5,44,Urban,Software Engineer,100243,0 +28523,Female,48,PhD,19,77,13,42,23,5.0,6,63,Semi-Urban,ML Engineer,135952,0 +28524,Male,53,Bachelors,7,0,8,82,98,3.0,4,68,Urban,ML Engineer,140207,0 +28525,Male,58,High School,11,12,93,56,32,0.0,5,6,Urban,ML Engineer,66992,0 +28526,Male,42,High School,18,74,10,89,74,6.0,6,84,Urban,Manager,29194,1 +28527,Male,52,Diploma,10,45,33,21,53,3.0,6,27,Urban,Software Engineer,78331,0 +28528,Male,29,High School,8,14,75,63,75,6.0,2,58,Rural,ML Engineer,79045,0 +28529,Male,52,Bachelors,0,3,37,10,65,1.0,5,18,Urban,Manager,115100,0 +28530,Male,51,High School,4,56,94,79,53,7.0,1,17,Urban,Manager,44371,1 +28531,Female,41,Bachelors,17,22,67,65,88,1.0,0,66,Rural,ML Engineer,52576,0 +28532,Male,39,Masters,0,9,73,91,69,2.0,6,17,Urban,Software Engineer,95377,0 +28533,Other,52,Masters,13,32,40,67,9,4.0,3,44,Urban,Data Analyst,146194,0 +28534,Female,41,Diploma,16,62,33,23,21,,7,95,Urban,Software Engineer,37952,0 +28535,Male,36,High School,5,42,41,47,29,2.0,4,32,Urban,Data Analyst,88714,0 +28536,Male,35,Masters,10,47,90,73,28,0.0,5,24,Semi-Urban,ML Engineer,79650,0 +28537,Male,43,Bachelors,1,10,16,29,99,7.0,4,17,Urban,Data Analyst,69597,0 +28538,Female,54,Masters,6,77,67,69,45,7.0,5,23,Semi-Urban,Manager,128908,0 +28539,Male,47,Masters,9,19,6,79,16,7.0,7,46,Urban,Manager,50934,0 +28540,Male,28,Diploma,18,98,94,53,17,0.0,6,70,Semi-Urban,Software Engineer,108005,1 +28541,Male,47,Bachelors,16,59,66,11,17,0.0,3,95,Urban,HR Executive,75440,0 +28542,Male,24,Masters,11,95,55,95,71,8.0,1,26,Rural,Manager,82751,1 +28543,Female,33,Bachelors,12,99,87,46,13,5.0,2,77,Rural,Software Engineer,98928,1 +28544,Male,36,PhD,14,10,26,88,58,7.0,5,3,Urban,Software Engineer,134905,0 +28545,Male,59,Bachelors,9,94,9,35,60,1.0,0,30,Urban,Manager,82773,0 +28546,Male,43,High School,3,10,3,90,68,4.0,7,65,Urban,Data Analyst,88220,0 +28547,Female,24,Diploma,10,47,92,69,21,9.0,2,90,Urban,Software Engineer,95010,1 +28548,Male,58,Diploma,8,37,88,32,34,3.0,5,4,Semi-Urban,Software Engineer,24411,0 +28549,Female,53,Bachelors,18,75,30,70,94,0.0,5,71,Semi-Urban,Data Analyst,20924,1 +28550,Female,48,Bachelors,13,30,9,17,31,2.0,2,72,Urban,Manager,20864,0 +28551,Female,37,High School,0,38,87,1,18,9.0,6,98,Semi-Urban,Software Engineer,104358,0 +28552,Male,47,PhD,6,33,57,87,63,1.0,4,62,Semi-Urban,ML Engineer,72294,1 +28553,Male,48,High School,3,24,65,27,71,0.0,2,44,Urban,Software Engineer,107401,0 +28554,Male,38,Bachelors,11,72,15,65,34,2.0,0,32,Rural,Manager,70504,0 +28555,Male,33,Bachelors,13,59,41,56,72,7.0,0,32,Urban,ML Engineer,101901,0 +28556,Male,36,Bachelors,17,99,51,80,16,5.0,2,49,Urban,Manager,22352,1 +28557,Male,43,Bachelors,2,96,71,57,48,6.0,4,49,Semi-Urban,Software Engineer,110520,1 +28558,Male,37,Bachelors,4,73,33,41,38,3.0,3,12,Semi-Urban,Data Analyst,26990,0 +28559,Female,28,Bachelors,15,77,87,89,99,6.0,0,86,Rural,HR Executive,37697,1 +28560,Male,52,Masters,15,20,83,87,92,8.0,7,19,Urban,Software Engineer,63435,0 +28561,Male,53,Bachelors,12,42,98,89,80,4.0,1,3,Semi-Urban,Data Analyst,22815,0 +28562,Female,46,Bachelors,18,45,82,42,28,5.0,0,19,Semi-Urban,Software Engineer,75977,0 +28563,Male,44,Bachelors,15,53,46,65,65,3.0,2,12,Semi-Urban,Data Analyst,93790,0 +28564,Female,34,Bachelors,16,58,95,15,60,6.0,4,26,Rural,Data Analyst,135139,0 +28565,Male,35,Masters,8,11,79,49,28,9.0,5,12,Semi-Urban,Manager,74182,0 +28566,Other,59,Bachelors,19,18,19,75,88,2.0,5,33,Semi-Urban,Software Engineer,124718,0 +28567,Female,54,High School,12,91,81,98,19,0.0,5,53,Urban,HR Executive,140992,1 +28568,Male,38,Bachelors,19,82,58,49,13,2.0,4,8,Urban,Data Analyst,61021,0 +28569,Female,32,Masters,2,98,84,8,63,4.0,4,84,Urban,Manager,106725,1 +28570,Male,35,High School,18,21,77,69,76,5.0,4,56,Urban,Data Analyst,39277,0 +28571,Male,38,Bachelors,17,0,66,15,3,4.0,2,81,Semi-Urban,Software Engineer,147902,0 +28572,Female,26,Masters,7,1,78,75,20,6.0,7,84,Rural,Data Analyst,23246,0 +28573,Female,48,High School,16,46,56,57,66,3.0,6,84,Urban,Manager,141519,1 +28574,Male,39,Bachelors,7,85,63,90,12,7.0,4,58,Semi-Urban,Software Engineer,80248,1 +28575,Male,54,Bachelors,16,41,13,66,68,8.0,4,95,Semi-Urban,Manager,54544,0 +28576,Female,40,Bachelors,14,61,38,44,54,7.0,0,62,Rural,Data Analyst,114643,0 +28577,Male,48,Bachelors,12,58,12,41,20,7.0,0,32,Urban,HR Executive,137422,0 +28578,Female,51,Diploma,17,38,26,44,4,2.0,1,65,Rural,ML Engineer,140312,0 +28579,Female,28,Masters,14,81,35,97,61,1.0,5,20,Urban,Data Analyst,130301,0 +28580,Male,38,Bachelors,15,65,81,20,61,9.0,2,88,Urban,Manager,98345,1 +28581,Male,25,Diploma,4,98,93,49,70,9.0,7,44,Urban,Software Engineer,140697,1 +28582,Male,37,High School,12,46,58,84,98,6.0,2,80,Urban,ML Engineer,79066,1 +28583,Female,42,Masters,18,72,24,85,17,2.0,1,98,Urban,Software Engineer,61064,1 +28584,Female,26,High School,2,66,42,76,26,6.0,6,70,Rural,Software Engineer,99130,1 +28585,Male,44,Masters,15,28,39,24,5,4.0,7,46,Semi-Urban,Manager,122709,0 +28586,Male,40,PhD,19,58,81,80,80,7.0,3,85,Urban,Data Analyst,105929,1 +28587,Female,57,Masters,17,33,52,28,70,4.0,3,88,Semi-Urban,Data Analyst,44350,0 +28588,Male,25,Bachelors,14,22,47,82,19,1.0,1,99,Urban,ML Engineer,100767,1 +28589,Female,53,Bachelors,13,32,0,99,56,0.0,0,93,Semi-Urban,Data Analyst,90017,0 +28590,Male,56,Diploma,18,31,79,66,50,5.0,7,45,Rural,Manager,27503,0 +28591,Female,55,Bachelors,10,52,98,68,6,4.0,6,16,Urban,Software Engineer,28963,0 +28592,Female,43,Bachelors,0,57,91,10,79,3.0,7,47,Urban,Manager,115725,0 +28593,Male,56,Diploma,13,20,20,2,6,3.0,7,67,Urban,Data Analyst,89958,0 +28594,Female,28,Masters,5,89,0,36,13,2.0,7,22,Urban,Manager,115829,0 +28595,Male,36,Diploma,4,84,82,32,82,5.0,6,68,Urban,Data Analyst,21339,1 +28596,Male,36,Masters,19,5,89,18,93,9.0,2,26,Semi-Urban,Manager,123023,0 +28597,Male,22,Diploma,8,67,83,14,86,1.0,3,67,Urban,HR Executive,54052,0 +28598,Female,45,High School,17,57,28,92,12,9.0,3,73,Rural,ML Engineer,42981,1 +28599,Female,59,Diploma,9,45,20,38,95,4.0,1,80,Semi-Urban,HR Executive,25517,0 +28600,Female,36,Bachelors,12,82,90,11,33,8.0,4,75,Urban,Manager,82233,1 +28601,Female,23,Bachelors,6,20,94,28,67,3.0,0,24,Semi-Urban,Software Engineer,28327,0 +28602,Male,47,Bachelors,7,79,13,66,36,7.0,3,51,Urban,Manager,32763,0 +28603,Male,35,Diploma,1,41,66,35,84,5.0,7,93,Urban,Software Engineer,91786,1 +28604,Male,24,High School,18,88,66,98,35,8.0,1,96,Urban,Data Analyst,64559,1 +28605,Female,51,Diploma,15,0,89,19,85,5.0,5,9,Urban,ML Engineer,107888,0 +28606,Other,53,Bachelors,4,47,93,2,56,0.0,1,99,Urban,ML Engineer,116556,1 +28607,Male,21,Bachelors,19,6,17,93,28,8.0,4,12,Urban,Software Engineer,52689,0 +28608,Female,36,PhD,17,62,82,96,1,6.0,5,50,Semi-Urban,Data Analyst,76391,1 +28609,Male,29,PhD,7,72,39,26,40,7.0,6,54,Semi-Urban,Manager,95301,0 +28610,Male,21,Diploma,6,65,36,29,0,9.0,6,18,Urban,Software Engineer,77928,0 +28611,Male,44,Bachelors,12,61,18,49,16,2.0,1,69,Rural,HR Executive,65252,0 +28612,Female,46,Bachelors,10,57,98,46,29,3.0,6,1,Semi-Urban,Software Engineer,24610,0 +28613,Male,40,Diploma,6,77,34,8,27,7.0,1,55,Urban,Manager,33935,0 +28614,Female,51,Masters,19,69,51,79,15,2.0,7,8,Urban,Data Analyst,116849,0 +28615,Male,57,PhD,19,57,36,66,6,6.0,5,45,Urban,Data Analyst,128155,0 +28616,Male,34,High School,11,25,28,86,23,2.0,5,24,Rural,Manager,98535,0 +28617,Male,48,PhD,2,89,6,29,83,7.0,2,98,Semi-Urban,Manager,115027,0 +28618,Female,37,Bachelors,3,17,42,6,72,9.0,2,7,Urban,Data Analyst,103170,0 +28619,Male,53,Bachelors,12,64,70,57,62,7.0,4,47,Urban,Software Engineer,122709,1 +28620,Female,48,Bachelors,17,51,62,61,6,5.0,7,40,Urban,ML Engineer,109984,0 +28621,Male,21,Bachelors,8,83,36,20,24,1.0,3,32,Urban,Software Engineer,101713,0 +28622,Male,25,PhD,16,90,36,84,56,3.0,3,61,Semi-Urban,HR Executive,26163,1 +28623,Female,57,Bachelors,3,92,42,47,10,7.0,0,69,Semi-Urban,Data Analyst,109982,1 +28624,Male,27,Bachelors,11,34,18,92,55,3.0,0,29,Semi-Urban,ML Engineer,74250,0 +28625,Female,48,High School,0,79,84,18,39,6.0,1,79,Semi-Urban,Software Engineer,88321,1 +28626,Male,31,Bachelors,15,14,1,16,61,8.0,3,3,Semi-Urban,Software Engineer,29324,0 +28627,Female,24,Bachelors,17,46,0,64,56,6.0,1,48,Urban,Software Engineer,71059,0 +28628,Female,32,PhD,11,47,62,92,85,0.0,7,22,Urban,ML Engineer,123118,0 +28629,Female,46,Masters,2,27,66,83,84,8.0,0,57,Urban,ML Engineer,142976,0 +28630,Male,46,High School,4,49,11,76,45,2.0,3,35,Semi-Urban,Manager,114738,0 +28631,Female,44,Diploma,16,64,48,32,88,9.0,2,84,Semi-Urban,HR Executive,32721,0 +28632,Male,56,Masters,15,27,41,81,51,3.0,6,19,Semi-Urban,Manager,97267,0 +28633,Male,34,Bachelors,12,97,89,24,61,6.0,4,76,Semi-Urban,HR Executive,36191,1 +28634,Male,52,Bachelors,4,35,95,7,20,6.0,4,77,Urban,ML Engineer,121375,0 +28635,Male,49,High School,0,36,66,18,17,7.0,2,42,Urban,Data Analyst,41197,0 +28636,Female,28,Bachelors,1,33,48,75,44,7.0,0,56,Rural,Manager,29264,0 +28637,Female,37,Diploma,17,37,18,56,72,6.0,0,60,Urban,Software Engineer,148270,0 +28638,Male,47,Bachelors,15,27,63,61,65,9.0,4,95,Urban,Software Engineer,33437,1 +28639,Female,49,Masters,10,11,87,26,63,5.0,6,90,Urban,Data Analyst,127816,0 +28640,Male,31,Masters,19,46,24,43,35,4.0,7,51,Rural,HR Executive,138768,0 +28641,Female,55,Diploma,8,8,50,4,89,5.0,3,96,Semi-Urban,Software Engineer,144592,0 +28642,Female,39,Diploma,12,48,8,7,46,8.0,7,94,Semi-Urban,Software Engineer,138573,0 +28643,Female,51,Bachelors,14,34,79,51,91,6.0,2,20,Urban,Manager,46762,0 +28644,Male,43,High School,10,40,96,78,62,2.0,6,45,Semi-Urban,Software Engineer,74087,1 +28645,Female,44,Diploma,11,86,70,27,40,9.0,1,80,Urban,HR Executive,24102,1 +28646,Male,41,High School,16,25,20,46,96,5.0,0,27,Rural,Software Engineer,57045,0 +28647,Female,27,PhD,2,1,23,2,43,0.0,4,22,Urban,Manager,43667,0 +28648,Male,31,High School,16,60,95,52,50,8.0,2,40,Semi-Urban,Manager,142177,1 +28649,Female,29,Bachelors,13,86,71,23,17,9.0,4,47,Rural,HR Executive,48017,0 +28650,Male,56,Diploma,12,45,19,3,22,3.0,0,60,Urban,Software Engineer,127600,0 +28651,Male,55,Masters,6,2,40,76,31,9.0,6,50,Urban,ML Engineer,112414,0 +28652,Male,45,Diploma,2,70,28,86,78,2.0,3,65,Urban,Manager,68280,1 +28653,Female,39,Diploma,9,85,32,29,93,2.0,5,89,Semi-Urban,HR Executive,103908,0 +28654,Female,42,Bachelors,2,65,17,14,30,2.0,6,37,Semi-Urban,Manager,103876,0 +28655,Female,25,High School,7,78,97,5,60,0.0,6,92,Urban,Data Analyst,141212,1 +28656,Female,36,Bachelors,18,20,46,48,1,6.0,5,38,Semi-Urban,ML Engineer,64421,0 +28657,Male,23,Masters,13,27,75,57,74,8.0,7,46,Urban,Manager,27005,0 +28658,Female,52,Bachelors,6,50,57,95,45,2.0,5,20,Semi-Urban,Data Analyst,43697,0 +28659,Male,38,Bachelors,8,96,28,43,5,4.0,4,75,Rural,HR Executive,56824,1 +28660,Female,25,PhD,10,12,67,96,26,2.0,3,27,Semi-Urban,HR Executive,145639,0 +28661,Female,58,Diploma,5,46,61,74,15,8.0,3,93,Urban,Manager,140237,1 +28662,Male,34,Bachelors,10,62,77,60,25,7.0,0,78,Urban,Software Engineer,53266,1 +28663,Female,31,PhD,0,74,11,42,91,5.0,3,58,Urban,Manager,91172,0 +28664,Female,33,Masters,0,11,94,55,29,3.0,5,83,Urban,Software Engineer,115828,1 +28665,Male,24,Bachelors,15,46,19,39,95,3.0,1,66,Urban,Software Engineer,33623,0 +28666,Male,51,Bachelors,9,27,87,43,56,2.0,7,14,Rural,Manager,87812,0 +28667,Male,24,Bachelors,11,22,38,69,41,2.0,2,80,Urban,ML Engineer,57050,0 +28668,Other,30,Bachelors,18,88,11,50,58,1.0,2,52,Urban,Manager,25409,0 +28669,Male,49,Masters,11,9,42,38,0,4.0,3,21,Urban,Manager,124714,0 +28670,Male,55,Bachelors,14,72,44,45,57,2.0,6,42,Urban,Software Engineer,127517,0 +28671,Male,33,Bachelors,2,57,99,12,23,5.0,1,89,Semi-Urban,Manager,71283,1 +28672,Male,36,Bachelors,17,7,4,9,10,5.0,1,81,Rural,Manager,74896,0 +28673,Female,42,Bachelors,2,9,44,90,4,5.0,5,96,Urban,ML Engineer,27772,0 +28674,Male,33,Bachelors,17,20,95,37,82,4.0,4,53,Urban,HR Executive,28089,0 +28675,Other,50,Masters,17,47,63,40,59,0.0,0,51,Urban,ML Engineer,21828,0 +28676,Male,41,Bachelors,11,4,37,88,73,1.0,6,29,Rural,Software Engineer,87208,0 +28677,Male,37,Bachelors,18,77,27,94,64,3.0,1,61,Urban,Manager,25288,1 +28678,Male,57,Bachelors,14,40,69,87,99,3.0,2,62,Urban,ML Engineer,138989,1 +28679,Other,54,PhD,16,55,24,34,77,8.0,7,98,Semi-Urban,ML Engineer,104491,0 +28680,Male,52,Masters,13,21,64,76,90,9.0,6,73,Urban,Data Analyst,101814,0 +28681,Male,31,Bachelors,13,82,78,63,77,4.0,1,96,Urban,Data Analyst,104718,1 +28682,Male,28,Diploma,14,61,38,0,76,2.0,5,3,Urban,Software Engineer,90150,0 +28683,Male,49,Diploma,13,27,63,97,45,2.0,6,32,Urban,ML Engineer,71674,0 +28684,Female,36,Bachelors,19,26,88,16,95,3.0,7,18,Rural,ML Engineer,43765,0 +28685,Female,54,Masters,16,73,66,2,63,4.0,5,35,Urban,Software Engineer,132293,0 +28686,Male,57,Masters,16,95,78,48,84,1.0,1,70,Semi-Urban,HR Executive,21011,1 +28687,Male,30,Diploma,15,75,85,45,23,0.0,5,72,Urban,Data Analyst,54081,1 +28688,Female,44,Bachelors,19,37,92,77,17,6.0,3,61,Semi-Urban,HR Executive,39685,1 +28689,Male,58,Masters,19,71,31,26,91,4.0,6,99,Semi-Urban,Manager,46388,0 +28690,Male,34,Bachelors,9,80,48,36,23,3.0,7,54,Urban,Manager,96958,0 +28691,Male,30,Diploma,9,25,88,86,74,4.0,6,11,Rural,HR Executive,20896,0 +28692,Male,32,High School,19,31,96,49,91,5.0,2,89,Rural,Software Engineer,31291,1 +28693,Male,30,Bachelors,1,94,85,94,26,1.0,0,7,Urban,ML Engineer,113907,1 +28694,Male,41,Diploma,5,41,90,80,10,8.0,0,73,Semi-Urban,Manager,149014,1 +28695,Male,30,Bachelors,9,55,84,26,21,0.0,4,98,Urban,ML Engineer,79727,1 +28696,Male,38,Bachelors,0,60,6,53,80,2.0,0,96,Urban,HR Executive,70939,0 +28697,Female,23,Bachelors,17,41,33,99,18,8.0,7,57,Semi-Urban,HR Executive,86920,0 +28698,Other,23,Bachelors,12,95,48,99,18,5.0,3,64,Rural,Software Engineer,116157,1 +28699,Other,28,High School,14,69,40,50,36,3.0,6,92,Rural,HR Executive,78890,1 +28700,Female,53,High School,13,87,16,87,87,3.0,3,17,Urban,Manager,78936,0 +28701,Male,38,Bachelors,15,63,66,0,62,8.0,5,23,Urban,ML Engineer,94619,0 +28702,Male,34,Bachelors,18,8,37,8,86,5.0,0,74,Rural,Software Engineer,130589,0 +28703,Female,28,Diploma,2,17,58,88,60,2.0,3,58,Urban,Software Engineer,69294,0 +28704,Male,39,Masters,16,38,63,97,23,1.0,7,80,Rural,Data Analyst,76442,1 +28705,Male,37,Bachelors,17,54,60,51,17,3.0,7,81,Urban,ML Engineer,124541,1 +28706,Male,46,Bachelors,12,30,57,46,75,2.0,5,72,Urban,Manager,20008,0 +28707,Male,31,Masters,14,15,50,34,33,9.0,2,54,Semi-Urban,Data Analyst,22690,0 +28708,Female,22,High School,0,37,52,46,8,6.0,6,74,Semi-Urban,HR Executive,112033,0 +28709,Female,59,Bachelors,10,86,48,72,45,9.0,4,72,Semi-Urban,Software Engineer,37815,1 +28710,Female,32,Bachelors,4,49,99,22,82,1.0,4,26,Urban,Data Analyst,74204,0 +28711,Female,36,Bachelors,8,39,17,16,76,9.0,6,19,Rural,Software Engineer,52240,0 +28712,Male,51,Diploma,6,99,86,66,99,5.0,4,61,Rural,Software Engineer,76021,1 +28713,Female,36,Diploma,14,55,27,61,0,2.0,6,44,Urban,HR Executive,37696,0 +28714,Male,56,High School,15,11,11,29,11,0.0,5,95,Semi-Urban,Manager,70235,0 +28715,Female,52,Bachelors,13,58,98,19,58,1.0,4,59,Semi-Urban,Manager,107233,0 +28716,Male,34,Bachelors,13,79,39,53,17,2.0,4,43,Urban,ML Engineer,78029,0 +28717,Female,30,Bachelors,10,47,32,97,61,8.0,1,4,Urban,Software Engineer,94667,0 +28718,Other,58,Diploma,13,30,24,15,59,0.0,3,23,Rural,Manager,122921,0 +28719,Male,50,Masters,6,36,3,86,7,9.0,7,50,Urban,HR Executive,78175,0 +28720,Male,24,Bachelors,5,97,96,78,20,3.0,4,29,Urban,Data Analyst,94966,1 +28721,Male,24,High School,8,96,91,14,6,5.0,1,35,Urban,HR Executive,30404,1 +28722,Male,36,Bachelors,13,83,23,71,60,4.0,6,18,Urban,ML Engineer,72208,0 +28723,Male,29,Diploma,1,32,63,34,24,8.0,7,19,Urban,HR Executive,61424,0 +28724,Female,42,High School,14,67,97,79,61,7.0,5,5,Urban,Data Analyst,133006,1 +28725,Male,56,Diploma,2,88,27,56,65,8.0,5,10,Rural,Manager,40996,0 +28726,Male,58,Bachelors,13,45,79,56,20,7.0,1,27,Urban,Software Engineer,52193,0 +28727,Female,52,Bachelors,8,37,14,39,60,9.0,6,96,Semi-Urban,HR Executive,38496,0 +28728,Male,52,Bachelors,17,71,55,16,52,6.0,6,75,Urban,Data Analyst,90221,0 +28729,Male,28,Masters,5,65,43,22,86,3.0,2,70,Semi-Urban,Manager,63089,0 +28730,Female,30,Masters,3,6,55,75,58,4.0,7,73,Semi-Urban,Software Engineer,113031,0 +28731,Female,54,Masters,9,30,32,18,33,3.0,0,1,Urban,Data Analyst,25231,0 +28732,Male,44,Bachelors,5,63,24,95,26,4.0,4,79,Semi-Urban,Manager,143862,1 +28733,Male,26,High School,4,39,37,66,80,1.0,7,31,Urban,Software Engineer,57533,0 +28734,Male,32,Masters,12,49,48,72,79,1.0,4,8,Semi-Urban,Data Analyst,124904,0 +28735,Male,40,Diploma,16,62,11,87,91,5.0,7,89,Urban,ML Engineer,54830,1 +28736,Male,33,Bachelors,4,74,86,50,69,3.0,6,88,Urban,Manager,112257,1 +28737,Female,32,Bachelors,8,54,70,93,84,3.0,7,0,Urban,ML Engineer,32574,0 +28738,Female,31,Diploma,9,2,19,2,46,0.0,6,6,Semi-Urban,Data Analyst,42957,0 +28739,Male,58,Masters,13,95,52,99,56,5.0,2,61,Rural,ML Engineer,33640,1 +28740,Male,36,High School,6,58,0,17,10,2.0,4,5,Semi-Urban,HR Executive,108305,0 +28741,Male,27,Bachelors,13,64,58,51,44,4.0,1,17,Semi-Urban,Manager,30652,0 +28742,Male,50,Diploma,19,12,63,46,3,7.0,2,88,Semi-Urban,Manager,52855,0 +28743,Female,41,Bachelors,12,52,12,76,51,1.0,5,31,Urban,ML Engineer,99845,0 +28744,Female,50,Masters,10,62,97,23,72,3.0,3,87,Rural,ML Engineer,50831,1 +28745,Male,26,Bachelors,19,21,19,67,24,7.0,6,30,Urban,ML Engineer,136385,0 +28746,Male,27,PhD,15,88,15,5,12,3.0,0,33,Semi-Urban,ML Engineer,113688,0 +28747,Female,22,Bachelors,17,11,76,6,33,4.0,6,97,Rural,HR Executive,21775,0 +28748,Male,47,Masters,19,3,77,55,28,8.0,2,23,Urban,Software Engineer,123073,0 +28749,Male,38,Bachelors,7,26,94,56,58,2.0,5,78,Semi-Urban,ML Engineer,29621,1 +28750,Male,40,Diploma,3,37,62,40,18,6.0,2,31,Urban,Software Engineer,63826,0 +28751,Male,53,Bachelors,17,31,7,38,27,4.0,4,31,Urban,Software Engineer,142557,0 +28752,Male,37,High School,8,90,20,61,41,0.0,6,96,Urban,Software Engineer,89452,1 +28753,Other,23,Bachelors,10,92,14,80,90,9.0,0,71,Rural,Software Engineer,77792,1 +28754,Male,40,Bachelors,9,53,42,92,32,1.0,0,84,Urban,Software Engineer,75151,1 +28755,Male,52,Bachelors,9,4,54,12,3,3.0,5,46,Rural,Data Analyst,93865,0 +28756,Female,58,High School,7,19,60,18,95,7.0,4,77,Urban,Software Engineer,33807,0 +28757,Male,33,Bachelors,1,18,64,77,88,7.0,0,3,Urban,HR Executive,92083,0 +28758,Male,56,Masters,19,81,37,28,22,0.0,5,97,Rural,Data Analyst,85123,1 +28759,Male,37,Diploma,6,80,63,88,21,6.0,7,81,Rural,Data Analyst,28110,1 +28760,Male,42,Bachelors,5,62,82,61,37,4.0,1,23,Rural,Manager,138735,0 +28761,Female,35,High School,1,56,65,47,64,2.0,4,86,Urban,Software Engineer,63655,1 +28762,Male,35,Bachelors,4,3,13,37,34,8.0,5,71,Urban,Manager,57566,0 +28763,Female,32,Diploma,4,22,70,48,88,1.0,0,40,Urban,Software Engineer,143448,0 +28764,Female,28,Bachelors,12,88,58,22,73,6.0,3,96,Urban,Data Analyst,37035,1 +28765,Male,42,PhD,9,22,71,84,86,7.0,5,58,Semi-Urban,Data Analyst,35237,1 +28766,Male,49,Bachelors,5,89,37,15,73,2.0,5,22,Urban,Data Analyst,33929,0 +28767,Male,32,Bachelors,7,84,60,72,93,4.0,1,53,Urban,HR Executive,52253,1 +28768,Male,56,Diploma,15,63,62,58,68,0.0,0,36,Semi-Urban,Data Analyst,142273,0 +28769,Male,29,Bachelors,11,88,62,30,80,9.0,2,55,Urban,Manager,86082,1 +28770,Male,36,High School,1,79,38,89,49,6.0,6,57,Rural,HR Executive,90765,1 +28771,Female,45,Masters,8,88,55,83,86,6.0,7,86,Urban,Manager,149195,1 +28772,Male,34,Bachelors,12,7,71,62,48,2.0,3,57,Urban,HR Executive,78966,0 +28773,Male,54,High School,11,44,98,80,92,4.0,3,25,Urban,Software Engineer,144334,1 +28774,Male,58,Diploma,3,36,20,99,71,2.0,6,11,Urban,HR Executive,138640,0 +28775,Male,46,Bachelors,18,16,78,19,38,0.0,3,88,Urban,HR Executive,97696,0 +28776,Female,50,Bachelors,16,94,63,31,91,9.0,3,45,Semi-Urban,HR Executive,50922,0 +28777,Female,44,Diploma,5,75,19,36,19,8.0,3,50,Urban,Manager,42596,0 +28778,Male,40,Bachelors,3,5,94,5,39,0.0,7,2,Urban,Manager,27106,0 +28779,Female,38,Masters,2,18,71,34,4,7.0,2,95,Urban,Software Engineer,24398,0 +28780,Female,38,Bachelors,14,77,2,82,62,0.0,7,28,Semi-Urban,Software Engineer,141532,0 +28781,Female,41,Bachelors,5,1,35,19,85,3.0,4,92,Semi-Urban,HR Executive,91541,0 +28782,Female,39,Masters,12,94,37,82,58,2.0,0,12,Semi-Urban,HR Executive,93271,0 +28783,Female,21,Bachelors,11,6,39,36,7,1.0,4,67,Urban,Data Analyst,36466,0 +28784,Male,59,Masters,2,81,65,40,32,4.0,2,53,Semi-Urban,Data Analyst,145581,1 +28785,Male,30,Bachelors,17,17,6,96,53,5.0,4,58,Urban,HR Executive,80246,0 +28786,Male,21,High School,13,23,71,53,59,5.0,2,4,Rural,ML Engineer,70366,0 +28787,Male,56,Bachelors,10,48,74,12,41,9.0,0,28,Rural,ML Engineer,100437,0 +28788,Female,28,High School,8,72,72,16,99,9.0,4,13,Urban,Manager,60655,0 +28789,Male,49,Bachelors,5,26,96,57,81,8.0,2,79,Urban,Software Engineer,42461,1 +28790,Female,48,Bachelors,8,72,14,69,3,1.0,7,41,Urban,HR Executive,69476,0 +28791,Male,50,Diploma,15,68,6,56,59,3.0,3,99,Semi-Urban,Manager,65560,0 +28792,Female,52,Masters,15,92,31,60,58,0.0,3,34,Urban,Software Engineer,63586,0 +28793,Female,25,Masters,4,45,4,60,89,2.0,5,98,Semi-Urban,Software Engineer,116322,0 +28794,Female,41,High School,1,50,95,17,65,3.0,3,13,Semi-Urban,ML Engineer,73043,0 +28795,Female,56,Bachelors,0,67,34,92,71,3.0,6,69,Urban,ML Engineer,53797,1 +28796,Male,52,Bachelors,0,55,27,66,14,3.0,6,41,Semi-Urban,ML Engineer,57369,0 +28797,Male,29,Bachelors,17,10,53,4,34,0.0,5,16,Urban,Manager,72058,0 +28798,Other,54,PhD,16,10,55,48,16,4.0,5,54,Urban,Software Engineer,91300,0 +28799,Male,27,Bachelors,13,71,60,47,72,9.0,7,27,Semi-Urban,Manager,68854,0 +28800,Male,42,Bachelors,3,85,23,17,62,6.0,7,3,Rural,Software Engineer,84734,0 +28801,Male,55,Diploma,8,94,96,79,1,9.0,5,17,Urban,Manager,21917,1 +28802,Male,56,High School,8,64,79,45,96,6.0,7,42,Rural,HR Executive,31231,0 +28803,Female,32,Bachelors,17,84,5,25,3,2.0,7,98,Rural,HR Executive,105134,0 +28804,Female,50,PhD,6,58,65,23,32,3.0,6,90,Urban,ML Engineer,48080,0 +28805,Female,25,Diploma,11,11,25,81,30,2.0,0,27,Urban,HR Executive,99861,0 +28806,Male,27,High School,5,43,58,80,1,6.0,5,0,Semi-Urban,ML Engineer,36376,0 +28807,Male,22,High School,14,39,22,51,62,3.0,3,28,Urban,ML Engineer,35671,0 +28808,Female,58,Bachelors,1,56,79,49,7,2.0,5,60,Rural,HR Executive,80796,1 +28809,Other,56,Masters,12,65,29,17,32,3.0,2,9,Urban,Manager,101510,0 +28810,Other,50,High School,0,34,13,22,66,0.0,0,24,Urban,HR Executive,85073,0 +28811,Female,41,Bachelors,12,50,77,81,18,5.0,1,40,Rural,Manager,29527,1 +28812,Male,57,Masters,16,90,44,53,79,3.0,4,98,Rural,Software Engineer,67272,1 +28813,Male,30,High School,19,56,69,34,91,1.0,4,68,Urban,ML Engineer,26669,0 +28814,Female,46,Masters,16,63,13,85,6,9.0,5,47,Semi-Urban,HR Executive,111334,0 +28815,Female,41,Bachelors,7,69,87,68,24,9.0,1,87,Rural,Software Engineer,132274,1 +28816,Female,30,Bachelors,1,84,39,43,41,4.0,1,59,Semi-Urban,ML Engineer,134161,0 +28817,Male,57,High School,11,55,10,30,57,0.0,3,14,Urban,ML Engineer,29349,0 +28818,Female,54,Bachelors,12,13,14,47,88,9.0,0,64,Urban,Data Analyst,93658,0 +28819,Male,25,Bachelors,3,71,0,83,81,2.0,1,19,Urban,Manager,61092,0 +28820,Male,21,Diploma,6,10,59,50,61,4.0,4,71,Urban,Software Engineer,123183,0 +28821,Male,40,Bachelors,9,40,86,43,95,4.0,6,50,Semi-Urban,ML Engineer,81187,0 +28822,Female,38,Bachelors,19,66,51,5,61,3.0,5,66,Urban,HR Executive,139923,0 +28823,Male,55,Diploma,5,64,76,35,63,2.0,7,32,Rural,Manager,117354,0 +28824,Male,45,Diploma,9,62,56,84,17,7.0,4,99,Urban,Software Engineer,96988,1 +28825,Male,58,Masters,12,21,49,14,14,8.0,5,92,Rural,HR Executive,74329,0 +28826,Female,54,Bachelors,13,15,46,21,53,1.0,0,39,Urban,Manager,103400,0 +28827,Male,57,Masters,19,97,94,83,11,8.0,2,4,Urban,HR Executive,20265,1 +28828,Female,38,Diploma,19,16,5,0,36,5.0,3,66,Rural,ML Engineer,48057,0 +28829,Male,51,Bachelors,1,16,62,97,61,0.0,3,39,Urban,Data Analyst,89843,0 +28830,Male,57,Diploma,14,91,54,75,85,7.0,6,88,Urban,Manager,71764,1 +28831,Female,32,Bachelors,0,41,52,47,13,5.0,2,40,Urban,Manager,63452,0 +28832,Male,28,Bachelors,9,87,30,25,10,3.0,1,63,Urban,Software Engineer,100730,0 +28833,Male,43,Masters,8,87,33,30,17,0.0,3,70,Urban,HR Executive,99109,0 +28834,Male,52,Masters,13,42,31,29,23,2.0,3,74,Rural,ML Engineer,77108,0 +28835,Female,42,Diploma,9,28,61,33,21,3.0,4,68,Semi-Urban,Manager,62536,0 +28836,Male,53,Diploma,6,71,80,19,38,1.0,1,14,Semi-Urban,Software Engineer,111689,0 +28837,Male,53,Bachelors,7,33,82,32,79,7.0,6,86,Urban,Data Analyst,127662,0 +28838,Female,23,Bachelors,17,66,66,58,31,4.0,0,76,Urban,HR Executive,107803,1 +28839,Male,31,High School,15,44,61,71,37,1.0,7,52,Urban,Software Engineer,44125,0 +28840,Male,32,PhD,11,96,90,4,41,5.0,0,24,Semi-Urban,ML Engineer,72536,0 +28841,Male,46,High School,9,34,26,5,63,7.0,7,44,Urban,ML Engineer,100259,0 +28842,Female,29,High School,7,90,72,18,6,6.0,0,79,Urban,Software Engineer,139056,1 +28843,Male,29,Diploma,16,57,25,15,73,1.0,0,98,Urban,Software Engineer,76458,0 +28844,Female,33,Diploma,14,61,37,7,74,5.0,1,89,Urban,Software Engineer,79785,0 +28845,Female,35,High School,2,72,63,45,84,2.0,6,32,Urban,HR Executive,36712,0 +28846,Male,43,Masters,5,27,86,2,83,5.0,2,2,Semi-Urban,Data Analyst,149560,0 +28847,Female,45,Masters,16,57,69,48,28,5.0,4,94,Rural,Data Analyst,116343,1 +28848,Male,50,Bachelors,3,38,1,52,83,4.0,5,95,Rural,HR Executive,83861,0 +28849,Male,58,High School,11,83,79,33,19,6.0,0,25,Urban,Software Engineer,65040,0 +28850,Female,45,High School,9,37,99,76,34,9.0,1,26,Urban,Data Analyst,113338,0 +28851,Male,43,PhD,18,16,90,64,30,9.0,6,63,Urban,HR Executive,129782,0 +28852,Male,42,Bachelors,15,71,55,41,96,1.0,6,58,Urban,Manager,122716,0 +28853,Male,35,Masters,13,77,42,60,18,7.0,3,7,Rural,HR Executive,123547,0 +28854,Male,23,Bachelors,19,39,75,4,77,7.0,6,9,Rural,HR Executive,35406,0 +28855,Male,34,Diploma,4,93,98,46,99,7.0,5,76,Urban,HR Executive,52902,1 +28856,Female,31,Masters,12,29,63,22,76,0.0,4,94,Urban,Manager,120067,0 +28857,Female,22,High School,7,18,90,85,25,6.0,7,27,Semi-Urban,Manager,104102,0 +28858,Male,58,Bachelors,10,69,80,87,63,3.0,1,69,Urban,Data Analyst,125998,1 +28859,Male,31,Diploma,17,22,58,25,48,8.0,3,87,Semi-Urban,HR Executive,75759,0 +28860,Male,52,Bachelors,19,98,70,74,47,4.0,1,42,Urban,Software Engineer,129023,1 +28861,Male,43,Bachelors,16,9,9,23,28,6.0,3,7,Urban,Software Engineer,102895,0 +28862,Male,29,Bachelors,12,21,53,38,40,4.0,2,98,Urban,HR Executive,101380,0 +28863,Male,43,Bachelors,2,29,49,16,48,0.0,1,90,Urban,ML Engineer,56341,0 +28864,Male,53,PhD,14,35,24,51,71,4.0,5,70,Urban,ML Engineer,54344,0 +28865,Male,53,Bachelors,14,20,22,96,93,4.0,0,18,Urban,Data Analyst,46674,0 +28866,Female,23,Bachelors,14,73,22,31,7,8.0,3,12,Semi-Urban,Data Analyst,27728,0 +28867,Male,44,Bachelors,14,88,99,56,84,4.0,7,38,Urban,ML Engineer,138525,1 +28868,Female,51,Masters,15,73,12,75,57,9.0,4,73,Urban,ML Engineer,57157,0 +28869,Female,56,High School,1,81,86,65,8,9.0,3,45,Urban,Manager,28226,1 +28870,Other,31,Masters,13,2,31,39,94,1.0,7,58,Urban,Software Engineer,130105,0 +28871,Female,43,Diploma,4,63,13,38,66,7.0,6,83,Urban,Software Engineer,99162,0 +28872,Female,25,High School,0,78,0,54,94,0.0,5,71,Semi-Urban,ML Engineer,130424,0 +28873,Male,38,Bachelors,16,66,52,35,59,9.0,0,33,Urban,Software Engineer,141477,0 +28874,Male,23,PhD,11,70,66,31,98,9.0,4,24,Semi-Urban,Manager,91017,0 +28875,Female,53,Bachelors,16,59,75,64,63,7.0,0,23,Urban,ML Engineer,50509,0 +28876,Female,50,Masters,2,38,65,25,81,1.0,4,0,Urban,ML Engineer,121571,0 +28877,Male,51,Bachelors,13,82,61,56,17,8.0,1,58,Urban,HR Executive,148862,1 +28878,Female,49,Diploma,10,15,5,22,24,7.0,3,23,Urban,ML Engineer,51260,0 +28879,Male,39,Bachelors,0,88,34,67,64,3.0,2,16,Urban,Data Analyst,87854,0 +28880,Male,53,Diploma,12,20,32,33,40,6.0,7,91,Semi-Urban,Data Analyst,126697,0 +28881,Male,21,Bachelors,9,14,77,79,23,1.0,7,8,Rural,Manager,135657,0 +28882,Female,39,Diploma,9,3,78,36,54,5.0,1,52,Rural,Manager,69606,0 +28883,Female,54,Masters,4,70,27,87,40,4.0,0,66,Semi-Urban,Manager,116744,1 +28884,Female,23,Bachelors,9,30,86,62,3,6.0,6,94,Rural,Data Analyst,121094,1 +28885,Female,49,Bachelors,4,70,94,93,29,1.0,0,54,Urban,Data Analyst,107405,1 +28886,Male,50,Diploma,13,7,76,78,83,9.0,1,37,Urban,HR Executive,109056,0 +28887,Female,30,Bachelors,7,43,31,89,70,1.0,1,17,Semi-Urban,HR Executive,102238,0 +28888,Male,22,High School,3,19,40,34,86,9.0,2,61,Semi-Urban,Software Engineer,139105,0 +28889,Female,31,Diploma,0,37,7,40,99,8.0,5,60,Urban,HR Executive,48445,0 +28890,Male,25,Diploma,8,61,31,10,28,1.0,6,99,Urban,Software Engineer,58563,0 +28891,Male,51,Bachelors,12,6,65,24,78,2.0,5,65,Urban,HR Executive,80484,0 +28892,Female,56,Diploma,15,46,67,29,56,7.0,3,82,Rural,Manager,112771,0 +28893,Female,23,PhD,3,22,55,55,55,7.0,3,35,Rural,ML Engineer,53319,0 +28894,Male,46,Diploma,4,54,10,33,52,8.0,7,33,Urban,ML Engineer,78748,0 +28895,Female,48,Masters,17,4,70,93,56,9.0,5,66,Urban,Software Engineer,116322,0 +28896,Male,25,High School,9,85,43,19,80,5.0,7,52,Urban,Manager,124277,0 +28897,Male,59,High School,10,60,61,97,61,9.0,6,12,Semi-Urban,Software Engineer,66668,0 +28898,Female,51,High School,2,97,18,14,0,7.0,2,42,Urban,Manager,140267,0 +28899,Male,50,Bachelors,3,63,26,73,48,8.0,5,64,Urban,Software Engineer,57929,0 +28900,Female,29,Bachelors,10,9,41,1,82,0.0,0,33,Semi-Urban,Manager,102981,0 +28901,Male,27,Bachelors,11,17,81,26,87,4.0,7,44,Rural,Software Engineer,123821,0 +28902,Male,55,Masters,9,42,2,97,93,7.0,3,68,Urban,ML Engineer,133697,0 +28903,Male,41,Diploma,6,68,78,56,28,0.0,1,82,Semi-Urban,Manager,99027,1 +28904,Male,25,Bachelors,13,80,46,57,51,2.0,0,83,Urban,HR Executive,127681,1 +28905,Male,43,Diploma,9,20,81,60,17,4.0,4,95,Urban,ML Engineer,45301,1 +28906,Female,51,High School,13,80,27,93,87,6.0,5,96,Urban,Manager,142079,1 +28907,Other,54,Bachelors,11,13,6,4,25,6.0,3,56,Rural,HR Executive,137913,0 +28908,Female,40,Bachelors,16,58,28,25,43,8.0,5,19,Urban,Data Analyst,92767,0 +28909,Female,41,PhD,12,52,78,75,47,4.0,7,63,Urban,HR Executive,98327,1 +28910,Male,36,High School,6,97,2,14,15,9.0,2,30,Urban,Manager,124930,0 +28911,Male,45,Diploma,8,10,32,48,61,0.0,5,92,Semi-Urban,HR Executive,31675,0 +28912,Male,27,Bachelors,6,51,64,15,45,0.0,2,44,Urban,Data Analyst,74206,0 +28913,Male,28,Bachelors,10,35,54,49,48,2.0,3,1,Semi-Urban,HR Executive,124067,0 +28914,Female,51,Bachelors,7,56,33,80,40,8.0,3,68,Urban,Data Analyst,82676,0 +28915,Male,22,Masters,13,3,40,24,95,6.0,6,80,Urban,Manager,70187,0 +28916,Male,42,Bachelors,16,58,62,31,90,2.0,7,76,Semi-Urban,Data Analyst,62588,0 +28917,Male,22,High School,14,68,28,44,89,0.0,6,21,Semi-Urban,Software Engineer,131395,0 +28918,Male,51,Bachelors,12,98,46,25,38,8.0,7,58,Semi-Urban,Software Engineer,45235,0 +28919,Male,35,Bachelors,12,7,95,81,35,0.0,1,43,Urban,HR Executive,30907,0 +28920,Female,26,Masters,8,91,37,62,62,8.0,0,14,Rural,Manager,35656,0 +28921,Male,24,High School,18,99,7,36,17,9.0,5,95,Urban,HR Executive,65253,1 +28922,Female,43,Bachelors,10,30,45,44,55,0.0,3,38,Urban,Software Engineer,132041,0 +28923,Male,44,Masters,10,9,69,29,75,0.0,4,5,Urban,HR Executive,23684,0 +28924,Female,59,Masters,13,13,50,64,45,1.0,0,50,Rural,Data Analyst,72623,0 +28925,Female,52,High School,11,14,67,92,12,6.0,3,88,Urban,ML Engineer,98772,1 +28926,Female,48,High School,18,75,62,53,65,5.0,5,67,Rural,Software Engineer,82885,1 +28927,Male,45,Diploma,19,72,2,46,88,6.0,6,9,Urban,Manager,90954,0 +28928,Male,59,Masters,6,81,83,60,28,0.0,3,17,Urban,ML Engineer,61438,1 +28929,Female,34,High School,16,41,31,2,86,3.0,4,73,Semi-Urban,Manager,33287,0 +28930,Male,55,High School,3,40,31,40,50,3.0,6,53,Urban,Data Analyst,110886,0 +28931,Male,33,Bachelors,10,94,28,21,55,9.0,4,55,Rural,Data Analyst,140069,0 +28932,Male,41,Masters,8,84,86,50,75,5.0,2,10,Semi-Urban,Software Engineer,141031,0 +28933,Female,57,Bachelors,17,89,11,39,4,0.0,6,31,Semi-Urban,Manager,34313,0 +28934,Male,31,Masters,12,67,60,74,56,0.0,5,13,Urban,Data Analyst,100444,0 +28935,Female,24,Masters,17,49,67,35,41,0.0,6,6,Semi-Urban,HR Executive,100146,0 +28936,Male,24,Bachelors,5,68,20,50,19,1.0,4,89,Rural,Data Analyst,118085,0 +28937,Male,29,Diploma,14,40,19,76,2,7.0,0,62,Urban,ML Engineer,53650,0 +28938,Male,58,High School,1,68,73,64,70,3.0,5,94,Urban,HR Executive,63926,1 +28939,Male,25,Bachelors,2,26,86,26,53,0.0,0,96,Urban,Data Analyst,131358,0 +28940,Male,33,Diploma,9,48,5,59,98,5.0,0,85,Semi-Urban,HR Executive,140883,0 +28941,Male,31,Diploma,6,93,81,47,29,0.0,5,92,Rural,HR Executive,148500,1 +28942,Male,27,Diploma,3,77,64,81,24,7.0,4,42,Semi-Urban,Data Analyst,74859,1 +28943,Female,34,Bachelors,14,17,75,62,30,6.0,3,79,Urban,Data Analyst,76264,0 +28944,Male,35,Masters,19,2,84,88,35,6.0,1,8,Semi-Urban,ML Engineer,100600,0 +28945,Male,53,Bachelors,8,89,94,78,49,4.0,5,43,Urban,Manager,48130,1 +28946,Male,59,Diploma,2,84,51,66,72,4.0,3,49,Semi-Urban,Data Analyst,146784,1 +28947,Male,54,Diploma,2,41,4,44,44,2.0,3,16,Rural,Software Engineer,28032,0 +28948,Male,39,Bachelors,5,35,73,58,37,2.0,0,68,Semi-Urban,ML Engineer,67447,0 +28949,Male,33,Masters,1,15,65,74,20,3.0,3,66,Urban,HR Executive,32627,0 +28950,Female,49,Diploma,9,28,10,28,41,5.0,0,26,Semi-Urban,Software Engineer,24564,0 +28951,Male,24,High School,9,17,1,92,45,7.0,0,13,Urban,Data Analyst,38367,0 +28952,Female,53,Masters,15,3,96,95,65,7.0,1,57,Urban,Manager,69570,1 +28953,Male,24,Masters,2,81,35,11,6,2.0,2,65,Urban,HR Executive,58971,0 +28954,Female,22,Bachelors,9,68,54,76,10,1.0,4,80,Urban,Manager,129968,1 +28955,Male,59,Bachelors,5,27,53,49,45,0.0,4,1,Urban,Software Engineer,90900,0 +28956,Male,21,Diploma,19,83,29,9,71,0.0,0,64,Urban,ML Engineer,74148,0 +28957,Female,59,Diploma,9,2,19,75,70,3.0,0,77,Rural,ML Engineer,27565,0 +28958,Male,34,Bachelors,7,70,88,85,68,8.0,0,95,Urban,HR Executive,98762,1 +28959,Male,54,Bachelors,17,1,83,42,30,4.0,0,14,Urban,Data Analyst,121153,0 +28960,Male,24,High School,1,40,36,20,11,8.0,7,84,Semi-Urban,Manager,126721,0 +28961,Female,24,Masters,14,85,44,73,74,3.0,3,58,Rural,Data Analyst,107330,1 +28962,Female,43,Diploma,9,42,37,54,59,1.0,6,43,Urban,Data Analyst,126747,0 +28963,Female,44,Bachelors,5,16,4,48,49,5.0,2,69,Semi-Urban,Data Analyst,133269,0 +28964,Female,44,High School,2,92,92,6,35,7.0,0,10,Urban,Data Analyst,36879,0 +28965,Male,46,Diploma,3,32,77,10,73,7.0,2,34,Semi-Urban,Software Engineer,149457,0 +28966,Male,56,Bachelors,2,53,38,3,29,8.0,3,1,Urban,Data Analyst,65905,0 +28967,Female,22,Bachelors,6,70,65,6,20,5.0,5,60,Urban,Data Analyst,52205,0 +28968,Other,27,Bachelors,10,13,74,57,1,3.0,1,35,Urban,ML Engineer,116340,0 +28969,Male,38,Masters,6,83,71,66,16,6.0,6,66,Semi-Urban,Manager,54937,1 +28970,Other,44,Masters,17,18,51,17,82,8.0,6,97,Rural,Software Engineer,142730,0 +28971,Male,48,High School,7,21,13,62,42,6.0,4,45,Urban,HR Executive,134857,0 +28972,Female,54,Bachelors,4,49,0,26,57,7.0,6,5,Rural,ML Engineer,131798,0 +28973,Female,30,Masters,14,15,15,28,61,5.0,7,47,Urban,HR Executive,130200,0 +28974,Female,50,Masters,14,67,82,85,82,1.0,6,56,Rural,ML Engineer,141187,1 +28975,Male,41,Diploma,7,44,41,12,28,9.0,4,51,Semi-Urban,Manager,126173,0 +28976,Male,47,Masters,19,72,96,74,81,0.0,7,18,Rural,ML Engineer,88857,1 +28977,Male,25,High School,12,37,69,87,42,3.0,1,47,Rural,ML Engineer,138774,1 +28978,Male,55,Bachelors,14,74,74,78,18,6.0,1,25,Semi-Urban,Software Engineer,136185,1 +28979,Female,44,PhD,19,41,46,92,66,3.0,0,93,Urban,HR Executive,58860,1 +28980,Female,46,Bachelors,5,30,44,44,50,6.0,1,47,Rural,Software Engineer,87519,0 +28981,Male,21,Bachelors,4,15,27,26,28,5.0,4,46,Rural,Manager,122513,0 +28982,Male,52,Masters,13,89,38,43,32,8.0,1,53,Rural,Software Engineer,62787,0 +28983,Male,30,Masters,10,64,52,68,54,7.0,7,4,Rural,ML Engineer,141333,0 +28984,Male,44,Bachelors,11,96,33,85,26,7.0,6,69,Urban,Software Engineer,127040,1 +28985,Female,36,Bachelors,18,9,29,77,5,8.0,6,69,Semi-Urban,Software Engineer,30808,0 +28986,Female,44,Masters,3,64,0,52,17,0.0,4,22,Urban,HR Executive,101812,0 +28987,Other,49,Diploma,16,55,96,58,35,4.0,1,0,Semi-Urban,Manager,111608,0 +28988,Male,41,High School,9,81,39,99,79,6.0,0,42,Urban,Data Analyst,102217,1 +28989,Male,46,Masters,7,49,66,39,95,5.0,6,10,Urban,Software Engineer,97447,0 +28990,Male,25,Masters,4,42,4,1,24,1.0,4,17,Urban,Software Engineer,93555,0 +28991,Male,24,High School,8,88,62,22,76,6.0,5,95,Semi-Urban,Data Analyst,36235,1 +28992,Other,49,Diploma,19,3,54,88,99,2.0,6,62,Urban,ML Engineer,61205,0 +28993,Male,28,Bachelors,18,57,84,63,70,3.0,1,31,Semi-Urban,Manager,133550,1 +28994,Male,28,Masters,14,32,98,30,63,2.0,5,41,Urban,ML Engineer,79734,0 +28995,Female,31,Diploma,4,66,59,54,2,6.0,1,16,Rural,Manager,127930,0 +28996,Female,56,Masters,6,44,73,38,24,5.0,7,72,Rural,Data Analyst,24181,0 +28997,Male,33,Masters,10,75,99,40,32,6.0,3,33,Semi-Urban,HR Executive,147383,1 +28998,Female,59,Bachelors,5,12,44,12,59,6.0,7,28,Urban,Software Engineer,57765,0 +28999,Male,45,Diploma,16,78,58,0,46,3.0,5,87,Urban,Data Analyst,129677,0 +29000,Female,39,Masters,19,30,51,90,66,3.0,4,79,Urban,Software Engineer,58780,1 +29001,Male,56,Bachelors,9,40,47,10,90,5.0,6,58,Urban,HR Executive,100836,0 +29002,Male,45,Diploma,4,97,11,17,36,3.0,4,13,Urban,Manager,60242,0 +29003,Male,53,High School,13,55,22,92,1,5.0,0,59,Urban,Software Engineer,136727,0 +29004,Male,40,Diploma,13,92,17,56,78,1.0,7,53,Rural,HR Executive,84285,0 +29005,Male,33,Diploma,18,31,57,27,78,2.0,0,40,Urban,Software Engineer,106696,0 +29006,Female,48,Bachelors,8,16,77,77,17,7.0,2,84,Urban,HR Executive,57925,1 +29007,Male,52,Bachelors,10,45,30,73,66,3.0,3,92,Semi-Urban,HR Executive,68196,1 +29008,Female,49,Diploma,2,60,98,51,70,7.0,2,82,Urban,HR Executive,139712,1 +29009,Male,30,Diploma,19,0,52,77,2,2.0,7,51,Urban,Manager,80139,0 +29010,Male,40,Bachelors,3,25,57,74,39,0.0,7,85,Urban,Software Engineer,63076,1 +29011,Other,52,Bachelors,15,49,50,75,56,6.0,2,26,Urban,HR Executive,99572,0 +29012,Female,48,PhD,9,14,68,1,63,8.0,7,97,Urban,HR Executive,126865,0 +29013,Male,32,Bachelors,7,80,48,19,12,4.0,7,6,Urban,Software Engineer,54599,0 +29014,Male,58,PhD,13,0,86,76,62,4.0,1,31,Urban,Data Analyst,78635,0 +29015,Female,29,Bachelors,11,83,68,97,40,7.0,3,80,Urban,Data Analyst,77557,1 +29016,Male,39,Masters,8,53,40,38,67,7.0,6,44,Rural,Data Analyst,141257,0 +29017,Male,51,High School,12,97,65,82,5,6.0,4,42,Rural,Data Analyst,99415,1 +29018,Male,39,Masters,12,27,22,36,83,8.0,0,66,Rural,Data Analyst,91078,0 +29019,Male,30,Bachelors,3,41,27,25,10,7.0,6,31,Rural,Manager,128776,0 +29020,Male,43,Bachelors,16,28,37,63,22,0.0,1,8,Urban,ML Engineer,52375,0 +29021,Female,22,Bachelors,17,76,10,14,34,2.0,3,82,Semi-Urban,Manager,46139,0 +29022,Male,50,Masters,3,89,0,8,0,3.0,7,75,Rural,Manager,37335,0 +29023,Male,52,Bachelors,10,92,16,83,68,6.0,5,16,Rural,Software Engineer,148459,0 +29024,Female,54,High School,19,5,66,68,26,4.0,5,80,Urban,Data Analyst,54281,0 +29025,Female,41,Masters,12,99,51,89,4,7.0,0,14,Semi-Urban,Software Engineer,101386,1 +29026,Male,35,Bachelors,5,54,43,29,51,5.0,7,42,Semi-Urban,ML Engineer,58066,0 +29027,Female,50,Bachelors,6,37,53,88,59,4.0,0,13,Semi-Urban,Data Analyst,88811,0 +29028,Female,28,Bachelors,3,98,11,73,3,6.0,5,18,Rural,Software Engineer,148663,0 +29029,Male,39,Masters,3,3,39,82,34,0.0,0,37,Semi-Urban,ML Engineer,67404,0 +29030,Male,50,PhD,16,95,85,15,11,3.0,3,89,Semi-Urban,Manager,141184,1 +29031,Female,45,Diploma,12,64,78,43,74,2.0,5,24,Semi-Urban,ML Engineer,143346,0 +29032,Male,34,Diploma,6,19,87,30,48,7.0,6,5,Urban,Data Analyst,49455,0 +29033,Male,23,Bachelors,8,63,97,29,57,6.0,1,64,Rural,Software Engineer,66651,1 +29034,Female,39,Diploma,11,42,14,91,2,0.0,3,65,Urban,Manager,56744,0 +29035,Male,37,Bachelors,10,13,36,82,13,8.0,2,34,Urban,Data Analyst,96286,0 +29036,Female,26,Bachelors,3,26,0,25,80,6.0,4,14,Rural,HR Executive,103333,0 +29037,Male,45,Diploma,4,84,94,35,50,2.0,7,39,Urban,Software Engineer,149633,1 +29038,Male,40,Bachelors,9,10,29,10,83,1.0,4,29,Semi-Urban,Manager,88518,0 +29039,Male,35,High School,12,11,52,57,63,4.0,2,87,Urban,Manager,128143,0 +29040,Male,37,Masters,6,37,34,30,77,0.0,5,70,Semi-Urban,HR Executive,128732,0 +29041,Female,28,Diploma,17,88,4,36,94,5.0,6,46,Urban,HR Executive,49908,0 +29042,Female,57,Bachelors,0,72,45,38,79,1.0,6,57,Urban,HR Executive,70826,0 +29043,Male,50,Diploma,13,71,17,35,95,9.0,4,73,Urban,HR Executive,69934,0 +29044,Other,25,Bachelors,15,85,38,56,95,8.0,7,30,Urban,HR Executive,69202,0 +29045,Male,56,Bachelors,16,12,51,28,69,0.0,5,10,Urban,Manager,71489,0 +29046,Male,33,Bachelors,1,8,90,37,47,3.0,2,20,Urban,Manager,29197,0 +29047,Male,31,Diploma,0,14,57,44,12,4.0,3,42,Rural,Manager,143549,0 +29048,Male,34,Diploma,11,6,58,46,92,7.0,2,14,Urban,Data Analyst,69701,0 +29049,Female,37,Bachelors,1,12,60,76,58,5.0,1,43,Urban,Data Analyst,119310,0 +29050,Male,29,Masters,6,42,64,15,35,5.0,3,54,Rural,HR Executive,79389,0 +29051,Male,29,Diploma,2,41,54,25,81,1.0,3,16,Urban,Data Analyst,64261,0 +29052,Male,44,High School,6,61,42,84,14,0.0,5,74,Urban,ML Engineer,145186,1 +29053,Female,44,Masters,18,77,62,50,89,2.0,2,5,Urban,Data Analyst,23584,0 +29054,Female,27,Diploma,1,8,25,38,95,0.0,1,81,Urban,ML Engineer,39044,0 +29055,Female,50,Bachelors,15,83,86,66,10,7.0,4,95,Semi-Urban,ML Engineer,74192,1 +29056,Male,56,Bachelors,19,51,30,93,9,9.0,3,94,Urban,ML Engineer,49988,1 +29057,Male,53,Bachelors,5,64,35,2,57,8.0,0,50,Urban,ML Engineer,106467,0 +29058,Male,38,Diploma,4,18,80,51,51,1.0,7,89,Rural,HR Executive,36152,1 +29059,Male,51,PhD,16,54,98,36,35,2.0,1,8,Rural,HR Executive,76912,0 +29060,Female,58,Bachelors,7,65,33,50,3,1.0,5,63,Semi-Urban,ML Engineer,148349,0 +29061,Male,35,High School,1,53,88,80,37,3.0,0,86,Urban,Manager,136474,1 +29062,Male,47,Masters,16,6,38,7,23,6.0,3,79,Semi-Urban,Data Analyst,124057,0 +29063,Male,38,High School,9,37,30,1,43,6.0,5,29,Urban,Data Analyst,87496,0 +29064,Male,21,Diploma,7,79,14,66,32,0.0,3,82,Semi-Urban,ML Engineer,51775,1 +29065,Male,50,Masters,0,47,46,75,19,7.0,6,32,Semi-Urban,Manager,144055,0 +29066,Male,49,Bachelors,14,13,48,48,52,6.0,1,0,Urban,ML Engineer,100407,0 +29067,Male,32,High School,11,12,55,76,80,8.0,3,11,Urban,Manager,127682,0 +29068,Female,32,Bachelors,10,47,48,75,81,8.0,5,7,Semi-Urban,Data Analyst,20493,0 +29069,Male,23,Bachelors,17,93,45,25,92,5.0,3,50,Semi-Urban,Manager,70408,0 +29070,Female,47,High School,7,98,60,32,3,6.0,4,32,Urban,HR Executive,76514,0 +29071,Female,21,PhD,16,83,10,34,4,1.0,5,98,Urban,ML Engineer,149460,0 +29072,Female,54,Bachelors,12,85,90,52,1,0.0,4,81,Semi-Urban,Software Engineer,145951,1 +29073,Male,52,Bachelors,19,72,19,15,21,6.0,6,85,Urban,ML Engineer,144290,0 +29074,Male,59,High School,2,11,80,2,72,9.0,4,21,Urban,HR Executive,62419,0 +29075,Female,47,Bachelors,1,53,77,15,5,2.0,3,3,Rural,HR Executive,115916,0 +29076,Male,22,Diploma,4,61,28,79,25,2.0,1,78,Semi-Urban,ML Engineer,76321,1 +29077,Male,30,High School,11,23,17,20,69,0.0,1,49,Urban,Software Engineer,123320,0 +29078,Male,43,PhD,2,1,8,45,35,3.0,4,33,Urban,HR Executive,70857,0 +29079,Female,41,Bachelors,18,67,1,3,51,9.0,3,29,Semi-Urban,Software Engineer,140370,0 +29080,Other,29,Bachelors,11,48,42,85,78,9.0,6,13,Semi-Urban,HR Executive,132662,0 +29081,Male,47,Diploma,10,49,64,51,92,0.0,2,1,Semi-Urban,ML Engineer,68847,0 +29082,Male,44,Masters,18,70,40,84,52,6.0,0,67,Rural,Manager,114711,1 +29083,Female,27,Masters,15,15,44,37,38,2.0,5,12,Urban,Data Analyst,50797,0 +29084,Male,30,Masters,13,19,7,53,37,8.0,6,87,Rural,Data Analyst,23155,0 +29085,Male,22,Bachelors,15,30,52,15,59,6.0,0,41,Urban,ML Engineer,123298,0 +29086,Male,50,Diploma,6,68,68,65,5,7.0,6,28,Urban,HR Executive,101950,0 +29087,Female,56,Masters,3,48,30,63,14,4.0,5,10,Urban,Software Engineer,106983,0 +29088,Male,34,Diploma,2,97,49,29,55,7.0,2,54,Urban,ML Engineer,47549,0 +29089,Male,53,PhD,18,50,47,19,97,4.0,4,69,Urban,Software Engineer,58145,0 +29090,Male,24,Diploma,9,63,12,49,95,0.0,3,33,Urban,ML Engineer,108762,0 +29091,Female,53,Diploma,2,83,72,6,34,1.0,0,84,Urban,Manager,110399,1 +29092,Female,44,Bachelors,2,73,13,62,7,1.0,0,39,Urban,HR Executive,86230,0 +29093,Male,34,Masters,7,91,21,4,43,4.0,0,91,Semi-Urban,ML Engineer,43789,0 +29094,Female,32,Bachelors,13,18,10,67,32,8.0,3,59,Urban,HR Executive,138071,0 +29095,Male,52,Bachelors,8,42,74,70,85,0.0,1,53,Semi-Urban,Software Engineer,56635,1 +29096,Male,52,High School,15,50,61,66,90,9.0,6,34,Urban,Manager,32063,0 +29097,Female,33,Masters,9,58,53,91,12,9.0,7,13,Semi-Urban,Data Analyst,23037,0 +29098,Male,26,Bachelors,4,57,91,66,38,5.0,3,15,Urban,Software Engineer,144275,0 +29099,Male,57,Masters,1,11,95,20,90,9.0,2,97,Urban,HR Executive,27130,0 +29100,Male,59,Diploma,5,18,55,24,82,6.0,1,38,Urban,Manager,145310,0 +29101,Female,24,Diploma,9,78,63,21,76,5.0,7,87,Urban,HR Executive,98382,1 +29102,Female,30,Bachelors,8,18,26,29,95,,3,21,Semi-Urban,ML Engineer,84558,0 +29103,Female,44,Masters,17,30,48,55,17,2.0,6,47,Urban,Manager,37609,0 +29104,Male,32,Bachelors,10,36,38,67,60,3.0,0,99,Semi-Urban,Manager,138661,1 +29105,Female,52,High School,10,36,59,12,44,6.0,3,1,Urban,Software Engineer,58946,0 +29106,Male,53,Bachelors,2,41,95,18,54,7.0,5,24,Semi-Urban,ML Engineer,78716,0 +29107,Female,34,Diploma,5,44,33,1,71,1.0,6,45,Urban,Software Engineer,34500,0 +29108,Female,58,Diploma,13,96,68,69,83,0.0,5,53,Rural,Data Analyst,26779,1 +29109,Male,59,Diploma,15,18,95,81,5,6.0,3,31,Semi-Urban,Data Analyst,36556,0 +29110,Male,30,Masters,0,33,8,56,52,4.0,2,23,Urban,Software Engineer,45019,0 +29111,Male,29,PhD,6,68,57,71,15,3.0,1,75,Semi-Urban,HR Executive,73997,1 +29112,Female,22,Bachelors,2,15,58,79,79,3.0,1,0,Urban,Software Engineer,118216,0 +29113,Male,56,High School,2,98,58,98,38,4.0,0,76,Urban,Data Analyst,70657,1 +29114,Male,34,High School,2,50,67,45,54,9.0,3,58,Urban,Manager,148387,0 +29115,Male,57,Masters,10,71,13,97,61,2.0,5,84,Rural,ML Engineer,53503,1 +29116,Male,44,Bachelors,5,1,52,28,45,0.0,4,11,Rural,Data Analyst,92010,0 +29117,Female,27,Bachelors,16,29,67,17,61,5.0,0,39,Urban,Data Analyst,83335,0 +29118,Male,39,Diploma,5,23,88,95,60,4.0,2,30,Urban,Software Engineer,38905,1 +29119,Male,48,Bachelors,3,74,1,36,60,3.0,0,92,Urban,Data Analyst,37584,0 +29120,Female,57,Diploma,1,38,99,98,21,7.0,3,88,Semi-Urban,Software Engineer,100677,1 +29121,Female,31,Masters,16,96,4,11,32,6.0,5,71,Urban,Software Engineer,126973,0 +29122,Male,56,Masters,9,55,41,55,2,8.0,7,59,Rural,Data Analyst,75376,0 +29123,Male,50,Diploma,18,79,30,47,74,5.0,4,48,Urban,Data Analyst,80114,0 +29124,Female,52,Bachelors,18,15,0,53,73,2.0,4,63,Urban,HR Executive,111850,0 +29125,Male,52,Diploma,19,79,32,81,77,3.0,3,99,Semi-Urban,Manager,94430,1 +29126,Female,37,Bachelors,9,22,61,13,26,2.0,3,73,Rural,Software Engineer,81744,0 +29127,Male,29,Bachelors,9,49,0,94,77,7.0,3,89,Semi-Urban,ML Engineer,101215,0 +29128,Male,25,Diploma,1,62,90,3,16,2.0,5,51,Urban,Software Engineer,92122,0 +29129,Male,46,Bachelors,5,68,84,48,96,6.0,0,29,Rural,ML Engineer,76711,0 +29130,Male,39,High School,0,78,69,97,28,7.0,5,57,Urban,Data Analyst,68389,1 +29131,Female,37,Masters,6,9,67,96,79,1.0,5,82,Rural,HR Executive,35329,1 +29132,Other,38,PhD,1,49,17,6,19,2.0,4,92,Urban,ML Engineer,141287,0 +29133,Other,22,Diploma,16,8,82,40,9,3.0,4,84,Urban,ML Engineer,132089,0 +29134,Female,36,Diploma,4,41,61,88,58,8.0,0,9,Semi-Urban,Manager,62048,0 +29135,Female,57,Diploma,1,2,56,43,37,0.0,2,45,Rural,Software Engineer,59902,0 +29136,Female,21,Bachelors,1,50,43,47,23,5.0,7,35,Rural,ML Engineer,90701,0 +29137,Female,52,Diploma,7,71,66,72,39,3.0,2,25,Urban,Manager,103913,0 +29138,Male,35,High School,9,24,56,14,32,1.0,0,35,Urban,Data Analyst,61228,0 +29139,Male,54,High School,12,28,16,91,72,0.0,4,10,Urban,Software Engineer,50075,0 +29140,Female,40,Masters,2,64,43,28,63,1.0,3,83,Rural,Software Engineer,121188,0 +29141,Female,33,Masters,15,36,9,75,14,7.0,7,98,Urban,Software Engineer,100707,0 +29142,Female,42,Bachelors,3,26,71,64,54,8.0,6,80,Semi-Urban,Data Analyst,142231,1 +29143,Female,54,Diploma,15,53,12,10,20,6.0,1,33,Rural,ML Engineer,78276,0 +29144,Male,45,Bachelors,18,76,81,76,4,9.0,6,31,Urban,ML Engineer,27686,1 +29145,Female,41,Bachelors,19,14,96,64,72,4.0,4,78,Urban,Manager,143497,1 +29146,Other,24,PhD,18,51,15,23,6,7.0,0,13,Semi-Urban,Manager,149910,0 +29147,Male,53,High School,0,44,3,43,85,3.0,1,65,Rural,Data Analyst,32478,0 +29148,Female,23,Diploma,2,88,12,11,93,0.0,1,88,Urban,Manager,57089,0 +29149,Male,59,Masters,3,66,9,14,81,1.0,7,33,Semi-Urban,Manager,62200,0 +29150,Female,21,Masters,4,35,41,8,53,7.0,7,26,Urban,ML Engineer,29458,0 +29151,Female,54,Masters,18,81,8,47,75,9.0,5,4,Urban,Software Engineer,72121,0 +29152,Male,30,Masters,7,76,98,41,62,2.0,6,64,Urban,ML Engineer,106005,1 +29153,Male,27,Bachelors,15,95,59,86,29,7.0,7,47,Semi-Urban,Data Analyst,36676,1 +29154,Male,42,Diploma,10,73,3,55,50,2.0,3,90,Rural,Software Engineer,72350,0 +29155,Male,25,High School,7,26,85,80,48,5.0,7,54,Urban,ML Engineer,74661,1 +29156,Male,36,Bachelors,19,88,19,22,81,8.0,7,7,Urban,Software Engineer,36938,0 +29157,Male,49,Diploma,11,96,68,66,10,0.0,1,41,Rural,Software Engineer,110004,1 +29158,Female,25,Masters,0,47,49,82,40,3.0,6,63,Urban,HR Executive,21097,1 +29159,Male,50,Masters,5,29,87,85,93,7.0,3,49,Urban,HR Executive,101772,1 +29160,Male,54,High School,16,35,89,12,48,1.0,1,18,Rural,HR Executive,136891,0 +29161,Female,47,Bachelors,10,54,79,90,42,4.0,0,10,Rural,Software Engineer,65375,0 +29162,Female,30,Bachelors,16,81,23,6,61,2.0,0,94,Urban,Data Analyst,91514,0 +29163,Female,30,Bachelors,0,31,23,52,25,2.0,2,11,Urban,ML Engineer,31193,0 +29164,Male,43,Bachelors,19,55,6,21,7,2.0,5,70,Urban,Software Engineer,81657,0 +29165,Male,26,High School,6,4,55,10,80,5.0,5,97,Rural,HR Executive,117451,0 +29166,Male,47,Masters,18,17,25,12,42,3.0,6,61,Semi-Urban,Data Analyst,20129,0 +29167,Male,34,Bachelors,1,34,83,99,31,1.0,2,26,Urban,Software Engineer,111555,1 +29168,Female,43,PhD,7,70,81,10,30,3.0,7,30,Urban,HR Executive,73403,0 +29169,Male,54,Bachelors,0,75,42,34,70,9.0,3,90,Urban,Manager,102564,1 +29170,Female,37,Bachelors,6,8,96,31,2,9.0,7,57,Semi-Urban,ML Engineer,133750,0 +29171,Male,54,Masters,17,71,91,3,57,5.0,4,39,Semi-Urban,Data Analyst,104453,0 +29172,Male,51,Bachelors,11,10,59,96,57,7.0,6,50,Rural,ML Engineer,100281,0 +29173,Male,42,Diploma,7,58,14,96,89,8.0,0,8,Semi-Urban,Data Analyst,20542,0 +29174,Female,25,Bachelors,17,82,86,40,25,0.0,6,64,Urban,ML Engineer,99410,1 +29175,Male,29,Bachelors,4,97,13,66,93,4.0,5,34,Semi-Urban,HR Executive,134936,0 +29176,Male,38,Bachelors,10,97,73,29,88,7.0,6,71,Semi-Urban,Data Analyst,121832,1 +29177,Male,41,Bachelors,18,25,27,32,99,7.0,6,89,Semi-Urban,Software Engineer,115641,0 +29178,Male,26,High School,18,28,98,18,46,3.0,7,28,Rural,HR Executive,35436,0 +29179,Female,49,Bachelors,5,12,20,15,38,1.0,6,6,Urban,ML Engineer,73638,0 +29180,Male,39,Bachelors,19,56,80,72,85,4.0,0,2,Urban,ML Engineer,38346,0 +29181,Male,59,Bachelors,2,14,61,50,69,9.0,1,50,Semi-Urban,HR Executive,72369,0 +29182,Female,24,Masters,5,82,67,7,96,3.0,4,0,Rural,Data Analyst,31757,0 +29183,Male,59,Masters,17,76,57,98,74,2.0,5,33,Urban,Software Engineer,59758,1 +29184,Male,54,Diploma,15,63,32,22,79,3.0,1,97,Semi-Urban,ML Engineer,113849,0 +29185,Male,23,Bachelors,18,28,7,24,50,7.0,0,78,Urban,HR Executive,102811,0 +29186,Male,48,Bachelors,2,82,76,23,55,0.0,6,88,Semi-Urban,Software Engineer,120940,1 +29187,Male,32,PhD,15,71,74,96,55,0.0,0,31,Urban,Data Analyst,54884,1 +29188,Female,30,Masters,15,33,77,11,1,0.0,0,86,Urban,ML Engineer,100100,0 +29189,Female,33,Diploma,11,10,65,12,17,9.0,6,21,Semi-Urban,HR Executive,40999,0 +29190,Male,49,High School,10,12,37,89,44,9.0,3,65,Semi-Urban,ML Engineer,30231,0 +29191,Female,43,Bachelors,1,93,75,75,29,9.0,0,51,Urban,Software Engineer,133053,1 +29192,Male,43,Diploma,5,52,28,81,32,3.0,4,82,Urban,Software Engineer,25071,1 +29193,Male,47,Masters,19,61,17,7,67,9.0,2,97,Semi-Urban,Software Engineer,61693,0 +29194,Female,26,High School,17,91,75,94,41,3.0,2,81,Urban,Manager,137595,1 +29195,Male,39,PhD,16,30,60,95,11,4.0,2,55,Urban,HR Executive,130019,1 +29196,Male,45,Masters,19,7,81,22,84,1.0,2,55,Urban,Manager,131045,0 +29197,Female,33,Bachelors,0,31,55,29,76,8.0,6,62,Semi-Urban,HR Executive,51724,0 +29198,Male,31,Bachelors,1,17,36,69,93,1.0,7,29,Semi-Urban,ML Engineer,147624,0 +29199,Male,26,Bachelors,5,47,4,15,98,8.0,3,51,Urban,Data Analyst,68205,0 +29200,Female,39,Diploma,0,39,50,29,85,2.0,7,1,Rural,ML Engineer,144805,0 +29201,Female,43,High School,0,67,34,64,10,1.0,3,13,Urban,ML Engineer,110100,0 +29202,Female,52,Diploma,10,25,83,33,5,8.0,1,53,Semi-Urban,HR Executive,76358,0 +29203,Male,41,Bachelors,18,73,81,63,87,5.0,1,75,Rural,ML Engineer,76673,1 +29204,Male,56,Diploma,10,57,31,39,1,3.0,4,36,Urban,ML Engineer,109623,0 +29205,Male,46,Bachelors,6,52,64,32,55,1.0,7,80,Urban,Manager,92116,0 +29206,Male,43,Bachelors,8,49,32,95,29,7.0,0,39,Rural,ML Engineer,135246,0 +29207,Male,44,Bachelors,11,81,38,68,49,7.0,5,93,Urban,ML Engineer,96429,1 +29208,Female,28,Bachelors,4,72,75,42,17,6.0,3,31,Semi-Urban,Data Analyst,107605,0 +29209,Male,24,Masters,15,39,89,66,7,2.0,1,20,Semi-Urban,ML Engineer,111522,0 +29210,Male,36,Bachelors,7,97,91,22,94,8.0,5,18,Rural,HR Executive,33454,0 +29211,Male,40,Bachelors,5,37,36,67,74,8.0,1,92,Urban,Manager,22959,0 +29212,Other,41,High School,10,20,74,84,89,5.0,1,31,Urban,HR Executive,131481,0 +29213,Female,51,Diploma,8,2,98,15,51,7.0,1,24,Semi-Urban,Data Analyst,148379,0 +29214,Other,28,High School,18,96,70,42,19,7.0,6,68,Rural,HR Executive,29262,1 +29215,Male,55,Masters,17,79,88,97,10,4.0,1,62,Rural,HR Executive,123613,1 +29216,Male,49,Bachelors,17,51,14,69,3,8.0,7,22,Urban,ML Engineer,106928,0 +29217,Male,26,Bachelors,1,71,6,72,1,7.0,1,55,Rural,Manager,133268,0 +29218,Female,31,Masters,10,34,0,35,58,0.0,1,3,Urban,Manager,99665,0 +29219,Male,45,Diploma,1,4,92,62,4,8.0,5,81,Urban,Software Engineer,28218,1 +29220,Male,24,Diploma,8,54,41,18,80,4.0,7,28,Semi-Urban,HR Executive,111965,0 +29221,Male,51,Bachelors,3,32,41,57,25,8.0,0,57,Urban,Software Engineer,58072,0 +29222,Male,50,Bachelors,5,31,83,58,96,1.0,3,85,Urban,Manager,82280,1 +29223,Male,38,Bachelors,5,84,11,0,6,9.0,4,15,Urban,HR Executive,109779,0 +29224,Male,54,Masters,16,25,69,17,65,5.0,3,14,Urban,Manager,115241,0 +29225,Male,59,Bachelors,5,26,84,82,51,7.0,0,89,Semi-Urban,Data Analyst,106286,1 +29226,Male,41,Bachelors,12,6,14,91,42,0.0,3,16,Urban,ML Engineer,50207,0 +29227,Male,52,Diploma,6,31,75,23,8,2.0,2,94,Urban,Software Engineer,39506,0 +29228,Female,27,Masters,16,40,69,96,28,9.0,0,71,Rural,Manager,89503,1 +29229,Male,42,Bachelors,6,13,63,69,89,7.0,6,3,Rural,Manager,79198,0 +29230,Female,54,Diploma,6,72,39,77,30,0.0,0,29,Urban,Software Engineer,93252,0 +29231,Male,52,Diploma,13,12,72,5,22,9.0,3,7,Semi-Urban,Manager,112496,0 +29232,Male,29,Bachelors,6,69,16,29,2,3.0,4,49,Semi-Urban,Manager,99544,0 +29233,Male,53,Masters,6,64,27,63,75,1.0,4,30,Urban,Software Engineer,145469,0 +29234,Other,26,Masters,1,61,29,83,40,4.0,5,82,Urban,ML Engineer,132930,1 +29235,Male,44,Bachelors,7,23,9,18,8,5.0,4,93,Urban,ML Engineer,31536,0 +29236,Male,35,Bachelors,8,92,49,37,91,2.0,5,50,Urban,Data Analyst,140738,0 +29237,Male,33,High School,6,69,65,44,4,2.0,7,54,Urban,ML Engineer,66608,0 +29238,Male,34,High School,1,10,50,21,67,8.0,4,35,Semi-Urban,Data Analyst,144338,0 +29239,Male,34,Bachelors,13,51,79,60,96,7.0,2,50,Urban,Software Engineer,66992,1 +29240,Male,30,Bachelors,8,59,63,78,61,3.0,5,61,Urban,Manager,99562,1 +29241,Male,47,High School,11,57,81,67,15,2.0,1,19,Semi-Urban,Data Analyst,41005,0 +29242,Male,59,Bachelors,11,17,75,42,62,4.0,6,72,Rural,HR Executive,92140,0 +29243,Female,33,Diploma,0,1,71,41,51,1.0,5,56,Urban,Manager,133069,0 +29244,Male,59,Diploma,14,39,93,92,74,2.0,3,60,Semi-Urban,Data Analyst,140094,1 +29245,Male,32,Masters,19,38,63,75,65,8.0,4,66,Urban,ML Engineer,51847,1 +29246,Female,49,Bachelors,13,85,67,94,8,5.0,7,40,Urban,Manager,23887,1 +29247,Female,32,Bachelors,16,20,94,63,44,6.0,6,83,Urban,Software Engineer,44464,1 +29248,Male,51,High School,14,34,28,64,64,3.0,7,38,Rural,ML Engineer,74003,0 +29249,Male,43,High School,5,7,79,79,16,0.0,0,51,Rural,Data Analyst,55585,0 +29250,Female,51,Masters,1,19,34,80,58,1.0,6,10,Urban,ML Engineer,57476,0 +29251,Male,39,Diploma,2,0,97,20,5,2.0,3,93,Rural,HR Executive,62119,0 +29252,Female,52,Bachelors,12,31,85,35,40,0.0,3,80,Rural,Data Analyst,72943,0 +29253,Male,21,Bachelors,12,34,35,86,9,3.0,1,48,Urban,ML Engineer,69363,0 +29254,Male,33,PhD,10,3,96,87,35,8.0,7,43,Urban,Manager,49647,0 +29255,Female,55,High School,7,64,35,60,4,2.0,5,97,Semi-Urban,Data Analyst,47307,1 +29256,Other,29,PhD,18,46,70,86,21,7.0,2,39,Urban,ML Engineer,100420,1 +29257,Male,33,Diploma,10,38,52,10,68,1.0,4,16,Urban,Software Engineer,55933,0 +29258,Female,55,Bachelors,14,81,25,60,17,5.0,2,10,Semi-Urban,Manager,144207,0 +29259,Male,28,High School,16,16,29,67,62,3.0,5,5,Semi-Urban,Manager,140829,0 +29260,Female,31,Bachelors,17,38,85,49,12,2.0,4,0,Rural,HR Executive,113767,0 +29261,Female,55,Diploma,5,84,47,96,28,7.0,4,31,Urban,Manager,75068,1 +29262,Male,38,Bachelors,10,61,99,70,91,5.0,4,80,Semi-Urban,Manager,84160,1 +29263,Male,34,High School,4,45,75,95,17,8.0,0,82,Semi-Urban,Data Analyst,22643,1 +29264,Male,22,High School,17,71,81,62,14,6.0,0,57,Rural,HR Executive,66345,1 +29265,Male,35,Bachelors,1,42,65,79,15,9.0,6,53,Urban,Software Engineer,61701,1 +29266,Male,43,Bachelors,3,66,84,3,52,7.0,0,6,Urban,Manager,50969,0 +29267,Female,35,Masters,11,94,47,27,7,7.0,7,27,Urban,Data Analyst,91008,0 +29268,Male,22,High School,16,35,84,25,6,2.0,0,52,Urban,Data Analyst,91287,0 +29269,Male,41,Bachelors,6,85,74,72,5,5.0,1,25,Rural,Data Analyst,58266,1 +29270,Female,43,Bachelors,6,9,95,5,55,2.0,7,62,Urban,HR Executive,92747,0 +29271,Male,49,Diploma,13,25,21,34,68,,7,36,Semi-Urban,ML Engineer,112459,0 +29272,Male,51,Bachelors,1,35,38,3,18,1.0,1,21,Rural,Manager,137186,0 +29273,Male,42,PhD,13,2,25,50,59,9.0,2,50,Urban,HR Executive,139170,0 +29274,Male,26,High School,10,20,19,95,79,9.0,6,16,Urban,HR Executive,141180,0 +29275,Male,32,Bachelors,5,85,74,63,23,9.0,2,49,Rural,HR Executive,70050,1 +29276,Female,46,High School,5,29,47,95,9,3.0,1,35,Urban,Software Engineer,105407,0 +29277,Male,30,High School,9,1,71,13,63,9.0,0,6,Urban,ML Engineer,85564,0 +29278,Female,32,Masters,14,56,81,28,55,5.0,2,87,Rural,Data Analyst,68012,1 +29279,Female,35,Bachelors,5,92,4,16,24,7.0,5,8,Urban,ML Engineer,26016,0 +29280,Female,38,Diploma,19,99,72,57,55,5.0,5,43,Urban,Manager,128846,1 +29281,Male,25,Bachelors,13,1,51,1,55,2.0,6,75,Rural,ML Engineer,59832,0 +29282,Male,35,Bachelors,18,62,68,85,70,0.0,5,21,Semi-Urban,Software Engineer,115235,1 +29283,Female,48,Bachelors,6,4,58,52,36,6.0,1,99,Semi-Urban,Data Analyst,129167,0 +29284,Male,29,PhD,12,68,49,41,68,7.0,7,39,Rural,Data Analyst,91123,0 +29285,Male,56,Masters,7,4,87,46,82,1.0,1,26,Urban,HR Executive,90410,0 +29286,Female,37,Bachelors,0,63,3,24,98,9.0,6,64,Urban,Data Analyst,69979,0 +29287,Female,41,Bachelors,6,88,56,11,39,4.0,0,30,Rural,Manager,134706,0 +29288,Male,47,Bachelors,9,30,71,37,97,9.0,6,86,Urban,Manager,29873,0 +29289,Female,49,Diploma,1,69,47,34,34,6.0,1,93,Rural,ML Engineer,31451,1 +29290,Male,59,Bachelors,4,36,66,96,28,4.0,0,11,Urban,ML Engineer,119227,0 +29291,Male,30,High School,7,83,89,58,74,6.0,2,26,Urban,ML Engineer,147236,1 +29292,Female,23,Masters,1,27,11,34,27,5.0,1,47,Urban,Software Engineer,72815,0 +29293,Female,24,Masters,5,61,52,80,96,1.0,5,23,Urban,Data Analyst,29787,0 +29294,Other,54,Masters,13,75,56,44,14,8.0,6,59,Semi-Urban,Software Engineer,50720,0 +29295,Male,34,High School,0,90,12,91,11,9.0,5,48,Semi-Urban,Manager,39461,1 +29296,Female,43,Masters,14,69,23,44,47,9.0,4,35,Semi-Urban,Manager,114379,0 +29297,Male,51,High School,12,4,78,39,62,2.0,4,30,Urban,HR Executive,55094,0 +29298,Male,58,Masters,5,13,33,24,26,9.0,3,49,Urban,Software Engineer,63247,0 +29299,Female,23,Masters,6,98,69,23,72,2.0,6,60,Semi-Urban,HR Executive,58212,1 +29300,Male,33,Bachelors,3,32,41,29,18,8.0,2,76,Urban,ML Engineer,93919,0 +29301,Male,39,Bachelors,7,18,64,49,44,9.0,1,12,Urban,Software Engineer,63524,0 +29302,Male,54,Bachelors,16,75,57,74,24,1.0,7,60,Semi-Urban,Data Analyst,81895,1 +29303,Male,51,Bachelors,11,15,74,29,50,8.0,0,79,Rural,Software Engineer,95001,0 +29304,Male,23,Bachelors,8,97,12,18,42,2.0,7,1,Urban,HR Executive,59020,0 +29305,Male,26,Bachelors,2,36,43,86,1,8.0,7,13,Urban,Manager,118389,0 +29306,Male,47,Diploma,14,95,85,2,38,3.0,5,48,Urban,Manager,67913,0 +29307,Male,26,Diploma,3,41,51,43,51,9.0,5,85,Semi-Urban,Software Engineer,116868,0 +29308,Female,28,High School,10,90,26,17,21,9.0,7,10,Semi-Urban,ML Engineer,131182,0 +29309,Female,52,High School,4,26,61,38,8,0.0,6,18,Rural,ML Engineer,128755,0 +29310,Male,33,Bachelors,16,24,63,34,0,1.0,2,95,Urban,Software Engineer,77858,0 +29311,Male,55,Diploma,14,94,19,95,67,9.0,2,50,Urban,Manager,50391,1 +29312,Female,22,Masters,5,61,31,77,64,8.0,7,75,Rural,ML Engineer,105220,1 +29313,Male,53,Diploma,16,20,2,60,96,6.0,6,34,Semi-Urban,Manager,131946,0 +29314,Male,36,Masters,6,56,34,39,98,0.0,1,87,Semi-Urban,Manager,110323,0 +29315,Female,49,Diploma,18,88,56,21,20,3.0,2,27,Semi-Urban,Manager,61379,0 +29316,Male,57,Diploma,17,46,87,60,8,4.0,7,43,Rural,Manager,134217,1 +29317,Male,30,Masters,1,53,69,53,51,9.0,3,58,Urban,Software Engineer,145847,0 +29318,Male,52,Diploma,7,46,53,72,68,5.0,7,83,Rural,Software Engineer,47630,1 +29319,Male,51,Bachelors,6,47,45,32,78,0.0,5,51,Urban,Data Analyst,110705,0 +29320,Male,33,High School,7,78,75,26,44,6.0,7,41,Semi-Urban,Software Engineer,20006,0 +29321,Female,58,Bachelors,9,68,54,43,8,2.0,0,5,Semi-Urban,Data Analyst,95646,0 +29322,Female,36,Diploma,2,6,26,52,27,5.0,4,80,Urban,ML Engineer,142775,0 +29323,Male,46,Bachelors,11,33,7,26,33,4.0,3,46,Semi-Urban,ML Engineer,92195,0 +29324,Other,24,Diploma,17,14,75,39,66,2.0,0,0,Semi-Urban,Manager,103203,0 +29325,Female,48,Bachelors,5,17,2,60,48,9.0,5,53,Semi-Urban,Software Engineer,44844,0 +29326,Male,35,Masters,2,19,97,16,84,4.0,4,48,Urban,HR Executive,38937,0 +29327,Male,58,Bachelors,13,27,5,57,21,8.0,6,0,Urban,Software Engineer,35273,0 +29328,Male,47,High School,15,19,88,63,31,7.0,6,91,Urban,Manager,115429,1 +29329,Female,48,Bachelors,1,40,50,96,9,4.0,7,70,Urban,ML Engineer,37954,1 +29330,Male,44,Diploma,18,0,75,24,93,5.0,5,33,Urban,Software Engineer,84740,0 +29331,Female,47,High School,9,11,33,65,71,6.0,2,54,Urban,HR Executive,20342,0 +29332,Male,43,Masters,2,49,54,8,20,4.0,7,46,Urban,Manager,145473,0 +29333,Male,33,Diploma,17,78,75,32,91,4.0,3,8,Semi-Urban,Manager,61303,0 +29334,Male,24,Bachelors,12,19,37,23,71,8.0,1,35,Semi-Urban,Manager,111840,0 +29335,Female,53,Masters,1,9,25,90,61,9.0,4,4,Rural,Manager,50502,0 +29336,Male,51,Masters,15,60,4,28,55,2.0,7,57,Urban,HR Executive,76080,0 +29337,Male,22,Bachelors,9,25,36,57,8,1.0,2,31,Semi-Urban,Software Engineer,22034,0 +29338,Male,47,Masters,16,93,60,95,55,3.0,1,96,Urban,Manager,81684,1 +29339,Female,42,Bachelors,8,23,25,74,65,4.0,0,11,Urban,HR Executive,49461,0 +29340,Female,31,Diploma,17,90,93,94,27,5.0,3,8,Urban,ML Engineer,48141,1 +29341,Male,48,High School,0,69,78,71,89,2.0,7,37,Urban,ML Engineer,25124,1 +29342,Female,54,High School,9,83,52,38,10,0.0,5,9,Urban,Data Analyst,127986,0 +29343,Male,45,Bachelors,18,43,3,23,36,5.0,6,80,Urban,Data Analyst,62899,0 +29344,Male,22,Diploma,14,95,42,72,6,9.0,5,92,Urban,ML Engineer,44891,1 +29345,Male,30,High School,10,6,23,68,41,7.0,5,65,Urban,Manager,31177,0 +29346,Male,34,Masters,2,69,59,20,14,0.0,4,53,Semi-Urban,HR Executive,69160,0 +29347,Male,23,Bachelors,11,73,47,68,84,7.0,0,50,Urban,ML Engineer,78936,1 +29348,Female,29,Diploma,3,94,97,98,56,4.0,6,60,Semi-Urban,Software Engineer,97942,1 +29349,Female,52,Diploma,14,96,91,24,97,4.0,3,51,Semi-Urban,Data Analyst,23974,1 +29350,Female,50,Bachelors,4,33,20,20,53,4.0,4,22,Semi-Urban,ML Engineer,96821,0 +29351,Female,52,Bachelors,3,66,68,49,95,4.0,4,3,Semi-Urban,HR Executive,79712,0 +29352,Female,23,Diploma,15,42,72,75,98,7.0,2,59,Urban,ML Engineer,81046,1 +29353,Male,37,Bachelors,1,57,78,50,27,3.0,0,85,Rural,Manager,127067,1 +29354,Female,35,Diploma,0,75,37,50,80,1.0,0,56,Urban,Data Analyst,86459,0 +29355,Male,42,Bachelors,4,27,57,35,93,0.0,6,78,Urban,Software Engineer,45722,0 +29356,Female,54,Bachelors,12,19,37,89,52,8.0,1,93,Urban,HR Executive,50414,0 +29357,Male,33,Bachelors,14,22,29,81,29,1.0,0,94,Urban,Software Engineer,112098,0 +29358,Male,38,Bachelors,2,48,81,84,71,7.0,2,14,Urban,ML Engineer,96115,0 +29359,Female,42,High School,2,18,25,77,92,0.0,5,72,Semi-Urban,Software Engineer,138381,0 +29360,Female,35,High School,10,26,11,3,56,4.0,3,48,Rural,Manager,106927,0 +29361,Male,35,Bachelors,17,46,52,88,46,0.0,5,72,Rural,Data Analyst,84396,1 +29362,Male,28,Bachelors,8,0,9,26,27,4.0,6,12,Semi-Urban,Data Analyst,136340,0 +29363,Male,48,PhD,6,0,16,17,57,6.0,4,58,Semi-Urban,ML Engineer,49879,0 +29364,Other,40,Diploma,15,54,56,61,29,2.0,2,18,Urban,Software Engineer,62372,0 +29365,Male,59,Bachelors,15,25,36,57,89,4.0,7,24,Urban,ML Engineer,63964,0 +29366,Male,36,Diploma,15,63,25,70,81,9.0,2,10,Urban,ML Engineer,57762,0 +29367,Male,42,Diploma,3,17,46,28,47,5.0,3,2,Urban,HR Executive,79369,0 +29368,Male,51,Bachelors,4,34,90,1,43,1.0,4,64,Urban,Data Analyst,58657,0 +29369,Male,34,High School,13,19,98,25,43,5.0,6,27,Urban,ML Engineer,95204,0 +29370,Female,46,Diploma,7,73,82,48,30,4.0,1,6,Urban,ML Engineer,47490,0 +29371,Female,39,Bachelors,18,13,2,80,6,4.0,2,40,Urban,Software Engineer,26005,0 +29372,Male,35,Bachelors,6,30,63,86,58,4.0,2,44,Semi-Urban,ML Engineer,49989,0 +29373,Female,49,Diploma,18,83,36,51,90,3.0,4,93,Urban,HR Executive,46489,1 +29374,Male,56,Bachelors,2,0,32,36,95,3.0,1,96,Semi-Urban,ML Engineer,87456,0 +29375,Male,54,Bachelors,7,2,24,82,53,0.0,4,64,Urban,ML Engineer,22584,0 +29376,Male,44,Masters,4,11,74,1,51,5.0,3,46,Semi-Urban,HR Executive,92469,0 +29377,Male,34,High School,9,11,56,9,20,3.0,2,45,Semi-Urban,HR Executive,123113,0 +29378,Female,25,Masters,0,60,49,0,17,1.0,2,55,Rural,ML Engineer,119368,0 +29379,Male,21,Bachelors,16,63,49,73,90,9.0,2,96,Semi-Urban,Data Analyst,36694,1 +29380,Female,55,Masters,17,49,47,76,20,8.0,1,51,Urban,Software Engineer,83204,0 +29381,Female,49,High School,2,91,45,70,22,6.0,2,23,Urban,Data Analyst,75390,0 +29382,Female,51,Masters,16,28,64,23,47,5.0,7,49,Urban,ML Engineer,100324,0 +29383,Female,45,Diploma,12,79,13,92,19,0.0,5,5,Semi-Urban,ML Engineer,42533,0 +29384,Female,37,Diploma,16,61,23,48,53,8.0,0,54,Urban,HR Executive,98446,0 +29385,Male,26,PhD,3,31,24,0,89,3.0,4,30,Urban,Software Engineer,141249,0 +29386,Male,47,Masters,8,27,77,54,39,6.0,1,71,Rural,HR Executive,109329,0 +29387,Male,33,Bachelors,10,71,79,65,55,4.0,4,93,Urban,HR Executive,73706,1 +29388,Female,41,Masters,12,74,57,83,19,5.0,2,65,Urban,ML Engineer,80841,1 +29389,Male,30,Masters,2,57,89,65,70,3.0,2,75,Urban,Data Analyst,104615,1 +29390,Female,54,Bachelors,17,3,94,17,8,4.0,7,36,Urban,ML Engineer,51179,0 +29391,Male,35,Bachelors,19,92,3,85,19,9.0,7,79,Urban,ML Engineer,76755,1 +29392,Male,43,Diploma,3,63,0,72,23,8.0,7,23,Urban,Data Analyst,102309,0 +29393,Male,52,Masters,2,30,48,70,44,8.0,0,59,Urban,Manager,81666,0 +29394,Female,42,Diploma,16,10,55,54,32,5.0,4,60,Semi-Urban,Manager,52073,0 +29395,Male,50,High School,2,56,65,53,93,0.0,2,77,Urban,HR Executive,109319,1 +29396,Male,47,Bachelors,6,62,54,99,48,0.0,4,12,Rural,Data Analyst,71738,0 +29397,Male,51,Bachelors,3,51,63,1,89,3.0,4,38,Urban,Software Engineer,23345,0 +29398,Male,24,Bachelors,0,99,71,37,92,0.0,5,46,Urban,Software Engineer,129281,1 +29399,Male,54,Bachelors,8,21,98,85,88,1.0,7,10,Rural,Manager,31096,0 +29400,Male,45,Diploma,13,65,83,28,64,3.0,3,80,Rural,Manager,128409,1 +29401,Male,40,Bachelors,12,96,41,2,51,0.0,7,54,Urban,Data Analyst,142294,0 +29402,Male,44,Masters,12,17,19,10,48,9.0,0,85,Rural,HR Executive,51841,0 +29403,Other,43,Bachelors,19,85,14,96,10,7.0,5,27,Rural,Software Engineer,51177,0 +29404,Other,26,Bachelors,14,93,91,18,45,2.0,7,93,Urban,Data Analyst,27946,1 +29405,Male,33,Bachelors,12,0,26,86,93,5.0,6,48,Semi-Urban,Data Analyst,115810,0 +29406,Male,25,Bachelors,7,13,68,40,91,4.0,0,98,Urban,HR Executive,137032,0 +29407,Male,21,High School,9,15,17,86,95,8.0,7,95,Urban,HR Executive,86793,0 +29408,Other,53,Bachelors,4,62,11,59,77,9.0,6,36,Rural,Data Analyst,65007,0 +29409,Male,28,Diploma,6,69,51,54,3,1.0,1,81,Urban,Software Engineer,60480,1 +29410,Male,29,Diploma,19,26,33,1,74,1.0,6,15,Semi-Urban,Data Analyst,58235,0 +29411,Male,37,Diploma,10,24,29,42,23,9.0,2,30,Rural,Software Engineer,39684,0 +29412,Male,51,Masters,14,9,67,14,83,7.0,6,30,Semi-Urban,Manager,145169,0 +29413,Male,51,Bachelors,8,61,33,23,77,1.0,0,77,Urban,HR Executive,35603,0 +29414,Female,26,Bachelors,0,88,21,92,59,9.0,5,55,Rural,Data Analyst,135492,1 +29415,Male,30,Bachelors,10,24,52,74,51,8.0,7,22,Semi-Urban,Manager,122646,0 +29416,Male,26,Masters,7,23,12,23,17,8.0,1,54,Semi-Urban,HR Executive,110124,0 +29417,Male,35,Diploma,3,60,34,29,70,9.0,5,7,Urban,ML Engineer,63510,0 +29418,Female,21,Bachelors,3,20,66,32,42,7.0,2,41,Urban,Data Analyst,78772,0 +29419,Male,44,Masters,8,39,69,23,98,3.0,5,68,Urban,ML Engineer,75232,0 +29420,Male,28,Bachelors,8,99,11,56,14,3.0,1,64,Urban,ML Engineer,20134,0 +29421,Female,39,Bachelors,18,4,44,82,30,1.0,6,35,Semi-Urban,ML Engineer,136554,0 +29422,Female,50,Masters,17,55,43,8,84,0.0,6,8,Urban,HR Executive,112947,0 +29423,Male,54,PhD,14,82,6,29,68,1.0,1,84,Semi-Urban,HR Executive,98741,0 +29424,Male,49,Bachelors,2,39,11,61,92,7.0,7,83,Semi-Urban,Software Engineer,133146,0 +29425,Male,22,Diploma,6,21,67,43,58,0.0,0,76,Urban,Data Analyst,87049,0 +29426,Female,40,Bachelors,7,76,13,46,40,7.0,3,26,Urban,Data Analyst,75154,0 +29427,Male,28,Diploma,8,51,90,4,32,5.0,2,14,Rural,ML Engineer,92211,0 +29428,Male,35,Masters,14,83,68,49,59,0.0,4,12,Semi-Urban,ML Engineer,126904,0 +29429,Male,42,Bachelors,13,31,83,27,66,0.0,2,35,Semi-Urban,Software Engineer,148705,0 +29430,Male,22,Diploma,4,98,63,81,13,7.0,0,68,Rural,HR Executive,149144,1 +29431,Male,43,Diploma,17,64,91,77,9,1.0,7,73,Urban,ML Engineer,112314,1 +29432,Other,37,High School,5,93,98,72,96,8.0,3,30,Semi-Urban,Data Analyst,90171,1 +29433,Male,33,Diploma,14,51,7,75,27,2.0,4,52,Urban,Manager,105078,0 +29434,Female,30,Bachelors,2,4,52,25,41,8.0,5,75,Urban,Manager,81539,0 +29435,Male,49,Bachelors,10,44,57,53,47,5.0,2,7,Urban,Software Engineer,28339,0 +29436,Female,37,Masters,8,27,26,97,18,2.0,2,2,Urban,Data Analyst,101468,0 +29437,Female,31,PhD,7,13,53,8,2,2.0,2,95,Urban,Software Engineer,124960,0 +29438,Male,52,Diploma,6,40,50,83,84,1.0,4,74,Urban,ML Engineer,116737,1 +29439,Male,25,Bachelors,15,96,40,76,53,4.0,3,62,Urban,Manager,118843,1 +29440,Male,26,Diploma,5,52,24,6,65,9.0,3,85,Urban,Software Engineer,24349,0 +29441,Male,29,Diploma,5,85,51,28,72,0.0,7,68,Urban,Software Engineer,46838,0 +29442,Male,44,Diploma,7,32,1,84,84,9.0,2,65,Semi-Urban,ML Engineer,95683,0 +29443,Male,26,Bachelors,8,33,93,39,2,2.0,6,69,Rural,Data Analyst,131836,0 +29444,Female,21,Diploma,3,13,7,13,82,9.0,0,89,Urban,Data Analyst,83325,0 +29445,Female,48,Bachelors,19,84,30,13,28,8.0,2,63,Urban,Data Analyst,39849,0 +29446,Male,53,Bachelors,6,67,8,37,87,9.0,4,7,Urban,Software Engineer,119696,0 +29447,Female,39,Diploma,9,24,22,81,28,7.0,4,25,Urban,Software Engineer,136618,0 +29448,Female,53,Bachelors,15,1,37,54,75,9.0,0,26,Urban,Software Engineer,20041,0 +29449,Male,55,Masters,19,11,75,64,44,7.0,1,98,Urban,Data Analyst,64657,1 +29450,Male,26,Bachelors,0,79,92,66,60,2.0,3,61,Urban,Manager,78081,1 +29451,Male,55,Bachelors,0,53,84,43,67,5.0,7,21,Urban,ML Engineer,122663,0 +29452,Male,40,Bachelors,6,14,41,56,55,8.0,7,12,Rural,Manager,66771,0 +29453,Male,28,Diploma,8,61,78,30,0,6.0,4,4,Rural,HR Executive,148074,0 +29454,Male,40,High School,12,38,17,9,28,6.0,4,30,Urban,HR Executive,101541,0 +29455,Female,33,High School,12,16,82,34,7,0.0,1,10,Urban,Software Engineer,29496,0 +29456,Female,27,Diploma,7,74,37,90,20,6.0,6,28,Rural,HR Executive,117780,0 +29457,Male,36,High School,2,63,27,70,94,7.0,0,4,Urban,Software Engineer,127230,0 +29458,Female,53,Diploma,19,9,62,94,68,4.0,7,37,Urban,Manager,76948,0 +29459,Female,46,Diploma,14,61,28,49,88,6.0,2,19,Urban,HR Executive,146256,0 +29460,Male,41,High School,2,0,56,95,9,3.0,2,36,Urban,Manager,83862,0 +29461,Female,31,Bachelors,18,8,27,49,21,5.0,1,54,Rural,ML Engineer,47273,0 +29462,Male,26,High School,5,33,67,71,1,0.0,6,58,Urban,Manager,149130,0 +29463,Male,43,Bachelors,2,50,78,21,35,4.0,5,81,Urban,Manager,30895,0 +29464,Male,45,Diploma,6,1,86,10,93,6.0,1,8,Urban,Manager,112271,0 +29465,Male,36,High School,6,23,43,16,1,9.0,4,73,Urban,Data Analyst,71552,0 +29466,Male,46,Bachelors,10,66,2,79,13,0.0,6,8,Urban,Manager,145679,0 +29467,Male,46,Bachelors,8,60,98,13,21,8.0,0,1,Rural,ML Engineer,83840,0 +29468,Female,25,Masters,12,87,79,69,28,0.0,3,81,Urban,Manager,49970,1 +29469,Female,30,Bachelors,6,74,5,24,39,5.0,0,90,Urban,ML Engineer,122026,0 +29470,Male,32,High School,3,73,45,45,2,6.0,6,58,Urban,HR Executive,39910,0 +29471,Male,40,Bachelors,15,87,66,77,80,9.0,3,7,Urban,Data Analyst,89744,1 +29472,Female,25,Masters,15,70,71,43,1,5.0,2,86,Rural,Software Engineer,77163,1 +29473,Male,44,High School,17,50,39,90,25,5.0,0,7,Urban,Manager,53192,0 +29474,Male,30,High School,11,59,10,1,56,9.0,7,86,Semi-Urban,Software Engineer,32834,0 +29475,Male,29,Masters,5,5,17,96,3,4.0,4,34,Urban,Data Analyst,53244,0 +29476,Female,33,Bachelors,7,76,72,61,2,5.0,6,84,Urban,Manager,141316,1 +29477,Female,44,Diploma,7,16,47,84,43,6.0,5,86,Urban,HR Executive,59253,0 +29478,Female,39,Diploma,18,26,17,50,78,4.0,3,69,Semi-Urban,HR Executive,55748,0 +29479,Male,42,Masters,7,12,71,3,92,1.0,3,85,Rural,Manager,74118,0 +29480,Female,22,Diploma,2,10,9,29,36,8.0,6,53,Urban,HR Executive,24503,0 +29481,Male,21,Diploma,3,81,37,2,15,1.0,5,20,Rural,Manager,117450,0 +29482,Male,23,PhD,0,53,2,81,85,4.0,2,52,Urban,HR Executive,144660,0 +29483,Male,53,Diploma,13,4,38,2,94,8.0,6,19,Semi-Urban,Data Analyst,58044,0 +29484,Female,45,Bachelors,6,76,25,46,34,1.0,4,18,Urban,Data Analyst,122324,0 +29485,Male,43,Bachelors,16,79,75,40,16,2.0,7,50,Urban,ML Engineer,149108,1 +29486,Male,26,Diploma,11,78,46,15,91,1.0,2,76,Rural,HR Executive,67756,0 +29487,Female,39,Bachelors,1,91,14,80,94,0.0,1,18,Urban,Software Engineer,29688,0 +29488,Female,30,Bachelors,4,72,84,82,59,1.0,3,1,Urban,Data Analyst,133520,0 +29489,Female,57,Diploma,1,14,68,33,57,1.0,2,53,Rural,Software Engineer,61057,0 +29490,Male,38,Diploma,3,67,81,19,7,8.0,6,76,Urban,Manager,139593,1 +29491,Female,57,Bachelors,4,37,2,2,38,6.0,3,31,Rural,ML Engineer,106358,0 +29492,Female,53,Bachelors,6,41,83,76,59,8.0,2,72,Rural,ML Engineer,64371,1 +29493,Male,55,Diploma,15,17,23,51,26,4.0,4,23,Rural,HR Executive,128860,0 +29494,Male,57,Diploma,19,4,95,42,58,6.0,1,58,Urban,Software Engineer,29509,0 +29495,Male,24,High School,1,50,21,95,52,5.0,1,28,Urban,Manager,92114,0 +29496,Male,56,Bachelors,15,91,59,32,55,8.0,5,82,Urban,HR Executive,121656,1 +29497,Male,52,Bachelors,7,4,21,93,45,6.0,6,88,Urban,HR Executive,58321,0 +29498,Male,35,Bachelors,10,29,2,8,68,4.0,0,22,Rural,Manager,55648,0 +29499,Male,41,Bachelors,0,16,19,65,26,4.0,7,12,Urban,Manager,51198,0 +29500,Male,41,High School,17,30,45,2,65,1.0,5,25,Rural,Software Engineer,130879,0 +29501,Female,46,Masters,9,43,29,71,86,6.0,4,84,Semi-Urban,Data Analyst,118061,0 +29502,Male,31,High School,7,9,64,53,68,5.0,3,9,Semi-Urban,Software Engineer,137133,0 +29503,Male,48,Bachelors,15,1,44,23,19,1.0,2,74,Rural,HR Executive,81819,0 +29504,Female,44,Bachelors,9,7,48,97,82,2.0,6,31,Urban,Manager,109902,0 +29505,Male,35,Masters,5,18,90,47,17,9.0,7,42,Urban,Software Engineer,84312,0 +29506,Male,50,High School,9,47,20,72,4,6.0,6,95,Rural,Manager,28001,0 +29507,Male,55,High School,17,26,80,7,75,1.0,7,51,Rural,Manager,124065,0 +29508,Female,50,Diploma,10,6,94,86,98,6.0,4,98,Rural,ML Engineer,113866,1 +29509,Other,22,High School,14,66,55,45,81,9.0,5,79,Semi-Urban,ML Engineer,144635,1 +29510,Female,47,High School,6,93,80,20,5,6.0,2,64,Semi-Urban,ML Engineer,98253,1 +29511,Female,29,Diploma,11,99,12,5,80,9.0,2,88,Urban,HR Executive,91515,0 +29512,Male,57,Diploma,2,20,24,11,28,0.0,2,40,Urban,Software Engineer,68027,0 +29513,Female,33,Diploma,18,20,15,75,96,9.0,7,33,Rural,Data Analyst,112977,0 +29514,Other,51,Masters,4,22,89,29,53,2.0,1,21,Rural,Software Engineer,21340,0 +29515,Male,57,Masters,8,46,69,69,14,7.0,6,10,Rural,Data Analyst,136270,0 +29516,Female,59,Diploma,19,80,86,9,94,0.0,6,35,Urban,Data Analyst,31965,0 +29517,Male,43,Bachelors,19,36,87,78,77,7.0,2,68,Urban,Data Analyst,119341,1 +29518,Male,27,Diploma,8,6,37,87,88,6.0,2,97,Urban,Data Analyst,26384,0 +29519,Female,27,High School,12,29,36,80,59,5.0,2,16,Urban,Data Analyst,35213,0 +29520,Male,32,High School,8,97,27,88,95,8.0,6,36,Urban,Data Analyst,48720,1 +29521,Male,37,Diploma,0,86,50,54,28,3.0,2,91,Rural,Data Analyst,27818,1 +29522,Female,24,Diploma,19,66,50,38,84,4.0,3,48,Urban,Software Engineer,69606,0 +29523,Female,33,Bachelors,18,35,84,40,62,1.0,0,40,Urban,Manager,55313,0 +29524,Female,59,Bachelors,7,62,68,83,95,5.0,4,89,Urban,ML Engineer,98130,1 +29525,Male,36,Masters,8,31,75,36,24,6.0,5,23,Semi-Urban,HR Executive,75879,0 +29526,Male,29,Bachelors,15,65,75,10,10,6.0,0,83,Rural,HR Executive,36031,0 +29527,Other,38,Bachelors,14,45,1,4,33,3.0,2,38,Urban,Software Engineer,40887,0 +29528,Male,45,Diploma,0,97,61,92,63,5.0,4,32,Urban,HR Executive,70569,1 +29529,Female,34,Masters,8,16,62,67,98,6.0,3,84,Urban,HR Executive,141837,0 +29530,Female,59,Masters,14,81,23,48,37,5.0,4,13,Urban,HR Executive,85121,0 +29531,Female,49,Bachelors,9,79,56,89,26,7.0,4,71,Rural,HR Executive,53747,1 +29532,Male,51,Diploma,8,2,46,26,9,0.0,6,52,Semi-Urban,Manager,105804,0 +29533,Male,22,Bachelors,18,33,23,63,19,8.0,1,16,Urban,Manager,34212,0 +29534,Female,32,Bachelors,7,75,42,97,42,4.0,2,69,Rural,ML Engineer,110837,1 +29535,Male,25,Masters,0,91,61,27,41,7.0,2,13,Rural,Manager,96243,0 +29536,Female,49,Diploma,16,39,68,35,79,4.0,2,1,Urban,Data Analyst,64756,0 +29537,Female,27,Bachelors,3,65,73,9,43,9.0,6,2,Semi-Urban,Software Engineer,85420,0 +29538,Male,30,Bachelors,3,98,33,61,31,2.0,2,74,Semi-Urban,Manager,123526,1 +29539,Female,35,PhD,16,86,84,0,97,3.0,7,49,Urban,Data Analyst,70840,0 +29540,Male,53,Bachelors,16,39,23,57,81,8.0,5,79,Rural,HR Executive,69709,0 +29541,Male,48,Bachelors,19,56,37,24,70,3.0,6,9,Semi-Urban,ML Engineer,37242,0 +29542,Male,48,Bachelors,13,62,19,58,88,1.0,3,41,Urban,Data Analyst,117626,0 +29543,Female,24,High School,15,37,28,35,81,5.0,4,24,Semi-Urban,Data Analyst,36531,0 +29544,Male,31,Masters,5,3,57,54,46,0.0,3,28,Urban,ML Engineer,53905,0 +29545,Male,47,Bachelors,11,7,0,11,42,0.0,0,80,Semi-Urban,ML Engineer,47949,0 +29546,Male,27,Diploma,10,20,10,84,80,4.0,4,75,Semi-Urban,HR Executive,97654,0 +29547,Male,58,Diploma,18,89,76,83,58,9.0,4,72,Urban,Manager,73403,1 +29548,Male,44,Diploma,13,14,79,47,27,1.0,7,12,Urban,Software Engineer,110151,0 +29549,Male,44,High School,5,61,70,68,52,5.0,6,25,Rural,Manager,141719,0 +29550,Female,33,Bachelors,3,13,53,43,77,7.0,0,44,Semi-Urban,Data Analyst,72445,0 +29551,Male,27,Masters,3,20,92,91,0,8.0,6,85,Semi-Urban,ML Engineer,132576,1 +29552,Male,32,High School,7,35,99,63,41,8.0,4,34,Urban,HR Executive,62752,0 +29553,Male,39,Diploma,19,48,30,50,38,8.0,6,71,Rural,Manager,144686,0 +29554,Other,52,Bachelors,13,46,65,61,82,2.0,4,28,Urban,Manager,70508,0 +29555,Male,43,High School,7,26,91,82,93,6.0,3,52,Semi-Urban,ML Engineer,85777,1 +29556,Female,39,Diploma,11,6,4,56,6,6.0,0,45,Urban,ML Engineer,137702,0 +29557,Female,52,High School,19,73,27,17,70,8.0,5,37,Rural,ML Engineer,88061,0 +29558,Female,39,Masters,8,44,19,36,90,3.0,6,10,Urban,Manager,97610,0 +29559,Female,54,High School,2,32,92,79,33,6.0,4,45,Rural,Data Analyst,87610,1 +29560,Male,43,Masters,7,93,82,97,41,9.0,2,99,Rural,ML Engineer,41650,1 +29561,Female,48,Bachelors,19,55,64,59,68,2.0,0,93,Urban,Software Engineer,96667,1 +29562,Male,41,Bachelors,16,39,23,32,22,0.0,1,74,Semi-Urban,HR Executive,131533,0 +29563,Female,44,Bachelors,14,70,62,0,71,2.0,6,39,Rural,Software Engineer,114331,0 +29564,Other,40,Bachelors,8,99,98,61,59,9.0,0,51,Rural,Manager,52847,1 +29565,Female,52,Masters,3,14,8,56,53,7.0,2,98,Rural,Software Engineer,128841,0 +29566,Male,34,Bachelors,0,57,24,65,62,5.0,7,21,Rural,HR Executive,60501,0 +29567,Male,53,Masters,14,14,99,82,56,5.0,5,46,Semi-Urban,ML Engineer,30011,1 +29568,Male,23,Bachelors,2,32,26,65,24,8.0,4,5,Urban,HR Executive,55547,0 +29569,Male,54,Bachelors,17,90,27,91,20,4.0,3,34,Urban,Data Analyst,22644,1 +29570,Male,35,Bachelors,14,81,4,46,13,7.0,6,44,Urban,Data Analyst,137086,0 +29571,Male,56,Bachelors,9,90,50,77,75,0.0,5,59,Urban,Software Engineer,134760,1 +29572,Other,46,Bachelors,10,37,30,13,63,6.0,5,49,Urban,ML Engineer,38017,0 +29573,Male,29,High School,15,78,93,91,83,6.0,0,52,Semi-Urban,ML Engineer,105296,1 +29574,Female,34,Bachelors,15,11,36,2,36,3.0,4,37,Semi-Urban,Data Analyst,85347,0 +29575,Male,29,High School,0,32,79,19,4,4.0,1,92,Urban,Data Analyst,123370,0 +29576,Female,53,Masters,2,18,83,53,45,5.0,7,54,Rural,HR Executive,108620,0 +29577,Other,48,Diploma,15,98,65,23,26,9.0,1,30,Rural,ML Engineer,133310,0 +29578,Male,23,Diploma,8,96,95,87,40,7.0,2,19,Urban,Manager,60338,1 +29579,Male,43,Masters,11,40,73,82,59,4.0,2,98,Urban,Data Analyst,20599,1 +29580,Male,26,Bachelors,16,30,28,14,65,2.0,5,70,Semi-Urban,HR Executive,128460,0 +29581,Other,34,Bachelors,7,34,1,90,89,8.0,7,43,Urban,Data Analyst,52524,0 +29582,Male,28,Diploma,18,34,0,3,56,4.0,5,86,Semi-Urban,Software Engineer,126487,0 +29583,Male,43,Masters,2,99,18,33,35,4.0,3,35,Rural,Data Analyst,75647,0 +29584,Male,51,Bachelors,11,96,25,91,11,7.0,3,2,Urban,Manager,70419,0 +29585,Male,37,Bachelors,17,13,64,34,1,3.0,0,68,Urban,ML Engineer,104972,0 +29586,Female,59,Diploma,7,2,46,78,49,6.0,3,68,Urban,ML Engineer,117786,0 +29587,Male,30,PhD,6,73,2,6,85,5.0,5,21,Urban,Software Engineer,93031,0 +29588,Male,32,Bachelors,15,81,64,21,82,7.0,6,43,Urban,Software Engineer,28020,0 +29589,Male,42,Diploma,0,30,8,96,25,8.0,1,28,Urban,Data Analyst,144648,0 +29590,Other,31,Bachelors,5,40,11,62,73,1.0,1,42,Semi-Urban,Manager,113960,0 +29591,Male,42,Bachelors,12,55,83,36,81,2.0,3,59,Urban,HR Executive,58896,0 +29592,Female,45,Bachelors,17,9,58,37,22,8.0,5,42,Urban,ML Engineer,47846,0 +29593,Male,24,Bachelors,19,15,73,46,23,6.0,6,83,Semi-Urban,Data Analyst,68742,0 +29594,Female,54,Diploma,6,77,58,47,12,2.0,4,11,Urban,HR Executive,110047,0 +29595,Other,38,High School,11,80,29,22,93,0.0,6,4,Rural,Data Analyst,149187,0 +29596,Male,35,Bachelors,17,95,82,72,81,9.0,2,93,Urban,HR Executive,40581,1 +29597,Male,59,Bachelors,6,16,72,36,59,2.0,5,98,Urban,Manager,120285,0 +29598,Male,54,High School,13,50,66,13,5,3.0,1,63,Urban,Software Engineer,26892,0 +29599,Female,42,Bachelors,5,61,12,10,52,9.0,6,98,Urban,HR Executive,136606,0 +29600,Male,24,Diploma,19,37,4,70,8,5.0,2,5,Urban,Software Engineer,113728,0 +29601,Male,29,Bachelors,12,66,63,55,43,8.0,7,86,Urban,Manager,121628,1 +29602,Male,27,Masters,8,48,82,66,39,0.0,2,49,Semi-Urban,Manager,143594,1 +29603,Male,43,PhD,16,92,80,1,85,1.0,7,65,Semi-Urban,ML Engineer,26488,1 +29604,Male,31,Bachelors,18,72,91,4,72,0.0,2,28,Urban,ML Engineer,114946,0 +29605,Female,22,Bachelors,14,66,79,59,75,3.0,7,60,Semi-Urban,Software Engineer,140002,1 +29606,Female,35,Diploma,0,33,13,35,24,9.0,2,73,Urban,ML Engineer,110012,0 +29607,Male,54,Diploma,3,14,57,47,99,3.0,6,10,Semi-Urban,Data Analyst,82794,0 +29608,Female,56,High School,7,62,83,76,92,3.0,7,23,Urban,Manager,125095,1 +29609,Female,33,Masters,6,30,91,21,32,3.0,4,63,Rural,Data Analyst,89082,0 +29610,Female,39,Bachelors,9,12,50,10,20,4.0,2,69,Rural,ML Engineer,148022,0 +29611,Male,35,Diploma,12,7,66,23,84,5.0,5,78,Rural,Manager,105840,0 +29612,Male,53,Masters,4,9,73,93,50,7.0,1,60,Semi-Urban,Data Analyst,39913,1 +29613,Female,37,PhD,16,9,5,16,33,6.0,5,85,Semi-Urban,ML Engineer,101987,0 +29614,Female,22,High School,6,41,37,25,33,2.0,7,37,Semi-Urban,HR Executive,22191,0 +29615,Male,26,Masters,6,99,72,21,55,6.0,3,9,Rural,Data Analyst,30660,0 +29616,Male,30,Bachelors,6,39,69,20,67,5.0,0,54,Rural,ML Engineer,49007,0 +29617,Male,42,High School,7,88,85,57,1,5.0,1,73,Rural,Software Engineer,62849,1 +29618,Male,39,Masters,9,66,29,63,81,8.0,6,59,Urban,ML Engineer,126409,0 +29619,Male,51,Masters,7,61,75,82,49,0.0,3,60,Urban,ML Engineer,94234,1 +29620,Male,24,Diploma,4,67,22,25,30,7.0,4,42,Rural,ML Engineer,108692,0 +29621,Male,34,Bachelors,13,30,36,79,32,9.0,7,53,Urban,Software Engineer,80237,0 +29622,Female,52,Bachelors,19,79,82,35,24,2.0,1,74,Urban,HR Executive,91417,1 +29623,Male,45,Masters,5,60,35,50,25,4.0,6,91,Rural,ML Engineer,104029,1 +29624,Male,58,Bachelors,15,50,60,37,59,8.0,6,45,Rural,Data Analyst,37903,0 +29625,Male,25,Bachelors,5,59,44,92,78,1.0,2,32,Rural,Software Engineer,70279,0 +29626,Male,29,Masters,7,57,35,98,24,3.0,5,87,Urban,Software Engineer,114531,1 +29627,Male,24,Bachelors,16,64,43,49,78,5.0,7,70,Rural,ML Engineer,53814,0 +29628,Female,33,Diploma,19,10,68,68,14,0.0,1,1,Rural,ML Engineer,141549,0 +29629,Male,28,High School,10,18,3,77,14,8.0,5,60,Urban,HR Executive,68358,0 +29630,Female,46,Masters,7,58,99,19,0,7.0,5,29,Rural,HR Executive,36788,0 +29631,Female,34,Bachelors,18,80,63,9,59,0.0,5,58,Semi-Urban,Data Analyst,129431,0 +29632,Female,48,Diploma,15,43,87,90,10,6.0,3,19,Urban,Data Analyst,50093,0 +29633,Female,48,High School,8,69,32,74,79,0.0,3,6,Urban,HR Executive,42032,0 +29634,Female,37,Masters,5,87,64,87,31,5.0,6,70,Semi-Urban,ML Engineer,57864,1 +29635,Male,43,Bachelors,3,58,41,54,52,4.0,5,72,Rural,Data Analyst,71165,0 +29636,Other,52,Bachelors,9,31,15,80,31,5.0,2,25,Rural,Software Engineer,38735,0 +29637,Male,34,Diploma,8,61,39,2,55,7.0,3,18,Urban,HR Executive,103294,0 +29638,Male,30,Bachelors,19,37,77,21,73,0.0,6,92,Rural,Manager,89385,0 +29639,Male,55,Bachelors,11,94,32,13,14,2.0,1,68,Semi-Urban,Data Analyst,104263,0 +29640,Female,23,Diploma,18,62,15,39,9,5.0,4,78,Rural,HR Executive,78727,0 +29641,Male,22,Bachelors,12,92,58,9,84,0.0,1,69,Urban,Manager,83623,0 +29642,Female,38,Diploma,0,31,98,2,28,6.0,1,24,Rural,ML Engineer,119256,0 +29643,Male,25,Bachelors,4,36,24,89,37,7.0,1,33,Urban,ML Engineer,46872,0 +29644,Female,51,Diploma,1,97,82,62,71,1.0,2,2,Semi-Urban,ML Engineer,37279,1 +29645,Male,29,High School,17,82,20,26,22,6.0,2,86,Urban,ML Engineer,127276,0 +29646,Male,25,Bachelors,11,68,12,79,88,6.0,1,39,Urban,Manager,49077,0 +29647,Male,36,Diploma,9,93,11,75,33,1.0,5,3,Urban,Data Analyst,112163,0 +29648,Male,44,Bachelors,11,79,70,60,95,4.0,3,8,Rural,Data Analyst,56042,0 +29649,Male,31,PhD,12,16,1,3,2,4.0,5,80,Urban,ML Engineer,45783,0 +29650,Female,36,Masters,8,36,96,96,35,2.0,6,77,Urban,HR Executive,107242,1 +29651,Male,52,Masters,2,78,22,30,13,4.0,4,1,Rural,ML Engineer,96209,0 +29652,Female,54,Masters,9,89,83,79,5,9.0,1,93,Urban,Software Engineer,54610,1 +29653,Male,25,Diploma,17,16,31,84,74,0.0,1,67,Urban,ML Engineer,76280,0 +29654,Male,56,Bachelors,16,89,60,17,49,1.0,6,94,Urban,Data Analyst,91905,1 +29655,Male,42,High School,6,83,34,24,33,8.0,7,55,Urban,HR Executive,31464,0 +29656,Male,33,PhD,19,34,86,61,12,4.0,3,86,Semi-Urban,ML Engineer,124710,1 +29657,Female,43,Diploma,3,25,51,68,11,3.0,6,95,Semi-Urban,Data Analyst,22011,0 +29658,Female,37,Bachelors,2,33,14,68,54,2.0,1,9,Urban,HR Executive,141828,0 +29659,Male,55,PhD,18,54,35,6,10,4.0,6,13,Urban,Manager,93685,0 +29660,Female,43,Bachelors,18,11,13,54,51,7.0,0,47,Urban,ML Engineer,115971,0 +29661,Male,31,Masters,17,94,9,75,2,3.0,3,74,Urban,Software Engineer,99731,1 +29662,Female,48,Masters,16,98,29,40,98,4.0,3,20,Semi-Urban,ML Engineer,54324,0 +29663,Female,38,High School,1,6,99,4,67,1.0,6,53,Urban,Data Analyst,22530,0 +29664,Female,39,Bachelors,0,54,47,11,97,4.0,3,87,Rural,Data Analyst,149752,0 +29665,Male,37,Bachelors,1,18,27,0,97,8.0,3,38,Semi-Urban,Software Engineer,36312,0 +29666,Male,42,Bachelors,11,83,26,19,83,6.0,4,94,Urban,Software Engineer,100122,0 +29667,Male,27,Masters,17,57,17,71,69,7.0,2,6,Urban,Data Analyst,32157,0 +29668,Other,36,Masters,6,24,82,54,56,7.0,1,24,Semi-Urban,ML Engineer,22156,0 +29669,Female,47,Diploma,12,24,27,72,57,9.0,7,17,Semi-Urban,ML Engineer,118925,0 +29670,Male,22,Diploma,6,18,27,94,67,2.0,6,57,Urban,Data Analyst,94949,0 +29671,Female,40,Diploma,8,88,65,7,13,2.0,1,32,Urban,HR Executive,38802,0 +29672,Female,48,Diploma,10,88,95,85,32,3.0,4,42,Rural,ML Engineer,121282,1 +29673,Male,33,Masters,4,68,98,21,14,7.0,7,92,Rural,Manager,20141,1 +29674,Female,41,Bachelors,4,89,43,33,81,7.0,4,96,Rural,Data Analyst,124958,1 +29675,Male,51,PhD,2,49,46,43,12,2.0,5,63,Semi-Urban,Software Engineer,144203,0 +29676,Male,24,Masters,3,52,76,9,41,4.0,4,2,Urban,Manager,72560,0 +29677,Male,50,Bachelors,17,18,49,9,20,6.0,6,31,Urban,Data Analyst,53021,0 +29678,Male,29,Bachelors,0,21,39,91,83,2.0,7,5,Rural,ML Engineer,29450,0 +29679,Female,57,Masters,12,33,93,71,87,1.0,1,41,Semi-Urban,ML Engineer,109517,0 +29680,Male,56,Masters,1,5,42,25,19,6.0,6,42,Urban,Data Analyst,120818,0 +29681,Male,45,Diploma,14,46,8,34,77,8.0,6,32,Urban,Manager,79479,0 +29682,Male,46,Bachelors,6,51,35,5,77,8.0,0,25,Urban,ML Engineer,114586,0 +29683,Male,33,PhD,15,27,28,74,57,9.0,6,96,Semi-Urban,ML Engineer,54404,0 +29684,Male,25,Masters,1,36,38,24,82,8.0,5,38,Urban,ML Engineer,38217,0 +29685,Male,35,Diploma,3,40,68,93,58,9.0,4,75,Urban,Data Analyst,102770,1 +29686,Male,23,Masters,11,74,6,65,20,6.0,2,20,Urban,Manager,63755,0 +29687,Female,44,Bachelors,0,82,44,88,28,7.0,0,49,Semi-Urban,Manager,90660,1 +29688,Female,40,Masters,2,56,90,71,33,0.0,5,60,Urban,Data Analyst,89132,1 +29689,Male,30,High School,1,84,96,44,45,2.0,4,26,Urban,HR Executive,141878,1 +29690,Female,47,PhD,10,1,93,71,4,6.0,7,22,Urban,Manager,51701,0 +29691,Female,38,Bachelors,8,63,88,24,88,4.0,4,29,Urban,Software Engineer,97687,0 +29692,Female,26,Masters,18,90,75,31,17,0.0,4,49,Rural,Software Engineer,109893,1 +29693,Female,40,High School,2,34,85,13,79,1.0,3,32,Urban,Data Analyst,116987,0 +29694,Female,56,Bachelors,19,39,95,91,17,2.0,3,82,Urban,Software Engineer,64824,1 +29695,Male,26,Bachelors,10,62,0,73,65,6.0,2,24,Urban,Software Engineer,98956,0 +29696,Male,23,Diploma,1,37,11,23,21,7.0,2,30,Urban,HR Executive,66614,0 +29697,Female,56,High School,19,87,93,24,7,4.0,7,98,Urban,Data Analyst,37848,1 +29698,Male,36,Bachelors,0,98,91,42,4,3.0,5,26,Semi-Urban,Software Engineer,127042,1 +29699,Female,39,High School,8,96,38,68,48,9.0,6,32,Rural,HR Executive,42630,0 +29700,Female,39,Diploma,2,64,3,67,78,1.0,1,37,Semi-Urban,ML Engineer,105363,0 +29701,Male,37,PhD,18,54,21,92,39,0.0,3,16,Urban,Manager,129023,0 +29702,Female,38,Bachelors,14,65,48,32,33,4.0,0,2,Urban,ML Engineer,59542,0 +29703,Male,45,Bachelors,11,27,30,87,29,8.0,1,34,Semi-Urban,Manager,22396,0 +29704,Female,56,Masters,2,92,33,21,97,4.0,3,94,Urban,Data Analyst,27282,0 +29705,Male,44,High School,15,41,83,51,75,1.0,3,10,Urban,ML Engineer,123291,0 +29706,Female,47,High School,7,27,60,26,39,7.0,5,85,Semi-Urban,HR Executive,70989,0 +29707,Male,50,Diploma,5,26,10,85,4,1.0,0,43,Urban,Manager,131065,0 +29708,Female,30,Bachelors,5,47,38,78,21,2.0,6,73,Semi-Urban,HR Executive,83342,0 +29709,Other,51,Bachelors,7,79,7,83,50,7.0,4,68,Urban,Manager,58607,0 +29710,Male,57,Bachelors,1,2,58,39,29,7.0,4,2,Rural,Manager,88533,0 +29711,Female,53,Diploma,5,66,8,95,35,0.0,5,63,Rural,Manager,31623,0 +29712,Male,46,Bachelors,6,93,26,12,95,4.0,0,82,Semi-Urban,HR Executive,115440,0 +29713,Female,48,Bachelors,16,94,65,71,58,1.0,1,33,Urban,Data Analyst,139319,1 +29714,Male,53,High School,17,17,32,3,0,1.0,0,24,Rural,ML Engineer,46723,0 +29715,Female,36,Masters,13,6,36,40,78,5.0,1,23,Urban,HR Executive,87715,0 +29716,Female,53,Bachelors,8,22,24,54,1,3.0,2,14,Urban,HR Executive,60080,0 +29717,Male,36,Diploma,4,90,17,78,76,6.0,1,44,Urban,ML Engineer,61122,0 +29718,Male,26,Masters,2,39,35,59,24,0.0,5,50,Urban,ML Engineer,55369,0 +29719,Female,21,Masters,7,3,77,28,10,6.0,7,53,Semi-Urban,HR Executive,66698,0 +29720,Male,57,Masters,17,62,7,87,18,1.0,0,59,Semi-Urban,Data Analyst,83459,0 +29721,Male,52,Masters,4,40,44,23,3,4.0,6,94,Semi-Urban,Manager,35058,0 +29722,Male,55,High School,15,56,90,55,17,9.0,6,90,Urban,HR Executive,112557,1 +29723,Male,53,Diploma,11,41,17,63,3,3.0,5,49,Semi-Urban,Data Analyst,62453,0 +29724,Male,51,Bachelors,11,29,49,40,94,0.0,7,9,Urban,Manager,20512,0 +29725,Female,52,PhD,6,1,30,57,89,5.0,2,53,Semi-Urban,Software Engineer,45443,0 +29726,Female,52,Bachelors,0,39,28,48,9,1.0,7,88,Urban,HR Executive,30924,0 +29727,Female,58,Bachelors,8,27,43,44,77,2.0,6,16,Semi-Urban,ML Engineer,139780,0 +29728,Male,39,Masters,16,82,68,81,70,7.0,3,40,Urban,ML Engineer,47107,1 +29729,Male,33,Masters,1,9,33,83,25,4.0,7,14,Semi-Urban,Manager,53686,0 +29730,Male,41,Bachelors,7,76,40,56,24,7.0,7,0,Urban,Data Analyst,127260,0 +29731,Other,56,Diploma,19,33,82,86,81,2.0,0,63,Semi-Urban,ML Engineer,33295,1 +29732,Male,21,Bachelors,2,86,3,78,82,3.0,3,82,Semi-Urban,ML Engineer,45736,1 +29733,Male,40,Diploma,1,83,26,62,92,4.0,1,56,Rural,HR Executive,86273,0 +29734,Male,42,Diploma,4,76,88,18,5,1.0,1,34,Rural,HR Executive,124245,0 +29735,Female,21,PhD,12,32,58,63,11,6.0,1,7,Urban,Manager,113557,0 +29736,Female,45,Diploma,5,45,21,73,18,7.0,0,76,Urban,ML Engineer,55832,0 +29737,Male,39,Masters,10,46,94,86,29,4.0,3,48,Urban,Data Analyst,61678,1 +29738,Male,30,Bachelors,7,11,26,39,29,8.0,3,91,Urban,Software Engineer,38332,0 +29739,Female,27,Bachelors,13,38,51,16,66,4.0,2,76,Semi-Urban,Data Analyst,127759,0 +29740,Male,38,Bachelors,12,10,55,60,9,8.0,6,76,Rural,Manager,76334,0 +29741,Female,34,Masters,13,73,37,14,37,6.0,1,33,Urban,HR Executive,75334,0 +29742,Female,30,PhD,7,19,12,65,12,9.0,6,11,Rural,HR Executive,84703,0 +29743,Female,38,High School,6,55,95,33,4,6.0,0,54,Urban,ML Engineer,27016,0 +29744,Female,50,Bachelors,11,67,70,95,53,1.0,1,9,Urban,Data Analyst,31174,1 +29745,Female,28,Bachelors,11,70,35,37,11,4.0,4,60,Urban,Software Engineer,108381,0 +29746,Female,57,Diploma,11,12,49,49,45,6.0,3,34,Urban,Software Engineer,140091,0 +29747,Male,55,Diploma,16,24,46,8,7,7.0,6,43,Urban,Data Analyst,79008,0 +29748,Male,36,Masters,3,96,8,11,17,9.0,7,70,Urban,Software Engineer,139022,0 +29749,Female,23,Bachelors,5,74,91,31,58,6.0,3,1,Urban,Manager,139027,0 +29750,Male,51,Bachelors,2,2,39,20,36,6.0,6,34,Urban,Data Analyst,101787,0 +29751,Female,43,Masters,1,40,73,17,33,6.0,1,53,Semi-Urban,Data Analyst,96067,0 +29752,Male,56,Bachelors,13,91,2,69,92,7.0,0,61,Urban,Software Engineer,55341,0 +29753,Female,42,High School,3,79,7,77,41,7.0,4,19,Urban,HR Executive,115841,0 +29754,Male,53,High School,14,74,44,30,53,1.0,0,34,Rural,ML Engineer,128397,0 +29755,Female,58,Diploma,19,62,34,61,89,9.0,6,11,Rural,Software Engineer,148511,0 +29756,Male,49,High School,8,36,18,24,91,2.0,1,7,Urban,Manager,77227,0 +29757,Other,29,Bachelors,4,52,75,59,86,2.0,4,50,Urban,Data Analyst,69015,0 +29758,Male,25,High School,6,17,55,41,84,0.0,0,86,Semi-Urban,Software Engineer,127694,0 +29759,Male,40,High School,9,43,6,6,50,9.0,4,94,Urban,Software Engineer,66758,0 +29760,Male,38,Bachelors,19,53,55,23,71,0.0,2,23,Semi-Urban,Software Engineer,49453,0 +29761,Female,48,Bachelors,9,44,61,69,43,3.0,3,62,Urban,Data Analyst,124111,0 +29762,Male,28,Bachelors,16,43,96,70,70,4.0,5,25,Urban,ML Engineer,51813,0 +29763,Female,53,Diploma,10,25,49,46,0,2.0,4,26,Urban,ML Engineer,126953,0 +29764,Female,42,PhD,18,91,98,23,43,3.0,4,10,Urban,Manager,118502,0 +29765,Female,40,Diploma,1,52,44,43,94,8.0,6,2,Urban,Manager,84002,0 +29766,Female,53,Masters,12,29,94,76,3,1.0,6,86,Semi-Urban,Software Engineer,144197,1 +29767,Male,56,Bachelors,16,16,57,54,24,7.0,0,31,Urban,Manager,69774,0 +29768,Female,29,Masters,3,57,31,35,59,0.0,0,72,Rural,Manager,31807,0 +29769,Female,41,Bachelors,15,68,99,54,47,6.0,2,91,Semi-Urban,ML Engineer,143248,1 +29770,Male,52,Bachelors,7,52,78,62,9,3.0,3,82,Urban,Software Engineer,95664,1 +29771,Male,48,Bachelors,6,47,75,78,75,3.0,3,5,Semi-Urban,HR Executive,23248,0 +29772,Male,35,Masters,5,23,48,84,98,6.0,0,10,Semi-Urban,HR Executive,119986,0 +29773,Male,47,Bachelors,9,29,38,48,11,5.0,0,36,Semi-Urban,Software Engineer,137846,0 +29774,Male,36,Bachelors,1,1,69,64,50,9.0,4,59,Urban,Software Engineer,130855,0 +29775,Female,51,PhD,11,24,44,26,72,8.0,0,58,Semi-Urban,Data Analyst,103672,0 +29776,Other,53,Diploma,15,92,49,91,53,7.0,4,42,Semi-Urban,HR Executive,20269,1 +29777,Male,48,Masters,5,30,35,89,16,1.0,2,24,Semi-Urban,Data Analyst,71875,0 +29778,Female,43,Masters,16,71,18,55,49,9.0,1,47,Semi-Urban,HR Executive,102995,0 +29779,Male,42,Bachelors,4,7,56,91,59,8.0,6,60,Semi-Urban,ML Engineer,74794,0 +29780,Male,31,Bachelors,7,41,0,89,83,9.0,5,6,Semi-Urban,Manager,40580,0 +29781,Female,43,High School,9,38,82,91,95,4.0,0,82,Urban,HR Executive,142218,1 +29782,Other,43,PhD,17,46,30,85,91,5.0,5,15,Rural,Manager,29478,0 +29783,Male,40,PhD,0,3,24,55,66,4.0,5,40,Urban,ML Engineer,112744,0 +29784,Male,21,Bachelors,7,65,70,39,8,3.0,3,63,Urban,Data Analyst,140633,1 +29785,Male,35,Bachelors,14,40,93,96,66,6.0,6,90,Urban,Manager,122733,1 +29786,Male,38,Bachelors,4,31,47,1,74,7.0,3,99,Rural,Data Analyst,21988,0 +29787,Female,44,Diploma,17,21,84,66,55,9.0,4,12,Semi-Urban,ML Engineer,43596,0 +29788,Female,49,Bachelors,10,43,5,4,11,8.0,6,56,Rural,ML Engineer,124193,0 +29789,Female,43,Bachelors,16,7,42,81,98,1.0,3,59,Semi-Urban,Software Engineer,145561,0 +29790,Male,52,High School,0,97,88,67,44,9.0,0,55,Urban,Software Engineer,81538,1 +29791,Female,50,Masters,7,29,15,12,63,5.0,3,17,Semi-Urban,Data Analyst,78637,0 +29792,Male,27,Masters,15,68,82,79,4,0.0,1,78,Urban,Data Analyst,94870,1 +29793,Female,45,Bachelors,3,35,71,62,51,6.0,6,80,Urban,ML Engineer,103533,1 +29794,Male,49,Bachelors,10,83,80,59,82,7.0,4,81,Urban,Data Analyst,135671,1 +29795,Female,45,Bachelors,5,22,9,15,7,5.0,1,69,Urban,Manager,78234,0 +29796,Female,39,Masters,9,3,86,35,32,2.0,2,99,Urban,HR Executive,136915,0 +29797,Female,41,Diploma,18,18,9,97,59,1.0,2,81,Rural,Data Analyst,140107,0 +29798,Male,44,PhD,16,65,40,72,41,7.0,4,99,Semi-Urban,ML Engineer,34806,1 +29799,Female,58,Diploma,7,7,70,85,58,0.0,5,28,Semi-Urban,Manager,84895,0 +29800,Female,53,Diploma,13,43,21,8,89,4.0,4,34,Rural,ML Engineer,30827,0 +29801,Female,46,PhD,8,33,65,65,94,2.0,3,84,Semi-Urban,Software Engineer,129018,1 +29802,Male,33,Bachelors,6,25,36,8,75,2.0,7,13,Urban,HR Executive,38158,0 +29803,Male,22,Bachelors,2,54,27,89,16,9.0,5,83,Urban,Software Engineer,21014,1 +29804,Male,21,Bachelors,2,65,53,12,36,5.0,4,22,Rural,Software Engineer,20449,0 +29805,Male,54,Diploma,14,96,89,81,45,0.0,0,64,Urban,ML Engineer,131014,1 +29806,Female,40,Masters,0,36,14,79,51,7.0,6,68,Rural,Manager,55204,0 +29807,Female,21,Bachelors,17,12,74,96,61,0.0,4,71,Urban,Software Engineer,71739,1 +29808,Male,46,Bachelors,3,16,13,96,61,2.0,0,62,Urban,Data Analyst,89572,0 +29809,Female,40,Bachelors,18,42,71,15,20,4.0,7,95,Urban,Data Analyst,121507,0 +29810,Male,38,Masters,11,43,53,7,88,5.0,7,48,Semi-Urban,Manager,70780,0 +29811,Male,56,Diploma,1,92,82,12,9,9.0,4,16,Semi-Urban,Manager,45748,0 +29812,Male,50,Bachelors,17,48,59,92,91,6.0,0,44,Urban,ML Engineer,103185,1 +29813,Female,48,Bachelors,6,25,74,37,16,4.0,7,31,Urban,ML Engineer,103488,0 +29814,Female,38,Bachelors,3,21,87,0,9,7.0,3,85,Rural,Data Analyst,24463,0 +29815,Male,49,Bachelors,5,0,86,17,11,5.0,3,57,Rural,Software Engineer,146930,0 +29816,Female,54,Bachelors,13,72,36,76,13,4.0,2,67,Rural,Software Engineer,92261,1 +29817,Male,46,High School,7,36,86,18,91,5.0,6,1,Urban,Data Analyst,148665,0 +29818,Male,47,Diploma,19,85,27,75,30,5.0,1,72,Rural,Data Analyst,65359,1 +29819,Male,51,Bachelors,10,55,73,14,14,7.0,7,71,Urban,Manager,53587,0 +29820,Male,49,PhD,17,82,16,19,88,7.0,6,49,Semi-Urban,ML Engineer,45181,0 +29821,Female,33,Diploma,10,33,34,14,68,3.0,2,81,Urban,HR Executive,44818,0 +29822,Female,56,Bachelors,16,92,8,15,20,3.0,4,59,Semi-Urban,Software Engineer,81676,0 +29823,Male,53,Bachelors,11,9,42,96,94,3.0,1,42,Urban,Data Analyst,147342,0 +29824,Male,27,High School,15,53,46,63,29,8.0,1,15,Urban,Manager,25136,0 +29825,Male,46,Diploma,15,6,98,12,62,1.0,6,13,Rural,Software Engineer,40355,0 +29826,Male,53,Diploma,7,61,38,64,81,9.0,7,71,Urban,Manager,78637,0 +29827,Male,39,Bachelors,9,2,99,74,72,1.0,5,96,Urban,Manager,20524,1 +29828,Male,22,Diploma,4,86,76,69,41,9.0,7,76,Rural,Data Analyst,27431,1 +29829,Female,55,Masters,13,50,22,41,16,6.0,0,11,Urban,Data Analyst,144009,0 +29830,Male,42,Bachelors,14,60,96,38,98,1.0,6,10,Urban,Data Analyst,106763,0 +29831,Male,44,Diploma,6,40,65,90,98,3.0,6,8,Urban,Data Analyst,21884,0 +29832,Female,53,Masters,17,51,76,86,26,6.0,3,66,Rural,HR Executive,51719,1 +29833,Male,22,Diploma,1,60,46,27,55,5.0,2,57,Urban,Software Engineer,134520,0 +29834,Male,27,PhD,9,72,79,49,0,4.0,3,74,Urban,ML Engineer,114422,1 +29835,Male,50,Bachelors,0,90,64,64,49,0.0,6,22,Urban,ML Engineer,57487,1 +29836,Male,56,Bachelors,16,64,80,90,58,9.0,1,55,Rural,Software Engineer,125255,1 +29837,Male,27,Bachelors,18,48,46,16,95,4.0,2,19,Semi-Urban,Software Engineer,59824,0 +29838,Male,29,Bachelors,16,85,61,58,16,4.0,4,44,Urban,Software Engineer,24024,1 +29839,Female,44,Masters,10,81,84,16,8,6.0,0,33,Semi-Urban,Manager,51500,0 +29840,Female,44,Bachelors,15,85,68,30,37,1.0,5,16,Rural,Manager,140935,0 +29841,Female,45,Bachelors,4,4,52,5,31,3.0,2,96,Urban,HR Executive,129152,0 +29842,Male,24,High School,17,76,35,38,51,4.0,1,15,Semi-Urban,HR Executive,25172,0 +29843,Male,23,Bachelors,16,28,85,1,30,9.0,5,70,Urban,Software Engineer,56326,0 +29844,Male,37,Masters,6,20,8,24,38,1.0,3,27,Rural,Data Analyst,53811,0 +29845,Male,33,Masters,14,43,81,77,69,0.0,7,20,Semi-Urban,Manager,85770,0 +29846,Male,54,Bachelors,10,94,24,37,94,2.0,5,35,Urban,Data Analyst,69308,0 +29847,Male,55,Masters,16,89,48,90,98,6.0,1,78,Urban,ML Engineer,49426,1 +29848,Male,29,Masters,19,72,27,52,71,5.0,5,70,Urban,Manager,98135,0 +29849,Male,32,Diploma,1,34,34,53,19,0.0,3,42,Semi-Urban,Software Engineer,57611,0 +29850,Male,55,Masters,15,92,51,88,9,7.0,2,66,Urban,Data Analyst,46796,1 +29851,Male,41,Masters,17,75,39,99,27,2.0,5,93,Rural,Software Engineer,76709,1 +29852,Male,59,Bachelors,13,46,61,35,69,8.0,0,69,Semi-Urban,Software Engineer,58457,0 +29853,Male,54,Bachelors,4,36,27,29,30,6.0,3,87,Urban,Data Analyst,88690,0 +29854,Male,57,High School,7,74,58,79,93,4.0,3,2,Urban,HR Executive,71942,0 +29855,Male,36,Masters,11,96,51,23,86,5.0,0,48,Urban,HR Executive,141223,0 +29856,Male,48,Bachelors,10,78,80,46,17,4.0,2,16,Urban,Manager,66877,0 +29857,Male,42,Masters,0,39,68,35,74,8.0,0,27,Rural,ML Engineer,41784,0 +29858,Male,26,Bachelors,17,19,19,13,33,4.0,1,95,Urban,ML Engineer,89817,0 +29859,Female,56,Bachelors,7,94,8,2,82,9.0,7,65,Urban,Manager,133735,0 +29860,Male,42,High School,0,16,10,41,87,3.0,4,2,Semi-Urban,Data Analyst,36063,0 +29861,Male,29,Bachelors,3,94,61,31,65,3.0,0,42,Urban,HR Executive,143989,0 +29862,Male,47,High School,17,20,39,29,29,1.0,0,90,Rural,Data Analyst,79156,0 +29863,Male,50,Masters,5,95,4,55,20,5.0,6,93,Rural,Software Engineer,70832,1 +29864,Male,43,Bachelors,3,80,49,4,17,0.0,7,13,Urban,Manager,106394,0 +29865,Other,54,Diploma,10,12,51,93,94,3.0,1,64,Rural,Manager,72172,0 +29866,Female,30,Masters,7,54,61,87,0,3.0,5,50,Semi-Urban,Data Analyst,111358,1 +29867,Male,36,Bachelors,2,70,92,37,56,1.0,3,81,Urban,ML Engineer,78310,1 +29868,Female,48,Bachelors,14,42,30,35,14,0.0,5,86,Rural,Data Analyst,57773,0 +29869,Male,32,Bachelors,19,94,89,9,31,9.0,6,80,Urban,Software Engineer,63359,1 +29870,Male,32,Diploma,7,72,9,93,72,8.0,3,96,Semi-Urban,Manager,61707,1 +29871,Female,45,Masters,6,13,46,70,83,4.0,0,5,Urban,Manager,99810,0 +29872,Male,33,Bachelors,3,89,92,7,79,8.0,2,93,Urban,HR Executive,86083,1 +29873,Male,54,Diploma,6,60,31,48,51,2.0,5,45,Rural,HR Executive,82749,0 +29874,Female,36,Bachelors,5,64,55,96,90,6.0,3,18,Urban,Software Engineer,45423,0 +29875,Male,48,Masters,13,63,38,78,25,6.0,1,37,Semi-Urban,HR Executive,45858,0 +29876,Other,46,PhD,5,99,85,80,55,4.0,2,54,Semi-Urban,HR Executive,99801,1 +29877,Female,44,High School,4,35,34,11,54,1.0,4,38,Urban,ML Engineer,76717,0 +29878,Female,54,Bachelors,3,72,62,30,30,5.0,3,32,Rural,ML Engineer,71176,0 +29879,Male,31,Diploma,8,87,9,9,68,8.0,3,95,Urban,Data Analyst,44273,0 +29880,Male,56,Diploma,9,16,80,40,69,9.0,4,51,Semi-Urban,Data Analyst,67727,0 +29881,Female,22,Diploma,11,68,74,91,38,0.0,5,1,Urban,Data Analyst,38407,0 +29882,Other,33,Diploma,0,96,32,54,66,9.0,3,32,Semi-Urban,Data Analyst,36089,0 +29883,Male,53,Bachelors,18,43,72,63,82,5.0,6,94,Rural,Manager,137571,1 +29884,Other,56,Bachelors,6,32,8,25,34,2.0,0,22,Semi-Urban,ML Engineer,26880,0 +29885,Male,55,Bachelors,6,92,61,31,0,8.0,0,48,Urban,Data Analyst,112134,0 +29886,Male,33,Diploma,9,59,33,61,83,0.0,3,13,Rural,Manager,67801,0 +29887,Male,42,High School,18,12,73,66,30,7.0,7,93,Urban,Data Analyst,109628,1 +29888,Male,45,Diploma,7,77,74,2,3,7.0,3,0,Urban,Software Engineer,47165,0 +29889,Female,31,Bachelors,11,41,49,41,74,8.0,4,26,Rural,HR Executive,86587,0 +29890,Male,47,Bachelors,14,61,3,69,65,4.0,5,23,Urban,HR Executive,33524,0 +29891,Female,21,High School,19,2,22,56,47,8.0,1,94,Urban,HR Executive,33482,0 +29892,Male,40,Bachelors,15,80,46,10,56,0.0,6,16,Rural,Data Analyst,100453,0 +29893,Male,27,Masters,10,68,84,87,47,4.0,2,5,Urban,ML Engineer,134420,1 +29894,Female,40,Masters,8,39,77,77,29,2.0,5,37,Urban,Data Analyst,116395,0 +29895,Male,39,Bachelors,6,88,71,21,41,5.0,0,45,Urban,Software Engineer,108172,0 +29896,Female,23,Masters,17,50,64,4,73,0.0,5,90,Urban,HR Executive,83546,0 +29897,Male,25,High School,2,35,24,81,21,0.0,4,39,Rural,Data Analyst,52396,0 +29898,Male,26,High School,10,14,92,5,17,6.0,3,84,Urban,Manager,100686,0 +29899,Male,36,Diploma,17,42,28,73,58,6.0,0,31,Rural,Software Engineer,145261,0 +29900,Female,41,Bachelors,3,0,99,22,61,6.0,6,46,Urban,Manager,74487,0 +29901,Male,30,High School,13,53,79,93,17,5.0,4,83,Urban,Data Analyst,64715,1 +29902,Female,28,Diploma,15,29,23,13,99,7.0,0,25,Semi-Urban,Data Analyst,97926,0 +29903,Female,57,Bachelors,18,0,20,41,37,8.0,6,91,Semi-Urban,Manager,111685,0 +29904,Male,35,Bachelors,3,40,71,41,6,0.0,6,25,Urban,ML Engineer,122091,0 +29905,Female,44,Bachelors,3,45,49,89,22,1.0,6,72,Semi-Urban,Manager,104698,1 +29906,Male,25,Bachelors,16,49,14,19,80,9.0,4,24,Semi-Urban,HR Executive,74908,0 +29907,Male,32,Diploma,17,87,58,79,82,3.0,6,98,Urban,ML Engineer,68389,1 +29908,Male,49,Diploma,5,78,72,35,92,0.0,7,14,Rural,ML Engineer,129191,0 +29909,Male,38,Masters,18,62,60,92,15,2.0,4,60,Urban,Manager,144687,1 +29910,Male,57,High School,5,11,36,17,78,3.0,0,63,Urban,HR Executive,139841,0 +29911,Male,23,High School,19,79,23,59,92,9.0,1,61,Semi-Urban,Software Engineer,43087,0 +29912,Male,47,Masters,16,11,12,30,32,2.0,7,7,Urban,Manager,81572,0 +29913,Female,42,Bachelors,6,34,55,17,1,0.0,5,90,Semi-Urban,ML Engineer,115600,0 +29914,Male,26,Masters,7,73,25,36,21,1.0,6,91,Urban,Data Analyst,143610,0 +29915,Female,56,Bachelors,19,30,66,51,55,0.0,5,63,Rural,Software Engineer,110977,0 +29916,Male,39,Diploma,14,22,81,64,56,9.0,5,76,Semi-Urban,Data Analyst,57819,1 +29917,Female,46,High School,14,47,59,68,5,7.0,0,32,Semi-Urban,Software Engineer,132014,0 +29918,Male,38,PhD,5,26,63,80,4,1.0,3,93,Semi-Urban,HR Executive,137328,1 +29919,Male,57,Diploma,4,56,64,29,18,2.0,2,79,Urban,Software Engineer,90744,0 +29920,Male,50,Bachelors,12,15,65,72,0,6.0,3,72,Rural,Data Analyst,38396,0 +29921,Male,24,Bachelors,8,8,16,49,96,8.0,0,79,Rural,Software Engineer,63576,0 +29922,Male,38,Masters,8,49,67,19,77,8.0,7,25,Semi-Urban,ML Engineer,122182,0 +29923,Female,36,Bachelors,10,3,23,38,81,5.0,2,55,Urban,Software Engineer,63392,0 +29924,Female,48,Bachelors,18,35,95,70,91,7.0,6,26,Semi-Urban,ML Engineer,51358,0 +29925,Female,53,Diploma,18,25,73,77,91,6.0,3,41,Urban,HR Executive,22932,0 +29926,Male,32,Bachelors,19,5,63,44,62,7.0,1,65,Rural,HR Executive,25959,0 +29927,Male,22,Bachelors,18,96,0,34,12,7.0,3,91,Semi-Urban,Manager,136527,0 +29928,Female,40,Diploma,11,2,6,33,80,9.0,2,4,Semi-Urban,Software Engineer,94173,0 +29929,Male,35,Diploma,13,24,32,35,35,1.0,0,50,Rural,Data Analyst,68578,0 +29930,Female,59,Bachelors,17,9,28,50,25,9.0,4,36,Semi-Urban,HR Executive,50937,0 +29931,Male,44,High School,6,9,65,18,85,5.0,7,60,Urban,ML Engineer,97010,0 +29932,Other,54,Bachelors,3,90,92,19,15,3.0,3,52,Urban,ML Engineer,91257,1 +29933,Female,22,Diploma,2,26,18,85,58,1.0,6,93,Semi-Urban,Data Analyst,121474,0 +29934,Female,54,Masters,13,35,4,5,6,7.0,5,62,Semi-Urban,Software Engineer,23700,0 +29935,Male,48,Masters,11,21,60,10,85,9.0,4,52,Rural,Manager,124067,0 +29936,Male,39,Bachelors,19,97,22,83,35,4.0,0,42,Urban,HR Executive,33067,1 +29937,Female,52,Diploma,0,68,59,30,3,0.0,0,77,Urban,Data Analyst,81128,0 +29938,Female,52,Diploma,9,17,20,12,48,1.0,2,67,Rural,Manager,129203,0 +29939,Male,49,Bachelors,17,87,26,40,44,1.0,2,42,Semi-Urban,ML Engineer,143602,0 +29940,Male,56,High School,14,5,11,93,25,4.0,0,69,Urban,Software Engineer,144261,0 +29941,Female,22,Bachelors,15,32,4,54,70,4.0,2,78,Urban,ML Engineer,31922,0 +29942,Male,58,High School,8,29,1,3,12,2.0,2,89,Rural,HR Executive,125605,0 +29943,Female,59,Masters,17,13,74,35,28,1.0,7,48,Urban,Manager,148509,0 +29944,Female,21,Bachelors,7,77,29,19,28,3.0,2,19,Semi-Urban,Manager,114044,0 +29945,Female,44,High School,1,64,16,76,98,7.0,5,97,Semi-Urban,ML Engineer,83431,1 +29946,Male,29,Bachelors,9,40,25,95,9,1.0,5,93,Rural,Manager,146678,1 +29947,Male,39,Masters,14,47,35,2,58,9.0,1,22,Urban,Data Analyst,61575,0 +29948,Male,42,Diploma,0,5,27,12,78,1.0,2,77,Urban,Software Engineer,113828,0 +29949,Female,51,Bachelors,15,2,69,41,87,2.0,0,20,Urban,ML Engineer,124335,0 +29950,Male,45,Diploma,8,27,99,46,27,8.0,6,61,Urban,Data Analyst,23874,0 +29951,Male,32,Masters,9,95,35,78,18,9.0,4,21,Rural,Software Engineer,27995,0 +29952,Male,31,Bachelors,19,52,93,42,30,5.0,7,40,Urban,HR Executive,92014,0 +29953,Male,43,Diploma,9,9,74,80,97,8.0,1,17,Semi-Urban,HR Executive,139019,0 +29954,Female,26,Masters,9,92,95,79,79,6.0,4,70,Semi-Urban,Data Analyst,77423,1 +29955,Female,35,Bachelors,3,61,42,36,39,8.0,1,92,Urban,ML Engineer,96103,0 +29956,Female,39,Bachelors,17,95,47,57,45,7.0,0,71,Urban,HR Executive,143254,1 +29957,Male,29,Bachelors,17,39,93,8,93,5.0,5,11,Urban,Software Engineer,26460,0 +29958,Female,48,High School,18,14,14,24,54,5.0,5,78,Urban,HR Executive,91985,0 +29959,Male,50,Diploma,10,30,83,35,13,1.0,5,78,Semi-Urban,Data Analyst,104095,0 +29960,Female,46,High School,12,27,14,45,70,0.0,6,57,Urban,Data Analyst,129875,0 +29961,Male,40,Diploma,2,12,73,57,46,8.0,6,90,Semi-Urban,HR Executive,119109,0 +29962,Male,56,Bachelors,7,36,19,58,36,0.0,2,72,Urban,Data Analyst,20962,0 +29963,Male,50,High School,5,2,74,32,68,4.0,0,82,Rural,Manager,82326,0 +29964,Male,54,Bachelors,15,98,40,75,72,7.0,7,80,Rural,Software Engineer,96849,1 +29965,Female,38,Diploma,2,77,22,31,4,3.0,6,48,Rural,Software Engineer,125163,0 +29966,Male,23,Diploma,1,13,49,5,0,5.0,3,90,Semi-Urban,Manager,131331,0 +29967,Male,23,Masters,14,25,13,47,87,7.0,3,46,Urban,Data Analyst,33491,0 +29968,Female,47,Bachelors,1,1,67,29,77,0.0,3,38,Urban,Software Engineer,88845,0 +29969,Male,45,Bachelors,7,10,14,17,11,5.0,7,7,Urban,Data Analyst,71689,0 +29970,Male,32,Diploma,11,44,89,10,1,0.0,2,69,Urban,HR Executive,143563,0 +29971,Male,41,Bachelors,8,10,80,6,85,4.0,4,50,Rural,Data Analyst,114108,0 +29972,Female,48,Diploma,7,64,27,80,71,4.0,1,90,Urban,HR Executive,148501,1 +29973,Male,44,Bachelors,8,98,67,2,87,9.0,0,10,Urban,ML Engineer,134797,0 +29974,Other,33,Bachelors,2,68,33,30,71,8.0,5,59,Urban,ML Engineer,101347,0 +29975,Male,32,High School,1,32,0,64,91,3.0,2,90,Semi-Urban,Data Analyst,92132,0 +29976,Male,31,Diploma,13,89,50,67,25,9.0,1,3,Semi-Urban,Manager,112665,0 +29977,Male,40,High School,2,6,47,75,10,3.0,6,74,Semi-Urban,ML Engineer,68320,0 +29978,Female,52,Bachelors,10,28,80,52,75,2.0,4,52,Rural,Data Analyst,56784,0 +29979,Male,51,Diploma,12,45,82,14,54,4.0,2,56,Urban,ML Engineer,125948,0 +29980,Female,44,Bachelors,6,22,44,52,63,2.0,3,86,Urban,Manager,62970,0 +29981,Male,34,Bachelors,0,83,73,83,60,9.0,0,65,Semi-Urban,HR Executive,118877,1 +29982,Male,52,Bachelors,16,3,54,32,36,0.0,4,57,Urban,Software Engineer,31832,0 +29983,Female,43,Bachelors,6,21,83,30,72,0.0,2,38,Urban,HR Executive,113130,0 +29984,Female,39,Bachelors,8,56,79,89,19,2.0,2,89,Rural,Software Engineer,70578,1 +29985,Male,35,Masters,17,87,53,79,8,3.0,6,91,Urban,ML Engineer,77468,1 +29986,Female,34,High School,19,55,64,29,29,7.0,5,87,Urban,Data Analyst,26260,0 +29987,Female,39,Diploma,4,72,37,49,45,0.0,7,23,Rural,HR Executive,60075,0 +29988,Male,33,Diploma,15,36,84,25,68,5.0,7,49,Urban,Manager,57242,0 +29989,Male,28,Bachelors,8,90,12,12,96,9.0,2,98,Rural,HR Executive,126073,0 +29990,Male,24,Masters,10,52,95,22,35,4.0,6,69,Rural,ML Engineer,127530,1 +29991,Male,51,Bachelors,12,84,34,56,27,7.0,2,18,Semi-Urban,HR Executive,99411,0 +29992,Female,22,Masters,5,1,34,79,8,5.0,7,67,Urban,ML Engineer,49842,0 +29993,Male,50,PhD,17,65,2,93,17,6.0,6,74,Urban,HR Executive,43289,0 +29994,Male,56,Masters,1,51,16,30,77,7.0,7,13,Urban,ML Engineer,146733,0 +29995,Male,39,Masters,16,38,98,98,10,4.0,2,96,Semi-Urban,Data Analyst,85074,1 +29996,Other,39,High School,7,85,41,84,15,2.0,2,14,Urban,ML Engineer,112776,0 +29997,Female,48,PhD,0,54,77,2,11,6.0,7,1,Semi-Urban,Software Engineer,67522,0 +29998,Male,39,Diploma,8,69,13,45,18,6.0,1,77,Rural,Software Engineer,117171,0 +29999,Male,43,Masters,6,39,45,60,72,3.0,4,62,Urban,Manager,146558,0 +30000,Male,41,Diploma,18,84,97,10,25,7.0,0,14,Rural,Data Analyst,141223,0 +30001,Female,47,Bachelors,9,54,6,48,96,7.0,3,58,Rural,HR Executive,64859,0 +30002,Male,50,Masters,3,98,90,92,34,4.0,6,24,Semi-Urban,ML Engineer,117350,1 +30003,Other,53,Bachelors,1,82,20,83,43,5.0,1,80,Urban,HR Executive,89412,1 +30004,Male,23,Bachelors,12,30,10,68,15,2.0,4,28,Semi-Urban,ML Engineer,23056,0 +30005,Male,41,Diploma,17,30,42,85,20,2.0,2,41,Urban,Software Engineer,21842,0 +30006,Female,54,Bachelors,8,27,54,87,26,5.0,4,3,Urban,Data Analyst,100221,0 +30007,Female,34,Bachelors,13,16,88,48,89,5.0,4,32,Semi-Urban,Data Analyst,119314,0 +30008,Male,21,Masters,0,19,50,39,9,0.0,7,77,Urban,HR Executive,38435,0 +30009,Female,35,Masters,13,37,20,76,93,5.0,4,76,Urban,ML Engineer,57230,0 +30010,Male,23,Bachelors,16,61,99,7,67,3.0,7,53,Urban,Manager,90222,0 +30011,Male,25,Masters,19,31,41,8,94,5.0,2,72,Urban,Software Engineer,113054,0 +30012,Female,48,Diploma,10,82,27,39,78,1.0,5,50,Urban,Data Analyst,43147,0 +30013,Female,51,Diploma,11,41,61,10,66,0.0,4,70,Semi-Urban,HR Executive,93815,0 +30014,Female,30,Bachelors,8,0,0,99,50,6.0,6,0,Semi-Urban,Manager,99368,0 +30015,Male,25,Bachelors,14,83,91,44,47,5.0,6,23,Semi-Urban,Data Analyst,35939,1 +30016,Female,35,Bachelors,11,81,99,92,78,9.0,1,14,Urban,Data Analyst,55692,1 +30017,,51,Bachelors,5,82,27,25,11,0.0,6,14,Urban,Data Analyst,95486,0 +30018,Male,39,Bachelors,10,41,70,57,7,4.0,2,41,Urban,Data Analyst,97179,0 +30019,Female,48,High School,10,28,62,51,44,6.0,6,57,Rural,HR Executive,41154,0 +30020,Male,48,Bachelors,17,71,20,88,7,7.0,2,88,Rural,Manager,119427,1 +30021,Other,32,Bachelors,4,74,11,29,56,7.0,3,87,Rural,Software Engineer,64110,0 +30022,Male,39,Masters,1,85,59,22,47,1.0,4,43,Rural,Software Engineer,100311,0 +30023,Male,41,Bachelors,7,26,9,53,12,8.0,3,78,Urban,Manager,105876,0 +30024,Female,23,Bachelors,0,40,18,69,96,7.0,3,21,Semi-Urban,HR Executive,133541,0 +30025,Female,24,Masters,13,56,38,21,53,0.0,4,54,Urban,ML Engineer,137299,0 +30026,Male,23,Diploma,9,61,4,84,59,2.0,2,85,Rural,Manager,130042,0 +30027,Male,49,Diploma,1,83,70,85,26,3.0,1,40,Urban,HR Executive,142460,1 +30028,Female,59,Diploma,17,80,43,2,27,7.0,2,51,Urban,Software Engineer,78521,0 +30029,Male,30,High School,10,91,83,6,60,5.0,6,61,Semi-Urban,HR Executive,85686,1 +30030,Male,55,Bachelors,9,20,70,19,53,5.0,7,93,Urban,Data Analyst,68563,0 +30031,Female,23,Bachelors,17,6,35,3,4,6.0,3,13,Semi-Urban,ML Engineer,134268,0 +30032,Male,36,Bachelors,5,9,1,9,12,5.0,6,58,Urban,ML Engineer,113066,0 +30033,Other,58,Diploma,13,23,76,58,7,4.0,4,50,Urban,Data Analyst,92169,0 +30034,Female,50,Diploma,1,36,49,73,85,8.0,2,76,Semi-Urban,ML Engineer,48371,0 +30035,Other,46,Masters,0,11,85,55,83,1.0,7,74,Urban,ML Engineer,32169,0 +30036,Male,21,Bachelors,11,8,53,40,11,0.0,3,10,Semi-Urban,HR Executive,98673,0 +30037,Other,36,Bachelors,4,26,19,86,86,2.0,0,53,Rural,HR Executive,124694,0 +30038,Male,39,Bachelors,16,19,74,97,79,2.0,5,96,Urban,ML Engineer,96821,1 +30039,Male,32,Diploma,8,70,38,44,39,9.0,3,22,Urban,ML Engineer,71049,0 +30040,Male,25,High School,4,36,7,17,91,1.0,1,90,Semi-Urban,Manager,66319,0 +30041,Male,44,Masters,1,60,47,71,20,0.0,1,80,Semi-Urban,Data Analyst,72588,1 +30042,Male,42,High School,18,47,71,22,86,9.0,1,39,Urban,HR Executive,31180,0 +30043,Male,31,Bachelors,12,48,79,53,53,6.0,2,4,Rural,ML Engineer,90575,0 +30044,Male,46,Bachelors,2,8,64,8,45,4.0,1,74,Semi-Urban,HR Executive,79658,0 +30045,Male,41,Masters,5,27,86,32,10,5.0,6,13,Urban,Software Engineer,111086,0 +30046,Female,29,Bachelors,12,13,76,55,91,6.0,6,4,Rural,ML Engineer,129405,0 +30047,Male,45,High School,18,66,39,20,87,3.0,3,47,Rural,Software Engineer,37403,0 +30048,Female,51,Bachelors,8,50,0,77,82,2.0,2,73,Urban,Data Analyst,51077,0 +30049,Male,23,Masters,1,90,3,86,21,8.0,1,36,Rural,Data Analyst,146292,0 +30050,Female,45,Diploma,14,74,58,82,39,1.0,4,64,Rural,ML Engineer,53047,1 +30051,Male,58,PhD,10,66,96,58,56,3.0,4,46,Rural,Data Analyst,104726,1 +30052,Other,45,Bachelors,1,25,91,70,44,0.0,6,53,Semi-Urban,HR Executive,99726,0 +30053,Male,48,Bachelors,16,38,90,85,48,0.0,7,52,Urban,ML Engineer,70723,1 +30054,Other,29,Bachelors,0,58,67,72,52,1.0,0,27,Semi-Urban,ML Engineer,72064,0 +30055,Male,51,Bachelors,6,5,58,63,46,3.0,5,86,Semi-Urban,ML Engineer,32317,0 +30056,Female,43,Diploma,15,72,77,79,83,7.0,7,59,Urban,Data Analyst,93382,1 +30057,Female,29,Bachelors,10,0,34,6,94,7.0,7,49,Urban,Manager,28200,0 +30058,Male,39,Diploma,6,71,87,78,47,7.0,6,23,Semi-Urban,ML Engineer,143015,1 +30059,Male,22,Masters,14,30,3,51,56,6.0,3,20,Urban,HR Executive,56996,0 +30060,Female,55,Bachelors,15,7,25,33,86,6.0,4,8,Semi-Urban,ML Engineer,128824,0 +30061,Male,29,Masters,9,62,51,92,93,4.0,5,88,Urban,HR Executive,52606,1 +30062,Male,50,Diploma,19,30,80,32,3,4.0,2,42,Urban,Data Analyst,107961,0 +30063,Female,39,Bachelors,12,14,26,22,47,1.0,4,63,Semi-Urban,Manager,24815,0 +30064,Male,52,Diploma,8,45,43,15,3,9.0,0,84,Urban,ML Engineer,48622,0 +30065,Female,41,High School,15,36,20,59,8,1.0,3,73,Rural,ML Engineer,22350,0 +30066,Male,23,High School,9,43,84,32,99,2.0,4,77,Urban,Software Engineer,137591,1 +30067,Male,43,Bachelors,10,27,90,99,63,9.0,6,7,Urban,Software Engineer,71126,0 +30068,Male,44,Bachelors,6,81,17,87,88,6.0,1,90,Semi-Urban,Manager,116243,1 +30069,Female,54,Masters,0,80,2,83,12,1.0,6,16,Urban,HR Executive,36850,0 +30070,Other,37,High School,0,93,68,79,98,6.0,4,33,Semi-Urban,ML Engineer,123049,1 +30071,Male,45,Bachelors,0,50,75,78,48,8.0,6,64,Urban,Software Engineer,114926,1 +30072,Male,22,High School,9,53,5,73,53,6.0,4,48,Urban,Manager,127302,0 +30073,Male,54,High School,11,93,3,52,2,4.0,5,27,Urban,Manager,122754,0 +30074,Female,51,Bachelors,8,29,29,85,3,6.0,7,45,Urban,Software Engineer,89325,0 +30075,Male,41,Bachelors,6,67,64,77,6,7.0,7,38,Urban,HR Executive,59304,1 +30076,Male,31,Diploma,8,8,89,40,98,2.0,3,35,Urban,Data Analyst,115108,0 +30077,Male,54,Diploma,4,67,22,2,17,0.0,3,91,Urban,Manager,76967,0 +30078,Male,25,Diploma,9,38,97,16,68,7.0,6,41,Urban,Software Engineer,67933,0 +30079,Male,30,PhD,16,41,97,74,58,1.0,1,98,Urban,Data Analyst,47875,1 +30080,Male,58,Bachelors,16,30,13,25,71,6.0,1,7,Semi-Urban,HR Executive,112721,0 +30081,Female,44,Bachelors,9,63,96,99,40,0.0,4,93,Semi-Urban,HR Executive,148984,1 +30082,Female,43,Masters,5,65,33,61,95,0.0,0,93,Urban,HR Executive,141977,1 +30083,Female,36,Masters,17,88,92,5,70,0.0,0,39,Urban,ML Engineer,144520,0 +30084,Male,32,Masters,16,28,9,68,46,5.0,1,86,Rural,HR Executive,137725,0 +30085,Male,36,PhD,16,62,67,92,78,7.0,6,1,Urban,ML Engineer,47936,0 +30086,Male,54,Diploma,4,83,63,27,62,1.0,7,66,Urban,Data Analyst,98724,1 +30087,Female,34,High School,2,56,35,44,42,4.0,2,23,Urban,Manager,146521,0 +30088,Male,41,Masters,2,23,48,99,96,5.0,6,27,Urban,ML Engineer,143255,0 +30089,Female,21,Masters,17,80,11,13,75,3.0,6,89,Urban,ML Engineer,50513,0 +30090,Male,58,Diploma,4,89,9,78,21,4.0,1,12,Rural,HR Executive,120579,0 +30091,Female,51,Diploma,16,42,96,87,9,2.0,4,87,Urban,Software Engineer,66034,1 +30092,Female,59,Diploma,16,63,79,35,83,1.0,6,37,Rural,HR Executive,133695,0 +30093,Male,56,Bachelors,7,78,74,76,59,5.0,1,2,Rural,Manager,120616,0 +30094,Female,53,High School,1,74,74,52,8,3.0,6,43,Urban,Data Analyst,135596,1 +30095,Female,51,Bachelors,2,55,9,16,90,3.0,5,78,Semi-Urban,ML Engineer,91522,0 +30096,Female,40,Bachelors,5,65,31,4,70,9.0,3,55,Semi-Urban,Software Engineer,138449,0 +30097,Female,53,Masters,12,2,50,59,36,2.0,2,67,Semi-Urban,ML Engineer,139832,0 +30098,Male,48,Bachelors,18,25,88,38,85,4.0,6,64,Rural,Data Analyst,109775,0 +30099,Female,50,Bachelors,10,39,55,38,21,1.0,5,42,Rural,Manager,89424,0 +30100,Female,40,Bachelors,12,81,21,22,76,0.0,3,24,Urban,HR Executive,65251,0 +30101,Male,26,Diploma,6,99,10,63,78,9.0,6,23,Semi-Urban,Software Engineer,122943,0 +30102,Male,31,Bachelors,10,5,56,26,24,8.0,0,32,Urban,Manager,121663,0 +30103,Male,43,High School,3,90,0,33,23,3.0,1,17,Urban,Manager,82710,0 +30104,Male,25,Masters,8,53,37,91,60,8.0,1,76,Urban,Software Engineer,149688,1 +30105,Female,56,Masters,18,94,93,75,34,7.0,5,14,Semi-Urban,Software Engineer,110525,1 +30106,Male,39,High School,1,29,49,71,25,4.0,6,88,Urban,Software Engineer,25580,1 +30107,Male,55,High School,2,85,32,43,87,7.0,1,4,Urban,ML Engineer,44421,0 +30108,Male,27,Bachelors,1,71,85,35,93,6.0,7,79,Urban,HR Executive,31264,1 +30109,Male,54,Bachelors,13,17,97,96,84,5.0,3,74,Semi-Urban,HR Executive,105243,1 +30110,Male,41,Masters,4,52,75,56,29,0.0,3,18,Semi-Urban,Data Analyst,112456,0 +30111,Male,45,Diploma,13,74,12,76,54,0.0,5,98,Urban,ML Engineer,39972,1 +30112,Male,21,Masters,10,88,25,20,58,5.0,3,90,Urban,Manager,29610,0 +30113,Female,53,Bachelors,13,98,35,27,43,4.0,3,55,Rural,Manager,105633,0 +30114,Male,59,Diploma,14,82,36,89,59,9.0,5,71,Urban,HR Executive,78322,1 +30115,Male,22,High School,8,21,91,64,61,5.0,7,24,Urban,ML Engineer,119906,0 +30116,Male,36,Diploma,0,86,1,76,30,6.0,1,65,Urban,ML Engineer,62149,0 +30117,Male,21,Masters,8,84,46,27,62,0.0,0,19,Urban,HR Executive,31002,0 +30118,Male,59,Diploma,14,3,50,57,40,2.0,4,54,Semi-Urban,HR Executive,46800,0 +30119,Male,53,High School,16,45,96,24,90,5.0,6,0,Rural,Data Analyst,28915,0 +30120,Male,29,Masters,1,20,96,27,18,0.0,2,6,Urban,HR Executive,62956,0 +30121,Male,54,Bachelors,3,19,76,23,35,8.0,7,40,Urban,Software Engineer,24177,0 +30122,Male,42,Diploma,17,3,43,33,73,2.0,1,7,Urban,ML Engineer,103710,0 +30123,Female,37,High School,2,47,83,28,41,8.0,0,50,Urban,Data Analyst,111321,0 +30124,Male,34,Diploma,4,87,18,25,71,9.0,4,35,Semi-Urban,Software Engineer,80421,0 +30125,Female,37,Diploma,4,60,61,76,2,7.0,6,60,Urban,Manager,75925,1 +30126,Female,31,Bachelors,1,86,47,90,61,0.0,2,49,Semi-Urban,ML Engineer,38226,1 +30127,Female,45,Bachelors,10,51,90,58,1,4.0,1,96,Semi-Urban,Manager,123612,1 +30128,Male,57,Masters,9,49,62,12,14,7.0,4,96,Urban,ML Engineer,28238,0 +30129,Female,58,PhD,14,27,51,73,49,5.0,4,25,Urban,Software Engineer,105500,0 +30130,Male,40,High School,18,23,26,1,76,2.0,6,96,Urban,Manager,109368,0 +30131,Male,29,PhD,11,46,72,91,58,2.0,1,0,Rural,Software Engineer,92372,0 +30132,Male,51,Bachelors,19,99,33,48,65,7.0,7,22,Rural,Manager,21216,0 +30133,Female,27,Masters,17,53,71,43,45,7.0,6,66,Urban,ML Engineer,70859,0 +30134,Male,58,Bachelors,7,76,22,21,8,6.0,1,70,Semi-Urban,ML Engineer,55398,0 +30135,Female,31,Bachelors,13,7,39,32,97,4.0,5,71,Urban,Software Engineer,100952,0 +30136,Male,52,Bachelors,16,77,7,44,75,1.0,0,71,Rural,Data Analyst,92823,0 +30137,Female,28,Bachelors,3,57,72,95,87,4.0,7,19,Urban,Data Analyst,92313,1 +30138,Female,34,Bachelors,4,11,23,21,95,0.0,2,19,Urban,Software Engineer,130633,0 +30139,Female,31,High School,7,18,24,6,45,2.0,2,86,Rural,Data Analyst,102117,0 +30140,Male,55,Masters,1,49,32,77,14,4.0,3,72,Urban,ML Engineer,62702,0 +30141,Female,29,Bachelors,0,22,92,60,85,8.0,6,48,Urban,ML Engineer,60680,0 +30142,Other,26,Bachelors,13,97,0,22,49,3.0,0,88,Rural,Manager,66295,0 +30143,Male,51,High School,7,49,49,24,69,3.0,2,27,Urban,Software Engineer,119581,0 +30144,Male,46,High School,3,52,61,25,19,8.0,7,21,Semi-Urban,Manager,91165,0 +30145,Female,30,Bachelors,6,65,15,7,16,6.0,4,80,Rural,Data Analyst,64527,0 +30146,Male,43,Bachelors,19,47,23,65,25,0.0,7,60,Rural,Data Analyst,25943,0 +30147,Female,57,High School,5,95,8,35,17,8.0,5,42,Urban,HR Executive,36293,0 +30148,Male,31,Bachelors,12,14,98,90,17,4.0,2,43,Urban,Manager,58679,1 +30149,Male,48,Diploma,0,6,30,48,73,1.0,7,11,Semi-Urban,Data Analyst,64216,0 +30150,Male,23,Bachelors,17,95,41,12,77,7.0,4,49,Urban,ML Engineer,148851,0 +30151,Male,58,Bachelors,5,87,53,16,73,9.0,0,86,Rural,Data Analyst,117396,1 +30152,Male,56,Masters,10,43,12,94,0,6.0,6,45,Rural,Software Engineer,89945,0 +30153,Female,25,PhD,6,86,58,95,95,3.0,0,77,Semi-Urban,Data Analyst,107867,1 +30154,Male,41,Bachelors,2,82,51,65,87,3.0,0,14,Rural,Manager,107169,0 +30155,Female,28,Bachelors,11,95,36,79,12,6.0,7,34,Rural,Software Engineer,39253,1 +30156,Female,34,Bachelors,17,28,9,59,98,1.0,4,15,Semi-Urban,Manager,85967,0 +30157,Male,38,High School,15,96,84,1,81,7.0,1,63,Urban,HR Executive,60204,1 +30158,Male,36,High School,7,66,92,79,83,6.0,3,36,Urban,HR Executive,95381,1 +30159,Male,22,Diploma,18,78,52,0,35,7.0,0,38,Rural,Software Engineer,136344,0 +30160,Male,22,Diploma,11,65,89,37,6,8.0,2,33,Urban,Manager,84768,0 +30161,Male,43,Bachelors,2,67,12,44,4,4.0,6,39,Urban,Software Engineer,136874,0 +30162,Male,51,Bachelors,8,55,67,4,34,8.0,2,96,Urban,ML Engineer,51522,0 +30163,Other,21,Bachelors,12,40,8,28,90,5.0,6,33,Semi-Urban,Manager,25418,0 +30164,Male,53,High School,17,60,41,40,51,2.0,7,26,Rural,HR Executive,139259,0 +30165,Male,51,,0,26,83,0,88,9.0,5,17,Rural,Data Analyst,32836,0 +30166,Other,22,Masters,19,46,35,46,75,6.0,1,11,Rural,Manager,43616,0 +30167,Female,35,High School,18,42,17,12,40,5.0,5,24,Urban,Data Analyst,75327,0 +30168,Female,56,Bachelors,12,59,21,34,92,2.0,6,81,Semi-Urban,Manager,35039,0 +30169,Female,56,Bachelors,10,14,57,16,99,5.0,1,3,Urban,Data Analyst,102791,0 +30170,Male,47,Diploma,19,78,17,6,28,9.0,0,58,Urban,Software Engineer,75554,0 +30171,Female,37,Masters,5,82,62,23,14,7.0,0,17,Rural,Manager,123474,0 +30172,Female,28,Bachelors,17,92,81,83,18,7.0,1,35,Semi-Urban,HR Executive,69486,1 +30173,Male,47,Bachelors,4,75,60,92,1,2.0,4,60,Urban,Manager,37223,1 +30174,Male,42,High School,8,68,38,77,64,7.0,6,98,Urban,Data Analyst,33920,1 +30175,Male,44,Bachelors,13,0,30,88,2,1.0,6,56,Semi-Urban,HR Executive,71092,0 +30176,Male,56,Diploma,1,4,71,73,42,6.0,3,42,Urban,ML Engineer,89227,0 +30177,Male,34,Bachelors,17,28,45,46,66,2.0,5,36,Urban,ML Engineer,47647,0 +30178,Female,35,Masters,2,73,92,37,52,2.0,0,12,Urban,Manager,35437,0 +30179,Male,59,Bachelors,17,36,91,37,47,0.0,3,28,Urban,Data Analyst,53723,0 +30180,Male,50,Bachelors,13,69,65,6,19,1.0,5,70,Semi-Urban,Software Engineer,31840,0 +30181,Male,51,Bachelors,1,56,53,97,2,9.0,4,40,Urban,HR Executive,95253,1 +30182,Female,43,High School,2,18,48,29,82,0.0,6,74,Rural,ML Engineer,40751,0 +30183,Male,35,Diploma,8,63,51,56,51,9.0,0,24,Semi-Urban,HR Executive,101199,0 +30184,Male,33,Bachelors,3,3,34,3,3,6.0,1,36,Urban,Manager,37886,0 +30185,Female,41,High School,8,6,31,42,31,7.0,1,3,Semi-Urban,Manager,102559,0 +30186,Male,31,Diploma,7,44,99,92,90,5.0,6,68,Rural,Data Analyst,84464,1 +30187,Male,51,Masters,7,56,7,35,90,7.0,6,41,Urban,Data Analyst,105675,0 +30188,Male,25,High School,6,66,74,2,66,2.0,6,97,Urban,Software Engineer,131791,1 +30189,Female,21,Diploma,7,93,34,78,81,4.0,6,39,Urban,Data Analyst,32468,1 +30190,Female,21,Bachelors,17,9,70,6,87,8.0,0,68,Urban,Data Analyst,112324,0 +30191,Male,55,Diploma,1,64,8,69,95,0.0,1,75,Urban,Software Engineer,49394,0 +30192,Male,51,Masters,11,8,6,38,45,4.0,0,85,Urban,ML Engineer,88872,0 +30193,Female,55,Bachelors,7,77,17,73,74,5.0,4,5,Urban,Manager,116409,0 +30194,Female,55,Masters,0,81,10,66,20,1.0,5,29,Urban,HR Executive,33954,0 +30195,Female,31,Diploma,2,57,9,97,50,3.0,6,15,Urban,Manager,136451,0 +30196,Female,29,High School,5,77,37,92,75,7.0,4,59,Urban,HR Executive,61140,1 +30197,Male,52,Masters,0,48,57,66,48,3.0,3,45,Rural,Manager,48295,0 +30198,Female,56,Bachelors,15,47,33,97,94,7.0,5,18,Urban,Software Engineer,91304,0 +30199,Female,31,Bachelors,7,98,78,91,12,6.0,6,14,Urban,Manager,136136,1 +30200,Female,58,Bachelors,10,97,68,25,53,7.0,3,15,Urban,HR Executive,24595,0 +30201,Female,51,Masters,14,21,5,44,94,7.0,6,55,Semi-Urban,ML Engineer,129913,0 +30202,Male,38,Diploma,14,96,81,2,19,8.0,0,40,Urban,ML Engineer,37973,0 +30203,Female,44,High School,2,78,88,57,61,5.0,4,47,Urban,HR Executive,54189,1 +30204,Female,59,High School,1,94,37,11,34,0.0,3,49,Semi-Urban,ML Engineer,50082,0 +30205,Female,23,High School,15,30,44,36,96,6.0,7,5,Urban,Software Engineer,122968,0 +30206,Male,49,Masters,9,45,81,30,61,3.0,7,0,Urban,Software Engineer,126044,0 +30207,Female,46,Bachelors,17,62,58,75,10,0.0,3,42,Urban,Manager,88225,0 +30208,Female,40,Masters,17,56,90,91,91,3.0,7,47,Urban,Manager,105566,1 +30209,Male,36,High School,8,11,32,46,85,9.0,6,96,Urban,ML Engineer,65250,0 +30210,Female,39,Bachelors,17,70,62,88,73,9.0,4,62,Urban,Data Analyst,89377,1 +30211,Female,52,Bachelors,5,78,76,6,94,2.0,4,97,Urban,Data Analyst,78606,1 +30212,Male,27,Diploma,18,36,38,17,7,7.0,0,37,Semi-Urban,ML Engineer,62971,0 +30213,Male,49,Masters,3,2,64,7,75,1.0,5,52,Urban,ML Engineer,33752,0 +30214,Male,34,Bachelors,18,62,63,99,14,0.0,1,96,Rural,Software Engineer,91613,1 +30215,Male,33,Bachelors,18,20,7,57,12,9.0,4,32,Rural,ML Engineer,83654,0 +30216,Male,56,Masters,17,4,38,31,24,7.0,1,62,Semi-Urban,ML Engineer,40551,0 +30217,Male,21,Diploma,17,22,62,0,38,9.0,3,76,Urban,HR Executive,136714,0 +30218,Male,22,Diploma,16,29,90,40,83,9.0,1,25,Semi-Urban,Manager,105583,0 +30219,Male,33,PhD,17,99,22,21,90,9.0,4,84,Rural,Data Analyst,115695,0 +30220,Male,45,Diploma,16,45,18,48,52,5.0,5,25,Urban,Software Engineer,88928,0 +30221,Female,42,High School,0,21,35,17,11,1.0,2,73,Urban,Manager,56016,0 +30222,Male,29,PhD,15,96,90,60,93,2.0,2,6,Rural,ML Engineer,37203,1 +30223,Female,28,Masters,11,60,58,73,85,6.0,2,53,Rural,Manager,122551,1 +30224,Male,28,Masters,13,74,90,91,44,6.0,1,83,Urban,HR Executive,92740,1 +30225,Male,45,Bachelors,4,25,99,25,90,2.0,7,61,Urban,Data Analyst,62256,0 +30226,Male,36,Bachelors,11,82,50,5,93,2.0,6,97,Urban,HR Executive,29886,0 +30227,Female,50,Diploma,6,79,88,57,61,7.0,0,92,Urban,Manager,48391,1 +30228,Female,53,PhD,18,39,98,58,66,3.0,2,59,Urban,HR Executive,115628,1 +30229,Female,43,Diploma,4,65,68,77,43,3.0,6,20,Urban,ML Engineer,87862,0 +30230,Male,27,PhD,4,27,91,86,65,5.0,1,96,Urban,ML Engineer,109369,1 +30231,Female,37,Bachelors,17,65,80,95,51,8.0,2,90,Urban,Manager,47171,1 +30232,Male,50,Bachelors,14,80,41,71,65,0.0,6,59,Semi-Urban,HR Executive,58297,1 +30233,Female,48,High School,11,45,0,91,76,6.0,0,46,Semi-Urban,Manager,74452,0 +30234,Male,31,Bachelors,15,72,12,56,42,9.0,6,20,Urban,Data Analyst,68825,0 +30235,Male,41,Bachelors,16,36,3,69,4,6.0,4,87,Urban,Data Analyst,61066,0 +30236,Male,27,Masters,13,15,85,10,28,1.0,3,90,Rural,HR Executive,122812,0 +30237,Female,42,Bachelors,19,70,71,65,21,9.0,2,69,Semi-Urban,Manager,31978,1 +30238,Male,49,Bachelors,8,1,38,29,44,1.0,7,57,Urban,ML Engineer,78069,0 +30239,Male,27,Bachelors,15,46,92,21,42,6.0,3,10,Urban,HR Executive,105093,0 +30240,Male,28,Diploma,17,20,10,42,29,9.0,4,97,Semi-Urban,Software Engineer,29656,0 +30241,Other,31,Masters,11,16,79,83,89,1.0,0,38,Urban,HR Executive,130848,0 +30242,Male,29,Bachelors,1,10,78,69,29,2.0,5,69,Semi-Urban,ML Engineer,63634,0 +30243,Female,51,Bachelors,17,20,19,8,27,4.0,1,55,Semi-Urban,ML Engineer,101895,0 +30244,Other,40,High School,4,90,40,5,20,9.0,2,75,Urban,Data Analyst,37925,0 +30245,Female,56,High School,13,91,58,3,22,5.0,4,69,Urban,Software Engineer,50312,0 +30246,Female,28,PhD,10,85,33,0,41,0.0,4,9,Urban,ML Engineer,117383,0 +30247,Female,45,Masters,15,38,61,71,4,0.0,1,96,Urban,Data Analyst,85064,1 +30248,Male,49,Bachelors,17,81,93,89,98,6.0,7,36,Urban,ML Engineer,82698,1 +30249,Male,40,High School,7,46,63,16,10,5.0,7,77,Urban,Manager,115116,0 +30250,Female,44,High School,2,96,9,83,80,8.0,6,35,Rural,Manager,108278,0 +30251,Male,50,Bachelors,15,91,69,87,87,2.0,3,98,Urban,HR Executive,149834,1 +30252,Male,47,Diploma,14,8,47,44,31,6.0,7,78,Urban,ML Engineer,43706,0 +30253,Female,42,High School,17,53,1,80,81,6.0,5,20,Urban,HR Executive,134858,0 +30254,Male,50,Bachelors,12,89,80,71,98,1.0,7,66,Urban,Data Analyst,143105,1 +30255,Female,26,Bachelors,2,39,72,11,17,6.0,3,34,Urban,Data Analyst,127243,0 +30256,Female,23,Masters,19,4,46,37,18,4.0,3,72,Urban,Data Analyst,27954,0 +30257,Male,25,High School,7,99,94,57,25,8.0,6,69,Rural,Data Analyst,64222,1 +30258,Male,51,Masters,10,57,14,34,93,7.0,5,25,Urban,HR Executive,129473,0 +30259,Male,36,PhD,2,70,98,16,59,0.0,1,20,Rural,Software Engineer,129146,0 +30260,Other,53,Diploma,2,2,36,78,43,2.0,0,84,Rural,Software Engineer,135904,0 +30261,Male,56,High School,11,37,26,46,17,2.0,6,78,Urban,Software Engineer,31208,0 +30262,Male,25,Masters,17,44,78,94,67,1.0,6,11,Urban,Software Engineer,52819,0 +30263,Female,31,Diploma,10,15,40,92,48,9.0,0,93,Semi-Urban,ML Engineer,41856,0 +30264,Male,33,PhD,12,90,22,14,95,5.0,4,24,Urban,Data Analyst,75964,0 +30265,Male,49,High School,5,61,2,12,31,7.0,1,46,Semi-Urban,HR Executive,101591,0 +30266,Male,23,Bachelors,11,95,76,15,35,3.0,6,28,Rural,Software Engineer,21228,0 +30267,Male,46,PhD,13,94,11,81,94,8.0,5,52,Urban,HR Executive,146235,1 +30268,Male,46,Bachelors,1,39,54,37,71,3.0,0,93,Semi-Urban,HR Executive,132265,0 +30269,Female,44,Bachelors,17,82,13,17,5,0.0,2,19,Urban,ML Engineer,130056,0 +30270,Male,26,Bachelors,14,18,21,42,88,0.0,3,67,Urban,Manager,146886,0 +30271,Male,40,Masters,17,40,66,36,63,0.0,6,7,Urban,Manager,109918,0 +30272,Male,26,High School,10,34,28,2,13,3.0,6,90,Urban,Manager,108572,0 +30273,Male,45,High School,18,73,42,29,28,0.0,7,98,Urban,Manager,122697,1 +30274,Female,49,Bachelors,14,88,83,57,86,9.0,4,17,Urban,Software Engineer,29549,1 +30275,Male,23,Bachelors,15,44,48,21,29,6.0,6,69,Semi-Urban,Data Analyst,96435,0 +30276,Other,21,Masters,3,97,74,12,11,1.0,1,57,Semi-Urban,ML Engineer,106436,0 +30277,Male,48,Diploma,9,86,32,40,50,1.0,6,36,Urban,ML Engineer,31107,0 +30278,Female,48,Masters,14,97,19,87,59,8.0,6,45,Semi-Urban,Manager,54693,1 +30279,Male,46,High School,19,37,54,43,35,5.0,1,80,Urban,ML Engineer,145810,0 +30280,Male,58,Bachelors,12,24,82,78,12,9.0,7,66,Semi-Urban,HR Executive,49726,1 +30281,Male,25,PhD,0,92,29,92,25,2.0,2,11,Rural,ML Engineer,109704,0 +30282,Female,26,High School,18,43,7,16,72,7.0,2,81,Urban,ML Engineer,98724,0 +30283,Male,34,Diploma,16,80,78,6,38,5.0,4,17,Urban,HR Executive,57994,0 +30284,Male,58,PhD,16,20,46,10,73,9.0,4,54,Semi-Urban,Software Engineer,32725,0 +30285,Female,21,High School,9,69,42,19,40,4.0,5,61,Urban,Data Analyst,35645,0 +30286,Male,48,Bachelors,3,12,91,13,38,9.0,4,24,Urban,ML Engineer,139222,0 +30287,Male,50,Bachelors,12,39,65,80,62,6.0,5,93,Urban,ML Engineer,128186,1 +30288,Female,32,Masters,8,64,74,36,9,8.0,3,21,Rural,HR Executive,112702,0 +30289,Male,58,Diploma,8,36,63,66,16,6.0,0,84,Rural,HR Executive,93169,1 +30290,Female,45,Bachelors,10,10,56,97,33,1.0,4,90,Rural,Data Analyst,147203,1 +30291,Male,49,Masters,4,73,96,18,92,1.0,0,31,Urban,ML Engineer,47490,0 +30292,Male,22,Bachelors,2,45,45,83,56,9.0,2,24,Urban,Manager,134925,0 +30293,Male,56,Masters,4,25,41,67,19,7.0,3,6,Urban,Data Analyst,109451,0 +30294,Female,56,Bachelors,2,28,26,89,0,2.0,7,92,Semi-Urban,ML Engineer,76745,0 +30295,Female,58,Bachelors,8,27,43,28,77,7.0,2,21,Urban,Data Analyst,104200,0 +30296,Other,58,Diploma,12,34,99,79,68,4.0,3,50,Urban,Data Analyst,105742,1 +30297,Male,42,Bachelors,18,86,58,95,72,5.0,1,2,Urban,ML Engineer,26920,1 +30298,Female,49,Masters,16,71,0,69,1,6.0,0,95,Urban,ML Engineer,51728,0 +30299,Male,23,High School,6,6,85,88,33,8.0,5,46,Urban,Manager,50485,0 +30300,Male,36,Bachelors,6,53,46,83,8,9.0,0,84,Urban,Software Engineer,131201,1 +30301,Female,51,Bachelors,13,17,77,60,73,5.0,0,19,Urban,Manager,116353,0 +30302,Male,41,Masters,2,89,7,13,54,5.0,5,87,Rural,Software Engineer,80083,0 +30303,Male,53,Bachelors,1,56,3,85,7,4.0,0,17,Urban,Data Analyst,26760,0 +30304,Male,43,High School,13,1,82,30,72,5.0,7,47,Urban,ML Engineer,25863,0 +30305,Female,28,Bachelors,18,61,89,96,3,4.0,1,62,Semi-Urban,Software Engineer,137877,1 +30306,Male,48,Bachelors,10,69,6,63,15,2.0,0,71,Urban,Software Engineer,88375,0 +30307,Male,24,Bachelors,12,94,70,3,20,3.0,3,65,Urban,Data Analyst,33796,0 +30308,Other,52,Bachelors,3,30,71,22,94,9.0,3,47,Urban,Software Engineer,75744,0 +30309,Male,34,High School,13,36,43,68,0,9.0,0,92,Semi-Urban,HR Executive,28773,1 +30310,Male,53,Bachelors,1,27,67,65,64,7.0,7,57,Rural,Data Analyst,75888,0 +30311,Female,44,Bachelors,3,22,15,55,61,6.0,1,37,Urban,Software Engineer,126490,0 +30312,Female,27,Bachelors,12,67,83,54,14,0.0,7,22,Urban,Manager,127016,0 +30313,Male,22,Bachelors,8,35,33,2,19,6.0,2,95,Urban,HR Executive,136254,0 +30314,Female,39,Bachelors,7,45,18,47,85,2.0,2,36,Rural,ML Engineer,31026,0 +30315,Male,53,High School,14,72,63,14,97,8.0,3,51,Urban,Data Analyst,50870,0 +30316,Male,35,Masters,8,74,85,49,59,2.0,5,41,Urban,Data Analyst,91087,1 +30317,Male,51,Bachelors,7,62,7,38,70,7.0,0,63,Semi-Urban,Data Analyst,100127,0 +30318,Male,26,Masters,9,29,73,5,96,4.0,5,29,Urban,HR Executive,147834,0 +30319,Male,23,Masters,19,71,42,87,86,5.0,7,79,Urban,ML Engineer,142731,1 +30320,Female,23,Bachelors,2,59,34,45,66,1.0,1,61,Urban,HR Executive,119687,0 +30321,Female,41,Masters,2,35,19,77,93,8.0,3,24,Urban,Software Engineer,64503,0 +30322,Female,58,High School,19,94,0,93,56,8.0,4,28,Urban,Data Analyst,124433,0 +30323,Female,41,Diploma,19,29,25,26,37,7.0,2,49,Urban,ML Engineer,105184,0 +30324,Male,33,Diploma,0,53,95,68,14,9.0,7,15,Semi-Urban,ML Engineer,116398,0 +30325,Male,54,Masters,0,90,82,97,15,4.0,4,51,Rural,Data Analyst,74764,1 +30326,Female,54,Diploma,8,19,86,69,96,1.0,1,30,Rural,HR Executive,24161,0 +30327,Female,38,Bachelors,6,35,68,10,45,2.0,3,74,Urban,ML Engineer,115776,0 +30328,Other,34,Bachelors,4,89,83,98,11,8.0,2,26,Semi-Urban,HR Executive,98105,1 +30329,Male,22,Bachelors,7,13,10,38,42,8.0,6,91,Urban,Software Engineer,140613,0 +30330,Male,34,Masters,2,22,51,6,20,5.0,4,42,Urban,Manager,134342,0 +30331,Male,59,Diploma,13,66,75,78,46,1.0,5,62,Semi-Urban,ML Engineer,94323,1 +30332,Male,59,Bachelors,15,81,81,67,96,9.0,4,38,Urban,ML Engineer,65899,1 +30333,Male,31,Bachelors,7,80,2,83,81,1.0,4,30,Urban,Data Analyst,38290,0 +30334,Male,22,Bachelors,10,40,82,51,36,6.0,2,76,Semi-Urban,Software Engineer,55340,1 +30335,Female,24,Bachelors,3,61,7,24,16,6.0,7,64,Urban,ML Engineer,139041,0 +30336,Male,58,Masters,16,2,82,8,76,7.0,3,40,Urban,ML Engineer,94066,0 +30337,Male,22,Masters,3,40,30,94,28,9.0,0,65,Urban,Data Analyst,75354,0 +30338,Female,31,Bachelors,5,24,93,38,95,9.0,3,74,Urban,Data Analyst,112292,0 +30339,Male,35,Diploma,18,71,86,48,8,5.0,0,54,Rural,Data Analyst,113991,1 +30340,Male,34,Masters,11,19,78,62,4,9.0,0,68,Urban,Data Analyst,130028,0 +30341,Male,55,Diploma,12,15,88,54,63,0.0,3,73,Urban,HR Executive,147671,0 +30342,Female,23,Masters,19,18,0,81,92,2.0,4,5,Rural,Data Analyst,141243,0 +30343,Male,23,Bachelors,4,27,63,89,27,6.0,0,12,Rural,HR Executive,64961,0 +30344,Female,37,Bachelors,9,33,40,24,4,3.0,5,31,Urban,HR Executive,21156,0 +30345,Male,42,Bachelors,14,67,53,81,93,0.0,6,46,Semi-Urban,HR Executive,105821,1 +30346,Male,54,Diploma,3,84,96,74,43,5.0,7,25,Rural,Manager,72429,1 +30347,Male,50,Bachelors,17,53,21,26,13,9.0,1,27,Urban,Data Analyst,109115,0 +30348,Male,34,Bachelors,14,57,97,23,81,1.0,1,34,Urban,Manager,138252,0 +30349,Male,24,Masters,18,56,58,1,30,3.0,7,29,Urban,HR Executive,63676,0 +30350,Female,48,High School,6,64,77,82,65,5.0,2,69,Semi-Urban,ML Engineer,78146,1 +30351,Male,57,Bachelors,14,58,17,29,15,0.0,6,80,Urban,ML Engineer,117960,0 +30352,Female,56,Masters,15,21,17,83,40,5.0,5,86,Urban,ML Engineer,53968,0 +30353,Female,55,Bachelors,9,22,54,91,70,7.0,0,7,Urban,Software Engineer,73971,0 +30354,Female,58,Bachelors,14,33,94,4,48,5.0,6,69,Urban,HR Executive,108017,0 +30355,Male,24,Diploma,12,66,52,94,60,9.0,6,59,Urban,ML Engineer,20944,1 +30356,Other,32,Masters,16,23,96,14,64,0.0,0,80,Urban,HR Executive,103877,0 +30357,Male,35,Diploma,15,91,23,34,84,3.0,0,34,Semi-Urban,ML Engineer,42190,0 +30358,Male,22,Diploma,1,34,6,41,20,3.0,5,23,Urban,Data Analyst,92184,0 +30359,Female,53,Masters,3,13,63,75,41,7.0,6,9,Rural,HR Executive,25149,0 +30360,Male,35,Bachelors,13,54,78,23,86,1.0,7,18,Semi-Urban,Manager,111234,0 +30361,Female,57,Bachelors,11,84,74,8,61,3.0,1,67,Semi-Urban,Software Engineer,61289,0 +30362,Male,42,Masters,8,40,21,86,9,9.0,7,79,Rural,Manager,20598,0 +30363,Male,39,Bachelors,13,4,69,76,0,9.0,3,19,Semi-Urban,Manager,74148,0 +30364,Male,46,Diploma,17,65,71,28,27,2.0,7,57,Urban,Software Engineer,120168,0 +30365,Male,24,Bachelors,4,79,63,48,20,7.0,7,27,Semi-Urban,Data Analyst,87969,0 +30366,Male,52,Bachelors,4,68,5,78,58,6.0,7,83,Rural,Software Engineer,88898,0 +30367,Male,41,Masters,0,3,72,88,11,1.0,5,78,Semi-Urban,ML Engineer,50452,1 +30368,Female,29,Masters,19,24,7,18,16,8.0,7,56,Semi-Urban,HR Executive,22435,0 +30369,Female,53,High School,16,93,62,71,97,7.0,4,71,Semi-Urban,HR Executive,46029,1 +30370,Female,41,Diploma,3,1,62,51,68,6.0,6,13,Rural,Data Analyst,103346,0 +30371,Female,52,PhD,5,12,28,65,10,6.0,2,39,Rural,Data Analyst,127789,0 +30372,Male,31,PhD,0,11,52,46,23,2.0,7,58,Urban,HR Executive,117032,0 +30373,Female,26,Bachelors,0,52,63,76,68,6.0,5,45,Urban,HR Executive,143179,0 +30374,Male,30,Bachelors,6,52,62,17,40,0.0,2,80,Urban,ML Engineer,90017,0 +30375,Male,22,Masters,18,99,62,91,88,7.0,4,81,Urban,Software Engineer,54444,1 +30376,Female,54,Bachelors,14,73,99,22,31,9.0,2,17,Rural,Software Engineer,42432,0 +30377,Male,59,Bachelors,17,3,66,98,4,6.0,1,15,Rural,Manager,75289,0 +30378,Female,28,High School,4,57,74,98,23,2.0,7,91,Rural,Manager,100044,1 +30379,Male,46,PhD,19,62,2,67,57,9.0,0,45,Urban,HR Executive,75929,0 +30380,Male,58,PhD,4,94,14,78,14,4.0,7,63,Urban,Manager,88451,1 +30381,Male,51,Diploma,0,53,63,6,3,5.0,3,57,Semi-Urban,ML Engineer,101168,0 +30382,Male,50,High School,10,61,10,61,11,8.0,5,22,Urban,Data Analyst,64857,0 +30383,Female,39,Diploma,11,21,32,49,93,8.0,2,9,Semi-Urban,ML Engineer,82765,0 +30384,Other,36,PhD,10,35,65,3,38,2.0,2,80,Urban,Manager,100846,0 +30385,Male,22,Diploma,17,97,95,19,93,8.0,3,81,Urban,HR Executive,90003,1 +30386,Male,53,Bachelors,0,58,4,15,91,3.0,2,87,Rural,Manager,106230,0 +30387,Male,41,High School,9,33,82,19,5,5.0,2,29,Semi-Urban,HR Executive,54912,0 +30388,Female,53,Bachelors,4,33,14,47,64,3.0,2,20,Urban,ML Engineer,60860,0 +30389,Male,48,Masters,11,51,50,39,97,2.0,5,53,Urban,ML Engineer,46531,0 +30390,Female,32,Bachelors,12,46,9,88,25,2.0,3,68,Urban,ML Engineer,80004,0 +30391,Female,39,Diploma,7,35,79,38,35,3.0,0,14,Semi-Urban,ML Engineer,137434,0 +30392,Female,24,High School,12,78,21,30,64,6.0,2,66,Urban,Software Engineer,139871,0 +30393,Male,33,PhD,3,28,99,34,91,8.0,3,86,Semi-Urban,Data Analyst,125279,1 +30394,Female,42,Bachelors,19,7,48,75,88,2.0,4,56,Urban,Manager,39780,0 +30395,Female,43,Bachelors,10,10,22,21,67,8.0,1,4,Urban,ML Engineer,60850,0 +30396,Female,53,High School,19,11,16,5,27,8.0,6,62,Rural,Data Analyst,58277,0 +30397,Female,28,Diploma,4,53,33,43,3,1.0,6,56,Urban,Data Analyst,128826,0 +30398,Male,39,Masters,6,32,30,20,39,6.0,7,23,Urban,ML Engineer,37982,0 +30399,Female,34,Bachelors,0,62,18,97,38,9.0,7,4,Urban,Software Engineer,83193,0 +30400,Female,42,Bachelors,12,91,72,90,77,9.0,5,47,Urban,HR Executive,105251,1 +30401,Female,37,Bachelors,2,40,6,78,63,7.0,0,14,Urban,ML Engineer,44188,0 +30402,Female,55,Bachelors,8,28,64,48,63,4.0,6,71,Urban,Data Analyst,100028,0 +30403,Male,38,Bachelors,15,14,54,30,62,6.0,5,10,Rural,ML Engineer,57384,0 +30404,Male,42,Diploma,16,53,66,48,51,8.0,4,62,Semi-Urban,ML Engineer,67077,0 +30405,Female,34,Masters,19,60,68,92,34,0.0,1,4,Urban,Software Engineer,102545,0 +30406,Male,49,Bachelors,12,2,73,22,78,4.0,1,62,Urban,HR Executive,54041,0 +30407,Male,27,Masters,19,68,52,41,16,9.0,3,53,Semi-Urban,Software Engineer,29068,0 +30408,Male,49,PhD,15,8,27,85,3,5.0,2,55,Urban,ML Engineer,96511,0 +30409,Female,40,Masters,17,45,15,55,99,2.0,3,37,Urban,ML Engineer,94953,0 +30410,Male,45,High School,16,65,40,47,77,4.0,7,25,Semi-Urban,HR Executive,96052,0 +30411,Male,56,Masters,16,4,67,15,23,9.0,3,64,Semi-Urban,HR Executive,22566,0 +30412,Male,33,High School,3,99,29,79,2,2.0,6,93,Urban,HR Executive,36398,1 +30413,Female,58,High School,13,9,69,94,96,9.0,0,93,Urban,HR Executive,70867,1 +30414,Female,29,High School,15,67,71,78,53,0.0,2,68,Semi-Urban,Data Analyst,101627,1 +30415,Male,46,Bachelors,1,49,45,28,71,7.0,3,90,Urban,ML Engineer,30672,0 +30416,Male,38,Masters,11,94,20,85,5,2.0,5,83,Semi-Urban,Data Analyst,42123,1 +30417,Female,30,Diploma,6,78,24,59,0,6.0,1,21,Urban,Software Engineer,95203,0 +30418,Female,38,Bachelors,17,61,15,36,73,6.0,3,47,Semi-Urban,Software Engineer,84972,0 +30419,Female,44,Bachelors,13,11,8,93,55,5.0,7,17,Urban,Data Analyst,79174,0 +30420,Female,27,Diploma,18,39,65,76,46,1.0,7,17,Urban,Manager,145292,0 +30421,Female,39,PhD,13,20,96,38,59,2.0,2,83,Urban,Software Engineer,79160,0 +30422,Male,42,Masters,5,98,89,97,24,2.0,4,88,Urban,Software Engineer,100085,1 +30423,Male,33,Bachelors,2,48,48,81,61,6.0,7,5,Urban,HR Executive,22943,0 +30424,Female,21,PhD,10,23,49,51,54,2.0,2,15,Rural,Manager,141662,0 +30425,Female,23,Masters,10,95,28,95,24,0.0,5,71,Urban,Manager,45502,1 +30426,Male,22,High School,8,57,87,91,88,5.0,3,25,Urban,Software Engineer,26307,1 +30427,Other,34,Masters,2,37,54,35,9,7.0,4,88,Urban,ML Engineer,36802,0 +30428,Female,36,Masters,0,13,10,70,90,8.0,2,17,Urban,Data Analyst,71685,0 +30429,Female,30,Diploma,10,39,70,1,18,6.0,3,71,Urban,ML Engineer,107230,0 +30430,Male,32,Diploma,17,56,85,91,13,7.0,7,81,Urban,Data Analyst,122790,1 +30431,Male,22,Diploma,8,1,16,4,83,3.0,7,37,Rural,Manager,34680,0 +30432,Female,23,Bachelors,16,63,42,58,83,9.0,4,41,Urban,HR Executive,62094,0 +30433,Male,57,Masters,18,97,14,47,20,6.0,6,30,Urban,HR Executive,135435,0 +30434,Male,45,Masters,1,12,96,7,71,6.0,5,64,Urban,Software Engineer,71515,0 +30435,Female,54,Diploma,12,60,63,22,49,2.0,4,7,Urban,Data Analyst,134736,0 +30436,Female,54,Bachelors,1,41,56,26,31,1.0,3,76,Rural,HR Executive,134445,0 +30437,Male,43,Masters,10,53,88,29,98,4.0,1,24,Urban,Data Analyst,38944,0 +30438,Female,54,Bachelors,3,2,98,28,65,2.0,6,61,Urban,ML Engineer,52600,0 +30439,Male,26,Bachelors,16,2,88,41,2,0.0,4,44,Urban,HR Executive,70431,0 +30440,Male,27,Diploma,13,21,60,46,42,4.0,0,96,Rural,HR Executive,41181,0 +30441,Female,49,Bachelors,13,31,35,13,59,1.0,5,77,Urban,HR Executive,28850,0 +30442,Female,44,Bachelors,6,29,23,97,50,8.0,2,77,Urban,Software Engineer,35286,0 +30443,Male,24,Bachelors,18,96,72,93,46,4.0,3,29,Rural,Data Analyst,49493,1 +30444,Male,57,Bachelors,19,47,2,77,82,3.0,2,43,Urban,Data Analyst,98836,0 +30445,Male,45,Diploma,18,79,35,51,55,8.0,1,81,Semi-Urban,ML Engineer,139459,1 +30446,Other,23,Bachelors,1,15,52,58,85,1.0,7,82,Rural,Data Analyst,102422,0 +30447,Female,40,Masters,5,14,56,75,50,1.0,1,30,Urban,ML Engineer,63538,0 +30448,Male,24,Bachelors,7,8,86,54,17,9.0,4,78,Urban,Data Analyst,107899,0 +30449,Male,52,Diploma,14,86,96,73,79,3.0,6,38,Rural,ML Engineer,69924,1 +30450,Male,43,Diploma,0,34,59,80,21,6.0,6,63,Urban,Data Analyst,118463,1 +30451,Female,35,Diploma,16,57,30,76,25,5.0,6,93,Urban,Software Engineer,49282,1 +30452,Female,35,Masters,11,32,82,59,94,5.0,4,19,Urban,Manager,118136,0 +30453,Male,22,Bachelors,15,41,50,88,1,9.0,1,42,Urban,Data Analyst,33010,0 +30454,Other,33,Diploma,19,58,9,10,40,4.0,5,20,Rural,Data Analyst,38857,0 +30455,Male,50,Bachelors,1,11,1,22,82,2.0,1,78,Rural,Data Analyst,100539,0 +30456,Male,32,Bachelors,7,38,48,29,77,0.0,0,45,Urban,Manager,72516,0 +30457,Male,35,Bachelors,7,54,75,25,22,4.0,4,23,Urban,Software Engineer,139547,0 +30458,Male,33,Masters,7,18,96,10,81,0.0,3,15,Urban,ML Engineer,23647,0 +30459,Female,21,High School,12,76,41,63,70,8.0,4,92,Urban,Data Analyst,112333,1 +30460,Female,50,Bachelors,4,51,54,53,33,5.0,2,2,Rural,Data Analyst,70493,0 +30461,Male,27,Bachelors,16,48,38,58,20,7.0,3,91,Semi-Urban,HR Executive,111417,1 +30462,Male,27,Masters,10,77,46,27,65,2.0,7,3,Semi-Urban,HR Executive,112930,0 +30463,Male,36,High School,10,39,66,99,3,1.0,6,1,Urban,Data Analyst,100022,0 +30464,Male,37,Masters,15,20,19,6,36,4.0,5,76,Semi-Urban,Data Analyst,53676,0 +30465,Female,32,Bachelors,13,64,95,99,87,0.0,7,76,Rural,Data Analyst,102984,1 +30466,Female,55,Diploma,2,73,61,4,68,8.0,6,43,Rural,Manager,79919,0 +30467,Male,35,Bachelors,14,36,5,14,39,9.0,6,77,Semi-Urban,ML Engineer,119476,0 +30468,Male,42,Diploma,5,17,32,74,17,9.0,2,23,Urban,Data Analyst,147768,0 +30469,Male,48,High School,3,11,27,79,52,9.0,4,67,Rural,Software Engineer,29921,0 +30470,Female,47,Bachelors,2,35,78,51,39,7.0,3,29,Rural,ML Engineer,106666,0 +30471,Male,52,High School,15,99,65,9,30,0.0,0,12,Semi-Urban,ML Engineer,53968,0 +30472,Male,57,Bachelors,9,37,48,98,73,4.0,4,25,Rural,ML Engineer,116266,0 +30473,Male,46,Bachelors,14,20,76,94,20,5.0,2,53,Urban,Software Engineer,120879,1 +30474,Male,26,Masters,13,93,73,65,3,4.0,1,93,Urban,HR Executive,41874,1 +30475,Male,32,Diploma,7,17,15,60,42,7.0,7,46,Urban,Software Engineer,116415,0 +30476,Female,53,Diploma,11,70,79,74,72,3.0,2,58,Rural,Data Analyst,61479,1 +30477,Other,47,Bachelors,4,48,87,27,16,2.0,5,90,Semi-Urban,HR Executive,134800,1 +30478,Male,50,Masters,18,39,34,47,93,4.0,1,64,Rural,HR Executive,130381,0 +30479,Male,29,Diploma,10,67,88,96,60,5.0,7,92,Semi-Urban,Manager,60035,1 +30480,Female,27,High School,5,97,77,10,84,8.0,1,84,Semi-Urban,Manager,43145,1 +30481,Female,49,PhD,5,35,34,30,67,1.0,7,13,Urban,Data Analyst,117776,0 +30482,Male,42,Masters,0,48,90,86,56,9.0,7,92,Urban,Manager,24106,1 +30483,Female,54,Bachelors,17,74,26,68,70,5.0,1,18,Semi-Urban,HR Executive,86088,0 +30484,Female,29,High School,11,38,9,23,89,9.0,3,47,Urban,ML Engineer,26187,0 +30485,Male,56,Diploma,8,4,73,65,66,9.0,7,8,Urban,ML Engineer,20231,0 +30486,Male,29,Bachelors,12,33,18,18,21,8.0,6,36,Urban,Software Engineer,53075,0 +30487,Female,25,Bachelors,17,67,10,82,18,6.0,6,32,Urban,ML Engineer,138484,0 +30488,Female,48,Bachelors,16,68,48,87,66,4.0,4,45,Urban,Data Analyst,113163,1 +30489,Male,29,Masters,12,58,70,23,2,8.0,1,13,Semi-Urban,HR Executive,40163,0 +30490,Male,29,Diploma,4,48,73,32,19,3.0,3,43,Urban,Software Engineer,136663,0 +30491,Male,53,Masters,18,19,35,20,2,5.0,0,98,Urban,Software Engineer,115115,0 +30492,Female,58,High School,8,36,49,72,36,8.0,6,99,Rural,Manager,32999,1 +30493,Male,59,Diploma,0,35,19,43,34,7.0,6,44,Urban,Data Analyst,88783,0 +30494,Male,25,Bachelors,3,54,45,92,54,5.0,7,8,Urban,ML Engineer,28357,0 +30495,Female,58,Diploma,19,4,60,38,3,8.0,0,17,Urban,Data Analyst,118075,0 +30496,Male,31,Diploma,1,78,11,96,90,5.0,3,55,Semi-Urban,HR Executive,22767,1 +30497,Female,57,Bachelors,16,78,9,68,91,4.0,3,57,Urban,Data Analyst,80517,0 +30498,Male,28,Bachelors,0,61,3,6,82,0.0,5,9,Rural,HR Executive,149815,0 +30499,Male,49,Masters,8,65,82,67,46,5.0,4,62,Rural,ML Engineer,90959,1 +30500,Male,31,PhD,10,10,39,30,40,6.0,7,51,Rural,HR Executive,115163,0 +30501,Other,49,High School,12,74,13,40,40,4.0,2,58,Semi-Urban,ML Engineer,39730,0 +30502,Female,57,High School,16,49,12,62,7,5.0,7,91,Urban,ML Engineer,66758,0 +30503,Male,33,High School,4,47,9,10,35,7.0,3,17,Urban,ML Engineer,102732,0 +30504,Other,51,PhD,13,66,15,47,85,3.0,2,31,Rural,HR Executive,72595,0 +30505,Female,22,Bachelors,17,90,10,40,5,2.0,1,35,Semi-Urban,Data Analyst,51020,0 +30506,Male,27,Bachelors,14,78,85,26,51,3.0,6,2,Urban,HR Executive,32161,0 +30507,Male,45,Bachelors,18,34,31,37,25,4.0,0,54,Urban,HR Executive,82514,0 +30508,Male,33,Bachelors,6,28,45,49,32,5.0,7,32,Urban,ML Engineer,125884,0 +30509,Female,48,Masters,3,50,14,10,73,7.0,5,65,Urban,Data Analyst,89947,0 +30510,Female,42,Diploma,11,25,94,53,71,4.0,4,98,Semi-Urban,ML Engineer,134097,1 +30511,Male,44,Masters,15,31,97,14,98,1.0,2,59,Semi-Urban,Manager,59035,0 +30512,Male,21,Masters,2,28,22,26,29,6.0,7,14,Urban,HR Executive,118558,0 +30513,Male,51,Bachelors,18,5,3,62,56,1.0,6,1,Urban,HR Executive,108992,0 +30514,Male,56,High School,10,19,91,83,14,4.0,5,67,Urban,Data Analyst,144865,1 +30515,Male,52,Diploma,6,31,4,97,5,1.0,1,38,Rural,Software Engineer,122457,0 +30516,Male,38,Bachelors,7,30,19,64,0,7.0,7,92,Urban,Software Engineer,21733,0 +30517,Male,46,High School,7,18,47,27,9,6.0,2,55,Semi-Urban,HR Executive,84786,0 +30518,Female,44,High School,8,9,63,71,55,5.0,4,44,Semi-Urban,HR Executive,71567,0 +30519,Male,38,Bachelors,8,49,45,46,24,1.0,3,99,Urban,Manager,64353,1 +30520,Male,59,Diploma,6,37,27,72,34,8.0,4,37,Semi-Urban,HR Executive,139203,0 +30521,Male,22,Masters,1,21,8,83,5,4.0,4,50,Rural,Software Engineer,47428,0 +30522,Male,45,Diploma,5,4,37,17,23,7.0,2,3,Semi-Urban,Data Analyst,120524,0 +30523,Female,33,Bachelors,19,36,32,25,20,9.0,1,87,Urban,Software Engineer,109806,0 +30524,Male,36,Bachelors,5,34,74,51,40,1.0,5,6,Semi-Urban,Software Engineer,113764,0 +30525,Male,32,Diploma,17,1,12,14,49,2.0,1,73,Urban,Software Engineer,26585,0 +30526,Male,50,Bachelors,5,86,60,94,72,2.0,6,93,Urban,ML Engineer,59493,1 +30527,Male,43,Bachelors,8,72,26,1,32,6.0,0,3,Semi-Urban,Manager,139686,0 +30528,Male,46,Bachelors,2,79,14,10,22,2.0,4,75,Rural,Manager,56959,0 +30529,Female,22,Masters,15,85,31,36,46,9.0,7,97,Urban,ML Engineer,80610,1 +30530,Male,24,PhD,13,24,57,27,0,5.0,6,97,Semi-Urban,ML Engineer,132850,0 +30531,Female,28,Bachelors,0,17,21,48,91,1.0,1,34,Urban,ML Engineer,110401,0 +30532,Male,48,Diploma,16,80,71,77,49,7.0,6,94,Rural,HR Executive,24183,1 +30533,Male,29,Masters,6,12,58,70,62,4.0,7,66,Urban,Software Engineer,117309,0 +30534,Male,55,Bachelors,14,40,47,12,98,6.0,4,73,Urban,ML Engineer,82890,0 +30535,Other,27,Masters,10,25,46,85,29,5.0,5,85,Urban,Manager,126513,1 +30536,Male,56,High School,15,10,97,34,21,4.0,0,4,Urban,ML Engineer,43272,0 +30537,Male,57,Bachelors,14,11,85,12,85,0.0,2,27,Semi-Urban,HR Executive,115938,0 +30538,Male,54,High School,6,18,29,1,76,7.0,1,29,Urban,Data Analyst,69565,0 +30539,Female,36,Masters,14,2,31,42,64,8.0,6,59,Urban,Software Engineer,51201,0 +30540,Male,44,Masters,4,94,47,61,87,7.0,5,98,Semi-Urban,HR Executive,33260,1 +30541,Female,40,Bachelors,18,7,28,70,82,0.0,5,78,Urban,Manager,75500,0 +30542,Female,27,Masters,0,8,90,50,69,3.0,0,94,Semi-Urban,Manager,36149,1 +30543,Female,26,Diploma,10,54,0,30,83,7.0,6,71,Urban,Data Analyst,145879,0 +30544,Male,21,Bachelors,7,17,30,1,28,8.0,5,39,Rural,Manager,40048,0 +30545,Female,47,Bachelors,6,4,97,89,22,2.0,6,60,Rural,Data Analyst,74039,1 +30546,Male,54,Bachelors,4,81,91,44,83,1.0,6,40,Semi-Urban,Software Engineer,105649,1 +30547,Male,47,Masters,18,36,28,9,78,3.0,2,3,Urban,Software Engineer,65768,0 +30548,Female,36,Diploma,10,95,9,21,52,0.0,4,70,Urban,HR Executive,37070,0 +30549,Male,59,Bachelors,11,92,96,14,94,2.0,4,32,Semi-Urban,Software Engineer,61968,0 +30550,Female,34,Bachelors,12,51,87,31,79,3.0,0,86,Semi-Urban,Data Analyst,143908,1 +30551,Male,37,Diploma,18,29,14,33,72,3.0,5,56,Urban,HR Executive,94753,0 +30552,Other,42,Bachelors,19,66,72,35,99,0.0,5,29,Rural,Data Analyst,137480,0 +30553,Male,25,Masters,15,97,0,54,19,4.0,0,36,Urban,Manager,79307,0 +30554,Female,45,Diploma,4,15,18,51,10,5.0,3,6,Urban,ML Engineer,84110,0 +30555,Male,39,Masters,4,63,88,80,9,6.0,6,49,Rural,HR Executive,62138,1 +30556,Male,26,Masters,0,94,60,46,29,6.0,4,21,Urban,Data Analyst,43199,0 +30557,Female,26,Bachelors,14,75,63,53,2,0.0,3,13,Urban,Software Engineer,126835,0 +30558,Female,45,PhD,1,14,17,63,40,7.0,4,6,Semi-Urban,Manager,132082,0 +30559,Male,41,Bachelors,0,49,33,29,78,0.0,5,23,Semi-Urban,HR Executive,140091,0 +30560,Male,57,Bachelors,11,29,74,53,95,4.0,5,16,Urban,ML Engineer,96466,0 +30561,Male,54,Bachelors,17,7,51,76,5,4.0,2,69,Semi-Urban,ML Engineer,141747,0 +30562,Male,25,Bachelors,5,56,58,35,5,6.0,4,62,Rural,ML Engineer,52565,0 +30563,Male,40,Bachelors,17,84,53,63,41,1.0,2,14,Semi-Urban,Software Engineer,76930,0 +30564,Female,42,High School,6,40,10,69,75,6.0,7,89,Urban,Manager,87929,0 +30565,Male,26,Diploma,15,20,12,7,57,3.0,1,53,Semi-Urban,HR Executive,114724,0 +30566,Male,28,Masters,19,84,4,70,6,7.0,4,54,Urban,Data Analyst,40886,0 +30567,Other,49,High School,8,25,50,32,53,3.0,6,99,Urban,Data Analyst,27785,0 +30568,Male,44,Bachelors,2,49,48,17,81,3.0,1,42,Urban,ML Engineer,107300,0 +30569,Male,43,Bachelors,0,5,72,63,1,9.0,0,64,Urban,ML Engineer,70947,0 +30570,Female,21,Masters,10,71,43,20,88,6.0,6,78,Urban,Software Engineer,100848,0 +30571,Female,40,High School,4,36,93,65,12,3.0,6,99,Urban,Data Analyst,21323,1 +30572,Female,31,Masters,7,62,40,84,85,5.0,0,75,Semi-Urban,Software Engineer,116579,1 +30573,Female,34,Bachelors,15,68,46,57,75,2.0,5,68,Urban,Software Engineer,24877,0 +30574,Male,59,PhD,16,33,95,60,73,5.0,4,68,Urban,Software Engineer,102219,1 +30575,Male,49,PhD,8,25,65,68,37,2.0,3,57,Semi-Urban,Manager,42753,0 +30576,Female,32,PhD,14,72,70,80,11,9.0,3,34,Semi-Urban,Software Engineer,36566,1 +30577,Male,44,Bachelors,3,81,48,75,1,4.0,1,91,Urban,Software Engineer,30268,1 +30578,Male,28,PhD,0,7,81,4,25,7.0,1,33,Rural,Software Engineer,34932,0 +30579,Female,55,Bachelors,2,59,71,46,20,0.0,1,10,Urban,HR Executive,51989,0 +30580,Female,53,Masters,5,54,30,43,21,1.0,1,4,Urban,Software Engineer,79335,0 +30581,Male,56,Masters,17,39,64,33,48,8.0,4,36,Urban,Software Engineer,84600,0 +30582,Female,22,Diploma,18,3,82,76,11,2.0,0,44,Urban,HR Executive,138422,0 +30583,Female,31,Masters,11,49,0,28,97,6.0,0,93,Urban,ML Engineer,138208,0 +30584,Other,39,Bachelors,4,90,42,48,89,2.0,2,36,Urban,Manager,134937,0 +30585,Female,57,High School,15,95,80,26,23,1.0,7,60,Rural,Data Analyst,138972,1 +30586,Male,30,Bachelors,16,99,3,23,24,0.0,6,75,Semi-Urban,Software Engineer,31408,0 +30587,Female,30,Diploma,13,70,76,12,55,1.0,5,71,Rural,Manager,35711,0 +30588,Female,51,Diploma,19,32,50,61,88,6.0,4,7,Semi-Urban,Manager,66900,0 +30589,Female,58,Masters,1,6,18,95,2,9.0,7,23,Semi-Urban,ML Engineer,115858,0 +30590,Female,59,Bachelors,14,44,73,91,38,8.0,0,27,Semi-Urban,Software Engineer,138847,0 +30591,Male,28,Masters,9,52,4,74,24,3.0,2,44,Semi-Urban,Data Analyst,28575,0 +30592,Male,50,Masters,16,36,27,88,79,4.0,4,57,Urban,Manager,128622,0 +30593,Male,39,Bachelors,16,59,68,14,64,8.0,1,31,Urban,ML Engineer,35620,0 +30594,Female,25,Bachelors,13,53,68,99,28,0.0,7,69,Urban,Data Analyst,62858,1 +30595,Female,42,Bachelors,4,28,85,31,85,2.0,1,94,Urban,HR Executive,52807,0 +30596,Male,39,Masters,0,58,96,8,43,5.0,5,33,Rural,Data Analyst,116500,0 +30597,Male,50,Diploma,1,32,54,39,51,4.0,3,4,Urban,Data Analyst,45549,0 +30598,Female,55,Bachelors,6,31,40,9,17,1.0,0,19,Rural,Software Engineer,28720,0 +30599,Male,26,PhD,10,46,87,97,50,0.0,0,33,Semi-Urban,Software Engineer,114186,1 +30600,Male,38,Bachelors,7,78,43,25,14,6.0,2,30,Urban,HR Executive,88780,0 +30601,Male,56,Diploma,17,24,12,22,91,2.0,2,92,Urban,Data Analyst,148491,0 +30602,Female,54,High School,14,79,34,36,52,5.0,6,38,Rural,HR Executive,85212,0 +30603,Female,53,Masters,17,53,93,92,63,0.0,3,26,Urban,HR Executive,68909,1 +30604,Male,58,Bachelors,3,71,35,71,34,4.0,6,17,Urban,Data Analyst,146323,0 +30605,Male,25,High School,1,61,78,59,42,5.0,4,72,Rural,HR Executive,41518,1 +30606,Female,24,Diploma,7,91,5,8,47,9.0,5,46,Semi-Urban,Data Analyst,27963,0 +30607,Female,40,Diploma,11,9,59,36,42,8.0,6,16,Rural,Software Engineer,113003,0 +30608,Female,32,Bachelors,19,77,79,3,93,9.0,5,18,Urban,Data Analyst,26596,0 +30609,Male,34,Masters,2,52,60,61,7,0.0,6,73,Semi-Urban,Manager,111970,1 +30610,Male,49,Bachelors,5,70,88,71,32,4.0,4,89,Urban,Data Analyst,71384,1 +30611,Female,26,Diploma,3,68,23,51,97,2.0,6,70,Rural,HR Executive,30456,0 +30612,Male,37,Masters,7,31,65,49,62,7.0,2,3,Urban,Software Engineer,46620,0 +30613,Male,36,Diploma,17,89,37,77,91,1.0,7,41,Semi-Urban,Software Engineer,113295,1 +30614,Female,51,Bachelors,11,59,15,55,74,5.0,5,97,Urban,Manager,65006,0 +30615,Other,41,Bachelors,18,98,80,88,14,3.0,0,84,Semi-Urban,Data Analyst,27523,1 +30616,Female,42,Masters,17,9,30,53,54,4.0,0,93,Semi-Urban,ML Engineer,60992,0 +30617,Female,33,High School,3,32,23,74,35,3.0,5,76,Urban,Software Engineer,39535,0 +30618,Male,47,Masters,0,27,48,90,84,8.0,2,13,Semi-Urban,Data Analyst,37908,0 +30619,Male,27,Bachelors,11,49,2,96,48,1.0,4,17,Urban,ML Engineer,100013,0 +30620,Male,44,Diploma,11,52,31,79,60,5.0,4,71,Urban,Software Engineer,26137,0 +30621,Male,40,Bachelors,9,26,81,69,38,3.0,7,86,Rural,ML Engineer,78198,1 +30622,Male,48,Bachelors,18,67,60,28,68,9.0,2,88,Urban,Data Analyst,93793,1 +30623,Female,30,Diploma,16,7,64,16,33,2.0,7,6,Rural,Software Engineer,91142,0 +30624,Male,37,Bachelors,18,91,60,34,18,5.0,4,0,Rural,Software Engineer,74332,0 +30625,Male,38,High School,7,90,9,48,90,7.0,6,15,Semi-Urban,HR Executive,50807,0 +30626,Male,42,Diploma,12,80,57,92,78,4.0,1,94,Urban,HR Executive,94710,1 +30627,Female,58,High School,1,70,77,4,32,7.0,5,68,Urban,Manager,54536,0 +30628,Male,37,Bachelors,7,28,62,16,19,7.0,5,24,Urban,ML Engineer,21314,0 +30629,Female,22,Masters,8,85,28,87,34,2.0,4,69,Urban,HR Executive,116976,1 +30630,Male,43,Diploma,12,10,2,37,70,8.0,0,45,Urban,HR Executive,123147,0 +30631,Female,52,Bachelors,7,76,89,78,87,1.0,7,98,Urban,Manager,38658,1 +30632,Female,33,Masters,16,55,75,73,22,0.0,5,22,Urban,Manager,144000,0 +30633,Male,22,Bachelors,16,92,80,43,26,0.0,1,50,Semi-Urban,ML Engineer,78401,1 +30634,Female,21,Bachelors,14,9,29,80,46,6.0,3,70,Semi-Urban,HR Executive,96074,0 +30635,Male,42,Masters,10,51,66,56,67,5.0,2,75,Urban,Manager,63881,1 +30636,Female,58,Diploma,17,28,55,8,58,2.0,2,27,Semi-Urban,Data Analyst,86357,0 +30637,Female,26,Bachelors,14,80,78,35,11,2.0,0,61,Urban,Software Engineer,133846,1 +30638,Male,26,Bachelors,7,98,0,17,79,0.0,1,4,Semi-Urban,Data Analyst,146131,0 +30639,Male,57,Diploma,8,64,95,96,23,1.0,2,75,Urban,ML Engineer,118239,1 +30640,Male,30,Bachelors,2,85,86,71,20,9.0,1,76,Urban,Software Engineer,45779,1 +30641,Other,41,Bachelors,3,23,34,70,13,1.0,6,4,Urban,Software Engineer,95660,0 +30642,Male,28,High School,13,96,10,63,7,2.0,7,88,Semi-Urban,ML Engineer,85726,1 +30643,Female,30,Diploma,7,10,80,60,89,5.0,5,84,Rural,Software Engineer,133979,0 +30644,Female,21,Bachelors,10,97,81,85,94,0.0,4,86,Rural,Manager,87067,1 +30645,Female,35,Bachelors,6,31,29,79,80,7.0,7,58,Urban,Manager,143332,0 +30646,Male,25,Diploma,14,49,88,92,52,9.0,6,75,Urban,HR Executive,97332,1 +30647,Male,52,Bachelors,6,36,19,9,66,7.0,5,79,Urban,Data Analyst,108002,0 +30648,Male,39,Masters,19,6,27,58,32,4.0,1,66,Urban,ML Engineer,110541,0 +30649,Male,24,Diploma,0,67,40,45,14,4.0,6,55,Urban,Software Engineer,124638,0 +30650,Male,55,Bachelors,13,29,70,38,82,9.0,1,57,Urban,HR Executive,38932,0 +30651,Male,48,Bachelors,1,5,23,64,85,9.0,1,94,Rural,ML Engineer,52456,0 +30652,Male,57,High School,12,27,15,10,1,1.0,7,26,Semi-Urban,HR Executive,46850,0 +30653,Male,29,Bachelors,16,16,24,15,98,7.0,1,66,Rural,ML Engineer,76307,0 +30654,Male,47,High School,13,60,66,20,38,8.0,6,79,Rural,HR Executive,47769,0 +30655,Male,24,Masters,11,88,85,93,5,5.0,7,88,Urban,Manager,34295,1 +30656,Male,48,Bachelors,7,22,8,99,0,2.0,2,19,Urban,Data Analyst,46565,0 +30657,Male,53,Bachelors,7,30,88,95,21,4.0,6,14,Urban,Manager,44911,0 +30658,Male,33,Diploma,11,96,97,5,69,2.0,3,72,Urban,Software Engineer,130073,1 +30659,Female,25,Bachelors,14,80,34,66,24,7.0,4,68,Semi-Urban,ML Engineer,23275,1 +30660,Male,42,PhD,15,38,38,51,20,6.0,6,20,Semi-Urban,ML Engineer,97485,0 +30661,Female,38,PhD,7,48,78,41,86,8.0,0,10,Semi-Urban,Data Analyst,148825,0 +30662,Male,44,Diploma,4,24,39,19,30,5.0,2,18,Urban,Data Analyst,97342,0 +30663,Female,33,Bachelors,2,9,3,46,57,0.0,7,63,Urban,Software Engineer,26418,0 +30664,Female,24,Bachelors,6,5,91,68,13,0.0,7,95,Urban,HR Executive,58598,1 +30665,Female,23,Diploma,9,87,5,23,85,2.0,7,46,Urban,Manager,63951,0 +30666,Female,31,Masters,15,57,18,77,63,0.0,7,8,Urban,Software Engineer,21627,0 +30667,Male,35,Bachelors,18,95,17,21,22,1.0,3,42,Semi-Urban,HR Executive,124828,0 +30668,Male,40,Diploma,12,48,92,56,99,2.0,7,63,Rural,Software Engineer,23986,1 +30669,Male,31,Masters,3,65,98,51,0,2.0,6,59,Rural,Software Engineer,45017,1 +30670,Male,57,High School,13,21,56,26,21,0.0,6,56,Rural,Software Engineer,54001,0 +30671,Male,29,Bachelors,13,10,58,65,6,9.0,0,1,Urban,ML Engineer,99848,0 +30672,Male,54,Diploma,9,2,38,38,6,1.0,4,39,Urban,Manager,144483,0 +30673,Male,23,Bachelors,16,99,91,73,46,0.0,5,17,Rural,Data Analyst,105324,1 +30674,Male,28,Diploma,2,8,72,85,39,7.0,5,88,Urban,Data Analyst,43017,1 +30675,Male,33,Bachelors,16,81,3,81,74,6.0,5,68,Semi-Urban,Data Analyst,48634,0 +30676,Female,58,Diploma,1,0,38,95,46,3.0,2,78,Semi-Urban,ML Engineer,50640,0 +30677,Other,34,Diploma,9,98,16,83,58,2.0,6,33,Semi-Urban,Manager,55381,0 +30678,Male,56,High School,5,54,49,96,39,9.0,6,85,Semi-Urban,HR Executive,100408,1 +30679,Male,55,Masters,17,3,73,13,64,6.0,3,21,Semi-Urban,HR Executive,34892,0 +30680,Male,54,Masters,6,79,70,10,7,2.0,7,99,Urban,Data Analyst,23638,1 +30681,Female,25,PhD,4,92,43,23,5,2.0,7,53,Semi-Urban,Software Engineer,88209,0 +30682,Male,34,Masters,8,28,75,3,44,7.0,6,95,Urban,ML Engineer,110115,0 +30683,Other,29,Bachelors,12,49,7,20,54,3.0,3,92,Urban,Data Analyst,31442,0 +30684,Male,40,PhD,13,0,99,3,24,4.0,6,44,Urban,Data Analyst,111016,0 +30685,Male,21,Bachelors,10,68,72,37,25,6.0,0,50,Rural,Software Engineer,135738,0 +30686,Other,40,Bachelors,12,48,51,58,72,1.0,5,14,Urban,Software Engineer,41868,0 +30687,Female,49,Bachelors,5,99,97,0,55,2.0,6,86,Urban,Software Engineer,58171,1 +30688,Female,53,Bachelors,14,16,97,6,90,9.0,7,50,Urban,Data Analyst,51607,0 +30689,Male,51,Bachelors,15,58,16,59,74,9.0,6,15,Urban,Data Analyst,66340,0 +30690,Female,35,Bachelors,19,62,53,30,86,3.0,2,93,Urban,ML Engineer,95662,0 +30691,Male,34,Diploma,0,95,54,45,37,5.0,3,4,Urban,Data Analyst,140227,0 +30692,Male,35,Bachelors,18,76,97,22,81,6.0,6,31,Semi-Urban,HR Executive,50867,0 +30693,Male,28,Bachelors,5,60,29,41,66,8.0,4,64,Urban,Data Analyst,128939,0 +30694,Male,28,High School,19,35,81,43,19,4.0,4,57,Urban,HR Executive,65761,0 +30695,Female,50,Diploma,4,44,32,31,2,5.0,6,32,Urban,Manager,140560,0 +30696,Male,36,Masters,15,17,66,5,89,2.0,2,53,Semi-Urban,Software Engineer,116464,0 +30697,Female,29,PhD,3,21,61,53,45,1.0,7,13,Urban,Data Analyst,61328,0 +30698,Male,55,Masters,5,26,73,64,80,1.0,6,63,Urban,ML Engineer,106157,0 +30699,Male,21,Bachelors,19,22,89,79,79,7.0,0,46,Urban,HR Executive,74436,1 +30700,Female,50,High School,17,1,87,85,52,8.0,0,6,Semi-Urban,Manager,94364,0 +30701,Female,57,PhD,3,56,52,44,92,5.0,7,49,Urban,Manager,37914,0 +30702,Other,57,Bachelors,3,98,40,99,51,9.0,0,34,Semi-Urban,Software Engineer,140206,1 +30703,Female,40,High School,2,66,37,74,42,0.0,5,87,Urban,ML Engineer,83051,1 +30704,Male,45,Bachelors,7,61,86,42,34,7.0,3,8,Semi-Urban,HR Executive,23048,0 +30705,Other,23,Bachelors,7,26,55,42,11,2.0,4,82,Urban,Manager,87444,0 +30706,Female,54,PhD,18,0,7,60,99,5.0,0,49,Urban,HR Executive,27566,0 +30707,Male,27,High School,9,69,12,36,91,9.0,5,91,Urban,Software Engineer,137145,0 +30708,Male,46,PhD,4,61,8,81,45,1.0,1,45,Semi-Urban,Software Engineer,53405,0 +30709,Male,23,PhD,15,58,2,22,82,8.0,4,71,Semi-Urban,HR Executive,80740,0 +30710,Male,40,Diploma,7,66,65,55,74,1.0,1,64,Urban,HR Executive,139060,1 +30711,Other,36,Bachelors,17,25,28,5,6,0.0,3,99,Semi-Urban,Manager,111612,0 +30712,Male,29,Masters,6,84,62,76,25,5.0,5,40,Urban,Manager,27203,1 +30713,Female,29,Masters,12,77,22,32,49,9.0,5,7,Urban,Data Analyst,100646,0 +30714,Male,52,Bachelors,18,95,30,84,89,1.0,1,44,Rural,Manager,59731,1 +30715,Male,59,Bachelors,11,40,70,21,53,7.0,4,59,Urban,Manager,74953,0 +30716,Female,57,High School,12,43,79,28,73,7.0,6,10,Semi-Urban,Data Analyst,38960,0 +30717,Male,34,Masters,10,32,49,80,33,1.0,2,64,Rural,Data Analyst,101480,0 +30718,Male,23,High School,7,22,53,95,79,3.0,5,21,Urban,Software Engineer,127029,0 +30719,Other,52,Bachelors,14,25,49,69,15,3.0,1,91,Urban,Data Analyst,126713,0 +30720,Female,45,Masters,0,46,98,75,31,2.0,2,89,Semi-Urban,Manager,84469,1 +30721,Male,25,Masters,11,56,92,66,30,8.0,0,86,Semi-Urban,Software Engineer,138508,1 +30722,Male,55,Bachelors,8,77,69,0,89,6.0,7,22,Semi-Urban,Software Engineer,25139,0 +30723,Male,44,Masters,6,46,55,59,25,3.0,7,72,Urban,Manager,93385,0 +30724,Female,38,Masters,16,20,50,97,43,0.0,4,1,Urban,HR Executive,74129,0 +30725,Female,41,Bachelors,13,66,26,84,8,6.0,2,92,Rural,Data Analyst,98891,1 +30726,Male,41,Masters,16,60,71,32,98,5.0,2,0,Urban,Data Analyst,77051,0 +30727,Female,37,Bachelors,9,21,53,97,52,8.0,4,6,Urban,Manager,146866,0 +30728,Male,30,Masters,13,25,73,56,11,6.0,0,0,Urban,HR Executive,64482,0 +30729,Male,23,Masters,2,23,22,96,32,6.0,0,18,Rural,HR Executive,37505,0 +30730,Male,23,Bachelors,12,95,66,66,1,8.0,1,74,Semi-Urban,ML Engineer,81691,1 +30731,Male,51,Diploma,17,14,91,3,73,9.0,6,10,Semi-Urban,Manager,133578,0 +30732,Male,24,Bachelors,3,44,63,80,81,7.0,4,68,Urban,ML Engineer,89315,1 +30733,Female,45,Masters,12,26,42,27,84,8.0,4,86,Urban,Data Analyst,92481,0 +30734,Male,39,Bachelors,19,35,72,72,90,0.0,6,31,Semi-Urban,HR Executive,26096,0 +30735,Female,23,High School,8,31,27,66,31,3.0,7,78,Urban,Data Analyst,120409,0 +30736,Female,39,Bachelors,13,91,79,81,30,5.0,7,41,Urban,HR Executive,134873,1 +30737,Female,51,Bachelors,11,31,59,57,51,5.0,1,67,Urban,HR Executive,37639,0 +30738,Male,23,Masters,4,43,23,20,64,6.0,4,66,Urban,Data Analyst,139433,0 +30739,Male,57,Diploma,5,8,54,95,7,2.0,3,97,Urban,Data Analyst,29801,1 +30740,Female,28,Masters,12,8,45,77,91,4.0,7,23,Urban,Software Engineer,148456,0 +30741,Male,51,Masters,10,91,34,2,53,9.0,4,81,Urban,Manager,47889,0 +30742,Female,54,Bachelors,13,30,98,19,82,1.0,4,19,Urban,HR Executive,143347,0 +30743,Male,28,Masters,17,33,68,99,44,1.0,0,71,Urban,Software Engineer,61110,1 +30744,Male,47,Bachelors,0,23,86,82,98,7.0,4,22,Urban,Data Analyst,52915,0 +30745,Female,41,High School,0,94,78,54,98,6.0,6,34,Semi-Urban,ML Engineer,96496,1 +30746,Female,49,Bachelors,13,85,92,58,28,6.0,1,11,Rural,Data Analyst,130770,1 +30747,Male,31,Bachelors,1,75,8,6,34,1.0,2,59,Urban,Software Engineer,78445,0 +30748,Male,58,Bachelors,16,19,56,9,57,1.0,0,9,Urban,Manager,79179,0 +30749,Female,32,Diploma,8,98,65,79,80,1.0,7,28,Semi-Urban,Manager,142456,1 +30750,Male,52,Bachelors,15,47,57,71,26,5.0,3,61,Urban,Data Analyst,130222,1 +30751,Male,57,Bachelors,0,70,71,61,29,9.0,4,40,Urban,Manager,115893,1 +30752,Male,45,High School,7,49,22,97,59,1.0,7,66,Rural,Software Engineer,109849,0 +30753,Male,39,Diploma,16,93,27,55,40,5.0,3,44,Urban,Software Engineer,56647,0 +30754,Male,51,Bachelors,1,33,74,69,72,2.0,6,82,Rural,Data Analyst,70298,1 +30755,Male,57,Bachelors,1,19,70,68,97,5.0,7,70,Urban,HR Executive,55423,0 +30756,Female,21,Masters,17,53,86,62,69,4.0,6,20,Urban,HR Executive,73216,0 +30757,Female,48,Bachelors,13,50,34,13,72,3.0,0,97,Urban,Data Analyst,124820,0 +30758,Other,57,Masters,18,73,83,36,13,9.0,2,48,Urban,HR Executive,66003,0 +30759,Male,52,Bachelors,5,0,57,10,11,3.0,2,87,Semi-Urban,HR Executive,119634,0 +30760,Male,38,Diploma,3,42,85,28,50,3.0,1,26,Semi-Urban,Software Engineer,89800,0 +30761,Other,33,Diploma,11,35,93,1,22,8.0,2,20,Rural,HR Executive,101659,0 +30762,Male,27,Bachelors,19,49,77,79,31,9.0,4,16,Urban,Software Engineer,42052,0 +30763,Female,58,Bachelors,13,70,83,75,45,9.0,6,13,Urban,HR Executive,107391,1 +30764,Male,35,High School,17,11,88,26,3,1.0,4,30,Urban,ML Engineer,96919,0 +30765,Female,51,Diploma,0,5,5,35,94,3.0,7,73,Urban,ML Engineer,72138,0 +30766,Female,56,Diploma,6,77,27,17,57,5.0,7,33,Urban,ML Engineer,51605,0 +30767,Male,39,Bachelors,4,64,6,99,3,2.0,7,32,Semi-Urban,Software Engineer,141628,0 +30768,Male,54,Bachelors,0,12,32,91,89,3.0,6,74,Semi-Urban,ML Engineer,148528,0 +30769,Male,31,Masters,10,76,40,1,40,9.0,0,18,Rural,HR Executive,31544,0 +30770,Male,41,High School,10,68,72,98,49,7.0,5,55,Urban,ML Engineer,69703,1 +30771,Male,29,PhD,6,62,15,23,70,1.0,6,39,Urban,ML Engineer,37623,0 +30772,Female,51,Diploma,16,95,39,46,13,5.0,6,40,Urban,Data Analyst,103053,0 +30773,Male,37,Masters,8,8,82,33,12,5.0,0,99,Urban,Software Engineer,122081,0 +30774,Male,27,Bachelors,16,56,59,76,74,3.0,6,44,Urban,Manager,22280,1 +30775,Male,44,Bachelors,0,73,3,20,86,7.0,2,32,Rural,HR Executive,65604,0 +30776,Male,40,Masters,4,9,65,6,38,8.0,5,93,Urban,HR Executive,38389,0 +30777,Male,38,Bachelors,11,66,69,50,69,1.0,6,99,Urban,ML Engineer,82353,1 +30778,Female,44,Bachelors,10,88,18,23,67,1.0,7,85,Urban,ML Engineer,102953,0 +30779,Female,37,Bachelors,2,2,43,79,0,9.0,5,46,Urban,Software Engineer,129987,0 +30780,Male,29,Bachelors,3,88,32,18,18,8.0,2,13,Urban,ML Engineer,115350,0 +30781,Male,58,Bachelors,9,96,93,71,5,7.0,4,33,Semi-Urban,ML Engineer,24874,1 +30782,Female,52,Bachelors,13,63,90,51,2,6.0,0,31,Urban,ML Engineer,46996,0 +30783,Male,25,Bachelors,10,7,66,74,73,7.0,3,41,Rural,Manager,25645,0 +30784,Male,28,Bachelors,10,41,13,91,53,5.0,2,2,Urban,Data Analyst,72542,0 +30785,Female,59,Masters,17,52,84,9,13,1.0,5,81,Urban,ML Engineer,62813,0 +30786,Male,50,High School,3,61,68,54,18,7.0,7,99,Semi-Urban,HR Executive,47591,1 +30787,Male,42,Diploma,12,87,21,7,30,4.0,6,32,Urban,Data Analyst,59650,0 +30788,Other,48,PhD,8,15,59,88,46,2.0,0,44,Urban,Manager,137300,0 +30789,Male,23,Diploma,15,75,3,32,50,6.0,1,98,Urban,Software Engineer,68055,0 +30790,Female,39,Diploma,19,70,93,2,76,8.0,0,49,Urban,Software Engineer,141326,0 +30791,Male,32,Diploma,13,76,59,37,14,2.0,6,85,Urban,Manager,62540,1 +30792,Female,56,Diploma,12,79,58,83,81,5.0,7,47,Rural,HR Executive,89683,1 +30793,Male,28,High School,19,80,5,10,59,0.0,3,14,Urban,Software Engineer,50070,0 +30794,Male,23,Diploma,13,29,60,71,72,9.0,4,7,Semi-Urban,Manager,118285,0 +30795,Female,25,High School,0,44,37,37,14,7.0,7,40,Semi-Urban,HR Executive,98704,0 +30796,Female,42,Bachelors,19,57,25,49,21,7.0,6,39,Urban,ML Engineer,119736,0 +30797,Male,31,Diploma,2,7,60,37,14,3.0,6,85,Urban,Software Engineer,63412,0 +30798,Female,34,Bachelors,13,26,19,91,99,1.0,7,10,Urban,Manager,99230,0 +30799,Male,35,Masters,14,42,28,27,17,6.0,2,12,Urban,Data Analyst,95530,0 +30800,Female,56,High School,1,94,90,41,87,4.0,6,50,Urban,HR Executive,140869,1 +30801,Female,38,Diploma,13,71,40,46,73,2.0,4,12,Rural,HR Executive,146736,0 +30802,Male,42,PhD,4,45,5,27,45,6.0,6,83,Rural,ML Engineer,129648,0 +30803,Male,21,Bachelors,10,81,92,6,11,9.0,6,95,Urban,Manager,148144,1 +30804,Male,46,Masters,4,4,0,95,93,0.0,2,67,Urban,Manager,44929,0 +30805,Female,46,Diploma,15,84,3,10,59,8.0,7,82,Rural,Data Analyst,107714,0 +30806,Male,23,Bachelors,15,94,31,25,93,3.0,6,46,Semi-Urban,ML Engineer,24811,0 +30807,Female,38,Diploma,18,93,29,6,14,6.0,2,48,Urban,ML Engineer,102467,0 +30808,Male,54,High School,13,20,51,21,36,7.0,3,57,Semi-Urban,Data Analyst,39971,0 +30809,Female,49,High School,7,96,80,0,11,0.0,2,45,Urban,ML Engineer,149747,0 +30810,Female,32,Bachelors,9,87,68,41,18,7.0,6,28,Urban,HR Executive,146734,0 +30811,Female,43,Bachelors,10,86,16,66,5,5.0,7,57,Urban,Data Analyst,102412,0 +30812,Female,36,Diploma,9,85,61,3,65,6.0,6,61,Semi-Urban,HR Executive,32760,0 +30813,Male,39,Masters,2,21,65,82,67,7.0,6,36,Urban,ML Engineer,52373,0 +30814,Male,33,Masters,2,44,78,38,53,1.0,2,83,Urban,HR Executive,100667,1 +30815,Other,33,Masters,3,26,43,2,87,5.0,1,83,Urban,HR Executive,124363,0 +30816,Male,31,High School,11,58,83,66,99,7.0,5,46,Urban,HR Executive,68775,1 +30817,Female,23,Bachelors,5,95,45,41,43,3.0,4,64,Urban,Data Analyst,98290,1 +30818,Female,36,High School,4,45,88,25,38,1.0,6,29,Semi-Urban,HR Executive,35301,0 +30819,Female,52,Diploma,3,87,79,19,40,3.0,3,46,Rural,Manager,48900,0 +30820,Male,51,Bachelors,17,51,63,45,6,8.0,0,65,Rural,ML Engineer,49722,0 +30821,Male,37,Diploma,17,72,92,97,12,6.0,1,38,Urban,Manager,95820,1 +30822,Female,49,Bachelors,15,65,87,22,90,7.0,7,18,Urban,Manager,71334,0 +30823,Male,50,Bachelors,19,77,88,65,87,4.0,5,82,Urban,ML Engineer,62269,1 +30824,Female,56,High School,7,94,57,50,93,5.0,2,4,Semi-Urban,Software Engineer,115075,0 +30825,Male,43,Bachelors,18,87,29,3,49,7.0,7,94,Urban,Data Analyst,113395,0 +30826,Male,51,Masters,6,56,48,75,23,9.0,2,78,Rural,HR Executive,124527,1 +30827,Male,40,Masters,8,7,1,34,19,9.0,4,15,Urban,HR Executive,80696,0 +30828,Female,40,Diploma,16,22,45,55,22,6.0,4,46,Urban,HR Executive,78240,0 +30829,Male,21,Bachelors,0,53,26,62,20,2.0,6,88,Urban,ML Engineer,47952,0 +30830,Male,36,Bachelors,1,90,95,50,73,5.0,0,52,Semi-Urban,HR Executive,72137,1 +30831,Female,45,Bachelors,11,74,29,28,49,1.0,5,92,Urban,HR Executive,78777,0 +30832,Female,52,Bachelors,1,7,12,55,68,3.0,3,33,Urban,ML Engineer,97789,0 +30833,Other,57,High School,0,82,56,69,63,7.0,2,74,Rural,Manager,62700,1 +30834,Male,54,Bachelors,10,30,15,92,49,3.0,0,42,Urban,Manager,118600,0 +30835,Female,29,Bachelors,8,96,31,43,97,8.0,4,16,Urban,Data Analyst,111312,0 +30836,Male,52,PhD,16,52,92,53,20,8.0,6,65,Urban,Software Engineer,49747,1 +30837,Female,34,Bachelors,2,4,34,45,78,2.0,5,29,Urban,Software Engineer,133352,0 +30838,Female,24,High School,9,98,32,35,73,7.0,5,64,Urban,Data Analyst,68385,0 +30839,Male,40,Bachelors,19,7,67,25,23,5.0,2,76,Semi-Urban,Manager,75387,0 +30840,Male,38,Diploma,14,97,16,98,51,6.0,1,31,Semi-Urban,Software Engineer,83937,1 +30841,Female,55,Masters,14,37,53,43,95,0.0,4,68,Urban,HR Executive,123360,0 +30842,Male,41,Bachelors,0,20,97,37,48,3.0,7,15,Semi-Urban,ML Engineer,111570,0 +30843,Female,55,Diploma,3,31,51,14,23,8.0,0,9,Semi-Urban,Software Engineer,79648,0 +30844,Male,42,Masters,15,38,91,21,2,4.0,4,15,Urban,ML Engineer,92060,0 +30845,Female,52,Bachelors,10,70,10,72,52,6.0,1,50,Urban,ML Engineer,127245,0 +30846,Male,24,Bachelors,10,61,65,97,6,1.0,0,88,Semi-Urban,Software Engineer,63781,1 +30847,Male,57,Diploma,18,93,72,36,50,2.0,7,42,Urban,ML Engineer,57075,1 +30848,Male,46,High School,19,92,44,65,72,3.0,1,13,Rural,Data Analyst,68518,0 +30849,Male,36,Masters,19,16,95,22,81,9.0,4,80,Urban,Manager,39268,0 +30850,Male,55,Bachelors,14,15,59,98,25,1.0,2,88,Rural,Manager,99646,1 +30851,Male,36,High School,4,13,21,75,4,7.0,4,91,Urban,Data Analyst,26256,0 +30852,Male,37,Masters,4,68,27,24,64,5.0,6,31,Urban,HR Executive,31537,0 +30853,Female,29,Bachelors,5,32,22,3,18,2.0,1,28,Rural,ML Engineer,131395,0 +30854,Male,35,High School,0,10,96,36,41,2.0,2,74,Urban,Manager,74851,0 +30855,Female,48,Masters,15,13,9,90,32,5.0,0,23,Rural,Manager,41906,0 +30856,Male,42,Diploma,1,25,35,95,34,7.0,1,47,Semi-Urban,Manager,91176,0 +30857,Male,50,Masters,14,79,2,53,77,3.0,5,64,Rural,Data Analyst,140577,0 +30858,Male,30,Bachelors,17,48,16,43,23,0.0,3,34,Semi-Urban,ML Engineer,106526,0 +30859,Female,40,Bachelors,10,31,3,65,37,5.0,4,29,Semi-Urban,Data Analyst,63468,0 +30860,Male,22,High School,6,87,83,2,98,8.0,4,52,Semi-Urban,Software Engineer,122171,0 +30861,Male,26,Bachelors,13,31,49,77,73,7.0,5,7,Rural,HR Executive,108762,0 +30862,Male,56,Bachelors,10,60,68,15,68,7.0,4,98,Rural,Software Engineer,21777,1 +30863,Male,23,Bachelors,8,70,3,15,84,3.0,1,3,Semi-Urban,Data Analyst,69409,0 +30864,Male,59,PhD,6,26,91,36,56,4.0,6,43,Urban,Manager,64363,0 +30865,Male,56,Bachelors,2,41,13,62,43,2.0,7,68,Urban,Manager,42139,0 +30866,Male,50,Bachelors,1,25,18,30,15,9.0,6,71,Urban,Data Analyst,137102,0 +30867,Female,49,Masters,5,62,10,77,96,7.0,7,80,Urban,Manager,145840,0 +30868,Male,55,Diploma,1,92,1,82,56,7.0,1,97,Semi-Urban,Software Engineer,39612,1 +30869,Male,59,Diploma,2,12,72,86,13,3.0,2,3,Urban,Software Engineer,148262,0 +30870,Male,28,Bachelors,4,99,45,36,57,9.0,2,72,Urban,ML Engineer,138055,1 +30871,Male,54,Bachelors,0,74,41,28,2,8.0,6,51,Urban,Software Engineer,26363,0 +30872,Male,25,Diploma,5,22,85,2,38,3.0,2,66,Rural,Data Analyst,28833,0 +30873,Female,54,Masters,14,54,53,39,38,2.0,6,32,Rural,HR Executive,65759,0 +30874,Female,29,Bachelors,6,42,65,29,16,1.0,0,19,Urban,ML Engineer,65985,0 +30875,Male,37,Masters,14,63,88,31,49,6.0,5,80,Urban,Software Engineer,111667,1 +30876,Male,21,PhD,7,42,66,2,48,3.0,0,48,Urban,Data Analyst,49068,0 +30877,Male,57,Diploma,16,22,80,32,54,0.0,6,86,Urban,Manager,23433,0 +30878,Male,57,Masters,12,9,76,67,62,8.0,0,90,Semi-Urban,Software Engineer,57108,1 +30879,Female,48,Bachelors,15,93,4,95,83,3.0,0,54,Urban,Software Engineer,94100,1 +30880,Female,47,Bachelors,13,62,54,40,98,4.0,4,41,Rural,HR Executive,27897,0 +30881,Male,45,Diploma,2,51,95,57,95,6.0,2,18,Semi-Urban,Data Analyst,65557,0 +30882,Other,43,Bachelors,10,1,91,84,32,1.0,1,94,Urban,Software Engineer,69347,1 +30883,Male,26,Diploma,19,79,77,14,75,2.0,2,48,Urban,HR Executive,127129,0 +30884,Male,44,Bachelors,6,49,24,7,83,9.0,1,91,Urban,Manager,125464,0 +30885,Male,31,PhD,18,80,39,70,0,6.0,2,49,Urban,Manager,34559,1 +30886,Male,55,Masters,11,80,34,75,77,4.0,3,33,Urban,Manager,31050,0 +30887,Female,37,Diploma,16,56,6,24,13,4.0,7,14,Urban,Data Analyst,93535,0 +30888,Female,34,Bachelors,3,0,97,28,42,0.0,5,30,Urban,ML Engineer,60427,0 +30889,Female,42,PhD,17,91,77,39,99,5.0,3,95,Urban,ML Engineer,97524,1 +30890,Male,46,Bachelors,14,43,75,43,58,6.0,7,91,Semi-Urban,HR Executive,119495,1 +30891,Female,56,Diploma,7,77,55,85,15,8.0,0,30,Urban,ML Engineer,145021,1 +30892,Female,48,Diploma,15,37,94,51,1,4.0,1,95,Semi-Urban,ML Engineer,131331,1 +30893,Male,54,Diploma,3,72,27,73,87,9.0,2,94,Urban,HR Executive,51081,1 +30894,Male,54,Bachelors,19,10,18,98,36,9.0,5,5,Rural,Software Engineer,145638,0 +30895,Female,30,High School,6,31,51,16,82,7.0,5,64,Semi-Urban,Manager,31813,0 +30896,Female,33,High School,6,50,97,26,91,9.0,5,75,Urban,ML Engineer,126652,1 +30897,Female,55,Diploma,5,42,80,65,29,7.0,5,10,Urban,Software Engineer,26016,0 +30898,Male,41,Bachelors,12,4,55,10,40,8.0,6,83,Urban,HR Executive,41963,0 +30899,Male,41,Bachelors,6,46,78,8,87,6.0,2,65,Urban,Data Analyst,27315,0 +30900,Female,23,Diploma,0,70,82,51,46,4.0,6,23,Urban,ML Engineer,79785,0 +30901,Female,57,Diploma,4,57,8,42,95,3.0,2,22,Rural,Software Engineer,148573,0 +30902,Male,27,Bachelors,9,14,48,91,20,0.0,5,21,Semi-Urban,ML Engineer,68339,0 +30903,Male,30,Bachelors,19,85,73,67,50,8.0,6,56,Urban,Data Analyst,72710,1 +30904,Female,46,Bachelors,5,47,54,34,79,5.0,1,30,Semi-Urban,Data Analyst,49003,0 +30905,Female,46,Bachelors,6,67,59,51,11,4.0,2,73,Urban,Software Engineer,82509,1 +30906,Female,58,Bachelors,8,57,82,88,51,1.0,7,48,Urban,Software Engineer,146545,1 +30907,Male,29,High School,6,60,39,36,77,2.0,3,69,Rural,Software Engineer,22357,0 +30908,Female,44,Bachelors,19,24,5,63,76,5.0,7,92,Urban,Manager,88542,0 +30909,Male,26,Masters,13,63,23,33,61,6.0,4,47,Urban,Software Engineer,44170,0 +30910,Female,35,Masters,9,46,20,11,33,9.0,0,1,Urban,Manager,52642,0 +30911,Male,26,Masters,0,40,5,53,76,2.0,5,77,Semi-Urban,Software Engineer,24043,0 +30912,Female,48,Diploma,2,60,37,57,17,4.0,0,5,Urban,Data Analyst,92963,0 +30913,Female,28,Bachelors,10,20,59,29,73,5.0,1,46,Urban,HR Executive,110100,0 +30914,Female,21,Bachelors,19,48,44,39,18,6.0,0,40,Urban,ML Engineer,145766,0 +30915,Male,39,Diploma,7,82,67,4,88,9.0,6,12,Urban,Data Analyst,82107,0 +30916,Male,30,Bachelors,19,83,43,63,87,7.0,3,94,Rural,Software Engineer,118769,1 +30917,Female,57,Bachelors,14,20,4,69,26,1.0,0,13,Urban,Software Engineer,121374,0 +30918,Male,27,PhD,15,20,17,41,99,2.0,4,2,Urban,Manager,102707,0 +30919,Male,52,Diploma,9,80,66,82,81,9.0,4,86,Urban,Data Analyst,53361,1 +30920,Other,57,Diploma,3,94,36,98,49,7.0,7,93,Urban,Data Analyst,78554,1 +30921,Male,59,Bachelors,7,80,97,70,47,5.0,6,41,Urban,Software Engineer,143508,1 +30922,Female,31,Diploma,3,43,51,15,65,9.0,1,66,Urban,Software Engineer,97078,0 +30923,Male,33,Bachelors,14,53,55,22,93,7.0,1,92,Semi-Urban,Manager,88500,0 +30924,Female,52,Bachelors,17,79,13,57,96,9.0,0,11,Urban,Data Analyst,80489,0 +30925,Female,40,High School,7,50,37,60,71,4.0,7,21,Urban,HR Executive,27254,0 +30926,Female,45,Bachelors,1,64,40,30,39,6.0,2,50,Urban,HR Executive,95935,0 +30927,Other,25,Masters,12,99,51,83,50,0.0,6,51,Urban,Data Analyst,122431,1 +30928,Male,48,Masters,9,32,26,94,53,0.0,6,75,Urban,ML Engineer,56230,0 +30929,Female,27,PhD,3,36,65,27,34,4.0,5,69,Rural,Software Engineer,125110,0 +30930,Female,43,Diploma,8,63,0,12,4,2.0,7,86,Urban,Software Engineer,39449,0 +30931,Male,42,High School,17,22,63,2,79,1.0,2,58,Urban,HR Executive,86896,0 +30932,Male,24,Masters,9,30,81,76,86,3.0,4,99,Urban,Software Engineer,124863,1 +30933,Other,43,Diploma,15,16,83,82,10,2.0,6,9,Semi-Urban,ML Engineer,133335,0 +30934,Male,55,Bachelors,16,36,83,43,41,4.0,5,27,Urban,Data Analyst,149124,0 +30935,Male,39,Diploma,7,25,28,10,68,3.0,4,63,Urban,Software Engineer,97967,0 +30936,Male,36,Bachelors,1,92,48,34,42,6.0,3,56,Semi-Urban,HR Executive,37352,0 +30937,Male,25,High School,18,77,21,1,62,9.0,5,22,Urban,Software Engineer,34014,0 +30938,Female,29,Diploma,6,64,65,8,77,4.0,4,96,Urban,HR Executive,115427,0 +30939,Male,53,Masters,0,26,51,20,73,2.0,5,51,Semi-Urban,Software Engineer,45828,0 +30940,Male,39,Bachelors,0,61,12,93,41,9.0,1,65,Rural,HR Executive,91575,0 +30941,Female,48,Bachelors,0,65,60,66,8,9.0,4,83,Semi-Urban,HR Executive,55865,1 +30942,Male,58,Bachelors,0,91,49,94,80,2.0,7,8,Rural,Data Analyst,23110,1 +30943,Female,54,PhD,19,6,83,81,44,6.0,3,82,Urban,Data Analyst,50474,1 +30944,Female,39,Diploma,18,64,40,51,14,1.0,1,19,Urban,HR Executive,42240,0 +30945,Female,28,High School,14,74,25,91,63,5.0,4,87,Semi-Urban,HR Executive,57615,1 +30946,Female,49,Bachelors,14,56,56,59,16,6.0,2,33,Urban,Software Engineer,52866,0 +30947,Male,26,Bachelors,11,60,84,53,55,1.0,5,50,Urban,Manager,109228,1 +30948,Male,57,High School,17,15,0,12,49,4.0,0,65,Urban,Manager,114253,0 +30949,Male,26,Bachelors,8,84,8,17,83,0.0,3,91,Urban,Manager,43408,0 +30950,Male,57,Bachelors,3,63,66,57,71,5.0,2,40,Semi-Urban,Manager,28035,0 +30951,Male,32,PhD,16,66,78,60,83,7.0,4,50,Urban,ML Engineer,62586,1 +30952,Male,30,Masters,11,29,80,98,88,8.0,0,24,Urban,Manager,100997,0 +30953,Male,21,Diploma,2,23,67,39,63,6.0,4,37,Urban,HR Executive,37037,0 +30954,Male,31,Bachelors,13,41,28,31,92,0.0,0,58,Urban,ML Engineer,22179,0 +30955,Male,21,Bachelors,10,62,41,10,70,5.0,5,99,Semi-Urban,Data Analyst,115669,0 +30956,Male,52,Masters,8,83,14,68,8,4.0,6,80,Rural,Manager,55867,1 +30957,Male,36,Bachelors,10,61,0,12,29,7.0,1,60,Urban,Data Analyst,38983,0 +30958,Female,55,Diploma,4,29,24,82,9,2.0,2,65,Semi-Urban,Software Engineer,102949,0 +30959,Female,23,Masters,7,66,41,89,94,5.0,7,28,Urban,Software Engineer,70427,0 +30960,Female,53,Bachelors,0,56,92,65,6,8.0,3,91,Urban,Software Engineer,115964,1 +30961,Female,40,Masters,14,46,61,2,49,2.0,3,33,Urban,Manager,87145,0 +30962,Female,36,Diploma,19,46,80,52,40,9.0,4,14,Urban,HR Executive,99550,0 +30963,Female,36,Masters,7,15,40,30,61,6.0,3,45,Semi-Urban,Data Analyst,93983,0 +30964,Male,46,PhD,2,83,8,38,5,3.0,6,85,Urban,ML Engineer,120960,0 +30965,Male,49,Masters,0,87,38,99,85,5.0,4,44,Semi-Urban,Data Analyst,67813,1 +30966,Female,45,High School,3,38,57,83,67,2.0,1,57,Urban,Software Engineer,124514,0 +30967,Male,30,PhD,14,71,77,30,61,2.0,3,78,Rural,ML Engineer,116858,1 +30968,Male,58,Masters,19,14,57,32,78,8.0,6,72,Semi-Urban,HR Executive,120635,0 +30969,Male,25,Bachelors,6,48,0,16,53,3.0,6,14,Semi-Urban,HR Executive,122507,0 +30970,Male,27,Diploma,11,19,25,32,76,3.0,2,15,Urban,Software Engineer,65163,0 +30971,Female,27,Bachelors,19,57,87,18,74,0.0,5,93,Urban,Software Engineer,121817,1 +30972,Male,35,Bachelors,13,60,7,44,15,9.0,0,11,Urban,HR Executive,115083,0 +30973,Male,33,Bachelors,9,7,33,23,41,3.0,7,70,Urban,ML Engineer,120127,0 +30974,Male,58,High School,7,2,87,97,14,6.0,4,41,Urban,HR Executive,63419,0 +30975,Female,30,Diploma,4,91,99,47,28,5.0,3,35,Semi-Urban,HR Executive,130351,1 +30976,Female,34,Diploma,16,46,4,52,23,5.0,3,61,Semi-Urban,Software Engineer,116096,0 +30977,Male,31,Bachelors,19,5,87,98,85,3.0,2,80,Urban,Manager,101016,1 +30978,Female,25,Masters,1,92,81,52,42,3.0,0,22,Urban,HR Executive,110032,1 +30979,Male,49,Masters,0,46,48,24,4,5.0,3,53,Urban,Data Analyst,34815,0 +30980,Female,35,High School,6,40,75,61,94,4.0,5,93,Rural,ML Engineer,118232,1 +30981,Female,28,Masters,14,41,92,38,83,0.0,7,23,Semi-Urban,Software Engineer,86809,0 +30982,Other,30,Masters,9,29,19,37,92,3.0,2,30,Urban,HR Executive,74735,0 +30983,Male,33,High School,9,14,11,95,12,7.0,0,99,Semi-Urban,Data Analyst,88914,0 +30984,Male,29,Bachelors,4,49,68,11,79,0.0,1,78,Urban,HR Executive,143813,0 +30985,Male,37,PhD,19,75,72,74,28,8.0,7,99,Urban,Data Analyst,50188,1 +30986,Male,55,Bachelors,11,44,85,85,10,9.0,2,71,Semi-Urban,Data Analyst,34199,1 +30987,Male,35,Diploma,2,59,3,4,80,9.0,0,27,Semi-Urban,HR Executive,58588,0 +30988,Male,22,Bachelors,8,27,79,92,19,8.0,6,3,Urban,Manager,96295,0 +30989,Male,34,Masters,5,44,10,85,89,6.0,6,88,Urban,HR Executive,149583,0 +30990,Female,27,Bachelors,7,57,77,53,10,1.0,4,76,Urban,Software Engineer,96896,1 +30991,Male,21,Masters,18,82,86,51,0,8.0,4,14,Urban,ML Engineer,136553,0 +30992,Other,47,Bachelors,16,84,13,45,13,7.0,6,56,Semi-Urban,Manager,33227,0 +30993,Female,31,High School,1,79,22,19,72,2.0,2,76,Urban,Manager,66430,0 +30994,Female,39,Diploma,1,74,10,19,84,8.0,1,90,Urban,ML Engineer,116202,0 +30995,Female,44,High School,4,12,48,32,84,1.0,0,12,Semi-Urban,Software Engineer,50422,0 +30996,Female,49,Bachelors,6,84,90,85,40,0.0,2,19,Urban,Data Analyst,140135,1 +30997,Female,27,Bachelors,8,65,72,96,27,6.0,1,63,Semi-Urban,Data Analyst,56432,1 +30998,Male,43,Masters,10,54,47,37,74,3.0,4,54,Urban,HR Executive,70357,0 +30999,Male,33,Bachelors,7,36,74,75,43,6.0,4,46,Semi-Urban,Manager,56967,0 +31000,Female,56,Masters,4,3,43,92,62,4.0,7,21,Rural,Data Analyst,71746,0 +31001,Male,54,Bachelors,1,95,59,95,20,6.0,2,3,Urban,ML Engineer,127853,1 +31002,Male,23,Bachelors,3,41,99,41,25,8.0,1,79,Urban,ML Engineer,69771,1 +31003,Female,21,Diploma,8,9,29,45,26,5.0,3,53,Urban,HR Executive,93068,0 +31004,Male,23,High School,5,11,2,25,26,8.0,2,49,Semi-Urban,Data Analyst,124926,0 +31005,Female,33,Masters,8,58,52,35,76,4.0,3,31,Semi-Urban,Software Engineer,25671,0 +31006,Male,46,Diploma,2,81,49,67,24,6.0,2,83,Urban,HR Executive,105434,1 +31007,Female,38,Bachelors,5,73,51,22,97,9.0,1,78,Semi-Urban,HR Executive,85549,0 +31008,Male,49,Diploma,14,16,11,3,81,4.0,4,31,Rural,Data Analyst,121958,0 +31009,Female,54,Masters,13,20,86,84,90,2.0,7,11,Urban,Software Engineer,84982,0 +31010,Male,33,Diploma,7,57,5,34,29,0.0,4,48,Semi-Urban,Software Engineer,104547,0 +31011,Female,27,Masters,5,39,51,30,43,8.0,3,96,Semi-Urban,ML Engineer,119527,0 +31012,Male,23,Diploma,0,5,19,76,69,4.0,5,34,Urban,HR Executive,128333,0 +31013,Male,47,High School,13,4,78,63,79,1.0,0,44,Urban,Data Analyst,91680,0 +31014,Male,43,Masters,14,16,18,52,35,2.0,5,80,Urban,Manager,37948,0 +31015,Male,59,High School,3,47,58,59,59,6.0,5,17,Urban,Data Analyst,79940,0 +31016,Female,42,Bachelors,15,68,17,38,74,9.0,7,93,Semi-Urban,Manager,88104,0 +31017,Male,21,Bachelors,17,68,84,71,28,9.0,4,73,Urban,Data Analyst,117760,1 +31018,Male,31,Masters,9,36,15,91,5,1.0,2,24,Urban,Software Engineer,101539,0 +31019,Male,24,Bachelors,6,73,56,93,27,7.0,3,96,Rural,HR Executive,83610,1 +31020,Female,31,Bachelors,16,65,62,78,22,8.0,0,8,Urban,HR Executive,99061,0 +31021,Male,37,Diploma,11,35,12,87,76,9.0,5,65,Rural,Software Engineer,97016,0 +31022,Male,38,High School,4,49,34,32,30,4.0,0,53,Semi-Urban,Manager,98915,0 +31023,Female,58,Bachelors,9,2,98,98,4,8.0,3,33,Urban,Software Engineer,105985,0 +31024,Female,46,Bachelors,6,14,50,72,96,1.0,4,19,Urban,Software Engineer,140985,0 +31025,Female,24,High School,8,85,22,20,41,9.0,1,26,Urban,ML Engineer,122628,0 +31026,Female,38,Bachelors,1,66,89,31,58,2.0,6,17,Urban,Software Engineer,143948,0 +31027,Male,31,PhD,9,82,66,30,10,9.0,0,56,Urban,HR Executive,29122,0 +31028,Female,56,High School,11,47,33,43,5,6.0,5,81,Rural,Data Analyst,140056,0 +31029,Female,30,Diploma,14,37,88,38,42,9.0,6,82,Urban,HR Executive,93928,1 +31030,Female,29,Diploma,8,96,98,93,62,4.0,7,68,Urban,ML Engineer,105408,1 +31031,Male,51,High School,19,9,33,75,88,8.0,5,92,Semi-Urban,Software Engineer,56992,0 +31032,Female,47,Masters,14,61,90,33,5,5.0,2,79,Semi-Urban,ML Engineer,42265,1 +31033,Male,27,Bachelors,1,74,34,35,12,0.0,2,91,Rural,Data Analyst,127872,0 +31034,Female,39,Masters,10,40,59,45,21,5.0,2,83,Rural,ML Engineer,94641,0 +31035,Male,52,Bachelors,14,39,50,70,68,2.0,3,94,Urban,HR Executive,73648,1 +31036,Male,37,Diploma,5,18,40,26,28,7.0,2,29,Semi-Urban,Software Engineer,93617,0 +31037,Male,54,High School,8,78,20,89,32,5.0,2,22,Semi-Urban,Software Engineer,87059,0 +31038,Male,51,Bachelors,7,45,72,69,90,1.0,2,69,Urban,Software Engineer,149233,1 +31039,Female,51,Diploma,6,94,32,85,86,1.0,0,52,Semi-Urban,Data Analyst,63945,1 +31040,Female,39,PhD,16,15,13,62,34,5.0,6,18,Urban,Manager,45098,0 +31041,Female,57,Diploma,0,42,91,4,18,5.0,1,61,Urban,Manager,20268,0 +31042,Male,24,Bachelors,12,28,53,32,33,5.0,6,16,Urban,Data Analyst,88206,0 +31043,Other,50,High School,0,36,70,11,40,8.0,4,28,Rural,Manager,104186,0 +31044,Female,54,Bachelors,1,80,4,17,25,9.0,2,15,Urban,ML Engineer,83633,0 +31045,Male,31,High School,8,23,86,16,17,7.0,0,19,Semi-Urban,Data Analyst,27482,0 +31046,Female,41,High School,2,40,82,37,18,0.0,7,56,Urban,Data Analyst,87742,0 +31047,Male,42,Bachelors,3,85,75,85,18,2.0,3,7,Rural,Software Engineer,61950,1 +31048,Male,48,Bachelors,3,0,30,50,90,5.0,7,60,Semi-Urban,HR Executive,105086,0 +31049,Male,51,High School,11,6,16,47,60,2.0,0,39,Semi-Urban,Manager,121897,0 +31050,Male,53,Bachelors,14,13,42,15,63,8.0,1,22,Urban,Manager,144391,0 +31051,Male,40,Bachelors,7,46,10,57,44,8.0,2,14,Urban,Software Engineer,35460,0 +31052,Male,22,High School,18,98,54,6,14,8.0,2,27,Urban,Software Engineer,113647,0 +31053,Female,23,Masters,17,72,77,21,59,9.0,2,25,Rural,Data Analyst,113667,0 +31054,Male,49,High School,17,7,34,72,68,3.0,4,8,Rural,Data Analyst,134204,0 +31055,Male,30,Bachelors,12,5,36,46,63,6.0,3,32,Urban,Software Engineer,133069,0 +31056,Other,34,High School,2,20,50,65,31,6.0,5,73,Urban,Software Engineer,130130,0 +31057,Male,28,Diploma,6,48,52,46,76,4.0,4,45,Rural,HR Executive,54167,0 +31058,Female,57,Bachelors,13,98,83,12,83,1.0,1,54,Rural,Software Engineer,58356,1 +31059,Male,59,High School,3,8,11,44,6,4.0,1,28,Rural,Software Engineer,37733,0 +31060,Male,22,High School,2,23,38,18,8,5.0,5,31,Rural,ML Engineer,113592,0 +31061,Male,34,PhD,4,19,41,89,50,2.0,4,56,Urban,HR Executive,46749,0 +31062,Other,30,Masters,9,32,10,11,93,3.0,6,45,Urban,HR Executive,139476,0 +31063,Male,46,High School,14,96,55,10,32,5.0,5,39,Urban,HR Executive,82582,0 +31064,Male,47,Masters,0,91,5,32,15,4.0,6,78,Urban,Software Engineer,95753,0 +31065,Female,41,High School,3,37,89,10,84,5.0,2,31,Urban,Software Engineer,102283,0 +31066,Other,50,Masters,1,5,6,7,1,2.0,2,9,Semi-Urban,ML Engineer,101316,0 +31067,Male,34,Bachelors,1,13,77,35,1,3.0,7,53,Urban,Manager,116736,0 +31068,Female,25,Bachelors,14,61,88,86,17,0.0,1,14,Urban,Software Engineer,65582,1 +31069,Male,35,Bachelors,3,5,43,98,87,3.0,4,47,Urban,Software Engineer,106610,0 +31070,Male,32,Bachelors,2,90,10,55,58,3.0,7,52,Urban,HR Executive,47390,0 +31071,Male,31,Bachelors,11,22,82,71,86,8.0,2,54,Urban,ML Engineer,49893,0 +31072,Male,33,Diploma,9,3,64,81,33,8.0,5,94,Semi-Urban,HR Executive,109289,1 +31073,Male,32,Bachelors,14,57,35,91,57,6.0,7,26,Semi-Urban,Software Engineer,132672,0 +31074,Male,39,Bachelors,7,30,24,26,70,4.0,1,39,Urban,Data Analyst,89881,0 +31075,Male,55,Bachelors,1,17,47,10,75,9.0,3,63,Semi-Urban,Data Analyst,82001,0 +31076,Male,58,PhD,17,51,81,8,62,1.0,6,65,Semi-Urban,Manager,40689,0 +31077,Male,51,High School,4,94,73,92,82,7.0,5,45,Urban,ML Engineer,31360,1 +31078,Other,48,Masters,9,98,39,63,22,8.0,4,15,Rural,Data Analyst,124794,0 +31079,Female,27,High School,2,69,67,76,37,1.0,3,33,Urban,ML Engineer,142387,1 +31080,Male,36,Bachelors,14,22,91,22,26,2.0,5,87,Urban,ML Engineer,93858,0 +31081,Female,22,Bachelors,6,50,53,23,55,4.0,3,35,Urban,Software Engineer,39286,0 +31082,Male,52,Bachelors,19,47,97,65,90,8.0,4,55,Urban,HR Executive,70281,1 +31083,Male,26,Masters,19,79,53,9,52,7.0,4,61,Semi-Urban,HR Executive,112119,0 +31084,Male,43,Bachelors,16,61,13,43,78,5.0,5,47,Urban,HR Executive,77936,0 +31085,Male,50,Diploma,15,46,45,57,54,8.0,7,12,Semi-Urban,Data Analyst,138648,0 +31086,Female,34,Diploma,8,40,12,67,90,0.0,0,74,Semi-Urban,HR Executive,57799,0 +31087,Other,36,PhD,4,0,2,21,50,9.0,7,98,Semi-Urban,Data Analyst,46444,0 +31088,Male,33,Diploma,5,52,47,90,20,8.0,2,27,Semi-Urban,HR Executive,68468,0 +31089,Male,25,High School,12,11,55,14,27,9.0,0,31,Urban,Data Analyst,37106,0 +31090,Male,30,PhD,14,84,20,39,44,1.0,4,63,Urban,Software Engineer,25745,0 +31091,Male,50,Masters,0,65,15,4,14,2.0,0,69,Urban,ML Engineer,140698,0 +31092,Female,35,Masters,15,35,80,98,0,4.0,7,94,Semi-Urban,Software Engineer,35140,1 +31093,Female,52,PhD,5,30,64,18,53,9.0,2,63,Urban,Data Analyst,92992,0 +31094,Male,26,Diploma,15,61,16,17,59,4.0,4,81,Urban,HR Executive,52661,0 +31095,Female,40,Bachelors,13,24,26,17,70,5.0,4,64,Rural,Data Analyst,87112,0 +31096,Male,25,Masters,1,51,86,95,48,9.0,4,84,Rural,Data Analyst,82542,1 +31097,Other,28,Masters,14,45,50,82,28,0.0,7,17,Urban,Data Analyst,128280,0 +31098,Male,30,Bachelors,6,88,44,19,86,0.0,7,23,Semi-Urban,Manager,74834,0 +31099,Female,49,Bachelors,8,80,26,48,35,8.0,0,8,Semi-Urban,Software Engineer,135180,0 +31100,Male,36,High School,17,81,93,86,8,7.0,2,59,Urban,ML Engineer,146663,1 +31101,Male,27,Bachelors,6,20,49,23,33,0.0,4,17,Urban,Manager,43310,0 +31102,Female,38,Masters,13,1,36,11,88,3.0,6,84,Urban,Manager,142410,0 +31103,Male,51,Bachelors,1,31,2,75,88,8.0,5,57,Urban,Manager,29344,0 +31104,Female,49,Masters,14,32,33,45,40,4.0,0,42,Urban,ML Engineer,53852,0 +31105,Male,57,Masters,10,41,98,50,29,4.0,7,27,Urban,Software Engineer,122811,0 +31106,Female,22,Bachelors,7,1,77,87,42,6.0,1,58,Urban,ML Engineer,77232,0 +31107,Other,40,Bachelors,15,84,47,33,41,0.0,4,13,Semi-Urban,ML Engineer,119996,0 +31108,Male,27,Masters,2,93,5,70,91,9.0,3,52,Semi-Urban,ML Engineer,84172,0 +31109,Male,46,Bachelors,3,89,62,92,99,9.0,6,94,Urban,Software Engineer,22582,1 +31110,Female,57,High School,18,51,7,81,71,1.0,4,50,Urban,HR Executive,42927,0 +31111,Male,34,Bachelors,5,7,57,60,36,4.0,2,21,Semi-Urban,HR Executive,75771,0 +31112,Female,42,PhD,17,49,74,5,22,3.0,4,12,Urban,Data Analyst,63521,0 +31113,Male,35,Bachelors,4,27,77,15,85,4.0,7,97,Semi-Urban,ML Engineer,41222,0 +31114,Female,40,Diploma,6,84,36,86,35,8.0,6,12,Urban,ML Engineer,132601,0 +31115,Male,46,Bachelors,12,49,81,86,57,5.0,6,60,Semi-Urban,Manager,86062,1 +31116,Female,41,Bachelors,13,0,37,32,84,2.0,7,5,Urban,HR Executive,64594,0 +31117,Male,51,Diploma,16,1,89,35,67,9.0,0,49,Urban,Data Analyst,28116,0 +31118,Female,53,Bachelors,5,71,79,83,29,4.0,6,85,Rural,HR Executive,106008,1 +31119,Male,25,High School,12,29,7,5,37,0.0,1,14,Semi-Urban,Data Analyst,140793,0 +31120,Male,50,Bachelors,8,81,3,54,54,4.0,7,93,Urban,ML Engineer,57309,0 +31121,Other,53,Masters,7,87,4,50,89,8.0,1,70,Semi-Urban,HR Executive,141630,0 +31122,Female,43,Bachelors,10,60,91,38,52,1.0,2,55,Semi-Urban,Manager,41672,1 +31123,Other,41,Bachelors,17,56,71,83,31,4.0,2,65,Urban,Manager,43313,1 +31124,Male,59,High School,5,54,94,50,65,4.0,1,35,Urban,Software Engineer,116439,0 +31125,Female,51,Diploma,12,75,20,90,21,5.0,5,19,Semi-Urban,Software Engineer,139505,0 +31126,Female,50,Bachelors,17,69,1,91,36,5.0,4,1,Semi-Urban,HR Executive,68257,0 +31127,Female,27,Diploma,4,44,50,89,66,2.0,6,97,Rural,Data Analyst,78350,1 +31128,Male,40,Bachelors,15,11,68,80,75,5.0,4,97,Rural,Manager,96861,1 +31129,Male,21,Bachelors,11,1,55,36,35,4.0,6,22,Semi-Urban,Manager,128606,0 +31130,Female,36,Bachelors,0,68,35,43,12,4.0,6,26,Semi-Urban,Software Engineer,122890,0 +31131,Male,57,Masters,3,4,70,36,95,1.0,6,91,Semi-Urban,Software Engineer,104832,0 +31132,Other,44,Bachelors,14,6,46,60,55,2.0,0,31,Rural,Data Analyst,77867,0 +31133,Male,54,Diploma,6,72,89,44,99,6.0,2,34,Urban,Software Engineer,85509,1 +31134,Other,40,High School,7,66,82,84,7,3.0,3,70,Urban,Software Engineer,40861,1 +31135,Female,39,PhD,2,96,14,84,58,7.0,7,34,Rural,Manager,125870,0 +31136,Female,28,PhD,11,79,61,74,1,8.0,0,55,Urban,Manager,130758,1 +31137,Male,31,Bachelors,17,59,64,24,95,3.0,0,56,Urban,HR Executive,41214,0 +31138,Female,52,Masters,18,55,52,21,99,3.0,0,27,Urban,Software Engineer,58926,0 +31139,Male,23,Bachelors,1,80,72,70,30,9.0,0,10,Semi-Urban,Software Engineer,56577,0 +31140,Female,39,Masters,8,74,5,84,49,6.0,4,19,Semi-Urban,Data Analyst,140967,0 +31141,Male,46,Masters,17,38,63,62,42,9.0,0,78,Urban,Manager,132231,1 +31142,Female,24,Diploma,3,87,73,33,35,7.0,6,13,Urban,HR Executive,65754,0 +31143,Female,56,Bachelors,7,94,16,27,53,7.0,5,38,Semi-Urban,Data Analyst,106408,0 +31144,Male,45,High School,12,54,98,29,7,9.0,0,42,Urban,Data Analyst,147739,0 +31145,Female,53,Diploma,3,39,69,22,50,0.0,7,30,Urban,ML Engineer,26514,0 +31146,Male,34,Bachelors,16,86,53,80,37,8.0,5,84,Semi-Urban,Software Engineer,59942,1 +31147,Female,27,Bachelors,13,21,75,11,4,4.0,3,75,Rural,Software Engineer,40386,0 +31148,Other,46,Bachelors,17,88,31,77,53,1.0,4,8,Semi-Urban,Manager,89990,0 +31149,Male,36,Masters,4,12,89,63,5,3.0,5,21,Rural,HR Executive,111417,0 +31150,Male,32,Diploma,1,57,89,91,19,4.0,6,8,Rural,Data Analyst,59232,1 +31151,Female,51,High School,19,35,2,56,57,1.0,0,33,Urban,Software Engineer,94298,0 +31152,Male,44,Diploma,13,83,8,33,18,0.0,7,9,Urban,HR Executive,70027,0 +31153,Male,28,Bachelors,4,54,15,56,28,9.0,3,31,Urban,Software Engineer,137241,0 +31154,Male,57,High School,9,41,87,49,17,2.0,3,99,Urban,ML Engineer,107265,1 +31155,Male,32,Bachelors,0,2,30,79,13,3.0,3,92,Urban,ML Engineer,116065,0 +31156,Male,56,Bachelors,17,17,63,45,31,0.0,2,5,Rural,Manager,45114,0 +31157,Male,34,Masters,19,55,3,48,80,3.0,0,48,Rural,Data Analyst,141309,0 +31158,Male,39,Diploma,2,8,24,98,12,2.0,1,33,Semi-Urban,Software Engineer,100338,0 +31159,Female,30,Masters,3,10,12,47,50,0.0,1,1,Urban,ML Engineer,39960,0 +31160,Male,36,Masters,13,23,10,90,56,7.0,6,74,Urban,Software Engineer,111361,0 +31161,Male,31,Diploma,18,61,69,73,10,2.0,5,87,Rural,Manager,34763,1 +31162,Female,53,Masters,17,73,8,43,22,0.0,2,87,Semi-Urban,Manager,36222,0 +31163,Female,57,Bachelors,4,18,29,33,90,0.0,2,85,Urban,HR Executive,66471,0 +31164,Male,28,Bachelors,17,77,36,99,16,8.0,6,26,Semi-Urban,ML Engineer,104065,1 +31165,Female,47,Masters,15,89,37,48,50,8.0,7,58,Semi-Urban,Software Engineer,130519,0 +31166,Female,50,Bachelors,11,65,50,96,90,6.0,3,40,Urban,HR Executive,53709,1 +31167,Male,32,Bachelors,5,19,52,66,20,9.0,1,52,Semi-Urban,Manager,78998,0 +31168,Male,48,Diploma,0,32,2,12,21,8.0,7,9,Urban,Data Analyst,85274,0 +31169,Male,33,High School,5,18,1,28,10,7.0,6,31,Semi-Urban,ML Engineer,43558,0 +31170,Female,29,High School,4,12,87,50,89,9.0,1,77,Urban,Manager,69918,0 +31171,Male,45,Bachelors,7,53,93,31,99,9.0,1,69,Semi-Urban,ML Engineer,46805,1 +31172,Other,45,Bachelors,1,88,28,62,37,9.0,4,36,Semi-Urban,Software Engineer,75065,0 +31173,Female,36,Masters,13,30,4,54,48,5.0,4,48,Urban,Data Analyst,32956,0 +31174,Male,30,PhD,16,32,27,46,25,4.0,3,81,Urban,Software Engineer,108882,0 +31175,Male,45,High School,2,55,41,6,89,9.0,3,48,Semi-Urban,ML Engineer,146573,0 +31176,Male,26,Bachelors,7,13,26,93,79,0.0,4,60,Urban,ML Engineer,69710,0 +31177,Male,51,High School,16,78,52,13,9,2.0,4,12,Urban,Software Engineer,47923,0 +31178,Male,21,Bachelors,7,89,33,59,71,4.0,0,68,Rural,Software Engineer,106328,1 +31179,Female,34,Masters,12,40,94,73,67,0.0,5,92,Rural,ML Engineer,101406,1 +31180,Female,34,Bachelors,4,26,71,12,53,1.0,7,54,Urban,Data Analyst,112886,0 +31181,Male,34,Bachelors,16,26,73,50,58,4.0,2,0,Urban,Manager,77681,0 +31182,Male,52,Bachelors,9,27,60,83,76,2.0,5,63,Urban,HR Executive,127636,0 +31183,Male,45,PhD,9,41,10,4,82,4.0,7,0,Urban,Manager,22999,0 +31184,Male,36,Bachelors,7,16,85,67,30,5.0,1,29,Urban,HR Executive,71406,0 +31185,Female,30,Bachelors,19,79,50,86,42,8.0,0,93,Urban,HR Executive,135877,1 +31186,Male,34,Diploma,12,80,31,72,78,3.0,0,42,Rural,ML Engineer,103988,0 +31187,Female,46,Diploma,13,89,96,38,97,5.0,4,0,Rural,HR Executive,127135,0 +31188,Other,52,PhD,16,19,32,6,32,6.0,2,7,Urban,ML Engineer,52304,0 +31189,Female,32,Diploma,11,38,50,81,13,7.0,6,7,Rural,Data Analyst,75774,0 +31190,Male,29,Masters,5,18,3,24,92,3.0,7,82,Semi-Urban,ML Engineer,20904,0 +31191,Male,38,Diploma,16,85,3,47,83,9.0,0,34,Urban,Software Engineer,95897,0 +31192,Male,22,Bachelors,19,86,69,59,99,5.0,3,23,Urban,Software Engineer,58904,1 +31193,Female,25,High School,14,75,12,33,94,8.0,7,29,Urban,ML Engineer,83245,0 +31194,Female,22,Bachelors,3,40,36,25,23,6.0,7,74,Urban,Software Engineer,143238,0 +31195,Female,42,Bachelors,3,46,31,20,14,5.0,6,5,Urban,ML Engineer,46260,0 +31196,Female,22,High School,10,3,24,62,66,5.0,4,78,Urban,Data Analyst,59074,0 +31197,Female,22,High School,0,62,15,87,92,2.0,5,15,Urban,Software Engineer,144951,0 +31198,Female,45,Bachelors,1,2,14,5,42,9.0,4,19,Urban,HR Executive,119460,0 +31199,Male,41,Bachelors,0,76,36,90,43,0.0,5,60,Semi-Urban,HR Executive,99695,1 +31200,Female,48,Diploma,9,29,88,73,64,8.0,0,0,Rural,Software Engineer,134773,0 +31201,Female,32,Masters,8,25,89,15,93,6.0,6,7,Urban,HR Executive,127728,0 +31202,Male,50,Bachelors,6,18,79,55,32,3.0,5,12,Urban,Manager,102293,0 +31203,Other,33,Bachelors,18,7,87,99,25,1.0,3,95,Rural,Data Analyst,43790,1 +31204,Other,45,Masters,3,66,18,23,89,5.0,4,52,Urban,ML Engineer,104835,0 +31205,Male,24,Bachelors,18,89,46,57,5,9.0,4,57,Urban,Manager,58621,1 +31206,Female,35,High School,7,15,73,6,95,7.0,5,73,Urban,Software Engineer,67602,0 +31207,Male,52,Bachelors,8,56,98,56,63,3.0,2,17,Urban,ML Engineer,104399,0 +31208,Male,21,Diploma,17,57,22,64,38,2.0,3,20,Urban,Data Analyst,33582,0 +31209,Male,48,Masters,3,95,23,74,71,0.0,5,20,Semi-Urban,ML Engineer,49355,0 +31210,Male,42,Masters,12,4,19,46,98,3.0,7,67,Semi-Urban,Manager,140839,0 +31211,Male,51,Masters,5,92,6,62,1,2.0,4,11,Rural,Manager,133033,0 +31212,Male,51,Masters,16,58,15,36,4,9.0,6,81,Urban,HR Executive,64327,0 +31213,Female,28,Diploma,3,87,61,43,67,8.0,6,28,Urban,ML Engineer,33665,0 +31214,Male,52,Bachelors,1,51,37,49,36,6.0,3,43,Urban,Software Engineer,142313,0 +31215,Male,48,Masters,18,82,52,76,9,8.0,0,12,Urban,Manager,131306,0 +31216,Male,33,Diploma,15,15,66,2,97,4.0,4,2,Urban,Software Engineer,127560,0 +31217,Male,55,Bachelors,9,45,31,41,50,5.0,0,27,Rural,HR Executive,95021,0 +31218,Male,35,Bachelors,7,69,76,44,90,9.0,1,37,Semi-Urban,HR Executive,132088,0 +31219,Male,33,Masters,3,22,52,27,71,7.0,0,10,Urban,HR Executive,57510,0 +31220,Male,49,Diploma,0,98,41,67,79,1.0,5,10,Urban,ML Engineer,41801,0 +31221,Male,50,Masters,4,31,82,14,6,0.0,0,59,Rural,ML Engineer,106629,0 +31222,Male,44,PhD,12,78,2,44,23,5.0,1,88,Rural,HR Executive,132454,0 +31223,Female,35,Masters,14,21,4,23,1,1.0,1,11,Urban,Software Engineer,45576,0 +31224,Male,51,Bachelors,10,86,5,89,18,1.0,5,42,Urban,HR Executive,72883,0 +31225,Female,45,Bachelors,8,12,22,84,71,5.0,6,56,Semi-Urban,ML Engineer,135391,0 +31226,Male,39,Bachelors,4,69,99,21,41,2.0,2,97,Semi-Urban,ML Engineer,72225,1 +31227,Male,59,High School,11,68,66,63,42,8.0,3,56,Urban,ML Engineer,34839,1 +31228,Male,29,Bachelors,5,39,97,6,58,0.0,2,61,Rural,Data Analyst,115082,0 +31229,Female,22,Bachelors,16,35,23,70,1,9.0,2,16,Urban,HR Executive,36558,0 +31230,Male,30,Bachelors,19,71,8,83,57,1.0,0,77,Urban,Manager,60534,1 +31231,Female,34,Masters,9,48,42,86,12,6.0,3,22,Urban,ML Engineer,49891,0 +31232,Female,22,Masters,4,84,94,39,54,0.0,4,72,Rural,Software Engineer,75346,1 +31233,Male,55,Bachelors,12,20,23,61,20,8.0,7,52,Urban,Manager,51893,0 +31234,Female,31,Bachelors,0,27,20,38,90,8.0,5,65,Semi-Urban,Manager,130670,0 +31235,Male,42,Masters,16,41,59,31,47,2.0,2,30,Urban,ML Engineer,111873,0 +31236,Male,29,Bachelors,9,75,48,89,67,5.0,6,43,Urban,Manager,83906,1 +31237,Male,26,Masters,2,21,68,8,66,1.0,2,48,Urban,Software Engineer,72976,0 +31238,Male,33,Diploma,6,86,90,38,2,9.0,5,88,Urban,Manager,102547,1 +31239,Male,53,High School,0,56,93,95,36,4.0,7,4,Semi-Urban,Manager,70390,1 +31240,Female,55,Bachelors,5,11,75,90,97,7.0,6,73,Semi-Urban,Data Analyst,44331,1 +31241,Male,25,Bachelors,3,69,40,21,26,6.0,0,27,Urban,HR Executive,62362,0 +31242,Female,55,Bachelors,15,2,74,77,18,5.0,5,43,Urban,ML Engineer,128319,0 +31243,Male,58,Bachelors,12,4,98,73,77,7.0,6,66,Urban,Data Analyst,59187,1 +31244,Other,56,Bachelors,11,1,15,83,25,8.0,3,50,Rural,Data Analyst,70279,0 +31245,Male,28,Bachelors,8,32,88,77,33,0.0,6,25,Semi-Urban,Manager,87973,0 +31246,Female,40,Bachelors,0,33,92,59,9,4.0,4,50,Rural,Software Engineer,82254,0 +31247,Female,38,Bachelors,16,27,55,40,24,6.0,3,25,Rural,Data Analyst,59191,0 +31248,Male,30,Bachelors,14,57,19,45,22,6.0,4,58,Semi-Urban,Manager,23086,0 +31249,Male,48,Bachelors,14,33,84,35,58,0.0,4,79,Semi-Urban,HR Executive,124475,0 +31250,Male,22,Diploma,11,27,73,23,59,0.0,7,35,Semi-Urban,HR Executive,59604,0 +31251,Male,45,High School,11,99,95,10,94,8.0,6,38,Semi-Urban,HR Executive,72141,1 +31252,Male,21,High School,2,96,54,17,48,0.0,3,73,Urban,Data Analyst,69637,1 +31253,Female,47,High School,12,81,45,55,31,5.0,3,49,Urban,ML Engineer,45656,0 +31254,Male,27,Bachelors,17,72,59,6,7,8.0,2,96,Urban,Manager,26123,0 +31255,Male,54,Bachelors,2,11,75,92,39,2.0,0,5,Semi-Urban,ML Engineer,149879,0 +31256,Male,57,Diploma,9,89,23,52,13,1.0,5,44,Rural,Software Engineer,125436,0 +31257,Female,30,High School,16,81,23,27,97,9.0,4,17,Urban,HR Executive,36245,0 +31258,Male,56,Diploma,4,64,34,7,87,1.0,3,26,Semi-Urban,Data Analyst,81520,0 +31259,Male,55,Bachelors,0,95,39,43,51,7.0,1,54,Urban,HR Executive,109048,0 +31260,Male,58,Bachelors,5,74,6,90,46,3.0,1,43,Urban,Manager,39691,0 +31261,Male,30,Masters,19,61,80,61,3,4.0,6,46,Semi-Urban,HR Executive,109336,1 +31262,Female,36,PhD,10,98,79,17,0,7.0,4,30,Urban,Data Analyst,84835,0 +31263,Female,40,Bachelors,2,16,99,34,85,9.0,0,6,Urban,ML Engineer,79793,0 +31264,Female,54,Bachelors,4,8,9,7,23,3.0,2,44,Rural,HR Executive,74625,0 +31265,Male,30,Bachelors,2,58,75,44,24,8.0,5,85,Urban,Manager,107185,1 +31266,Other,29,Masters,3,54,22,89,66,7.0,3,89,Rural,ML Engineer,97877,1 +31267,Male,44,Bachelors,7,99,60,48,16,3.0,1,20,Semi-Urban,ML Engineer,63301,0 +31268,Male,25,Diploma,5,16,70,51,77,5.0,4,93,Urban,Software Engineer,85023,0 +31269,Male,58,High School,0,57,49,65,62,1.0,2,21,Urban,ML Engineer,64075,0 +31270,Male,25,Diploma,1,28,23,39,5,0.0,0,8,Rural,ML Engineer,82100,0 +31271,Male,33,Diploma,13,80,88,11,21,2.0,7,19,Urban,Data Analyst,27393,0 +31272,Male,26,PhD,2,73,15,37,30,6.0,2,0,Urban,Manager,141290,0 +31273,Male,48,Diploma,2,99,76,33,16,1.0,0,48,Rural,HR Executive,59204,1 +31274,Male,57,Masters,14,28,81,42,37,5.0,2,67,Urban,Manager,40043,0 +31275,Female,25,High School,15,36,77,20,43,1.0,7,11,Urban,ML Engineer,140094,0 +31276,Other,22,PhD,5,81,62,54,10,4.0,2,52,Urban,HR Executive,99064,1 +31277,Male,48,High School,19,93,19,41,96,2.0,1,2,Urban,Manager,115093,0 +31278,Female,39,Diploma,1,98,53,76,66,9.0,7,97,Semi-Urban,Software Engineer,148918,1 +31279,Female,24,High School,13,55,77,1,47,5.0,2,80,Rural,Manager,120496,0 +31280,Other,48,Masters,9,1,60,86,26,2.0,1,21,Urban,Data Analyst,65200,0 +31281,Male,46,Bachelors,14,76,80,11,14,2.0,5,11,Rural,Manager,81391,0 +31282,Female,42,PhD,15,69,98,49,42,2.0,0,28,Urban,Software Engineer,27107,1 +31283,Male,42,High School,0,98,0,78,74,7.0,2,73,Urban,HR Executive,106546,1 +31284,Female,38,Diploma,19,39,83,15,27,7.0,1,69,Urban,ML Engineer,76596,0 +31285,Female,58,Masters,5,13,68,2,75,2.0,7,16,Urban,Software Engineer,34235,0 +31286,Female,30,Bachelors,2,97,88,76,56,7.0,7,24,Urban,Data Analyst,115203,1 +31287,Male,56,Bachelors,0,45,45,96,56,5.0,0,82,Rural,HR Executive,118086,1 +31288,Female,29,Masters,19,9,45,92,10,1.0,1,62,Urban,Data Analyst,117782,0 +31289,Male,42,Diploma,6,14,6,23,96,8.0,0,32,Semi-Urban,Software Engineer,141858,0 +31290,Male,42,Diploma,16,89,15,36,98,5.0,4,72,Urban,HR Executive,147556,0 +31291,Male,46,Bachelors,12,26,88,25,17,1.0,7,23,Urban,Software Engineer,87108,0 +31292,Female,22,Masters,14,82,16,76,13,4.0,2,32,Semi-Urban,ML Engineer,114346,0 +31293,Other,26,Bachelors,8,46,64,42,91,7.0,1,76,Urban,Manager,88323,0 +31294,Female,34,Masters,7,29,74,31,17,1.0,2,30,Urban,HR Executive,35804,0 +31295,Male,45,Masters,2,79,27,11,15,2.0,3,97,Rural,Manager,134183,0 +31296,Male,46,Masters,14,12,97,48,50,4.0,6,26,Urban,Software Engineer,39579,0 +31297,Male,39,Diploma,4,82,5,16,99,6.0,2,65,Urban,Software Engineer,137010,0 +31298,Male,54,Masters,14,42,64,70,65,5.0,5,43,Urban,Data Analyst,58212,0 +31299,Male,26,Bachelors,1,48,61,41,99,1.0,0,45,Rural,HR Executive,107018,0 +31300,Male,22,Masters,16,11,14,95,81,5.0,1,81,Rural,ML Engineer,129318,0 +31301,Male,40,Masters,14,50,1,41,84,2.0,3,59,Rural,Data Analyst,42044,0 +31302,Female,25,High School,3,71,74,6,40,6.0,4,1,Rural,Data Analyst,75809,0 +31303,Female,47,Diploma,17,42,72,59,83,0.0,0,5,Semi-Urban,Manager,47710,0 +31304,Female,35,Bachelors,18,94,66,32,90,3.0,0,98,Urban,Data Analyst,136995,1 +31305,Male,56,Diploma,2,84,58,25,16,3.0,2,40,Urban,Manager,68067,0 +31306,Male,29,Bachelors,2,44,9,41,38,5.0,2,68,Urban,Manager,144134,0 +31307,Male,46,Diploma,14,1,61,0,46,4.0,7,61,Semi-Urban,ML Engineer,60895,0 +31308,Male,27,Diploma,2,39,15,17,18,2.0,3,17,Rural,Software Engineer,137195,0 +31309,Female,45,Masters,14,14,36,82,0,8.0,2,2,Rural,ML Engineer,125247,0 +31310,Male,57,Bachelors,7,26,36,39,97,1.0,2,97,Urban,Manager,74829,0 +31311,Female,48,Bachelors,0,62,37,99,79,5.0,7,79,Urban,HR Executive,128170,1 +31312,Female,21,Diploma,5,81,21,29,97,5.0,6,89,Semi-Urban,Data Analyst,54784,0 +31313,Male,24,Masters,0,28,44,27,43,3.0,0,57,Rural,Data Analyst,96076,0 +31314,Male,58,Bachelors,9,52,70,38,94,4.0,3,82,Urban,ML Engineer,88213,1 +31315,Female,57,High School,3,25,90,51,67,7.0,6,38,Urban,Manager,44748,0 +31316,Female,48,Bachelors,11,68,47,16,78,9.0,0,41,Semi-Urban,Software Engineer,23950,0 +31317,Female,31,Diploma,10,54,2,52,56,9.0,1,96,Urban,HR Executive,38037,0 +31318,Female,44,Bachelors,1,74,61,82,20,6.0,2,23,Urban,Manager,146507,0 +31319,Male,53,PhD,19,97,50,45,55,1.0,7,20,Semi-Urban,Software Engineer,61512,0 +31320,Male,30,Diploma,14,34,33,17,14,3.0,2,6,Urban,HR Executive,87054,0 +31321,Male,33,Bachelors,9,79,15,1,43,0.0,4,12,Rural,Data Analyst,125697,0 +31322,Male,22,Diploma,2,67,51,99,70,0.0,2,97,Rural,Software Engineer,25006,1 +31323,Male,54,High School,14,48,44,75,91,8.0,3,99,Rural,HR Executive,91491,1 +31324,Male,29,High School,12,62,68,25,88,1.0,3,30,Urban,ML Engineer,76624,0 +31325,Female,21,Masters,14,48,20,38,69,3.0,0,50,Semi-Urban,ML Engineer,40638,0 +31326,Male,55,Diploma,6,72,27,72,45,3.0,7,33,Rural,Software Engineer,26091,0 +31327,Male,24,Bachelors,15,11,12,65,19,3.0,7,71,Urban,Data Analyst,130820,0 +31328,Male,47,Masters,18,91,96,26,62,1.0,5,91,Urban,ML Engineer,101663,1 +31329,Male,49,Bachelors,14,60,64,61,96,0.0,4,19,Urban,HR Executive,127050,0 +31330,Male,22,Bachelors,15,46,25,85,33,9.0,6,23,Rural,Manager,45846,0 +31331,Female,23,Bachelors,14,61,64,65,65,0.0,6,23,Semi-Urban,HR Executive,131651,0 +31332,Female,38,Bachelors,14,58,32,42,72,7.0,6,22,Urban,Software Engineer,109326,0 +31333,Male,39,Bachelors,17,27,38,97,59,1.0,3,18,Urban,Data Analyst,84943,0 +31334,Male,30,High School,16,52,58,90,7,1.0,2,3,Urban,HR Executive,82488,0 +31335,Female,43,Masters,4,52,86,97,61,1.0,5,79,Rural,Software Engineer,28799,1 +31336,Male,40,Bachelors,17,73,3,72,55,5.0,1,70,Urban,Software Engineer,49854,0 +31337,Male,49,Bachelors,5,13,37,78,98,8.0,0,73,Urban,ML Engineer,65732,0 +31338,Male,25,Bachelors,16,46,77,94,97,3.0,7,72,Rural,Data Analyst,53012,1 +31339,Female,49,Masters,14,92,41,82,97,0.0,5,27,Semi-Urban,HR Executive,34737,1 +31340,Male,42,Bachelors,19,58,98,29,67,1.0,3,20,Urban,Manager,148081,0 +31341,Female,32,Bachelors,2,66,21,79,74,7.0,6,84,Semi-Urban,Data Analyst,99095,1 +31342,Male,33,Bachelors,14,24,59,90,37,7.0,3,96,Semi-Urban,HR Executive,127298,1 +31343,Male,45,Diploma,12,5,35,16,52,5.0,6,77,Semi-Urban,ML Engineer,85312,0 +31344,Female,43,Diploma,14,83,75,73,79,7.0,6,10,Rural,HR Executive,113495,1 +31345,Male,50,Diploma,1,77,56,43,15,6.0,1,31,Urban,Data Analyst,28869,0 +31346,Male,57,High School,1,44,13,93,41,1.0,0,22,Urban,Data Analyst,139914,0 +31347,Male,42,Bachelors,17,72,91,25,76,7.0,0,51,Urban,Software Engineer,24259,1 +31348,Male,58,Bachelors,16,42,22,51,28,3.0,5,71,Semi-Urban,Software Engineer,119368,0 +31349,Male,26,Masters,19,25,23,90,12,2.0,7,68,Semi-Urban,Manager,67706,0 +31350,Female,21,Bachelors,18,58,62,64,29,1.0,7,54,Semi-Urban,HR Executive,39304,0 +31351,Female,26,Diploma,16,75,37,87,60,0.0,3,67,Urban,Manager,87090,1 +31352,Other,45,Bachelors,1,24,5,63,47,2.0,5,91,Semi-Urban,Software Engineer,28584,0 +31353,Female,30,Masters,17,86,30,84,7,9.0,0,10,Urban,Manager,27284,0 +31354,Female,29,Diploma,2,84,52,72,90,4.0,0,90,Urban,HR Executive,134815,1 +31355,Female,38,Bachelors,11,74,36,59,16,9.0,5,14,Urban,Manager,113222,0 +31356,Female,57,Diploma,2,1,53,37,98,8.0,5,87,Urban,Software Engineer,118494,0 +31357,Male,52,High School,6,94,41,26,3,7.0,0,94,Semi-Urban,HR Executive,145385,1 +31358,Male,54,Bachelors,10,28,14,1,68,9.0,2,25,Urban,Software Engineer,135846,0 +31359,Female,29,PhD,17,58,74,41,25,5.0,6,63,Semi-Urban,Software Engineer,102736,0 +31360,Male,56,Masters,17,39,31,4,34,0.0,2,74,Urban,Data Analyst,65522,0 +31361,Female,24,Bachelors,0,19,55,69,23,9.0,5,16,Rural,ML Engineer,92226,0 +31362,Male,51,High School,7,75,51,30,1,9.0,0,70,Rural,HR Executive,53026,0 +31363,Male,43,Bachelors,17,51,73,23,5,7.0,7,95,Urban,Data Analyst,64884,1 +31364,Female,26,Bachelors,4,79,27,57,22,5.0,4,84,Urban,Software Engineer,92430,1 +31365,Male,29,Masters,3,33,87,67,86,5.0,0,79,Rural,ML Engineer,147203,1 +31366,Other,41,Diploma,18,99,32,64,29,1.0,5,79,Semi-Urban,Software Engineer,70085,1 +31367,Other,51,Bachelors,6,13,5,90,82,0.0,1,70,Urban,Software Engineer,34041,0 +31368,Female,59,Diploma,1,50,89,4,22,2.0,2,55,Urban,ML Engineer,102667,0 +31369,Male,45,High School,11,5,5,94,91,0.0,5,73,Rural,HR Executive,28005,0 +31370,Male,39,Masters,0,63,14,54,96,9.0,1,8,Urban,Data Analyst,123643,0 +31371,Male,38,Bachelors,1,30,34,26,75,2.0,2,88,Urban,HR Executive,127715,0 +31372,Female,41,Bachelors,11,63,15,73,40,1.0,5,90,Urban,Manager,46370,1 +31373,Male,43,High School,12,62,58,54,73,5.0,6,89,Semi-Urban,Data Analyst,49464,1 +31374,Male,33,Diploma,10,6,32,2,19,7.0,3,77,Semi-Urban,Software Engineer,98355,0 +31375,Male,25,PhD,17,76,88,24,88,1.0,0,78,Urban,Manager,29104,1 +31376,Male,38,Bachelors,4,94,48,54,64,9.0,7,39,Urban,ML Engineer,63745,1 +31377,Female,45,Diploma,13,79,67,18,77,4.0,5,38,Rural,Data Analyst,143811,0 +31378,Male,32,High School,8,94,66,27,55,2.0,5,28,Urban,Software Engineer,144602,0 +31379,Male,25,Bachelors,9,2,53,32,93,0.0,5,16,Rural,Manager,66326,0 +31380,Female,32,Bachelors,10,99,8,35,88,4.0,2,61,Urban,HR Executive,62851,0 +31381,Female,21,Masters,5,98,83,88,31,2.0,4,36,Urban,Data Analyst,142162,1 +31382,Female,49,Bachelors,1,25,38,89,65,3.0,0,38,Semi-Urban,Data Analyst,145672,0 +31383,Female,46,Bachelors,8,50,55,96,43,3.0,7,5,Urban,Software Engineer,97343,0 +31384,Male,53,Masters,10,72,26,96,91,4.0,0,21,Urban,Data Analyst,44084,0 +31385,Male,37,Bachelors,1,70,49,58,5,2.0,4,16,Rural,HR Executive,119927,0 +31386,Other,55,Diploma,5,90,25,15,59,7.0,3,17,Urban,Data Analyst,107942,0 +31387,Other,55,Bachelors,8,52,1,59,23,9.0,6,92,Urban,Manager,24254,0 +31388,Female,24,Bachelors,7,4,31,4,54,0.0,4,26,Semi-Urban,Software Engineer,50657,0 +31389,Female,41,Bachelors,4,3,86,57,40,3.0,0,25,Urban,Manager,124973,0 +31390,Other,55,Diploma,11,53,82,96,68,2.0,4,25,Urban,Manager,68904,1 +31391,Male,29,Masters,11,46,93,64,51,1.0,0,56,Rural,Manager,24656,1 +31392,Male,58,Bachelors,0,95,82,48,99,2.0,0,30,Semi-Urban,ML Engineer,63414,1 +31393,Female,28,Masters,12,1,36,16,63,0.0,6,42,Urban,Data Analyst,132026,0 +31394,Other,24,Bachelors,13,85,76,32,85,4.0,7,31,Semi-Urban,Manager,112268,0 +31395,Female,28,Masters,5,60,4,4,52,4.0,0,81,Semi-Urban,Data Analyst,67551,0 +31396,Female,43,Masters,9,39,17,90,65,7.0,3,88,Urban,Data Analyst,44531,0 +31397,Male,42,High School,9,85,61,31,72,8.0,2,29,Urban,Manager,125044,0 +31398,Male,22,Bachelors,8,44,34,85,44,6.0,0,93,Urban,Software Engineer,46899,1 +31399,Male,56,Bachelors,12,88,17,8,27,5.0,7,2,Rural,HR Executive,33112,0 +31400,Other,34,Bachelors,15,27,53,55,17,6.0,0,71,Rural,ML Engineer,113529,0 +31401,Male,56,Masters,4,43,45,71,72,0.0,7,85,Semi-Urban,Software Engineer,33284,1 +31402,Male,42,High School,5,16,7,16,24,3.0,1,55,Urban,Manager,117346,0 +31403,Other,53,Masters,4,74,86,78,85,4.0,5,25,Urban,Data Analyst,87100,1 +31404,Male,59,Bachelors,6,72,40,89,71,5.0,3,29,Rural,Software Engineer,108731,0 +31405,Female,43,Bachelors,7,16,94,38,61,0.0,5,59,Semi-Urban,Manager,129976,0 +31406,Male,43,High School,11,9,97,98,14,3.0,2,12,Urban,HR Executive,65440,0 +31407,Male,33,Masters,10,86,77,8,87,6.0,7,64,Semi-Urban,Manager,125999,1 +31408,Female,21,Diploma,13,86,6,2,49,9.0,7,63,Rural,HR Executive,79209,0 +31409,Other,39,Bachelors,0,4,92,88,11,3.0,4,41,Rural,ML Engineer,89105,0 +31410,Male,54,Bachelors,17,36,70,68,33,2.0,5,79,Semi-Urban,Data Analyst,75121,1 +31411,Female,58,High School,15,46,66,97,19,1.0,7,54,Urban,ML Engineer,98214,1 +31412,Male,44,Diploma,16,78,18,96,18,0.0,7,87,Semi-Urban,Data Analyst,20663,1 +31413,Male,57,Diploma,0,54,57,72,18,4.0,1,27,Urban,Data Analyst,134635,0 +31414,Male,21,Bachelors,5,27,63,1,27,1.0,6,76,Urban,HR Executive,88234,0 +31415,Female,25,High School,3,62,45,35,84,9.0,5,66,Rural,Data Analyst,48269,0 +31416,Male,27,Diploma,19,66,2,77,20,8.0,1,77,Rural,Data Analyst,93731,0 +31417,Male,48,PhD,17,68,51,46,85,9.0,1,12,Urban,ML Engineer,118088,0 +31418,Female,21,Bachelors,7,19,21,96,71,7.0,7,87,Urban,ML Engineer,117813,0 +31419,Male,33,High School,17,90,64,7,72,7.0,7,51,Urban,Manager,110996,0 +31420,Male,27,Bachelors,19,92,48,15,87,9.0,5,99,Rural,ML Engineer,133747,1 +31421,Male,42,Bachelors,19,18,18,44,15,1.0,5,87,Semi-Urban,HR Executive,34428,0 +31422,Female,41,Diploma,1,0,62,3,99,2.0,3,25,Urban,HR Executive,110549,0 +31423,Male,36,Bachelors,14,89,3,50,1,8.0,0,5,Urban,Software Engineer,52926,0 +31424,Female,33,Masters,16,77,74,42,65,3.0,7,39,Semi-Urban,Software Engineer,33497,0 +31425,Male,35,High School,15,67,14,81,18,3.0,7,70,Urban,Software Engineer,126083,0 +31426,Male,40,High School,7,27,82,11,92,3.0,2,93,Urban,HR Executive,111399,0 +31427,Female,51,Masters,6,21,37,23,42,4.0,0,28,Urban,Software Engineer,70522,0 +31428,Male,43,Masters,15,21,39,84,69,0.0,5,98,Rural,HR Executive,57217,1 +31429,Female,41,Masters,8,90,42,10,11,0.0,6,35,Urban,Software Engineer,24112,0 +31430,Male,39,Masters,18,32,12,15,45,1.0,5,63,Urban,Data Analyst,122221,0 +31431,Male,40,Bachelors,7,53,77,2,60,7.0,1,81,Urban,HR Executive,39440,0 +31432,Male,51,Masters,8,66,60,24,85,4.0,4,67,Semi-Urban,ML Engineer,42338,0 +31433,Male,29,Masters,2,49,37,86,6,6.0,3,36,Urban,Manager,72250,0 +31434,Male,25,Diploma,14,59,72,94,0,8.0,2,10,Urban,HR Executive,22727,1 +31435,Male,59,High School,11,64,30,14,94,7.0,4,14,Urban,ML Engineer,149025,0 +31436,Male,34,High School,8,55,23,3,71,2.0,6,17,Urban,ML Engineer,135270,0 +31437,Male,59,Masters,6,94,81,14,77,5.0,2,4,Semi-Urban,Manager,64323,0 +31438,Male,30,Masters,7,98,64,22,29,9.0,0,31,Urban,Manager,39430,0 +31439,Male,52,Bachelors,2,72,38,51,92,3.0,1,23,Semi-Urban,HR Executive,111806,0 +31440,Male,26,Bachelors,2,31,26,93,15,0.0,1,99,Semi-Urban,Manager,138384,1 +31441,Male,47,Diploma,8,60,15,99,95,0.0,0,27,Semi-Urban,ML Engineer,80402,0 +31442,Male,22,Bachelors,14,17,67,62,58,3.0,7,31,Urban,Software Engineer,32978,0 +31443,Female,40,Bachelors,10,14,21,47,29,9.0,2,39,Urban,Manager,70930,0 +31444,Female,40,Diploma,19,63,89,73,71,2.0,0,29,Urban,Software Engineer,77788,1 +31445,Male,23,Diploma,0,41,91,33,32,0.0,0,64,Semi-Urban,Software Engineer,118319,0 +31446,Male,53,High School,13,51,36,30,36,0.0,0,88,Urban,ML Engineer,100130,0 +31447,Male,28,Masters,8,14,20,41,90,2.0,7,29,Urban,Manager,45717,0 +31448,Female,26,Bachelors,4,75,11,92,36,4.0,2,52,Urban,Manager,112438,0 +31449,Male,42,Diploma,17,51,33,79,97,9.0,2,32,Urban,Manager,90639,0 +31450,Male,34,Masters,3,79,40,8,22,9.0,6,50,Rural,Data Analyst,68008,0 +31451,Male,46,Masters,13,20,36,30,52,1.0,3,91,Semi-Urban,HR Executive,35113,0 +31452,Female,56,Bachelors,14,91,77,65,28,9.0,0,3,Urban,Software Engineer,28655,0 +31453,Female,57,High School,11,94,63,49,1,6.0,4,15,Urban,HR Executive,23310,0 +31454,Male,59,Bachelors,11,61,69,43,18,4.0,6,71,Semi-Urban,HR Executive,52810,1 +31455,Male,49,High School,0,4,22,77,17,7.0,7,74,Semi-Urban,Software Engineer,68427,0 +31456,Female,21,Masters,9,65,50,81,39,0.0,0,82,Urban,HR Executive,104405,1 +31457,Male,54,Masters,3,29,17,12,76,0.0,2,51,Urban,Manager,60100,0 +31458,Male,33,Bachelors,13,74,50,17,62,2.0,0,95,Rural,Data Analyst,112891,1 +31459,Female,27,Bachelors,15,46,62,92,8,3.0,4,57,Urban,Software Engineer,51671,1 +31460,Male,29,Masters,4,23,83,85,5,4.0,4,14,Semi-Urban,Software Engineer,94797,0 +31461,Male,37,Diploma,13,19,20,73,13,8.0,3,14,Urban,Software Engineer,82992,0 +31462,Male,42,High School,1,47,26,27,89,4.0,5,85,Urban,Data Analyst,35100,0 +31463,Female,31,Diploma,0,25,99,10,75,7.0,7,72,Urban,HR Executive,138509,0 +31464,Male,24,High School,2,49,55,12,33,4.0,0,7,Semi-Urban,Manager,70858,0 +31465,Female,50,Diploma,3,62,89,27,81,6.0,1,64,Semi-Urban,Manager,68120,1 +31466,Male,41,PhD,0,8,56,49,54,2.0,7,77,Semi-Urban,ML Engineer,23207,0 +31467,Female,38,Bachelors,3,6,91,60,12,0.0,4,13,Semi-Urban,HR Executive,104604,0 +31468,Female,45,Diploma,18,30,28,30,89,7.0,7,46,Rural,Software Engineer,132054,0 +31469,Male,39,Masters,8,37,13,77,39,3.0,5,60,Urban,HR Executive,92111,0 +31470,Male,49,Diploma,18,1,26,11,57,0.0,2,43,Rural,Data Analyst,25188,0 +31471,Female,36,Bachelors,17,20,86,90,90,1.0,3,21,Semi-Urban,Manager,68001,0 +31472,Female,30,Diploma,3,82,14,8,36,7.0,2,24,Urban,ML Engineer,133942,0 +31473,Male,59,PhD,16,61,91,10,99,9.0,0,5,Rural,Manager,123729,0 +31474,Female,53,Bachelors,5,90,99,23,36,8.0,6,17,Rural,Manager,23269,0 +31475,Male,42,Bachelors,10,4,69,10,43,8.0,7,46,Urban,Software Engineer,54479,0 +31476,Male,25,Bachelors,1,90,88,95,34,7.0,7,49,Urban,ML Engineer,90236,1 +31477,Female,24,Bachelors,11,77,83,92,44,8.0,3,49,Urban,Software Engineer,132202,1 +31478,Male,37,Bachelors,11,69,63,11,10,3.0,2,46,Urban,Software Engineer,71294,0 +31479,Male,48,Bachelors,3,15,54,92,36,3.0,4,73,Urban,Data Analyst,130061,0 +31480,Other,35,Masters,5,54,27,55,38,5.0,4,90,Semi-Urban,HR Executive,38897,0 +31481,Female,54,Bachelors,6,19,50,26,20,4.0,7,46,Semi-Urban,Software Engineer,89058,0 +31482,Female,28,Masters,12,77,25,32,85,6.0,7,86,Urban,Software Engineer,90814,0 +31483,Female,59,Masters,2,56,47,68,24,3.0,1,83,Semi-Urban,ML Engineer,22629,1 +31484,Female,33,High School,12,64,64,49,59,0.0,2,91,Semi-Urban,Data Analyst,29021,1 +31485,Male,40,PhD,11,89,9,10,11,5.0,1,44,Semi-Urban,Manager,76230,0 +31486,Male,53,Masters,18,46,68,0,13,1.0,7,3,Urban,Data Analyst,28874,0 +31487,Male,52,Masters,5,10,0,73,21,7.0,0,76,Semi-Urban,Software Engineer,129460,0 +31488,Male,38,PhD,15,64,13,60,18,8.0,5,18,Rural,HR Executive,66394,0 +31489,Other,41,Diploma,13,16,14,8,79,3.0,0,23,Rural,HR Executive,105995,0 +31490,Male,31,Bachelors,0,96,26,71,73,4.0,1,17,Semi-Urban,Manager,105045,0 +31491,Male,31,Bachelors,16,69,13,31,60,7.0,5,78,Semi-Urban,HR Executive,64290,0 +31492,Female,29,Diploma,10,36,45,90,95,9.0,2,72,Semi-Urban,Software Engineer,100358,1 +31493,Male,36,Masters,3,67,65,16,3,5.0,5,46,Semi-Urban,ML Engineer,110133,0 +31494,Male,58,Diploma,14,49,77,87,44,0.0,4,87,Urban,ML Engineer,99476,1 +31495,Male,48,Bachelors,17,89,78,44,61,7.0,0,38,Rural,Software Engineer,142032,1 +31496,Female,42,High School,6,29,69,14,66,9.0,2,74,Urban,HR Executive,112424,0 +31497,Male,59,High School,12,44,99,89,59,4.0,4,39,Semi-Urban,HR Executive,50230,1 +31498,Male,52,Diploma,7,0,46,8,17,7.0,4,34,Urban,Data Analyst,56292,0 +31499,Male,42,Bachelors,16,52,22,46,49,4.0,4,52,Urban,HR Executive,78182,0 +31500,Male,23,Bachelors,18,83,48,88,78,0.0,1,0,Rural,ML Engineer,117456,0 +31501,Male,50,Diploma,10,44,34,12,21,7.0,4,60,Semi-Urban,HR Executive,57055,0 +31502,Other,31,Bachelors,5,40,26,86,73,3.0,7,19,Urban,Data Analyst,139994,0 +31503,Male,43,Masters,2,73,91,69,50,3.0,2,94,Urban,HR Executive,108474,1 +31504,Male,33,Bachelors,15,61,99,73,48,8.0,2,39,Rural,Software Engineer,51059,1 +31505,Other,46,High School,18,96,23,40,87,3.0,6,5,Urban,Manager,86958,0 +31506,Female,46,Bachelors,19,29,64,25,59,8.0,1,24,Urban,HR Executive,94974,0 +31507,Male,39,Masters,9,76,73,4,30,0.0,3,79,Rural,Data Analyst,114445,0 +31508,Male,53,Bachelors,17,3,43,75,41,6.0,5,36,Urban,Data Analyst,88925,0 +31509,Female,41,Bachelors,1,85,28,76,7,2.0,1,29,Semi-Urban,ML Engineer,51063,0 +31510,Male,55,Bachelors,9,6,0,34,26,9.0,6,63,Rural,HR Executive,103150,0 +31511,Male,44,High School,17,85,60,53,67,5.0,3,54,Urban,ML Engineer,63988,1 +31512,Male,42,High School,0,13,57,2,92,7.0,2,92,Urban,Data Analyst,53678,0 +31513,Male,34,Bachelors,0,42,51,16,41,3.0,3,98,Urban,Manager,56276,0 +31514,Female,55,High School,8,68,81,38,84,0.0,5,17,Rural,Software Engineer,35138,0 +31515,Male,25,Diploma,19,80,94,32,68,2.0,1,74,Rural,ML Engineer,123101,1 +31516,Male,42,Diploma,11,19,44,66,92,9.0,1,87,Urban,Manager,76245,0 +31517,Female,45,Diploma,8,91,65,87,4,0.0,3,57,Rural,ML Engineer,27432,1 +31518,Male,54,Masters,7,7,67,91,47,4.0,6,90,Urban,HR Executive,128688,1 +31519,Male,54,Bachelors,8,12,33,60,82,9.0,2,95,Urban,HR Executive,96110,0 +31520,Male,35,Bachelors,15,67,46,90,23,9.0,0,66,Rural,Software Engineer,118365,1 +31521,Female,30,Diploma,2,40,79,63,41,8.0,0,84,Urban,Data Analyst,58905,1 +31522,Male,56,Bachelors,10,19,99,18,57,6.0,7,87,Urban,HR Executive,109796,0 +31523,Female,31,Masters,2,47,55,36,54,4.0,1,33,Urban,HR Executive,114830,0 +31524,Male,24,High School,6,36,77,62,4,6.0,3,20,Urban,Software Engineer,55643,0 +31525,Female,28,Bachelors,19,81,8,27,43,5.0,6,44,Semi-Urban,ML Engineer,69311,0 +31526,Female,31,Masters,19,46,53,38,55,6.0,2,95,Urban,ML Engineer,33594,0 +31527,Female,49,Bachelors,14,93,4,91,9,1.0,6,78,Semi-Urban,ML Engineer,42694,1 +31528,Male,46,High School,6,73,39,46,2,3.0,0,79,Urban,Manager,83701,1 +31529,Male,51,Diploma,6,36,57,77,59,6.0,4,86,Urban,Data Analyst,131338,1 +31530,Male,45,Bachelors,3,39,42,30,8,0.0,7,30,Urban,HR Executive,69071,0 +31531,Male,54,Masters,4,15,37,96,75,1.0,1,26,Urban,Manager,127822,0 +31532,Male,31,Bachelors,2,98,90,40,64,4.0,2,93,Rural,Software Engineer,57791,1 +31533,Male,47,Masters,2,84,93,65,35,7.0,5,87,Urban,ML Engineer,32859,1 +31534,Other,33,Masters,18,91,84,20,92,9.0,2,55,Urban,Data Analyst,44847,1 +31535,Female,21,Bachelors,16,48,88,91,86,9.0,5,63,Urban,Software Engineer,149786,1 +31536,Male,30,Diploma,10,31,21,12,73,8.0,0,16,Urban,HR Executive,129518,0 +31537,Male,58,Bachelors,12,4,28,59,58,2.0,1,55,Semi-Urban,Manager,33199,0 +31538,Female,33,Diploma,15,43,61,67,48,8.0,5,88,Semi-Urban,Manager,90651,1 +31539,Male,58,Bachelors,15,12,67,17,81,3.0,6,89,Urban,Data Analyst,106134,0 +31540,Male,22,Diploma,3,72,72,96,35,7.0,1,40,Urban,Manager,86648,1 +31541,Male,21,Diploma,1,83,67,74,25,5.0,0,31,Semi-Urban,HR Executive,143410,1 +31542,Male,22,Bachelors,13,81,40,17,2,1.0,6,83,Urban,HR Executive,46035,0 +31543,Female,52,Diploma,5,2,79,49,0,3.0,5,80,Urban,ML Engineer,126057,0 +31544,Other,32,High School,2,72,28,68,12,8.0,0,19,Rural,Manager,40283,0 +31545,Male,59,Masters,15,85,69,43,9,1.0,3,50,Rural,Data Analyst,52176,1 +31546,Male,53,Bachelors,8,93,57,9,37,4.0,7,28,Urban,Software Engineer,58099,0 +31547,Male,56,High School,13,51,99,9,37,9.0,3,6,Urban,Data Analyst,32220,0 +31548,Female,41,Diploma,3,21,17,49,67,3.0,3,8,Semi-Urban,Data Analyst,27518,0 +31549,Female,59,Bachelors,19,91,9,88,7,5.0,5,2,Rural,ML Engineer,97626,0 +31550,Male,25,Diploma,0,71,5,28,73,4.0,2,32,Urban,Data Analyst,101649,0 +31551,Female,36,Masters,12,32,17,27,80,0.0,2,4,Rural,Data Analyst,126106,0 +31552,Male,34,Diploma,12,41,74,24,80,0.0,3,46,Rural,HR Executive,81392,0 +31553,Male,32,High School,0,77,95,79,22,1.0,7,31,Urban,Manager,86886,1 +31554,Female,55,Bachelors,9,82,24,92,72,7.0,3,61,Urban,Data Analyst,35453,1 +31555,Male,23,Bachelors,9,0,85,15,18,7.0,7,15,Urban,Software Engineer,145561,0 +31556,Male,40,Bachelors,2,95,73,3,19,1.0,3,25,Semi-Urban,Manager,59088,0 +31557,Female,57,Masters,18,89,6,54,43,6.0,5,55,Urban,ML Engineer,48328,0 +31558,Male,29,High School,6,19,63,59,63,8.0,0,50,Rural,HR Executive,73689,0 +31559,Male,28,Bachelors,3,85,39,71,75,9.0,0,91,Rural,HR Executive,145151,1 +31560,Male,37,Diploma,1,74,79,42,36,9.0,7,15,Urban,Manager,98588,0 +31561,Male,52,Bachelors,10,52,28,4,35,7.0,5,4,Rural,ML Engineer,105226,0 +31562,Male,48,Diploma,12,73,6,47,39,4.0,5,65,Semi-Urban,HR Executive,60976,0 +31563,Male,59,High School,14,73,33,54,51,1.0,6,99,Urban,ML Engineer,94531,1 +31564,Female,33,Diploma,3,35,70,9,94,9.0,2,77,Urban,Manager,80443,0 +31565,Female,58,Diploma,9,48,9,98,98,7.0,4,94,Urban,ML Engineer,72307,1 +31566,Male,35,Diploma,2,24,66,13,31,0.0,3,49,Semi-Urban,ML Engineer,20697,0 +31567,Male,48,Bachelors,5,53,87,14,42,2.0,7,13,Urban,Manager,107428,0 +31568,Female,42,Masters,0,4,24,8,20,7.0,6,56,Urban,HR Executive,86589,0 +31569,Other,22,High School,10,61,71,50,45,3.0,6,87,Rural,ML Engineer,36941,1 +31570,Male,31,High School,17,14,24,61,52,0.0,1,43,Urban,Data Analyst,113111,0 +31571,Female,50,Bachelors,16,87,85,19,72,5.0,5,73,Urban,Data Analyst,94363,1 +31572,Male,40,Bachelors,6,51,66,73,82,0.0,3,69,Urban,Software Engineer,108197,1 +31573,Other,29,Diploma,10,32,20,81,87,7.0,1,65,Semi-Urban,Software Engineer,106447,0 +31574,Male,59,Bachelors,1,78,31,53,17,8.0,6,89,Rural,Data Analyst,79994,1 +31575,Other,22,Diploma,13,45,15,13,81,5.0,2,74,Urban,Software Engineer,22307,0 +31576,Male,55,Bachelors,13,13,93,51,10,8.0,2,99,Rural,HR Executive,143135,1 +31577,Other,29,Diploma,4,75,71,66,18,6.0,5,68,Rural,Manager,25520,1 +31578,Male,34,Diploma,6,79,93,40,82,8.0,0,22,Semi-Urban,Manager,40488,0 +31579,Male,34,Bachelors,11,75,58,39,62,1.0,5,1,Rural,Data Analyst,21552,0 +31580,Female,21,Bachelors,4,28,70,27,75,0.0,1,61,Urban,Software Engineer,78099,0 +31581,Female,32,High School,18,69,10,65,41,7.0,1,99,Urban,ML Engineer,149686,1 +31582,Female,55,Bachelors,12,21,63,1,42,8.0,2,62,Semi-Urban,Software Engineer,40629,0 +31583,Male,45,Bachelors,19,36,34,28,95,4.0,5,26,Urban,Manager,144758,0 +31584,Female,27,Masters,5,2,57,29,22,6.0,6,92,Urban,Manager,112285,0 +31585,Female,59,Diploma,19,39,48,77,20,7.0,2,29,Rural,Software Engineer,109754,0 +31586,Male,55,PhD,0,42,17,86,2,5.0,4,15,Urban,ML Engineer,147664,0 +31587,Male,31,Masters,11,28,11,54,32,2.0,3,19,Urban,ML Engineer,79706,0 +31588,Female,27,PhD,18,90,74,73,73,3.0,1,21,Semi-Urban,Data Analyst,28773,1 +31589,Female,43,Bachelors,14,24,85,2,78,3.0,3,15,Urban,Data Analyst,112649,0 +31590,Female,44,Masters,17,67,70,45,24,1.0,0,27,Urban,Data Analyst,116558,0 +31591,Female,21,Bachelors,1,20,16,15,77,1.0,3,80,Semi-Urban,HR Executive,30267,0 +31592,Female,56,Masters,19,6,76,20,82,5.0,4,82,Rural,Manager,74716,0 +31593,Female,30,Masters,5,48,10,51,74,1.0,4,91,Rural,Software Engineer,22008,0 +31594,Other,33,Bachelors,14,20,1,94,11,1.0,4,29,Urban,Software Engineer,57071,0 +31595,Female,51,PhD,1,4,36,33,42,9.0,2,4,Rural,ML Engineer,121516,0 +31596,Female,31,Bachelors,14,40,70,77,3,1.0,1,3,Urban,ML Engineer,27059,0 +31597,Male,52,Masters,11,64,34,51,0,8.0,4,83,Semi-Urban,Data Analyst,109803,0 +31598,Male,43,Masters,12,1,55,78,97,9.0,6,44,Urban,Software Engineer,76126,0 +31599,Male,51,Masters,2,13,79,53,19,5.0,5,54,Urban,HR Executive,128874,0 +31600,Female,55,Diploma,4,60,6,98,19,6.0,3,49,Urban,Manager,53800,0 +31601,Male,50,High School,12,52,8,19,70,9.0,6,78,Urban,Manager,104778,0 +31602,Male,34,Diploma,5,63,21,90,88,3.0,5,35,Rural,ML Engineer,120658,0 +31603,Male,48,Diploma,12,86,79,96,18,3.0,2,19,Rural,Manager,40846,1 +31604,Female,34,Bachelors,13,30,74,46,61,4.0,1,28,Semi-Urban,Software Engineer,70830,0 +31605,Female,41,Bachelors,12,91,76,82,34,4.0,0,50,Rural,Software Engineer,88066,1 +31606,Female,39,Masters,11,38,70,40,36,4.0,7,45,Urban,Manager,59606,0 +31607,Male,36,Bachelors,1,2,18,28,42,8.0,4,27,Rural,Software Engineer,117448,0 +31608,Male,59,Diploma,12,5,52,55,24,3.0,1,32,Rural,Software Engineer,89661,0 +31609,Male,55,Bachelors,18,83,25,38,9,2.0,2,56,Urban,ML Engineer,30401,0 +31610,Male,23,Masters,6,3,93,18,15,9.0,1,2,Urban,HR Executive,137039,0 +31611,Female,25,Masters,0,80,70,63,64,6.0,6,34,Urban,HR Executive,130474,1 +31612,Male,57,Masters,2,98,35,18,1,2.0,4,45,Urban,Manager,47488,0 +31613,Male,46,Masters,2,2,70,81,94,0.0,4,53,Rural,ML Engineer,96375,0 +31614,Male,48,Bachelors,18,84,56,1,65,0.0,0,19,Semi-Urban,ML Engineer,87580,0 +31615,Male,48,Diploma,8,21,21,90,92,6.0,4,11,Rural,Manager,55934,0 +31616,Male,33,Bachelors,3,19,75,76,50,2.0,0,9,Urban,Data Analyst,149773,0 +31617,Male,46,Diploma,16,63,64,53,3,3.0,6,9,Urban,ML Engineer,25094,0 +31618,Male,54,Diploma,1,57,99,48,95,0.0,5,83,Urban,ML Engineer,96718,1 +31619,Male,24,Bachelors,2,79,76,85,82,9.0,4,2,Semi-Urban,HR Executive,57388,1 +31620,Male,42,Bachelors,16,0,50,34,71,5.0,6,30,Urban,Data Analyst,36151,0 +31621,Female,53,Bachelors,9,53,7,23,92,5.0,0,66,Urban,Software Engineer,36470,0 +31622,Other,27,Masters,11,71,16,89,37,1.0,4,60,Semi-Urban,Software Engineer,105000,0 +31623,Male,29,Diploma,2,3,28,5,82,0.0,5,58,Semi-Urban,Manager,77890,0 +31624,Female,41,Bachelors,5,88,48,59,47,3.0,6,68,Semi-Urban,ML Engineer,87772,1 +31625,Female,37,Diploma,2,84,99,11,73,6.0,1,78,Urban,Data Analyst,33416,1 +31626,Male,54,Bachelors,15,64,56,69,91,6.0,5,28,Rural,ML Engineer,32339,0 +31627,Male,25,Bachelors,19,80,31,52,96,0.0,0,11,Rural,Manager,67769,0 +31628,Male,59,High School,2,67,98,47,75,3.0,3,43,Rural,Manager,137095,1 +31629,Male,58,Masters,1,67,13,14,17,1.0,7,67,Rural,Data Analyst,115988,0 +31630,Female,30,Diploma,11,12,20,46,9,3.0,3,46,Semi-Urban,Software Engineer,57421,0 +31631,Male,45,Bachelors,9,57,18,76,8,2.0,1,58,Semi-Urban,Manager,142248,0 +31632,Female,30,Diploma,17,80,69,10,72,7.0,4,28,Urban,Data Analyst,133262,0 +31633,Male,56,High School,4,21,6,81,14,6.0,5,58,Urban,Software Engineer,105725,0 +31634,Female,41,Bachelors,18,67,41,77,44,7.0,3,16,Semi-Urban,Software Engineer,113285,0 +31635,Female,33,Masters,8,47,84,76,12,5.0,1,42,Rural,Manager,20060,1 +31636,Other,39,Bachelors,4,19,18,50,4,5.0,0,74,Semi-Urban,Software Engineer,48498,0 +31637,Female,41,Bachelors,10,82,22,10,43,1.0,1,9,Urban,Data Analyst,33418,0 +31638,Male,59,Diploma,9,12,86,12,5,4.0,1,42,Rural,Manager,76776,0 +31639,Female,50,Bachelors,3,41,37,11,89,1.0,6,25,Rural,HR Executive,99452,0 +31640,Male,32,Diploma,13,42,71,19,92,0.0,5,20,Urban,Data Analyst,89276,0 +31641,Female,58,Masters,15,26,47,2,32,4.0,0,76,Urban,HR Executive,30096,0 +31642,Male,24,Bachelors,15,3,83,59,82,6.0,0,44,Rural,ML Engineer,137017,0 +31643,Male,44,Bachelors,14,99,67,1,17,3.0,3,84,Urban,Manager,145308,1 +31644,Female,51,Diploma,12,43,27,54,93,2.0,7,25,Urban,Software Engineer,37410,0 +31645,Male,45,Diploma,17,26,98,63,28,0.0,5,40,Urban,Manager,146173,0 +31646,Male,39,High School,3,31,75,2,53,6.0,1,82,Rural,Manager,129448,0 +31647,Male,38,Masters,10,77,58,50,70,6.0,7,23,Urban,ML Engineer,66081,0 +31648,Female,58,Masters,12,20,58,66,71,6.0,5,49,Urban,Software Engineer,82472,0 +31649,Female,38,High School,17,43,33,25,68,1.0,2,13,Semi-Urban,HR Executive,26833,0 +31650,Female,44,Bachelors,7,9,89,88,66,3.0,0,6,Semi-Urban,Software Engineer,22323,0 +31651,Female,25,Masters,6,30,1,89,81,7.0,6,37,Urban,Manager,106631,0 +31652,Male,47,High School,3,82,88,19,1,2.0,1,32,Urban,Software Engineer,112891,0 +31653,Male,43,Bachelors,2,26,73,42,31,9.0,4,87,Urban,ML Engineer,129188,0 +31654,Female,25,Masters,16,29,17,30,13,3.0,7,55,Rural,Manager,62363,0 +31655,Female,29,Bachelors,4,24,63,40,51,7.0,3,16,Urban,ML Engineer,65697,0 +31656,Male,27,Bachelors,7,82,70,0,56,7.0,6,71,Urban,Data Analyst,79881,0 +31657,Male,21,Masters,15,74,79,28,3,2.0,5,20,Urban,Software Engineer,82609,0 +31658,Male,32,Diploma,2,12,99,52,33,8.0,4,45,Rural,ML Engineer,48671,0 +31659,Male,57,Masters,15,71,31,16,94,1.0,0,27,Urban,HR Executive,145764,0 +31660,Male,47,Diploma,2,62,50,97,5,9.0,6,98,Urban,HR Executive,33442,1 +31661,Male,47,Bachelors,9,57,84,37,2,7.0,2,48,Urban,ML Engineer,128311,0 +31662,Male,58,High School,19,72,17,11,24,6.0,6,6,Urban,ML Engineer,135946,0 +31663,Male,28,Masters,0,37,94,20,53,8.0,2,54,Urban,Software Engineer,71729,0 +31664,Female,36,Bachelors,4,61,14,23,10,1.0,5,16,Urban,ML Engineer,58110,0 +31665,Female,41,Masters,7,70,59,47,36,1.0,1,14,Urban,ML Engineer,120368,0 +31666,Male,33,High School,0,51,50,68,69,2.0,3,1,Urban,HR Executive,96626,0 +31667,Male,44,Diploma,17,35,39,76,84,1.0,0,24,Urban,ML Engineer,23065,0 +31668,Other,54,Diploma,8,12,77,82,93,4.0,6,92,Rural,Manager,122758,1 +31669,Male,37,Diploma,6,10,36,86,37,9.0,3,89,Urban,HR Executive,67364,0 +31670,Other,45,Masters,12,89,26,92,60,7.0,6,30,Urban,Data Analyst,113669,0 +31671,Male,32,Bachelors,6,54,62,75,37,8.0,0,96,Urban,Data Analyst,135495,1 +31672,Female,45,Diploma,9,27,55,65,92,3.0,2,56,Urban,Data Analyst,51458,0 +31673,Male,44,Masters,8,44,10,96,79,4.0,0,31,Urban,HR Executive,129123,0 +31674,Male,42,High School,10,1,32,55,42,8.0,5,63,Semi-Urban,Data Analyst,41692,0 +31675,Other,49,Bachelors,5,35,30,88,83,5.0,1,60,Semi-Urban,Manager,116804,0 +31676,Other,52,Masters,0,15,62,62,40,2.0,7,86,Semi-Urban,Software Engineer,81076,0 +31677,Male,56,High School,16,63,69,37,70,2.0,7,80,Urban,Software Engineer,63636,1 +31678,Other,53,Bachelors,6,41,16,69,44,5.0,1,39,Urban,HR Executive,21092,0 +31679,Male,55,High School,4,5,76,11,83,0.0,1,90,Urban,Data Analyst,106101,0 +31680,Female,49,High School,5,67,82,23,97,5.0,6,29,Urban,ML Engineer,62106,0 +31681,Male,44,Bachelors,9,14,76,24,81,3.0,7,73,Semi-Urban,Manager,107534,0 +31682,Male,24,High School,11,61,92,72,79,0.0,2,91,Urban,HR Executive,45830,1 +31683,Female,33,Bachelors,4,25,43,25,24,5.0,5,30,Urban,ML Engineer,46571,0 +31684,Male,34,Bachelors,3,37,49,2,97,1.0,3,53,Semi-Urban,HR Executive,106529,0 +31685,Male,42,Bachelors,5,46,90,53,87,2.0,4,22,Semi-Urban,Software Engineer,110919,0 +31686,Male,50,Masters,18,80,36,12,97,7.0,6,92,Urban,HR Executive,100091,0 +31687,Male,22,Masters,8,74,43,39,8,8.0,6,6,Urban,Software Engineer,129811,0 +31688,Female,57,Bachelors,19,62,65,85,17,9.0,2,18,Urban,ML Engineer,134779,0 +31689,Male,50,Masters,1,42,10,5,79,1.0,3,90,Semi-Urban,Software Engineer,87083,0 +31690,Female,59,Masters,17,11,92,95,72,6.0,2,40,Urban,HR Executive,66849,0 +31691,Male,47,High School,15,63,78,48,23,1.0,0,9,Urban,Data Analyst,59752,0 +31692,Male,23,Masters,12,46,35,0,15,6.0,6,1,Semi-Urban,ML Engineer,89007,0 +31693,Male,46,Masters,7,79,3,29,9,2.0,4,30,Rural,Software Engineer,46669,0 +31694,Female,33,Bachelors,16,96,72,73,66,5.0,7,36,Urban,ML Engineer,94733,1 +31695,Male,49,Diploma,5,5,24,39,53,4.0,7,78,Urban,Software Engineer,119322,0 +31696,Male,44,Diploma,9,4,53,40,80,0.0,1,99,Urban,HR Executive,121832,0 +31697,Male,41,Bachelors,15,3,84,5,10,8.0,6,45,Semi-Urban,ML Engineer,97005,0 +31698,Female,47,Bachelors,13,66,6,46,39,7.0,5,22,Urban,Manager,82316,0 +31699,Male,31,High School,5,81,84,32,68,8.0,7,3,Semi-Urban,Data Analyst,68525,0 +31700,Female,50,Bachelors,5,56,89,86,2,4.0,6,26,Rural,ML Engineer,134478,1 +31701,Male,23,Masters,6,67,82,45,17,1.0,1,86,Semi-Urban,Data Analyst,139260,1 +31702,Male,55,Bachelors,15,67,18,65,38,3.0,4,58,Urban,HR Executive,114291,0 +31703,Male,30,Bachelors,12,34,74,56,14,1.0,2,55,Rural,Data Analyst,25043,0 +31704,Male,43,Bachelors,7,38,31,48,93,5.0,1,79,Semi-Urban,Manager,88700,0 +31705,Male,55,Masters,12,55,84,99,74,5.0,4,26,Semi-Urban,Data Analyst,120037,1 +31706,Other,28,Bachelors,2,77,16,50,54,6.0,3,56,Semi-Urban,Software Engineer,42706,0 +31707,Male,49,Masters,16,74,67,30,15,4.0,3,17,Rural,Software Engineer,115697,0 +31708,Male,58,PhD,3,95,84,17,0,1.0,1,80,Urban,HR Executive,98646,1 +31709,Male,57,Bachelors,15,44,49,36,23,8.0,7,86,Urban,Data Analyst,124978,0 +31710,Male,46,Bachelors,0,21,19,61,11,3.0,6,18,Rural,Software Engineer,133288,0 +31711,Male,32,Masters,17,13,73,36,88,0.0,1,69,Semi-Urban,HR Executive,137648,0 +31712,Female,39,High School,16,33,4,70,51,3.0,6,62,Urban,Software Engineer,63318,0 +31713,Male,47,High School,6,32,61,1,82,1.0,6,65,Urban,ML Engineer,149271,0 +31714,Female,41,PhD,13,82,9,56,67,1.0,7,45,Urban,Manager,31258,0 +31715,Male,48,Diploma,9,50,50,49,17,5.0,6,72,Urban,HR Executive,42747,0 +31716,Male,27,Bachelors,5,65,24,40,65,7.0,0,46,Rural,HR Executive,123537,0 +31717,Male,31,Masters,18,26,78,59,4,5.0,1,16,Urban,Software Engineer,58693,0 +31718,Male,47,Diploma,19,74,48,80,92,3.0,3,92,Urban,Software Engineer,133178,1 +31719,Male,34,Diploma,13,66,2,89,63,7.0,6,53,Urban,ML Engineer,134592,0 +31720,Male,26,Bachelors,14,80,49,96,16,1.0,0,97,Semi-Urban,Manager,88196,1 +31721,Male,56,PhD,18,25,12,39,9,5.0,5,75,Semi-Urban,Manager,49964,0 +31722,Female,27,Masters,9,5,60,52,88,8.0,0,48,Urban,Software Engineer,75335,0 +31723,Male,55,Bachelors,18,31,34,54,48,3.0,7,18,Semi-Urban,HR Executive,116831,0 +31724,Female,29,Bachelors,5,59,95,75,48,0.0,1,96,Urban,HR Executive,97134,1 +31725,Male,35,High School,15,71,15,74,45,4.0,2,99,Rural,HR Executive,51227,1 +31726,Female,24,Masters,1,0,38,15,71,4.0,5,34,Rural,Manager,48734,0 +31727,Male,52,High School,14,66,72,25,53,4.0,3,60,Urban,HR Executive,25591,0 +31728,Male,29,Masters,19,38,60,96,51,3.0,7,10,Semi-Urban,ML Engineer,109816,0 +31729,Other,33,Diploma,4,42,96,63,37,3.0,0,55,Rural,HR Executive,91840,1 +31730,Male,34,Bachelors,11,67,99,80,87,6.0,2,14,Urban,Data Analyst,115317,1 +31731,Male,50,Masters,14,17,83,31,73,9.0,1,34,Urban,ML Engineer,95595,0 +31732,Male,21,Bachelors,0,22,36,16,46,1.0,1,2,Semi-Urban,Software Engineer,60595,0 +31733,Male,27,Bachelors,7,13,31,45,42,6.0,3,61,Semi-Urban,Software Engineer,58189,0 +31734,Other,48,Diploma,1,94,19,23,64,0.0,6,95,Rural,Software Engineer,67017,0 +31735,Female,32,Diploma,9,49,51,12,56,4.0,5,8,Urban,Data Analyst,64792,0 +31736,Female,54,Masters,8,60,60,29,20,6.0,0,17,Urban,ML Engineer,109654,0 +31737,Other,57,Diploma,14,13,99,88,42,1.0,7,6,Semi-Urban,Manager,26051,0 +31738,Male,38,Bachelors,1,74,88,43,45,7.0,3,27,Urban,ML Engineer,79140,0 +31739,Male,44,Diploma,9,59,73,49,9,0.0,3,15,Urban,Software Engineer,105143,0 +31740,Female,24,Bachelors,2,85,14,57,90,9.0,5,39,Semi-Urban,ML Engineer,39794,0 +31741,Male,34,Diploma,11,45,27,16,60,2.0,5,93,Urban,HR Executive,65361,0 +31742,Male,58,High School,13,96,41,70,38,6.0,5,55,Semi-Urban,HR Executive,104868,1 +31743,Male,30,Diploma,7,21,15,82,77,5.0,7,80,Rural,Data Analyst,70504,0 +31744,Female,40,Masters,4,3,24,24,7,0.0,2,12,Semi-Urban,Data Analyst,68771,0 +31745,Male,53,Bachelors,16,46,55,67,58,3.0,0,33,Urban,Manager,134518,0 +31746,Female,59,Diploma,6,50,71,22,58,1.0,6,75,Rural,ML Engineer,91698,0 +31747,Male,22,Masters,5,66,20,50,75,5.0,2,35,Semi-Urban,HR Executive,47669,0 +31748,Male,56,High School,5,76,63,81,10,5.0,3,3,Rural,HR Executive,108660,0 +31749,Female,36,PhD,9,96,11,12,63,8.0,4,69,Urban,ML Engineer,119923,0 +31750,Other,51,Masters,2,95,8,0,97,7.0,6,46,Semi-Urban,ML Engineer,148220,0 +31751,Male,49,Masters,17,67,70,4,95,4.0,6,20,Urban,Manager,31866,0 +31752,Male,56,High School,15,61,31,89,12,5.0,0,56,Urban,ML Engineer,89222,1 +31753,Male,35,Diploma,8,43,86,14,32,2.0,6,87,Urban,HR Executive,27088,0 +31754,Female,46,Bachelors,7,94,38,67,96,9.0,1,69,Urban,Software Engineer,21248,1 +31755,Male,54,High School,3,7,54,32,79,6.0,5,57,Semi-Urban,HR Executive,136357,0 +31756,Male,42,Bachelors,17,18,57,54,25,0.0,4,94,Rural,HR Executive,69495,0 +31757,Female,27,Bachelors,2,85,75,15,32,7.0,5,48,Rural,Software Engineer,40710,0 +31758,Male,25,Masters,10,96,5,79,27,5.0,3,23,Urban,Software Engineer,142547,0 +31759,Male,50,Diploma,14,6,71,62,96,3.0,5,2,Urban,Data Analyst,91263,0 +31760,Female,53,Masters,0,46,85,84,27,3.0,6,78,Semi-Urban,HR Executive,33232,1 +31761,Female,41,High School,18,21,23,27,46,5.0,6,35,Urban,Manager,92389,0 +31762,Female,37,Bachelors,8,99,45,29,19,4.0,5,84,Urban,HR Executive,38235,1 +31763,Male,50,Bachelors,3,55,17,82,21,2.0,0,1,Rural,Data Analyst,92927,0 +31764,Female,22,Masters,13,37,0,49,65,1.0,7,59,Urban,HR Executive,48547,0 +31765,Female,46,Bachelors,14,69,10,77,93,7.0,1,84,Semi-Urban,ML Engineer,95531,0 +31766,Male,47,Masters,13,95,50,82,14,5.0,5,80,Rural,Data Analyst,104008,1 +31767,Female,23,Bachelors,12,7,1,88,22,4.0,7,96,Urban,Data Analyst,130933,0 +31768,Male,23,High School,9,31,0,64,82,1.0,1,25,Semi-Urban,Software Engineer,123237,0 +31769,Female,57,Masters,18,42,37,1,76,1.0,0,35,Rural,Data Analyst,81338,0 +31770,Female,45,High School,7,5,98,88,68,0.0,6,88,Urban,HR Executive,127796,1 +31771,Female,38,Diploma,5,39,66,58,57,0.0,0,94,Urban,Software Engineer,97956,1 +31772,Male,35,Bachelors,13,89,49,54,9,0.0,0,50,Urban,Data Analyst,116885,1 +31773,Female,57,Bachelors,11,45,37,72,74,2.0,5,93,Urban,Software Engineer,60177,1 +31774,Male,53,Diploma,13,7,60,87,93,6.0,0,5,Urban,HR Executive,69835,0 +31775,Female,37,Bachelors,19,12,55,53,24,7.0,0,60,Semi-Urban,Software Engineer,89533,0 +31776,Female,31,Bachelors,14,26,65,85,37,1.0,6,45,Urban,ML Engineer,106288,0 +31777,Male,26,Bachelors,18,92,62,95,11,5.0,0,33,Semi-Urban,Data Analyst,135305,1 +31778,Male,35,Bachelors,3,83,66,89,41,2.0,5,19,Semi-Urban,Data Analyst,74766,1 +31779,Female,25,Bachelors,14,35,98,41,83,9.0,4,97,Semi-Urban,ML Engineer,108293,1 +31780,Male,54,High School,11,7,23,62,30,5.0,2,95,Urban,HR Executive,112605,0 +31781,Female,59,High School,15,87,28,86,19,9.0,2,77,Urban,Manager,121077,1 +31782,Male,32,Masters,1,91,32,87,30,0.0,3,33,Urban,Manager,23939,1 +31783,Female,53,High School,17,8,60,91,85,2.0,7,83,Urban,Manager,35306,1 +31784,Male,26,Diploma,10,14,35,7,71,5.0,4,39,Urban,Software Engineer,101611,0 +31785,Male,37,High School,6,33,44,31,7,6.0,7,28,Semi-Urban,Data Analyst,129439,0 +31786,Other,46,PhD,13,68,47,10,54,0.0,3,56,Semi-Urban,ML Engineer,115649,0 +31787,Female,42,Diploma,2,62,98,15,20,1.0,0,30,Urban,Manager,73076,0 +31788,Male,46,PhD,9,8,25,39,68,5.0,7,91,Urban,Manager,26860,0 +31789,Other,55,Bachelors,16,46,27,62,32,4.0,0,97,Urban,Data Analyst,131157,0 +31790,Male,33,Diploma,2,31,18,59,90,5.0,5,61,Urban,Data Analyst,34715,0 +31791,Female,25,Diploma,15,94,27,6,44,9.0,3,51,Rural,Manager,118264,0 +31792,Male,42,High School,11,23,93,93,66,4.0,3,38,Semi-Urban,Software Engineer,89720,1 +31793,Male,59,Bachelors,11,6,5,30,13,9.0,5,84,Rural,Data Analyst,115830,0 +31794,Male,55,Masters,4,73,8,74,74,2.0,4,68,Semi-Urban,Manager,83784,0 +31795,Male,26,Diploma,8,72,31,59,49,8.0,7,73,Urban,Data Analyst,68605,1 +31796,Female,29,Bachelors,1,48,35,62,37,5.0,5,16,Rural,Software Engineer,23793,0 +31797,Female,43,Bachelors,19,84,67,56,69,1.0,4,72,Urban,ML Engineer,78737,1 +31798,Male,49,Diploma,5,52,88,88,64,4.0,1,94,Rural,Manager,129180,1 +31799,Male,31,Bachelors,12,80,58,35,26,6.0,0,87,Semi-Urban,HR Executive,67232,1 +31800,Female,57,Masters,12,2,68,44,17,6.0,1,23,Urban,Manager,99941,0 +31801,Male,36,Bachelors,3,71,58,71,95,8.0,1,48,Urban,Data Analyst,34291,1 +31802,Male,25,Bachelors,6,45,5,9,21,7.0,0,53,Urban,ML Engineer,88241,0 +31803,Male,39,Diploma,5,21,60,91,56,4.0,3,37,Urban,Data Analyst,62883,0 +31804,Male,49,Bachelors,11,93,36,77,6,9.0,1,97,Urban,Software Engineer,148662,1 +31805,Male,50,Masters,5,34,21,2,66,5.0,1,81,Urban,Data Analyst,53902,0 +31806,Female,30,Diploma,1,3,66,57,2,5.0,4,40,Urban,Manager,105143,0 +31807,Male,51,PhD,8,30,94,58,42,1.0,5,1,Semi-Urban,ML Engineer,99817,0 +31808,Female,32,Bachelors,6,84,23,92,42,0.0,1,97,Semi-Urban,HR Executive,109589,1 +31809,Male,39,High School,15,28,76,81,56,5.0,5,17,Semi-Urban,HR Executive,63027,0 +31810,Male,49,PhD,4,58,13,1,45,6.0,7,37,Rural,Software Engineer,97795,0 +31811,Male,41,Bachelors,13,64,57,22,23,3.0,0,19,Urban,Manager,45888,0 +31812,Female,27,Bachelors,4,5,45,42,54,7.0,2,62,Semi-Urban,HR Executive,141483,0 +31813,Male,46,High School,0,67,13,54,67,3.0,3,84,Urban,Software Engineer,136475,0 +31814,Male,26,Bachelors,8,34,42,68,86,9.0,1,9,Urban,ML Engineer,146284,0 +31815,Female,50,Bachelors,13,89,29,50,54,9.0,1,85,Semi-Urban,ML Engineer,43990,1 +31816,Male,41,High School,3,62,74,61,60,5.0,7,92,Rural,ML Engineer,82455,1 +31817,Female,39,High School,16,5,98,54,95,0.0,0,62,Urban,Data Analyst,37035,0 +31818,Other,49,High School,14,12,92,33,92,8.0,3,70,Urban,HR Executive,57111,0 +31819,Male,40,Diploma,3,66,28,32,4,3.0,3,57,Urban,Manager,58630,0 +31820,Male,35,Bachelors,6,6,30,88,82,0.0,1,86,Urban,Manager,29196,0 +31821,Male,27,Bachelors,9,46,30,23,25,6.0,6,66,Urban,ML Engineer,23259,0 +31822,Female,22,Masters,8,67,30,28,1,5.0,6,64,Urban,ML Engineer,23225,0 +31823,Male,56,Masters,16,44,88,29,94,6.0,7,13,Semi-Urban,Software Engineer,117720,0 +31824,Female,30,High School,3,13,93,66,81,9.0,5,18,Urban,Manager,82735,0 +31825,Female,57,Bachelors,0,1,6,15,68,4.0,5,68,Semi-Urban,Data Analyst,108789,0 +31826,Male,36,Bachelors,15,40,38,70,67,6.0,1,97,Semi-Urban,Manager,84102,1 +31827,Female,29,Bachelors,6,41,1,72,73,6.0,2,79,Semi-Urban,Data Analyst,68173,0 +31828,Male,32,Bachelors,4,95,78,15,9,8.0,5,10,Rural,HR Executive,67064,0 +31829,Male,48,PhD,5,69,73,73,12,9.0,4,3,Semi-Urban,Data Analyst,88447,0 +31830,Female,35,Masters,19,59,61,78,10,1.0,4,4,Urban,ML Engineer,139886,0 +31831,Male,25,High School,15,53,29,89,94,5.0,2,33,Urban,ML Engineer,103537,0 +31832,Male,25,Masters,16,34,59,59,86,8.0,5,62,Rural,ML Engineer,134444,0 +31833,Female,24,Masters,16,38,53,78,78,7.0,6,48,Urban,Data Analyst,31907,0 +31834,Female,28,Diploma,9,16,58,30,97,9.0,4,52,Urban,Software Engineer,51689,0 +31835,Male,25,High School,2,54,81,0,61,0.0,5,48,Semi-Urban,Manager,109564,0 +31836,Female,39,Bachelors,9,45,67,32,87,3.0,6,20,Urban,Software Engineer,121783,0 +31837,Male,47,Diploma,17,10,2,59,79,8.0,1,2,Urban,HR Executive,111864,0 +31838,Female,27,Bachelors,10,50,65,87,29,7.0,7,78,Semi-Urban,ML Engineer,28611,1 +31839,Female,26,Bachelors,6,43,79,42,95,9.0,5,29,Semi-Urban,Manager,127867,0 +31840,Male,39,High School,9,58,72,19,81,3.0,4,90,Rural,Software Engineer,54478,1 +31841,Male,58,Masters,7,79,48,12,26,4.0,3,45,Urban,Data Analyst,84814,0 +31842,Female,53,Masters,14,89,94,64,47,1.0,0,22,Urban,ML Engineer,126524,1 +31843,Female,53,High School,8,77,99,22,6,0.0,2,3,Semi-Urban,ML Engineer,130066,0 +31844,Male,25,Bachelors,5,17,73,68,91,9.0,0,42,Semi-Urban,Data Analyst,136848,0 +31845,Male,36,Masters,12,34,72,64,40,8.0,7,78,Urban,ML Engineer,86511,1 +31846,Male,30,Bachelors,5,37,63,14,40,0.0,6,22,Semi-Urban,HR Executive,144393,0 +31847,Male,27,Diploma,0,13,63,62,3,1.0,5,79,Semi-Urban,Software Engineer,62035,0 +31848,Female,36,Bachelors,11,39,73,99,58,9.0,4,56,Semi-Urban,Manager,146256,1 +31849,Male,50,High School,12,47,11,96,65,5.0,3,31,Semi-Urban,HR Executive,24646,0 +31850,Female,57,Bachelors,19,94,92,33,67,7.0,1,99,Urban,ML Engineer,135521,1 +31851,Female,34,Bachelors,15,73,0,52,38,1.0,7,76,Urban,HR Executive,37226,0 +31852,Other,37,Masters,13,55,58,64,82,7.0,5,96,Urban,ML Engineer,27777,1 +31853,Male,28,High School,2,54,41,63,93,2.0,5,43,Rural,Data Analyst,88072,0 +31854,Female,33,High School,1,38,61,4,82,6.0,4,68,Urban,Manager,120520,0 +31855,Female,49,Bachelors,19,56,1,6,71,5.0,1,54,Urban,Data Analyst,52676,0 +31856,Male,23,High School,3,2,64,89,11,2.0,7,64,Urban,HR Executive,80400,0 +31857,Male,28,PhD,18,28,26,47,71,2.0,7,98,Semi-Urban,Manager,120045,0 +31858,Female,52,Bachelors,2,53,8,18,68,7.0,1,58,Urban,Software Engineer,94682,0 +31859,Male,25,High School,10,0,11,76,26,6.0,1,38,Urban,Data Analyst,33076,0 +31860,Female,31,Bachelors,0,84,76,31,6,2.0,5,81,Urban,Data Analyst,76104,1 +31861,Male,56,Diploma,6,1,17,56,3,0.0,2,6,Semi-Urban,ML Engineer,132723,0 +31862,Male,55,Masters,11,24,61,79,24,1.0,2,18,Urban,HR Executive,44117,0 +31863,Male,49,Bachelors,1,15,51,20,53,0.0,0,43,Rural,Data Analyst,110412,0 +31864,Male,25,High School,17,64,1,21,47,7.0,7,38,Semi-Urban,Data Analyst,147031,0 +31865,Male,33,Bachelors,5,70,66,86,53,8.0,7,30,Semi-Urban,Software Engineer,105468,1 +31866,Male,44,Bachelors,7,89,51,12,50,6.0,6,33,Urban,Data Analyst,117501,0 +31867,Male,39,Bachelors,17,28,25,63,57,4.0,1,74,Semi-Urban,HR Executive,62478,0 +31868,Male,45,PhD,19,5,92,33,75,1.0,4,9,Semi-Urban,HR Executive,24460,0 +31869,Male,51,Masters,18,64,20,90,51,4.0,4,79,Urban,Data Analyst,94965,1 +31870,Female,45,Diploma,7,70,52,69,24,5.0,7,21,Urban,Manager,100356,0 +31871,Male,29,Bachelors,8,1,17,39,2,0.0,5,80,Urban,ML Engineer,52822,0 +31872,Female,44,Bachelors,1,22,45,32,52,8.0,2,29,Urban,Manager,145577,0 +31873,Female,58,Bachelors,15,5,26,34,95,4.0,5,83,Semi-Urban,ML Engineer,92506,0 +31874,Male,48,Masters,1,66,96,61,91,4.0,7,37,Semi-Urban,HR Executive,30154,1 +31875,Male,26,Masters,12,12,76,6,69,9.0,3,59,Urban,Software Engineer,23422,0 +31876,Female,42,Bachelors,14,69,30,29,18,4.0,2,50,Urban,Software Engineer,63165,0 +31877,Female,38,PhD,4,82,18,83,36,7.0,6,13,Urban,Data Analyst,87408,0 +31878,Male,29,Bachelors,6,51,6,47,66,5.0,1,31,Urban,ML Engineer,77192,0 +31879,Female,25,Bachelors,14,74,14,28,44,1.0,3,15,Rural,ML Engineer,137166,0 +31880,Male,53,Diploma,14,34,85,85,51,6.0,5,80,Semi-Urban,ML Engineer,102202,1 +31881,Male,29,Bachelors,10,69,34,51,78,7.0,5,89,Rural,ML Engineer,89737,1 +31882,Male,39,Masters,14,95,24,74,71,3.0,6,88,Urban,Software Engineer,48789,1 +31883,Male,25,Diploma,17,23,29,62,25,3.0,4,57,Urban,Manager,28467,0 +31884,Other,26,Bachelors,7,0,19,31,40,1.0,2,71,Rural,Data Analyst,92559,0 +31885,Female,49,High School,7,52,53,6,68,2.0,7,31,Urban,HR Executive,134764,0 +31886,Female,49,Bachelors,3,31,25,40,36,7.0,2,58,Urban,ML Engineer,143506,0 +31887,Male,54,PhD,13,45,49,1,81,7.0,0,19,Rural,Manager,113644,0 +31888,Male,42,Bachelors,9,80,36,25,95,8.0,1,75,Urban,Manager,50543,0 +31889,Male,39,Bachelors,5,47,36,42,69,2.0,0,98,Urban,HR Executive,147363,0 +31890,Male,48,High School,16,88,68,5,86,7.0,1,58,Urban,Software Engineer,122382,0 +31891,Male,58,High School,3,29,80,50,70,3.0,1,22,Semi-Urban,Manager,63755,0 +31892,Male,23,Diploma,5,20,18,69,92,2.0,0,17,Urban,ML Engineer,77721,0 +31893,Male,46,Bachelors,16,89,89,76,23,2.0,1,12,Rural,Software Engineer,140788,1 +31894,Female,46,High School,6,93,5,97,13,4.0,5,78,Urban,Data Analyst,126067,1 +31895,Female,25,Bachelors,0,52,14,26,44,1.0,6,96,Urban,Software Engineer,59452,0 +31896,Male,48,High School,11,2,39,82,47,8.0,7,41,Semi-Urban,Manager,54598,0 +31897,Female,40,High School,7,48,86,18,51,9.0,5,15,Urban,Data Analyst,52174,0 +31898,Male,57,Masters,0,65,68,63,85,9.0,7,80,Semi-Urban,Manager,80136,1 +31899,Male,30,PhD,2,16,64,64,28,5.0,0,4,Urban,HR Executive,73565,0 +31900,Female,52,PhD,15,79,72,11,75,2.0,0,66,Urban,Data Analyst,60903,0 +31901,Female,40,Masters,10,28,30,10,74,8.0,4,49,Semi-Urban,Data Analyst,122115,0 +31902,Male,34,Masters,4,95,88,19,54,4.0,1,51,Semi-Urban,HR Executive,97989,1 +31903,Male,49,High School,13,62,97,50,4,4.0,7,69,Urban,HR Executive,72121,1 +31904,Female,51,High School,18,88,26,10,61,3.0,7,68,Urban,ML Engineer,128591,0 +31905,Male,59,Bachelors,12,41,37,75,39,2.0,4,87,Rural,Software Engineer,36758,1 +31906,Male,48,Bachelors,6,67,79,9,76,5.0,0,43,Rural,Manager,74678,0 +31907,Female,53,Diploma,19,37,4,33,72,8.0,6,17,Semi-Urban,ML Engineer,137943,0 +31908,Male,23,Bachelors,13,46,57,25,90,5.0,4,97,Urban,Software Engineer,64136,0 +31909,Male,26,Diploma,13,16,53,35,23,4.0,3,62,Urban,ML Engineer,29477,0 +31910,Male,31,High School,9,72,33,64,66,7.0,1,85,Urban,Manager,69163,1 +31911,Female,46,Diploma,11,47,78,34,96,5.0,3,40,Urban,Data Analyst,127395,0 +31912,Female,37,Bachelors,13,41,54,64,2,3.0,2,54,Urban,Software Engineer,93493,0 +31913,Male,45,Bachelors,17,99,99,11,47,6.0,6,54,Rural,Software Engineer,110282,1 +31914,Male,47,High School,3,86,12,94,46,7.0,0,79,Urban,Data Analyst,47539,1 +31915,Male,33,Bachelors,8,73,41,9,77,5.0,6,55,Semi-Urban,HR Executive,76207,0 +31916,Male,34,Bachelors,5,35,17,32,89,7.0,5,78,Urban,Software Engineer,50516,0 +31917,Male,35,High School,11,34,24,94,19,3.0,1,57,Rural,ML Engineer,104421,0 +31918,Male,40,High School,8,69,39,49,71,8.0,1,33,Urban,ML Engineer,78905,0 +31919,Male,44,Masters,7,18,20,62,66,4.0,6,78,Urban,HR Executive,34763,0 +31920,Other,29,Masters,8,68,54,57,69,8.0,1,67,Semi-Urban,ML Engineer,38532,1 +31921,Male,46,Bachelors,13,31,89,30,65,9.0,0,74,Rural,HR Executive,134882,0 +31922,Male,42,Masters,11,95,70,0,62,3.0,3,94,Rural,Manager,114818,1 +31923,Male,40,High School,14,93,6,60,93,8.0,6,25,Urban,Data Analyst,143840,0 +31924,Female,33,Bachelors,19,91,7,73,10,4.0,5,67,Urban,Software Engineer,129475,0 +31925,Male,27,Masters,16,43,17,67,84,0.0,6,64,Urban,HR Executive,132162,0 +31926,Male,55,Masters,14,79,12,69,31,1.0,3,91,Urban,HR Executive,84148,1 +31927,Female,43,Bachelors,2,87,42,12,87,9.0,1,1,Urban,Data Analyst,24344,0 +31928,Other,55,Bachelors,9,55,95,76,57,2.0,0,56,Semi-Urban,Data Analyst,110137,1 +31929,Female,45,Bachelors,5,88,96,29,4,6.0,5,1,Semi-Urban,Manager,131633,0 +31930,Male,22,Diploma,17,96,7,17,29,1.0,3,31,Semi-Urban,Software Engineer,90975,0 +31931,Male,54,Bachelors,10,90,86,0,10,0.0,6,35,Urban,Manager,58350,0 +31932,Female,46,Bachelors,13,27,33,17,5,5.0,2,40,Semi-Urban,HR Executive,70560,0 +31933,Male,48,Masters,6,44,41,47,10,2.0,4,97,Urban,ML Engineer,95293,0 +31934,Male,43,Bachelors,15,99,34,71,32,4.0,1,54,Semi-Urban,Manager,121604,1 +31935,Other,51,Masters,19,70,14,6,31,3.0,2,27,Urban,Software Engineer,51002,0 +31936,Female,33,Bachelors,11,8,33,83,59,5.0,0,10,Semi-Urban,Software Engineer,143660,0 +31937,Female,39,Diploma,11,38,98,60,8,5.0,2,55,Rural,ML Engineer,64085,1 +31938,Female,59,Bachelors,12,36,18,98,3,0.0,6,84,Urban,HR Executive,86160,0 +31939,Female,31,Bachelors,5,29,90,44,62,2.0,6,16,Rural,Data Analyst,78516,0 +31940,Female,22,Diploma,16,88,96,91,96,4.0,0,9,Rural,Software Engineer,34598,1 +31941,Male,50,Masters,2,82,23,1,37,4.0,0,90,Urban,Data Analyst,51498,0 +31942,Other,50,Bachelors,2,64,10,54,0,8.0,4,37,Urban,Software Engineer,51202,0 +31943,Male,21,Bachelors,17,4,82,96,10,0.0,7,33,Urban,Data Analyst,28877,0 +31944,Male,31,Diploma,1,30,95,75,99,4.0,2,31,Urban,Manager,74445,0 +31945,Male,29,Masters,7,62,37,62,86,7.0,3,56,Urban,Data Analyst,88665,0 +31946,Male,51,High School,16,88,47,88,17,6.0,4,72,Rural,HR Executive,24485,1 +31947,Male,49,Masters,5,14,73,67,79,0.0,7,91,Rural,Manager,148279,1 +31948,Male,34,Bachelors,12,38,69,60,33,0.0,6,87,Urban,HR Executive,74449,1 +31949,Male,34,Diploma,5,80,40,25,96,6.0,2,65,Urban,Data Analyst,96230,0 +31950,Male,29,Bachelors,14,29,64,11,18,9.0,6,47,Semi-Urban,HR Executive,60524,0 +31951,Male,21,Masters,7,52,89,8,41,4.0,3,40,Semi-Urban,HR Executive,122416,0 +31952,Male,46,Bachelors,0,61,72,36,57,8.0,5,74,Urban,Manager,112837,1 +31953,Male,43,Diploma,8,81,27,98,14,7.0,2,35,Urban,Manager,28911,1 +31954,Female,26,Bachelors,12,33,44,48,43,7.0,4,10,Urban,Data Analyst,55329,0 +31955,Male,47,High School,4,1,10,67,41,7.0,0,37,Urban,Data Analyst,32970,0 +31956,Male,41,Bachelors,1,19,70,32,4,7.0,7,90,Semi-Urban,Manager,114600,0 +31957,Male,57,Masters,2,33,29,24,91,4.0,4,33,Urban,HR Executive,51700,0 +31958,Female,54,Masters,8,5,41,15,11,2.0,5,32,Urban,ML Engineer,128583,0 +31959,Female,39,PhD,2,51,78,31,93,3.0,2,94,Semi-Urban,Manager,65300,1 +31960,Male,21,Diploma,0,7,38,91,39,1.0,1,10,Urban,ML Engineer,149138,0 +31961,Female,56,Masters,18,49,87,20,9,8.0,6,91,Semi-Urban,HR Executive,82705,1 +31962,Female,38,Masters,0,78,37,17,31,1.0,3,64,Semi-Urban,HR Executive,79400,0 +31963,Female,22,Bachelors,4,69,13,63,85,2.0,7,7,Rural,Software Engineer,127063,0 +31964,Male,39,Bachelors,4,81,30,15,80,1.0,6,2,Urban,Manager,81602,0 +31965,Female,36,Diploma,8,59,10,56,73,0.0,0,47,Urban,Software Engineer,98510,0 +31966,Male,59,Masters,6,42,38,34,2,7.0,1,37,Urban,Data Analyst,125235,0 +31967,Female,55,Diploma,0,84,25,23,6,0.0,6,6,Rural,HR Executive,104847,0 +31968,Female,47,Diploma,8,68,7,80,11,5.0,0,57,Rural,HR Executive,48679,0 +31969,Female,57,High School,2,55,99,4,5,4.0,3,22,Urban,Manager,102455,0 +31970,Male,47,Masters,19,79,78,16,38,2.0,3,87,Urban,ML Engineer,78532,1 +31971,Female,28,Diploma,12,39,59,45,1,6.0,4,18,Urban,HR Executive,116525,0 +31972,Male,55,PhD,2,45,93,73,73,7.0,7,89,Urban,HR Executive,121423,1 +31973,Male,53,Diploma,17,23,89,6,89,4.0,5,69,Urban,Software Engineer,130437,0 +31974,Male,40,High School,9,19,81,34,43,3.0,7,71,Rural,Software Engineer,108519,0 +31975,Female,24,High School,19,85,17,24,85,0.0,4,43,Semi-Urban,Data Analyst,35451,0 +31976,Male,58,Masters,2,25,27,80,63,2.0,1,9,Urban,Manager,110422,0 +31977,Male,57,Bachelors,7,8,64,87,39,5.0,0,93,Urban,Manager,106198,1 +31978,Male,34,Bachelors,5,3,95,83,79,5.0,6,77,Semi-Urban,Manager,21325,1 +31979,Female,43,High School,13,58,51,0,19,2.0,3,3,Urban,ML Engineer,47186,0 +31980,Female,25,PhD,16,65,22,36,14,4.0,5,93,Urban,HR Executive,26130,0 +31981,Female,34,Masters,0,96,26,90,20,0.0,4,36,Semi-Urban,Manager,99285,1 +31982,Male,48,Diploma,11,67,80,80,57,9.0,3,95,Urban,Data Analyst,134853,1 +31983,Other,34,Diploma,10,22,86,94,14,0.0,4,59,Urban,Manager,31738,1 +31984,Female,53,High School,11,63,24,28,67,9.0,0,12,Urban,Manager,145011,0 +31985,Female,39,Diploma,15,11,2,73,8,5.0,0,49,Rural,Software Engineer,45041,0 +31986,Female,26,Diploma,8,99,10,16,43,2.0,1,61,Semi-Urban,ML Engineer,84689,0 +31987,Other,35,Masters,9,8,9,9,42,5.0,4,1,Urban,Manager,85543,0 +31988,Female,40,Masters,16,49,97,63,4,0.0,0,77,Urban,HR Executive,20454,1 +31989,Male,24,Bachelors,7,99,91,97,9,9.0,4,94,Rural,HR Executive,35462,1 +31990,Male,34,Bachelors,18,52,92,52,87,3.0,0,42,Rural,ML Engineer,124515,1 +31991,Female,57,Masters,13,33,23,26,97,0.0,0,70,Urban,Software Engineer,97006,0 +31992,Male,42,High School,8,66,11,25,73,6.0,0,58,Urban,Manager,102724,0 +31993,Female,29,Bachelors,15,21,46,56,52,8.0,0,23,Urban,Software Engineer,109150,0 +31994,Male,21,Diploma,8,28,52,57,84,7.0,3,85,Semi-Urban,Data Analyst,70817,0 +31995,Male,25,Masters,11,41,29,54,71,1.0,1,8,Urban,HR Executive,81941,0 +31996,Male,46,Masters,14,27,27,46,5,6.0,7,53,Semi-Urban,HR Executive,135512,0 +31997,Female,50,Bachelors,7,43,91,10,24,6.0,7,20,Rural,Manager,102776,0 +31998,Female,21,Diploma,5,97,58,22,0,8.0,0,18,Urban,Software Engineer,94616,0 +31999,Male,38,Masters,2,34,62,5,38,5.0,2,8,Rural,ML Engineer,124692,0 +32000,Male,54,Masters,0,97,95,67,10,9.0,5,72,Urban,Data Analyst,99735,1 +32001,Male,39,High School,13,57,57,49,86,6.0,3,19,Urban,Manager,76882,0 +32002,Male,48,Bachelors,2,42,65,26,3,6.0,4,9,Rural,Data Analyst,108615,0 +32003,Male,44,Diploma,8,18,10,85,11,5.0,4,68,Urban,Software Engineer,122177,0 +32004,Female,28,Masters,14,13,60,46,41,1.0,2,2,Urban,Software Engineer,39877,0 +32005,Female,31,Diploma,6,8,37,87,37,9.0,5,64,Urban,Data Analyst,31775,0 +32006,Male,30,PhD,18,14,21,31,47,0.0,3,19,Rural,Manager,124012,0 +32007,Male,26,PhD,16,65,57,61,93,8.0,3,12,Urban,Software Engineer,32878,0 +32008,Female,35,PhD,19,99,4,43,66,1.0,7,62,Urban,Data Analyst,101211,0 +32009,Other,46,Diploma,9,22,70,69,53,3.0,7,24,Urban,Manager,142370,0 +32010,Female,53,PhD,3,78,49,90,15,1.0,2,88,Semi-Urban,Software Engineer,117045,1 +32011,Male,34,Diploma,10,3,32,26,85,2.0,5,90,Rural,HR Executive,102199,0 +32012,Male,41,Bachelors,2,86,35,98,7,0.0,3,26,Semi-Urban,Data Analyst,114777,1 +32013,Male,55,Masters,15,63,65,13,19,6.0,5,75,Urban,HR Executive,133859,0 +32014,Female,51,Masters,10,84,76,39,21,4.0,6,51,Semi-Urban,ML Engineer,138373,1 +32015,Female,54,Bachelors,0,48,3,56,41,6.0,1,86,Urban,Data Analyst,147494,0 +32016,Male,31,Bachelors,17,5,57,8,32,1.0,6,69,Rural,Software Engineer,106959,0 +32017,Female,41,Bachelors,3,52,31,79,71,1.0,3,71,Semi-Urban,Manager,147015,0 +32018,Male,29,Bachelors,1,36,97,13,34,5.0,2,8,Urban,Software Engineer,61746,0 +32019,Other,27,Bachelors,14,12,77,48,80,6.0,4,94,Urban,HR Executive,49793,0 +32020,Male,57,Bachelors,14,32,36,64,54,5.0,6,57,Rural,Manager,138605,0 +32021,Male,47,Bachelors,1,96,94,45,46,1.0,4,59,Rural,Data Analyst,136429,1 +32022,Male,24,Bachelors,19,83,84,54,82,3.0,4,64,Semi-Urban,Software Engineer,123259,1 +32023,Male,34,Masters,17,68,73,17,46,3.0,4,80,Semi-Urban,Data Analyst,101967,1 +32024,Female,57,Bachelors,17,5,9,61,20,8.0,7,84,Semi-Urban,Software Engineer,147585,0 +32025,Male,45,Bachelors,6,96,97,50,5,2.0,1,18,Urban,HR Executive,98640,1 +32026,Female,42,High School,17,13,60,75,14,6.0,4,12,Rural,HR Executive,113953,0 +32027,Male,27,Masters,13,58,4,27,88,4.0,2,0,Urban,Software Engineer,58629,0 +32028,Male,27,Masters,19,30,38,27,58,7.0,2,13,Urban,Data Analyst,79626,0 +32029,Female,27,Bachelors,12,21,43,70,67,8.0,7,64,Semi-Urban,ML Engineer,26883,0 +32030,Other,24,Bachelors,0,57,73,70,1,0.0,6,46,Urban,HR Executive,103515,1 +32031,Male,44,Bachelors,14,67,9,47,54,5.0,1,93,Urban,Data Analyst,116706,0 +32032,Other,30,Diploma,11,15,60,6,52,9.0,3,15,Urban,Manager,66092,0 +32033,Female,39,Bachelors,3,84,1,38,83,5.0,2,86,Rural,ML Engineer,128609,0 +32034,Male,32,PhD,18,5,13,59,3,3.0,7,75,Urban,Software Engineer,86440,0 +32035,Female,49,Bachelors,8,81,6,21,66,8.0,5,51,Urban,HR Executive,119316,0 +32036,Male,24,High School,5,65,50,30,80,0.0,0,48,Urban,Software Engineer,148966,0 +32037,Male,58,Diploma,18,96,85,75,9,6.0,3,57,Urban,ML Engineer,20375,1 +32038,Female,45,High School,3,63,2,11,4,3.0,5,59,Semi-Urban,Data Analyst,67252,0 +32039,Male,52,Bachelors,19,59,35,37,71,1.0,1,72,Urban,HR Executive,72970,0 +32040,Male,56,Bachelors,15,78,20,3,29,9.0,3,48,Urban,Data Analyst,135677,0 +32041,Male,21,Diploma,2,14,28,54,6,4.0,0,76,Semi-Urban,Software Engineer,108085,0 +32042,Female,27,High School,9,21,59,36,92,6.0,4,61,Rural,HR Executive,113526,0 +32043,Female,54,Bachelors,16,68,70,54,97,9.0,5,29,Semi-Urban,ML Engineer,117721,0 +32044,Male,40,Bachelors,4,22,9,85,43,5.0,1,53,Rural,ML Engineer,64620,0 +32045,Female,47,Bachelors,2,32,85,5,22,6.0,5,86,Urban,Manager,65537,0 +32046,Male,45,Diploma,6,30,12,38,4,6.0,5,4,Urban,Software Engineer,47355,0 +32047,Female,55,Bachelors,8,61,21,21,78,1.0,7,74,Urban,HR Executive,34900,0 +32048,Female,53,Bachelors,9,53,52,68,86,5.0,2,30,Semi-Urban,Data Analyst,26298,0 +32049,Female,24,Masters,7,51,76,91,18,1.0,0,83,Urban,Data Analyst,95704,1 +32050,Male,30,Bachelors,13,15,13,28,90,2.0,4,20,Urban,ML Engineer,145500,0 +32051,Female,56,Masters,2,9,20,80,61,7.0,6,94,Urban,HR Executive,147032,0 +32052,Male,30,Masters,3,98,4,9,2,4.0,7,21,Urban,HR Executive,20230,0 +32053,Female,26,Bachelors,13,91,32,94,83,6.0,3,41,Rural,HR Executive,85842,1 +32054,Male,57,High School,1,19,40,1,72,1.0,1,6,Semi-Urban,HR Executive,148133,0 +32055,Male,52,Bachelors,5,25,41,91,9,4.0,3,33,Rural,HR Executive,56884,0 +32056,Male,43,Diploma,13,87,62,1,90,5.0,3,25,Urban,Manager,74624,0 +32057,Male,51,Masters,5,24,20,71,11,5.0,5,62,Rural,HR Executive,83278,0 +32058,Male,46,Diploma,4,38,58,98,45,3.0,7,83,Semi-Urban,HR Executive,132964,1 +32059,Female,45,Diploma,8,85,59,65,35,0.0,7,54,Semi-Urban,Software Engineer,49611,1 +32060,Male,27,Bachelors,12,36,79,96,76,0.0,1,49,Urban,Data Analyst,114132,1 +32061,Male,23,Masters,14,27,68,40,51,6.0,0,1,Semi-Urban,Manager,146354,0 +32062,Male,25,Masters,9,45,16,16,19,2.0,7,8,Urban,HR Executive,28225,0 +32063,Female,54,Bachelors,14,35,25,83,22,8.0,1,1,Rural,Data Analyst,131505,0 +32064,Male,52,Masters,1,2,7,50,48,4.0,7,72,Urban,Software Engineer,146093,0 +32065,Male,59,Bachelors,7,3,25,16,37,8.0,0,42,Urban,HR Executive,147918,0 +32066,Male,27,Masters,5,95,16,85,82,0.0,5,65,Semi-Urban,HR Executive,100842,1 +32067,Female,21,Bachelors,14,5,77,81,74,8.0,0,2,Urban,Data Analyst,22506,0 +32068,Male,57,High School,12,87,36,96,14,4.0,1,69,Urban,Manager,64392,1 +32069,Male,46,High School,9,1,97,80,33,5.0,4,65,Urban,Manager,66867,1 +32070,Female,28,Bachelors,1,26,82,43,39,5.0,5,37,Rural,ML Engineer,131981,0 +32071,Male,38,Diploma,6,60,18,51,38,8.0,4,31,Semi-Urban,ML Engineer,99172,0 +32072,Male,50,Bachelors,17,9,72,15,43,0.0,0,74,Semi-Urban,ML Engineer,68137,0 +32073,Male,31,Diploma,14,97,88,39,60,4.0,3,12,Urban,Manager,68742,1 +32074,Other,56,Bachelors,6,75,46,72,83,5.0,7,88,Urban,HR Executive,31009,1 +32075,Male,35,Bachelors,4,4,22,50,50,2.0,4,24,Urban,Software Engineer,148425,0 +32076,Male,38,Bachelors,19,7,20,62,2,7.0,0,1,Urban,HR Executive,67437,0 +32077,Male,35,Diploma,9,46,3,81,13,8.0,3,26,Urban,HR Executive,56865,0 +32078,Female,53,Bachelors,12,73,25,48,54,7.0,0,93,Urban,ML Engineer,90319,0 +32079,Male,34,High School,18,11,90,29,81,0.0,4,27,Semi-Urban,ML Engineer,84777,0 +32080,Male,49,Masters,5,21,0,85,80,7.0,5,75,Urban,Software Engineer,32480,0 +32081,Female,49,High School,2,10,9,62,47,7.0,4,99,Urban,HR Executive,113016,0 +32082,Other,55,Bachelors,11,20,44,71,33,9.0,2,32,Semi-Urban,Manager,101697,0 +32083,Female,34,Bachelors,11,95,21,92,21,4.0,0,88,Rural,HR Executive,32012,1 +32084,Male,38,Bachelors,5,95,15,4,19,5.0,0,25,Urban,HR Executive,87918,0 +32085,Male,45,Diploma,5,84,1,86,41,9.0,2,52,Rural,Manager,27658,0 +32086,Male,34,Bachelors,9,64,85,96,29,0.0,6,39,Rural,Software Engineer,111745,1 +32087,Female,57,Diploma,19,53,81,4,20,0.0,2,67,Rural,ML Engineer,144856,0 +32088,Female,56,Diploma,2,27,44,21,90,7.0,5,47,Rural,Manager,67265,0 +32089,Female,52,Bachelors,18,27,87,16,76,7.0,0,4,Rural,Software Engineer,51574,0 +32090,Male,28,Masters,9,86,69,11,48,8.0,6,94,Urban,Software Engineer,118481,1 +32091,Female,46,Bachelors,14,42,35,47,56,8.0,4,11,Rural,ML Engineer,63209,0 +32092,Female,24,High School,14,3,6,62,83,1.0,2,16,Semi-Urban,HR Executive,140276,0 +32093,Female,33,PhD,7,17,0,31,13,3.0,5,43,Urban,Software Engineer,124866,0 +32094,Female,45,Masters,13,49,3,61,70,2.0,5,69,Semi-Urban,Software Engineer,139960,0 +32095,Female,46,Bachelors,5,81,14,51,76,0.0,5,42,Semi-Urban,Software Engineer,88360,0 +32096,Male,48,Diploma,6,1,63,57,9,4.0,6,11,Semi-Urban,HR Executive,30531,0 +32097,Male,36,Diploma,7,45,67,89,47,3.0,4,52,Urban,Software Engineer,22677,1 +32098,Male,29,Bachelors,6,62,95,74,42,0.0,6,39,Semi-Urban,Software Engineer,95893,1 +32099,Male,51,Diploma,7,48,49,47,32,8.0,6,86,Urban,ML Engineer,92770,0 +32100,Male,55,Diploma,1,65,42,61,18,7.0,7,71,Rural,HR Executive,90434,1 +32101,Male,43,Diploma,0,60,74,4,70,8.0,4,85,Semi-Urban,Data Analyst,28814,0 +32102,Female,57,Diploma,13,53,80,42,74,4.0,5,58,Urban,HR Executive,40279,0 +32103,Male,23,Masters,5,29,73,16,78,0.0,0,46,Urban,Manager,54457,0 +32104,Male,57,Masters,1,20,27,13,21,3.0,1,47,Semi-Urban,Data Analyst,87581,0 +32105,Male,43,High School,0,17,30,35,41,6.0,0,36,Urban,Software Engineer,121500,0 +32106,Male,27,Masters,14,50,60,70,58,9.0,6,72,Urban,HR Executive,92979,1 +32107,Male,22,High School,5,53,53,27,53,4.0,4,91,Urban,Software Engineer,127810,0 +32108,Other,38,Bachelors,7,60,16,92,27,9.0,4,92,Urban,ML Engineer,142644,1 +32109,Male,55,Masters,8,47,17,52,22,1.0,2,11,Semi-Urban,Data Analyst,111431,0 +32110,Male,36,Bachelors,19,46,74,55,85,2.0,0,30,Urban,Software Engineer,139692,0 +32111,Male,39,Bachelors,0,86,57,30,99,9.0,7,91,Semi-Urban,Manager,56074,1 +32112,Female,58,Bachelors,19,87,44,1,61,0.0,2,85,Urban,Manager,66252,0 +32113,Female,22,Bachelors,12,26,62,97,43,9.0,7,15,Semi-Urban,Data Analyst,131224,0 +32114,Male,59,Masters,5,86,28,90,82,5.0,7,23,Urban,ML Engineer,122363,0 +32115,Female,43,PhD,14,30,31,45,83,1.0,0,19,Urban,HR Executive,37848,0 +32116,Female,22,Diploma,19,38,81,41,40,5.0,3,10,Semi-Urban,Software Engineer,149629,0 +32117,Male,50,High School,13,50,36,77,78,3.0,7,71,Urban,Software Engineer,139654,0 +32118,Male,43,Bachelors,12,47,71,82,94,0.0,0,68,Semi-Urban,Software Engineer,131478,1 +32119,Male,58,Bachelors,4,78,44,60,43,3.0,0,29,Rural,ML Engineer,84119,0 +32120,Male,53,Masters,10,68,8,69,57,3.0,0,56,Semi-Urban,ML Engineer,100845,0 +32121,Female,53,Masters,0,91,19,57,19,6.0,0,29,Urban,Manager,29976,0 +32122,Male,48,Diploma,6,13,6,67,34,9.0,2,97,Semi-Urban,HR Executive,131980,0 +32123,Male,42,Bachelors,11,5,21,53,83,7.0,5,80,Urban,Manager,106219,0 +32124,Male,43,Bachelors,11,14,52,27,69,3.0,2,92,Urban,HR Executive,58925,0 +32125,Male,48,Diploma,17,32,55,36,64,6.0,5,96,Semi-Urban,ML Engineer,83695,0 +32126,Female,52,Masters,17,23,86,31,79,6.0,7,63,Urban,ML Engineer,49424,0 +32127,Male,43,Diploma,2,55,31,52,55,1.0,6,99,Urban,Data Analyst,82427,1 +32128,Male,51,Bachelors,16,49,94,17,56,5.0,5,82,Urban,HR Executive,68123,1 +32129,Female,33,Bachelors,16,28,79,92,44,6.0,0,4,Rural,Manager,54600,0 +32130,Male,32,High School,18,69,45,58,50,7.0,3,14,Semi-Urban,Manager,127069,0 +32131,Male,44,Bachelors,19,77,13,83,17,4.0,7,34,Semi-Urban,HR Executive,61535,0 +32132,Male,39,Masters,2,25,61,69,18,9.0,0,5,Urban,Data Analyst,113665,0 +32133,Male,23,Bachelors,6,47,39,84,75,6.0,6,65,Urban,Manager,58271,1 +32134,Male,52,Masters,14,44,42,93,54,0.0,3,62,Semi-Urban,ML Engineer,66225,1 +32135,Male,48,Bachelors,3,95,7,15,79,8.0,7,2,Urban,ML Engineer,90483,0 +32136,Male,38,Diploma,13,24,10,75,12,1.0,4,65,Semi-Urban,Software Engineer,123593,0 +32137,Male,24,Bachelors,19,42,44,32,8,1.0,1,28,Rural,Software Engineer,121762,0 +32138,Male,35,Bachelors,8,65,87,69,35,2.0,7,56,Semi-Urban,HR Executive,46257,1 +32139,Other,36,Diploma,18,26,82,9,81,9.0,1,31,Urban,HR Executive,83961,0 +32140,Male,47,Masters,18,3,87,60,94,6.0,3,62,Rural,Manager,118157,0 +32141,Female,42,High School,9,42,64,26,62,7.0,5,79,Rural,ML Engineer,77308,0 +32142,Female,50,Diploma,6,12,30,81,60,3.0,1,5,Urban,ML Engineer,146347,0 +32143,Male,42,High School,12,66,11,20,98,9.0,5,32,Rural,Software Engineer,49977,0 +32144,Female,49,Bachelors,5,19,95,44,91,1.0,7,85,Rural,Software Engineer,42988,1 +32145,Female,31,Bachelors,10,26,60,72,12,7.0,6,46,Urban,Manager,117625,0 +32146,Male,56,Diploma,19,31,82,28,70,8.0,1,93,Urban,Software Engineer,105529,0 +32147,Other,35,Diploma,9,22,48,60,55,6.0,3,70,Semi-Urban,HR Executive,135424,0 +32148,Male,21,Bachelors,9,73,49,34,70,0.0,0,94,Urban,HR Executive,29205,1 +32149,Male,24,High School,2,48,40,28,81,0.0,2,56,Urban,Data Analyst,93620,0 +32150,Female,48,Masters,14,35,85,30,25,7.0,4,34,Urban,Software Engineer,126260,0 +32151,Male,43,Bachelors,0,46,91,67,88,3.0,3,44,Urban,Software Engineer,30098,1 +32152,Female,37,Masters,6,94,58,66,7,2.0,1,42,Semi-Urban,ML Engineer,146171,1 +32153,Female,59,Diploma,8,78,24,87,10,7.0,0,52,Semi-Urban,HR Executive,121352,1 +32154,Other,36,Bachelors,8,4,6,46,31,2.0,0,64,Urban,ML Engineer,91566,0 +32155,Male,44,Bachelors,7,29,97,36,25,6.0,4,16,Rural,Data Analyst,83411,0 +32156,Other,41,Diploma,5,70,17,74,40,8.0,7,24,Urban,Software Engineer,114987,0 +32157,Male,43,Bachelors,17,31,74,85,67,5.0,1,73,Rural,HR Executive,87289,1 +32158,Male,40,Masters,15,63,79,60,19,1.0,0,22,Semi-Urban,ML Engineer,43200,0 +32159,Male,52,High School,9,66,78,43,50,2.0,2,57,Urban,HR Executive,25287,1 +32160,Female,25,Bachelors,7,71,55,99,55,8.0,5,18,Urban,Data Analyst,132636,1 +32161,Male,52,Masters,6,79,80,48,49,3.0,7,47,Semi-Urban,ML Engineer,116039,1 +32162,Male,34,Masters,11,68,77,71,42,2.0,6,55,Rural,HR Executive,124826,1 +32163,Male,39,Bachelors,19,63,40,81,8,0.0,5,50,Urban,HR Executive,79930,0 +32164,Male,44,Masters,17,78,77,82,20,1.0,1,23,Urban,Manager,88920,1 +32165,Other,56,Masters,2,18,57,35,92,6.0,3,65,Rural,ML Engineer,65667,0 +32166,Male,47,Bachelors,7,50,49,87,19,8.0,0,8,Rural,HR Executive,109391,0 +32167,Male,31,Bachelors,6,64,23,23,59,9.0,4,87,Rural,ML Engineer,117878,0 +32168,Female,37,Bachelors,10,88,51,77,41,7.0,1,42,Urban,Manager,62898,1 +32169,Male,50,High School,3,4,37,27,74,1.0,2,76,Urban,Software Engineer,58127,0 +32170,Female,55,Masters,9,69,87,63,30,1.0,5,26,Urban,ML Engineer,128769,1 +32171,Male,35,Bachelors,9,47,44,15,93,2.0,4,0,Urban,Software Engineer,60412,0 +32172,Male,45,Bachelors,3,20,18,44,59,7.0,1,0,Urban,HR Executive,123233,0 +32173,Male,58,Masters,1,48,26,38,72,8.0,6,60,Semi-Urban,Data Analyst,36447,0 +32174,Male,27,High School,1,17,58,77,76,3.0,2,81,Semi-Urban,ML Engineer,72378,0 +32175,Female,22,Bachelors,14,41,64,43,66,5.0,5,72,Semi-Urban,Data Analyst,111547,0 +32176,Male,23,High School,6,95,40,34,67,4.0,4,22,Urban,Manager,134217,0 +32177,Female,54,Masters,2,63,49,11,32,5.0,7,88,Semi-Urban,Manager,134201,0 +32178,Male,27,High School,11,44,64,89,81,2.0,1,16,Urban,HR Executive,140119,0 +32179,Male,40,Bachelors,17,51,1,67,14,7.0,4,48,Urban,Software Engineer,125654,0 +32180,Female,21,Diploma,0,0,29,6,63,3.0,5,24,Semi-Urban,Data Analyst,68922,0 +32181,Female,50,Diploma,19,1,38,55,58,2.0,1,10,Urban,Data Analyst,50700,0 +32182,Female,21,Bachelors,5,17,48,2,16,1.0,6,98,Urban,HR Executive,135954,0 +32183,Female,49,Diploma,5,80,10,81,17,2.0,4,33,Rural,Software Engineer,124486,0 +32184,Male,25,Bachelors,17,48,68,7,75,4.0,0,81,Urban,Manager,98671,0 +32185,Female,23,Masters,1,29,79,39,97,2.0,2,55,Urban,Software Engineer,140199,0 +32186,Male,50,Diploma,3,74,99,92,28,0.0,1,13,Semi-Urban,Software Engineer,69461,1 +32187,Male,21,Diploma,16,96,8,20,2,6.0,2,80,Urban,Manager,140794,0 +32188,Female,31,High School,12,67,37,6,73,4.0,0,74,Semi-Urban,HR Executive,111930,0 +32189,Male,37,High School,13,50,49,9,83,1.0,7,81,Semi-Urban,HR Executive,27355,0 +32190,Female,59,Masters,7,54,78,13,54,8.0,0,80,Semi-Urban,Software Engineer,46010,0 +32191,Male,41,Masters,1,39,10,27,28,3.0,3,3,Semi-Urban,HR Executive,36513,0 +32192,Male,48,Bachelors,10,32,67,83,85,9.0,5,22,Urban,ML Engineer,53024,0 +32193,Male,24,High School,11,59,8,95,50,9.0,6,7,Urban,ML Engineer,104712,0 +32194,Male,31,Bachelors,19,1,13,69,11,3.0,6,89,Semi-Urban,HR Executive,68695,0 +32195,Male,22,Masters,16,18,23,55,44,0.0,3,83,Rural,Manager,121203,0 +32196,Male,58,Bachelors,16,66,63,46,32,3.0,0,77,Semi-Urban,ML Engineer,77021,1 +32197,Female,29,Diploma,15,98,22,81,26,4.0,7,50,Rural,Data Analyst,62165,1 +32198,Male,59,Masters,2,17,41,60,50,0.0,5,2,Semi-Urban,Software Engineer,110044,0 +32199,Male,35,Masters,11,55,35,58,47,7.0,0,14,Semi-Urban,Manager,65144,0 +32200,Female,57,Bachelors,8,75,19,31,10,0.0,7,84,Semi-Urban,HR Executive,122774,0 +32201,Female,32,Masters,3,37,75,91,39,8.0,2,3,Urban,ML Engineer,72235,0 +32202,Male,57,Diploma,7,99,47,8,88,1.0,7,43,Semi-Urban,Software Engineer,113491,0 +32203,Female,26,High School,18,68,69,16,51,9.0,0,35,Urban,Data Analyst,96469,0 +32204,Male,32,Bachelors,9,71,36,71,50,1.0,4,20,Semi-Urban,HR Executive,37434,0 +32205,Male,53,Bachelors,13,96,18,25,19,9.0,6,94,Urban,ML Engineer,43834,0 +32206,Female,50,Masters,10,4,86,48,39,0.0,1,66,Urban,HR Executive,27641,0 +32207,Female,40,Diploma,10,50,97,39,78,7.0,1,29,Semi-Urban,ML Engineer,36168,0 +32208,Male,30,Bachelors,16,60,70,59,44,2.0,6,90,Urban,Data Analyst,79160,1 +32209,Male,32,Masters,17,45,84,90,43,6.0,4,6,Urban,HR Executive,109152,0 +32210,Male,28,Diploma,13,73,42,15,7,7.0,4,85,Rural,Software Engineer,29663,0 +32211,Male,43,High School,4,3,87,68,46,9.0,3,62,Urban,ML Engineer,95470,0 +32212,Female,24,Masters,1,92,82,49,44,7.0,1,41,Rural,Manager,87147,1 +32213,Male,49,Diploma,14,42,0,73,96,3.0,1,94,Rural,Data Analyst,142385,0 +32214,Male,53,High School,11,49,64,52,92,0.0,7,29,Rural,Data Analyst,35990,0 +32215,Male,24,High School,13,87,40,58,99,2.0,7,49,Rural,Software Engineer,116988,0 +32216,Female,35,Bachelors,19,26,12,11,89,7.0,2,59,Urban,Data Analyst,143948,0 +32217,Male,32,High School,5,98,38,67,66,6.0,0,67,Semi-Urban,HR Executive,60219,1 +32218,Female,40,PhD,12,81,67,83,75,6.0,0,64,Rural,Software Engineer,129114,1 +32219,Female,54,PhD,7,86,74,81,5,4.0,7,30,Rural,HR Executive,96962,1 +32220,Male,44,High School,3,7,25,31,5,5.0,0,15,Urban,Data Analyst,24130,0 +32221,Female,36,Bachelors,12,75,65,0,83,9.0,2,10,Semi-Urban,ML Engineer,148343,0 +32222,Female,55,Diploma,14,80,70,31,51,1.0,1,57,Urban,Manager,25991,0 +32223,Male,51,Masters,9,35,76,53,94,9.0,1,55,Urban,ML Engineer,52627,0 +32224,Male,27,Masters,11,72,48,35,69,2.0,3,88,Semi-Urban,ML Engineer,20756,1 +32225,Female,34,Bachelors,13,3,51,60,89,5.0,7,70,Urban,ML Engineer,103979,0 +32226,Male,52,Bachelors,2,14,22,7,72,4.0,7,74,Urban,ML Engineer,85432,0 +32227,Male,47,Diploma,13,58,77,42,79,7.0,5,71,Urban,ML Engineer,126131,1 +32228,Male,43,Masters,10,54,56,24,85,4.0,7,74,Rural,HR Executive,110966,0 +32229,Female,45,Bachelors,12,2,2,77,88,2.0,0,94,Urban,ML Engineer,85716,0 +32230,Male,52,Diploma,2,4,58,84,9,8.0,3,43,Rural,Data Analyst,22515,0 +32231,Male,55,Masters,15,63,35,93,69,8.0,3,89,Rural,Software Engineer,57552,1 +32232,Male,58,High School,3,28,94,55,13,6.0,6,8,Urban,HR Executive,120209,0 +32233,Female,29,Bachelors,7,69,10,99,30,8.0,5,10,Urban,ML Engineer,100592,0 +32234,Male,41,Diploma,7,51,12,30,43,8.0,2,6,Rural,Data Analyst,51766,0 +32235,Male,24,Masters,6,73,98,44,66,8.0,5,8,Rural,Manager,123228,0 +32236,Male,38,Bachelors,9,18,33,49,90,8.0,1,12,Rural,HR Executive,134900,0 +32237,Male,36,High School,13,4,77,18,57,1.0,2,64,Semi-Urban,Manager,24823,0 +32238,Male,32,Masters,4,40,6,82,79,1.0,2,3,Semi-Urban,ML Engineer,31375,0 +32239,Female,32,Masters,11,78,42,91,31,0.0,7,26,Urban,Manager,29579,0 +32240,Female,45,PhD,4,24,70,72,34,3.0,2,56,Urban,Data Analyst,125487,0 +32241,Female,51,Bachelors,11,98,21,44,39,0.0,5,46,Semi-Urban,ML Engineer,100638,0 +32242,Male,27,Diploma,7,99,24,58,4,5.0,7,47,Urban,Manager,120689,0 +32243,Male,43,High School,5,17,43,43,80,6.0,4,97,Urban,ML Engineer,116731,0 +32244,Other,53,High School,19,39,10,35,16,2.0,2,55,Semi-Urban,Manager,126893,0 +32245,Male,59,Diploma,9,52,66,37,70,3.0,0,74,Urban,Data Analyst,66619,0 +32246,Female,29,Masters,10,72,24,76,65,2.0,6,16,Semi-Urban,Software Engineer,38524,0 +32247,Female,56,Masters,15,92,14,7,64,7.0,2,70,Semi-Urban,ML Engineer,60302,0 +32248,Female,37,Bachelors,0,30,5,95,38,6.0,5,60,Urban,Manager,47518,0 +32249,Male,32,Bachelors,6,48,92,84,59,6.0,7,14,Urban,Manager,91367,1 +32250,Male,57,Diploma,16,78,27,60,78,4.0,7,26,Urban,Software Engineer,83289,0 +32251,Male,54,Bachelors,12,48,27,17,46,4.0,1,0,Rural,HR Executive,106620,0 +32252,Female,28,Bachelors,15,75,1,88,88,3.0,7,30,Urban,Manager,53952,0 +32253,Female,38,Diploma,14,0,41,1,2,7.0,5,8,Urban,Data Analyst,147210,0 +32254,Female,40,Diploma,12,16,18,51,56,5.0,7,74,Semi-Urban,ML Engineer,84827,0 +32255,Male,31,Bachelors,9,55,91,80,15,6.0,7,23,Rural,Data Analyst,22627,1 +32256,Female,45,Bachelors,8,4,59,87,87,1.0,2,38,Urban,Data Analyst,46328,0 +32257,Female,39,PhD,1,79,10,45,28,6.0,0,25,Urban,Data Analyst,31744,0 +32258,Male,37,Masters,19,75,82,92,17,5.0,6,75,Urban,Software Engineer,138956,1 +32259,Male,43,Diploma,9,19,46,38,71,0.0,1,43,Rural,Software Engineer,20388,0 +32260,Female,51,Bachelors,2,3,16,0,3,0.0,6,77,Urban,Software Engineer,43321,0 +32261,Male,23,Bachelors,18,56,43,23,99,2.0,6,40,Rural,Data Analyst,66790,0 +32262,Male,32,Diploma,8,86,97,44,80,7.0,3,15,Urban,Software Engineer,138862,1 +32263,Male,36,Masters,4,13,66,68,67,9.0,7,74,Urban,Data Analyst,62397,0 +32264,Female,31,Diploma,0,63,87,91,66,6.0,1,29,Rural,Manager,131357,1 +32265,Male,51,Masters,15,85,24,97,10,3.0,4,15,Urban,ML Engineer,109803,0 +32266,Male,47,Diploma,17,0,79,72,72,3.0,6,39,Urban,Manager,24944,0 +32267,Female,37,Masters,13,55,74,89,68,5.0,4,5,Urban,ML Engineer,70899,0 +32268,Female,48,Bachelors,11,74,24,78,84,2.0,6,17,Urban,Manager,106908,0 +32269,Female,22,Bachelors,16,46,98,44,44,3.0,1,75,Rural,Manager,68348,1 +32270,Male,58,Bachelors,12,22,21,64,10,5.0,5,92,Urban,Software Engineer,146991,0 +32271,Male,38,Diploma,9,52,64,80,65,6.0,2,83,Semi-Urban,Software Engineer,100671,1 +32272,Female,57,Masters,2,3,2,71,72,8.0,4,43,Urban,ML Engineer,131030,0 +32273,Other,33,Bachelors,1,52,80,3,73,9.0,5,32,Urban,HR Executive,101507,0 +32274,Male,36,Diploma,11,85,60,72,33,4.0,0,39,Urban,HR Executive,36945,1 +32275,Male,23,Masters,0,42,84,70,79,7.0,0,96,Urban,Software Engineer,84577,1 +32276,Male,34,Bachelors,4,98,61,28,85,7.0,7,23,Semi-Urban,Manager,56837,0 +32277,Female,41,High School,2,25,54,57,94,9.0,1,85,Rural,HR Executive,103618,0 +32278,Male,44,Bachelors,11,8,75,35,3,5.0,6,68,Urban,Data Analyst,91796,0 +32279,Male,24,Bachelors,19,80,40,58,87,1.0,1,16,Urban,Data Analyst,60567,0 +32280,Male,54,Bachelors,7,6,25,10,64,4.0,2,42,Urban,Data Analyst,38852,0 +32281,Male,54,Bachelors,7,49,53,51,33,1.0,7,26,Semi-Urban,ML Engineer,95755,0 +32282,Male,27,Diploma,19,17,20,70,28,6.0,2,48,Urban,Software Engineer,68789,0 +32283,Other,25,High School,4,81,26,28,51,9.0,6,95,Semi-Urban,ML Engineer,68863,0 +32284,Female,56,Bachelors,16,63,67,64,73,6.0,3,93,Urban,ML Engineer,137187,1 +32285,Male,40,Masters,10,35,52,37,18,5.0,5,73,Urban,Software Engineer,20611,0 +32286,Male,24,High School,9,3,1,78,46,3.0,6,21,Semi-Urban,HR Executive,147769,0 +32287,Male,43,Bachelors,10,3,59,68,64,8.0,6,67,Rural,ML Engineer,134131,0 +32288,Female,53,Bachelors,11,28,72,47,30,1.0,7,55,Urban,Software Engineer,64848,0 +32289,Male,24,PhD,16,56,9,37,33,0.0,4,54,Semi-Urban,ML Engineer,54181,0 +32290,Other,38,Diploma,0,96,46,10,51,5.0,6,30,Urban,Software Engineer,28898,0 +32291,Female,24,High School,12,16,35,10,41,5.0,7,77,Urban,HR Executive,38901,0 +32292,Male,55,Masters,0,62,59,0,32,4.0,0,99,Urban,Software Engineer,113100,0 +32293,Female,51,Bachelors,10,84,15,82,67,1.0,0,51,Urban,Software Engineer,121849,0 +32294,Female,41,Bachelors,15,66,14,32,20,9.0,1,87,Semi-Urban,Manager,129383,0 +32295,Male,48,Diploma,9,32,94,98,93,1.0,5,91,Rural,Manager,133092,1 +32296,Male,27,Masters,3,79,20,8,5,7.0,1,76,Urban,Software Engineer,74457,0 +32297,Male,34,Masters,2,95,20,86,54,4.0,3,96,Urban,ML Engineer,81254,1 +32298,Male,21,High School,9,13,0,24,78,1.0,4,57,Semi-Urban,Manager,79996,0 +32299,Male,24,Bachelors,18,45,86,85,43,1.0,0,36,Urban,Manager,95602,1 +32300,Male,48,Bachelors,12,81,61,88,15,5.0,5,71,Rural,HR Executive,116973,1 +32301,Male,53,Bachelors,10,82,78,60,24,1.0,6,30,Semi-Urban,Software Engineer,72348,1 +32302,Male,52,Bachelors,11,53,82,40,79,3.0,4,60,Urban,HR Executive,111940,1 +32303,Female,56,Bachelors,2,85,64,61,94,7.0,2,62,Urban,ML Engineer,98748,1 +32304,Female,45,Bachelors,2,78,9,36,62,9.0,3,14,Urban,Data Analyst,49997,0 +32305,Female,42,Masters,11,37,57,63,23,3.0,3,29,Urban,ML Engineer,86718,0 +32306,Male,25,Masters,1,46,81,80,31,1.0,5,6,Rural,ML Engineer,56249,0 +32307,Female,34,PhD,4,72,91,57,57,6.0,4,38,Urban,Software Engineer,58236,1 +32308,Other,45,Diploma,4,3,88,27,52,7.0,4,56,Urban,ML Engineer,113677,0 +32309,Male,25,Bachelors,18,45,10,38,69,2.0,7,37,Urban,HR Executive,62110,0 +32310,Female,25,High School,2,77,82,29,69,1.0,6,90,Semi-Urban,ML Engineer,73156,1 +32311,Male,24,PhD,16,85,58,10,28,5.0,3,16,Urban,ML Engineer,32904,0 +32312,Female,32,Masters,16,98,82,80,54,4.0,3,98,Rural,Manager,137912,1 +32313,Female,58,Bachelors,17,4,46,74,68,1.0,5,1,Semi-Urban,Software Engineer,32687,0 +32314,Female,52,Diploma,10,31,44,55,87,8.0,4,51,Urban,ML Engineer,39241,0 +32315,Male,57,Diploma,13,62,24,56,47,4.0,6,79,Urban,ML Engineer,55355,0 +32316,Male,57,Masters,17,59,5,45,97,2.0,1,54,Urban,Data Analyst,32053,0 +32317,Male,36,High School,8,1,99,99,88,4.0,2,42,Semi-Urban,Data Analyst,91275,1 +32318,Male,26,Masters,11,37,61,63,92,7.0,6,62,Rural,Software Engineer,56283,0 +32319,Male,58,Masters,14,51,78,12,86,9.0,5,12,Rural,Software Engineer,31784,0 +32320,Male,42,Bachelors,3,33,90,42,30,7.0,5,79,Urban,HR Executive,59593,1 +32321,Female,41,High School,12,63,67,51,97,7.0,1,25,Urban,Manager,127483,0 +32322,Male,51,High School,9,49,28,74,68,2.0,3,51,Urban,Software Engineer,27766,0 +32323,Female,41,High School,1,91,32,61,93,0.0,4,61,Urban,Software Engineer,77825,1 +32324,Male,26,High School,18,83,61,33,26,4.0,2,25,Urban,Data Analyst,66099,0 +32325,Male,26,Bachelors,12,52,44,37,48,4.0,4,50,Urban,ML Engineer,122494,0 +32326,Female,43,Diploma,7,18,57,49,68,3.0,2,84,Semi-Urban,Software Engineer,119803,0 +32327,Female,36,Bachelors,2,89,28,82,47,6.0,5,15,Urban,Software Engineer,136453,0 +32328,Male,43,Masters,16,41,19,35,38,2.0,4,33,Urban,Manager,64367,0 +32329,Female,32,Diploma,13,9,27,35,59,1.0,6,23,Urban,Manager,58709,0 +32330,Male,31,Masters,12,20,49,32,12,2.0,1,23,Semi-Urban,Data Analyst,132941,0 +32331,Female,23,Bachelors,3,38,62,95,64,0.0,0,4,Urban,HR Executive,131825,0 +32332,Female,54,Bachelors,15,11,14,91,26,5.0,0,30,Semi-Urban,HR Executive,113804,0 +32333,Male,21,PhD,18,22,0,77,76,2.0,5,41,Urban,HR Executive,109195,0 +32334,Female,23,Diploma,18,86,66,98,19,3.0,2,80,Semi-Urban,Software Engineer,130222,1 +32335,Female,44,Masters,11,93,66,7,3,3.0,3,72,Semi-Urban,HR Executive,146335,0 +32336,Other,58,Masters,17,88,12,66,0,5.0,2,14,Rural,Software Engineer,110817,0 +32337,Female,54,Diploma,8,44,8,7,99,4.0,5,66,Urban,Software Engineer,141967,0 +32338,Female,31,Bachelors,13,61,51,8,52,5.0,6,92,Urban,HR Executive,89290,0 +32339,Male,28,Masters,10,5,57,49,96,8.0,5,6,Rural,HR Executive,119787,0 +32340,Male,29,Masters,17,41,36,56,91,7.0,1,2,Urban,Data Analyst,34471,0 +32341,Female,48,Bachelors,13,74,39,86,26,6.0,2,37,Urban,Software Engineer,43924,0 +32342,Female,32,Bachelors,4,85,22,35,75,2.0,1,55,Semi-Urban,HR Executive,67768,0 +32343,Male,22,High School,17,29,69,12,47,5.0,6,14,Rural,HR Executive,110438,0 +32344,Male,29,Masters,1,86,15,85,13,8.0,7,62,Semi-Urban,Data Analyst,47788,1 +32345,Female,43,High School,3,57,72,79,35,5.0,7,28,Urban,ML Engineer,143131,0 +32346,Male,56,High School,11,11,93,63,74,8.0,3,13,Urban,Software Engineer,44712,0 +32347,Male,32,High School,11,38,14,85,76,1.0,0,81,Urban,HR Executive,106446,0 +32348,Male,56,Bachelors,19,25,22,62,12,1.0,4,7,Rural,Manager,145116,0 +32349,Female,35,Diploma,18,19,33,64,35,8.0,5,81,Urban,Data Analyst,33990,0 +32350,Male,50,Bachelors,13,6,49,35,74,3.0,0,21,Semi-Urban,Software Engineer,41525,0 +32351,Male,39,High School,16,29,42,5,44,4.0,2,55,Urban,ML Engineer,20304,0 +32352,Female,55,Masters,10,81,1,57,33,0.0,4,32,Semi-Urban,ML Engineer,134030,0 +32353,Female,30,Bachelors,4,74,93,52,2,5.0,4,39,Rural,Manager,45315,1 +32354,Male,22,Bachelors,16,4,61,56,8,5.0,4,56,Urban,Software Engineer,112841,0 +32355,Male,46,Bachelors,15,21,42,48,49,1.0,5,62,Urban,HR Executive,141483,0 +32356,Male,45,Masters,13,79,24,29,99,0.0,0,86,Urban,Manager,137651,0 +32357,Female,55,Bachelors,11,52,6,73,32,4.0,2,93,Urban,Data Analyst,65221,0 +32358,Male,40,Masters,2,53,7,35,62,0.0,4,77,Semi-Urban,Data Analyst,102601,0 +32359,Male,50,Masters,18,50,14,1,41,5.0,0,37,Semi-Urban,Manager,108807,0 +32360,Female,28,Bachelors,13,92,7,17,77,4.0,1,42,Urban,ML Engineer,116181,0 +32361,Female,25,Bachelors,6,55,69,98,42,7.0,3,61,Semi-Urban,ML Engineer,148206,1 +32362,Male,22,Diploma,12,89,4,23,80,1.0,0,8,Urban,Data Analyst,142068,0 +32363,Male,30,Masters,3,47,68,43,26,2.0,4,5,Urban,HR Executive,42498,0 +32364,Male,21,Bachelors,3,42,58,64,91,7.0,6,94,Rural,Software Engineer,144360,1 +32365,Male,28,Diploma,0,43,43,83,38,6.0,2,47,Urban,Software Engineer,44484,0 +32366,Male,47,Masters,7,10,93,46,93,1.0,0,72,Urban,Data Analyst,59837,0 +32367,Male,23,Diploma,12,13,11,6,67,6.0,1,44,Urban,HR Executive,49413,0 +32368,Male,25,Bachelors,18,39,19,91,66,9.0,4,63,Urban,Manager,117308,0 +32369,Male,40,Diploma,3,56,46,47,94,8.0,5,4,Urban,Software Engineer,144289,0 +32370,Female,44,Masters,18,32,6,46,86,9.0,3,54,Urban,ML Engineer,147533,0 +32371,Female,36,Bachelors,19,14,45,48,24,9.0,4,29,Urban,Data Analyst,81173,0 +32372,Male,26,High School,11,5,99,92,21,8.0,4,71,Rural,HR Executive,110762,1 +32373,Other,45,Bachelors,4,41,5,16,7,0.0,4,35,Urban,HR Executive,23743,0 +32374,Female,50,Diploma,18,86,74,68,29,8.0,3,31,Semi-Urban,Data Analyst,43452,1 +32375,Female,48,High School,13,54,0,41,65,5.0,0,35,Urban,Manager,74094,0 +32376,Male,54,Diploma,1,8,10,59,96,5.0,6,80,Rural,Manager,78569,0 +32377,Male,59,Masters,11,42,2,79,54,7.0,6,58,Urban,ML Engineer,133399,0 +32378,Male,44,Diploma,6,53,34,92,63,5.0,4,86,Rural,HR Executive,56380,1 +32379,Male,42,Bachelors,3,74,45,77,27,5.0,4,22,Semi-Urban,Manager,77713,0 +32380,Male,21,Masters,11,53,77,57,15,9.0,1,55,Rural,Data Analyst,81246,1 +32381,Female,35,Masters,8,2,55,36,38,7.0,0,18,Semi-Urban,ML Engineer,114549,0 +32382,Male,55,High School,1,22,41,50,42,4.0,0,67,Urban,HR Executive,116946,0 +32383,Female,34,Bachelors,15,2,6,47,32,8.0,2,51,Urban,Manager,68380,0 +32384,Male,33,Bachelors,16,17,72,34,31,6.0,3,73,Urban,ML Engineer,67685,0 +32385,Female,59,PhD,7,39,3,30,31,7.0,5,15,Urban,Software Engineer,65779,0 +32386,Male,27,Diploma,11,2,52,10,30,1.0,6,13,Urban,Data Analyst,29247,0 +32387,Other,36,High School,4,42,85,27,98,7.0,0,15,Urban,Manager,21970,0 +32388,Male,31,Bachelors,10,86,76,34,17,2.0,2,2,Semi-Urban,ML Engineer,125492,0 +32389,Other,33,High School,15,75,7,20,74,6.0,5,64,Rural,Data Analyst,134099,0 +32390,Male,56,Bachelors,4,15,16,12,71,1.0,4,3,Rural,Software Engineer,131647,0 +32391,Female,51,High School,14,11,74,72,27,2.0,0,96,Rural,ML Engineer,133224,1 +32392,Male,35,Diploma,6,66,79,50,82,8.0,3,57,Urban,Data Analyst,27836,1 +32393,Female,59,Diploma,8,8,26,85,0,3.0,7,27,Semi-Urban,HR Executive,138436,0 +32394,Female,50,High School,11,14,42,3,17,5.0,6,82,Urban,HR Executive,148804,0 +32395,Female,46,Bachelors,14,84,37,34,67,6.0,1,17,Urban,HR Executive,61141,0 +32396,Male,54,Bachelors,13,15,74,1,80,8.0,6,48,Rural,ML Engineer,57303,0 +32397,Female,52,Bachelors,18,44,21,16,35,4.0,6,31,Rural,Software Engineer,22993,0 +32398,Male,27,Bachelors,17,72,60,69,36,4.0,7,69,Urban,ML Engineer,48271,1 +32399,Male,35,Masters,3,59,56,53,87,9.0,2,53,Rural,Data Analyst,20831,0 +32400,Male,28,Masters,19,56,41,46,57,6.0,7,42,Semi-Urban,Data Analyst,131260,0 +32401,Male,50,Bachelors,10,35,91,78,81,4.0,1,35,Urban,Manager,88969,1 +32402,Female,57,High School,2,49,1,11,14,5.0,6,56,Urban,Data Analyst,61154,0 +32403,Male,36,High School,19,95,88,23,82,4.0,0,1,Urban,Data Analyst,53596,0 +32404,Male,28,Bachelors,18,65,1,17,40,8.0,0,74,Urban,Manager,134892,0 +32405,Female,46,Bachelors,19,70,99,97,56,8.0,2,86,Rural,HR Executive,91391,1 +32406,Other,30,Bachelors,8,28,83,53,11,4.0,0,63,Semi-Urban,ML Engineer,134861,0 +32407,Female,57,Diploma,5,61,30,13,25,3.0,6,31,Urban,ML Engineer,142270,0 +32408,Female,32,Masters,13,98,37,87,83,3.0,4,54,Semi-Urban,ML Engineer,65553,1 +32409,Male,24,Bachelors,2,85,83,65,4,3.0,5,49,Rural,Data Analyst,129603,1 +32410,Female,47,Diploma,18,41,33,69,19,3.0,7,30,Urban,Software Engineer,70395,0 +32411,Other,54,Bachelors,12,18,54,65,31,8.0,5,70,Semi-Urban,Software Engineer,63627,0 +32412,Male,35,High School,11,95,56,15,56,7.0,7,45,Urban,Data Analyst,61545,0 +32413,Male,34,Bachelors,13,62,6,83,81,1.0,3,39,Rural,Manager,135773,0 +32414,Female,55,High School,12,12,38,11,97,6.0,4,14,Urban,HR Executive,52902,0 +32415,Other,36,Bachelors,1,41,85,85,41,5.0,5,53,Rural,ML Engineer,72635,1 +32416,Male,35,Bachelors,5,95,95,3,31,2.0,0,57,Urban,Data Analyst,58885,1 +32417,Male,23,Diploma,5,55,19,65,1,8.0,1,71,Semi-Urban,Software Engineer,119245,0 +32418,Female,45,Masters,5,22,70,44,36,2.0,4,8,Semi-Urban,Data Analyst,64846,0 +32419,Male,25,Bachelors,5,27,19,13,48,3.0,5,64,Urban,Manager,145363,0 +32420,Male,26,Masters,4,73,53,21,52,3.0,6,82,Semi-Urban,Software Engineer,116795,0 +32421,Female,46,Diploma,10,35,46,34,51,5.0,5,28,Semi-Urban,Software Engineer,148076,0 +32422,Male,29,Masters,8,69,76,23,2,2.0,0,71,Urban,Data Analyst,128425,1 +32423,Male,45,Diploma,19,28,48,7,39,9.0,6,17,Semi-Urban,Data Analyst,129953,0 +32424,Other,32,Diploma,0,87,55,49,93,0.0,0,88,Semi-Urban,HR Executive,102551,1 +32425,Female,43,Diploma,8,76,45,90,2,9.0,6,30,Urban,ML Engineer,95221,1 +32426,Female,59,Diploma,18,38,59,45,72,0.0,6,92,Semi-Urban,HR Executive,25549,0 +32427,Female,52,Bachelors,11,53,83,11,87,6.0,5,26,Semi-Urban,HR Executive,149096,0 +32428,Female,28,Bachelors,15,43,52,95,23,5.0,1,36,Rural,Data Analyst,30320,0 +32429,Female,51,Bachelors,1,40,48,65,48,1.0,0,85,Rural,HR Executive,44476,0 +32430,Male,23,Diploma,10,60,40,31,3,1.0,4,99,Rural,Software Engineer,55053,0 +32431,Female,50,Bachelors,14,26,95,88,96,0.0,6,20,Rural,Software Engineer,139637,0 +32432,Male,55,Bachelors,14,44,42,65,32,1.0,6,97,Urban,Software Engineer,101626,1 +32433,Female,29,Diploma,1,65,98,56,53,1.0,6,80,Semi-Urban,Manager,64831,1 +32434,Male,50,High School,4,8,18,84,99,6.0,5,35,Rural,ML Engineer,72447,0 +32435,Male,34,Masters,9,77,59,59,63,4.0,3,30,Rural,ML Engineer,41725,0 +32436,Male,44,High School,6,2,72,84,1,4.0,0,42,Urban,HR Executive,60702,0 +32437,Female,29,Diploma,15,57,3,64,37,2.0,6,43,Urban,ML Engineer,46945,0 +32438,Other,42,Bachelors,0,87,26,69,9,6.0,6,51,Urban,Data Analyst,81366,0 +32439,Other,56,Bachelors,0,20,92,60,12,1.0,6,96,Semi-Urban,HR Executive,89471,1 +32440,Male,51,Masters,9,19,81,97,73,9.0,3,20,Semi-Urban,HR Executive,48248,0 +32441,Male,48,Masters,14,77,48,52,21,3.0,3,94,Urban,Manager,128164,1 +32442,Male,54,High School,10,56,17,65,85,2.0,6,23,Rural,HR Executive,110066,0 +32443,Male,57,Bachelors,0,64,25,7,0,4.0,7,7,Urban,ML Engineer,145634,0 +32444,Female,56,Bachelors,14,13,36,38,55,0.0,1,18,Urban,ML Engineer,107320,0 +32445,Female,55,Diploma,4,12,12,13,64,7.0,5,44,Urban,Manager,147012,0 +32446,Male,21,Masters,6,24,92,2,37,2.0,6,13,Urban,ML Engineer,62299,0 +32447,Male,32,Bachelors,12,48,3,49,75,0.0,2,89,Urban,Data Analyst,117774,0 +32448,Male,24,Bachelors,12,74,66,4,55,3.0,3,80,Rural,Software Engineer,69157,0 +32449,Male,21,Bachelors,10,51,30,89,9,8.0,1,3,Urban,Manager,97739,0 +32450,Female,59,PhD,14,20,10,93,45,7.0,3,74,Rural,HR Executive,93955,0 +32451,Female,53,Bachelors,9,78,95,91,93,2.0,3,93,Urban,Manager,125564,1 +32452,Female,47,Diploma,16,9,78,70,20,6.0,4,65,Rural,Software Engineer,71235,0 +32453,Male,46,Masters,0,14,51,83,53,8.0,2,84,Urban,Data Analyst,47158,0 +32454,Male,50,High School,4,24,46,12,29,3.0,2,63,Rural,Manager,117106,0 +32455,Male,26,Masters,16,64,70,68,9,0.0,0,42,Rural,Data Analyst,79684,1 +32456,Male,40,Bachelors,7,29,20,7,19,0.0,2,25,Urban,HR Executive,140808,0 +32457,Female,42,Diploma,13,65,33,57,6,6.0,4,84,Urban,Data Analyst,89424,0 +32458,Female,59,Masters,11,17,93,85,17,4.0,5,38,Semi-Urban,Data Analyst,78369,0 +32459,Female,26,Masters,10,57,48,99,61,0.0,2,67,Semi-Urban,HR Executive,24239,1 +32460,Male,28,Bachelors,6,12,33,3,12,8.0,5,31,Urban,ML Engineer,100752,0 +32461,Female,39,Bachelors,0,32,80,63,29,6.0,0,55,Rural,Data Analyst,59114,0 +32462,Male,40,Masters,12,45,55,85,96,3.0,0,3,Urban,Software Engineer,74107,0 +32463,Male,22,Diploma,15,59,52,19,91,9.0,2,65,Rural,ML Engineer,65258,0 +32464,Male,59,Diploma,18,53,71,50,38,9.0,3,19,Urban,Manager,137006,0 +32465,Male,47,Masters,1,53,18,97,10,6.0,3,61,Semi-Urban,Software Engineer,93996,0 +32466,Female,27,Bachelors,18,94,21,20,52,3.0,3,24,Semi-Urban,Manager,77655,0 +32467,Female,23,Masters,16,60,62,5,54,5.0,3,55,Semi-Urban,Data Analyst,110349,0 +32468,Male,50,Diploma,19,30,23,12,38,8.0,3,11,Rural,Data Analyst,32753,0 +32469,Male,46,Bachelors,5,76,3,51,86,7.0,7,13,Urban,Software Engineer,149429,0 +32470,Male,23,Diploma,17,1,51,98,76,8.0,6,9,Urban,Software Engineer,144739,0 +32471,Male,56,Masters,13,47,84,34,73,7.0,4,40,Urban,ML Engineer,147633,0 +32472,Male,48,Diploma,8,54,23,96,58,0.0,6,81,Urban,ML Engineer,40333,1 +32473,Female,26,PhD,14,61,32,69,55,0.0,2,11,Urban,Manager,44705,0 +32474,Male,22,High School,10,84,80,13,72,8.0,0,97,Rural,HR Executive,92305,1 +32475,Female,47,Masters,8,41,95,26,54,4.0,0,39,Urban,HR Executive,80282,0 +32476,Male,38,High School,11,2,50,64,71,7.0,7,10,Urban,HR Executive,123007,0 +32477,Male,25,High School,19,65,83,21,8,1.0,1,39,Semi-Urban,Data Analyst,113621,0 +32478,Male,22,Bachelors,5,4,23,95,29,2.0,7,62,Urban,Manager,46308,0 +32479,Female,52,Masters,11,98,79,94,83,3.0,1,12,Rural,Software Engineer,35139,1 +32480,Male,22,Diploma,4,86,63,65,36,8.0,1,84,Urban,ML Engineer,58837,1 +32481,Male,42,Diploma,3,28,4,77,72,6.0,7,43,Semi-Urban,Data Analyst,119645,0 +32482,Female,31,Bachelors,12,40,72,19,40,3.0,6,75,Urban,Software Engineer,40972,0 +32483,Male,55,High School,13,29,74,91,17,2.0,1,12,Rural,HR Executive,104281,0 +32484,Female,25,High School,14,30,9,68,4,2.0,7,88,Semi-Urban,Data Analyst,141515,0 +32485,Male,56,PhD,10,9,40,29,48,6.0,1,61,Rural,HR Executive,122691,0 +32486,Female,46,Diploma,18,92,45,55,60,2.0,3,75,Semi-Urban,HR Executive,90797,1 +32487,Male,53,Bachelors,11,66,94,20,83,8.0,0,56,Semi-Urban,Data Analyst,115177,1 +32488,Male,54,Bachelors,19,71,57,13,46,4.0,3,90,Semi-Urban,Manager,29342,0 +32489,Male,22,Masters,3,60,1,83,70,5.0,0,16,Urban,Data Analyst,91424,0 +32490,Male,54,Masters,9,44,37,33,1,8.0,2,20,Rural,HR Executive,87581,0 +32491,Female,31,Diploma,11,56,99,31,93,5.0,0,79,Urban,Data Analyst,30779,1 +32492,Female,23,Masters,13,30,34,89,90,2.0,5,62,Rural,HR Executive,38881,0 +32493,Male,35,Diploma,4,78,43,72,59,6.0,6,23,Urban,HR Executive,83234,0 +32494,Male,36,Bachelors,7,33,28,1,20,2.0,3,83,Urban,Manager,94968,0 +32495,Male,26,Diploma,2,95,41,91,72,8.0,5,98,Semi-Urban,ML Engineer,110428,1 +32496,Female,33,Bachelors,0,40,24,23,69,2.0,4,92,Urban,Data Analyst,72079,0 +32497,Male,25,Masters,18,89,22,23,23,6.0,6,92,Urban,Software Engineer,51339,0 +32498,Male,21,Bachelors,10,90,72,41,9,5.0,1,59,Urban,HR Executive,101351,1 +32499,Female,57,Bachelors,12,64,45,92,98,4.0,1,99,Semi-Urban,Data Analyst,44624,1 +32500,Male,34,Masters,0,5,65,80,46,4.0,1,22,Semi-Urban,ML Engineer,149415,0 +32501,Male,53,PhD,10,60,91,43,94,6.0,0,23,Urban,Data Analyst,90805,0 +32502,Male,59,Bachelors,8,19,20,46,72,5.0,4,86,Urban,Manager,82700,0 +32503,Female,51,Bachelors,19,61,37,10,8,2.0,0,40,Urban,HR Executive,66723,0 +32504,Male,22,Bachelors,9,77,75,87,92,7.0,4,49,Semi-Urban,Manager,126734,1 +32505,Female,39,Masters,1,80,75,37,31,1.0,0,98,Rural,HR Executive,38254,1 +32506,Male,59,Bachelors,0,8,92,24,64,6.0,0,65,Urban,Manager,124523,0 +32507,Male,22,Bachelors,19,47,97,85,13,8.0,0,10,Urban,Software Engineer,126991,1 +32508,Female,33,Bachelors,17,22,65,96,51,1.0,5,70,Rural,Manager,114863,1 +32509,Male,46,PhD,3,23,14,91,98,7.0,5,36,Semi-Urban,Software Engineer,99323,0 +32510,Male,51,Bachelors,16,32,20,10,91,1.0,4,20,Urban,Data Analyst,59812,0 +32511,Male,48,Diploma,1,89,48,51,28,6.0,4,85,Urban,Manager,105711,1 +32512,Male,35,Bachelors,17,57,57,18,88,7.0,1,14,Semi-Urban,Data Analyst,25210,0 +32513,Female,28,Bachelors,10,26,18,82,88,8.0,3,12,Urban,Data Analyst,96949,0 +32514,Male,21,PhD,8,3,9,30,30,0.0,3,30,Urban,Data Analyst,30863,0 +32515,Female,58,Masters,16,92,1,58,40,8.0,7,4,Urban,Software Engineer,74502,0 +32516,Female,48,Diploma,18,21,21,73,94,1.0,4,84,Urban,Manager,142871,0 +32517,Female,52,Bachelors,3,2,91,7,89,7.0,1,64,Semi-Urban,Data Analyst,46463,0 +32518,Female,50,Masters,14,30,3,66,8,4.0,0,46,Urban,HR Executive,61842,0 +32519,Female,53,Bachelors,0,83,29,90,13,9.0,0,76,Rural,ML Engineer,79746,1 +32520,Male,57,Diploma,9,12,84,67,61,5.0,3,19,Urban,Manager,135610,0 +32521,Male,39,Masters,9,76,77,26,46,6.0,7,50,Semi-Urban,HR Executive,147402,0 +32522,Male,28,High School,17,18,21,10,68,1.0,2,56,Urban,ML Engineer,105459,0 +32523,Female,39,PhD,6,36,56,29,80,5.0,5,94,Urban,Software Engineer,120962,0 +32524,Female,54,Bachelors,9,97,85,40,39,6.0,1,76,Urban,Manager,50688,1 +32525,Male,49,Bachelors,7,82,81,91,4,2.0,0,45,Urban,ML Engineer,23667,1 +32526,Female,23,Bachelors,15,37,83,29,98,9.0,4,90,Semi-Urban,Data Analyst,99981,0 +32527,Male,57,High School,15,30,31,65,67,9.0,6,94,Semi-Urban,Data Analyst,103106,0 +32528,Male,45,Bachelors,7,84,65,3,58,5.0,5,17,Urban,HR Executive,84003,0 +32529,Male,29,Diploma,9,80,26,52,36,0.0,5,1,Urban,HR Executive,119943,0 +32530,Male,28,Bachelors,15,18,16,92,0,9.0,0,35,Urban,ML Engineer,68975,0 +32531,Female,27,PhD,0,71,14,60,14,5.0,5,4,Urban,Data Analyst,113719,0 +32532,Male,33,High School,19,18,50,11,68,8.0,7,89,Rural,Software Engineer,90025,0 +32533,Male,53,High School,0,48,66,77,56,4.0,4,17,Urban,ML Engineer,72798,0 +32534,Other,52,Diploma,11,45,51,42,36,4.0,6,77,Urban,Data Analyst,33639,0 +32535,Female,41,Bachelors,4,47,63,50,20,6.0,6,79,Rural,Manager,73930,0 +32536,Male,41,Bachelors,9,40,97,57,18,3.0,5,95,Urban,Software Engineer,121619,1 +32537,Male,52,Bachelors,9,60,38,93,51,1.0,5,79,Rural,Manager,26667,1 +32538,Male,36,Bachelors,8,55,35,73,5,0.0,3,76,Urban,Data Analyst,121267,1 +32539,Other,25,Masters,6,15,35,94,38,9.0,6,29,Urban,HR Executive,21074,0 +32540,Female,56,Bachelors,11,87,11,47,79,6.0,0,43,Rural,HR Executive,66532,0 +32541,Female,43,Bachelors,7,70,3,6,2,2.0,1,22,Semi-Urban,HR Executive,122934,0 +32542,Male,41,Diploma,7,12,10,75,14,6.0,2,81,Urban,ML Engineer,59897,0 +32543,Male,44,Bachelors,13,24,47,6,51,0.0,1,87,Urban,ML Engineer,116392,0 +32544,Male,26,PhD,16,16,17,34,85,0.0,6,1,Urban,Data Analyst,41024,0 +32545,Male,24,High School,18,0,14,30,45,5.0,6,8,Urban,Manager,66138,0 +32546,Male,30,Bachelors,7,62,44,14,92,0.0,0,84,Urban,Manager,87714,0 +32547,Female,32,Masters,4,61,17,21,9,0.0,7,68,Urban,Software Engineer,82374,0 +32548,Male,50,Bachelors,14,46,61,31,17,5.0,6,86,Urban,HR Executive,34587,0 +32549,Male,21,Bachelors,14,30,4,56,10,8.0,3,92,Urban,HR Executive,130892,0 +32550,Female,39,Masters,2,43,53,18,11,2.0,4,62,Rural,Manager,21752,0 +32551,Male,57,Bachelors,15,62,18,44,99,8.0,7,25,Urban,Software Engineer,88324,0 +32552,Female,42,Bachelors,3,32,82,66,41,0.0,1,68,Semi-Urban,HR Executive,48091,1 +32553,Male,22,Diploma,8,40,47,59,73,7.0,2,48,Urban,Data Analyst,35513,0 +32554,Male,22,Bachelors,5,6,87,17,81,0.0,7,97,Urban,Data Analyst,106451,0 +32555,Male,59,High School,9,29,16,66,80,9.0,4,52,Urban,HR Executive,84426,0 +32556,Other,39,Diploma,3,22,43,51,79,7.0,7,16,Urban,HR Executive,30219,0 +32557,Female,59,Bachelors,9,83,43,5,88,8.0,4,57,Rural,Data Analyst,130558,0 +32558,Male,27,Bachelors,18,13,17,88,5,0.0,1,77,Semi-Urban,Manager,53097,0 +32559,Male,51,Bachelors,14,35,61,88,7,2.0,0,7,Urban,HR Executive,75222,0 +32560,Female,38,Bachelors,8,69,53,54,64,7.0,2,97,Urban,HR Executive,34495,1 +32561,Male,21,High School,12,55,19,89,54,3.0,4,63,Semi-Urban,HR Executive,60374,0 +32562,Other,21,PhD,4,60,4,79,2,2.0,3,9,Urban,Software Engineer,88962,0 +32563,Other,38,High School,1,64,46,36,92,1.0,5,4,Semi-Urban,Manager,30694,0 +32564,Female,58,Bachelors,15,95,15,44,95,9.0,2,64,Rural,Software Engineer,131545,0 +32565,Other,23,Diploma,2,39,22,73,74,8.0,7,73,Rural,ML Engineer,70577,0 +32566,Male,38,Masters,15,14,88,33,70,8.0,6,19,Urban,ML Engineer,53573,0 +32567,Male,42,High School,3,97,36,15,53,6.0,6,27,Semi-Urban,HR Executive,88857,0 +32568,Male,28,Bachelors,3,24,14,20,35,2.0,4,53,Urban,Data Analyst,104848,0 +32569,Male,58,Masters,17,52,12,12,52,7.0,0,9,Urban,HR Executive,120420,0 +32570,Other,30,Diploma,16,55,97,51,34,9.0,2,6,Semi-Urban,Data Analyst,28335,0 +32571,Male,23,Bachelors,5,31,5,74,9,2.0,2,14,Urban,Software Engineer,138779,0 +32572,Female,37,Masters,18,34,65,15,17,4.0,1,53,Semi-Urban,Manager,72269,0 +32573,Female,27,Masters,1,22,6,35,18,4.0,2,95,Urban,Manager,118850,0 +32574,Male,57,High School,11,75,26,98,37,9.0,4,99,Urban,HR Executive,133777,1 +32575,Male,42,Bachelors,7,32,92,19,38,8.0,4,21,Rural,Manager,28014,0 +32576,Male,31,Masters,17,47,52,54,17,4.0,2,4,Semi-Urban,Manager,144380,0 +32577,Male,39,High School,4,74,92,37,75,5.0,6,86,Urban,Manager,34124,1 +32578,Male,49,Bachelors,0,27,59,61,12,1.0,6,13,Rural,Software Engineer,57304,0 +32579,Male,48,Bachelors,1,89,98,4,61,5.0,5,87,Urban,Software Engineer,107291,1 +32580,Male,48,Masters,17,94,21,98,26,0.0,4,14,Urban,Manager,33084,0 +32581,Female,56,Diploma,15,37,42,93,45,7.0,6,25,Urban,HR Executive,29785,0 +32582,Male,44,PhD,18,36,70,99,49,8.0,7,69,Semi-Urban,Manager,128878,1 +32583,Male,31,High School,9,2,2,74,60,1.0,5,77,Urban,Software Engineer,117006,0 +32584,Female,51,Diploma,12,82,78,75,89,4.0,0,2,Semi-Urban,Data Analyst,66423,0 +32585,Male,28,High School,4,74,74,40,4,3.0,5,73,Rural,Manager,46152,1 +32586,Male,38,Diploma,3,39,74,10,60,6.0,4,35,Urban,Manager,142092,0 +32587,Female,52,High School,0,31,27,78,64,1.0,6,31,Urban,ML Engineer,104323,0 +32588,Female,51,Masters,15,30,52,80,51,7.0,0,84,Semi-Urban,Data Analyst,96988,1 +32589,Female,32,PhD,5,98,38,84,1,6.0,0,73,Urban,Software Engineer,98631,1 +32590,Male,48,Bachelors,5,44,1,14,74,7.0,3,24,Semi-Urban,Software Engineer,121221,0 +32591,Male,28,Masters,16,2,76,16,59,0.0,1,43,Semi-Urban,Software Engineer,122566,0 +32592,Male,39,Bachelors,6,20,52,90,41,2.0,2,7,Urban,HR Executive,78620,0 +32593,Other,44,Bachelors,17,19,15,29,47,5.0,0,17,Rural,Manager,42046,0 +32594,Male,50,Bachelors,1,92,83,75,98,7.0,6,65,Semi-Urban,HR Executive,102730,1 +32595,Male,52,Bachelors,3,13,66,69,59,4.0,0,45,Urban,Software Engineer,37879,0 +32596,Female,31,Diploma,3,35,45,14,65,9.0,6,57,Urban,Data Analyst,110731,0 +32597,Other,35,Masters,7,21,77,96,10,8.0,6,2,Rural,Manager,20518,0 +32598,Female,22,PhD,12,71,57,42,3,7.0,4,91,Semi-Urban,Manager,134569,1 +32599,Male,30,High School,7,35,69,3,66,1.0,6,72,Rural,ML Engineer,101819,0 +32600,Male,22,High School,2,34,43,4,75,7.0,1,95,Urban,Data Analyst,37431,0 +32601,Female,48,PhD,7,54,40,3,27,1.0,0,8,Semi-Urban,Software Engineer,117425,0 +32602,Male,31,High School,4,45,80,21,18,8.0,1,48,Urban,HR Executive,66584,0 +32603,Male,47,Diploma,6,79,15,1,87,2.0,5,54,Semi-Urban,Software Engineer,70244,0 +32604,Male,51,PhD,5,88,64,44,23,7.0,7,38,Urban,Software Engineer,106221,0 +32605,Female,28,Diploma,12,29,33,23,21,0.0,4,68,Semi-Urban,HR Executive,115271,0 +32606,Male,27,Masters,18,55,37,7,28,5.0,3,52,Urban,ML Engineer,60389,0 +32607,Female,45,Bachelors,5,12,19,49,97,2.0,6,39,Semi-Urban,Manager,128994,0 +32608,Male,37,Bachelors,15,64,3,34,79,6.0,1,97,Rural,Software Engineer,129549,0 +32609,Male,40,Bachelors,19,12,3,61,68,2.0,7,17,Urban,Manager,147938,0 +32610,Other,40,Bachelors,3,16,28,72,40,2.0,7,95,Semi-Urban,Software Engineer,79162,0 +32611,Male,22,High School,6,23,51,65,9,5.0,2,56,Semi-Urban,Manager,126229,0 +32612,Female,22,Diploma,15,4,87,96,30,2.0,6,79,Urban,ML Engineer,42725,1 +32613,Male,46,Masters,19,98,85,90,61,3.0,3,52,Urban,ML Engineer,130887,1 +32614,Male,48,High School,11,61,22,88,40,5.0,0,51,Semi-Urban,Manager,53796,0 +32615,Female,34,Bachelors,9,35,98,53,41,5.0,2,58,Rural,ML Engineer,130317,1 +32616,Female,34,Diploma,13,10,10,14,54,0.0,5,11,Urban,Manager,82731,0 +32617,Female,35,Diploma,9,75,69,85,37,0.0,4,51,Semi-Urban,Data Analyst,149062,1 +32618,Male,36,High School,12,86,57,9,2,3.0,3,73,Rural,Manager,105303,0 +32619,Male,59,Bachelors,6,54,28,64,23,5.0,0,2,Rural,Manager,83394,0 +32620,Female,55,Diploma,3,5,98,6,50,4.0,4,16,Urban,Software Engineer,55752,0 +32621,Male,24,Bachelors,18,39,3,41,8,1.0,0,52,Urban,Manager,133809,0 +32622,Female,39,Bachelors,18,59,93,25,61,2.0,0,35,Semi-Urban,Data Analyst,125216,0 +32623,Male,56,High School,14,20,90,33,83,9.0,3,14,Urban,Data Analyst,65259,0 +32624,Female,54,Diploma,5,67,77,40,33,2.0,3,52,Urban,ML Engineer,88176,0 +32625,Female,55,Bachelors,19,9,23,60,76,5.0,7,11,Urban,ML Engineer,36496,0 +32626,Male,26,Bachelors,19,95,41,67,76,6.0,7,21,Semi-Urban,HR Executive,50440,0 +32627,Female,28,Masters,12,31,32,30,3,2.0,3,50,Urban,Data Analyst,94327,0 +32628,Male,44,Bachelors,3,0,63,31,0,4.0,2,20,Urban,ML Engineer,42434,0 +32629,Male,55,Masters,10,40,67,1,30,5.0,0,18,Urban,ML Engineer,120535,0 +32630,Male,50,Masters,7,5,14,47,66,0.0,5,45,Semi-Urban,Data Analyst,90042,0 +32631,Male,48,Bachelors,11,18,94,92,72,5.0,4,14,Urban,Data Analyst,144538,0 +32632,Male,36,High School,7,9,26,39,23,2.0,3,28,Semi-Urban,ML Engineer,40799,0 +32633,Male,41,Bachelors,0,75,78,23,48,2.0,1,4,Urban,ML Engineer,58355,0 +32634,Male,53,Masters,7,78,83,49,28,0.0,1,50,Rural,Data Analyst,28089,1 +32635,Male,27,Bachelors,1,96,59,27,77,7.0,6,52,Rural,Software Engineer,20187,0 +32636,Male,31,Bachelors,9,93,42,16,11,5.0,5,18,Urban,Software Engineer,130390,0 +32637,Male,47,Bachelors,19,3,97,89,89,6.0,0,64,Urban,Manager,134544,1 +32638,Female,54,High School,1,28,96,23,97,6.0,2,10,Urban,Data Analyst,78862,0 +32639,Female,51,Diploma,8,84,31,79,98,6.0,1,95,Urban,Manager,38372,1 +32640,Female,51,High School,6,53,21,27,77,6.0,5,90,Urban,Manager,136199,0 +32641,Male,47,PhD,6,26,7,58,96,8.0,3,53,Urban,HR Executive,67723,0 +32642,Male,27,Masters,8,13,38,77,59,0.0,6,99,Urban,ML Engineer,137860,0 +32643,Female,48,Bachelors,19,44,59,17,68,8.0,1,71,Semi-Urban,Manager,104359,0 +32644,Female,32,High School,13,57,97,47,62,6.0,7,91,Urban,Manager,106314,1 +32645,Male,57,Bachelors,3,50,11,13,25,0.0,5,22,Urban,ML Engineer,78468,0 +32646,Female,23,Masters,13,39,75,67,79,3.0,3,42,Rural,HR Executive,86989,0 +32647,Male,46,Bachelors,15,41,62,11,4,7.0,2,45,Urban,Data Analyst,120862,0 +32648,Male,53,Diploma,7,38,74,89,34,7.0,2,32,Rural,ML Engineer,71570,0 +32649,Female,48,Bachelors,3,46,45,37,82,1.0,1,63,Semi-Urban,HR Executive,128971,0 +32650,Male,42,High School,13,72,75,52,5,2.0,0,36,Semi-Urban,Software Engineer,54036,1 +32651,Male,39,Masters,9,73,37,86,96,3.0,2,51,Rural,Data Analyst,138498,1 +32652,Male,33,High School,14,83,53,21,75,3.0,4,16,Rural,Manager,110741,0 +32653,Male,45,Diploma,3,91,25,8,57,1.0,4,61,Urban,Data Analyst,34381,0 +32654,Male,24,Bachelors,7,13,11,22,3,3.0,5,94,Urban,Data Analyst,90741,0 +32655,Male,59,Bachelors,8,55,93,44,22,4.0,5,74,Rural,Manager,142553,1 +32656,Other,30,Bachelors,7,68,10,59,90,5.0,3,23,Rural,Manager,25319,0 +32657,Female,45,Masters,5,5,37,75,82,0.0,5,79,Urban,Software Engineer,60003,0 +32658,Male,26,Bachelors,8,25,35,12,34,4.0,7,98,Rural,HR Executive,125454,0 +32659,Male,55,Diploma,18,8,68,5,56,4.0,5,98,Urban,Software Engineer,76545,0 +32660,Male,54,High School,16,45,84,88,61,7.0,7,95,Urban,ML Engineer,53151,1 +32661,Female,58,Masters,14,53,40,49,27,5.0,2,61,Semi-Urban,Manager,101480,0 +32662,Male,39,Diploma,2,83,82,36,42,7.0,0,5,Urban,ML Engineer,90271,0 +32663,Male,54,Bachelors,16,4,64,31,63,6.0,7,3,Urban,Software Engineer,41559,0 +32664,Male,36,Bachelors,6,77,88,31,74,7.0,2,28,Urban,Manager,33023,0 +32665,Male,41,Diploma,14,40,61,48,15,6.0,5,31,Semi-Urban,Data Analyst,32140,0 +32666,Female,26,Diploma,12,55,10,19,58,7.0,5,62,Semi-Urban,HR Executive,86563,0 +32667,Female,24,Masters,2,72,13,52,30,4.0,2,26,Semi-Urban,Software Engineer,128565,0 +32668,Female,35,Bachelors,18,98,45,25,64,0.0,1,31,Rural,Software Engineer,106078,0 +32669,Male,59,PhD,9,31,89,56,13,9.0,7,48,Urban,Data Analyst,73243,0 +32670,Female,48,Diploma,5,41,57,39,80,0.0,4,16,Rural,ML Engineer,140489,0 +32671,Male,32,Bachelors,6,25,53,66,34,9.0,5,48,Urban,Software Engineer,54256,0 +32672,Male,43,PhD,9,29,97,77,90,2.0,5,74,Semi-Urban,Data Analyst,63599,1 +32673,Male,21,Bachelors,18,49,80,26,84,7.0,2,42,Semi-Urban,Software Engineer,112470,0 +32674,Male,29,Masters,17,59,84,62,27,5.0,0,68,Urban,Software Engineer,118279,1 +32675,Male,58,High School,6,88,2,81,52,9.0,4,80,Semi-Urban,ML Engineer,149811,1 +32676,Female,41,Masters,4,11,23,58,86,7.0,1,15,Urban,Software Engineer,102599,0 +32677,Male,26,PhD,5,29,80,96,21,0.0,3,64,Urban,ML Engineer,39280,1 +32678,Male,51,Bachelors,7,40,92,12,5,1.0,5,60,Semi-Urban,Software Engineer,146572,0 +32679,Female,31,PhD,5,3,19,37,51,4.0,6,55,Semi-Urban,ML Engineer,92141,0 +32680,Male,58,Bachelors,13,38,71,46,87,5.0,0,17,Urban,Software Engineer,20795,0 +32681,Female,37,Bachelors,5,81,74,5,4,1.0,5,26,Urban,Software Engineer,147225,0 +32682,Female,54,Masters,3,31,1,54,79,5.0,2,14,Semi-Urban,Data Analyst,87227,0 +32683,Male,49,Diploma,15,13,49,34,62,0.0,3,44,Rural,Data Analyst,112329,0 +32684,Male,51,Bachelors,2,55,37,43,90,0.0,5,23,Urban,Software Engineer,84775,0 +32685,Female,50,Bachelors,15,56,90,72,96,6.0,6,65,Urban,Software Engineer,81901,1 +32686,Female,55,Masters,14,91,63,14,97,8.0,5,40,Semi-Urban,Data Analyst,98512,0 +32687,Male,47,Masters,19,84,20,79,21,1.0,3,98,Urban,Software Engineer,136087,1 +32688,Male,39,Bachelors,16,48,16,15,85,9.0,1,54,Urban,Software Engineer,109292,0 +32689,Male,48,Bachelors,7,81,65,57,82,0.0,5,35,Rural,HR Executive,87157,1 +32690,Female,25,Diploma,15,54,87,95,87,7.0,0,93,Rural,Manager,77259,1 +32691,Male,31,PhD,10,4,85,70,86,7.0,1,48,Semi-Urban,HR Executive,135117,0 +32692,Female,46,High School,9,64,99,85,75,3.0,1,88,Urban,Software Engineer,72231,1 +32693,Other,26,Diploma,12,46,66,19,88,4.0,6,82,Rural,HR Executive,124525,0 +32694,Female,53,Bachelors,5,81,49,57,55,9.0,3,32,Semi-Urban,Manager,142579,0 +32695,Female,38,Bachelors,19,56,33,76,66,6.0,0,54,Semi-Urban,Data Analyst,87565,0 +32696,Male,26,Bachelors,4,56,73,48,48,5.0,2,45,Semi-Urban,Software Engineer,140987,0 +32697,Male,50,Diploma,3,61,94,53,23,7.0,6,72,Urban,HR Executive,118301,1 +32698,Male,34,Bachelors,3,52,63,65,6,3.0,3,68,Urban,Manager,76280,1 +32699,Male,33,PhD,2,86,84,73,47,1.0,6,2,Semi-Urban,Manager,68013,1 +32700,Male,21,Bachelors,3,25,27,26,67,8.0,4,72,Urban,Data Analyst,48020,0 +32701,Female,41,Bachelors,6,87,27,44,62,5.0,2,95,Urban,ML Engineer,72433,1 +32702,Male,38,Diploma,11,43,39,39,3,6.0,6,33,Rural,ML Engineer,78987,0 +32703,Female,58,Diploma,3,67,40,16,32,0.0,4,39,Semi-Urban,HR Executive,85715,0 +32704,Male,59,High School,3,72,58,44,96,3.0,3,6,Urban,ML Engineer,52726,0 +32705,Male,36,Masters,15,65,89,64,66,0.0,7,83,Rural,Software Engineer,47389,1 +32706,Male,25,Bachelors,11,47,43,13,27,5.0,0,72,Urban,ML Engineer,47413,0 +32707,Other,36,Masters,17,73,5,9,79,6.0,2,85,Urban,Data Analyst,123135,0 +32708,Female,29,Masters,10,59,30,22,48,6.0,6,94,Urban,ML Engineer,89160,0 +32709,Male,39,Masters,7,7,61,64,92,7.0,7,10,Semi-Urban,Software Engineer,118637,0 +32710,Male,36,Diploma,3,52,35,30,75,8.0,6,82,Urban,Data Analyst,140288,0 +32711,Female,53,Bachelors,2,11,15,50,55,7.0,7,66,Rural,Software Engineer,38998,0 +32712,Male,48,Diploma,9,76,67,6,89,6.0,4,93,Urban,ML Engineer,43220,1 +32713,Male,26,Masters,10,16,21,91,79,4.0,0,3,Urban,Manager,33447,0 +32714,Male,49,High School,0,11,72,63,76,3.0,5,3,Urban,Software Engineer,48778,0 +32715,Male,39,PhD,5,45,20,11,16,7.0,4,83,Urban,Software Engineer,67180,0 +32716,Male,48,Diploma,7,71,8,97,26,0.0,1,98,Urban,HR Executive,46414,1 +32717,Male,24,Bachelors,13,27,23,1,39,3.0,7,35,Urban,Manager,146035,0 +32718,Female,22,Masters,1,78,35,45,18,7.0,5,39,Rural,HR Executive,49614,0 +32719,Male,46,Bachelors,2,69,51,84,85,1.0,7,96,Urban,Manager,55667,1 +32720,Female,34,Diploma,4,34,29,33,29,8.0,0,32,Semi-Urban,Software Engineer,116984,0 +32721,Male,34,Diploma,11,4,59,10,99,9.0,2,5,Urban,HR Executive,69954,0 +32722,Male,32,Bachelors,13,57,88,48,58,3.0,1,32,Rural,Manager,90318,0 +32723,Male,49,Bachelors,4,32,9,22,85,6.0,7,11,Semi-Urban,ML Engineer,96534,0 +32724,Female,46,Bachelors,2,90,32,71,92,7.0,4,9,Rural,ML Engineer,43717,0 +32725,Male,49,Masters,14,73,94,84,15,4.0,1,80,Semi-Urban,Data Analyst,134836,1 +32726,Male,52,Bachelors,7,82,47,38,91,0.0,0,51,Urban,Manager,122599,0 +32727,Male,56,PhD,1,38,66,36,56,0.0,4,96,Urban,Manager,114221,1 +32728,Female,46,High School,8,0,42,84,63,0.0,4,42,Semi-Urban,HR Executive,118891,0 +32729,Male,28,Diploma,8,2,9,88,79,9.0,4,32,Urban,Manager,67520,0 +32730,Male,34,High School,15,46,11,12,26,7.0,1,21,Rural,ML Engineer,140472,0 +32731,Male,33,Bachelors,12,82,60,57,98,9.0,0,5,Rural,Manager,144424,0 +32732,Female,52,PhD,8,53,25,12,90,2.0,5,54,Semi-Urban,Manager,125989,0 +32733,Male,56,Bachelors,2,27,67,71,50,1.0,2,49,Rural,Data Analyst,45958,0 +32734,Female,24,Masters,9,80,32,54,48,0.0,6,21,Semi-Urban,ML Engineer,90197,0 +32735,Female,58,Masters,2,24,45,69,18,3.0,3,98,Urban,ML Engineer,145481,0 +32736,Female,31,Masters,1,95,10,84,93,8.0,1,75,Rural,ML Engineer,25576,1 +32737,Male,32,Masters,6,95,1,28,32,3.0,0,99,Rural,HR Executive,37668,0 +32738,Male,21,Bachelors,17,12,84,7,33,7.0,6,1,Urban,ML Engineer,98561,0 +32739,Female,29,Masters,2,34,84,31,20,8.0,1,52,Urban,HR Executive,54989,0 +32740,Male,57,High School,9,1,77,68,56,3.0,3,50,Rural,Manager,100808,0 +32741,Male,46,Bachelors,9,47,98,90,8,0.0,4,67,Urban,Software Engineer,71496,1 +32742,Male,43,Masters,1,23,27,40,18,7.0,6,47,Urban,Manager,69172,0 +32743,Female,21,Diploma,15,22,10,94,21,8.0,5,2,Urban,Data Analyst,29529,0 +32744,Male,24,Bachelors,12,86,93,17,21,9.0,1,59,Semi-Urban,Software Engineer,112088,1 +32745,Male,34,Bachelors,3,36,62,68,77,9.0,6,37,Urban,Manager,103593,0 +32746,Female,31,Bachelors,17,59,25,58,46,0.0,4,34,Rural,Software Engineer,116413,0 +32747,Male,52,Diploma,0,61,15,82,11,2.0,3,91,Semi-Urban,HR Executive,97635,1 +32748,Female,59,Bachelors,1,25,29,48,84,4.0,1,13,Urban,HR Executive,45034,0 +32749,Male,41,PhD,9,44,46,41,26,6.0,4,25,Urban,Data Analyst,72561,0 +32750,Female,59,Bachelors,9,5,2,31,74,7.0,0,34,Urban,Manager,96531,0 +32751,Male,23,Masters,12,50,82,48,64,6.0,4,34,Rural,HR Executive,130809,0 +32752,Female,57,Bachelors,3,89,71,12,5,2.0,3,59,Urban,Data Analyst,27540,0 +32753,Female,51,Diploma,10,24,38,6,12,6.0,6,16,Rural,Manager,61450,0 +32754,Female,44,High School,7,9,78,85,91,3.0,6,79,Urban,HR Executive,128307,1 +32755,Female,37,Diploma,19,45,80,85,26,3.0,0,1,Urban,ML Engineer,36864,0 +32756,Male,53,Masters,14,66,17,70,37,4.0,1,84,Urban,Data Analyst,23202,1 +32757,Female,50,PhD,14,21,86,12,32,3.0,4,41,Semi-Urban,HR Executive,127521,0 +32758,Female,31,Bachelors,4,85,50,56,3,4.0,5,14,Rural,ML Engineer,75537,0 +32759,Female,22,Bachelors,19,5,69,6,36,7.0,5,78,Urban,ML Engineer,114106,0 +32760,Female,51,Masters,10,33,25,56,72,5.0,1,2,Urban,ML Engineer,31411,0 +32761,Male,24,Bachelors,0,48,20,92,74,0.0,7,3,Urban,ML Engineer,115047,0 +32762,Female,27,PhD,13,22,67,59,54,5.0,1,49,Rural,ML Engineer,119137,0 +32763,Male,31,Bachelors,12,82,29,3,86,9.0,2,71,Urban,HR Executive,26714,0 +32764,Female,47,Bachelors,7,87,27,58,60,4.0,3,43,Urban,ML Engineer,140444,0 +32765,Male,47,Diploma,14,92,9,32,4,6.0,1,12,Semi-Urban,ML Engineer,137731,0 +32766,Male,48,Diploma,14,20,76,93,24,4.0,5,22,Semi-Urban,Software Engineer,28546,0 +32767,Other,27,Bachelors,7,24,60,98,40,7.0,7,35,Urban,Software Engineer,122622,0 +32768,Female,21,Masters,5,69,65,67,22,6.0,7,69,Urban,ML Engineer,22920,1 +32769,Female,51,Bachelors,8,84,0,90,39,8.0,3,8,Urban,Manager,51561,0 +32770,Female,29,Masters,15,65,66,85,92,9.0,5,17,Urban,ML Engineer,116707,0 +32771,Female,40,Bachelors,19,80,12,22,64,3.0,4,27,Urban,Manager,57451,0 +32772,Female,58,Bachelors,14,41,36,20,6,3.0,4,83,Urban,Manager,131200,0 +32773,Male,35,Diploma,7,26,74,22,61,1.0,4,75,Urban,Software Engineer,33792,0 +32774,Female,23,High School,18,5,76,9,98,9.0,0,40,Semi-Urban,HR Executive,33714,0 +32775,Female,56,Bachelors,14,99,79,34,54,0.0,1,29,Semi-Urban,Data Analyst,28328,1 +32776,Female,36,High School,13,40,42,24,3,7.0,5,27,Semi-Urban,Data Analyst,51651,0 +32777,Female,22,High School,19,30,20,56,55,4.0,1,76,Urban,Data Analyst,142149,0 +32778,Male,34,Masters,3,31,21,81,43,5.0,4,33,Semi-Urban,ML Engineer,58044,0 +32779,Male,52,Masters,15,49,71,2,44,8.0,0,1,Urban,Data Analyst,121515,0 +32780,Other,54,PhD,17,15,97,88,77,2.0,0,58,Urban,Data Analyst,89843,1 +32781,Male,42,High School,16,62,91,18,54,4.0,3,27,Urban,HR Executive,105059,0 +32782,Female,34,Bachelors,8,57,86,14,96,6.0,2,17,Semi-Urban,ML Engineer,115097,0 +32783,Male,40,PhD,12,9,73,2,76,8.0,0,20,Urban,Software Engineer,52086,0 +32784,Female,38,High School,18,56,60,92,7,7.0,4,3,Rural,ML Engineer,45768,0 +32785,Female,45,Bachelors,6,53,7,59,42,8.0,5,3,Urban,Manager,133756,0 +32786,Female,54,Masters,15,14,67,21,1,5.0,4,28,Urban,Data Analyst,134266,0 +32787,Male,43,Diploma,0,15,9,11,53,9.0,6,62,Urban,HR Executive,77099,0 +32788,Male,26,Bachelors,7,15,78,36,61,2.0,6,92,Urban,HR Executive,129532,0 +32789,Female,36,Masters,4,5,42,71,14,8.0,2,81,Urban,ML Engineer,90231,0 +32790,Female,51,Diploma,13,31,32,62,48,9.0,7,27,Urban,ML Engineer,51455,0 +32791,Male,39,Bachelors,16,27,70,46,42,5.0,4,92,Urban,HR Executive,60421,1 +32792,Male,52,Bachelors,2,67,97,58,95,9.0,5,95,Urban,ML Engineer,46813,1 +32793,Male,57,Diploma,15,70,77,12,67,1.0,3,44,Urban,HR Executive,58677,0 +32794,Female,41,Diploma,7,95,76,82,97,9.0,6,37,Rural,Data Analyst,99316,1 +32795,Female,25,Masters,3,23,70,87,18,1.0,2,7,Urban,ML Engineer,26425,0 +32796,Other,49,Bachelors,13,40,85,12,43,6.0,6,55,Semi-Urban,Data Analyst,70968,0 +32797,Male,47,High School,17,3,89,29,38,4.0,6,1,Urban,Data Analyst,71187,0 +32798,Male,39,Diploma,7,41,95,8,26,6.0,6,31,Urban,Data Analyst,31532,0 +32799,Female,22,Diploma,2,96,0,32,7,9.0,5,0,Semi-Urban,Data Analyst,74960,0 +32800,Male,45,Bachelors,14,18,44,16,86,0.0,4,20,Urban,Manager,32136,0 +32801,Male,38,Masters,12,64,83,71,57,7.0,4,12,Rural,Data Analyst,87046,0 +32802,Male,23,High School,13,68,26,82,19,0.0,4,67,Urban,ML Engineer,33419,1 +32803,Male,50,Bachelors,8,77,89,86,98,0.0,5,65,Urban,ML Engineer,112886,1 +32804,Male,27,Diploma,14,12,42,75,37,7.0,3,30,Urban,Data Analyst,30592,0 +32805,Male,22,Diploma,15,96,19,82,87,8.0,0,41,Urban,Data Analyst,84883,1 +32806,Male,43,Masters,7,89,72,75,7,8.0,5,19,Urban,Software Engineer,145156,1 +32807,Male,53,Masters,19,19,91,94,63,1.0,4,82,Rural,Software Engineer,65243,1 +32808,Female,57,High School,1,54,43,72,10,8.0,4,18,Rural,Manager,106921,0 +32809,Male,54,Diploma,11,79,5,49,73,6.0,0,18,Urban,Manager,122754,0 +32810,Male,53,Diploma,0,97,95,57,22,3.0,3,51,Urban,Data Analyst,147304,1 +32811,Male,48,Bachelors,2,20,69,66,61,0.0,7,58,Rural,Software Engineer,119080,0 +32812,Male,34,Masters,19,83,8,88,39,2.0,6,61,Semi-Urban,Software Engineer,127136,1 +32813,Female,37,Diploma,12,20,16,65,43,1.0,7,67,Semi-Urban,HR Executive,41397,0 +32814,Female,31,Bachelors,8,17,72,58,35,5.0,7,66,Urban,Data Analyst,51808,0 +32815,Female,52,Masters,4,8,39,39,46,9.0,5,0,Urban,Software Engineer,95745,0 +32816,Male,59,Bachelors,5,54,8,97,20,7.0,1,34,Urban,Data Analyst,139136,0 +32817,Male,39,Bachelors,6,24,12,69,85,6.0,1,18,Urban,Software Engineer,132934,0 +32818,Male,23,Bachelors,2,97,90,33,65,7.0,1,44,Urban,Manager,146678,1 +32819,Other,38,PhD,13,33,99,35,6,1.0,2,38,Urban,ML Engineer,146406,0 +32820,Female,33,Diploma,8,99,56,13,75,0.0,1,95,Urban,HR Executive,24100,1 +32821,Male,25,Masters,11,66,54,56,27,6.0,6,52,Rural,ML Engineer,83415,0 +32822,Male,32,Masters,5,34,72,23,70,2.0,0,33,Semi-Urban,HR Executive,126221,0 +32823,Male,43,Masters,10,33,69,93,20,8.0,3,40,Urban,Data Analyst,25822,1 +32824,Male,39,Bachelors,15,94,92,95,55,4.0,4,30,Urban,HR Executive,141935,1 +32825,Female,38,Bachelors,5,65,83,8,26,6.0,4,70,Urban,Data Analyst,65874,0 +32826,Male,40,PhD,9,2,89,68,93,1.0,7,7,Urban,Software Engineer,56152,0 +32827,Female,34,Bachelors,16,84,63,48,7,1.0,5,55,Urban,Data Analyst,58479,1 +32828,Male,59,Masters,9,15,88,78,94,9.0,3,22,Urban,ML Engineer,94646,0 +32829,Male,50,Diploma,1,85,91,7,30,3.0,7,31,Rural,Data Analyst,52905,0 +32830,Male,43,Masters,11,35,77,75,71,6.0,4,46,Urban,Software Engineer,76806,0 +32831,Female,36,Masters,1,8,1,45,68,3.0,5,84,Urban,Software Engineer,35168,0 +32832,Male,21,Diploma,6,21,81,80,77,8.0,1,90,Urban,Manager,39598,1 +32833,Male,33,Diploma,6,33,61,34,47,3.0,6,83,Urban,HR Executive,98649,0 +32834,Female,51,Bachelors,18,29,27,51,81,3.0,7,95,Urban,Software Engineer,45546,0 +32835,Male,25,Masters,14,61,96,40,83,0.0,6,74,Rural,ML Engineer,98697,1 +32836,Male,31,High School,14,82,43,62,62,9.0,3,38,Urban,Software Engineer,22621,0 +32837,Male,35,Masters,7,30,74,56,3,0.0,6,96,Urban,Data Analyst,122561,1 +32838,Female,35,Bachelors,4,79,49,36,13,7.0,7,90,Semi-Urban,Manager,69424,1 +32839,Male,51,Bachelors,14,85,14,92,22,7.0,1,97,Urban,Manager,140610,1 +32840,Female,25,Bachelors,5,9,58,27,71,3.0,2,39,Urban,Data Analyst,114585,0 +32841,Male,27,Masters,18,81,83,26,82,1.0,1,9,Urban,HR Executive,105885,0 +32842,Male,41,High School,4,94,4,78,41,3.0,7,45,Urban,Manager,78641,0 +32843,Female,44,Bachelors,8,79,0,31,7,4.0,1,57,Semi-Urban,Data Analyst,136747,0 +32844,Female,21,PhD,10,48,3,64,12,9.0,6,93,Semi-Urban,Manager,97453,0 +32845,Female,49,Masters,15,81,88,16,48,7.0,0,15,Urban,Data Analyst,82453,0 +32846,Male,44,Bachelors,3,42,13,42,50,3.0,3,27,Rural,ML Engineer,61841,0 +32847,Male,25,Bachelors,7,92,93,47,83,2.0,3,76,Semi-Urban,Data Analyst,76200,1 +32848,Female,43,Masters,6,95,20,77,20,2.0,7,14,Semi-Urban,ML Engineer,20586,0 +32849,Male,42,Bachelors,5,88,53,13,40,1.0,5,17,Urban,ML Engineer,66640,0 +32850,Male,21,Bachelors,13,10,56,41,95,9.0,2,56,Urban,Manager,132098,0 +32851,Male,48,High School,9,96,88,18,98,9.0,4,60,Semi-Urban,Manager,132936,1 +32852,Male,58,Diploma,6,34,55,53,14,0.0,5,12,Rural,Software Engineer,121760,0 +32853,Male,26,Bachelors,18,87,84,29,22,1.0,0,51,Urban,ML Engineer,91257,1 +32854,Female,52,High School,17,63,83,43,8,5.0,6,98,Rural,Data Analyst,45533,1 +32855,Female,33,High School,0,76,49,57,58,1.0,5,12,Urban,HR Executive,121137,0 +32856,Female,21,Masters,12,97,31,50,12,3.0,0,2,Semi-Urban,Data Analyst,90920,0 +32857,Other,34,Diploma,18,36,72,54,84,2.0,1,54,Semi-Urban,ML Engineer,113099,0 +32858,Male,57,Bachelors,14,29,17,86,78,7.0,3,65,Urban,HR Executive,81232,0 +32859,Male,58,Bachelors,18,59,25,98,40,9.0,4,92,Semi-Urban,HR Executive,100332,1 +32860,Male,29,Bachelors,1,66,34,86,40,7.0,2,59,Urban,HR Executive,77113,1 +32861,Female,54,Bachelors,3,49,91,48,15,8.0,2,33,Rural,ML Engineer,136855,0 +32862,Male,40,Bachelors,2,32,90,61,62,8.0,4,18,Rural,ML Engineer,95440,0 +32863,Male,53,Diploma,2,85,32,51,88,6.0,2,83,Urban,HR Executive,29223,1 +32864,,41,Masters,0,34,74,46,68,4.0,0,86,Rural,HR Executive,105791,1 +32865,Male,46,Bachelors,15,79,78,34,67,0.0,6,14,Rural,Software Engineer,88185,0 +32866,Male,59,Masters,13,65,47,77,2,2.0,4,63,Urban,Software Engineer,63540,1 +32867,Male,29,Diploma,16,15,60,1,65,0.0,3,93,Urban,Data Analyst,81212,0 +32868,Female,26,Bachelors,5,45,80,92,16,7.0,7,30,Urban,HR Executive,28496,1 +32869,Male,49,Diploma,0,99,53,33,34,8.0,7,85,Urban,Manager,70104,1 +32870,Other,56,Diploma,19,27,96,62,61,9.0,1,86,Urban,HR Executive,111153,1 +32871,Male,59,High School,10,14,19,6,87,4.0,2,12,Urban,ML Engineer,108182,0 +32872,Female,39,Masters,8,2,72,38,42,6.0,2,64,Urban,HR Executive,60510,0 +32873,Male,48,Bachelors,13,52,15,39,95,0.0,7,3,Rural,Data Analyst,74160,0 +32874,Female,55,Diploma,1,90,78,14,8,4.0,6,18,Urban,Manager,111511,0 +32875,Male,59,Bachelors,0,85,51,93,37,2.0,3,71,Rural,Data Analyst,116981,1 +32876,Female,23,Masters,19,95,28,9,76,6.0,2,70,Urban,Data Analyst,111064,0 +32877,Female,57,High School,0,91,85,87,98,7.0,6,44,Semi-Urban,Data Analyst,89451,1 +32878,Male,34,Bachelors,4,92,36,80,59,6.0,7,39,Urban,Manager,53707,1 +32879,Male,35,Masters,0,54,25,41,40,8.0,3,91,Semi-Urban,Manager,124693,0 +32880,Male,47,Diploma,17,81,71,10,55,6.0,4,12,Rural,ML Engineer,107163,0 +32881,Male,50,Bachelors,3,97,51,0,30,4.0,5,15,Urban,Software Engineer,83997,0 +32882,Male,41,High School,18,29,51,76,26,0.0,3,46,Urban,Software Engineer,140797,0 +32883,Female,43,Masters,3,74,53,12,58,8.0,3,9,Urban,Data Analyst,48945,0 +32884,Male,29,Bachelors,12,99,18,92,8,7.0,7,51,Urban,Manager,58337,1 +32885,Female,27,Bachelors,3,74,97,43,9,9.0,4,70,Urban,HR Executive,55295,1 +32886,Female,54,Bachelors,17,17,66,74,93,3.0,7,80,Urban,ML Engineer,20311,0 +32887,Female,21,Diploma,12,98,48,67,20,1.0,0,31,Rural,HR Executive,105039,1 +32888,Male,44,PhD,16,80,58,5,18,0.0,7,28,Semi-Urban,Data Analyst,101154,0 +32889,Male,37,Masters,0,23,15,38,62,4.0,1,49,Semi-Urban,Software Engineer,32938,0 +32890,Male,21,Diploma,0,76,75,2,91,6.0,3,92,Urban,HR Executive,43987,1 +32891,Male,24,Bachelors,9,63,74,83,49,6.0,3,99,Urban,Data Analyst,126935,1 +32892,Male,50,Bachelors,17,5,72,64,65,5.0,6,41,Urban,ML Engineer,79632,0 +32893,Female,55,Bachelors,7,67,95,83,78,4.0,5,36,Rural,ML Engineer,90352,1 +32894,Female,54,High School,17,42,60,93,65,4.0,1,34,Urban,HR Executive,47099,0 +32895,Male,30,Masters,1,34,4,36,4,1.0,6,87,Rural,ML Engineer,98687,0 +32896,Male,55,Diploma,8,5,47,8,15,2.0,6,71,Urban,ML Engineer,93345,0 +32897,Male,42,Diploma,12,45,31,47,43,0.0,6,10,Urban,ML Engineer,82957,0 +32898,Other,39,Diploma,2,22,56,79,27,7.0,6,1,Urban,ML Engineer,69407,0 +32899,Other,51,Bachelors,10,73,11,4,77,6.0,0,34,Urban,ML Engineer,27920,0 +32900,Male,50,PhD,11,91,99,54,72,6.0,6,19,Urban,Software Engineer,83153,1 +32901,Male,22,Bachelors,8,6,10,90,68,3.0,7,21,Rural,Software Engineer,70346,0 +32902,Male,57,Bachelors,17,57,48,22,35,2.0,4,20,Rural,HR Executive,46067,0 +32903,Male,53,High School,7,20,63,14,60,2.0,4,14,Urban,Data Analyst,139738,0 +32904,Male,34,Bachelors,2,9,76,64,21,8.0,2,44,Rural,HR Executive,115276,0 +32905,Female,45,Masters,17,31,23,65,20,3.0,2,98,Urban,HR Executive,91245,0 +32906,Male,36,Masters,4,98,58,21,40,1.0,4,2,Semi-Urban,Data Analyst,52588,0 +32907,Female,46,Diploma,12,59,33,70,81,4.0,2,63,Urban,HR Executive,84208,0 +32908,Male,56,Bachelors,12,9,56,34,28,1.0,5,24,Semi-Urban,HR Executive,134899,0 +32909,Female,41,Bachelors,4,25,19,44,73,5.0,4,79,Semi-Urban,HR Executive,123050,0 +32910,Female,34,Masters,19,98,36,32,53,2.0,5,12,Urban,HR Executive,63812,0 +32911,Male,32,Diploma,9,38,94,76,25,7.0,3,50,Semi-Urban,Data Analyst,49196,1 +32912,Female,48,Diploma,7,34,67,42,93,6.0,1,12,Urban,ML Engineer,25083,0 +32913,Male,58,High School,0,24,86,51,73,3.0,1,57,Urban,Data Analyst,143827,0 +32914,Male,40,Masters,0,66,17,67,25,8.0,2,2,Semi-Urban,HR Executive,59967,0 +32915,Male,50,Masters,18,75,4,51,22,3.0,7,29,Semi-Urban,Software Engineer,80786,0 +32916,Male,50,PhD,7,14,20,24,16,4.0,0,75,Urban,Data Analyst,29420,0 +32917,Male,40,Diploma,6,48,68,97,68,7.0,4,66,Urban,Data Analyst,26627,1 +32918,Female,48,Diploma,6,28,0,72,86,1.0,1,94,Semi-Urban,Manager,141220,0 +32919,Male,28,Masters,2,72,14,37,9,6.0,6,45,Semi-Urban,Software Engineer,41975,0 +32920,Male,30,Masters,16,53,69,47,17,9.0,0,20,Urban,Data Analyst,145442,0 +32921,Female,46,Diploma,7,35,67,12,43,5.0,7,45,Urban,ML Engineer,107695,0 +32922,Female,24,Bachelors,5,61,1,6,3,6.0,4,11,Urban,Data Analyst,83256,0 +32923,Male,24,High School,1,57,13,41,20,9.0,6,76,Semi-Urban,Manager,91313,0 +32924,Male,53,High School,2,94,67,87,26,6.0,5,51,Urban,Data Analyst,95267,1 +32925,Male,42,Diploma,3,98,14,39,14,9.0,4,88,Urban,Data Analyst,98547,1 +32926,Male,44,Masters,1,93,98,10,92,7.0,0,14,Urban,Data Analyst,98285,0 +32927,Female,50,High School,1,54,56,34,11,6.0,3,82,Urban,Data Analyst,43997,0 +32928,Male,40,Bachelors,18,99,19,97,0,4.0,4,16,Urban,Manager,51049,0 +32929,Male,58,Bachelors,5,47,70,39,67,9.0,2,19,Semi-Urban,Data Analyst,33471,0 +32930,Other,22,High School,13,35,45,8,56,4.0,2,78,Urban,HR Executive,138567,0 +32931,Female,59,Bachelors,19,3,72,66,35,7.0,0,41,Semi-Urban,Manager,139767,0 +32932,Male,37,Masters,13,19,8,97,94,6.0,2,98,Urban,Software Engineer,122630,0 +32933,Female,56,Bachelors,7,82,11,39,35,6.0,5,31,Semi-Urban,HR Executive,63977,0 +32934,Female,58,Bachelors,5,31,55,84,95,5.0,7,42,Semi-Urban,Data Analyst,80248,0 +32935,Male,38,Diploma,18,28,87,55,51,1.0,7,75,Urban,ML Engineer,125223,1 +32936,Female,44,PhD,19,72,19,11,38,7.0,5,66,Urban,ML Engineer,55603,0 +32937,Male,24,Bachelors,12,25,24,21,87,7.0,7,35,Urban,Software Engineer,104256,0 +32938,Female,48,Diploma,17,79,92,16,50,6.0,3,18,Rural,Software Engineer,104721,0 +32939,Other,47,Masters,19,67,91,82,6,5.0,1,24,Urban,Software Engineer,66174,1 +32940,Male,34,Bachelors,5,19,52,36,5,7.0,7,28,Urban,Data Analyst,36414,0 +32941,Female,29,Bachelors,11,20,47,64,36,7.0,5,54,Semi-Urban,Data Analyst,50372,0 +32942,Female,24,High School,1,84,29,57,78,7.0,6,39,Urban,HR Executive,61397,0 +32943,Female,30,Masters,2,52,15,91,87,0.0,4,92,Urban,Data Analyst,139547,1 +32944,Female,35,Diploma,9,6,88,28,18,4.0,6,75,Urban,Manager,129105,0 +32945,Male,23,Masters,16,68,84,87,62,9.0,2,98,Urban,HR Executive,51277,1 +32946,Female,54,Bachelors,11,78,91,35,45,7.0,6,42,Semi-Urban,Software Engineer,147285,1 +32947,Female,27,Masters,4,31,26,48,5,1.0,2,19,Semi-Urban,HR Executive,49668,0 +32948,Female,56,Masters,2,88,43,60,88,3.0,1,63,Semi-Urban,Software Engineer,128663,1 +32949,Female,44,Bachelors,10,25,13,86,37,9.0,2,43,Urban,Manager,25208,0 +32950,Male,55,Bachelors,7,17,10,16,42,9.0,4,74,Urban,Manager,96822,0 +32951,Male,32,Diploma,6,79,3,28,3,5.0,3,71,Semi-Urban,Data Analyst,129555,0 +32952,Female,51,Bachelors,17,73,65,38,69,9.0,2,50,Semi-Urban,Software Engineer,47109,0 +32953,Female,54,Bachelors,19,93,22,6,92,2.0,2,48,Urban,Manager,35383,0 +32954,Male,49,Bachelors,13,5,49,68,5,7.0,6,40,Rural,Data Analyst,108208,0 +32955,Male,37,Bachelors,13,48,63,52,22,9.0,1,44,Urban,HR Executive,149717,0 +32956,Female,28,Bachelors,8,48,78,46,97,5.0,4,42,Urban,Manager,140900,0 +32957,Female,56,PhD,19,77,72,18,86,7.0,0,85,Urban,Data Analyst,125962,1 +32958,Female,31,High School,11,12,21,6,34,2.0,6,71,Semi-Urban,Software Engineer,138931,0 +32959,Male,58,Bachelors,8,22,12,74,73,5.0,1,55,Urban,ML Engineer,88796,0 +32960,Female,50,Bachelors,3,83,95,53,97,5.0,0,6,Urban,Manager,143933,0 +32961,Female,47,High School,5,56,85,12,75,4.0,5,68,Semi-Urban,Manager,101141,0 +32962,Female,26,PhD,8,96,43,36,67,1.0,5,43,Urban,ML Engineer,109949,0 +32963,Female,43,Masters,6,38,49,59,36,6.0,2,87,Semi-Urban,HR Executive,46110,0 +32964,Male,47,Masters,8,14,5,43,16,0.0,4,42,Rural,ML Engineer,92217,0 +32965,Other,45,Bachelors,6,37,99,55,32,6.0,5,37,Semi-Urban,Manager,109756,0 +32966,Female,37,Diploma,12,66,18,52,39,3.0,7,75,Urban,Software Engineer,127570,0 +32967,Male,42,Diploma,5,14,83,62,64,8.0,3,7,Urban,Manager,78434,0 +32968,Female,42,High School,14,98,52,56,87,5.0,0,20,Urban,Manager,131269,0 +32969,Female,45,Masters,18,67,77,20,10,1.0,7,99,Semi-Urban,Manager,134523,1 +32970,Female,47,Masters,15,44,70,11,66,9.0,1,16,Rural,HR Executive,102576,0 +32971,Male,32,Bachelors,10,29,94,49,1,1.0,3,96,Urban,ML Engineer,99707,1 +32972,Male,26,Bachelors,8,57,76,21,19,1.0,0,90,Semi-Urban,Software Engineer,51610,1 +32973,Male,36,Diploma,10,17,76,71,17,7.0,6,29,Rural,Software Engineer,121013,0 +32974,Male,41,Bachelors,14,86,75,80,42,2.0,5,65,Urban,ML Engineer,44713,1 +32975,Male,52,Bachelors,2,48,90,96,39,4.0,1,6,Semi-Urban,Data Analyst,138004,1 +32976,Male,46,Bachelors,14,99,36,69,59,6.0,1,7,Rural,HR Executive,80148,0 +32977,Male,41,Bachelors,9,5,89,70,53,4.0,0,55,Semi-Urban,Data Analyst,59263,0 +32978,Female,26,High School,1,49,37,41,78,2.0,7,70,Semi-Urban,Manager,77340,0 +32979,Male,58,Masters,15,50,59,46,2,9.0,3,69,Urban,Manager,99557,0 +32980,Male,54,Bachelors,3,14,73,2,26,1.0,3,15,Urban,HR Executive,35281,0 +32981,Male,37,Bachelors,9,15,63,1,84,3.0,1,81,Urban,ML Engineer,50260,0 +32982,Male,38,Bachelors,5,66,86,50,52,7.0,0,54,Semi-Urban,ML Engineer,51925,1 +32983,Female,37,Bachelors,15,40,40,21,55,3.0,3,59,Urban,HR Executive,135428,0 +32984,Male,31,Diploma,18,77,11,71,74,5.0,2,32,Urban,HR Executive,107782,0 +32985,Female,21,PhD,16,2,40,39,63,6.0,7,62,Urban,Software Engineer,61712,0 +32986,Female,45,Bachelors,9,20,76,64,83,3.0,6,90,Urban,Data Analyst,58579,1 +32987,Male,35,Bachelors,1,58,37,49,23,2.0,2,92,Semi-Urban,Manager,22582,1 +32988,Male,55,High School,0,74,34,83,19,4.0,6,34,Rural,Software Engineer,41003,0 +32989,Male,32,High School,13,7,16,21,97,8.0,6,34,Urban,Data Analyst,65544,0 +32990,Male,42,High School,12,83,82,99,18,0.0,1,32,Semi-Urban,ML Engineer,147562,1 +32991,Male,43,High School,1,98,62,3,32,5.0,2,98,Rural,Data Analyst,113390,1 +32992,Female,22,Diploma,9,62,70,15,95,5.0,4,43,Urban,HR Executive,82556,0 +32993,Male,25,Diploma,3,99,28,55,21,2.0,7,65,Rural,Data Analyst,145300,1 +32994,Male,55,PhD,7,80,61,81,36,7.0,5,46,Rural,HR Executive,72798,1 +32995,Male,48,High School,17,16,6,21,65,0.0,6,16,Rural,Software Engineer,76287,0 +32996,Female,21,Masters,17,57,15,70,70,1.0,5,16,Urban,HR Executive,98711,0 +32997,Male,37,Bachelors,6,6,90,25,6,2.0,4,98,Urban,HR Executive,121587,0 +32998,Male,42,Bachelors,19,51,10,83,67,9.0,0,65,Semi-Urban,Software Engineer,81509,0 +32999,Female,22,Bachelors,11,55,50,77,62,8.0,6,64,Urban,Data Analyst,52430,1 +33000,Male,21,High School,18,29,12,39,28,6.0,4,22,Urban,Software Engineer,56361,0 +33001,Male,57,Diploma,5,73,58,16,7,6.0,5,61,Urban,Manager,26023,0 +33002,Male,49,Bachelors,19,78,31,89,20,6.0,4,27,Urban,HR Executive,74541,0 +33003,Female,36,Diploma,15,49,65,16,90,0.0,7,22,Urban,Software Engineer,39188,0 +33004,Male,44,Masters,6,26,77,28,3,2.0,4,73,Urban,Manager,113964,0 +33005,Male,54,Diploma,1,86,32,46,76,1.0,2,26,Urban,ML Engineer,57590,0 +33006,Other,27,High School,5,6,44,64,18,7.0,1,35,Rural,HR Executive,37074,0 +33007,Male,38,Bachelors,8,49,61,73,22,8.0,6,4,Urban,Software Engineer,141675,0 +33008,Female,31,Masters,17,54,31,12,45,6.0,1,33,Urban,Software Engineer,25461,0 +33009,Male,43,Bachelors,5,37,76,71,8,8.0,3,21,Urban,Software Engineer,127545,0 +33010,Male,33,Bachelors,8,94,56,4,53,8.0,3,26,Urban,ML Engineer,129897,0 +33011,Female,34,Bachelors,7,5,20,33,37,3.0,3,69,Urban,Data Analyst,135341,0 +33012,Female,38,Bachelors,6,7,74,54,70,9.0,6,64,Urban,Manager,42730,0 +33013,Male,22,Bachelors,8,59,97,45,51,2.0,5,63,Rural,Manager,127166,1 +33014,Female,22,PhD,8,78,75,60,79,1.0,2,37,Semi-Urban,ML Engineer,62575,1 +33015,Female,24,Diploma,16,19,98,38,57,7.0,1,30,Semi-Urban,Data Analyst,132163,0 +33016,Male,37,Diploma,15,29,67,24,55,8.0,4,55,Urban,ML Engineer,67338,0 +33017,Female,34,High School,9,20,19,84,26,6.0,2,70,Urban,Data Analyst,84762,0 +33018,Male,42,Masters,14,26,47,93,78,4.0,4,62,Rural,Software Engineer,148560,0 +33019,Male,36,Masters,13,97,72,40,84,4.0,1,2,Semi-Urban,Data Analyst,22476,0 +33020,Male,29,Bachelors,18,9,95,79,53,1.0,5,93,Urban,HR Executive,144685,1 +33021,Female,35,High School,0,41,39,55,17,5.0,6,13,Urban,Software Engineer,25908,0 +33022,Male,53,Diploma,8,51,54,70,45,1.0,2,76,Rural,Data Analyst,144073,1 +33023,Female,23,Masters,16,2,69,79,66,8.0,5,54,Urban,Software Engineer,38487,0 +33024,Male,24,Bachelors,8,61,55,72,92,5.0,4,42,Urban,HR Executive,70071,0 +33025,Male,55,Masters,6,56,0,4,51,4.0,2,70,Urban,ML Engineer,60846,0 +33026,Female,53,Masters,5,74,21,49,66,1.0,3,71,Urban,Software Engineer,51039,0 +33027,Female,30,High School,5,74,77,28,52,9.0,5,45,Urban,Software Engineer,146853,0 +33028,Male,31,Bachelors,13,47,68,34,8,1.0,3,80,Urban,Software Engineer,82876,0 +33029,Male,35,High School,15,41,73,94,98,7.0,6,58,Semi-Urban,Software Engineer,48495,1 +33030,Female,56,High School,7,73,84,90,31,4.0,3,51,Urban,Data Analyst,114252,1 +33031,Male,38,Bachelors,10,65,4,12,59,4.0,6,88,Semi-Urban,Software Engineer,48715,0 +33032,Female,38,PhD,13,84,48,31,82,1.0,2,76,Urban,HR Executive,65568,0 +33033,Female,48,Bachelors,19,30,36,52,33,7.0,3,27,Urban,Data Analyst,111992,0 +33034,Female,29,Bachelors,8,17,49,13,84,8.0,1,29,Urban,Software Engineer,52527,0 +33035,Female,51,Diploma,0,28,34,97,13,7.0,7,94,Urban,ML Engineer,114978,1 +33036,Female,37,Diploma,17,11,27,55,54,1.0,5,10,Urban,Manager,105431,0 +33037,Male,41,Bachelors,2,5,21,30,79,5.0,5,45,Semi-Urban,Data Analyst,57207,0 +33038,Male,37,Bachelors,7,36,57,87,76,5.0,2,25,Rural,HR Executive,43344,0 +33039,Male,22,Diploma,3,81,13,90,67,9.0,3,97,Semi-Urban,Manager,92481,1 +33040,Male,31,Bachelors,16,50,61,35,84,3.0,2,99,Rural,Software Engineer,63939,1 +33041,Female,43,Diploma,6,58,47,70,0,7.0,4,2,Rural,ML Engineer,74636,0 +33042,Male,40,Bachelors,1,50,26,71,98,2.0,0,16,Urban,Software Engineer,130991,0 +33043,Female,56,Diploma,14,79,94,64,58,1.0,3,98,Semi-Urban,ML Engineer,114024,1 +33044,Female,39,High School,0,13,29,19,85,7.0,1,3,Urban,ML Engineer,44207,0 +33045,Female,32,Bachelors,13,44,31,51,84,5.0,2,56,Semi-Urban,Software Engineer,134078,0 +33046,Male,24,Diploma,14,76,75,82,49,3.0,3,80,Urban,ML Engineer,94355,1 +33047,Female,39,High School,1,91,1,68,86,5.0,2,85,Semi-Urban,Manager,21255,1 +33048,Male,42,Bachelors,17,77,52,26,86,0.0,2,39,Urban,Data Analyst,24587,0 +33049,Female,36,Diploma,17,80,16,15,60,8.0,1,75,Rural,Manager,55225,0 +33050,Male,32,Masters,4,89,96,41,48,8.0,7,57,Rural,Data Analyst,128760,1 +33051,Female,55,Bachelors,14,22,0,68,99,7.0,5,74,Urban,Data Analyst,43558,0 +33052,Male,39,Bachelors,12,84,23,19,99,7.0,5,37,Rural,ML Engineer,77872,0 +33053,Male,54,Bachelors,19,47,71,29,24,6.0,2,73,Semi-Urban,ML Engineer,92593,0 +33054,Male,53,Bachelors,3,52,15,34,91,2.0,6,90,Urban,HR Executive,144580,0 +33055,Female,27,Bachelors,3,56,65,23,39,3.0,1,16,Rural,HR Executive,75631,0 +33056,Female,52,Bachelors,17,55,98,59,31,0.0,7,6,Urban,ML Engineer,128061,0 +33057,Male,59,Bachelors,11,67,8,86,80,0.0,7,53,Semi-Urban,Software Engineer,49923,0 +33058,Male,22,Bachelors,16,19,11,5,3,5.0,1,2,Semi-Urban,Software Engineer,92927,0 +33059,Male,38,Bachelors,19,34,39,15,67,5.0,4,58,Urban,Software Engineer,119303,0 +33060,Male,34,Bachelors,5,87,19,24,26,6.0,2,13,Semi-Urban,Data Analyst,32343,0 +33061,Male,24,Diploma,19,62,3,21,1,6.0,5,82,Urban,ML Engineer,35847,0 +33062,Male,38,High School,0,33,70,15,62,3.0,4,92,Semi-Urban,ML Engineer,93634,0 +33063,Female,39,Bachelors,13,54,38,95,44,6.0,1,66,Semi-Urban,HR Executive,90801,1 +33064,Male,54,Diploma,11,98,33,37,48,8.0,2,59,Urban,Data Analyst,136162,0 +33065,Female,35,Bachelors,14,23,45,87,8,2.0,0,58,Urban,ML Engineer,34185,0 +33066,Male,32,Masters,8,29,64,16,23,7.0,0,21,Rural,HR Executive,82585,0 +33067,Female,40,PhD,4,71,8,62,77,1.0,2,24,Urban,HR Executive,140883,0 +33068,Female,47,High School,19,61,60,79,33,2.0,6,98,Semi-Urban,Manager,130280,1 +33069,Male,43,Bachelors,8,17,86,38,35,0.0,4,13,Urban,ML Engineer,127919,0 +33070,Male,49,Bachelors,1,86,72,42,11,4.0,1,28,Urban,HR Executive,85366,0 +33071,Male,46,Bachelors,8,65,57,92,38,7.0,2,35,Semi-Urban,Data Analyst,148143,1 +33072,Male,22,Bachelors,17,80,32,90,28,9.0,6,93,Rural,Data Analyst,38693,1 +33073,Male,23,High School,0,46,84,20,85,6.0,3,37,Semi-Urban,Software Engineer,115227,0 +33074,Male,41,PhD,0,26,54,63,74,6.0,7,20,Urban,Software Engineer,32593,0 +33075,Male,57,Bachelors,4,77,89,31,94,0.0,7,7,Urban,Manager,28513,0 +33076,Male,39,Bachelors,2,71,84,74,39,9.0,1,68,Urban,HR Executive,127143,1 +33077,Male,56,High School,4,72,72,34,3,0.0,0,68,Urban,ML Engineer,106040,1 +33078,Male,49,Bachelors,14,23,21,35,57,1.0,2,66,Semi-Urban,HR Executive,95061,0 +33079,Male,22,Masters,4,94,10,59,45,7.0,2,54,Semi-Urban,Data Analyst,34679,0 +33080,Female,34,Bachelors,6,23,84,8,72,7.0,5,24,Rural,ML Engineer,42036,0 +33081,Female,43,Masters,0,8,45,23,49,7.0,2,53,Urban,ML Engineer,119373,0 +33082,Female,21,Diploma,5,91,97,32,45,3.0,0,46,Urban,HR Executive,42191,1 +33083,Male,23,Bachelors,1,17,67,55,17,3.0,6,64,Semi-Urban,Software Engineer,83324,0 +33084,Male,36,Bachelors,15,65,64,96,37,7.0,1,62,Semi-Urban,Data Analyst,94037,1 +33085,Male,55,High School,8,53,36,37,85,2.0,3,70,Urban,Data Analyst,132830,0 +33086,Male,53,Bachelors,18,96,11,52,1,4.0,6,30,Urban,HR Executive,39048,0 +33087,Female,59,Diploma,3,79,42,80,70,4.0,3,53,Urban,ML Engineer,22466,1 +33088,Male,57,Masters,4,27,79,68,85,3.0,6,94,Urban,Software Engineer,91142,1 +33089,Female,38,Masters,5,0,79,33,85,5.0,3,74,Urban,Software Engineer,56617,0 +33090,Female,48,Masters,1,89,45,49,66,3.0,7,94,Semi-Urban,HR Executive,130923,1 +33091,Other,45,Bachelors,10,42,39,48,70,8.0,2,22,Urban,HR Executive,88773,0 +33092,Male,46,Diploma,6,36,14,71,71,7.0,3,11,Urban,Data Analyst,119377,0 +33093,Male,44,High School,12,26,72,9,97,7.0,3,52,Rural,ML Engineer,65102,0 +33094,Male,50,PhD,2,58,31,43,65,9.0,5,13,Urban,HR Executive,38658,0 +33095,Male,54,High School,16,95,69,46,30,7.0,0,6,Urban,ML Engineer,125514,0 +33096,Female,52,Diploma,5,62,94,89,60,7.0,7,33,Semi-Urban,Software Engineer,72957,1 +33097,Male,39,High School,10,17,76,4,29,2.0,2,11,Rural,Software Engineer,44375,0 +33098,Male,22,Bachelors,17,62,11,44,81,8.0,5,93,Urban,ML Engineer,70430,0 +33099,Male,57,Masters,5,81,95,48,72,8.0,2,65,Urban,Software Engineer,127373,1 +33100,Male,34,Bachelors,1,36,75,57,7,6.0,6,80,Urban,ML Engineer,26063,1 +33101,Male,29,Bachelors,19,62,95,69,28,8.0,0,46,Semi-Urban,Data Analyst,91882,1 +33102,Male,49,High School,10,21,18,30,36,3.0,2,67,Rural,ML Engineer,118093,0 +33103,Female,39,Bachelors,8,77,75,31,39,2.0,4,40,Urban,Data Analyst,84884,0 +33104,Other,38,Masters,19,17,20,33,36,0.0,4,49,Rural,HR Executive,92254,0 +33105,Male,59,Masters,2,36,16,27,16,0.0,6,72,Rural,Software Engineer,114595,0 +33106,Male,49,High School,1,73,4,72,13,9.0,4,23,Urban,Data Analyst,31721,0 +33107,Male,40,Masters,0,19,6,10,54,9.0,7,0,Urban,HR Executive,46509,0 +33108,Female,37,Masters,3,65,29,53,65,0.0,2,25,Urban,HR Executive,117789,0 +33109,Male,58,Masters,18,56,8,68,20,8.0,5,25,Urban,ML Engineer,39191,0 +33110,Female,45,Diploma,7,63,55,18,53,5.0,4,70,Rural,Manager,65673,0 +33111,Male,27,Masters,14,69,87,39,75,6.0,7,4,Urban,Software Engineer,104846,0 +33112,Male,52,Bachelors,7,92,39,94,23,9.0,4,53,Rural,HR Executive,136222,1 +33113,Male,34,High School,11,22,20,67,26,4.0,7,72,Urban,Data Analyst,90493,0 +33114,Other,56,Diploma,12,44,74,62,5,6.0,7,21,Urban,Data Analyst,34874,0 +33115,Male,31,Bachelors,15,16,70,3,6,5.0,1,60,Semi-Urban,ML Engineer,53040,0 +33116,Male,53,Masters,16,40,28,65,2,9.0,1,5,Rural,Software Engineer,117835,0 +33117,Male,36,Bachelors,5,66,44,35,15,4.0,3,14,Urban,Data Analyst,48080,0 +33118,Male,23,High School,11,88,53,57,58,2.0,6,71,Urban,HR Executive,32283,1 +33119,Male,47,High School,6,63,42,38,82,7.0,1,15,Urban,Manager,106417,0 +33120,Female,30,High School,7,51,61,54,46,4.0,2,28,Urban,HR Executive,47481,0 +33121,Female,27,Bachelors,7,82,32,0,7,0.0,3,93,Urban,Data Analyst,62837,0 +33122,Female,40,Bachelors,2,41,60,12,71,1.0,2,60,Urban,HR Executive,124962,0 +33123,Male,25,Bachelors,1,39,93,40,74,7.0,4,71,Semi-Urban,ML Engineer,103135,1 +33124,Male,40,Diploma,19,77,94,78,21,2.0,0,42,Urban,Manager,143466,1 +33125,Male,30,Masters,8,57,8,8,19,1.0,7,15,Semi-Urban,Data Analyst,81024,0 +33126,Male,25,Bachelors,15,22,46,89,39,7.0,0,40,Urban,Data Analyst,142007,0 +33127,Female,58,Bachelors,16,97,26,80,6,1.0,5,91,Rural,Manager,88731,1 +33128,Male,24,Bachelors,16,20,9,38,15,4.0,1,24,Rural,Manager,102438,0 +33129,Female,37,Diploma,7,25,59,28,73,5.0,3,29,Semi-Urban,ML Engineer,114502,0 +33130,Female,49,PhD,1,42,22,19,33,3.0,1,45,Urban,ML Engineer,57704,0 +33131,Male,53,Bachelors,6,26,68,55,98,3.0,7,21,Urban,HR Executive,138095,0 +33132,Female,46,PhD,3,50,3,78,0,7.0,6,45,Rural,Software Engineer,143177,0 +33133,Male,37,Masters,10,38,59,71,9,3.0,0,76,Urban,HR Executive,132385,1 +33134,Male,50,Diploma,12,66,86,24,56,0.0,3,9,Urban,Software Engineer,65698,0 +33135,Male,25,High School,7,17,3,97,6,5.0,0,58,Semi-Urban,Software Engineer,148916,0 +33136,Female,29,Bachelors,0,3,95,51,37,5.0,7,88,Urban,Data Analyst,112678,0 +33137,Male,36,High School,18,18,51,69,78,0.0,5,41,Urban,Manager,75570,0 +33138,Female,58,High School,4,88,97,5,86,6.0,4,18,Rural,Data Analyst,92896,0 +33139,Female,42,Bachelors,19,42,61,5,13,4.0,4,18,Semi-Urban,ML Engineer,82614,0 +33140,Female,33,Bachelors,16,95,17,31,89,0.0,3,90,Urban,ML Engineer,148261,0 +33141,Female,22,Bachelors,2,29,97,58,59,9.0,3,18,Urban,Manager,57897,0 +33142,Male,33,Diploma,11,72,45,65,47,3.0,2,25,Urban,Software Engineer,96697,0 +33143,Female,41,Bachelors,5,92,27,27,33,3.0,5,28,Rural,ML Engineer,31131,0 +33144,Male,59,High School,18,82,92,74,52,1.0,2,80,Urban,ML Engineer,106342,1 +33145,Male,42,Bachelors,4,1,55,7,15,0.0,2,11,Urban,ML Engineer,88226,0 +33146,Male,45,High School,15,75,83,79,32,5.0,5,18,Urban,HR Executive,110093,1 +33147,Male,23,Diploma,18,34,89,10,60,7.0,0,42,Urban,Software Engineer,30824,0 +33148,Female,44,Diploma,6,84,63,89,60,8.0,4,50,Urban,Data Analyst,78178,1 +33149,Male,38,Bachelors,12,36,30,57,19,9.0,0,73,Urban,HR Executive,109696,0 +33150,Male,47,Bachelors,7,73,12,86,43,9.0,7,32,Urban,Software Engineer,31044,0 +33151,Male,57,Bachelors,13,29,32,31,49,9.0,0,27,Semi-Urban,Data Analyst,59418,0 +33152,Male,59,High School,16,64,12,76,94,9.0,3,65,Urban,ML Engineer,106668,0 +33153,Male,56,Bachelors,6,24,95,11,38,6.0,1,71,Semi-Urban,Data Analyst,30490,0 +33154,Male,46,Bachelors,5,19,26,52,10,8.0,6,43,Urban,Software Engineer,93528,0 +33155,Female,51,Bachelors,8,63,47,5,52,9.0,6,12,Rural,Data Analyst,117749,0 +33156,Male,36,Bachelors,12,92,63,77,53,1.0,1,35,Urban,HR Executive,130665,1 +33157,Male,30,Bachelors,12,93,52,80,97,3.0,0,50,Urban,ML Engineer,122417,1 +33158,Male,21,High School,18,72,33,6,71,2.0,1,23,Urban,Data Analyst,21707,0 +33159,Male,29,High School,2,18,79,8,61,8.0,5,78,Urban,HR Executive,91153,0 +33160,Female,57,Masters,15,99,46,87,62,9.0,4,27,Urban,Data Analyst,21093,1 +33161,Male,34,Bachelors,8,15,51,63,0,8.0,3,18,Urban,ML Engineer,80863,0 +33162,Male,49,Masters,1,34,73,42,71,6.0,5,52,Rural,Data Analyst,20818,0 +33163,Male,22,Bachelors,5,0,48,53,86,6.0,4,59,Rural,HR Executive,45572,0 +33164,Female,23,Bachelors,6,29,44,27,37,1.0,6,81,Urban,HR Executive,61050,0 +33165,Male,47,Diploma,15,73,80,0,70,7.0,6,67,Rural,ML Engineer,36349,0 +33166,Male,26,Diploma,1,23,97,80,22,5.0,0,55,Urban,Software Engineer,149770,1 +33167,Male,57,Bachelors,6,46,86,40,32,1.0,0,62,Semi-Urban,Manager,40318,0 +33168,Female,49,Masters,5,70,23,0,17,0.0,3,68,Urban,Data Analyst,136367,0 +33169,Female,33,Diploma,6,62,1,1,96,3.0,0,47,Semi-Urban,HR Executive,79298,0 +33170,Male,36,Masters,12,55,83,59,58,1.0,4,45,Urban,ML Engineer,109693,1 +33171,Female,21,Bachelors,15,61,17,21,49,5.0,1,57,Rural,Manager,73350,0 +33172,Male,44,Diploma,8,95,4,71,82,4.0,7,55,Urban,ML Engineer,57982,0 +33173,Male,48,Bachelors,9,95,75,84,70,6.0,3,1,Urban,Data Analyst,83057,1 +33174,Male,31,Bachelors,19,19,55,37,97,6.0,4,53,Semi-Urban,Manager,97412,0 +33175,Female,43,Masters,8,76,77,36,49,2.0,6,11,Semi-Urban,Data Analyst,79878,0 +33176,Male,50,Bachelors,14,64,50,84,82,2.0,4,96,Rural,HR Executive,99808,1 +33177,Female,35,Bachelors,13,77,27,8,45,5.0,0,51,Urban,ML Engineer,100924,0 +33178,Male,43,High School,16,88,97,84,73,3.0,4,96,Urban,Manager,48651,1 +33179,Female,34,Bachelors,17,64,91,95,54,4.0,0,24,Urban,Manager,38625,1 +33180,Male,37,Diploma,12,57,28,88,90,5.0,6,25,Urban,Data Analyst,61047,0 +33181,Male,59,Masters,12,64,16,23,69,8.0,1,85,Urban,Manager,78781,0 +33182,Male,35,Masters,19,89,67,68,65,1.0,7,68,Semi-Urban,Software Engineer,60403,1 +33183,Male,30,Masters,18,16,40,40,3,2.0,5,14,Semi-Urban,HR Executive,42779,0 +33184,Male,52,Bachelors,17,22,1,31,55,0.0,7,70,Urban,ML Engineer,34007,0 +33185,Male,43,Diploma,10,15,19,92,18,6.0,6,93,Urban,Software Engineer,29879,0 +33186,Other,58,Masters,8,55,37,74,11,3.0,4,6,Rural,Software Engineer,99685,0 +33187,Male,32,Masters,14,29,98,76,40,1.0,4,4,Urban,Software Engineer,140992,0 +33188,Male,29,High School,5,76,81,64,22,4.0,4,17,Urban,Manager,146798,1 +33189,Male,47,High School,6,99,33,93,43,3.0,4,69,Semi-Urban,Manager,40029,1 +33190,Male,41,Masters,4,58,5,80,33,4.0,4,69,Urban,ML Engineer,148897,0 +33191,Male,45,PhD,15,81,12,8,71,4.0,3,69,Urban,Manager,73427,0 +33192,Female,30,Diploma,0,76,59,97,82,0.0,7,50,Semi-Urban,Manager,41349,1 +33193,Male,34,High School,12,17,2,1,17,7.0,3,0,Urban,Data Analyst,21183,0 +33194,Female,33,High School,13,7,42,92,54,5.0,7,34,Urban,Manager,74293,0 +33195,Male,41,Bachelors,7,12,74,20,36,4.0,2,94,Semi-Urban,Manager,147973,0 +33196,Other,23,High School,19,65,11,54,64,4.0,5,82,Rural,Data Analyst,85324,0 +33197,Male,35,Bachelors,10,63,74,88,57,4.0,5,3,Urban,ML Engineer,49714,0 +33198,Male,26,Masters,6,68,10,13,66,8.0,4,19,Rural,HR Executive,132144,0 +33199,Male,24,Masters,10,28,85,69,65,5.0,7,14,Semi-Urban,Software Engineer,38685,0 +33200,Other,35,PhD,5,88,64,75,58,2.0,0,37,Urban,HR Executive,93844,1 +33201,Female,28,Diploma,19,36,91,4,91,2.0,7,14,Semi-Urban,ML Engineer,98084,0 +33202,Male,36,Bachelors,19,99,82,19,24,2.0,3,1,Urban,Data Analyst,46211,0 +33203,Male,53,Bachelors,9,80,77,2,26,4.0,6,1,Urban,ML Engineer,77256,0 +33204,Female,31,Bachelors,18,42,15,4,85,9.0,2,99,Rural,ML Engineer,50356,0 +33205,Male,36,Bachelors,18,76,79,83,56,4.0,2,67,Semi-Urban,ML Engineer,129435,1 +33206,Male,39,Bachelors,14,84,17,32,92,4.0,4,1,Semi-Urban,Data Analyst,33550,0 +33207,Female,39,Bachelors,5,52,50,95,0,3.0,4,5,Rural,Data Analyst,81762,0 +33208,Female,23,Diploma,14,32,32,15,38,0.0,1,76,Urban,Manager,34970,0 +33209,Female,33,High School,8,24,1,12,1,0.0,5,5,Urban,Manager,23611,0 +33210,Other,27,Diploma,9,39,98,88,75,9.0,1,65,Urban,ML Engineer,72953,1 +33211,Male,25,Diploma,14,22,71,80,84,8.0,3,39,Urban,ML Engineer,43158,0 +33212,Male,27,PhD,16,62,52,52,47,7.0,1,44,Urban,Manager,146850,0 +33213,Female,35,Diploma,7,17,86,57,2,9.0,4,65,Urban,HR Executive,118329,0 +33214,Female,48,Diploma,13,33,8,4,6,0.0,6,93,Semi-Urban,Manager,58374,0 +33215,Female,35,Bachelors,13,58,94,32,66,7.0,2,73,Urban,Manager,138707,1 +33216,Female,21,Masters,14,46,80,22,54,0.0,0,56,Urban,Data Analyst,22656,0 +33217,Male,39,Masters,8,20,43,39,59,9.0,7,83,Semi-Urban,Software Engineer,28103,0 +33218,Male,51,Diploma,19,69,9,28,20,0.0,2,93,Rural,Data Analyst,95162,0 +33219,Male,56,Bachelors,15,78,93,32,82,6.0,1,57,Urban,HR Executive,99141,1 +33220,Female,53,PhD,17,48,56,99,72,6.0,3,46,Urban,Manager,98643,1 +33221,Male,33,Diploma,16,19,9,71,57,6.0,7,84,Urban,Software Engineer,52260,0 +33222,Female,33,Masters,13,86,36,29,69,9.0,6,93,Urban,Data Analyst,64001,1 +33223,Male,29,PhD,12,60,30,87,34,2.0,7,29,Urban,HR Executive,67653,0 +33224,Male,58,High School,9,91,44,76,42,0.0,0,79,Urban,Manager,52598,1 +33225,Male,28,Diploma,9,16,76,4,77,2.0,5,58,Urban,Software Engineer,71312,0 +33226,Female,49,Masters,15,51,91,71,49,9.0,4,36,Urban,HR Executive,110165,1 +33227,Male,26,Diploma,13,0,0,57,21,0.0,4,16,Semi-Urban,Software Engineer,66735,0 +33228,Female,41,Diploma,17,5,73,84,81,6.0,6,92,Urban,HR Executive,137935,1 +33229,Male,30,Masters,4,7,82,25,31,9.0,5,78,Rural,Software Engineer,70993,0 +33230,Male,42,Bachelors,13,21,52,14,43,0.0,2,65,Rural,ML Engineer,82845,0 +33231,Male,57,Diploma,6,4,70,30,65,6.0,1,42,Rural,Software Engineer,32348,0 +33232,Female,28,Bachelors,15,92,60,54,67,4.0,7,64,Urban,Data Analyst,64504,1 +33233,Male,26,Masters,9,22,30,65,25,8.0,1,78,Urban,HR Executive,128595,0 +33234,Female,48,Masters,10,24,81,57,50,5.0,1,70,Urban,Data Analyst,59832,0 +33235,Male,41,PhD,4,13,28,60,83,8.0,5,92,Rural,Data Analyst,31824,0 +33236,Male,46,Diploma,9,98,50,36,57,4.0,2,61,Rural,ML Engineer,32723,1 +33237,Male,40,Masters,18,42,90,98,66,9.0,3,53,Urban,Software Engineer,85347,1 +33238,Male,52,Bachelors,13,80,45,27,61,5.0,0,15,Urban,Manager,56067,0 +33239,Male,52,PhD,16,94,66,24,80,3.0,2,79,Urban,ML Engineer,58524,1 +33240,Male,23,Bachelors,13,69,9,67,14,9.0,1,61,Rural,Software Engineer,71037,0 +33241,Female,53,Masters,9,75,52,77,98,9.0,5,65,Rural,HR Executive,40777,1 +33242,Male,57,Bachelors,10,10,32,56,79,7.0,6,12,Urban,Data Analyst,96533,0 +33243,Male,37,Bachelors,2,98,5,75,63,5.0,1,25,Semi-Urban,Software Engineer,73112,0 +33244,Male,32,Masters,3,66,26,4,48,6.0,2,30,Urban,HR Executive,116754,0 +33245,Male,36,Bachelors,10,20,5,14,99,6.0,0,56,Urban,Software Engineer,109330,0 +33246,Male,36,Masters,8,25,77,51,33,3.0,4,30,Urban,Software Engineer,92559,0 +33247,Other,31,PhD,3,66,80,30,35,9.0,4,79,Urban,Manager,145309,1 +33248,Female,28,Bachelors,0,38,33,1,7,1.0,6,95,Rural,Software Engineer,131339,0 +33249,Female,38,Bachelors,15,73,6,16,23,2.0,0,22,Urban,HR Executive,64258,0 +33250,Male,31,Masters,16,1,25,98,41,1.0,0,37,Urban,Software Engineer,122406,0 +33251,Male,44,Masters,13,17,93,35,37,6.0,0,77,Urban,ML Engineer,127004,0 +33252,Male,48,High School,3,8,93,18,71,7.0,5,21,Urban,HR Executive,113519,0 +33253,Male,51,Bachelors,12,10,92,37,97,8.0,6,29,Urban,Data Analyst,61608,0 +33254,Male,53,Bachelors,10,50,8,33,21,9.0,2,17,Semi-Urban,Manager,118662,0 +33255,Male,54,Masters,15,10,29,94,48,5.0,4,45,Urban,HR Executive,94988,0 +33256,Female,52,Bachelors,16,72,59,87,99,0.0,1,33,Urban,HR Executive,99703,1 +33257,Other,58,Masters,17,17,9,90,89,2.0,4,27,Urban,Data Analyst,103027,0 +33258,Male,40,Bachelors,7,33,15,49,71,7.0,5,61,Semi-Urban,Software Engineer,44221,0 +33259,Female,59,Diploma,12,82,11,57,35,8.0,3,86,Urban,Software Engineer,129547,0 +33260,Female,48,Diploma,18,8,85,9,1,3.0,1,8,Urban,HR Executive,60112,0 +33261,Male,52,Diploma,16,99,76,72,38,3.0,6,33,Semi-Urban,Software Engineer,141026,1 +33262,Female,57,High School,6,62,24,60,12,2.0,7,70,Semi-Urban,Manager,24639,0 +33263,Male,41,High School,14,39,44,88,5,7.0,6,94,Semi-Urban,ML Engineer,103094,1 +33264,Female,59,Diploma,1,37,55,52,87,8.0,2,89,Rural,HR Executive,107588,0 +33265,Male,52,Bachelors,13,28,48,8,70,7.0,5,33,Rural,HR Executive,79799,0 +33266,Male,35,High School,6,5,42,50,65,8.0,3,13,Urban,ML Engineer,112228,0 +33267,Male,46,Bachelors,11,42,25,18,94,4.0,5,99,Semi-Urban,Software Engineer,49923,0 +33268,Female,27,Bachelors,5,76,5,43,61,8.0,6,49,Semi-Urban,Manager,29305,0 +33269,Male,44,Masters,11,2,56,49,95,8.0,3,84,Semi-Urban,HR Executive,51375,0 +33270,Male,55,Bachelors,0,31,55,80,11,6.0,4,15,Semi-Urban,Software Engineer,42607,0 +33271,Male,48,PhD,0,34,91,79,69,2.0,3,10,Urban,Data Analyst,81536,0 +33272,Male,54,Bachelors,5,43,18,50,48,9.0,3,36,Rural,Software Engineer,39597,0 +33273,Female,51,Masters,1,89,67,76,72,8.0,5,80,Semi-Urban,Manager,39817,1 +33274,Female,52,Bachelors,0,51,80,28,35,5.0,7,8,Urban,ML Engineer,115623,0 +33275,Female,50,Masters,8,26,53,1,77,8.0,3,96,Urban,Software Engineer,83643,0 +33276,Female,40,Bachelors,3,17,68,23,7,8.0,0,50,Urban,HR Executive,34937,0 +33277,Female,38,Diploma,15,95,84,24,10,6.0,2,0,Urban,Manager,69126,0 +33278,Female,38,Masters,18,86,36,21,80,5.0,3,54,Urban,Data Analyst,85436,0 +33279,Female,43,Masters,18,92,6,28,86,9.0,7,45,Semi-Urban,HR Executive,92140,0 +33280,Male,45,Bachelors,15,18,54,2,42,8.0,3,71,Rural,ML Engineer,133238,0 +33281,Male,39,Bachelors,5,89,30,41,18,1.0,5,46,Rural,Data Analyst,107508,0 +33282,Other,47,Bachelors,2,13,88,82,7,6.0,6,31,Semi-Urban,ML Engineer,57411,0 +33283,Female,33,Diploma,19,1,2,96,64,4.0,4,27,Rural,ML Engineer,149073,0 +33284,Female,47,Bachelors,13,19,8,52,1,4.0,7,0,Urban,HR Executive,36596,0 +33285,Male,41,PhD,19,38,65,95,9,8.0,0,9,Urban,Manager,128835,0 +33286,Female,45,High School,13,45,59,60,64,3.0,3,61,Urban,Manager,59030,0 +33287,Female,43,PhD,1,18,89,21,45,0.0,1,17,Semi-Urban,Software Engineer,78096,0 +33288,Male,42,High School,9,11,92,38,72,5.0,7,24,Urban,Software Engineer,99342,0 +33289,Male,42,Diploma,13,61,73,21,79,3.0,5,80,Urban,Software Engineer,68966,1 +33290,Male,27,Diploma,7,22,35,51,69,4.0,0,98,Semi-Urban,Software Engineer,79393,0 +33291,Female,36,Masters,10,47,14,80,83,2.0,3,76,Semi-Urban,Data Analyst,113458,0 +33292,Female,28,High School,0,26,23,96,2,0.0,2,32,Semi-Urban,Manager,29814,0 +33293,Female,35,Bachelors,18,84,84,17,73,2.0,0,62,Urban,Software Engineer,82528,1 +33294,Male,42,High School,16,65,12,72,70,7.0,4,56,Urban,Data Analyst,98394,0 +33295,Female,41,Diploma,18,79,64,44,25,8.0,1,99,Urban,Data Analyst,71464,1 +33296,Male,51,Masters,14,71,67,44,35,1.0,5,18,Rural,Software Engineer,26977,0 +33297,Male,55,Bachelors,4,24,35,57,53,1.0,1,19,Semi-Urban,HR Executive,110199,0 +33298,Male,45,High School,13,0,71,67,79,7.0,5,91,Semi-Urban,Data Analyst,103858,0 +33299,Other,47,Bachelors,15,18,59,65,60,4.0,6,11,Semi-Urban,HR Executive,45122,0 +33300,Male,30,Bachelors,14,27,92,64,76,8.0,1,55,Semi-Urban,Software Engineer,136837,1 +33301,Male,50,Bachelors,12,43,25,83,7,0.0,3,50,Semi-Urban,HR Executive,34143,0 +33302,Male,42,High School,14,78,4,26,0,8.0,1,64,Rural,Software Engineer,98910,0 +33303,Male,48,Bachelors,12,23,53,79,90,8.0,6,87,Urban,Manager,96787,1 +33304,Female,56,Bachelors,7,86,88,34,25,0.0,7,83,Urban,ML Engineer,91783,1 +33305,Male,45,Bachelors,19,29,59,48,75,3.0,0,7,Urban,Software Engineer,80820,0 +33306,Female,57,Bachelors,7,0,12,31,83,1.0,5,56,Urban,Data Analyst,105955,0 +33307,Female,52,Bachelors,12,51,23,30,19,2.0,1,10,Semi-Urban,ML Engineer,103781,0 +33308,Male,50,Bachelors,4,17,43,74,52,1.0,2,72,Urban,HR Executive,85107,0 +33309,Female,50,Bachelors,13,86,13,45,14,0.0,1,61,Urban,Software Engineer,42989,0 +33310,Male,54,Diploma,2,53,74,59,21,9.0,7,95,Semi-Urban,HR Executive,140389,1 +33311,Other,29,Bachelors,1,21,72,94,82,8.0,2,33,Semi-Urban,ML Engineer,33006,0 +33312,Male,22,High School,3,99,9,89,94,8.0,5,94,Urban,Manager,144932,1 +33313,Female,37,Diploma,0,92,84,34,96,2.0,4,50,Urban,Data Analyst,111209,1 +33314,Female,38,Diploma,2,84,23,63,81,2.0,3,98,Semi-Urban,ML Engineer,96806,1 +33315,Male,26,Bachelors,1,33,80,0,46,1.0,2,50,Urban,ML Engineer,147052,0 +33316,Male,31,Diploma,8,16,85,51,38,2.0,3,46,Urban,HR Executive,83651,0 +33317,Male,36,Masters,8,58,90,63,80,2.0,7,93,Urban,Manager,62168,1 +33318,Male,40,High School,9,69,33,91,96,9.0,6,50,Urban,Software Engineer,30118,1 +33319,Male,41,Bachelors,4,21,46,82,72,1.0,1,69,Rural,Manager,106463,0 +33320,Other,46,Bachelors,2,92,57,85,44,6.0,6,1,Urban,Software Engineer,50323,0 +33321,Male,28,High School,1,11,83,7,7,3.0,2,32,Semi-Urban,ML Engineer,20675,0 +33322,Male,59,Bachelors,3,26,41,4,69,7.0,6,22,Urban,Manager,77794,0 +33323,Male,56,Diploma,19,84,78,90,75,5.0,0,43,Urban,Software Engineer,112884,1 +33324,Male,29,Masters,9,79,51,92,29,8.0,7,22,Semi-Urban,ML Engineer,149460,1 +33325,Male,32,Bachelors,13,26,26,91,93,8.0,7,68,Urban,HR Executive,33296,0 +33326,Other,25,Bachelors,12,96,2,46,80,5.0,2,30,Urban,Manager,53438,0 +33327,Female,49,Bachelors,16,7,84,5,1,8.0,5,36,Semi-Urban,HR Executive,55984,0 +33328,Male,24,High School,1,79,81,33,26,7.0,7,0,Urban,HR Executive,90898,0 +33329,Male,32,Bachelors,7,20,98,38,72,0.0,2,1,Urban,Data Analyst,64080,0 +33330,Male,59,Diploma,1,94,36,9,32,9.0,0,19,Semi-Urban,Software Engineer,142802,0 +33331,Female,39,Diploma,9,46,36,82,39,5.0,5,0,Urban,HR Executive,35326,0 +33332,Female,38,Bachelors,15,72,32,98,96,9.0,6,81,Urban,Data Analyst,96378,1 +33333,Female,55,High School,3,85,19,99,26,3.0,3,62,Semi-Urban,Manager,78725,1 +33334,Male,34,Masters,18,27,14,2,14,4.0,6,44,Urban,Data Analyst,118220,0 +33335,Female,57,Bachelors,3,75,6,90,71,8.0,2,25,Urban,HR Executive,90610,0 +33336,Male,54,Diploma,0,94,50,68,86,5.0,1,19,Urban,Data Analyst,26428,0 +33337,Male,23,Bachelors,5,48,92,60,97,2.0,2,95,Urban,ML Engineer,85878,1 +33338,Female,43,Bachelors,15,43,99,91,21,3.0,2,31,Urban,HR Executive,120366,1 +33339,Male,33,Bachelors,16,41,52,12,10,9.0,7,89,Semi-Urban,HR Executive,64078,0 +33340,Male,53,Bachelors,14,94,4,5,41,4.0,2,17,Rural,Software Engineer,145985,0 +33341,Male,29,PhD,16,28,60,26,33,5.0,7,72,Semi-Urban,Manager,78825,0 +33342,Male,59,Bachelors,5,93,54,80,53,0.0,1,39,Rural,Manager,132878,1 +33343,Male,39,Masters,13,20,92,48,27,5.0,1,49,Urban,Manager,144816,0 +33344,Male,39,Bachelors,11,48,8,52,35,0.0,7,44,Urban,Manager,117530,0 +33345,Male,39,Bachelors,4,37,51,48,58,6.0,7,33,Urban,Software Engineer,46658,0 +33346,Female,30,Bachelors,13,26,54,66,61,5.0,7,7,Urban,Data Analyst,108337,0 +33347,Male,29,Diploma,5,87,60,36,60,7.0,1,56,Semi-Urban,Software Engineer,46896,1 +33348,Female,46,High School,12,23,98,71,86,6.0,6,99,Urban,Manager,26029,1 +33349,Male,46,Diploma,10,2,72,31,49,9.0,1,67,Rural,Software Engineer,56414,0 +33350,Male,58,Masters,3,90,66,12,84,4.0,4,34,Urban,ML Engineer,57100,0 +33351,Male,22,Diploma,6,78,45,58,88,8.0,7,61,Semi-Urban,ML Engineer,88483,1 +33352,Female,24,Bachelors,7,73,77,28,61,3.0,0,64,Semi-Urban,HR Executive,144345,1 +33353,Female,52,Bachelors,12,25,80,70,61,4.0,0,79,Urban,Data Analyst,57713,1 +33354,Male,26,Bachelors,4,34,96,94,9,2.0,6,10,Semi-Urban,ML Engineer,143949,0 +33355,Female,30,Diploma,9,49,70,15,6,3.0,1,75,Urban,HR Executive,77619,0 +33356,Female,42,Masters,9,89,46,27,16,6.0,1,25,Urban,Software Engineer,139587,0 +33357,Male,43,Bachelors,5,54,73,0,77,3.0,1,27,Semi-Urban,ML Engineer,109336,0 +33358,Female,43,Bachelors,17,93,14,20,45,5.0,3,51,Semi-Urban,Manager,30761,0 +33359,Male,27,Masters,15,33,58,98,65,4.0,5,55,Semi-Urban,Manager,73520,1 +33360,Male,37,Bachelors,0,85,51,28,94,4.0,1,94,Semi-Urban,HR Executive,68033,1 +33361,Male,36,Masters,16,81,70,69,20,8.0,7,48,Urban,Software Engineer,113734,1 +33362,Other,52,Bachelors,3,27,10,94,79,2.0,0,66,Urban,Manager,42316,0 +33363,Male,59,Diploma,0,45,5,17,23,8.0,5,80,Semi-Urban,Manager,87934,0 +33364,Female,50,High School,14,7,69,88,84,4.0,0,26,Semi-Urban,HR Executive,148090,0 +33365,Female,48,Bachelors,13,60,4,9,89,1.0,0,63,Rural,HR Executive,113236,0 +33366,Male,50,Bachelors,18,70,9,79,99,8.0,7,41,Semi-Urban,Data Analyst,104950,0 +33367,Male,25,Bachelors,18,4,15,69,62,1.0,7,73,Semi-Urban,HR Executive,139496,0 +33368,Female,48,Bachelors,12,3,17,30,16,5.0,1,63,Rural,HR Executive,136710,0 +33369,Male,54,Bachelors,2,21,94,71,96,6.0,2,69,Urban,Data Analyst,83115,1 +33370,Male,53,Bachelors,8,71,27,98,10,1.0,2,93,Semi-Urban,Software Engineer,23277,1 +33371,Female,55,High School,3,3,80,22,95,1.0,3,8,Semi-Urban,ML Engineer,36259,0 +33372,Female,39,High School,4,88,30,23,60,2.0,3,29,Rural,Software Engineer,66325,0 +33373,Female,52,Bachelors,19,8,47,71,50,9.0,1,5,Urban,Data Analyst,87652,0 +33374,Male,44,Bachelors,3,41,10,53,15,4.0,5,34,Urban,Manager,53324,0 +33375,Male,51,Masters,13,17,39,29,26,2.0,6,21,Urban,ML Engineer,107791,0 +33376,Other,33,Diploma,5,79,81,73,97,9.0,3,55,Urban,HR Executive,43416,1 +33377,Female,39,High School,2,12,75,12,92,5.0,0,29,Urban,Manager,100575,0 +33378,Male,53,Masters,0,47,70,62,47,0.0,0,90,Semi-Urban,Software Engineer,29119,1 +33379,Female,45,Bachelors,1,34,88,54,15,6.0,3,62,Urban,Data Analyst,42859,0 +33380,Male,22,Diploma,4,48,54,24,80,7.0,5,33,Semi-Urban,Data Analyst,57291,0 +33381,Male,37,High School,6,71,79,59,84,1.0,0,34,Urban,Manager,71119,1 +33382,Male,52,Bachelors,14,48,9,45,96,3.0,3,46,Urban,Data Analyst,76141,0 +33383,Male,42,Bachelors,16,59,33,13,50,7.0,0,58,Rural,ML Engineer,135211,0 +33384,Female,58,Bachelors,8,71,72,91,72,7.0,7,56,Urban,ML Engineer,22349,1 +33385,Male,50,Bachelors,10,85,51,23,64,6.0,2,35,Urban,HR Executive,129604,0 +33386,Male,29,High School,0,60,37,28,93,3.0,3,69,Urban,HR Executive,129594,0 +33387,Female,55,Masters,11,93,90,35,61,2.0,2,7,Semi-Urban,ML Engineer,66049,0 +33388,Female,46,Bachelors,17,34,7,98,25,4.0,5,56,Urban,ML Engineer,45756,0 +33389,Male,43,Masters,0,7,12,13,19,2.0,6,51,Semi-Urban,ML Engineer,145891,0 +33390,Female,58,Masters,5,88,60,7,29,1.0,6,77,Rural,HR Executive,142987,0 +33391,Female,33,High School,0,80,24,57,95,3.0,4,52,Rural,ML Engineer,69840,0 +33392,Female,59,Diploma,1,89,35,64,14,2.0,7,6,Semi-Urban,Software Engineer,43796,0 +33393,Female,37,Bachelors,2,5,3,97,31,3.0,6,24,Urban,Manager,73528,0 +33394,Male,29,Bachelors,10,84,25,95,8,7.0,3,46,Urban,Data Analyst,32317,1 +33395,Male,30,Diploma,1,82,38,33,38,8.0,4,29,Semi-Urban,ML Engineer,94677,0 +33396,Female,42,Bachelors,18,84,98,84,35,5.0,2,55,Urban,ML Engineer,149594,1 +33397,Female,51,PhD,6,44,99,59,82,2.0,3,55,Semi-Urban,Software Engineer,105474,1 +33398,Male,32,Diploma,13,62,31,51,52,2.0,2,56,Semi-Urban,Data Analyst,100456,0 +33399,Male,39,Diploma,14,68,3,16,84,6.0,4,14,Semi-Urban,Software Engineer,119695,0 +33400,Female,58,High School,7,66,86,31,10,3.0,1,67,Rural,ML Engineer,106273,1 +33401,Male,34,Masters,7,37,76,27,77,0.0,0,66,Rural,ML Engineer,102880,0 +33402,Male,58,High School,6,96,65,57,99,1.0,3,7,Urban,ML Engineer,92641,0 +33403,Male,54,Bachelors,8,5,12,86,93,2.0,2,95,Semi-Urban,Data Analyst,28608,0 +33404,Male,31,Bachelors,7,33,45,2,48,4.0,4,34,Semi-Urban,ML Engineer,30608,0 +33405,Male,58,High School,12,27,56,96,86,5.0,5,7,Semi-Urban,Manager,120865,0 +33406,Male,32,Bachelors,0,8,8,59,15,3.0,4,71,Semi-Urban,Software Engineer,126261,0 +33407,Male,42,Bachelors,6,86,43,84,57,1.0,2,2,Urban,Data Analyst,149656,0 +33408,Other,55,Bachelors,7,43,73,98,70,9.0,2,15,Urban,Data Analyst,90525,0 +33409,Female,58,Bachelors,6,28,21,99,21,8.0,4,61,Urban,Manager,136453,0 +33410,Female,40,Masters,15,33,76,55,16,4.0,4,66,Urban,Software Engineer,49270,0 +33411,Female,56,Masters,4,10,59,51,41,0.0,0,67,Urban,ML Engineer,100574,0 +33412,Female,50,Bachelors,1,14,86,97,69,7.0,1,93,Semi-Urban,HR Executive,33858,1 +33413,Male,56,Diploma,1,71,26,79,67,1.0,0,45,Urban,ML Engineer,102908,0 +33414,Male,22,Bachelors,10,60,64,44,93,7.0,2,32,Urban,ML Engineer,143927,0 +33415,Male,29,Diploma,0,36,45,52,29,5.0,4,90,Semi-Urban,Manager,85241,0 +33416,Male,58,Bachelors,18,43,99,54,90,6.0,7,83,Rural,Software Engineer,97542,1 +33417,Male,53,Bachelors,9,72,83,61,58,4.0,7,5,Urban,Manager,148140,0 +33418,Other,53,PhD,17,3,44,91,6,5.0,4,63,Urban,ML Engineer,144612,0 +33419,Male,51,Masters,15,86,62,96,3,9.0,5,11,Urban,Data Analyst,54956,1 +33420,Male,45,Bachelors,0,38,1,45,76,3.0,4,38,Rural,Manager,141530,0 +33421,Female,35,PhD,18,88,11,79,92,8.0,1,59,Semi-Urban,HR Executive,108404,0 +33422,Male,29,Bachelors,18,32,27,34,24,7.0,6,41,Semi-Urban,Data Analyst,53683,0 +33423,Female,50,Bachelors,2,32,62,88,99,2.0,3,40,Rural,Software Engineer,145092,0 +33424,Male,26,Bachelors,8,87,4,67,62,6.0,0,52,Semi-Urban,ML Engineer,45206,0 +33425,Male,30,Bachelors,15,59,10,91,82,0.0,5,2,Urban,Software Engineer,28082,0 +33426,Female,47,Masters,19,30,35,11,21,8.0,7,93,Rural,HR Executive,96725,0 +33427,Female,42,Diploma,1,28,60,78,34,9.0,1,63,Urban,ML Engineer,134581,0 +33428,Male,52,High School,2,0,52,44,77,5.0,3,14,Semi-Urban,Data Analyst,111587,0 +33429,Male,24,Masters,6,72,83,14,95,2.0,0,61,Rural,ML Engineer,139191,0 +33430,Female,30,High School,8,15,36,25,93,7.0,1,23,Urban,HR Executive,62350,0 +33431,Male,57,Diploma,14,61,54,19,89,1.0,7,35,Urban,Software Engineer,112088,0 +33432,Female,39,PhD,10,25,9,86,36,2.0,6,88,Urban,HR Executive,127705,0 +33433,Other,51,Diploma,4,56,62,57,28,8.0,0,79,Urban,Software Engineer,38187,1 +33434,Male,49,Diploma,3,83,53,71,76,7.0,3,8,Rural,ML Engineer,51919,0 +33435,Female,46,High School,7,62,29,43,25,5.0,0,93,Rural,ML Engineer,78978,0 +33436,Female,59,Bachelors,4,56,94,80,27,7.0,1,11,Rural,Software Engineer,126078,1 +33437,Male,56,Bachelors,12,24,3,73,82,3.0,6,20,Rural,Software Engineer,119599,0 +33438,Other,32,Bachelors,13,93,71,67,31,6.0,5,79,Urban,Software Engineer,60822,1 +33439,Female,51,PhD,9,26,60,11,37,2.0,5,33,Urban,Software Engineer,132514,0 +33440,Male,28,Diploma,9,93,55,86,51,4.0,3,19,Urban,Data Analyst,100805,1 +33441,Female,34,High School,8,28,25,31,5,7.0,4,82,Semi-Urban,Software Engineer,108060,0 +33442,Male,41,Bachelors,7,70,24,26,2,2.0,0,21,Urban,Data Analyst,81466,0 +33443,Male,59,High School,15,60,37,29,82,7.0,0,39,Rural,Software Engineer,113450,0 +33444,Female,32,Diploma,14,15,91,25,46,3.0,0,38,Urban,Data Analyst,59463,0 +33445,Male,59,Bachelors,16,32,32,74,8,1.0,0,46,Semi-Urban,HR Executive,139585,0 +33446,Female,53,Diploma,5,42,34,34,37,1.0,5,39,Urban,Manager,70746,0 +33447,Male,32,Bachelors,5,90,94,72,47,2.0,6,30,Urban,Manager,31028,1 +33448,Male,36,Bachelors,10,97,50,60,48,0.0,7,80,Rural,Software Engineer,124618,1 +33449,Female,41,High School,7,21,29,0,81,1.0,3,84,Urban,Manager,47143,0 +33450,Other,43,Bachelors,7,35,63,7,41,2.0,4,62,Urban,Data Analyst,144387,0 +33451,Female,35,Bachelors,7,31,41,7,5,7.0,5,78,Urban,Manager,58283,0 +33452,Female,36,High School,7,37,18,0,50,2.0,2,87,Rural,ML Engineer,93939,0 +33453,Male,37,Diploma,13,48,65,61,82,4.0,1,40,Urban,HR Executive,51295,0 +33454,Female,50,Bachelors,16,55,35,24,39,7.0,1,27,Rural,Software Engineer,50264,0 +33455,Male,40,Diploma,16,87,13,94,40,6.0,6,47,Semi-Urban,Data Analyst,126257,1 +33456,Male,21,Bachelors,13,27,68,34,57,4.0,4,44,Semi-Urban,Data Analyst,113411,0 +33457,Male,33,Masters,11,31,23,27,88,7.0,7,80,Urban,Manager,123550,0 +33458,Female,30,Bachelors,13,98,19,34,8,8.0,1,21,Rural,Data Analyst,97344,0 +33459,Male,57,Diploma,9,96,13,15,78,0.0,7,67,Rural,Data Analyst,95234,0 +33460,Male,21,Diploma,19,90,23,45,23,9.0,7,69,Urban,Software Engineer,114815,0 +33461,Male,34,Diploma,2,87,72,82,75,1.0,7,65,Urban,Manager,21213,1 +33462,Male,34,Masters,14,96,20,28,41,3.0,4,29,Urban,Data Analyst,132668,0 +33463,Female,30,Masters,7,3,1,73,13,1.0,5,15,Rural,Data Analyst,123438,0 +33464,Male,58,Masters,1,92,6,1,24,1.0,1,42,Urban,ML Engineer,121498,0 +33465,Male,27,Diploma,5,62,73,79,36,1.0,3,65,Semi-Urban,Software Engineer,134215,1 +33466,Male,47,Diploma,14,63,1,37,56,0.0,1,40,Urban,Data Analyst,55398,0 +33467,Male,22,Bachelors,7,91,94,51,26,1.0,0,60,Urban,Data Analyst,36428,1 +33468,Male,24,High School,1,0,39,24,1,2.0,2,5,Semi-Urban,HR Executive,59073,0 +33469,Male,37,Bachelors,16,95,25,97,4,4.0,1,53,Urban,ML Engineer,147349,1 +33470,Male,40,High School,17,85,43,73,29,7.0,3,56,Urban,HR Executive,40531,1 +33471,Male,27,High School,10,79,92,80,61,9.0,3,0,Urban,ML Engineer,140472,1 +33472,Female,26,Diploma,3,67,95,76,22,5.0,1,87,Semi-Urban,Software Engineer,145345,1 +33473,Other,28,Masters,8,20,14,81,22,7.0,2,81,Urban,ML Engineer,94786,0 +33474,Male,30,Bachelors,1,73,65,15,28,8.0,2,30,Rural,HR Executive,75357,0 +33475,Male,45,Masters,8,89,31,36,83,4.0,0,63,Urban,Software Engineer,31591,0 +33476,Female,24,Masters,5,67,55,7,67,0.0,7,6,Semi-Urban,ML Engineer,146974,0 +33477,Male,36,Masters,7,43,4,62,88,8.0,1,74,Rural,Software Engineer,115233,0 +33478,Male,28,Bachelors,3,42,40,59,96,0.0,4,80,Semi-Urban,Software Engineer,97965,0 +33479,Male,57,Masters,1,77,58,69,80,1.0,6,93,Rural,ML Engineer,76294,1 +33480,Female,44,Bachelors,1,18,91,10,68,3.0,1,34,Semi-Urban,Data Analyst,33606,0 +33481,Female,38,Masters,18,51,23,45,17,3.0,3,41,Semi-Urban,Software Engineer,49554,0 +33482,Male,24,Masters,9,31,26,81,30,9.0,2,63,Urban,HR Executive,21530,0 +33483,Male,43,Bachelors,9,71,55,36,39,1.0,3,74,Rural,ML Engineer,54652,1 +33484,Male,43,Masters,1,13,96,6,17,7.0,3,8,Semi-Urban,Data Analyst,101017,0 +33485,Male,25,Bachelors,2,47,47,28,50,3.0,3,45,Urban,ML Engineer,145651,0 +33486,Male,32,Bachelors,7,7,36,33,90,9.0,1,57,Urban,ML Engineer,53037,0 +33487,Female,21,High School,16,90,31,9,41,2.0,5,76,Urban,Manager,115415,0 +33488,Male,26,Diploma,12,83,11,39,90,1.0,2,35,Rural,HR Executive,147255,0 +33489,Male,44,Bachelors,14,68,15,7,73,5.0,2,7,Semi-Urban,Manager,71195,0 +33490,Male,35,High School,11,60,62,48,45,8.0,3,17,Rural,HR Executive,27002,0 +33491,Male,33,Masters,16,80,45,88,22,4.0,6,82,Urban,HR Executive,64170,1 +33492,Other,32,Masters,1,51,10,26,19,0.0,3,34,Semi-Urban,Data Analyst,123213,0 +33493,Male,48,High School,15,37,19,58,77,3.0,5,83,Rural,ML Engineer,63891,0 +33494,Male,34,Bachelors,13,90,72,58,62,4.0,2,46,Urban,Manager,141923,1 +33495,Male,58,Diploma,3,29,39,99,18,1.0,0,38,Semi-Urban,HR Executive,32618,0 +33496,Male,37,High School,13,37,55,54,62,2.0,7,35,Urban,ML Engineer,34250,0 +33497,Female,31,Bachelors,15,79,75,47,38,2.0,3,31,Urban,ML Engineer,58766,0 +33498,Male,56,Masters,18,99,51,9,46,9.0,1,38,Semi-Urban,HR Executive,43443,0 +33499,Male,48,Bachelors,11,52,20,54,96,6.0,3,39,Urban,Data Analyst,126150,0 +33500,Male,45,High School,15,52,31,77,65,4.0,0,52,Urban,HR Executive,115688,0 +33501,Female,32,Bachelors,1,88,2,1,69,5.0,0,45,Urban,ML Engineer,20169,0 +33502,Female,57,High School,17,88,96,61,16,8.0,5,41,Rural,Manager,94455,1 +33503,Female,40,Bachelors,5,85,86,96,13,3.0,3,85,Semi-Urban,Software Engineer,126051,1 +33504,Male,48,High School,6,50,26,89,53,0.0,4,17,Rural,Manager,148412,0 +33505,Female,36,Bachelors,9,29,33,70,56,1.0,5,72,Urban,HR Executive,101330,0 +33506,Male,28,Diploma,1,65,87,87,12,6.0,3,85,Rural,ML Engineer,101257,1 +33507,Male,29,Bachelors,6,7,41,96,87,2.0,0,4,Semi-Urban,HR Executive,60540,0 +33508,Female,48,Bachelors,16,55,67,87,6,1.0,1,90,Rural,HR Executive,69690,1 +33509,Male,23,Masters,16,71,35,63,91,8.0,1,28,Urban,HR Executive,68412,0 +33510,Male,58,Bachelors,2,2,22,47,15,5.0,4,7,Urban,ML Engineer,72300,0 +33511,Male,55,Bachelors,14,32,96,53,60,0.0,5,69,Rural,Data Analyst,149278,1 +33512,Male,59,High School,16,83,35,98,47,3.0,4,99,Semi-Urban,Manager,116568,1 +33513,Male,36,Bachelors,6,38,27,78,92,4.0,5,70,Urban,Manager,90567,0 +33514,Female,25,High School,11,6,81,97,14,3.0,6,85,Urban,Manager,37434,1 +33515,Male,25,PhD,1,65,52,99,6,8.0,5,2,Rural,Software Engineer,30445,0 +33516,Female,55,Diploma,18,72,1,7,5,7.0,3,94,Rural,HR Executive,111329,0 +33517,Female,46,Bachelors,1,19,97,76,10,4.0,2,16,Urban,HR Executive,79773,0 +33518,Male,29,Bachelors,0,51,85,22,37,6.0,3,30,Urban,Data Analyst,134660,0 +33519,Male,50,High School,6,4,45,2,47,9.0,2,62,Semi-Urban,Software Engineer,61336,0 +33520,Female,56,Bachelors,17,45,81,81,19,9.0,3,99,Urban,HR Executive,34886,1 +33521,Female,47,Bachelors,9,44,20,0,65,5.0,4,14,Rural,ML Engineer,121820,0 +33522,Male,21,High School,3,83,22,66,80,5.0,1,22,Urban,Software Engineer,79935,0 +33523,Male,46,Bachelors,0,5,65,49,55,0.0,1,19,Semi-Urban,Software Engineer,141672,0 +33524,Female,30,Bachelors,11,21,7,82,77,1.0,2,30,Urban,Data Analyst,110325,0 +33525,Male,24,Bachelors,1,6,62,8,24,6.0,0,15,Urban,Software Engineer,43344,0 +33526,Female,24,Masters,9,45,33,57,91,4.0,1,56,Semi-Urban,Manager,137127,0 +33527,Male,24,Bachelors,16,41,35,61,13,3.0,7,21,Rural,Data Analyst,117281,0 +33528,Female,58,Bachelors,12,48,18,69,89,6.0,5,41,Semi-Urban,Software Engineer,146532,0 +33529,Male,29,Bachelors,16,38,5,40,31,4.0,7,22,Rural,Manager,79450,0 +33530,Female,54,Bachelors,13,82,34,68,59,5.0,6,45,Rural,Manager,131551,0 +33531,Other,25,Diploma,15,73,59,65,73,1.0,3,78,Urban,Software Engineer,108779,1 +33532,Male,51,Bachelors,5,35,5,63,5,0.0,4,66,Semi-Urban,Manager,55056,0 +33533,Female,56,High School,6,99,92,87,73,2.0,2,22,Semi-Urban,Manager,65159,1 +33534,Male,53,Bachelors,5,86,51,97,33,9.0,5,12,Urban,Data Analyst,114925,1 +33535,Male,33,Masters,18,67,8,59,29,5.0,0,0,Urban,ML Engineer,83358,0 +33536,Female,31,High School,4,51,50,44,93,8.0,5,93,Urban,Software Engineer,40544,0 +33537,Male,57,Bachelors,5,18,35,17,75,6.0,1,95,Urban,Manager,30295,0 +33538,Male,55,High School,4,71,98,17,49,5.0,4,62,Rural,Data Analyst,23898,1 +33539,Male,38,Masters,4,48,76,76,24,5.0,0,39,Semi-Urban,HR Executive,138097,1 +33540,Male,50,Diploma,8,87,84,71,92,1.0,0,12,Urban,Manager,117952,1 +33541,Female,59,Bachelors,14,41,14,7,68,4.0,2,89,Urban,ML Engineer,127445,0 +33542,Male,33,Bachelors,9,87,66,9,26,4.0,6,40,Semi-Urban,Manager,47331,0 +33543,Male,25,Diploma,14,67,79,26,52,8.0,7,14,Urban,HR Executive,122388,0 +33544,Male,26,High School,16,91,84,66,91,4.0,1,23,Semi-Urban,Software Engineer,97342,1 +33545,Male,26,Bachelors,2,32,79,88,71,5.0,2,45,Semi-Urban,ML Engineer,76975,1 +33546,Male,23,Bachelors,3,42,98,85,35,9.0,5,78,Semi-Urban,Manager,80830,1 +33547,Female,49,Masters,16,12,82,76,47,0.0,3,10,Rural,Software Engineer,85760,0 +33548,Male,41,PhD,17,26,67,20,74,6.0,2,64,Urban,HR Executive,94585,0 +33549,Male,28,Diploma,1,97,54,78,69,7.0,7,95,Urban,ML Engineer,94403,1 +33550,Female,48,Masters,18,18,50,37,95,7.0,0,0,Urban,Manager,35289,0 +33551,Male,32,Bachelors,16,35,67,80,22,1.0,4,12,Urban,HR Executive,142193,0 +33552,Male,58,Diploma,17,31,36,36,22,9.0,0,95,Urban,Data Analyst,36783,0 +33553,Female,33,Masters,10,88,87,42,31,4.0,7,27,Urban,Data Analyst,52213,1 +33554,Male,51,PhD,0,27,88,73,9,1.0,1,2,Urban,HR Executive,45245,0 +33555,Male,53,Bachelors,1,18,64,80,59,5.0,4,27,Urban,HR Executive,137851,0 +33556,Male,52,Masters,13,22,78,9,28,0.0,7,32,Semi-Urban,ML Engineer,84170,0 +33557,Male,47,High School,8,45,84,68,82,2.0,0,91,Urban,Data Analyst,116211,1 +33558,Male,38,Masters,1,5,6,18,94,7.0,7,2,Semi-Urban,HR Executive,76526,0 +33559,Other,35,Bachelors,8,74,29,38,26,1.0,1,47,Urban,ML Engineer,89172,0 +33560,Male,24,PhD,3,89,87,84,50,5.0,6,11,Semi-Urban,ML Engineer,57001,1 +33561,Female,31,Masters,5,44,34,77,39,6.0,5,28,Rural,Data Analyst,37811,0 +33562,Female,39,Bachelors,3,94,92,73,48,6.0,5,56,Rural,Manager,115783,1 +33563,Female,49,Bachelors,19,22,21,52,33,4.0,5,82,Semi-Urban,ML Engineer,89844,0 +33564,Male,35,Diploma,1,51,10,26,29,4.0,1,51,Semi-Urban,Manager,128327,0 +33565,Male,53,PhD,12,47,3,74,15,3.0,7,26,Urban,Manager,105978,0 +33566,Male,52,High School,6,5,90,65,41,5.0,1,60,Semi-Urban,ML Engineer,71958,0 +33567,Female,41,Diploma,3,67,7,9,61,4.0,1,80,Urban,Software Engineer,134638,0 +33568,Male,21,Bachelors,9,21,76,36,40,1.0,4,21,Rural,Software Engineer,75237,0 +33569,Female,34,Masters,5,72,96,85,57,9.0,4,1,Semi-Urban,HR Executive,115029,1 +33570,Male,37,Bachelors,7,31,23,11,69,7.0,5,7,Semi-Urban,HR Executive,67039,0 +33571,Female,46,Bachelors,9,5,61,22,98,3.0,2,81,Rural,Manager,45462,0 +33572,Male,26,Diploma,17,15,8,43,87,4.0,6,75,Urban,Software Engineer,62334,0 +33573,Female,27,Bachelors,18,47,61,15,49,1.0,6,95,Urban,Manager,142676,0 +33574,Male,36,Bachelors,14,40,2,36,39,5.0,3,40,Semi-Urban,ML Engineer,111095,0 +33575,Female,37,Bachelors,4,56,52,16,7,1.0,3,91,Semi-Urban,Data Analyst,62242,0 +33576,Male,54,Bachelors,4,20,23,51,29,9.0,6,92,Urban,Software Engineer,27615,0 +33577,Female,44,Bachelors,10,32,3,74,39,3.0,6,60,Urban,Data Analyst,22530,0 +33578,Female,57,Masters,9,48,77,25,58,3.0,3,88,Urban,ML Engineer,125139,0 +33579,Male,30,Diploma,0,53,48,66,79,0.0,4,43,Rural,Manager,107336,0 +33580,Male,47,High School,11,56,36,38,64,7.0,5,82,Rural,Manager,82506,0 +33581,Male,43,Bachelors,15,67,30,70,88,7.0,7,53,Urban,Data Analyst,81457,0 +33582,Male,22,PhD,4,33,47,56,45,3.0,6,26,Urban,ML Engineer,73355,0 +33583,Female,29,Masters,5,73,44,95,23,4.0,1,95,Urban,HR Executive,149153,1 +33584,Male,57,Diploma,11,98,74,9,65,1.0,1,38,Urban,Manager,38981,0 +33585,Male,24,High School,18,96,10,39,31,9.0,7,0,Rural,ML Engineer,112118,0 +33586,Female,51,High School,18,32,25,82,75,9.0,3,41,Urban,Manager,24726,0 +33587,Male,52,Masters,0,50,41,19,45,8.0,7,95,Rural,Manager,87380,0 +33588,Other,41,Bachelors,5,4,95,0,85,3.0,0,54,Semi-Urban,HR Executive,119328,0 +33589,Male,41,Masters,12,99,92,13,1,4.0,1,18,Urban,Data Analyst,34716,0 +33590,Male,32,Bachelors,6,38,82,6,30,4.0,4,0,Urban,Software Engineer,110841,0 +33591,Male,35,Masters,6,13,77,36,96,5.0,2,89,Urban,Data Analyst,149560,0 +33592,Male,35,Diploma,6,56,28,14,82,2.0,6,59,Urban,ML Engineer,79340,0 +33593,Male,38,Bachelors,3,51,66,46,29,1.0,4,61,Urban,Software Engineer,80672,0 +33594,Male,40,Masters,9,26,4,68,85,1.0,0,35,Rural,Data Analyst,62323,0 +33595,Male,46,Masters,6,70,39,77,97,6.0,2,1,Semi-Urban,Software Engineer,48158,0 +33596,Male,44,Bachelors,17,71,2,79,30,0.0,6,58,Urban,Manager,84896,0 +33597,Male,41,Diploma,12,69,68,22,77,1.0,6,67,Urban,Data Analyst,80219,0 +33598,Male,34,Masters,7,92,61,66,1,8.0,3,71,Urban,HR Executive,87010,1 +33599,Female,22,PhD,17,89,88,52,86,8.0,4,32,Semi-Urban,ML Engineer,138239,1 +33600,Other,41,PhD,11,34,31,59,92,8.0,0,37,Rural,Manager,64752,0 +33601,Other,51,High School,2,74,9,23,16,4.0,1,73,Urban,Data Analyst,36757,0 +33602,Female,23,Bachelors,17,80,42,89,6,4.0,7,67,Urban,Data Analyst,94301,1 +33603,Female,40,Bachelors,7,41,95,15,76,3.0,3,64,Urban,ML Engineer,93905,0 +33604,Male,42,Bachelors,0,57,80,72,32,9.0,1,81,Urban,Software Engineer,124508,1 +33605,Male,31,Bachelors,8,23,62,34,96,6.0,2,43,Urban,HR Executive,128732,0 +33606,Male,41,Diploma,5,13,96,48,40,5.0,0,70,Urban,Data Analyst,117953,0 +33607,Female,37,Masters,19,31,57,28,47,2.0,0,27,Semi-Urban,Software Engineer,132692,0 +33608,Female,28,Bachelors,10,78,31,6,28,8.0,7,53,Semi-Urban,HR Executive,73391,0 +33609,Male,54,Bachelors,15,11,35,91,70,2.0,2,34,Urban,Data Analyst,57244,0 +33610,Male,21,Bachelors,4,62,77,61,12,0.0,7,54,Rural,Software Engineer,71381,1 +33611,Female,34,Masters,5,16,57,6,89,2.0,4,43,Urban,Software Engineer,93926,0 +33612,Male,24,High School,1,19,83,40,91,6.0,1,35,Semi-Urban,HR Executive,142141,0 +33613,Male,23,PhD,7,69,69,13,94,0.0,1,16,Rural,HR Executive,92970,0 +33614,Male,44,Bachelors,1,23,89,21,78,7.0,7,44,Urban,Software Engineer,75754,0 +33615,Other,30,Diploma,17,33,55,97,19,7.0,4,81,Rural,Data Analyst,117621,1 +33616,Male,46,Masters,4,6,2,82,55,3.0,2,87,Urban,Software Engineer,76312,0 +33617,Male,51,Diploma,19,16,85,87,19,2.0,6,76,Rural,ML Engineer,73293,1 +33618,Male,30,Bachelors,6,26,7,25,13,4.0,1,64,Urban,ML Engineer,37236,0 +33619,Male,33,Diploma,15,43,50,12,25,5.0,6,16,Urban,Data Analyst,33874,0 +33620,Male,28,Bachelors,3,69,24,28,38,9.0,2,68,Urban,HR Executive,86439,0 +33621,Male,48,Diploma,8,74,72,4,38,7.0,1,11,Semi-Urban,Software Engineer,34031,0 +33622,Male,48,High School,18,78,63,76,6,2.0,6,21,Semi-Urban,HR Executive,59781,1 +33623,Male,57,Masters,11,26,44,75,43,4.0,1,63,Urban,Software Engineer,54585,0 +33624,Male,34,Diploma,11,57,62,28,92,1.0,0,9,Rural,Data Analyst,90696,0 +33625,Male,43,High School,2,30,46,56,47,8.0,5,31,Semi-Urban,HR Executive,83911,0 +33626,Female,41,Diploma,13,1,68,9,84,7.0,2,54,Rural,HR Executive,43587,0 +33627,Male,53,Bachelors,10,66,82,54,52,9.0,5,59,Urban,ML Engineer,89432,1 +33628,Male,49,Bachelors,8,84,13,36,73,8.0,5,96,Urban,Software Engineer,148993,0 +33629,Female,36,PhD,5,56,45,44,84,0.0,7,73,Rural,HR Executive,118590,0 +33630,Male,30,Masters,14,75,72,46,47,8.0,1,39,Urban,Manager,118623,0 +33631,Male,38,High School,9,13,9,77,6,5.0,0,48,Urban,Data Analyst,116895,0 +33632,Male,45,High School,18,35,36,7,5,4.0,1,20,Urban,ML Engineer,54828,0 +33633,Female,40,Bachelors,1,38,85,70,11,2.0,6,25,Urban,Software Engineer,92125,0 +33634,Female,39,Bachelors,3,69,1,20,97,3.0,3,21,Urban,Manager,44038,0 +33635,Male,24,Diploma,19,69,79,28,54,0.0,5,57,Rural,Software Engineer,62454,0 +33636,Female,25,Bachelors,11,10,47,22,96,6.0,7,82,Semi-Urban,ML Engineer,100914,0 +33637,Male,58,Masters,9,77,46,81,46,3.0,6,60,Urban,Manager,36268,1 +33638,Female,24,Bachelors,14,82,61,69,56,6.0,1,84,Urban,Software Engineer,48785,1 +33639,Male,56,High School,3,19,50,27,69,0.0,3,14,Urban,HR Executive,69857,0 +33640,Female,26,Masters,8,47,57,7,37,6.0,4,14,Semi-Urban,Software Engineer,42312,0 +33641,Male,31,Bachelors,14,21,8,96,67,8.0,4,35,Semi-Urban,ML Engineer,23872,0 +33642,Male,29,High School,14,1,99,80,11,1.0,4,86,Rural,ML Engineer,130761,1 +33643,Male,22,Diploma,18,46,42,31,17,6.0,3,65,Semi-Urban,Software Engineer,55416,0 +33644,Female,29,High School,7,57,12,99,99,5.0,6,14,Semi-Urban,Data Analyst,84323,0 +33645,Female,29,Masters,3,76,47,2,99,9.0,3,73,Semi-Urban,Software Engineer,36945,0 +33646,Male,29,High School,0,16,10,97,62,4.0,1,78,Urban,Data Analyst,35318,0 +33647,Female,47,Masters,4,49,81,20,46,9.0,7,56,Urban,HR Executive,95984,0 +33648,Female,44,High School,16,55,52,65,38,7.0,5,19,Urban,ML Engineer,127961,0 +33649,Female,29,Bachelors,19,28,55,58,90,9.0,1,65,Urban,ML Engineer,89090,0 +33650,Male,44,Bachelors,17,94,71,32,98,4.0,1,49,Urban,ML Engineer,114043,1 +33651,Male,59,Bachelors,18,56,75,68,77,2.0,1,87,Urban,Software Engineer,38204,1 +33652,Male,46,Diploma,10,66,59,94,91,9.0,4,12,Rural,HR Executive,59619,0 +33653,Male,32,Diploma,9,88,94,58,90,4.0,5,57,Urban,HR Executive,44576,1 +33654,Female,21,Bachelors,11,43,51,19,40,0.0,3,56,Semi-Urban,Data Analyst,109381,0 +33655,Female,21,Bachelors,15,99,7,9,81,3.0,6,51,Urban,Data Analyst,94930,0 +33656,Female,45,Bachelors,2,72,94,69,21,1.0,5,87,Urban,ML Engineer,107070,1 +33657,Male,56,High School,19,14,26,56,11,6.0,5,62,Rural,Data Analyst,93946,0 +33658,Female,43,Diploma,14,45,16,29,17,4.0,0,43,Rural,HR Executive,49486,0 +33659,Male,47,PhD,14,45,12,34,51,1.0,2,53,Semi-Urban,Manager,88451,0 +33660,Female,38,Bachelors,18,32,1,94,89,0.0,3,64,Semi-Urban,HR Executive,110742,0 +33661,Male,28,Masters,0,71,55,25,63,9.0,5,34,Rural,HR Executive,132583,0 +33662,Female,42,Bachelors,4,72,3,5,71,8.0,7,60,Semi-Urban,ML Engineer,44305,0 +33663,Female,38,Diploma,3,68,65,95,74,4.0,3,9,Semi-Urban,ML Engineer,36598,0 +33664,Female,46,High School,2,96,45,88,19,4.0,7,84,Urban,Manager,142822,1 +33665,Male,49,Bachelors,10,94,89,35,29,9.0,5,21,Urban,ML Engineer,111362,1 +33666,Male,42,Bachelors,12,80,65,79,43,6.0,6,76,Rural,Data Analyst,55964,1 +33667,Male,35,High School,1,24,4,40,11,7.0,6,59,Urban,HR Executive,92243,0 +33668,Male,24,Masters,18,50,19,4,14,1.0,7,27,Urban,Software Engineer,139676,0 +33669,Female,52,Bachelors,17,36,89,51,7,5.0,2,43,Urban,Software Engineer,81218,0 +33670,Female,31,High School,0,1,36,54,73,4.0,2,94,Semi-Urban,Manager,84817,0 +33671,Male,27,Masters,13,84,72,72,77,6.0,0,7,Rural,Data Analyst,147924,1 +33672,Male,26,Diploma,1,2,15,20,16,3.0,5,47,Urban,ML Engineer,145777,0 +33673,Female,29,Bachelors,3,77,66,40,31,1.0,4,25,Rural,Manager,143213,0 +33674,Male,36,Bachelors,16,44,34,23,35,8.0,2,80,Urban,ML Engineer,141046,0 +33675,Male,39,Bachelors,2,55,31,23,17,4.0,2,80,Urban,Software Engineer,74716,0 +33676,Female,26,Masters,8,10,67,51,57,3.0,1,67,Semi-Urban,Software Engineer,94354,0 +33677,Female,27,Bachelors,17,16,58,72,37,8.0,5,70,Urban,ML Engineer,93199,0 +33678,Male,59,Bachelors,10,91,36,1,84,6.0,4,77,Urban,Data Analyst,55948,0 +33679,Male,55,Masters,5,13,26,90,93,3.0,1,80,Rural,Software Engineer,135194,0 +33680,Male,26,Diploma,2,77,37,34,64,8.0,6,69,Rural,HR Executive,137979,0 +33681,Male,51,Bachelors,1,22,43,22,62,1.0,4,27,Urban,ML Engineer,51987,0 +33682,Male,56,Bachelors,8,18,63,30,51,1.0,5,55,Urban,Software Engineer,45109,0 +33683,Male,25,Bachelors,12,59,34,87,71,3.0,5,83,Urban,Data Analyst,110513,1 +33684,Female,32,Bachelors,10,6,62,99,84,1.0,0,44,Rural,Manager,76567,0 +33685,Female,27,Bachelors,0,1,14,77,84,2.0,4,76,Urban,Data Analyst,54783,0 +33686,Female,41,Masters,8,47,62,65,81,6.0,5,42,Urban,HR Executive,128523,0 +33687,Male,38,Diploma,4,65,78,87,71,6.0,7,79,Semi-Urban,HR Executive,72214,1 +33688,Male,34,Bachelors,12,8,43,10,1,6.0,7,20,Rural,Manager,63380,0 +33689,Female,24,High School,14,67,50,98,23,2.0,7,48,Urban,Manager,110516,1 +33690,Female,45,Bachelors,11,61,77,84,13,3.0,4,91,Urban,Manager,27855,1 +33691,Female,45,Bachelors,0,63,68,98,64,2.0,3,90,Rural,Data Analyst,125604,1 +33692,Other,53,Bachelors,10,83,27,53,23,6.0,2,55,Rural,Software Engineer,96115,0 +33693,Female,35,Diploma,17,33,2,23,6,5.0,3,6,Urban,Software Engineer,125363,0 +33694,Male,51,Bachelors,8,92,22,80,9,9.0,1,27,Semi-Urban,Software Engineer,66328,0 +33695,Male,58,PhD,16,21,62,78,51,5.0,3,55,Semi-Urban,Manager,142142,0 +33696,Male,37,Diploma,17,23,6,24,49,5.0,5,69,Urban,Data Analyst,113097,0 +33697,Female,40,Bachelors,10,53,62,56,13,5.0,6,40,Rural,HR Executive,88256,0 +33698,Male,25,Diploma,18,29,99,55,75,1.0,6,99,Semi-Urban,Manager,72960,1 +33699,Female,49,High School,7,48,31,18,45,0.0,0,89,Urban,HR Executive,142323,0 +33700,Male,58,Bachelors,17,88,34,14,44,2.0,3,19,Urban,ML Engineer,118345,0 +33701,Female,24,High School,8,26,27,89,63,0.0,4,16,Urban,ML Engineer,25260,0 +33702,Male,58,Bachelors,7,97,6,27,80,7.0,6,2,Rural,HR Executive,61369,0 +33703,Male,56,Diploma,9,10,96,54,17,9.0,1,2,Urban,Manager,56963,0 +33704,Female,23,High School,15,23,93,73,92,0.0,7,66,Rural,Manager,72736,1 +33705,Male,27,Diploma,13,90,32,49,14,2.0,2,17,Urban,Software Engineer,46967,0 +33706,Male,54,Bachelors,1,48,51,48,58,8.0,1,16,Urban,Data Analyst,79973,0 +33707,Male,22,Masters,9,3,98,79,56,9.0,3,65,Semi-Urban,Manager,79204,1 +33708,Female,43,PhD,10,22,59,3,86,7.0,7,92,Urban,Manager,42231,0 +33709,Female,38,Bachelors,7,87,88,88,39,5.0,5,80,Urban,ML Engineer,70791,1 +33710,Female,51,Bachelors,9,98,93,48,61,4.0,3,14,Semi-Urban,Data Analyst,26526,1 +33711,Female,32,Masters,15,51,43,51,53,5.0,2,35,Urban,Data Analyst,31454,0 +33712,Female,33,Bachelors,0,67,81,38,6,8.0,4,9,Rural,Data Analyst,50244,0 +33713,Male,26,PhD,12,40,37,47,68,3.0,7,54,Urban,HR Executive,23248,0 +33714,Male,26,Bachelors,18,89,16,62,38,9.0,3,47,Rural,Manager,32103,0 +33715,Male,50,Masters,2,23,12,59,78,9.0,6,22,Urban,Manager,32401,0 +33716,Male,52,High School,1,92,15,73,53,1.0,7,92,Urban,Software Engineer,125183,1 +33717,Female,48,Bachelors,10,57,4,74,74,4.0,2,63,Semi-Urban,ML Engineer,71587,0 +33718,Male,47,Diploma,11,85,99,20,48,0.0,3,28,Urban,Manager,31165,0 +33719,Male,53,Diploma,6,79,5,12,94,8.0,6,78,Urban,ML Engineer,111786,0 +33720,Male,37,High School,16,87,82,10,25,9.0,7,46,Rural,ML Engineer,79520,0 +33721,Male,33,Bachelors,14,45,14,5,7,4.0,3,6,Rural,Data Analyst,41642,0 +33722,Female,36,Diploma,17,17,16,52,49,4.0,6,7,Urban,HR Executive,58725,0 +33723,Male,46,Bachelors,17,40,4,45,63,8.0,5,48,Semi-Urban,Data Analyst,44306,0 +33724,Female,47,Bachelors,10,99,47,12,46,4.0,4,25,Rural,Data Analyst,115119,0 +33725,Male,48,Masters,15,76,52,80,47,2.0,2,91,Rural,Manager,125890,1 +33726,Other,45,High School,5,64,29,6,19,3.0,5,23,Urban,Software Engineer,121152,0 +33727,Male,43,Masters,11,91,66,50,26,0.0,6,93,Urban,Software Engineer,47862,1 +33728,Male,42,Diploma,1,27,15,46,29,6.0,1,46,Rural,Manager,76268,0 +33729,Female,35,Masters,17,36,37,64,36,4.0,0,29,Urban,Manager,52011,0 +33730,Male,56,Masters,11,78,10,56,16,0.0,6,78,Urban,HR Executive,121628,0 +33731,Male,27,Bachelors,18,24,15,95,32,5.0,1,21,Rural,Software Engineer,63274,0 +33732,Male,42,Diploma,19,0,34,56,92,0.0,1,27,Urban,Data Analyst,112471,0 +33733,Male,50,Bachelors,6,62,89,18,25,8.0,3,89,Semi-Urban,Software Engineer,131944,1 +33734,Female,30,Masters,13,74,27,92,50,6.0,2,47,Rural,Software Engineer,24213,0 +33735,Male,45,Bachelors,3,19,91,67,21,9.0,3,51,Urban,ML Engineer,78161,0 +33736,Female,39,Diploma,6,52,87,97,80,3.0,1,2,Urban,Manager,74339,0 +33737,Male,55,Diploma,12,2,31,80,66,0.0,5,58,Urban,ML Engineer,129475,0 +33738,Male,21,Bachelors,14,9,8,51,17,3.0,7,23,Semi-Urban,HR Executive,89447,0 +33739,Male,52,Bachelors,9,34,55,11,5,2.0,7,19,Urban,Manager,25118,0 +33740,Female,51,Bachelors,2,55,45,35,91,0.0,2,28,Urban,ML Engineer,145182,0 +33741,Male,53,Diploma,9,96,10,71,3,6.0,0,55,Rural,Data Analyst,55058,0 +33742,Other,35,Bachelors,2,53,91,35,82,2.0,5,7,Semi-Urban,Manager,36853,0 +33743,Male,59,Bachelors,9,1,19,67,23,3.0,2,31,Urban,Software Engineer,142446,0 +33744,Female,32,High School,12,44,88,27,59,7.0,0,1,Urban,Manager,93222,0 +33745,Female,40,Bachelors,11,42,85,98,27,8.0,7,59,Urban,Manager,104351,1 +33746,Male,21,Bachelors,19,20,86,6,89,9.0,4,57,Urban,HR Executive,35077,0 +33747,Female,27,High School,15,66,11,81,61,2.0,6,57,Urban,Data Analyst,123305,0 +33748,Male,29,Diploma,12,42,0,69,14,0.0,3,63,Semi-Urban,HR Executive,43359,0 +33749,Male,42,High School,12,28,80,54,45,1.0,0,91,Semi-Urban,HR Executive,131719,1 +33750,Male,54,Diploma,11,60,91,52,80,9.0,1,75,Urban,HR Executive,46812,1 +33751,Female,51,Bachelors,4,48,84,29,45,4.0,5,80,Urban,Data Analyst,95291,1 +33752,Male,29,Bachelors,4,2,49,27,97,1.0,3,34,Semi-Urban,Data Analyst,100206,0 +33753,Male,24,Bachelors,4,51,26,99,99,3.0,0,2,Urban,Data Analyst,50066,0 +33754,Other,35,Diploma,18,90,54,9,89,1.0,3,88,Urban,Software Engineer,93783,1 +33755,Male,33,Bachelors,13,17,61,52,12,9.0,6,65,Urban,Software Engineer,103011,0 +33756,Male,32,Diploma,5,35,78,63,14,2.0,7,48,Urban,HR Executive,76344,0 +33757,Other,54,Bachelors,7,18,87,22,15,3.0,0,64,Urban,Manager,50481,0 +33758,Male,29,PhD,12,78,63,13,9,4.0,2,73,Urban,ML Engineer,64431,0 +33759,Male,51,High School,8,2,60,95,50,1.0,6,62,Urban,HR Executive,46547,0 +33760,Female,41,Masters,2,86,72,35,81,2.0,0,62,Urban,Manager,21929,1 +33761,Male,56,Diploma,5,68,88,20,11,3.0,4,93,Urban,Software Engineer,120669,1 +33762,Male,30,Masters,16,38,54,32,97,8.0,2,23,Urban,Software Engineer,23796,0 +33763,Male,21,High School,19,25,86,50,85,1.0,1,70,Urban,Data Analyst,93312,0 +33764,Female,40,Diploma,17,75,36,71,87,2.0,0,59,Semi-Urban,Manager,79679,1 +33765,Male,39,Bachelors,4,8,24,80,93,9.0,1,26,Urban,Manager,55875,0 +33766,Male,33,Masters,0,61,87,32,31,9.0,1,71,Urban,Software Engineer,110302,1 +33767,Male,37,Diploma,19,51,66,63,32,3.0,1,50,Semi-Urban,Manager,66276,0 +33768,Male,49,Bachelors,13,28,41,6,97,2.0,0,69,Urban,HR Executive,44258,0 +33769,Female,25,Bachelors,13,12,6,36,93,8.0,4,73,Semi-Urban,Manager,73344,0 +33770,Male,35,High School,17,23,42,67,11,1.0,3,21,Urban,Software Engineer,102893,0 +33771,Female,36,High School,14,3,3,9,24,5.0,4,47,Rural,Manager,53499,0 +33772,Male,48,Bachelors,3,17,39,45,67,1.0,5,57,Urban,Software Engineer,56280,0 +33773,Male,54,Diploma,16,77,22,3,39,0.0,3,52,Urban,Software Engineer,64898,0 +33774,Male,34,High School,5,60,62,94,0,7.0,6,11,Rural,ML Engineer,109512,0 +33775,Male,30,Diploma,1,96,66,45,8,5.0,6,14,Urban,HR Executive,64160,0 +33776,Male,42,Diploma,17,40,62,24,24,8.0,6,99,Urban,ML Engineer,68768,0 +33777,Female,39,Diploma,17,36,91,38,25,6.0,7,29,Urban,Data Analyst,73360,0 +33778,Female,25,PhD,5,1,66,31,79,7.0,1,23,Semi-Urban,Data Analyst,123797,0 +33779,Male,27,Bachelors,1,45,1,51,94,5.0,7,38,Urban,Data Analyst,125892,0 +33780,Female,32,Masters,4,57,62,75,25,7.0,7,25,Semi-Urban,HR Executive,124155,0 +33781,Other,26,Bachelors,5,48,30,7,76,4.0,0,30,Semi-Urban,Software Engineer,94215,0 +33782,Male,43,Bachelors,5,91,10,95,49,7.0,2,41,Urban,HR Executive,138543,1 +33783,Male,27,Bachelors,9,47,47,69,50,8.0,5,30,Urban,ML Engineer,139821,0 +33784,Female,47,Masters,16,28,49,91,48,7.0,1,48,Urban,Data Analyst,106980,0 +33785,Male,30,Diploma,15,26,57,62,7,5.0,5,27,Rural,Data Analyst,32485,0 +33786,Female,36,Bachelors,6,15,61,73,9,3.0,4,83,Urban,ML Engineer,111174,0 +33787,Other,37,High School,11,81,24,71,12,9.0,3,0,Semi-Urban,Data Analyst,89084,0 +33788,Male,21,Bachelors,11,81,96,84,40,9.0,6,88,Urban,ML Engineer,136130,1 +33789,Female,39,Bachelors,5,87,44,38,42,9.0,7,3,Semi-Urban,Software Engineer,42780,0 +33790,Male,46,Bachelors,0,45,76,96,34,1.0,6,28,Urban,Software Engineer,58104,1 +33791,Male,24,Masters,8,51,32,86,86,5.0,2,85,Rural,HR Executive,133065,1 +33792,Male,32,Masters,9,19,51,6,49,4.0,2,41,Urban,HR Executive,74347,0 +33793,Male,53,Bachelors,18,51,51,21,24,3.0,4,25,Semi-Urban,Software Engineer,41618,0 +33794,Male,41,High School,16,66,95,73,39,4.0,4,42,Rural,Manager,138107,1 +33795,Male,48,Diploma,4,71,29,16,97,7.0,1,94,Semi-Urban,Data Analyst,107457,0 +33796,Female,50,High School,5,33,9,82,65,2.0,1,82,Urban,HR Executive,146012,0 +33797,Male,59,High School,7,47,36,46,59,7.0,1,4,Urban,Manager,148449,0 +33798,Male,23,Diploma,18,62,43,70,75,7.0,1,39,Urban,Data Analyst,23986,0 +33799,Male,21,Diploma,14,23,42,11,15,3.0,0,19,Urban,Data Analyst,131478,0 +33800,Male,22,Diploma,1,51,62,21,96,9.0,2,9,Urban,Manager,64595,0 +33801,Male,57,Bachelors,12,63,33,15,49,5.0,6,67,Rural,ML Engineer,138968,0 +33802,Female,51,Bachelors,19,98,54,1,61,3.0,7,23,Urban,Manager,127400,0 +33803,Male,31,Masters,15,84,44,75,5,6.0,2,53,Urban,ML Engineer,83254,1 +33804,Female,32,Diploma,14,7,58,84,38,6.0,6,46,Urban,Software Engineer,57797,0 +33805,Male,22,Diploma,14,24,29,91,24,9.0,7,47,Rural,HR Executive,96604,0 +33806,Female,40,Bachelors,19,28,10,29,80,6.0,0,94,Urban,ML Engineer,130727,0 +33807,Male,58,Masters,8,41,48,82,80,1.0,7,54,Rural,Software Engineer,49310,0 +33808,Male,32,Bachelors,13,59,44,4,26,1.0,5,5,Semi-Urban,ML Engineer,47993,0 +33809,Female,33,Bachelors,9,23,67,83,51,5.0,3,19,Urban,HR Executive,147342,0 +33810,Male,50,High School,7,14,37,41,15,5.0,1,80,Urban,Software Engineer,112352,0 +33811,Female,25,PhD,5,70,91,82,55,2.0,2,13,Urban,ML Engineer,22416,1 +33812,Female,50,High School,3,80,15,46,53,2.0,2,0,Urban,Manager,27292,0 +33813,Male,42,High School,17,76,79,59,49,6.0,2,8,Urban,ML Engineer,79584,0 +33814,Female,23,Diploma,5,25,53,93,43,9.0,5,82,Urban,Manager,80826,1 +33815,Female,56,Masters,12,29,0,1,76,6.0,3,99,Rural,HR Executive,118975,0 +33816,Male,21,High School,0,76,54,59,26,6.0,2,97,Urban,Software Engineer,92052,1 +33817,Male,22,Diploma,18,46,27,94,50,4.0,5,91,Urban,ML Engineer,51650,1 +33818,Male,35,High School,3,85,96,4,14,5.0,0,20,Urban,HR Executive,130588,0 +33819,Male,36,Masters,14,67,82,22,40,8.0,0,82,Semi-Urban,Manager,58014,1 +33820,Male,51,Bachelors,18,51,15,60,99,6.0,0,13,Urban,Manager,109270,0 +33821,Female,53,Masters,11,19,58,24,54,3.0,5,33,Urban,ML Engineer,54284,0 +33822,Female,27,Bachelors,11,6,57,56,42,3.0,1,88,Semi-Urban,HR Executive,65569,0 +33823,Female,34,Bachelors,7,18,78,7,29,4.0,0,36,Rural,Data Analyst,112990,0 +33824,Female,40,Diploma,14,90,86,53,3,2.0,5,15,Semi-Urban,Data Analyst,40615,1 +33825,Male,30,Diploma,3,80,49,31,99,7.0,6,29,Urban,Data Analyst,116616,0 +33826,Male,21,Masters,12,68,67,1,63,2.0,1,36,Urban,Manager,74391,0 +33827,Female,30,Masters,8,16,81,46,94,8.0,5,87,Semi-Urban,Manager,119266,0 +33828,Male,56,High School,8,38,53,22,61,0.0,1,56,Urban,ML Engineer,59405,0 +33829,Female,53,Bachelors,0,99,32,13,34,8.0,5,0,Urban,HR Executive,119646,0 +33830,Male,41,Masters,4,3,50,90,36,3.0,1,91,Rural,Data Analyst,47801,0 +33831,Male,45,Diploma,8,75,37,85,73,1.0,1,94,Urban,Data Analyst,34313,1 +33832,Male,50,Masters,15,29,99,3,85,6.0,5,72,Rural,Manager,56346,0 +33833,Male,37,Masters,8,18,4,6,62,6.0,6,59,Urban,HR Executive,122463,0 +33834,Male,58,High School,4,49,66,24,77,4.0,7,27,Urban,ML Engineer,82551,0 +33835,Male,35,Bachelors,13,16,89,28,6,9.0,7,85,Urban,HR Executive,54884,0 +33836,Male,55,High School,16,58,69,93,48,4.0,0,74,Urban,Manager,82724,1 +33837,Male,29,Masters,19,64,54,23,18,0.0,5,16,Urban,HR Executive,41294,0 +33838,Male,58,Bachelors,11,23,65,90,56,0.0,7,98,Urban,Manager,120018,1 +33839,Male,35,High School,19,29,94,31,26,7.0,7,40,Urban,HR Executive,115249,0 +33840,Female,56,PhD,13,59,73,18,5,4.0,7,54,Semi-Urban,HR Executive,44833,0 +33841,Male,32,High School,4,92,1,62,75,3.0,0,8,Urban,Manager,34571,0 +33842,Male,31,Diploma,19,3,64,54,2,7.0,0,12,Semi-Urban,ML Engineer,120293,0 +33843,Female,54,Bachelors,14,61,17,54,85,5.0,3,13,Semi-Urban,Data Analyst,40919,0 +33844,Female,31,Bachelors,18,89,71,71,26,9.0,4,11,Urban,HR Executive,32586,1 +33845,Male,35,Masters,8,90,57,76,46,5.0,6,87,Urban,Manager,77938,1 +33846,Male,41,Masters,15,11,52,56,53,0.0,5,63,Semi-Urban,Software Engineer,101622,0 +33847,Male,45,High School,15,87,49,27,37,7.0,4,77,Semi-Urban,ML Engineer,29464,1 +33848,Male,23,Bachelors,8,21,84,67,90,8.0,1,1,Urban,ML Engineer,62397,0 +33849,Female,44,Bachelors,5,48,91,24,90,5.0,7,28,Urban,Software Engineer,87024,0 +33850,Other,49,Bachelors,4,43,64,41,73,6.0,7,21,Urban,ML Engineer,149071,0 +33851,Female,53,Bachelors,19,62,52,31,43,3.0,0,42,Rural,Manager,106440,0 +33852,Other,47,Bachelors,7,9,62,0,39,9.0,3,23,Urban,HR Executive,85188,0 +33853,Male,33,Bachelors,4,31,82,74,13,2.0,1,10,Urban,Manager,67144,0 +33854,Female,21,Bachelors,0,0,36,90,77,2.0,2,37,Rural,Data Analyst,81825,0 +33855,Male,36,High School,19,4,13,78,28,5.0,6,86,Semi-Urban,HR Executive,73322,0 +33856,Male,21,Bachelors,10,71,87,1,13,0.0,4,75,Semi-Urban,Software Engineer,58764,0 +33857,Female,32,Bachelors,9,86,58,12,63,3.0,7,79,Semi-Urban,Manager,80616,0 +33858,Male,38,Diploma,6,70,69,76,17,5.0,7,41,Urban,HR Executive,70749,1 +33859,Male,41,High School,4,63,40,33,47,0.0,7,67,Urban,Data Analyst,69285,0 +33860,Female,46,Diploma,15,46,54,80,59,6.0,6,86,Urban,Software Engineer,92583,1 +33861,Male,40,Bachelors,15,24,79,86,8,9.0,2,62,Urban,ML Engineer,75519,1 +33862,Male,32,High School,15,54,65,20,8,8.0,0,41,Urban,ML Engineer,24880,0 +33863,Male,24,Masters,10,62,12,12,25,4.0,6,71,Urban,HR Executive,65168,0 +33864,Female,21,Bachelors,15,89,21,4,15,3.0,5,27,Urban,Software Engineer,107202,0 +33865,Male,22,Bachelors,1,77,98,10,62,5.0,6,14,Urban,Data Analyst,57264,0 +33866,Male,45,Diploma,4,2,23,12,15,0.0,5,88,Urban,Data Analyst,142850,0 +33867,Male,25,Bachelors,18,5,56,30,78,5.0,6,3,Urban,HR Executive,28132,0 +33868,Female,46,Bachelors,19,2,27,84,97,1.0,3,40,Semi-Urban,HR Executive,129799,0 +33869,Female,49,High School,2,56,84,83,44,5.0,1,94,Urban,HR Executive,96727,1 +33870,Male,51,Masters,12,72,43,84,46,5.0,1,8,Urban,HR Executive,28986,0 +33871,Male,39,Diploma,7,46,75,37,96,8.0,7,0,Rural,Data Analyst,36508,0 +33872,Male,22,Bachelors,7,32,25,89,87,9.0,3,36,Urban,HR Executive,62252,0 +33873,Male,40,High School,1,24,86,90,38,8.0,5,40,Rural,Data Analyst,78106,1 +33874,Male,25,Bachelors,13,1,34,0,27,2.0,1,16,Rural,Manager,30678,0 +33875,Male,38,Bachelors,13,67,70,15,24,2.0,7,27,Urban,Manager,111641,0 +33876,Female,32,High School,17,13,50,13,68,4.0,2,89,Rural,ML Engineer,21241,0 +33877,Female,27,Diploma,13,20,50,65,66,0.0,0,99,Urban,HR Executive,80499,0 +33878,Male,36,High School,19,15,88,79,3,0.0,0,42,Rural,Data Analyst,138815,0 +33879,Male,24,Diploma,1,19,4,74,88,2.0,6,35,Urban,Software Engineer,109916,0 +33880,Male,21,Masters,13,83,88,9,50,3.0,2,7,Urban,Manager,61541,0 +33881,Male,55,Masters,16,29,8,76,20,5.0,5,93,Urban,Software Engineer,27381,0 +33882,Male,35,Bachelors,2,88,39,48,28,7.0,4,20,Semi-Urban,ML Engineer,92471,0 +33883,Male,33,Bachelors,3,15,4,3,40,1.0,0,95,Semi-Urban,HR Executive,73213,0 +33884,Male,21,Bachelors,8,35,33,81,96,1.0,5,17,Urban,Data Analyst,109404,0 +33885,Male,44,Bachelors,4,4,43,22,25,0.0,7,19,Urban,Data Analyst,48225,0 +33886,Female,29,Bachelors,2,95,61,82,39,3.0,3,69,Semi-Urban,Manager,111920,1 +33887,Male,36,Bachelors,17,41,27,39,49,2.0,6,61,Rural,HR Executive,24487,0 +33888,Male,56,Bachelors,0,97,14,35,12,2.0,1,21,Rural,Data Analyst,104953,0 +33889,Male,21,Bachelors,13,25,96,5,87,9.0,0,65,Semi-Urban,Manager,103307,0 +33890,Female,55,PhD,0,66,25,79,31,1.0,2,80,Urban,HR Executive,59101,1 +33891,Male,38,Diploma,13,36,78,85,92,7.0,3,65,Urban,Data Analyst,133411,1 +33892,Male,57,High School,6,77,66,13,10,0.0,2,91,Urban,Software Engineer,24875,1 +33893,Female,53,Masters,15,55,95,26,54,8.0,5,89,Urban,HR Executive,109147,1 +33894,Female,35,Masters,13,5,26,11,58,7.0,4,32,Rural,HR Executive,83419,0 +33895,Female,49,Masters,13,62,84,84,38,5.0,3,67,Semi-Urban,Software Engineer,98865,1 +33896,Male,24,Bachelors,4,91,88,25,46,0.0,5,89,Semi-Urban,ML Engineer,73200,1 +33897,Female,30,Masters,10,18,31,51,14,5.0,3,76,Rural,Software Engineer,142103,0 +33898,Female,35,Bachelors,4,77,62,64,13,2.0,6,34,Semi-Urban,ML Engineer,147508,0 +33899,Female,47,PhD,14,81,62,54,41,1.0,6,37,Semi-Urban,Manager,92649,0 +33900,Male,55,PhD,16,32,12,79,57,0.0,0,83,Urban,Software Engineer,42482,0 +33901,Male,30,Bachelors,16,71,1,78,44,6.0,2,7,Semi-Urban,ML Engineer,25822,0 +33902,Female,34,Bachelors,3,19,1,34,96,1.0,5,77,Urban,Software Engineer,107832,0 +33903,Female,40,Masters,4,95,78,54,62,0.0,7,72,Semi-Urban,Manager,85049,1 +33904,Female,56,Bachelors,8,54,97,12,31,2.0,7,13,Urban,ML Engineer,128132,0 +33905,Female,48,Masters,0,96,25,24,50,9.0,2,46,Urban,Data Analyst,111679,0 +33906,Male,34,Bachelors,3,65,69,76,32,5.0,1,21,Semi-Urban,Software Engineer,112429,0 +33907,Male,56,High School,0,56,34,60,16,0.0,4,57,Rural,ML Engineer,32011,0 +33908,Female,37,Diploma,3,69,11,45,64,7.0,5,46,Semi-Urban,ML Engineer,75370,0 +33909,Female,42,High School,7,90,71,13,59,4.0,3,5,Urban,Manager,78776,0 +33910,Female,38,Diploma,14,30,64,46,8,3.0,0,8,Urban,HR Executive,36164,0 +33911,Female,29,Masters,7,40,64,42,84,1.0,2,99,Urban,Manager,109033,1 +33912,Male,30,Masters,3,32,14,42,18,0.0,5,13,Urban,ML Engineer,76117,0 +33913,Male,37,Bachelors,2,31,3,71,0,8.0,2,46,Rural,HR Executive,146880,0 +33914,Female,23,Masters,8,67,86,30,75,0.0,7,84,Urban,HR Executive,47882,1 +33915,Male,46,Masters,15,34,13,13,0,0.0,7,26,Urban,Manager,20283,0 +33916,Female,31,High School,4,52,84,73,69,9.0,4,37,Urban,ML Engineer,50043,1 +33917,Female,34,Bachelors,8,92,2,98,47,7.0,3,51,Urban,Software Engineer,125342,1 +33918,Male,33,Bachelors,11,18,66,89,45,3.0,4,91,Rural,HR Executive,104603,1 +33919,Female,33,Masters,18,13,43,92,44,5.0,2,37,Semi-Urban,HR Executive,44369,0 +33920,Male,53,High School,18,40,55,15,38,6.0,1,6,Semi-Urban,Manager,134494,0 +33921,Female,38,Bachelors,10,19,40,79,70,7.0,6,34,Rural,HR Executive,73688,0 +33922,Male,31,High School,6,64,16,51,93,1.0,2,52,Rural,ML Engineer,113350,0 +33923,Female,22,Diploma,18,60,48,22,58,8.0,5,13,Urban,Software Engineer,29140,0 +33924,Female,50,Masters,14,27,17,67,63,7.0,7,56,Urban,Software Engineer,146508,0 +33925,Male,36,Masters,2,73,26,90,2,7.0,1,52,Rural,Data Analyst,48052,1 +33926,Female,45,Masters,4,80,21,8,90,5.0,1,10,Urban,Software Engineer,78028,0 +33927,Female,55,Diploma,8,54,89,13,62,2.0,6,77,Semi-Urban,HR Executive,91169,0 +33928,Female,27,Bachelors,13,2,53,0,73,1.0,6,83,Semi-Urban,Manager,148148,0 +33929,Other,34,High School,0,37,1,74,3,4.0,3,73,Semi-Urban,ML Engineer,102835,0 +33930,Male,37,High School,6,46,60,59,36,8.0,1,4,Urban,Software Engineer,61582,0 +33931,Male,52,Bachelors,3,76,94,2,71,5.0,7,47,Rural,ML Engineer,43429,0 +33932,Male,43,Bachelors,0,39,54,31,31,2.0,6,95,Urban,Software Engineer,30488,0 +33933,Other,31,Diploma,3,24,56,15,10,6.0,0,67,Semi-Urban,Software Engineer,20565,0 +33934,Male,28,Bachelors,18,46,38,24,92,5.0,3,4,Urban,Data Analyst,117736,0 +33935,Male,56,Diploma,3,59,99,48,43,2.0,1,55,Urban,Software Engineer,53902,1 +33936,Male,33,Masters,6,9,67,35,47,8.0,0,78,Urban,HR Executive,58065,0 +33937,Male,58,Bachelors,6,85,92,48,87,1.0,6,98,Urban,Manager,83693,1 +33938,Female,23,Diploma,10,44,4,17,81,9.0,7,84,Urban,HR Executive,29698,0 +33939,Male,37,High School,11,79,91,57,26,4.0,1,9,Urban,Manager,112242,1 +33940,Female,47,Bachelors,9,67,81,41,71,7.0,5,13,Urban,Manager,113363,0 +33941,Male,39,Bachelors,12,74,14,77,17,8.0,3,98,Urban,Software Engineer,84191,1 +33942,Female,48,Masters,11,32,47,28,74,1.0,1,85,Urban,Data Analyst,115506,0 +33943,Male,50,Bachelors,15,43,77,33,15,1.0,1,15,Urban,Manager,44210,0 +33944,Male,22,Masters,17,80,32,21,4,1.0,2,46,Urban,Software Engineer,68100,0 +33945,Male,33,Bachelors,18,40,57,2,3,0.0,7,93,Urban,Software Engineer,81985,0 +33946,Male,37,High School,7,94,96,80,86,9.0,2,95,Urban,Software Engineer,81101,1 +33947,Male,38,Bachelors,16,65,28,77,43,7.0,4,81,Urban,HR Executive,116872,1 +33948,Male,54,Masters,9,71,34,25,74,1.0,5,61,Urban,Manager,97453,0 +33949,Male,31,Bachelors,10,16,93,26,67,2.0,4,25,Urban,HR Executive,123737,0 +33950,Male,40,High School,1,88,97,84,61,3.0,3,40,Semi-Urban,Data Analyst,70759,1 +33951,Female,51,High School,17,30,93,13,85,8.0,0,36,Urban,HR Executive,79469,0 +33952,Male,59,Bachelors,15,40,53,91,21,4.0,3,31,Semi-Urban,ML Engineer,46924,0 +33953,Female,29,High School,11,55,69,86,90,5.0,2,61,Rural,HR Executive,105086,1 +33954,Other,49,Diploma,2,35,87,88,98,3.0,4,53,Urban,ML Engineer,72297,1 +33955,Male,40,High School,7,83,56,96,55,5.0,1,87,Urban,Data Analyst,85324,1 +33956,Male,28,Bachelors,2,37,79,85,49,3.0,1,63,Rural,Software Engineer,101032,1 +33957,Male,54,High School,7,40,38,0,26,7.0,7,17,Semi-Urban,HR Executive,54237,0 +33958,Male,21,Masters,1,9,33,63,87,2.0,6,69,Semi-Urban,Software Engineer,139133,0 +33959,Female,51,Bachelors,13,10,15,6,77,7.0,3,5,Rural,Manager,71328,0 +33960,Male,52,Masters,6,31,39,94,19,9.0,7,29,Urban,Data Analyst,131242,0 +33961,Male,21,Bachelors,1,5,7,52,50,3.0,3,5,Semi-Urban,Data Analyst,54907,0 +33962,Male,54,Bachelors,14,59,52,32,55,2.0,2,89,Urban,Data Analyst,119583,0 +33963,Female,48,Diploma,18,93,63,67,17,4.0,5,98,Urban,Data Analyst,25656,1 +33964,Female,50,Bachelors,10,13,22,95,91,4.0,4,23,Rural,ML Engineer,124641,0 +33965,Other,32,High School,18,0,77,97,19,3.0,0,8,Urban,Data Analyst,65438,0 +33966,Female,47,Diploma,7,30,55,73,73,5.0,0,61,Urban,Manager,109030,0 +33967,Male,30,Diploma,12,80,69,46,69,1.0,6,42,Rural,Data Analyst,147876,1 +33968,Male,21,Diploma,15,12,61,89,40,3.0,6,2,Urban,Data Analyst,107326,0 +33969,Male,29,Masters,15,80,58,49,8,9.0,0,85,Urban,HR Executive,63628,1 +33970,Male,33,Bachelors,18,57,84,96,97,9.0,5,37,Rural,HR Executive,59637,1 +33971,Male,56,Bachelors,9,77,65,59,97,5.0,3,86,Rural,Data Analyst,32821,1 +33972,Male,36,High School,9,91,41,63,51,0.0,4,3,Urban,HR Executive,54088,0 +33973,Male,44,High School,6,54,47,9,67,2.0,3,28,Semi-Urban,ML Engineer,71429,0 +33974,Male,44,Bachelors,14,85,38,98,3,7.0,3,23,Urban,Data Analyst,107508,1 +33975,Female,26,High School,15,27,97,57,59,3.0,3,91,Urban,Data Analyst,60540,1 +33976,Female,50,Masters,12,99,11,58,57,0.0,5,68,Semi-Urban,Data Analyst,125779,0 +33977,Male,35,Masters,12,60,21,27,41,4.0,3,63,Urban,Software Engineer,32018,0 +33978,Male,29,Diploma,13,14,97,68,55,9.0,3,76,Urban,HR Executive,96362,1 +33979,Male,38,Bachelors,1,6,13,2,41,6.0,3,48,Rural,HR Executive,45607,0 +33980,Female,56,Bachelors,8,31,95,4,75,3.0,7,55,Urban,ML Engineer,31984,0 +33981,Other,58,Masters,1,69,21,79,64,5.0,6,26,Urban,HR Executive,22993,0 +33982,Male,54,Diploma,13,46,1,7,83,0.0,2,80,Semi-Urban,HR Executive,131184,0 +33983,Male,28,Bachelors,9,71,73,41,16,5.0,1,62,Semi-Urban,ML Engineer,147339,1 +33984,Male,34,Diploma,4,2,64,46,5,4.0,4,12,Urban,HR Executive,76548,0 +33985,Male,34,High School,1,20,41,3,26,4.0,3,44,Urban,HR Executive,110243,0 +33986,Female,40,Masters,12,86,70,28,80,3.0,4,24,Urban,ML Engineer,107525,0 +33987,Male,49,Bachelors,13,17,43,55,18,5.0,3,37,Urban,Manager,75224,0 +33988,Other,43,Masters,18,15,56,97,90,7.0,2,69,Rural,Software Engineer,139313,0 +33989,Male,57,Diploma,13,71,26,14,28,2.0,4,40,Urban,HR Executive,137663,0 +33990,Female,43,Diploma,6,97,34,2,98,3.0,5,14,Rural,ML Engineer,144978,0 +33991,Male,22,Bachelors,11,12,26,85,90,3.0,5,32,Urban,Data Analyst,99574,0 +33992,Male,57,PhD,15,42,69,3,34,9.0,3,33,Urban,Manager,68554,0 +33993,Female,33,Masters,19,71,73,88,33,2.0,2,99,Rural,HR Executive,51226,1 +33994,Female,43,Bachelors,18,24,14,18,71,9.0,3,34,Rural,Manager,44532,0 +33995,Female,58,Diploma,10,22,70,71,12,0.0,5,35,Urban,Software Engineer,50876,0 +33996,Female,40,Diploma,7,58,21,9,6,2.0,1,86,Urban,Software Engineer,32795,0 +33997,Female,22,High School,5,33,20,65,98,2.0,1,94,Urban,HR Executive,124435,0 +33998,Male,56,Diploma,0,80,49,48,34,7.0,1,26,Semi-Urban,Data Analyst,93976,0 +33999,Female,37,Bachelors,14,70,88,9,68,0.0,7,56,Urban,Data Analyst,52261,0 +34000,Female,29,Bachelors,11,42,71,85,42,6.0,0,59,Urban,HR Executive,98941,1 +34001,Male,58,Bachelors,9,24,0,25,0,9.0,3,80,Urban,Data Analyst,88833,0 +34002,Male,33,Bachelors,2,40,46,32,38,9.0,7,43,Urban,Software Engineer,74364,0 +34003,Female,57,Diploma,3,54,53,83,19,9.0,7,5,Rural,Manager,44131,0 +34004,Female,55,Bachelors,11,43,86,22,89,7.0,6,80,Rural,Software Engineer,95092,0 +34005,Male,29,Bachelors,0,30,18,79,78,3.0,3,15,Urban,Manager,125884,0 +34006,Female,50,High School,13,84,63,49,70,7.0,0,27,Urban,HR Executive,81980,0 +34007,Female,25,High School,2,78,71,9,54,6.0,5,78,Urban,ML Engineer,78308,0 +34008,Male,40,High School,1,10,11,90,37,4.0,0,85,Rural,HR Executive,44301,0 +34009,Female,56,High School,19,28,14,74,59,7.0,7,58,Semi-Urban,Data Analyst,21314,0 +34010,Male,49,High School,4,81,52,77,71,5.0,4,24,Semi-Urban,HR Executive,144123,0 +34011,Male,43,High School,12,0,38,99,69,4.0,6,10,Urban,Software Engineer,137179,0 +34012,Male,50,High School,2,92,30,72,19,6.0,2,44,Rural,HR Executive,39891,1 +34013,Female,29,Bachelors,17,54,51,27,52,2.0,6,44,Semi-Urban,Manager,130487,0 +34014,Male,27,Diploma,13,45,5,81,13,4.0,7,39,Urban,Software Engineer,38334,0 +34015,Female,31,Bachelors,18,68,77,24,93,7.0,5,89,Urban,Manager,112336,1 +34016,Male,33,Diploma,18,59,12,25,6,1.0,0,48,Urban,Manager,91093,0 +34017,Female,46,Bachelors,9,61,57,13,62,5.0,3,35,Semi-Urban,Software Engineer,145809,0 +34018,Female,30,High School,18,66,74,21,92,7.0,7,59,Urban,Manager,67748,0 +34019,Female,41,Bachelors,19,49,18,70,6,5.0,7,61,Urban,ML Engineer,50564,0 +34020,Female,37,Masters,19,21,32,68,47,2.0,2,25,Semi-Urban,HR Executive,85837,0 +34021,Female,26,Bachelors,6,53,52,65,62,6.0,4,70,Urban,Data Analyst,100654,0 +34022,Male,38,Bachelors,6,45,31,99,4,0.0,3,98,Urban,Software Engineer,125408,1 +34023,Male,28,Diploma,12,49,95,85,37,5.0,6,94,Urban,Software Engineer,100219,1 +34024,Male,47,Diploma,14,79,79,45,65,7.0,6,3,Urban,HR Executive,52997,0 +34025,Female,43,High School,2,95,24,16,92,0.0,5,63,Urban,Data Analyst,25453,0 +34026,Male,56,Bachelors,14,89,33,22,55,6.0,6,78,Urban,Software Engineer,61468,0 +34027,Male,53,Masters,4,4,21,89,2,1.0,7,59,Semi-Urban,Manager,115390,0 +34028,Female,24,Bachelors,14,74,83,6,83,1.0,1,44,Semi-Urban,Software Engineer,77558,0 +34029,Female,51,Masters,15,88,9,87,93,0.0,4,47,Semi-Urban,HR Executive,115506,0 +34030,Female,58,High School,18,12,38,42,17,8.0,6,10,Urban,Software Engineer,33650,0 +34031,Male,30,Bachelors,8,72,24,44,24,7.0,1,39,Urban,HR Executive,130043,0 +34032,Male,31,PhD,0,26,53,83,83,9.0,2,90,Rural,HR Executive,48609,1 +34033,Male,37,Masters,2,5,12,79,77,8.0,1,59,Rural,Software Engineer,49257,0 +34034,Male,37,PhD,15,76,10,3,7,2.0,6,25,Urban,ML Engineer,102646,0 +34035,Male,32,Masters,0,63,84,89,58,0.0,7,49,Rural,Manager,108958,1 +34036,Male,22,Bachelors,18,91,50,57,48,2.0,7,58,Rural,ML Engineer,22407,1 +34037,Male,25,Masters,3,52,97,85,72,3.0,1,8,Urban,ML Engineer,109201,1 +34038,Male,31,High School,17,61,65,66,25,3.0,2,56,Rural,ML Engineer,132947,1 +34039,Male,54,PhD,6,64,84,88,72,5.0,3,71,Urban,HR Executive,88323,1 +34040,Male,47,Diploma,5,37,6,13,26,0.0,3,1,Urban,Software Engineer,134738,0 +34041,Female,26,Bachelors,7,0,33,65,43,1.0,7,63,Rural,Data Analyst,137822,0 +34042,Female,43,Bachelors,11,70,90,42,3,6.0,2,17,Urban,Data Analyst,138616,0 +34043,Female,35,PhD,18,37,59,9,76,6.0,5,70,Urban,Data Analyst,24811,0 +34044,Male,47,Diploma,6,32,77,26,30,5.0,5,91,Rural,Data Analyst,143338,0 +34045,Other,47,Masters,7,14,78,5,16,3.0,2,13,Urban,Data Analyst,126066,0 +34046,Female,37,Bachelors,11,75,7,55,54,3.0,0,98,Urban,ML Engineer,110244,0 +34047,Male,27,Masters,6,1,72,21,40,7.0,3,42,Urban,Software Engineer,29923,0 +34048,Male,26,Bachelors,6,67,85,95,56,3.0,6,22,Urban,Data Analyst,115471,1 +34049,Male,55,Bachelors,10,95,23,31,84,7.0,1,23,Urban,ML Engineer,102461,0 +34050,Female,56,Bachelors,8,81,79,40,67,6.0,4,14,Urban,Software Engineer,57818,0 +34051,Male,58,Bachelors,18,90,71,55,25,5.0,4,2,Urban,Software Engineer,125317,0 +34052,Female,37,Bachelors,3,19,4,62,50,3.0,4,2,Rural,Manager,68334,0 +34053,Male,48,Bachelors,15,31,64,11,97,7.0,7,93,Urban,Data Analyst,44235,0 +34054,Other,21,High School,15,75,57,29,13,4.0,7,96,Urban,HR Executive,130386,1 +34055,Female,41,Bachelors,10,50,34,35,42,2.0,4,19,Rural,Software Engineer,68073,0 +34056,Other,56,PhD,12,19,53,97,78,8.0,5,43,Rural,Manager,93381,0 +34057,Male,51,Bachelors,16,24,71,94,50,4.0,4,53,Urban,Software Engineer,20255,1 +34058,Male,42,Masters,8,21,22,50,64,4.0,1,2,Urban,Software Engineer,76284,0 +34059,Female,30,High School,5,5,14,72,38,2.0,3,66,Urban,HR Executive,92526,0 +34060,Female,48,Bachelors,19,68,73,31,56,0.0,6,12,Urban,Software Engineer,26579,0 +34061,Male,47,Diploma,5,36,84,79,59,4.0,3,45,Urban,HR Executive,34152,1 +34062,Female,33,Diploma,18,93,13,2,87,7.0,6,54,Urban,Data Analyst,120106,0 +34063,Male,21,Masters,9,95,9,79,81,3.0,3,1,Rural,Software Engineer,21291,0 +34064,Male,42,Bachelors,10,35,70,95,23,2.0,2,37,Urban,Software Engineer,20165,1 +34065,Male,43,Bachelors,15,84,25,41,73,6.0,0,21,Urban,ML Engineer,35611,0 +34066,Female,54,Bachelors,10,21,97,84,1,7.0,4,11,Urban,Software Engineer,86342,0 +34067,Male,31,Diploma,7,31,67,74,16,0.0,7,20,Urban,Software Engineer,141771,0 +34068,Female,42,Diploma,11,39,47,51,5,6.0,4,75,Urban,Software Engineer,74309,0 +34069,Male,25,High School,5,95,75,96,71,4.0,5,59,Semi-Urban,Data Analyst,29383,1 +34070,Female,30,Masters,18,80,72,85,32,9.0,6,50,Semi-Urban,Manager,54400,1 +34071,Female,29,Bachelors,12,49,54,67,56,1.0,4,52,Urban,HR Executive,146640,0 +34072,Male,37,Bachelors,13,98,62,58,47,8.0,4,80,Semi-Urban,Software Engineer,38278,1 +34073,Male,36,Masters,16,51,56,77,66,4.0,2,10,Urban,Software Engineer,112263,0 +34074,Female,30,Diploma,3,44,93,57,28,2.0,4,89,Urban,Software Engineer,90816,1 +34075,Female,41,Bachelors,3,49,18,26,6,5.0,5,21,Semi-Urban,HR Executive,34911,0 +34076,Male,22,Bachelors,8,17,40,3,92,3.0,2,91,Urban,Software Engineer,51172,0 +34077,Male,56,Bachelors,19,4,4,44,83,7.0,4,50,Semi-Urban,HR Executive,34875,0 +34078,Male,53,Diploma,9,47,13,31,77,1.0,2,13,Semi-Urban,Software Engineer,57401,0 +34079,Male,29,Bachelors,10,54,83,41,16,1.0,1,36,Urban,Data Analyst,136679,0 +34080,Male,37,Masters,13,63,27,54,79,3.0,7,71,Rural,ML Engineer,81056,0 +34081,Female,53,Bachelors,14,57,22,35,0,9.0,2,92,Urban,ML Engineer,110882,0 +34082,Male,32,Diploma,6,25,57,42,18,8.0,4,6,Urban,Data Analyst,53727,0 +34083,Male,33,Masters,8,53,39,59,64,1.0,4,31,Semi-Urban,Software Engineer,36305,0 +34084,Female,21,High School,5,97,35,87,47,2.0,5,50,Urban,Data Analyst,122863,1 +34085,Male,42,High School,13,90,27,41,29,3.0,5,4,Rural,ML Engineer,115925,0 +34086,Female,30,Diploma,0,19,84,66,16,9.0,2,77,Semi-Urban,HR Executive,70962,1 +34087,Female,58,Diploma,1,13,63,74,39,1.0,1,1,Rural,HR Executive,116066,0 +34088,Male,52,Diploma,19,33,83,11,9,5.0,5,95,Urban,ML Engineer,48139,0 +34089,Male,33,Diploma,16,7,6,27,72,3.0,2,5,Urban,Software Engineer,123951,0 +34090,Male,21,Diploma,0,92,72,51,5,4.0,3,71,Urban,Manager,120434,1 +34091,Male,44,Masters,5,39,45,37,4,0.0,7,2,Semi-Urban,HR Executive,70275,0 +34092,Male,56,Diploma,15,37,72,33,43,5.0,6,3,Urban,HR Executive,77983,0 +34093,Other,42,Diploma,1,38,30,41,7,9.0,5,36,Urban,Data Analyst,132834,0 +34094,Male,32,Bachelors,12,65,37,45,22,6.0,5,50,Urban,ML Engineer,120184,0 +34095,Female,38,Bachelors,15,50,3,87,7,9.0,3,37,Semi-Urban,Manager,51952,0 +34096,Male,41,Masters,18,32,25,64,6,5.0,7,26,Semi-Urban,ML Engineer,68782,0 +34097,Female,50,Masters,10,51,97,47,62,7.0,3,91,Urban,HR Executive,41598,1 +34098,Female,24,Bachelors,2,68,70,58,9,5.0,1,63,Rural,Manager,92787,1 +34099,Female,23,Bachelors,0,21,53,31,97,8.0,1,66,Urban,Data Analyst,72302,0 +34100,Male,22,Masters,0,27,97,13,57,7.0,2,29,Urban,ML Engineer,100236,0 +34101,Male,24,Bachelors,18,3,94,30,19,4.0,7,61,Rural,Manager,41354,0 +34102,Male,24,Masters,0,17,95,46,10,6.0,7,77,Semi-Urban,Software Engineer,28833,1 +34103,Female,28,Bachelors,14,21,93,46,16,2.0,2,17,Rural,ML Engineer,132393,0 +34104,Female,30,Diploma,11,81,18,68,41,8.0,2,55,Urban,ML Engineer,24631,0 +34105,Male,49,Diploma,1,49,38,90,57,6.0,5,97,Urban,Software Engineer,36665,1 +34106,Female,53,Bachelors,3,69,2,6,35,5.0,3,80,Urban,Data Analyst,69612,0 +34107,Female,50,Bachelors,10,25,20,40,79,9.0,2,73,Rural,Manager,106120,0 +34108,Male,42,Bachelors,19,80,10,79,87,5.0,7,77,Urban,ML Engineer,72880,1 +34109,Male,48,Diploma,19,1,47,61,74,2.0,2,49,Semi-Urban,HR Executive,44756,0 +34110,Female,49,Bachelors,5,81,32,24,23,2.0,2,50,Urban,Manager,30108,0 +34111,Male,57,Diploma,15,9,56,21,2,7.0,6,17,Semi-Urban,HR Executive,112449,0 +34112,Female,33,Diploma,10,9,4,37,4,3.0,5,37,Semi-Urban,HR Executive,44800,0 +34113,Female,26,Bachelors,18,82,37,69,32,7.0,2,51,Rural,Manager,20382,0 +34114,Male,49,Diploma,19,59,81,58,40,9.0,0,39,Urban,Manager,117465,1 +34115,Female,35,High School,15,11,31,35,24,2.0,3,5,Urban,Data Analyst,65954,0 +34116,Male,23,Masters,17,50,61,99,46,4.0,3,25,Rural,Software Engineer,30807,1 +34117,Female,23,Bachelors,13,37,91,87,34,6.0,0,60,Urban,ML Engineer,112740,1 +34118,Male,30,High School,14,36,87,18,16,9.0,1,98,Rural,ML Engineer,109777,1 +34119,Male,52,Bachelors,1,60,54,69,10,0.0,5,90,Urban,HR Executive,54576,1 +34120,Female,22,Bachelors,17,79,25,3,86,5.0,2,52,Urban,Data Analyst,135228,0 +34121,Male,37,Bachelors,8,66,19,76,59,1.0,7,14,Rural,ML Engineer,40560,0 +34122,Female,42,Bachelors,3,30,43,43,25,4.0,4,8,Urban,HR Executive,114862,0 +34123,Male,58,Bachelors,17,64,87,39,38,9.0,7,73,Urban,HR Executive,80547,1 +34124,Male,42,High School,18,50,71,42,46,3.0,4,12,Urban,HR Executive,61828,0 +34125,Female,25,Diploma,4,59,47,20,20,5.0,4,31,Urban,HR Executive,36774,0 +34126,Male,47,Diploma,9,59,68,87,9,5.0,6,90,Urban,Software Engineer,40881,1 +34127,Other,25,Masters,5,31,59,57,32,9.0,7,45,Urban,Software Engineer,81687,0 +34128,Male,53,Masters,0,94,11,82,17,2.0,3,46,Urban,Data Analyst,125990,0 +34129,Male,53,Masters,6,5,53,7,73,0.0,3,36,Urban,Data Analyst,56486,0 +34130,Male,46,Bachelors,7,43,83,46,74,2.0,6,2,Urban,Data Analyst,147303,0 +34131,Female,42,Masters,3,64,40,90,61,5.0,1,88,Urban,ML Engineer,106322,1 +34132,Male,37,High School,5,56,47,83,82,8.0,4,76,Urban,Manager,34263,1 +34133,Male,47,Masters,5,72,21,24,53,8.0,0,88,Urban,Software Engineer,67156,0 +34134,Female,22,Bachelors,12,73,35,57,39,0.0,7,21,Urban,ML Engineer,144815,0 +34135,Male,40,Masters,0,12,77,88,1,8.0,1,85,Rural,ML Engineer,45240,1 +34136,Male,57,Masters,12,70,67,56,83,2.0,0,87,Urban,Data Analyst,123840,1 +34137,Male,59,Masters,15,24,80,24,76,4.0,2,14,Urban,Data Analyst,83135,0 +34138,Male,35,High School,4,25,29,55,32,3.0,7,97,Semi-Urban,ML Engineer,100309,0 +34139,Male,51,Bachelors,18,38,91,23,2,7.0,1,11,Urban,Manager,35783,0 +34140,Male,48,Diploma,11,10,51,76,56,3.0,5,22,Semi-Urban,HR Executive,39638,0 +34141,Male,27,Bachelors,18,66,47,90,19,5.0,5,34,Urban,Data Analyst,57374,1 +34142,Male,59,Bachelors,6,69,31,19,59,4.0,5,18,Urban,Manager,77246,0 +34143,Male,21,Bachelors,6,86,8,10,66,4.0,4,98,Urban,HR Executive,118865,0 +34144,Female,27,Bachelors,0,96,3,59,40,1.0,4,3,Rural,Manager,135396,0 +34145,Female,27,Diploma,18,54,27,60,72,8.0,7,23,Rural,Software Engineer,74953,0 +34146,Male,29,Masters,1,72,33,2,6,0.0,5,15,Semi-Urban,ML Engineer,61062,0 +34147,Female,31,Diploma,5,95,77,26,64,3.0,2,83,Urban,Data Analyst,73838,1 +34148,Female,43,Bachelors,6,3,18,12,90,0.0,6,7,Urban,Software Engineer,139738,0 +34149,Other,58,Diploma,4,17,10,94,81,6.0,7,24,Semi-Urban,ML Engineer,33708,0 +34150,Male,38,High School,3,54,12,54,61,6.0,5,21,Semi-Urban,HR Executive,138048,0 +34151,Female,36,Bachelors,14,83,94,5,50,9.0,4,78,Urban,HR Executive,60700,1 +34152,Male,25,Diploma,6,40,71,65,68,5.0,6,18,Rural,ML Engineer,68924,0 +34153,Female,45,Diploma,4,18,25,31,35,8.0,4,74,Urban,ML Engineer,51337,0 +34154,Male,25,Bachelors,18,57,45,95,12,6.0,2,47,Semi-Urban,Manager,64664,1 +34155,Male,50,Diploma,7,52,15,42,73,2.0,3,56,Urban,ML Engineer,111292,0 +34156,Male,45,Diploma,1,66,99,79,68,7.0,3,69,Urban,Manager,112373,1 +34157,Male,24,Bachelors,19,54,26,38,26,1.0,1,13,Urban,ML Engineer,140541,0 +34158,Male,39,Bachelors,6,5,78,38,68,5.0,2,71,Urban,Manager,136466,0 +34159,Male,52,Bachelors,14,4,78,13,27,8.0,7,42,Semi-Urban,Software Engineer,69039,0 +34160,Male,32,Bachelors,6,18,74,40,59,8.0,6,98,Rural,HR Executive,49175,0 +34161,Female,27,Bachelors,6,82,13,13,96,9.0,4,21,Rural,Data Analyst,116223,0 +34162,Female,56,Bachelors,17,70,51,93,78,5.0,0,60,Semi-Urban,ML Engineer,117960,1 +34163,Male,26,High School,15,37,64,19,17,8.0,6,91,Rural,ML Engineer,44063,0 +34164,Male,37,Bachelors,14,67,20,90,57,9.0,6,94,Urban,Software Engineer,36515,1 +34165,Male,34,High School,8,70,4,57,51,0.0,2,99,Semi-Urban,Manager,120149,0 +34166,Male,22,PhD,4,85,63,48,21,7.0,0,70,Urban,ML Engineer,133278,1 +34167,Male,32,Masters,2,4,11,79,46,9.0,1,72,Urban,HR Executive,85951,0 +34168,Male,31,Masters,16,68,39,56,56,2.0,1,61,Urban,Data Analyst,70596,0 +34169,Female,53,Diploma,8,24,52,39,18,0.0,6,9,Urban,Data Analyst,89856,0 +34170,Male,22,Diploma,8,81,22,40,20,7.0,4,30,Semi-Urban,HR Executive,146915,0 +34171,Male,44,Bachelors,13,75,56,48,34,2.0,6,60,Rural,Data Analyst,48124,1 +34172,Male,36,Bachelors,0,41,78,55,86,3.0,5,82,Rural,ML Engineer,97477,1 +34173,Male,23,Masters,18,95,14,26,48,9.0,0,53,Semi-Urban,Software Engineer,99942,0 +34174,Female,29,Masters,9,73,26,25,38,8.0,2,34,Semi-Urban,ML Engineer,60531,0 +34175,Male,25,Bachelors,16,27,9,31,41,4.0,1,7,Rural,Data Analyst,139936,0 +34176,Male,21,Diploma,11,69,64,86,31,6.0,1,33,Urban,ML Engineer,57499,1 +34177,Female,36,Diploma,16,81,42,98,37,6.0,2,8,Rural,HR Executive,71509,0 +34178,Male,45,Masters,11,21,57,12,51,6.0,0,76,Semi-Urban,Data Analyst,103201,0 +34179,Male,45,High School,3,54,32,38,87,1.0,6,85,Urban,Manager,62521,0 +34180,Male,39,Diploma,13,33,71,46,9,9.0,0,27,Semi-Urban,HR Executive,124332,0 +34181,Male,38,Diploma,14,97,68,97,50,9.0,3,1,Semi-Urban,Software Engineer,116451,1 +34182,Male,47,Bachelors,13,63,53,26,65,0.0,6,7,Semi-Urban,Software Engineer,144174,0 +34183,Female,29,Bachelors,18,29,51,23,74,2.0,2,90,Rural,Data Analyst,116084,0 +34184,Male,58,Masters,10,76,74,47,81,6.0,1,81,Urban,Manager,43618,1 +34185,Male,41,Bachelors,15,27,93,10,75,2.0,3,38,Semi-Urban,Manager,62602,0 +34186,Female,25,Bachelors,6,33,72,57,14,7.0,0,76,Urban,HR Executive,43717,0 +34187,Male,50,Masters,16,41,58,44,71,6.0,0,45,Urban,Software Engineer,79321,0 +34188,Other,28,High School,1,31,85,7,79,1.0,7,89,Urban,Data Analyst,31391,0 +34189,Male,48,PhD,4,28,82,83,7,6.0,1,16,Urban,HR Executive,76106,0 +34190,Female,37,Bachelors,0,79,57,25,28,8.0,1,28,Urban,Data Analyst,52528,0 +34191,Female,57,Diploma,13,36,74,99,19,8.0,0,89,Rural,Software Engineer,122950,1 +34192,Female,41,Bachelors,0,64,63,18,59,9.0,0,45,Urban,ML Engineer,107102,0 +34193,Male,38,Bachelors,3,94,8,29,49,5.0,1,59,Semi-Urban,Software Engineer,62434,0 +34194,Male,30,Bachelors,16,48,35,39,90,5.0,7,47,Urban,Software Engineer,146960,0 +34195,Male,26,Bachelors,17,13,26,64,8,5.0,7,1,Rural,HR Executive,126179,0 +34196,Female,57,Masters,17,53,24,8,95,8.0,7,28,Urban,Data Analyst,34228,0 +34197,Male,43,Bachelors,14,17,42,95,88,8.0,6,75,Urban,Software Engineer,121261,0 +34198,Female,38,Masters,0,87,39,12,29,9.0,6,55,Rural,HR Executive,73126,0 +34199,Male,34,PhD,19,72,4,48,50,9.0,4,99,Urban,HR Executive,128527,0 +34200,Male,52,Masters,9,93,66,34,60,4.0,4,45,Semi-Urban,Data Analyst,132590,1 +34201,Male,40,High School,14,92,3,89,36,8.0,0,86,Urban,Manager,36348,1 +34202,Male,57,Diploma,12,21,44,95,59,0.0,6,80,Semi-Urban,HR Executive,134884,1 +34203,Female,25,Bachelors,8,78,96,83,17,6.0,3,41,Urban,Manager,143574,1 +34204,Male,45,High School,10,18,21,40,95,6.0,0,77,Urban,Manager,107922,0 +34205,Female,55,High School,16,58,21,49,33,6.0,5,22,Rural,Software Engineer,24987,0 +34206,Male,42,Masters,2,24,26,21,16,8.0,4,63,Urban,Manager,69788,0 +34207,Female,28,Bachelors,12,34,45,1,87,7.0,6,77,Rural,Manager,103932,0 +34208,Female,55,Bachelors,18,40,50,8,34,9.0,3,4,Rural,Manager,91049,0 +34209,Male,31,Diploma,6,44,63,74,65,7.0,4,12,Urban,Software Engineer,55284,0 +34210,Male,21,Bachelors,13,37,84,27,75,6.0,7,23,Urban,HR Executive,130242,0 +34211,Male,52,Bachelors,8,31,67,69,13,3.0,0,0,Semi-Urban,Manager,128413,0 +34212,Male,46,Bachelors,13,93,33,88,72,6.0,5,52,Semi-Urban,Software Engineer,53089,1 +34213,Female,52,Bachelors,5,67,17,79,6,2.0,5,55,Urban,Software Engineer,137596,0 +34214,Other,52,Masters,2,27,49,79,53,2.0,5,17,Urban,Software Engineer,63925,0 +34215,Female,54,Bachelors,9,9,7,97,25,7.0,0,68,Rural,HR Executive,141671,0 +34216,Female,57,Bachelors,8,0,78,76,2,3.0,7,93,Urban,Data Analyst,137941,1 +34217,Male,33,Bachelors,1,1,75,14,71,1.0,4,73,Urban,Software Engineer,48850,0 +34218,Male,35,Masters,0,57,31,80,80,4.0,0,19,Rural,Software Engineer,49317,0 +34219,Female,58,Diploma,9,56,93,54,26,0.0,1,70,Urban,HR Executive,63284,1 +34220,Male,23,Bachelors,6,96,95,48,0,8.0,0,84,Semi-Urban,Data Analyst,128932,1 +34221,Female,36,Bachelors,1,31,3,9,43,9.0,7,88,Urban,Manager,24791,0 +34222,Female,56,Diploma,8,37,80,53,77,2.0,4,58,Urban,ML Engineer,97155,0 +34223,Male,22,Diploma,14,73,47,74,10,6.0,4,93,Urban,Manager,93144,1 +34224,Male,35,Bachelors,15,5,18,38,36,1.0,2,64,Urban,ML Engineer,96737,0 +34225,Female,24,Masters,19,82,91,93,87,3.0,3,19,Urban,Manager,92074,1 +34226,Male,33,Diploma,11,22,68,10,72,4.0,2,4,Urban,HR Executive,137308,0 +34227,Female,59,Bachelors,13,20,85,8,4,7.0,1,62,Urban,Software Engineer,45027,0 +34228,Male,36,Masters,7,9,10,53,30,7.0,7,59,Semi-Urban,Manager,69134,0 +34229,Male,29,Bachelors,16,33,50,42,55,2.0,2,60,Rural,HR Executive,144514,0 +34230,Male,55,Masters,4,30,51,80,17,2.0,3,71,Urban,HR Executive,131941,0 +34231,Female,46,Diploma,3,7,82,59,81,2.0,4,44,Semi-Urban,Data Analyst,40810,0 +34232,Male,47,Bachelors,14,79,82,27,78,8.0,7,42,Urban,HR Executive,79845,0 +34233,Male,59,Diploma,14,46,69,3,63,0.0,2,60,Urban,Software Engineer,58311,0 +34234,Male,36,High School,11,42,60,31,22,0.0,7,78,Urban,ML Engineer,119696,0 +34235,Male,30,High School,4,65,20,31,49,7.0,3,75,Semi-Urban,HR Executive,134322,0 +34236,Male,41,Diploma,9,7,86,53,50,5.0,6,58,Urban,Data Analyst,109843,0 +34237,Male,47,Diploma,9,95,42,21,80,7.0,4,45,Semi-Urban,Data Analyst,52692,0 +34238,Male,36,Bachelors,18,56,57,64,40,1.0,1,90,Urban,ML Engineer,31364,1 +34239,Male,51,Masters,3,21,49,35,84,5.0,5,19,Urban,Data Analyst,60974,0 +34240,Male,45,Diploma,18,82,84,53,77,0.0,5,66,Rural,Manager,134462,1 +34241,Male,33,Masters,18,19,58,58,25,4.0,7,9,Semi-Urban,HR Executive,77293,0 +34242,Male,56,Masters,5,93,20,93,9,8.0,3,18,Urban,HR Executive,83953,0 +34243,Male,50,High School,11,86,70,16,96,1.0,0,81,Urban,Manager,25024,1 +34244,Male,26,Bachelors,0,7,82,15,68,2.0,4,19,Semi-Urban,HR Executive,34203,0 +34245,Other,59,Masters,15,75,93,76,36,1.0,4,21,Urban,HR Executive,96599,1 +34246,Male,53,Masters,16,22,81,39,42,3.0,3,40,Urban,Manager,72588,0 +34247,Female,26,Diploma,6,81,28,76,81,3.0,3,85,Rural,Software Engineer,34291,1 +34248,Male,25,Bachelors,9,81,14,22,68,3.0,7,3,Urban,ML Engineer,116310,0 +34249,Female,49,High School,0,25,8,36,67,7.0,6,21,Rural,ML Engineer,85340,0 +34250,Female,38,Masters,8,72,2,42,29,8.0,3,23,Semi-Urban,ML Engineer,50785,0 +34251,Male,34,Masters,0,68,47,60,97,9.0,7,42,Semi-Urban,Software Engineer,142623,0 +34252,Female,30,Masters,13,29,22,6,13,0.0,4,40,Urban,HR Executive,113689,0 +34253,Male,36,Bachelors,3,4,75,94,28,4.0,2,72,Urban,Manager,96946,1 +34254,Male,28,Bachelors,3,34,28,31,85,6.0,6,58,Semi-Urban,Software Engineer,68841,0 +34255,Male,28,Diploma,15,18,58,10,18,0.0,5,69,Semi-Urban,Data Analyst,146193,0 +34256,Male,39,PhD,1,34,15,23,72,8.0,4,84,Rural,Software Engineer,133111,0 +34257,Male,59,High School,14,3,43,43,39,9.0,5,61,Urban,Software Engineer,148930,0 +34258,Male,58,Masters,8,63,51,44,81,5.0,2,7,Urban,Data Analyst,47871,0 +34259,Male,43,Diploma,11,16,35,86,87,2.0,1,49,Urban,Software Engineer,115979,0 +34260,Female,43,High School,12,53,26,18,3,0.0,4,82,Semi-Urban,Manager,123731,0 +34261,Male,49,Masters,11,47,7,72,31,3.0,6,35,Urban,HR Executive,119186,0 +34262,Male,31,Masters,5,21,82,74,73,8.0,4,42,Urban,Data Analyst,32166,0 +34263,Male,26,Masters,16,89,35,80,77,2.0,4,68,Urban,Manager,92682,1 +34264,Male,54,Masters,5,44,94,51,73,6.0,5,79,Urban,ML Engineer,98504,1 +34265,Male,50,Bachelors,19,84,75,30,21,6.0,2,26,Urban,Software Engineer,27246,0 +34266,Male,36,Bachelors,5,18,54,83,56,3.0,3,71,Urban,Manager,119906,0 +34267,Male,24,Bachelors,2,14,66,99,40,7.0,7,70,Rural,Data Analyst,50877,1 +34268,Male,38,Bachelors,8,27,17,63,1,4.0,6,84,Urban,Data Analyst,129997,0 +34269,Female,58,Bachelors,18,26,15,54,29,5.0,6,44,Urban,ML Engineer,50136,0 +34270,Male,58,Diploma,6,31,73,13,3,3.0,7,72,Urban,Manager,112552,0 +34271,Male,49,Masters,0,81,21,20,53,7.0,1,98,Urban,Manager,101142,0 +34272,Male,58,Masters,11,68,63,26,5,5.0,5,65,Urban,ML Engineer,90759,0 +34273,Other,29,Bachelors,2,83,63,12,39,9.0,3,35,Rural,ML Engineer,123072,0 +34274,Female,47,Diploma,16,9,0,51,9,4.0,6,52,Urban,Manager,80834,0 +34275,Male,37,Bachelors,8,64,14,19,83,8.0,3,92,Semi-Urban,HR Executive,81586,0 +34276,Male,31,Bachelors,15,36,44,68,26,1.0,6,94,Urban,Manager,68702,1 +34277,Male,53,High School,14,28,22,29,63,2.0,7,33,Urban,HR Executive,28188,0 +34278,Male,28,PhD,14,84,69,64,50,3.0,1,72,Urban,HR Executive,89606,1 +34279,Female,32,Bachelors,1,84,70,49,13,0.0,6,29,Urban,Software Engineer,107965,0 +34280,Male,23,Masters,5,8,30,56,9,2.0,7,96,Semi-Urban,HR Executive,140147,0 +34281,Male,31,Bachelors,16,57,72,10,32,2.0,3,48,Urban,Manager,105553,0 +34282,Male,30,Masters,3,39,15,13,4,5.0,4,2,Semi-Urban,Software Engineer,141187,0 +34283,Female,43,Bachelors,12,99,17,92,96,5.0,7,10,Urban,Manager,75118,0 +34284,Male,35,Bachelors,3,94,69,52,94,1.0,2,94,Urban,Data Analyst,80748,1 +34285,Female,54,Diploma,6,67,46,53,26,0.0,4,2,Urban,Manager,76336,0 +34286,Male,46,Diploma,5,34,56,49,95,6.0,0,80,Urban,Software Engineer,79679,0 +34287,Female,54,High School,12,74,83,12,17,4.0,5,42,Urban,ML Engineer,112573,0 +34288,Male,37,Masters,17,99,75,20,12,3.0,0,15,Urban,HR Executive,38862,0 +34289,Male,27,Diploma,6,84,21,88,88,9.0,5,22,Rural,HR Executive,133141,0 +34290,Female,46,Bachelors,18,72,39,13,46,4.0,1,68,Semi-Urban,Software Engineer,71119,0 +34291,Female,47,Bachelors,2,71,17,89,96,2.0,3,68,Urban,ML Engineer,99506,1 +34292,Male,35,High School,5,29,90,90,60,0.0,0,43,Rural,Software Engineer,136952,1 +34293,Female,52,High School,19,2,59,10,67,0.0,5,74,Rural,Data Analyst,113714,0 +34294,Female,55,Masters,1,66,93,51,79,7.0,4,86,Semi-Urban,Data Analyst,129253,1 +34295,Male,44,Masters,8,63,52,99,75,8.0,6,93,Urban,Data Analyst,143907,1 +34296,Female,41,Bachelors,13,47,90,99,66,7.0,1,76,Urban,Manager,72394,1 +34297,Male,38,Bachelors,1,51,39,90,33,2.0,7,33,Semi-Urban,Software Engineer,77987,0 +34298,Female,58,Masters,15,99,19,22,73,7.0,4,50,Urban,HR Executive,134179,0 +34299,Male,39,Bachelors,2,7,84,95,43,3.0,0,75,Urban,Software Engineer,90794,1 +34300,Male,43,Masters,19,96,47,71,34,2.0,6,75,Rural,Manager,62792,1 +34301,Female,43,Masters,7,8,46,0,15,3.0,5,26,Semi-Urban,Software Engineer,140643,0 +34302,Male,54,Bachelors,3,18,38,59,54,7.0,6,30,Rural,Data Analyst,63258,0 +34303,Male,21,High School,1,79,72,85,41,4.0,3,25,Urban,Data Analyst,28321,1 +34304,Female,28,Bachelors,14,40,78,5,25,8.0,1,72,Semi-Urban,Software Engineer,147139,0 +34305,Female,28,Diploma,13,88,43,40,73,1.0,5,45,Urban,HR Executive,146057,0 +34306,Male,45,Bachelors,0,12,75,43,45,2.0,0,76,Urban,Data Analyst,48189,0 +34307,Male,27,Bachelors,9,97,41,87,57,9.0,1,20,Semi-Urban,Data Analyst,23697,1 +34308,Female,36,Bachelors,17,59,21,93,85,4.0,7,57,Semi-Urban,Software Engineer,28146,0 +34309,Male,55,Bachelors,18,84,56,30,45,3.0,7,84,Urban,Manager,113871,1 +34310,Male,37,Masters,17,58,63,71,78,9.0,6,22,Rural,ML Engineer,106640,0 +34311,Male,42,Diploma,11,40,66,77,89,2.0,5,81,Urban,HR Executive,139108,1 +34312,Male,47,High School,16,43,98,13,3,0.0,7,27,Semi-Urban,ML Engineer,128169,0 +34313,Male,57,Bachelors,3,44,88,85,49,0.0,5,60,Rural,HR Executive,34526,1 +34314,Female,31,Bachelors,5,23,38,55,30,0.0,1,8,Urban,Manager,59198,0 +34315,Female,23,Bachelors,6,58,42,39,86,8.0,5,88,Rural,ML Engineer,51454,0 +34316,Male,34,Bachelors,6,22,78,83,38,1.0,4,51,Urban,ML Engineer,132430,0 +34317,Male,38,Diploma,12,3,84,62,20,2.0,7,25,Urban,ML Engineer,112610,0 +34318,Male,29,Masters,9,55,56,11,63,0.0,2,5,Urban,ML Engineer,36821,0 +34319,Male,28,Bachelors,13,4,43,55,13,1.0,3,24,Semi-Urban,Data Analyst,144826,0 +34320,Male,24,High School,3,3,62,27,58,3.0,1,41,Urban,HR Executive,94223,0 +34321,Female,21,Masters,2,42,70,17,65,8.0,7,54,Semi-Urban,Manager,91122,0 +34322,Male,34,Diploma,7,94,8,99,88,0.0,3,23,Urban,HR Executive,138553,0 +34323,Female,46,Diploma,18,66,19,17,84,9.0,1,29,Rural,Data Analyst,81532,0 +34324,Female,55,High School,13,64,22,37,79,1.0,3,74,Semi-Urban,Data Analyst,67089,0 +34325,Male,59,PhD,8,77,14,54,92,9.0,5,98,Urban,HR Executive,121093,1 +34326,Male,29,Diploma,10,76,51,79,94,6.0,0,96,Rural,HR Executive,31855,1 +34327,Female,28,Masters,12,44,51,39,83,7.0,1,62,Urban,Manager,99577,0 +34328,Female,41,Bachelors,2,31,95,58,44,3.0,3,66,Rural,Data Analyst,121958,1 +34329,Other,52,Diploma,17,26,32,86,16,1.0,5,22,Rural,Manager,113599,0 +34330,Male,27,Diploma,2,53,43,31,49,6.0,4,32,Urban,Manager,38631,0 +34331,Female,36,Bachelors,0,15,22,12,91,5.0,2,50,Semi-Urban,HR Executive,99617,0 +34332,Male,52,Bachelors,15,25,98,95,70,2.0,4,69,Semi-Urban,ML Engineer,39482,1 +34333,Male,52,Masters,12,7,79,17,11,8.0,6,10,Urban,Data Analyst,31638,0 +34334,Male,55,Diploma,10,27,73,9,14,9.0,1,60,Semi-Urban,Software Engineer,110681,0 +34335,Male,30,Bachelors,8,41,30,95,43,1.0,1,32,Rural,Software Engineer,133991,0 +34336,Female,52,Bachelors,7,57,9,16,62,2.0,4,26,Urban,Software Engineer,28023,0 +34337,Male,43,Bachelors,12,49,93,16,60,9.0,1,9,Rural,ML Engineer,31909,0 +34338,Female,40,Masters,14,64,38,83,97,8.0,7,33,Urban,Manager,57480,0 +34339,Male,21,Bachelors,19,30,87,78,72,5.0,4,21,Urban,Manager,79486,0 +34340,Female,56,Diploma,2,94,81,95,61,2.0,4,4,Semi-Urban,ML Engineer,130070,1 +34341,Male,51,Bachelors,18,79,9,81,85,6.0,3,38,Rural,Manager,122501,0 +34342,Female,27,High School,10,64,67,78,9,3.0,2,50,Urban,Data Analyst,113815,1 +34343,Male,47,Masters,0,34,87,60,64,6.0,4,29,Rural,Software Engineer,78491,0 +34344,Male,22,High School,1,36,7,98,3,1.0,6,87,Urban,Software Engineer,31997,0 +34345,Female,48,Bachelors,13,10,53,29,45,4.0,7,79,Rural,ML Engineer,131947,0 +34346,Male,54,Masters,16,23,93,27,58,7.0,2,13,Rural,Data Analyst,116299,0 +34347,Male,42,Bachelors,18,39,95,3,72,5.0,7,67,Urban,Manager,74635,0 +34348,Female,30,Bachelors,19,8,29,81,16,4.0,0,47,Urban,HR Executive,74879,0 +34349,Male,43,Diploma,17,16,29,65,96,6.0,0,47,Semi-Urban,Manager,139495,0 +34350,Male,39,Bachelors,19,46,9,58,21,7.0,5,37,Urban,HR Executive,114126,0 +34351,Male,30,PhD,8,46,14,24,54,4.0,6,34,Semi-Urban,Software Engineer,46886,0 +34352,Male,43,PhD,8,90,59,87,47,2.0,0,61,Semi-Urban,Data Analyst,37318,1 +34353,Female,48,Bachelors,12,3,28,45,77,1.0,7,29,Urban,ML Engineer,29886,0 +34354,Male,34,Masters,4,40,73,96,46,7.0,2,45,Urban,Data Analyst,145875,1 +34355,Male,33,Bachelors,0,92,12,96,64,9.0,4,31,Semi-Urban,ML Engineer,112550,0 +34356,Female,46,High School,10,12,35,2,24,4.0,7,92,Semi-Urban,Data Analyst,24549,0 +34357,Female,45,Masters,4,38,24,20,47,0.0,6,82,Rural,Data Analyst,75958,0 +34358,Female,33,Bachelors,7,62,6,95,44,2.0,4,2,Urban,HR Executive,39829,0 +34359,Male,49,Bachelors,0,77,82,33,77,3.0,6,73,Urban,Manager,31034,1 +34360,Male,22,Diploma,16,34,43,46,15,9.0,2,66,Urban,Data Analyst,54923,0 +34361,Male,55,Bachelors,9,41,78,61,19,0.0,2,77,Rural,Software Engineer,32398,1 +34362,Male,48,Bachelors,0,5,30,94,48,1.0,6,24,Semi-Urban,ML Engineer,82113,0 +34363,Male,29,Masters,4,61,70,25,20,0.0,2,68,Urban,HR Executive,101438,0 +34364,Female,58,Diploma,10,21,39,9,21,7.0,2,91,Rural,HR Executive,61081,0 +34365,Female,48,Bachelors,16,76,22,60,67,5.0,7,12,Rural,HR Executive,129733,0 +34366,Male,56,Masters,16,93,36,9,98,0.0,3,35,Rural,Data Analyst,90257,0 +34367,Male,23,PhD,9,12,98,12,90,7.0,5,31,Urban,Manager,134123,0 +34368,Male,25,Masters,3,28,75,10,25,7.0,4,96,Semi-Urban,HR Executive,138671,0 +34369,Female,56,Masters,17,55,2,47,54,6.0,4,93,Rural,Manager,34971,0 +34370,Female,25,Bachelors,12,57,9,24,39,8.0,0,78,Urban,Manager,138596,0 +34371,Male,46,High School,14,20,56,85,41,9.0,2,83,Urban,Software Engineer,75587,1 +34372,Female,34,Diploma,14,61,21,55,83,3.0,6,60,Urban,Software Engineer,108879,0 +34373,Male,45,Diploma,0,59,94,21,59,4.0,4,28,Urban,HR Executive,137775,0 +34374,Male,23,Bachelors,0,40,3,85,74,4.0,5,38,Urban,Data Analyst,100304,0 +34375,Male,39,PhD,11,70,7,31,50,4.0,1,76,Rural,Manager,104873,0 +34376,Male,49,High School,12,71,70,6,91,5.0,2,38,Rural,HR Executive,128294,0 +34377,Male,40,Bachelors,1,76,76,21,1,2.0,4,64,Semi-Urban,Software Engineer,80002,1 +34378,Male,31,High School,19,55,97,29,76,4.0,0,60,Rural,Manager,40772,1 +34379,Male,32,Masters,3,51,35,72,57,0.0,5,77,Rural,Manager,92251,1 +34380,Male,56,Masters,19,53,98,84,9,9.0,3,85,Rural,ML Engineer,142489,1 +34381,Female,29,Bachelors,15,99,1,27,6,4.0,7,72,Rural,Software Engineer,91111,0 +34382,Male,49,Bachelors,18,63,20,9,65,1.0,3,6,Rural,HR Executive,69543,0 +34383,Female,30,PhD,15,7,76,55,31,7.0,0,91,Urban,ML Engineer,51340,0 +34384,Male,23,Bachelors,18,80,23,35,31,9.0,2,85,Rural,HR Executive,47545,0 +34385,Male,38,Bachelors,1,87,2,32,10,6.0,3,49,Rural,Data Analyst,62803,0 +34386,Male,21,Diploma,13,10,36,43,55,4.0,0,85,Urban,ML Engineer,103684,0 +34387,Male,52,Diploma,17,77,56,74,28,4.0,2,62,Urban,HR Executive,149211,1 +34388,Male,34,Masters,18,98,36,75,97,8.0,2,10,Rural,HR Executive,149598,0 +34389,Male,56,Bachelors,14,9,76,58,92,3.0,0,1,Urban,Data Analyst,59466,0 +34390,Female,24,Diploma,13,81,16,59,28,8.0,3,90,Urban,Manager,138967,1 +34391,Female,24,Bachelors,1,65,51,35,1,4.0,0,39,Rural,Manager,89874,0 +34392,Female,21,PhD,1,95,11,17,31,6.0,0,11,Rural,ML Engineer,54506,0 +34393,Male,55,Bachelors,19,67,41,40,84,9.0,0,50,Urban,HR Executive,110493,0 +34394,Male,35,Masters,2,3,71,30,86,6.0,7,27,Urban,HR Executive,129084,0 +34395,Male,55,Bachelors,14,80,35,40,90,3.0,7,32,Semi-Urban,Software Engineer,145934,0 +34396,Female,24,Bachelors,7,3,86,4,73,4.0,5,19,Urban,Manager,76137,0 +34397,Other,35,Bachelors,19,37,56,10,93,4.0,2,0,Rural,Data Analyst,45603,0 +34398,Female,43,Bachelors,4,79,7,9,64,1.0,4,64,Urban,ML Engineer,61156,0 +34399,Male,53,High School,1,36,32,63,7,7.0,3,38,Urban,ML Engineer,127936,0 +34400,Male,27,Diploma,0,56,8,31,92,8.0,5,19,Rural,Software Engineer,46496,0 +34401,Male,24,Masters,1,58,99,59,82,5.0,5,26,Semi-Urban,Software Engineer,145647,1 +34402,Male,25,Bachelors,12,23,9,5,24,4.0,3,90,Semi-Urban,HR Executive,86021,0 +34403,Male,30,Masters,3,73,14,7,55,5.0,0,95,Urban,Manager,32178,0 +34404,Male,32,Bachelors,12,66,79,73,18,1.0,6,93,Urban,ML Engineer,77004,1 +34405,Male,53,Diploma,18,35,15,18,89,1.0,6,89,Urban,ML Engineer,68572,0 +34406,Male,54,Diploma,7,8,27,95,48,3.0,2,85,Urban,HR Executive,77089,0 +34407,Male,54,High School,16,29,83,62,48,4.0,0,97,Semi-Urban,Software Engineer,119229,1 +34408,Female,45,Bachelors,15,89,30,0,71,5.0,5,35,Urban,Software Engineer,55360,0 +34409,Male,39,Masters,19,93,96,84,22,0.0,6,86,Semi-Urban,ML Engineer,141534,1 +34410,Male,24,Bachelors,15,94,82,13,89,3.0,3,23,Urban,HR Executive,118076,0 +34411,Female,44,Diploma,4,28,10,63,28,7.0,3,42,Urban,Software Engineer,25509,0 +34412,Male,52,Bachelors,10,64,34,17,11,3.0,7,58,Urban,ML Engineer,60676,0 +34413,Male,52,Bachelors,0,74,97,23,98,6.0,0,17,Rural,HR Executive,73156,0 +34414,Female,36,Bachelors,0,57,51,3,91,1.0,5,42,Rural,Data Analyst,104887,0 +34415,Male,42,High School,5,29,91,29,36,7.0,0,51,Semi-Urban,ML Engineer,38388,0 +34416,Male,35,Bachelors,8,80,11,13,93,8.0,7,33,Urban,ML Engineer,120418,0 +34417,Male,40,Bachelors,1,56,91,75,71,8.0,1,75,Urban,HR Executive,33027,1 +34418,Male,48,Bachelors,18,96,36,3,22,1.0,6,15,Semi-Urban,ML Engineer,104095,0 +34419,Male,30,Masters,3,87,34,61,37,9.0,6,40,Urban,Manager,135876,0 +34420,Male,36,Bachelors,14,94,8,80,7,8.0,6,97,Urban,Data Analyst,107099,1 +34421,Male,37,Masters,12,73,92,83,61,5.0,6,90,Semi-Urban,ML Engineer,41591,1 +34422,Female,56,High School,6,2,64,45,65,8.0,4,51,Rural,Manager,48658,0 +34423,Male,49,Masters,10,69,24,88,9,1.0,2,2,Semi-Urban,Software Engineer,96423,0 +34424,Female,37,Bachelors,17,96,43,26,4,0.0,6,81,Urban,Software Engineer,88919,1 +34425,Male,50,High School,12,69,60,37,56,7.0,0,82,Rural,Software Engineer,144777,1 +34426,Male,50,Masters,9,69,40,26,26,8.0,4,31,Urban,HR Executive,92079,0 +34427,Male,40,Diploma,15,56,61,52,66,0.0,1,91,Urban,Software Engineer,149859,1 +34428,Female,48,High School,4,86,19,0,64,0.0,7,2,Rural,ML Engineer,55348,0 +34429,Female,30,Masters,9,62,15,68,16,4.0,6,54,Rural,ML Engineer,91368,0 +34430,Male,47,Masters,13,77,93,2,98,2.0,3,8,Semi-Urban,HR Executive,117757,0 +34431,Male,22,Masters,19,7,33,46,6,8.0,0,84,Semi-Urban,ML Engineer,56400,0 +34432,Female,24,High School,13,8,49,29,10,3.0,1,33,Semi-Urban,ML Engineer,128219,0 +34433,Female,56,High School,17,67,11,98,91,4.0,6,42,Semi-Urban,Software Engineer,128456,0 +34434,Male,52,Masters,18,2,32,65,85,7.0,3,69,Semi-Urban,ML Engineer,89800,0 +34435,Male,58,Bachelors,19,64,37,60,25,8.0,7,95,Urban,ML Engineer,25232,1 +34436,Female,22,Masters,18,24,59,18,39,0.0,5,43,Urban,ML Engineer,103500,0 +34437,Male,34,High School,1,35,86,75,30,1.0,2,6,Semi-Urban,Data Analyst,112824,0 +34438,Female,58,Bachelors,3,59,18,9,3,5.0,6,26,Urban,Data Analyst,41658,0 +34439,Male,47,PhD,4,80,37,10,9,4.0,0,32,Urban,HR Executive,21984,0 +34440,Female,34,High School,4,40,60,32,88,2.0,7,33,Semi-Urban,ML Engineer,56064,0 +34441,Male,21,Bachelors,12,4,27,83,87,0.0,1,4,Rural,Data Analyst,95311,0 +34442,Male,43,Bachelors,12,37,13,42,68,5.0,6,90,Urban,Data Analyst,83670,0 +34443,Male,58,High School,14,69,50,23,94,3.0,5,83,Urban,Manager,127031,0 +34444,Female,34,High School,3,51,26,35,68,9.0,1,75,Urban,Manager,21618,0 +34445,Female,29,High School,5,76,14,31,74,6.0,4,44,Semi-Urban,Data Analyst,82464,0 +34446,Female,42,High School,13,5,88,12,47,6.0,1,19,Urban,Data Analyst,81447,0 +34447,Female,54,High School,6,22,40,48,24,3.0,3,36,Semi-Urban,Software Engineer,24276,0 +34448,Male,34,Masters,14,46,91,7,68,5.0,1,14,Urban,Data Analyst,31554,0 +34449,Male,33,High School,12,81,12,61,31,5.0,0,36,Urban,ML Engineer,122892,0 +34450,Female,55,High School,11,66,42,16,70,3.0,7,19,Urban,HR Executive,123463,0 +34451,Female,37,Bachelors,11,54,75,93,97,6.0,1,23,Urban,Data Analyst,64299,1 +34452,Male,53,Bachelors,6,77,39,43,32,1.0,5,12,Urban,Manager,67130,0 +34453,Male,46,Bachelors,10,26,11,21,1,1.0,1,48,Urban,Software Engineer,140844,0 +34454,Male,38,Masters,1,89,74,69,26,3.0,6,73,Urban,ML Engineer,50794,1 +34455,Male,48,Masters,3,5,30,54,76,2.0,4,12,Urban,HR Executive,44043,0 +34456,Female,37,Bachelors,18,61,33,13,35,4.0,3,49,Urban,Manager,74900,0 +34457,Female,23,Bachelors,13,81,25,79,12,6.0,3,80,Rural,Data Analyst,83335,1 +34458,Female,42,Bachelors,4,14,19,76,51,3.0,3,80,Urban,HR Executive,80490,0 +34459,Female,36,Bachelors,10,48,68,23,25,0.0,2,99,Urban,ML Engineer,40611,0 +34460,Male,48,High School,3,76,36,35,50,0.0,1,65,Rural,ML Engineer,74793,0 +34461,Male,33,Masters,4,19,2,58,65,7.0,3,22,Urban,Software Engineer,78460,0 +34462,Female,24,High School,17,53,3,91,71,9.0,4,35,Semi-Urban,Manager,50435,0 +34463,Male,42,Diploma,3,52,17,94,20,2.0,2,99,Urban,HR Executive,55435,1 +34464,Male,23,High School,16,94,96,8,26,9.0,4,90,Semi-Urban,Data Analyst,40288,1 +34465,Female,36,Masters,8,5,11,5,22,8.0,4,79,Urban,Data Analyst,116919,0 +34466,Female,51,High School,10,90,34,29,67,7.0,0,60,Urban,Manager,94655,0 +34467,Female,26,Masters,19,33,3,71,53,0.0,4,14,Urban,HR Executive,149783,0 +34468,Female,42,Diploma,13,82,69,26,86,9.0,4,95,Urban,Manager,79187,1 +34469,Male,44,Bachelors,0,70,60,65,35,2.0,4,69,Rural,Data Analyst,146314,1 +34470,Male,29,High School,7,36,27,72,56,6.0,4,89,Urban,Software Engineer,98372,0 +34471,Female,32,Masters,10,59,75,18,90,6.0,6,24,Urban,HR Executive,132292,0 +34472,Female,59,Diploma,18,5,9,29,80,6.0,7,15,Urban,ML Engineer,37152,0 +34473,Male,34,PhD,11,5,83,38,82,6.0,5,61,Semi-Urban,HR Executive,116798,0 +34474,Male,56,Bachelors,9,53,70,84,98,5.0,7,74,Urban,Manager,140505,1 +34475,Female,44,Diploma,4,32,85,92,17,4.0,1,62,Rural,ML Engineer,147392,1 +34476,Male,36,Masters,15,45,84,19,85,0.0,2,5,Urban,Manager,105464,0 +34477,Female,50,High School,1,57,5,33,10,9.0,0,64,Urban,Data Analyst,45538,0 +34478,Male,46,Diploma,18,82,55,32,9,8.0,7,37,Urban,Manager,99253,0 +34479,Male,42,Masters,2,9,49,38,94,3.0,0,11,Rural,HR Executive,113134,0 +34480,Female,33,Masters,16,25,17,29,20,9.0,5,90,Urban,Manager,53506,0 +34481,Male,46,Masters,7,62,26,22,24,6.0,6,51,Urban,Software Engineer,98142,0 +34482,Male,34,Masters,16,22,28,73,49,5.0,1,11,Urban,ML Engineer,125497,0 +34483,Female,54,Diploma,18,24,38,4,81,9.0,6,75,Urban,ML Engineer,110661,0 +34484,Female,49,Diploma,6,36,94,95,48,1.0,7,33,Semi-Urban,ML Engineer,61794,1 +34485,Male,46,Masters,10,25,9,5,74,9.0,4,85,Semi-Urban,ML Engineer,23931,0 +34486,Male,53,Bachelors,13,8,76,83,16,0.0,5,49,Urban,Data Analyst,76821,0 +34487,Male,38,High School,9,91,26,21,3,2.0,0,83,Urban,ML Engineer,136814,0 +34488,Male,36,High School,18,3,7,84,82,5.0,2,36,Urban,Software Engineer,56462,0 +34489,Male,39,Masters,0,36,9,69,21,1.0,6,0,Urban,Manager,113936,0 +34490,Male,35,Diploma,15,5,70,45,84,4.0,2,43,Urban,HR Executive,95520,0 +34491,Male,40,High School,6,49,14,55,62,3.0,3,58,Rural,Data Analyst,71511,0 +34492,Male,40,High School,1,42,79,58,10,0.0,2,0,Urban,Software Engineer,104858,0 +34493,Male,25,Masters,19,56,19,28,10,5.0,2,75,Urban,HR Executive,77357,0 +34494,Male,37,Masters,11,9,15,90,30,2.0,1,32,Urban,Manager,141534,0 +34495,Other,39,High School,10,29,4,44,37,6.0,7,0,Urban,ML Engineer,66429,0 +34496,Other,42,Bachelors,15,38,41,9,84,1.0,2,22,Rural,Data Analyst,26497,0 +34497,Male,45,Diploma,8,5,91,90,60,1.0,1,71,Rural,Manager,91214,1 +34498,Female,44,Bachelors,5,82,22,40,40,0.0,1,98,Rural,Software Engineer,98096,1 +34499,Female,55,Bachelors,18,5,81,77,6,5.0,6,79,Semi-Urban,Software Engineer,119057,1 +34500,Male,53,Bachelors,18,84,67,70,89,0.0,1,67,Urban,HR Executive,119653,1 +34501,Male,58,Masters,15,76,54,60,88,6.0,6,8,Urban,Manager,24749,0 +34502,Male,48,High School,10,75,45,82,11,4.0,6,30,Urban,ML Engineer,120312,0 +34503,Male,56,High School,18,89,68,50,76,4.0,6,97,Urban,HR Executive,90778,1 +34504,Male,51,Masters,7,85,87,27,57,7.0,6,31,Rural,ML Engineer,133278,0 +34505,Female,34,Bachelors,12,75,71,49,21,2.0,4,72,Urban,HR Executive,115327,1 +34506,Female,59,High School,3,3,84,70,90,9.0,7,92,Rural,Data Analyst,106251,1 +34507,Female,28,Bachelors,2,58,9,84,18,0.0,0,68,Urban,ML Engineer,114822,0 +34508,Female,23,Bachelors,5,68,10,6,70,3.0,7,46,Rural,ML Engineer,51707,0 +34509,Female,58,High School,1,35,85,44,67,8.0,2,62,Urban,Software Engineer,32394,0 +34510,Male,29,Bachelors,16,29,96,66,73,9.0,2,93,Semi-Urban,HR Executive,41113,1 +34511,Male,55,Bachelors,2,57,48,32,71,3.0,3,83,Urban,HR Executive,127324,0 +34512,Male,31,Diploma,19,92,90,93,33,6.0,2,89,Semi-Urban,Software Engineer,90624,1 +34513,Female,27,Bachelors,8,39,70,39,45,5.0,2,62,Rural,Software Engineer,51578,0 +34514,Male,40,Diploma,19,64,99,0,94,4.0,6,93,Semi-Urban,Manager,110275,1 +34515,Female,57,Bachelors,7,80,5,0,74,6.0,7,64,Urban,Manager,86733,0 +34516,Other,39,Diploma,14,3,79,32,13,8.0,7,15,Urban,Software Engineer,100648,0 +34517,Male,32,Bachelors,10,67,38,31,25,6.0,5,39,Semi-Urban,HR Executive,45341,0 +34518,Male,41,Bachelors,2,18,8,66,3,9.0,1,85,Urban,Manager,38199,0 +34519,Female,32,Bachelors,19,81,73,37,72,2.0,7,87,Rural,Manager,111011,1 +34520,Male,56,Bachelors,0,64,31,27,83,4.0,4,22,Semi-Urban,HR Executive,132940,0 +34521,Male,34,Diploma,6,94,64,3,2,8.0,3,54,Urban,Manager,75442,0 +34522,Female,41,Masters,5,64,47,0,34,4.0,0,20,Urban,Software Engineer,36640,0 +34523,Female,39,Bachelors,18,59,92,38,45,8.0,2,71,Semi-Urban,Data Analyst,34769,1 +34524,Male,47,Diploma,3,0,17,65,92,2.0,1,82,Urban,ML Engineer,106422,0 +34525,Female,41,Bachelors,13,66,47,41,95,9.0,5,63,Urban,Manager,138373,0 +34526,Male,38,Diploma,0,97,5,12,76,7.0,6,79,Urban,ML Engineer,90520,0 +34527,Female,58,Masters,5,45,18,17,28,6.0,0,5,Urban,Software Engineer,35425,0 +34528,Female,34,Bachelors,0,73,80,15,73,6.0,2,51,Semi-Urban,ML Engineer,89986,0 +34529,Male,28,Diploma,3,82,98,99,3,3.0,1,32,Semi-Urban,Manager,70597,1 +34530,Male,58,High School,8,52,42,9,37,2.0,7,87,Urban,ML Engineer,121541,0 +34531,Female,25,Bachelors,14,12,7,11,87,4.0,5,28,Semi-Urban,ML Engineer,84289,0 +34532,Male,27,High School,16,79,0,82,21,8.0,3,39,Rural,Manager,135105,0 +34533,Male,42,PhD,18,8,93,28,23,2.0,3,85,Urban,Data Analyst,88688,0 +34534,Male,55,Masters,5,7,28,59,64,9.0,0,36,Semi-Urban,Software Engineer,116608,0 +34535,Male,24,Bachelors,11,87,54,51,9,6.0,6,2,Urban,Manager,101893,0 +34536,Female,48,Bachelors,9,48,31,96,88,2.0,0,21,Semi-Urban,Software Engineer,149437,0 +34537,Male,33,Bachelors,9,91,94,64,81,9.0,4,0,Rural,Data Analyst,108069,1 +34538,Female,32,Bachelors,3,8,84,16,29,9.0,0,58,Semi-Urban,ML Engineer,105506,0 +34539,Male,53,Diploma,5,65,61,45,24,8.0,4,70,Urban,Data Analyst,97492,1 +34540,Female,57,Bachelors,9,33,52,58,56,8.0,2,9,Urban,Software Engineer,23073,0 +34541,Male,37,Diploma,4,65,35,97,15,7.0,7,5,Urban,ML Engineer,89240,0 +34542,Male,23,Diploma,14,93,3,9,13,8.0,3,11,Urban,ML Engineer,99133,0 +34543,Other,47,Diploma,19,32,92,70,52,0.0,1,14,Urban,Manager,38105,0 +34544,Male,26,High School,13,26,54,16,46,3.0,6,42,Urban,ML Engineer,103345,0 +34545,Male,32,Bachelors,0,87,90,47,19,2.0,2,14,Urban,Manager,79761,1 +34546,Other,37,Bachelors,5,7,66,78,90,6.0,0,93,Urban,ML Engineer,80360,1 +34547,Female,39,Masters,14,75,18,3,67,1.0,2,42,Semi-Urban,Manager,25660,0 +34548,Female,24,Bachelors,3,2,66,15,3,1.0,1,42,Urban,ML Engineer,89906,0 +34549,Male,58,Bachelors,5,82,46,88,66,3.0,0,34,Urban,Manager,137552,1 +34550,Male,38,High School,13,52,91,78,19,6.0,0,30,Rural,ML Engineer,125380,1 +34551,Male,58,PhD,4,29,77,16,34,6.0,7,30,Semi-Urban,Software Engineer,133651,0 +34552,Other,27,Bachelors,2,76,21,25,71,3.0,0,45,Urban,ML Engineer,85696,0 +34553,Other,44,Bachelors,18,67,83,98,25,0.0,1,69,Rural,ML Engineer,126663,1 +34554,Male,56,Bachelors,13,60,26,97,69,1.0,0,32,Urban,ML Engineer,32604,0 +34555,Male,44,Masters,18,71,94,89,82,7.0,0,50,Rural,Manager,90138,1 +34556,Male,39,Masters,10,29,56,51,20,4.0,2,7,Urban,Software Engineer,54182,0 +34557,Male,56,Masters,8,61,38,53,79,3.0,7,83,Urban,ML Engineer,110465,1 +34558,Male,39,Bachelors,8,96,0,59,52,4.0,2,28,Semi-Urban,HR Executive,108819,0 +34559,Female,43,Bachelors,14,47,59,38,71,3.0,7,68,Semi-Urban,ML Engineer,148069,0 +34560,Female,35,Masters,17,70,56,75,2,6.0,7,42,Urban,Manager,28780,1 +34561,Female,41,Diploma,5,11,26,56,3,7.0,5,49,Rural,HR Executive,80987,0 +34562,Female,38,Bachelors,6,46,9,30,76,4.0,3,17,Rural,Manager,50828,0 +34563,Female,42,Bachelors,6,35,49,41,79,3.0,5,55,Urban,Manager,138927,0 +34564,Female,44,High School,2,54,30,31,62,0.0,7,48,Urban,Manager,103949,0 +34565,Male,31,High School,10,94,62,55,10,2.0,1,30,Urban,Manager,30117,1 +34566,Male,31,Bachelors,17,36,58,58,0,2.0,2,45,Urban,ML Engineer,128118,0 +34567,Male,49,Masters,13,39,15,47,74,6.0,5,27,Urban,Manager,51674,0 +34568,Female,26,Masters,4,52,93,26,30,2.0,7,5,Urban,Data Analyst,22606,0 +34569,Other,48,Bachelors,1,11,39,15,35,3.0,0,32,Urban,HR Executive,88503,0 +34570,Male,42,Diploma,10,74,32,53,37,1.0,5,9,Urban,Software Engineer,76602,0 +34571,Female,22,Bachelors,10,80,26,48,99,7.0,7,31,Urban,Data Analyst,147707,0 +34572,Male,53,PhD,14,44,71,27,59,1.0,1,90,Urban,Software Engineer,37300,0 +34573,Female,43,High School,7,72,30,20,64,7.0,6,84,Semi-Urban,Software Engineer,130052,0 +34574,Female,46,High School,18,97,29,47,56,0.0,0,97,Urban,Data Analyst,89916,1 +34575,Female,26,Bachelors,8,74,82,27,51,8.0,0,33,Rural,ML Engineer,56858,0 +34576,Female,25,Diploma,7,68,86,79,33,9.0,1,57,Urban,Data Analyst,65846,1 +34577,Male,37,PhD,10,52,41,60,92,8.0,4,23,Semi-Urban,Data Analyst,69113,0 +34578,Male,38,Masters,10,78,47,56,83,4.0,7,43,Semi-Urban,Manager,62338,0 +34579,Male,25,Bachelors,4,61,6,57,62,2.0,1,26,Semi-Urban,HR Executive,108282,0 +34580,Male,49,Diploma,6,80,72,77,99,1.0,7,35,Rural,ML Engineer,139112,1 +34581,Female,52,Bachelors,9,38,90,31,48,1.0,0,6,Urban,Manager,47902,0 +34582,Male,55,Bachelors,5,39,59,15,87,7.0,4,64,Rural,Data Analyst,67869,0 +34583,Female,29,Bachelors,13,21,10,62,69,3.0,2,42,Urban,ML Engineer,29736,0 +34584,Female,31,PhD,2,97,72,9,10,4.0,4,74,Urban,Software Engineer,56144,1 +34585,Male,38,Masters,18,16,54,40,98,2.0,3,27,Rural,ML Engineer,108568,0 +34586,Male,51,Masters,7,79,17,9,11,3.0,4,60,Urban,Manager,36476,0 +34587,Male,56,Bachelors,13,94,7,13,86,3.0,4,64,Urban,HR Executive,54397,0 +34588,Male,21,Bachelors,12,6,99,24,4,1.0,1,47,Semi-Urban,ML Engineer,143884,0 +34589,Male,50,Bachelors,14,75,8,85,66,7.0,0,88,Rural,Software Engineer,21721,1 +34590,Male,28,Bachelors,2,36,4,91,65,1.0,6,75,Semi-Urban,HR Executive,104269,0 +34591,Male,46,Bachelors,16,33,2,26,25,7.0,1,50,Urban,Software Engineer,48879,0 +34592,Female,58,Bachelors,12,17,47,90,44,2.0,1,5,Urban,Software Engineer,105957,0 +34593,Female,36,Masters,9,35,73,18,95,8.0,2,67,Urban,Software Engineer,41097,0 +34594,Female,22,Bachelors,1,41,1,66,69,9.0,5,29,Urban,Software Engineer,76421,0 +34595,Male,52,Bachelors,8,66,63,76,93,2.0,6,51,Urban,HR Executive,54962,1 +34596,Other,49,Bachelors,0,5,75,25,14,2.0,1,75,Urban,Manager,60458,0 +34597,Female,21,Diploma,19,12,93,68,99,1.0,0,27,Rural,HR Executive,82026,0 +34598,Other,24,Bachelors,10,74,56,20,52,8.0,6,80,Urban,Data Analyst,47690,0 +34599,Male,49,High School,5,53,44,42,59,4.0,4,76,Urban,HR Executive,46384,0 +34600,Female,52,Diploma,19,65,44,22,50,6.0,7,10,Urban,Manager,56810,0 +34601,Female,49,Masters,8,4,98,34,35,3.0,1,49,Urban,Data Analyst,20829,0 +34602,Male,57,Diploma,9,14,26,37,58,1.0,1,0,Semi-Urban,Data Analyst,68848,0 +34603,Male,24,High School,15,82,52,18,83,3.0,6,92,Semi-Urban,Software Engineer,25775,1 +34604,Female,25,PhD,11,70,5,16,2,2.0,5,11,Rural,ML Engineer,103697,0 +34605,Male,36,Diploma,9,11,23,38,36,4.0,7,6,Urban,Software Engineer,48087,0 +34606,Male,48,Masters,13,76,76,61,34,3.0,3,54,Urban,ML Engineer,48077,1 +34607,Male,39,Bachelors,18,25,71,67,78,3.0,6,34,Urban,HR Executive,59841,0 +34608,Female,32,PhD,13,39,65,23,80,1.0,1,35,Rural,ML Engineer,144105,0 +34609,Female,33,Diploma,16,85,92,71,99,1.0,7,61,Urban,HR Executive,101002,1 +34610,Male,56,Bachelors,12,30,34,98,86,1.0,2,60,Urban,ML Engineer,134549,0 +34611,Female,41,Bachelors,9,29,9,59,82,4.0,5,70,Urban,HR Executive,64057,0 +34612,Male,40,Bachelors,7,7,50,7,22,6.0,1,15,Semi-Urban,ML Engineer,62292,0 +34613,Female,57,High School,16,30,84,18,40,0.0,1,21,Semi-Urban,HR Executive,30627,0 +34614,Male,40,High School,4,7,58,56,34,0.0,7,30,Rural,ML Engineer,100278,0 +34615,Female,39,Diploma,16,20,76,57,74,0.0,3,97,Urban,Data Analyst,62733,1 +34616,Male,50,Bachelors,12,36,76,35,18,7.0,0,30,Urban,Manager,20508,0 +34617,Male,36,Diploma,5,8,87,97,62,2.0,0,51,Rural,Software Engineer,31987,1 +34618,Male,24,Bachelors,6,70,13,44,72,8.0,5,8,Urban,Data Analyst,102085,0 +34619,Female,31,Bachelors,4,21,5,23,67,4.0,0,82,Semi-Urban,Manager,120814,0 +34620,Other,33,Masters,1,11,1,69,83,4.0,3,28,Urban,Software Engineer,149930,0 +34621,Male,42,Bachelors,17,0,28,42,85,7.0,0,38,Rural,ML Engineer,113512,0 +34622,Male,39,Bachelors,2,85,24,34,86,6.0,0,70,Semi-Urban,ML Engineer,99597,0 +34623,Female,49,Masters,14,18,37,14,57,4.0,7,11,Urban,Manager,78754,0 +34624,Female,31,Bachelors,11,71,59,81,37,4.0,1,11,Urban,HR Executive,104750,0 +34625,Male,29,Diploma,0,36,80,31,54,8.0,2,42,Urban,HR Executive,116106,0 +34626,Male,55,Bachelors,1,70,69,45,57,5.0,3,35,Urban,Data Analyst,91262,0 +34627,Male,50,Bachelors,2,16,15,86,58,7.0,5,89,Urban,ML Engineer,43995,0 +34628,Male,41,Diploma,18,43,81,81,36,8.0,2,61,Semi-Urban,HR Executive,82701,1 +34629,Male,21,Masters,5,19,81,83,61,5.0,0,48,Rural,HR Executive,64682,0 +34630,Male,24,Masters,0,12,9,74,52,1.0,5,60,Rural,Software Engineer,89992,0 +34631,Male,47,Bachelors,15,73,94,28,3,1.0,4,67,Urban,HR Executive,57335,1 +34632,Female,37,Diploma,8,1,21,55,31,7.0,2,74,Semi-Urban,HR Executive,80674,0 +34633,Other,33,High School,5,23,58,99,83,5.0,5,38,Urban,HR Executive,122138,0 +34634,Female,47,Bachelors,13,63,8,13,98,6.0,5,47,Urban,ML Engineer,72855,0 +34635,Female,52,Diploma,12,84,90,61,5,1.0,0,0,Urban,Manager,132285,0 +34636,Female,30,Bachelors,3,10,57,33,33,2.0,7,1,Urban,Manager,45545,0 +34637,Male,57,Masters,19,50,16,11,59,2.0,6,86,Semi-Urban,HR Executive,87773,0 +34638,Female,27,Diploma,14,29,68,28,46,3.0,4,65,Semi-Urban,Software Engineer,127515,0 +34639,Male,31,Bachelors,15,53,2,39,59,1.0,5,55,Urban,ML Engineer,141676,0 +34640,Female,35,Masters,13,89,88,54,79,3.0,0,77,Urban,Software Engineer,70396,1 +34641,Other,21,PhD,0,24,65,35,48,5.0,5,50,Urban,HR Executive,85033,0 +34642,Female,37,Masters,8,36,95,49,97,2.0,0,44,Urban,ML Engineer,53171,0 +34643,Male,22,Diploma,3,19,97,8,73,5.0,0,64,Semi-Urban,Software Engineer,109745,0 +34644,Female,49,Diploma,11,17,54,66,31,2.0,2,48,Urban,ML Engineer,106416,0 +34645,Female,21,Bachelors,3,95,72,46,89,4.0,7,93,Rural,Software Engineer,124297,1 +34646,Male,59,PhD,6,8,17,98,41,6.0,2,18,Urban,ML Engineer,25671,0 +34647,Female,25,Diploma,6,70,38,2,51,6.0,4,71,Semi-Urban,ML Engineer,122133,0 +34648,Male,37,Bachelors,9,89,57,26,43,2.0,3,54,Rural,ML Engineer,51315,0 +34649,Female,37,Masters,14,66,92,26,82,8.0,2,71,Urban,Manager,46745,1 +34650,Male,50,PhD,14,3,48,37,96,3.0,7,53,Urban,HR Executive,43944,0 +34651,Male,59,Bachelors,7,6,34,81,3,4.0,0,3,Rural,Manager,54733,0 +34652,Female,31,Diploma,5,17,3,62,45,6.0,0,97,Semi-Urban,Data Analyst,92873,0 +34653,Male,55,PhD,19,22,8,3,43,0.0,1,39,Urban,Data Analyst,116922,0 +34654,Male,40,Masters,17,12,60,25,28,2.0,3,9,Semi-Urban,Software Engineer,66968,0 +34655,Male,32,Bachelors,15,81,75,48,97,4.0,2,61,Urban,HR Executive,89617,1 +34656,Female,26,Bachelors,1,76,42,26,0,8.0,2,43,Urban,HR Executive,101223,0 +34657,Male,23,Masters,16,36,42,87,18,9.0,5,8,Urban,Software Engineer,37837,0 +34658,Female,26,Diploma,9,93,90,35,92,2.0,0,86,Urban,ML Engineer,30779,1 +34659,Female,57,Bachelors,16,94,81,57,47,8.0,4,90,Urban,Software Engineer,82310,1 +34660,Male,42,Masters,16,70,73,45,10,9.0,0,13,Urban,Data Analyst,129749,0 +34661,Female,22,Bachelors,18,94,79,90,26,6.0,2,8,Urban,Manager,145737,1 +34662,Male,41,Masters,10,23,12,29,84,9.0,3,38,Rural,ML Engineer,93200,0 +34663,Male,29,PhD,13,10,73,97,91,6.0,0,19,Urban,HR Executive,62413,0 +34664,Male,58,Bachelors,18,17,84,6,1,1.0,6,83,Urban,HR Executive,140085,0 +34665,Male,58,Masters,9,20,12,32,48,8.0,0,19,Urban,HR Executive,105904,0 +34666,Male,37,Bachelors,12,99,6,95,86,4.0,0,90,Urban,ML Engineer,133294,1 +34667,Male,23,Bachelors,5,28,68,0,62,1.0,1,55,Urban,Manager,140843,0 +34668,Female,55,Bachelors,3,50,56,36,64,6.0,6,74,Urban,Software Engineer,101100,0 +34669,Male,39,Bachelors,9,0,86,17,99,7.0,1,88,Urban,Data Analyst,113794,0 +34670,Female,48,High School,9,11,22,82,9,8.0,7,79,Urban,Manager,95668,0 +34671,Male,40,High School,11,58,36,2,31,8.0,3,78,Urban,Manager,75748,0 +34672,Male,25,Masters,13,3,60,0,71,4.0,2,17,Semi-Urban,Data Analyst,142597,0 +34673,Male,44,Bachelors,6,59,3,22,39,9.0,6,16,Rural,Manager,146192,0 +34674,Male,30,Bachelors,7,41,11,3,85,7.0,6,60,Semi-Urban,ML Engineer,29159,0 +34675,Female,51,Bachelors,5,63,44,97,35,2.0,0,84,Urban,Data Analyst,146196,1 +34676,Male,42,Masters,7,24,49,34,48,7.0,2,8,Semi-Urban,Manager,77584,0 +34677,Male,43,Diploma,9,61,6,78,84,5.0,5,58,Rural,ML Engineer,125411,0 +34678,Male,43,Bachelors,2,28,32,55,0,9.0,7,54,Semi-Urban,Data Analyst,50853,0 +34679,Male,52,PhD,0,77,31,12,90,0.0,2,67,Semi-Urban,Manager,46377,0 +34680,Male,29,Bachelors,10,5,11,36,79,9.0,1,25,Rural,Data Analyst,113582,0 +34681,Male,45,Masters,19,82,3,38,70,0.0,4,43,Urban,Data Analyst,98838,0 +34682,Male,49,Bachelors,11,97,88,96,68,1.0,0,15,Rural,Software Engineer,46829,1 +34683,Male,45,High School,12,32,98,16,44,8.0,5,9,Urban,HR Executive,144621,0 +34684,Male,34,Bachelors,15,59,32,31,34,5.0,0,51,Rural,ML Engineer,52098,0 +34685,Female,24,Bachelors,17,63,41,68,81,1.0,2,69,Semi-Urban,HR Executive,114492,1 +34686,Male,25,Bachelors,5,37,83,62,95,0.0,3,32,Rural,ML Engineer,75654,0 +34687,Male,34,Masters,7,23,66,77,55,1.0,0,84,Urban,ML Engineer,125736,1 +34688,Male,21,Masters,1,14,95,7,44,9.0,3,74,Urban,Software Engineer,117077,0 +34689,Male,50,Bachelors,7,18,39,76,73,6.0,3,67,Urban,Software Engineer,42817,0 +34690,Male,47,PhD,19,35,99,77,31,9.0,7,63,Urban,HR Executive,130520,1 +34691,Male,41,Masters,15,30,87,75,33,3.0,4,17,Urban,Manager,87677,0 +34692,Male,47,Diploma,7,29,72,22,38,1.0,1,11,Semi-Urban,HR Executive,44906,0 +34693,Male,59,PhD,13,22,68,40,4,4.0,3,39,Urban,Data Analyst,46226,0 +34694,Female,31,Masters,3,77,8,87,28,7.0,0,72,Urban,Manager,30178,1 +34695,Female,21,Bachelors,6,7,87,90,20,5.0,3,68,Urban,Software Engineer,101756,1 +34696,Male,57,Diploma,3,17,26,21,82,7.0,2,76,Urban,HR Executive,115897,0 +34697,Male,58,Masters,11,36,68,97,31,1.0,2,31,Semi-Urban,Data Analyst,42882,0 +34698,Female,47,Diploma,10,18,8,25,16,0.0,5,66,Urban,ML Engineer,125664,0 +34699,Female,24,Diploma,14,40,80,98,53,0.0,6,56,Semi-Urban,ML Engineer,104482,1 +34700,Other,22,Masters,4,26,17,71,3,7.0,1,71,Semi-Urban,Manager,55209,0 +34701,Male,22,Bachelors,19,27,8,41,30,3.0,1,40,Urban,Software Engineer,116652,0 +34702,Male,33,Bachelors,1,63,92,16,52,8.0,2,8,Urban,HR Executive,49859,0 +34703,Female,50,Bachelors,8,60,41,75,39,6.0,5,27,Urban,HR Executive,143918,0 +34704,Female,52,Diploma,13,31,80,86,95,7.0,3,5,Urban,ML Engineer,67558,0 +34705,Male,53,Bachelors,12,9,28,76,28,1.0,5,93,Urban,Manager,90324,0 +34706,Female,41,Bachelors,9,21,57,20,49,2.0,3,44,Semi-Urban,ML Engineer,64627,0 +34707,Male,25,Masters,16,18,6,81,33,8.0,1,40,Urban,Data Analyst,127170,0 +34708,Male,41,Masters,13,41,49,85,3,0.0,6,29,Urban,Manager,83420,0 +34709,Male,34,PhD,12,48,55,15,48,7.0,5,25,Urban,ML Engineer,27560,0 +34710,Male,22,Bachelors,17,49,23,36,4,9.0,3,55,Urban,HR Executive,141758,0 +34711,Female,45,Masters,18,54,35,8,45,8.0,5,90,Semi-Urban,Manager,54200,0 +34712,Female,27,Masters,19,11,23,42,60,8.0,4,10,Urban,HR Executive,55455,0 +34713,Female,39,Diploma,16,42,34,16,80,0.0,2,27,Semi-Urban,ML Engineer,130124,0 +34714,Male,31,High School,17,2,79,39,32,3.0,2,92,Urban,Software Engineer,35628,0 +34715,Male,23,Bachelors,8,78,75,31,60,3.0,7,29,Rural,Software Engineer,24569,0 +34716,Male,38,Masters,18,91,57,99,63,2.0,1,95,Urban,ML Engineer,110336,1 +34717,Male,56,Masters,1,50,26,25,76,1.0,7,77,Urban,ML Engineer,92525,0 +34718,Female,40,High School,0,43,32,1,6,4.0,5,80,Urban,HR Executive,125002,0 +34719,Male,25,Diploma,2,81,81,60,29,7.0,4,56,Urban,Manager,144843,1 +34720,Male,22,Bachelors,3,19,81,31,85,0.0,4,78,Urban,Software Engineer,40768,0 +34721,Male,49,Masters,13,29,26,71,9,6.0,0,5,Urban,Data Analyst,120454,0 +34722,Male,47,Bachelors,17,3,84,16,60,7.0,3,61,Urban,HR Executive,94072,0 +34723,Female,30,Masters,1,52,84,97,5,8.0,4,34,Urban,Data Analyst,59368,1 +34724,Male,29,Masters,12,27,11,10,88,6.0,0,39,Urban,ML Engineer,77182,0 +34725,Female,53,Masters,2,80,55,54,97,2.0,7,12,Urban,Manager,142233,0 +34726,Female,38,Masters,15,28,22,91,36,5.0,1,96,Urban,Software Engineer,59587,0 +34727,Male,59,Diploma,2,19,90,62,12,2.0,4,79,Urban,HR Executive,112672,1 +34728,Male,23,Bachelors,11,16,76,63,91,7.0,5,0,Semi-Urban,Data Analyst,37422,0 +34729,Female,34,Bachelors,1,34,4,64,52,2.0,7,27,Urban,ML Engineer,79877,0 +34730,Male,31,Bachelors,18,91,82,94,21,9.0,4,88,Rural,Manager,100004,1 +34731,Female,40,High School,10,85,40,70,38,0.0,1,62,Urban,Manager,92224,1 +34732,Male,45,Bachelors,15,72,78,40,58,3.0,6,90,Urban,Manager,93341,1 +34733,Male,52,High School,1,11,55,15,71,3.0,3,49,Urban,Manager,21922,0 +34734,Female,44,Bachelors,4,51,81,11,92,8.0,3,67,Semi-Urban,ML Engineer,81874,0 +34735,Male,34,PhD,18,12,5,36,89,5.0,5,32,Semi-Urban,ML Engineer,149257,0 +34736,Male,26,Bachelors,17,58,74,0,14,7.0,4,34,Urban,HR Executive,58594,0 +34737,Male,46,Bachelors,4,22,9,22,91,2.0,6,59,Semi-Urban,Data Analyst,123366,0 +34738,Male,43,Bachelors,10,46,39,12,88,8.0,6,56,Semi-Urban,HR Executive,41759,0 +34739,Male,54,PhD,15,73,35,30,29,9.0,4,16,Rural,Manager,122355,0 +34740,Male,58,Diploma,5,63,77,20,94,8.0,1,98,Urban,ML Engineer,91972,1 +34741,Male,47,Masters,14,10,14,76,45,1.0,1,5,Semi-Urban,Manager,107786,0 +34742,Female,41,Bachelors,4,44,26,13,96,6.0,4,82,Urban,Manager,58441,0 +34743,Male,21,Diploma,4,86,82,60,71,8.0,0,31,Semi-Urban,ML Engineer,53253,1 +34744,Male,21,High School,9,37,59,1,37,7.0,1,46,Rural,Data Analyst,98810,0 +34745,Male,24,Masters,13,47,36,8,90,2.0,1,35,Rural,Software Engineer,81029,0 +34746,Male,30,Bachelors,13,20,21,2,71,4.0,5,14,Semi-Urban,Data Analyst,44934,0 +34747,Male,31,High School,16,21,38,12,4,2.0,3,21,Urban,Software Engineer,120295,0 +34748,Male,24,Bachelors,3,83,34,54,57,1.0,6,92,Urban,Manager,142580,1 +34749,Female,46,Bachelors,6,33,72,49,99,3.0,5,70,Urban,ML Engineer,96599,0 +34750,Male,28,Masters,8,44,3,76,55,7.0,2,38,Semi-Urban,ML Engineer,95826,0 +34751,Male,26,Masters,14,28,66,7,32,6.0,3,80,Semi-Urban,HR Executive,90829,0 +34752,Female,43,High School,13,26,95,90,85,1.0,7,25,Urban,Software Engineer,106115,0 +34753,Male,24,Bachelors,10,15,46,1,92,3.0,3,75,Urban,HR Executive,89791,0 +34754,Female,46,Diploma,17,86,69,59,42,8.0,1,84,Semi-Urban,Software Engineer,31675,1 +34755,Male,46,Bachelors,10,11,86,77,25,8.0,0,16,Urban,Manager,50497,0 +34756,Female,47,Diploma,7,32,52,55,81,7.0,3,57,Semi-Urban,Data Analyst,93126,0 +34757,Female,28,Bachelors,9,62,78,73,87,7.0,7,53,Semi-Urban,Manager,97788,1 +34758,Female,42,PhD,14,3,64,91,90,3.0,7,38,Urban,Manager,80239,0 +34759,Male,58,Bachelors,12,48,86,3,36,7.0,0,26,Urban,Manager,66395,0 +34760,Female,28,Masters,2,75,99,13,80,5.0,1,96,Semi-Urban,Data Analyst,119407,1 +34761,Male,43,Bachelors,5,89,26,94,80,5.0,3,84,Urban,Software Engineer,24418,1 +34762,Female,32,Bachelors,10,32,36,5,12,4.0,5,49,Semi-Urban,Data Analyst,106650,0 +34763,Male,39,Bachelors,13,33,49,10,82,1.0,5,61,Semi-Urban,Data Analyst,106476,0 +34764,Male,40,Bachelors,16,54,29,29,94,3.0,3,68,Urban,ML Engineer,22931,0 +34765,Male,53,Bachelors,18,41,36,13,98,5.0,1,10,Urban,Software Engineer,29172,0 +34766,Male,30,Diploma,4,81,51,5,78,3.0,0,71,Rural,Software Engineer,144473,0 +34767,Male,31,Bachelors,16,13,8,83,87,0.0,5,83,Urban,HR Executive,120464,0 +34768,Female,54,Diploma,11,86,11,15,82,7.0,4,65,Semi-Urban,Manager,98229,0 +34769,Male,27,Bachelors,12,78,30,59,49,5.0,1,22,Rural,Data Analyst,65469,0 +34770,Female,40,Bachelors,1,46,32,30,93,2.0,5,17,Rural,Manager,41998,0 +34771,Male,26,Diploma,13,34,8,71,35,9.0,0,99,Urban,Manager,58260,0 +34772,Male,41,Diploma,11,20,28,89,64,1.0,0,27,Urban,Data Analyst,28515,0 +34773,Male,54,Masters,10,78,6,33,75,2.0,6,96,Urban,Manager,73912,0 +34774,Male,48,Bachelors,15,62,6,70,21,9.0,3,71,Rural,Data Analyst,124857,0 +34775,Male,32,Bachelors,17,21,22,52,57,4.0,5,35,Urban,HR Executive,135337,0 +34776,Other,42,PhD,18,89,12,49,23,4.0,0,69,Urban,HR Executive,141445,0 +34777,Male,21,Masters,14,40,78,39,26,4.0,6,58,Semi-Urban,HR Executive,57974,0 +34778,Female,34,Diploma,19,14,14,31,61,5.0,5,77,Semi-Urban,Manager,114576,0 +34779,Male,57,Bachelors,18,64,85,25,68,2.0,7,89,Rural,Data Analyst,135296,1 +34780,Female,48,Masters,3,97,38,26,39,6.0,2,11,Urban,Software Engineer,35063,0 +34781,Male,58,Diploma,17,48,31,59,26,7.0,5,42,Urban,Software Engineer,44986,0 +34782,Female,26,High School,18,44,68,3,82,0.0,3,6,Semi-Urban,Data Analyst,147646,0 +34783,Male,27,High School,4,97,80,92,49,4.0,1,57,Urban,HR Executive,59636,1 +34784,Male,51,Bachelors,12,64,93,29,22,1.0,3,96,Semi-Urban,Data Analyst,119942,1 +34785,Male,24,Bachelors,5,19,26,42,85,2.0,7,95,Semi-Urban,Software Engineer,45202,0 +34786,Male,46,Bachelors,11,26,32,93,19,4.0,1,20,Urban,ML Engineer,103486,0 +34787,Male,47,Bachelors,14,89,26,43,59,3.0,5,13,Semi-Urban,Data Analyst,90557,0 +34788,Male,59,Masters,13,29,15,87,5,2.0,0,50,Urban,Software Engineer,87751,0 +34789,Female,44,Bachelors,3,15,58,66,96,1.0,0,87,Semi-Urban,HR Executive,34815,0 +34790,Male,54,Diploma,2,11,60,31,10,5.0,0,49,Rural,Data Analyst,29338,0 +34791,Male,42,Bachelors,2,89,30,2,4,0.0,2,30,Urban,Software Engineer,29255,0 +34792,Male,21,High School,2,68,50,72,29,3.0,1,58,Urban,ML Engineer,148523,1 +34793,Female,43,Bachelors,11,52,60,70,67,1.0,0,89,Urban,HR Executive,119400,1 +34794,Male,47,Bachelors,2,73,63,53,13,1.0,3,86,Urban,Software Engineer,131630,1 +34795,Male,34,PhD,0,27,13,61,79,7.0,1,22,Rural,Software Engineer,102449,0 +34796,Male,31,Bachelors,16,83,95,89,14,5.0,0,29,Urban,Data Analyst,29862,1 +34797,Male,44,Diploma,10,87,34,17,23,2.0,5,14,Semi-Urban,HR Executive,129420,0 +34798,Male,44,Bachelors,18,19,23,76,45,4.0,5,49,Urban,ML Engineer,116892,0 +34799,Female,57,Bachelors,8,43,0,49,31,2.0,7,68,Semi-Urban,Manager,77035,0 +34800,Male,36,Masters,8,99,95,94,74,3.0,4,42,Urban,HR Executive,92614,1 +34801,Male,28,Bachelors,10,25,63,21,67,0.0,3,39,Semi-Urban,Manager,116279,0 +34802,Female,27,High School,5,62,78,58,46,2.0,7,22,Rural,ML Engineer,85487,0 +34803,Male,30,Bachelors,9,75,9,12,77,1.0,1,56,Semi-Urban,HR Executive,73377,0 +34804,Female,38,High School,6,2,46,50,3,3.0,0,8,Urban,Software Engineer,82684,0 +34805,Other,58,Masters,7,63,78,20,73,3.0,7,87,Urban,Manager,55064,1 +34806,Other,25,High School,2,29,50,91,77,5.0,3,56,Urban,Data Analyst,86940,0 +34807,Male,57,Diploma,12,39,57,76,8,2.0,4,2,Urban,ML Engineer,117960,0 +34808,Male,28,Bachelors,16,94,63,48,25,7.0,7,67,Urban,ML Engineer,69267,1 +34809,Female,57,Bachelors,4,37,70,8,57,7.0,4,90,Semi-Urban,Software Engineer,69821,0 +34810,Male,28,Diploma,0,12,1,14,98,4.0,7,47,Semi-Urban,Software Engineer,105284,0 +34811,Male,29,Diploma,13,57,24,82,54,9.0,3,82,Urban,Manager,147360,1 +34812,Male,31,PhD,9,30,89,37,87,8.0,2,3,Urban,ML Engineer,119986,0 +34813,Male,28,High School,0,93,98,10,56,9.0,7,68,Semi-Urban,Software Engineer,109708,1 +34814,Other,50,High School,10,59,46,52,17,3.0,5,84,Urban,Manager,80688,1 +34815,Female,52,Masters,16,64,3,42,80,2.0,4,77,Urban,ML Engineer,67686,0 +34816,Male,47,Diploma,19,66,80,25,16,1.0,4,35,Rural,Manager,36729,0 +34817,Female,22,Diploma,3,18,21,22,73,5.0,7,5,Urban,HR Executive,78018,0 +34818,Male,32,Diploma,12,83,66,62,82,3.0,7,92,Semi-Urban,ML Engineer,88617,1 +34819,Female,56,Bachelors,15,18,11,48,43,1.0,4,90,Urban,Software Engineer,84169,0 +34820,Male,44,High School,4,30,44,47,13,5.0,0,40,Semi-Urban,Manager,82807,0 +34821,Male,51,Diploma,9,60,17,21,9,4.0,6,47,Rural,ML Engineer,21087,0 +34822,Male,30,Masters,8,90,14,77,81,5.0,0,77,Semi-Urban,Software Engineer,66443,1 +34823,Male,38,Diploma,9,74,43,33,62,7.0,6,52,Rural,HR Executive,27654,0 +34824,Male,27,Diploma,2,67,51,82,96,8.0,6,26,Urban,ML Engineer,20871,0 +34825,Male,42,High School,16,22,15,51,13,3.0,7,13,Urban,HR Executive,97404,0 +34826,Other,52,Masters,18,22,6,2,16,9.0,3,25,Urban,HR Executive,39702,0 +34827,Female,37,Bachelors,3,28,40,30,22,4.0,3,99,Urban,ML Engineer,120188,0 +34828,Female,29,Bachelors,10,70,21,76,93,4.0,2,60,Urban,Manager,143499,0 +34829,Female,39,Bachelors,11,86,17,66,45,6.0,7,83,Urban,Manager,121667,1 +34830,Female,21,Masters,9,6,10,42,19,5.0,3,27,Urban,Manager,74890,0 +34831,Female,50,Bachelors,3,31,96,9,32,3.0,6,7,Urban,Software Engineer,122266,0 +34832,Male,48,Masters,14,61,35,91,94,2.0,2,74,Rural,Data Analyst,136080,1 +34833,Female,50,Bachelors,5,46,45,61,74,3.0,3,1,Semi-Urban,Software Engineer,140090,0 +34834,Male,47,Bachelors,13,15,29,22,28,6.0,6,12,Semi-Urban,Manager,79382,0 +34835,Male,56,Bachelors,9,31,67,54,99,4.0,6,11,Urban,Manager,123847,0 +34836,Male,54,PhD,5,84,15,61,62,9.0,7,42,Urban,ML Engineer,89662,0 +34837,Male,43,Masters,10,61,79,34,60,8.0,3,71,Semi-Urban,Data Analyst,42456,1 +34838,Female,34,Masters,5,67,23,96,97,6.0,0,44,Urban,Data Analyst,41112,0 +34839,Female,54,Masters,4,22,23,33,49,5.0,4,87,Urban,Manager,29555,0 +34840,Female,52,Masters,0,60,61,10,12,2.0,1,12,Urban,Manager,75443,0 +34841,Female,32,Bachelors,17,95,25,8,15,3.0,0,52,Urban,Data Analyst,55548,0 +34842,Male,34,Bachelors,17,17,57,37,2,1.0,5,3,Urban,Manager,71154,0 +34843,Female,57,Bachelors,19,9,67,84,14,4.0,3,35,Urban,HR Executive,134951,0 +34844,Male,39,Diploma,9,58,6,53,37,5.0,5,89,Rural,Manager,66026,0 +34845,Male,35,Bachelors,19,43,20,89,29,1.0,2,66,Urban,Data Analyst,47487,0 +34846,Female,43,Diploma,3,35,53,97,88,9.0,3,67,Rural,Manager,56390,1 +34847,Female,25,Bachelors,5,49,50,21,34,1.0,2,4,Urban,ML Engineer,113973,0 +34848,Female,24,Diploma,8,48,64,47,29,8.0,1,41,Semi-Urban,HR Executive,145035,0 +34849,Male,50,Bachelors,12,98,71,89,26,4.0,6,65,Rural,Data Analyst,117287,1 +34850,Female,30,Bachelors,3,98,91,29,35,1.0,7,16,Urban,Software Engineer,73354,0 +34851,Male,29,Bachelors,4,64,85,65,59,4.0,7,25,Rural,Data Analyst,37040,1 +34852,Male,51,Masters,4,68,44,63,73,4.0,1,84,Semi-Urban,Software Engineer,83321,1 +34853,Male,27,Masters,3,20,58,70,48,9.0,4,7,Urban,ML Engineer,71660,0 +34854,Male,47,Masters,10,0,82,76,50,5.0,0,19,Urban,Manager,53503,0 +34855,Male,41,Bachelors,3,26,85,20,58,3.0,3,3,Urban,Manager,141222,0 +34856,Male,36,Bachelors,13,71,56,76,82,7.0,5,16,Semi-Urban,HR Executive,116721,0 +34857,Female,38,High School,2,38,21,70,80,2.0,4,82,Semi-Urban,ML Engineer,100950,0 +34858,Male,56,Bachelors,2,8,37,36,73,1.0,4,37,Urban,Manager,118439,0 +34859,Male,34,Bachelors,12,34,24,41,62,6.0,1,10,Semi-Urban,HR Executive,123689,0 +34860,Male,42,Bachelors,15,49,81,52,98,3.0,3,71,Semi-Urban,Software Engineer,79686,1 +34861,Female,32,Diploma,6,32,59,91,34,7.0,6,83,Semi-Urban,HR Executive,130662,1 +34862,Female,41,Bachelors,2,8,16,78,12,3.0,0,40,Urban,HR Executive,70404,0 +34863,Male,42,Diploma,11,49,50,40,58,4.0,5,33,Urban,Software Engineer,138099,0 +34864,Male,39,Bachelors,12,10,78,64,82,7.0,7,54,Urban,HR Executive,117962,0 +34865,Male,52,Diploma,2,94,5,1,7,2.0,6,36,Urban,Manager,127186,0 +34866,Male,45,High School,15,45,41,68,62,2.0,4,85,Urban,Data Analyst,22860,1 +34867,Male,23,Diploma,16,22,41,30,89,8.0,4,7,Urban,Software Engineer,105334,0 +34868,Male,49,Bachelors,15,50,85,38,61,5.0,4,51,Semi-Urban,Manager,46080,0 +34869,Male,22,Bachelors,12,63,77,10,25,6.0,5,43,Semi-Urban,ML Engineer,116378,0 +34870,Female,46,Masters,15,66,73,36,52,3.0,7,42,Urban,Software Engineer,91341,0 +34871,Male,56,Bachelors,3,27,45,53,88,5.0,7,10,Urban,ML Engineer,44792,0 +34872,Male,55,Bachelors,14,76,53,93,57,8.0,6,22,Urban,Software Engineer,142676,1 +34873,Female,48,Bachelors,1,41,61,23,81,0.0,5,27,Urban,ML Engineer,48724,0 +34874,Female,34,Bachelors,9,68,3,88,25,8.0,4,47,Urban,Manager,79034,0 +34875,Female,42,Diploma,15,27,56,89,94,3.0,7,54,Urban,Data Analyst,32287,0 +34876,Male,43,Diploma,3,2,89,88,60,6.0,6,75,Urban,HR Executive,110815,1 +34877,Male,52,Diploma,17,59,93,12,22,5.0,0,68,Urban,Manager,112357,0 +34878,Male,54,Bachelors,5,79,11,54,3,7.0,1,58,Urban,HR Executive,130025,0 +34879,Male,25,Masters,7,50,97,80,61,6.0,6,59,Urban,ML Engineer,135937,1 +34880,Male,39,High School,17,85,99,74,41,2.0,5,59,Urban,ML Engineer,149616,1 +34881,Female,55,Bachelors,12,62,7,79,5,9.0,4,62,Semi-Urban,Software Engineer,29623,0 +34882,Other,51,High School,6,34,83,36,54,0.0,4,5,Urban,Data Analyst,62552,0 +34883,Female,31,Masters,2,10,18,46,23,4.0,5,77,Semi-Urban,Data Analyst,124787,0 +34884,Female,49,Bachelors,15,90,83,38,59,6.0,4,31,Semi-Urban,Manager,148025,1 +34885,Male,51,PhD,15,69,80,90,59,0.0,2,47,Urban,Software Engineer,72832,1 +34886,Female,30,Bachelors,6,50,5,14,69,6.0,0,85,Rural,HR Executive,141031,0 +34887,Female,42,High School,0,19,91,48,34,2.0,5,63,Urban,Software Engineer,100012,0 +34888,Female,37,PhD,14,12,11,40,18,8.0,3,48,Urban,Software Engineer,102403,0 +34889,Male,31,Bachelors,0,29,26,45,33,6.0,2,27,Urban,HR Executive,93985,0 +34890,Male,23,Diploma,14,72,50,4,60,9.0,2,53,Semi-Urban,HR Executive,90294,0 +34891,Male,25,Bachelors,3,83,3,88,80,4.0,7,83,Urban,ML Engineer,143118,1 +34892,Male,32,Masters,19,12,16,38,26,9.0,2,4,Urban,HR Executive,23989,0 +34893,Female,40,Bachelors,13,72,94,16,77,8.0,1,80,Semi-Urban,Data Analyst,76381,1 +34894,Female,53,Bachelors,13,32,89,22,23,4.0,4,34,Rural,Data Analyst,24201,0 +34895,Female,21,Masters,12,81,68,59,17,8.0,6,59,Semi-Urban,ML Engineer,123119,1 +34896,Male,26,Bachelors,11,97,29,31,9,3.0,6,51,Rural,HR Executive,91711,0 +34897,Male,30,Bachelors,8,42,69,14,56,1.0,5,21,Urban,Software Engineer,133644,0 +34898,Male,33,PhD,5,71,73,9,1,0.0,5,12,Urban,HR Executive,45237,0 +34899,Female,30,PhD,13,90,75,35,85,9.0,1,63,Urban,Software Engineer,92726,1 +34900,Male,37,Bachelors,9,26,44,0,55,0.0,4,43,Urban,Manager,121396,0 +34901,Other,30,Bachelors,18,28,46,53,49,6.0,3,76,Urban,Data Analyst,102324,0 +34902,Female,28,Diploma,19,36,76,35,68,8.0,4,71,Urban,Software Engineer,144077,0 +34903,Female,35,Masters,17,88,1,88,13,8.0,7,8,Urban,Software Engineer,142050,0 +34904,Female,46,High School,18,42,26,36,61,1.0,0,24,Urban,Software Engineer,118033,0 +34905,Other,22,Masters,12,4,90,20,64,7.0,3,65,Semi-Urban,Software Engineer,34184,0 +34906,Male,41,High School,1,72,28,25,37,9.0,5,81,Urban,Data Analyst,55873,0 +34907,Female,28,Masters,13,7,99,31,18,4.0,1,93,Semi-Urban,HR Executive,81247,0 +34908,Male,37,Diploma,14,92,5,40,5,1.0,2,90,Urban,Data Analyst,36249,0 +34909,Male,44,Bachelors,12,38,43,37,22,5.0,1,39,Semi-Urban,ML Engineer,140711,0 +34910,Male,41,High School,11,54,36,71,88,2.0,6,39,Urban,Software Engineer,137305,0 +34911,Female,21,Bachelors,14,14,58,71,10,5.0,0,81,Rural,Manager,80453,0 +34912,Male,44,Bachelors,15,28,29,24,3,6.0,5,22,Semi-Urban,HR Executive,111206,0 +34913,Female,23,Bachelors,8,0,25,39,49,1.0,7,87,Urban,ML Engineer,58221,0 +34914,Female,53,Bachelors,18,51,88,70,47,0.0,3,50,Urban,Data Analyst,144783,1 +34915,Female,48,Masters,5,50,93,66,79,4.0,6,4,Urban,Data Analyst,96874,0 +34916,Male,34,Masters,8,20,56,93,35,2.0,6,68,Rural,Manager,67375,1 +34917,Female,49,Bachelors,11,57,24,22,10,5.0,0,86,Urban,ML Engineer,135850,0 +34918,Male,23,Bachelors,17,31,52,22,74,0.0,5,10,Urban,Data Analyst,27942,0 +34919,Male,44,Masters,11,0,72,53,62,1.0,1,18,Rural,Software Engineer,149336,0 +34920,Other,46,Masters,13,13,81,87,49,6.0,2,43,Rural,ML Engineer,29273,0 +34921,Male,44,High School,15,61,1,3,11,0.0,5,44,Semi-Urban,Manager,148326,0 +34922,Male,33,Masters,9,10,33,67,57,1.0,2,23,Rural,Data Analyst,72618,0 +34923,Female,34,Bachelors,9,50,29,89,2,1.0,3,8,Urban,ML Engineer,52790,0 +34924,Male,31,Masters,16,68,24,30,36,5.0,5,43,Urban,Manager,116440,0 +34925,Male,24,PhD,2,28,99,28,41,7.0,0,71,Semi-Urban,Software Engineer,121925,0 +34926,Female,23,Masters,6,8,96,20,75,5.0,4,27,Semi-Urban,Data Analyst,42476,0 +34927,Male,58,Bachelors,7,2,66,71,44,9.0,0,2,Urban,ML Engineer,122868,0 +34928,Male,32,Masters,6,81,52,58,65,7.0,3,91,Semi-Urban,Data Analyst,40803,1 +34929,Female,59,Masters,10,30,6,27,93,4.0,7,65,Semi-Urban,Manager,83950,0 +34930,Female,21,Diploma,19,28,57,58,36,8.0,5,27,Urban,Data Analyst,32406,0 +34931,Female,34,Bachelors,17,15,43,96,2,5.0,5,15,Urban,Data Analyst,102581,0 +34932,Female,42,Bachelors,14,8,8,25,16,9.0,7,74,Urban,ML Engineer,142775,0 +34933,Male,44,High School,15,83,97,40,49,3.0,6,53,Urban,Software Engineer,144363,1 +34934,Female,33,Bachelors,6,66,67,83,60,2.0,5,47,Semi-Urban,Software Engineer,114654,1 +34935,Female,25,Bachelors,10,17,74,68,34,9.0,5,39,Semi-Urban,HR Executive,109306,0 +34936,Male,55,Bachelors,12,68,19,34,19,2.0,0,72,Rural,Data Analyst,124653,0 +34937,Other,45,Diploma,4,86,90,1,5,2.0,6,32,Urban,HR Executive,83115,0 +34938,Female,41,Bachelors,8,80,20,7,50,0.0,2,7,Semi-Urban,Manager,80245,0 +34939,Male,57,Bachelors,12,11,33,12,37,1.0,0,28,Urban,ML Engineer,23726,0 +34940,Female,49,Diploma,2,66,44,36,16,1.0,6,65,Urban,ML Engineer,145306,0 +34941,Female,41,Masters,12,26,64,62,42,9.0,0,61,Urban,Data Analyst,107767,0 +34942,Male,47,Bachelors,9,12,12,69,17,0.0,1,82,Urban,Data Analyst,110372,0 +34943,Female,41,Bachelors,4,64,98,24,4,1.0,2,38,Urban,Software Engineer,131912,0 +34944,Female,42,PhD,1,63,55,28,64,0.0,6,92,Rural,Data Analyst,142365,0 +34945,Female,35,High School,9,77,15,91,80,1.0,5,7,Rural,HR Executive,24939,0 +34946,Male,38,Diploma,2,56,43,30,5,3.0,7,47,Urban,HR Executive,73542,0 +34947,Male,54,PhD,16,70,1,5,30,0.0,7,86,Urban,ML Engineer,116295,0 +34948,Male,22,Diploma,0,5,70,4,12,9.0,7,80,Rural,ML Engineer,53657,0 +34949,Female,50,Bachelors,12,71,26,87,31,6.0,3,52,Urban,Manager,21786,0 +34950,Female,22,Diploma,6,12,50,96,76,8.0,6,44,Rural,HR Executive,89749,0 +34951,Male,55,High School,6,86,24,96,69,5.0,4,62,Semi-Urban,HR Executive,69264,1 +34952,Male,50,Bachelors,2,43,74,5,88,3.0,4,50,Urban,Manager,61298,0 +34953,Male,37,Bachelors,8,55,19,85,60,6.0,2,48,Urban,Data Analyst,67738,0 +34954,Female,33,Bachelors,8,62,99,98,59,6.0,4,83,Rural,Software Engineer,55496,1 +34955,Female,53,Diploma,9,72,69,50,15,5.0,0,9,Urban,HR Executive,95605,0 +34956,Male,35,Bachelors,1,62,72,54,49,1.0,5,51,Urban,Software Engineer,128340,1 +34957,Male,23,Masters,4,92,48,92,45,5.0,2,11,Urban,ML Engineer,40412,1 +34958,Male,53,Bachelors,0,28,55,34,22,4.0,6,60,Semi-Urban,HR Executive,64520,0 +34959,Male,31,PhD,9,32,80,22,54,0.0,4,16,Urban,HR Executive,91660,0 +34960,Female,31,Diploma,1,95,31,34,39,1.0,7,72,Semi-Urban,Manager,74750,0 +34961,Male,46,High School,16,97,13,90,7,6.0,3,0,Urban,Manager,115958,0 +34962,Male,41,High School,19,74,97,47,10,9.0,4,72,Urban,Data Analyst,39143,1 +34963,Female,59,High School,0,40,70,30,52,0.0,0,93,Rural,Data Analyst,24606,0 +34964,Other,50,Bachelors,1,58,30,99,0,2.0,3,26,Rural,HR Executive,66156,0 +34965,Other,50,Masters,6,84,68,87,37,2.0,0,31,Rural,Data Analyst,139598,1 +34966,Other,34,Bachelors,9,50,71,30,61,0.0,3,44,Urban,Software Engineer,86498,0 +34967,Female,59,Masters,2,93,56,10,16,4.0,1,72,Urban,Manager,81230,0 +34968,Female,59,PhD,0,34,31,52,3,8.0,1,67,Urban,HR Executive,97670,0 +34969,Female,33,Bachelors,2,44,52,61,62,9.0,6,97,Semi-Urban,HR Executive,104940,1 +34970,Female,34,Diploma,16,28,1,61,60,1.0,4,13,Urban,ML Engineer,136438,0 +34971,Other,49,Bachelors,2,24,8,59,42,5.0,6,13,Urban,HR Executive,45403,0 +34972,Male,54,Bachelors,0,76,69,17,63,0.0,7,11,Semi-Urban,Software Engineer,55957,0 +34973,Male,23,Masters,10,88,84,33,79,6.0,3,35,Semi-Urban,HR Executive,78969,1 +34974,Male,58,Diploma,15,83,85,58,80,3.0,0,69,Urban,ML Engineer,115661,1 +34975,Female,36,PhD,9,19,98,26,65,1.0,5,24,Urban,Software Engineer,117517,0 +34976,Female,34,Diploma,16,60,9,55,15,3.0,3,49,Rural,HR Executive,109240,0 +34977,Female,55,Diploma,9,48,79,67,84,7.0,0,57,Semi-Urban,HR Executive,134223,1 +34978,Male,46,Bachelors,13,77,36,38,24,1.0,2,15,Semi-Urban,HR Executive,126677,0 +34979,Male,57,Bachelors,19,19,56,88,2,6.0,2,76,Urban,Data Analyst,73169,1 +34980,Other,51,Bachelors,10,31,17,50,20,7.0,7,55,Urban,Data Analyst,84881,0 +34981,Male,53,Bachelors,13,81,87,89,33,2.0,3,40,Urban,Data Analyst,67159,1 +34982,Male,52,High School,19,60,19,14,5,8.0,3,61,Rural,HR Executive,102688,0 +34983,Female,48,Diploma,11,81,45,39,9,3.0,0,25,Semi-Urban,Data Analyst,36028,0 +34984,Male,27,Diploma,4,20,40,89,51,1.0,4,25,Rural,Manager,84799,0 +34985,Male,30,Bachelors,4,94,89,60,5,1.0,4,46,Urban,HR Executive,122281,1 +34986,Male,41,Masters,14,48,54,70,99,0.0,7,33,Semi-Urban,HR Executive,28871,0 +34987,Male,48,Bachelors,19,17,94,45,24,9.0,5,44,Semi-Urban,ML Engineer,71479,0 +34988,Male,33,Masters,5,28,93,53,71,3.0,2,47,Semi-Urban,HR Executive,90846,0 +34989,Male,42,High School,12,12,16,62,3,6.0,6,18,Urban,ML Engineer,99089,0 +34990,Male,41,Bachelors,8,98,34,35,70,5.0,0,12,Urban,Data Analyst,50858,0 +34991,Male,46,Bachelors,14,11,44,43,13,9.0,7,60,Rural,HR Executive,62578,0 +34992,Female,32,High School,4,31,81,75,87,9.0,3,76,Rural,HR Executive,92649,1 +34993,Male,22,Bachelors,19,51,41,94,85,7.0,4,60,Urban,Software Engineer,48771,1 +34994,Male,55,Bachelors,12,16,77,62,83,9.0,5,28,Urban,ML Engineer,23102,0 +34995,Male,37,Bachelors,18,77,18,59,45,8.0,7,38,Urban,Manager,144329,0 +34996,Male,32,Masters,14,38,10,37,70,5.0,7,86,Semi-Urban,HR Executive,81548,0 +34997,Male,38,Bachelors,13,55,42,92,43,8.0,2,14,Urban,Data Analyst,74950,0 +34998,Male,26,Masters,14,3,58,40,89,2.0,0,67,Urban,Software Engineer,88975,0 +34999,Other,34,Bachelors,8,66,69,43,48,7.0,3,13,Urban,Software Engineer,46242,0 +35000,Female,39,Diploma,19,32,0,37,84,7.0,4,53,Semi-Urban,HR Executive,75081,0 +35001,Female,49,Masters,10,49,82,98,72,8.0,5,9,Urban,ML Engineer,91498,0 +35002,Male,27,Diploma,8,36,83,7,7,5.0,0,75,Semi-Urban,Manager,86368,0 +35003,Female,51,Bachelors,17,61,4,56,2,6.0,5,79,Urban,Software Engineer,114037,0 +35004,Male,26,High School,6,80,82,12,33,1.0,6,56,Semi-Urban,Manager,66952,0 +35005,Female,56,Masters,15,3,90,90,84,9.0,4,63,Urban,Manager,122055,1 +35006,Male,45,Bachelors,9,62,38,77,86,8.0,2,87,Rural,ML Engineer,148555,1 +35007,Female,41,Bachelors,10,47,16,84,78,6.0,2,85,Rural,Software Engineer,75650,0 +35008,Female,36,Masters,2,6,61,80,52,9.0,6,58,Urban,Manager,95364,0 +35009,Male,25,Diploma,15,70,96,44,17,8.0,1,36,Rural,HR Executive,146949,1 +35010,Male,39,Bachelors,2,46,81,49,48,7.0,3,39,Rural,Software Engineer,80277,0 +35011,Male,47,Diploma,9,45,45,19,4,0.0,7,61,Urban,Data Analyst,44206,0 +35012,Male,55,Bachelors,11,73,11,16,96,1.0,4,65,Urban,Manager,96584,0 +35013,Female,27,Bachelors,6,81,13,96,46,7.0,0,45,Urban,Manager,140124,0 +35014,Male,24,Diploma,6,26,32,40,88,3.0,3,48,Urban,Data Analyst,47712,0 +35015,Male,50,Masters,19,9,80,66,54,5.0,7,96,Rural,Manager,50180,1 +35016,Female,48,Diploma,11,65,80,10,62,0.0,3,85,Semi-Urban,HR Executive,105864,0 +35017,Male,53,Bachelors,7,78,79,21,22,7.0,0,75,Rural,Software Engineer,128406,1 +35018,Male,36,Masters,18,61,59,49,71,8.0,1,56,Urban,Manager,21516,0 +35019,Male,47,High School,9,69,32,84,83,6.0,2,43,Semi-Urban,HR Executive,52041,0 +35020,Female,34,Bachelors,13,79,47,57,82,9.0,7,19,Urban,Data Analyst,89133,0 +35021,Male,38,Bachelors,15,89,52,81,40,6.0,7,89,Urban,Manager,28571,1 +35022,Female,38,Diploma,11,11,63,34,26,3.0,5,19,Urban,ML Engineer,110654,0 +35023,Male,42,PhD,13,35,81,29,33,4.0,3,44,Semi-Urban,Software Engineer,115148,0 +35024,Male,24,PhD,12,34,21,52,45,9.0,4,26,Semi-Urban,Manager,132404,0 +35025,Male,40,High School,9,47,90,29,11,6.0,0,18,Semi-Urban,Data Analyst,45167,0 +35026,Other,36,High School,4,42,91,78,95,9.0,5,89,Semi-Urban,Manager,122035,1 +35027,Male,51,Masters,12,21,50,8,19,5.0,4,93,Semi-Urban,ML Engineer,54404,0 +35028,Male,28,High School,10,95,64,30,81,0.0,6,9,Rural,ML Engineer,106473,0 +35029,Female,32,Bachelors,9,67,80,26,9,2.0,7,72,Rural,HR Executive,29715,1 +35030,Other,40,Bachelors,2,33,57,26,96,1.0,6,66,Urban,Manager,88148,0 +35031,Female,35,Bachelors,19,27,75,33,63,2.0,7,2,Urban,Software Engineer,95188,0 +35032,Male,58,High School,4,47,60,83,15,5.0,0,99,Urban,HR Executive,80798,1 +35033,Male,48,Masters,11,12,58,7,48,5.0,6,90,Urban,ML Engineer,117368,0 +35034,Male,37,Bachelors,12,31,41,58,67,8.0,0,99,Urban,Manager,84443,0 +35035,Female,36,Masters,14,93,65,35,41,0.0,5,6,Semi-Urban,ML Engineer,67946,0 +35036,Male,28,Masters,5,49,42,27,36,2.0,3,39,Urban,Manager,78960,0 +35037,Male,32,Diploma,13,8,96,93,90,0.0,1,8,Semi-Urban,ML Engineer,136417,0 +35038,Male,41,Bachelors,15,3,34,68,20,1.0,6,57,Semi-Urban,Manager,69698,0 +35039,Male,50,High School,0,57,90,47,83,9.0,7,2,Urban,Manager,70190,0 +35040,Female,44,Bachelors,9,65,26,39,91,5.0,3,22,Urban,Software Engineer,42490,0 +35041,Female,56,Bachelors,2,28,61,3,75,8.0,6,55,Urban,Data Analyst,94868,0 +35042,Female,53,Bachelors,10,29,41,82,42,6.0,1,89,Urban,ML Engineer,59862,1 +35043,Male,32,Bachelors,12,23,14,21,7,5.0,7,8,Urban,Data Analyst,87892,0 +35044,Female,46,Masters,17,62,85,8,96,6.0,0,99,Urban,Manager,86109,1 +35045,Male,24,Masters,8,15,62,53,90,0.0,2,16,Rural,ML Engineer,144542,0 +35046,Male,39,Bachelors,5,61,34,3,91,7.0,6,70,Urban,ML Engineer,105712,0 +35047,Male,58,High School,9,82,77,17,62,7.0,6,15,Urban,Data Analyst,125526,0 +35048,Male,47,Masters,10,64,36,92,27,8.0,0,30,Urban,ML Engineer,107795,0 +35049,Male,22,PhD,14,93,88,94,66,0.0,2,18,Urban,ML Engineer,96080,1 +35050,Male,25,Masters,6,99,80,60,70,8.0,5,45,Urban,Manager,52550,1 +35051,Female,35,Bachelors,4,23,49,54,44,7.0,4,30,Urban,Manager,39979,0 +35052,Female,57,High School,14,11,24,59,39,9.0,0,20,Rural,ML Engineer,118594,0 +35053,Male,58,Diploma,13,18,23,98,89,2.0,1,91,Urban,Data Analyst,105884,0 +35054,Male,55,Masters,11,30,17,87,15,9.0,6,14,Semi-Urban,Manager,59445,0 +35055,Male,36,Diploma,19,17,9,65,68,0.0,2,15,Urban,Data Analyst,82146,0 +35056,Male,29,Masters,7,92,19,74,11,3.0,1,11,Urban,Manager,76720,0 +35057,Male,42,Bachelors,15,20,3,20,72,2.0,2,2,Urban,HR Executive,30403,0 +35058,Male,47,Bachelors,5,60,60,40,75,0.0,0,58,Semi-Urban,HR Executive,132396,0 +35059,Female,32,Masters,15,73,64,44,5,4.0,0,36,Rural,Data Analyst,55246,0 +35060,Male,25,Masters,13,30,30,25,4,1.0,5,18,Rural,Data Analyst,136101,0 +35061,Male,59,Masters,6,18,80,17,10,0.0,3,34,Rural,Data Analyst,64222,0 +35062,Female,44,Diploma,3,53,46,31,48,1.0,1,55,Urban,Manager,128317,0 +35063,Female,54,Masters,9,10,46,83,71,4.0,5,16,Urban,HR Executive,41344,0 +35064,Male,34,Bachelors,18,97,87,82,21,4.0,1,26,Urban,ML Engineer,127183,1 +35065,Male,41,High School,9,69,74,64,72,1.0,3,41,Semi-Urban,Software Engineer,89520,1 +35066,Female,26,High School,17,42,16,89,31,5.0,2,69,Semi-Urban,ML Engineer,78865,0 +35067,Female,59,PhD,10,13,14,31,81,2.0,6,0,Urban,ML Engineer,85961,0 +35068,Male,40,Masters,0,99,95,50,80,2.0,1,51,Rural,Manager,120730,1 +35069,Female,42,High School,0,69,85,16,58,1.0,1,30,Urban,ML Engineer,62957,0 +35070,Male,56,Bachelors,10,31,26,14,13,3.0,0,99,Semi-Urban,Software Engineer,138216,0 +35071,Female,54,High School,6,1,3,44,91,7.0,1,42,Rural,HR Executive,148292,0 +35072,Male,54,Diploma,10,5,87,7,43,6.0,3,75,Urban,Manager,99535,0 +35073,Male,52,Diploma,3,22,93,85,40,8.0,0,80,Urban,ML Engineer,48433,1 +35074,Female,24,Masters,7,81,27,20,10,9.0,6,49,Rural,Software Engineer,26665,0 +35075,Female,49,High School,8,63,50,77,32,8.0,0,24,Rural,HR Executive,74733,0 +35076,Male,38,Bachelors,7,39,63,90,30,9.0,2,39,Semi-Urban,Data Analyst,89064,0 +35077,Male,41,Bachelors,11,46,22,3,36,7.0,4,6,Semi-Urban,Manager,119866,0 +35078,Male,42,Diploma,2,32,52,7,70,8.0,7,3,Rural,Data Analyst,65720,0 +35079,Male,28,Bachelors,16,74,43,36,94,7.0,3,42,Rural,Manager,82393,0 +35080,Male,43,Diploma,11,84,32,11,60,4.0,0,37,Semi-Urban,Software Engineer,30228,0 +35081,Female,32,Bachelors,14,33,42,35,99,3.0,3,20,Urban,Data Analyst,78164,0 +35082,Male,37,Diploma,9,34,45,34,29,1.0,6,21,Urban,HR Executive,58258,0 +35083,Female,56,High School,13,28,63,76,97,9.0,1,88,Semi-Urban,ML Engineer,36796,1 +35084,Female,59,Bachelors,14,51,42,14,94,2.0,7,31,Rural,Software Engineer,47414,0 +35085,Male,49,Diploma,9,50,58,55,89,6.0,0,40,Urban,HR Executive,25268,0 +35086,Female,48,High School,13,32,24,60,89,4.0,5,14,Urban,ML Engineer,144529,0 +35087,Other,29,Masters,19,64,95,53,85,0.0,5,4,Rural,ML Engineer,47684,0 +35088,Male,38,Masters,2,95,82,11,44,9.0,2,30,Rural,Data Analyst,86452,0 +35089,Female,37,Bachelors,15,26,91,22,36,9.0,4,73,Semi-Urban,Data Analyst,40333,0 +35090,Female,38,PhD,15,45,25,64,14,1.0,2,58,Urban,Manager,95565,0 +35091,Male,34,Diploma,5,38,30,14,54,6.0,4,47,Semi-Urban,ML Engineer,119716,0 +35092,Male,52,Bachelors,6,30,33,71,80,9.0,3,14,Rural,ML Engineer,97370,0 +35093,Female,38,High School,4,97,56,14,74,3.0,2,32,Semi-Urban,ML Engineer,21906,0 +35094,Male,33,Bachelors,1,9,1,10,24,5.0,2,26,Urban,Data Analyst,104183,0 +35095,Female,49,Masters,3,28,55,13,48,0.0,6,29,Urban,Software Engineer,75278,0 +35096,Female,59,Diploma,10,68,75,38,42,0.0,4,83,Urban,Data Analyst,112337,1 +35097,Male,46,Diploma,9,14,80,77,77,8.0,4,0,Urban,ML Engineer,125682,0 +35098,Male,42,Diploma,15,93,45,39,67,6.0,6,69,Urban,Data Analyst,104302,1 +35099,Male,51,Diploma,4,34,59,79,14,5.0,3,52,Urban,Manager,46206,0 +35100,Male,21,Bachelors,6,34,1,52,32,3.0,3,85,Rural,ML Engineer,130196,0 +35101,Female,36,PhD,11,65,97,70,94,8.0,3,23,Rural,ML Engineer,67201,1 +35102,Male,45,Bachelors,10,79,44,96,76,1.0,6,57,Urban,Data Analyst,58917,1 +35103,Male,32,Masters,4,76,94,87,59,2.0,0,90,Urban,HR Executive,103151,1 +35104,Male,32,Bachelors,5,24,6,46,93,3.0,3,49,Urban,Manager,65228,0 +35105,Female,51,Diploma,5,26,95,20,39,0.0,1,69,Urban,Manager,89728,0 +35106,Male,31,Diploma,7,10,48,22,53,9.0,0,38,Urban,Data Analyst,60425,0 +35107,Other,21,Masters,15,29,96,68,27,9.0,0,10,Urban,Data Analyst,47467,0 +35108,Female,26,Masters,3,75,98,27,61,4.0,3,67,Semi-Urban,Software Engineer,107766,1 +35109,Female,25,Bachelors,2,36,78,39,78,0.0,3,32,Urban,Manager,131183,0 +35110,Male,39,Bachelors,13,90,78,72,60,7.0,5,24,Urban,HR Executive,35405,1 +35111,Male,52,High School,16,93,76,13,91,5.0,6,19,Semi-Urban,Data Analyst,82420,0 +35112,Male,25,Bachelors,8,14,28,49,29,7.0,2,28,Urban,Data Analyst,34136,0 +35113,Male,31,High School,6,12,71,44,6,8.0,2,24,Semi-Urban,Manager,85639,0 +35114,Female,49,Bachelors,8,55,9,62,67,1.0,1,58,Semi-Urban,Software Engineer,75010,0 +35115,Male,27,Diploma,16,29,64,62,8,3.0,6,72,Urban,Software Engineer,20846,0 +35116,Male,47,High School,2,34,94,30,19,6.0,6,89,Urban,Data Analyst,51526,1 +35117,Female,48,Masters,19,37,12,74,77,6.0,5,76,Urban,Data Analyst,109551,0 +35118,Male,40,High School,4,4,27,51,36,0.0,2,22,Urban,Data Analyst,89830,0 +35119,Male,34,Bachelors,18,53,36,89,2,4.0,7,19,Semi-Urban,ML Engineer,108716,0 +35120,Male,52,Diploma,19,73,2,69,65,3.0,7,38,Semi-Urban,Manager,116519,0 +35121,Female,37,Bachelors,14,34,4,42,11,0.0,7,72,Urban,Data Analyst,65272,0 +35122,Male,48,Masters,14,14,83,35,93,0.0,2,43,Urban,HR Executive,107735,0 +35123,Female,44,Bachelors,10,66,82,20,71,1.0,3,2,Rural,Manager,141523,0 +35124,Male,31,Bachelors,19,6,29,91,77,7.0,7,9,Rural,Software Engineer,46169,0 +35125,Male,49,Masters,13,78,18,89,52,3.0,4,89,Urban,ML Engineer,132230,1 +35126,Female,45,High School,13,99,91,16,2,3.0,2,14,Urban,ML Engineer,95021,0 +35127,Female,43,Diploma,4,85,36,3,67,3.0,6,70,Urban,ML Engineer,145794,0 +35128,Male,33,PhD,17,77,94,77,70,3.0,2,84,Urban,ML Engineer,135635,1 +35129,Female,42,Diploma,8,47,80,23,47,9.0,3,48,Urban,ML Engineer,73723,0 +35130,Male,51,Bachelors,3,70,73,42,25,2.0,5,65,Rural,Manager,85142,1 +35131,Female,26,Bachelors,14,26,80,92,28,6.0,0,17,Rural,Data Analyst,134363,0 +35132,Female,53,Diploma,0,42,97,82,46,0.0,7,28,Urban,HR Executive,87032,1 +35133,Male,52,Bachelors,8,42,92,44,19,8.0,2,22,Urban,ML Engineer,120692,0 +35134,Female,36,High School,9,87,22,56,76,6.0,0,28,Urban,ML Engineer,58825,0 +35135,Male,45,PhD,4,90,1,6,94,5.0,6,91,Semi-Urban,Software Engineer,119397,0 +35136,Female,55,Masters,19,12,99,31,64,8.0,4,31,Urban,Data Analyst,67515,0 +35137,Other,55,Masters,0,7,81,96,26,2.0,4,33,Urban,ML Engineer,118278,0 +35138,Male,37,High School,13,72,86,79,52,2.0,0,33,Semi-Urban,Manager,37932,1 +35139,Male,39,Bachelors,16,56,12,36,67,9.0,6,89,Semi-Urban,ML Engineer,121253,0 +35140,Female,23,Diploma,4,17,85,48,38,9.0,2,72,Urban,ML Engineer,138815,0 +35141,Male,46,PhD,6,36,44,25,62,3.0,3,24,Urban,Manager,108994,0 +35142,Female,39,High School,9,73,64,6,64,8.0,3,77,Semi-Urban,Manager,122682,0 +35143,Male,51,Diploma,8,3,97,3,66,1.0,3,86,Semi-Urban,ML Engineer,90282,0 +35144,Female,36,Bachelors,15,48,90,88,90,6.0,3,94,Urban,Software Engineer,46843,1 +35145,Male,35,PhD,0,30,59,77,4,8.0,0,77,Semi-Urban,ML Engineer,78421,1 +35146,Male,53,Bachelors,3,79,40,2,64,9.0,1,4,Urban,Software Engineer,122727,0 +35147,Female,42,Diploma,10,42,36,38,7,3.0,5,32,Semi-Urban,Data Analyst,119209,0 +35148,Female,33,Bachelors,9,24,11,26,93,6.0,5,12,Urban,Software Engineer,68242,0 +35149,Male,54,Bachelors,6,79,71,83,56,0.0,5,83,Semi-Urban,Software Engineer,135003,1 +35150,Male,35,Diploma,7,3,67,40,97,3.0,7,75,Urban,Data Analyst,117759,0 +35151,Female,32,High School,6,84,26,26,23,9.0,0,36,Urban,Manager,87802,0 +35152,Female,40,Masters,9,36,76,45,79,9.0,3,74,Urban,Data Analyst,134961,0 +35153,Female,45,Diploma,5,27,1,98,68,1.0,5,10,Urban,Manager,79730,0 +35154,Female,52,Bachelors,13,40,7,49,5,0.0,4,10,Rural,HR Executive,84659,0 +35155,Male,31,Bachelors,11,84,11,34,43,7.0,3,15,Rural,HR Executive,94347,0 +35156,Female,43,Masters,7,78,75,56,64,5.0,5,26,Urban,HR Executive,33051,0 +35157,Female,55,Masters,9,6,79,4,73,7.0,1,35,Urban,Manager,143459,0 +35158,Male,54,Bachelors,13,10,26,62,10,6.0,2,39,Urban,Software Engineer,100550,0 +35159,Male,53,Diploma,10,80,94,7,41,6.0,1,30,Urban,Data Analyst,52866,0 +35160,Male,49,PhD,5,48,18,64,6,5.0,7,61,Urban,Software Engineer,55791,0 +35161,Female,48,Diploma,4,48,88,49,55,4.0,1,76,Urban,Software Engineer,56564,1 +35162,Female,33,High School,18,5,22,66,79,3.0,1,38,Urban,Manager,44815,0 +35163,Female,57,High School,2,62,20,47,58,5.0,7,12,Urban,Manager,88960,0 +35164,Male,56,Bachelors,10,80,92,67,98,5.0,3,8,Urban,Software Engineer,41051,1 +35165,Female,40,High School,19,79,17,56,73,6.0,2,99,Rural,HR Executive,52302,1 +35166,Female,47,Masters,14,89,47,91,0,2.0,4,61,Urban,Software Engineer,98071,1 +35167,Male,57,Diploma,18,59,24,79,31,1.0,3,40,Urban,ML Engineer,83466,0 +35168,Male,56,Masters,13,65,63,25,87,9.0,2,68,Urban,Manager,33043,0 +35169,Female,21,Bachelors,17,3,91,61,79,7.0,7,5,Semi-Urban,Manager,128655,0 +35170,Female,30,Bachelors,3,36,57,4,24,4.0,2,81,Rural,Data Analyst,47304,0 +35171,Male,21,Diploma,6,24,22,13,8,9.0,7,68,Urban,Manager,107317,0 +35172,Male,41,Bachelors,12,82,82,32,84,9.0,7,84,Urban,Manager,91650,1 +35173,Male,41,Diploma,7,11,74,20,97,2.0,6,65,Urban,Data Analyst,21356,0 +35174,Male,48,Bachelors,13,20,75,95,52,4.0,2,42,Semi-Urban,ML Engineer,83199,0 +35175,Male,21,Masters,14,71,16,9,29,5.0,7,29,Rural,Software Engineer,38755,0 +35176,Male,27,High School,18,37,98,13,31,8.0,5,15,Semi-Urban,HR Executive,131532,0 +35177,Female,30,Masters,15,66,43,69,71,7.0,2,80,Urban,Software Engineer,76922,1 +35178,Female,38,Masters,0,14,69,89,54,2.0,2,65,Semi-Urban,Manager,102192,0 +35179,Male,33,Masters,17,5,63,84,0,8.0,4,72,Semi-Urban,Manager,110836,0 +35180,Female,47,Bachelors,5,79,23,99,26,3.0,0,5,Urban,HR Executive,95184,0 +35181,Female,43,Bachelors,4,91,74,29,56,5.0,1,11,Urban,Software Engineer,118965,0 +35182,Male,49,High School,9,42,89,95,10,4.0,4,89,Urban,ML Engineer,80394,1 +35183,Male,34,Diploma,18,98,36,62,12,9.0,6,23,Urban,Software Engineer,36396,0 +35184,Female,33,High School,15,32,0,82,17,7.0,3,17,Urban,ML Engineer,42162,0 +35185,Female,42,Masters,13,77,70,13,91,3.0,3,41,Semi-Urban,Software Engineer,88341,0 +35186,Male,32,Masters,16,89,4,31,50,1.0,2,43,Urban,Software Engineer,132924,0 +35187,Male,21,Bachelors,7,13,77,15,64,5.0,3,21,Urban,Manager,53734,0 +35188,Female,43,High School,15,85,38,47,70,5.0,3,79,Urban,Data Analyst,138452,1 +35189,Male,57,High School,17,0,76,61,3,1.0,2,73,Semi-Urban,Software Engineer,52022,0 +35190,Female,52,Bachelors,12,71,99,67,8,2.0,6,58,Urban,Manager,99286,1 +35191,Female,57,Diploma,10,87,36,26,90,3.0,1,6,Urban,ML Engineer,75625,0 +35192,Male,39,Bachelors,17,99,61,47,82,4.0,6,50,Rural,Data Analyst,115817,1 +35193,Male,45,Diploma,3,72,70,58,60,4.0,5,68,Urban,ML Engineer,38529,1 +35194,Male,25,Bachelors,8,75,25,37,68,8.0,7,83,Semi-Urban,Data Analyst,131132,0 +35195,Male,32,PhD,16,97,83,36,73,8.0,1,22,Urban,Manager,105544,1 +35196,Male,53,Bachelors,12,33,65,28,18,1.0,0,50,Urban,Manager,42259,0 +35197,Female,31,Bachelors,4,69,55,43,47,4.0,1,82,Urban,Software Engineer,45024,1 +35198,Male,57,Bachelors,8,49,29,84,6,0.0,5,39,Urban,Software Engineer,34891,0 +35199,Male,34,Bachelors,8,30,62,17,45,7.0,1,90,Urban,Software Engineer,97122,0 +35200,Female,38,Bachelors,0,66,14,98,88,4.0,1,11,Urban,Data Analyst,42830,0 +35201,Female,44,High School,7,58,54,21,53,7.0,1,44,Urban,Software Engineer,47227,0 +35202,Female,44,Bachelors,6,34,41,19,38,0.0,0,54,Rural,HR Executive,65030,0 +35203,Male,25,Masters,2,18,88,29,41,8.0,0,71,Semi-Urban,ML Engineer,135668,0 +35204,Male,56,Diploma,12,5,83,28,79,9.0,4,94,Semi-Urban,Data Analyst,67141,0 +35205,Male,44,Masters,3,85,86,96,63,9.0,0,21,Urban,HR Executive,64941,1 +35206,Male,23,Bachelors,0,19,70,91,21,8.0,5,87,Semi-Urban,HR Executive,43977,1 +35207,Female,23,High School,18,40,14,96,10,6.0,6,66,Urban,ML Engineer,87425,0 +35208,Male,38,Bachelors,15,98,31,11,58,4.0,2,6,Urban,HR Executive,111605,0 +35209,Female,38,Bachelors,1,14,95,79,57,8.0,6,69,Urban,Data Analyst,90287,1 +35210,Male,39,PhD,2,75,25,44,54,8.0,3,34,Rural,ML Engineer,37493,0 +35211,Male,22,Bachelors,19,42,74,50,32,8.0,0,71,Urban,Manager,106181,1 +35212,Female,34,Bachelors,16,44,80,32,3,8.0,0,39,Urban,Manager,62510,0 +35213,Male,50,Masters,10,73,36,57,47,9.0,3,55,Urban,Software Engineer,94349,0 +35214,Male,26,Diploma,19,70,42,97,34,9.0,6,35,Semi-Urban,ML Engineer,123736,1 +35215,Male,44,Masters,1,95,85,71,51,4.0,6,2,Semi-Urban,ML Engineer,114162,1 +35216,Other,45,PhD,15,79,88,37,63,4.0,6,91,Urban,Data Analyst,98368,1 +35217,Male,42,Diploma,14,69,57,46,2,5.0,1,73,Urban,Manager,123773,1 +35218,Male,26,Diploma,10,64,90,47,56,6.0,0,11,Urban,HR Executive,88783,0 +35219,Female,51,Bachelors,19,16,6,6,53,3.0,5,18,Urban,Manager,56927,0 +35220,Female,40,Diploma,12,77,19,58,93,1.0,2,88,Urban,Manager,65987,1 +35221,Female,38,Bachelors,1,86,24,41,86,1.0,3,76,Urban,Data Analyst,132547,0 +35222,Male,21,Bachelors,3,94,2,68,77,9.0,2,51,Semi-Urban,ML Engineer,119402,0 +35223,Other,46,Bachelors,9,19,54,90,76,3.0,2,40,Semi-Urban,ML Engineer,142740,0 +35224,Female,59,Bachelors,10,64,79,21,97,3.0,6,68,Rural,Software Engineer,127729,0 +35225,Male,49,Bachelors,16,56,62,52,35,6.0,2,50,Urban,Software Engineer,136206,0 +35226,Male,55,Masters,6,0,59,12,88,8.0,3,7,Semi-Urban,Software Engineer,78036,0 +35227,Female,45,Bachelors,18,49,46,73,24,4.0,6,19,Rural,ML Engineer,46338,0 +35228,Female,23,Diploma,7,3,99,60,90,7.0,6,89,Urban,Data Analyst,125345,1 +35229,Female,43,PhD,4,6,38,41,53,6.0,5,68,Urban,HR Executive,138741,0 +35230,Female,39,Masters,1,64,75,30,4,5.0,5,44,Semi-Urban,Manager,49171,0 +35231,Male,34,Diploma,14,75,85,41,40,9.0,5,19,Semi-Urban,HR Executive,38612,0 +35232,Male,51,Bachelors,8,1,73,54,2,3.0,3,57,Semi-Urban,Manager,60265,0 +35233,Male,33,Masters,15,65,87,88,25,8.0,0,64,Urban,HR Executive,40409,1 +35234,Male,56,High School,16,51,41,18,93,2.0,7,89,Rural,Data Analyst,119842,0 +35235,Male,57,Diploma,19,79,11,86,18,2.0,3,61,Semi-Urban,HR Executive,98579,1 +35236,Male,27,Diploma,13,65,80,88,37,7.0,3,1,Urban,ML Engineer,49722,0 +35237,Female,44,Bachelors,4,11,29,51,67,4.0,2,83,Semi-Urban,Data Analyst,90905,0 +35238,Male,44,Masters,6,60,67,67,19,8.0,6,13,Urban,Software Engineer,107045,0 +35239,Male,54,Masters,7,36,50,63,62,5.0,4,96,Semi-Urban,Data Analyst,38143,1 +35240,Female,32,Bachelors,10,63,12,77,18,0.0,5,31,Semi-Urban,Manager,128849,0 +35241,Female,44,Bachelors,3,79,26,29,68,6.0,5,87,Urban,ML Engineer,77828,0 +35242,Male,59,Bachelors,7,71,45,75,93,0.0,4,16,Urban,Data Analyst,138226,0 +35243,Female,46,High School,18,6,85,99,20,1.0,7,82,Rural,Data Analyst,127714,1 +35244,Female,28,Masters,7,20,90,64,7,1.0,5,7,Urban,Manager,111546,0 +35245,Male,53,Masters,17,2,41,97,50,3.0,7,64,Urban,Software Engineer,33875,0 +35246,Male,22,Bachelors,19,23,18,32,53,5.0,4,1,Urban,Data Analyst,61527,0 +35247,Male,59,Diploma,13,71,17,54,66,5.0,7,33,Urban,Data Analyst,149720,0 +35248,Female,34,Masters,18,66,56,27,51,8.0,6,79,Rural,HR Executive,117613,0 +35249,Male,52,Bachelors,3,2,92,8,28,4.0,7,87,Urban,Manager,52908,0 +35250,Male,58,Bachelors,3,28,6,43,62,4.0,4,93,Rural,Manager,106211,0 +35251,Female,42,Bachelors,1,31,53,14,37,8.0,0,96,Urban,HR Executive,47540,0 +35252,Male,49,High School,15,17,27,50,5,5.0,6,64,Semi-Urban,ML Engineer,133744,0 +35253,Male,42,PhD,17,41,53,2,4,8.0,5,91,Semi-Urban,ML Engineer,98487,0 +35254,Male,42,Diploma,3,14,8,16,94,8.0,4,78,Urban,ML Engineer,73717,0 +35255,Male,35,Bachelors,10,74,35,44,76,8.0,4,61,Urban,ML Engineer,121882,0 +35256,Female,51,Masters,9,89,32,38,54,5.0,0,31,Semi-Urban,ML Engineer,82590,0 +35257,Female,56,Masters,1,69,55,51,38,8.0,5,97,Semi-Urban,ML Engineer,149362,1 +35258,Male,55,Masters,8,80,97,28,34,8.0,0,79,Semi-Urban,Manager,28773,1 +35259,Male,51,Diploma,4,84,80,89,75,9.0,7,14,Rural,Manager,35272,1 +35260,Male,38,Masters,13,75,64,95,59,2.0,1,15,Rural,Manager,89699,1 +35261,Other,51,Bachelors,7,70,89,26,29,0.0,5,88,Semi-Urban,HR Executive,50141,1 +35262,Female,31,Masters,2,12,12,9,1,0.0,4,71,Urban,ML Engineer,106750,0 +35263,Male,25,Masters,8,52,23,41,34,7.0,1,57,Urban,ML Engineer,33628,0 +35264,Male,27,Diploma,1,35,95,78,93,2.0,7,61,Urban,Software Engineer,50981,1 +35265,Male,57,High School,17,65,70,24,17,2.0,0,99,Urban,Manager,147376,1 +35266,Male,40,Diploma,6,69,26,72,99,1.0,7,26,Semi-Urban,Data Analyst,133419,0 +35267,Other,26,Bachelors,4,97,14,90,47,0.0,4,77,Semi-Urban,HR Executive,117024,1 +35268,Female,32,Bachelors,6,21,64,6,55,1.0,6,99,Semi-Urban,Data Analyst,41108,0 +35269,Female,58,Bachelors,2,17,69,38,23,4.0,0,36,Semi-Urban,ML Engineer,110014,0 +35270,Male,35,Bachelors,12,5,54,36,23,7.0,2,5,Rural,HR Executive,125923,0 +35271,Male,58,Masters,12,70,68,63,61,6.0,2,73,Urban,Software Engineer,109938,1 +35272,Male,33,Masters,11,83,5,65,9,0.0,4,98,Rural,Data Analyst,109534,1 +35273,Male,34,Masters,1,58,70,5,76,4.0,0,12,Semi-Urban,Software Engineer,116404,0 +35274,Male,41,Bachelors,4,95,1,65,31,6.0,1,2,Urban,ML Engineer,20545,0 +35275,Male,50,High School,4,69,87,7,37,4.0,3,87,Urban,ML Engineer,118121,1 +35276,Male,26,High School,15,59,35,79,30,2.0,1,12,Urban,Data Analyst,134985,0 +35277,Male,56,Bachelors,15,98,18,39,36,8.0,7,35,Rural,Data Analyst,56718,0 +35278,Female,55,Masters,19,66,39,82,0,0.0,4,81,Rural,Manager,103361,1 +35279,Female,54,High School,18,79,18,67,66,1.0,3,56,Urban,HR Executive,80718,0 +35280,Male,56,Diploma,11,33,51,55,73,9.0,4,89,Urban,Data Analyst,149157,0 +35281,Male,49,Bachelors,5,69,3,49,82,5.0,7,13,Urban,ML Engineer,86635,0 +35282,Male,23,Bachelors,8,67,87,33,25,7.0,7,65,Urban,Software Engineer,57081,1 +35283,Female,25,High School,14,52,81,92,60,9.0,7,32,Urban,ML Engineer,75866,1 +35284,Other,29,High School,13,43,61,7,55,2.0,7,2,Rural,Software Engineer,90597,0 +35285,Female,40,Bachelors,0,63,46,70,43,6.0,4,80,Rural,HR Executive,66630,1 +35286,Female,56,Masters,12,8,80,78,91,4.0,7,70,Semi-Urban,Manager,72103,0 +35287,Male,56,Diploma,17,42,8,31,67,6.0,6,17,Rural,Software Engineer,114764,0 +35288,Male,56,Bachelors,15,14,78,85,75,6.0,3,67,Semi-Urban,HR Executive,44988,1 +35289,Male,35,Bachelors,13,54,23,19,32,7.0,4,76,Semi-Urban,ML Engineer,136866,0 +35290,Female,27,Bachelors,5,89,23,77,64,1.0,4,65,Urban,Data Analyst,105867,1 +35291,Male,39,Bachelors,2,59,40,57,56,8.0,1,8,Semi-Urban,Manager,41463,0 +35292,Female,54,Masters,15,17,27,7,85,7.0,4,51,Rural,ML Engineer,127253,0 +35293,Female,31,Diploma,5,18,13,38,23,3.0,4,30,Urban,ML Engineer,88607,0 +35294,Male,39,Masters,3,24,58,47,30,1.0,1,68,Urban,ML Engineer,77698,0 +35295,Female,39,High School,10,56,18,31,45,7.0,3,62,Rural,Software Engineer,75658,0 +35296,Male,46,Diploma,6,63,90,96,93,4.0,7,89,Semi-Urban,Data Analyst,142562,1 +35297,Female,42,High School,0,45,51,81,45,1.0,7,65,Urban,Data Analyst,149389,1 +35298,Female,41,Bachelors,7,95,4,98,76,2.0,6,47,Urban,Manager,35830,1 +35299,Male,53,PhD,11,87,93,58,45,7.0,6,56,Rural,Manager,69618,1 +35300,Male,41,Diploma,3,14,98,56,70,3.0,1,17,Urban,Data Analyst,71413,0 +35301,Male,46,Diploma,6,98,93,82,98,4.0,3,13,Urban,Software Engineer,93109,1 +35302,Female,34,Diploma,1,8,11,46,13,4.0,7,63,Semi-Urban,Manager,126978,0 +35303,Male,38,Bachelors,16,82,0,9,94,6.0,0,70,Urban,HR Executive,20615,0 +35304,Female,26,High School,15,80,74,46,77,1.0,1,79,Urban,Data Analyst,48213,1 +35305,Male,30,Diploma,6,49,68,0,38,5.0,0,14,Rural,Data Analyst,101551,0 +35306,Female,36,Bachelors,14,33,31,24,78,8.0,1,93,Semi-Urban,HR Executive,62144,0 +35307,Other,53,Masters,5,74,20,13,32,5.0,1,92,Urban,Data Analyst,103058,0 +35308,Female,22,Masters,7,30,67,82,9,5.0,3,81,Rural,HR Executive,126296,1 +35309,Male,55,High School,18,97,73,61,74,1.0,0,0,Urban,Manager,88528,0 +35310,Male,43,Diploma,15,45,77,13,52,2.0,7,0,Urban,Manager,46773,0 +35311,Male,46,Masters,5,44,14,99,32,2.0,6,28,Urban,Manager,54915,0 +35312,Male,40,High School,0,84,47,99,52,4.0,5,88,Urban,Manager,90034,1 +35313,Male,41,Bachelors,3,3,53,68,61,4.0,4,2,Urban,ML Engineer,142841,0 +35314,Male,46,High School,9,17,64,60,42,9.0,4,54,Rural,Manager,106557,0 +35315,Female,45,Bachelors,1,12,31,55,99,0.0,4,67,Urban,HR Executive,81779,0 +35316,Male,27,High School,16,94,56,97,43,7.0,6,91,Rural,HR Executive,121876,1 +35317,Female,48,Diploma,16,95,24,42,92,8.0,2,72,Urban,Software Engineer,51777,0 +35318,Male,32,High School,15,63,72,23,44,8.0,4,82,Urban,HR Executive,22170,1 +35319,Male,57,Bachelors,3,81,85,22,73,0.0,4,79,Semi-Urban,Data Analyst,119112,1 +35320,Male,43,Bachelors,12,2,13,48,23,1.0,4,52,Rural,Manager,75467,0 +35321,Male,25,Diploma,4,47,80,8,80,6.0,2,18,Urban,ML Engineer,26088,0 +35322,Male,34,Diploma,8,76,39,48,31,5.0,2,19,Urban,Software Engineer,95956,0 +35323,Female,55,Masters,2,25,71,79,83,7.0,2,28,Urban,Software Engineer,58579,0 +35324,Other,33,Bachelors,19,63,30,53,93,7.0,6,62,Rural,Data Analyst,22018,0 +35325,Male,24,Bachelors,8,58,57,13,63,9.0,7,33,Urban,HR Executive,80873,0 +35326,Male,33,Bachelors,0,78,4,0,7,8.0,5,13,Urban,Software Engineer,75448,0 +35327,Male,34,High School,16,55,67,76,18,7.0,6,74,Urban,Data Analyst,56135,1 +35328,Female,38,Masters,6,24,38,82,83,1.0,6,54,Urban,Manager,33038,0 +35329,Female,52,Bachelors,19,85,17,11,13,1.0,7,23,Urban,HR Executive,56654,0 +35330,Female,45,Masters,18,72,96,75,77,2.0,7,36,Urban,ML Engineer,119656,1 +35331,Male,52,High School,0,46,5,59,99,0.0,1,16,Urban,Manager,43236,0 +35332,Male,46,High School,9,63,62,52,1,3.0,2,10,Urban,Manager,26669,0 +35333,Male,39,Masters,18,97,28,71,11,1.0,0,44,Urban,Data Analyst,44051,1 +35334,Female,57,Masters,14,39,63,9,1,8.0,6,56,Semi-Urban,Software Engineer,21333,0 +35335,Male,32,Diploma,9,89,35,92,37,4.0,5,81,Semi-Urban,Data Analyst,148063,1 +35336,Female,56,High School,17,56,99,84,0,0.0,0,18,Urban,ML Engineer,94789,1 +35337,Male,42,Masters,1,37,32,92,73,5.0,1,90,Semi-Urban,Manager,140711,1 +35338,Male,58,Diploma,10,42,80,72,43,8.0,1,88,Urban,HR Executive,39538,1 +35339,Male,27,Diploma,16,75,98,13,74,5.0,0,56,Semi-Urban,ML Engineer,63569,1 +35340,Female,40,High School,5,19,73,84,28,6.0,0,54,Urban,Manager,101769,0 +35341,Male,38,Bachelors,10,3,81,7,77,5.0,1,57,Semi-Urban,ML Engineer,21336,0 +35342,Other,31,Masters,11,55,91,64,59,7.0,5,94,Urban,ML Engineer,46072,1 +35343,Male,21,PhD,18,28,4,61,18,0.0,7,37,Semi-Urban,HR Executive,33801,0 +35344,Male,35,Masters,1,14,70,29,79,0.0,5,87,Urban,Software Engineer,75441,0 +35345,Male,41,Bachelors,3,61,80,55,8,9.0,5,19,Urban,ML Engineer,121324,0 +35346,Female,31,High School,8,66,58,90,34,9.0,7,39,Urban,Manager,105298,1 +35347,Male,23,Bachelors,3,5,88,58,12,0.0,1,61,Urban,HR Executive,54595,0 +35348,Male,59,Masters,2,37,62,87,32,6.0,2,29,Urban,Software Engineer,70618,0 +35349,Male,58,High School,17,62,62,84,25,8.0,0,22,Urban,HR Executive,53123,0 +35350,Male,46,Bachelors,15,72,90,83,48,0.0,3,73,Urban,Data Analyst,139278,1 +35351,Female,31,Bachelors,14,24,3,48,29,4.0,2,28,Urban,HR Executive,139260,0 +35352,Male,54,Bachelors,2,71,81,44,29,6.0,4,63,Rural,ML Engineer,77966,1 +35353,Female,23,PhD,16,60,46,11,26,1.0,6,72,Urban,Manager,122337,0 +35354,Female,50,Masters,17,75,1,47,90,8.0,0,18,Urban,Software Engineer,115552,0 +35355,Female,23,Bachelors,10,43,61,83,21,3.0,1,59,Urban,ML Engineer,79491,1 +35356,Male,46,High School,0,9,60,20,66,8.0,3,85,Urban,Data Analyst,149006,0 +35357,Male,38,High School,6,99,0,93,49,2.0,3,86,Urban,HR Executive,30639,1 +35358,Female,34,Bachelors,0,22,10,27,5,2.0,0,89,Urban,Software Engineer,146487,0 +35359,Female,34,Masters,9,12,32,78,55,8.0,4,47,Rural,Data Analyst,113740,0 +35360,Male,35,Bachelors,18,29,51,91,47,1.0,1,21,Rural,Manager,99695,0 +35361,Male,42,Masters,11,93,19,8,54,1.0,6,62,Semi-Urban,HR Executive,42178,0 +35362,Female,25,Bachelors,2,68,50,74,22,0.0,1,73,Semi-Urban,HR Executive,83559,1 +35363,Male,52,Diploma,2,98,75,68,23,2.0,4,73,Semi-Urban,ML Engineer,24694,1 +35364,Female,50,Bachelors,1,78,6,68,32,8.0,4,72,Rural,HR Executive,70059,0 +35365,Male,27,Bachelors,10,34,90,46,1,0.0,0,52,Rural,Manager,94600,0 +35366,Male,28,High School,1,95,56,10,99,6.0,5,15,Urban,Software Engineer,73205,0 +35367,Male,52,Bachelors,15,5,34,0,34,3.0,4,33,Semi-Urban,Software Engineer,54567,0 +35368,Male,22,PhD,18,15,91,29,98,0.0,4,0,Semi-Urban,ML Engineer,38969,0 +35369,Male,26,Diploma,8,87,18,56,68,7.0,7,8,Rural,ML Engineer,88574,0 +35370,Female,55,Bachelors,18,14,98,89,71,4.0,5,37,Urban,ML Engineer,74900,0 +35371,Female,24,Bachelors,13,75,28,45,39,2.0,6,45,Urban,Data Analyst,119186,0 +35372,Female,40,Masters,7,45,41,3,91,2.0,3,94,Semi-Urban,Data Analyst,124520,0 +35373,Female,47,Diploma,13,82,5,24,11,3.0,2,61,Semi-Urban,HR Executive,56970,0 +35374,Male,23,Diploma,14,25,9,40,5,5.0,7,99,Semi-Urban,Software Engineer,122639,0 +35375,Male,40,Bachelors,6,21,62,24,93,5.0,6,11,Semi-Urban,Software Engineer,25052,0 +35376,Female,49,High School,8,47,1,6,65,3.0,1,77,Urban,Data Analyst,30590,0 +35377,Male,47,Bachelors,10,23,68,92,69,2.0,2,38,Urban,ML Engineer,108329,0 +35378,Male,21,High School,18,87,84,73,57,1.0,0,64,Urban,Manager,108173,1 +35379,Other,51,Diploma,5,38,17,69,92,1.0,3,5,Rural,ML Engineer,51440,0 +35380,Male,23,Diploma,9,10,64,1,89,3.0,3,49,Urban,ML Engineer,105676,0 +35381,Female,57,Bachelors,2,55,87,76,19,5.0,2,24,Semi-Urban,ML Engineer,108923,1 +35382,Female,37,High School,11,28,97,79,0,6.0,1,48,Urban,ML Engineer,93879,1 +35383,Male,41,Bachelors,1,37,50,43,36,3.0,2,49,Urban,Data Analyst,108007,0 +35384,Male,42,Bachelors,14,6,85,17,34,4.0,7,26,Urban,Software Engineer,104817,0 +35385,Other,42,High School,12,72,70,59,47,4.0,4,75,Urban,HR Executive,107764,1 +35386,Male,34,Bachelors,0,5,16,8,34,1.0,7,81,Urban,Manager,74098,0 +35387,Male,51,Masters,10,61,95,36,38,4.0,3,17,Semi-Urban,Manager,104087,0 +35388,Male,32,Bachelors,10,82,60,20,39,9.0,4,55,Semi-Urban,ML Engineer,123754,0 +35389,Female,25,Diploma,9,13,5,13,69,8.0,4,12,Semi-Urban,Data Analyst,73782,0 +35390,Female,43,Bachelors,4,93,75,38,57,3.0,7,54,Urban,HR Executive,108478,1 +35391,Female,44,PhD,17,38,94,3,38,2.0,7,82,Urban,HR Executive,48339,0 +35392,Female,29,High School,16,89,46,87,68,4.0,0,81,Rural,Manager,67267,1 +35393,Female,27,Masters,15,89,89,99,30,2.0,6,6,Semi-Urban,Data Analyst,40810,1 +35394,Male,27,Bachelors,9,72,86,19,85,8.0,1,49,Urban,Data Analyst,110660,0 +35395,Female,38,Masters,10,69,74,13,55,7.0,1,10,Urban,Manager,78788,0 +35396,Male,41,High School,12,42,60,43,84,7.0,4,63,Urban,Manager,38867,0 +35397,Male,57,Bachelors,5,84,89,56,47,9.0,0,72,Urban,Data Analyst,131374,1 +35398,Female,21,High School,13,25,15,74,49,3.0,0,31,Urban,HR Executive,141255,0 +35399,Male,59,Masters,5,34,21,78,20,8.0,7,49,Urban,HR Executive,125759,0 +35400,Female,22,Diploma,17,68,70,50,33,8.0,7,66,Rural,Data Analyst,135545,1 +35401,Male,44,Masters,14,57,30,99,98,3.0,2,3,Urban,Software Engineer,21841,0 +35402,Female,34,Diploma,14,25,94,61,1,2.0,3,69,Urban,Data Analyst,149985,1 +35403,Male,59,Bachelors,11,74,75,24,25,6.0,3,84,Semi-Urban,Software Engineer,35182,1 +35404,Male,23,Bachelors,10,90,82,97,44,2.0,0,96,Urban,Software Engineer,26142,1 +35405,Male,41,Bachelors,8,57,64,73,90,6.0,0,99,Semi-Urban,Manager,104704,1 +35406,Male,54,High School,6,58,87,94,86,2.0,4,46,Urban,Data Analyst,79537,1 +35407,Male,55,PhD,10,81,12,36,7,9.0,0,81,Urban,ML Engineer,120569,0 +35408,Female,40,Bachelors,17,49,99,78,7,9.0,2,88,Rural,HR Executive,73833,1 +35409,Female,58,Bachelors,17,62,58,17,74,2.0,2,94,Rural,ML Engineer,146877,0 +35410,Male,29,Masters,1,48,35,21,23,7.0,4,53,Semi-Urban,HR Executive,20246,0 +35411,Male,35,Masters,18,44,47,22,4,9.0,6,72,Rural,Software Engineer,50220,0 +35412,Male,51,Diploma,19,17,99,95,78,9.0,3,8,Rural,Manager,125772,0 +35413,Male,29,Diploma,1,88,47,56,19,2.0,4,23,Semi-Urban,Data Analyst,118356,0 +35414,Female,33,Bachelors,1,67,63,30,31,0.0,3,30,Urban,Data Analyst,60673,0 +35415,Male,58,Masters,14,68,63,90,72,7.0,1,82,Rural,HR Executive,37503,1 +35416,Female,52,Bachelors,14,25,35,99,18,3.0,5,41,Semi-Urban,ML Engineer,103116,0 +35417,Male,40,Bachelors,9,1,95,21,33,0.0,2,52,Semi-Urban,HR Executive,143793,0 +35418,Male,41,Bachelors,13,94,15,80,13,3.0,0,17,Semi-Urban,HR Executive,129043,0 +35419,Female,39,Bachelors,19,45,29,46,14,8.0,7,47,Urban,Software Engineer,136576,0 +35420,Male,47,Diploma,8,41,74,61,20,4.0,4,17,Urban,Data Analyst,72848,0 +35421,Female,31,Diploma,3,31,50,57,33,8.0,6,15,Semi-Urban,Manager,28103,0 +35422,Female,35,Diploma,5,51,58,20,33,7.0,1,39,Urban,HR Executive,131978,0 +35423,Female,28,Masters,18,2,5,74,12,8.0,0,32,Urban,Software Engineer,125540,0 +35424,Male,29,Masters,15,31,38,22,54,7.0,3,44,Semi-Urban,Data Analyst,142778,0 +35425,Female,59,Bachelors,9,87,81,35,63,1.0,4,89,Urban,Manager,48304,1 +35426,Female,57,Bachelors,8,22,3,84,6,9.0,0,68,Urban,ML Engineer,129467,0 +35427,Male,40,Bachelors,4,95,36,80,16,9.0,1,47,Urban,Software Engineer,80543,1 +35428,Male,30,Bachelors,7,90,68,81,43,5.0,1,90,Rural,Manager,50211,1 +35429,Male,39,Bachelors,12,91,53,74,30,2.0,7,19,Urban,HR Executive,88856,1 +35430,Male,30,High School,19,69,58,10,46,4.0,7,71,Urban,ML Engineer,80090,0 +35431,Other,42,Masters,2,15,43,21,45,4.0,5,9,Rural,Data Analyst,65470,0 +35432,Male,45,Bachelors,11,71,57,49,91,7.0,4,64,Urban,ML Engineer,32726,1 +35433,Female,44,Masters,4,77,61,89,59,9.0,7,31,Urban,Software Engineer,80129,1 +35434,Male,46,Diploma,13,78,45,41,79,8.0,1,19,Rural,HR Executive,131379,0 +35435,Male,35,High School,13,65,90,73,59,5.0,2,44,Urban,HR Executive,39296,1 +35436,Other,51,Masters,18,49,93,65,68,7.0,4,49,Semi-Urban,Software Engineer,147644,1 +35437,Male,55,Diploma,16,7,61,1,32,5.0,0,67,Urban,Software Engineer,41386,0 +35438,Male,27,Diploma,13,26,1,28,83,0.0,7,1,Urban,Manager,82377,0 +35439,Female,47,Bachelors,1,72,39,83,79,0.0,3,28,Urban,Software Engineer,76673,0 +35440,Female,25,Bachelors,6,35,67,93,29,0.0,3,37,Rural,Manager,29796,0 +35441,Female,33,Diploma,10,35,88,55,54,3.0,1,48,Rural,Manager,60917,0 +35442,Female,24,High School,14,92,60,87,97,9.0,4,57,Urban,Software Engineer,98154,1 +35443,Female,49,Bachelors,19,65,26,1,91,9.0,6,47,Urban,Manager,80063,0 +35444,Male,31,Bachelors,14,94,71,46,72,3.0,3,0,Urban,Manager,102714,0 +35445,Female,49,Diploma,14,53,95,22,92,8.0,6,57,Rural,Software Engineer,115200,0 +35446,Other,28,High School,1,38,32,85,0,5.0,2,97,Rural,Software Engineer,149612,1 +35447,Male,54,Masters,16,90,74,73,93,1.0,7,5,Rural,ML Engineer,114647,1 +35448,Male,38,Bachelors,1,78,70,99,67,5.0,7,65,Urban,Software Engineer,20973,1 +35449,Male,46,Diploma,15,51,88,39,31,4.0,2,0,Rural,Manager,134410,0 +35450,Female,38,PhD,12,78,35,23,38,2.0,2,26,Urban,Manager,145413,0 +35451,Male,44,Diploma,8,95,75,22,55,3.0,0,45,Urban,HR Executive,129398,1 +35452,Female,55,Masters,14,77,90,45,33,9.0,3,83,Rural,Software Engineer,129776,1 +35453,Male,53,PhD,4,59,63,48,40,2.0,6,73,Urban,Data Analyst,129859,1 +35454,Female,38,Bachelors,1,29,64,2,68,6.0,5,65,Urban,Manager,147121,0 +35455,Male,51,High School,13,29,17,40,54,3.0,3,59,Urban,ML Engineer,98957,0 +35456,Male,49,Bachelors,2,27,71,19,11,6.0,4,21,Rural,Data Analyst,32180,0 +35457,Female,21,Bachelors,2,92,60,17,89,2.0,7,36,Urban,HR Executive,136697,0 +35458,Male,37,Masters,2,4,98,40,34,7.0,0,97,Urban,HR Executive,34267,1 +35459,Male,55,Bachelors,19,21,29,46,13,2.0,6,78,Rural,Software Engineer,136786,0 +35460,Male,44,Bachelors,11,53,59,16,33,6.0,0,60,Semi-Urban,HR Executive,61270,0 +35461,Male,23,High School,1,9,97,72,48,5.0,0,4,Semi-Urban,Software Engineer,79365,0 +35462,Male,57,Bachelors,11,21,32,99,89,4.0,2,53,Semi-Urban,HR Executive,106116,0 +35463,Other,42,PhD,6,28,37,40,54,8.0,5,54,Rural,Data Analyst,144467,0 +35464,Female,41,Masters,4,20,64,24,19,3.0,7,19,Urban,Software Engineer,85427,0 +35465,Female,36,Diploma,15,57,71,97,86,7.0,7,23,Semi-Urban,ML Engineer,102343,1 +35466,Male,37,Masters,13,13,67,18,37,4.0,5,58,Semi-Urban,HR Executive,58284,0 +35467,Male,59,Bachelors,0,63,11,36,61,7.0,2,74,Urban,Software Engineer,115107,0 +35468,Male,22,Masters,0,28,18,96,92,4.0,7,64,Urban,HR Executive,123093,0 +35469,Female,53,Diploma,18,33,69,11,48,8.0,6,43,Semi-Urban,HR Executive,31817,0 +35470,Male,51,Bachelors,17,67,2,53,16,8.0,7,20,Semi-Urban,Manager,88417,0 +35471,Female,32,PhD,17,80,11,54,24,7.0,4,38,Urban,ML Engineer,77564,0 +35472,Male,37,Bachelors,18,24,18,14,13,0.0,3,18,Urban,HR Executive,61037,0 +35473,Male,54,PhD,17,46,73,27,66,2.0,5,2,Urban,Manager,49102,0 +35474,Male,22,Diploma,15,33,18,48,9,1.0,0,73,Semi-Urban,HR Executive,84011,0 +35475,Female,44,Diploma,10,29,27,22,54,1.0,2,18,Rural,Data Analyst,22582,0 +35476,Male,53,Bachelors,15,82,25,25,83,7.0,0,73,Rural,HR Executive,143469,0 +35477,Male,35,Masters,4,97,70,83,68,4.0,1,27,Semi-Urban,Software Engineer,94573,1 +35478,Female,29,Bachelors,18,19,85,48,40,4.0,7,98,Urban,ML Engineer,131831,1 +35479,Female,32,PhD,17,69,66,86,18,6.0,7,85,Urban,HR Executive,79373,1 +35480,Male,57,Diploma,1,7,90,17,15,3.0,5,47,Urban,HR Executive,100778,0 +35481,Male,25,Masters,6,11,24,48,53,7.0,0,16,Urban,ML Engineer,37517,0 +35482,Male,22,Bachelors,6,12,87,22,85,5.0,1,94,Semi-Urban,Manager,29782,0 +35483,Male,48,Bachelors,8,22,64,51,29,9.0,5,76,Urban,HR Executive,116347,0 +35484,Female,41,Masters,8,78,9,52,97,4.0,7,5,Urban,HR Executive,84014,0 +35485,Male,34,Bachelors,7,58,85,71,98,2.0,6,15,Semi-Urban,Software Engineer,66319,0 +35486,Female,21,Masters,2,54,80,54,43,2.0,1,87,Urban,ML Engineer,44921,1 +35487,Male,42,Bachelors,12,25,45,90,56,2.0,2,85,Rural,Software Engineer,64242,1 +35488,Male,24,Masters,3,94,11,78,76,8.0,2,51,Urban,HR Executive,83616,0 +35489,Other,28,High School,11,15,59,28,61,8.0,7,78,Rural,Manager,58231,0 +35490,Male,22,Diploma,18,93,20,62,3,7.0,1,43,Semi-Urban,Data Analyst,101209,0 +35491,Female,36,Bachelors,15,45,25,72,13,7.0,7,10,Urban,ML Engineer,72245,0 +35492,Female,36,Bachelors,12,18,7,98,50,8.0,0,55,Urban,HR Executive,52997,0 +35493,Male,56,Bachelors,14,16,8,81,31,7.0,7,48,Urban,HR Executive,46410,0 +35494,Male,51,Diploma,2,9,86,97,3,3.0,2,43,Urban,Software Engineer,96648,1 +35495,Male,32,Diploma,13,46,7,96,12,6.0,4,36,Urban,ML Engineer,148845,0 +35496,Female,50,Bachelors,5,25,83,5,30,3.0,3,8,Urban,Manager,143099,0 +35497,Male,48,Diploma,7,63,93,56,89,1.0,7,13,Urban,HR Executive,97528,0 +35498,Male,46,High School,12,15,8,24,46,6.0,3,22,Semi-Urban,Software Engineer,136974,0 +35499,Male,36,Bachelors,18,48,26,22,66,4.0,0,68,Urban,Software Engineer,82875,0 +35500,Female,27,Diploma,0,82,5,8,44,7.0,7,21,Urban,HR Executive,120561,0 +35501,Male,33,High School,4,46,77,44,65,7.0,7,0,Semi-Urban,Data Analyst,104472,0 +35502,Male,28,Bachelors,19,39,27,35,2,7.0,0,62,Rural,Data Analyst,25913,0 +35503,Other,47,Bachelors,17,3,12,51,58,2.0,5,35,Semi-Urban,Manager,85835,0 +35504,Male,51,Diploma,12,40,46,42,94,9.0,4,62,Rural,HR Executive,77245,0 +35505,Male,28,PhD,3,8,87,83,10,9.0,1,76,Urban,ML Engineer,79293,1 +35506,Female,35,Diploma,14,14,29,10,12,9.0,3,16,Rural,Manager,47796,0 +35507,Female,49,Diploma,9,75,5,82,48,1.0,1,52,Urban,Software Engineer,132139,0 +35508,Male,50,Diploma,10,48,17,18,11,0.0,1,45,Rural,ML Engineer,137013,0 +35509,Male,31,Bachelors,14,33,58,81,85,6.0,1,66,Urban,Manager,123564,1 +35510,Male,57,Diploma,11,77,54,73,94,3.0,1,26,Rural,Software Engineer,63173,0 +35511,Male,22,High School,3,37,89,72,24,5.0,2,38,Urban,Manager,116017,1 +35512,Female,48,Diploma,3,83,12,76,55,0.0,7,19,Semi-Urban,Manager,72130,0 +35513,Male,25,High School,3,72,3,38,46,6.0,0,71,Urban,Software Engineer,79536,0 +35514,Female,54,High School,11,43,50,26,90,7.0,2,28,Rural,Manager,118604,0 +35515,Male,45,Bachelors,6,26,81,4,93,6.0,6,64,Urban,ML Engineer,132440,0 +35516,Female,23,Bachelors,16,4,17,45,14,4.0,7,61,Urban,Manager,38740,0 +35517,Male,50,Bachelors,9,84,14,97,30,2.0,4,77,Rural,HR Executive,99210,1 +35518,Female,57,Diploma,9,98,77,19,92,4.0,4,23,Urban,Manager,86395,0 +35519,Male,46,Diploma,9,93,28,76,24,8.0,2,98,Urban,Data Analyst,76692,1 +35520,Female,52,Diploma,5,10,81,30,86,2.0,6,15,Urban,Data Analyst,124296,0 +35521,Male,44,Bachelors,19,67,72,95,63,7.0,5,79,Urban,HR Executive,104538,1 +35522,Male,37,High School,5,8,37,33,53,9.0,3,84,Urban,Manager,85204,0 +35523,Female,55,Bachelors,14,17,22,50,56,9.0,1,57,Urban,HR Executive,60768,0 +35524,Male,36,Bachelors,15,46,84,71,14,1.0,3,52,Urban,Manager,137640,1 +35525,Male,25,Bachelors,3,79,54,14,15,1.0,4,17,Semi-Urban,Manager,142210,0 +35526,Female,52,Masters,8,62,81,53,50,2.0,7,1,Urban,HR Executive,93761,0 +35527,Female,48,Bachelors,3,86,64,14,8,0.0,1,44,Rural,Manager,144745,0 +35528,Male,23,Bachelors,9,16,61,45,1,5.0,7,0,Urban,Data Analyst,132418,0 +35529,Male,46,Bachelors,18,88,43,67,41,4.0,6,85,Semi-Urban,Software Engineer,129402,1 +35530,Male,41,Masters,6,62,82,75,83,6.0,1,5,Rural,ML Engineer,84142,0 +35531,Female,31,Diploma,11,55,84,43,62,3.0,4,75,Rural,ML Engineer,88934,1 +35532,Male,22,Bachelors,18,83,34,76,47,7.0,5,97,Urban,Software Engineer,106034,1 +35533,Female,22,Bachelors,9,25,51,92,52,3.0,7,34,Semi-Urban,ML Engineer,68735,0 +35534,Male,24,High School,8,54,12,76,75,0.0,4,81,Urban,Manager,98261,0 +35535,Male,47,High School,3,16,25,90,59,4.0,6,73,Rural,Data Analyst,90678,0 +35536,Male,44,Bachelors,6,45,6,47,32,2.0,1,13,Urban,Data Analyst,146823,0 +35537,Female,23,Bachelors,16,29,42,24,1,1.0,7,69,Urban,Data Analyst,21558,0 +35538,Male,36,High School,6,1,72,59,48,0.0,4,56,Rural,ML Engineer,147636,0 +35539,Male,58,Masters,19,52,38,63,78,4.0,7,72,Urban,Manager,111450,0 +35540,Male,49,Diploma,17,35,40,7,58,8.0,3,77,Semi-Urban,Data Analyst,48411,0 +35541,Male,56,Bachelors,6,6,89,81,61,9.0,3,13,Urban,Manager,137958,0 +35542,Male,45,PhD,8,77,28,28,16,0.0,5,84,Urban,Data Analyst,29798,0 +35543,Male,53,Bachelors,6,48,7,26,80,8.0,6,52,Urban,Data Analyst,39427,0 +35544,Female,25,High School,13,55,75,44,84,3.0,7,16,Semi-Urban,Software Engineer,71687,0 +35545,Male,33,Masters,15,39,75,63,15,4.0,5,32,Urban,Software Engineer,111425,0 +35546,Male,24,High School,15,16,9,67,24,2.0,6,64,Urban,ML Engineer,88842,0 +35547,Other,56,Masters,3,59,7,74,14,7.0,6,32,Urban,Data Analyst,29888,0 +35548,Male,37,Bachelors,15,96,7,14,54,1.0,7,51,Urban,Software Engineer,33916,0 +35549,Female,59,High School,1,63,95,6,72,7.0,1,11,Semi-Urban,HR Executive,105358,0 +35550,Male,44,Masters,4,23,82,93,86,6.0,2,65,Urban,Data Analyst,22334,1 +35551,Male,49,Diploma,10,38,9,47,60,9.0,4,30,Urban,Data Analyst,87308,0 +35552,Male,40,Masters,15,85,85,49,40,5.0,6,64,Semi-Urban,Data Analyst,130311,1 +35553,Male,31,PhD,5,19,56,30,53,4.0,5,5,Rural,Manager,79021,0 +35554,Male,55,Bachelors,4,43,49,23,40,4.0,4,73,Urban,Data Analyst,28563,0 +35555,Male,41,Bachelors,6,58,72,25,97,1.0,2,77,Urban,HR Executive,83370,0 +35556,Female,30,Masters,8,11,73,28,70,1.0,7,18,Semi-Urban,Software Engineer,48377,0 +35557,Male,47,Bachelors,6,64,82,82,32,4.0,4,1,Semi-Urban,ML Engineer,34955,0 +35558,Male,31,Bachelors,7,42,57,97,53,8.0,4,60,Urban,Software Engineer,93698,1 +35559,Male,26,High School,8,20,16,87,89,8.0,1,4,Semi-Urban,Data Analyst,32083,0 +35560,Female,59,Bachelors,8,96,68,88,74,0.0,5,19,Urban,Software Engineer,133185,1 +35561,Male,54,High School,14,5,76,77,81,1.0,3,96,Urban,Data Analyst,31147,1 +35562,Male,31,Diploma,0,49,90,27,62,0.0,1,32,Semi-Urban,Software Engineer,41343,0 +35563,Female,43,Bachelors,19,36,25,13,31,8.0,2,49,Rural,Software Engineer,70545,0 +35564,Other,25,Bachelors,13,6,40,97,34,9.0,7,85,Urban,Data Analyst,86060,0 +35565,Male,53,High School,5,98,50,28,78,8.0,0,68,Urban,Software Engineer,148607,1 +35566,Female,26,Bachelors,16,9,35,88,47,7.0,6,63,Rural,HR Executive,46686,0 +35567,Male,25,Masters,9,16,77,57,40,6.0,7,78,Urban,ML Engineer,134143,0 +35568,Female,43,Bachelors,8,20,33,47,78,7.0,6,90,Urban,ML Engineer,126988,0 +35569,Female,59,PhD,17,84,46,52,96,6.0,4,81,Urban,Data Analyst,56861,1 +35570,Female,36,Bachelors,1,31,14,69,50,6.0,6,19,Semi-Urban,Data Analyst,72067,0 +35571,Female,36,Bachelors,9,3,47,5,7,6.0,5,8,Urban,Manager,44956,0 +35572,Male,55,Bachelors,18,58,95,75,43,4.0,0,45,Urban,ML Engineer,131896,1 +35573,Male,46,Masters,4,89,74,47,20,8.0,5,60,Semi-Urban,Data Analyst,82238,1 +35574,Male,58,Bachelors,15,81,92,45,80,0.0,4,5,Urban,HR Executive,116518,0 +35575,Male,39,Masters,4,27,42,7,54,5.0,6,47,Urban,Data Analyst,46735,0 +35576,Male,52,Masters,1,7,4,21,89,2.0,1,94,Semi-Urban,Data Analyst,100420,0 +35577,Other,33,Bachelors,13,77,16,14,92,4.0,3,92,Urban,ML Engineer,30385,0 +35578,Male,21,Masters,1,66,4,1,24,0.0,3,23,Urban,Manager,97201,0 +35579,Male,35,Bachelors,5,21,18,52,70,5.0,4,89,Semi-Urban,Software Engineer,22112,0 +35580,Male,30,High School,7,72,23,23,24,8.0,2,62,Urban,ML Engineer,74702,0 +35581,Female,38,Bachelors,12,66,77,0,17,4.0,7,87,Rural,Software Engineer,27022,0 +35582,Male,47,Bachelors,3,57,33,42,86,9.0,6,9,Rural,ML Engineer,68187,0 +35583,Male,51,PhD,4,20,96,20,17,9.0,1,83,Urban,Manager,36012,0 +35584,Female,53,High School,13,5,27,88,98,2.0,3,30,Semi-Urban,Software Engineer,126516,0 +35585,Female,22,Masters,4,85,58,46,91,9.0,4,83,Rural,Software Engineer,112843,1 +35586,Female,26,Bachelors,8,32,27,52,24,2.0,4,27,Urban,Manager,36968,0 +35587,Female,47,Bachelors,10,86,60,67,64,9.0,1,84,Urban,Software Engineer,29473,1 +35588,Male,35,Bachelors,10,86,8,57,69,0.0,0,26,Rural,HR Executive,80041,0 +35589,Female,28,PhD,12,37,47,20,2,9.0,2,73,Urban,HR Executive,114411,0 +35590,Male,56,Bachelors,3,0,77,3,92,5.0,5,99,Urban,Manager,146463,0 +35591,Male,54,Masters,17,30,12,32,46,0.0,3,76,Urban,HR Executive,74890,0 +35592,Male,26,Bachelors,10,81,22,67,59,8.0,6,12,Urban,Software Engineer,141836,0 +35593,Male,45,Bachelors,9,81,11,36,38,2.0,3,0,Semi-Urban,ML Engineer,103226,0 +35594,Male,55,Diploma,11,14,86,27,25,3.0,3,16,Semi-Urban,ML Engineer,147305,0 +35595,Male,52,Masters,2,92,40,22,38,9.0,7,99,Urban,HR Executive,119590,1 +35596,Male,59,Bachelors,2,42,92,96,0,9.0,1,38,Urban,Manager,30033,1 +35597,Male,44,Diploma,10,44,51,43,71,6.0,0,65,Rural,Data Analyst,86614,0 +35598,Female,46,Diploma,1,58,60,64,62,6.0,7,39,Semi-Urban,Manager,21573,0 +35599,Male,24,Bachelors,17,43,17,69,6,6.0,0,55,Urban,Manager,35968,0 +35600,Female,57,Bachelors,9,63,45,98,28,1.0,5,77,Rural,Software Engineer,86225,1 +35601,Male,41,PhD,10,37,2,76,68,5.0,0,61,Urban,Data Analyst,142884,0 +35602,Female,44,Bachelors,15,16,39,95,95,5.0,5,47,Semi-Urban,ML Engineer,137032,0 +35603,Female,41,Diploma,9,10,86,93,73,7.0,3,75,Rural,Data Analyst,54101,1 +35604,Other,36,Diploma,19,72,38,70,74,4.0,3,23,Urban,ML Engineer,113027,0 +35605,Male,25,Masters,7,80,72,63,15,7.0,2,71,Urban,HR Executive,96046,1 +35606,Male,39,Masters,17,70,28,61,22,7.0,1,49,Urban,Software Engineer,87458,0 +35607,Male,50,High School,18,53,56,78,68,8.0,2,79,Urban,Manager,56479,1 +35608,Male,55,Diploma,13,15,94,39,83,6.0,2,70,Semi-Urban,HR Executive,115791,0 +35609,Male,30,Bachelors,12,47,73,65,1,6.0,7,46,Semi-Urban,ML Engineer,145912,0 +35610,Female,23,Diploma,18,25,76,61,0,4.0,4,67,Urban,Manager,41775,0 +35611,Male,37,Diploma,14,76,65,70,72,0.0,0,18,Urban,HR Executive,57550,0 +35612,Male,29,High School,2,89,86,32,47,0.0,6,7,Semi-Urban,HR Executive,29580,0 +35613,Male,54,Bachelors,8,48,31,89,47,9.0,6,69,Urban,Data Analyst,47950,1 +35614,Male,31,Diploma,12,93,30,17,42,5.0,6,54,Urban,Data Analyst,68809,0 +35615,Female,38,Bachelors,0,53,55,22,34,3.0,5,10,Rural,Manager,132463,0 +35616,Female,23,Bachelors,6,78,77,30,97,3.0,6,45,Urban,Software Engineer,50215,0 +35617,Male,56,Bachelors,15,62,92,26,96,5.0,3,31,Semi-Urban,HR Executive,51181,0 +35618,Male,59,High School,13,67,23,84,77,2.0,6,75,Semi-Urban,HR Executive,97769,1 +35619,Female,59,Diploma,3,86,72,86,96,7.0,6,37,Urban,HR Executive,99949,1 +35620,Male,55,Bachelors,0,43,94,26,68,5.0,4,27,Urban,Manager,118347,0 +35621,Female,37,Masters,10,6,21,33,41,6.0,1,3,Semi-Urban,HR Executive,40452,0 +35622,Female,54,High School,2,25,44,13,61,7.0,4,8,Urban,Manager,61153,0 +35623,Male,29,Bachelors,0,95,95,33,39,7.0,1,57,Urban,Manager,82163,1 +35624,Male,28,Masters,15,41,48,83,75,8.0,1,65,Urban,Manager,144239,1 +35625,Male,36,Bachelors,19,55,37,17,91,5.0,0,15,Semi-Urban,ML Engineer,128831,0 +35626,Female,52,Bachelors,0,51,99,44,73,9.0,5,1,Rural,Manager,83109,0 +35627,Male,42,Masters,7,85,93,47,75,9.0,5,7,Urban,ML Engineer,115335,0 +35628,Male,58,Diploma,17,9,99,63,69,6.0,6,9,Urban,Data Analyst,148303,0 +35629,Female,23,Bachelors,12,5,45,84,71,1.0,7,87,Rural,Software Engineer,55644,0 +35630,Female,50,Diploma,0,71,51,73,88,2.0,3,92,Semi-Urban,Software Engineer,115815,1 +35631,Male,59,Diploma,15,87,98,46,14,2.0,2,9,Urban,Manager,111820,1 +35632,Male,38,Bachelors,0,78,27,38,63,7.0,1,12,Urban,HR Executive,65956,0 +35633,Male,28,Bachelors,0,31,51,5,22,3.0,1,90,Urban,Manager,117812,0 +35634,Male,58,Masters,19,56,73,78,53,8.0,1,40,Urban,Data Analyst,44601,1 +35635,Male,54,PhD,10,44,67,93,19,1.0,6,5,Semi-Urban,Data Analyst,139634,0 +35636,Female,41,Bachelors,15,15,6,49,34,3.0,0,92,Rural,Software Engineer,36279,0 +35637,Male,36,Bachelors,18,26,94,16,53,6.0,3,22,Urban,Data Analyst,92878,0 +35638,Male,35,Masters,13,91,14,43,47,5.0,3,5,Urban,ML Engineer,42477,0 +35639,Male,33,Bachelors,18,55,61,97,50,7.0,3,89,Semi-Urban,HR Executive,55634,1 +35640,Male,54,Bachelors,16,94,5,35,25,0.0,6,27,Semi-Urban,Manager,123998,0 +35641,Female,22,Diploma,1,87,74,42,3,0.0,6,33,Urban,ML Engineer,59240,0 +35642,Female,23,PhD,0,19,7,27,83,5.0,1,37,Urban,Data Analyst,90597,0 +35643,Female,35,Bachelors,15,67,89,31,38,7.0,0,23,Semi-Urban,ML Engineer,57007,0 +35644,Female,59,Bachelors,8,0,84,32,62,6.0,0,84,Urban,HR Executive,139951,0 +35645,Female,30,Bachelors,3,16,12,41,17,4.0,6,69,Urban,Software Engineer,36758,0 +35646,Male,34,Bachelors,3,72,84,53,35,7.0,5,90,Urban,ML Engineer,146222,1 +35647,Male,25,Diploma,6,83,69,40,17,8.0,7,44,Urban,Manager,96333,1 +35648,Female,38,Masters,9,12,45,56,91,0.0,7,20,Semi-Urban,Software Engineer,27445,0 +35649,Male,28,High School,4,3,32,99,92,9.0,5,86,Urban,Data Analyst,50862,0 +35650,Male,21,Diploma,4,77,58,73,54,8.0,7,35,Urban,ML Engineer,73169,1 +35651,Male,54,Bachelors,9,84,67,90,89,3.0,2,18,Rural,ML Engineer,26348,1 +35652,Male,32,PhD,12,17,47,17,30,5.0,3,65,Rural,ML Engineer,102480,0 +35653,Male,32,Diploma,7,43,7,10,49,9.0,6,89,Urban,Data Analyst,129709,0 +35654,Female,48,Bachelors,18,10,39,67,57,7.0,2,60,Rural,HR Executive,89630,0 +35655,Male,59,Bachelors,11,55,67,95,28,6.0,2,82,Urban,Software Engineer,65406,1 +35656,Female,45,Masters,15,88,74,56,63,4.0,7,43,Urban,ML Engineer,31125,1 +35657,Male,59,Bachelors,8,5,38,83,96,4.0,5,10,Semi-Urban,HR Executive,106624,0 +35658,Male,59,Bachelors,7,58,59,67,80,2.0,6,11,Rural,ML Engineer,98913,0 +35659,Male,27,Masters,11,72,84,16,30,3.0,0,76,Urban,Software Engineer,107821,1 +35660,Male,47,Bachelors,9,89,80,17,20,3.0,4,88,Rural,Data Analyst,87557,1 +35661,Female,26,Diploma,9,32,22,29,33,1.0,3,34,Urban,ML Engineer,84121,0 +35662,Male,31,Diploma,3,8,23,9,64,7.0,3,59,Urban,Software Engineer,34430,0 +35663,Male,27,High School,4,32,69,24,80,7.0,0,68,Urban,ML Engineer,25046,0 +35664,Male,48,Bachelors,6,96,97,41,93,4.0,0,65,Urban,Manager,102045,1 +35665,Male,56,Bachelors,11,71,16,39,68,9.0,0,15,Urban,HR Executive,35327,0 +35666,Male,30,Diploma,4,90,12,82,52,1.0,2,52,Semi-Urban,Software Engineer,112267,1 +35667,Male,56,High School,5,5,43,90,99,0.0,6,50,Urban,Manager,53544,0 +35668,Male,27,Bachelors,13,70,81,27,97,3.0,4,48,Semi-Urban,Software Engineer,26558,0 +35669,Female,28,Bachelors,1,76,84,13,43,9.0,6,62,Semi-Urban,HR Executive,141568,0 +35670,Female,51,Diploma,15,35,84,26,21,8.0,3,87,Semi-Urban,Data Analyst,137326,0 +35671,Male,55,Bachelors,16,55,11,0,13,4.0,3,92,Rural,Data Analyst,94249,0 +35672,Male,46,Bachelors,0,93,57,27,70,8.0,6,72,Urban,HR Executive,21388,1 +35673,Female,38,Bachelors,8,93,31,21,24,3.0,4,62,Urban,ML Engineer,98985,0 +35674,Female,35,Masters,10,49,83,72,23,0.0,7,5,Urban,Data Analyst,118560,0 +35675,Male,41,Diploma,8,52,93,69,89,8.0,3,7,Semi-Urban,ML Engineer,56868,0 +35676,Male,41,Diploma,2,23,42,45,81,9.0,5,70,Semi-Urban,Software Engineer,64652,0 +35677,Male,47,High School,9,50,79,35,33,6.0,5,96,Urban,ML Engineer,92400,1 +35678,Male,30,High School,19,80,79,12,27,4.0,2,93,Urban,Manager,66917,1 +35679,Male,58,PhD,14,97,77,15,96,6.0,4,3,Urban,ML Engineer,140385,0 +35680,Male,55,High School,7,97,53,46,46,2.0,6,62,Semi-Urban,HR Executive,77251,1 +35681,Female,34,PhD,5,1,19,95,69,6.0,2,42,Urban,Software Engineer,142311,0 +35682,Male,49,High School,18,67,23,61,68,4.0,2,65,Semi-Urban,ML Engineer,122022,0 +35683,Male,21,Diploma,6,80,59,63,37,9.0,5,2,Urban,Software Engineer,126821,0 +35684,Female,57,Masters,0,35,69,74,93,8.0,1,63,Urban,ML Engineer,90020,1 +35685,Female,22,Masters,4,20,29,2,91,9.0,2,67,Semi-Urban,Data Analyst,86148,0 +35686,Male,42,Bachelors,11,92,39,86,30,9.0,0,93,Semi-Urban,Software Engineer,33345,1 +35687,Male,57,Bachelors,0,27,75,82,55,6.0,2,11,Urban,Data Analyst,128832,0 +35688,Male,53,Bachelors,3,76,48,60,33,8.0,4,14,Semi-Urban,Data Analyst,43892,0 +35689,Male,49,Bachelors,19,36,76,94,36,6.0,5,15,Rural,Data Analyst,133881,0 +35690,Male,39,High School,6,49,91,14,74,6.0,1,88,Rural,Data Analyst,127661,1 +35691,Male,21,High School,8,77,39,0,23,1.0,0,36,Semi-Urban,Manager,102915,0 +35692,Male,38,High School,2,14,73,71,18,4.0,7,52,Semi-Urban,Data Analyst,118352,0 +35693,Female,36,Bachelors,8,81,77,86,33,2.0,1,9,Rural,ML Engineer,112945,1 +35694,Male,32,Masters,16,99,71,77,89,4.0,2,94,Urban,Manager,73047,1 +35695,Male,59,High School,13,36,95,61,47,2.0,3,49,Semi-Urban,Manager,88665,1 +35696,Male,34,High School,5,65,79,94,20,2.0,6,90,Semi-Urban,Software Engineer,31501,1 +35697,Female,29,Masters,17,65,56,11,5,0.0,4,85,Rural,Software Engineer,69242,0 +35698,Female,44,Diploma,15,26,42,52,63,8.0,4,58,Urban,HR Executive,88620,0 +35699,Female,42,Bachelors,15,88,78,95,64,6.0,1,69,Urban,Software Engineer,45005,1 +35700,Other,55,Diploma,10,55,27,14,60,5.0,1,91,Rural,HR Executive,137414,0 +35701,Male,38,Bachelors,7,5,24,36,6,1.0,1,33,Semi-Urban,HR Executive,129685,0 +35702,Male,45,Bachelors,18,83,34,30,41,5.0,0,17,Urban,Software Engineer,89480,0 +35703,Male,37,PhD,1,48,78,78,65,1.0,6,13,Urban,HR Executive,81762,0 +35704,Male,43,Masters,8,46,82,76,87,8.0,3,16,Semi-Urban,ML Engineer,61178,0 +35705,Male,54,High School,15,92,77,65,16,5.0,2,86,Urban,Software Engineer,135279,1 +35706,Male,52,Masters,7,12,22,71,64,1.0,6,34,Semi-Urban,Manager,84021,0 +35707,Male,58,Masters,0,77,43,44,54,1.0,5,68,Urban,HR Executive,87114,0 +35708,Male,22,Bachelors,17,12,12,32,0,2.0,5,50,Semi-Urban,Data Analyst,84011,0 +35709,Other,26,Bachelors,14,60,60,24,33,5.0,4,21,Semi-Urban,Manager,123101,0 +35710,Male,48,Bachelors,16,11,55,7,61,1.0,2,52,Urban,HR Executive,81082,0 +35711,Male,28,Bachelors,9,87,34,84,32,6.0,1,10,Rural,ML Engineer,43927,0 +35712,Male,24,Bachelors,14,54,28,2,52,5.0,6,96,Urban,ML Engineer,143283,0 +35713,Female,49,Diploma,2,4,32,13,61,5.0,2,47,Semi-Urban,Software Engineer,25006,0 +35714,Female,58,High School,9,6,90,70,59,7.0,2,63,Semi-Urban,Manager,89776,0 +35715,Male,22,High School,14,95,48,53,6,7.0,0,38,Urban,Software Engineer,108071,0 +35716,Male,39,Diploma,11,85,66,39,96,0.0,5,56,Urban,ML Engineer,31737,1 +35717,Female,57,High School,0,13,22,56,77,8.0,6,16,Urban,ML Engineer,101379,0 +35718,Male,23,High School,14,22,37,49,82,1.0,7,22,Semi-Urban,Software Engineer,34984,0 +35719,Other,52,Masters,3,66,48,5,20,1.0,5,73,Urban,Manager,134795,0 +35720,Male,47,Masters,4,39,13,5,80,0.0,5,96,Rural,Manager,149904,0 +35721,Male,46,Bachelors,9,37,32,81,15,9.0,6,80,Semi-Urban,Data Analyst,128748,0 +35722,Female,22,Bachelors,13,81,42,71,7,4.0,0,62,Rural,Manager,146412,1 +35723,Male,55,Bachelors,3,47,68,82,0,7.0,3,67,Urban,ML Engineer,102486,1 +35724,Male,22,Diploma,5,99,2,9,88,3.0,6,96,Rural,Manager,69372,0 +35725,Male,46,Diploma,4,98,28,50,16,9.0,2,46,Urban,Software Engineer,118132,0 +35726,Female,22,Diploma,4,32,17,8,68,5.0,3,62,Rural,Data Analyst,142757,0 +35727,Male,53,Bachelors,10,75,17,42,66,6.0,7,22,Urban,Software Engineer,133651,0 +35728,Male,35,High School,19,73,7,67,31,8.0,4,84,Semi-Urban,Manager,54619,0 +35729,Male,21,High School,4,26,73,88,32,8.0,2,45,Urban,Software Engineer,30624,0 +35730,Female,52,High School,7,22,81,60,35,5.0,1,75,Semi-Urban,ML Engineer,43926,0 +35731,Male,39,Bachelors,17,67,93,94,85,7.0,1,17,Rural,Software Engineer,97213,1 +35732,Male,34,Diploma,4,3,38,26,20,4.0,4,99,Urban,HR Executive,91871,0 +35733,Male,28,Masters,10,26,49,26,56,3.0,3,96,Urban,HR Executive,20590,0 +35734,Female,32,Bachelors,8,29,48,61,19,6.0,3,62,Rural,HR Executive,97826,0 +35735,Female,35,Masters,9,35,20,25,25,5.0,4,42,Urban,ML Engineer,131427,0 +35736,Male,54,Masters,8,83,66,31,92,8.0,6,29,Urban,ML Engineer,89494,0 +35737,Female,26,Bachelors,0,33,18,61,37,7.0,5,7,Semi-Urban,ML Engineer,45214,0 +35738,Male,47,Bachelors,9,18,51,81,10,2.0,5,25,Urban,HR Executive,20992,0 +35739,Male,47,Diploma,2,34,38,63,55,2.0,4,51,Urban,Software Engineer,106321,0 +35740,Female,47,Diploma,5,44,81,60,46,1.0,7,98,Urban,HR Executive,77963,1 +35741,Male,58,Masters,5,16,35,26,79,1.0,0,33,Urban,Manager,88721,0 +35742,Female,30,PhD,17,9,83,45,16,6.0,5,72,Urban,Manager,20949,0 +35743,Female,57,Bachelors,19,4,9,16,23,4.0,6,37,Urban,Software Engineer,96486,0 +35744,Male,47,Bachelors,15,14,20,44,36,9.0,6,48,Urban,Manager,33514,0 +35745,Male,48,High School,15,51,60,43,12,6.0,7,34,Urban,Data Analyst,32947,0 +35746,Female,29,Diploma,16,19,60,68,99,3.0,2,47,Urban,Software Engineer,129452,0 +35747,Male,48,Masters,19,27,47,35,99,1.0,2,98,Urban,ML Engineer,67518,0 +35748,Male,51,Bachelors,4,76,18,99,76,9.0,4,23,Semi-Urban,ML Engineer,99781,0 +35749,Male,24,Bachelors,17,24,17,2,63,2.0,3,70,Semi-Urban,Manager,55440,0 +35750,Male,42,Diploma,7,86,80,41,26,6.0,6,98,Rural,ML Engineer,55211,1 +35751,Female,53,PhD,17,70,58,22,84,7.0,0,50,Urban,Manager,122886,0 +35752,Male,45,Bachelors,16,28,72,98,66,0.0,6,10,Semi-Urban,Software Engineer,68943,0 +35753,Female,40,Diploma,12,73,32,59,80,0.0,3,16,Urban,Data Analyst,38911,0 +35754,Female,21,Diploma,11,71,86,44,25,3.0,2,70,Urban,Data Analyst,45142,1 +35755,Male,36,High School,13,48,1,24,10,1.0,4,18,Urban,ML Engineer,44684,0 +35756,Male,22,Bachelors,8,63,34,85,95,8.0,1,79,Urban,HR Executive,72483,1 +35757,Female,29,PhD,7,52,45,94,81,0.0,6,27,Urban,ML Engineer,148914,0 +35758,Female,33,PhD,3,4,40,76,12,5.0,5,43,Semi-Urban,Data Analyst,80047,0 +35759,Male,26,High School,14,54,45,49,5,5.0,2,20,Urban,Manager,35396,0 +35760,Male,32,Masters,16,88,49,42,28,9.0,6,55,Rural,Data Analyst,68950,0 +35761,Male,33,Bachelors,16,18,34,8,38,4.0,2,31,Urban,ML Engineer,56075,0 +35762,Male,28,Bachelors,12,88,52,36,20,9.0,7,64,Urban,ML Engineer,63960,1 +35763,Male,21,PhD,13,34,0,67,53,7.0,7,17,Urban,HR Executive,97787,0 +35764,Female,30,Bachelors,18,8,8,11,59,7.0,5,13,Urban,HR Executive,47711,0 +35765,Male,21,Bachelors,9,32,67,28,69,3.0,0,28,Urban,HR Executive,26605,0 +35766,Other,37,Bachelors,3,58,50,8,81,2.0,6,73,Urban,Manager,54802,0 +35767,Female,41,Bachelors,9,21,99,78,66,3.0,6,81,Urban,Manager,32059,1 +35768,Male,32,Bachelors,2,59,71,57,71,8.0,0,0,Urban,Data Analyst,32420,0 +35769,Male,26,Masters,16,73,46,41,82,3.0,7,38,Semi-Urban,Data Analyst,144056,0 +35770,Female,22,High School,14,63,69,31,5,9.0,3,66,Urban,Software Engineer,31096,0 +35771,Female,56,Bachelors,10,89,67,1,1,0.0,7,80,Urban,Software Engineer,148626,0 +35772,Other,23,Diploma,9,33,95,24,32,0.0,0,1,Semi-Urban,HR Executive,83824,0 +35773,Male,38,Bachelors,14,41,18,54,0,3.0,1,16,Semi-Urban,Software Engineer,74669,0 +35774,Male,50,Masters,11,68,57,58,3,1.0,7,10,Rural,Data Analyst,48622,0 +35775,Female,40,Diploma,5,44,68,51,64,6.0,4,71,Urban,Manager,53154,0 +35776,Male,52,Bachelors,11,92,4,62,30,7.0,1,70,Urban,Software Engineer,22712,0 +35777,Female,41,High School,17,28,55,99,81,3.0,3,10,Urban,Data Analyst,129046,0 +35778,Male,44,Masters,9,61,52,63,84,4.0,0,55,Urban,ML Engineer,116715,0 +35779,Female,40,High School,0,5,11,42,44,8.0,0,8,Rural,Software Engineer,91055,0 +35780,Male,58,Bachelors,6,70,76,92,27,3.0,0,93,Urban,HR Executive,67144,1 +35781,Female,30,High School,18,91,65,77,94,3.0,2,36,Urban,ML Engineer,91826,1 +35782,Male,26,Bachelors,9,86,18,69,23,4.0,6,42,Rural,ML Engineer,60394,0 +35783,Other,37,Diploma,15,17,98,30,95,3.0,4,57,Semi-Urban,ML Engineer,145443,0 +35784,Male,57,Bachelors,10,30,61,91,24,1.0,7,26,Semi-Urban,Manager,123453,0 +35785,Male,22,Bachelors,1,50,28,62,55,0.0,0,81,Semi-Urban,Data Analyst,60674,0 +35786,Male,40,Bachelors,3,92,29,32,57,2.0,7,28,Semi-Urban,Manager,32490,0 +35787,Female,35,Masters,12,0,62,71,58,3.0,1,70,Semi-Urban,HR Executive,112850,0 +35788,Male,49,High School,18,83,58,67,5,8.0,5,34,Rural,Data Analyst,125378,1 +35789,Male,27,Bachelors,19,36,11,2,83,0.0,7,40,Urban,Data Analyst,92903,0 +35790,Male,56,Bachelors,3,85,87,25,40,3.0,6,38,Urban,HR Executive,131191,1 +35791,Male,48,High School,4,12,63,9,90,0.0,0,27,Semi-Urban,Data Analyst,55944,0 +35792,Male,45,Bachelors,10,14,89,55,92,8.0,5,89,Urban,Manager,92365,1 +35793,Male,25,High School,7,39,2,5,92,1.0,7,74,Rural,HR Executive,59801,0 +35794,Female,50,High School,13,32,97,0,62,1.0,2,90,Urban,ML Engineer,135204,0 +35795,Male,50,Bachelors,7,5,46,84,55,1.0,7,39,Semi-Urban,Manager,106388,0 +35796,Female,54,Bachelors,9,76,60,15,17,8.0,3,78,Urban,ML Engineer,47653,0 +35797,Female,27,Bachelors,7,83,65,41,92,7.0,6,1,Rural,ML Engineer,110186,0 +35798,Female,37,High School,12,3,73,82,90,2.0,1,42,Urban,ML Engineer,50300,0 +35799,Female,25,Bachelors,17,87,83,42,40,2.0,6,14,Rural,ML Engineer,101153,0 +35800,Male,59,Diploma,1,38,2,23,57,7.0,4,22,Rural,Data Analyst,95752,0 +35801,Female,34,Masters,6,75,88,95,3,3.0,2,15,Urban,ML Engineer,59633,1 +35802,Male,29,Bachelors,12,41,55,56,20,7.0,7,67,Urban,Data Analyst,120073,0 +35803,Male,21,Masters,9,28,1,10,54,5.0,3,95,Semi-Urban,Data Analyst,147687,0 +35804,Female,39,Bachelors,11,62,91,35,97,4.0,2,77,Semi-Urban,Manager,69152,1 +35805,Female,53,Masters,16,72,78,66,48,9.0,0,46,Urban,ML Engineer,79024,1 +35806,Male,38,Bachelors,6,64,58,55,0,2.0,3,38,Urban,HR Executive,61990,0 +35807,Male,28,High School,12,77,66,91,57,7.0,1,6,Rural,ML Engineer,25805,1 +35808,Male,22,Bachelors,9,72,47,99,19,9.0,6,31,Rural,Manager,109752,1 +35809,Male,26,Masters,14,58,37,39,97,6.0,0,38,Urban,Software Engineer,78196,0 +35810,Female,58,Bachelors,19,77,45,68,85,0.0,5,77,Urban,ML Engineer,41301,1 +35811,Male,49,Bachelors,8,94,65,83,74,3.0,5,63,Urban,Software Engineer,95128,1 +35812,Male,24,Masters,3,30,97,93,52,3.0,6,77,Rural,ML Engineer,73261,1 +35813,Male,27,Masters,6,62,90,46,98,8.0,0,13,Urban,ML Engineer,56136,0 +35814,Female,42,Bachelors,2,7,89,44,99,7.0,4,13,Urban,ML Engineer,49679,0 +35815,Female,21,Diploma,19,99,26,33,29,3.0,4,38,Urban,Manager,97943,0 +35816,Female,37,Masters,9,52,43,3,78,4.0,7,15,Semi-Urban,HR Executive,91176,0 +35817,Male,44,Bachelors,4,7,36,56,5,2.0,5,0,Semi-Urban,Manager,57147,0 +35818,Female,49,High School,15,98,21,20,62,6.0,1,90,Rural,ML Engineer,83822,0 +35819,Male,28,Masters,12,5,48,27,36,0.0,2,96,Rural,Manager,130523,0 +35820,Female,37,Bachelors,12,62,94,40,1,6.0,3,3,Urban,Data Analyst,141499,0 +35821,Male,37,PhD,19,57,56,74,44,9.0,3,44,Urban,ML Engineer,59896,0 +35822,Male,58,Diploma,14,80,88,78,37,0.0,1,27,Semi-Urban,Data Analyst,22783,1 +35823,Male,40,PhD,6,73,78,79,59,4.0,6,13,Semi-Urban,Manager,33823,1 +35824,Male,52,Masters,7,17,65,23,77,9.0,5,12,Urban,Data Analyst,73763,0 +35825,Male,37,High School,18,40,93,70,16,7.0,3,72,Rural,ML Engineer,100218,1 +35826,Female,46,Masters,9,64,52,58,97,6.0,5,21,Urban,Software Engineer,20983,0 +35827,Male,50,Bachelors,13,40,70,69,42,3.0,2,65,Semi-Urban,Software Engineer,97646,1 +35828,Male,41,Bachelors,11,21,98,51,18,1.0,4,0,Semi-Urban,Software Engineer,113274,0 +35829,Male,43,Diploma,3,86,88,70,94,1.0,6,90,Urban,Software Engineer,84636,1 +35830,Male,46,High School,13,51,83,29,15,1.0,6,18,Urban,ML Engineer,122380,0 +35831,Female,33,Bachelors,19,85,41,77,68,0.0,0,65,Semi-Urban,Software Engineer,97125,1 +35832,Male,23,Diploma,10,18,43,86,6,3.0,3,87,Semi-Urban,ML Engineer,54842,0 +35833,Female,21,Bachelors,4,86,0,60,69,3.0,3,10,Urban,Software Engineer,36173,0 +35834,Male,42,Masters,9,54,92,61,31,1.0,3,68,Semi-Urban,ML Engineer,30368,1 +35835,Female,41,Bachelors,4,10,17,71,78,4.0,1,8,Rural,Manager,128395,0 +35836,Male,58,Masters,2,54,90,79,13,0.0,6,58,Semi-Urban,Software Engineer,33702,1 +35837,Female,40,Masters,7,14,80,15,93,1.0,4,36,Urban,HR Executive,118653,0 +35838,Male,45,PhD,15,59,3,72,19,6.0,0,8,Urban,ML Engineer,34902,0 +35839,Female,38,Bachelors,6,54,30,33,43,1.0,4,53,Semi-Urban,Data Analyst,138169,0 +35840,Male,33,Masters,10,33,15,53,41,7.0,5,69,Rural,ML Engineer,36079,0 +35841,Male,39,Masters,19,66,19,17,88,1.0,2,30,Semi-Urban,ML Engineer,30098,0 +35842,Male,21,Masters,6,55,5,37,95,5.0,7,16,Semi-Urban,Manager,104796,0 +35843,Female,59,Masters,16,7,42,27,67,3.0,0,37,Urban,HR Executive,62703,0 +35844,Male,38,Masters,9,47,15,80,3,7.0,4,18,Urban,Software Engineer,140759,0 +35845,Male,43,Bachelors,0,50,67,98,23,0.0,4,72,Rural,Data Analyst,88733,1 +35846,Female,45,Masters,11,9,44,48,17,1.0,1,57,Urban,Software Engineer,131891,0 +35847,Female,37,Bachelors,3,71,49,45,90,8.0,7,9,Urban,Data Analyst,71518,0 +35848,Other,42,Masters,18,30,83,8,41,5.0,6,70,Urban,ML Engineer,54596,0 +35849,Male,56,Masters,0,57,31,45,48,7.0,1,91,Rural,HR Executive,44396,0 +35850,Male,57,Bachelors,11,49,4,94,53,0.0,1,19,Urban,Manager,80269,0 +35851,Male,36,Diploma,4,52,12,46,69,2.0,7,55,Urban,Manager,73201,0 +35852,Female,46,Masters,8,66,59,5,86,9.0,3,36,Semi-Urban,ML Engineer,115248,0 +35853,Female,52,Bachelors,7,58,57,85,79,4.0,7,30,Semi-Urban,Manager,49404,0 +35854,Other,38,Diploma,7,45,10,32,16,9.0,2,4,Semi-Urban,Manager,121996,0 +35855,Female,57,Diploma,2,82,52,64,50,2.0,4,88,Rural,HR Executive,147359,1 +35856,Female,50,Diploma,2,39,40,33,53,0.0,1,83,Urban,HR Executive,117198,0 +35857,Other,41,Diploma,14,39,44,77,4,1.0,5,13,Urban,Manager,108715,0 +35858,Male,45,Bachelors,5,74,28,54,93,0.0,6,9,Rural,HR Executive,75645,0 +35859,Female,36,Diploma,13,41,61,38,15,4.0,5,64,Urban,ML Engineer,116304,0 +35860,Female,29,Bachelors,5,85,43,74,7,0.0,3,24,Urban,Data Analyst,128523,0 +35861,Male,55,Masters,12,22,6,69,76,2.0,1,70,Urban,Data Analyst,66366,0 +35862,Male,52,Bachelors,19,17,36,21,15,3.0,4,0,Semi-Urban,Software Engineer,74645,0 +35863,Male,58,Bachelors,3,63,32,2,75,8.0,3,9,Urban,Software Engineer,148689,0 +35864,Female,30,Masters,17,24,55,27,65,9.0,1,52,Semi-Urban,Manager,124583,0 +35865,Female,22,Bachelors,1,99,31,7,45,4.0,7,14,Urban,Data Analyst,118687,0 +35866,Male,44,Bachelors,17,70,40,19,69,4.0,7,83,Rural,Manager,79513,0 +35867,Female,54,Bachelors,7,75,69,97,78,8.0,7,58,Rural,Manager,111618,1 +35868,Male,49,Bachelors,0,10,88,63,3,5.0,1,31,Urban,HR Executive,86318,0 +35869,Female,59,Bachelors,6,9,74,36,69,6.0,0,87,Urban,HR Executive,134141,0 +35870,Female,50,Diploma,10,8,2,43,15,1.0,5,43,Rural,Software Engineer,98857,0 +35871,Other,51,Masters,5,60,35,14,8,2.0,5,38,Semi-Urban,ML Engineer,52463,0 +35872,Male,36,High School,18,69,73,30,5,1.0,2,61,Urban,Software Engineer,86588,0 +35873,Female,50,Bachelors,15,60,79,28,84,0.0,3,28,Urban,HR Executive,43049,0 +35874,Male,55,Diploma,17,74,75,76,29,3.0,5,39,Rural,HR Executive,61932,1 +35875,Male,58,Bachelors,4,4,46,12,92,1.0,5,57,Urban,Manager,132665,0 +35876,Male,31,High School,0,71,66,56,35,5.0,7,37,Urban,Data Analyst,37336,0 +35877,Female,26,Bachelors,11,52,2,57,12,6.0,1,13,Semi-Urban,Software Engineer,90437,0 +35878,Other,38,Masters,8,77,11,52,10,0.0,0,8,Urban,Software Engineer,55576,0 +35879,Male,27,Diploma,16,71,97,7,58,9.0,7,21,Urban,Manager,140012,0 +35880,Female,35,Masters,7,54,28,97,69,6.0,4,59,Rural,HR Executive,65316,0 +35881,Male,49,Bachelors,11,46,62,97,17,8.0,6,91,Semi-Urban,ML Engineer,45107,1 +35882,Male,58,Bachelors,0,93,17,28,57,3.0,7,0,Urban,HR Executive,138726,0 +35883,Male,24,Bachelors,3,50,88,69,29,9.0,0,70,Urban,ML Engineer,66555,1 +35884,Male,49,Bachelors,11,8,97,39,50,2.0,7,1,Rural,Data Analyst,119302,0 +35885,Other,36,Bachelors,17,17,45,50,86,1.0,3,54,Rural,Data Analyst,142802,0 +35886,Female,36,Bachelors,18,75,48,38,25,8.0,3,14,Urban,Manager,58376,0 +35887,Male,25,Diploma,1,8,49,84,9,6.0,0,85,Urban,Software Engineer,70352,0 +35888,Female,38,Diploma,10,31,28,64,81,9.0,2,38,Semi-Urban,Manager,55993,0 +35889,Male,41,High School,8,94,89,56,60,6.0,7,38,Semi-Urban,Data Analyst,47961,1 +35890,Male,45,Masters,17,34,99,86,60,9.0,0,1,Semi-Urban,Data Analyst,46641,0 +35891,Male,21,High School,7,47,53,12,9,4.0,7,92,Semi-Urban,Data Analyst,71208,0 +35892,Female,56,Bachelors,6,74,30,44,9,6.0,1,43,Semi-Urban,Data Analyst,41668,0 +35893,Other,26,High School,10,63,94,64,77,0.0,0,89,Rural,Manager,111153,1 +35894,Male,24,Masters,5,25,16,37,69,3.0,6,24,Semi-Urban,HR Executive,98785,0 +35895,Male,24,Bachelors,19,38,18,68,2,0.0,1,95,Semi-Urban,HR Executive,70462,0 +35896,Male,21,Masters,12,73,26,27,34,2.0,3,31,Semi-Urban,HR Executive,97510,0 +35897,Male,53,Diploma,1,98,9,7,18,8.0,2,49,Semi-Urban,HR Executive,47903,0 +35898,Female,23,Masters,16,93,24,46,87,4.0,4,47,Urban,Manager,36492,0 +35899,Male,27,Masters,18,51,98,27,48,2.0,1,28,Rural,Data Analyst,95133,0 +35900,Female,36,Bachelors,5,71,15,3,7,8.0,3,80,Semi-Urban,Software Engineer,136032,0 +35901,Male,43,High School,3,35,30,45,44,3.0,7,84,Urban,HR Executive,48776,0 +35902,Male,36,PhD,15,83,87,44,28,1.0,5,80,Urban,HR Executive,59475,1 +35903,Male,21,PhD,17,8,58,7,47,0.0,5,16,Urban,Software Engineer,56827,0 +35904,Male,22,Bachelors,6,27,68,78,43,2.0,1,0,Urban,Manager,94216,0 +35905,Female,31,High School,4,38,61,18,61,9.0,3,54,Urban,Software Engineer,22407,0 +35906,Male,21,Bachelors,4,34,73,15,58,8.0,4,12,Urban,Manager,32666,0 +35907,Male,34,High School,1,26,93,3,10,9.0,5,40,Urban,HR Executive,146504,0 +35908,Female,22,PhD,5,78,22,84,49,8.0,7,34,Urban,Software Engineer,61587,0 +35909,Other,52,Bachelors,8,71,45,93,86,6.0,1,5,Urban,Data Analyst,118167,0 +35910,Female,50,Masters,4,65,20,14,35,5.0,0,63,Semi-Urban,HR Executive,30250,0 +35911,Male,52,Bachelors,15,11,23,42,36,5.0,3,18,Rural,HR Executive,123737,0 +35912,Male,36,Bachelors,7,30,72,44,75,3.0,1,7,Urban,HR Executive,113066,0 +35913,Female,47,Diploma,2,46,27,95,30,9.0,1,59,Urban,Data Analyst,109302,0 +35914,Female,57,Bachelors,3,76,71,0,37,9.0,4,4,Semi-Urban,ML Engineer,30044,0 +35915,Male,50,Masters,10,87,63,79,47,0.0,2,92,Urban,Data Analyst,35945,1 +35916,Male,21,Masters,0,62,43,97,19,5.0,7,32,Semi-Urban,ML Engineer,29714,0 +35917,Male,31,High School,19,20,24,28,25,6.0,0,41,Urban,Data Analyst,45038,0 +35918,Male,53,Diploma,11,54,88,48,9,8.0,3,94,Urban,ML Engineer,35967,1 +35919,Male,49,Diploma,4,80,0,38,49,6.0,2,64,Urban,Software Engineer,51053,0 +35920,Male,48,Diploma,8,0,44,72,61,4.0,2,4,Urban,Software Engineer,132764,0 +35921,Male,49,High School,10,68,15,91,26,7.0,7,29,Urban,Manager,46961,0 +35922,Male,38,High School,7,84,41,21,58,6.0,2,42,Rural,ML Engineer,111852,0 +35923,Male,58,Bachelors,12,94,34,47,95,9.0,2,47,Semi-Urban,Manager,90412,0 +35924,Male,31,Diploma,5,87,59,27,6,3.0,1,41,Urban,ML Engineer,94898,0 +35925,Male,38,Bachelors,6,56,17,95,40,6.0,3,8,Urban,ML Engineer,53478,0 +35926,Female,46,Masters,5,78,19,15,24,2.0,0,88,Urban,ML Engineer,65213,0 +35927,Male,43,Bachelors,18,26,14,29,97,1.0,7,99,Semi-Urban,Manager,113291,0 +35928,Female,55,Masters,17,13,0,86,91,0.0,2,78,Urban,Data Analyst,47365,0 +35929,Female,56,Bachelors,9,22,83,19,8,0.0,0,86,Rural,Data Analyst,109706,0 +35930,Male,30,Bachelors,6,56,33,1,42,0.0,0,83,Rural,HR Executive,55062,0 +35931,Male,45,Diploma,4,39,75,83,2,3.0,3,55,Rural,ML Engineer,120613,1 +35932,Male,43,Bachelors,7,19,5,61,61,0.0,5,73,Rural,Data Analyst,84768,0 +35933,Female,34,Bachelors,12,79,42,28,78,8.0,0,93,Semi-Urban,HR Executive,86669,1 +35934,Male,38,Masters,4,1,22,60,54,6.0,3,19,Rural,Data Analyst,49717,0 +35935,Male,52,Bachelors,15,35,97,97,3,1.0,7,89,Rural,Data Analyst,129700,1 +35936,Female,27,Diploma,1,27,29,48,18,4.0,7,83,Urban,ML Engineer,143314,0 +35937,Female,35,High School,19,50,6,97,98,1.0,7,84,Urban,Manager,46444,0 +35938,Male,53,PhD,2,29,11,91,70,9.0,4,49,Urban,Manager,70028,0 +35939,Female,34,Diploma,15,75,1,32,46,9.0,5,22,Rural,Software Engineer,92488,0 +35940,Male,22,Masters,14,36,68,92,67,2.0,2,7,Rural,Software Engineer,37200,0 +35941,Female,34,Bachelors,15,87,34,92,57,7.0,6,66,Semi-Urban,Manager,123361,1 +35942,Male,56,Masters,18,43,82,39,73,0.0,3,83,Rural,Software Engineer,78565,1 +35943,Female,47,High School,14,79,62,49,43,8.0,3,18,Semi-Urban,ML Engineer,109533,0 +35944,Male,27,High School,4,70,39,7,70,6.0,7,22,Rural,Software Engineer,68965,0 +35945,Male,48,Diploma,9,91,73,34,53,9.0,7,37,Urban,Manager,129009,1 +35946,Male,30,Bachelors,12,35,6,38,97,8.0,1,70,Semi-Urban,Software Engineer,47629,0 +35947,Female,26,Diploma,2,56,62,36,57,6.0,0,77,Urban,ML Engineer,59528,0 +35948,Male,48,Bachelors,13,32,13,95,52,0.0,3,34,Urban,ML Engineer,112481,0 +35949,Male,23,Bachelors,9,67,54,72,89,0.0,0,58,Urban,ML Engineer,147473,1 +35950,Male,50,Bachelors,8,73,48,96,78,3.0,4,88,Urban,HR Executive,103373,1 +35951,Male,54,High School,18,57,70,91,59,8.0,1,47,Urban,HR Executive,62016,1 +35952,Female,46,Bachelors,13,24,94,79,1,6.0,0,97,Urban,Manager,139170,1 +35953,Other,56,Diploma,11,26,94,45,80,1.0,7,91,Urban,ML Engineer,86292,1 +35954,Female,23,Bachelors,3,40,6,92,46,0.0,4,74,Semi-Urban,ML Engineer,136482,0 +35955,Female,23,Bachelors,4,10,40,44,42,4.0,1,89,Urban,Software Engineer,68585,0 +35956,Male,23,Diploma,8,75,95,46,0,5.0,2,18,Rural,HR Executive,43047,0 +35957,Male,48,Diploma,4,13,55,62,61,5.0,1,41,Semi-Urban,Software Engineer,108036,0 +35958,Male,48,PhD,11,88,14,24,58,8.0,0,27,Urban,Software Engineer,57263,0 +35959,Other,46,PhD,10,24,65,32,79,1.0,3,25,Rural,ML Engineer,114102,0 +35960,Female,36,Bachelors,0,24,92,41,86,0.0,5,97,Urban,Data Analyst,41341,1 +35961,Male,31,Bachelors,14,54,9,4,49,7.0,3,96,Semi-Urban,HR Executive,143487,0 +35962,Male,52,Bachelors,1,63,26,85,82,9.0,0,46,Urban,ML Engineer,82190,0 +35963,Male,46,Diploma,14,75,91,62,85,8.0,0,96,Semi-Urban,HR Executive,54335,1 +35964,Male,27,Bachelors,17,34,15,72,99,0.0,3,11,Urban,HR Executive,23863,0 +35965,Female,55,Diploma,7,26,39,98,30,2.0,3,18,Urban,Data Analyst,45463,0 +35966,Male,54,High School,7,72,9,20,68,5.0,3,29,Urban,HR Executive,112184,0 +35967,Female,48,Bachelors,15,49,62,84,17,9.0,1,97,Urban,ML Engineer,70275,1 +35968,Female,25,Bachelors,3,67,90,16,60,4.0,0,44,Semi-Urban,Manager,116557,0 +35969,Female,32,High School,16,13,13,33,16,0.0,1,85,Semi-Urban,HR Executive,101252,0 +35970,Female,47,High School,12,94,55,63,10,8.0,6,7,Rural,Data Analyst,133886,0 +35971,Male,37,Diploma,16,33,90,63,94,8.0,4,50,Rural,Manager,34254,1 +35972,Other,43,PhD,11,54,47,51,78,5.0,7,94,Rural,Data Analyst,81282,1 +35973,Male,45,Bachelors,19,36,36,52,24,2.0,7,28,Urban,ML Engineer,33069,0 +35974,Female,33,Bachelors,13,13,55,98,84,4.0,0,18,Urban,Data Analyst,144094,0 +35975,Male,28,Bachelors,7,77,35,71,88,5.0,5,8,Urban,Software Engineer,54628,0 +35976,Male,38,Bachelors,11,50,3,83,79,8.0,7,52,Semi-Urban,HR Executive,149117,0 +35977,Male,36,High School,4,41,9,10,56,6.0,0,87,Rural,Data Analyst,117087,0 +35978,Male,33,Bachelors,0,18,99,92,75,8.0,2,7,Rural,Data Analyst,26158,0 +35979,Female,26,Bachelors,11,71,87,83,79,8.0,6,36,Semi-Urban,Manager,80168,1 +35980,Female,44,Bachelors,16,73,93,86,97,2.0,2,88,Urban,ML Engineer,30811,1 +35981,Male,48,PhD,5,94,64,59,57,8.0,2,97,Urban,Manager,134966,1 +35982,Male,46,Bachelors,19,4,84,73,90,0.0,7,87,Semi-Urban,Data Analyst,53894,1 +35983,Female,35,Bachelors,10,91,53,19,63,7.0,7,32,Rural,Software Engineer,139850,0 +35984,Male,52,Bachelors,15,50,4,0,43,9.0,2,26,Urban,Data Analyst,119342,0 +35985,Female,53,Bachelors,9,40,37,32,53,9.0,6,93,Semi-Urban,Manager,68257,0 +35986,Male,46,Diploma,16,43,83,6,83,7.0,6,55,Urban,HR Executive,44032,0 +35987,Female,56,Bachelors,2,78,38,95,54,5.0,1,55,Rural,Data Analyst,82929,1 +35988,Other,31,High School,2,41,79,24,3,1.0,7,44,Urban,ML Engineer,112742,0 +35989,Male,56,Bachelors,3,20,47,26,87,4.0,4,59,Rural,HR Executive,70585,0 +35990,Male,48,Bachelors,19,60,55,62,49,9.0,2,93,Urban,Software Engineer,75008,1 +35991,Female,34,Diploma,19,86,67,79,52,5.0,2,69,Rural,Software Engineer,98934,1 +35992,Female,51,Diploma,3,0,34,25,43,0.0,6,86,Urban,Data Analyst,62106,0 +35993,Other,22,Bachelors,12,84,20,56,77,6.0,6,40,Urban,HR Executive,149003,0 +35994,Male,32,High School,14,25,53,80,54,4.0,7,72,Rural,HR Executive,77862,0 +35995,Male,57,Masters,3,27,16,87,99,3.0,2,13,Urban,Data Analyst,104538,0 +35996,Male,37,Bachelors,11,0,0,71,12,2.0,5,22,Urban,Data Analyst,25822,0 +35997,Male,49,Masters,1,75,42,52,13,9.0,3,79,Urban,Software Engineer,147604,1 +35998,Female,29,Bachelors,11,79,79,26,36,7.0,6,55,Urban,Data Analyst,31114,0 +35999,Male,21,Masters,11,25,68,89,2,5.0,3,60,Urban,Data Analyst,119754,1 +36000,Female,21,Bachelors,13,32,60,61,7,9.0,0,56,Urban,Data Analyst,37983,0 +36001,Female,58,Masters,17,68,95,79,16,8.0,3,89,Semi-Urban,Manager,93530,1 +36002,Other,26,Diploma,6,10,55,41,90,5.0,1,88,Urban,ML Engineer,109162,0 +36003,Male,39,Bachelors,1,97,53,54,20,1.0,7,35,Urban,Data Analyst,90878,1 +36004,Male,46,Diploma,7,6,57,97,21,8.0,3,10,Urban,HR Executive,143379,0 +36005,Female,42,Masters,3,18,88,76,68,9.0,6,44,Semi-Urban,Software Engineer,136160,0 +36006,Male,21,Bachelors,0,95,24,33,2,4.0,7,18,Urban,HR Executive,85466,0 +36007,Female,56,Masters,1,91,77,59,61,7.0,7,90,Urban,HR Executive,48916,1 +36008,Female,24,Bachelors,3,57,94,42,21,9.0,3,21,Urban,Manager,61747,0 +36009,Male,36,Diploma,13,30,35,94,47,2.0,3,55,Rural,Manager,136166,0 +36010,Male,44,Bachelors,18,64,92,78,37,1.0,3,21,Urban,HR Executive,109131,1 +36011,Male,37,Bachelors,13,21,74,3,14,7.0,0,25,Urban,Manager,101340,0 +36012,Female,34,High School,3,53,67,57,46,8.0,7,59,Urban,HR Executive,40953,0 +36013,Male,48,Masters,4,70,83,15,98,1.0,2,0,Semi-Urban,Data Analyst,95724,0 +36014,Female,40,Masters,16,22,17,81,0,2.0,5,39,Urban,Data Analyst,77037,0 +36015,Female,35,PhD,19,91,78,50,63,5.0,4,83,Semi-Urban,Manager,74776,1 +36016,Male,38,Masters,4,49,81,86,34,5.0,3,49,Semi-Urban,Software Engineer,137618,1 +36017,Other,53,Bachelors,16,86,61,4,4,5.0,0,83,Urban,Manager,56308,0 +36018,Female,41,Bachelors,17,18,70,86,43,8.0,1,69,Urban,Manager,47878,1 +36019,Female,54,Bachelors,8,20,71,71,64,9.0,1,95,Urban,Manager,84260,1 +36020,Male,29,High School,5,93,29,40,9,6.0,3,85,Semi-Urban,Manager,26804,1 +36021,Male,57,Bachelors,7,65,90,64,20,6.0,0,55,Rural,HR Executive,42639,1 +36022,Male,30,High School,11,99,45,32,5,5.0,1,44,Semi-Urban,Data Analyst,54401,0 +36023,Male,24,Bachelors,9,87,41,26,12,5.0,2,41,Urban,HR Executive,80576,0 +36024,Male,50,Bachelors,16,98,8,39,67,9.0,1,17,Urban,Software Engineer,120524,0 +36025,Female,58,Masters,13,64,22,51,82,6.0,6,76,Urban,HR Executive,111711,0 +36026,Male,37,Diploma,3,77,96,67,99,2.0,0,31,Urban,ML Engineer,43521,1 +36027,Other,43,Bachelors,12,27,56,37,31,6.0,6,6,Urban,HR Executive,122036,0 +36028,Male,25,High School,10,1,41,92,60,4.0,7,73,Urban,ML Engineer,99671,0 +36029,Male,55,Bachelors,4,77,37,85,9,1.0,6,42,Urban,Manager,81398,1 +36030,Male,44,Diploma,19,49,5,21,9,4.0,0,0,Urban,Manager,38588,0 +36031,Other,45,Diploma,14,31,30,46,13,5.0,1,43,Semi-Urban,Data Analyst,138042,0 +36032,Male,43,Bachelors,11,6,79,82,66,4.0,5,45,Urban,Manager,64140,0 +36033,Male,54,Masters,14,33,81,70,52,2.0,7,75,Semi-Urban,Software Engineer,106485,1 +36034,Female,35,Masters,19,49,53,62,69,4.0,4,8,Rural,HR Executive,72475,0 +36035,Male,31,Bachelors,17,14,83,60,89,3.0,3,63,Urban,Software Engineer,106583,0 +36036,Female,55,Bachelors,8,65,61,60,62,7.0,0,31,Urban,Software Engineer,149129,0 +36037,Male,30,Diploma,19,30,78,39,0,8.0,4,16,Rural,HR Executive,99723,0 +36038,Male,23,Bachelors,16,15,74,22,5,8.0,5,80,Urban,Software Engineer,62762,0 +36039,Male,47,Bachelors,12,8,18,74,42,7.0,0,4,Semi-Urban,Data Analyst,96333,0 +36040,Female,30,High School,4,97,18,38,89,2.0,1,86,Urban,ML Engineer,132738,0 +36041,Female,30,PhD,4,97,77,20,29,0.0,2,65,Urban,Data Analyst,85796,1 +36042,Male,21,Masters,10,27,40,89,69,8.0,4,70,Urban,Software Engineer,91450,0 +36043,Male,29,Bachelors,4,22,30,40,58,3.0,6,72,Rural,Data Analyst,137422,0 +36044,Male,47,High School,14,31,88,59,97,0.0,2,48,Semi-Urban,Manager,74497,0 +36045,Male,51,Masters,10,93,30,40,39,3.0,3,28,Urban,ML Engineer,86175,0 +36046,Male,27,Bachelors,9,19,87,76,32,2.0,7,41,Urban,Software Engineer,48600,0 +36047,Male,37,High School,1,37,70,10,98,6.0,5,94,Urban,HR Executive,104428,0 +36048,Male,59,Bachelors,3,99,64,93,59,0.0,3,21,Semi-Urban,Manager,127330,1 +36049,Male,39,Diploma,2,40,8,64,90,5.0,2,92,Urban,Data Analyst,142889,0 +36050,Female,23,Bachelors,13,24,84,8,92,3.0,3,98,Semi-Urban,Data Analyst,74728,0 +36051,Female,54,Bachelors,7,66,86,96,44,4.0,4,55,Rural,Software Engineer,24389,1 +36052,Male,33,Masters,19,33,3,69,44,8.0,7,26,Semi-Urban,Data Analyst,81616,0 +36053,Female,36,Diploma,10,45,47,37,3,9.0,4,20,Rural,Manager,133977,0 +36054,Male,49,Diploma,12,11,80,21,20,7.0,3,35,Urban,Data Analyst,50468,0 +36055,Male,24,High School,19,83,8,62,65,7.0,0,39,Urban,Data Analyst,61914,0 +36056,Female,36,Diploma,16,90,70,37,57,9.0,0,86,Urban,HR Executive,32003,1 +36057,Female,39,Bachelors,2,45,73,69,38,9.0,3,3,Urban,ML Engineer,48882,0 +36058,Male,47,Bachelors,3,42,10,96,15,4.0,7,35,Semi-Urban,Software Engineer,109092,0 +36059,Male,59,Masters,0,37,43,16,25,1.0,4,93,Urban,HR Executive,51449,0 +36060,Female,53,PhD,8,86,51,88,52,3.0,6,31,Rural,Software Engineer,61668,1 +36061,Female,36,Bachelors,17,69,71,82,85,8.0,4,47,Urban,ML Engineer,109083,1 +36062,Female,42,Masters,8,68,54,35,89,2.0,4,75,Urban,HR Executive,118944,0 +36063,Female,44,High School,11,86,14,42,82,1.0,5,61,Urban,HR Executive,113380,0 +36064,Male,58,Bachelors,4,7,39,0,98,9.0,3,39,Urban,Manager,32124,0 +36065,Male,35,Diploma,14,0,60,87,97,6.0,3,89,Urban,Manager,145940,1 +36066,Other,31,Masters,8,68,3,48,72,4.0,4,94,Urban,Manager,25621,0 +36067,Male,45,Bachelors,2,89,46,95,9,7.0,5,47,Urban,ML Engineer,107936,1 +36068,Male,28,Bachelors,18,70,90,25,93,8.0,6,21,Urban,HR Executive,20939,0 +36069,Female,36,Bachelors,0,4,10,87,20,2.0,0,35,Urban,HR Executive,124306,0 +36070,Male,37,Diploma,6,54,58,64,6,2.0,3,89,Semi-Urban,Data Analyst,143378,1 +36071,Male,59,Bachelors,2,32,66,74,99,5.0,0,51,Rural,ML Engineer,110360,0 +36072,Male,55,Masters,7,61,6,33,12,4.0,2,15,Urban,Manager,101767,0 +36073,Male,21,Masters,16,81,1,4,99,4.0,6,76,Rural,Manager,145673,0 +36074,Female,42,Masters,16,99,10,96,80,5.0,5,57,Urban,Software Engineer,140207,1 +36075,Male,48,Diploma,9,45,52,39,49,9.0,3,17,Semi-Urban,Software Engineer,50486,0 +36076,Male,42,Bachelors,11,57,44,69,68,8.0,4,78,Rural,HR Executive,146030,1 +36077,Male,22,Diploma,12,14,75,91,52,9.0,7,2,Urban,ML Engineer,103827,0 +36078,Male,26,Diploma,4,31,8,58,17,1.0,3,4,Semi-Urban,Manager,123074,0 +36079,Male,35,Bachelors,16,64,13,84,14,4.0,6,6,Urban,HR Executive,68060,0 +36080,Male,50,High School,5,2,32,50,86,2.0,5,96,Urban,Manager,54942,0 +36081,Female,42,PhD,19,59,56,12,79,6.0,2,27,Rural,ML Engineer,142698,0 +36082,Female,33,Bachelors,8,38,93,96,16,4.0,3,34,Urban,Software Engineer,118413,1 +36083,Male,49,Diploma,17,7,28,37,25,7.0,7,19,Semi-Urban,ML Engineer,71714,0 +36084,Male,57,Bachelors,4,96,61,31,54,4.0,6,71,Urban,Manager,25849,1 +36085,Male,58,Masters,6,68,31,49,41,0.0,5,1,Urban,HR Executive,102149,0 +36086,Male,41,Diploma,19,71,37,0,31,1.0,4,91,Rural,HR Executive,111712,0 +36087,Male,50,Diploma,9,74,23,84,30,6.0,2,51,Urban,HR Executive,29711,0 +36088,Male,37,Diploma,9,85,11,25,44,7.0,5,68,Semi-Urban,Manager,60426,0 +36089,Male,50,Diploma,3,1,84,69,63,6.0,7,31,Rural,Manager,79793,0 +36090,Other,54,Masters,10,29,64,82,84,7.0,5,82,Urban,Data Analyst,122957,1 +36091,Female,57,PhD,7,37,75,65,88,0.0,6,54,Urban,ML Engineer,79352,0 +36092,Female,50,Diploma,6,82,86,2,37,5.0,3,49,Semi-Urban,ML Engineer,147438,0 +36093,Male,52,Diploma,18,24,68,60,9,3.0,4,54,Rural,ML Engineer,92777,0 +36094,Male,56,PhD,16,94,82,44,74,4.0,1,8,Semi-Urban,Manager,77852,0 +36095,Male,54,Diploma,8,79,0,2,49,1.0,5,40,Semi-Urban,Data Analyst,79591,0 +36096,Other,27,Diploma,0,21,27,85,52,5.0,7,89,Urban,Software Engineer,21154,0 +36097,Male,37,Diploma,7,21,45,23,0,0.0,0,57,Semi-Urban,Data Analyst,60887,0 +36098,Male,47,Bachelors,16,77,8,41,45,3.0,4,29,Urban,Software Engineer,119944,0 +36099,Male,49,Masters,11,36,53,72,83,9.0,1,27,Semi-Urban,ML Engineer,37819,0 +36100,Female,57,Bachelors,7,12,80,10,95,9.0,5,81,Urban,Manager,43263,0 +36101,Male,26,Bachelors,11,53,65,75,72,5.0,2,48,Semi-Urban,Manager,23285,1 +36102,Male,45,Diploma,0,54,69,25,33,0.0,6,80,Semi-Urban,Manager,114251,0 +36103,Other,58,Bachelors,5,78,71,3,79,6.0,5,94,Urban,HR Executive,68957,1 +36104,Male,35,Bachelors,13,13,63,44,69,1.0,2,53,Urban,Software Engineer,50558,0 +36105,Male,43,Masters,13,44,86,43,43,1.0,5,49,Urban,Data Analyst,44643,0 +36106,Male,57,Diploma,14,37,59,61,53,5.0,2,6,Urban,Manager,77832,0 +36107,Female,44,Bachelors,6,50,1,76,3,5.0,6,75,Rural,ML Engineer,116766,0 +36108,Male,53,Masters,15,40,67,95,38,9.0,3,35,Rural,HR Executive,91686,1 +36109,Male,41,Masters,12,35,49,58,22,8.0,3,59,Rural,Data Analyst,149540,0 +36110,Female,55,Diploma,15,92,21,75,2,5.0,4,26,Urban,Manager,92056,0 +36111,Male,50,Diploma,15,44,70,68,1,4.0,0,73,Semi-Urban,Software Engineer,83223,1 +36112,Female,50,Bachelors,13,32,54,56,26,3.0,7,90,Urban,ML Engineer,88283,0 +36113,Female,46,Bachelors,5,75,88,67,22,1.0,0,72,Urban,Manager,136584,1 +36114,Male,51,Bachelors,17,40,10,19,31,8.0,0,76,Semi-Urban,Data Analyst,31813,0 +36115,Male,43,Masters,7,62,92,64,93,7.0,5,42,Urban,Software Engineer,148489,1 +36116,Female,54,High School,11,24,67,5,91,6.0,7,82,Urban,ML Engineer,36727,0 +36117,Female,45,Masters,3,57,39,66,37,1.0,3,49,Urban,Data Analyst,97379,0 +36118,Female,30,Bachelors,11,57,32,65,65,2.0,4,19,Semi-Urban,Software Engineer,132347,0 +36119,Male,32,Masters,5,40,41,81,91,8.0,0,39,Urban,HR Executive,62363,0 +36120,Female,27,Bachelors,15,5,94,3,87,6.0,4,60,Semi-Urban,Data Analyst,114949,0 +36121,Male,49,Bachelors,1,67,36,22,11,3.0,1,95,Urban,Manager,94332,0 +36122,Male,51,Bachelors,7,3,31,11,21,2.0,4,59,Urban,Software Engineer,140186,0 +36123,Other,54,Bachelors,0,76,5,10,88,6.0,4,46,Urban,ML Engineer,67533,0 +36124,Female,36,Bachelors,17,0,38,97,65,9.0,4,46,Urban,HR Executive,38311,0 +36125,Male,39,Bachelors,8,44,46,33,13,3.0,6,66,Semi-Urban,Data Analyst,96339,0 +36126,Female,33,Masters,9,79,66,8,30,7.0,1,96,Urban,ML Engineer,117046,1 +36127,Male,45,Masters,16,92,26,92,98,5.0,4,18,Urban,Manager,126360,0 +36128,Male,52,Bachelors,11,84,25,47,41,5.0,7,37,Semi-Urban,ML Engineer,99887,0 +36129,Female,45,Diploma,16,85,19,73,17,4.0,6,73,Semi-Urban,Software Engineer,147653,1 +36130,Male,30,Masters,9,24,28,54,70,3.0,3,96,Urban,Manager,122596,0 +36131,Female,38,Bachelors,11,96,77,4,91,4.0,0,71,Urban,Data Analyst,148619,1 +36132,Female,58,Diploma,0,79,9,95,96,3.0,1,90,Urban,Software Engineer,127368,1 +36133,Male,43,Bachelors,0,42,59,81,63,2.0,4,78,Urban,ML Engineer,106362,1 +36134,Female,54,High School,16,60,78,22,9,5.0,3,36,Rural,Software Engineer,85615,0 +36135,Male,22,Diploma,2,64,3,75,50,8.0,2,87,Urban,Software Engineer,63523,0 +36136,Male,48,Masters,19,70,80,15,13,7.0,3,39,Semi-Urban,Software Engineer,137039,0 +36137,Female,28,Bachelors,6,79,99,40,97,6.0,2,49,Semi-Urban,HR Executive,133825,1 +36138,Female,57,Bachelors,12,5,70,8,60,8.0,2,60,Semi-Urban,Manager,139815,0 +36139,Male,25,Bachelors,1,34,14,93,45,1.0,1,73,Urban,Software Engineer,97585,0 +36140,Male,49,Bachelors,19,5,9,38,62,3.0,5,2,Urban,HR Executive,100398,0 +36141,Male,38,High School,0,95,54,40,70,7.0,4,9,Semi-Urban,Software Engineer,109445,0 +36142,Male,57,High School,15,17,21,76,39,6.0,5,79,Urban,Software Engineer,130724,0 +36143,Male,39,Bachelors,16,65,47,66,20,9.0,5,74,Urban,Software Engineer,107782,1 +36144,Male,39,Masters,0,6,87,66,2,5.0,5,13,Urban,Data Analyst,138451,0 +36145,Male,23,Bachelors,12,97,14,62,92,9.0,6,78,Rural,Manager,97257,1 +36146,Female,26,Diploma,17,0,39,76,24,5.0,0,46,Semi-Urban,HR Executive,83618,0 +36147,Male,47,Bachelors,4,7,90,92,93,1.0,2,8,Rural,Software Engineer,51251,0 +36148,Male,28,High School,19,68,83,82,99,6.0,3,21,Urban,HR Executive,110573,1 +36149,Other,30,Bachelors,2,91,35,83,24,0.0,2,32,Semi-Urban,Data Analyst,100022,1 +36150,Male,57,Diploma,9,7,41,86,85,3.0,4,69,Semi-Urban,Manager,83199,0 +36151,Female,29,PhD,18,53,27,31,47,5.0,4,93,Urban,Manager,23989,0 +36152,Male,39,Masters,13,92,13,78,39,5.0,7,3,Urban,Manager,39158,0 +36153,Male,53,High School,2,96,40,40,94,2.0,3,41,Urban,Manager,109006,0 +36154,Male,55,Diploma,10,45,72,95,11,2.0,2,46,Urban,Data Analyst,138395,1 +36155,Male,51,Bachelors,16,50,56,0,42,2.0,0,80,Urban,ML Engineer,45104,0 +36156,Male,36,Masters,5,62,4,23,70,6.0,3,9,Semi-Urban,Manager,54398,0 +36157,Male,34,Diploma,3,8,22,90,81,9.0,2,71,Urban,HR Executive,38484,0 +36158,Male,40,High School,3,9,82,21,89,6.0,0,76,Semi-Urban,Software Engineer,27304,0 +36159,Male,54,High School,11,63,84,33,98,5.0,3,8,Urban,Manager,100194,0 +36160,Male,57,Bachelors,1,28,9,62,30,4.0,7,95,Rural,ML Engineer,116712,0 +36161,Other,28,Bachelors,16,85,20,34,69,5.0,1,40,Urban,Data Analyst,34980,0 +36162,Female,25,PhD,17,64,47,96,65,9.0,7,15,Urban,Data Analyst,51373,0 +36163,Female,27,Bachelors,17,29,89,21,78,8.0,2,56,Rural,HR Executive,82811,0 +36164,Female,21,PhD,12,13,26,79,48,8.0,3,25,Rural,Software Engineer,91404,0 +36165,Male,36,PhD,10,43,90,94,71,4.0,4,67,Urban,ML Engineer,110894,1 +36166,Male,46,High School,8,46,55,40,10,6.0,5,33,Urban,Manager,32867,0 +36167,Female,29,PhD,8,94,8,45,65,9.0,1,21,Urban,HR Executive,103043,0 +36168,Male,49,High School,12,12,61,92,42,4.0,7,40,Rural,HR Executive,84860,0 +36169,Male,47,PhD,9,75,87,37,0,3.0,4,83,Rural,ML Engineer,73098,1 +36170,Male,44,Diploma,8,88,93,45,34,9.0,4,98,Urban,HR Executive,127345,1 +36171,Male,30,Bachelors,1,20,13,30,53,3.0,5,16,Urban,ML Engineer,122751,0 +36172,Male,27,High School,12,43,17,50,1,5.0,7,6,Urban,ML Engineer,66136,0 +36173,Other,48,Bachelors,17,27,35,99,75,2.0,5,4,Urban,Data Analyst,135242,0 +36174,Female,40,Diploma,8,22,74,47,14,7.0,5,92,Urban,Manager,44660,0 +36175,Male,54,PhD,10,18,46,46,43,2.0,5,92,Urban,ML Engineer,63729,0 +36176,Female,49,Masters,6,19,79,20,94,8.0,4,20,Urban,HR Executive,138569,0 +36177,Male,22,Bachelors,10,79,64,52,21,6.0,1,68,Rural,HR Executive,39897,1 +36178,Female,22,Bachelors,0,53,13,73,85,9.0,6,29,Semi-Urban,Manager,100261,0 +36179,Female,37,PhD,8,60,68,37,3,2.0,3,96,Semi-Urban,ML Engineer,117847,1 +36180,Male,50,High School,5,31,3,86,22,3.0,7,39,Urban,Manager,36876,0 +36181,Female,30,Bachelors,2,9,86,8,22,9.0,1,61,Semi-Urban,ML Engineer,75935,0 +36182,Male,52,Bachelors,10,6,59,26,31,2.0,4,40,Rural,Data Analyst,81599,0 +36183,Male,27,High School,14,28,40,30,51,2.0,6,2,Semi-Urban,HR Executive,138615,0 +36184,Female,42,Bachelors,5,70,98,50,43,2.0,7,25,Urban,HR Executive,78987,1 +36185,Female,37,Bachelors,15,6,60,87,2,5.0,7,89,Semi-Urban,Software Engineer,34840,1 +36186,Female,35,PhD,9,93,74,8,89,8.0,5,84,Urban,Data Analyst,101471,1 +36187,Other,58,High School,18,7,79,33,3,8.0,6,28,Rural,Software Engineer,68063,0 +36188,Female,35,Diploma,11,4,54,96,69,7.0,6,21,Urban,Software Engineer,132958,0 +36189,Female,47,Bachelors,17,28,54,95,80,2.0,7,86,Semi-Urban,ML Engineer,112965,1 +36190,Female,21,Bachelors,12,58,46,30,30,4.0,5,24,Urban,Software Engineer,138690,0 +36191,Male,50,Bachelors,18,19,70,76,76,9.0,5,93,Urban,ML Engineer,62436,1 +36192,Male,29,Masters,5,48,98,82,61,0.0,5,26,Urban,Software Engineer,91901,1 +36193,Male,44,Masters,6,30,26,19,13,3.0,0,73,Urban,HR Executive,76331,0 +36194,Male,28,Diploma,13,93,87,26,36,2.0,0,33,Semi-Urban,Data Analyst,51115,1 +36195,Female,58,Bachelors,18,63,67,24,50,6.0,3,27,Urban,Software Engineer,52628,0 +36196,Male,31,Bachelors,6,66,5,62,81,5.0,0,22,Urban,Software Engineer,114501,0 +36197,Male,49,Bachelors,4,72,59,25,42,2.0,2,46,Urban,ML Engineer,90194,0 +36198,Female,46,Diploma,3,23,12,57,46,3.0,5,18,Rural,Data Analyst,113959,0 +36199,Male,27,PhD,11,89,62,95,22,1.0,2,42,Rural,ML Engineer,24510,1 +36200,Male,30,Bachelors,5,81,70,20,53,1.0,0,87,Urban,ML Engineer,62422,1 +36201,Male,47,Diploma,19,40,6,16,26,3.0,3,55,Semi-Urban,Manager,24103,0 +36202,Female,24,High School,2,13,37,21,37,9.0,4,42,Rural,HR Executive,56976,0 +36203,Male,55,Diploma,9,53,10,6,4,4.0,6,8,Semi-Urban,Data Analyst,69652,0 +36204,Other,57,Bachelors,1,90,57,91,6,5.0,7,52,Rural,HR Executive,46573,1 +36205,Male,44,Masters,16,69,6,7,46,2.0,2,87,Urban,Manager,57009,0 +36206,Female,46,Diploma,3,13,73,48,42,1.0,6,3,Rural,Manager,83227,0 +36207,Male,47,Bachelors,14,23,2,44,74,0.0,3,93,Urban,Data Analyst,38435,0 +36208,Male,50,Masters,5,72,43,83,52,2.0,0,82,Urban,HR Executive,31045,1 +36209,Male,52,High School,9,72,40,48,23,5.0,2,10,Urban,Data Analyst,48273,0 +36210,Male,46,Diploma,8,96,75,43,35,8.0,0,28,Semi-Urban,Manager,130839,1 +36211,Male,49,Masters,19,30,0,63,23,8.0,5,59,Rural,ML Engineer,97986,0 +36212,Male,40,Bachelors,5,88,94,77,53,6.0,0,85,Urban,Data Analyst,105126,1 +36213,Male,44,Masters,14,88,73,85,75,7.0,1,4,Semi-Urban,ML Engineer,38357,1 +36214,Female,57,PhD,4,65,46,53,83,7.0,0,8,Urban,HR Executive,26193,0 +36215,Male,54,Masters,19,79,45,78,88,9.0,3,8,Urban,ML Engineer,24330,0 +36216,Other,21,Masters,4,48,92,29,95,0.0,1,23,Rural,Software Engineer,121727,0 +36217,Female,37,High School,12,46,30,5,6,9.0,6,0,Urban,HR Executive,125739,0 +36218,Male,52,Masters,4,78,56,90,90,6.0,5,26,Urban,ML Engineer,23030,1 +36219,Male,42,Bachelors,1,19,18,89,23,1.0,3,56,Urban,HR Executive,110423,0 +36220,Female,43,High School,4,54,80,66,0,0.0,3,31,Rural,ML Engineer,106595,0 +36221,Female,45,Bachelors,6,34,59,70,28,6.0,3,94,Urban,Software Engineer,124965,1 +36222,Female,58,Masters,16,65,31,17,36,2.0,5,90,Urban,Data Analyst,125868,0 +36223,Female,51,High School,19,86,94,83,51,3.0,3,69,Urban,ML Engineer,134729,1 +36224,Male,37,Masters,6,32,68,89,37,5.0,0,80,Semi-Urban,HR Executive,134850,1 +36225,Male,42,Bachelors,18,50,7,18,93,8.0,1,75,Urban,HR Executive,145818,0 +36226,Female,35,Bachelors,17,28,37,6,94,3.0,1,15,Urban,ML Engineer,58563,0 +36227,Female,49,Bachelors,10,47,90,6,40,9.0,1,45,Urban,Manager,112519,0 +36228,Female,37,Bachelors,16,66,2,31,17,8.0,4,29,Urban,ML Engineer,32968,0 +36229,Female,27,High School,19,5,55,38,44,0.0,6,83,Urban,Data Analyst,113486,0 +36230,Male,46,Bachelors,17,83,61,52,69,3.0,5,13,Urban,ML Engineer,27578,0 +36231,Other,45,Diploma,0,90,88,0,59,7.0,2,48,Urban,Data Analyst,24065,0 +36232,Female,56,Masters,10,27,40,92,8,6.0,5,80,Urban,Manager,122462,0 +36233,Male,26,Bachelors,6,20,28,1,48,3.0,7,97,Urban,Manager,121963,0 +36234,Male,59,Diploma,3,19,21,68,52,1.0,1,15,Urban,Software Engineer,122502,0 +36235,Male,24,High School,14,10,51,45,23,1.0,0,14,Urban,HR Executive,53451,0 +36236,Female,34,Masters,12,1,19,46,29,3.0,7,54,Urban,Data Analyst,49344,0 +36237,Male,42,Bachelors,13,97,18,95,35,8.0,4,94,Semi-Urban,ML Engineer,113905,1 +36238,Male,42,Bachelors,10,2,63,76,82,2.0,6,70,Semi-Urban,Software Engineer,50539,0 +36239,Male,45,Bachelors,12,27,6,56,54,4.0,7,42,Urban,HR Executive,51518,0 +36240,Male,51,PhD,1,91,98,87,36,2.0,7,36,Urban,HR Executive,100151,1 +36241,Male,25,Bachelors,18,73,19,44,3,4.0,6,77,Semi-Urban,HR Executive,48888,0 +36242,Female,48,Bachelors,18,90,36,32,16,1.0,2,88,Urban,Software Engineer,134687,1 +36243,Female,29,Bachelors,4,26,37,68,44,1.0,2,96,Semi-Urban,Software Engineer,140549,0 +36244,Male,45,High School,7,53,43,48,46,4.0,2,11,Urban,ML Engineer,113363,0 +36245,Female,51,Masters,18,63,33,63,68,3.0,5,80,Semi-Urban,Manager,126716,0 +36246,Female,22,Bachelors,12,37,96,29,16,3.0,7,34,Urban,Data Analyst,79947,0 +36247,Male,34,Masters,5,92,10,50,3,2.0,4,88,Semi-Urban,ML Engineer,60436,1 +36248,Male,57,Bachelors,17,22,98,42,52,5.0,4,4,Urban,HR Executive,49266,0 +36249,Male,29,PhD,7,31,99,63,67,3.0,7,79,Urban,ML Engineer,38398,1 +36250,Male,50,Bachelors,3,66,88,95,34,9.0,0,11,Urban,Software Engineer,146953,1 +36251,Female,41,Bachelors,16,96,22,71,37,3.0,4,6,Urban,Data Analyst,59877,0 +36252,Female,48,Bachelors,9,94,20,0,98,5.0,2,9,Urban,Software Engineer,112453,0 +36253,Male,54,Masters,8,24,56,31,42,6.0,1,4,Rural,Software Engineer,56191,0 +36254,Female,55,High School,5,43,67,88,55,0.0,4,95,Urban,HR Executive,110246,1 +36255,Female,30,High School,18,15,77,64,14,5.0,1,59,Semi-Urban,ML Engineer,57799,0 +36256,Female,56,Diploma,9,66,30,7,28,9.0,0,3,Urban,ML Engineer,74623,0 +36257,Male,33,Bachelors,19,3,98,53,17,3.0,5,45,Urban,Manager,70821,0 +36258,Female,54,Masters,13,57,5,62,51,7.0,6,1,Rural,ML Engineer,40706,0 +36259,Female,46,Masters,0,61,37,87,25,4.0,5,20,Urban,Data Analyst,72952,0 +36260,Female,38,Bachelors,10,95,32,79,61,5.0,4,29,Urban,Manager,68585,0 +36261,Male,29,High School,17,43,33,39,27,8.0,7,20,Urban,Software Engineer,133511,0 +36262,Female,46,Bachelors,17,34,92,7,82,1.0,2,68,Semi-Urban,Data Analyst,117972,0 +36263,Male,22,Bachelors,5,8,66,65,93,9.0,1,81,Rural,HR Executive,44590,0 +36264,Female,30,Masters,1,10,24,91,79,1.0,3,50,Urban,Software Engineer,40271,0 +36265,Female,25,Diploma,10,5,85,41,89,1.0,7,86,Urban,ML Engineer,23148,0 +36266,Male,48,Masters,11,57,16,77,62,1.0,0,72,Rural,HR Executive,43872,0 +36267,Male,36,Masters,8,91,71,51,48,4.0,2,51,Urban,Software Engineer,63153,1 +36268,Female,51,Bachelors,10,4,47,62,92,2.0,1,53,Urban,Software Engineer,50633,0 +36269,Male,59,Bachelors,18,84,83,58,20,5.0,2,67,Urban,ML Engineer,74660,1 +36270,Male,44,Bachelors,6,20,21,35,28,9.0,2,72,Urban,HR Executive,30833,0 +36271,Female,30,Diploma,4,3,90,13,51,4.0,5,96,Urban,HR Executive,130712,0 +36272,Female,57,High School,13,54,19,32,23,0.0,3,81,Urban,Manager,33771,0 +36273,Male,44,High School,17,98,87,34,79,2.0,6,94,Urban,Data Analyst,55923,1 +36274,Male,57,Bachelors,15,52,48,19,22,7.0,0,63,Urban,ML Engineer,117753,0 +36275,Female,46,High School,1,49,11,66,18,5.0,0,17,Rural,ML Engineer,105051,0 +36276,Female,40,Masters,13,38,83,74,34,8.0,6,68,Urban,Manager,147661,1 +36277,Male,33,Masters,5,84,37,7,94,6.0,5,21,Rural,ML Engineer,137180,0 +36278,Male,42,Bachelors,0,57,3,4,7,5.0,0,73,Urban,Manager,74768,0 +36279,Male,41,Masters,18,82,42,83,16,1.0,7,58,Urban,HR Executive,32595,1 +36280,Female,50,Bachelors,5,5,24,34,19,3.0,2,97,Urban,ML Engineer,67557,0 +36281,Male,24,Masters,2,48,57,51,12,6.0,1,35,Urban,Data Analyst,30148,0 +36282,Male,28,High School,12,33,14,68,11,8.0,1,9,Urban,Software Engineer,120586,0 +36283,Male,42,Diploma,8,6,61,87,18,7.0,3,23,Semi-Urban,Manager,126103,0 +36284,Male,33,Bachelors,0,64,10,36,14,7.0,0,65,Rural,Data Analyst,50255,0 +36285,Female,56,Bachelors,3,50,65,91,30,3.0,7,88,Urban,Software Engineer,26477,1 +36286,Male,53,Diploma,14,86,20,58,62,6.0,3,78,Semi-Urban,Manager,107018,1 +36287,Male,34,Masters,13,11,61,84,77,8.0,2,74,Semi-Urban,Software Engineer,63738,0 +36288,Male,46,Bachelors,6,69,67,38,94,9.0,3,96,Rural,Software Engineer,115580,1 +36289,Male,31,Diploma,7,52,13,55,95,2.0,1,26,Semi-Urban,Manager,87639,0 +36290,Female,27,Diploma,19,58,99,94,46,5.0,2,75,Semi-Urban,ML Engineer,92966,1 +36291,Male,31,Bachelors,7,77,25,88,44,3.0,4,78,Urban,Data Analyst,68135,1 +36292,Female,23,Bachelors,16,86,9,41,10,4.0,0,56,Urban,HR Executive,93848,0 +36293,Male,38,Diploma,4,50,16,83,25,3.0,1,65,Semi-Urban,Software Engineer,144596,0 +36294,Male,24,Masters,6,4,91,23,80,9.0,5,19,Rural,Data Analyst,117660,0 +36295,Male,30,Diploma,0,77,38,81,15,7.0,4,29,Semi-Urban,Software Engineer,95576,0 +36296,Female,51,Masters,10,38,4,79,15,9.0,5,28,Rural,Manager,67933,0 +36297,Male,32,Bachelors,10,23,74,51,20,6.0,1,75,Semi-Urban,Manager,25581,0 +36298,Female,54,High School,6,19,18,15,81,2.0,5,37,Urban,ML Engineer,119093,0 +36299,Male,41,PhD,13,6,33,36,35,3.0,1,25,Rural,Data Analyst,87241,0 +36300,Male,36,Bachelors,0,38,95,22,97,3.0,2,39,Urban,ML Engineer,134984,0 +36301,Male,48,Masters,0,64,57,41,57,9.0,2,57,Urban,Manager,74511,0 +36302,Female,49,Diploma,4,14,38,7,92,1.0,4,93,Semi-Urban,Manager,129509,0 +36303,Male,57,Bachelors,0,45,46,58,5,6.0,0,29,Urban,ML Engineer,43312,0 +36304,Female,58,Bachelors,16,4,57,50,67,9.0,7,7,Urban,Manager,142641,0 +36305,Other,26,Bachelors,12,86,18,62,16,0.0,0,59,Rural,Data Analyst,148020,0 +36306,Male,47,Masters,15,98,80,1,70,6.0,5,59,Urban,Manager,65943,1 +36307,Male,40,Bachelors,7,16,37,81,58,5.0,7,60,Urban,Software Engineer,126584,0 +36308,Male,42,Diploma,15,74,16,8,94,9.0,1,31,Rural,Data Analyst,76984,0 +36309,Male,22,Diploma,4,23,32,76,84,4.0,4,44,Urban,Software Engineer,72643,0 +36310,Male,38,Bachelors,14,69,15,61,24,6.0,4,56,Rural,Software Engineer,123761,0 +36311,Female,41,High School,10,70,83,47,77,4.0,4,24,Semi-Urban,Data Analyst,41025,0 +36312,Female,26,High School,1,81,55,83,41,6.0,1,22,Urban,Data Analyst,21152,1 +36313,Female,43,Bachelors,16,56,23,88,1,3.0,6,34,Urban,HR Executive,73740,0 +36314,Female,54,Bachelors,0,93,27,7,92,4.0,7,94,Urban,HR Executive,51026,0 +36315,Male,34,Diploma,8,50,5,96,7,3.0,3,76,Semi-Urban,Manager,129619,0 +36316,Male,24,High School,3,48,25,77,32,4.0,4,92,Semi-Urban,HR Executive,53992,1 +36317,Male,36,Bachelors,9,77,80,17,30,5.0,0,65,Urban,Software Engineer,109261,1 +36318,Male,59,Masters,3,24,12,69,47,4.0,2,54,Rural,Data Analyst,46532,0 +36319,Male,41,Diploma,15,93,41,94,49,6.0,2,11,Rural,HR Executive,45008,1 +36320,Male,39,Bachelors,1,61,35,5,33,7.0,0,10,Urban,HR Executive,144927,0 +36321,Female,49,Bachelors,6,8,55,12,86,6.0,0,2,Rural,ML Engineer,49965,0 +36322,Other,45,High School,19,72,76,60,18,6.0,2,43,Semi-Urban,Manager,30780,1 +36323,Male,39,Diploma,0,51,39,69,8,3.0,2,43,Urban,HR Executive,62643,0 +36324,Female,33,Bachelors,16,10,17,7,51,4.0,2,29,Rural,HR Executive,23019,0 +36325,Female,42,Diploma,8,45,99,69,60,9.0,2,90,Rural,ML Engineer,77519,1 +36326,Male,58,Bachelors,1,53,48,56,83,9.0,4,9,Urban,Data Analyst,52400,0 +36327,Male,48,Diploma,4,20,85,11,64,5.0,4,49,Urban,Manager,59692,0 +36328,Other,29,Bachelors,9,54,85,31,23,5.0,7,5,Urban,ML Engineer,91125,0 +36329,Female,37,Masters,13,43,63,89,96,7.0,3,48,Rural,Software Engineer,93069,1 +36330,Other,54,Bachelors,16,4,25,86,85,2.0,3,14,Semi-Urban,ML Engineer,101701,0 +36331,Male,25,PhD,11,39,75,72,50,9.0,0,45,Urban,Software Engineer,98221,0 +36332,Male,27,Bachelors,17,97,46,44,89,5.0,2,42,Urban,Data Analyst,71241,0 +36333,Male,51,High School,10,16,82,25,28,8.0,3,79,Urban,HR Executive,119106,0 +36334,Other,49,Diploma,15,72,78,97,95,5.0,5,3,Rural,HR Executive,70328,1 +36335,Male,27,Bachelors,5,87,57,77,79,1.0,4,96,Urban,ML Engineer,44138,1 +36336,Male,28,High School,6,15,48,9,25,2.0,5,18,Urban,Data Analyst,104428,0 +36337,Male,54,Masters,0,67,37,98,5,7.0,1,75,Urban,ML Engineer,35321,1 +36338,Male,59,Bachelors,16,23,25,48,81,0.0,7,87,Semi-Urban,Manager,36647,0 +36339,Male,37,Bachelors,19,33,53,28,89,4.0,6,39,Rural,Data Analyst,141494,0 +36340,Female,24,Bachelors,13,0,60,32,87,8.0,3,90,Rural,ML Engineer,37044,0 +36341,Male,44,Masters,17,37,29,87,92,7.0,5,66,Semi-Urban,Manager,76473,0 +36342,Male,51,Diploma,11,53,19,77,3,3.0,3,20,Urban,Software Engineer,117752,0 +36343,Male,32,Bachelors,14,64,58,80,55,0.0,5,7,Urban,ML Engineer,51419,0 +36344,Male,44,Bachelors,13,70,11,12,23,9.0,3,32,Urban,HR Executive,141852,0 +36345,Male,29,Masters,13,62,97,90,37,6.0,0,83,Urban,Data Analyst,91998,1 +36346,Male,25,PhD,0,4,40,55,83,5.0,2,53,Semi-Urban,HR Executive,60277,0 +36347,Female,53,Masters,0,9,20,22,46,0.0,6,18,Semi-Urban,Software Engineer,95960,0 +36348,Male,53,Diploma,8,45,28,35,97,5.0,2,61,Semi-Urban,Data Analyst,70681,0 +36349,Male,41,Diploma,7,8,29,6,1,5.0,6,5,Urban,Manager,47465,0 +36350,Male,25,Bachelors,17,54,70,74,45,5.0,4,35,Semi-Urban,Data Analyst,51185,0 +36351,Male,27,Diploma,11,56,80,19,69,9.0,3,77,Urban,Manager,136488,0 +36352,Male,48,Bachelors,19,59,48,42,65,6.0,5,91,Urban,ML Engineer,40224,1 +36353,Female,28,Diploma,2,41,70,75,24,1.0,4,84,Urban,Data Analyst,108373,1 +36354,Female,56,Bachelors,8,85,61,27,12,2.0,0,61,Urban,Software Engineer,44874,0 +36355,Female,34,Bachelors,4,78,39,52,80,2.0,2,42,Urban,Data Analyst,45273,0 +36356,Male,24,Bachelors,6,55,98,59,79,8.0,2,35,Urban,ML Engineer,134348,1 +36357,Male,44,Bachelors,0,99,53,55,41,8.0,4,10,Urban,Software Engineer,87512,0 +36358,Female,56,Diploma,11,26,75,5,31,2.0,6,8,Rural,Manager,129033,0 +36359,Male,28,High School,4,38,27,41,65,2.0,7,79,Urban,HR Executive,73227,0 +36360,Male,54,Diploma,18,70,41,83,22,4.0,5,23,Urban,Data Analyst,105570,0 +36361,Female,53,Diploma,5,43,32,32,91,0.0,7,44,Urban,Data Analyst,35566,0 +36362,Male,43,Diploma,9,8,87,5,37,0.0,0,88,Urban,Data Analyst,137379,0 +36363,Female,36,PhD,15,5,32,9,99,6.0,1,52,Urban,Manager,85579,0 +36364,Male,40,PhD,6,39,65,64,6,5.0,0,28,Semi-Urban,Manager,42167,0 +36365,Male,38,Diploma,12,25,73,70,24,2.0,7,11,Urban,HR Executive,41248,0 +36366,Female,56,Diploma,8,89,3,34,27,8.0,3,57,Urban,HR Executive,102116,0 +36367,Male,40,Bachelors,15,63,14,48,53,3.0,1,1,Urban,Data Analyst,125618,0 +36368,Male,34,High School,14,22,42,66,80,5.0,6,14,Semi-Urban,Software Engineer,87399,0 +36369,Male,37,Bachelors,19,93,60,70,71,9.0,1,75,Urban,Manager,101258,1 +36370,Male,27,Masters,5,55,8,24,46,0.0,5,33,Rural,ML Engineer,124853,0 +36371,Male,37,Bachelors,3,66,50,75,15,0.0,3,92,Semi-Urban,Software Engineer,126974,1 +36372,Male,57,Bachelors,9,26,69,2,50,9.0,3,93,Urban,Manager,87549,0 +36373,Other,21,Diploma,7,37,52,29,98,7.0,3,73,Semi-Urban,Software Engineer,85648,0 +36374,Female,49,Bachelors,4,55,98,56,40,4.0,6,21,Semi-Urban,HR Executive,108055,0 +36375,Female,39,Diploma,13,83,27,2,12,5.0,3,31,Urban,ML Engineer,61840,0 +36376,Female,53,Masters,6,80,11,61,59,4.0,0,99,Rural,Manager,49377,1 +36377,Male,36,Masters,7,28,68,16,48,1.0,7,39,Rural,Manager,131217,0 +36378,Male,59,Bachelors,2,53,0,9,72,4.0,3,96,Semi-Urban,ML Engineer,110249,0 +36379,Male,24,Masters,10,88,59,14,22,5.0,7,53,Urban,HR Executive,98010,0 +36380,Female,55,Masters,3,80,82,94,35,0.0,2,38,Urban,Software Engineer,105586,1 +36381,Male,25,Masters,4,38,45,87,34,2.0,1,70,Urban,ML Engineer,69001,1 +36382,Male,36,Bachelors,14,45,16,95,34,9.0,3,22,Urban,Software Engineer,37004,0 +36383,Female,48,PhD,5,9,10,96,14,7.0,7,41,Urban,Data Analyst,91455,0 +36384,Male,22,Masters,3,96,61,56,47,2.0,5,72,Urban,HR Executive,46344,1 +36385,Male,54,High School,18,90,33,49,38,0.0,6,92,Semi-Urban,Software Engineer,136265,1 +36386,Male,34,Bachelors,19,0,85,22,48,7.0,3,61,Urban,Software Engineer,90360,0 +36387,Male,48,Bachelors,13,35,64,54,77,6.0,2,61,Urban,ML Engineer,42816,0 +36388,Male,43,Diploma,10,70,14,23,9,3.0,3,53,Semi-Urban,Data Analyst,58920,0 +36389,Male,59,Diploma,19,67,81,37,43,1.0,7,1,Urban,Manager,66817,0 +36390,Male,37,Bachelors,8,0,33,82,17,8.0,0,74,Semi-Urban,Data Analyst,88796,0 +36391,Male,37,High School,9,8,86,93,91,9.0,4,66,Urban,HR Executive,39095,1 +36392,Male,34,Masters,3,37,0,36,67,7.0,0,79,Rural,ML Engineer,83799,0 +36393,Other,59,Bachelors,3,71,62,24,18,0.0,3,70,Urban,Data Analyst,136540,0 +36394,Male,46,Masters,3,69,88,31,46,0.0,6,73,Urban,Software Engineer,39078,1 +36395,Female,52,Bachelors,18,49,98,6,82,0.0,5,21,Urban,Software Engineer,72024,0 +36396,Female,50,High School,0,5,18,44,45,8.0,5,40,Urban,ML Engineer,120466,0 +36397,Male,56,Diploma,7,92,89,64,0,2.0,0,56,Urban,Software Engineer,23235,1 +36398,Male,33,High School,17,68,38,24,68,6.0,2,0,Urban,ML Engineer,109307,0 +36399,Male,33,Masters,3,98,28,33,17,1.0,7,22,Rural,Manager,24834,0 +36400,Female,46,Diploma,3,6,94,90,20,9.0,0,88,Urban,ML Engineer,97517,1 +36401,Male,50,Diploma,19,83,34,0,67,8.0,3,20,Urban,Data Analyst,41216,0 +36402,Male,57,Masters,5,49,25,97,58,0.0,4,78,Urban,Data Analyst,101710,1 +36403,Male,54,Bachelors,1,87,56,28,17,6.0,2,5,Rural,Data Analyst,41804,0 +36404,Male,22,Bachelors,10,96,24,98,88,5.0,0,23,Urban,ML Engineer,65309,1 +36405,Male,46,Masters,9,9,4,20,11,2.0,4,8,Semi-Urban,ML Engineer,52545,0 +36406,Female,48,Bachelors,16,21,96,33,15,6.0,6,41,Rural,Manager,136995,0 +36407,Male,21,Masters,17,45,85,59,61,9.0,4,14,Urban,Manager,77230,0 +36408,Male,27,Masters,11,41,34,7,70,8.0,3,27,Semi-Urban,ML Engineer,143436,0 +36409,Female,23,Bachelors,6,56,63,50,53,5.0,5,56,Semi-Urban,Data Analyst,138353,0 +36410,Female,51,Diploma,4,2,33,38,49,8.0,6,38,Urban,ML Engineer,20550,0 +36411,Male,23,Bachelors,11,29,26,76,65,3.0,7,54,Urban,HR Executive,140869,0 +36412,Male,35,Bachelors,7,18,88,93,97,4.0,2,48,Semi-Urban,HR Executive,115610,1 +36413,Male,55,Bachelors,18,47,55,75,5,2.0,3,12,Urban,Manager,55000,0 +36414,Male,53,Bachelors,19,91,61,60,57,3.0,1,72,Semi-Urban,ML Engineer,24347,1 +36415,Male,38,Bachelors,12,32,43,43,12,8.0,7,37,Urban,Data Analyst,143569,0 +36416,Male,35,PhD,3,44,3,15,20,2.0,4,32,Rural,Manager,124438,0 +36417,Male,22,Masters,19,87,56,75,45,9.0,4,2,Urban,HR Executive,29850,0 +36418,Female,35,Diploma,15,43,53,1,81,0.0,1,89,Urban,Data Analyst,99388,0 +36419,Male,36,Bachelors,9,39,62,79,21,9.0,7,41,Rural,HR Executive,76431,0 +36420,Male,44,Diploma,2,4,62,61,87,3.0,6,52,Urban,Manager,57367,0 +36421,Other,52,High School,6,22,30,9,77,5.0,7,42,Urban,ML Engineer,48616,0 +36422,Female,25,Bachelors,9,90,92,78,12,8.0,3,62,Urban,ML Engineer,68178,1 +36423,Male,36,Bachelors,18,1,2,2,38,6.0,4,77,Urban,Software Engineer,52026,0 +36424,Male,44,Bachelors,8,14,29,34,9,7.0,2,63,Urban,ML Engineer,95404,0 +36425,Other,42,High School,16,10,95,6,30,5.0,3,6,Urban,ML Engineer,146617,0 +36426,Male,34,Diploma,0,71,93,79,38,2.0,7,19,Urban,Software Engineer,133891,1 +36427,Female,35,Bachelors,11,35,27,17,53,2.0,2,68,Semi-Urban,Manager,91725,0 +36428,Female,37,PhD,11,65,56,92,57,9.0,3,39,Urban,HR Executive,48128,1 +36429,Male,39,Bachelors,17,10,9,50,24,8.0,1,56,Urban,Software Engineer,138437,0 +36430,Female,34,Bachelors,8,16,3,80,87,5.0,4,49,Urban,HR Executive,67455,0 +36431,Other,42,Bachelors,17,95,12,72,66,9.0,7,35,Semi-Urban,Data Analyst,24334,0 +36432,Female,31,Diploma,16,84,16,82,93,8.0,6,60,Rural,Software Engineer,49497,1 +36433,Male,54,Masters,3,38,24,76,65,5.0,4,30,Semi-Urban,Data Analyst,50338,0 +36434,Female,21,Masters,4,94,91,25,26,5.0,7,56,Rural,ML Engineer,67089,1 +36435,Male,42,Bachelors,2,10,24,85,58,9.0,3,97,Rural,Software Engineer,28292,0 +36436,Female,34,High School,14,9,45,36,83,0.0,6,5,Urban,Software Engineer,46177,0 +36437,Male,31,Diploma,19,94,49,68,28,1.0,7,84,Urban,Software Engineer,91928,1 +36438,Male,23,Diploma,6,56,21,22,18,5.0,5,37,Rural,Software Engineer,45090,0 +36439,Male,32,Diploma,5,55,30,76,72,0.0,2,44,Semi-Urban,HR Executive,26577,0 +36440,Male,26,Masters,15,79,2,39,42,6.0,0,84,Urban,Data Analyst,79771,0 +36441,Male,26,Bachelors,9,44,4,12,39,5.0,7,26,Urban,HR Executive,115203,0 +36442,Male,40,High School,6,69,15,88,58,7.0,1,0,Urban,Software Engineer,21337,0 +36443,Male,35,Bachelors,2,55,88,90,16,9.0,7,32,Semi-Urban,Software Engineer,48230,1 +36444,Male,40,Masters,13,6,56,80,96,8.0,6,38,Semi-Urban,Manager,125440,0 +36445,Female,31,Diploma,4,62,44,21,97,2.0,1,83,Rural,ML Engineer,42770,0 +36446,Female,30,Masters,0,39,79,91,48,3.0,5,21,Semi-Urban,Manager,122722,0 +36447,Male,50,High School,7,91,62,59,4,3.0,7,54,Semi-Urban,Software Engineer,66761,1 +36448,Male,24,Masters,9,62,78,76,5,6.0,7,21,Urban,Data Analyst,21593,1 +36449,Male,42,Diploma,4,85,10,64,93,0.0,7,89,Urban,Manager,25808,1 +36450,Male,48,Diploma,6,22,61,79,84,4.0,6,78,Semi-Urban,Data Analyst,115062,1 +36451,Female,43,Diploma,3,99,82,67,65,4.0,2,17,Semi-Urban,Data Analyst,37224,1 +36452,Female,53,Bachelors,16,12,91,30,54,9.0,3,49,Rural,ML Engineer,119171,0 +36453,Male,28,Masters,0,65,82,43,47,7.0,5,78,Urban,HR Executive,142047,1 +36454,Female,36,Diploma,1,43,98,70,8,4.0,4,54,Urban,Data Analyst,39433,1 +36455,Female,46,Bachelors,16,11,87,62,28,7.0,5,57,Urban,Manager,45061,0 +36456,Male,32,Masters,17,22,63,65,9,1.0,4,21,Semi-Urban,Software Engineer,139600,0 +36457,Male,56,Diploma,5,78,69,13,16,0.0,7,90,Semi-Urban,Manager,117700,1 +36458,Male,22,PhD,11,70,88,29,44,7.0,7,67,Urban,Data Analyst,127683,1 +36459,Male,36,Bachelors,2,19,68,12,1,5.0,6,21,Urban,Software Engineer,101916,0 +36460,Male,51,Masters,3,31,24,10,46,5.0,6,55,Rural,HR Executive,99794,0 +36461,Male,49,Bachelors,17,85,43,85,80,4.0,0,26,Semi-Urban,Manager,128221,1 +36462,Male,34,High School,11,4,26,19,57,8.0,3,66,Urban,Software Engineer,61715,0 +36463,Male,25,Diploma,19,89,97,65,68,4.0,5,74,Urban,HR Executive,98008,1 +36464,Male,25,Bachelors,4,80,96,92,46,1.0,7,75,Urban,HR Executive,74267,1 +36465,Male,43,Masters,2,31,40,10,24,3.0,2,65,Semi-Urban,Data Analyst,130163,0 +36466,Male,57,Diploma,18,11,44,97,24,6.0,2,0,Urban,Software Engineer,111159,0 +36467,Male,29,Masters,5,7,1,63,61,1.0,5,55,Urban,ML Engineer,80876,0 +36468,Male,58,High School,2,69,72,88,84,8.0,3,89,Urban,Software Engineer,91721,1 +36469,Female,33,High School,4,2,75,22,83,4.0,6,45,Urban,HR Executive,97393,0 +36470,Female,56,Bachelors,4,22,90,23,70,8.0,1,70,Semi-Urban,Data Analyst,90565,0 +36471,Male,26,High School,13,56,99,89,16,5.0,2,82,Urban,ML Engineer,64135,1 +36472,Male,49,PhD,0,22,72,60,20,7.0,1,22,Urban,Data Analyst,49998,0 +36473,Female,44,Bachelors,19,28,14,0,10,0.0,2,89,Urban,Data Analyst,109741,0 +36474,Female,56,Masters,1,93,28,80,5,6.0,6,70,Urban,HR Executive,80962,1 +36475,Male,57,Bachelors,11,75,17,2,33,6.0,6,56,Rural,ML Engineer,42526,0 +36476,Female,30,Masters,7,17,65,1,31,6.0,1,47,Urban,ML Engineer,135618,0 +36477,Male,41,PhD,2,80,84,94,64,2.0,7,15,Urban,Manager,116419,1 +36478,Male,39,High School,3,38,88,42,16,6.0,5,35,Urban,ML Engineer,31685,0 +36479,Other,27,PhD,7,61,41,24,50,8.0,7,67,Urban,Manager,35666,0 +36480,Male,58,Bachelors,9,15,66,99,28,4.0,7,28,Semi-Urban,HR Executive,131306,0 +36481,Female,25,Bachelors,8,96,97,40,29,3.0,5,26,Semi-Urban,Data Analyst,102726,1 +36482,Male,29,PhD,18,46,44,60,10,1.0,3,83,Urban,Data Analyst,63323,0 +36483,Male,47,High School,19,20,14,48,75,0.0,3,87,Urban,ML Engineer,48089,0 +36484,Male,23,Masters,7,0,78,62,12,8.0,4,66,Urban,Data Analyst,81570,0 +36485,Female,28,Masters,2,90,95,49,37,6.0,6,35,Urban,Manager,75753,1 +36486,Male,40,Diploma,14,92,26,61,75,5.0,1,4,Urban,Data Analyst,34077,0 +36487,Female,30,Diploma,7,60,15,22,12,0.0,1,68,Urban,Manager,48082,0 +36488,Female,36,Bachelors,15,24,34,99,99,6.0,5,62,Urban,ML Engineer,68753,0 +36489,Male,32,Bachelors,7,12,80,82,48,4.0,5,18,Rural,Software Engineer,95230,0 +36490,Male,22,Bachelors,1,61,57,64,99,0.0,2,62,Semi-Urban,Manager,136026,1 +36491,Male,23,Diploma,19,39,59,10,70,9.0,4,32,Rural,HR Executive,125956,0 +36492,Female,45,Bachelors,19,97,99,44,83,8.0,7,12,Urban,Manager,136740,1 +36493,Female,29,PhD,13,85,31,37,64,4.0,0,9,Urban,HR Executive,58350,0 +36494,Male,51,Bachelors,10,53,22,85,56,1.0,2,47,Urban,Manager,46716,0 +36495,Male,56,Diploma,6,17,33,65,36,9.0,2,85,Semi-Urban,Data Analyst,89132,0 +36496,Male,41,Diploma,0,62,13,80,14,5.0,2,15,Urban,Software Engineer,141554,0 +36497,Male,27,Bachelors,10,9,52,10,27,4.0,4,41,Urban,Manager,27343,0 +36498,Male,40,PhD,19,32,20,49,95,4.0,3,48,Semi-Urban,Data Analyst,92371,0 +36499,Female,57,Diploma,16,37,63,12,25,5.0,3,5,Rural,Manager,117748,0 +36500,Other,50,Masters,0,3,19,54,58,2.0,1,91,Semi-Urban,HR Executive,85970,0 +36501,Female,59,Bachelors,14,29,99,99,26,9.0,6,35,Urban,Data Analyst,64887,1 +36502,Male,54,Diploma,1,21,21,59,4,6.0,7,80,Urban,ML Engineer,55654,0 +36503,Male,24,Masters,3,16,95,54,4,4.0,5,53,Urban,HR Executive,111205,0 +36504,Male,49,Bachelors,10,35,35,34,89,8.0,5,88,Urban,HR Executive,101944,0 +36505,Male,26,High School,1,10,6,31,25,8.0,0,20,Urban,ML Engineer,113181,0 +36506,Male,39,High School,10,82,46,79,57,2.0,2,25,Rural,HR Executive,139645,0 +36507,Male,30,Bachelors,2,99,22,56,13,0.0,5,8,Urban,ML Engineer,111496,0 +36508,Female,54,Bachelors,2,23,43,57,6,3.0,5,10,Semi-Urban,Software Engineer,90110,0 +36509,Male,36,Diploma,14,92,34,73,92,1.0,1,92,Semi-Urban,HR Executive,41301,1 +36510,Female,23,Bachelors,6,64,37,73,9,7.0,1,38,Urban,Software Engineer,37397,0 +36511,Male,42,Bachelors,18,93,77,38,45,5.0,5,99,Semi-Urban,HR Executive,147172,1 +36512,Male,36,Bachelors,19,64,71,61,12,3.0,4,28,Semi-Urban,ML Engineer,81905,0 +36513,Male,51,Diploma,8,48,96,98,66,2.0,3,71,Urban,Manager,66124,1 +36514,Male,37,High School,13,28,44,71,91,1.0,5,23,Semi-Urban,ML Engineer,73769,0 +36515,Other,57,Bachelors,2,70,28,30,20,4.0,2,25,Urban,HR Executive,24232,0 +36516,Male,43,Bachelors,7,60,84,45,23,0.0,0,28,Urban,Software Engineer,116999,0 +36517,Female,58,PhD,8,34,97,91,95,2.0,4,47,Urban,HR Executive,127523,1 +36518,Male,47,PhD,8,43,93,27,81,1.0,7,12,Urban,ML Engineer,71479,0 +36519,Male,25,Masters,0,41,34,25,36,1.0,1,23,Rural,ML Engineer,91665,0 +36520,Male,45,Bachelors,19,28,73,60,42,0.0,0,12,Urban,HR Executive,119604,0 +36521,Female,31,Bachelors,8,61,9,4,3,2.0,4,6,Urban,Software Engineer,127249,0 +36522,Male,29,Bachelors,18,58,97,66,55,8.0,5,88,Urban,Data Analyst,117039,1 +36523,Other,25,High School,8,90,17,60,58,9.0,6,51,Urban,Manager,141191,0 +36524,Male,44,High School,1,18,79,0,94,0.0,0,22,Semi-Urban,Software Engineer,44759,0 +36525,Male,36,Diploma,17,27,33,96,78,7.0,0,62,Semi-Urban,Manager,54237,0 +36526,Female,22,High School,1,17,67,90,75,3.0,1,16,Rural,Manager,26363,0 +36527,Male,22,High School,5,65,5,31,41,1.0,0,30,Rural,HR Executive,47101,0 +36528,Male,40,Bachelors,12,39,37,68,75,5.0,5,99,Urban,Software Engineer,23113,1 +36529,Female,24,Bachelors,8,42,38,21,45,5.0,1,70,Urban,ML Engineer,31465,0 +36530,Male,54,Diploma,3,61,66,74,19,2.0,2,21,Semi-Urban,HR Executive,94968,0 +36531,Male,28,Masters,0,72,77,69,69,9.0,6,53,Urban,Manager,68416,1 +36532,Male,22,PhD,5,43,90,84,89,7.0,0,36,Urban,Software Engineer,103952,1 +36533,Male,35,High School,12,22,74,5,52,1.0,7,86,Rural,ML Engineer,117061,0 +36534,Male,28,Bachelors,8,42,56,80,69,1.0,0,54,Urban,Software Engineer,135999,0 +36535,Male,44,Bachelors,5,62,41,62,17,8.0,7,32,Urban,Software Engineer,21956,0 +36536,Female,53,Bachelors,5,67,55,57,33,2.0,3,93,Urban,HR Executive,57597,1 +36537,Male,49,Bachelors,12,46,89,25,44,4.0,6,4,Semi-Urban,Data Analyst,22441,0 +36538,Female,21,Bachelors,7,89,2,38,1,9.0,5,13,Urban,HR Executive,99329,0 +36539,Male,46,Diploma,15,71,36,45,93,7.0,3,82,Urban,Manager,127036,0 +36540,Male,24,Bachelors,9,92,84,91,53,6.0,4,59,Semi-Urban,HR Executive,46973,1 +36541,Male,22,Bachelors,8,47,19,86,53,9.0,5,52,Urban,ML Engineer,44444,0 +36542,Female,44,Diploma,4,25,40,79,66,1.0,6,83,Rural,HR Executive,31663,0 +36543,Female,25,Bachelors,16,51,3,59,26,0.0,7,17,Urban,Manager,107994,0 +36544,Male,26,Diploma,5,27,61,44,96,6.0,4,53,Urban,HR Executive,134263,0 +36545,Male,51,Masters,6,72,40,92,98,1.0,4,57,Urban,Data Analyst,39318,1 +36546,Female,47,Diploma,15,36,62,35,56,4.0,0,71,Urban,Data Analyst,34444,0 +36547,Female,52,Bachelors,12,49,50,32,78,5.0,5,1,Urban,Data Analyst,136528,0 +36548,Female,51,Diploma,18,52,71,18,86,8.0,2,60,Semi-Urban,Software Engineer,25235,0 +36549,Male,37,Diploma,5,86,83,3,75,8.0,1,41,Urban,Software Engineer,44346,0 +36550,Male,56,Diploma,5,7,33,76,86,9.0,3,32,Urban,HR Executive,104375,0 +36551,Female,37,Bachelors,8,53,73,85,48,9.0,6,45,Urban,ML Engineer,70557,1 +36552,Male,35,Bachelors,9,52,28,41,19,8.0,4,52,Semi-Urban,Manager,84246,0 +36553,Male,53,Diploma,6,14,69,85,38,4.0,4,83,Semi-Urban,ML Engineer,102516,1 +36554,Male,42,Bachelors,18,54,95,60,45,0.0,0,27,Semi-Urban,Manager,60277,1 +36555,Male,34,Diploma,15,32,26,53,71,3.0,0,35,Semi-Urban,HR Executive,43272,0 +36556,Other,46,Bachelors,5,21,99,24,56,8.0,7,34,Urban,Software Engineer,102256,0 +36557,Female,35,Diploma,19,91,6,61,44,4.0,4,62,Urban,Software Engineer,32449,0 +36558,Male,22,Bachelors,17,39,42,99,96,3.0,0,16,Urban,Manager,101395,0 +36559,Male,48,High School,8,16,5,82,18,3.0,0,16,Urban,ML Engineer,117006,0 +36560,Female,32,Bachelors,2,81,2,43,36,2.0,3,89,Semi-Urban,Data Analyst,22492,0 +36561,Male,26,Diploma,8,82,45,28,23,1.0,0,60,Semi-Urban,Software Engineer,28749,0 +36562,Male,24,Bachelors,11,0,30,9,86,9.0,6,27,Urban,ML Engineer,84039,0 +36563,Male,32,Masters,12,78,44,92,84,5.0,7,35,Semi-Urban,Manager,33655,1 +36564,Male,29,Masters,7,93,27,62,9,6.0,5,62,Semi-Urban,HR Executive,109507,1 +36565,Male,38,High School,0,92,74,62,16,6.0,4,85,Rural,Manager,143238,1 +36566,Male,24,High School,16,62,11,74,26,6.0,7,18,Urban,ML Engineer,41709,0 +36567,Male,25,Masters,2,34,29,20,89,2.0,0,20,Urban,ML Engineer,99977,0 +36568,Female,48,High School,19,31,5,28,90,1.0,1,22,Urban,HR Executive,81769,0 +36569,Female,22,High School,5,82,64,48,14,3.0,4,43,Semi-Urban,HR Executive,146801,0 +36570,Female,44,Bachelors,0,56,91,21,63,4.0,4,16,Urban,Software Engineer,115442,0 +36571,Male,24,PhD,3,81,76,51,64,1.0,5,21,Urban,Data Analyst,100145,0 +36572,Male,48,Bachelors,15,76,61,50,74,3.0,0,3,Urban,HR Executive,25643,0 +36573,Female,35,Masters,19,28,75,88,18,6.0,7,81,Urban,Software Engineer,64353,1 +36574,Female,24,Bachelors,7,60,98,45,86,2.0,2,83,Rural,ML Engineer,112660,1 +36575,Male,52,Bachelors,13,61,40,76,46,1.0,0,54,Urban,Manager,64107,0 +36576,Male,39,Diploma,5,78,75,38,73,7.0,5,60,Semi-Urban,Software Engineer,34429,1 +36577,Male,42,Bachelors,14,9,5,91,85,2.0,7,65,Semi-Urban,Data Analyst,99097,0 +36578,Male,22,Diploma,13,34,27,9,42,0.0,0,0,Semi-Urban,Manager,26909,0 +36579,Male,28,Bachelors,0,67,40,53,0,7.0,6,7,Urban,Software Engineer,96975,0 +36580,Other,56,Bachelors,19,6,31,92,33,0.0,4,77,Urban,HR Executive,64468,0 +36581,Male,28,Bachelors,8,10,25,10,9,5.0,4,35,Semi-Urban,HR Executive,131152,0 +36582,Male,44,Diploma,9,88,4,53,81,2.0,1,5,Urban,ML Engineer,48609,0 +36583,Other,53,Masters,11,11,14,11,63,6.0,0,5,Urban,Software Engineer,72643,0 +36584,Male,25,Bachelors,16,51,15,37,25,0.0,5,21,Urban,Data Analyst,120338,0 +36585,Female,30,High School,17,15,99,52,41,1.0,7,66,Semi-Urban,Software Engineer,125088,0 +36586,Male,58,High School,10,44,62,72,75,5.0,0,28,Semi-Urban,Software Engineer,71637,0 +36587,Other,32,Diploma,14,55,8,24,16,6.0,2,69,Rural,ML Engineer,126213,0 +36588,Male,34,High School,17,80,85,30,22,8.0,0,48,Urban,ML Engineer,120553,1 +36589,Other,45,Diploma,6,63,3,37,80,7.0,4,66,Urban,Software Engineer,37419,0 +36590,Male,55,Diploma,11,70,16,62,57,9.0,7,13,Urban,Software Engineer,142172,0 +36591,Male,45,Masters,18,5,11,2,77,1.0,0,13,Semi-Urban,Data Analyst,38018,0 +36592,Male,42,PhD,5,88,5,14,59,9.0,7,7,Rural,HR Executive,80615,0 +36593,Male,24,Diploma,8,32,63,39,30,7.0,7,54,Semi-Urban,Software Engineer,145381,0 +36594,Male,39,Bachelors,19,11,23,76,38,2.0,0,18,Semi-Urban,HR Executive,50184,0 +36595,Other,40,Diploma,18,48,75,18,34,1.0,5,53,Rural,Software Engineer,133090,0 +36596,Male,47,Diploma,14,93,21,95,64,0.0,4,50,Urban,HR Executive,114411,1 +36597,Female,43,Bachelors,14,70,64,32,15,3.0,3,79,Urban,HR Executive,68403,1 +36598,Male,59,High School,10,57,12,54,47,0.0,2,4,Urban,ML Engineer,66616,0 +36599,Female,33,Diploma,14,92,56,91,48,2.0,5,59,Rural,ML Engineer,107319,1 +36600,Male,35,PhD,7,40,10,88,9,0.0,0,90,Rural,Manager,80333,0 +36601,Other,36,Masters,4,87,33,61,16,1.0,1,27,Urban,ML Engineer,106834,0 +36602,Male,59,Masters,1,58,29,90,9,8.0,0,0,Urban,Manager,114730,0 +36603,Male,46,Bachelors,18,13,93,89,31,4.0,7,96,Semi-Urban,ML Engineer,147187,1 +36604,Male,46,Diploma,11,21,2,21,31,9.0,2,72,Urban,Software Engineer,73155,0 +36605,Female,27,Bachelors,0,82,64,7,38,5.0,1,0,Urban,Software Engineer,33369,0 +36606,Female,21,Masters,18,43,78,14,41,7.0,0,96,Urban,Manager,41913,0 +36607,Female,29,High School,6,11,28,57,52,7.0,5,1,Urban,HR Executive,126117,0 +36608,Male,28,High School,16,63,60,65,41,8.0,3,53,Urban,Manager,107586,1 +36609,Male,43,Masters,15,12,38,8,60,5.0,3,70,Urban,Manager,43048,0 +36610,Female,35,High School,8,36,35,81,49,2.0,5,72,Semi-Urban,Software Engineer,123590,0 +36611,Male,38,Bachelors,12,2,18,23,25,9.0,4,99,Rural,Software Engineer,61911,0 +36612,Male,39,PhD,0,27,74,24,86,1.0,0,1,Urban,Manager,52680,0 +36613,Female,59,Bachelors,16,52,7,61,93,3.0,6,87,Semi-Urban,Manager,65591,0 +36614,Male,46,Bachelors,19,51,0,29,32,7.0,5,38,Urban,Data Analyst,105147,0 +36615,Female,32,Masters,15,70,8,99,97,2.0,0,24,Urban,Software Engineer,41941,0 +36616,Male,57,Diploma,15,66,21,42,63,4.0,4,11,Urban,ML Engineer,103912,0 +36617,Other,56,Diploma,12,89,6,49,0,9.0,5,8,Urban,ML Engineer,41535,0 +36618,Female,27,Masters,11,16,92,56,68,4.0,1,2,Urban,Data Analyst,29332,0 +36619,Female,29,Bachelors,17,63,26,16,99,5.0,2,11,Semi-Urban,Software Engineer,141869,0 +36620,Male,51,Bachelors,15,23,90,15,71,9.0,4,29,Urban,Data Analyst,47089,0 +36621,Male,58,Bachelors,16,17,30,22,30,8.0,6,59,Urban,Data Analyst,62054,0 +36622,Female,42,Bachelors,3,28,24,73,70,3.0,1,97,Rural,HR Executive,75279,0 +36623,Male,32,Bachelors,3,87,78,51,86,7.0,7,82,Urban,Manager,61942,1 +36624,Female,54,Bachelors,8,50,21,22,47,6.0,0,40,Rural,Data Analyst,35057,0 +36625,Male,22,Bachelors,15,18,13,22,17,6.0,2,61,Urban,ML Engineer,102105,0 +36626,Male,52,Masters,14,50,89,69,47,2.0,4,77,Rural,ML Engineer,133802,1 +36627,Male,21,Diploma,14,55,66,61,55,4.0,1,57,Urban,HR Executive,21666,1 +36628,Male,45,High School,10,94,27,90,58,2.0,7,69,Urban,ML Engineer,69336,1 +36629,Female,24,Masters,0,91,13,64,47,4.0,7,81,Semi-Urban,Manager,96867,1 +36630,Female,58,Masters,2,14,36,14,64,2.0,3,19,Urban,Data Analyst,133268,0 +36631,Male,24,Diploma,10,69,86,27,75,7.0,2,46,Urban,HR Executive,137665,0 +36632,Female,29,Diploma,17,48,61,43,21,6.0,2,33,Urban,Data Analyst,39240,0 +36633,Female,38,High School,16,55,32,81,89,5.0,3,42,Semi-Urban,Software Engineer,24428,0 +36634,Female,31,Bachelors,12,32,34,38,62,0.0,4,20,Urban,HR Executive,28530,0 +36635,Male,26,Bachelors,11,41,16,48,72,3.0,6,53,Semi-Urban,ML Engineer,83547,0 +36636,Male,36,Diploma,6,59,75,95,82,9.0,6,7,Semi-Urban,ML Engineer,55138,1 +36637,Female,28,Masters,10,92,60,87,69,3.0,7,69,Rural,Manager,35845,1 +36638,Male,39,Bachelors,18,77,23,44,16,5.0,6,7,Urban,HR Executive,88612,0 +36639,Female,25,Bachelors,1,55,84,21,86,4.0,0,86,Rural,ML Engineer,146874,1 +36640,Female,46,High School,18,82,94,78,19,8.0,7,70,Semi-Urban,Data Analyst,92200,1 +36641,Female,45,Diploma,2,25,6,13,98,8.0,5,65,Urban,Manager,123393,0 +36642,Other,45,Bachelors,7,3,53,9,6,9.0,0,67,Urban,Data Analyst,25387,0 +36643,Female,29,Bachelors,19,97,84,9,74,3.0,0,81,Rural,Software Engineer,123865,1 +36644,Male,55,Diploma,6,40,24,90,18,8.0,7,1,Urban,Data Analyst,23445,0 +36645,Male,21,Bachelors,15,54,93,75,5,9.0,7,6,Urban,Data Analyst,97493,0 +36646,Male,22,Masters,6,37,31,97,77,3.0,4,7,Urban,Data Analyst,71786,0 +36647,Male,45,High School,17,47,77,96,87,0.0,7,1,Semi-Urban,ML Engineer,116598,0 +36648,Male,56,Masters,16,97,51,86,12,1.0,1,46,Semi-Urban,ML Engineer,106271,1 +36649,Male,56,Masters,1,41,71,49,53,0.0,0,51,Urban,Data Analyst,90292,0 +36650,Male,32,High School,11,10,20,48,83,3.0,1,1,Urban,Manager,63201,0 +36651,Male,49,Masters,18,51,61,0,27,6.0,1,11,Semi-Urban,HR Executive,145329,0 +36652,Female,32,Bachelors,3,9,44,97,13,9.0,1,71,Semi-Urban,Data Analyst,43268,0 +36653,Female,33,High School,19,1,85,4,23,0.0,2,96,Rural,Manager,52753,0 +36654,Female,31,High School,8,35,34,63,2,5.0,7,33,Urban,Software Engineer,52225,0 +36655,Male,27,Masters,19,10,90,53,19,0.0,4,24,Urban,Data Analyst,62776,0 +36656,Male,59,Bachelors,11,83,61,85,80,6.0,6,86,Urban,ML Engineer,34455,1 +36657,Male,42,Bachelors,7,50,84,8,26,3.0,4,41,Urban,HR Executive,56780,0 +36658,Male,29,PhD,2,19,95,20,56,6.0,0,25,Semi-Urban,Data Analyst,144951,0 +36659,Male,59,Masters,8,49,85,60,59,9.0,2,68,Semi-Urban,Manager,92571,1 +36660,Male,52,Bachelors,16,30,79,12,89,6.0,6,0,Rural,Data Analyst,127193,0 +36661,Male,34,Masters,17,29,74,78,47,3.0,5,82,Semi-Urban,ML Engineer,38919,1 +36662,Female,49,Masters,1,24,1,39,86,8.0,7,59,Urban,Software Engineer,109824,0 +36663,Female,55,Diploma,18,74,86,83,44,2.0,5,53,Semi-Urban,Manager,24858,1 +36664,Male,32,High School,11,36,5,72,45,0.0,5,18,Urban,Data Analyst,61659,0 +36665,Male,51,Diploma,12,9,38,17,32,4.0,3,7,Urban,HR Executive,124604,0 +36666,Male,58,Bachelors,10,81,97,27,60,1.0,3,13,Semi-Urban,Software Engineer,143464,0 +36667,Male,55,Diploma,18,76,55,11,52,9.0,3,51,Urban,Data Analyst,114035,0 +36668,Other,35,High School,5,86,42,89,70,3.0,2,35,Rural,Data Analyst,29423,1 +36669,Female,36,High School,4,27,0,46,46,3.0,7,74,Urban,Software Engineer,81982,0 +36670,Male,39,Bachelors,10,29,29,66,76,5.0,1,35,Urban,HR Executive,54205,0 +36671,Male,36,Bachelors,4,3,45,59,63,6.0,4,66,Semi-Urban,ML Engineer,139434,0 +36672,Male,49,Bachelors,7,41,38,43,81,2.0,0,10,Semi-Urban,ML Engineer,126215,0 +36673,Male,49,Masters,1,51,60,71,87,0.0,6,42,Urban,HR Executive,120430,0 +36674,Female,49,Diploma,8,19,49,17,50,3.0,3,16,Semi-Urban,Software Engineer,130619,0 +36675,Female,50,Bachelors,5,28,12,96,65,2.0,6,98,Urban,ML Engineer,100158,0 +36676,Male,41,Bachelors,17,19,43,27,51,0.0,2,94,Urban,Data Analyst,69221,0 +36677,Male,45,Bachelors,4,12,11,24,38,5.0,4,55,Semi-Urban,Data Analyst,120289,0 +36678,Female,28,High School,4,68,9,34,25,3.0,7,69,Urban,Manager,124878,0 +36679,Male,34,Bachelors,1,28,87,81,53,9.0,1,38,Semi-Urban,ML Engineer,60330,0 +36680,Female,38,Diploma,13,39,35,59,7,6.0,7,81,Semi-Urban,Data Analyst,21979,0 +36681,Male,28,Masters,2,0,3,58,94,8.0,1,41,Urban,Data Analyst,67083,0 +36682,Male,52,PhD,19,85,50,54,86,1.0,3,77,Urban,ML Engineer,130657,1 +36683,Female,59,Bachelors,18,66,33,11,43,8.0,0,18,Urban,Software Engineer,139588,0 +36684,Male,54,Masters,10,5,46,75,30,8.0,6,38,Rural,ML Engineer,111831,0 +36685,Male,35,Masters,12,67,38,98,8,3.0,5,53,Rural,Data Analyst,131385,1 +36686,Male,38,Bachelors,5,97,94,56,88,8.0,0,13,Semi-Urban,ML Engineer,48166,1 +36687,Male,32,High School,10,20,73,72,27,0.0,3,40,Urban,HR Executive,139280,0 +36688,Female,34,High School,11,28,8,54,0,4.0,3,50,Urban,Manager,91454,0 +36689,Male,59,PhD,14,70,81,62,83,7.0,3,69,Urban,Software Engineer,47917,1 +36690,Female,39,Diploma,15,48,75,52,59,0.0,6,70,Urban,Manager,111775,1 +36691,Male,39,High School,8,96,23,67,96,9.0,4,7,Rural,Manager,33944,0 +36692,Male,58,Masters,12,89,1,81,63,6.0,5,8,Urban,Manager,118966,0 +36693,Female,58,Bachelors,9,24,28,0,11,7.0,5,66,Urban,Software Engineer,53837,0 +36694,Female,24,High School,17,88,5,30,76,4.0,2,2,Urban,Data Analyst,42419,0 +36695,Male,48,Bachelors,9,56,57,23,3,4.0,3,45,Semi-Urban,Software Engineer,98447,0 +36696,Male,46,Diploma,13,40,59,12,32,5.0,7,32,Urban,ML Engineer,57037,0 +36697,Male,41,Masters,12,88,8,69,94,3.0,1,20,Urban,HR Executive,129836,0 +36698,Female,56,Bachelors,8,27,20,65,19,1.0,2,82,Semi-Urban,Software Engineer,69368,0 +36699,Male,36,Diploma,12,62,77,30,88,8.0,4,72,Rural,Manager,137673,1 +36700,Male,22,Masters,8,57,91,82,53,6.0,1,37,Semi-Urban,ML Engineer,76484,1 +36701,Male,37,High School,15,61,14,23,63,7.0,3,79,Semi-Urban,Manager,34313,0 +36702,Male,21,Diploma,18,9,0,70,39,8.0,2,25,Semi-Urban,HR Executive,100701,0 +36703,Female,47,Bachelors,6,96,48,82,91,8.0,1,37,Urban,Manager,85035,1 +36704,Male,27,Bachelors,15,87,47,51,70,1.0,7,53,Urban,Manager,116431,1 +36705,Male,37,High School,14,21,58,27,65,6.0,6,35,Urban,ML Engineer,114103,0 +36706,Male,22,Bachelors,16,53,56,65,47,3.0,2,34,Urban,Manager,59329,0 +36707,Male,21,Masters,7,74,22,51,23,5.0,1,51,Semi-Urban,HR Executive,47800,0 +36708,Male,59,Masters,19,94,30,98,54,4.0,0,32,Urban,HR Executive,104689,1 +36709,Male,38,High School,16,30,31,0,69,2.0,2,55,Urban,Data Analyst,106637,0 +36710,Male,51,Bachelors,5,81,15,13,87,2.0,0,66,Rural,Data Analyst,105378,0 +36711,Female,35,High School,19,65,16,21,13,7.0,5,93,Urban,Software Engineer,61004,0 +36712,Female,55,Bachelors,5,27,38,61,99,5.0,2,62,Rural,HR Executive,131872,0 +36713,Male,35,Masters,11,11,35,28,41,9.0,3,22,Urban,ML Engineer,42445,0 +36714,Male,31,Masters,16,11,37,81,26,8.0,6,44,Semi-Urban,Software Engineer,70530,0 +36715,Male,37,Bachelors,6,96,97,56,69,9.0,3,10,Rural,Software Engineer,82231,1 +36716,Male,22,Masters,2,37,99,29,45,5.0,4,87,Rural,Data Analyst,98846,1 +36717,Female,47,Masters,19,64,33,46,26,3.0,1,72,Semi-Urban,ML Engineer,27012,0 +36718,Other,30,High School,17,56,58,29,30,1.0,7,39,Urban,Manager,138038,0 +36719,Female,55,Masters,0,89,91,13,43,4.0,4,93,Semi-Urban,Software Engineer,103852,1 +36720,Male,28,Bachelors,15,15,88,57,11,5.0,0,90,Urban,HR Executive,115825,1 +36721,Female,27,High School,9,58,74,38,24,3.0,1,30,Rural,Manager,99253,0 +36722,Male,25,Diploma,12,11,55,76,30,6.0,3,14,Rural,Software Engineer,113022,0 +36723,Female,29,High School,5,44,26,87,44,0.0,2,49,Rural,Manager,128991,0 +36724,Male,30,High School,13,35,30,21,26,0.0,1,12,Urban,ML Engineer,55214,0 +36725,Male,46,Bachelors,19,96,18,82,20,9.0,1,33,Rural,Software Engineer,139015,0 +36726,Male,45,Bachelors,4,16,81,12,9,0.0,5,93,Urban,Software Engineer,112711,0 +36727,Male,28,Bachelors,9,26,25,81,3,2.0,6,58,Rural,ML Engineer,71099,0 +36728,Female,50,Bachelors,11,25,5,16,74,8.0,3,21,Rural,ML Engineer,143292,0 +36729,Female,50,Masters,2,25,32,88,78,9.0,0,38,Semi-Urban,ML Engineer,43976,0 +36730,Female,30,Bachelors,8,28,66,26,66,0.0,2,30,Urban,Data Analyst,48280,0 +36731,Other,31,High School,15,74,91,22,43,8.0,6,53,Urban,Manager,87281,0 +36732,Male,59,Bachelors,15,81,16,64,50,6.0,4,19,Urban,Data Analyst,113871,0 +36733,Male,22,Masters,0,31,31,87,69,2.0,2,22,Urban,HR Executive,83215,0 +36734,Male,43,Bachelors,11,99,58,66,17,1.0,4,51,Rural,ML Engineer,126061,1 +36735,Female,25,Diploma,4,19,15,98,36,4.0,5,79,Rural,Data Analyst,29969,0 +36736,Male,21,Masters,14,66,8,28,83,6.0,0,30,Urban,Data Analyst,127951,0 +36737,Male,52,Masters,13,47,59,19,8,3.0,1,95,Urban,HR Executive,94897,0 +36738,Male,50,Bachelors,3,36,72,85,69,4.0,3,26,Semi-Urban,HR Executive,32819,0 +36739,Other,46,Masters,10,77,7,82,88,2.0,2,5,Rural,HR Executive,100749,0 +36740,Female,58,Bachelors,9,58,68,53,80,2.0,3,69,Rural,Data Analyst,63346,1 +36741,Male,29,Masters,6,51,29,26,39,7.0,4,83,Semi-Urban,Manager,129829,0 +36742,Female,32,High School,3,75,76,1,12,2.0,0,49,Urban,HR Executive,46839,0 +36743,Male,27,Masters,1,4,46,65,13,5.0,3,4,Urban,ML Engineer,55812,0 +36744,Male,49,Diploma,3,89,45,58,95,7.0,3,42,Urban,Software Engineer,92821,0 +36745,Female,28,Diploma,12,53,90,58,83,6.0,3,35,Urban,Manager,77928,0 +36746,Male,24,Bachelors,7,97,36,14,58,4.0,3,89,Urban,Manager,82931,1 +36747,Male,50,Bachelors,8,50,4,32,62,0.0,6,21,Rural,ML Engineer,101588,0 +36748,Female,43,High School,13,92,31,65,57,4.0,1,35,Urban,ML Engineer,117695,0 +36749,Female,49,Bachelors,4,29,69,91,4,1.0,3,79,Urban,Software Engineer,81845,1 +36750,Other,59,High School,9,51,8,29,89,3.0,2,7,Semi-Urban,HR Executive,147691,0 +36751,Male,32,High School,8,95,99,19,48,4.0,7,33,Rural,Manager,116950,1 +36752,Male,32,Diploma,6,16,35,82,22,8.0,7,61,Rural,HR Executive,87715,0 +36753,Male,38,Bachelors,18,5,4,1,79,5.0,0,27,Urban,Software Engineer,41353,0 +36754,Female,41,Bachelors,9,57,80,11,58,7.0,3,80,Semi-Urban,HR Executive,138952,0 +36755,Male,47,Bachelors,13,94,55,6,18,1.0,5,80,Rural,Software Engineer,127392,1 +36756,Male,39,PhD,14,80,52,92,76,7.0,1,48,Semi-Urban,Data Analyst,20181,1 +36757,Male,24,High School,19,35,13,38,16,9.0,2,10,Urban,HR Executive,99081,0 +36758,Female,40,High School,0,2,49,74,49,0.0,3,99,Semi-Urban,Data Analyst,82924,0 +36759,Male,36,Diploma,1,47,4,78,41,8.0,4,72,Semi-Urban,HR Executive,33384,0 +36760,Male,26,Masters,15,20,29,82,72,3.0,4,61,Urban,Data Analyst,76264,0 +36761,Male,42,Diploma,1,27,44,88,88,7.0,3,1,Semi-Urban,Manager,134787,0 +36762,Male,44,Masters,18,45,86,69,85,3.0,1,8,Urban,Manager,41461,0 +36763,Male,59,Masters,14,63,96,1,76,1.0,7,75,Urban,Manager,108922,1 +36764,Male,57,Diploma,2,84,9,72,91,3.0,4,65,Urban,Data Analyst,42006,0 +36765,Female,52,Bachelors,4,17,27,71,50,9.0,5,75,Urban,Manager,124929,0 +36766,Male,53,Masters,11,44,63,3,94,7.0,5,17,Urban,HR Executive,22718,0 +36767,Male,27,Bachelors,7,32,92,59,24,8.0,3,49,Urban,Software Engineer,121451,0 +36768,Male,49,Masters,3,28,35,10,86,6.0,1,87,Urban,Software Engineer,44578,0 +36769,Other,50,High School,10,47,72,96,16,0.0,0,43,Semi-Urban,Manager,91158,1 +36770,Male,39,High School,7,59,63,42,85,1.0,4,66,Urban,HR Executive,45546,0 +36771,Female,33,Diploma,3,5,61,20,97,3.0,1,32,Rural,ML Engineer,105677,0 +36772,Female,42,Bachelors,7,87,42,91,20,3.0,4,3,Urban,Data Analyst,65468,0 +36773,Male,59,Bachelors,6,51,2,82,53,1.0,4,15,Rural,Software Engineer,34933,0 +36774,Male,49,Diploma,8,94,78,68,95,3.0,1,52,Urban,HR Executive,139875,1 +36775,Female,38,Bachelors,7,18,52,39,46,7.0,7,33,Rural,HR Executive,87774,0 +36776,Female,28,Masters,8,22,51,91,78,2.0,2,83,Urban,Software Engineer,73370,1 +36777,Female,27,Masters,7,51,55,74,71,8.0,3,76,Semi-Urban,Software Engineer,56858,1 +36778,Female,57,Bachelors,9,99,10,32,77,7.0,2,81,Semi-Urban,Software Engineer,61006,0 +36779,Male,54,Bachelors,18,42,46,67,61,6.0,2,77,Rural,ML Engineer,30934,0 +36780,Female,56,Bachelors,0,1,71,79,1,8.0,5,52,Urban,Data Analyst,104839,0 +36781,Male,30,Bachelors,15,50,1,31,72,0.0,1,49,Semi-Urban,HR Executive,71162,0 +36782,Male,55,Bachelors,8,90,68,2,74,9.0,1,81,Urban,HR Executive,140316,1 +36783,Female,25,Bachelors,0,56,25,42,63,9.0,0,28,Semi-Urban,HR Executive,60479,0 +36784,Male,46,Masters,18,94,78,67,90,2.0,0,82,Rural,HR Executive,74229,1 +36785,Male,27,Diploma,3,81,32,31,94,9.0,3,94,Urban,Software Engineer,126461,1 +36786,Male,27,Masters,15,51,17,9,42,3.0,7,98,Urban,HR Executive,68581,0 +36787,Male,32,Diploma,12,31,22,63,71,9.0,7,78,Rural,ML Engineer,59930,0 +36788,Female,59,Bachelors,11,45,3,85,63,9.0,5,99,Semi-Urban,ML Engineer,148695,0 +36789,Male,45,Bachelors,11,55,21,94,84,8.0,2,19,Semi-Urban,ML Engineer,96993,0 +36790,Female,26,Bachelors,14,67,90,32,35,3.0,0,54,Urban,Manager,136076,1 +36791,Male,28,Masters,17,25,70,92,94,7.0,2,81,Urban,HR Executive,27147,1 +36792,Male,29,Bachelors,15,50,21,1,56,0.0,7,55,Urban,Manager,55800,0 +36793,Male,21,High School,13,87,39,28,28,0.0,7,95,Urban,Software Engineer,85107,1 +36794,Male,59,Bachelors,3,86,31,69,16,5.0,3,61,Rural,Manager,23170,1 +36795,Male,29,Bachelors,0,54,16,92,88,3.0,2,1,Semi-Urban,ML Engineer,133381,0 +36796,Female,53,Masters,15,42,6,13,72,3.0,2,51,Rural,ML Engineer,76194,0 +36797,Male,43,Masters,4,16,89,92,29,0.0,6,67,Urban,Software Engineer,118749,1 +36798,Male,57,Bachelors,12,15,92,89,73,5.0,4,31,Urban,Manager,69579,0 +36799,Male,27,Masters,6,87,85,45,50,2.0,5,54,Rural,Manager,42797,1 +36800,Male,58,Bachelors,18,89,76,4,38,3.0,0,58,Semi-Urban,Software Engineer,146950,0 +36801,Male,34,Masters,18,38,16,39,20,7.0,0,1,Rural,Data Analyst,79956,0 +36802,Female,37,Bachelors,15,74,2,59,50,2.0,6,73,Semi-Urban,Software Engineer,30853,0 +36803,Male,53,Masters,8,72,38,26,47,3.0,6,13,Urban,Software Engineer,148168,0 +36804,Male,59,Masters,3,54,35,98,31,3.0,0,98,Urban,Manager,49528,1 +36805,Male,26,Bachelors,11,44,80,59,30,6.0,1,45,Urban,Data Analyst,74602,0 +36806,Male,35,High School,3,38,48,89,84,5.0,0,46,Semi-Urban,Data Analyst,49950,0 +36807,Male,51,Diploma,6,79,3,66,66,5.0,5,38,Urban,Software Engineer,68672,0 +36808,Female,59,Bachelors,10,4,29,15,0,9.0,5,93,Urban,Software Engineer,100413,0 +36809,Female,56,Masters,9,96,73,73,72,1.0,7,49,Urban,Manager,61277,1 +36810,Male,25,Diploma,11,39,26,99,46,4.0,3,45,Urban,HR Executive,111496,0 +36811,Female,58,High School,18,91,95,65,93,5.0,4,2,Rural,Software Engineer,123228,1 +36812,Male,49,Masters,18,45,85,18,20,6.0,6,62,Urban,Manager,71884,0 +36813,Female,28,Masters,19,63,39,84,18,5.0,1,25,Rural,Data Analyst,20906,0 +36814,Female,51,Bachelors,14,57,79,39,35,4.0,3,45,Rural,Manager,133965,0 +36815,Male,50,Diploma,12,2,66,44,41,2.0,0,33,Semi-Urban,HR Executive,118556,0 +36816,Male,53,Bachelors,11,15,58,23,7,6.0,4,39,Urban,ML Engineer,92881,0 +36817,Male,52,Bachelors,10,69,17,58,3,2.0,0,69,Semi-Urban,ML Engineer,34969,0 +36818,Male,53,PhD,14,16,47,33,40,2.0,4,27,Urban,ML Engineer,133593,0 +36819,Male,59,Diploma,11,89,91,68,63,1.0,0,5,Rural,Software Engineer,22075,1 +36820,Female,47,Bachelors,5,19,67,52,68,3.0,0,23,Urban,Software Engineer,37794,0 +36821,Male,21,Masters,17,33,20,25,11,5.0,7,29,Urban,HR Executive,51817,0 +36822,Male,40,Masters,16,48,16,98,71,9.0,4,64,Urban,HR Executive,38091,0 +36823,Female,51,PhD,19,40,67,88,99,3.0,7,59,Urban,HR Executive,71222,1 +36824,Female,35,Bachelors,1,75,46,95,20,7.0,0,44,Urban,Software Engineer,40930,1 +36825,Male,23,Bachelors,18,34,33,15,94,9.0,6,0,Rural,HR Executive,133273,0 +36826,Female,24,Masters,10,85,57,99,6,9.0,6,32,Urban,ML Engineer,108011,1 +36827,Female,38,Bachelors,6,59,92,27,72,5.0,7,30,Semi-Urban,HR Executive,117461,0 +36828,Male,32,Bachelors,14,72,9,8,47,3.0,7,33,Rural,ML Engineer,32300,0 +36829,Male,52,Masters,11,21,80,95,4,5.0,5,72,Semi-Urban,Manager,112171,1 +36830,Female,33,Masters,11,62,0,37,91,7.0,6,13,Urban,ML Engineer,96873,0 +36831,Female,39,Masters,8,78,38,22,13,9.0,7,49,Urban,HR Executive,36829,0 +36832,Male,40,Masters,10,39,73,60,76,1.0,2,69,Semi-Urban,Software Engineer,74135,1 +36833,Male,59,Diploma,18,82,43,68,27,2.0,3,21,Urban,HR Executive,93162,0 +36834,Female,55,Masters,6,33,11,77,62,9.0,5,25,Urban,HR Executive,34982,0 +36835,Other,29,Masters,2,6,41,53,45,9.0,5,33,Urban,ML Engineer,68807,0 +36836,Female,46,Bachelors,15,31,91,37,65,6.0,4,13,Semi-Urban,Manager,95100,0 +36837,Other,23,Diploma,7,98,68,24,84,1.0,6,66,Urban,ML Engineer,88110,1 +36838,Female,24,Bachelors,6,39,97,43,92,8.0,6,15,Urban,ML Engineer,36120,0 +36839,Female,33,Diploma,6,67,21,10,62,6.0,2,36,Urban,Software Engineer,88292,0 +36840,Female,30,Diploma,5,61,82,91,7,7.0,3,34,Urban,Software Engineer,41365,1 +36841,Female,46,Masters,2,28,89,37,76,6.0,0,36,Urban,Manager,45456,0 +36842,Male,30,Bachelors,1,63,29,33,98,0.0,1,23,Rural,HR Executive,55432,0 +36843,Female,50,Diploma,2,95,66,71,96,8.0,3,22,Rural,HR Executive,120971,1 +36844,Male,27,Masters,8,25,54,75,4,3.0,5,13,Semi-Urban,Manager,132575,0 +36845,Male,46,Diploma,15,47,35,48,77,0.0,3,82,Urban,Software Engineer,132099,0 +36846,Male,42,Bachelors,5,38,42,30,66,7.0,4,12,Urban,ML Engineer,82044,0 +36847,Male,53,Bachelors,13,79,83,15,56,6.0,3,18,Urban,Data Analyst,123718,0 +36848,Male,26,High School,13,49,81,7,85,1.0,5,28,Urban,HR Executive,115182,0 +36849,Other,31,Bachelors,3,75,10,28,85,5.0,6,69,Rural,ML Engineer,43825,0 +36850,Female,43,Bachelors,13,24,30,36,13,8.0,2,92,Semi-Urban,Software Engineer,39269,0 +36851,Female,47,Diploma,14,83,57,70,75,9.0,1,9,Semi-Urban,ML Engineer,104000,0 +36852,Other,45,Bachelors,8,86,6,18,77,2.0,3,52,Semi-Urban,Software Engineer,102679,0 +36853,Male,38,High School,4,37,51,85,66,6.0,3,12,Urban,ML Engineer,56347,0 +36854,Male,51,Diploma,8,79,97,35,98,4.0,3,97,Semi-Urban,Manager,111327,1 +36855,Male,25,Diploma,18,89,24,95,0,4.0,5,58,Urban,Data Analyst,147947,1 +36856,Male,52,Masters,3,91,95,63,28,0.0,6,97,Urban,HR Executive,80207,1 +36857,Female,43,High School,15,22,96,99,29,5.0,1,59,Rural,Manager,57943,1 +36858,Male,50,Diploma,12,33,23,83,83,1.0,0,4,Urban,Manager,57661,0 +36859,Male,40,Masters,5,71,31,30,34,2.0,2,90,Semi-Urban,ML Engineer,35767,0 +36860,Male,29,Diploma,6,59,73,1,73,9.0,5,58,Semi-Urban,Data Analyst,114376,0 +36861,Male,22,Bachelors,10,6,17,23,45,8.0,3,40,Urban,Manager,50671,0 +36862,Male,31,Bachelors,0,38,57,37,65,2.0,0,45,Rural,Manager,85795,0 +36863,Female,36,Diploma,18,44,20,88,63,7.0,0,89,Urban,HR Executive,47011,1 +36864,Male,27,Masters,15,22,93,78,83,4.0,1,12,Semi-Urban,Manager,46391,0 +36865,Male,56,Diploma,15,79,70,18,67,5.0,5,10,Semi-Urban,Software Engineer,112895,0 +36866,Male,47,Bachelors,7,58,35,95,5,2.0,0,59,Rural,HR Executive,146297,1 +36867,Female,33,High School,7,12,7,35,19,5.0,1,37,Urban,HR Executive,61771,0 +36868,Male,32,Masters,9,53,4,49,50,0.0,1,82,Rural,ML Engineer,118123,0 +36869,Male,40,Bachelors,15,57,97,65,85,6.0,1,15,Semi-Urban,Software Engineer,118274,0 +36870,Male,58,Bachelors,12,24,60,61,6,7.0,5,17,Semi-Urban,HR Executive,29002,0 +36871,Female,37,Diploma,9,93,25,2,51,6.0,0,28,Urban,HR Executive,146402,0 +36872,Female,55,Bachelors,18,51,64,61,4,8.0,3,86,Urban,Data Analyst,76867,1 +36873,Male,45,High School,16,3,70,45,32,6.0,3,40,Urban,ML Engineer,105470,0 +36874,Female,41,Masters,0,3,79,15,23,9.0,6,1,Urban,Data Analyst,128616,0 +36875,Male,56,Diploma,1,64,46,1,62,8.0,7,66,Urban,ML Engineer,46970,0 +36876,Male,37,High School,9,42,71,78,76,2.0,3,13,Semi-Urban,ML Engineer,70984,0 +36877,Male,56,Bachelors,0,34,31,39,11,3.0,6,99,Urban,Software Engineer,20432,0 +36878,Male,27,Bachelors,0,58,86,96,59,6.0,7,60,Urban,Data Analyst,61621,1 +36879,Female,35,Diploma,12,15,40,1,63,1.0,7,46,Urban,Software Engineer,36631,0 +36880,Female,46,PhD,17,46,23,21,67,2.0,4,42,Semi-Urban,ML Engineer,117051,0 +36881,Male,38,Bachelors,4,33,85,30,49,1.0,4,8,Urban,Data Analyst,105035,0 +36882,Male,57,Bachelors,17,11,95,96,10,9.0,5,18,Urban,Software Engineer,90746,0 +36883,Male,32,Masters,5,6,24,9,85,2.0,6,24,Urban,Data Analyst,87738,0 +36884,Male,48,Masters,8,45,97,79,81,4.0,3,12,Semi-Urban,Manager,22310,0 +36885,Female,48,PhD,4,87,72,86,81,7.0,2,18,Rural,Manager,63750,1 +36886,Female,44,High School,6,26,15,45,96,1.0,4,74,Urban,Manager,97979,0 +36887,Female,36,Bachelors,18,59,92,51,5,1.0,5,20,Urban,Software Engineer,28309,0 +36888,Male,44,Bachelors,6,9,66,75,22,5.0,1,82,Urban,ML Engineer,128918,0 +36889,Female,26,Diploma,17,76,60,97,64,8.0,0,42,Rural,Data Analyst,136012,1 +36890,Male,45,Bachelors,14,5,43,54,27,1.0,6,45,Urban,Manager,68635,0 +36891,Other,48,Masters,11,20,14,52,93,5.0,3,55,Rural,Manager,147457,0 +36892,Male,39,Diploma,14,25,40,9,72,8.0,2,40,Urban,Data Analyst,61061,0 +36893,Male,47,Bachelors,4,16,59,68,85,6.0,5,61,Semi-Urban,Data Analyst,62920,0 +36894,Male,59,Masters,1,16,4,37,24,9.0,1,0,Urban,Software Engineer,40533,0 +36895,Male,26,Bachelors,15,58,40,0,60,3.0,3,95,Urban,ML Engineer,116963,0 +36896,Female,38,High School,1,35,25,97,29,7.0,1,51,Urban,HR Executive,52067,0 +36897,Female,21,Bachelors,10,12,16,4,75,8.0,6,64,Semi-Urban,Data Analyst,97973,0 +36898,Female,59,High School,13,13,75,4,53,3.0,1,73,Urban,ML Engineer,28219,0 +36899,Male,31,Diploma,10,36,91,7,69,2.0,0,7,Urban,Data Analyst,95174,0 +36900,Male,29,Masters,18,3,60,44,42,3.0,7,6,Rural,ML Engineer,75729,0 +36901,Female,22,Bachelors,1,10,2,81,45,5.0,0,91,Rural,ML Engineer,148720,0 +36902,Female,57,Bachelors,3,61,94,43,60,8.0,3,62,Urban,HR Executive,88625,1 +36903,Male,28,Diploma,12,38,29,81,85,9.0,2,25,Semi-Urban,Data Analyst,123065,0 +36904,Female,26,Bachelors,6,9,53,15,94,2.0,3,71,Semi-Urban,ML Engineer,21405,0 +36905,Other,26,Diploma,8,9,98,46,71,0.0,7,86,Urban,ML Engineer,77702,0 +36906,Female,42,Masters,13,90,84,3,98,7.0,7,98,Rural,ML Engineer,64912,1 +36907,Male,48,Bachelors,14,48,90,21,81,2.0,1,43,Urban,Manager,73035,0 +36908,Female,26,Diploma,1,13,74,73,53,1.0,1,19,Urban,Data Analyst,101708,0 +36909,Male,24,Bachelors,9,5,3,32,51,4.0,2,19,Urban,HR Executive,20119,0 +36910,Female,45,Bachelors,1,22,52,7,63,3.0,5,68,Urban,Data Analyst,142781,0 +36911,Male,42,Bachelors,4,7,76,80,88,4.0,2,52,Semi-Urban,Data Analyst,50793,0 +36912,Female,38,Diploma,8,45,67,19,98,1.0,4,6,Urban,Data Analyst,59836,0 +36913,Female,29,Bachelors,1,34,97,79,67,5.0,5,44,Semi-Urban,HR Executive,123804,1 +36914,Male,35,Diploma,8,97,93,11,15,4.0,2,25,Urban,ML Engineer,113964,0 +36915,Female,44,PhD,13,95,77,94,67,5.0,7,54,Rural,Data Analyst,80949,1 +36916,Male,47,Bachelors,14,43,93,85,81,4.0,3,86,Semi-Urban,Software Engineer,35639,1 +36917,Male,49,Diploma,8,42,94,91,31,3.0,0,80,Urban,Software Engineer,143046,1 +36918,Male,55,High School,6,15,11,1,31,9.0,4,49,Urban,Manager,84195,0 +36919,Male,51,Diploma,19,41,28,98,93,5.0,3,49,Urban,Software Engineer,102805,0 +36920,Other,46,Masters,14,59,31,43,49,4.0,1,96,Urban,Software Engineer,136410,0 +36921,Male,44,Diploma,5,86,42,57,8,3.0,4,56,Urban,Software Engineer,88864,1 +36922,Female,57,Bachelors,0,28,61,98,7,2.0,6,74,Semi-Urban,Manager,147361,1 +36923,Male,43,Bachelors,5,67,79,29,65,1.0,6,34,Rural,HR Executive,115217,0 +36924,Female,42,Bachelors,8,91,91,66,32,5.0,4,23,Urban,Manager,77073,1 +36925,Male,40,Masters,10,8,63,46,77,8.0,5,64,Urban,Software Engineer,81968,0 +36926,Male,53,Diploma,19,82,34,14,28,0.0,3,99,Urban,Data Analyst,123451,0 +36927,Other,50,High School,7,71,69,24,9,7.0,3,4,Urban,HR Executive,59659,0 +36928,Male,41,Bachelors,18,99,68,65,98,7.0,6,78,Urban,Data Analyst,140405,1 +36929,Female,37,PhD,3,84,31,15,39,1.0,7,82,Urban,HR Executive,103638,0 +36930,Male,32,Bachelors,11,3,22,30,10,0.0,5,97,Rural,Data Analyst,98264,0 +36931,Male,49,Bachelors,11,21,26,40,67,3.0,3,43,Urban,Software Engineer,88350,0 +36932,Female,27,Masters,6,35,73,10,47,7.0,7,72,Semi-Urban,Manager,37189,0 +36933,Female,46,Masters,3,15,62,10,37,1.0,4,15,Semi-Urban,ML Engineer,37700,0 +36934,Male,29,High School,10,47,29,22,54,5.0,2,60,Semi-Urban,ML Engineer,41176,0 +36935,Female,26,Bachelors,2,54,6,31,0,0.0,7,71,Urban,Data Analyst,71625,0 +36936,Male,46,Diploma,5,47,92,9,13,8.0,7,10,Semi-Urban,Data Analyst,103259,0 +36937,Male,39,Diploma,8,94,97,31,17,9.0,3,83,Urban,Data Analyst,88610,1 +36938,Male,24,Bachelors,7,85,11,74,71,3.0,0,30,Rural,Data Analyst,33542,0 +36939,Female,52,Bachelors,16,91,45,77,60,1.0,7,33,Semi-Urban,Manager,38843,1 +36940,Male,35,PhD,3,83,95,1,26,8.0,0,35,Semi-Urban,HR Executive,102909,0 +36941,Male,23,Bachelors,2,56,23,16,82,8.0,4,28,Rural,Software Engineer,80091,0 +36942,Other,22,High School,6,65,97,95,89,6.0,0,7,Semi-Urban,ML Engineer,113639,1 +36943,Male,34,High School,0,79,79,99,30,7.0,5,32,Urban,Manager,29854,1 +36944,Male,39,Bachelors,6,69,75,97,8,8.0,4,31,Semi-Urban,Manager,24659,1 +36945,Male,31,Bachelors,0,79,33,90,33,4.0,5,48,Urban,ML Engineer,31724,1 +36946,Male,53,Diploma,7,32,35,61,63,6.0,2,52,Semi-Urban,Data Analyst,104454,0 +36947,Male,41,Bachelors,18,78,12,14,46,0.0,3,47,Rural,Software Engineer,137729,0 +36948,Male,41,High School,9,21,77,98,34,3.0,7,21,Semi-Urban,HR Executive,61411,0 +36949,Male,39,Bachelors,7,32,79,12,63,0.0,1,0,Urban,Data Analyst,126142,0 +36950,Male,49,Masters,15,31,5,41,92,0.0,1,84,Urban,ML Engineer,60009,0 +36951,Female,58,Bachelors,2,32,0,52,35,9.0,4,93,Rural,HR Executive,82288,0 +36952,Other,28,Diploma,15,92,66,76,90,1.0,1,20,Urban,HR Executive,82645,1 +36953,Female,52,Bachelors,11,32,57,91,13,9.0,4,70,Urban,ML Engineer,74684,1 +36954,Male,54,Diploma,16,48,82,6,63,9.0,4,41,Urban,Data Analyst,26636,0 +36955,Male,41,Masters,1,27,67,99,20,1.0,2,36,Urban,HR Executive,125535,0 +36956,Female,40,Bachelors,5,75,90,83,34,2.0,1,67,Rural,Data Analyst,142583,1 +36957,Female,47,Bachelors,16,64,54,31,52,1.0,0,51,Semi-Urban,ML Engineer,142942,0 +36958,Male,43,High School,14,68,77,32,98,1.0,7,29,Rural,Manager,37979,0 +36959,Male,36,Bachelors,7,47,26,41,49,6.0,1,52,Urban,ML Engineer,107994,0 +36960,Female,33,Bachelors,1,80,31,30,18,5.0,4,72,Rural,Manager,147180,0 +36961,Male,41,Bachelors,15,93,40,23,21,9.0,3,6,Rural,Software Engineer,138675,0 +36962,Male,27,Masters,11,26,73,68,20,9.0,7,36,Semi-Urban,Data Analyst,148189,0 +36963,Male,45,Bachelors,1,67,93,94,14,1.0,0,66,Urban,Software Engineer,97397,1 +36964,Female,36,Masters,3,82,55,90,48,2.0,7,47,Urban,HR Executive,29708,1 +36965,Female,57,Bachelors,19,21,44,33,35,9.0,3,45,Rural,Manager,78273,0 +36966,Female,41,Bachelors,15,78,53,51,39,0.0,7,54,Semi-Urban,ML Engineer,107938,0 +36967,Female,49,Diploma,19,83,74,2,11,8.0,0,29,Rural,Software Engineer,146694,0 +36968,Male,56,Diploma,3,72,96,81,88,7.0,2,14,Rural,Manager,69229,1 +36969,Female,50,Bachelors,5,94,86,53,88,0.0,5,1,Urban,HR Executive,127398,0 +36970,Male,41,Bachelors,12,42,35,92,19,9.0,7,82,Rural,HR Executive,58720,1 +36971,Male,54,Masters,10,20,46,60,71,0.0,4,62,Semi-Urban,HR Executive,131844,0 +36972,Female,48,Bachelors,13,16,50,48,22,1.0,0,85,Semi-Urban,Software Engineer,121551,0 +36973,Male,40,Diploma,11,22,71,49,3,7.0,4,36,Urban,Manager,108531,0 +36974,Male,23,Bachelors,5,67,54,7,48,6.0,0,98,Semi-Urban,Manager,41937,0 +36975,Other,44,High School,3,77,88,50,59,6.0,1,35,Urban,HR Executive,142502,1 +36976,Other,34,Bachelors,18,25,97,56,5,1.0,0,98,Urban,Manager,112559,1 +36977,Male,40,Bachelors,6,88,29,91,18,7.0,2,3,Rural,Software Engineer,90806,0 +36978,Male,28,Diploma,16,65,20,4,53,2.0,4,87,Urban,Software Engineer,82985,0 +36979,Male,38,High School,6,89,91,11,20,1.0,2,61,Urban,ML Engineer,90681,1 +36980,Female,37,High School,3,90,59,23,79,9.0,3,52,Urban,ML Engineer,54136,0 +36981,Male,24,High School,8,88,21,18,81,9.0,2,30,Urban,Manager,30751,0 +36982,Other,43,Bachelors,3,69,18,8,37,9.0,3,52,Urban,ML Engineer,48560,0 +36983,Male,32,Bachelors,8,4,18,20,45,5.0,4,79,Rural,Software Engineer,79682,0 +36984,Male,54,PhD,11,50,38,70,2,3.0,4,58,Rural,Manager,52232,0 +36985,Male,21,Diploma,9,13,61,96,70,2.0,1,61,Semi-Urban,ML Engineer,68533,0 +36986,Male,55,Diploma,11,89,35,82,79,7.0,7,30,Urban,HR Executive,55330,1 +36987,Female,50,Masters,11,48,35,26,75,9.0,7,21,Rural,Software Engineer,70950,0 +36988,Female,41,PhD,10,32,7,28,28,0.0,1,62,Urban,Manager,129337,0 +36989,Male,55,Bachelors,8,99,74,32,6,2.0,1,6,Urban,Data Analyst,33211,0 +36990,Male,43,High School,12,41,42,22,34,2.0,0,88,Urban,Data Analyst,92192,0 +36991,Female,35,Bachelors,17,42,9,4,64,2.0,0,5,Semi-Urban,ML Engineer,133728,0 +36992,Male,43,High School,5,99,47,21,59,8.0,5,78,Urban,HR Executive,84258,1 +36993,Female,21,Masters,0,50,18,14,28,5.0,0,75,Semi-Urban,ML Engineer,32377,0 +36994,Male,51,Bachelors,6,8,76,92,99,0.0,1,97,Rural,ML Engineer,61644,1 +36995,Male,47,Masters,19,83,74,77,34,6.0,1,23,Urban,Manager,120646,1 +36996,Male,43,Masters,7,73,92,18,66,7.0,2,30,Urban,Manager,76912,0 +36997,Male,40,Masters,12,74,0,73,32,9.0,7,11,Semi-Urban,HR Executive,23461,0 +36998,Male,59,High School,13,51,41,45,56,2.0,7,79,Semi-Urban,Data Analyst,121819,0 +36999,Other,52,Masters,9,57,38,5,96,1.0,6,28,Urban,Manager,149067,0 +37000,Male,52,Diploma,12,33,81,36,50,3.0,7,0,Urban,Manager,77855,0 +37001,Male,40,Diploma,3,52,37,99,98,8.0,3,70,Urban,Manager,130430,1 +37002,Male,48,Bachelors,3,50,96,8,49,5.0,4,33,Semi-Urban,Data Analyst,142816,0 +37003,Female,42,Bachelors,12,44,72,13,40,7.0,0,69,Semi-Urban,Data Analyst,40495,0 +37004,Female,25,Bachelors,1,33,38,58,77,1.0,2,72,Semi-Urban,Manager,88784,0 +37005,Female,23,PhD,9,27,57,66,20,7.0,0,34,Urban,ML Engineer,102114,0 +37006,Male,53,Bachelors,7,52,74,39,76,4.0,4,49,Urban,ML Engineer,83288,0 +37007,Female,57,PhD,14,93,44,53,58,6.0,1,23,Urban,HR Executive,49724,0 +37008,Female,37,Bachelors,12,9,58,97,90,3.0,0,40,Rural,Manager,30984,0 +37009,Male,56,Bachelors,12,19,92,87,97,4.0,4,83,Urban,ML Engineer,68081,1 +37010,Male,55,High School,17,22,95,14,86,6.0,2,41,Urban,Manager,149497,0 +37011,Female,31,High School,0,11,8,87,20,9.0,4,16,Semi-Urban,HR Executive,21005,0 +37012,Male,56,High School,1,94,0,49,64,3.0,0,88,Urban,HR Executive,115389,0 +37013,Male,29,Bachelors,14,77,87,32,42,9.0,1,37,Semi-Urban,Manager,80828,0 +37014,Male,23,Bachelors,10,47,63,13,67,9.0,1,99,Urban,Software Engineer,107693,0 +37015,Male,47,Diploma,7,10,40,26,24,0.0,2,68,Urban,Manager,141243,0 +37016,Male,59,High School,17,61,6,70,4,5.0,2,33,Urban,Data Analyst,139791,0 +37017,Female,43,Bachelors,13,55,92,54,35,2.0,2,94,Semi-Urban,Manager,96674,1 +37018,Female,27,Bachelors,8,16,8,64,3,0.0,6,81,Urban,Data Analyst,147561,0 +37019,Male,31,Bachelors,15,0,80,72,34,5.0,6,48,Urban,ML Engineer,109263,0 +37020,Male,55,Bachelors,10,10,71,85,59,4.0,7,19,Urban,HR Executive,54367,0 +37021,Female,58,PhD,12,29,80,38,66,4.0,5,43,Semi-Urban,HR Executive,90343,0 +37022,Female,39,High School,19,58,2,7,59,7.0,2,54,Urban,Manager,73147,0 +37023,Male,30,PhD,0,17,25,99,19,8.0,6,5,Urban,Software Engineer,25676,0 +37024,Female,48,Masters,2,98,85,80,73,8.0,3,82,Rural,HR Executive,86507,1 +37025,Female,29,Bachelors,13,20,93,81,64,2.0,3,50,Semi-Urban,Software Engineer,25446,1 +37026,Male,25,Masters,8,85,65,54,87,6.0,5,90,Semi-Urban,ML Engineer,125135,1 +37027,Male,48,Bachelors,4,48,59,31,68,4.0,7,25,Urban,Software Engineer,147743,0 +37028,Male,39,Bachelors,17,23,44,60,10,9.0,2,67,Rural,Manager,46550,0 +37029,Other,35,Masters,5,84,38,40,29,9.0,3,90,Rural,Manager,141313,1 +37030,Male,47,Bachelors,10,24,41,87,50,7.0,2,67,Rural,Manager,133914,0 +37031,Male,21,Bachelors,2,55,36,37,81,4.0,0,11,Urban,ML Engineer,24534,0 +37032,Male,57,Masters,9,20,13,75,79,3.0,6,88,Urban,Data Analyst,23272,0 +37033,Female,48,Bachelors,1,65,6,28,95,9.0,1,70,Urban,Manager,71944,0 +37034,Male,24,Diploma,7,22,18,49,78,0.0,7,32,Semi-Urban,Manager,80450,0 +37035,Female,33,Diploma,7,95,40,24,51,7.0,3,16,Urban,ML Engineer,45123,0 +37036,Female,35,Diploma,19,7,30,6,16,4.0,7,54,Urban,HR Executive,116769,0 +37037,Female,32,Bachelors,2,60,66,35,41,1.0,2,13,Rural,Software Engineer,44814,0 +37038,Female,32,Diploma,0,82,2,46,17,1.0,5,34,Urban,HR Executive,142358,0 +37039,Male,58,Diploma,8,59,46,40,4,8.0,6,58,Urban,HR Executive,94592,0 +37040,Female,52,Bachelors,10,17,42,91,0,2.0,4,64,Semi-Urban,Manager,128635,0 +37041,Female,45,Masters,13,91,19,82,87,6.0,1,34,Rural,Data Analyst,85454,0 +37042,Female,38,PhD,1,58,74,75,24,3.0,6,94,Urban,ML Engineer,115366,1 +37043,Female,51,Bachelors,0,82,16,10,58,0.0,4,19,Urban,Software Engineer,63317,0 +37044,Female,32,High School,15,93,76,32,24,4.0,2,95,Rural,Software Engineer,100412,1 +37045,Male,38,Bachelors,15,6,71,32,76,7.0,2,72,Semi-Urban,Data Analyst,86530,0 +37046,Male,26,Masters,1,77,39,60,68,4.0,2,78,Urban,Manager,142661,1 +37047,Male,23,PhD,17,71,76,49,76,1.0,6,49,Rural,Data Analyst,74690,1 +37048,Male,33,Masters,17,43,2,0,45,0.0,6,43,Rural,Software Engineer,85819,0 +37049,Female,26,Bachelors,9,45,76,91,42,1.0,7,97,Semi-Urban,Data Analyst,38234,1 +37050,Male,32,High School,17,65,28,17,2,0.0,1,92,Semi-Urban,Software Engineer,91811,0 +37051,Male,27,Bachelors,12,24,7,76,62,5.0,2,53,Urban,Software Engineer,65831,0 +37052,Female,41,Bachelors,15,25,22,11,53,6.0,7,69,Semi-Urban,Data Analyst,142416,0 +37053,Female,24,High School,7,18,85,61,80,6.0,0,66,Urban,Software Engineer,39063,0 +37054,Female,52,Bachelors,1,38,35,47,14,4.0,3,31,Urban,Manager,149041,0 +37055,Female,32,Bachelors,17,26,94,9,73,6.0,5,14,Urban,Software Engineer,133721,0 +37056,Male,27,Bachelors,16,83,9,7,20,5.0,4,77,Urban,Data Analyst,52448,0 +37057,Female,50,Masters,3,30,59,99,79,2.0,5,54,Urban,ML Engineer,33832,1 +37058,Male,39,Bachelors,11,86,49,21,93,1.0,6,11,Urban,Manager,26782,0 +37059,Other,53,PhD,9,4,51,39,84,1.0,6,10,Urban,Manager,79622,0 +37060,Male,49,Bachelors,13,65,40,89,75,6.0,5,77,Semi-Urban,ML Engineer,44945,1 +37061,Female,32,Masters,17,75,22,13,69,8.0,5,63,Urban,Software Engineer,135439,0 +37062,Female,41,PhD,15,62,69,87,22,0.0,7,53,Semi-Urban,ML Engineer,73699,1 +37063,Male,23,Masters,17,16,13,0,62,4.0,2,49,Rural,Manager,43466,0 +37064,Female,43,High School,13,45,10,25,66,1.0,0,3,Rural,Manager,56337,0 +37065,Female,34,Bachelors,0,19,92,86,70,5.0,5,17,Urban,ML Engineer,43598,0 +37066,Female,43,Bachelors,8,12,73,51,45,4.0,1,21,Urban,Manager,41002,0 +37067,Male,32,Bachelors,19,11,81,33,81,2.0,2,63,Semi-Urban,Software Engineer,142039,0 +37068,Male,38,Diploma,2,86,4,51,40,1.0,4,63,Rural,HR Executive,58819,0 +37069,Male,46,Bachelors,19,50,72,30,63,8.0,4,80,Urban,Software Engineer,102029,0 +37070,Male,53,Masters,16,89,15,69,47,8.0,4,78,Urban,Manager,25686,1 +37071,Male,37,Bachelors,17,95,66,54,16,0.0,7,38,Rural,ML Engineer,123990,1 +37072,Female,39,Bachelors,16,90,85,45,26,1.0,0,45,Rural,ML Engineer,38282,1 +37073,Male,37,Diploma,13,1,48,36,69,3.0,1,73,Rural,Software Engineer,62794,0 +37074,Female,29,Diploma,1,21,56,54,51,9.0,6,64,Rural,HR Executive,55515,0 +37075,Male,32,Bachelors,5,63,23,25,65,6.0,7,67,Semi-Urban,HR Executive,142137,0 +37076,Male,27,PhD,14,65,49,26,37,6.0,2,89,Urban,Data Analyst,120812,0 +37077,Male,22,Masters,3,79,67,24,57,4.0,2,32,Semi-Urban,Manager,60704,0 +37078,Female,23,Bachelors,2,76,85,10,7,0.0,0,91,Semi-Urban,HR Executive,78207,1 +37079,Female,56,Masters,0,18,1,16,7,0.0,3,41,Urban,HR Executive,146781,0 +37080,Male,29,Bachelors,6,43,60,13,16,8.0,3,93,Urban,Data Analyst,62556,0 +37081,Male,48,Diploma,6,42,19,21,44,0.0,4,19,Urban,Manager,38184,0 +37082,Male,25,Masters,18,21,8,96,64,4.0,1,55,Urban,Software Engineer,66590,0 +37083,Female,43,Masters,7,95,68,6,94,4.0,7,61,Rural,Manager,138203,0 +37084,Female,26,High School,13,4,30,54,57,8.0,4,31,Urban,ML Engineer,97742,0 +37085,Female,48,Bachelors,1,97,94,13,32,1.0,4,5,Urban,Manager,126831,0 +37086,Male,55,Bachelors,15,7,39,11,4,2.0,7,40,Urban,Software Engineer,72054,0 +37087,Male,53,Bachelors,3,81,54,80,74,4.0,6,14,Urban,ML Engineer,126123,0 +37088,Male,42,Diploma,8,30,11,28,58,0.0,3,11,Urban,Software Engineer,38851,0 +37089,Male,24,Bachelors,17,39,73,85,66,8.0,3,41,Urban,Manager,141273,1 +37090,Male,47,Bachelors,12,91,51,96,93,7.0,6,34,Urban,HR Executive,87777,1 +37091,Male,56,Masters,10,77,77,5,74,7.0,1,59,Urban,ML Engineer,40649,0 +37092,Male,57,Bachelors,2,95,29,29,38,3.0,3,67,Urban,Software Engineer,124889,0 +37093,Male,40,PhD,3,58,67,97,14,0.0,0,56,Semi-Urban,ML Engineer,37462,1 +37094,Male,52,Diploma,6,10,85,19,71,9.0,7,80,Urban,Software Engineer,46986,0 +37095,Male,55,Bachelors,18,98,92,96,75,7.0,2,63,Rural,ML Engineer,128117,1 +37096,Female,35,Masters,16,1,29,22,61,1.0,6,68,Urban,ML Engineer,70583,0 +37097,Female,53,Masters,18,19,46,37,6,8.0,1,42,Semi-Urban,ML Engineer,77289,0 +37098,Male,40,Diploma,15,93,21,74,91,1.0,4,40,Urban,HR Executive,144664,0 +37099,Female,43,High School,15,23,67,2,21,8.0,6,17,Rural,HR Executive,133508,0 +37100,Female,54,Bachelors,1,35,71,16,48,0.0,5,77,Urban,Manager,113596,0 +37101,Male,42,Bachelors,12,64,35,77,49,0.0,2,97,Urban,Data Analyst,138186,1 +37102,Male,28,High School,19,4,87,52,59,5.0,5,89,Urban,Data Analyst,33178,0 +37103,Female,29,Diploma,4,56,95,63,55,3.0,4,70,Urban,HR Executive,61416,1 +37104,Female,23,Diploma,1,87,78,75,82,3.0,5,51,Semi-Urban,HR Executive,52903,1 +37105,Male,46,Bachelors,14,77,70,56,89,0.0,0,28,Urban,HR Executive,120565,0 +37106,Male,39,Diploma,8,59,82,31,9,8.0,7,16,Rural,Manager,110987,0 +37107,Female,33,Masters,9,40,53,77,78,6.0,1,21,Semi-Urban,Manager,112551,0 +37108,Male,50,Masters,8,2,4,30,59,0.0,1,73,Urban,ML Engineer,85396,0 +37109,Female,59,Masters,16,8,4,37,71,5.0,3,13,Urban,Manager,108114,0 +37110,Male,48,Masters,3,48,0,36,93,5.0,3,41,Rural,ML Engineer,81033,0 +37111,Female,43,Bachelors,13,97,10,54,85,9.0,5,54,Urban,Manager,105144,0 +37112,Male,55,Bachelors,6,19,0,22,47,6.0,3,99,Rural,Data Analyst,79322,0 +37113,Male,55,Masters,3,17,46,41,79,6.0,7,90,Semi-Urban,Software Engineer,68922,0 +37114,Other,45,Masters,12,4,58,9,24,8.0,7,54,Semi-Urban,HR Executive,47465,0 +37115,Male,49,Bachelors,13,70,40,33,9,2.0,6,82,Urban,Software Engineer,93590,0 +37116,Male,38,Masters,18,52,97,47,84,6.0,1,8,Rural,Software Engineer,125440,0 +37117,Female,54,PhD,12,59,73,97,56,6.0,7,81,Rural,HR Executive,23898,1 +37118,Male,31,High School,16,30,11,99,84,4.0,6,75,Rural,ML Engineer,144395,0 +37119,Male,54,Bachelors,9,90,44,28,72,9.0,6,46,Rural,ML Engineer,149133,0 +37120,Male,27,Diploma,11,6,35,72,22,5.0,4,64,Rural,Data Analyst,28476,0 +37121,Female,35,Bachelors,10,47,3,60,16,1.0,0,87,Rural,Manager,74802,0 +37122,Female,40,PhD,17,90,64,93,6,0.0,5,14,Urban,Software Engineer,47000,1 +37123,Female,58,Diploma,15,76,80,4,19,7.0,7,29,Urban,ML Engineer,51219,0 +37124,Male,34,High School,15,5,33,28,49,0.0,2,73,Semi-Urban,ML Engineer,131553,0 +37125,Male,30,High School,7,76,26,53,60,9.0,2,62,Rural,HR Executive,89797,0 +37126,Male,48,Bachelors,5,71,73,73,71,2.0,7,67,Urban,Software Engineer,137484,1 +37127,Female,36,Bachelors,3,24,35,10,90,8.0,7,16,Urban,Data Analyst,43379,0 +37128,Female,43,Diploma,16,62,78,45,91,9.0,6,39,Urban,Software Engineer,144737,0 +37129,Female,51,Bachelors,9,51,74,67,70,5.0,3,92,Semi-Urban,ML Engineer,36696,1 +37130,Other,51,High School,14,36,72,77,41,0.0,5,21,Urban,Manager,25536,0 +37131,Male,44,Diploma,9,11,90,59,1,4.0,3,60,Urban,ML Engineer,24629,0 +37132,Male,21,Masters,3,98,92,1,81,1.0,1,93,Semi-Urban,ML Engineer,75870,1 +37133,Female,26,PhD,19,42,99,1,77,5.0,7,48,Urban,HR Executive,143133,0 +37134,Male,28,PhD,0,67,42,5,13,7.0,5,12,Urban,Manager,135715,0 +37135,Male,50,Diploma,2,90,13,44,82,1.0,7,57,Rural,Software Engineer,80110,0 +37136,Female,52,Diploma,4,49,63,94,26,9.0,3,9,Rural,Data Analyst,79804,0 +37137,Male,37,Diploma,0,19,42,61,36,1.0,2,95,Rural,ML Engineer,109733,0 +37138,Male,58,Masters,4,58,24,68,56,7.0,1,17,Urban,Manager,87431,0 +37139,Male,56,Masters,4,75,71,49,84,3.0,4,97,Urban,ML Engineer,41725,1 +37140,Female,28,Diploma,0,90,39,22,82,7.0,2,70,Semi-Urban,ML Engineer,128019,0 +37141,Male,46,Bachelors,14,43,59,45,32,4.0,4,91,Rural,Data Analyst,116416,1 +37142,Female,45,Diploma,17,45,71,54,42,3.0,0,6,Semi-Urban,ML Engineer,51105,0 +37143,Male,55,Bachelors,8,36,2,31,90,9.0,5,87,Urban,Manager,81889,0 +37144,Female,41,Masters,5,20,29,62,40,7.0,0,98,Rural,ML Engineer,79218,0 +37145,Male,25,Bachelors,4,60,85,19,61,5.0,5,84,Urban,Manager,76888,1 +37146,Female,21,Masters,7,14,96,44,34,5.0,7,11,Rural,ML Engineer,111127,0 +37147,Male,30,Bachelors,8,61,73,27,57,8.0,3,98,Urban,Manager,145568,1 +37148,Other,23,Bachelors,3,73,68,86,79,9.0,0,92,Urban,Data Analyst,131863,1 +37149,Female,53,PhD,7,77,32,50,36,5.0,7,82,Urban,Data Analyst,111861,1 +37150,Male,43,Masters,13,26,58,59,3,0.0,7,14,Semi-Urban,Manager,102734,0 +37151,Male,49,High School,12,95,87,83,73,4.0,0,38,Semi-Urban,HR Executive,20984,1 +37152,Male,55,Diploma,12,98,2,92,45,8.0,3,0,Rural,Software Engineer,82955,0 +37153,Female,50,Bachelors,16,24,54,67,8,9.0,6,28,Rural,Data Analyst,144540,0 +37154,Male,26,Bachelors,12,13,87,79,84,4.0,1,62,Rural,HR Executive,65364,1 +37155,Male,53,Bachelors,11,16,53,26,10,3.0,3,57,Semi-Urban,Manager,40375,0 +37156,Female,53,Masters,9,53,59,26,99,2.0,1,30,Urban,HR Executive,148656,0 +37157,Female,52,Masters,9,69,65,50,15,6.0,7,64,Urban,Manager,112594,1 +37158,Male,54,Bachelors,1,55,84,73,61,9.0,4,93,Semi-Urban,Data Analyst,31783,1 +37159,Male,48,Diploma,3,9,53,53,66,4.0,4,7,Semi-Urban,Data Analyst,76309,0 +37160,Male,26,Masters,0,6,43,47,24,2.0,0,53,Urban,ML Engineer,93603,0 +37161,Male,28,Bachelors,15,94,20,94,29,7.0,5,71,Urban,HR Executive,118074,1 +37162,Male,53,Bachelors,0,34,56,28,2,1.0,6,33,Rural,Software Engineer,70713,0 +37163,Female,32,Bachelors,15,87,84,2,86,2.0,5,28,Urban,HR Executive,85055,0 +37164,Male,57,Masters,6,3,0,76,27,3.0,6,13,Semi-Urban,HR Executive,133796,0 +37165,Male,56,High School,14,89,19,94,9,6.0,7,57,Semi-Urban,Manager,90982,1 +37166,Male,25,Bachelors,11,18,6,99,16,3.0,1,91,Urban,ML Engineer,26564,0 +37167,Other,48,Masters,1,49,2,76,26,3.0,5,81,Urban,Software Engineer,97914,0 +37168,Male,50,Bachelors,17,25,24,4,55,3.0,0,1,Semi-Urban,Software Engineer,42002,0 +37169,Other,22,Masters,2,4,12,70,28,7.0,6,11,Urban,Software Engineer,106342,0 +37170,Male,53,Bachelors,8,36,87,58,90,0.0,1,53,Urban,Manager,95280,0 +37171,Male,23,Bachelors,8,26,50,62,22,7.0,3,89,Urban,HR Executive,51382,0 +37172,Female,52,Diploma,3,33,81,71,57,8.0,5,56,Urban,Data Analyst,72351,1 +37173,Male,30,Masters,6,54,43,18,85,2.0,6,57,Urban,Data Analyst,100184,0 +37174,Female,35,PhD,3,21,23,48,77,1.0,1,91,Semi-Urban,ML Engineer,112648,0 +37175,Female,26,High School,0,51,9,90,20,2.0,7,7,Urban,Manager,76829,0 +37176,Male,48,Bachelors,10,65,80,87,83,8.0,2,8,Rural,Data Analyst,111204,1 +37177,Female,42,Bachelors,3,1,81,82,19,4.0,7,30,Semi-Urban,Manager,95767,0 +37178,Female,58,Diploma,12,65,76,30,45,4.0,5,96,Rural,Software Engineer,103658,1 +37179,Female,46,Bachelors,15,6,28,50,75,2.0,6,10,Rural,Data Analyst,123696,0 +37180,Male,37,Bachelors,5,70,24,25,66,2.0,2,99,Semi-Urban,Software Engineer,93565,0 +37181,Male,44,Bachelors,15,39,41,52,97,2.0,0,21,Urban,ML Engineer,32607,0 +37182,Male,31,Bachelors,10,27,86,79,13,3.0,1,56,Semi-Urban,Data Analyst,26717,1 +37183,Other,40,PhD,9,96,72,48,23,8.0,7,43,Semi-Urban,Data Analyst,24486,1 +37184,Male,30,Masters,0,27,23,97,70,5.0,6,77,Urban,Data Analyst,61283,0 +37185,Male,43,Bachelors,13,68,21,65,19,1.0,5,10,Urban,Data Analyst,149719,0 +37186,Male,40,Diploma,15,24,50,76,61,3.0,4,62,Urban,HR Executive,60298,0 +37187,Female,51,High School,18,73,75,92,85,0.0,7,93,Semi-Urban,Software Engineer,27720,1 +37188,Male,53,High School,18,29,8,85,14,5.0,4,71,Urban,HR Executive,79016,0 +37189,Male,22,Bachelors,18,94,34,96,3,6.0,6,27,Urban,ML Engineer,47275,1 +37190,Female,54,Diploma,6,59,19,4,59,5.0,6,46,Urban,ML Engineer,121426,0 +37191,Male,25,Bachelors,2,63,72,14,88,7.0,0,2,Urban,Data Analyst,142636,0 +37192,Male,54,High School,9,7,60,73,90,7.0,7,93,Urban,HR Executive,117164,0 +37193,Male,29,Masters,16,77,90,70,40,6.0,1,54,Rural,ML Engineer,48365,1 +37194,Male,37,Diploma,16,34,90,16,48,4.0,7,75,Urban,ML Engineer,34750,0 +37195,Male,45,Bachelors,2,36,55,95,22,8.0,7,95,Rural,ML Engineer,132447,1 +37196,Male,59,Masters,17,52,9,14,46,0.0,2,60,Urban,Software Engineer,29527,0 +37197,Male,34,Diploma,10,65,8,81,62,1.0,7,63,Semi-Urban,HR Executive,94329,0 +37198,Female,45,Masters,13,81,63,48,6,6.0,6,38,Urban,Data Analyst,113518,0 +37199,Male,59,Masters,17,91,87,43,1,2.0,5,46,Urban,Manager,77300,1 +37200,Male,52,Masters,2,83,31,30,58,0.0,1,39,Urban,Manager,30713,0 +37201,Male,47,Bachelors,5,66,24,94,66,9.0,2,95,Urban,HR Executive,112073,1 +37202,Male,30,High School,7,79,13,59,11,0.0,6,70,Semi-Urban,Data Analyst,87316,0 +37203,Female,41,Bachelors,13,5,16,37,17,5.0,4,84,Urban,HR Executive,38485,0 +37204,Male,36,PhD,12,42,23,23,97,6.0,2,7,Urban,Data Analyst,90983,0 +37205,Male,28,Bachelors,8,59,76,69,92,1.0,0,89,Urban,Data Analyst,26533,1 +37206,Female,52,Bachelors,6,62,23,70,45,2.0,2,63,Rural,Software Engineer,44202,0 +37207,Female,53,Diploma,17,11,31,64,41,7.0,6,80,Urban,Data Analyst,60988,0 +37208,Female,54,Diploma,9,17,69,87,56,0.0,3,1,Semi-Urban,ML Engineer,43678,0 +37209,Female,44,Bachelors,10,61,64,2,33,7.0,5,41,Urban,Manager,124489,0 +37210,Male,35,Bachelors,6,32,4,43,65,8.0,3,89,Semi-Urban,Data Analyst,21233,0 +37211,Other,45,Bachelors,19,86,21,24,8,6.0,0,46,Rural,ML Engineer,66880,0 +37212,Female,47,Bachelors,9,16,49,85,93,5.0,6,6,Urban,ML Engineer,131455,0 +37213,Male,45,Bachelors,12,19,45,54,91,1.0,4,72,Urban,Data Analyst,47830,0 +37214,Female,38,Diploma,7,11,91,13,96,2.0,3,68,Urban,ML Engineer,149437,0 +37215,Male,40,Masters,17,82,67,50,55,4.0,4,33,Urban,Manager,129217,0 +37216,Female,56,Masters,8,96,23,25,39,5.0,6,80,Urban,Data Analyst,106150,0 +37217,Male,48,Masters,18,12,5,3,67,5.0,3,7,Urban,Software Engineer,33547,0 +37218,Male,34,High School,17,80,5,16,82,2.0,2,78,Urban,Data Analyst,120619,0 +37219,Male,58,High School,8,97,34,36,39,4.0,3,47,Semi-Urban,Data Analyst,38075,0 +37220,Male,31,Bachelors,3,41,99,51,7,4.0,0,70,Urban,ML Engineer,79937,1 +37221,Male,48,High School,5,82,0,24,23,4.0,1,12,Semi-Urban,Data Analyst,20013,0 +37222,Male,35,Masters,12,93,39,58,18,5.0,4,18,Urban,Manager,118964,0 +37223,Female,50,Masters,11,35,98,60,24,2.0,3,8,Urban,HR Executive,125327,0 +37224,Female,25,Bachelors,0,44,51,45,23,4.0,5,70,Rural,Manager,42281,0 +37225,Male,24,High School,7,24,80,63,26,3.0,4,50,Semi-Urban,ML Engineer,59550,0 +37226,Female,27,High School,3,0,48,12,80,7.0,3,11,Urban,HR Executive,31513,0 +37227,Male,59,Bachelors,5,90,91,3,22,3.0,1,25,Semi-Urban,Data Analyst,108034,0 +37228,Female,55,Bachelors,6,80,85,22,29,3.0,3,93,Rural,ML Engineer,135889,1 +37229,Male,23,Diploma,8,13,63,93,82,7.0,3,19,Urban,ML Engineer,105807,0 +37230,Female,48,Bachelors,10,20,12,87,50,4.0,3,15,Urban,Data Analyst,98998,0 +37231,Female,57,Diploma,16,12,72,77,14,7.0,0,8,Rural,Data Analyst,20653,0 +37232,Male,24,Masters,8,63,30,25,85,9.0,4,5,Urban,ML Engineer,93108,0 +37233,Male,31,Diploma,15,72,79,0,78,9.0,1,69,Rural,ML Engineer,53047,0 +37234,Other,24,Bachelors,0,49,41,43,80,7.0,1,66,Urban,Software Engineer,138004,0 +37235,Female,24,Bachelors,10,72,96,85,13,1.0,7,1,Rural,ML Engineer,111104,1 +37236,Male,46,Diploma,6,18,16,84,43,9.0,3,84,Urban,Manager,76124,0 +37237,Male,46,High School,19,91,66,81,90,7.0,6,21,Urban,ML Engineer,44329,1 +37238,Female,29,Bachelors,0,9,95,75,3,4.0,7,71,Urban,Data Analyst,118026,1 +37239,Other,33,Bachelors,1,63,60,3,60,3.0,2,14,Semi-Urban,Software Engineer,95587,0 +37240,Male,35,Masters,11,78,43,67,44,5.0,5,31,Urban,Data Analyst,82720,0 +37241,Female,47,Masters,4,57,20,48,66,1.0,3,19,Urban,Data Analyst,36718,0 +37242,Male,29,Bachelors,1,40,70,22,73,5.0,3,14,Urban,ML Engineer,102433,0 +37243,Other,38,High School,14,96,90,40,81,0.0,0,76,Semi-Urban,Data Analyst,125499,1 +37244,Female,52,Bachelors,14,52,44,64,81,0.0,0,71,Urban,Manager,118180,0 +37245,Male,30,Diploma,9,52,89,65,45,6.0,5,96,Urban,Data Analyst,58759,1 +37246,Male,58,Bachelors,13,9,26,4,77,7.0,1,14,Rural,Manager,82399,0 +37247,Female,56,High School,16,95,66,23,66,1.0,2,18,Urban,Manager,62160,0 +37248,Male,58,High School,10,44,14,59,86,4.0,6,57,Urban,Data Analyst,90126,0 +37249,Female,30,Bachelors,6,46,76,37,68,1.0,7,44,Rural,HR Executive,25166,0 +37250,Female,27,Bachelors,7,37,44,46,61,7.0,6,81,Rural,ML Engineer,73078,0 +37251,Male,35,Bachelors,10,98,21,44,78,4.0,1,81,Urban,ML Engineer,63047,1 +37252,Female,31,Masters,4,23,14,62,58,7.0,6,90,Urban,Manager,107657,0 +37253,Male,30,Diploma,10,41,25,76,65,7.0,2,22,Urban,Data Analyst,108566,0 +37254,Female,25,Masters,11,53,44,65,89,4.0,3,73,Urban,ML Engineer,125041,0 +37255,Female,39,High School,8,12,85,9,78,0.0,6,31,Urban,Data Analyst,22324,0 +37256,Female,52,Bachelors,15,87,65,7,76,2.0,3,87,Urban,Software Engineer,145983,1 +37257,Male,33,Bachelors,13,62,90,13,38,3.0,7,17,Urban,Data Analyst,48471,0 +37258,Male,28,Bachelors,5,49,57,14,68,6.0,7,72,Rural,Manager,127098,0 +37259,Male,31,Bachelors,13,72,82,26,96,6.0,5,88,Urban,Manager,43202,1 +37260,Male,22,Bachelors,3,63,5,18,8,5.0,2,9,Urban,HR Executive,87952,0 +37261,Male,32,Bachelors,0,65,94,41,73,1.0,5,34,Rural,ML Engineer,42608,0 +37262,Female,37,Diploma,17,85,12,81,43,7.0,5,76,Urban,Software Engineer,90685,1 +37263,Male,30,Bachelors,2,83,71,16,31,8.0,0,53,Urban,Manager,145553,0 +37264,Male,32,Diploma,8,52,44,90,88,9.0,2,11,Semi-Urban,Data Analyst,93606,0 +37265,Male,59,Bachelors,6,3,14,1,71,4.0,5,23,Semi-Urban,Data Analyst,29624,0 +37266,Male,57,High School,3,43,1,76,74,9.0,5,12,Rural,Software Engineer,64275,0 +37267,Female,56,Diploma,16,57,47,60,47,7.0,2,81,Urban,HR Executive,33363,1 +37268,Male,58,Bachelors,11,43,1,5,66,0.0,4,95,Urban,Manager,98736,0 +37269,Male,37,High School,8,41,43,61,67,9.0,2,56,Urban,Manager,47990,0 +37270,Male,56,Diploma,14,35,67,52,76,5.0,5,3,Semi-Urban,Data Analyst,23483,0 +37271,Male,52,High School,2,93,25,48,21,9.0,7,58,Urban,Data Analyst,116981,0 +37272,Male,41,Masters,17,33,68,3,23,7.0,0,78,Rural,Software Engineer,85189,0 +37273,Female,44,Bachelors,12,83,95,59,28,6.0,6,70,Urban,ML Engineer,53684,1 +37274,Female,41,PhD,11,99,33,24,70,6.0,1,93,Semi-Urban,Data Analyst,44810,1 +37275,Male,25,Bachelors,10,4,32,5,3,3.0,1,52,Urban,HR Executive,98553,0 +37276,Male,52,Masters,4,31,40,75,78,7.0,1,29,Urban,HR Executive,43534,0 +37277,Female,35,Bachelors,11,85,61,18,46,7.0,4,79,Semi-Urban,Data Analyst,119952,1 +37278,Male,51,High School,1,17,14,31,62,6.0,2,41,Rural,Data Analyst,139656,0 +37279,Male,39,Diploma,12,10,15,95,49,9.0,6,91,Urban,Data Analyst,90521,0 +37280,Male,30,Masters,0,1,41,94,54,6.0,0,56,Urban,Manager,115793,0 +37281,Female,29,PhD,5,70,36,7,35,3.0,4,47,Semi-Urban,Manager,143595,0 +37282,Other,31,Masters,2,63,71,18,9,2.0,4,3,Urban,Manager,28371,0 +37283,Male,44,Masters,8,2,43,28,51,0.0,0,76,Urban,ML Engineer,47058,0 +37284,Male,24,Diploma,6,36,67,24,70,1.0,4,18,Semi-Urban,Software Engineer,83029,0 +37285,Female,53,Bachelors,6,58,9,7,45,5.0,7,36,Urban,Data Analyst,125190,0 +37286,Other,51,High School,3,23,69,0,27,9.0,2,81,Urban,HR Executive,58829,0 +37287,Female,44,Bachelors,1,82,6,7,70,2.0,7,56,Urban,HR Executive,54797,0 +37288,Female,22,Diploma,15,63,72,84,12,2.0,2,40,Urban,ML Engineer,143490,1 +37289,Female,26,Bachelors,6,20,51,69,5,9.0,2,90,Rural,Software Engineer,76637,0 +37290,Male,53,Bachelors,15,48,19,91,12,2.0,7,82,Semi-Urban,Software Engineer,98219,1 +37291,Male,23,Diploma,3,73,30,78,32,3.0,7,18,Semi-Urban,Data Analyst,108353,0 +37292,Male,56,Diploma,0,95,62,77,10,3.0,3,83,Urban,Manager,121189,1 +37293,Male,53,Bachelors,19,69,41,25,25,9.0,6,53,Semi-Urban,Data Analyst,147437,0 +37294,Female,24,Bachelors,13,98,87,70,31,0.0,1,41,Urban,Data Analyst,135458,1 +37295,Female,58,Diploma,13,99,88,18,66,3.0,1,23,Urban,Software Engineer,45324,0 +37296,Female,44,Bachelors,3,66,9,48,39,5.0,5,11,Semi-Urban,Manager,82565,0 +37297,Female,27,Diploma,12,34,47,56,56,4.0,7,50,Semi-Urban,ML Engineer,29587,0 +37298,Male,26,High School,7,64,9,43,76,7.0,2,60,Rural,Data Analyst,23067,0 +37299,Female,28,Bachelors,15,4,53,14,88,7.0,2,51,Urban,Data Analyst,81576,0 +37300,Male,31,Bachelors,10,20,63,24,6,1.0,5,70,Rural,Software Engineer,74480,0 +37301,Female,25,Bachelors,7,56,57,66,41,6.0,3,38,Semi-Urban,ML Engineer,49093,0 +37302,Male,32,Bachelors,0,94,39,5,20,9.0,2,95,Urban,HR Executive,94042,0 +37303,Male,51,High School,8,92,67,63,23,3.0,6,49,Rural,Manager,28545,1 +37304,Male,40,Masters,13,29,46,41,81,7.0,4,34,Urban,Data Analyst,116068,0 +37305,Male,35,Masters,17,49,18,39,37,9.0,1,26,Urban,Software Engineer,63670,0 +37306,Male,21,Diploma,6,50,44,42,41,3.0,1,4,Semi-Urban,ML Engineer,64315,0 +37307,Male,54,High School,11,32,83,6,4,3.0,5,11,Rural,HR Executive,108063,0 +37308,Male,43,Diploma,18,32,92,6,13,4.0,2,75,Rural,ML Engineer,97934,0 +37309,Female,46,Masters,13,61,32,63,84,2.0,7,11,Rural,ML Engineer,131926,0 +37310,Female,38,High School,9,14,68,19,72,6.0,6,97,Urban,HR Executive,43871,0 +37311,Female,26,Diploma,16,17,41,41,58,2.0,4,23,Semi-Urban,ML Engineer,81921,0 +37312,Female,59,Bachelors,4,5,75,99,52,2.0,2,90,Semi-Urban,Data Analyst,73389,1 +37313,Male,43,Masters,8,2,20,32,52,0.0,4,11,Urban,ML Engineer,52133,0 +37314,Female,44,High School,3,26,6,6,50,4.0,2,10,Rural,Software Engineer,62109,0 +37315,Male,26,Diploma,10,70,58,22,35,5.0,7,53,Semi-Urban,HR Executive,120286,0 +37316,Male,38,Diploma,1,8,97,1,20,9.0,7,42,Urban,Data Analyst,29867,0 +37317,Female,40,Bachelors,1,90,93,73,12,8.0,6,8,Rural,ML Engineer,83851,1 +37318,Male,37,Bachelors,6,88,70,52,4,0.0,2,43,Rural,HR Executive,128185,1 +37319,Male,56,High School,14,8,15,59,9,2.0,2,27,Urban,Data Analyst,106770,0 +37320,Female,23,High School,3,40,67,34,46,9.0,5,9,Urban,Software Engineer,135070,0 +37321,Female,46,High School,14,68,94,30,93,6.0,3,80,Urban,ML Engineer,65757,1 +37322,Female,53,Bachelors,6,27,24,26,98,6.0,0,61,Urban,ML Engineer,119573,0 +37323,Male,37,High School,16,93,24,31,63,9.0,3,70,Rural,Manager,86099,0 +37324,Female,46,Diploma,12,12,84,10,47,3.0,3,49,Urban,Software Engineer,48982,0 +37325,Female,33,Masters,19,98,58,0,54,3.0,7,64,Semi-Urban,Software Engineer,58502,0 +37326,Female,43,PhD,12,3,18,43,3,2.0,5,5,Urban,HR Executive,51387,0 +37327,Female,50,Bachelors,2,34,11,26,17,0.0,6,16,Semi-Urban,HR Executive,71213,0 +37328,Male,24,Diploma,12,69,21,60,95,0.0,0,96,Urban,Software Engineer,24754,1 +37329,Male,28,Bachelors,0,34,83,9,33,7.0,3,80,Semi-Urban,ML Engineer,102884,0 +37330,Female,51,Bachelors,1,55,3,39,88,0.0,7,69,Urban,Data Analyst,83477,0 +37331,Female,28,Bachelors,1,9,50,3,88,1.0,3,1,Urban,Data Analyst,87772,0 +37332,Male,24,Bachelors,9,17,17,4,87,4.0,6,99,Semi-Urban,Manager,115085,0 +37333,Female,45,Diploma,16,46,46,78,72,3.0,5,57,Semi-Urban,Data Analyst,113152,0 +37334,Male,35,High School,17,45,21,40,28,3.0,1,34,Rural,HR Executive,21819,0 +37335,Male,54,Diploma,13,56,13,78,55,4.0,4,4,Urban,ML Engineer,39566,0 +37336,Male,53,Diploma,14,34,57,91,28,2.0,4,40,Semi-Urban,Software Engineer,87216,0 +37337,Male,47,Masters,8,20,62,99,3,5.0,2,53,Rural,Data Analyst,133351,0 +37338,Male,38,High School,13,99,16,52,60,2.0,3,87,Semi-Urban,Manager,109937,1 +37339,Female,47,PhD,18,41,95,65,99,7.0,7,54,Urban,HR Executive,75226,1 +37340,Male,35,Bachelors,18,70,85,10,75,5.0,1,37,Semi-Urban,Software Engineer,88374,0 +37341,Male,24,Bachelors,8,6,75,46,62,0.0,0,94,Urban,Manager,62292,0 +37342,Other,26,High School,14,19,93,69,18,5.0,3,38,Urban,ML Engineer,115317,0 +37343,Male,48,High School,2,59,38,65,92,0.0,0,58,Urban,Data Analyst,25602,0 +37344,Female,34,Diploma,19,31,58,32,36,0.0,3,72,Urban,Data Analyst,105744,0 +37345,Female,25,Bachelors,12,83,69,50,97,4.0,4,93,Urban,HR Executive,125937,1 +37346,Male,26,Masters,19,4,75,44,3,2.0,6,85,Semi-Urban,Manager,96306,0 +37347,Female,35,Masters,0,11,4,79,85,9.0,3,75,Rural,Data Analyst,109880,0 +37348,Other,53,Diploma,12,62,48,94,74,5.0,0,60,Urban,Software Engineer,61118,1 +37349,Female,25,Diploma,2,87,59,58,48,5.0,6,17,Urban,Manager,142168,0 +37350,Male,58,Masters,15,43,14,40,90,1.0,6,28,Semi-Urban,Software Engineer,99090,0 +37351,Male,36,Masters,2,53,48,4,39,1.0,2,47,Urban,ML Engineer,129413,0 +37352,Male,21,Masters,17,20,83,48,60,8.0,3,11,Rural,ML Engineer,91990,0 +37353,Female,27,Bachelors,12,32,82,81,96,6.0,3,30,Urban,Software Engineer,62542,0 +37354,Female,24,Bachelors,16,68,52,88,80,4.0,4,54,Urban,HR Executive,130218,1 +37355,Female,42,PhD,19,43,80,86,76,2.0,4,91,Urban,Manager,115889,1 +37356,Male,50,Bachelors,11,60,15,68,39,4.0,7,85,Rural,Software Engineer,25797,0 +37357,Male,33,Bachelors,4,38,69,53,53,6.0,2,38,Rural,Data Analyst,42550,0 +37358,Male,47,Diploma,14,17,54,46,7,8.0,7,86,Urban,HR Executive,39768,0 +37359,Male,50,Diploma,18,4,1,28,66,8.0,5,86,Urban,Manager,115944,0 +37360,Female,32,Masters,7,56,71,51,24,2.0,4,83,Rural,Manager,29522,1 +37361,Male,24,PhD,5,58,98,59,69,9.0,3,3,Urban,ML Engineer,125226,0 +37362,Male,31,Diploma,9,4,40,75,73,6.0,6,39,Urban,ML Engineer,49019,0 +37363,Female,37,Bachelors,15,40,44,74,10,4.0,3,44,Urban,Manager,85406,0 +37364,Male,29,Diploma,1,81,67,86,56,2.0,4,67,Semi-Urban,HR Executive,93055,1 +37365,Female,35,Bachelors,6,88,79,33,14,5.0,7,35,Urban,Manager,118315,0 +37366,Male,25,Bachelors,6,96,69,69,82,1.0,7,30,Urban,Software Engineer,121357,1 +37367,Female,27,Masters,8,11,55,23,72,1.0,7,99,Semi-Urban,ML Engineer,55585,0 +37368,Male,30,High School,13,13,99,71,43,7.0,3,6,Urban,HR Executive,69813,0 +37369,Male,51,Masters,17,0,94,20,44,3.0,7,68,Semi-Urban,ML Engineer,40600,0 +37370,Female,24,Bachelors,17,9,23,43,18,3.0,2,7,Urban,HR Executive,109672,0 +37371,Female,33,Masters,6,71,86,82,75,9.0,5,6,Semi-Urban,Software Engineer,66214,1 +37372,Male,52,Masters,16,18,76,0,95,5.0,3,81,Rural,HR Executive,80455,0 +37373,Female,22,High School,17,21,24,24,94,8.0,3,25,Urban,HR Executive,50480,0 +37374,Other,53,Masters,14,68,82,65,41,8.0,4,66,Urban,Software Engineer,75925,1 +37375,Male,27,Diploma,3,87,30,67,3,5.0,5,85,Rural,ML Engineer,66189,1 +37376,Female,38,Bachelors,12,41,4,38,55,1.0,6,77,Urban,Manager,20022,0 +37377,Male,22,Diploma,1,74,87,7,49,5.0,1,26,Semi-Urban,Software Engineer,58190,0 +37378,Male,58,Diploma,8,41,3,21,96,2.0,0,70,Semi-Urban,Software Engineer,90349,0 +37379,Male,57,Bachelors,0,3,92,19,28,5.0,7,9,Rural,Software Engineer,119367,0 +37380,Male,57,Masters,11,89,41,55,58,8.0,7,22,Urban,Data Analyst,130607,0 +37381,Male,32,Bachelors,18,9,43,79,34,5.0,1,10,Semi-Urban,Data Analyst,67105,0 +37382,Male,27,Bachelors,12,13,75,82,86,5.0,7,76,Urban,Software Engineer,89507,1 +37383,Male,32,Masters,5,81,51,39,24,9.0,5,6,Semi-Urban,Manager,118253,0 +37384,Female,34,Masters,13,51,91,26,81,8.0,2,92,Urban,ML Engineer,55661,1 +37385,Female,44,Bachelors,3,62,19,50,25,9.0,2,10,Urban,HR Executive,38432,0 +37386,Male,53,High School,15,13,49,52,33,3.0,0,73,Urban,ML Engineer,24082,0 +37387,Male,30,Diploma,11,77,18,49,74,1.0,0,13,Urban,HR Executive,111816,0 +37388,Female,26,Diploma,7,41,81,88,55,3.0,3,73,Urban,Manager,48557,1 +37389,Male,48,Masters,15,6,66,54,0,1.0,1,1,Urban,HR Executive,33225,0 +37390,Male,21,Masters,4,73,28,48,27,0.0,2,76,Rural,Software Engineer,91176,0 +37391,Male,58,PhD,2,74,3,11,93,8.0,7,65,Rural,HR Executive,131155,0 +37392,Female,58,Bachelors,5,89,5,87,91,2.0,4,37,Semi-Urban,ML Engineer,31352,0 +37393,Male,23,Bachelors,14,9,98,67,11,4.0,6,93,Urban,Manager,95241,1 +37394,Male,49,Bachelors,11,79,63,11,23,2.0,2,57,Semi-Urban,HR Executive,74630,0 +37395,Female,58,High School,7,73,92,29,71,6.0,4,71,Urban,Manager,112457,1 +37396,Male,56,Masters,6,50,36,19,51,2.0,5,88,Semi-Urban,Software Engineer,78613,0 +37397,Male,26,PhD,17,11,11,89,90,2.0,2,71,Urban,ML Engineer,57941,0 +37398,Female,24,Bachelors,6,19,27,85,84,5.0,4,33,Urban,Data Analyst,28784,0 +37399,Male,35,Diploma,8,37,20,5,36,9.0,6,70,Rural,ML Engineer,140516,0 +37400,Female,47,Bachelors,5,63,98,29,32,7.0,7,35,Rural,Data Analyst,74988,0 +37401,Male,32,Diploma,0,60,48,71,97,0.0,4,38,Semi-Urban,ML Engineer,66899,0 +37402,Male,46,Bachelors,7,92,16,9,44,1.0,5,3,Urban,Software Engineer,45261,0 +37403,Male,47,Bachelors,2,35,98,94,43,0.0,6,40,Urban,ML Engineer,115995,1 +37404,Female,36,Bachelors,16,10,69,33,34,2.0,2,5,Urban,ML Engineer,149602,0 +37405,Male,57,Bachelors,15,31,26,46,84,5.0,3,71,Urban,HR Executive,113326,0 +37406,Male,34,Bachelors,13,27,49,21,84,0.0,2,79,Urban,ML Engineer,65746,0 +37407,Other,52,Masters,12,73,22,29,55,1.0,1,76,Rural,HR Executive,65242,0 +37408,Female,40,High School,9,59,78,18,45,1.0,1,30,Urban,ML Engineer,59775,0 +37409,Male,33,Diploma,16,30,24,19,93,2.0,6,17,Semi-Urban,Manager,32688,0 +37410,Male,57,Bachelors,8,25,63,16,52,7.0,3,27,Urban,HR Executive,36704,0 +37411,Male,57,PhD,0,36,19,51,52,9.0,1,43,Urban,Software Engineer,45763,0 +37412,Male,55,High School,10,77,37,42,70,8.0,3,60,Urban,HR Executive,39438,0 +37413,Other,59,High School,18,18,22,36,9,8.0,5,22,Rural,ML Engineer,147626,0 +37414,Other,31,High School,10,2,62,22,60,8.0,5,90,Urban,HR Executive,127972,0 +37415,Male,25,Masters,9,40,50,27,87,3.0,5,31,Urban,HR Executive,82227,0 +37416,Male,29,Bachelors,17,64,23,70,2,9.0,0,12,Semi-Urban,Manager,28799,0 +37417,Female,26,High School,5,82,7,11,36,1.0,7,96,Rural,Manager,43004,0 +37418,Female,50,Bachelors,9,41,59,11,55,2.0,4,97,Semi-Urban,HR Executive,29342,0 +37419,Male,49,High School,5,89,99,28,19,9.0,3,41,Urban,HR Executive,76845,1 +37420,Male,43,Diploma,8,97,25,63,71,4.0,1,81,Urban,HR Executive,71276,1 +37421,Male,46,Bachelors,13,29,78,71,4,5.0,6,54,Urban,Software Engineer,55274,0 +37422,Female,42,High School,7,9,40,81,50,0.0,2,36,Urban,Software Engineer,42563,0 +37423,Male,41,Bachelors,3,65,62,57,61,3.0,2,52,Urban,ML Engineer,23974,1 +37424,Female,26,Masters,15,93,78,6,23,7.0,6,76,Semi-Urban,Software Engineer,39640,1 +37425,Male,43,Bachelors,0,21,54,40,79,1.0,0,70,Urban,ML Engineer,85669,0 +37426,Female,42,Bachelors,15,11,53,29,41,9.0,3,45,Rural,HR Executive,134069,0 +37427,Male,38,Bachelors,2,57,18,72,62,6.0,3,77,Urban,Manager,142897,0 +37428,Male,59,Bachelors,13,85,68,84,20,3.0,1,95,Rural,Data Analyst,73134,1 +37429,Male,38,High School,3,2,83,21,80,1.0,2,30,Rural,Data Analyst,69348,0 +37430,Male,50,Masters,18,51,24,18,74,7.0,4,26,Rural,Manager,55676,0 +37431,Male,53,Diploma,4,32,0,62,45,7.0,5,24,Urban,Data Analyst,104431,0 +37432,Female,26,Bachelors,6,3,17,39,66,0.0,2,57,Urban,Data Analyst,94547,0 +37433,Male,39,High School,12,84,93,73,32,7.0,7,59,Semi-Urban,HR Executive,101427,1 +37434,Male,32,Bachelors,1,4,57,76,62,9.0,6,51,Urban,HR Executive,138018,0 +37435,Male,57,Bachelors,18,22,28,46,85,4.0,3,96,Urban,Data Analyst,128641,0 +37436,Male,38,Diploma,3,81,69,83,94,9.0,1,52,Semi-Urban,ML Engineer,145045,1 +37437,Male,34,Bachelors,11,4,1,81,60,4.0,6,81,Rural,HR Executive,102351,0 +37438,Male,32,Bachelors,10,11,44,28,8,4.0,3,80,Rural,Data Analyst,81349,0 +37439,Male,24,Masters,16,95,29,58,4,3.0,5,14,Semi-Urban,Manager,30269,0 +37440,Male,57,Bachelors,13,16,81,15,67,0.0,0,56,Urban,Software Engineer,100079,0 +37441,Male,27,Masters,5,59,48,63,69,4.0,6,76,Urban,ML Engineer,68687,1 +37442,Male,53,Bachelors,15,92,87,85,14,6.0,4,99,Semi-Urban,ML Engineer,93091,1 +37443,Male,58,PhD,10,69,98,56,93,9.0,0,38,Urban,HR Executive,28602,1 +37444,Female,54,Bachelors,0,81,40,29,18,2.0,0,88,Urban,HR Executive,42162,0 +37445,Male,30,Diploma,16,99,62,42,35,5.0,7,17,Urban,Software Engineer,81435,0 +37446,Male,34,Bachelors,11,57,1,26,31,9.0,7,63,Rural,HR Executive,121182,0 +37447,Female,34,Bachelors,18,76,48,17,40,1.0,6,18,Semi-Urban,Software Engineer,21329,0 +37448,Male,32,Diploma,1,46,92,17,38,0.0,6,1,Urban,HR Executive,101190,0 +37449,Male,29,Diploma,12,76,16,64,85,8.0,2,87,Urban,Software Engineer,29887,1 +37450,Male,27,Masters,0,5,78,3,24,8.0,4,27,Rural,Manager,128217,0 +37451,Female,36,Diploma,17,37,65,61,2,2.0,0,43,Urban,Data Analyst,64087,0 +37452,Female,25,Masters,11,68,92,51,78,2.0,1,29,Urban,Data Analyst,56584,0 +37453,Female,59,PhD,18,92,16,82,82,4.0,4,75,Urban,HR Executive,50708,1 +37454,Female,48,Bachelors,12,50,45,50,66,8.0,6,25,Urban,Data Analyst,95580,0 +37455,Female,27,Masters,9,64,64,43,80,3.0,0,36,Urban,Data Analyst,44349,0 +37456,Female,55,Masters,4,84,11,93,17,4.0,7,0,Urban,Manager,87864,0 +37457,Male,52,Masters,2,98,86,82,30,3.0,6,36,Rural,ML Engineer,101131,1 +37458,Male,34,Bachelors,19,26,19,45,99,6.0,6,13,Urban,Data Analyst,104378,0 +37459,Female,37,PhD,1,63,20,70,83,1.0,1,37,Semi-Urban,Data Analyst,106770,0 +37460,Female,41,Bachelors,1,66,23,2,15,9.0,0,10,Urban,ML Engineer,78410,0 +37461,Male,52,Diploma,3,69,80,17,48,1.0,1,29,Semi-Urban,ML Engineer,92003,0 +37462,Male,21,Diploma,19,5,73,15,64,4.0,6,20,Urban,Data Analyst,38167,0 +37463,Female,22,Bachelors,2,1,90,9,53,6.0,3,70,Semi-Urban,Manager,84852,0 +37464,Male,55,Masters,9,95,83,69,83,1.0,0,52,Semi-Urban,Software Engineer,125199,1 +37465,Male,49,Diploma,17,60,94,89,99,3.0,2,49,Urban,Manager,48471,1 +37466,Female,47,Masters,12,56,24,6,41,5.0,6,79,Urban,Manager,110870,0 +37467,Male,58,Bachelors,2,31,39,97,33,2.0,5,1,Rural,HR Executive,127965,0 +37468,Male,48,Bachelors,18,1,9,57,55,8.0,7,63,Semi-Urban,Data Analyst,124247,0 +37469,Female,46,High School,15,25,4,86,28,8.0,7,55,Rural,HR Executive,122976,0 +37470,Male,27,Masters,9,13,47,63,10,2.0,4,53,Urban,Manager,74163,0 +37471,Female,40,PhD,11,76,12,18,38,3.0,5,87,Urban,ML Engineer,64956,0 +37472,Other,57,Diploma,6,23,64,90,72,5.0,7,66,Semi-Urban,ML Engineer,125570,1 +37473,Female,54,High School,4,37,26,46,13,2.0,6,85,Semi-Urban,ML Engineer,30915,0 +37474,Other,52,Bachelors,3,80,35,22,1,2.0,1,84,Semi-Urban,HR Executive,130349,0 +37475,Male,37,Masters,5,91,61,15,78,6.0,4,51,Rural,ML Engineer,92755,0 +37476,Male,36,Bachelors,14,8,0,68,89,4.0,0,93,Rural,Manager,25831,0 +37477,Female,22,Masters,18,24,21,0,14,5.0,5,80,Rural,Software Engineer,98861,0 +37478,Male,39,High School,7,42,4,0,13,5.0,1,26,Urban,Software Engineer,35081,0 +37479,Male,51,Bachelors,11,73,22,22,7,3.0,5,58,Rural,ML Engineer,23552,0 +37480,Female,44,High School,2,94,22,27,23,5.0,3,83,Rural,ML Engineer,125551,0 +37481,Female,47,Diploma,12,77,41,81,10,0.0,5,57,Urban,ML Engineer,69300,1 +37482,Female,45,Bachelors,6,8,0,0,96,3.0,5,34,Urban,Data Analyst,43800,0 +37483,Female,24,Diploma,16,58,88,54,91,8.0,5,7,Rural,Data Analyst,141410,0 +37484,Female,52,Masters,10,38,50,16,44,7.0,6,18,Semi-Urban,Data Analyst,109890,0 +37485,Female,30,Masters,1,81,8,0,99,6.0,4,49,Urban,Manager,80374,0 +37486,Male,42,Bachelors,10,31,38,75,5,6.0,7,76,Rural,Software Engineer,97627,0 +37487,Male,38,Bachelors,11,59,8,46,92,9.0,5,92,Semi-Urban,Software Engineer,42810,0 +37488,Female,49,Bachelors,11,62,33,26,72,1.0,2,40,Rural,Software Engineer,123300,0 +37489,Male,40,Diploma,16,91,45,68,39,0.0,6,69,Semi-Urban,Software Engineer,52527,1 +37490,Other,31,Bachelors,5,93,76,33,69,7.0,6,76,Urban,Data Analyst,75258,1 +37491,Female,53,Diploma,18,83,0,10,80,4.0,6,65,Urban,HR Executive,71138,0 +37492,Female,37,Masters,6,26,68,41,11,1.0,3,6,Semi-Urban,Data Analyst,48271,0 +37493,Other,57,Bachelors,10,57,67,84,93,3.0,6,39,Rural,Software Engineer,102027,1 +37494,Female,45,Bachelors,12,49,59,38,94,5.0,3,18,Semi-Urban,Software Engineer,42582,0 +37495,Male,25,Masters,10,75,95,74,71,8.0,0,36,Urban,Software Engineer,33205,1 +37496,Male,32,Diploma,6,31,12,46,73,1.0,2,74,Urban,Software Engineer,123362,0 +37497,Male,38,Masters,2,85,10,18,67,3.0,1,4,Urban,Manager,85318,0 +37498,Male,37,Bachelors,19,95,90,64,23,0.0,1,45,Urban,Manager,130060,1 +37499,Male,48,Diploma,5,23,20,78,30,6.0,2,93,Semi-Urban,Manager,31180,0 +37500,Female,39,Bachelors,3,29,43,29,52,8.0,0,30,Semi-Urban,HR Executive,38152,0 +37501,Male,53,High School,7,40,40,11,92,2.0,6,9,Semi-Urban,Data Analyst,136209,0 +37502,Male,37,Bachelors,0,32,94,75,65,7.0,0,56,Semi-Urban,Software Engineer,64037,1 +37503,Male,34,Bachelors,8,21,82,68,45,3.0,4,4,Semi-Urban,Data Analyst,43483,0 +37504,Male,55,Masters,16,14,23,87,59,7.0,3,32,Urban,Data Analyst,143629,0 +37505,Male,29,Masters,19,46,79,60,17,8.0,7,83,Urban,Software Engineer,109326,1 +37506,Male,44,Masters,3,57,75,37,82,5.0,2,0,Urban,Manager,101344,0 +37507,Female,30,Bachelors,14,25,43,4,22,2.0,6,16,Semi-Urban,Data Analyst,75573,0 +37508,Male,53,Masters,14,20,43,27,31,5.0,6,12,Urban,HR Executive,96803,0 +37509,Male,47,Bachelors,11,25,19,24,88,0.0,6,36,Rural,ML Engineer,87846,0 +37510,Male,55,Diploma,0,37,11,55,60,3.0,3,88,Urban,HR Executive,58378,0 +37511,Female,27,Diploma,15,39,47,74,36,7.0,2,26,Urban,Manager,95372,0 +37512,Female,38,High School,0,50,50,95,89,2.0,2,1,Semi-Urban,HR Executive,148659,0 +37513,Other,45,Diploma,5,90,68,88,71,2.0,6,75,Semi-Urban,ML Engineer,55003,1 +37514,Female,27,PhD,18,18,58,0,96,6.0,7,88,Semi-Urban,Software Engineer,107834,0 +37515,Male,44,Diploma,18,52,79,77,12,2.0,0,97,Urban,Software Engineer,129058,1 +37516,Male,39,Bachelors,15,12,94,55,8,1.0,3,16,Urban,HR Executive,117928,0 +37517,Male,56,Bachelors,13,90,29,46,43,1.0,2,77,Semi-Urban,Software Engineer,93518,1 +37518,Female,30,Bachelors,7,51,70,86,79,8.0,5,96,Urban,Software Engineer,42818,1 +37519,Male,28,Masters,13,61,56,40,67,9.0,6,30,Urban,Data Analyst,66905,0 +37520,Female,54,Diploma,11,38,48,73,78,9.0,7,79,Semi-Urban,ML Engineer,67711,0 +37521,Male,26,Bachelors,11,83,62,76,26,2.0,0,48,Urban,Data Analyst,144863,1 +37522,Male,48,Bachelors,18,67,62,21,49,7.0,1,5,Urban,Manager,41377,0 +37523,Male,52,Bachelors,0,44,62,55,36,8.0,0,75,Rural,ML Engineer,61953,1 +37524,Female,42,Diploma,13,31,23,50,31,1.0,5,65,Rural,HR Executive,98122,0 +37525,Male,52,Diploma,17,39,65,70,40,7.0,7,53,Urban,ML Engineer,93112,0 +37526,Female,38,Diploma,9,12,8,48,6,7.0,3,92,Urban,ML Engineer,35921,0 +37527,Male,28,Masters,8,67,85,70,35,9.0,6,99,Semi-Urban,HR Executive,78043,1 +37528,Male,40,High School,2,78,86,99,61,1.0,4,61,Urban,Data Analyst,90901,1 +37529,Male,34,Masters,9,75,56,62,49,0.0,0,47,Urban,Software Engineer,24675,1 +37530,Male,41,Diploma,10,10,99,49,15,8.0,5,26,Semi-Urban,Manager,113654,0 +37531,Male,28,Diploma,15,41,71,23,27,3.0,4,37,Urban,Data Analyst,45406,0 +37532,Male,33,Diploma,14,75,63,3,17,0.0,4,37,Urban,Manager,72879,0 +37533,Male,46,Masters,12,29,62,95,30,7.0,5,6,Urban,ML Engineer,75684,0 +37534,Female,29,Masters,2,80,35,66,43,6.0,0,50,Urban,Manager,79866,0 +37535,Male,56,Masters,16,2,6,52,22,4.0,3,28,Urban,Data Analyst,120784,0 +37536,Male,42,Diploma,1,29,94,26,20,4.0,2,67,Urban,Manager,67698,0 +37537,Female,38,Masters,18,14,71,98,86,9.0,4,17,Urban,Software Engineer,23576,0 +37538,Female,51,High School,12,84,78,24,62,6.0,7,11,Urban,Manager,85731,0 +37539,Male,50,Masters,18,75,86,0,75,9.0,6,80,Rural,HR Executive,23543,1 +37540,Female,31,Bachelors,14,0,15,27,67,3.0,2,99,Urban,Manager,61466,0 +37541,Female,35,High School,6,32,43,19,72,9.0,1,10,Rural,Data Analyst,73951,0 +37542,Male,41,Diploma,8,64,82,21,80,0.0,1,39,Rural,Manager,33957,0 +37543,Male,51,Bachelors,17,35,18,33,35,3.0,4,4,Urban,Software Engineer,109123,0 +37544,Male,37,Masters,13,81,32,14,19,5.0,7,11,Urban,Software Engineer,31518,0 +37545,Male,24,High School,12,29,7,85,32,9.0,3,35,Semi-Urban,HR Executive,48525,0 +37546,Other,21,High School,6,94,17,96,80,1.0,0,98,Urban,HR Executive,30750,1 +37547,Male,33,High School,17,41,55,5,20,3.0,6,29,Rural,ML Engineer,64754,0 +37548,Male,35,Bachelors,15,32,40,59,15,4.0,1,17,Semi-Urban,Software Engineer,96297,0 +37549,Other,56,Masters,19,8,62,79,37,5.0,5,24,Urban,Software Engineer,37484,0 +37550,Female,58,Masters,16,20,0,27,16,9.0,3,30,Semi-Urban,HR Executive,45081,0 +37551,Male,23,High School,18,24,22,44,28,5.0,4,71,Urban,ML Engineer,87164,0 +37552,Female,33,Masters,1,89,99,52,97,3.0,5,38,Semi-Urban,ML Engineer,128044,1 +37553,Female,47,Bachelors,15,53,39,69,89,6.0,5,76,Rural,Software Engineer,48051,0 +37554,Female,25,High School,9,58,58,49,46,7.0,2,56,Rural,Data Analyst,104452,0 +37555,Male,39,Bachelors,18,20,61,74,2,6.0,5,67,Urban,HR Executive,37502,0 +37556,Male,59,Bachelors,11,44,95,96,46,1.0,6,13,Urban,Manager,132153,1 +37557,Male,41,PhD,10,2,1,64,79,2.0,2,83,Rural,Data Analyst,42023,0 +37558,Male,56,Diploma,14,92,47,19,77,7.0,2,60,Urban,Data Analyst,93324,0 +37559,Male,48,Masters,18,66,29,95,83,2.0,2,41,Rural,Software Engineer,73099,0 +37560,Female,37,Bachelors,2,49,6,26,14,1.0,6,75,Urban,Manager,40910,0 +37561,Male,43,Diploma,2,96,20,40,92,4.0,4,56,Urban,HR Executive,59889,0 +37562,Male,35,Bachelors,0,71,1,40,47,0.0,6,51,Rural,HR Executive,86236,0 +37563,Female,38,Bachelors,8,76,39,82,2,0.0,3,63,Semi-Urban,HR Executive,78400,1 +37564,Male,45,High School,16,53,37,55,6,1.0,4,43,Urban,Data Analyst,81852,0 +37565,Female,59,High School,14,74,9,72,92,8.0,3,43,Urban,Software Engineer,23503,0 +37566,Female,44,Masters,10,7,71,84,37,5.0,5,27,Semi-Urban,ML Engineer,113021,0 +37567,Other,22,Masters,19,5,25,79,37,2.0,2,39,Urban,HR Executive,32945,0 +37568,Male,46,Bachelors,2,44,81,27,98,4.0,4,83,Urban,Manager,64463,1 +37569,Female,37,Masters,12,83,63,82,58,5.0,6,16,Urban,Data Analyst,58109,1 +37570,Female,55,High School,17,49,61,70,93,9.0,0,90,Semi-Urban,Manager,144417,1 +37571,Female,23,Bachelors,17,77,35,17,69,1.0,7,62,Semi-Urban,Data Analyst,142114,0 +37572,Female,28,Bachelors,0,53,88,21,35,9.0,5,21,Semi-Urban,Manager,87062,0 +37573,Male,42,Bachelors,16,1,50,77,14,9.0,3,33,Urban,Software Engineer,83448,0 +37574,Male,23,Masters,8,83,81,85,18,1.0,4,56,Rural,HR Executive,112666,1 +37575,Female,26,Masters,6,81,61,34,19,7.0,0,3,Urban,HR Executive,93577,0 +37576,Female,21,Bachelors,2,30,34,92,88,8.0,5,27,Urban,ML Engineer,144279,0 +37577,Female,23,Diploma,10,0,69,67,79,9.0,5,67,Rural,Manager,25581,0 +37578,Male,34,Bachelors,1,56,26,98,56,0.0,6,6,Rural,Software Engineer,79173,0 +37579,Male,37,PhD,3,95,99,12,79,6.0,3,91,Semi-Urban,Data Analyst,23382,1 +37580,Male,53,Bachelors,10,92,40,13,82,2.0,4,62,Rural,HR Executive,20611,0 +37581,Female,49,Bachelors,13,14,57,8,71,5.0,1,53,Urban,HR Executive,57254,0 +37582,Female,58,Bachelors,8,7,4,16,36,4.0,4,13,Urban,Manager,131578,0 +37583,Male,30,Diploma,3,20,14,43,26,8.0,2,46,Urban,ML Engineer,131731,0 +37584,Female,59,Diploma,4,13,0,89,79,5.0,6,97,Rural,Software Engineer,64119,0 +37585,Male,59,Bachelors,18,10,0,16,45,7.0,4,59,Urban,ML Engineer,90205,0 +37586,Male,56,High School,15,78,85,49,42,8.0,2,11,Urban,Data Analyst,47526,0 +37587,Male,41,Masters,16,23,70,45,71,1.0,1,44,Semi-Urban,Manager,47306,0 +37588,Female,53,Bachelors,12,93,81,71,27,3.0,6,69,Urban,Data Analyst,121617,1 +37589,Female,52,Bachelors,5,54,3,21,55,6.0,7,71,Urban,HR Executive,147554,0 +37590,Male,33,Bachelors,17,99,87,14,3,1.0,3,45,Urban,ML Engineer,93024,1 +37591,Male,45,Bachelors,0,88,25,84,88,6.0,2,85,Urban,HR Executive,100115,1 +37592,Female,22,Bachelors,4,55,57,12,6,9.0,7,56,Semi-Urban,Software Engineer,75891,0 +37593,Male,56,Bachelors,8,9,26,93,12,9.0,4,93,Urban,HR Executive,124371,0 +37594,Other,33,Bachelors,12,13,95,30,65,3.0,0,76,Semi-Urban,HR Executive,45891,0 +37595,Female,22,High School,11,28,17,84,97,2.0,0,80,Semi-Urban,Manager,77567,0 +37596,Male,22,Bachelors,9,96,18,28,51,7.0,1,74,Urban,Data Analyst,88707,0 +37597,Male,49,Diploma,0,76,79,29,49,0.0,2,96,Semi-Urban,ML Engineer,134003,1 +37598,Male,29,Diploma,13,90,60,58,85,6.0,5,64,Urban,ML Engineer,46536,1 +37599,Male,50,Masters,7,53,24,10,72,1.0,5,90,Urban,Data Analyst,82920,0 +37600,Female,54,Masters,6,4,0,72,65,5.0,7,5,Urban,Software Engineer,39242,0 +37601,Male,56,Diploma,2,27,56,25,64,1.0,7,40,Urban,HR Executive,78633,0 +37602,Female,59,Bachelors,7,98,93,72,99,1.0,2,0,Urban,HR Executive,71203,1 +37603,Male,46,Masters,1,13,21,95,35,0.0,3,99,Urban,ML Engineer,20048,0 +37604,Other,53,Bachelors,11,51,94,63,44,7.0,1,87,Urban,Data Analyst,91953,1 +37605,Male,52,Bachelors,18,19,88,97,90,4.0,6,8,Urban,HR Executive,107997,0 +37606,Female,48,Bachelors,13,91,84,76,92,3.0,3,18,Semi-Urban,HR Executive,46227,1 +37607,Female,40,Diploma,7,84,27,53,31,1.0,0,57,Rural,Data Analyst,84945,0 +37608,Male,32,Bachelors,12,83,16,11,43,1.0,4,78,Urban,Manager,85569,0 +37609,Male,36,High School,1,6,40,72,96,0.0,7,20,Urban,HR Executive,128934,0 +37610,Female,22,Bachelors,7,82,85,3,71,1.0,6,1,Urban,ML Engineer,56310,0 +37611,Male,48,Masters,5,80,62,33,72,8.0,3,15,Urban,HR Executive,101390,0 +37612,Male,36,Diploma,2,41,96,45,45,1.0,5,40,Urban,HR Executive,119319,0 +37613,Female,49,Masters,6,34,86,25,21,9.0,4,42,Semi-Urban,Manager,125322,0 +37614,Male,31,Diploma,1,63,24,92,50,6.0,5,14,Semi-Urban,Data Analyst,43796,0 +37615,Male,47,Bachelors,8,16,62,34,66,3.0,4,47,Semi-Urban,Data Analyst,41122,0 +37616,Female,22,Bachelors,4,18,93,62,44,2.0,3,66,Rural,Manager,116987,0 +37617,Female,59,Diploma,2,24,37,59,13,5.0,4,63,Urban,HR Executive,131053,0 +37618,Male,34,High School,4,75,61,17,72,6.0,5,1,Semi-Urban,HR Executive,105832,0 +37619,Male,30,Bachelors,9,30,32,55,98,3.0,1,55,Urban,Manager,76993,0 +37620,Female,45,Diploma,15,44,98,49,44,2.0,4,15,Urban,Manager,95614,0 +37621,Male,39,Masters,19,32,27,24,66,2.0,7,43,Urban,Manager,42005,0 +37622,Female,40,Masters,15,7,65,8,86,2.0,1,75,Semi-Urban,Software Engineer,123698,0 +37623,Male,51,High School,9,26,79,49,93,0.0,5,88,Urban,Software Engineer,69582,1 +37624,Female,52,High School,3,94,89,83,56,7.0,7,70,Urban,HR Executive,133010,1 +37625,Male,42,High School,9,76,90,98,80,2.0,1,71,Semi-Urban,Manager,95820,1 +37626,Other,34,PhD,2,84,40,22,47,9.0,4,23,Urban,Data Analyst,149626,0 +37627,Male,37,High School,14,19,82,30,98,7.0,2,51,Urban,Manager,82062,0 +37628,Male,54,Bachelors,10,77,70,18,50,2.0,1,32,Rural,ML Engineer,129757,0 +37629,Male,30,Bachelors,1,59,77,15,46,9.0,6,20,Semi-Urban,ML Engineer,47287,0 +37630,Male,42,Masters,12,37,22,7,23,8.0,1,84,Urban,Software Engineer,110186,0 +37631,Male,37,Masters,7,83,83,32,67,4.0,6,94,Urban,Manager,40064,1 +37632,Female,55,Bachelors,0,39,99,78,63,0.0,4,68,Semi-Urban,HR Executive,110871,1 +37633,Female,48,Masters,8,14,96,78,14,3.0,6,41,Urban,Software Engineer,125161,0 +37634,Male,54,Diploma,13,4,66,53,30,9.0,1,76,Urban,Data Analyst,50196,0 +37635,Male,42,High School,12,73,40,76,51,3.0,6,59,Urban,Data Analyst,58090,1 +37636,Female,28,Bachelors,14,4,95,19,37,3.0,2,55,Urban,Manager,23176,0 +37637,Male,30,Diploma,2,31,11,57,3,8.0,2,26,Urban,Software Engineer,59810,0 +37638,Male,38,High School,1,21,92,61,77,2.0,5,30,Semi-Urban,HR Executive,136636,0 +37639,Male,55,Bachelors,9,19,5,13,68,7.0,4,77,Urban,ML Engineer,71823,0 +37640,Male,42,Bachelors,18,31,61,46,88,6.0,6,30,Semi-Urban,Manager,24097,0 +37641,Male,56,Masters,3,55,75,1,98,4.0,0,77,Urban,Software Engineer,84065,0 +37642,Female,54,High School,14,18,3,55,34,0.0,7,13,Urban,Data Analyst,61715,0 +37643,Male,57,Diploma,5,28,23,78,75,2.0,0,1,Rural,Software Engineer,109798,0 +37644,Female,46,Diploma,5,12,46,86,42,3.0,4,6,Semi-Urban,Software Engineer,98446,0 +37645,Male,42,Diploma,16,58,39,10,1,1.0,5,8,Urban,Manager,117649,0 +37646,Male,59,PhD,13,74,75,50,35,5.0,5,10,Urban,HR Executive,134724,0 +37647,Male,46,PhD,17,53,6,67,20,2.0,2,45,Urban,ML Engineer,116633,0 +37648,Female,41,Bachelors,0,6,99,53,81,6.0,0,47,Urban,Manager,88319,0 +37649,Male,44,Diploma,2,61,47,42,6,6.0,5,76,Urban,Data Analyst,51729,0 +37650,Male,50,Masters,12,81,69,40,41,9.0,6,28,Urban,ML Engineer,132570,0 +37651,Male,36,Diploma,3,67,71,42,42,4.0,7,55,Semi-Urban,ML Engineer,28142,1 +37652,Male,50,Bachelors,12,3,27,49,83,1.0,1,65,Semi-Urban,Manager,91748,0 +37653,Male,58,Diploma,18,77,9,59,11,9.0,1,21,Urban,Software Engineer,26438,0 +37654,Male,27,Bachelors,8,93,15,93,6,2.0,7,57,Semi-Urban,ML Engineer,77825,1 +37655,Male,55,Masters,3,99,62,97,21,1.0,3,44,Semi-Urban,Software Engineer,98753,1 +37656,Other,59,Bachelors,11,92,42,85,23,3.0,7,39,Urban,HR Executive,35062,1 +37657,Male,45,PhD,11,75,53,11,78,9.0,6,55,Urban,Data Analyst,126081,0 +37658,Female,26,Diploma,8,47,50,85,72,4.0,3,48,Urban,Manager,126137,0 +37659,Male,34,Diploma,15,70,79,41,47,0.0,4,77,Urban,Software Engineer,80137,1 +37660,Male,31,PhD,13,96,11,20,62,9.0,7,32,Semi-Urban,Data Analyst,39068,0 +37661,Other,51,Masters,3,86,63,6,75,6.0,2,15,Semi-Urban,ML Engineer,93025,0 +37662,Female,50,Bachelors,1,51,56,4,50,8.0,6,48,Rural,Software Engineer,62082,0 +37663,Female,50,Diploma,2,66,86,11,35,3.0,5,96,Semi-Urban,Data Analyst,37658,1 +37664,Female,42,Bachelors,7,73,92,90,14,5.0,3,39,Urban,ML Engineer,80664,1 +37665,Other,30,Bachelors,11,13,12,54,89,0.0,1,83,Urban,Manager,141686,0 +37666,Male,58,Diploma,7,20,6,30,44,6.0,1,63,Semi-Urban,Software Engineer,135256,0 +37667,Male,22,Masters,16,77,59,96,13,9.0,7,58,Rural,ML Engineer,81361,1 +37668,Male,54,Diploma,1,65,85,33,23,6.0,2,79,Semi-Urban,HR Executive,27365,1 +37669,Female,54,Bachelors,18,14,71,26,7,2.0,5,16,Urban,Software Engineer,38677,0 +37670,Female,37,Masters,15,24,16,90,16,3.0,7,76,Semi-Urban,Software Engineer,90702,0 +37671,Female,52,Diploma,17,16,15,82,72,7.0,6,5,Urban,Data Analyst,107491,0 +37672,Male,21,Diploma,8,37,98,24,1,4.0,7,95,Urban,ML Engineer,63506,1 +37673,Female,52,Bachelors,8,13,75,53,35,3.0,2,15,Semi-Urban,Software Engineer,20571,0 +37674,Male,58,Bachelors,7,54,24,74,42,3.0,4,70,Urban,HR Executive,93030,0 +37675,Female,24,Bachelors,11,46,96,62,32,8.0,5,40,Semi-Urban,Data Analyst,122587,1 +37676,Male,38,Bachelors,3,10,23,18,29,1.0,7,10,Urban,Data Analyst,57017,0 +37677,Other,33,PhD,3,37,11,1,74,5.0,3,2,Semi-Urban,Manager,69423,0 +37678,Male,23,Diploma,14,14,34,18,40,0.0,6,10,Semi-Urban,Manager,80921,0 +37679,Male,57,Bachelors,4,7,78,30,92,4.0,3,96,Semi-Urban,ML Engineer,54392,0 +37680,Female,49,Diploma,18,4,49,89,52,9.0,5,4,Rural,Data Analyst,72003,0 +37681,Female,28,High School,8,58,69,2,1,0.0,1,43,Rural,ML Engineer,26242,0 +37682,Male,52,High School,3,55,4,92,6,0.0,5,12,Urban,HR Executive,91541,0 +37683,Female,50,Bachelors,12,4,13,59,99,1.0,7,11,Semi-Urban,Data Analyst,137829,0 +37684,Female,42,High School,3,36,34,4,66,2.0,6,98,Urban,Manager,76565,0 +37685,Male,24,High School,4,38,29,23,55,1.0,4,34,Urban,Manager,91258,0 +37686,Male,45,Masters,18,59,55,22,56,3.0,2,90,Rural,Manager,121068,0 +37687,Male,36,PhD,0,2,67,74,43,9.0,6,16,Urban,Manager,105656,0 +37688,Male,44,Masters,8,46,55,41,56,4.0,3,8,Urban,ML Engineer,44612,0 +37689,Female,49,Masters,4,22,98,87,89,1.0,2,38,Urban,ML Engineer,76256,1 +37690,Male,33,Bachelors,9,2,68,69,29,6.0,7,67,Urban,Data Analyst,119485,0 +37691,Female,47,Diploma,12,54,60,52,32,3.0,1,49,Urban,Software Engineer,26465,0 +37692,Female,55,High School,13,38,61,21,23,8.0,2,8,Semi-Urban,Data Analyst,125371,0 +37693,Female,49,Bachelors,18,13,20,67,1,5.0,0,95,Urban,Data Analyst,73133,0 +37694,Female,22,Diploma,7,16,95,28,79,4.0,6,2,Urban,ML Engineer,117324,0 +37695,Female,55,Diploma,12,64,89,81,86,2.0,0,73,Semi-Urban,Manager,86170,1 +37696,Male,30,Bachelors,11,26,92,97,52,6.0,7,32,Rural,Manager,77610,1 +37697,Female,36,Bachelors,4,18,46,78,92,9.0,0,53,Urban,Manager,87195,0 +37698,Other,25,Bachelors,16,75,33,95,60,8.0,0,40,Urban,Manager,123605,1 +37699,Male,52,Diploma,18,51,25,72,88,6.0,4,27,Urban,HR Executive,128272,0 +37700,Other,31,Bachelors,6,36,51,1,67,2.0,0,46,Urban,Manager,63115,0 +37701,Male,58,Bachelors,3,92,80,8,92,7.0,1,52,Rural,Data Analyst,105560,0 +37702,Male,56,Bachelors,6,57,90,4,20,8.0,6,53,Semi-Urban,Manager,91521,0 +37703,Female,52,High School,8,12,66,91,50,7.0,2,5,Urban,HR Executive,24344,0 +37704,Female,54,Bachelors,13,88,73,99,36,8.0,2,13,Urban,Data Analyst,148865,1 +37705,Female,40,Bachelors,11,26,84,1,71,2.0,1,47,Rural,HR Executive,116159,0 +37706,Male,50,Masters,0,74,52,64,75,5.0,5,52,Semi-Urban,HR Executive,43430,1 +37707,Female,42,Masters,2,13,99,42,43,0.0,4,0,Rural,Data Analyst,86772,0 +37708,Female,47,Diploma,17,99,2,96,22,3.0,2,12,Rural,Data Analyst,30018,0 +37709,Male,59,Bachelors,16,58,16,66,62,6.0,4,50,Urban,HR Executive,142853,0 +37710,Male,35,Bachelors,9,46,35,44,11,5.0,7,33,Urban,ML Engineer,148670,0 +37711,Female,59,Bachelors,3,83,32,45,39,3.0,4,59,Urban,HR Executive,80122,0 +37712,Male,37,High School,19,38,19,4,13,1.0,4,10,Urban,HR Executive,35940,0 +37713,Male,36,High School,10,46,22,11,79,4.0,0,62,Semi-Urban,Data Analyst,96911,0 +37714,Male,21,Masters,13,75,43,72,93,6.0,5,66,Urban,ML Engineer,36324,1 +37715,Female,22,Masters,13,36,48,73,36,6.0,6,27,Semi-Urban,Software Engineer,52320,0 +37716,Male,38,Bachelors,5,74,26,42,34,3.0,0,7,Rural,Manager,124088,0 +37717,Male,34,Bachelors,1,82,67,72,19,6.0,1,91,Rural,Manager,99418,1 +37718,Male,55,Bachelors,5,61,74,47,81,3.0,1,10,Urban,Software Engineer,69314,0 +37719,Male,46,Bachelors,18,27,31,67,2,1.0,3,24,Urban,ML Engineer,27276,0 +37720,Male,38,High School,11,57,36,75,57,3.0,2,3,Urban,HR Executive,149557,0 +37721,Male,52,Bachelors,10,51,88,72,21,7.0,1,44,Urban,Software Engineer,140635,1 +37722,Male,25,Bachelors,3,28,9,20,30,1.0,0,15,Urban,ML Engineer,25530,0 +37723,Male,40,Bachelors,0,35,78,47,98,1.0,3,39,Urban,HR Executive,20962,0 +37724,Female,38,Masters,0,93,53,76,13,2.0,5,7,Semi-Urban,ML Engineer,116352,0 +37725,Male,42,High School,0,11,21,88,30,1.0,1,83,Urban,Manager,117382,0 +37726,Female,25,Masters,13,5,5,30,14,0.0,1,58,Rural,Software Engineer,43484,0 +37727,Female,25,PhD,3,68,55,4,68,9.0,6,38,Rural,Software Engineer,134231,0 +37728,Male,30,Bachelors,5,6,16,37,28,7.0,0,16,Urban,HR Executive,62641,0 +37729,Male,53,Bachelors,9,44,74,5,6,0.0,0,42,Urban,ML Engineer,119300,0 +37730,Other,28,Masters,17,10,64,69,78,9.0,4,95,Semi-Urban,Manager,50025,0 +37731,Female,49,Bachelors,14,6,77,92,53,7.0,1,27,Semi-Urban,Software Engineer,71335,0 +37732,Male,31,Masters,8,50,44,85,96,6.0,5,12,Urban,HR Executive,146411,0 +37733,Male,30,Bachelors,12,44,75,29,50,6.0,4,43,Urban,Manager,115670,0 +37734,Male,33,High School,8,54,36,18,3,5.0,2,77,Rural,Software Engineer,131507,0 +37735,Female,30,Masters,19,61,77,47,33,4.0,0,85,Rural,HR Executive,39361,1 +37736,Female,51,Masters,1,85,17,4,25,6.0,7,62,Urban,ML Engineer,53237,0 +37737,Male,42,Masters,7,95,35,22,44,8.0,6,33,Semi-Urban,HR Executive,93102,0 +37738,Male,44,High School,9,62,9,84,99,8.0,3,21,Urban,ML Engineer,31854,0 +37739,Male,51,High School,13,88,20,52,98,1.0,3,16,Urban,Software Engineer,33996,0 +37740,Other,41,PhD,13,11,11,25,11,5.0,7,81,Urban,Manager,87723,0 +37741,Male,33,Diploma,2,13,47,27,95,4.0,4,3,Rural,HR Executive,61258,0 +37742,Female,46,High School,0,29,19,31,45,9.0,1,80,Urban,Manager,72156,0 +37743,Male,48,Diploma,14,60,78,96,31,7.0,3,12,Urban,Data Analyst,29114,1 +37744,Female,36,Bachelors,10,32,40,7,90,4.0,0,1,Semi-Urban,ML Engineer,139713,0 +37745,Male,33,Masters,5,62,55,47,19,6.0,7,77,Semi-Urban,Software Engineer,108866,1 +37746,Female,23,Masters,3,78,70,67,44,8.0,5,1,Semi-Urban,HR Executive,46623,0 +37747,Male,40,Bachelors,12,23,96,93,70,3.0,1,56,Urban,Software Engineer,146521,1 +37748,Female,32,Diploma,14,19,87,48,90,9.0,7,9,Urban,HR Executive,47373,0 +37749,Male,34,PhD,3,11,16,67,87,1.0,6,87,Urban,HR Executive,142859,0 +37750,Female,23,Bachelors,3,44,46,64,63,5.0,0,56,Semi-Urban,HR Executive,119416,0 +37751,Male,40,Bachelors,5,53,6,25,5,2.0,7,3,Rural,Data Analyst,47590,0 +37752,Male,26,Masters,0,7,13,53,24,5.0,2,22,Urban,HR Executive,107366,0 +37753,Male,24,High School,2,85,2,59,29,6.0,0,69,Urban,HR Executive,22647,0 +37754,Male,43,High School,6,41,17,98,7,9.0,7,13,Urban,Data Analyst,104238,0 +37755,Male,25,PhD,4,42,76,4,5,0.0,0,31,Urban,HR Executive,128055,0 +37756,Male,32,Masters,0,11,39,95,19,2.0,1,77,Urban,HR Executive,105229,0 +37757,Male,46,Diploma,16,20,33,7,38,8.0,0,57,Urban,ML Engineer,46641,0 +37758,Male,52,Diploma,19,94,25,12,44,8.0,5,69,Semi-Urban,HR Executive,131643,0 +37759,Male,46,Bachelors,15,98,97,49,65,0.0,4,11,Urban,HR Executive,28431,1 +37760,Male,49,Bachelors,3,9,71,0,6,0.0,6,67,Urban,Software Engineer,116377,0 +37761,Male,33,Diploma,9,28,23,66,43,0.0,0,95,Urban,Manager,83984,0 +37762,Male,29,Masters,6,2,54,93,50,6.0,4,56,Urban,Software Engineer,147306,0 +37763,Female,29,Diploma,1,75,1,62,27,6.0,6,93,Urban,Manager,116287,0 +37764,Male,54,Bachelors,12,19,12,43,60,5.0,2,54,Urban,Manager,133276,0 +37765,Female,43,Bachelors,1,84,84,86,45,1.0,7,72,Semi-Urban,ML Engineer,100200,1 +37766,Male,45,Bachelors,13,51,9,68,25,7.0,7,96,Rural,ML Engineer,115186,0 +37767,Other,42,Bachelors,15,98,84,44,38,0.0,1,11,Urban,Software Engineer,88793,0 +37768,Male,38,Bachelors,19,39,91,90,98,5.0,1,45,Rural,Manager,21797,1 +37769,Female,52,Masters,15,73,73,51,52,1.0,4,33,Urban,Manager,83824,0 +37770,Male,40,Bachelors,12,75,30,14,31,1.0,3,17,Urban,HR Executive,125273,0 +37771,Male,28,High School,4,1,48,9,34,0.0,2,2,Urban,Manager,80584,0 +37772,Male,51,Bachelors,19,18,8,80,90,9.0,0,35,Semi-Urban,HR Executive,81965,0 +37773,Male,41,Bachelors,4,0,7,5,53,7.0,7,20,Urban,HR Executive,144450,0 +37774,Male,35,Masters,16,42,55,15,44,2.0,0,22,Semi-Urban,Manager,41408,0 +37775,Male,21,Diploma,15,54,44,42,90,6.0,5,12,Semi-Urban,HR Executive,53719,0 +37776,Female,47,Bachelors,19,55,25,85,52,7.0,3,7,Urban,Data Analyst,129502,0 +37777,Male,38,Masters,14,55,63,90,15,7.0,0,3,Semi-Urban,HR Executive,45087,0 +37778,Male,34,High School,6,21,33,28,87,7.0,7,21,Semi-Urban,HR Executive,47938,0 +37779,Female,30,Bachelors,7,43,4,78,95,5.0,7,4,Urban,ML Engineer,126904,0 +37780,Female,52,Masters,1,73,70,40,28,9.0,7,89,Urban,ML Engineer,36521,1 +37781,Male,25,Masters,17,13,41,10,30,1.0,2,52,Urban,Data Analyst,56984,0 +37782,Female,21,High School,12,55,75,98,31,2.0,3,9,Urban,ML Engineer,90085,0 +37783,Male,43,Diploma,17,75,48,19,30,0.0,4,61,Urban,Manager,59815,0 +37784,Male,52,Diploma,5,15,85,7,62,0.0,0,43,Semi-Urban,HR Executive,79566,0 +37785,Male,32,Masters,12,58,98,73,75,2.0,7,45,Rural,Software Engineer,60390,1 +37786,Male,53,Bachelors,11,90,26,24,19,4.0,3,44,Urban,Software Engineer,37890,0 +37787,Male,28,High School,4,81,27,80,5,1.0,5,0,Rural,Software Engineer,144786,0 +37788,Male,28,Bachelors,2,8,17,46,40,3.0,4,31,Urban,ML Engineer,93224,0 +37789,Male,31,Bachelors,1,61,39,95,78,1.0,7,1,Urban,Manager,61718,0 +37790,Male,41,High School,18,43,22,45,87,3.0,3,30,Semi-Urban,Data Analyst,53293,0 +37791,Female,53,PhD,4,11,95,66,85,5.0,5,44,Semi-Urban,Data Analyst,61337,0 +37792,Female,36,Masters,5,1,34,69,55,8.0,3,52,Urban,Software Engineer,145460,0 +37793,Female,30,Bachelors,4,74,15,31,8,9.0,2,72,Urban,Manager,116522,0 +37794,Female,38,Bachelors,12,48,38,60,87,8.0,3,24,Urban,ML Engineer,138273,0 +37795,Female,54,Bachelors,7,38,93,20,72,8.0,2,87,Urban,ML Engineer,32599,0 +37796,Female,35,High School,12,6,24,80,69,7.0,7,13,Semi-Urban,Software Engineer,116272,0 +37797,Male,56,Diploma,10,65,37,58,29,1.0,1,87,Urban,ML Engineer,57280,1 +37798,Male,41,Bachelors,1,48,63,48,76,3.0,1,83,Rural,HR Executive,88741,1 +37799,Male,24,Bachelors,7,7,21,70,87,5.0,3,16,Semi-Urban,HR Executive,83758,0 +37800,Male,53,Bachelors,0,71,56,30,3,8.0,6,11,Semi-Urban,Manager,36784,0 +37801,Male,43,Masters,14,33,36,10,71,5.0,1,10,Rural,Software Engineer,39463,0 +37802,Male,52,Bachelors,19,22,64,47,41,5.0,4,87,Urban,HR Executive,70818,0 +37803,Other,29,Bachelors,1,37,65,17,92,4.0,0,71,Urban,Software Engineer,145416,0 +37804,Male,25,Masters,9,55,48,4,80,4.0,5,79,Semi-Urban,ML Engineer,90245,0 +37805,Male,57,Bachelors,14,62,52,99,90,4.0,6,42,Urban,ML Engineer,149087,1 +37806,Male,44,Bachelors,15,87,4,68,70,5.0,7,58,Rural,Software Engineer,54252,0 +37807,Female,46,Bachelors,5,72,73,38,9,5.0,3,74,Urban,HR Executive,62617,1 +37808,Male,40,Bachelors,0,13,96,28,38,0.0,5,84,Rural,Software Engineer,119492,0 +37809,Male,53,Diploma,17,59,67,75,87,6.0,5,63,Semi-Urban,Data Analyst,20045,1 +37810,Other,38,Bachelors,0,53,1,19,58,9.0,3,81,Semi-Urban,ML Engineer,86806,0 +37811,Female,57,Bachelors,17,80,61,87,95,9.0,5,7,Urban,Manager,35357,0 +37812,Female,54,Diploma,17,69,93,70,1,2.0,6,40,Urban,HR Executive,58284,1 +37813,Other,26,Bachelors,8,89,2,18,25,4.0,5,85,Urban,Data Analyst,63308,0 +37814,Male,40,Masters,1,5,83,1,52,2.0,7,54,Urban,Manager,47178,0 +37815,Female,50,Bachelors,0,43,54,61,54,2.0,2,82,Urban,Software Engineer,133369,0 +37816,Male,49,High School,10,48,22,32,88,9.0,2,82,Urban,Data Analyst,130128,0 +37817,Female,34,Diploma,12,25,71,4,66,9.0,2,92,Rural,Software Engineer,137864,0 +37818,Male,28,Bachelors,12,31,79,6,14,1.0,0,13,Urban,Data Analyst,86577,0 +37819,Male,48,Masters,17,25,36,1,85,2.0,6,22,Urban,Software Engineer,48133,0 +37820,Male,49,Bachelors,3,12,49,8,92,8.0,7,79,Urban,Data Analyst,65588,0 +37821,Male,34,High School,1,26,42,90,98,7.0,2,9,Semi-Urban,Manager,120331,0 +37822,Male,46,Bachelors,5,85,29,40,15,8.0,4,69,Urban,HR Executive,75384,0 +37823,Male,54,Bachelors,4,78,49,14,35,8.0,1,89,Rural,Manager,112063,0 +37824,Female,42,Bachelors,6,78,44,48,71,1.0,3,24,Urban,Data Analyst,24412,0 +37825,Male,44,Bachelors,4,6,4,19,68,9.0,6,92,Semi-Urban,Software Engineer,42842,0 +37826,Male,21,Diploma,8,76,71,68,58,8.0,5,29,Urban,Manager,57631,1 +37827,Female,31,Bachelors,9,43,70,27,37,9.0,2,20,Rural,Software Engineer,42606,0 +37828,Female,35,Bachelors,17,77,82,51,91,6.0,5,33,Semi-Urban,Manager,130734,1 +37829,Male,45,Diploma,11,63,13,38,93,0.0,4,98,Urban,HR Executive,82532,0 +37830,Male,37,PhD,8,3,63,84,12,7.0,0,11,Semi-Urban,Software Engineer,66163,0 +37831,Female,38,High School,6,45,90,79,17,7.0,0,4,Urban,Data Analyst,86067,0 +37832,Male,49,Bachelors,2,4,14,36,18,7.0,3,31,Semi-Urban,Data Analyst,118655,0 +37833,Male,44,Bachelors,7,87,55,42,45,5.0,4,49,Urban,HR Executive,52456,0 +37834,Male,27,Bachelors,10,77,9,58,97,5.0,0,76,Rural,ML Engineer,63692,0 +37835,Female,51,High School,8,21,84,4,92,6.0,6,44,Semi-Urban,Manager,142279,0 +37836,Male,23,Bachelors,10,31,43,85,24,5.0,6,40,Rural,Manager,25049,0 +37837,Male,35,Masters,13,7,88,4,0,0.0,1,72,Urban,Manager,93903,0 +37838,Female,22,PhD,0,81,6,31,1,4.0,1,46,Urban,Manager,45482,0 +37839,Male,54,Bachelors,5,42,80,81,4,4.0,1,84,Urban,Software Engineer,21578,1 +37840,Male,56,Bachelors,6,46,73,62,56,5.0,0,62,Urban,Software Engineer,130621,1 +37841,Male,27,Diploma,18,20,48,54,37,0.0,2,78,Semi-Urban,Data Analyst,138601,0 +37842,Other,29,High School,3,76,46,54,94,7.0,1,80,Rural,Software Engineer,34275,1 +37843,Female,52,Bachelors,12,79,47,40,48,2.0,7,68,Rural,ML Engineer,54266,0 +37844,Female,51,Bachelors,6,68,43,85,4,4.0,3,84,Rural,Data Analyst,122815,1 +37845,Male,44,Masters,10,79,3,66,37,3.0,3,41,Semi-Urban,HR Executive,119470,0 +37846,Male,22,Diploma,10,43,78,37,53,0.0,2,94,Semi-Urban,HR Executive,85823,1 +37847,Male,31,Bachelors,14,67,34,2,59,7.0,3,83,Semi-Urban,Software Engineer,91019,0 +37848,Male,22,Masters,12,47,48,47,31,4.0,1,75,Semi-Urban,Manager,110245,0 +37849,Female,28,Bachelors,12,90,37,32,98,5.0,6,36,Urban,Data Analyst,110662,0 +37850,Male,23,Diploma,6,57,27,30,99,1.0,7,5,Urban,Software Engineer,58875,0 +37851,Female,40,Masters,10,78,68,80,19,2.0,6,18,Urban,ML Engineer,47999,1 +37852,Male,29,Bachelors,0,52,23,5,66,7.0,0,0,Rural,ML Engineer,108500,0 +37853,Male,31,Masters,8,49,97,92,68,6.0,6,50,Semi-Urban,HR Executive,78314,1 +37854,Female,48,Bachelors,1,95,16,13,99,4.0,6,1,Urban,ML Engineer,28170,0 +37855,Male,46,Bachelors,18,75,51,85,28,1.0,7,60,Rural,Software Engineer,129067,1 +37856,Female,44,Bachelors,16,78,51,85,63,4.0,3,29,Semi-Urban,Software Engineer,34470,1 +37857,Male,57,Diploma,18,9,6,77,55,7.0,7,38,Rural,Data Analyst,140877,0 +37858,Female,33,Diploma,5,6,83,14,50,6.0,6,24,Rural,Software Engineer,112123,0 +37859,Female,40,Bachelors,7,43,44,67,97,4.0,5,20,Urban,HR Executive,23410,0 +37860,Male,51,Bachelors,5,42,80,44,70,6.0,2,79,Urban,ML Engineer,93169,1 +37861,Male,38,Bachelors,2,90,61,78,92,3.0,3,45,Urban,Software Engineer,146772,1 +37862,Male,46,Bachelors,19,64,48,85,68,4.0,1,78,Semi-Urban,Software Engineer,77588,1 +37863,Female,57,Bachelors,14,79,6,61,12,5.0,3,33,Semi-Urban,ML Engineer,96086,0 +37864,Male,22,Diploma,5,10,53,18,89,3.0,2,95,Semi-Urban,ML Engineer,107751,0 +37865,Male,47,High School,7,43,23,60,92,1.0,4,28,Semi-Urban,Manager,62476,0 +37866,Female,39,Masters,9,46,80,92,63,1.0,3,29,Semi-Urban,Software Engineer,128674,1 +37867,Female,38,Bachelors,11,38,22,7,26,3.0,6,33,Urban,Data Analyst,133739,0 +37868,Female,23,Bachelors,17,3,44,46,33,7.0,6,4,Urban,ML Engineer,87824,0 +37869,Male,46,Masters,9,27,72,93,68,2.0,1,39,Semi-Urban,Software Engineer,96013,0 +37870,Male,45,Bachelors,13,39,38,22,2,9.0,1,78,Rural,Manager,73007,0 +37871,Female,59,Masters,17,90,78,17,67,2.0,3,37,Urban,ML Engineer,87730,0 +37872,Male,21,Bachelors,10,87,8,36,91,5.0,1,75,Urban,Manager,20644,0 +37873,Female,21,Bachelors,2,24,77,33,58,4.0,6,74,Semi-Urban,Manager,96023,0 +37874,Female,50,Diploma,11,60,84,40,22,2.0,5,18,Rural,Data Analyst,67874,0 +37875,Male,22,High School,11,45,65,91,95,2.0,6,38,Urban,Manager,145304,1 +37876,Male,48,Bachelors,10,61,92,31,89,6.0,4,19,Rural,Data Analyst,52865,0 +37877,Male,47,Bachelors,0,97,37,47,14,7.0,0,4,Urban,Data Analyst,107167,0 +37878,Male,28,Bachelors,8,90,32,92,5,4.0,2,50,Urban,ML Engineer,50141,1 +37879,Male,45,Masters,1,76,12,23,77,9.0,0,64,Semi-Urban,HR Executive,147736,0 +37880,Female,39,Bachelors,18,73,6,86,58,2.0,5,90,Rural,HR Executive,123765,1 +37881,Male,33,High School,8,38,18,11,93,5.0,1,13,Urban,Software Engineer,57550,0 +37882,Male,51,Bachelors,10,49,39,87,5,8.0,3,12,Urban,HR Executive,21385,0 +37883,Male,24,Diploma,15,73,66,58,47,4.0,3,53,Semi-Urban,Manager,61398,1 +37884,Male,26,Bachelors,7,90,29,22,93,4.0,3,14,Rural,Data Analyst,103577,0 +37885,Male,55,Bachelors,3,91,60,63,20,1.0,5,73,Urban,HR Executive,129073,1 +37886,Male,33,Bachelors,7,53,22,3,15,7.0,3,6,Rural,Data Analyst,72437,0 +37887,Male,28,Masters,15,75,69,22,90,2.0,2,62,Semi-Urban,Software Engineer,24260,0 +37888,Male,43,Bachelors,3,27,46,70,3,7.0,5,54,Urban,ML Engineer,115585,0 +37889,Male,55,Diploma,14,86,90,67,43,3.0,6,47,Semi-Urban,Manager,37236,1 +37890,Female,33,Diploma,18,62,49,96,74,9.0,1,8,Urban,ML Engineer,68180,0 +37891,Male,42,High School,11,73,99,81,80,0.0,7,16,Urban,Software Engineer,32003,1 +37892,Male,49,High School,1,99,52,24,15,8.0,7,65,Urban,Data Analyst,140251,1 +37893,Female,26,Bachelors,0,90,97,69,21,7.0,5,15,Semi-Urban,Manager,68419,1 +37894,Female,36,High School,19,87,28,47,49,1.0,5,22,Urban,ML Engineer,50524,0 +37895,Male,43,Bachelors,1,26,91,69,6,8.0,3,1,Rural,Data Analyst,148593,0 +37896,Male,59,Bachelors,11,53,68,61,30,2.0,1,81,Urban,Data Analyst,103736,1 +37897,Female,52,Bachelors,5,83,65,98,79,6.0,3,58,Semi-Urban,Data Analyst,59625,1 +37898,Male,43,Bachelors,8,94,51,7,13,6.0,7,8,Urban,ML Engineer,69639,0 +37899,Male,23,High School,1,40,46,57,25,3.0,0,90,Urban,Software Engineer,134066,0 +37900,Male,29,Diploma,15,80,91,24,91,8.0,3,53,Semi-Urban,Data Analyst,53417,1 +37901,Female,26,Bachelors,10,46,64,47,39,3.0,4,69,Urban,Software Engineer,37902,0 +37902,Male,24,Masters,3,98,39,92,27,9.0,1,4,Rural,ML Engineer,102610,0 +37903,Male,40,Diploma,5,74,79,27,15,6.0,6,9,Semi-Urban,Data Analyst,133904,0 +37904,Male,57,High School,2,49,98,32,5,5.0,4,57,Urban,ML Engineer,120381,1 +37905,Male,25,Diploma,6,69,0,41,46,8.0,3,4,Rural,Manager,100868,0 +37906,Male,34,Bachelors,13,64,55,89,42,9.0,2,94,Rural,Software Engineer,143280,1 +37907,Female,23,Bachelors,1,34,95,32,68,6.0,1,65,Rural,HR Executive,27258,0 +37908,Male,39,Bachelors,7,14,14,28,49,0.0,4,44,Rural,ML Engineer,113952,0 +37909,Other,47,Bachelors,3,53,7,56,13,6.0,3,84,Semi-Urban,Software Engineer,99648,0 +37910,Male,50,Masters,11,68,35,48,93,1.0,6,88,Rural,HR Executive,125458,1 +37911,Male,55,Masters,17,98,59,11,59,9.0,0,46,Urban,ML Engineer,60495,0 +37912,Male,22,Masters,0,69,22,7,13,5.0,4,53,Semi-Urban,Manager,24084,0 +37913,Male,22,Bachelors,1,63,26,10,37,1.0,2,89,Urban,Data Analyst,122142,0 +37914,Male,35,Diploma,17,27,11,94,80,1.0,7,70,Urban,Manager,121658,0 +37915,Female,28,Diploma,9,52,15,69,54,8.0,7,25,Rural,Manager,70811,0 +37916,Male,50,PhD,6,66,2,59,22,4.0,7,56,Urban,Data Analyst,47324,0 +37917,Male,58,Bachelors,2,55,34,9,44,7.0,7,83,Rural,Manager,54390,0 +37918,Female,43,Diploma,19,29,12,53,7,7.0,7,68,Semi-Urban,HR Executive,146063,0 +37919,Male,51,Diploma,2,0,73,98,86,3.0,7,87,Urban,HR Executive,79799,1 +37920,Male,53,Diploma,18,59,23,88,4,5.0,6,43,Semi-Urban,Manager,112868,0 +37921,Male,24,PhD,18,23,20,26,83,7.0,5,60,Urban,Data Analyst,102018,0 +37922,Male,59,Bachelors,19,79,24,37,36,4.0,7,29,Urban,Manager,52876,0 +37923,Female,30,Bachelors,1,43,47,65,87,2.0,1,50,Semi-Urban,HR Executive,147945,0 +37924,Male,21,Bachelors,12,40,43,77,18,7.0,2,83,Semi-Urban,Manager,69226,1 +37925,Female,46,Bachelors,4,68,46,64,45,2.0,5,8,Urban,HR Executive,86809,0 +37926,Female,59,Diploma,16,42,28,19,87,7.0,3,3,Urban,ML Engineer,99367,0 +37927,Male,53,High School,17,68,99,64,48,2.0,0,76,Rural,Data Analyst,139792,1 +37928,Male,48,Diploma,6,27,30,16,21,3.0,1,80,Rural,Data Analyst,137091,0 +37929,Female,50,Bachelors,13,15,11,21,16,4.0,6,9,Urban,ML Engineer,51140,0 +37930,Female,29,Bachelors,19,28,28,69,11,2.0,1,66,Urban,ML Engineer,56196,0 +37931,Male,55,Masters,8,41,86,94,39,4.0,2,90,Urban,HR Executive,29720,1 +37932,Female,54,Diploma,19,82,99,48,30,0.0,5,95,Urban,Software Engineer,25769,1 +37933,Female,26,Bachelors,13,48,71,99,90,0.0,7,62,Urban,Software Engineer,84526,1 +37934,Male,39,Bachelors,2,16,23,98,91,7.0,7,29,Urban,Software Engineer,77883,0 +37935,Female,50,Masters,18,54,10,46,97,8.0,3,71,Urban,HR Executive,130654,0 +37936,Male,39,High School,3,46,21,94,74,4.0,7,16,Semi-Urban,Software Engineer,116613,0 +37937,Male,31,Masters,4,46,49,90,44,5.0,6,45,Semi-Urban,Data Analyst,92853,0 +37938,Male,38,High School,15,21,52,31,38,5.0,5,6,Urban,ML Engineer,59764,0 +37939,Male,37,Diploma,12,13,90,75,52,5.0,5,4,Urban,Manager,23161,0 +37940,Female,30,Bachelors,19,41,34,80,33,5.0,3,26,Urban,HR Executive,85278,0 +37941,Male,36,Bachelors,13,74,78,96,10,8.0,1,81,Urban,Manager,59212,1 +37942,Male,27,Masters,19,88,94,45,36,3.0,6,39,Urban,HR Executive,29526,1 +37943,Female,52,Bachelors,18,83,39,38,4,1.0,6,41,Semi-Urban,HR Executive,76015,0 +37944,Male,29,Diploma,19,14,61,41,76,7.0,0,21,Urban,ML Engineer,91337,0 +37945,Male,39,Diploma,8,34,24,45,39,5.0,7,90,Rural,Software Engineer,99581,0 +37946,Male,45,High School,15,85,9,5,18,6.0,4,74,Urban,HR Executive,77744,0 +37947,Male,54,High School,6,1,28,7,16,2.0,1,25,Urban,HR Executive,21820,0 +37948,Female,21,Masters,14,50,8,81,47,6.0,0,4,Urban,Manager,99871,0 +37949,Male,23,High School,3,59,40,82,92,9.0,5,48,Semi-Urban,Data Analyst,57769,0 +37950,Male,52,Bachelors,6,31,46,15,31,0.0,2,90,Urban,Manager,80956,0 +37951,Male,36,Bachelors,5,8,86,30,12,7.0,5,17,Semi-Urban,HR Executive,116928,0 +37952,Male,42,Bachelors,6,92,16,67,59,0.0,0,26,Rural,ML Engineer,63721,0 +37953,Male,25,Masters,11,51,70,78,97,6.0,6,56,Urban,Manager,41074,1 +37954,Male,27,Bachelors,13,31,60,39,39,0.0,4,70,Semi-Urban,Data Analyst,112404,0 +37955,Male,54,Bachelors,17,32,23,56,86,1.0,0,61,Urban,ML Engineer,20347,0 +37956,Male,35,Masters,11,58,33,96,22,7.0,5,74,Urban,Manager,62868,1 +37957,Male,55,Bachelors,19,42,41,31,24,4.0,7,82,Urban,Software Engineer,38176,0 +37958,Male,52,Bachelors,11,34,26,93,39,3.0,0,19,Semi-Urban,Data Analyst,125222,0 +37959,Male,45,Masters,0,7,99,63,11,9.0,1,52,Urban,Manager,101987,0 +37960,Female,41,Masters,16,15,5,55,13,7.0,5,45,Urban,Data Analyst,103866,0 +37961,Female,35,Diploma,2,15,12,35,77,0.0,6,95,Urban,ML Engineer,27792,0 +37962,Male,50,Diploma,17,86,32,85,51,3.0,4,60,Urban,Data Analyst,67017,1 +37963,Female,34,Bachelors,8,83,53,29,29,3.0,7,43,Urban,Data Analyst,143618,0 +37964,Female,50,High School,13,99,61,23,87,7.0,6,58,Urban,Manager,104577,1 +37965,Male,43,PhD,14,21,89,2,51,1.0,1,21,Urban,Manager,85911,0 +37966,Female,24,Bachelors,10,11,34,76,95,2.0,1,42,Urban,ML Engineer,63105,0 +37967,Male,47,Masters,11,50,15,0,0,3.0,6,44,Urban,ML Engineer,44538,0 +37968,Female,44,Masters,7,51,57,17,70,3.0,5,48,Urban,ML Engineer,121911,0 +37969,Male,50,Diploma,0,96,23,85,19,5.0,5,25,Urban,Manager,113304,0 +37970,Other,34,Diploma,15,80,16,74,31,7.0,7,70,Semi-Urban,Manager,36626,0 +37971,Male,28,Bachelors,5,43,6,58,37,9.0,2,57,Urban,ML Engineer,136249,0 +37972,Male,24,High School,16,91,36,65,8,2.0,6,84,Semi-Urban,Software Engineer,79138,1 +37973,Female,50,High School,16,37,34,30,23,7.0,2,51,Rural,Manager,107445,0 +37974,Female,52,Masters,17,33,39,29,6,6.0,5,90,Semi-Urban,ML Engineer,68844,0 +37975,Female,32,Masters,2,8,11,73,77,1.0,6,41,Urban,Data Analyst,100735,0 +37976,Female,34,Bachelors,2,86,6,83,35,4.0,5,5,Rural,Data Analyst,50717,0 +37977,Female,25,Bachelors,18,58,5,0,48,2.0,6,80,Urban,Software Engineer,65283,0 +37978,Female,47,High School,16,96,4,54,70,3.0,2,9,Urban,Manager,89566,0 +37979,Male,56,Bachelors,11,17,69,33,59,1.0,1,17,Urban,Data Analyst,73643,0 +37980,Male,31,Bachelors,10,68,38,95,97,3.0,2,86,Rural,ML Engineer,73943,1 +37981,Male,29,High School,0,46,36,91,57,2.0,6,88,Semi-Urban,Data Analyst,66035,1 +37982,Female,37,PhD,17,43,47,43,82,6.0,3,93,Rural,Software Engineer,113225,0 +37983,Male,27,Masters,17,52,21,32,0,2.0,2,50,Semi-Urban,Software Engineer,54236,0 +37984,Male,47,Diploma,12,81,15,67,11,7.0,2,87,Semi-Urban,Software Engineer,121558,1 +37985,Male,28,Masters,7,6,7,84,17,6.0,5,28,Semi-Urban,ML Engineer,24574,0 +37986,Female,47,Bachelors,9,3,34,50,30,2.0,2,69,Rural,Software Engineer,89202,0 +37987,Male,46,Diploma,14,22,93,75,88,1.0,6,85,Urban,ML Engineer,74215,1 +37988,Male,57,Bachelors,9,62,90,19,99,5.0,3,5,Rural,Data Analyst,138418,0 +37989,Male,23,Masters,13,62,59,27,48,0.0,3,60,Urban,Data Analyst,97703,0 +37990,Male,42,Diploma,15,73,19,81,68,9.0,0,92,Urban,ML Engineer,118525,1 +37991,Male,38,Bachelors,1,35,9,16,71,7.0,3,58,Semi-Urban,Manager,134784,0 +37992,Male,29,Bachelors,12,98,26,31,98,6.0,7,34,Urban,Software Engineer,137415,0 +37993,Male,49,Bachelors,2,90,22,40,70,8.0,5,22,Urban,Data Analyst,148853,0 +37994,Female,53,Bachelors,7,46,42,70,51,6.0,2,87,Semi-Urban,Data Analyst,125691,1 +37995,Female,27,PhD,3,30,83,92,56,4.0,2,13,Rural,Manager,37355,0 +37996,Male,53,Bachelors,19,60,68,41,71,2.0,3,99,Rural,Data Analyst,65403,1 +37997,Female,25,Bachelors,17,94,31,92,43,4.0,7,71,Urban,ML Engineer,74643,1 +37998,Female,57,Masters,4,70,42,36,92,5.0,0,15,Rural,Software Engineer,71583,0 +37999,Female,30,Bachelors,8,21,43,57,42,3.0,5,16,Urban,ML Engineer,64544,0 +38000,Male,28,Masters,1,32,57,19,48,4.0,1,92,Semi-Urban,ML Engineer,61426,0 +38001,Male,21,Diploma,16,81,68,85,89,9.0,4,7,Semi-Urban,HR Executive,25554,1 +38002,Female,37,Masters,10,19,65,13,65,3.0,4,39,Urban,Software Engineer,125057,0 +38003,Male,34,High School,4,70,95,1,18,7.0,3,99,Rural,Data Analyst,39604,1 +38004,Male,50,Bachelors,1,73,46,35,75,5.0,5,75,Urban,Data Analyst,54521,0 +38005,Male,41,Bachelors,13,7,98,48,66,8.0,1,40,Rural,Software Engineer,53878,0 +38006,Female,57,Diploma,11,55,1,98,99,2.0,7,52,Urban,ML Engineer,26252,0 +38007,Male,41,Masters,10,28,98,53,1,1.0,5,38,Urban,ML Engineer,46078,0 +38008,Male,29,Masters,1,10,96,48,46,8.0,0,43,Semi-Urban,ML Engineer,127886,0 +38009,Female,40,Bachelors,9,60,49,93,18,2.0,4,84,Rural,Data Analyst,96348,1 +38010,Female,32,High School,19,85,24,37,93,8.0,7,46,Urban,HR Executive,85864,0 +38011,Male,50,High School,17,77,30,85,65,8.0,2,47,Rural,HR Executive,137030,1 +38012,Male,22,Bachelors,8,84,4,33,82,4.0,7,7,Rural,HR Executive,92993,0 +38013,Female,24,Bachelors,1,63,49,86,36,7.0,2,15,Urban,Manager,33990,0 +38014,Male,52,High School,4,13,77,43,26,1.0,5,68,Rural,Data Analyst,111832,0 +38015,Female,23,Bachelors,2,66,40,97,66,2.0,3,38,Urban,HR Executive,116062,1 +38016,Female,51,Bachelors,10,31,91,76,34,6.0,3,3,Urban,Data Analyst,49544,0 +38017,Male,49,Bachelors,9,70,73,67,65,3.0,4,58,Urban,Data Analyst,104335,1 +38018,Male,34,PhD,18,66,91,15,81,2.0,2,6,Semi-Urban,Data Analyst,95401,0 +38019,Male,44,PhD,10,43,57,58,38,2.0,4,76,Urban,ML Engineer,96335,0 +38020,Female,52,Bachelors,0,20,41,71,24,2.0,2,10,Semi-Urban,Manager,122717,0 +38021,Male,33,Diploma,7,63,87,35,87,6.0,3,82,Rural,Software Engineer,104913,1 +38022,Male,38,Bachelors,16,2,80,80,82,9.0,4,92,Urban,Manager,131116,1 +38023,Male,42,Diploma,9,58,10,82,41,4.0,6,18,Urban,Manager,96742,0 +38024,Male,31,Bachelors,3,75,22,4,12,9.0,3,94,Urban,Manager,46356,0 +38025,Male,51,Bachelors,6,58,37,67,46,0.0,1,19,Rural,Data Analyst,32980,0 +38026,Male,44,Bachelors,11,12,8,18,98,4.0,3,30,Semi-Urban,Software Engineer,142441,0 +38027,Female,25,Bachelors,1,43,73,31,89,9.0,2,60,Urban,Data Analyst,108522,0 +38028,Male,28,High School,18,75,71,0,68,3.0,0,87,Semi-Urban,ML Engineer,86168,0 +38029,Male,33,Diploma,12,23,74,88,37,7.0,6,35,Urban,Software Engineer,85632,0 +38030,Female,34,Bachelors,19,39,18,45,95,1.0,0,24,Rural,Software Engineer,82730,0 +38031,Female,30,Masters,16,91,89,86,65,5.0,4,41,Urban,HR Executive,80427,1 +38032,Female,43,Bachelors,3,97,25,83,29,1.0,3,78,Semi-Urban,HR Executive,24910,1 +38033,Male,33,Bachelors,6,92,21,8,27,1.0,7,75,Rural,HR Executive,45445,0 +38034,Male,23,High School,16,51,51,39,86,2.0,2,54,Urban,Data Analyst,87264,0 +38035,Male,30,High School,7,48,92,92,92,1.0,5,31,Rural,HR Executive,111191,1 +38036,Female,59,Bachelors,10,26,53,93,15,7.0,5,35,Urban,HR Executive,98707,0 +38037,Female,46,High School,14,80,80,45,70,5.0,6,25,Semi-Urban,Data Analyst,97114,0 +38038,Female,54,Diploma,9,28,56,40,75,2.0,0,63,Semi-Urban,Software Engineer,90368,0 +38039,Male,48,Bachelors,15,19,16,81,82,2.0,2,81,Rural,Data Analyst,93137,0 +38040,Female,41,High School,8,30,6,68,28,1.0,6,94,Semi-Urban,Data Analyst,120962,0 +38041,Female,31,Bachelors,8,5,93,20,18,5.0,6,73,Semi-Urban,HR Executive,75062,0 +38042,Male,40,Masters,11,62,73,94,24,8.0,3,9,Semi-Urban,HR Executive,112659,1 +38043,Male,44,High School,10,70,91,33,35,8.0,1,99,Urban,Software Engineer,143387,1 +38044,Male,42,Bachelors,17,50,80,27,4,0.0,5,4,Semi-Urban,Manager,24031,0 +38045,Male,29,High School,14,96,29,80,75,6.0,7,88,Urban,ML Engineer,133517,1 +38046,Male,56,Diploma,17,57,5,53,40,4.0,3,31,Urban,Software Engineer,148539,0 +38047,Female,48,Bachelors,10,86,32,5,72,0.0,3,62,Urban,HR Executive,128165,0 +38048,Female,42,Bachelors,3,28,45,29,63,0.0,3,4,Rural,Data Analyst,58472,0 +38049,Female,51,Masters,17,40,8,9,55,1.0,1,59,Rural,Software Engineer,88115,0 +38050,Male,57,Diploma,14,3,84,70,92,6.0,5,12,Rural,Data Analyst,86521,0 +38051,Male,40,Masters,0,61,56,92,27,0.0,5,19,Urban,ML Engineer,97435,0 +38052,Female,41,Bachelors,12,76,84,1,32,6.0,0,9,Semi-Urban,Software Engineer,46171,0 +38053,Male,55,Bachelors,11,73,2,69,48,3.0,7,39,Urban,ML Engineer,27136,0 +38054,Male,29,Bachelors,11,29,77,23,91,0.0,1,13,Urban,Software Engineer,112247,0 +38055,Female,57,PhD,0,1,38,72,87,4.0,2,66,Semi-Urban,Software Engineer,72606,0 +38056,Male,57,High School,18,13,20,49,82,5.0,3,82,Urban,Manager,42602,0 +38057,Male,30,Bachelors,11,89,55,55,31,3.0,1,37,Semi-Urban,Manager,98567,1 +38058,Male,45,Bachelors,11,92,36,42,67,4.0,2,22,Urban,Software Engineer,27045,0 +38059,Female,30,Masters,7,9,49,3,55,8.0,1,65,Semi-Urban,ML Engineer,108343,0 +38060,Male,21,Bachelors,10,77,42,29,25,9.0,1,9,Semi-Urban,ML Engineer,67754,0 +38061,Male,32,High School,16,35,13,92,21,9.0,0,51,Urban,HR Executive,102370,0 +38062,Other,54,Masters,18,65,31,65,21,4.0,4,0,Semi-Urban,Data Analyst,145374,0 +38063,Male,41,Diploma,1,21,32,74,31,4.0,1,99,Urban,Data Analyst,32580,0 +38064,Male,51,Diploma,12,47,99,25,70,6.0,4,27,Urban,HR Executive,115801,0 +38065,Male,52,Diploma,14,88,72,36,75,2.0,6,23,Urban,Manager,132436,0 +38066,Male,35,High School,16,35,14,89,33,3.0,6,94,Urban,Software Engineer,138652,0 +38067,Male,40,Bachelors,9,72,47,85,42,5.0,3,84,Urban,HR Executive,129539,1 +38068,Female,54,PhD,3,69,28,64,30,5.0,6,71,Rural,Manager,142076,0 +38069,Male,27,PhD,19,22,87,0,97,3.0,1,30,Urban,HR Executive,85952,0 +38070,Female,48,Masters,12,89,93,48,23,9.0,2,74,Urban,Data Analyst,82300,1 +38071,Male,23,High School,12,98,41,25,42,2.0,6,48,Urban,Data Analyst,90225,0 +38072,Male,30,Bachelors,0,43,87,44,84,0.0,2,0,Urban,ML Engineer,27486,0 +38073,Male,42,PhD,1,55,44,94,80,4.0,0,39,Urban,Manager,78567,0 +38074,Male,40,PhD,7,99,91,69,37,5.0,5,36,Rural,Manager,110046,1 +38075,Male,38,Masters,9,66,1,39,59,2.0,1,44,Semi-Urban,Manager,99910,0 +38076,Male,52,Diploma,6,13,95,58,80,3.0,0,79,Rural,Software Engineer,41440,1 +38077,Male,24,Diploma,1,37,0,94,26,3.0,5,31,Urban,Software Engineer,22196,0 +38078,Female,53,Bachelors,7,61,11,36,49,0.0,1,59,Urban,Manager,91004,0 +38079,Male,22,Bachelors,19,50,49,17,20,7.0,7,91,Rural,ML Engineer,30570,0 +38080,Male,36,High School,0,72,18,13,90,0.0,6,59,Urban,Manager,96765,0 +38081,Female,28,Diploma,17,58,36,96,21,5.0,3,41,Semi-Urban,ML Engineer,120467,0 +38082,Male,57,Masters,6,61,65,11,80,4.0,3,35,Urban,Software Engineer,97322,0 +38083,Female,27,PhD,1,16,67,20,1,6.0,6,36,Urban,Manager,75626,0 +38084,Female,37,Bachelors,0,56,16,5,76,4.0,4,21,Urban,Data Analyst,57062,0 +38085,Other,46,Bachelors,14,70,10,86,90,5.0,7,83,Rural,Manager,98525,1 +38086,Male,34,Bachelors,15,35,99,63,24,6.0,6,60,Semi-Urban,Data Analyst,149116,1 +38087,Female,28,High School,8,49,37,57,10,5.0,4,98,Urban,HR Executive,31194,1 +38088,Female,39,Bachelors,7,56,41,54,93,0.0,2,5,Urban,Manager,43594,0 +38089,Female,48,Bachelors,1,70,34,48,97,8.0,0,53,Urban,Data Analyst,53534,0 +38090,Female,33,Bachelors,12,93,95,80,81,5.0,3,34,Urban,HR Executive,94230,1 +38091,Male,57,Bachelors,4,91,22,11,85,3.0,5,31,Urban,Manager,84237,0 +38092,Female,23,Bachelors,14,33,52,92,48,7.0,7,85,Urban,HR Executive,31778,1 +38093,Male,29,Bachelors,14,72,82,17,33,1.0,6,89,Semi-Urban,ML Engineer,125246,1 +38094,Male,34,Masters,17,95,2,59,75,8.0,5,47,Semi-Urban,Data Analyst,88952,0 +38095,Male,31,Diploma,4,15,53,24,18,7.0,3,91,Semi-Urban,ML Engineer,59354,0 +38096,Male,56,Bachelors,7,25,63,15,64,4.0,0,61,Rural,HR Executive,111268,0 +38097,Male,34,Masters,18,97,8,87,3,4.0,6,83,Urban,ML Engineer,96110,1 +38098,Other,42,Masters,17,38,77,41,95,0.0,2,74,Urban,Data Analyst,127180,0 +38099,Female,46,Bachelors,9,89,57,57,9,1.0,6,69,Urban,Software Engineer,28552,1 +38100,Female,52,Bachelors,0,90,81,89,98,1.0,4,69,Urban,Data Analyst,53793,1 +38101,Female,56,Diploma,0,63,26,43,43,3.0,6,88,Urban,Data Analyst,146356,0 +38102,Male,47,Bachelors,7,91,69,20,69,4.0,5,41,Semi-Urban,Manager,142714,0 +38103,Male,32,Diploma,18,94,50,64,84,3.0,4,80,Semi-Urban,Manager,59354,1 +38104,Male,56,Diploma,17,54,26,93,48,9.0,0,34,Urban,Manager,143498,0 +38105,Male,41,High School,4,61,31,5,25,0.0,3,43,Urban,Manager,33138,0 +38106,Female,23,Masters,3,24,65,96,72,7.0,0,3,Urban,Manager,117385,0 +38107,Female,51,Bachelors,2,92,62,93,82,7.0,1,67,Semi-Urban,HR Executive,60256,1 +38108,Male,39,High School,12,72,27,85,78,1.0,7,61,Semi-Urban,ML Engineer,75546,1 +38109,Male,38,Bachelors,9,40,79,8,15,2.0,6,17,Rural,Software Engineer,145377,0 +38110,Male,34,Bachelors,1,63,3,71,30,2.0,2,77,Semi-Urban,Software Engineer,93325,0 +38111,Male,56,PhD,12,90,94,13,2,3.0,2,96,Urban,Data Analyst,82703,1 +38112,Male,47,High School,1,63,79,69,99,9.0,5,91,Rural,Software Engineer,136225,1 +38113,Male,57,Bachelors,2,20,1,20,66,6.0,0,4,Urban,ML Engineer,131697,0 +38114,Male,24,Masters,18,52,56,67,12,3.0,2,75,Rural,Data Analyst,143953,1 +38115,Female,21,Diploma,0,9,58,47,83,9.0,0,11,Urban,Manager,113814,0 +38116,Male,40,Masters,9,68,6,0,91,2.0,6,2,Rural,Manager,120833,0 +38117,Female,24,Diploma,8,78,13,33,56,8.0,5,78,Rural,Manager,30704,0 +38118,Female,21,High School,16,14,20,40,46,0.0,3,37,Urban,HR Executive,88134,0 +38119,Male,45,Diploma,10,73,8,21,9,5.0,3,72,Semi-Urban,Manager,121035,0 +38120,Female,39,Bachelors,15,9,51,27,76,7.0,3,42,Urban,ML Engineer,60083,0 +38121,Male,43,Masters,12,58,74,28,60,4.0,1,63,Semi-Urban,Manager,72044,0 +38122,Male,53,Masters,9,78,76,95,91,9.0,4,16,Urban,Manager,41622,1 +38123,Male,37,Diploma,17,11,65,96,45,6.0,3,88,Urban,HR Executive,83600,1 +38124,Female,53,Masters,6,41,39,70,82,5.0,7,54,Semi-Urban,ML Engineer,49641,0 +38125,Male,31,Diploma,16,2,2,70,93,6.0,1,2,Urban,Manager,101283,0 +38126,Male,58,Bachelors,4,11,90,48,62,5.0,4,73,Rural,ML Engineer,132651,0 +38127,Male,59,High School,1,12,74,26,17,3.0,1,51,Semi-Urban,Manager,91732,0 +38128,Male,27,High School,4,94,32,31,71,6.0,3,4,Urban,Software Engineer,70207,0 +38129,Female,41,Bachelors,10,88,72,9,64,2.0,7,51,Urban,Manager,87462,0 +38130,Female,50,High School,10,25,72,24,30,7.0,5,47,Urban,Manager,87201,0 +38131,Male,45,Masters,18,86,91,24,44,1.0,7,43,Semi-Urban,ML Engineer,108390,1 +38132,Male,28,Masters,15,63,18,57,78,6.0,5,21,Urban,ML Engineer,38623,0 +38133,Female,50,Bachelors,17,68,39,14,8,6.0,3,64,Semi-Urban,HR Executive,85208,0 +38134,Female,28,Bachelors,2,35,6,51,11,8.0,4,22,Urban,HR Executive,123717,0 +38135,Female,40,Masters,10,81,61,67,72,4.0,4,47,Semi-Urban,Data Analyst,97077,1 +38136,Male,55,Masters,0,81,91,74,49,6.0,6,34,Urban,Software Engineer,70082,1 +38137,Male,23,Masters,6,57,1,55,63,4.0,5,58,Semi-Urban,ML Engineer,96721,0 +38138,Female,37,Bachelors,14,71,67,57,52,7.0,5,42,Urban,Data Analyst,99900,0 +38139,Male,45,Bachelors,5,89,34,24,4,7.0,5,55,Rural,ML Engineer,61951,0 +38140,Female,24,Bachelors,2,78,62,78,76,8.0,6,95,Urban,Data Analyst,60166,1 +38141,Female,52,Bachelors,8,31,83,57,34,3.0,7,65,Semi-Urban,Data Analyst,133734,0 +38142,Male,32,Bachelors,7,58,17,28,44,6.0,0,78,Urban,HR Executive,39819,0 +38143,Female,24,Masters,18,48,28,34,79,5.0,3,6,Urban,Software Engineer,106998,0 +38144,Male,35,Bachelors,13,23,38,37,94,5.0,2,44,Urban,Manager,107468,0 +38145,Female,47,Bachelors,11,29,12,98,66,0.0,7,32,Urban,HR Executive,129476,0 +38146,Other,26,Bachelors,14,98,28,93,34,4.0,0,26,Urban,ML Engineer,103015,1 +38147,Other,53,Bachelors,15,99,50,74,90,5.0,6,34,Semi-Urban,Data Analyst,39329,1 +38148,Female,27,Masters,13,69,81,55,4,7.0,6,52,Urban,Software Engineer,104170,1 +38149,Male,23,Masters,16,70,79,30,7,3.0,2,18,Urban,Manager,85595,0 +38150,Female,55,Diploma,13,24,25,85,50,8.0,7,35,Semi-Urban,HR Executive,30953,0 +38151,Female,39,Diploma,15,79,25,50,59,3.0,2,64,Rural,Manager,43639,0 +38152,Male,25,Diploma,12,17,1,51,97,8.0,3,81,Urban,HR Executive,123053,0 +38153,Male,34,Bachelors,16,3,7,34,65,3.0,1,47,Rural,ML Engineer,94210,0 +38154,Male,25,Diploma,18,67,47,23,0,8.0,1,54,Urban,HR Executive,129364,0 +38155,Male,27,Bachelors,7,5,85,95,90,3.0,1,4,Urban,ML Engineer,51517,0 +38156,Female,57,Bachelors,11,85,40,71,94,0.0,0,52,Urban,Manager,88381,1 +38157,Male,52,Masters,14,13,41,61,51,1.0,6,35,Urban,HR Executive,124888,0 +38158,Male,25,Bachelors,3,68,58,0,22,4.0,1,86,Urban,Data Analyst,127476,0 +38159,Male,30,Bachelors,19,9,62,5,91,2.0,7,92,Rural,Manager,50362,0 +38160,Female,30,High School,12,23,18,99,48,6.0,3,6,Rural,HR Executive,48915,0 +38161,Female,38,Bachelors,9,83,83,28,46,6.0,7,27,Urban,ML Engineer,76743,0 +38162,Male,40,Bachelors,0,84,55,30,25,4.0,4,19,Urban,ML Engineer,101301,0 +38163,Female,31,High School,9,57,81,9,70,2.0,1,28,Urban,HR Executive,47088,0 +38164,Male,59,High School,4,60,24,55,72,8.0,6,91,Rural,Manager,93383,0 +38165,Male,29,Diploma,5,34,58,85,45,9.0,0,67,Semi-Urban,HR Executive,140574,1 +38166,Female,47,Bachelors,0,12,83,78,99,7.0,6,5,Semi-Urban,HR Executive,101948,0 +38167,Male,34,Bachelors,12,77,45,22,69,0.0,4,68,Urban,HR Executive,35153,0 +38168,Male,31,Masters,2,9,0,87,17,1.0,1,43,Semi-Urban,Data Analyst,26127,0 +38169,Male,58,High School,1,80,99,60,28,5.0,6,75,Semi-Urban,Software Engineer,42984,1 +38170,Male,33,High School,6,22,38,81,22,2.0,6,89,Rural,Data Analyst,119711,0 +38171,Male,30,High School,18,33,33,82,33,1.0,3,17,Semi-Urban,Manager,83626,0 +38172,Male,35,Bachelors,0,38,58,93,27,0.0,1,90,Urban,Software Engineer,44824,1 +38173,Female,28,Bachelors,0,6,48,99,45,9.0,6,43,Urban,ML Engineer,59509,0 +38174,Male,44,Masters,11,14,17,9,64,4.0,3,27,Semi-Urban,Software Engineer,106637,0 +38175,Male,53,Bachelors,15,93,35,56,34,2.0,4,63,Semi-Urban,Software Engineer,62932,1 +38176,Male,54,Masters,13,11,2,62,51,1.0,2,1,Semi-Urban,Software Engineer,29887,0 +38177,Female,35,Masters,16,26,23,22,90,1.0,3,53,Urban,Software Engineer,148807,0 +38178,Female,58,Bachelors,3,63,61,26,91,0.0,2,99,Semi-Urban,HR Executive,39510,1 +38179,Other,31,Bachelors,12,69,5,13,80,4.0,2,12,Urban,Software Engineer,139818,0 +38180,Male,28,Bachelors,0,48,99,60,94,7.0,4,96,Rural,ML Engineer,73546,1 +38181,Female,38,Diploma,1,7,52,82,38,6.0,7,15,Urban,Manager,73706,0 +38182,Male,26,High School,18,83,41,74,4,1.0,1,10,Semi-Urban,Software Engineer,67064,0 +38183,Female,34,High School,7,0,5,82,5,6.0,5,23,Rural,Software Engineer,24337,0 +38184,Male,42,Bachelors,15,41,79,68,71,6.0,3,82,Semi-Urban,ML Engineer,103696,1 +38185,Female,21,Bachelors,19,94,21,39,11,8.0,5,89,Rural,ML Engineer,106032,1 +38186,Male,36,Diploma,12,67,60,18,13,6.0,1,22,Urban,HR Executive,128428,0 +38187,Male,38,High School,15,30,75,63,64,4.0,6,12,Semi-Urban,HR Executive,107008,0 +38188,Female,42,Masters,16,6,62,99,87,4.0,5,57,Urban,HR Executive,104448,0 +38189,Female,53,Bachelors,16,59,95,96,73,1.0,7,46,Urban,Data Analyst,99339,1 +38190,Male,38,Bachelors,2,29,44,54,82,9.0,3,1,Urban,Software Engineer,42623,0 +38191,Female,44,Bachelors,7,90,74,60,60,1.0,7,0,Rural,HR Executive,136587,0 +38192,Male,51,Bachelors,16,98,54,50,4,0.0,6,66,Rural,ML Engineer,77437,1 +38193,Female,53,Masters,11,76,18,68,73,6.0,0,28,Urban,Data Analyst,67712,0 +38194,Other,26,Masters,5,81,8,60,31,6.0,6,74,Urban,HR Executive,29913,0 +38195,Male,37,Diploma,11,81,15,35,66,1.0,5,33,Urban,Manager,60139,0 +38196,Male,54,Bachelors,10,69,91,21,50,3.0,3,12,Urban,HR Executive,84326,0 +38197,Male,57,Bachelors,1,80,78,55,74,3.0,1,41,Rural,HR Executive,76827,1 +38198,Male,40,Masters,13,39,98,39,7,9.0,5,84,Urban,Software Engineer,111740,1 +38199,Female,24,Bachelors,15,12,39,86,73,4.0,6,84,Semi-Urban,Manager,39006,0 +38200,Female,44,Bachelors,0,41,59,54,1,9.0,6,59,Rural,Software Engineer,127356,0 +38201,Other,31,PhD,6,72,82,41,96,5.0,3,70,Urban,ML Engineer,129104,1 +38202,Male,42,Masters,4,3,29,17,89,2.0,4,21,Rural,HR Executive,142111,0 +38203,Male,47,Bachelors,11,85,71,67,81,9.0,5,96,Urban,HR Executive,71214,1 +38204,Male,56,High School,12,19,11,91,64,7.0,5,93,Urban,Software Engineer,54929,0 +38205,Female,49,Masters,9,80,28,34,57,3.0,3,40,Rural,Manager,69231,0 +38206,Male,31,Bachelors,13,48,91,49,9,5.0,6,3,Rural,Data Analyst,63565,0 +38207,Other,51,Masters,6,39,15,38,89,6.0,5,4,Urban,HR Executive,78169,0 +38208,Male,22,Bachelors,13,6,92,66,50,3.0,7,5,Urban,HR Executive,85968,0 +38209,Female,36,Diploma,8,32,61,58,40,3.0,7,92,Urban,Software Engineer,47245,1 +38210,Male,38,Bachelors,9,31,49,82,18,4.0,3,36,Urban,HR Executive,129878,0 +38211,Female,32,Masters,9,65,70,96,93,2.0,0,93,Semi-Urban,Software Engineer,145650,1 +38212,Male,59,Diploma,2,58,74,86,21,9.0,7,2,Urban,ML Engineer,124994,0 +38213,Female,33,Masters,5,49,69,31,49,0.0,4,82,Rural,Software Engineer,115601,0 +38214,Female,50,PhD,14,20,88,61,78,7.0,0,33,Urban,Manager,38998,0 +38215,Male,38,High School,0,35,21,68,36,2.0,3,47,Urban,HR Executive,140148,0 +38216,Male,25,Bachelors,10,61,40,78,63,3.0,5,78,Semi-Urban,Manager,85636,1 +38217,Female,50,Bachelors,18,57,92,68,29,1.0,6,13,Semi-Urban,Data Analyst,136418,0 +38218,Male,57,Bachelors,12,23,68,90,81,1.0,1,21,Semi-Urban,Data Analyst,113461,0 +38219,Female,23,Bachelors,11,98,26,10,69,5.0,5,59,Urban,HR Executive,21766,0 +38220,Female,21,High School,8,11,95,4,71,2.0,3,48,Semi-Urban,Software Engineer,118485,0 +38221,Male,55,Masters,5,45,69,62,69,4.0,2,33,Urban,Manager,120735,0 +38222,Male,28,Bachelors,19,2,81,36,63,1.0,3,52,Semi-Urban,ML Engineer,123081,0 +38223,Female,28,Bachelors,11,3,41,22,85,5.0,0,80,Urban,Software Engineer,149369,0 +38224,Female,56,Bachelors,3,39,44,31,58,2.0,2,83,Urban,Data Analyst,134151,0 +38225,Female,31,Diploma,8,53,64,16,76,3.0,3,92,Semi-Urban,HR Executive,117419,0 +38226,Male,30,PhD,6,96,36,38,96,5.0,2,44,Urban,Software Engineer,144001,0 +38227,Female,37,Diploma,3,47,36,40,79,5.0,1,50,Rural,Software Engineer,73262,0 +38228,Male,56,Diploma,3,93,6,79,12,2.0,7,23,Urban,Manager,96760,0 +38229,Female,50,Bachelors,5,97,66,70,65,1.0,4,87,Semi-Urban,HR Executive,126861,1 +38230,Male,33,Bachelors,11,6,28,37,20,7.0,5,50,Urban,ML Engineer,37151,0 +38231,Male,30,Masters,12,16,96,65,85,3.0,1,98,Rural,ML Engineer,25415,1 +38232,Male,23,Bachelors,6,4,6,58,22,4.0,3,7,Urban,Manager,141573,0 +38233,Male,52,Masters,19,2,71,88,14,9.0,0,35,Urban,ML Engineer,66674,0 +38234,Other,38,Diploma,17,35,21,62,55,9.0,1,9,Urban,Manager,44027,0 +38235,Male,56,Masters,15,2,31,39,89,4.0,6,3,Urban,Data Analyst,99558,0 +38236,Male,56,Masters,13,38,22,58,95,2.0,6,84,Rural,Software Engineer,52429,0 +38237,Male,39,High School,4,13,28,67,51,6.0,3,25,Urban,ML Engineer,102003,0 +38238,Male,52,High School,1,61,50,45,33,8.0,2,59,Rural,Data Analyst,132928,0 +38239,Male,56,Diploma,15,16,85,65,27,4.0,7,27,Urban,HR Executive,47728,0 +38240,Male,24,Diploma,7,34,81,47,49,3.0,1,73,Semi-Urban,Manager,96990,1 +38241,Male,25,Bachelors,14,10,74,25,44,5.0,2,10,Urban,Data Analyst,60225,0 +38242,Male,52,PhD,16,6,0,24,47,8.0,2,72,Rural,Software Engineer,101937,0 +38243,Male,27,Diploma,3,94,4,2,82,8.0,2,73,Urban,Manager,74021,0 +38244,Male,28,Bachelors,13,3,20,36,85,4.0,4,43,Semi-Urban,ML Engineer,77657,0 +38245,Female,23,Masters,16,38,42,95,42,4.0,4,44,Urban,ML Engineer,102568,0 +38246,Female,52,Bachelors,16,25,26,81,83,3.0,1,96,Semi-Urban,HR Executive,68224,0 +38247,Female,56,High School,10,12,58,63,80,6.0,5,83,Urban,ML Engineer,47871,0 +38248,Other,54,PhD,7,38,24,61,56,3.0,1,29,Urban,Manager,33728,0 +38249,Female,58,Bachelors,0,93,0,40,24,2.0,0,80,Urban,HR Executive,99209,0 +38250,Male,53,Diploma,5,93,2,10,44,1.0,3,14,Rural,HR Executive,23384,0 +38251,Male,44,Diploma,3,44,54,42,91,1.0,7,59,Urban,Manager,37392,0 +38252,Female,40,Diploma,10,47,3,46,9,0.0,2,98,Semi-Urban,Data Analyst,67535,0 +38253,Female,31,Bachelors,9,2,68,86,94,3.0,2,25,Rural,HR Executive,59479,0 +38254,Male,59,Bachelors,8,81,41,14,13,1.0,3,35,Urban,Manager,76846,0 +38255,Male,22,Bachelors,13,11,34,94,78,2.0,5,42,Urban,ML Engineer,33896,0 +38256,Other,21,Diploma,12,15,25,58,39,7.0,3,7,Urban,ML Engineer,68517,0 +38257,Female,27,Masters,12,96,69,17,97,5.0,5,75,Rural,HR Executive,145708,1 +38258,Male,34,Bachelors,16,6,87,28,69,8.0,0,22,Urban,HR Executive,83790,0 +38259,Other,23,Masters,8,34,44,3,7,3.0,5,17,Urban,HR Executive,58214,0 +38260,Other,36,PhD,1,90,35,95,71,4.0,5,96,Semi-Urban,Software Engineer,116117,1 +38261,Male,51,Diploma,8,92,51,96,54,5.0,1,18,Rural,HR Executive,90137,1 +38262,Female,36,Bachelors,5,86,7,89,44,9.0,4,46,Urban,HR Executive,38830,0 +38263,Female,22,High School,2,0,47,90,13,9.0,5,64,Urban,Software Engineer,83314,0 +38264,Male,41,Bachelors,19,56,17,75,63,0.0,6,75,Urban,HR Executive,101371,0 +38265,Female,54,Diploma,12,30,62,29,73,3.0,2,65,Urban,HR Executive,81944,0 +38266,Male,30,Bachelors,7,38,16,66,48,4.0,7,51,Rural,Manager,111643,0 +38267,Female,29,High School,1,4,19,29,43,5.0,4,46,Rural,ML Engineer,85863,0 +38268,Female,34,Diploma,11,0,50,61,81,3.0,4,87,Urban,ML Engineer,43651,0 +38269,Male,36,Diploma,14,84,49,78,56,9.0,4,2,Urban,Manager,52111,0 +38270,Male,49,High School,18,40,99,7,63,2.0,1,94,Urban,ML Engineer,34788,1 +38271,Female,39,High School,8,98,52,81,91,4.0,5,28,Rural,ML Engineer,120767,1 +38272,Other,42,High School,2,2,2,12,15,5.0,0,27,Urban,HR Executive,79014,0 +38273,Male,44,Diploma,18,65,39,77,94,0.0,5,66,Urban,Data Analyst,77553,1 +38274,Female,37,High School,11,63,43,94,83,9.0,2,21,Urban,Software Engineer,111593,0 +38275,Male,58,Bachelors,12,77,76,98,45,4.0,4,86,Semi-Urban,ML Engineer,61444,1 +38276,Male,29,Diploma,15,89,49,14,98,4.0,4,59,Urban,Manager,28219,0 +38277,Female,50,Bachelors,7,11,4,47,62,2.0,7,72,Urban,Manager,32979,0 +38278,Female,47,Bachelors,12,60,64,33,63,1.0,6,23,Semi-Urban,Manager,42752,0 +38279,Female,57,Bachelors,17,91,37,79,97,8.0,5,62,Urban,Data Analyst,111485,1 +38280,Male,31,Bachelors,8,83,88,37,16,2.0,2,7,Semi-Urban,ML Engineer,136132,0 +38281,Male,26,Diploma,0,30,48,94,71,3.0,5,28,Rural,HR Executive,40841,0 +38282,Female,42,High School,8,96,47,78,38,1.0,7,13,Urban,Software Engineer,126161,0 +38283,Male,46,Masters,12,1,1,72,63,0.0,3,94,Rural,Manager,23719,0 +38284,Male,35,High School,11,66,5,9,49,1.0,1,75,Urban,Data Analyst,147840,0 +38285,Female,35,Bachelors,9,71,89,78,11,1.0,2,92,Urban,HR Executive,66071,1 +38286,Female,30,Bachelors,3,11,80,35,81,1.0,1,19,Urban,Software Engineer,135688,0 +38287,Male,26,Masters,0,87,48,37,45,6.0,1,45,Rural,Manager,80617,0 +38288,Male,58,Bachelors,7,84,38,97,76,8.0,3,43,Urban,Manager,145130,1 +38289,Female,46,Diploma,18,71,39,31,42,3.0,3,85,Semi-Urban,HR Executive,140389,0 +38290,Other,37,High School,8,96,74,53,7,4.0,4,2,Rural,Data Analyst,40619,0 +38291,Male,25,Bachelors,1,74,45,98,6,4.0,0,80,Rural,ML Engineer,87220,1 +38292,Male,22,Bachelors,12,5,22,18,49,3.0,0,16,Urban,ML Engineer,79650,0 +38293,Male,46,High School,19,1,10,60,72,4.0,7,57,Urban,Manager,84165,0 +38294,Female,37,Bachelors,17,45,23,49,72,2.0,6,10,Rural,Data Analyst,78270,0 +38295,Male,35,High School,17,3,14,0,64,6.0,7,26,Rural,Software Engineer,46481,0 +38296,Female,46,Bachelors,14,86,22,18,39,2.0,1,61,Urban,Software Engineer,100862,0 +38297,Male,44,High School,10,34,82,94,24,1.0,5,97,Urban,HR Executive,35145,1 +38298,Male,59,High School,12,33,29,68,63,4.0,1,52,Rural,Manager,132475,0 +38299,Female,47,Masters,18,26,42,43,87,4.0,6,50,Urban,Manager,81667,0 +38300,Male,58,Bachelors,15,22,42,73,40,8.0,6,41,Rural,ML Engineer,104980,0 +38301,Female,33,Bachelors,0,91,87,86,53,7.0,0,59,Semi-Urban,Software Engineer,133885,1 +38302,Male,28,High School,16,88,46,60,9,6.0,7,9,Semi-Urban,HR Executive,30799,0 +38303,Male,32,Bachelors,8,68,86,46,10,8.0,7,0,Urban,Data Analyst,138449,0 +38304,Male,49,High School,2,61,22,99,87,5.0,0,51,Rural,Manager,124003,0 +38305,Male,39,Bachelors,8,90,65,86,89,0.0,2,33,Urban,Software Engineer,35710,1 +38306,Male,25,PhD,2,85,83,10,23,3.0,6,59,Urban,ML Engineer,129474,1 +38307,Female,56,Bachelors,17,81,10,19,92,0.0,4,71,Semi-Urban,Data Analyst,54625,0 +38308,Male,42,High School,3,88,76,31,44,8.0,3,99,Urban,HR Executive,34222,1 +38309,Female,53,Diploma,18,89,70,29,55,0.0,0,39,Rural,HR Executive,110769,0 +38310,Male,53,Bachelors,6,23,30,14,14,5.0,1,21,Urban,Software Engineer,26190,0 +38311,Male,29,Bachelors,10,1,29,10,33,6.0,5,73,Semi-Urban,HR Executive,63321,0 +38312,Male,50,Bachelors,12,0,84,18,21,3.0,0,18,Rural,Manager,95686,0 +38313,Female,30,High School,7,55,49,20,51,0.0,2,76,Urban,Data Analyst,121990,0 +38314,Male,45,Diploma,10,4,91,57,10,2.0,6,90,Rural,Software Engineer,125850,1 +38315,Male,41,Bachelors,9,94,38,87,72,7.0,3,57,Semi-Urban,Software Engineer,52494,1 +38316,Male,43,Bachelors,6,85,43,21,61,9.0,0,11,Urban,Manager,107941,0 +38317,Male,54,Bachelors,16,10,77,72,1,5.0,5,94,Urban,Data Analyst,53293,1 +38318,Male,39,Diploma,12,75,62,3,72,7.0,3,42,Semi-Urban,Data Analyst,82308,0 +38319,Male,30,Masters,8,81,90,29,14,6.0,0,68,Rural,HR Executive,92250,1 +38320,Male,26,Bachelors,16,93,43,60,35,6.0,0,30,Urban,HR Executive,29250,0 +38321,Male,41,Diploma,14,47,21,64,62,8.0,1,22,Semi-Urban,ML Engineer,93910,0 +38322,Female,51,Diploma,3,10,78,74,62,3.0,2,35,Semi-Urban,Data Analyst,140516,0 +38323,Female,47,High School,8,56,17,68,50,6.0,7,69,Urban,Software Engineer,136367,0 +38324,Female,42,Diploma,1,20,18,96,2,7.0,2,37,Semi-Urban,Manager,25843,0 +38325,Male,37,Bachelors,3,59,11,2,64,3.0,7,3,Urban,Data Analyst,104961,0 +38326,Male,25,Masters,2,43,80,97,52,9.0,1,70,Semi-Urban,Software Engineer,104683,1 +38327,Female,39,Bachelors,13,80,49,76,78,0.0,2,2,Urban,Manager,82455,0 +38328,Male,41,Bachelors,0,85,75,57,5,9.0,4,56,Rural,Manager,57520,1 +38329,Male,21,Masters,15,81,82,9,67,7.0,0,18,Rural,Data Analyst,43256,0 +38330,Female,35,Bachelors,13,5,24,41,31,2.0,0,20,Urban,Data Analyst,138199,0 +38331,Other,31,Masters,4,5,29,99,66,9.0,6,10,Urban,Data Analyst,62636,0 +38332,Female,43,High School,2,83,40,25,38,2.0,1,15,Urban,HR Executive,139673,0 +38333,Other,59,High School,5,84,7,54,52,1.0,7,79,Urban,ML Engineer,107762,0 +38334,Female,47,Bachelors,2,20,24,1,8,0.0,0,63,Urban,Software Engineer,75680,0 +38335,Female,37,Diploma,8,37,56,62,5,9.0,6,46,Urban,Data Analyst,54264,0 +38336,Male,40,Diploma,15,80,79,25,83,6.0,7,82,Semi-Urban,Manager,64703,1 +38337,Other,55,Bachelors,3,71,43,87,20,8.0,7,92,Urban,Data Analyst,44788,1 +38338,Female,36,Masters,9,50,77,76,6,5.0,6,17,Urban,HR Executive,64363,0 +38339,Male,33,High School,16,86,93,99,45,1.0,6,48,Urban,Software Engineer,114149,1 +38340,Male,32,Masters,9,9,54,11,43,4.0,4,9,Urban,HR Executive,84263,0 +38341,Male,33,Diploma,16,78,22,76,31,8.0,5,49,Urban,Data Analyst,118534,0 +38342,Other,39,Bachelors,7,5,12,17,95,8.0,5,6,Urban,Software Engineer,106205,0 +38343,Male,59,Bachelors,8,14,96,76,37,4.0,6,42,Rural,ML Engineer,84186,0 +38344,Male,51,Bachelors,5,49,40,65,65,4.0,0,1,Semi-Urban,Data Analyst,61698,0 +38345,Male,49,Bachelors,19,26,50,18,8,3.0,3,86,Urban,Data Analyst,89946,0 +38346,Other,25,Diploma,18,39,18,5,79,9.0,1,86,Urban,Software Engineer,45343,0 +38347,Female,47,Bachelors,19,73,59,37,9,2.0,2,28,Urban,ML Engineer,23132,0 +38348,Male,30,PhD,2,90,94,17,12,6.0,5,89,Semi-Urban,HR Executive,93745,1 +38349,Male,50,Diploma,7,31,40,90,52,9.0,5,39,Urban,Software Engineer,120251,0 +38350,Male,43,Masters,0,58,46,97,90,1.0,0,46,Urban,HR Executive,101564,1 +38351,Male,59,Diploma,0,5,7,56,67,6.0,6,10,Urban,HR Executive,100113,0 +38352,Male,51,Bachelors,2,37,27,51,22,6.0,4,49,Urban,ML Engineer,91637,0 +38353,Male,46,Diploma,16,59,93,15,76,7.0,1,55,Urban,Manager,31545,0 +38354,Male,30,Diploma,1,62,36,70,17,0.0,1,92,Semi-Urban,Manager,66671,1 +38355,Male,23,Diploma,19,23,75,88,86,4.0,3,7,Rural,Data Analyst,80842,0 +38356,Male,28,Bachelors,15,63,66,42,72,2.0,7,83,Rural,ML Engineer,58314,1 +38357,Female,21,Masters,18,50,84,95,53,7.0,1,75,Urban,Data Analyst,49796,1 +38358,Male,28,Masters,4,66,19,70,47,4.0,3,95,Semi-Urban,Software Engineer,104686,1 +38359,Male,53,Bachelors,10,69,15,68,66,3.0,4,73,Rural,Data Analyst,139278,0 +38360,Male,43,Masters,14,2,22,89,11,7.0,5,41,Semi-Urban,Data Analyst,46547,0 +38361,Male,26,Masters,5,68,44,44,76,3.0,5,60,Rural,Data Analyst,57731,0 +38362,Male,37,Bachelors,6,84,27,19,94,2.0,2,39,Urban,Software Engineer,28662,0 +38363,Male,53,Masters,10,77,19,16,75,3.0,3,29,Rural,Manager,147989,0 +38364,Female,35,High School,17,80,24,23,96,1.0,3,32,Rural,Data Analyst,65353,0 +38365,Male,52,Masters,2,46,68,81,74,2.0,2,94,Rural,Data Analyst,118748,1 +38366,Male,26,Masters,3,37,75,36,0,1.0,2,67,Urban,Manager,145339,0 +38367,Female,37,Diploma,3,69,54,28,12,6.0,0,22,Semi-Urban,HR Executive,140723,0 +38368,Male,48,Bachelors,0,34,27,7,32,3.0,3,36,Urban,ML Engineer,74042,0 +38369,Female,59,Bachelors,4,42,20,82,18,1.0,6,68,Semi-Urban,Software Engineer,85384,0 +38370,Male,23,High School,14,93,27,47,92,8.0,3,85,Semi-Urban,ML Engineer,118827,1 +38371,Male,53,Diploma,4,29,18,65,33,5.0,4,11,Urban,Manager,36797,0 +38372,Male,46,Diploma,8,56,79,22,37,8.0,1,94,Urban,Software Engineer,125997,1 +38373,Male,41,Diploma,6,54,42,51,27,6.0,7,25,Semi-Urban,Manager,35913,0 +38374,Female,44,High School,16,77,34,76,12,2.0,3,21,Urban,Manager,60958,0 +38375,Male,50,Masters,9,96,6,71,52,8.0,7,88,Rural,HR Executive,82523,1 +38376,Male,47,Bachelors,12,71,42,16,2,7.0,2,44,Urban,Software Engineer,33548,0 +38377,Female,24,High School,16,0,45,99,10,1.0,2,91,Semi-Urban,ML Engineer,27344,0 +38378,Male,38,High School,8,63,33,7,43,3.0,4,42,Urban,ML Engineer,94969,0 +38379,Female,55,Bachelors,9,89,36,78,46,7.0,1,8,Urban,Software Engineer,39692,0 +38380,Male,47,Masters,11,17,64,9,43,4.0,1,16,Rural,HR Executive,127468,0 +38381,Female,27,Masters,10,92,86,64,51,5.0,2,61,Semi-Urban,Manager,72392,1 +38382,Female,44,Diploma,8,71,83,44,22,1.0,6,42,Rural,ML Engineer,134593,0 +38383,Male,34,Bachelors,18,53,34,47,70,0.0,6,53,Urban,Software Engineer,119798,0 +38384,Male,48,High School,6,83,86,30,58,3.0,5,61,Rural,Software Engineer,26992,1 +38385,Male,44,Diploma,5,9,54,42,62,3.0,5,64,Urban,Software Engineer,119524,0 +38386,Male,27,Bachelors,3,26,27,52,43,8.0,7,67,Urban,Data Analyst,42972,0 +38387,Male,59,Diploma,8,36,77,82,96,0.0,6,61,Urban,Manager,59081,1 +38388,Other,52,Masters,1,39,95,56,22,9.0,6,6,Urban,Manager,82520,0 +38389,Male,30,Bachelors,4,13,99,16,36,5.0,6,68,Rural,Manager,36580,0 +38390,Male,33,Bachelors,10,68,53,79,22,9.0,0,96,Rural,ML Engineer,54712,1 +38391,Male,42,Diploma,6,57,14,5,37,2.0,4,15,Urban,HR Executive,85784,0 +38392,Male,59,Bachelors,2,62,16,96,63,7.0,6,92,Rural,ML Engineer,131386,1 +38393,Male,54,Diploma,8,99,11,39,32,0.0,5,24,Rural,HR Executive,144423,0 +38394,Male,58,Diploma,13,76,9,34,44,1.0,1,84,Urban,Data Analyst,96165,0 +38395,Male,59,Bachelors,16,95,99,35,8,3.0,3,19,Urban,Data Analyst,31750,1 +38396,Male,57,Bachelors,6,10,80,69,2,2.0,3,67,Semi-Urban,Manager,146655,0 +38397,Female,44,Bachelors,4,37,16,56,74,2.0,6,6,Urban,HR Executive,98546,0 +38398,Female,56,Bachelors,2,88,38,38,48,6.0,6,83,Rural,ML Engineer,75601,1 +38399,Male,59,Diploma,16,83,13,33,87,0.0,0,79,Rural,Manager,90207,0 +38400,Female,34,Bachelors,0,9,19,39,18,7.0,2,76,Rural,Manager,94066,0 +38401,Male,23,Masters,4,34,43,68,84,8.0,4,16,Semi-Urban,HR Executive,62960,0 +38402,Female,22,Diploma,1,93,27,52,37,6.0,6,34,Rural,Manager,97253,0 +38403,Male,51,Masters,9,14,52,49,0,3.0,6,26,Semi-Urban,ML Engineer,120298,0 +38404,Female,29,Bachelors,9,66,60,15,76,8.0,1,47,Semi-Urban,Data Analyst,126803,0 +38405,Female,28,Bachelors,10,63,33,2,32,5.0,2,37,Rural,ML Engineer,148357,0 +38406,Female,56,Bachelors,4,99,55,16,68,4.0,1,5,Semi-Urban,HR Executive,31513,0 +38407,Female,34,Bachelors,4,20,94,1,8,3.0,1,64,Urban,ML Engineer,141029,0 +38408,Male,35,Masters,3,5,19,68,8,5.0,2,82,Urban,Software Engineer,145833,0 +38409,Male,27,Masters,14,57,17,80,4,9.0,4,80,Semi-Urban,HR Executive,56371,0 +38410,Female,52,PhD,3,62,10,16,85,2.0,1,7,Urban,Manager,66057,0 +38411,Male,21,Bachelors,13,81,56,58,64,1.0,3,6,Semi-Urban,Software Engineer,83598,0 +38412,Male,56,Masters,5,11,27,20,86,9.0,3,35,Urban,HR Executive,62728,0 +38413,Male,24,Bachelors,2,53,0,22,2,0.0,0,57,Semi-Urban,HR Executive,49137,0 +38414,Female,28,Masters,0,15,87,72,11,6.0,5,13,Semi-Urban,Software Engineer,89302,0 +38415,Male,39,Diploma,14,60,37,14,9,6.0,7,68,Urban,HR Executive,54147,0 +38416,Female,40,Diploma,15,27,40,7,50,2.0,0,86,Urban,Manager,36840,0 +38417,Female,33,Diploma,9,20,37,59,12,7.0,4,40,Urban,ML Engineer,118900,0 +38418,Male,59,PhD,19,45,49,16,42,5.0,4,87,Semi-Urban,Software Engineer,102672,0 +38419,Male,34,Masters,14,8,26,75,16,8.0,7,93,Semi-Urban,Software Engineer,141750,0 +38420,Other,24,Masters,11,57,64,13,35,5.0,4,90,Rural,Manager,43897,0 +38421,Female,24,Bachelors,17,25,34,71,39,1.0,5,73,Rural,Data Analyst,96778,0 +38422,Male,46,Diploma,12,29,57,23,91,3.0,7,85,Rural,HR Executive,142633,0 +38423,Male,48,Bachelors,6,21,93,48,78,3.0,5,81,Semi-Urban,Software Engineer,49999,1 +38424,Male,37,Diploma,4,47,42,40,44,6.0,5,62,Semi-Urban,ML Engineer,111768,0 +38425,Male,56,High School,13,78,97,69,43,3.0,7,89,Rural,Manager,148302,1 +38426,Male,29,Diploma,17,16,99,41,8,1.0,5,39,Urban,ML Engineer,25737,0 +38427,Female,39,Bachelors,0,6,51,1,67,0.0,2,41,Semi-Urban,Data Analyst,147172,0 +38428,Other,37,Masters,6,54,60,58,9,5.0,7,23,Urban,ML Engineer,110108,0 +38429,Female,28,Bachelors,12,86,58,82,73,6.0,7,81,Urban,Data Analyst,39887,1 +38430,Male,52,Diploma,16,73,31,17,40,0.0,5,49,Urban,ML Engineer,58566,0 +38431,Male,30,Diploma,6,51,2,50,99,1.0,1,1,Urban,Software Engineer,121483,0 +38432,Male,21,Bachelors,18,49,94,39,96,1.0,3,51,Rural,Software Engineer,74344,0 +38433,Female,52,Bachelors,10,29,79,18,98,3.0,1,4,Urban,ML Engineer,124238,0 +38434,Male,32,Diploma,12,3,48,60,67,8.0,6,2,Urban,Data Analyst,142379,0 +38435,Female,46,Bachelors,10,37,72,34,51,3.0,4,25,Urban,HR Executive,29198,0 +38436,Female,44,High School,18,97,63,37,45,6.0,5,4,Urban,Data Analyst,89534,0 +38437,Female,52,Diploma,16,59,91,96,44,2.0,6,57,Urban,Data Analyst,81989,1 +38438,Male,40,Diploma,12,2,89,20,24,8.0,6,39,Urban,HR Executive,68942,0 +38439,Female,47,Masters,6,96,98,93,36,7.0,4,10,Rural,HR Executive,149325,1 +38440,Male,24,High School,9,8,68,63,1,5.0,4,15,Urban,Manager,140067,0 +38441,Female,57,Masters,6,53,31,52,79,6.0,6,89,Rural,HR Executive,24802,0 +38442,Male,50,Bachelors,10,33,60,83,30,3.0,1,58,Semi-Urban,Manager,29075,0 +38443,Male,34,High School,17,72,71,8,26,1.0,1,46,Rural,Manager,147351,0 +38444,Male,30,Diploma,19,11,24,53,19,9.0,6,2,Urban,ML Engineer,85421,0 +38445,Male,28,Diploma,1,36,93,6,7,5.0,0,51,Semi-Urban,ML Engineer,32416,0 +38446,Other,30,Bachelors,16,32,3,22,24,9.0,1,74,Urban,Software Engineer,34215,0 +38447,Male,53,Bachelors,12,68,14,16,12,4.0,7,10,Urban,Software Engineer,123880,0 +38448,Female,53,Bachelors,1,93,47,45,34,4.0,1,37,Rural,HR Executive,39296,0 +38449,Male,44,Diploma,0,50,36,58,59,5.0,7,27,Rural,HR Executive,127603,0 +38450,Male,26,Bachelors,1,19,30,62,18,2.0,6,95,Urban,HR Executive,83011,0 +38451,Male,28,Masters,1,91,26,49,14,8.0,0,16,Urban,ML Engineer,144692,0 +38452,Male,41,Bachelors,0,92,75,28,89,2.0,0,60,Urban,Manager,42193,1 +38453,Female,59,Masters,17,50,82,12,74,5.0,2,74,Urban,ML Engineer,128944,0 +38454,Male,46,Bachelors,2,50,89,15,54,7.0,6,87,Urban,HR Executive,101151,1 +38455,Female,28,Bachelors,16,80,39,35,71,1.0,0,45,Urban,HR Executive,111556,0 +38456,Male,36,Diploma,0,92,19,67,94,4.0,5,28,Semi-Urban,HR Executive,75616,0 +38457,Male,28,Diploma,5,33,50,39,92,0.0,6,26,Urban,ML Engineer,139179,0 +38458,Male,22,Diploma,9,81,66,72,19,5.0,5,73,Urban,Manager,37612,1 +38459,Female,22,Bachelors,8,31,71,40,14,6.0,7,20,Urban,Manager,116109,0 +38460,Female,32,Bachelors,0,31,96,69,6,4.0,7,86,Urban,Manager,103033,1 +38461,Male,58,Masters,4,34,17,77,71,3.0,3,65,Rural,Manager,94938,0 +38462,Male,44,Masters,5,16,48,62,47,5.0,5,67,Urban,Software Engineer,103291,0 +38463,Female,28,High School,13,19,51,15,0,0.0,5,47,Semi-Urban,Software Engineer,140911,0 +38464,Female,45,Masters,16,11,38,76,89,3.0,4,59,Urban,Software Engineer,35318,0 +38465,Male,24,Diploma,10,21,56,70,76,3.0,5,5,Urban,Software Engineer,32795,0 +38466,Female,56,Bachelors,18,19,99,70,82,6.0,1,19,Rural,Data Analyst,90944,0 +38467,Male,42,Masters,8,41,86,20,9,5.0,2,13,Urban,HR Executive,102834,0 +38468,Male,51,High School,18,19,20,87,62,7.0,4,89,Semi-Urban,HR Executive,141467,0 +38469,Other,50,High School,18,0,51,46,67,6.0,4,78,Urban,ML Engineer,90561,0 +38470,Female,38,Masters,16,40,69,34,80,4.0,2,71,Semi-Urban,ML Engineer,45672,0 +38471,Female,51,Bachelors,12,85,68,17,15,3.0,7,21,Semi-Urban,Manager,60220,0 +38472,Male,53,Bachelors,2,42,20,26,69,9.0,2,11,Semi-Urban,Software Engineer,128171,0 +38473,Male,41,Diploma,7,82,76,70,13,6.0,6,78,Semi-Urban,ML Engineer,145978,1 +38474,Female,41,Diploma,11,34,34,84,87,8.0,5,50,Semi-Urban,Software Engineer,32156,0 +38475,Female,32,Masters,1,36,49,61,85,6.0,6,60,Urban,Manager,135426,0 +38476,Female,23,High School,14,12,44,34,85,3.0,4,22,Urban,Software Engineer,24692,0 +38477,Male,30,Masters,15,54,0,36,55,4.0,2,99,Urban,HR Executive,34157,0 +38478,Male,28,Bachelors,7,33,63,22,3,5.0,0,95,Semi-Urban,HR Executive,70923,0 +38479,Male,37,Diploma,12,57,58,54,44,2.0,2,15,Semi-Urban,Software Engineer,139266,0 +38480,Male,50,Bachelors,7,5,86,63,38,6.0,4,74,Urban,ML Engineer,40998,0 +38481,Male,59,Diploma,5,95,11,93,32,2.0,5,48,Semi-Urban,ML Engineer,56748,1 +38482,Male,23,Bachelors,10,74,47,83,45,2.0,2,22,Urban,Data Analyst,100202,0 +38483,Female,34,Bachelors,9,36,99,67,93,8.0,0,31,Rural,HR Executive,26779,0 +38484,Female,36,High School,12,38,66,98,51,6.0,7,38,Urban,ML Engineer,75802,0 +38485,Female,38,Bachelors,18,67,34,92,81,1.0,2,4,Urban,Software Engineer,69844,0 +38486,Female,25,Bachelors,3,84,72,37,21,1.0,7,23,Semi-Urban,ML Engineer,95709,0 +38487,Male,32,Masters,2,98,54,30,20,3.0,5,28,Semi-Urban,Manager,59509,0 +38488,Female,58,Masters,16,32,4,32,39,4.0,2,87,Urban,Software Engineer,149470,0 +38489,Female,35,Masters,17,97,14,52,42,7.0,1,80,Urban,Software Engineer,80046,1 +38490,Other,54,Diploma,0,94,57,86,32,9.0,3,33,Urban,Software Engineer,57609,1 +38491,Male,32,Bachelors,13,27,64,79,64,0.0,0,31,Semi-Urban,Software Engineer,57263,0 +38492,Male,56,High School,7,53,26,50,47,2.0,6,79,Urban,Software Engineer,24347,0 +38493,Female,35,Bachelors,7,94,2,86,13,6.0,1,6,Rural,HR Executive,108000,0 +38494,Female,58,Bachelors,13,64,23,50,43,4.0,5,50,Urban,Data Analyst,52609,0 +38495,Female,23,Bachelors,12,2,36,98,67,0.0,0,92,Semi-Urban,Manager,148345,0 +38496,Female,50,Diploma,7,41,23,42,18,0.0,3,16,Semi-Urban,Data Analyst,58385,0 +38497,Male,57,Diploma,8,56,83,18,37,1.0,6,98,Urban,ML Engineer,21983,1 +38498,Female,33,Diploma,7,5,32,50,99,7.0,1,55,Semi-Urban,ML Engineer,47490,0 +38499,Female,24,Diploma,14,63,87,82,89,1.0,7,19,Semi-Urban,Manager,55923,1 +38500,Female,42,PhD,6,9,86,69,9,8.0,5,28,Rural,Data Analyst,142877,0 +38501,Female,22,Bachelors,8,44,90,83,5,2.0,0,29,Urban,HR Executive,94394,1 +38502,Male,29,High School,0,44,70,87,80,3.0,2,85,Urban,HR Executive,77605,1 +38503,Female,56,Diploma,4,60,22,55,69,8.0,7,26,Urban,HR Executive,96067,0 +38504,Male,57,Bachelors,5,10,10,15,40,6.0,2,74,Rural,Data Analyst,59327,0 +38505,Other,52,Diploma,6,45,34,63,56,0.0,5,43,Semi-Urban,ML Engineer,129591,0 +38506,Female,58,Bachelors,7,39,65,27,46,5.0,7,51,Urban,ML Engineer,89973,0 +38507,Female,43,Diploma,14,81,62,1,37,0.0,6,14,Urban,ML Engineer,82759,0 +38508,Other,38,Diploma,18,34,42,97,43,6.0,7,24,Urban,Data Analyst,129354,0 +38509,Male,58,Diploma,18,36,4,96,49,3.0,2,83,Urban,Software Engineer,46968,0 +38510,Male,23,Diploma,5,40,63,50,49,3.0,7,7,Urban,Data Analyst,98732,0 +38511,Female,59,High School,6,51,38,30,29,3.0,3,95,Urban,Software Engineer,114453,0 +38512,Male,48,PhD,13,75,49,54,28,8.0,1,27,Urban,HR Executive,34978,0 +38513,Male,38,Diploma,7,12,60,70,3,1.0,4,32,Urban,Data Analyst,101868,0 +38514,Female,49,Bachelors,6,52,84,18,42,4.0,5,28,Urban,ML Engineer,96350,0 +38515,Male,31,High School,5,52,49,34,83,9.0,7,79,Urban,Manager,140244,0 +38516,Male,51,Bachelors,11,2,96,14,79,1.0,5,23,Semi-Urban,HR Executive,70025,0 +38517,Male,39,High School,17,39,99,76,94,0.0,7,44,Semi-Urban,HR Executive,45568,1 +38518,Male,33,High School,9,28,94,98,71,2.0,6,19,Urban,Data Analyst,84578,1 +38519,Male,49,Diploma,3,6,69,20,37,9.0,7,6,Semi-Urban,Data Analyst,105790,0 +38520,Male,51,Bachelors,3,50,79,49,53,0.0,6,71,Rural,Data Analyst,139723,1 +38521,Female,53,High School,7,19,25,50,4,5.0,0,2,Urban,Software Engineer,94600,0 +38522,Male,46,Diploma,14,50,39,54,76,1.0,5,15,Semi-Urban,HR Executive,96340,0 +38523,Male,23,Bachelors,11,86,25,73,87,5.0,0,12,Urban,ML Engineer,140756,0 +38524,Male,47,Masters,18,0,53,69,30,5.0,5,80,Rural,ML Engineer,132743,0 +38525,Female,37,Bachelors,8,79,96,87,1,3.0,6,6,Semi-Urban,HR Executive,127053,1 +38526,Male,54,PhD,6,72,43,80,63,7.0,5,73,Urban,ML Engineer,76768,1 +38527,Male,30,Bachelors,1,88,75,85,0,2.0,6,94,Urban,HR Executive,42785,1 +38528,Female,46,Bachelors,19,92,96,87,73,5.0,3,72,Rural,ML Engineer,80391,1 +38529,Male,57,Bachelors,0,0,81,71,89,6.0,4,36,Urban,HR Executive,46582,0 +38530,Male,52,Diploma,6,70,49,32,53,2.0,1,53,Urban,Manager,35468,0 +38531,Female,26,High School,18,32,35,67,66,1.0,0,46,Urban,ML Engineer,103178,0 +38532,Male,46,Bachelors,13,49,58,24,0,4.0,4,1,Urban,Software Engineer,82769,0 +38533,Male,37,Diploma,12,61,97,98,49,0.0,5,13,Semi-Urban,Manager,76166,1 +38534,Male,43,High School,6,84,90,59,1,0.0,5,85,Urban,ML Engineer,36081,1 +38535,Female,52,High School,4,45,42,54,50,0.0,5,96,Urban,Software Engineer,122566,0 +38536,Female,52,PhD,14,0,16,0,30,6.0,1,18,Semi-Urban,Software Engineer,139019,0 +38537,Male,58,Masters,3,70,90,76,26,4.0,7,35,Rural,Software Engineer,50896,1 +38538,Male,49,Bachelors,7,53,9,95,92,6.0,0,40,Urban,Manager,124668,0 +38539,Male,24,High School,5,80,21,50,82,4.0,0,26,Semi-Urban,Software Engineer,108001,0 +38540,Female,31,Masters,9,84,30,19,68,8.0,6,60,Urban,HR Executive,117021,0 +38541,Male,44,High School,14,17,62,27,0,5.0,5,72,Urban,Manager,83985,0 +38542,Male,45,High School,2,48,97,75,58,7.0,3,54,Urban,Manager,149450,1 +38543,Female,29,High School,5,13,4,75,61,5.0,5,11,Urban,HR Executive,87761,0 +38544,Male,51,Diploma,8,14,31,55,40,9.0,3,90,Rural,HR Executive,51646,0 +38545,Male,50,High School,13,54,98,56,58,6.0,2,42,Semi-Urban,HR Executive,69897,1 +38546,Female,37,Masters,10,20,20,82,62,3.0,3,84,Urban,Software Engineer,105757,0 +38547,Female,30,Bachelors,14,83,25,0,82,6.0,5,68,Urban,Software Engineer,102950,0 +38548,Female,39,Diploma,18,30,19,29,63,0.0,3,83,Urban,ML Engineer,50178,0 +38549,Female,58,Diploma,12,17,75,44,20,4.0,3,23,Urban,Data Analyst,120407,0 +38550,Male,53,Masters,8,21,47,2,89,8.0,3,87,Semi-Urban,Manager,118912,0 +38551,Male,48,Bachelors,6,20,48,86,64,0.0,3,90,Urban,Manager,30857,1 +38552,Male,28,Diploma,19,22,4,4,88,2.0,3,11,Urban,HR Executive,82804,0 +38553,Male,42,Bachelors,17,97,72,14,0,8.0,7,76,Semi-Urban,ML Engineer,112351,1 +38554,Male,24,High School,10,84,16,91,64,7.0,0,40,Rural,Data Analyst,87533,0 +38555,Male,49,Bachelors,1,52,59,34,18,1.0,6,50,Urban,ML Engineer,57890,0 +38556,Male,39,High School,12,74,37,34,91,9.0,5,16,Semi-Urban,Manager,124514,0 +38557,Male,59,Diploma,18,57,59,46,22,5.0,6,86,Urban,ML Engineer,103376,1 +38558,Male,40,PhD,0,59,46,50,76,6.0,7,65,Urban,ML Engineer,135058,0 +38559,Male,52,Bachelors,11,48,54,40,20,3.0,3,2,Rural,Software Engineer,92242,0 +38560,Female,55,Diploma,4,66,17,83,80,0.0,2,0,Urban,Manager,94003,0 +38561,Male,21,High School,9,29,88,18,36,0.0,0,3,Semi-Urban,Manager,116670,0 +38562,Male,29,Bachelors,1,17,15,28,74,7.0,1,5,Semi-Urban,ML Engineer,127627,0 +38563,Other,52,Diploma,11,37,0,60,91,7.0,0,68,Rural,Data Analyst,134915,0 +38564,Female,36,Diploma,2,99,38,76,81,5.0,5,68,Urban,Manager,116355,1 +38565,Male,40,Diploma,12,25,89,43,33,9.0,6,95,Urban,Data Analyst,26850,1 +38566,Male,37,PhD,17,5,28,72,27,4.0,6,52,Urban,Software Engineer,32076,0 +38567,Female,23,Bachelors,2,29,47,99,47,1.0,4,22,Semi-Urban,Manager,65059,0 +38568,Male,26,Bachelors,3,1,49,98,60,5.0,4,79,Rural,Data Analyst,68362,0 +38569,Male,47,Masters,12,16,85,52,20,1.0,2,26,Semi-Urban,Manager,28754,0 +38570,Female,41,Bachelors,17,83,80,40,42,2.0,0,23,Urban,Manager,28436,0 +38571,Male,55,Diploma,6,92,22,49,91,3.0,4,20,Rural,Manager,102880,0 +38572,Male,22,Bachelors,7,99,19,1,99,4.0,5,2,Urban,Data Analyst,53591,0 +38573,Male,21,Masters,16,52,3,97,14,1.0,6,91,Semi-Urban,Data Analyst,68467,1 +38574,Male,59,Bachelors,18,87,25,17,43,8.0,6,82,Urban,ML Engineer,54473,0 +38575,Female,56,Diploma,2,43,44,22,78,8.0,1,37,Urban,Software Engineer,21624,0 +38576,Male,48,High School,8,24,92,64,4,6.0,1,9,Urban,Data Analyst,80476,0 +38577,Male,22,Diploma,9,29,27,88,10,9.0,2,81,Rural,ML Engineer,94620,0 +38578,Female,32,Bachelors,16,53,77,33,62,2.0,5,36,Semi-Urban,Data Analyst,140291,0 +38579,Male,58,High School,16,58,22,49,55,2.0,5,83,Semi-Urban,Software Engineer,63950,0 +38580,Male,28,Bachelors,18,89,51,30,51,1.0,4,23,Rural,HR Executive,71211,0 +38581,Male,42,Masters,15,98,56,32,15,7.0,0,96,Rural,Software Engineer,79220,1 +38582,Male,37,Diploma,16,87,5,21,84,4.0,2,37,Urban,ML Engineer,121772,0 +38583,Female,24,Masters,15,43,79,5,84,4.0,4,41,Urban,HR Executive,91130,0 +38584,Male,35,Bachelors,12,25,4,92,32,8.0,6,64,Urban,Software Engineer,24230,0 +38585,Male,36,PhD,7,83,99,8,85,7.0,0,13,Urban,Manager,138501,0 +38586,Other,50,High School,3,3,68,73,48,4.0,2,52,Semi-Urban,ML Engineer,148940,0 +38587,Male,52,Diploma,1,14,65,85,65,4.0,5,59,Urban,Manager,33579,0 +38588,Male,43,Bachelors,1,45,22,76,53,9.0,3,91,Rural,ML Engineer,20727,0 +38589,Male,36,Bachelors,1,54,74,11,63,7.0,2,14,Urban,ML Engineer,50296,0 +38590,Male,50,Masters,18,34,44,97,62,0.0,7,18,Semi-Urban,HR Executive,63320,0 +38591,Male,33,High School,13,31,59,33,94,1.0,3,42,Rural,Data Analyst,24343,0 +38592,Male,54,Bachelors,4,13,86,35,0,8.0,3,33,Rural,Data Analyst,117312,0 +38593,Male,45,Bachelors,15,78,21,8,93,1.0,6,62,Semi-Urban,Data Analyst,79434,0 +38594,Male,40,Diploma,2,48,75,0,75,2.0,3,21,Urban,Software Engineer,114455,0 +38595,Male,26,Diploma,17,83,50,11,71,0.0,6,14,Urban,Software Engineer,48698,0 +38596,Female,45,Masters,16,36,10,10,48,9.0,2,80,Rural,Data Analyst,94412,0 +38597,Female,58,Bachelors,11,2,38,27,98,2.0,5,60,Urban,Manager,24316,0 +38598,Male,51,Bachelors,19,70,93,80,51,2.0,2,36,Urban,ML Engineer,31279,1 +38599,Other,52,Bachelors,0,12,3,14,23,2.0,7,17,Urban,Data Analyst,27333,0 +38600,Female,27,Bachelors,0,87,34,4,65,3.0,2,19,Urban,Manager,122486,0 +38601,Female,37,Diploma,15,80,17,24,91,1.0,3,91,Urban,Software Engineer,114337,0 +38602,Male,55,Bachelors,3,37,60,93,19,2.0,3,44,Urban,HR Executive,48348,0 +38603,Female,56,Bachelors,3,25,78,35,98,0.0,4,18,Urban,Software Engineer,65486,0 +38604,Female,59,Bachelors,2,34,12,26,8,6.0,4,94,Urban,Manager,45565,0 +38605,Male,52,Bachelors,3,85,99,57,48,1.0,5,14,Urban,ML Engineer,108350,1 +38606,Female,59,Diploma,13,86,64,57,31,7.0,4,70,Semi-Urban,Manager,120500,1 +38607,Female,32,High School,9,83,16,0,95,3.0,3,90,Rural,Software Engineer,64293,0 +38608,Male,43,High School,3,43,47,71,78,2.0,6,83,Urban,Manager,53094,1 +38609,Male,36,High School,4,44,48,43,56,6.0,2,99,Urban,Data Analyst,142539,0 +38610,Male,56,Diploma,5,63,97,7,26,6.0,1,0,Rural,ML Engineer,127215,0 +38611,Male,51,High School,17,6,53,18,42,3.0,4,93,Urban,Manager,52375,0 +38612,Male,55,Diploma,14,97,39,56,67,1.0,5,90,Urban,ML Engineer,147540,1 +38613,Male,37,Bachelors,4,8,95,75,53,2.0,1,33,Urban,ML Engineer,101473,0 +38614,Female,25,Diploma,14,65,93,24,55,5.0,2,61,Semi-Urban,Manager,91191,1 +38615,Female,55,Masters,16,50,20,53,64,5.0,2,3,Urban,ML Engineer,67849,0 +38616,Male,24,PhD,16,51,78,1,22,7.0,4,32,Urban,Manager,29832,0 +38617,Male,24,PhD,16,3,77,26,93,0.0,5,33,Semi-Urban,Manager,54897,0 +38618,Male,46,Diploma,11,37,38,72,61,4.0,1,59,Urban,ML Engineer,67625,0 +38619,Female,37,Bachelors,0,64,11,78,7,7.0,2,51,Urban,Manager,140336,0 +38620,Male,44,Bachelors,17,23,20,56,35,9.0,7,54,Urban,Software Engineer,103726,0 +38621,Female,53,Bachelors,4,64,76,97,73,6.0,5,28,Semi-Urban,Manager,25317,1 +38622,Male,23,Bachelors,12,54,21,79,11,0.0,7,53,Urban,Data Analyst,148631,0 +38623,Male,32,Bachelors,4,12,76,73,96,6.0,3,71,Rural,ML Engineer,140383,0 +38624,Male,36,Diploma,7,89,89,65,73,6.0,1,99,Rural,Data Analyst,40126,1 +38625,Male,40,Bachelors,19,6,63,19,88,7.0,0,49,Urban,HR Executive,105457,0 +38626,Female,36,Masters,18,62,49,56,41,3.0,0,35,Urban,Software Engineer,138671,0 +38627,Male,54,Bachelors,19,90,72,87,74,4.0,0,60,Urban,Data Analyst,145346,1 +38628,Male,25,Bachelors,4,29,22,84,73,4.0,4,13,Urban,ML Engineer,123709,0 +38629,Female,28,High School,0,41,12,3,5,7.0,1,27,Urban,Software Engineer,44575,0 +38630,Male,38,Diploma,19,16,94,85,81,9.0,1,26,Rural,Software Engineer,102530,0 +38631,Male,42,High School,10,55,80,21,25,1.0,5,77,Semi-Urban,Software Engineer,48631,0 +38632,Female,51,Bachelors,8,1,44,30,37,2.0,6,58,Rural,HR Executive,143843,0 +38633,Male,47,Bachelors,16,70,27,27,24,0.0,1,97,Semi-Urban,ML Engineer,114699,0 +38634,Female,35,Bachelors,17,74,96,26,57,7.0,4,10,Urban,Data Analyst,43215,0 +38635,Female,53,Diploma,18,98,93,64,96,4.0,7,66,Semi-Urban,Manager,131146,1 +38636,Male,39,High School,4,35,69,79,54,7.0,4,21,Semi-Urban,Manager,92936,0 +38637,Male,25,Masters,11,71,60,91,42,6.0,7,79,Urban,Software Engineer,115743,1 +38638,Male,34,Bachelors,15,80,85,64,82,6.0,3,84,Urban,HR Executive,133699,1 +38639,Male,50,High School,5,25,28,50,54,3.0,2,53,Urban,Software Engineer,128235,0 +38640,Female,58,High School,11,30,32,96,57,3.0,6,86,Urban,Data Analyst,41989,1 +38641,Male,24,Diploma,7,10,75,39,71,1.0,1,71,Semi-Urban,Software Engineer,68232,0 +38642,Male,40,Diploma,6,29,44,70,92,6.0,7,48,Semi-Urban,Data Analyst,66840,0 +38643,Male,52,Masters,17,31,37,93,80,3.0,6,56,Rural,Manager,40146,0 +38644,Male,39,Bachelors,14,16,55,84,71,8.0,1,19,Urban,Software Engineer,79433,0 +38645,Female,28,Bachelors,11,65,86,56,61,6.0,4,43,Urban,Software Engineer,68542,1 +38646,Female,44,Masters,16,1,36,52,17,9.0,6,10,Urban,ML Engineer,71456,0 +38647,Female,35,Bachelors,15,59,65,30,48,9.0,4,19,Rural,HR Executive,61518,0 +38648,Female,44,Masters,12,87,97,41,58,6.0,7,6,Rural,Data Analyst,75965,0 +38649,Male,52,High School,0,4,5,90,32,5.0,2,71,Semi-Urban,Software Engineer,133945,0 +38650,Male,58,Diploma,3,99,18,99,49,4.0,6,3,Urban,HR Executive,49461,0 +38651,Male,53,Diploma,8,40,51,57,21,2.0,7,17,Semi-Urban,Data Analyst,57324,0 +38652,Other,28,Diploma,15,96,33,29,26,7.0,3,45,Urban,Manager,71288,0 +38653,Male,42,Masters,4,34,6,36,96,1.0,5,91,Semi-Urban,Software Engineer,35870,0 +38654,Other,28,Masters,11,1,92,35,85,7.0,6,89,Urban,HR Executive,34055,0 +38655,Female,46,Bachelors,2,0,37,64,0,2.0,7,18,Semi-Urban,HR Executive,44250,0 +38656,Female,36,Bachelors,0,1,98,36,57,2.0,3,53,Rural,ML Engineer,78332,0 +38657,Male,21,Bachelors,4,97,98,12,90,1.0,7,95,Urban,Software Engineer,85871,1 +38658,Male,58,Bachelors,5,64,15,2,45,7.0,7,5,Urban,Manager,118924,0 +38659,Male,25,Bachelors,8,13,10,72,27,8.0,7,69,Urban,ML Engineer,104370,0 +38660,Male,21,Bachelors,6,64,97,50,14,1.0,5,59,Rural,HR Executive,55451,1 +38661,Female,47,Masters,12,26,63,39,59,4.0,1,27,Urban,Data Analyst,110458,0 +38662,Female,30,High School,15,68,7,42,7,1.0,2,74,Semi-Urban,ML Engineer,94469,0 +38663,Female,54,Diploma,12,17,31,6,41,9.0,4,48,Urban,ML Engineer,114937,0 +38664,Male,21,Bachelors,13,7,73,53,40,4.0,5,1,Urban,ML Engineer,50614,0 +38665,Male,42,Bachelors,18,10,19,85,79,3.0,2,75,Urban,Manager,56368,0 +38666,Female,41,PhD,8,7,42,30,38,8.0,4,93,Urban,ML Engineer,77116,0 +38667,Male,54,Bachelors,0,84,14,79,71,5.0,0,78,Urban,Manager,109967,1 +38668,Female,37,PhD,1,10,29,43,4,4.0,1,35,Semi-Urban,ML Engineer,107834,0 +38669,Female,31,High School,9,15,77,46,74,8.0,2,35,Urban,Software Engineer,66162,0 +38670,Male,45,Bachelors,0,39,92,26,24,4.0,6,98,Urban,Data Analyst,30509,1 +38671,Female,21,Bachelors,17,18,70,86,65,3.0,6,55,Urban,HR Executive,89580,0 +38672,Female,43,Diploma,7,63,68,10,51,6.0,5,21,Semi-Urban,Software Engineer,72971,0 +38673,Male,23,Masters,1,70,83,13,81,1.0,2,9,Semi-Urban,Software Engineer,107796,0 +38674,Male,45,Diploma,1,69,0,9,60,5.0,7,87,Rural,ML Engineer,42400,0 +38675,Male,37,Bachelors,19,36,49,37,52,0.0,1,6,Rural,Software Engineer,69112,0 +38676,Male,49,Bachelors,5,46,48,94,38,5.0,5,54,Urban,HR Executive,112785,1 +38677,Female,22,High School,7,36,38,81,80,3.0,2,34,Rural,ML Engineer,94409,0 +38678,Male,57,Diploma,6,69,56,85,10,9.0,7,61,Rural,Data Analyst,110750,1 +38679,Female,26,Bachelors,14,69,50,16,26,4.0,0,25,Urban,HR Executive,54322,0 +38680,Male,35,Bachelors,1,46,43,32,10,3.0,4,19,Rural,Software Engineer,27001,0 +38681,Female,47,High School,0,5,11,72,65,0.0,3,29,Rural,ML Engineer,55360,0 +38682,Other,53,Bachelors,18,51,49,69,3,7.0,1,56,Semi-Urban,Software Engineer,62738,0 +38683,Female,28,Masters,19,95,7,59,66,2.0,6,9,Semi-Urban,Data Analyst,104393,0 +38684,Male,22,Masters,19,29,32,26,49,1.0,2,24,Semi-Urban,HR Executive,95862,0 +38685,Male,35,Bachelors,16,17,93,59,69,6.0,0,70,Urban,Software Engineer,78131,1 +38686,Male,54,Masters,15,64,58,28,80,8.0,0,99,Rural,HR Executive,141904,1 +38687,Male,39,High School,9,53,18,52,53,5.0,5,67,Urban,ML Engineer,55783,0 +38688,Male,21,Bachelors,5,43,62,25,96,0.0,4,6,Semi-Urban,HR Executive,24108,0 +38689,Female,34,Bachelors,9,83,29,66,42,1.0,3,38,Urban,ML Engineer,117705,0 +38690,Male,55,High School,18,10,23,68,57,4.0,2,54,Semi-Urban,HR Executive,96642,0 +38691,Male,44,Diploma,5,31,23,13,27,7.0,6,41,Semi-Urban,Software Engineer,69808,0 +38692,Male,49,High School,19,38,11,28,27,5.0,4,7,Urban,HR Executive,31908,0 +38693,Female,59,Masters,1,36,71,98,13,0.0,2,76,Urban,HR Executive,112505,1 +38694,Male,57,Diploma,16,39,85,63,94,8.0,2,30,Urban,ML Engineer,106840,0 +38695,Male,34,Masters,6,35,86,84,28,3.0,7,2,Urban,Data Analyst,141916,0 +38696,Female,40,Bachelors,19,92,39,43,70,2.0,3,63,Semi-Urban,ML Engineer,44177,0 +38697,Male,32,Bachelors,9,14,86,57,50,6.0,7,42,Urban,Software Engineer,129939,0 +38698,Female,54,High School,19,39,35,7,58,3.0,4,95,Semi-Urban,ML Engineer,57900,0 +38699,Female,50,Bachelors,13,89,75,30,78,3.0,0,16,Semi-Urban,Data Analyst,80522,0 +38700,Male,54,Masters,18,0,68,30,40,8.0,4,72,Rural,Software Engineer,94742,0 +38701,Male,43,Bachelors,7,4,4,94,77,8.0,2,52,Semi-Urban,Data Analyst,92697,0 +38702,Female,37,Bachelors,3,99,42,71,87,3.0,3,93,Urban,Manager,122589,1 +38703,Male,42,PhD,16,44,57,89,88,0.0,5,28,Urban,Software Engineer,144468,0 +38704,Male,29,Masters,18,94,90,34,48,7.0,3,93,Urban,Data Analyst,32510,1 +38705,Male,39,Bachelors,9,44,6,79,88,6.0,2,50,Urban,HR Executive,97605,0 +38706,Male,41,Diploma,4,9,5,58,18,5.0,7,17,Rural,Software Engineer,33400,0 +38707,Male,43,Masters,15,43,27,4,24,1.0,0,58,Semi-Urban,Software Engineer,125081,0 +38708,Female,22,PhD,15,6,56,73,80,2.0,5,28,Urban,Data Analyst,109241,0 +38709,Female,52,Bachelors,9,67,23,90,97,7.0,4,65,Semi-Urban,HR Executive,112510,1 +38710,Male,39,Diploma,7,8,94,61,21,9.0,0,92,Rural,ML Engineer,73360,1 +38711,Male,26,Bachelors,3,14,64,44,4,7.0,6,92,Urban,Data Analyst,31817,0 +38712,Male,43,High School,16,16,22,79,72,7.0,5,37,Semi-Urban,Software Engineer,143059,0 +38713,Female,27,Bachelors,9,11,49,60,44,1.0,5,45,Rural,Data Analyst,50992,0 +38714,Male,32,Bachelors,15,16,52,89,96,9.0,4,60,Rural,Software Engineer,104144,0 +38715,Male,52,Masters,4,98,55,59,60,3.0,6,1,Urban,Data Analyst,103625,0 +38716,Female,51,Bachelors,9,89,94,2,76,1.0,5,95,Semi-Urban,Manager,30397,1 +38717,Male,58,Bachelors,11,75,38,39,96,2.0,3,8,Semi-Urban,ML Engineer,103184,0 +38718,Male,52,PhD,6,58,21,93,1,4.0,2,21,Urban,ML Engineer,85981,0 +38719,Male,31,Diploma,15,2,12,75,33,4.0,4,64,Semi-Urban,Data Analyst,72586,0 +38720,Female,48,Bachelors,18,60,44,43,2,5.0,3,79,Rural,Manager,94726,0 +38721,Female,22,Masters,11,73,48,81,96,3.0,5,55,Urban,ML Engineer,100770,1 +38722,Female,49,Bachelors,9,17,7,52,45,0.0,7,81,Urban,ML Engineer,111237,0 +38723,Male,52,Bachelors,2,75,41,84,83,8.0,3,23,Semi-Urban,HR Executive,69481,0 +38724,Male,27,High School,6,92,55,81,42,3.0,3,5,Urban,Manager,38973,0 +38725,Female,49,Masters,6,26,2,76,94,6.0,7,97,Urban,Manager,138921,0 +38726,Female,25,High School,14,99,23,77,57,7.0,5,65,Urban,HR Executive,79277,1 +38727,Male,49,Masters,4,40,46,88,17,1.0,0,1,Semi-Urban,HR Executive,143717,0 +38728,Male,57,Diploma,18,48,29,80,14,9.0,2,97,Semi-Urban,Manager,113916,1 +38729,Female,22,High School,0,28,34,46,14,7.0,2,62,Urban,ML Engineer,32533,0 +38730,Male,59,High School,14,9,80,64,10,6.0,0,57,Semi-Urban,ML Engineer,53056,0 +38731,Male,49,Masters,19,11,40,19,12,5.0,7,94,Semi-Urban,Manager,22632,0 +38732,Male,41,High School,5,70,85,4,91,7.0,1,66,Urban,HR Executive,116297,0 +38733,Other,32,Bachelors,5,33,21,7,28,9.0,5,5,Rural,Software Engineer,116892,0 +38734,Female,46,Diploma,6,26,35,80,85,1.0,7,46,Urban,Manager,47933,0 +38735,Male,52,Masters,10,11,13,37,98,2.0,3,80,Urban,Manager,130370,0 +38736,Female,40,Diploma,14,20,60,14,66,0.0,0,21,Rural,Data Analyst,144686,0 +38737,Male,25,Bachelors,3,33,40,60,15,2.0,5,10,Semi-Urban,HR Executive,113888,0 +38738,Male,24,Diploma,10,59,18,4,5,3.0,7,55,Urban,Software Engineer,144430,0 +38739,Male,30,Bachelors,15,53,5,34,24,4.0,3,19,Semi-Urban,ML Engineer,46037,0 +38740,Male,32,Bachelors,13,61,12,75,44,5.0,3,35,Urban,Manager,87829,0 +38741,Female,53,Bachelors,7,96,84,11,86,9.0,1,39,Semi-Urban,Software Engineer,129684,0 +38742,Male,25,High School,15,58,29,52,47,3.0,6,2,Urban,Manager,133044,0 +38743,Male,31,High School,7,91,58,41,82,9.0,7,53,Semi-Urban,ML Engineer,145150,1 +38744,Female,57,Masters,7,51,13,47,79,0.0,5,92,Urban,ML Engineer,84530,0 +38745,Male,50,Diploma,18,89,38,24,96,2.0,4,58,Urban,Data Analyst,91489,0 +38746,Male,47,Masters,5,27,67,34,95,9.0,4,46,Urban,Manager,86079,0 +38747,Male,50,Masters,17,99,20,84,93,5.0,2,36,Urban,Manager,149066,1 +38748,Other,33,Diploma,6,59,23,36,1,4.0,5,3,Urban,Manager,26564,0 +38749,Male,45,Bachelors,2,52,94,34,15,2.0,0,0,Urban,Software Engineer,109954,0 +38750,Male,35,Bachelors,11,42,24,49,43,0.0,6,67,Rural,Data Analyst,83099,0 +38751,Male,22,High School,9,14,14,43,42,7.0,1,60,Urban,Data Analyst,127455,0 +38752,Other,31,Bachelors,7,8,63,93,49,3.0,6,80,Rural,Manager,83676,1 +38753,Female,21,Bachelors,14,32,20,14,8,2.0,3,69,Urban,Manager,118446,0 +38754,Male,42,Diploma,19,96,35,65,34,8.0,1,43,Urban,Software Engineer,24267,1 +38755,Female,21,Diploma,13,13,17,76,68,2.0,5,55,Urban,ML Engineer,120256,0 +38756,Female,55,High School,18,20,98,94,26,2.0,6,66,Urban,HR Executive,40565,1 +38757,Female,30,High School,4,1,51,87,68,7.0,1,77,Rural,Manager,26728,0 +38758,Female,52,High School,18,49,44,77,16,9.0,5,66,Semi-Urban,Software Engineer,111724,0 +38759,Male,33,Bachelors,5,39,73,6,93,0.0,2,50,Semi-Urban,Data Analyst,94669,0 +38760,Female,26,High School,15,94,79,22,6,8.0,0,61,Semi-Urban,Data Analyst,119723,1 +38761,Female,54,Masters,12,23,39,60,34,8.0,7,44,Rural,Software Engineer,108996,0 +38762,Male,29,Bachelors,15,18,39,77,10,7.0,5,84,Urban,Manager,65243,0 +38763,Male,40,Diploma,14,22,5,11,66,5.0,2,34,Urban,Software Engineer,20869,0 +38764,Male,29,Bachelors,6,33,44,70,64,4.0,5,95,Urban,Data Analyst,75479,1 +38765,Female,51,High School,7,47,14,94,93,7.0,5,97,Urban,ML Engineer,44268,1 +38766,Female,40,Bachelors,7,84,3,55,95,7.0,0,10,Semi-Urban,ML Engineer,88129,0 +38767,Male,24,Masters,1,38,93,70,59,7.0,4,39,Urban,ML Engineer,100094,1 +38768,Female,58,Masters,7,95,65,82,26,3.0,5,46,Rural,HR Executive,90290,1 +38769,Female,59,PhD,16,53,22,73,97,4.0,7,35,Semi-Urban,ML Engineer,30845,0 +38770,Female,49,High School,3,78,22,54,11,5.0,2,3,Semi-Urban,ML Engineer,135674,0 +38771,Male,58,Bachelors,9,69,50,97,85,3.0,2,99,Urban,Data Analyst,105416,1 +38772,Male,37,Bachelors,12,20,68,54,61,8.0,1,87,Urban,HR Executive,21128,0 +38773,Female,37,Bachelors,10,42,21,67,59,4.0,5,63,Urban,Software Engineer,32282,0 +38774,Male,59,High School,0,46,31,33,51,9.0,7,71,Urban,ML Engineer,141751,0 +38775,Male,54,PhD,10,0,97,54,20,3.0,2,72,Semi-Urban,Manager,137561,0 +38776,Male,59,Diploma,14,94,69,40,93,3.0,2,51,Urban,Manager,148103,1 +38777,Female,55,Bachelors,11,62,25,21,63,5.0,6,73,Semi-Urban,Data Analyst,148996,0 +38778,Male,56,Diploma,16,51,74,22,26,6.0,0,26,Urban,ML Engineer,67576,0 +38779,Male,42,Bachelors,12,25,38,75,32,7.0,7,86,Semi-Urban,Data Analyst,36021,0 +38780,Male,41,High School,3,54,16,13,92,0.0,4,12,Urban,Data Analyst,131952,0 +38781,Male,38,Bachelors,15,53,89,15,88,8.0,4,72,Semi-Urban,ML Engineer,125345,0 +38782,Female,34,High School,2,11,16,33,88,1.0,1,82,Urban,ML Engineer,64378,0 +38783,Male,48,Diploma,19,72,37,66,53,9.0,7,49,Semi-Urban,ML Engineer,21598,0 +38784,Male,38,High School,1,53,88,52,28,4.0,2,25,Semi-Urban,Data Analyst,95802,0 +38785,Male,53,Diploma,5,0,75,85,45,7.0,7,61,Rural,Data Analyst,48175,0 +38786,Male,48,High School,16,89,9,27,40,4.0,1,0,Rural,Software Engineer,77126,0 +38787,Female,39,Bachelors,15,98,1,8,79,1.0,7,68,Rural,Software Engineer,106214,0 +38788,Other,54,High School,17,44,82,16,82,5.0,5,61,Semi-Urban,ML Engineer,137103,0 +38789,Male,35,PhD,6,57,78,21,69,0.0,6,40,Urban,ML Engineer,72254,0 +38790,Male,35,Bachelors,1,27,5,33,25,9.0,5,5,Urban,Manager,119197,0 +38791,Male,40,Bachelors,1,39,40,31,94,9.0,2,61,Urban,Software Engineer,81700,0 +38792,Male,57,PhD,1,36,17,41,47,2.0,5,60,Urban,Data Analyst,145915,0 +38793,Female,48,Bachelors,3,87,2,49,20,5.0,7,75,Urban,ML Engineer,77419,0 +38794,Male,56,High School,7,32,49,96,69,6.0,3,10,Semi-Urban,HR Executive,95637,0 +38795,Female,33,Bachelors,1,49,62,47,89,8.0,5,5,Urban,Manager,84423,0 +38796,Female,27,Masters,12,90,59,72,81,0.0,2,84,Semi-Urban,Manager,71245,1 +38797,Male,41,Diploma,14,14,24,76,96,6.0,3,92,Urban,Manager,34581,0 +38798,Female,38,Bachelors,3,51,35,5,86,1.0,2,62,Urban,ML Engineer,100280,0 +38799,Female,30,Bachelors,8,39,66,83,83,6.0,1,88,Urban,Software Engineer,103252,1 +38800,Male,59,Masters,6,88,12,55,26,4.0,2,47,Rural,Manager,120580,0 +38801,Female,23,Bachelors,8,80,77,67,92,4.0,0,90,Urban,Data Analyst,119492,1 +38802,Female,43,Diploma,4,7,39,52,21,3.0,4,34,Rural,Data Analyst,47987,0 +38803,Male,26,Diploma,11,69,67,18,52,5.0,7,99,Urban,Software Engineer,97287,1 +38804,Female,58,High School,15,85,82,55,75,8.0,4,87,Semi-Urban,Software Engineer,144386,1 +38805,Female,47,Masters,8,93,0,89,34,9.0,7,63,Urban,Manager,94945,1 +38806,Male,50,PhD,11,0,22,95,97,8.0,5,49,Semi-Urban,ML Engineer,51183,0 +38807,Male,50,Diploma,18,58,75,51,33,0.0,3,49,Semi-Urban,ML Engineer,22342,0 +38808,Female,35,Masters,10,30,6,95,94,2.0,3,92,Rural,ML Engineer,117283,0 +38809,Male,22,High School,13,1,58,50,72,2.0,3,57,Rural,HR Executive,67553,0 +38810,Male,23,Bachelors,17,76,24,98,39,9.0,7,9,Urban,Data Analyst,143901,0 +38811,Male,30,Bachelors,9,36,48,98,11,4.0,3,7,Urban,ML Engineer,45313,0 +38812,Male,50,Bachelors,18,46,19,73,43,0.0,5,90,Urban,ML Engineer,120389,0 +38813,Female,40,Diploma,7,21,83,84,98,5.0,7,32,Semi-Urban,Data Analyst,35369,0 +38814,Male,30,Bachelors,3,1,24,26,37,0.0,7,56,Urban,HR Executive,131264,0 +38815,Male,36,Diploma,3,95,15,30,42,3.0,7,6,Rural,Software Engineer,48240,0 +38816,Female,56,Diploma,5,92,75,68,30,4.0,1,91,Urban,Data Analyst,93517,1 +38817,Female,58,Masters,3,65,1,49,11,8.0,3,36,Urban,HR Executive,23454,0 +38818,Female,24,Diploma,11,2,43,49,44,4.0,0,61,Urban,Manager,131473,0 +38819,Male,44,High School,10,42,91,91,92,7.0,2,38,Urban,HR Executive,112101,1 +38820,Female,44,Bachelors,18,54,5,16,89,2.0,4,86,Urban,Software Engineer,62593,0 +38821,Female,26,Masters,5,59,42,15,6,7.0,7,53,Urban,HR Executive,91388,0 +38822,Male,29,Bachelors,19,43,47,49,26,1.0,6,39,Urban,Data Analyst,78574,0 +38823,Female,22,Diploma,19,92,66,31,84,1.0,0,26,Urban,Manager,63733,0 +38824,Male,32,Bachelors,2,32,88,4,57,9.0,7,14,Urban,ML Engineer,95529,0 +38825,Male,39,High School,6,72,87,99,59,4.0,6,19,Urban,ML Engineer,142534,1 +38826,Female,36,Diploma,18,70,52,11,56,2.0,7,65,Urban,Software Engineer,55035,0 +38827,Male,52,Diploma,5,61,18,75,67,9.0,0,6,Urban,HR Executive,45384,0 +38828,Female,30,Bachelors,11,13,35,60,38,3.0,7,6,Semi-Urban,Data Analyst,35527,0 +38829,Male,23,Masters,2,90,58,16,10,5.0,4,4,Urban,ML Engineer,60723,0 +38830,Female,41,Diploma,15,72,37,10,59,1.0,2,5,Urban,Data Analyst,86723,0 +38831,Male,57,Bachelors,5,37,53,37,55,5.0,5,59,Urban,HR Executive,35762,0 +38832,Male,52,Bachelors,18,74,47,38,77,8.0,3,32,Urban,Data Analyst,79162,0 +38833,Male,31,High School,7,92,9,38,66,3.0,6,87,Urban,ML Engineer,64597,0 +38834,Male,31,Bachelors,9,67,69,72,90,9.0,6,61,Semi-Urban,ML Engineer,24891,1 +38835,Female,24,Bachelors,3,91,73,6,73,7.0,5,72,Urban,ML Engineer,85313,1 +38836,Female,33,Masters,2,20,9,51,15,2.0,4,24,Urban,Software Engineer,89166,0 +38837,Male,31,Bachelors,9,91,75,2,64,3.0,3,74,Urban,Manager,115292,1 +38838,Male,54,Bachelors,15,65,40,21,51,2.0,7,34,Semi-Urban,Data Analyst,82525,0 +38839,Male,21,Bachelors,4,23,8,0,85,4.0,2,89,Urban,Data Analyst,64384,0 +38840,Female,55,Masters,6,31,67,23,42,0.0,4,84,Urban,ML Engineer,137684,0 +38841,Male,26,Bachelors,0,99,15,77,59,1.0,4,92,Urban,Manager,146792,1 +38842,Male,38,Bachelors,13,18,14,0,44,2.0,3,10,Urban,Data Analyst,115039,0 +38843,Male,29,Masters,12,80,24,79,97,0.0,2,65,Urban,Data Analyst,124174,1 +38844,Male,43,Diploma,12,46,47,27,11,9.0,5,57,Rural,HR Executive,131247,0 +38845,Male,45,Diploma,19,21,75,55,56,8.0,5,28,Semi-Urban,Data Analyst,41030,0 +38846,Male,58,High School,3,62,37,84,25,6.0,2,98,Urban,HR Executive,126922,1 +38847,Male,42,Masters,1,67,92,2,47,0.0,5,6,Rural,HR Executive,139959,0 +38848,Male,37,Masters,5,35,44,90,48,0.0,5,12,Urban,Data Analyst,32452,0 +38849,Male,29,Masters,19,2,99,88,28,5.0,3,94,Urban,Data Analyst,85376,1 +38850,Male,58,Diploma,0,94,34,51,91,3.0,1,45,Urban,Software Engineer,98697,0 +38851,Male,33,Bachelors,0,19,36,0,66,9.0,7,39,Semi-Urban,HR Executive,114699,0 +38852,Male,38,Bachelors,6,22,58,12,48,4.0,3,75,Urban,HR Executive,31728,0 +38853,Female,30,High School,17,56,7,54,27,7.0,2,32,Urban,Manager,109657,0 +38854,Female,35,Diploma,16,98,61,74,26,3.0,4,81,Semi-Urban,Software Engineer,57217,1 +38855,Female,57,Bachelors,12,50,72,63,86,7.0,7,13,Urban,Software Engineer,26636,0 +38856,Male,38,Bachelors,10,80,53,48,12,4.0,4,90,Urban,Manager,118487,1 +38857,Female,25,Diploma,10,96,80,35,33,4.0,1,84,Semi-Urban,Software Engineer,126391,1 +38858,Male,56,Diploma,12,34,68,29,30,1.0,6,90,Urban,Software Engineer,23461,0 +38859,Male,25,Bachelors,8,59,25,2,44,4.0,4,83,Urban,Software Engineer,61553,0 +38860,Male,57,High School,18,78,99,99,44,3.0,0,30,Urban,Data Analyst,43702,1 +38861,Male,28,Bachelors,4,48,60,4,8,2.0,0,54,Urban,Manager,107280,0 +38862,Male,40,Bachelors,11,71,14,89,96,9.0,1,19,Urban,Software Engineer,104096,0 +38863,Male,54,Bachelors,13,2,70,20,7,2.0,0,49,Semi-Urban,HR Executive,131053,0 +38864,Male,46,Diploma,18,41,31,10,48,9.0,2,54,Semi-Urban,ML Engineer,125474,0 +38865,Female,35,Masters,9,21,19,34,64,7.0,3,89,Rural,HR Executive,97418,0 +38866,Female,45,Diploma,15,95,26,3,86,1.0,5,51,Rural,Data Analyst,92669,0 +38867,Other,51,Bachelors,15,65,36,20,92,0.0,5,50,Semi-Urban,HR Executive,30428,0 +38868,Male,29,Masters,2,66,95,1,70,5.0,7,62,Urban,HR Executive,57708,0 +38869,Female,57,Bachelors,17,12,45,49,74,5.0,4,71,Semi-Urban,HR Executive,56085,0 +38870,Female,55,Diploma,18,74,6,64,57,4.0,1,42,Urban,ML Engineer,135101,0 +38871,Female,46,Bachelors,13,77,23,49,12,2.0,5,77,Urban,ML Engineer,51800,0 +38872,Male,24,Bachelors,5,0,52,43,23,0.0,2,67,Rural,ML Engineer,129233,0 +38873,Female,46,PhD,17,82,70,6,28,2.0,6,52,Urban,Data Analyst,124585,0 +38874,Male,31,Masters,15,26,17,59,48,4.0,0,22,Urban,ML Engineer,29931,0 +38875,Male,59,Diploma,5,64,54,86,31,0.0,6,3,Rural,Software Engineer,36060,0 +38876,Male,25,Bachelors,9,19,93,60,13,0.0,0,16,Urban,Manager,148398,0 +38877,Female,40,High School,3,67,32,56,93,2.0,4,49,Urban,Data Analyst,27053,0 +38878,Male,43,Diploma,12,51,13,86,23,4.0,7,69,Rural,HR Executive,94507,0 +38879,Male,57,Bachelors,11,60,75,33,3,8.0,1,24,Urban,ML Engineer,79287,0 +38880,Female,23,Bachelors,0,2,30,35,22,9.0,4,20,Semi-Urban,HR Executive,57121,0 +38881,Male,33,Bachelors,1,87,7,7,24,2.0,3,59,Urban,Manager,137217,0 +38882,Female,56,High School,17,40,44,95,32,7.0,6,16,Urban,Data Analyst,55772,0 +38883,Female,53,Masters,13,77,12,3,36,2.0,2,50,Urban,Manager,51664,0 +38884,Male,41,Diploma,2,93,62,9,44,3.0,2,87,Semi-Urban,HR Executive,71639,1 +38885,Male,40,Bachelors,2,17,3,67,7,1.0,4,17,Urban,HR Executive,25276,0 +38886,Male,38,Bachelors,0,20,29,78,97,0.0,6,69,Urban,Data Analyst,148808,0 +38887,Other,48,Bachelors,9,60,7,5,79,2.0,3,52,Urban,HR Executive,96624,0 +38888,Female,47,Diploma,7,48,7,41,62,3.0,2,86,Semi-Urban,Manager,28179,0 +38889,Male,44,Bachelors,18,97,13,22,58,0.0,1,67,Rural,Manager,59997,0 +38890,Male,53,Bachelors,0,0,52,30,63,6.0,5,56,Semi-Urban,ML Engineer,99921,0 +38891,Male,26,High School,6,56,72,14,4,7.0,3,51,Rural,HR Executive,127104,0 +38892,Female,56,Diploma,4,23,33,35,55,8.0,2,36,Semi-Urban,Data Analyst,40457,0 +38893,Male,56,Masters,7,24,69,38,18,8.0,7,12,Urban,HR Executive,66489,0 +38894,Male,30,Masters,6,81,68,75,47,9.0,7,11,Urban,ML Engineer,94447,1 +38895,Female,47,Bachelors,0,34,54,43,23,8.0,3,34,Urban,Data Analyst,128777,0 +38896,Male,35,Diploma,4,93,26,41,71,9.0,0,29,Urban,Manager,95451,0 +38897,Male,55,Diploma,5,44,7,18,23,1.0,0,55,Semi-Urban,HR Executive,132296,0 +38898,Female,52,High School,17,83,14,80,83,4.0,7,11,Semi-Urban,Data Analyst,38028,0 +38899,Male,49,Bachelors,14,35,1,69,70,3.0,2,25,Semi-Urban,Data Analyst,141192,0 +38900,Male,58,Diploma,4,71,29,37,75,2.0,6,34,Urban,ML Engineer,32933,0 +38901,Female,23,PhD,12,75,42,26,64,8.0,0,84,Semi-Urban,Manager,55387,0 +38902,Male,36,Bachelors,6,62,19,36,30,0.0,1,5,Urban,Manager,129401,0 +38903,Female,56,Masters,19,40,97,51,89,5.0,6,68,Rural,Manager,84034,1 +38904,Female,59,Bachelors,8,92,37,1,8,1.0,4,22,Urban,Software Engineer,83577,0 +38905,Female,32,Masters,19,69,8,87,99,9.0,7,67,Urban,ML Engineer,61610,0 +38906,Female,51,Bachelors,11,75,59,0,16,9.0,7,94,Semi-Urban,Manager,91408,0 +38907,Female,56,High School,8,30,99,30,20,5.0,0,50,Urban,Manager,32797,0 +38908,Male,54,Bachelors,16,7,96,31,46,7.0,2,40,Rural,Data Analyst,115216,0 +38909,Male,47,PhD,19,10,4,53,65,0.0,3,21,Urban,Software Engineer,68989,0 +38910,Male,25,Bachelors,13,79,48,41,26,4.0,6,55,Urban,Manager,149499,0 +38911,Female,55,Bachelors,14,52,89,29,70,8.0,2,29,Rural,Data Analyst,57430,0 +38912,Male,31,Diploma,14,18,37,80,92,8.0,1,82,Rural,Data Analyst,81965,0 +38913,Male,39,Diploma,4,84,5,64,23,9.0,4,68,Urban,HR Executive,86358,0 +38914,Female,34,Bachelors,12,97,17,99,8,2.0,6,20,Urban,Manager,112025,0 +38915,Male,54,High School,11,92,98,42,35,3.0,6,81,Urban,Manager,56268,1 +38916,Female,58,Bachelors,19,48,96,93,77,7.0,5,52,Urban,Software Engineer,116350,1 +38917,Male,34,Bachelors,0,55,43,52,30,3.0,6,19,Urban,Software Engineer,125604,0 +38918,Male,34,Bachelors,16,97,12,6,61,1.0,3,43,Semi-Urban,ML Engineer,101895,0 +38919,Male,41,Bachelors,0,88,71,19,11,1.0,4,41,Semi-Urban,HR Executive,117498,0 +38920,Male,34,Masters,13,41,25,78,11,2.0,2,84,Semi-Urban,Software Engineer,60661,0 +38921,Male,24,Diploma,13,11,70,21,15,5.0,6,27,Urban,ML Engineer,94180,0 +38922,Male,39,Bachelors,11,94,10,91,41,8.0,5,31,Urban,HR Executive,46733,0 +38923,Male,56,Diploma,4,87,35,59,70,7.0,7,36,Semi-Urban,ML Engineer,94590,0 +38924,Female,38,Diploma,11,57,97,68,25,4.0,7,88,Semi-Urban,Manager,49943,1 +38925,Male,43,Bachelors,10,84,42,52,98,5.0,1,77,Semi-Urban,Manager,71448,1 +38926,Female,39,High School,5,7,78,71,33,7.0,7,54,Urban,Software Engineer,31609,0 +38927,Female,48,Masters,19,81,91,13,75,8.0,7,83,Urban,HR Executive,133425,1 +38928,Male,32,Bachelors,4,18,16,89,94,3.0,7,36,Urban,HR Executive,33428,0 +38929,Male,21,Diploma,11,44,52,58,87,8.0,7,72,Rural,HR Executive,110855,0 +38930,Male,39,PhD,12,51,98,41,45,2.0,6,47,Urban,ML Engineer,84608,1 +38931,Female,50,High School,13,94,82,81,57,4.0,3,97,Urban,Software Engineer,72158,1 +38932,Female,55,Bachelors,15,96,46,4,53,0.0,5,78,Urban,ML Engineer,78619,0 +38933,Male,57,Diploma,11,22,71,30,11,5.0,2,79,Urban,Data Analyst,41159,0 +38934,Male,27,Bachelors,19,98,63,47,16,2.0,3,32,Urban,HR Executive,83519,1 +38935,Other,27,Masters,13,28,81,14,39,2.0,2,64,Urban,ML Engineer,140339,0 +38936,Female,25,Bachelors,5,16,82,3,12,2.0,6,30,Urban,ML Engineer,104490,0 +38937,Male,27,Diploma,0,56,72,78,98,1.0,5,59,Semi-Urban,Manager,42704,1 +38938,Male,53,Masters,14,58,98,26,12,9.0,5,60,Semi-Urban,Software Engineer,23798,1 +38939,Male,54,Masters,9,0,59,17,98,2.0,2,68,Rural,Data Analyst,133095,0 +38940,Female,41,Masters,11,47,77,21,3,9.0,1,91,Urban,ML Engineer,109926,0 +38941,Female,28,Bachelors,2,13,24,80,14,6.0,4,76,Semi-Urban,Manager,148734,0 +38942,Male,43,Bachelors,16,7,25,50,32,6.0,4,37,Urban,HR Executive,135124,0 +38943,Male,54,Masters,5,3,20,65,1,6.0,5,58,Rural,HR Executive,46675,0 +38944,Female,43,Bachelors,5,11,42,45,99,8.0,6,66,Semi-Urban,ML Engineer,142258,0 +38945,Female,56,High School,13,2,45,37,38,7.0,7,32,Urban,Data Analyst,41483,0 +38946,Male,31,Bachelors,12,70,74,52,97,5.0,1,46,Urban,Data Analyst,22840,1 +38947,Male,30,High School,10,29,57,81,1,2.0,4,6,Urban,Manager,26817,0 +38948,Male,58,Bachelors,7,14,40,36,60,1.0,3,28,Semi-Urban,Software Engineer,125120,0 +38949,Male,57,Diploma,12,49,98,47,9,1.0,3,5,Rural,Software Engineer,37259,0 +38950,Male,57,Bachelors,5,66,5,84,81,1.0,1,5,Semi-Urban,Manager,121763,0 +38951,Male,22,Bachelors,16,67,91,15,23,4.0,6,32,Urban,ML Engineer,79285,0 +38952,Other,23,High School,7,30,87,50,90,5.0,0,92,Semi-Urban,Manager,135343,1 +38953,Female,31,High School,7,85,32,90,32,2.0,0,75,Urban,HR Executive,89687,1 +38954,Male,46,Diploma,19,32,19,1,8,2.0,0,18,Urban,Data Analyst,92099,0 +38955,Female,44,Diploma,15,23,88,6,8,0.0,5,86,Urban,Manager,46162,0 +38956,Female,57,Bachelors,12,93,64,69,72,2.0,1,1,Urban,Manager,127104,0 +38957,Male,34,Bachelors,0,10,22,61,70,6.0,5,65,Semi-Urban,HR Executive,118107,0 +38958,Female,47,Bachelors,3,74,40,45,34,3.0,1,6,Semi-Urban,HR Executive,71549,0 +38959,Male,27,Diploma,8,6,33,97,33,2.0,3,98,Rural,ML Engineer,139882,0 +38960,Female,22,Bachelors,15,1,53,22,99,5.0,1,75,Rural,HR Executive,122070,0 +38961,Male,35,Masters,6,77,18,69,96,5.0,5,95,Rural,Data Analyst,66824,1 +38962,Male,50,Masters,16,78,48,89,27,2.0,6,70,Urban,Manager,136845,1 +38963,Male,26,Bachelors,1,21,49,0,96,6.0,6,55,Urban,HR Executive,97071,0 +38964,Male,47,Bachelors,15,42,65,9,51,3.0,4,62,Urban,HR Executive,91321,0 +38965,Male,42,Bachelors,6,45,85,87,38,8.0,1,7,Urban,Manager,145564,0 +38966,Female,25,Diploma,18,74,59,27,8,6.0,5,66,Urban,Manager,76652,0 +38967,Female,49,Bachelors,16,61,82,18,60,6.0,4,75,Urban,Data Analyst,94954,0 +38968,Male,54,Masters,5,61,25,36,50,0.0,3,36,Urban,Software Engineer,115557,0 +38969,Male,37,Bachelors,14,49,89,17,37,0.0,6,76,Semi-Urban,ML Engineer,59496,0 +38970,Female,28,Diploma,16,88,11,74,8,1.0,5,58,Urban,ML Engineer,126360,0 +38971,Male,35,Diploma,1,67,2,10,98,8.0,7,24,Semi-Urban,Data Analyst,88985,0 +38972,Male,36,High School,7,25,42,81,22,2.0,2,21,Rural,HR Executive,126873,0 +38973,Female,46,High School,9,98,0,82,31,4.0,0,67,Rural,ML Engineer,121934,1 +38974,Female,38,Diploma,17,77,69,71,14,2.0,2,32,Urban,Data Analyst,135993,1 +38975,Female,56,Bachelors,9,75,54,82,29,3.0,0,30,Urban,Data Analyst,85813,1 +38976,Male,27,Bachelors,6,47,1,44,45,1.0,6,31,Rural,Data Analyst,23009,0 +38977,Male,49,Bachelors,14,45,42,17,99,8.0,7,78,Urban,Manager,65317,0 +38978,Female,23,Bachelors,13,34,87,4,35,9.0,3,5,Urban,Manager,124864,0 +38979,Female,28,Diploma,7,7,44,82,88,8.0,2,84,Rural,Software Engineer,113331,0 +38980,Other,41,Masters,2,80,81,95,70,9.0,2,0,Urban,Manager,58302,1 +38981,Male,27,Masters,14,76,67,59,30,3.0,5,7,Urban,ML Engineer,24766,0 +38982,Female,48,Bachelors,17,36,82,89,85,6.0,3,35,Urban,ML Engineer,109639,1 +38983,Male,52,Bachelors,15,68,64,66,13,0.0,0,32,Semi-Urban,ML Engineer,130394,0 +38984,Male,54,Bachelors,9,21,57,52,45,1.0,4,99,Semi-Urban,Manager,115295,0 +38985,Male,53,Bachelors,4,38,60,23,12,9.0,7,17,Rural,ML Engineer,52637,0 +38986,Other,49,PhD,10,48,26,0,36,7.0,0,63,Urban,Software Engineer,137200,0 +38987,Male,39,Masters,15,6,16,1,58,4.0,6,34,Semi-Urban,HR Executive,109760,0 +38988,Male,43,Diploma,10,51,75,71,31,6.0,4,55,Rural,ML Engineer,26008,1 +38989,Female,40,Diploma,19,70,76,38,87,4.0,2,98,Rural,HR Executive,28349,1 +38990,Male,44,High School,4,89,24,80,43,6.0,4,33,Urban,ML Engineer,120339,0 +38991,Male,23,Bachelors,7,4,18,79,62,2.0,3,88,Rural,Data Analyst,86095,0 +38992,Female,34,PhD,7,82,4,66,60,7.0,6,39,Semi-Urban,ML Engineer,128146,0 +38993,Female,46,Masters,4,33,56,58,98,9.0,7,9,Rural,Data Analyst,53040,0 +38994,Male,21,Bachelors,2,82,71,33,24,3.0,1,84,Urban,Manager,40480,1 +38995,Female,44,Bachelors,2,8,66,82,17,1.0,0,44,Urban,Software Engineer,144688,0 +38996,Male,26,Bachelors,4,95,71,7,34,8.0,7,26,Semi-Urban,Manager,96077,0 +38997,Female,24,High School,12,83,2,41,16,6.0,2,78,Semi-Urban,Manager,73277,0 +38998,Female,49,Diploma,17,90,63,44,59,8.0,0,12,Urban,ML Engineer,53689,0 +38999,Male,29,Bachelors,13,21,96,82,86,6.0,1,35,Urban,Manager,110989,0 +39000,Female,24,High School,13,59,0,99,7,6.0,3,55,Rural,ML Engineer,90870,0 +39001,Male,24,Diploma,12,96,94,40,31,2.0,3,82,Rural,Manager,68573,1 +39002,Male,35,Bachelors,17,57,10,18,71,2.0,6,92,Urban,Data Analyst,60919,0 +39003,Female,51,Bachelors,1,3,49,20,69,9.0,3,17,Urban,Data Analyst,123821,0 +39004,Male,44,Bachelors,10,92,87,13,70,9.0,6,67,Urban,Software Engineer,69227,1 +39005,Male,42,Diploma,16,44,18,4,42,7.0,3,43,Urban,Software Engineer,54235,0 +39006,Male,50,Bachelors,4,30,77,45,80,0.0,1,79,Urban,ML Engineer,45361,0 +39007,Male,55,Masters,4,90,66,79,83,6.0,4,17,Rural,HR Executive,110815,1 +39008,Female,46,Bachelors,6,71,78,52,78,9.0,3,49,Urban,Manager,81015,1 +39009,Female,22,PhD,15,1,16,8,16,2.0,7,53,Urban,Software Engineer,24638,0 +39010,Male,35,Diploma,4,54,89,88,81,1.0,5,7,Urban,Manager,77416,1 +39011,Male,48,PhD,13,97,94,1,84,7.0,3,11,Semi-Urban,HR Executive,81060,0 +39012,Male,49,Bachelors,11,84,4,95,78,8.0,3,40,Semi-Urban,HR Executive,99748,0 +39013,Male,48,Bachelors,5,19,0,97,14,8.0,0,75,Semi-Urban,Data Analyst,94534,0 +39014,Male,34,Bachelors,8,80,77,10,19,3.0,5,75,Urban,Manager,137123,1 +39015,Male,24,PhD,1,61,68,94,86,6.0,2,21,Rural,Manager,95265,1 +39016,Male,42,Diploma,1,53,65,2,7,8.0,0,2,Semi-Urban,Software Engineer,147075,0 +39017,Female,57,Masters,5,32,45,26,41,4.0,3,67,Urban,ML Engineer,25404,0 +39018,Female,59,Diploma,5,70,62,85,17,2.0,2,84,Rural,Manager,127493,1 +39019,Female,45,Bachelors,11,15,52,16,51,8.0,6,52,Semi-Urban,Software Engineer,116936,0 +39020,Female,21,Bachelors,16,33,35,28,88,1.0,0,27,Urban,Manager,103914,0 +39021,Male,36,High School,19,48,6,29,21,0.0,1,27,Semi-Urban,Manager,94977,0 +39022,Female,33,Bachelors,10,25,92,14,4,3.0,6,61,Urban,Data Analyst,143343,0 +39023,Female,45,High School,15,9,89,20,42,9.0,5,58,Rural,ML Engineer,134336,0 +39024,Female,52,Bachelors,15,63,59,22,65,5.0,2,26,Urban,Data Analyst,107627,0 +39025,Male,43,Diploma,5,66,72,4,12,2.0,3,35,Urban,Data Analyst,51785,0 +39026,Female,43,Bachelors,18,28,68,42,61,3.0,1,59,Urban,HR Executive,74000,0 +39027,Female,53,High School,11,20,57,69,84,6.0,1,8,Semi-Urban,Data Analyst,70212,0 +39028,Male,38,Bachelors,6,16,47,26,30,2.0,7,57,Urban,Manager,78650,0 +39029,Other,57,High School,5,56,33,89,16,5.0,1,20,Rural,HR Executive,32495,0 +39030,Male,26,Diploma,11,93,3,10,34,8.0,2,40,Urban,ML Engineer,134773,0 +39031,Male,22,Masters,16,98,20,36,86,2.0,5,85,Urban,Manager,87890,1 +39032,Male,31,Bachelors,14,31,27,31,32,4.0,3,1,Rural,ML Engineer,41233,0 +39033,Male,29,Diploma,16,20,81,80,13,5.0,7,79,Urban,Software Engineer,71732,1 +39034,Female,35,Masters,10,64,86,10,7,3.0,6,38,Urban,Data Analyst,53960,0 +39035,Male,31,Masters,6,99,10,5,4,4.0,2,12,Semi-Urban,Manager,140810,0 +39036,Male,27,Diploma,11,20,15,47,41,3.0,6,55,Urban,ML Engineer,97878,0 +39037,Female,42,High School,13,98,94,60,52,3.0,6,56,Urban,Software Engineer,130960,1 +39038,Male,24,Masters,10,32,55,81,44,3.0,2,57,Semi-Urban,Data Analyst,121289,0 +39039,Female,26,PhD,8,36,42,7,62,7.0,3,99,Semi-Urban,Manager,140781,0 +39040,Female,27,Masters,7,82,76,54,11,2.0,3,83,Semi-Urban,HR Executive,107459,1 +39041,Male,52,Bachelors,16,8,42,24,89,2.0,3,39,Urban,HR Executive,43882,0 +39042,Other,35,Masters,17,47,68,0,48,9.0,6,35,Semi-Urban,Software Engineer,54159,0 +39043,Male,24,Bachelors,14,69,13,12,67,7.0,6,70,Rural,HR Executive,50212,0 +39044,Female,46,Diploma,13,30,17,90,46,3.0,1,48,Urban,ML Engineer,143565,0 +39045,Female,59,Masters,11,3,83,98,54,9.0,6,91,Rural,Software Engineer,113170,1 +39046,Female,52,Masters,19,36,81,32,93,4.0,5,31,Urban,ML Engineer,120469,0 +39047,Male,51,Bachelors,1,54,27,24,28,0.0,3,53,Urban,Data Analyst,95987,0 +39048,Male,51,PhD,0,12,57,88,82,0.0,6,14,Urban,Data Analyst,106328,0 +39049,Female,48,High School,12,69,37,80,62,6.0,2,8,Urban,ML Engineer,98852,0 +39050,Other,56,Bachelors,1,42,3,64,33,9.0,6,79,Urban,Manager,136992,0 +39051,Male,41,Bachelors,11,77,29,63,30,4.0,3,92,Urban,ML Engineer,66615,1 +39052,Male,59,Diploma,18,13,44,91,15,9.0,3,6,Urban,Data Analyst,90704,0 +39053,Male,47,Diploma,14,65,19,88,49,6.0,2,51,Urban,HR Executive,146248,0 +39054,Female,29,Masters,11,43,23,76,89,2.0,5,53,Urban,ML Engineer,53370,0 +39055,Male,48,High School,13,80,35,90,97,4.0,2,71,Urban,Software Engineer,81828,1 +39056,Female,30,Bachelors,14,84,71,90,12,9.0,1,98,Urban,HR Executive,134768,1 +39057,Female,52,Bachelors,18,34,77,40,66,7.0,7,91,Rural,ML Engineer,149217,1 +39058,Male,57,Bachelors,15,44,30,10,49,8.0,2,72,Semi-Urban,Software Engineer,34645,0 +39059,Male,41,Diploma,10,47,80,8,26,5.0,2,60,Semi-Urban,ML Engineer,72388,0 +39060,Female,46,Diploma,9,57,44,3,62,7.0,7,80,Urban,ML Engineer,61146,0 +39061,Male,57,Bachelors,12,16,79,56,93,7.0,0,56,Urban,Data Analyst,99974,0 +39062,Male,48,PhD,3,70,93,9,14,5.0,0,83,Urban,Data Analyst,66857,1 +39063,Male,45,Bachelors,15,91,33,66,2,0.0,6,9,Urban,Data Analyst,69967,0 +39064,Male,33,High School,11,4,49,15,94,9.0,0,16,Urban,Manager,25854,0 +39065,Male,48,PhD,8,22,48,20,38,8.0,6,20,Rural,Data Analyst,144458,0 +39066,Female,27,Diploma,17,40,22,30,95,8.0,3,65,Urban,Manager,123929,0 +39067,Female,51,Diploma,16,91,4,52,4,6.0,6,62,Semi-Urban,ML Engineer,70491,0 +39068,Other,37,High School,12,97,70,25,58,3.0,2,25,Rural,Software Engineer,38885,0 +39069,Male,32,Bachelors,4,51,5,83,21,1.0,2,82,Urban,Data Analyst,37584,0 +39070,Male,38,Bachelors,10,60,1,51,84,2.0,6,97,Rural,HR Executive,35493,0 +39071,Male,39,Bachelors,12,40,81,54,14,8.0,2,6,Semi-Urban,HR Executive,133253,0 +39072,Male,38,PhD,4,51,4,42,2,3.0,7,62,Urban,ML Engineer,118813,0 +39073,Male,40,Masters,3,95,77,80,32,3.0,0,5,Rural,Software Engineer,36997,1 +39074,Male,25,Bachelors,5,68,16,19,83,9.0,3,6,Semi-Urban,ML Engineer,92809,0 +39075,Male,34,Bachelors,3,11,32,44,63,5.0,1,70,Semi-Urban,Software Engineer,31898,0 +39076,Male,34,Bachelors,12,54,38,7,20,7.0,7,15,Rural,HR Executive,84078,0 +39077,Male,27,Diploma,0,57,98,81,18,3.0,0,27,Semi-Urban,Software Engineer,87888,1 +39078,Male,53,Masters,9,9,83,97,0,9.0,7,38,Urban,HR Executive,89525,0 +39079,Male,39,Bachelors,5,98,9,68,37,3.0,6,33,Urban,ML Engineer,118169,0 +39080,Female,42,Masters,13,81,2,19,29,6.0,6,53,Urban,Manager,36794,0 +39081,Male,58,Masters,15,33,17,77,51,5.0,5,45,Semi-Urban,ML Engineer,66116,0 +39082,Male,25,Diploma,0,57,51,34,72,6.0,2,12,Urban,ML Engineer,100423,0 +39083,Male,30,Bachelors,1,76,64,16,47,8.0,3,75,Semi-Urban,HR Executive,49400,0 +39084,Male,51,Bachelors,11,92,30,2,32,3.0,7,22,Semi-Urban,ML Engineer,43912,0 +39085,Female,43,Diploma,18,76,43,18,12,0.0,0,67,Semi-Urban,HR Executive,75858,0 +39086,Male,58,Bachelors,6,95,85,42,81,8.0,3,52,Semi-Urban,Data Analyst,80851,1 +39087,Female,35,Bachelors,16,2,80,22,9,7.0,1,36,Semi-Urban,HR Executive,58376,0 +39088,Male,23,High School,4,12,78,47,78,4.0,0,94,Rural,HR Executive,92090,0 +39089,Female,53,Masters,3,73,16,45,52,4.0,5,32,Urban,ML Engineer,62720,0 +39090,Female,41,Bachelors,11,63,5,13,10,6.0,7,72,Semi-Urban,HR Executive,33616,0 +39091,Female,29,Bachelors,8,41,20,8,31,3.0,2,86,Semi-Urban,HR Executive,71796,0 +39092,Male,51,Masters,13,17,8,53,71,0.0,6,73,Semi-Urban,Data Analyst,70895,0 +39093,Female,27,Bachelors,4,67,80,60,38,5.0,7,10,Urban,ML Engineer,80571,0 +39094,Male,56,Diploma,14,75,23,43,11,9.0,3,23,Urban,HR Executive,93824,0 +39095,Male,43,High School,17,99,50,25,35,2.0,0,72,Urban,Software Engineer,103722,1 +39096,Female,44,Bachelors,12,55,78,95,97,9.0,2,79,Rural,ML Engineer,37227,1 +39097,Other,31,Bachelors,15,11,9,47,60,9.0,7,29,Rural,Data Analyst,37685,0 +39098,Male,54,High School,16,81,31,1,12,1.0,6,73,Urban,ML Engineer,131961,0 +39099,Female,22,Bachelors,2,88,40,8,38,4.0,1,12,Rural,Manager,71884,0 +39100,Male,36,Bachelors,13,26,33,10,36,6.0,3,53,Semi-Urban,Software Engineer,147092,0 +39101,Male,43,Masters,18,56,87,82,73,7.0,2,16,Urban,Software Engineer,140134,1 +39102,Female,26,Diploma,10,23,10,85,56,5.0,1,94,Urban,Manager,70512,0 +39103,Male,22,Masters,1,7,79,79,32,0.0,0,0,Rural,Software Engineer,105688,0 +39104,Male,42,High School,11,62,83,35,30,0.0,0,98,Urban,ML Engineer,55613,1 +39105,Male,25,Diploma,12,28,53,27,4,0.0,3,95,Urban,ML Engineer,141871,0 +39106,Female,47,Masters,10,77,61,36,15,2.0,3,48,Urban,Software Engineer,52943,0 +39107,Male,44,Bachelors,8,5,59,79,21,7.0,3,83,Urban,Manager,27509,0 +39108,Male,39,PhD,5,99,76,69,3,0.0,1,43,Urban,Data Analyst,29386,1 +39109,Male,54,High School,12,29,45,92,55,3.0,6,78,Urban,HR Executive,110794,1 +39110,Female,24,Bachelors,12,49,27,42,48,0.0,5,47,Rural,Manager,65107,0 +39111,Female,23,Diploma,17,30,22,31,24,4.0,3,48,Urban,Data Analyst,66100,0 +39112,Female,54,Bachelors,5,89,20,82,20,7.0,3,6,Urban,Manager,105654,0 +39113,Female,27,Diploma,11,31,61,47,24,7.0,4,61,Urban,HR Executive,95243,0 +39114,Male,29,Masters,16,46,76,95,36,0.0,0,22,Rural,ML Engineer,36925,1 +39115,Male,21,Diploma,10,42,55,56,55,9.0,5,91,Rural,Data Analyst,134993,1 +39116,Male,48,Diploma,15,71,68,79,54,2.0,3,45,Urban,ML Engineer,53656,1 +39117,Male,56,Diploma,3,64,99,37,20,0.0,2,39,Urban,Data Analyst,35792,1 +39118,Male,28,Masters,13,53,37,36,2,4.0,4,82,Urban,HR Executive,57606,0 +39119,Female,30,Diploma,17,21,50,91,27,8.0,5,15,Urban,Manager,74801,0 +39120,Male,45,Masters,7,6,86,97,83,7.0,2,59,Rural,Software Engineer,117827,1 +39121,Male,47,Masters,13,40,52,93,0,0.0,1,84,Semi-Urban,HR Executive,35731,1 +39122,Male,23,High School,0,79,41,18,84,6.0,6,47,Urban,Data Analyst,68934,0 +39123,Male,56,Masters,1,90,13,42,39,5.0,7,33,Urban,ML Engineer,24327,0 +39124,Male,45,Masters,9,71,68,73,18,4.0,6,21,Semi-Urban,Manager,74683,0 +39125,Female,50,Diploma,8,63,13,31,12,6.0,5,50,Semi-Urban,Data Analyst,42311,0 +39126,Male,36,Bachelors,4,84,54,6,55,1.0,1,51,Semi-Urban,Data Analyst,43366,0 +39127,Male,55,PhD,2,50,28,53,33,7.0,2,86,Rural,Software Engineer,33296,0 +39128,Female,41,Masters,6,86,72,59,44,2.0,6,94,Urban,HR Executive,36866,1 +39129,Male,42,Bachelors,16,22,78,6,0,0.0,3,17,Urban,Manager,131058,0 +39130,Female,24,Bachelors,16,39,28,37,61,5.0,6,10,Urban,HR Executive,58365,0 +39131,Male,53,Diploma,14,46,80,66,51,4.0,2,99,Semi-Urban,Manager,25090,1 +39132,Female,51,Masters,17,33,28,63,36,9.0,4,18,Rural,HR Executive,109662,0 +39133,Male,53,Bachelors,9,52,15,95,59,6.0,2,18,Semi-Urban,ML Engineer,139377,0 +39134,Female,40,Diploma,2,25,78,21,75,4.0,1,17,Rural,Data Analyst,31300,0 +39135,Male,32,Bachelors,7,38,44,15,56,8.0,1,91,Semi-Urban,Data Analyst,44637,0 +39136,Male,50,Bachelors,14,53,71,69,3,1.0,6,40,Urban,Manager,122088,0 +39137,Female,53,Bachelors,19,61,77,46,29,8.0,6,72,Rural,ML Engineer,137623,1 +39138,Male,47,Diploma,13,53,68,44,97,5.0,2,30,Semi-Urban,ML Engineer,32461,0 +39139,Male,40,Bachelors,18,51,87,85,62,1.0,7,6,Urban,ML Engineer,80077,0 +39140,Male,41,Diploma,19,17,28,45,11,6.0,3,94,Semi-Urban,HR Executive,51205,0 +39141,Male,24,Diploma,4,22,9,24,55,4.0,2,71,Semi-Urban,ML Engineer,137005,0 +39142,Female,49,Masters,13,52,94,59,28,4.0,0,71,Semi-Urban,Manager,131198,1 +39143,Female,24,Diploma,7,25,21,58,41,1.0,5,39,Semi-Urban,Data Analyst,92996,0 +39144,Male,31,Bachelors,11,49,35,36,96,7.0,4,62,Rural,Data Analyst,33465,0 +39145,Male,55,Masters,5,22,94,34,11,0.0,2,38,Urban,Data Analyst,112362,0 +39146,Female,56,Bachelors,10,78,3,42,37,7.0,3,46,Semi-Urban,Data Analyst,89866,0 +39147,Male,45,Masters,15,9,68,85,20,1.0,5,43,Urban,ML Engineer,52607,0 +39148,Female,54,Bachelors,17,90,51,5,0,8.0,4,34,Rural,Software Engineer,107500,0 +39149,Male,26,Masters,6,8,70,15,12,9.0,6,67,Rural,Manager,43452,0 +39150,Female,31,Masters,5,20,46,18,9,1.0,5,96,Semi-Urban,HR Executive,84013,0 +39151,Male,49,Diploma,10,20,49,59,9,2.0,5,76,Urban,Software Engineer,98482,0 +39152,Male,48,Diploma,12,12,39,46,40,8.0,4,54,Urban,Manager,48218,0 +39153,Male,22,Bachelors,16,39,70,87,1,4.0,5,72,Semi-Urban,ML Engineer,138661,1 +39154,Female,55,Diploma,15,61,77,31,0,0.0,7,17,Urban,HR Executive,66755,0 +39155,Male,23,Bachelors,7,33,33,55,14,3.0,5,44,Semi-Urban,HR Executive,53479,0 +39156,Female,48,Bachelors,11,93,8,39,16,9.0,4,38,Urban,Software Engineer,72077,0 +39157,Male,22,Bachelors,19,79,77,83,81,5.0,3,55,Rural,ML Engineer,66082,1 +39158,Male,32,Diploma,5,19,95,12,23,2.0,6,28,Semi-Urban,Manager,70231,0 +39159,Female,26,Bachelors,9,91,2,12,19,0.0,5,73,Rural,Software Engineer,41697,0 +39160,Male,48,High School,2,7,61,32,89,0.0,3,37,Urban,Manager,93408,0 +39161,Male,57,Diploma,14,53,51,42,88,9.0,4,33,Semi-Urban,Data Analyst,94511,0 +39162,Male,34,Bachelors,17,73,7,57,18,9.0,5,37,Urban,Software Engineer,67454,0 +39163,Other,43,Bachelors,8,92,23,33,62,6.0,4,44,Urban,ML Engineer,24332,0 +39164,Male,32,Masters,5,83,17,94,15,7.0,3,4,Rural,Data Analyst,43403,0 +39165,Male,48,PhD,18,14,90,86,42,6.0,3,44,Semi-Urban,Data Analyst,77678,0 +39166,Male,30,Bachelors,4,91,61,23,0,6.0,7,0,Semi-Urban,ML Engineer,86709,0 +39167,Male,27,Bachelors,5,28,15,3,24,7.0,1,82,Urban,Software Engineer,149849,0 +39168,Male,28,Masters,6,52,14,44,9,7.0,2,8,Urban,ML Engineer,46038,0 +39169,Female,37,Bachelors,1,51,25,94,13,4.0,5,84,Urban,Data Analyst,25437,1 +39170,Male,50,High School,16,22,98,10,95,4.0,6,72,Rural,ML Engineer,139179,0 +39171,Female,49,Bachelors,16,87,48,35,28,3.0,2,5,Urban,Software Engineer,44862,0 +39172,Male,39,High School,15,61,41,75,94,4.0,5,76,Urban,Data Analyst,21844,1 +39173,Female,58,Bachelors,15,72,25,40,83,6.0,0,66,Rural,ML Engineer,77690,0 +39174,Other,23,Masters,12,61,74,40,41,5.0,4,58,Rural,HR Executive,98640,0 +39175,Male,26,Bachelors,19,64,61,61,50,4.0,2,36,Semi-Urban,Data Analyst,43814,0 +39176,Male,28,Diploma,10,17,14,19,48,4.0,5,24,Rural,ML Engineer,81646,0 +39177,Female,35,Masters,11,67,12,59,96,3.0,4,26,Urban,HR Executive,52277,0 +39178,Male,27,Bachelors,19,72,38,66,59,5.0,4,2,Urban,Software Engineer,92719,0 +39179,Male,32,High School,7,55,28,18,74,5.0,3,7,Rural,Data Analyst,21828,0 +39180,Other,21,Masters,14,1,88,60,89,9.0,5,59,Rural,Software Engineer,49078,0 +39181,Male,36,Masters,13,95,11,98,13,0.0,3,40,Urban,Manager,41086,1 +39182,Male,48,Masters,2,90,36,22,26,9.0,0,73,Urban,Software Engineer,81894,0 +39183,Female,32,High School,3,70,34,58,3,6.0,5,56,Urban,Software Engineer,58024,0 +39184,Male,54,Bachelors,2,98,65,28,60,8.0,1,31,Rural,Software Engineer,131875,0 +39185,Male,53,High School,0,84,32,13,54,1.0,1,46,Urban,Data Analyst,84712,0 +39186,Male,40,Diploma,2,0,59,97,30,8.0,1,63,Semi-Urban,Data Analyst,80111,0 +39187,Male,40,PhD,7,40,98,32,89,3.0,1,10,Urban,Data Analyst,36346,0 +39188,Female,27,Bachelors,0,90,88,35,13,7.0,1,33,Urban,HR Executive,97545,1 +39189,Female,45,Diploma,19,76,86,81,68,2.0,0,35,Urban,Software Engineer,130578,1 +39190,Male,33,Masters,7,35,10,26,72,4.0,1,68,Urban,ML Engineer,118873,0 +39191,Female,54,PhD,0,40,73,97,57,9.0,6,90,Urban,Manager,70865,1 +39192,Male,38,Masters,4,32,96,33,72,0.0,4,51,Rural,HR Executive,147439,0 +39193,Female,36,Masters,14,35,19,58,32,7.0,3,9,Urban,Software Engineer,53549,0 +39194,Male,48,Masters,7,37,9,19,89,2.0,3,68,Rural,HR Executive,115219,0 +39195,Male,56,Masters,15,35,70,5,79,7.0,1,15,Urban,Manager,20966,0 +39196,Male,55,Bachelors,6,98,92,86,52,8.0,2,30,Urban,Software Engineer,95493,1 +39197,Male,39,Masters,5,82,0,42,39,7.0,3,17,Urban,Data Analyst,99880,0 +39198,Male,40,Diploma,13,32,42,65,80,5.0,0,77,Urban,HR Executive,43858,0 +39199,Male,52,Diploma,9,68,87,30,52,7.0,3,32,Semi-Urban,Data Analyst,97534,0 +39200,Other,31,Bachelors,12,31,0,49,6,5.0,2,93,Semi-Urban,ML Engineer,37392,0 +39201,Other,50,Bachelors,15,75,26,27,74,9.0,1,86,Urban,HR Executive,87722,0 +39202,Female,39,Diploma,3,5,52,91,47,3.0,3,40,Semi-Urban,Manager,76743,0 +39203,Male,53,Bachelors,6,5,19,71,78,9.0,4,40,Rural,Manager,51358,0 +39204,Male,33,Bachelors,6,9,5,22,64,1.0,6,83,Rural,Data Analyst,56299,0 +39205,Male,52,PhD,6,35,79,20,27,0.0,5,83,Semi-Urban,Software Engineer,139533,0 +39206,Male,37,Bachelors,12,62,20,19,11,5.0,0,25,Urban,HR Executive,41305,0 +39207,Male,23,Bachelors,14,71,72,99,22,0.0,2,42,Urban,Software Engineer,114717,1 +39208,Male,25,Bachelors,8,82,53,56,98,1.0,6,13,Urban,HR Executive,44694,0 +39209,Male,46,Masters,13,14,54,76,71,2.0,1,22,Rural,HR Executive,106374,0 +39210,Female,27,Bachelors,19,92,94,42,35,0.0,1,18,Urban,Manager,130863,1 +39211,Female,38,Bachelors,19,37,62,99,31,3.0,1,65,Urban,Software Engineer,147240,1 +39212,Male,59,Diploma,4,96,11,35,62,3.0,1,13,Semi-Urban,HR Executive,129471,0 +39213,Female,58,PhD,7,66,9,78,48,9.0,5,10,Rural,ML Engineer,118296,0 +39214,Male,33,Diploma,11,94,38,34,64,6.0,6,70,Urban,Manager,100938,1 +39215,Male,21,Masters,4,29,92,60,81,9.0,7,38,Urban,Software Engineer,100254,0 +39216,Male,55,Diploma,15,82,40,20,85,3.0,2,84,Rural,Manager,111187,0 +39217,Female,43,High School,9,6,41,96,8,1.0,6,73,Urban,HR Executive,108179,0 +39218,Male,40,Bachelors,7,16,40,67,77,9.0,0,15,Urban,ML Engineer,43059,0 +39219,Male,58,Bachelors,18,83,90,77,53,6.0,0,79,Urban,HR Executive,139668,1 +39220,Male,49,High School,1,93,20,39,82,1.0,2,17,Urban,Software Engineer,32560,0 +39221,Male,57,Masters,15,15,23,68,36,6.0,1,41,Rural,Manager,70701,0 +39222,Male,26,Masters,18,58,16,87,17,7.0,0,71,Urban,Data Analyst,61178,0 +39223,Female,33,Bachelors,13,2,86,76,22,4.0,1,67,Rural,Data Analyst,42224,0 +39224,Male,43,Bachelors,2,50,44,4,96,6.0,4,56,Semi-Urban,HR Executive,106065,0 +39225,Female,24,High School,4,97,38,47,35,4.0,1,66,Urban,HR Executive,27724,1 +39226,Male,56,Bachelors,13,47,47,16,8,4.0,3,52,Urban,Data Analyst,89416,0 +39227,Male,35,Bachelors,4,11,3,73,93,7.0,1,46,Rural,Software Engineer,58548,0 +39228,Female,31,Diploma,18,43,36,7,15,2.0,3,19,Urban,Software Engineer,119939,0 +39229,Male,42,Masters,6,35,80,65,56,2.0,1,87,Urban,HR Executive,107440,1 +39230,Male,50,Diploma,2,7,24,50,14,6.0,7,42,Urban,Software Engineer,44236,0 +39231,Male,38,Diploma,14,76,54,59,10,6.0,4,38,Semi-Urban,Software Engineer,30883,0 +39232,Female,30,High School,11,31,82,47,78,0.0,0,14,Semi-Urban,Manager,95925,0 +39233,Female,25,Diploma,13,48,24,18,1,1.0,4,56,Urban,ML Engineer,23850,0 +39234,Male,51,Masters,15,28,94,34,12,0.0,7,36,Urban,ML Engineer,100952,0 +39235,Male,53,Masters,19,38,17,42,46,7.0,3,24,Semi-Urban,ML Engineer,134357,0 +39236,Female,38,Masters,7,2,93,2,19,7.0,5,7,Urban,Data Analyst,95297,0 +39237,Male,27,PhD,7,0,89,85,70,4.0,0,63,Urban,HR Executive,82544,1 +39238,Male,45,Bachelors,5,30,62,12,39,8.0,6,17,Semi-Urban,Manager,91659,0 +39239,Female,41,Bachelors,4,46,75,58,60,0.0,4,76,Semi-Urban,Software Engineer,102156,1 +39240,Female,54,Bachelors,4,85,59,22,20,0.0,0,49,Urban,HR Executive,62617,0 +39241,Male,43,Bachelors,17,14,0,44,93,7.0,2,58,Urban,Manager,35750,0 +39242,Female,36,High School,4,81,16,70,72,2.0,1,39,Urban,HR Executive,47169,0 +39243,Male,47,High School,13,86,27,9,84,9.0,1,16,Urban,Data Analyst,64953,0 +39244,Female,33,Bachelors,8,83,3,74,19,3.0,1,66,Urban,Software Engineer,93913,0 +39245,Male,33,Diploma,10,70,1,9,79,8.0,6,77,Urban,ML Engineer,112874,0 +39246,Male,45,Bachelors,9,51,77,15,35,6.0,5,81,Urban,Data Analyst,60032,0 +39247,Male,53,Bachelors,5,49,28,14,26,2.0,0,60,Semi-Urban,HR Executive,80631,0 +39248,Male,37,Bachelors,0,66,10,38,7,2.0,3,98,Urban,HR Executive,147832,0 +39249,Male,45,Bachelors,17,39,92,43,97,6.0,6,30,Urban,ML Engineer,114503,0 +39250,Female,38,Masters,2,7,10,76,6,6.0,5,83,Urban,HR Executive,134360,0 +39251,Male,38,Bachelors,3,88,70,0,20,4.0,7,17,Urban,Manager,27191,0 +39252,Female,36,Masters,8,73,12,17,39,8.0,3,32,Urban,Software Engineer,101317,0 +39253,Male,47,Bachelors,7,31,83,63,32,2.0,7,66,Urban,Software Engineer,103936,1 +39254,Female,30,High School,14,49,10,71,62,1.0,2,15,Urban,Data Analyst,64093,0 +39255,Male,44,Masters,7,1,73,20,99,7.0,1,59,Urban,Data Analyst,23449,0 +39256,Male,44,Bachelors,12,58,3,9,85,0.0,2,3,Urban,Data Analyst,90715,0 +39257,Male,21,Masters,5,32,69,97,22,8.0,0,1,Semi-Urban,Software Engineer,149849,0 +39258,Male,52,Bachelors,18,46,10,90,36,9.0,2,45,Rural,Manager,97918,0 +39259,Male,39,Bachelors,0,69,57,80,34,6.0,6,9,Rural,Software Engineer,65297,0 +39260,Male,29,Masters,0,63,92,4,33,4.0,5,74,Rural,ML Engineer,144638,0 +39261,Other,25,Masters,2,94,93,34,65,1.0,5,59,Urban,Data Analyst,29101,1 +39262,Female,42,Diploma,10,8,93,3,94,4.0,0,69,Urban,Data Analyst,88236,0 +39263,Female,44,Masters,17,68,11,67,36,2.0,2,9,Urban,ML Engineer,81164,0 +39264,Male,50,Bachelors,13,44,70,33,95,6.0,2,56,Urban,ML Engineer,146842,0 +39265,Female,32,Masters,1,76,6,66,46,7.0,3,24,Urban,Software Engineer,142594,0 +39266,Male,36,Diploma,8,90,89,8,11,0.0,0,0,Urban,Data Analyst,138329,0 +39267,Male,32,Masters,2,29,25,54,27,3.0,4,8,Urban,Manager,114581,0 +39268,Male,41,Bachelors,6,76,39,96,84,5.0,4,45,Urban,Software Engineer,122115,1 +39269,Male,31,Masters,4,30,24,24,86,1.0,3,12,Rural,Manager,135850,0 +39270,Male,41,Bachelors,19,74,27,9,83,7.0,1,22,Semi-Urban,Software Engineer,149601,0 +39271,Male,22,High School,1,96,92,22,17,3.0,6,10,Rural,Data Analyst,73464,0 +39272,Male,47,High School,1,70,72,47,64,7.0,5,85,Rural,Software Engineer,36342,1 +39273,Female,45,Diploma,10,18,38,73,30,1.0,1,42,Urban,ML Engineer,29862,0 +39274,Female,31,Diploma,18,15,99,92,74,1.0,5,87,Semi-Urban,HR Executive,93286,1 +39275,Male,37,Bachelors,3,24,9,1,39,6.0,5,33,Urban,Data Analyst,74734,0 +39276,Male,53,Bachelors,4,42,55,44,93,6.0,0,66,Semi-Urban,ML Engineer,22701,0 +39277,Female,55,Masters,14,80,67,13,27,3.0,4,95,Rural,Manager,42587,1 +39278,Male,40,Bachelors,13,52,73,57,15,8.0,2,31,Rural,ML Engineer,35710,0 +39279,Female,46,Bachelors,6,89,76,72,34,1.0,5,57,Urban,Manager,52984,1 +39280,Female,35,Diploma,14,56,27,81,34,2.0,2,2,Rural,Manager,56635,0 +39281,Male,39,High School,15,80,37,68,69,4.0,5,25,Rural,Software Engineer,129263,0 +39282,Male,21,Diploma,17,93,66,35,82,6.0,5,45,Rural,ML Engineer,51814,1 +39283,Other,45,Diploma,13,38,39,3,30,6.0,5,71,Urban,Manager,110879,0 +39284,Other,54,High School,5,82,15,21,89,6.0,0,8,Urban,Manager,120744,0 +39285,Male,52,High School,15,70,42,18,47,0.0,4,30,Urban,Data Analyst,77428,0 +39286,Male,33,Diploma,6,50,41,16,21,1.0,7,57,Rural,Software Engineer,30380,0 +39287,Female,39,Diploma,9,66,62,24,7,4.0,1,8,Semi-Urban,Manager,89552,0 +39288,Male,41,Masters,6,35,8,27,70,9.0,2,33,Semi-Urban,ML Engineer,70187,0 +39289,Female,38,Masters,2,8,33,58,58,7.0,2,90,Rural,HR Executive,78589,0 +39290,Female,28,Masters,7,93,57,70,25,1.0,5,31,Urban,ML Engineer,85465,1 +39291,Female,39,Masters,8,53,60,97,34,3.0,2,16,Rural,ML Engineer,80206,0 +39292,Male,41,Bachelors,16,83,40,27,52,3.0,5,89,Urban,Data Analyst,25427,1 +39293,Female,57,Bachelors,13,77,84,52,57,4.0,7,30,Urban,HR Executive,110613,1 +39294,Male,55,Bachelors,9,84,21,83,44,1.0,4,84,Urban,Manager,47045,1 +39295,Male,41,Diploma,9,8,37,41,21,6.0,2,38,Semi-Urban,HR Executive,101547,0 +39296,Male,23,Diploma,4,69,72,27,89,4.0,4,12,Urban,ML Engineer,136193,0 +39297,Male,50,Masters,8,19,39,84,52,8.0,1,76,Rural,Manager,24475,0 +39298,Female,51,Bachelors,18,72,32,40,78,6.0,6,1,Urban,Software Engineer,134616,0 +39299,Female,23,Masters,11,22,31,38,2,6.0,6,96,Semi-Urban,Software Engineer,32573,0 +39300,Male,50,Diploma,14,71,98,98,98,5.0,7,68,Semi-Urban,ML Engineer,126466,1 +39301,Male,24,Bachelors,2,68,31,79,43,3.0,3,19,Semi-Urban,Data Analyst,134635,0 +39302,Male,50,Diploma,16,39,23,15,33,6.0,1,85,Urban,Software Engineer,82494,0 +39303,Male,47,High School,7,56,66,75,41,5.0,0,71,Semi-Urban,Software Engineer,70060,1 +39304,Female,25,Masters,0,84,58,86,77,2.0,4,23,Urban,Data Analyst,68474,1 +39305,Male,49,Masters,5,97,6,76,70,6.0,2,5,Urban,ML Engineer,66963,0 +39306,Female,51,Masters,9,84,11,6,44,8.0,0,90,Urban,Data Analyst,40016,0 +39307,Female,29,Bachelors,8,49,18,19,34,3.0,7,5,Urban,HR Executive,123081,0 +39308,Male,44,Bachelors,1,38,67,75,82,8.0,4,48,Semi-Urban,ML Engineer,75686,0 +39309,Male,32,Diploma,5,88,89,20,89,7.0,2,35,Rural,Software Engineer,68619,0 +39310,Male,38,High School,12,87,67,48,62,2.0,2,60,Semi-Urban,Manager,114336,1 +39311,Male,22,Bachelors,13,41,97,44,29,9.0,7,49,Urban,HR Executive,67416,0 +39312,Male,29,Bachelors,1,19,30,91,0,9.0,6,65,Semi-Urban,HR Executive,76781,0 +39313,Male,44,Bachelors,6,34,30,12,18,6.0,7,52,Urban,Manager,85401,0 +39314,Other,26,Masters,13,46,6,35,37,0.0,6,14,Urban,HR Executive,21571,0 +39315,Male,25,Bachelors,16,72,91,26,52,7.0,3,37,Urban,Data Analyst,101535,0 +39316,Female,53,Bachelors,1,15,14,33,23,5.0,7,66,Urban,ML Engineer,85797,0 +39317,Male,44,Masters,4,21,64,93,32,1.0,5,10,Urban,Software Engineer,106401,0 +39318,Male,27,Bachelors,9,9,50,54,94,3.0,7,69,Urban,HR Executive,63896,0 +39319,Male,21,Diploma,12,65,48,34,31,9.0,7,56,Urban,Software Engineer,46094,0 +39320,Male,28,Masters,5,83,89,74,50,8.0,3,67,Urban,Software Engineer,133829,1 +39321,Male,53,Diploma,14,63,45,2,63,8.0,5,45,Rural,ML Engineer,37104,0 +39322,Female,55,Bachelors,5,99,16,62,71,3.0,1,46,Urban,ML Engineer,118030,0 +39323,Male,44,Masters,10,27,37,43,20,7.0,0,38,Urban,Software Engineer,63923,0 +39324,Female,23,High School,10,95,62,47,83,5.0,5,97,Semi-Urban,Software Engineer,63111,1 +39325,Female,24,PhD,16,13,33,1,49,3.0,6,29,Semi-Urban,Data Analyst,26061,0 +39326,Female,48,Bachelors,8,12,0,71,71,7.0,1,97,Urban,Data Analyst,130937,0 +39327,Female,28,High School,7,41,14,73,18,9.0,5,89,Rural,Manager,43227,0 +39328,Male,44,PhD,4,3,23,30,46,4.0,7,24,Urban,ML Engineer,44049,0 +39329,Other,30,Bachelors,9,92,17,39,84,4.0,1,69,Semi-Urban,Software Engineer,90177,0 +39330,Female,42,Bachelors,11,57,61,98,43,9.0,7,3,Urban,HR Executive,60568,0 +39331,Female,27,High School,12,59,47,76,74,2.0,3,65,Urban,HR Executive,84284,1 +39332,Male,45,Diploma,8,20,99,91,32,1.0,4,27,Urban,Software Engineer,88273,1 +39333,Male,48,PhD,7,16,38,10,82,4.0,3,94,Urban,ML Engineer,46694,0 +39334,Female,49,Bachelors,1,84,70,99,45,0.0,7,63,Urban,Software Engineer,46996,1 +39335,Female,27,Bachelors,3,35,74,12,31,2.0,6,94,Semi-Urban,HR Executive,65279,0 +39336,Female,32,Bachelors,7,91,80,88,46,5.0,2,86,Rural,Data Analyst,140671,1 +39337,Female,58,Bachelors,17,58,76,65,86,6.0,5,47,Urban,Software Engineer,147973,1 +39338,Male,40,Diploma,16,58,98,43,7,6.0,6,28,Urban,Software Engineer,89906,0 +39339,Male,53,Diploma,12,65,12,61,70,7.0,5,0,Rural,HR Executive,33888,0 +39340,Female,58,Bachelors,19,83,95,46,87,4.0,4,80,Urban,Software Engineer,147216,1 +39341,Male,58,High School,0,34,66,30,42,1.0,6,11,Urban,Manager,118769,0 +39342,Female,24,Bachelors,14,74,85,88,93,5.0,2,44,Rural,HR Executive,76817,1 +39343,Female,40,Bachelors,0,3,50,18,79,8.0,0,69,Urban,ML Engineer,109156,0 +39344,Male,55,Masters,18,82,14,23,53,8.0,3,54,Urban,ML Engineer,99819,0 +39345,Male,22,Bachelors,6,32,32,84,71,3.0,2,44,Rural,HR Executive,93673,0 +39346,Female,58,High School,13,74,21,52,95,8.0,3,57,Rural,HR Executive,122639,0 +39347,Male,39,Diploma,11,44,72,46,45,7.0,7,68,Rural,Manager,87546,0 +39348,Male,36,Bachelors,2,40,36,22,83,6.0,3,77,Rural,HR Executive,96548,0 +39349,Female,36,PhD,2,17,2,61,94,2.0,1,61,Urban,HR Executive,88591,0 +39350,Female,22,Masters,6,46,55,94,18,2.0,3,26,Semi-Urban,Manager,146850,0 +39351,Female,41,Diploma,5,93,32,0,52,4.0,4,56,Urban,Manager,149482,0 +39352,Male,37,High School,11,63,36,83,97,7.0,5,62,Urban,ML Engineer,73299,1 +39353,Male,41,High School,8,86,67,19,28,8.0,6,64,Urban,ML Engineer,109144,1 +39354,Female,52,Diploma,14,49,76,6,17,1.0,5,41,Urban,ML Engineer,79718,0 +39355,Male,28,Bachelors,15,83,13,59,47,2.0,1,80,Urban,Software Engineer,24258,1 +39356,Male,32,Bachelors,10,45,44,84,58,7.0,7,15,Urban,Software Engineer,110092,0 +39357,Male,43,High School,19,19,52,27,46,5.0,1,82,Rural,ML Engineer,81336,0 +39358,Male,36,Diploma,6,43,56,69,78,3.0,5,29,Urban,Data Analyst,80730,0 +39359,Male,47,Diploma,3,32,75,56,71,7.0,2,26,Urban,Manager,127851,0 +39360,Male,27,Bachelors,14,55,99,56,69,1.0,0,46,Semi-Urban,Software Engineer,22486,1 +39361,Male,35,Diploma,10,25,69,19,62,8.0,6,47,Semi-Urban,Data Analyst,103086,0 +39362,Other,28,PhD,10,36,47,56,83,6.0,4,19,Urban,HR Executive,83574,0 +39363,Male,43,Bachelors,19,82,85,89,32,4.0,1,50,Semi-Urban,HR Executive,126005,1 +39364,Male,53,Bachelors,12,63,46,99,75,5.0,0,40,Urban,HR Executive,69008,1 +39365,Male,50,Bachelors,12,62,51,19,75,9.0,1,5,Urban,Manager,76463,0 +39366,Male,43,Diploma,5,48,48,92,30,1.0,5,55,Rural,Manager,72386,1 +39367,Female,44,High School,19,10,54,13,27,3.0,7,43,Semi-Urban,Manager,109054,0 +39368,Female,23,Bachelors,3,30,80,5,38,4.0,1,17,Semi-Urban,ML Engineer,139853,0 +39369,Female,34,High School,10,71,15,40,99,7.0,3,95,Semi-Urban,HR Executive,112132,0 +39370,Female,22,High School,3,66,23,26,23,6.0,7,49,Urban,Manager,122558,0 +39371,Female,26,Bachelors,7,40,42,53,90,6.0,2,12,Urban,HR Executive,112615,0 +39372,Male,52,Masters,2,76,15,19,20,6.0,3,37,Semi-Urban,Manager,75632,0 +39373,Male,39,Bachelors,7,50,35,4,27,3.0,0,34,Urban,ML Engineer,40185,0 +39374,Male,30,Masters,6,13,42,90,3,2.0,2,56,Urban,Software Engineer,115292,0 +39375,Male,54,Diploma,10,73,63,1,29,4.0,2,45,Urban,Manager,61210,0 +39376,Female,46,High School,5,28,4,15,13,0.0,1,48,Urban,ML Engineer,111157,0 +39377,Male,45,Diploma,0,96,95,99,26,6.0,7,79,Urban,Data Analyst,146229,1 +39378,Female,24,Masters,13,17,1,88,70,5.0,3,26,Urban,ML Engineer,144603,0 +39379,Male,39,High School,1,39,39,53,49,9.0,4,50,Urban,Software Engineer,124227,0 +39380,Male,22,PhD,15,7,15,31,25,1.0,0,0,Urban,Data Analyst,95395,0 +39381,Male,50,Bachelors,8,72,22,87,90,3.0,3,66,Urban,Manager,20033,1 +39382,Female,36,Bachelors,12,83,22,66,92,7.0,7,25,Urban,Data Analyst,105752,0 +39383,Female,59,Bachelors,5,37,99,40,79,1.0,0,64,Rural,HR Executive,100093,0 +39384,Other,29,Masters,8,98,28,34,95,4.0,0,49,Semi-Urban,Data Analyst,112030,0 +39385,Female,35,Bachelors,7,7,89,2,96,0.0,4,43,Urban,Manager,126786,0 +39386,Male,34,Bachelors,12,90,93,77,13,9.0,7,36,Rural,Manager,61042,1 +39387,Male,59,High School,13,65,71,41,48,5.0,2,60,Semi-Urban,Manager,75374,1 +39388,Female,52,Bachelors,11,99,67,93,77,5.0,3,17,Semi-Urban,Software Engineer,106104,1 +39389,Female,44,Bachelors,5,12,36,67,57,8.0,2,94,Urban,HR Executive,80168,0 +39390,Male,29,Bachelors,19,53,66,94,58,4.0,2,8,Urban,Manager,61017,0 +39391,Male,44,Masters,8,65,58,14,75,4.0,4,55,Rural,HR Executive,78742,0 +39392,Male,49,Bachelors,3,54,34,87,80,4.0,1,2,Urban,ML Engineer,47662,0 +39393,Male,55,Masters,9,60,74,38,76,0.0,7,81,Urban,ML Engineer,20530,1 +39394,Female,47,Bachelors,7,77,68,63,88,3.0,6,54,Urban,HR Executive,146992,1 +39395,Female,55,Bachelors,7,53,49,39,11,9.0,1,11,Urban,Data Analyst,126531,0 +39396,Male,23,Diploma,17,38,25,84,8,9.0,6,65,Urban,ML Engineer,136787,0 +39397,Male,36,Diploma,19,99,12,67,47,4.0,2,74,Rural,Data Analyst,143027,1 +39398,Female,23,PhD,6,44,50,37,74,5.0,1,25,Urban,HR Executive,85955,0 +39399,Female,47,Masters,0,35,39,62,59,9.0,3,27,Rural,ML Engineer,67013,0 +39400,Male,36,Diploma,9,25,80,58,52,6.0,7,56,Rural,ML Engineer,49193,0 +39401,Female,28,Bachelors,12,57,21,68,66,1.0,6,64,Semi-Urban,Data Analyst,104767,0 +39402,Female,24,Masters,4,16,73,91,3,7.0,3,91,Urban,Software Engineer,53070,1 +39403,Male,32,Masters,7,39,66,69,50,4.0,5,56,Rural,ML Engineer,131928,0 +39404,Female,57,Bachelors,19,48,56,92,89,7.0,6,0,Rural,ML Engineer,71643,0 +39405,Male,38,Masters,19,64,62,85,35,9.0,5,94,Rural,Manager,138756,1 +39406,Male,41,Bachelors,11,24,63,42,63,5.0,6,66,Rural,ML Engineer,148917,0 +39407,Male,26,Bachelors,17,90,33,17,13,2.0,6,29,Semi-Urban,ML Engineer,98110,0 +39408,Male,27,Bachelors,8,8,87,27,91,8.0,3,58,Urban,Data Analyst,95326,0 +39409,Male,33,Masters,7,53,2,72,79,4.0,4,4,Urban,Data Analyst,100175,0 +39410,Female,53,Bachelors,6,57,57,10,82,6.0,2,54,Rural,Software Engineer,54726,0 +39411,Male,29,Masters,2,82,4,90,4,4.0,0,70,Urban,HR Executive,51502,1 +39412,Female,54,Bachelors,18,23,80,70,50,5.0,2,9,Semi-Urban,Software Engineer,112295,0 +39413,Female,33,Masters,11,74,6,59,29,7.0,4,3,Semi-Urban,Data Analyst,81215,0 +39414,Male,43,PhD,19,43,51,7,48,3.0,0,8,Rural,Software Engineer,56303,0 +39415,Male,32,Masters,8,98,38,51,68,5.0,5,13,Semi-Urban,ML Engineer,29393,0 +39416,Male,56,Bachelors,15,41,73,33,81,1.0,6,84,Urban,Data Analyst,70926,0 +39417,Male,40,Masters,15,47,45,24,44,7.0,7,69,Rural,Software Engineer,22342,0 +39418,Male,21,Bachelors,16,60,44,20,39,4.0,1,23,Urban,Data Analyst,40643,0 +39419,Male,38,Masters,3,67,89,13,30,8.0,5,44,Urban,ML Engineer,90887,0 +39420,Male,38,Diploma,6,94,19,76,85,1.0,5,15,Semi-Urban,HR Executive,25196,0 +39421,Male,23,PhD,17,99,2,13,74,6.0,6,41,Semi-Urban,HR Executive,72372,0 +39422,Male,55,Bachelors,15,96,84,8,39,7.0,1,7,Semi-Urban,Data Analyst,100378,0 +39423,Female,46,Masters,16,22,35,87,23,5.0,6,21,Urban,Data Analyst,133130,0 +39424,Male,56,Diploma,17,86,73,79,35,0.0,4,25,Semi-Urban,HR Executive,133764,1 +39425,Male,49,High School,14,71,10,36,33,6.0,3,95,Urban,Data Analyst,31078,0 +39426,Male,55,Bachelors,9,35,90,90,68,3.0,6,26,Rural,HR Executive,113007,1 +39427,Male,30,High School,11,91,2,88,73,9.0,1,20,Urban,Data Analyst,88857,0 +39428,Female,50,Bachelors,16,23,17,43,19,8.0,6,36,Urban,ML Engineer,33806,0 +39429,Male,27,Diploma,6,83,14,85,9,8.0,5,43,Semi-Urban,Software Engineer,69807,0 +39430,Male,34,Masters,3,9,88,75,36,5.0,3,22,Urban,HR Executive,26008,0 +39431,Male,49,Bachelors,10,9,0,14,31,1.0,3,70,Urban,ML Engineer,103094,0 +39432,Male,53,Diploma,6,99,20,57,54,0.0,1,54,Rural,Manager,106880,0 +39433,Male,48,Bachelors,2,70,31,4,0,9.0,0,92,Urban,Data Analyst,23238,0 +39434,Male,34,Bachelors,1,47,65,47,91,6.0,0,9,Semi-Urban,HR Executive,22887,0 +39435,Male,48,Diploma,0,48,82,90,53,0.0,5,42,Rural,Manager,139893,1 +39436,Male,44,Diploma,6,6,48,66,97,1.0,5,79,Rural,ML Engineer,129758,0 +39437,Other,34,Diploma,5,3,70,88,23,0.0,7,88,Urban,ML Engineer,135311,1 +39438,Male,53,Bachelors,3,67,52,83,10,6.0,6,53,Urban,ML Engineer,102837,1 +39439,Male,58,Masters,2,53,62,7,48,3.0,1,36,Urban,Manager,101010,0 +39440,Female,24,Bachelors,15,43,79,29,82,4.0,3,57,Semi-Urban,Data Analyst,21542,0 +39441,Female,25,Bachelors,10,79,59,2,72,4.0,0,84,Urban,Data Analyst,128818,0 +39442,Female,26,Bachelors,15,42,69,0,20,5.0,1,93,Urban,Software Engineer,66427,0 +39443,Female,34,High School,17,52,88,92,39,4.0,6,72,Rural,Manager,111991,1 +39444,Male,57,Diploma,4,39,32,21,68,0.0,3,69,Semi-Urban,HR Executive,111432,0 +39445,Male,53,Bachelors,11,58,50,22,75,6.0,6,7,Urban,ML Engineer,112103,0 +39446,Female,34,Diploma,5,54,53,65,41,9.0,0,27,Semi-Urban,Manager,42294,0 +39447,Female,58,Masters,11,38,79,9,31,8.0,0,28,Rural,Software Engineer,98583,0 +39448,Male,28,Bachelors,9,74,26,8,76,6.0,0,31,Semi-Urban,Data Analyst,85158,0 +39449,Male,21,Diploma,4,81,5,78,42,4.0,1,66,Urban,HR Executive,114593,0 +39450,Female,42,High School,13,50,14,96,47,5.0,5,13,Urban,ML Engineer,120029,0 +39451,Male,50,Masters,3,46,61,32,52,6.0,1,99,Urban,Software Engineer,84141,1 +39452,Female,42,Diploma,4,62,62,55,83,4.0,3,3,Urban,HR Executive,76823,0 +39453,Male,48,Masters,3,54,98,71,44,6.0,0,41,Semi-Urban,Data Analyst,62465,1 +39454,Female,26,Diploma,5,98,39,42,75,8.0,7,84,Urban,ML Engineer,114301,1 +39455,Male,52,Bachelors,13,19,46,16,26,2.0,0,87,Semi-Urban,Manager,28484,0 +39456,Male,45,High School,17,6,93,58,37,0.0,4,1,Urban,Data Analyst,74571,0 +39457,Male,33,Masters,8,24,19,37,47,6.0,6,66,Urban,Data Analyst,82582,0 +39458,Male,30,Diploma,8,35,89,49,20,1.0,0,50,Urban,ML Engineer,55480,0 +39459,Male,37,Diploma,0,12,71,46,27,1.0,5,1,Rural,Data Analyst,123698,0 +39460,Female,34,PhD,19,32,8,13,93,7.0,0,32,Semi-Urban,ML Engineer,55401,0 +39461,Male,36,High School,8,52,62,39,36,4.0,3,48,Urban,Manager,29310,0 +39462,Male,48,Bachelors,7,87,29,59,22,0.0,0,20,Urban,HR Executive,64589,0 +39463,Male,33,Bachelors,18,75,31,67,78,9.0,7,86,Urban,HR Executive,42407,1 +39464,Female,47,Bachelors,10,26,54,19,18,9.0,2,99,Urban,Data Analyst,144119,0 +39465,Male,37,Masters,0,52,92,91,45,3.0,2,29,Urban,ML Engineer,27704,1 +39466,Other,30,Bachelors,1,40,20,27,65,5.0,2,94,Semi-Urban,Manager,97461,0 +39467,Female,55,Diploma,15,46,68,98,0,4.0,2,28,Semi-Urban,ML Engineer,46249,0 +39468,Female,58,Bachelors,4,44,93,14,53,7.0,5,14,Semi-Urban,Manager,82033,0 +39469,Male,30,Diploma,1,0,81,15,45,7.0,7,41,Urban,ML Engineer,120517,0 +39470,Female,53,Bachelors,9,13,62,42,57,4.0,1,2,Urban,Software Engineer,30060,0 +39471,Male,57,Masters,9,67,63,99,72,1.0,3,93,Urban,Software Engineer,62869,1 +39472,Male,46,PhD,9,88,3,9,11,9.0,4,43,Semi-Urban,Manager,86365,0 +39473,Male,46,Diploma,5,15,48,75,34,9.0,4,47,Rural,Manager,24649,0 +39474,Male,52,Masters,16,36,3,79,36,8.0,5,66,Urban,ML Engineer,104823,0 +39475,Male,42,Diploma,9,23,50,37,13,0.0,6,10,Rural,Software Engineer,139869,0 +39476,Male,50,Bachelors,8,77,78,72,93,5.0,2,15,Urban,Software Engineer,81848,1 +39477,Male,26,Bachelors,17,16,63,5,90,6.0,5,55,Semi-Urban,HR Executive,72740,0 +39478,Male,44,Masters,14,82,52,40,86,3.0,0,51,Urban,Data Analyst,145381,0 +39479,Female,35,Masters,7,70,71,57,17,0.0,3,37,Semi-Urban,Manager,121043,0 +39480,Other,58,Bachelors,7,79,55,72,61,7.0,6,50,Semi-Urban,ML Engineer,115994,1 +39481,Female,31,Bachelors,12,70,60,73,56,2.0,1,50,Urban,Software Engineer,41302,1 +39482,Male,53,Masters,1,52,70,47,86,7.0,2,1,Rural,Data Analyst,27317,0 +39483,Male,47,Diploma,0,85,60,58,44,2.0,5,55,Urban,Software Engineer,34216,1 +39484,Male,28,Masters,18,91,50,14,93,4.0,2,80,Urban,Manager,50132,1 +39485,Male,58,Diploma,5,48,28,69,40,8.0,6,80,Semi-Urban,Software Engineer,86082,0 +39486,Other,28,Masters,16,66,80,18,3,0.0,7,31,Urban,ML Engineer,129368,0 +39487,Male,31,Bachelors,13,41,64,6,27,2.0,7,87,Urban,Software Engineer,72183,0 +39488,Female,39,Bachelors,18,4,71,4,37,3.0,0,18,Urban,Software Engineer,21756,0 +39489,Female,53,Diploma,15,50,97,69,43,6.0,0,6,Urban,HR Executive,97089,0 +39490,Female,35,Bachelors,19,86,93,8,63,0.0,1,81,Urban,HR Executive,115742,1 +39491,Female,27,Bachelors,12,31,52,59,60,6.0,2,15,Semi-Urban,Software Engineer,51196,0 +39492,Male,29,High School,15,18,91,74,26,5.0,7,74,Semi-Urban,Data Analyst,87897,1 +39493,Male,30,Diploma,12,22,21,10,14,0.0,7,79,Semi-Urban,ML Engineer,80648,0 +39494,Female,32,Diploma,4,13,27,28,69,4.0,5,11,Urban,Software Engineer,28872,0 +39495,Male,34,Bachelors,3,8,34,98,22,1.0,7,62,Urban,ML Engineer,40457,0 +39496,Male,23,Diploma,1,39,3,51,21,8.0,3,94,Rural,Manager,96659,0 +39497,Male,43,Diploma,17,30,40,55,27,9.0,3,22,Semi-Urban,Manager,60514,0 +39498,Female,48,Diploma,12,79,85,17,15,6.0,7,76,Urban,ML Engineer,100838,1 +39499,Male,57,High School,11,30,21,49,14,8.0,7,54,Semi-Urban,Manager,30575,0 +39500,Female,28,High School,11,22,57,77,78,7.0,5,55,Rural,Manager,55934,0 +39501,Male,53,Bachelors,2,75,20,82,25,1.0,2,76,Urban,Data Analyst,27920,1 +39502,Female,32,Masters,17,75,79,78,73,6.0,2,39,Urban,HR Executive,97661,1 +39503,Female,41,Bachelors,1,76,45,9,73,5.0,6,97,Semi-Urban,Manager,88220,0 +39504,Male,42,Bachelors,15,44,91,69,54,0.0,7,14,Urban,Data Analyst,71860,0 +39505,Male,39,PhD,10,71,28,89,9,3.0,0,3,Urban,Data Analyst,132794,0 +39506,Female,57,Bachelors,12,22,41,98,75,9.0,0,66,Semi-Urban,Data Analyst,69965,0 +39507,Female,46,High School,9,96,70,78,29,4.0,7,68,Urban,Software Engineer,28244,1 +39508,Female,23,Bachelors,3,88,0,51,6,9.0,4,81,Rural,Data Analyst,134504,0 +39509,Male,46,Diploma,2,36,7,22,90,9.0,3,93,Semi-Urban,Manager,40750,0 +39510,Male,43,PhD,12,3,27,61,7,5.0,3,57,Semi-Urban,Data Analyst,82838,0 +39511,Male,53,High School,14,16,36,4,13,4.0,6,79,Urban,Manager,116870,0 +39512,Male,32,High School,5,69,82,58,86,1.0,2,38,Urban,Software Engineer,64405,1 +39513,Female,37,Bachelors,6,85,44,77,80,4.0,3,30,Urban,Manager,37870,0 +39514,Male,43,Masters,2,81,0,64,55,5.0,0,76,Urban,Software Engineer,48976,0 +39515,Female,26,Bachelors,15,50,78,77,79,2.0,2,33,Urban,Manager,24728,0 +39516,Male,24,Masters,11,99,54,1,96,4.0,5,69,Rural,ML Engineer,48394,0 +39517,Male,52,Diploma,5,6,18,38,29,2.0,6,33,Semi-Urban,Data Analyst,26727,0 +39518,Female,33,Bachelors,0,48,13,61,37,0.0,1,18,Semi-Urban,HR Executive,45192,0 +39519,Female,48,Diploma,2,54,84,41,30,3.0,5,39,Urban,HR Executive,85686,0 +39520,Female,59,Diploma,3,65,17,71,28,6.0,4,48,Rural,ML Engineer,125333,0 +39521,Female,56,High School,17,9,26,73,77,5.0,3,40,Urban,Manager,136509,0 +39522,Female,41,Bachelors,15,5,14,18,58,5.0,1,1,Urban,Software Engineer,58825,0 +39523,Female,31,High School,18,92,65,39,13,5.0,6,8,Urban,Data Analyst,80109,0 +39524,Female,21,High School,5,35,61,60,98,7.0,7,20,Urban,Data Analyst,26643,0 +39525,Other,52,Masters,17,1,3,27,86,8.0,6,55,Urban,Software Engineer,60317,0 +39526,Male,56,Bachelors,6,88,42,72,70,6.0,0,87,Semi-Urban,HR Executive,64615,1 +39527,Female,33,High School,17,25,4,50,67,4.0,1,96,Urban,Data Analyst,91933,0 +39528,Male,53,Bachelors,4,55,76,15,40,8.0,7,66,Rural,HR Executive,48683,0 +39529,Male,55,PhD,2,81,98,81,73,8.0,6,43,Semi-Urban,Software Engineer,116064,1 +39530,Male,25,Masters,11,46,45,52,29,4.0,7,36,Semi-Urban,HR Executive,29398,0 +39531,Female,37,Bachelors,2,2,36,68,52,7.0,1,66,Rural,Manager,67923,0 +39532,Male,42,Bachelors,19,74,91,95,74,4.0,0,40,Semi-Urban,Data Analyst,103345,1 +39533,Other,34,Masters,9,6,69,17,32,1.0,6,37,Semi-Urban,ML Engineer,129084,0 +39534,Male,30,Bachelors,18,23,34,76,39,2.0,2,33,Semi-Urban,Data Analyst,142593,0 +39535,Male,55,PhD,13,5,31,48,50,7.0,2,51,Semi-Urban,ML Engineer,66755,0 +39536,Male,56,Bachelors,0,68,18,97,71,1.0,0,77,Semi-Urban,Data Analyst,29353,1 +39537,Male,43,Bachelors,15,8,35,66,66,5.0,4,40,Semi-Urban,HR Executive,147280,0 +39538,Female,39,Masters,14,78,82,75,73,7.0,4,27,Rural,Data Analyst,22842,1 +39539,Female,56,Diploma,19,44,29,79,56,7.0,3,17,Urban,HR Executive,56911,0 +39540,Male,47,Diploma,3,70,74,49,17,2.0,4,9,Semi-Urban,Manager,81895,0 +39541,Male,23,High School,9,78,82,54,42,6.0,6,73,Urban,ML Engineer,102537,1 +39542,Male,25,Bachelors,14,83,25,67,45,1.0,4,31,Urban,Data Analyst,23541,0 +39543,Female,45,Masters,1,67,52,66,56,4.0,3,93,Urban,Data Analyst,65707,1 +39544,Male,25,PhD,13,92,39,36,59,3.0,4,65,Urban,ML Engineer,43421,0 +39545,Male,26,Masters,9,20,63,33,83,0.0,2,1,Urban,Data Analyst,147232,0 +39546,Male,21,High School,15,0,46,92,85,6.0,3,55,Urban,Data Analyst,124864,0 +39547,Female,51,Bachelors,16,31,84,62,33,0.0,1,38,Semi-Urban,HR Executive,54741,0 +39548,Male,56,Masters,3,59,23,53,18,5.0,3,96,Urban,Software Engineer,135715,0 +39549,Male,52,High School,2,67,36,75,50,5.0,1,36,Rural,HR Executive,93370,0 +39550,Female,27,Diploma,14,67,90,19,42,8.0,7,69,Urban,Software Engineer,70612,1 +39551,Other,52,Masters,9,44,32,48,43,8.0,4,55,Urban,ML Engineer,135674,0 +39552,Female,25,Bachelors,10,77,1,63,49,9.0,7,41,Rural,HR Executive,62590,0 +39553,Male,28,Bachelors,4,9,97,9,66,6.0,6,40,Semi-Urban,Software Engineer,128112,0 +39554,Male,34,PhD,13,45,20,25,52,8.0,1,15,Semi-Urban,ML Engineer,24726,0 +39555,Other,30,Diploma,8,2,31,7,89,5.0,6,31,Semi-Urban,Data Analyst,37686,0 +39556,Male,48,Bachelors,5,29,22,25,18,7.0,0,93,Rural,Manager,36637,0 +39557,Male,48,Diploma,9,51,88,90,19,2.0,0,97,Urban,HR Executive,72081,1 +39558,Male,45,Diploma,16,2,53,85,1,7.0,7,40,Urban,ML Engineer,144793,0 +39559,Other,54,PhD,2,77,10,29,80,5.0,0,60,Semi-Urban,HR Executive,101888,0 +39560,Female,26,Diploma,14,44,79,7,79,5.0,4,44,Rural,HR Executive,28974,0 +39561,Female,44,High School,1,23,58,77,68,9.0,7,65,Rural,Manager,71463,0 +39562,Male,54,Masters,9,58,45,57,79,0.0,4,61,Semi-Urban,HR Executive,76541,0 +39563,Male,33,Diploma,1,90,99,7,41,7.0,5,38,Urban,Manager,122529,0 +39564,Male,21,High School,11,30,98,71,69,3.0,6,51,Semi-Urban,ML Engineer,105475,1 +39565,Male,39,High School,10,20,4,7,6,2.0,7,6,Rural,Data Analyst,144241,0 +39566,Female,41,Diploma,7,54,6,80,25,8.0,6,14,Semi-Urban,HR Executive,61087,0 +39567,Male,29,Diploma,7,79,92,6,16,6.0,3,65,Urban,Data Analyst,125684,1 +39568,Male,56,Masters,7,35,79,51,94,6.0,4,27,Semi-Urban,Manager,49338,0 +39569,Female,29,Bachelors,1,56,35,45,49,1.0,4,15,Urban,Software Engineer,64368,0 +39570,Male,24,High School,8,25,39,66,42,3.0,5,33,Urban,Software Engineer,70791,0 +39571,Female,54,Masters,4,83,76,67,55,5.0,1,82,Urban,ML Engineer,104718,1 +39572,Female,21,Bachelors,18,48,69,74,70,9.0,3,52,Urban,HR Executive,130136,1 +39573,Female,56,Masters,4,67,45,73,48,3.0,2,67,Semi-Urban,Data Analyst,96530,1 +39574,Female,26,Masters,15,63,97,78,71,2.0,6,60,Urban,ML Engineer,130462,1 +39575,Female,24,Bachelors,19,72,31,39,24,8.0,6,70,Rural,Software Engineer,29988,0 +39576,Male,33,Bachelors,9,28,87,51,46,1.0,5,22,Rural,Software Engineer,86203,0 +39577,Male,21,Masters,8,66,26,50,32,6.0,2,55,Urban,Manager,83385,0 +39578,Female,44,Diploma,6,49,78,64,23,0.0,1,59,Urban,Manager,105401,1 +39579,Male,47,Bachelors,18,52,79,31,24,3.0,6,92,Urban,ML Engineer,36099,1 +39580,Female,30,Bachelors,4,44,18,32,91,6.0,3,52,Urban,Data Analyst,31356,0 +39581,Male,26,Bachelors,11,92,27,68,86,8.0,1,61,Urban,Data Analyst,66663,1 +39582,Male,33,Bachelors,8,34,9,3,78,4.0,4,85,Rural,HR Executive,21246,0 +39583,Male,36,PhD,9,64,74,26,21,7.0,6,96,Semi-Urban,HR Executive,94482,1 +39584,Male,25,Diploma,5,44,46,23,64,4.0,2,35,Semi-Urban,Data Analyst,137731,0 +39585,Other,49,Bachelors,16,28,82,48,73,3.0,0,2,Rural,Software Engineer,67818,0 +39586,Female,56,Masters,8,0,21,34,77,5.0,2,37,Urban,Manager,21063,0 +39587,Male,46,High School,17,60,5,8,31,1.0,2,58,Semi-Urban,Data Analyst,127922,0 +39588,Female,46,Masters,10,11,96,19,26,5.0,4,22,Urban,Software Engineer,31329,0 +39589,Male,27,High School,5,1,50,23,55,4.0,1,35,Rural,Data Analyst,67068,0 +39590,Female,22,Bachelors,18,40,83,56,19,9.0,4,28,Urban,HR Executive,56740,0 +39591,Female,29,Masters,1,85,67,6,68,5.0,3,96,Urban,Manager,65394,1 +39592,Male,29,Bachelors,2,96,12,16,87,2.0,3,16,Urban,HR Executive,59429,0 +39593,Male,58,High School,12,99,50,83,78,5.0,3,37,Urban,Data Analyst,137275,1 +39594,Female,22,Diploma,12,48,46,9,80,2.0,1,56,Semi-Urban,Manager,65964,0 +39595,Other,33,High School,8,27,38,79,64,7.0,0,32,Urban,ML Engineer,55743,0 +39596,Female,55,High School,12,76,94,71,97,5.0,4,26,Urban,Manager,20766,1 +39597,Female,26,High School,8,36,1,60,42,7.0,1,9,Urban,ML Engineer,60701,0 +39598,Female,43,High School,7,48,19,72,67,7.0,4,51,Semi-Urban,HR Executive,46930,0 +39599,Male,27,PhD,12,52,94,5,92,5.0,6,25,Urban,Data Analyst,116813,0 +39600,Female,57,PhD,0,34,67,17,75,4.0,4,96,Rural,Data Analyst,40171,0 +39601,Male,50,Bachelors,8,41,40,6,94,3.0,2,49,Urban,ML Engineer,121610,0 +39602,Male,59,Masters,2,20,45,94,3,8.0,7,37,Semi-Urban,Software Engineer,85747,0 +39603,Female,22,Masters,1,52,59,34,45,4.0,4,64,Semi-Urban,HR Executive,116980,0 +39604,Male,26,Masters,17,86,87,27,93,1.0,1,28,Semi-Urban,Software Engineer,128932,0 +39605,Male,23,PhD,18,41,82,79,2,4.0,7,48,Urban,ML Engineer,39592,1 +39606,Female,59,Bachelors,6,64,41,41,26,1.0,7,13,Semi-Urban,HR Executive,62965,0 +39607,Male,34,Masters,16,33,41,4,37,3.0,7,27,Urban,HR Executive,127873,0 +39608,Female,34,PhD,15,60,62,49,12,3.0,4,41,Urban,Manager,108807,0 +39609,Other,35,Masters,8,26,24,58,76,8.0,3,31,Urban,Manager,149776,0 +39610,Male,45,Diploma,16,30,67,16,51,9.0,0,88,Semi-Urban,Software Engineer,21991,0 +39611,Male,58,High School,13,38,65,98,75,4.0,2,19,Urban,ML Engineer,111575,0 +39612,Female,58,Bachelors,14,52,3,0,19,6.0,2,50,Urban,ML Engineer,68784,0 +39613,Male,38,Bachelors,18,3,9,67,85,3.0,4,25,Urban,Manager,29570,0 +39614,Male,47,Masters,5,41,9,93,5,2.0,6,42,Semi-Urban,Software Engineer,92971,0 +39615,Female,38,Diploma,8,22,20,34,94,1.0,0,64,Rural,HR Executive,113341,0 +39616,Female,27,Masters,3,65,92,82,54,7.0,3,24,Urban,Software Engineer,95340,1 +39617,Male,28,High School,19,99,46,79,87,2.0,0,32,Semi-Urban,HR Executive,74907,1 +39618,Female,38,High School,4,16,24,22,93,3.0,2,18,Semi-Urban,Data Analyst,53099,0 +39619,Female,27,Bachelors,4,37,18,30,5,6.0,6,1,Semi-Urban,Manager,96139,0 +39620,Male,26,High School,17,68,3,55,93,4.0,6,9,Urban,Manager,118627,0 +39621,Female,34,High School,19,85,82,10,29,0.0,7,33,Semi-Urban,Software Engineer,36766,0 +39622,Male,36,Masters,6,70,85,74,23,7.0,2,10,Semi-Urban,HR Executive,88313,1 +39623,Male,38,Diploma,8,39,26,61,49,2.0,2,75,Semi-Urban,Software Engineer,133678,0 +39624,Female,59,Diploma,19,52,29,96,60,7.0,6,71,Urban,HR Executive,51481,1 +39625,Female,30,High School,8,36,89,71,6,1.0,0,90,Urban,Software Engineer,134379,1 +39626,Male,37,Diploma,8,45,2,8,55,3.0,7,94,Urban,Data Analyst,88377,0 +39627,Female,30,High School,5,22,33,47,2,7.0,7,16,Rural,HR Executive,139989,0 +39628,Male,44,Masters,0,67,88,85,0,2.0,3,63,Semi-Urban,Data Analyst,109421,1 +39629,Male,45,Diploma,18,8,66,52,79,3.0,6,95,Urban,Data Analyst,54622,0 +39630,Male,31,Bachelors,3,88,57,80,74,4.0,1,10,Urban,Manager,116460,1 +39631,Male,22,Bachelors,16,52,95,25,35,8.0,0,94,Urban,HR Executive,80760,1 +39632,Male,26,Masters,19,89,66,36,28,6.0,5,53,Urban,Data Analyst,119739,1 +39633,Female,59,High School,8,96,4,51,67,1.0,4,12,Semi-Urban,Software Engineer,46592,0 +39634,Male,31,Bachelors,5,33,63,24,4,6.0,2,38,Rural,Software Engineer,74680,0 +39635,Male,34,Bachelors,15,59,54,3,80,1.0,2,58,Urban,Software Engineer,96177,0 +39636,Female,54,Bachelors,1,27,3,93,57,9.0,2,6,Urban,Software Engineer,121320,0 +39637,Male,54,Bachelors,13,10,50,71,65,3.0,7,49,Urban,Manager,84132,0 +39638,Female,57,Masters,18,29,73,68,44,1.0,3,51,Urban,ML Engineer,48197,0 +39639,Male,35,Bachelors,11,88,3,51,19,6.0,4,78,Rural,Data Analyst,116875,0 +39640,Male,50,Bachelors,6,97,41,35,38,4.0,2,34,Urban,Data Analyst,56904,0 +39641,Female,31,Bachelors,9,97,0,46,91,4.0,2,22,Urban,Manager,96149,0 +39642,Male,40,Bachelors,2,99,70,13,51,4.0,6,80,Urban,Manager,80202,1 +39643,Male,45,Bachelors,15,70,41,66,82,6.0,4,5,Urban,Data Analyst,48392,0 +39644,Male,48,Masters,8,66,11,73,94,2.0,6,77,Urban,HR Executive,125294,0 +39645,Male,33,Bachelors,18,37,40,48,23,9.0,1,95,Rural,Manager,44353,0 +39646,Female,43,Bachelors,16,93,32,31,25,6.0,3,25,Rural,Data Analyst,43011,0 +39647,Male,31,Diploma,9,68,44,12,69,5.0,1,44,Semi-Urban,HR Executive,22501,0 +39648,Male,35,Masters,17,45,27,86,24,6.0,0,59,Urban,Data Analyst,109809,0 +39649,Male,47,PhD,15,75,97,78,17,9.0,4,66,Urban,Data Analyst,83571,1 +39650,Male,29,Diploma,7,74,49,58,58,8.0,7,86,Rural,Manager,118888,1 +39651,Female,42,Masters,16,12,7,27,78,3.0,3,59,Rural,Manager,20845,0 +39652,Other,49,Diploma,13,35,46,7,94,0.0,3,27,Urban,Manager,113737,0 +39653,Male,21,Bachelors,13,83,32,19,97,4.0,3,76,Semi-Urban,HR Executive,102777,0 +39654,Male,39,Bachelors,15,68,91,60,1,0.0,3,59,Urban,ML Engineer,130531,1 +39655,Male,59,Bachelors,13,51,70,62,58,1.0,0,20,Urban,Software Engineer,120641,0 +39656,Male,55,High School,7,22,93,95,31,7.0,1,27,Urban,ML Engineer,32038,1 +39657,Male,52,Bachelors,2,15,75,14,52,4.0,2,87,Rural,Data Analyst,56382,0 +39658,Male,35,Bachelors,11,90,71,44,27,5.0,1,59,Urban,Manager,103395,1 +39659,Female,28,Diploma,14,12,22,73,22,0.0,0,78,Urban,Manager,63535,0 +39660,Male,34,Diploma,4,93,71,92,85,5.0,3,64,Semi-Urban,Data Analyst,122324,1 +39661,Other,27,Diploma,15,81,37,66,68,5.0,5,52,Urban,HR Executive,67450,0 +39662,Male,27,Masters,3,45,71,72,85,5.0,2,12,Rural,Data Analyst,127591,0 +39663,Female,52,Bachelors,3,41,11,97,22,7.0,3,35,Semi-Urban,HR Executive,31585,0 +39664,Female,40,Masters,14,42,33,74,53,9.0,3,99,Urban,Data Analyst,84405,1 +39665,Male,54,High School,4,66,7,93,66,9.0,7,92,Semi-Urban,HR Executive,82106,1 +39666,Female,26,Bachelors,11,95,92,50,60,6.0,2,18,Rural,Data Analyst,117497,1 +39667,Male,41,Diploma,2,71,31,76,48,2.0,5,26,Urban,Manager,33213,0 +39668,Other,47,Masters,17,30,9,41,18,9.0,6,14,Urban,ML Engineer,24745,0 +39669,Other,34,High School,2,16,35,10,89,9.0,6,76,Rural,Software Engineer,85905,0 +39670,Male,48,Bachelors,12,97,30,99,97,3.0,3,96,Rural,ML Engineer,112109,1 +39671,Female,27,PhD,1,48,72,4,72,0.0,3,8,Semi-Urban,Software Engineer,51009,0 +39672,Male,45,Bachelors,16,62,80,8,79,8.0,0,55,Semi-Urban,Manager,139811,0 +39673,Male,31,Bachelors,4,42,83,90,75,3.0,5,6,Urban,Manager,68089,0 +39674,Male,25,Diploma,7,99,52,31,1,6.0,3,96,Semi-Urban,Software Engineer,104201,1 +39675,Male,58,High School,11,57,5,24,50,9.0,5,89,Rural,Manager,70306,0 +39676,Female,24,Bachelors,1,33,61,36,71,9.0,7,55,Urban,ML Engineer,78156,0 +39677,Male,22,Bachelors,14,40,91,10,98,2.0,3,33,Rural,HR Executive,57084,0 +39678,Female,48,Bachelors,16,84,78,72,66,8.0,2,78,Urban,Manager,25862,1 +39679,Male,24,Diploma,14,66,44,62,54,1.0,4,7,Urban,Manager,79261,0 +39680,Other,53,Diploma,15,58,95,24,78,7.0,1,56,Urban,Software Engineer,48898,0 +39681,Male,46,Masters,3,58,19,51,39,1.0,4,56,Semi-Urban,ML Engineer,104627,0 +39682,Male,39,PhD,5,94,92,92,27,5.0,4,53,Semi-Urban,Data Analyst,140789,1 +39683,Female,49,High School,11,48,99,74,53,2.0,1,58,Urban,Data Analyst,120623,1 +39684,Female,31,Bachelors,0,30,22,91,75,7.0,6,71,Semi-Urban,Manager,75914,0 +39685,Female,35,Masters,1,48,10,12,29,8.0,6,71,Urban,Manager,123518,0 +39686,Male,37,Masters,6,24,33,19,71,7.0,5,85,Rural,Data Analyst,73848,0 +39687,Male,47,Bachelors,17,97,2,8,84,9.0,7,0,Semi-Urban,Data Analyst,28962,0 +39688,Male,24,Bachelors,19,70,37,0,90,2.0,3,25,Urban,Data Analyst,105051,0 +39689,Male,32,High School,6,3,82,2,26,7.0,0,53,Urban,Manager,45878,0 +39690,Male,59,Diploma,14,46,27,86,73,9.0,6,61,Urban,Manager,70838,0 +39691,Male,25,Bachelors,1,86,82,0,70,6.0,5,85,Urban,Software Engineer,81876,1 +39692,Male,22,High School,17,13,73,50,42,7.0,3,71,Urban,ML Engineer,62606,0 +39693,Female,28,Diploma,16,95,88,94,53,4.0,2,17,Semi-Urban,Data Analyst,61008,1 +39694,Female,59,Bachelors,16,74,37,11,11,3.0,6,17,Urban,HR Executive,56811,0 +39695,Male,51,PhD,6,56,53,58,92,7.0,6,55,Semi-Urban,ML Engineer,149072,0 +39696,Male,48,Bachelors,15,11,92,54,18,3.0,4,67,Urban,Software Engineer,131115,0 +39697,Male,52,Bachelors,17,12,16,86,37,1.0,3,62,Semi-Urban,HR Executive,131817,0 +39698,Male,45,Bachelors,12,41,4,56,51,9.0,0,27,Urban,Software Engineer,24566,0 +39699,Female,33,Masters,10,22,54,68,22,7.0,6,30,Semi-Urban,Data Analyst,55333,0 +39700,Female,42,Bachelors,12,80,31,86,26,3.0,1,55,Urban,HR Executive,23308,1 +39701,Female,36,Masters,1,27,79,13,18,7.0,6,95,Urban,Data Analyst,28605,0 +39702,Male,44,Bachelors,10,47,2,15,85,9.0,7,75,Urban,HR Executive,72353,0 +39703,Female,50,PhD,14,33,16,30,91,1.0,2,32,Rural,ML Engineer,60694,0 +39704,Male,47,Bachelors,14,41,72,49,77,8.0,5,74,Semi-Urban,Manager,135853,1 +39705,Female,38,Masters,14,39,25,52,37,1.0,2,89,Urban,HR Executive,148047,0 +39706,Male,28,Bachelors,9,49,50,32,27,5.0,1,54,Rural,ML Engineer,26422,0 +39707,Male,23,PhD,8,85,3,27,47,8.0,7,66,Semi-Urban,HR Executive,128254,0 +39708,Male,35,Diploma,5,14,88,8,52,3.0,5,11,Urban,HR Executive,72296,0 +39709,Male,29,Bachelors,18,9,30,54,33,0.0,3,62,Urban,ML Engineer,135139,0 +39710,Male,53,Diploma,16,36,57,12,19,0.0,1,90,Rural,HR Executive,78925,0 +39711,Female,45,High School,0,28,77,93,65,1.0,5,74,Urban,Software Engineer,138126,1 +39712,Male,27,High School,1,92,88,16,92,2.0,0,35,Rural,Manager,117493,0 +39713,Female,39,Bachelors,16,17,18,29,72,3.0,1,86,Urban,Software Engineer,30880,0 +39714,Female,37,Masters,7,91,51,46,66,3.0,4,62,Urban,Manager,135984,1 +39715,Female,30,Bachelors,8,86,87,1,36,8.0,4,38,Urban,Data Analyst,73182,0 +39716,Male,27,Diploma,10,84,72,66,99,9.0,3,91,Urban,Software Engineer,104749,1 +39717,Other,26,Diploma,4,94,98,8,8,3.0,4,43,Urban,HR Executive,117968,1 +39718,Male,27,Bachelors,16,49,22,14,52,0.0,1,71,Semi-Urban,HR Executive,134732,0 +39719,Male,43,Diploma,18,26,0,25,60,7.0,2,27,Urban,Data Analyst,43401,0 +39720,Female,44,Bachelors,16,97,5,40,75,0.0,6,22,Rural,ML Engineer,139389,0 +39721,Male,24,Bachelors,7,47,81,11,79,4.0,6,54,Urban,Data Analyst,110259,0 +39722,Female,26,Masters,0,58,89,46,10,3.0,1,74,Urban,Software Engineer,74114,1 +39723,Male,22,Bachelors,14,45,77,46,3,4.0,6,11,Urban,Manager,134533,0 +39724,Male,28,Diploma,13,73,77,8,38,1.0,6,43,Urban,Manager,133639,0 +39725,Male,24,Diploma,17,43,51,86,22,9.0,2,95,Semi-Urban,Manager,97875,1 +39726,Other,42,Bachelors,10,41,51,6,58,2.0,0,86,Urban,ML Engineer,100285,0 +39727,Female,34,Diploma,4,64,59,21,38,4.0,1,83,Urban,ML Engineer,42280,0 +39728,Male,29,Diploma,1,60,28,74,47,7.0,0,94,Rural,HR Executive,81514,1 +39729,Male,51,Masters,3,33,73,41,91,9.0,4,46,Semi-Urban,Data Analyst,83899,0 +39730,Male,23,High School,17,75,70,72,51,9.0,4,50,Urban,HR Executive,115587,1 +39731,Male,46,Bachelors,2,39,85,98,31,8.0,4,5,Semi-Urban,Data Analyst,94165,0 +39732,Female,23,Bachelors,6,1,16,11,37,8.0,1,33,Urban,HR Executive,146940,0 +39733,Other,51,Bachelors,6,35,8,71,64,6.0,0,46,Semi-Urban,Software Engineer,71927,0 +39734,Female,46,High School,9,34,42,91,67,9.0,4,97,Urban,Manager,55397,1 +39735,Male,22,Masters,12,22,66,16,41,1.0,6,80,Rural,Software Engineer,47202,0 +39736,Male,49,Diploma,1,21,24,77,62,2.0,3,98,Urban,Manager,32010,0 +39737,Male,53,Bachelors,19,7,6,9,5,5.0,1,35,Semi-Urban,HR Executive,62056,0 +39738,Male,52,Bachelors,18,22,24,11,98,1.0,1,86,Urban,Software Engineer,68395,0 +39739,Male,40,Bachelors,6,65,25,51,44,5.0,1,17,Urban,HR Executive,147879,0 +39740,Female,23,Bachelors,15,10,11,34,88,5.0,0,82,Urban,ML Engineer,54256,0 +39741,Male,39,Masters,0,59,10,14,48,3.0,1,48,Semi-Urban,Software Engineer,62863,0 +39742,Male,59,Bachelors,11,62,7,95,95,7.0,6,95,Urban,ML Engineer,38502,1 +39743,Male,56,Masters,12,6,93,13,91,7.0,5,44,Urban,Software Engineer,81366,0 +39744,Other,35,Bachelors,0,70,87,54,95,1.0,0,57,Urban,Manager,21533,1 +39745,Female,54,Bachelors,12,50,88,40,8,5.0,1,50,Urban,Manager,126516,0 +39746,Male,32,Bachelors,6,23,41,16,16,8.0,6,45,Semi-Urban,HR Executive,23744,0 +39747,Female,43,Bachelors,3,45,30,59,99,2.0,6,17,Urban,Software Engineer,117937,0 +39748,Male,33,Bachelors,10,83,52,40,41,4.0,5,6,Urban,Manager,47183,0 +39749,Male,54,Bachelors,10,35,76,87,3,6.0,3,27,Urban,ML Engineer,144247,0 +39750,Male,22,Bachelors,3,94,21,1,85,5.0,7,34,Rural,ML Engineer,54566,0 +39751,Male,51,Bachelors,1,73,77,91,41,4.0,3,53,Rural,HR Executive,22271,1 +39752,Male,45,Bachelors,6,18,89,75,46,2.0,3,88,Semi-Urban,Data Analyst,65653,1 +39753,Female,37,High School,3,98,15,31,38,2.0,4,46,Urban,Software Engineer,113297,0 +39754,Male,24,Bachelors,16,59,87,35,78,2.0,2,48,Semi-Urban,ML Engineer,86487,0 +39755,Male,46,Bachelors,2,17,66,53,96,6.0,6,48,Semi-Urban,Software Engineer,72832,0 +39756,Male,44,Bachelors,16,38,73,36,18,2.0,6,22,Rural,Software Engineer,95227,0 +39757,Female,28,Bachelors,0,25,4,55,88,4.0,0,5,Urban,HR Executive,37624,0 +39758,Female,45,Bachelors,4,76,29,60,78,4.0,3,3,Urban,Data Analyst,141415,0 +39759,Male,30,Diploma,14,69,75,49,82,0.0,7,23,Rural,Data Analyst,120353,0 +39760,Male,46,Bachelors,13,69,51,81,42,7.0,7,54,Urban,Data Analyst,136172,1 +39761,Male,39,Masters,9,43,64,29,42,9.0,0,83,Urban,HR Executive,143343,0 +39762,Male,44,Bachelors,16,21,76,67,74,3.0,5,61,Rural,ML Engineer,93704,0 +39763,Male,44,Masters,3,65,59,21,20,3.0,7,36,Rural,HR Executive,52043,0 +39764,Male,29,Diploma,6,74,56,77,11,3.0,7,49,Semi-Urban,Manager,54408,1 +39765,Female,47,Diploma,1,71,17,83,26,5.0,5,52,Semi-Urban,Data Analyst,47177,0 +39766,Male,48,Masters,2,57,40,43,7,7.0,0,45,Urban,Software Engineer,21604,0 +39767,Female,58,Diploma,13,35,0,77,21,9.0,0,99,Rural,Software Engineer,94583,0 +39768,Female,23,Bachelors,4,15,47,92,53,2.0,5,71,Urban,ML Engineer,106238,0 +39769,Male,59,Masters,7,11,43,90,4,2.0,1,47,Semi-Urban,Data Analyst,20012,0 +39770,Female,26,Bachelors,5,54,43,2,0,4.0,0,90,Urban,HR Executive,149070,0 +39771,Male,56,Bachelors,18,76,13,85,19,9.0,7,55,Urban,HR Executive,125448,0 +39772,Female,22,Diploma,12,80,78,20,28,3.0,1,4,Rural,Data Analyst,51408,0 +39773,Male,24,Bachelors,8,56,5,5,87,0.0,7,25,Urban,ML Engineer,47341,0 +39774,Male,49,Masters,13,31,0,0,12,2.0,4,66,Semi-Urban,Data Analyst,149051,0 +39775,Male,36,Bachelors,19,26,75,13,97,1.0,2,0,Urban,Software Engineer,35989,0 +39776,Male,49,Bachelors,9,46,58,81,3,9.0,4,30,Semi-Urban,HR Executive,45288,0 +39777,Male,29,Bachelors,9,56,13,20,2,1.0,6,98,Urban,Software Engineer,56397,0 +39778,Male,36,Diploma,2,73,55,68,97,0.0,6,78,Rural,ML Engineer,120154,1 +39779,Male,22,High School,16,39,20,67,36,5.0,4,38,Urban,HR Executive,139074,0 +39780,Female,28,High School,10,67,59,71,32,3.0,5,92,Semi-Urban,Software Engineer,102700,1 +39781,Male,39,Diploma,3,14,7,61,48,7.0,7,57,Urban,HR Executive,76864,0 +39782,Male,27,Diploma,8,93,56,30,9,2.0,4,20,Urban,HR Executive,145193,0 +39783,Male,24,High School,8,95,83,61,35,3.0,7,1,Rural,Manager,28250,1 +39784,Male,50,Masters,0,54,23,22,14,8.0,4,45,Urban,ML Engineer,119995,0 +39785,Female,51,Diploma,15,80,26,55,67,1.0,4,33,Urban,Manager,123995,0 +39786,Male,23,Diploma,1,32,87,53,86,7.0,0,85,Urban,HR Executive,35023,1 +39787,Female,48,Bachelors,4,99,62,52,69,7.0,5,63,Semi-Urban,Manager,81724,1 +39788,Male,52,Masters,6,73,37,74,55,4.0,7,69,Rural,Software Engineer,85999,1 +39789,Male,48,High School,7,18,74,44,77,7.0,6,50,Semi-Urban,Manager,62867,0 +39790,Female,36,Masters,7,58,33,6,21,8.0,6,27,Rural,HR Executive,34676,0 +39791,Male,38,Bachelors,4,71,87,52,30,9.0,3,88,Urban,Software Engineer,140539,1 +39792,Male,56,Diploma,19,3,66,12,13,0.0,7,96,Rural,Manager,90687,0 +39793,Male,25,Diploma,16,98,58,53,17,7.0,7,13,Urban,HR Executive,67480,0 +39794,Male,57,Diploma,0,38,52,36,39,4.0,0,27,Urban,ML Engineer,74191,0 +39795,Male,26,Diploma,13,56,2,9,0,5.0,3,28,Urban,Software Engineer,37029,0 +39796,Male,23,Masters,18,9,73,1,57,1.0,7,73,Urban,ML Engineer,25198,0 +39797,Male,52,Bachelors,7,98,5,23,41,1.0,5,51,Semi-Urban,Manager,127234,0 +39798,Female,46,PhD,9,28,3,8,69,5.0,3,6,Urban,HR Executive,144171,0 +39799,Female,54,Bachelors,4,74,74,52,85,9.0,1,63,Urban,Manager,43916,1 +39800,Female,23,Bachelors,10,52,18,81,48,0.0,4,31,Urban,Manager,33709,0 +39801,Female,50,Masters,1,35,15,33,75,5.0,4,11,Urban,HR Executive,20450,0 +39802,Female,22,Masters,14,41,70,82,67,9.0,0,19,Urban,Manager,88362,0 +39803,Other,21,Bachelors,0,18,80,48,69,9.0,5,68,Urban,Data Analyst,60947,0 +39804,Male,41,Bachelors,16,28,53,20,75,4.0,7,0,Urban,Software Engineer,118349,0 +39805,Male,27,Bachelors,1,89,38,68,57,2.0,3,68,Urban,Data Analyst,128654,1 +39806,Male,39,Masters,14,68,49,19,87,9.0,1,64,Rural,Software Engineer,87887,0 +39807,Male,54,Masters,7,33,70,97,90,0.0,1,36,Semi-Urban,Manager,101728,1 +39808,Male,47,Diploma,13,13,83,20,47,9.0,6,41,Urban,Data Analyst,134763,0 +39809,Male,38,Diploma,16,42,93,45,30,8.0,3,19,Urban,Manager,92232,0 +39810,Male,29,Bachelors,3,6,34,17,93,1.0,1,53,Urban,Software Engineer,74408,0 +39811,Other,34,Masters,15,19,65,14,80,8.0,2,92,Rural,Data Analyst,90245,0 +39812,Other,44,Diploma,13,57,1,66,80,6.0,0,59,Urban,Data Analyst,90083,0 +39813,Female,27,Bachelors,17,7,11,94,72,3.0,7,47,Urban,Software Engineer,98810,0 +39814,Male,50,Bachelors,14,99,85,81,61,4.0,6,12,Urban,Data Analyst,69239,1 +39815,Female,25,Bachelors,4,27,25,50,49,8.0,3,59,Urban,Manager,101188,0 +39816,Female,30,Bachelors,12,91,5,69,6,1.0,2,42,Urban,Manager,90601,0 +39817,Female,31,Bachelors,7,74,85,32,75,9.0,6,12,Urban,HR Executive,106044,0 +39818,Female,24,High School,14,10,30,80,97,2.0,1,79,Urban,HR Executive,61300,0 +39819,Male,22,Diploma,5,78,29,47,45,6.0,5,51,Urban,ML Engineer,21882,0 +39820,Male,41,Masters,7,86,67,22,8,8.0,3,60,Rural,Manager,126599,1 +39821,Female,30,PhD,7,83,74,66,35,8.0,0,37,Rural,Manager,103642,1 +39822,Male,50,Masters,19,40,75,17,88,6.0,7,85,Semi-Urban,HR Executive,109058,0 +39823,Male,29,Bachelors,4,74,8,29,7,9.0,7,44,Urban,HR Executive,134456,0 +39824,Male,27,Bachelors,17,85,64,25,9,8.0,3,83,Urban,Software Engineer,69342,1 +39825,Male,39,Masters,7,14,11,81,23,1.0,0,26,Urban,HR Executive,51395,0 +39826,Female,36,Diploma,2,13,21,57,0,9.0,0,93,Urban,Software Engineer,111349,0 +39827,Male,49,Bachelors,10,60,43,72,53,1.0,2,56,Semi-Urban,Software Engineer,111586,0 +39828,Male,38,Bachelors,19,40,28,91,3,6.0,2,56,Rural,Manager,51958,0 +39829,Other,34,Diploma,4,52,94,4,55,7.0,2,56,Urban,Manager,117528,0 +39830,Male,30,High School,15,94,0,32,42,8.0,6,41,Urban,HR Executive,39067,0 +39831,Female,32,High School,10,4,7,58,4,3.0,1,39,Urban,ML Engineer,102025,0 +39832,Male,55,Diploma,17,47,92,47,60,9.0,7,8,Semi-Urban,Software Engineer,149606,0 +39833,Female,41,Masters,5,49,85,37,11,5.0,5,67,Semi-Urban,Data Analyst,121706,0 +39834,Male,42,Bachelors,2,16,40,36,50,0.0,2,46,Urban,Data Analyst,50725,0 +39835,Male,53,Bachelors,5,47,17,54,78,8.0,7,65,Rural,Manager,59286,0 +39836,Male,30,Masters,10,73,58,57,20,7.0,2,40,Semi-Urban,Software Engineer,29536,0 +39837,Other,36,Bachelors,12,46,88,27,71,3.0,4,47,Urban,Data Analyst,26930,0 +39838,Male,38,Bachelors,6,34,77,62,54,1.0,5,29,Rural,Data Analyst,51157,0 +39839,Male,42,Bachelors,1,37,78,38,40,3.0,0,90,Urban,Software Engineer,63161,1 +39840,Female,26,Diploma,3,12,15,58,20,1.0,3,75,Urban,Manager,52123,0 +39841,Male,55,Diploma,8,92,12,66,0,6.0,1,65,Urban,HR Executive,29785,1 +39842,Female,27,Diploma,15,88,4,41,2,3.0,2,47,Rural,ML Engineer,58523,0 +39843,Female,46,High School,5,70,72,89,55,2.0,7,20,Semi-Urban,HR Executive,132701,1 +39844,Male,58,Diploma,7,58,3,11,58,3.0,7,99,Semi-Urban,HR Executive,95514,0 +39845,Male,30,Diploma,19,98,0,96,15,6.0,0,57,Semi-Urban,HR Executive,141357,1 +39846,Female,56,High School,11,75,76,7,51,8.0,6,78,Rural,ML Engineer,60619,0 +39847,Male,30,Diploma,18,29,47,69,82,2.0,7,93,Urban,Software Engineer,39266,1 +39848,Male,36,Diploma,0,69,49,88,5,8.0,3,73,Rural,HR Executive,104751,1 +39849,Female,57,Bachelors,14,89,18,87,96,1.0,6,7,Semi-Urban,Manager,26112,0 +39850,Male,26,Masters,19,29,45,46,47,9.0,7,31,Urban,ML Engineer,48646,0 +39851,Female,44,Diploma,10,18,73,56,87,9.0,2,7,Urban,HR Executive,88949,0 +39852,Male,38,PhD,2,54,46,2,52,2.0,1,70,Urban,Data Analyst,119001,0 +39853,Female,32,High School,1,10,86,20,4,5.0,0,81,Semi-Urban,Data Analyst,63420,0 +39854,Male,43,High School,5,21,42,68,40,2.0,2,21,Rural,HR Executive,83686,0 +39855,Male,39,Diploma,6,55,83,50,67,8.0,5,90,Semi-Urban,Software Engineer,97236,1 +39856,Female,46,Bachelors,18,32,65,10,82,5.0,4,46,Urban,Software Engineer,111354,0 +39857,Male,45,PhD,4,65,14,60,91,5.0,3,0,Urban,Software Engineer,70073,0 +39858,Male,48,Bachelors,12,41,32,54,69,7.0,3,32,Urban,ML Engineer,74383,0 +39859,Female,47,High School,12,3,98,38,40,7.0,1,16,Urban,Software Engineer,50772,0 +39860,Female,58,High School,8,53,20,52,62,5.0,5,45,Semi-Urban,Data Analyst,30329,0 +39861,Male,23,Masters,0,54,7,60,23,6.0,0,42,Urban,HR Executive,149952,0 +39862,Male,59,Bachelors,16,27,54,38,91,1.0,7,34,Urban,Data Analyst,102994,0 +39863,Female,56,Bachelors,15,45,23,31,5,7.0,1,53,Urban,Data Analyst,95318,0 +39864,Male,44,Masters,15,17,11,47,68,4.0,3,33,Semi-Urban,Manager,33520,0 +39865,Female,59,High School,13,40,28,16,81,1.0,7,27,Urban,ML Engineer,65453,0 +39866,Male,23,High School,15,2,41,96,28,1.0,2,55,Urban,Software Engineer,125351,0 +39867,Female,24,High School,2,54,25,69,76,9.0,7,64,Urban,ML Engineer,23247,0 +39868,Male,25,Masters,8,73,27,70,43,3.0,0,97,Rural,Software Engineer,85086,1 +39869,Male,37,Bachelors,4,10,74,82,79,9.0,0,29,Rural,HR Executive,122802,0 +39870,Male,28,Bachelors,7,66,31,21,79,3.0,1,69,Semi-Urban,Manager,124389,0 +39871,Male,29,Masters,0,30,97,26,92,6.0,7,68,Urban,HR Executive,55049,0 +39872,Male,30,Bachelors,12,54,37,86,11,2.0,5,46,Rural,ML Engineer,89264,0 +39873,Male,57,High School,7,65,6,7,8,1.0,4,53,Urban,Manager,103546,0 +39874,Female,30,Bachelors,1,99,10,67,20,0.0,3,76,Urban,HR Executive,68365,1 +39875,Male,48,Masters,14,77,77,39,93,8.0,0,62,Semi-Urban,Manager,67732,1 +39876,Other,59,Bachelors,9,30,51,64,48,0.0,3,45,Semi-Urban,Manager,56684,0 +39877,Male,30,Diploma,8,28,37,37,76,0.0,7,10,Urban,ML Engineer,79755,0 +39878,Female,57,Masters,15,43,16,90,4,8.0,2,74,Semi-Urban,Software Engineer,99673,0 +39879,Female,44,Bachelors,9,91,3,99,23,7.0,1,59,Urban,Manager,80093,1 +39880,Female,44,High School,0,48,83,88,47,2.0,4,39,Semi-Urban,Software Engineer,126027,1 +39881,Male,33,Bachelors,3,52,74,24,19,4.0,4,11,Semi-Urban,ML Engineer,145625,0 +39882,Female,52,Bachelors,1,83,60,69,57,4.0,2,54,Urban,Data Analyst,121915,1 +39883,Male,59,Diploma,5,92,4,52,82,2.0,2,70,Urban,Data Analyst,85627,0 +39884,Male,35,Diploma,15,19,11,52,61,7.0,0,74,Rural,ML Engineer,110192,0 +39885,Female,54,PhD,6,83,19,1,64,7.0,7,81,Urban,ML Engineer,103400,0 +39886,Male,28,Bachelors,3,18,91,97,9,6.0,2,50,Rural,Software Engineer,89323,1 +39887,Male,59,Masters,5,2,12,40,22,4.0,7,70,Semi-Urban,HR Executive,145197,0 +39888,Male,22,Masters,14,41,59,61,64,6.0,6,65,Semi-Urban,Software Engineer,64098,0 +39889,Male,39,High School,14,93,58,70,36,3.0,3,30,Rural,HR Executive,128958,1 +39890,Male,35,Bachelors,5,2,97,4,33,6.0,6,21,Semi-Urban,ML Engineer,147481,0 +39891,Female,25,Masters,6,79,75,31,81,2.0,4,4,Rural,Software Engineer,32109,0 +39892,Male,31,Masters,18,76,33,38,66,9.0,0,21,Semi-Urban,HR Executive,115755,0 +39893,Female,41,Diploma,15,29,85,88,18,4.0,4,82,Semi-Urban,HR Executive,74581,1 +39894,Female,27,Diploma,3,83,13,26,92,8.0,6,16,Rural,ML Engineer,71538,0 +39895,Male,50,Diploma,12,60,26,84,64,1.0,4,87,Urban,Manager,27324,1 +39896,Female,49,Bachelors,8,15,17,49,67,3.0,1,9,Semi-Urban,Software Engineer,46287,0 +39897,Female,59,Bachelors,1,26,71,37,22,8.0,7,81,Semi-Urban,ML Engineer,102169,0 +39898,Male,30,Masters,15,35,86,89,10,3.0,6,87,Urban,Software Engineer,33368,1 +39899,Male,53,Masters,9,2,41,81,7,3.0,6,60,Urban,Data Analyst,61445,0 +39900,Female,38,Masters,16,66,30,68,13,6.0,2,14,Urban,Manager,49724,0 +39901,Other,44,Bachelors,10,88,56,41,65,9.0,6,15,Rural,Data Analyst,33014,0 +39902,Female,51,High School,7,88,29,68,12,9.0,0,17,Urban,Data Analyst,94254,0 +39903,Male,26,Bachelors,2,96,50,49,16,7.0,4,78,Urban,Software Engineer,53193,1 +39904,Male,41,Masters,5,63,91,74,96,2.0,1,1,Urban,Manager,115051,0 +39905,Male,56,PhD,3,0,7,71,87,6.0,3,31,Rural,ML Engineer,41105,0 +39906,Female,27,Bachelors,12,56,52,42,63,7.0,3,45,Urban,Data Analyst,129907,0 +39907,Female,25,Bachelors,10,90,46,26,7,8.0,5,51,Rural,ML Engineer,83746,0 +39908,Male,54,Bachelors,19,93,28,41,95,1.0,5,8,Urban,Data Analyst,45559,0 +39909,Female,44,PhD,3,70,87,14,30,8.0,6,81,Urban,HR Executive,51174,1 +39910,Male,34,High School,10,43,24,22,97,4.0,1,44,Rural,ML Engineer,44414,0 +39911,Female,49,Diploma,0,93,6,52,60,1.0,3,70,Urban,Software Engineer,95418,0 +39912,Male,33,PhD,14,67,36,73,56,7.0,0,20,Semi-Urban,Software Engineer,50693,0 +39913,Female,58,Bachelors,9,54,97,79,31,4.0,3,62,Urban,Data Analyst,133322,1 +39914,Male,34,Bachelors,7,87,39,18,77,4.0,1,91,Semi-Urban,ML Engineer,139793,1 +39915,Male,35,Bachelors,13,52,99,4,92,2.0,4,87,Urban,HR Executive,121194,1 +39916,Male,30,Bachelors,9,95,4,46,85,4.0,3,91,Urban,Manager,56515,1 +39917,Female,31,Bachelors,17,1,68,65,30,7.0,5,88,Urban,Software Engineer,97081,0 +39918,Female,39,Bachelors,2,79,89,35,94,7.0,1,83,Rural,Software Engineer,121531,1 +39919,Male,37,High School,16,29,79,74,6,8.0,7,15,Semi-Urban,Software Engineer,87325,0 +39920,Female,25,Bachelors,16,30,4,14,78,1.0,7,15,Semi-Urban,Software Engineer,36162,0 +39921,Female,37,Masters,8,55,48,11,87,1.0,6,51,Urban,HR Executive,49101,0 +39922,Female,51,High School,19,28,12,14,13,7.0,5,73,Urban,HR Executive,71679,0 +39923,Male,57,Bachelors,4,32,69,19,21,2.0,5,22,Urban,Data Analyst,123365,0 +39924,Male,31,High School,10,28,9,65,36,2.0,4,91,Urban,HR Executive,53978,0 +39925,Male,30,Bachelors,13,57,93,71,3,1.0,5,13,Rural,Data Analyst,143554,0 +39926,Male,54,Bachelors,12,70,51,18,5,0.0,1,98,Urban,Software Engineer,129702,1 +39927,Female,44,Diploma,1,75,92,80,30,1.0,4,81,Semi-Urban,ML Engineer,115874,1 +39928,Male,33,High School,16,81,69,36,16,2.0,7,95,Semi-Urban,ML Engineer,64509,1 +39929,Male,54,Bachelors,12,2,78,76,22,3.0,2,40,Rural,ML Engineer,85917,0 +39930,Male,35,High School,3,43,4,76,75,2.0,0,29,Urban,HR Executive,127423,0 +39931,Male,55,Diploma,3,82,74,74,13,5.0,6,49,Rural,Manager,83689,1 +39932,Other,36,Masters,1,46,95,53,96,9.0,7,3,Semi-Urban,HR Executive,64499,0 +39933,Female,54,Masters,11,70,78,96,6,3.0,7,26,Semi-Urban,Software Engineer,132332,1 +39934,Male,43,Diploma,6,81,96,70,94,7.0,3,87,Urban,Manager,84455,1 +39935,Female,53,Bachelors,8,26,35,56,34,9.0,2,90,Rural,Manager,118779,0 +39936,Male,50,Bachelors,12,97,52,75,21,3.0,0,0,Urban,HR Executive,140319,0 +39937,Female,22,Diploma,13,32,15,63,95,7.0,0,32,Urban,Manager,122148,0 +39938,Male,31,PhD,2,80,11,11,77,8.0,2,51,Urban,Data Analyst,70086,0 +39939,Male,43,Bachelors,5,42,48,9,14,9.0,7,82,Urban,ML Engineer,81186,0 +39940,Female,49,Masters,14,40,79,30,15,6.0,0,23,Urban,ML Engineer,118714,0 +39941,Female,38,High School,1,0,15,96,29,8.0,2,39,Rural,ML Engineer,126240,0 +39942,Male,38,Bachelors,10,38,90,99,65,2.0,3,85,Urban,ML Engineer,40484,1 +39943,Female,47,Diploma,15,40,73,92,29,5.0,1,29,Rural,Software Engineer,134127,0 +39944,Female,40,Masters,8,5,68,30,74,2.0,6,86,Rural,HR Executive,70609,0 +39945,Male,45,Diploma,0,10,1,24,69,7.0,4,92,Semi-Urban,HR Executive,72789,0 +39946,Male,23,High School,2,52,70,72,0,7.0,3,64,Semi-Urban,ML Engineer,42617,1 +39947,Male,51,Bachelors,7,46,79,30,71,4.0,0,98,Urban,Software Engineer,41672,1 +39948,Female,37,Masters,4,29,86,33,9,5.0,5,86,Semi-Urban,Software Engineer,110198,0 +39949,Other,26,Diploma,10,9,36,5,66,2.0,7,4,Semi-Urban,Software Engineer,142432,0 +39950,Male,51,Bachelors,12,7,74,82,63,8.0,6,22,Urban,Software Engineer,107199,0 +39951,Female,48,Diploma,19,26,5,72,21,3.0,1,9,Semi-Urban,HR Executive,128517,0 +39952,Female,42,Bachelors,8,41,89,47,12,2.0,7,63,Semi-Urban,Software Engineer,62966,0 +39953,Male,45,Diploma,18,96,55,24,39,1.0,1,76,Urban,ML Engineer,89968,1 +39954,Male,48,Bachelors,14,81,91,89,2,8.0,1,43,Rural,ML Engineer,101865,1 +39955,Male,41,High School,18,33,6,36,22,3.0,2,12,Urban,Software Engineer,119159,0 +39956,Male,48,Bachelors,4,54,90,16,59,6.0,7,16,Semi-Urban,Manager,53647,0 +39957,Female,24,Bachelors,11,49,66,6,37,8.0,3,4,Urban,Data Analyst,96892,0 +39958,Male,22,Diploma,19,1,65,75,38,4.0,4,35,Urban,HR Executive,61841,0 +39959,Male,51,Bachelors,3,24,7,91,8,2.0,6,5,Urban,Manager,99767,0 +39960,Female,59,Bachelors,12,25,11,96,88,0.0,5,71,Urban,Software Engineer,26199,0 +39961,Male,42,Bachelors,8,95,43,47,31,8.0,3,72,Urban,Data Analyst,68359,1 +39962,Male,43,Masters,6,49,66,88,82,4.0,2,16,Semi-Urban,ML Engineer,83613,0 +39963,Male,31,Bachelors,2,90,19,39,58,9.0,1,77,Rural,Data Analyst,36423,0 +39964,Male,25,Bachelors,9,67,24,5,38,8.0,1,5,Semi-Urban,Data Analyst,92529,0 +39965,Female,47,Masters,17,76,25,35,43,3.0,5,29,Rural,ML Engineer,81959,0 +39966,Male,47,Masters,19,78,82,67,93,6.0,0,1,Urban,ML Engineer,127287,0 +39967,Female,54,Masters,0,41,28,10,86,0.0,3,13,Urban,Data Analyst,83328,0 +39968,Male,23,Bachelors,2,88,44,98,12,8.0,4,62,Urban,Data Analyst,83381,1 +39969,Male,42,Bachelors,19,42,61,80,62,3.0,6,70,Urban,Software Engineer,107107,1 +39970,Male,55,Diploma,11,38,33,7,45,0.0,7,93,Urban,Data Analyst,71392,0 +39971,Female,48,Diploma,4,83,0,1,32,0.0,7,55,Semi-Urban,HR Executive,79431,0 +39972,Male,36,High School,12,8,89,34,37,1.0,4,51,Urban,Software Engineer,145071,0 +39973,Male,27,Masters,16,8,42,0,30,5.0,5,2,Urban,Manager,89705,0 +39974,Female,23,Bachelors,10,40,17,99,55,6.0,7,83,Urban,ML Engineer,39962,0 +39975,Male,52,Masters,8,65,13,31,17,9.0,5,82,Urban,HR Executive,91039,0 +39976,Male,33,Bachelors,0,28,84,59,84,8.0,2,74,Semi-Urban,HR Executive,144343,1 +39977,Male,50,Bachelors,19,89,4,78,92,6.0,3,99,Urban,HR Executive,50367,1 +39978,Female,41,Masters,8,87,4,37,89,0.0,5,44,Rural,Manager,34403,0 +39979,Other,32,High School,19,2,21,51,75,6.0,4,4,Urban,Software Engineer,124313,0 +39980,Male,40,Masters,8,8,37,0,5,0.0,0,29,Semi-Urban,Software Engineer,81047,0 +39981,Male,54,High School,9,72,70,6,75,0.0,4,21,Semi-Urban,Software Engineer,37427,0 +39982,Male,30,High School,1,71,44,40,97,2.0,0,37,Rural,ML Engineer,115545,0 +39983,Female,47,Bachelors,7,38,21,61,80,3.0,3,35,Urban,Data Analyst,37293,0 +39984,Male,25,Bachelors,11,64,97,78,13,7.0,7,48,Urban,Manager,43963,1 +39985,Male,31,Diploma,2,13,32,45,42,1.0,0,88,Rural,HR Executive,85516,0 +39986,Female,36,Masters,2,85,96,31,65,7.0,3,76,Urban,Software Engineer,70571,1 +39987,Male,30,High School,7,52,1,77,3,8.0,0,65,Urban,Manager,140126,0 +39988,Male,45,High School,6,49,72,40,28,4.0,1,34,Semi-Urban,Manager,99232,0 +39989,Other,26,High School,14,43,59,99,39,7.0,5,10,Urban,Software Engineer,147428,0 +39990,Other,31,Bachelors,17,52,41,65,84,3.0,6,20,Semi-Urban,HR Executive,119021,0 +39991,Male,40,High School,1,31,49,70,83,7.0,5,76,Rural,Manager,119025,0 +39992,Male,35,Bachelors,13,32,37,62,11,7.0,1,21,Urban,Software Engineer,31811,0 +39993,Male,24,Masters,15,96,35,88,2,0.0,7,87,Rural,Software Engineer,106840,1 +39994,Male,24,High School,16,33,38,93,17,1.0,3,27,Urban,Data Analyst,85885,0 +39995,Female,40,Diploma,19,40,49,31,25,4.0,4,6,Urban,ML Engineer,55705,0 +39996,Female,25,Bachelors,11,50,0,80,20,6.0,1,48,Semi-Urban,Data Analyst,91197,0 +39997,Female,53,Bachelors,4,63,93,37,14,0.0,3,17,Semi-Urban,Manager,112467,0 +39998,Male,38,High School,11,15,41,83,71,6.0,7,17,Rural,Data Analyst,57307,0 +39999,Male,45,Bachelors,6,80,27,87,34,8.0,4,41,Urban,Data Analyst,90224,1 +40000,Male,23,Diploma,16,27,33,33,84,8.0,3,46,Urban,Data Analyst,71729,0 +40001,Male,33,Masters,6,70,3,50,1,3.0,6,33,Urban,HR Executive,77330,0 +40002,Male,32,Bachelors,0,2,79,75,63,2.0,1,65,Urban,HR Executive,30600,0 +40003,Male,29,Diploma,14,53,72,44,69,5.0,4,17,Urban,HR Executive,79511,0 +40004,Male,48,Bachelors,3,23,9,86,36,2.0,0,52,Semi-Urban,HR Executive,28362,0 +40005,Male,28,PhD,3,61,88,14,37,0.0,0,22,Urban,Manager,144061,0 +40006,Male,30,Bachelors,5,56,59,30,54,1.0,7,43,Urban,Data Analyst,24811,0 +40007,Male,39,Diploma,11,98,31,98,39,9.0,5,95,Urban,HR Executive,143766,1 +40008,Male,51,Bachelors,1,1,89,53,64,8.0,7,34,Urban,HR Executive,20544,0 +40009,Male,24,Diploma,19,23,55,84,72,8.0,4,95,Urban,Data Analyst,50462,1 +40010,Male,36,Masters,7,92,41,23,85,4.0,7,35,Rural,Software Engineer,65874,0 +40011,Female,21,High School,16,24,79,75,4,2.0,6,83,Urban,Software Engineer,106277,1 +40012,Male,24,Bachelors,4,50,98,13,6,7.0,7,7,Urban,Manager,86430,0 +40013,Female,50,High School,2,60,33,22,56,0.0,7,63,Semi-Urban,Data Analyst,117539,0 +40014,Female,48,Masters,9,17,85,94,32,9.0,7,54,Semi-Urban,Manager,89704,1 +40015,Male,34,Bachelors,0,83,62,10,38,0.0,3,47,Urban,HR Executive,103226,0 +40016,Male,38,High School,16,91,10,12,34,1.0,5,43,Urban,Manager,76629,0 +40017,Male,24,Bachelors,9,10,98,10,56,2.0,5,49,Urban,Manager,88269,0 +40018,Male,21,High School,4,14,22,65,94,1.0,3,23,Urban,Software Engineer,55948,0 +40019,Male,42,Masters,4,97,10,60,96,3.0,1,82,Urban,HR Executive,30829,1 +40020,Female,31,Bachelors,16,60,0,58,55,9.0,1,90,Rural,Manager,128789,0 +40021,Male,39,Bachelors,9,93,87,86,75,5.0,4,34,Rural,Software Engineer,28264,1 +40022,Other,27,Masters,4,6,52,9,80,6.0,3,91,Urban,Software Engineer,140536,0 +40023,Female,47,Bachelors,10,83,90,65,14,9.0,7,0,Urban,ML Engineer,133455,0 +40024,Male,48,Diploma,5,19,13,32,85,4.0,4,53,Urban,ML Engineer,96032,0 +40025,Male,54,High School,14,99,29,25,38,3.0,6,24,Rural,Software Engineer,91668,0 +40026,Male,23,Bachelors,8,33,2,46,14,9.0,5,50,Urban,Software Engineer,84290,0 +40027,Male,33,Masters,11,70,65,21,85,1.0,5,86,Rural,Data Analyst,45095,1 +40028,Male,55,Diploma,10,35,99,97,89,9.0,7,22,Semi-Urban,HR Executive,26196,1 +40029,Female,53,Masters,4,73,31,6,16,7.0,0,37,Semi-Urban,HR Executive,55589,0 +40030,Male,42,Bachelors,7,33,66,38,55,0.0,3,34,Urban,Manager,94741,0 +40031,Male,53,Diploma,12,63,50,47,93,1.0,1,20,Urban,Data Analyst,36251,0 +40032,Female,24,Masters,5,22,17,43,64,9.0,0,93,Urban,Manager,36656,0 +40033,Male,41,Bachelors,0,3,27,41,70,4.0,1,18,Urban,Software Engineer,92359,0 +40034,Male,57,Bachelors,15,72,28,11,32,7.0,6,50,Rural,Software Engineer,30731,0 +40035,Male,45,Masters,8,41,65,4,47,0.0,0,29,Urban,Data Analyst,86560,0 +40036,Male,23,Bachelors,10,40,22,71,15,7.0,3,85,Rural,ML Engineer,66312,0 +40037,Female,29,Bachelors,10,42,48,80,89,7.0,7,10,Urban,HR Executive,20287,0 +40038,Female,25,Bachelors,6,76,95,25,42,3.0,6,59,Urban,Data Analyst,76406,1 +40039,Male,39,Bachelors,18,92,74,99,65,1.0,3,27,Rural,ML Engineer,54832,1 +40040,Male,44,Bachelors,11,52,0,48,29,5.0,2,21,Urban,Data Analyst,121575,0 +40041,Male,40,Masters,5,96,60,7,12,6.0,4,52,Urban,Manager,28350,0 +40042,Female,26,Bachelors,7,54,27,40,4,1.0,2,5,Urban,ML Engineer,73868,0 +40043,Female,21,Diploma,16,99,74,0,88,4.0,0,86,Urban,ML Engineer,79625,1 +40044,Male,52,Bachelors,1,30,99,27,1,4.0,1,55,Urban,Manager,88284,0 +40045,Male,41,Bachelors,9,39,16,60,79,3.0,7,47,Urban,HR Executive,135100,0 +40046,Female,49,Bachelors,13,4,96,43,54,8.0,1,64,Rural,Software Engineer,54231,0 +40047,Male,28,Bachelors,11,29,27,24,82,9.0,1,96,Urban,Data Analyst,122144,0 +40048,Female,23,Bachelors,3,48,9,65,6,1.0,5,54,Urban,ML Engineer,100397,0 +40049,Female,35,Diploma,12,79,34,6,39,9.0,2,12,Rural,ML Engineer,122310,0 +40050,Male,28,High School,15,25,76,21,42,1.0,6,90,Rural,Manager,22119,0 +40051,Female,46,Bachelors,8,82,43,59,43,9.0,3,44,Semi-Urban,HR Executive,42000,0 +40052,Male,35,High School,5,10,87,23,57,5.0,1,43,Rural,Manager,56599,0 +40053,Other,37,Diploma,3,72,87,25,18,8.0,2,62,Urban,ML Engineer,80869,1 +40054,Male,21,High School,17,25,23,94,32,6.0,5,27,Urban,HR Executive,51830,0 +40055,Male,46,High School,19,27,84,3,41,6.0,1,99,Urban,ML Engineer,47059,0 +40056,Male,39,Masters,19,64,34,2,60,9.0,0,32,Semi-Urban,HR Executive,33237,0 +40057,Female,47,Bachelors,19,96,62,79,23,8.0,0,71,Urban,Software Engineer,118306,1 +40058,Male,58,Diploma,2,87,26,70,85,8.0,3,29,Urban,Manager,48596,0 +40059,Male,34,Bachelors,5,85,65,32,89,2.0,3,80,Urban,HR Executive,100645,1 +40060,Male,34,Masters,6,14,23,50,25,2.0,4,8,Rural,Software Engineer,104325,0 +40061,Male,29,Bachelors,7,31,38,25,44,8.0,1,89,Urban,ML Engineer,27945,0 +40062,Female,55,Bachelors,3,63,24,29,91,0.0,0,93,Urban,ML Engineer,71090,0 +40063,Male,47,Bachelors,7,99,6,67,55,7.0,1,37,Urban,ML Engineer,132326,0 +40064,Female,44,Bachelors,17,42,52,92,83,7.0,4,8,Rural,HR Executive,31742,0 +40065,Female,51,Masters,11,37,78,85,32,9.0,1,55,Urban,ML Engineer,133191,1 +40066,Female,27,Diploma,11,65,47,96,37,9.0,6,1,Rural,ML Engineer,72456,0 +40067,Female,48,Masters,11,30,31,60,15,3.0,1,2,Semi-Urban,Manager,25358,0 +40068,Male,34,Masters,5,55,24,97,36,7.0,1,79,Semi-Urban,HR Executive,132039,1 +40069,Male,34,Bachelors,7,88,88,7,1,5.0,4,58,Urban,ML Engineer,70405,1 +40070,Other,50,Bachelors,14,51,66,41,38,4.0,5,26,Urban,Data Analyst,109007,0 +40071,Female,52,Bachelors,11,61,58,77,78,1.0,4,73,Semi-Urban,Data Analyst,50488,1 +40072,Male,31,Diploma,19,84,79,50,53,0.0,4,69,Semi-Urban,Software Engineer,40799,1 +40073,Female,40,Masters,19,58,9,21,17,0.0,3,19,Rural,ML Engineer,145877,0 +40074,Female,37,Bachelors,1,90,32,10,34,0.0,2,99,Urban,Software Engineer,138867,0 +40075,Female,38,Masters,18,51,87,12,24,1.0,1,6,Rural,Manager,82511,0 +40076,Female,21,High School,8,60,87,63,27,6.0,4,49,Urban,Data Analyst,25125,1 +40077,Female,53,High School,3,8,56,21,20,6.0,6,99,Semi-Urban,Manager,88619,0 +40078,Female,29,High School,19,98,30,49,7,4.0,6,9,Rural,ML Engineer,73434,0 +40079,Male,31,Bachelors,15,3,3,26,41,1.0,3,4,Semi-Urban,ML Engineer,102299,0 +40080,Other,58,Diploma,4,22,99,73,89,3.0,5,13,Urban,Software Engineer,59024,0 +40081,Male,23,Bachelors,17,44,33,72,18,8.0,6,77,Urban,Manager,78726,0 +40082,Male,34,Masters,10,42,38,21,88,6.0,0,35,Urban,Software Engineer,92843,0 +40083,Female,24,High School,2,20,21,70,76,3.0,0,37,Semi-Urban,Data Analyst,113951,0 +40084,Female,43,Diploma,11,77,85,96,42,6.0,6,95,Rural,Data Analyst,117856,1 +40085,Female,32,Masters,15,9,94,46,78,4.0,6,89,Urban,Software Engineer,126760,0 +40086,Male,58,Bachelors,15,69,90,16,93,3.0,6,41,Urban,ML Engineer,142799,0 +40087,Male,51,Masters,9,9,80,34,14,9.0,4,65,Urban,Manager,138003,0 +40088,Male,46,Diploma,1,96,23,15,29,9.0,4,96,Urban,Manager,59510,0 +40089,Male,50,Diploma,9,48,22,53,48,2.0,6,59,Semi-Urban,Data Analyst,133698,0 +40090,Female,52,Diploma,3,56,68,78,7,0.0,1,18,Rural,ML Engineer,149513,0 +40091,Male,57,PhD,16,12,52,85,31,9.0,0,15,Rural,Manager,57690,0 +40092,Male,37,PhD,2,69,58,62,21,6.0,2,33,Urban,Data Analyst,120596,0 +40093,Male,39,Bachelors,2,14,47,68,99,1.0,5,17,Urban,Data Analyst,136318,0 +40094,Female,34,Bachelors,8,47,94,11,33,1.0,3,86,Urban,Data Analyst,117091,0 +40095,Male,24,High School,0,80,74,6,56,3.0,0,3,Urban,Manager,36035,0 +40096,Female,32,Diploma,10,75,21,45,82,4.0,4,95,Rural,Manager,136953,0 +40097,Male,27,Masters,0,68,97,65,29,6.0,1,98,Rural,Data Analyst,134906,1 +40098,Male,24,Diploma,16,35,30,44,48,7.0,5,48,Urban,Manager,36175,0 +40099,Female,56,Diploma,14,91,84,27,53,2.0,1,4,Urban,ML Engineer,118059,0 +40100,Male,24,Masters,13,55,39,73,85,7.0,5,33,Semi-Urban,HR Executive,140174,0 +40101,Male,21,Bachelors,10,72,71,45,89,2.0,1,9,Urban,HR Executive,25183,0 +40102,Female,41,High School,14,86,28,74,0,6.0,3,42,Urban,Data Analyst,131775,0 +40103,Female,53,Masters,0,73,75,74,68,7.0,2,73,Urban,Manager,62273,1 +40104,Female,56,Diploma,11,84,70,77,68,3.0,2,91,Semi-Urban,Software Engineer,78910,1 +40105,Female,22,Bachelors,16,5,66,50,92,2.0,7,88,Rural,Data Analyst,90970,0 +40106,Male,24,High School,15,77,38,50,47,8.0,4,76,Semi-Urban,Software Engineer,139668,1 +40107,Male,57,Bachelors,0,4,33,41,17,5.0,2,17,Urban,Software Engineer,66930,0 +40108,Male,29,Bachelors,4,1,3,1,80,8.0,5,78,Urban,ML Engineer,38634,0 +40109,Female,48,Bachelors,9,40,19,98,96,6.0,5,88,Semi-Urban,HR Executive,144055,1 +40110,Other,31,PhD,7,23,36,75,80,4.0,1,32,Rural,Manager,68769,0 +40111,Male,40,Bachelors,14,35,26,27,5,1.0,0,18,Urban,ML Engineer,40871,0 +40112,Male,33,Masters,8,48,52,75,27,6.0,5,49,Rural,Manager,103789,0 +40113,Male,22,Bachelors,12,49,33,39,54,6.0,3,53,Semi-Urban,Software Engineer,24155,0 +40114,Female,33,Diploma,8,23,92,1,30,5.0,3,71,Rural,HR Executive,68433,0 +40115,Male,23,Masters,14,63,50,17,96,2.0,6,43,Urban,Manager,59914,0 +40116,Female,21,Bachelors,0,39,88,31,79,4.0,6,62,Rural,HR Executive,145850,0 +40117,Female,39,Bachelors,16,81,1,42,54,9.0,1,68,Urban,Software Engineer,29433,0 +40118,Other,43,Diploma,7,43,21,22,19,3.0,3,11,Urban,ML Engineer,24013,0 +40119,Male,21,Bachelors,17,25,39,75,18,9.0,4,70,Rural,Software Engineer,84125,0 +40120,Other,50,Diploma,1,32,76,28,85,0.0,1,32,Urban,ML Engineer,90892,0 +40121,Female,51,High School,10,84,79,97,29,0.0,7,86,Urban,Manager,147207,1 +40122,Male,21,High School,4,89,56,55,9,9.0,4,43,Urban,Data Analyst,39162,1 +40123,Male,26,Bachelors,14,71,3,61,63,7.0,6,83,Urban,Manager,45688,0 +40124,Female,31,Masters,5,38,21,60,52,4.0,1,81,Semi-Urban,Software Engineer,36855,0 +40125,Other,25,High School,2,25,51,15,86,8.0,7,13,Semi-Urban,Data Analyst,22125,0 +40126,Male,40,Masters,8,47,90,96,21,3.0,0,45,Urban,Data Analyst,126000,1 +40127,Male,45,Diploma,15,57,3,56,32,7.0,4,82,Urban,Manager,94110,0 +40128,Male,44,Masters,16,17,1,9,49,1.0,6,46,Rural,Software Engineer,75215,0 +40129,Other,56,Bachelors,6,35,35,4,92,7.0,3,98,Urban,Data Analyst,81739,0 +40130,Other,46,Diploma,9,31,56,27,89,6.0,5,41,Rural,HR Executive,44088,0 +40131,Male,36,High School,10,85,48,12,45,5.0,1,59,Rural,ML Engineer,117520,0 +40132,Male,42,Bachelors,0,51,56,63,33,4.0,1,80,Urban,ML Engineer,75875,1 +40133,Female,30,Diploma,16,67,84,65,38,6.0,1,10,Urban,ML Engineer,58427,0 +40134,Female,32,Masters,5,60,88,17,20,1.0,7,63,Semi-Urban,Manager,142634,0 +40135,Other,49,Bachelors,1,80,70,10,29,5.0,5,1,Rural,ML Engineer,106721,0 +40136,Female,50,Diploma,7,16,84,1,46,8.0,1,98,Rural,Manager,93673,0 +40137,Male,32,Masters,5,80,59,92,9,9.0,0,86,Urban,Software Engineer,41413,1 +40138,Female,45,Diploma,19,31,20,45,40,4.0,4,76,Urban,Software Engineer,80323,0 +40139,Male,34,High School,2,11,75,89,12,0.0,4,24,Urban,ML Engineer,62744,0 +40140,Female,44,Bachelors,11,34,66,80,16,9.0,3,15,Urban,HR Executive,100404,0 +40141,Female,24,High School,14,83,17,21,24,6.0,6,52,Semi-Urban,Data Analyst,37687,0 +40142,Other,35,Bachelors,5,27,31,14,44,8.0,3,2,Urban,Data Analyst,137849,0 +40143,Other,56,Bachelors,19,69,93,39,60,2.0,4,64,Rural,Data Analyst,59048,1 +40144,Male,31,Diploma,9,9,61,65,87,0.0,6,82,Urban,ML Engineer,48630,0 +40145,Male,25,Bachelors,7,12,34,63,96,2.0,2,4,Urban,Software Engineer,84177,0 +40146,Male,27,Diploma,16,9,57,50,61,4.0,7,91,Rural,Manager,84351,0 +40147,Female,33,Bachelors,4,61,15,28,45,6.0,6,57,Rural,Data Analyst,140861,0 +40148,Female,47,PhD,14,45,89,66,24,2.0,7,70,Urban,Data Analyst,44394,1 +40149,Other,38,Bachelors,19,67,40,66,1,2.0,6,59,Rural,Data Analyst,60492,0 +40150,Female,49,High School,11,25,76,80,64,7.0,5,83,Semi-Urban,Manager,143555,1 +40151,Male,59,Bachelors,18,81,25,91,27,7.0,5,0,Urban,Software Engineer,38384,0 +40152,Male,59,Bachelors,12,98,61,98,59,5.0,3,45,Urban,Data Analyst,108681,1 +40153,Male,35,Diploma,3,28,97,7,24,5.0,6,25,Rural,Manager,53680,0 +40154,Female,22,Bachelors,12,83,33,8,86,6.0,4,79,Semi-Urban,Manager,30338,0 +40155,Female,37,Diploma,15,74,44,2,21,2.0,5,31,Rural,HR Executive,95201,0 +40156,Male,30,Masters,11,12,11,68,83,4.0,3,75,Rural,Manager,43071,0 +40157,Female,30,Diploma,10,23,85,81,62,7.0,5,50,Urban,Data Analyst,86628,0 +40158,Male,23,Bachelors,6,69,82,4,57,3.0,0,11,Rural,ML Engineer,119739,0 +40159,Male,45,Diploma,11,26,37,93,57,3.0,0,78,Rural,Manager,141842,0 +40160,Male,50,Bachelors,12,59,75,83,56,4.0,2,76,Urban,ML Engineer,144476,1 +40161,Male,30,Bachelors,12,35,35,68,56,7.0,3,0,Rural,Data Analyst,98980,0 +40162,Female,32,Bachelors,17,32,76,27,63,2.0,2,91,Urban,HR Executive,107225,0 +40163,Male,40,High School,9,12,16,80,95,0.0,1,3,Urban,Manager,46366,0 +40164,Male,45,Bachelors,5,97,97,87,37,0.0,0,20,Urban,HR Executive,139737,1 +40165,Female,36,High School,7,59,92,77,3,7.0,3,49,Rural,Manager,130520,1 +40166,Other,32,Bachelors,18,77,82,95,54,7.0,7,32,Semi-Urban,ML Engineer,120499,1 +40167,Female,31,Masters,8,29,50,94,94,7.0,0,6,Rural,Manager,132491,0 +40168,Male,56,High School,7,21,76,7,8,2.0,1,45,Urban,Data Analyst,123680,0 +40169,Male,50,Diploma,10,23,12,58,8,6.0,1,92,Semi-Urban,ML Engineer,140009,0 +40170,Male,40,High School,16,48,33,10,29,4.0,7,85,Urban,ML Engineer,144862,0 +40171,Male,21,Bachelors,15,31,48,99,61,3.0,2,3,Semi-Urban,HR Executive,68425,0 +40172,Female,29,Masters,11,26,11,23,20,5.0,5,6,Rural,ML Engineer,120285,0 +40173,Male,32,Masters,5,31,67,31,36,8.0,2,93,Urban,HR Executive,45510,0 +40174,Male,45,Bachelors,15,10,79,24,69,9.0,6,27,Rural,Data Analyst,123995,0 +40175,Female,23,Masters,14,32,57,66,50,2.0,0,19,Semi-Urban,ML Engineer,55868,0 +40176,Female,39,Diploma,5,95,32,21,17,8.0,0,45,Rural,Data Analyst,129415,0 +40177,Male,32,Masters,11,41,89,11,31,9.0,0,93,Urban,HR Executive,41552,0 +40178,Male,39,Diploma,16,81,41,28,53,2.0,0,43,Rural,HR Executive,29803,0 +40179,Male,42,Bachelors,5,20,45,81,11,6.0,1,10,Urban,Data Analyst,127874,0 +40180,Male,23,Bachelors,8,3,60,35,52,9.0,4,85,Rural,Manager,72940,0 +40181,Male,39,Masters,15,38,23,47,79,7.0,5,15,Semi-Urban,Manager,133263,0 +40182,Male,54,PhD,1,37,83,20,93,2.0,5,90,Urban,Data Analyst,21085,0 +40183,Male,40,Bachelors,19,81,47,64,67,8.0,4,3,Urban,HR Executive,69670,0 +40184,Male,49,Bachelors,6,55,48,26,80,7.0,3,97,Urban,Data Analyst,23294,0 +40185,Male,45,Diploma,8,70,48,30,57,7.0,0,20,Urban,Software Engineer,47865,0 +40186,Other,55,Bachelors,4,1,38,84,49,7.0,4,86,Urban,Manager,91559,0 +40187,Male,32,Masters,15,99,59,92,53,9.0,4,41,Urban,Manager,73780,1 +40188,Female,23,High School,1,56,68,24,0,4.0,6,96,Semi-Urban,ML Engineer,98261,1 +40189,Male,50,Bachelors,17,98,58,35,51,7.0,0,20,Semi-Urban,HR Executive,61403,0 +40190,Female,25,High School,13,84,27,84,55,0.0,4,17,Rural,Data Analyst,149021,0 +40191,Male,22,Diploma,4,73,48,29,45,6.0,4,42,Semi-Urban,HR Executive,143724,0 +40192,Male,50,Bachelors,6,62,9,53,93,7.0,4,42,Rural,Manager,31584,0 +40193,Female,30,Diploma,11,61,67,20,62,0.0,5,26,Urban,Data Analyst,66457,0 +40194,Female,50,Bachelors,11,62,32,91,45,8.0,0,46,Urban,ML Engineer,131638,0 +40195,Other,53,Bachelors,19,14,29,3,93,9.0,5,20,Semi-Urban,ML Engineer,22869,0 +40196,Female,57,Masters,10,4,19,86,72,7.0,2,2,Semi-Urban,Software Engineer,128079,0 +40197,Male,28,Diploma,9,84,78,41,80,8.0,2,33,Semi-Urban,Manager,35519,1 +40198,Male,25,Bachelors,2,63,22,50,18,2.0,2,21,Rural,Manager,144222,0 +40199,Male,52,High School,14,45,90,68,19,0.0,0,87,Urban,Software Engineer,22819,1 +40200,Male,46,PhD,13,75,41,45,23,9.0,0,37,Urban,Software Engineer,138491,0 +40201,Female,29,Bachelors,3,64,56,32,53,6.0,6,44,Rural,ML Engineer,119052,0 +40202,Male,37,Bachelors,9,6,5,20,4,7.0,1,68,Urban,Manager,117761,0 +40203,Female,48,Bachelors,2,23,32,6,10,0.0,7,56,Urban,ML Engineer,133562,0 +40204,Male,30,Bachelors,13,85,18,87,42,1.0,3,76,Urban,ML Engineer,98294,1 +40205,Male,46,High School,7,16,6,97,35,6.0,0,44,Urban,HR Executive,93143,0 +40206,Male,43,Masters,2,47,97,24,54,2.0,3,36,Urban,Data Analyst,144257,0 +40207,Male,34,Masters,4,61,10,89,25,3.0,0,64,Urban,ML Engineer,98894,0 +40208,Female,23,High School,13,28,71,36,48,9.0,0,21,Rural,Data Analyst,30350,0 +40209,Other,50,High School,12,22,58,78,35,7.0,6,58,Urban,HR Executive,119057,0 +40210,Male,42,Bachelors,2,37,53,90,62,6.0,3,44,Rural,Data Analyst,144125,0 +40211,Female,23,Diploma,6,13,26,67,78,9.0,6,70,Semi-Urban,Data Analyst,89158,0 +40212,Female,39,PhD,12,25,61,50,37,7.0,5,73,Urban,Data Analyst,75809,0 +40213,Other,54,Masters,10,82,21,23,91,7.0,5,1,Urban,Data Analyst,132666,0 +40214,Male,33,Diploma,14,45,82,37,60,3.0,3,50,Urban,Data Analyst,74571,0 +40215,Male,23,High School,7,78,19,21,3,9.0,5,29,Urban,Data Analyst,92603,0 +40216,Male,28,Bachelors,16,33,46,5,21,4.0,6,80,Urban,HR Executive,30234,0 +40217,Male,56,High School,0,29,43,82,31,0.0,6,33,Rural,Software Engineer,114398,0 +40218,Male,27,Diploma,14,99,58,59,84,8.0,4,12,Urban,ML Engineer,146560,0 +40219,Male,27,High School,10,11,50,22,6,2.0,7,64,Semi-Urban,Data Analyst,36083,0 +40220,Female,24,Masters,0,51,92,25,79,3.0,5,52,Urban,Data Analyst,46206,0 +40221,Male,24,Bachelors,11,66,16,39,50,0.0,3,66,Semi-Urban,HR Executive,107297,0 +40222,Female,38,Bachelors,4,74,58,13,69,6.0,6,88,Urban,Data Analyst,148221,0 +40223,Female,56,Bachelors,8,37,87,31,44,0.0,3,14,Urban,Manager,73271,0 +40224,Female,24,Masters,7,15,15,3,57,5.0,2,97,Semi-Urban,HR Executive,41171,0 +40225,Male,43,Masters,19,31,66,39,47,6.0,7,50,Urban,HR Executive,83557,0 +40226,Male,51,High School,13,23,79,10,92,9.0,6,63,Semi-Urban,HR Executive,22159,0 +40227,Male,52,Bachelors,11,42,42,44,52,0.0,5,94,Rural,Manager,132072,0 +40228,Male,48,High School,1,70,38,7,45,1.0,2,9,Urban,ML Engineer,81386,0 +40229,Female,52,Bachelors,1,80,76,21,1,4.0,3,40,Urban,Software Engineer,100797,0 +40230,Male,57,Bachelors,13,56,41,13,54,2.0,3,28,Urban,Data Analyst,125430,0 +40231,Male,24,Bachelors,17,15,54,22,5,8.0,4,41,Urban,Software Engineer,42401,0 +40232,Male,36,High School,4,74,35,67,37,0.0,2,16,Urban,Manager,86024,0 +40233,Male,29,High School,16,73,60,83,57,4.0,2,89,Urban,Manager,142328,1 +40234,Other,42,Diploma,3,4,74,82,92,9.0,6,43,Semi-Urban,ML Engineer,95915,0 +40235,Other,46,High School,0,61,99,62,67,3.0,2,3,Urban,ML Engineer,95077,0 +40236,Male,22,Bachelors,9,84,23,22,21,0.0,6,37,Urban,Data Analyst,21574,0 +40237,Male,31,High School,1,31,7,1,72,3.0,1,76,Urban,HR Executive,113002,0 +40238,Female,35,Bachelors,8,68,41,42,24,8.0,2,89,Semi-Urban,Manager,28591,0 +40239,Female,57,PhD,5,12,5,72,77,1.0,4,34,Urban,ML Engineer,132639,0 +40240,Female,48,Bachelors,8,68,57,93,0,9.0,4,59,Semi-Urban,Manager,60294,1 +40241,Male,40,Bachelors,13,68,93,49,82,4.0,0,73,Urban,Manager,73232,1 +40242,Male,23,Bachelors,16,99,19,48,31,7.0,6,30,Semi-Urban,Manager,62600,0 +40243,Male,25,Bachelors,1,64,92,94,27,0.0,1,42,Urban,ML Engineer,37225,1 +40244,Female,45,Bachelors,1,30,66,98,2,6.0,0,40,Urban,Manager,115884,0 +40245,Female,57,Masters,16,5,41,66,76,1.0,5,86,Semi-Urban,Data Analyst,143961,0 +40246,Male,24,Masters,15,54,20,86,16,0.0,6,30,Rural,Data Analyst,124338,0 +40247,Male,32,Bachelors,8,51,92,87,59,5.0,5,72,Semi-Urban,HR Executive,136182,1 +40248,Female,48,Diploma,12,89,44,11,58,6.0,2,73,Urban,ML Engineer,109294,0 +40249,Female,25,Masters,1,40,70,22,87,8.0,6,14,Urban,Software Engineer,142683,0 +40250,Female,59,Bachelors,2,22,92,19,7,0.0,1,21,Rural,ML Engineer,28543,0 +40251,Female,42,High School,5,64,65,91,15,8.0,0,17,Rural,HR Executive,27971,0 +40252,Male,35,High School,6,4,46,8,89,0.0,6,25,Rural,Manager,61561,0 +40253,Male,40,Bachelors,3,8,75,70,36,7.0,7,30,Urban,Data Analyst,96116,0 +40254,Female,30,Bachelors,9,75,14,21,69,0.0,7,54,Urban,Data Analyst,84266,0 +40255,Female,56,Masters,3,19,27,71,5,7.0,5,85,Semi-Urban,ML Engineer,129588,0 +40256,Male,42,PhD,13,63,13,22,62,6.0,7,26,Semi-Urban,Manager,52918,0 +40257,Male,27,PhD,0,20,14,82,28,6.0,1,86,Rural,Manager,108305,0 +40258,Female,57,Bachelors,15,45,67,92,20,2.0,6,11,Semi-Urban,HR Executive,56424,0 +40259,Male,26,Bachelors,7,93,81,6,53,9.0,3,86,Semi-Urban,ML Engineer,60091,1 +40260,Male,44,Masters,19,65,68,32,2,2.0,7,56,Rural,Software Engineer,123692,0 +40261,Female,54,Diploma,10,8,28,54,23,4.0,1,42,Semi-Urban,Data Analyst,84935,0 +40262,Female,41,Masters,6,99,35,64,74,5.0,6,36,Semi-Urban,HR Executive,130460,0 +40263,Female,57,Bachelors,6,41,48,76,1,6.0,3,79,Rural,Software Engineer,91386,1 +40264,Male,54,High School,18,24,87,65,4,2.0,0,90,Urban,Data Analyst,40153,1 +40265,Male,22,Masters,18,70,5,70,54,1.0,4,33,Semi-Urban,Data Analyst,93683,0 +40266,Male,33,Bachelors,18,55,41,18,81,3.0,0,21,Urban,ML Engineer,50402,0 +40267,Female,42,Bachelors,19,15,87,65,82,2.0,7,47,Semi-Urban,Data Analyst,46708,0 +40268,Female,52,Masters,11,83,74,59,4,5.0,2,74,Rural,ML Engineer,128788,1 +40269,Male,55,Diploma,12,32,14,70,35,8.0,2,28,Semi-Urban,Data Analyst,38079,0 +40270,Male,30,High School,13,45,23,69,42,6.0,1,96,Urban,Software Engineer,136425,0 +40271,Male,38,Diploma,11,53,54,65,8,6.0,4,74,Urban,HR Executive,84747,1 +40272,Male,42,Bachelors,19,69,98,67,52,9.0,7,47,Semi-Urban,Manager,46645,1 +40273,Male,57,Masters,11,43,95,69,32,5.0,7,79,Semi-Urban,Software Engineer,123657,1 +40274,Female,48,Bachelors,7,84,38,85,47,2.0,5,1,Semi-Urban,Data Analyst,72343,0 +40275,Female,32,Bachelors,12,90,68,58,34,2.0,3,91,Semi-Urban,HR Executive,73113,1 +40276,Female,36,Diploma,14,46,13,57,68,8.0,1,54,Urban,ML Engineer,142593,0 +40277,Female,58,Masters,19,22,11,45,99,2.0,3,10,Urban,ML Engineer,32635,0 +40278,Male,51,High School,10,91,59,69,69,0.0,3,90,Rural,Data Analyst,28402,1 +40279,Female,58,Bachelors,8,41,31,69,50,0.0,2,8,Rural,Software Engineer,51594,0 +40280,Male,31,Diploma,16,82,38,54,5,5.0,5,97,Urban,Manager,149430,1 +40281,Male,24,Diploma,3,55,3,87,11,2.0,2,30,Rural,HR Executive,146277,0 +40282,Male,27,High School,0,63,5,18,54,0.0,4,51,Semi-Urban,Data Analyst,98105,0 +40283,Male,27,Diploma,5,20,21,0,66,0.0,1,1,Urban,HR Executive,78934,0 +40284,Male,44,Diploma,19,84,84,50,25,3.0,7,75,Semi-Urban,HR Executive,130218,1 +40285,Male,33,Diploma,4,67,44,6,23,3.0,4,4,Rural,Data Analyst,32713,0 +40286,Male,37,PhD,1,23,21,77,77,9.0,1,57,Semi-Urban,Manager,142516,0 +40287,Female,54,PhD,15,85,4,27,65,3.0,1,73,Urban,ML Engineer,48706,0 +40288,Male,41,Masters,0,25,27,70,58,0.0,1,51,Rural,Manager,112083,0 +40289,Male,54,Bachelors,10,64,88,26,39,8.0,3,90,Urban,Data Analyst,20434,1 +40290,Female,29,Diploma,7,82,74,20,44,8.0,1,35,Urban,Manager,126795,0 +40291,Female,40,PhD,1,76,60,15,10,5.0,0,10,Urban,Manager,86150,0 +40292,Male,38,Bachelors,12,17,31,19,83,7.0,7,55,Semi-Urban,Software Engineer,118402,0 +40293,Male,30,Bachelors,14,48,88,43,91,2.0,5,58,Urban,Manager,34321,1 +40294,Female,43,Bachelors,0,23,18,97,73,0.0,7,60,Urban,Manager,51618,0 +40295,Male,50,Bachelors,16,89,94,47,87,2.0,5,8,Rural,Software Engineer,80436,1 +40296,Male,23,Bachelors,0,83,76,34,67,9.0,5,36,Rural,ML Engineer,23231,0 +40297,Male,58,Diploma,7,36,64,63,19,6.0,2,70,Semi-Urban,Manager,132776,0 +40298,Female,37,PhD,6,9,0,69,26,4.0,3,54,Urban,Data Analyst,110568,0 +40299,Male,39,PhD,5,7,94,48,92,8.0,5,77,Rural,ML Engineer,51217,0 +40300,Male,41,Diploma,5,95,16,76,73,6.0,5,65,Semi-Urban,HR Executive,138856,1 +40301,Male,42,Bachelors,2,45,60,40,53,6.0,4,0,Urban,Data Analyst,119135,0 +40302,Female,38,Bachelors,2,24,40,25,12,7.0,7,8,Urban,ML Engineer,71470,0 +40303,Female,35,Diploma,3,1,44,97,88,8.0,7,56,Semi-Urban,ML Engineer,22318,0 +40304,Female,24,Bachelors,0,43,11,85,9,8.0,1,38,Urban,Software Engineer,105787,0 +40305,Male,51,Diploma,19,65,94,18,17,3.0,2,45,Urban,Software Engineer,76274,0 +40306,Female,25,Bachelors,1,91,7,29,95,2.0,2,67,Rural,Data Analyst,125657,0 +40307,Male,46,High School,2,86,90,29,66,5.0,2,28,Urban,Software Engineer,22121,0 +40308,Male,44,Bachelors,11,38,32,65,86,9.0,5,79,Urban,Software Engineer,44936,0 +40309,Female,30,Bachelors,19,82,13,74,66,8.0,5,46,Urban,Manager,40041,0 +40310,Other,53,Bachelors,5,64,91,49,41,8.0,3,92,Urban,HR Executive,65766,1 +40311,Female,27,PhD,9,79,36,43,46,0.0,2,2,Semi-Urban,HR Executive,71081,0 +40312,Female,50,Bachelors,19,67,97,18,85,7.0,1,43,Rural,Data Analyst,29614,0 +40313,Male,22,Bachelors,1,86,81,64,4,7.0,7,84,Urban,Software Engineer,112419,1 +40314,Male,48,Masters,17,97,36,96,55,7.0,7,58,Urban,ML Engineer,130710,1 +40315,Male,44,Masters,18,68,65,98,75,3.0,4,53,Urban,Software Engineer,39724,1 +40316,Male,48,Bachelors,10,65,10,75,25,0.0,3,22,Semi-Urban,Software Engineer,44579,0 +40317,Female,47,Bachelors,10,45,97,11,68,0.0,4,5,Rural,ML Engineer,113896,0 +40318,Male,51,High School,9,83,72,29,24,1.0,1,36,Urban,HR Executive,26686,0 +40319,Female,34,High School,4,54,1,93,65,9.0,1,26,Urban,Manager,141260,0 +40320,Male,50,Diploma,7,10,75,52,73,9.0,1,34,Semi-Urban,HR Executive,56035,0 +40321,Male,52,Masters,14,74,20,89,39,1.0,4,1,Urban,ML Engineer,29044,0 +40322,Male,54,Masters,14,28,35,16,49,7.0,5,86,Rural,Manager,50569,0 +40323,Other,30,High School,19,21,15,87,0,7.0,0,52,Semi-Urban,Data Analyst,67444,0 +40324,Female,55,Bachelors,9,96,99,9,90,5.0,7,2,Rural,Data Analyst,93221,0 +40325,Female,59,Diploma,19,37,83,34,58,3.0,5,39,Semi-Urban,Data Analyst,36633,0 +40326,Female,57,High School,11,24,15,49,13,0.0,1,83,Rural,Manager,146586,0 +40327,Female,49,Diploma,10,89,37,36,69,7.0,0,68,Urban,Data Analyst,97168,0 +40328,Female,30,Diploma,19,88,62,18,69,7.0,1,93,Rural,ML Engineer,95515,1 +40329,Male,36,PhD,12,72,68,92,83,6.0,7,33,Semi-Urban,HR Executive,145609,1 +40330,Male,31,Bachelors,5,14,65,28,43,5.0,5,64,Urban,Data Analyst,109538,0 +40331,Male,52,Masters,12,47,6,8,53,0.0,2,87,Urban,Manager,68733,0 +40332,Other,53,Bachelors,2,37,72,78,65,1.0,6,48,Rural,ML Engineer,130654,0 +40333,Other,31,Bachelors,4,47,51,12,0,2.0,4,46,Urban,ML Engineer,148330,0 +40334,Female,56,Bachelors,11,1,91,91,43,1.0,1,78,Urban,Data Analyst,135598,1 +40335,Male,21,Masters,0,54,77,38,74,8.0,7,96,Semi-Urban,Manager,112151,1 +40336,Male,29,PhD,6,77,90,34,57,7.0,3,78,Urban,HR Executive,37372,1 +40337,Male,21,High School,15,45,2,30,95,5.0,5,41,Rural,Manager,90998,0 +40338,Male,56,High School,2,3,74,76,58,6.0,1,70,Rural,Data Analyst,100832,0 +40339,Male,47,Bachelors,7,81,38,61,65,5.0,0,41,Semi-Urban,Manager,106038,0 +40340,Male,29,Diploma,7,39,72,38,99,7.0,3,24,Rural,Software Engineer,93054,0 +40341,Other,46,Bachelors,0,17,70,9,31,5.0,2,49,Rural,Software Engineer,98407,0 +40342,Male,48,Diploma,6,48,60,10,97,1.0,1,25,Urban,Software Engineer,138781,0 +40343,Female,58,Masters,9,66,96,46,47,5.0,4,70,Rural,HR Executive,116183,1 +40344,Female,29,High School,18,57,75,72,79,1.0,3,57,Rural,Software Engineer,29813,1 +40345,Male,34,Bachelors,6,54,22,81,40,0.0,0,8,Urban,HR Executive,42949,0 +40346,Male,49,Bachelors,17,40,62,10,6,1.0,3,67,Semi-Urban,Software Engineer,82492,0 +40347,Other,25,Bachelors,7,72,96,25,61,6.0,4,57,Rural,Data Analyst,29937,1 +40348,Female,25,High School,0,69,35,73,33,7.0,7,26,Urban,Software Engineer,133033,0 +40349,Male,46,Bachelors,17,63,48,76,22,0.0,2,28,Urban,HR Executive,86357,0 +40350,Male,33,Bachelors,14,22,87,66,83,1.0,2,60,Rural,Software Engineer,24699,1 +40351,Female,51,Diploma,3,44,30,47,77,2.0,0,1,Urban,ML Engineer,126870,0 +40352,Male,54,High School,13,78,79,69,56,8.0,1,24,Urban,ML Engineer,108986,1 +40353,Male,54,Diploma,9,65,32,45,50,6.0,1,29,Semi-Urban,Manager,33151,0 +40354,Female,39,Bachelors,15,42,11,92,63,0.0,5,31,Urban,Software Engineer,148123,0 +40355,Female,43,Bachelors,5,20,91,56,47,4.0,1,57,Rural,ML Engineer,22316,0 +40356,Male,43,Masters,14,24,35,44,0,8.0,2,23,Semi-Urban,Software Engineer,111048,0 +40357,Female,22,Masters,9,87,45,57,58,7.0,5,13,Urban,ML Engineer,21479,0 +40358,Female,56,Diploma,6,57,72,95,61,6.0,4,18,Semi-Urban,Manager,110093,1 +40359,Female,23,Diploma,7,36,4,38,85,3.0,3,47,Urban,ML Engineer,69211,0 +40360,Male,39,Bachelors,10,23,13,23,90,4.0,0,39,Urban,HR Executive,132517,0 +40361,Male,50,Bachelors,18,51,49,51,41,2.0,7,39,Semi-Urban,Data Analyst,107658,0 +40362,Male,59,Bachelors,5,11,64,56,69,5.0,4,56,Urban,Manager,89690,0 +40363,Male,29,Bachelors,3,26,58,16,96,1.0,3,36,Rural,Manager,21050,0 +40364,Other,52,Bachelors,14,64,99,67,17,3.0,5,28,Urban,ML Engineer,97746,1 +40365,Other,38,Bachelors,12,81,16,10,3,7.0,4,46,Urban,Data Analyst,94673,0 +40366,Female,58,Bachelors,0,42,49,16,17,3.0,2,70,Urban,Manager,84841,0 +40367,Male,44,Bachelors,3,51,27,91,71,8.0,7,13,Urban,Data Analyst,74605,0 +40368,Female,38,Bachelors,1,86,98,14,60,9.0,7,77,Urban,Data Analyst,76297,1 +40369,Male,24,Masters,2,48,24,34,18,0.0,5,24,Semi-Urban,HR Executive,61223,0 +40370,Male,26,Masters,3,13,89,99,85,7.0,6,17,Urban,ML Engineer,106241,0 +40371,Male,56,High School,10,85,16,3,60,5.0,1,96,Semi-Urban,Manager,21259,0 +40372,Male,46,High School,0,50,25,7,67,4.0,1,17,Urban,Data Analyst,145318,0 +40373,Male,29,PhD,13,2,10,93,52,7.0,2,6,Rural,HR Executive,67486,0 +40374,Male,58,High School,13,47,73,7,89,8.0,6,44,Urban,Data Analyst,132271,0 +40375,Male,21,Bachelors,18,13,24,36,63,3.0,0,98,Urban,Manager,103159,0 +40376,Female,43,High School,5,12,8,90,29,8.0,1,28,Urban,Manager,39250,0 +40377,Male,29,Masters,17,36,5,90,74,4.0,6,3,Semi-Urban,HR Executive,69776,0 +40378,Female,48,Masters,12,7,2,61,49,3.0,6,91,Urban,Data Analyst,29295,0 +40379,Male,34,High School,16,18,59,69,36,4.0,0,92,Rural,ML Engineer,112743,1 +40380,Male,42,Masters,5,67,75,4,26,1.0,7,62,Urban,Manager,62419,0 +40381,Female,25,PhD,9,25,26,10,6,1.0,4,45,Rural,ML Engineer,61986,0 +40382,Male,35,Diploma,8,6,11,63,83,1.0,6,49,Semi-Urban,Software Engineer,52642,0 +40383,Male,35,Bachelors,18,40,75,29,29,7.0,0,31,Urban,Software Engineer,106625,0 +40384,Female,55,High School,13,19,12,38,63,4.0,5,82,Semi-Urban,ML Engineer,28940,0 +40385,Male,51,Masters,6,33,67,60,43,4.0,4,52,Urban,ML Engineer,50240,0 +40386,Female,45,Masters,10,98,44,98,10,1.0,6,55,Urban,ML Engineer,77674,1 +40387,Male,30,Masters,8,36,65,17,41,6.0,0,18,Rural,HR Executive,102777,0 +40388,Male,58,Bachelors,19,21,37,29,82,5.0,3,63,Rural,ML Engineer,102345,0 +40389,Female,55,Diploma,12,19,72,11,36,7.0,4,63,Semi-Urban,ML Engineer,134986,0 +40390,Male,55,Bachelors,6,82,42,9,68,3.0,2,33,Urban,Manager,68575,0 +40391,Male,26,Masters,14,98,10,95,28,0.0,6,65,Rural,HR Executive,32124,1 +40392,Male,37,High School,16,38,76,56,73,5.0,4,39,Urban,Software Engineer,34133,0 +40393,Male,28,High School,14,88,52,17,76,6.0,5,28,Rural,Software Engineer,46432,0 +40394,Female,57,Diploma,5,29,63,40,52,0.0,0,21,Semi-Urban,Manager,105375,0 +40395,Female,51,PhD,3,13,78,55,29,9.0,5,2,Urban,Software Engineer,131426,0 +40396,Female,27,Bachelors,14,63,4,50,82,2.0,0,90,Urban,ML Engineer,36568,0 +40397,Male,54,Bachelors,10,15,50,42,9,4.0,5,78,Semi-Urban,HR Executive,71796,0 +40398,Female,37,Masters,8,18,78,52,38,2.0,1,57,Urban,Manager,144193,0 +40399,Male,57,Masters,9,42,88,82,5,1.0,2,21,Rural,Software Engineer,74697,0 +40400,Female,26,High School,6,7,48,94,97,8.0,5,34,Rural,HR Executive,63382,0 +40401,Female,33,Masters,1,57,40,46,27,5.0,4,43,Semi-Urban,HR Executive,68776,0 +40402,Male,34,High School,17,97,97,69,20,9.0,7,89,Semi-Urban,Data Analyst,57398,1 +40403,Other,42,Diploma,2,90,53,61,68,3.0,6,94,Urban,Data Analyst,29333,1 +40404,Female,46,Masters,17,43,9,48,39,0.0,0,78,Rural,Manager,59126,0 +40405,Female,28,Bachelors,12,19,4,63,60,3.0,4,31,Urban,Manager,39260,0 +40406,Female,57,Masters,9,52,77,40,1,7.0,5,57,Urban,HR Executive,59452,0 +40407,Female,32,Bachelors,0,56,13,23,71,5.0,4,40,Semi-Urban,Software Engineer,130747,0 +40408,Other,31,Masters,14,92,25,8,19,6.0,2,75,Urban,Software Engineer,92638,0 +40409,Female,29,Diploma,9,89,0,20,42,2.0,2,40,Urban,ML Engineer,77353,0 +40410,Male,53,Bachelors,18,48,94,70,1,1.0,1,0,Rural,Data Analyst,74946,0 +40411,Female,39,Diploma,15,53,34,64,10,1.0,6,59,Urban,Software Engineer,77844,0 +40412,Male,30,Masters,19,75,27,60,5,6.0,4,17,Urban,HR Executive,132463,0 +40413,Other,58,Bachelors,14,95,82,71,86,3.0,2,25,Rural,Manager,80830,1 +40414,Female,23,Bachelors,9,43,89,22,63,8.0,3,59,Rural,Data Analyst,83942,0 +40415,Male,54,Bachelors,19,50,29,54,32,4.0,7,94,Semi-Urban,ML Engineer,40696,0 +40416,Female,52,Diploma,9,14,62,86,43,9.0,0,32,Urban,HR Executive,82458,0 +40417,Female,51,High School,19,50,26,61,0,2.0,3,71,Urban,Manager,77618,0 +40418,Male,45,High School,19,51,42,36,78,2.0,4,56,Urban,Software Engineer,26763,0 +40419,Male,51,Diploma,15,4,57,21,75,4.0,2,79,Urban,Manager,64557,0 +40420,Male,47,Diploma,19,32,16,13,39,7.0,5,82,Urban,Manager,121597,0 +40421,Female,53,Diploma,18,41,0,30,38,0.0,4,61,Urban,Data Analyst,134501,0 +40422,Male,35,Diploma,4,21,43,64,25,4.0,7,41,Urban,Manager,37982,0 +40423,Female,56,Masters,1,17,65,21,29,4.0,1,39,Rural,ML Engineer,142979,0 +40424,Male,59,Bachelors,8,19,7,12,94,7.0,2,82,Semi-Urban,HR Executive,104071,0 +40425,Male,41,Diploma,9,59,10,70,6,8.0,3,2,Urban,Manager,100709,0 +40426,Male,54,Bachelors,11,48,20,76,52,6.0,3,93,Semi-Urban,Data Analyst,54021,1 +40427,Male,39,Bachelors,2,30,7,12,73,9.0,4,78,Urban,ML Engineer,86677,0 +40428,Male,28,PhD,17,27,25,3,4,0.0,0,99,Urban,ML Engineer,108154,0 +40429,Male,38,High School,12,70,54,89,14,0.0,3,90,Urban,HR Executive,101122,1 +40430,Female,32,Masters,2,19,34,91,60,4.0,6,91,Urban,ML Engineer,23114,0 +40431,Male,42,Masters,7,38,78,14,5,5.0,1,66,Urban,Data Analyst,75600,0 +40432,Female,33,Bachelors,12,45,9,31,30,5.0,6,36,Rural,HR Executive,107517,0 +40433,Male,32,High School,11,88,99,24,16,4.0,4,31,Rural,Manager,70846,1 +40434,Male,23,Bachelors,5,38,32,11,81,2.0,2,65,Semi-Urban,HR Executive,21289,0 +40435,Male,42,Bachelors,9,29,29,24,66,8.0,0,68,Urban,Manager,117744,0 +40436,Female,58,Diploma,6,93,19,43,26,3.0,7,34,Urban,Software Engineer,55274,0 +40437,Male,34,PhD,1,95,70,77,47,6.0,7,14,Urban,Software Engineer,87552,1 +40438,Male,56,Masters,10,23,31,24,58,6.0,7,27,Rural,Manager,29832,0 +40439,Other,29,Masters,15,11,26,70,31,5.0,6,82,Semi-Urban,Software Engineer,51657,0 +40440,Female,24,Bachelors,1,34,61,72,5,0.0,4,37,Urban,HR Executive,139039,0 +40441,Male,21,Diploma,19,72,35,46,61,1.0,2,76,Urban,ML Engineer,80306,0 +40442,Female,24,Diploma,4,27,95,42,97,8.0,2,28,Urban,Software Engineer,34044,0 +40443,Female,36,Bachelors,14,63,83,84,99,8.0,3,98,Urban,ML Engineer,136362,1 +40444,Female,47,Diploma,16,91,23,21,33,9.0,2,61,Urban,ML Engineer,74763,0 +40445,Male,42,PhD,7,43,20,28,84,4.0,4,29,Urban,ML Engineer,95846,0 +40446,Male,22,Diploma,6,74,51,36,80,2.0,7,98,Semi-Urban,Software Engineer,77445,1 +40447,Female,45,Bachelors,2,19,46,74,99,8.0,4,14,Rural,Software Engineer,130958,0 +40448,Male,36,Bachelors,14,63,66,2,94,3.0,1,52,Urban,HR Executive,88601,0 +40449,Female,54,Bachelors,11,89,21,58,97,0.0,7,80,Urban,ML Engineer,105511,1 +40450,Male,48,Masters,3,93,5,49,60,7.0,3,10,Urban,ML Engineer,48460,0 +40451,Male,42,Diploma,12,93,56,81,12,6.0,1,60,Urban,Data Analyst,128076,1 +40452,Female,30,Bachelors,9,95,39,81,46,4.0,5,22,Rural,Manager,43752,0 +40453,Male,24,Bachelors,8,4,51,35,14,3.0,3,88,Semi-Urban,Software Engineer,136718,0 +40454,Male,32,High School,0,15,91,57,77,8.0,0,39,Rural,ML Engineer,123009,0 +40455,Female,56,Bachelors,11,34,73,13,59,8.0,3,88,Urban,HR Executive,43064,0 +40456,Male,42,Bachelors,8,9,57,66,53,1.0,2,31,Urban,Data Analyst,45677,0 +40457,Female,46,Bachelors,16,56,49,55,11,5.0,5,32,Rural,ML Engineer,114715,0 +40458,Male,39,Bachelors,3,65,66,82,86,4.0,6,97,Urban,ML Engineer,109809,1 +40459,Male,51,PhD,16,29,29,41,91,5.0,5,0,Semi-Urban,Data Analyst,67586,0 +40460,Male,37,Masters,14,72,28,23,18,2.0,4,89,Urban,ML Engineer,77399,0 +40461,Female,55,Diploma,4,87,76,15,38,7.0,2,15,Semi-Urban,HR Executive,35900,0 +40462,Male,55,Diploma,4,31,40,42,80,3.0,6,52,Urban,ML Engineer,89528,0 +40463,Male,58,Bachelors,0,17,41,30,0,7.0,1,68,Semi-Urban,ML Engineer,148340,0 +40464,Female,33,Bachelors,1,75,6,69,53,9.0,7,72,Rural,Data Analyst,32669,0 +40465,Female,52,Bachelors,0,76,66,76,34,9.0,1,30,Urban,Data Analyst,63382,1 +40466,Female,22,Bachelors,6,83,37,87,38,4.0,4,77,Semi-Urban,HR Executive,145743,1 +40467,Male,38,PhD,6,13,83,25,96,3.0,5,75,Semi-Urban,Manager,20478,0 +40468,Male,52,High School,1,3,14,76,18,2.0,2,8,Urban,ML Engineer,34686,0 +40469,Female,21,Masters,2,45,61,27,13,8.0,3,45,Semi-Urban,Manager,122125,0 +40470,Female,51,Bachelors,14,89,59,82,29,0.0,3,15,Rural,Software Engineer,148224,1 +40471,Female,56,Bachelors,3,89,82,17,3,1.0,6,41,Rural,Software Engineer,55650,0 +40472,Female,38,Diploma,17,12,17,41,36,3.0,7,61,Urban,Data Analyst,147567,0 +40473,Female,54,Masters,6,44,68,71,74,0.0,7,74,Rural,HR Executive,68285,1 +40474,Male,54,High School,16,66,41,68,30,0.0,4,62,Urban,Manager,141985,1 +40475,Female,21,High School,16,12,18,72,34,0.0,2,15,Semi-Urban,Manager,127395,0 +40476,Female,56,Diploma,18,13,15,26,43,9.0,3,78,Rural,ML Engineer,39779,0 +40477,Female,53,Masters,8,1,72,14,33,5.0,0,55,Urban,ML Engineer,102591,0 +40478,Female,31,Bachelors,2,68,65,32,20,1.0,2,18,Urban,Software Engineer,70864,0 +40479,Male,52,Diploma,9,20,69,21,75,7.0,6,99,Rural,ML Engineer,126931,0 +40480,Female,41,Diploma,13,21,73,26,2,6.0,4,32,Semi-Urban,Manager,64422,0 +40481,Male,57,PhD,4,3,15,57,42,4.0,0,37,Rural,ML Engineer,118955,0 +40482,Male,39,Diploma,1,22,5,38,13,0.0,2,27,Urban,HR Executive,78854,0 +40483,Male,43,High School,7,3,21,89,48,3.0,1,29,Urban,ML Engineer,136114,0 +40484,Other,36,Bachelors,14,4,2,60,82,7.0,3,77,Urban,HR Executive,147243,0 +40485,Female,50,Bachelors,12,83,38,80,99,5.0,1,49,Semi-Urban,Software Engineer,61513,1 +40486,Female,51,Masters,0,27,79,88,82,4.0,6,50,Rural,Data Analyst,20036,1 +40487,Male,22,Bachelors,8,30,69,54,80,2.0,2,65,Urban,Data Analyst,123313,0 +40488,Male,38,Diploma,4,21,39,52,64,6.0,3,53,Semi-Urban,HR Executive,41635,0 +40489,Female,29,Diploma,16,50,59,85,38,0.0,0,34,Semi-Urban,ML Engineer,46234,0 +40490,Male,34,Bachelors,0,75,98,22,64,3.0,7,55,Urban,ML Engineer,79383,1 +40491,Male,27,Diploma,16,43,31,51,29,1.0,0,65,Urban,HR Executive,124805,0 +40492,Female,45,Masters,9,97,48,29,22,2.0,5,74,Urban,Software Engineer,143831,1 +40493,Male,30,Bachelors,0,51,65,86,83,1.0,4,17,Urban,ML Engineer,77073,0 +40494,Male,24,Bachelors,7,55,5,42,91,4.0,3,75,Semi-Urban,Data Analyst,108559,0 +40495,Male,55,Diploma,7,11,16,26,40,9.0,4,39,Semi-Urban,Manager,106914,0 +40496,Female,49,Masters,2,28,62,94,37,5.0,7,46,Urban,Software Engineer,22934,0 +40497,Female,33,Bachelors,4,33,88,66,58,4.0,0,54,Rural,Data Analyst,30774,1 +40498,Other,35,Bachelors,17,23,75,8,71,5.0,7,88,Urban,HR Executive,127027,0 +40499,Female,34,Diploma,6,50,23,75,55,7.0,0,39,Semi-Urban,Manager,56368,0 +40500,Male,42,PhD,10,5,70,84,56,1.0,5,23,Semi-Urban,Software Engineer,75739,0 +40501,Female,29,Bachelors,3,69,60,88,47,9.0,3,96,Urban,ML Engineer,114386,1 +40502,Male,45,PhD,14,2,56,62,37,9.0,1,95,Urban,ML Engineer,56510,0 +40503,Male,23,Masters,14,17,67,75,98,4.0,3,2,Urban,Manager,138474,0 +40504,Male,29,Diploma,5,8,10,20,68,9.0,6,77,Urban,HR Executive,47185,0 +40505,Female,47,Bachelors,7,36,71,32,27,7.0,4,33,Urban,Software Engineer,93104,0 +40506,Female,38,Bachelors,16,74,39,97,15,7.0,5,91,Urban,Data Analyst,112749,1 +40507,Male,39,Diploma,8,47,4,49,87,4.0,0,17,Urban,HR Executive,48541,0 +40508,Male,23,Bachelors,7,3,35,9,11,4.0,0,36,Urban,ML Engineer,35059,0 +40509,Female,49,Diploma,10,16,26,54,10,3.0,3,70,Urban,HR Executive,41744,0 +40510,Male,35,Diploma,11,50,54,57,58,9.0,0,93,Urban,Manager,127783,1 +40511,Female,56,Bachelors,10,4,45,77,95,5.0,4,74,Semi-Urban,Software Engineer,87995,0 +40512,Male,59,High School,1,62,91,95,97,9.0,3,26,Urban,Software Engineer,43769,1 +40513,Male,57,Bachelors,17,99,13,52,74,4.0,5,35,Urban,Manager,66666,0 +40514,Male,24,Bachelors,1,3,51,52,32,0.0,2,58,Semi-Urban,HR Executive,76400,0 +40515,Male,26,Bachelors,3,24,23,87,81,5.0,4,80,Urban,ML Engineer,36875,0 +40516,Female,57,Masters,16,75,49,25,2,0.0,0,31,Urban,ML Engineer,100517,0 +40517,Female,29,Bachelors,16,79,10,78,91,0.0,4,96,Urban,Software Engineer,94384,1 +40518,Male,37,PhD,19,26,84,3,43,6.0,7,31,Urban,Software Engineer,57244,0 +40519,Female,51,Diploma,10,49,97,93,93,9.0,6,88,Rural,Data Analyst,81184,1 +40520,Female,40,Bachelors,1,44,66,20,90,1.0,2,33,Semi-Urban,HR Executive,87181,0 +40521,Male,48,Masters,15,41,26,56,89,5.0,3,31,Urban,HR Executive,110120,0 +40522,Male,23,Masters,7,3,97,21,52,6.0,3,42,Rural,HR Executive,143634,0 +40523,Female,41,Bachelors,7,70,12,86,51,2.0,0,40,Semi-Urban,Manager,97787,0 +40524,Male,25,Diploma,2,40,95,69,3,5.0,6,7,Urban,Software Engineer,56242,0 +40525,Male,25,Masters,11,63,31,12,60,6.0,7,83,Urban,Manager,140764,0 +40526,Other,43,Diploma,4,42,25,29,92,2.0,7,82,Urban,ML Engineer,95395,0 +40527,Female,32,Diploma,1,90,43,90,94,1.0,1,63,Semi-Urban,ML Engineer,124848,1 +40528,Male,46,Masters,4,5,31,0,94,3.0,0,4,Semi-Urban,HR Executive,24059,0 +40529,Male,40,Bachelors,9,42,11,17,11,3.0,3,57,Semi-Urban,ML Engineer,115798,0 +40530,Male,22,Masters,15,72,86,59,60,5.0,1,63,Semi-Urban,ML Engineer,144414,1 +40531,Male,39,Bachelors,6,65,63,79,0,9.0,5,55,Urban,Data Analyst,142358,1 +40532,Male,25,Bachelors,2,71,6,87,11,1.0,0,7,Rural,Software Engineer,62574,0 +40533,Male,38,High School,11,11,99,10,3,3.0,2,96,Urban,ML Engineer,120477,0 +40534,Male,41,Bachelors,5,21,50,46,7,9.0,7,91,Urban,Manager,122290,0 +40535,Female,26,Diploma,12,38,35,74,46,5.0,7,34,Semi-Urban,ML Engineer,109574,0 +40536,Male,33,Bachelors,10,75,95,51,13,6.0,4,42,Urban,Manager,62682,1 +40537,Male,48,Diploma,2,56,62,73,14,6.0,0,77,Urban,ML Engineer,85673,1 +40538,Male,28,High School,5,91,38,52,50,4.0,3,91,Urban,Manager,36660,1 +40539,Male,47,Diploma,13,65,41,90,45,9.0,2,89,Urban,ML Engineer,134252,1 +40540,Male,33,Diploma,10,10,62,53,76,6.0,3,81,Urban,Manager,42218,0 +40541,Male,48,Bachelors,18,48,4,36,30,9.0,5,67,Urban,HR Executive,103521,0 +40542,Male,49,Bachelors,12,67,85,12,83,6.0,7,42,Urban,HR Executive,86238,0 +40543,Male,21,Masters,19,15,79,5,15,7.0,3,38,Rural,Software Engineer,120027,0 +40544,Female,34,Masters,0,92,26,4,5,6.0,3,3,Semi-Urban,ML Engineer,95993,0 +40545,Male,30,Bachelors,0,84,2,45,33,4.0,1,86,Urban,Software Engineer,52518,0 +40546,Male,41,Bachelors,2,65,82,30,15,7.0,0,20,Urban,Data Analyst,42745,0 +40547,Male,47,Bachelors,12,48,29,97,47,0.0,5,16,Semi-Urban,Data Analyst,86459,0 +40548,Other,59,Diploma,1,33,63,84,19,7.0,5,42,Rural,HR Executive,121923,0 +40549,Other,41,Diploma,10,38,28,0,24,1.0,2,83,Urban,Software Engineer,103158,0 +40550,Male,37,Bachelors,16,34,96,71,8,9.0,4,81,Semi-Urban,ML Engineer,97326,1 +40551,Male,48,PhD,2,60,74,0,81,7.0,2,68,Rural,Software Engineer,131896,0 +40552,Male,50,Bachelors,14,88,69,18,52,4.0,5,44,Rural,ML Engineer,146759,0 +40553,Male,47,High School,10,92,1,27,85,0.0,3,99,Urban,Data Analyst,62441,0 +40554,Male,40,Masters,8,72,69,99,66,1.0,0,80,Rural,ML Engineer,49175,1 +40555,Male,56,Bachelors,8,62,83,38,18,4.0,0,82,Semi-Urban,Data Analyst,81654,1 +40556,Male,59,Bachelors,4,60,33,38,25,9.0,2,6,Urban,ML Engineer,138716,0 +40557,Male,52,Diploma,12,67,54,18,70,4.0,1,2,Urban,HR Executive,149049,0 +40558,Male,25,Masters,12,80,44,12,6,3.0,4,86,Urban,HR Executive,76543,0 +40559,Female,55,High School,7,77,92,90,55,1.0,0,49,Rural,Data Analyst,120759,1 +40560,Male,59,Bachelors,18,82,17,15,70,0.0,4,86,Semi-Urban,Software Engineer,25954,0 +40561,Female,42,Masters,12,28,30,37,49,7.0,2,52,Semi-Urban,ML Engineer,42176,0 +40562,Male,29,Bachelors,3,3,45,13,24,1.0,1,60,Urban,Data Analyst,33077,0 +40563,Male,32,Bachelors,16,9,70,8,27,4.0,7,91,Urban,Software Engineer,84190,0 +40564,Female,36,High School,17,16,47,11,42,8.0,2,64,Rural,HR Executive,139682,0 +40565,Male,29,Bachelors,19,71,26,37,52,3.0,1,93,Semi-Urban,ML Engineer,27594,0 +40566,Male,38,High School,15,59,16,81,16,4.0,2,6,Urban,Manager,48407,0 +40567,Male,50,Diploma,7,37,23,8,44,6.0,3,51,Semi-Urban,Software Engineer,33737,0 +40568,Male,23,Diploma,8,22,45,96,23,2.0,5,56,Urban,ML Engineer,95581,0 +40569,Male,53,Diploma,18,40,5,26,82,8.0,1,6,Urban,HR Executive,126366,0 +40570,Male,48,Bachelors,18,5,92,85,58,0.0,7,43,Rural,HR Executive,125758,0 +40571,Male,36,Diploma,3,92,72,85,71,7.0,1,73,Urban,ML Engineer,108308,1 +40572,Male,48,Bachelors,4,85,17,87,31,3.0,5,55,Urban,ML Engineer,71249,1 +40573,Male,45,Bachelors,9,6,73,45,6,3.0,0,64,Urban,Data Analyst,63450,0 +40574,Male,59,Bachelors,10,15,19,12,3,1.0,2,51,Semi-Urban,Data Analyst,90963,0 +40575,Female,50,Bachelors,4,63,15,11,88,5.0,7,86,Rural,HR Executive,66693,0 +40576,Male,55,Masters,10,43,41,60,74,5.0,2,53,Semi-Urban,Manager,74572,0 +40577,Female,46,Bachelors,13,17,16,3,77,0.0,1,23,Semi-Urban,Data Analyst,51140,0 +40578,Female,25,Diploma,6,16,26,42,45,7.0,2,56,Urban,Data Analyst,101127,0 +40579,Male,55,Diploma,5,75,16,79,18,6.0,3,34,Urban,Data Analyst,144674,0 +40580,Male,49,High School,14,51,2,73,40,4.0,3,73,Urban,HR Executive,29579,0 +40581,Male,33,PhD,5,33,63,57,82,3.0,2,89,Urban,Software Engineer,109044,1 +40582,Male,46,Diploma,8,75,24,7,53,0.0,2,14,Urban,Software Engineer,141574,0 +40583,Female,29,Diploma,16,70,85,24,99,2.0,2,96,Rural,HR Executive,132653,1 +40584,Male,54,Bachelors,6,22,6,83,93,7.0,3,0,Semi-Urban,ML Engineer,130758,0 +40585,Male,40,Diploma,19,56,88,38,71,3.0,0,93,Semi-Urban,ML Engineer,129181,1 +40586,Male,44,Bachelors,10,85,47,71,94,6.0,1,56,Urban,Software Engineer,69753,1 +40587,Female,53,Diploma,12,94,88,95,0,4.0,4,26,Urban,Manager,123969,1 +40588,Male,58,Masters,14,90,11,73,67,5.0,5,5,Urban,Data Analyst,70925,0 +40589,Female,38,Bachelors,3,58,55,27,78,5.0,1,9,Urban,Data Analyst,135796,0 +40590,Female,30,Diploma,16,54,51,72,24,9.0,3,33,Urban,Manager,35490,0 +40591,Male,52,Diploma,4,75,30,7,6,5.0,2,91,Urban,Data Analyst,133351,0 +40592,Male,53,Bachelors,11,40,0,93,63,5.0,2,36,Urban,ML Engineer,146401,0 +40593,Male,56,Diploma,10,50,36,36,1,7.0,3,3,Urban,HR Executive,125222,0 +40594,Male,37,Masters,7,31,45,27,3,3.0,6,93,Rural,HR Executive,45636,0 +40595,Female,34,Bachelors,18,41,0,33,30,3.0,2,18,Urban,ML Engineer,109123,0 +40596,Male,41,Bachelors,19,65,77,98,89,5.0,0,21,Urban,Manager,45434,1 +40597,Male,23,Bachelors,9,35,49,75,45,7.0,1,62,Semi-Urban,Manager,21636,0 +40598,Male,43,PhD,17,61,32,75,6,1.0,4,59,Urban,ML Engineer,85440,0 +40599,Male,48,PhD,17,81,67,82,61,8.0,4,91,Urban,Data Analyst,76892,1 +40600,Male,29,High School,10,93,4,93,79,1.0,5,97,Urban,HR Executive,32395,1 +40601,Male,57,PhD,15,93,31,14,97,2.0,3,25,Rural,Data Analyst,124860,0 +40602,Male,41,Bachelors,8,58,76,71,66,8.0,5,96,Urban,ML Engineer,47385,1 +40603,Male,25,Masters,7,56,15,58,22,4.0,2,42,Urban,Data Analyst,86511,0 +40604,Male,31,Bachelors,2,37,55,85,93,9.0,7,21,Urban,HR Executive,89460,0 +40605,Male,58,Diploma,10,77,27,89,63,5.0,4,26,Urban,ML Engineer,33593,0 +40606,Male,54,Masters,11,63,80,55,31,4.0,2,55,Urban,Manager,99527,1 +40607,Male,58,Diploma,6,17,79,64,90,3.0,5,70,Semi-Urban,Manager,122016,0 +40608,Male,30,Bachelors,18,79,32,80,48,2.0,3,40,Urban,Data Analyst,135390,0 +40609,Male,31,Bachelors,15,50,23,96,19,6.0,2,62,Rural,ML Engineer,66299,0 +40610,Male,29,Bachelors,10,16,58,75,96,5.0,0,64,Semi-Urban,Manager,84759,0 +40611,Male,22,Masters,9,81,5,25,50,6.0,3,10,Urban,Manager,138715,0 +40612,Male,41,Masters,19,95,14,69,86,2.0,3,6,Urban,Data Analyst,125135,0 +40613,Male,59,Bachelors,11,93,24,16,44,3.0,1,9,Semi-Urban,HR Executive,51344,0 +40614,Male,31,Bachelors,6,39,17,36,81,2.0,2,60,Rural,Data Analyst,48242,0 +40615,Male,27,Bachelors,13,43,0,61,71,7.0,7,30,Urban,Data Analyst,42277,0 +40616,Male,30,Bachelors,2,7,79,19,17,2.0,6,16,Rural,Manager,61732,0 +40617,Male,53,Bachelors,1,33,60,58,83,6.0,7,99,Semi-Urban,ML Engineer,148878,1 +40618,Female,54,Diploma,13,33,63,94,53,6.0,5,68,Rural,ML Engineer,60972,1 +40619,Male,34,Diploma,3,48,63,95,22,7.0,2,86,Semi-Urban,HR Executive,133001,1 +40620,Male,36,High School,9,58,1,54,3,2.0,3,44,Urban,Manager,80828,0 +40621,Male,35,High School,5,77,24,9,50,9.0,6,41,Urban,ML Engineer,40739,0 +40622,Male,27,Bachelors,8,16,79,79,79,3.0,5,86,Urban,ML Engineer,64309,1 +40623,Male,47,Bachelors,10,6,50,4,55,8.0,7,19,Semi-Urban,HR Executive,63995,0 +40624,Male,31,Masters,6,27,72,37,18,2.0,0,1,Semi-Urban,Software Engineer,61478,0 +40625,Male,54,Masters,5,33,1,98,20,9.0,0,88,Rural,Manager,66054,0 +40626,Female,59,Bachelors,0,14,24,61,71,7.0,5,28,Rural,Manager,80204,0 +40627,Male,43,Diploma,4,2,44,14,34,9.0,1,22,Urban,HR Executive,102556,0 +40628,Female,24,Masters,15,89,97,88,94,9.0,5,90,Semi-Urban,Data Analyst,142356,1 +40629,Female,41,Bachelors,3,65,99,71,48,3.0,1,65,Urban,ML Engineer,57521,1 +40630,Female,55,Bachelors,6,64,70,40,60,9.0,7,19,Urban,HR Executive,38848,0 +40631,Female,57,Diploma,13,41,7,95,11,7.0,5,32,Rural,HR Executive,91609,0 +40632,Male,44,PhD,10,45,57,40,18,0.0,4,18,Rural,Manager,120890,0 +40633,Male,36,Diploma,9,47,93,82,17,0.0,6,81,Semi-Urban,Data Analyst,49730,1 +40634,Male,31,Diploma,10,3,52,92,69,8.0,2,66,Urban,Manager,76223,0 +40635,Male,52,High School,14,10,60,41,41,3.0,6,28,Rural,HR Executive,112857,0 +40636,Male,21,Diploma,8,77,94,72,61,6.0,2,74,Urban,Software Engineer,32374,1 +40637,Female,40,Bachelors,19,91,78,64,17,7.0,5,76,Rural,HR Executive,23041,1 +40638,Male,59,Bachelors,7,44,63,18,73,9.0,4,47,Urban,Manager,53303,0 +40639,Male,49,Bachelors,8,10,77,35,2,8.0,1,74,Rural,Software Engineer,144717,0 +40640,Female,29,Diploma,14,83,94,18,43,8.0,3,5,Rural,Manager,147678,0 +40641,Male,55,PhD,2,55,2,48,58,1.0,2,5,Rural,Manager,29321,0 +40642,Male,58,High School,12,26,57,77,69,7.0,0,43,Urban,HR Executive,38897,0 +40643,Male,26,High School,3,19,62,94,57,1.0,0,3,Urban,Data Analyst,121023,0 +40644,Female,33,High School,18,57,71,4,71,3.0,3,23,Semi-Urban,ML Engineer,144897,0 +40645,Male,31,Masters,15,60,75,73,87,0.0,6,8,Urban,Manager,67616,0 +40646,Female,47,Diploma,9,83,80,76,13,5.0,7,68,Semi-Urban,HR Executive,134183,1 +40647,Male,26,Masters,6,84,18,10,85,0.0,2,56,Urban,Data Analyst,52791,0 +40648,Female,47,Bachelors,5,66,82,41,72,6.0,7,1,Semi-Urban,ML Engineer,103655,0 +40649,Male,31,Diploma,5,42,53,33,85,4.0,1,61,Urban,Software Engineer,57359,0 +40650,Female,35,Bachelors,17,66,44,96,69,2.0,1,99,Urban,Software Engineer,145103,1 +40651,Other,46,Masters,0,64,88,29,79,5.0,5,18,Urban,HR Executive,95285,0 +40652,Male,44,Masters,2,46,21,4,68,1.0,7,25,Semi-Urban,Software Engineer,80889,0 +40653,Male,46,Bachelors,6,45,32,71,32,7.0,3,38,Semi-Urban,Data Analyst,148162,0 +40654,Male,23,Bachelors,10,84,97,58,44,9.0,4,64,Urban,ML Engineer,125727,1 +40655,Male,48,Bachelors,5,69,65,72,82,5.0,0,56,Urban,ML Engineer,83770,1 +40656,Female,41,Masters,16,9,92,7,8,3.0,3,2,Urban,Software Engineer,46448,0 +40657,Male,46,Diploma,2,44,26,23,32,3.0,3,21,Urban,HR Executive,120360,0 +40658,Female,52,Diploma,17,64,77,51,3,3.0,5,55,Semi-Urban,Manager,93860,1 +40659,Female,47,Bachelors,17,90,32,40,23,5.0,6,97,Urban,Software Engineer,148352,1 +40660,Male,40,High School,14,73,27,36,81,5.0,0,77,Urban,Manager,139704,0 +40661,Male,50,Diploma,0,22,6,14,55,7.0,0,34,Urban,HR Executive,71790,0 +40662,Male,45,Masters,17,61,7,81,26,3.0,3,42,Semi-Urban,Data Analyst,149757,0 +40663,Male,31,Bachelors,7,84,13,29,17,8.0,1,7,Urban,Data Analyst,62653,0 +40664,Male,43,Diploma,0,43,77,14,54,8.0,5,39,Rural,Data Analyst,41622,0 +40665,Male,48,Diploma,11,27,57,71,69,3.0,6,47,Urban,HR Executive,132239,0 +40666,Female,27,High School,3,69,76,86,24,8.0,2,1,Semi-Urban,HR Executive,35904,0 +40667,Male,24,High School,19,54,28,96,98,5.0,1,49,Rural,Data Analyst,84426,0 +40668,Male,22,Bachelors,19,39,44,67,76,8.0,0,10,Semi-Urban,HR Executive,31176,0 +40669,Male,34,PhD,6,29,95,64,20,9.0,0,94,Urban,Data Analyst,85211,1 +40670,Female,23,Bachelors,2,15,34,27,79,2.0,4,64,Semi-Urban,HR Executive,65915,0 +40671,Male,47,Diploma,19,48,96,48,37,1.0,0,61,Semi-Urban,ML Engineer,78241,1 +40672,Male,22,Diploma,4,87,86,0,14,5.0,6,61,Urban,Software Engineer,60784,0 +40673,Female,36,Bachelors,14,34,28,37,26,0.0,6,71,Urban,ML Engineer,67468,0 +40674,Female,27,Diploma,15,99,97,42,21,8.0,2,88,Urban,ML Engineer,100722,1 +40675,Female,56,Bachelors,6,19,58,6,61,2.0,5,95,Urban,Manager,132306,0 +40676,Female,32,Bachelors,6,22,32,83,25,7.0,2,43,Semi-Urban,Software Engineer,60830,0 +40677,Male,50,High School,17,89,53,45,19,9.0,4,39,Urban,ML Engineer,107455,0 +40678,Female,25,Masters,11,45,43,83,69,4.0,3,46,Urban,Data Analyst,30827,0 +40679,Male,48,Masters,2,22,22,65,39,6.0,4,9,Urban,ML Engineer,113804,0 +40680,Male,46,Bachelors,5,80,14,59,60,2.0,2,50,Rural,Manager,88657,0 +40681,Other,55,Bachelors,3,61,9,19,15,7.0,1,77,Rural,Software Engineer,130811,0 +40682,Male,41,Bachelors,19,76,20,82,92,0.0,1,89,Semi-Urban,Manager,24678,1 +40683,Male,24,High School,11,97,3,26,30,3.0,1,48,Urban,HR Executive,31690,0 +40684,Male,42,High School,10,86,37,43,23,4.0,4,27,Urban,Data Analyst,142522,0 +40685,Male,46,PhD,9,33,25,62,11,3.0,2,33,Rural,Software Engineer,106065,0 +40686,Male,27,Bachelors,12,44,22,50,1,3.0,0,24,Urban,Data Analyst,39140,0 +40687,Female,22,Diploma,0,84,80,65,82,0.0,4,43,Urban,Data Analyst,125468,1 +40688,Other,26,Bachelors,10,61,92,92,90,0.0,2,83,Urban,Software Engineer,54341,1 +40689,Male,26,Diploma,8,66,57,96,92,2.0,3,80,Semi-Urban,Manager,93161,1 +40690,Female,50,Diploma,7,71,10,2,79,7.0,1,68,Urban,Software Engineer,129467,0 +40691,Male,31,Bachelors,14,26,11,54,4,3.0,6,25,Semi-Urban,HR Executive,143724,0 +40692,Male,49,Diploma,3,21,11,59,60,2.0,7,57,Urban,Software Engineer,21388,0 +40693,Female,26,Diploma,9,12,9,59,87,3.0,3,31,Urban,Software Engineer,136820,0 +40694,Female,51,High School,0,74,15,17,35,1.0,0,44,Semi-Urban,Software Engineer,91298,0 +40695,Male,28,PhD,10,81,71,53,84,9.0,2,78,Rural,Manager,121524,1 +40696,Male,44,Diploma,13,17,25,11,7,5.0,1,14,Urban,HR Executive,116936,0 +40697,Male,36,Diploma,14,97,77,85,28,4.0,5,19,Semi-Urban,HR Executive,20903,1 +40698,Female,38,Diploma,13,11,54,54,40,5.0,6,13,Semi-Urban,HR Executive,147414,0 +40699,Male,27,Masters,13,1,56,94,89,5.0,5,51,Urban,Manager,57053,0 +40700,Male,28,Diploma,12,47,77,29,26,5.0,0,96,Semi-Urban,ML Engineer,67314,1 +40701,Female,56,Masters,19,48,24,53,71,6.0,6,64,Rural,ML Engineer,30076,0 +40702,Male,51,Diploma,14,34,20,28,36,0.0,3,45,Semi-Urban,HR Executive,75857,0 +40703,Female,40,High School,1,10,13,32,9,5.0,4,49,Semi-Urban,HR Executive,92335,0 +40704,Female,29,Bachelors,15,71,37,76,35,7.0,5,46,Semi-Urban,HR Executive,68913,0 +40705,Male,24,Masters,19,30,77,97,97,3.0,7,79,Semi-Urban,Manager,28638,1 +40706,Male,43,High School,17,60,29,29,96,7.0,7,46,Urban,Software Engineer,106344,0 +40707,Male,59,Masters,18,60,68,2,57,0.0,6,39,Urban,Data Analyst,83173,0 +40708,Other,59,Bachelors,6,81,57,78,41,4.0,0,69,Urban,HR Executive,123765,1 +40709,Male,46,Diploma,17,60,89,96,71,7.0,0,35,Semi-Urban,Software Engineer,128021,1 +40710,Female,44,Masters,5,16,89,27,49,1.0,7,24,Urban,Data Analyst,101570,0 +40711,Male,55,Diploma,1,62,26,48,24,4.0,1,1,Semi-Urban,Software Engineer,92610,0 +40712,Male,33,Diploma,15,77,50,61,78,6.0,2,17,Rural,Manager,135447,0 +40713,Male,29,Bachelors,1,75,91,20,50,5.0,4,37,Urban,Software Engineer,63127,0 +40714,Male,54,Bachelors,11,23,49,38,10,0.0,5,22,Urban,HR Executive,29533,0 +40715,Male,43,Bachelors,14,36,69,23,85,3.0,7,27,Urban,ML Engineer,90208,0 +40716,Male,54,High School,10,1,73,55,89,5.0,0,12,Semi-Urban,Manager,130948,0 +40717,Male,30,Diploma,4,97,25,76,45,5.0,5,54,Semi-Urban,Manager,45378,1 +40718,Male,51,Bachelors,13,83,68,65,34,4.0,2,33,Semi-Urban,ML Engineer,106355,1 +40719,Male,39,PhD,7,93,20,44,39,6.0,0,60,Rural,Manager,34465,0 +40720,Male,43,Diploma,7,25,75,62,60,7.0,6,94,Urban,Software Engineer,22671,1 +40721,Male,48,High School,5,26,23,77,59,7.0,5,17,Urban,Data Analyst,26042,0 +40722,Male,30,Diploma,6,31,2,41,66,0.0,1,12,Semi-Urban,Data Analyst,116980,0 +40723,Female,58,Bachelors,5,95,63,98,82,8.0,0,45,Semi-Urban,ML Engineer,112242,1 +40724,Male,54,Bachelors,2,75,61,26,67,1.0,1,49,Urban,HR Executive,108892,0 +40725,Other,21,Masters,0,72,80,9,55,1.0,7,90,Semi-Urban,HR Executive,80370,1 +40726,Male,41,Bachelors,18,32,21,75,64,0.0,4,36,Urban,Software Engineer,50596,0 +40727,Female,52,Diploma,16,68,88,75,44,5.0,1,6,Urban,Data Analyst,90833,0 +40728,Male,29,Diploma,12,0,79,17,60,2.0,0,79,Urban,HR Executive,22955,0 +40729,Male,31,Bachelors,10,53,70,32,94,9.0,2,41,Semi-Urban,Data Analyst,148406,0 +40730,Male,33,Bachelors,6,74,28,63,34,7.0,3,80,Urban,Data Analyst,69949,1 +40731,Male,47,Bachelors,14,26,94,37,47,4.0,0,60,Semi-Urban,HR Executive,27241,0 +40732,Male,57,Diploma,0,64,73,56,32,4.0,2,78,Urban,ML Engineer,82165,1 +40733,Female,38,High School,0,88,82,42,20,1.0,3,79,Semi-Urban,HR Executive,146647,1 +40734,Male,38,Bachelors,14,72,88,70,34,0.0,5,44,Semi-Urban,ML Engineer,134372,1 +40735,Male,31,Bachelors,10,88,9,30,46,1.0,6,59,Rural,HR Executive,96981,0 +40736,Female,59,Bachelors,10,44,86,70,94,4.0,4,49,Urban,Software Engineer,26466,1 +40737,Male,49,Bachelors,18,93,28,7,60,5.0,3,73,Rural,HR Executive,95681,0 +40738,Male,42,Bachelors,8,92,53,36,82,5.0,6,73,Rural,HR Executive,26381,1 +40739,Male,51,Bachelors,1,89,43,61,97,9.0,7,21,Rural,ML Engineer,108309,0 +40740,Male,30,High School,6,5,74,86,99,6.0,2,46,Semi-Urban,ML Engineer,142589,0 +40741,Male,22,Diploma,7,33,84,16,85,1.0,3,6,Urban,ML Engineer,54975,0 +40742,Male,27,High School,1,22,80,65,62,9.0,4,43,Urban,Data Analyst,117027,0 +40743,Male,58,PhD,8,49,23,58,69,6.0,5,16,Urban,HR Executive,135219,0 +40744,Male,24,Masters,8,49,70,44,29,6.0,0,41,Semi-Urban,HR Executive,122757,0 +40745,Male,26,Bachelors,8,3,10,12,75,5.0,7,6,Urban,ML Engineer,83921,0 +40746,Other,35,Bachelors,4,25,8,49,88,5.0,2,26,Rural,Software Engineer,130807,0 +40747,Other,48,High School,3,12,54,30,56,5.0,2,28,Semi-Urban,Manager,98546,0 +40748,Male,22,Bachelors,18,65,82,69,98,9.0,2,32,Rural,HR Executive,68813,1 +40749,Male,39,Diploma,3,5,58,0,34,4.0,1,65,Urban,ML Engineer,132213,0 +40750,Male,46,Masters,3,82,82,24,40,7.0,5,68,Urban,HR Executive,29275,1 +40751,Male,36,Masters,17,55,61,66,58,5.0,0,72,Semi-Urban,Manager,61988,1 +40752,Male,45,Bachelors,4,82,71,31,52,4.0,6,93,Urban,HR Executive,81789,1 +40753,Male,53,Diploma,18,40,83,28,19,2.0,3,7,Rural,ML Engineer,21868,0 +40754,Male,48,Masters,0,85,56,79,21,3.0,0,44,Semi-Urban,HR Executive,102801,1 +40755,Female,44,Masters,12,60,45,3,28,0.0,7,37,Urban,Data Analyst,112463,0 +40756,Female,48,Bachelors,1,32,4,89,58,7.0,0,53,Urban,ML Engineer,69101,0 +40757,Other,44,Bachelors,0,19,88,25,43,9.0,7,78,Urban,Software Engineer,43247,0 +40758,Male,44,Bachelors,1,19,19,42,15,7.0,6,37,Semi-Urban,ML Engineer,82430,0 +40759,Female,51,High School,10,49,1,60,47,3.0,1,11,Rural,HR Executive,22909,0 +40760,Male,32,Bachelors,3,56,60,1,61,3.0,3,69,Urban,Data Analyst,134322,0 +40761,Male,27,High School,9,35,13,13,23,0.0,2,56,Semi-Urban,Data Analyst,144658,0 +40762,Female,48,Masters,12,12,11,14,26,2.0,2,43,Semi-Urban,Software Engineer,110652,0 +40763,Female,47,High School,7,18,15,5,74,6.0,6,15,Urban,ML Engineer,39118,0 +40764,Female,46,High School,0,19,26,50,89,4.0,5,16,Rural,ML Engineer,131083,0 +40765,Male,30,Bachelors,14,9,4,64,93,6.0,7,75,Rural,HR Executive,147849,0 +40766,Male,53,High School,13,44,28,62,24,4.0,3,53,Urban,HR Executive,46984,0 +40767,Female,46,PhD,1,10,86,68,80,6.0,1,73,Urban,ML Engineer,90173,0 +40768,Female,27,Masters,15,52,57,62,30,9.0,0,97,Urban,Manager,55871,1 +40769,Female,44,Bachelors,15,57,29,9,74,3.0,5,41,Urban,Manager,102799,0 +40770,Male,28,High School,0,48,78,4,9,1.0,2,2,Urban,HR Executive,47349,0 +40771,Male,57,PhD,7,83,36,73,0,1.0,5,6,Urban,Manager,45754,0 +40772,Male,24,Masters,17,60,82,78,74,1.0,2,54,Semi-Urban,ML Engineer,23231,1 +40773,Female,29,High School,19,90,96,44,73,6.0,5,89,Urban,Data Analyst,124429,1 +40774,Male,42,Masters,7,45,64,15,60,8.0,4,38,Rural,Software Engineer,105561,0 +40775,Male,31,Bachelors,0,20,75,17,80,2.0,6,78,Urban,ML Engineer,103329,0 +40776,Female,35,High School,2,45,32,98,98,0.0,0,27,Urban,Manager,121901,0 +40777,Male,56,Diploma,16,82,85,72,15,6.0,5,68,Semi-Urban,Software Engineer,64104,1 +40778,Female,39,High School,2,49,80,48,35,1.0,2,82,Urban,ML Engineer,126753,1 +40779,Female,38,Masters,4,87,85,11,19,5.0,2,13,Urban,Software Engineer,42122,0 +40780,Male,32,Bachelors,0,24,44,75,80,4.0,1,49,Rural,Data Analyst,69059,0 +40781,Male,43,Bachelors,11,12,74,88,48,1.0,0,37,Urban,Data Analyst,42645,0 +40782,Female,53,Bachelors,0,52,63,83,10,6.0,4,28,Urban,HR Executive,123728,0 +40783,Male,38,Bachelors,7,65,18,18,46,6.0,4,65,Rural,Software Engineer,33690,0 +40784,Male,38,Bachelors,11,90,7,5,3,0.0,7,57,Urban,ML Engineer,83157,0 +40785,Male,33,Bachelors,3,37,98,10,17,0.0,1,47,Semi-Urban,Data Analyst,124080,0 +40786,Male,50,High School,8,68,24,5,62,8.0,0,62,Semi-Urban,Manager,58937,0 +40787,Male,43,Bachelors,12,66,39,77,30,5.0,6,25,Urban,Data Analyst,121393,0 +40788,Male,41,Masters,5,25,3,56,12,4.0,0,83,Urban,HR Executive,50154,0 +40789,Male,23,Bachelors,12,39,53,19,55,1.0,3,27,Semi-Urban,HR Executive,29260,0 +40790,Male,38,Bachelors,3,98,87,37,99,4.0,7,91,Urban,Manager,86456,1 +40791,Male,49,Bachelors,10,60,60,15,36,2.0,1,21,Urban,ML Engineer,127330,0 +40792,Male,40,Diploma,14,3,88,22,67,4.0,2,14,Urban,Manager,126570,0 +40793,Female,26,PhD,8,96,24,31,25,5.0,7,87,Semi-Urban,Manager,112877,0 +40794,Male,30,Bachelors,10,59,60,18,35,2.0,7,74,Urban,ML Engineer,147670,0 +40795,Female,30,Bachelors,14,67,68,29,39,3.0,7,16,Urban,HR Executive,43068,0 +40796,Male,57,Masters,9,4,38,36,64,5.0,0,0,Urban,HR Executive,59216,0 +40797,Male,35,High School,6,85,90,2,52,3.0,4,80,Urban,Software Engineer,32184,1 +40798,Female,28,Diploma,19,91,85,66,43,5.0,7,76,Urban,Data Analyst,79432,1 +40799,Male,27,Diploma,8,74,97,94,27,6.0,5,94,Urban,Manager,113798,1 +40800,Male,56,Diploma,3,30,83,74,90,4.0,0,40,Rural,ML Engineer,112463,0 +40801,Male,40,Masters,16,65,4,37,46,8.0,1,71,Urban,ML Engineer,147502,0 +40802,Male,48,Diploma,4,10,57,85,43,0.0,4,82,Semi-Urban,Manager,62579,0 +40803,Male,58,High School,2,15,92,92,49,3.0,1,81,Rural,Manager,50843,1 +40804,Male,27,Bachelors,11,85,25,89,81,9.0,7,78,Urban,ML Engineer,88430,1 +40805,Male,46,Diploma,9,16,27,15,3,5.0,7,12,Urban,Software Engineer,63645,0 +40806,Female,21,Bachelors,4,75,91,20,57,5.0,1,94,Urban,Manager,48517,1 +40807,Female,44,Diploma,18,9,95,7,2,8.0,0,70,Urban,HR Executive,146316,0 +40808,Male,29,Bachelors,15,92,26,25,11,3.0,5,97,Rural,Data Analyst,63782,1 +40809,Female,30,High School,16,8,19,40,59,6.0,7,76,Urban,ML Engineer,63131,0 +40810,Male,23,Diploma,3,9,7,9,68,7.0,3,60,Rural,HR Executive,126599,0 +40811,Male,42,Bachelors,8,39,41,21,7,8.0,2,48,Urban,Manager,32415,0 +40812,Female,28,High School,0,56,59,27,96,9.0,5,99,Semi-Urban,Manager,33860,1 +40813,Male,39,Bachelors,12,90,78,89,62,7.0,1,93,Semi-Urban,Manager,114024,1 +40814,Male,41,Bachelors,16,48,34,42,81,9.0,5,16,Semi-Urban,ML Engineer,95596,0 +40815,Male,43,Masters,2,72,7,87,89,5.0,5,45,Urban,HR Executive,102957,0 +40816,Male,31,Bachelors,7,2,52,57,5,6.0,2,87,Urban,HR Executive,24588,0 +40817,Male,57,High School,15,0,11,63,66,3.0,6,67,Urban,ML Engineer,46466,0 +40818,Female,40,High School,12,63,88,82,9,5.0,2,37,Urban,HR Executive,33337,1 +40819,Male,43,Diploma,9,53,68,87,22,2.0,7,61,Urban,HR Executive,129955,1 +40820,Male,42,High School,11,87,37,30,34,4.0,3,94,Urban,ML Engineer,79591,1 +40821,Male,39,High School,6,90,68,78,95,3.0,7,28,Semi-Urban,ML Engineer,51824,1 +40822,Female,24,Bachelors,6,61,48,59,0,5.0,7,86,Semi-Urban,HR Executive,25305,1 +40823,Male,23,Bachelors,18,41,68,93,81,0.0,6,8,Semi-Urban,Manager,54479,0 +40824,Male,33,Masters,19,3,9,82,82,2.0,5,83,Semi-Urban,ML Engineer,137565,0 +40825,Female,47,Diploma,1,49,12,44,46,3.0,7,58,Semi-Urban,Data Analyst,102703,0 +40826,Male,27,Bachelors,14,8,35,50,0,3.0,4,29,Semi-Urban,ML Engineer,133376,0 +40827,Male,47,High School,5,79,1,32,29,8.0,7,28,Urban,HR Executive,61693,0 +40828,Male,27,Bachelors,8,47,58,15,57,4.0,7,14,Urban,Manager,125403,0 +40829,Male,35,PhD,17,29,16,34,66,5.0,0,41,Semi-Urban,Software Engineer,39571,0 +40830,Male,22,Bachelors,12,48,87,28,47,7.0,2,41,Urban,ML Engineer,132073,0 +40831,Male,33,Bachelors,2,88,83,22,15,5.0,0,40,Urban,Data Analyst,82829,0 +40832,Male,41,Diploma,16,53,72,24,47,7.0,4,24,Rural,Data Analyst,32431,0 +40833,Other,59,Masters,9,0,11,88,13,9.0,1,56,Urban,Manager,146858,0 +40834,Male,48,Diploma,17,97,84,58,33,3.0,7,99,Urban,Manager,65234,1 +40835,Male,28,Bachelors,14,24,88,88,73,9.0,7,28,Urban,ML Engineer,46073,0 +40836,Female,56,Masters,3,60,60,92,98,8.0,7,27,Semi-Urban,HR Executive,129157,0 +40837,Male,45,Diploma,12,45,47,41,19,8.0,4,97,Rural,Software Engineer,24800,0 +40838,Male,54,Diploma,12,35,31,32,78,8.0,6,29,Rural,HR Executive,84928,0 +40839,Male,42,Diploma,6,43,60,62,37,5.0,0,96,Rural,Manager,87434,1 +40840,Male,37,Bachelors,9,24,83,78,12,3.0,2,77,Rural,Software Engineer,21453,1 +40841,Male,34,Bachelors,9,76,57,21,23,9.0,0,57,Urban,Data Analyst,26777,0 +40842,Male,24,Bachelors,2,54,65,35,47,1.0,3,78,Semi-Urban,ML Engineer,33548,0 +40843,Female,55,Bachelors,19,72,8,36,80,2.0,5,71,Rural,Data Analyst,146913,0 +40844,Male,52,Bachelors,14,22,92,72,60,7.0,1,24,Urban,HR Executive,142915,0 +40845,Male,24,High School,0,92,94,16,66,0.0,1,11,Urban,Data Analyst,34356,0 +40846,Male,44,PhD,1,84,17,66,93,5.0,6,11,Rural,Software Engineer,145713,0 +40847,Female,44,Diploma,19,61,8,55,13,9.0,0,57,Rural,HR Executive,64002,0 +40848,Male,40,Bachelors,16,47,82,20,44,3.0,3,76,Semi-Urban,Data Analyst,145409,0 +40849,Female,54,Bachelors,12,97,74,10,91,8.0,0,93,Urban,Manager,119794,1 +40850,Female,43,Bachelors,16,34,49,74,45,2.0,2,55,Urban,Software Engineer,69442,0 +40851,Male,35,Diploma,11,12,47,96,44,2.0,7,58,Urban,HR Executive,41315,0 +40852,Male,28,Masters,16,4,89,10,27,6.0,0,93,Semi-Urban,Manager,28437,0 +40853,Male,24,PhD,3,93,43,18,81,4.0,4,21,Urban,ML Engineer,137801,0 +40854,Male,57,Diploma,9,25,7,76,3,4.0,3,72,Semi-Urban,Manager,38354,0 +40855,Male,39,Diploma,17,62,79,87,94,6.0,3,25,Urban,Manager,75044,1 +40856,Female,50,Diploma,14,38,92,53,65,2.0,5,3,Urban,ML Engineer,36681,0 +40857,Female,34,Bachelors,14,51,24,32,57,9.0,0,37,Semi-Urban,Software Engineer,59189,0 +40858,Male,45,Bachelors,17,76,19,69,10,6.0,4,83,Rural,Software Engineer,104869,1 +40859,Female,28,High School,10,29,35,37,72,4.0,7,83,Urban,ML Engineer,76651,0 +40860,Female,38,High School,6,32,66,29,3,3.0,1,89,Urban,Software Engineer,92334,0 +40861,Male,33,Bachelors,19,87,78,80,76,8.0,4,27,Semi-Urban,HR Executive,49714,1 +40862,Male,45,Masters,15,53,97,70,71,4.0,4,87,Rural,Manager,81346,1 +40863,Male,38,Bachelors,5,31,0,29,55,3.0,1,14,Urban,Manager,132444,0 +40864,Male,46,Bachelors,10,12,64,56,76,6.0,0,98,Urban,Software Engineer,144408,0 +40865,Male,35,Bachelors,7,3,98,90,7,7.0,2,85,Rural,Software Engineer,24660,1 +40866,Female,55,Diploma,4,69,75,93,97,8.0,1,55,Urban,Manager,47199,1 +40867,Male,28,Bachelors,12,10,5,53,81,9.0,5,45,Urban,ML Engineer,75989,0 +40868,Female,46,Diploma,5,77,10,81,65,1.0,7,99,Urban,Data Analyst,138327,1 +40869,Male,42,Masters,16,48,11,3,16,7.0,6,54,Rural,ML Engineer,115492,0 +40870,Male,48,PhD,12,57,22,48,82,6.0,6,26,Semi-Urban,Manager,110762,0 +40871,Female,32,Diploma,15,37,7,85,12,4.0,6,24,Semi-Urban,Data Analyst,87173,0 +40872,Male,26,High School,7,58,18,74,33,3.0,5,16,Semi-Urban,Software Engineer,143047,0 +40873,Female,29,Diploma,12,83,29,30,87,8.0,6,29,Rural,HR Executive,63328,0 +40874,Male,29,Masters,14,95,22,10,59,0.0,7,0,Semi-Urban,Data Analyst,32662,0 +40875,Female,36,Masters,7,59,67,65,61,5.0,3,44,Semi-Urban,HR Executive,131263,0 +40876,Male,47,Bachelors,19,91,79,95,89,7.0,4,80,Semi-Urban,Data Analyst,77286,1 +40877,Male,32,PhD,13,5,30,70,31,6.0,5,31,Urban,Software Engineer,36132,0 +40878,Female,55,High School,19,15,38,77,0,6.0,0,26,Urban,HR Executive,60640,0 +40879,Female,57,Bachelors,4,24,4,23,33,7.0,1,58,Semi-Urban,ML Engineer,99512,0 +40880,Male,34,Bachelors,13,60,66,53,20,8.0,2,65,Semi-Urban,Manager,145013,1 +40881,Other,58,Masters,12,51,47,49,0,6.0,7,0,Urban,Manager,42231,0 +40882,Female,50,Diploma,12,43,92,68,91,6.0,1,97,Urban,HR Executive,99068,1 +40883,Male,41,Masters,17,39,39,57,8,4.0,1,21,Rural,Software Engineer,45615,0 +40884,Male,40,Bachelors,4,38,77,68,7,8.0,7,12,Urban,ML Engineer,144666,0 +40885,Male,43,Bachelors,16,40,62,80,56,1.0,0,66,Rural,ML Engineer,147324,1 +40886,Male,44,Diploma,11,70,11,76,77,0.0,3,47,Rural,Software Engineer,131778,0 +40887,Male,31,Masters,17,58,0,15,5,6.0,0,32,Semi-Urban,HR Executive,39967,0 +40888,Female,30,Bachelors,18,56,64,55,33,7.0,5,89,Rural,Manager,79871,1 +40889,Female,57,Bachelors,16,80,69,7,80,4.0,1,74,Semi-Urban,HR Executive,118223,0 +40890,Male,55,Bachelors,1,0,84,73,21,5.0,3,97,Semi-Urban,HR Executive,21423,1 +40891,Male,34,Diploma,1,10,68,95,57,3.0,2,18,Rural,HR Executive,127328,0 +40892,Other,35,Bachelors,11,0,74,98,13,0.0,5,23,Urban,Software Engineer,23289,0 +40893,Male,22,Bachelors,2,53,25,91,75,6.0,0,13,Urban,Data Analyst,111447,0 +40894,Male,27,Diploma,6,16,99,42,71,4.0,4,98,Semi-Urban,HR Executive,120785,1 +40895,Female,44,Masters,5,23,47,88,31,3.0,4,86,Rural,ML Engineer,148659,1 +40896,Female,55,Bachelors,5,87,56,0,7,4.0,7,33,Rural,Manager,99790,0 +40897,Other,44,Bachelors,3,41,84,68,2,2.0,3,16,Urban,Manager,141535,0 +40898,Other,22,Bachelors,5,35,66,15,75,3.0,4,96,Urban,Manager,93290,0 +40899,Female,45,Diploma,9,33,49,75,6,7.0,1,96,Urban,ML Engineer,52833,1 +40900,Male,44,Bachelors,7,7,45,26,52,5.0,2,88,Urban,Data Analyst,69128,0 +40901,Male,36,Diploma,19,28,27,32,53,3.0,5,63,Urban,ML Engineer,136885,0 +40902,Male,39,Bachelors,6,32,81,25,4,5.0,6,52,Rural,ML Engineer,21910,0 +40903,Male,47,PhD,15,1,83,99,68,3.0,7,67,Urban,Manager,97762,1 +40904,Male,22,Bachelors,12,35,27,56,13,6.0,4,51,Urban,ML Engineer,126336,0 +40905,Male,52,Bachelors,5,35,98,74,55,1.0,0,48,Urban,Software Engineer,72888,1 +40906,Male,41,Bachelors,9,73,23,87,84,8.0,5,9,Urban,Software Engineer,124653,0 +40907,Male,23,Bachelors,15,51,39,80,33,0.0,6,42,Urban,Software Engineer,58961,0 +40908,Male,35,Diploma,14,82,76,84,29,2.0,3,75,Semi-Urban,HR Executive,112837,1 +40909,Male,41,Masters,19,76,50,28,39,4.0,7,84,Urban,Software Engineer,26441,1 +40910,Female,28,Bachelors,13,94,5,0,98,3.0,2,79,Urban,ML Engineer,106740,0 +40911,Female,47,High School,19,47,67,45,73,5.0,3,18,Urban,HR Executive,76487,0 +40912,Female,31,Bachelors,11,80,9,47,35,8.0,2,71,Rural,ML Engineer,20739,0 +40913,Male,23,Bachelors,8,36,3,61,91,1.0,6,77,Urban,Data Analyst,32572,0 +40914,Male,32,Bachelors,19,55,16,27,30,3.0,7,6,Urban,HR Executive,81018,0 +40915,Male,42,Diploma,17,74,53,53,53,9.0,2,75,Urban,ML Engineer,79227,1 +40916,Female,49,Bachelors,3,66,85,8,28,8.0,6,50,Urban,HR Executive,106443,0 +40917,Female,23,Bachelors,13,99,23,63,6,7.0,6,27,Rural,Manager,67159,0 +40918,Male,50,Bachelors,11,13,1,13,54,7.0,2,72,Rural,Data Analyst,128445,0 +40919,Female,32,Bachelors,1,62,57,17,86,8.0,1,11,Rural,Manager,88866,0 +40920,Male,37,Bachelors,6,19,95,56,84,9.0,6,7,Urban,ML Engineer,97284,0 +40921,Male,58,Diploma,11,36,41,44,21,7.0,7,5,Rural,ML Engineer,22788,0 +40922,Female,33,Bachelors,5,48,83,43,52,9.0,5,62,Semi-Urban,Data Analyst,44936,0 +40923,Male,56,Bachelors,10,80,5,87,83,3.0,2,85,Semi-Urban,Manager,80090,1 +40924,Male,51,Diploma,8,60,41,57,75,8.0,5,60,Semi-Urban,Manager,76379,0 +40925,Male,40,Bachelors,6,46,2,74,36,0.0,7,87,Urban,HR Executive,59436,0 +40926,Female,54,PhD,11,13,52,69,14,9.0,5,46,Urban,Software Engineer,143066,0 +40927,Male,59,Diploma,9,40,96,85,64,0.0,5,20,Semi-Urban,ML Engineer,53987,1 +40928,Male,42,Diploma,18,78,16,47,97,4.0,5,68,Rural,Software Engineer,76961,0 +40929,Female,59,Bachelors,12,83,99,33,43,9.0,4,66,Urban,HR Executive,94399,1 +40930,Male,34,Diploma,8,64,84,42,98,4.0,0,26,Urban,ML Engineer,127927,0 +40931,Male,23,Bachelors,1,32,44,94,39,7.0,3,1,Urban,ML Engineer,145878,0 +40932,Male,36,Bachelors,4,79,75,2,60,1.0,7,1,Urban,Data Analyst,72885,0 +40933,Female,21,High School,19,84,30,72,14,7.0,3,91,Semi-Urban,Data Analyst,69830,1 +40934,Male,29,Bachelors,13,52,74,14,26,1.0,3,27,Rural,Software Engineer,145541,0 +40935,Female,24,Masters,6,6,10,4,61,0.0,1,89,Rural,Software Engineer,86177,0 +40936,Other,24,Diploma,10,85,36,82,35,7.0,1,77,Urban,ML Engineer,141502,1 +40937,Female,48,High School,14,22,33,63,81,0.0,3,83,Urban,Software Engineer,102629,0 +40938,Male,25,Diploma,8,72,12,72,70,3.0,5,26,Urban,HR Executive,27092,0 +40939,Female,23,Masters,10,14,95,41,90,8.0,6,20,Urban,Manager,105941,0 +40940,Female,57,High School,12,2,86,2,24,5.0,6,97,Urban,Data Analyst,78750,0 +40941,Male,30,Masters,13,85,3,95,97,0.0,6,17,Semi-Urban,Manager,74801,0 +40942,Male,22,Bachelors,2,20,9,29,82,9.0,5,56,Semi-Urban,Data Analyst,87534,0 +40943,Female,39,Bachelors,3,2,4,39,57,7.0,2,49,Rural,HR Executive,139694,0 +40944,Male,40,Diploma,9,89,79,47,42,0.0,3,52,Urban,Manager,137877,1 +40945,Male,21,Bachelors,2,58,45,22,41,6.0,2,50,Rural,Software Engineer,143083,0 +40946,Female,41,Bachelors,6,47,78,32,79,4.0,7,37,Urban,Manager,74927,0 +40947,Female,43,PhD,13,61,32,20,84,5.0,4,52,Urban,Software Engineer,73165,0 +40948,Male,35,Bachelors,17,71,40,15,88,1.0,5,80,Urban,Manager,113337,0 +40949,Male,58,Bachelors,9,84,91,12,5,9.0,5,94,Urban,HR Executive,61621,1 +40950,Female,21,High School,16,0,87,54,66,1.0,3,45,Urban,ML Engineer,139095,0 +40951,Female,36,Diploma,16,26,79,3,59,5.0,4,89,Semi-Urban,Manager,37190,0 +40952,Other,35,High School,5,74,62,80,82,5.0,5,5,Urban,Software Engineer,78470,0 +40953,Female,40,Diploma,1,25,88,10,42,6.0,3,31,Urban,Data Analyst,105998,0 +40954,Female,38,PhD,7,2,22,1,13,8.0,0,25,Urban,Data Analyst,51452,0 +40955,Other,24,Diploma,0,28,9,81,72,3.0,2,72,Rural,Data Analyst,137318,0 +40956,Male,21,High School,0,40,78,22,11,9.0,5,7,Urban,Manager,53172,0 +40957,Male,31,Diploma,11,83,85,80,64,8.0,1,44,Rural,Data Analyst,101146,1 +40958,Male,45,Diploma,1,33,55,49,70,2.0,7,77,Rural,Software Engineer,96288,0 +40959,Male,23,Bachelors,14,74,17,61,7,5.0,5,60,Rural,Software Engineer,70449,0 +40960,Male,55,Bachelors,3,20,76,86,65,5.0,7,37,Urban,HR Executive,69592,0 +40961,Male,41,Bachelors,10,97,16,2,42,0.0,7,6,Rural,Manager,98965,0 +40962,Female,38,PhD,10,55,41,40,32,0.0,2,80,Semi-Urban,HR Executive,58995,0 +40963,Female,21,Masters,17,5,72,31,5,1.0,2,42,Urban,HR Executive,122311,0 +40964,Male,24,Diploma,7,93,12,7,59,6.0,1,14,Rural,ML Engineer,80134,0 +40965,Male,49,Bachelors,7,72,33,91,85,9.0,4,36,Semi-Urban,ML Engineer,85635,0 +40966,Male,35,Bachelors,10,75,99,77,60,3.0,1,98,Urban,HR Executive,48733,1 +40967,Female,34,Masters,3,67,51,53,93,6.0,2,3,Semi-Urban,Software Engineer,129022,0 +40968,Male,31,PhD,6,28,53,2,7,9.0,5,19,Urban,HR Executive,108319,0 +40969,Female,43,Bachelors,12,39,45,44,49,5.0,1,90,Rural,Data Analyst,50113,0 +40970,Male,27,Bachelors,4,57,45,26,42,1.0,6,9,Urban,Data Analyst,31548,0 +40971,Male,38,Bachelors,19,43,51,68,71,1.0,1,78,Semi-Urban,Manager,111915,1 +40972,Male,27,Bachelors,10,96,22,18,43,5.0,4,49,Urban,Manager,20050,0 +40973,Male,29,Diploma,18,9,71,33,31,2.0,4,75,Rural,HR Executive,133156,0 +40974,Female,45,Masters,3,10,37,25,45,1.0,4,76,Rural,Data Analyst,121586,0 +40975,Female,42,Diploma,6,92,3,39,79,3.0,1,77,Urban,Data Analyst,121639,0 +40976,Male,39,Masters,9,86,18,63,26,4.0,4,21,Urban,Data Analyst,87966,0 +40977,Female,30,Masters,3,88,60,47,87,5.0,3,42,Urban,Software Engineer,109096,0 +40978,Male,36,Diploma,19,30,11,13,45,1.0,1,93,Rural,Manager,30785,0 +40979,Male,53,Diploma,5,95,66,22,40,0.0,0,16,Urban,Software Engineer,97699,0 +40980,Female,26,Bachelors,19,54,7,19,12,4.0,6,59,Semi-Urban,ML Engineer,109047,0 +40981,Male,29,PhD,16,6,85,53,94,9.0,2,8,Urban,Manager,73824,0 +40982,Male,56,Bachelors,10,54,89,12,50,3.0,5,52,Rural,HR Executive,40498,0 +40983,Male,52,Bachelors,18,16,46,68,97,5.0,1,63,Urban,Manager,22209,0 +40984,Male,36,Masters,7,31,63,90,35,9.0,0,57,Urban,Data Analyst,60232,1 +40985,Male,55,High School,2,39,4,47,6,6.0,0,43,Semi-Urban,Manager,109097,0 +40986,Female,55,High School,2,35,65,54,62,7.0,7,97,Urban,Manager,86877,1 +40987,Male,31,Diploma,11,74,74,9,29,2.0,3,9,Semi-Urban,Data Analyst,51170,0 +40988,Male,52,Masters,17,82,75,65,89,6.0,0,26,Rural,Manager,117754,1 +40989,Male,48,Diploma,9,84,28,31,6,5.0,5,14,Urban,ML Engineer,135325,0 +40990,Male,50,Masters,12,76,8,25,93,2.0,2,23,Semi-Urban,ML Engineer,83020,0 +40991,Female,42,Masters,16,73,75,33,86,3.0,2,99,Urban,ML Engineer,107730,1 +40992,Female,44,Bachelors,9,10,40,65,61,7.0,0,6,Urban,HR Executive,54156,0 +40993,Other,22,Diploma,14,91,77,23,23,5.0,7,23,Urban,HR Executive,21364,0 +40994,Male,50,Bachelors,13,40,68,19,25,1.0,5,94,Urban,Data Analyst,115941,0 +40995,Other,53,Masters,5,98,41,14,76,2.0,0,11,Urban,Manager,43917,0 +40996,Male,58,High School,16,66,51,88,57,0.0,4,87,Urban,Data Analyst,98642,1 +40997,Male,44,Bachelors,7,87,31,43,47,9.0,5,12,Urban,Data Analyst,117259,0 +40998,Female,58,Bachelors,0,30,23,22,44,7.0,3,86,Urban,Manager,34267,0 +40999,Male,38,Diploma,10,90,92,6,75,7.0,4,88,Urban,Software Engineer,142058,1 +41000,Male,37,Masters,14,23,7,15,94,5.0,5,98,Urban,Software Engineer,56060,0 +41001,Female,49,High School,9,64,6,5,60,4.0,3,71,Semi-Urban,HR Executive,38491,0 +41002,Female,35,High School,9,22,7,2,98,9.0,4,11,Urban,Software Engineer,145269,0 +41003,Male,30,Bachelors,10,75,52,13,76,9.0,1,15,Semi-Urban,Manager,110789,0 +41004,Female,35,High School,12,5,86,31,50,7.0,1,40,Semi-Urban,Data Analyst,93748,0 +41005,Female,58,Bachelors,12,21,48,9,62,7.0,3,44,Semi-Urban,ML Engineer,81551,0 +41006,Female,37,PhD,8,35,26,39,98,8.0,3,67,Semi-Urban,Data Analyst,111679,0 +41007,Male,42,Bachelors,3,13,9,66,25,6.0,7,68,Urban,ML Engineer,77782,0 +41008,Female,40,Bachelors,9,39,28,9,79,7.0,5,89,Urban,Data Analyst,65545,0 +41009,Female,35,Bachelors,0,16,25,61,29,6.0,0,21,Rural,Software Engineer,141866,0 +41010,Female,39,Diploma,1,79,83,30,6,0.0,2,99,Urban,HR Executive,21521,1 +41011,Female,40,Bachelors,6,27,25,97,84,3.0,5,2,Semi-Urban,Manager,23076,0 +41012,Male,32,High School,15,1,15,19,66,2.0,3,99,Rural,Data Analyst,65711,0 +41013,Male,36,Bachelors,1,70,71,38,69,5.0,0,50,Semi-Urban,Manager,146355,0 +41014,Other,54,Bachelors,12,30,90,9,92,3.0,3,37,Urban,Manager,144901,0 +41015,Male,40,Bachelors,12,90,23,34,10,8.0,4,89,Urban,Data Analyst,41044,1 +41016,Male,44,High School,6,29,72,91,6,7.0,7,4,Semi-Urban,HR Executive,140319,0 +41017,Female,56,Bachelors,8,89,23,77,26,3.0,3,61,Urban,ML Engineer,35083,1 +41018,Male,50,Masters,19,53,60,71,61,0.0,1,24,Urban,ML Engineer,97246,0 +41019,Male,40,Diploma,10,90,18,4,77,2.0,7,17,Urban,HR Executive,143523,0 +41020,Male,45,Diploma,19,6,81,21,52,9.0,7,0,Urban,Manager,23226,0 +41021,Female,25,Bachelors,13,55,48,64,60,4.0,0,3,Urban,HR Executive,55384,0 +41022,Female,57,Masters,3,12,76,4,37,8.0,1,97,Semi-Urban,HR Executive,76521,0 +41023,Female,35,Bachelors,15,5,7,77,35,2.0,2,80,Urban,Data Analyst,125706,0 +41024,Male,41,Diploma,7,27,36,81,36,2.0,1,76,Urban,Software Engineer,24375,0 +41025,Other,37,PhD,14,68,16,28,37,6.0,6,9,Urban,Software Engineer,49137,0 +41026,Male,21,High School,4,98,86,39,18,1.0,6,55,Semi-Urban,Data Analyst,84730,1 +41027,Male,58,Masters,11,75,10,85,35,6.0,4,1,Rural,ML Engineer,138841,0 +41028,Male,57,Bachelors,0,7,57,54,74,7.0,0,61,Semi-Urban,Manager,130942,0 +41029,Other,50,Bachelors,6,48,69,72,69,7.0,5,0,Semi-Urban,Data Analyst,117806,0 +41030,Male,55,Bachelors,2,19,38,22,26,6.0,6,77,Urban,HR Executive,138972,0 +41031,Female,40,Bachelors,2,54,19,51,88,9.0,1,77,Urban,ML Engineer,133052,0 +41032,Male,24,Diploma,2,25,38,9,94,9.0,6,28,Rural,HR Executive,137785,0 +41033,Male,44,Bachelors,10,13,27,46,24,5.0,5,8,Urban,ML Engineer,133641,0 +41034,Female,54,Bachelors,13,96,35,12,69,4.0,3,70,Semi-Urban,HR Executive,67038,0 +41035,Male,56,High School,8,20,99,34,34,4.0,5,52,Urban,Software Engineer,102461,0 +41036,Female,34,Bachelors,11,89,5,96,77,7.0,4,5,Rural,Data Analyst,126660,0 +41037,Male,50,Diploma,8,73,50,2,54,4.0,2,63,Urban,ML Engineer,31717,0 +41038,Female,23,PhD,9,1,46,91,6,8.0,5,36,Urban,Software Engineer,145436,0 +41039,Female,42,Bachelors,3,87,59,83,81,2.0,2,90,Rural,Manager,63551,1 +41040,Male,37,Masters,11,88,11,68,31,1.0,1,98,Urban,Manager,32122,1 +41041,Male,54,Bachelors,14,40,82,45,50,6.0,4,99,Urban,ML Engineer,80650,1 +41042,Other,32,Bachelors,16,48,20,2,41,7.0,3,73,Urban,Data Analyst,98295,0 +41043,Female,37,High School,7,5,53,91,66,9.0,5,92,Rural,Manager,123112,1 +41044,Male,25,Masters,18,28,84,67,67,9.0,3,25,Urban,HR Executive,85219,0 +41045,Female,38,Masters,7,3,62,39,4,7.0,7,59,Rural,HR Executive,51804,0 +41046,Female,25,Bachelors,6,78,91,59,97,4.0,5,72,Rural,Manager,96767,1 +41047,Male,31,Masters,1,63,48,65,79,2.0,3,72,Semi-Urban,Data Analyst,95632,1 +41048,Male,27,Bachelors,1,36,61,96,37,0.0,0,7,Urban,Manager,117819,0 +41049,Other,25,Bachelors,8,94,62,71,20,3.0,0,23,Rural,Software Engineer,38814,1 +41050,Female,26,Masters,11,75,66,42,26,0.0,0,96,Urban,ML Engineer,68601,1 +41051,Female,44,Masters,14,59,37,48,52,5.0,3,33,Urban,ML Engineer,82641,0 +41052,Male,54,Diploma,16,68,45,6,39,7.0,1,8,Urban,Manager,73070,0 +41053,Other,38,Diploma,9,33,67,70,35,4.0,1,35,Urban,Software Engineer,117114,0 +41054,Female,53,Masters,8,16,1,53,48,5.0,5,71,Urban,Manager,61385,0 +41055,Male,57,High School,11,68,17,98,18,6.0,6,13,Rural,Data Analyst,30418,0 +41056,Female,31,Diploma,1,28,21,82,75,1.0,0,86,Urban,Data Analyst,130936,0 +41057,Female,58,PhD,6,5,16,15,36,2.0,0,72,Urban,ML Engineer,63402,0 +41058,Male,37,Bachelors,5,91,61,77,15,3.0,6,10,Urban,Manager,136724,1 +41059,Female,50,Bachelors,5,37,27,85,76,0.0,4,28,Urban,Manager,85683,0 +41060,Female,56,Masters,0,14,73,47,30,5.0,4,17,Urban,ML Engineer,118573,0 +41061,Male,40,High School,18,40,13,50,19,0.0,3,7,Rural,HR Executive,66756,0 +41062,Female,22,Bachelors,2,94,43,86,36,4.0,2,31,Urban,Data Analyst,134681,1 +41063,Female,33,Diploma,13,90,36,55,75,9.0,3,81,Semi-Urban,HR Executive,92180,1 +41064,Male,54,Diploma,4,12,96,85,46,0.0,1,26,Semi-Urban,Data Analyst,72617,0 +41065,Male,54,High School,7,37,68,66,32,1.0,5,2,Rural,ML Engineer,37617,0 +41066,Male,36,Masters,6,99,22,1,49,7.0,3,83,Urban,HR Executive,28854,0 +41067,Male,27,Diploma,3,51,86,74,60,1.0,6,47,Urban,Manager,114686,1 +41068,Female,37,Diploma,8,72,69,20,46,0.0,3,51,Urban,Software Engineer,113394,0 +41069,Male,59,Diploma,4,53,13,5,89,7.0,0,32,Rural,HR Executive,85150,0 +41070,Other,38,Bachelors,19,70,11,99,56,3.0,7,45,Urban,ML Engineer,59363,0 +41071,Other,34,Masters,19,26,37,94,40,6.0,6,66,Urban,HR Executive,138998,0 +41072,Male,22,High School,11,66,85,75,62,4.0,0,54,Urban,HR Executive,84574,1 +41073,Male,32,Masters,16,26,2,28,86,4.0,1,57,Urban,Manager,118899,0 +41074,Male,34,Diploma,14,79,7,60,14,8.0,2,5,Semi-Urban,ML Engineer,82399,0 +41075,Male,32,Masters,14,26,31,56,66,1.0,7,82,Semi-Urban,Software Engineer,33735,0 +41076,Male,52,Bachelors,10,29,90,24,32,9.0,1,4,Urban,Manager,145985,0 +41077,Male,36,Bachelors,18,63,82,87,4,0.0,6,44,Urban,ML Engineer,107631,1 +41078,Male,40,Diploma,16,91,58,49,57,6.0,4,5,Semi-Urban,Data Analyst,59246,0 +41079,Male,59,Bachelors,0,66,21,24,82,7.0,7,60,Urban,Software Engineer,49989,0 +41080,Female,41,Masters,2,25,43,78,59,8.0,1,23,Semi-Urban,ML Engineer,52174,0 +41081,Male,35,Bachelors,7,94,41,26,55,9.0,3,97,Urban,Software Engineer,53396,1 +41082,Male,39,Diploma,14,18,21,31,7,1.0,6,74,Urban,ML Engineer,29713,0 +41083,Female,49,Diploma,10,27,64,58,34,2.0,2,52,Urban,Software Engineer,125588,0 +41084,Male,37,Masters,5,55,74,48,67,6.0,4,1,Urban,Manager,88885,0 +41085,Male,29,Bachelors,15,96,17,12,78,6.0,6,58,Urban,ML Engineer,27231,0 +41086,Female,57,Diploma,12,98,62,23,37,9.0,7,65,Urban,ML Engineer,107020,1 +41087,Male,25,Bachelors,6,88,22,27,19,4.0,6,77,Urban,Data Analyst,90633,0 +41088,Male,23,High School,18,29,21,61,47,2.0,7,89,Urban,Manager,38844,0 +41089,Male,29,Diploma,7,92,65,7,74,9.0,0,33,Urban,HR Executive,56410,0 +41090,Male,31,Masters,5,9,31,96,57,1.0,3,48,Urban,Data Analyst,53815,0 +41091,Male,55,Bachelors,13,58,13,15,3,9.0,7,49,Urban,Data Analyst,48941,0 +41092,Female,33,High School,9,86,32,25,84,4.0,5,28,Urban,ML Engineer,33133,0 +41093,Male,38,High School,13,48,77,97,13,7.0,0,92,Urban,ML Engineer,91327,1 +41094,Male,36,Bachelors,1,34,64,7,22,4.0,1,23,Rural,Data Analyst,107317,0 +41095,Female,22,Diploma,2,23,59,52,19,5.0,2,72,Rural,Software Engineer,122028,0 +41096,Female,26,Masters,1,12,64,96,16,8.0,6,78,Semi-Urban,HR Executive,41701,1 +41097,Female,45,Diploma,19,42,45,59,23,9.0,6,78,Urban,ML Engineer,97694,0 +41098,Male,41,Diploma,5,7,51,55,94,8.0,1,34,Rural,Software Engineer,127562,0 +41099,Male,52,PhD,18,69,90,50,2,6.0,2,98,Rural,Software Engineer,115927,1 +41100,Male,43,Bachelors,11,44,40,46,11,4.0,4,63,Urban,ML Engineer,135195,0 +41101,Female,22,PhD,15,41,53,2,89,8.0,6,40,Rural,Software Engineer,61642,0 +41102,Female,41,Masters,0,43,64,82,61,1.0,0,95,Urban,ML Engineer,43009,1 +41103,Male,46,PhD,2,62,37,82,92,8.0,0,91,Rural,HR Executive,97937,1 +41104,Male,58,Diploma,2,47,62,58,28,1.0,4,4,Urban,ML Engineer,143625,0 +41105,Male,53,Bachelors,7,38,41,22,32,0.0,5,15,Rural,Software Engineer,124273,0 +41106,Male,33,PhD,2,66,40,24,84,7.0,2,32,Urban,Data Analyst,77747,0 +41107,Other,24,Bachelors,9,40,50,9,37,8.0,1,7,Rural,Data Analyst,104836,0 +41108,Male,56,Diploma,9,26,61,14,66,7.0,4,2,Semi-Urban,Software Engineer,146603,0 +41109,Male,49,Masters,10,74,25,18,0,5.0,3,60,Semi-Urban,Data Analyst,134887,0 +41110,Female,21,High School,7,94,68,72,59,7.0,3,42,Semi-Urban,Software Engineer,92115,1 +41111,Male,43,Diploma,8,44,32,61,56,6.0,0,41,Urban,Manager,29509,0 +41112,Male,51,Bachelors,6,35,1,80,72,5.0,1,5,Urban,ML Engineer,69856,0 +41113,Male,36,Diploma,11,32,81,17,75,8.0,2,80,Semi-Urban,Software Engineer,29108,0 +41114,Male,57,Masters,1,94,32,26,92,0.0,6,51,Urban,HR Executive,67505,0 +41115,Male,59,High School,4,46,48,87,86,6.0,5,73,Urban,Manager,63154,1 +41116,Male,27,Masters,16,32,24,57,93,7.0,4,89,Urban,Data Analyst,57798,0 +41117,Male,21,Bachelors,10,20,90,16,23,4.0,7,78,Urban,Data Analyst,54411,0 +41118,Male,52,Bachelors,1,84,82,6,47,2.0,4,0,Semi-Urban,HR Executive,30802,0 +41119,Male,51,Diploma,9,56,15,63,96,4.0,3,63,Urban,ML Engineer,92499,0 +41120,Female,43,Bachelors,13,41,59,18,29,2.0,2,75,Urban,ML Engineer,39802,0 +41121,Male,48,Bachelors,7,43,96,31,98,3.0,4,28,Urban,Manager,73266,0 +41122,Male,22,Bachelors,14,73,49,87,58,8.0,4,12,Rural,Software Engineer,49751,0 +41123,Male,31,High School,4,43,19,76,21,0.0,1,59,Rural,Software Engineer,129102,0 +41124,Male,54,Masters,5,79,12,63,5,2.0,1,54,Urban,Data Analyst,79994,0 +41125,Male,40,Bachelors,5,77,33,93,12,6.0,0,2,Semi-Urban,Data Analyst,30971,0 +41126,Female,34,Bachelors,8,19,5,33,38,6.0,7,45,Rural,ML Engineer,131690,0 +41127,Male,45,PhD,6,74,78,87,5,2.0,6,96,Semi-Urban,Software Engineer,99177,1 +41128,Female,52,Bachelors,1,84,93,33,91,1.0,2,88,Rural,Data Analyst,87828,1 +41129,Male,29,Bachelors,13,93,27,47,14,3.0,3,14,Urban,Software Engineer,115287,0 +41130,Female,52,High School,6,60,37,68,22,2.0,1,40,Rural,HR Executive,57055,0 +41131,Other,41,High School,18,76,78,89,86,1.0,5,93,Urban,Manager,88391,1 +41132,Male,22,High School,7,52,19,93,7,2.0,4,4,Semi-Urban,HR Executive,127650,0 +41133,Male,22,Bachelors,16,14,51,5,42,0.0,5,52,Rural,Data Analyst,94268,0 +41134,Male,40,Diploma,5,82,79,23,46,3.0,3,62,Urban,Manager,56558,1 +41135,Female,41,Masters,12,32,71,0,33,7.0,6,13,Urban,ML Engineer,84071,0 +41136,Male,37,Bachelors,1,46,98,87,53,0.0,5,37,Urban,HR Executive,51812,1 +41137,Female,57,High School,10,53,94,50,21,4.0,2,1,Semi-Urban,ML Engineer,96759,0 +41138,Female,32,Bachelors,16,46,98,62,27,9.0,6,55,Semi-Urban,Software Engineer,105300,1 +41139,Male,47,Diploma,19,26,69,5,35,4.0,4,6,Urban,Data Analyst,101488,0 +41140,Male,27,High School,17,45,59,68,36,4.0,6,83,Urban,Data Analyst,107596,1 +41141,Male,25,Bachelors,16,36,48,37,3,9.0,1,1,Urban,Manager,37848,0 +41142,Female,45,Bachelors,0,4,18,12,57,2.0,5,94,Urban,Manager,25374,0 +41143,Male,52,Bachelors,10,33,86,84,42,3.0,7,47,Semi-Urban,Manager,45695,1 +41144,Male,41,Diploma,12,92,72,66,13,8.0,4,73,Urban,Data Analyst,103003,1 +41145,Male,57,Bachelors,14,85,21,89,22,9.0,7,77,Semi-Urban,Manager,44442,1 +41146,Male,31,Bachelors,6,99,1,51,80,6.0,0,58,Urban,Data Analyst,115547,0 +41147,Male,54,Bachelors,7,24,44,5,36,0.0,4,22,Rural,Data Analyst,75072,0 +41148,Female,35,Masters,12,72,30,73,13,0.0,3,5,Urban,Manager,43277,0 +41149,Female,40,Masters,12,55,66,36,32,6.0,2,56,Rural,Software Engineer,51778,0 +41150,Female,24,Bachelors,6,54,66,69,69,1.0,6,80,Urban,Data Analyst,27667,1 +41151,Female,47,Diploma,7,10,12,7,84,4.0,3,10,Urban,HR Executive,59217,0 +41152,Female,39,Bachelors,18,27,70,29,37,5.0,6,2,Urban,Software Engineer,36235,0 +41153,Male,46,Diploma,9,83,50,98,66,9.0,3,23,Rural,HR Executive,143683,1 +41154,Female,25,Masters,1,41,72,37,96,9.0,5,63,Urban,Manager,85968,0 +41155,Male,59,Masters,13,20,16,35,58,6.0,7,88,Rural,Data Analyst,49562,0 +41156,Male,46,High School,3,79,12,46,98,6.0,6,87,Rural,Software Engineer,54558,0 +41157,Male,49,Diploma,12,37,54,50,82,3.0,6,57,Semi-Urban,Manager,115992,0 +41158,Male,58,High School,17,23,25,18,66,0.0,6,50,Urban,ML Engineer,39533,0 +41159,Male,27,Bachelors,1,44,59,61,80,6.0,6,22,Rural,Manager,138844,0 +41160,Male,44,Masters,12,85,27,50,24,0.0,6,49,Semi-Urban,Manager,141069,0 +41161,Female,53,PhD,14,9,80,76,4,1.0,5,56,Urban,Software Engineer,83567,0 +41162,Male,38,High School,10,49,13,75,40,4.0,1,3,Urban,Software Engineer,130616,0 +41163,Male,42,High School,15,21,92,29,98,1.0,7,72,Semi-Urban,Data Analyst,68212,0 +41164,Female,39,Bachelors,6,74,59,71,12,1.0,2,18,Urban,Software Engineer,125781,0 +41165,Male,50,Diploma,5,52,4,54,67,1.0,2,64,Urban,Data Analyst,75800,0 +41166,Male,49,Diploma,9,32,87,30,15,1.0,6,65,Semi-Urban,Manager,40479,0 +41167,Female,46,High School,19,86,77,0,72,6.0,2,50,Semi-Urban,Data Analyst,53420,0 +41168,Male,50,PhD,13,25,35,70,53,6.0,7,55,Semi-Urban,Manager,142012,0 +41169,Male,56,Diploma,9,33,19,63,33,8.0,4,15,Semi-Urban,Software Engineer,65307,0 +41170,Male,32,Bachelors,16,80,8,22,37,2.0,6,69,Semi-Urban,ML Engineer,22586,0 +41171,Male,40,PhD,0,96,9,70,99,6.0,6,12,Urban,ML Engineer,136448,0 +41172,Male,46,Masters,16,74,47,42,35,1.0,1,73,Rural,HR Executive,47471,1 +41173,Male,45,High School,4,9,75,12,42,0.0,6,73,Urban,Data Analyst,30946,0 +41174,Male,42,Bachelors,19,3,7,32,33,8.0,6,95,Rural,HR Executive,42616,0 +41175,Male,56,Masters,1,81,84,11,69,7.0,1,85,Semi-Urban,Software Engineer,27127,1 +41176,Other,30,Masters,8,75,67,34,53,5.0,6,17,Urban,HR Executive,111874,0 +41177,Male,28,Bachelors,0,3,23,45,35,0.0,7,60,Semi-Urban,HR Executive,39162,0 +41178,Female,30,Bachelors,18,35,58,3,4,2.0,7,63,Rural,Data Analyst,126358,0 +41179,Male,44,Bachelors,14,30,36,37,34,5.0,0,93,Urban,Manager,104004,0 +41180,Female,48,High School,16,13,61,64,49,1.0,0,90,Urban,Software Engineer,88302,0 +41181,Male,51,Diploma,15,60,18,52,65,1.0,2,29,Urban,Data Analyst,92860,0 +41182,Male,57,High School,0,16,91,5,98,7.0,1,99,Urban,HR Executive,119347,0 +41183,Male,31,Bachelors,6,33,12,80,94,7.0,1,70,Urban,HR Executive,35553,0 +41184,Female,48,Masters,10,30,0,20,7,6.0,2,86,Rural,ML Engineer,55675,0 +41185,Male,57,Masters,8,13,70,9,53,8.0,0,14,Urban,Software Engineer,91873,0 +41186,Male,21,High School,9,90,96,31,7,0.0,2,47,Semi-Urban,HR Executive,62062,1 +41187,Male,56,Bachelors,19,2,38,35,86,9.0,7,7,Urban,Manager,140679,0 +41188,Male,56,Diploma,10,9,2,58,17,1.0,2,52,Urban,Software Engineer,135780,0 +41189,Female,32,Masters,5,18,64,88,63,5.0,4,65,Urban,Software Engineer,62640,0 +41190,Female,47,Bachelors,0,52,26,58,74,7.0,7,69,Semi-Urban,Manager,125012,0 +41191,Male,31,Masters,7,32,3,18,51,5.0,5,73,Rural,HR Executive,52244,0 +41192,Male,42,Diploma,3,4,84,46,25,9.0,3,2,Urban,HR Executive,59155,0 +41193,Male,55,High School,4,91,76,19,50,0.0,0,10,Urban,Data Analyst,109966,0 +41194,Other,38,PhD,7,97,62,72,87,4.0,4,19,Rural,Software Engineer,62712,1 +41195,Male,22,Bachelors,11,22,74,32,32,4.0,2,16,Rural,Software Engineer,136973,0 +41196,Male,28,Bachelors,10,69,55,53,66,2.0,6,7,Urban,ML Engineer,82471,0 +41197,Male,57,Masters,9,57,30,5,40,6.0,5,65,Semi-Urban,HR Executive,38212,0 +41198,Male,33,Masters,1,43,21,74,50,2.0,3,64,Urban,HR Executive,23510,0 +41199,Female,53,Bachelors,5,35,73,66,84,8.0,3,20,Urban,Data Analyst,125518,0 +41200,Male,24,PhD,8,76,81,78,63,1.0,2,70,Urban,Software Engineer,101006,1 +41201,Female,45,Bachelors,12,1,60,72,90,1.0,3,86,Semi-Urban,ML Engineer,95110,0 +41202,Male,44,Masters,2,75,32,0,49,9.0,0,63,Urban,ML Engineer,44769,0 +41203,Female,52,Diploma,18,86,61,80,98,1.0,7,23,Urban,ML Engineer,42609,1 +41204,Male,26,Bachelors,9,62,36,76,89,1.0,0,85,Rural,Software Engineer,84601,1 +41205,Female,51,High School,1,60,72,21,40,3.0,6,30,Semi-Urban,HR Executive,84782,0 +41206,Male,28,Diploma,0,60,77,12,46,6.0,3,89,Urban,Manager,136525,1 +41207,Female,42,Bachelors,2,91,3,92,18,2.0,7,21,Urban,Software Engineer,82116,0 +41208,Female,51,Masters,11,18,94,5,61,4.0,0,29,Urban,HR Executive,109280,0 +41209,Male,44,Masters,15,60,35,19,44,2.0,3,62,Urban,Software Engineer,44128,0 +41210,Male,40,Bachelors,0,7,1,90,38,4.0,3,14,Urban,ML Engineer,45103,0 +41211,Other,47,Bachelors,5,81,47,29,19,6.0,6,77,Semi-Urban,Manager,136259,0 +41212,Male,35,Bachelors,13,61,24,87,76,9.0,3,24,Urban,Software Engineer,144258,0 +41213,Female,44,High School,19,71,72,42,52,0.0,0,85,Rural,HR Executive,71581,1 +41214,Male,50,Bachelors,6,6,68,44,55,4.0,0,76,Urban,Manager,110783,0 +41215,Male,30,Masters,6,94,73,67,35,2.0,4,93,Rural,Software Engineer,23275,1 +41216,Male,35,Diploma,13,58,87,59,29,5.0,6,51,Semi-Urban,Software Engineer,94056,1 +41217,Male,36,Bachelors,10,63,20,82,97,8.0,3,31,Semi-Urban,Manager,29990,0 +41218,Male,27,High School,11,95,89,94,12,1.0,4,54,Semi-Urban,Software Engineer,72012,1 +41219,Male,55,Bachelors,3,47,47,42,87,4.0,3,69,Urban,HR Executive,126753,0 +41220,Other,58,Masters,19,28,52,28,80,7.0,4,31,Urban,HR Executive,38987,0 +41221,Female,59,PhD,4,78,27,81,60,0.0,2,65,Urban,ML Engineer,44424,1 +41222,Male,29,Bachelors,8,8,63,7,65,1.0,3,59,Semi-Urban,ML Engineer,120410,0 +41223,Male,35,Masters,16,70,43,33,35,9.0,2,39,Urban,HR Executive,115608,0 +41224,Female,42,Bachelors,10,43,90,69,42,6.0,5,38,Urban,Data Analyst,115901,0 +41225,Male,49,Diploma,5,60,71,58,1,0.0,4,0,Urban,Software Engineer,89954,0 +41226,Female,31,Masters,0,93,96,41,29,8.0,1,76,Rural,Software Engineer,149415,1 +41227,Male,26,Bachelors,5,23,22,60,16,8.0,5,55,Urban,Software Engineer,99676,0 +41228,Female,46,Diploma,18,62,71,62,27,0.0,6,95,Semi-Urban,Data Analyst,37806,1 +41229,Male,28,Masters,15,87,50,73,81,5.0,0,48,Semi-Urban,HR Executive,99389,1 +41230,Female,37,Masters,19,95,97,90,42,9.0,5,37,Urban,ML Engineer,130853,1 +41231,Male,33,Bachelors,9,0,40,90,56,7.0,7,78,Urban,ML Engineer,136843,0 +41232,Male,57,Bachelors,16,69,19,5,55,4.0,3,39,Urban,Manager,102360,0 +41233,Male,59,Diploma,19,87,33,61,81,7.0,2,78,Semi-Urban,HR Executive,59727,1 +41234,Male,43,Diploma,8,72,3,26,59,9.0,7,68,Semi-Urban,Manager,62679,0 +41235,Male,22,Bachelors,12,34,38,60,77,7.0,0,65,Rural,ML Engineer,54110,0 +41236,Female,42,Diploma,18,36,72,67,23,8.0,3,15,Urban,Manager,36214,0 +41237,Male,22,Diploma,6,82,89,2,84,4.0,1,33,Urban,Data Analyst,77763,0 +41238,Male,28,Bachelors,14,0,65,62,2,8.0,6,78,Semi-Urban,HR Executive,111296,0 +41239,Male,57,Bachelors,1,9,96,85,39,2.0,0,88,Semi-Urban,HR Executive,30982,1 +41240,Female,22,Masters,8,94,76,33,81,6.0,0,95,Rural,Software Engineer,63411,1 +41241,Female,53,PhD,14,57,95,86,63,9.0,6,77,Rural,HR Executive,83514,1 +41242,Female,56,Masters,16,18,96,3,48,2.0,1,33,Semi-Urban,ML Engineer,81882,0 +41243,Female,32,High School,14,65,30,94,79,7.0,2,23,Urban,ML Engineer,148389,0 +41244,Other,41,High School,11,17,23,4,55,9.0,2,64,Urban,ML Engineer,56282,0 +41245,Female,57,Diploma,15,43,91,61,63,5.0,1,43,Urban,Data Analyst,42610,0 +41246,Male,45,Diploma,1,93,73,9,30,6.0,4,79,Rural,Data Analyst,56546,1 +41247,Male,23,Masters,3,91,68,37,75,0.0,7,11,Urban,Data Analyst,147890,0 +41248,Male,21,High School,2,60,90,20,36,0.0,6,70,Rural,Software Engineer,114937,1 +41249,Other,43,Bachelors,18,68,12,99,67,5.0,2,16,Urban,ML Engineer,55604,0 +41250,Male,55,Bachelors,8,74,41,17,19,4.0,7,18,Semi-Urban,Manager,104802,0 +41251,Male,32,Bachelors,0,13,45,97,41,3.0,6,94,Urban,Manager,26761,1 +41252,Female,51,High School,0,96,70,81,37,5.0,3,50,Urban,Software Engineer,77888,1 +41253,Male,34,High School,18,85,67,12,35,2.0,7,80,Rural,Software Engineer,42987,1 +41254,Female,29,Masters,9,48,22,34,50,1.0,6,10,Semi-Urban,ML Engineer,95875,0 +41255,Female,42,Bachelors,9,52,88,99,19,4.0,0,19,Urban,ML Engineer,144867,1 +41256,Female,31,Diploma,9,72,12,51,27,8.0,5,45,Urban,HR Executive,126478,0 +41257,Female,47,Bachelors,7,71,53,5,18,9.0,6,40,Urban,Manager,145284,0 +41258,Female,28,Diploma,13,94,23,48,99,9.0,1,73,Semi-Urban,ML Engineer,56562,0 +41259,Female,53,PhD,12,67,89,82,41,2.0,5,29,Urban,Data Analyst,67738,1 +41260,Male,49,Bachelors,4,95,74,18,79,4.0,1,44,Urban,HR Executive,111605,0 +41261,Female,44,Bachelors,17,27,98,6,62,9.0,5,43,Semi-Urban,Software Engineer,137976,0 +41262,Female,54,Diploma,16,28,83,24,20,1.0,2,55,Urban,HR Executive,77191,0 +41263,Male,26,High School,5,30,66,24,83,6.0,6,58,Urban,Manager,100234,0 +41264,Male,24,High School,19,76,79,35,98,4.0,4,97,Rural,HR Executive,148310,1 +41265,Male,39,Diploma,4,79,43,53,49,7.0,3,52,Urban,Software Engineer,103587,0 +41266,Male,27,High School,12,80,16,8,74,0.0,6,60,Rural,ML Engineer,118582,0 +41267,Male,53,PhD,15,27,56,98,17,0.0,4,54,Urban,Data Analyst,68542,1 +41268,Female,24,PhD,11,5,99,41,72,4.0,7,75,Rural,Data Analyst,95620,0 +41269,Male,49,High School,12,1,82,58,16,1.0,7,2,Urban,Data Analyst,102612,0 +41270,Male,56,Bachelors,10,14,43,2,63,1.0,2,43,Urban,Data Analyst,77868,0 +41271,Male,36,Bachelors,12,19,99,59,24,1.0,2,6,Urban,Software Engineer,85093,0 +41272,Male,34,High School,2,0,62,80,74,4.0,6,90,Urban,HR Executive,45257,0 +41273,Male,43,Diploma,1,45,1,68,91,1.0,4,21,Rural,Manager,101273,0 +41274,Male,38,Masters,10,88,8,86,41,4.0,7,64,Urban,Software Engineer,68489,1 +41275,Female,21,Masters,10,81,59,1,74,0.0,4,29,Semi-Urban,Software Engineer,104395,0 +41276,Female,38,Bachelors,2,98,0,79,63,3.0,2,48,Urban,ML Engineer,107352,0 +41277,Female,30,Masters,4,42,87,1,48,4.0,7,38,Semi-Urban,Manager,118868,0 +41278,Male,58,Masters,3,70,2,78,14,5.0,6,67,Rural,Software Engineer,80540,0 +41279,Female,51,Bachelors,14,66,42,2,69,4.0,2,48,Rural,Data Analyst,59091,0 +41280,Female,37,Bachelors,12,25,69,83,13,8.0,3,1,Rural,Manager,91741,0 +41281,Other,29,Diploma,2,37,33,90,73,0.0,7,97,Semi-Urban,Data Analyst,147857,1 +41282,Male,34,Diploma,8,7,44,19,10,5.0,4,68,Urban,ML Engineer,44294,0 +41283,Male,25,Masters,1,33,93,50,20,6.0,2,59,Urban,ML Engineer,40363,1 +41284,Male,40,Masters,3,43,60,29,58,3.0,4,59,Urban,Manager,78549,0 +41285,Female,52,Bachelors,15,37,23,50,37,6.0,3,50,Semi-Urban,HR Executive,24900,0 +41286,Female,36,Bachelors,7,77,4,33,20,1.0,5,50,Rural,HR Executive,146477,0 +41287,Male,47,Bachelors,6,72,27,80,67,5.0,0,25,Urban,ML Engineer,126968,0 +41288,Male,41,Bachelors,0,64,77,85,63,6.0,0,29,Semi-Urban,Software Engineer,50484,1 +41289,Female,53,Diploma,2,68,51,9,30,1.0,2,34,Semi-Urban,Software Engineer,112216,0 +41290,Female,45,High School,2,1,92,66,79,0.0,3,26,Semi-Urban,Manager,129313,0 +41291,Female,40,High School,19,2,10,83,24,8.0,2,76,Rural,Manager,103017,0 +41292,Female,23,Bachelors,13,44,87,28,43,1.0,4,39,Urban,Manager,59408,0 +41293,Male,27,Bachelors,19,49,56,28,24,6.0,2,90,Semi-Urban,Manager,78007,0 +41294,Male,29,Bachelors,10,61,96,10,54,8.0,1,9,Urban,Data Analyst,20219,0 +41295,Female,26,Bachelors,19,13,81,41,60,4.0,1,5,Urban,Software Engineer,140636,0 +41296,Female,30,Bachelors,17,48,81,78,71,0.0,1,15,Semi-Urban,Data Analyst,143901,0 +41297,Female,37,High School,4,37,39,81,10,0.0,7,29,Rural,Data Analyst,71599,0 +41298,Male,43,Masters,17,62,40,38,67,6.0,1,86,Rural,Data Analyst,84064,0 +41299,Male,48,Masters,14,73,11,75,25,1.0,0,19,Urban,HR Executive,24774,0 +41300,Male,24,Bachelors,0,8,8,25,37,9.0,4,61,Urban,ML Engineer,138719,0 +41301,Male,52,Diploma,13,8,46,93,98,4.0,3,94,Urban,Software Engineer,91535,1 +41302,Male,21,Bachelors,3,38,63,87,63,1.0,6,76,Semi-Urban,ML Engineer,77902,1 +41303,Female,25,Bachelors,14,26,2,63,55,7.0,5,28,Urban,HR Executive,141383,0 +41304,Female,32,Bachelors,14,60,38,79,93,7.0,6,96,Rural,Software Engineer,111675,1 +41305,Male,21,Bachelors,14,20,77,17,35,5.0,1,35,Rural,Software Engineer,128657,0 +41306,Male,26,Bachelors,7,72,62,9,97,5.0,6,74,Urban,Software Engineer,20577,0 +41307,Female,24,Bachelors,17,50,61,48,81,3.0,0,3,Semi-Urban,Data Analyst,71595,0 +41308,Male,50,Masters,1,28,21,29,72,1.0,5,10,Urban,Manager,50504,0 +41309,Female,31,Bachelors,0,44,26,3,6,5.0,7,77,Semi-Urban,Software Engineer,102852,0 +41310,Male,37,Bachelors,2,51,64,66,56,7.0,7,65,Urban,Manager,143780,1 +41311,Male,58,Bachelors,13,21,81,64,39,9.0,3,48,Urban,Data Analyst,96127,0 +41312,Male,48,Masters,7,0,38,6,45,8.0,7,65,Urban,ML Engineer,114521,0 +41313,Male,26,Bachelors,8,78,40,53,93,7.0,0,55,Rural,ML Engineer,115134,0 +41314,Male,54,Bachelors,16,88,44,15,27,8.0,0,76,Urban,Data Analyst,123399,0 +41315,Female,38,Diploma,13,73,32,25,53,1.0,1,10,Rural,ML Engineer,103755,0 +41316,Female,48,Bachelors,16,80,54,57,88,0.0,4,68,Rural,Manager,104974,1 +41317,Other,29,PhD,1,94,63,73,6,6.0,3,28,Rural,ML Engineer,111020,1 +41318,Female,46,Diploma,8,97,32,49,99,7.0,0,11,Semi-Urban,Software Engineer,50198,0 +41319,Male,25,PhD,9,18,1,89,24,6.0,3,95,Urban,Data Analyst,118236,0 +41320,Male,21,High School,8,60,10,93,7,6.0,7,50,Urban,ML Engineer,109271,0 +41321,Female,26,Bachelors,14,93,24,58,37,1.0,3,33,Urban,Manager,47192,0 +41322,Male,26,PhD,13,25,4,45,37,6.0,3,59,Urban,HR Executive,70718,0 +41323,Other,27,Masters,19,57,36,37,84,3.0,7,69,Urban,Data Analyst,106353,0 +41324,Male,26,Masters,12,75,56,76,46,3.0,7,68,Urban,Manager,50871,1 +41325,Female,30,Masters,11,55,29,30,60,9.0,6,15,Urban,ML Engineer,66296,0 +41326,Other,52,Bachelors,8,47,13,1,46,2.0,3,13,Urban,Software Engineer,21516,0 +41327,Male,40,Diploma,1,8,44,55,90,7.0,0,22,Urban,Software Engineer,133637,0 +41328,Male,23,High School,16,8,8,41,86,5.0,6,83,Urban,ML Engineer,33905,0 +41329,Male,54,Bachelors,1,76,0,56,93,8.0,3,73,Rural,ML Engineer,78276,0 +41330,Male,33,High School,3,93,34,9,72,8.0,0,6,Rural,HR Executive,149273,0 +41331,Female,37,Diploma,5,70,15,84,39,4.0,0,22,Urban,Manager,23652,0 +41332,Male,46,Diploma,3,7,80,4,68,2.0,3,12,Urban,Manager,142618,0 +41333,Male,41,High School,9,5,24,36,55,8.0,4,33,Semi-Urban,Manager,104608,0 +41334,Female,25,Masters,1,91,7,64,42,1.0,6,1,Urban,HR Executive,25176,0 +41335,Other,51,Masters,16,81,93,22,86,4.0,1,0,Rural,ML Engineer,29716,0 +41336,Male,32,Masters,12,77,96,68,2,9.0,0,38,Semi-Urban,ML Engineer,102055,1 +41337,Female,45,Bachelors,4,99,43,54,39,4.0,4,26,Urban,Data Analyst,94356,0 +41338,Male,29,Bachelors,7,21,19,98,89,6.0,5,81,Urban,Software Engineer,147618,0 +41339,Female,29,Bachelors,9,56,94,5,45,6.0,5,49,Semi-Urban,HR Executive,35725,0 +41340,Male,37,Diploma,16,48,58,15,89,4.0,6,91,Urban,HR Executive,110173,0 +41341,Other,33,Masters,19,61,25,85,60,3.0,1,95,Urban,ML Engineer,68073,1 +41342,Female,24,Bachelors,18,92,98,68,80,9.0,4,42,Urban,HR Executive,72004,1 +41343,Male,57,Bachelors,2,58,57,80,14,9.0,1,35,Urban,Manager,67365,0 +41344,Male,25,Bachelors,4,76,1,97,51,2.0,3,42,Urban,HR Executive,145139,0 +41345,Male,58,Bachelors,4,31,99,79,43,6.0,1,42,Semi-Urban,Data Analyst,60979,1 +41346,Female,45,Bachelors,5,35,28,28,93,3.0,7,31,Urban,Software Engineer,47737,0 +41347,Female,44,Bachelors,15,4,33,57,45,6.0,3,64,Urban,ML Engineer,21484,0 +41348,Female,56,Bachelors,15,2,5,30,7,3.0,1,75,Urban,Software Engineer,102132,0 +41349,Female,51,Diploma,10,31,20,66,71,0.0,4,15,Rural,Manager,56995,0 +41350,Female,25,Bachelors,7,47,62,70,35,5.0,2,29,Urban,Manager,27667,0 +41351,Other,31,High School,19,20,39,53,82,8.0,6,97,Rural,HR Executive,104904,0 +41352,Female,32,Bachelors,5,51,78,61,37,8.0,4,8,Urban,Software Engineer,52011,0 +41353,Male,48,Bachelors,6,83,26,35,31,0.0,4,14,Semi-Urban,Software Engineer,133459,0 +41354,Female,25,Diploma,11,9,67,17,57,7.0,3,56,Urban,HR Executive,83135,0 +41355,Male,48,High School,9,38,98,66,77,2.0,0,82,Urban,ML Engineer,20766,1 +41356,Other,42,Bachelors,12,11,9,70,14,7.0,0,74,Urban,Manager,35513,0 +41357,Male,46,Bachelors,0,60,62,53,43,4.0,7,8,Urban,Data Analyst,64814,0 +41358,Male,46,Bachelors,9,56,13,83,52,4.0,7,55,Rural,ML Engineer,30882,0 +41359,Male,36,Bachelors,14,37,87,22,1,4.0,0,67,Urban,Software Engineer,83599,0 +41360,Female,56,High School,15,3,63,83,3,1.0,0,4,Semi-Urban,ML Engineer,37429,0 +41361,Male,39,Bachelors,17,19,56,30,16,4.0,3,44,Urban,Manager,78275,0 +41362,Other,34,Diploma,1,82,38,82,34,6.0,6,11,Urban,ML Engineer,48729,0 +41363,Male,37,PhD,17,47,93,55,9,7.0,1,48,Rural,ML Engineer,47871,1 +41364,Male,55,High School,17,72,95,13,21,1.0,1,1,Urban,ML Engineer,26967,0 +41365,Male,54,Diploma,2,85,38,35,1,6.0,3,85,Urban,Software Engineer,36657,1 +41366,Male,21,Masters,4,78,34,96,46,1.0,2,34,Urban,ML Engineer,74230,1 +41367,Male,56,Bachelors,5,91,55,19,81,8.0,2,46,Semi-Urban,ML Engineer,59624,0 +41368,Male,23,Bachelors,16,30,92,56,70,3.0,1,75,Urban,Software Engineer,69865,1 +41369,Male,21,High School,10,87,47,86,40,7.0,2,45,Urban,Data Analyst,36249,1 +41370,Male,23,Diploma,14,81,40,1,25,4.0,2,77,Urban,Software Engineer,126343,0 +41371,Male,35,Diploma,12,74,71,31,53,3.0,7,90,Semi-Urban,ML Engineer,64817,1 +41372,Female,54,Masters,10,86,25,1,30,2.0,3,74,Rural,Data Analyst,132096,0 +41373,Male,53,Diploma,14,62,34,85,41,6.0,2,27,Urban,Manager,71680,0 +41374,Male,59,Bachelors,13,26,85,66,79,2.0,4,32,Urban,Software Engineer,32580,0 +41375,Male,54,Diploma,9,70,34,98,9,7.0,1,42,Urban,HR Executive,59703,1 +41376,Male,50,Diploma,19,30,62,93,82,4.0,1,31,Urban,Data Analyst,103252,0 +41377,Male,32,Bachelors,0,66,38,17,89,4.0,4,23,Semi-Urban,Manager,67350,0 +41378,Female,58,Bachelors,10,0,91,72,25,8.0,1,30,Urban,ML Engineer,61505,0 +41379,Other,39,High School,3,80,26,41,77,4.0,4,85,Urban,HR Executive,133312,0 +41380,Male,31,PhD,12,5,80,40,42,9.0,6,36,Urban,Data Analyst,84673,0 +41381,Male,26,Diploma,0,63,23,4,13,5.0,5,8,Urban,Software Engineer,83025,0 +41382,Male,38,Bachelors,16,60,55,42,44,4.0,3,56,Rural,Manager,89065,0 +41383,Male,46,Diploma,19,61,24,40,13,9.0,4,49,Rural,ML Engineer,148074,0 +41384,Male,54,Diploma,5,75,81,49,31,6.0,4,57,Rural,ML Engineer,90235,1 +41385,Male,41,High School,5,66,76,18,37,0.0,7,88,Rural,Data Analyst,116121,1 +41386,Female,48,Bachelors,11,90,95,26,67,1.0,2,28,Rural,Data Analyst,51969,0 +41387,Male,35,Diploma,4,61,31,84,3,5.0,0,48,Urban,Software Engineer,132183,0 +41388,Male,52,PhD,13,73,2,22,56,0.0,3,40,Urban,Manager,131790,0 +41389,Female,39,Bachelors,0,87,89,57,72,8.0,5,34,Urban,Manager,47313,1 +41390,Male,25,Diploma,8,7,57,52,89,4.0,2,34,Semi-Urban,Data Analyst,67926,0 +41391,Male,37,Bachelors,0,54,60,96,99,5.0,5,56,Rural,HR Executive,53141,1 +41392,Female,32,Masters,11,82,64,47,18,6.0,3,90,Urban,Manager,85000,1 +41393,Male,24,Masters,2,72,46,48,43,4.0,6,56,Urban,HR Executive,86826,0 +41394,Female,54,Bachelors,10,37,65,50,75,0.0,1,85,Rural,HR Executive,130042,0 +41395,Male,55,Diploma,13,94,60,69,64,6.0,5,47,Rural,Software Engineer,55975,1 +41396,Male,53,Bachelors,11,72,68,62,14,5.0,4,18,Semi-Urban,HR Executive,135027,0 +41397,Female,38,Bachelors,5,82,81,41,17,5.0,3,56,Semi-Urban,HR Executive,54774,1 +41398,Male,26,Diploma,8,80,18,51,38,0.0,5,35,Urban,Software Engineer,105063,0 +41399,Male,46,Masters,17,36,66,7,38,3.0,2,39,Rural,Manager,23743,0 +41400,Male,33,Masters,17,8,98,53,36,9.0,2,57,Urban,Data Analyst,61091,0 +41401,Female,54,Diploma,9,10,4,95,50,3.0,6,52,Urban,Software Engineer,29534,0 +41402,Female,26,High School,19,49,52,72,35,1.0,6,36,Urban,HR Executive,62565,0 +41403,Male,59,Diploma,13,87,4,85,69,2.0,0,76,Semi-Urban,Software Engineer,114320,1 +41404,Female,40,PhD,14,74,14,27,44,0.0,5,54,Rural,ML Engineer,56065,0 +41405,Female,25,Bachelors,18,10,66,39,40,9.0,7,77,Urban,Data Analyst,124760,0 +41406,Other,25,Bachelors,1,82,96,84,52,2.0,6,28,Urban,Manager,29527,1 +41407,Male,46,Diploma,9,75,67,88,70,4.0,5,67,Rural,Data Analyst,63818,1 +41408,Female,47,Bachelors,8,27,70,19,58,0.0,3,61,Semi-Urban,Data Analyst,32193,0 +41409,Male,48,Masters,8,66,22,79,62,7.0,6,64,Urban,ML Engineer,145314,0 +41410,Female,42,Masters,6,80,31,46,16,6.0,5,87,Urban,Data Analyst,50779,1 +41411,Male,27,PhD,3,91,61,25,68,0.0,7,69,Urban,ML Engineer,79812,1 +41412,Male,40,Masters,19,77,87,12,69,4.0,1,97,Semi-Urban,ML Engineer,103806,1 +41413,Female,51,Diploma,6,13,0,35,5,0.0,7,85,Urban,Data Analyst,121554,0 +41414,Female,56,Masters,14,78,90,28,30,4.0,2,16,Urban,Data Analyst,149676,0 +41415,Male,44,Masters,1,56,18,80,63,6.0,4,19,Urban,Software Engineer,57102,0 +41416,Male,50,Bachelors,7,23,9,22,40,8.0,6,63,Rural,Manager,118261,0 +41417,Male,26,High School,19,31,62,40,66,7.0,3,67,Urban,Software Engineer,65518,0 +41418,Male,55,PhD,19,61,84,49,74,2.0,6,46,Rural,ML Engineer,23807,1 +41419,Male,27,Diploma,12,63,56,72,12,1.0,2,6,Rural,Software Engineer,143353,0 +41420,Male,25,Bachelors,0,89,42,78,88,7.0,3,74,Urban,Manager,46515,1 +41421,Male,51,High School,11,99,98,2,65,1.0,2,88,Urban,Manager,89442,1 +41422,Male,54,Diploma,1,64,41,89,98,3.0,6,1,Semi-Urban,ML Engineer,58590,0 +41423,Male,28,Bachelors,11,57,28,84,96,6.0,6,52,Semi-Urban,Data Analyst,122320,0 +41424,Female,35,Diploma,17,96,19,39,94,2.0,7,74,Semi-Urban,HR Executive,104975,0 +41425,Male,40,Masters,11,11,32,90,94,0.0,6,77,Semi-Urban,Data Analyst,145138,0 +41426,Female,31,Masters,18,16,1,85,27,5.0,2,55,Urban,Manager,136651,0 +41427,Female,49,High School,15,76,82,32,28,4.0,5,84,Rural,Software Engineer,118471,1 +41428,Male,48,Bachelors,19,11,52,84,43,7.0,1,82,Semi-Urban,Data Analyst,68599,0 +41429,Male,38,Bachelors,7,5,63,48,40,6.0,0,5,Semi-Urban,Data Analyst,134768,0 +41430,Male,52,Diploma,5,82,79,1,93,1.0,0,6,Rural,Software Engineer,111528,0 +41431,Male,39,Bachelors,8,56,70,67,58,2.0,4,8,Semi-Urban,ML Engineer,21643,0 +41432,Male,40,Bachelors,18,56,75,97,9,7.0,1,49,Semi-Urban,ML Engineer,113665,1 +41433,Male,21,Diploma,0,20,67,7,30,8.0,4,41,Urban,Manager,74090,0 +41434,Female,32,High School,13,18,84,26,79,9.0,5,48,Urban,HR Executive,90569,0 +41435,Male,56,Bachelors,19,37,30,3,24,4.0,0,58,Rural,Manager,145913,0 +41436,Female,24,Bachelors,15,21,70,43,50,6.0,0,76,Urban,HR Executive,131770,0 +41437,Male,43,Bachelors,16,62,76,46,80,5.0,4,27,Urban,Manager,73827,0 +41438,Male,36,High School,13,26,81,37,48,9.0,1,32,Urban,ML Engineer,95436,0 +41439,Male,44,Bachelors,0,57,55,91,58,0.0,7,13,Urban,Manager,69402,0 +41440,Male,39,Bachelors,13,94,30,37,93,6.0,5,40,Urban,HR Executive,127765,0 +41441,Female,53,Bachelors,8,96,16,30,89,4.0,3,49,Semi-Urban,HR Executive,119662,0 +41442,Male,37,Bachelors,3,18,44,34,1,5.0,6,56,Semi-Urban,Software Engineer,95947,0 +41443,Male,23,Bachelors,14,76,99,85,90,7.0,6,20,Urban,Software Engineer,86354,1 +41444,Male,38,Masters,1,8,2,63,26,1.0,3,0,Semi-Urban,Manager,69593,0 +41445,Male,35,Masters,6,65,19,5,21,3.0,0,12,Semi-Urban,Manager,61751,0 +41446,Female,34,Diploma,3,56,9,28,77,1.0,6,5,Semi-Urban,ML Engineer,87478,0 +41447,Female,50,Bachelors,14,79,53,61,35,7.0,7,10,Rural,Software Engineer,79007,0 +41448,Female,45,Bachelors,17,66,46,45,55,7.0,5,54,Urban,HR Executive,87695,0 +41449,Male,28,Diploma,12,37,80,6,1,6.0,3,54,Urban,Manager,137106,0 +41450,Male,46,High School,11,32,61,44,52,9.0,6,33,Semi-Urban,ML Engineer,90046,0 +41451,Male,30,Bachelors,5,1,6,46,44,9.0,2,9,Urban,Data Analyst,114469,0 +41452,Female,30,High School,2,6,50,5,12,6.0,3,28,Urban,HR Executive,97193,0 +41453,Male,34,Diploma,12,10,56,63,26,2.0,0,66,Rural,Manager,41124,0 +41454,Other,24,High School,4,31,40,34,97,0.0,4,13,Urban,Manager,109751,0 +41455,Other,50,Bachelors,18,45,49,94,31,2.0,5,41,Urban,Manager,101717,0 +41456,Female,44,High School,3,26,28,48,29,3.0,5,62,Urban,Manager,80793,0 +41457,Male,22,High School,7,42,96,96,47,5.0,0,21,Urban,HR Executive,56363,1 +41458,Male,38,High School,9,60,55,21,34,6.0,5,45,Semi-Urban,Data Analyst,62104,0 +41459,Female,36,Bachelors,7,11,5,87,25,1.0,4,16,Urban,Data Analyst,87750,0 +41460,Female,59,Diploma,8,34,3,35,1,3.0,7,33,Urban,HR Executive,29335,0 +41461,Female,50,PhD,18,81,63,36,46,3.0,5,81,Semi-Urban,Data Analyst,78130,1 +41462,Male,30,High School,15,35,96,27,97,2.0,2,20,Urban,HR Executive,49140,0 +41463,Female,24,Bachelors,17,76,38,61,53,8.0,3,77,Urban,ML Engineer,65260,1 +41464,Male,44,Masters,11,66,15,33,42,4.0,6,68,Urban,Software Engineer,74706,0 +41465,Male,21,Diploma,14,67,93,86,21,3.0,4,9,Urban,ML Engineer,20853,1 +41466,Female,45,Bachelors,14,15,81,28,61,7.0,7,8,Rural,Manager,47712,0 +41467,Male,49,Bachelors,4,6,43,93,90,4.0,4,65,Semi-Urban,Manager,34767,0 +41468,Female,45,Bachelors,1,72,91,43,36,9.0,6,57,Urban,Manager,39336,1 +41469,Male,54,Diploma,14,18,55,63,4,7.0,7,48,Semi-Urban,ML Engineer,89581,0 +41470,Male,58,Masters,9,21,83,49,32,9.0,6,2,Urban,Manager,43538,0 +41471,Male,47,Diploma,5,6,21,53,28,4.0,2,48,Semi-Urban,ML Engineer,118232,0 +41472,Male,25,Bachelors,16,8,32,41,1,2.0,5,23,Semi-Urban,Manager,22872,0 +41473,Male,42,Bachelors,15,57,16,17,94,8.0,4,39,Urban,Software Engineer,81735,0 +41474,Male,39,Masters,5,77,68,27,50,6.0,0,10,Urban,Data Analyst,103791,0 +41475,Female,42,Masters,13,87,51,96,21,6.0,3,74,Urban,ML Engineer,74684,1 +41476,Male,28,Diploma,4,57,50,88,13,1.0,3,61,Urban,HR Executive,63630,1 +41477,Female,45,Bachelors,10,60,45,45,90,9.0,5,92,Rural,Manager,24626,1 +41478,Male,56,High School,8,33,48,1,25,0.0,7,72,Urban,Software Engineer,94306,0 +41479,Female,47,Bachelors,16,18,27,59,29,2.0,5,42,Semi-Urban,Data Analyst,93980,0 +41480,Male,39,High School,3,44,77,91,35,3.0,6,5,Urban,Data Analyst,135653,0 +41481,Male,49,Masters,12,50,19,57,2,1.0,3,75,Rural,ML Engineer,64154,0 +41482,Female,49,Masters,7,51,44,42,69,6.0,1,96,Semi-Urban,Data Analyst,103834,0 +41483,Male,36,Bachelors,18,37,72,24,51,7.0,4,43,Urban,HR Executive,136749,0 +41484,Other,53,Bachelors,13,57,28,36,15,8.0,1,19,Urban,HR Executive,59001,0 +41485,Male,41,Bachelors,5,84,44,26,16,0.0,5,33,Urban,Data Analyst,50445,0 +41486,Female,37,Bachelors,8,83,60,63,17,3.0,5,89,Rural,ML Engineer,61866,1 +41487,Male,55,High School,15,51,63,30,19,7.0,4,80,Urban,Software Engineer,110920,0 +41488,Male,47,High School,11,87,80,44,89,2.0,1,64,Urban,Manager,75470,1 +41489,Male,59,Masters,14,72,98,48,93,7.0,6,23,Urban,HR Executive,41303,1 +41490,Male,58,Masters,1,76,68,88,8,0.0,3,43,Semi-Urban,Software Engineer,65983,1 +41491,Male,58,Bachelors,0,20,58,73,59,4.0,3,71,Rural,Data Analyst,93063,0 +41492,Male,58,PhD,6,36,22,4,65,9.0,7,63,Urban,ML Engineer,48139,0 +41493,Male,23,Diploma,2,50,36,50,29,9.0,6,4,Urban,Manager,129416,0 +41494,Female,42,Masters,10,67,28,84,75,2.0,1,59,Rural,Manager,134398,0 +41495,Female,47,High School,1,59,83,22,32,8.0,2,10,Urban,Data Analyst,74329,0 +41496,Male,37,Bachelors,15,69,20,46,86,8.0,2,82,Urban,ML Engineer,117821,0 +41497,Male,28,Bachelors,8,21,74,54,48,7.0,3,80,Urban,HR Executive,143934,0 +41498,Male,56,Masters,9,27,32,37,12,8.0,4,59,Urban,HR Executive,112228,0 +41499,Female,22,Masters,0,70,70,37,63,6.0,0,30,Urban,Manager,83893,0 +41500,Male,40,Bachelors,18,1,71,9,10,6.0,3,75,Semi-Urban,Software Engineer,20679,0 +41501,Female,59,Bachelors,1,78,16,38,7,6.0,4,50,Semi-Urban,Manager,138261,0 +41502,Male,34,Bachelors,17,88,64,87,73,1.0,3,56,Urban,Manager,122765,1 +41503,Male,31,Masters,5,76,33,92,3,5.0,1,41,Rural,Manager,63190,1 +41504,Male,25,Bachelors,18,9,91,11,94,7.0,0,2,Rural,Manager,142685,0 +41505,Male,26,PhD,6,46,0,11,39,5.0,1,36,Urban,Manager,87099,0 +41506,Male,46,Masters,18,51,5,22,83,4.0,7,73,Urban,HR Executive,28220,0 +41507,Female,51,Bachelors,6,82,34,57,62,1.0,4,17,Urban,HR Executive,77397,0 +41508,Male,53,Bachelors,11,3,1,43,25,3.0,4,14,Urban,Software Engineer,122313,0 +41509,Male,49,Masters,19,0,89,99,86,8.0,0,1,Rural,Data Analyst,68552,0 +41510,Female,47,Bachelors,13,78,94,4,53,6.0,3,67,Rural,HR Executive,97153,1 +41511,Male,21,High School,18,65,94,49,6,9.0,0,93,Semi-Urban,Data Analyst,67131,1 +41512,Male,27,Bachelors,1,13,39,14,0,8.0,1,76,Urban,HR Executive,87668,0 +41513,Female,50,Bachelors,5,11,91,70,94,0.0,6,89,Urban,ML Engineer,88365,1 +41514,Female,25,Bachelors,18,77,47,23,31,4.0,4,8,Semi-Urban,ML Engineer,117539,0 +41515,Male,57,Bachelors,11,59,83,90,67,1.0,7,26,Rural,ML Engineer,47882,1 +41516,Female,28,High School,0,87,22,98,85,7.0,2,83,Urban,HR Executive,147638,1 +41517,Male,39,Masters,17,67,88,48,60,5.0,2,23,Urban,HR Executive,124510,0 +41518,Male,50,Bachelors,16,0,61,55,72,3.0,0,19,Rural,Manager,113673,0 +41519,Male,59,Masters,10,79,39,3,90,6.0,6,80,Urban,HR Executive,45861,0 +41520,Male,31,Bachelors,19,46,8,89,78,9.0,7,6,Semi-Urban,Software Engineer,63174,0 +41521,Female,44,Masters,6,19,1,23,37,5.0,7,24,Urban,Manager,115025,0 +41522,Female,35,Bachelors,6,94,7,77,53,1.0,5,38,Rural,Manager,51724,0 +41523,Male,22,Diploma,10,28,91,44,32,7.0,1,77,Rural,HR Executive,135512,1 +41524,Male,38,Bachelors,9,51,76,90,69,4.0,0,33,Semi-Urban,ML Engineer,129649,1 +41525,Female,48,Bachelors,8,92,56,67,89,6.0,7,35,Urban,HR Executive,116310,1 +41526,Female,57,Masters,13,9,27,72,65,9.0,0,5,Urban,HR Executive,23251,0 +41527,Male,43,Bachelors,5,57,48,52,91,7.0,2,5,Urban,Data Analyst,67733,0 +41528,Male,40,Bachelors,11,97,72,6,61,7.0,3,79,Urban,Data Analyst,139436,1 +41529,Female,22,High School,16,73,91,21,43,4.0,0,63,Urban,Data Analyst,107974,1 +41530,Female,42,PhD,11,16,65,79,29,2.0,4,22,Rural,Data Analyst,108373,0 +41531,Male,24,PhD,8,7,81,87,42,9.0,5,88,Urban,Manager,136773,1 +41532,Female,41,Diploma,1,50,71,54,10,9.0,1,77,Urban,Software Engineer,55544,1 +41533,Male,27,High School,7,82,27,58,13,6.0,4,28,Rural,HR Executive,95278,0 +41534,Male,54,Bachelors,13,96,28,59,21,0.0,2,48,Rural,Manager,147319,0 +41535,Male,49,Bachelors,14,94,39,61,40,4.0,0,32,Semi-Urban,HR Executive,42568,0 +41536,Male,46,Diploma,6,86,63,31,85,2.0,4,21,Urban,HR Executive,52269,0 +41537,Female,25,Masters,16,67,67,45,95,8.0,3,18,Rural,Software Engineer,85809,0 +41538,Male,32,Bachelors,14,66,6,23,34,3.0,4,50,Urban,Software Engineer,129928,0 +41539,Male,50,Diploma,6,86,78,51,20,4.0,4,55,Urban,HR Executive,68755,1 +41540,Female,43,Bachelors,17,67,29,43,32,0.0,1,89,Rural,Software Engineer,66769,0 +41541,Male,21,Diploma,12,76,84,67,11,6.0,7,83,Urban,HR Executive,71650,1 +41542,Female,56,Diploma,9,99,57,65,69,5.0,2,95,Semi-Urban,HR Executive,92592,1 +41543,Female,52,Bachelors,11,44,51,75,22,2.0,0,42,Urban,Manager,42166,0 +41544,Male,27,Diploma,16,47,1,27,49,2.0,5,59,Urban,ML Engineer,123496,0 +41545,Male,41,Masters,4,90,35,15,70,8.0,1,12,Urban,HR Executive,109940,0 +41546,Female,38,Bachelors,3,27,47,70,57,9.0,2,52,Rural,Manager,127582,0 +41547,Male,27,High School,17,73,55,69,64,7.0,6,61,Rural,Data Analyst,143377,1 +41548,Male,40,Masters,13,34,85,22,56,9.0,4,86,Semi-Urban,Data Analyst,112583,0 +41549,Female,59,Masters,10,82,33,35,75,5.0,0,7,Urban,Manager,122744,0 +41550,Male,24,Diploma,12,40,98,16,12,5.0,3,70,Urban,Software Engineer,111486,0 +41551,Male,40,Bachelors,6,94,16,87,80,3.0,6,9,Urban,ML Engineer,35187,0 +41552,Female,25,Bachelors,8,78,95,78,37,4.0,1,29,Urban,Manager,131569,1 +41553,Female,30,Diploma,6,9,47,58,14,2.0,4,25,Urban,ML Engineer,70316,0 +41554,Male,26,Diploma,10,19,18,96,91,5.0,5,85,Rural,HR Executive,73776,0 +41555,Male,43,Diploma,2,20,90,40,75,3.0,2,63,Urban,ML Engineer,74043,0 +41556,Male,25,Masters,18,77,25,20,82,9.0,0,87,Rural,ML Engineer,23019,0 +41557,Female,43,Bachelors,3,9,96,62,95,9.0,3,17,Urban,Manager,131627,0 +41558,Female,32,Bachelors,8,89,42,45,17,6.0,6,94,Rural,Software Engineer,50759,1 +41559,Male,47,Masters,5,10,48,5,0,2.0,3,97,Urban,Data Analyst,85154,0 +41560,Female,46,Diploma,10,72,56,47,24,9.0,2,31,Urban,HR Executive,118387,0 +41561,Male,30,High School,7,47,43,19,54,8.0,2,19,Urban,Data Analyst,93780,0 +41562,Female,25,Bachelors,13,24,58,33,6,7.0,7,74,Urban,Data Analyst,136934,0 +41563,Male,46,PhD,19,18,66,88,35,9.0,1,20,Urban,HR Executive,65910,0 +41564,Female,50,Masters,15,65,56,6,61,1.0,0,8,Urban,Software Engineer,116837,0 +41565,Female,49,Diploma,4,49,42,51,21,7.0,1,55,Urban,ML Engineer,126112,0 +41566,Female,36,Bachelors,8,45,51,21,19,5.0,2,11,Semi-Urban,HR Executive,84203,0 +41567,Female,41,Bachelors,10,94,84,94,21,8.0,1,8,Semi-Urban,Manager,139276,1 +41568,Female,27,Masters,16,2,56,43,87,4.0,1,8,Urban,Manager,29553,0 +41569,Female,41,Bachelors,19,23,34,55,34,8.0,3,56,Urban,Data Analyst,64962,0 +41570,Female,56,Bachelors,5,34,45,94,99,1.0,2,45,Urban,Software Engineer,107729,0 +41571,Female,56,Diploma,0,45,2,7,66,4.0,7,71,Urban,Data Analyst,37369,0 +41572,Female,33,Bachelors,4,61,19,38,42,1.0,0,87,Urban,HR Executive,76439,0 +41573,Male,36,Bachelors,10,65,12,14,69,8.0,1,7,Urban,Data Analyst,117673,0 +41574,Male,37,Bachelors,16,2,29,72,0,8.0,6,2,Rural,HR Executive,99655,0 +41575,Male,27,Masters,18,72,2,70,48,7.0,5,84,Semi-Urban,ML Engineer,149042,0 +41576,Male,36,Diploma,3,88,12,23,73,9.0,3,10,Semi-Urban,HR Executive,51639,0 +41577,Female,52,Diploma,11,0,19,35,55,1.0,4,32,Semi-Urban,Software Engineer,110658,0 +41578,Male,58,Bachelors,12,63,83,66,45,0.0,1,52,Rural,Data Analyst,98394,1 +41579,Male,56,Bachelors,1,9,96,70,12,9.0,3,80,Urban,ML Engineer,117819,1 +41580,Male,34,Diploma,15,31,3,67,56,0.0,0,2,Rural,HR Executive,44768,0 +41581,Male,36,High School,18,4,24,15,0,1.0,3,89,Semi-Urban,Software Engineer,121164,0 +41582,Male,31,Bachelors,8,46,54,50,64,1.0,3,22,Rural,ML Engineer,90460,0 +41583,Female,34,Diploma,6,96,47,60,67,5.0,3,66,Semi-Urban,HR Executive,142356,1 +41584,Female,52,Bachelors,13,67,55,9,7,8.0,7,82,Rural,Manager,148086,0 +41585,Male,33,Diploma,9,67,32,55,1,2.0,0,57,Urban,HR Executive,66209,0 +41586,Male,21,High School,16,70,77,36,92,1.0,6,30,Semi-Urban,Manager,86231,0 +41587,Female,59,Masters,10,59,8,60,30,3.0,4,72,Urban,Data Analyst,76807,0 +41588,Female,59,High School,12,30,20,86,99,3.0,0,93,Semi-Urban,HR Executive,85824,0 +41589,Male,50,Bachelors,0,69,65,97,64,1.0,5,22,Rural,Data Analyst,144466,1 +41590,Male,44,Bachelors,15,88,65,0,56,6.0,7,45,Rural,Manager,114413,0 +41591,Male,37,Masters,3,76,65,49,4,7.0,2,14,Urban,Software Engineer,30735,0 +41592,Male,35,Masters,17,11,95,99,10,2.0,6,29,Urban,Manager,68299,0 +41593,Male,51,High School,11,50,65,2,71,1.0,4,58,Urban,Software Engineer,139207,0 +41594,Female,50,Masters,18,51,35,40,47,2.0,3,29,Urban,Software Engineer,113885,0 +41595,Female,59,High School,15,97,54,33,94,6.0,2,23,Urban,ML Engineer,145574,0 +41596,Male,25,High School,16,30,91,40,63,9.0,4,99,Rural,Manager,87881,1 +41597,Female,29,Bachelors,16,76,57,35,50,4.0,0,33,Urban,ML Engineer,78059,0 +41598,Other,56,Diploma,1,9,43,77,91,7.0,1,18,Urban,HR Executive,74021,0 +41599,Female,24,High School,15,21,60,43,13,3.0,4,13,Rural,ML Engineer,114816,0 +41600,Female,24,High School,1,0,88,93,86,3.0,4,96,Rural,HR Executive,147406,1 +41601,Female,21,Diploma,0,8,80,28,8,9.0,2,25,Semi-Urban,HR Executive,133274,0 +41602,Male,44,PhD,0,37,41,98,74,6.0,5,64,Urban,ML Engineer,120230,1 +41603,Male,52,High School,2,75,89,0,32,6.0,2,91,Urban,ML Engineer,94883,1 +41604,Other,58,Bachelors,14,41,84,71,62,1.0,2,19,Urban,Data Analyst,80306,0 +41605,Male,31,Bachelors,19,5,85,4,62,9.0,0,93,Semi-Urban,ML Engineer,20546,0 +41606,Female,43,Diploma,12,83,6,89,53,9.0,1,28,Urban,Data Analyst,115089,0 +41607,Female,31,Diploma,17,25,35,17,79,9.0,7,8,Urban,Manager,62289,0 +41608,Male,46,High School,12,85,70,69,11,4.0,3,26,Urban,Manager,128924,1 +41609,Male,26,Masters,8,29,63,4,18,7.0,3,47,Urban,Data Analyst,128748,0 +41610,Male,41,Bachelors,15,94,35,21,66,7.0,0,14,Urban,Data Analyst,40313,0 +41611,Male,39,Bachelors,2,1,77,12,68,8.0,4,62,Urban,Data Analyst,77486,0 +41612,Male,47,High School,1,25,33,73,48,0.0,1,8,Urban,ML Engineer,126011,0 +41613,Male,48,Masters,19,68,69,54,77,6.0,2,79,Rural,ML Engineer,114215,1 +41614,Male,22,Diploma,7,49,10,20,59,3.0,4,86,Semi-Urban,ML Engineer,82164,0 +41615,Male,55,Masters,8,7,65,0,63,6.0,6,60,Semi-Urban,Data Analyst,33515,0 +41616,Male,44,Bachelors,2,9,60,55,25,5.0,3,94,Rural,ML Engineer,28144,0 +41617,Female,38,Diploma,4,93,23,7,13,9.0,1,81,Urban,ML Engineer,21146,0 +41618,Female,27,Bachelors,6,97,20,38,51,1.0,7,88,Urban,Data Analyst,38636,1 +41619,Male,32,Bachelors,17,15,27,56,49,8.0,3,40,Urban,HR Executive,145912,0 +41620,Male,31,PhD,3,67,42,6,67,3.0,6,51,Urban,Software Engineer,87478,0 +41621,Other,49,PhD,13,36,8,50,12,7.0,7,28,Urban,Data Analyst,21959,0 +41622,Male,42,Diploma,18,56,41,68,56,6.0,4,90,Urban,Manager,107856,1 +41623,Male,23,PhD,7,41,70,10,62,7.0,1,71,Urban,HR Executive,122459,0 +41624,Male,44,Bachelors,16,58,67,82,46,1.0,4,33,Urban,HR Executive,21431,1 +41625,Male,49,Bachelors,2,16,95,35,68,4.0,6,67,Urban,Software Engineer,115958,0 +41626,Male,58,Diploma,6,88,50,2,48,5.0,3,38,Urban,HR Executive,106983,0 +41627,Male,47,Masters,4,94,9,91,14,3.0,6,30,Urban,Data Analyst,107834,0 +41628,Male,54,Masters,11,53,21,80,68,4.0,6,45,Urban,Data Analyst,74896,0 +41629,Male,35,PhD,7,94,14,26,75,1.0,2,53,Semi-Urban,ML Engineer,37307,0 +41630,Male,38,Bachelors,0,55,89,38,92,3.0,7,38,Rural,Data Analyst,30731,0 +41631,Female,31,Diploma,2,46,59,45,5,1.0,1,78,Urban,Manager,44054,0 +41632,Male,44,Bachelors,13,27,60,46,82,7.0,1,6,Semi-Urban,HR Executive,115247,0 +41633,Male,35,Bachelors,5,39,2,93,88,1.0,7,97,Urban,ML Engineer,98038,0 +41634,Female,43,Masters,4,20,87,4,41,2.0,4,16,Urban,Data Analyst,81959,0 +41635,Male,33,Bachelors,8,77,24,81,96,1.0,7,39,Urban,Software Engineer,88683,0 +41636,Male,24,High School,1,10,51,88,83,7.0,6,63,Urban,HR Executive,24085,0 +41637,Male,55,Diploma,12,25,5,59,82,6.0,2,81,Urban,Software Engineer,71210,0 +41638,Female,28,Bachelors,6,40,73,23,17,4.0,7,50,Urban,Software Engineer,133236,0 +41639,Female,50,Bachelors,18,65,36,44,38,9.0,4,91,Urban,Software Engineer,36616,0 +41640,Male,36,Bachelors,4,40,1,89,79,6.0,1,93,Urban,Software Engineer,43179,0 +41641,Male,27,Diploma,6,82,46,14,33,7.0,0,65,Semi-Urban,ML Engineer,86175,0 +41642,Male,45,Bachelors,8,39,91,5,7,6.0,3,6,Rural,ML Engineer,72337,0 +41643,Female,39,Bachelors,17,58,31,17,32,5.0,5,28,Semi-Urban,HR Executive,114196,0 +41644,Female,37,Diploma,10,91,21,59,7,1.0,6,0,Urban,Data Analyst,132776,0 +41645,Male,50,Bachelors,5,1,68,66,8,5.0,1,30,Urban,Manager,128529,0 +41646,Male,58,Bachelors,9,90,19,42,14,8.0,3,3,Urban,Manager,40034,0 +41647,Male,35,High School,0,8,65,60,6,2.0,4,12,Urban,ML Engineer,34569,0 +41648,Male,48,High School,19,92,96,43,13,1.0,2,48,Urban,HR Executive,119586,1 +41649,Female,57,PhD,13,39,24,58,49,0.0,7,84,Urban,Software Engineer,47957,0 +41650,Male,40,Diploma,16,77,78,27,97,0.0,3,61,Rural,Software Engineer,80911,1 +41651,Male,44,Bachelors,13,77,88,6,97,6.0,1,61,Semi-Urban,ML Engineer,93391,0 +41652,Female,23,Diploma,15,86,72,12,7,6.0,6,87,Semi-Urban,ML Engineer,49547,1 +41653,Male,22,Bachelors,6,21,45,10,88,5.0,6,0,Urban,Data Analyst,43933,0 +41654,Female,28,Masters,10,46,64,16,35,1.0,4,88,Rural,Manager,45425,0 +41655,Male,34,Masters,0,98,59,45,75,8.0,1,50,Urban,Data Analyst,52582,1 +41656,Male,33,High School,0,86,23,1,72,2.0,6,97,Urban,Software Engineer,130568,0 +41657,Female,30,Masters,12,85,78,64,94,7.0,0,27,Semi-Urban,HR Executive,81256,1 +41658,Female,23,Diploma,19,0,62,9,13,2.0,2,31,Semi-Urban,ML Engineer,94931,0 +41659,Male,36,Masters,9,56,78,51,44,6.0,3,20,Semi-Urban,Manager,91981,0 +41660,Female,45,Masters,18,6,9,5,24,3.0,7,0,Urban,Data Analyst,39254,0 +41661,Female,47,Masters,9,10,84,47,64,1.0,2,49,Semi-Urban,Manager,39308,0 +41662,Female,37,Bachelors,11,52,44,68,55,2.0,3,75,Urban,HR Executive,90439,0 +41663,Female,50,Bachelors,19,69,51,73,48,1.0,7,36,Urban,HR Executive,75345,0 +41664,Male,40,PhD,14,8,97,16,24,9.0,6,71,Rural,Software Engineer,92531,0 +41665,Male,39,Bachelors,4,98,8,62,10,1.0,7,21,Rural,Software Engineer,122402,0 +41666,Female,21,Diploma,19,31,58,36,50,7.0,4,64,Rural,HR Executive,98803,0 +41667,Male,47,PhD,10,46,57,37,75,1.0,2,28,Rural,HR Executive,125563,0 +41668,Female,44,Diploma,11,58,60,74,49,3.0,2,59,Urban,ML Engineer,25021,1 +41669,Male,49,Diploma,4,59,90,17,17,9.0,1,48,Rural,Software Engineer,55514,0 +41670,Female,41,High School,14,43,3,59,96,3.0,6,46,Semi-Urban,ML Engineer,70005,0 +41671,Male,58,Masters,8,23,89,22,89,8.0,1,36,Urban,Software Engineer,106974,0 +41672,Male,50,Bachelors,19,81,42,81,79,7.0,1,68,Semi-Urban,HR Executive,42410,1 +41673,Female,39,Bachelors,18,94,47,31,89,3.0,3,98,Urban,ML Engineer,43251,1 +41674,Female,45,Bachelors,6,89,46,2,76,1.0,1,5,Urban,Software Engineer,45338,0 +41675,Male,57,Bachelors,5,31,25,5,12,1.0,3,95,Urban,Data Analyst,127945,0 +41676,Male,33,Diploma,19,7,92,32,90,9.0,1,98,Rural,HR Executive,38407,0 +41677,Female,55,PhD,19,44,51,51,72,1.0,0,91,Urban,Software Engineer,109802,0 +41678,Female,44,High School,1,18,55,11,91,4.0,2,80,Urban,Software Engineer,97610,0 +41679,Male,48,High School,12,20,36,82,89,2.0,5,35,Semi-Urban,ML Engineer,91926,0 +41680,Male,44,Bachelors,17,11,37,87,49,0.0,0,15,Urban,ML Engineer,97782,0 +41681,Male,31,Masters,3,42,59,99,62,1.0,6,32,Urban,Software Engineer,101543,0 +41682,Female,21,Diploma,8,86,78,53,6,9.0,7,32,Rural,Software Engineer,66758,1 +41683,Male,46,Bachelors,5,53,29,20,35,3.0,3,8,Urban,Software Engineer,61073,0 +41684,Male,35,Bachelors,15,32,75,84,64,5.0,7,75,Rural,HR Executive,83958,1 +41685,Male,40,Masters,14,65,45,5,40,3.0,7,53,Rural,Manager,27579,0 +41686,Female,34,Bachelors,0,53,72,5,98,0.0,7,88,Urban,Data Analyst,136252,0 +41687,Female,29,PhD,13,46,28,48,43,3.0,4,7,Urban,ML Engineer,90449,0 +41688,Male,49,Diploma,3,77,53,85,91,9.0,4,0,Semi-Urban,ML Engineer,86766,0 +41689,Male,42,Bachelors,3,50,95,52,32,3.0,4,32,Urban,Manager,68044,0 +41690,Male,52,Bachelors,7,47,5,87,2,2.0,3,44,Urban,Manager,95476,0 +41691,Male,35,High School,4,95,68,94,75,5.0,3,16,Semi-Urban,HR Executive,96935,1 +41692,Male,47,Bachelors,7,78,3,72,42,2.0,5,6,Urban,Software Engineer,110863,0 +41693,Female,57,Diploma,9,67,24,84,49,8.0,2,96,Rural,Data Analyst,106141,1 +41694,Female,33,Bachelors,15,70,46,6,80,0.0,5,29,Urban,Manager,26608,0 +41695,Other,50,High School,8,89,36,82,51,6.0,3,85,Semi-Urban,Software Engineer,149911,1 +41696,Male,31,Bachelors,17,68,69,64,95,3.0,2,30,Urban,HR Executive,39536,0 +41697,Male,30,Bachelors,10,42,35,4,91,6.0,3,11,Urban,ML Engineer,118792,0 +41698,Female,40,Bachelors,9,12,25,4,10,0.0,0,81,Rural,ML Engineer,116608,0 +41699,Male,37,High School,9,92,25,61,4,9.0,3,3,Urban,Manager,64928,0 +41700,Male,30,Bachelors,13,10,4,23,36,9.0,5,82,Urban,HR Executive,143802,0 +41701,Male,39,High School,11,20,67,35,83,7.0,7,83,Urban,ML Engineer,84798,0 +41702,Other,59,Bachelors,7,34,93,52,64,0.0,5,89,Urban,Manager,83458,1 +41703,Female,42,High School,10,3,65,80,53,3.0,6,44,Urban,Data Analyst,72267,0 +41704,Male,24,Bachelors,5,4,27,14,92,2.0,1,70,Rural,Manager,69693,0 +41705,Male,46,Bachelors,4,2,32,59,88,0.0,7,54,Rural,Data Analyst,106306,0 +41706,Female,54,Diploma,7,2,83,27,28,2.0,6,69,Semi-Urban,Software Engineer,132652,0 +41707,Female,43,Diploma,9,14,4,78,66,0.0,0,59,Urban,Data Analyst,20125,0 +41708,Female,28,Diploma,2,16,73,80,37,8.0,5,88,Urban,ML Engineer,71231,1 +41709,Male,27,High School,8,97,51,71,72,5.0,4,97,Rural,HR Executive,99222,1 +41710,Male,54,Diploma,7,90,9,1,84,0.0,5,23,Urban,ML Engineer,115748,0 +41711,Female,53,Diploma,7,79,0,4,29,0.0,4,80,Urban,Software Engineer,133866,0 +41712,Female,39,Bachelors,16,74,47,68,86,7.0,1,86,Urban,Data Analyst,93119,1 +41713,Male,59,Bachelors,11,5,15,12,61,7.0,4,80,Rural,Data Analyst,44346,0 +41714,Male,21,Diploma,0,57,13,67,89,5.0,1,1,Semi-Urban,Software Engineer,135360,0 +41715,Male,23,Bachelors,13,29,51,71,8,4.0,7,74,Semi-Urban,Software Engineer,113564,0 +41716,Male,30,Bachelors,5,47,18,89,40,2.0,6,77,Urban,HR Executive,80284,0 +41717,Male,26,High School,14,25,0,71,71,9.0,1,87,Urban,Data Analyst,147027,0 +41718,Female,46,Diploma,17,73,95,96,14,2.0,1,49,Urban,ML Engineer,104449,1 +41719,Male,24,Bachelors,8,76,3,77,74,2.0,6,45,Urban,ML Engineer,69942,0 +41720,Male,38,Masters,17,88,99,88,55,5.0,4,12,Semi-Urban,Software Engineer,91891,1 +41721,Male,37,Masters,19,80,57,40,98,1.0,6,72,Rural,ML Engineer,94096,1 +41722,Female,53,Diploma,18,36,98,38,48,8.0,0,28,Semi-Urban,Data Analyst,88305,0 +41723,Female,51,Diploma,5,93,86,37,85,8.0,0,24,Urban,ML Engineer,37361,0 +41724,Male,34,Masters,16,10,76,74,23,6.0,0,6,Urban,ML Engineer,114274,0 +41725,Male,47,Bachelors,16,5,89,65,13,4.0,2,55,Rural,ML Engineer,96879,0 +41726,Male,33,High School,2,40,17,54,67,4.0,5,68,Semi-Urban,Software Engineer,142406,0 +41727,Male,48,Bachelors,5,14,98,94,61,4.0,3,49,Rural,ML Engineer,24957,1 +41728,Male,26,Bachelors,10,64,16,97,0,4.0,7,16,Rural,Manager,75619,0 +41729,Female,57,Masters,1,70,20,98,90,1.0,4,13,Urban,Manager,58290,0 +41730,Male,55,High School,7,3,89,57,4,8.0,3,2,Urban,Data Analyst,145820,0 +41731,Other,26,High School,9,8,76,23,52,6.0,1,34,Rural,Software Engineer,115932,0 +41732,Male,50,Masters,13,54,74,54,53,1.0,2,96,Semi-Urban,Software Engineer,122262,1 +41733,Male,39,Masters,0,42,66,46,75,4.0,0,64,Semi-Urban,Manager,39145,0 +41734,Male,42,High School,2,69,82,44,28,9.0,5,23,Rural,Data Analyst,90676,0 +41735,Male,57,High School,2,8,61,80,73,4.0,4,12,Semi-Urban,ML Engineer,113694,0 +41736,Male,34,Masters,16,94,39,39,34,7.0,0,36,Urban,Software Engineer,60714,0 +41737,Female,26,Masters,18,43,80,21,28,2.0,0,1,Urban,Data Analyst,121338,0 +41738,Male,22,Bachelors,3,69,97,47,21,1.0,4,15,Urban,HR Executive,64673,0 +41739,Male,44,Diploma,6,70,69,65,68,1.0,5,37,Urban,Data Analyst,123269,1 +41740,Female,54,Diploma,18,19,20,18,8,7.0,1,41,Urban,Data Analyst,105809,0 +41741,Female,40,Diploma,19,98,49,60,7,9.0,3,62,Rural,ML Engineer,143457,1 +41742,Female,51,High School,1,43,74,57,98,2.0,1,82,Semi-Urban,HR Executive,45836,1 +41743,Female,37,Bachelors,15,28,75,88,18,5.0,0,34,Urban,Manager,86537,0 +41744,Male,24,Bachelors,1,73,2,94,21,2.0,7,11,Urban,Manager,77483,0 +41745,Male,47,Bachelors,1,10,24,73,7,1.0,3,85,Rural,HR Executive,104561,0 +41746,Male,21,Bachelors,14,86,73,79,8,1.0,4,54,Rural,HR Executive,144879,1 +41747,Other,43,Masters,16,99,41,76,65,3.0,2,14,Rural,Manager,47416,0 +41748,Male,30,Diploma,16,23,33,45,46,5.0,1,40,Rural,HR Executive,64096,0 +41749,Male,45,Bachelors,7,92,21,84,16,3.0,7,37,Semi-Urban,ML Engineer,35004,0 +41750,Male,43,Bachelors,19,48,73,96,97,5.0,1,51,Semi-Urban,ML Engineer,29973,1 +41751,Male,42,Masters,10,73,28,6,37,9.0,1,48,Urban,Data Analyst,122125,0 +41752,Male,25,Masters,5,75,76,12,31,2.0,4,14,Semi-Urban,Data Analyst,132044,0 +41753,Male,52,PhD,1,60,18,81,36,4.0,1,58,Rural,Software Engineer,90187,0 +41754,Male,25,Bachelors,6,47,24,37,23,3.0,1,15,Semi-Urban,Software Engineer,38500,0 +41755,Male,40,Masters,11,47,60,16,12,3.0,0,61,Urban,Data Analyst,57420,0 +41756,Male,29,Diploma,11,75,89,97,19,0.0,4,9,Semi-Urban,Data Analyst,54192,1 +41757,Male,33,Masters,17,38,32,48,17,7.0,3,2,Rural,HR Executive,122186,0 +41758,Female,37,Bachelors,3,81,43,96,71,8.0,7,42,Semi-Urban,HR Executive,142900,1 +41759,Male,37,Diploma,17,42,27,53,58,3.0,3,99,Rural,Software Engineer,24121,0 +41760,Female,42,Diploma,8,32,40,65,52,6.0,4,8,Semi-Urban,Manager,58279,0 +41761,Male,37,High School,5,41,1,61,91,9.0,0,29,Semi-Urban,Data Analyst,145480,0 +41762,Male,58,High School,2,55,95,1,24,9.0,2,35,Urban,Data Analyst,106511,0 +41763,Female,24,Bachelors,19,42,0,86,43,4.0,0,41,Urban,HR Executive,137166,0 +41764,Male,52,High School,13,6,69,28,53,5.0,4,19,Rural,Data Analyst,128887,0 +41765,Male,51,Masters,17,62,91,50,21,4.0,7,42,Semi-Urban,Software Engineer,86917,1 +41766,Female,22,Bachelors,6,4,45,92,95,1.0,1,47,Rural,Software Engineer,137589,0 +41767,Male,53,Diploma,7,52,70,98,0,4.0,3,86,Semi-Urban,Software Engineer,142923,1 +41768,Male,59,Bachelors,5,99,23,56,26,8.0,6,55,Rural,Software Engineer,117353,0 +41769,Female,27,Bachelors,16,62,50,33,42,1.0,0,71,Urban,Software Engineer,75143,0 +41770,Male,41,Bachelors,18,8,57,46,76,5.0,3,86,Urban,Software Engineer,22848,0 +41771,Female,58,Diploma,2,62,15,6,72,8.0,0,68,Rural,Software Engineer,106045,0 +41772,Male,49,Bachelors,16,70,35,72,20,7.0,1,35,Rural,Software Engineer,70209,0 +41773,Male,40,High School,17,59,22,41,90,6.0,6,82,Urban,Manager,147269,0 +41774,Male,35,Bachelors,16,9,93,57,29,5.0,0,38,Rural,HR Executive,38609,0 +41775,Male,44,High School,1,68,53,48,0,3.0,0,21,Urban,Manager,88553,0 +41776,Female,30,High School,13,51,47,40,89,3.0,2,91,Urban,Data Analyst,90312,0 +41777,Female,28,Masters,7,47,0,27,28,4.0,3,59,Urban,HR Executive,128549,0 +41778,Male,41,Bachelors,12,72,29,3,51,2.0,4,58,Urban,Manager,85427,0 +41779,Female,42,Bachelors,0,15,33,32,24,0.0,6,48,Urban,Manager,29685,0 +41780,Male,34,Diploma,9,30,99,83,44,8.0,1,81,Urban,Manager,79426,1 +41781,Male,51,PhD,14,35,17,42,65,3.0,1,45,Urban,Software Engineer,68309,0 +41782,Other,49,Masters,1,0,76,56,67,3.0,0,56,Rural,ML Engineer,53895,0 +41783,Male,34,Bachelors,11,78,65,75,96,9.0,0,68,Semi-Urban,HR Executive,123644,1 +41784,Male,38,Bachelors,7,24,11,62,55,2.0,1,73,Urban,Manager,58336,0 +41785,Male,27,Masters,10,50,44,72,92,3.0,5,6,Semi-Urban,Data Analyst,94364,0 +41786,Male,34,Bachelors,3,90,25,18,83,0.0,6,41,Semi-Urban,HR Executive,90540,0 +41787,Male,38,Bachelors,17,33,5,47,83,7.0,5,24,Semi-Urban,Manager,85266,0 +41788,Female,27,Masters,15,53,89,77,65,7.0,7,9,Semi-Urban,ML Engineer,141857,0 +41789,Female,30,Bachelors,3,62,65,49,68,1.0,3,18,Urban,Manager,149018,0 +41790,Male,50,High School,1,25,48,55,11,8.0,1,44,Urban,HR Executive,104883,0 +41791,Male,42,Bachelors,7,72,2,49,9,9.0,3,84,Urban,Manager,65737,0 +41792,Male,22,Masters,18,99,36,59,46,4.0,5,54,Semi-Urban,Software Engineer,131595,1 +41793,Male,39,Bachelors,8,38,22,94,50,3.0,7,19,Urban,Data Analyst,83605,0 +41794,Female,28,Masters,15,86,64,69,75,6.0,5,40,Urban,HR Executive,97204,1 +41795,Female,57,High School,13,22,21,43,63,9.0,6,73,Rural,Data Analyst,123663,0 +41796,Female,44,Diploma,10,13,26,94,40,6.0,1,29,Urban,HR Executive,57290,0 +41797,Female,44,High School,3,89,17,54,8,7.0,5,70,Semi-Urban,Software Engineer,46434,0 +41798,Female,34,Masters,9,34,59,96,88,2.0,1,39,Rural,Data Analyst,107442,0 +41799,Male,50,Diploma,6,53,18,54,88,9.0,1,85,Semi-Urban,ML Engineer,97204,0 +41800,Male,24,Diploma,8,43,68,77,40,9.0,5,81,Semi-Urban,Manager,20731,1 +41801,Male,22,Bachelors,16,55,39,69,60,8.0,1,26,Urban,Manager,107218,0 +41802,Female,50,High School,18,59,82,0,43,0.0,3,70,Urban,Software Engineer,53448,0 +41803,Male,30,Bachelors,9,93,73,22,62,1.0,4,47,Urban,HR Executive,62493,1 +41804,Male,51,Masters,9,35,49,1,6,9.0,7,51,Urban,Data Analyst,124334,0 +41805,Male,49,Diploma,8,88,25,36,51,0.0,6,20,Rural,ML Engineer,101953,0 +41806,Female,43,High School,4,18,6,54,55,4.0,4,27,Urban,Software Engineer,81493,0 +41807,Female,30,Diploma,13,78,62,24,52,2.0,5,79,Urban,ML Engineer,140029,1 +41808,Male,56,Bachelors,12,4,79,28,69,2.0,0,85,Urban,Software Engineer,140545,0 +41809,Female,39,Diploma,16,59,1,14,94,9.0,4,78,Rural,ML Engineer,76175,0 +41810,Male,40,Bachelors,13,33,8,5,5,0.0,1,23,Urban,Software Engineer,102693,0 +41811,Female,55,Masters,0,95,81,78,46,4.0,2,35,Semi-Urban,HR Executive,106568,1 +41812,Male,42,Bachelors,17,30,95,58,3,3.0,3,91,Rural,ML Engineer,88299,1 +41813,Male,23,Bachelors,2,98,8,5,95,5.0,7,17,Urban,Software Engineer,31042,0 +41814,Male,34,Bachelors,5,67,47,90,29,4.0,2,3,Urban,Software Engineer,40247,0 +41815,Male,21,Bachelors,8,11,8,77,26,1.0,5,64,Rural,Software Engineer,30967,0 +41816,Female,52,PhD,17,45,34,39,68,7.0,4,45,Semi-Urban,Data Analyst,105453,0 +41817,Other,23,High School,1,79,61,13,84,2.0,1,39,Urban,Data Analyst,32913,0 +41818,Male,42,Bachelors,6,73,77,80,51,5.0,0,29,Rural,HR Executive,89340,1 +41819,Male,44,High School,17,21,54,65,29,6.0,0,69,Urban,Data Analyst,20689,0 +41820,Female,45,PhD,5,82,28,91,24,5.0,0,69,Urban,Software Engineer,43452,1 +41821,Male,55,Bachelors,19,30,54,21,56,0.0,1,95,Rural,Software Engineer,148095,0 +41822,Male,52,Bachelors,11,23,35,1,41,6.0,4,51,Urban,Manager,59812,0 +41823,Male,30,High School,7,20,76,84,32,9.0,1,88,Semi-Urban,ML Engineer,75592,1 +41824,Female,46,Masters,12,13,88,76,37,5.0,1,18,Urban,ML Engineer,53818,0 +41825,Female,30,Bachelors,15,78,72,8,20,3.0,0,29,Semi-Urban,Software Engineer,126565,0 +41826,Female,50,Masters,8,96,30,33,82,0.0,2,33,Semi-Urban,Software Engineer,43431,0 +41827,Male,54,Bachelors,1,77,52,2,86,7.0,0,89,Urban,Data Analyst,82143,0 +41828,Female,34,Diploma,0,30,93,19,3,6.0,1,26,Urban,Data Analyst,63117,0 +41829,Male,35,PhD,18,82,21,79,6,4.0,5,5,Rural,Manager,100205,0 +41830,Male,40,Bachelors,1,33,22,71,83,2.0,0,32,Urban,Data Analyst,73828,0 +41831,Female,53,Bachelors,1,29,86,4,40,3.0,4,46,Urban,Data Analyst,107838,0 +41832,Other,42,Bachelors,6,73,95,46,20,9.0,3,34,Rural,Software Engineer,147937,1 +41833,Female,25,Masters,10,62,6,50,36,6.0,1,61,Urban,ML Engineer,80409,0 +41834,Female,43,Masters,12,95,14,45,58,3.0,4,82,Rural,Software Engineer,149406,0 +41835,Female,38,High School,17,35,70,0,42,5.0,4,52,Urban,ML Engineer,115163,0 +41836,Female,58,Bachelors,14,47,60,81,85,2.0,6,80,Semi-Urban,Software Engineer,36617,1 +41837,Female,32,High School,13,52,24,82,80,0.0,6,90,Rural,ML Engineer,148110,1 +41838,Male,33,Bachelors,6,70,60,69,33,1.0,0,84,Rural,HR Executive,44672,1 +41839,Male,25,PhD,0,1,98,61,84,8.0,6,48,Urban,ML Engineer,144915,0 +41840,Female,56,Bachelors,11,81,33,37,81,1.0,4,98,Urban,Manager,52668,1 +41841,Female,41,High School,0,31,0,77,93,2.0,7,31,Rural,ML Engineer,114089,0 +41842,Male,51,Masters,7,49,86,83,17,4.0,5,59,Urban,HR Executive,33668,1 +41843,Female,36,Bachelors,10,96,20,65,66,5.0,1,42,Rural,Data Analyst,65227,0 +41844,Male,59,Bachelors,0,75,13,20,65,5.0,6,82,Urban,Manager,20252,0 +41845,Female,48,Diploma,17,65,57,78,95,6.0,1,20,Urban,Software Engineer,146637,0 +41846,Female,48,Masters,19,10,68,83,25,6.0,5,8,Urban,Data Analyst,61503,0 +41847,Male,36,High School,15,83,60,1,98,5.0,4,76,Rural,Data Analyst,149139,0 +41848,Female,27,Masters,16,49,48,57,75,8.0,0,89,Urban,Manager,86096,1 +41849,Female,50,High School,18,33,53,86,50,3.0,3,92,Urban,Data Analyst,22700,1 +41850,Female,31,Diploma,0,13,6,64,44,5.0,7,72,Semi-Urban,Data Analyst,120015,0 +41851,Female,58,Bachelors,3,56,88,71,93,0.0,6,37,Urban,HR Executive,24437,1 +41852,Male,26,Masters,11,78,51,69,39,4.0,4,64,Rural,ML Engineer,79020,1 +41853,Male,52,Diploma,5,50,77,88,5,5.0,2,9,Urban,HR Executive,116229,0 +41854,Female,32,Masters,11,38,96,14,70,0.0,2,29,Rural,Data Analyst,52975,0 +41855,Female,31,Masters,7,86,10,69,66,7.0,6,66,Urban,Data Analyst,53231,0 +41856,Male,44,Diploma,7,13,77,45,10,5.0,1,0,Urban,Manager,79555,0 +41857,Male,55,Diploma,12,49,26,92,63,1.0,2,30,Semi-Urban,Software Engineer,106421,0 +41858,Male,34,Bachelors,7,81,36,12,79,8.0,4,74,Urban,Manager,66939,0 +41859,Male,26,Bachelors,3,34,55,81,87,5.0,7,57,Urban,Software Engineer,92059,0 +41860,Female,36,Bachelors,4,52,18,48,86,2.0,7,57,Semi-Urban,Software Engineer,109544,0 +41861,Male,58,Diploma,2,95,19,13,57,8.0,5,46,Urban,ML Engineer,31247,0 +41862,Male,28,Bachelors,13,43,20,91,58,5.0,0,20,Semi-Urban,ML Engineer,85321,0 +41863,Female,22,Diploma,14,48,10,29,6,8.0,2,27,Rural,HR Executive,132852,0 +41864,Male,59,High School,0,99,39,9,70,6.0,3,86,Urban,Data Analyst,53681,0 +41865,Female,26,Masters,13,7,55,45,34,6.0,3,90,Rural,Manager,62148,0 +41866,Male,22,PhD,5,97,73,64,81,8.0,0,20,Semi-Urban,Software Engineer,70517,1 +41867,Female,59,Bachelors,6,85,19,29,25,3.0,2,9,Semi-Urban,Data Analyst,95970,0 +41868,Male,48,Masters,0,3,38,34,18,7.0,0,19,Urban,ML Engineer,38405,0 +41869,Male,57,Bachelors,13,75,55,97,36,0.0,2,4,Urban,Software Engineer,51919,0 +41870,Male,40,High School,14,14,82,40,77,2.0,6,94,Semi-Urban,ML Engineer,71483,0 +41871,Female,49,Diploma,4,33,87,32,99,5.0,7,19,Urban,Software Engineer,56991,0 +41872,Male,46,Masters,10,24,62,21,89,4.0,0,24,Semi-Urban,Manager,41442,0 +41873,Male,53,PhD,11,28,86,85,70,5.0,5,98,Semi-Urban,Data Analyst,69372,1 +41874,Female,27,Diploma,12,86,1,43,11,2.0,2,74,Urban,HR Executive,108651,0 +41875,Male,31,Masters,17,52,91,39,9,7.0,4,7,Urban,Manager,123742,0 +41876,Female,54,Bachelors,14,37,83,94,49,0.0,5,56,Urban,Manager,57547,1 +41877,Male,52,Bachelors,6,61,97,99,57,5.0,6,37,Urban,Manager,138574,1 +41878,Male,48,Masters,8,39,66,48,38,7.0,7,71,Urban,ML Engineer,76085,0 +41879,Male,38,PhD,7,56,65,45,0,3.0,3,27,Semi-Urban,ML Engineer,50154,0 +41880,Male,31,Bachelors,11,18,32,88,24,6.0,1,35,Rural,HR Executive,132576,0 +41881,Male,45,Masters,12,83,23,22,10,8.0,3,66,Urban,Software Engineer,80226,0 +41882,Male,58,Bachelors,1,65,6,89,15,1.0,7,44,Urban,Manager,20824,0 +41883,Male,48,Bachelors,11,59,89,22,69,0.0,7,80,Semi-Urban,Data Analyst,131915,1 +41884,Female,35,Diploma,12,91,58,67,64,0.0,4,1,Urban,ML Engineer,50601,0 +41885,Female,22,Bachelors,15,11,69,75,85,2.0,1,69,Urban,HR Executive,61338,0 +41886,Female,45,Bachelors,2,47,87,83,23,6.0,3,23,Semi-Urban,HR Executive,88043,0 +41887,Male,41,Bachelors,5,51,56,41,86,5.0,7,51,Semi-Urban,Data Analyst,66635,0 +41888,Female,33,Bachelors,5,60,83,65,56,2.0,2,6,Rural,Manager,67354,0 +41889,Male,54,Diploma,14,95,27,11,93,5.0,7,30,Rural,Software Engineer,134483,0 +41890,Female,26,Bachelors,19,33,85,74,89,7.0,3,40,Urban,Data Analyst,78435,0 +41891,Male,27,Bachelors,17,92,82,63,3,4.0,2,33,Rural,ML Engineer,147931,1 +41892,Female,28,Bachelors,1,94,77,75,64,6.0,2,33,Urban,ML Engineer,121696,1 +41893,Female,53,Bachelors,6,92,97,52,45,0.0,7,90,Urban,Manager,35939,1 +41894,Female,32,High School,4,33,50,24,81,4.0,4,54,Rural,Data Analyst,87732,0 +41895,Female,39,Bachelors,7,57,27,6,23,4.0,3,24,Semi-Urban,HR Executive,54385,0 +41896,Male,44,Bachelors,11,54,37,98,42,9.0,7,1,Urban,Software Engineer,112223,0 +41897,Female,28,PhD,1,66,51,71,99,8.0,3,83,Urban,Software Engineer,57386,1 +41898,Male,42,High School,4,95,39,75,20,1.0,0,34,Rural,Software Engineer,113581,1 +41899,Male,42,Masters,0,76,24,41,3,1.0,6,60,Urban,Software Engineer,74253,0 +41900,Male,46,Bachelors,10,13,87,14,50,3.0,2,56,Urban,Data Analyst,79359,0 +41901,Female,28,Bachelors,10,86,28,59,74,3.0,7,44,Urban,ML Engineer,105203,0 +41902,Male,33,Diploma,9,72,38,92,24,0.0,5,32,Urban,ML Engineer,120695,0 +41903,Male,47,Masters,8,18,86,23,86,7.0,5,36,Semi-Urban,HR Executive,89615,0 +41904,Male,42,High School,12,11,67,13,85,6.0,6,74,Urban,Manager,136488,0 +41905,Female,24,Masters,7,91,62,42,37,7.0,5,66,Urban,ML Engineer,142005,1 +41906,Female,51,Bachelors,11,50,52,80,99,3.0,7,90,Urban,Manager,148090,1 +41907,Male,22,Bachelors,5,39,8,10,59,4.0,7,7,Urban,ML Engineer,112994,0 +41908,Male,49,Bachelors,4,19,27,87,17,2.0,6,78,Urban,HR Executive,77337,0 +41909,Male,47,Masters,13,14,85,18,40,6.0,7,25,Urban,HR Executive,128056,0 +41910,Male,23,PhD,18,93,90,31,45,0.0,2,60,Rural,HR Executive,137017,1 +41911,Female,41,Diploma,19,24,92,51,34,0.0,3,46,Semi-Urban,ML Engineer,85754,0 +41912,Male,55,Masters,16,13,59,50,5,1.0,4,60,Rural,Software Engineer,40557,0 +41913,Male,34,Bachelors,3,95,31,31,30,0.0,1,17,Semi-Urban,Data Analyst,103601,0 +41914,Female,24,Diploma,14,43,84,73,65,2.0,2,30,Urban,Data Analyst,72971,0 +41915,Male,22,Bachelors,17,5,51,64,85,5.0,3,3,Semi-Urban,Software Engineer,99353,0 +41916,Female,59,Bachelors,12,71,58,69,48,7.0,4,66,Urban,HR Executive,118149,1 +41917,Female,46,Diploma,5,7,88,62,70,2.0,3,4,Semi-Urban,ML Engineer,32600,0 +41918,Male,29,Bachelors,19,86,38,36,85,4.0,1,24,Urban,Manager,54564,0 +41919,Male,32,Diploma,2,55,84,24,15,0.0,6,13,Urban,ML Engineer,93483,0 +41920,Male,23,Masters,12,47,20,62,96,9.0,0,13,Urban,Manager,147734,0 +41921,Male,49,Masters,10,38,22,87,39,1.0,5,80,Urban,Software Engineer,27811,0 +41922,Male,40,Bachelors,1,57,6,40,30,8.0,0,68,Semi-Urban,Data Analyst,83552,0 +41923,Female,36,PhD,3,76,65,57,83,1.0,5,57,Semi-Urban,ML Engineer,71679,1 +41924,Female,51,Masters,7,19,68,31,5,6.0,6,67,Urban,HR Executive,59095,0 +41925,Male,24,Bachelors,15,74,77,15,49,7.0,0,33,Urban,HR Executive,21264,0 +41926,Female,50,Bachelors,12,22,75,94,89,2.0,3,21,Urban,Manager,88347,0 +41927,Male,29,Diploma,2,17,55,39,72,0.0,6,66,Semi-Urban,Data Analyst,146347,0 +41928,Female,35,Masters,8,29,22,11,15,8.0,7,87,Urban,Manager,52304,0 +41929,Male,48,Bachelors,13,5,64,91,81,0.0,0,7,Urban,Manager,39935,0 +41930,Male,37,PhD,9,46,55,3,55,4.0,7,47,Urban,Manager,130734,0 +41931,Female,31,Bachelors,7,12,5,12,36,1.0,0,39,Urban,Manager,84545,0 +41932,Male,31,Masters,19,65,85,81,53,7.0,5,28,Urban,ML Engineer,27872,1 +41933,Male,29,Bachelors,15,76,92,10,68,5.0,4,33,Urban,ML Engineer,114250,0 +41934,Male,50,Masters,11,85,50,9,97,8.0,2,63,Semi-Urban,ML Engineer,79959,0 +41935,Male,55,Masters,15,11,87,87,48,2.0,7,89,Urban,HR Executive,102545,1 +41936,Female,31,Diploma,9,29,82,14,28,6.0,7,81,Semi-Urban,Software Engineer,70963,0 +41937,Female,23,Bachelors,2,82,18,55,1,6.0,3,93,Urban,HR Executive,45325,1 +41938,Male,57,High School,0,22,92,8,38,0.0,1,85,Urban,Data Analyst,124418,0 +41939,Male,21,Masters,18,92,40,6,26,6.0,6,93,Urban,HR Executive,134300,0 +41940,Male,39,Masters,3,46,94,64,64,4.0,0,72,Urban,Data Analyst,129260,1 +41941,Female,21,Diploma,8,10,12,82,42,1.0,5,11,Rural,Software Engineer,40642,0 +41942,Male,57,Masters,5,86,62,54,80,8.0,3,41,Urban,Software Engineer,125417,1 +41943,Female,35,High School,0,35,93,86,15,1.0,2,2,Rural,ML Engineer,81367,0 +41944,Other,55,Bachelors,9,16,41,44,69,2.0,0,60,Urban,ML Engineer,62000,0 +41945,Male,36,PhD,16,82,47,24,15,6.0,6,46,Urban,Data Analyst,127584,0 +41946,Male,25,Diploma,8,75,99,49,30,8.0,0,35,Semi-Urban,Manager,87374,1 +41947,Female,35,High School,3,80,26,28,5,1.0,3,39,Rural,ML Engineer,82673,0 +41948,Male,59,High School,5,18,96,35,5,9.0,4,63,Urban,Manager,108175,0 +41949,Male,59,Bachelors,11,79,86,36,53,4.0,5,4,Semi-Urban,Software Engineer,104561,0 +41950,Female,21,Bachelors,17,17,99,5,78,5.0,3,61,Urban,HR Executive,44533,0 +41951,Female,32,Bachelors,16,47,96,14,85,7.0,3,42,Semi-Urban,ML Engineer,76737,0 +41952,Male,56,Diploma,11,3,46,23,97,2.0,4,43,Urban,Software Engineer,52743,0 +41953,Male,57,Masters,14,68,42,70,58,1.0,2,25,Urban,Data Analyst,137929,0 +41954,Male,58,Diploma,8,5,93,78,14,4.0,4,58,Semi-Urban,ML Engineer,47876,0 +41955,Female,24,Diploma,14,1,42,3,63,3.0,5,9,Rural,ML Engineer,58995,0 +41956,Female,42,Masters,11,25,66,21,70,6.0,0,33,Urban,Manager,45081,0 +41957,Female,32,High School,2,99,7,0,70,0.0,1,4,Semi-Urban,Manager,77790,0 +41958,Female,53,Bachelors,3,23,40,2,16,4.0,7,27,Urban,ML Engineer,27248,0 +41959,Male,58,Bachelors,9,98,70,48,28,3.0,7,51,Urban,Manager,63545,1 +41960,Male,23,Bachelors,1,91,39,42,81,5.0,1,86,Rural,ML Engineer,131340,1 +41961,Male,44,Bachelors,4,85,48,71,38,6.0,6,36,Urban,HR Executive,145960,1 +41962,Female,25,High School,0,9,26,2,25,5.0,2,79,Semi-Urban,ML Engineer,29888,0 +41963,Male,35,Diploma,7,35,20,88,29,3.0,1,53,Urban,ML Engineer,55116,0 +41964,Female,56,Diploma,13,28,11,57,33,4.0,7,57,Urban,Manager,61175,0 +41965,Female,27,Masters,0,55,53,9,54,0.0,0,26,Semi-Urban,ML Engineer,107990,0 +41966,Female,28,Bachelors,17,73,78,74,30,6.0,3,75,Semi-Urban,Data Analyst,59900,1 +41967,Female,42,Masters,14,61,25,54,90,4.0,6,24,Urban,Software Engineer,39815,0 +41968,Male,38,Diploma,19,16,40,26,81,2.0,0,0,Rural,HR Executive,92565,0 +41969,Male,28,High School,5,99,24,40,44,6.0,3,55,Semi-Urban,Manager,135811,0 +41970,Male,34,Diploma,14,22,52,63,52,1.0,6,71,Urban,Software Engineer,82038,0 +41971,Male,24,Diploma,4,74,13,83,73,9.0,1,36,Rural,Data Analyst,36536,0 +41972,Male,37,Diploma,19,97,25,34,93,6.0,6,6,Urban,ML Engineer,107287,0 +41973,Male,32,Masters,9,31,84,44,87,4.0,5,86,Semi-Urban,ML Engineer,32826,1 +41974,Female,40,Masters,8,62,94,21,31,5.0,5,77,Rural,Software Engineer,149633,1 +41975,Male,50,High School,18,39,70,11,77,4.0,4,47,Rural,ML Engineer,143564,0 +41976,Female,27,High School,7,69,47,8,14,9.0,0,77,Semi-Urban,Software Engineer,39692,0 +41977,Male,23,Diploma,12,46,66,70,94,6.0,6,16,Semi-Urban,HR Executive,113643,0 +41978,Other,41,Masters,18,38,54,23,64,0.0,6,55,Urban,HR Executive,102171,0 +41979,Male,36,Bachelors,12,51,1,28,1,2.0,1,85,Semi-Urban,HR Executive,126090,0 +41980,Male,54,Bachelors,10,8,85,66,17,4.0,4,86,Urban,ML Engineer,141787,1 +41981,Male,56,High School,15,90,1,16,0,0.0,6,40,Urban,Software Engineer,127887,0 +41982,Female,48,Bachelors,13,76,43,2,93,7.0,0,33,Semi-Urban,Manager,37627,0 +41983,Male,43,High School,16,12,52,85,7,4.0,2,69,Semi-Urban,HR Executive,138607,0 +41984,Female,50,Masters,7,11,55,12,90,8.0,2,98,Urban,Software Engineer,53330,0 +41985,Female,42,Bachelors,10,96,59,36,96,9.0,6,19,Rural,ML Engineer,65133,0 +41986,Male,39,High School,13,54,68,6,35,6.0,0,70,Rural,Data Analyst,27489,0 +41987,Male,48,High School,4,89,23,65,95,6.0,2,98,Urban,HR Executive,149896,1 +41988,Female,23,Bachelors,6,9,70,54,76,0.0,3,70,Urban,ML Engineer,38865,0 +41989,Male,52,Diploma,2,87,87,80,5,1.0,0,96,Semi-Urban,Manager,123152,1 +41990,Female,42,Bachelors,16,38,7,84,74,4.0,1,23,Urban,Software Engineer,70209,0 +41991,Male,34,Bachelors,4,84,28,57,90,6.0,7,55,Rural,Manager,90556,0 +41992,Female,32,Diploma,0,45,44,67,40,6.0,0,6,Semi-Urban,HR Executive,91548,0 +41993,Female,32,Diploma,19,95,7,88,6,4.0,5,51,Rural,ML Engineer,119261,1 +41994,Female,31,Bachelors,6,33,73,61,83,8.0,0,15,Urban,ML Engineer,140640,0 +41995,Male,26,Masters,11,1,34,45,53,1.0,1,95,Urban,Software Engineer,57249,0 +41996,Female,29,Bachelors,5,37,62,24,77,4.0,6,99,Rural,Software Engineer,37466,0 +41997,Female,38,Bachelors,17,82,16,55,30,7.0,3,50,Urban,HR Executive,100492,0 +41998,Male,38,Masters,15,22,3,24,70,9.0,3,65,Urban,Data Analyst,65392,0 +41999,Female,54,Bachelors,14,74,21,7,50,6.0,7,36,Rural,ML Engineer,75337,0 +42000,Male,32,Bachelors,19,35,19,34,85,0.0,6,40,Rural,Manager,138466,0 +42001,Female,45,High School,0,1,52,97,48,7.0,0,63,Urban,Manager,146194,0 +42002,Female,27,Masters,18,51,61,58,74,6.0,6,52,Urban,HR Executive,93996,0 +42003,Male,27,Masters,0,26,2,16,67,2.0,4,87,Urban,Data Analyst,101163,0 +42004,Male,53,Bachelors,10,81,75,19,20,0.0,7,64,Urban,Manager,55522,1 +42005,Other,47,Bachelors,4,60,49,19,42,4.0,0,15,Rural,Software Engineer,46874,0 +42006,Male,53,Masters,9,46,66,80,42,6.0,4,13,Semi-Urban,ML Engineer,127224,0 +42007,Other,36,High School,10,59,31,84,63,7.0,7,87,Urban,ML Engineer,104752,1 +42008,Female,37,High School,16,46,70,80,4,2.0,2,73,Rural,ML Engineer,59390,1 +42009,Male,54,Bachelors,5,17,93,5,89,7.0,7,66,Urban,Data Analyst,109875,0 +42010,Male,34,Masters,7,37,63,97,29,4.0,2,92,Rural,Manager,66031,1 +42011,Male,25,Bachelors,4,69,52,56,93,6.0,1,17,Semi-Urban,Data Analyst,135133,0 +42012,Female,21,High School,11,98,40,39,42,3.0,6,98,Urban,Manager,61741,1 +42013,Male,28,Masters,5,83,30,26,6,2.0,5,37,Semi-Urban,Manager,65623,0 +42014,Male,33,High School,13,15,81,71,99,9.0,1,61,Urban,Software Engineer,114123,0 +42015,Female,22,Masters,8,24,68,77,82,1.0,0,21,Semi-Urban,HR Executive,67908,0 +42016,Male,52,Masters,7,41,54,98,11,3.0,0,17,Semi-Urban,ML Engineer,142880,0 +42017,Male,25,Masters,4,39,36,94,3,5.0,5,76,Semi-Urban,Software Engineer,147153,1 +42018,Male,49,High School,16,90,72,29,20,1.0,4,73,Urban,Data Analyst,52149,1 +42019,Male,57,Masters,15,30,87,31,52,0.0,7,98,Semi-Urban,Software Engineer,145103,1 +42020,Male,38,Masters,5,12,93,58,84,3.0,4,96,Urban,HR Executive,52736,1 +42021,Male,36,Bachelors,15,12,26,88,49,8.0,0,95,Urban,Data Analyst,88402,0 +42022,Male,37,Bachelors,3,29,21,84,23,3.0,1,85,Urban,ML Engineer,97481,0 +42023,Male,42,Bachelors,19,29,35,39,7,6.0,2,62,Urban,HR Executive,21006,0 +42024,Female,30,Bachelors,3,33,6,95,10,2.0,4,54,Urban,Data Analyst,37860,0 +42025,Female,36,Diploma,10,53,18,83,32,3.0,3,29,Urban,Software Engineer,92117,0 +42026,Male,48,Bachelors,2,46,66,37,41,5.0,1,40,Semi-Urban,ML Engineer,41795,0 +42027,Male,21,Bachelors,11,63,79,5,77,6.0,0,20,Urban,Software Engineer,118761,0 +42028,Male,38,Diploma,11,82,83,48,52,1.0,5,36,Semi-Urban,Manager,61773,1 +42029,Male,56,Masters,14,33,36,23,24,5.0,1,87,Semi-Urban,HR Executive,44781,0 +42030,Male,24,Bachelors,12,57,29,15,87,2.0,7,1,Semi-Urban,Manager,121950,0 +42031,Female,47,Masters,4,32,23,22,39,7.0,2,98,Urban,Data Analyst,64861,0 +42032,Male,55,Diploma,12,78,64,43,89,5.0,6,2,Urban,Manager,45367,0 +42033,Male,59,Bachelors,18,43,65,52,81,6.0,4,29,Urban,HR Executive,123134,0 +42034,Female,23,Bachelors,13,52,65,15,15,9.0,1,39,Rural,HR Executive,79686,0 +42035,Female,31,Bachelors,15,74,8,88,8,7.0,3,52,Urban,Data Analyst,106811,0 +42036,Other,34,Bachelors,1,9,98,96,77,4.0,5,58,Urban,Manager,41167,1 +42037,Male,46,Bachelors,12,58,15,6,15,6.0,6,21,Semi-Urban,Data Analyst,115438,0 +42038,Male,21,High School,17,99,4,79,56,8.0,2,62,Semi-Urban,Manager,44309,1 +42039,Male,33,Bachelors,14,75,17,12,67,4.0,4,36,Semi-Urban,Data Analyst,65697,0 +42040,Male,32,Diploma,1,83,65,45,97,2.0,7,89,Semi-Urban,ML Engineer,86067,1 +42041,Male,42,Diploma,6,84,48,4,23,9.0,3,23,Urban,Software Engineer,146700,0 +42042,Female,58,Diploma,14,34,76,32,85,8.0,7,91,Urban,HR Executive,117805,0 +42043,Female,36,Masters,19,84,35,74,10,1.0,3,77,Rural,Software Engineer,83859,1 +42044,Male,32,Diploma,12,22,6,98,34,4.0,4,74,Rural,HR Executive,40881,0 +42045,Male,45,Masters,15,49,57,83,94,4.0,3,84,Semi-Urban,Data Analyst,70656,1 +42046,Female,47,PhD,17,19,49,27,39,6.0,3,75,Urban,ML Engineer,96270,0 +42047,Male,29,Masters,1,3,10,95,51,4.0,4,86,Urban,Data Analyst,120602,0 +42048,Female,52,High School,14,88,8,4,50,6.0,2,32,Urban,Manager,70956,0 +42049,Female,27,Bachelors,7,63,11,94,97,2.0,3,53,Semi-Urban,Manager,147516,0 +42050,Other,33,High School,3,44,61,66,32,7.0,5,20,Semi-Urban,ML Engineer,24313,0 +42051,Female,36,Bachelors,17,72,85,6,42,9.0,7,24,Semi-Urban,Manager,131556,0 +42052,Male,48,High School,18,66,70,74,97,0.0,5,32,Urban,HR Executive,78755,1 +42053,Female,46,Bachelors,15,4,46,88,50,5.0,5,22,Rural,Manager,94307,0 +42054,Male,41,Masters,6,65,0,80,41,6.0,4,44,Urban,Software Engineer,142509,0 +42055,Male,42,Masters,14,40,15,74,59,0.0,0,0,Urban,Data Analyst,88066,0 +42056,Male,59,Bachelors,13,50,88,19,39,5.0,0,49,Urban,Software Engineer,63615,0 +42057,Male,39,Diploma,14,32,8,64,50,8.0,1,45,Urban,Manager,112392,0 +42058,Male,33,Diploma,17,97,99,53,90,3.0,5,94,Rural,Manager,44394,1 +42059,Male,47,Diploma,16,1,54,41,97,6.0,1,9,Semi-Urban,ML Engineer,59343,0 +42060,Male,26,High School,15,60,31,53,8,8.0,0,6,Urban,ML Engineer,72137,0 +42061,Other,42,Diploma,8,70,20,29,46,2.0,1,44,Urban,Software Engineer,40021,0 +42062,Male,47,Masters,0,55,36,90,22,6.0,4,2,Urban,ML Engineer,135874,0 +42063,Male,30,High School,13,41,32,86,63,2.0,1,8,Rural,Software Engineer,109719,0 +42064,Male,21,Bachelors,16,55,19,33,48,1.0,7,83,Urban,Data Analyst,145968,0 +42065,Male,34,Masters,5,48,79,15,42,8.0,1,47,Semi-Urban,Data Analyst,59338,0 +42066,Female,40,Bachelors,2,27,54,91,90,1.0,1,52,Urban,ML Engineer,24615,0 +42067,Female,24,PhD,11,41,28,90,63,1.0,2,27,Rural,HR Executive,147037,0 +42068,Male,39,Diploma,5,11,42,43,9,4.0,5,25,Urban,Data Analyst,34675,0 +42069,Male,48,Diploma,3,80,12,94,33,9.0,7,64,Semi-Urban,ML Engineer,34873,1 +42070,Female,52,Diploma,19,32,92,70,62,5.0,3,93,Rural,ML Engineer,102449,1 +42071,Male,35,Masters,11,16,73,5,26,7.0,5,30,Urban,HR Executive,79144,0 +42072,Male,41,Bachelors,3,96,42,57,86,6.0,7,8,Semi-Urban,Software Engineer,52417,0 +42073,Female,26,Bachelors,0,57,95,88,86,7.0,2,79,Rural,Manager,75734,1 +42074,Female,27,Diploma,7,82,43,52,29,9.0,6,32,Rural,HR Executive,84687,0 +42075,Male,40,Diploma,5,53,18,13,51,9.0,0,92,Semi-Urban,Data Analyst,106400,0 +42076,Male,43,High School,0,16,43,72,63,1.0,7,13,Semi-Urban,Software Engineer,80397,0 +42077,Female,43,Bachelors,4,32,62,2,33,2.0,6,80,Semi-Urban,Manager,53153,0 +42078,Male,36,Bachelors,11,80,25,80,69,4.0,3,30,Rural,ML Engineer,25507,0 +42079,Female,46,High School,15,53,82,51,29,1.0,6,87,Rural,ML Engineer,145334,1 +42080,Male,34,Diploma,11,92,3,37,64,3.0,3,74,Rural,Manager,31230,0 +42081,Male,43,Bachelors,1,41,63,14,25,7.0,5,29,Urban,Software Engineer,82474,0 +42082,Male,32,Diploma,13,9,69,89,41,5.0,7,80,Rural,HR Executive,112140,1 +42083,Female,42,High School,18,52,67,89,33,4.0,5,69,Semi-Urban,Data Analyst,105987,1 +42084,Female,27,Bachelors,13,49,82,24,31,3.0,7,42,Semi-Urban,Manager,36965,0 +42085,Female,30,Bachelors,13,71,37,55,33,1.0,2,7,Urban,Manager,69610,0 +42086,Male,42,Diploma,7,95,74,23,36,9.0,3,44,Urban,HR Executive,70252,1 +42087,Female,49,Masters,12,43,14,88,21,2.0,2,82,Semi-Urban,ML Engineer,109681,0 +42088,Female,42,Diploma,1,19,61,91,62,4.0,3,90,Urban,Software Engineer,145739,1 +42089,Male,52,Bachelors,14,46,81,18,73,5.0,2,83,Urban,Data Analyst,145643,0 +42090,Other,59,Bachelors,1,12,45,7,10,8.0,7,46,Semi-Urban,HR Executive,77883,0 +42091,Female,55,Bachelors,5,79,22,97,37,9.0,2,47,Semi-Urban,ML Engineer,124161,1 +42092,Other,37,Bachelors,7,5,62,60,94,8.0,7,90,Urban,Manager,25111,0 +42093,Female,22,Diploma,11,30,60,64,83,9.0,3,52,Semi-Urban,HR Executive,78892,0 +42094,Female,36,Masters,4,60,36,37,70,6.0,5,37,Urban,Manager,66709,0 +42095,Female,40,Masters,3,70,68,57,53,9.0,7,78,Urban,HR Executive,70264,1 +42096,Male,27,Diploma,4,70,50,10,72,2.0,2,47,Urban,Manager,36682,0 +42097,Female,21,Diploma,17,54,92,37,47,4.0,0,72,Semi-Urban,Manager,120615,1 +42098,Male,42,Bachelors,19,47,61,72,20,9.0,5,9,Urban,Manager,47349,0 +42099,Female,30,Bachelors,14,18,46,72,75,3.0,0,46,Urban,Manager,67841,0 +42100,Female,43,Bachelors,5,47,27,75,84,9.0,5,42,Urban,Data Analyst,34795,0 +42101,Female,37,High School,10,93,66,29,77,3.0,2,43,Urban,Data Analyst,125889,0 +42102,Female,25,Diploma,18,41,56,3,73,8.0,5,70,Rural,Manager,93243,0 +42103,Male,52,Masters,18,44,48,39,98,4.0,5,73,Urban,Manager,52620,0 +42104,Male,39,Diploma,8,84,94,79,83,4.0,2,43,Urban,Software Engineer,128717,1 +42105,Male,22,High School,2,53,12,42,21,9.0,2,96,Urban,Software Engineer,50937,0 +42106,Male,31,Bachelors,8,21,71,46,43,9.0,4,60,Semi-Urban,HR Executive,115078,0 +42107,Female,51,Masters,13,3,70,47,67,4.0,5,87,Semi-Urban,Software Engineer,101885,0 +42108,Male,29,Diploma,1,68,72,73,94,7.0,5,50,Urban,Manager,37847,1 +42109,Male,53,Bachelors,0,85,48,26,21,4.0,0,90,Urban,Manager,112469,1 +42110,Male,24,Masters,0,65,17,88,9,1.0,4,66,Semi-Urban,Data Analyst,143841,1 +42111,Male,44,Bachelors,16,37,79,72,52,3.0,7,3,Semi-Urban,Data Analyst,62500,0 +42112,Female,48,Diploma,16,5,33,4,20,5.0,1,26,Urban,HR Executive,85817,0 +42113,Female,25,Bachelors,1,65,6,84,46,1.0,3,37,Rural,HR Executive,62764,0 +42114,Male,24,Bachelors,17,20,53,58,96,8.0,4,12,Semi-Urban,Data Analyst,55474,0 +42115,Female,55,Bachelors,9,7,79,48,74,3.0,2,0,Semi-Urban,Data Analyst,27316,0 +42116,Male,50,Bachelors,2,3,11,31,66,6.0,6,96,Urban,HR Executive,94107,0 +42117,Female,34,Bachelors,18,83,92,40,19,3.0,5,32,Urban,Manager,148533,1 +42118,Male,43,Bachelors,18,10,50,52,3,5.0,0,72,Urban,HR Executive,127564,0 +42119,Other,36,Masters,18,95,54,2,54,5.0,4,98,Semi-Urban,Data Analyst,119526,1 +42120,Male,50,Bachelors,7,39,85,15,28,5.0,2,92,Semi-Urban,ML Engineer,149882,0 +42121,Female,37,Bachelors,8,9,58,76,50,3.0,0,43,Urban,ML Engineer,48357,0 +42122,Male,59,Diploma,6,34,66,26,99,2.0,0,25,Semi-Urban,HR Executive,146412,0 +42123,Male,23,Diploma,14,86,74,0,2,0.0,7,0,Urban,ML Engineer,127209,0 +42124,Male,47,Bachelors,4,70,53,1,59,8.0,3,41,Semi-Urban,ML Engineer,103000,0 +42125,Male,21,Masters,2,42,76,90,32,0.0,4,67,Urban,Software Engineer,75042,1 +42126,Female,28,Diploma,1,89,57,83,49,7.0,0,77,Urban,ML Engineer,148941,1 +42127,Male,47,Diploma,2,23,85,70,38,4.0,5,7,Urban,HR Executive,132360,0 +42128,Female,42,High School,16,78,86,15,63,5.0,0,91,Urban,Software Engineer,52557,1 +42129,Female,43,PhD,19,0,90,59,2,2.0,5,44,Semi-Urban,Data Analyst,32001,0 +42130,Male,49,Masters,13,98,7,38,61,1.0,2,64,Rural,Manager,116361,0 +42131,Male,35,Diploma,9,25,26,75,20,0.0,5,20,Urban,Software Engineer,90491,0 +42132,Female,54,Bachelors,13,30,89,12,56,2.0,1,61,Rural,HR Executive,64879,0 +42133,Male,49,Bachelors,3,95,6,23,1,6.0,3,71,Urban,Manager,68875,0 +42134,Male,55,Masters,13,27,41,27,88,8.0,3,45,Urban,Software Engineer,24851,0 +42135,Female,45,Bachelors,19,31,72,89,19,6.0,7,90,Urban,Software Engineer,126619,1 +42136,Male,58,Bachelors,10,0,99,93,18,5.0,6,92,Rural,ML Engineer,52403,1 +42137,Male,45,Bachelors,0,21,3,31,86,4.0,6,23,Urban,Software Engineer,93393,0 +42138,Male,34,Bachelors,7,6,36,23,39,5.0,1,50,Urban,Software Engineer,60379,0 +42139,Other,36,High School,18,28,34,90,32,0.0,5,79,Semi-Urban,HR Executive,72212,0 +42140,Male,33,Bachelors,16,87,91,28,95,7.0,3,58,Urban,Software Engineer,41223,1 +42141,Other,25,High School,7,18,38,19,55,7.0,2,46,Urban,Data Analyst,98887,0 +42142,Male,30,Bachelors,7,41,48,83,94,4.0,3,90,Urban,Data Analyst,101579,1 +42143,Male,37,Masters,5,28,89,6,30,7.0,4,70,Urban,Manager,24061,0 +42144,Female,28,Masters,3,99,26,46,43,3.0,4,2,Semi-Urban,Software Engineer,92920,0 +42145,Male,42,Diploma,0,13,4,39,48,0.0,1,20,Urban,ML Engineer,56604,0 +42146,Male,26,Bachelors,18,14,39,5,49,7.0,6,58,Urban,ML Engineer,93977,0 +42147,Male,54,Diploma,17,38,75,49,46,5.0,3,34,Urban,Software Engineer,45360,0 +42148,Other,30,Bachelors,15,3,92,9,42,9.0,5,99,Semi-Urban,Data Analyst,42986,0 +42149,Male,25,Masters,18,56,26,0,66,4.0,2,19,Urban,Manager,130307,0 +42150,Female,40,Bachelors,8,68,12,44,21,8.0,0,7,Urban,Data Analyst,52040,0 +42151,Male,48,Masters,15,89,25,52,41,5.0,7,40,Urban,Data Analyst,61019,0 +42152,Male,34,Bachelors,18,87,30,16,69,8.0,3,81,Urban,Data Analyst,127935,0 +42153,Male,46,Diploma,4,68,13,42,67,9.0,7,65,Urban,HR Executive,37744,0 +42154,Female,54,High School,14,22,41,43,23,9.0,4,30,Urban,Software Engineer,121195,0 +42155,Female,50,Masters,4,17,5,7,13,7.0,1,75,Urban,Data Analyst,51799,0 +42156,Female,56,Bachelors,2,76,56,79,73,1.0,6,23,Urban,Manager,40223,0 +42157,Male,34,Bachelors,8,32,41,85,10,4.0,3,28,Urban,ML Engineer,70604,0 +42158,Male,24,Masters,13,62,88,39,52,7.0,3,63,Urban,Software Engineer,44008,1 +42159,Female,55,Masters,15,22,94,15,86,5.0,6,14,Urban,Manager,79003,0 +42160,Female,56,Diploma,19,11,10,4,39,9.0,7,42,Urban,HR Executive,21832,0 +42161,Female,48,Bachelors,18,40,71,86,11,1.0,3,54,Urban,Software Engineer,48379,1 +42162,Male,24,Bachelors,10,37,81,34,95,9.0,6,66,Semi-Urban,ML Engineer,46799,0 +42163,Other,42,Bachelors,13,67,41,21,0,4.0,7,58,Urban,HR Executive,93014,0 +42164,Male,58,Bachelors,8,87,5,72,0,4.0,6,77,Semi-Urban,ML Engineer,88508,1 +42165,Male,55,High School,12,33,84,81,27,1.0,5,98,Rural,Manager,90749,1 +42166,Female,26,Bachelors,12,73,49,98,69,3.0,1,33,Rural,ML Engineer,98455,1 +42167,Female,29,Bachelors,10,80,12,44,39,3.0,3,15,Urban,Software Engineer,51121,0 +42168,Male,29,Masters,9,72,56,78,68,6.0,1,75,Rural,Software Engineer,66492,1 +42169,Female,43,Masters,6,80,85,31,17,7.0,4,85,Semi-Urban,Software Engineer,99675,1 +42170,Male,53,Masters,13,75,74,55,50,0.0,5,91,Urban,Data Analyst,119473,1 +42171,Male,25,High School,14,27,62,11,13,5.0,1,42,Rural,Data Analyst,57210,0 +42172,Female,35,Masters,3,85,39,60,2,9.0,7,24,Urban,HR Executive,53857,0 +42173,Male,55,Bachelors,16,52,19,83,54,3.0,7,55,Urban,ML Engineer,50241,0 +42174,Male,28,Masters,5,47,78,86,3,0.0,0,72,Rural,Manager,70232,1 +42175,Male,42,Bachelors,7,42,82,87,59,0.0,0,42,Rural,Data Analyst,110029,1 +42176,Male,44,Bachelors,14,37,76,99,25,3.0,3,23,Semi-Urban,ML Engineer,134448,1 +42177,Male,33,Bachelors,12,26,40,71,89,6.0,2,1,Semi-Urban,ML Engineer,76154,0 +42178,Female,33,Bachelors,2,55,79,71,90,3.0,5,57,Urban,HR Executive,109153,1 +42179,Male,53,High School,2,49,24,96,37,7.0,6,19,Semi-Urban,Data Analyst,89421,0 +42180,Male,41,Bachelors,15,1,24,47,78,7.0,7,9,Urban,Software Engineer,113528,0 +42181,Female,33,Masters,8,28,16,48,91,4.0,4,68,Urban,Software Engineer,100083,0 +42182,Female,28,Bachelors,18,28,1,46,96,9.0,1,29,Urban,ML Engineer,33558,0 +42183,Female,27,Bachelors,16,81,89,46,82,6.0,4,10,Semi-Urban,Manager,46318,0 +42184,Male,33,Masters,14,74,64,58,96,5.0,4,51,Urban,ML Engineer,79109,1 +42185,Male,21,Bachelors,12,37,48,50,77,3.0,3,57,Semi-Urban,Software Engineer,61246,0 +42186,Female,48,Diploma,5,56,8,63,58,2.0,7,36,Urban,HR Executive,66169,0 +42187,Male,56,High School,6,51,0,2,61,5.0,5,55,Semi-Urban,Data Analyst,30418,0 +42188,Male,55,Bachelors,18,25,11,69,66,5.0,2,90,Semi-Urban,ML Engineer,146921,0 +42189,Female,41,Masters,4,91,15,86,95,3.0,3,95,Urban,HR Executive,122196,1 +42190,Male,22,High School,16,20,37,98,69,4.0,1,89,Semi-Urban,Software Engineer,60068,1 +42191,Other,45,Bachelors,17,56,75,8,0,2.0,0,63,Urban,ML Engineer,55243,0 +42192,Female,43,Bachelors,16,9,26,59,60,1.0,7,20,Urban,HR Executive,26344,0 +42193,Female,41,Bachelors,5,46,29,4,2,8.0,3,53,Urban,Software Engineer,96826,0 +42194,Female,37,Masters,19,5,83,91,98,4.0,2,12,Semi-Urban,HR Executive,23203,0 +42195,Male,44,Diploma,4,39,40,16,7,3.0,1,1,Semi-Urban,ML Engineer,100373,0 +42196,Female,53,Bachelors,0,52,54,15,67,5.0,4,5,Urban,Software Engineer,117107,0 +42197,Female,36,Bachelors,7,16,7,11,90,8.0,4,12,Rural,Data Analyst,137243,0 +42198,Male,37,Masters,0,1,41,84,14,8.0,1,58,Urban,Manager,62932,0 +42199,Female,36,High School,17,56,44,42,14,1.0,3,4,Semi-Urban,ML Engineer,110542,0 +42200,Female,25,Bachelors,16,39,14,79,46,8.0,7,85,Urban,Software Engineer,80359,0 +42201,Other,55,Diploma,4,14,53,71,97,9.0,1,3,Semi-Urban,ML Engineer,129576,0 +42202,Female,29,Diploma,8,7,88,35,3,7.0,3,97,Rural,Data Analyst,36253,0 +42203,Male,50,Masters,12,36,54,49,18,8.0,1,32,Semi-Urban,HR Executive,57790,0 +42204,Male,42,Bachelors,0,65,63,60,74,6.0,1,24,Rural,HR Executive,92297,0 +42205,Male,58,Diploma,19,93,11,62,40,3.0,2,64,Rural,Software Engineer,124394,0 +42206,Male,57,High School,3,75,48,80,81,5.0,7,66,Urban,HR Executive,117505,1 +42207,Male,36,Masters,9,21,17,23,26,5.0,1,69,Rural,HR Executive,49500,0 +42208,Male,42,Bachelors,16,53,8,82,71,5.0,6,77,Semi-Urban,ML Engineer,98515,0 +42209,Female,47,Bachelors,8,45,77,94,27,3.0,2,65,Urban,Data Analyst,49480,1 +42210,Male,27,Bachelors,10,47,67,43,52,5.0,2,66,Urban,Data Analyst,130203,0 +42211,Male,58,High School,16,39,19,95,12,3.0,5,38,Urban,Data Analyst,65708,0 +42212,Male,49,Bachelors,4,43,43,9,36,2.0,0,72,Semi-Urban,HR Executive,41803,0 +42213,Female,53,Masters,6,47,94,12,87,7.0,7,44,Rural,Software Engineer,109989,0 +42214,Other,55,PhD,0,45,38,24,82,3.0,2,18,Urban,Data Analyst,29976,0 +42215,Female,46,High School,18,92,38,71,34,7.0,4,25,Semi-Urban,ML Engineer,42264,0 +42216,Male,35,Bachelors,0,57,42,80,44,6.0,6,59,Urban,HR Executive,21094,1 +42217,Male,44,Bachelors,4,41,55,97,51,1.0,5,44,Urban,Data Analyst,93308,1 +42218,Female,23,Bachelors,16,70,35,35,77,2.0,7,19,Semi-Urban,Software Engineer,62844,0 +42219,Male,25,Masters,1,31,63,73,43,2.0,2,45,Urban,Data Analyst,117930,0 +42220,Other,41,High School,5,4,3,60,38,3.0,7,45,Semi-Urban,Software Engineer,143480,0 +42221,Male,30,High School,19,96,39,22,6,8.0,1,1,Urban,HR Executive,142510,0 +42222,Male,46,Bachelors,4,92,61,6,10,7.0,0,40,Rural,Manager,129879,0 +42223,Male,59,High School,3,1,75,13,41,0.0,7,78,Urban,Software Engineer,100520,0 +42224,Female,24,Bachelors,2,44,76,86,47,0.0,6,71,Urban,Data Analyst,72527,1 +42225,Male,55,Bachelors,19,22,49,45,68,3.0,1,40,Semi-Urban,HR Executive,84896,0 +42226,Male,39,Bachelors,7,23,13,98,67,2.0,1,57,Urban,Software Engineer,42909,0 +42227,Male,25,Masters,11,96,36,65,86,5.0,5,17,Urban,ML Engineer,127447,0 +42228,Male,26,Masters,13,88,21,15,9,1.0,2,0,Urban,HR Executive,35811,0 +42229,Other,35,Masters,7,90,75,21,64,5.0,5,60,Urban,Manager,69050,1 +42230,Male,26,Bachelors,5,56,47,51,3,6.0,0,84,Urban,Software Engineer,125165,1 +42231,Male,42,High School,15,91,87,42,16,9.0,7,77,Urban,Manager,96296,1 +42232,Male,24,Diploma,13,82,70,10,35,5.0,7,68,Rural,ML Engineer,90909,0 +42233,Male,35,Diploma,18,16,24,4,53,7.0,0,1,Semi-Urban,Manager,74166,0 +42234,Male,51,Bachelors,0,0,65,42,64,8.0,5,82,Rural,Manager,54289,0 +42235,Male,49,Masters,19,78,92,55,46,3.0,1,14,Semi-Urban,Software Engineer,141152,1 +42236,Female,43,Bachelors,9,26,28,92,69,6.0,0,0,Urban,Manager,125735,0 +42237,Female,22,Bachelors,9,13,73,38,68,0.0,5,4,Rural,Manager,141220,0 +42238,Male,25,Bachelors,10,37,82,44,54,4.0,7,39,Urban,Data Analyst,86890,0 +42239,Female,24,PhD,11,27,19,81,81,1.0,5,42,Urban,Manager,53489,0 +42240,Female,25,Bachelors,14,4,90,26,8,6.0,7,95,Semi-Urban,ML Engineer,22005,0 +42241,Male,52,Diploma,0,48,34,77,42,2.0,3,48,Urban,Software Engineer,49084,0 +42242,Male,36,Bachelors,4,74,25,13,69,3.0,7,37,Urban,Manager,40680,0 +42243,Female,56,Bachelors,12,57,86,47,67,4.0,7,48,Urban,HR Executive,35610,0 +42244,Female,24,Masters,12,86,48,42,4,6.0,0,84,Semi-Urban,Data Analyst,42757,1 +42245,Male,29,Bachelors,17,17,88,66,58,0.0,4,35,Urban,Manager,120900,0 +42246,Male,49,Masters,19,51,70,74,13,6.0,6,60,Semi-Urban,HR Executive,98862,1 +42247,Male,22,High School,8,24,14,15,53,1.0,0,77,Urban,Manager,65649,0 +42248,Male,48,Diploma,13,56,14,89,86,3.0,2,73,Urban,ML Engineer,93509,0 +42249,Female,34,Diploma,3,26,80,46,52,4.0,7,48,Urban,Data Analyst,37741,0 +42250,Female,21,Diploma,8,66,10,57,57,2.0,3,29,Urban,HR Executive,45572,0 +42251,Female,58,Bachelors,18,36,90,94,15,1.0,5,35,Semi-Urban,HR Executive,112093,1 +42252,Male,57,Diploma,3,90,52,49,23,0.0,3,92,Semi-Urban,HR Executive,80995,1 +42253,Male,59,Bachelors,12,67,85,34,37,7.0,6,40,Semi-Urban,HR Executive,119231,0 +42254,Female,40,Bachelors,6,88,22,10,49,1.0,3,27,Urban,Software Engineer,145641,0 +42255,Male,37,Masters,4,99,50,25,82,2.0,5,9,Semi-Urban,Software Engineer,126079,0 +42256,Female,36,Bachelors,15,57,7,89,11,3.0,1,81,Rural,HR Executive,99804,0 +42257,Female,23,PhD,7,21,8,48,86,6.0,3,77,Urban,HR Executive,103357,0 +42258,Female,30,Bachelors,13,5,89,5,99,6.0,5,77,Urban,ML Engineer,35417,0 +42259,Female,25,Diploma,18,45,58,8,4,6.0,4,71,Urban,Data Analyst,74343,0 +42260,Female,37,Diploma,7,58,94,47,88,1.0,2,0,Urban,Manager,142715,0 +42261,Male,29,Bachelors,16,60,59,48,49,8.0,4,61,Rural,Software Engineer,104685,0 +42262,Female,29,PhD,15,72,68,25,96,3.0,2,45,Urban,Software Engineer,57445,0 +42263,Male,42,Masters,14,70,42,14,12,2.0,1,53,Semi-Urban,ML Engineer,125661,0 +42264,Other,58,High School,0,77,89,25,81,7.0,1,20,Urban,ML Engineer,108733,0 +42265,Male,40,Diploma,17,35,91,89,76,2.0,3,5,Urban,HR Executive,74708,0 +42266,Male,30,Masters,4,72,74,87,40,0.0,3,14,Rural,ML Engineer,65261,1 +42267,Female,31,Masters,17,32,59,50,57,1.0,3,5,Urban,ML Engineer,64231,0 +42268,Female,33,Bachelors,18,6,56,89,54,8.0,0,92,Urban,ML Engineer,117649,1 +42269,Female,48,High School,7,85,55,55,9,8.0,5,49,Rural,Data Analyst,20255,1 +42270,Male,26,Masters,4,78,58,52,62,0.0,5,79,Semi-Urban,ML Engineer,55283,1 +42271,Female,37,Bachelors,8,8,93,99,89,0.0,0,8,Rural,ML Engineer,88805,0 +42272,Male,28,Bachelors,4,65,68,56,3,2.0,6,72,Rural,Software Engineer,146765,1 +42273,Male,47,PhD,13,80,16,41,76,1.0,5,43,Urban,Software Engineer,149940,0 +42274,Female,35,PhD,3,0,63,68,26,2.0,6,4,Rural,Data Analyst,146984,0 +42275,Female,38,Diploma,13,25,79,18,47,5.0,5,73,Urban,ML Engineer,147715,0 +42276,Male,38,Diploma,15,49,74,53,17,1.0,6,55,Rural,Data Analyst,115324,0 +42277,Male,52,High School,18,76,42,17,66,5.0,6,54,Urban,Data Analyst,107758,0 +42278,Female,39,Bachelors,6,0,98,87,83,7.0,0,50,Rural,ML Engineer,97768,0 +42279,Female,28,Diploma,7,1,8,14,33,4.0,2,53,Rural,Manager,66527,0 +42280,Male,52,Masters,3,71,99,84,38,6.0,4,21,Urban,Data Analyst,134224,1 +42281,Female,51,Bachelors,14,5,87,64,97,2.0,3,77,Urban,HR Executive,97267,0 +42282,Female,22,Diploma,3,7,73,19,36,6.0,3,1,Urban,Software Engineer,44599,0 +42283,Male,58,Bachelors,8,79,43,79,44,3.0,1,50,Urban,Manager,85928,1 +42284,Male,56,Masters,11,25,36,21,38,8.0,2,29,Semi-Urban,Manager,48517,0 +42285,Male,48,Bachelors,8,9,47,33,37,1.0,6,14,Rural,ML Engineer,25767,0 +42286,Female,42,Masters,5,86,25,96,27,5.0,2,95,Urban,Software Engineer,40269,1 +42287,Male,52,Masters,18,79,60,80,89,3.0,4,85,Semi-Urban,Software Engineer,66670,1 +42288,Female,34,Bachelors,3,93,30,22,57,6.0,2,90,Urban,ML Engineer,111788,0 +42289,Female,24,Bachelors,7,51,18,20,65,3.0,6,88,Urban,Software Engineer,93591,0 +42290,Female,30,Bachelors,9,10,26,47,41,6.0,2,62,Urban,Data Analyst,146643,0 +42291,Male,50,High School,13,69,57,2,70,1.0,0,72,Urban,Data Analyst,74842,0 +42292,Male,57,Bachelors,8,91,74,14,69,6.0,5,56,Urban,Manager,91532,1 +42293,Female,43,Masters,8,73,74,84,66,4.0,4,22,Semi-Urban,ML Engineer,122941,1 +42294,Female,25,Bachelors,2,31,95,40,33,9.0,1,2,Urban,HR Executive,49386,0 +42295,Male,27,High School,19,99,87,83,56,6.0,7,42,Rural,Software Engineer,62143,1 +42296,Male,59,Bachelors,11,55,70,19,82,9.0,3,64,Semi-Urban,ML Engineer,134818,0 +42297,Female,44,Bachelors,13,62,82,33,30,8.0,0,43,Semi-Urban,Manager,31840,0 +42298,Male,34,Diploma,19,81,48,34,12,2.0,6,28,Urban,Data Analyst,107021,0 +42299,Female,21,Masters,18,96,44,86,0,4.0,6,44,Semi-Urban,Data Analyst,20030,1 +42300,Male,40,Diploma,13,18,21,1,9,4.0,3,27,Rural,Manager,67601,0 +42301,Female,40,Masters,10,77,56,91,95,3.0,2,89,Rural,HR Executive,78234,1 +42302,Male,55,Masters,0,10,82,92,45,7.0,5,25,Semi-Urban,ML Engineer,26143,0 +42303,Female,56,Bachelors,18,31,17,29,33,3.0,5,91,Urban,HR Executive,123633,0 +42304,Male,56,Bachelors,8,78,80,0,76,3.0,6,80,Semi-Urban,Manager,72768,1 +42305,Male,32,Bachelors,15,23,28,58,37,7.0,2,37,Semi-Urban,Software Engineer,27480,0 +42306,Male,52,Bachelors,6,71,92,13,77,8.0,7,94,Semi-Urban,HR Executive,148439,1 +42307,Female,29,Bachelors,11,35,94,2,4,5.0,6,8,Urban,Manager,107916,0 +42308,Male,50,Masters,10,87,36,41,4,2.0,2,11,Urban,ML Engineer,68950,0 +42309,Male,52,Bachelors,7,67,61,3,66,4.0,4,45,Urban,ML Engineer,139940,0 +42310,Other,35,Masters,6,81,21,5,12,8.0,3,37,Semi-Urban,Manager,75394,0 +42311,Male,29,Bachelors,17,52,5,88,44,8.0,2,33,Urban,Data Analyst,120618,0 +42312,Male,29,Masters,2,68,93,55,72,9.0,4,85,Urban,HR Executive,113768,1 +42313,Female,24,Diploma,10,15,83,88,59,0.0,1,51,Urban,Data Analyst,109866,0 +42314,Female,46,Bachelors,17,76,32,75,96,8.0,4,48,Rural,Data Analyst,94692,0 +42315,Male,44,Masters,8,35,20,97,63,5.0,6,86,Urban,Data Analyst,144123,1 +42316,Female,49,Bachelors,2,23,76,70,14,5.0,3,33,Urban,ML Engineer,76267,0 +42317,Male,23,Masters,12,58,60,53,57,9.0,7,21,Urban,ML Engineer,125134,0 +42318,Male,34,Bachelors,4,70,71,77,20,2.0,7,43,Urban,HR Executive,138046,1 +42319,Male,30,Masters,0,17,96,76,23,5.0,0,67,Semi-Urban,Software Engineer,142252,1 +42320,Male,34,Bachelors,5,0,2,84,99,0.0,2,70,Urban,Software Engineer,78159,0 +42321,Male,26,Masters,1,51,29,11,80,4.0,5,24,Urban,ML Engineer,67033,0 +42322,Male,30,High School,15,72,13,25,24,3.0,4,61,Urban,Software Engineer,131087,0 +42323,Male,26,Masters,8,40,32,23,59,9.0,6,41,Semi-Urban,Manager,139135,0 +42324,Male,40,Diploma,1,15,16,50,48,6.0,1,0,Rural,Software Engineer,82115,0 +42325,Male,57,Bachelors,13,13,74,62,80,1.0,4,66,Rural,ML Engineer,101190,0 +42326,Male,32,Bachelors,18,26,11,1,58,2.0,0,97,Urban,ML Engineer,90775,0 +42327,Male,56,Masters,18,69,19,21,34,8.0,3,17,Semi-Urban,HR Executive,148982,0 +42328,Male,51,Diploma,18,60,66,34,79,7.0,1,99,Rural,Software Engineer,56159,1 +42329,Female,49,Diploma,0,30,6,2,38,9.0,3,51,Urban,ML Engineer,97046,0 +42330,Female,47,Diploma,14,82,20,0,68,7.0,5,99,Urban,Software Engineer,136070,0 +42331,Female,37,Bachelors,6,71,70,27,77,5.0,3,8,Urban,Manager,122009,0 +42332,Female,35,Masters,16,21,84,0,76,2.0,1,38,Urban,Software Engineer,144066,0 +42333,Male,23,Masters,6,32,82,0,93,3.0,1,32,Urban,HR Executive,101073,0 +42334,Female,48,Diploma,2,11,52,80,3,6.0,5,72,Semi-Urban,Manager,31752,0 +42335,Female,57,Bachelors,10,85,82,12,83,4.0,5,38,Urban,HR Executive,87866,0 +42336,Male,38,Masters,3,49,11,89,16,8.0,2,79,Semi-Urban,HR Executive,64826,0 +42337,Female,33,Bachelors,19,31,69,92,77,0.0,6,47,Urban,ML Engineer,148473,0 +42338,Male,47,Bachelors,13,81,4,48,57,6.0,1,17,Urban,Software Engineer,22435,0 +42339,Male,28,Diploma,10,62,31,10,58,6.0,1,71,Urban,HR Executive,135821,0 +42340,Male,26,High School,7,36,9,89,79,0.0,4,20,Urban,Manager,116769,0 +42341,Female,41,PhD,19,26,73,10,7,2.0,3,84,Rural,ML Engineer,72564,0 +42342,Female,33,Bachelors,10,25,20,0,8,0.0,1,76,Urban,Manager,93125,0 +42343,Female,59,Bachelors,10,76,75,97,89,9.0,1,87,Rural,Data Analyst,30438,1 +42344,Male,43,Diploma,7,69,75,71,78,8.0,3,59,Urban,Manager,118233,1 +42345,Female,26,Masters,2,32,19,65,63,1.0,4,13,Urban,HR Executive,29608,0 +42346,Male,30,Bachelors,3,73,21,81,80,4.0,6,12,Urban,HR Executive,147711,0 +42347,Male,36,High School,6,52,29,17,46,8.0,6,65,Rural,Manager,77107,0 +42348,Female,46,Bachelors,3,49,86,26,11,6.0,7,43,Urban,Software Engineer,61984,0 +42349,Male,53,Bachelors,17,65,87,85,81,3.0,2,77,Urban,Data Analyst,100316,1 +42350,Male,51,Bachelors,3,35,82,97,3,5.0,7,58,Rural,HR Executive,52887,1 +42351,Male,53,Bachelors,15,59,0,15,92,8.0,7,86,Urban,HR Executive,60740,0 +42352,Male,32,Diploma,1,91,38,67,55,3.0,0,22,Semi-Urban,Data Analyst,76410,0 +42353,Male,38,Bachelors,11,96,21,0,52,0.0,3,59,Urban,Manager,130362,0 +42354,Male,39,High School,16,38,4,6,9,1.0,6,57,Urban,ML Engineer,32169,0 +42355,Male,22,Masters,18,43,74,5,98,4.0,3,21,Rural,Manager,97042,0 +42356,Male,47,Diploma,18,10,97,25,89,1.0,2,74,Urban,Data Analyst,29335,0 +42357,Male,37,Diploma,1,13,15,98,14,0.0,3,69,Urban,Data Analyst,50838,0 +42358,Female,40,Bachelors,16,98,15,88,55,9.0,2,21,Rural,Software Engineer,72303,0 +42359,Female,39,High School,15,70,86,74,5,3.0,1,91,Semi-Urban,Software Engineer,141783,1 +42360,Female,39,Bachelors,5,91,61,4,13,8.0,4,35,Semi-Urban,Data Analyst,118699,0 +42361,Female,41,PhD,12,73,33,83,68,7.0,4,26,Semi-Urban,HR Executive,76862,0 +42362,Male,48,Bachelors,18,91,59,70,56,1.0,4,4,Urban,ML Engineer,62400,0 +42363,Female,22,Bachelors,16,50,78,79,6,3.0,1,36,Urban,ML Engineer,135878,1 +42364,Female,51,High School,11,17,40,4,36,9.0,3,23,Urban,HR Executive,149308,0 +42365,Male,50,Masters,16,71,36,79,45,9.0,1,77,Urban,Manager,53238,1 +42366,Male,42,Diploma,5,28,22,90,77,7.0,0,89,Rural,Data Analyst,65477,0 +42367,Female,55,Bachelors,10,67,65,94,36,3.0,1,54,Rural,Manager,89129,1 +42368,Male,54,Bachelors,12,96,31,64,80,7.0,1,59,Urban,Software Engineer,104616,1 +42369,Female,42,High School,8,10,52,87,58,9.0,6,13,Urban,Data Analyst,86784,0 +42370,Female,48,Masters,16,65,48,89,69,7.0,6,65,Urban,HR Executive,77088,1 +42371,Male,45,PhD,3,3,56,30,32,5.0,5,36,Urban,Data Analyst,52824,0 +42372,Male,36,Bachelors,5,84,86,75,49,4.0,1,60,Urban,Manager,135361,1 +42373,Female,38,Diploma,0,64,81,2,23,5.0,4,45,Rural,Software Engineer,73700,0 +42374,Male,37,Bachelors,11,36,67,15,61,2.0,6,95,Urban,ML Engineer,27249,0 +42375,Female,29,Bachelors,5,83,28,84,42,2.0,5,62,Rural,ML Engineer,119270,1 +42376,Male,41,Bachelors,3,12,32,3,43,8.0,4,80,Urban,HR Executive,93656,0 +42377,Other,33,Bachelors,9,72,16,41,71,4.0,6,97,Urban,Software Engineer,149091,0 +42378,Male,27,Bachelors,17,48,74,91,5,2.0,6,37,Urban,ML Engineer,97080,1 +42379,Female,51,Bachelors,9,84,36,50,27,6.0,4,77,Urban,Software Engineer,48296,1 +42380,Male,26,Masters,10,79,86,92,12,5.0,6,15,Urban,HR Executive,124029,1 +42381,Male,38,Masters,1,24,10,2,51,4.0,0,26,Urban,Software Engineer,139094,0 +42382,Female,45,High School,16,92,32,26,0,6.0,7,40,Urban,Software Engineer,41196,0 +42383,Male,42,Bachelors,16,8,57,54,46,7.0,3,25,Urban,Software Engineer,71637,0 +42384,Male,27,PhD,5,37,22,6,12,6.0,4,63,Rural,HR Executive,90392,0 +42385,Male,30,Bachelors,12,15,24,34,20,1.0,3,85,Semi-Urban,Manager,114400,0 +42386,Male,33,Bachelors,3,41,86,11,10,7.0,2,45,Semi-Urban,Software Engineer,83607,0 +42387,Male,25,Bachelors,15,94,95,95,24,3.0,0,10,Urban,HR Executive,128178,1 +42388,Female,39,Masters,0,13,95,56,68,8.0,4,47,Urban,Data Analyst,83277,0 +42389,Male,23,High School,2,9,7,60,41,4.0,1,50,Rural,Software Engineer,34470,0 +42390,Male,37,High School,18,64,2,60,57,5.0,6,58,Semi-Urban,Data Analyst,81164,0 +42391,Male,39,Bachelors,9,91,42,70,10,5.0,2,37,Rural,ML Engineer,36793,1 +42392,Female,35,Diploma,15,83,96,22,93,5.0,0,48,Rural,Data Analyst,118032,1 +42393,Female,55,Diploma,2,50,26,85,37,3.0,3,40,Semi-Urban,Software Engineer,123756,0 +42394,Male,27,PhD,2,66,45,25,71,0.0,7,96,Urban,ML Engineer,99990,0 +42395,Female,53,Bachelors,4,70,96,8,26,3.0,1,24,Rural,Manager,64292,0 +42396,Female,27,Diploma,13,56,16,54,80,9.0,4,45,Semi-Urban,ML Engineer,92602,0 +42397,Male,51,PhD,14,44,55,36,8,2.0,1,46,Rural,Software Engineer,109055,0 +42398,Male,21,Bachelors,3,52,95,8,37,1.0,5,1,Urban,Data Analyst,38770,0 +42399,Male,33,Bachelors,12,73,80,57,32,0.0,2,18,Urban,Data Analyst,129918,0 +42400,Male,48,Diploma,9,3,53,26,70,5.0,3,13,Urban,Manager,83890,0 +42401,Female,36,Bachelors,3,9,92,17,99,9.0,1,74,Urban,HR Executive,27800,0 +42402,Male,45,Diploma,18,90,43,12,28,8.0,1,69,Semi-Urban,HR Executive,43070,0 +42403,Male,45,Bachelors,17,53,77,86,35,8.0,2,27,Urban,Data Analyst,43783,1 +42404,Male,45,High School,1,82,45,89,90,8.0,5,29,Urban,Data Analyst,146134,1 +42405,Female,24,Masters,13,98,60,13,80,8.0,3,40,Urban,Manager,92983,0 +42406,Male,55,Masters,17,11,87,58,6,5.0,3,99,Semi-Urban,Manager,106448,1 +42407,Male,25,Diploma,4,58,48,28,19,4.0,3,29,Rural,Software Engineer,73636,0 +42408,Other,27,Diploma,14,13,23,51,88,4.0,2,38,Urban,Software Engineer,86644,0 +42409,Male,22,Masters,0,75,92,77,9,5.0,7,65,Semi-Urban,Software Engineer,56145,1 +42410,Male,29,Masters,6,62,42,9,8,7.0,5,77,Semi-Urban,ML Engineer,50569,0 +42411,Female,33,High School,0,85,95,83,61,8.0,4,81,Urban,HR Executive,95152,1 +42412,Female,54,Diploma,0,32,20,94,5,7.0,2,58,Urban,HR Executive,106624,0 +42413,Male,45,Bachelors,10,73,26,24,61,3.0,7,94,Rural,Manager,65421,0 +42414,Female,34,Diploma,14,55,78,97,57,2.0,3,52,Urban,Data Analyst,81144,1 +42415,Female,45,High School,15,88,28,9,48,0.0,6,19,Semi-Urban,Manager,66981,0 +42416,Male,22,Masters,2,66,99,48,34,1.0,0,15,Rural,Software Engineer,100581,0 +42417,Male,28,Bachelors,5,8,54,43,88,7.0,7,24,Urban,Manager,85166,0 +42418,Female,47,Bachelors,8,1,74,1,79,1.0,0,10,Semi-Urban,Data Analyst,20198,0 +42419,Male,34,High School,5,95,55,70,32,9.0,1,58,Urban,ML Engineer,147918,1 +42420,Male,48,Bachelors,8,47,60,98,15,7.0,2,48,Urban,ML Engineer,97693,1 +42421,Female,58,Bachelors,1,84,33,66,83,3.0,2,40,Semi-Urban,ML Engineer,55604,0 +42422,Male,23,Bachelors,15,0,1,99,42,3.0,7,71,Semi-Urban,Software Engineer,85236,0 +42423,Male,26,Diploma,19,42,80,76,90,8.0,0,9,Urban,Data Analyst,139937,0 +42424,Male,59,Bachelors,2,30,60,94,95,7.0,5,96,Urban,ML Engineer,26310,1 +42425,Female,27,Bachelors,2,48,99,8,29,8.0,1,41,Urban,Software Engineer,69031,0 +42426,Male,54,Masters,2,37,11,48,87,1.0,7,75,Semi-Urban,Data Analyst,43521,0 +42427,Female,36,High School,8,69,34,11,95,9.0,0,78,Urban,Software Engineer,130175,0 +42428,Female,39,Bachelors,5,85,99,5,70,0.0,6,10,Urban,Manager,125618,0 +42429,Male,56,Diploma,9,78,35,20,38,9.0,1,91,Urban,Data Analyst,103335,0 +42430,Other,39,High School,11,62,0,47,43,5.0,7,0,Rural,Manager,73753,0 +42431,Female,39,Bachelors,11,1,85,68,14,2.0,7,19,Semi-Urban,ML Engineer,77766,0 +42432,Male,48,Diploma,9,25,36,47,78,5.0,7,36,Rural,Software Engineer,73134,0 +42433,Male,22,Masters,9,1,21,78,14,7.0,7,16,Rural,HR Executive,140223,0 +42434,Male,38,Bachelors,12,74,30,77,20,6.0,5,18,Urban,ML Engineer,53469,0 +42435,Male,27,PhD,0,86,23,96,13,7.0,3,65,Semi-Urban,ML Engineer,107742,1 +42436,Male,33,Masters,1,46,88,71,89,4.0,7,83,Semi-Urban,Manager,24673,1 +42437,Male,55,Bachelors,9,87,36,29,17,5.0,4,42,Semi-Urban,HR Executive,145036,0 +42438,Male,35,Bachelors,19,31,31,7,60,8.0,0,58,Urban,Data Analyst,27921,0 +42439,Male,53,Bachelors,4,34,77,59,31,7.0,4,42,Urban,HR Executive,92163,0 +42440,Male,42,Bachelors,7,81,52,65,92,0.0,6,94,Urban,Data Analyst,97405,1 +42441,Male,54,Bachelors,19,11,58,51,21,6.0,6,69,Rural,Software Engineer,126251,0 +42442,Male,30,High School,12,6,70,38,0,1.0,2,68,Rural,Manager,92957,0 +42443,Male,50,High School,14,83,36,93,49,7.0,5,21,Urban,Manager,114996,0 +42444,Female,52,High School,16,82,61,50,22,7.0,2,18,Urban,Data Analyst,115762,0 +42445,Male,51,Masters,13,65,32,27,70,3.0,0,50,Urban,ML Engineer,135939,0 +42446,Female,36,PhD,2,5,41,83,74,3.0,2,60,Semi-Urban,ML Engineer,35342,0 +42447,Male,39,Masters,19,99,25,79,20,8.0,6,65,Urban,ML Engineer,94503,1 +42448,Female,50,Diploma,10,94,92,12,45,6.0,0,11,Urban,Data Analyst,63831,0 +42449,Male,22,Bachelors,2,63,28,72,22,4.0,7,20,Urban,Software Engineer,85819,0 +42450,Female,50,Bachelors,13,48,93,2,47,9.0,0,52,Urban,Manager,67252,0 +42451,Male,52,High School,10,58,22,33,90,0.0,5,95,Semi-Urban,Software Engineer,50010,0 +42452,Other,57,Diploma,5,26,30,75,47,1.0,4,84,Urban,Data Analyst,85874,0 +42453,Male,44,Diploma,5,85,18,93,51,0.0,5,24,Urban,Software Engineer,82877,0 +42454,Male,46,High School,15,5,4,84,85,9.0,1,1,Urban,Software Engineer,130546,0 +42455,Male,26,Diploma,13,49,69,73,28,6.0,0,79,Rural,Manager,25791,1 +42456,Female,26,Bachelors,9,79,44,30,30,7.0,5,54,Semi-Urban,Data Analyst,119874,0 +42457,Other,39,Bachelors,8,75,13,22,31,9.0,7,32,Semi-Urban,HR Executive,65599,0 +42458,Male,53,PhD,2,20,15,22,29,4.0,3,94,Semi-Urban,ML Engineer,77388,0 +42459,Female,22,Masters,12,68,59,93,0,1.0,0,3,Semi-Urban,Data Analyst,40704,0 +42460,Female,30,Bachelors,18,34,76,73,31,6.0,0,97,Semi-Urban,ML Engineer,123823,1 +42461,Male,35,Bachelors,7,14,3,68,22,3.0,3,75,Semi-Urban,ML Engineer,83321,0 +42462,Female,24,Bachelors,13,97,16,0,53,1.0,5,4,Urban,Data Analyst,128916,0 +42463,Male,53,High School,17,86,14,25,78,3.0,7,72,Rural,Manager,106051,0 +42464,Male,25,Bachelors,6,50,21,27,52,9.0,4,74,Semi-Urban,Software Engineer,128327,0 +42465,Female,35,High School,11,79,69,50,91,2.0,7,46,Urban,HR Executive,37005,1 +42466,Male,36,High School,3,36,41,36,70,4.0,1,89,Urban,Manager,36980,0 +42467,Female,50,High School,18,15,55,52,95,7.0,5,17,Rural,HR Executive,48932,0 +42468,Female,56,Masters,0,59,69,66,46,1.0,6,94,Semi-Urban,Software Engineer,136013,1 +42469,Female,55,High School,4,79,39,32,2,7.0,1,96,Urban,Manager,88159,1 +42470,Male,22,Diploma,13,31,91,91,46,3.0,7,41,Semi-Urban,Data Analyst,104625,1 +42471,Male,37,Bachelors,7,22,21,72,67,6.0,2,4,Urban,Data Analyst,120506,0 +42472,Male,59,Bachelors,6,75,85,12,4,1.0,2,63,Urban,Software Engineer,87734,1 +42473,Other,24,High School,13,85,17,4,55,4.0,3,47,Urban,Manager,138835,0 +42474,Male,56,High School,11,24,94,83,68,5.0,7,98,Semi-Urban,Software Engineer,29074,1 +42475,Male,35,Bachelors,11,27,56,48,64,0.0,2,68,Urban,Manager,86394,0 +42476,Male,50,PhD,9,85,19,68,70,2.0,6,88,Urban,HR Executive,72569,1 +42477,Male,49,Bachelors,4,35,63,63,57,6.0,5,29,Semi-Urban,ML Engineer,119579,0 +42478,Male,34,Bachelors,6,57,22,88,70,8.0,2,70,Urban,Manager,108392,1 +42479,Male,46,High School,5,99,9,36,74,2.0,3,2,Semi-Urban,Software Engineer,20053,0 +42480,Male,42,Bachelors,14,49,17,99,1,6.0,2,10,Semi-Urban,ML Engineer,115685,0 +42481,Other,45,High School,17,90,33,30,78,7.0,6,52,Urban,Software Engineer,22177,0 +42482,Female,29,Bachelors,15,59,95,46,76,0.0,0,44,Urban,ML Engineer,148356,1 +42483,Female,36,Bachelors,15,94,58,86,13,2.0,7,9,Urban,ML Engineer,32067,1 +42484,Male,56,Masters,10,55,75,4,32,5.0,7,65,Urban,Software Engineer,26734,0 +42485,Female,25,Masters,18,74,51,49,70,1.0,4,87,Urban,ML Engineer,108180,1 +42486,Female,25,Bachelors,19,15,68,77,40,1.0,7,24,Urban,ML Engineer,123034,0 +42487,Other,41,Bachelors,15,22,68,98,86,8.0,0,31,Urban,Software Engineer,59436,0 +42488,Male,47,Bachelors,3,56,10,78,15,2.0,4,91,Urban,Manager,38607,1 +42489,Female,44,Masters,4,48,25,28,72,2.0,6,83,Urban,Software Engineer,32971,0 +42490,Male,48,Bachelors,0,45,20,42,80,8.0,6,5,Urban,Manager,138545,0 +42491,Male,43,Bachelors,19,92,81,13,76,8.0,0,48,Rural,Manager,68504,0 +42492,Male,28,Bachelors,1,1,0,21,49,0.0,2,29,Semi-Urban,Manager,113574,0 +42493,Female,22,Bachelors,2,39,70,9,63,0.0,5,27,Urban,ML Engineer,56242,0 +42494,Male,58,High School,16,77,67,61,15,8.0,2,87,Urban,Software Engineer,120526,1 +42495,Male,59,Bachelors,8,24,7,91,57,7.0,2,68,Semi-Urban,Data Analyst,24123,0 +42496,Female,22,High School,14,16,11,59,97,4.0,2,71,Urban,Manager,29544,0 +42497,Male,28,Masters,5,64,19,33,4,7.0,7,31,Rural,Data Analyst,87024,0 +42498,Male,44,Masters,7,97,36,34,85,5.0,2,34,Urban,Software Engineer,71263,0 +42499,Male,56,Masters,15,8,97,59,30,0.0,0,73,Rural,Software Engineer,21710,1 +42500,Male,22,Diploma,19,56,44,84,20,4.0,4,74,Urban,ML Engineer,97153,1 +42501,Male,46,Bachelors,5,12,26,25,43,5.0,3,17,Urban,Manager,138036,0 +42502,Male,53,Bachelors,15,74,9,47,89,7.0,0,30,Urban,HR Executive,104997,0 +42503,Other,46,Masters,3,23,20,59,73,7.0,6,44,Semi-Urban,Software Engineer,40262,0 +42504,Female,57,Masters,13,56,21,28,97,3.0,5,13,Semi-Urban,Software Engineer,49192,0 +42505,Male,57,Bachelors,10,49,78,86,55,6.0,6,28,Semi-Urban,HR Executive,24840,1 +42506,Male,33,Bachelors,17,53,35,7,26,4.0,3,33,Urban,ML Engineer,129771,0 +42507,Male,57,Diploma,15,94,32,50,91,0.0,2,68,Urban,ML Engineer,130734,1 +42508,Male,40,High School,12,0,50,11,25,2.0,1,5,Urban,HR Executive,65276,0 +42509,Male,21,Diploma,4,56,42,75,50,6.0,2,83,Semi-Urban,HR Executive,129015,1 +42510,Male,44,High School,2,85,31,72,96,0.0,6,6,Rural,Manager,53570,0 +42511,Male,58,Bachelors,2,10,90,73,69,1.0,1,68,Rural,ML Engineer,130528,1 +42512,Male,40,Masters,15,65,73,92,43,0.0,4,41,Urban,Data Analyst,89205,1 +42513,Male,40,Diploma,18,50,37,80,80,2.0,3,22,Semi-Urban,ML Engineer,81519,0 +42514,Female,24,Bachelors,12,85,76,76,18,5.0,6,86,Rural,Software Engineer,98721,1 +42515,Other,54,Bachelors,10,34,67,62,84,3.0,1,21,Urban,Software Engineer,73242,0 +42516,Female,34,Bachelors,8,18,15,91,54,0.0,4,82,Rural,HR Executive,148217,0 +42517,Other,34,Bachelors,12,56,78,2,34,7.0,6,46,Rural,Manager,22280,0 +42518,Male,53,Bachelors,11,88,21,31,29,2.0,5,53,Rural,HR Executive,123235,0 +42519,Female,29,Masters,8,82,60,12,65,4.0,0,49,Urban,HR Executive,75138,0 +42520,Male,26,Bachelors,11,56,39,93,44,6.0,4,19,Urban,Data Analyst,65313,0 +42521,Female,59,Bachelors,6,79,70,92,37,7.0,6,65,Urban,ML Engineer,66395,1 +42522,Female,41,Masters,2,79,1,77,23,2.0,4,49,Urban,ML Engineer,137369,0 +42523,Male,26,Diploma,7,42,42,66,51,7.0,7,24,Urban,Data Analyst,116768,0 +42524,Male,33,Masters,18,98,48,74,1,2.0,1,48,Semi-Urban,ML Engineer,119246,1 +42525,Male,28,PhD,8,63,59,54,12,5.0,2,7,Urban,Data Analyst,33882,0 +42526,Male,35,Masters,1,18,67,54,26,3.0,6,63,Urban,Software Engineer,52861,0 +42527,Other,59,Diploma,0,4,76,99,57,3.0,1,53,Semi-Urban,Software Engineer,66284,0 +42528,Female,40,High School,10,10,70,95,45,5.0,1,47,Urban,ML Engineer,128303,0 +42529,Male,31,Bachelors,10,27,87,73,64,5.0,2,20,Urban,Manager,54843,0 +42530,Male,26,PhD,18,96,9,80,33,4.0,4,42,Semi-Urban,Manager,110889,0 +42531,Male,32,PhD,17,25,68,66,29,5.0,5,76,Urban,Software Engineer,89659,1 +42532,Other,48,Diploma,0,61,70,52,57,0.0,3,79,Urban,Manager,29860,1 +42533,Female,24,Diploma,7,21,25,87,25,8.0,6,83,Urban,Software Engineer,58769,0 +42534,Male,44,High School,8,82,59,86,25,2.0,2,9,Rural,HR Executive,111040,1 +42535,Female,56,Bachelors,18,63,78,34,16,9.0,3,26,Semi-Urban,Manager,98863,0 +42536,Female,28,Masters,7,8,91,93,73,8.0,4,27,Urban,ML Engineer,44682,0 +42537,Male,24,High School,6,55,28,36,71,4.0,2,97,Semi-Urban,HR Executive,149003,0 +42538,Female,33,Bachelors,2,84,37,11,23,2.0,4,37,Rural,Data Analyst,66068,0 +42539,Male,23,Masters,3,97,25,40,55,8.0,7,42,Urban,HR Executive,112198,0 +42540,Male,40,Masters,18,22,87,56,93,3.0,3,88,Semi-Urban,HR Executive,58359,1 +42541,Male,55,Bachelors,16,3,74,99,93,5.0,3,83,Semi-Urban,Manager,142519,1 +42542,Female,29,Bachelors,18,99,83,81,84,0.0,3,92,Semi-Urban,HR Executive,143010,1 +42543,Male,54,High School,6,21,9,47,72,2.0,2,25,Semi-Urban,HR Executive,108552,0 +42544,Female,57,Diploma,2,15,32,60,88,3.0,7,52,Urban,Data Analyst,67771,0 +42545,Female,37,PhD,5,38,64,27,9,0.0,5,49,Rural,Manager,147044,0 +42546,Female,41,Bachelors,9,47,56,7,37,0.0,6,18,Rural,Software Engineer,125151,0 +42547,Female,21,Bachelors,15,37,20,31,51,5.0,7,49,Rural,ML Engineer,25792,0 +42548,Male,49,Bachelors,19,95,60,69,53,5.0,5,77,Semi-Urban,HR Executive,48462,1 +42549,Male,59,High School,0,43,69,67,95,9.0,1,79,Rural,Manager,97408,1 +42550,Male,27,Masters,18,73,56,62,25,9.0,5,24,Semi-Urban,ML Engineer,42885,0 +42551,Male,39,Bachelors,10,37,76,78,77,8.0,3,94,Semi-Urban,HR Executive,113077,1 +42552,Female,47,Masters,4,90,51,15,73,6.0,3,50,Urban,HR Executive,85374,0 +42553,Female,48,Masters,8,67,86,42,77,6.0,3,9,Urban,ML Engineer,77219,0 +42554,Male,24,PhD,19,50,61,45,40,3.0,4,72,Semi-Urban,Manager,85106,0 +42555,Female,32,Masters,4,2,98,51,71,1.0,3,69,Urban,Manager,123536,0 +42556,Female,55,Masters,4,95,84,78,24,0.0,6,89,Rural,Manager,33767,1 +42557,Other,35,Diploma,5,37,78,39,43,2.0,3,24,Semi-Urban,ML Engineer,63708,0 +42558,Male,45,High School,2,21,45,88,95,4.0,6,6,Urban,Manager,125456,0 +42559,Female,34,Masters,18,17,54,2,14,6.0,0,3,Urban,HR Executive,119491,0 +42560,Male,49,Diploma,9,62,25,5,15,9.0,0,92,Rural,HR Executive,128163,0 +42561,Male,56,High School,11,21,16,77,41,2.0,0,92,Urban,Data Analyst,144671,0 +42562,Male,50,Bachelors,12,42,72,96,13,0.0,0,65,Semi-Urban,Software Engineer,72208,1 +42563,Male,50,High School,14,29,44,22,70,1.0,6,96,Urban,ML Engineer,141234,0 +42564,Male,28,Masters,7,14,56,6,67,1.0,5,82,Urban,ML Engineer,50515,0 +42565,Male,58,High School,19,47,41,47,12,2.0,4,97,Urban,Data Analyst,92807,0 +42566,Female,27,Masters,4,51,77,5,33,8.0,1,50,Urban,HR Executive,127350,0 +42567,Female,52,Bachelors,1,34,97,65,7,3.0,5,48,Semi-Urban,ML Engineer,127218,1 +42568,Other,23,Bachelors,5,34,81,45,71,3.0,0,22,Urban,Manager,81615,0 +42569,Male,27,Bachelors,18,24,6,3,33,8.0,0,26,Urban,Data Analyst,67544,0 +42570,Female,27,Diploma,1,77,86,38,35,2.0,7,83,Urban,ML Engineer,85015,1 +42571,Female,58,Bachelors,15,80,0,38,87,5.0,3,32,Urban,ML Engineer,138813,0 +42572,Male,23,Diploma,17,25,76,98,21,3.0,0,59,Rural,Manager,95901,1 +42573,Female,26,Masters,11,68,12,95,33,9.0,3,14,Urban,HR Executive,55696,0 +42574,Female,30,Bachelors,10,58,7,52,86,6.0,2,76,Urban,Data Analyst,39280,0 +42575,Male,34,High School,4,60,73,82,11,6.0,4,25,Urban,Manager,89112,1 +42576,Female,58,Bachelors,2,94,15,42,74,6.0,2,80,Urban,Manager,67526,0 +42577,Female,47,Bachelors,2,7,27,95,30,0.0,0,43,Rural,Data Analyst,95202,0 +42578,Other,41,PhD,15,89,68,96,78,6.0,3,36,Semi-Urban,HR Executive,21630,1 +42579,Female,38,High School,19,72,9,91,69,0.0,7,96,Urban,ML Engineer,41039,1 +42580,Female,55,Bachelors,8,99,77,74,95,4.0,2,6,Semi-Urban,Manager,83027,1 +42581,Female,44,PhD,8,10,28,15,40,4.0,6,62,Urban,Manager,100045,0 +42582,Female,23,High School,18,73,24,76,0,9.0,3,89,Semi-Urban,HR Executive,104810,1 +42583,Other,28,Bachelors,3,32,13,22,73,7.0,2,67,Urban,HR Executive,83800,0 +42584,Female,36,Masters,10,95,66,89,98,9.0,0,33,Semi-Urban,HR Executive,23144,1 +42585,Female,33,Bachelors,10,48,95,25,21,8.0,5,76,Urban,HR Executive,87815,1 +42586,Male,57,Bachelors,2,40,72,23,6,3.0,1,13,Semi-Urban,HR Executive,92171,0 +42587,Female,35,Masters,8,2,45,71,3,7.0,3,62,Urban,ML Engineer,92327,0 +42588,Male,43,Diploma,17,36,58,65,93,1.0,0,65,Rural,Manager,47808,0 +42589,Male,59,Bachelors,13,6,89,0,73,2.0,1,5,Urban,Data Analyst,105655,0 +42590,Male,52,Bachelors,0,3,82,97,57,3.0,0,57,Urban,ML Engineer,24238,1 +42591,Male,53,Bachelors,17,31,46,81,35,9.0,0,63,Urban,Software Engineer,90425,0 +42592,Male,47,Bachelors,12,38,51,15,33,3.0,4,36,Rural,ML Engineer,117499,0 +42593,Female,30,High School,17,29,56,36,79,2.0,4,88,Urban,Manager,63419,0 +42594,Female,32,Masters,11,21,79,53,39,8.0,5,36,Rural,Manager,140999,0 +42595,Male,28,Masters,4,1,82,57,6,2.0,4,49,Urban,ML Engineer,138371,0 +42596,Female,53,Bachelors,9,0,16,47,90,3.0,5,84,Rural,ML Engineer,67219,0 +42597,Other,58,Bachelors,10,63,79,26,24,9.0,4,36,Urban,HR Executive,127696,0 +42598,Male,54,Diploma,16,27,32,7,74,3.0,7,76,Urban,Software Engineer,110925,0 +42599,Male,34,Diploma,11,81,0,81,71,6.0,2,83,Rural,Software Engineer,52040,1 +42600,Male,39,Masters,16,89,76,22,27,6.0,3,52,Rural,ML Engineer,118980,1 +42601,Female,32,High School,13,63,26,10,30,6.0,2,18,Rural,Software Engineer,102925,0 +42602,Male,57,Masters,17,65,28,25,52,5.0,0,46,Semi-Urban,ML Engineer,127269,0 +42603,Other,38,Bachelors,15,13,22,70,25,5.0,6,66,Urban,Software Engineer,64103,0 +42604,Male,26,Masters,18,23,9,21,89,9.0,0,98,Rural,Manager,119858,0 +42605,Male,25,Masters,17,25,87,42,35,4.0,7,55,Rural,Manager,147014,0 +42606,Male,55,PhD,3,44,77,30,82,5.0,0,70,Urban,HR Executive,71324,0 +42607,Male,49,PhD,18,8,14,35,45,6.0,7,32,Semi-Urban,Manager,129570,0 +42608,Female,56,Bachelors,11,8,66,66,74,5.0,2,68,Urban,HR Executive,24017,0 +42609,Male,36,High School,18,10,23,79,38,8.0,4,40,Urban,Data Analyst,59050,0 +42610,Male,58,Diploma,11,8,60,67,76,5.0,5,93,Semi-Urban,ML Engineer,32018,0 +42611,Male,47,Bachelors,2,74,97,81,61,0.0,0,58,Urban,Manager,107055,1 +42612,Female,40,Diploma,9,71,42,69,87,0.0,4,59,Semi-Urban,Data Analyst,123943,1 +42613,Female,44,Bachelors,3,39,38,72,76,6.0,5,88,Rural,Manager,110692,0 +42614,Female,27,Masters,9,57,4,19,26,4.0,4,86,Urban,ML Engineer,75971,0 +42615,Other,34,Bachelors,4,40,88,3,38,1.0,6,80,Urban,ML Engineer,71206,0 +42616,Male,24,Bachelors,18,75,95,56,40,1.0,4,77,Semi-Urban,Software Engineer,59553,1 +42617,Male,37,Masters,0,76,40,77,26,6.0,5,67,Semi-Urban,Software Engineer,140743,1 +42618,Male,53,Diploma,4,28,17,5,55,0.0,2,4,Urban,ML Engineer,85790,0 +42619,Male,44,Bachelors,8,98,6,34,66,0.0,2,63,Urban,ML Engineer,149615,0 +42620,Male,33,Bachelors,8,61,23,93,41,0.0,2,83,Rural,Manager,66087,1 +42621,Female,44,High School,15,13,93,96,8,2.0,4,82,Urban,ML Engineer,23557,1 +42622,Female,33,Diploma,19,49,18,35,88,7.0,0,6,Urban,Software Engineer,134512,0 +42623,Male,46,High School,14,30,39,24,29,8.0,6,17,Urban,Data Analyst,116727,0 +42624,Male,30,PhD,16,52,20,47,12,0.0,4,71,Urban,Data Analyst,55129,0 +42625,Female,40,Masters,15,81,98,71,25,8.0,7,51,Semi-Urban,Manager,50012,1 +42626,Other,45,Bachelors,12,88,86,99,15,8.0,0,6,Urban,HR Executive,65779,1 +42627,Male,55,High School,4,80,94,75,97,5.0,3,18,Semi-Urban,Software Engineer,47949,1 +42628,Male,34,Bachelors,5,96,30,64,82,3.0,1,18,Semi-Urban,Data Analyst,125044,0 +42629,Other,36,Masters,0,80,94,11,43,9.0,7,80,Rural,HR Executive,76641,1 +42630,Other,36,PhD,4,32,71,75,11,1.0,3,77,Rural,Manager,97112,1 +42631,Male,29,Diploma,18,30,20,70,23,0.0,1,69,Urban,ML Engineer,83185,0 +42632,Male,44,Bachelors,17,68,37,37,29,2.0,6,86,Urban,Software Engineer,85640,0 +42633,Male,40,High School,10,39,43,76,14,2.0,3,0,Urban,ML Engineer,32888,0 +42634,Female,49,Diploma,5,12,67,75,22,3.0,7,2,Urban,ML Engineer,93542,0 +42635,Male,59,Bachelors,18,86,38,98,8,4.0,0,37,Semi-Urban,HR Executive,116272,1 +42636,Female,56,High School,0,20,25,5,89,9.0,3,96,Urban,Manager,45929,0 +42637,Male,53,Bachelors,11,14,46,86,8,2.0,3,56,Rural,ML Engineer,25509,0 +42638,Female,36,Diploma,11,10,25,96,36,1.0,2,54,Urban,ML Engineer,33075,0 +42639,Female,57,Diploma,15,15,75,54,30,2.0,3,97,Rural,HR Executive,77208,1 +42640,Male,31,Bachelors,1,72,22,59,73,8.0,6,43,Urban,Data Analyst,53076,0 +42641,Male,35,Bachelors,8,91,43,47,60,9.0,2,85,Semi-Urban,HR Executive,107715,1 +42642,Male,24,Bachelors,3,87,44,35,62,3.0,4,8,Urban,HR Executive,57530,0 +42643,Female,46,Bachelors,0,62,61,29,92,9.0,1,26,Urban,Data Analyst,71932,0 +42644,Male,45,Masters,15,99,57,19,41,9.0,0,69,Urban,Manager,133457,1 +42645,Female,42,Diploma,4,68,53,0,83,4.0,3,44,Rural,Data Analyst,97079,0 +42646,Female,22,High School,1,82,97,98,59,7.0,1,50,Urban,Software Engineer,39186,1 +42647,Male,36,Bachelors,10,14,34,87,22,6.0,3,76,Rural,Software Engineer,57230,0 +42648,Female,54,Diploma,6,74,37,71,49,0.0,6,0,Rural,HR Executive,134164,0 +42649,Female,34,High School,19,91,21,55,41,6.0,2,86,Urban,Software Engineer,136008,1 +42650,Female,47,Bachelors,12,65,99,57,37,0.0,4,56,Urban,Manager,148883,1 +42651,Male,29,Bachelors,3,91,20,78,43,7.0,0,60,Semi-Urban,Software Engineer,107249,1 +42652,Female,46,Bachelors,14,23,63,71,56,7.0,2,89,Urban,Data Analyst,133597,1 +42653,Male,33,Diploma,9,2,17,32,64,3.0,5,39,Rural,Data Analyst,25153,0 +42654,Female,42,Diploma,9,56,40,41,3,1.0,1,24,Semi-Urban,Software Engineer,34114,0 +42655,Male,41,Masters,1,68,92,31,2,1.0,7,87,Urban,Data Analyst,21754,1 +42656,Female,21,Masters,7,78,93,20,40,5.0,0,59,Urban,Software Engineer,111420,1 +42657,Female,55,Diploma,12,46,83,89,18,9.0,6,8,Urban,Software Engineer,51718,0 +42658,Male,28,Masters,7,88,34,93,26,2.0,5,34,Rural,ML Engineer,51884,1 +42659,Male,56,Bachelors,18,37,89,11,73,5.0,5,50,Rural,Manager,138054,0 +42660,Male,58,Bachelors,2,56,37,4,34,1.0,6,60,Semi-Urban,ML Engineer,60897,0 +42661,Male,31,Bachelors,2,73,48,45,30,3.0,1,9,Urban,HR Executive,104931,0 +42662,Female,23,Bachelors,0,50,44,5,0,3.0,3,38,Urban,HR Executive,100248,0 +42663,Female,47,Diploma,14,59,26,36,84,5.0,0,84,Urban,ML Engineer,35420,0 +42664,Male,41,Bachelors,5,27,92,91,33,5.0,4,55,Urban,HR Executive,60625,1 +42665,Male,49,Bachelors,14,21,44,81,36,6.0,1,86,Urban,Software Engineer,124650,0 +42666,Female,55,Bachelors,4,5,18,38,13,8.0,0,40,Urban,Data Analyst,101336,0 +42667,Male,39,Masters,17,12,53,94,26,7.0,7,53,Urban,ML Engineer,97668,0 +42668,Other,31,PhD,13,75,49,25,42,4.0,3,35,Urban,Data Analyst,123989,0 +42669,Male,43,Diploma,14,48,65,94,68,6.0,4,59,Rural,Data Analyst,104776,1 +42670,Female,44,Bachelors,4,61,8,53,32,4.0,7,7,Urban,Software Engineer,116151,0 +42671,Male,42,Masters,17,93,45,50,91,6.0,0,96,Urban,Manager,31310,1 +42672,Male,44,Bachelors,7,25,0,85,74,7.0,3,0,Urban,HR Executive,47339,0 +42673,Male,26,Bachelors,11,53,38,9,15,3.0,1,85,Urban,Software Engineer,57365,0 +42674,Female,58,Bachelors,18,36,22,3,52,4.0,7,76,Semi-Urban,Data Analyst,75926,0 +42675,Male,26,Diploma,7,66,3,38,5,6.0,2,2,Rural,Data Analyst,125030,0 +42676,Female,35,Bachelors,4,59,85,90,66,1.0,6,71,Semi-Urban,Data Analyst,118409,1 +42677,Male,24,Bachelors,13,30,5,80,80,6.0,7,92,Urban,Software Engineer,20129,0 +42678,Male,33,Bachelors,2,95,42,23,82,4.0,2,18,Urban,ML Engineer,133587,0 +42679,Male,28,Bachelors,17,32,13,80,93,4.0,3,6,Rural,HR Executive,149113,0 +42680,Male,36,Bachelors,10,63,68,54,90,6.0,0,72,Semi-Urban,HR Executive,136689,1 +42681,Male,51,Diploma,12,13,56,26,59,7.0,5,27,Semi-Urban,Software Engineer,59371,0 +42682,Male,46,Diploma,3,56,4,54,13,8.0,5,93,Rural,Manager,94006,0 +42683,Female,53,Bachelors,7,73,94,11,0,2.0,6,46,Semi-Urban,HR Executive,114117,0 +42684,Other,58,Bachelors,5,4,13,53,26,6.0,1,73,Urban,Software Engineer,113632,0 +42685,Female,56,Bachelors,10,18,49,44,21,4.0,5,51,Urban,Manager,23552,0 +42686,Male,31,Bachelors,8,71,49,22,2,0.0,7,81,Urban,Manager,30606,0 +42687,Male,45,Diploma,15,31,96,87,87,5.0,1,59,Rural,Software Engineer,98793,1 +42688,Male,40,High School,7,75,64,71,90,3.0,4,89,Urban,HR Executive,39459,1 +42689,Male,49,High School,3,4,51,71,0,1.0,5,57,Urban,ML Engineer,142683,0 +42690,Male,36,Masters,19,9,60,59,60,0.0,3,42,Urban,Data Analyst,34649,0 +42691,Male,28,Bachelors,15,61,8,99,30,5.0,5,3,Rural,Manager,90929,0 +42692,Male,31,Bachelors,16,16,83,26,56,8.0,5,88,Semi-Urban,HR Executive,138616,0 +42693,Male,26,Diploma,11,27,33,28,91,7.0,2,58,Semi-Urban,Data Analyst,57916,0 +42694,Male,52,High School,7,1,18,91,17,0.0,5,57,Urban,Manager,120221,0 +42695,Male,27,Diploma,14,61,86,6,53,5.0,3,2,Rural,Manager,99951,0 +42696,Male,56,Bachelors,0,44,43,10,32,2.0,4,74,Urban,Software Engineer,48482,0 +42697,Female,43,High School,5,40,10,12,19,8.0,3,81,Semi-Urban,ML Engineer,138794,0 +42698,Male,47,Bachelors,4,55,86,30,69,2.0,7,93,Semi-Urban,ML Engineer,70613,1 +42699,Male,46,High School,11,3,8,41,88,8.0,4,2,Semi-Urban,Manager,96986,0 +42700,Male,36,Bachelors,13,75,97,23,21,6.0,3,88,Semi-Urban,Software Engineer,55664,1 +42701,Male,28,High School,14,1,51,84,20,1.0,0,94,Urban,ML Engineer,118211,0 +42702,Female,49,Masters,0,52,47,47,97,0.0,5,26,Urban,Manager,73330,0 +42703,Male,59,Diploma,14,19,35,3,16,0.0,4,33,Urban,ML Engineer,33074,0 +42704,Male,44,Masters,16,86,47,57,40,6.0,5,81,Urban,Manager,75876,1 +42705,Female,40,Masters,14,20,13,5,17,0.0,6,46,Semi-Urban,ML Engineer,60166,0 +42706,Male,47,Masters,11,94,83,21,81,2.0,0,60,Urban,Manager,70232,1 +42707,Female,41,Diploma,2,28,16,42,49,1.0,7,3,Semi-Urban,Data Analyst,83934,0 +42708,Female,27,Bachelors,3,99,36,26,98,4.0,2,89,Urban,Data Analyst,111464,1 +42709,Male,41,Diploma,6,53,32,7,44,9.0,0,70,Urban,Manager,87896,0 +42710,Male,23,Diploma,15,36,87,71,60,4.0,2,65,Urban,Software Engineer,110105,1 +42711,Female,40,Bachelors,15,3,62,79,68,9.0,6,46,Semi-Urban,Software Engineer,136923,0 +42712,Other,34,Bachelors,8,37,2,64,2,2.0,7,60,Urban,Manager,128316,0 +42713,Female,58,PhD,12,52,36,55,33,5.0,5,86,Semi-Urban,ML Engineer,36304,0 +42714,Male,41,Bachelors,11,10,82,52,81,0.0,4,56,Rural,Software Engineer,69987,0 +42715,Male,31,Masters,18,38,80,40,38,2.0,0,42,Urban,HR Executive,23000,0 +42716,Female,21,Masters,10,8,11,82,51,9.0,6,33,Semi-Urban,Data Analyst,98107,0 +42717,Male,36,Masters,7,6,38,20,46,8.0,5,31,Urban,Data Analyst,36109,0 +42718,Male,32,Masters,3,97,96,9,71,2.0,2,37,Urban,Software Engineer,115363,1 +42719,Female,32,Diploma,13,15,47,55,88,4.0,0,29,Rural,HR Executive,95830,0 +42720,Male,30,PhD,9,32,35,39,59,6.0,3,55,Urban,Software Engineer,141510,0 +42721,Female,31,High School,0,31,45,49,94,9.0,2,84,Rural,ML Engineer,101299,0 +42722,Female,56,Bachelors,9,79,19,95,95,1.0,2,66,Semi-Urban,Manager,37047,1 +42723,Male,58,High School,1,63,23,10,68,3.0,2,95,Urban,Software Engineer,76069,0 +42724,Female,52,Bachelors,2,69,57,20,65,3.0,1,34,Urban,Software Engineer,103364,0 +42725,Female,49,High School,16,66,85,68,71,4.0,5,13,Urban,HR Executive,24940,0 +42726,Male,45,Diploma,1,71,20,66,47,2.0,7,67,Urban,Manager,89683,0 +42727,Male,42,Masters,11,87,37,62,47,0.0,1,68,Rural,ML Engineer,68366,1 +42728,Male,36,High School,16,15,24,31,70,2.0,6,72,Semi-Urban,HR Executive,51635,0 +42729,Female,24,High School,2,82,83,0,22,8.0,5,54,Rural,Software Engineer,45978,0 +42730,Male,37,Diploma,7,32,51,19,12,6.0,4,12,Semi-Urban,Software Engineer,60905,0 +42731,Male,37,Diploma,1,37,99,39,54,0.0,3,29,Semi-Urban,Software Engineer,29088,0 +42732,Male,51,High School,16,48,60,79,75,1.0,1,30,Semi-Urban,Data Analyst,102002,0 +42733,Male,28,Bachelors,13,17,23,55,67,0.0,0,66,Semi-Urban,HR Executive,125318,0 +42734,Male,33,Bachelors,5,79,2,77,63,8.0,0,20,Rural,ML Engineer,30912,0 +42735,Male,47,Bachelors,11,9,8,35,44,6.0,6,88,Urban,HR Executive,106521,0 +42736,Male,44,Bachelors,17,39,46,50,80,2.0,5,11,Urban,ML Engineer,65109,0 +42737,Male,52,Masters,5,97,84,21,32,1.0,3,59,Urban,ML Engineer,137337,1 +42738,Female,37,Masters,6,37,45,68,89,2.0,5,65,Rural,HR Executive,35793,0 +42739,Female,49,High School,13,70,94,19,3,2.0,6,14,Rural,ML Engineer,109983,0 +42740,Male,34,PhD,18,92,84,75,6,6.0,7,86,Urban,HR Executive,38500,1 +42741,Female,50,High School,19,15,24,28,2,1.0,3,68,Urban,ML Engineer,109055,0 +42742,Male,57,Bachelors,18,5,0,94,19,4.0,4,86,Rural,Manager,68832,0 +42743,Male,57,Diploma,19,0,42,15,35,5.0,2,48,Rural,ML Engineer,140715,0 +42744,Male,46,Masters,15,49,61,19,57,1.0,5,40,Urban,Software Engineer,83262,0 +42745,Male,28,High School,1,64,71,40,14,5.0,3,1,Semi-Urban,Manager,75831,0 +42746,Male,36,Masters,4,53,39,70,71,1.0,0,23,Urban,Manager,110372,0 +42747,Male,22,Bachelors,16,88,64,75,48,4.0,4,92,Urban,HR Executive,35172,1 +42748,Male,45,High School,2,19,71,96,65,4.0,3,99,Rural,HR Executive,49443,1 +42749,Male,31,Bachelors,13,68,49,18,67,5.0,2,28,Urban,ML Engineer,22027,0 +42750,Male,32,Bachelors,2,51,90,11,49,0.0,2,2,Rural,ML Engineer,68914,0 +42751,Other,44,Bachelors,18,61,81,94,67,8.0,0,8,Rural,Manager,96293,1 +42752,Male,41,Bachelors,6,78,20,4,51,2.0,2,38,Urban,Manager,100612,0 +42753,Female,38,Bachelors,4,16,36,32,77,6.0,6,41,Rural,ML Engineer,129298,0 +42754,Male,33,Bachelors,10,98,75,83,17,0.0,1,53,Urban,Data Analyst,109220,1 +42755,Male,52,High School,8,91,1,89,36,9.0,6,92,Rural,HR Executive,36638,1 +42756,Other,37,Bachelors,2,8,90,10,64,3.0,0,99,Rural,Data Analyst,122783,0 +42757,Female,23,Bachelors,2,29,96,4,68,1.0,6,10,Urban,ML Engineer,122320,0 +42758,Male,47,Diploma,10,38,14,16,51,3.0,6,37,Urban,ML Engineer,46005,0 +42759,Male,52,Bachelors,16,5,74,55,79,2.0,0,18,Urban,Manager,29699,0 +42760,Male,44,High School,13,93,52,25,71,2.0,1,32,Rural,ML Engineer,65359,0 +42761,Female,40,PhD,15,32,92,57,19,3.0,1,33,Semi-Urban,ML Engineer,115871,0 +42762,Male,52,Diploma,12,21,15,71,11,4.0,6,11,Rural,Software Engineer,74217,0 +42763,Female,40,Diploma,4,64,45,73,32,4.0,6,96,Urban,Data Analyst,84206,1 +42764,Female,51,Bachelors,3,10,80,86,11,4.0,7,6,Urban,ML Engineer,120994,0 +42765,Male,33,Diploma,4,48,70,3,74,1.0,7,57,Urban,Data Analyst,67413,0 +42766,Female,33,Bachelors,4,31,44,22,15,8.0,1,51,Urban,ML Engineer,49441,0 +42767,Female,27,Bachelors,7,30,60,3,65,2.0,2,48,Urban,Software Engineer,71199,0 +42768,Male,25,Bachelors,2,17,60,85,59,3.0,7,41,Rural,HR Executive,30488,0 +42769,Male,27,Diploma,7,34,85,84,40,0.0,3,33,Rural,Data Analyst,107545,1 +42770,Female,42,High School,15,36,27,79,59,8.0,2,45,Urban,HR Executive,72181,0 +42771,Male,38,Masters,17,1,31,4,46,9.0,5,0,Urban,ML Engineer,96686,0 +42772,Female,40,Bachelors,3,33,87,98,49,4.0,3,93,Semi-Urban,HR Executive,143789,1 +42773,Male,33,Diploma,7,90,40,0,78,6.0,3,51,Rural,HR Executive,62396,0 +42774,Male,59,Bachelors,6,51,33,36,25,0.0,2,96,Semi-Urban,Software Engineer,87583,0 +42775,Other,43,Bachelors,14,97,11,7,11,1.0,3,95,Urban,Data Analyst,70751,0 +42776,Male,28,Diploma,1,98,32,75,88,8.0,4,23,Urban,Software Engineer,20758,0 +42777,Male,48,Masters,16,23,39,55,30,8.0,7,23,Urban,Data Analyst,102861,0 +42778,Female,30,PhD,3,4,81,65,32,9.0,6,69,Urban,ML Engineer,95400,0 +42779,Female,52,Bachelors,8,19,67,6,61,0.0,3,86,Urban,Data Analyst,94705,0 +42780,Male,40,High School,16,63,97,74,50,9.0,5,19,Urban,Manager,34068,1 +42781,Female,37,High School,14,7,60,62,35,2.0,4,95,Urban,ML Engineer,144304,0 +42782,Male,41,Bachelors,5,97,87,42,30,6.0,0,14,Semi-Urban,ML Engineer,148807,1 +42783,Female,43,PhD,15,80,81,49,42,5.0,4,57,Rural,Software Engineer,36838,1 +42784,Male,42,Bachelors,8,15,15,50,44,7.0,2,78,Rural,HR Executive,65298,0 +42785,Male,54,Masters,0,96,93,54,36,3.0,0,6,Rural,ML Engineer,22373,1 +42786,Female,53,Masters,10,79,48,24,94,9.0,7,1,Urban,Manager,108512,0 +42787,Female,33,Masters,3,93,1,27,45,7.0,2,68,Urban,Software Engineer,133144,0 +42788,Female,56,Bachelors,6,39,79,14,4,1.0,4,62,Urban,Manager,55453,0 +42789,Male,50,Bachelors,7,87,80,44,34,2.0,1,26,Urban,Data Analyst,122837,1 +42790,Female,41,Bachelors,10,14,47,48,76,0.0,1,78,Urban,HR Executive,92437,0 +42791,Male,24,Bachelors,11,54,79,54,78,8.0,7,25,Semi-Urban,Data Analyst,78384,0 +42792,Male,41,Diploma,19,54,21,96,97,3.0,1,48,Rural,HR Executive,22420,0 +42793,Female,30,High School,18,67,90,33,74,0.0,1,14,Rural,Software Engineer,89958,0 +42794,Male,50,Bachelors,17,28,45,63,12,1.0,5,14,Urban,HR Executive,83925,0 +42795,Male,56,Bachelors,5,30,84,67,31,1.0,4,97,Urban,ML Engineer,105694,1 +42796,Other,26,Bachelors,11,45,28,15,13,1.0,5,57,Rural,HR Executive,25750,0 +42797,Other,41,PhD,16,64,8,10,89,5.0,3,47,Urban,Data Analyst,71413,0 +42798,Female,56,Diploma,16,66,76,61,99,8.0,4,68,Rural,HR Executive,104845,1 +42799,Male,59,Diploma,19,57,61,72,36,9.0,2,96,Urban,ML Engineer,65446,1 +42800,Male,48,Bachelors,10,69,43,93,56,5.0,1,30,Urban,HR Executive,61306,1 +42801,Male,24,Diploma,0,59,70,46,96,7.0,5,3,Rural,Software Engineer,64546,0 +42802,Male,40,Diploma,16,92,51,7,77,6.0,0,83,Urban,Manager,81487,0 +42803,Male,34,Bachelors,14,13,27,45,9,1.0,4,40,Urban,ML Engineer,118581,0 +42804,Male,51,High School,5,79,46,8,42,0.0,4,4,Urban,Manager,95571,0 +42805,Male,41,Masters,3,37,20,16,98,6.0,2,30,Urban,Manager,75020,0 +42806,Male,28,Masters,19,8,90,70,99,7.0,7,28,Urban,Data Analyst,75660,0 +42807,Female,59,Diploma,0,66,69,63,47,3.0,3,38,Semi-Urban,HR Executive,144266,0 +42808,Male,31,Bachelors,1,89,26,71,75,6.0,4,90,Urban,Data Analyst,75928,1 +42809,Female,50,PhD,17,4,2,92,91,8.0,4,17,Semi-Urban,Software Engineer,129358,0 +42810,Male,47,Bachelors,6,71,25,0,40,2.0,6,7,Urban,Data Analyst,82763,0 +42811,Male,59,Bachelors,3,4,18,7,0,6.0,4,42,Semi-Urban,ML Engineer,96306,0 +42812,Male,42,Bachelors,14,7,18,25,55,6.0,5,49,Semi-Urban,Data Analyst,61262,0 +42813,Male,32,Masters,9,27,74,41,68,9.0,4,61,Urban,Data Analyst,140406,0 +42814,Male,56,Bachelors,15,33,64,66,28,7.0,1,49,Rural,Data Analyst,86780,0 +42815,Female,54,PhD,7,77,18,66,59,8.0,4,7,Urban,Manager,23409,0 +42816,Male,35,Masters,0,20,35,31,82,2.0,3,87,Urban,HR Executive,84137,0 +42817,Female,28,Bachelors,6,73,99,5,49,7.0,2,36,Semi-Urban,ML Engineer,24851,0 +42818,Female,27,Bachelors,8,82,11,1,34,6.0,1,60,Urban,Data Analyst,34787,0 +42819,Male,27,Diploma,10,81,7,73,45,5.0,6,21,Urban,HR Executive,51405,0 +42820,Male,34,Masters,12,94,23,31,35,1.0,3,62,Rural,ML Engineer,73327,0 +42821,Female,49,Bachelors,15,33,48,36,29,3.0,5,48,Rural,Manager,55807,0 +42822,Female,35,Masters,16,82,6,79,92,6.0,3,0,Semi-Urban,HR Executive,138746,0 +42823,Female,40,Bachelors,15,36,70,25,68,8.0,2,18,Urban,Data Analyst,84004,0 +42824,Female,31,Diploma,14,47,33,41,37,3.0,1,77,Rural,ML Engineer,93259,0 +42825,Male,32,Bachelors,12,12,24,37,78,5.0,3,96,Rural,Software Engineer,42936,0 +42826,Male,42,Masters,10,7,73,17,20,0.0,0,18,Urban,Software Engineer,39106,0 +42827,Female,57,Bachelors,12,21,42,95,94,9.0,4,84,Urban,HR Executive,35140,1 +42828,Male,44,Bachelors,11,63,22,57,19,3.0,3,85,Semi-Urban,Software Engineer,52441,0 +42829,Male,25,Masters,18,36,84,11,1,8.0,6,82,Urban,HR Executive,144589,0 +42830,Female,47,Diploma,16,62,89,25,62,1.0,6,58,Rural,Software Engineer,28364,0 +42831,Male,50,Masters,6,38,41,11,43,4.0,4,5,Urban,HR Executive,56899,0 +42832,Male,32,Diploma,17,27,69,25,51,5.0,2,15,Urban,HR Executive,56301,0 +42833,Female,23,Diploma,8,36,76,8,90,8.0,1,79,Urban,HR Executive,95753,0 +42834,Male,37,Bachelors,14,23,23,64,34,2.0,5,93,Semi-Urban,Software Engineer,139667,0 +42835,Female,42,Masters,12,61,23,81,58,5.0,6,80,Urban,Data Analyst,60109,1 +42836,Female,52,Masters,11,42,74,39,88,0.0,2,84,Semi-Urban,HR Executive,83026,0 +42837,Male,32,Bachelors,5,61,0,60,9,2.0,3,93,Urban,Manager,69888,0 +42838,Male,40,Bachelors,4,3,44,2,0,5.0,3,59,Urban,Manager,102341,0 +42839,Female,33,Diploma,5,32,73,43,81,2.0,2,63,Rural,Software Engineer,145652,0 +42840,Male,55,Bachelors,5,89,65,79,42,9.0,6,78,Urban,HR Executive,37260,1 +42841,Male,46,High School,16,69,29,11,3,9.0,3,84,Urban,Software Engineer,146691,0 +42842,Female,46,Diploma,16,24,4,25,67,5.0,0,61,Urban,ML Engineer,59640,0 +42843,Female,52,Bachelors,19,58,90,28,43,9.0,4,34,Urban,Manager,101547,0 +42844,Male,53,High School,8,14,22,41,31,9.0,3,28,Urban,HR Executive,60463,0 +42845,Male,55,Diploma,14,53,3,66,74,8.0,2,65,Urban,Data Analyst,45055,0 +42846,Other,52,Bachelors,9,22,76,39,22,3.0,4,17,Semi-Urban,Data Analyst,144593,0 +42847,Female,39,Diploma,10,60,30,56,36,7.0,5,13,Semi-Urban,Manager,40010,0 +42848,Male,25,Masters,8,60,13,93,87,0.0,0,22,Urban,HR Executive,149359,0 +42849,Female,34,Diploma,1,49,43,66,73,2.0,2,81,Urban,Manager,103860,0 +42850,Male,51,Bachelors,16,39,57,8,80,7.0,7,89,Urban,ML Engineer,97343,0 +42851,Male,53,Diploma,8,63,1,40,68,2.0,0,11,Urban,ML Engineer,38702,0 +42852,Male,30,Diploma,3,42,95,26,58,2.0,4,40,Rural,Software Engineer,117559,0 +42853,Male,22,Bachelors,3,69,16,66,74,7.0,4,35,Semi-Urban,Software Engineer,83648,0 +42854,Female,57,Diploma,13,97,17,72,73,8.0,3,75,Semi-Urban,ML Engineer,55252,1 +42855,Male,43,High School,4,9,98,59,46,9.0,4,83,Urban,Manager,125743,1 +42856,Female,49,Bachelors,18,37,8,7,55,5.0,3,5,Urban,ML Engineer,43321,0 +42857,Male,33,Bachelors,9,23,93,22,74,5.0,6,74,Urban,Data Analyst,68183,0 +42858,Male,49,Masters,3,80,8,52,77,5.0,1,23,Rural,HR Executive,34481,0 +42859,Male,48,Diploma,13,63,45,61,51,9.0,5,28,Urban,Software Engineer,82186,0 +42860,Male,41,High School,11,71,29,73,98,9.0,5,32,Urban,Data Analyst,61499,0 +42861,Male,46,Bachelors,17,77,37,65,31,3.0,2,14,Urban,Software Engineer,127729,0 +42862,Male,59,Diploma,17,4,93,86,72,3.0,3,45,Urban,Manager,62686,0 +42863,Female,45,Bachelors,9,55,92,21,95,9.0,0,37,Urban,Data Analyst,78791,0 +42864,Female,57,Masters,18,82,34,6,88,8.0,6,78,Urban,Data Analyst,62749,0 +42865,Female,36,Diploma,14,82,73,67,13,2.0,0,53,Urban,Software Engineer,80957,1 +42866,Female,47,Masters,19,78,10,93,9,5.0,7,30,Semi-Urban,Software Engineer,130145,0 +42867,Female,44,Bachelors,8,59,60,61,87,8.0,2,88,Urban,HR Executive,67587,1 +42868,Male,31,Diploma,16,28,47,25,71,9.0,7,80,Urban,Data Analyst,30680,0 +42869,Other,30,Bachelors,14,99,86,64,96,6.0,4,66,Semi-Urban,Data Analyst,107247,1 +42870,Male,36,Masters,7,71,48,99,35,4.0,4,37,Urban,ML Engineer,27610,1 +42871,Female,42,Bachelors,1,70,45,61,31,6.0,5,24,Semi-Urban,Software Engineer,106254,0 +42872,Female,23,Diploma,0,83,10,16,2,4.0,5,59,Urban,Data Analyst,121968,0 +42873,Male,55,Bachelors,5,1,94,66,39,5.0,2,69,Urban,Data Analyst,111312,0 +42874,Other,54,Masters,7,64,91,45,11,0.0,6,18,Semi-Urban,Data Analyst,77620,0 +42875,Male,38,Diploma,18,51,89,36,83,6.0,6,39,Semi-Urban,Software Engineer,27941,0 +42876,Male,51,Masters,4,4,78,16,26,8.0,1,85,Urban,ML Engineer,42214,0 +42877,Male,29,Bachelors,5,26,60,59,4,9.0,4,95,Semi-Urban,ML Engineer,119027,1 +42878,Male,46,High School,0,37,17,67,49,0.0,0,18,Urban,Manager,130922,0 +42879,Female,47,Bachelors,4,12,60,60,86,7.0,5,51,Rural,Manager,77466,0 +42880,Male,36,High School,10,48,70,45,76,0.0,2,41,Urban,Data Analyst,117324,0 +42881,Female,41,Masters,12,19,31,92,78,7.0,0,75,Urban,Software Engineer,108376,0 +42882,Female,24,High School,18,63,73,97,30,0.0,6,47,Semi-Urban,ML Engineer,105202,1 +42883,Male,51,Masters,1,47,20,4,56,7.0,4,78,Urban,Manager,99035,0 +42884,Male,30,PhD,0,77,12,72,53,7.0,5,29,Urban,Manager,77622,0 +42885,Male,40,Bachelors,4,64,58,8,99,6.0,3,79,Urban,Software Engineer,41785,0 +42886,Female,32,Diploma,16,45,57,24,8,1.0,3,34,Urban,Software Engineer,142139,0 +42887,Female,48,Bachelors,11,15,10,3,95,3.0,0,25,Urban,Manager,114170,0 +42888,Male,30,Diploma,4,99,75,75,79,0.0,2,2,Urban,ML Engineer,147333,1 +42889,Male,46,Bachelors,3,30,98,52,12,5.0,0,1,Semi-Urban,HR Executive,32417,0 +42890,Male,50,Bachelors,18,29,71,35,23,0.0,4,55,Rural,Data Analyst,66113,0 +42891,Male,25,Diploma,18,6,79,3,96,9.0,1,86,Urban,HR Executive,66611,0 +42892,Female,51,High School,17,87,16,90,41,3.0,7,0,Rural,Data Analyst,106312,0 +42893,Female,33,Bachelors,6,52,24,20,9,7.0,7,66,Urban,Software Engineer,137920,0 +42894,Male,42,Masters,2,53,17,85,81,9.0,1,90,Urban,ML Engineer,93582,1 +42895,Female,28,Masters,19,61,17,72,43,2.0,0,46,Urban,HR Executive,57997,0 +42896,Male,29,Bachelors,17,80,38,83,43,1.0,6,31,Semi-Urban,HR Executive,65238,0 +42897,Male,48,Bachelors,3,4,36,42,34,0.0,1,38,Urban,HR Executive,58238,0 +42898,Female,32,Bachelors,0,97,55,45,18,4.0,2,64,Urban,ML Engineer,141053,1 +42899,Male,27,Bachelors,15,56,16,8,8,3.0,2,87,Urban,Manager,62140,0 +42900,Male,39,Masters,11,92,75,67,58,2.0,6,11,Semi-Urban,HR Executive,86904,1 +42901,Male,35,Bachelors,17,76,93,65,48,1.0,6,6,Urban,Data Analyst,64400,1 +42902,Male,45,Masters,3,2,82,17,73,2.0,7,18,Urban,ML Engineer,66694,0 +42903,Male,37,Masters,2,50,61,15,93,1.0,7,52,Urban,Software Engineer,73820,0 +42904,Female,22,Masters,12,50,43,73,30,3.0,4,37,Semi-Urban,ML Engineer,129281,0 +42905,Male,47,Masters,18,22,90,46,93,4.0,1,10,Semi-Urban,Data Analyst,139634,0 +42906,Male,52,Bachelors,15,83,58,45,44,6.0,4,96,Semi-Urban,Software Engineer,46170,1 +42907,Male,58,Bachelors,4,21,83,64,61,8.0,6,37,Urban,ML Engineer,63112,0 +42908,Male,58,Diploma,17,71,61,77,79,4.0,7,19,Semi-Urban,Software Engineer,81221,0 +42909,Male,54,Masters,2,40,68,70,22,4.0,4,66,Semi-Urban,ML Engineer,70298,1 +42910,Female,39,Masters,1,59,6,35,88,5.0,0,22,Urban,Data Analyst,63643,0 +42911,Female,32,Diploma,0,76,59,84,85,9.0,4,95,Semi-Urban,Manager,50631,1 +42912,Male,28,Bachelors,8,79,10,42,58,9.0,2,48,Rural,Software Engineer,123247,0 +42913,Female,21,Diploma,7,48,36,1,0,3.0,0,43,Urban,ML Engineer,91389,0 +42914,Male,28,PhD,8,34,15,0,83,7.0,5,1,Urban,HR Executive,69563,0 +42915,Male,58,Diploma,2,52,19,82,75,8.0,0,53,Rural,ML Engineer,75775,0 +42916,Female,27,Bachelors,9,82,35,67,52,9.0,2,87,Semi-Urban,Software Engineer,116734,1 +42917,Female,49,Diploma,17,29,36,61,13,0.0,0,43,Semi-Urban,Data Analyst,91801,0 +42918,Male,51,Bachelors,9,22,15,76,75,7.0,4,75,Rural,HR Executive,136736,0 +42919,Male,31,Masters,14,16,64,25,28,1.0,7,62,Urban,Manager,143928,0 +42920,Male,53,Diploma,19,75,72,13,25,9.0,3,83,Semi-Urban,ML Engineer,46438,1 +42921,Male,46,Diploma,19,5,38,37,44,2.0,1,51,Rural,Manager,70973,0 +42922,Male,41,Diploma,3,19,61,19,34,1.0,3,9,Urban,Manager,93214,0 +42923,Female,43,Bachelors,11,26,49,93,43,0.0,5,95,Urban,Data Analyst,146313,1 +42924,Male,53,Masters,14,62,24,64,50,7.0,7,61,Semi-Urban,Manager,133229,0 +42925,Male,52,Diploma,11,76,48,48,16,0.0,6,13,Semi-Urban,Manager,140477,0 +42926,Male,43,High School,1,34,96,33,89,9.0,3,69,Urban,Software Engineer,51569,0 +42927,Female,29,PhD,17,86,27,16,20,9.0,5,44,Semi-Urban,HR Executive,32416,0 +42928,Male,23,Diploma,13,43,39,68,94,3.0,0,86,Rural,Manager,37160,1 +42929,Male,47,High School,8,16,33,71,50,0.0,5,39,Semi-Urban,Data Analyst,73979,0 +42930,Male,51,Diploma,10,89,52,96,27,7.0,0,63,Semi-Urban,Software Engineer,80585,1 +42931,Female,43,Bachelors,2,18,15,39,64,3.0,6,87,Urban,ML Engineer,36732,0 +42932,Male,58,Diploma,11,14,44,1,52,6.0,7,51,Urban,Data Analyst,139687,0 +42933,Male,31,Bachelors,6,72,19,68,46,9.0,5,31,Urban,ML Engineer,145215,0 +42934,Male,21,High School,11,13,2,2,27,2.0,3,70,Urban,ML Engineer,55263,0 +42935,Male,21,Bachelors,3,79,93,75,21,9.0,7,51,Semi-Urban,Manager,115549,1 +42936,Male,30,Diploma,9,86,80,11,35,0.0,6,91,Semi-Urban,ML Engineer,126461,1 +42937,Male,33,Masters,17,98,6,45,85,3.0,2,51,Rural,Manager,126969,0 +42938,Male,36,Bachelors,6,61,20,99,83,7.0,4,11,Urban,ML Engineer,53715,0 +42939,Female,29,Masters,4,27,57,44,38,8.0,2,91,Urban,HR Executive,101532,0 +42940,Male,22,Bachelors,4,29,57,45,19,4.0,5,36,Urban,ML Engineer,120613,0 +42941,Female,38,Bachelors,17,32,6,21,88,8.0,2,73,Urban,Software Engineer,40408,0 +42942,Male,41,Bachelors,7,1,59,3,65,1.0,7,94,Rural,Software Engineer,104880,0 +42943,Other,58,Bachelors,3,90,67,20,73,4.0,4,58,Urban,ML Engineer,33229,0 +42944,Other,27,High School,16,32,14,65,80,4.0,0,34,Semi-Urban,Data Analyst,22377,0 +42945,Female,23,Masters,10,59,5,50,86,2.0,7,71,Urban,Data Analyst,129678,0 +42946,Other,22,Bachelors,18,22,72,40,63,4.0,7,56,Urban,Manager,73413,0 +42947,Male,48,Masters,7,66,65,61,85,9.0,2,97,Semi-Urban,Manager,62259,1 +42948,Female,31,Masters,14,30,73,35,51,8.0,3,78,Semi-Urban,HR Executive,146065,0 +42949,Male,41,Bachelors,1,17,52,69,12,4.0,1,61,Urban,HR Executive,107632,0 +42950,Female,55,Bachelors,14,39,48,38,79,2.0,0,31,Rural,Software Engineer,22749,0 +42951,Male,59,High School,6,97,66,42,90,2.0,4,46,Urban,HR Executive,79068,1 +42952,Male,39,Bachelors,4,55,3,18,83,3.0,3,92,Urban,Software Engineer,67960,0 +42953,Other,54,Diploma,6,97,43,88,65,1.0,5,70,Urban,ML Engineer,106632,1 +42954,Male,33,Diploma,19,95,10,68,94,9.0,1,71,Urban,Data Analyst,56182,1 +42955,Female,55,Diploma,15,72,2,89,18,5.0,7,49,Urban,ML Engineer,73164,0 +42956,Female,31,Diploma,9,30,94,73,66,1.0,2,25,Urban,ML Engineer,116474,0 +42957,Male,49,Diploma,3,60,50,40,2,9.0,0,38,Semi-Urban,HR Executive,103974,0 +42958,Male,32,Diploma,3,62,87,19,39,8.0,6,87,Rural,Data Analyst,103501,1 +42959,Male,39,Masters,6,9,36,54,9,1.0,2,71,Rural,HR Executive,96810,0 +42960,Female,41,Bachelors,10,58,36,30,41,5.0,5,53,Urban,Manager,52092,0 +42961,Other,51,Masters,10,15,43,93,14,7.0,7,23,Rural,Software Engineer,62002,0 +42962,Female,53,Masters,14,45,18,84,54,6.0,4,81,Rural,ML Engineer,122101,0 +42963,Female,43,Diploma,2,22,92,32,30,2.0,6,13,Rural,Software Engineer,145025,0 +42964,Male,32,Diploma,11,48,72,64,45,0.0,5,87,Urban,Software Engineer,54237,1 +42965,Male,39,Bachelors,17,21,50,25,11,9.0,4,19,Semi-Urban,Software Engineer,24186,0 +42966,Male,41,High School,12,56,60,76,13,8.0,1,80,Urban,Manager,50071,1 +42967,Male,24,High School,2,78,93,79,69,5.0,7,87,Semi-Urban,HR Executive,61556,1 +42968,Male,52,Bachelors,16,8,75,64,91,8.0,5,45,Rural,Manager,52350,0 +42969,Male,55,Diploma,15,74,0,46,54,9.0,5,64,Semi-Urban,HR Executive,49753,0 +42970,Female,27,Diploma,4,79,6,63,5,4.0,5,97,Urban,Data Analyst,61825,1 +42971,Male,43,Bachelors,17,26,24,36,17,6.0,7,69,Urban,Software Engineer,39869,0 +42972,Male,45,Masters,6,22,31,74,53,6.0,4,9,Urban,Manager,120096,0 +42973,Male,49,Masters,7,1,34,63,5,6.0,7,72,Urban,HR Executive,89293,0 +42974,Female,30,Masters,3,40,7,47,16,6.0,3,86,Urban,ML Engineer,40731,0 +42975,Male,54,Bachelors,5,70,80,79,5,9.0,1,7,Urban,ML Engineer,29516,1 +42976,Male,27,High School,0,41,13,4,60,5.0,7,71,Urban,ML Engineer,73631,0 +42977,Female,49,Masters,13,97,90,86,78,2.0,0,12,Semi-Urban,ML Engineer,130515,1 +42978,Male,32,Diploma,10,79,58,38,7,1.0,5,54,Semi-Urban,Software Engineer,67057,0 +42979,Male,27,High School,14,21,51,66,90,6.0,4,53,Urban,Manager,105950,0 +42980,Female,53,PhD,16,0,18,54,23,7.0,5,72,Semi-Urban,Data Analyst,79933,0 +42981,Male,57,High School,6,22,14,66,43,7.0,7,34,Urban,HR Executive,134772,0 +42982,Male,59,Diploma,4,82,59,44,34,8.0,3,75,Semi-Urban,ML Engineer,25501,1 +42983,Male,49,High School,3,43,49,90,68,8.0,4,37,Semi-Urban,Data Analyst,51611,0 +42984,Male,32,Bachelors,0,93,36,44,42,2.0,3,25,Rural,Software Engineer,99542,0 +42985,Male,48,Diploma,2,44,70,71,73,3.0,2,15,Urban,HR Executive,56950,0 +42986,Male,45,Bachelors,9,59,4,92,90,3.0,3,63,Urban,HR Executive,26201,0 +42987,Female,38,Diploma,17,25,59,22,58,5.0,1,94,Rural,Manager,86667,0 +42988,Male,34,Masters,6,18,41,1,55,0.0,5,37,Urban,Manager,43093,0 +42989,Male,43,Diploma,15,25,29,7,31,4.0,4,26,Urban,Manager,100736,0 +42990,Male,37,Masters,12,47,88,92,78,0.0,0,24,Urban,ML Engineer,42577,1 +42991,Female,31,High School,12,40,90,21,83,8.0,1,93,Semi-Urban,Data Analyst,103034,1 +42992,Female,44,Bachelors,15,86,17,29,60,2.0,4,23,Urban,Software Engineer,44617,0 +42993,Male,48,Bachelors,6,6,31,2,11,6.0,3,65,Urban,Data Analyst,43641,0 +42994,Male,58,Diploma,5,94,37,59,49,4.0,0,94,Urban,HR Executive,100155,1 +42995,Male,46,Bachelors,19,85,15,56,78,8.0,3,75,Urban,HR Executive,126123,0 +42996,Male,48,Bachelors,11,79,39,23,88,0.0,7,11,Rural,Data Analyst,87528,0 +42997,Male,37,Masters,13,25,25,92,67,6.0,5,73,Semi-Urban,Manager,95542,0 +42998,Male,24,Masters,17,98,53,47,32,1.0,0,99,Urban,Manager,27498,1 +42999,Male,56,Masters,11,30,78,9,34,0.0,5,77,Urban,Data Analyst,52525,0 +43000,Male,30,High School,16,46,18,81,64,7.0,3,65,Rural,HR Executive,95521,0 +43001,Male,43,Bachelors,6,74,72,28,7,0.0,2,65,Rural,HR Executive,137061,1 +43002,Male,46,Bachelors,2,33,38,18,22,5.0,7,27,Urban,Data Analyst,131583,0 +43003,Male,51,Bachelors,17,25,66,92,62,3.0,5,78,Rural,Software Engineer,84994,1 +43004,Female,36,Diploma,10,45,98,46,54,9.0,5,77,Urban,ML Engineer,58761,1 +43005,Female,58,Diploma,3,13,73,16,59,2.0,4,3,Urban,Data Analyst,92540,0 +43006,Other,27,Bachelors,4,85,24,3,52,8.0,3,27,Rural,Manager,87193,0 +43007,Male,30,Bachelors,17,75,41,95,8,9.0,5,49,Semi-Urban,Manager,66588,1 +43008,Male,54,Masters,3,35,9,98,26,0.0,5,35,Urban,HR Executive,52898,0 +43009,Female,28,Masters,6,29,22,38,16,9.0,5,86,Semi-Urban,Software Engineer,68758,0 +43010,Male,27,Bachelors,16,55,87,12,58,5.0,2,46,Rural,Software Engineer,124396,0 +43011,Male,23,Diploma,10,59,8,79,23,2.0,6,41,Urban,Data Analyst,142926,0 +43012,Male,57,Bachelors,6,71,15,45,76,2.0,1,35,Urban,HR Executive,61148,0 +43013,Male,23,Bachelors,9,35,67,80,7,7.0,3,8,Urban,Software Engineer,102545,0 +43014,Female,53,Diploma,15,82,9,73,99,3.0,3,10,Urban,Data Analyst,121900,0 +43015,Female,41,Bachelors,15,54,47,96,82,1.0,4,78,Urban,Data Analyst,78461,1 +43016,Other,33,High School,7,12,13,71,79,1.0,0,53,Urban,ML Engineer,126292,0 +43017,Female,50,Diploma,12,51,92,98,23,7.0,2,70,Urban,Software Engineer,25303,1 +43018,Male,50,Diploma,14,17,1,79,94,9.0,6,51,Semi-Urban,Manager,34796,0 +43019,Male,35,Diploma,15,48,45,37,80,8.0,5,28,Rural,Manager,70400,0 +43020,Male,57,Bachelors,11,56,27,36,93,8.0,4,54,Semi-Urban,Manager,144725,0 +43021,Male,40,PhD,18,24,92,21,41,0.0,4,36,Urban,Data Analyst,62557,0 +43022,Male,28,Masters,0,12,93,34,17,5.0,7,29,Urban,Software Engineer,142842,0 +43023,Male,40,Bachelors,19,54,99,78,96,1.0,0,23,Urban,HR Executive,35426,1 +43024,Male,50,High School,2,32,84,24,51,8.0,4,57,Urban,Manager,50150,0 +43025,Female,29,PhD,1,46,42,59,15,3.0,5,41,Urban,Manager,85046,0 +43026,Male,46,Bachelors,0,97,28,10,53,5.0,7,66,Urban,Software Engineer,104082,0 +43027,Male,26,Bachelors,1,16,34,6,97,2.0,6,96,Urban,ML Engineer,133886,0 +43028,Male,24,Bachelors,1,98,50,75,11,2.0,7,53,Urban,Data Analyst,62669,1 +43029,Female,31,High School,0,48,18,45,41,9.0,3,79,Semi-Urban,Software Engineer,35220,0 +43030,Female,49,Bachelors,16,7,76,27,42,8.0,0,66,Semi-Urban,Data Analyst,119571,0 +43031,Male,48,Bachelors,0,88,65,33,54,4.0,6,76,Urban,ML Engineer,96576,1 +43032,Female,53,Bachelors,5,48,70,96,14,2.0,0,93,Urban,HR Executive,102917,1 +43033,Male,32,Masters,8,70,36,54,6,4.0,4,40,Rural,Manager,32211,0 +43034,Female,40,High School,11,42,38,64,83,0.0,7,83,Semi-Urban,ML Engineer,63107,0 +43035,Male,57,Bachelors,9,28,72,73,52,2.0,7,43,Urban,Data Analyst,126078,0 +43036,Male,27,Diploma,16,78,46,0,88,1.0,2,20,Semi-Urban,HR Executive,144012,0 +43037,Male,23,Diploma,18,58,62,20,30,5.0,4,83,Rural,Data Analyst,37755,0 +43038,Male,46,Diploma,17,73,62,51,78,5.0,2,62,Urban,ML Engineer,31844,1 +43039,Female,38,Masters,3,54,35,8,50,1.0,3,63,Urban,Software Engineer,31935,0 +43040,Female,58,Masters,9,37,42,2,76,2.0,2,35,Urban,ML Engineer,35242,0 +43041,Male,43,Masters,10,86,87,27,2,4.0,4,87,Urban,Software Engineer,114809,1 +43042,Male,36,Bachelors,12,28,19,94,22,3.0,2,25,Semi-Urban,Software Engineer,63015,0 +43043,Male,57,Masters,9,83,41,3,18,7.0,5,13,Urban,Software Engineer,65779,0 +43044,Male,41,Bachelors,1,71,69,56,16,1.0,1,99,Urban,ML Engineer,38840,1 +43045,Female,33,High School,13,77,33,93,78,3.0,1,62,Urban,HR Executive,63977,1 +43046,Male,51,Bachelors,1,10,97,0,85,4.0,4,62,Urban,Data Analyst,95604,0 +43047,Male,56,Bachelors,11,81,8,14,34,4.0,5,58,Semi-Urban,Data Analyst,106834,0 +43048,Female,45,Masters,10,41,14,60,99,3.0,3,85,Urban,HR Executive,123184,0 +43049,Male,46,Masters,4,77,46,24,43,2.0,3,13,Rural,Data Analyst,68881,0 +43050,Male,22,Bachelors,13,38,60,48,91,7.0,6,27,Semi-Urban,Manager,96869,0 +43051,Male,57,Bachelors,8,6,74,42,75,8.0,7,63,Urban,Data Analyst,140509,0 +43052,Male,50,Diploma,12,55,97,82,28,5.0,3,42,Semi-Urban,HR Executive,127153,1 +43053,Male,39,Bachelors,7,50,68,82,98,3.0,6,87,Semi-Urban,Software Engineer,126063,1 +43054,Male,43,Bachelors,8,11,57,98,90,6.0,7,62,Semi-Urban,Software Engineer,78648,0 +43055,Female,54,High School,5,90,52,27,90,0.0,1,54,Urban,HR Executive,90012,0 +43056,Female,47,Masters,15,16,28,27,60,2.0,0,89,Urban,Manager,23440,0 +43057,Female,58,Masters,19,30,67,61,12,8.0,6,65,Semi-Urban,ML Engineer,72820,0 +43058,Female,59,Bachelors,3,81,30,91,25,3.0,0,53,Urban,ML Engineer,58352,1 +43059,Male,35,Diploma,12,1,94,32,88,7.0,7,1,Semi-Urban,Data Analyst,99204,0 +43060,Male,29,Diploma,11,29,34,64,99,9.0,6,70,Semi-Urban,HR Executive,119509,0 +43061,Female,38,Bachelors,10,31,89,51,66,6.0,0,90,Rural,Data Analyst,60624,1 +43062,Male,45,Bachelors,5,92,19,1,57,5.0,4,78,Urban,Manager,126832,0 +43063,Male,38,Bachelors,9,15,69,1,12,8.0,1,26,Urban,HR Executive,87767,0 +43064,Male,39,High School,10,82,13,26,79,0.0,7,13,Semi-Urban,Software Engineer,92144,0 +43065,Female,38,Bachelors,7,90,21,30,33,9.0,0,98,Rural,Software Engineer,56341,0 +43066,Male,22,Masters,10,40,65,89,63,0.0,6,19,Semi-Urban,Data Analyst,149664,0 +43067,Male,32,Bachelors,11,88,17,23,37,6.0,4,44,Urban,Software Engineer,55646,0 +43068,Male,49,High School,7,75,24,57,98,2.0,6,56,Urban,Software Engineer,105792,0 +43069,Female,24,Bachelors,16,12,79,23,21,7.0,4,3,Urban,ML Engineer,29795,0 +43070,Male,31,Bachelors,0,20,35,26,32,1.0,0,10,Urban,HR Executive,57147,0 +43071,Male,33,Masters,7,33,96,1,34,3.0,6,87,Rural,ML Engineer,84288,0 +43072,Female,55,Bachelors,3,91,89,25,86,0.0,5,96,Rural,Software Engineer,56037,1 +43073,Female,28,High School,13,78,14,33,22,3.0,3,33,Urban,ML Engineer,48036,0 +43074,Male,35,Bachelors,10,47,41,28,40,2.0,2,82,Urban,HR Executive,84421,0 +43075,Male,45,PhD,7,38,36,31,50,7.0,7,29,Urban,Manager,28042,0 +43076,Male,47,Masters,9,12,90,98,93,4.0,5,6,Rural,Manager,71470,0 +43077,Female,36,Bachelors,0,19,83,12,35,7.0,5,45,Rural,Software Engineer,38080,0 +43078,Male,49,Diploma,14,9,61,28,81,7.0,5,9,Urban,Data Analyst,136942,0 +43079,Male,35,Bachelors,12,44,18,13,35,0.0,0,10,Urban,ML Engineer,88184,0 +43080,Male,57,Masters,2,56,98,56,86,4.0,5,68,Urban,Software Engineer,72376,1 +43081,Female,25,Masters,6,58,50,56,52,4.0,3,81,Rural,ML Engineer,29979,1 +43082,Female,59,Bachelors,8,73,38,9,41,2.0,4,57,Rural,HR Executive,80711,0 +43083,Male,39,High School,8,91,51,82,82,3.0,1,1,Urban,Manager,84916,0 +43084,Male,33,Bachelors,4,82,97,63,48,4.0,7,40,Urban,HR Executive,124345,1 +43085,Female,48,Masters,0,88,43,25,47,3.0,4,37,Urban,HR Executive,46776,0 +43086,Female,42,Masters,11,47,4,30,53,4.0,0,39,Urban,Manager,134706,0 +43087,Female,54,High School,11,62,76,96,68,7.0,2,72,Semi-Urban,HR Executive,69336,1 +43088,Female,37,High School,1,92,14,76,66,0.0,6,79,Urban,Data Analyst,70421,1 +43089,Male,21,Bachelors,16,82,49,5,82,6.0,3,58,Rural,HR Executive,74580,0 +43090,Male,56,Diploma,15,44,29,63,50,1.0,5,10,Rural,ML Engineer,118682,0 +43091,Female,59,Diploma,16,70,9,56,52,5.0,5,85,Urban,Manager,61070,0 +43092,Male,42,High School,9,60,99,92,2,6.0,3,17,Urban,HR Executive,64818,1 +43093,Male,27,Bachelors,11,6,84,47,26,8.0,3,28,Urban,Manager,30829,0 +43094,Male,56,Diploma,3,80,96,98,75,2.0,3,27,Urban,ML Engineer,50337,1 +43095,Female,25,High School,17,70,18,94,19,6.0,2,56,Urban,Software Engineer,64940,0 +43096,Male,57,Masters,9,31,8,77,75,9.0,1,81,Semi-Urban,HR Executive,43665,0 +43097,Male,40,High School,6,80,16,73,53,8.0,7,49,Rural,HR Executive,72298,0 +43098,Female,36,Masters,3,30,45,75,31,4.0,5,39,Rural,Software Engineer,85275,0 +43099,Female,22,Bachelors,17,68,36,97,62,8.0,7,30,Urban,ML Engineer,135902,0 +43100,Female,40,PhD,15,67,4,47,90,6.0,5,54,Urban,Software Engineer,130373,0 +43101,Male,23,Diploma,8,32,19,3,27,8.0,3,24,Urban,Data Analyst,77755,0 +43102,Male,26,Masters,14,25,34,36,27,1.0,7,84,Urban,Manager,82157,0 +43103,Male,54,Bachelors,4,74,13,65,37,4.0,0,93,Urban,HR Executive,99917,1 +43104,Female,47,High School,1,65,71,98,99,6.0,1,0,Rural,Software Engineer,90600,0 +43105,Male,40,High School,15,16,79,38,50,1.0,4,16,Rural,Software Engineer,37645,0 +43106,Female,29,Diploma,10,22,57,84,12,0.0,2,43,Semi-Urban,HR Executive,105367,0 +43107,Male,24,PhD,3,45,19,91,26,1.0,0,19,Semi-Urban,Data Analyst,96254,0 +43108,Male,48,Bachelors,9,69,13,87,54,1.0,5,12,Urban,Data Analyst,126781,0 +43109,Male,54,Diploma,4,82,69,58,41,3.0,3,32,Urban,Manager,59998,1 +43110,Female,32,Bachelors,8,87,70,76,45,5.0,4,13,Rural,Software Engineer,59943,1 +43111,Other,48,Masters,9,76,62,42,16,5.0,7,9,Urban,Data Analyst,26211,0 +43112,Female,26,Bachelors,16,71,15,35,36,7.0,7,54,Urban,Software Engineer,60484,0 +43113,Male,57,Bachelors,7,56,76,48,58,5.0,4,17,Urban,ML Engineer,143837,0 +43114,Female,50,Masters,14,92,62,7,66,8.0,0,69,Urban,ML Engineer,132764,0 +43115,Female,31,Diploma,4,32,6,3,63,8.0,7,4,Urban,Data Analyst,34934,0 +43116,Male,48,Diploma,15,59,96,15,34,4.0,3,45,Urban,Software Engineer,25990,0 +43117,Other,40,Masters,13,16,61,29,43,6.0,0,31,Urban,HR Executive,54628,0 +43118,Male,34,Bachelors,12,67,75,4,83,3.0,7,7,Rural,Manager,143352,0 +43119,Other,43,Masters,11,41,33,94,14,1.0,7,8,Urban,HR Executive,77964,0 +43120,Female,46,Diploma,13,11,99,98,84,0.0,5,20,Urban,Manager,97494,0 +43121,Male,59,High School,4,73,86,18,99,1.0,2,99,Urban,ML Engineer,123920,1 +43122,Male,30,PhD,10,86,83,2,2,8.0,1,79,Rural,Software Engineer,91444,1 +43123,Male,57,High School,10,24,36,89,56,0.0,5,37,Urban,HR Executive,135801,0 +43124,Male,30,High School,16,97,29,88,74,3.0,5,15,Rural,Software Engineer,57808,0 +43125,Male,40,Bachelors,12,36,40,19,30,7.0,1,29,Urban,ML Engineer,133832,0 +43126,Female,29,Bachelors,9,85,60,64,95,8.0,2,87,Urban,Manager,25214,1 +43127,Male,27,Bachelors,10,85,35,76,40,5.0,3,59,Semi-Urban,HR Executive,75380,1 +43128,Male,27,PhD,5,85,99,88,9,2.0,3,19,Urban,HR Executive,144602,1 +43129,Other,35,Diploma,15,20,13,4,1,0.0,7,40,Urban,HR Executive,48079,0 +43130,Male,55,Bachelors,11,22,82,63,77,3.0,6,44,Semi-Urban,HR Executive,148865,0 +43131,Female,21,Diploma,6,24,44,9,27,4.0,7,44,Rural,Manager,52157,0 +43132,Male,58,Bachelors,4,95,52,7,38,6.0,7,26,Rural,Manager,63013,0 +43133,Female,46,Diploma,3,50,96,1,59,5.0,7,25,Urban,Manager,72949,0 +43134,Male,50,Bachelors,17,77,59,73,52,9.0,2,56,Urban,Data Analyst,60221,1 +43135,Female,49,Diploma,6,71,50,16,13,6.0,7,51,Rural,Software Engineer,118152,0 +43136,Female,42,Bachelors,18,21,98,93,60,8.0,4,51,Rural,Manager,50669,1 +43137,Female,55,Diploma,8,81,2,80,58,3.0,6,55,Urban,Software Engineer,59311,0 +43138,Male,42,Masters,5,63,35,29,65,1.0,5,57,Semi-Urban,ML Engineer,28811,0 +43139,Male,28,Bachelors,1,91,97,89,29,9.0,5,63,Urban,HR Executive,148089,1 +43140,Female,56,Masters,17,74,71,72,78,3.0,2,28,Semi-Urban,ML Engineer,88334,1 +43141,Male,56,Bachelors,0,71,22,52,66,7.0,7,17,Urban,HR Executive,78676,0 +43142,Male,24,Diploma,14,31,46,17,73,7.0,1,27,Urban,Manager,84020,0 +43143,Male,42,Masters,7,91,96,22,84,2.0,2,36,Urban,Data Analyst,82098,1 +43144,Male,58,Bachelors,12,31,99,63,74,2.0,4,80,Urban,Manager,125403,1 +43145,Male,27,Bachelors,1,88,68,92,50,9.0,3,39,Urban,HR Executive,117581,1 +43146,Male,29,Diploma,11,5,36,97,63,2.0,2,19,Urban,Software Engineer,92386,0 +43147,Male,24,Bachelors,8,74,24,18,33,1.0,0,10,Urban,Data Analyst,86223,0 +43148,Male,49,High School,0,49,17,97,0,0.0,2,8,Semi-Urban,Software Engineer,110155,0 +43149,Male,43,Bachelors,14,9,88,27,47,5.0,2,73,Semi-Urban,Software Engineer,128239,0 +43150,Female,22,Bachelors,3,21,21,12,90,4.0,7,27,Rural,Data Analyst,39407,0 +43151,Female,45,Masters,1,25,14,85,7,6.0,7,11,Urban,Software Engineer,46973,0 +43152,Male,38,Bachelors,10,17,87,13,68,8.0,4,68,Urban,Data Analyst,35919,0 +43153,Female,37,Masters,2,74,71,5,66,6.0,7,28,Rural,HR Executive,31514,0 +43154,Female,40,Masters,16,94,79,7,95,7.0,7,6,Semi-Urban,Data Analyst,135396,0 +43155,Female,28,Masters,14,0,47,28,18,9.0,0,6,Rural,Software Engineer,109256,0 +43156,Other,26,Bachelors,3,88,38,49,57,8.0,6,41,Urban,ML Engineer,144634,0 +43157,Male,24,Bachelors,14,9,65,65,3,7.0,7,66,Urban,Manager,79334,0 +43158,Female,45,Bachelors,3,42,61,53,67,7.0,2,76,Rural,Data Analyst,124558,0 +43159,Female,31,Bachelors,0,36,37,15,25,5.0,6,45,Rural,HR Executive,31885,0 +43160,Male,47,Diploma,0,48,8,33,84,5.0,0,84,Urban,Manager,45134,0 +43161,Female,41,Masters,6,77,19,23,21,1.0,2,60,Urban,Software Engineer,40434,0 +43162,Male,47,Masters,16,12,77,1,99,3.0,5,98,Urban,Manager,84797,0 +43163,Male,35,Bachelors,3,18,7,80,18,3.0,4,7,Urban,Manager,134655,0 +43164,Male,32,Masters,8,62,71,13,18,8.0,3,64,Semi-Urban,Data Analyst,58148,0 +43165,Female,42,Masters,0,14,39,10,2,4.0,6,59,Semi-Urban,ML Engineer,21678,0 +43166,Female,53,Bachelors,12,76,30,51,0,0.0,2,30,Rural,HR Executive,133153,0 +43167,Male,48,Diploma,9,62,42,3,94,0.0,0,41,Rural,ML Engineer,31789,0 +43168,Male,42,Diploma,1,42,13,58,43,4.0,2,39,Semi-Urban,Data Analyst,63389,0 +43169,Male,44,Bachelors,12,88,96,5,81,0.0,7,87,Semi-Urban,ML Engineer,48998,1 +43170,Male,41,Bachelors,4,55,71,16,36,9.0,1,98,Urban,HR Executive,144354,1 +43171,Female,56,Diploma,8,39,68,58,88,9.0,4,77,Urban,ML Engineer,113756,1 +43172,Female,26,Masters,0,17,92,26,85,9.0,7,84,Urban,Software Engineer,35060,0 +43173,Female,33,Bachelors,16,19,13,2,29,4.0,5,58,Urban,Software Engineer,65404,0 +43174,Other,59,High School,2,67,44,92,21,7.0,3,2,Urban,Software Engineer,111044,0 +43175,Female,40,Bachelors,1,55,41,3,85,9.0,3,4,Semi-Urban,Software Engineer,104925,0 +43176,Male,29,Bachelors,12,17,96,32,22,5.0,4,53,Semi-Urban,ML Engineer,33631,0 +43177,Male,47,Masters,2,96,62,99,33,6.0,2,21,Urban,Manager,132302,1 +43178,Male,44,Masters,8,15,92,18,36,1.0,1,51,Rural,HR Executive,133513,0 +43179,Male,56,High School,5,1,94,98,24,5.0,5,50,Rural,Manager,95981,1 +43180,Female,31,Masters,0,8,99,4,56,3.0,3,78,Urban,Manager,58932,0 +43181,Male,54,Diploma,7,10,78,48,87,6.0,6,35,Urban,ML Engineer,124369,0 +43182,Female,35,Bachelors,6,70,67,71,77,0.0,0,47,Urban,Data Analyst,104260,1 +43183,Male,40,Diploma,12,62,67,54,46,5.0,5,92,Semi-Urban,HR Executive,135677,1 +43184,Female,35,Diploma,8,24,40,24,57,9.0,4,16,Rural,Software Engineer,49282,0 +43185,Male,58,Bachelors,11,78,86,33,86,5.0,7,19,Semi-Urban,Software Engineer,84626,0 +43186,Male,58,Bachelors,18,41,55,73,42,2.0,7,36,Semi-Urban,Data Analyst,138741,0 +43187,Female,34,Bachelors,3,8,41,31,31,6.0,4,74,Semi-Urban,ML Engineer,35984,0 +43188,Female,24,Bachelors,19,34,93,0,90,0.0,3,59,Urban,HR Executive,137815,0 +43189,Female,24,Masters,9,86,51,40,92,3.0,7,60,Urban,HR Executive,43943,0 +43190,Female,22,Diploma,19,20,33,0,43,1.0,0,28,Semi-Urban,Software Engineer,50082,0 +43191,Male,21,Bachelors,0,33,5,10,32,6.0,7,3,Semi-Urban,Software Engineer,58170,0 +43192,Male,59,Bachelors,17,18,2,8,9,4.0,2,23,Semi-Urban,Manager,54782,0 +43193,Female,48,Masters,12,73,84,34,29,0.0,3,35,Urban,ML Engineer,65967,0 +43194,Male,58,Bachelors,12,86,1,48,99,1.0,6,8,Urban,Manager,27131,0 +43195,Female,22,Masters,19,2,14,14,0,1.0,2,96,Semi-Urban,HR Executive,38636,0 +43196,Male,28,Diploma,10,1,44,72,14,4.0,5,62,Urban,ML Engineer,29907,0 +43197,Male,38,High School,5,17,76,67,38,6.0,0,84,Urban,ML Engineer,101867,1 +43198,Male,39,Masters,15,19,17,46,85,3.0,1,99,Urban,Manager,97449,0 +43199,Female,23,Masters,18,55,97,10,48,8.0,6,3,Semi-Urban,Software Engineer,93588,0 +43200,Female,29,Diploma,1,53,30,57,93,0.0,3,80,Urban,Manager,65239,0 +43201,Female,49,Diploma,15,75,25,50,91,6.0,0,93,Urban,Data Analyst,87106,1 +43202,Male,45,Bachelors,19,81,66,87,58,4.0,5,99,Semi-Urban,Software Engineer,31209,1 +43203,Male,50,Diploma,12,87,39,67,75,4.0,6,82,Urban,Manager,55368,1 +43204,Other,52,Masters,8,77,62,45,90,2.0,2,21,Semi-Urban,Manager,81662,0 +43205,Male,53,Bachelors,18,91,0,0,15,2.0,1,50,Semi-Urban,ML Engineer,140672,0 +43206,Male,31,Bachelors,3,11,46,4,55,0.0,4,28,Urban,Data Analyst,108702,0 +43207,Male,58,High School,5,68,69,86,47,8.0,0,58,Urban,Manager,134588,1 +43208,Male,51,Bachelors,14,1,86,55,91,5.0,5,78,Urban,Manager,139391,0 +43209,Male,23,Bachelors,14,59,35,10,9,0.0,3,75,Urban,Software Engineer,74628,0 +43210,Female,32,Diploma,17,47,36,98,44,5.0,6,71,Urban,Manager,120853,1 +43211,Other,47,Bachelors,9,22,23,73,55,1.0,2,60,Urban,Data Analyst,117694,0 +43212,Male,33,Diploma,7,15,75,95,43,3.0,2,46,Semi-Urban,Software Engineer,28563,0 +43213,Male,28,Diploma,12,58,30,99,20,7.0,6,95,Semi-Urban,Data Analyst,53277,1 +43214,Female,41,Bachelors,2,99,72,15,11,5.0,6,33,Semi-Urban,Manager,103972,0 +43215,Male,30,Bachelors,17,12,82,24,89,5.0,5,55,Urban,HR Executive,50964,0 +43216,Other,37,Diploma,8,70,61,42,30,6.0,7,38,Rural,ML Engineer,24974,0 +43217,Male,33,Masters,11,37,23,26,51,7.0,6,30,Rural,Data Analyst,80769,0 +43218,Male,57,Bachelors,19,39,74,7,86,0.0,5,46,Urban,HR Executive,105632,0 +43219,Female,27,Bachelors,0,50,74,19,40,8.0,6,6,Rural,Manager,47257,0 +43220,Female,26,High School,19,4,8,35,14,5.0,4,67,Urban,HR Executive,86482,0 +43221,Male,54,Bachelors,18,29,27,55,96,7.0,4,78,Rural,Software Engineer,22079,0 +43222,Male,49,Masters,3,66,5,92,37,4.0,0,37,Rural,HR Executive,91190,0 +43223,Male,54,Bachelors,5,98,20,80,73,8.0,4,90,Rural,Software Engineer,113248,1 +43224,Male,57,Bachelors,19,46,70,18,57,2.0,5,72,Semi-Urban,Software Engineer,44411,0 +43225,Male,36,Bachelors,8,85,64,69,92,9.0,3,11,Urban,ML Engineer,80252,0 +43226,Female,44,High School,10,59,62,79,93,0.0,0,87,Urban,Data Analyst,61193,1 +43227,Male,49,Diploma,13,20,23,50,20,6.0,4,68,Urban,Software Engineer,134141,0 +43228,Male,30,Masters,2,29,73,68,11,4.0,6,86,Semi-Urban,Manager,91650,1 +43229,Female,43,Bachelors,11,70,62,86,24,6.0,1,38,Urban,ML Engineer,132457,1 +43230,Male,27,High School,17,85,23,63,8,1.0,5,18,Semi-Urban,Software Engineer,109274,0 +43231,Female,42,Masters,12,50,95,27,97,0.0,6,36,Semi-Urban,Manager,28326,0 +43232,Female,37,Masters,0,89,19,8,1,2.0,6,46,Rural,Manager,100820,0 +43233,Male,56,Bachelors,9,13,67,60,31,0.0,7,18,Semi-Urban,Data Analyst,134433,0 +43234,Female,28,Masters,15,37,66,16,7,1.0,7,43,Urban,Manager,87023,0 +43235,Male,25,Bachelors,13,45,29,5,8,1.0,6,69,Rural,Manager,26986,0 +43236,Female,34,Bachelors,15,58,23,52,79,5.0,2,65,Urban,Manager,95812,0 +43237,Female,58,Masters,3,95,89,1,79,1.0,6,90,Urban,Manager,71685,1 +43238,Female,53,Diploma,10,24,55,49,14,9.0,4,51,Semi-Urban,HR Executive,139483,0 +43239,Male,32,Diploma,19,53,82,79,88,6.0,3,89,Urban,Data Analyst,59071,1 +43240,Male,27,Diploma,2,89,12,67,96,6.0,0,71,Urban,Manager,92190,1 +43241,Male,34,Bachelors,11,52,93,26,38,0.0,4,28,Semi-Urban,HR Executive,85292,0 +43242,Female,40,Bachelors,11,14,81,14,52,6.0,1,93,Urban,Software Engineer,132146,0 +43243,Female,39,Bachelors,12,8,99,71,47,0.0,2,87,Semi-Urban,HR Executive,58332,1 +43244,Male,34,Bachelors,3,27,90,39,64,8.0,1,13,Urban,HR Executive,80412,0 +43245,Male,50,Bachelors,15,25,79,18,26,0.0,5,16,Urban,Data Analyst,107323,0 +43246,Female,56,Diploma,8,32,71,98,32,1.0,3,40,Rural,Manager,85494,1 +43247,Male,46,Bachelors,19,78,31,42,43,8.0,1,46,Semi-Urban,HR Executive,35493,0 +43248,Male,25,High School,0,29,24,21,80,1.0,4,5,Urban,ML Engineer,47416,0 +43249,Male,39,Bachelors,18,89,84,85,50,9.0,0,54,Urban,Software Engineer,62491,1 +43250,Male,52,Diploma,0,72,65,80,14,9.0,4,92,Urban,HR Executive,92096,1 +43251,Other,36,Masters,18,12,48,59,78,2.0,2,9,Urban,Manager,102574,0 +43252,Other,46,Diploma,5,24,84,35,49,4.0,6,35,Urban,ML Engineer,110775,0 +43253,Male,24,Bachelors,8,76,70,26,77,7.0,0,21,Urban,HR Executive,23505,0 +43254,Other,43,Masters,5,31,61,74,76,3.0,2,82,Semi-Urban,Software Engineer,54544,1 +43255,Male,46,Masters,18,52,16,77,16,9.0,3,67,Urban,Data Analyst,77184,0 +43256,Female,38,Diploma,8,28,71,38,51,2.0,1,44,Urban,Software Engineer,58994,0 +43257,Male,42,Diploma,1,0,21,0,48,4.0,7,29,Urban,ML Engineer,29305,0 +43258,Female,21,Bachelors,11,0,6,5,23,3.0,7,65,Urban,Software Engineer,52881,0 +43259,Male,42,Masters,4,9,9,53,84,1.0,4,57,Urban,Manager,27434,0 +43260,Male,33,Masters,6,70,36,31,80,9.0,4,50,Rural,HR Executive,28564,0 +43261,Female,49,Bachelors,18,58,58,27,45,8.0,6,60,Urban,HR Executive,59424,0 +43262,Male,53,High School,10,38,6,86,63,6.0,5,79,Semi-Urban,HR Executive,134903,0 +43263,Other,38,Bachelors,3,9,15,43,37,4.0,5,7,Urban,Data Analyst,109515,0 +43264,Male,21,Masters,1,12,7,72,18,0.0,7,89,Urban,Software Engineer,141145,0 +43265,Male,34,Bachelors,7,19,53,1,49,6.0,4,0,Semi-Urban,ML Engineer,26374,0 +43266,Female,49,Masters,14,84,32,69,64,2.0,6,41,Semi-Urban,Software Engineer,82044,0 +43267,Male,35,Diploma,6,54,60,52,66,8.0,2,23,Rural,ML Engineer,148400,0 +43268,Male,30,Diploma,5,19,35,56,29,1.0,3,4,Semi-Urban,ML Engineer,122143,0 +43269,Male,56,Bachelors,8,16,67,33,38,7.0,0,55,Semi-Urban,Software Engineer,47563,0 +43270,Male,50,High School,13,12,30,68,14,1.0,2,30,Urban,Data Analyst,52722,0 +43271,Male,51,Diploma,18,64,43,25,94,7.0,0,22,Semi-Urban,HR Executive,65577,0 +43272,Male,52,Bachelors,13,66,10,99,43,7.0,6,42,Semi-Urban,ML Engineer,119967,0 +43273,Female,42,Bachelors,18,39,64,50,12,8.0,6,71,Rural,Software Engineer,146662,0 +43274,Female,39,Diploma,13,88,35,22,16,1.0,6,45,Rural,Data Analyst,113842,0 +43275,Other,47,Bachelors,19,86,60,16,90,2.0,2,61,Rural,Manager,78459,0 +43276,Female,30,Bachelors,12,21,9,48,73,4.0,3,88,Semi-Urban,ML Engineer,49826,0 +43277,Male,28,Diploma,10,96,4,75,18,1.0,2,86,Rural,Manager,134725,1 +43278,Male,56,Masters,5,98,33,80,96,5.0,5,68,Rural,HR Executive,116310,1 +43279,Male,33,Bachelors,14,68,76,66,11,5.0,5,2,Urban,HR Executive,141732,0 +43280,Male,43,Bachelors,10,90,4,0,23,4.0,7,81,Urban,ML Engineer,147419,0 +43281,Male,58,Bachelors,3,84,34,5,73,5.0,3,21,Urban,Data Analyst,28229,0 +43282,Female,58,High School,7,32,99,26,29,2.0,2,55,Urban,Manager,116585,0 +43283,Female,52,Bachelors,12,31,2,54,35,2.0,5,76,Urban,ML Engineer,91916,0 +43284,Female,39,Diploma,11,65,84,32,75,0.0,5,74,Urban,ML Engineer,33136,1 +43285,Male,25,Bachelors,1,97,94,61,2,4.0,1,76,Urban,ML Engineer,139738,1 +43286,Male,23,Diploma,19,49,83,95,52,6.0,4,33,Urban,Data Analyst,110963,1 +43287,Female,49,Masters,19,32,42,34,16,7.0,0,33,Urban,Manager,51073,0 +43288,Female,30,Bachelors,9,87,55,98,74,2.0,5,76,Urban,Data Analyst,96442,1 +43289,Female,33,Masters,7,87,6,75,4,3.0,6,84,Rural,ML Engineer,144054,1 +43290,Male,28,Bachelors,12,82,92,18,95,2.0,0,66,Urban,Manager,87648,1 +43291,Female,40,High School,5,79,96,29,60,4.0,6,44,Urban,HR Executive,47470,1 +43292,Female,59,Bachelors,0,66,92,67,13,0.0,1,5,Urban,Data Analyst,95240,0 +43293,Male,56,Masters,18,28,20,47,15,1.0,2,63,Urban,HR Executive,55667,0 +43294,Male,45,High School,18,9,4,78,24,8.0,2,24,Semi-Urban,ML Engineer,68855,0 +43295,Female,38,Bachelors,15,42,45,63,43,7.0,6,61,Urban,HR Executive,33265,0 +43296,Male,46,High School,13,60,10,46,27,7.0,7,75,Urban,Software Engineer,81930,0 +43297,Female,23,Masters,12,76,35,38,84,4.0,3,2,Rural,Data Analyst,87405,0 +43298,Male,44,Bachelors,0,81,43,66,75,1.0,5,25,Urban,Software Engineer,138013,0 +43299,Male,54,Masters,15,97,42,41,79,8.0,2,98,Semi-Urban,Data Analyst,143024,1 +43300,Male,34,Diploma,3,36,90,2,54,5.0,7,46,Rural,Software Engineer,125919,0 +43301,Male,58,PhD,4,18,5,79,50,7.0,0,22,Rural,ML Engineer,52735,0 +43302,Male,25,Bachelors,2,0,0,45,21,4.0,0,89,Urban,ML Engineer,54569,0 +43303,Female,39,Bachelors,4,17,69,62,81,1.0,1,97,Urban,HR Executive,64705,1 +43304,Female,46,Bachelors,10,44,98,4,25,5.0,0,81,Urban,Data Analyst,22009,0 +43305,Other,22,High School,19,17,18,57,7,3.0,7,76,Urban,Software Engineer,65386,0 +43306,Male,53,High School,8,59,83,81,65,6.0,0,5,Urban,Manager,31736,0 +43307,Male,36,Diploma,6,9,97,70,23,3.0,7,78,Semi-Urban,HR Executive,76161,1 +43308,Male,39,Bachelors,14,36,52,83,12,6.0,5,83,Urban,HR Executive,92988,1 +43309,Male,34,High School,18,81,23,1,93,7.0,1,45,Semi-Urban,Data Analyst,135255,0 +43310,Male,25,Bachelors,2,82,24,19,39,0.0,6,15,Semi-Urban,ML Engineer,112159,0 +43311,Female,56,Bachelors,19,99,92,22,10,8.0,6,46,Urban,ML Engineer,109208,1 +43312,Male,38,Bachelors,16,10,19,5,1,3.0,2,75,Urban,ML Engineer,38126,0 +43313,Male,45,Masters,4,1,37,41,47,2.0,1,64,Urban,Data Analyst,48060,0 +43314,Male,21,Bachelors,7,4,17,71,16,7.0,5,58,Urban,HR Executive,145958,0 +43315,Male,29,Masters,3,67,81,85,20,4.0,0,70,Rural,Data Analyst,118751,1 +43316,Female,32,Bachelors,9,96,46,83,68,5.0,7,85,Urban,Software Engineer,95816,1 +43317,Female,45,Bachelors,8,48,76,88,66,7.0,2,95,Rural,Software Engineer,74866,1 +43318,Male,54,Bachelors,13,59,76,44,61,6.0,2,88,Urban,Software Engineer,37857,1 +43319,Female,30,Bachelors,18,17,12,31,33,0.0,6,93,Urban,HR Executive,41071,0 +43320,Male,48,Bachelors,19,24,51,9,63,0.0,4,96,Rural,ML Engineer,136647,0 +43321,Male,42,Diploma,1,66,49,59,71,6.0,6,6,Urban,Data Analyst,25255,0 +43322,Male,32,Diploma,4,26,64,18,88,0.0,7,72,Semi-Urban,ML Engineer,91983,0 +43323,Female,40,Diploma,6,89,38,65,42,3.0,2,96,Rural,Data Analyst,146267,1 +43324,Male,56,Diploma,19,12,53,75,27,7.0,2,10,Urban,Data Analyst,136663,0 +43325,Male,47,High School,16,18,99,19,0,5.0,0,95,Urban,Manager,101451,0 +43326,Male,31,Bachelors,10,33,71,68,65,6.0,6,14,Urban,Software Engineer,22726,0 +43327,Male,30,Bachelors,10,2,28,45,72,8.0,5,8,Urban,ML Engineer,21004,0 +43328,Female,26,High School,5,40,53,73,51,1.0,7,20,Urban,Data Analyst,57705,0 +43329,Female,25,Diploma,0,10,26,56,59,0.0,1,97,Urban,Software Engineer,148213,0 +43330,Female,22,Bachelors,12,16,72,28,64,3.0,6,8,Urban,Manager,64971,0 +43331,Other,21,Masters,0,50,95,29,66,1.0,6,43,Semi-Urban,HR Executive,94189,0 +43332,Female,30,Masters,11,92,28,77,14,6.0,5,84,Urban,Manager,122664,1 +43333,Male,42,Masters,12,34,19,18,93,8.0,1,61,Semi-Urban,Software Engineer,56571,0 +43334,Male,52,Diploma,9,72,42,3,13,8.0,3,75,Rural,Manager,56625,0 +43335,Male,26,PhD,12,40,6,31,78,4.0,3,48,Rural,HR Executive,62163,0 +43336,Male,37,High School,10,91,20,27,42,6.0,4,7,Urban,HR Executive,35753,0 +43337,Male,23,Bachelors,13,92,80,92,7,2.0,0,28,Semi-Urban,Software Engineer,46473,1 +43338,Female,52,Masters,1,31,65,75,31,9.0,4,89,Urban,Manager,68988,1 +43339,Male,55,High School,16,53,50,65,72,5.0,6,41,Semi-Urban,Software Engineer,106066,0 +43340,Female,34,High School,0,5,44,46,23,7.0,2,48,Urban,Software Engineer,144628,0 +43341,Male,52,High School,13,14,10,19,82,2.0,6,64,Urban,Data Analyst,109263,0 +43342,Male,40,Bachelors,19,17,71,79,61,9.0,4,76,Urban,ML Engineer,102361,1 +43343,Male,44,Bachelors,5,73,6,49,29,2.0,6,81,Semi-Urban,HR Executive,108414,0 +43344,Male,45,Bachelors,14,24,12,70,96,5.0,4,63,Rural,Manager,117517,0 +43345,Male,48,Masters,9,73,40,87,11,5.0,3,67,Urban,ML Engineer,48378,1 +43346,Male,23,High School,15,45,68,87,44,0.0,4,8,Urban,HR Executive,144408,0 +43347,Male,48,Diploma,13,52,64,80,0,1.0,7,7,Semi-Urban,ML Engineer,99735,0 +43348,Male,41,PhD,9,12,55,82,41,1.0,2,4,Urban,Software Engineer,119690,0 +43349,Female,26,Diploma,13,24,2,72,21,5.0,5,36,Urban,HR Executive,128625,0 +43350,Male,56,Bachelors,12,38,62,69,46,6.0,7,21,Urban,Software Engineer,137582,0 +43351,Female,29,PhD,1,69,13,14,23,9.0,3,67,Semi-Urban,Software Engineer,100168,0 +43352,Male,43,Bachelors,0,78,95,54,54,6.0,7,91,Semi-Urban,ML Engineer,86010,1 +43353,Male,51,Masters,19,7,23,81,6,4.0,5,42,Urban,Software Engineer,106081,0 +43354,Female,44,Diploma,6,46,34,80,50,8.0,5,62,Semi-Urban,Data Analyst,93009,0 +43355,Female,37,Masters,0,46,38,7,0,8.0,0,83,Urban,HR Executive,86412,0 +43356,Female,46,Bachelors,5,20,38,6,72,4.0,3,84,Urban,Manager,98687,0 +43357,Male,54,Bachelors,11,43,63,13,97,2.0,0,6,Rural,Manager,113732,0 +43358,Male,25,Masters,5,87,7,91,69,3.0,5,36,Rural,Data Analyst,110955,0 +43359,Female,22,Masters,11,31,13,20,42,6.0,6,89,Urban,HR Executive,115022,0 +43360,Male,42,High School,14,41,45,5,41,1.0,0,63,Urban,ML Engineer,52729,0 +43361,Female,25,Bachelors,3,83,30,48,57,7.0,5,38,Semi-Urban,Manager,132584,0 +43362,Male,46,Bachelors,6,18,12,82,33,1.0,4,55,Rural,ML Engineer,89329,0 +43363,Male,41,Bachelors,11,84,45,11,65,5.0,2,58,Rural,ML Engineer,43756,0 +43364,Male,22,High School,18,47,98,57,0,6.0,1,84,Urban,HR Executive,134389,1 +43365,Female,55,Diploma,5,43,31,54,87,6.0,7,73,Semi-Urban,HR Executive,68752,0 +43366,Male,41,Masters,8,63,24,28,38,1.0,2,65,Rural,Data Analyst,115084,0 +43367,Female,35,High School,2,52,58,10,71,5.0,3,81,Semi-Urban,HR Executive,45875,0 +43368,Male,34,Bachelors,11,59,40,58,37,1.0,4,99,Urban,Data Analyst,64912,1 +43369,Female,46,Bachelors,7,72,17,56,42,1.0,0,66,Urban,Data Analyst,26698,0 +43370,Male,28,Masters,6,25,67,87,63,9.0,5,13,Urban,HR Executive,44119,0 +43371,Female,36,Masters,2,78,89,87,86,8.0,1,67,Urban,ML Engineer,27706,1 +43372,Male,58,Masters,17,46,96,86,3,1.0,6,24,Urban,Data Analyst,32262,1 +43373,Female,42,Bachelors,4,4,16,53,47,3.0,6,17,Rural,HR Executive,55146,0 +43374,Male,43,Bachelors,15,70,46,52,12,6.0,7,34,Urban,Data Analyst,119735,0 +43375,Male,28,PhD,11,33,97,44,80,9.0,1,16,Semi-Urban,ML Engineer,107040,0 +43376,Male,27,Masters,3,45,27,2,24,2.0,0,72,Semi-Urban,Manager,41033,0 +43377,Female,48,Diploma,14,6,56,37,86,6.0,0,25,Urban,Software Engineer,63258,0 +43378,Male,46,Masters,9,81,10,58,77,1.0,2,49,Semi-Urban,Data Analyst,132520,0 +43379,Male,42,Bachelors,17,23,45,69,77,5.0,1,55,Rural,ML Engineer,70164,0 +43380,Male,48,High School,7,53,25,65,44,1.0,7,79,Urban,Software Engineer,43111,0 +43381,Male,46,Diploma,16,79,97,55,19,6.0,5,51,Rural,ML Engineer,67577,1 +43382,Female,56,High School,13,4,64,42,56,8.0,3,56,Semi-Urban,HR Executive,24776,0 +43383,Male,55,High School,15,89,3,61,81,7.0,2,79,Urban,Manager,119971,0 +43384,Male,29,Bachelors,14,48,78,62,43,3.0,2,34,Urban,HR Executive,104364,0 +43385,Male,32,Bachelors,2,36,9,15,42,6.0,2,52,Semi-Urban,Data Analyst,56166,0 +43386,Male,33,Bachelors,1,18,54,12,91,6.0,2,22,Urban,Data Analyst,140255,0 +43387,Male,38,Diploma,4,78,65,48,69,4.0,3,87,Semi-Urban,Manager,53250,1 +43388,Male,55,Bachelors,19,35,46,59,45,6.0,4,98,Semi-Urban,Software Engineer,83603,1 +43389,Male,22,Bachelors,8,47,19,67,54,1.0,2,91,Urban,Software Engineer,116012,0 +43390,Male,23,Diploma,15,23,76,5,38,8.0,2,69,Urban,Data Analyst,142514,0 +43391,Female,57,Masters,5,87,14,99,51,2.0,6,3,Urban,ML Engineer,40517,0 +43392,Male,58,Masters,7,80,67,35,2,6.0,0,12,Semi-Urban,Software Engineer,136132,0 +43393,Female,27,Diploma,17,64,32,47,52,9.0,5,19,Urban,Data Analyst,92863,0 +43394,Male,56,Masters,2,35,18,57,37,1.0,2,35,Urban,Manager,102960,0 +43395,Female,46,High School,12,74,45,0,56,8.0,0,37,Urban,Manager,95542,0 +43396,Male,42,Bachelors,10,73,88,86,26,8.0,5,95,Urban,Software Engineer,92888,1 +43397,Male,38,Masters,2,68,78,76,22,3.0,2,59,Urban,Software Engineer,125364,1 +43398,Female,56,Diploma,19,56,21,77,63,9.0,3,34,Urban,ML Engineer,131596,0 +43399,Female,46,Masters,19,0,90,76,81,5.0,3,49,Urban,Manager,48166,0 +43400,Male,27,Diploma,4,17,77,32,51,5.0,6,81,Rural,Manager,82625,0 +43401,Male,54,Bachelors,16,87,74,36,86,7.0,7,45,Semi-Urban,ML Engineer,114703,1 +43402,Male,46,High School,8,73,10,90,97,1.0,7,15,Urban,Software Engineer,30130,0 +43403,Female,29,Bachelors,14,59,97,64,33,7.0,4,16,Urban,HR Executive,46740,0 +43404,Female,55,Bachelors,0,41,80,28,71,3.0,4,60,Urban,ML Engineer,137397,0 +43405,Male,57,Masters,17,58,88,46,42,9.0,5,31,Urban,Data Analyst,81125,0 +43406,Female,33,Masters,9,10,72,30,45,9.0,5,61,Rural,ML Engineer,132938,0 +43407,Male,30,Bachelors,17,93,76,50,7,9.0,4,86,Urban,HR Executive,41823,1 +43408,Female,32,Diploma,7,64,53,59,36,2.0,6,51,Urban,Manager,102506,0 +43409,Male,22,Bachelors,6,16,22,88,1,2.0,0,0,Semi-Urban,Software Engineer,87027,0 +43410,Male,58,Bachelors,0,56,99,20,52,3.0,4,44,Urban,Data Analyst,22986,0 +43411,Male,37,Bachelors,4,62,2,85,2,2.0,5,5,Urban,Software Engineer,45153,0 +43412,Other,59,High School,17,2,50,84,96,9.0,5,72,Urban,Software Engineer,20455,0 +43413,Female,26,Diploma,12,58,37,32,56,5.0,5,74,Semi-Urban,Data Analyst,90745,0 +43414,Female,55,Bachelors,10,45,36,6,47,4.0,3,46,Urban,Software Engineer,65662,0 +43415,Male,58,Diploma,1,63,75,34,60,1.0,5,81,Urban,Manager,86574,1 +43416,Male,30,PhD,7,78,51,28,99,6.0,3,12,Rural,Manager,55487,0 +43417,Male,35,Bachelors,10,16,47,52,19,3.0,5,60,Urban,ML Engineer,46963,0 +43418,Female,55,Masters,18,68,62,98,51,1.0,5,30,Semi-Urban,HR Executive,58266,1 +43419,Female,45,Bachelors,12,65,27,15,7,9.0,5,52,Urban,Software Engineer,33150,0 +43420,Male,47,Masters,9,65,10,4,60,9.0,3,33,Rural,Software Engineer,88921,0 +43421,Female,38,Bachelors,5,60,68,56,61,5.0,3,4,Urban,HR Executive,77238,0 +43422,Female,25,Bachelors,0,42,47,64,61,3.0,3,6,Urban,HR Executive,35463,0 +43423,Male,41,High School,0,27,4,47,86,0.0,6,81,Urban,Manager,63993,0 +43424,Male,49,Bachelors,7,88,94,69,18,8.0,1,49,Rural,HR Executive,106496,1 +43425,Male,31,Bachelors,5,89,80,35,25,3.0,5,96,Semi-Urban,ML Engineer,105807,1 +43426,Female,36,Masters,0,67,31,5,59,1.0,5,85,Urban,HR Executive,29844,0 +43427,Female,42,Diploma,6,40,79,18,35,0.0,6,97,Urban,Manager,76770,0 +43428,Female,54,Bachelors,14,85,33,84,2,5.0,4,82,Semi-Urban,Data Analyst,35000,1 +43429,Female,27,Bachelors,14,70,77,91,66,9.0,4,62,Rural,Software Engineer,115238,1 +43430,Male,41,Bachelors,11,22,4,55,75,9.0,2,93,Rural,Manager,60641,0 +43431,Female,44,Bachelors,16,22,3,27,91,7.0,0,93,Rural,Software Engineer,38219,0 +43432,Female,41,Diploma,12,58,0,25,33,2.0,7,36,Semi-Urban,Manager,21549,0 +43433,Female,56,High School,8,41,53,15,85,2.0,4,96,Urban,Data Analyst,129606,0 +43434,Male,42,High School,2,73,35,37,62,1.0,2,32,Urban,ML Engineer,141107,0 +43435,Female,23,High School,13,93,49,87,7,3.0,6,18,Urban,HR Executive,98824,1 +43436,Female,57,Masters,7,97,49,69,2,2.0,7,80,Urban,ML Engineer,144274,1 +43437,Female,31,Diploma,12,77,31,86,6,7.0,2,43,Rural,Data Analyst,149947,0 +43438,Female,54,Diploma,6,9,15,13,24,5.0,0,70,Semi-Urban,Data Analyst,44677,0 +43439,Male,46,Diploma,11,40,81,37,11,6.0,0,62,Urban,ML Engineer,44022,0 +43440,Female,43,Bachelors,19,61,3,85,52,7.0,4,11,Semi-Urban,Software Engineer,79126,0 +43441,Male,52,Bachelors,8,59,9,74,12,9.0,2,66,Semi-Urban,Software Engineer,34536,0 +43442,Male,40,Masters,2,4,60,96,88,0.0,4,33,Urban,Manager,122825,0 +43443,Female,29,Masters,16,88,89,69,53,9.0,5,37,Rural,HR Executive,61530,1 +43444,Male,46,High School,17,1,82,42,35,5.0,4,64,Urban,Software Engineer,143095,0 +43445,Male,35,Bachelors,16,55,99,70,23,4.0,5,71,Rural,Data Analyst,131836,1 +43446,Other,43,High School,19,43,69,87,17,5.0,3,63,Urban,Software Engineer,130154,1 +43447,Male,51,Diploma,17,39,21,54,35,2.0,2,27,Urban,HR Executive,86373,0 +43448,Female,48,Bachelors,1,90,35,32,31,3.0,3,56,Urban,Data Analyst,23071,0 +43449,Male,29,Diploma,2,76,24,68,22,5.0,3,85,Urban,HR Executive,90709,1 +43450,Male,25,Masters,5,53,83,57,76,8.0,2,92,Urban,HR Executive,121513,1 +43451,Male,36,Bachelors,12,81,21,89,28,0.0,5,23,Semi-Urban,Manager,125665,0 +43452,Female,53,Masters,7,26,7,85,75,0.0,0,19,Rural,ML Engineer,102381,0 +43453,Male,50,Bachelors,9,71,16,56,42,8.0,0,93,Rural,Manager,106827,1 +43454,Other,36,Diploma,14,93,29,16,15,0.0,7,79,Urban,HR Executive,103602,0 +43455,Female,30,PhD,8,63,17,13,19,7.0,2,11,Urban,Manager,88565,0 +43456,Female,42,Bachelors,7,13,84,50,5,2.0,2,78,Rural,Data Analyst,147251,0 +43457,Male,48,Bachelors,12,69,2,42,78,9.0,6,92,Urban,HR Executive,80057,0 +43458,Male,44,Bachelors,2,4,68,24,70,7.0,0,89,Semi-Urban,ML Engineer,137118,0 +43459,Female,54,Bachelors,5,98,4,55,76,3.0,0,18,Semi-Urban,Data Analyst,67803,0 +43460,Male,34,Masters,10,78,66,0,12,8.0,3,4,Urban,Manager,72668,0 +43461,Male,27,Bachelors,16,23,67,48,7,9.0,7,79,Urban,Software Engineer,86076,0 +43462,Male,40,PhD,10,56,96,40,32,6.0,5,69,Urban,Manager,64773,1 +43463,Female,32,Bachelors,11,0,4,98,48,9.0,3,49,Urban,Software Engineer,125814,0 +43464,Male,24,Bachelors,13,20,26,11,45,5.0,3,21,Urban,ML Engineer,47349,0 +43465,Male,22,High School,4,92,18,17,1,3.0,0,48,Urban,Manager,131589,0 +43466,Female,33,High School,15,53,12,33,0,6.0,1,77,Semi-Urban,ML Engineer,50180,0 +43467,Female,32,Masters,4,49,60,36,21,2.0,6,50,Urban,Data Analyst,72599,0 +43468,Male,58,Masters,14,67,38,2,37,9.0,6,10,Urban,HR Executive,39628,0 +43469,Male,28,Bachelors,6,94,64,33,93,1.0,1,53,Rural,Manager,52981,1 +43470,Male,22,Masters,14,68,82,45,21,6.0,0,64,Urban,Manager,50281,1 +43471,Male,41,Bachelors,1,21,0,16,63,8.0,7,77,Urban,Manager,93822,0 +43472,Male,33,Masters,7,13,42,35,77,2.0,3,78,Urban,Manager,49128,0 +43473,Male,26,Bachelors,7,70,54,19,23,8.0,5,16,Urban,ML Engineer,123027,0 +43474,Male,26,Masters,16,32,28,42,12,3.0,3,98,Urban,Software Engineer,24512,0 +43475,Male,42,Bachelors,17,53,5,48,58,1.0,2,32,Semi-Urban,Manager,37865,0 +43476,Male,35,Bachelors,10,60,3,79,48,6.0,0,37,Semi-Urban,Manager,80318,0 +43477,Female,58,Masters,1,28,8,51,34,8.0,2,95,Rural,HR Executive,51378,0 +43478,Male,54,Bachelors,2,28,76,2,53,8.0,6,2,Urban,Software Engineer,52895,0 +43479,Male,41,Bachelors,0,83,18,63,23,3.0,0,67,Urban,Data Analyst,87196,0 +43480,Male,45,Masters,18,9,45,63,68,0.0,4,34,Urban,HR Executive,139285,0 +43481,Male,57,High School,4,33,56,89,13,1.0,2,75,Rural,HR Executive,102406,1 +43482,Female,28,Masters,14,94,74,50,75,8.0,7,18,Rural,HR Executive,68018,0 +43483,Female,30,Diploma,2,84,43,58,58,4.0,6,82,Urban,HR Executive,88887,1 +43484,Male,36,Bachelors,9,54,9,80,85,9.0,2,91,Urban,Manager,32362,0 +43485,Female,31,Bachelors,0,20,34,67,29,4.0,0,95,Semi-Urban,Data Analyst,109596,0 +43486,Female,25,High School,10,61,98,84,38,0.0,1,37,Semi-Urban,Software Engineer,25311,1 +43487,Male,40,Diploma,15,67,6,71,13,4.0,0,92,Rural,Data Analyst,20557,1 +43488,Male,43,Diploma,15,10,84,89,37,2.0,4,33,Urban,Software Engineer,91806,0 +43489,Female,50,Diploma,0,86,85,56,39,4.0,4,61,Semi-Urban,HR Executive,89388,1 +43490,Other,49,High School,13,14,56,98,43,8.0,7,21,Urban,Manager,50062,0 +43491,Male,21,Bachelors,13,2,14,41,30,8.0,7,49,Urban,Software Engineer,131711,0 +43492,Male,46,Bachelors,18,85,86,78,5,2.0,7,33,Urban,Data Analyst,68068,1 +43493,Female,39,Masters,12,72,15,49,16,9.0,5,83,Semi-Urban,Manager,41326,0 +43494,,59,Bachelors,18,12,47,33,48,5.0,6,76,Urban,Data Analyst,93073,0 +43495,Female,24,Bachelors,1,79,15,42,37,9.0,3,56,Urban,Data Analyst,38304,0 +43496,Male,40,Diploma,5,73,14,9,67,8.0,4,79,Semi-Urban,ML Engineer,80179,0 +43497,Male,55,PhD,17,2,42,54,91,6.0,7,29,Semi-Urban,ML Engineer,41255,0 +43498,Male,24,Bachelors,4,52,88,14,27,6.0,2,48,Urban,HR Executive,128412,0 +43499,Female,30,High School,0,24,76,71,73,6.0,2,26,Rural,Manager,117203,0 +43500,Male,59,Bachelors,10,75,24,10,83,5.0,7,94,Urban,ML Engineer,22507,0 +43501,Female,54,Bachelors,11,54,39,5,37,0.0,0,88,Rural,Manager,115514,0 +43502,Male,57,Bachelors,4,18,82,67,15,6.0,6,33,Urban,Manager,68236,0 +43503,Male,51,PhD,6,98,94,99,68,2.0,6,50,Urban,HR Executive,67620,1 +43504,Male,53,Diploma,13,73,0,36,79,6.0,5,96,Urban,HR Executive,119521,0 +43505,Female,31,Diploma,8,13,76,15,67,7.0,5,87,Urban,Software Engineer,79075,0 +43506,Female,35,Diploma,8,92,83,90,94,2.0,1,13,Urban,Manager,35444,1 +43507,Male,32,Bachelors,16,30,37,43,76,5.0,2,46,Semi-Urban,ML Engineer,149039,0 +43508,Male,29,Bachelors,12,63,21,77,14,8.0,5,11,Rural,Software Engineer,120612,0 +43509,Female,27,Diploma,2,42,33,68,99,7.0,7,12,Urban,Data Analyst,54786,0 +43510,Male,40,Masters,4,81,50,89,51,4.0,4,4,Urban,Manager,128751,0 +43511,Male,22,Masters,7,58,47,6,48,2.0,0,84,Urban,ML Engineer,128447,0 +43512,Male,52,Bachelors,9,6,15,45,71,0.0,4,73,Urban,ML Engineer,141492,0 +43513,Other,47,Bachelors,6,23,99,99,98,4.0,7,18,Urban,Data Analyst,120763,0 +43514,Female,54,Bachelors,11,27,41,88,88,8.0,1,50,Urban,HR Executive,113386,0 +43515,Male,59,Bachelors,14,42,75,5,91,0.0,0,49,Rural,Manager,29648,0 +43516,Male,46,Masters,8,52,98,58,91,3.0,4,55,Semi-Urban,Manager,38785,1 +43517,Female,24,Bachelors,7,45,54,0,77,7.0,3,94,Urban,Software Engineer,114261,0 +43518,Male,34,Diploma,1,23,6,19,58,1.0,0,22,Semi-Urban,HR Executive,149900,0 +43519,Male,28,Masters,0,63,75,96,4,5.0,3,71,Urban,Data Analyst,21499,1 +43520,Male,58,Bachelors,13,8,77,98,92,0.0,5,15,Urban,Data Analyst,123785,0 +43521,Male,39,High School,3,23,3,98,12,3.0,2,68,Urban,Data Analyst,31955,0 +43522,Female,56,Bachelors,18,24,44,30,6,0.0,0,27,Urban,Manager,128539,0 +43523,Male,56,Masters,10,53,47,87,33,5.0,0,66,Urban,HR Executive,39097,1 +43524,Male,46,PhD,18,27,64,19,55,0.0,4,99,Semi-Urban,Manager,87600,0 +43525,Male,43,Bachelors,12,99,79,89,42,4.0,6,85,Semi-Urban,Data Analyst,92092,1 +43526,Female,39,PhD,1,21,40,34,5,8.0,2,94,Rural,ML Engineer,102881,0 +43527,Female,42,High School,16,82,69,70,58,7.0,3,99,Rural,Data Analyst,85057,1 +43528,Male,22,Diploma,10,63,95,98,0,8.0,7,82,Urban,Data Analyst,64024,1 +43529,Female,37,Bachelors,19,3,34,82,70,1.0,7,15,Urban,Software Engineer,42937,0 +43530,Male,24,Masters,4,31,24,64,19,5.0,7,78,Semi-Urban,ML Engineer,123659,0 +43531,Female,54,Bachelors,13,74,8,46,25,8.0,7,3,Urban,Manager,79251,0 +43532,Male,51,Diploma,18,92,10,4,11,2.0,2,22,Urban,ML Engineer,47152,0 +43533,Male,22,Bachelors,6,72,60,5,94,1.0,6,92,Semi-Urban,HR Executive,69316,0 +43534,Male,25,Diploma,2,72,34,5,87,9.0,7,58,Semi-Urban,HR Executive,134800,0 +43535,Male,51,Masters,16,61,54,33,66,7.0,3,93,Urban,HR Executive,118355,1 +43536,Female,52,Diploma,19,47,78,28,75,9.0,4,6,Urban,ML Engineer,135766,0 +43537,Female,39,Diploma,11,60,5,72,5,2.0,6,39,Urban,Manager,28108,0 +43538,Female,47,Bachelors,15,9,53,3,99,5.0,2,53,Urban,ML Engineer,55825,0 +43539,Male,39,Bachelors,0,7,55,83,36,8.0,0,23,Rural,Manager,108183,0 +43540,Other,37,Masters,1,59,70,26,39,9.0,4,54,Urban,Software Engineer,87822,0 +43541,Male,37,High School,5,86,5,62,75,3.0,7,87,Urban,Manager,27769,1 +43542,Female,32,Bachelors,14,38,38,54,65,8.0,0,34,Urban,ML Engineer,56276,0 +43543,Female,54,High School,16,7,19,54,53,3.0,4,12,Urban,HR Executive,82740,0 +43544,Male,57,Diploma,16,2,5,52,89,8.0,2,46,Urban,HR Executive,91514,0 +43545,Female,52,Bachelors,13,35,50,35,14,5.0,0,83,Rural,Software Engineer,135614,0 +43546,Male,56,Bachelors,7,11,6,95,1,7.0,6,87,Semi-Urban,Manager,76381,0 +43547,Male,36,Bachelors,16,70,15,49,75,4.0,5,42,Urban,Manager,129936,0 +43548,Female,30,Masters,16,93,9,27,81,6.0,5,2,Semi-Urban,ML Engineer,28588,0 +43549,Male,36,Bachelors,7,5,65,98,72,6.0,6,15,Urban,Software Engineer,63881,0 +43550,Male,47,Bachelors,4,12,17,11,58,4.0,2,81,Urban,Software Engineer,34078,0 +43551,Male,58,Diploma,17,90,56,47,14,6.0,6,19,Rural,Data Analyst,30798,0 +43552,Male,56,Diploma,14,57,31,6,18,4.0,0,44,Semi-Urban,HR Executive,24747,0 +43553,Male,26,PhD,3,86,36,39,76,2.0,4,8,Rural,Data Analyst,23976,0 +43554,Female,42,Bachelors,6,90,98,61,8,1.0,4,58,Semi-Urban,Data Analyst,61991,1 +43555,Male,29,High School,19,55,0,59,12,8.0,7,75,Urban,Data Analyst,86105,0 +43556,Female,28,Bachelors,0,54,79,70,49,2.0,5,43,Semi-Urban,Manager,143996,1 +43557,Female,59,High School,5,57,35,58,83,0.0,7,93,Urban,ML Engineer,99265,1 +43558,Male,32,High School,11,88,9,6,44,2.0,6,54,Urban,HR Executive,68956,0 +43559,Female,32,Diploma,17,38,11,87,84,8.0,7,5,Semi-Urban,Data Analyst,57162,0 +43560,Male,39,Masters,7,44,2,24,14,7.0,6,88,Semi-Urban,Manager,115428,0 +43561,Male,33,Diploma,5,39,94,97,16,5.0,3,7,Semi-Urban,Manager,87078,1 +43562,Male,47,Diploma,13,54,71,88,43,7.0,2,5,Semi-Urban,ML Engineer,20202,0 +43563,Male,46,Diploma,16,30,99,35,68,1.0,5,10,Rural,Software Engineer,146268,0 +43564,Other,47,Bachelors,13,86,47,44,24,6.0,6,22,Semi-Urban,Data Analyst,134762,0 +43565,Male,27,Bachelors,1,8,79,96,95,3.0,7,52,Urban,ML Engineer,78120,1 +43566,Female,30,Diploma,8,70,68,84,88,5.0,4,50,Semi-Urban,Software Engineer,137228,1 +43567,Female,30,Diploma,6,94,42,17,12,2.0,5,28,Urban,Manager,41525,0 +43568,Male,49,Masters,1,7,35,64,95,3.0,6,1,Semi-Urban,Data Analyst,83409,0 +43569,Female,49,Bachelors,12,16,7,45,9,9.0,5,0,Urban,Software Engineer,85009,0 +43570,Other,46,Masters,6,31,19,7,7,7.0,1,59,Semi-Urban,Data Analyst,58174,0 +43571,Female,59,Bachelors,18,74,32,84,81,5.0,5,24,Urban,HR Executive,29455,0 +43572,Male,51,Bachelors,4,13,75,0,92,3.0,5,28,Urban,ML Engineer,31304,0 +43573,Male,36,Diploma,4,94,57,0,40,0.0,2,13,Rural,HR Executive,111339,0 +43574,Male,32,Bachelors,9,54,94,94,70,4.0,1,96,Semi-Urban,ML Engineer,138785,1 +43575,Female,52,Diploma,14,4,72,85,28,5.0,5,93,Urban,ML Engineer,25536,1 +43576,Male,45,Bachelors,7,91,13,82,3,1.0,0,33,Urban,Data Analyst,55378,0 +43577,Female,30,Diploma,18,76,7,85,47,1.0,2,11,Urban,Software Engineer,49111,0 +43578,Female,28,High School,18,30,57,38,5,8.0,7,54,Urban,ML Engineer,76536,0 +43579,Male,59,Bachelors,6,21,2,31,55,1.0,7,3,Urban,Software Engineer,38058,0 +43580,Male,38,Masters,6,41,35,72,73,7.0,6,62,Semi-Urban,HR Executive,42860,0 +43581,Other,33,Diploma,2,22,84,65,87,3.0,7,43,Semi-Urban,Software Engineer,43759,0 +43582,Male,27,Bachelors,3,31,72,83,56,0.0,7,17,Semi-Urban,Manager,52286,0 +43583,Male,30,Bachelors,12,95,11,19,27,7.0,1,89,Urban,Software Engineer,59294,0 +43584,Male,44,PhD,16,76,14,93,11,8.0,6,66,Urban,ML Engineer,135374,1 +43585,Male,40,Masters,8,80,1,53,23,5.0,7,63,Semi-Urban,HR Executive,95420,0 +43586,Male,37,Bachelors,16,83,96,90,35,5.0,5,77,Urban,HR Executive,139910,1 +43587,Male,50,Bachelors,11,39,64,14,26,8.0,5,46,Urban,Manager,57612,0 +43588,Male,35,Bachelors,6,32,33,97,39,7.0,6,13,Urban,HR Executive,52511,0 +43589,Male,51,Bachelors,12,16,88,41,65,5.0,3,37,Rural,Manager,140103,0 +43590,Male,53,Diploma,19,36,92,51,58,5.0,2,58,Semi-Urban,Data Analyst,59589,1 +43591,Male,38,High School,3,97,33,47,78,7.0,1,45,Rural,HR Executive,81871,0 +43592,Female,59,Masters,11,15,46,2,17,0.0,5,77,Urban,Software Engineer,46915,0 +43593,Male,35,Masters,16,51,61,73,46,8.0,5,88,Urban,Data Analyst,33107,1 +43594,Male,31,Bachelors,15,37,33,66,53,6.0,1,25,Urban,HR Executive,118417,0 +43595,Female,46,Diploma,14,54,66,94,15,6.0,7,51,Rural,Software Engineer,70518,1 +43596,Male,36,High School,5,51,3,44,73,9.0,1,72,Urban,Manager,99764,0 +43597,Male,22,Bachelors,9,50,9,15,80,4.0,4,31,Semi-Urban,HR Executive,137098,0 +43598,Female,46,High School,15,34,98,35,96,3.0,6,22,Urban,Software Engineer,48795,0 +43599,Male,41,Bachelors,0,8,61,39,4,6.0,7,49,Semi-Urban,Data Analyst,105151,0 +43600,Female,34,Diploma,6,59,0,27,61,4.0,4,15,Urban,Software Engineer,108539,0 +43601,Female,28,Masters,10,3,74,24,44,9.0,4,14,Semi-Urban,Data Analyst,62784,0 +43602,Male,48,PhD,6,87,84,41,12,2.0,2,5,Semi-Urban,HR Executive,28994,0 +43603,Male,49,Bachelors,15,20,44,85,11,9.0,7,97,Semi-Urban,Data Analyst,87621,1 +43604,Male,55,Bachelors,15,67,65,9,15,0.0,5,78,Semi-Urban,ML Engineer,109497,0 +43605,Male,39,Diploma,13,68,36,3,2,7.0,6,40,Urban,ML Engineer,78259,0 +43606,Female,40,Diploma,16,13,96,22,82,3.0,5,64,Urban,Manager,71468,0 +43607,Male,40,High School,18,63,16,16,36,7.0,3,11,Urban,ML Engineer,94833,0 +43608,Male,30,Bachelors,3,31,27,21,40,2.0,3,97,Rural,HR Executive,120205,0 +43609,Male,41,High School,3,33,48,47,80,0.0,3,83,Semi-Urban,HR Executive,125388,0 +43610,Male,27,Diploma,15,82,39,90,92,8.0,3,77,Semi-Urban,ML Engineer,69739,1 +43611,Male,51,Bachelors,11,12,26,58,52,9.0,3,40,Urban,Data Analyst,74791,0 +43612,Male,46,High School,2,60,72,14,68,2.0,1,69,Urban,Manager,67641,0 +43613,Female,57,Bachelors,16,56,17,84,6,8.0,7,7,Urban,Manager,103012,0 +43614,Male,43,Diploma,17,49,91,92,22,2.0,1,28,Urban,HR Executive,85795,1 +43615,Male,22,Masters,12,51,14,17,79,7.0,4,88,Urban,Manager,71527,0 +43616,Male,34,Bachelors,1,34,22,67,31,5.0,0,33,Semi-Urban,Data Analyst,83576,0 +43617,Male,56,Masters,1,56,22,6,7,7.0,0,18,Rural,ML Engineer,138907,0 +43618,Male,35,Diploma,1,3,95,4,55,6.0,4,61,Semi-Urban,Software Engineer,128984,0 +43619,Male,54,Diploma,4,72,28,49,32,6.0,6,62,Urban,Manager,72532,0 +43620,Male,31,Bachelors,17,96,38,52,84,2.0,0,35,Semi-Urban,Software Engineer,138754,0 +43621,Male,21,Masters,13,30,84,95,87,9.0,5,43,Rural,HR Executive,141921,1 +43622,Male,49,Diploma,6,79,34,48,47,0.0,6,49,Rural,HR Executive,72130,0 +43623,Female,39,Diploma,17,79,79,10,35,3.0,1,86,Urban,Data Analyst,133389,1 +43624,Male,52,Bachelors,7,84,5,40,99,9.0,0,66,Urban,HR Executive,89667,0 +43625,Female,22,Masters,19,59,1,84,82,8.0,7,3,Urban,Software Engineer,98765,0 +43626,Male,55,Masters,2,42,42,3,23,7.0,6,10,Urban,Data Analyst,68624,0 +43627,Female,59,Bachelors,0,10,80,61,26,9.0,4,16,Semi-Urban,Manager,88929,0 +43628,Male,36,Masters,16,69,57,35,67,8.0,2,69,Urban,Data Analyst,70443,0 +43629,Male,59,Masters,8,54,71,44,78,5.0,2,3,Urban,Software Engineer,33713,0 +43630,Female,57,High School,4,86,9,50,41,1.0,3,98,Urban,Data Analyst,74401,1 +43631,Female,59,Bachelors,18,7,40,62,80,6.0,6,3,Urban,Manager,45973,0 +43632,Other,44,Bachelors,5,48,85,17,53,1.0,5,70,Urban,HR Executive,127897,0 +43633,Male,29,Diploma,15,63,74,1,49,3.0,1,60,Urban,Software Engineer,97512,0 +43634,Male,30,Masters,6,46,25,48,75,5.0,7,48,Semi-Urban,Software Engineer,144047,0 +43635,Male,34,Bachelors,4,61,68,67,9,3.0,4,29,Urban,Manager,125499,0 +43636,Female,56,Bachelors,8,85,8,75,62,2.0,3,85,Urban,Data Analyst,127108,1 +43637,Other,48,PhD,5,57,2,65,58,1.0,0,12,Urban,Software Engineer,67115,0 +43638,Male,33,Bachelors,4,43,39,49,62,1.0,2,45,Semi-Urban,Software Engineer,71891,0 +43639,Female,22,Masters,7,46,27,33,85,6.0,6,33,Urban,Data Analyst,70872,0 +43640,Male,44,Bachelors,4,8,17,12,65,9.0,5,73,Urban,ML Engineer,77651,0 +43641,Male,22,Diploma,0,33,51,5,91,1.0,7,49,Semi-Urban,HR Executive,40728,0 +43642,Male,28,Bachelors,11,98,46,97,29,9.0,1,26,Urban,Manager,110581,1 +43643,Male,23,Bachelors,0,84,70,68,62,1.0,0,44,Urban,Manager,38515,1 +43644,Male,23,High School,2,88,84,63,13,8.0,2,80,Rural,HR Executive,81208,1 +43645,Male,58,High School,8,56,67,13,26,7.0,7,41,Urban,HR Executive,130847,0 +43646,Male,54,Masters,19,95,98,85,33,0.0,1,64,Semi-Urban,Data Analyst,27147,1 +43647,Male,34,Bachelors,7,31,48,71,74,8.0,1,45,Semi-Urban,Manager,63307,0 +43648,Female,42,Bachelors,3,28,37,39,47,8.0,5,19,Urban,ML Engineer,38858,0 +43649,Male,29,Masters,12,32,32,19,43,9.0,1,84,Rural,Software Engineer,112532,0 +43650,Male,37,High School,10,8,26,72,15,3.0,5,76,Urban,Manager,39044,0 +43651,Male,39,Masters,14,37,45,36,14,4.0,0,90,Rural,ML Engineer,140137,0 +43652,Female,59,Bachelors,19,69,13,20,56,6.0,2,25,Semi-Urban,Data Analyst,42313,0 +43653,Male,55,Bachelors,9,8,96,33,60,5.0,0,57,Semi-Urban,Data Analyst,96021,0 +43654,Other,50,Diploma,2,37,10,89,88,5.0,2,73,Urban,Manager,34808,0 +43655,Male,48,Bachelors,6,3,2,87,62,1.0,7,54,Rural,Software Engineer,94868,0 +43656,Male,58,Bachelors,0,75,26,64,35,3.0,4,76,Urban,HR Executive,143101,1 +43657,Male,43,Bachelors,11,32,79,73,54,8.0,0,40,Semi-Urban,Software Engineer,67608,0 +43658,Male,33,PhD,2,15,60,20,70,6.0,5,28,Semi-Urban,ML Engineer,145484,0 +43659,Male,43,Bachelors,11,17,57,28,91,1.0,7,84,Semi-Urban,Manager,66139,0 +43660,Male,37,Bachelors,14,87,51,55,65,7.0,0,56,Urban,HR Executive,32014,1 +43661,Male,30,Masters,2,16,17,4,68,2.0,4,46,Urban,Manager,100060,0 +43662,Male,22,Diploma,19,84,60,71,71,9.0,6,69,Semi-Urban,Data Analyst,22256,1 +43663,Female,24,Diploma,13,56,96,46,16,8.0,5,57,Urban,Data Analyst,81620,1 +43664,Female,28,Bachelors,6,48,45,7,14,1.0,0,9,Semi-Urban,Data Analyst,50713,0 +43665,Male,51,Diploma,18,4,32,23,6,1.0,2,40,Rural,Manager,53556,0 +43666,Male,27,Masters,5,44,71,49,60,5.0,0,0,Rural,Software Engineer,122902,0 +43667,Male,45,Diploma,11,44,66,34,31,3.0,1,7,Urban,HR Executive,123765,0 +43668,Male,28,Bachelors,17,62,39,38,76,1.0,6,49,Urban,Manager,111658,0 +43669,Female,36,Masters,9,34,5,87,29,9.0,7,64,Urban,Data Analyst,110607,0 +43670,Female,53,Bachelors,13,87,68,46,73,2.0,3,49,Urban,Manager,37008,1 +43671,Male,50,Masters,0,63,51,65,45,2.0,1,85,Urban,Software Engineer,61093,1 +43672,Male,41,Bachelors,13,6,57,66,93,1.0,4,90,Semi-Urban,Software Engineer,30292,0 +43673,Male,45,Masters,14,90,21,70,82,5.0,6,63,Urban,HR Executive,55742,1 +43674,Female,48,Bachelors,3,8,60,53,1,9.0,1,32,Urban,HR Executive,126638,0 +43675,Male,26,Masters,7,66,93,65,98,6.0,7,90,Urban,ML Engineer,80598,1 +43676,Other,54,Bachelors,4,37,90,51,37,1.0,1,17,Semi-Urban,Manager,67685,0 +43677,Other,58,Bachelors,5,78,82,58,30,3.0,2,82,Rural,Data Analyst,40732,1 +43678,Female,32,Bachelors,10,78,40,92,66,4.0,4,80,Semi-Urban,Data Analyst,128299,1 +43679,Male,28,Diploma,7,15,70,42,95,3.0,0,65,Urban,ML Engineer,109932,0 +43680,Male,57,PhD,9,39,55,51,77,2.0,4,46,Urban,Software Engineer,60765,0 +43681,Male,49,Diploma,15,5,95,5,98,3.0,0,87,Urban,ML Engineer,133971,0 +43682,Other,55,Bachelors,9,20,78,51,48,0.0,1,96,Urban,HR Executive,146855,1 +43683,Male,30,Diploma,5,1,24,57,17,1.0,2,57,Urban,Data Analyst,51657,0 +43684,Female,28,High School,3,29,18,77,38,7.0,4,88,Urban,ML Engineer,49060,0 +43685,Other,52,Masters,4,82,97,82,32,1.0,6,2,Urban,Data Analyst,89646,1 +43686,Female,34,Bachelors,4,59,38,10,33,0.0,3,57,Semi-Urban,Manager,45047,0 +43687,Male,25,Masters,8,59,1,76,40,0.0,7,50,Urban,ML Engineer,60081,0 +43688,Male,50,High School,5,32,30,28,84,1.0,2,54,Urban,HR Executive,115104,0 +43689,Male,49,Bachelors,17,64,22,68,88,4.0,7,18,Urban,HR Executive,72191,0 +43690,Male,49,Masters,10,88,64,49,68,9.0,1,92,Urban,ML Engineer,76542,1 +43691,Other,34,Bachelors,2,44,66,18,20,7.0,3,3,Urban,ML Engineer,22921,0 +43692,Female,44,Bachelors,15,28,7,97,79,1.0,4,2,Urban,HR Executive,54460,0 +43693,Male,34,Bachelors,10,40,42,16,3,7.0,1,6,Urban,Manager,39013,0 +43694,Male,53,Masters,7,59,60,11,32,1.0,1,28,Urban,Data Analyst,75964,0 +43695,Male,28,Diploma,9,13,92,93,79,5.0,2,59,Urban,Manager,103441,1 +43696,Male,47,Masters,0,1,93,57,62,8.0,4,79,Urban,Software Engineer,67390,0 +43697,Male,48,Diploma,9,7,23,13,39,0.0,1,58,Urban,Software Engineer,60637,0 +43698,Male,21,Masters,18,18,4,95,24,5.0,2,88,Urban,Manager,74338,0 +43699,Other,34,Bachelors,12,83,69,96,42,6.0,5,17,Urban,HR Executive,86263,1 +43700,Other,29,High School,12,45,57,93,26,8.0,7,55,Urban,Software Engineer,88124,1 +43701,Male,59,Diploma,15,6,58,63,35,3.0,6,98,Rural,Data Analyst,29174,0 +43702,Female,25,Bachelors,7,16,98,53,27,2.0,7,90,Urban,ML Engineer,129873,1 +43703,Male,28,Bachelors,8,5,61,96,55,3.0,5,50,Rural,HR Executive,20235,0 +43704,Female,39,High School,13,6,15,43,30,7.0,5,32,Semi-Urban,Data Analyst,128034,0 +43705,Male,27,Masters,14,65,4,27,53,9.0,7,75,Urban,ML Engineer,107723,0 +43706,Male,57,Masters,8,43,89,83,58,1.0,0,63,Semi-Urban,Data Analyst,91059,1 +43707,Male,46,Diploma,19,11,10,79,53,3.0,1,90,Urban,Manager,86032,0 +43708,Male,27,Bachelors,5,49,52,99,35,3.0,3,78,Urban,Manager,146843,1 +43709,Female,31,Masters,0,77,56,20,46,8.0,6,72,Urban,Data Analyst,46640,0 +43710,Other,56,High School,18,33,55,8,65,0.0,4,93,Urban,HR Executive,66002,0 +43711,Female,50,Masters,18,7,15,41,9,0.0,1,92,Urban,Software Engineer,81550,0 +43712,Female,44,Bachelors,17,20,11,55,24,6.0,0,57,Urban,ML Engineer,119627,0 +43713,Male,30,Bachelors,4,93,76,20,81,1.0,5,19,Semi-Urban,Software Engineer,80962,0 +43714,Male,43,Diploma,8,49,76,17,83,1.0,1,97,Urban,Software Engineer,58026,1 +43715,Female,56,Diploma,5,66,69,38,53,8.0,4,95,Urban,ML Engineer,106731,1 +43716,Male,44,Bachelors,3,95,37,34,58,5.0,0,16,Urban,Manager,108376,0 +43717,Male,45,Diploma,0,10,36,82,96,9.0,7,18,Rural,ML Engineer,102485,0 +43718,Female,21,Bachelors,11,19,4,53,20,2.0,5,67,Semi-Urban,HR Executive,123114,0 +43719,Male,41,Bachelors,3,44,33,26,92,3.0,3,77,Rural,ML Engineer,65110,0 +43720,Male,25,Diploma,5,85,70,49,69,4.0,2,28,Urban,Data Analyst,82241,0 +43721,Male,22,Bachelors,1,17,38,78,69,1.0,0,60,Urban,Manager,132020,0 +43722,Male,50,Bachelors,3,19,67,57,94,3.0,4,31,Urban,HR Executive,97948,0 +43723,Female,29,Diploma,16,97,6,77,62,1.0,1,80,Urban,Software Engineer,68407,1 +43724,Female,57,Diploma,17,52,81,28,83,7.0,6,18,Urban,Data Analyst,99890,0 +43725,Male,56,PhD,13,54,85,16,58,4.0,6,84,Semi-Urban,Manager,141735,1 +43726,Other,41,Masters,19,41,45,72,84,7.0,3,25,Rural,Data Analyst,93473,0 +43727,Female,54,Bachelors,19,4,50,73,66,9.0,6,34,Semi-Urban,ML Engineer,45135,0 +43728,Male,44,Diploma,1,60,39,16,70,4.0,4,91,Urban,Data Analyst,72089,0 +43729,Female,53,Bachelors,19,84,81,97,11,6.0,2,17,Urban,ML Engineer,78303,1 +43730,Male,21,Bachelors,14,47,1,4,29,5.0,0,24,Urban,Manager,86906,0 +43731,Female,28,Bachelors,9,89,1,52,34,2.0,4,31,Rural,Software Engineer,38621,0 +43732,Female,32,Bachelors,5,58,89,88,29,5.0,3,64,Semi-Urban,ML Engineer,104435,1 +43733,Male,22,Masters,11,24,16,35,37,5.0,4,24,Semi-Urban,ML Engineer,113102,0 +43734,Female,59,Bachelors,4,2,97,5,45,0.0,7,34,Urban,HR Executive,29524,0 +43735,Female,29,Diploma,7,70,10,37,16,3.0,3,66,Semi-Urban,Software Engineer,69797,0 +43736,Male,54,Bachelors,5,49,83,20,25,3.0,7,51,Urban,Data Analyst,111130,0 +43737,Male,26,PhD,7,88,88,79,1,0.0,0,59,Urban,Manager,53811,1 +43738,Male,21,Bachelors,19,51,80,15,21,5.0,1,49,Semi-Urban,Software Engineer,145172,0 +43739,Male,43,Diploma,19,12,62,59,53,9.0,2,96,Rural,HR Executive,37546,0 +43740,Male,55,Masters,7,44,19,72,1,1.0,3,56,Rural,Data Analyst,112680,0 +43741,Male,56,PhD,6,21,67,18,77,2.0,2,8,Urban,Software Engineer,131935,0 +43742,Male,58,Masters,17,87,56,83,90,6.0,5,41,Urban,Manager,56458,1 +43743,Male,37,Masters,1,24,72,46,14,6.0,7,70,Rural,Data Analyst,75772,0 +43744,Female,45,High School,10,85,27,72,59,1.0,4,81,Urban,HR Executive,111575,1 +43745,Other,23,Bachelors,16,62,30,15,20,0.0,1,91,Semi-Urban,HR Executive,97916,0 +43746,Female,43,Bachelors,10,21,91,25,3,9.0,7,45,Urban,Data Analyst,109788,0 +43747,Male,37,Bachelors,4,6,47,97,1,6.0,2,82,Semi-Urban,Manager,67726,0 +43748,Female,36,Bachelors,15,64,58,47,36,5.0,7,34,Rural,ML Engineer,109160,0 +43749,Female,51,Bachelors,0,71,36,15,61,1.0,1,33,Semi-Urban,ML Engineer,54185,0 +43750,Female,26,Masters,2,36,39,2,89,1.0,3,82,Rural,Manager,68097,0 +43751,Female,39,Bachelors,3,33,57,19,49,1.0,5,59,Urban,ML Engineer,52305,0 +43752,Female,38,Masters,0,28,47,56,55,2.0,2,15,Semi-Urban,Manager,116481,0 +43753,Male,54,High School,18,81,23,66,60,6.0,3,68,Semi-Urban,ML Engineer,53388,1 +43754,Male,54,Masters,14,52,99,46,27,3.0,1,18,Semi-Urban,Software Engineer,74871,0 +43755,Male,58,Bachelors,18,41,5,57,57,2.0,3,2,Urban,HR Executive,22695,0 +43756,Male,55,High School,19,33,96,2,45,9.0,6,7,Semi-Urban,Data Analyst,62980,0 +43757,Other,24,High School,15,29,38,61,22,0.0,6,0,Urban,Manager,52931,0 +43758,Male,45,Masters,17,53,47,71,69,1.0,0,0,Urban,HR Executive,51319,0 +43759,Other,42,Masters,14,6,69,21,2,0.0,5,55,Semi-Urban,Manager,147043,0 +43760,Female,37,Bachelors,19,58,43,8,36,0.0,2,0,Urban,HR Executive,128369,0 +43761,Male,47,High School,7,99,18,72,50,1.0,3,46,Urban,ML Engineer,108915,1 +43762,Male,33,Bachelors,4,96,39,42,70,4.0,6,58,Urban,HR Executive,53102,1 +43763,Male,31,High School,3,91,94,14,47,7.0,4,98,Semi-Urban,Manager,147316,1 +43764,Female,47,Bachelors,3,75,90,46,0,2.0,5,17,Rural,Manager,35318,0 +43765,Female,37,Masters,17,13,19,86,87,1.0,0,85,Urban,Manager,62784,0 +43766,Other,41,Diploma,14,84,67,20,88,6.0,4,80,Semi-Urban,HR Executive,143017,1 +43767,Male,51,Bachelors,7,30,42,37,17,2.0,2,57,Urban,HR Executive,147075,0 +43768,Male,32,Bachelors,8,83,92,76,45,1.0,3,16,Urban,Data Analyst,114346,1 +43769,Male,51,Bachelors,17,91,7,1,79,1.0,4,42,Rural,Software Engineer,109253,0 +43770,Male,55,PhD,16,82,66,27,63,1.0,5,30,Semi-Urban,ML Engineer,35615,0 +43771,Female,37,Bachelors,13,80,87,89,32,9.0,7,47,Rural,HR Executive,149534,1 +43772,Male,47,Masters,6,1,39,58,1,7.0,0,94,Semi-Urban,Software Engineer,96939,0 +43773,Male,27,High School,8,32,97,25,0,9.0,0,90,Rural,Manager,73879,1 +43774,Male,52,Masters,16,20,10,3,39,5.0,6,8,Semi-Urban,Software Engineer,100011,0 +43775,Male,26,Masters,18,50,5,18,32,7.0,7,96,Urban,Software Engineer,83211,0 +43776,Female,53,Bachelors,18,24,90,9,92,9.0,3,54,Semi-Urban,ML Engineer,99644,0 +43777,Male,56,Bachelors,12,60,4,99,71,3.0,2,41,Rural,Data Analyst,98253,0 +43778,Male,21,Bachelors,15,35,94,42,99,8.0,0,91,Urban,Software Engineer,46730,1 +43779,Female,38,Bachelors,8,31,53,89,98,3.0,3,15,Semi-Urban,Software Engineer,137110,0 +43780,Male,25,Bachelors,14,45,30,10,0,5.0,4,69,Rural,Software Engineer,105454,0 +43781,Female,49,Diploma,8,10,70,71,9,9.0,5,64,Urban,ML Engineer,142242,0 +43782,Other,33,Masters,3,82,34,68,54,2.0,0,26,Semi-Urban,Software Engineer,119419,0 +43783,Female,52,PhD,8,10,24,84,32,5.0,0,45,Semi-Urban,Data Analyst,139189,0 +43784,Male,34,Bachelors,17,51,57,64,73,5.0,5,66,Urban,ML Engineer,147592,1 +43785,Female,42,Masters,1,55,45,5,19,7.0,4,42,Urban,HR Executive,25711,0 +43786,Female,37,Masters,5,19,7,34,50,9.0,5,17,Rural,HR Executive,104102,0 +43787,Male,52,Diploma,8,94,65,44,4,5.0,4,39,Semi-Urban,ML Engineer,132549,1 +43788,Female,40,PhD,1,54,60,26,44,4.0,7,57,Semi-Urban,Data Analyst,86762,0 +43789,Male,29,Bachelors,16,39,71,34,30,7.0,5,11,Semi-Urban,Manager,128931,0 +43790,Female,21,Bachelors,10,91,98,13,72,3.0,4,88,Semi-Urban,ML Engineer,147881,1 +43791,Male,29,Diploma,11,3,37,85,98,2.0,7,54,Semi-Urban,Software Engineer,144681,0 +43792,Female,26,Bachelors,1,65,30,11,40,8.0,0,26,Semi-Urban,Data Analyst,29526,0 +43793,Male,34,Bachelors,15,77,79,39,89,2.0,7,98,Urban,HR Executive,77679,1 +43794,Male,33,Masters,10,27,24,29,36,2.0,2,20,Urban,Data Analyst,124468,0 +43795,Male,55,Diploma,14,50,43,51,55,6.0,2,9,Semi-Urban,ML Engineer,119984,0 +43796,Male,27,Bachelors,7,87,12,25,76,6.0,7,68,Urban,Manager,34656,0 +43797,Male,58,Masters,17,62,47,88,91,7.0,2,8,Urban,Software Engineer,135491,0 +43798,Male,29,Masters,5,22,46,7,81,3.0,0,13,Urban,HR Executive,101813,0 +43799,Male,54,Bachelors,2,91,19,43,18,4.0,2,61,Urban,Manager,60385,0 +43800,Male,21,Bachelors,10,91,3,30,7,0.0,6,47,Semi-Urban,Software Engineer,109403,0 +43801,Male,35,Bachelors,4,28,66,50,51,4.0,3,85,Rural,Manager,50224,0 +43802,Male,59,Masters,3,63,76,83,95,9.0,3,67,Urban,Data Analyst,96345,1 +43803,Male,22,Diploma,11,32,11,48,97,2.0,0,46,Rural,ML Engineer,74149,0 +43804,Male,31,High School,16,67,49,29,3,1.0,6,1,Urban,HR Executive,29154,0 +43805,Male,57,Bachelors,3,35,25,79,90,1.0,1,74,Rural,HR Executive,79312,0 +43806,Male,29,PhD,7,34,78,77,3,4.0,2,52,Semi-Urban,Data Analyst,130010,1 +43807,Male,30,Bachelors,6,31,1,11,82,9.0,4,49,Rural,Data Analyst,57015,0 +43808,Male,45,Diploma,18,89,81,78,76,7.0,5,92,Urban,ML Engineer,84859,1 +43809,Male,27,PhD,19,42,58,94,35,5.0,6,65,Urban,Software Engineer,148891,1 +43810,Male,27,Bachelors,11,4,8,35,83,2.0,4,3,Semi-Urban,Manager,95085,0 +43811,Male,53,Diploma,6,85,76,64,89,3.0,2,35,Urban,Data Analyst,35912,1 +43812,Male,42,Diploma,14,89,89,60,68,9.0,3,7,Semi-Urban,Software Engineer,77357,1 +43813,Male,33,Bachelors,0,77,77,9,19,9.0,4,32,Urban,ML Engineer,105752,0 +43814,Female,58,Bachelors,7,95,57,95,91,3.0,3,9,Urban,HR Executive,33406,1 +43815,Female,28,Bachelors,19,32,85,69,75,7.0,4,43,Urban,HR Executive,88718,0 +43816,Other,40,Bachelors,16,0,68,47,18,7.0,6,13,Urban,Software Engineer,76231,0 +43817,Male,35,Bachelors,5,16,52,66,59,7.0,6,21,Urban,HR Executive,146735,0 +43818,Male,47,Masters,1,67,74,92,50,3.0,4,49,Urban,Manager,67308,1 +43819,Female,34,Diploma,1,16,20,60,56,3.0,2,56,Rural,Software Engineer,25718,0 +43820,Male,21,Bachelors,3,19,40,88,22,0.0,2,18,Urban,Data Analyst,105398,0 +43821,Male,21,Diploma,19,10,15,71,42,6.0,6,81,Urban,Manager,86184,0 +43822,Male,25,Bachelors,6,79,79,65,95,5.0,5,87,Rural,Data Analyst,131722,1 +43823,Male,53,High School,18,71,12,77,3,4.0,3,23,Urban,Software Engineer,134713,0 +43824,Male,59,Bachelors,8,22,13,78,3,9.0,0,68,Urban,Manager,38477,0 +43825,Female,33,Bachelors,5,47,0,83,3,1.0,3,74,Rural,Software Engineer,97029,0 +43826,Other,47,Bachelors,15,10,9,31,12,3.0,5,14,Rural,HR Executive,146845,0 +43827,Male,46,Bachelors,2,81,40,52,47,9.0,2,18,Urban,Manager,149906,0 +43828,Female,42,Bachelors,13,66,94,48,14,3.0,7,92,Rural,Data Analyst,22993,1 +43829,Male,29,Bachelors,4,0,0,70,53,9.0,1,33,Semi-Urban,Manager,20858,0 +43830,Male,30,High School,7,39,43,83,89,3.0,3,44,Urban,ML Engineer,113883,0 +43831,Female,23,Diploma,4,91,46,75,15,7.0,5,57,Rural,ML Engineer,112279,1 +43832,Male,35,Bachelors,16,61,28,10,82,7.0,0,30,Rural,Data Analyst,50212,0 +43833,Male,59,Bachelors,14,58,70,76,18,0.0,0,54,Rural,Software Engineer,135689,1 +43834,Male,47,Masters,7,41,62,29,82,6.0,6,34,Urban,HR Executive,95188,0 +43835,Male,34,Diploma,8,17,5,62,80,8.0,2,32,Urban,Manager,75596,0 +43836,Male,22,High School,15,20,5,14,21,9.0,5,84,Urban,ML Engineer,29462,0 +43837,Female,25,Bachelors,5,83,85,38,92,1.0,6,50,Urban,Software Engineer,76879,1 +43838,Female,35,Bachelors,15,82,20,23,35,8.0,3,40,Semi-Urban,Software Engineer,75287,0 +43839,Male,58,Bachelors,4,96,71,29,41,6.0,3,54,Rural,HR Executive,144607,1 +43840,Male,24,Masters,16,64,79,36,74,7.0,4,89,Rural,Manager,27601,1 +43841,Female,36,Masters,4,64,69,9,16,8.0,3,65,Urban,Data Analyst,129430,0 +43842,Female,43,Bachelors,18,80,90,24,49,7.0,0,23,Rural,ML Engineer,143072,0 +43843,Male,52,Bachelors,11,88,76,37,35,7.0,3,49,Urban,Data Analyst,130644,1 +43844,Male,53,Masters,0,42,98,29,68,8.0,6,93,Urban,Manager,87556,1 +43845,Male,57,Bachelors,1,37,95,58,32,6.0,6,11,Urban,Manager,109789,0 +43846,Male,47,Bachelors,19,73,27,27,50,5.0,3,27,Urban,Manager,131589,0 +43847,Female,58,Bachelors,6,93,60,35,21,5.0,3,26,Urban,Software Engineer,103651,0 +43848,Male,50,High School,6,63,9,81,78,6.0,1,9,Semi-Urban,HR Executive,22197,0 +43849,Other,25,PhD,11,19,16,14,25,2.0,2,10,Urban,ML Engineer,141746,0 +43850,Male,31,Masters,11,27,46,48,27,7.0,4,83,Rural,HR Executive,145006,0 +43851,Male,27,Diploma,17,79,8,3,92,5.0,0,47,Urban,Software Engineer,25172,0 +43852,Male,49,Bachelors,19,35,82,6,38,1.0,3,1,Rural,Manager,80215,0 +43853,Male,21,Masters,4,92,77,88,39,9.0,4,65,Urban,Manager,73156,1 +43854,Male,40,Diploma,1,68,5,12,4,8.0,5,2,Semi-Urban,Software Engineer,99546,0 +43855,Male,42,PhD,17,77,47,89,11,6.0,5,88,Rural,HR Executive,103515,1 +43856,Other,23,Bachelors,17,67,97,21,2,7.0,6,68,Urban,ML Engineer,68845,1 +43857,Male,25,Masters,4,79,65,25,18,3.0,0,68,Urban,Data Analyst,89984,1 +43858,Male,47,Masters,7,35,96,45,6,7.0,0,35,Semi-Urban,Data Analyst,127310,0 +43859,Male,52,High School,15,27,7,27,72,2.0,1,47,Urban,HR Executive,25849,0 +43860,Male,59,High School,1,58,15,14,14,0.0,3,67,Urban,HR Executive,63870,0 +43861,Male,28,PhD,9,98,50,27,89,1.0,1,66,Urban,HR Executive,36263,1 +43862,Male,30,Bachelors,4,30,8,61,52,0.0,0,0,Urban,Data Analyst,125009,0 +43863,Male,39,Bachelors,17,61,2,65,72,9.0,6,51,Semi-Urban,Manager,69405,0 +43864,Female,57,Bachelors,4,38,67,68,76,3.0,1,26,Urban,Software Engineer,37428,0 +43865,Male,53,High School,16,90,15,46,64,4.0,2,12,Urban,Manager,82529,0 +43866,Female,58,Masters,16,64,71,93,65,4.0,5,70,Urban,HR Executive,74150,1 +43867,Male,27,Bachelors,13,52,63,70,31,1.0,7,13,Semi-Urban,Data Analyst,149771,0 +43868,Male,23,Bachelors,7,34,0,89,27,6.0,0,84,Urban,Software Engineer,141451,0 +43869,Male,28,High School,16,51,91,38,76,2.0,0,69,Urban,Data Analyst,68999,1 +43870,Male,30,Bachelors,8,39,93,52,82,8.0,2,86,Semi-Urban,Software Engineer,54154,1 +43871,Male,52,Diploma,3,70,33,72,15,4.0,1,58,Semi-Urban,HR Executive,90419,0 +43872,Male,53,High School,12,83,30,39,44,1.0,2,4,Semi-Urban,Software Engineer,79800,0 +43873,Other,42,Bachelors,14,96,78,15,53,3.0,6,12,Urban,Data Analyst,72847,0 +43874,Female,51,Masters,5,41,6,88,41,8.0,5,84,Semi-Urban,HR Executive,94574,0 +43875,Male,54,Bachelors,18,1,94,49,30,6.0,6,57,Urban,Data Analyst,109924,0 +43876,Male,40,Bachelors,14,96,43,92,56,9.0,2,18,Urban,Manager,35970,1 +43877,Male,33,PhD,13,65,2,75,53,9.0,1,92,Rural,ML Engineer,122103,0 +43878,Male,54,Bachelors,15,2,51,72,43,7.0,4,67,Urban,Manager,110267,0 +43879,Female,27,Masters,18,52,56,21,55,5.0,4,43,Semi-Urban,Manager,147820,0 +43880,Female,32,Bachelors,13,26,1,46,2,8.0,2,15,Rural,Software Engineer,79877,0 +43881,Male,54,High School,15,91,76,39,58,6.0,1,27,Urban,HR Executive,25730,0 +43882,Male,45,Masters,0,64,43,64,28,4.0,3,39,Urban,ML Engineer,107914,0 +43883,Male,23,Diploma,19,31,82,47,5,4.0,6,6,Urban,Software Engineer,107637,0 +43884,Female,22,Masters,11,60,46,97,75,6.0,5,25,Semi-Urban,Software Engineer,53547,0 +43885,Male,59,Bachelors,3,87,47,73,54,7.0,2,58,Semi-Urban,Data Analyst,70580,1 +43886,Other,54,Bachelors,19,94,1,0,3,9.0,5,73,Urban,HR Executive,143335,0 +43887,Female,39,High School,19,83,39,96,93,2.0,1,84,Urban,HR Executive,36860,1 +43888,Other,28,PhD,4,26,37,51,54,4.0,7,23,Urban,ML Engineer,121807,0 +43889,Male,49,Masters,7,29,58,41,97,0.0,2,7,Rural,HR Executive,49412,0 +43890,Male,32,Diploma,15,4,94,22,38,7.0,5,43,Rural,Data Analyst,123895,0 +43891,Female,32,Bachelors,15,7,58,82,51,0.0,0,73,Urban,Manager,32827,0 +43892,Female,48,Masters,19,98,77,91,91,2.0,3,93,Urban,Manager,120771,1 +43893,Male,44,Masters,8,94,30,87,51,6.0,1,53,Urban,HR Executive,46858,1 +43894,Other,31,Bachelors,14,15,84,70,39,7.0,6,68,Semi-Urban,ML Engineer,114448,0 +43895,Female,47,Masters,12,47,27,69,44,4.0,5,23,Urban,Manager,39705,0 +43896,Male,54,Bachelors,9,90,38,55,94,3.0,4,65,Semi-Urban,Software Engineer,21407,1 +43897,Male,24,Bachelors,11,34,75,20,35,9.0,2,20,Urban,HR Executive,143389,0 +43898,Male,50,High School,16,63,39,38,5,2.0,5,47,Semi-Urban,Manager,35825,0 +43899,Female,36,High School,7,86,65,24,27,7.0,3,40,Urban,Software Engineer,51395,0 +43900,Female,55,Diploma,4,60,44,32,58,8.0,7,76,Urban,Data Analyst,59343,0 +43901,Male,59,Bachelors,14,18,67,7,66,6.0,4,12,Semi-Urban,Data Analyst,112720,0 +43902,Male,30,Diploma,6,69,58,70,28,6.0,5,46,Urban,ML Engineer,90787,1 +43903,Male,40,PhD,17,49,85,78,55,9.0,1,79,Rural,HR Executive,106127,1 +43904,Male,26,Bachelors,1,74,33,48,62,3.0,5,11,Semi-Urban,Software Engineer,50520,0 +43905,Male,39,Bachelors,4,70,83,80,46,8.0,7,89,Semi-Urban,Manager,93240,1 +43906,Female,50,High School,10,98,84,95,48,4.0,0,49,Urban,Manager,82532,1 +43907,Female,38,Diploma,0,18,24,98,12,7.0,6,60,Semi-Urban,Software Engineer,27757,0 +43908,Male,41,Diploma,1,71,79,92,96,4.0,0,43,Urban,Software Engineer,123873,1 +43909,Female,48,Bachelors,16,67,31,47,67,2.0,5,60,Urban,ML Engineer,67648,0 +43910,Male,41,Masters,13,95,0,15,4,3.0,6,61,Urban,Manager,88665,0 +43911,Male,28,Bachelors,13,62,14,9,13,2.0,5,2,Rural,Software Engineer,71841,0 +43912,Female,33,Masters,14,80,53,16,80,6.0,6,33,Urban,ML Engineer,133325,0 +43913,Male,31,Bachelors,18,11,74,44,19,9.0,0,95,Semi-Urban,Data Analyst,88914,0 +43914,Male,38,Masters,0,38,89,50,87,1.0,7,99,Urban,Data Analyst,148545,1 +43915,Male,21,Diploma,1,76,21,8,48,7.0,3,10,Urban,Data Analyst,121201,0 +43916,Male,37,Bachelors,0,2,59,52,63,2.0,7,34,Rural,Software Engineer,141890,0 +43917,Female,43,Masters,0,57,98,59,41,3.0,1,23,Urban,ML Engineer,85502,0 +43918,Male,30,Diploma,2,40,63,27,73,3.0,1,17,Urban,HR Executive,112886,0 +43919,Male,49,Diploma,5,34,69,30,45,1.0,3,35,Urban,ML Engineer,35691,0 +43920,Female,31,Masters,12,30,74,9,61,8.0,4,51,Urban,HR Executive,25231,0 +43921,Male,31,High School,12,13,0,53,41,8.0,0,3,Rural,ML Engineer,99816,0 +43922,Male,24,Bachelors,8,63,45,10,18,6.0,7,84,Semi-Urban,Manager,90367,0 +43923,Male,35,Diploma,6,26,75,97,68,8.0,4,27,Rural,Data Analyst,148487,0 +43924,Female,27,Masters,18,41,31,45,24,2.0,6,73,Urban,ML Engineer,137293,0 +43925,Female,24,Bachelors,9,15,70,36,71,9.0,2,50,Semi-Urban,HR Executive,38621,0 +43926,Male,50,Masters,2,94,2,1,6,7.0,6,99,Urban,Software Engineer,45208,0 +43927,Female,58,Diploma,9,43,22,26,77,7.0,4,27,Urban,Manager,129823,0 +43928,Male,46,Masters,6,73,85,62,94,2.0,1,11,Urban,ML Engineer,78638,0 +43929,Male,23,High School,11,88,61,97,15,8.0,1,26,Rural,ML Engineer,139232,1 +43930,Female,58,Diploma,6,53,66,71,47,9.0,7,45,Urban,Manager,42506,0 +43931,Male,54,Diploma,14,89,66,1,20,4.0,6,89,Urban,HR Executive,29801,1 +43932,Female,50,Masters,1,81,8,53,50,9.0,2,13,Semi-Urban,HR Executive,69280,0 +43933,Male,58,Bachelors,18,44,16,13,59,2.0,4,3,Rural,Manager,66181,0 +43934,Male,31,Bachelors,6,25,8,18,38,4.0,7,76,Urban,Manager,120816,0 +43935,Male,28,Diploma,10,61,71,17,12,5.0,3,72,Urban,Software Engineer,24271,0 +43936,Male,51,High School,1,96,90,22,50,5.0,3,98,Urban,Manager,90954,1 +43937,Male,28,Masters,9,79,58,92,19,6.0,6,31,Semi-Urban,Manager,74199,1 +43938,Male,57,Bachelors,17,86,92,46,9,3.0,1,50,Urban,Manager,33428,1 +43939,Female,25,Masters,0,51,53,28,32,1.0,1,46,Semi-Urban,ML Engineer,129679,0 +43940,Male,56,PhD,0,59,85,23,23,7.0,4,35,Urban,ML Engineer,109115,0 +43941,Male,30,Diploma,8,74,80,34,11,9.0,1,45,Urban,Software Engineer,37802,0 +43942,Male,28,PhD,10,16,38,46,12,6.0,1,11,Rural,Software Engineer,100859,0 +43943,Male,45,Bachelors,3,55,99,32,77,4.0,6,88,Semi-Urban,HR Executive,95419,1 +43944,Female,37,High School,12,43,79,98,78,7.0,6,38,Urban,Manager,104401,1 +43945,Male,41,High School,18,44,20,45,45,2.0,5,20,Urban,Data Analyst,58143,0 +43946,Female,49,Bachelors,16,95,62,99,19,9.0,6,4,Urban,Data Analyst,136482,1 +43947,Female,39,High School,4,99,12,71,44,8.0,5,30,Urban,Data Analyst,105171,0 +43948,Male,40,Bachelors,0,79,54,6,88,7.0,5,56,Urban,HR Executive,106267,0 +43949,Female,38,Bachelors,19,18,91,80,62,8.0,3,6,Urban,Manager,24766,0 +43950,Female,21,Masters,19,46,33,20,23,9.0,2,95,Semi-Urban,Software Engineer,137323,0 +43951,Female,37,Diploma,0,52,50,11,78,8.0,5,88,Urban,HR Executive,138020,0 +43952,Male,33,PhD,17,12,98,96,81,3.0,6,10,Semi-Urban,ML Engineer,97512,0 +43953,Male,56,Masters,14,94,42,21,22,8.0,7,5,Urban,Software Engineer,74139,0 +43954,Male,33,Bachelors,10,65,40,77,22,7.0,6,88,Semi-Urban,Software Engineer,65790,1 +43955,Male,56,Masters,15,27,38,9,1,2.0,1,38,Urban,Manager,124573,0 +43956,Female,40,High School,2,9,20,22,16,0.0,3,85,Semi-Urban,Data Analyst,54324,0 +43957,Female,55,Masters,15,29,45,56,36,4.0,6,23,Urban,Software Engineer,114717,0 +43958,Female,23,Masters,12,60,53,23,11,7.0,1,26,Rural,HR Executive,136563,0 +43959,Female,47,Diploma,15,92,81,80,97,1.0,0,98,Urban,Software Engineer,29308,1 +43960,Other,35,Bachelors,2,28,32,14,20,6.0,3,49,Semi-Urban,ML Engineer,72548,0 +43961,Male,48,Bachelors,6,31,62,44,21,7.0,6,0,Urban,ML Engineer,59929,0 +43962,Female,41,Diploma,6,47,91,85,78,0.0,7,47,Semi-Urban,Data Analyst,59250,1 +43963,Male,52,Bachelors,18,36,65,70,44,4.0,6,33,Rural,Manager,22420,0 +43964,Male,26,Bachelors,17,50,52,91,31,4.0,2,1,Urban,ML Engineer,120609,0 +43965,Other,38,Bachelors,5,47,17,66,52,0.0,2,60,Urban,Data Analyst,66071,0 +43966,Female,21,Bachelors,5,29,57,21,73,3.0,3,44,Urban,ML Engineer,74911,0 +43967,Female,44,Diploma,9,97,24,20,68,5.0,5,3,Urban,HR Executive,72413,0 +43968,Male,43,Bachelors,4,24,77,99,92,0.0,6,36,Urban,ML Engineer,126189,1 +43969,Female,41,Bachelors,17,34,8,27,40,8.0,0,52,Semi-Urban,Software Engineer,96725,0 +43970,Male,44,Masters,18,23,29,84,73,1.0,1,33,Urban,ML Engineer,43332,0 +43971,Male,37,Bachelors,13,71,75,55,88,9.0,1,50,Urban,Software Engineer,81507,1 +43972,Male,33,Bachelors,1,50,4,15,65,0.0,3,3,Urban,Manager,117094,0 +43973,Male,48,Bachelors,19,79,52,59,23,0.0,1,6,Urban,Software Engineer,107000,0 +43974,Male,54,Bachelors,7,87,82,55,22,1.0,1,10,Semi-Urban,ML Engineer,93913,0 +43975,Female,45,Diploma,9,47,69,31,20,4.0,7,42,Semi-Urban,Data Analyst,146692,0 +43976,Male,55,Diploma,0,73,69,46,41,6.0,3,74,Rural,HR Executive,69413,1 +43977,Female,56,Masters,8,65,82,25,96,1.0,1,46,Semi-Urban,HR Executive,143381,0 +43978,Male,38,Bachelors,12,47,71,40,7,5.0,0,41,Semi-Urban,Data Analyst,51689,0 +43979,Male,51,Diploma,8,62,29,84,57,1.0,4,1,Semi-Urban,ML Engineer,80871,0 +43980,Male,35,Masters,1,8,89,73,12,4.0,0,71,Urban,Data Analyst,127653,1 +43981,Female,41,PhD,2,99,54,28,40,5.0,3,1,Urban,Manager,108953,0 +43982,Female,55,Masters,11,10,35,58,99,2.0,6,57,Semi-Urban,Software Engineer,51520,0 +43983,Male,53,Bachelors,11,5,85,72,11,2.0,7,47,Semi-Urban,Manager,129681,0 +43984,Male,45,Masters,8,26,57,7,22,8.0,4,32,Urban,ML Engineer,133210,0 +43985,Female,26,Masters,6,39,63,49,46,1.0,1,27,Urban,Software Engineer,28439,0 +43986,Male,35,Bachelors,0,76,55,3,36,5.0,4,67,Urban,HR Executive,89681,0 +43987,Male,35,Masters,1,89,83,36,46,9.0,3,23,Urban,ML Engineer,90194,0 +43988,Male,27,Masters,4,77,61,42,76,3.0,7,73,Urban,Manager,92440,1 +43989,Male,24,Bachelors,1,10,69,11,34,5.0,6,29,Semi-Urban,Software Engineer,122421,0 +43990,Male,58,Masters,13,59,22,12,98,6.0,6,69,Semi-Urban,ML Engineer,35036,0 +43991,Male,26,Diploma,9,64,8,92,95,8.0,7,45,Urban,Software Engineer,148135,0 +43992,Male,47,Diploma,11,12,81,74,37,6.0,2,55,Urban,ML Engineer,32251,0 +43993,Male,26,High School,8,87,14,48,58,8.0,3,2,Rural,ML Engineer,118193,0 +43994,Male,42,Masters,6,49,78,23,39,6.0,4,39,Rural,Software Engineer,45387,0 +43995,Female,38,Bachelors,9,88,5,40,52,4.0,1,95,Rural,Manager,45353,0 +43996,Male,45,Diploma,17,96,42,13,86,8.0,7,26,Urban,Data Analyst,49813,0 +43997,Male,21,High School,12,74,61,95,94,4.0,6,47,Urban,HR Executive,52559,1 +43998,Male,33,Masters,0,5,23,96,89,0.0,6,5,Urban,ML Engineer,44853,0 +43999,Male,39,Bachelors,6,36,53,28,82,0.0,2,41,Urban,Manager,43441,0 +44000,Female,22,Diploma,11,72,45,72,60,1.0,4,64,Urban,Manager,28808,1 +44001,Male,52,High School,2,18,25,16,88,2.0,0,17,Semi-Urban,Software Engineer,145206,0 +44002,Female,53,High School,13,7,24,77,38,0.0,5,91,Rural,HR Executive,136970,0 +44003,Female,25,Bachelors,3,59,66,92,76,2.0,6,9,Semi-Urban,ML Engineer,134644,0 +44004,Female,55,Bachelors,15,89,26,92,78,5.0,1,14,Urban,HR Executive,77158,0 +44005,Male,38,Masters,10,60,63,88,29,5.0,1,70,Rural,Data Analyst,107471,1 +44006,Male,40,Bachelors,11,88,37,25,81,5.0,2,32,Rural,Manager,29880,0 +44007,Male,33,Diploma,9,41,49,57,7,2.0,3,44,Urban,HR Executive,93068,0 +44008,Female,30,Diploma,14,38,41,20,88,0.0,6,12,Urban,Software Engineer,126682,0 +44009,Male,37,Bachelors,0,15,96,91,87,6.0,5,28,Urban,Software Engineer,123574,0 +44010,Female,24,Bachelors,3,8,53,15,88,2.0,6,69,Rural,ML Engineer,106083,0 +44011,Male,43,Bachelors,10,74,22,47,22,4.0,5,43,Urban,Software Engineer,118248,0 +44012,Male,41,Bachelors,2,48,30,10,94,1.0,6,20,Urban,ML Engineer,109225,0 +44013,Male,21,Bachelors,19,13,4,36,22,7.0,3,57,Semi-Urban,Software Engineer,149184,0 +44014,Male,55,Diploma,9,30,32,94,57,1.0,6,94,Urban,Data Analyst,114262,1 +44015,Male,26,Diploma,7,33,91,52,73,9.0,6,6,Urban,Manager,28521,0 +44016,Male,41,Masters,17,51,63,67,97,6.0,1,1,Urban,Software Engineer,34208,0 +44017,Male,39,Masters,15,21,35,27,88,0.0,7,19,Urban,Data Analyst,58672,0 +44018,Female,57,Bachelors,11,46,80,61,33,2.0,1,68,Urban,Data Analyst,146237,1 +44019,Male,40,Masters,5,95,89,93,55,3.0,1,29,Semi-Urban,Data Analyst,144264,1 +44020,Male,31,Bachelors,3,12,98,90,25,1.0,1,0,Semi-Urban,ML Engineer,137086,0 +44021,Male,26,Masters,19,94,34,5,76,7.0,4,35,Urban,Data Analyst,100413,0 +44022,Female,38,Bachelors,2,30,20,96,9,3.0,7,64,Semi-Urban,Data Analyst,127907,0 +44023,Male,50,Bachelors,1,11,46,20,35,7.0,0,84,Urban,Software Engineer,141916,0 +44024,Other,39,High School,4,52,42,22,6,9.0,1,67,Semi-Urban,Software Engineer,139643,0 +44025,Male,50,Bachelors,0,31,51,42,2,6.0,6,41,Urban,Manager,124311,0 +44026,Other,37,Bachelors,2,46,46,64,6,2.0,7,72,Semi-Urban,Data Analyst,85155,0 +44027,Male,58,High School,3,29,19,55,73,8.0,7,15,Urban,Data Analyst,112941,0 +44028,Male,26,High School,17,67,71,19,89,0.0,2,94,Urban,Manager,77286,1 +44029,Female,38,Bachelors,17,90,45,17,4,4.0,4,9,Urban,Manager,46527,0 +44030,Other,34,Diploma,19,33,96,49,87,7.0,3,82,Semi-Urban,HR Executive,119159,1 +44031,Female,58,Bachelors,0,25,72,75,90,2.0,3,58,Urban,Software Engineer,28164,0 +44032,Male,25,Bachelors,6,13,76,69,23,1.0,7,11,Urban,ML Engineer,79231,0 +44033,Male,24,High School,14,79,66,37,60,1.0,0,54,Urban,HR Executive,132499,1 +44034,Male,29,High School,16,58,24,54,35,0.0,1,41,Urban,HR Executive,138318,0 +44035,Male,55,Masters,9,3,34,19,67,3.0,2,92,Urban,HR Executive,72767,0 +44036,Male,22,Bachelors,19,63,10,20,49,2.0,7,26,Urban,Manager,106759,0 +44037,Male,28,Bachelors,1,68,75,81,99,5.0,3,1,Urban,Data Analyst,55358,0 +44038,Male,48,Diploma,6,55,4,94,14,3.0,4,28,Urban,Software Engineer,96784,0 +44039,Female,37,Masters,18,9,63,11,4,9.0,3,35,Semi-Urban,HR Executive,117797,0 +44040,Male,28,Bachelors,6,19,89,18,44,2.0,6,91,Urban,HR Executive,111762,0 +44041,Male,48,Bachelors,9,66,33,88,45,1.0,6,1,Semi-Urban,Manager,132384,0 +44042,Male,50,Bachelors,13,21,65,38,10,3.0,3,45,Urban,Software Engineer,32267,0 +44043,Male,29,Diploma,2,41,82,60,41,6.0,5,18,Urban,Manager,84334,0 +44044,Male,39,High School,12,31,50,8,40,6.0,2,31,Urban,Software Engineer,86754,0 +44045,Male,31,High School,18,7,78,48,11,2.0,7,12,Urban,HR Executive,113943,0 +44046,Female,37,Masters,17,55,70,78,37,7.0,5,89,Urban,Manager,28593,1 +44047,Male,52,Bachelors,19,52,9,47,46,3.0,7,85,Rural,Data Analyst,28397,0 +44048,Male,32,Diploma,17,66,88,92,45,2.0,1,36,Urban,Manager,139026,1 +44049,Male,54,Bachelors,2,98,47,64,97,8.0,3,73,Urban,Software Engineer,21609,1 +44050,Male,33,Diploma,17,81,53,43,23,2.0,1,30,Semi-Urban,Manager,62148,0 +44051,Male,24,Masters,18,52,57,60,20,4.0,6,32,Urban,Manager,109896,0 +44052,Male,29,Diploma,19,6,8,32,31,0.0,0,10,Semi-Urban,ML Engineer,105494,0 +44053,Male,39,Diploma,4,67,24,52,97,9.0,0,59,Urban,Data Analyst,38434,0 +44054,Female,57,Bachelors,8,26,11,50,88,6.0,0,54,Urban,HR Executive,36251,0 +44055,Female,24,Diploma,5,5,71,29,47,0.0,0,69,Urban,Software Engineer,126020,0 +44056,Male,29,Masters,5,74,94,40,38,4.0,2,29,Urban,Software Engineer,67437,1 +44057,Female,24,Bachelors,4,70,41,87,3,5.0,4,26,Urban,Data Analyst,70402,0 +44058,Male,40,Masters,7,99,30,87,99,1.0,4,64,Semi-Urban,Manager,127471,1 +44059,Male,50,High School,9,81,83,15,19,3.0,6,84,Rural,Software Engineer,51378,1 +44060,Male,38,Bachelors,9,33,75,39,37,8.0,7,40,Urban,ML Engineer,103737,0 +44061,Male,50,High School,18,63,80,97,56,1.0,3,88,Semi-Urban,Manager,50328,1 +44062,Male,29,High School,0,30,30,20,81,4.0,1,44,Semi-Urban,Data Analyst,38294,0 +44063,Female,51,High School,5,88,91,27,53,2.0,0,22,Urban,ML Engineer,148655,0 +44064,Female,52,Masters,1,27,29,51,68,5.0,5,58,Urban,Software Engineer,122415,0 +44065,Female,44,Masters,12,4,21,85,39,2.0,5,88,Urban,Manager,66479,0 +44066,Male,29,Bachelors,18,90,30,17,40,9.0,0,23,Urban,ML Engineer,77088,0 +44067,Male,32,Masters,16,65,62,36,95,1.0,3,98,Urban,Software Engineer,70276,1 +44068,Male,22,Bachelors,1,90,7,53,40,2.0,7,35,Urban,Software Engineer,101439,0 +44069,Female,28,Bachelors,7,76,98,18,17,3.0,7,87,Rural,ML Engineer,93674,1 +44070,Female,42,Masters,3,13,6,63,28,6.0,1,21,Semi-Urban,HR Executive,61940,0 +44071,Female,45,High School,3,32,39,95,40,1.0,2,0,Rural,Manager,146062,0 +44072,Male,31,Bachelors,6,62,78,10,76,1.0,0,57,Urban,Manager,149134,0 +44073,Male,48,Bachelors,17,45,8,58,54,3.0,0,48,Rural,ML Engineer,69080,0 +44074,Male,57,Bachelors,16,34,9,32,42,1.0,4,55,Rural,HR Executive,77807,0 +44075,Female,37,Masters,3,63,28,16,72,3.0,3,50,Urban,ML Engineer,129347,0 +44076,Female,34,Bachelors,0,72,24,39,46,2.0,6,40,Urban,Software Engineer,148285,0 +44077,Male,53,Diploma,6,43,78,1,94,5.0,0,75,Rural,Data Analyst,48347,0 +44078,Male,41,Diploma,19,34,0,78,14,5.0,7,43,Urban,Manager,56246,0 +44079,Female,25,Diploma,19,28,36,84,99,7.0,1,74,Semi-Urban,Software Engineer,118328,0 +44080,Male,58,Bachelors,4,31,21,24,39,1.0,0,77,Semi-Urban,Manager,112611,0 +44081,Female,53,Bachelors,18,54,11,58,82,1.0,6,51,Rural,Manager,83097,0 +44082,Male,52,Diploma,0,81,98,7,56,0.0,5,97,Rural,ML Engineer,119259,1 +44083,Male,38,Bachelors,10,48,62,1,85,8.0,2,11,Urban,HR Executive,24729,0 +44084,Female,41,Bachelors,11,70,66,36,55,9.0,3,67,Urban,Manager,120790,0 +44085,Female,32,Diploma,8,72,35,22,18,4.0,6,24,Semi-Urban,Manager,22782,0 +44086,Male,55,High School,2,32,42,5,6,9.0,0,84,Urban,HR Executive,133166,0 +44087,Female,45,Masters,9,74,38,58,22,1.0,3,15,Urban,Manager,38719,0 +44088,Other,43,High School,10,27,63,22,63,3.0,5,54,Rural,HR Executive,108624,0 +44089,Male,28,Diploma,17,91,47,84,51,7.0,4,85,Semi-Urban,Software Engineer,94513,1 +44090,Male,50,Bachelors,16,90,62,81,22,2.0,6,85,Urban,Software Engineer,68700,1 +44091,Male,56,Bachelors,19,82,60,84,61,7.0,4,39,Rural,Data Analyst,29345,1 +44092,Male,45,Diploma,2,33,34,70,72,4.0,1,85,Urban,Data Analyst,80629,0 +44093,Female,25,Diploma,4,50,86,64,86,7.0,6,12,Urban,ML Engineer,114012,0 +44094,Male,53,High School,2,89,97,29,86,8.0,5,49,Semi-Urban,HR Executive,105479,1 +44095,Male,58,High School,4,5,42,31,73,3.0,0,74,Urban,ML Engineer,101017,0 +44096,Female,53,High School,2,39,48,69,27,8.0,3,23,Semi-Urban,Software Engineer,23093,0 +44097,Male,50,Bachelors,9,5,62,27,51,4.0,6,38,Rural,Data Analyst,134063,0 +44098,Female,33,High School,10,44,76,33,52,1.0,6,2,Urban,ML Engineer,115388,0 +44099,Male,33,Bachelors,10,93,29,50,88,1.0,6,90,Semi-Urban,Data Analyst,65109,1 +44100,Other,26,Masters,12,12,74,83,58,4.0,7,90,Urban,Manager,145264,1 +44101,Female,43,Bachelors,1,20,73,40,17,0.0,5,92,Semi-Urban,Manager,32557,0 +44102,Female,49,High School,3,93,48,50,32,7.0,7,26,Urban,ML Engineer,105518,0 +44103,Other,36,Masters,0,13,43,52,78,0.0,1,22,Urban,Data Analyst,73384,0 +44104,Male,39,Bachelors,8,4,88,1,33,7.0,6,2,Rural,HR Executive,99220,0 +44105,Male,23,High School,14,50,40,28,62,0.0,1,57,Rural,Software Engineer,38436,0 +44106,Female,56,High School,2,51,67,7,62,8.0,2,45,Urban,HR Executive,94143,0 +44107,Female,28,Diploma,13,26,34,65,41,7.0,5,9,Urban,Software Engineer,43536,0 +44108,Male,51,High School,9,46,21,83,56,6.0,0,98,Urban,Manager,143021,1 +44109,Female,22,Bachelors,8,25,45,27,48,2.0,6,27,Rural,Software Engineer,56233,0 +44110,Male,31,Diploma,19,61,85,19,83,4.0,4,53,Urban,Data Analyst,105814,0 +44111,Female,36,Masters,7,60,52,46,67,7.0,1,30,Urban,HR Executive,86728,0 +44112,Male,45,Diploma,18,62,78,9,50,1.0,1,72,Rural,Data Analyst,52329,0 +44113,Male,58,High School,2,8,0,73,21,2.0,7,44,Urban,ML Engineer,86782,0 +44114,Male,42,Bachelors,11,48,75,81,94,8.0,7,26,Urban,ML Engineer,62500,0 +44115,Male,23,Bachelors,14,35,67,54,73,7.0,7,54,Rural,HR Executive,42284,0 +44116,Male,26,Bachelors,16,22,83,53,11,5.0,4,0,Urban,Manager,47129,0 +44117,Male,32,High School,1,88,58,99,24,1.0,4,20,Rural,Software Engineer,111453,1 +44118,Male,45,Masters,8,12,86,30,90,8.0,1,50,Rural,HR Executive,113824,0 +44119,Female,59,Masters,5,11,62,52,36,8.0,4,99,Urban,HR Executive,26812,0 +44120,Male,35,PhD,8,44,31,95,83,8.0,0,19,Urban,Data Analyst,141551,0 +44121,Male,46,Bachelors,14,54,57,29,5,8.0,0,16,Semi-Urban,ML Engineer,129352,0 +44122,Female,33,PhD,16,73,35,89,33,1.0,1,97,Rural,Manager,112850,1 +44123,Female,50,Diploma,0,43,46,46,17,9.0,2,70,Rural,ML Engineer,46353,0 +44124,Male,28,Masters,12,85,95,78,81,7.0,4,22,Rural,HR Executive,59411,1 +44125,Female,34,Bachelors,1,38,69,31,16,0.0,5,27,Urban,Software Engineer,37831,0 +44126,Other,25,Diploma,2,50,85,33,65,2.0,4,13,Rural,Software Engineer,123450,0 +44127,Female,53,Bachelors,12,17,97,97,41,9.0,2,71,Urban,ML Engineer,144318,1 +44128,Female,57,Bachelors,13,12,8,1,34,7.0,3,22,Urban,Manager,83145,0 +44129,Female,35,Masters,14,83,86,85,88,2.0,0,62,Semi-Urban,Data Analyst,139761,1 +44130,Male,53,PhD,2,94,92,85,10,6.0,3,26,Urban,Software Engineer,35760,1 +44131,Female,29,Bachelors,18,71,11,27,30,9.0,0,10,Urban,Software Engineer,93408,0 +44132,Female,28,Bachelors,9,30,43,71,54,4.0,0,27,Urban,Software Engineer,127585,0 +44133,Male,34,Diploma,11,1,99,31,73,8.0,0,60,Urban,ML Engineer,51444,0 +44134,Male,48,Diploma,10,50,2,58,5,5.0,2,95,Urban,HR Executive,104275,0 +44135,Male,52,Bachelors,8,72,15,28,3,6.0,1,77,Urban,Data Analyst,129769,0 +44136,Female,41,Masters,12,50,21,78,35,6.0,5,9,Rural,Software Engineer,147691,0 +44137,Male,43,Bachelors,16,61,57,93,46,3.0,3,52,Urban,Manager,59461,1 +44138,Male,43,High School,11,1,3,68,83,6.0,1,91,Urban,Software Engineer,82275,0 +44139,Female,41,Bachelors,3,4,8,69,13,4.0,3,69,Urban,Software Engineer,93398,0 +44140,Male,56,Diploma,17,27,3,71,77,9.0,5,96,Semi-Urban,ML Engineer,47721,0 +44141,Other,24,Diploma,14,28,20,84,53,9.0,1,27,Rural,Software Engineer,76112,0 +44142,Male,36,Bachelors,12,66,39,52,15,9.0,4,62,Semi-Urban,Software Engineer,55402,0 +44143,Male,46,Bachelors,1,20,80,58,55,4.0,6,94,Urban,ML Engineer,138184,1 +44144,Male,55,PhD,5,7,62,64,48,8.0,4,30,Urban,HR Executive,36085,0 +44145,Male,41,Bachelors,6,95,90,12,4,7.0,6,45,Semi-Urban,Manager,147195,1 +44146,Male,30,Bachelors,10,42,61,0,0,8.0,4,37,Rural,HR Executive,89697,0 +44147,Female,22,High School,17,67,66,42,10,2.0,2,76,Semi-Urban,ML Engineer,68256,1 +44148,Female,33,High School,3,64,81,13,71,9.0,0,76,Urban,Data Analyst,88848,0 +44149,Female,55,Bachelors,0,2,50,59,4,9.0,6,94,Urban,HR Executive,95464,0 +44150,Male,44,Masters,3,11,26,95,36,0.0,3,67,Rural,Software Engineer,46094,0 +44151,Male,48,PhD,9,47,67,44,5,1.0,7,72,Urban,Manager,129473,0 +44152,Male,58,Masters,7,73,90,4,79,0.0,6,93,Rural,Software Engineer,97436,1 +44153,Male,54,Bachelors,8,40,73,64,3,1.0,3,97,Semi-Urban,ML Engineer,104395,1 +44154,Female,40,PhD,8,89,28,16,73,3.0,1,92,Urban,Manager,86760,0 +44155,Male,58,Bachelors,15,50,85,74,99,9.0,3,5,Urban,Data Analyst,88339,0 +44156,Female,51,Diploma,13,73,34,74,44,6.0,0,11,Rural,Software Engineer,63951,0 +44157,Female,35,Masters,13,22,53,80,5,7.0,4,27,Urban,ML Engineer,65331,0 +44158,Female,59,PhD,12,30,29,70,19,9.0,2,16,Rural,Software Engineer,33380,0 +44159,Female,43,Bachelors,6,51,74,27,78,1.0,2,64,Rural,HR Executive,141350,0 +44160,Male,24,High School,18,85,68,57,59,4.0,7,67,Rural,Data Analyst,137153,1 +44161,Female,35,Masters,6,74,97,10,10,3.0,1,10,Semi-Urban,ML Engineer,20941,0 +44162,Male,51,Bachelors,4,57,96,54,58,9.0,6,15,Semi-Urban,Manager,72407,0 +44163,Male,36,Masters,10,91,61,66,67,2.0,3,75,Urban,Manager,113107,1 +44164,Male,22,Masters,11,23,8,15,5,7.0,1,82,Urban,Software Engineer,128991,0 +44165,Male,38,Bachelors,3,56,37,83,59,9.0,6,96,Semi-Urban,HR Executive,118570,1 +44166,Male,22,Diploma,17,88,41,18,82,2.0,3,8,Semi-Urban,Manager,142140,0 +44167,Male,22,Bachelors,4,11,37,18,85,6.0,6,8,Urban,Data Analyst,32786,0 +44168,Male,53,Masters,17,5,74,19,8,9.0,4,94,Urban,Software Engineer,99153,0 +44169,Female,52,Bachelors,2,27,10,56,71,0.0,2,67,Urban,Software Engineer,84630,0 +44170,Male,28,High School,3,92,79,42,10,5.0,5,23,Semi-Urban,Manager,53978,1 +44171,Male,32,Bachelors,12,40,79,97,46,2.0,3,41,Urban,ML Engineer,111347,1 +44172,Male,44,Bachelors,18,26,84,30,36,0.0,3,92,Semi-Urban,Software Engineer,110397,0 +44173,Female,39,Diploma,18,98,56,20,40,6.0,4,50,Urban,ML Engineer,35821,0 +44174,Male,28,Diploma,12,85,30,91,7,1.0,6,60,Rural,Data Analyst,144679,1 +44175,Male,49,High School,13,15,6,48,94,5.0,2,23,Urban,Software Engineer,141822,0 +44176,Male,42,Bachelors,0,5,12,36,25,1.0,1,89,Semi-Urban,Data Analyst,24459,0 +44177,Female,24,Bachelors,9,4,86,93,69,7.0,3,60,Urban,Manager,136560,1 +44178,Male,34,High School,15,20,0,25,62,5.0,5,23,Semi-Urban,Software Engineer,103526,0 +44179,Male,30,Masters,19,32,13,8,40,4.0,2,10,Urban,Manager,20483,0 +44180,Male,42,Masters,6,35,0,28,38,1.0,3,2,Semi-Urban,ML Engineer,136140,0 +44181,Female,35,High School,0,37,62,34,96,5.0,1,6,Semi-Urban,Software Engineer,90579,0 +44182,Male,29,Bachelors,4,85,22,48,88,1.0,7,94,Rural,Software Engineer,88856,1 +44183,Female,26,Bachelors,2,60,18,6,26,3.0,3,76,Urban,Data Analyst,122828,0 +44184,Male,58,Bachelors,16,44,0,35,49,8.0,4,84,Urban,HR Executive,27704,0 +44185,Male,57,Bachelors,16,6,44,4,63,0.0,3,55,Rural,Manager,76959,0 +44186,Male,27,Masters,2,76,73,46,43,8.0,7,75,Rural,Software Engineer,85939,1 +44187,Female,40,Diploma,6,55,46,6,20,2.0,3,94,Urban,ML Engineer,137841,0 +44188,Male,27,Bachelors,10,50,70,51,96,7.0,0,70,Semi-Urban,ML Engineer,132607,1 +44189,Male,25,Diploma,14,8,40,68,9,5.0,2,0,Urban,Software Engineer,62284,0 +44190,Female,37,Masters,6,56,26,66,84,9.0,2,48,Urban,Software Engineer,55106,0 +44191,Male,53,Bachelors,12,24,67,4,23,2.0,0,67,Semi-Urban,Data Analyst,148020,0 +44192,Male,48,Bachelors,16,28,89,46,23,6.0,2,3,Urban,ML Engineer,124615,0 +44193,Male,33,Bachelors,15,26,92,29,12,0.0,6,70,Semi-Urban,HR Executive,149433,0 +44194,Female,38,Masters,17,91,12,55,1,6.0,0,26,Urban,HR Executive,56288,0 +44195,Female,33,High School,8,54,21,32,24,2.0,3,84,Rural,ML Engineer,93576,0 +44196,Female,47,Masters,8,70,30,30,0,3.0,5,20,Urban,Data Analyst,26901,0 +44197,Male,41,High School,0,18,65,37,46,7.0,5,43,Rural,Data Analyst,95575,0 +44198,Male,47,Masters,8,87,12,77,8,5.0,6,62,Rural,ML Engineer,129986,1 +44199,Male,45,Diploma,5,1,67,19,63,7.0,0,90,Urban,Manager,119173,0 +44200,Male,49,Masters,9,72,9,5,99,2.0,5,84,Urban,HR Executive,60128,0 +44201,Male,36,High School,0,55,27,38,51,4.0,6,60,Rural,Software Engineer,44101,0 +44202,Female,58,Bachelors,16,14,76,13,29,1.0,5,41,Semi-Urban,Software Engineer,66170,0 +44203,Male,23,High School,14,88,84,92,51,1.0,0,4,Rural,Software Engineer,81788,1 +44204,Female,23,Bachelors,14,17,5,47,52,3.0,0,92,Urban,Software Engineer,76893,0 +44205,Male,48,Bachelors,13,66,61,52,97,9.0,3,9,Semi-Urban,ML Engineer,116794,0 +44206,Female,23,Bachelors,3,50,63,64,77,4.0,3,88,Urban,ML Engineer,118729,1 +44207,Male,32,Masters,15,56,75,72,24,5.0,4,51,Urban,HR Executive,50699,1 +44208,Male,37,High School,19,30,33,3,23,7.0,5,7,Urban,HR Executive,87350,0 +44209,Male,35,High School,16,73,89,13,71,4.0,4,17,Urban,Data Analyst,112078,0 +44210,Other,42,Bachelors,18,79,33,84,16,3.0,6,4,Semi-Urban,HR Executive,107566,0 +44211,Other,34,Diploma,5,88,45,99,78,2.0,2,54,Semi-Urban,Data Analyst,31759,1 +44212,Male,26,Bachelors,11,13,41,31,89,7.0,2,38,Semi-Urban,Software Engineer,52491,0 +44213,Male,34,High School,8,91,86,72,39,7.0,3,59,Semi-Urban,Data Analyst,51209,1 +44214,Male,55,Diploma,8,36,93,37,12,6.0,5,88,Urban,Data Analyst,55945,1 +44215,Male,32,Diploma,11,72,25,63,4,3.0,3,89,Rural,ML Engineer,61499,1 +44216,Female,59,Bachelors,16,35,67,11,3,0.0,5,89,Urban,Data Analyst,97889,0 +44217,Male,54,Bachelors,12,81,81,59,96,4.0,3,88,Semi-Urban,HR Executive,112750,1 +44218,Male,38,Masters,11,3,75,9,34,5.0,4,3,Semi-Urban,Manager,120276,0 +44219,Female,41,Bachelors,4,56,17,80,31,4.0,2,24,Rural,HR Executive,53032,0 +44220,Male,34,Masters,2,84,21,69,80,2.0,0,78,Semi-Urban,Software Engineer,60343,1 +44221,Female,51,PhD,5,3,18,97,76,7.0,6,92,Urban,Software Engineer,34687,0 +44222,Male,49,Masters,2,49,7,75,58,5.0,4,11,Urban,HR Executive,32546,0 +44223,Female,21,Bachelors,1,12,66,73,90,3.0,5,69,Semi-Urban,Software Engineer,21814,0 +44224,Male,22,High School,9,99,90,21,53,1.0,4,26,Urban,HR Executive,45806,1 +44225,Male,42,Diploma,2,34,83,27,95,5.0,1,90,Urban,HR Executive,98322,0 +44226,Other,45,Bachelors,8,15,61,69,70,4.0,0,1,Rural,ML Engineer,24015,0 +44227,Male,28,Bachelors,0,97,50,4,2,2.0,1,39,Urban,Software Engineer,113918,0 +44228,Female,59,Bachelors,15,39,63,11,86,4.0,6,91,Rural,Software Engineer,121024,0 +44229,Female,41,Masters,9,35,28,44,28,3.0,4,24,Urban,Software Engineer,52985,0 +44230,Female,55,Bachelors,11,36,42,93,55,6.0,1,60,Urban,HR Executive,31611,0 +44231,Male,57,Bachelors,2,64,57,54,22,0.0,1,65,Rural,Manager,62608,1 +44232,Male,34,Diploma,12,84,41,6,12,1.0,3,75,Urban,Software Engineer,43931,0 +44233,Female,40,Bachelors,5,85,58,46,97,5.0,4,64,Semi-Urban,Manager,27621,1 +44234,Female,38,Bachelors,16,53,10,28,12,6.0,3,0,Urban,HR Executive,65329,0 +44235,Female,30,Bachelors,16,19,15,89,97,8.0,4,61,Semi-Urban,ML Engineer,119737,0 +44236,Male,25,Bachelors,0,11,36,82,13,5.0,3,70,Urban,Manager,136852,0 +44237,Female,25,High School,13,14,53,75,49,7.0,1,32,Urban,Manager,147595,0 +44238,Male,41,High School,0,71,98,81,68,7.0,5,3,Urban,Data Analyst,21180,1 +44239,Female,30,High School,4,73,31,68,32,5.0,5,43,Urban,ML Engineer,100913,0 +44240,Male,38,Bachelors,1,17,29,97,17,4.0,1,4,Rural,HR Executive,136358,0 +44241,Male,26,Masters,15,56,68,7,17,2.0,1,55,Urban,ML Engineer,73748,0 +44242,Male,38,Diploma,14,45,72,51,58,1.0,3,46,Urban,ML Engineer,56875,0 +44243,Female,24,High School,0,54,92,52,99,4.0,5,49,Rural,ML Engineer,119494,1 +44244,Female,53,Bachelors,9,84,10,6,43,7.0,5,72,Rural,ML Engineer,111598,0 +44245,Other,25,Diploma,10,75,54,59,50,8.0,1,56,Urban,Manager,45546,1 +44246,Male,48,Bachelors,12,57,9,94,69,3.0,7,5,Urban,HR Executive,108500,0 +44247,Male,28,Bachelors,3,65,78,18,45,7.0,6,2,Semi-Urban,Data Analyst,44653,0 +44248,Male,47,Diploma,16,97,69,74,19,3.0,3,41,Rural,ML Engineer,143021,1 +44249,Male,50,Masters,7,16,81,28,90,7.0,3,14,Urban,Software Engineer,69840,0 +44250,Male,26,High School,7,5,28,32,56,0.0,6,71,Urban,HR Executive,60258,0 +44251,Male,35,Diploma,19,47,55,99,27,2.0,4,85,Urban,Manager,135650,1 +44252,Male,28,Masters,15,45,65,65,7,7.0,3,56,Semi-Urban,Data Analyst,105905,0 +44253,Male,42,Bachelors,0,82,25,27,39,4.0,3,69,Semi-Urban,Data Analyst,109351,0 +44254,Male,22,Diploma,15,88,4,75,98,0.0,6,22,Urban,ML Engineer,58591,0 +44255,Female,53,Diploma,4,26,15,46,9,8.0,2,12,Urban,Data Analyst,82054,0 +44256,Female,37,Diploma,11,47,23,62,28,6.0,1,39,Urban,Data Analyst,145869,0 +44257,Female,25,Bachelors,17,7,41,1,86,7.0,3,76,Urban,HR Executive,141567,0 +44258,Female,23,Diploma,4,58,52,58,27,6.0,2,68,Rural,ML Engineer,32441,0 +44259,Male,28,Bachelors,1,55,77,3,4,6.0,4,44,Semi-Urban,Software Engineer,139247,0 +44260,Female,30,Diploma,18,70,20,57,30,5.0,5,35,Urban,Data Analyst,65983,0 +44261,Female,46,Diploma,5,60,50,88,79,3.0,6,5,Rural,Software Engineer,36646,0 +44262,Male,49,Bachelors,9,14,88,36,29,6.0,3,30,Urban,Manager,148040,0 +44263,Female,36,High School,0,50,97,16,18,4.0,2,97,Rural,Software Engineer,59618,1 +44264,Male,43,Diploma,12,3,99,36,43,8.0,6,70,Urban,Software Engineer,72562,0 +44265,Male,28,Bachelors,1,37,63,95,29,5.0,1,14,Urban,Data Analyst,89037,0 +44266,Female,31,Diploma,1,27,45,26,87,1.0,4,39,Urban,Software Engineer,136080,0 +44267,Female,47,Diploma,0,87,42,54,62,7.0,3,40,Semi-Urban,HR Executive,130647,0 +44268,Male,31,Bachelors,15,86,89,93,37,4.0,5,12,Urban,Manager,74129,1 +44269,Male,58,Masters,4,57,37,36,70,4.0,2,51,Rural,ML Engineer,48805,0 +44270,Male,32,High School,15,85,35,25,60,8.0,7,12,Urban,Manager,75746,0 +44271,Male,51,Bachelors,15,38,68,13,34,1.0,1,78,Rural,Manager,37359,0 +44272,Other,48,Bachelors,10,4,93,9,94,1.0,3,21,Urban,Manager,74722,0 +44273,Female,36,High School,5,46,64,68,42,1.0,4,17,Urban,ML Engineer,27479,0 +44274,Female,39,Masters,4,23,67,52,83,0.0,3,1,Urban,Manager,80023,0 +44275,Male,38,High School,9,13,22,64,22,3.0,2,4,Semi-Urban,Manager,66933,0 +44276,Male,43,Bachelors,17,84,73,13,27,1.0,1,35,Rural,HR Executive,119248,0 +44277,Male,34,Diploma,5,24,93,53,98,8.0,0,8,Urban,Data Analyst,141762,0 +44278,Male,35,Bachelors,6,82,98,92,78,1.0,0,11,Rural,HR Executive,138495,1 +44279,Male,21,Diploma,13,99,24,60,51,3.0,1,68,Urban,Software Engineer,35235,1 +44280,Male,31,Diploma,0,89,36,8,7,1.0,1,21,Urban,Data Analyst,80511,0 +44281,Male,33,Diploma,17,64,7,4,16,0.0,1,71,Rural,ML Engineer,123953,0 +44282,Male,52,Masters,19,7,12,22,36,2.0,4,48,Urban,ML Engineer,123786,0 +44283,Male,33,Masters,0,86,18,65,67,0.0,5,11,Urban,Data Analyst,55287,0 +44284,Male,59,Bachelors,16,11,80,49,6,2.0,3,51,Urban,Software Engineer,119874,0 +44285,Female,22,Bachelors,6,45,92,80,14,4.0,5,77,Urban,Data Analyst,134150,1 +44286,Male,36,Masters,1,3,43,9,9,3.0,0,5,Urban,Manager,128220,0 +44287,Female,59,Diploma,18,91,0,72,70,9.0,0,92,Urban,Manager,24049,1 +44288,Female,35,Bachelors,3,97,47,5,22,6.0,6,14,Urban,Manager,107363,0 +44289,Female,22,Bachelors,14,35,36,90,64,7.0,0,82,Semi-Urban,HR Executive,124147,1 +44290,Male,45,High School,1,56,41,28,17,4.0,2,56,Urban,Data Analyst,77445,0 +44291,Male,42,High School,4,56,53,56,99,6.0,0,91,Rural,Manager,57049,1 +44292,Male,49,Bachelors,9,68,26,93,92,5.0,7,9,Rural,Data Analyst,113449,0 +44293,Female,59,Diploma,14,97,75,4,6,7.0,1,21,Semi-Urban,Software Engineer,123771,0 +44294,Female,54,Diploma,19,65,89,62,13,0.0,0,97,Urban,ML Engineer,112814,1 +44295,Male,50,Bachelors,13,19,4,84,21,7.0,7,69,Urban,ML Engineer,36014,0 +44296,Male,59,Bachelors,6,16,15,57,10,6.0,4,81,Rural,Software Engineer,145406,0 +44297,Male,51,Masters,16,95,0,44,63,2.0,1,42,Semi-Urban,HR Executive,56561,0 +44298,Male,43,Masters,14,45,90,55,72,8.0,7,48,Urban,Data Analyst,63177,1 +44299,Female,21,Bachelors,7,53,37,58,43,6.0,4,4,Urban,ML Engineer,108385,0 +44300,Male,27,PhD,16,52,77,59,42,7.0,6,30,Urban,ML Engineer,69523,0 +44301,Male,21,High School,12,2,18,99,74,0.0,1,85,Rural,ML Engineer,76966,0 +44302,Male,46,High School,19,2,93,3,64,1.0,6,61,Semi-Urban,Data Analyst,80820,0 +44303,Male,33,Masters,14,81,45,98,94,0.0,3,51,Urban,Data Analyst,42180,1 +44304,Male,53,Bachelors,3,98,82,15,85,0.0,1,52,Urban,Manager,49844,1 +44305,Male,26,Masters,12,38,76,64,15,3.0,6,64,Urban,Data Analyst,145693,1 +44306,Male,25,Bachelors,4,74,63,55,81,7.0,0,89,Rural,ML Engineer,116624,1 +44307,Female,53,Diploma,6,9,24,68,6,8.0,1,16,Urban,Software Engineer,121090,0 +44308,Male,39,Bachelors,13,81,35,30,17,7.0,0,63,Rural,Data Analyst,101213,0 +44309,Male,34,Masters,18,24,95,48,44,4.0,7,10,Urban,HR Executive,31915,0 +44310,Female,55,Diploma,10,41,94,22,75,8.0,1,85,Urban,HR Executive,45368,1 +44311,Male,46,Bachelors,0,93,30,21,71,1.0,4,77,Semi-Urban,Software Engineer,61421,0 +44312,Male,51,Diploma,18,53,3,96,99,2.0,1,38,Rural,HR Executive,25914,0 +44313,Male,57,Diploma,14,95,38,29,41,9.0,3,19,Semi-Urban,Manager,74761,0 +44314,Male,39,Bachelors,12,71,71,42,0,5.0,5,52,Semi-Urban,HR Executive,23825,1 +44315,Male,24,Bachelors,14,51,93,70,95,2.0,3,84,Urban,Software Engineer,44872,1 +44316,Male,54,Diploma,16,69,9,94,23,4.0,0,24,Urban,Software Engineer,84072,0 +44317,Male,46,Masters,14,8,1,23,84,1.0,0,49,Urban,Data Analyst,136487,0 +44318,Female,26,Diploma,14,1,54,60,64,2.0,5,76,Semi-Urban,HR Executive,53113,0 +44319,Male,28,Bachelors,18,35,99,75,23,5.0,0,1,Urban,ML Engineer,43088,0 +44320,Female,25,Bachelors,15,96,24,63,48,2.0,5,24,Rural,Manager,96234,0 +44321,Female,57,Diploma,19,68,69,7,96,4.0,5,59,Rural,ML Engineer,27764,0 +44322,Female,44,High School,4,12,62,7,45,6.0,5,58,Urban,ML Engineer,83209,0 +44323,Female,23,Masters,6,5,68,86,48,3.0,2,57,Semi-Urban,ML Engineer,125132,0 +44324,Male,26,High School,17,1,73,14,58,7.0,1,72,Semi-Urban,Data Analyst,113892,0 +44325,Male,53,Bachelors,0,85,14,94,91,8.0,5,13,Urban,ML Engineer,124748,0 +44326,Female,33,Diploma,0,53,15,8,1,2.0,1,82,Urban,Software Engineer,146659,0 +44327,Male,58,Bachelors,8,49,96,74,77,9.0,5,74,Urban,HR Executive,114722,1 +44328,Male,37,Bachelors,4,74,38,70,61,6.0,6,54,Semi-Urban,HR Executive,66455,1 +44329,Male,59,Diploma,12,15,92,44,60,5.0,0,23,Rural,Data Analyst,69963,0 +44330,Male,56,Bachelors,18,57,53,54,11,9.0,3,34,Urban,Manager,133733,0 +44331,Male,32,Bachelors,17,58,96,39,27,2.0,7,17,Rural,HR Executive,59377,0 +44332,Male,51,Bachelors,13,18,92,61,39,7.0,1,35,Urban,Data Analyst,45459,0 +44333,Female,24,Bachelors,10,16,70,20,41,8.0,0,42,Urban,Manager,52279,0 +44334,Male,46,High School,3,61,67,95,57,4.0,1,35,Rural,Software Engineer,109980,1 +44335,Female,33,Masters,10,4,60,77,94,4.0,4,50,Urban,Software Engineer,56489,0 +44336,Male,29,PhD,16,37,17,37,45,4.0,4,47,Urban,HR Executive,50486,0 +44337,Male,33,High School,2,52,12,99,7,9.0,0,28,Urban,Software Engineer,25454,0 +44338,Male,26,Bachelors,16,52,69,31,89,3.0,7,53,Rural,Software Engineer,147768,0 +44339,Female,52,High School,0,46,26,61,17,6.0,1,15,Semi-Urban,Software Engineer,40666,0 +44340,Female,44,High School,19,70,40,0,56,4.0,1,12,Urban,Software Engineer,60579,0 +44341,Male,56,Diploma,15,26,5,27,8,9.0,3,42,Urban,HR Executive,29495,0 +44342,Male,40,Bachelors,7,89,23,50,48,6.0,6,30,Urban,HR Executive,105057,0 +44343,Female,27,Masters,15,70,76,88,41,6.0,1,70,Urban,ML Engineer,30035,1 +44344,Female,29,Masters,17,50,93,49,8,3.0,3,8,Urban,ML Engineer,36224,0 +44345,Male,42,Bachelors,8,36,59,29,60,8.0,0,63,Urban,Manager,90594,0 +44346,Male,54,Bachelors,2,87,38,83,75,9.0,6,36,Rural,Software Engineer,141211,1 +44347,Female,27,Diploma,19,63,61,27,37,6.0,3,83,Rural,ML Engineer,48357,0 +44348,Male,34,High School,9,89,16,47,75,9.0,2,5,Urban,Data Analyst,91565,0 +44349,Male,34,Bachelors,14,37,1,39,84,7.0,2,40,Urban,HR Executive,99511,0 +44350,Male,38,Masters,3,15,8,72,50,4.0,5,53,Semi-Urban,ML Engineer,32026,0 +44351,Female,38,Diploma,13,0,35,47,17,2.0,6,12,Rural,Data Analyst,73559,0 +44352,Male,41,PhD,5,32,59,92,80,2.0,6,6,Semi-Urban,Manager,21546,0 +44353,Female,44,Bachelors,8,52,3,27,43,8.0,0,15,Urban,Data Analyst,64517,0 +44354,Female,57,Diploma,18,16,25,38,43,1.0,5,48,Semi-Urban,Manager,64939,0 +44355,Male,52,PhD,1,37,91,78,98,1.0,2,31,Semi-Urban,Manager,34208,1 +44356,Male,38,Bachelors,10,17,90,31,82,2.0,3,59,Urban,HR Executive,77920,0 +44357,Other,27,Bachelors,7,69,10,9,34,1.0,0,86,Urban,ML Engineer,40751,0 +44358,Male,36,Bachelors,8,40,42,6,16,8.0,4,3,Urban,HR Executive,68785,0 +44359,Male,49,High School,15,0,62,57,97,0.0,0,24,Rural,Software Engineer,95751,0 +44360,Other,30,Bachelors,12,77,14,13,98,3.0,4,21,Rural,HR Executive,131388,0 +44361,Female,57,Bachelors,17,25,18,45,77,7.0,0,91,Semi-Urban,Data Analyst,109384,0 +44362,Male,59,PhD,1,22,85,74,21,8.0,3,11,Urban,Software Engineer,79927,0 +44363,Male,42,Bachelors,6,94,10,26,47,3.0,5,50,Rural,Software Engineer,96017,0 +44364,Male,34,Masters,18,71,84,0,47,9.0,6,48,Urban,Manager,145840,0 +44365,Female,35,Diploma,2,23,81,88,82,8.0,6,85,Semi-Urban,Manager,76747,1 +44366,Female,46,Bachelors,12,61,19,55,13,9.0,1,8,Urban,Data Analyst,115903,0 +44367,Male,21,Masters,2,49,26,27,18,2.0,1,61,Semi-Urban,ML Engineer,120290,0 +44368,Female,32,Diploma,0,14,18,11,49,2.0,6,79,Semi-Urban,Manager,113883,0 +44369,Female,43,Bachelors,1,39,74,51,74,6.0,2,94,Semi-Urban,Software Engineer,121733,1 +44370,Male,27,High School,17,89,13,67,87,7.0,1,71,Urban,Software Engineer,42270,1 +44371,Female,38,Bachelors,14,30,18,8,20,0.0,3,65,Urban,Software Engineer,130985,0 +44372,Male,45,Bachelors,18,86,81,43,4,6.0,3,28,Urban,ML Engineer,78847,1 +44373,Female,48,High School,7,13,65,70,85,7.0,1,69,Semi-Urban,HR Executive,58938,0 +44374,Male,24,Diploma,2,50,58,37,48,4.0,7,19,Rural,HR Executive,90875,0 +44375,Female,43,High School,8,7,18,71,74,0.0,5,33,Semi-Urban,Software Engineer,128706,0 +44376,Male,54,Masters,13,76,13,26,19,8.0,0,78,Rural,Data Analyst,126324,0 +44377,Male,22,Diploma,12,57,16,74,24,1.0,6,48,Urban,Software Engineer,144012,0 +44378,Male,34,Masters,12,27,93,18,82,5.0,1,83,Urban,ML Engineer,82085,0 +44379,Female,32,High School,10,14,28,22,59,9.0,4,12,Urban,Manager,111233,0 +44380,Male,22,Diploma,12,95,23,58,1,0.0,2,18,Rural,ML Engineer,75074,0 +44381,Female,59,Bachelors,17,98,20,20,75,2.0,1,0,Urban,HR Executive,110460,0 +44382,Male,57,Bachelors,2,2,59,61,90,5.0,5,10,Urban,Data Analyst,23771,0 +44383,Female,52,Bachelors,0,39,65,3,28,8.0,3,90,Urban,Data Analyst,110678,0 +44384,Male,41,Diploma,19,28,42,58,90,7.0,3,88,Urban,Software Engineer,31870,0 +44385,Male,59,Bachelors,11,19,6,15,53,2.0,4,94,Urban,Manager,140739,0 +44386,Male,47,Diploma,7,42,25,63,27,2.0,2,86,Semi-Urban,ML Engineer,91808,0 +44387,Male,59,Diploma,5,78,8,16,13,6.0,4,73,Urban,Data Analyst,53409,0 +44388,Female,57,Diploma,4,51,93,50,71,0.0,5,42,Urban,HR Executive,115079,0 +44389,Female,41,Bachelors,3,86,21,94,61,7.0,3,34,Semi-Urban,ML Engineer,50129,0 +44390,Male,36,Bachelors,5,42,1,92,72,4.0,1,69,Urban,Software Engineer,50972,0 +44391,Female,27,Bachelors,15,85,24,55,69,1.0,2,19,Semi-Urban,Data Analyst,47050,0 +44392,Male,45,Masters,14,43,59,82,70,4.0,3,94,Urban,Manager,137892,1 +44393,Male,34,Bachelors,13,38,21,15,62,1.0,5,75,Urban,HR Executive,47470,0 +44394,Male,31,Masters,16,97,67,94,22,9.0,4,7,Rural,ML Engineer,47980,1 +44395,Male,31,Bachelors,4,95,57,96,37,8.0,6,89,Urban,ML Engineer,126629,1 +44396,Female,34,Diploma,3,6,74,22,5,0.0,3,19,Rural,Software Engineer,55374,0 +44397,Other,59,Bachelors,19,26,79,49,32,9.0,5,28,Urban,Manager,128681,0 +44398,Male,56,Bachelors,9,34,40,3,43,5.0,0,96,Semi-Urban,Manager,78109,0 +44399,Male,55,High School,5,76,85,19,0,4.0,1,7,Urban,HR Executive,147418,0 +44400,Female,29,PhD,2,20,27,59,48,0.0,1,47,Rural,ML Engineer,110648,0 +44401,Male,22,Bachelors,3,22,78,74,61,2.0,3,15,Urban,Software Engineer,106988,0 +44402,Male,55,Diploma,16,60,88,97,48,9.0,1,10,Rural,ML Engineer,137485,1 +44403,Male,38,Diploma,8,20,35,72,98,2.0,5,81,Rural,HR Executive,87401,0 +44404,Female,22,Diploma,17,6,52,70,61,3.0,1,42,Rural,Software Engineer,136554,0 +44405,Female,34,Bachelors,19,95,8,63,2,8.0,0,9,Urban,ML Engineer,86184,0 +44406,Female,24,Masters,9,80,11,80,20,7.0,3,56,Urban,ML Engineer,43666,0 +44407,Male,37,Diploma,10,63,90,46,11,7.0,7,44,Rural,ML Engineer,81222,1 +44408,Female,49,High School,2,37,69,38,43,6.0,4,18,Urban,Manager,111316,0 +44409,Male,48,Bachelors,7,15,41,15,56,5.0,7,7,Rural,Manager,124608,0 +44410,Other,27,PhD,1,31,83,65,87,0.0,2,39,Urban,Manager,35636,0 +44411,Male,37,Masters,2,2,35,72,12,0.0,2,5,Semi-Urban,Data Analyst,117470,0 +44412,Male,49,Masters,12,35,87,4,64,1.0,7,31,Semi-Urban,HR Executive,123375,0 +44413,Female,52,Diploma,0,35,47,35,33,6.0,3,55,Urban,Manager,75122,0 +44414,Female,31,High School,12,58,87,68,30,7.0,3,69,Urban,HR Executive,140920,1 +44415,Female,55,Masters,8,86,77,45,56,7.0,1,89,Rural,ML Engineer,24986,1 +44416,Male,56,Masters,6,37,42,70,11,4.0,1,55,Urban,Software Engineer,57484,0 +44417,Female,42,Diploma,7,63,1,68,49,6.0,7,42,Urban,ML Engineer,139950,0 +44418,Female,25,High School,19,25,90,40,67,9.0,4,30,Urban,Software Engineer,55015,0 +44419,Female,53,Diploma,16,52,80,78,52,2.0,0,76,Semi-Urban,Data Analyst,80898,1 +44420,Other,28,Diploma,19,67,10,26,38,3.0,0,34,Rural,Manager,23920,0 +44421,Male,27,Bachelors,6,34,45,24,79,5.0,1,42,Urban,Data Analyst,30872,0 +44422,Male,27,High School,11,70,96,58,51,3.0,7,65,Urban,Manager,71979,1 +44423,Female,50,Bachelors,13,96,93,14,59,0.0,1,14,Rural,Data Analyst,91790,0 +44424,Male,26,Bachelors,12,14,62,97,15,4.0,5,94,Urban,Manager,90230,1 +44425,Male,51,Bachelors,9,97,66,99,23,4.0,5,15,Urban,Data Analyst,39133,1 +44426,Male,42,Bachelors,0,94,68,41,62,7.0,1,27,Semi-Urban,Data Analyst,142877,0 +44427,Female,33,Masters,2,17,81,10,87,3.0,1,56,Urban,ML Engineer,23992,0 +44428,Male,26,Masters,5,39,32,59,32,8.0,0,17,Rural,Software Engineer,49916,0 +44429,Male,34,Bachelors,16,38,52,13,39,1.0,5,41,Urban,Data Analyst,74134,0 +44430,Male,23,Bachelors,7,31,4,58,77,3.0,6,61,Urban,ML Engineer,91033,0 +44431,Male,48,Masters,5,73,39,51,6,9.0,1,27,Urban,ML Engineer,22928,0 +44432,Male,43,Bachelors,6,25,92,6,48,3.0,7,94,Urban,Manager,134661,0 +44433,Male,59,High School,10,27,79,64,76,4.0,7,57,Semi-Urban,HR Executive,137977,0 +44434,Female,55,Bachelors,14,99,43,87,91,2.0,3,59,Rural,Data Analyst,36863,1 +44435,Male,55,Bachelors,1,57,17,14,38,9.0,7,41,Semi-Urban,Data Analyst,33963,0 +44436,Female,30,Diploma,0,41,98,33,72,3.0,6,50,Urban,HR Executive,97456,0 +44437,Female,45,Diploma,19,2,53,77,68,5.0,6,86,Urban,HR Executive,135925,0 +44438,Male,52,Bachelors,13,74,72,87,58,1.0,2,57,Urban,Data Analyst,133215,1 +44439,Male,37,Bachelors,7,17,29,24,24,2.0,6,34,Semi-Urban,Manager,32953,0 +44440,Female,48,High School,1,48,6,94,30,9.0,3,41,Urban,ML Engineer,40186,0 +44441,Male,33,Diploma,17,44,18,6,90,8.0,5,25,Semi-Urban,ML Engineer,133282,0 +44442,Male,44,Bachelors,8,83,12,89,24,6.0,7,94,Rural,ML Engineer,104274,1 +44443,Male,47,Masters,7,44,55,81,63,6.0,2,53,Semi-Urban,Data Analyst,135342,0 +44444,Male,35,Diploma,14,35,80,15,6,2.0,1,64,Semi-Urban,Software Engineer,121846,0 +44445,Male,47,Diploma,19,46,34,36,87,5.0,5,85,Urban,Software Engineer,128829,0 +44446,Male,21,Bachelors,15,75,49,91,15,2.0,2,17,Urban,Software Engineer,112900,0 +44447,Male,55,Diploma,3,48,60,77,42,5.0,4,38,Semi-Urban,Data Analyst,129412,0 +44448,Female,50,Bachelors,5,69,45,26,95,4.0,4,35,Semi-Urban,Software Engineer,93931,0 +44449,Female,40,Bachelors,16,63,79,85,33,9.0,4,20,Urban,Data Analyst,91104,1 +44450,Male,56,Diploma,15,20,58,45,71,1.0,1,51,Urban,ML Engineer,125380,0 +44451,Male,36,Bachelors,11,11,5,59,57,2.0,4,6,Urban,Data Analyst,48022,0 +44452,Female,25,Bachelors,4,78,93,59,20,5.0,6,99,Semi-Urban,ML Engineer,75606,1 +44453,Male,24,Diploma,10,24,93,81,37,3.0,7,37,Semi-Urban,HR Executive,55449,1 +44454,Male,34,Masters,2,44,79,22,90,8.0,1,61,Urban,HR Executive,137948,0 +44455,Female,25,Masters,2,94,19,40,77,1.0,7,96,Rural,Data Analyst,40934,1 +44456,Female,30,Masters,17,49,96,72,62,4.0,0,25,Urban,Software Engineer,54622,1 +44457,Male,31,Diploma,14,86,95,5,85,0.0,3,51,Urban,Software Engineer,53908,1 +44458,Male,42,Bachelors,16,19,70,74,47,9.0,2,4,Urban,ML Engineer,81839,0 +44459,Male,33,Masters,17,46,5,83,23,3.0,3,4,Semi-Urban,Data Analyst,116609,0 +44460,Male,58,Masters,8,7,76,72,56,4.0,6,58,Semi-Urban,Software Engineer,21134,0 +44461,Male,45,High School,1,80,63,88,83,2.0,0,47,Urban,ML Engineer,60310,1 +44462,Male,31,Diploma,4,56,53,15,99,0.0,0,83,Urban,Data Analyst,77782,0 +44463,Male,36,Diploma,19,96,55,83,37,3.0,3,52,Urban,Data Analyst,74215,1 +44464,Male,48,Bachelors,16,68,84,48,53,4.0,1,87,Semi-Urban,Manager,51749,1 +44465,Male,41,Bachelors,18,96,24,61,84,7.0,0,58,Urban,Software Engineer,95266,1 +44466,Female,29,Bachelors,9,18,92,63,88,4.0,4,45,Urban,Manager,88735,0 +44467,Female,26,Bachelors,11,31,63,38,27,6.0,3,31,Urban,ML Engineer,141003,0 +44468,Female,38,Bachelors,17,19,32,89,18,8.0,3,2,Urban,ML Engineer,80721,0 +44469,Male,49,Diploma,5,74,38,13,16,3.0,6,30,Rural,Software Engineer,79835,0 +44470,Male,46,Diploma,12,55,38,95,99,2.0,6,99,Semi-Urban,Manager,100128,1 +44471,Female,58,Diploma,3,89,9,59,66,3.0,3,22,Urban,ML Engineer,44139,0 +44472,Female,36,Masters,12,15,50,71,48,1.0,0,29,Rural,ML Engineer,73778,0 +44473,Female,28,High School,14,47,29,38,84,8.0,3,79,Semi-Urban,Software Engineer,78315,0 +44474,Male,48,Bachelors,8,15,80,98,85,1.0,6,47,Urban,HR Executive,30274,1 +44475,Female,43,Diploma,3,36,0,5,79,9.0,2,77,Rural,HR Executive,29478,0 +44476,Female,51,Bachelors,3,69,1,94,49,2.0,6,12,Rural,Software Engineer,99845,0 +44477,Male,23,Bachelors,16,21,79,40,13,9.0,4,73,Rural,ML Engineer,82087,0 +44478,Male,36,Masters,8,47,38,59,8,1.0,0,64,Urban,ML Engineer,40536,0 +44479,Male,33,High School,10,20,13,95,1,2.0,1,53,Urban,HR Executive,134618,0 +44480,Female,25,High School,17,70,17,57,19,3.0,5,43,Rural,HR Executive,78848,0 +44481,Male,44,Masters,3,19,18,58,88,0.0,4,20,Urban,HR Executive,49345,0 +44482,Female,29,High School,9,58,61,64,89,9.0,3,39,Urban,Software Engineer,55578,0 +44483,Male,35,PhD,2,75,56,80,76,6.0,7,87,Urban,Software Engineer,91769,1 +44484,Female,26,Bachelors,14,98,17,56,89,2.0,0,90,Semi-Urban,Software Engineer,68442,1 +44485,Male,44,Bachelors,17,10,18,10,52,9.0,2,30,Semi-Urban,HR Executive,104279,0 +44486,Male,57,High School,4,96,28,97,54,1.0,3,75,Urban,HR Executive,29513,1 +44487,Female,54,Masters,16,27,90,18,91,8.0,3,87,Rural,ML Engineer,119214,0 +44488,Female,22,Bachelors,6,80,18,10,57,6.0,4,33,Semi-Urban,HR Executive,138168,0 +44489,Other,25,Masters,11,42,35,60,38,6.0,7,91,Rural,ML Engineer,31820,0 +44490,Male,48,Diploma,14,78,66,0,80,5.0,1,79,Urban,ML Engineer,22815,0 +44491,Male,52,Masters,6,79,4,96,12,8.0,1,13,Rural,Software Engineer,131156,0 +44492,Male,38,Bachelors,9,20,44,69,89,3.0,7,54,Semi-Urban,Manager,139125,0 +44493,Male,21,Diploma,13,35,4,66,27,1.0,6,46,Urban,HR Executive,136340,0 +44494,Male,52,Bachelors,13,21,63,0,32,4.0,1,24,Semi-Urban,Manager,58897,0 +44495,Male,49,Bachelors,11,22,5,28,83,9.0,3,38,Semi-Urban,Manager,120690,0 +44496,Female,40,High School,6,11,66,34,77,4.0,4,30,Urban,Software Engineer,90766,0 +44497,Male,25,Bachelors,18,26,65,9,61,0.0,1,70,Urban,HR Executive,90807,0 +44498,Female,29,Bachelors,11,41,38,62,27,6.0,1,83,Rural,Software Engineer,71335,0 +44499,Female,43,Bachelors,14,97,94,38,42,3.0,4,39,Semi-Urban,ML Engineer,78367,1 +44500,Male,50,PhD,13,33,39,9,13,3.0,6,20,Semi-Urban,HR Executive,70893,0 +44501,Other,53,Bachelors,13,64,6,62,7,5.0,5,73,Urban,Manager,51553,0 +44502,Male,35,Masters,2,8,69,41,50,8.0,7,25,Rural,Data Analyst,56505,0 +44503,Female,40,High School,15,48,35,79,66,2.0,0,62,Urban,ML Engineer,25597,0 +44504,Female,23,High School,16,57,18,13,27,4.0,1,25,Urban,ML Engineer,94718,0 +44505,Female,45,Diploma,2,85,47,92,96,1.0,6,55,Urban,Manager,79226,1 +44506,Female,22,Masters,6,20,5,45,39,9.0,7,1,Urban,Data Analyst,69645,0 +44507,Male,27,Masters,3,25,95,29,32,8.0,2,78,Urban,ML Engineer,45696,0 +44508,Male,53,Masters,4,94,53,68,27,1.0,5,65,Urban,Data Analyst,92208,1 +44509,Male,21,Diploma,8,22,96,10,38,6.0,6,10,Semi-Urban,Manager,101637,0 +44510,Male,44,Bachelors,10,83,62,95,35,6.0,3,69,Semi-Urban,Software Engineer,95228,1 +44511,Female,52,Bachelors,13,6,53,72,28,4.0,6,47,Rural,ML Engineer,49627,0 +44512,Female,35,Masters,17,49,75,87,66,4.0,5,25,Semi-Urban,Software Engineer,52390,0 +44513,Male,21,Masters,1,81,88,25,63,7.0,4,27,Urban,HR Executive,136617,0 +44514,Male,57,Diploma,19,23,77,68,92,5.0,7,79,Urban,Manager,122028,1 +44515,Male,53,Bachelors,1,41,13,16,3,5.0,3,61,Urban,HR Executive,141894,0 +44516,Male,35,Bachelors,7,99,40,55,95,5.0,7,72,Urban,Data Analyst,48916,1 +44517,Male,43,Diploma,9,32,93,5,64,0.0,4,27,Urban,Software Engineer,46132,0 +44518,Female,40,Bachelors,7,91,33,68,7,4.0,0,44,Rural,Software Engineer,23516,0 +44519,Female,28,Diploma,9,62,92,50,6,1.0,5,47,Semi-Urban,HR Executive,115446,1 +44520,Male,35,Diploma,9,24,6,0,80,2.0,7,59,Semi-Urban,Data Analyst,112419,0 +44521,Male,27,Masters,15,52,60,40,30,1.0,0,24,Semi-Urban,HR Executive,35018,0 +44522,Female,51,Diploma,5,47,5,35,62,7.0,4,12,Rural,HR Executive,110480,0 +44523,Male,37,Masters,10,92,62,0,98,5.0,7,23,Semi-Urban,Data Analyst,81229,0 +44524,Other,22,Masters,17,13,5,68,44,7.0,7,12,Urban,Data Analyst,76468,0 +44525,Male,47,Bachelors,7,84,98,44,82,0.0,5,32,Semi-Urban,Manager,101986,1 +44526,Male,27,High School,16,77,40,96,19,2.0,3,14,Urban,Manager,59549,0 +44527,Female,58,Bachelors,12,47,0,25,26,1.0,4,56,Semi-Urban,Software Engineer,72343,0 +44528,Male,49,Diploma,19,14,36,12,6,0.0,6,84,Urban,HR Executive,147130,0 +44529,Male,34,Masters,11,72,46,52,73,2.0,1,12,Urban,Manager,149364,0 +44530,Female,22,Masters,12,52,78,69,57,5.0,2,75,Semi-Urban,Manager,129263,1 +44531,Female,42,Diploma,10,77,53,41,44,3.0,7,36,Urban,Data Analyst,131804,0 +44532,Male,53,Diploma,14,49,3,58,49,9.0,7,67,Urban,Manager,137214,0 +44533,Male,58,High School,17,42,43,37,75,0.0,3,73,Semi-Urban,ML Engineer,88230,0 +44534,Male,21,High School,5,87,33,88,94,8.0,0,71,Urban,ML Engineer,97967,1 +44535,Female,21,High School,19,78,83,13,82,2.0,1,78,Rural,Software Engineer,25930,1 +44536,Male,47,Masters,5,47,77,62,84,4.0,2,4,Urban,Manager,80631,0 +44537,Female,36,Bachelors,6,33,8,61,52,2.0,1,14,Semi-Urban,ML Engineer,101667,0 +44538,Female,39,Bachelors,1,8,79,3,7,7.0,3,13,Urban,HR Executive,112315,0 +44539,Male,24,Bachelors,6,50,41,33,85,2.0,5,52,Urban,HR Executive,108842,0 +44540,Male,22,Diploma,9,61,55,56,51,6.0,0,9,Rural,HR Executive,127373,0 +44541,Male,27,Bachelors,16,0,26,99,90,6.0,5,9,Urban,Software Engineer,113646,0 +44542,Male,38,Diploma,16,21,74,3,58,9.0,4,4,Urban,Software Engineer,51518,0 +44543,Female,36,Masters,9,94,5,79,20,0.0,1,98,Semi-Urban,Data Analyst,86767,1 +44544,Female,59,Bachelors,19,78,84,61,24,8.0,4,74,Rural,Data Analyst,62037,1 +44545,Male,35,Bachelors,3,86,28,45,64,1.0,3,98,Urban,Manager,43197,1 +44546,Female,28,High School,3,65,24,82,33,5.0,2,74,Urban,Software Engineer,117853,1 +44547,Male,29,Bachelors,13,13,93,6,24,2.0,3,77,Semi-Urban,Manager,139523,0 +44548,Male,38,Masters,16,64,44,72,82,4.0,3,18,Urban,Software Engineer,143485,0 +44549,Male,54,Diploma,17,26,57,4,28,8.0,7,52,Semi-Urban,Manager,121237,0 +44550,Male,46,Masters,13,25,25,47,12,5.0,4,55,Urban,Manager,110472,0 +44551,Male,57,Masters,11,39,69,46,27,7.0,2,84,Rural,Data Analyst,61193,1 +44552,Female,31,PhD,4,45,4,16,27,4.0,4,66,Rural,Software Engineer,94771,0 +44553,Male,59,Masters,10,31,26,8,42,1.0,4,56,Urban,Data Analyst,81554,0 +44554,Female,22,Bachelors,13,40,23,0,57,4.0,4,8,Urban,Manager,86905,0 +44555,Male,50,Masters,6,96,85,31,50,2.0,3,20,Urban,Manager,72147,0 +44556,Female,48,Masters,13,23,34,54,48,3.0,3,51,Urban,ML Engineer,75043,0 +44557,Female,33,Bachelors,13,59,37,9,21,4.0,2,38,Urban,Manager,148777,0 +44558,Male,35,Diploma,15,70,94,84,9,0.0,3,82,Semi-Urban,ML Engineer,114489,1 +44559,Male,47,Bachelors,12,68,59,52,39,6.0,4,48,Urban,ML Engineer,141112,0 +44560,Male,43,PhD,1,62,40,90,82,7.0,1,18,Urban,Manager,115297,0 +44561,Other,49,Bachelors,15,6,93,57,84,2.0,7,70,Urban,Data Analyst,49021,0 +44562,Female,21,Bachelors,19,59,28,32,13,7.0,6,26,Rural,Manager,134119,0 +44563,Female,32,Bachelors,0,15,17,96,3,8.0,5,41,Urban,Manager,66206,0 +44564,Female,27,PhD,18,38,41,72,11,9.0,3,23,Urban,Software Engineer,74000,0 +44565,Male,28,Masters,12,60,13,70,23,1.0,7,8,Urban,Manager,77157,0 +44566,Male,27,Bachelors,14,76,72,43,99,1.0,3,71,Semi-Urban,Data Analyst,21141,1 +44567,Male,41,Bachelors,14,59,33,91,2,4.0,7,61,Urban,ML Engineer,100493,1 +44568,Male,47,High School,17,87,0,8,53,5.0,7,95,Semi-Urban,HR Executive,54762,0 +44569,Female,42,Bachelors,4,5,82,94,21,3.0,4,55,Semi-Urban,Software Engineer,102828,0 +44570,Female,41,Bachelors,0,58,54,95,50,8.0,5,62,Semi-Urban,ML Engineer,71221,1 +44571,Other,39,Masters,0,63,95,71,73,7.0,1,6,Urban,Manager,142468,0 +44572,Male,58,Diploma,17,10,71,91,11,0.0,7,91,Urban,ML Engineer,83512,1 +44573,Male,54,PhD,15,11,41,70,30,4.0,6,30,Rural,Software Engineer,130671,0 +44574,Female,23,Masters,12,38,10,97,10,9.0,7,85,Rural,Manager,61876,0 +44575,Male,23,Bachelors,6,55,65,87,58,0.0,7,88,Urban,Software Engineer,139806,1 +44576,Male,24,Bachelors,4,92,7,97,94,8.0,0,51,Semi-Urban,Manager,68308,1 +44577,Male,48,High School,9,38,67,71,46,1.0,1,82,Rural,Data Analyst,54339,1 +44578,Male,57,Masters,14,58,44,73,94,2.0,4,54,Rural,Software Engineer,67213,0 +44579,Other,48,Masters,12,77,77,2,26,8.0,0,92,Semi-Urban,Manager,64137,1 +44580,Male,32,Bachelors,11,53,98,58,22,6.0,5,53,Semi-Urban,ML Engineer,143783,1 +44581,Female,58,Bachelors,0,15,91,2,71,8.0,7,4,Urban,ML Engineer,39115,0 +44582,Female,31,Diploma,2,97,92,86,53,0.0,0,17,Urban,ML Engineer,54594,1 +44583,Male,21,Bachelors,5,91,30,23,14,0.0,5,59,Rural,Software Engineer,122926,0 +44584,Female,24,Bachelors,8,21,63,76,37,7.0,7,12,Semi-Urban,Data Analyst,55088,0 +44585,Male,52,Masters,2,32,25,25,9,9.0,0,32,Urban,Manager,85160,0 +44586,Male,25,Bachelors,1,22,5,71,28,7.0,6,44,Rural,Data Analyst,102222,0 +44587,Female,24,High School,6,44,65,60,75,6.0,0,38,Semi-Urban,ML Engineer,146088,0 +44588,Male,53,Diploma,19,11,82,19,67,0.0,3,81,Urban,HR Executive,32392,0 +44589,Male,35,Masters,12,43,79,23,29,9.0,2,70,Urban,Software Engineer,39346,0 +44590,Male,28,Masters,6,95,8,38,28,2.0,2,7,Urban,Manager,71687,0 +44591,Male,53,Diploma,4,72,66,48,52,6.0,1,20,Urban,Software Engineer,35126,0 +44592,Male,40,Bachelors,4,94,67,78,40,7.0,6,24,Urban,Manager,84168,1 +44593,Male,45,Bachelors,7,54,97,37,41,8.0,4,53,Semi-Urban,HR Executive,90040,1 +44594,Male,54,Masters,13,26,46,56,61,8.0,7,48,Urban,Manager,124214,0 +44595,Female,29,Bachelors,13,64,60,82,80,7.0,4,33,Urban,Software Engineer,33691,0 +44596,Male,36,High School,16,15,25,45,20,5.0,2,49,Rural,ML Engineer,40018,0 +44597,Male,33,Bachelors,14,1,80,33,1,5.0,6,89,Rural,Manager,145951,0 +44598,Male,26,Bachelors,9,26,88,25,63,8.0,0,9,Urban,Software Engineer,91339,0 +44599,Female,30,PhD,13,0,26,0,91,4.0,7,35,Urban,ML Engineer,95643,0 +44600,Male,48,Bachelors,1,59,43,31,18,8.0,1,20,Semi-Urban,Manager,76680,0 +44601,Other,58,Diploma,12,53,47,71,99,8.0,6,79,Urban,Manager,56830,1 +44602,Female,33,Bachelors,12,3,39,54,53,4.0,6,11,Urban,ML Engineer,132079,0 +44603,Male,31,Diploma,6,35,84,56,87,8.0,1,83,Urban,HR Executive,117095,1 +44604,Male,47,Diploma,4,50,33,25,25,3.0,3,85,Urban,HR Executive,79322,0 +44605,Male,42,Bachelors,2,82,10,77,34,4.0,5,22,Rural,ML Engineer,82919,0 +44606,Female,46,Bachelors,5,45,23,74,41,2.0,3,15,Rural,Data Analyst,133461,0 +44607,Male,50,Bachelors,8,92,51,53,45,5.0,3,5,Urban,HR Executive,51086,0 +44608,Female,41,Bachelors,4,25,14,68,64,7.0,7,37,Urban,Manager,81106,0 +44609,Female,29,Masters,3,68,12,15,31,5.0,6,36,Rural,Manager,76167,0 +44610,Female,32,High School,17,87,13,67,35,1.0,1,57,Semi-Urban,Data Analyst,114329,0 +44611,Female,35,Masters,1,20,45,15,92,0.0,4,61,Urban,Software Engineer,117696,0 +44612,Female,38,Diploma,9,79,82,51,28,5.0,0,37,Urban,HR Executive,95139,1 +44613,Male,27,High School,12,73,85,31,83,2.0,1,41,Urban,HR Executive,141274,0 +44614,Male,49,Bachelors,2,81,8,20,71,7.0,4,4,Urban,Data Analyst,117258,0 +44615,Male,46,Diploma,19,76,29,74,21,8.0,7,95,Urban,Software Engineer,50457,1 +44616,Male,42,High School,15,61,36,25,32,3.0,4,29,Semi-Urban,ML Engineer,34622,0 +44617,Female,47,High School,2,9,27,60,40,9.0,6,69,Urban,Manager,117046,0 +44618,Male,54,High School,8,23,95,67,30,1.0,0,14,Rural,Manager,124135,0 +44619,Female,58,Bachelors,19,8,57,13,42,2.0,7,85,Semi-Urban,Data Analyst,106424,0 +44620,Female,31,Bachelors,12,16,52,19,78,1.0,3,75,Semi-Urban,Software Engineer,113321,0 +44621,Female,42,Bachelors,8,78,77,32,51,6.0,1,93,Urban,Data Analyst,117825,1 +44622,Male,52,Masters,15,37,19,22,98,2.0,7,33,Urban,Software Engineer,47497,0 +44623,Male,56,Bachelors,0,57,52,16,44,5.0,2,43,Urban,Software Engineer,99648,0 +44624,Male,32,Diploma,10,17,97,81,99,1.0,5,76,Urban,Software Engineer,55721,1 +44625,Female,38,Bachelors,18,13,88,42,60,7.0,3,19,Urban,Data Analyst,101230,0 +44626,Male,29,Masters,13,47,96,20,29,6.0,1,93,Urban,HR Executive,122079,1 +44627,Male,31,High School,2,9,90,83,96,7.0,1,62,Rural,Software Engineer,114113,1 +44628,Male,57,Masters,16,60,22,74,63,5.0,1,18,Urban,ML Engineer,29075,0 +44629,Male,38,Diploma,9,18,31,98,44,0.0,5,91,Urban,HR Executive,148870,1 +44630,Male,49,Bachelors,11,15,36,32,10,3.0,6,88,Urban,Manager,78437,0 +44631,Other,50,Bachelors,3,55,95,95,50,8.0,6,35,Urban,Data Analyst,77169,1 +44632,Female,34,Bachelors,1,96,79,1,74,9.0,7,71,Semi-Urban,Manager,77588,1 +44633,Female,54,Bachelors,8,78,21,7,73,4.0,2,81,Rural,ML Engineer,29107,0 +44634,Male,38,Diploma,0,70,12,79,41,4.0,6,61,Rural,Data Analyst,123029,0 +44635,Male,53,Diploma,16,67,23,9,64,8.0,6,46,Semi-Urban,Software Engineer,26874,0 +44636,Female,29,Bachelors,17,19,80,79,0,3.0,0,14,Urban,Data Analyst,117353,0 +44637,Female,36,Diploma,12,78,72,33,58,4.0,6,43,Urban,ML Engineer,96438,0 +44638,Male,27,High School,12,29,50,46,3,3.0,3,73,Urban,Data Analyst,45840,0 +44639,Female,23,PhD,11,14,35,91,59,7.0,7,25,Semi-Urban,HR Executive,108064,0 +44640,Other,59,Diploma,3,96,48,76,33,5.0,7,72,Urban,HR Executive,83267,1 +44641,Male,26,Masters,7,17,16,36,59,6.0,5,62,Urban,Data Analyst,101670,0 +44642,Male,23,Masters,10,2,43,58,65,4.0,7,31,Urban,Software Engineer,20768,0 +44643,Male,35,High School,10,85,71,3,28,5.0,4,27,Semi-Urban,Data Analyst,141404,0 +44644,Other,23,High School,11,35,42,42,35,8.0,6,50,Urban,Manager,23778,0 +44645,Male,43,PhD,11,3,96,60,56,8.0,4,60,Urban,Software Engineer,89253,0 +44646,Female,21,Bachelors,12,77,24,26,62,2.0,3,20,Urban,Manager,47287,0 +44647,Female,45,High School,8,37,76,71,15,8.0,3,18,Semi-Urban,Software Engineer,73932,0 +44648,Male,53,Masters,7,91,62,56,66,2.0,7,65,Semi-Urban,Software Engineer,70910,1 +44649,Male,24,Bachelors,8,85,35,62,34,5.0,7,12,Rural,ML Engineer,51859,0 +44650,Male,53,Bachelors,10,36,16,14,34,5.0,4,65,Rural,ML Engineer,107765,0 +44651,Female,53,Diploma,3,69,16,82,15,5.0,7,59,Rural,Data Analyst,35792,0 +44652,Female,21,Bachelors,18,9,48,67,74,2.0,5,95,Urban,Manager,130319,0 +44653,Female,44,Masters,6,68,33,54,19,3.0,5,43,Urban,Manager,139828,0 +44654,Male,52,Masters,9,49,36,87,86,3.0,7,18,Semi-Urban,Data Analyst,113190,0 +44655,Male,47,High School,18,7,7,85,77,6.0,3,76,Urban,Data Analyst,48578,0 +44656,Female,25,High School,14,45,49,45,50,8.0,3,70,Rural,HR Executive,103964,0 +44657,Male,49,High School,17,10,28,88,83,7.0,3,18,Urban,ML Engineer,121198,0 +44658,Male,48,Bachelors,8,99,79,46,55,2.0,6,99,Urban,ML Engineer,46290,1 +44659,Male,31,PhD,19,83,87,57,8,9.0,5,52,Semi-Urban,Manager,64152,1 +44660,Male,50,Bachelors,3,40,8,43,83,2.0,1,14,Urban,Manager,89264,0 +44661,Male,44,Bachelors,11,79,33,74,11,6.0,5,79,Rural,Software Engineer,97249,1 +44662,Male,46,Masters,13,22,24,66,99,7.0,2,87,Urban,Data Analyst,87146,0 +44663,Female,22,Diploma,19,10,57,32,7,6.0,1,95,Rural,Data Analyst,37081,0 +44664,Male,54,Bachelors,5,77,15,21,85,9.0,0,14,Semi-Urban,HR Executive,117893,0 +44665,Female,36,PhD,13,22,57,52,84,3.0,5,11,Urban,Software Engineer,79589,0 +44666,Male,22,Bachelors,10,57,48,88,9,2.0,3,89,Urban,Manager,84817,1 +44667,Male,32,High School,8,12,73,51,40,9.0,6,83,Semi-Urban,HR Executive,86501,0 +44668,Male,27,Masters,16,51,74,30,38,9.0,4,9,Rural,Software Engineer,49428,0 +44669,Female,34,Bachelors,19,92,51,37,21,2.0,0,85,Urban,Manager,104959,1 +44670,Female,52,High School,15,60,2,35,38,8.0,6,64,Urban,ML Engineer,104521,0 +44671,Male,27,High School,17,28,28,71,44,1.0,1,26,Rural,Software Engineer,43306,0 +44672,Male,56,Bachelors,18,38,90,32,27,2.0,7,30,Urban,Manager,116947,0 +44673,Male,55,Diploma,5,97,29,17,96,3.0,2,68,Rural,Software Engineer,67135,0 +44674,Female,38,Masters,0,52,98,19,46,0.0,7,54,Urban,ML Engineer,107736,0 +44675,Female,52,Bachelors,5,38,46,6,50,4.0,4,0,Rural,ML Engineer,39182,0 +44676,Female,33,High School,1,74,23,28,29,0.0,7,15,Urban,ML Engineer,127688,0 +44677,Male,30,Bachelors,7,17,54,99,45,2.0,4,80,Urban,Data Analyst,20041,1 +44678,Male,32,PhD,8,49,12,64,50,8.0,4,66,Urban,HR Executive,100190,0 +44679,Female,23,PhD,12,37,80,24,47,0.0,3,30,Rural,ML Engineer,95056,0 +44680,Female,42,High School,14,63,78,27,84,3.0,3,68,Rural,Data Analyst,65078,0 +44681,Male,40,Bachelors,5,72,63,33,40,0.0,0,71,Semi-Urban,ML Engineer,65480,1 +44682,Male,29,Bachelors,2,11,9,42,85,6.0,1,89,Urban,Manager,108828,0 +44683,Female,30,Bachelors,3,3,88,26,79,1.0,5,29,Urban,Software Engineer,47551,0 +44684,Male,22,Bachelors,10,62,75,58,1,5.0,6,57,Rural,Manager,147040,1 +44685,Male,45,Diploma,13,97,45,61,23,8.0,6,24,Urban,Manager,44549,0 +44686,Male,27,Masters,11,84,61,58,13,9.0,4,1,Urban,Data Analyst,51252,0 +44687,Male,23,PhD,12,33,22,87,0,4.0,3,43,Urban,Software Engineer,112310,0 +44688,Male,25,High School,19,62,85,23,80,7.0,0,61,Urban,Data Analyst,69869,0 +44689,Female,37,Bachelors,14,65,16,69,53,5.0,4,16,Rural,ML Engineer,61277,0 +44690,Male,44,Bachelors,8,80,12,22,56,6.0,7,44,Semi-Urban,Manager,81895,0 +44691,Male,27,Bachelors,8,69,63,66,27,9.0,4,55,Semi-Urban,Software Engineer,148985,1 +44692,Female,35,Bachelors,0,25,39,23,65,3.0,5,76,Semi-Urban,Manager,107632,0 +44693,Other,51,Bachelors,4,41,89,62,52,6.0,1,30,Urban,Software Engineer,41012,0 +44694,Female,33,Masters,6,24,86,12,64,6.0,4,52,Rural,Software Engineer,127046,0 +44695,Female,57,Bachelors,8,27,56,95,40,2.0,6,84,Urban,Manager,96062,1 +44696,Female,24,Diploma,0,96,82,22,10,7.0,4,36,Urban,Data Analyst,84350,0 +44697,Female,31,Diploma,10,53,52,96,17,5.0,1,88,Urban,Manager,35371,1 +44698,Other,55,Diploma,6,45,48,76,0,1.0,0,41,Semi-Urban,HR Executive,106995,0 +44699,Female,34,Bachelors,1,28,65,77,46,4.0,4,21,Semi-Urban,ML Engineer,135922,0 +44700,Female,38,Diploma,16,15,61,77,40,7.0,6,11,Semi-Urban,Data Analyst,146339,0 +44701,Female,28,Masters,7,13,36,75,14,3.0,4,81,Urban,Data Analyst,72884,0 +44702,Female,53,Diploma,6,37,38,76,80,4.0,4,41,Rural,Manager,42275,0 +44703,Female,29,Bachelors,17,6,90,44,55,7.0,2,20,Urban,ML Engineer,65211,0 +44704,Female,47,High School,12,36,86,44,15,4.0,5,28,Semi-Urban,Manager,54952,0 +44705,Male,56,Masters,1,51,4,11,84,4.0,4,56,Semi-Urban,HR Executive,102565,0 +44706,Female,41,Masters,15,16,70,80,16,0.0,7,27,Urban,Manager,107793,0 +44707,Male,56,Diploma,19,64,60,66,21,1.0,4,84,Urban,Manager,112150,1 +44708,Male,39,Diploma,1,38,62,75,5,4.0,5,76,Urban,HR Executive,90769,1 +44709,Female,38,High School,2,34,52,89,92,4.0,2,78,Urban,Manager,25338,1 +44710,Male,34,High School,3,25,98,41,82,2.0,2,1,Rural,Software Engineer,105894,0 +44711,Male,46,High School,9,83,16,72,80,8.0,1,85,Urban,Data Analyst,121183,1 +44712,Male,23,High School,17,7,32,18,78,9.0,2,50,Rural,HR Executive,79461,0 +44713,Male,55,High School,18,34,62,54,97,7.0,6,3,Semi-Urban,Software Engineer,118582,0 +44714,Male,58,Bachelors,16,16,36,11,40,7.0,0,23,Urban,Data Analyst,76737,0 +44715,Male,52,High School,9,78,45,60,77,1.0,6,42,Rural,ML Engineer,133500,0 +44716,Female,24,Diploma,12,55,94,91,0,4.0,3,84,Semi-Urban,Data Analyst,138659,1 +44717,Male,24,Bachelors,10,89,24,42,34,2.0,5,32,Urban,Data Analyst,110821,0 +44718,Female,33,Bachelors,14,97,47,41,91,1.0,4,62,Rural,HR Executive,53804,1 +44719,Female,44,Bachelors,8,26,41,15,17,0.0,1,63,Rural,Data Analyst,56849,0 +44720,Male,29,Diploma,7,66,25,69,50,3.0,6,43,Urban,HR Executive,101790,0 +44721,Female,43,High School,3,20,53,83,46,9.0,7,80,Urban,ML Engineer,56498,0 +44722,Male,29,Diploma,4,68,61,60,92,3.0,7,11,Semi-Urban,Data Analyst,47271,0 +44723,Female,47,High School,16,22,61,63,16,6.0,1,28,Urban,HR Executive,27158,0 +44724,Male,29,Masters,2,23,2,76,53,8.0,7,52,Rural,HR Executive,47657,0 +44725,Other,49,PhD,2,8,86,28,1,5.0,6,6,Urban,ML Engineer,29508,0 +44726,Male,54,PhD,4,19,96,29,49,9.0,1,85,Semi-Urban,Manager,29100,0 +44727,Male,42,Bachelors,3,3,48,76,93,4.0,1,96,Semi-Urban,Manager,90057,0 +44728,Male,59,Bachelors,0,95,87,12,66,3.0,0,58,Semi-Urban,Manager,34862,1 +44729,Female,30,Bachelors,13,32,67,87,30,1.0,3,40,Urban,Manager,45712,0 +44730,Male,38,Bachelors,8,78,71,8,94,5.0,1,9,Urban,Manager,98063,0 +44731,Male,37,Bachelors,16,63,10,22,49,9.0,2,50,Urban,ML Engineer,127005,0 +44732,Male,58,Masters,15,67,21,94,47,1.0,1,83,Rural,Software Engineer,55159,1 +44733,Male,28,Diploma,6,74,44,34,92,2.0,2,90,Urban,Data Analyst,57764,1 +44734,Female,51,Masters,9,13,77,74,33,0.0,1,99,Urban,Software Engineer,67784,1 +44735,Male,45,Diploma,16,98,33,72,31,7.0,6,73,Urban,Software Engineer,86141,1 +44736,Female,42,PhD,0,81,27,46,29,1.0,0,95,Urban,ML Engineer,84389,1 +44737,Male,55,Masters,18,95,0,16,44,2.0,0,97,Urban,Data Analyst,132452,0 +44738,Male,41,Bachelors,5,26,78,5,11,9.0,3,39,Urban,HR Executive,97513,0 +44739,Male,33,High School,15,83,35,0,43,3.0,2,44,Urban,Manager,120130,0 +44740,Female,37,Bachelors,9,28,34,47,95,3.0,4,13,Urban,Data Analyst,74133,0 +44741,Female,26,Masters,14,79,44,71,61,4.0,2,8,Urban,Manager,100097,0 +44742,Male,54,Masters,1,70,67,4,87,4.0,7,70,Rural,ML Engineer,82910,0 +44743,Female,33,Masters,6,39,37,17,84,5.0,7,60,Urban,Software Engineer,105344,0 +44744,Female,35,Bachelors,7,71,36,83,5,0.0,7,80,Rural,ML Engineer,44112,1 +44745,Male,21,Bachelors,4,58,99,6,87,7.0,5,78,Urban,Software Engineer,68033,1 +44746,Male,38,Masters,0,29,4,52,35,4.0,4,99,Rural,HR Executive,141041,0 +44747,Male,31,Diploma,15,56,56,50,69,6.0,1,50,Semi-Urban,Software Engineer,44669,0 +44748,Male,48,Bachelors,18,66,84,82,4,9.0,0,39,Urban,Data Analyst,36761,1 +44749,Male,24,Bachelors,0,99,98,92,34,7.0,5,18,Urban,ML Engineer,49875,1 +44750,Female,53,Bachelors,4,3,46,31,13,8.0,6,10,Urban,HR Executive,147226,0 +44751,Male,53,Diploma,18,88,2,77,74,2.0,7,51,Semi-Urban,HR Executive,52537,0 +44752,Male,35,High School,14,88,82,76,17,8.0,3,93,Urban,ML Engineer,85010,1 +44753,Male,57,Bachelors,0,51,69,86,1,7.0,5,3,Urban,Software Engineer,82662,0 +44754,Male,51,Bachelors,11,15,71,99,3,2.0,3,9,Urban,HR Executive,146606,0 +44755,Male,44,Diploma,4,59,12,9,30,4.0,2,33,Urban,Software Engineer,83826,0 +44756,Female,28,High School,8,70,79,31,23,6.0,4,11,Urban,HR Executive,140017,0 +44757,Male,53,High School,14,2,27,73,74,1.0,7,59,Semi-Urban,HR Executive,100737,0 +44758,Female,37,Bachelors,8,63,69,81,72,6.0,7,35,Urban,Software Engineer,47434,1 +44759,Male,22,Bachelors,8,68,29,16,2,2.0,4,11,Semi-Urban,ML Engineer,119587,0 +44760,Female,49,Masters,5,35,62,34,73,9.0,7,83,Semi-Urban,Data Analyst,110871,0 +44761,Male,25,Bachelors,0,2,89,41,65,5.0,7,49,Urban,Data Analyst,145902,0 +44762,Female,52,Diploma,5,98,11,46,32,2.0,4,60,Rural,Software Engineer,40755,0 +44763,Female,52,Diploma,12,18,44,98,12,8.0,6,29,Urban,Software Engineer,97087,0 +44764,Male,58,Masters,18,11,90,84,47,5.0,1,67,Rural,Software Engineer,42707,1 +44765,Female,58,High School,8,63,36,92,55,4.0,6,40,Semi-Urban,Software Engineer,101081,0 +44766,Male,38,Masters,11,47,48,21,31,2.0,7,11,Urban,Software Engineer,37597,0 +44767,Male,31,Bachelors,7,61,18,13,15,1.0,2,68,Rural,Data Analyst,120632,0 +44768,Female,48,Bachelors,4,31,41,96,83,9.0,3,61,Urban,HR Executive,100306,0 +44769,Male,46,Masters,4,33,62,78,98,1.0,3,8,Semi-Urban,Software Engineer,21279,0 +44770,Male,57,PhD,14,98,79,21,58,2.0,0,83,Urban,Manager,37653,1 +44771,Male,42,Bachelors,10,87,98,25,96,7.0,3,68,Urban,Data Analyst,105475,1 +44772,Male,48,Bachelors,9,32,62,38,91,5.0,1,91,Semi-Urban,ML Engineer,65239,0 +44773,Female,25,Diploma,2,83,92,77,94,3.0,1,62,Semi-Urban,Software Engineer,81536,1 +44774,Male,23,Bachelors,10,59,24,17,97,4.0,5,61,Semi-Urban,HR Executive,27885,0 +44775,Male,55,Bachelors,14,52,43,84,57,7.0,4,3,Urban,ML Engineer,61451,0 +44776,Male,54,Diploma,4,75,7,61,14,3.0,3,6,Urban,Software Engineer,82227,0 +44777,Male,35,Masters,15,48,94,60,90,9.0,3,84,Rural,Data Analyst,94642,1 +44778,Male,43,Bachelors,18,24,89,47,48,9.0,0,14,Urban,Manager,43963,0 +44779,Male,55,High School,6,84,55,13,86,4.0,2,33,Urban,Data Analyst,122981,0 +44780,Male,34,Masters,16,80,99,92,61,5.0,3,71,Urban,Data Analyst,57314,1 +44781,Female,43,Masters,18,94,22,75,31,3.0,5,58,Urban,Software Engineer,93262,1 +44782,Male,58,PhD,16,58,98,39,54,2.0,0,76,Urban,Data Analyst,72565,1 +44783,Male,29,Masters,16,10,89,14,33,5.0,2,30,Semi-Urban,HR Executive,125217,0 +44784,Other,35,Diploma,19,35,58,72,30,3.0,0,2,Urban,Manager,116546,0 +44785,Female,57,PhD,5,23,74,2,97,9.0,0,47,Urban,Data Analyst,132088,0 +44786,Female,29,Bachelors,9,18,81,85,78,1.0,2,4,Urban,Software Engineer,99499,0 +44787,Female,52,Diploma,0,18,75,72,84,8.0,2,64,Rural,Software Engineer,99155,0 +44788,Male,37,Masters,5,94,24,90,31,9.0,7,2,Urban,Software Engineer,86486,0 +44789,Female,23,Masters,15,82,56,69,71,4.0,5,13,Semi-Urban,Manager,108797,0 +44790,Male,32,Diploma,19,7,30,69,71,5.0,6,49,Urban,Software Engineer,88535,0 +44791,Female,58,High School,17,66,52,31,65,5.0,2,56,Urban,HR Executive,103268,0 +44792,Male,53,Diploma,4,85,75,99,93,3.0,3,70,Semi-Urban,ML Engineer,50111,1 +44793,Other,53,Bachelors,19,49,28,52,54,6.0,4,3,Urban,Data Analyst,141244,0 +44794,Female,47,Diploma,2,5,73,13,25,8.0,2,2,Semi-Urban,ML Engineer,86353,0 +44795,Male,35,Bachelors,11,4,14,77,97,2.0,4,78,Semi-Urban,Manager,88642,0 +44796,Male,24,Masters,12,5,18,50,60,3.0,3,29,Semi-Urban,Data Analyst,51910,0 +44797,Male,50,Masters,3,87,41,13,29,6.0,7,44,Urban,ML Engineer,117063,0 +44798,Female,37,Bachelors,13,70,27,55,0,7.0,0,4,Semi-Urban,Data Analyst,101897,0 +44799,Male,23,Diploma,12,54,32,76,25,2.0,0,83,Urban,Manager,85699,1 +44800,Male,54,Diploma,5,63,1,51,69,5.0,2,57,Semi-Urban,Manager,121173,0 +44801,Other,49,Bachelors,0,28,78,32,71,6.0,0,22,Rural,ML Engineer,148565,0 +44802,Female,36,PhD,2,12,47,24,70,5.0,4,97,Semi-Urban,ML Engineer,94371,0 +44803,Other,45,Masters,18,12,62,25,37,4.0,6,8,Urban,ML Engineer,34436,0 +44804,Male,31,Masters,6,36,0,50,61,2.0,7,31,Urban,ML Engineer,70105,0 +44805,Female,45,Masters,18,89,88,93,4,0.0,7,26,Semi-Urban,Data Analyst,143928,1 +44806,Female,33,High School,18,86,80,33,56,9.0,5,41,Urban,ML Engineer,23183,0 +44807,Male,23,Masters,14,74,49,27,29,4.0,6,60,Urban,HR Executive,28187,0 +44808,Male,40,High School,9,63,53,28,22,2.0,0,12,Urban,Manager,103266,0 +44809,Female,41,Bachelors,7,0,75,51,17,6.0,0,46,Rural,Software Engineer,38234,0 +44810,Female,35,PhD,10,39,88,2,43,4.0,4,5,Semi-Urban,Software Engineer,81954,0 +44811,Female,28,Bachelors,14,51,18,74,2,7.0,7,31,Semi-Urban,Manager,139764,0 +44812,Male,59,High School,3,29,48,41,97,5.0,4,40,Urban,HR Executive,110486,0 +44813,Male,50,Bachelors,18,62,9,3,56,3.0,6,26,Urban,ML Engineer,111354,0 +44814,Female,38,Diploma,8,15,74,7,4,1.0,3,69,Urban,HR Executive,62315,0 +44815,Male,28,High School,9,86,74,3,8,5.0,1,71,Urban,Manager,73312,0 +44816,Female,30,High School,12,53,50,26,61,6.0,6,22,Urban,Manager,55755,0 +44817,Male,39,Bachelors,12,82,12,61,36,5.0,4,97,Urban,Software Engineer,121936,1 +44818,Male,29,PhD,16,99,79,14,85,3.0,7,74,Urban,ML Engineer,84991,1 +44819,Male,29,Bachelors,5,97,73,94,89,4.0,7,1,Rural,ML Engineer,148700,1 +44820,Male,48,Masters,5,37,15,22,28,0.0,6,17,Semi-Urban,Data Analyst,114683,0 +44821,Female,39,High School,9,73,55,20,68,5.0,1,27,Urban,HR Executive,42047,0 +44822,Male,51,Diploma,14,54,26,63,89,5.0,0,56,Urban,Software Engineer,95211,0 +44823,Female,46,Bachelors,18,42,13,91,57,0.0,4,17,Urban,Manager,134102,0 +44824,Female,48,Bachelors,2,84,97,79,37,0.0,7,16,Rural,Data Analyst,54727,1 +44825,Male,51,Bachelors,10,48,11,95,80,5.0,4,7,Urban,ML Engineer,32316,0 +44826,Female,32,Bachelors,17,96,43,78,32,4.0,2,87,Semi-Urban,Data Analyst,99845,1 +44827,Female,58,PhD,12,24,62,90,78,0.0,1,41,Urban,Data Analyst,70441,0 +44828,Female,35,High School,19,86,90,58,96,1.0,5,89,Urban,Software Engineer,136767,1 +44829,Female,23,High School,12,93,86,61,89,7.0,2,7,Semi-Urban,ML Engineer,143192,1 +44830,Male,49,Bachelors,17,11,56,49,11,7.0,1,13,Rural,HR Executive,93516,0 +44831,Male,28,Diploma,0,51,54,4,74,1.0,4,88,Semi-Urban,Data Analyst,120528,0 +44832,Male,22,Bachelors,16,24,84,12,77,5.0,2,0,Semi-Urban,Software Engineer,119837,0 +44833,Male,23,Bachelors,19,69,19,49,58,0.0,0,69,Urban,Manager,105335,0 +44834,Male,50,Masters,12,95,1,95,9,7.0,4,60,Urban,Manager,39572,1 +44835,Female,53,Diploma,12,28,63,75,66,7.0,0,24,Urban,Software Engineer,101245,0 +44836,Male,56,Masters,4,70,55,67,61,4.0,6,80,Urban,HR Executive,119699,1 +44837,Male,41,Bachelors,18,55,15,94,52,8.0,2,55,Urban,Data Analyst,91657,0 +44838,Male,55,Masters,15,10,4,68,7,0.0,1,25,Rural,Software Engineer,108961,0 +44839,Male,36,Masters,14,8,83,51,79,0.0,2,25,Rural,HR Executive,21954,0 +44840,Female,30,High School,2,30,45,36,98,3.0,6,78,Urban,ML Engineer,114750,0 +44841,Female,21,Bachelors,9,22,37,35,90,2.0,2,59,Rural,Data Analyst,135171,0 +44842,Male,21,Diploma,14,18,66,52,60,4.0,2,69,Rural,Software Engineer,89558,0 +44843,Male,52,High School,15,0,19,4,2,6.0,4,43,Semi-Urban,Manager,128252,0 +44844,Male,37,High School,18,15,32,32,28,2.0,2,51,Rural,Data Analyst,52523,0 +44845,Female,26,Diploma,18,35,69,1,79,7.0,1,96,Urban,Data Analyst,78447,0 +44846,Other,25,Diploma,14,8,28,8,4,1.0,5,57,Urban,Software Engineer,89368,0 +44847,Male,47,Bachelors,15,39,32,95,54,8.0,0,80,Semi-Urban,Data Analyst,107365,1 +44848,Female,54,Diploma,11,99,55,27,41,9.0,3,68,Urban,ML Engineer,53754,1 +44849,Female,21,Masters,16,32,11,6,87,3.0,0,67,Urban,ML Engineer,148832,0 +44850,Male,58,High School,5,21,92,14,31,1.0,4,40,Rural,ML Engineer,71385,0 +44851,Female,52,Masters,12,49,42,93,83,7.0,6,29,Urban,HR Executive,22217,0 +44852,Male,53,Diploma,14,29,18,28,10,4.0,6,45,Urban,Data Analyst,102172,0 +44853,Other,39,High School,6,8,7,66,45,0.0,1,60,Urban,Data Analyst,39894,0 +44854,Male,35,Diploma,14,67,7,22,52,7.0,1,85,Urban,HR Executive,66258,0 +44855,Male,30,PhD,5,78,86,48,60,1.0,0,67,Urban,Data Analyst,127981,1 +44856,Other,46,Diploma,11,76,64,77,96,8.0,6,85,Urban,Software Engineer,88699,1 +44857,Male,39,Masters,12,11,77,44,65,1.0,2,68,Urban,HR Executive,23582,0 +44858,Female,57,High School,15,50,81,73,55,2.0,6,48,Semi-Urban,Software Engineer,54954,1 +44859,Male,22,High School,5,99,40,59,0,6.0,4,93,Urban,ML Engineer,113171,1 +44860,Female,28,Bachelors,7,50,29,78,46,8.0,0,75,Urban,HR Executive,123243,0 +44861,Male,31,Bachelors,3,73,40,33,7,3.0,1,93,Semi-Urban,Data Analyst,127031,1 +44862,Other,25,PhD,14,43,12,3,58,9.0,0,27,Semi-Urban,ML Engineer,109119,0 +44863,Male,31,Bachelors,17,63,87,24,80,4.0,1,65,Urban,Software Engineer,76173,1 +44864,Male,36,Bachelors,18,77,50,60,94,1.0,0,72,Urban,HR Executive,71652,1 +44865,Female,55,Diploma,16,66,4,48,28,0.0,7,21,Urban,ML Engineer,73250,0 +44866,Other,47,Diploma,10,26,30,76,3,6.0,2,66,Rural,Data Analyst,102907,0 +44867,Male,31,Bachelors,6,91,92,43,28,7.0,0,92,Urban,Data Analyst,122386,1 +44868,Male,56,Bachelors,11,58,46,58,54,8.0,6,25,Semi-Urban,HR Executive,94494,0 +44869,Male,50,Bachelors,16,70,25,12,72,5.0,7,20,Semi-Urban,Software Engineer,89965,0 +44870,Male,23,High School,3,2,6,86,43,9.0,1,6,Urban,Manager,144811,0 +44871,Female,58,Masters,16,1,75,54,42,7.0,6,24,Semi-Urban,Data Analyst,59636,0 +44872,Male,44,Bachelors,9,85,58,12,65,3.0,3,73,Urban,Data Analyst,67296,0 +44873,Female,25,Masters,17,86,6,92,99,1.0,7,67,Urban,HR Executive,80750,1 +44874,Male,33,Bachelors,10,35,2,25,72,8.0,1,48,Urban,Data Analyst,146868,0 +44875,Male,42,Masters,10,7,25,30,4,3.0,1,57,Urban,ML Engineer,80517,0 +44876,Male,54,Bachelors,6,96,82,22,29,2.0,6,21,Urban,Software Engineer,118195,0 +44877,Female,43,Diploma,12,79,61,66,83,7.0,1,5,Urban,ML Engineer,33702,0 +44878,Male,34,High School,15,87,70,28,1,2.0,0,94,Urban,Software Engineer,55830,1 +44879,Male,36,PhD,4,52,78,66,3,3.0,0,21,Urban,Software Engineer,82564,0 +44880,Male,59,Masters,13,56,71,92,49,3.0,3,77,Semi-Urban,ML Engineer,138260,1 +44881,Female,36,Bachelors,15,25,9,23,54,6.0,2,44,Urban,Manager,116275,0 +44882,Male,26,Bachelors,14,87,22,62,58,9.0,1,38,Urban,Manager,126185,0 +44883,Female,29,Bachelors,8,88,6,64,42,4.0,1,74,Urban,Manager,148989,0 +44884,Female,48,Bachelors,2,50,73,17,12,1.0,1,89,Semi-Urban,Software Engineer,60877,0 +44885,Male,22,Bachelors,16,46,31,51,38,8.0,7,53,Rural,HR Executive,86163,0 +44886,Male,39,High School,11,39,54,24,33,3.0,7,32,Urban,Data Analyst,145299,0 +44887,Male,47,Bachelors,9,96,7,16,75,1.0,3,21,Semi-Urban,HR Executive,68094,0 +44888,Female,35,Bachelors,11,89,63,28,20,1.0,1,49,Semi-Urban,HR Executive,47122,0 +44889,Male,32,Bachelors,15,61,35,27,37,2.0,2,37,Rural,ML Engineer,23735,0 +44890,Male,41,Masters,1,87,52,92,62,0.0,1,73,Urban,ML Engineer,85175,1 +44891,Male,21,High School,10,60,53,25,3,2.0,7,97,Urban,HR Executive,97721,1 +44892,Female,37,Diploma,5,10,63,96,6,1.0,3,81,Urban,ML Engineer,122060,1 +44893,Female,33,Masters,16,4,63,77,60,8.0,6,85,Urban,HR Executive,123343,0 +44894,Female,47,High School,6,11,13,58,50,3.0,4,24,Rural,Software Engineer,84746,0 +44895,Male,53,Bachelors,7,38,69,25,93,6.0,2,70,Urban,ML Engineer,50622,0 +44896,Male,23,Masters,16,21,8,95,29,7.0,6,83,Urban,Software Engineer,34078,0 +44897,Male,54,Masters,8,38,59,65,71,4.0,5,5,Semi-Urban,HR Executive,103701,0 +44898,Female,31,Bachelors,7,66,94,44,73,0.0,0,97,Urban,Software Engineer,114174,1 +44899,Other,41,Bachelors,7,23,25,88,8,7.0,6,11,Urban,Manager,32581,0 +44900,Other,39,Bachelors,16,53,79,75,31,5.0,6,58,Urban,Data Analyst,31479,1 +44901,Male,43,Bachelors,6,10,69,59,63,6.0,1,67,Semi-Urban,HR Executive,36111,0 +44902,Male,31,Bachelors,6,42,6,85,84,3.0,6,51,Semi-Urban,ML Engineer,68956,0 +44903,Male,39,High School,13,30,61,52,48,1.0,0,67,Rural,Data Analyst,81247,0 +44904,Male,34,Bachelors,18,23,67,70,6,4.0,6,22,Semi-Urban,Manager,133950,0 +44905,Male,27,Diploma,8,74,26,18,96,0.0,1,2,Rural,ML Engineer,69380,0 +44906,Male,52,Bachelors,5,76,36,4,28,2.0,5,4,Rural,ML Engineer,139164,0 +44907,Male,30,High School,11,78,71,4,25,9.0,0,48,Rural,Manager,64070,0 +44908,Male,50,Bachelors,13,33,19,50,10,9.0,5,17,Rural,Manager,98245,0 +44909,Male,21,Diploma,0,71,5,64,50,2.0,4,4,Rural,ML Engineer,29831,0 +44910,Male,27,Diploma,9,53,47,45,21,2.0,6,70,Rural,HR Executive,70051,0 +44911,Female,24,Masters,1,14,86,9,74,9.0,2,55,Urban,ML Engineer,147942,0 +44912,Male,32,Diploma,4,48,7,61,9,1.0,2,82,Semi-Urban,Manager,42019,0 +44913,Female,32,Bachelors,11,65,68,41,74,6.0,1,33,Rural,Data Analyst,44065,0 +44914,Male,58,Bachelors,2,24,99,82,86,9.0,3,57,Rural,HR Executive,105660,1 +44915,Female,31,Diploma,12,81,20,51,1,0.0,4,81,Semi-Urban,ML Engineer,107829,0 +44916,Male,25,Diploma,3,63,71,89,86,5.0,4,11,Urban,ML Engineer,59083,0 +44917,Male,56,Bachelors,9,30,50,48,69,5.0,1,40,Rural,Data Analyst,27808,0 +44918,Female,51,Masters,1,11,16,16,7,1.0,7,78,Urban,Manager,115135,0 +44919,Female,41,Bachelors,11,80,12,39,47,1.0,7,10,Semi-Urban,HR Executive,147614,0 +44920,Male,51,Bachelors,3,80,12,1,51,9.0,0,25,Urban,Data Analyst,73295,0 +44921,Male,48,Bachelors,16,44,87,30,96,8.0,3,49,Urban,Software Engineer,36289,0 +44922,Female,50,Masters,2,9,25,91,9,8.0,5,82,Semi-Urban,Manager,43258,0 +44923,Male,53,High School,9,17,94,38,29,7.0,3,35,Urban,Manager,56360,0 +44924,Male,29,Bachelors,19,82,32,50,36,4.0,5,41,Semi-Urban,Data Analyst,92441,0 +44925,Female,50,Diploma,4,21,16,15,87,8.0,2,31,Semi-Urban,Data Analyst,77703,0 +44926,Female,53,High School,19,51,32,37,48,8.0,2,39,Semi-Urban,HR Executive,142020,0 +44927,Male,26,Masters,7,97,2,76,61,3.0,1,44,Semi-Urban,HR Executive,74287,0 +44928,Other,38,High School,18,12,28,82,57,9.0,5,56,Urban,Manager,147513,0 +44929,Male,50,Diploma,14,11,60,98,77,4.0,0,2,Urban,Manager,117471,0 +44930,Male,22,Bachelors,9,66,45,12,40,3.0,1,70,Urban,Software Engineer,43671,0 +44931,Female,42,High School,9,5,62,49,32,6.0,2,41,Semi-Urban,ML Engineer,83355,0 +44932,Male,28,Masters,12,92,21,58,47,2.0,3,64,Urban,ML Engineer,83518,1 +44933,Male,42,Masters,5,66,22,85,77,4.0,1,63,Urban,Data Analyst,123299,1 +44934,Other,57,Bachelors,19,29,10,65,60,0.0,5,31,Urban,Manager,118610,0 +44935,Male,56,High School,6,35,99,24,77,0.0,5,13,Urban,Manager,89248,0 +44936,Female,47,Diploma,10,47,24,41,85,2.0,1,1,Urban,HR Executive,107578,0 +44937,Male,50,Masters,2,38,85,0,30,5.0,6,9,Semi-Urban,ML Engineer,66712,0 +44938,Male,42,Diploma,6,16,78,95,77,4.0,1,75,Urban,ML Engineer,136323,1 +44939,Female,51,Bachelors,19,41,47,10,73,7.0,3,43,Rural,Data Analyst,110402,0 +44940,Female,26,Masters,14,36,68,36,54,5.0,4,82,Urban,ML Engineer,113913,0 +44941,Female,50,Bachelors,17,89,28,29,55,6.0,3,49,Urban,HR Executive,29951,0 +44942,Female,30,Bachelors,8,20,10,27,36,6.0,7,52,Semi-Urban,Data Analyst,109268,0 +44943,Male,26,PhD,4,21,69,23,23,3.0,7,63,Urban,ML Engineer,100368,0 +44944,Male,22,Diploma,4,32,42,17,17,9.0,0,89,Semi-Urban,Manager,57241,0 +44945,Male,50,Bachelors,0,12,24,70,14,7.0,7,67,Urban,Manager,82242,0 +44946,Male,42,Bachelors,4,9,25,32,19,7.0,6,32,Urban,Manager,67440,0 +44947,Male,59,Diploma,2,88,6,99,93,6.0,4,97,Urban,Manager,68722,1 +44948,Male,23,Bachelors,17,65,41,90,39,7.0,2,49,Urban,ML Engineer,38692,1 +44949,Female,30,High School,11,18,3,46,49,2.0,2,57,Urban,HR Executive,124044,0 +44950,Male,47,Masters,16,68,75,44,26,1.0,7,90,Semi-Urban,Data Analyst,43459,1 +44951,Other,24,Bachelors,1,35,8,29,15,6.0,3,78,Semi-Urban,HR Executive,129894,0 +44952,Male,52,Masters,14,59,5,82,20,6.0,6,1,Rural,Manager,95334,0 +44953,Male,56,Bachelors,7,55,76,84,23,0.0,2,39,Semi-Urban,Manager,135435,1 +44954,Female,52,Masters,14,27,95,72,64,6.0,7,59,Rural,HR Executive,122802,1 +44955,Female,52,Masters,12,11,58,69,30,8.0,7,51,Semi-Urban,HR Executive,83168,0 +44956,Male,52,Bachelors,11,89,75,94,46,7.0,0,11,Semi-Urban,Manager,144888,1 +44957,Male,59,Bachelors,19,54,78,97,67,1.0,5,1,Urban,Manager,100109,0 +44958,Male,39,PhD,8,38,41,7,51,2.0,4,99,Urban,Manager,26237,0 +44959,Female,47,Bachelors,15,11,93,61,33,8.0,1,27,Rural,ML Engineer,148657,0 +44960,Female,26,Bachelors,11,89,90,71,39,8.0,1,81,Urban,HR Executive,48840,1 +44961,Male,47,Masters,18,83,49,90,56,1.0,6,34,Rural,Data Analyst,94555,1 +44962,Male,22,Masters,9,2,46,38,75,6.0,0,43,Semi-Urban,Manager,57058,0 +44963,Male,35,PhD,12,93,68,73,96,3.0,5,73,Semi-Urban,Software Engineer,45576,1 +44964,Male,32,Bachelors,15,5,42,51,91,9.0,5,7,Urban,HR Executive,67724,0 +44965,Male,45,Bachelors,11,81,53,6,98,0.0,4,41,Urban,ML Engineer,28907,0 +44966,Male,48,Bachelors,1,67,34,33,13,2.0,0,35,Urban,Data Analyst,56323,0 +44967,Male,36,Masters,7,37,87,27,3,4.0,2,91,Urban,Software Engineer,106881,1 +44968,Male,36,Bachelors,0,30,36,85,45,5.0,4,60,Urban,Data Analyst,96095,0 +44969,Male,46,High School,16,91,74,16,84,4.0,4,55,Urban,HR Executive,133598,1 +44970,Male,57,Bachelors,4,0,87,91,38,7.0,1,5,Urban,Data Analyst,42094,0 +44971,Female,52,Bachelors,5,55,37,96,88,1.0,3,77,Rural,ML Engineer,80452,1 +44972,Other,46,High School,8,22,47,44,81,4.0,6,66,Urban,Software Engineer,39407,0 +44973,Male,58,Bachelors,16,66,16,19,85,6.0,6,46,Semi-Urban,Software Engineer,38926,0 +44974,Male,28,Bachelors,4,70,95,75,78,9.0,6,55,Urban,ML Engineer,148200,1 +44975,Male,53,PhD,6,76,44,52,97,2.0,1,23,Semi-Urban,HR Executive,112363,0 +44976,Male,32,Bachelors,14,22,55,67,60,3.0,4,59,Urban,ML Engineer,125505,0 +44977,Male,58,Bachelors,18,29,12,9,22,3.0,7,51,Urban,Software Engineer,134386,0 +44978,Female,55,Bachelors,13,54,73,13,78,2.0,7,73,Semi-Urban,HR Executive,94495,0 +44979,Male,43,Bachelors,14,18,52,60,23,2.0,5,9,Semi-Urban,Manager,90119,0 +44980,Male,21,Diploma,18,24,96,15,29,9.0,2,45,Rural,ML Engineer,25073,0 +44981,Female,31,High School,12,37,76,9,8,5.0,6,23,Rural,Software Engineer,48957,0 +44982,Male,56,PhD,2,30,72,28,11,6.0,2,31,Urban,ML Engineer,21236,0 +44983,Male,23,Bachelors,7,6,53,91,65,0.0,5,5,Urban,Software Engineer,22556,0 +44984,Female,46,Masters,15,28,57,90,4,2.0,4,22,Urban,Data Analyst,38811,0 +44985,Male,28,Bachelors,0,60,40,74,16,2.0,5,65,Semi-Urban,Software Engineer,40024,1 +44986,Female,24,Diploma,17,54,44,11,88,3.0,4,20,Semi-Urban,Data Analyst,22876,0 +44987,Other,46,Bachelors,4,74,53,51,94,2.0,0,77,Urban,ML Engineer,131064,1 +44988,Female,57,Diploma,13,79,70,65,25,0.0,5,10,Urban,ML Engineer,47557,0 +44989,Male,46,Masters,14,61,37,18,9,0.0,4,96,Urban,Software Engineer,101089,0 +44990,Male,37,Bachelors,4,7,54,86,38,8.0,0,34,Urban,ML Engineer,84764,0 +44991,Male,45,Bachelors,16,3,69,81,14,0.0,0,50,Semi-Urban,Data Analyst,59965,0 +44992,Other,51,Masters,16,0,3,40,39,9.0,7,2,Rural,ML Engineer,79881,0 +44993,Other,33,Diploma,5,91,39,77,22,0.0,7,55,Semi-Urban,ML Engineer,91167,1 +44994,Male,55,PhD,12,62,93,85,2,9.0,6,13,Rural,HR Executive,141038,1 +44995,Female,30,Bachelors,1,26,60,94,71,3.0,6,4,Urban,Data Analyst,74893,0 +44996,Male,33,High School,1,69,45,92,2,3.0,6,42,Semi-Urban,ML Engineer,119507,1 +44997,Male,21,Masters,3,17,68,41,73,4.0,4,18,Rural,Data Analyst,83234,0 +44998,Male,48,Bachelors,11,32,20,45,87,8.0,6,66,Semi-Urban,Software Engineer,119260,0 +44999,Male,34,PhD,10,7,79,60,47,3.0,7,14,Urban,ML Engineer,49846,0 +45000,Female,40,Diploma,17,8,82,1,17,3.0,5,86,Rural,ML Engineer,55704,0 +45001,Male,25,PhD,1,14,53,72,79,8.0,6,27,Semi-Urban,HR Executive,129374,0 +45002,Female,27,Diploma,10,9,25,77,50,6.0,0,27,Urban,ML Engineer,37717,0 +45003,Other,24,PhD,3,84,42,3,27,2.0,2,96,Urban,ML Engineer,41618,0 +45004,Female,45,Diploma,9,26,3,91,23,4.0,7,51,Urban,Data Analyst,45351,0 +45005,Male,32,PhD,17,70,37,67,8,4.0,7,90,Semi-Urban,HR Executive,124605,1 +45006,Female,47,Bachelors,11,99,52,63,37,0.0,3,69,Urban,Manager,128181,1 +45007,Male,44,Bachelors,17,65,43,9,52,0.0,0,71,Semi-Urban,ML Engineer,43367,0 +45008,Female,45,Bachelors,1,78,37,33,27,5.0,2,96,Semi-Urban,Manager,138884,1 +45009,Male,36,PhD,16,66,21,84,94,9.0,2,72,Urban,HR Executive,31527,1 +45010,Female,47,PhD,14,4,35,36,5,0.0,3,66,Urban,ML Engineer,113975,0 +45011,Female,48,Diploma,16,60,65,88,61,1.0,7,47,Rural,Software Engineer,109399,1 +45012,Female,56,Masters,4,49,24,6,10,9.0,4,67,Urban,Software Engineer,96053,0 +45013,Other,21,Diploma,19,28,68,0,59,9.0,3,32,Urban,Software Engineer,127314,0 +45014,Male,48,Diploma,19,81,74,14,17,0.0,0,49,Urban,Software Engineer,82676,0 +45015,Male,35,Bachelors,6,46,33,15,77,5.0,5,33,Urban,HR Executive,74569,0 +45016,Male,51,Bachelors,10,49,84,59,96,0.0,2,77,Urban,Software Engineer,97255,1 +45017,Male,38,Diploma,5,86,59,53,88,1.0,4,74,Rural,ML Engineer,25186,1 +45018,Male,34,High School,8,97,0,59,39,3.0,6,94,Urban,Data Analyst,120683,1 +45019,Male,55,Bachelors,8,66,39,55,49,2.0,2,75,Urban,Manager,128538,1 +45020,Female,41,Bachelors,3,9,60,40,22,8.0,2,41,Urban,HR Executive,20574,0 +45021,Female,58,Diploma,6,39,75,82,55,3.0,6,70,Semi-Urban,Manager,32476,1 +45022,Male,33,Masters,2,61,24,53,59,8.0,2,46,Urban,Data Analyst,31881,0 +45023,Male,29,PhD,3,73,87,95,41,2.0,6,71,Urban,Data Analyst,136302,1 +45024,Male,57,Bachelors,19,90,3,88,52,1.0,6,68,Rural,Software Engineer,129461,1 +45025,Male,30,High School,2,90,41,31,99,6.0,3,72,Urban,ML Engineer,121813,0 +45026,Female,48,Masters,13,9,70,71,87,5.0,2,74,Urban,HR Executive,96038,0 +45027,Male,49,Bachelors,8,26,1,26,18,3.0,4,71,Urban,Data Analyst,43340,0 +45028,Female,53,Diploma,15,86,61,2,54,5.0,5,5,Urban,Data Analyst,27567,0 +45029,Male,49,Diploma,16,77,93,58,21,3.0,7,7,Rural,ML Engineer,92930,1 +45030,Other,59,Diploma,16,24,75,26,25,0.0,7,79,Urban,ML Engineer,96737,0 +45031,Female,22,Bachelors,0,55,71,15,27,6.0,6,53,Rural,Software Engineer,132784,0 +45032,Female,22,Diploma,18,40,17,81,76,2.0,3,64,Urban,Manager,41095,0 +45033,Male,31,Bachelors,1,91,87,58,12,2.0,4,37,Urban,ML Engineer,41386,1 +45034,Male,40,Masters,18,62,36,22,91,7.0,6,96,Semi-Urban,Software Engineer,26307,0 +45035,Male,38,Bachelors,1,12,5,11,66,5.0,5,40,Semi-Urban,Data Analyst,112004,0 +45036,Female,43,Diploma,14,88,12,65,99,9.0,3,78,Semi-Urban,Software Engineer,48201,1 +45037,Male,44,High School,11,30,45,47,55,0.0,2,6,Semi-Urban,Manager,141760,0 +45038,Female,23,Bachelors,2,58,35,84,18,1.0,3,46,Rural,Software Engineer,115545,0 +45039,Female,30,Masters,2,4,10,15,53,2.0,5,46,Urban,Manager,86083,0 +45040,Male,52,Bachelors,8,66,6,66,98,7.0,0,93,Rural,ML Engineer,87435,0 +45041,Female,54,High School,8,72,53,56,2,1.0,7,62,Semi-Urban,ML Engineer,80035,1 +45042,Male,46,Bachelors,2,87,63,40,75,8.0,4,68,Urban,Data Analyst,136169,1 +45043,Male,56,Bachelors,3,77,16,38,28,2.0,1,81,Urban,Data Analyst,77555,0 +45044,Female,36,Masters,11,96,8,45,76,3.0,5,29,Urban,HR Executive,36501,0 +45045,Other,33,Masters,17,12,44,68,92,9.0,4,60,Urban,Data Analyst,49359,0 +45046,Female,37,Bachelors,7,52,87,8,36,9.0,7,90,Semi-Urban,Data Analyst,104454,0 +45047,Female,52,Diploma,8,5,8,20,75,2.0,2,44,Rural,ML Engineer,110200,0 +45048,Female,51,Masters,5,92,2,67,92,6.0,0,99,Urban,Manager,113988,1 +45049,Male,31,Diploma,16,65,85,11,15,9.0,0,61,Semi-Urban,HR Executive,115530,0 +45050,Other,58,PhD,4,56,64,72,2,3.0,5,61,Urban,Software Engineer,73867,1 +45051,Male,39,Bachelors,6,44,46,79,7,7.0,3,17,Urban,HR Executive,91936,0 +45052,Male,23,Bachelors,18,17,71,0,97,3.0,0,65,Urban,Data Analyst,89390,0 +45053,Male,45,High School,10,70,2,18,82,3.0,0,81,Urban,ML Engineer,48124,0 +45054,Male,58,Diploma,3,66,10,25,17,4.0,1,16,Semi-Urban,Manager,56013,0 +45055,Male,55,Diploma,2,64,26,19,32,4.0,5,14,Urban,Data Analyst,133132,0 +45056,Male,58,Bachelors,10,13,92,68,79,6.0,0,41,Urban,HR Executive,30845,0 +45057,Male,37,PhD,15,95,30,65,62,9.0,2,9,Urban,HR Executive,123729,0 +45058,Male,31,Bachelors,2,77,92,43,66,0.0,4,54,Rural,ML Engineer,49202,1 +45059,Male,56,High School,4,37,65,20,27,3.0,6,24,Semi-Urban,Manager,128249,0 +45060,Female,36,High School,7,24,32,93,92,8.0,7,12,Rural,Software Engineer,148242,0 +45061,Male,42,High School,16,79,4,64,41,3.0,5,66,Semi-Urban,ML Engineer,67732,0 +45062,Male,55,Bachelors,15,20,56,79,7,6.0,1,96,Rural,Manager,130880,1 +45063,Male,42,Bachelors,15,14,25,30,77,9.0,5,25,Urban,Manager,28068,0 +45064,Male,36,Masters,1,0,0,99,26,8.0,4,87,Semi-Urban,Manager,125829,0 +45065,Female,56,Bachelors,13,94,67,21,79,5.0,3,6,Semi-Urban,Manager,118267,0 +45066,Female,28,Bachelors,2,54,32,8,17,6.0,4,39,Urban,Manager,110243,0 +45067,Female,53,Diploma,9,94,32,1,56,3.0,2,78,Urban,Data Analyst,82896,0 +45068,Male,48,Bachelors,14,9,2,19,86,5.0,1,63,Urban,Manager,112142,0 +45069,Male,41,Masters,10,12,57,61,62,7.0,7,10,Urban,ML Engineer,35284,0 +45070,Male,21,Bachelors,12,45,27,38,82,7.0,3,80,Semi-Urban,ML Engineer,85015,0 +45071,Female,25,Masters,7,52,78,4,53,4.0,6,95,Urban,HR Executive,114954,0 +45072,Female,27,Bachelors,18,49,66,49,24,5.0,4,40,Rural,HR Executive,44293,0 +45073,Female,43,Bachelors,3,9,21,12,69,8.0,0,47,Semi-Urban,ML Engineer,134538,0 +45074,Male,34,Bachelors,16,69,93,66,91,5.0,0,16,Urban,Data Analyst,86321,1 +45075,Male,53,High School,15,58,26,83,76,1.0,1,30,Rural,Data Analyst,78012,0 +45076,Male,46,Bachelors,9,79,77,78,23,1.0,4,15,Urban,HR Executive,69597,1 +45077,Female,34,Diploma,9,27,55,45,98,9.0,1,9,Urban,ML Engineer,72417,0 +45078,Male,50,Bachelors,2,72,21,96,23,6.0,3,69,Urban,Data Analyst,21034,1 +45079,Male,30,Bachelors,13,69,50,48,76,9.0,4,80,Urban,HR Executive,118349,1 +45080,Female,36,Masters,1,72,96,69,16,1.0,4,49,Urban,ML Engineer,29838,1 +45081,Female,46,Diploma,1,32,44,32,17,8.0,0,95,Semi-Urban,HR Executive,91592,0 +45082,Male,38,Bachelors,0,60,44,0,35,7.0,3,92,Semi-Urban,ML Engineer,82756,0 +45083,Male,39,Masters,13,33,11,4,50,7.0,5,80,Semi-Urban,Manager,144006,0 +45084,Female,45,Bachelors,13,13,82,86,50,9.0,4,53,Urban,Manager,59262,0 +45085,Male,33,Bachelors,9,82,32,45,45,2.0,3,38,Urban,Manager,118142,0 +45086,Female,42,Diploma,17,40,44,91,79,9.0,7,85,Semi-Urban,Software Engineer,140939,1 +45087,Male,29,Bachelors,11,76,97,65,80,7.0,2,43,Urban,Manager,41868,1 +45088,Female,40,Bachelors,18,54,8,44,59,3.0,4,58,Urban,ML Engineer,102929,0 +45089,Female,50,Bachelors,17,61,20,95,43,1.0,5,13,Semi-Urban,ML Engineer,130579,0 +45090,Female,30,Masters,19,69,92,97,11,0.0,3,6,Urban,HR Executive,129273,1 +45091,Male,38,Diploma,11,14,21,54,95,0.0,4,99,Rural,Manager,54922,0 +45092,Male,59,Diploma,15,3,65,5,34,3.0,3,7,Semi-Urban,Data Analyst,135559,0 +45093,Male,24,PhD,13,96,12,40,22,1.0,4,84,Urban,Data Analyst,130291,0 +45094,Female,25,Bachelors,17,66,14,21,45,0.0,4,10,Urban,HR Executive,50432,0 +45095,Male,40,Bachelors,11,84,93,37,11,9.0,5,72,Semi-Urban,Software Engineer,149615,1 +45096,Male,23,Bachelors,3,60,91,42,51,5.0,6,85,Urban,ML Engineer,34196,1 +45097,Male,43,Masters,14,87,34,19,11,8.0,6,85,Semi-Urban,HR Executive,97258,0 +45098,Female,51,Bachelors,2,66,59,40,98,4.0,5,72,Rural,Manager,97572,0 +45099,Female,22,Masters,6,67,31,42,82,7.0,2,70,Semi-Urban,ML Engineer,35560,0 +45100,Female,36,Bachelors,19,94,13,48,57,0.0,2,84,Rural,Manager,25824,0 +45101,Male,24,Masters,2,63,2,89,5,4.0,1,55,Urban,Software Engineer,37436,0 +45102,Other,45,High School,18,73,49,44,68,9.0,1,59,Rural,Software Engineer,66580,0 +45103,Male,35,Masters,8,38,87,92,50,9.0,2,72,Urban,Manager,61671,1 +45104,Female,25,Diploma,12,38,18,69,44,8.0,1,72,Semi-Urban,HR Executive,44870,0 +45105,Male,58,Bachelors,5,33,69,10,54,8.0,3,38,Urban,Data Analyst,48717,0 +45106,Male,52,Masters,3,81,10,25,87,4.0,6,54,Urban,Data Analyst,78547,0 +45107,Male,26,Bachelors,7,82,41,55,8,4.0,1,9,Urban,Manager,129887,0 +45108,Male,59,Diploma,15,45,1,63,32,2.0,3,18,Urban,Software Engineer,111287,0 +45109,Male,49,Bachelors,9,27,39,54,49,7.0,0,72,Urban,Manager,67340,0 +45110,Male,23,Bachelors,12,13,85,1,35,4.0,6,56,Urban,ML Engineer,142686,0 +45111,Male,43,Bachelors,10,71,25,58,90,4.0,6,59,Urban,Software Engineer,94010,0 +45112,Male,54,Masters,18,19,87,0,36,4.0,6,8,Urban,HR Executive,72792,0 +45113,Male,53,High School,18,52,0,46,97,1.0,4,99,Urban,Data Analyst,65300,0 +45114,Female,51,Bachelors,18,90,10,73,23,2.0,4,85,Urban,ML Engineer,109547,1 +45115,Female,56,Masters,17,49,61,84,74,4.0,6,42,Urban,Manager,137095,0 +45116,Other,53,Bachelors,12,38,5,69,42,1.0,3,94,Urban,ML Engineer,102446,0 +45117,Female,37,Bachelors,0,19,61,82,47,8.0,1,66,Urban,HR Executive,20582,0 +45118,Female,51,Masters,3,54,46,52,6,2.0,7,11,Urban,ML Engineer,148828,0 +45119,Female,25,Bachelors,9,82,45,3,94,1.0,0,10,Urban,Manager,85807,0 +45120,Female,44,High School,9,82,79,86,34,1.0,7,35,Urban,Data Analyst,40480,1 +45121,Male,54,Bachelors,11,83,92,65,50,3.0,1,73,Urban,Manager,49202,1 +45122,Male,44,Diploma,8,7,29,3,67,8.0,5,81,Urban,Data Analyst,145254,0 +45123,Male,43,Diploma,1,55,95,63,65,9.0,5,69,Rural,ML Engineer,95055,1 +45124,Female,22,Diploma,15,45,93,39,57,1.0,7,7,Urban,Software Engineer,70744,0 +45125,Female,35,Bachelors,14,38,19,47,60,6.0,4,6,Urban,ML Engineer,141871,0 +45126,Male,59,Bachelors,4,84,4,14,78,0.0,0,77,Rural,ML Engineer,33884,0 +45127,Male,45,Diploma,17,12,91,43,60,7.0,2,90,Urban,Software Engineer,60626,1 +45128,Male,35,Bachelors,19,78,78,11,26,5.0,7,58,Rural,Data Analyst,46260,0 +45129,Female,58,Diploma,7,39,47,7,26,5.0,3,85,Urban,Software Engineer,101397,0 +45130,Male,43,Bachelors,2,52,41,26,37,7.0,3,35,Urban,Software Engineer,51702,0 +45131,Male,48,Diploma,18,71,34,28,50,7.0,0,21,Semi-Urban,Data Analyst,110053,0 +45132,Male,27,Masters,10,71,81,37,19,8.0,1,89,Urban,HR Executive,130115,1 +45133,Female,56,Bachelors,18,91,7,5,57,2.0,0,49,Urban,ML Engineer,112703,0 +45134,Other,53,Bachelors,3,52,27,16,69,8.0,6,59,Urban,Software Engineer,113928,0 +45135,Female,39,Masters,1,39,37,85,65,0.0,1,51,Urban,Software Engineer,47260,0 +45136,Male,34,Diploma,13,89,74,66,67,5.0,1,44,Urban,HR Executive,97018,1 +45137,Male,48,Masters,15,12,85,71,10,3.0,5,41,Urban,Manager,121732,0 +45138,Male,33,Masters,7,62,40,92,51,2.0,7,16,Urban,Manager,60484,0 +45139,Male,51,PhD,16,33,24,7,76,7.0,1,1,Rural,Manager,52362,0 +45140,Female,23,Bachelors,19,91,59,81,85,6.0,2,67,Semi-Urban,ML Engineer,98775,1 +45141,Male,38,Bachelors,2,10,67,42,50,9.0,4,99,Urban,ML Engineer,60108,0 +45142,Female,31,Diploma,14,89,22,46,87,3.0,2,36,Urban,Data Analyst,34272,0 +45143,Male,35,Masters,12,68,8,66,17,4.0,4,42,Urban,Data Analyst,87862,0 +45144,Other,32,Bachelors,19,58,52,94,39,7.0,1,47,Urban,Manager,48402,1 +45145,Male,51,Bachelors,2,67,10,37,51,4.0,1,45,Urban,ML Engineer,31156,0 +45146,Male,59,Bachelors,5,82,63,2,67,4.0,1,30,Semi-Urban,Software Engineer,48032,0 +45147,Female,46,Masters,1,91,48,15,25,9.0,6,3,Rural,Software Engineer,137226,0 +45148,Female,46,Diploma,3,0,94,29,43,3.0,0,8,Urban,Manager,125241,0 +45149,Male,40,Bachelors,18,72,85,24,88,2.0,1,63,Semi-Urban,Data Analyst,94284,1 +45150,Other,30,High School,11,81,55,12,18,0.0,6,77,Rural,Manager,26658,0 +45151,Male,52,High School,3,11,47,2,84,7.0,1,13,Semi-Urban,HR Executive,121479,0 +45152,Male,25,Bachelors,7,8,22,9,88,2.0,7,63,Rural,ML Engineer,147763,0 +45153,Female,35,Bachelors,10,40,72,51,72,9.0,4,79,Urban,Manager,136419,1 +45154,Male,34,Masters,7,0,49,12,55,4.0,4,78,Urban,Software Engineer,95266,0 +45155,Male,37,Bachelors,15,64,75,91,71,1.0,7,94,Rural,ML Engineer,92555,1 +45156,Female,27,High School,13,46,79,58,96,9.0,2,20,Urban,Manager,115709,0 +45157,Female,21,Bachelors,14,30,76,17,20,8.0,0,91,Urban,Software Engineer,119231,0 +45158,Male,41,PhD,4,36,74,56,87,1.0,2,95,Semi-Urban,ML Engineer,90257,1 +45159,Male,27,Bachelors,6,91,88,39,95,7.0,7,33,Urban,Software Engineer,26710,1 +45160,Male,32,Bachelors,19,74,33,41,44,1.0,7,33,Rural,Data Analyst,116730,0 +45161,Male,28,Diploma,8,47,70,18,38,6.0,4,18,Urban,HR Executive,65005,0 +45162,Female,57,Masters,3,44,69,82,30,0.0,3,59,Rural,ML Engineer,102892,1 +45163,Male,23,Masters,1,30,23,56,83,1.0,3,20,Urban,Data Analyst,40907,0 +45164,Male,21,Diploma,7,46,52,23,9,4.0,1,51,Urban,HR Executive,74584,0 +45165,Female,24,Diploma,0,95,62,44,78,3.0,5,31,Urban,HR Executive,129439,0 +45166,Female,44,Bachelors,17,0,15,54,30,2.0,1,19,Semi-Urban,Data Analyst,119915,0 +45167,Female,58,Bachelors,14,79,8,66,80,5.0,2,63,Rural,HR Executive,104183,0 +45168,Male,45,Masters,18,74,65,22,80,9.0,1,92,Urban,Manager,39055,1 +45169,Female,52,Bachelors,3,0,17,4,41,7.0,0,97,Semi-Urban,HR Executive,28381,0 +45170,Male,25,PhD,14,42,28,65,13,0.0,2,54,Semi-Urban,HR Executive,136838,0 +45171,Male,36,Bachelors,18,12,76,86,89,0.0,7,66,Semi-Urban,Software Engineer,91278,1 +45172,Female,45,Masters,1,21,79,59,65,7.0,7,14,Semi-Urban,Manager,101634,0 +45173,Male,48,Bachelors,8,22,24,6,58,1.0,5,80,Semi-Urban,HR Executive,80992,0 +45174,Female,44,Bachelors,17,66,55,95,16,8.0,7,92,Urban,Software Engineer,67272,1 +45175,Male,38,High School,2,69,68,97,82,8.0,2,0,Urban,HR Executive,47565,0 +45176,Female,22,Bachelors,3,5,21,14,9,6.0,3,33,Urban,Manager,97911,0 +45177,Male,37,High School,6,75,41,88,1,6.0,0,28,Rural,Data Analyst,130601,0 +45178,Female,38,Bachelors,17,61,86,78,4,9.0,5,50,Urban,ML Engineer,33711,1 +45179,Female,55,Bachelors,8,1,54,36,42,3.0,3,95,Semi-Urban,Data Analyst,119218,0 +45180,Female,56,Bachelors,8,16,32,77,38,6.0,6,49,Semi-Urban,ML Engineer,108727,0 +45181,Male,42,Bachelors,0,70,66,7,45,5.0,1,12,Urban,HR Executive,133968,0 +45182,Other,22,Masters,7,12,50,91,52,3.0,4,47,Urban,HR Executive,93199,0 +45183,Male,58,Bachelors,2,77,37,2,66,0.0,5,21,Rural,Software Engineer,132567,0 +45184,Male,52,High School,13,48,20,76,75,7.0,0,19,Semi-Urban,HR Executive,39430,0 +45185,Female,35,Bachelors,3,59,4,45,95,3.0,0,91,Urban,HR Executive,28229,0 +45186,Male,38,Bachelors,10,12,77,67,29,1.0,3,57,Urban,Software Engineer,125297,0 +45187,Male,36,Bachelors,18,65,9,40,31,6.0,6,86,Rural,HR Executive,39682,0 +45188,Female,59,High School,16,8,96,46,85,7.0,5,48,Urban,ML Engineer,56532,0 +45189,Male,56,High School,16,1,72,73,88,5.0,6,79,Rural,Software Engineer,70496,0 +45190,Female,28,High School,2,96,70,9,2,2.0,2,36,Semi-Urban,Software Engineer,30464,0 +45191,Female,39,Bachelors,14,68,18,82,61,3.0,4,53,Urban,Software Engineer,131846,0 +45192,Male,34,Masters,14,81,3,20,79,1.0,2,82,Semi-Urban,Manager,114570,0 +45193,Male,57,High School,11,8,41,15,41,5.0,1,5,Rural,Manager,108445,0 +45194,Female,45,High School,0,27,54,58,19,8.0,4,18,Urban,HR Executive,31588,0 +45195,Female,22,High School,18,61,51,59,31,6.0,0,93,Urban,Manager,23920,1 +45196,Male,43,Bachelors,7,18,40,42,92,8.0,0,29,Rural,Manager,26305,0 +45197,Male,36,Diploma,6,14,43,37,56,3.0,2,95,Urban,Software Engineer,143841,0 +45198,Male,40,Bachelors,4,54,86,11,37,6.0,7,83,Urban,ML Engineer,30018,0 +45199,Female,52,Diploma,7,5,75,13,76,3.0,0,11,Rural,ML Engineer,112341,0 +45200,Female,40,Masters,17,77,13,80,95,8.0,5,32,Semi-Urban,Manager,57803,0 +45201,Male,55,Bachelors,13,3,58,69,11,1.0,1,66,Urban,Software Engineer,149797,0 +45202,Female,32,Bachelors,19,72,81,60,48,6.0,2,81,Urban,Software Engineer,94062,1 +45203,Female,53,Masters,1,49,85,62,38,5.0,1,52,Rural,ML Engineer,134450,1 +45204,Male,31,Masters,7,93,70,10,61,7.0,7,23,Urban,Data Analyst,42437,0 +45205,Female,44,Bachelors,14,29,48,11,36,6.0,5,43,Urban,HR Executive,138015,0 +45206,Female,41,Bachelors,3,96,35,57,32,3.0,6,13,Urban,Data Analyst,63205,0 +45207,Other,56,Diploma,14,38,1,53,19,8.0,6,72,Urban,Manager,33292,0 +45208,Male,29,Diploma,18,62,78,96,69,2.0,6,66,Urban,HR Executive,111863,1 +45209,Male,28,Bachelors,5,7,0,79,2,3.0,7,48,Semi-Urban,Software Engineer,55138,0 +45210,Other,52,Bachelors,2,36,96,55,85,8.0,0,91,Rural,Data Analyst,124559,1 +45211,Male,48,Bachelors,0,35,82,79,63,1.0,4,66,Urban,ML Engineer,119337,1 +45212,Male,38,Diploma,11,23,1,96,37,3.0,0,50,Urban,Manager,74744,0 +45213,Male,28,High School,14,92,22,68,31,7.0,2,21,Rural,ML Engineer,122530,0 +45214,Female,35,High School,5,49,16,57,28,5.0,5,92,Urban,Software Engineer,62346,0 +45215,Male,56,High School,5,70,42,73,93,7.0,0,48,Rural,Manager,45667,0 +45216,Female,24,Diploma,19,84,78,42,5,7.0,6,54,Urban,Manager,86149,1 +45217,Male,25,Bachelors,18,55,30,79,77,1.0,7,74,Semi-Urban,Software Engineer,139376,1 +45218,Female,29,PhD,19,43,98,9,8,6.0,4,16,Rural,Software Engineer,74116,0 +45219,Male,37,Bachelors,1,76,16,60,46,5.0,3,74,Rural,Data Analyst,120085,0 +45220,Male,46,Bachelors,15,20,55,33,0,9.0,6,75,Rural,Manager,110820,0 +45221,Male,58,Diploma,8,20,44,47,68,5.0,1,71,Rural,Data Analyst,125590,0 +45222,Other,36,Masters,6,57,49,8,83,8.0,7,26,Urban,HR Executive,113267,0 +45223,Male,21,Diploma,8,16,70,49,74,8.0,0,59,Urban,ML Engineer,83485,0 +45224,Female,24,PhD,17,54,74,27,62,7.0,2,68,Rural,Manager,71965,0 +45225,Female,22,Bachelors,9,34,76,76,21,4.0,5,80,Urban,Data Analyst,130271,1 +45226,Male,23,Masters,10,47,97,42,63,4.0,0,3,Semi-Urban,Manager,105426,0 +45227,Female,45,High School,15,92,90,9,94,1.0,2,21,Semi-Urban,Manager,28025,0 +45228,Male,38,High School,1,35,43,68,14,3.0,7,45,Urban,Data Analyst,100141,0 +45229,Female,22,Bachelors,5,47,50,35,52,4.0,6,4,Urban,Manager,117658,0 +45230,Male,42,Masters,13,2,11,98,99,7.0,7,45,Semi-Urban,Manager,149554,0 +45231,Female,40,Masters,5,11,83,70,16,8.0,2,37,Rural,Software Engineer,136713,0 +45232,Female,46,Bachelors,19,66,23,75,58,2.0,6,19,Urban,HR Executive,93344,0 +45233,Male,29,Bachelors,10,29,50,13,38,5.0,1,92,Urban,Data Analyst,135878,0 +45234,Male,48,Bachelors,17,50,92,20,90,6.0,1,1,Urban,Data Analyst,62227,0 +45235,Male,39,High School,12,71,13,5,81,9.0,6,21,Urban,Software Engineer,85687,0 +45236,Female,30,Bachelors,0,92,35,57,4,5.0,3,75,Urban,Data Analyst,36307,1 +45237,Male,21,Diploma,7,23,86,78,88,1.0,4,45,Urban,Manager,102587,0 +45238,Male,47,Diploma,19,78,72,62,22,7.0,6,90,Rural,ML Engineer,114704,1 +45239,Male,48,Bachelors,10,62,11,93,11,6.0,5,96,Urban,Software Engineer,78152,1 +45240,Other,43,Diploma,7,60,1,36,96,8.0,1,46,Semi-Urban,Software Engineer,32002,0 +45241,Male,46,Diploma,4,94,39,44,85,2.0,1,9,Urban,Manager,129332,0 +45242,Male,24,High School,14,1,57,80,91,8.0,6,72,Urban,ML Engineer,108678,0 +45243,Female,32,Bachelors,15,16,27,84,72,2.0,6,74,Urban,ML Engineer,87577,0 +45244,Other,46,Diploma,9,6,5,18,5,5.0,1,61,Urban,Manager,45529,0 +45245,Female,58,Bachelors,7,87,37,79,69,8.0,2,52,Urban,HR Executive,58006,1 +45246,Male,29,Diploma,7,14,56,69,39,0.0,1,25,Semi-Urban,Data Analyst,64864,0 +45247,Male,22,Masters,8,55,81,42,66,4.0,5,41,Urban,Software Engineer,65916,0 +45248,Male,52,Masters,14,88,19,51,63,8.0,6,54,Urban,ML Engineer,48156,0 +45249,Male,28,PhD,4,26,98,2,72,3.0,7,50,Semi-Urban,Data Analyst,60333,0 +45250,Male,30,Bachelors,5,50,17,40,31,5.0,1,57,Urban,Manager,133676,0 +45251,Female,34,Diploma,3,70,55,41,38,3.0,7,28,Urban,Data Analyst,22549,0 +45252,Female,27,Bachelors,8,49,27,36,69,1.0,1,20,Semi-Urban,Data Analyst,122502,0 +45253,Female,26,Diploma,16,76,65,43,57,7.0,4,91,Urban,ML Engineer,37791,1 +45254,Male,47,Diploma,16,64,4,19,49,0.0,1,13,Rural,HR Executive,91119,0 +45255,Female,26,Bachelors,15,95,13,56,20,2.0,5,63,Urban,Software Engineer,38443,0 +45256,Male,29,Bachelors,15,92,53,64,66,2.0,6,24,Urban,HR Executive,97477,0 +45257,Male,42,Diploma,13,57,72,25,0,1.0,7,12,Urban,ML Engineer,39638,0 +45258,Male,50,Bachelors,15,51,73,13,68,2.0,2,94,Urban,Manager,87337,0 +45259,Male,47,Bachelors,9,4,80,97,85,8.0,7,27,Semi-Urban,Data Analyst,88905,0 +45260,Male,22,Diploma,6,66,40,74,55,5.0,4,89,Urban,ML Engineer,103600,1 +45261,Male,52,PhD,1,68,33,93,97,2.0,4,62,Rural,HR Executive,114992,1 +45262,Male,43,Diploma,5,59,73,10,4,8.0,7,27,Semi-Urban,Manager,87168,0 +45263,Male,21,Diploma,12,4,84,66,39,8.0,1,1,Semi-Urban,ML Engineer,140040,0 +45264,Male,22,Diploma,4,43,85,21,15,4.0,2,90,Urban,ML Engineer,77011,1 +45265,Female,53,Diploma,6,82,64,72,65,1.0,4,23,Urban,Data Analyst,79328,1 +45266,Female,44,Diploma,14,4,45,73,70,7.0,2,70,Urban,Software Engineer,124125,0 +45267,Other,41,Diploma,5,89,61,89,38,1.0,5,39,Urban,Manager,47037,1 +45268,Female,32,PhD,0,31,59,99,94,2.0,6,13,Urban,HR Executive,35639,0 +45269,Other,59,High School,17,15,50,33,27,9.0,3,56,Semi-Urban,HR Executive,79407,0 +45270,Female,33,Bachelors,3,24,87,30,60,9.0,1,59,Urban,HR Executive,86857,0 +45271,Other,54,Bachelors,0,13,60,78,17,8.0,2,40,Urban,Manager,36523,0 +45272,Female,51,Masters,3,83,70,71,36,7.0,7,53,Semi-Urban,HR Executive,59482,1 +45273,Female,26,Bachelors,7,47,41,6,85,7.0,4,4,Urban,Manager,68289,0 +45274,Male,34,Bachelors,2,10,27,96,48,9.0,0,11,Semi-Urban,Software Engineer,68727,0 +45275,Female,54,High School,5,1,68,13,9,7.0,5,2,Rural,Software Engineer,25434,0 +45276,Female,31,PhD,19,17,16,94,31,6.0,3,59,Rural,Data Analyst,145824,0 +45277,Male,36,Bachelors,9,92,77,34,97,3.0,0,84,Urban,ML Engineer,94745,1 +45278,Male,39,Masters,4,79,91,7,98,7.0,6,6,Semi-Urban,HR Executive,74106,0 +45279,Male,31,Masters,18,8,15,89,74,9.0,6,82,Semi-Urban,ML Engineer,58767,0 +45280,Female,29,Bachelors,2,19,22,23,71,3.0,5,75,Urban,Manager,142528,0 +45281,Female,45,Diploma,13,85,68,26,50,5.0,3,32,Urban,Software Engineer,108518,0 +45282,Male,26,High School,7,57,35,86,34,4.0,1,16,Urban,Data Analyst,118065,0 +45283,Male,58,Bachelors,0,87,44,98,71,1.0,2,24,Urban,Software Engineer,147847,1 +45284,Female,55,PhD,10,92,30,8,91,0.0,1,24,Urban,Manager,99544,0 +45285,Female,39,Bachelors,3,69,68,73,6,5.0,7,25,Urban,Data Analyst,57316,0 +45286,Male,34,Bachelors,10,46,40,2,3,6.0,5,80,Urban,Software Engineer,28449,0 +45287,Female,26,Bachelors,1,93,53,46,85,9.0,4,67,Urban,Software Engineer,55435,1 +45288,Male,23,Bachelors,0,19,67,35,8,4.0,0,60,Rural,HR Executive,30437,0 +45289,Male,23,Diploma,10,48,11,11,65,0.0,3,94,Semi-Urban,Manager,63107,0 +45290,Female,25,PhD,2,3,54,25,72,0.0,7,68,Rural,HR Executive,44122,0 +45291,Female,41,PhD,14,60,83,16,98,0.0,7,55,Semi-Urban,HR Executive,59874,0 +45292,Male,33,Masters,15,53,57,39,17,8.0,6,57,Rural,Manager,139768,0 +45293,Male,25,Diploma,9,84,62,46,62,3.0,7,38,Urban,Software Engineer,139704,0 +45294,Male,56,High School,14,97,36,93,48,7.0,2,60,Rural,Data Analyst,111211,1 +45295,Female,38,Bachelors,19,31,88,22,93,2.0,5,49,Semi-Urban,Manager,49520,0 +45296,Female,56,Bachelors,18,4,16,98,90,0.0,3,63,Urban,Data Analyst,70840,0 +45297,Male,45,Bachelors,16,83,29,40,86,4.0,0,34,Semi-Urban,HR Executive,99573,0 +45298,Male,48,Masters,9,22,93,90,27,0.0,2,42,Urban,Software Engineer,29897,1 +45299,Male,43,Masters,17,37,81,82,65,3.0,0,86,Urban,Data Analyst,29811,1 +45300,Female,45,Bachelors,1,71,62,38,88,2.0,1,68,Rural,ML Engineer,69781,0 +45301,Male,52,High School,7,81,85,54,69,8.0,2,15,Urban,HR Executive,139899,1 +45302,Male,46,Bachelors,12,80,85,30,19,4.0,5,48,Semi-Urban,Manager,98832,1 +45303,Female,34,Bachelors,1,20,56,27,72,1.0,6,59,Urban,ML Engineer,98317,0 +45304,Male,38,Bachelors,2,41,7,49,90,5.0,5,74,Urban,Manager,75930,0 +45305,Male,26,Diploma,2,68,46,68,56,8.0,3,23,Semi-Urban,ML Engineer,99786,0 +45306,Male,44,Bachelors,5,74,16,15,81,5.0,2,76,Semi-Urban,HR Executive,40032,0 +45307,Female,25,Bachelors,11,12,20,88,83,6.0,2,47,Urban,Manager,56422,0 +45308,Female,47,Diploma,15,47,48,66,97,6.0,0,81,Urban,Data Analyst,93429,1 +45309,Male,34,Diploma,12,87,78,23,12,8.0,7,40,Urban,Software Engineer,138240,0 +45310,Male,41,Masters,18,2,2,59,69,3.0,3,23,Urban,HR Executive,88738,0 +45311,Male,41,Masters,17,55,8,10,86,7.0,2,71,Urban,Data Analyst,101973,0 +45312,Male,50,PhD,6,84,2,99,6,3.0,2,16,Semi-Urban,Software Engineer,44497,0 +45313,Male,22,Bachelors,17,72,74,37,13,3.0,2,64,Rural,ML Engineer,22752,1 +45314,Male,37,Masters,11,96,59,25,35,0.0,2,89,Rural,HR Executive,126160,1 +45315,Other,41,Bachelors,18,79,50,77,39,2.0,2,43,Urban,Software Engineer,54312,1 +45316,Female,30,Diploma,5,34,59,36,51,2.0,2,33,Urban,Data Analyst,85629,0 +45317,Female,57,Masters,4,35,45,1,1,1.0,1,49,Semi-Urban,Manager,138505,0 +45318,Female,50,Bachelors,12,46,93,20,36,4.0,1,8,Semi-Urban,Manager,137396,0 +45319,Female,26,High School,7,5,37,22,90,4.0,6,32,Semi-Urban,Manager,147110,0 +45320,Female,34,Masters,1,25,44,85,4,7.0,2,25,Urban,HR Executive,63737,0 +45321,Female,45,Bachelors,17,9,7,49,6,5.0,5,81,Rural,HR Executive,22380,0 +45322,Male,26,Bachelors,1,60,41,43,96,0.0,0,74,Urban,Software Engineer,139935,0 +45323,Male,42,High School,12,19,64,71,44,6.0,2,46,Urban,Software Engineer,121392,0 +45324,Male,58,Bachelors,4,69,3,43,43,2.0,2,19,Urban,Software Engineer,75257,0 +45325,Female,38,Diploma,2,73,29,6,54,9.0,6,74,Semi-Urban,ML Engineer,116887,0 +45326,Male,25,PhD,8,21,32,91,79,7.0,3,28,Rural,Manager,147586,0 +45327,Male,29,Diploma,7,20,33,25,84,0.0,6,78,Urban,Software Engineer,60559,0 +45328,Female,40,Bachelors,19,93,17,65,80,0.0,4,10,Semi-Urban,Data Analyst,115060,0 +45329,Male,58,Bachelors,17,27,17,38,59,9.0,7,66,Rural,Software Engineer,76165,0 +45330,Female,38,PhD,4,12,5,41,94,9.0,0,94,Semi-Urban,ML Engineer,94375,0 +45331,Male,27,Bachelors,14,69,5,8,99,2.0,2,6,Urban,ML Engineer,42202,0 +45332,Female,36,Diploma,1,74,25,13,53,0.0,5,92,Urban,ML Engineer,116903,0 +45333,Female,25,High School,17,41,64,76,23,3.0,5,67,Rural,Data Analyst,95706,1 +45334,Other,22,Masters,9,1,66,12,43,6.0,0,9,Urban,HR Executive,92733,0 +45335,Male,35,Diploma,10,2,35,15,32,4.0,3,61,Urban,Software Engineer,40132,0 +45336,Female,51,Bachelors,19,10,42,96,65,4.0,1,42,Urban,Data Analyst,127650,0 +45337,Male,26,Bachelors,4,19,21,58,36,1.0,7,95,Urban,Manager,58572,0 +45338,Male,41,Bachelors,7,56,16,94,81,2.0,6,32,Urban,HR Executive,43338,0 +45339,Male,35,Bachelors,0,1,54,94,16,3.0,7,2,Urban,ML Engineer,47316,0 +45340,Female,44,Diploma,15,80,12,4,73,3.0,4,50,Urban,Manager,142568,0 +45341,Male,36,Bachelors,11,77,9,99,21,0.0,3,86,Urban,Data Analyst,70946,1 +45342,Male,37,Masters,18,20,24,19,78,5.0,7,93,Urban,ML Engineer,45056,0 +45343,Male,58,Bachelors,13,48,52,71,51,2.0,2,35,Urban,Data Analyst,53124,0 +45344,Male,47,Bachelors,12,1,13,32,57,0.0,7,85,Semi-Urban,Software Engineer,103526,0 +45345,Male,23,Diploma,11,15,80,97,72,1.0,0,0,Rural,Manager,21714,0 +45346,Male,51,Diploma,12,38,36,89,5,8.0,0,39,Urban,ML Engineer,87255,0 +45347,Female,43,Bachelors,4,50,35,81,84,7.0,6,40,Rural,Data Analyst,129080,0 +45348,Male,29,Bachelors,13,65,31,20,10,1.0,0,22,Urban,Software Engineer,40385,0 +45349,Male,33,Bachelors,2,81,18,48,61,4.0,7,91,Semi-Urban,Data Analyst,121928,1 +45350,Female,59,High School,2,81,5,10,15,9.0,0,20,Urban,Manager,141668,0 +45351,Male,35,Diploma,16,70,95,29,89,9.0,1,60,Urban,HR Executive,110328,1 +45352,Male,43,High School,13,95,78,71,72,7.0,5,49,Semi-Urban,Manager,34419,1 +45353,Male,55,High School,2,90,68,43,65,4.0,4,97,Urban,Manager,144955,1 +45354,Female,54,Bachelors,17,84,13,0,71,3.0,3,40,Rural,ML Engineer,30109,0 +45355,Other,38,Bachelors,12,48,42,74,29,1.0,0,28,Urban,ML Engineer,113644,0 +45356,Male,37,Bachelors,14,52,27,1,20,4.0,7,92,Urban,ML Engineer,143265,0 +45357,Male,57,Bachelors,6,41,30,54,25,3.0,1,84,Urban,ML Engineer,25791,0 +45358,Male,51,Bachelors,19,13,30,82,64,8.0,2,24,Urban,Data Analyst,68101,0 +45359,Male,50,Bachelors,9,91,87,45,54,2.0,5,3,Rural,Manager,117390,0 +45360,Male,46,Masters,15,45,56,4,59,0.0,4,73,Urban,ML Engineer,33942,0 +45361,Female,34,Bachelors,16,13,77,66,61,6.0,7,75,Semi-Urban,Data Analyst,71585,0 +45362,Male,56,Bachelors,16,45,29,28,90,1.0,7,41,Urban,Manager,139002,0 +45363,Female,59,Bachelors,10,42,51,24,55,5.0,3,94,Urban,Manager,43917,0 +45364,Male,22,Bachelors,5,46,48,29,12,4.0,2,13,Urban,HR Executive,58740,0 +45365,Female,32,High School,3,19,53,43,7,6.0,4,88,Semi-Urban,Manager,129222,0 +45366,Male,51,High School,19,68,0,43,23,1.0,0,60,Semi-Urban,HR Executive,41898,0 +45367,Female,39,Bachelors,1,46,89,35,69,8.0,0,87,Rural,ML Engineer,29801,1 +45368,Female,32,Bachelors,0,91,38,77,86,3.0,6,95,Rural,ML Engineer,148268,1 +45369,Female,30,Bachelors,1,27,62,41,42,0.0,5,81,Urban,Software Engineer,116463,0 +45370,Male,59,Diploma,13,10,37,46,71,0.0,7,34,Semi-Urban,HR Executive,52839,0 +45371,Male,39,Bachelors,14,41,21,76,69,3.0,3,90,Rural,ML Engineer,145201,0 +45372,Female,53,Masters,16,98,64,82,15,6.0,4,2,Urban,Data Analyst,104450,1 +45373,Female,30,Bachelors,3,67,9,76,52,2.0,7,17,Rural,HR Executive,75876,0 +45374,Male,27,Diploma,2,19,85,38,95,2.0,6,4,Rural,HR Executive,120256,0 +45375,Male,30,Diploma,14,64,97,58,33,4.0,0,41,Urban,ML Engineer,23208,1 +45376,Male,27,Bachelors,3,87,40,6,61,2.0,3,25,Urban,Data Analyst,27075,0 +45377,Female,44,Masters,19,51,71,38,54,9.0,3,66,Urban,HR Executive,149184,0 +45378,Female,30,Diploma,10,84,56,86,31,3.0,4,53,Rural,Manager,99757,1 +45379,Female,53,Bachelors,14,0,8,33,26,5.0,3,96,Urban,Data Analyst,58751,0 +45380,Male,32,Bachelors,15,0,31,9,44,8.0,2,24,Urban,Manager,104967,0 +45381,Male,46,Diploma,4,97,2,23,33,1.0,4,90,Rural,Software Engineer,27305,0 +45382,Female,41,Diploma,6,65,50,96,7,8.0,7,99,Urban,ML Engineer,136826,1 +45383,Male,39,Bachelors,16,83,26,90,51,5.0,2,19,Semi-Urban,Data Analyst,65149,0 +45384,Male,57,Bachelors,15,24,81,27,60,2.0,1,41,Rural,ML Engineer,24441,0 +45385,Male,58,Bachelors,7,19,32,95,13,8.0,1,26,Urban,Data Analyst,93327,0 +45386,Male,32,Masters,12,54,47,89,81,4.0,1,49,Semi-Urban,Manager,24007,1 +45387,Female,34,Bachelors,17,82,93,60,84,5.0,4,82,Urban,Data Analyst,116359,1 +45388,Male,39,Diploma,0,50,7,35,33,2.0,3,33,Rural,ML Engineer,139894,0 +45389,Male,21,Bachelors,1,89,46,59,19,4.0,5,28,Urban,ML Engineer,127530,0 +45390,Male,23,PhD,0,74,92,16,38,7.0,1,23,Semi-Urban,Software Engineer,72776,0 +45391,Female,25,Bachelors,15,99,4,95,35,5.0,6,18,Semi-Urban,Software Engineer,38687,0 +45392,Male,43,Bachelors,17,83,85,80,84,4.0,2,3,Semi-Urban,ML Engineer,98068,1 +45393,Female,50,Bachelors,16,39,81,16,93,9.0,4,39,Rural,ML Engineer,115333,0 +45394,Male,23,Bachelors,9,6,87,7,28,1.0,7,94,Urban,ML Engineer,83106,0 +45395,Male,49,High School,10,84,24,56,71,3.0,4,30,Urban,HR Executive,120424,0 +45396,Male,48,Bachelors,4,88,18,92,34,7.0,4,97,Urban,ML Engineer,73813,1 +45397,Other,32,Diploma,8,34,64,81,17,5.0,1,70,Urban,HR Executive,88960,1 +45398,Male,32,Diploma,9,7,34,91,33,5.0,2,46,Urban,Data Analyst,120292,0 +45399,Female,32,Bachelors,17,93,57,93,70,9.0,1,30,Semi-Urban,ML Engineer,137003,1 +45400,Female,25,Masters,14,61,92,91,16,0.0,7,27,Rural,ML Engineer,132659,1 +45401,Male,22,Masters,8,18,31,53,41,8.0,0,45,Urban,ML Engineer,139491,0 +45402,Female,48,Masters,12,15,74,57,61,8.0,5,32,Semi-Urban,ML Engineer,113769,0 +45403,Male,21,Bachelors,9,17,35,72,1,9.0,1,15,Rural,HR Executive,118589,0 +45404,Male,57,Bachelors,6,46,41,9,70,6.0,2,60,Semi-Urban,Manager,48733,0 +45405,Male,47,Masters,9,7,39,20,36,7.0,0,12,Semi-Urban,Manager,146601,0 +45406,Female,35,Bachelors,16,81,61,93,72,8.0,3,40,Urban,HR Executive,62459,1 +45407,Male,31,PhD,16,85,11,17,86,2.0,0,41,Rural,ML Engineer,53101,0 +45408,Male,57,Masters,9,16,18,21,24,5.0,2,2,Urban,Software Engineer,103547,0 +45409,Male,44,Masters,0,94,94,44,60,4.0,3,24,Semi-Urban,Manager,95334,1 +45410,Male,43,Masters,16,95,83,17,73,9.0,7,43,Urban,Data Analyst,137396,1 +45411,Female,56,High School,16,12,48,19,20,2.0,7,78,Semi-Urban,HR Executive,119648,0 +45412,Male,51,Masters,0,77,90,16,54,3.0,3,70,Urban,HR Executive,141193,1 +45413,Female,43,Bachelors,4,31,67,91,66,9.0,5,16,Urban,ML Engineer,137295,0 +45414,Female,36,Bachelors,15,52,60,91,60,9.0,7,70,Urban,ML Engineer,144079,1 +45415,Female,23,Bachelors,15,28,3,55,33,5.0,2,55,Semi-Urban,Data Analyst,141860,0 +45416,Male,35,Bachelors,5,83,3,19,68,1.0,3,33,Urban,Software Engineer,100118,0 +45417,Male,30,Bachelors,10,90,38,8,40,4.0,1,7,Urban,Data Analyst,69160,0 +45418,Male,29,Bachelors,19,31,91,4,44,0.0,4,75,Urban,Software Engineer,20563,0 +45419,Male,58,Masters,3,27,42,95,14,9.0,5,47,Urban,Data Analyst,62730,0 +45420,Male,33,Diploma,12,26,25,8,66,9.0,0,63,Urban,Manager,101943,0 +45421,Male,37,PhD,6,25,63,94,68,1.0,0,69,Urban,Data Analyst,80983,1 +45422,Other,27,Bachelors,13,70,20,29,14,0.0,5,72,Urban,Manager,65215,0 +45423,Male,47,High School,5,83,57,48,84,9.0,2,83,Urban,Software Engineer,113489,1 +45424,Male,58,Bachelors,16,9,68,76,30,2.0,7,73,Semi-Urban,ML Engineer,39297,0 +45425,Female,32,Bachelors,3,65,67,40,50,7.0,7,87,Urban,Software Engineer,96199,1 +45426,Male,52,PhD,12,78,90,2,33,8.0,1,38,Semi-Urban,ML Engineer,40809,0 +45427,Male,57,Masters,6,71,28,56,77,8.0,7,51,Urban,Software Engineer,87254,0 +45428,Male,53,Masters,2,57,44,27,33,4.0,6,21,Urban,Data Analyst,65665,0 +45429,Male,34,Masters,1,42,46,21,79,7.0,7,96,Rural,Data Analyst,31505,0 +45430,Male,44,Bachelors,2,28,41,55,12,8.0,4,37,Rural,HR Executive,79625,0 +45431,Male,30,Bachelors,10,88,30,86,95,9.0,4,84,Semi-Urban,Software Engineer,86318,1 +45432,Male,52,Bachelors,1,75,58,91,55,8.0,3,27,Urban,HR Executive,27399,1 +45433,Male,32,PhD,18,65,57,85,30,1.0,6,54,Semi-Urban,HR Executive,73337,1 +45434,Male,37,Bachelors,8,28,22,70,39,8.0,3,23,Semi-Urban,Manager,70877,0 +45435,Female,49,Bachelors,2,32,77,3,66,7.0,3,57,Rural,ML Engineer,34820,0 +45436,Male,22,Diploma,7,41,3,16,94,0.0,3,7,Urban,Software Engineer,122014,0 +45437,Male,55,Masters,18,23,80,89,34,2.0,7,99,Urban,Manager,87054,1 +45438,Female,55,Masters,19,93,26,27,78,6.0,1,30,Semi-Urban,Software Engineer,63307,0 +45439,Female,33,Diploma,4,75,54,74,64,7.0,5,22,Semi-Urban,Software Engineer,123446,0 +45440,Male,37,Bachelors,17,95,13,83,33,3.0,2,55,Semi-Urban,ML Engineer,26409,1 +45441,Other,47,Bachelors,6,3,3,51,22,8.0,4,45,Urban,Manager,60328,0 +45442,Female,28,Masters,4,28,99,58,81,9.0,0,35,Rural,ML Engineer,82880,0 +45443,Male,38,Diploma,13,48,90,67,18,1.0,0,53,Semi-Urban,Data Analyst,57953,1 +45444,Other,21,Masters,11,93,2,66,84,7.0,5,44,Rural,Software Engineer,116627,0 +45445,Male,57,Masters,12,63,30,60,92,6.0,4,7,Urban,Data Analyst,36814,0 +45446,Other,43,Bachelors,5,41,91,60,42,1.0,0,53,Semi-Urban,ML Engineer,92508,1 +45447,Male,30,Bachelors,5,41,23,19,39,7.0,4,90,Semi-Urban,Data Analyst,25134,0 +45448,Male,46,Bachelors,7,16,55,47,4,0.0,4,24,Urban,Data Analyst,111996,0 +45449,Female,36,Bachelors,11,71,85,93,81,2.0,7,57,Rural,Data Analyst,145293,1 +45450,Male,28,Bachelors,2,57,88,60,33,0.0,6,24,Urban,Manager,145445,0 +45451,Male,52,Diploma,5,78,68,24,61,6.0,0,35,Urban,Software Engineer,48885,0 +45452,Female,21,Bachelors,9,12,47,98,36,5.0,1,24,Rural,Software Engineer,52882,0 +45453,Male,42,Masters,2,96,68,82,20,9.0,5,45,Semi-Urban,ML Engineer,144045,1 +45454,Female,35,Diploma,19,26,11,14,57,7.0,7,4,Urban,ML Engineer,149069,0 +45455,Male,49,Diploma,11,66,39,76,51,9.0,2,62,Semi-Urban,Manager,39988,1 +45456,Female,58,Diploma,3,31,42,41,23,9.0,1,65,Urban,Manager,76872,0 +45457,Male,48,Bachelors,3,42,87,63,85,2.0,1,82,Semi-Urban,Software Engineer,126912,1 +45458,Male,24,Bachelors,16,59,79,81,12,4.0,5,80,Rural,Software Engineer,70171,1 +45459,Male,45,Masters,10,10,66,81,45,6.0,6,31,Urban,Data Analyst,116234,0 +45460,Female,47,Masters,1,4,23,79,1,9.0,1,21,Urban,Software Engineer,101935,0 +45461,Male,39,Bachelors,16,40,79,7,93,5.0,7,97,Semi-Urban,ML Engineer,55345,0 +45462,Male,26,High School,4,76,52,48,69,4.0,2,97,Urban,Software Engineer,126861,1 +45463,Male,41,High School,11,53,49,18,92,5.0,2,72,Rural,ML Engineer,24040,0 +45464,Male,45,Masters,12,18,4,40,95,6.0,6,25,Urban,Manager,98390,0 +45465,Male,41,Bachelors,18,67,62,72,89,3.0,4,53,Urban,Software Engineer,65631,1 +45466,Female,29,Bachelors,2,73,46,11,7,0.0,6,76,Semi-Urban,Software Engineer,51309,0 +45467,Male,54,PhD,0,62,57,39,34,4.0,4,73,Urban,Manager,120347,0 +45468,Male,57,Masters,10,70,72,97,32,0.0,4,24,Semi-Urban,Data Analyst,51400,1 +45469,Female,52,High School,19,50,49,31,64,7.0,5,36,Urban,ML Engineer,68088,0 +45470,Female,55,High School,14,36,52,93,81,8.0,7,43,Semi-Urban,Manager,121014,0 +45471,Female,38,High School,18,95,10,39,62,0.0,7,56,Semi-Urban,ML Engineer,92798,0 +45472,Female,46,Bachelors,15,52,50,20,5,1.0,4,2,Urban,HR Executive,131717,0 +45473,Male,33,Bachelors,12,85,33,26,22,6.0,0,75,Semi-Urban,Manager,22171,0 +45474,Other,25,Masters,3,86,91,45,39,6.0,4,52,Rural,Software Engineer,27270,1 +45475,Male,53,Masters,14,47,90,63,48,7.0,7,51,Semi-Urban,Manager,44438,1 +45476,Female,39,Diploma,15,98,50,35,6,9.0,3,36,Urban,Software Engineer,49349,0 +45477,Male,31,Bachelors,16,69,26,91,51,8.0,6,78,Rural,Manager,107088,1 +45478,Male,27,Bachelors,17,92,63,14,7,3.0,4,76,Semi-Urban,HR Executive,111883,1 +45479,Female,43,High School,4,16,5,20,86,3.0,3,3,Semi-Urban,HR Executive,136744,0 +45480,Female,25,Diploma,16,69,45,28,27,3.0,3,47,Semi-Urban,Manager,85801,0 +45481,Female,45,Bachelors,2,19,61,8,36,0.0,0,24,Semi-Urban,HR Executive,28912,0 +45482,Male,24,Bachelors,15,32,3,52,99,1.0,3,41,Rural,Software Engineer,128069,0 +45483,Male,59,Masters,8,26,33,62,30,6.0,5,7,Semi-Urban,Software Engineer,20007,0 +45484,Female,48,Bachelors,11,34,44,75,58,9.0,2,11,Rural,Software Engineer,146222,0 +45485,Male,43,Bachelors,8,50,77,26,29,8.0,6,2,Urban,Software Engineer,86307,0 +45486,Female,41,Masters,19,89,85,14,74,6.0,0,86,Urban,Software Engineer,38220,1 +45487,Male,46,Bachelors,11,21,29,44,61,5.0,1,92,Urban,HR Executive,42561,0 +45488,Male,26,Bachelors,19,18,71,17,1,6.0,4,90,Urban,Manager,137720,0 +45489,Female,22,Masters,14,81,4,44,87,8.0,4,20,Urban,HR Executive,69259,0 +45490,Female,51,High School,10,96,13,7,92,0.0,5,45,Urban,HR Executive,37526,0 +45491,Female,54,Bachelors,2,90,97,30,3,4.0,4,50,Urban,HR Executive,39706,1 +45492,Male,58,Bachelors,2,91,78,68,30,9.0,2,55,Urban,HR Executive,32163,1 +45493,Female,41,Bachelors,12,72,64,75,11,9.0,2,79,Urban,HR Executive,116960,1 +45494,Other,54,Bachelors,5,26,57,33,55,9.0,1,88,Urban,Software Engineer,137606,0 +45495,Female,47,Bachelors,17,10,2,59,25,7.0,7,72,Rural,Data Analyst,118633,0 +45496,Female,54,Masters,16,46,41,8,27,9.0,5,92,Rural,Manager,24275,0 +45497,Female,34,Masters,14,52,73,15,69,0.0,0,58,Semi-Urban,ML Engineer,38584,0 +45498,Male,38,Bachelors,2,53,18,95,32,0.0,7,94,Rural,Manager,114319,1 +45499,Male,41,High School,0,8,40,40,3,2.0,6,92,Rural,HR Executive,30981,0 +45500,Female,45,High School,7,11,51,58,53,5.0,4,31,Semi-Urban,Software Engineer,53617,0 +45501,Female,29,Diploma,13,11,51,65,26,4.0,0,58,Urban,Software Engineer,63831,0 +45502,Male,54,High School,3,29,90,28,13,9.0,4,2,Urban,Data Analyst,26249,0 +45503,Female,29,Bachelors,14,57,83,19,55,1.0,3,77,Urban,HR Executive,125000,0 +45504,Female,41,Bachelors,13,9,40,70,37,8.0,1,50,Urban,HR Executive,22241,0 +45505,Male,36,Diploma,14,31,94,78,24,6.0,2,23,Urban,Data Analyst,116806,0 +45506,Male,38,Bachelors,2,0,31,32,92,3.0,3,70,Urban,Manager,146498,0 +45507,Female,25,Bachelors,19,54,43,73,91,1.0,2,41,Semi-Urban,HR Executive,111514,0 +45508,Male,46,Bachelors,5,79,2,73,43,6.0,5,38,Urban,Manager,38111,0 +45509,Male,51,High School,0,22,9,1,44,3.0,2,56,Semi-Urban,Data Analyst,24385,0 +45510,Female,25,Bachelors,8,3,79,48,55,6.0,3,3,Semi-Urban,Data Analyst,99555,0 +45511,Female,21,Bachelors,5,29,69,79,74,8.0,0,17,Semi-Urban,Software Engineer,80066,0 +45512,Male,35,Diploma,12,62,21,53,71,4.0,1,18,Urban,Software Engineer,113792,0 +45513,Female,49,Masters,4,61,19,94,70,5.0,6,40,Rural,Manager,140546,0 +45514,Male,45,High School,3,78,78,40,51,3.0,3,65,Urban,Data Analyst,91497,1 +45515,Male,58,Diploma,3,48,94,35,29,3.0,0,21,Semi-Urban,Manager,83457,0 +45516,Female,51,Masters,9,45,44,96,88,7.0,6,6,Urban,HR Executive,131122,0 +45517,Female,45,Masters,1,38,76,50,6,0.0,3,9,Urban,HR Executive,121454,0 +45518,Male,24,High School,11,59,61,22,80,3.0,5,42,Urban,ML Engineer,83662,0 +45519,Male,30,High School,2,0,69,52,44,9.0,2,28,Urban,HR Executive,31391,0 +45520,Female,43,Diploma,8,82,22,26,8,8.0,1,4,Rural,HR Executive,87576,0 +45521,Female,59,Bachelors,18,22,54,35,86,6.0,6,92,Urban,HR Executive,33596,0 +45522,Male,58,Masters,11,90,21,97,74,4.0,2,17,Urban,Data Analyst,32125,0 +45523,Male,21,High School,6,17,99,42,89,5.0,3,12,Urban,Data Analyst,94201,0 +45524,Male,45,Masters,16,40,20,26,92,8.0,5,30,Semi-Urban,HR Executive,66499,0 +45525,Male,35,Masters,12,70,48,68,27,0.0,6,82,Semi-Urban,Software Engineer,128148,1 +45526,Male,24,High School,17,5,56,67,21,2.0,2,24,Urban,HR Executive,74797,0 +45527,Male,21,Diploma,9,90,25,80,55,8.0,4,58,Rural,HR Executive,77350,1 +45528,Male,34,Bachelors,9,61,10,10,24,6.0,4,68,Semi-Urban,Software Engineer,116522,0 +45529,Male,36,PhD,10,91,19,63,89,9.0,3,46,Urban,Data Analyst,94367,0 +45530,Male,31,High School,14,75,62,86,86,1.0,6,67,Semi-Urban,Manager,131789,1 +45531,Male,26,PhD,4,94,20,14,95,0.0,1,56,Urban,Software Engineer,103249,0 +45532,Female,41,Bachelors,18,95,1,59,6,7.0,3,16,Semi-Urban,HR Executive,125649,0 +45533,Male,52,Bachelors,1,51,0,43,2,5.0,5,14,Urban,Data Analyst,84949,0 +45534,Female,59,Diploma,15,16,81,78,22,7.0,1,7,Urban,Software Engineer,26194,0 +45535,Female,48,High School,5,76,89,62,11,7.0,3,94,Semi-Urban,Data Analyst,119959,1 +45536,Male,49,Bachelors,15,81,2,32,99,6.0,1,88,Urban,Manager,25905,0 +45537,Male,42,Masters,19,1,33,52,90,3.0,6,37,Rural,Data Analyst,30713,0 +45538,Female,56,High School,6,44,60,67,39,7.0,5,87,Urban,HR Executive,114888,1 +45539,Male,53,Bachelors,9,80,53,0,37,1.0,3,29,Urban,Software Engineer,53217,0 +45540,Male,35,High School,7,45,87,56,7,9.0,0,73,Rural,Data Analyst,89410,1 +45541,Female,25,High School,19,51,36,89,45,0.0,5,32,Semi-Urban,HR Executive,43358,0 +45542,Male,33,Bachelors,2,50,36,19,78,7.0,0,87,Rural,ML Engineer,103348,0 +45543,Female,22,PhD,2,28,33,30,90,1.0,6,89,Semi-Urban,HR Executive,50322,0 +45544,Female,26,Bachelors,7,87,76,67,61,1.0,3,92,Semi-Urban,Software Engineer,107261,1 +45545,Male,43,Bachelors,10,27,80,43,52,4.0,7,40,Semi-Urban,ML Engineer,49322,0 +45546,Male,35,Bachelors,3,63,76,93,30,9.0,6,13,Rural,Data Analyst,67805,1 +45547,Male,26,Bachelors,13,5,65,32,26,8.0,3,96,Urban,Manager,104389,0 +45548,Other,42,Masters,9,25,26,75,48,9.0,1,92,Urban,Data Analyst,135512,0 +45549,Male,33,Masters,11,30,8,80,34,4.0,4,23,Urban,ML Engineer,129505,0 +45550,Male,33,High School,14,36,85,32,89,8.0,1,21,Rural,Software Engineer,91633,0 +45551,Male,57,PhD,0,82,77,10,45,9.0,5,4,Urban,Data Analyst,67528,0 +45552,Male,56,Masters,2,87,69,23,62,9.0,6,20,Urban,Manager,38980,0 +45553,Male,29,Bachelors,3,39,70,37,48,9.0,1,94,Semi-Urban,HR Executive,31604,1 +45554,Male,25,Bachelors,10,84,54,45,82,4.0,5,21,Urban,ML Engineer,96971,0 +45555,Male,24,Bachelors,7,26,82,62,87,6.0,1,42,Rural,HR Executive,73228,0 +45556,Other,30,Masters,0,56,27,10,36,0.0,4,65,Urban,Data Analyst,127231,0 +45557,Female,51,Diploma,18,53,57,46,20,0.0,4,41,Rural,Manager,56412,0 +45558,Female,28,Bachelors,15,49,76,27,27,9.0,6,19,Urban,Data Analyst,67554,0 +45559,Male,44,Bachelors,9,24,64,95,42,5.0,7,75,Urban,HR Executive,43892,1 +45560,Male,46,High School,13,3,46,55,3,3.0,5,55,Semi-Urban,HR Executive,28103,0 +45561,Female,31,Bachelors,0,39,39,58,66,1.0,4,9,Semi-Urban,Manager,24909,0 +45562,Male,26,Diploma,0,34,89,87,61,5.0,1,75,Urban,HR Executive,90974,1 +45563,Male,53,High School,15,6,41,41,28,4.0,1,55,Urban,Manager,84589,0 +45564,Male,47,Masters,18,76,14,22,78,3.0,1,5,Semi-Urban,Software Engineer,84044,0 +45565,Male,34,PhD,3,54,76,72,54,2.0,7,67,Urban,Software Engineer,22630,1 +45566,Male,44,Masters,14,27,42,66,70,2.0,1,34,Semi-Urban,ML Engineer,97336,0 +45567,Male,54,Diploma,10,78,25,38,83,5.0,0,70,Urban,HR Executive,91082,0 +45568,Male,43,Bachelors,13,74,47,10,61,8.0,5,75,Urban,Software Engineer,98224,0 +45569,Female,47,Masters,18,9,75,70,59,8.0,3,31,Urban,HR Executive,114376,0 +45570,Male,28,Bachelors,3,91,2,75,94,6.0,6,94,Urban,Software Engineer,56631,1 +45571,Female,34,Diploma,8,2,69,16,41,9.0,5,11,Urban,HR Executive,74788,0 +45572,Female,28,Bachelors,17,27,55,18,35,9.0,3,81,Semi-Urban,Manager,109430,0 +45573,Female,56,Bachelors,18,91,76,30,21,9.0,1,24,Semi-Urban,Data Analyst,40567,0 +45574,Other,41,Bachelors,2,85,3,83,10,3.0,6,79,Urban,HR Executive,36237,1 +45575,Male,49,Bachelors,10,92,91,68,98,1.0,5,34,Urban,Manager,102079,1 +45576,Female,42,Bachelors,1,0,50,1,32,3.0,7,81,Semi-Urban,HR Executive,130903,0 +45577,Female,33,Masters,19,96,86,90,82,4.0,4,24,Urban,Manager,141808,1 +45578,Male,44,High School,6,81,69,62,23,1.0,2,76,Semi-Urban,HR Executive,49119,1 +45579,Male,41,Bachelors,16,37,71,19,1,9.0,7,73,Semi-Urban,Software Engineer,126397,0 +45580,Male,30,Bachelors,3,86,44,53,62,5.0,6,36,Urban,ML Engineer,58208,0 +45581,Male,29,Bachelors,18,84,88,90,94,0.0,7,10,Urban,Manager,111021,1 +45582,Female,58,Bachelors,5,19,93,89,88,7.0,0,53,Urban,HR Executive,58160,1 +45583,Male,54,Diploma,10,93,76,7,17,9.0,6,1,Semi-Urban,HR Executive,71606,0 +45584,Male,21,Bachelors,17,17,4,27,19,5.0,4,69,Urban,HR Executive,52447,0 +45585,Female,26,High School,6,90,37,9,51,6.0,1,73,Urban,HR Executive,60713,0 +45586,Male,53,High School,19,66,57,38,43,0.0,6,43,Rural,HR Executive,52821,0 +45587,Female,29,High School,1,66,15,82,0,2.0,3,12,Urban,Software Engineer,145659,0 +45588,Other,29,Diploma,9,54,0,95,50,8.0,7,94,Rural,HR Executive,48599,1 +45589,Female,33,Masters,5,78,5,38,84,3.0,1,5,Urban,Manager,125413,0 +45590,Female,30,Diploma,16,12,74,86,9,6.0,4,57,Urban,ML Engineer,50612,0 +45591,Female,59,Diploma,8,32,15,55,6,0.0,4,33,Urban,ML Engineer,38106,0 +45592,Female,41,Masters,18,88,27,38,64,7.0,2,69,Urban,ML Engineer,101279,0 +45593,Male,50,Bachelors,8,39,1,94,44,7.0,5,65,Semi-Urban,ML Engineer,88485,0 +45594,Male,43,Masters,19,85,61,91,0,3.0,7,60,Urban,Software Engineer,34139,1 +45595,Male,33,High School,15,21,18,63,73,3.0,3,62,Urban,Software Engineer,88485,0 +45596,Female,46,High School,6,7,18,82,58,0.0,0,15,Semi-Urban,ML Engineer,131131,0 +45597,Female,21,Masters,10,99,71,18,76,0.0,0,10,Urban,Software Engineer,87194,0 +45598,Male,58,Bachelors,3,46,14,51,24,6.0,6,19,Urban,ML Engineer,35959,0 +45599,Female,35,Masters,17,45,95,45,2,1.0,3,58,Urban,Software Engineer,117755,1 +45600,Female,45,Diploma,15,44,84,19,17,3.0,4,64,Urban,Manager,36553,0 +45601,Female,31,Bachelors,19,57,15,7,7,6.0,3,95,Urban,Data Analyst,55828,0 +45602,Male,23,Masters,1,42,14,64,88,8.0,1,2,Urban,ML Engineer,22016,0 +45603,Male,25,Bachelors,2,10,64,62,5,5.0,4,2,Urban,ML Engineer,134608,0 +45604,Male,44,Masters,0,10,0,15,52,8.0,3,95,Urban,Software Engineer,122228,0 +45605,Male,37,Masters,3,32,58,24,4,8.0,7,75,Urban,Software Engineer,141253,0 +45606,Male,40,High School,7,19,93,16,91,2.0,5,51,Rural,HR Executive,87798,0 +45607,Female,41,Bachelors,19,52,19,38,97,1.0,0,18,Semi-Urban,Manager,85619,0 +45608,Male,54,Bachelors,6,89,54,86,27,0.0,5,52,Urban,ML Engineer,123529,1 +45609,Male,30,Masters,9,44,79,90,0,1.0,6,18,Urban,Data Analyst,95584,0 +45610,Female,39,Diploma,19,60,76,70,74,8.0,3,85,Semi-Urban,Software Engineer,147217,1 +45611,Male,27,Bachelors,8,41,64,24,79,3.0,7,58,Semi-Urban,Software Engineer,61310,0 +45612,Female,36,Bachelors,7,28,66,39,13,0.0,3,57,Urban,Manager,56721,0 +45613,Female,34,Bachelors,1,42,6,5,46,0.0,4,17,Rural,Data Analyst,93269,0 +45614,Female,28,Bachelors,2,94,16,6,99,5.0,0,47,Urban,Software Engineer,84836,0 +45615,Female,24,Diploma,17,39,75,40,20,6.0,0,50,Rural,HR Executive,73097,0 +45616,Female,59,High School,19,63,4,97,51,3.0,1,33,Urban,Software Engineer,64346,0 +45617,Male,46,High School,10,80,68,52,40,7.0,4,70,Semi-Urban,Manager,139434,1 +45618,Male,30,Diploma,9,96,59,5,45,4.0,4,71,Urban,Data Analyst,76441,0 +45619,Male,31,Bachelors,12,6,94,66,56,6.0,0,43,Urban,Manager,89771,0 +45620,Male,22,High School,17,28,22,14,94,8.0,7,27,Urban,HR Executive,69403,0 +45621,Male,38,Bachelors,4,23,61,71,4,6.0,7,77,Urban,Software Engineer,65937,0 +45622,Male,44,Bachelors,0,9,13,19,63,2.0,0,82,Urban,Data Analyst,70834,0 +45623,Female,48,Masters,9,73,3,29,90,9.0,5,14,Urban,Manager,96735,0 +45624,Female,59,Bachelors,7,45,55,20,0,5.0,6,2,Urban,ML Engineer,139895,0 +45625,Male,29,Diploma,8,14,37,76,69,7.0,4,65,Semi-Urban,Software Engineer,136096,0 +45626,Male,26,Masters,1,96,18,64,32,6.0,6,63,Semi-Urban,Software Engineer,73813,1 +45627,Female,29,Diploma,5,88,47,81,75,3.0,4,89,Rural,Manager,63678,1 +45628,Female,58,PhD,16,6,32,70,25,7.0,7,2,Urban,ML Engineer,146142,0 +45629,Male,35,Masters,3,35,53,81,82,3.0,5,13,Urban,ML Engineer,30778,0 +45630,Male,25,Bachelors,8,64,98,9,73,6.0,2,59,Rural,HR Executive,41698,0 +45631,Male,41,Diploma,5,18,96,10,86,3.0,4,55,Urban,Manager,71512,0 +45632,Male,36,Bachelors,2,29,7,19,30,2.0,3,26,Urban,Software Engineer,127556,0 +45633,Female,42,Bachelors,3,67,33,48,11,4.0,1,33,Semi-Urban,ML Engineer,24847,0 +45634,Male,51,Masters,2,93,33,91,62,2.0,1,21,Urban,ML Engineer,108672,1 +45635,Male,24,High School,17,93,78,90,84,3.0,0,78,Semi-Urban,HR Executive,109225,1 +45636,Male,28,Bachelors,18,68,14,13,78,2.0,5,55,Rural,Data Analyst,85223,0 +45637,Female,25,Diploma,12,84,66,97,29,0.0,5,70,Urban,Manager,115736,1 +45638,Male,35,Bachelors,6,1,77,91,32,8.0,3,1,Urban,Data Analyst,23245,0 +45639,Male,40,Bachelors,12,79,48,38,98,6.0,7,14,Rural,ML Engineer,145303,0 +45640,Female,47,Bachelors,13,75,1,89,4,0.0,3,80,Urban,ML Engineer,55089,1 +45641,Female,24,Diploma,9,23,45,82,53,0.0,1,65,Rural,Manager,88951,0 +45642,Female,59,High School,7,1,87,91,99,2.0,3,53,Urban,Software Engineer,132922,0 +45643,Male,25,Masters,18,69,18,47,39,5.0,1,61,Urban,ML Engineer,65066,0 +45644,Other,59,Bachelors,8,39,23,17,84,7.0,6,46,Semi-Urban,HR Executive,99100,0 +45645,Male,42,Masters,12,23,15,20,71,4.0,2,45,Urban,Manager,69010,0 +45646,Male,52,High School,18,76,59,98,72,4.0,2,81,Semi-Urban,Software Engineer,98112,1 +45647,Male,48,Bachelors,6,76,3,77,28,6.0,0,91,Rural,Manager,149718,1 +45648,Male,48,High School,17,47,96,12,66,3.0,7,68,Urban,Manager,35503,0 +45649,Male,54,Bachelors,19,7,12,80,88,4.0,2,28,Rural,Manager,80621,0 +45650,Female,23,Masters,9,98,47,69,64,3.0,6,38,Urban,Software Engineer,60031,1 +45651,Male,37,High School,4,37,81,52,33,5.0,0,59,Urban,Software Engineer,24874,0 +45652,Female,42,Masters,19,37,67,39,64,6.0,0,13,Urban,Software Engineer,46227,0 +45653,Female,31,High School,18,31,83,58,54,8.0,2,71,Urban,Data Analyst,33377,1 +45654,Female,54,Masters,11,78,45,29,58,4.0,0,73,Semi-Urban,Software Engineer,69475,0 +45655,Female,36,Diploma,10,23,56,37,70,5.0,2,49,Urban,HR Executive,91652,0 +45656,Female,38,Bachelors,10,85,76,25,75,3.0,1,45,Semi-Urban,HR Executive,86990,0 +45657,Female,46,Diploma,12,23,64,66,95,4.0,6,88,Semi-Urban,Manager,24706,1 +45658,Female,35,Masters,8,77,37,13,53,2.0,1,21,Urban,ML Engineer,32781,0 +45659,Male,54,High School,15,40,44,68,39,6.0,3,80,Urban,ML Engineer,95637,0 +45660,Male,56,High School,16,91,41,68,60,1.0,7,82,Semi-Urban,Data Analyst,137994,1 +45661,Male,23,PhD,13,12,18,23,21,7.0,4,31,Rural,Software Engineer,147278,0 +45662,Female,55,High School,8,41,5,29,92,8.0,7,31,Semi-Urban,Manager,134789,0 +45663,Male,28,High School,9,23,31,96,48,5.0,5,99,Urban,HR Executive,148962,1 +45664,Male,49,Bachelors,4,29,26,62,62,7.0,5,97,Urban,ML Engineer,45080,0 +45665,Male,29,Bachelors,19,16,25,71,56,7.0,7,53,Urban,ML Engineer,103042,0 +45666,Female,38,Bachelors,19,83,2,52,27,4.0,4,91,Semi-Urban,Manager,136585,0 +45667,Other,37,Diploma,15,9,55,59,80,2.0,1,51,Rural,Data Analyst,131101,0 +45668,Female,49,Bachelors,1,5,26,2,97,3.0,1,88,Urban,Data Analyst,43248,0 +45669,Female,58,Diploma,6,16,72,30,29,9.0,3,94,Urban,Manager,128418,0 +45670,Male,40,Diploma,17,48,58,77,64,9.0,5,74,Rural,Software Engineer,133264,1 +45671,Male,32,High School,4,72,75,70,25,1.0,7,9,Semi-Urban,HR Executive,131612,0 +45672,Male,59,Masters,13,15,88,99,61,1.0,0,0,Rural,Software Engineer,116003,0 +45673,Male,41,Bachelors,4,92,21,41,71,9.0,6,78,Rural,HR Executive,127340,0 +45674,Male,59,Diploma,19,91,36,51,41,7.0,2,97,Rural,Data Analyst,27842,1 +45675,Female,38,Bachelors,12,96,94,13,41,6.0,3,67,Urban,Software Engineer,115491,1 +45676,Male,25,High School,18,81,86,41,44,2.0,0,69,Semi-Urban,ML Engineer,23652,1 +45677,Male,34,Masters,8,92,64,80,51,4.0,4,11,Urban,Software Engineer,64187,1 +45678,Female,31,Masters,8,98,20,31,28,4.0,5,35,Rural,Software Engineer,76272,0 +45679,Male,53,PhD,9,10,19,71,40,4.0,0,44,Urban,Manager,38444,0 +45680,Male,54,Bachelors,1,15,7,18,57,0.0,6,77,Rural,Data Analyst,38222,0 +45681,Male,23,Bachelors,16,42,24,31,76,2.0,7,51,Rural,Manager,137066,0 +45682,Male,21,Bachelors,0,61,24,27,40,3.0,1,36,Rural,Software Engineer,63924,0 +45683,Female,46,Bachelors,8,64,83,25,35,3.0,1,15,Urban,ML Engineer,40887,0 +45684,Male,44,High School,14,43,30,48,83,1.0,7,83,Urban,ML Engineer,53577,0 +45685,Female,25,High School,17,83,97,57,94,4.0,2,48,Urban,Software Engineer,60917,1 +45686,Female,57,Bachelors,3,17,62,77,69,5.0,5,49,Semi-Urban,ML Engineer,87909,0 +45687,Male,49,Diploma,11,66,2,47,43,7.0,5,91,Urban,Software Engineer,66043,0 +45688,Male,41,High School,13,68,56,26,68,3.0,2,30,Semi-Urban,HR Executive,139535,0 +45689,Female,28,High School,0,61,63,89,22,8.0,2,24,Semi-Urban,ML Engineer,20411,0 +45690,Male,23,High School,9,86,42,1,99,4.0,0,15,Rural,Software Engineer,52006,0 +45691,Male,59,Diploma,7,10,38,75,3,5.0,2,60,Urban,ML Engineer,55174,0 +45692,Female,24,High School,8,5,21,41,94,9.0,0,3,Urban,Manager,142254,0 +45693,Male,39,Diploma,1,48,36,27,4,9.0,0,27,Urban,Manager,42949,0 +45694,Female,24,High School,16,24,91,92,40,4.0,6,31,Urban,Manager,94497,0 +45695,Male,45,PhD,19,2,28,76,80,9.0,0,96,Urban,Data Analyst,129015,0 +45696,Male,41,Masters,13,42,52,62,94,0.0,2,61,Rural,Software Engineer,99068,0 +45697,Female,50,Bachelors,11,51,83,64,84,9.0,3,51,Urban,Manager,45670,1 +45698,Male,54,Bachelors,16,64,54,77,85,7.0,5,86,Semi-Urban,Software Engineer,81236,1 +45699,Male,59,Masters,14,14,4,38,43,4.0,0,48,Urban,Software Engineer,129435,0 +45700,Female,43,Masters,8,88,34,69,59,5.0,4,31,Urban,Software Engineer,41080,0 +45701,Male,52,Bachelors,14,19,55,84,76,8.0,1,20,Semi-Urban,HR Executive,30721,0 +45702,Male,44,Masters,0,42,77,24,11,3.0,5,55,Urban,Software Engineer,78709,0 +45703,Male,59,High School,15,51,88,66,30,2.0,0,84,Rural,Manager,63887,1 +45704,Male,27,PhD,1,33,84,5,57,8.0,7,82,Urban,Software Engineer,77298,0 +45705,Female,23,Diploma,19,98,9,23,51,4.0,5,6,Urban,Data Analyst,39828,0 +45706,Male,48,Bachelors,12,97,30,90,27,8.0,3,35,Urban,Manager,30624,1 +45707,Female,29,Masters,17,12,11,31,11,6.0,6,10,Semi-Urban,Software Engineer,80060,0 +45708,Male,52,High School,4,3,16,37,56,9.0,1,10,Urban,Software Engineer,98204,0 +45709,Female,36,High School,15,73,88,14,55,5.0,7,18,Urban,HR Executive,46814,0 +45710,Male,51,Masters,5,91,26,0,27,6.0,0,72,Urban,Software Engineer,124339,0 +45711,Female,23,Diploma,18,69,65,9,71,4.0,5,46,Urban,HR Executive,106177,0 +45712,Female,58,Bachelors,10,82,63,85,93,4.0,7,60,Semi-Urban,Software Engineer,136858,1 +45713,Male,48,Bachelors,13,91,83,82,34,8.0,3,41,Semi-Urban,ML Engineer,67641,1 +45714,Male,59,Masters,1,55,33,64,49,4.0,3,45,Rural,Software Engineer,60528,0 +45715,Male,32,High School,19,88,40,7,28,9.0,6,78,Rural,Software Engineer,23312,0 +45716,Other,24,Bachelors,5,55,8,36,51,8.0,5,27,Semi-Urban,HR Executive,80585,0 +45717,Female,51,High School,10,74,99,79,48,9.0,0,36,Semi-Urban,Manager,58731,1 +45718,Female,24,High School,5,58,9,62,47,5.0,3,91,Urban,ML Engineer,29565,0 +45719,Female,31,Masters,16,39,30,99,83,7.0,5,4,Rural,Software Engineer,50028,0 +45720,Male,23,Bachelors,18,22,65,57,8,5.0,3,20,Urban,Software Engineer,120767,0 +45721,Male,44,Diploma,11,33,92,16,49,7.0,4,31,Urban,Software Engineer,107379,0 +45722,Female,46,Bachelors,9,58,45,82,97,0.0,4,56,Urban,Manager,130394,1 +45723,Male,27,Bachelors,16,85,85,59,30,7.0,4,0,Urban,HR Executive,117164,0 +45724,Male,28,Diploma,13,40,8,46,61,9.0,3,14,Urban,Data Analyst,101470,0 +45725,Male,45,Diploma,19,66,23,61,17,0.0,3,76,Urban,Manager,89388,0 +45726,Male,45,Diploma,10,56,15,80,7,6.0,7,13,Rural,Manager,56447,0 +45727,Male,24,Bachelors,8,3,86,60,62,7.0,4,62,Urban,ML Engineer,105152,0 +45728,Female,25,PhD,16,67,18,87,77,1.0,0,70,Rural,Data Analyst,85601,1 +45729,Male,26,Masters,13,50,66,32,66,4.0,7,31,Urban,Software Engineer,76572,0 +45730,Male,35,Masters,3,90,43,27,83,9.0,4,0,Urban,HR Executive,60092,0 +45731,Male,25,Bachelors,17,5,34,41,6,2.0,6,5,Rural,HR Executive,29268,0 +45732,Female,37,Diploma,15,89,81,24,67,7.0,4,70,Urban,Data Analyst,34946,1 +45733,Male,23,Diploma,3,83,55,66,46,3.0,7,13,Semi-Urban,Data Analyst,114720,0 +45734,Male,44,Masters,14,77,68,51,45,1.0,4,23,Semi-Urban,HR Executive,85128,0 +45735,Other,59,Bachelors,12,79,31,70,82,5.0,7,99,Urban,Software Engineer,82408,1 +45736,Male,30,High School,4,46,58,20,37,8.0,3,71,Semi-Urban,HR Executive,23453,0 +45737,Male,56,High School,6,53,2,76,42,8.0,6,98,Urban,Software Engineer,90515,0 +45738,Male,59,Masters,1,48,18,71,25,2.0,5,47,Rural,Software Engineer,145209,0 +45739,Male,55,Bachelors,16,65,85,72,85,8.0,4,54,Rural,Manager,64923,1 +45740,Male,23,Bachelors,16,15,52,22,26,8.0,4,47,Semi-Urban,HR Executive,114915,0 +45741,Female,46,Bachelors,15,25,91,29,29,7.0,5,60,Urban,ML Engineer,104922,0 +45742,Male,31,PhD,4,69,60,70,87,1.0,1,12,Semi-Urban,Software Engineer,136914,0 +45743,Female,31,Masters,18,7,31,99,16,0.0,5,53,Urban,Data Analyst,79137,0 +45744,Female,23,High School,3,66,32,38,2,3.0,7,26,Urban,Manager,53493,0 +45745,Male,32,Bachelors,11,76,25,77,98,6.0,2,17,Urban,Manager,130957,0 +45746,Male,27,High School,14,77,46,95,68,9.0,6,20,Semi-Urban,ML Engineer,71359,1 +45747,Female,38,Diploma,1,74,45,28,6,3.0,2,3,Rural,HR Executive,63601,0 +45748,Male,47,Masters,11,60,30,43,92,4.0,6,57,Rural,HR Executive,114694,0 +45749,Female,32,Diploma,16,75,54,76,86,7.0,6,61,Urban,ML Engineer,98717,1 +45750,Female,22,Bachelors,12,9,17,21,10,5.0,1,85,Urban,Manager,70600,0 +45751,Male,45,Bachelors,2,98,18,16,59,9.0,6,69,Rural,Manager,125771,0 +45752,Male,44,Masters,15,17,67,78,73,7.0,7,6,Urban,Data Analyst,41949,0 +45753,Male,45,Diploma,8,90,99,31,35,8.0,0,29,Rural,ML Engineer,120141,1 +45754,Male,29,Bachelors,1,68,25,51,92,5.0,5,15,Rural,HR Executive,104908,0 +45755,Male,44,Bachelors,0,22,53,53,26,3.0,2,44,Urban,HR Executive,143419,0 +45756,Female,47,Bachelors,8,97,77,98,15,1.0,3,62,Rural,HR Executive,59528,1 +45757,Male,52,Bachelors,4,85,19,23,78,4.0,6,89,Urban,HR Executive,143711,0 +45758,Female,56,Bachelors,5,73,9,58,32,3.0,7,63,Semi-Urban,ML Engineer,111964,0 +45759,Male,55,High School,14,4,13,79,9,9.0,4,72,Urban,HR Executive,69160,0 +45760,Female,45,Bachelors,4,66,31,8,90,6.0,1,77,Semi-Urban,ML Engineer,21271,0 +45761,Female,29,PhD,9,10,75,64,11,8.0,4,74,Urban,ML Engineer,67055,0 +45762,Female,52,Diploma,0,75,35,61,64,9.0,5,54,Urban,Software Engineer,100589,0 +45763,Male,26,Masters,9,6,83,83,72,5.0,3,82,Urban,ML Engineer,61545,1 +45764,Male,59,Bachelors,0,53,27,84,13,9.0,6,62,Semi-Urban,ML Engineer,100018,0 +45765,Male,57,Bachelors,12,27,43,0,91,0.0,1,58,Semi-Urban,Data Analyst,59593,0 +45766,Male,55,Bachelors,3,70,33,20,43,9.0,6,93,Urban,ML Engineer,61273,0 +45767,Other,58,Bachelors,4,71,60,91,61,0.0,7,17,Urban,Data Analyst,122763,0 +45768,Male,49,PhD,18,61,54,34,88,5.0,3,39,Urban,ML Engineer,47898,0 +45769,Female,28,High School,0,80,3,7,9,1.0,2,83,Rural,ML Engineer,45321,0 +45770,Female,28,PhD,5,83,42,40,1,4.0,0,30,Semi-Urban,Software Engineer,149159,0 +45771,Male,49,Bachelors,12,24,49,33,81,0.0,2,69,Semi-Urban,Software Engineer,49916,0 +45772,Male,56,Bachelors,14,49,4,92,28,8.0,5,29,Urban,Software Engineer,37674,0 +45773,Male,39,Bachelors,19,71,68,55,37,5.0,0,16,Urban,Data Analyst,32702,0 +45774,Male,55,Diploma,5,53,74,6,7,6.0,6,42,Urban,Manager,140756,0 +45775,Female,26,Bachelors,19,24,48,85,0,9.0,5,92,Urban,ML Engineer,96272,1 +45776,Female,33,Diploma,19,62,30,8,95,7.0,7,54,Urban,Manager,97657,0 +45777,Male,24,Masters,13,79,34,10,38,9.0,2,2,Urban,ML Engineer,119859,0 +45778,Male,52,PhD,1,8,66,82,17,1.0,7,44,Urban,Software Engineer,20935,0 +45779,Male,31,Bachelors,11,20,70,31,62,1.0,0,79,Semi-Urban,Manager,125002,0 +45780,Male,50,Masters,14,8,76,74,87,4.0,7,78,Semi-Urban,Software Engineer,144770,1 +45781,Male,59,Bachelors,8,93,61,11,16,7.0,7,34,Rural,Software Engineer,33031,0 +45782,Female,27,Diploma,0,79,54,6,18,2.0,4,39,Rural,ML Engineer,67596,0 +45783,Male,34,PhD,7,82,86,84,2,6.0,3,13,Urban,Data Analyst,78957,1 +45784,Male,21,Diploma,2,85,19,52,39,6.0,6,88,Urban,Manager,133789,1 +45785,Male,38,Masters,0,11,23,19,87,8.0,7,17,Rural,ML Engineer,143267,0 +45786,Female,21,High School,11,2,82,20,57,9.0,0,36,Semi-Urban,Software Engineer,38631,0 +45787,Male,26,Masters,17,23,56,73,21,0.0,4,22,Semi-Urban,Manager,127502,0 +45788,Male,27,Masters,3,62,7,32,96,0.0,3,99,Urban,HR Executive,81596,0 +45789,Male,30,Diploma,2,72,85,63,57,6.0,2,83,Urban,ML Engineer,27915,1 +45790,Male,30,Diploma,8,19,26,16,16,6.0,3,11,Urban,Manager,135086,0 +45791,Male,48,Masters,3,6,41,40,88,3.0,4,27,Rural,Manager,70697,0 +45792,Female,46,Bachelors,11,24,77,15,20,2.0,2,42,Urban,Data Analyst,54827,0 +45793,Male,44,Bachelors,15,66,49,65,99,5.0,5,12,Urban,ML Engineer,138752,0 +45794,Female,52,Bachelors,11,94,76,88,77,5.0,4,23,Semi-Urban,Software Engineer,55997,1 +45795,Female,42,Bachelors,10,44,81,85,57,9.0,5,48,Urban,Data Analyst,33939,1 +45796,Female,25,Bachelors,19,71,30,71,82,1.0,4,12,Urban,Manager,108158,0 +45797,Male,43,Diploma,16,7,76,41,17,2.0,4,40,Semi-Urban,Manager,35697,0 +45798,Female,39,High School,18,76,44,36,89,7.0,1,93,Urban,Data Analyst,45508,1 +45799,Female,33,Masters,10,15,98,23,67,6.0,6,22,Rural,Software Engineer,45074,0 +45800,Male,34,Diploma,9,10,91,86,43,5.0,6,25,Urban,ML Engineer,36064,0 +45801,Female,31,Bachelors,14,65,27,72,68,3.0,0,10,Urban,Manager,74791,0 +45802,Male,51,Bachelors,18,60,99,91,43,4.0,3,86,Urban,Manager,101220,1 +45803,Male,55,Bachelors,15,66,83,95,53,1.0,6,78,Urban,Data Analyst,99999,1 +45804,Male,53,Diploma,7,5,44,65,84,2.0,2,24,Semi-Urban,Data Analyst,116553,0 +45805,Female,55,Bachelors,8,40,2,3,20,0.0,3,51,Rural,Manager,25332,0 +45806,Female,26,Masters,14,46,82,83,41,6.0,3,45,Semi-Urban,HR Executive,94248,1 +45807,Female,56,Masters,4,49,80,25,98,0.0,2,14,Rural,ML Engineer,32807,0 +45808,Male,30,Diploma,7,82,3,65,4,9.0,2,37,Semi-Urban,HR Executive,86952,0 +45809,Male,28,Masters,8,76,98,53,58,2.0,0,56,Rural,Software Engineer,108155,1 +45810,Male,36,High School,7,25,18,53,98,0.0,2,58,Urban,ML Engineer,94535,0 +45811,Female,30,Bachelors,15,32,96,37,47,5.0,5,80,Semi-Urban,ML Engineer,76731,1 +45812,Male,57,Bachelors,13,30,28,48,35,4.0,5,12,Urban,Software Engineer,83037,0 +45813,Male,43,Bachelors,8,77,27,20,66,6.0,0,79,Urban,HR Executive,104292,0 +45814,Female,58,Diploma,8,61,52,55,97,8.0,6,78,Urban,HR Executive,69827,1 +45815,Female,36,Diploma,0,52,90,93,67,9.0,6,56,Urban,Software Engineer,132039,1 +45816,Female,29,Bachelors,18,69,43,71,40,2.0,4,48,Urban,ML Engineer,111248,0 +45817,Male,54,Masters,4,60,12,89,1,4.0,4,56,Urban,ML Engineer,51234,0 +45818,Female,58,High School,18,56,75,48,30,0.0,2,41,Urban,Manager,108237,0 +45819,Female,33,Bachelors,17,29,4,77,79,1.0,3,39,Semi-Urban,Software Engineer,127551,0 +45820,Female,32,High School,4,95,70,66,36,4.0,1,40,Urban,Manager,95239,1 +45821,Female,48,Masters,8,34,64,70,13,8.0,0,96,Semi-Urban,HR Executive,75354,1 +45822,Female,58,High School,19,99,97,49,18,0.0,7,84,Rural,Manager,43562,1 +45823,Male,50,High School,19,27,92,60,2,6.0,2,87,Rural,ML Engineer,62750,1 +45824,Male,50,Diploma,3,69,57,28,9,3.0,3,6,Semi-Urban,HR Executive,41978,0 +45825,Female,59,Diploma,14,93,85,72,77,9.0,6,96,Rural,Data Analyst,117621,1 +45826,Male,39,Bachelors,13,18,19,96,92,1.0,6,92,Semi-Urban,Data Analyst,20819,0 +45827,Male,29,Bachelors,15,87,47,99,88,1.0,6,93,Semi-Urban,ML Engineer,126427,1 +45828,Female,23,Bachelors,9,21,20,24,12,3.0,3,55,Urban,Data Analyst,62661,0 +45829,Male,23,High School,16,28,1,5,69,7.0,5,92,Urban,Software Engineer,108013,0 +45830,Male,56,Bachelors,11,38,37,66,34,9.0,7,1,Semi-Urban,HR Executive,112708,0 +45831,Male,31,Bachelors,1,86,37,13,64,9.0,5,0,Urban,Data Analyst,34324,0 +45832,Male,51,Bachelors,3,42,0,40,30,7.0,6,53,Semi-Urban,Software Engineer,29652,0 +45833,Female,41,Bachelors,17,63,63,90,38,4.0,5,72,Urban,Manager,57772,1 +45834,Female,47,Masters,12,59,53,40,18,9.0,3,79,Urban,HR Executive,128577,0 +45835,Female,59,Masters,18,8,18,56,3,6.0,3,54,Rural,Software Engineer,111201,0 +45836,Female,48,High School,0,21,24,92,90,4.0,1,28,Urban,ML Engineer,87728,0 +45837,Male,48,Bachelors,14,24,79,99,61,5.0,7,77,Urban,ML Engineer,120374,1 +45838,Male,56,Masters,13,10,77,77,3,1.0,0,7,Semi-Urban,ML Engineer,37040,0 +45839,Female,29,Masters,5,2,19,27,27,3.0,0,10,Urban,ML Engineer,36390,0 +45840,Female,21,Diploma,4,24,59,53,26,1.0,2,12,Urban,Manager,38088,0 +45841,Male,42,Diploma,13,73,27,79,42,3.0,7,78,Urban,Software Engineer,62900,1 +45842,Female,43,Bachelors,14,20,94,73,52,6.0,0,79,Semi-Urban,Software Engineer,103008,1 +45843,Other,38,Diploma,14,19,51,22,44,4.0,2,58,Semi-Urban,HR Executive,137130,0 +45844,Male,55,Masters,18,22,79,71,14,8.0,3,94,Semi-Urban,HR Executive,146125,1 +45845,Male,58,Diploma,7,69,76,46,70,6.0,6,53,Semi-Urban,HR Executive,29634,1 +45846,Male,50,High School,11,14,37,32,12,1.0,1,56,Semi-Urban,Data Analyst,39432,0 +45847,Male,29,High School,3,89,54,42,52,3.0,6,31,Urban,Data Analyst,121142,0 +45848,Female,33,PhD,8,79,8,39,40,3.0,1,75,Urban,Software Engineer,60365,0 +45849,Female,54,Diploma,11,36,5,37,50,6.0,0,5,Urban,Manager,122836,0 +45850,Female,21,Masters,11,67,72,64,74,0.0,0,48,Semi-Urban,ML Engineer,97664,1 +45851,Female,34,Diploma,13,50,2,69,77,1.0,6,8,Urban,Manager,114304,0 +45852,Female,21,Bachelors,0,11,66,13,78,8.0,2,75,Urban,HR Executive,50341,0 +45853,Male,47,Masters,17,87,59,21,64,4.0,0,77,Semi-Urban,Data Analyst,79114,1 +45854,Female,27,Bachelors,18,62,86,75,77,8.0,6,20,Semi-Urban,ML Engineer,38386,1 +45855,Female,28,Bachelors,12,59,51,64,60,2.0,2,26,Rural,ML Engineer,118865,0 +45856,Female,36,Diploma,2,22,8,14,73,8.0,6,68,Urban,Data Analyst,148474,0 +45857,Male,43,Masters,13,87,10,13,23,5.0,2,12,Urban,Data Analyst,130380,0 +45858,Male,50,High School,4,30,97,74,64,8.0,3,63,Semi-Urban,HR Executive,67677,1 +45859,Male,29,Masters,9,85,44,85,18,0.0,2,59,Semi-Urban,ML Engineer,94901,1 +45860,Female,40,Bachelors,13,43,74,62,48,4.0,6,40,Rural,Data Analyst,80749,0 +45861,Male,53,PhD,2,74,56,7,38,2.0,3,59,Urban,Software Engineer,147746,0 +45862,Male,48,High School,1,10,84,39,11,9.0,7,50,Urban,ML Engineer,75882,0 +45863,Female,53,Bachelors,0,56,71,46,93,7.0,3,55,Urban,Software Engineer,41274,0 +45864,Male,46,Bachelors,6,36,73,25,69,9.0,6,19,Urban,Manager,69972,0 +45865,Male,53,Diploma,11,36,64,44,17,5.0,1,86,Urban,Manager,139617,0 +45866,Female,33,Bachelors,6,57,3,6,28,0.0,2,29,Urban,HR Executive,70562,0 +45867,Male,58,Diploma,1,88,54,57,9,5.0,1,74,Semi-Urban,HR Executive,63392,1 +45868,Male,47,Bachelors,6,37,14,96,47,5.0,7,86,Rural,Manager,96386,0 +45869,Male,51,Masters,1,84,72,93,67,0.0,5,74,Urban,Manager,21936,1 +45870,Male,40,Bachelors,12,19,22,32,83,8.0,4,42,Semi-Urban,Software Engineer,148847,0 +45871,Male,35,Bachelors,8,35,75,15,67,4.0,1,49,Urban,HR Executive,124540,0 +45872,Female,25,Masters,6,68,76,89,29,4.0,2,99,Rural,HR Executive,127285,1 +45873,Male,46,High School,4,92,24,99,89,8.0,5,8,Rural,HR Executive,107528,0 +45874,Male,27,Bachelors,16,37,53,84,20,3.0,6,83,Rural,Manager,141904,1 +45875,Male,38,Diploma,0,62,16,45,17,6.0,2,19,Semi-Urban,ML Engineer,92280,0 +45876,Male,42,Diploma,13,91,15,31,40,8.0,6,58,Urban,ML Engineer,119724,0 +45877,Male,51,Masters,17,64,19,60,95,2.0,5,67,Rural,ML Engineer,71489,0 +45878,Male,42,PhD,17,37,46,63,90,7.0,0,95,Urban,Manager,45995,1 +45879,Male,33,Bachelors,14,53,52,15,66,0.0,1,9,Semi-Urban,HR Executive,35201,0 +45880,Male,21,Diploma,14,91,1,14,47,6.0,6,83,Urban,Software Engineer,54231,0 +45881,Male,34,Diploma,6,29,24,30,58,5.0,0,14,Semi-Urban,Software Engineer,33406,0 +45882,Male,22,Bachelors,9,11,79,1,71,3.0,7,13,Urban,HR Executive,96306,0 +45883,Female,27,Bachelors,5,22,70,43,7,5.0,4,71,Urban,Data Analyst,62363,0 +45884,Male,51,Bachelors,17,47,9,95,98,4.0,6,47,Rural,Manager,75534,0 +45885,Male,35,Bachelors,6,27,26,66,8,1.0,7,91,Rural,Software Engineer,58199,0 +45886,Male,29,Masters,1,39,6,3,61,7.0,1,48,Rural,Data Analyst,147811,0 +45887,Male,52,High School,9,15,42,97,45,4.0,4,85,Urban,ML Engineer,21064,1 +45888,Male,22,Diploma,4,84,94,49,47,8.0,4,76,Urban,HR Executive,41172,1 +45889,Male,27,Diploma,14,16,14,59,87,9.0,3,79,Rural,Manager,91431,0 +45890,Female,38,Diploma,10,96,6,31,18,4.0,3,0,Urban,Software Engineer,32177,0 +45891,Female,47,Diploma,5,43,61,42,49,2.0,5,77,Urban,Data Analyst,26909,0 +45892,Male,38,Diploma,11,63,47,17,25,3.0,7,25,Semi-Urban,HR Executive,73310,0 +45893,Male,54,Masters,15,15,73,51,71,9.0,0,24,Urban,Data Analyst,144009,0 +45894,Male,29,Masters,19,38,28,81,77,0.0,0,0,Urban,Data Analyst,63656,0 +45895,Female,25,Diploma,7,23,25,1,35,4.0,4,53,Semi-Urban,Manager,55144,0 +45896,Male,33,Masters,0,18,87,91,63,2.0,2,86,Semi-Urban,Manager,93579,1 +45897,Male,55,Diploma,0,35,83,12,14,4.0,1,33,Rural,ML Engineer,53290,0 +45898,Male,24,Diploma,1,18,31,18,87,4.0,3,92,Urban,Data Analyst,108796,0 +45899,Female,58,PhD,9,16,80,51,57,1.0,7,67,Rural,Data Analyst,148354,0 +45900,Male,40,Bachelors,17,5,10,8,64,6.0,2,42,Urban,HR Executive,120984,0 +45901,Male,48,Diploma,4,75,63,2,50,5.0,2,0,Semi-Urban,Manager,88455,0 +45902,Female,58,Diploma,1,5,27,98,9,3.0,3,51,Urban,Software Engineer,129899,0 +45903,Male,59,Bachelors,19,96,80,50,84,1.0,7,55,Urban,HR Executive,121644,1 +45904,Male,49,Masters,7,56,21,64,95,6.0,1,14,Rural,HR Executive,93147,0 +45905,Female,50,PhD,14,17,86,24,59,3.0,0,76,Rural,Data Analyst,21641,0 +45906,Female,27,High School,9,78,21,33,80,4.0,4,90,Urban,HR Executive,103417,0 +45907,Female,58,Diploma,15,81,72,25,84,7.0,6,44,Semi-Urban,Manager,54901,0 +45908,Male,33,Diploma,15,28,21,76,59,4.0,6,90,Rural,Software Engineer,60941,0 +45909,Female,59,Masters,7,33,82,90,99,7.0,5,14,Semi-Urban,HR Executive,112872,0 +45910,Female,44,Bachelors,3,74,2,92,75,3.0,6,57,Semi-Urban,Software Engineer,126632,0 +45911,Male,50,Diploma,11,19,14,92,33,5.0,5,8,Semi-Urban,Manager,114002,0 +45912,Male,54,Bachelors,12,44,82,51,79,1.0,3,52,Urban,Software Engineer,104182,0 +45913,Female,36,Masters,3,72,68,55,32,4.0,3,68,Urban,Manager,90205,1 +45914,Male,43,High School,16,94,92,40,56,3.0,0,85,Rural,HR Executive,125380,1 +45915,Male,29,Diploma,2,98,6,83,31,8.0,6,87,Urban,Software Engineer,54734,1 +45916,Male,45,High School,15,80,91,57,98,1.0,1,80,Urban,ML Engineer,100847,1 +45917,Male,32,High School,0,26,39,53,2,9.0,2,32,Rural,HR Executive,85045,0 +45918,Female,30,Masters,18,35,60,84,91,3.0,7,46,Semi-Urban,ML Engineer,100540,0 +45919,Male,34,Masters,5,40,5,94,67,9.0,1,96,Urban,Data Analyst,42687,1 +45920,Male,50,Masters,4,86,42,39,33,9.0,5,45,Urban,ML Engineer,57464,0 +45921,Female,25,Bachelors,13,82,21,93,76,2.0,0,50,Urban,ML Engineer,126479,1 +45922,Female,36,Bachelors,2,26,23,4,50,2.0,6,7,Urban,HR Executive,127903,0 +45923,Female,26,PhD,18,80,49,94,73,0.0,5,92,Urban,Software Engineer,93149,1 +45924,Male,33,Bachelors,6,78,4,68,39,6.0,0,5,Semi-Urban,HR Executive,100885,0 +45925,Male,50,Masters,18,97,4,46,95,3.0,3,14,Urban,HR Executive,136836,0 +45926,Male,50,Bachelors,16,90,33,50,61,8.0,6,43,Urban,Data Analyst,123521,0 +45927,Male,51,Bachelors,18,27,43,93,36,2.0,1,89,Urban,ML Engineer,68982,1 +45928,Male,46,Masters,15,81,94,12,96,6.0,0,6,Urban,Manager,145368,0 +45929,Female,34,Diploma,15,65,50,61,18,5.0,1,43,Urban,Software Engineer,62366,0 +45930,Male,49,Bachelors,14,82,71,91,90,2.0,6,94,Rural,Manager,103117,1 +45931,Male,37,Masters,1,17,57,17,22,3.0,0,79,Semi-Urban,Data Analyst,73572,0 +45932,Female,45,PhD,8,13,13,62,79,0.0,7,98,Semi-Urban,ML Engineer,94415,0 +45933,Male,55,Bachelors,15,99,99,93,99,9.0,2,19,Urban,HR Executive,101494,1 +45934,Male,55,Diploma,1,42,71,71,3,8.0,3,15,Semi-Urban,ML Engineer,43096,0 +45935,Male,31,Diploma,0,56,97,91,56,7.0,5,97,Rural,Software Engineer,133681,1 +45936,Male,48,Bachelors,9,48,46,20,95,6.0,2,51,Urban,Data Analyst,57799,0 +45937,Other,25,Masters,1,44,12,76,46,2.0,5,6,Rural,Manager,105448,0 +45938,Female,44,Bachelors,18,89,22,9,12,3.0,4,13,Semi-Urban,HR Executive,76506,0 +45939,Male,21,Masters,14,67,95,3,88,1.0,1,19,Rural,Manager,51445,0 +45940,Male,46,Bachelors,4,4,61,86,59,0.0,5,91,Urban,ML Engineer,122886,1 +45941,Male,48,Masters,14,55,55,68,23,5.0,2,82,Rural,HR Executive,139710,1 +45942,Female,28,Bachelors,5,71,78,9,23,9.0,5,82,Semi-Urban,ML Engineer,85288,0 +45943,Female,41,Bachelors,16,83,80,50,9,4.0,1,74,Urban,Manager,73928,1 +45944,Male,55,High School,9,64,69,54,84,2.0,6,13,Urban,Data Analyst,102102,0 +45945,Female,57,Bachelors,6,75,15,75,27,4.0,6,13,Urban,Software Engineer,21738,0 +45946,Male,25,Bachelors,5,85,24,5,78,1.0,4,25,Urban,Manager,50078,0 +45947,Male,53,Bachelors,18,11,75,42,88,6.0,2,27,Semi-Urban,Software Engineer,88953,0 +45948,Male,47,Bachelors,9,71,42,51,57,7.0,4,59,Semi-Urban,Manager,68330,0 +45949,Female,33,Masters,13,71,94,91,12,4.0,2,83,Rural,Software Engineer,102044,1 +45950,Male,41,Masters,13,69,3,71,18,2.0,7,41,Rural,Data Analyst,34246,0 +45951,Female,22,Diploma,19,7,41,54,81,4.0,7,6,Rural,HR Executive,110170,0 +45952,Male,27,PhD,2,35,22,21,61,3.0,0,55,Urban,Manager,63694,0 +45953,Female,41,High School,5,74,50,36,39,0.0,4,58,Urban,Data Analyst,120215,0 +45954,Male,54,PhD,6,40,5,69,80,7.0,5,50,Urban,ML Engineer,80051,0 +45955,Male,56,PhD,10,90,19,39,96,1.0,7,47,Urban,HR Executive,121790,0 +45956,Male,24,PhD,1,93,44,15,73,0.0,1,53,Urban,ML Engineer,140743,0 +45957,Female,50,Bachelors,9,51,76,43,96,1.0,7,38,Semi-Urban,Software Engineer,31835,0 +45958,Female,59,Diploma,5,15,72,67,94,3.0,0,21,Urban,Data Analyst,79131,0 +45959,Male,44,High School,0,88,95,14,42,4.0,0,67,Urban,Software Engineer,62612,1 +45960,Male,53,Bachelors,3,37,92,11,28,8.0,2,24,Urban,ML Engineer,101132,0 +45961,Female,43,Bachelors,1,86,26,84,66,9.0,6,0,Rural,Manager,114213,0 +45962,Male,54,Diploma,3,42,79,76,5,8.0,0,9,Rural,Software Engineer,23988,0 +45963,Female,32,Bachelors,17,58,45,96,38,1.0,5,46,Urban,ML Engineer,88506,1 +45964,Female,44,High School,12,20,56,80,65,5.0,0,36,Urban,Data Analyst,132647,0 +45965,Male,41,Bachelors,6,89,11,82,57,3.0,0,67,Urban,HR Executive,39844,1 +45966,Female,56,Masters,18,82,55,21,5,0.0,1,13,Semi-Urban,Software Engineer,138088,0 +45967,Female,25,PhD,11,16,72,59,43,0.0,5,99,Rural,Manager,75543,1 +45968,Male,57,Masters,7,40,44,37,43,9.0,6,62,Rural,HR Executive,56200,0 +45969,Male,41,PhD,0,22,69,45,94,1.0,4,84,Urban,HR Executive,87839,0 +45970,Male,25,Diploma,13,72,81,83,39,6.0,2,83,Rural,HR Executive,137761,1 +45971,Female,23,Diploma,0,22,19,65,38,5.0,0,59,Urban,Software Engineer,74525,0 +45972,Female,25,Bachelors,11,79,11,15,90,2.0,7,62,Semi-Urban,Software Engineer,141768,0 +45973,Male,36,Diploma,0,19,15,37,82,1.0,1,84,Urban,Manager,58241,0 +45974,Male,40,Bachelors,6,22,91,37,66,2.0,5,31,Semi-Urban,Manager,63559,0 +45975,Male,42,Diploma,3,74,87,0,44,8.0,5,14,Urban,Software Engineer,48298,0 +45976,Female,39,PhD,12,77,87,1,3,8.0,1,65,Semi-Urban,HR Executive,92008,0 +45977,Male,23,Masters,1,65,83,19,80,1.0,0,38,Rural,Manager,81382,0 +45978,Female,33,Diploma,17,98,84,53,1,4.0,6,25,Urban,ML Engineer,101966,1 +45979,Male,48,Bachelors,12,83,2,32,94,6.0,1,62,Urban,HR Executive,117398,0 +45980,Male,58,Bachelors,12,66,78,96,45,5.0,4,97,Urban,Data Analyst,35482,1 +45981,Male,25,Masters,14,8,98,56,80,9.0,0,25,Rural,Data Analyst,48098,0 +45982,Male,29,Diploma,15,86,43,16,49,5.0,3,27,Urban,Data Analyst,31148,0 +45983,Female,57,Diploma,13,24,83,45,88,3.0,0,67,Rural,HR Executive,89974,0 +45984,Female,31,Bachelors,0,99,48,83,69,5.0,4,92,Urban,Software Engineer,20268,1 +45985,Other,50,Diploma,16,59,37,20,89,5.0,1,57,Urban,Data Analyst,141221,0 +45986,Female,49,Masters,0,85,52,45,56,5.0,7,55,Urban,Data Analyst,94991,0 +45987,Male,57,High School,18,64,78,38,5,0.0,1,87,Rural,Software Engineer,52755,1 +45988,Female,55,Bachelors,13,93,67,37,68,8.0,2,69,Rural,Data Analyst,87256,1 +45989,Female,43,Bachelors,10,41,31,60,80,1.0,7,91,Semi-Urban,ML Engineer,125673,0 +45990,Male,43,Masters,8,4,45,95,40,4.0,4,74,Urban,Data Analyst,76689,0 +45991,Male,24,Masters,7,15,82,39,28,0.0,2,51,Semi-Urban,Manager,52726,0 +45992,Female,34,Bachelors,7,99,49,2,99,5.0,4,32,Urban,ML Engineer,92554,0 +45993,Female,21,Bachelors,1,51,42,92,48,5.0,4,21,Urban,ML Engineer,30995,0 +45994,Female,39,High School,13,62,87,80,58,7.0,4,54,Urban,Manager,26316,1 +45995,Male,33,Masters,14,76,76,44,52,3.0,1,51,Urban,Manager,92018,1 +45996,Female,48,Masters,15,97,13,10,60,6.0,4,47,Urban,ML Engineer,145770,0 +45997,Male,30,High School,0,41,64,57,7,9.0,1,44,Semi-Urban,ML Engineer,42831,0 +45998,Male,47,Bachelors,5,94,96,73,39,3.0,0,55,Rural,Manager,45254,1 +45999,Female,56,High School,7,32,62,97,67,6.0,2,92,Urban,Software Engineer,125667,1 +46000,Female,40,Bachelors,6,93,51,37,3,7.0,5,60,Urban,ML Engineer,65455,1 +46001,Male,44,Bachelors,1,0,10,93,93,3.0,5,75,Semi-Urban,HR Executive,62003,0 +46002,Male,56,Masters,13,6,40,45,5,4.0,3,36,Urban,Data Analyst,78638,0 +46003,Male,43,High School,4,49,14,19,46,8.0,2,98,Urban,HR Executive,68147,0 +46004,Male,34,Bachelors,9,23,75,81,33,6.0,3,79,Rural,ML Engineer,60699,1 +46005,Male,26,Bachelors,13,7,91,29,37,9.0,1,54,Urban,ML Engineer,84910,0 +46006,Male,46,Bachelors,4,33,7,49,17,4.0,2,11,Semi-Urban,ML Engineer,133099,0 +46007,Male,40,Bachelors,18,55,33,31,4,9.0,1,53,Urban,Data Analyst,120318,0 +46008,Female,47,PhD,19,20,67,62,82,2.0,5,56,Rural,HR Executive,84599,0 +46009,Male,33,Bachelors,4,93,18,98,3,4.0,5,23,Urban,Data Analyst,130148,0 +46010,Male,42,Bachelors,6,30,38,87,22,6.0,2,17,Semi-Urban,Manager,122757,0 +46011,Female,53,Diploma,3,70,24,53,7,9.0,0,7,Urban,Data Analyst,85438,0 +46012,Female,36,Bachelors,15,44,60,93,52,4.0,5,74,Urban,Manager,96044,1 +46013,Male,33,Bachelors,10,15,62,2,31,4.0,0,0,Semi-Urban,Data Analyst,109501,0 +46014,Male,24,Bachelors,10,15,33,0,51,2.0,1,40,Urban,HR Executive,129588,0 +46015,Female,57,Masters,13,79,1,72,87,4.0,0,72,Semi-Urban,HR Executive,110436,0 +46016,Male,56,Diploma,19,58,44,89,89,7.0,4,46,Rural,Data Analyst,123443,1 +46017,Female,36,Bachelors,4,46,73,40,48,4.0,3,33,Rural,HR Executive,49735,0 +46018,Male,47,Bachelors,8,65,81,67,7,3.0,5,30,Urban,HR Executive,29617,1 +46019,Other,22,Bachelors,5,14,44,44,29,5.0,4,68,Urban,ML Engineer,93348,0 +46020,Female,45,High School,12,73,18,34,67,3.0,1,26,Rural,HR Executive,139404,0 +46021,Male,46,Masters,0,18,50,52,11,0.0,7,53,Urban,Manager,36295,0 +46022,Male,32,Masters,4,60,2,11,87,9.0,3,62,Urban,Data Analyst,110386,0 +46023,Male,37,Masters,11,41,83,2,99,5.0,5,23,Urban,Manager,59394,0 +46024,Male,46,Diploma,1,65,66,45,28,0.0,3,29,Urban,ML Engineer,125922,0 +46025,Male,59,Bachelors,6,42,87,80,92,8.0,3,16,Rural,Manager,117187,0 +46026,Male,38,Diploma,0,16,66,82,71,8.0,4,11,Semi-Urban,Software Engineer,100596,0 +46027,Male,48,Diploma,16,87,99,33,76,3.0,2,84,Rural,HR Executive,122855,1 +46028,Female,50,Bachelors,14,72,26,88,94,2.0,2,29,Urban,Manager,149154,0 +46029,Male,39,Bachelors,16,17,31,2,36,0.0,4,57,Urban,Software Engineer,127758,0 +46030,Female,38,Diploma,18,95,61,70,90,2.0,7,25,Rural,HR Executive,43740,1 +46031,Female,58,Masters,2,81,4,35,34,3.0,6,20,Urban,ML Engineer,93174,0 +46032,Female,51,Diploma,0,40,98,9,91,1.0,6,26,Urban,ML Engineer,97114,0 +46033,Female,23,Diploma,12,15,94,80,60,3.0,6,61,Rural,HR Executive,148823,1 +46034,Female,30,Masters,18,0,4,24,91,9.0,4,77,Urban,Software Engineer,41181,0 +46035,Other,37,Masters,2,67,30,51,51,4.0,6,47,Urban,Software Engineer,111213,0 +46036,Male,27,Diploma,6,1,64,64,67,5.0,5,89,Urban,HR Executive,22163,0 +46037,Male,54,Bachelors,19,71,91,31,32,1.0,3,17,Urban,Data Analyst,113445,0 +46038,Male,43,Diploma,6,43,66,65,11,7.0,4,76,Urban,HR Executive,65056,1 +46039,Male,28,Diploma,13,97,3,83,13,3.0,2,76,Urban,ML Engineer,57881,1 +46040,Male,41,High School,5,76,94,3,43,2.0,2,59,Urban,Data Analyst,127361,0 +46041,Female,34,Diploma,16,47,10,58,51,9.0,6,18,Urban,Manager,84227,0 +46042,Male,46,Bachelors,13,21,86,33,1,4.0,4,44,Semi-Urban,HR Executive,76499,0 +46043,Male,55,Diploma,12,65,29,58,98,5.0,5,98,Urban,Data Analyst,86894,1 +46044,Male,40,Bachelors,11,68,85,40,59,1.0,3,89,Rural,HR Executive,109756,1 +46045,Female,41,Bachelors,4,99,91,52,76,6.0,4,42,Urban,HR Executive,108413,1 +46046,Male,56,Bachelors,8,32,37,12,85,5.0,3,31,Rural,HR Executive,69540,0 +46047,Female,58,Masters,11,25,50,3,4,3.0,1,71,Rural,HR Executive,141050,0 +46048,Male,21,Bachelors,7,52,63,4,10,6.0,4,33,Semi-Urban,ML Engineer,94632,0 +46049,Female,26,Diploma,12,22,61,60,80,0.0,1,93,Rural,Manager,117001,0 +46050,Male,32,Bachelors,0,42,54,46,60,3.0,7,80,Urban,Data Analyst,149181,0 +46051,Male,45,Masters,9,90,47,35,91,1.0,5,78,Urban,Software Engineer,70107,1 +46052,Other,49,Bachelors,19,53,53,73,56,3.0,7,82,Rural,Data Analyst,146334,1 +46053,Male,35,Bachelors,11,65,79,86,28,1.0,4,22,Rural,HR Executive,140881,1 +46054,Male,31,Diploma,17,49,36,1,36,8.0,4,92,Urban,ML Engineer,57084,0 +46055,Male,35,Masters,16,31,38,62,90,8.0,4,96,Rural,Manager,69537,0 +46056,Female,52,Bachelors,12,68,36,76,10,8.0,7,92,Rural,Software Engineer,66435,1 +46057,Other,55,Diploma,1,62,3,2,46,0.0,5,7,Semi-Urban,Software Engineer,96662,0 +46058,Female,57,Bachelors,5,89,77,82,26,7.0,6,13,Semi-Urban,Manager,36177,1 +46059,Male,21,Bachelors,3,63,28,76,18,8.0,1,52,Rural,ML Engineer,78688,0 +46060,Male,34,Diploma,12,72,99,73,33,0.0,3,75,Semi-Urban,Software Engineer,46389,1 +46061,Male,26,PhD,12,4,22,73,26,9.0,1,49,Urban,Software Engineer,33184,0 +46062,Female,36,Bachelors,18,2,40,82,85,3.0,1,91,Urban,Software Engineer,105818,0 +46063,Male,53,High School,9,98,49,29,58,3.0,2,56,Urban,HR Executive,97647,0 +46064,Female,41,High School,13,71,32,28,45,1.0,4,30,Semi-Urban,Data Analyst,40551,0 +46065,Male,42,Bachelors,1,54,84,40,62,8.0,1,33,Urban,Manager,143818,0 +46066,Male,32,Bachelors,14,3,58,63,25,0.0,5,15,Urban,Data Analyst,61169,0 +46067,Male,22,High School,9,77,74,69,26,1.0,7,48,Semi-Urban,Software Engineer,93568,1 +46068,Male,29,High School,10,52,52,61,56,2.0,5,41,Semi-Urban,Data Analyst,84832,0 +46069,Female,44,Masters,0,89,92,46,71,2.0,0,90,Urban,Manager,63080,1 +46070,Male,58,High School,7,75,12,25,58,9.0,1,52,Urban,HR Executive,117553,0 +46071,Male,31,Diploma,0,53,40,53,88,7.0,1,49,Rural,Data Analyst,26637,0 +46072,Male,54,Bachelors,1,53,10,76,45,3.0,4,42,Urban,HR Executive,122635,0 +46073,Male,45,Bachelors,17,16,3,93,90,3.0,0,12,Urban,Data Analyst,139618,0 +46074,Male,37,Bachelors,12,39,95,63,83,4.0,0,82,Urban,ML Engineer,54095,1 +46075,Female,47,Bachelors,10,58,13,87,63,3.0,3,86,Semi-Urban,Data Analyst,50753,1 +46076,Male,28,Bachelors,13,58,43,91,68,2.0,6,55,Semi-Urban,Data Analyst,140015,1 +46077,Male,26,Bachelors,8,47,23,23,7,1.0,4,98,Urban,Data Analyst,76112,0 +46078,Female,26,Diploma,9,74,79,57,88,3.0,3,1,Urban,Data Analyst,60107,0 +46079,Female,36,Diploma,16,2,65,75,25,6.0,1,71,Urban,HR Executive,30259,0 +46080,Male,54,Diploma,14,84,73,75,55,0.0,5,68,Urban,Data Analyst,51382,1 +46081,Female,42,Diploma,2,53,78,42,39,0.0,1,41,Rural,ML Engineer,123240,0 +46082,Other,32,Diploma,10,70,94,84,67,5.0,7,11,Semi-Urban,Software Engineer,113011,1 +46083,Male,41,Bachelors,10,49,3,26,73,7.0,0,66,Rural,Software Engineer,78119,0 +46084,Female,27,Bachelors,19,32,38,36,25,7.0,6,52,Urban,Manager,112504,0 +46085,Male,27,Bachelors,9,32,53,92,27,0.0,0,79,Rural,HR Executive,27205,1 +46086,Male,55,Bachelors,6,42,84,31,18,2.0,6,35,Urban,ML Engineer,103169,0 +46087,Male,48,Diploma,10,0,53,67,79,0.0,6,35,Semi-Urban,Data Analyst,140682,0 +46088,Female,43,Bachelors,10,58,72,10,15,1.0,5,28,Urban,Software Engineer,51224,0 +46089,Female,34,Bachelors,9,46,88,37,92,1.0,3,39,Urban,ML Engineer,76274,0 +46090,Male,41,High School,7,64,13,46,93,4.0,3,74,Urban,HR Executive,113701,0 +46091,Male,22,Masters,6,4,39,58,32,2.0,5,94,Rural,Data Analyst,87877,0 +46092,Male,45,Bachelors,4,52,78,17,36,5.0,1,0,Semi-Urban,Software Engineer,43206,0 +46093,Male,21,Masters,2,7,36,27,94,5.0,7,93,Urban,HR Executive,62704,0 +46094,Female,21,Bachelors,12,63,70,64,72,4.0,0,28,Urban,ML Engineer,95803,0 +46095,Male,40,Masters,2,33,8,76,17,6.0,3,41,Urban,Data Analyst,129765,0 +46096,Male,34,PhD,13,41,29,72,45,2.0,2,92,Urban,Data Analyst,75462,0 +46097,Male,21,Bachelors,7,55,60,0,20,0.0,5,12,Semi-Urban,Software Engineer,112016,0 +46098,Female,54,Diploma,4,95,8,53,32,1.0,1,79,Semi-Urban,ML Engineer,131729,0 +46099,Female,31,Bachelors,19,96,16,88,52,2.0,1,62,Urban,Manager,73858,1 +46100,Male,41,PhD,8,25,87,50,61,8.0,3,22,Semi-Urban,Software Engineer,101059,0 +46101,Male,33,Bachelors,2,81,82,67,43,7.0,2,50,Semi-Urban,Manager,115655,1 +46102,Male,45,Bachelors,3,56,33,6,34,9.0,5,51,Urban,Manager,36731,0 +46103,Other,47,Bachelors,1,48,26,19,5,6.0,2,82,Urban,Data Analyst,27766,0 +46104,Male,43,Bachelors,18,83,95,85,99,5.0,0,34,Urban,Manager,38169,1 +46105,Male,32,Bachelors,1,25,46,92,64,7.0,6,20,Urban,ML Engineer,111209,0 +46106,Male,50,Masters,18,58,86,72,25,3.0,7,14,Urban,Data Analyst,41545,0 +46107,Male,32,Masters,2,52,87,9,57,9.0,1,86,Urban,HR Executive,133952,0 +46108,Male,26,Diploma,12,68,19,18,4,5.0,3,35,Rural,HR Executive,29359,0 +46109,Male,45,Diploma,0,74,16,31,18,3.0,3,24,Urban,HR Executive,101826,0 +46110,Male,45,Bachelors,7,79,24,25,36,3.0,6,52,Urban,Manager,98991,0 +46111,Male,50,Masters,4,47,71,31,73,8.0,0,31,Urban,Manager,79849,0 +46112,Male,59,Bachelors,17,67,58,85,94,0.0,5,27,Urban,Software Engineer,44996,1 +46113,Male,35,Bachelors,17,70,19,58,64,5.0,7,47,Urban,HR Executive,124041,0 +46114,Female,32,Bachelors,4,99,71,75,62,6.0,3,52,Semi-Urban,Software Engineer,148683,1 +46115,Male,31,Diploma,9,61,76,59,93,6.0,4,82,Urban,HR Executive,29734,1 +46116,Male,40,High School,2,50,22,39,88,0.0,6,17,Urban,HR Executive,121532,0 +46117,Female,51,PhD,3,24,92,22,90,8.0,4,36,Rural,ML Engineer,68386,0 +46118,Female,25,Bachelors,12,50,21,96,95,1.0,3,0,Semi-Urban,ML Engineer,22672,0 +46119,Male,26,PhD,17,84,90,31,88,3.0,1,85,Urban,HR Executive,132591,1 +46120,Male,55,Bachelors,19,93,86,68,55,6.0,5,74,Urban,ML Engineer,118211,1 +46121,Female,41,Bachelors,10,86,51,59,53,8.0,0,12,Rural,HR Executive,138851,0 +46122,Male,27,Bachelors,7,61,65,21,91,3.0,2,1,Semi-Urban,HR Executive,61453,0 +46123,Female,36,High School,10,67,83,77,19,2.0,7,31,Semi-Urban,Data Analyst,121731,1 +46124,Female,22,High School,17,58,28,21,20,1.0,5,87,Rural,HR Executive,69293,0 +46125,Male,27,Masters,12,12,24,3,35,2.0,7,45,Semi-Urban,HR Executive,99237,0 +46126,Male,56,Diploma,10,69,75,40,31,6.0,0,78,Semi-Urban,Manager,50841,1 +46127,Male,48,Masters,12,4,61,70,27,5.0,7,21,Rural,Manager,116401,0 +46128,Other,32,PhD,10,41,95,41,99,3.0,5,55,Urban,HR Executive,33637,0 +46129,Female,52,PhD,8,12,5,30,1,3.0,7,11,Rural,Manager,43651,0 +46130,Male,25,Bachelors,8,85,58,0,74,8.0,1,77,Urban,Software Engineer,147361,0 +46131,Male,38,Bachelors,15,81,79,10,25,3.0,7,76,Urban,Data Analyst,89370,1 +46132,Female,34,PhD,17,24,31,20,88,2.0,0,2,Rural,Data Analyst,130378,0 +46133,Other,26,Diploma,0,24,76,36,79,5.0,4,57,Semi-Urban,Software Engineer,47065,0 +46134,Female,44,Bachelors,8,46,23,43,33,5.0,2,49,Rural,ML Engineer,145382,0 +46135,Male,49,Masters,17,76,40,31,19,9.0,4,53,Urban,Manager,102437,0 +46136,Male,58,Bachelors,10,77,65,77,79,3.0,5,63,Urban,Software Engineer,110491,1 +46137,Male,21,Diploma,1,54,90,29,77,2.0,5,45,Semi-Urban,Data Analyst,59183,0 +46138,Female,23,High School,17,15,26,15,55,3.0,4,42,Semi-Urban,HR Executive,135104,0 +46139,Male,53,Masters,7,6,83,29,70,5.0,5,34,Urban,Data Analyst,25628,0 +46140,Female,48,Bachelors,9,37,21,97,11,4.0,2,63,Semi-Urban,Manager,101468,0 +46141,Male,56,Bachelors,15,86,40,70,2,3.0,7,0,Rural,HR Executive,135772,0 +46142,Male,46,PhD,8,84,11,45,70,2.0,1,62,Urban,Manager,108543,0 +46143,Female,47,Bachelors,0,31,17,85,7,6.0,2,50,Semi-Urban,Manager,45307,0 +46144,Female,40,High School,15,89,67,36,83,3.0,3,42,Urban,Software Engineer,36264,0 +46145,Male,41,Diploma,2,75,45,90,99,4.0,5,99,Urban,Manager,139419,1 +46146,Male,23,Bachelors,8,83,7,15,30,1.0,5,20,Urban,Software Engineer,120538,0 +46147,Female,34,Bachelors,12,57,33,46,28,5.0,6,12,Urban,ML Engineer,52746,0 +46148,Female,30,Diploma,19,61,61,28,80,4.0,3,48,Urban,Software Engineer,50964,0 +46149,Female,59,Diploma,4,3,95,99,74,6.0,0,14,Urban,Manager,145337,0 +46150,Male,37,PhD,17,73,8,96,50,0.0,3,60,Urban,Software Engineer,73176,1 +46151,Male,46,Bachelors,8,12,3,65,78,5.0,5,80,Rural,Software Engineer,29008,0 +46152,Female,29,Bachelors,16,36,97,42,30,6.0,3,50,Urban,Data Analyst,78745,0 +46153,Female,52,Bachelors,10,58,79,18,63,4.0,0,23,Urban,Data Analyst,27398,0 +46154,Male,54,Bachelors,15,37,86,49,29,9.0,0,50,Urban,Software Engineer,133486,0 +46155,Other,28,Bachelors,6,51,1,17,70,0.0,1,96,Urban,ML Engineer,100656,0 +46156,Male,53,Diploma,5,76,90,26,96,2.0,3,13,Rural,ML Engineer,100916,0 +46157,Male,24,High School,7,1,74,34,2,1.0,2,7,Urban,Software Engineer,25695,0 +46158,Female,36,Bachelors,3,90,63,37,58,5.0,1,36,Semi-Urban,Software Engineer,107969,0 +46159,Male,43,Bachelors,0,54,61,22,93,7.0,2,3,Urban,ML Engineer,87565,0 +46160,Other,46,PhD,17,53,27,26,50,2.0,5,66,Urban,Manager,149282,0 +46161,Male,35,High School,16,11,70,58,42,4.0,7,16,Urban,Data Analyst,69459,0 +46162,Male,32,Bachelors,5,0,16,17,65,9.0,2,36,Rural,ML Engineer,39842,0 +46163,Male,35,High School,19,79,15,72,55,1.0,7,1,Semi-Urban,Software Engineer,76720,0 +46164,Male,31,Bachelors,16,76,55,16,18,3.0,6,64,Semi-Urban,Software Engineer,98802,0 +46165,Male,35,Diploma,8,74,88,81,3,1.0,7,31,Urban,Manager,138409,1 +46166,Male,32,Bachelors,8,60,9,0,77,0.0,4,17,Rural,ML Engineer,123925,0 +46167,Male,40,High School,6,78,5,10,95,6.0,0,57,Urban,Data Analyst,41278,0 +46168,Female,31,Bachelors,19,63,40,70,45,6.0,7,69,Urban,HR Executive,95368,1 +46169,Male,30,Bachelors,1,36,62,23,89,0.0,7,64,Urban,Manager,52873,0 +46170,Female,45,Diploma,4,97,12,43,28,1.0,5,90,Urban,Data Analyst,144633,1 +46171,Male,31,Masters,18,60,79,4,53,3.0,2,17,Rural,HR Executive,117562,0 +46172,Male,49,Bachelors,11,77,22,87,80,4.0,3,82,Semi-Urban,Manager,29631,1 +46173,Male,50,Masters,0,63,69,4,38,4.0,2,29,Urban,ML Engineer,41182,0 +46174,Male,45,Bachelors,9,7,28,44,23,9.0,0,69,Semi-Urban,Software Engineer,91852,0 +46175,Female,32,High School,14,74,55,88,21,6.0,0,9,Urban,HR Executive,88313,0 +46176,Other,52,PhD,9,99,98,23,94,6.0,5,27,Urban,ML Engineer,69806,1 +46177,Male,21,Diploma,4,77,74,5,22,9.0,4,17,Urban,Data Analyst,40338,0 +46178,Male,43,Bachelors,8,4,2,97,31,9.0,3,80,Semi-Urban,Manager,121387,0 +46179,Male,32,Bachelors,14,11,41,48,22,2.0,0,12,Urban,Data Analyst,43609,0 +46180,Other,50,Diploma,10,91,16,74,72,3.0,5,75,Urban,Data Analyst,98782,1 +46181,Female,47,Masters,0,30,25,13,71,7.0,6,57,Urban,ML Engineer,77686,0 +46182,Male,22,Bachelors,18,10,35,86,93,2.0,6,77,Urban,Manager,67093,0 +46183,Male,46,Bachelors,5,13,39,65,73,9.0,1,28,Semi-Urban,ML Engineer,138660,0 +46184,Male,57,Masters,15,25,44,76,97,3.0,7,77,Semi-Urban,Data Analyst,143933,0 +46185,Female,55,Bachelors,11,86,51,32,22,9.0,0,96,Urban,Manager,102269,1 +46186,Female,32,Bachelors,16,64,46,41,63,9.0,2,91,Semi-Urban,Software Engineer,138901,1 +46187,Other,27,Bachelors,14,10,65,37,86,2.0,7,15,Urban,HR Executive,25362,0 +46188,Male,35,Bachelors,12,95,10,74,54,3.0,3,38,Urban,Software Engineer,58125,0 +46189,Female,58,Bachelors,2,7,85,11,99,1.0,1,82,Urban,ML Engineer,35996,0 +46190,Male,31,Diploma,0,90,73,33,33,4.0,4,86,Urban,Data Analyst,20821,1 +46191,Female,35,Bachelors,15,91,28,49,69,2.0,3,16,Rural,HR Executive,30220,0 +46192,Male,58,Bachelors,3,35,9,58,9,3.0,5,82,Urban,Manager,124312,0 +46193,Female,28,Bachelors,12,88,97,80,10,7.0,5,26,Urban,Manager,107991,1 +46194,Male,43,Bachelors,15,66,44,51,3,2.0,7,31,Urban,Software Engineer,81091,0 +46195,Male,33,Masters,15,15,48,39,12,0.0,0,47,Urban,Software Engineer,40631,0 +46196,Female,35,Diploma,9,12,55,66,75,2.0,0,36,Semi-Urban,Manager,113991,0 +46197,Female,36,Bachelors,7,54,48,95,42,2.0,3,58,Semi-Urban,Software Engineer,21905,1 +46198,Female,37,Diploma,19,29,38,81,78,8.0,1,1,Rural,Software Engineer,20666,0 +46199,Female,40,High School,12,73,98,20,2,2.0,0,48,Semi-Urban,Software Engineer,50662,0 +46200,Female,52,Bachelors,1,14,3,37,3,0.0,2,92,Rural,Data Analyst,115725,0 +46201,Male,57,Bachelors,9,75,29,95,80,7.0,5,79,Urban,Manager,52168,1 +46202,Male,30,Bachelors,7,56,3,14,46,8.0,6,35,Semi-Urban,HR Executive,51355,0 +46203,Female,22,Diploma,9,5,70,41,65,2.0,0,28,Rural,Data Analyst,31976,0 +46204,Female,45,Bachelors,6,89,58,9,72,3.0,2,1,Urban,ML Engineer,60929,0 +46205,Male,29,High School,3,1,54,23,10,9.0,5,15,Urban,HR Executive,32664,0 +46206,Male,50,Diploma,16,63,17,38,22,9.0,7,75,Urban,Data Analyst,69613,0 +46207,Female,26,Diploma,16,35,31,6,93,7.0,3,26,Rural,ML Engineer,128328,0 +46208,Female,27,Bachelors,5,0,79,60,92,0.0,0,78,Semi-Urban,ML Engineer,23535,0 +46209,Male,47,PhD,4,39,51,99,5,2.0,2,75,Urban,Software Engineer,130709,1 +46210,Male,25,Bachelors,15,70,0,10,54,6.0,2,5,Urban,Data Analyst,70327,0 +46211,Other,36,Bachelors,5,13,28,18,73,9.0,6,40,Semi-Urban,Manager,121903,0 +46212,Male,45,Diploma,3,55,82,14,4,1.0,2,99,Urban,HR Executive,83640,1 +46213,Male,37,Bachelors,3,41,61,56,28,2.0,3,18,Rural,HR Executive,120283,0 +46214,Male,52,Masters,15,3,41,55,85,2.0,5,68,Semi-Urban,Data Analyst,62443,0 +46215,Male,33,High School,9,61,65,93,72,4.0,7,8,Urban,ML Engineer,54452,0 +46216,Male,48,High School,0,11,36,44,96,1.0,7,22,Rural,Manager,103390,0 +46217,Male,38,Diploma,17,84,17,74,22,9.0,7,18,Semi-Urban,Manager,64664,0 +46218,Male,50,High School,9,21,28,9,46,7.0,4,95,Urban,Manager,108971,0 +46219,Female,27,High School,0,94,58,87,90,2.0,0,3,Semi-Urban,Manager,131924,1 +46220,Male,25,Masters,3,22,89,64,30,4.0,3,88,Urban,Data Analyst,125223,1 +46221,Male,56,Bachelors,2,96,50,18,81,7.0,6,9,Semi-Urban,Data Analyst,60339,0 +46222,Male,36,Bachelors,2,48,71,52,29,7.0,5,20,Urban,HR Executive,52473,0 +46223,Male,23,Diploma,11,29,64,87,2,9.0,6,2,Urban,Data Analyst,117672,0 +46224,Male,38,High School,17,26,66,47,11,7.0,1,84,Rural,Software Engineer,130392,0 +46225,Female,51,Bachelors,8,87,66,92,76,5.0,6,74,Urban,Software Engineer,69935,1 +46226,Male,28,Bachelors,10,95,99,45,85,3.0,3,91,Rural,Data Analyst,24371,1 +46227,Male,31,High School,14,47,23,30,3,5.0,3,53,Urban,HR Executive,112558,0 +46228,Female,23,Diploma,19,60,79,10,62,2.0,1,10,Semi-Urban,Software Engineer,101274,0 +46229,Male,56,High School,7,19,27,57,56,3.0,5,10,Urban,Software Engineer,40703,0 +46230,Male,41,High School,15,21,3,94,20,0.0,2,45,Urban,Manager,119017,0 +46231,Female,21,Masters,18,0,30,1,87,6.0,7,53,Urban,HR Executive,143758,0 +46232,Female,40,Masters,2,73,28,21,57,6.0,5,52,Urban,Data Analyst,78426,0 +46233,Female,30,Bachelors,5,32,72,9,1,7.0,5,8,Urban,Manager,127320,0 +46234,Male,26,Masters,13,79,52,99,38,0.0,5,54,Urban,ML Engineer,85488,1 +46235,Other,35,High School,2,71,2,67,19,6.0,4,40,Rural,Manager,46992,0 +46236,Female,55,Bachelors,4,24,67,86,33,7.0,5,22,Urban,Software Engineer,143595,0 +46237,Male,57,High School,10,17,62,3,5,5.0,4,94,Urban,Data Analyst,96579,0 +46238,Female,34,Masters,8,22,26,73,33,7.0,3,19,Urban,HR Executive,83878,0 +46239,Male,43,Diploma,0,73,61,79,74,6.0,3,97,Urban,ML Engineer,42318,1 +46240,Male,57,High School,2,2,2,84,10,6.0,3,93,Urban,Software Engineer,106487,0 +46241,Male,25,Bachelors,5,14,16,8,63,4.0,3,45,Urban,ML Engineer,54977,0 +46242,Male,30,Bachelors,3,60,20,68,66,0.0,1,38,Urban,ML Engineer,37422,0 +46243,Male,32,Diploma,8,82,6,28,50,6.0,1,14,Rural,Manager,25750,0 +46244,Male,41,Diploma,8,96,22,29,23,9.0,2,24,Rural,Software Engineer,72681,0 +46245,Male,26,Bachelors,0,52,3,3,38,6.0,1,5,Urban,Manager,73516,0 +46246,Female,28,Diploma,11,1,26,4,35,4.0,3,67,Urban,Data Analyst,38902,0 +46247,Male,26,Bachelors,18,64,37,58,93,8.0,2,54,Rural,Software Engineer,143412,0 +46248,Female,49,Diploma,5,97,86,54,77,2.0,2,63,Semi-Urban,Manager,49442,1 +46249,Male,31,Bachelors,9,66,52,75,0,9.0,6,46,Urban,HR Executive,133384,1 +46250,Female,27,Diploma,12,66,55,26,0,8.0,3,92,Urban,Data Analyst,38313,0 +46251,Male,43,Masters,9,90,82,92,10,0.0,3,45,Semi-Urban,ML Engineer,98076,1 +46252,Female,46,Masters,2,22,92,61,80,9.0,5,32,Urban,Manager,108119,0 +46253,Female,51,Diploma,6,40,77,52,14,4.0,5,20,Urban,ML Engineer,29420,0 +46254,Female,28,Bachelors,5,13,83,88,97,8.0,3,88,Urban,Data Analyst,37730,1 +46255,Male,40,Masters,2,55,13,81,66,3.0,6,75,Semi-Urban,Software Engineer,135669,0 +46256,Male,40,Diploma,12,65,13,2,48,5.0,6,29,Urban,Data Analyst,26301,0 +46257,Male,33,Diploma,1,15,30,28,75,3.0,6,96,Semi-Urban,HR Executive,80185,0 +46258,Male,24,High School,14,40,24,61,1,8.0,7,51,Rural,ML Engineer,36391,0 +46259,Male,44,Bachelors,14,19,62,97,70,4.0,1,87,Urban,HR Executive,137704,1 +46260,Female,25,Bachelors,4,5,95,18,49,8.0,5,40,Urban,Data Analyst,149254,0 +46261,Male,49,Bachelors,8,32,10,25,68,2.0,4,4,Urban,Data Analyst,102731,0 +46262,Male,35,PhD,13,79,67,37,28,0.0,2,91,Urban,Manager,58522,1 +46263,Female,42,Bachelors,13,41,68,76,23,9.0,1,90,Urban,Software Engineer,132325,1 +46264,Male,40,Bachelors,18,18,73,43,85,8.0,2,1,Urban,Software Engineer,37531,0 +46265,Male,34,Masters,0,85,67,68,85,9.0,5,45,Semi-Urban,Manager,126924,1 +46266,Female,35,High School,5,70,56,38,17,5.0,6,50,Urban,Manager,39159,0 +46267,Male,24,Diploma,13,39,45,25,5,0.0,2,91,Urban,Manager,129309,0 +46268,Female,21,Bachelors,16,9,16,70,91,2.0,6,82,Semi-Urban,HR Executive,53659,0 +46269,Male,56,Masters,12,77,38,89,72,0.0,5,3,Semi-Urban,ML Engineer,98702,0 +46270,Male,51,Diploma,8,96,36,11,41,4.0,5,37,Rural,ML Engineer,25515,0 +46271,Female,54,Bachelors,12,88,92,90,87,7.0,2,60,Urban,Data Analyst,29020,1 +46272,Other,41,High School,9,67,13,28,94,6.0,1,83,Urban,Manager,62774,0 +46273,Male,37,Bachelors,13,97,52,38,22,1.0,6,82,Urban,ML Engineer,43584,1 +46274,Female,31,High School,5,78,34,33,40,8.0,4,63,Urban,Manager,126424,0 +46275,Male,37,Bachelors,17,19,89,71,83,5.0,6,62,Urban,Manager,143111,1 +46276,Male,38,Bachelors,13,44,34,50,97,9.0,4,8,Urban,Software Engineer,74259,0 +46277,Female,28,High School,11,95,32,95,89,4.0,7,4,Urban,Data Analyst,77201,0 +46278,Male,53,Bachelors,3,10,30,92,9,2.0,5,48,Rural,HR Executive,95048,0 +46279,Female,40,Masters,3,2,54,26,58,4.0,2,83,Semi-Urban,HR Executive,120445,0 +46280,Female,31,Bachelors,4,43,66,57,35,5.0,2,49,Urban,Manager,83842,0 +46281,Female,24,Bachelors,13,43,1,41,46,4.0,4,60,Urban,Manager,72138,0 +46282,Male,46,Diploma,6,46,0,16,95,7.0,4,72,Urban,Manager,90054,0 +46283,Female,22,Bachelors,6,37,9,21,32,7.0,5,72,Urban,Software Engineer,29376,0 +46284,Other,55,Diploma,3,29,7,1,43,2.0,0,30,Semi-Urban,Manager,122361,0 +46285,Male,32,Diploma,3,88,64,87,48,3.0,3,35,Urban,Manager,131085,1 +46286,Male,28,Bachelors,7,48,87,92,47,1.0,5,49,Urban,Software Engineer,31178,1 +46287,Other,38,Bachelors,6,77,47,60,35,6.0,2,64,Urban,Data Analyst,106958,1 +46288,Male,43,Diploma,16,95,73,57,90,9.0,2,84,Urban,Manager,50669,1 +46289,Male,21,Diploma,15,79,59,45,13,3.0,0,64,Semi-Urban,Manager,98725,1 +46290,Male,23,Bachelors,1,31,36,31,53,8.0,6,80,Rural,Software Engineer,128033,0 +46291,Male,57,Bachelors,17,47,43,2,79,2.0,1,49,Urban,Manager,97865,0 +46292,Male,27,Masters,10,79,57,9,7,4.0,7,49,Rural,Data Analyst,134105,0 +46293,Male,34,Bachelors,15,48,87,29,35,1.0,7,27,Rural,Data Analyst,121278,0 +46294,Male,41,Masters,4,79,19,88,2,0.0,2,98,Semi-Urban,ML Engineer,139806,1 +46295,Female,37,Diploma,6,30,90,91,37,1.0,1,12,Semi-Urban,HR Executive,72379,0 +46296,Male,44,Bachelors,18,81,77,57,5,2.0,2,71,Semi-Urban,Data Analyst,134043,1 +46297,Male,28,Bachelors,7,60,37,74,66,4.0,4,98,Semi-Urban,HR Executive,31168,1 +46298,Female,36,Bachelors,0,11,32,62,85,7.0,0,29,Urban,Software Engineer,65257,0 +46299,Female,31,Diploma,8,85,95,87,17,9.0,0,0,Rural,Manager,133571,1 +46300,Male,57,High School,15,87,80,57,37,6.0,2,32,Semi-Urban,HR Executive,132846,1 +46301,Male,53,High School,2,37,78,1,9,6.0,7,86,Rural,HR Executive,48388,0 +46302,Male,48,Masters,6,68,36,47,90,7.0,1,90,Urban,Manager,59665,1 +46303,Male,27,PhD,4,3,53,89,41,3.0,0,58,Rural,ML Engineer,22764,0 +46304,Female,34,Masters,18,74,30,42,84,5.0,1,53,Semi-Urban,Software Engineer,72754,0 +46305,Male,41,High School,9,82,95,66,16,1.0,2,15,Semi-Urban,ML Engineer,47731,1 +46306,Male,56,Bachelors,6,74,34,59,5,1.0,3,38,Urban,ML Engineer,53246,0 +46307,Male,43,Bachelors,13,11,0,93,58,6.0,4,79,Urban,HR Executive,140842,0 +46308,Male,58,PhD,3,59,83,71,32,4.0,7,33,Urban,Manager,84382,1 +46309,Male,39,Bachelors,5,69,24,68,14,1.0,4,25,Semi-Urban,Data Analyst,30904,0 +46310,Female,22,Bachelors,4,7,98,79,50,7.0,7,78,Rural,Software Engineer,48792,1 +46311,Other,29,Diploma,0,21,97,22,62,8.0,4,42,Urban,Software Engineer,125433,0 +46312,Male,49,PhD,9,88,97,22,72,9.0,5,80,Rural,HR Executive,148295,1 +46313,Male,33,Masters,4,79,48,70,42,4.0,3,15,Rural,Data Analyst,102658,0 +46314,Male,39,Masters,16,22,72,64,68,9.0,6,47,Semi-Urban,HR Executive,141066,0 +46315,Female,36,Masters,15,82,87,85,74,6.0,3,30,Semi-Urban,Manager,126129,1 +46316,Male,35,Diploma,17,36,0,93,37,8.0,4,41,Semi-Urban,HR Executive,38255,0 +46317,Female,26,Masters,9,4,61,80,15,6.0,3,83,Urban,Manager,145747,0 +46318,Male,47,Bachelors,13,50,64,85,87,3.0,2,48,Semi-Urban,HR Executive,88625,1 +46319,Male,37,High School,9,39,85,68,49,0.0,6,12,Urban,Software Engineer,137792,0 +46320,Male,28,Diploma,5,89,91,58,68,9.0,7,69,Urban,ML Engineer,38505,1 +46321,Male,55,Bachelors,8,15,91,52,26,8.0,2,56,Semi-Urban,Manager,102555,0 +46322,Female,56,Masters,10,4,2,89,94,3.0,5,18,Rural,ML Engineer,116316,0 +46323,Male,59,Bachelors,3,61,80,45,23,9.0,2,15,Semi-Urban,ML Engineer,73898,0 +46324,Female,40,High School,5,7,81,43,97,5.0,2,53,Urban,HR Executive,66665,0 +46325,Male,51,High School,14,39,55,61,16,3.0,3,44,Rural,ML Engineer,73615,0 +46326,Male,32,Bachelors,12,66,69,74,92,5.0,3,61,Urban,Manager,50841,1 +46327,Male,49,High School,1,85,69,27,62,5.0,0,38,Semi-Urban,Manager,112314,0 +46328,Male,44,Diploma,14,76,77,56,82,3.0,7,28,Semi-Urban,HR Executive,64985,1 +46329,Female,42,Bachelors,15,61,61,94,93,9.0,6,61,Semi-Urban,Data Analyst,45926,1 +46330,Male,31,High School,3,5,66,89,53,7.0,1,64,Urban,Software Engineer,123842,0 +46331,Male,53,Bachelors,9,73,73,44,19,1.0,0,42,Urban,Manager,51719,0 +46332,Male,55,Bachelors,9,59,56,58,16,6.0,6,42,Urban,Manager,22926,0 +46333,Male,27,PhD,19,38,30,67,51,4.0,4,43,Urban,Software Engineer,73164,0 +46334,Female,46,Bachelors,3,7,88,52,94,6.0,3,43,Urban,Data Analyst,39146,0 +46335,Female,37,Diploma,14,37,95,10,31,5.0,2,71,Semi-Urban,ML Engineer,86473,0 +46336,Male,36,Bachelors,15,43,20,99,72,2.0,5,12,Semi-Urban,Data Analyst,112584,0 +46337,Female,28,Masters,13,20,60,68,41,5.0,1,50,Urban,HR Executive,125174,0 +46338,Female,59,High School,8,37,14,76,90,8.0,6,96,Semi-Urban,Manager,133276,0 +46339,Male,23,Bachelors,1,51,1,14,45,8.0,3,80,Semi-Urban,Software Engineer,92247,0 +46340,Male,41,Bachelors,13,48,35,20,82,4.0,6,42,Urban,Data Analyst,27818,0 +46341,Male,52,Masters,0,29,50,74,15,3.0,2,22,Urban,Data Analyst,136822,0 +46342,Male,39,High School,13,94,63,60,27,9.0,5,9,Urban,Data Analyst,82668,0 +46343,Male,58,Diploma,18,39,38,51,67,0.0,3,52,Rural,Data Analyst,84377,0 +46344,Male,50,Bachelors,16,59,80,29,96,4.0,2,75,Urban,Software Engineer,61362,1 +46345,Male,36,High School,4,59,6,95,45,0.0,5,67,Rural,Software Engineer,71227,0 +46346,Female,48,Masters,10,91,22,37,0,0.0,7,70,Rural,Manager,122007,0 +46347,Male,59,Bachelors,16,83,32,55,79,0.0,1,81,Semi-Urban,Data Analyst,60698,1 +46348,Female,29,Masters,6,35,4,40,54,6.0,2,76,Semi-Urban,HR Executive,90288,0 +46349,Female,24,Bachelors,15,73,45,80,34,2.0,0,14,Rural,HR Executive,120104,0 +46350,Female,22,Bachelors,7,49,7,46,66,1.0,2,56,Urban,Software Engineer,143959,0 +46351,Male,41,Diploma,13,99,93,36,75,8.0,2,4,Rural,HR Executive,122560,0 +46352,Male,31,Bachelors,18,92,50,36,25,5.0,2,77,Semi-Urban,Data Analyst,120683,1 +46353,Male,56,Bachelors,10,98,3,68,67,6.0,7,75,Urban,Manager,93306,1 +46354,Other,42,High School,11,4,60,71,27,1.0,5,85,Urban,Software Engineer,75450,0 +46355,Female,50,Masters,9,70,51,72,56,3.0,7,68,Urban,ML Engineer,37379,1 +46356,Male,38,PhD,6,19,10,76,93,6.0,4,19,Urban,Manager,111016,0 +46357,Male,26,Diploma,17,71,87,77,54,8.0,0,20,Rural,Software Engineer,63561,1 +46358,Female,28,Bachelors,2,68,72,64,89,9.0,7,51,Semi-Urban,HR Executive,127031,1 +46359,Female,51,Bachelors,14,51,62,70,66,0.0,0,47,Rural,Manager,72076,0 +46360,Female,33,Bachelors,7,70,29,78,94,9.0,0,6,Urban,HR Executive,105218,0 +46361,Female,34,Masters,13,37,14,25,98,9.0,5,14,Urban,Software Engineer,38482,0 +46362,Male,39,Bachelors,3,97,12,6,17,2.0,2,10,Urban,Manager,54878,0 +46363,Female,25,High School,2,16,31,93,27,6.0,3,85,Rural,HR Executive,130274,0 +46364,Female,58,Bachelors,3,9,86,62,92,8.0,4,53,Rural,HR Executive,83964,0 +46365,Female,55,Diploma,8,22,26,41,27,0.0,2,19,Urban,Data Analyst,70801,0 +46366,Male,32,Bachelors,2,56,6,50,51,8.0,5,43,Urban,ML Engineer,130242,0 +46367,Female,39,Masters,1,19,95,20,44,7.0,5,80,Semi-Urban,HR Executive,48360,0 +46368,Female,37,Bachelors,12,66,95,39,50,8.0,6,29,Semi-Urban,Manager,44671,0 +46369,Male,59,Bachelors,19,51,0,39,80,0.0,5,29,Semi-Urban,Data Analyst,112402,0 +46370,Male,38,Masters,5,7,7,51,5,7.0,4,20,Urban,HR Executive,90519,0 +46371,Female,57,Bachelors,9,15,99,84,6,1.0,6,11,Semi-Urban,HR Executive,87392,0 +46372,Female,49,Bachelors,2,13,45,3,43,5.0,1,25,Urban,ML Engineer,22868,0 +46373,Male,41,Bachelors,6,41,38,89,34,1.0,3,95,Urban,ML Engineer,104492,1 +46374,Female,23,Bachelors,4,8,63,22,55,7.0,3,36,Urban,Software Engineer,37491,0 +46375,Male,51,Masters,2,96,54,69,90,4.0,6,57,Urban,ML Engineer,33110,1 +46376,Female,58,High School,19,65,14,2,86,7.0,2,14,Semi-Urban,ML Engineer,110756,0 +46377,Other,56,Bachelors,17,4,56,53,95,6.0,6,75,Urban,Software Engineer,50934,0 +46378,Male,40,High School,3,18,8,90,82,8.0,2,79,Rural,ML Engineer,48449,0 +46379,Other,24,Masters,3,6,91,26,83,4.0,2,11,Semi-Urban,ML Engineer,141056,0 +46380,Male,40,High School,15,93,13,19,86,5.0,4,71,Rural,Data Analyst,48746,0 +46381,Female,48,High School,7,57,53,54,33,2.0,5,98,Urban,Manager,85029,1 +46382,Male,48,High School,11,64,33,31,53,2.0,5,12,Semi-Urban,ML Engineer,146514,0 +46383,Male,55,Bachelors,0,68,98,11,92,3.0,2,61,Semi-Urban,HR Executive,31624,1 +46384,Female,30,Masters,7,95,30,19,29,6.0,2,16,Urban,Data Analyst,142540,0 +46385,Female,29,Masters,10,79,7,46,79,4.0,0,46,Urban,HR Executive,120359,0 +46386,Male,48,Bachelors,12,13,31,23,14,5.0,1,66,Semi-Urban,Data Analyst,94755,0 +46387,Male,46,Bachelors,2,19,82,7,24,8.0,6,37,Urban,Manager,80372,0 +46388,Male,39,High School,19,94,47,65,80,6.0,7,97,Urban,Software Engineer,37286,1 +46389,Female,58,PhD,3,38,11,2,85,5.0,5,44,Semi-Urban,Manager,107422,0 +46390,Male,28,Masters,16,20,0,60,18,3.0,3,77,Urban,Software Engineer,103558,0 +46391,Male,23,Bachelors,12,93,44,40,70,1.0,6,53,Urban,Software Engineer,85241,0 +46392,Female,34,Bachelors,19,78,63,85,47,6.0,5,43,Urban,ML Engineer,101589,1 +46393,Female,24,Diploma,19,55,10,29,67,9.0,5,56,Urban,Software Engineer,133833,0 +46394,Male,42,High School,10,61,83,30,86,0.0,7,11,Urban,Software Engineer,109022,0 +46395,Female,50,Masters,5,22,63,4,52,0.0,0,88,Urban,Software Engineer,43159,0 +46396,Female,31,Bachelors,8,2,4,67,74,1.0,7,29,Rural,Manager,67723,0 +46397,Male,27,Bachelors,5,74,32,63,36,4.0,2,81,Semi-Urban,Data Analyst,39637,1 +46398,Female,32,PhD,10,49,60,73,34,4.0,2,37,Semi-Urban,ML Engineer,71475,0 +46399,Female,48,High School,4,18,80,65,26,0.0,0,62,Semi-Urban,Data Analyst,97411,0 +46400,Male,55,Bachelors,0,44,6,97,72,6.0,7,40,Semi-Urban,HR Executive,89329,0 +46401,Male,45,Masters,5,19,71,59,88,2.0,4,55,Semi-Urban,Data Analyst,123314,0 +46402,Female,24,Bachelors,0,30,82,92,62,9.0,3,25,Urban,ML Engineer,53347,0 +46403,Male,35,Bachelors,6,89,50,45,38,5.0,1,87,Urban,Manager,47129,1 +46404,Male,37,High School,0,33,16,28,87,1.0,2,19,Urban,ML Engineer,122620,0 +46405,Male,35,High School,15,24,38,16,60,6.0,7,13,Rural,Data Analyst,125549,0 +46406,Male,59,Diploma,11,44,79,64,50,9.0,7,17,Semi-Urban,Data Analyst,42817,0 +46407,Male,55,Bachelors,2,36,34,69,88,6.0,6,51,Rural,ML Engineer,54779,0 +46408,Male,46,High School,11,79,59,7,87,7.0,5,7,Urban,ML Engineer,114965,0 +46409,Male,22,Bachelors,15,54,28,55,15,6.0,5,59,Urban,Data Analyst,94671,0 +46410,Male,46,Masters,4,88,10,77,18,6.0,3,78,Urban,Manager,111095,1 +46411,Male,45,Bachelors,3,83,15,70,77,7.0,3,52,Urban,Data Analyst,130491,0 +46412,Female,43,Masters,2,34,7,13,44,0.0,6,28,Urban,HR Executive,120962,0 +46413,Female,33,High School,1,91,97,73,56,5.0,1,16,Semi-Urban,Software Engineer,70539,1 +46414,Male,46,Diploma,16,16,87,65,79,0.0,4,55,Urban,Software Engineer,27282,0 +46415,Other,25,High School,1,53,0,36,7,6.0,4,63,Semi-Urban,ML Engineer,89375,0 +46416,Female,34,Masters,7,3,64,46,66,3.0,0,31,Urban,Data Analyst,146927,0 +46417,Female,25,High School,16,40,76,3,0,5.0,7,74,Urban,HR Executive,135463,0 +46418,Male,36,Masters,17,35,85,8,12,5.0,2,73,Semi-Urban,HR Executive,117004,0 +46419,Male,52,Masters,19,89,23,42,39,2.0,0,74,Semi-Urban,ML Engineer,58097,0 +46420,Other,28,Diploma,6,63,73,95,57,7.0,5,19,Urban,Software Engineer,143154,1 +46421,Male,50,Bachelors,14,83,93,88,90,3.0,4,48,Urban,ML Engineer,109534,1 +46422,Female,48,Diploma,11,45,78,89,96,0.0,6,18,Urban,Software Engineer,40578,0 +46423,Male,39,Bachelors,16,45,78,11,90,2.0,0,46,Urban,Data Analyst,75676,0 +46424,Female,29,Diploma,12,25,18,49,58,8.0,0,66,Semi-Urban,ML Engineer,117719,0 +46425,Male,57,Bachelors,18,39,95,6,49,7.0,4,64,Rural,Software Engineer,121808,0 +46426,Male,42,PhD,14,36,8,68,91,0.0,4,12,Semi-Urban,ML Engineer,94330,0 +46427,Female,26,PhD,12,39,42,74,21,9.0,4,58,Urban,HR Executive,59302,0 +46428,Male,26,Masters,6,6,83,68,97,8.0,0,54,Urban,Software Engineer,33478,0 +46429,Male,21,PhD,11,18,16,83,85,4.0,4,78,Semi-Urban,Software Engineer,88102,0 +46430,Male,56,Masters,4,43,32,31,92,0.0,6,87,Urban,ML Engineer,61409,0 +46431,Male,50,Bachelors,1,51,48,25,96,2.0,1,90,Rural,Manager,41645,0 +46432,Male,28,High School,2,15,77,68,51,1.0,5,21,Urban,Software Engineer,117674,0 +46433,Female,43,High School,15,4,11,26,0,7.0,3,5,Urban,HR Executive,71999,0 +46434,Female,43,Masters,14,24,2,93,47,2.0,6,10,Semi-Urban,ML Engineer,60846,0 +46435,Other,23,Bachelors,6,1,46,21,32,4.0,2,27,Urban,HR Executive,51699,0 +46436,Male,45,Bachelors,13,48,39,96,0,4.0,1,9,Urban,Software Engineer,137232,0 +46437,Male,53,Masters,15,50,92,20,70,3.0,6,40,Semi-Urban,Software Engineer,113146,0 +46438,Female,24,Bachelors,5,39,26,20,98,3.0,5,58,Urban,HR Executive,141445,0 +46439,Female,44,Bachelors,2,80,13,55,12,8.0,2,92,Urban,Data Analyst,123837,0 +46440,Female,21,PhD,16,24,43,19,36,9.0,4,57,Urban,HR Executive,130210,0 +46441,Male,29,Masters,16,33,53,82,85,6.0,2,66,Urban,Software Engineer,100982,0 +46442,Female,50,PhD,3,91,80,70,68,8.0,1,85,Rural,ML Engineer,96136,1 +46443,Male,58,Diploma,18,22,47,79,31,5.0,6,7,Urban,HR Executive,89901,0 +46444,Male,26,Masters,5,13,83,66,27,7.0,5,78,Rural,Data Analyst,52889,1 +46445,Female,39,Diploma,4,59,46,9,43,4.0,5,9,Urban,Manager,43698,0 +46446,Male,35,Diploma,10,56,41,59,74,5.0,3,9,Semi-Urban,Software Engineer,28781,0 +46447,Male,54,High School,3,87,66,41,63,4.0,2,57,Urban,Data Analyst,80073,1 +46448,Female,49,Diploma,15,43,61,9,52,5.0,2,13,Urban,HR Executive,65771,0 +46449,Female,23,Bachelors,4,75,73,81,9,5.0,5,97,Urban,Manager,41745,1 +46450,Female,23,High School,17,66,0,90,83,3.0,7,82,Urban,Data Analyst,145933,0 +46451,Male,52,Diploma,19,35,64,83,64,3.0,4,19,Urban,Software Engineer,149826,0 +46452,Male,51,Bachelors,18,12,54,33,86,0.0,6,78,Urban,HR Executive,89333,0 +46453,Male,49,Masters,15,65,51,91,88,6.0,1,83,Urban,Manager,51861,1 +46454,Female,25,Bachelors,4,14,45,47,44,7.0,7,67,Semi-Urban,Data Analyst,136236,0 +46455,Male,22,Bachelors,10,86,38,16,35,6.0,4,71,Urban,Data Analyst,106519,0 +46456,Male,36,Diploma,9,5,31,46,28,0.0,5,32,Urban,Data Analyst,147695,0 +46457,Male,51,Masters,15,25,86,25,6,1.0,0,45,Semi-Urban,ML Engineer,35305,0 +46458,Male,37,Bachelors,1,80,84,80,24,5.0,1,82,Rural,Software Engineer,141994,1 +46459,Female,29,Bachelors,3,12,72,25,53,6.0,5,24,Semi-Urban,Software Engineer,72515,0 +46460,Male,26,High School,19,53,43,1,67,1.0,7,98,Semi-Urban,HR Executive,48609,0 +46461,Female,36,Diploma,17,33,46,13,1,4.0,5,36,Urban,Software Engineer,68450,0 +46462,Male,24,High School,9,79,50,33,50,9.0,7,94,Semi-Urban,Data Analyst,64624,1 +46463,Male,57,Masters,15,87,16,0,23,1.0,3,72,Urban,Manager,78498,0 +46464,Female,23,Bachelors,1,26,87,66,18,0.0,6,43,Rural,Software Engineer,46691,0 +46465,Female,23,Bachelors,6,92,0,83,4,8.0,5,73,Urban,Manager,31744,1 +46466,Female,44,Diploma,18,50,95,52,91,1.0,4,19,Urban,HR Executive,44179,0 +46467,Female,25,Bachelors,8,46,61,61,75,7.0,1,62,Semi-Urban,Software Engineer,63614,0 +46468,Male,59,High School,1,6,34,48,58,6.0,4,15,Urban,ML Engineer,32634,0 +46469,Male,34,Diploma,15,23,82,56,72,2.0,5,47,Urban,Manager,123732,0 +46470,Male,48,Masters,3,43,3,20,51,3.0,7,29,Urban,Data Analyst,54187,0 +46471,Female,28,Bachelors,9,25,24,0,80,5.0,0,52,Urban,Software Engineer,47360,0 +46472,Male,57,Diploma,14,75,32,32,25,9.0,0,75,Rural,HR Executive,75641,0 +46473,Male,53,Bachelors,0,31,77,66,63,9.0,4,84,Urban,Manager,69716,1 +46474,Female,39,Diploma,7,7,90,84,12,0.0,7,6,Urban,HR Executive,37891,0 +46475,Male,38,Bachelors,14,71,84,36,2,4.0,3,30,Urban,Data Analyst,26824,0 +46476,Male,39,Diploma,18,14,64,74,8,8.0,3,78,Urban,HR Executive,93934,0 +46477,Male,55,Masters,11,34,84,73,59,8.0,4,62,Urban,ML Engineer,100240,1 +46478,Female,33,Bachelors,10,37,51,98,66,4.0,2,52,Urban,Software Engineer,48366,0 +46479,Other,55,High School,16,82,30,19,24,5.0,3,51,Rural,Software Engineer,84467,0 +46480,Male,37,Diploma,11,7,15,0,22,5.0,7,21,Urban,ML Engineer,117797,0 +46481,Male,59,Bachelors,8,36,99,45,27,2.0,7,1,Semi-Urban,ML Engineer,145647,0 +46482,Male,44,Diploma,1,79,38,6,75,7.0,7,12,Urban,Data Analyst,21961,0 +46483,Male,50,PhD,4,52,58,2,98,1.0,4,67,Urban,Software Engineer,109520,0 +46484,Male,40,Bachelors,0,5,80,30,46,9.0,6,37,Rural,Data Analyst,123500,0 +46485,Male,47,High School,13,56,75,96,6,7.0,4,72,Urban,Data Analyst,78533,1 +46486,Female,30,High School,9,47,56,14,21,1.0,4,1,Rural,Software Engineer,39868,0 +46487,Male,47,Bachelors,17,23,88,74,98,1.0,0,18,Rural,HR Executive,67364,0 +46488,Female,31,Bachelors,16,35,67,15,95,2.0,3,66,Semi-Urban,Software Engineer,103345,0 +46489,Male,51,Masters,12,37,52,89,8,8.0,4,21,Urban,Software Engineer,130306,0 +46490,Male,57,Diploma,4,73,66,8,69,1.0,6,27,Urban,HR Executive,31145,0 +46491,Male,37,High School,6,69,30,70,99,8.0,1,75,Rural,Manager,123570,1 +46492,Female,24,High School,12,42,28,7,83,6.0,4,47,Urban,Data Analyst,32754,0 +46493,Female,34,Masters,18,65,76,8,16,7.0,0,15,Urban,Manager,142417,0 +46494,Male,54,PhD,14,41,32,58,0,5.0,1,49,Rural,Software Engineer,106400,0 +46495,Male,33,Diploma,9,43,77,23,53,6.0,3,23,Semi-Urban,HR Executive,134246,0 +46496,Female,29,Diploma,12,91,10,84,50,5.0,3,11,Urban,Software Engineer,26567,0 +46497,Female,45,Diploma,18,32,88,97,42,4.0,7,29,Semi-Urban,HR Executive,94784,1 +46498,Female,24,Bachelors,0,36,16,51,16,7.0,7,33,Urban,HR Executive,93576,0 +46499,Male,42,Diploma,18,67,92,86,77,8.0,7,18,Semi-Urban,HR Executive,115505,1 +46500,Female,32,Masters,10,3,58,40,25,1.0,3,32,Semi-Urban,HR Executive,72601,0 +46501,Male,51,Bachelors,1,54,18,30,68,4.0,3,14,Rural,Data Analyst,53047,0 +46502,Male,21,Bachelors,7,91,27,50,74,5.0,5,35,Urban,Software Engineer,23240,0 +46503,Male,44,Bachelors,3,96,47,38,30,9.0,1,1,Rural,Software Engineer,53423,0 +46504,Male,22,Bachelors,13,70,22,83,33,7.0,6,11,Semi-Urban,ML Engineer,24522,0 +46505,Male,36,Diploma,2,74,57,66,11,4.0,2,69,Rural,ML Engineer,33748,1 +46506,Male,58,Bachelors,10,1,15,12,7,9.0,6,91,Urban,Software Engineer,91212,0 +46507,Male,37,Diploma,11,10,37,23,78,3.0,6,59,Urban,Data Analyst,78981,0 +46508,Female,35,Diploma,10,19,17,37,41,8.0,2,53,Rural,Manager,104731,0 +46509,Other,32,Masters,4,40,97,6,17,2.0,7,50,Urban,Software Engineer,64586,0 +46510,Male,59,High School,14,92,25,75,74,2.0,2,56,Urban,HR Executive,81029,1 +46511,Male,43,Diploma,9,27,70,6,87,0.0,7,22,Urban,Software Engineer,58830,0 +46512,Male,53,Masters,1,87,15,66,91,1.0,1,1,Semi-Urban,HR Executive,144041,0 +46513,Male,51,Masters,16,77,48,51,42,1.0,2,67,Rural,Data Analyst,37747,1 +46514,Male,49,High School,3,87,35,23,53,2.0,4,27,Urban,Manager,22542,0 +46515,Male,53,Bachelors,14,63,80,41,90,2.0,2,64,Urban,Manager,73530,1 +46516,Male,52,Bachelors,16,85,38,30,6,7.0,1,63,Urban,Data Analyst,97127,0 +46517,Female,43,Diploma,0,71,83,44,2,0.0,2,17,Rural,Manager,121706,0 +46518,Other,24,PhD,18,59,33,68,71,3.0,3,97,Semi-Urban,HR Executive,39630,1 +46519,Female,52,Masters,3,25,27,40,35,6.0,1,33,Urban,HR Executive,129503,0 +46520,Male,58,High School,19,56,59,44,64,4.0,1,55,Semi-Urban,HR Executive,31137,0 +46521,Female,25,Bachelors,15,31,71,65,45,3.0,2,53,Urban,Manager,81308,0 +46522,Male,26,Diploma,10,75,22,75,12,2.0,2,46,Semi-Urban,Manager,90306,0 +46523,Male,38,Masters,3,46,79,8,15,3.0,1,12,Semi-Urban,HR Executive,21205,0 +46524,Female,40,Diploma,4,55,3,64,37,7.0,2,53,Rural,Data Analyst,66012,0 +46525,Female,24,Diploma,3,23,54,8,67,1.0,3,71,Urban,Software Engineer,69088,0 +46526,Female,42,Masters,9,96,70,65,58,5.0,0,96,Urban,Data Analyst,56636,1 +46527,Male,22,Bachelors,1,95,64,46,22,1.0,5,60,Semi-Urban,ML Engineer,142068,1 +46528,Female,25,Masters,6,27,27,50,98,6.0,5,2,Semi-Urban,Software Engineer,99987,0 +46529,Female,30,Bachelors,1,15,26,18,5,4.0,1,36,Rural,ML Engineer,46432,0 +46530,Male,34,Bachelors,9,35,97,93,60,8.0,1,87,Rural,HR Executive,68043,1 +46531,Male,51,Diploma,4,46,66,0,84,3.0,7,74,Urban,ML Engineer,80052,0 +46532,Male,35,High School,13,92,46,46,85,5.0,7,6,Rural,Software Engineer,82060,0 +46533,Male,44,Masters,11,79,41,66,24,6.0,5,98,Semi-Urban,HR Executive,84712,1 +46534,Female,28,Bachelors,4,20,57,37,59,6.0,1,89,Rural,Manager,24858,0 +46535,Male,23,Bachelors,9,55,48,31,89,9.0,5,64,Urban,ML Engineer,21500,0 +46536,Female,55,Bachelors,13,90,43,51,56,5.0,2,15,Urban,Manager,71306,0 +46537,Female,57,PhD,0,8,16,8,12,7.0,1,80,Urban,HR Executive,114490,0 +46538,Male,41,High School,10,44,93,37,44,1.0,3,92,Urban,Data Analyst,53353,1 +46539,Male,41,Diploma,7,75,69,73,94,4.0,5,25,Urban,HR Executive,139649,1 +46540,Male,24,Diploma,4,69,23,76,26,5.0,3,83,Urban,Data Analyst,25317,1 +46541,Male,48,High School,1,41,26,97,19,9.0,5,18,Urban,Manager,97817,0 +46542,Male,48,High School,8,26,20,81,40,8.0,2,43,Urban,Data Analyst,143548,0 +46543,Male,40,Bachelors,15,43,98,20,64,9.0,2,64,Urban,HR Executive,91579,0 +46544,Female,58,Diploma,6,5,7,66,1,9.0,1,17,Urban,Data Analyst,104993,0 +46545,Female,22,Masters,14,18,40,1,34,9.0,5,66,Semi-Urban,Software Engineer,119423,0 +46546,Female,37,Bachelors,17,3,99,65,45,0.0,1,93,Rural,ML Engineer,87925,1 +46547,Female,44,Diploma,15,22,69,9,84,5.0,5,64,Rural,Software Engineer,109284,0 +46548,Female,42,Masters,1,1,3,63,74,8.0,0,74,Urban,Data Analyst,79769,0 +46549,Male,44,Masters,9,1,0,84,68,6.0,7,7,Semi-Urban,Software Engineer,116863,0 +46550,Male,46,Diploma,13,38,98,82,95,7.0,5,6,Semi-Urban,Software Engineer,55769,0 +46551,Female,25,Masters,10,37,25,25,24,9.0,3,12,Urban,Manager,57596,0 +46552,Female,26,Bachelors,0,56,5,94,17,7.0,5,46,Urban,ML Engineer,124825,0 +46553,Male,49,Diploma,10,66,35,46,43,0.0,5,89,Urban,Manager,39493,1 +46554,Male,22,Bachelors,17,77,99,88,65,4.0,7,89,Rural,Manager,81271,1 +46555,Male,49,Diploma,1,5,75,98,89,1.0,6,10,Semi-Urban,ML Engineer,109577,0 +46556,Male,24,Bachelors,1,57,34,64,1,7.0,0,32,Semi-Urban,Software Engineer,144292,0 +46557,Male,38,PhD,0,0,50,6,10,9.0,3,92,Rural,Software Engineer,21692,0 +46558,Male,52,Bachelors,13,25,35,24,3,7.0,1,21,Semi-Urban,ML Engineer,55831,0 +46559,Female,46,Masters,8,72,83,98,81,5.0,7,13,Rural,HR Executive,90983,1 +46560,Female,40,Bachelors,1,96,7,48,73,8.0,2,2,Urban,HR Executive,105121,0 +46561,Female,48,Masters,5,12,97,93,48,0.0,1,88,Semi-Urban,Manager,115435,1 +46562,Male,22,High School,18,24,48,54,4,4.0,6,84,Urban,Software Engineer,108500,0 +46563,Male,57,Diploma,9,50,44,39,65,8.0,3,74,Rural,HR Executive,69813,0 +46564,Male,38,Masters,0,5,8,76,46,0.0,7,84,Urban,Manager,144894,0 +46565,Female,59,Bachelors,13,7,30,80,8,2.0,6,1,Urban,ML Engineer,22113,0 +46566,Male,42,High School,12,74,77,20,88,6.0,2,8,Semi-Urban,Manager,118421,0 +46567,Male,45,PhD,17,78,1,13,81,5.0,2,1,Rural,ML Engineer,143401,0 +46568,Male,56,Masters,13,58,2,74,28,8.0,2,12,Semi-Urban,HR Executive,89523,0 +46569,Male,23,High School,6,46,26,47,40,2.0,6,48,Semi-Urban,Manager,147030,0 +46570,Male,28,Diploma,1,37,97,22,0,6.0,1,60,Urban,Manager,88514,0 +46571,Female,23,Masters,15,46,82,23,33,1.0,3,16,Rural,Software Engineer,75728,0 +46572,Male,47,Bachelors,3,20,54,74,4,7.0,1,6,Urban,Manager,127538,0 +46573,Male,57,Bachelors,10,18,99,44,91,4.0,1,75,Urban,Software Engineer,145528,1 +46574,Male,51,Masters,18,36,84,81,92,6.0,3,75,Urban,HR Executive,23912,1 +46575,Female,22,High School,12,0,22,93,73,9.0,1,64,Semi-Urban,Data Analyst,140477,0 +46576,Male,44,Bachelors,2,11,98,47,99,5.0,6,17,Urban,Manager,115631,0 +46577,Female,59,Diploma,6,52,25,86,37,6.0,0,57,Urban,Manager,104317,0 +46578,Male,38,Bachelors,9,63,26,62,3,8.0,4,10,Semi-Urban,Data Analyst,140808,0 +46579,Male,50,High School,19,57,94,95,79,5.0,6,80,Urban,ML Engineer,85228,1 +46580,Male,37,High School,2,81,94,77,15,8.0,7,72,Urban,ML Engineer,50365,1 +46581,Male,25,Diploma,1,80,73,2,94,0.0,3,91,Semi-Urban,Data Analyst,62673,1 +46582,Female,24,Masters,9,22,21,93,71,3.0,1,42,Urban,Manager,73715,0 +46583,Female,21,Masters,4,15,93,71,97,1.0,0,52,Semi-Urban,HR Executive,56172,0 +46584,Female,36,Bachelors,8,10,94,85,6,6.0,4,35,Semi-Urban,Data Analyst,61478,0 +46585,Male,48,High School,10,55,78,21,3,5.0,3,1,Semi-Urban,HR Executive,78649,0 +46586,Male,56,Bachelors,5,82,38,49,36,8.0,5,63,Semi-Urban,Software Engineer,97294,0 +46587,Female,24,High School,0,86,17,82,18,3.0,7,54,Semi-Urban,HR Executive,117580,0 +46588,Male,24,Masters,15,57,9,56,16,2.0,6,97,Urban,HR Executive,140278,0 +46589,Female,40,Diploma,14,60,79,3,1,6.0,2,75,Urban,HR Executive,104420,0 +46590,Other,49,Masters,1,85,70,32,13,7.0,3,78,Urban,HR Executive,141465,1 +46591,Male,51,High School,13,68,37,8,73,7.0,4,61,Rural,Software Engineer,30262,0 +46592,Male,26,Bachelors,2,96,49,96,47,4.0,3,24,Urban,Manager,42410,1 +46593,Female,25,PhD,6,45,31,86,45,7.0,6,11,Semi-Urban,Data Analyst,137285,0 +46594,Male,22,Diploma,7,63,45,11,95,5.0,5,2,Urban,Manager,68178,0 +46595,Male,58,Bachelors,18,71,43,39,42,3.0,5,53,Urban,Data Analyst,117070,0 +46596,Male,54,Bachelors,10,16,48,18,13,7.0,4,39,Rural,ML Engineer,141007,0 +46597,Male,49,Bachelors,9,89,31,98,24,4.0,1,48,Urban,Software Engineer,71603,1 +46598,Female,34,Diploma,17,53,43,65,18,8.0,0,98,Rural,HR Executive,129328,1 +46599,Male,38,Bachelors,12,27,19,70,88,1.0,5,77,Urban,Manager,148270,0 +46600,Female,40,High School,15,93,63,65,52,2.0,4,21,Semi-Urban,Manager,75724,1 +46601,Female,41,Masters,10,6,52,37,87,0.0,2,45,Urban,ML Engineer,54380,0 +46602,Male,45,Bachelors,16,0,7,2,38,2.0,5,16,Rural,Software Engineer,70362,0 +46603,Female,31,Bachelors,5,98,85,93,62,1.0,2,27,Semi-Urban,Software Engineer,143077,1 +46604,Male,52,High School,6,51,64,80,81,6.0,4,82,Semi-Urban,Software Engineer,134797,1 +46605,Female,37,Bachelors,16,27,60,92,27,4.0,1,54,Semi-Urban,Manager,79065,0 +46606,Female,28,Masters,0,74,29,11,26,0.0,3,10,Rural,Software Engineer,92641,0 +46607,Male,45,Bachelors,13,89,2,48,91,7.0,5,57,Semi-Urban,Data Analyst,86379,0 +46608,Female,25,Masters,8,41,96,73,28,4.0,6,32,Semi-Urban,HR Executive,58701,1 +46609,Male,29,Bachelors,7,70,87,5,94,8.0,4,66,Urban,HR Executive,22007,0 +46610,Female,43,Masters,17,63,38,31,78,0.0,3,28,Semi-Urban,Data Analyst,46470,0 +46611,Female,36,Masters,14,83,41,32,19,5.0,5,12,Semi-Urban,ML Engineer,136739,0 +46612,Female,33,Bachelors,11,9,85,0,1,4.0,2,41,Urban,ML Engineer,124726,0 +46613,Male,31,High School,15,77,40,19,98,4.0,1,81,Urban,Software Engineer,114105,0 +46614,Female,30,Diploma,12,95,78,96,22,1.0,1,74,Semi-Urban,Manager,60400,1 +46615,Female,55,Diploma,17,11,10,36,51,4.0,1,99,Urban,HR Executive,62339,0 +46616,Male,33,Masters,9,24,56,79,9,9.0,7,89,Urban,Manager,75107,1 +46617,Male,27,High School,15,24,55,60,96,3.0,7,12,Urban,ML Engineer,47037,0 +46618,Male,59,Bachelors,10,81,84,51,67,3.0,0,97,Semi-Urban,Software Engineer,108321,1 +46619,Male,56,Diploma,5,48,93,13,48,8.0,2,51,Rural,Data Analyst,67404,0 +46620,Male,35,Diploma,7,15,35,6,78,7.0,4,56,Rural,ML Engineer,35960,0 +46621,Male,47,Bachelors,17,76,73,24,45,3.0,0,38,Urban,Data Analyst,61117,0 +46622,Female,41,Bachelors,15,63,6,25,67,0.0,3,55,Semi-Urban,HR Executive,94485,0 +46623,Female,51,Bachelors,3,24,25,99,56,9.0,3,36,Semi-Urban,Data Analyst,111324,0 +46624,Female,28,Diploma,13,28,55,51,66,5.0,4,88,Rural,HR Executive,39811,0 +46625,Female,43,Masters,10,13,35,96,85,2.0,5,70,Urban,Data Analyst,31547,0 +46626,Male,46,Bachelors,18,46,70,46,36,9.0,1,10,Rural,Data Analyst,112598,0 +46627,Male,27,High School,4,39,82,75,64,7.0,1,54,Urban,Manager,99619,1 +46628,Female,56,High School,0,8,27,22,12,9.0,3,45,Urban,Software Engineer,134388,0 +46629,Female,30,Diploma,13,64,52,63,6,5.0,5,11,Urban,Data Analyst,53972,0 +46630,Male,44,High School,0,48,8,18,84,3.0,6,2,Urban,HR Executive,66136,0 +46631,Male,57,Diploma,11,16,88,97,99,9.0,5,20,Urban,HR Executive,124297,0 +46632,Male,25,Bachelors,7,12,36,60,43,2.0,4,69,Semi-Urban,Data Analyst,53804,0 +46633,Male,38,Masters,4,24,94,41,26,9.0,4,42,Semi-Urban,ML Engineer,138202,0 +46634,Male,22,Masters,16,72,20,34,40,6.0,0,91,Urban,ML Engineer,71065,0 +46635,Female,52,Bachelors,7,69,57,63,6,2.0,1,87,Urban,Manager,113396,1 +46636,Female,33,Bachelors,17,18,3,10,0,9.0,1,40,Semi-Urban,Manager,128759,0 +46637,Male,50,High School,8,87,81,97,4,5.0,1,94,Rural,HR Executive,128048,1 +46638,Male,21,Masters,15,35,2,78,73,5.0,2,35,Semi-Urban,HR Executive,80871,0 +46639,Female,58,Masters,6,9,29,41,76,8.0,7,56,Urban,Software Engineer,105459,0 +46640,Male,58,Bachelors,12,84,39,59,76,1.0,4,90,Urban,ML Engineer,56746,1 +46641,Female,46,Diploma,6,10,75,21,6,9.0,1,15,Semi-Urban,Software Engineer,136261,0 +46642,Male,33,Bachelors,8,16,63,58,25,7.0,7,54,Semi-Urban,HR Executive,36309,0 +46643,Male,56,Bachelors,17,76,77,4,36,9.0,5,24,Urban,Manager,28180,0 +46644,Male,57,Masters,14,16,44,97,58,3.0,7,24,Urban,Software Engineer,142383,0 +46645,Female,57,PhD,19,62,4,83,24,0.0,3,67,Urban,ML Engineer,147660,0 +46646,Male,57,Masters,13,52,61,72,11,0.0,6,57,Urban,Data Analyst,24728,1 +46647,Male,43,Masters,2,70,3,74,52,2.0,6,40,Semi-Urban,HR Executive,70761,0 +46648,Male,31,PhD,5,82,62,58,24,7.0,2,14,Rural,ML Engineer,146006,0 +46649,Female,39,Bachelors,16,18,4,69,69,9.0,6,55,Rural,Software Engineer,135016,0 +46650,Female,24,Bachelors,8,37,70,43,98,1.0,3,15,Urban,ML Engineer,147469,0 +46651,Male,40,High School,4,90,74,51,63,1.0,3,37,Rural,ML Engineer,23762,1 +46652,Male,31,Masters,5,3,15,46,29,3.0,2,75,Urban,ML Engineer,33480,0 +46653,Female,37,PhD,14,41,19,3,63,8.0,2,76,Rural,Software Engineer,98457,0 +46654,Female,39,PhD,1,90,26,8,84,4.0,3,54,Semi-Urban,HR Executive,112498,0 +46655,Female,57,Diploma,1,92,20,63,19,2.0,2,70,Urban,Data Analyst,124119,1 +46656,Female,33,Diploma,13,67,49,67,76,4.0,4,27,Urban,Data Analyst,99167,0 +46657,Female,21,Bachelors,3,36,27,53,25,3.0,7,79,Rural,ML Engineer,92370,0 +46658,Male,28,Bachelors,8,59,9,50,67,1.0,7,77,Urban,Software Engineer,102206,0 +46659,Male,59,Bachelors,2,77,65,73,95,7.0,3,81,Semi-Urban,Manager,142885,1 +46660,Female,57,Bachelors,3,89,17,52,22,4.0,0,51,Urban,Software Engineer,76365,0 +46661,Male,32,Bachelors,15,93,20,62,11,2.0,7,48,Urban,Data Analyst,46405,0 +46662,Male,40,Diploma,12,35,7,28,58,7.0,1,79,Rural,Data Analyst,127493,0 +46663,Female,58,Diploma,2,57,43,93,6,0.0,1,24,Urban,Software Engineer,148490,0 +46664,Male,29,Bachelors,18,30,14,15,88,9.0,6,66,Urban,Data Analyst,41361,0 +46665,Female,38,Masters,15,28,28,41,29,1.0,2,66,Urban,HR Executive,75853,0 +46666,Male,48,Bachelors,10,25,21,75,53,5.0,1,84,Rural,Manager,133761,0 +46667,Male,52,High School,9,53,67,62,34,3.0,6,72,Semi-Urban,HR Executive,113426,1 +46668,Male,22,Bachelors,9,18,74,30,67,8.0,7,68,Urban,HR Executive,99158,0 +46669,Female,51,Bachelors,12,27,6,15,21,5.0,5,83,Rural,ML Engineer,125960,0 +46670,Female,49,Bachelors,13,66,45,76,35,2.0,1,53,Rural,HR Executive,127357,0 +46671,Male,32,Bachelors,2,18,51,74,39,2.0,6,32,Urban,Manager,106190,0 +46672,Male,41,Masters,15,59,1,77,47,3.0,0,48,Urban,HR Executive,93981,0 +46673,Male,35,Masters,2,89,16,83,94,9.0,2,40,Urban,Manager,133947,0 +46674,Male,35,Bachelors,1,73,97,88,43,1.0,1,39,Semi-Urban,Software Engineer,125321,1 +46675,Male,30,High School,1,2,92,30,26,4.0,4,36,Urban,HR Executive,122182,0 +46676,Male,57,Bachelors,17,92,0,45,98,4.0,6,77,Semi-Urban,Software Engineer,115918,0 +46677,Female,46,Masters,16,68,26,44,63,1.0,0,64,Urban,Data Analyst,69515,0 +46678,Female,58,Masters,3,31,4,16,92,1.0,0,39,Rural,Software Engineer,75738,0 +46679,Male,32,Masters,13,59,72,64,30,2.0,1,80,Rural,ML Engineer,107511,1 +46680,Female,55,Bachelors,3,90,30,63,66,0.0,4,1,Rural,Manager,140389,0 +46681,Male,39,Masters,8,47,16,6,31,1.0,5,65,Urban,Software Engineer,98252,0 +46682,Male,29,Bachelors,18,22,21,30,57,5.0,1,83,Urban,Manager,74193,0 +46683,Female,44,High School,18,94,20,70,50,5.0,3,83,Urban,HR Executive,117963,1 +46684,Male,46,Masters,7,12,77,91,86,7.0,5,34,Rural,Manager,125712,0 +46685,Male,52,Masters,14,82,61,4,91,3.0,0,23,Semi-Urban,ML Engineer,144831,0 +46686,Male,39,Diploma,1,25,60,15,3,1.0,0,6,Rural,Manager,72133,0 +46687,Female,41,Diploma,4,0,27,22,22,9.0,2,12,Urban,Software Engineer,128053,0 +46688,Female,24,High School,2,91,25,25,12,2.0,1,55,Semi-Urban,Software Engineer,118498,0 +46689,Male,34,Bachelors,1,46,38,25,30,0.0,6,26,Rural,Data Analyst,62369,0 +46690,Female,34,Bachelors,10,87,69,91,77,6.0,2,98,Semi-Urban,ML Engineer,22920,1 +46691,Male,59,Masters,6,59,28,65,30,3.0,2,20,Rural,ML Engineer,106816,0 +46692,Female,21,Diploma,1,8,31,46,61,7.0,3,25,Rural,HR Executive,72272,0 +46693,Female,34,Bachelors,3,2,95,87,14,1.0,4,77,Semi-Urban,Software Engineer,74265,1 +46694,Male,57,Bachelors,0,64,88,6,13,8.0,7,30,Urban,HR Executive,78563,0 +46695,Female,21,Bachelors,0,25,34,21,11,7.0,6,22,Urban,Manager,83172,0 +46696,Female,55,Diploma,15,57,55,99,79,9.0,4,12,Semi-Urban,Software Engineer,80783,0 +46697,Female,42,Masters,9,28,28,71,78,2.0,0,75,Semi-Urban,HR Executive,106234,0 +46698,Female,37,Diploma,6,89,42,86,62,2.0,3,52,Semi-Urban,ML Engineer,42164,1 +46699,Male,52,Bachelors,17,76,13,71,6,6.0,3,22,Semi-Urban,Software Engineer,106377,0 +46700,Male,54,Bachelors,18,36,67,58,47,2.0,5,2,Urban,Data Analyst,39557,0 +46701,Male,58,Masters,13,7,49,23,88,6.0,5,29,Urban,Data Analyst,77882,0 +46702,Male,57,Bachelors,5,91,24,77,49,1.0,3,23,Urban,Software Engineer,59156,0 +46703,Male,31,Bachelors,9,79,73,98,79,1.0,2,52,Semi-Urban,ML Engineer,57935,1 +46704,Male,51,Bachelors,19,56,49,28,1,3.0,0,87,Rural,HR Executive,133286,0 +46705,Male,46,Bachelors,13,60,6,32,93,8.0,1,56,Urban,HR Executive,24277,0 +46706,Female,21,Diploma,10,28,66,91,1,5.0,6,21,Semi-Urban,Data Analyst,129548,0 +46707,Female,53,Diploma,0,7,0,57,8,5.0,0,5,Urban,ML Engineer,49573,0 +46708,Male,57,Bachelors,7,36,85,13,20,0.0,5,97,Semi-Urban,ML Engineer,97245,0 +46709,Male,54,Masters,11,0,32,74,57,7.0,0,66,Urban,HR Executive,42942,0 +46710,Male,26,PhD,17,53,21,57,2,0.0,5,60,Rural,HR Executive,31052,0 +46711,Female,57,PhD,12,19,24,53,26,2.0,6,90,Urban,HR Executive,110197,0 +46712,Male,27,High School,19,4,85,70,16,0.0,6,88,Urban,ML Engineer,126383,1 +46713,Other,21,High School,14,96,64,67,60,0.0,1,35,Urban,HR Executive,42627,1 +46714,Female,40,High School,5,38,11,91,69,6.0,4,4,Urban,ML Engineer,54056,0 +46715,Female,57,Diploma,3,35,63,70,21,4.0,5,21,Urban,Manager,30882,0 +46716,Male,31,High School,19,77,50,2,62,4.0,4,65,Rural,ML Engineer,117469,0 +46717,Male,25,Bachelors,4,48,57,11,16,0.0,1,8,Urban,Software Engineer,125587,0 +46718,Other,43,High School,4,10,79,96,52,6.0,0,9,Semi-Urban,ML Engineer,30859,0 +46719,Male,49,Diploma,11,63,82,50,33,3.0,3,40,Urban,HR Executive,136544,1 +46720,Male,48,Bachelors,3,16,70,99,90,1.0,2,75,Urban,HR Executive,99757,1 +46721,Male,26,Bachelors,2,84,26,64,86,2.0,4,79,Semi-Urban,Software Engineer,107757,1 +46722,Male,55,Masters,0,85,47,96,7,0.0,5,74,Urban,ML Engineer,108883,1 +46723,Female,38,Diploma,10,59,43,58,59,9.0,6,29,Semi-Urban,Manager,38583,0 +46724,Male,22,Bachelors,16,86,42,9,78,8.0,0,70,Urban,HR Executive,112291,0 +46725,Female,37,High School,14,89,97,34,47,1.0,3,67,Urban,ML Engineer,72345,1 +46726,Female,49,Masters,1,78,6,48,6,0.0,2,26,Urban,Data Analyst,64691,0 +46727,Male,22,PhD,2,83,48,33,50,2.0,2,41,Urban,Data Analyst,76333,0 +46728,Female,52,Bachelors,7,60,33,35,43,0.0,5,0,Semi-Urban,Software Engineer,71452,0 +46729,Other,53,Masters,1,48,61,71,36,7.0,7,97,Rural,Manager,53159,1 +46730,Other,37,PhD,5,79,72,32,81,2.0,1,72,Urban,Software Engineer,50349,1 +46731,Female,25,High School,18,95,89,89,1,7.0,5,4,Semi-Urban,HR Executive,31426,1 +46732,Male,51,Masters,12,74,43,78,26,7.0,2,77,Rural,Data Analyst,37726,1 +46733,Male,30,Bachelors,8,87,73,56,54,7.0,2,11,Semi-Urban,ML Engineer,84520,0 +46734,Male,33,High School,6,94,40,56,37,9.0,7,30,Semi-Urban,Data Analyst,86041,0 +46735,Male,24,Diploma,12,37,40,64,69,0.0,6,62,Urban,Manager,118756,0 +46736,Male,46,Bachelors,9,32,37,14,22,0.0,3,77,Urban,ML Engineer,115191,0 +46737,Male,24,Diploma,6,15,19,32,67,8.0,1,69,Rural,ML Engineer,43221,0 +46738,Male,41,Masters,6,43,64,14,19,8.0,1,47,Urban,ML Engineer,39578,0 +46739,Male,45,Diploma,11,9,21,67,19,3.0,5,8,Rural,Manager,71745,0 +46740,Male,37,Bachelors,14,88,86,86,84,2.0,5,3,Semi-Urban,Manager,35531,1 +46741,Male,59,Bachelors,12,82,46,55,16,1.0,7,64,Urban,Data Analyst,122887,1 +46742,Female,57,Bachelors,8,20,77,98,46,8.0,2,75,Semi-Urban,Data Analyst,118850,1 +46743,Male,52,High School,10,12,69,40,82,0.0,6,41,Urban,Software Engineer,106310,0 +46744,Female,35,Masters,16,19,11,86,86,8.0,3,76,Semi-Urban,Software Engineer,37688,0 +46745,Female,53,PhD,19,18,63,36,72,9.0,7,71,Urban,HR Executive,82400,0 +46746,Male,22,Bachelors,14,0,39,1,14,9.0,1,75,Semi-Urban,Manager,40721,0 +46747,Other,50,Masters,5,80,82,23,49,0.0,6,7,Urban,ML Engineer,70038,0 +46748,Female,26,Bachelors,7,22,34,79,20,0.0,6,41,Urban,ML Engineer,117071,0 +46749,Male,54,Masters,16,69,7,22,37,9.0,5,7,Urban,HR Executive,67174,0 +46750,Male,36,Bachelors,12,50,68,92,44,1.0,1,44,Urban,Data Analyst,21853,1 +46751,Female,41,High School,1,65,27,88,38,3.0,3,2,Semi-Urban,HR Executive,132787,0 +46752,Male,23,Diploma,17,68,11,83,59,8.0,4,59,Urban,HR Executive,46765,0 +46753,Male,59,Diploma,3,99,85,64,96,1.0,6,81,Urban,Manager,41323,1 +46754,Female,59,Bachelors,3,69,44,19,4,2.0,6,64,Semi-Urban,ML Engineer,138224,0 +46755,Female,25,Bachelors,9,98,62,18,71,4.0,2,12,Urban,Manager,141865,0 +46756,Female,30,Masters,12,0,79,67,86,8.0,4,87,Urban,Software Engineer,105736,0 +46757,Female,48,Masters,2,74,1,6,9,2.0,1,97,Urban,Manager,86657,0 +46758,Female,33,Masters,14,47,26,49,96,6.0,5,3,Urban,Software Engineer,34333,0 +46759,Male,43,Masters,12,87,70,76,78,2.0,6,28,Semi-Urban,Software Engineer,24089,1 +46760,Male,22,High School,7,15,73,97,72,5.0,3,23,Rural,Software Engineer,111285,0 +46761,Female,51,Bachelors,1,10,40,23,12,5.0,1,63,Urban,Software Engineer,107307,0 +46762,Male,36,Diploma,10,77,45,81,44,7.0,5,62,Rural,HR Executive,130571,1 +46763,Male,21,Masters,7,34,37,79,38,6.0,4,30,Urban,Data Analyst,111693,0 +46764,Male,39,Bachelors,8,96,12,48,38,1.0,5,13,Urban,Manager,73748,0 +46765,Male,41,Bachelors,5,76,86,36,14,7.0,1,69,Urban,Software Engineer,67979,1 +46766,Male,29,Bachelors,16,11,49,67,17,4.0,0,64,Semi-Urban,HR Executive,32387,0 +46767,Female,47,Bachelors,4,72,45,57,9,8.0,0,43,Rural,Software Engineer,131835,0 +46768,Female,47,Bachelors,18,96,48,76,98,5.0,0,13,Urban,ML Engineer,38789,0 +46769,Male,30,Diploma,16,61,28,24,79,1.0,5,5,Urban,ML Engineer,111544,0 +46770,Female,30,High School,3,65,84,60,78,8.0,6,12,Urban,Manager,48309,0 +46771,Female,54,High School,5,86,97,17,94,4.0,1,55,Urban,Data Analyst,125259,1 +46772,Male,23,Bachelors,10,11,41,50,85,9.0,5,97,Urban,ML Engineer,60292,0 +46773,Male,46,Diploma,13,55,45,43,76,1.0,6,59,Urban,ML Engineer,68113,0 +46774,Male,37,Bachelors,7,86,12,58,24,4.0,1,35,Rural,Manager,137839,0 +46775,Female,36,Bachelors,0,82,98,25,84,6.0,2,58,Urban,Software Engineer,85972,1 +46776,Male,24,Diploma,9,84,82,28,34,2.0,2,44,Urban,Data Analyst,104066,1 +46777,Male,57,Bachelors,18,10,84,29,5,8.0,6,73,Urban,HR Executive,71628,0 +46778,Male,52,Diploma,8,55,34,91,56,6.0,5,72,Urban,ML Engineer,131401,1 +46779,Female,52,Masters,2,92,8,36,83,1.0,5,35,Semi-Urban,HR Executive,109238,0 +46780,Female,38,Diploma,19,66,67,34,76,5.0,4,0,Urban,Software Engineer,129639,0 +46781,Male,21,Masters,1,92,3,74,55,0.0,5,56,Urban,Manager,55561,0 +46782,Female,48,Masters,6,13,5,35,60,5.0,5,7,Urban,Software Engineer,38190,0 +46783,Male,53,Bachelors,12,47,45,86,99,0.0,7,48,Semi-Urban,Data Analyst,51420,0 +46784,Female,42,High School,13,22,58,40,76,4.0,5,82,Rural,Data Analyst,148100,0 +46785,Male,35,High School,10,2,16,88,76,4.0,3,74,Rural,Manager,126702,0 +46786,Male,50,Diploma,6,86,19,97,35,8.0,1,95,Semi-Urban,ML Engineer,69929,1 +46787,Female,59,PhD,17,48,22,30,96,9.0,4,16,Semi-Urban,Software Engineer,82754,0 +46788,Female,28,Diploma,10,47,26,74,71,4.0,5,68,Urban,ML Engineer,24434,0 +46789,Male,30,Masters,19,2,47,42,47,2.0,7,31,Semi-Urban,Manager,122588,0 +46790,Male,50,Diploma,11,53,42,0,7,2.0,7,33,Rural,Software Engineer,109049,0 +46791,Male,25,Bachelors,6,25,66,21,75,2.0,3,66,Semi-Urban,Software Engineer,127700,0 +46792,Female,38,Bachelors,0,21,17,26,4,8.0,3,68,Rural,Software Engineer,109378,0 +46793,Male,32,Diploma,5,32,3,15,82,4.0,0,65,Urban,ML Engineer,43470,0 +46794,Female,22,Bachelors,14,23,46,43,92,1.0,3,40,Semi-Urban,Manager,113736,0 +46795,Female,26,Bachelors,17,20,13,10,80,0.0,5,65,Urban,Data Analyst,148516,0 +46796,Male,33,Masters,18,9,56,12,0,8.0,7,82,Rural,Manager,47179,0 +46797,Female,29,High School,10,77,67,36,25,7.0,0,89,Rural,Software Engineer,93006,1 +46798,Male,42,High School,8,42,59,2,15,6.0,0,20,Urban,Software Engineer,72170,0 +46799,Female,29,Bachelors,13,47,27,49,48,2.0,7,46,Urban,HR Executive,34382,0 +46800,Female,32,PhD,12,48,43,25,73,9.0,6,15,Semi-Urban,Software Engineer,62827,0 +46801,Male,28,Masters,14,29,94,38,92,6.0,4,45,Urban,Software Engineer,119579,0 +46802,Male,28,Bachelors,9,83,6,32,30,9.0,0,29,Urban,Software Engineer,142719,0 +46803,Female,44,Bachelors,9,86,10,36,34,4.0,0,23,Semi-Urban,Software Engineer,135070,0 +46804,Male,24,Bachelors,0,16,8,7,89,5.0,7,56,Rural,Data Analyst,22649,0 +46805,Male,35,Masters,17,90,54,86,67,0.0,0,16,Urban,Manager,40403,1 +46806,Male,27,Diploma,14,81,1,97,42,9.0,6,64,Urban,Manager,72855,1 +46807,Male,51,PhD,17,9,43,83,85,9.0,5,89,Semi-Urban,Software Engineer,84442,0 +46808,Male,39,Bachelors,1,46,78,62,79,7.0,0,38,Urban,Manager,139216,0 +46809,Male,53,Bachelors,15,19,75,38,96,5.0,6,42,Urban,ML Engineer,118813,0 +46810,Male,44,Bachelors,18,93,62,93,75,5.0,7,13,Urban,Software Engineer,29455,1 +46811,Female,57,Masters,3,84,70,74,66,1.0,4,22,Urban,Manager,61743,1 +46812,Male,41,Bachelors,8,40,33,78,32,2.0,5,27,Urban,Manager,87830,0 +46813,Male,35,Bachelors,16,85,38,95,50,2.0,5,98,Urban,ML Engineer,112967,1 +46814,Male,23,Bachelors,3,25,97,94,76,9.0,0,69,Rural,HR Executive,79452,1 +46815,Male,48,Masters,1,86,92,42,98,0.0,6,72,Rural,ML Engineer,105509,1 +46816,Male,57,Bachelors,13,42,5,12,9,5.0,6,35,Rural,HR Executive,104124,0 +46817,Male,40,Bachelors,6,86,44,7,22,9.0,3,80,Urban,Manager,59280,0 +46818,Male,32,Diploma,17,78,27,10,42,3.0,5,65,Urban,Data Analyst,82974,0 +46819,Male,52,Bachelors,13,32,69,39,32,9.0,6,89,Urban,HR Executive,55721,0 +46820,Female,46,Bachelors,1,53,22,4,92,0.0,0,74,Urban,Data Analyst,78074,0 +46821,Other,24,Diploma,0,24,49,28,15,4.0,2,40,Urban,HR Executive,34743,0 +46822,Male,31,Diploma,7,24,51,63,60,7.0,5,44,Urban,Software Engineer,43065,0 +46823,Female,55,Diploma,8,16,59,48,77,6.0,3,90,Rural,Data Analyst,39889,0 +46824,Male,53,Diploma,2,94,92,7,0,4.0,2,22,Rural,Data Analyst,59565,0 +46825,Female,57,Masters,15,81,93,20,6,0.0,6,17,Semi-Urban,HR Executive,60658,0 +46826,Female,23,High School,5,48,72,36,5,2.0,2,39,Urban,Data Analyst,27414,0 +46827,Female,30,Bachelors,9,46,60,99,95,6.0,7,24,Urban,HR Executive,114890,0 +46828,Female,29,Bachelors,9,22,76,62,15,5.0,2,75,Semi-Urban,HR Executive,97024,0 +46829,Male,37,Diploma,18,65,85,13,63,3.0,6,95,Semi-Urban,Software Engineer,57522,1 +46830,Male,29,Bachelors,11,97,93,89,94,8.0,1,46,Urban,ML Engineer,106330,1 +46831,Male,32,Diploma,1,29,86,92,16,1.0,0,48,Rural,ML Engineer,51127,1 +46832,Female,48,Diploma,0,41,6,96,89,1.0,3,12,Urban,Software Engineer,26288,0 +46833,Female,56,Bachelors,19,58,10,95,33,8.0,3,77,Semi-Urban,Data Analyst,114583,0 +46834,Male,40,PhD,7,96,9,41,99,6.0,2,59,Urban,HR Executive,122868,0 +46835,Male,22,Diploma,2,19,1,88,8,9.0,2,30,Rural,Software Engineer,104757,0 +46836,Female,51,Diploma,15,79,25,89,93,0.0,2,39,Urban,Software Engineer,52538,0 +46837,Male,51,Masters,5,82,85,31,96,9.0,7,27,Urban,ML Engineer,133430,0 +46838,Male,39,Bachelors,2,29,91,39,94,4.0,3,62,Semi-Urban,ML Engineer,59970,0 +46839,Male,34,Bachelors,16,22,75,80,8,1.0,0,57,Urban,ML Engineer,47483,0 +46840,Male,22,Diploma,15,13,13,1,58,2.0,5,75,Urban,Manager,60242,0 +46841,Male,35,Diploma,4,10,76,35,97,8.0,5,91,Urban,HR Executive,108925,0 +46842,Male,53,Bachelors,6,46,42,66,77,3.0,0,20,Urban,Data Analyst,73968,0 +46843,Male,24,Masters,5,53,24,67,40,1.0,1,91,Urban,Software Engineer,84849,1 +46844,Female,38,Bachelors,7,76,7,44,2,6.0,5,18,Urban,Manager,70511,0 +46845,Male,22,Masters,17,10,92,60,72,2.0,5,99,Urban,HR Executive,75117,1 +46846,Female,23,Masters,0,37,15,69,56,5.0,7,67,Semi-Urban,HR Executive,76387,0 +46847,Female,33,Bachelors,7,45,68,68,85,4.0,6,20,Urban,Data Analyst,119212,0 +46848,Female,33,Diploma,2,10,72,18,90,8.0,0,99,Urban,ML Engineer,41034,0 +46849,Female,26,High School,1,56,81,80,36,4.0,2,32,Urban,HR Executive,138522,1 +46850,Female,21,Bachelors,15,44,61,68,60,9.0,4,21,Urban,ML Engineer,29033,0 +46851,Female,50,Bachelors,8,93,4,76,29,8.0,0,41,Urban,Software Engineer,129324,0 +46852,Male,32,Bachelors,6,81,27,54,48,9.0,6,1,Urban,Data Analyst,104774,0 +46853,Male,22,Bachelors,17,6,99,92,9,4.0,0,62,Urban,HR Executive,32236,1 +46854,Male,55,Bachelors,3,7,73,9,3,3.0,5,88,Urban,ML Engineer,103501,0 +46855,Male,48,Masters,2,29,37,83,43,0.0,1,76,Semi-Urban,Data Analyst,140807,0 +46856,Male,24,Bachelors,4,56,37,43,79,6.0,5,67,Semi-Urban,ML Engineer,86689,0 +46857,Male,57,Diploma,15,37,54,22,83,0.0,6,49,Rural,HR Executive,137069,0 +46858,Male,24,Bachelors,2,6,71,63,24,7.0,7,52,Rural,ML Engineer,110490,0 +46859,Female,49,Bachelors,1,34,40,39,84,1.0,1,6,Urban,Data Analyst,41534,0 +46860,Female,24,Bachelors,2,69,73,51,34,4.0,3,13,Urban,Manager,94825,0 +46861,Male,54,Bachelors,4,35,44,88,48,7.0,1,60,Urban,Data Analyst,120994,0 +46862,Male,36,Diploma,3,59,17,70,3,0.0,3,2,Urban,Manager,95517,0 +46863,Other,25,Masters,6,89,72,62,77,0.0,4,87,Rural,Data Analyst,52116,1 +46864,Female,43,Bachelors,18,27,42,16,85,9.0,4,39,Urban,Data Analyst,94313,0 +46865,Female,52,Diploma,10,12,72,77,11,6.0,4,24,Urban,ML Engineer,112025,0 +46866,Male,44,Diploma,0,6,64,75,43,7.0,6,60,Urban,ML Engineer,114915,0 +46867,Female,45,PhD,1,59,73,43,86,5.0,7,79,Rural,HR Executive,33782,1 +46868,Female,40,Bachelors,7,75,61,18,98,3.0,6,39,Semi-Urban,Data Analyst,72127,0 +46869,Male,37,Diploma,2,69,73,2,27,6.0,4,24,Urban,HR Executive,84362,0 +46870,Male,27,Masters,6,93,62,47,97,0.0,6,61,Semi-Urban,Software Engineer,84682,1 +46871,Male,39,High School,15,40,11,18,68,1.0,3,23,Rural,ML Engineer,101724,0 +46872,Male,40,Masters,9,84,98,41,9,1.0,5,81,Semi-Urban,HR Executive,21770,1 +46873,Other,52,Bachelors,9,96,59,78,21,5.0,5,72,Urban,HR Executive,100703,1 +46874,Male,46,Masters,6,0,33,43,33,6.0,1,55,Urban,Data Analyst,86895,0 +46875,Female,32,High School,1,98,29,3,4,7.0,3,45,Semi-Urban,Manager,137884,0 +46876,Female,50,Masters,1,78,32,95,8,2.0,5,44,Rural,ML Engineer,43332,1 +46877,Male,58,Bachelors,12,38,14,14,33,9.0,5,85,Urban,Data Analyst,126806,0 +46878,Female,29,Masters,0,67,39,22,75,7.0,7,92,Rural,HR Executive,42561,0 +46879,Male,34,Diploma,10,4,59,88,35,1.0,0,11,Urban,ML Engineer,117164,0 +46880,Male,57,Bachelors,1,96,87,39,82,1.0,4,92,Semi-Urban,Data Analyst,48189,1 +46881,Other,31,PhD,13,15,71,76,53,3.0,7,31,Urban,ML Engineer,140256,0 +46882,Male,32,Bachelors,3,79,49,98,75,0.0,0,99,Urban,HR Executive,118284,1 +46883,Male,38,Bachelors,4,67,81,28,3,0.0,7,34,Urban,Software Engineer,119910,0 +46884,Female,55,Bachelors,2,28,34,52,21,3.0,4,8,Semi-Urban,HR Executive,48245,0 +46885,Female,53,High School,11,81,13,13,63,8.0,7,23,Urban,Data Analyst,80249,0 +46886,Female,53,Masters,0,15,22,29,20,7.0,0,59,Urban,HR Executive,50149,0 +46887,Female,53,Bachelors,5,95,74,44,11,0.0,3,94,Urban,HR Executive,90380,1 +46888,Male,25,Bachelors,18,34,49,67,36,1.0,5,33,Urban,ML Engineer,148513,0 +46889,Female,45,Bachelors,9,68,82,87,26,6.0,5,47,Urban,Software Engineer,45973,1 +46890,Female,26,High School,8,80,58,94,0,0.0,6,20,Semi-Urban,HR Executive,146653,1 +46891,Male,48,High School,0,58,74,55,76,7.0,2,1,Rural,Software Engineer,36597,0 +46892,Male,55,Bachelors,7,40,8,54,43,1.0,2,76,Urban,ML Engineer,144811,0 +46893,Male,31,Bachelors,6,12,84,93,4,4.0,3,82,Urban,HR Executive,146915,1 +46894,Male,35,Masters,1,3,81,47,67,4.0,5,3,Rural,Software Engineer,37713,0 +46895,Male,34,Bachelors,2,44,99,62,99,1.0,5,98,Rural,HR Executive,86645,1 +46896,Female,53,High School,17,76,90,66,64,1.0,7,5,Urban,HR Executive,64932,0 +46897,Female,50,Masters,1,60,31,41,20,9.0,4,1,Rural,Software Engineer,87896,0 +46898,Female,38,Masters,8,46,29,77,6,1.0,0,91,Urban,HR Executive,139512,1 +46899,Female,52,Bachelors,3,30,29,84,0,0.0,7,16,Semi-Urban,Data Analyst,135724,0 +46900,Male,26,Diploma,2,67,84,91,73,0.0,7,17,Urban,Manager,49719,1 +46901,Male,26,Masters,1,11,75,74,36,9.0,4,96,Urban,Data Analyst,104202,1 +46902,Other,28,Bachelors,14,49,66,52,80,0.0,5,33,Urban,Software Engineer,110909,0 +46903,Female,27,Masters,3,44,30,50,27,7.0,4,58,Urban,Software Engineer,25890,0 +46904,Male,37,Bachelors,0,49,66,25,74,0.0,5,59,Rural,Manager,107670,0 +46905,Female,42,Masters,13,53,7,4,33,1.0,6,1,Rural,ML Engineer,109809,0 +46906,Male,53,Bachelors,11,4,72,20,6,5.0,0,62,Urban,ML Engineer,127948,0 +46907,Male,28,Masters,14,90,0,43,80,4.0,1,23,Urban,ML Engineer,88895,0 +46908,Female,59,Bachelors,17,15,93,12,22,1.0,2,12,Urban,Manager,94861,0 +46909,Female,26,Masters,13,19,74,88,34,1.0,5,47,Semi-Urban,ML Engineer,104521,0 +46910,Male,23,Bachelors,12,43,67,26,50,4.0,0,5,Urban,Data Analyst,103273,0 +46911,Male,43,Masters,13,19,72,78,35,1.0,0,24,Urban,Data Analyst,118434,0 +46912,Male,57,Masters,7,80,70,66,32,5.0,6,41,Urban,Software Engineer,117760,1 +46913,Female,21,PhD,15,64,43,33,49,5.0,3,24,Urban,ML Engineer,101916,0 +46914,Male,49,High School,1,57,77,12,29,4.0,7,62,Urban,HR Executive,38443,0 +46915,Other,35,Diploma,5,56,23,70,72,5.0,6,12,Semi-Urban,Manager,127831,0 +46916,Female,48,Bachelors,8,20,59,0,52,4.0,7,61,Urban,Manager,77243,0 +46917,Male,57,Bachelors,11,67,71,46,0,7.0,5,13,Urban,HR Executive,143810,0 +46918,Female,27,Masters,13,69,6,39,41,2.0,2,73,Rural,ML Engineer,114271,0 +46919,Male,31,Bachelors,3,87,72,21,72,8.0,0,82,Semi-Urban,Manager,106904,1 +46920,Male,30,High School,17,90,95,84,41,3.0,4,3,Rural,HR Executive,38685,1 +46921,Male,25,Bachelors,11,60,35,24,31,8.0,5,58,Urban,Manager,59432,0 +46922,Other,29,Bachelors,14,49,38,35,67,5.0,2,27,Urban,Manager,94976,0 +46923,Male,50,PhD,14,83,68,31,0,1.0,0,68,Urban,Manager,122657,1 +46924,Female,55,Bachelors,6,82,56,17,11,2.0,4,83,Urban,Data Analyst,41312,0 +46925,Male,34,Masters,17,47,60,40,38,1.0,3,74,Semi-Urban,Software Engineer,45643,0 +46926,Male,41,Bachelors,1,60,53,68,9,7.0,2,46,Urban,ML Engineer,94388,0 +46927,Female,45,Bachelors,17,69,33,90,11,0.0,1,68,Rural,Data Analyst,66056,1 +46928,Female,41,Bachelors,3,74,45,93,20,2.0,6,70,Urban,Manager,54216,1 +46929,Male,48,Bachelors,19,40,95,39,86,3.0,4,53,Rural,ML Engineer,101021,0 +46930,Male,49,Bachelors,4,16,31,30,23,3.0,4,74,Urban,HR Executive,45863,0 +46931,Male,33,Masters,2,2,7,76,14,3.0,1,10,Urban,Data Analyst,139495,0 +46932,Male,40,Bachelors,0,0,74,86,88,3.0,0,26,Semi-Urban,ML Engineer,105781,0 +46933,Female,38,Masters,10,54,72,70,98,0.0,5,59,Semi-Urban,Software Engineer,79355,1 +46934,Male,41,Diploma,12,53,10,9,11,6.0,6,64,Semi-Urban,Software Engineer,31670,0 +46935,Female,42,Bachelors,9,51,18,28,96,3.0,3,16,Urban,Software Engineer,61201,0 +46936,Female,26,Masters,10,29,90,42,47,9.0,0,38,Semi-Urban,HR Executive,87059,0 +46937,Male,31,High School,8,43,75,69,81,3.0,5,14,Semi-Urban,Software Engineer,70498,0 +46938,Male,41,Bachelors,17,64,56,4,84,1.0,1,56,Urban,ML Engineer,149737,0 +46939,Male,24,Bachelors,6,3,33,45,32,2.0,1,71,Rural,Data Analyst,44454,0 +46940,Male,57,Bachelors,14,10,80,62,68,7.0,5,69,Rural,ML Engineer,146964,0 +46941,Female,40,Bachelors,1,2,46,99,90,6.0,4,24,Rural,ML Engineer,26125,0 +46942,Male,41,Diploma,8,2,66,16,3,5.0,6,55,Urban,Manager,45752,0 +46943,Female,35,Masters,4,76,72,35,31,5.0,6,94,Urban,ML Engineer,41981,1 +46944,Male,29,Diploma,12,16,30,43,34,8.0,0,12,Rural,HR Executive,136005,0 +46945,Male,54,Bachelors,14,74,95,78,41,3.0,3,99,Semi-Urban,ML Engineer,61668,1 +46946,Male,58,Diploma,10,88,93,81,16,1.0,0,27,Urban,Software Engineer,102487,1 +46947,Female,25,Bachelors,5,88,65,32,57,3.0,5,90,Urban,Software Engineer,102738,1 +46948,Male,42,Bachelors,13,54,79,11,98,4.0,0,54,Urban,Software Engineer,86918,0 +46949,Female,38,Bachelors,11,66,94,19,89,8.0,1,91,Urban,ML Engineer,144486,1 +46950,Male,43,Bachelors,4,89,93,63,45,1.0,4,62,Urban,Data Analyst,82963,1 +46951,Male,54,Diploma,4,62,93,39,2,5.0,1,6,Semi-Urban,Software Engineer,54753,0 +46952,Male,47,Diploma,10,25,38,14,53,1.0,7,48,Semi-Urban,ML Engineer,119487,0 +46953,Male,21,Masters,7,33,98,69,31,7.0,0,12,Semi-Urban,Software Engineer,71910,0 +46954,Female,31,PhD,4,99,23,4,81,2.0,6,3,Semi-Urban,Manager,97310,0 +46955,Male,45,Bachelors,18,88,75,13,77,8.0,4,92,Rural,Software Engineer,61465,1 +46956,Male,33,PhD,5,93,6,3,20,8.0,7,69,Rural,Manager,76432,0 +46957,Female,33,Masters,7,57,96,6,4,8.0,4,88,Urban,Data Analyst,103982,1 +46958,Male,57,Bachelors,3,35,73,78,59,3.0,1,92,Urban,HR Executive,148247,1 +46959,Male,41,Diploma,10,1,41,44,79,3.0,4,41,Semi-Urban,HR Executive,133550,0 +46960,Female,33,Diploma,10,77,49,4,13,6.0,4,15,Semi-Urban,HR Executive,72892,0 +46961,Male,59,Bachelors,16,11,57,6,25,5.0,2,93,Urban,Software Engineer,110393,0 +46962,Female,39,Bachelors,0,61,77,49,72,1.0,1,50,Urban,HR Executive,75122,0 +46963,Male,49,Diploma,19,89,1,52,20,2.0,6,3,Semi-Urban,HR Executive,51996,0 +46964,Male,37,Masters,11,57,80,85,52,0.0,7,96,Semi-Urban,HR Executive,76216,1 +46965,Female,49,High School,6,88,97,54,71,2.0,2,30,Urban,HR Executive,91667,1 +46966,Female,35,Bachelors,10,54,7,50,63,4.0,6,88,Urban,Data Analyst,54894,0 +46967,Male,57,High School,1,45,21,22,87,7.0,3,24,Rural,Manager,129735,0 +46968,Male,44,Diploma,7,14,62,72,79,5.0,7,40,Urban,Data Analyst,86651,0 +46969,Male,48,Bachelors,9,16,27,23,71,0.0,5,63,Rural,HR Executive,62490,0 +46970,Male,44,Diploma,18,9,29,37,4,0.0,7,88,Urban,ML Engineer,140541,0 +46971,Female,33,Bachelors,5,30,49,79,38,3.0,0,61,Semi-Urban,ML Engineer,92867,0 +46972,Male,26,Masters,3,54,75,97,56,3.0,7,96,Urban,HR Executive,88127,1 +46973,Male,30,Bachelors,8,55,85,88,50,0.0,2,28,Urban,HR Executive,58942,1 +46974,Male,36,PhD,1,72,82,21,58,3.0,2,61,Urban,Data Analyst,93394,1 +46975,Male,50,Diploma,12,60,22,66,26,4.0,0,80,Semi-Urban,ML Engineer,106018,0 +46976,Male,57,Bachelors,8,45,12,10,91,9.0,4,4,Urban,Data Analyst,44034,0 +46977,Male,35,Masters,3,49,59,6,48,0.0,2,39,Semi-Urban,Software Engineer,132833,0 +46978,Female,30,Bachelors,19,98,23,76,44,3.0,6,94,Semi-Urban,Data Analyst,134870,1 +46979,Male,31,Bachelors,14,38,25,14,44,7.0,3,20,Semi-Urban,ML Engineer,23078,0 +46980,Male,57,Bachelors,4,94,95,86,50,1.0,0,12,Rural,Manager,91315,1 +46981,Female,30,Bachelors,17,52,60,41,50,8.0,0,21,Semi-Urban,Data Analyst,93613,0 +46982,Female,43,Bachelors,8,14,37,58,82,5.0,7,90,Semi-Urban,ML Engineer,114230,0 +46983,Male,34,Bachelors,0,80,78,33,50,5.0,0,10,Urban,Data Analyst,54717,0 +46984,Other,30,High School,5,14,39,1,95,6.0,7,84,Rural,ML Engineer,80808,0 +46985,Female,56,Bachelors,3,66,78,64,48,9.0,6,93,Semi-Urban,HR Executive,40016,1 +46986,Male,28,High School,3,37,90,82,3,3.0,0,81,Semi-Urban,Software Engineer,143622,1 +46987,Female,46,Bachelors,9,69,23,69,54,6.0,0,66,Rural,ML Engineer,47338,0 +46988,Male,22,High School,18,76,11,50,17,2.0,1,64,Urban,HR Executive,147556,0 +46989,Male,52,Masters,10,49,74,71,80,0.0,1,31,Rural,Manager,41760,0 +46990,Male,59,Diploma,18,29,68,37,65,7.0,0,63,Urban,HR Executive,72094,0 +46991,Male,43,Bachelors,7,61,70,13,52,8.0,7,59,Urban,HR Executive,125061,0 +46992,Male,51,Masters,10,20,37,17,1,8.0,2,77,Urban,HR Executive,54220,0 +46993,Female,59,Bachelors,15,76,40,20,83,2.0,4,97,Urban,HR Executive,146465,0 +46994,Male,48,Bachelors,4,20,5,16,96,3.0,3,81,Urban,HR Executive,125123,0 +46995,Female,44,Masters,0,69,27,30,74,6.0,2,76,Urban,HR Executive,36702,0 +46996,Female,55,Masters,12,37,96,94,31,5.0,2,13,Urban,Manager,41540,0 +46997,Female,23,Bachelors,9,14,52,29,75,1.0,7,54,Urban,HR Executive,65739,0 +46998,Male,46,Diploma,12,17,49,83,73,7.0,3,79,Urban,Data Analyst,21310,0 +46999,Female,34,PhD,7,46,45,0,1,5.0,0,70,Urban,HR Executive,143808,0 +47000,Male,24,Bachelors,16,87,8,67,74,1.0,2,80,Rural,Software Engineer,65815,1 +47001,Female,39,Bachelors,7,74,81,23,27,9.0,3,26,Urban,HR Executive,136187,0 +47002,Male,37,High School,6,98,11,15,62,7.0,7,95,Urban,Manager,69685,0 +47003,Female,29,Bachelors,18,89,69,43,25,7.0,0,88,Rural,Data Analyst,28711,1 +47004,Male,57,Masters,5,23,18,91,85,4.0,3,81,Urban,Manager,24382,0 +47005,Female,25,High School,13,63,94,31,17,9.0,4,31,Urban,Data Analyst,103524,0 +47006,Female,50,Diploma,7,48,33,70,30,4.0,7,77,Urban,ML Engineer,119894,0 +47007,Female,48,Diploma,6,80,15,73,66,5.0,7,37,Rural,Manager,112733,0 +47008,Male,53,PhD,4,68,35,19,68,6.0,4,59,Semi-Urban,Software Engineer,41586,0 +47009,Male,46,Masters,4,92,52,44,50,6.0,4,37,Urban,ML Engineer,32826,0 +47010,Male,22,Bachelors,2,6,9,77,26,0.0,4,89,Urban,HR Executive,46408,0 +47011,Male,40,Diploma,17,77,39,67,43,0.0,6,57,Urban,Manager,54524,1 +47012,Male,36,Masters,16,78,38,31,17,9.0,1,59,Semi-Urban,ML Engineer,33159,0 +47013,Male,56,Bachelors,3,97,87,24,94,8.0,0,47,Rural,HR Executive,145843,1 +47014,Female,38,Masters,15,52,21,99,2,7.0,2,68,Urban,Data Analyst,51990,0 +47015,Male,23,Bachelors,0,35,73,10,87,8.0,7,82,Urban,HR Executive,84823,0 +47016,Female,59,High School,1,53,62,23,81,9.0,4,73,Semi-Urban,Software Engineer,31782,0 +47017,Male,29,High School,9,83,49,48,86,7.0,6,43,Rural,HR Executive,84550,0 +47018,Female,37,Bachelors,7,41,98,9,37,9.0,4,23,Urban,ML Engineer,36401,0 +47019,Male,35,PhD,7,9,52,10,52,0.0,5,61,Urban,Data Analyst,101111,0 +47020,Female,34,Bachelors,14,47,46,96,48,3.0,2,86,Urban,Manager,67228,1 +47021,Male,45,Masters,14,98,75,63,77,9.0,0,7,Urban,HR Executive,123228,1 +47022,Male,59,Diploma,1,3,33,98,6,7.0,2,41,Semi-Urban,Manager,25177,0 +47023,Male,56,Bachelors,19,51,29,87,72,7.0,4,31,Rural,Software Engineer,81646,0 +47024,Male,31,High School,1,47,85,15,20,2.0,6,82,Urban,Manager,126668,0 +47025,Male,44,Bachelors,1,78,77,62,35,3.0,7,60,Semi-Urban,HR Executive,27225,1 +47026,Female,57,Bachelors,10,18,56,44,15,4.0,2,34,Urban,HR Executive,36746,0 +47027,Male,39,PhD,2,72,65,63,38,5.0,2,40,Semi-Urban,Software Engineer,101215,1 +47028,Female,54,High School,17,81,98,10,46,7.0,0,98,Rural,Software Engineer,131317,1 +47029,Female,37,PhD,2,58,40,18,98,2.0,2,1,Urban,Data Analyst,111128,0 +47030,Female,27,Bachelors,3,86,1,17,1,0.0,4,67,Urban,Software Engineer,73667,0 +47031,Male,22,Bachelors,19,39,40,19,70,4.0,0,67,Urban,ML Engineer,103705,0 +47032,Male,30,Diploma,12,82,67,53,4,6.0,0,8,Urban,Data Analyst,147233,0 +47033,Male,49,Masters,10,71,45,31,54,2.0,5,47,Rural,ML Engineer,127525,0 +47034,Male,21,High School,17,39,74,79,74,1.0,2,57,Semi-Urban,ML Engineer,30232,1 +47035,Male,39,High School,8,61,98,73,17,5.0,4,93,Semi-Urban,Manager,78881,1 +47036,Male,39,Bachelors,0,4,48,32,50,5.0,7,73,Urban,Manager,104784,0 +47037,Male,49,High School,15,62,24,10,77,9.0,7,15,Semi-Urban,Manager,24080,0 +47038,Female,34,Bachelors,14,52,94,42,8,7.0,3,22,Rural,HR Executive,54062,0 +47039,Male,52,Masters,14,74,29,37,25,8.0,3,33,Rural,ML Engineer,56479,0 +47040,Male,22,Masters,16,56,88,76,34,6.0,0,41,Urban,Data Analyst,21000,1 +47041,Male,35,Bachelors,18,88,26,43,49,2.0,3,95,Urban,HR Executive,92694,1 +47042,Male,43,Bachelors,8,68,75,21,67,3.0,6,24,Urban,Manager,122601,0 +47043,Female,26,Bachelors,6,97,1,6,52,0.0,3,2,Urban,Manager,55358,0 +47044,Female,56,Bachelors,5,93,84,96,4,4.0,6,75,Rural,Data Analyst,66177,1 +47045,Female,57,Masters,11,69,6,34,61,4.0,2,82,Rural,Software Engineer,143232,0 +47046,Female,22,Bachelors,15,10,4,43,5,2.0,0,55,Urban,Software Engineer,36958,0 +47047,Male,40,Bachelors,13,91,58,0,20,9.0,1,15,Semi-Urban,Manager,64148,0 +47048,Male,58,Diploma,12,27,37,57,87,2.0,6,35,Semi-Urban,Software Engineer,45129,0 +47049,Female,45,Bachelors,6,62,81,44,52,3.0,5,31,Urban,ML Engineer,42991,0 +47050,Female,41,Masters,16,78,33,30,10,9.0,0,23,Urban,Software Engineer,44875,0 +47051,Female,36,High School,12,35,6,80,87,9.0,0,56,Semi-Urban,Data Analyst,20616,0 +47052,Female,47,Bachelors,8,85,8,26,8,4.0,2,76,Urban,Software Engineer,146819,0 +47053,Male,59,Masters,13,34,92,65,40,8.0,3,74,Rural,HR Executive,112305,1 +47054,Female,50,Masters,8,38,7,95,78,0.0,6,11,Rural,HR Executive,120661,0 +47055,Male,28,Bachelors,10,4,72,48,7,6.0,0,8,Rural,Manager,139410,0 +47056,Male,28,Bachelors,8,8,29,75,7,3.0,7,10,Semi-Urban,Manager,63058,0 +47057,Male,21,Diploma,11,61,40,87,53,5.0,1,82,Urban,Software Engineer,32667,1 +47058,Male,43,Bachelors,15,24,10,13,53,7.0,0,13,Urban,Software Engineer,149388,0 +47059,Male,53,Diploma,15,94,80,17,22,8.0,2,58,Semi-Urban,Manager,29063,1 +47060,Male,27,Masters,11,30,60,89,5,0.0,0,79,Semi-Urban,ML Engineer,87670,1 +47061,Male,48,Masters,8,40,49,74,86,7.0,7,79,Urban,ML Engineer,74896,1 +47062,Male,33,Diploma,2,31,53,22,27,8.0,0,96,Urban,ML Engineer,51075,0 +47063,Male,38,Bachelors,13,25,66,85,10,1.0,2,38,Semi-Urban,Software Engineer,51395,0 +47064,Female,49,Diploma,17,30,84,27,88,7.0,2,93,Semi-Urban,HR Executive,56813,0 +47065,Female,57,Masters,4,21,38,3,39,0.0,2,29,Urban,Software Engineer,124802,0 +47066,Male,50,Masters,6,39,53,69,79,6.0,6,31,Urban,Data Analyst,52697,0 +47067,Female,43,Bachelors,9,67,87,75,22,7.0,3,70,Rural,ML Engineer,144310,1 +47068,Male,36,Masters,1,18,49,85,79,3.0,2,8,Urban,ML Engineer,69199,0 +47069,Male,40,Bachelors,18,76,13,83,4,8.0,2,94,Urban,Manager,86566,1 +47070,Male,39,Bachelors,7,16,3,31,7,0.0,4,18,Urban,HR Executive,59063,0 +47071,Male,53,PhD,16,90,40,45,64,6.0,2,90,Urban,Manager,104414,1 +47072,Female,23,Bachelors,7,5,9,2,33,8.0,5,82,Semi-Urban,Data Analyst,89070,0 +47073,Male,37,Bachelors,0,34,89,78,78,9.0,3,92,Urban,Software Engineer,45587,1 +47074,Male,30,Masters,11,21,36,63,31,9.0,2,45,Urban,Data Analyst,20006,0 +47075,Male,37,Bachelors,7,3,75,7,24,7.0,4,5,Urban,Manager,41639,0 +47076,Female,51,Diploma,19,29,70,73,79,5.0,0,65,Rural,ML Engineer,86464,0 +47077,Male,23,Bachelors,10,22,96,32,5,3.0,3,85,Rural,Manager,73511,1 +47078,Other,55,Diploma,4,96,90,17,76,8.0,3,56,Rural,Data Analyst,51296,1 +47079,Other,53,Masters,8,55,34,44,24,1.0,1,15,Semi-Urban,Software Engineer,23831,0 +47080,Female,55,Diploma,16,77,3,46,47,2.0,5,64,Urban,Data Analyst,112421,0 +47081,Female,56,High School,7,15,65,0,37,1.0,4,66,Urban,HR Executive,47622,0 +47082,Male,46,PhD,9,21,17,60,4,2.0,4,22,Semi-Urban,HR Executive,42537,0 +47083,Male,44,Masters,0,22,76,4,77,6.0,5,70,Semi-Urban,Data Analyst,51703,0 +47084,Other,50,High School,12,94,12,63,90,8.0,5,47,Semi-Urban,Software Engineer,61541,0 +47085,Male,34,High School,13,56,93,37,70,9.0,3,69,Rural,Software Engineer,121419,1 +47086,Male,41,PhD,9,42,69,62,60,4.0,4,97,Urban,Manager,118554,1 +47087,Male,39,Diploma,9,26,75,44,88,2.0,2,77,Urban,Software Engineer,100495,0 +47088,Female,39,Bachelors,4,46,12,52,31,6.0,1,22,Semi-Urban,Software Engineer,59450,0 +47089,Male,23,Bachelors,14,43,57,53,93,9.0,0,85,Urban,HR Executive,116683,1 +47090,Male,57,Bachelors,10,22,40,15,33,7.0,0,7,Urban,HR Executive,115142,0 +47091,Female,31,Bachelors,6,9,23,73,32,5.0,4,14,Urban,Data Analyst,28739,0 +47092,Male,59,Bachelors,8,2,51,16,16,8.0,5,91,Urban,Data Analyst,39421,0 +47093,Male,48,Masters,3,93,81,89,96,8.0,7,35,Semi-Urban,HR Executive,42149,1 +47094,Male,39,High School,17,54,87,17,70,5.0,1,61,Rural,Software Engineer,93670,0 +47095,Male,26,Bachelors,17,21,45,41,45,9.0,1,38,Semi-Urban,Data Analyst,42904,0 +47096,Male,35,Diploma,7,92,10,94,64,2.0,5,11,Semi-Urban,Manager,78945,0 +47097,Male,43,Masters,19,31,78,59,30,1.0,7,32,Semi-Urban,Software Engineer,40462,0 +47098,Female,41,Masters,19,88,9,11,77,9.0,4,44,Urban,Data Analyst,136148,0 +47099,Female,42,Bachelors,18,27,96,61,98,6.0,0,16,Rural,Software Engineer,128055,0 +47100,Male,45,Bachelors,5,63,88,30,48,6.0,7,24,Urban,Data Analyst,113586,0 +47101,Female,34,Diploma,18,21,80,30,61,2.0,1,69,Urban,ML Engineer,133960,0 +47102,Male,51,High School,19,12,62,20,43,4.0,3,32,Urban,HR Executive,71630,0 +47103,Male,40,Bachelors,18,23,63,64,71,1.0,4,2,Rural,Software Engineer,144050,0 +47104,Female,57,PhD,19,37,80,90,49,8.0,6,37,Urban,HR Executive,143989,1 +47105,Male,53,Bachelors,8,43,28,92,89,1.0,7,36,Urban,HR Executive,130736,0 +47106,Female,34,Diploma,4,5,95,2,30,6.0,3,93,Urban,Data Analyst,78660,0 +47107,Male,52,Bachelors,16,0,56,99,30,3.0,2,22,Semi-Urban,ML Engineer,62709,0 +47108,Male,38,Diploma,9,79,60,89,55,0.0,0,51,Urban,HR Executive,127321,1 +47109,Female,24,Masters,16,29,19,53,39,8.0,7,82,Semi-Urban,HR Executive,139997,0 +47110,Male,32,Bachelors,15,21,92,45,62,0.0,5,60,Urban,ML Engineer,104644,0 +47111,Male,39,Masters,17,98,13,2,64,2.0,0,99,Semi-Urban,ML Engineer,137497,0 +47112,Male,56,Diploma,7,95,57,27,4,2.0,3,86,Rural,HR Executive,110639,1 +47113,Male,37,Bachelors,16,56,55,87,1,1.0,5,61,Semi-Urban,HR Executive,47640,1 +47114,Female,34,Bachelors,16,58,31,1,55,3.0,0,37,Urban,HR Executive,81725,0 +47115,Female,38,Diploma,4,60,10,61,15,9.0,5,77,Urban,Software Engineer,52143,0 +47116,Female,42,Diploma,9,9,61,0,67,2.0,6,65,Rural,Manager,29375,0 +47117,Male,45,Bachelors,14,31,17,38,54,4.0,0,33,Semi-Urban,ML Engineer,82938,0 +47118,Male,29,Bachelors,8,77,8,66,12,0.0,1,8,Urban,Manager,123994,0 +47119,Female,40,High School,0,74,7,25,58,3.0,4,96,Urban,Data Analyst,24135,0 +47120,Male,35,Bachelors,19,55,21,36,37,0.0,6,3,Urban,Software Engineer,133501,0 +47121,Male,56,PhD,9,87,68,50,56,5.0,7,48,Urban,HR Executive,51299,1 +47122,Female,24,Masters,5,15,4,68,58,7.0,7,22,Rural,HR Executive,126566,0 +47123,Male,24,Masters,7,83,49,32,72,3.0,5,43,Urban,Software Engineer,20548,0 +47124,Female,28,Masters,9,0,94,42,22,4.0,0,70,Semi-Urban,ML Engineer,31934,0 +47125,Male,54,Bachelors,14,17,12,44,41,6.0,3,78,Urban,Data Analyst,65223,0 +47126,Female,53,Diploma,8,15,38,0,0,4.0,1,1,Urban,Manager,145775,0 +47127,Male,51,PhD,7,53,69,8,2,7.0,5,54,Semi-Urban,ML Engineer,74313,0 +47128,Female,57,Diploma,8,12,52,65,73,2.0,7,28,Semi-Urban,ML Engineer,90066,0 +47129,Male,28,Bachelors,6,82,32,26,57,7.0,3,96,Urban,Software Engineer,34671,1 +47130,Female,32,Bachelors,13,49,19,83,76,5.0,5,47,Urban,Data Analyst,122506,0 +47131,Male,57,High School,15,57,76,29,51,5.0,7,51,Semi-Urban,HR Executive,88049,0 +47132,Female,30,Bachelors,7,76,74,63,67,2.0,2,18,Urban,Manager,142326,0 +47133,Female,33,Masters,16,31,40,61,26,3.0,2,61,Urban,ML Engineer,129040,0 +47134,Male,25,Bachelors,3,45,11,58,44,7.0,5,10,Semi-Urban,Manager,71180,0 +47135,Male,21,Masters,4,51,17,51,12,2.0,0,88,Urban,Manager,116590,0 +47136,Female,45,Bachelors,6,27,84,58,17,6.0,1,92,Urban,Software Engineer,70288,1 +47137,Male,29,Masters,6,45,9,49,91,2.0,3,45,Urban,Data Analyst,64026,0 +47138,Female,33,Bachelors,11,37,81,17,96,4.0,7,70,Urban,Software Engineer,29426,0 +47139,Male,31,Diploma,15,93,93,95,56,7.0,7,80,Urban,Software Engineer,46546,1 +47140,Female,57,Bachelors,9,44,39,53,29,9.0,6,99,Semi-Urban,ML Engineer,145738,0 +47141,Male,49,Masters,12,52,73,52,28,9.0,2,59,Urban,Manager,56847,1 +47142,Female,49,Bachelors,16,75,8,62,97,2.0,0,44,Urban,Manager,73657,0 +47143,Male,28,Masters,5,68,52,26,16,1.0,4,3,Rural,ML Engineer,52167,0 +47144,Male,29,Diploma,8,2,43,3,94,4.0,4,73,Rural,ML Engineer,40394,0 +47145,Male,59,Bachelors,8,9,81,98,20,7.0,6,17,Rural,ML Engineer,134398,0 +47146,Female,55,High School,16,0,92,15,50,4.0,2,23,Urban,ML Engineer,123266,0 +47147,Male,45,Diploma,1,56,4,90,62,1.0,4,40,Semi-Urban,ML Engineer,105113,0 +47148,Male,53,High School,10,5,46,66,66,2.0,0,38,Rural,Software Engineer,136632,0 +47149,Female,48,Diploma,12,53,9,52,76,0.0,6,44,Urban,Data Analyst,95097,0 +47150,Male,39,Masters,5,2,5,33,20,2.0,5,79,Semi-Urban,Software Engineer,87080,0 +47151,Female,21,High School,7,67,85,29,37,6.0,0,11,Urban,Software Engineer,20956,0 +47152,Female,52,Masters,2,7,40,78,8,8.0,6,4,Urban,HR Executive,57119,0 +47153,Male,36,Bachelors,19,77,20,51,9,7.0,2,46,Urban,HR Executive,23037,0 +47154,Male,45,High School,15,61,88,27,79,8.0,7,3,Rural,Manager,135806,0 +47155,Female,34,Bachelors,14,64,24,34,19,9.0,1,17,Rural,Data Analyst,119734,0 +47156,Male,57,Bachelors,2,26,63,32,84,8.0,2,45,Urban,Data Analyst,34769,0 +47157,Female,58,Bachelors,15,69,31,58,84,7.0,3,35,Rural,Data Analyst,115348,0 +47158,Male,24,High School,17,0,40,89,54,8.0,1,29,Urban,Manager,56309,0 +47159,Male,22,Diploma,5,67,64,68,73,6.0,3,75,Urban,ML Engineer,134766,1 +47160,Male,29,Bachelors,8,40,56,65,12,7.0,2,80,Semi-Urban,Software Engineer,60184,1 +47161,Other,30,Diploma,8,81,93,87,80,7.0,3,66,Semi-Urban,Manager,59573,1 +47162,Female,32,Bachelors,4,16,40,47,83,1.0,4,79,Semi-Urban,Manager,124118,0 +47163,Male,50,High School,8,43,24,96,39,7.0,1,40,Urban,Data Analyst,64681,0 +47164,Other,25,Bachelors,3,29,68,44,6,2.0,0,70,Semi-Urban,Data Analyst,122961,0 +47165,Male,51,Diploma,17,48,24,46,23,9.0,4,34,Urban,Manager,69296,0 +47166,Female,22,PhD,15,41,38,89,37,1.0,2,99,Rural,ML Engineer,141243,1 +47167,Female,41,Bachelors,18,21,12,92,32,5.0,4,0,Rural,Data Analyst,75972,0 +47168,Female,23,Bachelors,19,69,55,24,0,3.0,0,29,Urban,Manager,127962,0 +47169,Male,21,Masters,17,95,98,87,16,2.0,7,26,Urban,Software Engineer,26826,1 +47170,Male,39,Diploma,18,73,7,50,25,8.0,0,55,Urban,Manager,38235,0 +47171,Female,30,Masters,3,23,14,71,52,2.0,5,96,Semi-Urban,Data Analyst,31791,0 +47172,Male,37,Diploma,5,94,83,39,81,5.0,1,98,Urban,HR Executive,121391,1 +47173,Male,22,Bachelors,19,89,27,34,63,7.0,3,69,Urban,Data Analyst,93662,0 +47174,Female,53,Diploma,7,64,43,37,94,4.0,5,59,Urban,Software Engineer,35499,0 +47175,Female,38,Diploma,16,69,35,69,16,2.0,3,23,Semi-Urban,ML Engineer,62942,0 +47176,Male,38,High School,9,48,58,32,20,2.0,5,66,Urban,Manager,36144,0 +47177,Male,21,Bachelors,18,74,90,43,49,6.0,6,52,Urban,Data Analyst,53724,1 +47178,Male,25,Bachelors,16,73,0,38,48,3.0,4,46,Urban,HR Executive,41006,0 +47179,Female,25,Diploma,10,6,8,40,87,4.0,6,93,Semi-Urban,Software Engineer,149014,0 +47180,Female,31,High School,10,43,50,45,47,0.0,7,25,Rural,HR Executive,147523,0 +47181,Female,53,Bachelors,16,16,10,94,0,0.0,7,51,Rural,ML Engineer,20822,0 +47182,Female,57,Bachelors,16,29,19,48,35,0.0,2,87,Urban,ML Engineer,56334,0 +47183,Female,28,PhD,19,69,23,97,99,4.0,7,28,Urban,Software Engineer,107681,0 +47184,Male,22,Diploma,9,63,84,2,59,9.0,2,16,Urban,Manager,80006,0 +47185,Male,37,Diploma,10,84,79,22,78,8.0,6,48,Semi-Urban,Data Analyst,27569,0 +47186,Female,43,Masters,14,69,7,94,79,7.0,6,59,Rural,HR Executive,123549,0 +47187,Male,39,High School,17,11,38,82,4,0.0,7,92,Semi-Urban,Manager,148214,0 +47188,Other,39,Masters,15,15,31,54,35,7.0,5,57,Urban,Data Analyst,96674,0 +47189,Female,55,Masters,1,6,80,84,38,2.0,2,2,Semi-Urban,ML Engineer,21331,0 +47190,Male,25,Bachelors,6,42,83,91,49,6.0,3,71,Rural,Data Analyst,98166,1 +47191,Male,59,Bachelors,14,90,72,5,64,5.0,4,53,Urban,Data Analyst,96002,0 +47192,Male,42,Masters,1,39,23,9,5,1.0,1,75,Urban,Data Analyst,99486,0 +47193,Female,29,Masters,13,76,62,6,55,3.0,3,79,Semi-Urban,Software Engineer,49727,0 +47194,Female,32,High School,1,36,42,74,40,3.0,3,67,Urban,Software Engineer,63780,0 +47195,Male,34,Diploma,14,77,21,99,15,2.0,4,46,Urban,ML Engineer,24816,1 +47196,Female,33,Diploma,10,37,12,59,27,2.0,5,66,Urban,ML Engineer,69284,0 +47197,Female,56,High School,7,27,58,90,65,4.0,5,98,Urban,ML Engineer,31295,1 +47198,Male,29,Bachelors,12,71,9,21,19,1.0,5,85,Urban,HR Executive,137518,0 +47199,Male,45,Diploma,4,79,72,84,74,6.0,6,70,Semi-Urban,HR Executive,77698,1 +47200,Male,37,Diploma,5,75,5,17,43,0.0,4,2,Urban,HR Executive,67627,0 +47201,Male,35,Bachelors,0,39,79,85,36,3.0,3,80,Rural,Software Engineer,80288,1 +47202,Male,28,Diploma,3,89,64,51,71,4.0,1,63,Urban,Data Analyst,127443,1 +47203,Male,22,Bachelors,9,37,5,95,11,9.0,7,69,Semi-Urban,Data Analyst,125839,0 +47204,Female,25,Bachelors,7,4,25,64,51,1.0,4,95,Urban,Software Engineer,116013,0 +47205,Male,22,Bachelors,8,34,87,15,32,0.0,7,47,Rural,Manager,104441,0 +47206,Male,21,Bachelors,3,48,76,26,45,9.0,2,93,Semi-Urban,Data Analyst,28639,1 +47207,Male,39,Masters,5,97,76,93,79,4.0,3,91,Urban,Software Engineer,56728,1 +47208,Female,31,Diploma,11,8,55,70,16,0.0,3,64,Urban,HR Executive,120238,0 +47209,Female,33,Diploma,14,18,2,71,85,1.0,2,59,Urban,ML Engineer,79437,0 +47210,Female,32,PhD,12,97,41,79,12,4.0,5,70,Urban,Manager,107188,1 +47211,Female,34,Masters,5,44,87,36,4,3.0,6,11,Rural,ML Engineer,57293,0 +47212,Male,52,Bachelors,6,91,30,11,96,4.0,1,39,Rural,Software Engineer,64144,0 +47213,Male,55,High School,3,1,13,86,28,8.0,2,95,Semi-Urban,HR Executive,107735,0 +47214,Female,48,Bachelors,18,25,55,31,53,5.0,7,91,Rural,ML Engineer,115054,0 +47215,Male,33,Diploma,2,36,41,76,15,8.0,4,86,Semi-Urban,ML Engineer,35216,1 +47216,Female,47,Diploma,2,37,84,21,63,0.0,6,41,Semi-Urban,Software Engineer,81771,0 +47217,Male,53,Masters,8,66,72,90,70,7.0,2,6,Semi-Urban,Data Analyst,105614,0 +47218,Female,53,High School,18,42,11,3,45,0.0,6,62,Urban,HR Executive,92098,0 +47219,Male,58,Bachelors,19,43,59,80,67,9.0,6,59,Urban,Software Engineer,142491,1 +47220,Male,29,Diploma,13,44,45,62,58,2.0,7,7,Urban,Data Analyst,112610,0 +47221,Male,46,Diploma,12,29,7,58,87,5.0,6,28,Urban,Manager,116454,0 +47222,Female,25,Diploma,12,2,8,56,10,5.0,3,76,Rural,ML Engineer,118740,0 +47223,Male,54,Bachelors,17,45,83,10,14,2.0,5,14,Semi-Urban,HR Executive,20444,0 +47224,Male,23,High School,6,70,35,58,73,7.0,3,34,Semi-Urban,Data Analyst,36210,0 +47225,Male,49,High School,13,8,56,97,29,5.0,5,3,Urban,ML Engineer,100638,0 +47226,Male,38,High School,9,73,29,45,93,7.0,1,96,Urban,Software Engineer,39224,1 +47227,Male,50,Masters,18,32,3,91,35,6.0,2,4,Semi-Urban,Data Analyst,103128,0 +47228,Male,35,Masters,17,91,87,11,29,9.0,2,5,Urban,Data Analyst,107788,0 +47229,Female,34,High School,15,5,15,2,26,8.0,7,18,Semi-Urban,HR Executive,112512,0 +47230,Female,24,Bachelors,19,98,59,38,86,7.0,0,71,Semi-Urban,ML Engineer,87132,1 +47231,Male,45,Diploma,2,82,60,30,42,8.0,1,62,Urban,Software Engineer,56312,0 +47232,Male,40,Diploma,15,96,94,28,48,7.0,7,47,Urban,HR Executive,146089,1 +47233,Male,44,Diploma,12,48,26,29,51,8.0,5,89,Urban,Data Analyst,110076,0 +47234,Male,43,Diploma,9,96,59,92,12,8.0,3,5,Urban,Data Analyst,21671,1 +47235,Female,45,Bachelors,12,84,20,16,63,0.0,2,49,Urban,ML Engineer,111262,0 +47236,Male,40,Bachelors,19,51,33,13,60,8.0,2,6,Semi-Urban,HR Executive,35891,0 +47237,Female,34,Bachelors,8,71,68,86,16,3.0,5,20,Urban,HR Executive,107451,1 +47238,Male,54,Bachelors,2,13,69,82,69,2.0,5,82,Urban,HR Executive,59294,1 +47239,Male,53,Bachelors,1,55,19,28,87,7.0,4,0,Urban,Data Analyst,111179,0 +47240,Female,37,High School,11,25,18,0,81,8.0,5,65,Rural,HR Executive,28060,0 +47241,Male,43,Bachelors,7,63,90,14,74,3.0,0,77,Urban,Data Analyst,113448,1 +47242,Male,36,Masters,16,3,93,87,13,7.0,1,40,Urban,ML Engineer,137060,0 +47243,Male,50,Bachelors,2,64,16,40,98,1.0,1,70,Urban,Manager,148972,0 +47244,Male,28,Diploma,2,27,21,95,20,3.0,3,11,Urban,Software Engineer,27949,0 +47245,Male,57,Bachelors,16,46,98,86,25,7.0,7,90,Urban,Software Engineer,148461,1 +47246,Female,22,Diploma,9,88,65,16,41,3.0,0,98,Urban,Manager,107027,1 +47247,Female,24,Masters,19,9,85,8,16,9.0,3,32,Urban,ML Engineer,127473,0 +47248,Female,42,Masters,4,36,8,47,50,8.0,4,20,Urban,Software Engineer,83322,0 +47249,Male,23,Bachelors,4,17,5,74,40,3.0,5,54,Urban,ML Engineer,115231,0 +47250,Other,48,Masters,4,48,7,96,90,8.0,1,90,Urban,ML Engineer,71412,1 +47251,Female,32,Bachelors,14,97,70,95,2,3.0,2,85,Urban,Data Analyst,117736,1 +47252,Male,35,High School,3,23,68,16,11,8.0,0,71,Urban,Manager,57781,0 +47253,Male,48,Bachelors,14,42,99,66,88,7.0,0,15,Semi-Urban,Manager,74683,0 +47254,Female,49,Bachelors,2,21,91,90,17,1.0,6,58,Urban,Data Analyst,113851,1 +47255,Female,53,High School,12,75,18,41,35,8.0,1,76,Semi-Urban,ML Engineer,24181,0 +47256,Male,57,Diploma,8,14,30,42,39,1.0,5,4,Urban,Data Analyst,105325,0 +47257,Male,57,Bachelors,5,84,86,93,7,8.0,7,44,Urban,HR Executive,128185,1 +47258,Other,21,Bachelors,6,17,25,29,14,3.0,4,21,Urban,ML Engineer,79879,0 +47259,Male,42,Diploma,7,86,26,98,11,2.0,6,0,Urban,ML Engineer,100306,0 +47260,Male,30,Diploma,18,45,41,14,54,0.0,0,67,Urban,ML Engineer,92501,0 +47261,Female,44,Bachelors,11,58,90,80,38,9.0,4,57,Rural,HR Executive,31989,1 +47262,Male,42,Bachelors,17,88,63,84,30,6.0,0,80,Urban,Software Engineer,25217,1 +47263,Female,51,High School,2,56,53,72,33,3.0,2,5,Rural,ML Engineer,29335,0 +47264,Female,38,Masters,7,52,97,2,43,5.0,3,46,Urban,HR Executive,40050,0 +47265,Male,33,Bachelors,4,41,6,46,10,0.0,7,99,Urban,Data Analyst,121039,0 +47266,Male,51,Bachelors,0,74,15,26,19,4.0,0,27,Rural,Data Analyst,50562,0 +47267,Male,56,Bachelors,16,91,26,25,20,8.0,1,53,Urban,Data Analyst,45840,0 +47268,Male,25,Bachelors,9,4,19,6,25,7.0,0,42,Urban,HR Executive,133147,0 +47269,Female,40,Diploma,16,55,12,8,26,7.0,2,70,Urban,HR Executive,39713,0 +47270,Male,59,Diploma,14,5,69,98,75,0.0,1,67,Semi-Urban,Manager,57010,1 +47271,Female,27,Diploma,1,75,16,72,19,2.0,2,23,Urban,ML Engineer,88238,0 +47272,Female,28,Masters,6,75,97,47,66,9.0,1,18,Rural,ML Engineer,118053,0 +47273,Male,28,Bachelors,10,29,44,48,8,0.0,3,21,Urban,HR Executive,98421,0 +47274,Other,56,Bachelors,18,78,71,52,21,6.0,5,4,Rural,Data Analyst,127264,0 +47275,Female,43,Masters,11,25,59,89,33,2.0,3,32,Urban,Software Engineer,78210,0 +47276,Female,35,Bachelors,6,98,37,40,73,6.0,2,55,Urban,Data Analyst,93708,0 +47277,Male,52,Bachelors,16,16,6,13,0,2.0,7,87,Semi-Urban,Software Engineer,31687,0 +47278,Female,37,Diploma,18,72,37,15,10,4.0,0,90,Semi-Urban,Data Analyst,84133,0 +47279,Male,33,Bachelors,15,5,89,72,28,0.0,6,11,Semi-Urban,HR Executive,59888,0 +47280,Female,57,High School,6,83,24,47,80,3.0,6,41,Urban,Manager,53427,0 +47281,Male,59,PhD,18,55,87,40,46,0.0,7,85,Urban,Software Engineer,85904,1 +47282,Male,47,Bachelors,15,49,19,66,90,3.0,6,1,Semi-Urban,Data Analyst,29055,0 +47283,Male,47,Masters,8,84,39,42,77,7.0,2,23,Urban,Software Engineer,55988,0 +47284,Male,37,PhD,6,28,83,37,3,3.0,2,94,Urban,ML Engineer,120261,1 +47285,Male,43,Bachelors,10,68,60,39,78,9.0,4,18,Urban,Data Analyst,124094,0 +47286,Male,52,Diploma,16,70,75,98,14,0.0,1,52,Semi-Urban,Data Analyst,129239,1 +47287,Female,54,High School,13,64,94,52,12,9.0,3,52,Rural,Data Analyst,40712,1 +47288,Male,50,Bachelors,6,68,22,86,36,4.0,5,66,Urban,HR Executive,100217,1 +47289,Male,37,PhD,12,7,15,92,24,1.0,4,2,Urban,ML Engineer,88556,0 +47290,Female,42,Masters,7,48,61,87,90,6.0,6,73,Urban,HR Executive,59932,1 +47291,Male,39,Bachelors,12,65,24,60,95,3.0,6,34,Urban,ML Engineer,92649,0 +47292,Other,55,Diploma,13,21,65,15,46,8.0,6,27,Semi-Urban,HR Executive,57888,0 +47293,Male,24,PhD,18,92,16,24,44,7.0,5,22,Urban,Software Engineer,116135,0 +47294,Male,52,Diploma,8,51,82,31,91,2.0,2,59,Urban,HR Executive,107477,0 +47295,Male,32,Bachelors,17,53,35,68,53,3.0,0,36,Semi-Urban,Manager,125191,0 +47296,Other,44,Diploma,7,79,76,19,97,1.0,6,58,Urban,HR Executive,67732,0 +47297,Female,44,Masters,7,86,11,75,5,6.0,3,81,Urban,ML Engineer,138142,1 +47298,Female,21,Bachelors,4,45,93,18,99,8.0,1,23,Urban,Manager,31853,0 +47299,Male,58,Diploma,7,22,65,94,4,7.0,1,83,Rural,Software Engineer,46806,1 +47300,Other,31,Bachelors,8,33,65,50,31,5.0,0,90,Semi-Urban,Data Analyst,148826,0 +47301,Female,34,High School,17,49,73,0,37,6.0,3,83,Urban,ML Engineer,135472,0 +47302,Male,24,Bachelors,18,22,34,21,56,5.0,2,22,Semi-Urban,Manager,112809,0 +47303,Female,27,Bachelors,10,30,57,57,28,3.0,6,89,Urban,HR Executive,112811,0 +47304,Other,49,Bachelors,17,18,54,89,13,9.0,4,90,Urban,ML Engineer,84532,1 +47305,Male,43,Bachelors,18,70,41,87,38,8.0,4,29,Semi-Urban,Software Engineer,59825,0 +47306,Male,37,PhD,13,59,28,88,63,9.0,4,41,Urban,Software Engineer,21694,0 +47307,Female,57,PhD,10,41,65,93,65,7.0,6,43,Urban,Manager,144954,1 +47308,Male,29,Diploma,19,6,84,16,86,9.0,5,76,Semi-Urban,Software Engineer,31755,0 +47309,Other,21,Diploma,17,21,68,27,70,2.0,6,1,Rural,Data Analyst,131069,0 +47310,Male,51,Bachelors,15,1,71,47,93,1.0,5,79,Urban,Software Engineer,25234,0 +47311,Male,42,Masters,18,47,78,81,41,9.0,3,79,Rural,HR Executive,61111,1 +47312,Male,23,PhD,4,52,93,53,26,5.0,3,67,Urban,Software Engineer,87166,1 +47313,Female,50,Diploma,17,36,86,94,40,7.0,7,56,Urban,Software Engineer,123002,1 +47314,Male,28,Diploma,12,45,20,8,10,5.0,1,36,Rural,Software Engineer,80306,0 +47315,Male,36,High School,13,77,79,51,18,8.0,4,90,Urban,Manager,102887,1 +47316,Male,30,Bachelors,17,41,68,8,1,6.0,3,18,Urban,Software Engineer,61262,0 +47317,Female,38,Masters,14,12,69,32,34,1.0,6,51,Semi-Urban,Manager,147257,0 +47318,Other,36,Bachelors,13,26,20,81,31,3.0,0,7,Urban,Manager,98092,0 +47319,Female,25,Diploma,8,19,62,16,2,5.0,0,84,Semi-Urban,Manager,99992,0 +47320,Female,24,Diploma,5,63,71,70,43,8.0,5,60,Semi-Urban,Software Engineer,148959,1 +47321,Male,30,Bachelors,14,71,2,71,28,3.0,3,98,Urban,HR Executive,122041,1 +47322,Male,55,Diploma,3,3,60,24,20,0.0,4,49,Rural,Manager,86625,0 +47323,Male,45,Bachelors,19,72,49,59,62,1.0,6,70,Semi-Urban,HR Executive,90286,1 +47324,Female,32,Diploma,2,42,60,49,31,4.0,3,4,Urban,ML Engineer,62601,0 +47325,Female,28,Masters,2,21,22,95,71,9.0,6,31,Rural,ML Engineer,35914,0 +47326,Female,54,Bachelors,7,30,80,46,24,7.0,6,86,Urban,ML Engineer,72761,1 +47327,Other,21,PhD,13,88,96,10,38,9.0,1,56,Urban,Manager,48057,1 +47328,Female,37,Bachelors,14,2,77,15,38,9.0,7,10,Urban,ML Engineer,90280,0 +47329,Male,37,Bachelors,7,30,23,89,99,0.0,6,37,Urban,ML Engineer,24211,0 +47330,Male,57,Bachelors,10,23,1,81,10,3.0,6,14,Urban,HR Executive,99186,0 +47331,Female,24,Diploma,16,91,51,77,20,5.0,5,22,Rural,Software Engineer,75612,1 +47332,Female,28,Diploma,14,84,48,80,67,5.0,4,80,Urban,Manager,131163,1 +47333,Male,30,Diploma,12,66,13,97,35,3.0,6,67,Rural,ML Engineer,62070,1 +47334,Female,45,Bachelors,6,95,73,51,56,9.0,5,67,Urban,ML Engineer,87524,1 +47335,Male,46,High School,7,27,7,39,32,3.0,5,76,Semi-Urban,ML Engineer,56704,0 +47336,Male,57,Diploma,19,88,43,76,97,2.0,2,64,Urban,ML Engineer,67445,1 +47337,Female,36,Diploma,3,18,58,82,18,9.0,4,51,Urban,ML Engineer,108392,0 +47338,Female,32,Diploma,7,45,27,48,80,1.0,5,5,Semi-Urban,ML Engineer,104707,0 +47339,Male,55,Bachelors,18,67,35,2,36,4.0,2,90,Urban,HR Executive,93692,0 +47340,Male,57,Diploma,19,58,21,14,12,3.0,0,31,Semi-Urban,ML Engineer,64593,0 +47341,Female,32,Bachelors,11,13,19,2,72,4.0,1,6,Semi-Urban,Data Analyst,77361,0 +47342,Male,55,Bachelors,10,59,20,47,90,1.0,3,62,Rural,ML Engineer,128309,0 +47343,Male,25,High School,13,84,19,69,41,7.0,6,47,Rural,Software Engineer,86732,0 +47344,Male,37,Bachelors,17,71,55,56,80,8.0,2,70,Urban,Data Analyst,44867,1 +47345,Male,46,High School,10,79,85,87,21,0.0,4,71,Urban,ML Engineer,52814,1 +47346,Female,47,Bachelors,18,42,7,11,90,3.0,1,57,Urban,Manager,40617,0 +47347,Male,29,Bachelors,1,81,51,84,79,8.0,4,79,Rural,Manager,97713,1 +47348,Male,24,Diploma,16,99,80,32,83,7.0,4,11,Rural,HR Executive,120396,0 +47349,Female,46,Bachelors,6,29,43,99,69,2.0,5,68,Urban,Software Engineer,85214,0 +47350,Other,54,High School,10,51,98,26,28,8.0,7,5,Urban,Manager,94149,0 +47351,Male,54,Bachelors,9,79,51,95,32,1.0,1,82,Semi-Urban,HR Executive,51646,1 +47352,Male,51,Masters,6,4,16,28,71,1.0,5,60,Urban,ML Engineer,121181,0 +47353,Male,35,Diploma,9,9,75,43,36,9.0,1,99,Semi-Urban,Data Analyst,107756,0 +47354,Male,36,High School,14,87,82,41,13,3.0,6,13,Semi-Urban,Data Analyst,48796,0 +47355,Male,51,Masters,0,10,42,91,11,2.0,4,39,Rural,HR Executive,120474,0 +47356,Male,53,Diploma,5,76,17,89,7,3.0,7,45,Urban,Software Engineer,64208,0 +47357,Female,52,PhD,9,34,33,66,75,3.0,4,13,Urban,ML Engineer,107701,0 +47358,Other,30,Masters,9,49,92,69,39,9.0,0,39,Semi-Urban,Data Analyst,146823,1 +47359,Female,49,Masters,0,18,31,29,67,0.0,6,85,Urban,HR Executive,142126,0 +47360,Female,22,Bachelors,12,82,0,45,63,3.0,6,41,Rural,HR Executive,65621,0 +47361,Female,44,Masters,6,52,32,50,38,4.0,4,64,Semi-Urban,Manager,49399,0 +47362,Male,44,Bachelors,10,82,73,34,29,4.0,4,98,Urban,HR Executive,106990,1 +47363,Male,29,Bachelors,10,95,2,72,71,3.0,7,27,Rural,ML Engineer,113147,0 +47364,Female,58,High School,1,97,83,17,1,2.0,4,4,Rural,HR Executive,72046,0 +47365,Female,53,Diploma,3,15,90,2,49,4.0,1,65,Rural,Software Engineer,99145,0 +47366,Male,25,Masters,6,37,92,97,55,0.0,3,25,Semi-Urban,Software Engineer,93469,1 +47367,Male,31,Bachelors,14,56,87,60,91,0.0,7,16,Urban,Software Engineer,42929,0 +47368,Other,31,Bachelors,11,1,14,29,4,1.0,6,99,Urban,Software Engineer,99967,0 +47369,Male,58,Diploma,16,82,32,47,98,1.0,5,68,Urban,Manager,45380,0 +47370,Male,33,Bachelors,14,15,3,73,47,2.0,6,86,Urban,Manager,51651,0 +47371,Male,53,Bachelors,3,53,26,63,95,0.0,1,29,Semi-Urban,Software Engineer,74536,0 +47372,Male,24,Diploma,17,23,2,81,96,3.0,6,44,Urban,Manager,120287,0 +47373,Male,55,High School,9,40,88,69,23,7.0,2,91,Urban,HR Executive,112098,1 +47374,Male,26,Diploma,12,78,50,88,72,4.0,4,96,Urban,HR Executive,143151,1 +47375,Female,22,Masters,10,71,81,51,92,8.0,0,30,Urban,HR Executive,100220,0 +47376,Male,23,Bachelors,16,89,61,21,2,8.0,4,5,Urban,Data Analyst,29997,0 +47377,Female,32,Bachelors,19,23,63,77,96,9.0,6,43,Urban,Data Analyst,114963,0 +47378,Male,22,Bachelors,0,0,97,36,98,6.0,7,19,Urban,HR Executive,35234,0 +47379,Male,48,Bachelors,6,19,33,67,84,4.0,7,8,Rural,Software Engineer,122755,0 +47380,Female,25,Masters,1,96,42,27,34,2.0,4,16,Urban,Software Engineer,52234,0 +47381,Female,29,Masters,15,88,99,78,27,4.0,2,63,Urban,Manager,87871,1 +47382,Female,42,Bachelors,5,63,93,96,89,1.0,2,24,Semi-Urban,ML Engineer,95379,1 +47383,Male,32,Bachelors,1,76,92,74,82,9.0,7,52,Urban,HR Executive,56708,1 +47384,Male,23,Bachelors,5,83,31,93,20,9.0,0,28,Rural,ML Engineer,65129,1 +47385,Female,25,Masters,3,95,94,22,48,7.0,2,13,Rural,Manager,79429,0 +47386,Male,33,Bachelors,10,35,6,62,90,5.0,1,66,Semi-Urban,HR Executive,99568,0 +47387,Female,51,Bachelors,6,67,38,39,15,3.0,6,21,Rural,Manager,114961,0 +47388,Male,23,Bachelors,9,75,7,61,37,4.0,5,51,Urban,ML Engineer,127313,0 +47389,Female,38,Bachelors,6,60,32,26,17,6.0,1,33,Urban,HR Executive,94686,0 +47390,Female,36,Diploma,12,88,24,73,41,1.0,4,96,Semi-Urban,Software Engineer,75342,1 +47391,Male,22,Masters,12,34,98,78,67,8.0,5,16,Urban,ML Engineer,30220,0 +47392,Male,31,Diploma,9,10,70,25,96,7.0,2,35,Rural,Software Engineer,141057,0 +47393,Female,44,Diploma,15,3,33,66,25,3.0,5,31,Urban,Manager,69906,0 +47394,Female,49,High School,16,26,83,96,24,0.0,7,81,Urban,ML Engineer,28710,1 +47395,Male,27,Bachelors,1,14,63,12,15,9.0,4,91,Semi-Urban,Software Engineer,136734,0 +47396,Male,39,Masters,2,70,86,79,10,7.0,1,39,Rural,Data Analyst,56933,1 +47397,Male,37,Diploma,16,25,13,41,7,9.0,7,21,Urban,Software Engineer,139219,0 +47398,Male,27,Diploma,11,5,78,87,8,7.0,5,28,Semi-Urban,Data Analyst,56103,0 +47399,Male,23,Masters,16,74,12,38,94,0.0,4,32,Urban,Manager,114888,0 +47400,Female,54,Masters,14,97,65,39,36,0.0,5,64,Urban,Software Engineer,41250,1 +47401,Male,54,High School,6,35,57,45,61,4.0,3,75,Semi-Urban,Software Engineer,149606,0 +47402,Female,53,Bachelors,0,19,23,23,31,3.0,2,60,Rural,Software Engineer,117797,0 +47403,Female,52,Bachelors,7,27,83,23,10,7.0,7,14,Rural,Software Engineer,116315,0 +47404,Male,44,High School,14,2,62,88,51,5.0,0,41,Semi-Urban,ML Engineer,63746,0 +47405,Male,41,High School,7,74,83,16,28,6.0,1,74,Urban,Data Analyst,51400,1 +47406,Female,52,High School,18,74,36,91,18,2.0,5,17,Urban,Data Analyst,70723,0 +47407,Male,47,Diploma,11,39,31,37,23,9.0,1,50,Urban,Manager,120432,0 +47408,Male,42,Bachelors,14,97,91,42,39,1.0,7,7,Rural,Software Engineer,119881,1 +47409,Female,34,Bachelors,15,25,28,76,15,1.0,1,44,Urban,Manager,36131,0 +47410,Male,34,Bachelors,1,28,28,13,88,3.0,3,29,Urban,Data Analyst,33222,0 +47411,Male,31,Masters,19,24,83,61,73,2.0,2,30,Urban,Data Analyst,97447,0 +47412,Male,46,Diploma,15,83,49,39,42,0.0,2,90,Rural,Manager,105492,1 +47413,Female,47,Masters,0,95,35,44,4,6.0,7,11,Urban,HR Executive,64897,0 +47414,Male,40,Bachelors,11,71,52,30,1,6.0,2,54,Urban,HR Executive,34867,0 +47415,Male,23,Diploma,15,39,84,54,44,6.0,1,44,Rural,Data Analyst,30876,0 +47416,Male,50,Masters,6,91,83,27,72,2.0,6,8,Urban,Data Analyst,68224,0 +47417,Female,37,PhD,15,10,45,87,30,7.0,1,61,Semi-Urban,Software Engineer,113928,0 +47418,Female,31,Masters,17,97,38,29,53,8.0,4,12,Rural,Software Engineer,81664,0 +47419,Male,26,PhD,5,99,83,54,88,9.0,3,65,Urban,Manager,67057,1 +47420,Female,21,Bachelors,12,19,86,82,24,3.0,0,7,Urban,ML Engineer,67239,0 +47421,Male,32,PhD,0,3,92,69,65,8.0,4,30,Urban,Manager,106203,0 +47422,Male,52,Masters,10,57,96,34,82,1.0,3,47,Rural,Software Engineer,50239,0 +47423,Other,31,High School,9,48,80,0,88,2.0,5,41,Semi-Urban,Manager,98024,0 +47424,Male,25,Masters,13,10,45,50,54,9.0,5,11,Semi-Urban,Manager,80690,0 +47425,Other,58,PhD,2,57,34,41,17,0.0,1,69,Rural,ML Engineer,108881,0 +47426,Female,28,Masters,3,27,45,18,4,5.0,1,30,Urban,Manager,30739,0 +47427,Male,39,Bachelors,3,15,28,53,79,8.0,5,79,Urban,Manager,105177,0 +47428,Female,42,High School,17,15,35,58,86,8.0,7,41,Urban,Manager,26950,0 +47429,Male,55,Bachelors,7,43,73,16,97,0.0,3,95,Urban,ML Engineer,34549,0 +47430,Male,53,Diploma,2,9,55,93,46,0.0,4,30,Rural,Data Analyst,52405,0 +47431,Female,45,Bachelors,18,49,23,53,97,4.0,5,72,Urban,Manager,38916,0 +47432,Female,40,Diploma,5,22,1,0,79,1.0,2,74,Semi-Urban,Manager,69845,0 +47433,Male,57,Masters,4,82,16,70,94,8.0,4,19,Semi-Urban,ML Engineer,93641,0 +47434,Female,40,Bachelors,1,40,31,86,14,9.0,6,47,Urban,Manager,104104,0 +47435,Female,24,Masters,12,40,22,80,50,6.0,4,58,Urban,Software Engineer,63593,0 +47436,Male,29,High School,5,91,66,59,1,6.0,3,78,Urban,Software Engineer,60271,1 +47437,Female,42,Masters,0,0,91,3,18,8.0,0,50,Urban,HR Executive,65931,0 +47438,Male,32,Masters,18,27,7,67,75,5.0,3,11,Semi-Urban,Software Engineer,35274,0 +47439,Male,39,Bachelors,9,25,19,13,7,1.0,2,36,Urban,ML Engineer,41391,0 +47440,Other,48,Bachelors,5,82,98,9,2,9.0,3,84,Rural,Manager,55872,1 +47441,Male,44,Bachelors,12,5,58,94,34,3.0,2,27,Urban,Manager,140542,0 +47442,Female,56,Masters,11,51,38,8,31,9.0,6,93,Urban,Software Engineer,139467,0 +47443,Male,43,PhD,8,47,45,46,3,5.0,7,68,Semi-Urban,Manager,111948,0 +47444,Male,52,Bachelors,15,8,3,67,75,3.0,6,49,Urban,HR Executive,77860,0 +47445,Female,57,PhD,16,76,12,53,78,4.0,1,76,Semi-Urban,HR Executive,106935,0 +47446,Male,32,Masters,5,50,94,0,85,0.0,3,25,Urban,Software Engineer,110081,0 +47447,Male,39,High School,7,61,59,96,48,4.0,3,24,Semi-Urban,Software Engineer,107205,1 +47448,Female,43,Bachelors,4,43,0,17,73,9.0,4,75,Urban,Software Engineer,46178,0 +47449,Other,41,High School,10,41,67,90,82,5.0,4,83,Semi-Urban,Manager,125840,1 +47450,Male,23,High School,14,59,57,94,32,7.0,3,76,Urban,ML Engineer,68033,1 +47451,Male,59,Bachelors,19,84,42,79,85,1.0,3,42,Rural,ML Engineer,134510,1 +47452,Male,22,Masters,15,7,39,29,50,4.0,4,90,Semi-Urban,Data Analyst,53028,0 +47453,Female,34,Bachelors,0,80,68,29,54,1.0,3,70,Urban,Data Analyst,63753,1 +47454,Male,40,Masters,0,62,49,28,62,1.0,2,18,Urban,Data Analyst,71291,0 +47455,Male,42,Bachelors,1,7,65,48,93,1.0,7,3,Urban,HR Executive,69905,0 +47456,Female,54,High School,8,8,70,2,10,0.0,2,93,Semi-Urban,Data Analyst,31505,0 +47457,Male,28,Bachelors,4,5,6,44,40,3.0,4,4,Urban,Data Analyst,124246,0 +47458,Male,48,Bachelors,17,66,15,79,36,1.0,6,68,Rural,HR Executive,133908,0 +47459,Male,35,Diploma,8,42,52,80,21,7.0,0,38,Urban,Manager,25527,0 +47460,Female,26,Masters,14,14,79,0,4,5.0,0,53,Rural,ML Engineer,64870,0 +47461,Male,47,High School,1,59,25,19,83,3.0,5,71,Urban,Data Analyst,122792,0 +47462,Male,45,Masters,5,45,34,89,5,6.0,1,82,Urban,ML Engineer,122957,1 +47463,Female,29,Diploma,1,12,4,10,3,2.0,5,59,Rural,HR Executive,69937,0 +47464,Female,49,High School,16,68,27,31,20,6.0,4,36,Urban,Software Engineer,127179,0 +47465,Male,46,Bachelors,15,65,97,38,98,9.0,5,57,Urban,HR Executive,134198,1 +47466,Male,57,Diploma,8,41,12,99,16,3.0,2,50,Rural,HR Executive,31476,0 +47467,Male,57,Bachelors,13,85,89,14,88,6.0,0,90,Rural,Manager,44734,1 +47468,Male,56,Bachelors,13,46,45,73,71,1.0,0,51,Semi-Urban,Data Analyst,69311,0 +47469,Male,28,Bachelors,19,37,32,31,14,0.0,2,6,Semi-Urban,ML Engineer,59599,0 +47470,Male,43,Masters,19,56,73,85,27,7.0,5,20,Urban,Data Analyst,74926,0 +47471,Female,55,Bachelors,7,12,66,80,41,8.0,3,47,Semi-Urban,Software Engineer,114572,0 +47472,Male,21,Bachelors,1,66,16,57,8,8.0,0,52,Urban,Data Analyst,76235,0 +47473,Male,44,High School,1,16,81,95,37,7.0,2,71,Urban,ML Engineer,28045,1 +47474,Male,49,Bachelors,2,53,39,42,21,5.0,6,11,Rural,ML Engineer,57897,0 +47475,Other,36,High School,10,45,63,87,25,2.0,7,25,Urban,Software Engineer,68546,0 +47476,Male,25,Bachelors,17,94,7,60,91,9.0,6,36,Semi-Urban,HR Executive,23004,0 +47477,Female,21,Masters,17,0,36,28,8,0.0,2,46,Rural,HR Executive,48888,0 +47478,Male,53,Masters,7,10,7,36,97,2.0,5,90,Urban,ML Engineer,57157,0 +47479,Female,22,Bachelors,2,83,41,57,61,6.0,2,83,Rural,HR Executive,27378,1 +47480,Male,55,Bachelors,7,62,94,49,32,9.0,5,69,Semi-Urban,Manager,122576,1 +47481,Male,37,Diploma,9,54,27,62,54,1.0,6,22,Semi-Urban,ML Engineer,128013,0 +47482,Female,21,Bachelors,8,23,63,70,13,4.0,1,97,Rural,HR Executive,35372,1 +47483,Male,33,Bachelors,12,61,42,55,64,7.0,0,74,Urban,ML Engineer,108664,0 +47484,Male,28,Bachelors,0,57,54,97,95,1.0,3,10,Urban,ML Engineer,135671,0 +47485,Male,32,Bachelors,3,20,37,91,53,4.0,7,24,Semi-Urban,ML Engineer,32579,0 +47486,Male,36,High School,12,37,2,99,42,1.0,1,12,Rural,Manager,90677,0 +47487,Female,31,Masters,2,98,81,25,83,6.0,7,2,Urban,Software Engineer,88127,0 +47488,Male,58,PhD,7,83,9,24,24,5.0,4,84,Semi-Urban,HR Executive,131893,0 +47489,Male,25,Masters,11,64,66,32,62,1.0,4,2,Urban,Software Engineer,21517,0 +47490,Male,53,Diploma,10,59,7,85,62,9.0,4,5,Urban,Software Engineer,122124,0 +47491,Male,53,Bachelors,9,55,25,72,14,2.0,2,60,Urban,HR Executive,90190,0 +47492,Male,30,Bachelors,9,28,45,58,53,0.0,0,76,Urban,Manager,64543,0 +47493,Male,47,Diploma,14,28,43,84,2,8.0,4,13,Rural,Data Analyst,48282,0 +47494,Male,40,Bachelors,10,6,13,23,43,2.0,0,5,Rural,Manager,55859,0 +47495,Female,33,High School,13,3,1,91,46,8.0,7,90,Rural,Manager,47681,0 +47496,Male,34,Bachelors,8,85,30,98,81,3.0,4,60,Urban,Manager,126268,1 +47497,Female,34,Bachelors,17,59,18,29,31,6.0,7,98,Urban,ML Engineer,35828,0 +47498,Female,56,PhD,3,6,26,60,93,8.0,2,93,Semi-Urban,HR Executive,92579,0 +47499,Male,29,Bachelors,16,37,24,18,39,0.0,3,46,Urban,ML Engineer,83409,0 +47500,Male,45,Bachelors,5,68,43,28,81,5.0,7,65,Rural,Manager,31151,0 +47501,Male,22,High School,3,33,38,62,6,4.0,5,69,Semi-Urban,Software Engineer,39071,0 +47502,Male,23,Masters,11,17,62,46,85,4.0,3,33,Semi-Urban,ML Engineer,79625,0 +47503,Female,21,Diploma,2,13,96,90,79,4.0,1,52,Urban,Software Engineer,62365,1 +47504,Female,42,High School,14,85,55,22,3,8.0,5,18,Rural,ML Engineer,120264,0 +47505,Male,42,High School,5,83,13,48,35,7.0,5,66,Urban,Data Analyst,27222,0 +47506,Male,52,Diploma,3,96,6,43,80,8.0,1,94,Rural,Data Analyst,119908,1 +47507,Female,39,High School,11,58,85,75,61,3.0,3,78,Rural,Data Analyst,86822,1 +47508,Male,51,Masters,11,19,27,70,37,8.0,2,95,Rural,ML Engineer,134850,0 +47509,Other,51,High School,12,47,31,88,17,8.0,7,74,Urban,ML Engineer,133411,0 +47510,Male,30,Bachelors,9,40,45,76,73,3.0,4,61,Semi-Urban,ML Engineer,133374,0 +47511,Male,52,High School,2,40,34,5,90,0.0,6,24,Urban,Software Engineer,64471,0 +47512,Female,34,Bachelors,5,14,74,82,49,8.0,4,21,Rural,Data Analyst,65079,0 +47513,Male,56,Bachelors,9,52,75,65,0,7.0,2,32,Semi-Urban,Data Analyst,96139,0 +47514,Female,25,Masters,7,6,78,31,39,7.0,1,7,Semi-Urban,Data Analyst,120449,0 +47515,Male,37,Bachelors,15,72,42,34,80,8.0,4,95,Urban,Software Engineer,37915,1 +47516,Female,23,Diploma,15,41,97,79,77,9.0,3,68,Rural,Manager,145256,1 +47517,Female,38,Bachelors,10,72,56,96,37,8.0,6,8,Urban,HR Executive,59356,0 +47518,Male,26,Masters,4,35,52,74,27,4.0,3,92,Rural,ML Engineer,53710,1 +47519,Male,25,Masters,17,26,46,32,2,9.0,3,6,Urban,Software Engineer,75903,0 +47520,Female,46,High School,10,9,93,17,65,3.0,0,21,Semi-Urban,ML Engineer,136333,0 +47521,Other,21,Diploma,3,81,57,31,60,4.0,4,25,Rural,ML Engineer,67453,0 +47522,Female,40,Diploma,14,44,13,25,83,5.0,7,6,Urban,Software Engineer,30278,0 +47523,Other,48,Bachelors,16,84,12,5,95,5.0,1,84,Urban,ML Engineer,96709,0 +47524,Male,28,Masters,15,18,34,43,79,3.0,1,40,Semi-Urban,Data Analyst,94584,0 +47525,Female,53,Bachelors,5,88,12,24,31,1.0,1,62,Semi-Urban,ML Engineer,67536,0 +47526,Male,49,Bachelors,6,22,74,40,74,4.0,1,53,Urban,Software Engineer,125956,0 +47527,Male,54,Bachelors,19,13,69,52,33,9.0,0,2,Urban,Data Analyst,122203,0 +47528,Male,39,Bachelors,8,3,17,75,79,1.0,1,29,Semi-Urban,Manager,112938,0 +47529,Female,48,Bachelors,8,13,19,53,10,0.0,5,8,Urban,HR Executive,94567,0 +47530,Male,29,Diploma,16,97,82,23,86,0.0,4,15,Urban,Data Analyst,149536,0 +47531,Female,50,Diploma,0,45,92,80,94,3.0,3,25,Urban,Software Engineer,21292,1 +47532,Female,48,Bachelors,2,93,15,64,28,4.0,3,15,Semi-Urban,Data Analyst,57327,0 +47533,Female,21,Diploma,4,41,68,44,25,0.0,5,17,Urban,HR Executive,109425,0 +47534,Male,52,Masters,14,80,61,31,83,7.0,6,42,Urban,Data Analyst,41671,0 +47535,Male,55,Bachelors,5,98,16,7,57,0.0,3,28,Urban,Data Analyst,133101,0 +47536,Male,26,Bachelors,7,14,3,45,27,4.0,3,72,Urban,Software Engineer,47114,0 +47537,Female,37,PhD,18,88,50,22,20,5.0,3,45,Semi-Urban,Data Analyst,23741,0 +47538,Male,27,PhD,13,93,56,86,90,8.0,3,49,Urban,Manager,135321,1 +47539,Female,59,Bachelors,0,12,22,47,1,4.0,6,64,Semi-Urban,Manager,148380,0 +47540,Male,28,Bachelors,1,95,49,73,65,0.0,2,57,Urban,ML Engineer,105378,1 +47541,Female,27,Diploma,5,30,54,84,40,3.0,2,22,Rural,ML Engineer,46869,0 +47542,Male,44,Bachelors,7,38,39,9,40,0.0,4,97,Semi-Urban,Manager,138432,0 +47543,Female,38,Diploma,2,22,67,53,57,7.0,4,71,Rural,Data Analyst,145450,0 +47544,Male,45,Bachelors,12,38,27,33,39,5.0,3,60,Rural,Software Engineer,127180,0 +47545,Male,32,Masters,19,49,21,69,76,0.0,0,65,Semi-Urban,Data Analyst,79078,0 +47546,Female,33,High School,17,9,50,31,12,3.0,6,67,Semi-Urban,Data Analyst,42591,0 +47547,Male,40,Masters,8,20,90,29,4,4.0,4,76,Rural,HR Executive,60636,0 +47548,Other,40,High School,12,63,17,18,23,1.0,2,30,Rural,Manager,34253,0 +47549,Male,59,Diploma,2,40,67,35,13,7.0,4,69,Rural,Manager,126741,0 +47550,Male,33,Bachelors,6,53,43,46,85,2.0,6,36,Urban,Data Analyst,52851,0 +47551,Male,53,Diploma,9,43,68,83,63,1.0,5,16,Rural,ML Engineer,30431,0 +47552,Other,43,Masters,14,96,36,12,10,3.0,3,49,Urban,ML Engineer,94183,0 +47553,Other,45,Bachelors,14,23,62,65,31,2.0,2,23,Rural,Software Engineer,44341,0 +47554,Male,35,Masters,13,90,88,19,68,9.0,7,7,Semi-Urban,ML Engineer,32284,0 +47555,Male,34,Diploma,12,78,41,36,78,7.0,3,74,Semi-Urban,Software Engineer,29916,0 +47556,Female,54,High School,11,85,17,6,90,6.0,6,62,Urban,HR Executive,121328,0 +47557,Female,39,Bachelors,17,37,95,15,12,2.0,3,27,Urban,ML Engineer,61408,0 +47558,Female,53,High School,11,48,14,33,15,4.0,3,23,Urban,Data Analyst,35287,0 +47559,Female,36,Bachelors,0,76,74,66,9,5.0,4,39,Urban,Software Engineer,102535,1 +47560,Male,42,High School,3,70,16,85,13,8.0,4,77,Semi-Urban,Software Engineer,29919,1 +47561,Female,35,Bachelors,5,7,65,80,25,0.0,3,47,Semi-Urban,Software Engineer,86563,0 +47562,Female,30,PhD,9,97,38,92,32,5.0,4,3,Urban,Data Analyst,112510,0 +47563,Male,26,High School,14,84,50,77,68,4.0,7,25,Urban,Manager,149452,1 +47564,Female,21,Diploma,2,35,20,37,83,5.0,4,78,Semi-Urban,HR Executive,80857,0 +47565,Female,34,Bachelors,13,36,69,19,44,5.0,3,33,Rural,Data Analyst,33793,0 +47566,Female,58,PhD,12,64,25,69,20,9.0,4,32,Urban,Software Engineer,117810,0 +47567,Male,24,Masters,0,41,22,55,60,6.0,2,97,Urban,HR Executive,35296,0 +47568,Male,27,Bachelors,0,47,19,25,71,2.0,2,89,Rural,Manager,69223,0 +47569,Male,31,High School,14,18,77,50,15,5.0,3,30,Urban,Manager,80083,0 +47570,Male,21,Bachelors,9,35,94,88,89,0.0,2,25,Semi-Urban,Manager,44412,1 +47571,Other,59,Bachelors,17,50,23,14,98,5.0,0,99,Urban,Manager,59192,0 +47572,Male,56,Masters,17,27,56,46,59,1.0,5,89,Urban,HR Executive,93053,0 +47573,Female,57,Masters,19,47,43,55,6,8.0,3,75,Urban,Manager,75482,0 +47574,Male,38,Masters,14,54,11,61,37,8.0,1,22,Rural,Software Engineer,89204,0 +47575,Male,25,Diploma,16,41,10,53,50,7.0,2,94,Urban,HR Executive,117357,0 +47576,Male,28,Diploma,12,47,93,45,24,2.0,3,63,Urban,Data Analyst,136821,1 +47577,Male,34,Masters,4,20,89,14,95,5.0,4,73,Urban,ML Engineer,68591,0 +47578,Male,22,Bachelors,8,29,8,57,81,2.0,1,48,Semi-Urban,Manager,110539,0 +47579,Female,57,High School,18,93,67,32,9,7.0,6,42,Urban,Manager,86323,0 +47580,Female,22,Bachelors,1,25,6,59,44,6.0,2,7,Urban,Software Engineer,52750,0 +47581,Male,39,Bachelors,2,36,93,8,8,8.0,7,34,Urban,ML Engineer,103112,0 +47582,Male,43,Bachelors,17,47,5,80,74,3.0,3,3,Urban,Manager,131492,0 +47583,Female,38,High School,18,33,7,75,40,6.0,0,23,Semi-Urban,Software Engineer,70746,0 +47584,Female,49,Diploma,10,15,0,76,28,7.0,1,62,Semi-Urban,Manager,38802,0 +47585,Male,43,PhD,17,93,70,58,12,9.0,7,25,Semi-Urban,Data Analyst,43589,1 +47586,Male,33,Masters,1,43,93,86,78,2.0,2,9,Urban,Manager,129531,0 +47587,Male,50,Bachelors,17,6,4,76,44,1.0,0,61,Semi-Urban,Manager,54113,0 +47588,Male,26,Masters,12,80,94,81,23,3.0,5,33,Urban,Manager,112072,1 +47589,Male,57,Bachelors,18,21,4,40,20,8.0,4,23,Rural,Manager,72372,0 +47590,Male,46,Bachelors,10,49,10,63,76,6.0,4,57,Urban,ML Engineer,139245,0 +47591,Female,44,Bachelors,17,22,0,18,60,0.0,2,15,Urban,HR Executive,106978,0 +47592,Male,57,Diploma,19,42,52,93,27,6.0,7,69,Urban,HR Executive,22589,1 +47593,Female,57,Bachelors,18,43,38,48,0,6.0,6,64,Rural,Manager,70737,0 +47594,Male,35,High School,11,31,19,53,51,2.0,7,17,Urban,Data Analyst,51097,0 +47595,Female,32,Bachelors,15,22,41,44,23,5.0,2,34,Semi-Urban,HR Executive,20019,0 +47596,Female,32,Diploma,15,60,0,38,68,5.0,7,34,Semi-Urban,Data Analyst,143454,0 +47597,Female,45,Masters,7,64,32,57,67,6.0,5,71,Semi-Urban,Data Analyst,140708,0 +47598,Female,30,Masters,0,83,3,59,24,4.0,1,66,Urban,HR Executive,136814,0 +47599,Female,25,High School,8,76,78,94,13,3.0,0,34,Urban,ML Engineer,139816,1 +47600,Male,53,Bachelors,3,60,86,18,3,2.0,3,62,Semi-Urban,Data Analyst,113731,0 +47601,Male,55,Masters,2,55,72,36,8,0.0,6,24,Urban,Software Engineer,104876,0 +47602,Female,48,Bachelors,14,59,47,32,37,4.0,0,44,Urban,Software Engineer,93166,0 +47603,Female,27,Bachelors,18,6,79,68,66,6.0,6,8,Urban,ML Engineer,28390,0 +47604,Male,34,Diploma,7,74,38,87,79,2.0,2,44,Urban,Software Engineer,49992,1 +47605,Female,39,Bachelors,10,23,0,83,71,7.0,1,60,Urban,Software Engineer,58784,0 +47606,Male,55,Masters,12,45,22,36,13,3.0,6,11,Urban,ML Engineer,117438,0 +47607,Male,40,Bachelors,5,77,18,59,63,7.0,6,95,Urban,HR Executive,110957,1 +47608,Female,39,Masters,7,44,44,70,67,2.0,7,53,Rural,HR Executive,147268,0 +47609,Male,39,Bachelors,19,18,16,58,52,8.0,7,77,Rural,Manager,21323,0 +47610,Male,52,Masters,9,32,43,7,70,2.0,4,54,Rural,Manager,123376,0 +47611,Male,28,Bachelors,7,9,25,18,5,7.0,1,78,Urban,HR Executive,75016,0 +47612,Other,47,Diploma,18,8,61,82,52,3.0,1,28,Semi-Urban,Data Analyst,80580,0 +47613,Other,53,Diploma,7,23,34,28,63,7.0,5,71,Rural,Software Engineer,82201,0 +47614,Male,54,PhD,11,95,64,64,19,7.0,5,46,Urban,HR Executive,147557,1 +47615,Male,43,Bachelors,17,19,79,68,30,5.0,7,1,Rural,Data Analyst,69356,0 +47616,Male,50,PhD,11,7,16,73,18,1.0,0,29,Semi-Urban,HR Executive,38582,0 +47617,Female,50,PhD,1,28,39,23,57,0.0,3,44,Semi-Urban,Manager,66454,0 +47618,Female,27,Bachelors,1,12,31,29,53,3.0,0,37,Urban,HR Executive,54811,0 +47619,Male,22,Diploma,8,52,92,95,7,5.0,0,51,Urban,Data Analyst,102217,1 +47620,Female,30,High School,7,7,68,72,13,8.0,3,26,Urban,ML Engineer,129537,0 +47621,Female,42,Diploma,1,51,57,21,82,5.0,1,93,Urban,ML Engineer,89380,0 +47622,Male,25,Diploma,0,36,34,49,77,3.0,6,20,Urban,HR Executive,82459,0 +47623,Male,53,Diploma,8,43,73,18,85,8.0,6,32,Urban,HR Executive,107526,0 +47624,Male,31,Masters,18,58,79,49,64,3.0,2,11,Urban,Data Analyst,87222,0 +47625,Male,22,Masters,8,38,24,32,70,9.0,7,93,Urban,Manager,100000,0 +47626,Male,44,High School,15,58,11,90,18,2.0,3,10,Urban,Manager,22799,0 +47627,Male,44,Diploma,10,3,68,51,94,8.0,7,39,Urban,HR Executive,119834,0 +47628,Male,43,High School,12,44,55,2,81,6.0,1,63,Urban,HR Executive,104112,0 +47629,Male,55,Bachelors,1,62,31,23,90,8.0,4,76,Rural,HR Executive,42188,0 +47630,Female,22,Masters,14,78,19,44,37,5.0,7,31,Rural,ML Engineer,70551,0 +47631,Other,34,High School,1,25,3,74,5,6.0,0,69,Semi-Urban,ML Engineer,94801,0 +47632,Female,50,Diploma,14,68,47,37,29,9.0,2,17,Urban,Software Engineer,143748,0 +47633,Female,42,Bachelors,0,82,54,70,64,0.0,2,31,Urban,Software Engineer,100736,0 +47634,Female,24,Bachelors,0,0,69,7,83,1.0,6,27,Urban,Software Engineer,146747,0 +47635,Male,34,Masters,3,13,60,11,91,4.0,3,9,Rural,Data Analyst,139968,0 +47636,Male,35,Bachelors,18,51,76,70,21,3.0,2,78,Rural,Manager,33707,1 +47637,Male,46,Bachelors,11,87,12,84,3,9.0,0,37,Rural,Data Analyst,47107,0 +47638,Male,26,Masters,9,23,59,5,69,6.0,4,53,Rural,HR Executive,113276,0 +47639,Female,35,Masters,2,59,75,9,28,9.0,2,84,Urban,HR Executive,102399,0 +47640,Male,49,Diploma,8,79,56,52,79,4.0,0,69,Urban,Data Analyst,27060,1 +47641,Female,49,Diploma,12,21,60,37,8,1.0,2,88,Rural,ML Engineer,71484,0 +47642,Male,37,Bachelors,19,97,94,9,13,9.0,3,36,Urban,ML Engineer,102270,1 +47643,Male,50,High School,4,79,71,45,88,0.0,5,51,Semi-Urban,HR Executive,145905,1 +47644,Other,26,Masters,18,44,46,1,50,9.0,4,57,Rural,ML Engineer,104210,0 +47645,Male,22,High School,4,99,21,77,11,3.0,5,1,Rural,Data Analyst,54616,0 +47646,Male,46,Diploma,2,36,5,40,16,9.0,7,13,Urban,Data Analyst,43073,0 +47647,Male,45,Bachelors,16,17,82,4,42,4.0,4,18,Semi-Urban,ML Engineer,68655,0 +47648,Male,45,High School,17,16,20,32,34,0.0,2,87,Urban,Software Engineer,140436,0 +47649,Female,37,Bachelors,4,38,17,40,33,9.0,3,4,Semi-Urban,HR Executive,73411,0 +47650,Female,51,Bachelors,11,6,36,97,20,8.0,7,27,Semi-Urban,Manager,125911,0 +47651,Male,56,Bachelors,16,99,3,11,49,6.0,1,56,Rural,Data Analyst,25291,0 +47652,Female,35,Diploma,1,86,60,26,72,6.0,4,60,Urban,Data Analyst,45740,0 +47653,Female,24,Bachelors,7,90,13,20,99,4.0,0,72,Rural,Data Analyst,81233,0 +47654,Male,30,Masters,8,50,36,90,91,1.0,4,33,Urban,ML Engineer,78000,0 +47655,Male,42,Masters,0,42,24,86,39,9.0,3,59,Urban,HR Executive,87582,0 +47656,Female,43,Bachelors,17,87,0,99,16,0.0,6,10,Rural,Manager,130019,0 +47657,Female,56,Masters,12,90,36,59,43,9.0,0,69,Urban,Data Analyst,137250,1 +47658,Male,27,Bachelors,3,69,7,57,86,6.0,2,21,Urban,Software Engineer,44415,0 +47659,Male,26,Bachelors,7,84,28,47,2,0.0,7,86,Rural,HR Executive,46194,1 +47660,Male,39,Diploma,0,29,62,82,27,4.0,0,18,Urban,HR Executive,146849,0 +47661,Male,37,Bachelors,16,48,95,57,0,9.0,6,48,Urban,Data Analyst,44282,1 +47662,Male,58,Diploma,19,26,15,81,9,7.0,3,17,Semi-Urban,Manager,96561,0 +47663,Other,46,Masters,14,30,66,72,97,0.0,0,6,Urban,Manager,134756,0 +47664,Female,41,Diploma,0,60,19,38,2,3.0,5,82,Urban,Manager,39018,0 +47665,Female,39,Diploma,1,98,9,15,88,8.0,3,96,Urban,Data Analyst,123656,0 +47666,Male,22,Masters,17,78,53,8,10,2.0,5,34,Semi-Urban,Manager,31759,0 +47667,Male,52,Diploma,15,11,13,16,64,2.0,3,61,Urban,HR Executive,73389,0 +47668,Male,59,Diploma,13,11,86,66,48,6.0,7,99,Urban,Data Analyst,59307,1 +47669,Male,40,Masters,14,3,50,2,87,2.0,0,0,Urban,Manager,38682,0 +47670,Male,43,Bachelors,0,9,59,15,40,2.0,0,44,Urban,Software Engineer,65919,0 +47671,Male,41,Bachelors,11,25,62,37,19,7.0,3,57,Urban,Data Analyst,116338,0 +47672,Male,38,PhD,17,29,28,0,47,1.0,2,1,Urban,Software Engineer,103604,0 +47673,Female,25,Bachelors,16,6,56,14,12,7.0,0,64,Semi-Urban,HR Executive,60383,0 +47674,Female,26,High School,11,0,38,62,69,2.0,4,32,Rural,Manager,94254,0 +47675,Male,49,Bachelors,19,71,82,1,20,6.0,3,84,Urban,Data Analyst,92919,1 +47676,Female,35,High School,8,18,52,11,49,6.0,7,26,Semi-Urban,Manager,123699,0 +47677,Female,25,Masters,1,64,15,37,57,3.0,0,45,Rural,Software Engineer,89799,0 +47678,Male,55,Bachelors,8,60,47,99,2,0.0,3,11,Semi-Urban,Software Engineer,109080,0 +47679,Male,46,Bachelors,0,80,75,6,66,9.0,3,86,Semi-Urban,Manager,125806,1 +47680,Female,31,High School,5,91,19,86,22,8.0,3,46,Urban,HR Executive,79381,1 +47681,Male,50,High School,13,46,40,72,20,4.0,6,48,Urban,Manager,115918,0 +47682,Female,37,Masters,11,25,59,91,53,3.0,6,21,Urban,HR Executive,74043,0 +47683,Male,47,Diploma,1,52,7,82,67,5.0,4,69,Urban,ML Engineer,77550,0 +47684,Male,56,Masters,14,0,44,37,14,9.0,5,11,Semi-Urban,ML Engineer,31346,0 +47685,Male,28,Bachelors,1,91,55,6,32,1.0,2,66,Rural,HR Executive,102178,0 +47686,Female,39,Bachelors,11,79,55,56,62,3.0,4,72,Urban,ML Engineer,73074,1 +47687,Other,24,Bachelors,5,49,87,8,53,8.0,0,82,Rural,Data Analyst,58070,0 +47688,Male,26,Masters,15,40,23,37,84,3.0,5,48,Semi-Urban,Software Engineer,129474,0 +47689,Male,25,Diploma,19,66,64,26,98,3.0,1,83,Urban,Data Analyst,134029,1 +47690,Male,26,High School,11,61,28,44,9,2.0,1,73,Urban,Manager,50881,0 +47691,Female,42,Bachelors,16,72,37,19,54,6.0,6,54,Semi-Urban,ML Engineer,94760,0 +47692,Female,33,High School,16,37,78,99,76,7.0,2,14,Semi-Urban,Software Engineer,105639,0 +47693,Male,54,Bachelors,7,96,67,73,64,9.0,2,67,Rural,Manager,103183,1 +47694,Other,33,PhD,8,73,52,62,78,9.0,2,44,Urban,ML Engineer,85375,0 +47695,Female,40,PhD,7,42,78,71,12,9.0,7,94,Semi-Urban,ML Engineer,106790,1 +47696,Male,55,PhD,3,85,40,42,26,7.0,6,10,Rural,Data Analyst,25972,0 +47697,Male,21,High School,0,44,70,49,34,9.0,4,71,Urban,Manager,29770,0 +47698,Male,46,Masters,14,97,0,91,22,1.0,0,65,Urban,ML Engineer,56853,1 +47699,Female,58,Bachelors,0,63,77,97,12,6.0,5,63,Urban,HR Executive,85099,1 +47700,Male,50,Bachelors,4,53,4,39,98,5.0,4,67,Urban,ML Engineer,118593,0 +47701,Female,38,Bachelors,15,75,10,11,35,2.0,7,11,Urban,Manager,57465,0 +47702,Female,52,Bachelors,13,56,86,22,94,8.0,4,9,Urban,ML Engineer,41365,0 +47703,Female,45,Bachelors,10,64,90,71,17,9.0,5,9,Urban,HR Executive,137155,0 +47704,Male,59,Diploma,11,82,36,39,51,6.0,2,94,Urban,Manager,62040,1 +47705,Other,56,High School,8,58,98,80,28,4.0,7,22,Rural,Manager,115960,1 +47706,Male,30,High School,6,62,35,70,18,4.0,1,15,Urban,HR Executive,101244,0 +47707,Female,24,Masters,15,53,2,12,32,9.0,5,28,Urban,HR Executive,73151,0 +47708,Male,27,Bachelors,8,48,94,59,66,4.0,6,88,Semi-Urban,Data Analyst,49789,1 +47709,Other,56,PhD,8,80,96,96,85,9.0,6,15,Urban,Manager,70367,1 +47710,Female,30,Diploma,10,81,74,7,57,7.0,0,34,Urban,Manager,31788,0 +47711,Female,57,High School,1,80,61,12,80,9.0,5,92,Urban,HR Executive,83410,1 +47712,Male,24,Bachelors,8,44,50,93,4,5.0,6,46,Urban,ML Engineer,138678,0 +47713,Male,26,Masters,18,47,50,38,45,7.0,3,49,Urban,Data Analyst,120499,0 +47714,Male,40,Bachelors,7,38,38,4,45,7.0,5,32,Semi-Urban,Software Engineer,95333,0 +47715,Male,28,Bachelors,9,70,49,0,85,0.0,0,51,Urban,Data Analyst,52828,0 +47716,Male,49,Diploma,15,79,81,70,17,8.0,7,55,Urban,Manager,71136,1 +47717,Other,55,High School,5,66,64,21,54,7.0,5,43,Urban,Manager,35590,0 +47718,Female,37,Bachelors,19,18,49,96,47,3.0,6,21,Rural,Manager,79886,0 +47719,Male,38,Masters,3,15,98,8,14,2.0,2,13,Rural,HR Executive,127023,0 +47720,Other,37,Bachelors,6,62,32,90,84,4.0,5,95,Urban,Software Engineer,94863,1 +47721,Female,33,Bachelors,0,83,72,41,57,5.0,7,73,Urban,HR Executive,32988,1 +47722,Female,40,PhD,8,40,49,70,19,6.0,5,35,Semi-Urban,Software Engineer,102149,0 +47723,Female,41,Diploma,12,50,93,2,98,4.0,0,43,Semi-Urban,HR Executive,48971,0 +47724,Female,35,Diploma,15,69,20,10,33,4.0,6,20,Urban,Manager,147739,0 +47725,Male,57,Bachelors,1,38,80,15,11,9.0,7,22,Urban,Manager,84363,0 +47726,Other,25,Diploma,1,53,54,36,63,9.0,7,27,Urban,ML Engineer,80564,0 +47727,Male,29,Bachelors,18,51,7,38,35,3.0,2,93,Urban,Software Engineer,108160,0 +47728,Female,42,High School,14,43,3,50,43,8.0,4,71,Urban,ML Engineer,69803,0 +47729,Female,35,High School,12,9,72,30,84,3.0,5,76,Rural,Manager,45018,0 +47730,Male,41,Bachelors,3,17,87,55,70,5.0,5,33,Urban,Software Engineer,65803,0 +47731,Female,50,Masters,10,66,80,84,61,0.0,5,30,Urban,Software Engineer,47339,1 +47732,Male,51,Masters,17,19,59,95,60,7.0,7,34,Urban,Software Engineer,88283,0 +47733,Male,51,Bachelors,0,37,84,84,54,6.0,1,79,Urban,Software Engineer,46796,1 +47734,Male,33,Diploma,16,19,14,80,62,2.0,2,92,Urban,Manager,44092,0 +47735,Female,26,High School,8,48,19,74,82,9.0,7,93,Urban,Manager,104722,0 +47736,Male,37,Bachelors,5,53,42,68,19,0.0,1,53,Semi-Urban,Software Engineer,121386,0 +47737,Female,45,Bachelors,15,52,67,23,80,1.0,6,31,Rural,ML Engineer,90475,0 +47738,Female,33,Bachelors,10,55,22,27,28,2.0,6,83,Semi-Urban,Data Analyst,59462,0 +47739,Female,33,High School,8,11,7,58,0,7.0,6,37,Semi-Urban,Manager,69523,0 +47740,Female,50,High School,8,19,90,19,64,8.0,5,13,Urban,Software Engineer,103418,0 +47741,Male,27,PhD,3,3,40,18,20,8.0,6,95,Urban,Data Analyst,147669,0 +47742,Male,25,Bachelors,5,79,63,96,65,4.0,0,95,Urban,Manager,67650,1 +47743,Male,39,High School,11,13,69,46,6,3.0,7,89,Urban,ML Engineer,129469,0 +47744,Male,33,Masters,18,20,89,97,42,4.0,0,57,Urban,Data Analyst,94129,1 +47745,Male,48,PhD,2,51,94,55,64,3.0,4,79,Semi-Urban,Software Engineer,25806,1 +47746,Male,34,Masters,18,5,95,41,13,7.0,7,46,Rural,HR Executive,98061,0 +47747,Female,27,Bachelors,19,19,26,56,70,3.0,2,73,Semi-Urban,Manager,38094,0 +47748,Male,51,High School,4,45,10,7,22,0.0,6,25,Semi-Urban,HR Executive,80471,0 +47749,Female,31,PhD,11,8,49,56,9,3.0,3,29,Semi-Urban,Software Engineer,46070,0 +47750,Male,38,Bachelors,10,29,56,58,77,4.0,5,8,Urban,HR Executive,43902,0 +47751,Female,51,High School,0,62,14,99,42,2.0,7,55,Urban,ML Engineer,131082,0 +47752,Male,41,Masters,12,33,48,46,72,5.0,2,4,Rural,Data Analyst,91989,0 +47753,Female,21,Bachelors,17,2,25,2,33,2.0,3,88,Urban,HR Executive,61009,0 +47754,Male,45,Bachelors,3,72,15,58,70,6.0,3,53,Urban,ML Engineer,69596,0 +47755,Male,29,High School,13,92,26,62,17,9.0,1,5,Urban,Manager,35339,0 +47756,Male,38,Diploma,0,83,66,79,86,5.0,5,25,Semi-Urban,HR Executive,21045,1 +47757,Male,34,Bachelors,3,44,27,62,54,9.0,6,70,Urban,Manager,129571,0 +47758,Female,57,Masters,13,79,16,44,57,0.0,7,30,Rural,HR Executive,53298,0 +47759,Male,42,Masters,13,53,61,82,35,2.0,0,33,Rural,Data Analyst,25946,0 +47760,Male,35,Masters,8,47,82,30,2,6.0,7,46,Semi-Urban,ML Engineer,116585,0 +47761,Female,45,Diploma,4,82,90,87,98,9.0,1,38,Semi-Urban,Data Analyst,35823,1 +47762,Male,44,High School,13,67,17,20,80,0.0,5,69,Urban,Software Engineer,43595,0 +47763,Male,49,Diploma,6,31,28,39,50,9.0,7,9,Semi-Urban,Software Engineer,84727,0 +47764,Male,38,Bachelors,3,19,42,12,86,7.0,2,39,Urban,Software Engineer,69069,0 +47765,Male,55,Bachelors,7,67,19,4,76,7.0,0,12,Rural,Manager,76389,0 +47766,Male,33,Bachelors,8,65,44,91,33,6.0,1,8,Semi-Urban,Software Engineer,131892,0 +47767,Female,50,Diploma,14,55,59,14,47,1.0,1,13,Urban,HR Executive,65633,0 +47768,Male,27,Diploma,2,70,27,86,51,3.0,4,22,Urban,ML Engineer,112182,0 +47769,Female,43,Diploma,1,94,26,76,61,0.0,6,92,Urban,HR Executive,147254,1 +47770,Female,29,Masters,10,47,51,68,37,5.0,4,84,Urban,Data Analyst,125296,1 +47771,Female,23,Masters,9,77,68,9,65,8.0,0,9,Urban,HR Executive,117571,0 +47772,Male,55,Bachelors,9,66,66,44,0,9.0,2,94,Urban,Software Engineer,26035,1 +47773,Male,36,Diploma,12,52,47,45,84,4.0,1,63,Urban,Manager,131002,0 +47774,Male,30,Diploma,14,92,23,30,25,5.0,5,66,Semi-Urban,Data Analyst,49759,0 +47775,Female,42,High School,0,77,93,58,33,0.0,0,47,Urban,HR Executive,146623,1 +47776,Female,28,Bachelors,5,87,38,11,42,6.0,5,14,Rural,Data Analyst,58022,0 +47777,Male,33,High School,5,17,84,62,68,1.0,7,98,Urban,Software Engineer,52613,1 +47778,Other,44,Diploma,5,73,19,91,50,4.0,7,79,Urban,HR Executive,130799,1 +47779,Male,35,Masters,18,48,75,73,80,1.0,5,30,Urban,Software Engineer,27605,0 +47780,Female,47,Bachelors,0,75,66,38,38,9.0,7,33,Rural,HR Executive,69533,0 +47781,Female,37,Diploma,16,58,2,48,99,7.0,2,24,Urban,HR Executive,125808,0 +47782,Female,22,High School,16,84,55,45,41,8.0,0,65,Rural,Manager,146971,1 +47783,Other,57,High School,8,65,4,63,94,2.0,0,39,Urban,Software Engineer,81717,0 +47784,Male,48,PhD,9,93,75,71,57,7.0,7,99,Urban,Software Engineer,110619,1 +47785,Male,45,Masters,12,14,28,11,49,2.0,1,50,Semi-Urban,Software Engineer,39770,0 +47786,Male,58,Masters,15,33,69,39,33,0.0,5,61,Urban,Manager,134708,0 +47787,Female,50,High School,5,85,47,90,32,1.0,7,67,Urban,Software Engineer,28159,1 +47788,Female,30,Bachelors,5,64,66,25,57,5.0,7,46,Semi-Urban,Manager,75624,0 +47789,Male,26,Diploma,14,43,69,10,30,0.0,0,89,Rural,Manager,58977,0 +47790,Male,52,Bachelors,15,43,58,34,72,3.0,1,47,Urban,Data Analyst,130997,0 +47791,Male,30,Masters,18,26,83,20,59,0.0,5,4,Urban,ML Engineer,95229,0 +47792,Male,29,Bachelors,19,78,78,8,76,3.0,2,63,Rural,ML Engineer,91438,0 +47793,Male,51,Bachelors,14,80,63,80,49,1.0,0,82,Rural,ML Engineer,20781,1 +47794,Female,37,Diploma,5,17,5,51,67,9.0,6,66,Semi-Urban,HR Executive,71912,0 +47795,Male,30,Masters,15,64,96,12,10,9.0,0,27,Urban,ML Engineer,50345,0 +47796,Female,58,High School,4,50,92,39,91,8.0,6,99,Urban,Data Analyst,50167,1 +47797,Male,26,High School,0,92,61,61,87,5.0,4,78,Urban,HR Executive,72586,1 +47798,Female,47,High School,12,30,85,98,11,3.0,2,21,Urban,ML Engineer,87308,0 +47799,Female,58,High School,18,56,99,64,86,2.0,3,66,Urban,Manager,93055,1 +47800,Male,26,Diploma,11,46,90,83,47,1.0,1,89,Urban,Software Engineer,69922,1 +47801,Female,42,Masters,9,50,19,4,95,2.0,4,74,Rural,HR Executive,127864,0 +47802,Male,49,Bachelors,5,18,35,3,17,2.0,5,70,Semi-Urban,ML Engineer,68406,0 +47803,Other,35,Masters,2,21,16,82,7,2.0,7,35,Semi-Urban,ML Engineer,78667,0 +47804,Female,22,Masters,2,3,7,85,73,5.0,3,74,Semi-Urban,ML Engineer,50108,0 +47805,Female,38,Masters,11,71,74,99,34,2.0,7,44,Urban,Software Engineer,33898,1 +47806,Male,30,Masters,7,92,6,54,2,0.0,6,41,Semi-Urban,ML Engineer,87165,0 +47807,Male,21,Diploma,2,98,9,24,50,8.0,1,22,Semi-Urban,Software Engineer,51814,0 +47808,Male,33,PhD,2,21,5,76,5,9.0,7,23,Rural,ML Engineer,42926,0 +47809,Male,33,Diploma,19,56,81,58,97,7.0,7,17,Urban,Manager,105594,0 +47810,Female,53,High School,14,77,81,1,39,1.0,7,71,Urban,ML Engineer,67826,0 +47811,Male,43,Bachelors,17,42,46,50,96,6.0,6,53,Semi-Urban,HR Executive,99933,0 +47812,Male,53,Diploma,5,33,19,84,89,3.0,6,4,Urban,Data Analyst,58275,0 +47813,Male,55,Bachelors,18,80,11,97,3,2.0,4,78,Urban,Software Engineer,93704,1 +47814,Other,57,Diploma,19,86,11,76,92,8.0,0,70,Rural,Manager,95426,1 +47815,Other,38,Bachelors,3,41,94,71,82,4.0,4,36,Urban,HR Executive,109916,1 +47816,Male,58,Bachelors,9,2,39,52,74,9.0,3,23,Urban,Manager,128323,0 +47817,Male,44,Masters,12,28,50,85,60,9.0,5,81,Semi-Urban,Data Analyst,47818,1 +47818,Male,36,Bachelors,3,21,69,45,48,3.0,7,77,Urban,Data Analyst,103972,0 +47819,Male,25,High School,11,1,75,70,63,6.0,6,36,Urban,Manager,135938,0 +47820,Female,32,Bachelors,8,58,84,35,47,5.0,5,3,Semi-Urban,Software Engineer,23451,0 +47821,Female,44,Bachelors,9,15,76,24,64,5.0,2,22,Rural,Data Analyst,70208,0 +47822,Other,25,Diploma,1,7,88,33,78,8.0,3,4,Rural,Manager,43310,0 +47823,Female,26,Bachelors,4,62,8,19,64,1.0,7,92,Urban,ML Engineer,119940,0 +47824,Female,50,Bachelors,9,17,18,28,75,0.0,2,89,Semi-Urban,HR Executive,76434,0 +47825,Female,41,Diploma,12,43,25,72,45,8.0,0,69,Urban,HR Executive,45701,0 +47826,Female,27,Diploma,3,97,18,14,22,2.0,6,91,Urban,HR Executive,138417,0 +47827,Female,35,Masters,11,83,8,92,74,6.0,5,13,Semi-Urban,Software Engineer,40406,0 +47828,Male,41,PhD,2,12,33,10,37,8.0,2,56,Semi-Urban,HR Executive,69250,0 +47829,Female,41,Bachelors,14,60,80,85,98,2.0,1,18,Semi-Urban,ML Engineer,62679,1 +47830,Male,30,High School,16,57,46,66,4,0.0,3,29,Urban,HR Executive,120146,0 +47831,Other,47,Bachelors,14,89,48,85,46,3.0,7,22,Urban,ML Engineer,48380,1 +47832,Male,21,Masters,15,44,29,80,72,2.0,7,48,Semi-Urban,Data Analyst,123094,0 +47833,Male,51,Bachelors,1,88,80,1,12,0.0,7,87,Urban,Software Engineer,49989,1 +47834,Male,59,Diploma,1,44,68,6,57,8.0,6,4,Urban,ML Engineer,38790,0 +47835,Female,54,Masters,2,79,44,24,69,3.0,3,72,Semi-Urban,ML Engineer,30870,0 +47836,Other,30,Diploma,4,2,9,50,99,5.0,7,71,Rural,Manager,34195,0 +47837,Female,43,Bachelors,18,4,10,95,71,4.0,2,49,Rural,Software Engineer,38300,0 +47838,Male,51,Masters,3,56,29,75,3,7.0,4,0,Urban,ML Engineer,61333,0 +47839,Male,40,Bachelors,8,85,16,71,46,6.0,0,93,Semi-Urban,Data Analyst,109644,1 +47840,Male,26,Bachelors,2,39,77,4,92,4.0,7,39,Urban,ML Engineer,85368,0 +47841,Other,45,Bachelors,3,79,28,37,56,2.0,5,8,Urban,Manager,32118,0 +47842,Female,23,Masters,11,59,1,44,65,3.0,2,6,Semi-Urban,Data Analyst,20549,0 +47843,Female,34,Diploma,19,50,73,11,24,0.0,2,14,Rural,ML Engineer,92840,0 +47844,Female,38,Bachelors,15,59,39,65,2,4.0,0,83,Urban,Manager,20733,1 +47845,Female,49,Diploma,3,72,60,60,63,7.0,7,97,Urban,Data Analyst,102796,1 +47846,Male,31,Masters,2,66,4,26,22,7.0,3,70,Urban,Manager,140418,0 +47847,Male,37,Masters,2,9,96,90,49,7.0,1,68,Urban,Manager,126486,1 +47848,Female,34,PhD,15,51,55,40,80,4.0,2,26,Urban,HR Executive,137810,0 +47849,Male,30,Masters,13,55,32,32,76,4.0,0,66,Urban,ML Engineer,62669,0 +47850,Female,58,Bachelors,15,59,16,99,27,3.0,6,97,Urban,ML Engineer,111274,1 +47851,Female,39,Masters,3,35,93,23,66,6.0,4,94,Urban,ML Engineer,103229,1 +47852,Male,43,Bachelors,19,33,28,41,88,0.0,4,86,Rural,ML Engineer,62525,0 +47853,Male,29,Masters,12,59,43,48,75,5.0,3,24,Urban,ML Engineer,32608,0 +47854,Male,36,Bachelors,14,74,19,92,47,7.0,2,79,Urban,Software Engineer,36497,1 +47855,Female,58,Bachelors,13,62,45,37,76,1.0,4,46,Urban,Manager,65581,0 +47856,Male,50,Bachelors,1,22,34,0,86,0.0,5,75,Semi-Urban,Software Engineer,96890,0 +47857,Male,53,Diploma,15,85,12,13,51,8.0,5,69,Semi-Urban,Software Engineer,21183,0 +47858,Female,45,Bachelors,5,50,14,11,49,0.0,0,49,Rural,HR Executive,37329,0 +47859,Male,43,High School,4,67,27,51,95,0.0,2,67,Semi-Urban,Manager,27598,0 +47860,Male,45,Bachelors,19,85,3,56,87,0.0,5,19,Semi-Urban,ML Engineer,77531,0 +47861,Male,34,Bachelors,6,12,91,2,20,0.0,3,12,Rural,Data Analyst,80831,0 +47862,Male,49,High School,11,70,21,76,56,0.0,3,91,Semi-Urban,HR Executive,57056,1 +47863,Female,31,Bachelors,6,85,88,44,44,9.0,1,76,Rural,HR Executive,117031,1 +47864,Other,46,Masters,10,98,92,41,31,0.0,4,90,Urban,Manager,77709,1 +47865,Male,40,Diploma,8,5,56,9,57,2.0,2,52,Semi-Urban,Data Analyst,149618,0 +47866,Female,33,Masters,18,41,29,8,19,8.0,4,86,Urban,Software Engineer,74419,0 +47867,Male,41,Diploma,9,1,74,62,8,8.0,1,77,Rural,Manager,71462,0 +47868,Female,48,PhD,9,38,79,40,9,0.0,2,14,Semi-Urban,Manager,109594,0 +47869,Female,39,Diploma,10,81,30,76,70,8.0,1,6,Urban,ML Engineer,110263,0 +47870,Male,49,Masters,11,15,31,16,21,4.0,1,48,Semi-Urban,ML Engineer,83818,0 +47871,Male,43,Masters,10,4,18,94,91,0.0,3,22,Urban,Software Engineer,39045,0 +47872,Male,35,Bachelors,14,22,84,73,66,7.0,5,82,Semi-Urban,ML Engineer,28059,1 +47873,Female,51,Masters,15,46,97,5,21,1.0,4,11,Semi-Urban,ML Engineer,70704,0 +47874,Male,37,Bachelors,1,11,93,99,37,2.0,5,80,Urban,Data Analyst,100937,1 +47875,Male,46,High School,16,39,95,53,66,2.0,1,73,Urban,ML Engineer,59962,1 +47876,Male,28,Bachelors,12,45,15,61,55,1.0,7,72,Rural,Data Analyst,72332,0 +47877,Male,40,Bachelors,3,67,13,86,21,1.0,4,76,Urban,Software Engineer,50743,1 +47878,Female,26,High School,8,83,46,50,18,8.0,1,89,Semi-Urban,Software Engineer,134848,1 +47879,Female,46,Diploma,12,21,98,42,76,8.0,2,15,Urban,Manager,73339,0 +47880,Female,27,High School,5,7,79,33,63,2.0,6,49,Urban,Data Analyst,68279,0 +47881,Male,47,Bachelors,2,88,35,35,55,0.0,1,57,Urban,HR Executive,72038,0 +47882,Male,37,Bachelors,2,23,56,17,52,9.0,2,52,Semi-Urban,Manager,143556,0 +47883,Male,25,Bachelors,5,80,86,77,10,5.0,4,39,Urban,Software Engineer,84432,1 +47884,Female,49,Masters,1,72,58,64,56,2.0,4,82,Urban,ML Engineer,78964,1 +47885,Male,47,Bachelors,17,99,15,84,19,9.0,6,79,Urban,ML Engineer,32844,1 +47886,Other,36,Masters,4,44,47,99,20,0.0,5,82,Urban,ML Engineer,74984,1 +47887,Male,45,Bachelors,1,92,73,67,87,3.0,1,71,Urban,Data Analyst,116348,1 +47888,Other,32,Masters,19,55,71,72,2,7.0,3,26,Urban,Software Engineer,136628,0 +47889,Female,31,Bachelors,2,7,16,85,7,9.0,6,56,Urban,HR Executive,36103,0 +47890,Female,32,High School,19,66,17,19,72,5.0,2,76,Semi-Urban,HR Executive,131649,0 +47891,Male,43,Masters,10,34,5,4,81,8.0,6,14,Urban,Data Analyst,90901,0 +47892,Male,38,Diploma,17,18,89,11,23,6.0,0,35,Semi-Urban,Manager,63680,0 +47893,Female,50,Bachelors,13,81,86,76,64,2.0,7,92,Urban,Software Engineer,146583,1 +47894,Female,50,Bachelors,15,80,29,43,81,2.0,2,77,Rural,Manager,72843,0 +47895,Male,25,Diploma,2,65,73,1,31,1.0,5,48,Urban,Software Engineer,107507,0 +47896,Male,48,Bachelors,9,9,2,61,6,5.0,5,58,Urban,Software Engineer,119772,0 +47897,Female,25,Masters,14,23,89,42,25,0.0,4,71,Semi-Urban,HR Executive,91668,0 +47898,Female,25,High School,0,81,46,95,37,2.0,7,30,Urban,ML Engineer,115177,1 +47899,Male,39,Bachelors,2,1,63,93,7,8.0,0,97,Rural,Manager,115474,1 +47900,Male,22,Bachelors,3,41,74,99,48,4.0,7,26,Urban,ML Engineer,131902,1 +47901,Female,54,Bachelors,7,47,56,87,33,6.0,5,18,Rural,Software Engineer,54217,0 +47902,Female,24,Bachelors,14,17,70,97,39,3.0,7,36,Urban,HR Executive,28132,0 +47903,Male,43,High School,7,62,52,52,0,0.0,7,16,Urban,HR Executive,107350,0 +47904,Male,54,Bachelors,16,47,65,97,76,1.0,4,52,Semi-Urban,Data Analyst,30254,1 +47905,Female,38,Bachelors,5,73,77,24,41,0.0,5,32,Urban,HR Executive,38719,0 +47906,Male,32,High School,4,99,61,5,74,9.0,2,69,Rural,HR Executive,20355,0 +47907,Male,31,Diploma,15,59,50,63,59,6.0,7,55,Urban,Data Analyst,75915,0 +47908,Female,54,Diploma,9,63,19,23,67,5.0,2,34,Semi-Urban,Software Engineer,83541,0 +47909,Male,46,Diploma,1,63,49,82,61,9.0,1,79,Urban,Software Engineer,67898,1 +47910,Male,27,Diploma,6,94,95,56,64,9.0,2,4,Urban,Data Analyst,47609,1 +47911,Male,21,PhD,17,94,52,27,96,5.0,5,52,Urban,ML Engineer,24124,0 +47912,Female,50,Bachelors,1,19,36,18,77,0.0,2,14,Semi-Urban,ML Engineer,149452,0 +47913,Male,57,Masters,0,94,84,94,73,9.0,1,63,Urban,ML Engineer,134829,1 +47914,Male,39,Masters,12,54,95,22,62,2.0,4,79,Urban,Manager,68292,1 +47915,Male,50,Masters,1,62,32,54,54,5.0,2,51,Urban,HR Executive,141712,0 +47916,Male,58,Masters,14,95,42,43,1,1.0,6,60,Semi-Urban,HR Executive,109616,1 +47917,Female,33,Bachelors,4,53,66,38,2,4.0,1,36,Semi-Urban,HR Executive,68936,0 +47918,Other,43,Bachelors,13,28,0,68,57,9.0,2,89,Urban,Manager,148307,0 +47919,Female,46,Masters,5,78,50,30,7,2.0,1,95,Urban,Manager,76096,1 +47920,Male,42,High School,7,77,32,67,29,2.0,0,80,Semi-Urban,HR Executive,139806,1 +47921,Male,39,Bachelors,8,66,57,87,91,2.0,1,33,Semi-Urban,Manager,74471,1 +47922,Male,24,High School,4,0,85,55,44,9.0,0,14,Urban,Software Engineer,53569,0 +47923,Male,30,Bachelors,6,77,84,65,91,8.0,7,92,Urban,Data Analyst,81513,1 +47924,Male,41,Bachelors,0,47,69,55,17,3.0,3,73,Rural,Data Analyst,80826,1 +47925,Male,46,High School,0,82,76,33,90,9.0,7,6,Urban,Data Analyst,101671,0 +47926,Female,35,Masters,16,16,53,87,15,2.0,3,57,Rural,Manager,20616,0 +47927,Female,24,Diploma,16,18,91,85,38,6.0,3,96,Rural,Data Analyst,115113,1 +47928,Female,37,Diploma,2,20,63,40,5,0.0,3,43,Urban,Software Engineer,105396,0 +47929,Male,37,Masters,4,43,72,50,5,8.0,7,25,Urban,HR Executive,100264,0 +47930,Female,32,Bachelors,1,98,39,72,44,1.0,6,36,Urban,Software Engineer,90861,1 +47931,Male,22,High School,11,67,18,26,23,6.0,1,39,Urban,Data Analyst,75790,0 +47932,Male,22,Masters,0,15,16,12,26,4.0,4,93,Semi-Urban,Manager,32761,0 +47933,Male,58,Bachelors,6,53,22,75,42,9.0,4,83,Urban,Software Engineer,120843,0 +47934,Male,28,Masters,3,8,74,64,94,3.0,3,26,Urban,Manager,149655,0 +47935,Male,32,Diploma,10,25,23,35,77,5.0,4,77,Semi-Urban,ML Engineer,103667,0 +47936,Male,29,Bachelors,17,11,16,71,96,1.0,7,84,Semi-Urban,Manager,127440,0 +47937,Male,44,Diploma,15,2,8,4,84,1.0,5,42,Urban,Data Analyst,103697,0 +47938,Female,49,Bachelors,10,68,74,80,5,3.0,5,65,Semi-Urban,ML Engineer,53415,1 +47939,Male,27,Masters,16,96,7,9,67,4.0,6,46,Urban,Data Analyst,22646,0 +47940,Male,33,High School,18,20,80,95,83,3.0,6,65,Urban,Manager,22817,1 +47941,Male,57,High School,14,11,56,2,65,5.0,1,12,Urban,Manager,118727,0 +47942,Male,46,Diploma,9,66,48,87,60,4.0,0,90,Semi-Urban,Software Engineer,50582,1 +47943,Female,33,Bachelors,14,44,1,0,57,4.0,7,93,Semi-Urban,Manager,84585,0 +47944,Male,44,Bachelors,7,52,86,25,23,8.0,1,83,Urban,Data Analyst,64462,1 +47945,Male,34,Diploma,3,76,22,22,6,4.0,6,82,Urban,Data Analyst,115647,0 +47946,Female,25,High School,12,69,3,33,82,0.0,7,15,Rural,ML Engineer,142361,0 +47947,Female,26,High School,10,25,37,12,75,8.0,6,54,Urban,HR Executive,49312,0 +47948,Male,49,High School,8,42,92,87,72,3.0,7,88,Urban,HR Executive,109884,1 +47949,Male,28,Bachelors,7,81,25,2,55,9.0,7,42,Urban,HR Executive,31516,0 +47950,Other,56,Diploma,18,20,98,42,2,2.0,7,15,Semi-Urban,ML Engineer,66061,0 +47951,Female,57,Bachelors,14,79,92,45,50,3.0,2,94,Rural,HR Executive,57965,1 +47952,Other,58,Masters,2,28,22,98,51,7.0,2,95,Urban,HR Executive,104096,1 +47953,Female,44,High School,17,21,70,14,12,7.0,1,24,Urban,Manager,23855,0 +47954,Female,56,High School,5,76,96,31,98,3.0,1,38,Rural,HR Executive,72253,1 +47955,Male,36,High School,17,63,69,87,62,3.0,3,85,Urban,HR Executive,85892,1 +47956,Female,31,Bachelors,9,41,38,6,57,5.0,0,11,Urban,Software Engineer,147352,0 +47957,Female,23,Bachelors,0,3,88,51,8,3.0,1,68,Rural,ML Engineer,123775,0 +47958,Male,55,High School,18,70,86,43,60,6.0,2,71,Semi-Urban,HR Executive,29193,1 +47959,Female,52,High School,14,74,90,57,31,8.0,1,25,Urban,Software Engineer,105974,1 +47960,Female,56,Bachelors,14,61,83,94,19,1.0,4,91,Rural,Software Engineer,71776,1 +47961,Male,45,High School,8,26,73,51,96,1.0,5,25,Urban,HR Executive,67537,0 +47962,Male,22,Diploma,17,29,90,35,48,6.0,1,20,Semi-Urban,HR Executive,75836,0 +47963,Male,45,Masters,15,35,71,99,53,3.0,1,55,Urban,Software Engineer,147564,1 +47964,Female,56,Bachelors,13,65,31,41,83,1.0,2,60,Urban,ML Engineer,124678,0 +47965,Female,53,Diploma,10,36,35,75,10,1.0,3,74,Semi-Urban,ML Engineer,118632,0 +47966,Male,25,Masters,3,48,17,99,55,7.0,6,57,Rural,ML Engineer,136153,0 +47967,Male,53,Masters,13,96,62,30,4,8.0,3,19,Semi-Urban,ML Engineer,57207,0 +47968,Male,46,Diploma,0,49,78,3,8,9.0,1,97,Urban,ML Engineer,99909,0 +47969,Male,35,Masters,17,75,59,51,72,9.0,5,76,Urban,Manager,143166,1 +47970,Male,55,Masters,12,17,92,39,5,9.0,1,43,Urban,HR Executive,40119,0 +47971,Male,57,Bachelors,6,65,59,46,52,9.0,6,55,Semi-Urban,Software Engineer,94970,0 +47972,Male,49,Bachelors,1,8,47,94,78,8.0,2,64,Urban,Data Analyst,134831,0 +47973,Male,50,Bachelors,10,89,53,85,90,7.0,3,80,Rural,Data Analyst,79872,1 +47974,Female,49,Masters,0,20,0,26,33,3.0,3,59,Urban,HR Executive,131023,0 +47975,Other,53,High School,18,94,98,61,59,8.0,2,42,Urban,Manager,130803,1 +47976,Male,22,PhD,10,73,8,65,0,8.0,3,49,Urban,Manager,138417,0 +47977,Male,26,Diploma,17,47,34,76,76,4.0,3,57,Semi-Urban,ML Engineer,142020,0 +47978,Other,59,Diploma,7,43,41,29,12,4.0,3,8,Urban,Software Engineer,128901,0 +47979,Female,25,Bachelors,7,8,8,93,69,0.0,1,92,Semi-Urban,ML Engineer,101738,0 +47980,Male,31,Diploma,0,42,22,29,43,4.0,4,62,Urban,Data Analyst,149981,0 +47981,Male,27,Diploma,11,16,14,94,20,5.0,2,6,Rural,Manager,96450,0 +47982,Male,22,Masters,7,44,49,21,55,5.0,0,65,Rural,HR Executive,145052,0 +47983,Male,51,Bachelors,12,49,97,58,61,2.0,2,47,Urban,Data Analyst,143537,1 +47984,Male,45,Masters,6,41,41,22,4,6.0,7,70,Semi-Urban,Manager,46669,0 +47985,Male,37,PhD,8,40,54,25,83,5.0,2,8,Urban,Data Analyst,70193,0 +47986,Female,59,PhD,2,86,24,32,90,7.0,1,57,Urban,HR Executive,44586,0 +47987,Male,28,Bachelors,7,2,71,43,92,4.0,4,49,Urban,HR Executive,50831,0 +47988,Female,42,Bachelors,13,63,87,74,22,6.0,2,67,Semi-Urban,Data Analyst,107071,1 +47989,Male,39,Diploma,10,24,84,92,7,6.0,2,70,Urban,ML Engineer,136259,1 +47990,Male,21,Bachelors,3,95,69,29,62,7.0,0,26,Urban,Manager,36399,0 +47991,Female,41,High School,11,54,56,53,89,7.0,5,30,Semi-Urban,HR Executive,123054,0 +47992,Female,54,Diploma,4,98,14,73,57,8.0,2,11,Semi-Urban,ML Engineer,42956,0 +47993,Male,48,Bachelors,11,56,87,82,21,0.0,2,75,Semi-Urban,ML Engineer,72618,1 +47994,Male,55,Bachelors,9,31,73,99,28,8.0,0,85,Urban,Software Engineer,128370,1 +47995,Male,21,Diploma,17,63,54,44,64,7.0,5,42,Semi-Urban,HR Executive,141346,0 +47996,Male,58,Diploma,19,9,49,96,25,7.0,0,0,Urban,Software Engineer,35453,0 +47997,Male,37,High School,18,74,72,24,31,8.0,5,48,Urban,Software Engineer,20751,0 +47998,Male,50,Diploma,4,68,2,31,58,7.0,6,9,Semi-Urban,Manager,138570,0 +47999,Male,23,Masters,9,94,81,38,9,0.0,4,36,Urban,Software Engineer,76314,1 +48000,Male,49,High School,17,10,82,29,29,6.0,2,18,Rural,ML Engineer,95589,0 +48001,Female,40,Bachelors,17,35,97,28,84,7.0,2,41,Urban,Manager,28335,0 +48002,Male,46,Bachelors,4,14,78,36,82,7.0,3,2,Urban,ML Engineer,75921,0 +48003,Male,47,Diploma,9,1,70,64,0,7.0,0,41,Urban,Software Engineer,111659,0 +48004,Female,29,Masters,9,77,9,41,21,4.0,5,61,Urban,Software Engineer,34604,0 +48005,Female,36,Bachelors,1,69,21,70,77,9.0,3,34,Semi-Urban,HR Executive,77193,0 +48006,Male,30,Bachelors,15,13,4,13,87,0.0,7,78,Urban,HR Executive,38125,0 +48007,Male,52,High School,13,53,89,69,41,4.0,6,29,Urban,HR Executive,65463,1 +48008,Female,30,Bachelors,14,10,64,4,74,3.0,7,65,Semi-Urban,Manager,143256,0 +48009,Other,30,Bachelors,6,27,70,30,64,1.0,6,97,Urban,ML Engineer,89711,0 +48010,Male,27,Diploma,1,54,22,39,31,6.0,7,60,Urban,Manager,40957,0 +48011,Female,57,Diploma,15,46,95,13,85,4.0,0,5,Urban,Data Analyst,117217,0 +48012,Female,41,PhD,7,26,52,37,89,8.0,2,29,Urban,Software Engineer,30360,0 +48013,Male,38,High School,10,84,25,83,27,5.0,7,65,Urban,Data Analyst,81985,1 +48014,Male,24,Bachelors,10,46,43,40,21,6.0,2,49,Rural,Data Analyst,61201,0 +48015,Female,25,High School,5,61,51,99,42,1.0,0,78,Urban,Software Engineer,147340,1 +48016,Male,37,PhD,3,96,95,58,35,1.0,7,55,Urban,ML Engineer,115809,1 +48017,Male,48,High School,11,67,43,50,71,6.0,7,8,Rural,Data Analyst,128497,0 +48018,Male,49,Bachelors,12,43,76,45,98,8.0,2,85,Urban,ML Engineer,38632,1 +48019,Male,23,Masters,2,69,71,62,84,1.0,4,41,Rural,Software Engineer,86203,1 +48020,Male,52,Diploma,2,11,87,0,87,7.0,4,63,Urban,ML Engineer,92139,0 +48021,Female,34,High School,17,26,14,39,9,4.0,0,75,Rural,Manager,121720,0 +48022,Other,51,Bachelors,3,35,92,8,18,4.0,7,12,Urban,Software Engineer,149653,0 +48023,Male,52,Bachelors,2,84,15,93,21,8.0,1,28,Urban,Manager,116091,0 +48024,Male,39,High School,14,75,42,22,69,5.0,3,77,Urban,ML Engineer,30633,0 +48025,Female,36,Diploma,6,90,29,97,75,3.0,7,20,Semi-Urban,Data Analyst,116744,0 +48026,Male,59,PhD,3,16,85,44,26,6.0,1,80,Urban,Software Engineer,105800,0 +48027,Female,26,Diploma,11,74,18,23,22,7.0,5,38,Urban,Manager,71822,0 +48028,Female,50,Bachelors,14,82,26,29,73,1.0,5,4,Urban,Manager,28968,0 +48029,Female,36,Masters,3,33,20,99,69,8.0,0,76,Urban,HR Executive,147462,0 +48030,Male,23,High School,15,31,13,24,57,3.0,5,17,Urban,ML Engineer,51269,0 +48031,Male,58,Bachelors,17,88,29,30,28,9.0,7,63,Semi-Urban,Data Analyst,20079,0 +48032,Male,51,Bachelors,7,54,88,38,64,1.0,4,65,Semi-Urban,ML Engineer,94742,1 +48033,Male,55,Bachelors,6,64,20,96,15,5.0,1,82,Semi-Urban,ML Engineer,116381,1 +48034,Female,52,High School,16,43,66,28,6,0.0,1,54,Urban,Data Analyst,69458,0 +48035,Female,54,Diploma,15,14,31,61,45,6.0,2,83,Urban,Software Engineer,67558,0 +48036,Female,52,Diploma,11,0,2,44,23,1.0,4,53,Rural,Data Analyst,62337,0 +48037,Male,46,Bachelors,9,42,26,53,66,5.0,3,86,Urban,Software Engineer,52488,0 +48038,Female,29,High School,9,27,6,53,57,9.0,6,78,Urban,Manager,48137,0 +48039,Male,26,Diploma,19,16,43,78,50,3.0,3,85,Urban,Data Analyst,94678,0 +48040,Female,58,Bachelors,5,29,7,37,51,5.0,0,78,Rural,HR Executive,104044,0 +48041,Male,22,PhD,15,45,5,98,87,5.0,4,35,Rural,Manager,60798,0 +48042,Male,51,Masters,9,88,55,7,47,4.0,7,64,Semi-Urban,Software Engineer,38490,0 +48043,Female,59,Bachelors,5,50,4,82,38,4.0,2,29,Urban,Software Engineer,123534,0 +48044,Female,33,Diploma,1,14,86,13,26,3.0,4,83,Urban,Data Analyst,82520,0 +48045,Female,50,PhD,0,69,42,39,60,0.0,4,50,Rural,HR Executive,96303,0 +48046,Male,34,Diploma,6,95,35,33,36,7.0,6,10,Urban,ML Engineer,111036,0 +48047,Female,39,High School,17,78,80,87,44,3.0,4,95,Urban,Data Analyst,29458,1 +48048,Female,31,Masters,8,64,71,72,25,0.0,7,27,Rural,HR Executive,134374,0 +48049,Female,52,Diploma,13,54,1,97,90,2.0,4,65,Urban,HR Executive,76562,0 +48050,Male,26,Bachelors,12,7,55,49,69,0.0,3,17,Urban,Manager,43814,0 +48051,Female,49,Bachelors,8,18,71,78,47,6.0,0,71,Semi-Urban,Manager,98008,0 +48052,Male,22,Bachelors,18,6,93,96,75,4.0,7,93,Rural,HR Executive,148858,1 +48053,Male,57,High School,2,24,76,14,58,0.0,0,71,Urban,Software Engineer,123848,0 +48054,Male,57,Diploma,17,90,77,74,28,4.0,4,90,Urban,Manager,76728,1 +48055,Female,50,Masters,1,67,77,43,98,7.0,6,4,Urban,Data Analyst,24878,0 +48056,Male,45,Masters,11,3,88,19,75,9.0,3,77,Rural,Manager,128915,0 +48057,Male,32,Diploma,11,34,73,83,32,5.0,3,61,Semi-Urban,HR Executive,99681,1 +48058,Female,52,Masters,10,48,68,20,79,3.0,0,75,Urban,HR Executive,94450,0 +48059,Male,22,Diploma,14,32,4,59,20,7.0,1,0,Semi-Urban,HR Executive,106154,0 +48060,Male,44,Diploma,0,93,65,95,90,8.0,4,40,Urban,ML Engineer,54688,1 +48061,Female,37,High School,16,50,46,40,4,6.0,6,78,Urban,Data Analyst,96202,0 +48062,Male,28,High School,0,47,88,67,92,9.0,3,29,Semi-Urban,Software Engineer,140565,0 +48063,Male,23,Masters,14,13,46,38,98,8.0,2,29,Urban,ML Engineer,127068,0 +48064,Male,59,Diploma,4,85,24,44,23,9.0,4,50,Urban,Software Engineer,37823,0 +48065,Male,37,Diploma,15,21,5,34,5,2.0,2,89,Urban,Software Engineer,30261,0 +48066,Male,36,Diploma,9,41,37,9,42,5.0,4,70,Urban,Manager,90579,0 +48067,Female,53,Bachelors,17,93,49,2,52,4.0,3,26,Semi-Urban,Manager,74850,0 +48068,Female,24,Bachelors,13,53,74,77,94,9.0,1,58,Urban,ML Engineer,94479,1 +48069,Male,46,Bachelors,0,27,73,36,52,5.0,6,33,Urban,Software Engineer,49541,0 +48070,Male,26,Diploma,0,40,58,89,32,8.0,5,52,Rural,Software Engineer,73442,1 +48071,Male,33,High School,14,47,55,30,13,6.0,1,25,Semi-Urban,Data Analyst,99552,0 +48072,Male,39,High School,9,7,60,65,78,8.0,7,16,Semi-Urban,HR Executive,113565,0 +48073,Female,42,Bachelors,7,81,67,42,63,7.0,4,9,Urban,Data Analyst,58460,0 +48074,Male,40,Bachelors,8,83,40,90,3,3.0,6,90,Urban,ML Engineer,59009,1 +48075,Female,50,Masters,19,98,1,35,98,0.0,0,15,Urban,Manager,102397,0 +48076,Female,47,Masters,1,91,24,94,47,4.0,7,3,Semi-Urban,Data Analyst,43440,0 +48077,Female,44,Bachelors,19,99,9,99,4,8.0,2,64,Rural,Data Analyst,20923,1 +48078,Male,53,Bachelors,13,32,19,44,62,9.0,2,88,Semi-Urban,Data Analyst,116727,0 +48079,Male,31,High School,4,74,43,16,57,9.0,7,32,Urban,ML Engineer,31140,0 +48080,Male,21,Masters,10,37,93,60,88,2.0,6,39,Urban,ML Engineer,27583,0 +48081,Female,25,High School,14,30,68,90,10,8.0,1,20,Rural,ML Engineer,23341,0 +48082,Male,25,Masters,4,58,71,36,28,7.0,7,82,Urban,Data Analyst,95444,1 +48083,Male,36,Bachelors,18,85,16,94,1,7.0,3,83,Urban,Manager,124171,1 +48084,Female,37,PhD,3,20,75,62,1,2.0,2,68,Semi-Urban,Manager,63923,0 +48085,Male,54,Diploma,13,5,85,39,92,1.0,6,7,Urban,Data Analyst,143341,0 +48086,Male,26,High School,0,76,22,62,83,8.0,2,68,Urban,Data Analyst,111794,0 +48087,Male,36,Bachelors,3,88,94,2,58,6.0,6,9,Urban,Software Engineer,72264,0 +48088,Male,46,Diploma,15,78,2,86,50,8.0,1,2,Semi-Urban,Data Analyst,141229,0 +48089,Other,50,Bachelors,1,82,16,40,87,0.0,4,87,Urban,Software Engineer,55011,0 +48090,Male,28,Bachelors,1,56,85,30,55,3.0,6,31,Urban,Software Engineer,120778,0 +48091,Male,39,Diploma,2,25,22,12,81,2.0,0,42,Urban,Software Engineer,79276,0 +48092,Female,24,Bachelors,11,88,73,4,17,3.0,0,64,Urban,Data Analyst,120008,0 +48093,Male,33,High School,9,44,49,2,42,1.0,4,85,Urban,Data Analyst,58381,0 +48094,Male,30,Diploma,4,59,89,98,45,2.0,4,99,Urban,Data Analyst,130057,1 +48095,Male,37,Bachelors,17,54,39,43,47,1.0,0,77,Urban,ML Engineer,30828,0 +48096,Female,48,Bachelors,7,59,6,79,84,1.0,1,15,Urban,Manager,101188,0 +48097,Female,54,Masters,13,75,95,37,29,2.0,3,86,Semi-Urban,Software Engineer,135659,1 +48098,Male,41,Bachelors,13,75,87,30,39,9.0,1,63,Semi-Urban,HR Executive,83298,1 +48099,Male,58,Bachelors,4,5,22,98,34,2.0,0,29,Urban,HR Executive,97620,0 +48100,Female,31,Bachelors,19,39,81,92,86,8.0,2,2,Urban,ML Engineer,89592,0 +48101,Male,39,Bachelors,5,56,32,68,62,9.0,6,4,Rural,ML Engineer,121715,0 +48102,Male,43,PhD,11,99,32,8,48,2.0,3,1,Urban,ML Engineer,102421,0 +48103,Female,48,Diploma,3,37,30,65,81,7.0,1,95,Urban,Software Engineer,143563,0 +48104,Female,39,Diploma,14,43,78,16,64,7.0,0,45,Urban,Data Analyst,44207,0 +48105,Female,55,Bachelors,11,6,11,14,58,6.0,0,84,Urban,Data Analyst,144233,0 +48106,Female,47,High School,17,97,0,0,20,7.0,5,65,Rural,ML Engineer,44569,0 +48107,Female,47,Bachelors,15,99,75,46,57,6.0,3,6,Urban,Manager,136561,0 +48108,Female,40,Bachelors,6,63,65,47,67,3.0,3,27,Rural,HR Executive,31899,0 +48109,Male,41,High School,5,64,69,15,46,2.0,6,2,Urban,Software Engineer,81863,0 +48110,Male,32,Masters,4,87,62,16,60,9.0,1,52,Urban,Data Analyst,114016,0 +48111,Female,44,Diploma,15,72,91,52,33,7.0,3,49,Rural,Manager,141687,1 +48112,Male,32,Bachelors,19,87,94,41,3,8.0,1,49,Rural,Software Engineer,77310,1 +48113,Female,43,Bachelors,10,98,32,25,12,0.0,4,76,Urban,HR Executive,107819,0 +48114,Female,59,Bachelors,16,66,48,92,54,5.0,7,0,Semi-Urban,ML Engineer,55663,0 +48115,Male,29,High School,14,76,89,79,19,7.0,1,97,Urban,Software Engineer,142328,1 +48116,Male,31,High School,2,77,58,72,71,3.0,5,23,Rural,Data Analyst,138148,0 +48117,Male,45,High School,18,57,30,5,52,2.0,3,73,Semi-Urban,ML Engineer,136289,0 +48118,Male,43,Masters,13,90,72,88,41,2.0,4,96,Urban,ML Engineer,66160,1 +48119,Female,37,Bachelors,6,48,41,11,4,3.0,2,71,Semi-Urban,HR Executive,136082,0 +48120,Male,34,Masters,3,97,62,37,71,0.0,4,42,Urban,Software Engineer,84605,1 +48121,Female,54,Bachelors,8,74,58,29,11,1.0,1,44,Semi-Urban,Data Analyst,117176,0 +48122,Male,22,Masters,2,70,76,72,43,8.0,1,64,Urban,ML Engineer,42399,1 +48123,Female,34,Bachelors,10,63,82,27,80,4.0,4,67,Semi-Urban,ML Engineer,100446,0 +48124,Male,41,High School,0,87,76,54,96,8.0,5,63,Urban,HR Executive,34251,1 +48125,Male,34,PhD,3,5,36,44,57,9.0,5,49,Rural,ML Engineer,36158,0 +48126,Male,24,Masters,0,63,19,16,20,9.0,3,51,Semi-Urban,Manager,131825,0 +48127,Male,23,Masters,3,94,57,43,79,3.0,2,37,Urban,Manager,109385,0 +48128,Female,44,Bachelors,19,71,62,90,37,2.0,6,89,Semi-Urban,HR Executive,22413,1 +48129,Female,58,Masters,12,70,28,35,61,5.0,0,42,Semi-Urban,Data Analyst,139129,0 +48130,Male,48,Bachelors,13,83,40,33,4,1.0,4,39,Urban,Manager,142635,0 +48131,Male,42,Masters,0,77,24,36,19,2.0,0,89,Semi-Urban,HR Executive,121842,0 +48132,Female,29,Bachelors,13,63,53,17,51,9.0,1,67,Urban,ML Engineer,121931,0 +48133,Female,26,Masters,2,20,64,43,50,9.0,0,73,Urban,ML Engineer,70871,0 +48134,Male,42,Masters,5,93,7,36,90,8.0,2,80,Rural,Data Analyst,57276,0 +48135,Male,49,Masters,1,39,91,14,58,4.0,1,95,Urban,Data Analyst,72521,1 +48136,Male,32,High School,4,78,47,24,13,9.0,1,58,Urban,Data Analyst,29690,0 +48137,Male,46,Diploma,7,26,55,25,11,1.0,0,28,Rural,HR Executive,71148,0 +48138,Male,33,PhD,18,5,80,79,83,8.0,7,31,Semi-Urban,Manager,38162,0 +48139,Male,45,Bachelors,11,80,8,22,31,0.0,4,27,Semi-Urban,ML Engineer,136385,0 +48140,Male,30,Bachelors,18,86,52,66,64,4.0,5,88,Urban,ML Engineer,127575,1 +48141,Male,51,Bachelors,8,76,37,45,22,4.0,6,63,Rural,Software Engineer,83035,0 +48142,Male,30,Diploma,15,48,39,82,71,5.0,5,31,Rural,HR Executive,136486,0 +48143,Male,49,High School,6,95,29,35,42,3.0,5,71,Semi-Urban,HR Executive,107484,0 +48144,Male,45,High School,12,74,47,58,79,7.0,7,35,Urban,Software Engineer,63229,0 +48145,Male,27,PhD,4,84,88,45,88,3.0,7,22,Rural,HR Executive,23841,1 +48146,Male,50,Masters,16,26,30,79,31,9.0,6,45,Urban,HR Executive,53058,0 +48147,Male,37,Masters,6,54,8,59,39,5.0,2,15,Urban,Manager,77157,0 +48148,Female,26,High School,12,88,27,60,88,9.0,3,9,Semi-Urban,ML Engineer,101532,0 +48149,Male,37,Masters,4,25,95,57,85,7.0,2,14,Semi-Urban,Data Analyst,137060,0 +48150,Female,48,Bachelors,4,5,48,95,37,2.0,0,9,Urban,Manager,146838,0 +48151,Male,23,Diploma,7,8,32,15,64,6.0,1,99,Urban,Data Analyst,94581,0 +48152,Male,22,Bachelors,19,22,21,5,80,1.0,5,46,Urban,Manager,126849,0 +48153,Female,59,Diploma,10,27,73,44,76,4.0,0,19,Urban,Manager,31465,0 +48154,Male,46,Bachelors,11,85,91,8,56,2.0,1,64,Urban,HR Executive,148418,1 +48155,Male,41,Bachelors,6,7,22,76,30,9.0,6,84,Urban,Manager,38689,0 +48156,Male,54,Bachelors,11,74,12,51,34,1.0,2,65,Urban,ML Engineer,132511,0 +48157,Male,48,Diploma,11,10,21,20,84,1.0,4,97,Semi-Urban,HR Executive,37094,0 +48158,Male,34,High School,15,41,77,2,9,4.0,7,2,Semi-Urban,Data Analyst,76186,0 +48159,Female,43,Diploma,16,66,31,56,19,2.0,4,25,Urban,Software Engineer,116049,0 +48160,Male,39,High School,6,2,4,3,70,1.0,0,59,Rural,Data Analyst,61842,0 +48161,Other,48,Bachelors,6,25,68,67,6,7.0,7,6,Urban,Data Analyst,28522,0 +48162,Male,54,Diploma,1,71,67,12,14,2.0,7,0,Rural,Manager,44011,0 +48163,Male,54,Masters,12,35,81,33,50,0.0,5,68,Urban,HR Executive,58833,0 +48164,Female,57,Masters,7,79,26,85,43,2.0,1,19,Urban,HR Executive,55869,0 +48165,Male,51,High School,8,85,35,12,65,8.0,5,81,Rural,Software Engineer,62174,0 +48166,Other,53,Bachelors,2,33,55,51,28,9.0,5,89,Urban,Manager,122802,0 +48167,Male,44,Diploma,2,95,3,9,74,7.0,4,93,Semi-Urban,Software Engineer,75912,0 +48168,Male,51,Diploma,3,99,12,46,76,0.0,7,2,Semi-Urban,Manager,90980,0 +48169,Male,46,Bachelors,0,57,77,13,30,1.0,3,33,Semi-Urban,Software Engineer,78742,0 +48170,Male,46,Bachelors,13,85,17,51,84,0.0,0,99,Urban,Manager,92936,1 +48171,Male,26,Bachelors,4,64,84,12,59,0.0,5,62,Urban,Manager,41988,0 +48172,Male,25,Masters,1,62,99,65,46,7.0,0,3,Semi-Urban,Data Analyst,42458,0 +48173,Male,54,Bachelors,3,82,70,55,58,5.0,1,91,Rural,Data Analyst,112218,1 +48174,Male,59,Bachelors,15,70,75,46,20,5.0,0,71,Rural,Data Analyst,65546,1 +48175,Male,52,Diploma,8,18,2,52,30,5.0,6,83,Urban,ML Engineer,60334,0 +48176,Female,25,Masters,13,71,83,94,27,6.0,0,82,Urban,ML Engineer,41301,1 +48177,Male,30,PhD,10,89,41,29,88,0.0,5,73,Urban,Manager,36291,0 +48178,Female,46,Masters,13,79,16,26,28,8.0,7,83,Semi-Urban,HR Executive,88479,0 +48179,Male,21,Bachelors,19,13,15,35,4,3.0,1,47,Rural,Manager,105680,0 +48180,Male,41,Bachelors,13,27,59,67,74,9.0,2,50,Urban,HR Executive,57110,0 +48181,Male,47,Diploma,10,12,6,58,50,8.0,7,20,Urban,ML Engineer,52028,0 +48182,Female,52,High School,2,50,87,65,95,6.0,6,10,Rural,ML Engineer,87394,0 +48183,Female,40,High School,5,52,4,47,31,5.0,6,83,Rural,Software Engineer,33252,0 +48184,Male,38,Masters,4,31,86,60,44,9.0,0,28,Urban,Software Engineer,146561,0 +48185,Male,34,Masters,3,38,3,76,55,4.0,3,4,Semi-Urban,Manager,128730,0 +48186,Male,49,Masters,2,20,99,86,49,0.0,6,9,Urban,Manager,26664,0 +48187,Female,31,Bachelors,9,19,95,34,62,9.0,0,83,Semi-Urban,HR Executive,25126,0 +48188,Male,26,Masters,11,99,85,81,13,0.0,6,84,Urban,Manager,134973,1 +48189,Female,51,Bachelors,2,28,76,14,81,2.0,6,62,Urban,ML Engineer,59671,0 +48190,Female,52,High School,9,37,5,71,35,0.0,2,53,Rural,HR Executive,145279,0 +48191,Female,56,Masters,5,87,99,26,11,4.0,1,51,Semi-Urban,Data Analyst,49253,1 +48192,Male,21,Bachelors,15,36,5,37,62,2.0,0,38,Rural,HR Executive,136350,0 +48193,Female,56,Bachelors,14,86,93,57,68,0.0,4,96,Semi-Urban,Software Engineer,142964,1 +48194,Male,57,Bachelors,8,63,98,48,67,8.0,2,49,Urban,Data Analyst,24150,1 +48195,Male,24,Masters,3,81,1,64,82,9.0,6,23,Urban,Manager,115768,0 +48196,Male,29,Diploma,13,16,5,19,69,3.0,2,99,Urban,HR Executive,75577,0 +48197,Female,47,Bachelors,12,39,68,95,69,7.0,5,55,Urban,Software Engineer,42382,1 +48198,Male,51,Diploma,9,75,65,75,43,2.0,6,83,Urban,ML Engineer,110878,1 +48199,Female,35,Bachelors,0,44,77,50,82,9.0,2,42,Urban,Data Analyst,112198,0 +48200,Female,50,Bachelors,0,83,3,11,85,2.0,1,53,Urban,Data Analyst,34502,0 +48201,Female,28,Diploma,6,97,11,64,10,4.0,7,32,Rural,Software Engineer,115377,0 +48202,Male,32,Masters,17,6,93,57,73,5.0,3,81,Semi-Urban,HR Executive,124939,1 +48203,Female,44,PhD,5,28,49,72,46,7.0,0,86,Rural,Software Engineer,36397,0 +48204,Male,50,Bachelors,9,50,56,51,69,5.0,2,85,Rural,ML Engineer,63970,1 +48205,Female,39,Bachelors,14,69,26,92,51,7.0,6,55,Rural,HR Executive,50088,1 +48206,Male,43,Bachelors,1,14,10,27,38,8.0,6,1,Urban,Manager,116533,0 +48207,Female,35,Masters,0,19,53,75,34,8.0,7,55,Semi-Urban,Data Analyst,132628,0 +48208,Male,35,Bachelors,9,4,72,93,79,4.0,0,84,Urban,Manager,47205,1 +48209,Female,22,PhD,9,74,57,5,80,4.0,3,85,Semi-Urban,Manager,123731,0 +48210,Male,50,PhD,7,94,15,58,35,7.0,7,62,Semi-Urban,HR Executive,78456,0 +48211,Female,53,Masters,16,67,90,96,72,1.0,7,4,Urban,Data Analyst,44344,1 +48212,Male,46,Bachelors,9,70,69,3,91,6.0,3,37,Semi-Urban,Data Analyst,134004,0 +48213,Female,29,Diploma,14,31,87,93,77,5.0,7,69,Urban,Data Analyst,68420,1 +48214,Male,23,High School,8,10,1,44,98,3.0,6,34,Rural,HR Executive,99425,0 +48215,Female,22,Diploma,12,38,17,75,89,2.0,3,65,Rural,HR Executive,103314,0 +48216,Male,32,Bachelors,12,63,1,95,4,1.0,1,25,Rural,Software Engineer,117646,0 +48217,Male,45,Diploma,16,59,92,24,13,7.0,0,89,Semi-Urban,Data Analyst,149380,1 +48218,Female,27,Bachelors,16,70,88,10,67,5.0,0,23,Rural,ML Engineer,53693,0 +48219,Female,42,Masters,9,40,99,20,16,4.0,6,80,Rural,HR Executive,35948,0 +48220,Female,33,Diploma,19,9,50,74,60,2.0,3,63,Urban,Manager,148910,0 +48221,Female,35,Diploma,15,67,52,83,19,6.0,0,54,Rural,Manager,28385,1 +48222,Male,23,Masters,12,87,50,74,76,5.0,1,66,Urban,ML Engineer,59446,1 +48223,Male,50,Diploma,2,19,69,72,84,1.0,5,98,Semi-Urban,HR Executive,118686,1 +48224,Male,50,Bachelors,9,70,94,46,5,8.0,4,27,Semi-Urban,Software Engineer,33556,1 +48225,Male,54,Diploma,8,23,45,33,79,1.0,6,51,Urban,Data Analyst,118601,0 +48226,Male,46,High School,8,44,88,0,38,2.0,5,91,Rural,Manager,82945,0 +48227,Female,24,Diploma,16,99,65,79,0,0.0,4,19,Rural,Manager,140136,1 +48228,Male,48,High School,14,39,56,90,40,6.0,0,70,Semi-Urban,Manager,21377,1 +48229,Male,21,Diploma,19,26,8,11,76,0.0,3,99,Rural,HR Executive,129251,0 +48230,Male,35,Bachelors,17,33,17,47,49,0.0,3,3,Urban,Manager,136557,0 +48231,Male,21,Bachelors,4,87,13,85,49,8.0,3,91,Semi-Urban,ML Engineer,126887,1 +48232,Male,27,Bachelors,5,35,14,87,94,1.0,2,91,Rural,Software Engineer,55998,0 +48233,Male,26,High School,4,71,69,68,30,7.0,4,74,Urban,ML Engineer,97993,1 +48234,Other,50,Bachelors,6,42,96,4,37,0.0,5,82,Urban,HR Executive,46567,0 +48235,Male,40,Bachelors,15,96,87,45,9,5.0,4,98,Urban,Manager,139879,1 +48236,Female,33,High School,13,47,36,5,53,0.0,6,64,Semi-Urban,Data Analyst,109139,0 +48237,Male,53,Bachelors,5,79,84,10,59,0.0,5,60,Urban,Software Engineer,117563,0 +48238,Male,34,Bachelors,13,5,4,5,25,1.0,1,89,Urban,Data Analyst,22631,0 +48239,Male,30,Diploma,6,23,87,32,43,6.0,4,78,Urban,ML Engineer,137539,0 +48240,Female,50,Bachelors,18,65,26,73,6,8.0,3,71,Urban,Manager,119291,0 +48241,Other,22,Masters,1,16,28,10,43,1.0,3,75,Urban,ML Engineer,50715,0 +48242,Male,22,Bachelors,11,63,89,50,1,9.0,1,32,Urban,Software Engineer,142266,0 +48243,Male,45,Bachelors,11,96,91,18,85,7.0,6,32,Rural,Manager,72076,1 +48244,Male,21,Bachelors,1,87,21,83,11,9.0,7,54,Urban,HR Executive,68236,1 +48245,Male,50,Diploma,9,92,11,47,93,3.0,4,66,Urban,Software Engineer,44171,0 +48246,Female,43,PhD,2,47,9,21,61,0.0,3,10,Urban,Software Engineer,33370,0 +48247,Male,50,High School,19,86,21,96,65,2.0,0,9,Urban,Data Analyst,53209,0 +48248,Male,34,Diploma,5,75,6,54,43,2.0,4,45,Urban,Software Engineer,120055,0 +48249,Female,32,High School,19,81,76,45,67,9.0,6,86,Semi-Urban,ML Engineer,68662,1 +48250,Male,49,Bachelors,6,31,15,11,74,7.0,7,60,Urban,ML Engineer,78945,0 +48251,Female,53,Diploma,8,0,69,92,85,7.0,2,19,Semi-Urban,HR Executive,126086,0 +48252,Female,44,High School,10,29,19,28,14,6.0,0,24,Urban,Software Engineer,125892,0 +48253,Male,33,Bachelors,2,84,33,35,76,0.0,4,58,Rural,HR Executive,22351,0 +48254,Male,26,Masters,16,58,43,99,9,8.0,1,42,Urban,Manager,43579,1 +48255,Male,44,Masters,3,38,72,86,80,0.0,0,57,Urban,Data Analyst,148151,1 +48256,Other,32,Bachelors,4,39,44,5,97,1.0,4,75,Urban,ML Engineer,132369,0 +48257,Female,35,High School,10,41,78,52,14,2.0,1,31,Urban,HR Executive,26311,0 +48258,Male,44,High School,2,12,50,2,87,6.0,1,35,Semi-Urban,Software Engineer,127926,0 +48259,Female,49,Masters,13,55,26,42,2,8.0,7,60,Rural,Manager,100458,0 +48260,Female,21,Diploma,17,79,3,66,76,0.0,2,49,Urban,HR Executive,143534,0 +48261,Male,54,Bachelors,17,96,92,54,96,5.0,7,56,Urban,Manager,37600,1 +48262,Male,39,Bachelors,19,98,61,94,47,2.0,5,58,Urban,HR Executive,147121,1 +48263,Female,35,High School,3,35,1,49,57,7.0,1,85,Rural,HR Executive,35154,0 +48264,Male,54,Masters,11,37,67,36,11,7.0,5,10,Urban,ML Engineer,136412,0 +48265,Female,35,Bachelors,4,99,32,76,35,4.0,2,65,Urban,Software Engineer,138459,1 +48266,Female,38,High School,1,51,57,3,95,1.0,3,23,Urban,Software Engineer,25593,0 +48267,Male,45,Masters,8,32,98,75,51,4.0,7,25,Urban,Manager,41096,0 +48268,Female,37,PhD,11,19,21,8,2,9.0,6,66,Rural,Software Engineer,77419,0 +48269,Male,39,Bachelors,15,77,89,34,23,5.0,2,46,Urban,Software Engineer,103812,1 +48270,Female,56,Bachelors,4,45,46,17,65,0.0,0,77,Semi-Urban,Data Analyst,93517,0 +48271,Male,48,Masters,0,99,46,44,22,8.0,4,64,Rural,Software Engineer,103278,1 +48272,Female,44,Bachelors,0,44,48,74,71,1.0,2,0,Urban,Manager,139101,0 +48273,Female,26,Masters,0,70,93,56,96,1.0,0,33,Urban,Data Analyst,144751,1 +48274,Male,33,Bachelors,4,25,55,43,16,0.0,0,2,Urban,Software Engineer,71289,0 +48275,Male,22,High School,9,71,94,16,18,4.0,2,10,Rural,Manager,114112,0 +48276,Male,26,High School,14,29,70,56,43,9.0,0,97,Urban,Manager,82433,1 +48277,Male,46,High School,11,83,47,77,38,6.0,7,51,Semi-Urban,Software Engineer,145368,1 +48278,Male,40,High School,18,63,84,74,98,1.0,2,84,Semi-Urban,ML Engineer,92933,1 +48279,Other,46,Bachelors,5,46,27,50,91,2.0,4,66,Urban,Data Analyst,129583,0 +48280,Female,31,Diploma,14,2,27,92,92,6.0,2,94,Urban,Data Analyst,109552,0 +48281,Male,30,Masters,18,24,63,52,92,0.0,2,83,Rural,Data Analyst,137002,0 +48282,Female,34,Bachelors,2,4,34,93,58,2.0,6,68,Rural,Data Analyst,131649,0 +48283,Male,47,High School,5,87,32,86,93,8.0,1,28,Urban,ML Engineer,72842,0 +48284,Female,48,Bachelors,17,28,98,18,10,9.0,7,50,Semi-Urban,Manager,89200,0 +48285,Male,41,High School,3,64,71,65,13,7.0,6,53,Semi-Urban,Manager,80113,1 +48286,Male,35,Bachelors,17,90,12,30,12,3.0,5,10,Urban,Manager,31158,0 +48287,Male,47,Masters,4,58,65,90,31,2.0,6,71,Rural,Manager,113759,1 +48288,Other,28,Bachelors,5,73,76,84,28,5.0,5,99,Semi-Urban,Software Engineer,56634,1 +48289,Male,21,Masters,2,15,54,38,67,2.0,6,98,Semi-Urban,ML Engineer,42180,0 +48290,Male,43,Bachelors,13,57,57,98,14,6.0,0,26,Rural,ML Engineer,61804,1 +48291,Male,41,Masters,2,9,81,75,72,2.0,0,16,Urban,ML Engineer,143817,0 +48292,Male,57,Masters,17,38,35,44,48,1.0,3,6,Urban,Manager,38578,0 +48293,Male,53,Bachelors,4,43,30,27,17,4.0,7,63,Urban,ML Engineer,85393,0 +48294,Female,36,Masters,3,38,38,8,16,7.0,7,65,Urban,Manager,132864,0 +48295,Male,58,Bachelors,10,65,91,76,51,1.0,1,86,Rural,ML Engineer,55050,1 +48296,Male,59,Diploma,15,32,98,24,7,0.0,1,97,Urban,Data Analyst,114135,1 +48297,Male,43,Masters,14,97,30,51,50,7.0,5,69,Urban,HR Executive,23420,1 +48298,Male,56,Bachelors,5,51,84,40,64,8.0,2,55,Rural,Manager,84082,0 +48299,Male,55,PhD,14,1,23,43,74,9.0,5,10,Semi-Urban,HR Executive,51736,0 +48300,Male,29,Bachelors,5,65,65,9,91,1.0,3,23,Urban,Manager,139874,0 +48301,Male,33,Masters,8,98,24,58,32,2.0,3,67,Semi-Urban,ML Engineer,126458,1 +48302,Male,51,Diploma,9,42,19,74,80,9.0,0,2,Urban,HR Executive,81777,0 +48303,Male,59,Diploma,13,70,80,97,24,9.0,4,40,Urban,Manager,89114,1 +48304,Male,59,Bachelors,2,40,52,74,55,8.0,5,59,Urban,Manager,34827,0 +48305,Male,33,Bachelors,11,4,14,84,71,7.0,5,53,Urban,Manager,102316,0 +48306,Female,57,Bachelors,10,98,22,30,3,2.0,5,28,Urban,Data Analyst,89149,0 +48307,Female,45,Bachelors,8,64,33,89,69,8.0,6,13,Rural,ML Engineer,121085,0 +48308,Male,29,Diploma,14,52,34,95,26,4.0,5,45,Urban,ML Engineer,103826,0 +48309,Male,41,Bachelors,16,32,22,85,18,9.0,2,5,Urban,ML Engineer,88611,0 +48310,Male,55,High School,2,13,88,75,86,4.0,0,12,Urban,ML Engineer,88545,0 +48311,Other,44,Diploma,7,15,86,59,91,7.0,2,68,Semi-Urban,ML Engineer,33650,0 +48312,Male,31,Masters,2,38,38,58,40,0.0,3,71,Rural,Manager,127899,0 +48313,Male,45,High School,12,90,94,73,44,2.0,5,81,Rural,HR Executive,69767,1 +48314,Male,49,Diploma,15,78,79,53,72,0.0,6,16,Urban,Manager,104129,0 +48315,Male,28,Bachelors,15,12,33,71,70,8.0,7,72,Rural,ML Engineer,122042,0 +48316,Male,40,Bachelors,18,24,70,81,98,2.0,4,41,Rural,Data Analyst,99123,0 +48317,Female,50,Bachelors,5,21,77,1,73,2.0,1,26,Rural,HR Executive,83837,0 +48318,Male,39,Bachelors,8,60,63,22,79,6.0,5,28,Urban,HR Executive,62457,0 +48319,Male,26,Diploma,7,0,8,12,93,2.0,5,42,Urban,Data Analyst,103901,0 +48320,Other,54,High School,5,1,73,68,72,5.0,7,18,Rural,Software Engineer,106851,0 +48321,Male,59,Bachelors,2,72,29,94,59,9.0,1,13,Semi-Urban,ML Engineer,35471,0 +48322,Male,49,Bachelors,2,65,34,95,7,2.0,0,5,Urban,Manager,66685,0 +48323,Male,43,Masters,16,93,96,27,88,6.0,6,46,Semi-Urban,Software Engineer,57981,1 +48324,Male,54,Masters,18,46,11,73,58,4.0,0,60,Rural,Manager,109180,0 +48325,Female,25,High School,13,8,92,38,44,8.0,2,62,Urban,Software Engineer,20890,0 +48326,Male,41,High School,15,0,27,71,71,2.0,1,90,Urban,Software Engineer,64221,0 +48327,Female,58,Bachelors,6,98,26,89,69,6.0,0,74,Urban,ML Engineer,134466,1 +48328,Female,55,Bachelors,9,24,72,18,12,2.0,5,0,Rural,ML Engineer,143749,0 +48329,Male,52,Masters,9,38,57,22,89,0.0,3,28,Rural,Data Analyst,130618,0 +48330,Male,56,High School,2,94,33,38,52,4.0,7,31,Semi-Urban,Software Engineer,114018,0 +48331,Male,29,Bachelors,5,45,29,36,15,4.0,6,42,Urban,Data Analyst,81022,0 +48332,Female,53,Bachelors,17,94,73,1,72,6.0,1,32,Semi-Urban,Software Engineer,130575,0 +48333,Male,46,Masters,18,19,87,85,54,8.0,1,5,Semi-Urban,Software Engineer,48341,0 +48334,Male,33,Diploma,13,62,90,96,19,4.0,3,31,Urban,Data Analyst,69155,1 +48335,Female,36,Diploma,18,14,34,42,48,1.0,6,38,Urban,HR Executive,121664,0 +48336,Male,31,Diploma,16,13,69,35,99,0.0,0,29,Semi-Urban,Data Analyst,24951,0 +48337,Male,31,Masters,6,35,64,50,10,4.0,4,46,Urban,Manager,139667,0 +48338,Male,49,Bachelors,8,8,6,84,54,4.0,4,58,Rural,ML Engineer,47066,0 +48339,Male,44,Diploma,6,90,78,82,51,4.0,3,95,Urban,HR Executive,24290,1 +48340,Male,23,High School,15,13,91,42,6,3.0,6,50,Semi-Urban,Manager,74115,0 +48341,Female,51,Bachelors,16,90,49,22,15,6.0,1,71,Urban,ML Engineer,27713,0 +48342,Male,48,Bachelors,19,56,5,34,87,8.0,7,77,Urban,HR Executive,61527,0 +48343,Male,21,Masters,7,98,95,92,50,4.0,5,97,Urban,Data Analyst,37387,1 +48344,Male,56,Bachelors,4,65,66,43,81,0.0,4,45,Rural,Data Analyst,138527,0 +48345,Female,49,Bachelors,5,96,48,80,79,2.0,4,59,Urban,Manager,119506,1 +48346,Female,56,Diploma,10,94,6,29,20,9.0,6,15,Rural,ML Engineer,87090,0 +48347,Male,31,Bachelors,6,41,20,21,89,2.0,1,35,Urban,HR Executive,61953,0 +48348,Male,32,High School,4,94,69,92,15,0.0,0,89,Semi-Urban,ML Engineer,36915,1 +48349,Female,35,Masters,13,88,8,56,38,0.0,0,38,Rural,Data Analyst,132576,0 +48350,Male,35,Bachelors,10,2,27,63,77,9.0,1,26,Urban,Data Analyst,132515,0 +48351,Male,48,High School,11,83,2,85,58,5.0,0,14,Semi-Urban,HR Executive,81817,0 +48352,Male,50,Masters,10,72,6,91,33,4.0,3,47,Rural,ML Engineer,84576,0 +48353,Male,36,Bachelors,15,49,15,77,65,4.0,5,76,Urban,Software Engineer,58691,0 +48354,Male,23,High School,14,88,62,31,88,0.0,1,92,Urban,Manager,57394,1 +48355,Female,49,High School,13,21,82,63,55,8.0,4,12,Semi-Urban,ML Engineer,120552,0 +48356,Male,25,Bachelors,10,78,32,6,72,1.0,2,85,Urban,Software Engineer,116138,0 +48357,Male,38,Masters,15,63,59,80,29,5.0,2,0,Urban,Data Analyst,71177,0 +48358,Male,26,Bachelors,8,87,23,33,17,5.0,7,56,Semi-Urban,Software Engineer,132291,0 +48359,Male,53,Bachelors,3,67,60,21,56,5.0,5,84,Urban,Data Analyst,74941,0 +48360,Male,32,High School,8,15,82,98,10,7.0,0,21,Semi-Urban,ML Engineer,118548,0 +48361,Male,55,Bachelors,6,83,74,47,82,2.0,0,30,Urban,Manager,46263,0 +48362,Male,42,Diploma,3,40,72,89,19,2.0,6,92,Urban,Manager,116405,1 +48363,Male,25,Masters,12,50,9,28,79,7.0,0,68,Semi-Urban,HR Executive,31382,0 +48364,Male,27,High School,16,46,81,97,26,4.0,3,96,Rural,Manager,118054,1 +48365,Other,50,Masters,6,93,23,21,55,4.0,6,43,Urban,ML Engineer,67648,0 +48366,Male,44,Bachelors,10,30,62,73,2,1.0,7,39,Urban,HR Executive,50622,0 +48367,Female,34,High School,6,72,79,34,26,3.0,0,42,Urban,Manager,37696,0 +48368,Male,26,Bachelors,13,61,17,41,18,7.0,0,20,Urban,Software Engineer,122208,0 +48369,Male,58,Bachelors,7,23,63,46,78,3.0,3,40,Semi-Urban,HR Executive,70931,0 +48370,Male,45,Bachelors,4,43,35,96,3,8.0,0,8,Semi-Urban,ML Engineer,127488,0 +48371,Male,54,PhD,11,4,57,40,32,4.0,4,19,Urban,Software Engineer,31663,0 +48372,Male,21,Bachelors,12,63,31,83,14,7.0,6,92,Semi-Urban,Software Engineer,132132,1 +48373,Male,57,Diploma,6,58,67,18,17,4.0,5,3,Urban,Software Engineer,127659,0 +48374,Male,36,Bachelors,12,56,67,46,71,0.0,7,45,Semi-Urban,Software Engineer,102072,0 +48375,Male,49,Masters,13,13,31,3,3,3.0,6,30,Semi-Urban,Software Engineer,137949,0 +48376,Female,45,High School,8,78,41,45,58,6.0,2,52,Urban,ML Engineer,84164,0 +48377,Male,59,Bachelors,3,0,99,38,75,8.0,3,46,Urban,Manager,134393,0 +48378,Male,40,High School,12,63,35,20,32,8.0,5,72,Semi-Urban,ML Engineer,66091,0 +48379,Female,45,Masters,3,7,42,10,58,2.0,1,78,Rural,Software Engineer,77875,0 +48380,Male,37,Masters,2,71,95,35,26,0.0,4,49,Semi-Urban,HR Executive,42009,1 +48381,Female,56,Masters,12,28,23,41,63,5.0,6,42,Urban,Software Engineer,128796,0 +48382,Female,26,High School,2,33,24,67,66,2.0,5,75,Urban,ML Engineer,119955,0 +48383,Male,44,Masters,7,38,12,63,65,1.0,5,12,Semi-Urban,Manager,64823,0 +48384,Male,50,Diploma,19,38,51,63,51,9.0,0,71,Urban,Manager,70822,0 +48385,Other,29,Bachelors,6,8,55,78,85,5.0,4,33,Urban,Manager,69469,0 +48386,Male,46,High School,4,34,49,53,57,5.0,0,97,Urban,Software Engineer,133371,0 +48387,Male,57,PhD,0,94,28,37,53,0.0,4,87,Urban,Manager,59244,1 +48388,Male,53,Bachelors,3,58,47,42,12,1.0,7,62,Semi-Urban,Software Engineer,79120,0 +48389,Male,37,Masters,1,80,8,91,85,5.0,0,31,Semi-Urban,Manager,86492,0 +48390,Other,48,Bachelors,17,80,38,23,44,5.0,1,81,Urban,HR Executive,99752,0 +48391,Male,52,Masters,18,95,77,98,89,6.0,3,79,Semi-Urban,Data Analyst,128592,1 +48392,Male,59,Masters,9,52,88,20,18,6.0,7,24,Rural,Data Analyst,34287,0 +48393,Male,30,Diploma,7,79,75,86,44,0.0,4,26,Urban,HR Executive,136635,1 +48394,Male,50,Bachelors,3,63,84,84,57,0.0,6,87,Rural,ML Engineer,146745,1 +48395,Male,38,Diploma,8,4,27,91,82,9.0,0,0,Rural,HR Executive,54251,0 +48396,Other,40,Diploma,8,95,19,66,56,2.0,0,72,Semi-Urban,Manager,146577,1 +48397,Female,24,Bachelors,16,90,48,44,63,2.0,1,89,Semi-Urban,ML Engineer,66603,1 +48398,Male,32,High School,11,80,41,67,56,9.0,7,91,Urban,Data Analyst,43129,1 +48399,Male,49,Diploma,12,98,53,14,80,9.0,1,26,Urban,ML Engineer,45227,0 +48400,Male,43,Bachelors,11,15,12,24,10,3.0,7,44,Urban,Data Analyst,39936,0 +48401,Male,53,Diploma,0,73,66,97,88,1.0,3,39,Urban,HR Executive,125858,1 +48402,Male,36,Bachelors,3,12,2,21,70,8.0,0,49,Urban,Manager,126042,0 +48403,Female,47,Bachelors,15,45,63,76,67,6.0,7,32,Urban,Data Analyst,29401,0 +48404,Male,40,Bachelors,10,74,66,40,61,6.0,3,56,Urban,Manager,100904,1 +48405,Female,34,Masters,7,80,70,56,62,2.0,2,72,Semi-Urban,ML Engineer,147609,1 +48406,Male,59,Diploma,6,61,16,81,59,6.0,1,95,Semi-Urban,Software Engineer,93483,1 +48407,Female,53,Bachelors,1,64,83,96,31,3.0,4,34,Urban,Manager,137899,1 +48408,Male,36,PhD,0,6,48,58,73,9.0,4,52,Semi-Urban,Software Engineer,132212,0 +48409,Female,41,High School,11,98,25,94,81,5.0,4,12,Semi-Urban,Manager,144835,0 +48410,Female,48,Diploma,17,1,72,78,61,2.0,7,94,Urban,Manager,96935,1 +48411,Other,38,Masters,11,0,46,45,7,6.0,6,92,Urban,HR Executive,99865,0 +48412,Female,42,Bachelors,1,27,17,87,10,3.0,6,1,Urban,Software Engineer,66655,0 +48413,Female,59,Bachelors,4,19,53,40,50,8.0,0,38,Urban,Data Analyst,65099,0 +48414,Male,41,Diploma,18,95,44,66,73,4.0,0,63,Semi-Urban,ML Engineer,63420,1 +48415,Male,49,Bachelors,11,34,99,75,90,4.0,4,46,Rural,Data Analyst,109410,1 +48416,Male,44,High School,1,1,42,44,14,5.0,3,63,Urban,Software Engineer,91326,0 +48417,Male,51,Masters,7,63,98,63,72,3.0,1,5,Rural,ML Engineer,90841,0 +48418,Female,48,Bachelors,16,89,0,25,51,5.0,5,8,Urban,Data Analyst,21755,0 +48419,Male,30,Bachelors,16,16,72,29,59,6.0,4,41,Rural,HR Executive,63267,0 +48420,Male,58,Diploma,5,73,37,21,43,7.0,2,35,Urban,Data Analyst,38112,0 +48421,Male,21,Masters,7,65,94,7,18,9.0,0,16,Semi-Urban,HR Executive,25836,0 +48422,Male,37,Masters,15,84,82,73,26,7.0,7,69,Semi-Urban,Manager,45096,1 +48423,Male,50,Diploma,14,27,0,16,33,2.0,0,62,Urban,Manager,100926,0 +48424,Male,55,Bachelors,11,20,8,38,16,3.0,5,58,Urban,ML Engineer,123216,0 +48425,Male,37,Bachelors,5,49,67,15,35,8.0,1,74,Urban,ML Engineer,81618,0 +48426,Male,58,Masters,14,67,58,30,21,4.0,0,75,Rural,Data Analyst,64082,0 +48427,Male,56,Diploma,10,1,99,49,87,8.0,4,48,Urban,HR Executive,23174,0 +48428,Female,49,Bachelors,18,82,65,96,20,5.0,4,29,Rural,Manager,103811,1 +48429,Other,55,Bachelors,13,13,62,94,60,2.0,3,92,Urban,HR Executive,149432,1 +48430,Male,27,Masters,5,51,61,87,85,1.0,6,40,Urban,Software Engineer,56821,1 +48431,Male,57,Diploma,1,66,34,84,11,5.0,6,94,Rural,Software Engineer,67248,1 +48432,Male,21,High School,2,28,2,88,54,4.0,1,35,Urban,Data Analyst,105410,0 +48433,Female,36,Diploma,2,53,93,75,23,0.0,2,69,Urban,HR Executive,100180,1 +48434,Male,57,Diploma,13,86,72,19,92,7.0,5,76,Semi-Urban,Data Analyst,52746,1 +48435,Female,27,Diploma,1,26,81,67,52,9.0,5,62,Semi-Urban,HR Executive,113654,0 +48436,Female,57,Bachelors,4,2,24,64,94,4.0,4,98,Urban,ML Engineer,91007,0 +48437,Female,57,Masters,4,53,32,14,23,2.0,5,15,Semi-Urban,Manager,75911,0 +48438,Female,57,Masters,10,17,85,85,4,7.0,4,33,Urban,HR Executive,122050,0 +48439,Female,28,Bachelors,0,70,1,41,12,3.0,3,21,Urban,Data Analyst,94760,0 +48440,Female,38,Masters,3,90,69,42,57,9.0,5,30,Urban,Data Analyst,134349,0 +48441,Female,49,Masters,12,43,37,57,73,2.0,4,9,Rural,HR Executive,121103,0 +48442,Male,34,Masters,3,12,73,57,39,5.0,3,90,Rural,Software Engineer,24601,0 +48443,Other,48,Masters,12,37,83,99,9,6.0,0,61,Urban,Manager,85816,1 +48444,Female,32,High School,3,84,61,38,6,7.0,3,43,Rural,Manager,60944,0 +48445,Male,39,Masters,5,25,93,63,57,6.0,1,83,Semi-Urban,HR Executive,40201,1 +48446,Male,39,Bachelors,18,65,81,93,64,1.0,0,74,Urban,Data Analyst,78836,1 +48447,Female,25,Masters,1,93,72,8,42,4.0,3,69,Semi-Urban,Software Engineer,116469,1 +48448,Male,48,Diploma,6,27,75,15,65,2.0,4,53,Rural,Software Engineer,121709,0 +48449,Female,49,Masters,15,37,60,32,9,8.0,0,32,Urban,Software Engineer,106800,0 +48450,Male,34,PhD,7,99,65,27,7,7.0,6,37,Rural,Software Engineer,125767,0 +48451,Female,44,Masters,16,30,25,21,29,7.0,6,28,Urban,ML Engineer,68095,0 +48452,Male,58,High School,2,91,41,87,63,9.0,5,76,Urban,ML Engineer,90639,1 +48453,Male,48,Bachelors,16,65,21,94,74,5.0,5,39,Rural,Manager,112909,0 +48454,Female,52,Diploma,12,80,4,36,85,5.0,2,60,Urban,Manager,40285,0 +48455,Male,35,Bachelors,0,7,28,51,13,9.0,6,20,Urban,Software Engineer,113276,0 +48456,Female,47,Bachelors,15,35,80,1,15,1.0,6,0,Urban,ML Engineer,74597,0 +48457,Male,21,Bachelors,13,63,15,45,28,0.0,1,54,Semi-Urban,ML Engineer,34951,0 +48458,Female,28,Diploma,7,79,92,53,89,9.0,7,75,Urban,ML Engineer,88083,1 +48459,Male,58,Diploma,7,31,99,69,62,7.0,0,88,Semi-Urban,Manager,115845,1 +48460,Male,36,High School,1,47,97,73,29,4.0,3,71,Urban,Data Analyst,42617,1 +48461,Female,21,Bachelors,17,70,42,77,15,6.0,2,81,Urban,Software Engineer,95001,1 +48462,Male,40,Diploma,2,71,76,87,25,8.0,0,64,Urban,Data Analyst,50910,1 +48463,Female,30,Bachelors,11,53,20,44,73,9.0,0,16,Rural,Data Analyst,49958,0 +48464,Female,39,Bachelors,1,60,93,58,67,6.0,4,81,Rural,Software Engineer,62189,1 +48465,Male,23,Bachelors,5,59,79,42,90,8.0,0,92,Semi-Urban,Data Analyst,136043,1 +48466,Male,36,Bachelors,0,88,23,26,49,4.0,5,53,Semi-Urban,Manager,63974,0 +48467,Male,31,Diploma,6,25,17,60,28,6.0,4,63,Rural,HR Executive,39614,0 +48468,Male,27,High School,0,69,24,25,5,2.0,5,52,Semi-Urban,HR Executive,55009,0 +48469,Male,39,Diploma,19,36,82,89,82,8.0,5,21,Semi-Urban,Software Engineer,81861,0 +48470,Male,32,High School,5,26,4,0,17,0.0,1,28,Rural,Data Analyst,132031,0 +48471,Other,53,PhD,7,42,74,92,40,4.0,2,22,Rural,Manager,45760,0 +48472,Male,22,Bachelors,11,80,75,82,88,0.0,5,82,Semi-Urban,ML Engineer,109284,1 +48473,Male,27,Bachelors,18,72,44,14,58,4.0,4,34,Semi-Urban,Software Engineer,137831,0 +48474,Male,34,Diploma,6,38,53,17,54,5.0,4,6,Urban,Data Analyst,115883,0 +48475,Male,57,Bachelors,8,85,49,84,39,5.0,0,39,Semi-Urban,Data Analyst,125074,1 +48476,Female,30,Diploma,6,99,87,21,22,7.0,2,67,Urban,Data Analyst,115876,1 +48477,Male,46,Bachelors,2,17,10,88,51,0.0,1,55,Rural,Data Analyst,120295,0 +48478,Female,46,Masters,14,3,7,24,58,2.0,4,74,Semi-Urban,Manager,39921,0 +48479,Female,34,Diploma,8,72,61,33,47,5.0,5,51,Semi-Urban,HR Executive,23641,0 +48480,Male,59,PhD,11,33,86,86,81,3.0,2,42,Semi-Urban,Data Analyst,127428,1 +48481,Female,44,Bachelors,3,83,26,89,18,5.0,5,96,Urban,Data Analyst,127113,1 +48482,Female,52,Diploma,17,50,33,65,1,9.0,5,36,Semi-Urban,Manager,103725,0 +48483,Female,32,Bachelors,5,24,50,2,91,6.0,0,73,Urban,Manager,42917,0 +48484,Male,47,Masters,15,2,35,11,35,2.0,4,74,Semi-Urban,HR Executive,35558,0 +48485,Male,26,Masters,13,80,88,2,64,5.0,5,93,Urban,Data Analyst,90096,1 +48486,Male,48,Bachelors,12,13,41,6,84,7.0,7,63,Urban,Software Engineer,119247,0 +48487,Male,43,Bachelors,8,86,84,51,61,0.0,0,23,Urban,HR Executive,101084,1 +48488,Male,54,Masters,0,52,53,75,4,3.0,3,70,Rural,ML Engineer,61633,1 +48489,Female,50,Masters,2,0,60,81,27,8.0,3,69,Rural,Software Engineer,28331,0 +48490,Male,55,Bachelors,9,51,60,33,11,7.0,2,59,Urban,ML Engineer,53335,0 +48491,Male,37,PhD,10,17,90,47,97,9.0,4,84,Semi-Urban,HR Executive,44635,1 +48492,Male,45,Bachelors,4,93,37,5,11,7.0,0,21,Urban,HR Executive,70706,0 +48493,Male,58,High School,7,29,48,73,80,4.0,4,56,Urban,HR Executive,63147,0 +48494,Male,48,High School,13,1,85,64,17,9.0,1,93,Urban,Manager,67278,1 +48495,Female,51,Bachelors,6,31,6,3,56,8.0,3,38,Semi-Urban,Software Engineer,70883,0 +48496,Other,43,Diploma,14,1,24,65,76,1.0,4,80,Urban,HR Executive,53066,0 +48497,Male,23,Diploma,3,74,85,92,98,5.0,6,89,Urban,Software Engineer,133356,1 +48498,Male,36,Bachelors,18,65,14,64,96,6.0,6,74,Urban,ML Engineer,45466,0 +48499,Female,56,Masters,5,57,7,58,92,5.0,3,35,Urban,Software Engineer,41885,0 +48500,Male,28,Bachelors,10,44,32,97,77,8.0,5,22,Urban,ML Engineer,57223,0 +48501,Male,38,High School,19,79,56,52,54,2.0,2,35,Urban,HR Executive,67248,0 +48502,Male,47,Diploma,3,36,4,70,79,0.0,4,22,Rural,Data Analyst,62893,0 +48503,Male,34,Bachelors,9,99,43,69,39,6.0,2,55,Rural,Software Engineer,128879,1 +48504,Female,30,PhD,10,93,63,8,2,3.0,4,39,Urban,Software Engineer,115998,0 +48505,Female,28,Diploma,5,91,86,52,21,2.0,3,98,Rural,Manager,43838,1 +48506,Male,24,Bachelors,19,25,63,50,30,1.0,3,36,Urban,HR Executive,148103,0 +48507,Male,22,Masters,7,29,25,63,78,5.0,6,27,Semi-Urban,HR Executive,140959,0 +48508,Male,48,Masters,16,57,10,81,75,4.0,3,69,Semi-Urban,Data Analyst,77288,0 +48509,Male,29,High School,0,88,27,46,72,0.0,7,99,Urban,Manager,119592,1 +48510,Female,55,Masters,10,45,34,99,4,9.0,3,52,Urban,HR Executive,109070,0 +48511,Male,40,Bachelors,0,2,97,80,1,7.0,2,18,Urban,ML Engineer,118670,0 +48512,Male,46,Diploma,6,40,71,90,45,6.0,0,53,Urban,Data Analyst,38629,1 +48513,Male,58,Bachelors,16,39,47,69,96,3.0,7,52,Rural,Manager,50555,0 +48514,Male,54,Bachelors,12,52,18,26,8,4.0,4,85,Semi-Urban,ML Engineer,99721,0 +48515,Male,50,Masters,16,81,9,30,47,1.0,3,62,Semi-Urban,Data Analyst,46147,0 +48516,Male,22,Bachelors,5,8,9,69,32,3.0,0,80,Semi-Urban,Manager,69518,0 +48517,Female,42,Masters,2,89,27,85,46,2.0,6,53,Semi-Urban,Manager,70546,1 +48518,Male,43,Diploma,8,42,69,49,5,9.0,2,22,Urban,ML Engineer,122119,0 +48519,Female,32,High School,18,89,72,16,99,5.0,7,1,Urban,Data Analyst,30715,0 +48520,Female,32,Diploma,0,58,17,7,31,1.0,2,55,Rural,Manager,103327,0 +48521,Female,25,Diploma,19,36,17,0,88,6.0,7,12,Urban,ML Engineer,20562,0 +48522,Male,46,Bachelors,5,20,57,1,76,0.0,2,19,Urban,HR Executive,38674,0 +48523,Female,42,Bachelors,13,91,68,64,92,4.0,4,16,Urban,ML Engineer,83185,0 +48524,Female,50,Bachelors,16,97,83,61,68,8.0,3,84,Urban,HR Executive,46323,1 +48525,Male,43,Bachelors,4,35,44,66,46,7.0,0,1,Rural,HR Executive,23481,0 +48526,Female,36,High School,4,98,29,54,18,6.0,4,61,Urban,Software Engineer,108856,1 +48527,Male,28,Bachelors,9,34,55,92,44,2.0,0,25,Urban,HR Executive,47418,0 +48528,Female,58,Masters,1,66,5,86,84,1.0,4,86,Urban,Manager,79444,1 +48529,Male,33,Masters,12,23,55,93,11,9.0,5,55,Urban,Data Analyst,109738,0 +48530,Female,52,High School,8,28,25,92,2,2.0,1,80,Urban,Manager,35824,0 +48531,Male,54,Masters,12,39,28,82,42,2.0,2,33,Rural,Software Engineer,147982,0 +48532,Male,36,Bachelors,15,30,38,12,63,6.0,6,53,Rural,ML Engineer,129973,0 +48533,Male,37,Bachelors,13,45,28,48,78,7.0,6,63,Rural,Data Analyst,63598,0 +48534,Male,42,Bachelors,10,11,16,83,20,1.0,2,35,Urban,Data Analyst,50157,0 +48535,Other,42,High School,18,28,29,49,35,4.0,6,66,Rural,ML Engineer,24667,0 +48536,Male,49,Bachelors,14,7,83,3,49,7.0,7,56,Urban,Manager,65909,0 +48537,Male,44,Bachelors,17,92,50,74,65,0.0,2,2,Urban,Software Engineer,145946,0 +48538,Female,44,Bachelors,10,66,60,74,58,7.0,0,21,Urban,Manager,26480,0 +48539,Male,55,Bachelors,1,43,91,74,7,3.0,2,99,Rural,Software Engineer,143795,1 +48540,Male,48,Bachelors,16,82,33,31,58,2.0,6,8,Urban,Software Engineer,87142,0 +48541,Male,54,Bachelors,15,70,30,19,70,9.0,3,57,Urban,Manager,46861,0 +48542,Female,23,Bachelors,4,28,28,97,64,7.0,1,34,Rural,Software Engineer,80126,0 +48543,Female,42,Masters,13,21,53,12,15,2.0,5,29,Semi-Urban,Software Engineer,93766,0 +48544,Female,56,Bachelors,5,31,26,54,61,6.0,5,73,Rural,HR Executive,129992,0 +48545,Other,31,Diploma,11,32,14,88,47,1.0,7,25,Urban,HR Executive,108662,0 +48546,Male,34,Bachelors,7,10,86,89,77,6.0,7,43,Semi-Urban,Software Engineer,78669,0 +48547,Other,54,Masters,0,43,34,16,84,3.0,2,15,Urban,Software Engineer,132467,0 +48548,Male,22,Bachelors,16,96,33,12,96,4.0,4,85,Semi-Urban,Data Analyst,127987,0 +48549,Male,48,PhD,15,83,62,54,31,4.0,2,61,Rural,Software Engineer,106354,1 +48550,Male,34,Diploma,13,43,47,56,30,8.0,2,94,Urban,Manager,67534,1 +48551,Male,56,Bachelors,9,7,96,6,33,1.0,7,14,Semi-Urban,Data Analyst,109996,0 +48552,Female,58,Bachelors,0,9,1,97,59,5.0,1,82,Semi-Urban,HR Executive,37892,0 +48553,Male,38,Bachelors,14,30,42,25,6,0.0,1,33,Rural,HR Executive,145578,0 +48554,Female,56,High School,18,49,90,77,56,0.0,6,47,Semi-Urban,Data Analyst,121468,1 +48555,Male,50,Bachelors,19,21,83,50,63,3.0,5,28,Urban,Manager,20053,0 +48556,Male,45,Bachelors,9,7,69,40,42,7.0,3,59,Semi-Urban,Software Engineer,94921,0 +48557,Male,51,Bachelors,17,83,83,97,21,4.0,3,4,Rural,Software Engineer,90828,1 +48558,Male,42,Bachelors,19,95,92,92,96,4.0,2,77,Semi-Urban,Manager,75835,1 +48559,Other,56,Bachelors,17,8,92,35,8,3.0,0,98,Semi-Urban,Software Engineer,82277,0 +48560,Female,45,High School,7,77,83,64,64,3.0,4,36,Rural,Data Analyst,35077,1 +48561,Male,41,Bachelors,19,30,50,18,47,5.0,1,23,Urban,HR Executive,98412,0 +48562,Male,59,Diploma,4,32,49,54,57,5.0,2,51,Urban,ML Engineer,66935,0 +48563,Male,42,Diploma,12,30,1,32,3,1.0,4,86,Semi-Urban,Data Analyst,142540,0 +48564,Male,34,Masters,13,80,65,91,27,2.0,3,57,Urban,ML Engineer,52853,1 +48565,Female,49,Bachelors,4,56,35,44,78,4.0,3,76,Urban,Manager,90376,0 +48566,Male,29,Diploma,14,33,77,97,56,0.0,1,6,Urban,HR Executive,55955,0 +48567,Male,41,High School,14,11,28,64,44,2.0,1,43,Urban,Software Engineer,134578,0 +48568,Female,42,High School,4,29,6,11,2,3.0,2,76,Urban,HR Executive,131699,0 +48569,Male,31,Masters,9,15,79,81,54,7.0,7,3,Urban,ML Engineer,93551,0 +48570,Female,35,Bachelors,10,44,99,63,70,9.0,1,63,Semi-Urban,Manager,76281,1 +48571,Female,34,Bachelors,8,5,87,37,82,1.0,5,6,Semi-Urban,HR Executive,59315,0 +48572,Male,37,Diploma,15,47,97,19,8,6.0,0,67,Rural,Software Engineer,32771,0 +48573,Female,45,High School,3,62,41,91,67,5.0,6,13,Urban,ML Engineer,27421,0 +48574,Female,44,Diploma,5,82,92,96,91,5.0,4,0,Urban,Manager,62431,1 +48575,Male,26,PhD,0,3,78,39,47,6.0,1,35,Urban,ML Engineer,136500,0 +48576,Male,26,Bachelors,12,64,31,99,85,6.0,0,46,Urban,ML Engineer,72641,1 +48577,Male,26,High School,12,10,12,27,76,7.0,2,73,Urban,Software Engineer,58605,0 +48578,Female,45,Masters,6,70,19,14,28,7.0,2,8,Rural,HR Executive,118369,0 +48579,Male,40,Bachelors,9,46,57,89,41,3.0,1,81,Urban,ML Engineer,107025,1 +48580,Male,47,Bachelors,11,70,60,53,98,9.0,3,18,Urban,Software Engineer,130824,0 +48581,Male,39,PhD,13,77,23,41,65,0.0,2,80,Semi-Urban,Manager,32300,0 +48582,Male,55,Diploma,6,30,0,50,95,0.0,0,94,Semi-Urban,Manager,122596,0 +48583,Male,57,Masters,18,63,77,80,61,4.0,5,96,Rural,ML Engineer,123062,1 +48584,Male,45,Bachelors,16,1,70,52,19,0.0,5,4,Urban,HR Executive,116382,0 +48585,Male,32,High School,4,1,43,98,78,9.0,3,52,Urban,ML Engineer,27320,0 +48586,Female,35,Masters,4,91,2,48,7,0.0,2,62,Urban,HR Executive,22362,0 +48587,Female,49,Masters,19,40,83,89,50,1.0,3,55,Rural,Data Analyst,133020,1 +48588,Male,47,Bachelors,11,49,53,94,53,6.0,5,78,Urban,Software Engineer,121462,1 +48589,Female,49,High School,13,59,91,70,79,6.0,3,82,Urban,Software Engineer,36407,1 +48590,Male,56,Bachelors,15,21,50,13,60,1.0,4,97,Rural,Data Analyst,26402,0 +48591,Female,54,Bachelors,17,29,44,11,99,9.0,2,96,Semi-Urban,Data Analyst,145518,0 +48592,Male,50,Bachelors,5,20,28,21,15,6.0,6,77,Urban,Software Engineer,87286,0 +48593,Male,44,Bachelors,8,12,5,23,20,7.0,7,48,Urban,ML Engineer,90936,0 +48594,Male,35,High School,8,81,82,79,51,9.0,0,67,Urban,ML Engineer,81174,1 +48595,Male,51,Bachelors,13,80,88,90,85,3.0,7,20,Urban,Software Engineer,80011,1 +48596,Female,54,Bachelors,15,38,49,23,7,1.0,7,8,Urban,HR Executive,63465,0 +48597,Male,37,PhD,12,88,9,80,43,2.0,0,9,Semi-Urban,Data Analyst,60001,0 +48598,Male,22,Diploma,3,54,4,5,69,9.0,1,49,Urban,Software Engineer,48892,0 +48599,Female,52,Masters,17,38,65,3,66,5.0,3,20,Urban,Manager,21541,0 +48600,Female,32,Bachelors,13,57,71,87,33,6.0,3,51,Urban,Software Engineer,78046,1 +48601,Male,58,High School,4,25,31,27,66,4.0,1,61,Rural,HR Executive,26953,0 +48602,Male,34,Bachelors,19,50,84,37,7,4.0,7,55,Semi-Urban,Data Analyst,135820,0 +48603,Female,59,Masters,16,56,61,23,42,9.0,6,73,Urban,Manager,142848,0 +48604,Male,52,Masters,14,90,60,81,26,9.0,4,34,Urban,ML Engineer,75393,1 +48605,Female,29,Masters,16,3,69,47,55,1.0,4,79,Rural,Data Analyst,129465,0 +48606,Female,21,High School,9,17,37,61,25,0.0,5,80,Rural,Manager,124396,0 +48607,Male,44,Bachelors,8,40,25,79,20,7.0,4,97,Urban,HR Executive,136364,1 +48608,Female,44,Diploma,14,70,65,34,51,4.0,6,72,Urban,Data Analyst,64774,1 +48609,Male,42,Masters,8,61,44,47,69,6.0,2,0,Urban,Software Engineer,45315,0 +48610,Female,35,High School,18,60,91,66,82,5.0,7,59,Semi-Urban,ML Engineer,97735,1 +48611,Male,47,Diploma,14,24,53,93,57,2.0,2,35,Urban,ML Engineer,92938,0 +48612,Female,24,Bachelors,6,55,49,97,0,9.0,5,42,Urban,Manager,60576,1 +48613,Other,45,Diploma,1,11,20,96,53,1.0,7,94,Urban,HR Executive,134077,0 +48614,Male,57,PhD,12,68,54,67,68,3.0,1,93,Urban,Manager,95429,1 +48615,Female,28,Bachelors,2,34,4,24,35,6.0,0,95,Urban,Manager,149304,0 +48616,Male,42,High School,2,6,50,93,18,2.0,1,85,Urban,Software Engineer,66305,0 +48617,Female,23,Diploma,16,20,20,49,35,7.0,3,68,Rural,HR Executive,107632,0 +48618,Female,28,Bachelors,15,46,47,27,90,9.0,7,93,Urban,Manager,36733,0 +48619,Other,28,Bachelors,6,47,3,43,72,1.0,5,62,Rural,ML Engineer,86513,0 +48620,Female,44,Diploma,5,99,10,75,68,6.0,2,4,Urban,Manager,116313,0 +48621,Male,43,Bachelors,17,54,22,53,64,7.0,2,75,Urban,HR Executive,108511,0 +48622,Male,34,Diploma,7,63,74,13,84,1.0,2,10,Urban,Manager,69208,0 +48623,Female,26,Diploma,7,39,69,75,33,2.0,5,68,Semi-Urban,Manager,148325,1 +48624,Female,41,Masters,16,68,36,41,84,6.0,1,10,Urban,ML Engineer,34340,0 +48625,Male,40,Bachelors,4,12,77,94,66,4.0,2,40,Urban,Software Engineer,21182,0 +48626,Male,21,Diploma,3,1,61,53,47,6.0,1,59,Urban,ML Engineer,122880,0 +48627,Male,31,Bachelors,2,57,45,38,78,9.0,7,67,Rural,Data Analyst,49089,0 +48628,Female,50,Masters,11,0,53,85,26,4.0,4,85,Urban,Manager,102171,0 +48629,Female,56,Masters,15,54,80,91,68,8.0,7,74,Urban,Software Engineer,125855,1 +48630,Male,30,Bachelors,13,45,82,50,61,4.0,5,83,Semi-Urban,Software Engineer,105871,1 +48631,Male,38,Bachelors,7,58,17,81,92,0.0,1,10,Rural,Data Analyst,70316,0 +48632,Female,31,Diploma,0,86,15,32,91,6.0,2,57,Urban,ML Engineer,137706,0 +48633,Female,28,Bachelors,4,72,69,16,42,9.0,4,66,Urban,ML Engineer,109146,0 +48634,Male,25,Masters,0,85,61,5,90,5.0,2,79,Urban,HR Executive,137259,0 +48635,Female,57,Bachelors,9,24,31,37,50,5.0,3,84,Semi-Urban,Software Engineer,140540,0 +48636,Male,21,Bachelors,7,9,90,80,42,8.0,5,45,Rural,Software Engineer,138240,0 +48637,Female,37,Diploma,7,81,91,29,19,0.0,6,74,Rural,Software Engineer,105578,1 +48638,Female,40,Masters,3,1,81,52,25,0.0,2,19,Urban,ML Engineer,103902,0 +48639,Other,52,Masters,12,53,32,51,67,9.0,7,10,Urban,Data Analyst,73036,0 +48640,Female,38,Diploma,16,45,38,2,69,0.0,1,10,Semi-Urban,Software Engineer,132301,0 +48641,Male,41,High School,17,57,57,28,3,1.0,1,47,Rural,HR Executive,22582,0 +48642,Female,37,Masters,18,18,48,83,89,9.0,2,75,Urban,HR Executive,53559,0 +48643,Female,32,Bachelors,15,59,29,71,0,1.0,0,91,Semi-Urban,HR Executive,75260,1 +48644,Male,24,Masters,4,88,52,82,80,9.0,5,11,Semi-Urban,ML Engineer,91195,0 +48645,Male,46,Masters,3,22,87,27,71,9.0,3,9,Semi-Urban,Data Analyst,92734,0 +48646,Male,35,High School,1,52,68,38,17,2.0,0,6,Semi-Urban,ML Engineer,83610,0 +48647,Female,35,High School,17,9,59,27,88,8.0,5,45,Urban,HR Executive,57469,0 +48648,Female,26,Diploma,19,53,31,76,30,5.0,2,85,Urban,ML Engineer,90989,1 +48649,Male,45,Bachelors,19,15,86,24,11,9.0,7,24,Urban,HR Executive,146014,0 +48650,Male,25,Bachelors,10,59,26,8,89,2.0,0,71,Urban,HR Executive,26800,0 +48651,Male,41,High School,14,16,4,78,32,5.0,4,6,Semi-Urban,Software Engineer,141027,0 +48652,Male,22,Diploma,18,82,49,80,2,2.0,7,56,Urban,Manager,24941,1 +48653,Male,22,Bachelors,8,98,77,61,43,4.0,2,33,Urban,Data Analyst,95557,1 +48654,Other,37,Masters,5,11,74,21,42,1.0,7,31,Urban,ML Engineer,77198,0 +48655,Female,59,Diploma,17,60,28,14,54,3.0,2,90,Semi-Urban,Manager,30158,0 +48656,Male,47,Diploma,2,43,82,78,18,0.0,4,79,Urban,HR Executive,143190,1 +48657,Male,33,Bachelors,7,44,3,64,17,2.0,0,89,Urban,ML Engineer,44009,0 +48658,Male,48,High School,5,88,66,55,43,7.0,0,54,Semi-Urban,HR Executive,144770,1 +48659,Male,47,Bachelors,14,46,80,40,9,8.0,0,25,Urban,Manager,113582,0 +48660,Other,48,Bachelors,0,90,60,84,34,9.0,6,2,Urban,Manager,129288,0 +48661,Male,26,High School,0,79,66,6,8,6.0,4,72,Urban,Software Engineer,43400,0 +48662,Male,28,Diploma,4,63,81,33,11,0.0,7,36,Urban,Software Engineer,120257,0 +48663,Female,43,High School,12,45,26,31,39,6.0,0,1,Rural,Manager,92687,0 +48664,Male,35,Masters,19,12,32,91,9,6.0,4,86,Semi-Urban,Data Analyst,98065,0 +48665,Male,23,High School,3,97,57,53,28,8.0,2,13,Urban,Software Engineer,81579,0 +48666,Male,57,Bachelors,10,60,80,24,7,5.0,6,41,Urban,ML Engineer,62869,0 +48667,Male,21,Bachelors,1,20,53,24,43,6.0,3,75,Rural,Software Engineer,66235,0 +48668,Male,49,PhD,17,76,83,44,40,5.0,7,34,Rural,Software Engineer,142881,1 +48669,Female,55,High School,7,79,29,44,49,2.0,7,32,Urban,Data Analyst,142272,0 +48670,Female,37,Bachelors,18,10,92,55,43,5.0,0,36,Urban,HR Executive,79099,0 +48671,Female,26,Masters,11,16,97,57,26,5.0,2,35,Rural,Manager,100384,0 +48672,Female,52,High School,5,24,57,47,12,0.0,2,89,Urban,HR Executive,131477,0 +48673,Female,33,Diploma,10,79,70,78,46,3.0,5,18,Urban,Software Engineer,63518,1 +48674,Male,25,Bachelors,0,77,71,25,84,7.0,5,31,Rural,Data Analyst,85287,0 +48675,Female,23,Masters,17,78,81,57,10,2.0,3,44,Semi-Urban,HR Executive,78680,1 +48676,Male,26,Bachelors,0,52,76,42,86,7.0,0,15,Urban,Data Analyst,43860,0 +48677,Male,46,Bachelors,11,65,19,55,47,8.0,1,14,Semi-Urban,Software Engineer,36752,0 +48678,Female,36,Bachelors,17,95,21,59,20,1.0,4,93,Urban,Manager,68385,1 +48679,Female,35,High School,15,32,57,75,77,9.0,2,18,Urban,Manager,117680,0 +48680,Male,50,Bachelors,18,61,94,63,71,6.0,0,26,Urban,HR Executive,64732,1 +48681,Male,48,Bachelors,0,71,62,98,17,7.0,4,15,Rural,HR Executive,114950,1 +48682,Male,40,Masters,16,42,41,98,32,2.0,6,88,Urban,Software Engineer,86366,1 +48683,Female,27,Bachelors,18,31,51,94,98,1.0,4,12,Urban,Software Engineer,140632,0 +48684,Other,51,Masters,18,34,34,88,13,8.0,6,75,Urban,Manager,25521,0 +48685,Female,55,Bachelors,11,95,37,63,40,9.0,5,99,Semi-Urban,Data Analyst,107303,1 +48686,Female,40,Bachelors,8,74,23,40,38,2.0,2,36,Semi-Urban,Software Engineer,135167,0 +48687,Male,58,Masters,13,13,42,73,62,0.0,7,26,Semi-Urban,Manager,22793,0 +48688,Male,57,PhD,0,20,99,16,17,8.0,4,49,Urban,Software Engineer,82129,0 +48689,Female,51,Bachelors,8,97,42,37,87,0.0,0,9,Semi-Urban,HR Executive,103406,0 +48690,Male,53,Masters,16,63,82,95,20,1.0,7,97,Rural,HR Executive,84592,1 +48691,Male,57,High School,19,56,59,0,3,4.0,5,9,Rural,HR Executive,61160,0 +48692,Female,59,Diploma,2,36,72,61,35,4.0,7,41,Rural,Software Engineer,91838,0 +48693,Female,37,Diploma,17,28,89,10,37,7.0,7,20,Urban,Software Engineer,92484,0 +48694,Male,45,Masters,7,61,42,50,67,8.0,2,12,Urban,Data Analyst,59200,0 +48695,Other,31,Bachelors,5,71,58,8,27,0.0,1,66,Urban,Data Analyst,100316,0 +48696,Male,58,Masters,3,30,47,73,81,1.0,1,91,Urban,Data Analyst,126685,1 +48697,Male,41,Masters,8,84,29,67,19,9.0,7,93,Urban,HR Executive,43823,1 +48698,Male,51,High School,14,49,25,80,79,1.0,0,41,Rural,Software Engineer,61145,0 +48699,Female,25,Masters,14,13,37,0,1,4.0,5,80,Urban,HR Executive,58345,0 +48700,Male,46,Diploma,9,50,93,38,69,7.0,3,20,Rural,Software Engineer,132520,0 +48701,Female,45,Masters,17,53,71,97,77,2.0,7,82,Urban,Software Engineer,36952,1 +48702,Male,32,High School,6,64,79,43,20,8.0,0,81,Urban,ML Engineer,115017,1 +48703,Male,43,High School,1,71,14,50,83,8.0,1,88,Semi-Urban,Data Analyst,129398,0 +48704,Male,46,PhD,16,52,38,94,38,8.0,4,54,Semi-Urban,HR Executive,42455,1 +48705,Male,30,Masters,5,97,90,42,14,4.0,0,76,Urban,HR Executive,145699,1 +48706,Male,54,Diploma,10,6,84,98,38,3.0,6,15,Urban,Manager,52897,0 +48707,Male,31,Diploma,15,98,63,55,6,0.0,6,75,Rural,Data Analyst,143548,1 +48708,Female,43,Bachelors,17,94,77,48,45,6.0,6,22,Urban,Software Engineer,65959,1 +48709,Female,44,Bachelors,1,39,59,50,90,8.0,4,28,Urban,Manager,142624,0 +48710,Male,37,PhD,1,94,89,7,39,8.0,4,29,Rural,Software Engineer,117199,0 +48711,Male,49,Diploma,5,83,85,16,31,8.0,0,75,Urban,HR Executive,27861,1 +48712,Male,33,Bachelors,16,84,13,18,17,3.0,7,41,Rural,Manager,57170,0 +48713,Male,47,Bachelors,12,37,45,35,96,5.0,4,70,Rural,ML Engineer,120418,0 +48714,Female,27,Diploma,11,44,49,43,82,5.0,2,80,Urban,HR Executive,41179,0 +48715,Male,48,Masters,18,9,43,74,50,3.0,7,67,Urban,Software Engineer,144166,0 +48716,Female,26,Diploma,11,84,48,97,46,6.0,5,26,Rural,Data Analyst,41390,1 +48717,Female,51,Bachelors,8,28,7,26,1,3.0,6,71,Rural,Data Analyst,98994,0 +48718,Male,51,Diploma,11,56,15,7,21,6.0,4,83,Urban,Software Engineer,75155,0 +48719,Female,31,Diploma,4,77,4,68,49,7.0,5,9,Urban,Software Engineer,78145,0 +48720,Male,28,Diploma,19,36,77,69,63,9.0,0,84,Urban,Software Engineer,104080,1 +48721,Male,33,Masters,16,28,11,33,69,7.0,6,83,Semi-Urban,Data Analyst,101452,0 +48722,Other,27,Diploma,10,50,83,36,48,7.0,4,21,Urban,Software Engineer,86073,0 +48723,Female,52,Bachelors,0,18,92,81,83,8.0,2,58,Urban,ML Engineer,149865,1 +48724,Male,55,Bachelors,12,61,2,69,58,8.0,6,12,Urban,HR Executive,71327,0 +48725,Female,32,Bachelors,16,54,10,49,48,1.0,6,93,Rural,Manager,59657,0 +48726,Female,46,Bachelors,2,26,55,53,32,4.0,3,86,Semi-Urban,HR Executive,138567,0 +48727,Female,37,Diploma,10,16,20,75,14,9.0,3,60,Semi-Urban,Software Engineer,105240,0 +48728,Male,38,Bachelors,4,8,68,46,55,4.0,7,92,Rural,Software Engineer,85689,0 +48729,Female,54,Diploma,1,0,78,50,32,4.0,3,49,Semi-Urban,Software Engineer,131918,0 +48730,Female,38,Masters,9,7,30,18,77,0.0,6,14,Urban,ML Engineer,102986,0 +48731,Male,57,Bachelors,17,48,28,13,93,6.0,6,59,Semi-Urban,Software Engineer,27007,0 +48732,Male,54,High School,15,23,28,76,31,3.0,5,43,Urban,ML Engineer,67519,0 +48733,Male,25,Bachelors,1,24,42,94,77,1.0,0,71,Rural,Software Engineer,112215,0 +48734,Male,45,PhD,8,49,67,58,55,5.0,1,9,Semi-Urban,Manager,48263,0 +48735,Male,47,Diploma,13,40,14,90,61,9.0,1,0,Rural,HR Executive,79039,0 +48736,Female,56,Bachelors,2,94,44,99,30,0.0,3,41,Semi-Urban,ML Engineer,107050,1 +48737,Female,39,Diploma,7,33,77,68,96,9.0,1,94,Rural,Data Analyst,25991,1 +48738,Male,54,Bachelors,7,98,4,46,86,3.0,2,97,Semi-Urban,Software Engineer,107425,1 +48739,Female,41,High School,19,92,12,53,67,7.0,6,66,Urban,HR Executive,44262,0 +48740,Female,42,Bachelors,18,38,85,20,31,8.0,5,53,Rural,ML Engineer,122416,0 +48741,Male,38,Masters,11,41,14,10,54,6.0,6,12,Urban,Data Analyst,92370,0 +48742,Male,29,Diploma,0,69,44,95,8,4.0,5,22,Rural,ML Engineer,101337,0 +48743,Male,52,High School,1,77,70,91,28,6.0,3,92,Semi-Urban,Software Engineer,45459,1 +48744,Male,51,Bachelors,1,94,6,18,89,5.0,1,64,Urban,HR Executive,80391,0 +48745,Male,38,Bachelors,16,95,44,95,61,4.0,4,31,Urban,Data Analyst,99201,1 +48746,Male,32,Masters,8,58,55,91,45,0.0,7,71,Semi-Urban,Manager,45577,1 +48747,Female,30,Masters,18,59,80,73,53,4.0,5,20,Urban,Data Analyst,97488,0 +48748,Male,24,Bachelors,16,85,3,56,42,2.0,6,85,Urban,Manager,37102,0 +48749,Male,32,High School,6,54,21,35,21,3.0,1,11,Semi-Urban,Data Analyst,107758,0 +48750,Other,54,Bachelors,6,44,11,4,43,4.0,2,3,Semi-Urban,Data Analyst,77949,0 +48751,Female,59,High School,17,51,16,4,89,7.0,2,21,Semi-Urban,Manager,109232,0 +48752,Female,26,Bachelors,6,14,6,15,95,8.0,7,39,Urban,ML Engineer,42326,0 +48753,Male,24,High School,15,60,28,56,3,9.0,3,39,Urban,HR Executive,125357,0 +48754,Female,54,Masters,17,72,30,60,50,6.0,6,12,Urban,Data Analyst,44409,0 +48755,Male,41,Bachelors,9,44,39,82,90,2.0,0,89,Urban,Data Analyst,36094,1 +48756,Female,47,Bachelors,5,4,67,61,74,8.0,4,2,Rural,ML Engineer,147268,0 +48757,Male,25,High School,19,14,59,5,26,6.0,7,26,Urban,HR Executive,128902,0 +48758,Male,28,High School,19,53,77,76,92,7.0,3,25,Urban,HR Executive,124123,0 +48759,Other,38,High School,18,68,5,59,75,1.0,6,21,Urban,ML Engineer,145308,0 +48760,Male,31,Diploma,1,89,74,12,17,9.0,4,6,Rural,Software Engineer,43722,0 +48761,Male,26,Bachelors,14,4,55,31,18,8.0,3,62,Urban,Software Engineer,29512,0 +48762,Male,52,Diploma,2,55,56,47,13,5.0,4,97,Urban,Manager,138446,1 +48763,Male,56,Diploma,18,12,97,50,43,2.0,5,85,Semi-Urban,Software Engineer,100737,1 +48764,Male,56,Diploma,8,53,48,52,75,1.0,4,30,Urban,Software Engineer,61287,0 +48765,Female,52,High School,1,26,15,56,84,4.0,3,48,Urban,HR Executive,64452,0 +48766,Male,59,Masters,19,71,98,50,65,0.0,1,30,Urban,Software Engineer,61695,1 +48767,Male,21,Bachelors,16,57,77,9,19,7.0,3,64,Rural,Manager,34148,0 +48768,Female,49,Bachelors,7,20,40,4,69,1.0,3,8,Semi-Urban,HR Executive,21192,0 +48769,Female,43,High School,4,34,91,92,54,4.0,1,13,Semi-Urban,Manager,96006,0 +48770,Other,42,Bachelors,5,1,22,37,75,8.0,7,94,Urban,HR Executive,135258,0 +48771,Male,31,Bachelors,19,58,91,51,99,7.0,2,83,Urban,Data Analyst,21278,1 +48772,Male,41,Diploma,7,54,7,50,96,1.0,1,32,Urban,Manager,101563,0 +48773,Male,32,Masters,2,63,28,81,81,2.0,6,22,Urban,Software Engineer,123800,0 +48774,Female,30,Diploma,3,91,90,51,60,7.0,5,55,Rural,Data Analyst,123831,1 +48775,Male,51,High School,4,53,91,95,26,5.0,6,37,Urban,ML Engineer,88487,1 +48776,Female,51,PhD,14,62,19,3,95,2.0,5,33,Urban,Manager,59747,0 +48777,Other,24,Diploma,17,49,10,38,31,1.0,0,77,Urban,ML Engineer,93135,0 +48778,Male,34,Bachelors,4,94,44,46,29,1.0,6,41,Rural,ML Engineer,135215,0 +48779,Male,47,Diploma,11,37,5,8,54,1.0,1,86,Urban,Data Analyst,41077,0 +48780,Male,21,Masters,14,52,40,32,90,6.0,0,96,Semi-Urban,ML Engineer,29097,0 +48781,Male,28,High School,11,37,32,36,6,5.0,0,44,Urban,Manager,37703,0 +48782,Female,29,Bachelors,2,52,17,6,36,4.0,1,60,Urban,ML Engineer,95273,0 +48783,Male,32,Diploma,10,72,93,34,8,6.0,1,11,Urban,HR Executive,40514,0 +48784,Male,43,High School,9,26,63,41,38,6.0,3,40,Urban,ML Engineer,113161,0 +48785,Male,23,High School,13,85,56,38,42,1.0,1,36,Rural,ML Engineer,145093,0 +48786,Male,50,High School,7,85,36,66,80,2.0,6,0,Urban,Manager,59877,0 +48787,Male,37,PhD,0,98,32,25,6,2.0,1,58,Urban,Data Analyst,132270,0 +48788,Male,48,Bachelors,10,41,70,92,28,6.0,7,6,Urban,Software Engineer,130188,0 +48789,Male,30,PhD,12,84,58,72,81,5.0,7,77,Urban,Manager,90969,1 +48790,Female,22,High School,1,79,5,32,73,8.0,5,12,Semi-Urban,Manager,44634,0 +48791,Female,37,High School,10,42,68,99,37,7.0,6,58,Urban,Software Engineer,89457,1 +48792,Other,39,PhD,6,31,41,44,19,3.0,3,75,Rural,Manager,88268,0 +48793,Female,48,Masters,4,79,23,83,66,6.0,4,14,Urban,Manager,84750,0 +48794,Male,32,Diploma,3,56,42,47,85,4.0,2,29,Urban,Data Analyst,59287,0 +48795,Female,50,Bachelors,14,77,16,28,66,7.0,2,17,Semi-Urban,Software Engineer,54587,0 +48796,Male,50,Diploma,6,68,13,51,13,4.0,7,92,Urban,Software Engineer,62246,0 +48797,Male,38,Bachelors,4,20,84,3,60,7.0,6,30,Semi-Urban,Data Analyst,34465,0 +48798,Male,24,Masters,3,84,32,32,88,9.0,0,68,Urban,HR Executive,144858,0 +48799,Male,44,Bachelors,8,0,4,81,9,2.0,1,61,Rural,Software Engineer,143215,0 +48800,Female,41,High School,3,72,26,36,0,8.0,1,57,Rural,Software Engineer,53986,0 +48801,Male,56,Bachelors,6,73,44,74,80,8.0,3,85,Urban,HR Executive,129110,1 +48802,Male,26,Masters,6,80,43,5,9,4.0,4,48,Semi-Urban,Data Analyst,100354,0 +48803,Male,52,PhD,13,94,67,60,6,2.0,1,16,Urban,ML Engineer,117124,1 +48804,Female,49,PhD,19,82,84,22,84,9.0,7,49,Rural,ML Engineer,20077,0 +48805,Male,40,Diploma,4,69,41,4,71,7.0,2,16,Rural,HR Executive,29675,0 +48806,Male,51,Masters,5,36,3,70,4,2.0,7,73,Semi-Urban,Data Analyst,60859,0 +48807,Female,56,Diploma,2,89,59,53,47,8.0,6,3,Urban,ML Engineer,116565,0 +48808,Male,48,Bachelors,14,97,1,82,40,4.0,6,12,Rural,Data Analyst,27974,0 +48809,Female,58,Bachelors,5,61,66,58,68,1.0,6,11,Urban,ML Engineer,123116,0 +48810,Female,49,Bachelors,9,81,36,58,92,5.0,2,6,Urban,Manager,44549,0 +48811,Male,35,Bachelors,3,70,88,96,29,1.0,4,5,Urban,HR Executive,44933,1 +48812,Female,28,Masters,9,73,68,81,18,4.0,5,81,Rural,ML Engineer,104980,1 +48813,Other,26,Diploma,4,16,0,5,15,8.0,1,4,Semi-Urban,ML Engineer,106190,0 +48814,Male,25,Diploma,14,97,76,32,51,8.0,7,97,Urban,ML Engineer,47326,1 +48815,Male,41,Bachelors,18,32,77,3,94,7.0,3,9,Urban,ML Engineer,114640,0 +48816,Female,40,Masters,18,25,43,95,86,8.0,0,73,Rural,HR Executive,94597,0 +48817,Male,32,Diploma,16,3,65,57,10,1.0,0,28,Semi-Urban,Software Engineer,37920,0 +48818,Male,36,Masters,7,50,19,33,40,6.0,3,87,Urban,ML Engineer,115922,0 +48819,Female,36,Diploma,3,10,23,77,72,6.0,0,94,Semi-Urban,Software Engineer,77345,0 +48820,Male,55,Bachelors,2,10,28,82,73,0.0,2,63,Rural,HR Executive,96329,0 +48821,Female,32,Bachelors,2,11,62,51,56,3.0,3,28,Semi-Urban,Data Analyst,139776,0 +48822,Male,40,Bachelors,8,24,46,39,86,3.0,6,23,Semi-Urban,Data Analyst,52702,0 +48823,Female,38,Masters,9,86,65,32,75,4.0,4,6,Urban,Data Analyst,99460,0 +48824,Male,41,Bachelors,5,45,95,37,96,3.0,1,89,Urban,ML Engineer,118080,1 +48825,Male,24,PhD,12,50,94,42,68,3.0,5,89,Rural,HR Executive,114150,1 +48826,Male,49,Masters,19,37,91,18,32,4.0,5,25,Urban,Software Engineer,67209,0 +48827,Male,53,Masters,7,63,7,12,1,6.0,1,75,Semi-Urban,Manager,102525,0 +48828,Male,39,Bachelors,18,6,79,32,18,3.0,1,70,Urban,ML Engineer,22828,0 +48829,Male,29,Diploma,0,66,21,68,42,4.0,2,33,Urban,Data Analyst,135649,0 +48830,Other,39,Diploma,5,31,47,79,84,9.0,7,54,Rural,HR Executive,82264,0 +48831,Male,40,Bachelors,4,95,33,82,97,4.0,3,15,Urban,ML Engineer,57332,0 +48832,Male,23,Bachelors,11,14,55,54,24,9.0,3,30,Semi-Urban,Data Analyst,81168,0 +48833,Male,22,Bachelors,15,0,29,84,74,7.0,4,3,Urban,Data Analyst,114105,0 +48834,Other,26,Masters,9,68,50,10,25,3.0,6,91,Urban,Manager,57873,0 +48835,Female,35,High School,2,70,96,90,31,1.0,7,20,Urban,Software Engineer,57398,1 +48836,Female,34,Bachelors,5,43,44,40,69,9.0,2,44,Urban,HR Executive,34565,0 +48837,Male,36,Masters,3,52,67,80,20,1.0,3,41,Semi-Urban,Manager,99657,1 +48838,Male,38,High School,4,51,17,8,49,5.0,6,83,Rural,Software Engineer,34302,0 +48839,Male,56,Masters,19,92,4,99,34,8.0,6,83,Urban,Manager,98201,1 +48840,Female,38,Diploma,19,81,28,52,40,3.0,1,40,Urban,ML Engineer,88325,0 +48841,Male,30,Masters,9,90,4,67,20,9.0,5,38,Rural,Manager,148823,0 +48842,Female,51,Diploma,6,68,20,25,75,7.0,2,67,Urban,ML Engineer,139068,0 +48843,Male,26,Diploma,10,41,10,56,42,3.0,3,77,Rural,Manager,91615,0 +48844,Male,39,High School,16,3,12,64,65,8.0,4,23,Urban,HR Executive,64045,0 +48845,Male,38,High School,3,72,26,32,11,8.0,4,14,Urban,Software Engineer,144964,0 +48846,Male,43,Bachelors,19,2,67,12,2,9.0,6,75,Semi-Urban,Manager,53831,0 +48847,Male,39,Bachelors,4,87,57,8,44,3.0,5,36,Urban,Data Analyst,82618,0 +48848,Male,25,Bachelors,16,78,94,32,93,4.0,4,59,Semi-Urban,Manager,119923,1 +48849,Male,47,Diploma,19,39,62,29,88,0.0,3,11,Rural,Manager,50045,0 +48850,Female,28,Bachelors,9,24,38,32,31,9.0,5,98,Rural,ML Engineer,147203,0 +48851,Male,26,High School,13,57,56,74,91,4.0,6,11,Semi-Urban,Data Analyst,24335,0 +48852,Male,27,Masters,7,38,17,18,34,9.0,1,15,Rural,ML Engineer,65012,0 +48853,Male,45,Bachelors,4,52,60,71,73,3.0,1,59,Urban,Manager,139074,1 +48854,Male,23,Diploma,0,31,78,79,42,2.0,1,38,Semi-Urban,Software Engineer,128045,0 +48855,Male,53,Bachelors,6,19,95,28,71,7.0,2,18,Urban,Manager,26609,0 +48856,Male,23,Diploma,9,94,22,57,61,2.0,3,32,Urban,Software Engineer,42318,0 +48857,Male,41,Diploma,17,59,5,27,13,2.0,1,55,Semi-Urban,Software Engineer,71557,0 +48858,Male,46,Diploma,4,59,19,31,41,1.0,6,61,Urban,Software Engineer,39367,0 +48859,Female,55,High School,12,97,8,31,66,1.0,3,3,Urban,HR Executive,149650,0 +48860,Male,47,Diploma,16,22,72,85,87,2.0,7,20,Urban,Data Analyst,148098,0 +48861,Male,39,Masters,7,94,90,24,36,5.0,2,3,Semi-Urban,Manager,101913,0 +48862,Male,40,Bachelors,16,41,96,51,95,1.0,5,29,Rural,Software Engineer,97229,0 +48863,Male,29,Bachelors,18,25,43,57,4,2.0,0,3,Rural,Software Engineer,42802,0 +48864,Male,32,Bachelors,14,94,1,43,92,5.0,3,42,Semi-Urban,Data Analyst,121106,0 +48865,Male,36,Bachelors,12,13,66,44,56,6.0,0,40,Rural,HR Executive,56907,0 +48866,Male,39,Diploma,19,42,23,40,65,2.0,0,27,Semi-Urban,HR Executive,102668,0 +48867,Female,26,Masters,10,96,57,64,20,4.0,4,23,Rural,Software Engineer,143412,0 +48868,Male,21,Bachelors,11,29,67,82,53,1.0,5,40,Semi-Urban,Software Engineer,43517,0 +48869,Female,51,Diploma,11,82,91,72,22,3.0,4,38,Urban,Manager,140335,1 +48870,Female,54,Masters,15,28,13,24,18,6.0,5,52,Rural,Data Analyst,37622,0 +48871,Female,26,Bachelors,9,36,70,95,72,5.0,1,44,Semi-Urban,HR Executive,26183,1 +48872,Female,50,Masters,8,73,2,52,22,9.0,3,58,Rural,Software Engineer,36443,0 +48873,Male,47,High School,10,71,9,36,64,3.0,1,29,Urban,Software Engineer,54903,0 +48874,Male,41,Masters,7,36,29,10,90,0.0,4,34,Urban,ML Engineer,100161,0 +48875,Female,50,Bachelors,8,30,7,52,58,3.0,5,28,Rural,ML Engineer,35031,0 +48876,Male,40,Bachelors,2,31,1,48,25,8.0,2,63,Rural,Data Analyst,134889,0 +48877,Other,37,Masters,7,82,10,63,58,3.0,3,71,Semi-Urban,Manager,35855,0 +48878,Male,34,High School,5,56,63,83,87,9.0,2,64,Urban,ML Engineer,145328,1 +48879,Male,21,Diploma,15,39,41,25,7,6.0,0,77,Urban,ML Engineer,70413,0 +48880,Male,41,Diploma,12,55,36,41,44,6.0,6,81,Urban,HR Executive,28977,0 +48881,Male,48,Masters,18,94,20,57,91,3.0,7,50,Urban,Manager,81986,0 +48882,Male,31,Diploma,1,7,90,5,51,1.0,0,86,Urban,Software Engineer,21962,0 +48883,Female,54,Bachelors,18,78,19,44,0,4.0,5,31,Urban,ML Engineer,118374,0 +48884,Male,37,Diploma,12,66,45,8,6,0.0,7,95,Urban,ML Engineer,131393,0 +48885,Male,46,Bachelors,0,61,99,68,68,6.0,0,75,Urban,Data Analyst,101567,1 +48886,Male,39,Masters,0,20,4,77,15,9.0,6,7,Urban,Manager,130289,0 +48887,Male,31,Masters,14,47,66,91,3,4.0,0,59,Urban,Software Engineer,127400,1 +48888,Male,43,Bachelors,6,90,16,13,68,5.0,7,40,Rural,ML Engineer,57756,0 +48889,Male,40,Bachelors,1,54,89,42,5,9.0,4,35,Urban,Manager,88143,0 +48890,Male,56,Bachelors,17,68,54,11,36,8.0,6,99,Urban,Data Analyst,59880,0 +48891,Other,55,Diploma,11,44,7,69,49,6.0,7,23,Urban,Data Analyst,103228,0 +48892,Female,27,Bachelors,12,18,84,10,65,7.0,6,44,Semi-Urban,Manager,122125,0 +48893,Female,23,Masters,17,89,59,52,10,2.0,5,36,Rural,Manager,29640,0 +48894,Male,28,Diploma,2,15,61,70,58,2.0,2,78,Urban,Data Analyst,70631,0 +48895,Male,40,Masters,11,76,41,54,64,8.0,1,18,Rural,Software Engineer,146397,0 +48896,Female,34,High School,1,35,54,22,20,3.0,2,17,Urban,ML Engineer,135928,0 +48897,Female,35,PhD,17,87,69,80,58,5.0,3,24,Semi-Urban,Data Analyst,43185,1 +48898,Male,53,PhD,4,5,11,2,36,5.0,1,38,Rural,Data Analyst,134816,0 +48899,Male,51,Bachelors,1,15,86,43,41,1.0,2,27,Urban,HR Executive,135447,0 +48900,Male,59,PhD,15,16,86,72,25,2.0,1,92,Rural,ML Engineer,101315,1 +48901,Male,37,Diploma,15,39,49,31,25,2.0,4,51,Rural,Software Engineer,104552,0 +48902,Female,38,Bachelors,14,67,38,8,29,7.0,4,76,Semi-Urban,Data Analyst,67924,0 +48903,Male,31,High School,8,11,68,71,8,5.0,4,18,Semi-Urban,HR Executive,134366,0 +48904,Male,35,High School,8,9,90,73,16,2.0,1,24,Semi-Urban,Software Engineer,109864,0 +48905,Female,50,Bachelors,3,5,49,69,14,2.0,0,80,Urban,HR Executive,143581,0 +48906,Male,22,PhD,9,5,15,99,61,1.0,3,11,Urban,HR Executive,100132,0 +48907,Female,40,Diploma,0,37,0,1,75,8.0,4,52,Semi-Urban,Data Analyst,65185,0 +48908,Female,47,Diploma,0,7,58,51,74,9.0,7,53,Urban,Software Engineer,82001,0 +48909,Male,56,Bachelors,10,45,52,57,97,3.0,5,55,Rural,Manager,22516,0 +48910,Male,48,Bachelors,14,88,98,27,31,2.0,5,14,Rural,Data Analyst,40576,0 +48911,Male,21,Bachelors,3,98,73,5,72,0.0,5,10,Urban,Software Engineer,127958,0 +48912,Male,50,Bachelors,4,13,27,69,16,8.0,1,90,Semi-Urban,ML Engineer,57615,0 +48913,Female,46,PhD,8,52,26,67,46,9.0,1,64,Urban,ML Engineer,141167,0 +48914,Female,49,Bachelors,15,43,84,8,96,1.0,4,26,Urban,Software Engineer,68675,0 +48915,Female,32,Bachelors,6,76,52,39,77,3.0,2,13,Urban,HR Executive,58897,0 +48916,Female,38,Bachelors,14,82,73,69,76,5.0,7,84,Rural,Data Analyst,72283,1 +48917,Male,36,Diploma,16,45,78,65,46,5.0,3,92,Urban,HR Executive,118066,1 +48918,Female,21,Bachelors,3,6,21,14,78,2.0,4,39,Urban,Software Engineer,98359,0 +48919,Female,59,Bachelors,3,34,65,65,6,0.0,0,25,Semi-Urban,Manager,75340,0 +48920,Male,58,High School,10,32,26,79,89,7.0,5,93,Rural,Data Analyst,103837,0 +48921,Other,51,Bachelors,8,12,88,88,45,0.0,4,2,Urban,ML Engineer,82565,0 +48922,Male,54,High School,10,79,41,57,81,8.0,4,55,Urban,ML Engineer,64465,0 +48923,Female,45,Bachelors,7,78,17,45,90,8.0,3,56,Urban,HR Executive,112627,0 +48924,Female,51,Diploma,17,70,58,61,98,5.0,2,36,Urban,Manager,34715,0 +48925,Male,30,Bachelors,18,99,63,71,45,3.0,5,36,Urban,ML Engineer,35227,1 +48926,Male,28,High School,6,73,21,44,23,8.0,3,71,Semi-Urban,Data Analyst,128175,0 +48927,Male,28,Diploma,11,73,73,14,63,1.0,7,93,Semi-Urban,ML Engineer,106498,1 +48928,Male,37,Diploma,10,62,19,32,47,3.0,2,50,Urban,Manager,98523,0 +48929,Male,48,Bachelors,19,28,27,57,79,1.0,2,3,Urban,Manager,141026,0 +48930,Male,58,Masters,19,62,14,60,51,7.0,0,44,Urban,Manager,105872,0 +48931,Male,23,Masters,4,45,23,89,32,1.0,7,74,Semi-Urban,ML Engineer,89092,0 +48932,Male,55,High School,18,84,42,84,39,6.0,5,34,Urban,HR Executive,48767,1 +48933,Male,29,Diploma,1,3,29,89,78,2.0,2,42,Urban,Data Analyst,38564,0 +48934,Male,53,Bachelors,7,42,30,94,69,0.0,0,50,Urban,ML Engineer,102226,0 +48935,Female,22,Diploma,9,72,56,21,21,8.0,2,54,Semi-Urban,HR Executive,81684,0 +48936,Female,52,Bachelors,15,10,85,46,44,5.0,5,4,Semi-Urban,Manager,135098,0 +48937,Male,41,PhD,9,87,41,80,23,1.0,3,37,Urban,HR Executive,42564,1 +48938,Male,45,High School,19,6,36,4,79,3.0,7,61,Semi-Urban,ML Engineer,44915,0 +48939,Other,50,High School,16,49,58,35,66,3.0,7,37,Urban,ML Engineer,52020,0 +48940,Male,56,PhD,19,35,51,56,83,6.0,0,60,Urban,ML Engineer,73905,0 +48941,Female,40,Bachelors,0,80,25,22,38,4.0,6,54,Urban,Data Analyst,97650,0 +48942,Male,27,High School,7,45,81,63,51,7.0,0,7,Semi-Urban,HR Executive,129404,0 +48943,Male,37,Bachelors,15,40,86,16,25,0.0,2,16,Urban,Software Engineer,113369,0 +48944,Female,56,Masters,17,29,51,32,35,6.0,3,84,Urban,Software Engineer,141056,0 +48945,Other,48,Masters,16,93,55,95,25,8.0,2,77,Semi-Urban,Software Engineer,38003,1 +48946,Female,22,Diploma,8,71,28,85,24,9.0,2,8,Urban,Data Analyst,81775,0 +48947,Female,39,High School,3,7,78,61,76,9.0,0,7,Rural,Data Analyst,54158,0 +48948,Male,29,Masters,5,70,17,9,38,9.0,5,59,Semi-Urban,Manager,88545,0 +48949,Male,41,Masters,19,37,95,66,50,9.0,2,89,Urban,ML Engineer,135452,1 +48950,Male,57,Bachelors,7,38,67,28,51,9.0,7,96,Urban,Software Engineer,63989,0 +48951,Male,49,Masters,14,40,28,20,4,6.0,7,64,Urban,Manager,49177,0 +48952,Female,59,Diploma,14,88,32,99,43,7.0,1,84,Urban,HR Executive,69874,1 +48953,Male,41,PhD,2,24,52,1,79,2.0,1,96,Urban,ML Engineer,102901,0 +48954,Male,35,Masters,17,56,36,52,50,9.0,1,85,Semi-Urban,Data Analyst,73360,0 +48955,Male,40,Diploma,12,70,74,19,70,7.0,4,96,Urban,Manager,149855,1 +48956,Male,32,Bachelors,0,20,2,14,43,3.0,6,12,Rural,Manager,41567,0 +48957,Male,58,Bachelors,6,87,69,79,5,9.0,7,31,Semi-Urban,Data Analyst,63150,1 +48958,Male,30,Bachelors,8,35,60,71,68,1.0,2,25,Urban,Data Analyst,145450,0 +48959,Male,49,Masters,14,59,42,88,50,6.0,6,4,Urban,Manager,115359,0 +48960,Female,59,Bachelors,19,80,33,51,92,0.0,7,18,Urban,Manager,76290,0 +48961,Male,37,PhD,18,27,92,12,95,4.0,0,56,Urban,Manager,121940,0 +48962,Male,40,Bachelors,19,53,12,50,19,7.0,3,22,Semi-Urban,Manager,116230,0 +48963,Female,52,Bachelors,9,26,46,16,20,8.0,1,57,Urban,HR Executive,142422,0 +48964,Female,44,Diploma,5,75,60,3,30,6.0,1,54,Semi-Urban,Manager,126947,0 +48965,Male,50,Bachelors,0,62,97,79,76,4.0,1,96,Semi-Urban,Data Analyst,94235,1 +48966,Male,36,PhD,6,87,11,92,7,0.0,0,22,Rural,HR Executive,28105,0 +48967,Female,40,Masters,1,60,6,58,28,8.0,2,67,Semi-Urban,ML Engineer,48037,0 +48968,Male,31,Bachelors,16,68,81,12,27,5.0,0,73,Semi-Urban,HR Executive,72906,0 +48969,Male,53,High School,2,31,24,9,93,8.0,6,24,Semi-Urban,Manager,98069,0 +48970,Male,54,High School,11,54,78,57,97,4.0,6,39,Urban,Software Engineer,32274,0 +48971,Female,52,Bachelors,17,50,64,34,16,1.0,5,3,Urban,Data Analyst,114080,0 +48972,Female,22,High School,8,6,62,33,98,5.0,1,58,Semi-Urban,Data Analyst,116836,0 +48973,Female,37,Bachelors,6,70,63,56,10,5.0,4,33,Semi-Urban,Data Analyst,128968,0 +48974,Male,26,PhD,19,18,48,1,59,9.0,7,29,Urban,HR Executive,72201,0 +48975,Male,49,Bachelors,15,15,22,77,24,1.0,6,99,Urban,HR Executive,98284,0 +48976,Female,57,Diploma,19,21,62,58,86,9.0,0,4,Semi-Urban,HR Executive,96857,0 +48977,Male,31,Masters,10,54,31,5,81,9.0,0,78,Rural,Data Analyst,108187,0 +48978,Male,51,Bachelors,7,88,51,33,84,1.0,5,2,Rural,Software Engineer,86679,0 +48979,Male,53,High School,12,6,72,84,47,6.0,3,37,Rural,HR Executive,123985,0 +48980,Male,53,Bachelors,1,30,37,58,13,3.0,0,95,Rural,Manager,129794,0 +48981,Female,56,Bachelors,4,76,33,15,14,8.0,1,63,Urban,ML Engineer,136716,0 +48982,Male,25,PhD,11,23,5,96,68,4.0,1,55,Rural,Software Engineer,67695,0 +48983,Male,22,Bachelors,5,19,82,93,58,5.0,4,95,Urban,HR Executive,89985,1 +48984,Male,45,Diploma,8,29,42,7,47,3.0,5,69,Urban,Manager,72550,0 +48985,Female,22,Diploma,14,90,21,69,98,8.0,7,94,Urban,HR Executive,142936,1 +48986,Female,31,Masters,6,46,64,80,34,3.0,2,34,Urban,HR Executive,131492,0 +48987,Female,27,High School,1,99,95,16,94,7.0,7,79,Semi-Urban,Data Analyst,69080,1 +48988,Male,52,Masters,12,97,75,8,54,3.0,3,37,Urban,Manager,55400,0 +48989,Female,21,Bachelors,2,95,92,47,65,1.0,1,60,Urban,ML Engineer,69771,1 +48990,Male,27,Diploma,0,75,14,12,24,4.0,6,88,Rural,Data Analyst,106286,0 +48991,Male,27,Masters,7,75,81,72,16,6.0,6,63,Urban,Data Analyst,25015,1 +48992,Male,34,High School,2,7,65,61,0,2.0,1,17,Urban,Software Engineer,61177,0 +48993,Male,49,Diploma,4,3,15,42,67,8.0,5,8,Urban,Software Engineer,118408,0 +48994,Female,36,Bachelors,11,52,85,25,0,5.0,5,46,Urban,HR Executive,147091,0 +48995,Female,21,High School,15,33,88,32,58,3.0,7,68,Rural,Data Analyst,145622,0 +48996,Female,49,Bachelors,12,53,97,14,7,6.0,4,82,Semi-Urban,Manager,147990,1 +48997,Female,54,Diploma,18,9,63,7,81,8.0,4,68,Rural,Manager,79356,0 +48998,Male,53,High School,3,97,0,37,21,4.0,7,44,Rural,HR Executive,139837,0 +48999,Male,39,PhD,10,45,96,11,27,0.0,7,29,Urban,Manager,96110,0 +49000,Female,42,Bachelors,16,99,68,12,57,1.0,6,2,Semi-Urban,ML Engineer,50001,0 +49001,Female,44,Masters,15,57,41,5,84,5.0,2,93,Rural,Software Engineer,143279,0 +49002,Other,31,Bachelors,10,6,19,54,8,3.0,6,43,Semi-Urban,Data Analyst,116293,0 +49003,Male,29,Diploma,5,35,41,68,13,8.0,6,89,Urban,Software Engineer,49568,0 +49004,Female,33,High School,9,71,9,75,12,6.0,0,38,Urban,HR Executive,114227,0 +49005,Female,51,Diploma,19,31,10,56,70,1.0,0,96,Rural,Data Analyst,60539,0 +49006,Male,21,Bachelors,6,58,90,29,17,5.0,0,8,Urban,Data Analyst,43155,0 +49007,Female,51,Bachelors,13,51,80,71,10,3.0,7,34,Rural,HR Executive,53364,0 +49008,Male,52,Bachelors,18,98,37,45,4,4.0,3,23,Urban,ML Engineer,56480,0 +49009,Male,59,Bachelors,8,39,80,53,96,8.0,5,31,Semi-Urban,Software Engineer,39381,0 +49010,Female,38,Masters,16,51,23,28,17,6.0,7,50,Urban,ML Engineer,39020,0 +49011,Female,57,High School,9,49,41,30,56,0.0,1,38,Rural,Data Analyst,112356,0 +49012,Male,47,Bachelors,19,42,46,27,8,9.0,6,60,Semi-Urban,Data Analyst,57669,0 +49013,Female,57,Bachelors,17,25,85,53,27,1.0,0,97,Urban,Data Analyst,137964,1 +49014,Male,33,High School,11,92,34,53,45,5.0,4,48,Urban,ML Engineer,44177,0 +49015,Male,58,Diploma,15,75,85,83,87,4.0,7,85,Urban,Data Analyst,54035,1 +49016,Male,46,Diploma,1,89,90,87,0,8.0,7,92,Urban,Manager,104751,1 +49017,Female,45,Masters,3,11,71,41,85,1.0,1,7,Semi-Urban,Data Analyst,23274,0 +49018,Female,28,Bachelors,6,81,14,25,21,7.0,2,45,Urban,HR Executive,24699,0 +49019,Male,52,High School,17,30,23,35,29,4.0,1,27,Urban,Software Engineer,88728,0 +49020,Other,57,Bachelors,4,49,3,8,8,0.0,7,75,Urban,HR Executive,104987,0 +49021,Female,32,Bachelors,7,54,30,73,94,4.0,0,65,Urban,HR Executive,142006,0 +49022,Male,55,Diploma,15,33,99,67,29,5.0,1,78,Urban,Manager,94591,1 +49023,Female,35,Diploma,14,60,5,21,28,9.0,3,59,Urban,Data Analyst,28133,0 +49024,Female,38,Diploma,14,77,10,6,87,4.0,0,93,Urban,Data Analyst,112259,0 +49025,Male,35,Diploma,15,72,86,77,21,6.0,7,83,Urban,ML Engineer,101140,1 +49026,Male,22,Bachelors,2,98,50,72,38,3.0,3,63,Semi-Urban,Manager,60469,1 +49027,Male,28,PhD,16,61,60,76,83,7.0,6,81,Urban,Software Engineer,117682,1 +49028,Female,28,Diploma,6,86,99,88,1,8.0,5,40,Rural,HR Executive,70166,1 +49029,Female,37,Bachelors,3,86,74,9,64,4.0,1,36,Urban,HR Executive,67857,0 +49030,Male,40,Masters,7,60,53,50,4,8.0,4,23,Urban,Data Analyst,143848,0 +49031,Female,24,Masters,4,87,11,2,91,5.0,5,20,Urban,Manager,106255,0 +49032,Male,39,High School,3,72,27,14,55,5.0,0,70,Semi-Urban,Data Analyst,137331,0 +49033,Male,26,Bachelors,16,61,97,99,89,4.0,4,85,Urban,HR Executive,20811,1 +49034,Female,38,Masters,15,97,37,88,43,8.0,3,10,Urban,Data Analyst,131259,0 +49035,Male,41,Bachelors,16,56,34,1,21,4.0,3,91,Rural,Manager,51530,0 +49036,Male,47,Bachelors,16,9,96,15,12,4.0,4,49,Rural,Software Engineer,142487,0 +49037,Male,32,High School,11,19,12,9,68,1.0,7,2,Urban,Data Analyst,69083,0 +49038,Male,25,High School,5,16,81,32,0,3.0,3,17,Semi-Urban,Manager,125988,0 +49039,Female,35,Masters,6,87,29,68,86,5.0,7,77,Urban,Software Engineer,61563,1 +49040,Male,39,PhD,2,90,20,63,13,4.0,4,46,Urban,HR Executive,59951,0 +49041,Female,23,Bachelors,13,83,70,95,15,2.0,6,55,Urban,Software Engineer,107749,1 +49042,Female,55,Diploma,0,59,69,67,21,2.0,5,23,Urban,ML Engineer,137638,0 +49043,Male,27,Bachelors,13,33,62,81,60,9.0,1,55,Semi-Urban,Data Analyst,125107,0 +49044,Female,34,Bachelors,1,84,36,41,76,1.0,1,46,Urban,ML Engineer,131232,0 +49045,Other,47,Bachelors,6,8,73,4,71,2.0,0,84,Semi-Urban,HR Executive,67118,0 +49046,Male,35,Bachelors,16,23,63,45,53,2.0,2,5,Urban,Data Analyst,115352,0 +49047,Male,34,High School,5,0,54,82,67,4.0,0,53,Rural,Software Engineer,147490,0 +49048,Female,53,Diploma,17,90,69,60,74,7.0,7,47,Urban,ML Engineer,65251,1 +49049,Male,50,Bachelors,5,89,53,17,40,0.0,3,65,Urban,HR Executive,137008,0 +49050,Male,44,Bachelors,7,88,38,23,75,5.0,5,15,Urban,ML Engineer,33515,0 +49051,Male,28,Masters,3,28,56,88,29,1.0,5,93,Urban,Manager,55004,1 +49052,Male,30,Diploma,6,2,64,84,88,0.0,2,98,Rural,ML Engineer,130411,1 +49053,Male,54,Masters,1,59,81,31,74,0.0,4,77,Urban,Manager,57059,1 +49054,Male,46,Masters,14,74,9,93,50,7.0,2,86,Urban,ML Engineer,86380,1 +49055,Male,33,Masters,13,13,64,70,51,3.0,3,4,Rural,ML Engineer,147144,0 +49056,Male,55,Bachelors,0,42,32,25,57,9.0,2,97,Urban,Software Engineer,84070,0 +49057,Female,24,Masters,8,62,69,23,55,5.0,7,20,Urban,HR Executive,148074,0 +49058,Female,51,PhD,12,84,11,20,76,6.0,5,22,Urban,Software Engineer,101466,0 +49059,Male,26,Diploma,15,89,93,37,60,8.0,4,47,Urban,Data Analyst,73980,1 +49060,Male,56,Masters,10,77,52,45,62,6.0,6,11,Semi-Urban,ML Engineer,96251,0 +49061,Female,27,Bachelors,7,16,15,4,58,6.0,7,43,Urban,HR Executive,23811,0 +49062,Male,25,Masters,6,88,51,8,7,4.0,3,83,Urban,Software Engineer,96961,0 +49063,Female,54,Bachelors,19,83,20,98,1,9.0,2,29,Urban,ML Engineer,62913,0 +49064,Male,53,Bachelors,1,56,90,81,37,1.0,0,6,Urban,HR Executive,91097,0 +49065,Male,32,High School,13,31,57,19,68,4.0,0,22,Urban,Manager,51661,0 +49066,Male,45,Diploma,3,26,4,6,10,7.0,1,63,Urban,HR Executive,31396,0 +49067,Female,55,PhD,13,63,55,42,88,5.0,4,32,Urban,Manager,68252,0 +49068,Male,53,Bachelors,16,92,92,17,86,8.0,7,82,Urban,ML Engineer,99656,1 +49069,Female,29,Masters,9,89,10,75,15,3.0,2,79,Semi-Urban,Data Analyst,57083,1 +49070,Male,56,Bachelors,10,84,88,65,78,7.0,1,72,Semi-Urban,Data Analyst,100433,1 +49071,Male,57,Diploma,18,85,46,56,91,1.0,2,83,Rural,Manager,107525,1 +49072,Male,59,Diploma,11,71,40,49,15,5.0,0,27,Semi-Urban,Software Engineer,85536,0 +49073,Male,48,Bachelors,18,85,84,55,61,1.0,4,81,Semi-Urban,HR Executive,37168,1 +49074,Male,44,Bachelors,2,31,19,7,61,5.0,1,21,Urban,HR Executive,132913,0 +49075,Male,43,Masters,17,0,95,9,74,7.0,6,40,Urban,Data Analyst,37311,0 +49076,Male,23,Diploma,4,98,38,34,93,1.0,4,94,Semi-Urban,Data Analyst,79242,1 +49077,Male,28,Bachelors,4,24,84,50,15,9.0,6,47,Urban,Manager,64138,0 +49078,Female,44,Bachelors,11,42,31,8,15,6.0,3,80,Urban,ML Engineer,68024,0 +49079,Female,26,Masters,4,79,85,43,93,0.0,2,54,Urban,HR Executive,89679,1 +49080,Male,27,PhD,9,40,39,88,75,1.0,6,37,Urban,Manager,130027,0 +49081,Male,40,Diploma,4,55,97,9,68,5.0,1,14,Rural,Software Engineer,130411,0 +49082,Male,47,Bachelors,10,91,56,13,49,1.0,0,20,Urban,Data Analyst,44402,0 +49083,Male,53,Bachelors,14,69,66,13,43,4.0,4,38,Semi-Urban,ML Engineer,137815,0 +49084,Male,22,High School,10,28,28,70,54,9.0,0,86,Urban,Manager,98907,0 +49085,Male,45,Masters,17,24,85,45,68,8.0,1,43,Urban,HR Executive,39284,0 +49086,Female,23,Diploma,4,59,54,38,61,9.0,2,3,Urban,ML Engineer,148462,0 +49087,Female,30,High School,3,17,74,0,64,6.0,2,14,Semi-Urban,Data Analyst,84063,0 +49088,Male,56,PhD,1,55,43,23,53,8.0,4,27,Semi-Urban,ML Engineer,116028,0 +49089,Female,34,Bachelors,12,15,3,5,42,1.0,7,94,Semi-Urban,Software Engineer,46558,0 +49090,Male,54,Bachelors,6,57,40,76,21,0.0,0,20,Urban,Data Analyst,127089,0 +49091,Male,50,Masters,16,45,91,83,26,7.0,1,89,Urban,Data Analyst,80794,1 +49092,Female,50,Bachelors,11,34,94,60,36,0.0,5,86,Rural,ML Engineer,53258,1 +49093,Male,32,Bachelors,12,89,71,29,99,0.0,5,28,Urban,Manager,50508,0 +49094,Female,58,Diploma,0,25,65,94,73,2.0,3,74,Semi-Urban,HR Executive,130710,1 +49095,Male,30,Masters,11,85,78,83,17,6.0,2,52,Semi-Urban,Data Analyst,101964,1 +49096,Female,30,High School,4,43,33,62,93,3.0,5,10,Semi-Urban,ML Engineer,127746,0 +49097,Male,22,Bachelors,6,39,95,89,7,2.0,3,46,Rural,Software Engineer,75577,1 +49098,Female,43,Masters,19,79,82,62,99,6.0,7,33,Urban,Software Engineer,52521,1 +49099,Male,29,Masters,13,91,31,24,26,6.0,7,59,Semi-Urban,Data Analyst,128197,0 +49100,Male,46,Diploma,14,99,97,52,0,0.0,4,54,Rural,HR Executive,23275,1 +49101,Female,54,High School,18,52,15,55,29,7.0,6,89,Urban,Manager,128241,0 +49102,Female,38,Diploma,2,23,3,68,67,4.0,0,31,Semi-Urban,HR Executive,24624,0 +49103,Female,38,Masters,14,19,10,18,66,1.0,5,43,Urban,Data Analyst,121357,0 +49104,Male,45,Diploma,16,22,16,72,7,0.0,6,93,Urban,HR Executive,57934,0 +49105,Male,23,Bachelors,10,61,96,96,21,1.0,1,7,Urban,Software Engineer,144283,1 +49106,Male,36,Bachelors,0,3,9,89,60,3.0,2,89,Rural,Manager,107319,0 +49107,Male,36,High School,12,94,98,10,54,9.0,7,27,Urban,ML Engineer,110643,0 +49108,Female,49,Diploma,3,29,95,28,48,8.0,3,57,Urban,Data Analyst,109552,0 +49109,Female,36,Diploma,19,79,47,99,32,9.0,6,46,Urban,Data Analyst,59018,1 +49110,Female,58,High School,13,81,21,49,56,9.0,6,12,Urban,Manager,47444,0 +49111,Male,43,Bachelors,5,8,38,65,94,2.0,2,40,Rural,Software Engineer,145098,0 +49112,Male,55,Masters,12,52,36,49,8,0.0,0,40,Urban,ML Engineer,124627,0 +49113,Female,38,Masters,18,48,16,54,48,1.0,1,48,Urban,HR Executive,72831,0 +49114,Female,59,Bachelors,4,82,45,29,6,5.0,3,45,Urban,Manager,148204,0 +49115,Female,44,Masters,0,25,69,25,20,7.0,3,85,Semi-Urban,Data Analyst,137879,0 +49116,Female,34,Bachelors,1,31,49,69,25,7.0,7,34,Urban,Software Engineer,70505,0 +49117,Female,59,Bachelors,3,29,62,79,51,4.0,0,80,Rural,Manager,32196,1 +49118,Male,50,Bachelors,10,84,80,84,36,0.0,1,15,Urban,ML Engineer,106963,1 +49119,Female,36,Masters,11,56,88,32,81,1.0,2,98,Semi-Urban,Data Analyst,111382,1 +49120,Male,36,Bachelors,17,66,35,0,67,4.0,0,90,Urban,Manager,32399,0 +49121,Female,59,Bachelors,13,96,47,84,24,7.0,6,58,Semi-Urban,Software Engineer,123820,1 +49122,Female,45,Masters,11,47,96,62,30,1.0,0,83,Semi-Urban,HR Executive,63166,1 +49123,Male,55,Bachelors,15,34,87,78,30,4.0,2,27,Semi-Urban,Data Analyst,127094,0 +49124,Male,23,Bachelors,7,90,17,11,30,2.0,1,66,Urban,ML Engineer,96087,0 +49125,Male,57,Bachelors,14,2,91,92,39,1.0,5,96,Urban,Data Analyst,39970,1 +49126,Male,22,Bachelors,3,65,50,22,45,0.0,3,61,Urban,Software Engineer,24124,0 +49127,Male,29,Bachelors,17,88,30,72,43,8.0,4,62,Rural,ML Engineer,63704,1 +49128,Male,47,Bachelors,3,53,4,78,77,1.0,0,53,Rural,Software Engineer,101953,0 +49129,Male,40,Masters,1,40,81,89,63,0.0,5,89,Rural,ML Engineer,39062,1 +49130,Male,52,Bachelors,12,67,77,79,95,2.0,7,49,Semi-Urban,ML Engineer,96113,1 +49131,Male,34,Diploma,13,17,37,10,23,0.0,6,23,Urban,Data Analyst,48782,0 +49132,Male,31,High School,6,48,4,70,14,2.0,5,88,Urban,Data Analyst,95082,0 +49133,Male,32,Diploma,10,41,93,82,59,9.0,3,53,Urban,Software Engineer,78582,1 +49134,Female,45,Bachelors,0,64,83,19,48,9.0,6,31,Urban,HR Executive,108442,0 +49135,Female,21,Masters,0,98,79,39,56,6.0,1,36,Urban,Software Engineer,34435,1 +49136,Other,48,Bachelors,5,95,89,98,66,1.0,0,93,Semi-Urban,ML Engineer,70308,1 +49137,Male,31,Bachelors,8,42,5,17,40,1.0,7,46,Urban,Manager,80558,0 +49138,Female,59,Bachelors,1,36,64,66,43,1.0,5,99,Urban,Data Analyst,28778,1 +49139,Male,26,Masters,2,15,4,17,49,4.0,6,24,Urban,ML Engineer,85321,0 +49140,Male,49,PhD,6,92,44,94,97,6.0,6,11,Urban,Manager,92345,1 +49141,Male,48,Bachelors,19,89,59,14,74,2.0,5,85,Urban,ML Engineer,131104,1 +49142,Male,46,High School,0,31,84,32,71,9.0,6,64,Rural,ML Engineer,128585,0 +49143,Male,48,Bachelors,6,14,88,30,40,7.0,5,13,Urban,ML Engineer,39680,0 +49144,Female,33,Diploma,2,15,62,92,49,9.0,6,9,Rural,Data Analyst,115525,0 +49145,Female,29,High School,10,66,85,35,70,9.0,0,18,Urban,HR Executive,29438,0 +49146,Other,27,Bachelors,8,54,32,4,93,4.0,1,71,Urban,Manager,147981,0 +49147,Female,40,Diploma,2,88,91,85,17,6.0,6,11,Rural,HR Executive,94308,1 +49148,Female,21,Bachelors,1,12,14,14,42,5.0,4,0,Urban,ML Engineer,120119,0 +49149,Male,31,Diploma,16,37,13,85,18,2.0,6,92,Urban,Manager,33755,0 +49150,Female,55,Masters,8,84,19,14,66,7.0,4,87,Urban,HR Executive,47783,0 +49151,Female,21,High School,6,12,58,61,64,6.0,1,40,Rural,Software Engineer,117254,0 +49152,Male,23,High School,14,4,64,39,7,0.0,4,12,Urban,HR Executive,133303,0 +49153,Female,29,Diploma,14,85,12,11,1,5.0,1,57,Urban,Data Analyst,27241,0 +49154,Male,50,Bachelors,6,74,59,44,11,3.0,2,23,Semi-Urban,HR Executive,144476,0 +49155,Male,41,Diploma,11,2,85,27,51,0.0,4,86,Urban,Software Engineer,125867,0 +49156,Female,36,Bachelors,11,92,25,88,43,0.0,2,11,Rural,ML Engineer,21382,0 +49157,Female,59,Bachelors,15,20,66,84,23,0.0,5,87,Urban,Software Engineer,25906,1 +49158,Female,31,Bachelors,17,15,51,45,8,2.0,6,92,Semi-Urban,HR Executive,100175,0 +49159,Female,48,Bachelors,16,70,65,81,50,6.0,2,30,Urban,ML Engineer,135605,1 +49160,Male,41,Bachelors,3,49,31,42,75,4.0,2,3,Urban,Data Analyst,55821,0 +49161,Male,31,Bachelors,4,98,98,84,32,9.0,4,92,Rural,Data Analyst,102312,1 +49162,Male,45,High School,17,14,29,3,64,0.0,0,63,Urban,Software Engineer,108440,0 +49163,Female,53,Diploma,5,42,88,38,97,4.0,5,36,Urban,HR Executive,107884,0 +49164,Male,44,Diploma,18,33,60,59,9,9.0,0,37,Semi-Urban,Data Analyst,141594,0 +49165,Female,56,High School,15,52,26,71,90,3.0,6,50,Urban,HR Executive,137238,0 +49166,Male,57,High School,19,86,37,27,4,1.0,5,22,Semi-Urban,Data Analyst,65289,0 +49167,Female,32,High School,6,81,89,50,75,7.0,4,56,Urban,HR Executive,24066,1 +49168,Male,34,Masters,17,10,34,43,9,5.0,1,72,Urban,Software Engineer,114329,0 +49169,Male,49,Bachelors,18,92,80,89,37,1.0,0,21,Rural,HR Executive,79766,1 +49170,Male,24,Diploma,5,28,5,91,74,3.0,4,34,Urban,Data Analyst,146658,0 +49171,Male,23,Bachelors,5,21,41,39,26,7.0,5,44,Urban,Data Analyst,110899,0 +49172,Male,51,Bachelors,11,50,32,48,10,6.0,4,99,Rural,Data Analyst,40608,0 +49173,Female,49,Masters,12,32,40,91,1,0.0,6,86,Urban,Data Analyst,80944,1 +49174,Male,54,Diploma,16,26,65,28,71,6.0,6,71,Urban,HR Executive,23060,0 +49175,Female,25,Diploma,10,84,79,98,77,9.0,3,78,Urban,Data Analyst,79333,1 +49176,Female,30,Bachelors,14,18,98,95,13,7.0,5,73,Rural,ML Engineer,44955,1 +49177,Female,42,Bachelors,2,74,47,53,97,7.0,7,6,Urban,HR Executive,28207,0 +49178,Male,58,Diploma,13,20,1,10,40,8.0,1,52,Urban,Data Analyst,71966,0 +49179,Female,58,Bachelors,8,20,30,51,93,2.0,6,97,Semi-Urban,Data Analyst,101218,0 +49180,Male,56,Bachelors,7,70,83,11,72,4.0,0,72,Semi-Urban,Manager,85903,1 +49181,Male,41,Masters,6,92,38,83,15,8.0,4,9,Semi-Urban,Software Engineer,54664,0 +49182,Male,22,High School,7,97,14,77,34,5.0,1,75,Semi-Urban,HR Executive,99190,1 +49183,Male,56,Masters,7,45,6,36,59,8.0,6,29,Rural,Manager,58894,0 +49184,Female,33,Bachelors,15,53,10,32,17,0.0,4,79,Urban,Data Analyst,21933,0 +49185,Male,25,Bachelors,8,38,84,89,75,1.0,0,42,Urban,Manager,102388,1 +49186,Male,51,Bachelors,10,42,4,57,76,4.0,7,69,Rural,HR Executive,51323,0 +49187,Male,22,High School,16,42,27,32,49,6.0,0,47,Semi-Urban,HR Executive,57675,0 +49188,Male,28,Masters,2,98,28,11,69,3.0,5,77,Semi-Urban,HR Executive,64806,0 +49189,Male,43,Bachelors,13,50,62,9,30,3.0,6,5,Semi-Urban,Manager,81984,0 +49190,Male,54,Diploma,2,98,95,33,71,0.0,6,8,Urban,Software Engineer,22694,0 +49191,Male,40,Diploma,3,35,89,46,81,5.0,5,47,Urban,Data Analyst,100624,0 +49192,Female,52,Masters,0,36,31,33,28,2.0,5,37,Urban,HR Executive,65614,0 +49193,Female,33,Diploma,8,67,55,6,47,0.0,0,83,Rural,Software Engineer,46624,0 +49194,Male,28,High School,15,73,41,15,71,4.0,3,1,Semi-Urban,Data Analyst,93243,0 +49195,Female,45,Bachelors,18,73,24,2,33,5.0,4,34,Semi-Urban,Software Engineer,109893,0 +49196,Male,35,High School,11,30,60,34,13,5.0,3,1,Semi-Urban,Manager,20993,0 +49197,Female,31,Bachelors,15,6,40,9,30,1.0,4,63,Semi-Urban,Software Engineer,82651,0 +49198,Male,56,PhD,13,94,9,17,22,5.0,4,97,Urban,Software Engineer,132891,0 +49199,Female,40,Masters,19,18,67,66,15,2.0,7,38,Urban,ML Engineer,114101,0 +49200,Male,55,Diploma,2,64,88,48,93,2.0,1,22,Rural,Data Analyst,35746,0 +49201,Male,41,Diploma,9,47,47,77,62,7.0,7,85,Semi-Urban,HR Executive,58436,1 +49202,Male,52,High School,9,90,43,32,16,8.0,5,29,Urban,Software Engineer,27264,0 +49203,Male,48,Masters,15,57,84,28,65,9.0,1,43,Semi-Urban,Software Engineer,45114,0 +49204,Female,37,Diploma,2,65,77,3,98,7.0,3,64,Rural,HR Executive,75519,0 +49205,Female,59,Diploma,19,46,19,64,22,8.0,7,94,Urban,HR Executive,54216,0 +49206,Male,36,Masters,9,78,95,80,83,9.0,4,49,Urban,ML Engineer,97915,1 +49207,Male,32,High School,14,90,70,19,70,8.0,2,74,Urban,ML Engineer,146532,1 +49208,Male,26,Bachelors,6,16,28,86,56,7.0,2,39,Urban,HR Executive,129612,0 +49209,Male,54,Bachelors,9,29,25,64,9,9.0,3,96,Urban,HR Executive,106796,0 +49210,Male,47,Bachelors,1,75,70,49,46,4.0,4,68,Semi-Urban,Data Analyst,133033,1 +49211,Male,29,Bachelors,2,10,3,81,81,5.0,7,92,Urban,ML Engineer,140764,0 +49212,Female,24,Bachelors,18,96,38,8,13,9.0,2,47,Semi-Urban,ML Engineer,75564,0 +49213,Male,57,Bachelors,12,14,28,70,79,2.0,4,87,Rural,Software Engineer,122782,0 +49214,Female,31,Bachelors,11,9,84,44,36,0.0,2,80,Rural,HR Executive,74250,0 +49215,Female,24,Bachelors,11,15,83,97,80,2.0,7,95,Urban,ML Engineer,21245,1 +49216,Male,40,Diploma,7,20,51,67,63,8.0,6,45,Semi-Urban,Manager,32435,0 +49217,Male,35,Masters,3,36,62,12,58,7.0,4,61,Rural,Manager,23865,0 +49218,Female,36,Bachelors,15,74,33,90,93,2.0,6,64,Urban,Manager,24968,1 +49219,Male,53,High School,18,10,34,91,13,4.0,1,34,Urban,Software Engineer,86671,0 +49220,Male,47,Masters,8,4,91,76,66,1.0,1,35,Semi-Urban,Manager,89732,0 +49221,Female,55,Diploma,14,25,69,5,48,6.0,3,18,Urban,Software Engineer,53703,0 +49222,Male,47,High School,4,35,55,75,15,8.0,3,76,Urban,Data Analyst,27043,1 +49223,Female,54,Masters,7,73,63,52,8,2.0,7,67,Semi-Urban,Data Analyst,72581,1 +49224,Male,21,Masters,8,77,20,24,34,0.0,6,70,Urban,Manager,83910,0 +49225,Female,25,Bachelors,18,74,15,19,84,2.0,1,61,Rural,HR Executive,52425,0 +49226,Female,40,Bachelors,3,85,4,10,46,2.0,5,37,Urban,Data Analyst,126130,0 +49227,Male,52,High School,2,38,12,39,11,2.0,5,65,Urban,Data Analyst,64203,0 +49228,Female,34,Diploma,2,48,98,91,75,0.0,4,9,Rural,Software Engineer,110280,1 +49229,Female,33,Bachelors,7,53,20,78,79,5.0,5,14,Urban,Software Engineer,93660,0 +49230,Male,52,Bachelors,1,2,35,54,76,2.0,5,62,Semi-Urban,Data Analyst,28046,0 +49231,Female,44,Masters,4,95,91,34,31,4.0,7,1,Urban,Software Engineer,97154,0 +49232,Male,57,Masters,10,27,77,98,56,9.0,4,49,Rural,Manager,104831,1 +49233,Female,24,Diploma,7,16,79,67,51,1.0,6,46,Urban,HR Executive,82678,0 +49234,Male,57,Bachelors,4,34,25,25,57,0.0,0,14,Rural,ML Engineer,112964,0 +49235,Male,48,High School,15,80,65,24,66,5.0,0,5,Semi-Urban,Software Engineer,27260,0 +49236,Male,23,Diploma,5,59,52,63,88,7.0,2,45,Urban,HR Executive,23821,0 +49237,Male,33,Masters,19,24,62,40,82,4.0,6,78,Urban,Software Engineer,107015,0 +49238,Female,36,Bachelors,9,12,36,94,68,7.0,1,96,Rural,HR Executive,30209,0 +49239,Male,48,Diploma,14,5,83,66,91,8.0,5,93,Urban,HR Executive,124613,1 +49240,Male,24,Bachelors,17,90,81,48,99,0.0,6,48,Urban,Software Engineer,89038,1 +49241,Male,24,Diploma,9,38,75,9,17,3.0,7,71,Rural,ML Engineer,64518,0 +49242,Male,57,Bachelors,4,5,88,41,82,7.0,2,97,Urban,HR Executive,51758,0 +49243,Male,53,PhD,6,95,50,19,26,7.0,0,59,Urban,HR Executive,31951,0 +49244,Male,54,Diploma,6,33,95,0,85,0.0,5,90,Rural,Software Engineer,75913,0 +49245,Female,47,Bachelors,17,16,55,28,47,9.0,2,96,Rural,Manager,50220,0 +49246,Male,35,Masters,0,10,36,69,15,8.0,2,19,Urban,HR Executive,142282,0 +49247,Female,58,Bachelors,9,48,40,94,33,2.0,5,69,Semi-Urban,Data Analyst,107636,1 +49248,Female,37,Masters,9,25,5,45,86,8.0,4,55,Semi-Urban,Data Analyst,113748,0 +49249,Male,52,Bachelors,6,1,23,78,74,1.0,7,15,Semi-Urban,Software Engineer,116528,0 +49250,Female,58,Masters,16,21,13,91,6,9.0,4,54,Rural,Data Analyst,103571,0 +49251,Male,31,Bachelors,2,27,51,14,2,9.0,7,50,Rural,Manager,79621,0 +49252,Male,46,PhD,3,76,23,44,25,7.0,2,73,Urban,Manager,104155,0 +49253,Male,54,Diploma,17,0,61,34,58,7.0,2,23,Semi-Urban,HR Executive,106008,0 +49254,Male,52,High School,2,7,99,17,14,8.0,0,60,Urban,Manager,142303,0 +49255,Male,21,Bachelors,12,23,78,76,64,9.0,0,63,Urban,Data Analyst,113959,1 +49256,Female,47,Diploma,4,14,14,37,25,0.0,2,24,Semi-Urban,ML Engineer,116124,0 +49257,Female,31,Bachelors,14,39,31,57,50,8.0,0,63,Rural,Manager,70849,0 +49258,Female,27,Bachelors,18,83,30,93,6,1.0,0,61,Semi-Urban,Data Analyst,92501,1 +49259,Male,29,Masters,4,58,52,8,47,0.0,4,4,Urban,Software Engineer,113976,0 +49260,Female,34,Masters,3,46,81,72,38,6.0,6,59,Urban,HR Executive,78295,1 +49261,Female,43,Bachelors,10,21,81,95,63,6.0,2,49,Semi-Urban,Data Analyst,44882,1 +49262,Male,29,Masters,4,61,11,92,26,3.0,0,60,Urban,Manager,35465,0 +49263,Male,40,Bachelors,1,60,40,32,44,3.0,4,88,Rural,ML Engineer,139329,0 +49264,Male,25,Masters,13,48,45,10,58,8.0,5,3,Rural,HR Executive,71256,0 +49265,Male,30,Bachelors,13,64,3,49,92,7.0,3,49,Rural,Manager,49455,0 +49266,Female,48,High School,12,21,63,58,9,9.0,2,46,Rural,Software Engineer,25583,0 +49267,Female,51,Bachelors,10,55,17,67,24,9.0,3,30,Semi-Urban,Software Engineer,33194,0 +49268,Male,29,High School,15,63,82,39,82,0.0,0,73,Semi-Urban,ML Engineer,112012,1 +49269,Female,29,Masters,9,23,20,86,24,1.0,4,36,Urban,Software Engineer,132787,0 +49270,Female,29,Diploma,11,97,44,62,14,4.0,3,30,Urban,Manager,64503,0 +49271,Female,44,Diploma,14,17,25,53,83,9.0,0,48,Semi-Urban,Software Engineer,91112,0 +49272,Male,37,Masters,4,49,53,34,30,5.0,6,75,Rural,HR Executive,25222,0 +49273,Male,24,Masters,9,35,86,85,69,4.0,6,11,Urban,HR Executive,31582,0 +49274,Male,37,Bachelors,15,87,17,36,15,3.0,3,49,Urban,Software Engineer,149663,0 +49275,Female,21,PhD,4,74,77,86,92,6.0,4,47,Urban,Software Engineer,21777,1 +49276,Female,55,Masters,5,1,76,69,78,7.0,0,42,Semi-Urban,Software Engineer,136181,0 +49277,Male,25,Diploma,0,39,45,44,95,3.0,3,48,Urban,ML Engineer,128009,0 +49278,Male,53,High School,14,73,6,76,73,0.0,0,34,Urban,Software Engineer,27059,0 +49279,Female,32,Bachelors,6,18,55,18,45,4.0,7,18,Rural,HR Executive,149469,0 +49280,Male,47,Diploma,7,62,49,27,4,7.0,6,70,Urban,HR Executive,130105,0 +49281,Male,28,Bachelors,5,81,72,19,11,1.0,4,90,Urban,Data Analyst,113934,1 +49282,Male,30,PhD,6,76,55,73,42,8.0,7,81,Semi-Urban,ML Engineer,112377,1 +49283,Male,42,Masters,2,4,33,56,29,0.0,6,42,Rural,HR Executive,29587,0 +49284,Male,41,Masters,13,58,50,25,19,1.0,4,50,Urban,Data Analyst,132622,0 +49285,Male,42,High School,11,96,52,47,28,5.0,6,52,Urban,Software Engineer,92888,1 +49286,Female,25,Bachelors,5,69,14,0,93,3.0,3,51,Urban,Software Engineer,31042,0 +49287,Other,23,Bachelors,1,49,35,55,16,9.0,1,55,Semi-Urban,ML Engineer,91619,0 +49288,Male,50,Bachelors,11,70,21,41,66,6.0,1,42,Semi-Urban,ML Engineer,126556,0 +49289,Male,27,PhD,5,89,36,35,39,4.0,6,84,Semi-Urban,Manager,105570,1 +49290,Male,46,Bachelors,9,89,17,20,99,9.0,0,59,Urban,Manager,108484,0 +49291,Male,37,Masters,7,60,11,86,78,0.0,5,48,Urban,Data Analyst,141729,0 +49292,Female,36,High School,3,62,44,81,95,9.0,0,94,Urban,Data Analyst,92131,1 +49293,Male,27,Bachelors,7,98,92,14,54,7.0,6,42,Urban,Software Engineer,78935,1 +49294,Male,49,Bachelors,6,92,54,10,7,7.0,5,99,Urban,ML Engineer,118760,1 +49295,Female,33,High School,17,24,48,36,34,2.0,7,14,Urban,HR Executive,66771,0 +49296,Female,43,Diploma,7,15,52,53,16,8.0,6,45,Semi-Urban,HR Executive,35915,0 +49297,Male,51,High School,18,41,95,63,71,6.0,4,44,Semi-Urban,HR Executive,31313,1 +49298,Male,25,Bachelors,1,54,72,88,75,8.0,3,87,Urban,Software Engineer,88126,1 +49299,Male,52,Bachelors,12,60,65,86,18,1.0,6,64,Urban,HR Executive,126899,1 +49300,Male,26,Bachelors,18,99,95,25,61,2.0,0,83,Rural,Software Engineer,142694,1 +49301,Male,29,Bachelors,19,68,63,71,46,8.0,0,76,Semi-Urban,Data Analyst,127613,1 +49302,Female,27,Bachelors,5,67,15,45,34,5.0,1,92,Urban,ML Engineer,35972,0 +49303,Male,56,Bachelors,6,99,28,49,12,1.0,4,70,Urban,ML Engineer,56846,1 +49304,Female,33,Bachelors,16,94,7,91,6,8.0,0,64,Semi-Urban,Software Engineer,123762,1 +49305,Female,46,High School,16,27,78,51,54,0.0,2,83,Urban,ML Engineer,98773,0 +49306,Male,30,High School,0,39,98,35,77,1.0,2,56,Semi-Urban,Software Engineer,69993,0 +49307,Male,21,Bachelors,17,89,92,11,89,4.0,6,63,Semi-Urban,HR Executive,49457,1 +49308,Female,27,High School,4,0,15,27,75,3.0,7,48,Urban,Software Engineer,64000,0 +49309,Male,43,Masters,13,85,85,48,50,5.0,4,54,Semi-Urban,Data Analyst,21533,1 +49310,Male,30,Bachelors,13,75,87,3,2,2.0,6,24,Urban,Data Analyst,33930,0 +49311,Male,23,Bachelors,13,39,53,6,60,9.0,5,7,Urban,Data Analyst,102507,0 +49312,Female,29,Bachelors,5,12,58,81,1,6.0,2,14,Urban,Data Analyst,43660,0 +49313,Male,29,Diploma,1,46,36,12,92,1.0,4,87,Rural,Data Analyst,42923,0 +49314,Male,29,Bachelors,3,70,77,86,28,7.0,2,39,Urban,HR Executive,122453,1 +49315,Female,29,High School,4,3,69,9,15,7.0,1,17,Rural,ML Engineer,82626,0 +49316,Female,41,PhD,16,63,13,25,82,3.0,1,81,Rural,Manager,147980,0 +49317,Female,31,Bachelors,16,53,73,62,4,9.0,3,66,Urban,Data Analyst,106481,1 +49318,Female,33,High School,7,83,8,9,45,3.0,5,19,Urban,Data Analyst,48654,0 +49319,Male,41,Masters,15,44,55,63,70,0.0,1,21,Semi-Urban,Manager,67413,0 +49320,Other,45,Bachelors,12,84,11,55,35,2.0,4,56,Urban,Software Engineer,121741,0 +49321,Male,54,Bachelors,11,95,93,12,72,5.0,6,46,Urban,Manager,92570,1 +49322,Female,51,Masters,6,74,20,23,36,0.0,3,41,Semi-Urban,Manager,136432,0 +49323,Male,45,Bachelors,15,34,8,59,57,9.0,7,13,Rural,Software Engineer,35584,0 +49324,Female,28,Bachelors,14,63,16,69,31,8.0,5,75,Urban,Data Analyst,102664,0 +49325,Female,58,High School,16,30,75,78,96,9.0,5,15,Semi-Urban,Manager,23926,0 +49326,Male,42,Masters,10,84,99,91,93,5.0,0,88,Rural,Data Analyst,107163,1 +49327,Female,43,Bachelors,2,46,34,7,92,0.0,3,38,Urban,Data Analyst,67529,0 +49328,Female,59,Diploma,0,62,47,80,6,3.0,7,70,Semi-Urban,HR Executive,56672,1 +49329,Male,44,Diploma,4,27,78,80,97,1.0,6,58,Urban,Data Analyst,74096,1 +49330,Male,55,Bachelors,18,9,49,32,10,8.0,6,50,Urban,Data Analyst,144448,0 +49331,Female,34,PhD,10,46,65,35,79,4.0,0,92,Rural,Software Engineer,38949,0 +49332,Female,28,Bachelors,10,22,79,29,76,6.0,4,28,Rural,Software Engineer,80466,0 +49333,Male,27,Masters,11,52,78,65,96,8.0,4,61,Urban,Data Analyst,122270,1 +49334,Male,26,Bachelors,6,25,84,0,30,4.0,4,11,Urban,Manager,146414,0 +49335,Female,49,Bachelors,11,17,28,26,95,7.0,3,88,Rural,Data Analyst,26486,0 +49336,Male,25,Bachelors,13,75,50,25,82,5.0,3,86,Semi-Urban,ML Engineer,60154,1 +49337,Male,40,Masters,3,92,83,58,86,0.0,5,70,Urban,Manager,44247,1 +49338,Male,47,High School,3,92,75,2,13,4.0,1,99,Urban,Manager,104859,1 +49339,Male,44,Bachelors,11,43,12,99,88,7.0,6,47,Urban,Data Analyst,134788,0 +49340,Female,39,Diploma,7,42,10,47,62,4.0,2,22,Rural,Software Engineer,74964,0 +49341,Male,30,Masters,13,94,90,82,61,8.0,5,20,Semi-Urban,HR Executive,102510,1 +49342,Male,45,High School,16,60,4,38,40,6.0,7,20,Urban,HR Executive,30410,0 +49343,Male,43,Masters,7,27,41,90,19,1.0,1,88,Semi-Urban,HR Executive,115066,1 +49344,Male,32,Bachelors,10,17,98,10,43,0.0,7,47,Urban,Data Analyst,46062,0 +49345,Female,41,High School,4,17,0,45,86,8.0,0,17,Semi-Urban,HR Executive,120244,0 +49346,Male,29,Bachelors,4,44,43,29,2,0.0,7,31,Rural,Software Engineer,95857,0 +49347,Female,37,Bachelors,13,60,71,27,87,7.0,6,76,Urban,ML Engineer,131877,0 +49348,Female,31,Bachelors,4,93,65,71,73,5.0,1,84,Urban,HR Executive,80655,1 +49349,Male,34,Masters,4,60,39,36,32,4.0,0,13,Semi-Urban,Data Analyst,69906,0 +49350,Other,32,Bachelors,16,17,21,99,79,1.0,3,25,Rural,Data Analyst,141243,0 +49351,Male,32,Masters,18,18,98,15,93,3.0,4,49,Semi-Urban,Manager,114310,0 +49352,Female,34,Bachelors,10,34,40,23,74,4.0,4,31,Semi-Urban,Data Analyst,106068,0 +49353,Male,49,Bachelors,10,36,56,62,45,2.0,0,91,Urban,Data Analyst,63550,1 +49354,Male,33,Bachelors,17,95,8,55,25,3.0,7,54,Urban,Manager,137175,0 +49355,Female,37,Diploma,1,93,2,57,91,9.0,3,77,Semi-Urban,Manager,85846,0 +49356,Male,49,Bachelors,0,95,24,65,27,0.0,6,40,Rural,Software Engineer,131869,0 +49357,Male,49,Bachelors,3,34,45,23,98,8.0,4,81,Urban,Software Engineer,34679,0 +49358,Male,40,Diploma,2,43,86,66,88,4.0,4,41,Rural,ML Engineer,77251,1 +49359,Male,37,High School,16,86,49,79,94,3.0,3,15,Semi-Urban,ML Engineer,83135,0 +49360,Male,53,Masters,11,12,54,68,78,3.0,6,54,Rural,HR Executive,69141,0 +49361,Male,54,PhD,17,73,30,54,12,3.0,1,64,Semi-Urban,Software Engineer,88356,0 +49362,Female,39,Bachelors,12,43,9,28,70,8.0,0,83,Urban,ML Engineer,54915,0 +49363,Male,43,Bachelors,1,2,17,95,43,5.0,1,1,Urban,Data Analyst,49863,0 +49364,Male,31,High School,15,51,6,30,0,3.0,5,43,Urban,HR Executive,110046,0 +49365,Female,40,Bachelors,5,9,39,21,10,0.0,4,41,Urban,Data Analyst,34530,0 +49366,Female,37,Bachelors,9,48,15,68,97,9.0,2,45,Semi-Urban,ML Engineer,109811,0 +49367,Male,33,Bachelors,17,74,88,83,87,3.0,4,98,Urban,HR Executive,106364,1 +49368,Female,54,Bachelors,18,59,47,11,8,4.0,3,52,Semi-Urban,ML Engineer,79610,0 +49369,Male,33,Bachelors,3,21,10,73,37,7.0,3,98,Rural,ML Engineer,86800,0 +49370,Female,37,Diploma,9,61,42,16,23,9.0,0,40,Semi-Urban,Manager,42829,0 +49371,Male,54,Bachelors,16,53,46,50,72,8.0,6,19,Rural,Data Analyst,80934,0 +49372,Male,47,High School,17,1,65,20,84,2.0,0,29,Urban,HR Executive,122069,0 +49373,Male,25,Diploma,3,17,34,69,27,3.0,1,83,Urban,HR Executive,85395,0 +49374,Female,48,Masters,11,33,16,78,41,2.0,2,98,Semi-Urban,Manager,139302,0 +49375,Male,59,Bachelors,14,99,72,76,33,3.0,0,11,Urban,ML Engineer,22688,1 +49376,Other,32,PhD,9,79,11,99,47,9.0,5,23,Urban,Manager,23861,0 +49377,Female,45,Bachelors,4,99,81,2,71,3.0,5,86,Urban,ML Engineer,65457,1 +49378,Other,29,Masters,11,94,67,2,35,9.0,5,11,Urban,Manager,70938,0 +49379,Male,42,High School,18,57,91,45,63,8.0,7,21,Semi-Urban,ML Engineer,75962,0 +49380,Female,26,Bachelors,12,61,49,10,38,2.0,2,90,Semi-Urban,Software Engineer,27909,0 +49381,Male,25,Masters,12,76,37,82,14,9.0,6,95,Rural,Data Analyst,47304,1 +49382,Male,52,High School,8,45,4,65,63,4.0,1,18,Semi-Urban,Software Engineer,26456,0 +49383,Male,57,Bachelors,7,81,76,55,29,4.0,0,15,Semi-Urban,Data Analyst,61708,0 +49384,Male,46,Bachelors,17,89,24,48,16,9.0,2,68,Semi-Urban,HR Executive,55927,0 +49385,Female,59,Masters,16,23,60,60,33,2.0,7,52,Rural,Software Engineer,102072,0 +49386,Other,45,Masters,15,61,59,25,15,9.0,6,89,Urban,Manager,116825,0 +49387,Male,44,Diploma,6,37,99,81,92,0.0,3,83,Semi-Urban,Manager,94482,1 +49388,Male,54,Diploma,19,54,95,18,94,1.0,7,88,Semi-Urban,Data Analyst,125475,1 +49389,Female,36,Bachelors,12,32,12,35,36,7.0,5,53,Urban,Manager,74262,0 +49390,Male,39,Diploma,19,78,68,70,40,6.0,6,96,Semi-Urban,ML Engineer,113093,1 +49391,Female,39,Bachelors,3,99,15,31,62,5.0,7,64,Urban,Data Analyst,117913,0 +49392,Female,22,High School,7,33,52,40,88,1.0,0,3,Rural,ML Engineer,29506,0 +49393,Male,31,High School,6,72,20,5,33,3.0,0,97,Urban,Manager,134913,0 +49394,Female,23,Diploma,7,86,59,52,68,7.0,6,48,Semi-Urban,Software Engineer,119303,1 +49395,Female,27,Diploma,12,24,4,39,56,9.0,7,14,Rural,Manager,26970,0 +49396,Female,32,Masters,8,86,74,90,31,3.0,3,68,Rural,Software Engineer,146827,1 +49397,Male,40,Diploma,6,95,53,68,33,7.0,5,53,Urban,Data Analyst,127369,1 +49398,Female,36,Bachelors,8,65,84,49,43,9.0,6,89,Semi-Urban,ML Engineer,86683,1 +49399,Male,51,High School,6,19,14,93,21,6.0,0,28,Urban,Manager,40468,0 +49400,Female,47,Bachelors,8,70,55,2,24,9.0,3,28,Urban,Data Analyst,73853,0 +49401,Male,39,Masters,6,56,19,3,37,7.0,6,58,Semi-Urban,Data Analyst,119775,0 +49402,Male,40,Masters,9,87,50,5,45,1.0,6,22,Urban,Software Engineer,45791,0 +49403,Female,41,Diploma,17,86,35,33,54,9.0,5,57,Urban,ML Engineer,26539,0 +49404,Male,37,High School,8,93,64,55,77,8.0,5,7,Urban,ML Engineer,106252,0 +49405,Male,42,Diploma,18,34,97,53,44,0.0,0,31,Urban,Data Analyst,133516,0 +49406,Male,34,Bachelors,16,10,34,89,77,7.0,4,73,Urban,HR Executive,137045,0 +49407,Male,53,Masters,15,54,92,76,54,4.0,0,10,Rural,ML Engineer,119935,0 +49408,Male,30,Masters,1,71,82,75,7,4.0,2,10,Rural,Data Analyst,139586,1 +49409,Male,58,Masters,5,27,2,59,69,4.0,6,15,Urban,Software Engineer,95827,0 +49410,Male,40,Bachelors,18,69,71,13,63,3.0,6,13,Rural,HR Executive,29619,0 +49411,Male,46,Diploma,11,98,19,39,62,6.0,4,75,Urban,ML Engineer,79148,0 +49412,Male,33,Diploma,17,21,99,16,86,4.0,6,10,Urban,Manager,88994,0 +49413,Male,45,Masters,17,14,99,20,56,5.0,3,24,Urban,HR Executive,32074,0 +49414,Male,22,PhD,2,92,98,98,17,5.0,1,43,Semi-Urban,Data Analyst,65385,1 +49415,Male,48,High School,10,15,51,38,97,0.0,1,89,Urban,HR Executive,55046,0 +49416,Female,43,Diploma,6,1,37,73,26,1.0,3,15,Urban,Data Analyst,93325,0 +49417,Male,43,Bachelors,1,79,47,22,62,5.0,5,17,Urban,HR Executive,40267,0 +49418,Female,22,Diploma,3,61,88,34,34,5.0,0,5,Urban,Manager,98676,0 +49419,Female,39,Bachelors,13,84,66,19,53,3.0,4,75,Semi-Urban,Software Engineer,125745,1 +49420,Male,56,Masters,13,9,25,20,72,4.0,5,56,Urban,Software Engineer,80744,0 +49421,Male,51,High School,14,46,48,56,79,6.0,2,94,Rural,Data Analyst,80151,1 +49422,Male,41,Diploma,6,40,86,7,10,1.0,7,80,Urban,Data Analyst,121972,0 +49423,Male,26,High School,5,13,41,3,23,9.0,6,21,Urban,ML Engineer,73322,0 +49424,Male,53,Diploma,15,26,70,59,21,5.0,0,8,Urban,Manager,101613,0 +49425,Female,45,Diploma,1,22,79,60,51,1.0,7,46,Urban,ML Engineer,115222,0 +49426,Male,29,Diploma,8,45,87,68,63,2.0,7,24,Rural,Data Analyst,82859,0 +49427,Male,43,Bachelors,19,50,27,74,81,1.0,1,22,Urban,Software Engineer,46389,0 +49428,Female,59,Bachelors,16,1,34,74,58,0.0,3,28,Rural,HR Executive,33161,0 +49429,Female,48,Masters,0,94,81,91,90,9.0,5,11,Urban,ML Engineer,26803,1 +49430,Male,48,High School,16,6,93,79,52,1.0,2,22,Urban,HR Executive,57914,0 +49431,Male,47,High School,18,40,65,24,7,1.0,6,6,Urban,ML Engineer,134812,0 +49432,Female,59,Diploma,15,44,41,38,38,2.0,4,43,Urban,HR Executive,119561,0 +49433,Male,58,Bachelors,0,43,28,85,9,1.0,4,81,Semi-Urban,HR Executive,119068,1 +49434,Female,34,Masters,4,35,66,49,66,3.0,5,74,Urban,ML Engineer,20359,0 +49435,Male,55,Masters,17,77,77,20,51,0.0,5,55,Rural,ML Engineer,128276,0 +49436,Male,43,Bachelors,18,11,53,8,87,6.0,3,96,Urban,ML Engineer,120044,0 +49437,Male,57,Diploma,1,78,37,19,17,3.0,2,2,Urban,Software Engineer,125533,0 +49438,Female,52,Diploma,8,90,64,18,51,5.0,3,56,Semi-Urban,HR Executive,71903,0 +49439,Female,31,Bachelors,16,28,69,10,58,8.0,1,69,Rural,HR Executive,25074,0 +49440,Male,26,Masters,2,71,15,73,26,7.0,6,22,Urban,Manager,138479,0 +49441,Male,28,Diploma,15,36,14,13,42,3.0,1,68,Rural,Manager,80096,0 +49442,Male,49,Bachelors,19,2,5,11,10,0.0,5,28,Urban,HR Executive,115215,0 +49443,Female,33,Masters,5,63,16,29,67,5.0,1,93,Urban,ML Engineer,146089,0 +49444,Male,29,Diploma,4,58,30,82,80,5.0,0,1,Urban,Manager,142447,0 +49445,Female,55,Diploma,0,60,23,76,11,2.0,3,20,Urban,ML Engineer,71870,0 +49446,Female,32,Bachelors,19,58,1,15,68,1.0,7,96,Urban,Data Analyst,62664,0 +49447,Male,42,Bachelors,16,84,28,53,27,7.0,5,63,Semi-Urban,HR Executive,100475,0 +49448,Female,31,Diploma,4,21,53,54,50,7.0,0,93,Urban,ML Engineer,120306,0 +49449,Male,35,High School,7,4,90,50,10,4.0,2,54,Semi-Urban,ML Engineer,144377,0 +49450,Male,35,Diploma,1,83,2,7,22,5.0,3,2,Urban,ML Engineer,114768,0 +49451,Female,40,Diploma,9,98,95,36,17,7.0,4,75,Urban,ML Engineer,23011,1 +49452,Male,46,High School,19,95,74,65,96,1.0,2,56,Semi-Urban,Data Analyst,74570,1 +49453,Female,47,Bachelors,4,63,47,64,16,6.0,2,9,Urban,Software Engineer,62328,0 +49454,Male,57,Masters,7,70,82,33,7,4.0,1,95,Urban,ML Engineer,88061,1 +49455,Male,52,Diploma,12,12,72,7,62,0.0,0,66,Urban,ML Engineer,28992,0 +49456,Other,27,Bachelors,3,31,30,4,86,5.0,4,83,Urban,ML Engineer,56781,0 +49457,Female,53,Bachelors,15,69,85,98,9,4.0,5,96,Urban,Manager,48132,1 +49458,Female,34,Bachelors,7,45,93,0,80,2.0,4,39,Rural,HR Executive,139733,0 +49459,Male,56,Masters,3,65,38,94,76,2.0,5,11,Rural,Manager,26088,0 +49460,Male,48,Bachelors,9,38,36,0,3,8.0,2,62,Semi-Urban,Manager,50473,0 +49461,Female,35,Bachelors,18,14,7,98,57,9.0,1,7,Rural,HR Executive,116135,0 +49462,Male,47,Diploma,8,38,18,63,1,3.0,2,7,Semi-Urban,Manager,31097,0 +49463,Other,32,Masters,0,21,49,69,43,9.0,7,98,Rural,Manager,84439,0 +49464,Male,33,Diploma,9,86,87,55,44,2.0,2,54,Urban,HR Executive,37144,1 +49465,Male,55,Masters,13,52,70,81,60,5.0,3,33,Urban,Data Analyst,137363,1 +49466,Male,22,High School,14,52,18,26,78,0.0,7,27,Urban,ML Engineer,131845,0 +49467,Male,32,Masters,18,18,42,9,37,7.0,4,10,Urban,ML Engineer,49243,0 +49468,Female,34,Bachelors,3,72,88,0,75,4.0,0,80,Rural,Software Engineer,79635,0 +49469,Other,22,Bachelors,9,66,51,88,33,0.0,1,60,Semi-Urban,Software Engineer,34813,1 +49470,Male,47,Masters,4,50,54,15,54,8.0,0,89,Rural,Manager,90828,0 +49471,Male,33,High School,9,18,47,98,6,6.0,2,33,Rural,Software Engineer,27552,0 +49472,Female,52,High School,2,7,32,10,76,1.0,3,35,Urban,ML Engineer,102769,0 +49473,Female,53,Masters,7,85,58,30,53,6.0,3,48,Urban,ML Engineer,139009,0 +49474,Male,32,High School,0,79,59,58,83,0.0,6,45,Rural,Software Engineer,130213,1 +49475,Male,49,Diploma,17,54,48,55,12,0.0,6,98,Semi-Urban,Manager,38372,1 +49476,Male,52,High School,18,40,61,66,98,8.0,1,28,Rural,Data Analyst,129618,0 +49477,Female,48,Masters,14,27,38,28,84,5.0,1,74,Urban,Manager,103822,0 +49478,Male,35,Bachelors,6,38,71,92,87,6.0,2,19,Rural,Manager,31291,0 +49479,Female,55,Bachelors,5,56,38,89,21,1.0,2,79,Semi-Urban,HR Executive,101039,1 +49480,Male,56,Bachelors,11,49,3,53,48,7.0,7,22,Urban,ML Engineer,48764,0 +49481,Female,49,Bachelors,16,87,60,74,16,1.0,4,39,Urban,Manager,57570,1 +49482,Male,42,High School,2,85,80,75,54,7.0,4,77,Urban,Data Analyst,60380,1 +49483,Male,43,Diploma,19,97,43,2,51,6.0,7,30,Semi-Urban,ML Engineer,23729,0 +49484,Male,52,Bachelors,5,35,29,98,0,4.0,2,12,Semi-Urban,Manager,101053,0 +49485,Female,47,Masters,8,37,2,5,88,0.0,4,51,Urban,Software Engineer,144662,0 +49486,Male,50,Masters,18,75,2,14,28,9.0,6,85,Semi-Urban,ML Engineer,58049,0 +49487,Female,41,Diploma,12,12,46,47,22,5.0,1,74,Urban,HR Executive,102691,0 +49488,Female,38,Bachelors,5,34,92,28,90,1.0,4,41,Semi-Urban,ML Engineer,136051,0 +49489,Male,55,Diploma,5,57,69,26,17,0.0,6,91,Urban,Software Engineer,30099,1 +49490,Female,56,High School,7,82,99,19,33,8.0,5,70,Urban,Software Engineer,51700,1 +49491,Female,45,Bachelors,9,40,21,93,25,0.0,3,67,Semi-Urban,HR Executive,131513,0 +49492,Female,33,Diploma,3,99,46,91,76,3.0,5,15,Semi-Urban,Manager,78782,1 +49493,Female,30,Bachelors,7,88,20,22,64,9.0,7,52,Rural,Data Analyst,104036,0 +49494,Female,32,Bachelors,7,72,49,7,21,2.0,5,36,Urban,Manager,83198,0 +49495,Male,42,Diploma,11,67,94,79,14,9.0,2,34,Urban,Manager,66919,1 +49496,Female,25,PhD,11,64,14,23,28,7.0,0,84,Urban,Manager,149055,0 +49497,Female,32,Diploma,15,93,52,66,32,5.0,2,48,Urban,Data Analyst,68761,1 +49498,Male,28,Masters,9,53,71,35,73,6.0,0,77,Semi-Urban,Software Engineer,100259,1 +49499,Male,35,Bachelors,19,2,28,2,50,8.0,4,16,Urban,Data Analyst,61718,0 +49500,Female,32,Bachelors,16,3,80,64,77,6.0,2,20,Semi-Urban,HR Executive,58607,0 +49501,Male,31,Diploma,6,56,12,97,7,9.0,3,56,Urban,ML Engineer,79213,0 +49502,Female,25,Bachelors,4,84,43,61,79,7.0,3,71,Semi-Urban,Data Analyst,100122,1 +49503,Male,57,Bachelors,13,0,77,94,2,7.0,7,95,Semi-Urban,HR Executive,68786,1 +49504,Female,28,Masters,19,92,17,25,33,9.0,6,74,Urban,HR Executive,83473,0 +49505,Male,35,Masters,17,75,66,84,27,8.0,0,92,Urban,Software Engineer,94503,1 +49506,Female,48,Masters,5,51,59,44,8,6.0,7,26,Urban,Software Engineer,121731,0 +49507,Male,29,High School,10,7,59,49,17,7.0,1,7,Semi-Urban,HR Executive,67270,0 +49508,Female,46,Bachelors,6,51,94,86,55,1.0,2,23,Rural,Software Engineer,38375,1 +49509,Male,37,High School,16,31,16,38,91,4.0,0,72,Urban,Software Engineer,117770,0 +49510,Female,53,Bachelors,7,30,96,98,55,6.0,4,36,Urban,Data Analyst,75419,1 +49511,Male,37,Diploma,8,3,62,77,35,9.0,2,81,Semi-Urban,HR Executive,131887,0 +49512,Male,43,Bachelors,16,96,31,46,86,2.0,6,82,Urban,Data Analyst,31992,1 +49513,Male,22,Bachelors,16,74,20,36,49,0.0,2,67,Urban,HR Executive,101322,0 +49514,Other,45,Masters,14,79,99,9,99,5.0,1,20,Semi-Urban,ML Engineer,132550,0 +49515,Female,38,Masters,5,54,89,39,6,5.0,0,38,Urban,Manager,132321,0 +49516,Male,31,Diploma,0,16,29,23,94,2.0,5,78,Semi-Urban,Data Analyst,128893,0 +49517,Female,35,Masters,0,71,53,90,87,6.0,1,47,Rural,Manager,24122,1 +49518,Female,50,Diploma,7,71,98,20,30,0.0,1,41,Semi-Urban,Software Engineer,59025,0 +49519,Male,24,Bachelors,11,10,46,67,81,8.0,2,36,Semi-Urban,HR Executive,60118,0 +49520,Female,51,Diploma,19,49,62,55,78,6.0,7,67,Semi-Urban,ML Engineer,44548,0 +49521,Male,53,Bachelors,18,3,58,50,25,0.0,6,46,Semi-Urban,Manager,132654,0 +49522,Male,38,Bachelors,17,31,32,19,58,3.0,6,93,Rural,Data Analyst,121672,0 +49523,Female,49,Masters,11,37,52,39,32,2.0,6,67,Semi-Urban,ML Engineer,140926,0 +49524,Male,34,Bachelors,1,87,52,46,19,1.0,4,84,Urban,ML Engineer,68972,1 +49525,Male,40,High School,11,85,68,61,38,1.0,4,76,Rural,Manager,82221,1 +49526,Female,40,High School,14,15,56,50,8,6.0,1,51,Urban,HR Executive,119779,0 +49527,Female,59,Bachelors,14,0,99,50,45,4.0,2,78,Semi-Urban,HR Executive,40016,0 +49528,Male,39,Bachelors,19,73,31,56,92,9.0,1,85,Rural,HR Executive,139438,1 +49529,Male,55,Diploma,17,59,54,92,18,2.0,2,47,Semi-Urban,Manager,103931,1 +49530,Female,27,Masters,8,38,26,41,88,9.0,0,80,Urban,ML Engineer,105203,0 +49531,Female,45,Bachelors,7,43,44,77,72,3.0,3,91,Semi-Urban,HR Executive,146508,1 +49532,Female,43,Bachelors,5,98,61,45,55,0.0,2,7,Rural,Manager,103857,0 +49533,Male,41,Bachelors,9,67,57,2,49,3.0,4,71,Urban,Manager,149662,0 +49534,Female,41,Bachelors,3,83,99,25,48,9.0,3,76,Urban,ML Engineer,89156,1 +49535,Male,36,Bachelors,6,83,85,53,44,4.0,4,13,Urban,HR Executive,75482,0 +49536,Female,43,Bachelors,7,6,15,20,56,3.0,5,42,Semi-Urban,Manager,132538,0 +49537,Male,39,Bachelors,6,57,48,79,59,0.0,5,98,Semi-Urban,ML Engineer,69995,1 +49538,Female,37,Bachelors,1,11,30,65,18,2.0,6,28,Rural,ML Engineer,54329,0 +49539,Male,28,High School,0,97,60,20,53,7.0,3,54,Semi-Urban,ML Engineer,133297,0 +49540,Female,24,Bachelors,3,91,21,78,23,8.0,3,0,Semi-Urban,Software Engineer,149446,0 +49541,Male,52,Bachelors,11,17,10,82,91,8.0,3,94,Urban,HR Executive,48342,0 +49542,Male,38,High School,16,86,78,28,31,9.0,4,96,Rural,ML Engineer,98969,1 +49543,Female,40,High School,8,60,10,11,33,2.0,7,95,Semi-Urban,Manager,108266,0 +49544,Male,32,Bachelors,7,30,70,53,45,1.0,2,44,Semi-Urban,Data Analyst,96757,0 +49545,Male,52,Masters,2,1,35,50,25,3.0,7,55,Urban,HR Executive,88420,0 +49546,Male,21,Diploma,19,22,9,23,52,7.0,4,24,Urban,Manager,23333,0 +49547,Male,44,Masters,11,29,77,75,77,4.0,5,40,Semi-Urban,Data Analyst,149810,0 +49548,Male,34,Bachelors,5,78,25,38,88,2.0,3,10,Semi-Urban,ML Engineer,79549,0 +49549,Male,37,Bachelors,1,7,76,22,32,2.0,6,85,Rural,Data Analyst,34551,0 +49550,Female,34,High School,9,73,82,13,68,2.0,6,76,Rural,Data Analyst,127723,1 +49551,Female,50,Bachelors,14,43,83,83,49,4.0,2,5,Urban,Manager,115159,0 +49552,Male,29,PhD,16,74,67,57,33,7.0,6,62,Urban,Software Engineer,30742,1 +49553,Male,59,Masters,11,94,19,9,22,3.0,2,24,Semi-Urban,Data Analyst,140775,0 +49554,Female,30,Bachelors,17,80,98,98,69,3.0,2,48,Urban,Software Engineer,39396,1 +49555,Male,29,Diploma,3,11,45,38,93,5.0,6,91,Urban,Manager,33946,0 +49556,Male,48,Bachelors,16,71,30,4,8,3.0,4,77,Urban,HR Executive,54797,0 +49557,Male,32,Bachelors,15,96,19,40,0,6.0,7,87,Semi-Urban,ML Engineer,102721,1 +49558,Male,50,Diploma,16,78,32,16,19,3.0,6,35,Semi-Urban,Data Analyst,63233,0 +49559,Male,57,Masters,1,20,10,42,4,9.0,7,63,Urban,Software Engineer,92411,0 +49560,Female,36,Masters,2,82,89,46,2,8.0,5,79,Rural,Data Analyst,58753,1 +49561,Male,40,Bachelors,19,1,92,36,15,7.0,5,3,Urban,HR Executive,97003,0 +49562,Female,21,Bachelors,18,30,11,60,44,7.0,5,25,Semi-Urban,Manager,141545,0 +49563,Female,28,Masters,14,58,77,26,67,1.0,5,65,Rural,Manager,41421,0 +49564,Female,30,Bachelors,17,5,67,82,84,8.0,7,20,Urban,Software Engineer,90608,0 +49565,Male,37,Bachelors,0,10,90,61,24,2.0,1,68,Urban,HR Executive,29732,0 +49566,Male,42,Bachelors,16,78,9,64,34,8.0,4,41,Urban,HR Executive,87147,0 +49567,Male,24,Bachelors,19,96,71,18,85,1.0,4,27,Rural,Software Engineer,38927,0 +49568,Male,33,Bachelors,4,26,0,37,58,1.0,0,43,Urban,Data Analyst,136669,0 +49569,Female,47,Bachelors,6,70,71,14,58,1.0,6,10,Urban,Manager,75564,0 +49570,Male,29,Bachelors,6,86,16,53,89,9.0,5,75,Urban,Manager,21052,0 +49571,Female,24,Masters,11,35,42,45,43,8.0,2,96,Rural,Software Engineer,105581,0 +49572,Female,21,Masters,10,72,65,27,50,6.0,7,47,Urban,HR Executive,53954,0 +49573,Female,23,Bachelors,7,36,99,27,56,0.0,5,73,Urban,Software Engineer,129615,0 +49574,Male,33,Bachelors,10,79,47,71,68,3.0,4,33,Urban,Software Engineer,120340,0 +49575,Female,40,Bachelors,12,33,18,92,90,1.0,0,27,Urban,HR Executive,75825,0 +49576,Other,32,Diploma,16,56,85,92,65,8.0,7,88,Semi-Urban,Manager,133718,1 +49577,Male,38,Bachelors,14,16,54,39,19,6.0,1,27,Rural,Data Analyst,112660,0 +49578,Male,24,Bachelors,4,87,92,40,39,6.0,4,20,Urban,Data Analyst,137703,1 +49579,Male,41,Masters,16,51,89,25,3,5.0,6,61,Rural,Data Analyst,136718,0 +49580,Male,52,High School,18,99,37,31,93,6.0,7,41,Rural,HR Executive,30415,0 +49581,Male,31,Bachelors,1,21,75,25,46,1.0,4,37,Urban,Data Analyst,41054,0 +49582,Male,51,Bachelors,14,11,61,43,72,3.0,3,86,Urban,Manager,101816,0 +49583,Male,58,Bachelors,3,86,72,24,38,8.0,2,50,Semi-Urban,Software Engineer,40149,0 +49584,Female,46,High School,11,81,4,81,93,5.0,1,70,Rural,HR Executive,112604,0 +49585,Male,24,Diploma,18,25,94,95,72,6.0,0,20,Urban,Manager,57770,0 +49586,Female,28,Bachelors,14,68,78,32,31,8.0,5,95,Urban,ML Engineer,59076,1 +49587,Male,46,Masters,1,62,35,4,88,0.0,1,97,Urban,HR Executive,135456,0 +49588,Female,58,Diploma,5,14,38,11,58,8.0,3,64,Semi-Urban,HR Executive,77787,0 +49589,Male,37,PhD,16,29,95,41,61,5.0,5,10,Urban,Software Engineer,77684,0 +49590,Female,26,PhD,18,82,74,22,18,0.0,1,65,Urban,Manager,63207,1 +49591,Male,34,High School,9,16,66,17,63,2.0,6,95,Urban,ML Engineer,69536,0 +49592,Male,29,Bachelors,7,82,38,12,35,2.0,1,3,Rural,Software Engineer,107917,0 +49593,Female,58,High School,11,57,47,83,55,3.0,6,32,Rural,Manager,97360,0 +49594,Female,23,Bachelors,2,28,56,78,89,2.0,2,6,Urban,Manager,127688,0 +49595,Male,21,Masters,0,44,6,84,64,3.0,3,14,Semi-Urban,ML Engineer,50395,0 +49596,Other,22,Bachelors,1,67,50,7,11,8.0,1,72,Urban,Software Engineer,46719,0 +49597,Male,31,Bachelors,5,48,40,8,65,4.0,3,8,Urban,Manager,68016,0 +49598,Male,58,PhD,7,50,21,7,90,5.0,3,89,Urban,ML Engineer,56357,0 +49599,Female,30,Masters,8,79,38,9,13,7.0,0,99,Urban,Data Analyst,84384,0 +49600,Male,42,High School,9,47,72,9,67,5.0,4,15,Semi-Urban,Data Analyst,102405,0 +49601,Male,59,Bachelors,18,30,49,92,83,7.0,0,12,Semi-Urban,Data Analyst,41245,0 +49602,Male,50,High School,18,75,44,33,55,5.0,2,23,Urban,ML Engineer,58347,0 +49603,Male,29,Bachelors,16,84,16,5,43,1.0,6,52,Semi-Urban,ML Engineer,58538,0 +49604,Male,40,Bachelors,0,34,10,0,77,1.0,4,58,Urban,Software Engineer,92263,0 +49605,Male,24,High School,19,92,12,45,56,6.0,5,35,Semi-Urban,ML Engineer,113912,0 +49606,Female,59,Bachelors,8,1,87,64,98,3.0,3,75,Rural,HR Executive,38052,0 +49607,Male,31,High School,14,60,26,88,24,7.0,4,27,Urban,Software Engineer,67573,0 +49608,Male,31,Diploma,5,45,57,66,91,2.0,7,10,Urban,Data Analyst,48775,0 +49609,Female,44,Bachelors,11,16,53,97,14,2.0,0,43,Urban,HR Executive,25546,0 +49610,Male,28,Bachelors,5,3,42,55,84,2.0,5,92,Urban,Manager,23170,0 +49611,Male,50,Bachelors,7,73,35,69,3,1.0,3,75,Semi-Urban,HR Executive,120983,1 +49612,Other,56,Bachelors,3,28,69,36,85,4.0,0,85,Semi-Urban,Software Engineer,46605,0 +49613,Female,46,Diploma,12,1,99,1,50,7.0,1,67,Urban,Data Analyst,85056,0 +49614,Male,25,High School,8,11,95,62,49,0.0,5,39,Urban,Manager,87328,0 +49615,Female,51,Bachelors,9,45,88,4,6,5.0,7,82,Urban,HR Executive,51657,0 +49616,Female,22,Masters,6,26,74,56,8,5.0,0,48,Urban,ML Engineer,109084,0 +49617,Female,49,Diploma,6,35,73,27,92,0.0,3,3,Urban,Software Engineer,96572,0 +49618,Male,38,Diploma,8,8,82,47,75,4.0,0,50,Rural,Data Analyst,94622,0 +49619,Male,30,Masters,18,61,85,39,30,8.0,7,20,Rural,Software Engineer,140633,0 +49620,Male,34,Bachelors,3,78,80,51,29,0.0,7,12,Semi-Urban,HR Executive,115338,0 +49621,Female,32,Diploma,4,28,49,69,95,7.0,0,58,Semi-Urban,Data Analyst,142698,0 +49622,Female,55,Diploma,18,45,67,52,95,2.0,2,53,Urban,ML Engineer,90053,0 +49623,Female,53,Diploma,6,45,73,24,29,8.0,5,32,Semi-Urban,Data Analyst,26743,0 +49624,Male,40,Diploma,6,29,87,37,93,5.0,2,66,Rural,HR Executive,104435,0 +49625,Male,48,Masters,14,68,11,38,32,1.0,7,4,Semi-Urban,HR Executive,77245,0 +49626,Male,29,Bachelors,4,12,86,44,72,5.0,1,53,Semi-Urban,ML Engineer,119371,0 +49627,Female,46,High School,19,11,84,93,50,5.0,4,87,Urban,HR Executive,137877,1 +49628,Male,30,Masters,6,13,29,1,74,8.0,2,85,Urban,ML Engineer,124243,0 +49629,Female,57,Masters,9,46,52,5,78,8.0,0,54,Semi-Urban,HR Executive,31869,0 +49630,Female,35,Bachelors,17,47,77,86,45,1.0,7,37,Semi-Urban,Software Engineer,57713,1 +49631,Male,40,Bachelors,19,92,36,69,71,8.0,0,72,Semi-Urban,Manager,104445,1 +49632,Male,27,High School,7,75,6,26,84,8.0,5,5,Urban,Data Analyst,128251,0 +49633,Male,44,Bachelors,0,89,11,84,97,0.0,4,77,Urban,HR Executive,41898,1 +49634,Female,41,Bachelors,14,9,99,15,41,1.0,3,29,Urban,Manager,90085,0 +49635,Male,32,Diploma,6,64,78,14,26,9.0,1,34,Semi-Urban,ML Engineer,97583,0 +49636,Male,32,Bachelors,2,63,43,24,37,9.0,5,53,Urban,Software Engineer,74628,0 +49637,Female,59,Masters,17,0,79,32,24,4.0,0,82,Semi-Urban,Data Analyst,73785,0 +49638,Male,50,Masters,13,0,89,59,68,1.0,1,70,Semi-Urban,HR Executive,37802,0 +49639,Male,31,Bachelors,14,2,83,30,81,3.0,7,36,Semi-Urban,Data Analyst,60035,0 +49640,Female,23,Bachelors,3,29,75,5,88,4.0,1,39,Urban,Data Analyst,51836,0 +49641,Female,58,Bachelors,10,42,97,13,3,1.0,6,30,Urban,Manager,112612,0 +49642,Male,24,Bachelors,2,31,35,4,26,2.0,5,54,Rural,ML Engineer,45303,0 +49643,Male,51,Bachelors,9,85,97,89,38,5.0,4,72,Semi-Urban,HR Executive,128964,1 +49644,Female,24,Bachelors,15,12,65,19,78,3.0,4,62,Urban,Data Analyst,92263,0 +49645,Female,43,Diploma,9,29,53,23,67,6.0,7,14,Urban,Software Engineer,78103,0 +49646,Male,57,Bachelors,3,56,33,86,45,4.0,1,7,Semi-Urban,Manager,114033,0 +49647,Female,54,Bachelors,12,46,22,58,4,1.0,6,63,Rural,Software Engineer,62081,0 +49648,Female,31,Bachelors,10,44,8,19,31,3.0,6,1,Rural,Data Analyst,100242,0 +49649,Male,50,Bachelors,9,19,47,55,21,1.0,2,44,Urban,Software Engineer,59679,0 +49650,Male,47,Diploma,13,29,54,6,7,3.0,7,88,Rural,ML Engineer,118751,0 +49651,Female,44,Masters,8,61,83,65,49,7.0,0,38,Urban,Software Engineer,40738,1 +49652,Male,27,Bachelors,0,66,74,59,22,9.0,7,95,Rural,HR Executive,74359,1 +49653,Female,46,PhD,9,74,93,26,78,0.0,6,50,Semi-Urban,HR Executive,25099,1 +49654,Female,34,Bachelors,5,3,31,82,32,6.0,3,11,Urban,HR Executive,24913,0 +49655,Female,48,High School,14,47,21,59,87,8.0,1,36,Urban,ML Engineer,40276,0 +49656,Male,39,Bachelors,7,4,10,84,30,4.0,3,91,Urban,ML Engineer,93881,0 +49657,Female,31,Masters,13,98,74,9,38,5.0,7,32,Semi-Urban,Data Analyst,85036,0 +49658,Male,30,Masters,19,61,58,91,42,9.0,1,15,Urban,Software Engineer,67723,0 +49659,Male,53,Bachelors,16,40,56,30,8,1.0,1,58,Semi-Urban,Data Analyst,39593,0 +49660,Male,44,Bachelors,12,32,10,48,98,1.0,1,65,Rural,Software Engineer,59792,0 +49661,Female,51,Masters,15,38,65,3,10,0.0,0,22,Rural,HR Executive,124132,0 +49662,Male,52,Bachelors,7,6,97,14,95,7.0,6,23,Rural,HR Executive,57187,0 +49663,Female,43,High School,18,29,32,92,76,9.0,3,7,Urban,Software Engineer,128518,0 +49664,Male,25,Diploma,7,29,81,15,32,2.0,5,44,Semi-Urban,ML Engineer,134599,0 +49665,Female,39,Bachelors,13,40,72,99,62,5.0,2,21,Urban,Manager,37519,0 +49666,Male,27,Bachelors,14,5,63,9,4,2.0,7,1,Semi-Urban,Data Analyst,128986,0 +49667,Male,43,Masters,18,4,71,10,31,0.0,4,89,Urban,ML Engineer,122761,0 +49668,Other,54,Bachelors,4,79,27,17,8,0.0,5,97,Semi-Urban,HR Executive,70121,0 +49669,Male,35,Masters,14,35,29,7,14,6.0,6,7,Semi-Urban,Software Engineer,131359,0 +49670,Male,58,Bachelors,11,1,53,29,58,9.0,7,92,Urban,HR Executive,122186,0 +49671,Female,37,Diploma,4,23,11,60,72,8.0,1,50,Urban,Manager,23985,0 +49672,Female,27,Bachelors,16,77,8,92,25,4.0,2,42,Urban,ML Engineer,42827,0 +49673,Male,22,Bachelors,11,97,65,1,93,7.0,5,36,Semi-Urban,Data Analyst,105710,0 +49674,Female,36,High School,3,75,87,6,80,5.0,2,46,Semi-Urban,ML Engineer,149904,0 +49675,Female,56,Diploma,9,72,37,58,17,0.0,6,37,Urban,Software Engineer,34163,0 +49676,Male,33,Diploma,16,99,76,69,1,1.0,1,38,Urban,Manager,34644,1 +49677,Male,40,Diploma,16,61,63,61,9,7.0,2,23,Urban,HR Executive,75171,0 +49678,Male,25,Bachelors,2,3,36,39,91,7.0,2,21,Semi-Urban,HR Executive,54211,0 +49679,Male,50,Masters,1,2,94,45,10,4.0,2,29,Semi-Urban,ML Engineer,37352,0 +49680,Male,25,Bachelors,6,41,68,84,23,0.0,0,15,Urban,HR Executive,110157,0 +49681,Male,53,Bachelors,0,69,38,23,0,5.0,7,77,Urban,Software Engineer,102154,0 +49682,Male,48,Bachelors,18,80,32,90,18,3.0,5,19,Semi-Urban,Software Engineer,114982,0 +49683,Male,55,High School,10,0,76,58,7,3.0,4,89,Semi-Urban,HR Executive,45190,0 +49684,Male,31,Diploma,10,30,80,77,95,3.0,0,17,Urban,Data Analyst,85942,0 +49685,Male,50,Bachelors,11,30,52,15,19,7.0,0,35,Rural,ML Engineer,26976,0 +49686,Female,31,PhD,1,74,11,53,61,1.0,4,72,Rural,HR Executive,141353,0 +49687,Female,45,Bachelors,10,36,88,57,49,2.0,3,74,Urban,Data Analyst,142291,1 +49688,Male,30,Diploma,2,84,68,24,65,7.0,5,22,Rural,Manager,141864,0 +49689,Male,42,Bachelors,3,64,17,91,22,4.0,4,31,Rural,ML Engineer,94149,0 +49690,Female,39,Bachelors,13,43,95,66,11,0.0,6,52,Rural,HR Executive,69815,1 +49691,Female,38,Masters,7,30,76,20,94,3.0,1,4,Urban,ML Engineer,142438,0 +49692,Male,38,Diploma,2,54,31,56,0,7.0,5,86,Urban,ML Engineer,48604,0 +49693,Male,26,Bachelors,15,12,1,88,78,2.0,7,88,Rural,Data Analyst,63280,0 +49694,Male,29,Bachelors,0,55,82,56,71,5.0,6,44,Semi-Urban,Software Engineer,70102,1 +49695,Female,30,High School,7,58,5,79,3,2.0,4,61,Urban,ML Engineer,99646,0 +49696,Other,51,Bachelors,19,7,28,0,69,5.0,6,18,Urban,Software Engineer,126217,0 +49697,Female,37,Bachelors,2,49,79,53,58,4.0,2,84,Semi-Urban,HR Executive,94703,1 +49698,Male,22,Masters,16,96,94,17,53,0.0,1,27,Rural,ML Engineer,134061,0 +49699,Female,51,Masters,16,40,30,5,37,4.0,3,79,Urban,Data Analyst,28786,0 +49700,Male,40,Diploma,6,71,54,56,48,5.0,2,52,Semi-Urban,ML Engineer,35763,0 +49701,Female,59,Bachelors,9,17,57,23,0,8.0,2,11,Urban,Software Engineer,146414,0 +49702,Male,59,High School,3,33,70,53,58,3.0,6,2,Urban,ML Engineer,111562,0 +49703,Male,59,High School,9,54,4,38,96,1.0,0,67,Rural,Data Analyst,68466,0 +49704,Male,52,Masters,17,61,40,94,69,1.0,1,55,Semi-Urban,Manager,34801,1 +49705,Female,38,Bachelors,19,17,92,25,15,5.0,4,12,Semi-Urban,Data Analyst,55279,0 +49706,Female,28,Diploma,15,73,89,32,51,8.0,2,56,Rural,Data Analyst,125048,1 +49707,Male,23,Masters,10,98,9,12,49,0.0,5,84,Semi-Urban,Software Engineer,123401,0 +49708,Male,30,PhD,11,38,97,91,61,5.0,4,94,Urban,ML Engineer,127833,1 +49709,Male,38,Masters,19,64,85,76,67,3.0,1,56,Semi-Urban,ML Engineer,31742,1 +49710,Male,21,Bachelors,18,98,29,70,67,2.0,7,4,Urban,ML Engineer,148637,0 +49711,Male,37,Bachelors,13,21,10,21,20,2.0,0,99,Urban,ML Engineer,89740,0 +49712,Male,55,High School,8,59,81,16,7,9.0,1,62,Urban,ML Engineer,140858,0 +49713,Male,34,Masters,10,87,73,78,70,4.0,7,96,Semi-Urban,Manager,59506,1 +49714,Female,45,Bachelors,8,45,38,39,26,5.0,1,3,Urban,Software Engineer,123254,0 +49715,Female,22,Bachelors,4,62,44,29,99,7.0,0,12,Urban,HR Executive,77757,0 +49716,Male,56,Masters,5,5,33,55,16,6.0,6,31,Urban,Manager,90441,0 +49717,Male,42,Bachelors,14,68,8,66,26,4.0,6,11,Urban,HR Executive,133549,0 +49718,Male,49,Bachelors,17,65,10,67,23,0.0,4,42,Semi-Urban,HR Executive,24649,0 +49719,Male,33,Diploma,18,4,4,79,47,9.0,4,48,Semi-Urban,Software Engineer,120854,0 +49720,Female,59,Bachelors,18,21,90,25,94,2.0,2,77,Rural,Software Engineer,57899,0 +49721,Female,56,Diploma,12,82,16,73,21,6.0,6,20,Rural,HR Executive,120610,0 +49722,Male,23,Diploma,3,43,87,98,73,8.0,4,23,Urban,Data Analyst,45000,1 +49723,Female,53,Bachelors,15,70,49,77,39,7.0,2,8,Semi-Urban,Data Analyst,95772,0 +49724,Female,33,Diploma,8,55,92,83,75,3.0,1,13,Semi-Urban,Manager,93982,1 +49725,Male,42,Diploma,0,25,81,48,44,7.0,2,27,Rural,Software Engineer,34023,0 +49726,Female,49,Diploma,4,90,93,60,13,1.0,2,77,Urban,HR Executive,51459,1 +49727,Male,27,Bachelors,0,98,17,34,25,5.0,4,51,Urban,Data Analyst,54064,0 +49728,Male,53,Masters,9,56,35,44,94,8.0,3,44,Semi-Urban,ML Engineer,105975,0 +49729,Female,54,Bachelors,4,18,60,21,17,2.0,4,72,Semi-Urban,Software Engineer,56642,0 +49730,Female,26,Masters,12,98,92,93,93,8.0,4,35,Urban,ML Engineer,107306,1 +49731,Male,49,Masters,14,25,50,81,89,4.0,5,71,Urban,Software Engineer,120733,0 +49732,Male,37,Diploma,12,72,99,97,2,7.0,6,72,Urban,Software Engineer,44387,1 +49733,Female,59,Bachelors,7,95,59,20,31,4.0,1,89,Urban,Manager,23724,1 +49734,Male,36,Diploma,12,69,46,55,69,4.0,5,1,Urban,ML Engineer,72216,0 +49735,Female,50,Bachelors,1,61,62,19,18,2.0,2,42,Semi-Urban,ML Engineer,57885,0 +49736,Male,34,Bachelors,19,51,46,61,44,0.0,0,91,Urban,Manager,120747,1 +49737,Male,41,Bachelors,5,57,38,27,94,1.0,1,79,Urban,Manager,74581,0 +49738,Male,29,High School,8,56,76,7,53,8.0,4,94,Semi-Urban,HR Executive,31684,0 +49739,Female,23,Bachelors,2,26,22,99,70,7.0,5,2,Semi-Urban,Manager,90770,0 +49740,Male,26,Diploma,18,73,20,28,69,4.0,3,23,Urban,Data Analyst,68028,0 +49741,Male,23,Bachelors,3,33,79,72,26,8.0,5,63,Urban,ML Engineer,112766,1 +49742,Male,51,Bachelors,1,7,87,81,49,2.0,2,25,Semi-Urban,ML Engineer,144578,0 +49743,Male,49,Diploma,2,15,29,79,15,8.0,2,38,Urban,Data Analyst,106006,0 +49744,Male,42,Masters,16,19,9,76,55,5.0,7,82,Semi-Urban,Manager,29054,0 +49745,Male,21,Bachelors,9,59,58,88,5,8.0,3,66,Urban,Data Analyst,35766,1 +49746,Male,35,Diploma,7,22,73,95,89,6.0,3,83,Rural,ML Engineer,82644,1 +49747,Male,47,Bachelors,4,33,25,86,25,4.0,2,85,Urban,Data Analyst,41379,0 +49748,Female,33,Bachelors,17,60,89,40,95,1.0,5,15,Urban,Software Engineer,100709,0 +49749,Male,31,Bachelors,12,14,16,14,81,6.0,4,24,Semi-Urban,HR Executive,100666,0 +49750,Male,30,Masters,13,95,2,43,66,3.0,5,49,Rural,ML Engineer,85342,0 +49751,Male,48,Bachelors,14,39,21,9,16,5.0,4,65,Urban,ML Engineer,102836,0 +49752,Male,45,Bachelors,6,38,13,86,1,0.0,3,28,Rural,Manager,51541,0 +49753,Female,27,Bachelors,8,88,21,30,88,9.0,7,37,Urban,Manager,22014,0 +49754,Female,45,Diploma,6,92,23,82,38,0.0,4,32,Urban,HR Executive,118909,0 +49755,Male,54,Masters,4,78,19,31,75,8.0,5,73,Urban,Manager,72847,0 +49756,Female,35,High School,7,14,43,83,28,3.0,6,76,Urban,HR Executive,132533,0 +49757,Female,55,PhD,18,81,62,8,63,2.0,1,45,Urban,Manager,50855,0 +49758,Female,34,Diploma,10,19,18,62,90,2.0,7,17,Urban,Manager,74471,0 +49759,Female,40,High School,8,33,16,92,22,1.0,3,85,Rural,Software Engineer,145059,0 +49760,Male,49,Bachelors,0,67,77,39,93,6.0,3,1,Semi-Urban,HR Executive,86883,0 +49761,Other,52,Masters,1,61,54,41,7,7.0,1,26,Urban,HR Executive,73435,0 +49762,Other,57,Diploma,17,46,88,48,91,0.0,3,52,Urban,Manager,48430,0 +49763,Male,51,Bachelors,13,93,5,56,66,2.0,5,20,Semi-Urban,HR Executive,148220,0 +49764,Male,57,High School,3,19,2,24,29,9.0,7,41,Urban,Manager,66829,0 +49765,Female,38,Diploma,4,40,1,92,25,5.0,7,22,Rural,Manager,29725,0 +49766,Male,45,PhD,7,82,87,40,78,8.0,3,14,Urban,Manager,25198,0 +49767,Female,46,Bachelors,0,58,57,20,6,6.0,7,25,Urban,ML Engineer,89294,0 +49768,Male,37,High School,3,87,77,52,24,8.0,5,97,Semi-Urban,ML Engineer,60736,1 +49769,Male,39,Bachelors,1,38,10,2,22,3.0,5,26,Rural,Manager,81814,0 +49770,Female,42,Masters,18,1,52,88,52,4.0,4,66,Rural,Manager,130218,0 +49771,Female,48,High School,17,93,19,49,68,2.0,2,8,Urban,Data Analyst,113551,0 +49772,Male,54,High School,12,88,63,99,11,3.0,2,94,Urban,HR Executive,29498,1 +49773,Female,54,High School,12,75,60,81,4,9.0,1,99,Rural,HR Executive,21174,1 +49774,Male,58,High School,17,95,34,35,69,2.0,2,32,Semi-Urban,Manager,47395,0 +49775,Male,50,Bachelors,18,96,21,86,16,6.0,1,66,Urban,Manager,100948,1 +49776,Male,34,Diploma,13,77,48,18,41,1.0,6,77,Semi-Urban,HR Executive,145294,0 +49777,Male,25,Masters,11,67,96,84,46,2.0,7,32,Urban,HR Executive,58101,1 +49778,Male,49,Masters,17,61,55,98,49,1.0,3,42,Semi-Urban,Data Analyst,22726,1 +49779,Female,54,Masters,6,81,43,85,40,8.0,5,20,Urban,Data Analyst,50963,0 +49780,Female,27,Diploma,16,40,76,14,43,5.0,2,14,Rural,HR Executive,97813,0 +49781,Male,35,High School,0,20,43,62,28,7.0,2,95,Urban,HR Executive,148982,0 +49782,Female,21,Bachelors,1,34,88,73,87,4.0,0,61,Urban,Manager,62540,1 +49783,Other,28,Diploma,5,21,1,80,75,9.0,0,7,Semi-Urban,HR Executive,116700,0 +49784,Male,37,PhD,11,18,87,35,62,7.0,7,58,Rural,HR Executive,86116,0 +49785,Male,32,Diploma,3,10,76,11,20,0.0,6,92,Urban,Manager,43568,0 +49786,Female,38,Diploma,4,72,18,56,1,7.0,4,13,Urban,Manager,102967,0 +49787,Female,46,High School,5,65,12,64,76,0.0,6,47,Semi-Urban,Data Analyst,123808,0 +49788,Female,24,Masters,4,16,21,64,71,5.0,3,63,Urban,ML Engineer,85155,0 +49789,Male,54,High School,7,99,42,46,52,1.0,2,89,Rural,HR Executive,53541,1 +49790,Female,48,Diploma,7,59,11,13,89,1.0,5,20,Urban,Software Engineer,46058,0 +49791,Female,22,Diploma,12,98,15,19,37,9.0,1,5,Urban,Data Analyst,71973,0 +49792,Female,23,High School,8,80,9,37,93,9.0,0,40,Semi-Urban,ML Engineer,70143,0 +49793,Male,30,Bachelors,19,11,32,85,39,6.0,1,66,Urban,Manager,97351,0 +49794,Male,43,Diploma,3,70,0,41,47,7.0,7,60,Semi-Urban,Manager,76663,0 +49795,Male,38,Diploma,15,28,80,73,48,0.0,0,81,Semi-Urban,Manager,88701,1 +49796,Male,43,Bachelors,19,84,76,72,37,7.0,4,45,Urban,ML Engineer,59452,1 +49797,Male,40,Bachelors,4,17,68,45,32,6.0,2,1,Urban,HR Executive,56866,0 +49798,Female,59,Bachelors,5,53,40,4,2,7.0,4,82,Urban,Data Analyst,36539,0 +49799,Male,42,Bachelors,14,27,21,66,66,6.0,0,65,Urban,Data Analyst,80547,0 +49800,Male,34,High School,9,62,6,23,22,1.0,2,90,Urban,Data Analyst,89694,0 +49801,Male,39,Bachelors,16,24,33,73,67,8.0,2,28,Urban,Software Engineer,43361,0 +49802,Male,21,PhD,7,60,74,76,15,8.0,0,27,Urban,HR Executive,87762,1 +49803,Male,49,High School,18,36,11,53,30,2.0,0,33,Semi-Urban,Manager,65204,0 +49804,Male,54,Bachelors,17,0,63,16,57,1.0,6,82,Urban,HR Executive,56347,0 +49805,Female,55,Diploma,11,64,92,88,34,4.0,2,95,Semi-Urban,Manager,133237,1 +49806,Female,42,Masters,13,17,72,16,97,2.0,5,54,Semi-Urban,Data Analyst,26766,0 +49807,Male,30,Bachelors,0,38,6,1,60,3.0,5,20,Rural,ML Engineer,121900,0 +49808,Female,51,Bachelors,16,70,16,17,36,7.0,4,92,Urban,ML Engineer,90218,0 +49809,Male,29,Masters,19,65,39,77,59,7.0,2,70,Urban,Software Engineer,36037,1 +49810,Other,30,Bachelors,2,54,89,52,98,5.0,0,57,Rural,Software Engineer,78232,1 +49811,Female,32,Masters,1,32,84,63,27,4.0,3,89,Semi-Urban,Data Analyst,111640,1 +49812,Male,44,Bachelors,9,94,25,15,77,9.0,6,36,Urban,Software Engineer,69892,0 +49813,Male,44,Bachelors,2,92,25,20,31,7.0,2,38,Semi-Urban,Manager,115899,0 +49814,Male,49,High School,19,93,81,54,72,0.0,3,86,Urban,Software Engineer,65454,1 +49815,Male,53,Diploma,9,76,11,61,27,5.0,7,40,Urban,HR Executive,76209,0 +49816,Female,45,PhD,19,96,39,42,58,1.0,5,71,Urban,Data Analyst,22722,1 +49817,Male,23,Diploma,1,67,69,71,12,3.0,0,86,Urban,Software Engineer,96815,1 +49818,Male,48,Bachelors,14,62,71,86,65,5.0,5,19,Rural,Data Analyst,94541,1 +49819,Male,23,High School,13,89,35,93,63,2.0,7,66,Urban,Manager,134351,1 +49820,Male,46,Masters,7,25,90,88,77,7.0,1,40,Semi-Urban,HR Executive,107221,1 +49821,Male,43,Bachelors,2,58,16,30,8,7.0,6,88,Rural,HR Executive,55635,0 +49822,Male,51,High School,16,52,8,90,72,2.0,7,53,Urban,Data Analyst,79693,0 +49823,Female,24,Bachelors,18,6,56,11,98,7.0,3,14,Rural,ML Engineer,101839,0 +49824,Male,52,Masters,12,32,45,21,72,1.0,0,2,Semi-Urban,Manager,80651,0 +49825,Female,38,Masters,5,67,36,92,0,9.0,3,77,Rural,HR Executive,92444,1 +49826,Female,47,Bachelors,5,38,16,9,93,5.0,2,19,Semi-Urban,Manager,45440,0 +49827,Male,28,High School,5,53,34,62,16,6.0,3,17,Rural,Software Engineer,81103,0 +49828,Male,36,Bachelors,14,91,36,16,55,3.0,5,67,Semi-Urban,ML Engineer,48828,0 +49829,Male,39,Diploma,18,1,60,94,9,2.0,4,88,Urban,Software Engineer,100950,1 +49830,Female,40,Diploma,0,36,34,47,67,4.0,0,89,Urban,Data Analyst,61816,0 +49831,Male,28,Bachelors,18,68,35,45,90,2.0,6,25,Urban,HR Executive,45753,0 +49832,Male,42,High School,10,83,85,53,51,6.0,5,42,Semi-Urban,ML Engineer,60758,1 +49833,Female,29,Diploma,2,57,70,7,53,0.0,7,45,Urban,HR Executive,120204,0 +49834,Female,26,Bachelors,18,97,63,19,94,9.0,3,13,Rural,Manager,82968,0 +49835,Female,31,Bachelors,19,44,44,73,94,6.0,1,14,Rural,Software Engineer,144006,0 +49836,Male,35,Bachelors,16,52,7,52,25,8.0,1,42,Urban,ML Engineer,64679,0 +49837,Male,56,High School,11,92,93,30,22,3.0,0,14,Urban,ML Engineer,106558,0 +49838,Female,44,Masters,9,28,35,77,40,0.0,2,85,Urban,ML Engineer,50651,0 +49839,Male,30,Masters,0,16,9,53,95,9.0,2,94,Urban,Data Analyst,87329,0 +49840,Male,22,High School,5,48,76,36,3,9.0,1,41,Urban,Manager,81337,0 +49841,Female,39,Bachelors,1,44,19,49,90,7.0,4,24,Urban,ML Engineer,149037,0 +49842,Female,22,Bachelors,9,73,68,11,87,3.0,4,53,Urban,Software Engineer,92548,0 +49843,Female,51,Diploma,15,57,30,42,31,5.0,1,75,Semi-Urban,Manager,89925,0 +49844,Male,53,Bachelors,18,35,12,50,94,4.0,4,52,Urban,HR Executive,97790,0 +49845,Other,46,Diploma,6,95,38,34,75,0.0,7,6,Urban,Data Analyst,49891,0 +49846,Male,28,PhD,3,37,13,52,72,0.0,1,99,Rural,Data Analyst,23233,0 +49847,Male,41,High School,4,49,80,39,24,8.0,2,74,Urban,Software Engineer,54842,1 +49848,Female,39,Bachelors,2,72,4,89,52,6.0,7,43,Rural,HR Executive,45937,0 +49849,Female,24,Masters,16,20,23,73,72,9.0,0,93,Urban,Manager,129254,0 +49850,Male,24,PhD,12,20,27,38,65,1.0,2,24,Urban,Data Analyst,62611,0 +49851,Male,51,High School,0,77,51,76,31,3.0,1,1,Urban,ML Engineer,113639,0 +49852,Male,55,Masters,12,14,81,13,27,1.0,4,99,Semi-Urban,ML Engineer,96387,0 +49853,Male,48,High School,4,54,89,7,99,1.0,3,80,Semi-Urban,ML Engineer,47340,0 +49854,Female,32,Bachelors,2,48,27,50,35,9.0,0,88,Urban,Software Engineer,74232,0 +49855,Male,33,Masters,17,3,84,63,14,2.0,3,49,Rural,HR Executive,77175,0 +49856,Female,31,Diploma,1,9,8,19,4,8.0,1,94,Semi-Urban,Manager,53852,0 +49857,Male,39,Bachelors,9,56,79,1,66,2.0,3,35,Rural,Manager,63569,0 +49858,Male,54,Masters,16,10,51,0,4,0.0,0,28,Rural,Manager,53881,0 +49859,Male,49,Masters,9,57,81,66,43,8.0,3,47,Semi-Urban,Manager,98129,1 +49860,Male,31,Diploma,3,7,44,74,42,7.0,1,76,Urban,HR Executive,130622,0 +49861,Male,26,Bachelors,7,5,62,95,23,6.0,6,81,Urban,HR Executive,55104,1 +49862,Male,40,High School,10,70,14,45,16,4.0,7,49,Semi-Urban,Data Analyst,113957,0 +49863,Male,55,Bachelors,19,37,30,18,8,7.0,1,46,Rural,ML Engineer,36547,0 +49864,Female,53,Masters,13,52,20,18,8,3.0,7,10,Rural,Data Analyst,30295,0 +49865,Male,34,High School,13,92,33,70,98,6.0,5,3,Urban,Data Analyst,134864,0 +49866,Male,28,Bachelors,9,90,53,53,54,0.0,7,96,Urban,Software Engineer,82280,1 +49867,Male,32,Bachelors,10,91,83,93,80,6.0,3,58,Rural,Manager,31619,1 +49868,Male,44,Masters,19,1,21,49,12,6.0,0,8,Semi-Urban,Software Engineer,60888,0 +49869,Female,49,Bachelors,18,7,39,93,87,8.0,4,98,Rural,ML Engineer,124505,0 +49870,Female,45,Masters,8,53,1,9,26,8.0,6,18,Urban,ML Engineer,101775,0 +49871,Male,29,Masters,12,39,29,35,78,2.0,0,95,Urban,Data Analyst,143272,0 +49872,Male,24,Bachelors,8,87,74,85,72,0.0,5,20,Semi-Urban,Software Engineer,57965,1 +49873,Male,29,Bachelors,9,34,90,79,1,6.0,2,46,Urban,ML Engineer,115566,1 +49874,Male,43,High School,3,3,42,14,22,4.0,3,7,Semi-Urban,Manager,53911,0 +49875,Male,49,High School,0,54,54,17,96,6.0,7,56,Semi-Urban,Data Analyst,22970,0 +49876,Male,25,Diploma,4,34,67,37,6,6.0,6,82,Urban,ML Engineer,144311,0 +49877,Female,34,Bachelors,13,58,39,20,26,9.0,4,98,Rural,HR Executive,143471,0 +49878,Male,46,High School,12,0,95,31,45,5.0,5,55,Urban,Data Analyst,118605,0 +49879,Female,22,Masters,19,44,43,57,98,7.0,2,70,Rural,HR Executive,123406,0 +49880,Male,40,High School,3,91,85,91,85,2.0,3,25,Urban,Software Engineer,149437,1 +49881,Other,49,High School,11,97,84,82,89,3.0,1,47,Urban,Software Engineer,24777,1 +49882,Male,32,Masters,19,44,25,52,65,7.0,1,88,Urban,Manager,144089,0 +49883,Male,35,Diploma,11,72,85,81,82,9.0,1,73,Rural,HR Executive,30952,1 +49884,Male,34,Diploma,19,84,43,41,22,8.0,4,69,Urban,ML Engineer,57459,1 +49885,Male,49,High School,0,83,51,84,20,8.0,0,26,Urban,HR Executive,40171,1 +49886,Male,52,PhD,2,82,56,29,31,8.0,4,23,Semi-Urban,Software Engineer,138745,0 +49887,Male,38,Bachelors,17,15,43,66,74,0.0,7,25,Urban,ML Engineer,87939,0 +49888,Male,21,Diploma,1,43,29,50,84,7.0,7,87,Urban,HR Executive,37422,0 +49889,Male,33,Bachelors,6,68,38,8,78,4.0,2,87,Rural,Data Analyst,81696,0 +49890,Male,28,Bachelors,16,40,62,55,60,0.0,6,19,Semi-Urban,Manager,110659,0 +49891,Male,51,High School,15,29,80,37,27,2.0,5,89,Urban,HR Executive,118877,1 +49892,Female,49,Bachelors,17,83,51,20,27,1.0,7,65,Semi-Urban,HR Executive,127790,0 +49893,Male,36,High School,9,35,28,40,84,4.0,7,85,Rural,HR Executive,123508,0 +49894,Female,49,Masters,15,38,0,95,10,8.0,5,9,Rural,HR Executive,96473,0 +49895,Male,49,Diploma,0,22,97,82,32,2.0,5,65,Urban,ML Engineer,41236,1 +49896,Female,25,Bachelors,2,33,69,77,85,9.0,3,55,Urban,HR Executive,43293,0 +49897,Male,52,PhD,11,68,5,37,77,8.0,1,17,Rural,Data Analyst,106132,0 +49898,Male,47,Masters,14,61,26,98,0,2.0,4,83,Rural,HR Executive,79164,1 +49899,Male,40,Diploma,17,83,36,26,91,6.0,0,16,Semi-Urban,ML Engineer,56565,0 +49900,Female,36,Masters,7,9,51,78,57,9.0,6,73,Urban,Data Analyst,135128,0 +49901,Female,53,Diploma,12,56,56,76,53,4.0,4,64,Urban,HR Executive,29219,1 +49902,Female,58,Diploma,14,30,86,48,5,0.0,6,1,Urban,Manager,75836,0 +49903,Female,31,Bachelors,1,69,74,98,0,3.0,7,33,Rural,Software Engineer,26949,1 +49904,Female,47,Bachelors,6,70,1,81,47,6.0,6,94,Urban,Software Engineer,82705,1 +49905,Male,22,Bachelors,3,72,21,5,87,5.0,5,40,Urban,ML Engineer,105801,0 +49906,Female,48,Bachelors,15,81,42,27,54,1.0,4,79,Semi-Urban,Software Engineer,101627,0 +49907,Male,52,Diploma,19,81,65,79,77,1.0,3,6,Rural,Software Engineer,50245,0 +49908,Female,44,Bachelors,0,27,35,79,21,9.0,7,49,Urban,Data Analyst,99932,0 +49909,Male,27,Bachelors,16,54,63,53,91,7.0,1,35,Urban,Manager,129021,0 +49910,Male,46,Diploma,9,77,58,13,49,9.0,4,98,Rural,ML Engineer,122322,1 +49911,Male,24,Bachelors,2,88,92,10,90,3.0,7,4,Urban,HR Executive,54424,0 +49912,Male,58,Bachelors,1,76,19,93,87,2.0,2,15,Semi-Urban,Data Analyst,97675,0 +49913,Female,55,Diploma,6,28,86,61,18,9.0,6,95,Urban,HR Executive,93563,1 +49914,Male,42,High School,16,86,39,64,8,0.0,1,46,Urban,Software Engineer,75235,1 +49915,Other,28,Diploma,10,28,43,28,38,1.0,1,98,Urban,Software Engineer,24460,0 +49916,Male,40,Masters,12,34,62,19,69,2.0,6,2,Urban,Data Analyst,64502,0 +49917,Female,41,High School,16,74,56,7,19,5.0,3,71,Urban,ML Engineer,87053,0 +49918,Female,30,Bachelors,13,19,38,7,29,3.0,1,14,Semi-Urban,Manager,123184,0 +49919,Male,40,Diploma,6,63,72,33,23,6.0,5,45,Urban,Manager,111105,0 +49920,Female,55,Diploma,14,63,17,84,98,9.0,5,20,Semi-Urban,Data Analyst,30348,0 +49921,Male,55,Bachelors,15,38,33,61,85,1.0,6,24,Semi-Urban,Software Engineer,24554,0 +49922,Male,47,Masters,19,46,10,89,31,1.0,0,3,Rural,Software Engineer,111212,0 +49923,Male,24,Bachelors,2,43,73,24,56,7.0,1,87,Urban,ML Engineer,37716,0 +49924,Female,32,Bachelors,14,8,46,63,11,2.0,6,44,Urban,HR Executive,139934,0 +49925,Male,36,Diploma,0,69,39,32,14,5.0,4,64,Urban,Manager,103466,0 +49926,Male,34,High School,17,5,49,2,65,0.0,3,88,Semi-Urban,Manager,141135,0 +49927,Male,56,Bachelors,9,71,71,37,27,5.0,2,81,Urban,Data Analyst,125147,1 +49928,Male,35,Diploma,6,88,17,13,90,6.0,4,54,Semi-Urban,Data Analyst,21668,0 +49929,Female,45,Bachelors,6,20,71,77,59,2.0,6,15,Semi-Urban,HR Executive,21013,0 +49930,Male,45,Diploma,9,71,23,14,86,6.0,6,80,Urban,ML Engineer,34008,0 +49931,Male,59,Diploma,0,21,98,47,49,6.0,3,93,Rural,ML Engineer,105923,1 +49932,Male,22,Diploma,1,82,80,15,30,8.0,2,83,Semi-Urban,ML Engineer,20845,1 +49933,Male,36,Bachelors,5,24,1,30,94,1.0,6,30,Urban,Manager,75671,0 +49934,Female,31,Diploma,17,96,1,22,86,3.0,4,35,Semi-Urban,Software Engineer,38947,0 +49935,Male,48,Masters,9,57,38,2,97,4.0,0,32,Semi-Urban,Data Analyst,133415,0 +49936,Female,46,Masters,1,80,6,47,36,1.0,4,40,Urban,Software Engineer,147558,0 +49937,Male,27,Bachelors,5,9,94,78,50,5.0,1,38,Urban,ML Engineer,78805,0 +49938,Male,38,Diploma,15,45,96,25,5,3.0,5,81,Rural,Software Engineer,98800,1 +49939,Female,50,Bachelors,19,33,17,3,79,8.0,7,94,Urban,Manager,101461,0 +49940,Female,51,Bachelors,14,21,39,81,80,0.0,4,50,Rural,ML Engineer,98403,0 +49941,Other,48,Bachelors,15,0,13,91,86,5.0,1,0,Urban,Manager,29003,0 +49942,Male,32,Masters,19,63,24,9,56,3.0,4,63,Urban,Data Analyst,31593,0 +49943,Male,27,Masters,15,16,41,86,20,5.0,5,88,Urban,Manager,72878,0 +49944,Female,27,Masters,4,81,45,73,19,9.0,6,3,Semi-Urban,Software Engineer,135113,0 +49945,Male,38,Bachelors,10,50,86,13,46,0.0,1,26,Semi-Urban,Data Analyst,117978,0 +49946,Male,44,Diploma,15,3,71,1,77,4.0,7,88,Urban,Data Analyst,90070,0 +49947,Male,31,Masters,0,58,72,59,59,2.0,5,0,Urban,Manager,23739,0 +49948,Male,50,Bachelors,19,64,91,68,53,3.0,1,61,Urban,HR Executive,126610,1 +49949,Male,45,Bachelors,3,31,2,89,5,9.0,1,95,Urban,Data Analyst,81282,0 +49950,Other,49,Diploma,0,47,34,14,69,4.0,6,94,Rural,Data Analyst,43751,0 +49951,Male,37,Masters,14,37,27,40,93,5.0,5,44,Urban,Manager,112256,0 +49952,Female,52,High School,19,91,36,43,32,3.0,0,79,Urban,Software Engineer,39807,1 +49953,Male,58,PhD,0,69,53,23,3,3.0,4,25,Urban,Manager,104868,0 +49954,Male,48,Diploma,12,89,61,31,54,8.0,0,60,Rural,Data Analyst,61767,1 +49955,Male,47,High School,15,16,69,78,16,7.0,6,21,Urban,HR Executive,134522,0 +49956,Male,25,Diploma,13,77,7,44,14,9.0,5,99,Rural,Data Analyst,26845,0 +49957,Male,32,High School,0,76,50,36,35,4.0,5,94,Urban,Manager,115326,1 +49958,Female,56,Bachelors,2,10,39,60,28,4.0,3,94,Urban,Manager,70182,0 +49959,Female,49,Bachelors,8,73,74,99,79,2.0,1,22,Urban,ML Engineer,109045,1 +49960,Male,35,High School,2,9,44,37,28,0.0,0,46,Urban,Manager,49592,0 +49961,Male,27,Bachelors,7,71,22,51,39,9.0,6,28,Rural,Software Engineer,90655,0 +49962,Male,22,Bachelors,12,62,46,96,3,0.0,3,66,Urban,Data Analyst,130460,1 +49963,Male,59,Bachelors,2,94,67,21,24,7.0,7,75,Urban,Manager,56926,1 +49964,Female,52,Bachelors,14,61,96,55,60,4.0,3,31,Rural,HR Executive,136903,1 +49965,Male,22,Diploma,2,7,73,60,59,4.0,4,46,Rural,Data Analyst,39935,0 +49966,Male,27,Diploma,5,2,33,81,83,7.0,2,66,Urban,Data Analyst,67056,0 +49967,Female,26,PhD,0,45,7,86,60,8.0,6,13,Urban,HR Executive,144953,0 +49968,Male,54,Masters,4,85,21,4,83,0.0,2,20,Semi-Urban,HR Executive,85802,0 +49969,Male,28,Masters,3,73,49,75,62,0.0,6,19,Semi-Urban,ML Engineer,108293,0 +49970,Male,39,Bachelors,17,14,23,59,57,4.0,0,35,Urban,Software Engineer,144170,0 +49971,Male,50,Diploma,13,88,61,54,97,4.0,1,2,Rural,Software Engineer,123304,0 +49972,Other,37,Diploma,11,84,72,96,97,2.0,6,45,Urban,HR Executive,84612,1 +49973,Male,51,Masters,1,59,57,81,79,1.0,5,84,Semi-Urban,HR Executive,134743,1 +49974,Male,42,Bachelors,19,23,17,2,57,0.0,2,63,Semi-Urban,HR Executive,77603,0 +49975,Male,25,Bachelors,15,67,46,36,2,1.0,7,9,Urban,ML Engineer,47099,0 +49976,Male,52,Bachelors,11,28,40,46,32,9.0,4,8,Rural,Manager,84062,0 +49977,Male,22,High School,13,66,80,4,92,9.0,5,52,Urban,Software Engineer,34572,0 +49978,Other,31,Masters,16,21,59,52,13,8.0,3,58,Urban,HR Executive,75056,0 +49979,Male,21,High School,5,2,69,53,74,8.0,6,40,Urban,Data Analyst,107997,0 +49980,Female,22,Bachelors,2,68,76,35,67,0.0,4,84,Urban,ML Engineer,119804,1 +49981,Male,28,Diploma,12,8,10,8,61,2.0,5,38,Rural,Manager,142971,0 +49982,Male,54,Masters,16,99,43,18,61,8.0,4,0,Urban,Manager,39654,0 +49983,Female,33,Bachelors,12,67,80,75,69,1.0,0,36,Urban,Manager,122649,1 +49984,Female,37,Bachelors,8,50,68,87,38,3.0,5,93,Urban,ML Engineer,115091,1 +49985,Male,35,PhD,13,6,42,25,66,1.0,6,85,Rural,Data Analyst,88492,0 +49986,Male,44,Diploma,17,69,25,9,3,9.0,7,22,Urban,ML Engineer,28179,0 +49987,Male,27,Bachelors,3,13,85,88,35,8.0,2,53,Urban,Software Engineer,38395,1 +49988,Male,49,Bachelors,7,50,36,7,17,6.0,0,37,Semi-Urban,ML Engineer,141904,0 +49989,Male,47,Bachelors,7,27,1,25,6,1.0,2,27,Urban,Manager,80499,0 +49990,Female,23,High School,16,71,12,90,73,0.0,5,65,Rural,ML Engineer,94772,0 +49991,Male,38,High School,1,49,72,1,70,1.0,5,30,Urban,Data Analyst,114144,0 +49992,Male,52,Masters,12,9,96,17,84,3.0,2,61,Urban,HR Executive,75452,0 +49993,Male,56,Bachelors,11,43,61,76,3,3.0,0,29,Urban,ML Engineer,64294,0 +49994,Male,45,Diploma,12,65,16,99,93,0.0,5,68,Urban,Manager,43883,1 +49995,Male,24,Bachelors,14,66,57,1,36,5.0,5,94,Semi-Urban,Software Engineer,25675,0 +49996,Female,46,Diploma,11,75,8,87,4,6.0,5,72,Semi-Urban,Manager,94560,1 +49997,Male,59,Masters,13,18,25,50,48,0.0,7,81,Urban,Manager,45816,0 +49998,Female,24,Masters,3,2,5,80,61,9.0,6,46,Semi-Urban,Software Engineer,58204,0 +49999,Male,41,Diploma,13,23,36,64,1,8.0,7,92,Semi-Urban,Software Engineer,46694,0 +50000,Female,36,Bachelors,16,75,23,61,76,9.0,5,55,Rural,HR Executive,102018,0 +50001,Female,25,Masters,1,55,40,9,93,1.0,1,55,Urban,Data Analyst,67890,0 +50002,Male,50,Masters,2,52,72,34,25,8.0,0,73,Urban,Data Analyst,108009,0 +50003,Male,41,Bachelors,17,41,23,17,50,0.0,2,62,Urban,ML Engineer,53745,0 +50004,Female,54,Masters,2,14,36,88,14,4.0,4,79,Rural,Manager,117697,0 +50005,Male,26,Diploma,8,49,17,8,51,6.0,3,20,Urban,ML Engineer,108143,0 +50006,Male,52,Bachelors,3,85,17,51,45,9.0,6,69,Semi-Urban,Software Engineer,109006,0 +50007,Male,48,Bachelors,3,42,0,10,94,8.0,1,49,Semi-Urban,ML Engineer,96052,0 +50008,Female,36,Diploma,6,76,55,74,21,9.0,3,86,Rural,Data Analyst,140739,1 +50009,Male,35,Bachelors,17,27,81,57,88,8.0,2,53,Urban,Software Engineer,73265,0 +50010,Male,28,High School,8,99,73,16,69,0.0,2,82,Urban,Data Analyst,96099,1 +50011,Other,31,Diploma,1,41,50,78,96,3.0,7,41,Urban,Manager,112657,0 +50012,Male,25,Bachelors,19,64,83,16,72,4.0,7,55,Rural,Data Analyst,39317,0 +50013,Female,43,Diploma,7,91,29,99,91,1.0,0,62,Urban,HR Executive,20747,1 +50014,Female,24,Bachelors,8,72,85,35,42,9.0,7,11,Urban,ML Engineer,142201,0 +50015,Male,48,PhD,12,59,21,86,1,0.0,6,18,Urban,Software Engineer,105835,0 +50016,Female,51,Bachelors,19,85,3,74,72,7.0,4,75,Urban,ML Engineer,135034,0 +50017,Male,31,PhD,17,51,0,91,54,1.0,0,40,Semi-Urban,Software Engineer,64198,0 +50018,Female,59,Masters,19,64,8,41,67,3.0,1,49,Urban,Manager,33530,0 +50019,Female,21,Bachelors,5,87,71,19,95,5.0,0,6,Semi-Urban,Data Analyst,115880,0 +50020,Male,56,High School,7,10,18,67,61,5.0,7,25,Semi-Urban,ML Engineer,45466,0 +50021,Male,57,High School,14,23,61,53,43,6.0,7,38,Urban,HR Executive,145205,0 +50022,Female,40,Diploma,13,38,47,52,37,5.0,1,41,Rural,ML Engineer,20121,0 +50023,Male,28,High School,7,83,98,96,34,9.0,5,10,Semi-Urban,Software Engineer,120668,1 +50024,Female,55,Bachelors,8,68,37,45,6,2.0,1,63,Urban,Data Analyst,145393,0 +50025,Male,36,Masters,16,33,8,86,32,4.0,1,95,Urban,Data Analyst,137526,0 +50026,Female,23,PhD,13,26,58,72,69,2.0,4,80,Urban,HR Executive,137900,0 +50027,Male,52,Bachelors,14,66,33,20,65,3.0,3,14,Semi-Urban,Manager,37680,0 +50028,Female,30,Bachelors,1,90,49,76,26,9.0,7,53,Urban,Software Engineer,139076,1 +50029,Male,38,Diploma,4,40,96,28,46,2.0,5,59,Rural,ML Engineer,135697,0 +50030,Male,51,Diploma,14,93,0,53,37,8.0,2,59,Rural,Data Analyst,52970,0 +50031,Female,29,Bachelors,2,3,94,46,6,0.0,2,84,Urban,Manager,35679,0 +50032,Male,43,PhD,18,34,29,20,8,3.0,1,7,Semi-Urban,Software Engineer,133937,0 +50033,Female,32,Bachelors,8,93,28,50,70,0.0,2,78,Semi-Urban,Software Engineer,105562,1 +50034,Female,58,Bachelors,14,56,84,19,77,6.0,1,86,Rural,ML Engineer,147559,1 +50035,Female,36,Masters,10,53,1,27,12,0.0,1,32,Semi-Urban,Data Analyst,36300,0 +50036,Male,51,Diploma,7,95,27,52,84,1.0,5,27,Urban,HR Executive,35622,0 +50037,Male,50,Masters,2,72,98,70,26,0.0,5,32,Urban,Data Analyst,24229,1 +50038,Male,26,Masters,6,80,45,64,65,1.0,5,45,Urban,Data Analyst,128943,0 +50039,Male,42,Masters,19,53,12,58,75,3.0,1,95,Urban,Software Engineer,88637,0 +50040,Male,58,Masters,10,53,7,29,87,3.0,5,23,Semi-Urban,HR Executive,98116,0 +50041,Female,41,Diploma,18,84,23,42,4,7.0,0,54,Urban,Data Analyst,81556,0 +50042,Female,41,Masters,16,98,59,12,78,3.0,5,60,Rural,Software Engineer,51542,0 +50043,Male,25,Diploma,15,39,41,7,77,9.0,1,96,Semi-Urban,Software Engineer,118856,0 +50044,Female,32,PhD,7,41,51,84,49,0.0,2,51,Urban,Manager,34246,0 +50045,Male,47,Masters,0,46,96,12,41,2.0,5,94,Rural,Manager,51018,1 +50046,Male,46,Masters,13,48,50,64,88,8.0,3,23,Urban,ML Engineer,55768,0 +50047,Male,25,High School,11,31,20,19,49,0.0,6,50,Urban,ML Engineer,74452,0 +50048,Male,36,PhD,15,72,32,17,89,7.0,0,25,Urban,HR Executive,50576,0 +50049,Female,53,High School,5,72,83,93,44,7.0,4,19,Semi-Urban,Data Analyst,62598,1 +50050,Female,57,Bachelors,3,36,19,67,67,2.0,6,45,Rural,ML Engineer,98605,0 +50051,Male,45,Diploma,15,74,53,62,72,2.0,7,51,Urban,Data Analyst,110331,1 +50052,Female,37,Diploma,19,87,19,2,63,3.0,1,42,Semi-Urban,ML Engineer,28617,0 +50053,Male,30,Masters,11,97,63,38,60,6.0,5,15,Semi-Urban,Manager,107389,0 +50054,Female,54,Bachelors,2,33,43,47,84,2.0,0,53,Rural,Software Engineer,124116,0 +50055,Female,55,Bachelors,1,50,9,88,87,8.0,7,5,Urban,Manager,73755,0 +50056,Female,29,Bachelors,18,33,23,67,29,8.0,2,9,Urban,Software Engineer,90337,0 +50057,Male,48,Bachelors,16,85,23,27,0,1.0,5,28,Urban,Data Analyst,76709,0 +50058,Male,54,Bachelors,2,73,8,78,2,7.0,1,97,Rural,Software Engineer,92958,1 +50059,Male,51,Masters,2,61,76,96,26,5.0,2,66,Rural,Manager,50014,1 +50060,Male,58,Bachelors,16,81,97,42,67,1.0,5,70,Urban,Manager,49510,1 +50061,Male,34,Diploma,3,70,68,64,93,9.0,4,7,Semi-Urban,Data Analyst,145742,0 +50062,Male,31,Masters,5,69,33,15,48,8.0,6,60,Semi-Urban,ML Engineer,130954,0 +50063,Female,57,PhD,6,95,63,91,97,6.0,3,2,Semi-Urban,Software Engineer,109099,1 +50064,Male,23,Diploma,14,14,79,5,15,1.0,3,81,Urban,Data Analyst,121364,0 +50065,Female,21,PhD,17,21,54,51,8,6.0,6,11,Urban,HR Executive,84119,0 +50066,Male,28,Bachelors,10,92,87,11,25,0.0,7,32,Urban,Software Engineer,111261,0 +50067,Other,45,Bachelors,14,46,46,24,62,1.0,7,27,Rural,ML Engineer,129748,0 +50068,Other,27,High School,18,16,60,47,43,4.0,5,34,Semi-Urban,Data Analyst,74851,0 +50069,Male,28,Bachelors,16,40,82,29,19,8.0,5,0,Urban,Manager,69035,0 +50070,Other,41,High School,17,47,17,78,73,9.0,5,94,Urban,Manager,142823,0 +50071,Female,25,Bachelors,4,8,71,70,21,3.0,4,88,Urban,Data Analyst,62645,0 +50072,Male,53,Masters,5,69,48,18,9,6.0,4,49,Urban,Manager,139528,0 +50073,Female,28,High School,2,66,12,57,69,3.0,6,70,Urban,Data Analyst,135635,0 +50074,Male,48,Bachelors,11,2,29,92,66,0.0,3,16,Rural,HR Executive,49904,0 +50075,Male,53,Diploma,18,72,68,67,62,8.0,2,37,Urban,ML Engineer,69025,1 +50076,Male,56,Bachelors,16,18,16,32,48,7.0,3,88,Semi-Urban,ML Engineer,51890,0 +50077,Male,54,Bachelors,0,41,31,78,75,2.0,1,98,Rural,Software Engineer,94836,1 +50078,Male,45,Bachelors,1,9,45,72,96,7.0,5,35,Urban,Data Analyst,106321,0 +50079,Other,56,Masters,12,14,89,68,16,4.0,4,13,Rural,HR Executive,129883,0 +50080,Other,37,Bachelors,4,9,93,42,35,3.0,4,68,Urban,ML Engineer,23209,0 +50081,Female,32,Bachelors,18,44,2,61,96,1.0,7,88,Semi-Urban,Manager,126522,0 +50082,Male,28,Masters,8,86,35,33,13,1.0,1,71,Urban,Software Engineer,23082,0 +50083,Female,58,High School,3,15,88,3,99,4.0,4,93,Semi-Urban,Manager,94758,0 +50084,Male,44,Bachelors,6,6,48,42,31,3.0,3,2,Urban,Manager,50867,0 +50085,Female,57,Diploma,4,46,75,63,83,4.0,6,84,Urban,Manager,87436,1 +50086,Male,35,Bachelors,2,68,58,86,74,8.0,7,90,Urban,ML Engineer,23663,1 +50087,Female,32,Bachelors,5,41,14,93,26,9.0,5,90,Urban,Software Engineer,39051,0 +50088,Female,44,Diploma,14,35,34,82,25,6.0,0,75,Urban,HR Executive,39585,0 +50089,Other,48,Bachelors,11,81,96,88,13,8.0,7,46,Rural,Manager,73134,1 +50090,Female,48,Bachelors,19,99,34,28,53,5.0,6,97,Urban,Manager,147089,1 +50091,Female,24,Masters,18,64,88,35,5,9.0,3,29,Semi-Urban,Software Engineer,129075,0 +50092,Female,37,High School,3,83,81,38,90,9.0,3,17,Rural,Software Engineer,119210,0 +50093,Female,37,Bachelors,10,0,47,9,14,9.0,0,78,Semi-Urban,Data Analyst,99556,0 +50094,Female,34,Diploma,6,5,73,57,10,3.0,1,47,Rural,Manager,31823,0 +50095,Male,39,High School,5,19,10,41,86,7.0,1,60,Urban,HR Executive,25990,0 +50096,Female,31,Bachelors,11,18,5,19,2,8.0,5,35,Rural,HR Executive,85209,0 +50097,Male,48,Bachelors,10,33,98,77,16,6.0,4,13,Semi-Urban,Data Analyst,129091,0 +50098,Female,56,PhD,18,12,32,72,42,1.0,4,35,Rural,Software Engineer,22654,0 +50099,Male,59,High School,18,19,21,96,18,6.0,2,36,Semi-Urban,HR Executive,72975,0 +50100,Other,58,Diploma,10,0,56,45,17,9.0,6,24,Urban,Manager,90110,0 +50101,Male,59,Diploma,18,67,77,83,5,5.0,6,80,Rural,HR Executive,89731,1 +50102,Male,46,High School,6,74,98,32,1,3.0,4,86,Urban,ML Engineer,85139,1 +50103,Female,24,Diploma,9,83,42,29,98,6.0,2,94,Rural,Data Analyst,34015,1 +50104,Male,50,Masters,17,88,70,56,81,5.0,6,83,Urban,Manager,96599,1 +50105,Male,26,Diploma,8,60,75,62,49,2.0,0,75,Semi-Urban,Software Engineer,62039,1 +50106,Female,27,High School,9,88,58,49,67,4.0,4,69,Urban,ML Engineer,124720,1 +50107,Male,29,Bachelors,17,84,14,21,35,0.0,6,6,Semi-Urban,Software Engineer,73736,0 +50108,Male,26,High School,14,92,71,71,65,1.0,1,66,Urban,Software Engineer,54042,1 +50109,Female,31,Masters,9,52,2,46,62,3.0,4,40,Urban,ML Engineer,108515,0 +50110,Other,31,Diploma,2,85,62,82,93,5.0,0,37,Semi-Urban,Data Analyst,45148,1 +50111,Male,27,Bachelors,14,54,51,11,43,5.0,0,22,Semi-Urban,Manager,91377,0 +50112,Male,46,Masters,17,62,85,42,63,8.0,7,95,Semi-Urban,Manager,72521,1 +50113,Male,47,Bachelors,13,25,18,37,94,8.0,0,18,Urban,Software Engineer,33195,0 +50114,Male,32,Masters,3,51,83,60,25,3.0,5,39,Urban,HR Executive,92497,0 +50115,Male,48,Bachelors,17,20,61,19,73,9.0,7,35,Semi-Urban,HR Executive,58548,0 +50116,Male,21,Diploma,14,87,56,54,57,0.0,5,80,Semi-Urban,Data Analyst,111776,1 +50117,Male,27,Diploma,19,73,42,97,15,3.0,7,89,Rural,Manager,111794,1 +50118,Female,30,Masters,1,82,73,44,1,4.0,7,78,Urban,Software Engineer,117385,1 +50119,Male,55,Bachelors,17,0,30,68,73,2.0,0,36,Urban,Software Engineer,114867,0 +50120,Male,25,High School,4,99,20,39,59,1.0,7,85,Urban,ML Engineer,45271,1 +50121,Female,40,Bachelors,2,23,51,68,63,8.0,4,0,Semi-Urban,ML Engineer,130693,0 +50122,Male,36,Masters,15,3,81,60,69,0.0,7,79,Urban,Manager,20346,0 +50123,Female,33,PhD,14,16,15,24,29,6.0,7,87,Urban,ML Engineer,115441,0 +50124,Male,25,Bachelors,3,88,32,36,8,2.0,1,77,Semi-Urban,HR Executive,133217,0 +50125,Male,25,Masters,11,62,63,25,59,3.0,7,45,Semi-Urban,HR Executive,57058,0 +50126,Male,56,High School,15,16,11,85,47,8.0,6,43,Urban,Data Analyst,101496,0 +50127,Male,58,Bachelors,15,66,74,33,10,2.0,2,65,Urban,HR Executive,23537,1 +50128,Female,40,Diploma,1,36,57,59,24,7.0,1,56,Urban,Manager,82733,0 +50129,Female,29,Bachelors,10,77,25,14,84,2.0,7,19,Urban,ML Engineer,42902,0 +50130,Male,35,Bachelors,14,99,76,92,89,3.0,5,90,Urban,Data Analyst,108546,1 +50131,Male,55,Masters,10,12,83,25,74,3.0,7,24,Urban,Data Analyst,100936,0 +50132,Male,25,Masters,11,77,53,37,67,1.0,1,55,Urban,Software Engineer,111198,0 +50133,Female,29,Bachelors,1,26,15,72,48,4.0,4,39,Semi-Urban,ML Engineer,121430,0 +50134,Male,28,Bachelors,8,80,81,42,3,7.0,0,30,Rural,ML Engineer,73342,0 +50135,Male,22,Bachelors,3,92,10,53,5,0.0,3,47,Urban,HR Executive,68291,0 +50136,Male,28,PhD,2,34,40,20,71,3.0,5,33,Urban,HR Executive,118971,0 +50137,Male,22,Bachelors,13,44,72,67,53,3.0,3,94,Urban,Manager,73553,1 +50138,Male,26,Bachelors,13,45,57,17,35,0.0,1,38,Urban,Data Analyst,147928,0 +50139,Female,21,Bachelors,13,87,14,85,57,6.0,7,98,Rural,Data Analyst,74406,1 +50140,Female,40,Masters,6,8,1,80,87,3.0,5,34,Urban,Manager,82231,0 +50141,Female,24,Masters,18,56,17,15,29,3.0,6,42,Urban,HR Executive,88107,0 +50142,Male,39,Diploma,5,48,73,52,96,1.0,3,37,Urban,ML Engineer,75857,0 +50143,Male,44,Bachelors,11,23,58,54,66,2.0,2,44,Urban,Manager,49184,0 +50144,Male,39,Masters,2,46,97,87,29,6.0,2,45,Semi-Urban,Software Engineer,47534,1 +50145,Female,45,Bachelors,8,28,40,69,52,1.0,5,56,Rural,HR Executive,51399,0 +50146,Male,56,High School,12,3,19,13,12,6.0,4,39,Rural,Software Engineer,53125,0 +50147,Male,22,Bachelors,16,41,46,84,40,1.0,3,97,Rural,ML Engineer,60439,1 +50148,Female,47,Bachelors,19,30,53,45,64,2.0,6,38,Urban,Manager,92468,0 +50149,Male,25,High School,1,54,47,69,62,5.0,5,48,Urban,Data Analyst,115444,0 +50150,Male,47,Masters,15,51,4,72,9,6.0,0,13,Semi-Urban,HR Executive,145631,0 +50151,Male,32,Bachelors,12,22,18,47,49,8.0,4,15,Rural,Data Analyst,45247,0 +50152,Male,34,Masters,6,61,56,78,30,4.0,2,97,Urban,HR Executive,98534,1 +50153,Male,40,Bachelors,18,27,80,32,98,7.0,4,26,Rural,Data Analyst,143901,0 +50154,Male,35,Diploma,7,85,55,25,83,3.0,4,94,Urban,Data Analyst,66450,1 +50155,Male,56,Diploma,6,19,74,40,47,2.0,3,76,Semi-Urban,HR Executive,109088,0 +50156,Male,34,Masters,18,71,41,32,58,9.0,2,79,Urban,ML Engineer,112743,0 +50157,Male,42,Masters,12,81,5,34,16,2.0,7,99,Urban,ML Engineer,96184,0 +50158,Female,59,High School,14,3,14,57,61,3.0,6,43,Urban,HR Executive,112932,0 +50159,Male,25,Diploma,1,77,77,28,22,7.0,4,23,Urban,Software Engineer,24926,0 +50160,Male,47,Bachelors,6,78,44,29,74,5.0,6,43,Semi-Urban,ML Engineer,107617,0 +50161,Female,50,Bachelors,1,66,51,23,90,8.0,6,78,Urban,Manager,131452,0 +50162,Male,55,Bachelors,13,0,7,10,74,0.0,2,80,Urban,Manager,31133,0 +50163,Male,40,Masters,3,26,98,93,69,5.0,3,73,Urban,Data Analyst,30140,1 +50164,Male,28,Diploma,2,85,93,51,35,1.0,5,91,Rural,Data Analyst,144524,1 +50165,Other,52,High School,16,60,91,16,41,9.0,1,12,Semi-Urban,Software Engineer,68056,0 +50166,Other,46,Bachelors,17,92,73,55,75,8.0,2,96,Semi-Urban,Data Analyst,149212,1 +50167,Female,36,Bachelors,15,95,93,70,13,2.0,4,0,Semi-Urban,ML Engineer,126142,1 +50168,Female,30,Masters,7,49,0,30,45,7.0,5,49,Urban,Data Analyst,149637,0 +50169,Male,22,Diploma,18,77,70,66,68,4.0,6,31,Urban,Manager,142600,1 +50170,Other,31,Masters,15,94,18,32,39,2.0,7,92,Semi-Urban,Software Engineer,94740,0 +50171,Male,43,Diploma,16,44,72,1,84,4.0,2,65,Urban,Manager,136794,0 +50172,Male,40,PhD,5,26,93,68,88,1.0,7,16,Urban,Software Engineer,121300,0 +50173,Male,56,Masters,17,71,36,28,95,5.0,5,73,Urban,Software Engineer,87358,0 +50174,Male,44,Bachelors,3,6,78,85,66,7.0,1,78,Rural,Data Analyst,35054,1 +50175,Male,54,Bachelors,4,41,17,12,80,6.0,2,96,Urban,Manager,121364,0 +50176,Male,39,Diploma,18,4,91,78,70,7.0,5,96,Semi-Urban,Software Engineer,41962,1 +50177,Female,42,Diploma,17,3,78,68,30,7.0,6,96,Urban,HR Executive,101919,1 +50178,Male,29,High School,5,27,15,10,78,3.0,1,37,Rural,HR Executive,25284,0 +50179,Female,46,Masters,9,5,47,86,76,8.0,3,23,Semi-Urban,Software Engineer,82415,0 +50180,Male,39,Bachelors,10,61,88,83,72,2.0,7,89,Urban,HR Executive,128358,1 +50181,Female,41,Masters,4,9,65,47,41,4.0,5,77,Semi-Urban,Manager,143800,0 +50182,Male,32,Bachelors,2,0,54,77,88,7.0,1,87,Urban,HR Executive,24713,0 +50183,Female,38,Bachelors,8,83,74,56,59,2.0,1,97,Urban,HR Executive,122739,1 +50184,Male,59,Masters,18,6,61,66,44,4.0,1,94,Urban,HR Executive,146994,0 +50185,Male,29,High School,3,98,64,90,60,7.0,3,8,Rural,Manager,33527,1 +50186,Female,58,Bachelors,7,44,55,16,83,3.0,7,28,Semi-Urban,ML Engineer,118149,0 +50187,Female,55,Bachelors,12,58,39,97,6,6.0,2,48,Urban,ML Engineer,99991,1 +50188,Male,57,Masters,17,29,81,29,91,3.0,1,89,Urban,ML Engineer,45425,0 +50189,Male,32,Bachelors,11,98,59,27,34,1.0,7,93,Urban,Data Analyst,109959,1 +50190,Male,21,PhD,14,69,47,54,42,8.0,7,86,Urban,HR Executive,65538,1 +50191,Male,40,Diploma,14,20,9,78,31,6.0,7,29,Urban,Manager,119625,0 +50192,Female,37,Bachelors,13,46,43,84,14,2.0,5,53,Rural,HR Executive,141267,0 +50193,Male,24,Masters,3,30,43,1,89,1.0,6,95,Urban,Manager,84654,0 +50194,Female,22,Masters,12,85,61,84,36,9.0,0,36,Urban,HR Executive,145250,1 +50195,Female,41,Diploma,11,94,49,17,81,3.0,1,70,Urban,Manager,90150,0 +50196,Male,22,Bachelors,5,1,85,98,71,7.0,0,11,Semi-Urban,Data Analyst,44019,0 +50197,Male,30,Bachelors,0,17,98,37,76,4.0,1,85,Urban,Software Engineer,108008,1 +50198,Male,31,Masters,7,71,5,28,3,7.0,4,93,Urban,HR Executive,137003,0 +50199,Female,36,Diploma,2,59,54,33,5,8.0,2,44,Urban,Manager,82667,0 +50200,Male,23,Diploma,6,9,58,55,41,9.0,3,2,Semi-Urban,Manager,134585,0 +50201,Male,33,Masters,1,81,56,85,96,7.0,3,38,Semi-Urban,Data Analyst,147070,1 +50202,Male,42,PhD,9,18,1,49,12,5.0,0,14,Urban,Data Analyst,114165,0 +50203,Male,54,Diploma,0,50,74,92,97,2.0,1,61,Urban,HR Executive,124834,1 +50204,Male,53,Bachelors,9,88,17,74,83,4.0,3,54,Urban,HR Executive,33356,0 +50205,Male,46,Bachelors,14,72,89,47,34,2.0,6,21,Semi-Urban,HR Executive,50350,0 +50206,Male,48,Bachelors,16,54,98,1,10,9.0,4,40,Rural,HR Executive,38211,0 +50207,Female,47,Bachelors,17,79,55,98,97,5.0,4,89,Urban,Data Analyst,107508,1 +50208,Male,56,Masters,18,88,66,3,95,9.0,7,47,Urban,Data Analyst,54332,0 +50209,Female,48,Diploma,8,94,25,56,45,5.0,0,97,Urban,Data Analyst,30110,1 +50210,Male,59,Bachelors,7,84,48,74,43,9.0,4,12,Rural,ML Engineer,113741,0 +50211,Female,35,Masters,0,24,72,12,66,0.0,4,33,Semi-Urban,HR Executive,93167,0 +50212,Male,38,Bachelors,13,93,23,79,46,4.0,7,66,Semi-Urban,Software Engineer,60809,1 +50213,Male,55,Bachelors,13,6,2,48,45,3.0,1,56,Urban,ML Engineer,63047,0 +50214,Female,25,Bachelors,16,2,88,36,52,3.0,1,28,Rural,HR Executive,75523,0 +50215,Female,27,Diploma,4,36,92,13,34,2.0,0,21,Rural,Manager,116714,0 +50216,Male,38,Bachelors,18,59,67,18,36,2.0,5,32,Semi-Urban,Software Engineer,135216,0 +50217,Male,28,Diploma,9,5,51,80,9,8.0,3,8,Semi-Urban,ML Engineer,148399,0 +50218,Female,31,Bachelors,12,25,82,77,75,7.0,1,71,Semi-Urban,Software Engineer,77955,1 +50219,Male,59,Masters,7,29,10,75,41,3.0,7,31,Urban,Data Analyst,79589,0 +50220,Female,39,Bachelors,11,20,88,52,93,5.0,5,28,Urban,ML Engineer,25629,0 +50221,Other,31,Diploma,2,99,58,49,23,4.0,5,67,Urban,ML Engineer,85704,1 +50222,Male,42,High School,19,6,10,74,62,1.0,1,76,Urban,ML Engineer,75870,0 +50223,Female,52,Bachelors,19,58,73,46,81,2.0,4,48,Urban,ML Engineer,33179,0 +50224,Male,34,Diploma,10,17,60,97,33,6.0,6,59,Urban,ML Engineer,116484,0 +50225,Female,51,Diploma,12,68,41,84,96,5.0,5,43,Rural,HR Executive,39199,0 +50226,Male,38,Masters,5,39,73,96,71,0.0,3,63,Urban,ML Engineer,27115,1 +50227,Male,41,High School,17,46,31,17,62,7.0,3,96,Urban,Data Analyst,51190,0 +50228,Female,40,Diploma,5,33,95,76,79,9.0,3,40,Urban,Software Engineer,49980,1 +50229,Male,58,Masters,14,18,25,86,3,4.0,0,63,Urban,ML Engineer,110450,0 +50230,Female,23,Bachelors,3,50,72,9,15,5.0,1,20,Urban,Data Analyst,131656,0 +50231,Male,31,Bachelors,13,26,2,65,16,7.0,5,28,Urban,ML Engineer,118218,0 +50232,Male,57,High School,19,3,33,23,37,9.0,0,1,Urban,ML Engineer,20151,0 +50233,Male,57,Masters,11,6,28,43,61,4.0,2,2,Rural,Software Engineer,63961,0 +50234,Female,56,High School,0,55,96,36,79,2.0,1,60,Urban,HR Executive,64261,1 +50235,Male,33,Diploma,2,3,93,80,91,4.0,5,44,Semi-Urban,ML Engineer,142672,0 +50236,Female,40,High School,2,56,3,25,9,4.0,7,57,Urban,Software Engineer,41086,0 +50237,Male,31,Bachelors,13,61,43,67,80,0.0,2,45,Urban,Manager,45417,0 +50238,Male,58,Masters,12,53,61,55,62,0.0,0,68,Semi-Urban,Data Analyst,61444,1 +50239,Female,58,Bachelors,11,8,76,87,67,6.0,1,94,Urban,Data Analyst,28574,1 +50240,Male,32,PhD,8,92,71,90,46,6.0,4,13,Urban,Software Engineer,79589,1 +50241,Male,58,Bachelors,15,30,35,29,38,2.0,4,16,Semi-Urban,Manager,27015,0 +50242,Female,46,High School,4,8,0,22,54,1.0,1,92,Urban,Data Analyst,28207,0 +50243,Male,25,Masters,3,84,18,66,56,0.0,7,20,Urban,Manager,28558,0 +50244,Female,42,Bachelors,5,61,7,52,91,4.0,6,32,Urban,Data Analyst,85996,0 +50245,Female,31,High School,14,48,29,54,47,6.0,7,78,Semi-Urban,Data Analyst,40333,0 +50246,Male,49,Masters,5,61,44,12,65,2.0,6,24,Rural,Software Engineer,89432,0 +50247,Female,48,Diploma,16,22,37,42,64,7.0,7,56,Semi-Urban,Data Analyst,91466,0 +50248,Female,24,Diploma,3,30,75,44,67,9.0,0,54,Urban,Manager,108314,0 +50249,Female,30,High School,1,99,85,2,95,2.0,5,5,Rural,HR Executive,142100,0 +50250,Male,31,PhD,16,42,59,23,41,1.0,1,18,Rural,Software Engineer,132691,0 +50251,Female,24,Bachelors,11,81,15,42,51,4.0,2,31,Urban,Manager,23448,0 +50252,Female,37,Bachelors,11,66,97,38,1,6.0,6,26,Urban,Software Engineer,43064,0 +50253,Male,40,Diploma,6,76,15,96,57,4.0,5,96,Urban,HR Executive,69425,1 +50254,Male,33,Masters,6,73,64,54,8,4.0,1,82,Semi-Urban,HR Executive,52591,1 +50255,Male,40,Masters,13,16,36,38,56,6.0,7,46,Semi-Urban,HR Executive,142052,0 +50256,Female,45,Bachelors,4,50,82,12,7,2.0,3,54,Urban,ML Engineer,110552,0 +50257,Other,46,Diploma,12,52,86,29,97,7.0,2,10,Urban,Manager,57502,0 +50258,Male,30,High School,0,7,12,33,2,1.0,2,34,Urban,Data Analyst,134359,0 +50259,Other,54,Bachelors,11,79,63,7,64,9.0,5,71,Urban,HR Executive,105360,0 +50260,Male,34,Diploma,6,79,54,88,61,0.0,4,41,Urban,Manager,68801,1 +50261,Male,56,Masters,1,58,87,28,95,5.0,1,50,Urban,ML Engineer,86337,0 +50262,Male,39,Bachelors,2,7,5,22,69,6.0,3,10,Semi-Urban,Data Analyst,114731,0 +50263,Male,42,Masters,18,43,75,46,29,1.0,5,3,Rural,HR Executive,94224,0 +50264,Male,55,Diploma,7,29,23,7,32,0.0,2,32,Urban,Software Engineer,113184,0 +50265,Female,56,Bachelors,7,46,66,54,29,6.0,0,30,Urban,ML Engineer,110755,0 +50266,Male,27,Diploma,8,26,12,54,9,8.0,6,60,Semi-Urban,HR Executive,25967,0 +50267,Male,55,Diploma,2,66,33,60,92,5.0,1,87,Rural,ML Engineer,111542,1 +50268,Female,23,Diploma,7,51,99,61,97,3.0,2,10,Urban,HR Executive,44711,0 +50269,Female,45,PhD,18,8,50,75,71,4.0,3,20,Urban,HR Executive,99982,0 +50270,Other,24,Bachelors,16,70,74,51,29,5.0,3,34,Urban,Manager,26149,0 +50271,Male,44,Bachelors,17,97,27,27,13,2.0,0,23,Urban,Software Engineer,71427,0 +50272,Female,41,High School,6,54,0,8,31,7.0,6,70,Urban,Software Engineer,71091,0 +50273,Male,46,Masters,10,7,8,10,2,2.0,2,24,Semi-Urban,Data Analyst,67192,0 +50274,Male,52,Masters,4,4,45,50,19,9.0,2,48,Semi-Urban,HR Executive,51709,0 +50275,Other,44,Bachelors,9,18,49,7,16,7.0,1,61,Urban,Software Engineer,119629,0 +50276,Male,26,Bachelors,16,2,10,36,60,4.0,0,31,Rural,Manager,54125,0 +50277,Female,21,High School,3,75,96,29,49,8.0,2,14,Urban,Manager,38169,0 +50278,Female,38,High School,1,48,9,96,29,6.0,7,42,Semi-Urban,Data Analyst,108916,0 +50279,Male,50,High School,8,63,77,31,77,3.0,1,35,Semi-Urban,ML Engineer,126710,0 +50280,Female,57,Masters,3,25,68,37,12,3.0,1,42,Semi-Urban,Software Engineer,63658,0 +50281,Male,49,Diploma,15,99,59,76,51,1.0,1,63,Urban,Manager,25194,1 +50282,Male,27,Diploma,10,76,0,9,95,9.0,1,32,Urban,Software Engineer,74880,0 +50283,Female,37,Masters,10,73,64,33,76,6.0,6,17,Urban,Manager,107043,0 +50284,Female,53,High School,4,49,69,77,98,7.0,1,77,Semi-Urban,HR Executive,137980,1 +50285,Male,35,PhD,2,48,26,78,89,4.0,4,23,Rural,Data Analyst,88321,0 +50286,Other,54,Diploma,0,70,84,58,6,4.0,5,36,Semi-Urban,HR Executive,38653,1 +50287,Male,41,PhD,14,11,4,58,88,0.0,6,73,Urban,Manager,24487,0 +50288,Male,48,Bachelors,6,26,45,28,11,8.0,3,76,Rural,Manager,106869,0 +50289,Female,39,Bachelors,14,2,49,88,37,6.0,3,71,Urban,Manager,33376,0 +50290,Male,58,High School,7,91,56,39,85,0.0,3,93,Urban,HR Executive,50070,1 +50291,Female,54,High School,3,27,53,54,58,7.0,4,17,Urban,Data Analyst,63819,0 +50292,Female,35,Diploma,9,22,26,23,46,0.0,1,39,Semi-Urban,Data Analyst,47161,0 +50293,Female,35,Diploma,3,11,27,25,45,4.0,1,70,Semi-Urban,ML Engineer,104884,0 +50294,Female,58,Bachelors,1,77,18,55,38,5.0,0,90,Semi-Urban,HR Executive,81329,0 +50295,Female,40,High School,17,19,81,10,1,6.0,0,11,Semi-Urban,Software Engineer,41054,0 +50296,Female,55,PhD,5,95,83,97,41,3.0,4,37,Urban,Software Engineer,31578,1 +50297,Male,47,Bachelors,3,63,10,32,66,2.0,7,82,Semi-Urban,Data Analyst,120971,0 +50298,Female,26,High School,8,66,81,89,17,9.0,0,34,Urban,Manager,117895,1 +50299,Male,42,High School,0,95,6,51,78,9.0,1,48,Urban,ML Engineer,37641,0 +50300,Male,21,Bachelors,12,65,41,93,34,7.0,1,21,Rural,ML Engineer,40249,0 +50301,Male,54,Bachelors,19,72,40,68,85,8.0,5,10,Urban,ML Engineer,37914,0 +50302,Female,54,High School,1,10,80,26,39,8.0,5,34,Urban,Manager,120407,0 +50303,Male,34,PhD,14,72,97,1,73,8.0,5,10,Rural,Software Engineer,79600,0 +50304,Male,37,PhD,18,9,38,6,65,5.0,5,13,Semi-Urban,Data Analyst,21379,0 +50305,Male,29,High School,19,81,32,87,95,5.0,1,35,Urban,Data Analyst,74719,1 +50306,Male,55,Bachelors,3,23,36,40,81,2.0,5,74,Semi-Urban,ML Engineer,126433,0 +50307,Male,52,Bachelors,5,90,3,36,15,7.0,3,29,Urban,Software Engineer,87841,0 +50308,Female,59,Bachelors,2,9,92,67,73,2.0,3,22,Urban,HR Executive,40313,0 +50309,Male,41,High School,10,29,41,95,26,3.0,3,77,Semi-Urban,Data Analyst,96868,1 +50310,Female,21,Diploma,4,94,41,57,94,5.0,6,12,Urban,ML Engineer,96463,0 +50311,Male,33,Masters,10,57,67,82,10,3.0,0,62,Urban,Manager,72033,1 +50312,Male,39,PhD,18,8,39,68,82,3.0,1,14,Rural,Manager,144485,0 +50313,Female,38,Diploma,16,81,75,57,79,0.0,1,46,Semi-Urban,HR Executive,138957,1 +50314,Male,25,PhD,7,69,35,42,41,7.0,4,5,Urban,HR Executive,22372,0 +50315,Male,34,Masters,9,53,77,29,3,0.0,3,41,Semi-Urban,HR Executive,108696,0 +50316,Other,44,Diploma,0,61,97,35,1,8.0,1,44,Urban,Software Engineer,20808,0 +50317,Male,38,Diploma,7,34,33,17,56,0.0,1,36,Semi-Urban,Manager,66079,0 +50318,Male,54,Diploma,15,76,25,91,30,5.0,5,26,Urban,Data Analyst,120049,0 +50319,Male,39,Bachelors,2,16,69,69,79,4.0,6,24,Semi-Urban,HR Executive,95539,0 +50320,Male,55,Masters,18,32,75,70,66,7.0,5,65,Semi-Urban,Software Engineer,97695,1 +50321,,46,Diploma,12,5,4,13,81,0.0,4,10,Urban,Manager,66563,0 +50322,Female,26,Bachelors,11,57,56,58,42,7.0,1,4,Urban,Manager,89280,0 +50323,Male,55,High School,17,70,55,98,36,4.0,1,31,Urban,Software Engineer,75341,1 +50324,Male,32,Bachelors,7,60,30,17,44,1.0,1,17,Rural,HR Executive,125072,0 +50325,Female,38,Diploma,17,76,17,55,77,1.0,6,37,Semi-Urban,Software Engineer,91898,0 +50326,Male,49,PhD,8,85,54,94,85,0.0,2,24,Urban,ML Engineer,88618,1 +50327,Male,47,High School,8,93,26,45,83,5.0,7,60,Urban,ML Engineer,102684,0 +50328,Male,39,Bachelors,16,46,45,5,22,9.0,2,8,Semi-Urban,Manager,123983,0 +50329,Male,45,Masters,2,84,56,93,28,5.0,7,2,Semi-Urban,Data Analyst,72274,1 +50330,Male,38,Bachelors,15,62,42,89,6,2.0,3,31,Semi-Urban,Data Analyst,23326,0 +50331,Male,49,High School,17,53,85,41,44,5.0,6,55,Urban,Software Engineer,74675,0 +50332,Other,51,Masters,5,91,95,60,57,2.0,6,51,Semi-Urban,ML Engineer,70750,1 +50333,Male,39,Masters,0,49,76,33,76,1.0,3,26,Semi-Urban,Data Analyst,20398,0 +50334,Female,59,High School,3,25,33,29,62,0.0,3,86,Urban,Software Engineer,91070,0 +50335,Male,22,Bachelors,5,8,95,88,65,9.0,1,84,Urban,Manager,102464,1 +50336,Male,45,High School,9,4,80,46,36,6.0,0,50,Urban,Data Analyst,84960,0 +50337,Male,35,High School,12,22,37,34,53,0.0,1,55,Rural,ML Engineer,22641,0 +50338,Male,37,Diploma,15,63,26,10,96,0.0,7,14,Semi-Urban,Software Engineer,137939,0 +50339,Male,31,High School,5,98,78,60,6,6.0,1,51,Urban,ML Engineer,54959,1 +50340,Other,55,High School,3,30,42,20,60,0.0,3,68,Semi-Urban,ML Engineer,81699,0 +50341,Female,36,Diploma,4,60,84,72,95,6.0,3,80,Semi-Urban,Software Engineer,48021,1 +50342,Male,38,High School,16,93,67,6,4,7.0,2,37,Urban,Manager,80338,0 +50343,Male,35,Bachelors,13,24,44,53,42,6.0,7,70,Rural,Data Analyst,121981,0 +50344,Male,59,PhD,0,62,42,9,23,0.0,6,64,Urban,Software Engineer,122708,0 +50345,Female,27,High School,19,53,15,87,5,9.0,7,37,Urban,ML Engineer,101271,0 +50346,Male,32,High School,9,87,11,30,87,3.0,5,3,Urban,Software Engineer,73041,0 +50347,Male,27,Bachelors,15,5,94,14,34,0.0,4,9,Semi-Urban,HR Executive,37400,0 +50348,Male,40,Bachelors,11,7,18,91,40,5.0,7,60,Urban,Manager,24818,0 +50349,Male,26,PhD,2,5,29,4,43,4.0,2,90,Semi-Urban,Data Analyst,141493,0 +50350,Male,52,High School,4,9,8,0,65,9.0,3,8,Urban,HR Executive,119505,0 +50351,Other,39,Diploma,15,74,5,83,91,5.0,6,9,Urban,Data Analyst,37740,0 +50352,Male,51,Masters,13,47,82,57,7,4.0,7,6,Urban,Software Engineer,84470,0 +50353,Male,38,Bachelors,19,61,77,8,91,3.0,4,56,Urban,HR Executive,78057,0 +50354,Other,23,Diploma,0,2,77,40,27,2.0,5,96,Urban,Software Engineer,70190,0 +50355,Male,57,Diploma,0,97,3,77,6,2.0,3,87,Urban,Software Engineer,33314,1 +50356,Female,45,Bachelors,6,14,20,6,57,2.0,6,66,Urban,HR Executive,132362,0 +50357,Male,49,Diploma,17,18,39,90,26,6.0,1,60,Urban,HR Executive,83202,0 +50358,Male,25,Bachelors,15,58,69,25,81,1.0,3,67,Urban,HR Executive,78132,0 +50359,Male,50,Bachelors,19,5,25,26,69,8.0,2,60,Urban,HR Executive,128732,0 +50360,Male,45,High School,3,7,20,21,68,1.0,7,66,Semi-Urban,Manager,139172,0 +50361,Male,26,Bachelors,4,73,72,4,84,7.0,5,24,Urban,ML Engineer,145891,0 +50362,Male,33,Diploma,19,55,76,14,64,1.0,5,70,Urban,Data Analyst,39107,0 +50363,Male,42,Diploma,8,82,90,7,3,4.0,2,25,Semi-Urban,Software Engineer,79268,0 +50364,Female,56,Bachelors,8,98,38,10,10,7.0,1,12,Semi-Urban,Manager,107145,0 +50365,Male,55,Diploma,6,67,7,27,66,5.0,7,70,Urban,Manager,73132,0 +50366,Female,40,High School,8,97,28,20,70,3.0,0,31,Rural,Data Analyst,123331,0 +50367,Male,27,Bachelors,4,31,13,16,29,0.0,5,62,Semi-Urban,HR Executive,57637,0 +50368,Female,59,Diploma,0,35,22,89,35,4.0,2,26,Semi-Urban,ML Engineer,126652,0 +50369,Male,53,Masters,3,26,9,78,83,7.0,3,1,Rural,HR Executive,116044,0 +50370,Male,51,Masters,0,38,15,24,50,9.0,4,0,Urban,Data Analyst,79388,0 +50371,Male,32,Masters,11,6,10,14,83,1.0,2,18,Urban,ML Engineer,58832,0 +50372,Female,24,High School,0,10,98,74,35,8.0,6,44,Urban,HR Executive,80119,0 +50373,Female,52,Bachelors,17,28,31,29,70,6.0,1,70,Semi-Urban,ML Engineer,87813,0 +50374,Male,25,Masters,13,35,98,63,93,9.0,7,60,Urban,Data Analyst,114905,1 +50375,Female,55,Bachelors,5,58,29,62,74,3.0,5,74,Rural,Software Engineer,54520,0 +50376,Male,30,Diploma,9,34,39,13,24,8.0,2,12,Semi-Urban,Data Analyst,39297,0 +50377,Male,32,Diploma,14,52,51,75,44,4.0,7,39,Urban,ML Engineer,21127,0 +50378,Female,58,Bachelors,10,1,28,52,1,9.0,6,4,Urban,ML Engineer,89796,0 +50379,Male,24,High School,12,42,90,50,31,7.0,7,21,Urban,ML Engineer,26890,0 +50380,Male,45,Bachelors,15,59,85,3,70,9.0,1,99,Semi-Urban,Data Analyst,124796,1 +50381,Female,28,Diploma,7,16,2,52,41,0.0,5,40,Urban,Software Engineer,69238,0 +50382,Female,41,Bachelors,16,97,91,60,25,1.0,7,42,Urban,Data Analyst,120222,1 +50383,Male,53,Bachelors,1,61,71,49,94,4.0,2,69,Urban,HR Executive,47657,1 +50384,Male,56,Diploma,17,47,15,54,42,6.0,3,25,Urban,Software Engineer,26981,0 +50385,Male,28,Diploma,10,16,86,92,0,7.0,5,95,Semi-Urban,Data Analyst,27119,1 +50386,Male,40,Bachelors,8,34,44,77,58,8.0,4,95,Urban,HR Executive,80131,1 +50387,Male,47,Bachelors,16,97,32,27,75,1.0,7,56,Urban,ML Engineer,58597,0 +50388,Female,28,Bachelors,16,76,25,56,59,7.0,5,73,Rural,Software Engineer,37210,0 +50389,Male,40,Diploma,15,51,16,11,0,0.0,7,76,Urban,Software Engineer,54110,0 +50390,Male,36,Bachelors,0,46,52,69,17,3.0,5,86,Rural,Data Analyst,137210,1 +50391,Female,28,Bachelors,11,79,77,27,18,3.0,3,32,Urban,Manager,131746,0 +50392,Female,31,High School,19,25,55,12,19,2.0,4,54,Urban,HR Executive,58901,0 +50393,Male,40,Bachelors,3,58,5,83,8,0.0,3,8,Urban,Manager,48862,0 +50394,Male,37,Diploma,9,38,58,33,77,5.0,3,85,Urban,Software Engineer,34348,0 +50395,Female,42,Bachelors,7,26,26,5,77,5.0,1,73,Urban,HR Executive,26683,0 +50396,Male,45,High School,7,40,62,72,92,8.0,1,84,Urban,Data Analyst,31346,1 +50397,Male,21,Masters,5,19,66,6,27,9.0,5,33,Rural,Software Engineer,28218,0 +50398,Male,58,Diploma,2,69,42,99,94,5.0,5,86,Urban,ML Engineer,38700,1 +50399,Male,25,Diploma,17,79,56,96,41,7.0,7,55,Rural,Data Analyst,90699,1 +50400,Male,28,Diploma,11,55,80,3,19,7.0,7,64,Rural,HR Executive,62947,0 +50401,Female,54,High School,2,60,74,68,9,5.0,3,93,Semi-Urban,HR Executive,88717,1 +50402,Female,46,High School,10,27,24,21,25,9.0,5,36,Urban,Manager,88170,0 +50403,Male,24,Bachelors,18,34,13,70,38,8.0,5,6,Urban,Manager,146333,0 +50404,Female,50,High School,19,54,72,24,51,0.0,1,5,Rural,ML Engineer,74394,0 +50405,Male,53,Diploma,2,35,87,39,60,7.0,0,98,Rural,ML Engineer,55404,1 +50406,Female,29,Diploma,13,7,57,65,66,0.0,3,68,Urban,HR Executive,42428,0 +50407,Female,57,Bachelors,11,91,71,4,49,9.0,7,82,Urban,Software Engineer,68605,1 +50408,Female,23,Bachelors,10,54,51,19,72,7.0,7,86,Urban,HR Executive,126082,0 +50409,Male,53,Diploma,2,34,48,52,90,8.0,7,48,Urban,Software Engineer,72917,0 +50410,Female,37,PhD,17,50,51,83,33,9.0,1,9,Semi-Urban,ML Engineer,86227,0 +50411,Male,46,Bachelors,16,87,66,23,85,5.0,2,11,Urban,ML Engineer,58296,0 +50412,Male,56,Diploma,7,35,46,5,63,6.0,2,81,Urban,ML Engineer,42241,0 +50413,Male,24,Diploma,19,94,32,23,61,8.0,5,50,Rural,Manager,40552,0 +50414,Male,37,Masters,3,57,93,39,14,1.0,7,33,Urban,ML Engineer,35031,0 +50415,Male,46,Masters,5,10,29,10,84,9.0,2,91,Rural,Data Analyst,96665,0 +50416,Male,55,PhD,17,21,90,37,66,4.0,5,60,Semi-Urban,Data Analyst,32076,0 +50417,Male,40,Diploma,6,59,37,98,74,7.0,6,3,Rural,Software Engineer,111791,0 +50418,Female,24,Diploma,3,60,31,18,58,9.0,5,99,Urban,ML Engineer,87991,0 +50419,Male,29,Bachelors,13,58,52,59,47,0.0,5,69,Rural,Data Analyst,136323,1 +50420,Male,36,Bachelors,15,30,69,23,68,0.0,4,17,Rural,Data Analyst,128883,0 +50421,Male,32,High School,4,61,5,23,0,3.0,0,12,Urban,Data Analyst,47025,0 +50422,Male,37,Bachelors,4,41,37,14,63,7.0,2,13,Semi-Urban,Software Engineer,49991,0 +50423,Male,45,Bachelors,0,88,94,27,21,5.0,5,85,Urban,Software Engineer,58159,1 +50424,Female,34,Bachelors,4,19,96,80,23,3.0,6,39,Urban,Manager,134136,0 +50425,Female,27,High School,15,3,97,54,41,7.0,2,35,Urban,Manager,52225,0 +50426,Male,40,Diploma,3,15,39,50,47,4.0,5,60,Rural,Data Analyst,125559,0 +50427,Male,38,Masters,0,36,72,19,55,6.0,3,65,Urban,ML Engineer,50801,0 +50428,Male,47,Bachelors,7,89,84,39,8,5.0,5,77,Urban,ML Engineer,64123,1 +50429,Male,55,High School,17,46,94,24,82,8.0,0,22,Urban,Manager,88612,0 +50430,Other,35,High School,15,44,16,92,19,7.0,7,12,Semi-Urban,Software Engineer,128946,0 +50431,Male,58,Bachelors,15,56,23,91,88,1.0,0,72,Rural,Data Analyst,122825,1 +50432,Female,23,Bachelors,5,57,43,50,91,0.0,6,66,Urban,Software Engineer,110710,0 +50433,Other,49,Masters,18,84,79,76,2,7.0,6,90,Urban,Software Engineer,122840,1 +50434,Male,36,Bachelors,15,10,26,3,40,6.0,7,99,Urban,Software Engineer,119005,0 +50435,Male,30,Masters,18,20,27,39,93,2.0,2,58,Urban,Software Engineer,45175,0 +50436,Male,26,Diploma,0,32,72,28,97,8.0,3,69,Semi-Urban,Software Engineer,134183,0 +50437,Male,54,Bachelors,4,29,15,57,10,1.0,3,26,Urban,ML Engineer,58047,0 +50438,Male,34,High School,10,32,39,25,63,1.0,0,47,Urban,HR Executive,149477,0 +50439,Other,39,Bachelors,8,69,39,7,13,6.0,1,31,Rural,Data Analyst,92670,0 +50440,Other,39,Masters,6,53,39,44,14,6.0,4,10,Semi-Urban,HR Executive,85951,0 +50441,Female,22,High School,7,39,55,86,74,9.0,3,64,Urban,Software Engineer,86195,1 +50442,Female,43,Bachelors,16,16,91,84,1,7.0,1,46,Rural,Manager,24686,0 +50443,Male,39,Masters,15,83,77,77,83,0.0,4,72,Urban,ML Engineer,66695,1 +50444,Male,41,Bachelors,13,86,8,53,46,6.0,3,73,Urban,Manager,83257,0 +50445,Male,41,Masters,17,15,94,72,64,2.0,6,35,Semi-Urban,HR Executive,85107,0 +50446,Male,27,Masters,7,8,78,22,62,2.0,3,23,Urban,Data Analyst,93148,0 +50447,Male,28,High School,2,88,8,77,22,8.0,3,77,Urban,Data Analyst,44516,1 +50448,Female,35,Masters,11,69,23,37,92,8.0,2,19,Rural,HR Executive,132915,0 +50449,Male,57,Bachelors,18,65,16,60,67,5.0,4,49,Urban,Data Analyst,59414,0 +50450,Male,28,PhD,16,4,44,80,27,6.0,7,61,Semi-Urban,Manager,69193,0 +50451,Female,22,Bachelors,8,94,90,34,80,8.0,3,79,Urban,ML Engineer,64723,1 +50452,Female,58,Diploma,10,55,95,92,58,6.0,0,15,Rural,ML Engineer,60760,1 +50453,Male,25,Bachelors,0,42,81,58,2,5.0,5,5,Rural,Software Engineer,124200,0 +50454,Male,33,Bachelors,5,60,25,2,79,2.0,3,81,Urban,Manager,85103,0 +50455,Female,36,Diploma,2,69,63,40,24,0.0,7,24,Rural,Manager,135375,0 +50456,Male,26,High School,1,23,76,73,83,0.0,5,24,Urban,ML Engineer,96340,0 +50457,Female,41,Masters,7,5,86,79,39,7.0,7,17,Urban,ML Engineer,41072,0 +50458,Male,34,Masters,13,73,28,6,25,8.0,4,18,Urban,ML Engineer,104687,0 +50459,Female,56,Bachelors,7,52,20,74,9,2.0,0,34,Urban,ML Engineer,88849,0 +50460,Female,51,Bachelors,2,46,47,82,49,9.0,6,83,Urban,Data Analyst,27061,1 +50461,Female,52,High School,7,50,8,11,55,4.0,4,67,Urban,Manager,103448,0 +50462,Male,28,Bachelors,13,99,6,88,87,6.0,7,21,Urban,Manager,98319,0 +50463,Male,47,PhD,11,88,42,44,78,1.0,0,67,Semi-Urban,Software Engineer,95159,1 +50464,Female,38,Masters,10,90,7,22,46,9.0,6,16,Semi-Urban,Data Analyst,71800,0 +50465,Male,41,Masters,14,73,87,89,8,7.0,2,50,Rural,Data Analyst,122602,1 +50466,Female,36,Bachelors,17,53,81,3,87,0.0,1,83,Urban,HR Executive,48564,0 +50467,Female,31,Masters,5,43,75,42,43,6.0,3,26,Rural,HR Executive,127541,0 +50468,Male,23,Masters,19,68,55,92,49,7.0,1,83,Semi-Urban,Data Analyst,99154,1 +50469,Other,50,Bachelors,13,95,68,41,36,6.0,5,77,Semi-Urban,Manager,40867,1 +50470,Male,48,Bachelors,6,41,53,69,55,8.0,0,6,Rural,ML Engineer,145707,0 +50471,Female,21,Bachelors,13,21,67,64,81,6.0,6,95,Urban,ML Engineer,26744,1 +50472,Female,42,High School,17,85,17,45,81,0.0,4,35,Semi-Urban,Manager,84721,0 +50473,Male,45,Bachelors,15,92,81,2,68,9.0,3,92,Urban,Data Analyst,68130,1 +50474,Male,49,Masters,7,93,71,16,37,8.0,0,80,Semi-Urban,Software Engineer,61249,1 +50475,Female,55,Bachelors,5,31,62,48,1,3.0,1,94,Urban,HR Executive,69121,0 +50476,Male,41,Masters,13,19,88,39,54,1.0,6,32,Urban,Data Analyst,62336,0 +50477,Male,30,High School,16,15,86,73,63,0.0,5,72,Urban,HR Executive,106807,1 +50478,Female,39,Diploma,10,3,0,64,59,5.0,1,95,Urban,Manager,35588,0 +50479,Male,55,Bachelors,14,53,26,13,20,5.0,0,92,Semi-Urban,HR Executive,136014,0 +50480,Male,52,Diploma,1,81,46,82,35,9.0,6,28,Semi-Urban,Software Engineer,55443,1 +50481,Male,41,Bachelors,0,37,37,24,53,2.0,4,53,Urban,Manager,99201,0 +50482,Male,27,High School,7,63,87,59,90,1.0,6,31,Urban,Manager,147907,1 +50483,Female,24,Bachelors,9,76,22,98,39,4.0,2,99,Semi-Urban,Manager,94892,1 +50484,Female,21,Bachelors,9,10,41,85,14,0.0,3,75,Urban,Manager,34262,0 +50485,Other,23,Diploma,10,26,57,13,97,7.0,3,59,Semi-Urban,Data Analyst,50410,0 +50486,Male,21,Bachelors,9,77,66,71,65,1.0,5,20,Rural,Manager,79950,0 +50487,Female,25,Masters,15,12,23,3,75,8.0,4,32,Urban,Manager,63656,0 +50488,Male,42,High School,14,79,91,71,70,5.0,5,27,Rural,Data Analyst,82196,1 +50489,Male,38,Masters,16,45,16,94,36,1.0,1,63,Urban,ML Engineer,28287,0 +50490,Female,54,High School,19,87,20,63,92,5.0,3,56,Semi-Urban,ML Engineer,124514,0 +50491,Male,46,Bachelors,7,12,48,93,23,6.0,6,53,Semi-Urban,ML Engineer,134987,0 +50492,Male,23,Bachelors,16,70,21,43,4,6.0,7,84,Urban,Data Analyst,65132,0 +50493,Male,59,Masters,17,82,61,81,35,1.0,0,86,Semi-Urban,Manager,96426,1 +50494,Female,49,Masters,16,46,3,40,62,3.0,5,74,Urban,ML Engineer,52777,0 +50495,Female,42,Bachelors,19,14,93,96,96,4.0,3,1,Rural,Manager,74730,0 +50496,Male,55,Bachelors,19,85,26,99,61,1.0,3,45,Rural,ML Engineer,29579,1 +50497,Male,30,PhD,6,82,87,36,36,4.0,6,13,Rural,Data Analyst,53759,0 +50498,Male,41,Bachelors,12,62,14,70,12,0.0,5,4,Semi-Urban,Software Engineer,37956,0 +50499,Male,21,Bachelors,5,69,72,18,32,1.0,0,7,Semi-Urban,Software Engineer,105547,0 +50500,Female,33,Bachelors,9,98,44,44,39,9.0,3,78,Rural,Manager,91149,1 +50501,Female,50,Bachelors,16,78,9,65,51,8.0,3,34,Rural,ML Engineer,29561,0 +50502,Other,25,Bachelors,2,89,33,67,56,2.0,7,23,Urban,HR Executive,88177,0 +50503,Female,32,Masters,7,35,52,83,74,6.0,3,69,Semi-Urban,Manager,72996,0 +50504,Female,23,High School,13,17,39,86,14,6.0,6,72,Rural,Software Engineer,65853,0 +50505,Female,39,Bachelors,16,5,85,29,99,0.0,5,84,Urban,Data Analyst,33405,0 +50506,Other,25,Diploma,18,85,14,90,34,7.0,5,15,Urban,Software Engineer,107749,0 +50507,Female,42,Bachelors,0,79,64,15,95,2.0,3,82,Urban,Software Engineer,107924,0 +50508,Male,39,Bachelors,19,27,7,10,20,0.0,3,75,Urban,Software Engineer,61320,0 +50509,Male,59,PhD,8,91,32,44,35,6.0,3,54,Urban,Manager,79645,0 +50510,Male,25,High School,11,34,20,99,49,7.0,5,10,Semi-Urban,ML Engineer,34472,0 +50511,Female,32,Masters,11,84,19,96,2,4.0,2,98,Rural,HR Executive,59908,1 +50512,Male,47,Bachelors,6,68,26,0,61,2.0,2,36,Urban,ML Engineer,96840,0 +50513,Female,53,Diploma,11,92,37,14,64,8.0,6,73,Semi-Urban,ML Engineer,67664,0 +50514,Female,59,Bachelors,16,63,10,6,96,0.0,3,82,Urban,ML Engineer,49703,0 +50515,Male,29,Bachelors,19,5,23,7,11,9.0,4,86,Urban,HR Executive,91859,0 +50516,Male,39,Diploma,11,13,37,87,74,9.0,7,95,Rural,HR Executive,88961,0 +50517,Female,40,Bachelors,9,20,13,4,11,3.0,1,64,Urban,Software Engineer,35782,0 +50518,Male,29,Diploma,12,97,84,74,28,2.0,5,19,Semi-Urban,Data Analyst,60723,1 +50519,Male,50,Bachelors,15,28,75,39,73,9.0,6,3,Urban,Manager,134884,0 +50520,Female,39,Masters,11,42,72,70,72,2.0,1,34,Urban,HR Executive,38550,0 +50521,Male,56,PhD,1,76,32,19,49,8.0,6,8,Rural,Manager,97558,0 +50522,Male,50,Masters,8,89,34,38,57,3.0,1,1,Urban,HR Executive,35443,0 +50523,Male,45,Masters,12,94,56,18,90,2.0,4,75,Semi-Urban,Manager,70303,1 +50524,Female,48,Bachelors,7,65,45,51,92,5.0,6,45,Urban,Manager,58715,0 +50525,Female,37,High School,9,18,71,47,34,7.0,3,94,Semi-Urban,Manager,119662,0 +50526,Male,35,Masters,11,1,86,11,77,2.0,6,35,Rural,Software Engineer,25668,0 +50527,Female,30,High School,18,1,61,48,38,2.0,1,45,Rural,Software Engineer,97500,0 +50528,Female,33,Masters,16,63,9,48,32,0.0,0,30,Urban,Data Analyst,54078,0 +50529,Female,35,Bachelors,2,28,28,29,23,2.0,4,27,Rural,Software Engineer,117719,0 +50530,Female,49,Bachelors,2,67,33,60,50,1.0,6,36,Urban,Manager,149499,0 +50531,Female,45,Bachelors,2,70,15,84,89,8.0,6,83,Urban,Data Analyst,140023,1 +50532,Female,31,Bachelors,14,91,50,51,85,0.0,6,33,Rural,Data Analyst,136798,0 +50533,Male,38,PhD,6,68,63,55,15,9.0,0,47,Urban,HR Executive,137017,0 +50534,Male,50,Bachelors,17,84,53,47,74,7.0,3,12,Rural,ML Engineer,60244,0 +50535,Male,35,Bachelors,4,61,3,54,14,3.0,2,1,Semi-Urban,Manager,34909,0 +50536,Female,46,Diploma,1,50,68,35,50,9.0,7,91,Semi-Urban,Manager,67248,1 +50537,Male,57,Bachelors,5,41,50,41,7,3.0,5,45,Semi-Urban,Data Analyst,127744,0 +50538,Male,21,Bachelors,1,58,52,13,34,6.0,1,57,Urban,Manager,116060,0 +50539,Male,57,Masters,10,19,50,26,8,6.0,7,25,Semi-Urban,Software Engineer,40774,0 +50540,Male,23,Bachelors,2,81,2,1,91,4.0,5,42,Semi-Urban,Manager,142884,0 +50541,Male,37,Masters,12,75,35,91,39,1.0,6,56,Urban,ML Engineer,100815,1 +50542,Female,39,Masters,0,27,27,2,81,2.0,0,70,Urban,Manager,50644,0 +50543,Other,46,Masters,3,33,68,93,14,2.0,7,94,Rural,ML Engineer,78112,1 +50544,Female,42,High School,11,64,84,28,51,7.0,1,59,Urban,Software Engineer,145202,0 +50545,Female,57,Diploma,16,65,68,57,36,4.0,4,0,Rural,Software Engineer,138443,0 +50546,Other,43,High School,4,46,87,78,39,6.0,5,4,Urban,ML Engineer,127134,0 +50547,Male,47,Diploma,17,96,90,83,92,4.0,6,9,Rural,HR Executive,131253,1 +50548,Male,40,Bachelors,18,87,77,94,13,4.0,1,95,Urban,ML Engineer,75841,1 +50549,Male,56,Bachelors,3,11,98,27,20,7.0,0,29,Semi-Urban,Manager,130179,0 +50550,Female,21,Masters,12,61,70,57,29,8.0,7,96,Rural,Manager,59316,1 +50551,Male,48,Bachelors,1,30,76,58,71,9.0,7,42,Urban,Manager,135876,0 +50552,Female,30,Bachelors,13,42,78,25,32,5.0,2,23,Rural,Software Engineer,108131,0 +50553,Female,44,PhD,18,68,44,64,33,7.0,2,43,Semi-Urban,Data Analyst,55910,0 +50554,Male,29,Bachelors,19,92,76,25,11,8.0,4,39,Urban,Manager,83861,0 +50555,Male,43,Bachelors,5,30,26,53,45,9.0,2,20,Urban,HR Executive,61349,0 +50556,Female,40,Diploma,12,6,47,74,98,5.0,2,15,Urban,ML Engineer,27665,0 +50557,Female,33,Bachelors,9,62,13,63,47,9.0,0,14,Semi-Urban,ML Engineer,127825,0 +50558,Male,52,Bachelors,6,18,94,30,10,2.0,4,55,Semi-Urban,HR Executive,93278,0 +50559,Female,47,Masters,3,33,3,23,2,4.0,3,37,Rural,HR Executive,134571,0 +50560,Female,30,Diploma,16,91,68,89,42,5.0,7,49,Rural,Data Analyst,59459,1 +50561,Other,58,Bachelors,11,82,67,60,4,7.0,4,35,Urban,Manager,50396,1 +50562,Male,59,Bachelors,18,88,15,74,22,7.0,1,31,Rural,Software Engineer,112456,0 +50563,Male,41,Masters,17,31,97,86,80,9.0,0,26,Urban,ML Engineer,80021,1 +50564,Male,46,Diploma,0,12,24,78,55,0.0,1,89,Rural,Manager,89965,0 +50565,Female,29,Diploma,16,62,67,19,56,9.0,5,90,Urban,HR Executive,141380,0 +50566,Female,51,Bachelors,13,68,65,70,92,0.0,5,76,Semi-Urban,Manager,87969,1 +50567,Female,50,High School,11,78,77,40,10,7.0,5,73,Urban,Software Engineer,100118,1 +50568,Female,24,High School,5,96,99,94,46,7.0,1,2,Urban,Software Engineer,88962,1 +50569,Female,39,High School,11,21,88,83,85,8.0,1,99,Semi-Urban,Software Engineer,27449,1 +50570,Female,39,Bachelors,16,29,11,12,84,8.0,4,89,Semi-Urban,ML Engineer,35599,0 +50571,Male,45,Bachelors,5,70,16,74,17,4.0,1,46,Urban,Manager,93692,0 +50572,Male,53,Diploma,7,94,55,71,26,5.0,2,39,Semi-Urban,Data Analyst,38933,1 +50573,Female,44,Bachelors,0,7,97,86,88,3.0,0,35,Urban,HR Executive,79814,0 +50574,Female,33,Diploma,5,38,16,72,64,3.0,4,52,Semi-Urban,Manager,126039,0 +50575,Male,27,Masters,12,38,28,60,35,1.0,0,56,Rural,Manager,85919,0 +50576,Male,21,Diploma,7,45,18,37,12,8.0,6,73,Urban,Data Analyst,118395,0 +50577,Male,46,Bachelors,2,13,1,40,3,0.0,0,15,Urban,Software Engineer,37068,0 +50578,Male,46,Bachelors,4,44,24,96,39,7.0,1,29,Semi-Urban,Software Engineer,141847,0 +50579,Female,29,Diploma,13,6,93,15,34,2.0,7,68,Urban,HR Executive,100114,0 +50580,Male,59,High School,1,85,80,74,3,2.0,5,33,Semi-Urban,Data Analyst,95321,1 +50581,Male,23,Bachelors,11,59,26,21,39,6.0,3,41,Urban,Data Analyst,118572,0 +50582,Female,32,Bachelors,15,0,47,60,76,6.0,0,50,Urban,Manager,50841,0 +50583,Male,53,Masters,0,27,87,8,69,4.0,0,79,Urban,Software Engineer,104569,0 +50584,Male,52,Bachelors,17,8,50,80,61,9.0,2,24,Urban,ML Engineer,146145,0 +50585,Male,36,Bachelors,5,63,7,9,17,0.0,4,25,Rural,Manager,85413,0 +50586,Male,29,High School,11,59,48,4,30,2.0,2,56,Urban,HR Executive,101928,0 +50587,Male,38,Bachelors,3,11,15,27,80,7.0,6,29,Rural,ML Engineer,54681,0 +50588,Female,33,Bachelors,9,41,42,28,34,5.0,3,23,Semi-Urban,HR Executive,49562,0 +50589,Male,24,Bachelors,4,70,96,35,1,1.0,3,82,Urban,Software Engineer,50761,1 +50590,Female,23,Diploma,16,49,23,4,30,8.0,5,14,Semi-Urban,HR Executive,144536,0 +50591,Male,50,Bachelors,14,5,57,94,53,3.0,7,49,Semi-Urban,Manager,95544,0 +50592,Female,46,Bachelors,13,86,17,90,99,9.0,1,30,Semi-Urban,ML Engineer,84865,0 +50593,Female,28,High School,11,77,55,72,66,1.0,6,28,Rural,Manager,34061,0 +50594,Male,37,Diploma,15,52,86,22,1,6.0,6,59,Urban,Software Engineer,25073,0 +50595,Female,30,High School,13,15,1,96,44,4.0,2,54,Semi-Urban,HR Executive,92688,0 +50596,Male,28,Diploma,15,34,23,92,33,6.0,2,70,Urban,ML Engineer,128096,0 +50597,Male,40,Bachelors,6,63,47,30,87,6.0,7,55,Urban,Software Engineer,124990,0 +50598,Female,44,High School,8,93,83,31,59,0.0,3,27,Semi-Urban,ML Engineer,35347,0 +50599,Female,21,High School,10,78,15,54,94,6.0,6,5,Semi-Urban,HR Executive,132601,0 +50600,Female,56,PhD,16,10,59,55,73,2.0,6,15,Urban,Software Engineer,117922,0 +50601,Female,24,High School,17,72,19,43,20,4.0,7,87,Urban,ML Engineer,23939,0 +50602,Female,35,Diploma,19,50,92,71,77,9.0,7,85,Semi-Urban,Software Engineer,133917,1 +50603,Female,38,Diploma,12,28,19,67,95,3.0,3,60,Semi-Urban,Software Engineer,131112,0 +50604,Male,24,Masters,14,82,81,95,38,1.0,4,88,Semi-Urban,Software Engineer,104398,1 +50605,Male,29,Bachelors,18,65,81,58,91,2.0,7,33,Urban,ML Engineer,107887,1 +50606,Male,21,Diploma,8,75,22,16,65,6.0,5,21,Urban,HR Executive,85409,0 +50607,Male,45,Bachelors,19,43,7,32,8,2.0,3,24,Semi-Urban,Data Analyst,40378,0 +50608,Male,51,Bachelors,1,24,40,96,85,9.0,1,47,Rural,ML Engineer,120650,0 +50609,Female,46,Bachelors,2,77,92,16,66,2.0,1,77,Urban,Software Engineer,135122,1 +50610,Male,33,Masters,19,73,64,38,48,5.0,4,13,Urban,ML Engineer,146311,0 +50611,Female,25,Masters,17,68,47,40,72,6.0,4,87,Rural,Software Engineer,75704,1 +50612,Male,40,Bachelors,10,15,50,53,95,4.0,5,72,Rural,ML Engineer,64923,0 +50613,Female,25,Bachelors,7,72,97,67,98,3.0,5,23,Rural,Data Analyst,93886,1 +50614,Female,50,Masters,9,84,20,28,61,2.0,1,75,Urban,Software Engineer,88542,0 +50615,Male,29,Diploma,14,21,11,23,2,6.0,0,25,Rural,ML Engineer,78439,0 +50616,Female,30,PhD,3,0,95,38,8,5.0,0,21,Rural,Software Engineer,45991,0 +50617,Male,25,Bachelors,12,74,34,33,10,2.0,3,82,Urban,ML Engineer,143057,0 +50618,Female,44,High School,19,89,66,95,96,4.0,5,67,Urban,Manager,21741,1 +50619,Male,40,High School,0,23,63,90,4,8.0,0,1,Urban,HR Executive,73621,0 +50620,Male,41,Diploma,3,58,18,14,94,3.0,7,27,Urban,ML Engineer,122139,0 +50621,Other,33,Bachelors,12,27,23,58,86,8.0,0,80,Semi-Urban,HR Executive,74938,0 +50622,Female,43,Masters,11,11,33,35,80,7.0,2,79,Rural,Software Engineer,137141,0 +50623,Male,44,Masters,9,22,42,75,73,4.0,3,66,Urban,Data Analyst,69420,0 +50624,Female,37,Diploma,2,69,30,61,96,4.0,3,1,Rural,HR Executive,104511,0 +50625,Male,53,High School,7,92,99,92,76,6.0,1,27,Semi-Urban,Software Engineer,46134,1 +50626,Male,57,Diploma,17,57,82,5,67,6.0,0,11,Urban,Data Analyst,58716,0 +50627,Male,57,PhD,15,63,89,50,95,8.0,4,26,Rural,Manager,65600,0 +50628,Male,34,High School,3,24,95,51,39,3.0,1,40,Urban,HR Executive,144132,0 +50629,Female,28,Bachelors,19,19,65,75,32,8.0,7,75,Urban,ML Engineer,147350,0 +50630,Female,37,Diploma,9,44,43,10,91,0.0,0,17,Urban,Manager,88985,0 +50631,Male,41,Bachelors,4,10,89,74,89,1.0,7,61,Urban,Data Analyst,51512,0 +50632,Female,53,Bachelors,3,37,28,14,46,6.0,0,93,Semi-Urban,Manager,130853,0 +50633,Male,56,Masters,5,43,19,17,48,2.0,1,76,Semi-Urban,Software Engineer,102497,0 +50634,Male,50,High School,0,3,9,54,14,7.0,2,97,Urban,Data Analyst,62533,0 +50635,Female,58,Masters,10,28,52,25,90,9.0,2,7,Semi-Urban,Software Engineer,146922,0 +50636,Male,40,Bachelors,0,82,20,12,79,2.0,2,88,Urban,Data Analyst,76726,0 +50637,Male,42,Diploma,5,27,39,73,67,7.0,3,91,Urban,HR Executive,124041,0 +50638,Female,26,Masters,3,74,90,34,92,4.0,2,90,Urban,Software Engineer,38166,1 +50639,Other,31,High School,7,57,76,41,49,9.0,4,46,Urban,HR Executive,68802,0 +50640,Male,58,Bachelors,3,88,21,45,75,7.0,3,43,Semi-Urban,ML Engineer,65740,0 +50641,Male,32,Diploma,4,39,11,37,88,6.0,4,40,Urban,HR Executive,27931,0 +50642,Male,27,Bachelors,8,37,60,41,48,3.0,4,35,Semi-Urban,HR Executive,58275,0 +50643,Female,46,Diploma,13,28,98,66,8,1.0,6,75,Semi-Urban,HR Executive,49824,1 +50644,Female,59,Masters,4,44,62,21,68,8.0,1,8,Urban,HR Executive,57195,0 +50645,Female,28,Bachelors,9,20,41,55,86,0.0,3,48,Semi-Urban,Manager,22969,0 +50646,Female,40,High School,7,86,34,19,79,5.0,0,91,Rural,Data Analyst,90614,0 +50647,Female,37,Bachelors,18,96,81,2,43,2.0,5,72,Semi-Urban,Software Engineer,75995,1 +50648,Female,38,Diploma,17,41,59,68,86,8.0,5,17,Urban,HR Executive,55135,0 +50649,Male,45,Bachelors,4,94,22,86,47,0.0,0,26,Urban,ML Engineer,142660,0 +50650,Female,43,Masters,10,19,78,43,37,6.0,6,27,Urban,ML Engineer,129907,0 +50651,Female,52,Masters,19,47,77,58,36,1.0,0,42,Rural,ML Engineer,44830,0 +50652,Male,33,Bachelors,14,37,25,95,56,6.0,0,28,Rural,HR Executive,108654,0 +50653,Male,23,Masters,13,14,7,34,60,2.0,0,18,Urban,Data Analyst,77753,0 +50654,Male,54,Bachelors,8,66,26,67,16,9.0,1,30,Semi-Urban,HR Executive,31897,0 +50655,Female,23,Diploma,16,22,72,37,95,4.0,2,92,Urban,Data Analyst,128810,0 +50656,Male,47,Bachelors,6,80,61,41,69,0.0,4,94,Urban,HR Executive,59122,1 +50657,Female,21,Diploma,2,49,29,82,5,7.0,0,87,Urban,HR Executive,138051,1 +50658,Male,50,Diploma,13,52,81,36,1,0.0,6,65,Urban,Manager,74782,0 +50659,Female,36,Bachelors,7,63,15,21,55,1.0,4,92,Semi-Urban,Manager,36453,0 +50660,Male,50,Diploma,0,66,86,85,27,1.0,6,31,Semi-Urban,Software Engineer,24085,1 +50661,Female,27,PhD,4,29,72,34,55,0.0,3,58,Urban,ML Engineer,95150,0 +50662,Male,56,High School,8,12,61,30,43,8.0,0,69,Urban,ML Engineer,146652,0 +50663,Male,58,Diploma,0,51,80,73,99,8.0,6,97,Urban,Manager,33872,1 +50664,Male,58,Bachelors,16,55,76,19,65,0.0,0,43,Urban,HR Executive,53344,0 +50665,Male,30,High School,2,86,11,81,32,5.0,1,78,Semi-Urban,Manager,132855,1 +50666,Female,36,Bachelors,16,9,11,59,43,4.0,7,93,Semi-Urban,HR Executive,142258,0 +50667,Female,59,Bachelors,17,79,55,68,58,1.0,3,77,Urban,Data Analyst,40038,1 +50668,Male,43,Masters,10,37,38,53,51,6.0,5,24,Rural,Manager,127491,0 +50669,Male,27,Bachelors,10,30,26,99,6,7.0,4,62,Semi-Urban,Software Engineer,104917,0 +50670,Female,35,Bachelors,6,18,43,53,46,5.0,7,28,Urban,Data Analyst,137653,0 +50671,Female,33,Diploma,18,68,58,83,66,3.0,7,11,Urban,ML Engineer,129193,0 +50672,Male,27,Bachelors,18,19,96,65,3,8.0,5,70,Urban,Software Engineer,81101,1 +50673,Male,58,Masters,9,17,83,10,26,3.0,5,94,Rural,Software Engineer,47514,0 +50674,Male,49,High School,9,79,33,72,37,7.0,6,81,Urban,Manager,30521,1 +50675,Male,21,High School,19,2,12,39,6,8.0,4,31,Semi-Urban,ML Engineer,107775,0 +50676,Female,40,Diploma,11,33,92,74,38,3.0,2,36,Semi-Urban,ML Engineer,90318,0 +50677,Female,22,Diploma,11,99,64,99,13,0.0,3,42,Semi-Urban,Software Engineer,30784,1 +50678,Male,30,High School,3,79,72,70,34,7.0,6,56,Urban,Data Analyst,59253,1 +50679,Male,47,Masters,7,81,54,44,50,3.0,5,0,Urban,ML Engineer,73275,0 +50680,Female,55,Bachelors,9,27,90,70,5,0.0,2,30,Rural,Manager,44385,0 +50681,Male,51,Diploma,14,79,75,99,44,4.0,6,81,Urban,Data Analyst,147208,1 +50682,Male,46,PhD,7,11,77,30,37,6.0,5,91,Urban,ML Engineer,24208,0 +50683,Female,27,Diploma,15,18,29,44,79,4.0,2,58,Semi-Urban,HR Executive,108727,0 +50684,Male,37,High School,19,8,56,69,45,1.0,0,43,Rural,ML Engineer,104480,0 +50685,Female,44,Bachelors,19,27,69,45,45,1.0,4,18,Semi-Urban,Software Engineer,99443,0 +50686,Female,45,Bachelors,9,99,53,96,12,1.0,2,23,Urban,Manager,93631,1 +50687,Other,31,Masters,7,38,84,15,20,5.0,1,62,Rural,HR Executive,149851,0 +50688,Male,37,Bachelors,6,54,25,25,38,7.0,6,65,Urban,HR Executive,145287,0 +50689,Female,45,Masters,19,6,81,76,54,5.0,6,38,Urban,ML Engineer,131699,0 +50690,Female,50,High School,12,70,45,33,32,8.0,1,91,Rural,Software Engineer,25010,0 +50691,Male,56,High School,15,35,96,44,39,0.0,4,13,Urban,Software Engineer,144293,0 +50692,Male,29,Bachelors,19,2,15,27,52,8.0,0,22,Rural,ML Engineer,91634,0 +50693,Male,43,Bachelors,7,75,17,78,38,1.0,3,50,Urban,HR Executive,20516,0 +50694,Female,56,Diploma,16,45,47,2,18,7.0,2,32,Urban,ML Engineer,32087,0 +50695,Male,22,Bachelors,19,43,91,30,21,7.0,4,55,Urban,Data Analyst,112092,0 +50696,Male,37,Bachelors,15,5,88,13,36,8.0,1,91,Rural,HR Executive,101761,0 +50697,Female,27,Bachelors,10,45,2,36,2,5.0,3,82,Rural,HR Executive,76332,0 +50698,Male,28,High School,7,84,46,15,30,7.0,4,85,Semi-Urban,Software Engineer,48094,0 +50699,Male,29,High School,14,23,31,43,98,7.0,3,86,Urban,ML Engineer,49456,0 +50700,Male,32,High School,11,97,16,11,84,9.0,2,27,Urban,ML Engineer,141506,0 +50701,Female,21,Diploma,12,26,46,61,87,2.0,3,21,Urban,ML Engineer,90097,0 +50702,Female,23,Bachelors,17,77,8,57,58,4.0,5,79,Urban,Data Analyst,81936,0 +50703,Female,36,Bachelors,1,63,98,32,80,5.0,1,76,Urban,Software Engineer,38392,1 +50704,Male,48,High School,16,52,23,36,71,3.0,2,8,Urban,Data Analyst,84700,0 +50705,Female,55,Diploma,3,4,58,21,48,9.0,0,16,Urban,Data Analyst,47928,0 +50706,Male,29,Diploma,9,25,43,32,23,1.0,4,0,Urban,HR Executive,101818,0 +50707,Male,38,Bachelors,10,43,45,43,56,2.0,2,68,Semi-Urban,Software Engineer,51231,0 +50708,Female,44,High School,10,51,60,63,95,2.0,1,23,Urban,Data Analyst,148561,0 +50709,Female,38,Masters,1,12,51,88,39,5.0,4,16,Semi-Urban,Data Analyst,50042,0 +50710,Female,27,Bachelors,1,6,20,88,57,1.0,3,57,Urban,Software Engineer,52419,0 +50711,Male,24,High School,11,18,34,87,3,5.0,7,51,Semi-Urban,HR Executive,66731,0 +50712,Male,45,High School,6,69,30,80,5,3.0,6,40,Urban,HR Executive,81518,0 +50713,Male,44,Diploma,19,90,61,60,73,6.0,4,74,Urban,Software Engineer,27992,1 +50714,Male,52,Masters,2,90,45,54,69,7.0,4,44,Rural,ML Engineer,65919,0 +50715,Male,44,High School,3,83,28,83,92,7.0,6,74,Urban,Manager,72716,1 +50716,Female,49,PhD,1,15,92,15,94,2.0,7,51,Urban,ML Engineer,127597,0 +50717,Male,36,Diploma,17,10,44,1,83,4.0,2,80,Urban,ML Engineer,32208,0 +50718,Male,29,Diploma,13,91,21,44,54,7.0,0,33,Rural,HR Executive,87118,0 +50719,Male,25,High School,14,2,24,17,85,0.0,0,76,Rural,Manager,128089,0 +50720,Male,32,Diploma,8,56,26,80,68,1.0,1,72,Semi-Urban,ML Engineer,100991,0 +50721,Female,58,Diploma,4,25,65,31,54,5.0,2,15,Urban,HR Executive,20635,0 +50722,Female,42,High School,6,47,73,63,79,9.0,7,85,Rural,Manager,80747,1 +50723,Other,26,Bachelors,7,88,83,20,95,0.0,3,86,Urban,Data Analyst,91669,1 +50724,Female,34,High School,13,51,9,71,55,1.0,0,81,Semi-Urban,Software Engineer,103452,0 +50725,Male,31,Bachelors,3,45,9,99,65,0.0,1,84,Urban,Manager,138887,1 +50726,Female,44,Bachelors,11,40,88,54,81,7.0,0,33,Urban,Manager,23023,0 +50727,Male,37,Diploma,15,60,8,42,71,1.0,4,85,Rural,HR Executive,57561,0 +50728,Male,55,Masters,0,35,57,25,15,9.0,3,56,Semi-Urban,Software Engineer,134637,0 +50729,Male,23,Masters,15,86,8,14,9,6.0,4,2,Semi-Urban,Data Analyst,87509,0 +50730,Male,53,Masters,19,25,66,32,79,0.0,2,99,Urban,ML Engineer,87296,0 +50731,Male,57,Bachelors,12,25,1,45,75,7.0,0,62,Urban,Software Engineer,95119,0 +50732,Female,58,Bachelors,7,76,85,11,56,5.0,3,21,Urban,ML Engineer,82772,0 +50733,Male,49,Masters,4,38,70,73,52,6.0,0,48,Urban,Software Engineer,21403,0 +50734,Female,49,PhD,7,33,2,79,68,6.0,5,25,Urban,HR Executive,124504,0 +50735,Female,52,Masters,1,24,12,93,16,4.0,2,53,Semi-Urban,ML Engineer,32661,0 +50736,Other,54,Bachelors,5,87,28,67,42,4.0,7,11,Semi-Urban,Software Engineer,134692,0 +50737,Female,24,High School,6,54,80,25,61,5.0,2,65,Semi-Urban,ML Engineer,117219,0 +50738,Female,21,Bachelors,0,93,48,69,33,4.0,3,35,Semi-Urban,HR Executive,41737,1 +50739,Male,46,Masters,4,53,22,92,68,3.0,0,58,Rural,HR Executive,57136,0 +50740,Male,58,Diploma,0,72,94,38,19,3.0,0,85,Semi-Urban,HR Executive,113377,1 +50741,Female,59,Bachelors,14,4,61,1,20,8.0,0,67,Urban,HR Executive,139158,0 +50742,Female,33,Masters,19,71,75,53,51,6.0,6,77,Rural,Data Analyst,105074,1 +50743,Other,57,Bachelors,3,44,64,41,93,6.0,3,96,Semi-Urban,HR Executive,118169,1 +50744,Female,55,Diploma,12,9,3,51,19,5.0,1,9,Urban,Data Analyst,59067,0 +50745,Male,39,Bachelors,13,55,52,16,0,6.0,7,92,Urban,ML Engineer,138506,0 +50746,Other,43,High School,6,27,68,66,66,2.0,0,77,Semi-Urban,Data Analyst,130647,0 +50747,Other,33,Masters,15,98,48,60,77,5.0,4,49,Urban,HR Executive,72806,1 +50748,Male,30,Bachelors,9,31,38,19,88,0.0,4,53,Urban,Software Engineer,53346,0 +50749,Female,26,Bachelors,3,13,22,96,36,0.0,4,92,Semi-Urban,HR Executive,106446,0 +50750,Female,53,High School,9,88,82,98,34,7.0,2,55,Rural,ML Engineer,50031,1 +50751,Male,28,Bachelors,13,78,46,1,70,2.0,4,97,Urban,Software Engineer,93030,0 +50752,Female,31,Masters,18,63,5,71,53,9.0,7,45,Urban,Software Engineer,124164,0 +50753,Male,22,High School,18,47,46,99,15,8.0,5,7,Rural,Manager,82917,0 +50754,Male,47,Bachelors,15,37,99,12,87,1.0,6,43,Semi-Urban,Software Engineer,41857,0 +50755,Male,43,High School,7,71,6,52,92,1.0,5,46,Urban,Data Analyst,57343,0 +50756,Female,58,Bachelors,7,60,13,40,13,7.0,3,91,Rural,Manager,107898,0 +50757,Male,38,Masters,7,9,93,9,63,0.0,5,90,Urban,HR Executive,45200,0 +50758,Male,23,Masters,17,33,27,99,87,8.0,1,14,Urban,Manager,115953,0 +50759,Female,59,PhD,11,85,93,14,41,0.0,7,17,Rural,Manager,118105,0 +50760,Male,25,Diploma,6,43,49,67,50,6.0,1,44,Urban,Data Analyst,35773,0 +50761,Male,48,Diploma,7,25,78,90,39,8.0,2,58,Rural,Data Analyst,127948,1 +50762,Female,49,Bachelors,15,20,56,95,13,7.0,4,46,Urban,HR Executive,142609,0 +50763,Male,22,Diploma,11,15,29,51,4,8.0,4,92,Urban,HR Executive,144509,0 +50764,Female,26,Bachelors,11,5,25,32,42,1.0,4,65,Semi-Urban,ML Engineer,40498,0 +50765,Male,21,PhD,18,45,31,89,46,9.0,6,56,Rural,ML Engineer,71855,0 +50766,Female,33,Bachelors,4,45,15,5,49,2.0,0,23,Rural,Software Engineer,91683,0 +50767,Male,35,High School,15,34,20,47,98,9.0,3,36,Urban,Manager,123095,0 +50768,Female,55,Diploma,11,58,13,34,22,0.0,0,40,Semi-Urban,Data Analyst,146444,0 +50769,Male,22,Bachelors,19,5,81,89,67,0.0,6,24,Semi-Urban,Data Analyst,23570,0 +50770,Male,42,Bachelors,19,92,15,85,15,3.0,4,49,Rural,ML Engineer,40467,1 +50771,Other,52,Bachelors,16,55,47,46,79,3.0,7,12,Urban,ML Engineer,23371,0 +50772,Female,34,Diploma,17,89,37,47,11,0.0,7,19,Urban,ML Engineer,127249,0 +50773,Female,31,PhD,17,72,18,13,59,6.0,5,67,Semi-Urban,HR Executive,39534,0 +50774,Male,38,Diploma,11,43,66,85,33,4.0,7,91,Semi-Urban,Software Engineer,79742,1 +50775,Male,45,Diploma,6,52,0,73,62,7.0,1,27,Rural,Manager,94542,0 +50776,Male,33,Bachelors,12,69,84,83,21,8.0,1,40,Rural,HR Executive,36983,1 +50777,Male,56,High School,10,30,24,63,7,8.0,3,47,Urban,Manager,50060,0 +50778,Male,57,Diploma,12,22,63,27,29,8.0,4,96,Urban,Software Engineer,21016,0 +50779,Other,27,Masters,12,60,21,69,60,5.0,4,52,Rural,ML Engineer,24116,0 +50780,Male,36,Bachelors,5,55,69,90,77,2.0,3,78,Urban,Data Analyst,58396,1 +50781,Male,57,Masters,4,1,29,24,36,1.0,0,80,Rural,Data Analyst,69415,0 +50782,Male,53,High School,10,7,71,38,96,7.0,5,3,Semi-Urban,Data Analyst,91352,0 +50783,Female,34,Bachelors,5,17,74,99,18,3.0,7,84,Rural,ML Engineer,112339,1 +50784,Male,53,Diploma,13,91,26,27,6,8.0,6,50,Rural,Software Engineer,74795,0 +50785,Male,53,Bachelors,19,77,7,76,97,4.0,0,24,Urban,ML Engineer,140044,0 +50786,Female,46,Diploma,8,9,56,20,47,5.0,5,95,Urban,HR Executive,43555,0 +50787,Male,32,Masters,0,28,80,24,98,0.0,6,95,Semi-Urban,Software Engineer,66984,0 +50788,Male,37,Masters,10,38,35,24,95,8.0,7,32,Urban,ML Engineer,102056,0 +50789,Male,32,Diploma,5,62,79,24,43,8.0,0,21,Semi-Urban,Software Engineer,135234,0 +50790,Male,57,Bachelors,17,99,12,44,74,3.0,3,9,Semi-Urban,HR Executive,103973,0 +50791,Male,58,High School,8,35,12,85,0,2.0,2,10,Urban,Manager,139766,0 +50792,Male,48,High School,8,72,96,35,10,6.0,6,49,Urban,Manager,127255,1 +50793,Male,51,Masters,7,83,76,36,60,8.0,6,11,Urban,ML Engineer,132380,0 +50794,Male,48,Masters,14,32,25,39,23,6.0,0,52,Urban,Data Analyst,42675,0 +50795,Male,28,Diploma,14,11,67,87,52,4.0,2,55,Urban,ML Engineer,96718,0 +50796,Male,55,Bachelors,10,35,93,5,48,6.0,5,83,Rural,HR Executive,28548,0 +50797,Male,39,High School,11,80,19,6,84,8.0,0,58,Urban,ML Engineer,56053,0 +50798,Male,50,Masters,4,53,90,40,33,6.0,3,60,Urban,Manager,26090,1 +50799,Male,51,Bachelors,6,67,52,84,49,9.0,1,2,Urban,HR Executive,122324,0 +50800,Other,27,Bachelors,3,36,16,72,29,3.0,5,80,Urban,ML Engineer,101795,0 +50801,Male,47,Diploma,0,80,30,74,83,3.0,1,41,Urban,HR Executive,125040,0 +50802,Female,36,PhD,10,41,54,42,38,4.0,1,35,Urban,Manager,23070,0 +50803,Female,35,High School,5,32,85,31,98,3.0,2,75,Urban,Data Analyst,72207,0 +50804,Female,41,Bachelors,8,17,51,60,79,8.0,1,97,Urban,Data Analyst,36927,0 +50805,Female,36,Diploma,13,70,56,31,62,5.0,2,69,Rural,ML Engineer,33604,0 +50806,Female,22,Bachelors,13,93,79,42,85,6.0,5,8,Urban,Software Engineer,131941,0 +50807,Female,44,Diploma,11,90,67,8,51,7.0,3,74,Urban,Data Analyst,55478,0 +50808,Female,52,High School,19,18,13,45,22,1.0,5,73,Urban,Software Engineer,101742,0 +50809,Male,45,Bachelors,8,84,39,88,33,7.0,6,17,Urban,Manager,116217,0 +50810,Male,37,High School,13,4,80,0,77,2.0,3,22,Urban,Data Analyst,109880,0 +50811,Male,23,PhD,11,86,46,73,43,8.0,1,12,Urban,Manager,39223,0 +50812,Female,36,Bachelors,14,95,82,55,54,5.0,6,89,Semi-Urban,Manager,105593,1 +50813,Male,28,Diploma,11,65,65,82,73,3.0,1,50,Rural,HR Executive,62376,1 +50814,Female,24,Bachelors,18,16,23,97,42,7.0,4,13,Urban,Software Engineer,115881,0 +50815,Male,47,Bachelors,13,94,92,60,20,8.0,2,17,Urban,Data Analyst,42639,1 +50816,Male,39,Bachelors,4,4,38,21,47,3.0,4,43,Urban,Software Engineer,90493,0 +50817,Male,52,Masters,10,31,45,18,55,7.0,4,95,Urban,Manager,93872,0 +50818,Female,57,High School,13,16,22,49,54,8.0,0,77,Urban,HR Executive,62727,0 +50819,Female,53,Bachelors,4,92,7,53,29,3.0,3,12,Urban,Software Engineer,63197,0 +50820,Male,32,Masters,2,47,8,80,1,4.0,2,86,Semi-Urban,Software Engineer,121705,0 +50821,Female,59,Bachelors,4,45,16,3,64,8.0,1,71,Urban,Manager,80510,0 +50822,Male,54,Bachelors,8,23,16,45,78,9.0,0,74,Semi-Urban,Software Engineer,23974,0 +50823,Male,48,Masters,4,12,7,26,93,2.0,0,72,Semi-Urban,Manager,49199,0 +50824,Male,44,Bachelors,3,99,28,24,78,3.0,0,48,Urban,Software Engineer,78709,0 +50825,Female,37,Bachelors,14,4,47,76,4,1.0,4,52,Urban,ML Engineer,90404,0 +50826,Female,49,High School,2,66,78,81,61,8.0,7,70,Rural,Data Analyst,127621,1 +50827,Male,29,High School,10,63,20,65,30,5.0,3,32,Urban,HR Executive,38767,0 +50828,Male,57,Bachelors,19,27,7,35,97,0.0,1,92,Urban,Data Analyst,117690,0 +50829,Female,23,Bachelors,7,36,65,17,43,2.0,5,52,Urban,Manager,39191,0 +50830,Male,24,Bachelors,15,31,33,40,49,8.0,5,67,Urban,Software Engineer,36865,0 +50831,Male,25,Masters,6,30,42,99,37,4.0,6,21,Semi-Urban,Software Engineer,23869,0 +50832,Male,40,Bachelors,6,13,13,48,48,6.0,7,47,Semi-Urban,Manager,27407,0 +50833,Male,31,Masters,19,68,8,1,70,5.0,2,69,Urban,HR Executive,88357,0 +50834,Female,29,Bachelors,19,90,35,72,28,4.0,2,85,Semi-Urban,Software Engineer,94120,1 +50835,Male,41,Masters,19,39,24,31,31,5.0,0,64,Semi-Urban,Manager,89651,0 +50836,Female,46,Bachelors,6,4,66,93,6,7.0,2,68,Urban,HR Executive,53521,0 +50837,Female,26,Bachelors,3,32,14,90,59,1.0,3,19,Urban,Manager,27877,0 +50838,Female,25,Masters,7,9,5,27,80,0.0,4,17,Rural,Manager,27287,0 +50839,Male,26,Diploma,10,13,50,19,15,8.0,3,16,Urban,ML Engineer,88208,0 +50840,Male,53,Bachelors,17,81,25,75,99,1.0,1,79,Semi-Urban,Manager,105767,1 +50841,Female,39,High School,2,33,64,21,49,3.0,6,31,Urban,Data Analyst,144574,0 +50842,Female,50,Masters,3,25,38,59,71,0.0,5,66,Rural,Manager,124696,0 +50843,Male,46,High School,19,5,20,91,45,2.0,6,7,Urban,ML Engineer,61191,0 +50844,Male,57,Diploma,14,56,60,45,95,7.0,2,70,Urban,Software Engineer,94803,0 +50845,Male,52,Bachelors,8,1,12,96,22,3.0,0,33,Urban,Data Analyst,37970,0 +50846,Female,56,Diploma,9,46,59,9,81,1.0,4,72,Urban,Data Analyst,39891,0 +50847,Female,29,Diploma,7,93,1,54,2,8.0,4,23,Urban,ML Engineer,47853,0 +50848,Female,36,Diploma,14,55,61,34,50,4.0,4,65,Urban,ML Engineer,70983,0 +50849,Female,40,Bachelors,13,45,58,80,86,3.0,0,95,Semi-Urban,Software Engineer,32333,1 +50850,Female,23,Diploma,18,45,35,51,41,5.0,2,25,Urban,Manager,60721,0 +50851,Male,40,High School,8,13,42,72,98,6.0,0,35,Semi-Urban,Manager,64125,0 +50852,Female,30,Masters,8,50,62,55,44,3.0,3,21,Urban,ML Engineer,25891,0 +50853,Female,37,Masters,10,39,55,25,93,7.0,7,33,Urban,Software Engineer,26514,0 +50854,Male,33,Diploma,14,60,12,79,17,7.0,5,91,Urban,HR Executive,63940,1 +50855,Male,46,Diploma,4,44,4,42,77,9.0,4,56,Semi-Urban,Software Engineer,97379,0 +50856,Female,52,High School,10,57,3,27,5,2.0,1,36,Urban,ML Engineer,111517,0 +50857,Female,44,Masters,12,67,90,48,91,4.0,2,32,Rural,HR Executive,45269,0 +50858,Female,57,High School,6,56,5,9,53,6.0,5,94,Urban,ML Engineer,57071,0 +50859,Female,51,Masters,3,95,34,15,38,0.0,2,99,Semi-Urban,HR Executive,71794,1 +50860,Male,49,Bachelors,2,21,73,21,49,0.0,5,47,Semi-Urban,ML Engineer,50060,0 +50861,Female,37,Bachelors,2,83,8,81,3,2.0,0,70,Rural,Data Analyst,120541,1 +50862,Male,44,Bachelors,9,57,97,28,54,1.0,6,15,Urban,Software Engineer,147478,0 +50863,Male,53,Masters,1,73,61,66,2,8.0,4,52,Urban,Data Analyst,33805,1 +50864,Male,45,High School,15,96,65,93,18,7.0,3,66,Urban,Data Analyst,64083,1 +50865,Male,43,Bachelors,7,52,28,51,26,8.0,0,71,Urban,Data Analyst,49965,0 +50866,Male,45,Bachelors,1,60,49,35,5,2.0,3,18,Rural,Manager,69780,0 +50867,Female,28,Bachelors,12,50,23,54,34,9.0,5,97,Urban,HR Executive,87120,0 +50868,Male,59,Diploma,15,70,99,47,5,8.0,1,94,Rural,ML Engineer,78112,1 +50869,Male,39,Bachelors,15,22,80,45,89,5.0,6,66,Semi-Urban,Software Engineer,73317,0 +50870,Male,42,Masters,12,89,51,81,25,1.0,7,44,Urban,Data Analyst,116205,1 +50871,Female,39,PhD,18,32,17,83,49,0.0,0,5,Urban,Manager,82807,0 +50872,Male,43,PhD,2,78,34,23,10,4.0,7,34,Rural,Manager,55098,0 +50873,Male,52,Masters,8,62,1,62,44,1.0,5,21,Semi-Urban,ML Engineer,119021,0 +50874,Male,26,Bachelors,18,74,46,11,59,4.0,3,72,Semi-Urban,ML Engineer,36901,0 +50875,Male,51,Masters,13,93,62,2,76,0.0,3,82,Urban,Software Engineer,146004,1 +50876,Male,58,Bachelors,9,99,79,14,59,0.0,6,15,Urban,ML Engineer,106051,0 +50877,Female,52,Diploma,8,65,75,78,20,5.0,3,68,Rural,Software Engineer,71657,1 +50878,Male,34,High School,3,22,45,87,23,5.0,7,51,Urban,ML Engineer,61094,0 +50879,Male,26,Bachelors,10,28,46,71,0,1.0,0,85,Rural,Manager,63690,0 +50880,Male,37,Bachelors,8,94,48,75,43,9.0,0,72,Urban,ML Engineer,23158,1 +50881,Female,28,High School,2,95,56,42,2,9.0,5,62,Rural,HR Executive,76429,1 +50882,Male,34,Bachelors,5,55,7,84,28,3.0,5,47,Urban,Data Analyst,137769,0 +50883,Other,50,Bachelors,18,90,93,12,66,5.0,3,11,Urban,HR Executive,105403,0 +50884,Female,32,Bachelors,13,54,58,26,89,9.0,5,87,Urban,Manager,78094,0 +50885,Male,26,Bachelors,2,40,30,78,23,4.0,5,54,Semi-Urban,Software Engineer,91381,0 +50886,Female,22,Bachelors,3,10,55,87,81,0.0,7,88,Urban,Software Engineer,91295,0 +50887,Male,33,Diploma,5,97,40,34,98,4.0,5,55,Semi-Urban,Manager,109304,0 +50888,Male,21,Bachelors,10,53,61,28,33,9.0,0,2,Urban,HR Executive,93507,0 +50889,Male,31,Bachelors,16,59,38,86,70,1.0,7,59,Urban,Data Analyst,22832,1 +50890,Female,42,Bachelors,12,25,98,90,61,6.0,5,19,Rural,ML Engineer,99405,0 +50891,Male,55,Bachelors,3,8,62,42,33,4.0,4,58,Rural,Software Engineer,97694,0 +50892,Female,33,Diploma,9,48,52,71,56,0.0,2,36,Urban,Software Engineer,92886,0 +50893,Female,58,Bachelors,2,82,3,81,15,2.0,4,23,Rural,Software Engineer,87674,0 +50894,Male,24,Bachelors,14,66,79,31,91,9.0,2,85,Semi-Urban,HR Executive,83678,1 +50895,Other,28,High School,2,55,82,79,9,4.0,6,36,Urban,ML Engineer,71090,1 +50896,Male,55,Bachelors,4,47,5,70,63,8.0,5,16,Rural,Manager,27117,0 +50897,Female,50,Masters,1,94,68,96,75,6.0,7,47,Rural,ML Engineer,121600,1 +50898,Female,52,Masters,13,88,59,48,91,1.0,1,3,Rural,Data Analyst,106204,0 +50899,Female,37,Bachelors,9,0,33,41,79,3.0,7,85,Urban,Data Analyst,149616,0 +50900,Female,45,PhD,9,75,19,84,86,5.0,6,5,Semi-Urban,Manager,92145,0 +50901,Female,42,Bachelors,1,78,54,77,97,2.0,6,30,Urban,Software Engineer,146938,0 +50902,Male,38,Bachelors,11,58,92,73,18,8.0,1,88,Semi-Urban,Manager,69611,1 +50903,Female,52,Masters,2,38,97,59,79,2.0,7,11,Urban,ML Engineer,118496,0 +50904,Male,51,Bachelors,7,78,85,10,57,0.0,1,59,Urban,ML Engineer,113883,0 +50905,Male,32,Bachelors,13,32,24,81,20,7.0,3,43,Urban,Manager,44925,0 +50906,Female,25,High School,2,35,48,15,15,0.0,4,15,Urban,HR Executive,52506,0 +50907,Male,28,Diploma,8,49,96,44,37,0.0,7,31,Semi-Urban,Data Analyst,56801,0 +50908,Male,39,Masters,10,54,42,51,97,2.0,6,38,Urban,Manager,53529,0 +50909,Male,55,Masters,9,53,30,98,34,4.0,5,24,Rural,Software Engineer,114600,0 +50910,Male,30,Diploma,19,55,78,11,53,3.0,7,24,Urban,Manager,94687,0 +50911,Male,55,Diploma,13,97,59,31,14,6.0,2,70,Urban,Manager,69563,1 +50912,Male,37,Bachelors,7,27,26,88,98,9.0,5,83,Urban,Manager,94948,0 +50913,Female,33,Masters,7,46,42,61,21,2.0,7,38,Semi-Urban,Data Analyst,86021,0 +50914,Male,55,Masters,13,82,53,53,36,6.0,6,73,Urban,Software Engineer,88818,1 +50915,Male,29,Masters,11,91,2,51,19,5.0,0,2,Urban,Data Analyst,132805,0 +50916,Other,40,Bachelors,0,17,94,65,39,1.0,7,68,Urban,Manager,66345,1 +50917,Other,55,Masters,7,73,3,7,81,4.0,0,22,Urban,Software Engineer,74027,0 +50918,Female,38,High School,7,29,73,27,98,8.0,5,52,Rural,Data Analyst,124027,0 +50919,Male,29,High School,12,80,40,55,60,7.0,7,33,Semi-Urban,Data Analyst,57216,0 +50920,Male,48,Diploma,0,11,3,22,72,7.0,3,49,Semi-Urban,HR Executive,133421,0 +50921,Female,48,Diploma,5,78,37,76,26,3.0,7,50,Rural,Data Analyst,134563,1 +50922,Male,58,Bachelors,19,23,44,21,81,4.0,1,24,Rural,Data Analyst,148534,0 +50923,Other,38,Bachelors,3,17,54,47,38,6.0,3,21,Urban,Data Analyst,100598,0 +50924,Male,43,Masters,2,54,81,49,19,2.0,7,54,Semi-Urban,Software Engineer,149613,1 +50925,Female,53,Bachelors,8,94,68,2,31,1.0,2,4,Urban,Manager,20802,0 +50926,Male,22,Bachelors,13,60,53,9,97,8.0,1,61,Urban,Manager,127996,0 +50927,Male,59,Bachelors,6,48,77,48,86,7.0,4,39,Rural,Software Engineer,112865,0 +50928,Female,35,Diploma,16,74,51,60,26,9.0,2,61,Semi-Urban,ML Engineer,111032,1 +50929,Female,22,Bachelors,8,30,0,21,98,2.0,1,86,Urban,Manager,71167,0 +50930,Female,54,Masters,19,28,54,82,35,8.0,7,20,Rural,ML Engineer,101110,0 +50931,Male,37,High School,0,5,55,55,7,6.0,1,64,Semi-Urban,ML Engineer,80773,0 +50932,Female,56,Diploma,19,68,32,48,57,2.0,6,60,Rural,Software Engineer,134511,0 +50933,Male,30,Diploma,17,10,12,9,64,1.0,2,19,Semi-Urban,Software Engineer,61555,0 +50934,Male,44,Masters,19,15,14,21,71,4.0,2,36,Rural,Manager,24619,0 +50935,Male,39,Bachelors,2,92,50,68,98,7.0,3,13,Urban,ML Engineer,111960,0 +50936,Female,21,Bachelors,13,53,66,14,43,2.0,5,52,Urban,HR Executive,53114,0 +50937,Male,22,High School,18,65,2,42,64,2.0,6,86,Urban,ML Engineer,46841,0 +50938,Female,59,Bachelors,9,66,52,18,32,9.0,5,25,Urban,Data Analyst,48317,0 +50939,Male,27,Bachelors,1,77,87,38,47,8.0,2,77,Rural,HR Executive,113343,1 +50940,Male,31,Masters,15,97,53,63,46,5.0,4,3,Semi-Urban,HR Executive,115083,0 +50941,Male,24,High School,7,26,60,94,43,2.0,5,38,Urban,Software Engineer,104580,0 +50942,Male,34,High School,14,54,28,93,32,4.0,7,67,Semi-Urban,ML Engineer,80131,1 +50943,Male,47,Masters,13,46,3,65,73,0.0,2,32,Urban,Data Analyst,149235,0 +50944,Male,34,Bachelors,17,70,72,93,44,4.0,2,67,Urban,Software Engineer,125177,1 +50945,Male,27,Masters,16,96,25,89,77,2.0,1,96,Urban,Software Engineer,121109,1 +50946,Male,25,Diploma,5,18,48,0,31,0.0,5,93,Rural,Data Analyst,49938,0 +50947,Male,59,Diploma,2,35,36,57,21,8.0,5,62,Urban,Manager,39756,0 +50948,Male,34,Masters,18,90,22,55,96,5.0,7,47,Urban,Data Analyst,34959,0 +50949,Male,27,Masters,6,33,52,32,25,5.0,7,24,Urban,Software Engineer,48496,0 +50950,Male,23,Bachelors,1,59,30,33,99,8.0,1,29,Urban,HR Executive,48442,0 +50951,Other,56,Masters,0,90,4,86,74,8.0,5,81,Urban,Manager,115090,1 +50952,Male,47,Bachelors,1,28,70,79,62,5.0,5,72,Rural,ML Engineer,76182,1 +50953,Male,44,Masters,19,77,70,86,35,0.0,2,96,Urban,ML Engineer,27109,1 +50954,Male,56,High School,17,27,31,43,9,7.0,0,41,Urban,HR Executive,46326,0 +50955,Male,30,Bachelors,19,5,66,11,35,0.0,2,30,Semi-Urban,ML Engineer,123780,0 +50956,Male,36,Bachelors,3,20,22,3,96,9.0,6,8,Urban,ML Engineer,91533,0 +50957,Male,22,Bachelors,14,29,7,90,53,8.0,5,58,Semi-Urban,Data Analyst,70136,0 +50958,Male,29,High School,0,92,93,6,13,6.0,4,42,Semi-Urban,Data Analyst,131326,0 +50959,Female,46,Diploma,16,1,80,8,40,8.0,6,90,Semi-Urban,ML Engineer,92581,0 +50960,Female,32,PhD,16,39,80,51,57,4.0,3,54,Semi-Urban,Software Engineer,125298,0 +50961,Female,24,High School,0,69,95,92,55,1.0,2,59,Rural,Software Engineer,33695,1 +50962,Male,46,Masters,7,74,69,71,61,1.0,6,64,Urban,Data Analyst,97717,1 +50963,Female,48,Masters,15,80,43,72,88,7.0,0,82,Urban,ML Engineer,114356,1 +50964,Male,21,Bachelors,11,9,53,14,67,3.0,5,18,Rural,ML Engineer,49817,0 +50965,Female,59,Bachelors,1,89,9,17,69,9.0,4,20,Rural,Manager,137137,0 +50966,Male,56,Bachelors,1,28,70,98,52,2.0,5,46,Urban,Data Analyst,144289,1 +50967,Male,51,Masters,0,38,67,7,33,1.0,4,79,Semi-Urban,Software Engineer,117673,0 +50968,Male,34,High School,17,29,10,87,66,3.0,5,8,Urban,Manager,78465,0 +50969,Female,51,Diploma,8,9,71,91,80,4.0,3,29,Urban,ML Engineer,131166,0 +50970,Female,56,Bachelors,17,73,21,94,42,4.0,6,11,Semi-Urban,Manager,130006,0 +50971,Male,33,Bachelors,16,81,85,17,28,7.0,3,52,Semi-Urban,Manager,33366,1 +50972,Female,57,Bachelors,17,57,39,66,69,7.0,4,30,Semi-Urban,Software Engineer,44247,0 +50973,Female,58,Masters,13,38,9,98,21,2.0,7,95,Urban,ML Engineer,128435,0 +50974,Male,31,Diploma,19,0,91,46,89,4.0,1,36,Urban,HR Executive,115131,0 +50975,Male,59,Bachelors,3,0,76,38,20,3.0,7,20,Urban,Manager,124049,0 +50976,Female,28,PhD,7,83,54,21,7,6.0,1,4,Semi-Urban,Data Analyst,80959,0 +50977,Male,49,Bachelors,14,25,77,49,30,8.0,2,61,Urban,ML Engineer,115137,0 +50978,Female,49,Bachelors,0,90,44,95,79,5.0,1,33,Rural,HR Executive,114960,1 +50979,Male,22,High School,17,45,17,87,84,1.0,6,82,Urban,Manager,29979,0 +50980,Other,30,High School,19,92,5,77,96,4.0,2,76,Urban,Software Engineer,113693,1 +50981,Female,39,Bachelors,10,17,30,98,46,3.0,7,33,Rural,Manager,113590,0 +50982,Male,59,Masters,3,65,5,86,81,8.0,4,34,Urban,Manager,111474,0 +50983,Male,32,High School,1,5,68,51,32,7.0,6,40,Urban,Manager,73656,0 +50984,Male,28,Masters,19,46,37,87,6,8.0,0,13,Urban,Manager,115692,0 +50985,Male,27,Masters,18,2,39,89,88,2.0,2,23,Rural,Data Analyst,51292,0 +50986,Male,33,Diploma,4,79,32,26,48,8.0,4,17,Urban,Software Engineer,44312,0 +50987,Female,55,High School,6,96,91,82,25,8.0,6,13,Semi-Urban,Manager,99494,1 +50988,Female,22,Masters,17,31,98,2,1,8.0,2,75,Semi-Urban,ML Engineer,68189,0 +50989,Female,23,High School,6,24,15,52,2,7.0,6,54,Urban,ML Engineer,87397,0 +50990,Male,58,Bachelors,7,45,89,96,86,4.0,3,35,Urban,ML Engineer,61571,1 +50991,Female,52,Bachelors,17,75,98,75,79,9.0,0,72,Urban,HR Executive,115993,1 +50992,Male,32,Bachelors,15,60,60,73,66,9.0,3,2,Semi-Urban,Software Engineer,27654,0 +50993,Male,34,Masters,1,5,53,83,36,9.0,3,50,Semi-Urban,Software Engineer,85972,0 +50994,Male,38,Masters,1,35,7,52,54,4.0,4,80,Rural,HR Executive,45078,0 +50995,Female,44,Masters,16,48,30,96,0,4.0,4,89,Urban,Manager,50454,1 +50996,Male,39,Bachelors,4,69,2,35,39,6.0,1,87,Urban,ML Engineer,109971,0 +50997,Other,55,Diploma,11,93,9,31,1,6.0,3,2,Urban,HR Executive,98929,0 +50998,Female,37,Diploma,12,83,73,27,84,6.0,0,6,Urban,ML Engineer,67212,0 +50999,Male,40,Bachelors,5,81,34,40,52,8.0,7,78,Rural,Manager,44523,0 +51000,Male,47,Diploma,18,51,2,90,86,4.0,7,50,Urban,Software Engineer,119808,0 +51001,Male,25,Masters,12,7,48,69,28,4.0,4,41,Urban,HR Executive,88120,0 +51002,Female,54,Bachelors,15,12,17,37,89,4.0,7,13,Urban,HR Executive,22823,0 +51003,Male,57,Bachelors,16,43,96,60,71,9.0,1,64,Semi-Urban,Data Analyst,130681,1 +51004,Male,32,Bachelors,4,80,77,79,86,6.0,0,38,Urban,ML Engineer,86220,1 +51005,Male,56,Diploma,10,45,63,91,68,3.0,7,44,Urban,Manager,111035,1 +51006,Female,37,Bachelors,13,21,70,53,32,6.0,7,78,Urban,Manager,141824,0 +51007,Male,59,Masters,5,89,64,42,26,4.0,2,46,Urban,Software Engineer,141715,1 +51008,Male,55,Diploma,13,7,28,70,4,6.0,4,73,Urban,Software Engineer,21343,0 +51009,Female,24,Bachelors,14,18,94,42,88,6.0,2,91,Urban,Software Engineer,32136,1 +51010,Male,46,Masters,16,68,32,44,84,1.0,2,77,Urban,Data Analyst,62454,0 +51011,Female,37,Diploma,7,12,42,76,16,7.0,1,97,Urban,Manager,47186,0 +51012,Female,36,Masters,19,0,33,23,45,5.0,5,94,Semi-Urban,HR Executive,36813,0 +51013,Male,50,Bachelors,14,30,19,48,11,5.0,6,40,Urban,ML Engineer,33812,0 +51014,Female,29,High School,5,68,97,2,96,1.0,7,32,Urban,Software Engineer,120807,0 +51015,Female,40,Diploma,3,35,55,0,96,0.0,2,98,Semi-Urban,Manager,43364,0 +51016,Female,21,PhD,1,53,40,25,65,7.0,2,50,Semi-Urban,Manager,111313,0 +51017,Male,27,Masters,7,47,51,85,63,1.0,7,11,Rural,Data Analyst,110586,0 +51018,Other,24,Bachelors,15,25,35,33,5,1.0,5,69,Rural,Manager,73705,0 +51019,Male,24,Bachelors,9,18,66,8,56,6.0,1,30,Urban,HR Executive,122033,0 +51020,Male,45,PhD,4,40,97,13,83,1.0,5,40,Semi-Urban,Data Analyst,49297,0 +51021,Male,45,Bachelors,5,61,53,63,68,2.0,1,0,Urban,Manager,42774,0 +51022,Male,47,Masters,0,13,50,44,42,6.0,2,74,Rural,Manager,39548,0 +51023,Female,45,Bachelors,10,20,45,88,24,3.0,3,57,Urban,ML Engineer,137830,0 +51024,Female,39,Masters,3,95,86,1,54,1.0,2,28,Urban,Manager,132446,0 +51025,Female,24,PhD,7,40,25,20,37,4.0,4,97,Semi-Urban,Software Engineer,29128,0 +51026,Male,46,Masters,12,79,95,83,83,2.0,5,96,Urban,Data Analyst,46723,1 +51027,Female,41,PhD,5,10,1,54,80,6.0,6,8,Semi-Urban,Software Engineer,86925,0 +51028,Male,36,Bachelors,6,64,44,61,38,2.0,5,86,Urban,Manager,110038,1 +51029,Male,32,Masters,7,90,10,56,62,5.0,2,48,Rural,Software Engineer,24563,0 +51030,Female,51,High School,16,63,80,81,55,5.0,1,55,Semi-Urban,Manager,97433,1 +51031,Male,22,Bachelors,6,15,75,8,6,4.0,1,96,Urban,HR Executive,91345,0 +51032,Male,41,High School,12,27,23,77,79,5.0,2,7,Rural,ML Engineer,59337,0 +51033,Female,51,High School,6,57,51,30,50,2.0,4,85,Urban,Data Analyst,111183,0 +51034,Female,25,Masters,6,16,47,33,47,8.0,0,55,Urban,Software Engineer,101360,0 +51035,Female,49,Bachelors,1,50,53,65,62,2.0,2,93,Urban,Data Analyst,119683,1 +51036,Male,38,Bachelors,16,85,27,6,47,6.0,5,87,Rural,ML Engineer,50383,0 +51037,Male,40,Bachelors,15,66,85,51,72,1.0,4,30,Urban,Manager,111643,0 +51038,Male,57,Masters,16,46,17,63,86,5.0,1,98,Urban,ML Engineer,105645,0 +51039,Female,58,Bachelors,7,47,44,89,36,2.0,2,98,Urban,Manager,82826,1 +51040,Male,43,Bachelors,4,62,60,17,86,7.0,4,7,Urban,ML Engineer,58595,0 +51041,Female,50,Bachelors,6,38,25,13,7,2.0,5,15,Urban,HR Executive,71668,0 +51042,Male,45,Diploma,9,7,4,36,88,2.0,1,26,Urban,HR Executive,141141,0 +51043,Female,32,Bachelors,7,59,65,70,3,8.0,1,78,Semi-Urban,Software Engineer,22765,1 +51044,Male,42,Bachelors,1,18,85,77,95,0.0,2,44,Urban,ML Engineer,66206,0 +51045,Male,46,Bachelors,18,93,59,17,12,7.0,7,85,Semi-Urban,Software Engineer,26528,1 +51046,Female,43,Masters,0,0,7,63,2,7.0,2,34,Urban,ML Engineer,108056,0 +51047,Male,39,PhD,4,80,85,76,0,5.0,2,34,Urban,ML Engineer,108100,1 +51048,Male,26,Bachelors,9,52,91,29,12,9.0,0,94,Rural,Data Analyst,128146,1 +51049,Female,51,Masters,8,61,65,28,33,1.0,3,55,Urban,HR Executive,50176,0 +51050,Female,43,Bachelors,8,65,86,65,75,9.0,0,0,Rural,ML Engineer,76795,0 +51051,Male,48,Diploma,16,43,27,51,47,1.0,3,26,Semi-Urban,ML Engineer,57077,0 +51052,Female,55,Masters,14,29,18,73,29,9.0,4,65,Urban,HR Executive,60673,0 +51053,Female,39,Bachelors,11,51,52,38,56,2.0,1,73,Urban,HR Executive,35185,0 +51054,Female,58,Masters,7,92,18,57,51,1.0,0,94,Semi-Urban,HR Executive,21862,1 +51055,Female,54,Bachelors,13,68,46,14,43,9.0,6,99,Urban,ML Engineer,110487,0 +51056,Female,56,Masters,0,4,58,31,77,2.0,0,99,Semi-Urban,HR Executive,148103,0 +51057,Female,23,Bachelors,0,89,52,39,77,0.0,2,7,Semi-Urban,ML Engineer,117738,0 +51058,Male,22,Bachelors,8,99,35,81,24,9.0,5,48,Rural,Manager,43098,1 +51059,Other,58,Bachelors,15,81,31,15,20,8.0,1,69,Urban,ML Engineer,21356,0 +51060,Male,57,Diploma,13,51,79,89,97,4.0,0,89,Urban,HR Executive,49896,1 +51061,Other,26,Masters,0,48,7,44,70,1.0,3,23,Semi-Urban,Data Analyst,23315,0 +51062,Male,47,High School,0,68,33,95,98,1.0,0,2,Semi-Urban,ML Engineer,87214,0 +51063,Male,22,Masters,11,22,23,5,80,5.0,0,1,Urban,Manager,102421,0 +51064,Female,54,Bachelors,16,38,90,31,43,5.0,5,86,Rural,ML Engineer,64315,1 +51065,Male,33,Diploma,10,17,98,71,50,8.0,4,20,Urban,Manager,89983,0 +51066,Male,48,Diploma,9,79,50,27,39,4.0,3,83,Semi-Urban,ML Engineer,101964,1 +51067,Female,43,Masters,2,79,88,75,55,6.0,6,78,Urban,Data Analyst,117405,1 +51068,Female,42,High School,1,53,81,77,6,5.0,0,41,Urban,HR Executive,43917,1 +51069,Male,23,Bachelors,8,32,73,47,25,1.0,4,47,Urban,Software Engineer,85577,0 +51070,Male,39,Diploma,13,89,0,54,8,7.0,1,21,Urban,Software Engineer,49568,0 +51071,Male,33,Diploma,15,11,57,60,51,4.0,2,45,Rural,Software Engineer,134987,0 +51072,Male,47,Bachelors,14,33,94,77,42,4.0,1,34,Urban,ML Engineer,142992,1 +51073,Male,30,Bachelors,1,16,16,62,66,8.0,3,68,Rural,HR Executive,111841,0 +51074,Male,32,Bachelors,8,1,33,92,23,9.0,3,54,Semi-Urban,Manager,21774,0 +51075,Male,33,Masters,6,85,33,25,81,9.0,7,65,Rural,Data Analyst,58405,0 +51076,Female,41,Bachelors,11,40,92,73,6,9.0,7,21,Semi-Urban,ML Engineer,84250,0 +51077,Female,37,Bachelors,12,85,2,8,63,7.0,0,56,Rural,ML Engineer,77758,0 +51078,Male,22,Masters,13,38,24,54,3,6.0,5,53,Urban,Data Analyst,120838,0 +51079,Male,39,Bachelors,17,14,9,38,29,8.0,4,63,Semi-Urban,ML Engineer,43578,0 +51080,Female,26,Bachelors,2,26,54,13,73,1.0,2,51,Urban,Data Analyst,30627,0 +51081,Female,54,High School,10,86,47,58,96,3.0,2,76,Rural,Data Analyst,110989,1 +51082,Male,22,High School,13,52,95,36,0,2.0,4,95,Urban,Manager,113038,1 +51083,Male,22,Bachelors,16,57,48,24,35,3.0,6,10,Urban,Data Analyst,103488,0 +51084,Other,44,Bachelors,0,40,76,47,63,6.0,1,10,Rural,Manager,73957,0 +51085,Female,43,PhD,2,54,95,94,66,1.0,3,10,Rural,HR Executive,128951,1 +51086,Female,41,PhD,17,27,78,27,41,5.0,1,76,Urban,HR Executive,38906,0 +51087,Female,38,High School,18,53,50,74,17,4.0,4,63,Semi-Urban,HR Executive,32869,0 +51088,Male,46,High School,7,88,46,83,73,9.0,4,12,Semi-Urban,HR Executive,74576,0 +51089,Male,37,Diploma,11,5,34,68,84,1.0,3,82,Urban,Software Engineer,119254,0 +51090,Female,40,Bachelors,4,61,70,37,18,5.0,3,33,Urban,Software Engineer,32915,0 +51091,Male,59,Diploma,6,85,1,0,17,6.0,0,9,Semi-Urban,ML Engineer,54812,0 +51092,Male,47,High School,3,19,33,54,72,6.0,5,77,Semi-Urban,Software Engineer,78002,0 +51093,Male,34,Bachelors,4,57,6,62,39,8.0,2,97,Rural,ML Engineer,49422,0 +51094,Female,55,Diploma,11,36,99,60,96,3.0,6,88,Urban,Manager,75159,1 +51095,Female,41,Masters,11,35,83,9,20,9.0,0,31,Semi-Urban,Software Engineer,67910,0 +51096,Male,37,Masters,1,64,73,52,30,1.0,4,20,Semi-Urban,ML Engineer,148942,0 +51097,Female,35,PhD,8,80,99,54,56,3.0,5,68,Urban,Software Engineer,30750,1 +51098,Male,51,High School,14,25,55,2,12,8.0,7,7,Urban,Data Analyst,141403,0 +51099,Male,25,Diploma,7,71,72,15,87,0.0,6,20,Urban,HR Executive,128268,0 +51100,Male,25,Bachelors,17,16,47,28,14,2.0,3,82,Semi-Urban,HR Executive,73978,0 +51101,Female,44,Bachelors,17,69,78,62,73,9.0,5,59,Urban,HR Executive,74965,1 +51102,Male,54,Masters,13,19,75,46,35,1.0,0,52,Semi-Urban,ML Engineer,50941,0 +51103,Male,43,Bachelors,7,54,78,88,75,2.0,5,60,Urban,Data Analyst,106872,1 +51104,Male,26,Bachelors,4,29,39,62,78,4.0,2,84,Urban,Manager,136422,0 +51105,Male,45,Masters,7,99,36,58,60,2.0,5,31,Semi-Urban,ML Engineer,136868,0 +51106,Female,44,Diploma,13,23,29,20,0,7.0,6,15,Semi-Urban,Data Analyst,125088,0 +51107,Male,40,Diploma,7,79,7,63,4,9.0,0,89,Urban,ML Engineer,114909,1 +51108,Male,22,High School,3,71,12,67,44,5.0,1,52,Semi-Urban,Data Analyst,96732,0 +51109,Male,58,Masters,6,7,24,1,71,8.0,2,69,Urban,ML Engineer,61855,0 +51110,Male,38,High School,15,64,94,76,55,5.0,1,4,Semi-Urban,Software Engineer,110746,1 +51111,Male,47,Bachelors,13,48,13,64,66,7.0,1,56,Urban,Software Engineer,77225,0 +51112,Male,35,Bachelors,12,23,31,71,28,9.0,5,47,Urban,Manager,117765,0 +51113,Male,29,Diploma,16,79,47,3,15,7.0,7,59,Urban,HR Executive,76717,0 +51114,Male,40,Bachelors,5,66,6,29,73,1.0,0,87,Urban,ML Engineer,137308,0 +51115,Male,59,High School,12,26,66,96,62,7.0,4,87,Rural,Manager,35274,1 +51116,Male,42,Diploma,9,41,17,76,96,2.0,7,62,Semi-Urban,Data Analyst,126604,0 +51117,Female,49,Diploma,3,45,41,61,0,0.0,1,12,Semi-Urban,Manager,34699,0 +51118,Male,45,Masters,3,57,11,17,89,6.0,5,11,Urban,HR Executive,62194,0 +51119,Female,40,Bachelors,8,9,93,32,37,4.0,1,95,Urban,HR Executive,28324,0 +51120,Female,47,Bachelors,10,23,84,51,84,6.0,4,90,Semi-Urban,HR Executive,132236,1 +51121,Male,45,Bachelors,4,85,72,95,61,6.0,0,40,Urban,ML Engineer,123238,1 +51122,Female,32,High School,13,93,61,54,61,4.0,7,23,Urban,ML Engineer,56476,0 +51123,Female,38,Bachelors,10,61,27,41,19,5.0,2,11,Semi-Urban,Data Analyst,144773,0 +51124,Female,41,Bachelors,8,85,19,54,2,5.0,5,56,Rural,HR Executive,74096,0 +51125,Female,51,Bachelors,16,52,91,47,55,3.0,3,40,Rural,Data Analyst,78017,0 +51126,Male,38,Bachelors,15,37,81,66,96,6.0,5,79,Urban,HR Executive,57097,1 +51127,Male,36,High School,15,82,9,97,0,0.0,6,76,Urban,ML Engineer,20524,1 +51128,Male,40,Masters,9,33,3,57,89,6.0,4,4,Semi-Urban,Data Analyst,64408,0 +51129,Male,49,Bachelors,19,64,29,87,24,3.0,2,92,Urban,ML Engineer,136878,1 +51130,Male,31,Bachelors,14,56,20,71,41,4.0,5,97,Urban,Data Analyst,47694,1 +51131,Female,23,Diploma,4,42,96,45,96,0.0,2,66,Semi-Urban,Manager,123543,1 +51132,Male,28,Masters,5,76,65,60,40,6.0,1,70,Urban,Data Analyst,25018,1 +51133,Male,39,Bachelors,19,29,15,89,10,8.0,0,71,Urban,ML Engineer,49627,0 +51134,Male,46,Masters,9,30,1,16,19,0.0,4,7,Urban,HR Executive,100622,0 +51135,Male,47,Bachelors,0,17,51,6,22,7.0,6,60,Urban,Software Engineer,26994,0 +51136,Male,35,High School,16,72,2,67,48,4.0,7,22,Urban,ML Engineer,74271,0 +51137,Female,39,Masters,4,85,72,65,26,7.0,7,1,Urban,Data Analyst,50548,0 +51138,Other,52,Masters,16,7,77,40,60,1.0,4,97,Rural,Data Analyst,40063,0 +51139,Male,56,Bachelors,16,25,86,87,40,2.0,5,70,Urban,HR Executive,52554,1 +51140,Male,42,Masters,2,94,38,52,87,8.0,7,7,Rural,Manager,117065,0 +51141,Female,26,Diploma,0,39,49,12,51,8.0,2,54,Semi-Urban,Data Analyst,75479,0 +51142,Female,48,High School,1,52,7,22,20,8.0,6,83,Urban,ML Engineer,140178,0 +51143,Female,31,Bachelors,15,98,29,23,48,7.0,3,32,Urban,Data Analyst,87817,0 +51144,Female,25,Bachelors,12,21,26,69,52,9.0,1,83,Urban,Software Engineer,58082,0 +51145,Male,36,High School,16,28,29,87,81,7.0,5,12,Semi-Urban,Software Engineer,103908,0 +51146,Female,58,Bachelors,9,99,23,15,34,1.0,6,32,Urban,HR Executive,113630,0 +51147,Male,39,Bachelors,10,48,54,68,79,5.0,7,27,Urban,ML Engineer,28208,0 +51148,Female,27,High School,15,72,8,47,20,5.0,4,80,Urban,Data Analyst,119081,0 +51149,Female,53,Bachelors,19,39,58,60,51,3.0,2,74,Urban,ML Engineer,56993,0 +51150,Female,38,Diploma,1,92,45,45,12,1.0,3,59,Rural,HR Executive,136981,1 +51151,Male,24,Diploma,5,95,23,40,98,5.0,2,72,Urban,ML Engineer,116084,0 +51152,Female,53,Masters,12,97,50,71,32,7.0,0,24,Urban,HR Executive,108924,1 +51153,Female,40,Masters,16,74,65,82,75,0.0,4,6,Semi-Urban,Manager,94392,0 +51154,Male,52,Bachelors,1,80,39,46,76,0.0,4,25,Urban,Software Engineer,25302,0 +51155,Female,34,Bachelors,2,9,66,2,91,1.0,0,74,Urban,ML Engineer,91987,0 +51156,Female,29,High School,15,6,10,30,73,7.0,2,89,Semi-Urban,HR Executive,128367,0 +51157,Female,47,PhD,13,42,67,97,63,7.0,6,43,Semi-Urban,ML Engineer,123128,1 +51158,Male,44,Bachelors,4,11,19,31,66,6.0,3,2,Urban,Software Engineer,131021,0 +51159,Female,24,High School,12,99,72,38,99,7.0,4,42,Urban,Software Engineer,32309,1 +51160,Male,47,High School,7,7,54,16,1,7.0,4,19,Semi-Urban,Data Analyst,65968,0 +51161,Female,40,Bachelors,11,37,83,34,11,9.0,5,92,Urban,HR Executive,146864,1 +51162,Other,29,Bachelors,19,34,93,34,61,7.0,1,57,Semi-Urban,HR Executive,135327,0 +51163,Female,41,High School,5,93,92,66,29,2.0,1,92,Urban,HR Executive,131610,1 +51164,Female,42,Bachelors,11,90,75,77,14,8.0,0,98,Semi-Urban,Manager,31066,1 +51165,Male,27,Bachelors,15,22,83,34,80,1.0,2,72,Urban,HR Executive,74165,0 +51166,Other,23,Masters,1,55,41,49,52,8.0,6,88,Semi-Urban,ML Engineer,90872,0 +51167,Other,34,Bachelors,14,16,70,73,41,1.0,1,65,Urban,HR Executive,25824,0 +51168,Male,40,Masters,13,29,2,33,57,8.0,0,92,Semi-Urban,Manager,75506,0 +51169,Male,53,Masters,16,24,88,55,84,2.0,1,24,Rural,Software Engineer,99892,0 +51170,Male,46,Diploma,14,68,94,26,60,0.0,3,13,Urban,ML Engineer,61332,0 +51171,Male,37,High School,14,38,15,4,71,5.0,7,11,Urban,HR Executive,85059,0 +51172,Male,27,High School,12,13,81,71,54,6.0,7,67,Semi-Urban,ML Engineer,96472,0 +51173,Male,35,Diploma,5,59,54,34,47,2.0,6,47,Urban,Software Engineer,101378,0 +51174,Other,57,Bachelors,12,88,41,64,51,3.0,2,89,Rural,Software Engineer,120997,1 +51175,Male,36,Bachelors,16,26,3,63,56,7.0,5,48,Urban,Data Analyst,79949,0 +51176,Female,29,PhD,9,28,93,66,83,9.0,1,53,Urban,Manager,115079,0 +51177,Female,51,Bachelors,16,28,77,52,40,5.0,0,67,Semi-Urban,HR Executive,87658,0 +51178,Female,26,Bachelors,8,73,63,5,7,9.0,1,69,Urban,HR Executive,147220,0 +51179,Male,28,Masters,11,27,36,99,5,3.0,1,21,Semi-Urban,Data Analyst,131972,0 +51180,Male,58,Diploma,18,27,83,10,57,0.0,7,75,Urban,HR Executive,91682,0 +51181,Male,51,Diploma,11,91,61,28,10,2.0,0,52,Semi-Urban,HR Executive,135535,0 +51182,Female,47,Bachelors,3,7,76,37,21,4.0,6,90,Urban,ML Engineer,41344,0 +51183,Male,32,Bachelors,14,25,5,12,59,0.0,5,21,Urban,ML Engineer,138470,0 +51184,Male,25,Masters,9,6,57,78,33,6.0,7,90,Urban,ML Engineer,123386,0 +51185,Male,57,Bachelors,1,40,26,83,11,6.0,7,36,Rural,HR Executive,145560,0 +51186,Male,45,Bachelors,3,54,95,85,49,9.0,6,1,Urban,Software Engineer,128556,1 +51187,Other,59,Masters,14,1,81,56,15,5.0,2,38,Semi-Urban,ML Engineer,136953,0 +51188,Male,50,Diploma,7,78,15,78,47,0.0,6,86,Rural,Software Engineer,46493,1 +51189,Female,51,Diploma,5,45,72,4,62,0.0,2,7,Urban,Manager,42085,0 +51190,Male,51,Masters,4,84,82,19,97,2.0,6,1,Rural,ML Engineer,109083,0 +51191,Female,43,Diploma,5,36,61,80,20,7.0,7,22,Semi-Urban,Software Engineer,82855,0 +51192,Male,50,High School,13,25,74,59,53,1.0,7,87,Semi-Urban,ML Engineer,25938,1 +51193,Female,29,Diploma,19,32,65,86,61,0.0,3,25,Urban,HR Executive,70373,0 +51194,Male,23,High School,3,26,25,87,19,2.0,0,51,Semi-Urban,ML Engineer,87647,0 +51195,Female,29,PhD,12,75,50,26,30,5.0,7,86,Semi-Urban,Manager,44614,0 +51196,Male,22,Masters,16,38,20,92,77,7.0,3,60,Urban,Software Engineer,57727,0 +51197,Male,26,High School,10,88,10,96,61,6.0,0,50,Rural,Software Engineer,100998,1 +51198,Male,28,PhD,17,0,37,3,72,0.0,4,90,Semi-Urban,Data Analyst,112670,0 +51199,Male,49,Bachelors,11,47,98,11,80,7.0,1,75,Semi-Urban,Data Analyst,30198,0 +51200,Male,42,Bachelors,3,15,62,91,25,4.0,2,8,Urban,Manager,122380,0 +51201,Female,29,Bachelors,10,78,79,99,28,9.0,2,0,Semi-Urban,Manager,94064,1 +51202,Male,36,High School,9,62,47,80,58,9.0,2,50,Urban,Manager,50845,1 +51203,Male,34,Masters,18,70,15,28,4,6.0,6,25,Rural,HR Executive,57928,0 +51204,Male,26,High School,9,73,3,62,2,9.0,3,87,Urban,ML Engineer,20811,0 +51205,Male,32,High School,19,31,81,90,28,9.0,5,37,Urban,HR Executive,71276,1 +51206,Male,55,Diploma,6,60,58,27,72,2.0,4,96,Semi-Urban,ML Engineer,77378,1 +51207,Male,47,Diploma,3,66,18,72,11,2.0,5,92,Urban,Data Analyst,83051,1 +51208,Male,33,High School,11,50,67,58,13,6.0,4,18,Urban,ML Engineer,35406,0 +51209,Male,26,High School,12,69,46,19,99,5.0,1,39,Urban,Software Engineer,50384,0 +51210,Male,54,Bachelors,8,5,54,80,6,2.0,7,10,Semi-Urban,Data Analyst,110532,0 +51211,Male,48,PhD,18,30,56,76,31,1.0,2,37,Rural,ML Engineer,62431,0 +51212,Female,44,High School,12,4,43,14,35,0.0,0,59,Rural,Software Engineer,50219,0 +51213,Female,57,Diploma,0,41,77,71,74,0.0,2,74,Urban,Manager,83014,1 +51214,Female,37,Diploma,11,35,5,32,41,9.0,3,88,Urban,Software Engineer,65094,0 +51215,Male,48,Bachelors,9,71,47,7,33,1.0,0,10,Urban,Software Engineer,101908,0 +51216,Female,37,Bachelors,12,62,46,84,20,1.0,4,4,Urban,Manager,130400,0 +51217,Female,39,Bachelors,0,98,23,28,7,9.0,6,65,Urban,Software Engineer,137837,0 +51218,Male,36,High School,8,73,69,84,23,5.0,4,99,Rural,ML Engineer,123113,1 +51219,Male,32,Bachelors,1,39,40,93,0,2.0,7,66,Urban,ML Engineer,93642,1 +51220,Male,40,Bachelors,1,49,18,12,50,9.0,5,23,Rural,Software Engineer,74911,0 +51221,Male,27,Bachelors,17,15,92,85,32,7.0,4,37,Urban,Manager,87959,0 +51222,Female,47,High School,4,12,65,65,23,2.0,4,99,Urban,Data Analyst,76029,1 +51223,Female,53,Masters,1,47,29,98,38,1.0,6,52,Urban,HR Executive,138074,0 +51224,Male,52,Diploma,16,12,12,90,14,2.0,7,91,Rural,Manager,43824,0 +51225,Male,52,Bachelors,5,44,52,4,22,7.0,3,72,Urban,HR Executive,89967,0 +51226,Male,46,Diploma,1,17,19,20,12,6.0,2,25,Rural,Data Analyst,73473,0 +51227,Male,34,High School,17,44,92,43,38,3.0,2,8,Rural,Data Analyst,129071,0 +51228,Male,56,High School,5,98,35,28,70,2.0,3,36,Rural,ML Engineer,145740,0 +51229,Male,55,High School,10,2,69,1,88,7.0,5,16,Rural,ML Engineer,50973,0 +51230,Male,54,Bachelors,7,52,87,55,26,4.0,6,33,Urban,Software Engineer,83227,0 +51231,Female,50,Bachelors,4,59,73,96,81,3.0,2,29,Urban,ML Engineer,47981,1 +51232,Female,44,Bachelors,19,97,81,62,1,7.0,6,37,Rural,Software Engineer,82760,1 +51233,Female,40,Diploma,13,6,21,74,12,8.0,4,60,Rural,Data Analyst,60102,0 +51234,Female,54,Bachelors,0,72,35,70,77,8.0,5,19,Semi-Urban,ML Engineer,36820,0 +51235,Male,25,Bachelors,2,45,15,79,60,8.0,2,25,Urban,Data Analyst,58156,0 +51236,Female,47,High School,19,6,51,79,75,5.0,0,40,Rural,Software Engineer,60393,0 +51237,Male,32,Diploma,15,27,2,60,44,3.0,2,70,Urban,Software Engineer,130494,0 +51238,Male,55,PhD,11,48,68,29,34,8.0,4,3,Semi-Urban,ML Engineer,91399,0 +51239,Male,33,Bachelors,11,47,0,54,71,3.0,1,97,Semi-Urban,ML Engineer,86395,0 +51240,Male,34,PhD,6,14,30,36,96,6.0,5,39,Semi-Urban,Manager,24995,0 +51241,Male,24,Bachelors,16,96,66,85,57,4.0,6,91,Rural,HR Executive,20944,1 +51242,Male,45,Bachelors,0,5,25,76,86,4.0,3,4,Rural,Data Analyst,148184,0 +51243,Male,49,High School,0,22,36,74,58,1.0,0,49,Urban,ML Engineer,95376,0 +51244,Male,32,Bachelors,19,64,91,72,54,5.0,6,91,Urban,Manager,46780,1 +51245,Female,38,High School,12,96,75,35,22,7.0,2,1,Rural,Manager,126416,0 +51246,Male,56,Masters,1,98,51,6,79,3.0,3,13,Urban,HR Executive,108530,0 +51247,Male,58,Bachelors,1,61,45,45,10,7.0,3,53,Urban,ML Engineer,94303,0 +51248,Female,38,Bachelors,6,23,46,11,12,0.0,6,66,Urban,Manager,142113,0 +51249,Male,56,High School,8,92,18,55,67,7.0,7,27,Urban,Data Analyst,129099,0 +51250,Female,32,Masters,14,71,50,48,25,1.0,5,39,Rural,HR Executive,73019,0 +51251,Female,52,Bachelors,9,41,23,38,13,1.0,4,90,Urban,ML Engineer,121865,0 +51252,Other,38,Diploma,18,5,73,17,91,9.0,6,97,Rural,Software Engineer,143646,0 +51253,Male,50,High School,15,18,35,1,98,2.0,5,45,Urban,Data Analyst,103197,0 +51254,Male,45,Bachelors,13,23,90,82,71,3.0,4,77,Semi-Urban,Software Engineer,114353,1 +51255,Female,56,Diploma,2,81,72,93,99,2.0,7,30,Urban,ML Engineer,63525,1 +51256,Male,35,Masters,15,65,93,2,70,7.0,0,40,Semi-Urban,Data Analyst,121651,0 +51257,Male,52,Bachelors,3,60,69,22,98,2.0,3,23,Semi-Urban,HR Executive,21873,0 +51258,Male,45,Bachelors,2,35,13,97,37,1.0,2,43,Semi-Urban,Data Analyst,99951,0 +51259,Female,59,Bachelors,0,91,64,41,53,5.0,3,10,Rural,HR Executive,55859,0 +51260,Male,24,High School,12,77,64,44,36,3.0,4,15,Semi-Urban,Manager,100666,0 +51261,Female,49,Diploma,15,66,44,54,87,1.0,0,33,Rural,Data Analyst,36571,0 +51262,Male,34,Bachelors,2,42,21,95,79,5.0,3,41,Semi-Urban,Manager,136804,0 +51263,Female,54,High School,12,6,64,82,62,5.0,0,48,Urban,HR Executive,70046,0 +51264,Male,42,Diploma,0,69,48,83,94,0.0,5,20,Semi-Urban,Data Analyst,35842,0 +51265,Male,52,Bachelors,16,85,84,59,48,1.0,5,81,Urban,Software Engineer,83342,1 +51266,Male,49,Bachelors,3,82,96,29,1,4.0,4,54,Semi-Urban,HR Executive,115432,1 +51267,Male,27,High School,18,29,16,86,23,3.0,6,51,Urban,HR Executive,76470,0 +51268,Male,36,Diploma,14,37,24,35,17,4.0,1,41,Semi-Urban,Manager,92155,0 +51269,Male,39,Bachelors,4,77,35,54,17,4.0,0,81,Urban,Manager,120004,1 +51270,Other,40,Bachelors,17,97,25,50,5,2.0,1,75,Urban,ML Engineer,89474,1 +51271,Female,54,Masters,11,37,48,25,7,4.0,2,46,Rural,ML Engineer,147596,0 +51272,Female,55,Masters,9,52,15,89,62,2.0,6,0,Semi-Urban,HR Executive,136776,0 +51273,Other,24,Bachelors,13,62,57,23,8,1.0,0,17,Urban,Software Engineer,33784,0 +51274,Male,36,Masters,8,93,54,26,57,2.0,0,31,Urban,Manager,63514,0 +51275,Male,32,Bachelors,7,84,46,52,10,7.0,6,57,Urban,ML Engineer,80318,1 +51276,Female,58,Masters,18,20,47,49,25,5.0,4,96,Rural,Data Analyst,131048,0 +51277,Female,48,Diploma,1,29,19,54,91,0.0,6,12,Urban,Data Analyst,59603,0 +51278,Other,52,Bachelors,18,51,9,0,73,0.0,3,50,Urban,Manager,75530,0 +51279,Female,52,Bachelors,10,7,87,19,9,7.0,2,78,Urban,ML Engineer,131314,0 +51280,Female,53,Bachelors,2,98,92,61,77,7.0,3,85,Urban,Data Analyst,101545,1 +51281,Female,49,Diploma,5,74,38,20,85,3.0,2,83,Urban,Data Analyst,110277,0 +51282,Female,43,Bachelors,7,69,89,14,84,6.0,7,71,Rural,Software Engineer,49849,1 +51283,Male,44,High School,15,45,82,30,96,2.0,7,8,Semi-Urban,HR Executive,64500,0 +51284,Male,55,Masters,3,37,67,74,19,5.0,0,21,Rural,Data Analyst,52105,0 +51285,Female,47,Diploma,17,63,0,48,65,8.0,3,34,Rural,HR Executive,120367,0 +51286,Female,27,High School,9,39,4,83,58,5.0,6,7,Urban,HR Executive,36968,0 +51287,Male,44,Bachelors,8,26,65,39,22,5.0,7,26,Urban,Software Engineer,69093,0 +51288,Male,55,Bachelors,13,32,86,87,88,8.0,7,60,Semi-Urban,Software Engineer,134294,1 +51289,Female,53,Bachelors,5,34,8,34,90,2.0,1,55,Urban,ML Engineer,33021,0 +51290,Male,37,Masters,0,51,34,2,23,6.0,3,14,Semi-Urban,Data Analyst,76620,0 +51291,Male,31,Diploma,18,54,66,95,67,3.0,3,38,Urban,Data Analyst,69885,1 +51292,Male,26,Bachelors,4,56,53,48,67,7.0,1,1,Urban,Software Engineer,23450,0 +51293,Female,54,Masters,8,19,92,32,18,3.0,0,65,Urban,ML Engineer,61515,0 +51294,Male,44,Diploma,4,28,31,38,74,0.0,4,33,Rural,Data Analyst,96859,0 +51295,Male,55,Bachelors,5,8,13,82,79,3.0,6,62,Urban,Data Analyst,117316,0 +51296,Female,26,Diploma,11,79,41,79,69,9.0,5,45,Urban,Manager,63046,1 +51297,Male,58,Masters,1,59,37,70,86,7.0,7,28,Urban,HR Executive,129686,0 +51298,Male,30,Bachelors,13,48,22,18,81,2.0,3,36,Urban,Data Analyst,101936,0 +51299,Female,39,Masters,18,31,69,93,5,8.0,7,2,Rural,Software Engineer,110663,0 +51300,Female,25,Bachelors,8,16,42,72,46,1.0,1,75,Urban,Software Engineer,45001,0 +51301,Male,21,Diploma,17,26,32,21,32,0.0,1,60,Urban,Data Analyst,60645,0 +51302,Female,30,Bachelors,10,25,13,44,86,2.0,0,97,Rural,Data Analyst,33775,0 +51303,Female,46,High School,17,51,2,88,8,7.0,5,57,Rural,Software Engineer,129531,0 +51304,Female,29,High School,10,84,81,14,6,1.0,0,52,Semi-Urban,Data Analyst,144684,0 +51305,Male,49,Bachelors,5,32,3,44,63,1.0,1,90,Rural,Data Analyst,46489,0 +51306,Male,27,High School,7,17,37,46,15,1.0,3,31,Urban,Software Engineer,101811,0 +51307,Female,32,High School,14,49,73,82,60,1.0,5,9,Semi-Urban,HR Executive,102883,0 +51308,Male,28,Bachelors,10,95,92,37,93,6.0,7,88,Urban,HR Executive,38588,1 +51309,Male,39,Masters,19,33,39,95,90,8.0,0,95,Semi-Urban,ML Engineer,121798,1 +51310,Male,37,Masters,18,78,27,72,1,2.0,2,87,Semi-Urban,Data Analyst,87478,1 +51311,Male,39,Diploma,13,58,19,66,53,2.0,6,66,Urban,Data Analyst,111702,0 +51312,Male,39,High School,18,12,94,18,12,0.0,4,92,Semi-Urban,ML Engineer,67855,0 +51313,Male,53,Masters,19,45,70,69,85,3.0,5,70,Semi-Urban,Manager,26851,1 +51314,Female,47,High School,13,30,87,98,18,4.0,1,24,Urban,Software Engineer,46974,0 +51315,Male,43,Masters,9,19,79,40,67,9.0,7,10,Rural,Software Engineer,93254,0 +51316,Male,44,Bachelors,13,91,5,67,93,3.0,7,63,Urban,ML Engineer,85243,0 +51317,Female,30,Masters,11,1,13,58,83,9.0,1,80,Semi-Urban,ML Engineer,66138,0 +51318,Male,46,Bachelors,18,8,92,51,19,8.0,0,10,Urban,HR Executive,85479,0 +51319,Female,30,Bachelors,4,52,80,56,15,6.0,0,54,Semi-Urban,HR Executive,102564,1 +51320,Male,37,High School,6,36,77,1,88,4.0,0,41,Rural,HR Executive,136260,0 +51321,Male,28,Bachelors,14,8,55,23,47,4.0,1,64,Semi-Urban,Manager,72987,0 +51322,Male,45,Bachelors,15,50,24,94,28,7.0,4,71,Urban,ML Engineer,52134,1 +51323,Other,31,Bachelors,14,81,35,37,8,2.0,5,32,Urban,Manager,124571,0 +51324,Male,35,PhD,8,69,46,14,70,6.0,1,48,Urban,Software Engineer,26051,0 +51325,Female,23,High School,3,6,46,15,65,6.0,3,72,Urban,Manager,118320,0 +51326,Male,59,PhD,3,87,97,25,95,2.0,6,80,Urban,ML Engineer,121417,1 +51327,Male,24,Masters,14,69,5,6,47,9.0,2,26,Urban,HR Executive,135878,0 +51328,Male,42,Bachelors,14,55,28,95,27,6.0,6,48,Urban,Software Engineer,140877,0 +51329,Female,39,Bachelors,15,90,93,79,84,3.0,4,67,Urban,HR Executive,39563,1 +51330,Male,45,Bachelors,6,44,53,9,87,8.0,6,99,Urban,Software Engineer,77698,0 +51331,Male,25,Bachelors,17,0,0,5,78,4.0,1,14,Urban,Manager,124025,0 +51332,Female,38,Masters,7,7,54,29,41,3.0,1,98,Rural,Data Analyst,103818,0 +51333,Male,26,Diploma,0,30,55,10,1,8.0,1,80,Rural,HR Executive,49094,0 +51334,Male,37,Diploma,16,17,21,87,22,6.0,0,91,Rural,Data Analyst,51860,0 +51335,Male,38,Masters,5,85,72,46,12,4.0,2,88,Urban,Manager,118587,1 +51336,Other,58,Bachelors,14,56,86,93,53,2.0,6,13,Semi-Urban,HR Executive,62430,1 +51337,Male,29,Bachelors,6,67,93,90,85,9.0,5,97,Urban,ML Engineer,46222,1 +51338,Other,30,High School,12,11,42,21,88,0.0,1,76,Rural,HR Executive,145631,0 +51339,Male,56,Masters,4,35,90,43,30,5.0,3,0,Rural,Manager,32702,0 +51340,Male,59,Masters,10,60,45,75,19,3.0,6,6,Urban,HR Executive,49149,0 +51341,Female,47,Bachelors,18,9,37,5,20,1.0,1,44,Urban,Manager,45756,0 +51342,Male,47,Diploma,6,73,57,15,97,0.0,6,34,Semi-Urban,ML Engineer,139315,0 +51343,Male,57,Diploma,1,64,60,79,89,6.0,5,24,Urban,Software Engineer,32218,0 +51344,Male,51,Masters,7,24,28,84,18,5.0,7,85,Semi-Urban,Data Analyst,26540,0 +51345,Male,51,Masters,17,54,63,63,52,3.0,4,43,Urban,Data Analyst,143218,0 +51346,Female,44,Diploma,11,34,35,68,51,2.0,4,32,Urban,Software Engineer,127621,0 +51347,Female,45,Diploma,6,13,1,90,30,9.0,6,36,Urban,HR Executive,91429,0 +51348,Male,43,Bachelors,5,39,80,0,21,6.0,5,60,Urban,Manager,85405,0 +51349,Female,32,Bachelors,16,29,10,47,55,9.0,0,81,Semi-Urban,ML Engineer,142540,0 +51350,Male,33,Masters,8,41,69,2,20,6.0,4,70,Urban,Manager,115212,0 +51351,Male,36,Bachelors,12,8,82,96,11,3.0,1,25,Urban,Manager,131420,0 +51352,Male,39,Masters,10,23,79,94,26,6.0,6,69,Urban,ML Engineer,147729,1 +51353,Female,38,Bachelors,15,46,82,98,23,4.0,2,70,Semi-Urban,ML Engineer,118924,1 +51354,Male,24,Diploma,6,61,8,25,51,8.0,5,75,Semi-Urban,ML Engineer,127703,0 +51355,Male,21,Diploma,8,92,4,66,15,8.0,1,8,Urban,Data Analyst,106221,0 +51356,Female,43,Bachelors,19,9,33,52,80,7.0,4,50,Rural,HR Executive,55980,0 +51357,Female,21,Bachelors,4,5,45,11,51,2.0,5,98,Rural,HR Executive,37391,0 +51358,Female,41,Masters,0,80,80,31,22,5.0,5,54,Urban,HR Executive,104982,1 +51359,Male,54,Bachelors,16,67,27,32,94,2.0,3,7,Semi-Urban,Software Engineer,135774,0 +51360,Female,59,Bachelors,14,44,6,52,84,8.0,4,72,Urban,HR Executive,140078,0 +51361,Male,42,Bachelors,4,28,36,19,76,4.0,4,99,Urban,ML Engineer,44509,0 +51362,Female,36,High School,5,63,68,6,75,0.0,2,39,Urban,ML Engineer,33291,0 +51363,Male,38,Masters,13,30,16,70,37,9.0,4,11,Rural,Manager,66244,0 +51364,Male,46,High School,12,24,10,22,71,0.0,2,77,Semi-Urban,Manager,113801,0 +51365,Male,47,High School,13,98,17,88,8,6.0,1,39,Urban,ML Engineer,122061,1 +51366,Male,50,Masters,2,47,46,74,15,2.0,1,59,Rural,Software Engineer,73874,0 +51367,Male,44,High School,14,61,32,42,13,2.0,3,53,Urban,Manager,60382,0 +51368,Female,59,Masters,5,25,99,31,0,0.0,3,8,Semi-Urban,ML Engineer,79233,0 +51369,Female,45,Bachelors,6,87,53,5,86,5.0,3,16,Urban,Software Engineer,112641,0 +51370,Female,42,PhD,18,91,41,52,19,0.0,1,89,Urban,Data Analyst,31135,1 +51371,Male,46,Bachelors,18,86,38,94,30,9.0,7,31,Semi-Urban,Data Analyst,149717,1 +51372,Male,43,High School,0,47,89,45,37,1.0,6,4,Urban,Manager,79682,0 +51373,Other,46,Diploma,14,11,56,17,9,3.0,0,23,Semi-Urban,Manager,41673,0 +51374,Male,38,High School,6,8,95,17,36,8.0,1,42,Urban,ML Engineer,87790,0 +51375,Male,31,Masters,3,96,73,3,9,5.0,4,72,Urban,Data Analyst,36250,1 +51376,Male,56,Bachelors,16,11,68,47,41,0.0,2,28,Urban,HR Executive,78872,0 +51377,Other,37,Bachelors,17,90,45,73,86,3.0,2,22,Urban,HR Executive,127077,0 +51378,Male,52,Diploma,4,3,36,41,92,9.0,0,45,Urban,Software Engineer,142003,0 +51379,Male,59,Bachelors,3,97,75,25,7,0.0,6,73,Semi-Urban,ML Engineer,109901,1 +51380,Female,43,High School,0,47,16,39,26,3.0,4,39,Semi-Urban,Software Engineer,39365,0 +51381,Male,39,Diploma,12,4,10,66,23,6.0,5,31,Urban,Data Analyst,123633,0 +51382,Female,35,Bachelors,11,29,27,34,30,4.0,0,48,Urban,HR Executive,110892,0 +51383,Male,21,Bachelors,19,75,45,37,62,9.0,4,87,Urban,Software Engineer,132341,1 +51384,Male,23,Bachelors,7,55,62,70,49,7.0,4,91,Urban,ML Engineer,106920,1 +51385,Male,37,Diploma,3,33,23,52,62,3.0,2,41,Urban,Data Analyst,44677,0 +51386,Male,37,Masters,0,59,14,62,65,3.0,2,21,Urban,Software Engineer,76482,0 +51387,Female,49,Masters,0,50,68,29,31,1.0,7,63,Urban,ML Engineer,104355,0 +51388,Other,59,Bachelors,4,64,84,60,87,6.0,0,79,Semi-Urban,HR Executive,106611,1 +51389,Female,24,Diploma,7,66,76,84,17,1.0,4,28,Urban,Software Engineer,43322,1 +51390,Female,25,High School,16,43,67,29,28,0.0,5,36,Semi-Urban,ML Engineer,68356,0 +51391,Male,50,Bachelors,13,91,63,9,8,1.0,6,7,Rural,Manager,99518,0 +51392,Male,30,Diploma,1,85,7,80,36,8.0,2,38,Semi-Urban,HR Executive,28205,0 +51393,Female,58,Bachelors,18,92,8,9,92,3.0,6,51,Rural,Data Analyst,104844,0 +51394,Male,33,Bachelors,11,17,91,42,32,3.0,3,70,Urban,ML Engineer,89040,0 +51395,Male,23,Masters,0,34,85,69,27,5.0,6,33,Rural,HR Executive,146409,0 +51396,Female,29,Bachelors,10,95,53,84,5,6.0,0,44,Urban,Software Engineer,113808,1 +51397,Female,29,High School,17,53,33,84,85,1.0,6,68,Rural,ML Engineer,116398,0 +51398,Male,37,Bachelors,17,6,15,55,24,8.0,6,43,Rural,Software Engineer,107739,0 +51399,Female,55,High School,12,96,0,11,40,5.0,5,22,Urban,Manager,52896,0 +51400,Female,55,High School,17,32,74,96,72,5.0,5,36,Urban,ML Engineer,22869,0 +51401,Male,25,Masters,4,65,20,30,44,7.0,2,49,Semi-Urban,Data Analyst,136921,0 +51402,Female,28,Diploma,15,69,86,46,75,0.0,4,26,Urban,HR Executive,140505,0 +51403,Male,52,Masters,10,81,75,80,52,2.0,4,66,Urban,Data Analyst,51352,1 +51404,Other,37,Diploma,17,67,95,17,57,7.0,3,62,Rural,HR Executive,94870,1 +51405,Male,58,Bachelors,4,81,76,41,8,8.0,1,1,Rural,ML Engineer,24342,0 +51406,Female,30,Diploma,4,52,28,99,96,0.0,2,63,Semi-Urban,ML Engineer,48448,1 +51407,Female,58,High School,9,85,61,49,88,0.0,2,75,Semi-Urban,Software Engineer,44059,1 +51408,Female,59,Bachelors,5,7,85,72,7,0.0,1,21,Semi-Urban,Data Analyst,74480,0 +51409,Female,39,Bachelors,13,15,44,40,95,8.0,5,82,Urban,Software Engineer,61007,0 +51410,Male,55,Bachelors,12,6,73,98,56,9.0,1,43,Urban,HR Executive,60338,0 +51411,Female,39,Bachelors,18,87,63,22,50,9.0,5,73,Rural,Software Engineer,76914,1 +51412,Female,33,Bachelors,1,37,5,45,41,8.0,0,74,Urban,HR Executive,75373,0 +51413,Male,57,Masters,19,13,31,73,67,7.0,2,6,Urban,Data Analyst,45185,0 +51414,Male,37,Bachelors,0,48,0,77,24,8.0,3,36,Urban,Software Engineer,144862,0 +51415,Male,55,Bachelors,18,97,57,40,74,8.0,3,30,Rural,ML Engineer,103839,0 +51416,Female,24,Masters,0,7,37,29,54,2.0,2,53,Rural,Software Engineer,113675,0 +51417,Female,45,Bachelors,10,68,57,95,23,9.0,2,59,Urban,Data Analyst,66145,1 +51418,Female,45,Bachelors,15,42,70,10,26,9.0,6,17,Rural,ML Engineer,73337,0 +51419,Male,48,Bachelors,2,81,83,21,47,1.0,5,19,Urban,Data Analyst,43508,0 +51420,Male,51,Bachelors,16,16,16,58,90,1.0,5,60,Rural,ML Engineer,95602,0 +51421,Female,46,Bachelors,3,63,99,0,34,4.0,2,52,Urban,Software Engineer,39296,0 +51422,Female,48,Bachelors,13,72,66,33,46,0.0,6,70,Urban,Manager,22135,1 +51423,Male,36,Masters,0,97,15,45,33,4.0,2,10,Semi-Urban,Manager,31070,0 +51424,Female,49,Bachelors,6,10,78,68,49,3.0,2,14,Urban,Manager,136966,0 +51425,Male,40,Diploma,11,27,17,60,22,9.0,7,71,Rural,ML Engineer,81236,0 +51426,Male,30,Bachelors,8,86,69,39,72,5.0,1,6,Urban,Data Analyst,104876,0 +51427,Female,56,High School,8,93,49,21,39,9.0,5,0,Rural,ML Engineer,45471,0 +51428,Female,25,Masters,1,25,45,26,85,8.0,4,26,Urban,Manager,56066,0 +51429,Male,29,High School,0,29,8,78,81,0.0,1,40,Semi-Urban,HR Executive,98731,0 +51430,Female,42,High School,4,89,39,34,90,0.0,6,61,Urban,Software Engineer,98977,0 +51431,Male,47,Diploma,18,91,83,60,8,9.0,3,45,Semi-Urban,Manager,116904,1 +51432,Female,41,Masters,6,73,21,31,34,2.0,7,34,Urban,Data Analyst,81253,0 +51433,Male,49,Bachelors,13,88,39,69,56,3.0,1,4,Rural,HR Executive,87904,0 +51434,Female,25,Diploma,0,49,95,90,13,3.0,5,2,Semi-Urban,Manager,63611,0 +51435,Female,35,Diploma,7,80,81,39,75,6.0,4,52,Urban,Software Engineer,35265,1 +51436,Male,25,Masters,12,34,65,46,97,1.0,7,61,Semi-Urban,HR Executive,57522,0 +51437,Other,31,Masters,6,71,2,55,25,6.0,5,4,Urban,Software Engineer,100418,0 +51438,Male,24,Bachelors,11,86,45,82,63,9.0,4,39,Urban,Software Engineer,136269,1 +51439,Male,33,Bachelors,10,8,24,44,46,4.0,1,30,Urban,ML Engineer,100871,0 +51440,Female,29,Masters,5,39,11,33,17,8.0,3,55,Urban,Manager,118090,0 +51441,Female,44,Bachelors,9,38,56,1,4,7.0,2,83,Semi-Urban,ML Engineer,134934,0 +51442,Male,35,Masters,11,87,59,66,64,0.0,3,94,Semi-Urban,HR Executive,55164,1 +51443,Female,55,Bachelors,8,44,66,52,31,1.0,0,81,Urban,HR Executive,47377,1 +51444,Female,56,Bachelors,15,66,90,68,54,2.0,3,0,Urban,Software Engineer,148659,0 +51445,Male,59,Bachelors,1,64,28,0,56,5.0,4,81,Rural,Manager,32398,0 +51446,Female,58,Masters,17,72,35,15,69,4.0,4,1,Urban,Manager,95423,0 +51447,Male,54,Bachelors,19,6,12,25,46,9.0,7,44,Rural,Software Engineer,131045,0 +51448,Male,34,Bachelors,3,12,41,81,17,8.0,7,20,Semi-Urban,HR Executive,75483,0 +51449,Female,49,Diploma,17,51,2,49,49,5.0,3,87,Urban,ML Engineer,91199,0 +51450,Female,31,Bachelors,16,62,67,45,59,3.0,4,82,Rural,Manager,79056,1 +51451,Female,42,Bachelors,16,43,18,58,17,0.0,2,69,Urban,HR Executive,123812,0 +51452,Female,26,High School,11,20,89,54,94,4.0,0,38,Urban,Software Engineer,89326,0 +51453,Female,32,Masters,0,18,23,22,14,8.0,6,67,Urban,ML Engineer,34148,0 +51454,Male,52,Masters,17,32,70,89,42,1.0,1,82,Urban,ML Engineer,95831,1 +51455,Female,38,Masters,5,4,19,91,53,3.0,4,45,Urban,ML Engineer,70881,0 +51456,Male,29,PhD,10,75,51,35,93,9.0,6,48,Urban,HR Executive,92118,0 +51457,Male,37,PhD,11,0,22,69,1,9.0,6,90,Semi-Urban,ML Engineer,147494,0 +51458,Other,41,Masters,9,12,63,31,12,3.0,6,2,Rural,Data Analyst,112786,0 +51459,Female,51,Bachelors,9,88,88,88,58,9.0,3,92,Urban,ML Engineer,134380,1 +51460,Male,57,Bachelors,14,37,83,25,10,6.0,5,97,Urban,ML Engineer,75279,1 +51461,Female,44,Bachelors,8,73,63,9,39,1.0,7,62,Semi-Urban,ML Engineer,59138,0 +51462,Male,33,High School,0,34,99,86,15,3.0,0,24,Semi-Urban,Manager,143669,1 +51463,Male,33,Diploma,4,74,13,70,72,6.0,5,26,Urban,Software Engineer,139297,0 +51464,Female,44,Masters,18,2,35,34,23,2.0,5,42,Urban,Manager,109332,0 +51465,Female,53,High School,11,22,27,54,80,5.0,6,49,Semi-Urban,HR Executive,55025,0 +51466,Female,38,PhD,3,1,32,5,44,0.0,4,42,Urban,ML Engineer,105625,0 +51467,Male,44,Bachelors,4,87,62,95,48,5.0,7,46,Semi-Urban,Data Analyst,31739,1 +51468,Male,53,Bachelors,9,25,95,84,11,5.0,1,61,Semi-Urban,ML Engineer,105667,1 +51469,Female,49,Diploma,1,58,13,34,47,8.0,2,61,Semi-Urban,HR Executive,42207,0 +51470,Male,46,Bachelors,7,53,24,99,34,6.0,4,6,Semi-Urban,HR Executive,65958,0 +51471,Male,25,High School,17,28,46,75,90,2.0,1,37,Rural,Manager,43202,0 +51472,Other,48,Masters,16,93,16,78,26,4.0,3,71,Urban,ML Engineer,88499,1 +51473,Female,54,PhD,9,60,51,92,10,2.0,7,56,Urban,Manager,115011,1 +51474,Female,39,Diploma,3,75,39,49,37,6.0,7,47,Rural,Manager,68526,0 +51475,Male,24,Masters,12,68,73,97,43,3.0,3,98,Semi-Urban,ML Engineer,101156,1 +51476,Male,26,Masters,14,30,41,15,40,4.0,4,63,Urban,HR Executive,21901,0 +51477,Male,46,Bachelors,7,70,25,24,22,9.0,4,45,Rural,Manager,102195,0 +51478,Female,36,Masters,15,52,44,32,70,5.0,3,44,Rural,Software Engineer,28731,0 +51479,Female,23,Diploma,19,66,3,57,60,5.0,6,37,Rural,ML Engineer,38432,0 +51480,Female,47,Masters,16,33,57,20,9,0.0,4,97,Urban,Data Analyst,52331,0 +51481,Male,41,High School,12,59,35,48,17,7.0,6,11,Rural,Data Analyst,80094,0 +51482,Female,47,High School,7,29,1,78,50,4.0,3,56,Urban,Software Engineer,25931,0 +51483,Female,45,Diploma,12,35,73,4,33,6.0,2,97,Semi-Urban,Manager,117555,0 +51484,Female,47,Bachelors,10,51,98,95,16,8.0,4,33,Semi-Urban,HR Executive,110928,1 +51485,Other,26,Bachelors,0,19,61,61,71,6.0,6,43,Rural,HR Executive,62479,0 +51486,Female,58,Diploma,10,36,5,53,86,7.0,7,72,Rural,ML Engineer,126869,0 +51487,Male,46,PhD,9,92,36,77,58,4.0,0,6,Urban,ML Engineer,128721,0 +51488,Female,39,Bachelors,4,18,68,94,6,4.0,5,26,Semi-Urban,ML Engineer,102882,0 +51489,Male,46,PhD,3,28,95,80,90,8.0,1,96,Urban,HR Executive,58851,1 +51490,Other,38,Bachelors,13,27,69,11,63,2.0,5,78,Urban,HR Executive,100901,0 +51491,Female,57,High School,7,52,7,18,44,0.0,7,50,Rural,HR Executive,36628,0 +51492,Female,48,Bachelors,10,2,65,76,41,4.0,1,35,Urban,Software Engineer,63844,0 +51493,Male,25,Diploma,1,44,14,73,1,1.0,3,9,Urban,ML Engineer,37137,0 +51494,Male,35,Diploma,12,6,57,71,71,5.0,2,75,Urban,HR Executive,27157,0 +51495,Male,32,Bachelors,15,23,39,25,83,7.0,3,13,Urban,HR Executive,126230,0 +51496,Female,34,Masters,15,78,74,53,45,2.0,4,18,Urban,HR Executive,68051,0 +51497,Male,25,Masters,5,57,63,26,62,4.0,4,6,Urban,Manager,35091,0 +51498,Male,50,Diploma,11,15,13,20,14,8.0,4,30,Urban,Manager,42825,0 +51499,Female,50,High School,4,35,42,90,23,1.0,7,18,Rural,Data Analyst,87565,0 +51500,Male,50,PhD,17,39,44,57,11,8.0,3,85,Urban,Manager,80341,0 +51501,Female,35,Masters,11,21,23,72,10,3.0,2,98,Urban,Manager,41373,0 +51502,Male,24,Bachelors,1,42,46,92,23,6.0,1,38,Urban,HR Executive,95515,0 +51503,Male,29,High School,8,97,15,29,19,7.0,4,77,Semi-Urban,Data Analyst,77900,0 +51504,Female,28,Masters,10,10,55,15,0,4.0,6,43,Rural,Manager,100243,0 +51505,Female,45,Masters,11,3,19,53,97,7.0,2,12,Urban,Software Engineer,99253,0 +51506,Male,37,Masters,0,59,66,41,9,8.0,1,36,Urban,Software Engineer,141625,0 +51507,Male,37,Masters,10,7,58,34,34,4.0,5,34,Semi-Urban,ML Engineer,81966,0 +51508,Female,59,Diploma,16,76,75,5,54,2.0,5,43,Urban,Manager,142800,0 +51509,Male,50,Diploma,7,56,45,95,84,7.0,0,36,Urban,Data Analyst,133186,0 +51510,Male,44,High School,13,72,52,78,52,9.0,7,90,Semi-Urban,HR Executive,41519,1 +51511,Female,38,Bachelors,18,74,15,8,27,7.0,7,60,Rural,Data Analyst,97582,0 +51512,Female,54,Masters,15,48,45,62,68,3.0,1,69,Semi-Urban,Data Analyst,143253,0 +51513,Female,59,High School,3,93,71,80,42,4.0,6,67,Urban,Software Engineer,98373,1 +51514,Male,38,Masters,0,95,89,89,32,2.0,2,51,Urban,Data Analyst,84357,1 +51515,Male,30,Masters,12,3,48,69,87,3.0,1,17,Urban,HR Executive,147687,0 +51516,Female,32,Masters,0,2,14,51,68,8.0,6,24,Urban,Data Analyst,116867,0 +51517,Male,48,Diploma,3,73,61,69,17,6.0,4,85,Semi-Urban,Manager,21930,1 +51518,Male,51,Diploma,14,91,9,32,78,0.0,2,18,Urban,Data Analyst,22807,0 +51519,Female,58,Diploma,4,4,8,63,2,2.0,5,2,Semi-Urban,Manager,115550,0 +51520,Female,23,Bachelors,15,25,7,77,57,7.0,1,27,Rural,Software Engineer,26365,0 +51521,Male,48,Masters,9,42,15,83,30,1.0,4,1,Semi-Urban,ML Engineer,121681,0 +51522,Male,48,Bachelors,5,76,3,63,12,7.0,5,34,Urban,Software Engineer,126928,0 +51523,Male,21,Diploma,9,80,54,82,68,6.0,5,81,Semi-Urban,Data Analyst,37631,1 +51524,Female,40,Bachelors,8,66,85,18,49,7.0,4,39,Urban,Manager,111597,0 +51525,Female,29,PhD,7,82,7,56,44,7.0,5,37,Urban,Data Analyst,47807,0 +51526,Male,26,High School,14,40,28,88,57,4.0,3,56,Semi-Urban,HR Executive,90833,0 +51527,Male,23,Masters,17,97,77,4,3,5.0,0,54,Urban,HR Executive,78618,0 +51528,Female,45,Diploma,15,84,35,10,85,3.0,6,1,Urban,Software Engineer,99522,0 +51529,Female,54,Diploma,4,83,21,35,43,2.0,0,5,Urban,Data Analyst,44846,0 +51530,Female,52,Diploma,3,37,60,82,3,1.0,4,97,Rural,Manager,58627,1 +51531,Female,27,High School,7,81,22,92,16,9.0,6,72,Rural,ML Engineer,68707,1 +51532,Other,44,Diploma,10,64,94,37,35,6.0,3,67,Semi-Urban,Software Engineer,25700,1 +51533,Male,58,Masters,0,50,44,53,43,0.0,4,95,Urban,ML Engineer,29369,1 +51534,Male,28,Diploma,14,21,35,63,41,5.0,3,97,Urban,Data Analyst,100192,0 +51535,Male,48,Bachelors,0,91,87,12,41,7.0,3,20,Semi-Urban,Data Analyst,67868,0 +51536,Female,55,Diploma,3,4,95,85,97,5.0,4,71,Rural,Software Engineer,79067,1 +51537,Male,36,Masters,8,45,57,17,68,4.0,6,1,Rural,Software Engineer,123752,0 +51538,Male,53,Diploma,19,1,83,21,37,6.0,1,7,Urban,ML Engineer,104781,0 +51539,Male,25,Bachelors,4,37,2,96,58,9.0,7,47,Urban,HR Executive,108651,0 +51540,Male,50,High School,12,98,32,84,14,4.0,5,12,Rural,Manager,48164,0 +51541,Male,22,High School,7,14,49,73,55,2.0,6,95,Urban,Data Analyst,68477,0 +51542,Male,31,PhD,12,64,99,84,2,3.0,7,35,Rural,ML Engineer,94495,1 +51543,Other,47,Bachelors,10,61,5,90,66,2.0,7,24,Semi-Urban,HR Executive,43123,0 +51544,Male,51,Masters,5,98,0,52,91,2.0,1,99,Urban,Data Analyst,106054,1 +51545,Male,34,PhD,2,84,72,24,73,5.0,6,98,Urban,Data Analyst,30745,1 +51546,Male,43,Diploma,11,80,62,92,80,0.0,5,24,Rural,Data Analyst,92939,1 +51547,Female,58,Diploma,0,32,1,56,60,1.0,4,20,Urban,Data Analyst,72943,0 +51548,Male,28,Bachelors,13,23,11,90,54,8.0,1,79,Rural,Software Engineer,128389,0 +51549,Male,28,Masters,16,46,49,35,22,1.0,3,46,Semi-Urban,ML Engineer,21894,0 +51550,Female,58,Masters,10,69,46,61,13,5.0,5,20,Rural,ML Engineer,43988,0 +51551,Female,30,Masters,18,36,59,0,25,8.0,6,28,Semi-Urban,HR Executive,74283,0 +51552,Other,42,Bachelors,7,83,50,20,96,3.0,5,48,Urban,Software Engineer,25182,0 +51553,Male,37,High School,9,27,62,77,13,4.0,2,23,Semi-Urban,Data Analyst,129325,0 +51554,Male,33,Masters,14,8,7,84,59,8.0,1,98,Urban,Software Engineer,135311,0 +51555,Other,33,PhD,12,31,14,80,81,4.0,2,39,Urban,Software Engineer,134574,0 +51556,Female,51,Masters,8,4,87,58,92,1.0,4,56,Urban,HR Executive,132979,0 +51557,Female,45,Diploma,16,83,33,89,32,0.0,5,58,Rural,Manager,78749,1 +51558,Female,59,High School,5,50,44,12,92,6.0,7,35,Urban,HR Executive,43402,0 +51559,Female,46,High School,5,26,12,52,18,7.0,2,12,Rural,Software Engineer,98842,0 +51560,Female,36,Bachelors,2,21,88,71,55,2.0,7,64,Urban,HR Executive,126844,1 +51561,Male,55,Diploma,18,16,10,89,88,7.0,2,14,Rural,Software Engineer,42990,0 +51562,Female,31,Masters,4,48,69,76,60,8.0,3,55,Urban,ML Engineer,59772,1 +51563,Female,36,Bachelors,19,40,65,69,25,6.0,7,44,Urban,Software Engineer,113710,0 +51564,Male,45,Diploma,6,66,25,23,88,9.0,2,31,Semi-Urban,ML Engineer,33504,0 +51565,Male,57,High School,9,18,24,96,32,4.0,7,96,Urban,Software Engineer,91323,0 +51566,Male,43,Bachelors,5,45,57,59,72,3.0,2,67,Urban,HR Executive,30857,0 +51567,Female,40,Bachelors,17,23,38,82,34,8.0,1,70,Urban,ML Engineer,89391,0 +51568,Female,41,Masters,11,58,7,10,62,3.0,1,6,Urban,Software Engineer,136327,0 +51569,Female,47,Bachelors,16,19,27,9,84,7.0,5,18,Semi-Urban,Data Analyst,63017,0 +51570,Female,56,High School,11,57,33,18,79,6.0,5,53,Urban,Manager,56333,0 +51571,Male,53,Bachelors,1,76,6,37,3,1.0,2,0,Urban,HR Executive,37970,0 +51572,Female,21,PhD,10,92,12,59,87,9.0,0,18,Rural,HR Executive,120588,0 +51573,Male,43,Bachelors,9,93,50,59,0,2.0,1,37,Urban,Manager,47761,1 +51574,Female,41,High School,5,12,39,37,85,0.0,7,84,Semi-Urban,Data Analyst,96765,0 +51575,Male,36,Masters,5,27,40,17,45,7.0,5,27,Urban,HR Executive,97826,0 +51576,Male,36,Bachelors,7,8,77,39,87,2.0,6,64,Urban,Data Analyst,32281,0 +51577,Male,30,Bachelors,14,21,14,17,58,5.0,0,97,Urban,HR Executive,75204,0 +51578,Male,51,Bachelors,9,15,41,67,8,4.0,0,37,Urban,Manager,119702,0 +51579,Female,52,Bachelors,6,68,53,16,25,8.0,7,92,Urban,Manager,74282,0 +51580,Male,42,Bachelors,14,86,48,39,91,7.0,0,21,Urban,Data Analyst,115469,0 +51581,Male,40,Masters,3,96,54,63,11,4.0,7,0,Urban,HR Executive,81669,0 +51582,Other,25,Bachelors,6,64,63,36,43,7.0,4,0,Urban,HR Executive,26425,0 +51583,Male,42,Bachelors,8,82,67,42,29,6.0,3,78,Urban,Software Engineer,47330,1 +51584,Other,53,Bachelors,16,32,69,57,87,9.0,5,74,Urban,Manager,84872,0 +51585,Female,47,Bachelors,4,99,81,91,33,7.0,0,86,Urban,Software Engineer,56710,1 +51586,Male,21,High School,9,7,26,34,36,6.0,5,38,Urban,ML Engineer,93177,0 +51587,Male,39,PhD,11,33,7,80,67,6.0,2,48,Rural,Software Engineer,93115,0 +51588,Female,37,Masters,11,76,85,8,93,8.0,4,14,Urban,ML Engineer,118537,0 +51589,Female,50,Masters,15,50,3,60,35,2.0,7,65,Urban,Software Engineer,105253,0 +51590,Male,58,Masters,6,69,12,7,75,8.0,1,96,Rural,Manager,72477,0 +51591,Male,35,High School,19,18,17,83,89,4.0,2,97,Urban,Software Engineer,64986,0 +51592,Female,49,Bachelors,15,35,52,17,56,3.0,4,39,Urban,ML Engineer,130457,0 +51593,Male,33,Masters,2,12,93,14,47,7.0,4,72,Semi-Urban,HR Executive,135487,0 +51594,Male,58,Bachelors,7,86,4,4,66,0.0,0,32,Urban,HR Executive,86473,0 +51595,Female,59,High School,10,35,14,23,0,3.0,3,77,Urban,Software Engineer,120725,0 +51596,Female,33,Bachelors,15,21,37,75,44,2.0,5,76,Urban,ML Engineer,80422,0 +51597,Male,48,High School,8,3,34,1,59,0.0,4,26,Semi-Urban,HR Executive,45923,0 +51598,Male,46,High School,2,60,95,11,88,4.0,1,59,Urban,ML Engineer,45196,0 +51599,Female,25,Bachelors,5,61,30,85,83,0.0,1,44,Urban,ML Engineer,124005,0 +51600,Male,37,High School,16,12,91,65,76,9.0,0,54,Rural,Data Analyst,26492,0 +51601,Male,31,Bachelors,2,90,48,64,25,0.0,4,88,Urban,Data Analyst,92976,1 +51602,Female,43,High School,6,72,14,61,93,2.0,1,9,Semi-Urban,Data Analyst,55660,0 +51603,Other,50,Bachelors,17,65,88,90,17,2.0,5,92,Urban,Software Engineer,125735,1 +51604,Male,58,Masters,17,72,5,44,24,9.0,1,71,Semi-Urban,Software Engineer,110050,0 +51605,Female,27,Bachelors,0,33,74,63,45,8.0,1,77,Urban,Data Analyst,123001,1 +51606,Male,26,Bachelors,3,32,69,19,4,9.0,6,39,Rural,Manager,124668,0 +51607,Male,46,Diploma,6,63,89,35,30,9.0,3,39,Urban,Manager,56842,0 +51608,Male,57,High School,11,6,75,26,86,3.0,2,63,Urban,Data Analyst,34669,0 +51609,Male,25,High School,3,64,69,33,6,8.0,2,58,Urban,Manager,144392,0 +51610,Male,40,Diploma,12,73,53,30,62,9.0,4,61,Semi-Urban,Software Engineer,46908,0 +51611,Female,24,Bachelors,9,9,6,86,76,4.0,6,86,Semi-Urban,Software Engineer,90377,0 +51612,Male,54,Bachelors,13,34,5,81,60,7.0,1,54,Urban,HR Executive,61633,0 +51613,Male,40,PhD,5,78,95,24,31,9.0,7,13,Urban,Data Analyst,136532,0 +51614,Male,42,Diploma,3,23,89,42,80,8.0,4,79,Urban,HR Executive,36258,0 +51615,Female,55,Bachelors,0,41,63,51,55,6.0,2,61,Urban,HR Executive,68839,0 +51616,Male,36,Bachelors,17,24,69,49,20,2.0,3,55,Urban,Manager,135190,0 +51617,Male,35,Diploma,17,38,13,4,25,1.0,5,90,Urban,Manager,141637,0 +51618,Male,42,Bachelors,14,78,29,32,80,3.0,0,79,Urban,ML Engineer,132154,0 +51619,Male,25,Bachelors,4,72,55,85,78,9.0,4,0,Urban,Manager,133097,0 +51620,Male,44,Bachelors,1,57,96,41,32,0.0,2,15,Urban,Manager,96918,0 +51621,Male,38,Masters,14,64,19,79,48,1.0,5,59,Urban,HR Executive,80041,0 +51622,Female,31,High School,18,92,60,85,69,3.0,7,83,Semi-Urban,Manager,105914,1 +51623,Female,21,Bachelors,3,56,16,62,11,3.0,2,54,Rural,HR Executive,95853,0 +51624,Male,36,Bachelors,3,89,48,44,85,8.0,3,33,Urban,Data Analyst,144455,0 +51625,Male,57,Masters,18,38,4,90,85,9.0,1,37,Urban,Data Analyst,148855,0 +51626,Male,41,Bachelors,10,36,83,26,99,6.0,1,91,Urban,ML Engineer,33965,1 +51627,Other,45,Masters,7,59,21,73,31,4.0,0,0,Rural,Manager,50491,0 +51628,Male,30,Masters,5,52,86,57,95,5.0,2,69,Urban,Software Engineer,86583,1 +51629,Female,22,High School,13,56,83,61,62,0.0,3,66,Urban,Software Engineer,101203,1 +51630,Male,46,Bachelors,5,79,70,26,79,2.0,4,67,Urban,Software Engineer,82290,1 +51631,Male,28,Bachelors,4,21,26,48,66,6.0,2,92,Rural,ML Engineer,76751,0 +51632,Male,30,Diploma,2,72,28,29,36,8.0,2,99,Urban,ML Engineer,114512,0 +51633,Male,26,Bachelors,0,98,70,75,19,2.0,4,80,Rural,HR Executive,52845,1 +51634,Male,31,Bachelors,0,17,85,27,60,4.0,0,72,Semi-Urban,ML Engineer,117040,0 +51635,Male,33,Masters,11,15,94,58,36,3.0,4,55,Urban,Manager,80015,0 +51636,Male,39,Bachelors,17,94,67,77,32,0.0,6,34,Semi-Urban,Manager,107607,1 +51637,Female,49,Masters,10,83,66,30,19,7.0,0,89,Urban,Software Engineer,77364,1 +51638,Female,36,Diploma,17,49,4,10,27,6.0,0,72,Urban,Data Analyst,119218,0 +51639,Male,24,Masters,0,5,43,16,14,0.0,6,86,Rural,Data Analyst,27980,0 +51640,Male,34,High School,5,28,79,36,7,0.0,7,32,Rural,HR Executive,149595,0 +51641,Male,21,Bachelors,2,80,89,39,57,1.0,7,86,Urban,HR Executive,31126,1 +51642,Female,53,Diploma,2,23,48,51,11,4.0,2,54,Rural,ML Engineer,63886,0 +51643,Male,41,High School,15,76,8,57,22,2.0,3,98,Semi-Urban,ML Engineer,27867,1 +51644,Female,43,PhD,17,18,26,36,42,9.0,1,98,Rural,Data Analyst,129614,0 +51645,Female,23,High School,1,40,11,8,6,9.0,1,25,Urban,ML Engineer,136466,0 +51646,Male,30,Diploma,0,18,17,49,96,2.0,7,74,Semi-Urban,Software Engineer,94204,0 +51647,Female,36,Bachelors,18,18,24,12,3,3.0,4,51,Semi-Urban,ML Engineer,82965,0 +51648,Female,48,Bachelors,16,5,43,55,46,3.0,2,0,Urban,HR Executive,52343,0 +51649,Female,46,Diploma,0,52,78,80,11,5.0,2,77,Rural,HR Executive,124151,1 +51650,Female,38,Masters,7,43,85,95,5,5.0,3,2,Urban,Data Analyst,21289,0 +51651,Male,51,Masters,3,0,0,75,5,2.0,3,56,Urban,Data Analyst,48657,0 +51652,Female,26,Diploma,18,12,97,87,96,9.0,6,84,Urban,Data Analyst,148814,1 +51653,Female,29,Bachelors,10,73,59,26,34,8.0,2,35,Urban,Data Analyst,79935,0 +51654,Female,41,Masters,9,16,23,62,14,2.0,4,20,Urban,ML Engineer,136151,0 +51655,Female,57,Masters,10,24,49,71,59,3.0,7,17,Urban,Software Engineer,102399,0 +51656,Male,54,Bachelors,11,65,66,59,11,0.0,1,50,Semi-Urban,Software Engineer,20294,1 +51657,Male,36,Bachelors,14,86,63,80,99,6.0,7,25,Urban,HR Executive,26088,1 +51658,Female,42,Diploma,4,66,60,46,77,6.0,0,29,Rural,Data Analyst,144978,0 +51659,Male,37,Masters,15,73,57,38,34,9.0,0,44,Urban,Software Engineer,119579,0 +51660,Male,36,Bachelors,0,62,17,38,70,7.0,4,94,Semi-Urban,Software Engineer,99502,0 +51661,Male,48,Diploma,18,45,91,21,61,8.0,5,23,Urban,Software Engineer,34483,0 +51662,Male,38,Diploma,10,46,66,98,25,8.0,7,96,Rural,ML Engineer,108668,1 +51663,Male,42,High School,19,94,7,11,77,4.0,6,74,Rural,Manager,80175,0 +51664,Male,48,Bachelors,0,83,74,96,33,2.0,2,67,Urban,ML Engineer,91230,1 +51665,Male,55,Bachelors,11,14,35,52,80,0.0,3,35,Urban,ML Engineer,59414,0 +51666,Female,56,Bachelors,17,85,10,33,18,7.0,3,92,Urban,ML Engineer,141781,0 +51667,Male,22,Bachelors,12,86,25,61,66,2.0,2,91,Rural,Data Analyst,122185,1 +51668,Female,59,Masters,10,1,35,6,67,7.0,0,36,Urban,ML Engineer,28431,0 +51669,Male,43,High School,11,50,37,54,27,1.0,3,87,Urban,Data Analyst,49850,0 +51670,Female,58,Masters,17,92,77,85,31,9.0,7,42,Rural,Manager,144801,1 +51671,Female,49,Diploma,8,30,32,59,33,3.0,7,36,Rural,Software Engineer,59085,0 +51672,Male,54,Bachelors,15,19,42,1,12,3.0,6,28,Urban,Manager,37189,0 +51673,Male,55,Bachelors,1,5,42,45,96,0.0,6,93,Urban,Software Engineer,69852,0 +51674,Female,21,Diploma,18,44,26,62,36,1.0,5,82,Semi-Urban,HR Executive,76068,0 +51675,Female,36,Bachelors,19,97,25,76,25,5.0,5,95,Semi-Urban,Data Analyst,20680,1 +51676,Female,53,High School,7,85,48,80,91,4.0,6,37,Rural,Data Analyst,52557,1 +51677,Male,46,High School,12,40,96,67,49,0.0,1,64,Semi-Urban,HR Executive,124631,1 +51678,Other,37,Bachelors,15,61,92,66,66,4.0,0,97,Urban,Manager,95379,1 +51679,Male,26,PhD,2,7,98,42,92,9.0,2,29,Semi-Urban,Software Engineer,71735,0 +51680,Male,32,Bachelors,16,80,78,47,35,5.0,1,28,Urban,ML Engineer,114266,0 +51681,Male,58,Bachelors,11,57,45,89,36,1.0,3,7,Urban,Software Engineer,66169,0 +51682,Male,44,Bachelors,9,95,74,73,42,8.0,7,73,Urban,Software Engineer,106852,1 +51683,Female,30,Bachelors,1,99,69,26,8,8.0,6,60,Urban,ML Engineer,83431,1 +51684,Female,56,High School,5,85,60,81,21,5.0,0,85,Semi-Urban,ML Engineer,32299,1 +51685,Female,21,Masters,17,9,97,29,34,4.0,4,21,Rural,HR Executive,73711,0 +51686,Female,53,Diploma,5,17,52,35,64,1.0,7,13,Urban,HR Executive,102142,0 +51687,Male,51,Bachelors,14,62,22,58,90,4.0,6,48,Semi-Urban,Software Engineer,60581,0 +51688,Other,47,Bachelors,0,94,97,7,91,7.0,4,92,Rural,HR Executive,85540,1 +51689,Male,56,Diploma,15,67,97,12,10,9.0,7,46,Urban,ML Engineer,66706,0 +51690,Female,40,High School,6,61,28,60,88,1.0,6,65,Urban,ML Engineer,92271,0 +51691,Female,47,Bachelors,4,65,77,70,35,1.0,6,3,Semi-Urban,Data Analyst,96114,0 +51692,Male,59,Bachelors,15,10,50,69,3,3.0,3,6,Rural,Data Analyst,82781,0 +51693,Male,46,PhD,15,64,56,76,18,8.0,0,38,Rural,Data Analyst,99714,0 +51694,Male,58,Bachelors,12,10,80,18,0,1.0,2,57,Semi-Urban,HR Executive,117059,0 +51695,Female,50,PhD,6,74,78,61,99,4.0,4,61,Urban,Data Analyst,147786,1 +51696,Female,32,Masters,1,96,36,7,12,3.0,7,31,Urban,Data Analyst,123660,0 +51697,Female,51,Bachelors,16,84,65,50,30,9.0,3,94,Urban,Software Engineer,121731,1 +51698,Male,49,Bachelors,0,82,98,79,76,9.0,7,33,Urban,ML Engineer,21802,1 +51699,Male,32,Diploma,2,69,86,94,25,9.0,6,22,Urban,HR Executive,79668,1 +51700,Other,44,Bachelors,1,34,66,67,63,7.0,7,64,Urban,Data Analyst,94506,0 +51701,Male,42,Bachelors,8,15,43,76,61,7.0,6,8,Urban,ML Engineer,41738,0 +51702,Female,22,Masters,10,31,8,32,74,8.0,3,20,Semi-Urban,Software Engineer,31146,0 +51703,Female,56,Masters,6,49,30,32,84,4.0,1,46,Semi-Urban,Software Engineer,133752,0 +51704,Female,40,Bachelors,13,14,11,25,72,4.0,3,44,Rural,Manager,94562,0 +51705,Male,37,Masters,3,17,44,37,80,7.0,2,43,Urban,Software Engineer,27850,0 +51706,Male,30,Bachelors,17,98,36,39,16,6.0,5,11,Urban,Data Analyst,103098,0 +51707,Female,52,Diploma,15,94,96,17,11,9.0,5,97,Urban,ML Engineer,106692,1 +51708,Male,34,Masters,8,69,80,55,96,5.0,0,90,Urban,Software Engineer,108016,1 +51709,Female,30,Diploma,13,60,83,96,24,9.0,2,91,Semi-Urban,Software Engineer,141717,1 +51710,Male,59,High School,7,22,91,84,79,8.0,0,27,Urban,HR Executive,135284,0 +51711,Female,39,High School,15,32,89,25,44,8.0,3,36,Urban,Manager,28434,0 +51712,Other,26,Bachelors,1,19,99,74,9,9.0,1,34,Urban,Software Engineer,81149,0 +51713,Other,56,High School,13,27,42,39,32,6.0,6,68,Rural,Data Analyst,23419,0 +51714,Male,57,Masters,18,10,59,18,7,3.0,0,30,Urban,Manager,53817,0 +51715,Male,59,Masters,19,27,5,49,10,3.0,5,39,Urban,Software Engineer,146612,0 +51716,Male,30,Masters,18,20,91,5,58,5.0,7,53,Semi-Urban,HR Executive,135080,0 +51717,Male,42,Bachelors,10,96,14,77,79,2.0,6,29,Urban,Data Analyst,127123,0 +51718,Male,48,Masters,15,8,58,77,80,2.0,4,29,Semi-Urban,Software Engineer,63133,0 +51719,Female,37,Bachelors,1,41,52,73,28,6.0,7,36,Urban,Manager,105930,0 +51720,Male,37,Masters,5,55,59,95,91,6.0,1,3,Urban,ML Engineer,133782,0 +51721,Male,30,Bachelors,11,29,88,96,67,1.0,4,16,Urban,ML Engineer,43535,0 +51722,Male,55,Diploma,18,63,8,0,37,1.0,2,32,Semi-Urban,Manager,31734,0 +51723,Male,49,PhD,18,30,19,1,92,2.0,6,23,Rural,Data Analyst,58748,0 +51724,Male,34,PhD,16,52,26,25,20,6.0,5,74,Urban,Manager,100345,0 +51725,Male,39,Bachelors,4,51,19,86,76,1.0,4,24,Urban,Data Analyst,109525,0 +51726,Female,48,Bachelors,2,50,27,94,26,9.0,7,83,Urban,Manager,110217,1 +51727,Female,21,Bachelors,11,72,45,44,34,3.0,2,58,Urban,Manager,103444,0 +51728,Male,52,Bachelors,0,50,57,75,76,2.0,5,65,Urban,Software Engineer,145726,1 +51729,Male,43,Masters,14,86,12,28,47,0.0,2,95,Urban,HR Executive,104076,0 +51730,Male,54,High School,6,10,62,30,41,6.0,6,91,Urban,ML Engineer,25519,0 +51731,Male,35,Bachelors,5,0,28,59,15,3.0,7,86,Rural,HR Executive,113395,0 +51732,Male,37,Bachelors,14,6,58,32,93,4.0,6,55,Urban,HR Executive,83786,0 +51733,Female,24,Masters,19,61,89,86,42,2.0,6,47,Urban,Manager,66842,1 +51734,Male,55,Diploma,9,53,16,17,63,0.0,7,15,Urban,ML Engineer,85352,0 +51735,Male,48,Diploma,7,73,93,60,97,8.0,0,31,Rural,Data Analyst,123980,1 +51736,Male,29,Masters,16,83,23,92,65,3.0,7,88,Urban,HR Executive,113920,1 +51737,Male,38,Masters,12,48,30,34,43,2.0,6,38,Urban,Software Engineer,146345,0 +51738,Male,49,Bachelors,16,50,25,55,11,3.0,0,43,Urban,Manager,101160,0 +51739,Male,33,Masters,13,51,27,22,20,3.0,0,29,Urban,ML Engineer,84841,0 +51740,Male,40,Masters,3,42,41,42,12,8.0,3,72,Rural,Software Engineer,22349,0 +51741,Female,39,Diploma,18,39,31,6,30,1.0,5,23,Urban,Software Engineer,135724,0 +51742,Female,39,High School,1,85,17,17,4,2.0,4,99,Urban,Software Engineer,103004,0 +51743,Female,53,Masters,17,86,60,96,75,1.0,7,47,Urban,ML Engineer,81802,1 +51744,Male,35,Masters,5,52,30,25,82,6.0,7,46,Semi-Urban,ML Engineer,134560,0 +51745,Male,54,High School,15,13,80,64,40,0.0,4,82,Urban,ML Engineer,132165,1 +51746,Female,56,Masters,2,25,21,35,24,4.0,2,81,Urban,Software Engineer,38083,0 +51747,Male,38,Masters,18,76,25,14,96,1.0,4,5,Semi-Urban,ML Engineer,56935,0 +51748,Male,36,Bachelors,0,19,35,44,97,5.0,6,6,Urban,HR Executive,90594,0 +51749,Female,35,Masters,15,73,67,12,45,4.0,1,24,Urban,Data Analyst,48571,0 +51750,Male,24,Bachelors,13,31,67,95,60,8.0,5,90,Urban,ML Engineer,118416,1 +51751,Male,48,Diploma,14,33,38,81,15,8.0,5,37,Semi-Urban,ML Engineer,56863,0 +51752,Male,40,Bachelors,3,63,14,95,55,2.0,4,57,Urban,Manager,138551,0 +51753,Female,25,High School,15,97,78,99,35,2.0,3,9,Semi-Urban,HR Executive,35907,1 +51754,Female,58,High School,10,93,47,10,39,9.0,0,19,Urban,HR Executive,38200,0 +51755,Female,30,Bachelors,19,31,33,16,27,3.0,5,78,Rural,Data Analyst,148850,0 +51756,Male,37,PhD,15,41,85,86,39,5.0,3,34,Urban,ML Engineer,57851,1 +51757,Female,35,Bachelors,9,65,79,37,53,2.0,2,17,Semi-Urban,Software Engineer,116437,0 +51758,Other,30,Diploma,6,45,30,40,81,0.0,0,6,Urban,Manager,66070,0 +51759,Female,32,Masters,9,98,20,60,33,0.0,6,86,Rural,HR Executive,79779,1 +51760,Male,58,Bachelors,7,53,88,42,83,4.0,4,55,Urban,Data Analyst,139547,1 +51761,Female,21,Masters,18,26,91,96,26,2.0,6,30,Urban,HR Executive,130020,1 +51762,Female,56,Bachelors,0,71,64,32,34,8.0,5,50,Rural,HR Executive,76952,0 +51763,Female,31,Masters,6,70,8,98,75,8.0,0,14,Urban,Manager,71467,0 +51764,Female,24,Bachelors,7,42,10,24,54,0.0,5,97,Urban,HR Executive,111131,0 +51765,Female,38,Bachelors,6,59,18,92,32,0.0,2,21,Rural,ML Engineer,100329,0 +51766,Female,41,PhD,9,20,49,66,90,9.0,4,28,Urban,HR Executive,103498,0 +51767,Male,21,Diploma,18,58,44,5,7,2.0,7,60,Urban,Software Engineer,23616,0 +51768,Male,33,High School,19,82,21,75,74,3.0,4,1,Semi-Urban,ML Engineer,117710,0 +51769,Male,46,Diploma,3,9,61,52,11,8.0,1,11,Semi-Urban,Manager,82085,0 +51770,Male,38,Bachelors,9,72,30,24,82,3.0,1,77,Urban,Software Engineer,63036,0 +51771,Female,23,Diploma,12,24,0,33,3,1.0,2,6,Semi-Urban,ML Engineer,129352,0 +51772,Male,42,Diploma,6,78,65,65,92,8.0,5,90,Semi-Urban,Data Analyst,99796,1 +51773,Male,26,High School,15,16,22,74,36,5.0,5,76,Semi-Urban,Software Engineer,77012,0 +51774,Male,21,Bachelors,13,90,43,81,82,6.0,1,62,Urban,Data Analyst,112458,1 +51775,Male,40,Diploma,13,57,14,64,1,8.0,7,86,Urban,Data Analyst,117507,0 +51776,Female,50,Diploma,6,50,74,85,8,9.0,4,86,Urban,Data Analyst,127204,1 +51777,Female,29,Masters,8,7,74,64,65,2.0,3,17,Rural,Software Engineer,122318,0 +51778,Female,35,Bachelors,17,35,40,62,14,1.0,4,34,Urban,Data Analyst,42412,0 +51779,Male,36,High School,4,55,15,87,74,4.0,3,74,Rural,ML Engineer,87883,0 +51780,Male,33,Bachelors,3,51,19,69,18,8.0,5,61,Urban,Software Engineer,24344,0 +51781,Female,21,High School,7,26,70,88,24,6.0,0,69,Semi-Urban,ML Engineer,122697,1 +51782,Male,24,Diploma,8,16,81,65,46,0.0,0,15,Urban,Software Engineer,96264,0 +51783,Female,39,High School,18,61,73,68,49,1.0,6,57,Urban,ML Engineer,36788,1 +51784,Female,29,Bachelors,19,25,73,30,52,2.0,6,91,Urban,Manager,103223,0 +51785,Male,49,Bachelors,6,71,1,85,58,6.0,2,59,Semi-Urban,Data Analyst,123031,0 +51786,Male,37,Masters,11,19,81,83,56,3.0,6,31,Urban,HR Executive,118819,0 +51787,Male,55,High School,18,2,71,85,30,8.0,6,15,Urban,Data Analyst,132350,0 +51788,Female,37,Bachelors,4,33,80,77,90,4.0,7,23,Urban,ML Engineer,84036,0 +51789,Male,29,High School,5,35,13,27,56,6.0,5,8,Urban,Manager,105699,0 +51790,Male,46,High School,10,19,37,86,42,3.0,7,77,Urban,ML Engineer,34737,0 +51791,Male,44,Bachelors,9,54,37,24,12,1.0,1,24,Semi-Urban,Software Engineer,128165,0 +51792,Male,33,Bachelors,16,37,11,79,79,3.0,1,75,Urban,HR Executive,111878,0 +51793,Female,29,Bachelors,2,72,79,72,81,8.0,5,53,Semi-Urban,ML Engineer,107608,1 +51794,Male,30,Bachelors,3,13,38,49,27,3.0,7,74,Urban,Manager,102023,0 +51795,Male,35,Bachelors,2,34,85,73,0,5.0,5,15,Urban,Data Analyst,21315,0 +51796,Male,59,High School,19,69,1,60,16,9.0,4,49,Urban,Data Analyst,140889,0 +51797,Male,58,Masters,9,27,43,80,39,2.0,4,1,Semi-Urban,HR Executive,141879,0 +51798,Male,22,Diploma,18,24,46,86,32,9.0,7,18,Rural,Software Engineer,39033,0 +51799,Male,55,Diploma,19,1,57,47,70,9.0,3,68,Semi-Urban,HR Executive,61912,0 +51800,Female,46,Masters,5,83,25,52,31,0.0,4,28,Urban,Manager,71098,0 +51801,Male,33,Diploma,18,74,69,25,14,8.0,7,91,Semi-Urban,Data Analyst,71609,1 +51802,Male,57,High School,14,61,32,53,66,6.0,3,33,Semi-Urban,HR Executive,97674,0 +51803,Male,25,High School,11,93,36,29,80,4.0,3,58,Urban,HR Executive,68545,0 +51804,Male,55,Diploma,15,30,30,76,9,1.0,4,57,Semi-Urban,Data Analyst,73204,0 +51805,Female,51,Masters,11,9,59,0,36,5.0,3,11,Rural,Software Engineer,114789,0 +51806,Female,43,Masters,15,4,74,40,58,8.0,0,93,Rural,HR Executive,55293,0 +51807,Male,45,Bachelors,0,2,80,0,24,3.0,6,44,Rural,ML Engineer,118856,0 +51808,Male,55,High School,7,80,33,80,9,6.0,2,61,Urban,Manager,107745,1 +51809,Male,55,Masters,8,66,58,94,54,1.0,6,88,Urban,HR Executive,85274,1 +51810,Male,58,Bachelors,19,85,36,5,4,4.0,3,11,Rural,ML Engineer,25965,0 +51811,Female,50,Bachelors,10,84,87,66,46,1.0,0,13,Semi-Urban,HR Executive,131532,1 +51812,Female,32,Bachelors,1,72,23,35,3,7.0,1,82,Urban,Manager,85570,0 +51813,Male,53,Bachelors,19,13,52,9,34,2.0,4,41,Rural,Software Engineer,61444,0 +51814,Female,33,Bachelors,18,15,38,81,8,2.0,1,73,Semi-Urban,Manager,131760,0 +51815,Female,41,Masters,14,19,20,99,14,4.0,0,92,Urban,ML Engineer,98027,0 +51816,Female,40,Bachelors,18,61,70,85,63,6.0,3,57,Urban,Data Analyst,20805,1 +51817,Male,49,Masters,9,34,31,78,99,6.0,2,95,Urban,ML Engineer,44180,1 +51818,Male,49,Diploma,9,4,35,41,1,5.0,3,93,Urban,ML Engineer,62381,0 +51819,Male,37,Diploma,18,43,48,82,29,5.0,4,24,Semi-Urban,Software Engineer,50302,0 +51820,Male,44,Masters,10,91,28,43,73,8.0,0,29,Urban,ML Engineer,23589,0 +51821,Male,55,Masters,4,10,93,29,91,7.0,4,80,Urban,Manager,66733,0 +51822,Female,53,Masters,8,99,28,12,63,4.0,7,25,Semi-Urban,ML Engineer,103760,0 +51823,Male,29,High School,17,23,29,68,2,2.0,3,46,Rural,Manager,119397,0 +51824,Female,41,Bachelors,11,54,17,39,4,0.0,7,35,Urban,HR Executive,85973,0 +51825,Female,26,Diploma,7,54,50,54,90,9.0,0,25,Urban,Manager,78003,0 +51826,Male,56,Bachelors,2,34,25,49,61,2.0,7,7,Semi-Urban,ML Engineer,32769,0 +51827,Male,50,High School,11,75,45,48,68,7.0,0,32,Urban,Data Analyst,145893,0 +51828,Female,38,Bachelors,16,31,22,60,49,2.0,5,69,Urban,ML Engineer,106181,0 +51829,Female,30,Bachelors,15,10,8,85,89,5.0,6,93,Rural,Manager,81126,0 +51830,Other,37,Bachelors,1,47,24,91,66,6.0,2,95,Semi-Urban,ML Engineer,44306,1 +51831,Female,44,Bachelors,18,84,72,12,57,3.0,1,98,Semi-Urban,HR Executive,61197,1 +51832,Female,55,Bachelors,16,24,92,48,64,9.0,7,63,Rural,HR Executive,123521,0 +51833,Female,40,Bachelors,9,90,17,72,6,8.0,7,99,Urban,Manager,112815,1 +51834,Male,34,Masters,15,9,74,90,55,6.0,0,95,Semi-Urban,ML Engineer,40770,1 +51835,Female,24,Diploma,14,27,24,5,81,6.0,2,24,Semi-Urban,Manager,93918,0 +51836,Female,35,Diploma,12,62,24,71,74,4.0,7,35,Urban,Software Engineer,50357,0 +51837,Male,55,Masters,10,81,32,23,18,1.0,4,87,Urban,Data Analyst,136429,0 +51838,Male,49,High School,3,94,19,89,18,0.0,3,48,Semi-Urban,Software Engineer,103930,1 +51839,Male,25,Bachelors,19,91,12,8,32,2.0,1,38,Urban,Manager,87140,0 +51840,Other,43,Bachelors,4,19,22,14,38,3.0,0,59,Semi-Urban,Data Analyst,97013,0 +51841,Male,39,PhD,15,61,42,68,17,0.0,3,5,Urban,ML Engineer,122738,0 +51842,Female,23,Bachelors,1,81,2,29,24,2.0,6,42,Urban,Software Engineer,78713,0 +51843,Female,42,Diploma,9,27,40,2,26,7.0,1,23,Rural,HR Executive,79265,0 +51844,Female,35,Diploma,5,25,40,41,65,1.0,4,64,Urban,Data Analyst,114784,0 +51845,Male,28,Masters,13,39,51,81,47,1.0,1,51,Semi-Urban,Data Analyst,122793,0 +51846,Female,36,Bachelors,16,58,36,79,67,8.0,0,95,Urban,Software Engineer,27276,1 +51847,Male,58,Masters,1,82,98,57,3,5.0,5,75,Urban,Manager,106757,1 +51848,Male,50,Bachelors,12,3,11,35,51,2.0,6,28,Urban,ML Engineer,76263,0 +51849,Male,23,Masters,5,97,35,36,57,5.0,1,64,Rural,Manager,109804,0 +51850,Male,45,Diploma,2,71,31,64,78,0.0,2,67,Urban,ML Engineer,63742,0 +51851,Male,35,Masters,10,87,62,77,58,6.0,7,25,Semi-Urban,Data Analyst,54990,1 +51852,Male,37,Bachelors,16,64,40,29,24,0.0,1,20,Urban,ML Engineer,136682,0 +51853,Female,28,Bachelors,6,34,21,96,17,0.0,7,12,Urban,Data Analyst,98502,0 +51854,Male,32,Masters,2,53,56,33,23,4.0,0,74,Urban,Data Analyst,66556,0 +51855,Female,46,High School,2,38,23,68,14,5.0,2,48,Urban,Software Engineer,68627,0 +51856,Male,34,Bachelors,13,69,70,56,77,5.0,7,51,Rural,Software Engineer,73721,1 +51857,Male,27,Bachelors,11,90,96,72,23,5.0,6,46,Urban,Data Analyst,101381,1 +51858,Male,45,High School,2,64,22,94,32,7.0,5,9,Urban,Software Engineer,141529,0 +51859,Male,50,High School,8,41,3,79,95,9.0,3,15,Urban,ML Engineer,111624,0 +51860,Male,38,High School,17,28,62,8,18,2.0,0,96,Rural,HR Executive,128106,0 +51861,Male,30,Diploma,4,59,5,69,1,6.0,4,50,Urban,Manager,103037,0 +51862,Male,50,Masters,4,40,41,84,8,9.0,1,86,Urban,HR Executive,39256,1 +51863,Male,41,Bachelors,11,46,32,26,43,6.0,1,72,Urban,HR Executive,78138,0 +51864,Male,22,Diploma,2,27,82,95,61,2.0,6,85,Rural,Data Analyst,97029,1 +51865,Male,55,Diploma,10,63,46,35,7,7.0,7,4,Urban,Data Analyst,80651,0 +51866,Female,48,Masters,5,96,27,91,53,2.0,7,98,Semi-Urban,ML Engineer,122552,1 +51867,Male,37,High School,19,38,53,72,99,6.0,4,47,Rural,HR Executive,86771,0 +51868,Male,54,Masters,8,9,57,48,93,4.0,2,39,Semi-Urban,Manager,134886,0 +51869,Male,24,Bachelors,10,75,38,12,47,4.0,4,26,Urban,ML Engineer,58082,0 +51870,Female,53,Diploma,3,39,77,6,61,0.0,0,36,Rural,Manager,118721,0 +51871,Male,44,High School,16,42,4,59,13,9.0,6,57,Semi-Urban,Manager,91932,0 +51872,Male,51,Diploma,11,70,20,74,45,5.0,5,59,Semi-Urban,HR Executive,27111,0 +51873,Female,29,Diploma,13,49,80,84,77,2.0,2,0,Urban,ML Engineer,103008,0 +51874,Male,54,Masters,12,31,47,47,74,9.0,7,48,Rural,HR Executive,62911,0 +51875,Male,41,Bachelors,15,98,78,88,78,5.0,1,1,Urban,Manager,63583,1 +51876,Male,25,Bachelors,5,82,70,41,46,8.0,6,25,Urban,ML Engineer,29767,0 +51877,Other,30,Masters,16,49,77,59,39,4.0,7,47,Urban,ML Engineer,47484,0 +51878,Male,52,Bachelors,3,83,12,89,37,5.0,3,21,Semi-Urban,Manager,48587,0 +51879,Male,25,Bachelors,4,8,83,53,12,0.0,6,80,Semi-Urban,Software Engineer,36272,0 +51880,Male,28,Bachelors,15,90,30,48,0,4.0,2,10,Urban,HR Executive,32033,0 +51881,Female,25,Diploma,11,79,89,62,7,4.0,2,9,Urban,Data Analyst,121341,0 +51882,Male,22,High School,4,26,80,87,8,8.0,4,41,Urban,Data Analyst,136743,0 +51883,Male,56,Masters,2,15,66,55,56,7.0,2,95,Urban,Data Analyst,108984,0 +51884,Male,52,Bachelors,1,61,50,65,11,1.0,6,26,Urban,HR Executive,122362,0 +51885,Male,42,Diploma,1,88,9,88,46,5.0,5,50,Urban,ML Engineer,76713,1 +51886,Other,33,Diploma,3,79,34,83,74,9.0,4,68,Urban,Data Analyst,47982,1 +51887,Male,26,Masters,1,11,15,76,25,7.0,3,7,Semi-Urban,Manager,138669,0 +51888,Male,52,Masters,0,85,12,88,54,1.0,3,91,Rural,Manager,119415,1 +51889,Male,48,Bachelors,0,1,10,86,21,2.0,0,11,Urban,Data Analyst,115129,0 +51890,Female,52,High School,5,57,53,26,65,5.0,3,40,Urban,Data Analyst,85229,0 +51891,Male,51,Bachelors,13,0,6,84,46,3.0,7,92,Rural,HR Executive,99221,0 +51892,Female,50,Diploma,10,86,2,92,3,5.0,6,74,Urban,HR Executive,91695,1 +51893,Male,42,Diploma,3,28,52,85,83,8.0,4,29,Urban,HR Executive,25451,0 +51894,Male,25,High School,19,75,96,13,43,3.0,3,17,Urban,ML Engineer,144657,0 +51895,Male,40,Masters,19,94,59,0,95,5.0,3,11,Semi-Urban,Manager,96099,0 +51896,Male,33,Bachelors,18,6,74,86,37,8.0,2,97,Rural,HR Executive,89720,1 +51897,Male,23,Bachelors,15,90,71,65,90,3.0,7,3,Urban,Software Engineer,50376,0 +51898,Male,30,Masters,16,72,89,26,5,0.0,7,60,Rural,HR Executive,119701,1 +51899,Female,39,PhD,15,92,98,40,82,6.0,7,5,Urban,Software Engineer,119444,0 +51900,Male,37,High School,13,68,54,16,91,1.0,5,42,Urban,ML Engineer,118587,0 +51901,Female,57,PhD,9,25,80,19,31,1.0,2,54,Rural,Software Engineer,90663,0 +51902,Male,49,Bachelors,2,36,28,7,53,4.0,2,71,Urban,Software Engineer,88943,0 +51903,Male,23,High School,2,99,1,21,13,1.0,5,40,Urban,Data Analyst,47967,0 +51904,Male,58,Bachelors,2,56,35,65,41,0.0,1,91,Urban,Manager,24112,1 +51905,Male,35,High School,18,97,65,37,4,1.0,5,90,Semi-Urban,Data Analyst,141573,1 +51906,Male,57,Masters,18,22,91,15,46,2.0,2,48,Urban,HR Executive,138343,0 +51907,Male,28,Bachelors,2,45,31,88,79,5.0,3,20,Urban,Manager,138967,0 +51908,Female,38,Bachelors,1,61,93,45,76,0.0,3,73,Semi-Urban,Manager,22017,1 +51909,Male,49,Bachelors,10,69,50,64,92,0.0,7,48,Semi-Urban,Software Engineer,115029,0 +51910,Male,56,PhD,19,23,5,85,37,0.0,3,4,Semi-Urban,Software Engineer,37886,0 +51911,Female,24,Bachelors,17,92,31,77,19,9.0,7,96,Urban,Manager,148843,1 +51912,Male,27,High School,15,44,43,74,41,4.0,4,62,Urban,ML Engineer,117729,0 +51913,Female,57,Bachelors,10,36,14,78,40,5.0,0,35,Rural,Software Engineer,72796,0 +51914,Male,55,Masters,3,75,77,0,37,2.0,6,46,Urban,Data Analyst,134735,0 +51915,Male,32,Bachelors,1,87,15,76,59,0.0,2,2,Urban,Data Analyst,80196,0 +51916,Female,48,Diploma,18,45,88,72,84,1.0,3,34,Rural,ML Engineer,83100,0 +51917,Male,48,Diploma,19,74,92,26,4,5.0,0,50,Rural,Software Engineer,110706,1 +51918,Female,39,Diploma,0,58,90,32,30,9.0,4,11,Urban,ML Engineer,129052,0 +51919,Female,31,High School,12,62,35,11,62,5.0,5,84,Semi-Urban,HR Executive,140795,0 +51920,Female,46,Bachelors,10,14,46,72,31,0.0,1,89,Rural,Data Analyst,41550,0 +51921,Female,57,Bachelors,2,82,6,15,63,5.0,4,98,Urban,ML Engineer,72199,0 +51922,Male,59,Bachelors,8,97,12,44,58,6.0,4,1,Urban,Data Analyst,97640,0 +51923,Female,33,Diploma,15,52,92,9,80,9.0,0,36,Urban,Data Analyst,32096,0 +51924,Male,33,Bachelors,4,90,17,43,77,3.0,6,30,Urban,Software Engineer,80823,0 +51925,Female,57,Diploma,18,41,43,49,96,6.0,2,18,Urban,Software Engineer,108890,0 +51926,Male,37,Diploma,12,2,74,4,35,4.0,2,0,Semi-Urban,Data Analyst,144766,0 +51927,Male,30,Diploma,13,14,13,14,52,0.0,5,24,Urban,Data Analyst,116178,0 +51928,Female,32,Bachelors,1,40,93,20,61,0.0,3,51,Semi-Urban,HR Executive,35471,0 +51929,Female,59,High School,19,0,23,34,77,8.0,3,60,Rural,Manager,118421,0 +51930,Other,37,Masters,18,6,82,35,73,1.0,0,36,Rural,HR Executive,42188,0 +51931,Male,42,Bachelors,6,82,78,62,19,1.0,3,59,Urban,ML Engineer,29210,1 +51932,Male,37,High School,3,90,86,69,90,1.0,7,10,Urban,HR Executive,84598,1 +51933,Female,48,Bachelors,12,1,49,65,91,6.0,5,36,Rural,ML Engineer,114948,0 +51934,Male,26,Diploma,0,55,61,12,23,3.0,4,34,Urban,Data Analyst,33126,0 +51935,Female,45,Masters,11,50,26,30,4,8.0,0,52,Rural,Manager,65833,0 +51936,Female,25,Diploma,13,55,33,86,58,1.0,4,16,Urban,Software Engineer,75804,0 +51937,Female,54,Masters,17,68,21,7,6,0.0,6,94,Urban,Data Analyst,126794,0 +51938,Female,21,Bachelors,18,97,30,32,56,8.0,1,76,Urban,ML Engineer,71662,0 +51939,Female,55,High School,8,96,16,38,86,0.0,6,11,Urban,Manager,109764,0 +51940,Male,44,Bachelors,13,57,13,16,64,0.0,5,41,Rural,ML Engineer,100719,0 +51941,Other,52,Masters,12,36,81,9,19,0.0,1,40,Urban,HR Executive,45751,0 +51942,Male,35,Diploma,1,16,94,53,65,7.0,1,70,Semi-Urban,HR Executive,75899,0 +51943,Male,26,Bachelors,6,47,24,74,25,5.0,1,29,Semi-Urban,Software Engineer,21255,0 +51944,Male,42,High School,1,50,44,33,28,6.0,7,76,Urban,ML Engineer,98762,0 +51945,Female,43,Bachelors,17,3,35,14,21,9.0,5,39,Semi-Urban,HR Executive,50646,0 +51946,Female,46,Bachelors,6,9,75,92,31,6.0,3,68,Urban,Data Analyst,59827,1 +51947,Male,32,Masters,17,93,94,25,65,8.0,0,60,Urban,Data Analyst,133556,1 +51948,Female,21,Diploma,16,0,46,87,83,8.0,7,42,Urban,Software Engineer,64830,0 +51949,Female,58,Masters,5,62,37,93,32,3.0,5,21,Urban,Data Analyst,104746,0 +51950,Female,44,High School,0,36,40,81,19,6.0,4,78,Urban,Data Analyst,149612,0 +51951,Male,47,Bachelors,15,83,3,64,56,4.0,0,65,Urban,Data Analyst,120301,0 +51952,Female,50,PhD,8,11,9,5,78,3.0,7,51,Semi-Urban,Software Engineer,122450,0 +51953,Female,36,High School,10,12,32,69,61,3.0,7,27,Rural,Manager,49549,0 +51954,Female,58,Bachelors,0,34,88,50,52,1.0,0,33,Urban,ML Engineer,130402,0 +51955,Male,45,High School,14,42,91,4,39,2.0,1,36,Urban,Data Analyst,79791,0 +51956,Male,31,Bachelors,11,3,95,59,20,8.0,5,18,Semi-Urban,Software Engineer,135234,0 +51957,Male,24,High School,5,37,79,80,44,6.0,2,25,Semi-Urban,HR Executive,117571,0 +51958,Male,57,Bachelors,11,1,12,98,2,4.0,5,50,Semi-Urban,Software Engineer,90215,0 +51959,Male,52,Diploma,3,67,20,48,81,9.0,7,16,Rural,ML Engineer,100292,0 +51960,Male,45,Diploma,15,39,80,30,79,2.0,3,12,Semi-Urban,Software Engineer,47705,0 +51961,Female,32,PhD,7,78,12,74,96,9.0,4,78,Urban,HR Executive,134564,1 +51962,Male,22,High School,9,42,18,86,39,5.0,7,37,Urban,Data Analyst,50173,0 +51963,Male,58,Bachelors,10,37,54,48,26,4.0,1,86,Semi-Urban,HR Executive,53343,0 +51964,Male,27,Diploma,14,11,41,64,45,7.0,0,62,Semi-Urban,Data Analyst,70274,0 +51965,Male,30,Bachelors,18,37,40,41,60,1.0,7,97,Urban,Software Engineer,146518,0 +51966,Female,42,Bachelors,9,36,46,79,19,5.0,4,23,Urban,Data Analyst,145796,0 +51967,Male,26,Bachelors,18,91,25,93,70,2.0,0,14,Urban,Data Analyst,36265,0 +51968,Female,54,PhD,7,14,59,25,43,2.0,6,98,Urban,Data Analyst,79949,0 +51969,Male,49,Bachelors,9,63,28,19,41,8.0,4,69,Urban,Software Engineer,49256,0 +51970,Female,21,Masters,2,64,66,22,98,7.0,7,84,Urban,Data Analyst,142135,0 +51971,Male,42,Diploma,5,91,50,35,24,6.0,6,62,Urban,Data Analyst,35275,1 +51972,Male,35,Masters,6,16,20,50,34,6.0,5,1,Rural,HR Executive,73961,0 +51973,Female,28,Masters,19,17,39,67,50,3.0,6,77,Urban,Manager,90088,0 +51974,Male,48,Diploma,7,93,75,43,60,8.0,3,5,Urban,HR Executive,135866,0 +51975,Male,31,Masters,3,97,0,85,22,1.0,5,8,Urban,Data Analyst,146978,0 +51976,Female,51,Bachelors,12,19,82,39,40,3.0,7,12,Semi-Urban,HR Executive,142275,0 +51977,Male,51,Bachelors,19,34,80,5,90,1.0,6,17,Urban,Software Engineer,42596,0 +51978,Female,30,Diploma,13,1,64,15,96,1.0,5,85,Urban,ML Engineer,149370,0 +51979,Male,54,Bachelors,16,51,59,14,66,9.0,1,87,Rural,Manager,40436,0 +51980,Male,31,Masters,3,57,50,84,17,0.0,4,49,Semi-Urban,Software Engineer,126932,1 +51981,Male,31,Bachelors,17,31,50,72,68,2.0,5,34,Rural,Manager,34067,0 +51982,Male,46,High School,16,97,38,19,98,1.0,1,76,Semi-Urban,Manager,75526,0 +51983,Male,45,Bachelors,0,91,0,24,83,8.0,4,65,Urban,Manager,106119,0 +51984,Male,28,Diploma,4,46,15,70,62,5.0,1,31,Urban,Manager,82244,0 +51985,Female,49,Masters,6,84,32,65,81,1.0,3,71,Urban,Data Analyst,54799,1 +51986,Female,27,Bachelors,3,78,49,41,47,3.0,2,7,Urban,HR Executive,54088,0 +51987,Female,23,Bachelors,1,72,53,37,33,7.0,0,53,Urban,ML Engineer,116524,0 +51988,Male,54,Bachelors,6,95,10,84,50,0.0,6,9,Rural,Data Analyst,35196,0 +51989,Male,28,Bachelors,16,85,72,37,58,9.0,1,10,Urban,Manager,49389,0 +51990,Male,55,Masters,7,1,14,15,70,5.0,4,63,Urban,ML Engineer,54801,0 +51991,Male,49,High School,18,4,98,52,29,5.0,4,34,Urban,Manager,62569,0 +51992,Female,37,Diploma,0,72,74,95,18,5.0,6,21,Urban,Manager,32054,1 +51993,Female,59,Bachelors,4,12,74,24,18,4.0,5,49,Urban,Data Analyst,82055,0 +51994,Male,44,Bachelors,12,88,33,46,33,3.0,0,42,Urban,HR Executive,124904,0 +51995,Male,37,Diploma,1,1,56,84,9,1.0,1,57,Semi-Urban,ML Engineer,39668,0 +51996,Female,21,Diploma,2,60,95,73,47,8.0,7,27,Urban,ML Engineer,69052,1 +51997,Male,57,Masters,10,17,90,54,21,2.0,1,60,Urban,ML Engineer,81185,0 +51998,Female,22,High School,15,91,55,22,81,8.0,1,8,Urban,Data Analyst,28906,0 +51999,Female,21,Diploma,10,70,23,24,29,6.0,5,46,Urban,Data Analyst,136033,0 +52000,Male,25,Masters,4,74,10,62,22,3.0,5,99,Urban,HR Executive,129329,1 +52001,Male,39,Masters,3,93,84,48,92,9.0,2,99,Semi-Urban,Data Analyst,74443,1 +52002,Female,24,High School,7,2,55,55,3,3.0,5,32,Rural,HR Executive,82136,0 +52003,Female,49,PhD,5,73,95,45,30,3.0,3,91,Urban,HR Executive,60273,1 +52004,Male,43,Bachelors,14,36,23,48,6,7.0,2,63,Rural,HR Executive,77713,0 +52005,Male,34,Bachelors,14,19,20,76,99,0.0,4,68,Urban,Manager,39957,0 +52006,Female,38,Bachelors,15,18,21,73,2,4.0,2,37,Rural,Software Engineer,51499,0 +52007,Male,24,Diploma,5,73,87,83,91,2.0,4,0,Rural,Manager,29370,1 +52008,Male,36,Bachelors,14,74,17,80,40,5.0,4,72,Urban,ML Engineer,116977,1 +52009,Male,36,Bachelors,13,39,31,36,1,8.0,4,76,Urban,ML Engineer,113199,0 +52010,Male,55,High School,5,20,81,32,33,5.0,2,48,Semi-Urban,Data Analyst,94352,0 +52011,Male,31,High School,8,95,44,99,70,8.0,2,57,Urban,Manager,95077,1 +52012,Male,36,Bachelors,19,93,36,1,72,9.0,1,83,Rural,ML Engineer,90775,0 +52013,Male,53,Diploma,7,94,52,75,60,3.0,3,46,Urban,Software Engineer,85319,1 +52014,Male,59,Masters,13,86,51,93,62,4.0,3,48,Urban,ML Engineer,88407,1 +52015,Female,59,Diploma,10,91,96,49,34,2.0,4,82,Rural,Data Analyst,81605,1 +52016,Male,51,Bachelors,17,87,29,52,46,3.0,5,58,Urban,Software Engineer,51243,0 +52017,Male,50,Masters,4,26,24,92,12,8.0,5,13,Rural,Software Engineer,116937,0 +52018,Male,25,Masters,8,98,17,26,46,0.0,3,85,Rural,ML Engineer,46162,0 +52019,Male,30,Masters,14,62,93,84,70,8.0,5,9,Urban,Manager,35808,1 +52020,Female,29,Bachelors,10,32,81,68,70,2.0,7,75,Semi-Urban,HR Executive,105433,1 +52021,Male,36,Bachelors,19,15,35,96,55,3.0,0,61,Rural,Data Analyst,61802,0 +52022,Male,40,Masters,14,9,31,99,77,1.0,7,24,Rural,Manager,127522,0 +52023,Female,33,Bachelors,13,73,7,3,18,3.0,0,15,Semi-Urban,ML Engineer,61004,0 +52024,Female,40,Masters,15,7,0,65,62,0.0,7,58,Semi-Urban,Data Analyst,128881,0 +52025,Male,36,PhD,6,89,22,87,29,9.0,0,71,Semi-Urban,Data Analyst,42008,1 +52026,Female,38,Bachelors,7,68,33,48,8,6.0,4,44,Semi-Urban,HR Executive,54401,0 +52027,Female,56,Diploma,5,46,75,77,97,3.0,3,40,Urban,Data Analyst,116044,0 +52028,Other,57,Bachelors,2,58,94,43,41,6.0,7,51,Semi-Urban,HR Executive,68814,1 +52029,Male,27,Masters,2,56,15,16,10,3.0,0,23,Urban,ML Engineer,97851,0 +52030,Other,23,Bachelors,17,73,97,20,9,2.0,1,89,Urban,Data Analyst,84777,1 +52031,Male,45,High School,0,91,92,60,2,5.0,3,17,Semi-Urban,Data Analyst,50178,1 +52032,Female,42,Bachelors,7,38,26,75,99,5.0,5,43,Semi-Urban,Manager,64211,0 +52033,Male,22,Bachelors,4,42,31,17,55,3.0,6,72,Rural,Data Analyst,64731,0 +52034,Male,31,Bachelors,8,85,4,20,83,2.0,7,55,Rural,HR Executive,109355,0 +52035,Male,37,Diploma,9,27,48,4,26,5.0,2,68,Urban,Software Engineer,71003,0 +52036,Male,53,Masters,3,52,51,84,23,6.0,1,29,Urban,HR Executive,96182,0 +52037,Male,33,Bachelors,7,5,7,34,85,8.0,3,78,Urban,Manager,145379,0 +52038,Male,27,Bachelors,14,71,45,5,83,2.0,4,89,Rural,Manager,99740,0 +52039,Other,34,Bachelors,18,85,84,48,27,9.0,7,3,Urban,Software Engineer,54623,0 +52040,Female,25,Masters,10,8,83,23,69,2.0,3,32,Rural,ML Engineer,111087,0 +52041,Male,26,High School,15,6,21,53,19,8.0,3,26,Rural,ML Engineer,97936,0 +52042,Female,53,Bachelors,2,16,12,10,23,1.0,7,71,Urban,Software Engineer,46123,0 +52043,Female,21,Masters,4,12,98,84,34,6.0,0,86,Rural,Software Engineer,138811,1 +52044,Male,59,Diploma,1,48,89,28,81,2.0,3,36,Urban,HR Executive,56118,0 +52045,Female,59,High School,17,42,25,0,6,7.0,6,63,Urban,ML Engineer,56461,0 +52046,Female,30,Bachelors,10,78,57,36,17,2.0,6,62,Semi-Urban,HR Executive,94520,0 +52047,Male,35,Bachelors,13,35,81,81,38,4.0,1,26,Urban,Data Analyst,60754,0 +52048,Male,34,Bachelors,16,19,33,82,5,4.0,0,89,Urban,Software Engineer,118349,0 +52049,Male,25,Bachelors,4,19,84,18,81,4.0,0,2,Urban,Software Engineer,91883,0 +52050,Female,21,Bachelors,4,20,45,60,33,5.0,2,97,Semi-Urban,Data Analyst,29409,0 +52051,Male,58,Masters,1,21,70,84,88,7.0,4,4,Urban,ML Engineer,37210,0 +52052,Female,35,Bachelors,9,41,40,38,82,8.0,5,67,Urban,ML Engineer,76089,0 +52053,Male,25,Masters,16,33,25,80,4,1.0,5,42,Semi-Urban,ML Engineer,86749,0 +52054,Female,47,Diploma,11,87,31,98,94,1.0,5,91,Semi-Urban,Manager,33794,1 +52055,Female,44,Bachelors,19,31,13,33,57,5.0,1,39,Urban,Software Engineer,73141,0 +52056,Female,34,Diploma,2,87,0,62,38,4.0,0,56,Rural,Data Analyst,28105,0 +52057,Female,56,Bachelors,13,42,8,26,45,1.0,7,37,Semi-Urban,HR Executive,82743,0 +52058,Male,27,Masters,11,65,40,33,94,5.0,0,72,Urban,ML Engineer,127249,0 +52059,Female,52,Bachelors,6,46,76,62,94,1.0,0,32,Semi-Urban,Software Engineer,84693,0 +52060,Female,59,Bachelors,1,54,17,70,79,5.0,2,97,Rural,Software Engineer,111470,0 +52061,Female,50,High School,10,27,66,57,6,1.0,3,67,Semi-Urban,Manager,79651,0 +52062,Female,32,Masters,5,79,30,98,5,5.0,6,82,Rural,Software Engineer,130033,1 +52063,Male,41,Diploma,8,66,85,47,89,9.0,4,58,Rural,ML Engineer,134948,1 +52064,Female,44,Bachelors,12,19,75,30,83,9.0,1,89,Rural,Manager,137283,0 +52065,Male,27,High School,11,62,81,32,13,6.0,5,78,Urban,HR Executive,124983,1 +52066,Male,32,Masters,0,71,94,2,43,9.0,6,33,Semi-Urban,Manager,73676,0 +52067,Male,54,Bachelors,19,38,17,38,25,6.0,6,96,Urban,Data Analyst,99546,0 +52068,Male,41,Bachelors,18,63,69,71,14,9.0,5,63,Urban,Software Engineer,107041,1 +52069,Female,24,High School,8,44,99,2,29,0.0,3,1,Semi-Urban,HR Executive,104006,0 +52070,Female,46,Masters,17,7,86,47,15,9.0,5,90,Urban,HR Executive,22439,0 +52071,Female,40,Diploma,11,86,1,5,68,8.0,4,36,Urban,Software Engineer,75673,0 +52072,Other,33,Bachelors,12,65,63,82,81,9.0,4,54,Urban,Software Engineer,68855,1 +52073,Female,49,Bachelors,2,36,93,26,17,0.0,4,75,Rural,Software Engineer,130811,0 +52074,Other,49,Bachelors,9,39,84,35,82,9.0,2,99,Urban,HR Executive,120598,1 +52075,Female,34,Bachelors,8,81,76,63,60,7.0,6,15,Urban,Data Analyst,67745,0 +52076,Male,25,PhD,7,9,45,63,91,8.0,6,57,Urban,Software Engineer,58394,0 +52077,Male,56,Bachelors,16,49,58,46,36,0.0,4,8,Rural,ML Engineer,48310,0 +52078,Female,47,Bachelors,4,20,53,81,61,7.0,2,14,Semi-Urban,HR Executive,138744,0 +52079,Female,30,Bachelors,15,63,69,81,47,3.0,6,68,Rural,Data Analyst,82561,1 +52080,Female,57,Bachelors,13,58,49,8,9,1.0,3,12,Rural,Software Engineer,121797,0 +52081,Female,53,Bachelors,9,8,16,87,94,9.0,4,92,Rural,ML Engineer,136269,0 +52082,Female,48,Bachelors,15,26,11,95,78,5.0,4,78,Rural,HR Executive,71939,0 +52083,Male,47,Diploma,12,39,86,31,21,9.0,4,99,Semi-Urban,Data Analyst,142511,1 +52084,Male,33,Diploma,12,77,64,49,16,8.0,0,2,Semi-Urban,Manager,142994,0 +52085,Female,59,Bachelors,19,3,9,49,14,9.0,4,16,Urban,Software Engineer,43019,0 +52086,Male,45,PhD,10,32,73,54,33,9.0,2,52,Semi-Urban,ML Engineer,132906,0 +52087,Other,35,Bachelors,16,75,28,51,5,6.0,2,61,Rural,Manager,133520,0 +52088,Female,34,Diploma,17,11,40,32,23,7.0,4,81,Urban,ML Engineer,61916,0 +52089,Male,34,Diploma,13,69,2,32,83,9.0,0,61,Urban,Manager,141947,0 +52090,Male,29,High School,11,23,74,6,12,0.0,6,39,Rural,ML Engineer,115952,0 +52091,Female,22,High School,15,15,25,66,83,1.0,2,33,Rural,HR Executive,33368,0 +52092,Male,50,PhD,16,11,50,90,29,5.0,6,31,Rural,HR Executive,128886,0 +52093,Male,37,Bachelors,18,81,94,55,82,5.0,7,74,Semi-Urban,HR Executive,142887,1 +52094,Male,28,High School,4,4,43,98,87,0.0,6,31,Urban,HR Executive,42722,0 +52095,Female,57,Diploma,5,79,29,7,5,4.0,4,41,Urban,Software Engineer,88791,0 +52096,Female,57,Diploma,10,92,17,76,87,7.0,3,60,Rural,Data Analyst,82162,1 +52097,Male,44,Masters,8,24,86,15,10,4.0,6,88,Rural,ML Engineer,120584,0 +52098,Female,48,Bachelors,9,57,40,84,75,4.0,6,25,Urban,ML Engineer,72884,0 +52099,Female,44,Diploma,7,3,87,54,7,9.0,0,19,Semi-Urban,Software Engineer,111911,0 +52100,Male,32,Bachelors,17,21,76,57,69,6.0,2,18,Urban,Data Analyst,91340,0 +52101,Male,49,Diploma,11,40,72,57,21,3.0,3,37,Urban,Software Engineer,86323,0 +52102,Female,24,PhD,15,95,52,9,17,3.0,4,8,Semi-Urban,Manager,112651,0 +52103,Male,59,PhD,9,11,33,89,95,3.0,4,61,Semi-Urban,ML Engineer,115927,0 +52104,Male,25,Masters,0,83,83,64,16,9.0,1,9,Urban,Manager,117719,1 +52105,Male,29,Bachelors,5,14,82,56,75,3.0,5,6,Rural,ML Engineer,52027,0 +52106,Male,45,Masters,4,79,87,30,25,0.0,5,89,Rural,ML Engineer,148389,1 +52107,Male,27,Bachelors,4,89,92,3,98,5.0,6,29,Urban,HR Executive,68453,0 +52108,Female,52,Masters,0,69,31,19,48,0.0,0,35,Urban,HR Executive,27904,0 +52109,Male,55,Diploma,8,81,95,34,97,1.0,7,31,Urban,Software Engineer,125666,1 +52110,Female,42,Bachelors,10,34,46,36,53,8.0,2,39,Urban,ML Engineer,124855,0 +52111,Female,25,Bachelors,0,63,82,82,45,8.0,1,9,Semi-Urban,Data Analyst,22703,0 +52112,Male,47,Bachelors,5,4,22,89,45,3.0,5,32,Urban,Data Analyst,89169,0 +52113,Female,22,Masters,7,91,6,99,84,2.0,3,22,Urban,HR Executive,20827,0 +52114,Male,59,Masters,1,98,55,61,16,2.0,3,99,Semi-Urban,Software Engineer,68609,1 +52115,Female,57,High School,19,14,8,72,43,7.0,5,30,Urban,Manager,81655,0 +52116,Male,40,High School,10,35,16,68,77,5.0,1,8,Semi-Urban,Software Engineer,37580,0 +52117,Male,49,Bachelors,17,8,90,53,90,9.0,7,63,Urban,ML Engineer,54269,0 +52118,Male,47,Diploma,17,92,20,32,1,9.0,2,50,Urban,HR Executive,147282,0 +52119,Male,35,Bachelors,12,86,85,6,39,3.0,6,57,Rural,Data Analyst,104879,0 +52120,Male,41,High School,19,35,35,16,66,5.0,0,67,Urban,ML Engineer,103008,0 +52121,Female,22,Masters,15,37,46,71,36,8.0,5,27,Urban,Software Engineer,101482,0 +52122,Female,22,Bachelors,2,82,85,61,9,0.0,2,98,Urban,Software Engineer,96929,1 +52123,Other,38,Masters,0,14,25,66,35,4.0,4,52,Urban,Manager,59593,0 +52124,Female,25,PhD,14,99,72,80,15,9.0,5,52,Urban,Data Analyst,141988,1 +52125,Female,42,Masters,12,63,77,60,46,4.0,5,78,Urban,Software Engineer,111687,1 +52126,Male,40,Masters,9,12,8,50,82,1.0,0,7,Semi-Urban,Software Engineer,43385,0 +52127,Male,43,Bachelors,0,57,73,54,15,2.0,0,55,Urban,HR Executive,58124,1 +52128,Female,59,Diploma,16,85,68,88,88,2.0,7,4,Rural,HR Executive,31223,1 +52129,Male,30,Diploma,12,77,98,90,18,7.0,5,91,Semi-Urban,ML Engineer,39218,1 +52130,Male,28,Bachelors,5,26,59,10,17,7.0,3,75,Urban,Software Engineer,32795,0 +52131,Female,42,Masters,9,53,54,1,70,6.0,3,21,Urban,Manager,70881,0 +52132,Male,43,Bachelors,4,42,33,91,68,9.0,2,8,Urban,Software Engineer,123017,0 +52133,Male,32,Bachelors,12,64,4,39,17,8.0,7,17,Urban,Software Engineer,103174,0 +52134,Male,38,Masters,1,65,8,54,64,7.0,4,51,Urban,Manager,102453,0 +52135,Other,33,Diploma,3,4,69,91,40,2.0,6,1,Urban,Software Engineer,35251,0 +52136,Other,35,Bachelors,13,96,67,18,8,9.0,5,16,Urban,Manager,115957,0 +52137,Female,23,Diploma,16,25,70,24,75,6.0,2,64,Semi-Urban,Data Analyst,112991,0 +52138,Female,27,Bachelors,3,98,8,2,79,4.0,3,19,Urban,Software Engineer,78070,0 +52139,Male,35,Bachelors,12,23,46,94,84,1.0,1,52,Urban,Manager,53388,0 +52140,Male,44,Bachelors,17,44,34,35,37,8.0,7,78,Urban,ML Engineer,97169,0 +52141,Male,58,Bachelors,0,10,85,13,28,3.0,1,65,Semi-Urban,Manager,94819,0 +52142,Male,35,High School,19,62,4,50,36,6.0,5,23,Urban,Manager,86733,0 +52143,Male,43,Bachelors,9,27,7,74,90,6.0,1,34,Rural,Data Analyst,135983,0 +52144,Male,59,Bachelors,18,45,48,67,77,6.0,4,14,Urban,ML Engineer,146348,0 +52145,Male,48,Bachelors,19,29,7,52,82,2.0,7,63,Urban,ML Engineer,21920,0 +52146,Male,35,High School,3,69,58,28,59,3.0,6,22,Urban,Manager,30070,0 +52147,Male,49,Bachelors,0,30,85,52,71,4.0,1,0,Urban,Data Analyst,149166,0 +52148,Female,30,Diploma,19,50,74,77,17,4.0,4,36,Semi-Urban,ML Engineer,26971,0 +52149,Male,29,Bachelors,6,20,88,13,65,9.0,1,18,Urban,ML Engineer,80524,0 +52150,Male,53,High School,11,98,53,14,16,5.0,5,43,Semi-Urban,Data Analyst,124014,0 +52151,Male,44,Diploma,3,69,28,47,48,2.0,4,68,Urban,HR Executive,62674,0 +52152,Female,43,Diploma,1,8,67,30,72,2.0,3,54,Urban,Software Engineer,103843,0 +52153,Male,42,Masters,18,26,16,14,30,5.0,4,88,Urban,Manager,66466,0 +52154,Male,30,High School,3,43,52,17,69,9.0,7,96,Urban,Data Analyst,62552,0 +52155,Male,45,Masters,0,47,85,95,78,5.0,2,9,Semi-Urban,HR Executive,61874,1 +52156,Male,25,Bachelors,5,70,18,40,69,4.0,7,69,Urban,Data Analyst,63921,0 +52157,Male,23,Diploma,8,3,78,91,31,6.0,0,66,Semi-Urban,ML Engineer,142707,1 +52158,Male,42,Diploma,12,40,89,6,68,8.0,3,42,Urban,ML Engineer,134016,0 +52159,Male,56,Masters,10,74,22,65,17,8.0,5,86,Rural,HR Executive,25970,1 +52160,Female,52,Bachelors,12,87,67,64,12,0.0,5,74,Semi-Urban,Manager,83560,1 +52161,Male,38,Bachelors,14,98,2,94,44,2.0,2,92,Semi-Urban,Manager,131809,1 +52162,Female,47,Masters,19,13,44,92,89,6.0,5,34,Urban,ML Engineer,95569,0 +52163,Male,44,Diploma,1,31,25,20,48,7.0,3,25,Urban,Manager,119447,0 +52164,Male,23,Masters,11,31,77,58,56,9.0,3,51,Rural,ML Engineer,100870,0 +52165,Male,32,Masters,17,32,30,0,93,8.0,7,32,Urban,HR Executive,125935,0 +52166,Female,54,High School,15,26,81,81,8,6.0,1,10,Urban,Software Engineer,109952,0 +52167,Male,40,Masters,7,68,81,72,49,4.0,2,34,Urban,Data Analyst,91821,1 +52168,Male,40,PhD,14,64,63,95,15,1.0,6,90,Semi-Urban,ML Engineer,87229,1 +52169,Male,58,High School,10,72,31,97,70,2.0,0,37,Urban,Software Engineer,93403,1 +52170,Male,21,Bachelors,2,3,59,21,42,2.0,2,50,Urban,HR Executive,77706,0 +52171,Male,49,High School,11,44,15,54,90,9.0,1,79,Rural,Data Analyst,110177,0 +52172,Male,27,Bachelors,8,98,86,47,5,3.0,4,36,Urban,Manager,75915,1 +52173,Female,55,High School,16,54,90,30,78,7.0,7,16,Urban,Data Analyst,49189,0 +52174,Female,27,Masters,17,75,94,32,72,8.0,6,20,Rural,Data Analyst,75798,0 +52175,Male,32,PhD,12,70,35,85,40,7.0,3,82,Urban,Manager,133612,1 +52176,Female,42,High School,8,15,16,25,90,3.0,4,41,Urban,Software Engineer,105778,0 +52177,Male,22,Diploma,18,1,84,27,35,3.0,4,29,Urban,Manager,119322,0 +52178,Female,52,High School,19,56,23,41,81,0.0,1,96,Urban,Data Analyst,50961,0 +52179,Female,48,High School,12,7,67,26,43,5.0,4,75,Semi-Urban,Data Analyst,66992,0 +52180,Male,38,Masters,5,51,58,95,24,0.0,2,85,Semi-Urban,Manager,110843,1 +52181,Female,51,Bachelors,11,67,3,47,11,7.0,1,53,Urban,Manager,69472,0 +52182,Male,51,Masters,2,97,7,85,67,0.0,7,56,Urban,ML Engineer,99701,1 +52183,Male,45,High School,5,6,20,24,64,1.0,5,87,Semi-Urban,Data Analyst,52463,0 +52184,Female,40,Diploma,5,71,75,60,22,6.0,5,23,Urban,HR Executive,78539,0 +52185,Male,58,Diploma,13,53,2,37,5,5.0,1,38,Urban,Manager,143755,0 +52186,Male,38,Masters,11,29,96,78,92,9.0,2,27,Semi-Urban,Data Analyst,122989,0 +52187,Male,27,High School,3,65,24,2,65,1.0,2,90,Semi-Urban,HR Executive,140833,0 +52188,Female,51,High School,0,78,5,43,25,0.0,0,99,Semi-Urban,Software Engineer,140965,0 +52189,Male,52,Masters,15,45,57,38,82,0.0,3,88,Semi-Urban,Data Analyst,65001,0 +52190,Male,45,Diploma,0,52,4,9,40,2.0,6,92,Semi-Urban,HR Executive,63340,0 +52191,Male,29,Masters,8,3,84,17,87,9.0,0,94,Rural,Data Analyst,31080,0 +52192,Male,29,Diploma,6,10,27,2,41,2.0,4,65,Semi-Urban,Data Analyst,144868,0 +52193,Female,49,Bachelors,9,23,40,1,90,5.0,4,46,Rural,Data Analyst,61551,0 +52194,Male,49,Bachelors,7,18,96,61,85,9.0,1,66,Urban,ML Engineer,97867,1 +52195,Female,50,Bachelors,11,91,5,65,13,8.0,7,9,Urban,Software Engineer,129875,0 +52196,Female,45,Bachelors,13,4,35,9,13,3.0,7,18,Urban,ML Engineer,29220,0 +52197,Male,38,High School,11,83,36,59,71,4.0,5,30,Urban,HR Executive,142700,0 +52198,Male,58,Diploma,7,70,21,15,40,2.0,3,33,Rural,Data Analyst,68642,0 +52199,Female,35,Bachelors,16,71,23,33,82,1.0,6,47,Semi-Urban,ML Engineer,60672,0 +52200,Male,50,Bachelors,13,68,95,72,71,0.0,2,5,Semi-Urban,HR Executive,118998,1 +52201,Female,23,Masters,2,26,80,13,41,5.0,5,31,Urban,ML Engineer,62549,0 +52202,Female,43,Bachelors,6,9,15,52,25,1.0,6,84,Rural,Software Engineer,132414,0 +52203,Female,23,Diploma,4,71,45,83,52,9.0,3,47,Urban,HR Executive,27147,1 +52204,Other,58,Diploma,10,63,58,42,64,6.0,6,37,Urban,HR Executive,61137,0 +52205,Male,47,Bachelors,7,3,94,90,32,6.0,0,65,Semi-Urban,Manager,62705,1 +52206,Male,35,Diploma,13,86,36,69,5,0.0,3,47,Urban,ML Engineer,92666,1 +52207,Male,59,Masters,7,52,67,36,95,3.0,5,39,Urban,ML Engineer,114802,0 +52208,Male,40,Diploma,11,10,67,59,31,9.0,1,53,Rural,Software Engineer,112786,0 +52209,Male,49,Masters,2,51,42,70,74,4.0,4,44,Urban,Data Analyst,149833,0 +52210,Male,58,PhD,15,31,84,47,67,2.0,7,2,Rural,Data Analyst,87813,0 +52211,Male,21,Bachelors,7,60,9,37,27,3.0,2,38,Urban,ML Engineer,119161,0 +52212,Male,47,Diploma,5,49,15,44,41,1.0,3,8,Semi-Urban,Manager,142264,0 +52213,Male,26,Bachelors,19,44,90,56,53,0.0,4,56,Semi-Urban,HR Executive,149482,1 +52214,Male,48,Bachelors,2,94,73,16,31,6.0,0,47,Rural,Software Engineer,72146,0 +52215,Male,47,Diploma,15,71,95,44,90,9.0,2,56,Urban,HR Executive,47377,1 +52216,Female,22,Bachelors,1,79,52,23,76,1.0,0,76,Urban,ML Engineer,69807,0 +52217,Male,51,Bachelors,1,39,63,35,16,9.0,1,64,Urban,Data Analyst,34194,0 +52218,Female,55,High School,3,85,41,41,71,5.0,6,45,Semi-Urban,ML Engineer,142891,0 +52219,Female,27,Diploma,4,0,82,27,36,8.0,6,56,Urban,Data Analyst,123774,0 +52220,Female,57,Masters,14,21,46,2,35,2.0,1,32,Semi-Urban,Software Engineer,111412,0 +52221,Male,39,PhD,7,49,71,95,61,8.0,4,10,Semi-Urban,Manager,123268,0 +52222,Female,31,Masters,5,24,96,21,12,0.0,3,15,Rural,HR Executive,93703,0 +52223,Male,36,PhD,18,85,61,13,39,7.0,0,88,Urban,Manager,45156,1 +52224,Female,28,Bachelors,15,96,36,28,78,0.0,2,96,Urban,Software Engineer,122503,1 +52225,Male,44,Bachelors,0,36,81,77,63,2.0,3,88,Semi-Urban,Software Engineer,26949,1 +52226,Female,49,High School,19,78,16,36,47,1.0,0,52,Urban,HR Executive,113497,0 +52227,Female,43,Masters,0,49,88,2,60,1.0,0,75,Urban,ML Engineer,124522,0 +52228,Male,35,Masters,18,51,57,1,78,9.0,7,34,Semi-Urban,Software Engineer,94291,0 +52229,Female,24,Bachelors,13,47,23,74,74,6.0,5,18,Urban,Data Analyst,90621,0 +52230,Male,24,PhD,7,33,45,25,7,4.0,6,54,Semi-Urban,Software Engineer,30599,0 +52231,Male,47,High School,2,81,28,73,82,2.0,2,26,Semi-Urban,Software Engineer,119673,0 +52232,Male,35,High School,8,94,60,11,82,1.0,0,8,Urban,Manager,117420,0 +52233,Male,52,Bachelors,18,4,54,99,63,2.0,2,22,Rural,Software Engineer,77177,0 +52234,Male,22,Bachelors,0,59,63,38,81,1.0,6,31,Urban,HR Executive,20998,0 +52235,Male,31,High School,7,42,33,1,84,6.0,7,71,Urban,ML Engineer,144128,0 +52236,Male,52,Bachelors,12,44,36,91,47,4.0,2,66,Rural,Data Analyst,60249,1 +52237,Female,26,High School,12,9,55,31,34,0.0,2,56,Semi-Urban,HR Executive,95272,0 +52238,Male,44,Bachelors,3,12,92,66,24,1.0,0,62,Urban,Manager,87062,0 +52239,Male,23,Diploma,10,37,26,73,50,4.0,7,79,Semi-Urban,Manager,47424,0 +52240,Male,31,Masters,4,70,53,25,24,7.0,6,76,Urban,Software Engineer,136228,0 +52241,Male,31,Bachelors,12,74,6,94,79,0.0,4,23,Rural,Manager,27991,0 +52242,Female,41,Bachelors,5,0,20,33,1,2.0,4,38,Urban,Manager,73332,0 +52243,Male,58,Diploma,9,81,57,47,66,7.0,5,98,Rural,Data Analyst,83719,1 +52244,Male,39,Diploma,11,9,68,29,84,0.0,1,76,Rural,Software Engineer,24354,0 +52245,Female,22,High School,3,26,69,39,31,1.0,1,74,Urban,ML Engineer,94658,0 +52246,Male,58,Diploma,17,76,32,25,31,0.0,6,54,Urban,Data Analyst,25966,0 +52247,Male,42,Bachelors,12,99,59,19,68,5.0,0,62,Urban,Software Engineer,35865,1 +52248,Female,42,Masters,10,45,58,35,39,4.0,7,89,Urban,Data Analyst,107381,0 +52249,Male,33,Diploma,6,23,8,4,62,1.0,4,48,Semi-Urban,Data Analyst,32729,0 +52250,Female,29,Bachelors,4,15,52,58,74,2.0,1,23,Urban,ML Engineer,98704,0 +52251,Male,37,Bachelors,0,73,58,22,37,8.0,2,7,Urban,Manager,105552,0 +52252,Male,23,High School,19,9,16,49,43,6.0,3,83,Semi-Urban,HR Executive,64685,0 +52253,Male,22,High School,19,47,20,52,47,1.0,6,43,Semi-Urban,Manager,142239,0 +52254,Male,38,Bachelors,19,73,81,97,20,7.0,6,69,Urban,Software Engineer,121882,1 +52255,Female,41,Masters,0,86,69,47,99,3.0,5,98,Urban,ML Engineer,100026,1 +52256,Male,38,Masters,10,99,55,15,87,0.0,7,43,Semi-Urban,Software Engineer,127672,0 +52257,Female,41,Masters,15,83,62,19,95,6.0,1,35,Urban,Data Analyst,78557,0 +52258,Male,25,Bachelors,6,21,82,44,21,7.0,1,47,Rural,Manager,95881,0 +52259,Male,48,Masters,8,11,62,48,30,2.0,6,76,Urban,ML Engineer,27613,0 +52260,Female,27,Masters,14,30,18,82,87,2.0,2,85,Rural,ML Engineer,97074,0 +52261,Male,44,Bachelors,2,12,7,57,77,6.0,1,96,Urban,ML Engineer,113275,0 +52262,Male,38,High School,10,40,96,82,75,1.0,0,40,Semi-Urban,Data Analyst,34278,1 +52263,Male,26,Diploma,9,81,82,33,81,5.0,4,63,Urban,Manager,98262,1 +52264,Male,40,PhD,13,7,18,18,14,0.0,6,42,Semi-Urban,Data Analyst,129858,0 +52265,Male,39,Masters,16,62,35,80,29,6.0,5,97,Urban,Manager,90748,1 +52266,Female,29,Diploma,16,52,78,5,82,5.0,7,33,Urban,HR Executive,70293,0 +52267,Female,25,Bachelors,9,51,26,4,13,8.0,7,62,Rural,Manager,140149,0 +52268,Female,53,Masters,0,32,49,58,50,3.0,2,60,Rural,HR Executive,122681,0 +52269,Female,30,Diploma,14,19,5,80,80,5.0,5,59,Urban,HR Executive,48197,0 +52270,Other,32,PhD,12,93,88,99,44,2.0,0,1,Urban,Software Engineer,146492,1 +52271,Male,30,Diploma,10,12,30,64,94,6.0,1,24,Semi-Urban,ML Engineer,34541,0 +52272,Male,55,Diploma,4,8,23,48,93,7.0,2,63,Semi-Urban,Manager,47401,0 +52273,Female,51,Bachelors,18,98,22,96,72,9.0,5,80,Urban,Data Analyst,110979,1 +52274,Male,50,Bachelors,7,21,63,57,90,5.0,0,77,Rural,Manager,147761,0 +52275,Male,32,Diploma,19,20,45,93,85,0.0,3,44,Urban,Software Engineer,56920,0 +52276,Male,40,High School,8,49,99,49,13,8.0,3,71,Rural,Data Analyst,66622,1 +52277,Other,31,Diploma,12,34,94,83,86,2.0,2,2,Rural,ML Engineer,20847,0 +52278,Other,56,High School,2,1,39,82,48,3.0,7,25,Urban,Manager,89015,0 +52279,Female,29,Bachelors,4,78,11,55,1,9.0,0,68,Semi-Urban,HR Executive,80051,0 +52280,Male,34,Diploma,1,33,80,68,52,8.0,3,40,Urban,ML Engineer,149758,0 +52281,Male,26,Bachelors,19,57,48,26,98,7.0,5,18,Rural,Data Analyst,70345,0 +52282,Male,30,Bachelors,19,10,8,50,72,7.0,2,50,Semi-Urban,ML Engineer,43085,0 +52283,Female,24,Masters,11,44,59,74,94,5.0,5,22,Urban,HR Executive,149239,0 +52284,Female,40,Masters,13,56,86,8,56,2.0,3,26,Urban,Manager,105517,0 +52285,Female,23,Bachelors,17,98,51,19,31,6.0,3,25,Semi-Urban,ML Engineer,142492,0 +52286,Male,54,High School,4,24,54,25,26,2.0,7,50,Rural,Manager,116671,0 +52287,Male,36,Masters,4,62,89,23,62,3.0,4,79,Urban,Software Engineer,84525,1 +52288,Male,55,Diploma,1,13,59,2,78,0.0,7,17,Semi-Urban,Software Engineer,73204,0 +52289,Male,27,High School,6,94,99,43,75,9.0,7,18,Semi-Urban,HR Executive,37640,1 +52290,Male,26,PhD,2,73,32,14,68,9.0,5,54,Semi-Urban,Software Engineer,99628,0 +52291,Male,51,High School,15,9,56,51,76,4.0,6,19,Rural,ML Engineer,27967,0 +52292,Other,59,Diploma,5,66,33,43,94,1.0,7,27,Urban,HR Executive,114507,0 +52293,Female,47,Bachelors,13,7,49,86,74,2.0,4,15,Urban,Software Engineer,89852,0 +52294,Female,21,Diploma,19,23,76,70,77,0.0,5,68,Urban,Manager,59665,0 +52295,Male,32,High School,14,93,60,47,71,9.0,7,89,Rural,HR Executive,96493,1 +52296,Male,51,Diploma,6,68,9,6,99,5.0,5,32,Urban,HR Executive,125698,0 +52297,Male,53,Bachelors,15,57,69,31,52,4.0,2,82,Urban,ML Engineer,89791,1 +52298,Male,24,Bachelors,16,80,50,59,67,8.0,2,73,Urban,ML Engineer,79428,1 +52299,Female,39,Bachelors,14,11,91,24,29,5.0,3,86,Semi-Urban,HR Executive,44591,0 +52300,Male,46,Diploma,10,53,69,86,75,1.0,6,10,Rural,ML Engineer,28185,0 +52301,Male,46,Diploma,5,82,5,43,26,8.0,5,28,Urban,HR Executive,103596,0 +52302,Male,46,Masters,8,78,85,11,1,0.0,5,75,Semi-Urban,Manager,129319,1 +52303,Female,40,Bachelors,9,17,2,51,52,1.0,1,12,Urban,ML Engineer,27774,0 +52304,Female,38,Bachelors,6,81,40,93,31,4.0,7,77,Urban,ML Engineer,131974,1 +52305,Female,33,High School,10,18,73,48,12,5.0,7,77,Semi-Urban,Manager,121422,0 +52306,Male,58,Diploma,19,19,67,90,51,7.0,3,50,Semi-Urban,Manager,94058,0 +52307,Male,26,Bachelors,10,51,18,14,3,7.0,0,56,Semi-Urban,HR Executive,108230,0 +52308,Female,56,Bachelors,6,69,14,96,81,7.0,3,14,Urban,Software Engineer,135118,0 +52309,Male,36,High School,4,11,37,41,56,8.0,5,63,Urban,Data Analyst,108410,0 +52310,Male,34,High School,6,33,71,3,74,9.0,2,0,Urban,Data Analyst,48546,0 +52311,Male,21,Bachelors,16,17,92,72,88,3.0,2,50,Urban,Software Engineer,35134,0 +52312,Male,36,Diploma,9,36,80,48,7,4.0,2,11,Urban,ML Engineer,105228,0 +52313,Male,59,Masters,5,23,88,14,92,4.0,6,68,Rural,HR Executive,125275,0 +52314,Female,45,Bachelors,8,26,8,40,26,0.0,0,46,Urban,ML Engineer,147418,0 +52315,Male,48,High School,16,77,75,44,11,2.0,0,73,Semi-Urban,Manager,65417,1 +52316,Female,52,Masters,11,30,41,6,90,0.0,4,75,Rural,Manager,101556,0 +52317,Female,27,Diploma,19,35,36,91,7,8.0,6,89,Urban,HR Executive,110546,1 +52318,Male,55,High School,17,64,11,96,64,0.0,4,49,Semi-Urban,Software Engineer,56804,0 +52319,Male,54,Bachelors,6,39,67,26,48,6.0,0,61,Urban,Software Engineer,41573,0 +52320,Male,44,Bachelors,18,26,19,76,47,9.0,4,36,Urban,Data Analyst,147668,0 +52321,Female,54,Bachelors,11,46,69,45,72,3.0,2,72,Rural,HR Executive,101264,0 +52322,Male,29,Bachelors,0,38,38,94,90,9.0,7,9,Semi-Urban,Manager,115820,0 +52323,Female,34,High School,5,87,8,91,48,1.0,5,78,Semi-Urban,HR Executive,44380,1 +52324,Female,49,Diploma,13,20,76,36,0,1.0,6,85,Urban,Software Engineer,48746,0 +52325,Other,45,Bachelors,7,38,7,13,21,4.0,7,20,Rural,ML Engineer,24308,0 +52326,Female,33,Bachelors,6,11,4,77,28,6.0,5,31,Semi-Urban,Software Engineer,73050,0 +52327,Male,33,Bachelors,8,6,37,51,11,0.0,1,78,Semi-Urban,Manager,60874,0 +52328,Male,23,Bachelors,7,96,41,3,10,1.0,6,44,Urban,Software Engineer,107045,0 +52329,Male,31,Bachelors,5,39,38,26,65,9.0,0,25,Semi-Urban,ML Engineer,21856,0 +52330,Male,28,Bachelors,0,67,74,37,5,0.0,6,10,Semi-Urban,Software Engineer,139685,0 +52331,Female,27,Masters,3,46,86,61,38,9.0,5,23,Semi-Urban,Software Engineer,33602,0 +52332,Female,55,Diploma,4,49,56,85,18,8.0,2,24,Rural,Manager,27910,0 +52333,Other,57,Bachelors,12,88,73,87,37,4.0,4,86,Urban,ML Engineer,92094,1 +52334,Male,53,Bachelors,16,79,77,82,17,5.0,5,6,Semi-Urban,Manager,125883,1 +52335,Male,27,Bachelors,17,45,39,28,35,0.0,4,65,Rural,Software Engineer,142468,0 +52336,Male,58,Diploma,4,77,64,59,87,5.0,7,34,Urban,HR Executive,71747,0 +52337,Male,49,PhD,7,47,10,84,16,3.0,2,14,Urban,Data Analyst,66424,0 +52338,Male,48,Masters,14,19,71,74,37,1.0,5,28,Urban,Software Engineer,148758,0 +52339,Female,41,Diploma,5,49,68,75,98,3.0,2,55,Urban,ML Engineer,45738,1 +52340,Female,22,Bachelors,15,4,48,57,35,8.0,2,48,Rural,Data Analyst,110902,0 +52341,Female,47,Bachelors,1,6,5,77,57,6.0,6,1,Semi-Urban,Data Analyst,81295,0 +52342,Male,25,Bachelors,4,75,78,93,87,3.0,4,17,Rural,Data Analyst,34778,1 +52343,Male,50,Masters,12,55,74,94,53,5.0,5,58,Urban,Software Engineer,113814,1 +52344,Female,37,High School,0,43,57,50,7,7.0,3,38,Rural,Data Analyst,40520,0 +52345,Male,41,Bachelors,0,62,11,82,42,7.0,7,26,Urban,ML Engineer,27441,0 +52346,Female,30,Bachelors,10,95,80,25,75,3.0,6,30,Semi-Urban,Data Analyst,57143,0 +52347,Male,41,Diploma,5,5,63,44,24,8.0,2,19,Rural,ML Engineer,27903,0 +52348,Female,22,Diploma,11,94,46,55,70,7.0,5,98,Semi-Urban,ML Engineer,38976,1 +52349,Female,42,Bachelors,15,1,55,63,15,2.0,1,92,Urban,Manager,148894,0 +52350,Male,40,Diploma,8,74,11,62,96,8.0,5,35,Urban,ML Engineer,130511,0 +52351,Female,46,Bachelors,17,42,93,36,44,3.0,2,3,Urban,Data Analyst,27692,0 +52352,Male,28,Bachelors,4,3,44,2,18,8.0,1,72,Urban,Software Engineer,134588,0 +52353,Male,58,Bachelors,6,25,46,0,75,2.0,6,90,Semi-Urban,ML Engineer,100585,0 +52354,Female,29,Bachelors,10,17,5,14,94,2.0,7,57,Semi-Urban,ML Engineer,36133,0 +52355,Female,39,Diploma,18,28,63,76,61,6.0,3,21,Semi-Urban,Data Analyst,142338,0 +52356,Other,46,High School,11,22,35,28,99,9.0,3,25,Urban,HR Executive,55770,0 +52357,Male,48,Masters,8,84,16,56,89,6.0,0,0,Urban,ML Engineer,99054,0 +52358,Male,41,Diploma,11,82,19,42,98,5.0,6,45,Urban,ML Engineer,103033,0 +52359,Female,22,Bachelors,18,2,27,5,76,7.0,5,88,Semi-Urban,ML Engineer,90206,0 +52360,Male,25,Masters,11,95,76,1,91,4.0,5,82,Urban,HR Executive,33499,1 +52361,Female,43,Masters,4,74,61,42,57,9.0,3,60,Urban,Data Analyst,28230,0 +52362,Male,51,PhD,8,32,15,44,36,5.0,1,83,Urban,HR Executive,119113,0 +52363,Female,43,Bachelors,3,91,8,78,85,3.0,6,33,Rural,Software Engineer,119923,0 +52364,Female,31,High School,14,23,10,30,60,1.0,3,33,Semi-Urban,HR Executive,23565,0 +52365,Female,48,Diploma,6,90,75,7,74,0.0,4,60,Rural,Data Analyst,20141,0 +52366,Female,30,Bachelors,17,80,72,5,89,1.0,2,16,Urban,HR Executive,123499,0 +52367,Male,49,Bachelors,8,52,66,64,68,4.0,6,84,Urban,HR Executive,123759,1 +52368,Male,32,Masters,9,73,61,4,35,4.0,5,55,Semi-Urban,Data Analyst,104963,0 +52369,Male,40,Masters,5,55,45,14,5,0.0,5,50,Rural,Manager,84636,0 +52370,Male,55,High School,13,42,47,33,99,9.0,7,16,Urban,Manager,80880,0 +52371,Male,33,Diploma,19,88,83,17,51,2.0,4,28,Rural,HR Executive,143224,0 +52372,Other,35,Masters,14,32,6,78,94,3.0,6,7,Urban,Data Analyst,133577,0 +52373,Male,50,Diploma,14,31,11,67,74,8.0,4,1,Semi-Urban,ML Engineer,143901,0 +52374,Female,27,Diploma,2,73,17,99,94,5.0,6,28,Semi-Urban,ML Engineer,73033,0 +52375,Female,51,High School,1,54,77,88,68,7.0,4,83,Semi-Urban,Software Engineer,138130,1 +52376,Male,57,Bachelors,15,88,19,18,58,0.0,4,47,Rural,HR Executive,123951,0 +52377,Male,54,Diploma,19,96,77,63,9,2.0,3,21,Urban,HR Executive,59834,1 +52378,Male,59,High School,16,87,51,31,45,2.0,7,67,Urban,ML Engineer,69163,1 +52379,Female,54,Diploma,8,52,38,58,40,6.0,2,74,Urban,Manager,125609,0 +52380,Male,38,Bachelors,19,62,26,10,88,1.0,7,89,Urban,HR Executive,123132,0 +52381,Female,35,Bachelors,13,86,88,0,38,7.0,6,93,Urban,Data Analyst,146482,1 +52382,Male,34,Masters,2,60,57,95,80,7.0,5,69,Semi-Urban,Data Analyst,59003,1 +52383,Male,21,High School,6,36,61,99,71,5.0,1,41,Rural,Software Engineer,29765,1 +52384,Male,59,High School,5,75,38,37,44,8.0,2,91,Semi-Urban,Software Engineer,100742,1 +52385,Male,31,Diploma,9,19,70,41,95,0.0,3,50,Urban,Data Analyst,52750,0 +52386,Female,47,Masters,13,22,70,78,29,1.0,7,72,Semi-Urban,Manager,28775,1 +52387,Other,44,Bachelors,16,87,13,11,14,4.0,2,72,Rural,HR Executive,48421,0 +52388,Female,30,Bachelors,11,60,32,32,24,1.0,0,77,Semi-Urban,ML Engineer,101300,0 +52389,Male,56,Bachelors,14,63,91,96,30,6.0,5,3,Rural,Manager,26659,1 +52390,Female,27,Diploma,11,6,94,37,54,1.0,7,4,Urban,Software Engineer,97819,0 +52391,Male,55,Diploma,10,5,17,65,96,5.0,6,69,Urban,HR Executive,109605,0 +52392,Male,33,Bachelors,11,49,67,57,21,8.0,1,77,Semi-Urban,Data Analyst,32444,1 +52393,Male,40,Diploma,8,15,13,46,22,0.0,0,87,Urban,Software Engineer,22700,0 +52394,Male,57,Bachelors,15,26,35,70,87,4.0,1,82,Urban,Data Analyst,21967,0 +52395,Male,54,PhD,10,81,53,62,48,1.0,5,47,Semi-Urban,Software Engineer,42576,1 +52396,Male,38,High School,17,57,53,98,5,2.0,6,56,Urban,Software Engineer,79848,1 +52397,Other,27,Diploma,15,89,85,91,33,3.0,0,50,Urban,ML Engineer,144596,1 +52398,Female,23,High School,10,57,84,8,38,8.0,0,0,Urban,Manager,38076,0 +52399,Male,25,Bachelors,1,69,96,47,66,5.0,1,13,Rural,HR Executive,20288,0 +52400,Female,40,High School,2,74,41,84,9,3.0,2,16,Rural,HR Executive,88724,0 +52401,Female,31,Diploma,11,49,48,74,50,9.0,0,26,Rural,Software Engineer,98647,0 +52402,Female,46,Diploma,12,69,88,44,83,0.0,3,95,Urban,ML Engineer,134054,1 +52403,Female,39,Masters,7,54,3,25,21,2.0,3,57,Urban,ML Engineer,35699,0 +52404,Male,38,Diploma,18,11,59,92,6,0.0,1,4,Rural,ML Engineer,93750,0 +52405,Male,24,Bachelors,16,53,14,37,66,4.0,2,13,Urban,HR Executive,130560,0 +52406,Male,45,Masters,12,48,49,41,65,1.0,0,55,Urban,Manager,75990,0 +52407,Female,27,Masters,4,15,11,75,54,0.0,3,82,Urban,HR Executive,58974,0 +52408,Female,21,High School,2,35,69,16,72,4.0,2,0,Rural,Data Analyst,126608,0 +52409,Male,45,Diploma,19,36,38,90,41,5.0,4,29,Urban,HR Executive,113142,0 +52410,Female,36,Masters,1,10,10,40,34,4.0,0,19,Semi-Urban,Data Analyst,101451,0 +52411,Male,35,Diploma,4,27,15,6,83,7.0,0,31,Semi-Urban,HR Executive,63878,0 +52412,Female,55,Masters,7,80,75,79,15,3.0,2,72,Urban,Data Analyst,76070,1 +52413,Male,21,High School,17,88,26,35,32,9.0,7,66,Semi-Urban,HR Executive,54315,0 +52414,Female,38,PhD,15,22,30,13,94,9.0,1,71,Rural,ML Engineer,38049,0 +52415,Male,28,Masters,7,36,42,58,86,9.0,6,34,Rural,ML Engineer,131237,0 +52416,Male,38,High School,17,32,37,82,84,6.0,1,36,Urban,Software Engineer,33878,0 +52417,Female,38,High School,16,99,3,82,0,5.0,2,57,Urban,Software Engineer,21436,1 +52418,Male,48,Bachelors,15,93,39,27,19,3.0,4,12,Urban,HR Executive,95784,0 +52419,Female,46,Diploma,0,71,51,56,47,1.0,5,9,Rural,HR Executive,133864,0 +52420,Male,56,Diploma,12,64,41,63,32,5.0,3,60,Urban,ML Engineer,88441,0 +52421,Other,46,Bachelors,15,54,84,16,84,2.0,7,33,Urban,HR Executive,47938,0 +52422,Female,26,Bachelors,15,88,32,92,90,4.0,2,89,Urban,Manager,127406,1 +52423,Male,56,Diploma,1,15,45,77,88,7.0,3,71,Urban,Manager,65070,0 +52424,Female,30,Diploma,11,69,84,80,24,0.0,4,76,Urban,HR Executive,108043,1 +52425,Male,23,Bachelors,14,85,63,68,12,3.0,0,28,Urban,HR Executive,37787,1 +52426,Female,37,High School,3,4,53,33,15,0.0,7,27,Semi-Urban,Software Engineer,106442,0 +52427,Male,43,Bachelors,14,41,48,84,54,9.0,5,22,Urban,Data Analyst,87325,0 +52428,Male,48,Masters,13,92,46,98,46,3.0,6,84,Rural,ML Engineer,22593,1 +52429,Other,21,Bachelors,8,92,83,27,2,9.0,6,7,Rural,Data Analyst,111516,0 +52430,Male,44,High School,15,18,43,25,3,6.0,6,94,Urban,Data Analyst,89857,0 +52431,Male,54,Masters,8,23,16,23,24,1.0,2,26,Rural,Software Engineer,93918,0 +52432,Male,41,Masters,13,99,0,59,43,6.0,4,44,Urban,Data Analyst,137454,0 +52433,Female,53,High School,1,73,72,61,73,1.0,2,34,Urban,Software Engineer,108557,0 +52434,Male,29,Diploma,5,94,70,60,38,0.0,6,47,Semi-Urban,Software Engineer,87522,1 +52435,Male,47,Bachelors,6,41,60,18,12,8.0,4,79,Urban,Data Analyst,116793,0 +52436,Male,35,High School,3,21,95,53,28,4.0,6,51,Urban,Data Analyst,89540,0 +52437,Male,36,Bachelors,5,71,17,54,81,1.0,0,27,Rural,ML Engineer,138982,0 +52438,Female,50,Diploma,11,30,65,89,96,1.0,7,27,Urban,Software Engineer,41643,0 +52439,Female,53,Bachelors,8,43,16,79,33,5.0,6,12,Urban,Manager,66013,0 +52440,Female,34,Masters,10,27,6,42,22,4.0,1,49,Rural,HR Executive,94810,0 +52441,Male,59,Bachelors,4,91,79,37,47,0.0,0,15,Urban,HR Executive,81596,0 +52442,Male,42,Bachelors,11,51,64,15,46,8.0,3,53,Rural,Software Engineer,102284,0 +52443,Female,58,Diploma,17,22,60,18,33,5.0,0,58,Semi-Urban,Software Engineer,86873,0 +52444,Other,48,High School,5,18,35,25,3,8.0,3,36,Urban,Manager,104374,0 +52445,Female,38,Masters,8,6,78,92,33,2.0,3,68,Rural,ML Engineer,28986,1 +52446,Male,41,High School,16,30,58,6,95,9.0,4,92,Rural,Manager,98710,0 +52447,Female,52,Bachelors,10,95,13,86,93,1.0,3,16,Urban,Software Engineer,117793,0 +52448,Male,58,Masters,13,62,37,26,21,3.0,3,62,Urban,Manager,116098,0 +52449,Female,30,Bachelors,18,42,86,71,78,1.0,4,95,Urban,Manager,100986,1 +52450,Other,22,Masters,6,91,10,1,31,0.0,2,43,Semi-Urban,Data Analyst,71987,0 +52451,Other,26,Diploma,0,79,90,53,42,1.0,6,0,Urban,HR Executive,125268,0 +52452,Male,49,PhD,10,77,94,81,93,3.0,3,8,Urban,ML Engineer,27685,1 +52453,Male,37,Bachelors,4,53,72,21,93,6.0,7,42,Semi-Urban,Software Engineer,80470,0 +52454,Male,33,Diploma,10,21,3,65,65,8.0,5,23,Semi-Urban,Manager,141752,0 +52455,Male,43,High School,17,11,64,35,95,1.0,3,11,Urban,Data Analyst,114352,0 +52456,Male,34,High School,16,42,59,68,5,2.0,2,57,Urban,Manager,141799,0 +52457,Female,31,Bachelors,19,46,21,82,23,5.0,1,93,Urban,Software Engineer,60486,1 +52458,Male,47,Bachelors,6,80,91,91,35,7.0,7,22,Rural,Data Analyst,129346,1 +52459,Male,43,Diploma,18,81,85,79,66,5.0,6,69,Urban,Manager,64769,1 +52460,Male,52,Bachelors,9,32,27,0,89,1.0,2,20,Semi-Urban,HR Executive,121798,0 +52461,Other,31,Masters,16,92,18,92,95,3.0,2,35,Urban,Data Analyst,139165,0 +52462,Female,49,High School,14,23,90,47,54,0.0,6,40,Urban,Manager,135066,0 +52463,Female,50,Bachelors,12,4,87,13,84,0.0,2,9,Semi-Urban,Data Analyst,88749,0 +52464,Male,22,Bachelors,16,43,9,2,30,9.0,7,65,Semi-Urban,HR Executive,77713,0 +52465,Female,44,Masters,19,99,33,24,32,0.0,2,31,Rural,Software Engineer,100230,0 +52466,Male,59,Bachelors,0,5,72,37,77,8.0,2,20,Semi-Urban,Data Analyst,39524,0 +52467,Female,39,High School,13,66,68,9,39,4.0,4,14,Urban,Data Analyst,38159,0 +52468,Female,55,High School,13,74,97,55,5,1.0,7,3,Semi-Urban,HR Executive,101834,0 +52469,Female,58,Masters,7,89,51,2,63,4.0,2,98,Rural,Software Engineer,86312,0 +52470,Male,33,Bachelors,4,86,27,70,75,0.0,0,23,Rural,ML Engineer,89261,0 +52471,Male,36,High School,19,21,77,32,87,3.0,4,61,Rural,ML Engineer,62114,0 +52472,Female,26,Diploma,1,42,72,82,65,8.0,7,52,Urban,ML Engineer,43560,1 +52473,Female,21,Bachelors,13,64,26,42,55,4.0,1,70,Rural,Manager,71254,0 +52474,Male,37,Bachelors,2,91,58,44,14,0.0,6,44,Urban,Data Analyst,99201,1 +52475,Male,52,Masters,14,95,78,65,52,5.0,4,27,Urban,ML Engineer,31352,1 +52476,Male,55,Masters,16,69,38,52,94,5.0,0,99,Urban,Software Engineer,149472,1 +52477,Male,56,Masters,13,34,52,51,2,5.0,1,70,Semi-Urban,ML Engineer,78508,0 +52478,Female,53,High School,4,14,3,19,18,5.0,6,44,Semi-Urban,HR Executive,61745,0 +52479,Female,46,Masters,19,0,47,24,47,0.0,4,73,Urban,Data Analyst,53456,0 +52480,Male,47,Diploma,13,78,78,55,45,4.0,6,92,Rural,Data Analyst,74279,1 +52481,Female,34,Bachelors,11,70,38,96,38,9.0,3,91,Rural,Manager,56441,1 +52482,Male,28,Diploma,17,1,77,46,50,3.0,5,48,Rural,HR Executive,34465,0 +52483,Male,28,Diploma,17,25,13,63,45,3.0,2,66,Urban,ML Engineer,99113,0 +52484,Male,52,Bachelors,7,20,40,80,62,8.0,6,56,Urban,ML Engineer,98507,0 +52485,Male,44,Masters,13,40,21,9,20,4.0,5,73,Semi-Urban,HR Executive,70085,0 +52486,Female,41,Bachelors,19,31,41,4,45,1.0,4,51,Urban,Software Engineer,57422,0 +52487,Male,57,Bachelors,1,61,58,94,16,2.0,6,7,Urban,Data Analyst,146337,0 +52488,Male,36,Bachelors,8,31,43,69,42,2.0,6,0,Urban,ML Engineer,39297,0 +52489,Male,39,Bachelors,10,0,93,5,15,7.0,1,52,Rural,ML Engineer,70458,0 +52490,Other,41,High School,4,99,49,86,59,1.0,4,77,Urban,Software Engineer,132713,1 +52491,Female,56,Diploma,13,3,74,21,1,1.0,4,82,Semi-Urban,ML Engineer,45898,0 +52492,Female,49,Bachelors,15,29,90,67,94,0.0,0,61,Urban,ML Engineer,56990,1 +52493,Male,48,Masters,2,70,51,69,28,8.0,4,80,Urban,Manager,48721,1 +52494,Male,41,Diploma,1,53,71,7,11,6.0,0,87,Urban,Data Analyst,53101,0 +52495,Male,45,Bachelors,10,60,38,39,40,7.0,7,60,Semi-Urban,HR Executive,37959,0 +52496,Male,56,Masters,8,18,86,72,63,7.0,6,99,Urban,Manager,122538,1 +52497,Male,35,Bachelors,2,18,69,59,21,0.0,1,65,Urban,HR Executive,83783,0 +52498,Male,27,Masters,15,45,6,98,10,4.0,4,13,Rural,HR Executive,44491,0 +52499,Male,29,Masters,5,15,94,38,50,1.0,3,3,Semi-Urban,Software Engineer,127457,0 +52500,Female,49,Bachelors,18,48,65,46,79,3.0,7,46,Semi-Urban,Data Analyst,79690,0 +52501,Female,29,Diploma,8,1,74,37,95,2.0,2,57,Semi-Urban,Data Analyst,51158,0 +52502,Female,48,Bachelors,12,90,25,87,47,1.0,6,73,Urban,ML Engineer,50230,1 +52503,Male,57,Diploma,5,2,66,59,2,5.0,2,45,Urban,Software Engineer,65989,0 +52504,Male,51,Bachelors,1,8,15,50,23,6.0,1,97,Urban,Software Engineer,63747,0 +52505,Male,32,Bachelors,4,76,11,0,29,3.0,5,32,Semi-Urban,Manager,35964,0 +52506,Other,47,Diploma,12,81,28,25,54,6.0,7,0,Rural,Software Engineer,91424,0 +52507,Male,35,Masters,6,91,18,66,12,5.0,2,30,Semi-Urban,Software Engineer,38938,0 +52508,Male,31,Bachelors,15,90,66,36,72,6.0,7,15,Rural,HR Executive,54190,0 +52509,Male,36,Diploma,2,86,74,66,66,6.0,6,17,Urban,Manager,123358,1 +52510,Male,57,Bachelors,7,28,64,21,60,8.0,1,8,Rural,Data Analyst,141193,0 +52511,Male,23,High School,18,58,68,4,54,4.0,3,58,Semi-Urban,HR Executive,104742,0 +52512,Female,44,Bachelors,5,55,15,5,27,4.0,2,19,Urban,Software Engineer,24756,0 +52513,Male,21,High School,10,30,97,53,52,8.0,1,69,Urban,Manager,104670,1 +52514,Male,27,High School,11,19,21,67,50,2.0,0,56,Urban,HR Executive,143943,0 +52515,Male,53,Bachelors,15,85,32,21,20,7.0,7,86,Rural,Software Engineer,135453,0 +52516,Male,54,Diploma,18,2,72,67,0,2.0,7,89,Rural,Data Analyst,115714,0 +52517,Male,25,PhD,2,87,35,3,64,2.0,4,5,Semi-Urban,HR Executive,128100,0 +52518,Male,59,Masters,18,12,70,64,55,4.0,6,46,Urban,HR Executive,64495,0 +52519,Female,40,Masters,6,90,48,71,86,5.0,2,64,Urban,Data Analyst,84888,1 +52520,Male,48,Bachelors,3,43,10,16,50,8.0,1,12,Urban,HR Executive,39510,0 +52521,Male,56,High School,14,23,86,31,93,9.0,2,83,Semi-Urban,HR Executive,62959,0 +52522,Male,30,High School,9,29,64,7,37,1.0,7,14,Rural,HR Executive,22094,0 +52523,Female,48,Masters,14,28,51,87,23,9.0,1,49,Urban,Software Engineer,43653,0 +52524,Female,51,Bachelors,14,53,44,97,68,2.0,7,71,Urban,HR Executive,115860,1 +52525,Female,41,Bachelors,19,41,46,33,64,1.0,1,47,Urban,HR Executive,147017,0 +52526,Female,44,Bachelors,16,61,83,33,46,5.0,5,70,Urban,Data Analyst,64538,1 +52527,Male,25,Bachelors,13,32,59,68,40,3.0,1,63,Urban,HR Executive,132643,0 +52528,Female,24,Bachelors,0,58,23,1,16,0.0,2,73,Urban,Software Engineer,25423,0 +52529,Male,51,Diploma,1,32,47,13,54,2.0,3,77,Urban,Software Engineer,70504,0 +52530,Male,45,Diploma,3,21,23,27,71,3.0,1,94,Semi-Urban,Software Engineer,43733,0 +52531,Female,51,Bachelors,7,17,12,76,51,4.0,2,25,Rural,HR Executive,60941,0 +52532,Female,32,Bachelors,13,72,35,95,67,1.0,0,88,Rural,HR Executive,92707,1 +52533,Male,44,Bachelors,11,7,31,8,89,9.0,6,4,Urban,Software Engineer,102362,0 +52534,Other,54,High School,15,25,90,63,31,3.0,2,51,Urban,Manager,102797,0 +52535,Male,47,Bachelors,8,35,31,38,51,3.0,4,97,Semi-Urban,Manager,117592,0 +52536,Male,43,PhD,2,75,1,50,95,4.0,0,22,Urban,Manager,64850,0 +52537,Male,42,Diploma,9,95,1,13,70,8.0,3,25,Urban,Manager,52083,0 +52538,Male,42,Masters,4,3,58,50,9,9.0,3,71,Urban,Manager,113335,0 +52539,Other,29,Bachelors,9,50,26,72,55,9.0,7,5,Urban,Data Analyst,22303,0 +52540,Female,50,Bachelors,17,51,67,17,31,8.0,2,55,Semi-Urban,Manager,55223,0 +52541,Male,37,High School,5,35,74,69,35,6.0,7,40,Semi-Urban,Software Engineer,144684,0 +52542,Female,44,High School,2,14,88,63,8,1.0,4,48,Urban,Manager,111285,0 +52543,Female,22,Bachelors,17,11,25,87,87,9.0,1,13,Rural,ML Engineer,110621,0 +52544,Female,21,Masters,15,26,52,68,60,0.0,6,66,Urban,Software Engineer,87129,0 +52545,Male,41,High School,9,92,26,22,84,8.0,4,53,Urban,Manager,112928,0 +52546,Female,51,Diploma,13,64,19,17,44,8.0,3,24,Semi-Urban,ML Engineer,86312,0 +52547,Male,22,Bachelors,14,87,74,20,26,4.0,1,43,Rural,HR Executive,142368,0 +52548,Other,34,Bachelors,11,66,27,43,1,6.0,7,59,Urban,HR Executive,27247,0 +52549,Female,39,Diploma,14,44,77,18,81,2.0,7,62,Urban,HR Executive,25403,0 +52550,Male,23,Diploma,1,95,64,9,28,2.0,0,34,Urban,HR Executive,28029,0 +52551,Male,22,Bachelors,4,78,58,5,90,6.0,0,44,Urban,Software Engineer,133726,0 +52552,Male,22,Masters,4,72,99,31,4,7.0,7,34,Rural,HR Executive,140363,1 +52553,Female,31,Masters,13,78,24,68,40,7.0,5,79,Urban,Software Engineer,149051,1 +52554,Male,46,Masters,6,65,32,57,27,7.0,6,26,Urban,Manager,72320,0 +52555,Female,54,Diploma,15,98,11,55,18,5.0,0,54,Urban,Software Engineer,127544,0 +52556,Female,37,Bachelors,10,60,58,88,68,7.0,6,9,Rural,Software Engineer,48672,0 +52557,Male,32,Bachelors,0,66,32,69,25,0.0,3,49,Urban,Manager,94907,0 +52558,Female,21,Masters,9,28,17,10,7,4.0,5,0,Urban,HR Executive,46402,0 +52559,Male,48,Masters,7,66,12,0,68,5.0,4,73,Urban,Data Analyst,66928,0 +52560,Male,27,Bachelors,12,8,91,58,58,0.0,5,56,Urban,HR Executive,129022,0 +52561,Male,27,Masters,2,69,80,97,12,9.0,1,87,Urban,Data Analyst,90389,1 +52562,Female,57,Bachelors,16,71,8,42,62,5.0,3,47,Semi-Urban,Data Analyst,117230,0 +52563,Other,34,Diploma,16,27,17,67,93,6.0,0,28,Semi-Urban,Software Engineer,92295,0 +52564,Female,59,PhD,8,14,96,64,70,1.0,3,63,Rural,Data Analyst,91087,0 +52565,Male,52,Bachelors,2,25,74,94,94,3.0,5,83,Urban,Data Analyst,60600,1 +52566,Male,34,Masters,11,57,47,94,9,7.0,7,92,Urban,HR Executive,60498,1 +52567,Female,49,Bachelors,17,59,99,89,45,5.0,3,39,Rural,HR Executive,96268,1 +52568,Male,46,Bachelors,6,35,83,20,29,1.0,6,53,Urban,Data Analyst,25250,0 +52569,Female,55,High School,2,65,0,36,17,1.0,5,50,Semi-Urban,ML Engineer,88827,0 +52570,Male,26,Diploma,11,63,13,95,78,0.0,5,33,Urban,Manager,81010,0 +52571,Male,32,Masters,15,43,33,55,8,2.0,2,37,Urban,Data Analyst,118824,0 +52572,Male,53,Masters,10,93,1,72,95,8.0,2,36,Rural,HR Executive,112551,0 +52573,Female,26,Masters,18,85,53,73,51,1.0,2,73,Urban,HR Executive,24737,1 +52574,Male,44,Bachelors,2,42,91,76,74,4.0,6,36,Semi-Urban,HR Executive,128627,1 +52575,Male,24,Masters,1,88,77,88,29,1.0,0,6,Urban,HR Executive,81090,1 +52576,Male,41,Masters,9,4,71,13,18,0.0,4,62,Urban,ML Engineer,132882,0 +52577,Male,34,High School,11,32,89,38,71,4.0,7,46,Semi-Urban,Manager,130323,0 +52578,Other,41,Bachelors,12,44,21,14,30,0.0,7,33,Semi-Urban,Data Analyst,43512,0 +52579,Male,43,Bachelors,14,63,29,43,47,4.0,0,35,Urban,Manager,113562,0 +52580,Male,59,Bachelors,7,95,83,67,59,9.0,7,27,Semi-Urban,HR Executive,42304,1 +52581,Male,58,Masters,3,8,88,42,73,9.0,1,39,Rural,Software Engineer,126285,0 +52582,Male,39,Bachelors,17,92,85,57,72,6.0,4,74,Urban,HR Executive,74275,1 +52583,Male,39,Diploma,4,64,86,64,34,0.0,4,43,Semi-Urban,Data Analyst,37648,1 +52584,Male,31,Bachelors,0,37,85,93,70,3.0,4,2,Urban,ML Engineer,68115,0 +52585,Female,34,Masters,13,40,15,3,43,4.0,2,18,Urban,ML Engineer,28379,0 +52586,Male,32,Masters,4,75,61,71,37,7.0,6,61,Urban,Data Analyst,59493,1 +52587,Female,49,Diploma,13,68,7,2,59,7.0,5,74,Urban,Manager,69845,0 +52588,Female,21,High School,13,28,39,99,88,0.0,0,83,Urban,Manager,137644,1 +52589,Female,44,Masters,15,85,89,78,82,4.0,5,56,Urban,Software Engineer,107365,1 +52590,Male,32,Masters,17,32,30,20,86,9.0,5,8,Rural,Data Analyst,140218,0 +52591,Other,49,PhD,18,58,36,89,11,6.0,4,42,Rural,Data Analyst,27718,0 +52592,Female,52,Diploma,13,93,85,36,67,5.0,3,2,Urban,Software Engineer,113637,0 +52593,Male,31,High School,3,38,36,9,46,0.0,5,27,Semi-Urban,Software Engineer,30792,0 +52594,Female,46,Masters,5,42,60,45,44,7.0,1,70,Urban,Software Engineer,65411,0 +52595,Male,57,Bachelors,14,28,18,58,44,5.0,2,58,Urban,Manager,118665,0 +52596,Male,55,Bachelors,16,82,45,42,0,5.0,4,21,Semi-Urban,Data Analyst,58491,0 +52597,Female,32,Diploma,13,3,10,59,11,9.0,2,37,Urban,HR Executive,78738,0 +52598,Female,48,High School,17,64,59,66,19,4.0,6,93,Urban,Data Analyst,132143,1 +52599,Female,54,Diploma,16,64,0,72,66,9.0,3,54,Urban,Data Analyst,149336,0 +52600,Female,37,Diploma,12,34,70,62,17,8.0,7,53,Urban,Data Analyst,57988,0 +52601,Male,40,High School,7,35,19,81,33,7.0,2,87,Rural,Data Analyst,123275,0 +52602,Male,49,PhD,15,3,18,20,55,4.0,5,50,Semi-Urban,Data Analyst,101639,0 +52603,Female,46,Diploma,0,10,1,96,69,9.0,6,74,Semi-Urban,Manager,115835,0 +52604,Male,32,Bachelors,12,31,57,50,24,7.0,6,34,Rural,HR Executive,21363,0 +52605,Male,32,Masters,14,16,12,22,61,3.0,7,15,Rural,Data Analyst,61495,0 +52606,Male,49,Bachelors,4,31,94,85,53,6.0,3,51,Urban,HR Executive,28356,1 +52607,Male,44,Diploma,17,35,6,58,11,9.0,3,18,Urban,ML Engineer,108250,0 +52608,Male,28,Diploma,10,94,91,65,29,5.0,0,94,Urban,Software Engineer,94855,1 +52609,Male,48,Diploma,10,34,73,0,96,1.0,0,31,Urban,Manager,115564,0 +52610,Male,51,Diploma,9,54,15,1,60,2.0,2,48,Semi-Urban,Software Engineer,138647,0 +52611,Male,28,Diploma,7,64,47,6,78,9.0,7,13,Urban,HR Executive,78852,0 +52612,Male,57,High School,17,72,0,46,98,9.0,4,68,Semi-Urban,Software Engineer,82214,0 +52613,Male,26,Bachelors,18,15,44,2,38,6.0,3,54,Rural,Manager,72922,0 +52614,Female,44,Bachelors,7,75,18,1,4,0.0,7,21,Urban,ML Engineer,123007,0 +52615,Female,33,Masters,6,30,47,37,14,6.0,2,85,Urban,ML Engineer,20889,0 +52616,Male,59,High School,13,36,95,59,84,1.0,1,0,Urban,HR Executive,106994,0 +52617,Female,28,Masters,15,98,24,4,32,5.0,2,62,Semi-Urban,Manager,27492,0 +52618,Male,23,Bachelors,6,52,97,7,67,7.0,0,46,Urban,ML Engineer,127692,0 +52619,Male,28,Masters,3,14,22,34,63,4.0,5,80,Semi-Urban,Manager,31863,0 +52620,Male,48,Bachelors,13,55,11,34,63,7.0,3,91,Urban,HR Executive,91183,0 +52621,Female,58,Bachelors,18,93,11,62,43,6.0,1,95,Urban,ML Engineer,97353,1 +52622,Male,47,Diploma,7,16,49,43,87,9.0,6,66,Urban,HR Executive,123522,0 +52623,Male,47,Masters,12,67,12,34,19,1.0,7,21,Urban,HR Executive,49697,0 +52624,Female,40,High School,12,8,67,48,29,8.0,5,51,Semi-Urban,Software Engineer,50338,0 +52625,Female,48,Diploma,17,9,7,28,10,0.0,3,23,Rural,HR Executive,51386,0 +52626,Male,46,Bachelors,11,16,51,71,91,2.0,0,10,Urban,HR Executive,100081,0 +52627,Female,32,Bachelors,18,25,45,50,86,1.0,4,34,Urban,ML Engineer,140717,0 +52628,Male,34,Diploma,0,47,35,71,84,1.0,0,81,Semi-Urban,ML Engineer,103921,0 +52629,Female,22,Masters,0,21,95,11,38,0.0,6,78,Rural,HR Executive,62861,0 +52630,Male,58,Bachelors,16,68,24,41,65,8.0,1,10,Semi-Urban,HR Executive,135496,0 +52631,Male,39,Masters,15,97,14,11,87,5.0,6,47,Urban,Software Engineer,119393,0 +52632,Female,46,High School,11,57,45,6,0,8.0,4,43,Rural,Manager,126717,0 +52633,Female,31,Masters,13,65,46,54,73,0.0,7,53,Urban,Manager,26462,0 +52634,Other,39,Bachelors,1,56,87,86,79,6.0,4,71,Urban,Software Engineer,73111,1 +52635,Male,42,Diploma,2,2,80,93,72,8.0,4,67,Urban,HR Executive,135574,1 +52636,Female,52,Bachelors,13,29,61,54,36,2.0,1,85,Urban,HR Executive,91221,0 +52637,Female,41,PhD,15,4,52,64,54,3.0,7,98,Semi-Urban,Data Analyst,66005,0 +52638,Male,53,Masters,3,51,78,58,18,1.0,5,28,Semi-Urban,Manager,108336,0 +52639,Female,52,Diploma,1,78,14,85,46,0.0,4,45,Urban,HR Executive,76483,0 +52640,Male,38,High School,10,37,85,2,39,9.0,1,32,Semi-Urban,ML Engineer,131227,0 +52641,Male,47,Masters,11,30,55,46,84,3.0,3,61,Rural,Data Analyst,147405,0 +52642,Male,25,Diploma,18,51,2,31,74,7.0,1,22,Urban,Manager,55317,0 +52643,Male,32,High School,17,36,22,59,81,6.0,6,28,Urban,HR Executive,79629,0 +52644,Male,31,Diploma,3,73,61,76,49,4.0,5,72,Rural,HR Executive,27247,1 +52645,Male,40,High School,2,39,51,66,39,3.0,2,10,Urban,Software Engineer,44961,0 +52646,Female,54,Masters,15,0,76,3,44,0.0,4,98,Semi-Urban,Data Analyst,84218,0 +52647,Male,59,Bachelors,8,21,58,37,9,5.0,7,18,Semi-Urban,HR Executive,128025,0 +52648,Female,30,Diploma,8,8,65,67,35,9.0,4,14,Semi-Urban,Manager,100322,0 +52649,Male,28,High School,18,50,2,42,57,3.0,4,57,Semi-Urban,Manager,45750,0 +52650,Male,39,PhD,16,92,78,20,14,0.0,0,11,Semi-Urban,Data Analyst,65417,0 +52651,Male,44,High School,19,10,28,53,0,2.0,7,28,Urban,Data Analyst,88112,0 +52652,Male,59,Masters,8,72,2,45,27,1.0,0,79,Rural,HR Executive,119435,0 +52653,Male,21,Diploma,11,97,29,69,6,6.0,1,3,Rural,Manager,110264,0 +52654,Male,38,Diploma,6,52,31,51,35,2.0,6,23,Semi-Urban,HR Executive,119726,0 +52655,Male,52,Diploma,0,2,66,39,11,9.0,7,61,Urban,Manager,91841,0 +52656,Female,57,PhD,13,5,69,10,6,8.0,6,78,Semi-Urban,HR Executive,23639,0 +52657,Male,27,Bachelors,17,96,44,81,61,5.0,5,40,Urban,Manager,98325,1 +52658,Male,48,Masters,15,93,48,49,14,6.0,2,67,Rural,Manager,149505,1 +52659,Male,45,Diploma,8,71,97,61,62,5.0,4,19,Urban,Software Engineer,114942,1 +52660,Male,39,Masters,1,97,65,69,77,1.0,3,78,Urban,Manager,113204,1 +52661,Male,23,Masters,15,97,57,70,11,7.0,3,37,Semi-Urban,Manager,23339,1 +52662,Male,32,Bachelors,13,66,65,81,85,6.0,4,82,Urban,HR Executive,34938,1 +52663,Male,21,Bachelors,5,60,98,12,62,9.0,1,40,Semi-Urban,Software Engineer,113202,0 +52664,Female,34,Bachelors,7,67,48,95,36,0.0,7,33,Urban,Software Engineer,95657,1 +52665,Female,58,PhD,19,33,24,15,19,7.0,4,19,Urban,Manager,48511,0 +52666,Male,22,Masters,6,2,69,38,41,7.0,6,10,Urban,HR Executive,71201,0 +52667,Male,44,Masters,5,42,75,41,0,1.0,7,61,Rural,HR Executive,123644,0 +52668,Female,35,Bachelors,18,70,7,49,71,6.0,4,53,Urban,Data Analyst,59001,0 +52669,Female,45,High School,11,24,51,50,35,4.0,0,1,Urban,Manager,48189,0 +52670,Female,54,Bachelors,0,5,88,66,15,5.0,4,60,Urban,Software Engineer,64894,0 +52671,Male,35,Bachelors,1,7,33,57,16,4.0,5,8,Urban,HR Executive,125273,0 +52672,Female,33,Bachelors,8,92,33,91,59,5.0,1,91,Rural,HR Executive,89943,1 +52673,Female,45,Bachelors,12,52,52,73,0,6.0,6,59,Rural,Manager,70954,0 +52674,Female,22,PhD,13,36,11,31,92,3.0,5,24,Urban,Software Engineer,51170,0 +52675,Female,54,Bachelors,11,42,96,22,5,0.0,6,2,Urban,HR Executive,72704,0 +52676,Female,53,Bachelors,16,65,82,53,24,3.0,1,14,Urban,HR Executive,47917,0 +52677,Male,55,Masters,0,2,4,33,47,9.0,1,83,Urban,HR Executive,148871,0 +52678,Female,32,Diploma,7,49,97,13,97,8.0,5,18,Urban,Software Engineer,117465,0 +52679,Female,53,Bachelors,18,59,38,19,62,6.0,0,83,Rural,Data Analyst,37820,0 +52680,Female,55,Bachelors,9,80,17,19,88,5.0,1,70,Urban,Software Engineer,131397,0 +52681,Female,32,Bachelors,10,97,28,50,11,4.0,6,95,Urban,HR Executive,48977,1 +52682,Male,32,Bachelors,13,79,59,16,99,4.0,2,91,Rural,ML Engineer,132532,1 +52683,Male,22,Bachelors,14,88,59,40,76,8.0,1,64,Urban,Software Engineer,126525,1 +52684,Male,58,Masters,4,58,93,24,55,8.0,1,24,Semi-Urban,ML Engineer,60483,0 +52685,Female,49,Bachelors,6,41,83,65,95,9.0,2,11,Semi-Urban,Manager,71557,0 +52686,Male,42,Bachelors,8,25,51,38,81,5.0,0,2,Urban,Data Analyst,137735,0 +52687,Male,36,Diploma,7,12,75,64,63,6.0,2,79,Urban,Software Engineer,116976,0 +52688,Male,30,Diploma,18,5,53,20,75,5.0,3,16,Urban,Manager,39993,0 +52689,Male,57,Bachelors,6,73,90,58,29,9.0,7,34,Semi-Urban,Manager,35712,1 +52690,Male,37,Diploma,1,80,89,95,56,9.0,3,17,Rural,ML Engineer,134587,1 +52691,Female,56,High School,2,94,33,1,88,9.0,5,52,Urban,Software Engineer,77429,0 +52692,Male,35,Diploma,0,61,0,29,81,9.0,4,5,Urban,Software Engineer,44622,0 +52693,Female,51,Bachelors,9,58,4,16,19,4.0,2,38,Semi-Urban,Manager,56834,0 +52694,Female,43,Bachelors,1,58,25,62,33,8.0,7,17,Rural,Software Engineer,49771,0 +52695,Male,51,Bachelors,14,41,29,66,66,1.0,5,94,Rural,Manager,52380,0 +52696,Male,57,Bachelors,10,51,91,31,13,7.0,0,37,Rural,HR Executive,103445,0 +52697,Female,42,Bachelors,10,22,66,24,88,8.0,7,17,Urban,ML Engineer,36985,0 +52698,Male,27,High School,15,99,92,88,73,3.0,1,3,Semi-Urban,ML Engineer,66502,1 +52699,Male,30,Diploma,19,31,24,91,40,0.0,1,2,Rural,Data Analyst,36545,0 +52700,Female,22,Bachelors,14,14,10,60,36,3.0,2,27,Semi-Urban,ML Engineer,33621,0 +52701,Female,50,Bachelors,3,77,21,8,4,2.0,1,64,Urban,Data Analyst,27473,0 +52702,Male,47,Diploma,6,82,74,69,33,0.0,7,80,Urban,Data Analyst,89653,1 +52703,Female,54,Bachelors,13,44,26,64,54,8.0,6,60,Urban,ML Engineer,50099,0 +52704,Male,32,Diploma,1,56,40,69,99,1.0,2,28,Urban,Software Engineer,59708,0 +52705,Male,55,Bachelors,9,1,90,46,46,4.0,1,64,Urban,Manager,37970,0 +52706,Male,31,Bachelors,0,27,57,30,64,9.0,1,31,Semi-Urban,Data Analyst,32451,0 +52707,Male,30,Bachelors,18,1,96,10,52,4.0,1,16,Urban,HR Executive,39622,0 +52708,Male,39,Diploma,4,49,63,45,98,4.0,4,94,Urban,Data Analyst,48923,1 +52709,Male,44,Bachelors,13,12,66,73,29,5.0,5,69,Urban,Software Engineer,78943,0 +52710,Male,32,High School,15,23,96,67,42,7.0,1,20,Urban,HR Executive,47069,0 +52711,Female,59,Bachelors,10,57,71,11,2,1.0,1,91,Semi-Urban,Data Analyst,134588,0 +52712,Other,59,Masters,5,35,86,75,74,3.0,1,29,Urban,Data Analyst,80868,0 +52713,Male,41,Bachelors,11,26,65,81,10,9.0,7,29,Urban,Software Engineer,116654,0 +52714,Male,42,Masters,1,50,55,64,32,1.0,3,3,Rural,HR Executive,65538,0 +52715,Male,36,Diploma,12,69,24,10,25,2.0,6,18,Urban,ML Engineer,132029,0 +52716,Female,39,Masters,18,35,47,70,85,1.0,5,3,Urban,Manager,106891,0 +52717,Female,51,Bachelors,2,15,82,76,32,1.0,0,88,Urban,Software Engineer,110830,1 +52718,Male,33,Masters,12,78,29,69,33,0.0,2,74,Urban,Data Analyst,140746,1 +52719,Male,55,Bachelors,4,54,67,33,35,5.0,6,15,Semi-Urban,Software Engineer,124053,0 +52720,Female,32,Masters,9,71,12,99,82,1.0,6,98,Semi-Urban,Software Engineer,45164,1 +52721,Male,58,High School,11,44,74,1,73,5.0,6,97,Urban,HR Executive,149123,0 +52722,Female,23,Diploma,17,69,46,34,50,8.0,2,49,Rural,Manager,125610,0 +52723,Female,26,Masters,2,22,40,93,12,7.0,7,41,Urban,ML Engineer,134251,0 +52724,Female,43,Bachelors,16,26,26,93,75,9.0,2,98,Rural,Manager,105489,1 +52725,Male,47,Masters,19,23,93,2,93,8.0,3,82,Urban,Data Analyst,72913,0 +52726,Female,42,Bachelors,1,64,28,26,48,3.0,5,36,Urban,Software Engineer,47984,0 +52727,Male,21,High School,16,43,59,16,51,4.0,1,84,Semi-Urban,Manager,64105,0 +52728,Female,32,Masters,16,86,26,1,44,7.0,0,85,Urban,Data Analyst,114922,0 +52729,Female,53,Bachelors,8,91,21,58,29,1.0,5,38,Urban,Data Analyst,89427,0 +52730,Male,25,Bachelors,15,60,80,38,94,4.0,7,75,Urban,Data Analyst,93415,1 +52731,Male,33,Masters,14,17,30,0,82,0.0,7,32,Urban,Data Analyst,89003,0 +52732,Male,26,Diploma,7,60,60,55,42,0.0,7,20,Urban,Data Analyst,85549,0 +52733,Male,44,Diploma,18,44,41,99,27,3.0,2,9,Urban,Software Engineer,131468,0 +52734,Female,51,Diploma,16,28,41,18,81,9.0,5,74,Semi-Urban,Manager,97771,0 +52735,Female,30,Bachelors,15,5,4,35,39,1.0,2,93,Urban,Software Engineer,123791,0 +52736,Male,54,High School,0,37,22,16,19,7.0,7,41,Rural,HR Executive,109330,0 +52737,Male,59,Diploma,4,8,24,0,84,2.0,3,98,Urban,ML Engineer,41912,0 +52738,Male,45,Diploma,1,36,1,89,21,9.0,7,44,Semi-Urban,ML Engineer,25499,0 +52739,Male,58,Diploma,16,39,77,70,47,1.0,5,61,Urban,ML Engineer,102603,1 +52740,Female,54,Diploma,18,69,79,21,99,2.0,2,23,Semi-Urban,Software Engineer,57547,0 +52741,Male,27,Masters,9,46,37,88,4,5.0,0,90,Semi-Urban,Manager,54309,1 +52742,Female,39,Masters,4,83,11,83,88,9.0,6,65,Urban,Data Analyst,59205,1 +52743,Female,47,Masters,6,96,73,78,27,7.0,7,98,Rural,Data Analyst,93989,1 +52744,Female,27,Masters,19,59,22,56,34,7.0,2,41,Urban,Software Engineer,44579,0 +52745,Male,25,High School,5,36,83,87,74,1.0,5,59,Semi-Urban,ML Engineer,133144,1 +52746,Female,45,High School,6,86,6,1,58,0.0,1,75,Urban,Data Analyst,112415,0 +52747,Female,29,Bachelors,7,49,28,73,9,1.0,7,30,Semi-Urban,HR Executive,141040,0 +52748,Female,27,Diploma,17,89,15,21,85,1.0,7,37,Urban,Software Engineer,68875,0 +52749,Male,42,Diploma,4,19,35,68,74,2.0,7,62,Urban,ML Engineer,140287,0 +52750,Male,28,Diploma,15,89,45,24,30,5.0,3,8,Semi-Urban,Data Analyst,85912,0 +52751,Female,36,High School,3,80,22,61,88,9.0,5,3,Urban,Data Analyst,102358,0 +52752,Male,25,Diploma,6,13,80,46,98,4.0,1,6,Urban,Software Engineer,67901,0 +52753,Male,26,Bachelors,15,67,95,22,13,4.0,0,22,Rural,HR Executive,81525,0 +52754,Male,50,High School,0,51,96,33,18,0.0,4,21,Semi-Urban,Data Analyst,132059,0 +52755,Male,28,Diploma,18,95,72,24,83,7.0,2,28,Semi-Urban,HR Executive,144697,0 +52756,Male,47,Bachelors,15,49,34,29,84,3.0,6,47,Rural,ML Engineer,47755,0 +52757,Male,23,Diploma,6,4,10,13,42,2.0,2,72,Urban,Manager,135313,0 +52758,Male,57,Diploma,0,99,3,40,27,8.0,1,1,Urban,Manager,91793,0 +52759,Male,38,High School,8,36,0,90,21,0.0,7,79,Urban,Manager,95165,0 +52760,Female,56,Masters,4,30,56,95,17,8.0,3,57,Urban,ML Engineer,139628,0 +52761,Male,40,Diploma,13,48,64,68,55,2.0,0,72,Urban,Software Engineer,22951,1 +52762,Female,37,Masters,9,3,87,36,85,5.0,0,47,Urban,HR Executive,65008,0 +52763,Male,44,Diploma,13,6,68,28,85,1.0,6,85,Rural,HR Executive,146185,0 +52764,Female,55,Diploma,13,40,29,26,16,5.0,6,30,Urban,Software Engineer,95932,0 +52765,Male,28,Masters,5,44,59,52,22,7.0,7,27,Urban,Software Engineer,33484,0 +52766,Male,25,Bachelors,18,26,22,6,36,4.0,7,32,Urban,HR Executive,143705,0 +52767,Female,24,Bachelors,5,33,20,63,5,6.0,4,16,Semi-Urban,Data Analyst,61459,0 +52768,Male,56,Diploma,19,70,9,93,47,0.0,7,40,Rural,Data Analyst,122271,0 +52769,Male,43,PhD,14,71,42,59,18,7.0,1,13,Urban,Software Engineer,49708,0 +52770,Male,21,Bachelors,5,71,11,61,7,7.0,6,36,Urban,ML Engineer,67738,0 +52771,Male,27,Bachelors,11,45,82,59,71,8.0,6,92,Urban,Data Analyst,55392,1 +52772,Female,37,PhD,3,28,41,95,88,3.0,6,63,Urban,ML Engineer,114093,0 +52773,Female,48,Bachelors,0,88,31,15,70,0.0,3,72,Semi-Urban,Data Analyst,114874,0 +52774,Male,27,Masters,0,80,3,76,9,2.0,7,97,Semi-Urban,Manager,120429,1 +52775,Male,37,Bachelors,13,88,68,67,45,7.0,3,11,Semi-Urban,ML Engineer,72580,0 +52776,Male,55,High School,6,82,4,2,79,6.0,1,26,Urban,Data Analyst,141443,0 +52777,Male,52,High School,11,41,21,31,19,0.0,5,0,Urban,ML Engineer,100811,0 +52778,Male,45,Masters,6,49,12,31,91,0.0,7,17,Semi-Urban,HR Executive,104306,0 +52779,Female,37,PhD,9,24,28,33,4,7.0,1,0,Urban,Data Analyst,94038,0 +52780,Male,53,Bachelors,17,91,39,53,84,7.0,2,77,Urban,ML Engineer,99869,1 +52781,Female,48,Bachelors,13,37,31,92,26,1.0,4,55,Urban,ML Engineer,94677,0 +52782,Male,54,Diploma,2,17,38,31,99,0.0,7,75,Semi-Urban,Manager,49665,0 +52783,Female,31,Bachelors,17,89,46,80,25,8.0,4,34,Rural,Software Engineer,131776,1 +52784,Female,30,Masters,4,58,90,23,36,3.0,1,44,Urban,Software Engineer,32839,0 +52785,Male,53,Masters,1,25,80,99,38,2.0,3,5,Urban,ML Engineer,40568,0 +52786,Female,25,High School,17,10,88,95,57,0.0,5,5,Urban,ML Engineer,93128,0 +52787,Male,58,Bachelors,3,74,19,84,87,2.0,0,49,Urban,ML Engineer,96495,0 +52788,Male,43,High School,15,25,21,0,89,7.0,5,52,Semi-Urban,ML Engineer,64990,0 +52789,Male,42,High School,18,98,31,51,68,2.0,1,98,Rural,ML Engineer,39738,1 +52790,Male,25,Bachelors,2,75,97,1,88,3.0,2,5,Urban,HR Executive,75267,0 +52791,Male,45,Bachelors,10,31,30,64,28,7.0,1,81,Rural,Data Analyst,27042,0 +52792,Male,53,Bachelors,3,25,65,26,15,8.0,6,47,Urban,Manager,147508,0 +52793,Male,57,Bachelors,11,89,89,69,92,7.0,4,29,Rural,ML Engineer,76551,1 +52794,Male,25,PhD,2,54,94,93,34,4.0,2,52,Urban,Manager,30157,1 +52795,Female,27,Diploma,12,5,76,79,42,7.0,2,15,Urban,Manager,26203,0 +52796,Female,22,Bachelors,16,96,28,0,64,4.0,0,59,Rural,Data Analyst,40170,0 +52797,Male,32,Bachelors,5,39,15,98,9,2.0,5,57,Urban,Data Analyst,65601,0 +52798,Female,37,Diploma,14,90,12,51,26,2.0,1,83,Urban,Software Engineer,128033,0 +52799,Female,35,Bachelors,14,86,15,17,68,8.0,1,68,Rural,Software Engineer,70924,0 +52800,Male,54,Bachelors,15,46,11,59,75,4.0,5,16,Urban,ML Engineer,36603,0 +52801,Male,47,Bachelors,5,79,18,25,89,0.0,6,72,Urban,Manager,69269,0 +52802,Female,24,Bachelors,10,70,45,81,62,6.0,3,93,Urban,Data Analyst,70497,1 +52803,Female,25,Masters,10,24,47,65,24,1.0,3,32,Urban,Data Analyst,23420,0 +52804,Female,39,Diploma,17,85,46,81,89,7.0,4,84,Semi-Urban,Data Analyst,93720,1 +52805,Male,32,Bachelors,4,83,42,99,50,4.0,7,24,Urban,Manager,65937,1 +52806,Female,43,Diploma,14,1,80,41,56,1.0,0,38,Semi-Urban,Software Engineer,102555,0 +52807,Male,40,Diploma,19,48,1,11,62,9.0,2,70,Rural,Software Engineer,101925,0 +52808,Female,21,High School,4,33,37,25,40,2.0,0,38,Urban,Data Analyst,23052,0 +52809,Female,35,Bachelors,9,61,50,48,80,9.0,2,40,Urban,ML Engineer,115342,0 +52810,Male,41,Bachelors,3,3,19,58,41,6.0,4,52,Urban,Manager,112123,0 +52811,Female,30,PhD,7,74,66,17,70,8.0,2,2,Urban,ML Engineer,64996,0 +52812,Female,57,PhD,1,92,3,65,62,9.0,1,54,Urban,Software Engineer,74935,0 +52813,Male,21,Diploma,10,7,53,49,14,7.0,4,7,Urban,ML Engineer,147095,0 +52814,Male,45,PhD,1,2,81,75,13,9.0,0,23,Semi-Urban,Software Engineer,76002,0 +52815,Female,30,Masters,12,93,68,2,41,9.0,1,73,Urban,Software Engineer,69509,0 +52816,Other,40,Bachelors,19,2,82,97,87,5.0,4,56,Urban,Software Engineer,108314,0 +52817,Female,32,Masters,18,83,63,94,70,8.0,2,49,Semi-Urban,ML Engineer,36841,1 +52818,Male,47,Masters,11,92,37,59,94,2.0,3,33,Semi-Urban,ML Engineer,103236,0 +52819,Male,56,High School,18,78,88,72,62,9.0,4,40,Urban,HR Executive,73577,1 +52820,Male,32,Masters,14,30,76,11,13,3.0,0,96,Urban,HR Executive,69029,0 +52821,Female,29,Masters,2,62,25,92,53,9.0,3,15,Semi-Urban,ML Engineer,137615,0 +52822,Female,35,Bachelors,8,6,47,69,61,7.0,4,71,Semi-Urban,ML Engineer,81038,0 +52823,Female,59,Bachelors,18,4,85,46,69,9.0,4,82,Urban,HR Executive,38453,0 +52824,Female,53,Diploma,16,28,8,46,23,2.0,6,35,Semi-Urban,HR Executive,76688,0 +52825,Male,25,PhD,19,51,93,14,70,7.0,7,40,Rural,Manager,25487,0 +52826,Male,23,Bachelors,3,31,71,90,5,0.0,3,78,Urban,HR Executive,90699,1 +52827,Female,29,Masters,6,26,25,71,8,7.0,7,23,Urban,Manager,73028,0 +52828,Female,58,Bachelors,12,38,40,81,10,7.0,3,26,Urban,HR Executive,57645,0 +52829,Male,45,Masters,15,20,0,72,72,1.0,3,55,Semi-Urban,HR Executive,58879,0 +52830,Male,52,Bachelors,2,81,65,76,56,7.0,5,36,Urban,HR Executive,80177,1 +52831,Male,35,Bachelors,9,69,59,49,37,2.0,7,65,Rural,Data Analyst,134827,1 +52832,Male,37,High School,3,44,83,19,84,9.0,2,31,Semi-Urban,ML Engineer,75635,0 +52833,Male,59,High School,11,70,85,54,38,9.0,1,27,Semi-Urban,ML Engineer,134703,1 +52834,Male,43,Masters,13,60,62,79,81,2.0,2,29,Rural,Manager,135624,0 +52835,Female,36,Masters,2,4,50,42,41,6.0,5,6,Semi-Urban,Manager,44571,0 +52836,Male,55,High School,14,41,5,83,84,9.0,4,46,Rural,Software Engineer,127006,0 +52837,Other,38,Bachelors,0,15,69,95,88,7.0,0,13,Urban,Manager,108575,0 +52838,Male,39,Bachelors,3,54,31,17,12,8.0,0,70,Urban,HR Executive,135233,0 +52839,Male,52,Bachelors,7,85,50,14,73,3.0,4,13,Urban,HR Executive,66637,0 +52840,Male,34,PhD,6,12,73,21,44,1.0,4,38,Rural,Data Analyst,132133,0 +52841,Male,34,Bachelors,10,90,34,29,7,8.0,1,81,Semi-Urban,Software Engineer,109879,0 +52842,Male,45,High School,13,97,65,33,43,7.0,0,99,Urban,HR Executive,61251,1 +52843,Male,42,Bachelors,2,0,9,10,4,2.0,5,96,Urban,ML Engineer,116328,0 +52844,Male,27,Bachelors,13,26,90,48,97,2.0,6,8,Semi-Urban,ML Engineer,70608,0 +52845,Male,31,Bachelors,2,7,65,67,5,3.0,2,24,Rural,Manager,54856,0 +52846,Male,57,High School,8,29,20,70,45,3.0,6,66,Urban,Manager,61942,0 +52847,Male,39,Masters,11,37,65,40,13,3.0,5,8,Rural,Data Analyst,67555,0 +52848,Female,24,Masters,0,40,63,69,11,3.0,7,18,Urban,Manager,53110,0 +52849,Female,30,Masters,16,85,95,6,0,9.0,5,44,Semi-Urban,Software Engineer,149468,0 +52850,Male,24,Diploma,19,31,77,81,36,1.0,4,24,Urban,Manager,133476,0 +52851,Female,43,Bachelors,0,9,58,58,59,4.0,3,99,Urban,ML Engineer,94560,0 +52852,Male,50,Bachelors,18,23,53,35,94,4.0,4,82,Semi-Urban,Software Engineer,97536,0 +52853,Male,58,Diploma,8,87,9,90,1,2.0,3,0,Urban,ML Engineer,84433,0 +52854,Male,32,Bachelors,7,35,67,58,34,2.0,1,62,Urban,Data Analyst,22948,0 +52855,Female,26,PhD,9,89,28,63,97,7.0,1,23,Semi-Urban,Software Engineer,115271,0 +52856,Male,38,Bachelors,0,45,20,1,4,3.0,1,27,Urban,ML Engineer,24879,0 +52857,Male,53,Diploma,6,29,72,9,72,7.0,0,3,Urban,Software Engineer,64266,0 +52858,Male,34,Bachelors,17,81,93,2,66,0.0,7,53,Semi-Urban,Data Analyst,66145,0 +52859,Male,24,High School,3,12,5,89,4,2.0,0,33,Rural,Data Analyst,129941,0 +52860,Female,33,Bachelors,7,59,5,7,68,8.0,0,0,Semi-Urban,ML Engineer,143026,0 +52861,Female,36,Diploma,2,20,26,81,2,1.0,4,56,Rural,ML Engineer,141216,0 +52862,Male,51,Bachelors,11,62,3,72,66,4.0,0,91,Semi-Urban,ML Engineer,25517,0 +52863,Female,43,Bachelors,6,65,90,4,79,7.0,2,37,Urban,HR Executive,89109,0 +52864,Female,41,Diploma,9,84,74,14,66,0.0,5,82,Urban,Software Engineer,112943,1 +52865,Female,46,Bachelors,9,79,28,37,36,1.0,4,15,Semi-Urban,Manager,31483,0 +52866,Male,55,High School,8,37,57,97,11,0.0,5,90,Rural,ML Engineer,132870,1 +52867,Male,37,High School,2,89,28,0,91,1.0,3,68,Urban,HR Executive,36417,0 +52868,Female,49,Bachelors,12,6,23,63,62,1.0,3,69,Rural,Manager,140996,0 +52869,Female,58,Masters,7,40,80,96,36,4.0,6,27,Rural,Manager,54653,1 +52870,Male,57,Bachelors,2,32,81,14,74,4.0,2,79,Urban,Manager,44358,0 +52871,Male,57,Diploma,0,23,88,63,16,6.0,6,28,Urban,Software Engineer,34466,0 +52872,Male,57,Bachelors,3,17,68,92,58,9.0,1,62,Urban,Manager,89861,1 +52873,Male,49,Bachelors,14,61,49,19,48,6.0,7,84,Semi-Urban,HR Executive,32913,0 +52874,Male,51,PhD,9,68,44,28,46,0.0,3,69,Semi-Urban,Data Analyst,112688,0 +52875,Male,25,Masters,14,91,27,10,97,9.0,5,96,Rural,Data Analyst,128415,0 +52876,Male,47,Masters,6,50,44,85,76,2.0,7,97,Urban,Software Engineer,30111,1 +52877,Male,56,Bachelors,0,45,57,40,59,1.0,3,8,Semi-Urban,HR Executive,22389,0 +52878,Male,37,Masters,11,98,13,93,10,0.0,1,75,Urban,Data Analyst,93877,1 +52879,Male,29,Bachelors,18,57,56,10,55,6.0,4,21,Urban,ML Engineer,48292,0 +52880,Male,32,High School,2,61,90,35,97,1.0,3,35,Rural,Data Analyst,146785,0 +52881,Male,35,Bachelors,19,34,20,96,65,7.0,2,27,Rural,Software Engineer,111929,0 +52882,Male,43,Bachelors,5,57,14,28,60,3.0,4,73,Urban,Software Engineer,102705,0 +52883,Male,54,Bachelors,15,95,17,83,65,6.0,5,17,Rural,Manager,26906,0 +52884,Female,41,Bachelors,16,61,17,63,41,3.0,1,83,Urban,ML Engineer,101320,0 +52885,Female,29,Bachelors,3,82,27,32,55,1.0,1,97,Urban,Manager,65234,0 +52886,Male,22,High School,13,32,55,16,89,9.0,1,61,Urban,HR Executive,27612,0 +52887,Male,30,Bachelors,3,61,2,65,81,8.0,0,37,Semi-Urban,Software Engineer,88532,0 +52888,Male,28,Masters,1,11,25,95,72,5.0,5,7,Rural,ML Engineer,122287,0 +52889,Female,32,Masters,11,10,61,50,10,1.0,3,88,Semi-Urban,Manager,89884,0 +52890,Male,58,Bachelors,14,44,21,58,84,6.0,6,88,Semi-Urban,Software Engineer,142661,0 +52891,Female,29,Bachelors,14,84,23,73,68,1.0,2,69,Urban,HR Executive,87109,1 +52892,Female,55,Bachelors,1,14,62,27,54,6.0,4,23,Semi-Urban,HR Executive,37719,0 +52893,Female,59,Masters,0,93,65,41,72,7.0,6,69,Urban,Data Analyst,51861,1 +52894,Other,28,Diploma,11,99,78,21,11,3.0,3,86,Rural,ML Engineer,88266,1 +52895,Female,43,Bachelors,9,57,36,89,41,2.0,7,88,Urban,Software Engineer,100093,1 +52896,Male,25,Diploma,17,30,47,21,40,6.0,1,68,Urban,Data Analyst,76078,0 +52897,Female,34,Diploma,13,53,23,69,54,9.0,3,4,Semi-Urban,Data Analyst,63131,0 +52898,Male,37,PhD,1,20,53,81,4,4.0,6,49,Urban,HR Executive,30593,0 +52899,Male,42,Diploma,13,87,84,84,16,8.0,7,68,Urban,Manager,30688,1 +52900,Male,50,Bachelors,18,34,83,0,1,5.0,2,28,Rural,Data Analyst,137243,0 +52901,Other,25,Bachelors,7,81,37,35,99,0.0,7,88,Semi-Urban,Data Analyst,27978,1 +52902,Female,44,Bachelors,15,87,62,87,0,0.0,2,17,Urban,Software Engineer,106688,1 +52903,Male,49,PhD,11,0,77,5,48,8.0,7,24,Urban,HR Executive,100305,0 +52904,Female,53,Diploma,4,50,17,70,89,3.0,4,24,Rural,ML Engineer,138121,0 +52905,Male,39,High School,8,34,51,48,10,4.0,6,13,Urban,ML Engineer,103001,0 +52906,Male,30,Diploma,6,56,35,69,21,2.0,4,96,Rural,HR Executive,63193,1 +52907,Male,35,Bachelors,9,36,0,81,31,9.0,1,79,Rural,Data Analyst,28217,0 +52908,Male,41,High School,9,20,24,93,96,4.0,1,21,Urban,HR Executive,104829,0 +52909,Male,45,Bachelors,15,68,61,74,92,1.0,3,14,Semi-Urban,Data Analyst,38492,0 +52910,Female,41,PhD,12,63,47,15,64,2.0,2,8,Urban,ML Engineer,88585,0 +52911,Male,21,Bachelors,10,41,6,23,14,8.0,6,95,Urban,ML Engineer,133582,0 +52912,Male,43,High School,1,6,90,85,35,0.0,3,55,Urban,Software Engineer,57398,1 +52913,Male,37,Bachelors,4,97,55,51,44,1.0,5,7,Rural,ML Engineer,102937,0 +52914,Female,34,PhD,4,66,85,84,65,1.0,0,70,Urban,Manager,63215,1 +52915,Other,56,Masters,12,34,64,96,2,3.0,5,19,Urban,ML Engineer,57063,0 +52916,Female,54,PhD,9,89,38,50,82,6.0,6,10,Urban,ML Engineer,36318,0 +52917,Male,41,Diploma,18,87,87,94,74,5.0,4,50,Semi-Urban,Manager,114723,1 +52918,Male,36,Bachelors,18,44,35,73,13,9.0,3,82,Semi-Urban,Manager,64341,0 +52919,Male,39,Masters,18,79,73,78,29,9.0,2,8,Semi-Urban,Data Analyst,148990,1 +52920,Male,21,PhD,17,32,84,67,77,6.0,1,87,Urban,Manager,45370,1 +52921,Female,32,High School,3,48,51,84,94,7.0,5,26,Semi-Urban,Data Analyst,47836,0 +52922,Male,48,Bachelors,12,18,67,85,17,5.0,1,5,Semi-Urban,Manager,23116,0 +52923,Female,48,Diploma,9,22,76,95,38,0.0,0,15,Semi-Urban,Data Analyst,88907,0 +52924,Female,49,High School,9,52,50,96,18,3.0,4,59,Semi-Urban,ML Engineer,42960,1 +52925,Male,45,Bachelors,1,17,57,84,24,8.0,1,13,Urban,Data Analyst,58977,0 +52926,Male,55,Diploma,16,6,92,22,43,2.0,6,28,Urban,Software Engineer,103439,0 +52927,Male,48,High School,13,61,8,1,76,6.0,7,2,Urban,HR Executive,24241,0 +52928,Male,46,Masters,12,64,50,96,64,7.0,0,29,Urban,Manager,66942,1 +52929,Female,54,Masters,12,92,37,54,63,3.0,7,36,Urban,HR Executive,87938,0 +52930,Male,43,Diploma,9,70,75,45,36,1.0,2,64,Urban,Manager,142418,1 +52931,Female,55,Masters,8,94,23,47,60,7.0,4,37,Urban,Data Analyst,116599,0 +52932,Male,34,Diploma,10,50,22,42,25,0.0,0,47,Semi-Urban,HR Executive,136671,0 +52933,Male,21,Bachelors,10,14,96,84,49,5.0,2,49,Urban,HR Executive,110025,1 +52934,Female,41,Bachelors,11,48,51,30,69,2.0,7,7,Urban,Manager,132654,0 +52935,Male,55,Bachelors,5,46,92,78,50,6.0,6,89,Urban,Data Analyst,122943,1 +52936,Male,46,Diploma,2,93,81,12,97,2.0,0,26,Urban,HR Executive,56842,0 +52937,Male,42,Bachelors,17,94,40,99,75,1.0,4,60,Urban,Software Engineer,46243,1 +52938,Male,33,Diploma,0,43,48,69,39,9.0,6,25,Urban,ML Engineer,62545,0 +52939,Female,42,Diploma,7,18,69,30,11,4.0,7,86,Semi-Urban,Data Analyst,104967,0 +52940,Other,52,Bachelors,16,4,59,12,54,8.0,5,9,Urban,ML Engineer,59067,0 +52941,Male,32,High School,16,94,5,51,56,1.0,1,42,Urban,HR Executive,56121,0 +52942,Male,36,Bachelors,9,53,85,43,15,4.0,1,20,Urban,ML Engineer,96463,0 +52943,Male,35,High School,12,79,54,75,18,9.0,7,36,Semi-Urban,Software Engineer,48000,1 +52944,Male,49,Diploma,2,1,49,86,53,3.0,1,46,Urban,ML Engineer,100241,0 +52945,Male,28,High School,17,56,73,88,50,2.0,3,46,Urban,ML Engineer,59550,1 +52946,Male,44,Masters,10,96,86,2,12,1.0,3,58,Urban,ML Engineer,130639,1 +52947,Female,35,Masters,15,23,19,2,47,1.0,6,0,Urban,HR Executive,116243,0 +52948,Female,34,Masters,12,86,79,0,66,6.0,5,77,Urban,Data Analyst,27510,1 +52949,Male,22,Bachelors,15,75,55,44,91,9.0,3,70,Rural,HR Executive,101159,1 +52950,Male,44,Bachelors,12,23,37,28,22,8.0,1,46,Urban,Software Engineer,73204,0 +52951,Male,52,Bachelors,18,53,37,80,7,8.0,6,52,Rural,ML Engineer,118939,0 +52952,Male,52,Bachelors,14,12,48,50,60,0.0,0,98,Rural,Data Analyst,98343,0 +52953,Female,36,PhD,4,16,1,67,19,2.0,4,20,Urban,ML Engineer,134769,0 +52954,Male,41,Bachelors,13,7,28,95,61,3.0,1,5,Semi-Urban,Software Engineer,41981,0 +52955,Male,23,High School,6,37,19,65,8,7.0,2,42,Urban,Software Engineer,94078,0 +52956,Male,24,Diploma,17,2,11,86,39,0.0,2,58,Semi-Urban,Software Engineer,95032,0 +52957,Female,30,Masters,14,96,14,9,17,0.0,1,64,Rural,Manager,52839,0 +52958,Male,21,Diploma,0,34,2,4,63,5.0,6,51,Semi-Urban,Data Analyst,88194,0 +52959,Female,23,High School,4,27,78,69,21,1.0,2,66,Urban,HR Executive,140268,0 +52960,Male,27,Bachelors,1,30,94,79,62,9.0,6,87,Semi-Urban,HR Executive,89777,1 +52961,Female,46,High School,14,71,86,49,59,3.0,3,61,Urban,Data Analyst,39801,1 +52962,Male,46,Masters,11,66,52,85,59,5.0,3,24,Urban,Manager,106242,0 +52963,Female,34,Masters,6,31,38,67,12,9.0,2,87,Semi-Urban,HR Executive,44099,0 +52964,Female,26,Masters,10,68,95,89,2,2.0,6,42,Urban,ML Engineer,133693,1 +52965,Male,35,PhD,6,25,53,60,24,4.0,7,94,Rural,HR Executive,145615,0 +52966,Male,55,Bachelors,17,35,40,12,12,1.0,2,16,Rural,HR Executive,75722,0 +52967,Male,30,High School,19,75,45,11,23,4.0,1,0,Urban,Data Analyst,33824,0 +52968,Female,31,Diploma,9,84,50,60,9,7.0,0,92,Urban,HR Executive,128968,1 +52969,Female,52,High School,5,10,73,94,34,7.0,2,13,Urban,ML Engineer,83966,0 +52970,Female,48,Diploma,2,55,55,87,94,7.0,3,5,Urban,ML Engineer,20729,0 +52971,Female,25,Masters,2,98,57,15,58,2.0,4,60,Semi-Urban,Manager,145586,0 +52972,Male,45,Masters,0,28,56,49,76,0.0,0,84,Rural,HR Executive,135985,0 +52973,Male,47,PhD,17,73,82,69,33,4.0,5,28,Urban,Software Engineer,104182,1 +52974,Male,33,Masters,12,92,58,74,25,7.0,4,33,Urban,HR Executive,83468,1 +52975,Male,58,Masters,18,60,92,78,51,1.0,5,16,Urban,Data Analyst,88564,1 +52976,Male,41,PhD,18,84,43,79,43,0.0,5,13,Urban,Manager,85340,0 +52977,Female,31,Diploma,18,2,33,99,57,5.0,1,28,Urban,Software Engineer,141114,0 +52978,Female,44,High School,14,90,21,57,76,9.0,2,7,Urban,HR Executive,127381,0 +52979,Female,46,Bachelors,1,45,23,31,80,0.0,0,63,Rural,Manager,145795,0 +52980,Male,28,Diploma,4,46,2,72,53,5.0,4,27,Semi-Urban,Data Analyst,99849,0 +52981,Male,24,PhD,1,90,96,85,18,4.0,4,30,Urban,Manager,148719,1 +52982,Male,33,PhD,5,55,61,78,64,0.0,7,48,Urban,Software Engineer,83834,1 +52983,Male,59,Bachelors,16,92,9,98,92,9.0,0,55,Semi-Urban,Software Engineer,135252,1 +52984,Male,51,Bachelors,7,4,6,76,22,2.0,2,52,Urban,HR Executive,146676,0 +52985,Male,49,High School,15,70,94,36,9,7.0,5,49,Semi-Urban,Software Engineer,54697,1 +52986,Male,25,Bachelors,9,62,89,96,0,6.0,2,7,Urban,ML Engineer,32964,1 +52987,Female,58,Diploma,8,45,89,32,44,1.0,3,74,Urban,Manager,98022,0 +52988,Male,32,Bachelors,2,80,72,84,28,3.0,3,62,Rural,Software Engineer,118830,1 +52989,Male,26,Bachelors,11,53,21,29,10,1.0,0,0,Urban,Software Engineer,23086,0 +52990,Female,33,Masters,6,32,57,9,37,3.0,7,39,Urban,HR Executive,32168,0 +52991,Female,37,Diploma,12,49,59,64,26,8.0,5,89,Urban,Manager,99111,1 +52992,Male,45,PhD,6,97,4,94,16,9.0,6,6,Urban,Manager,115160,0 +52993,Male,28,Masters,8,26,59,38,75,0.0,1,12,Urban,Software Engineer,86337,0 +52994,Female,57,Bachelors,6,13,9,33,74,7.0,4,69,Rural,ML Engineer,73263,0 +52995,Male,24,Bachelors,11,3,72,33,56,4.0,4,12,Urban,HR Executive,75665,0 +52996,Female,27,Masters,8,60,33,65,51,5.0,6,32,Urban,Data Analyst,84106,0 +52997,Male,53,Bachelors,0,58,22,52,69,5.0,0,29,Urban,Manager,126753,0 +52998,Male,32,Diploma,3,85,50,99,79,2.0,2,19,Urban,ML Engineer,53872,1 +52999,Male,57,Bachelors,1,35,94,15,38,0.0,5,93,Rural,HR Executive,126594,1 +53000,Male,28,High School,4,35,92,56,30,2.0,2,37,Semi-Urban,HR Executive,48069,0 +53001,Female,32,Masters,9,61,73,28,73,3.0,2,92,Urban,ML Engineer,27183,1 +53002,Female,45,High School,17,51,48,86,46,0.0,0,2,Urban,ML Engineer,87509,0 +53003,Female,41,Masters,0,79,70,57,93,8.0,2,80,Urban,Manager,109021,1 +53004,Male,52,Masters,9,39,62,5,63,0.0,2,17,Urban,Manager,49883,0 +53005,Female,48,Bachelors,12,87,10,97,24,8.0,0,68,Urban,Data Analyst,148180,1 +53006,Female,33,Diploma,4,86,55,49,86,2.0,6,96,Semi-Urban,HR Executive,59816,1 +53007,Male,48,High School,6,35,4,37,33,7.0,1,90,Urban,HR Executive,138906,0 +53008,Male,40,Bachelors,5,85,79,20,34,8.0,6,26,Urban,Data Analyst,43838,0 +53009,Male,35,High School,13,52,72,85,41,3.0,1,99,Semi-Urban,Manager,143540,1 +53010,Male,34,Bachelors,6,33,97,2,51,7.0,7,66,Urban,ML Engineer,27297,0 +53011,Female,28,Bachelors,17,7,19,57,1,0.0,7,36,Semi-Urban,HR Executive,71684,0 +53012,Male,46,Masters,11,8,54,44,74,5.0,5,31,Rural,ML Engineer,105316,0 +53013,Male,30,High School,15,50,0,57,29,8.0,5,69,Rural,Software Engineer,145694,0 +53014,Male,51,High School,0,62,27,80,9,7.0,7,84,Rural,Data Analyst,138117,1 +53015,Male,29,Bachelors,17,95,42,97,90,7.0,5,60,Urban,Data Analyst,102811,1 +53016,Male,26,Bachelors,0,71,81,1,43,5.0,7,12,Semi-Urban,Manager,42930,0 +53017,Male,28,Masters,13,16,98,19,42,2.0,3,15,Semi-Urban,HR Executive,145412,0 +53018,Male,54,Masters,2,7,25,60,80,8.0,7,60,Urban,ML Engineer,38673,0 +53019,Male,27,Bachelors,3,45,19,55,63,9.0,5,55,Semi-Urban,HR Executive,90447,0 +53020,Male,38,Bachelors,19,90,49,4,34,9.0,5,89,Semi-Urban,Data Analyst,84209,0 +53021,Female,39,Masters,13,32,67,94,84,6.0,3,5,Urban,Data Analyst,58506,0 +53022,Male,51,Bachelors,7,27,5,20,67,4.0,3,5,Rural,HR Executive,121295,0 +53023,Male,36,Bachelors,12,79,66,37,35,5.0,6,46,Urban,Software Engineer,54298,0 +53024,Female,49,Bachelors,9,8,25,81,54,5.0,7,42,Urban,Data Analyst,103752,0 +53025,Male,42,Masters,16,73,4,3,68,4.0,2,4,Urban,Data Analyst,68658,0 +53026,Male,42,Masters,4,90,44,63,90,9.0,4,12,Urban,HR Executive,89415,0 +53027,Male,32,Bachelors,2,93,57,78,57,7.0,5,36,Semi-Urban,ML Engineer,142560,1 +53028,Female,36,Diploma,11,19,2,52,73,1.0,5,44,Rural,Data Analyst,92015,0 +53029,Male,32,High School,19,13,50,55,69,3.0,1,51,Rural,Software Engineer,57534,0 +53030,Male,43,Diploma,5,2,36,53,14,4.0,0,93,Urban,Manager,100184,0 +53031,Male,37,PhD,4,4,37,62,41,6.0,2,24,Rural,HR Executive,26042,0 +53032,Male,52,Bachelors,15,5,67,5,43,2.0,4,59,Semi-Urban,Data Analyst,76083,0 +53033,Female,29,Bachelors,4,98,59,44,94,1.0,3,3,Urban,Manager,74839,0 +53034,Male,42,Masters,1,66,4,47,76,3.0,0,85,Rural,ML Engineer,132071,0 +53035,Male,40,High School,10,98,1,37,3,2.0,5,25,Rural,Manager,63118,0 +53036,Male,23,High School,6,80,47,5,44,1.0,0,74,Semi-Urban,Data Analyst,72276,0 +53037,Female,39,Masters,15,26,46,5,48,9.0,0,82,Urban,Manager,62769,0 +53038,Female,24,Bachelors,1,72,27,95,11,3.0,2,50,Urban,Data Analyst,125620,1 +53039,Male,48,Masters,15,30,51,12,33,3.0,2,6,Urban,HR Executive,39525,0 +53040,Other,31,Diploma,1,85,50,45,53,9.0,0,49,Urban,ML Engineer,23954,0 +53041,Male,27,Bachelors,12,48,60,31,76,6.0,4,5,Urban,ML Engineer,113554,0 +53042,Other,51,Masters,18,15,44,71,53,3.0,6,20,Semi-Urban,HR Executive,50682,0 +53043,Male,40,High School,12,76,6,4,60,0.0,4,32,Urban,HR Executive,41937,0 +53044,Other,46,High School,7,84,6,95,78,3.0,5,39,Urban,ML Engineer,115698,0 +53045,Male,30,Masters,15,60,20,62,10,2.0,1,57,Rural,Data Analyst,123308,0 +53046,Female,58,Diploma,19,89,83,65,14,6.0,4,0,Urban,Data Analyst,83975,0 +53047,Female,37,High School,17,39,11,19,49,3.0,7,9,Urban,Manager,113256,0 +53048,Female,55,Diploma,0,30,0,65,69,7.0,0,99,Urban,Software Engineer,132792,0 +53049,Female,30,Diploma,0,49,94,19,84,5.0,3,77,Urban,Software Engineer,112523,0 +53050,Male,42,Masters,1,42,25,82,6,4.0,6,91,Rural,ML Engineer,108811,1 +53051,Male,41,Diploma,4,91,14,63,82,2.0,3,52,Semi-Urban,Data Analyst,45753,0 +53052,Male,51,Bachelors,0,60,74,6,27,5.0,1,93,Urban,Data Analyst,20879,0 +53053,Female,38,Diploma,9,84,22,2,92,4.0,0,81,Semi-Urban,Manager,125993,0 +53054,Female,33,High School,10,13,46,34,89,0.0,6,31,Urban,Manager,115484,0 +53055,Male,33,Masters,16,83,89,3,41,4.0,5,5,Semi-Urban,HR Executive,68732,0 +53056,Male,21,Masters,7,86,1,75,90,5.0,4,84,Semi-Urban,Manager,118242,1 +53057,Male,44,High School,6,35,99,26,94,8.0,0,99,Urban,Software Engineer,141724,1 +53058,Female,30,Bachelors,5,42,41,36,51,4.0,1,9,Urban,Data Analyst,116874,0 +53059,Female,55,Masters,18,93,45,46,80,3.0,3,92,Semi-Urban,HR Executive,21970,1 +53060,Male,22,Bachelors,19,1,31,51,28,3.0,4,64,Urban,HR Executive,78351,0 +53061,Female,28,Masters,7,29,8,86,25,5.0,5,31,Urban,Manager,82913,0 +53062,Female,22,Bachelors,19,40,51,9,81,3.0,7,28,Urban,Software Engineer,147788,0 +53063,Male,57,Bachelors,15,48,30,36,14,6.0,4,49,Semi-Urban,ML Engineer,28091,0 +53064,Male,30,Diploma,14,36,19,39,71,1.0,7,38,Semi-Urban,ML Engineer,83889,0 +53065,Male,46,Bachelors,8,23,38,97,70,9.0,5,4,Urban,ML Engineer,54025,0 +53066,Male,29,Bachelors,9,46,21,6,41,0.0,6,48,Semi-Urban,Manager,56355,0 +53067,Female,56,Bachelors,6,38,66,25,88,1.0,5,39,Semi-Urban,Data Analyst,42471,0 +53068,Male,34,PhD,1,98,46,20,67,4.0,1,85,Rural,Manager,112682,1 +53069,Male,24,Masters,3,5,78,52,97,2.0,7,60,Rural,HR Executive,43080,0 +53070,Male,44,Bachelors,15,8,52,15,27,9.0,7,13,Urban,Data Analyst,80023,0 +53071,Male,42,Masters,9,76,54,21,48,6.0,7,2,Urban,Manager,96163,0 +53072,Female,52,Bachelors,7,91,81,10,52,9.0,5,82,Urban,ML Engineer,102183,1 +53073,Male,57,Bachelors,2,51,24,83,21,5.0,7,14,Urban,Software Engineer,139218,0 +53074,Female,26,Diploma,15,65,15,68,60,9.0,5,87,Urban,Manager,117324,0 +53075,Male,32,PhD,14,37,76,91,42,8.0,1,45,Urban,ML Engineer,43449,1 +53076,Male,47,Bachelors,12,99,90,22,23,6.0,7,88,Urban,Manager,24407,1 +53077,Female,55,Masters,5,88,41,0,28,5.0,3,58,Urban,Software Engineer,103854,0 +53078,Male,49,Diploma,10,81,95,44,44,2.0,1,88,Urban,ML Engineer,46648,1 +53079,Male,28,Masters,15,74,58,52,87,8.0,1,88,Semi-Urban,ML Engineer,24382,1 +53080,Other,22,Diploma,19,17,21,61,66,8.0,5,29,Urban,Software Engineer,103148,0 +53081,Male,25,High School,19,72,48,74,43,0.0,1,58,Urban,Software Engineer,83281,1 +53082,Male,21,Masters,19,45,10,40,53,2.0,3,39,Semi-Urban,Manager,107541,0 +53083,Male,30,Bachelors,13,87,54,10,64,8.0,1,9,Rural,HR Executive,142631,0 +53084,Female,50,Masters,18,73,63,83,70,4.0,4,52,Urban,Manager,105224,1 +53085,Male,57,High School,15,33,58,65,10,6.0,0,67,Urban,Manager,77210,0 +53086,Male,38,Diploma,3,68,66,39,79,8.0,1,75,Rural,HR Executive,66756,1 +53087,Female,51,High School,19,96,55,42,94,6.0,6,55,Urban,Software Engineer,145353,1 +53088,Male,23,Bachelors,6,81,98,40,93,3.0,6,84,Urban,Data Analyst,89502,1 +53089,Other,27,Bachelors,17,88,76,62,92,6.0,5,58,Urban,HR Executive,44416,1 +53090,Male,55,High School,15,58,40,56,69,3.0,7,15,Urban,ML Engineer,84729,0 +53091,Male,40,Bachelors,16,61,47,81,20,3.0,1,94,Urban,Manager,149377,1 +53092,Male,26,Masters,5,82,25,16,90,8.0,5,79,Urban,HR Executive,56765,0 +53093,Male,43,High School,13,9,8,26,20,6.0,7,4,Urban,HR Executive,106803,0 +53094,Male,44,Diploma,11,94,7,98,10,8.0,1,82,Urban,Manager,115277,1 +53095,Male,38,Bachelors,2,63,32,53,35,0.0,5,58,Rural,ML Engineer,35831,0 +53096,Male,25,Masters,10,47,12,52,91,4.0,5,18,Urban,ML Engineer,73455,0 +53097,Male,50,Diploma,16,11,29,49,52,2.0,4,57,Urban,Data Analyst,100712,0 +53098,Other,46,Masters,6,90,20,13,37,3.0,0,90,Rural,HR Executive,44829,0 +53099,Male,22,Bachelors,7,59,71,21,89,1.0,3,39,Semi-Urban,Software Engineer,34503,0 +53100,Male,25,Bachelors,0,31,9,21,87,2.0,5,86,Urban,HR Executive,26447,0 +53101,Female,41,Masters,18,53,79,80,49,4.0,1,19,Urban,Software Engineer,78911,0 +53102,Female,42,Bachelors,15,49,40,32,3,1.0,2,26,Semi-Urban,Software Engineer,111460,0 +53103,Female,53,Bachelors,14,62,10,81,78,0.0,5,11,Rural,ML Engineer,135913,0 +53104,Female,22,Bachelors,11,32,5,15,88,0.0,6,4,Urban,ML Engineer,107104,0 +53105,Other,59,Diploma,6,80,21,84,1,0.0,4,86,Rural,HR Executive,52453,1 +53106,Female,48,Masters,17,22,93,43,33,5.0,4,44,Rural,ML Engineer,106437,0 +53107,Female,59,High School,11,26,82,87,15,3.0,0,42,Urban,ML Engineer,29272,0 +53108,Male,46,Masters,2,31,82,40,25,5.0,6,38,Rural,Manager,117032,0 +53109,Female,28,Diploma,18,93,37,17,54,0.0,4,17,Urban,ML Engineer,118375,0 +53110,Male,32,High School,18,4,25,53,49,0.0,4,26,Urban,HR Executive,123101,0 +53111,Male,44,Diploma,16,85,70,86,82,8.0,6,34,Urban,ML Engineer,60220,1 +53112,Male,37,Bachelors,2,98,70,8,19,4.0,7,10,Semi-Urban,Data Analyst,49365,0 +53113,Male,59,High School,15,17,25,41,26,8.0,5,35,Urban,Manager,25484,0 +53114,Male,34,Diploma,7,89,95,52,24,5.0,7,61,Urban,Data Analyst,145209,1 +53115,Male,53,Bachelors,7,89,36,73,69,3.0,6,25,Rural,Manager,129272,0 +53116,Male,25,High School,19,63,17,19,89,3.0,1,20,Semi-Urban,HR Executive,54795,0 +53117,Male,57,Bachelors,1,32,82,0,3,2.0,6,40,Semi-Urban,HR Executive,136801,0 +53118,Female,30,Diploma,14,91,65,51,19,0.0,7,78,Urban,Software Engineer,65231,1 +53119,Male,46,Diploma,3,54,39,66,8,6.0,7,31,Semi-Urban,Manager,38082,0 +53120,Male,45,Bachelors,7,53,46,28,26,8.0,3,50,Rural,HR Executive,37370,0 +53121,Male,43,Masters,12,52,64,69,79,7.0,1,29,Urban,ML Engineer,49989,0 +53122,Female,41,High School,3,76,71,48,47,9.0,3,98,Urban,HR Executive,41248,1 +53123,Female,46,Bachelors,13,22,91,64,32,4.0,6,33,Semi-Urban,Data Analyst,138104,0 +53124,Female,32,Diploma,19,16,1,71,80,7.0,3,75,Urban,Software Engineer,134768,0 +53125,Male,40,High School,4,66,69,67,25,2.0,1,59,Semi-Urban,Software Engineer,72075,1 +53126,Male,31,Bachelors,16,93,16,82,50,3.0,3,1,Urban,Data Analyst,99063,0 +53127,Other,54,Bachelors,7,90,74,43,38,5.0,7,40,Rural,ML Engineer,37880,1 +53128,Male,37,Bachelors,3,70,71,87,10,6.0,1,88,Urban,Data Analyst,80527,1 +53129,Male,28,Bachelors,4,2,83,67,96,4.0,0,89,Urban,Data Analyst,30114,1 +53130,Male,55,Diploma,5,57,17,78,97,3.0,0,72,Urban,Software Engineer,59839,0 +53131,Other,52,Masters,2,31,94,1,50,3.0,3,32,Urban,HR Executive,63805,0 +53132,Male,39,Bachelors,7,2,18,85,95,6.0,2,88,Urban,Software Engineer,134357,0 +53133,Female,28,High School,6,94,74,99,56,6.0,6,73,Rural,ML Engineer,54084,1 +53134,Male,40,Bachelors,4,82,63,23,48,6.0,3,39,Semi-Urban,Software Engineer,45386,0 +53135,Female,36,Bachelors,9,55,23,53,31,9.0,3,6,Urban,HR Executive,111273,0 +53136,Male,39,Bachelors,8,3,68,15,0,7.0,6,11,Urban,ML Engineer,42005,0 +53137,Male,23,Bachelors,1,17,35,33,65,0.0,6,23,Rural,Manager,145547,0 +53138,Female,40,Bachelors,6,33,58,97,33,9.0,2,14,Semi-Urban,Software Engineer,80451,0 +53139,Male,39,Bachelors,16,65,82,92,57,8.0,1,22,Urban,Data Analyst,101897,1 +53140,Female,30,High School,7,55,87,29,42,6.0,0,42,Urban,Data Analyst,50435,0 +53141,Other,45,PhD,2,94,1,85,77,0.0,2,37,Semi-Urban,Data Analyst,92496,0 +53142,Male,38,Diploma,1,7,35,45,92,6.0,7,9,Urban,Data Analyst,120862,0 +53143,Male,48,Diploma,11,49,98,10,14,1.0,7,1,Urban,ML Engineer,98433,0 +53144,Female,39,Diploma,5,19,64,37,11,8.0,1,9,Urban,Software Engineer,83730,0 +53145,Female,56,Bachelors,2,81,44,50,35,3.0,4,32,Rural,Software Engineer,134980,0 +53146,Female,59,Masters,5,7,9,79,28,8.0,7,75,Urban,Manager,85095,0 +53147,Male,22,Bachelors,5,18,9,69,28,5.0,1,34,Urban,HR Executive,39645,0 +53148,Female,48,Masters,1,37,43,73,98,2.0,0,55,Semi-Urban,Manager,95194,0 +53149,Male,59,Bachelors,16,16,15,15,88,6.0,0,34,Urban,Manager,32584,0 +53150,Male,35,Bachelors,3,64,57,15,78,7.0,1,49,Urban,Manager,142212,0 +53151,Male,58,Masters,13,46,73,35,18,6.0,7,10,Rural,Software Engineer,34025,0 +53152,Female,37,High School,11,55,68,3,21,3.0,4,88,Urban,ML Engineer,109952,0 +53153,Male,57,Bachelors,3,38,25,61,58,0.0,0,38,Rural,Data Analyst,71765,0 +53154,Male,42,High School,4,87,65,50,64,9.0,5,95,Semi-Urban,Manager,140448,1 +53155,Male,35,High School,1,86,55,46,10,1.0,7,97,Urban,ML Engineer,120427,1 +53156,Male,32,Masters,6,71,14,59,8,0.0,3,69,Urban,Manager,129304,0 +53157,Female,21,Bachelors,9,47,71,28,24,2.0,2,35,Rural,ML Engineer,101911,0 +53158,Male,46,Diploma,10,46,23,56,66,3.0,7,96,Urban,Software Engineer,35946,0 +53159,Male,45,High School,18,78,45,62,56,5.0,0,14,Urban,Manager,146911,0 +53160,Female,52,Diploma,10,71,68,6,52,9.0,7,46,Rural,ML Engineer,66906,0 +53161,Female,23,Diploma,8,68,93,36,30,7.0,1,83,Semi-Urban,Manager,137664,1 +53162,Female,59,Bachelors,8,43,89,56,88,9.0,3,83,Urban,Software Engineer,116684,1 +53163,Female,47,High School,14,63,6,3,87,5.0,6,69,Semi-Urban,Data Analyst,100568,0 +53164,Male,52,High School,0,97,72,84,67,5.0,2,21,Rural,Manager,145653,1 +53165,Male,53,Diploma,4,69,24,68,12,8.0,3,21,Urban,Data Analyst,23878,0 +53166,Female,51,High School,18,82,28,15,99,7.0,5,33,Semi-Urban,Manager,134337,0 +53167,Male,58,Masters,17,88,33,72,61,8.0,4,68,Urban,Data Analyst,44212,1 +53168,Female,27,Masters,17,83,80,18,68,8.0,0,2,Urban,ML Engineer,107777,0 +53169,Female,53,Masters,10,85,45,60,31,5.0,5,68,Semi-Urban,Data Analyst,146555,1 +53170,Female,53,High School,7,70,73,13,84,6.0,3,53,Urban,Manager,100892,0 +53171,Female,48,Bachelors,9,57,73,14,40,9.0,7,9,Urban,ML Engineer,86823,0 +53172,Male,52,High School,7,83,0,34,77,8.0,7,36,Urban,Software Engineer,76374,0 +53173,Female,29,Bachelors,12,35,15,45,76,1.0,7,90,Urban,ML Engineer,129736,0 +53174,Female,38,PhD,6,78,34,48,75,3.0,0,14,Semi-Urban,HR Executive,35245,0 +53175,Female,36,PhD,5,32,24,27,13,7.0,7,7,Urban,Data Analyst,89785,0 +53176,Male,59,Diploma,18,62,53,74,11,7.0,2,71,Urban,HR Executive,88640,1 +53177,Male,57,Masters,18,54,5,10,26,9.0,7,25,Urban,HR Executive,91294,0 +53178,Male,45,Masters,7,86,21,81,43,3.0,3,31,Rural,Data Analyst,127855,0 +53179,Female,53,Diploma,0,44,88,2,28,0.0,4,66,Semi-Urban,Data Analyst,93487,0 +53180,Male,41,Masters,19,87,2,27,31,9.0,4,54,Semi-Urban,HR Executive,25715,0 +53181,Male,31,Bachelors,3,71,97,75,4,1.0,3,1,Rural,HR Executive,113525,1 +53182,Male,43,Bachelors,15,75,99,35,37,6.0,0,38,Urban,Manager,35055,1 +53183,Female,41,Bachelors,16,44,17,45,11,1.0,5,92,Rural,Manager,27969,0 +53184,Male,59,Bachelors,4,22,71,42,58,2.0,5,84,Urban,HR Executive,144517,0 +53185,Female,31,Diploma,1,47,41,37,62,0.0,3,45,Urban,Manager,145356,0 +53186,Female,53,PhD,2,25,8,35,9,1.0,6,14,Urban,Software Engineer,39643,0 +53187,Male,52,Masters,18,91,85,52,21,5.0,7,39,Rural,Manager,25036,1 +53188,Male,33,High School,0,63,92,93,70,8.0,6,43,Urban,Software Engineer,66086,1 +53189,Female,51,Bachelors,12,5,34,80,79,2.0,1,27,Urban,HR Executive,117949,0 +53190,Female,49,Diploma,11,22,65,8,68,9.0,6,27,Semi-Urban,Data Analyst,131169,0 +53191,Female,40,Bachelors,17,6,97,7,53,6.0,7,70,Semi-Urban,ML Engineer,65061,0 +53192,Other,52,Bachelors,16,64,64,3,60,4.0,5,35,Urban,Data Analyst,22888,0 +53193,Male,52,Diploma,14,7,75,24,35,9.0,1,28,Urban,Manager,127817,0 +53194,Male,41,Masters,7,34,94,62,8,7.0,3,9,Urban,Manager,116517,0 +53195,Male,22,Bachelors,9,9,96,95,98,2.0,1,95,Urban,Manager,72024,1 +53196,Female,21,Bachelors,2,97,7,71,91,0.0,5,24,Semi-Urban,ML Engineer,85703,0 +53197,Male,30,Bachelors,2,65,11,86,55,1.0,7,40,Urban,ML Engineer,62943,0 +53198,Male,25,Masters,17,98,25,16,73,8.0,5,57,Rural,Software Engineer,135116,0 +53199,Female,34,Bachelors,0,35,55,26,35,9.0,0,90,Rural,Manager,99526,0 +53200,Female,47,Bachelors,4,4,83,78,57,6.0,5,53,Urban,ML Engineer,100792,0 +53201,Male,30,High School,1,74,94,16,19,7.0,4,99,Semi-Urban,Manager,87834,1 +53202,Female,51,Diploma,0,70,97,61,57,5.0,1,36,Urban,Manager,114701,1 +53203,Male,59,Bachelors,13,27,63,5,88,6.0,6,36,Urban,Manager,104348,0 +53204,Male,49,Bachelors,0,74,18,20,40,0.0,4,97,Urban,Data Analyst,125863,0 +53205,Male,33,Bachelors,4,44,66,32,26,9.0,4,21,Urban,Data Analyst,27666,0 +53206,Female,54,High School,19,22,12,94,58,9.0,4,96,Urban,Software Engineer,120586,0 +53207,Female,28,Bachelors,1,36,45,60,3,9.0,4,57,Rural,ML Engineer,57157,0 +53208,Male,32,PhD,19,9,7,47,99,1.0,1,97,Urban,Data Analyst,149559,0 +53209,Male,53,Masters,2,39,88,94,83,6.0,5,89,Semi-Urban,HR Executive,115518,1 +53210,Female,36,Diploma,6,70,44,64,30,6.0,5,83,Semi-Urban,Manager,40830,1 +53211,Male,26,Bachelors,6,34,97,16,19,9.0,1,20,Semi-Urban,Software Engineer,61316,0 +53212,Other,46,Bachelors,6,80,10,52,96,8.0,0,71,Semi-Urban,Data Analyst,122204,0 +53213,Female,31,Bachelors,7,75,34,55,24,8.0,1,78,Semi-Urban,Data Analyst,131798,1 +53214,Male,45,Diploma,19,97,60,28,8,0.0,1,61,Semi-Urban,Manager,96346,1 +53215,Female,32,High School,5,48,2,1,10,2.0,4,52,Semi-Urban,HR Executive,130235,0 +53216,Male,42,Bachelors,5,51,73,82,61,4.0,0,18,Rural,HR Executive,89833,0 +53217,Other,29,Diploma,13,97,10,20,88,2.0,6,18,Semi-Urban,HR Executive,20647,0 +53218,Male,59,Bachelors,17,14,14,82,1,7.0,3,40,Urban,HR Executive,55330,0 +53219,Male,31,High School,17,29,85,30,58,2.0,2,5,Urban,HR Executive,31832,0 +53220,Male,43,Masters,6,61,94,45,51,7.0,0,5,Rural,ML Engineer,102508,0 +53221,Male,22,Bachelors,17,50,56,50,69,0.0,3,49,Urban,HR Executive,93627,0 +53222,Male,54,Masters,5,75,73,6,83,5.0,0,71,Urban,ML Engineer,34598,0 +53223,Male,44,Masters,13,90,69,78,71,8.0,7,79,Rural,Software Engineer,36877,1 +53224,Male,50,PhD,9,64,76,94,37,9.0,0,62,Urban,Software Engineer,63888,1 +53225,Male,21,Masters,5,85,89,96,2,1.0,5,98,Urban,ML Engineer,106981,1 +53226,Female,50,High School,6,13,21,71,22,5.0,1,11,Urban,HR Executive,106760,0 +53227,Male,59,Masters,9,66,82,19,85,8.0,1,16,Urban,Data Analyst,143167,0 +53228,Female,40,Bachelors,18,89,9,62,97,9.0,1,37,Rural,Software Engineer,114451,0 +53229,Male,43,Bachelors,14,65,28,6,39,1.0,3,11,Rural,Data Analyst,46537,0 +53230,Male,59,Bachelors,12,82,0,98,86,6.0,4,92,Rural,Data Analyst,130719,1 +53231,Female,26,Masters,10,74,6,4,23,6.0,7,76,Urban,ML Engineer,33812,0 +53232,Male,35,Masters,18,83,98,14,72,5.0,2,98,Semi-Urban,ML Engineer,29414,1 +53233,Male,43,Diploma,1,6,81,61,82,2.0,1,87,Urban,ML Engineer,77116,1 +53234,Female,35,Bachelors,17,39,28,69,47,9.0,6,76,Urban,Software Engineer,127427,0 +53235,Male,25,Masters,14,50,15,29,53,8.0,5,4,Urban,Data Analyst,146476,0 +53236,Male,51,Masters,3,42,89,21,83,1.0,5,69,Urban,ML Engineer,143762,0 +53237,Female,27,Masters,2,53,43,49,32,8.0,2,71,Urban,ML Engineer,115933,0 +53238,Male,51,Masters,9,40,43,31,69,3.0,4,63,Urban,HR Executive,56061,0 +53239,Male,57,Diploma,0,36,21,99,71,1.0,5,60,Urban,HR Executive,92029,0 +53240,Male,47,Bachelors,0,16,68,29,6,5.0,1,26,Urban,Data Analyst,73672,0 +53241,Male,46,Masters,12,98,1,87,92,6.0,4,70,Semi-Urban,HR Executive,38866,1 +53242,Male,59,Masters,5,88,81,54,90,1.0,6,96,Urban,HR Executive,115489,1 +53243,Female,56,High School,14,84,60,50,39,2.0,5,1,Rural,Software Engineer,29027,0 +53244,Male,57,Bachelors,13,96,98,59,4,1.0,3,39,Rural,Manager,48423,1 +53245,Male,48,Diploma,18,29,47,15,63,2.0,4,56,Rural,ML Engineer,46731,0 +53246,Male,55,Bachelors,9,48,64,27,54,8.0,2,17,Rural,HR Executive,104069,0 +53247,Male,23,High School,17,35,99,65,41,7.0,0,52,Urban,ML Engineer,63468,1 +53248,Male,39,Bachelors,9,28,86,93,21,7.0,3,53,Urban,HR Executive,133829,1 +53249,Male,38,Diploma,6,23,88,42,43,8.0,0,1,Urban,Manager,90355,0 +53250,Female,50,High School,15,43,28,27,76,0.0,7,46,Urban,HR Executive,20875,0 +53251,Female,47,Diploma,7,99,59,75,17,9.0,3,39,Urban,Manager,140147,1 +53252,Male,37,High School,15,89,68,75,69,1.0,7,85,Urban,ML Engineer,58191,1 +53253,Male,32,Masters,5,97,30,64,35,8.0,3,47,Semi-Urban,Data Analyst,105816,1 +53254,Female,53,High School,19,22,35,93,65,9.0,4,0,Urban,HR Executive,84751,0 +53255,Other,52,Bachelors,4,6,34,1,34,3.0,3,13,Rural,Software Engineer,38398,0 +53256,Male,35,Bachelors,1,40,52,33,19,8.0,3,35,Semi-Urban,Manager,102789,0 +53257,Male,23,Masters,8,82,94,63,4,1.0,2,8,Semi-Urban,HR Executive,97268,1 +53258,Male,47,Diploma,14,76,48,75,11,5.0,3,99,Semi-Urban,Software Engineer,148052,1 +53259,Male,29,Bachelors,8,90,43,79,94,1.0,6,58,Urban,HR Executive,109094,1 +53260,Male,59,Masters,1,23,67,75,39,7.0,4,89,Semi-Urban,Manager,118371,1 +53261,Other,29,Diploma,7,0,35,73,92,5.0,6,66,Semi-Urban,ML Engineer,139947,0 +53262,Male,27,Bachelors,2,79,11,30,10,7.0,2,82,Semi-Urban,Manager,131053,0 +53263,Male,57,Diploma,13,90,50,76,58,4.0,3,67,Urban,Software Engineer,67539,1 +53264,Female,26,Diploma,15,22,71,18,72,7.0,2,19,Urban,Manager,51674,0 +53265,Male,23,Masters,4,17,19,80,60,6.0,6,45,Urban,Software Engineer,104461,0 +53266,Male,51,Bachelors,4,96,52,72,83,6.0,2,50,Semi-Urban,ML Engineer,51063,1 +53267,Other,33,Diploma,5,22,16,11,21,4.0,7,20,Urban,Data Analyst,20318,0 +53268,Male,38,Bachelors,2,80,16,71,92,3.0,1,98,Rural,Data Analyst,100023,1 +53269,Female,22,Diploma,13,10,49,9,7,5.0,1,17,Urban,Data Analyst,133365,0 +53270,Male,48,Masters,11,37,43,45,31,9.0,6,91,Urban,ML Engineer,58227,0 +53271,Male,31,Diploma,10,32,15,66,94,0.0,3,42,Urban,ML Engineer,24673,0 +53272,Female,25,Diploma,2,60,35,29,60,8.0,5,73,Urban,Data Analyst,61759,0 +53273,Male,37,High School,17,9,26,96,17,8.0,0,76,Urban,Software Engineer,148038,0 +53274,Female,31,Bachelors,7,92,68,92,21,9.0,0,66,Urban,Manager,85476,1 +53275,Male,57,Masters,15,70,13,70,5,7.0,7,36,Urban,Software Engineer,58475,0 +53276,Male,58,Masters,18,10,11,31,91,4.0,0,26,Urban,Data Analyst,117375,0 +53277,Female,29,Masters,11,65,80,17,67,1.0,4,17,Urban,HR Executive,149473,0 +53278,Female,23,Diploma,17,99,66,84,80,9.0,1,4,Urban,ML Engineer,110242,1 +53279,Female,35,Diploma,16,70,91,90,45,4.0,0,50,Rural,Manager,21481,1 +53280,Male,42,Bachelors,5,41,37,53,29,4.0,2,68,Urban,HR Executive,42192,0 +53281,Female,35,Bachelors,0,99,46,40,2,3.0,4,79,Urban,HR Executive,29048,1 +53282,Male,23,PhD,4,36,34,70,94,2.0,2,0,Urban,ML Engineer,78897,0 +53283,Female,28,Bachelors,3,85,45,85,53,0.0,3,25,Urban,HR Executive,129198,0 +53284,Male,34,Bachelors,1,68,2,7,22,2.0,2,73,Rural,HR Executive,73960,0 +53285,Male,43,High School,19,13,90,12,95,4.0,5,18,Urban,Manager,37074,0 +53286,Male,26,Masters,10,42,45,85,74,7.0,1,17,Semi-Urban,Manager,84189,0 +53287,Male,36,Diploma,7,20,85,49,58,6.0,7,62,Urban,Manager,137752,0 +53288,Female,38,Masters,9,97,58,20,78,1.0,4,82,Urban,Data Analyst,26919,1 +53289,Male,59,High School,12,81,21,1,37,7.0,7,73,Urban,Software Engineer,121086,0 +53290,Female,24,Bachelors,8,4,88,88,19,5.0,3,82,Semi-Urban,HR Executive,119930,1 +53291,Male,42,Diploma,7,38,76,8,4,9.0,5,11,Rural,ML Engineer,108482,0 +53292,Male,48,Diploma,8,39,78,46,10,9.0,5,45,Urban,ML Engineer,105236,0 +53293,Male,21,Diploma,7,9,34,84,92,5.0,4,80,Semi-Urban,Data Analyst,87578,0 +53294,Female,34,Diploma,8,56,53,44,7,7.0,5,40,Urban,Manager,37068,0 +53295,Other,27,High School,12,66,14,57,79,6.0,5,46,Rural,Software Engineer,85118,0 +53296,Male,46,Diploma,7,68,85,21,93,1.0,2,17,Rural,Software Engineer,112712,0 +53297,Male,42,Bachelors,8,26,25,25,66,3.0,6,34,Semi-Urban,ML Engineer,29378,0 +53298,Male,31,Bachelors,4,36,76,91,47,6.0,3,29,Rural,ML Engineer,37011,0 +53299,Female,26,PhD,4,18,29,30,46,5.0,4,76,Urban,Data Analyst,72306,0 +53300,Female,56,High School,16,70,89,92,42,4.0,5,51,Semi-Urban,Data Analyst,71514,1 +53301,Male,34,High School,11,71,23,36,49,1.0,7,69,Rural,HR Executive,83991,0 +53302,Male,58,High School,17,89,31,5,56,2.0,1,26,Rural,HR Executive,120434,0 +53303,Female,43,High School,18,33,12,85,74,5.0,3,3,Semi-Urban,HR Executive,43367,0 +53304,Male,50,Masters,3,11,2,46,57,6.0,4,69,Semi-Urban,Software Engineer,120751,0 +53305,Female,33,Bachelors,0,92,83,30,53,9.0,6,71,Semi-Urban,Software Engineer,141918,1 +53306,Male,50,Masters,16,34,47,41,72,6.0,3,50,Rural,Manager,105818,0 +53307,Female,36,Bachelors,11,49,19,96,53,6.0,1,69,Urban,Data Analyst,111800,0 +53308,Male,39,Bachelors,6,21,79,6,93,4.0,1,24,Urban,Data Analyst,112247,0 +53309,Male,30,Bachelors,9,52,83,63,63,4.0,4,10,Semi-Urban,HR Executive,131169,0 +53310,Male,51,Masters,3,68,75,31,64,2.0,4,49,Rural,Data Analyst,121536,0 +53311,Male,29,Bachelors,0,53,64,28,81,8.0,5,10,Urban,Software Engineer,141282,0 +53312,Male,26,Bachelors,9,83,8,16,5,5.0,2,25,Semi-Urban,HR Executive,115072,0 +53313,Male,37,Diploma,18,96,54,29,34,8.0,5,41,Urban,ML Engineer,32739,0 +53314,Other,40,Diploma,1,95,13,89,1,4.0,4,81,Urban,Manager,26044,1 +53315,Female,59,Bachelors,0,39,42,82,29,1.0,0,72,Urban,Software Engineer,148099,0 +53316,Male,44,Masters,16,35,70,79,49,2.0,5,17,Rural,Data Analyst,84543,0 +53317,Male,48,Bachelors,14,72,20,34,34,8.0,3,77,Semi-Urban,HR Executive,20784,0 +53318,Male,40,Bachelors,7,24,84,81,23,1.0,7,3,Urban,Software Engineer,86361,0 +53319,Female,56,Masters,19,61,49,72,46,3.0,0,95,Urban,ML Engineer,68939,1 +53320,Female,29,Masters,10,88,31,2,41,2.0,5,42,Semi-Urban,Data Analyst,38319,0 +53321,Male,44,Bachelors,9,37,97,1,38,6.0,5,8,Urban,Manager,106656,0 +53322,Female,45,Diploma,13,58,84,44,18,1.0,3,90,Urban,Data Analyst,109812,1 +53323,Female,33,Diploma,2,40,42,95,19,6.0,1,83,Urban,Manager,38757,1 +53324,Male,53,PhD,6,64,87,59,69,0.0,0,25,Rural,HR Executive,27494,1 +53325,Male,44,High School,3,52,30,57,43,5.0,1,11,Semi-Urban,Manager,97073,0 +53326,Female,28,Diploma,6,19,15,73,33,4.0,7,44,Rural,ML Engineer,137432,0 +53327,Male,52,Bachelors,14,84,95,80,83,7.0,3,41,Urban,Manager,37534,1 +53328,Male,29,Bachelors,13,83,20,86,84,5.0,4,66,Urban,Data Analyst,119855,1 +53329,Male,24,Bachelors,19,92,93,13,32,1.0,4,56,Urban,ML Engineer,106005,1 +53330,Female,26,Masters,10,6,81,69,89,1.0,1,32,Urban,Manager,75208,0 +53331,Male,48,Bachelors,16,10,64,19,71,1.0,1,8,Semi-Urban,Manager,86848,0 +53332,Male,33,Bachelors,18,49,38,10,30,0.0,0,54,Urban,Manager,58470,0 +53333,Female,31,Bachelors,3,84,83,87,92,1.0,3,8,Urban,Data Analyst,140373,1 +53334,Other,39,Masters,12,0,56,14,73,9.0,1,18,Semi-Urban,Manager,115650,0 +53335,Male,59,Bachelors,8,32,56,68,9,1.0,1,80,Urban,Software Engineer,90283,1 +53336,Male,51,Bachelors,8,32,35,93,78,9.0,5,60,Urban,ML Engineer,61710,0 +53337,Male,23,Diploma,18,79,56,29,37,2.0,6,26,Urban,ML Engineer,71522,0 +53338,Female,30,Masters,18,56,34,74,15,6.0,1,99,Rural,Software Engineer,137094,1 +53339,Male,36,PhD,0,40,34,20,97,9.0,2,11,Semi-Urban,ML Engineer,133083,0 +53340,Female,49,Bachelors,12,87,96,77,54,8.0,5,8,Urban,Data Analyst,122713,1 +53341,Male,50,Bachelors,12,26,25,57,1,9.0,4,46,Urban,Manager,126341,0 +53342,Male,31,Bachelors,8,43,80,37,53,6.0,7,32,Urban,ML Engineer,47859,0 +53343,Male,38,Diploma,4,15,19,73,63,3.0,5,29,Semi-Urban,HR Executive,58602,0 +53344,Male,22,Masters,10,18,73,7,83,9.0,5,1,Urban,ML Engineer,126917,0 +53345,Male,53,Diploma,17,62,90,65,60,0.0,1,46,Rural,Software Engineer,120443,1 +53346,Male,33,High School,9,58,68,28,80,7.0,2,35,Rural,Manager,86091,0 +53347,Female,57,Bachelors,7,67,58,17,2,9.0,7,97,Urban,Manager,148451,0 +53348,Female,49,Masters,10,87,24,76,24,9.0,5,32,Urban,Software Engineer,78009,0 +53349,Male,34,Bachelors,9,68,40,15,73,0.0,3,22,Rural,Data Analyst,127916,0 +53350,Female,27,Masters,8,3,59,82,59,1.0,5,4,Semi-Urban,Manager,103551,0 +53351,Female,24,Masters,19,28,75,44,63,4.0,6,39,Urban,HR Executive,121412,0 +53352,Male,39,Bachelors,13,16,99,40,25,9.0,5,2,Urban,Manager,83157,0 +53353,Male,47,Diploma,18,41,25,19,41,0.0,4,51,Rural,Software Engineer,72357,0 +53354,Female,53,Diploma,7,68,30,85,66,5.0,4,33,Urban,Software Engineer,30994,0 +53355,Male,24,Diploma,16,54,85,35,26,5.0,0,93,Rural,Data Analyst,69508,1 +53356,Male,49,Diploma,1,39,93,38,32,1.0,2,51,Urban,Manager,149829,0 +53357,Male,48,Diploma,16,7,26,86,68,5.0,6,92,Rural,HR Executive,114622,0 +53358,Male,50,Diploma,16,57,77,17,5,3.0,1,41,Semi-Urban,Manager,141917,0 +53359,Male,45,Masters,2,66,23,80,54,6.0,6,64,Rural,Data Analyst,84142,0 +53360,Male,39,Bachelors,1,8,82,16,41,5.0,6,27,Urban,HR Executive,126994,0 +53361,Female,49,Diploma,3,82,63,41,36,1.0,0,11,Urban,Data Analyst,143767,0 +53362,Male,27,High School,15,66,49,73,31,1.0,1,84,Urban,Software Engineer,69261,1 +53363,Male,35,Masters,5,43,86,98,84,2.0,2,79,Urban,HR Executive,60623,1 +53364,Male,58,Diploma,8,82,49,93,18,4.0,5,63,Urban,ML Engineer,74827,1 +53365,Other,36,Masters,4,16,52,2,1,6.0,1,16,Urban,Manager,103236,0 +53366,Male,39,PhD,8,24,27,1,4,5.0,1,11,Urban,Data Analyst,36221,0 +53367,Male,38,Bachelors,6,79,72,16,89,1.0,2,86,Urban,Software Engineer,36474,1 +53368,Male,39,Masters,15,9,41,2,74,8.0,5,4,Rural,Data Analyst,131644,0 +53369,Male,33,Masters,7,56,55,20,75,4.0,5,71,Rural,Software Engineer,106096,0 +53370,Male,59,Bachelors,17,77,39,91,90,4.0,6,50,Urban,ML Engineer,69702,1 +53371,Other,37,Diploma,7,62,27,68,39,0.0,0,87,Semi-Urban,Manager,108322,1 +53372,Female,28,High School,14,30,94,78,29,7.0,5,44,Semi-Urban,Data Analyst,60513,1 +53373,Male,21,Masters,8,43,39,36,88,9.0,3,70,Rural,ML Engineer,38484,0 +53374,Male,33,Bachelors,17,44,24,40,99,7.0,2,79,Urban,Manager,116377,0 +53375,Male,48,Bachelors,10,74,36,54,13,4.0,7,7,Urban,ML Engineer,141115,0 +53376,Male,38,Masters,19,8,35,86,96,9.0,6,96,Rural,Manager,34485,0 +53377,Female,32,PhD,3,44,44,92,98,9.0,6,12,Semi-Urban,HR Executive,128369,0 +53378,Male,51,High School,3,26,92,67,89,8.0,3,26,Semi-Urban,Software Engineer,126098,0 +53379,Male,59,Bachelors,14,32,49,12,10,8.0,6,10,Rural,Data Analyst,101787,0 +53380,Male,44,Diploma,12,68,80,64,79,6.0,3,41,Rural,Software Engineer,122028,1 +53381,Male,36,Masters,15,71,65,68,9,3.0,6,41,Semi-Urban,HR Executive,27684,1 +53382,Female,58,Bachelors,12,74,6,63,15,4.0,2,34,Urban,Software Engineer,149273,0 +53383,Male,23,Masters,17,69,87,16,56,0.0,7,75,Urban,Data Analyst,54035,1 +53384,Female,37,Diploma,0,76,39,53,42,9.0,1,4,Urban,HR Executive,91674,0 +53385,Female,51,Bachelors,10,52,73,51,24,3.0,6,39,Urban,Manager,55205,0 +53386,Male,48,High School,1,66,98,44,28,5.0,5,86,Urban,Data Analyst,112958,1 +53387,Other,57,Masters,8,0,28,38,0,0.0,3,95,Urban,ML Engineer,94938,0 +53388,Male,22,Diploma,19,58,8,68,38,8.0,5,50,Urban,Manager,92700,0 +53389,Male,44,Bachelors,1,91,34,21,52,8.0,3,96,Semi-Urban,ML Engineer,65905,1 +53390,Female,56,Bachelors,16,43,86,7,66,1.0,0,34,Semi-Urban,Data Analyst,129655,0 +53391,Male,51,Bachelors,11,62,59,68,91,3.0,0,11,Semi-Urban,ML Engineer,110461,0 +53392,Male,59,Bachelors,5,96,46,36,82,4.0,5,83,Semi-Urban,Software Engineer,70831,1 +53393,Female,24,Masters,5,45,18,48,96,7.0,4,64,Urban,Data Analyst,105050,0 +53394,Female,49,Masters,14,49,76,94,16,7.0,6,40,Urban,HR Executive,70245,1 +53395,Male,52,Bachelors,19,84,46,78,10,9.0,3,3,Semi-Urban,ML Engineer,49778,0 +53396,Female,37,Diploma,0,55,63,31,36,9.0,4,78,Rural,Manager,147439,0 +53397,Female,32,Masters,12,68,52,48,82,1.0,7,80,Rural,Data Analyst,51525,1 +53398,Male,39,Bachelors,0,89,81,70,69,7.0,2,22,Urban,HR Executive,123949,1 +53399,Male,22,High School,8,68,55,36,46,4.0,1,14,Urban,ML Engineer,88344,0 +53400,Other,35,Bachelors,0,80,4,67,33,5.0,5,64,Rural,Manager,143951,0 +53401,Other,41,Diploma,6,44,11,77,8,2.0,6,12,Urban,Data Analyst,36087,0 +53402,Male,55,Bachelors,1,57,34,1,88,8.0,5,18,Urban,ML Engineer,65212,0 +53403,Male,27,Masters,4,95,54,14,99,7.0,0,24,Urban,Manager,119040,0 +53404,Female,22,Bachelors,15,0,0,62,37,0.0,5,58,Urban,HR Executive,127073,0 +53405,Male,45,Bachelors,10,55,79,13,95,0.0,6,19,Urban,ML Engineer,145255,0 +53406,Female,59,Bachelors,19,28,83,4,81,0.0,7,36,Semi-Urban,ML Engineer,34547,0 +53407,Male,48,High School,9,6,64,30,17,1.0,0,15,Urban,HR Executive,127691,0 +53408,Female,46,Masters,13,69,50,4,22,6.0,4,86,Urban,ML Engineer,147793,0 +53409,Male,42,Bachelors,15,94,3,24,18,9.0,1,39,Urban,Software Engineer,32915,0 +53410,Female,48,Diploma,9,3,74,17,98,6.0,7,97,Semi-Urban,ML Engineer,51477,0 +53411,Male,49,Bachelors,2,68,42,30,36,0.0,3,73,Rural,ML Engineer,104785,0 +53412,Male,42,High School,4,86,38,61,22,5.0,4,86,Urban,ML Engineer,86829,1 +53413,Female,26,Bachelors,13,46,45,73,23,9.0,4,36,Urban,Data Analyst,127537,0 +53414,Male,40,Masters,1,78,65,51,64,7.0,6,31,Semi-Urban,ML Engineer,102980,0 +53415,Male,37,Diploma,0,76,56,70,90,1.0,3,70,Semi-Urban,Manager,64004,1 +53416,Female,48,Diploma,6,44,6,83,58,8.0,6,33,Urban,HR Executive,35406,0 +53417,Male,40,Bachelors,18,16,49,25,57,8.0,3,78,Urban,ML Engineer,62227,0 +53418,Female,40,Masters,9,33,12,95,24,5.0,1,71,Urban,Data Analyst,56608,0 +53419,Male,52,High School,9,7,26,97,37,8.0,6,66,Urban,ML Engineer,28555,0 +53420,Female,49,Bachelors,12,14,34,58,36,6.0,2,52,Semi-Urban,Software Engineer,53030,0 +53421,Male,34,Bachelors,12,0,15,33,40,6.0,5,53,Urban,Manager,26479,0 +53422,Male,35,Diploma,11,14,47,90,29,0.0,0,60,Semi-Urban,ML Engineer,122805,0 +53423,Female,45,Masters,11,87,39,76,82,3.0,1,84,Urban,HR Executive,35954,1 +53424,Male,21,High School,19,90,2,71,30,3.0,7,61,Urban,Software Engineer,30407,0 +53425,Other,43,Masters,10,2,76,31,1,5.0,1,33,Urban,Software Engineer,31099,0 +53426,Female,22,Masters,19,70,38,44,5,8.0,0,22,Rural,HR Executive,96045,0 +53427,Female,37,PhD,14,30,56,19,34,9.0,3,81,Semi-Urban,ML Engineer,94100,0 +53428,Male,38,Bachelors,2,42,49,3,42,5.0,2,62,Rural,Manager,54733,0 +53429,Male,56,Bachelors,19,26,62,71,73,9.0,7,47,Semi-Urban,Software Engineer,67665,0 +53430,Male,27,Masters,4,48,20,72,22,0.0,1,16,Rural,ML Engineer,33030,0 +53431,Male,21,Diploma,9,39,56,4,13,2.0,6,92,Urban,ML Engineer,103189,0 +53432,Male,23,Diploma,8,51,54,87,88,2.0,4,82,Urban,ML Engineer,143702,1 +53433,Other,59,Diploma,10,53,97,14,1,1.0,2,58,Semi-Urban,Software Engineer,64325,0 +53434,Male,59,Bachelors,4,95,85,24,73,4.0,6,39,Rural,Software Engineer,59063,1 +53435,Female,27,Masters,6,64,62,91,25,1.0,7,90,Urban,Software Engineer,59589,1 +53436,Male,24,Masters,18,54,47,57,21,6.0,1,91,Urban,HR Executive,94321,1 +53437,Male,47,Diploma,0,24,64,42,21,1.0,5,71,Semi-Urban,ML Engineer,127913,0 +53438,Male,26,Diploma,1,34,0,57,87,9.0,1,13,Semi-Urban,Data Analyst,24135,0 +53439,Male,58,Masters,3,22,84,40,34,8.0,0,65,Urban,Data Analyst,50036,0 +53440,Female,43,Diploma,6,12,99,25,31,9.0,0,96,Semi-Urban,HR Executive,107232,0 +53441,Female,42,Bachelors,2,89,53,88,50,5.0,1,36,Urban,HR Executive,98930,1 +53442,Female,39,Bachelors,4,31,47,6,69,2.0,0,87,Rural,ML Engineer,20964,0 +53443,Female,34,Bachelors,6,26,74,40,30,4.0,5,71,Rural,Manager,117730,0 +53444,Male,51,Masters,0,25,16,77,82,9.0,4,94,Rural,Manager,145851,0 +53445,Male,34,Diploma,0,23,54,52,37,4.0,5,4,Semi-Urban,HR Executive,31176,0 +53446,Male,22,Masters,17,84,89,57,36,0.0,0,14,Urban,Data Analyst,43664,1 +53447,Female,48,High School,4,31,97,15,4,2.0,6,45,Semi-Urban,Software Engineer,42897,0 +53448,Male,57,High School,17,42,22,85,32,7.0,1,55,Semi-Urban,ML Engineer,84237,0 +53449,Male,29,High School,6,39,37,18,51,0.0,4,57,Semi-Urban,Manager,85821,0 +53450,Male,25,High School,18,91,15,36,33,3.0,4,97,Urban,Manager,22183,1 +53451,Other,23,High School,5,85,47,51,82,1.0,1,23,Semi-Urban,HR Executive,101439,0 +53452,Female,24,High School,2,11,63,75,32,6.0,3,29,Urban,ML Engineer,89840,0 +53453,Male,26,Bachelors,18,32,62,29,91,0.0,3,95,Urban,Manager,55159,0 +53454,Other,39,Diploma,2,68,54,96,70,2.0,4,8,Semi-Urban,Software Engineer,32367,0 +53455,Male,57,Bachelors,7,57,22,31,96,3.0,5,84,Urban,Software Engineer,79769,0 +53456,Male,50,Diploma,15,38,7,94,20,4.0,3,46,Urban,Data Analyst,114277,0 +53457,Male,52,Bachelors,3,26,4,88,13,9.0,6,96,Urban,Data Analyst,93658,0 +53458,Male,25,Bachelors,7,5,40,94,97,0.0,4,43,Semi-Urban,ML Engineer,73738,0 +53459,Male,47,High School,18,41,15,3,9,4.0,7,38,Urban,ML Engineer,109479,0 +53460,Male,50,High School,10,93,88,45,53,4.0,3,70,Semi-Urban,HR Executive,47262,1 +53461,Female,57,High School,15,92,36,6,9,4.0,5,90,Semi-Urban,HR Executive,27317,0 +53462,Male,26,High School,3,19,39,93,65,0.0,5,72,Semi-Urban,Data Analyst,87810,0 +53463,Male,54,Bachelors,16,78,36,99,13,5.0,2,82,Rural,HR Executive,130684,1 +53464,Female,52,Masters,19,17,22,60,62,4.0,5,52,Urban,HR Executive,138320,0 +53465,Female,38,High School,2,60,65,68,67,4.0,4,54,Semi-Urban,ML Engineer,72605,1 +53466,Other,54,Diploma,16,9,16,76,91,3.0,6,9,Rural,Software Engineer,135044,0 +53467,Male,24,Masters,11,3,86,95,48,3.0,7,75,Rural,Data Analyst,51659,1 +53468,Female,28,Bachelors,8,10,12,73,14,0.0,2,73,Urban,ML Engineer,110003,0 +53469,Male,45,Diploma,1,86,67,29,41,0.0,0,20,Urban,Data Analyst,53712,0 +53470,Male,23,Diploma,3,78,51,61,72,3.0,1,53,Semi-Urban,HR Executive,88783,1 +53471,Male,49,Bachelors,8,67,77,70,94,0.0,2,79,Semi-Urban,Manager,123995,1 +53472,Male,44,Bachelors,11,3,12,2,32,6.0,7,18,Rural,HR Executive,138758,0 +53473,Male,32,Bachelors,12,0,22,81,10,1.0,5,56,Urban,ML Engineer,110880,0 +53474,Female,33,Masters,0,20,56,81,94,7.0,1,2,Rural,Software Engineer,71584,0 +53475,Male,24,Bachelors,19,80,42,98,50,2.0,0,80,Urban,Manager,22075,1 +53476,Other,26,High School,15,11,12,40,79,7.0,6,76,Urban,HR Executive,136340,0 +53477,Other,54,Bachelors,16,94,44,31,99,2.0,5,32,Urban,ML Engineer,39155,0 +53478,Male,45,Bachelors,5,13,55,22,55,0.0,5,91,Semi-Urban,Software Engineer,149842,0 +53479,Male,46,Diploma,5,75,52,8,93,7.0,5,55,Urban,HR Executive,75560,0 +53480,Male,45,PhD,17,98,47,15,83,2.0,1,96,Urban,ML Engineer,107517,1 +53481,Male,50,High School,0,7,76,31,66,1.0,2,25,Urban,Manager,142255,0 +53482,Other,51,Bachelors,11,27,51,77,54,2.0,2,45,Semi-Urban,Data Analyst,146859,0 +53483,Male,44,Bachelors,5,22,74,95,88,7.0,5,52,Urban,Software Engineer,76806,1 +53484,Male,58,Bachelors,1,16,79,48,70,9.0,0,49,Rural,Manager,25340,0 +53485,Male,38,Masters,12,33,83,16,53,6.0,4,37,Semi-Urban,Data Analyst,124781,0 +53486,Female,22,Bachelors,16,39,66,95,46,0.0,6,66,Urban,HR Executive,83198,1 +53487,Male,57,High School,11,26,48,7,12,8.0,5,10,Urban,ML Engineer,80912,0 +53488,Female,51,Masters,8,25,64,97,88,3.0,7,16,Urban,Data Analyst,104426,0 +53489,Male,37,Masters,19,93,17,97,44,6.0,3,90,Urban,Manager,133753,1 +53490,Female,22,Masters,8,85,55,75,45,9.0,2,47,Semi-Urban,ML Engineer,92593,1 +53491,Other,55,Diploma,6,74,61,8,50,8.0,5,87,Semi-Urban,Manager,82338,0 +53492,Female,43,PhD,19,81,87,96,71,0.0,4,7,Urban,Manager,41143,1 +53493,Female,54,Masters,1,50,8,44,71,1.0,2,7,Urban,Software Engineer,81202,0 +53494,Male,46,Bachelors,5,31,30,4,55,1.0,6,81,Semi-Urban,Manager,48844,0 +53495,Female,44,Bachelors,3,49,88,41,17,0.0,7,68,Urban,Software Engineer,96248,1 +53496,Female,38,Masters,19,51,42,6,50,9.0,1,80,Rural,Data Analyst,115581,0 +53497,Male,52,Diploma,15,5,74,68,93,5.0,3,52,Urban,Software Engineer,47755,0 +53498,Male,23,Masters,18,9,60,23,98,9.0,4,60,Semi-Urban,Data Analyst,70291,0 +53499,Male,28,Bachelors,7,74,58,82,6,0.0,6,40,Urban,Manager,61360,1 +53500,Female,53,Masters,10,29,45,81,77,6.0,0,1,Urban,Software Engineer,42253,0 +53501,Male,41,Bachelors,4,2,52,34,92,1.0,5,25,Urban,HR Executive,90699,0 +53502,Female,23,High School,15,19,29,10,51,5.0,2,96,Urban,Software Engineer,109794,0 +53503,Female,34,Bachelors,8,45,8,56,26,5.0,5,25,Urban,Data Analyst,62061,0 +53504,Male,54,Bachelors,0,86,7,30,27,5.0,1,76,Rural,HR Executive,100902,0 +53505,Female,24,Diploma,10,51,94,97,86,8.0,7,99,Rural,ML Engineer,103153,1 +53506,Female,26,Masters,13,76,22,91,98,9.0,6,50,Urban,Data Analyst,124949,0 +53507,Male,42,High School,11,27,13,65,3,4.0,2,38,Semi-Urban,Software Engineer,46024,0 +53508,Female,59,Bachelors,15,0,32,49,35,0.0,0,82,Urban,Data Analyst,111504,0 +53509,Female,45,High School,13,0,17,88,43,2.0,3,24,Urban,HR Executive,32449,0 +53510,Female,25,Bachelors,1,45,5,94,48,8.0,1,64,Semi-Urban,HR Executive,141016,0 +53511,Male,43,Bachelors,11,81,32,80,98,9.0,0,24,Urban,Data Analyst,87763,0 +53512,Male,45,Diploma,5,88,82,91,92,7.0,7,43,Semi-Urban,Data Analyst,24604,1 +53513,Female,34,Diploma,11,18,54,69,89,5.0,2,44,Urban,HR Executive,145790,0 +53514,Female,53,Bachelors,14,70,13,82,74,8.0,5,32,Rural,Software Engineer,46225,0 +53515,Male,45,High School,17,70,99,72,4,5.0,5,38,Semi-Urban,Software Engineer,115149,1 +53516,Other,36,High School,10,17,33,93,80,8.0,3,89,Semi-Urban,ML Engineer,94667,0 +53517,Male,54,Bachelors,1,87,99,29,19,8.0,0,76,Rural,ML Engineer,105665,1 +53518,Male,50,High School,10,75,26,34,36,4.0,0,99,Rural,Software Engineer,78196,0 +53519,Female,35,High School,5,63,55,99,65,2.0,1,45,Urban,Manager,67658,1 +53520,Male,46,Masters,3,76,34,92,9,4.0,4,84,Urban,Manager,27049,1 +53521,Male,47,Bachelors,2,1,1,80,19,5.0,2,11,Semi-Urban,HR Executive,82569,0 +53522,Female,41,Bachelors,6,40,24,57,72,0.0,5,26,Semi-Urban,HR Executive,106318,0 +53523,Female,30,Masters,8,19,25,1,58,0.0,2,78,Rural,ML Engineer,65537,0 +53524,Female,27,Bachelors,16,94,79,86,30,4.0,4,83,Semi-Urban,Manager,26043,1 +53525,Female,28,Bachelors,0,88,16,11,23,0.0,4,95,Urban,HR Executive,105950,0 +53526,Male,59,Diploma,13,75,52,48,22,6.0,4,40,Urban,Data Analyst,67591,0 +53527,Male,52,Diploma,4,34,29,52,38,9.0,1,56,Urban,ML Engineer,21545,0 +53528,Female,44,Bachelors,10,51,98,32,88,9.0,1,99,Urban,Data Analyst,89296,1 +53529,Male,42,Bachelors,2,45,35,34,81,0.0,5,43,Urban,ML Engineer,141519,0 +53530,Female,23,Bachelors,8,59,52,40,46,6.0,4,8,Urban,Software Engineer,128609,0 +53531,Male,40,Diploma,6,20,4,97,32,1.0,6,7,Rural,HR Executive,32203,0 +53532,Male,52,PhD,3,68,32,34,66,3.0,2,45,Urban,Software Engineer,82866,0 +53533,Male,56,Bachelors,10,15,31,55,79,9.0,7,96,Urban,Software Engineer,38776,0 +53534,Male,50,High School,3,93,76,14,16,5.0,0,44,Rural,ML Engineer,130226,0 +53535,Female,25,Bachelors,16,15,35,91,93,8.0,2,87,Urban,Manager,96788,0 +53536,Male,24,Masters,17,73,6,82,92,3.0,3,90,Semi-Urban,Software Engineer,118331,1 +53537,Male,48,Bachelors,7,3,99,44,42,0.0,2,42,Semi-Urban,Software Engineer,83741,0 +53538,Male,29,Masters,14,39,81,41,4,9.0,6,38,Rural,Software Engineer,134548,0 +53539,Male,53,High School,9,81,21,63,0,4.0,3,77,Urban,Software Engineer,143642,1 +53540,Male,24,Masters,12,92,53,43,76,1.0,3,71,Urban,Software Engineer,68533,1 +53541,Male,59,Bachelors,14,62,58,2,80,8.0,1,75,Rural,Manager,88335,0 +53542,Female,54,Masters,16,0,76,87,83,4.0,6,80,Semi-Urban,Manager,54223,1 +53543,Female,54,Bachelors,11,72,46,57,64,4.0,5,33,Rural,ML Engineer,128896,0 +53544,Female,36,High School,2,41,5,72,26,1.0,6,70,Urban,ML Engineer,28506,0 +53545,Female,52,Masters,0,78,54,39,49,6.0,1,82,Semi-Urban,ML Engineer,58799,1 +53546,Male,42,High School,17,94,28,24,63,0.0,1,86,Urban,ML Engineer,52484,0 +53547,Female,22,Bachelors,18,8,47,19,28,6.0,5,20,Rural,ML Engineer,132372,0 +53548,Male,28,Bachelors,14,40,53,58,48,6.0,0,35,Rural,Data Analyst,89963,0 +53549,Male,44,High School,10,22,16,30,63,7.0,2,1,Rural,Manager,124331,0 +53550,Male,34,Bachelors,1,8,11,73,59,6.0,7,45,Semi-Urban,Manager,45956,0 +53551,Male,48,Diploma,7,31,83,92,44,6.0,5,70,Urban,ML Engineer,67037,1 +53552,Male,24,Diploma,14,40,35,64,80,6.0,1,81,Urban,Manager,123708,0 +53553,Male,54,Diploma,2,18,26,41,38,7.0,5,69,Rural,HR Executive,20624,0 +53554,Other,47,Bachelors,9,3,42,14,51,9.0,6,54,Urban,Software Engineer,138717,0 +53555,Female,54,Bachelors,11,83,53,42,31,2.0,5,70,Rural,Manager,23590,1 +53556,Male,25,Bachelors,11,3,72,5,61,5.0,7,61,Urban,ML Engineer,130678,0 +53557,Male,59,Bachelors,6,82,84,19,52,3.0,6,81,Semi-Urban,HR Executive,47328,1 +53558,Male,33,Masters,14,92,77,98,12,9.0,2,87,Semi-Urban,Data Analyst,142534,1 +53559,Male,22,High School,17,53,54,54,81,9.0,0,50,Urban,Manager,81751,0 +53560,Female,58,Masters,4,38,39,40,6,7.0,4,14,Urban,Software Engineer,21062,0 +53561,Female,37,Bachelors,0,58,72,53,36,3.0,4,53,Rural,Manager,100969,0 +53562,Male,43,Bachelors,6,83,63,75,7,3.0,3,97,Urban,Manager,57322,1 +53563,Male,50,Diploma,18,66,4,63,40,7.0,2,74,Rural,Software Engineer,66380,0 +53564,Other,48,Bachelors,19,97,53,74,49,1.0,3,83,Urban,Software Engineer,131409,1 +53565,Male,35,High School,9,82,1,87,34,1.0,6,15,Rural,HR Executive,98581,0 +53566,Male,44,High School,1,57,45,4,26,1.0,0,12,Semi-Urban,ML Engineer,86447,0 +53567,Male,52,Diploma,11,17,27,94,23,8.0,4,73,Rural,ML Engineer,97049,0 +53568,Male,22,Bachelors,16,6,47,21,95,3.0,1,77,Urban,HR Executive,26211,0 +53569,Female,34,Bachelors,7,72,31,19,87,3.0,6,39,Semi-Urban,Software Engineer,97790,0 +53570,Female,49,Bachelors,18,69,74,69,91,6.0,1,79,Rural,Software Engineer,91043,1 +53571,Male,27,High School,15,46,42,24,2,8.0,5,96,Semi-Urban,ML Engineer,63903,0 +53572,Male,49,Diploma,13,36,86,68,94,6.0,2,58,Urban,Data Analyst,83690,1 +53573,Female,26,Bachelors,1,74,50,10,66,9.0,0,4,Semi-Urban,Manager,20366,0 +53574,Male,56,Diploma,0,94,47,1,29,8.0,3,68,Urban,HR Executive,109691,0 +53575,Male,36,Diploma,12,55,53,7,55,2.0,2,74,Urban,Software Engineer,54004,0 +53576,Female,49,Diploma,15,43,86,70,90,0.0,7,50,Urban,Manager,124263,1 +53577,Female,48,Bachelors,14,10,48,50,83,3.0,5,6,Urban,Manager,53018,0 +53578,Female,35,Bachelors,18,0,55,78,47,3.0,2,36,Rural,Software Engineer,134154,0 +53579,Female,27,High School,11,37,24,5,63,2.0,5,32,Rural,Data Analyst,79871,0 +53580,Male,38,High School,0,39,97,35,92,2.0,6,46,Rural,Software Engineer,22517,0 +53581,Female,50,Diploma,8,78,62,86,22,7.0,4,17,Urban,HR Executive,128362,1 +53582,Male,42,Bachelors,16,24,52,31,37,7.0,0,85,Urban,Software Engineer,47075,0 +53583,Male,36,Bachelors,9,90,62,79,75,7.0,5,26,Semi-Urban,ML Engineer,92624,1 +53584,Male,55,Bachelors,17,48,73,13,43,1.0,4,25,Semi-Urban,HR Executive,120905,0 +53585,Male,47,Masters,11,23,42,97,99,7.0,4,15,Urban,Data Analyst,78730,0 +53586,Male,22,Masters,8,58,68,45,94,1.0,1,53,Rural,ML Engineer,54054,0 +53587,Male,51,Bachelors,9,60,81,41,76,4.0,6,71,Semi-Urban,ML Engineer,30892,1 +53588,Male,48,High School,12,8,95,40,94,2.0,4,43,Urban,Data Analyst,97073,0 +53589,Male,50,Masters,6,46,11,76,91,6.0,0,65,Urban,ML Engineer,130674,0 +53590,Male,57,High School,13,82,12,69,91,4.0,5,13,Urban,Manager,140372,0 +53591,Male,50,Bachelors,16,22,15,70,88,3.0,5,8,Rural,Software Engineer,102147,0 +53592,Male,48,Diploma,4,34,2,37,53,5.0,5,3,Rural,Data Analyst,129010,0 +53593,Male,47,Bachelors,8,49,98,3,0,6.0,7,89,Semi-Urban,Manager,70112,1 +53594,Male,22,Bachelors,17,16,79,94,55,2.0,4,21,Urban,Software Engineer,119079,0 +53595,Male,27,Masters,10,50,59,92,29,8.0,7,91,Urban,Software Engineer,55643,1 +53596,Male,27,Bachelors,5,90,99,93,69,0.0,5,77,Urban,Manager,77342,1 +53597,Male,39,Bachelors,18,51,90,83,37,9.0,0,14,Urban,HR Executive,148233,1 +53598,Male,53,Bachelors,9,20,27,55,80,1.0,5,72,Semi-Urban,ML Engineer,78362,0 +53599,Female,54,Bachelors,16,85,8,24,7,1.0,5,39,Semi-Urban,ML Engineer,36239,0 +53600,Male,45,Diploma,12,25,30,24,15,9.0,5,41,Urban,Manager,143005,0 +53601,Female,51,Diploma,11,2,49,42,89,4.0,7,58,Urban,Manager,90832,0 +53602,Female,59,Diploma,10,17,75,31,22,9.0,2,46,Semi-Urban,ML Engineer,45216,0 +53603,Male,29,Masters,1,10,80,69,34,5.0,3,45,Semi-Urban,Software Engineer,58125,0 +53604,Male,58,Bachelors,16,56,79,58,48,6.0,0,68,Rural,Manager,22910,1 +53605,Female,43,Bachelors,9,2,61,10,56,2.0,7,99,Urban,ML Engineer,90323,0 +53606,Male,32,High School,18,77,71,78,56,7.0,4,90,Urban,Manager,120913,1 +53607,Female,50,PhD,17,0,44,42,57,0.0,3,9,Rural,Data Analyst,115936,0 +53608,Female,26,Diploma,16,98,60,96,4,4.0,7,80,Urban,HR Executive,48029,1 +53609,Male,34,Bachelors,5,24,66,71,74,4.0,1,78,Urban,ML Engineer,43500,1 +53610,Male,52,Masters,0,89,45,76,59,9.0,2,9,Urban,Software Engineer,136342,0 +53611,Male,25,Bachelors,3,38,86,13,8,1.0,7,51,Rural,Manager,64461,0 +53612,Male,31,Bachelors,1,19,47,83,74,8.0,2,72,Urban,ML Engineer,132361,0 +53613,Male,28,Bachelors,14,95,20,36,84,9.0,0,99,Rural,Data Analyst,84906,1 +53614,Male,48,Bachelors,19,65,0,14,77,0.0,3,29,Rural,ML Engineer,34520,0 +53615,Male,32,Bachelors,7,74,29,79,80,3.0,6,6,Semi-Urban,Manager,49390,0 +53616,Female,44,Diploma,11,30,9,44,58,3.0,6,77,Urban,ML Engineer,119553,0 +53617,Female,57,Diploma,4,23,69,86,40,4.0,3,42,Urban,Data Analyst,135373,0 +53618,Male,40,Masters,5,59,3,45,92,5.0,3,56,Urban,Manager,47636,0 +53619,Male,37,High School,18,90,72,74,10,8.0,4,2,Urban,HR Executive,50501,1 +53620,Male,36,High School,12,61,49,8,39,4.0,6,10,Urban,HR Executive,127842,0 +53621,Female,48,High School,17,2,14,89,36,5.0,1,9,Rural,Data Analyst,117935,0 +53622,Male,56,Masters,10,48,4,43,56,7.0,7,64,Urban,Manager,98966,0 +53623,Male,30,Bachelors,1,66,65,25,38,9.0,0,47,Urban,Software Engineer,26019,0 +53624,Female,51,Bachelors,4,56,68,13,78,4.0,0,86,Urban,HR Executive,38645,0 +53625,Male,36,High School,8,45,46,81,43,2.0,1,16,Urban,Software Engineer,51394,0 +53626,Male,59,Bachelors,6,45,88,83,41,0.0,3,63,Semi-Urban,HR Executive,85045,1 +53627,Other,42,Bachelors,9,98,15,59,41,2.0,2,62,Urban,HR Executive,83020,0 +53628,Male,49,Diploma,16,95,27,1,73,1.0,2,14,Urban,Manager,129800,0 +53629,Female,46,High School,19,50,13,95,79,0.0,7,18,Rural,Manager,144522,0 +53630,Female,43,High School,6,14,55,89,14,7.0,4,1,Rural,Data Analyst,37080,0 +53631,Male,31,Diploma,1,17,31,74,75,0.0,0,20,Urban,Software Engineer,91246,0 +53632,Female,30,Bachelors,1,85,50,14,34,8.0,2,18,Rural,HR Executive,30456,0 +53633,Male,55,Bachelors,4,63,1,66,1,4.0,3,60,Urban,ML Engineer,63699,0 +53634,Female,57,Bachelors,19,13,66,47,71,0.0,2,23,Urban,Data Analyst,72499,0 +53635,Male,45,Diploma,16,65,48,91,94,3.0,3,39,Semi-Urban,HR Executive,117889,1 +53636,Other,48,High School,1,15,36,20,74,1.0,0,73,Urban,Software Engineer,70873,0 +53637,Female,33,Bachelors,3,75,68,69,47,3.0,2,11,Rural,ML Engineer,97459,0 +53638,Female,59,Bachelors,13,68,74,6,55,8.0,6,81,Urban,ML Engineer,48516,0 +53639,Female,56,Bachelors,5,62,69,10,44,1.0,3,34,Urban,HR Executive,115800,0 +53640,Male,35,Bachelors,17,68,32,61,98,7.0,6,43,Semi-Urban,ML Engineer,80295,0 +53641,Male,22,Masters,2,2,44,58,37,4.0,3,81,Urban,HR Executive,29293,0 +53642,Male,51,Bachelors,10,25,16,17,55,1.0,0,13,Urban,HR Executive,120824,0 +53643,Male,36,Bachelors,4,3,28,67,50,3.0,5,80,Semi-Urban,Data Analyst,32502,0 +53644,Female,48,Diploma,5,21,21,4,67,2.0,5,79,Rural,HR Executive,70764,0 +53645,Female,55,PhD,5,7,75,91,18,2.0,6,92,Rural,Data Analyst,111470,1 +53646,Male,29,Bachelors,13,91,73,70,44,4.0,2,89,Urban,HR Executive,20876,1 +53647,Male,51,Bachelors,9,4,2,15,38,6.0,4,83,Urban,HR Executive,78353,0 +53648,Female,51,Bachelors,12,60,33,15,36,7.0,4,56,Semi-Urban,Manager,91595,0 +53649,Male,25,Bachelors,10,2,66,97,28,0.0,7,65,Semi-Urban,Software Engineer,83865,0 +53650,Female,48,Masters,17,9,10,74,27,8.0,1,80,Rural,Manager,144618,0 +53651,Male,22,Diploma,7,96,56,25,84,9.0,1,29,Rural,ML Engineer,138221,0 +53652,Male,50,Masters,7,77,87,1,20,0.0,2,41,Rural,Data Analyst,38178,0 +53653,Female,35,Bachelors,2,52,52,24,84,4.0,0,54,Urban,HR Executive,20848,0 +53654,Male,29,PhD,5,21,99,87,15,9.0,0,48,Rural,Software Engineer,40187,1 +53655,Male,28,Diploma,5,52,49,51,77,4.0,0,99,Rural,HR Executive,38640,1 +53656,Female,31,Masters,5,29,93,13,73,8.0,1,3,Urban,Software Engineer,36154,0 +53657,Male,51,Bachelors,5,58,21,34,29,3.0,6,82,Urban,Manager,74899,0 +53658,Male,23,Bachelors,4,60,16,26,62,6.0,0,37,Urban,ML Engineer,129855,0 +53659,Other,52,Bachelors,16,55,45,95,38,2.0,7,27,Urban,Manager,48711,0 +53660,Female,43,Bachelors,13,9,69,87,30,7.0,3,55,Urban,Manager,64861,0 +53661,Male,21,High School,13,47,0,2,7,2.0,2,93,Urban,HR Executive,65070,0 +53662,Male,36,Diploma,12,9,63,7,87,8.0,2,22,Urban,HR Executive,133054,0 +53663,Female,48,Diploma,13,1,90,27,97,5.0,7,79,Rural,Manager,132236,0 +53664,Male,22,Bachelors,2,32,5,29,18,5.0,3,44,Urban,Manager,111560,0 +53665,Male,54,Masters,4,84,83,85,76,4.0,0,83,Urban,ML Engineer,99631,1 +53666,Male,46,High School,3,13,94,39,49,5.0,2,77,Semi-Urban,Software Engineer,73790,0 +53667,Male,55,High School,8,86,70,18,38,0.0,7,37,Semi-Urban,Software Engineer,134819,0 +53668,Male,29,Bachelors,6,92,36,54,35,1.0,6,54,Semi-Urban,HR Executive,105796,1 +53669,Female,22,Bachelors,10,40,36,18,13,8.0,7,38,Urban,Data Analyst,38601,0 +53670,Male,21,Masters,13,60,31,84,84,5.0,0,81,Semi-Urban,Data Analyst,80490,1 +53671,Male,49,High School,9,16,83,89,72,4.0,4,70,Urban,HR Executive,145799,1 +53672,Male,38,Bachelors,7,82,13,29,17,9.0,3,31,Urban,Software Engineer,80210,0 +53673,Female,36,Diploma,6,48,78,97,95,1.0,6,9,Rural,Data Analyst,96134,0 +53674,Male,54,Bachelors,7,29,13,92,57,7.0,0,84,Rural,ML Engineer,78126,0 +53675,Male,47,Masters,17,92,80,27,34,1.0,0,69,Rural,HR Executive,99576,1 +53676,Male,58,High School,1,59,36,48,14,6.0,3,54,Semi-Urban,Software Engineer,138544,0 +53677,Male,24,Bachelors,10,52,72,37,68,0.0,3,9,Semi-Urban,HR Executive,147583,0 +53678,Male,29,High School,19,17,17,93,86,0.0,0,87,Semi-Urban,Data Analyst,57989,0 +53679,Male,26,Bachelors,3,34,62,16,29,3.0,4,56,Rural,Manager,93194,0 +53680,Male,36,Bachelors,19,98,52,60,18,1.0,3,21,Urban,HR Executive,51482,0 +53681,Female,26,Bachelors,7,61,15,42,77,9.0,4,12,Urban,Manager,115766,0 +53682,Female,29,Bachelors,18,55,77,66,25,7.0,4,88,Semi-Urban,HR Executive,66836,1 +53683,Female,43,Masters,3,14,85,69,13,3.0,3,28,Rural,HR Executive,44936,0 +53684,Male,24,Bachelors,15,62,27,58,36,7.0,7,71,Rural,HR Executive,69325,0 +53685,Female,41,Masters,4,23,87,36,90,1.0,4,43,Semi-Urban,Software Engineer,44421,0 +53686,Male,45,High School,9,82,52,84,67,9.0,6,23,Rural,Data Analyst,86114,1 +53687,Male,39,Masters,2,10,7,66,66,0.0,7,91,Urban,HR Executive,76268,0 +53688,Male,53,Bachelors,17,78,43,61,68,2.0,3,36,Urban,Manager,117678,0 +53689,Female,52,Masters,14,61,34,91,12,2.0,2,78,Urban,Manager,96960,1 +53690,Male,53,Masters,4,88,81,90,49,2.0,6,95,Rural,Manager,141786,1 +53691,Male,38,Diploma,18,45,3,7,17,6.0,3,42,Urban,Software Engineer,140077,0 +53692,Other,53,Diploma,15,55,37,72,41,0.0,2,84,Semi-Urban,Manager,51563,1 +53693,Male,44,Bachelors,4,25,90,54,53,9.0,0,83,Rural,Software Engineer,64109,1 +53694,Male,34,Diploma,11,63,70,72,85,3.0,1,13,Semi-Urban,Data Analyst,62716,0 +53695,Male,59,PhD,11,24,33,37,97,3.0,2,99,Urban,HR Executive,72960,0 +53696,Male,43,Bachelors,13,18,71,3,84,2.0,3,66,Urban,Software Engineer,132286,0 +53697,Female,42,Bachelors,16,34,79,51,62,1.0,7,2,Urban,Data Analyst,112500,0 +53698,Male,26,Masters,2,4,25,81,80,7.0,7,24,Rural,Software Engineer,142711,0 +53699,Male,37,Masters,11,37,2,50,24,8.0,4,13,Urban,Data Analyst,49385,0 +53700,Male,28,Diploma,10,58,72,88,73,9.0,4,7,Rural,ML Engineer,76387,0 +53701,Male,42,PhD,4,76,21,51,82,2.0,5,35,Urban,HR Executive,144526,0 +53702,Male,36,High School,3,90,85,45,32,3.0,3,43,Semi-Urban,HR Executive,60573,1 +53703,Male,36,Masters,19,88,85,3,13,6.0,3,60,Rural,ML Engineer,70296,1 +53704,Female,43,Bachelors,18,25,30,2,95,8.0,7,86,Rural,Data Analyst,89655,0 +53705,Male,33,Bachelors,19,22,19,16,38,6.0,1,96,Urban,ML Engineer,85554,0 +53706,Female,52,PhD,1,18,95,57,32,8.0,2,28,Urban,ML Engineer,138741,0 +53707,Female,47,Bachelors,18,98,30,3,13,6.0,5,62,Urban,Software Engineer,145920,0 +53708,Male,41,Masters,1,72,7,67,90,3.0,5,66,Urban,HR Executive,48189,0 +53709,Male,23,Bachelors,13,33,59,34,32,6.0,6,38,Urban,Software Engineer,72519,0 +53710,Male,41,High School,13,23,69,71,8,1.0,1,39,Urban,HR Executive,65581,0 +53711,Male,47,PhD,12,8,70,17,62,4.0,1,73,Urban,Software Engineer,139260,0 +53712,Female,35,High School,8,69,78,41,31,1.0,0,45,Urban,Manager,104742,0 +53713,Male,55,PhD,19,63,44,92,28,4.0,1,54,Semi-Urban,HR Executive,137191,1 +53714,Other,58,Diploma,9,45,64,19,56,4.0,5,37,Rural,ML Engineer,43511,0 +53715,Female,44,Masters,16,52,13,50,51,7.0,1,17,Urban,HR Executive,131662,0 +53716,Female,35,Masters,2,93,75,19,10,8.0,4,78,Rural,Data Analyst,39983,1 +53717,Male,31,Bachelors,13,22,70,22,80,0.0,5,23,Semi-Urban,Software Engineer,25757,0 +53718,Male,55,High School,7,99,92,12,25,5.0,7,8,Urban,Manager,141103,0 +53719,Male,59,Diploma,7,72,80,59,62,2.0,2,68,Rural,HR Executive,46203,1 +53720,Female,48,High School,10,52,31,28,93,0.0,5,71,Semi-Urban,HR Executive,132333,0 +53721,Male,24,Masters,12,92,97,71,27,0.0,6,73,Urban,Data Analyst,59369,1 +53722,Female,47,High School,6,99,70,19,19,2.0,0,61,Urban,Manager,112418,1 +53723,Male,33,Masters,13,8,82,8,71,1.0,7,34,Semi-Urban,HR Executive,42328,0 +53724,Male,32,Bachelors,11,26,2,68,65,2.0,4,35,Urban,HR Executive,130845,0 +53725,Male,35,Diploma,1,43,16,73,42,7.0,2,17,Rural,Software Engineer,148438,0 +53726,Male,35,Bachelors,5,84,50,66,90,2.0,6,68,Semi-Urban,Software Engineer,24276,1 +53727,Male,51,Bachelors,7,58,76,48,77,6.0,2,31,Urban,ML Engineer,139472,0 +53728,Male,54,Bachelors,19,82,50,20,56,0.0,3,53,Semi-Urban,Data Analyst,147378,0 +53729,Male,24,Diploma,4,72,37,98,36,2.0,2,42,Rural,Software Engineer,82786,1 +53730,Female,58,Bachelors,17,56,86,89,11,6.0,0,70,Semi-Urban,Software Engineer,146995,1 +53731,Male,43,Bachelors,8,97,29,84,78,7.0,5,34,Rural,ML Engineer,78398,1 +53732,Female,47,High School,15,60,30,18,11,4.0,7,94,Semi-Urban,ML Engineer,59511,0 +53733,Female,28,Bachelors,10,0,10,6,86,0.0,1,99,Urban,HR Executive,99321,0 +53734,Male,53,Diploma,9,32,93,7,4,8.0,6,29,Semi-Urban,HR Executive,39913,0 +53735,Male,40,Diploma,3,76,52,19,92,9.0,1,81,Semi-Urban,Data Analyst,39358,0 +53736,Male,32,Bachelors,2,13,72,62,39,1.0,7,57,Urban,Manager,98216,0 +53737,Male,22,Bachelors,8,98,72,46,59,2.0,0,66,Urban,ML Engineer,98257,1 +53738,Female,38,Diploma,13,74,66,15,84,3.0,7,96,Semi-Urban,ML Engineer,102431,1 +53739,Other,56,Masters,1,9,48,33,25,5.0,4,16,Semi-Urban,Manager,112088,0 +53740,Male,24,High School,7,59,67,84,22,2.0,0,40,Semi-Urban,Software Engineer,40048,1 +53741,Female,49,High School,13,94,35,4,9,9.0,3,59,Semi-Urban,Data Analyst,54037,0 +53742,Female,46,High School,7,36,5,22,66,2.0,0,9,Urban,Manager,128575,0 +53743,Male,22,Masters,9,9,3,26,62,0.0,4,84,Urban,ML Engineer,124797,0 +53744,Male,43,Bachelors,4,30,98,57,66,5.0,7,36,Semi-Urban,Data Analyst,29412,0 +53745,Male,57,Bachelors,11,42,65,96,36,0.0,4,9,Semi-Urban,Manager,113357,0 +53746,Male,50,Bachelors,4,81,78,19,46,4.0,4,79,Urban,Software Engineer,59346,1 +53747,Male,25,High School,18,28,91,63,43,4.0,3,45,Rural,Software Engineer,29264,0 +53748,Male,46,Masters,9,81,67,48,5,7.0,1,96,Urban,Manager,123079,1 +53749,Male,29,High School,15,97,39,93,43,6.0,5,15,Urban,Data Analyst,142414,1 +53750,Female,35,Bachelors,10,64,61,96,78,5.0,3,52,Urban,Data Analyst,27872,1 +53751,Male,49,Bachelors,13,54,83,42,2,8.0,1,0,Rural,Software Engineer,116666,0 +53752,Male,31,Masters,10,79,59,72,35,5.0,1,84,Semi-Urban,Manager,59524,1 +53753,Male,59,Masters,19,14,56,36,83,3.0,6,58,Rural,Software Engineer,69312,0 +53754,Male,49,Bachelors,10,93,18,26,61,3.0,0,41,Rural,HR Executive,140838,0 +53755,Female,33,Masters,12,10,57,17,81,0.0,0,59,Urban,Manager,76780,0 +53756,Female,49,High School,1,5,92,87,63,3.0,3,59,Rural,HR Executive,138600,1 +53757,Male,49,High School,3,17,92,42,28,5.0,7,95,Rural,Manager,40054,1 +53758,Female,39,Bachelors,18,17,31,17,61,5.0,1,67,Urban,Manager,35850,0 +53759,Male,25,Diploma,11,56,47,21,6,1.0,5,72,Semi-Urban,HR Executive,133756,0 +53760,Male,42,Bachelors,4,37,74,42,44,4.0,6,40,Semi-Urban,Manager,44727,0 +53761,Other,53,Diploma,8,1,29,63,29,4.0,1,28,Urban,Manager,145171,0 +53762,Female,51,Bachelors,13,45,61,65,40,7.0,0,75,Urban,Manager,103571,1 +53763,Female,56,PhD,7,67,16,64,34,0.0,0,35,Rural,Software Engineer,71973,0 +53764,Female,44,Bachelors,10,95,45,61,24,1.0,5,42,Urban,Software Engineer,40201,1 +53765,Male,56,Bachelors,14,19,1,37,37,3.0,6,57,Urban,Software Engineer,83703,0 +53766,Male,39,Masters,3,60,7,86,85,0.0,3,39,Urban,Software Engineer,56579,0 +53767,Male,41,Masters,16,74,43,43,98,3.0,3,19,Rural,HR Executive,77452,0 +53768,Female,39,Masters,17,97,13,18,25,4.0,5,0,Rural,Software Engineer,99221,0 +53769,Female,33,Bachelors,11,71,2,67,85,4.0,5,88,Rural,Data Analyst,114769,0 +53770,Female,41,Bachelors,13,7,92,80,9,9.0,6,95,Urban,Data Analyst,54210,1 +53771,Male,27,Bachelors,10,85,53,23,29,8.0,4,8,Rural,HR Executive,67918,0 +53772,Female,28,Bachelors,13,42,84,6,65,8.0,6,79,Urban,Data Analyst,30899,0 +53773,Female,29,Bachelors,13,6,41,7,58,5.0,3,84,Rural,Data Analyst,118895,0 +53774,Male,52,Diploma,10,93,73,5,91,6.0,7,50,Urban,Data Analyst,61068,0 +53775,Male,28,Bachelors,10,7,0,60,3,6.0,1,69,Rural,HR Executive,127000,0 +53776,Female,30,Diploma,0,63,43,79,12,6.0,6,5,Urban,Data Analyst,110891,0 +53777,Female,21,Masters,10,33,25,27,6,1.0,1,95,Urban,HR Executive,117594,0 +53778,Male,58,Bachelors,9,79,96,28,94,5.0,5,79,Urban,ML Engineer,65140,1 +53779,Male,51,Bachelors,11,2,92,22,13,4.0,6,4,Urban,Manager,66848,0 +53780,Male,50,Bachelors,5,2,63,19,76,5.0,5,63,Semi-Urban,ML Engineer,137515,0 +53781,Female,35,High School,6,17,51,40,42,6.0,0,72,Semi-Urban,Data Analyst,146977,0 +53782,Other,31,Masters,10,72,23,25,68,8.0,4,20,Rural,Software Engineer,92487,0 +53783,Female,41,Bachelors,8,92,4,13,55,1.0,5,51,Urban,Data Analyst,32790,0 +53784,Male,36,High School,13,86,90,84,2,7.0,1,75,Urban,HR Executive,81415,1 +53785,Female,46,High School,19,5,24,91,64,0.0,2,44,Semi-Urban,Manager,24898,0 +53786,Male,27,Diploma,11,78,92,3,62,7.0,0,12,Urban,ML Engineer,32889,0 +53787,Female,31,Bachelors,4,53,45,52,31,6.0,0,64,Urban,Data Analyst,74987,0 +53788,Male,50,Bachelors,10,15,28,71,34,1.0,3,89,Urban,HR Executive,69793,0 +53789,Female,54,PhD,14,72,41,47,20,1.0,7,69,Urban,Data Analyst,52528,0 +53790,Male,52,High School,18,50,0,23,61,2.0,7,8,Rural,Data Analyst,68518,0 +53791,Female,38,Bachelors,7,73,62,61,4,1.0,0,19,Rural,Manager,85399,0 +53792,Male,51,Diploma,2,43,79,58,80,1.0,2,30,Urban,Software Engineer,20828,0 +53793,Male,47,Masters,14,1,63,14,73,4.0,5,89,Rural,Manager,39649,0 +53794,Male,50,Bachelors,0,58,89,79,13,2.0,6,92,Urban,ML Engineer,43747,1 +53795,Male,31,Bachelors,6,21,96,87,8,8.0,3,53,Semi-Urban,ML Engineer,122827,1 +53796,Male,28,Bachelors,3,62,85,70,74,4.0,6,42,Rural,Manager,91193,1 +53797,Male,34,Diploma,19,95,91,30,16,0.0,7,26,Rural,HR Executive,46039,1 +53798,Male,52,Diploma,11,39,49,38,90,6.0,5,47,Urban,ML Engineer,39085,0 +53799,Female,38,Masters,2,73,45,54,59,5.0,6,86,Rural,Data Analyst,76664,1 +53800,Other,53,Bachelors,12,38,51,99,73,7.0,5,38,Rural,Manager,76837,0 +53801,Male,45,Bachelors,6,57,20,83,99,7.0,2,89,Rural,Manager,126819,1 +53802,Male,49,Bachelors,18,5,8,51,87,4.0,2,30,Urban,Manager,145023,0 +53803,Male,54,Diploma,15,45,57,47,85,2.0,1,60,Semi-Urban,Manager,24784,0 +53804,Male,43,Bachelors,2,31,21,96,17,4.0,3,82,Urban,Manager,146594,0 +53805,Female,49,Diploma,3,64,70,66,63,4.0,0,25,Semi-Urban,Software Engineer,125698,0 +53806,Male,43,Bachelors,9,95,25,64,81,9.0,5,33,Semi-Urban,Data Analyst,136536,0 +53807,Female,55,Diploma,2,70,11,98,85,2.0,3,13,Urban,Data Analyst,141821,0 +53808,Male,21,Bachelors,12,56,99,36,2,3.0,3,44,Rural,Manager,50122,1 +53809,Female,43,Bachelors,14,61,48,14,20,5.0,2,0,Urban,Manager,115925,0 +53810,Other,56,Bachelors,13,50,76,22,86,9.0,5,74,Semi-Urban,ML Engineer,34497,0 +53811,Male,21,Bachelors,11,44,51,72,2,1.0,3,68,Urban,Software Engineer,141730,1 +53812,Other,23,Bachelors,10,10,33,88,84,4.0,2,44,Urban,Data Analyst,93496,0 +53813,Male,32,Masters,0,57,91,15,11,5.0,1,61,Urban,HR Executive,91650,0 +53814,Male,38,Bachelors,10,63,52,15,9,4.0,2,36,Semi-Urban,Data Analyst,84077,0 +53815,Other,54,Bachelors,10,60,76,64,96,5.0,4,57,Urban,Software Engineer,26870,1 +53816,Female,44,Bachelors,5,43,17,25,80,1.0,5,93,Urban,Data Analyst,29609,0 +53817,Male,39,Diploma,1,21,51,66,27,3.0,4,81,Urban,Data Analyst,103231,0 +53818,Male,22,High School,17,89,6,81,34,4.0,0,87,Semi-Urban,Software Engineer,38126,1 +53819,Male,53,High School,19,84,55,93,59,4.0,2,6,Rural,HR Executive,119597,1 +53820,Female,42,Diploma,1,67,79,15,83,7.0,4,17,Semi-Urban,ML Engineer,109181,0 +53821,Female,22,Masters,6,96,98,19,48,4.0,5,36,Urban,ML Engineer,58150,1 +53822,Male,26,Bachelors,19,42,26,91,73,3.0,4,99,Semi-Urban,Software Engineer,20733,1 +53823,Female,40,Diploma,3,5,35,84,23,7.0,5,70,Urban,ML Engineer,147454,0 +53824,Male,44,Diploma,8,36,42,57,88,5.0,7,79,Rural,Manager,81583,0 +53825,Male,36,Bachelors,19,66,75,15,62,9.0,4,72,Semi-Urban,Software Engineer,149341,0 +53826,Male,52,High School,12,61,95,72,22,5.0,2,19,Urban,Data Analyst,87750,1 +53827,Male,22,Diploma,8,23,56,94,99,0.0,2,92,Semi-Urban,HR Executive,135789,1 +53828,Male,49,Masters,19,56,35,66,18,2.0,1,80,Urban,Software Engineer,129228,1 +53829,Male,53,High School,16,26,35,69,25,1.0,3,30,Urban,Software Engineer,59271,0 +53830,Male,39,Diploma,13,17,89,70,14,0.0,4,15,Urban,Manager,29112,0 +53831,Male,30,Bachelors,7,55,20,44,68,1.0,7,18,Rural,ML Engineer,112920,0 +53832,Male,59,Diploma,11,46,20,51,8,1.0,6,71,Urban,Manager,86672,0 +53833,Male,48,Diploma,15,87,48,29,1,9.0,0,61,Semi-Urban,Software Engineer,92969,0 +53834,Male,25,Diploma,12,73,31,76,83,8.0,5,26,Semi-Urban,Software Engineer,27204,0 +53835,Male,42,Masters,13,99,89,84,76,3.0,5,89,Rural,Data Analyst,145273,1 +53836,Male,39,Diploma,16,86,17,18,79,1.0,0,75,Semi-Urban,Data Analyst,121184,0 +53837,Other,24,Bachelors,15,19,22,41,61,0.0,6,62,Rural,HR Executive,85406,0 +53838,Male,40,PhD,5,73,56,28,11,7.0,4,30,Semi-Urban,HR Executive,89928,0 +53839,Male,29,Masters,18,96,58,93,19,3.0,4,76,Rural,Manager,113330,1 +53840,Female,40,Masters,7,50,24,65,57,3.0,2,33,Semi-Urban,Data Analyst,121634,0 +53841,Male,38,Masters,9,53,8,51,56,5.0,4,95,Urban,HR Executive,38994,0 +53842,Male,50,Masters,16,93,79,26,90,6.0,0,85,Rural,Manager,116829,1 +53843,Male,47,High School,2,62,45,24,13,9.0,4,77,Urban,Data Analyst,50724,0 +53844,Male,47,Masters,2,66,86,97,14,7.0,4,25,Urban,Software Engineer,58711,1 +53845,Female,34,Diploma,13,15,91,77,32,5.0,1,4,Rural,Data Analyst,125516,0 +53846,Male,45,PhD,12,43,1,68,29,2.0,1,29,Semi-Urban,Software Engineer,58730,0 +53847,Male,43,Diploma,1,42,19,14,65,3.0,7,14,Urban,ML Engineer,73922,0 +53848,Male,55,Bachelors,6,71,53,27,6,2.0,5,90,Urban,Manager,100787,1 +53849,Male,26,Diploma,19,98,62,95,41,4.0,7,68,Urban,ML Engineer,144414,1 +53850,Male,30,Bachelors,7,79,19,68,28,6.0,0,2,Urban,Software Engineer,26957,0 +53851,Male,21,Diploma,11,71,37,73,4,5.0,3,32,Urban,HR Executive,95894,0 +53852,Female,40,High School,0,1,91,59,72,4.0,0,14,Urban,Software Engineer,94933,0 +53853,Female,23,Bachelors,19,0,33,88,50,1.0,3,99,Urban,HR Executive,54039,0 +53854,Male,45,Bachelors,1,87,64,68,29,4.0,7,24,Urban,HR Executive,27190,1 +53855,Female,59,Diploma,19,42,42,12,76,8.0,7,48,Urban,Software Engineer,145073,0 +53856,Female,40,Bachelors,0,39,42,93,0,6.0,7,36,Urban,ML Engineer,106470,0 +53857,Other,56,Masters,14,98,65,36,70,5.0,5,34,Urban,HR Executive,100654,0 +53858,Male,52,Masters,0,9,17,57,25,6.0,1,51,Semi-Urban,ML Engineer,103194,0 +53859,Female,35,Masters,18,65,73,12,63,8.0,1,69,Urban,Data Analyst,70330,0 +53860,Male,59,Masters,14,95,34,17,6,3.0,0,91,Urban,ML Engineer,41829,1 +53861,Female,21,Bachelors,6,79,73,5,67,3.0,7,58,Urban,HR Executive,94193,0 +53862,Male,59,Diploma,14,21,83,43,17,6.0,0,93,Urban,Software Engineer,37984,1 +53863,Female,48,PhD,13,49,37,95,66,8.0,0,54,Rural,Manager,55728,0 +53864,Male,49,Bachelors,7,67,89,4,64,4.0,6,62,Rural,Data Analyst,67477,0 +53865,Female,52,Bachelors,10,59,36,44,22,0.0,2,87,Urban,Software Engineer,77651,0 +53866,Male,21,Masters,11,30,3,91,71,3.0,6,58,Semi-Urban,Data Analyst,114968,0 +53867,Female,28,Diploma,8,18,30,66,66,6.0,2,14,Urban,ML Engineer,98153,0 +53868,Other,54,Bachelors,16,3,54,64,80,2.0,0,55,Semi-Urban,Manager,134664,0 +53869,Male,23,Masters,14,82,62,60,54,2.0,1,82,Urban,Software Engineer,109367,1 +53870,Male,59,Bachelors,0,75,63,87,86,0.0,3,48,Urban,HR Executive,126148,1 +53871,Male,45,Masters,16,49,39,37,74,7.0,7,79,Urban,ML Engineer,78932,0 +53872,Male,30,Bachelors,18,5,48,74,84,6.0,1,32,Urban,ML Engineer,25003,0 +53873,Female,36,Diploma,12,47,88,94,19,2.0,6,69,Urban,ML Engineer,86048,1 +53874,Male,33,Bachelors,14,21,23,95,41,0.0,5,95,Urban,ML Engineer,23576,0 +53875,Male,30,Bachelors,10,60,74,15,60,9.0,7,2,Urban,Data Analyst,123967,0 +53876,Female,53,Bachelors,4,14,92,66,89,4.0,6,78,Urban,Data Analyst,80266,1 +53877,Male,59,High School,8,41,35,7,64,9.0,3,92,Urban,HR Executive,142649,0 +53878,Male,26,Bachelors,12,96,72,13,73,2.0,7,87,Urban,Software Engineer,115273,1 +53879,Male,25,Bachelors,6,50,68,38,17,7.0,5,27,Semi-Urban,ML Engineer,133874,0 +53880,Male,21,Diploma,13,94,15,62,5,2.0,4,94,Rural,Manager,21357,1 +53881,Male,59,Masters,6,52,51,15,26,8.0,0,18,Urban,Data Analyst,80444,0 +53882,Male,48,Diploma,3,54,45,74,34,7.0,2,88,Semi-Urban,Data Analyst,70340,1 +53883,Male,24,High School,9,66,87,87,68,8.0,2,54,Rural,ML Engineer,139940,1 +53884,Female,54,Diploma,11,70,1,43,64,1.0,7,37,Semi-Urban,Data Analyst,31963,0 +53885,Male,57,Bachelors,8,17,20,13,47,7.0,2,51,Semi-Urban,HR Executive,139387,0 +53886,Female,22,High School,10,97,77,2,8,1.0,3,80,Urban,HR Executive,75009,1 +53887,Female,48,Bachelors,6,88,11,67,21,3.0,3,49,Urban,Data Analyst,27824,0 +53888,Male,23,Bachelors,10,91,0,85,34,2.0,3,6,Semi-Urban,Software Engineer,123684,0 +53889,Female,46,Bachelors,16,61,50,44,69,3.0,4,3,Urban,Manager,91995,0 +53890,Male,28,Bachelors,8,42,12,57,17,9.0,1,59,Semi-Urban,ML Engineer,83871,0 +53891,Female,43,High School,17,6,6,48,9,6.0,7,58,Semi-Urban,HR Executive,21644,0 +53892,Female,39,Masters,2,57,82,83,34,5.0,0,47,Urban,HR Executive,114716,1 +53893,Male,23,Diploma,10,29,14,5,18,1.0,6,23,Urban,HR Executive,127944,0 +53894,Female,47,High School,12,54,5,78,89,5.0,6,79,Urban,Software Engineer,146805,0 +53895,Male,33,Masters,10,85,9,20,9,1.0,3,34,Urban,Software Engineer,51703,0 +53896,Male,56,PhD,2,84,18,33,97,9.0,2,83,Semi-Urban,Manager,59203,0 +53897,Male,49,Bachelors,5,6,76,82,94,9.0,7,84,Urban,Data Analyst,38128,1 +53898,Female,54,Masters,9,61,61,89,75,0.0,3,41,Urban,Manager,51370,1 +53899,Male,21,Bachelors,10,53,39,17,66,9.0,2,38,Rural,Manager,58780,0 +53900,Male,35,Bachelors,19,1,86,8,31,2.0,1,5,Urban,ML Engineer,111258,0 +53901,Female,38,Bachelors,17,91,96,13,24,8.0,3,52,Semi-Urban,Software Engineer,137550,1 +53902,Female,30,Bachelors,2,75,62,12,52,5.0,6,85,Urban,HR Executive,79859,0 +53903,Female,26,Bachelors,4,70,9,78,77,2.0,3,78,Urban,ML Engineer,89384,0 +53904,Male,31,High School,13,95,20,8,17,5.0,1,46,Urban,Software Engineer,77228,0 +53905,Male,41,Masters,5,23,28,15,94,6.0,1,7,Rural,Manager,49178,0 +53906,Female,53,Diploma,17,42,81,39,72,3.0,0,21,Semi-Urban,Software Engineer,99713,0 +53907,Male,33,Diploma,14,95,13,56,11,2.0,4,93,Urban,Manager,94306,1 +53908,Female,59,Bachelors,3,90,86,81,41,3.0,2,87,Urban,HR Executive,147937,1 +53909,Male,30,Diploma,9,98,13,41,89,2.0,6,66,Urban,Software Engineer,45638,0 +53910,Female,34,Bachelors,2,59,26,45,34,4.0,1,27,Urban,HR Executive,116212,0 +53911,Female,37,Bachelors,15,42,32,76,10,1.0,5,23,Urban,Software Engineer,36612,0 +53912,Female,34,Diploma,8,47,79,3,16,1.0,5,46,Rural,Software Engineer,108857,0 +53913,Male,21,Bachelors,11,11,12,27,12,8.0,1,99,Urban,ML Engineer,125532,0 +53914,Female,42,High School,2,23,28,72,57,6.0,4,56,Urban,Data Analyst,28340,0 +53915,Male,45,Masters,7,18,84,88,58,8.0,7,82,Semi-Urban,HR Executive,76615,1 +53916,Male,32,Bachelors,2,92,38,79,62,9.0,0,18,Urban,ML Engineer,128822,0 +53917,Male,55,Bachelors,2,52,39,46,69,5.0,0,46,Urban,HR Executive,82027,0 +53918,Male,33,Diploma,16,13,10,51,36,4.0,2,27,Rural,Data Analyst,48332,0 +53919,Male,34,Bachelors,2,25,28,42,56,8.0,0,75,Semi-Urban,Data Analyst,58854,0 +53920,Other,47,Bachelors,15,93,44,70,95,4.0,7,15,Rural,HR Executive,31004,0 +53921,Male,57,Diploma,6,88,85,63,93,4.0,4,78,Rural,ML Engineer,77871,1 +53922,Male,35,Bachelors,7,75,10,90,75,4.0,0,28,Urban,Data Analyst,112072,0 +53923,Other,36,Masters,4,78,3,70,18,3.0,2,93,Rural,Software Engineer,78650,1 +53924,Male,52,Bachelors,5,24,48,2,8,8.0,7,42,Semi-Urban,HR Executive,47052,0 +53925,Male,49,Diploma,19,53,41,57,13,3.0,5,24,Rural,Manager,23621,0 +53926,Male,24,Bachelors,13,67,89,84,75,3.0,2,55,Urban,Manager,122882,1 +53927,Male,31,Diploma,16,52,1,48,22,4.0,6,70,Rural,ML Engineer,147805,0 +53928,Male,50,Masters,5,81,92,64,12,8.0,4,55,Rural,ML Engineer,42147,1 +53929,Male,38,Diploma,15,73,54,44,62,3.0,4,41,Urban,Manager,83542,0 +53930,Female,46,High School,8,20,21,98,63,8.0,7,1,Urban,Software Engineer,63198,0 +53931,Female,50,Diploma,10,18,8,29,21,7.0,1,5,Urban,HR Executive,56260,0 +53932,Female,42,Masters,2,25,36,19,23,6.0,3,22,Semi-Urban,ML Engineer,83064,0 +53933,Male,37,Diploma,6,72,7,84,90,1.0,7,8,Semi-Urban,Manager,112897,0 +53934,Male,49,Masters,19,93,33,85,30,2.0,3,2,Urban,Software Engineer,33367,0 +53935,Male,44,High School,8,22,54,47,18,4.0,2,61,Urban,Data Analyst,144282,0 +53936,Male,35,High School,16,33,91,48,2,2.0,5,13,Urban,ML Engineer,43929,0 +53937,Female,49,Masters,5,23,44,40,32,6.0,4,68,Urban,Manager,78247,0 +53938,Male,45,Masters,11,32,22,46,58,3.0,4,4,Semi-Urban,HR Executive,124535,0 +53939,Other,30,Bachelors,4,81,59,38,51,0.0,7,89,Urban,Manager,114974,1 +53940,Male,42,Bachelors,15,8,5,38,24,0.0,7,15,Rural,Manager,20077,0 +53941,Male,40,Bachelors,7,0,29,63,9,2.0,7,2,Urban,Manager,148506,0 +53942,Male,34,Bachelors,3,52,1,3,28,6.0,7,12,Rural,Software Engineer,50184,0 +53943,Male,33,Bachelors,12,53,36,18,63,5.0,2,93,Semi-Urban,HR Executive,147746,0 +53944,Female,34,Bachelors,1,5,9,45,0,6.0,6,8,Urban,HR Executive,148774,0 +53945,Female,53,Diploma,1,70,39,85,69,5.0,1,81,Semi-Urban,ML Engineer,59381,1 +53946,Male,49,Diploma,14,63,50,13,79,3.0,1,51,Urban,HR Executive,80680,0 +53947,Male,51,Bachelors,16,82,25,5,57,3.0,1,33,Rural,Data Analyst,126112,0 +53948,Male,21,Diploma,8,65,13,41,16,1.0,6,16,Semi-Urban,Software Engineer,59671,0 +53949,Male,50,Masters,4,68,84,83,19,9.0,7,6,Urban,Manager,24679,1 +53950,Male,46,Bachelors,7,15,55,59,59,1.0,6,49,Urban,Data Analyst,145395,0 +53951,Female,46,Bachelors,18,88,31,72,79,0.0,0,57,Urban,ML Engineer,63780,1 +53952,Female,57,Masters,13,40,63,50,45,4.0,2,36,Rural,HR Executive,97611,0 +53953,Male,29,Bachelors,10,94,63,20,26,9.0,1,56,Urban,Data Analyst,28686,0 +53954,Male,32,Masters,15,50,11,23,4,1.0,2,84,Rural,HR Executive,33380,0 +53955,Female,45,Bachelors,0,16,25,60,0,6.0,0,73,Semi-Urban,Data Analyst,100940,0 +53956,Male,24,Masters,0,53,31,71,28,2.0,6,84,Semi-Urban,Manager,49414,1 +53957,Male,26,Masters,8,29,11,72,42,6.0,5,55,Urban,Software Engineer,21744,0 +53958,Male,50,Masters,3,17,50,97,14,3.0,3,20,Urban,ML Engineer,145587,0 +53959,Male,44,Diploma,4,27,81,56,31,3.0,4,94,Semi-Urban,Data Analyst,26058,1 +53960,Male,45,Diploma,14,57,35,88,30,7.0,1,96,Urban,Software Engineer,75056,1 +53961,Male,50,Masters,8,80,93,66,62,9.0,4,10,Urban,Manager,135457,1 +53962,Male,29,Diploma,4,16,70,29,4,3.0,6,75,Rural,HR Executive,95918,0 +53963,Female,32,Diploma,8,44,49,95,91,5.0,3,38,Urban,Data Analyst,25191,0 +53964,Male,46,Bachelors,2,22,16,71,6,3.0,0,32,Urban,HR Executive,123253,0 +53965,Male,28,Bachelors,11,6,10,21,55,4.0,1,98,Urban,Manager,50062,0 +53966,Female,39,High School,14,76,71,64,82,4.0,5,44,Urban,Software Engineer,36064,1 +53967,Female,53,Diploma,17,16,20,34,23,9.0,5,45,Urban,HR Executive,29565,0 +53968,Male,24,Bachelors,7,56,61,97,77,8.0,3,55,Rural,HR Executive,90085,1 +53969,Other,32,Bachelors,14,45,4,30,34,8.0,3,26,Urban,Data Analyst,68809,0 +53970,Male,28,High School,10,17,84,63,54,3.0,2,45,Urban,HR Executive,42986,0 +53971,Female,25,High School,8,16,20,79,23,5.0,3,48,Urban,Data Analyst,47276,0 +53972,Other,52,High School,19,33,23,49,41,0.0,2,36,Urban,HR Executive,144023,0 +53973,Female,25,Bachelors,3,77,88,13,74,3.0,3,75,Urban,ML Engineer,71142,1 +53974,Female,22,Bachelors,12,97,94,79,66,8.0,6,29,Semi-Urban,ML Engineer,63926,1 +53975,Female,25,Masters,1,80,53,64,98,0.0,3,32,Urban,Data Analyst,121486,0 +53976,Male,43,Bachelors,13,86,29,56,47,7.0,0,96,Rural,ML Engineer,140426,1 +53977,Male,25,Diploma,13,0,9,76,39,0.0,1,92,Urban,ML Engineer,131758,0 +53978,Female,37,Masters,18,49,92,17,62,5.0,3,32,Rural,ML Engineer,96813,0 +53979,Female,58,Bachelors,13,31,60,75,21,0.0,4,84,Rural,HR Executive,121964,1 +53980,Female,30,Masters,13,16,44,0,12,1.0,4,50,Urban,Software Engineer,83234,0 +53981,Other,26,Masters,16,22,45,66,26,5.0,2,50,Urban,Software Engineer,125091,0 +53982,Male,41,Masters,19,89,5,95,34,1.0,2,29,Urban,Software Engineer,142781,0 +53983,Female,36,Bachelors,11,80,8,11,74,2.0,0,31,Urban,Manager,128439,0 +53984,Female,51,Bachelors,5,59,76,68,47,6.0,4,63,Urban,Data Analyst,149005,1 +53985,Male,53,Masters,11,51,66,39,78,1.0,0,75,Urban,ML Engineer,124045,0 +53986,Other,56,Bachelors,14,72,41,8,50,4.0,4,61,Urban,HR Executive,29015,0 +53987,Male,28,PhD,2,57,88,77,98,7.0,7,35,Semi-Urban,Data Analyst,111719,1 +53988,Other,39,High School,16,75,77,69,73,7.0,4,45,Urban,Data Analyst,37042,1 +53989,Female,22,Bachelors,6,85,0,61,54,7.0,4,27,Rural,HR Executive,97038,0 +53990,Male,46,High School,5,24,10,97,52,0.0,6,32,Urban,Manager,83234,0 +53991,Male,26,Diploma,14,92,73,25,87,6.0,1,33,Urban,ML Engineer,22708,0 +53992,Male,39,Bachelors,4,58,68,28,89,5.0,6,91,Urban,Data Analyst,110449,1 +53993,Male,42,Bachelors,3,70,65,43,26,5.0,6,65,Urban,Software Engineer,135134,1 +53994,Male,55,Diploma,12,41,34,8,73,6.0,3,79,Urban,Data Analyst,115653,0 +53995,Male,56,High School,7,7,94,16,60,8.0,1,45,Urban,ML Engineer,49708,0 +53996,Male,59,High School,2,68,29,85,85,8.0,4,69,Semi-Urban,Software Engineer,41400,1 +53997,Male,28,Diploma,1,36,99,23,49,2.0,0,62,Rural,Data Analyst,111149,0 +53998,Female,21,Masters,13,65,57,84,65,6.0,4,8,Urban,Data Analyst,136026,0 +53999,Male,47,High School,5,70,80,57,27,1.0,4,22,Urban,HR Executive,39491,0 +54000,Female,32,Diploma,8,25,2,97,24,3.0,7,99,Urban,Data Analyst,95505,0 +54001,Male,57,Bachelors,7,10,57,7,59,6.0,1,66,Urban,Manager,90175,0 +54002,Female,48,High School,2,81,12,9,35,6.0,1,60,Rural,HR Executive,64177,0 +54003,Female,34,Bachelors,2,43,76,96,83,1.0,7,51,Urban,Manager,61049,1 +54004,Male,23,Bachelors,3,81,71,91,61,5.0,5,25,Semi-Urban,HR Executive,142155,1 +54005,Male,39,Bachelors,19,9,15,95,85,5.0,5,10,Semi-Urban,HR Executive,49142,0 +54006,Female,40,Bachelors,13,74,94,74,97,2.0,5,85,Urban,HR Executive,81912,1 +54007,Male,49,High School,18,88,25,63,58,9.0,1,97,Semi-Urban,ML Engineer,47858,1 +54008,Male,57,Bachelors,7,36,39,50,31,6.0,6,90,Urban,Manager,136431,0 +54009,Male,54,High School,3,98,66,69,92,8.0,1,90,Semi-Urban,Software Engineer,143100,1 +54010,Male,32,Masters,18,86,92,23,26,9.0,1,45,Urban,HR Executive,21959,1 +54011,Female,31,Bachelors,15,11,99,87,38,5.0,6,60,Semi-Urban,ML Engineer,139288,1 +54012,Female,49,Bachelors,19,64,85,17,70,1.0,0,93,Urban,Manager,35295,1 +54013,Male,26,Diploma,3,79,70,2,38,4.0,2,93,Rural,ML Engineer,43156,1 +54014,Male,33,Masters,11,37,74,1,80,9.0,1,30,Rural,Manager,63301,0 +54015,Male,55,Masters,13,57,4,35,89,3.0,7,5,Urban,ML Engineer,101419,0 +54016,Other,32,Bachelors,9,27,55,58,48,4.0,0,39,Semi-Urban,Software Engineer,147797,0 +54017,Female,25,High School,17,77,19,87,9,5.0,1,23,Semi-Urban,ML Engineer,54606,0 +54018,Male,54,Diploma,4,14,36,91,87,8.0,7,49,Urban,ML Engineer,104355,0 +54019,Female,48,Bachelors,5,74,76,94,44,4.0,3,10,Urban,Software Engineer,41083,1 +54020,Other,32,Bachelors,2,71,40,67,3,5.0,4,2,Rural,Data Analyst,141332,0 +54021,Male,42,Bachelors,10,73,70,44,72,8.0,1,17,Semi-Urban,Data Analyst,43225,0 +54022,Female,41,High School,16,54,50,12,81,1.0,4,21,Rural,Data Analyst,65303,0 +54023,Male,38,Bachelors,6,60,20,66,99,9.0,4,43,Urban,ML Engineer,33537,0 +54024,Male,32,PhD,15,31,53,13,96,4.0,3,32,Urban,Manager,43148,0 +54025,Male,46,Masters,10,3,31,13,69,5.0,1,71,Semi-Urban,HR Executive,76639,0 +54026,Male,44,Bachelors,10,24,13,83,23,6.0,7,99,Urban,ML Engineer,28459,0 +54027,Female,54,Masters,7,78,60,47,20,7.0,6,77,Urban,HR Executive,36077,1 +54028,Female,31,Diploma,15,88,90,77,75,7.0,2,54,Urban,ML Engineer,61181,1 +54029,Male,30,Bachelors,14,43,24,87,44,1.0,6,66,Rural,Data Analyst,107207,0 +54030,Male,57,Diploma,13,1,59,29,69,4.0,2,17,Urban,HR Executive,25449,0 +54031,Male,35,Masters,0,17,94,44,77,1.0,7,9,Rural,Software Engineer,39057,0 +54032,Male,30,High School,5,61,38,83,39,1.0,3,34,Rural,HR Executive,123258,0 +54033,Female,30,Bachelors,11,30,85,29,13,3.0,6,96,Urban,Software Engineer,39568,0 +54034,Male,57,High School,6,4,85,17,79,2.0,7,17,Urban,Manager,106236,0 +54035,Male,39,Diploma,1,36,65,44,55,7.0,3,69,Semi-Urban,Manager,22215,0 +54036,Male,30,Masters,2,95,31,4,47,8.0,3,58,Semi-Urban,Manager,126776,0 +54037,Male,37,Bachelors,11,15,11,69,85,8.0,1,31,Urban,Manager,115424,0 +54038,Female,39,PhD,7,82,1,25,17,8.0,3,91,Urban,Manager,43227,0 +54039,Male,21,High School,15,84,93,15,88,2.0,5,35,Urban,Software Engineer,60638,0 +54040,Female,49,Bachelors,12,26,70,88,75,0.0,3,1,Urban,Software Engineer,68355,0 +54041,Female,35,Diploma,0,48,92,5,8,8.0,7,81,Urban,HR Executive,46793,0 +54042,Male,54,Masters,2,29,24,1,80,8.0,5,18,Semi-Urban,ML Engineer,103491,0 +54043,Other,37,High School,16,7,57,48,48,3.0,3,16,Urban,ML Engineer,126484,0 +54044,Male,55,Bachelors,3,44,76,90,24,7.0,1,5,Rural,ML Engineer,140497,0 +54045,Female,46,Bachelors,6,96,11,21,61,6.0,7,2,Rural,ML Engineer,79032,0 +54046,Male,36,Bachelors,3,74,12,32,19,7.0,7,14,Urban,ML Engineer,43677,0 +54047,Male,24,Bachelors,18,45,41,30,79,7.0,7,3,Semi-Urban,Software Engineer,67417,0 +54048,Male,36,High School,14,47,92,85,94,3.0,5,60,Semi-Urban,Manager,146294,1 +54049,Male,31,Diploma,18,63,71,21,12,2.0,1,77,Semi-Urban,HR Executive,132813,0 +54050,Other,45,Bachelors,15,24,57,69,78,2.0,5,64,Semi-Urban,Data Analyst,81654,0 +54051,Male,32,Masters,15,61,2,53,54,7.0,0,90,Urban,HR Executive,110158,0 +54052,Female,28,Diploma,18,84,86,99,60,0.0,0,19,Semi-Urban,HR Executive,104242,1 +54053,Female,32,Bachelors,12,42,71,18,29,8.0,4,27,Rural,Data Analyst,92804,0 +54054,Male,43,High School,6,4,20,82,99,0.0,7,11,Semi-Urban,Manager,111948,0 +54055,Other,32,High School,12,32,49,50,33,0.0,1,82,Rural,ML Engineer,78863,0 +54056,Male,48,PhD,5,41,49,26,9,0.0,4,65,Urban,Software Engineer,61457,0 +54057,Female,56,Diploma,10,24,11,67,89,4.0,5,23,Urban,Manager,67266,0 +54058,Female,27,Bachelors,7,36,13,77,27,1.0,5,73,Urban,Software Engineer,90656,0 +54059,Female,30,Bachelors,2,79,27,21,40,4.0,5,34,Rural,ML Engineer,67527,0 +54060,Male,47,Bachelors,13,63,40,82,69,8.0,2,38,Urban,Data Analyst,52833,0 +54061,Female,34,Bachelors,9,75,70,24,84,3.0,0,46,Rural,Manager,54787,0 +54062,Male,29,High School,19,17,20,38,13,3.0,4,84,Urban,HR Executive,108303,0 +54063,Male,34,PhD,16,98,49,66,33,1.0,4,2,Urban,Data Analyst,89668,0 +54064,Male,49,Bachelors,12,76,87,93,36,0.0,0,89,Rural,ML Engineer,126735,1 +54065,Male,26,Masters,3,67,44,82,3,8.0,6,84,Rural,HR Executive,41850,1 +54066,Male,50,Diploma,16,97,37,77,13,9.0,7,23,Semi-Urban,Manager,68849,0 +54067,Female,39,Diploma,19,64,4,46,31,0.0,2,87,Semi-Urban,Data Analyst,95591,0 +54068,Female,28,Bachelors,1,71,25,35,48,0.0,6,10,Rural,Manager,37309,0 +54069,Female,21,Bachelors,10,63,16,74,11,9.0,2,29,Rural,Software Engineer,41573,0 +54070,Female,25,Diploma,18,42,78,74,62,0.0,7,58,Rural,ML Engineer,123068,1 +54071,Female,22,Masters,0,76,56,98,42,3.0,2,43,Urban,ML Engineer,97618,1 +54072,Male,55,Diploma,16,36,86,33,75,7.0,4,57,Rural,Manager,36126,0 +54073,Female,27,High School,18,31,71,57,82,8.0,5,25,Rural,HR Executive,81040,0 +54074,Other,27,High School,9,3,66,13,72,7.0,5,69,Urban,Data Analyst,56681,0 +54075,Male,53,Masters,9,9,27,63,49,3.0,5,6,Urban,Software Engineer,27045,0 +54076,Female,36,Bachelors,0,59,87,91,3,1.0,7,99,Urban,HR Executive,88901,1 +54077,Male,48,High School,16,6,76,4,49,2.0,6,18,Urban,HR Executive,146382,0 +54078,Male,58,Diploma,9,86,19,98,99,1.0,4,94,Urban,Manager,111925,1 +54079,Other,24,High School,2,50,45,83,84,2.0,0,92,Semi-Urban,Data Analyst,51664,1 +54080,Male,30,PhD,3,86,25,40,85,6.0,0,21,Rural,Manager,96465,0 +54081,Male,53,High School,18,34,32,37,73,3.0,3,0,Urban,Manager,54947,0 +54082,Other,21,PhD,18,50,30,8,86,2.0,4,58,Urban,ML Engineer,106208,0 +54083,Female,56,Bachelors,5,19,56,60,17,5.0,2,28,Semi-Urban,HR Executive,142927,0 +54084,Male,38,Bachelors,17,81,42,52,32,9.0,2,66,Urban,HR Executive,44947,1 +54085,Male,59,PhD,1,36,93,19,75,6.0,2,67,Urban,Software Engineer,135373,0 +54086,Female,47,Bachelors,3,9,27,93,94,3.0,4,59,Urban,HR Executive,48883,0 +54087,Male,50,Diploma,15,98,18,3,70,5.0,0,78,Semi-Urban,ML Engineer,123198,0 +54088,Male,31,Bachelors,3,4,49,29,97,7.0,7,28,Semi-Urban,Software Engineer,128268,0 +54089,Male,44,Masters,12,49,69,55,16,6.0,1,59,Urban,Data Analyst,103441,0 +54090,Other,39,Bachelors,10,64,67,64,29,0.0,0,99,Urban,ML Engineer,128566,1 +54091,Female,21,High School,17,7,40,71,78,5.0,2,96,Urban,Software Engineer,147618,0 +54092,Male,44,Masters,3,10,55,96,86,4.0,1,12,Rural,Software Engineer,63690,0 +54093,Female,39,Masters,16,59,13,22,42,9.0,2,98,Urban,Manager,94672,0 +54094,Female,52,Bachelors,3,76,31,4,20,1.0,1,29,Semi-Urban,ML Engineer,53869,0 +54095,Other,40,Bachelors,5,92,92,44,85,3.0,5,90,Rural,Manager,97753,1 +54096,Female,57,Bachelors,16,52,77,42,80,9.0,6,86,Semi-Urban,ML Engineer,24253,1 +54097,Female,47,Masters,9,4,53,17,27,3.0,0,59,Rural,Manager,66348,0 +54098,Male,51,Bachelors,5,56,60,17,16,1.0,4,85,Urban,HR Executive,130087,0 +54099,Male,21,Masters,14,89,42,54,16,9.0,5,65,Urban,Data Analyst,131880,1 +54100,Female,28,Bachelors,17,71,8,50,67,2.0,0,76,Rural,ML Engineer,21359,0 +54101,Female,25,Masters,9,77,20,53,99,4.0,3,51,Urban,Software Engineer,44410,0 +54102,Female,44,Masters,17,65,90,64,2,3.0,5,42,Urban,Software Engineer,36254,1 +54103,Male,58,Diploma,17,66,30,93,44,6.0,6,40,Urban,HR Executive,68637,0 +54104,Female,42,Bachelors,1,47,49,77,58,0.0,0,97,Urban,Manager,25194,1 +54105,Female,27,Diploma,11,38,19,55,90,5.0,4,20,Rural,HR Executive,139502,0 +54106,Female,21,High School,11,49,94,22,14,6.0,3,18,Rural,HR Executive,118916,0 +54107,Male,41,High School,11,37,55,74,96,3.0,6,12,Semi-Urban,Software Engineer,126806,0 +54108,Female,58,Masters,0,13,72,13,17,8.0,2,72,Urban,HR Executive,102695,0 +54109,Male,35,Bachelors,9,37,33,94,49,9.0,5,15,Semi-Urban,Manager,69722,0 +54110,Female,35,Bachelors,15,17,81,64,93,1.0,4,6,Urban,ML Engineer,84368,0 +54111,Female,55,Diploma,19,43,13,64,95,6.0,1,47,Urban,Software Engineer,41677,0 +54112,Male,25,Diploma,5,24,96,19,51,4.0,0,22,Urban,Data Analyst,96377,0 +54113,Female,52,Bachelors,11,29,78,48,16,3.0,4,39,Semi-Urban,Software Engineer,144280,0 +54114,Other,47,Bachelors,19,73,41,51,7,6.0,5,87,Urban,ML Engineer,61835,1 +54115,Male,50,High School,16,48,12,21,35,2.0,4,22,Rural,HR Executive,72387,0 +54116,Female,27,Bachelors,7,74,60,95,98,7.0,6,96,Urban,HR Executive,38632,1 +54117,Male,24,Diploma,10,67,45,54,86,7.0,5,5,Rural,HR Executive,142515,0 +54118,Female,32,High School,2,45,14,28,27,9.0,4,11,Semi-Urban,Manager,63013,0 +54119,Male,32,Masters,15,64,66,63,0,3.0,2,58,Urban,Manager,120592,1 +54120,Male,23,PhD,12,49,52,26,83,7.0,1,99,Semi-Urban,HR Executive,77288,0 +54121,Female,34,Masters,2,28,13,60,67,1.0,4,61,Urban,Manager,38454,0 +54122,Male,38,Bachelors,19,28,24,52,58,2.0,7,7,Semi-Urban,Data Analyst,128266,0 +54123,Male,49,Masters,8,49,27,92,17,5.0,4,0,Semi-Urban,Software Engineer,147698,0 +54124,Other,21,Masters,15,53,64,59,97,0.0,6,24,Urban,Data Analyst,131856,0 +54125,Female,59,Bachelors,6,97,32,37,62,9.0,2,48,Urban,Manager,32747,0 +54126,Female,23,Bachelors,12,86,39,74,79,9.0,6,63,Rural,ML Engineer,90990,1 +54127,Female,33,Bachelors,12,72,28,79,29,3.0,5,97,Urban,ML Engineer,86271,1 +54128,Female,33,Diploma,7,70,16,10,27,6.0,3,65,Semi-Urban,Manager,136418,0 +54129,Male,26,Bachelors,14,57,92,20,33,4.0,2,22,Rural,Manager,87332,0 +54130,Male,58,Masters,9,14,19,79,61,9.0,1,52,Urban,Data Analyst,55810,0 +54131,Male,49,High School,2,57,41,57,90,6.0,4,55,Urban,ML Engineer,145026,0 +54132,Male,42,Diploma,1,38,39,36,21,9.0,2,61,Semi-Urban,Software Engineer,58827,0 +54133,Male,46,Bachelors,13,66,89,20,87,0.0,7,26,Semi-Urban,HR Executive,89281,0 +54134,Female,51,Masters,1,1,64,29,26,9.0,6,59,Urban,Software Engineer,46645,0 +54135,Male,59,Diploma,11,50,15,80,79,0.0,2,20,Semi-Urban,Software Engineer,21163,0 +54136,Female,50,Bachelors,14,49,87,35,21,9.0,7,0,Urban,ML Engineer,90937,0 +54137,Female,57,Diploma,0,42,12,24,76,3.0,7,10,Urban,ML Engineer,90270,0 +54138,Male,43,Bachelors,6,84,31,24,23,4.0,1,92,Urban,ML Engineer,82043,0 +54139,Male,32,Diploma,14,7,73,35,46,8.0,7,87,Urban,HR Executive,124543,0 +54140,Female,58,Masters,6,58,22,67,17,0.0,3,10,Urban,ML Engineer,115960,0 +54141,Female,23,Masters,10,46,82,54,59,0.0,4,2,Semi-Urban,ML Engineer,85734,0 +54142,Female,58,Bachelors,2,52,10,51,69,1.0,4,3,Urban,HR Executive,136768,0 +54143,Male,54,High School,17,53,61,28,42,5.0,2,3,Semi-Urban,ML Engineer,78784,0 +54144,Other,54,High School,16,12,95,45,35,1.0,6,17,Rural,HR Executive,108107,0 +54145,Female,42,Diploma,5,31,4,16,85,8.0,3,89,Semi-Urban,Software Engineer,67135,0 +54146,Male,38,High School,0,33,89,26,64,0.0,1,90,Urban,Manager,30607,1 +54147,Male,22,Bachelors,4,54,8,18,33,2.0,0,83,Urban,Software Engineer,84335,0 +54148,Female,48,Diploma,17,39,93,69,95,4.0,2,3,Rural,HR Executive,72127,0 +54149,Male,37,Masters,2,94,74,97,22,4.0,1,39,Rural,HR Executive,80204,1 +54150,Female,43,Bachelors,1,69,92,61,80,9.0,5,24,Urban,Software Engineer,75483,1 +54151,Female,56,Masters,17,30,73,13,76,0.0,1,12,Urban,Manager,145265,0 +54152,Male,23,Diploma,19,39,30,53,96,4.0,4,7,Rural,Software Engineer,68559,0 +54153,Female,58,High School,16,0,41,70,19,7.0,0,68,Urban,Software Engineer,115900,0 +54154,Male,22,Bachelors,2,9,0,48,37,4.0,7,25,Rural,Software Engineer,88212,0 +54155,Male,24,Diploma,19,84,95,42,96,6.0,6,99,Semi-Urban,Manager,108605,1 +54156,Female,56,Diploma,8,42,92,16,36,3.0,3,79,Semi-Urban,HR Executive,24598,0 +54157,Female,58,Bachelors,11,47,49,0,62,0.0,2,57,Urban,HR Executive,131854,0 +54158,Male,55,High School,2,47,28,79,24,7.0,0,81,Urban,HR Executive,58549,1 +54159,Male,38,Bachelors,0,63,37,56,50,3.0,7,37,Rural,HR Executive,140603,0 +54160,Male,36,Bachelors,15,21,28,57,26,2.0,5,34,Semi-Urban,Manager,80226,0 +54161,Male,36,High School,7,98,16,79,35,5.0,1,93,Rural,Data Analyst,105687,1 +54162,Female,56,Bachelors,18,32,77,86,14,2.0,3,53,Urban,HR Executive,75333,1 +54163,Female,38,Masters,8,92,14,61,63,2.0,5,18,Semi-Urban,Software Engineer,90609,0 +54164,Female,23,High School,2,93,40,54,51,4.0,7,59,Urban,Manager,84618,1 +54165,Male,27,Bachelors,0,68,20,78,87,4.0,1,86,Urban,ML Engineer,47079,1 +54166,Male,44,Diploma,14,26,66,20,47,9.0,6,86,Semi-Urban,Data Analyst,137884,0 +54167,Male,49,Diploma,19,25,74,51,51,5.0,4,28,Semi-Urban,Data Analyst,71082,0 +54168,Male,51,Bachelors,9,79,73,34,17,6.0,7,64,Semi-Urban,Data Analyst,92522,1 +54169,Female,28,High School,16,64,78,68,18,6.0,2,65,Semi-Urban,ML Engineer,108478,1 +54170,Male,28,High School,18,10,99,54,96,3.0,5,41,Urban,Data Analyst,147508,0 +54171,Male,22,Bachelors,11,28,3,58,65,1.0,7,87,Rural,ML Engineer,49429,0 +54172,Male,39,Bachelors,12,9,83,63,27,8.0,1,89,Semi-Urban,Data Analyst,84824,1 +54173,Male,29,Bachelors,16,31,36,85,47,4.0,6,82,Semi-Urban,HR Executive,101673,0 +54174,Male,48,Bachelors,12,70,34,85,7,8.0,1,15,Urban,Data Analyst,23314,0 +54175,Male,24,PhD,3,51,75,91,44,2.0,2,64,Urban,Manager,67037,1 +54176,Male,23,PhD,9,87,15,2,60,1.0,5,3,Semi-Urban,HR Executive,38875,0 +54177,Male,31,Masters,14,6,89,76,36,8.0,6,29,Semi-Urban,Software Engineer,34021,0 +54178,Male,33,Masters,19,82,49,89,85,2.0,4,80,Urban,HR Executive,91535,1 +54179,Male,58,High School,8,78,7,3,30,3.0,7,3,Rural,HR Executive,56602,0 +54180,Female,39,Masters,5,2,39,72,77,9.0,7,75,Urban,ML Engineer,30586,0 +54181,Male,31,Bachelors,15,81,28,78,71,2.0,5,11,Semi-Urban,ML Engineer,61628,0 +54182,Female,25,Diploma,19,4,24,66,43,5.0,5,39,Urban,ML Engineer,52771,0 +54183,Male,55,High School,0,56,99,60,38,6.0,2,77,Urban,ML Engineer,33283,1 +54184,Male,27,Bachelors,11,71,23,4,29,3.0,6,13,Urban,Manager,142094,0 +54185,Male,29,Diploma,6,96,59,65,99,2.0,1,79,Semi-Urban,Manager,138622,1 +54186,Male,58,Bachelors,6,79,90,63,36,1.0,2,70,Rural,Manager,120031,1 +54187,Male,44,Masters,10,38,32,92,38,5.0,6,4,Rural,Manager,45453,0 +54188,Male,22,Bachelors,2,81,87,83,83,6.0,1,44,Semi-Urban,ML Engineer,20549,1 +54189,Male,57,Bachelors,8,68,16,93,51,6.0,3,41,Urban,HR Executive,117827,0 +54190,Female,24,High School,12,52,96,86,25,5.0,3,58,Rural,Software Engineer,94231,1 +54191,Male,56,Bachelors,13,58,91,36,12,8.0,7,67,Rural,Software Engineer,20976,1 +54192,Male,46,Bachelors,14,60,38,88,52,1.0,4,35,Urban,ML Engineer,65854,0 +54193,Female,47,Bachelors,5,16,79,20,81,0.0,5,8,Urban,ML Engineer,39535,0 +54194,Male,56,Bachelors,13,90,11,81,3,8.0,0,81,Semi-Urban,Data Analyst,42225,1 +54195,Male,26,Diploma,4,78,47,48,30,2.0,1,7,Rural,Software Engineer,57194,0 +54196,Male,56,Diploma,11,83,4,10,48,8.0,4,97,Urban,Software Engineer,26462,0 +54197,Male,26,Bachelors,0,15,3,59,48,6.0,7,23,Urban,Manager,58165,0 +54198,Male,46,Diploma,14,44,60,69,67,5.0,7,57,Urban,Data Analyst,88742,0 +54199,Female,31,Masters,11,80,47,22,68,4.0,5,40,Rural,ML Engineer,43275,0 +54200,Female,44,PhD,17,93,80,79,8,9.0,7,68,Urban,Software Engineer,50092,1 +54201,Male,49,Bachelors,17,2,80,64,25,2.0,1,61,Urban,Manager,69986,0 +54202,Male,48,Diploma,4,71,43,51,44,4.0,7,99,Urban,Software Engineer,40556,1 +54203,Male,34,Bachelors,17,90,39,33,21,4.0,3,88,Urban,ML Engineer,20889,1 +54204,Male,46,Diploma,16,54,84,10,84,1.0,1,5,Rural,ML Engineer,28680,0 +54205,Female,30,Diploma,13,93,12,24,22,0.0,6,92,Rural,Data Analyst,143186,0 +54206,Male,25,Bachelors,16,21,23,26,0,2.0,0,35,Semi-Urban,ML Engineer,28050,0 +54207,Male,27,Diploma,0,90,25,85,99,1.0,0,53,Semi-Urban,Software Engineer,31030,1 +54208,Male,48,Masters,17,95,11,32,41,5.0,5,75,Urban,Manager,116729,0 +54209,Female,52,Bachelors,18,19,48,96,1,2.0,6,6,Rural,ML Engineer,55309,0 +54210,Male,59,High School,2,63,99,97,62,3.0,0,3,Urban,Manager,135096,1 +54211,Female,48,High School,10,68,29,23,2,7.0,7,25,Urban,HR Executive,54574,0 +54212,Female,45,Bachelors,15,4,64,53,90,8.0,2,92,Urban,Data Analyst,144796,0 +54213,Male,48,Bachelors,15,90,86,75,89,9.0,3,18,Rural,Software Engineer,83603,1 +54214,Male,41,Bachelors,4,61,87,7,20,7.0,0,20,Semi-Urban,Software Engineer,85340,0 +54215,Male,50,Diploma,17,77,78,15,12,9.0,1,66,Urban,HR Executive,118591,1 +54216,Male,55,Diploma,15,53,73,45,24,1.0,6,16,Urban,Software Engineer,65331,0 +54217,Female,58,Masters,18,57,58,49,35,7.0,3,55,Urban,Data Analyst,119772,0 +54218,Female,42,High School,4,88,82,22,21,9.0,6,92,Semi-Urban,HR Executive,121087,1 +54219,Male,36,Diploma,3,97,76,54,53,4.0,3,92,Urban,Data Analyst,145474,1 +54220,Male,52,High School,7,69,73,93,27,9.0,5,1,Rural,ML Engineer,41144,1 +54221,Female,46,High School,4,95,75,59,16,0.0,0,68,Urban,HR Executive,45610,1 +54222,Female,56,Bachelors,5,88,89,59,64,0.0,6,4,Semi-Urban,ML Engineer,85118,0 +54223,Female,58,High School,18,91,46,94,90,6.0,3,36,Semi-Urban,ML Engineer,126405,1 +54224,Male,49,Bachelors,5,96,91,89,74,1.0,3,0,Urban,Data Analyst,34589,1 +54225,Male,45,Masters,4,24,43,11,79,6.0,0,81,Rural,ML Engineer,86765,0 +54226,Male,28,Diploma,6,78,87,35,46,6.0,2,64,Semi-Urban,Manager,21355,1 +54227,Male,53,Bachelors,0,56,8,8,28,5.0,7,98,Semi-Urban,Manager,20046,0 +54228,Female,59,PhD,3,73,23,90,40,8.0,3,82,Rural,Data Analyst,48761,1 +54229,Male,38,Bachelors,8,73,5,76,49,8.0,7,61,Urban,Manager,29627,0 +54230,Female,54,High School,17,0,5,46,88,0.0,3,33,Semi-Urban,Data Analyst,124675,0 +54231,Female,27,Masters,3,48,43,99,0,0.0,0,47,Urban,ML Engineer,27222,0 +54232,Male,21,Masters,13,12,31,95,11,6.0,3,85,Urban,Data Analyst,95953,0 +54233,Female,57,Diploma,7,68,3,46,42,8.0,5,32,Urban,Manager,106828,0 +54234,Male,51,High School,8,13,64,8,18,9.0,2,93,Semi-Urban,Data Analyst,52602,0 +54235,Male,24,Bachelors,8,36,25,1,13,1.0,1,5,Urban,Data Analyst,144417,0 +54236,Female,53,High School,9,21,39,42,53,4.0,0,63,Rural,HR Executive,88199,0 +54237,Female,52,High School,5,45,92,39,56,1.0,1,55,Urban,HR Executive,76268,0 +54238,Female,22,High School,0,91,76,90,42,4.0,3,46,Urban,Data Analyst,133608,1 +54239,Female,55,High School,7,0,57,16,92,6.0,5,89,Semi-Urban,ML Engineer,70215,0 +54240,Female,25,Masters,15,19,53,34,94,3.0,1,43,Urban,ML Engineer,55049,0 +54241,Male,33,Masters,1,35,11,42,63,0.0,3,83,Semi-Urban,Manager,85342,0 +54242,Female,41,Diploma,8,11,73,71,78,4.0,2,55,Semi-Urban,Software Engineer,119976,0 +54243,Male,31,PhD,15,87,12,12,74,1.0,0,29,Rural,HR Executive,54075,0 +54244,Male,39,High School,7,41,35,99,95,4.0,4,77,Semi-Urban,Data Analyst,40089,1 +54245,Female,32,Bachelors,13,20,13,68,31,3.0,7,32,Semi-Urban,ML Engineer,46552,0 +54246,Female,26,Bachelors,1,27,84,40,4,0.0,0,79,Urban,Software Engineer,30346,0 +54247,Male,44,High School,9,31,69,45,10,3.0,0,4,Rural,ML Engineer,34319,0 +54248,Male,33,Diploma,6,55,70,78,56,5.0,6,56,Urban,Data Analyst,40887,1 +54249,Other,40,High School,19,67,48,75,55,5.0,3,39,Rural,ML Engineer,63167,0 +54250,Male,55,High School,16,67,28,63,87,7.0,2,9,Urban,Data Analyst,104066,0 +54251,Other,46,Diploma,9,90,73,48,74,6.0,3,47,Semi-Urban,ML Engineer,88240,1 +54252,Female,26,High School,15,31,41,9,79,9.0,4,42,Semi-Urban,Manager,38457,0 +54253,Female,33,High School,19,71,71,25,96,7.0,2,31,Semi-Urban,HR Executive,23074,0 +54254,Male,29,Diploma,11,72,62,78,79,5.0,7,58,Urban,Software Engineer,82559,1 +54255,Male,34,Bachelors,17,54,2,20,13,5.0,1,56,Semi-Urban,Manager,43529,0 +54256,Male,23,Bachelors,18,57,74,49,66,5.0,4,34,Urban,Software Engineer,149864,0 +54257,Female,36,Bachelors,15,17,1,47,27,1.0,7,74,Semi-Urban,Data Analyst,21706,0 +54258,Male,32,Bachelors,8,83,54,16,16,3.0,7,16,Semi-Urban,ML Engineer,25401,0 +54259,Female,57,Bachelors,1,67,5,21,95,7.0,4,76,Semi-Urban,HR Executive,133907,0 +54260,Female,56,High School,0,51,37,54,66,3.0,0,14,Semi-Urban,ML Engineer,69731,0 +54261,Male,27,Diploma,10,42,20,19,88,3.0,6,25,Urban,HR Executive,42390,0 +54262,Female,47,High School,12,77,81,61,92,4.0,5,89,Rural,HR Executive,33838,1 +54263,Male,39,Masters,15,46,71,25,55,5.0,5,24,Semi-Urban,Data Analyst,60957,0 +54264,Male,28,Masters,6,27,11,56,77,4.0,7,51,Rural,Data Analyst,43102,0 +54265,Male,24,Bachelors,3,38,29,42,29,9.0,5,78,Urban,Data Analyst,142683,0 +54266,Male,43,Bachelors,12,67,35,90,56,0.0,4,61,Urban,Manager,137777,1 +54267,Female,54,Diploma,6,27,75,63,63,4.0,4,3,Urban,HR Executive,81126,0 +54268,Female,33,High School,4,26,12,52,85,8.0,6,72,Rural,Data Analyst,28966,0 +54269,Male,45,Bachelors,8,38,46,74,18,1.0,6,12,Urban,ML Engineer,114147,0 +54270,Female,46,High School,17,52,75,84,45,7.0,2,64,Semi-Urban,Data Analyst,28323,1 +54271,Female,22,Bachelors,17,37,20,67,24,1.0,0,2,Semi-Urban,Manager,54677,0 +54272,Male,34,Bachelors,7,74,43,82,76,9.0,2,40,Rural,ML Engineer,75480,1 +54273,Female,32,Bachelors,16,41,67,85,8,8.0,7,80,Urban,ML Engineer,62740,1 +54274,Male,46,Bachelors,1,2,80,90,87,8.0,2,26,Semi-Urban,Software Engineer,80982,0 +54275,Female,48,Bachelors,16,11,21,28,30,8.0,6,6,Rural,HR Executive,87960,0 +54276,Female,58,Masters,15,26,32,73,33,3.0,1,35,Rural,Manager,34730,0 +54277,Male,30,Bachelors,19,45,24,14,72,0.0,6,74,Urban,Software Engineer,142277,0 +54278,Male,32,Bachelors,10,60,87,21,71,1.0,6,78,Urban,Manager,54541,1 +54279,Female,29,Bachelors,0,92,18,10,75,5.0,6,99,Urban,Software Engineer,97236,0 +54280,Female,29,Bachelors,14,76,17,47,51,4.0,7,6,Rural,ML Engineer,56617,0 +54281,Male,47,Bachelors,4,53,22,4,1,1.0,4,75,Urban,Manager,60000,0 +54282,Male,42,High School,9,57,15,67,55,5.0,4,23,Semi-Urban,ML Engineer,48403,0 +54283,Male,44,Diploma,17,8,79,75,95,1.0,0,78,Semi-Urban,HR Executive,75195,1 +54284,Male,42,Diploma,15,42,50,16,18,6.0,2,72,Rural,Manager,97176,0 +54285,Male,42,Bachelors,13,92,14,81,5,5.0,6,24,Urban,Software Engineer,68761,0 +54286,Male,24,Bachelors,7,22,42,32,81,1.0,4,49,Semi-Urban,Software Engineer,116026,0 +54287,Male,51,Masters,0,87,41,55,36,1.0,7,21,Urban,Software Engineer,120935,0 +54288,Male,32,High School,5,63,70,18,92,7.0,3,82,Urban,ML Engineer,119775,0 +54289,Female,55,PhD,18,28,88,42,19,7.0,1,77,Urban,ML Engineer,42825,0 +54290,Male,21,High School,8,60,27,60,27,5.0,7,98,Urban,Data Analyst,105485,1 +54291,Male,44,Masters,7,8,68,16,0,2.0,2,44,Urban,Manager,61892,0 +54292,Male,54,Bachelors,19,76,90,4,43,7.0,7,17,Urban,Software Engineer,57151,0 +54293,Female,49,Bachelors,12,28,43,51,38,8.0,6,77,Urban,HR Executive,117379,0 +54294,Male,58,Bachelors,15,81,73,15,23,4.0,6,81,Urban,HR Executive,96907,1 +54295,Male,27,Bachelors,16,80,56,77,79,6.0,1,32,Urban,ML Engineer,41403,1 +54296,Female,40,Bachelors,7,32,22,26,8,7.0,2,46,Urban,Software Engineer,37556,0 +54297,Female,35,Bachelors,0,63,65,33,41,2.0,4,27,Semi-Urban,HR Executive,36898,0 +54298,Female,24,Bachelors,8,89,82,24,1,6.0,4,52,Semi-Urban,ML Engineer,25775,1 +54299,Male,24,High School,8,85,35,91,46,0.0,0,46,Rural,Software Engineer,32191,1 +54300,Male,49,High School,17,80,52,90,13,2.0,3,56,Urban,Manager,28697,1 +54301,Male,39,Masters,6,39,7,47,71,8.0,3,53,Urban,Manager,120015,0 +54302,Male,48,Bachelors,8,84,61,49,72,3.0,6,96,Semi-Urban,Data Analyst,114343,1 +54303,Male,27,Bachelors,12,53,99,76,75,4.0,6,55,Urban,Data Analyst,57575,1 +54304,Male,56,Masters,4,85,71,19,93,2.0,3,99,Rural,Data Analyst,72020,1 +54305,Male,50,Diploma,14,5,64,34,71,3.0,4,64,Semi-Urban,Software Engineer,23252,0 +54306,Female,36,Diploma,16,37,51,52,50,2.0,0,72,Urban,ML Engineer,88126,0 +54307,Female,55,Diploma,1,65,78,55,48,2.0,3,16,Rural,ML Engineer,97487,0 +54308,Male,49,Diploma,6,38,51,4,87,6.0,4,21,Urban,Manager,110111,0 +54309,Other,37,Bachelors,5,22,26,24,45,3.0,1,96,Semi-Urban,Software Engineer,50568,0 +54310,Female,58,Bachelors,7,32,64,42,83,9.0,7,25,Urban,Data Analyst,140492,0 +54311,Male,34,Bachelors,3,98,35,16,8,4.0,4,26,Urban,ML Engineer,64564,0 +54312,Male,56,Bachelors,5,89,44,77,38,7.0,1,57,Semi-Urban,Software Engineer,97594,1 +54313,Male,49,Masters,18,42,1,47,31,2.0,0,11,Rural,HR Executive,59446,0 +54314,Female,21,Masters,10,31,69,33,72,4.0,1,14,Semi-Urban,ML Engineer,93610,0 +54315,Male,42,Masters,10,52,9,83,13,6.0,7,2,Urban,HR Executive,109735,0 +54316,Male,25,PhD,0,83,36,77,72,1.0,5,80,Urban,HR Executive,138771,1 +54317,Male,39,Masters,3,3,51,11,75,7.0,6,90,Rural,Data Analyst,123318,0 +54318,Female,37,Bachelors,12,30,0,85,42,4.0,3,86,Urban,Software Engineer,136137,0 +54319,Male,53,Bachelors,4,83,24,88,82,7.0,2,61,Urban,Manager,129156,1 +54320,Male,32,Diploma,15,21,57,83,64,8.0,6,16,Rural,ML Engineer,111771,0 +54321,Male,47,Masters,4,77,36,4,1,9.0,2,33,Semi-Urban,ML Engineer,108560,0 +54322,Male,38,Bachelors,14,99,39,37,39,6.0,2,78,Semi-Urban,Data Analyst,108862,1 +54323,Male,56,Bachelors,9,41,10,8,89,4.0,7,70,Rural,ML Engineer,137613,0 +54324,Male,37,PhD,6,82,19,21,93,6.0,4,88,Semi-Urban,Data Analyst,34541,0 +54325,Male,55,High School,10,54,46,67,84,8.0,2,95,Semi-Urban,ML Engineer,77732,1 +54326,Male,58,Bachelors,2,56,96,51,45,1.0,7,76,Urban,Software Engineer,80915,1 +54327,Male,55,Bachelors,10,36,38,5,0,1.0,4,51,Urban,Manager,50461,0 +54328,Male,59,Diploma,3,49,81,11,57,5.0,3,45,Rural,Software Engineer,90223,0 +54329,Male,54,Masters,2,62,78,27,14,6.0,7,60,Urban,ML Engineer,121260,0 +54330,Male,37,Bachelors,3,40,55,89,55,7.0,3,26,Urban,Software Engineer,81391,0 +54331,Male,22,High School,4,80,38,35,98,4.0,7,54,Urban,Manager,26131,0 +54332,Male,50,High School,0,66,8,75,39,2.0,5,80,Urban,Data Analyst,42357,0 +54333,Male,40,Masters,3,80,81,25,18,0.0,1,71,Urban,Software Engineer,114114,1 +54334,Female,47,PhD,4,13,39,85,77,4.0,5,60,Urban,Data Analyst,104756,0 +54335,Female,59,High School,6,65,74,51,35,8.0,3,22,Urban,Manager,66903,0 +54336,Male,54,Bachelors,3,35,52,96,32,1.0,1,94,Urban,Data Analyst,89868,1 +54337,Male,44,Bachelors,4,6,53,8,7,0.0,6,90,Rural,HR Executive,118492,0 +54338,Other,53,Diploma,17,40,79,57,17,2.0,4,21,Rural,HR Executive,146960,0 +54339,Male,34,Diploma,4,43,10,71,9,6.0,5,30,Urban,Software Engineer,101089,0 +54340,Female,42,Masters,9,66,44,68,19,7.0,1,53,Urban,Software Engineer,52794,0 +54341,Female,27,High School,14,30,25,51,24,7.0,0,78,Semi-Urban,HR Executive,72315,0 +54342,Female,48,High School,7,28,65,49,37,5.0,0,62,Rural,Manager,108625,0 +54343,Male,34,Diploma,17,85,69,49,78,7.0,2,81,Urban,Manager,30677,1 +54344,Male,30,Bachelors,14,30,25,29,42,8.0,3,63,Semi-Urban,Software Engineer,33075,0 +54345,Male,38,Bachelors,19,10,42,42,25,4.0,7,21,Semi-Urban,Manager,55010,0 +54346,Male,53,Bachelors,8,12,62,8,82,7.0,0,5,Rural,Manager,35123,0 +54347,Male,38,Bachelors,7,17,55,23,85,6.0,6,34,Urban,Data Analyst,146173,0 +54348,Male,42,Bachelors,8,9,3,64,68,1.0,2,64,Semi-Urban,Data Analyst,32301,0 +54349,Male,31,Masters,13,23,99,58,4,5.0,0,93,Urban,ML Engineer,43378,1 +54350,Female,43,Diploma,5,58,52,85,39,7.0,6,56,Urban,ML Engineer,124968,1 +54351,Male,48,Diploma,5,33,83,41,23,7.0,0,21,Urban,Manager,26050,0 +54352,Female,52,Bachelors,17,98,24,38,92,0.0,7,37,Semi-Urban,ML Engineer,44632,0 +54353,Female,21,High School,9,20,57,22,90,5.0,3,1,Urban,HR Executive,81290,0 +54354,Male,59,High School,7,98,37,17,10,0.0,6,14,Rural,Manager,149373,0 +54355,Male,32,High School,4,72,52,19,84,9.0,7,74,Urban,HR Executive,35950,0 +54356,Female,58,Bachelors,13,73,86,26,52,7.0,6,37,Urban,Software Engineer,122972,0 +54357,Male,42,High School,10,65,77,37,63,0.0,6,63,Urban,Manager,33001,1 +54358,Female,29,Masters,9,88,37,31,93,4.0,0,66,Semi-Urban,Data Analyst,56981,0 +54359,Female,45,Bachelors,11,38,26,36,87,8.0,5,37,Semi-Urban,Manager,39939,0 +54360,Male,41,Bachelors,12,18,7,80,69,7.0,3,86,Urban,HR Executive,108808,0 +54361,Female,56,High School,0,80,90,0,55,0.0,5,7,Urban,HR Executive,32783,0 +54362,Male,55,Diploma,4,31,18,3,15,4.0,5,83,Urban,HR Executive,133347,0 +54363,Female,27,Bachelors,14,4,30,77,70,6.0,3,3,Urban,HR Executive,36621,0 +54364,Male,39,Bachelors,0,12,60,91,33,7.0,2,53,Rural,Software Engineer,111216,0 +54365,Male,25,Diploma,5,17,12,72,79,8.0,6,22,Urban,Software Engineer,53973,0 +54366,Male,51,High School,17,52,75,11,96,2.0,5,48,Urban,ML Engineer,135033,0 +54367,Female,34,High School,7,83,15,7,37,2.0,5,32,Semi-Urban,Data Analyst,123940,0 +54368,Female,21,Diploma,7,40,59,14,12,3.0,5,91,Semi-Urban,ML Engineer,72036,0 +54369,Female,41,High School,17,31,45,79,60,0.0,3,98,Urban,ML Engineer,122344,1 +54370,Male,59,Masters,11,0,5,10,20,8.0,1,21,Rural,Manager,83594,0 +54371,Male,33,Bachelors,12,18,81,65,96,3.0,5,79,Urban,Manager,48865,1 +54372,Male,56,Bachelors,7,83,84,68,79,4.0,0,78,Urban,Manager,149798,1 +54373,Female,28,Diploma,17,26,35,13,72,3.0,0,83,Rural,Manager,53530,0 +54374,Female,45,Bachelors,12,60,15,20,44,7.0,1,63,Urban,Manager,94864,0 +54375,Male,59,Diploma,1,34,8,94,12,5.0,0,11,Rural,Software Engineer,148132,0 +54376,Female,37,Bachelors,6,68,95,47,56,9.0,7,52,Rural,ML Engineer,103482,1 +54377,Male,38,Bachelors,5,77,84,39,70,3.0,1,31,Urban,Data Analyst,112008,0 +54378,Female,58,Bachelors,0,54,79,8,97,1.0,5,12,Urban,Manager,70897,0 +54379,Male,35,Bachelors,16,81,51,37,48,8.0,3,50,Semi-Urban,ML Engineer,91462,0 +54380,Male,25,Masters,2,87,78,77,65,5.0,0,87,Semi-Urban,Manager,101564,1 +54381,Female,37,Masters,19,99,31,62,89,7.0,6,36,Semi-Urban,Data Analyst,26398,0 +54382,Female,38,High School,6,75,53,35,26,6.0,1,30,Urban,Software Engineer,124465,0 +54383,Male,25,Bachelors,13,2,75,46,70,6.0,6,34,Semi-Urban,Data Analyst,130254,0 +54384,Male,34,Diploma,15,63,88,34,68,0.0,7,85,Semi-Urban,HR Executive,112064,1 +54385,Female,42,High School,5,99,2,36,67,9.0,0,23,Urban,HR Executive,39352,0 +54386,Female,39,Bachelors,19,3,15,49,96,0.0,5,15,Rural,Manager,134155,0 +54387,Other,28,High School,16,88,31,87,60,0.0,4,25,Rural,HR Executive,65679,0 +54388,Male,35,Bachelors,8,9,3,25,82,7.0,4,25,Urban,Software Engineer,147380,0 +54389,Male,22,Masters,10,97,89,83,0,6.0,5,84,Rural,HR Executive,46418,1 +54390,Female,24,Masters,0,46,2,55,99,0.0,3,48,Semi-Urban,Manager,36414,0 +54391,Male,39,Bachelors,17,7,60,58,89,1.0,4,82,Rural,HR Executive,106060,0 +54392,Male,31,Diploma,13,56,97,68,21,8.0,5,23,Urban,Software Engineer,33507,1 +54393,Male,22,Diploma,0,38,23,7,25,1.0,3,17,Urban,ML Engineer,132275,0 +54394,Male,40,Diploma,8,43,11,21,25,0.0,6,73,Semi-Urban,Data Analyst,56916,0 +54395,Male,57,High School,12,92,67,44,80,7.0,7,25,Urban,Data Analyst,76102,0 +54396,Male,33,High School,7,19,33,80,62,0.0,3,54,Rural,HR Executive,88372,0 +54397,Female,50,Bachelors,14,16,5,8,37,5.0,7,81,Semi-Urban,Manager,140444,0 +54398,Male,58,Bachelors,17,3,12,79,82,9.0,2,17,Urban,Software Engineer,97021,0 +54399,Female,45,Bachelors,8,93,13,5,13,9.0,0,45,Urban,Software Engineer,25756,0 +54400,Male,31,Masters,12,86,41,29,13,1.0,7,27,Urban,Software Engineer,82823,0 +54401,Male,25,Bachelors,9,91,31,88,86,6.0,4,20,Rural,Manager,68413,0 +54402,Other,57,High School,19,58,28,29,93,1.0,1,3,Rural,ML Engineer,97903,0 +54403,Male,41,Bachelors,7,1,90,73,7,4.0,2,1,Rural,Software Engineer,113864,0 +54404,Male,39,High School,10,34,11,89,48,5.0,1,3,Urban,Manager,109196,0 +54405,Female,34,Masters,16,40,41,34,62,1.0,3,88,Urban,ML Engineer,117813,0 +54406,Female,34,Masters,4,39,57,18,88,7.0,6,33,Semi-Urban,ML Engineer,48794,0 +54407,Male,35,Bachelors,13,99,42,42,84,3.0,2,46,Urban,Manager,22260,0 +54408,Female,56,Bachelors,2,68,4,57,10,7.0,1,91,Semi-Urban,Manager,82051,0 +54409,Male,47,Masters,11,1,66,9,13,8.0,1,43,Urban,ML Engineer,120117,0 +54410,Male,44,High School,6,72,35,60,37,9.0,5,58,Semi-Urban,HR Executive,64967,0 +54411,Female,51,Masters,2,89,24,91,98,0.0,3,29,Urban,Manager,124917,0 +54412,Male,55,Bachelors,14,23,39,47,72,8.0,7,61,Urban,Software Engineer,102735,0 +54413,Female,47,Bachelors,19,17,39,59,89,3.0,5,90,Urban,Data Analyst,131488,0 +54414,Male,37,PhD,13,19,36,58,12,5.0,3,96,Semi-Urban,HR Executive,20834,0 +54415,Male,39,Bachelors,0,32,31,75,30,0.0,5,73,Semi-Urban,Software Engineer,103628,0 +54416,Male,35,Bachelors,11,74,83,74,66,9.0,7,34,Urban,ML Engineer,90431,1 +54417,Female,36,Bachelors,11,29,70,28,86,2.0,6,68,Semi-Urban,Manager,70258,0 +54418,Male,34,High School,18,62,53,51,75,3.0,1,93,Rural,Data Analyst,134430,1 +54419,Male,52,PhD,8,88,49,88,46,9.0,6,16,Semi-Urban,HR Executive,123189,1 +54420,Other,27,High School,3,23,54,87,32,7.0,7,66,Urban,ML Engineer,49814,0 +54421,Female,21,Diploma,0,81,4,82,12,0.0,5,65,Urban,ML Engineer,54775,0 +54422,Male,47,Masters,18,21,81,63,27,2.0,4,27,Semi-Urban,Manager,67987,0 +54423,Male,50,Masters,16,45,46,39,19,1.0,7,14,Urban,Data Analyst,61433,0 +54424,Male,44,Bachelors,3,88,91,15,73,0.0,7,57,Urban,Data Analyst,20627,1 +54425,Female,50,Masters,13,72,47,22,22,2.0,1,21,Urban,Data Analyst,140561,0 +54426,Male,39,Diploma,12,8,39,17,95,5.0,2,83,Urban,Manager,127985,0 +54427,Female,58,Diploma,18,44,83,91,96,5.0,2,63,Urban,Manager,64439,1 +54428,Female,34,PhD,15,11,39,82,51,9.0,6,12,Urban,HR Executive,131590,0 +54429,Male,32,High School,12,35,20,87,97,3.0,7,34,Urban,Data Analyst,90289,0 +54430,Male,45,Bachelors,0,4,41,81,11,2.0,3,80,Urban,Software Engineer,67974,0 +54431,Male,29,Bachelors,4,2,35,56,35,1.0,2,30,Urban,Manager,48464,0 +54432,Female,25,Bachelors,4,21,43,18,95,7.0,3,23,Urban,Manager,73276,0 +54433,Male,55,High School,19,68,44,43,82,2.0,1,62,Urban,HR Executive,56173,0 +54434,Female,57,Diploma,3,4,47,34,79,2.0,5,66,Urban,Data Analyst,116257,0 +54435,Female,28,Bachelors,5,46,61,76,34,8.0,3,69,Urban,ML Engineer,44833,1 +54436,Male,49,Diploma,1,48,40,54,76,1.0,3,4,Urban,Data Analyst,27183,0 +54437,Male,21,Diploma,11,91,4,86,52,0.0,0,35,Rural,HR Executive,35979,0 +54438,Female,58,High School,8,23,85,39,56,5.0,3,86,Urban,Data Analyst,142734,0 +54439,Male,29,Bachelors,19,77,3,54,27,4.0,0,3,Urban,ML Engineer,93006,0 +54440,Male,55,High School,8,14,91,99,81,3.0,2,43,Semi-Urban,Data Analyst,117757,1 +54441,Male,30,Diploma,12,55,25,49,73,3.0,7,22,Rural,HR Executive,146661,0 +54442,Female,38,Bachelors,17,19,76,97,55,1.0,6,40,Semi-Urban,Manager,58018,0 +54443,Female,34,Bachelors,1,71,70,78,69,3.0,6,20,Rural,Manager,93205,0 +54444,Male,31,Bachelors,1,54,75,14,54,2.0,4,86,Urban,Manager,27532,0 +54445,Female,57,Bachelors,0,27,78,46,57,1.0,1,12,Urban,ML Engineer,111200,0 +54446,Female,38,High School,3,56,15,52,71,8.0,5,5,Rural,Data Analyst,88323,0 +54447,Female,39,Diploma,18,74,75,69,68,6.0,0,62,Urban,ML Engineer,45941,1 +54448,Female,34,Diploma,5,89,47,57,34,9.0,3,15,Semi-Urban,ML Engineer,88008,0 +54449,Male,39,Bachelors,18,81,72,35,55,1.0,2,50,Urban,ML Engineer,57752,1 +54450,Male,51,Diploma,7,31,69,80,95,7.0,0,3,Urban,ML Engineer,54647,0 +54451,Male,54,Bachelors,8,86,64,58,45,3.0,5,89,Rural,Data Analyst,95474,1 +54452,Female,54,Masters,1,44,46,25,56,7.0,1,43,Rural,Data Analyst,101470,0 +54453,Male,53,Masters,13,51,40,49,12,3.0,7,39,Urban,ML Engineer,68009,0 +54454,Other,56,Diploma,9,34,33,10,54,2.0,0,65,Urban,ML Engineer,141441,0 +54455,Male,50,Masters,6,88,90,37,13,7.0,2,2,Urban,ML Engineer,95585,0 +54456,Male,41,Bachelors,10,63,78,0,33,7.0,0,74,Urban,Software Engineer,71848,0 +54457,Female,59,High School,2,30,47,70,97,3.0,1,98,Urban,ML Engineer,125132,1 +54458,Female,39,Bachelors,0,72,39,31,89,4.0,4,29,Semi-Urban,Data Analyst,68988,0 +54459,Male,58,Masters,7,69,85,31,99,3.0,3,64,Semi-Urban,Manager,79944,1 +54460,Male,52,High School,7,89,4,86,87,1.0,5,20,Urban,Software Engineer,24740,0 +54461,Male,56,Bachelors,10,37,92,69,13,4.0,6,2,Semi-Urban,ML Engineer,122406,0 +54462,Female,40,Diploma,6,5,6,83,37,3.0,0,34,Semi-Urban,Data Analyst,56497,0 +54463,Female,52,Masters,6,17,31,75,7,1.0,6,98,Urban,Data Analyst,74440,0 +54464,Male,55,Bachelors,11,30,10,8,85,4.0,0,80,Semi-Urban,Data Analyst,79180,0 +54465,Male,32,Bachelors,14,30,63,4,27,1.0,6,73,Urban,Manager,37538,0 +54466,Male,45,High School,5,34,42,84,54,4.0,7,77,Semi-Urban,Manager,85447,1 +54467,Male,49,Diploma,5,43,69,71,43,5.0,7,32,Semi-Urban,HR Executive,52570,0 +54468,Male,45,High School,4,35,83,58,49,7.0,2,7,Urban,Data Analyst,43773,0 +54469,Other,53,Diploma,3,15,88,42,90,4.0,5,31,Urban,Data Analyst,95515,0 +54470,Female,38,Diploma,1,3,28,15,7,6.0,3,81,Rural,Software Engineer,97348,0 +54471,Male,56,Masters,1,19,56,56,30,1.0,0,98,Semi-Urban,Data Analyst,102936,0 +54472,Male,48,Bachelors,9,15,42,63,24,0.0,3,83,Rural,Software Engineer,58154,0 +54473,Male,50,Diploma,0,41,52,90,80,9.0,2,69,Rural,HR Executive,95546,1 +54474,Male,29,Bachelors,14,89,56,97,62,2.0,4,86,Semi-Urban,Software Engineer,59743,1 +54475,Female,56,Bachelors,9,40,29,1,53,2.0,2,46,Semi-Urban,Data Analyst,149100,0 +54476,Male,23,Bachelors,14,46,45,66,64,6.0,7,88,Urban,Data Analyst,47543,1 +54477,Male,59,Diploma,16,62,48,71,66,6.0,5,45,Urban,ML Engineer,113944,0 +54478,Male,44,Bachelors,10,27,24,10,20,4.0,1,99,Urban,ML Engineer,49057,0 +54479,Male,36,Bachelors,16,35,58,91,4,8.0,2,32,Rural,ML Engineer,36996,0 +54480,Male,53,High School,16,91,54,14,69,4.0,1,46,Semi-Urban,Manager,59422,0 +54481,Female,22,PhD,14,52,27,84,32,5.0,7,75,Urban,Manager,55467,0 +54482,Female,45,Bachelors,8,32,93,2,57,0.0,3,31,Semi-Urban,Manager,128693,0 +54483,Male,59,Masters,9,34,81,21,15,8.0,3,84,Semi-Urban,HR Executive,44628,0 +54484,Female,23,Bachelors,4,62,12,17,84,3.0,6,15,Semi-Urban,Software Engineer,51817,0 +54485,Female,24,Bachelors,8,57,75,29,74,8.0,7,44,Semi-Urban,Manager,143112,0 +54486,Female,56,High School,12,49,60,17,94,6.0,2,99,Urban,Manager,74064,0 +54487,Female,51,Masters,0,11,41,39,72,6.0,1,61,Rural,HR Executive,76611,0 +54488,Female,38,Bachelors,16,96,34,6,76,0.0,0,9,Semi-Urban,Manager,71326,0 +54489,Male,55,Diploma,1,99,27,53,54,3.0,7,45,Semi-Urban,Software Engineer,103090,0 +54490,Male,44,Bachelors,4,29,80,58,81,8.0,0,12,Urban,HR Executive,31346,0 +54491,Female,54,Bachelors,12,24,76,66,82,6.0,7,15,Rural,Data Analyst,65510,0 +54492,Female,29,Masters,8,32,73,70,21,6.0,7,15,Rural,HR Executive,46568,0 +54493,Male,41,Masters,1,47,55,22,0,4.0,3,18,Rural,ML Engineer,136603,0 +54494,Male,26,Bachelors,10,95,27,92,53,9.0,4,53,Rural,ML Engineer,109145,1 +54495,Male,57,Bachelors,9,85,34,67,82,0.0,2,26,Urban,HR Executive,25904,0 +54496,Female,42,Diploma,8,31,58,59,41,5.0,2,13,Urban,Software Engineer,74606,0 +54497,Female,26,Diploma,16,92,79,75,17,3.0,4,22,Rural,Software Engineer,116850,1 +54498,Male,56,Diploma,16,55,84,4,27,1.0,2,82,Urban,HR Executive,30441,0 +54499,Female,31,Bachelors,11,19,40,1,75,8.0,1,27,Rural,HR Executive,54688,0 +54500,Male,41,PhD,17,14,35,15,39,9.0,3,4,Urban,Software Engineer,92944,0 +54501,Male,58,High School,3,59,77,81,61,0.0,6,89,Urban,HR Executive,79041,1 +54502,Female,27,Masters,17,53,71,79,95,6.0,7,17,Urban,Data Analyst,27060,0 +54503,Male,41,Diploma,7,77,11,84,91,1.0,4,39,Urban,Data Analyst,105567,0 +54504,Male,23,Bachelors,9,70,11,47,47,5.0,0,26,Urban,ML Engineer,140122,0 +54505,Male,55,Masters,9,51,38,87,16,3.0,2,78,Urban,HR Executive,107936,1 +54506,Female,21,Diploma,19,76,41,72,92,5.0,2,37,Urban,Manager,115912,0 +54507,Male,31,Bachelors,1,82,82,7,16,4.0,5,18,Rural,HR Executive,82194,0 +54508,Female,24,Masters,4,50,76,37,31,5.0,5,90,Urban,Data Analyst,98709,1 +54509,Male,55,Diploma,3,99,29,62,65,8.0,2,81,Semi-Urban,ML Engineer,130680,1 +54510,Female,51,Bachelors,10,6,62,55,19,4.0,4,3,Urban,Manager,20298,0 +54511,Male,50,Bachelors,11,45,68,79,32,1.0,5,94,Semi-Urban,Software Engineer,100615,1 +54512,Female,50,Masters,10,13,43,51,32,5.0,6,36,Urban,Software Engineer,103667,0 +54513,Female,44,Diploma,3,43,73,71,45,0.0,3,1,Semi-Urban,HR Executive,145375,0 +54514,Male,42,Masters,1,41,74,57,87,9.0,5,5,Rural,HR Executive,72863,0 +54515,Male,22,Bachelors,12,94,76,21,26,8.0,7,89,Urban,Software Engineer,47583,1 +54516,Male,50,Masters,10,10,74,37,69,7.0,2,50,Urban,Data Analyst,44053,0 +54517,Female,39,High School,3,88,62,71,99,1.0,3,75,Semi-Urban,Data Analyst,104908,1 +54518,Male,43,Masters,18,27,80,86,53,0.0,2,38,Urban,Manager,34670,0 +54519,Female,37,Bachelors,16,54,40,94,31,8.0,1,22,Rural,ML Engineer,42635,0 +54520,Male,43,Bachelors,1,69,61,80,60,8.0,7,15,Urban,Data Analyst,117307,0 +54521,Male,25,Masters,16,61,64,54,81,3.0,0,30,Urban,HR Executive,95421,0 +54522,Female,25,Bachelors,14,49,62,16,31,1.0,6,17,Urban,HR Executive,23749,0 +54523,Female,42,Diploma,8,12,92,52,40,7.0,0,46,Semi-Urban,ML Engineer,136696,0 +54524,Female,37,Bachelors,12,35,77,13,53,1.0,4,8,Semi-Urban,ML Engineer,32428,0 +54525,Female,57,Diploma,2,94,13,32,56,4.0,0,5,Urban,Manager,27282,0 +54526,Other,33,Bachelors,8,66,15,80,82,8.0,2,95,Urban,Manager,109743,1 +54527,Male,58,Diploma,0,68,73,12,88,4.0,0,91,Semi-Urban,HR Executive,50823,1 +54528,Male,55,Diploma,7,2,40,74,74,9.0,5,14,Urban,HR Executive,72793,0 +54529,Male,26,Masters,5,97,53,79,84,3.0,1,92,Urban,ML Engineer,92185,1 +54530,Female,40,Bachelors,10,30,29,90,54,4.0,6,37,Semi-Urban,Manager,36836,0 +54531,Male,43,Masters,1,10,60,99,63,6.0,5,17,Urban,HR Executive,60609,0 +54532,Male,31,Masters,5,20,98,85,62,7.0,0,99,Semi-Urban,ML Engineer,132512,1 +54533,Female,24,Diploma,0,84,69,67,70,9.0,5,96,Urban,HR Executive,58292,1 +54534,Female,34,High School,3,78,28,57,68,5.0,1,7,Semi-Urban,Data Analyst,83556,0 +54535,Male,21,High School,8,72,80,85,72,4.0,2,69,Rural,HR Executive,147138,1 +54536,Male,50,Bachelors,18,15,71,95,98,6.0,6,99,Semi-Urban,Software Engineer,131188,1 +54537,Male,37,PhD,8,28,62,78,48,9.0,4,60,Urban,ML Engineer,130420,0 +54538,Male,40,Masters,10,10,2,41,64,7.0,0,20,Urban,HR Executive,121001,0 +54539,Male,56,Diploma,13,43,3,83,34,2.0,5,41,Urban,Software Engineer,75614,0 +54540,Male,35,Bachelors,2,15,65,82,71,1.0,6,28,Urban,Software Engineer,128629,0 +54541,Female,39,High School,6,42,63,27,81,0.0,3,22,Semi-Urban,Manager,125599,0 +54542,Other,53,Bachelors,6,68,56,72,68,4.0,5,7,Rural,ML Engineer,40204,0 +54543,Other,29,High School,4,94,45,5,19,7.0,1,56,Urban,Manager,117392,0 +54544,Male,21,Bachelors,10,47,77,73,63,1.0,6,30,Semi-Urban,Manager,73767,0 +54545,Female,55,PhD,15,60,88,44,72,2.0,7,6,Rural,ML Engineer,146804,0 +54546,Female,35,Bachelors,6,8,42,43,85,4.0,2,86,Urban,ML Engineer,69738,0 +54547,Female,56,PhD,13,75,3,24,50,7.0,5,82,Urban,Data Analyst,62235,0 +54548,Female,59,Bachelors,7,5,93,10,26,1.0,2,20,Rural,Data Analyst,111246,0 +54549,Other,45,Bachelors,10,38,44,80,6,4.0,1,94,Urban,Manager,44921,1 +54550,Male,42,Bachelors,4,59,59,18,79,1.0,6,10,Urban,Manager,29382,0 +54551,Female,28,High School,12,65,9,17,61,1.0,4,2,Semi-Urban,Software Engineer,73068,0 +54552,Female,26,Diploma,12,20,43,12,66,1.0,1,53,Urban,ML Engineer,96037,0 +54553,Male,40,PhD,17,76,12,52,3,6.0,7,19,Semi-Urban,ML Engineer,61997,0 +54554,Male,30,Bachelors,4,96,50,18,43,9.0,0,52,Rural,Data Analyst,119174,0 +54555,Male,42,Masters,3,41,28,15,63,1.0,2,91,Urban,ML Engineer,123079,0 +54556,Female,33,Masters,10,41,48,83,18,4.0,4,91,Urban,Data Analyst,109783,1 +54557,Female,29,Bachelors,14,31,45,55,87,3.0,0,64,Rural,HR Executive,106751,0 +54558,Female,56,Diploma,16,79,27,30,91,5.0,1,9,Rural,Data Analyst,143851,0 +54559,Male,46,Masters,1,49,50,38,91,4.0,0,3,Urban,HR Executive,70317,0 +54560,Male,29,High School,10,88,79,56,78,8.0,2,87,Semi-Urban,Manager,53503,1 +54561,Female,36,Masters,19,56,39,74,75,9.0,2,46,Urban,Software Engineer,64830,0 +54562,Male,41,PhD,1,98,97,22,84,4.0,2,72,Semi-Urban,ML Engineer,55177,1 +54563,Male,49,Diploma,7,92,69,22,21,9.0,4,8,Urban,ML Engineer,34553,0 +54564,Female,34,Masters,9,81,21,12,96,9.0,2,18,Urban,ML Engineer,32329,0 +54565,Female,36,Masters,5,82,41,56,88,8.0,1,15,Semi-Urban,Data Analyst,84814,0 +54566,Female,31,Bachelors,0,4,67,70,13,4.0,7,52,Rural,HR Executive,78970,0 +54567,Male,43,Masters,4,42,31,78,6,7.0,7,81,Semi-Urban,Software Engineer,85568,0 +54568,Male,34,Masters,13,33,93,98,61,3.0,3,7,Rural,HR Executive,40821,0 +54569,Female,27,High School,19,50,71,78,57,5.0,2,39,Rural,Data Analyst,145196,0 +54570,Male,32,Bachelors,17,65,70,34,45,7.0,3,66,Urban,Software Engineer,62022,1 +54571,Male,50,Bachelors,16,83,2,40,36,5.0,0,20,Rural,HR Executive,105219,0 +54572,Male,39,High School,0,3,30,21,3,1.0,5,93,Urban,HR Executive,100231,0 +54573,Male,27,Bachelors,3,16,44,99,37,0.0,6,13,Rural,Manager,31462,0 +54574,Male,51,High School,3,72,68,30,79,2.0,6,90,Urban,HR Executive,86757,1 +54575,Male,40,Bachelors,12,7,87,88,33,7.0,4,28,Semi-Urban,HR Executive,63624,0 +54576,Male,43,Diploma,6,59,38,89,25,1.0,6,58,Urban,Software Engineer,121963,1 +54577,Male,50,Diploma,15,15,98,91,30,8.0,1,67,Urban,ML Engineer,107476,1 +54578,Male,29,Masters,16,17,41,61,24,6.0,4,36,Semi-Urban,HR Executive,81825,0 +54579,Female,58,High School,11,55,32,76,97,5.0,3,63,Rural,ML Engineer,67636,0 +54580,Male,44,Bachelors,6,30,13,82,59,4.0,4,84,Urban,Software Engineer,59224,0 +54581,Male,24,Bachelors,11,92,11,8,65,5.0,2,2,Urban,ML Engineer,63477,0 +54582,Male,26,Bachelors,6,86,6,77,49,7.0,3,91,Rural,Manager,139418,1 +54583,Male,45,Bachelors,6,61,45,12,69,0.0,3,51,Urban,Manager,39762,0 +54584,Male,33,Bachelors,17,84,8,40,62,1.0,1,66,Urban,Data Analyst,79827,0 +54585,Male,42,Masters,8,72,84,26,88,8.0,7,37,Semi-Urban,HR Executive,139435,0 +54586,Male,57,Diploma,18,69,5,15,77,4.0,1,74,Urban,Software Engineer,143310,0 +54587,Male,29,PhD,6,41,43,35,38,5.0,5,49,Semi-Urban,HR Executive,84276,0 +54588,Male,45,Masters,3,33,43,80,69,4.0,7,83,Semi-Urban,HR Executive,97017,1 +54589,Male,58,Masters,3,90,68,76,82,9.0,6,60,Semi-Urban,Data Analyst,103009,1 +54590,Male,28,High School,8,51,58,38,46,1.0,4,37,Urban,Software Engineer,109863,0 +54591,Male,44,High School,3,45,55,50,17,0.0,2,41,Urban,Manager,48345,0 +54592,Female,39,Diploma,11,27,26,40,44,8.0,4,15,Semi-Urban,HR Executive,83023,0 +54593,Male,34,Bachelors,18,69,81,18,87,9.0,6,91,Urban,Data Analyst,96809,1 +54594,Other,27,Diploma,0,32,0,84,96,6.0,1,37,Urban,Software Engineer,127140,0 +54595,Other,39,Bachelors,16,80,82,4,37,4.0,5,3,Urban,HR Executive,136021,0 +54596,Male,27,High School,16,50,49,72,39,3.0,4,24,Rural,HR Executive,144877,0 +54597,Female,34,High School,17,2,24,59,72,8.0,6,74,Urban,HR Executive,22597,0 +54598,Female,45,Bachelors,4,48,63,3,37,0.0,0,3,Urban,ML Engineer,111443,0 +54599,Male,35,Diploma,12,8,48,83,46,2.0,6,53,Urban,Data Analyst,134556,0 +54600,Male,46,Bachelors,19,58,4,38,37,7.0,5,72,Urban,Manager,65956,0 +54601,Male,54,Masters,1,46,1,12,15,0.0,6,14,Urban,Data Analyst,129397,0 +54602,Male,54,Bachelors,0,67,14,41,21,4.0,2,85,Urban,Manager,93608,0 +54603,Male,28,Masters,18,25,8,84,22,2.0,7,28,Urban,Data Analyst,78252,0 +54604,Female,23,Bachelors,4,73,25,43,38,0.0,3,79,Urban,ML Engineer,143173,0 +54605,Male,23,Bachelors,8,47,98,84,16,2.0,7,46,Urban,Manager,28509,1 +54606,Female,36,Bachelors,6,79,30,32,26,2.0,6,18,Urban,Software Engineer,102288,0 +54607,Male,57,Bachelors,2,4,20,10,62,0.0,2,92,Urban,Software Engineer,84117,0 +54608,Female,29,Bachelors,5,76,57,34,97,5.0,3,97,Urban,HR Executive,68889,1 +54609,Female,30,Bachelors,13,79,78,94,6,3.0,5,62,Semi-Urban,Manager,33217,1 +54610,Male,21,Masters,7,21,89,50,42,6.0,5,30,Rural,ML Engineer,52737,0 +54611,Female,33,PhD,14,61,70,17,61,0.0,6,16,Semi-Urban,ML Engineer,140783,0 +54612,Male,41,Bachelors,3,10,57,26,61,6.0,5,98,Urban,HR Executive,65030,0 +54613,Male,55,Masters,16,23,39,4,12,2.0,1,13,Semi-Urban,Software Engineer,90959,0 +54614,Other,59,Masters,14,60,18,16,5,1.0,2,67,Urban,ML Engineer,68708,0 +54615,Male,23,Diploma,9,63,55,57,34,2.0,2,3,Urban,HR Executive,117988,0 +54616,Male,45,Bachelors,14,20,22,24,58,7.0,0,51,Rural,ML Engineer,79060,0 +54617,Male,27,Bachelors,14,37,12,15,34,3.0,6,41,Urban,ML Engineer,114838,0 +54618,Female,25,High School,10,51,59,1,32,7.0,1,45,Rural,Manager,84069,0 +54619,Male,28,Masters,2,65,76,33,53,5.0,6,60,Urban,Manager,95445,0 +54620,Female,43,High School,0,49,73,86,1,8.0,7,8,Semi-Urban,ML Engineer,145460,0 +54621,Female,59,High School,19,68,84,91,71,8.0,2,43,Urban,Manager,40014,1 +54622,Male,50,Bachelors,6,67,27,23,30,3.0,3,51,Urban,Data Analyst,129579,0 +54623,Male,56,Diploma,4,72,67,85,59,3.0,0,68,Rural,Manager,95559,1 +54624,Female,29,Bachelors,16,47,52,77,56,9.0,4,5,Urban,Manager,110495,0 +54625,Female,22,High School,8,31,4,36,29,9.0,3,33,Urban,Data Analyst,48931,0 +54626,Male,38,Bachelors,14,60,49,37,0,2.0,3,90,Urban,Software Engineer,39119,1 +54627,Male,45,Masters,3,35,82,90,49,6.0,3,41,Semi-Urban,ML Engineer,37939,1 +54628,Female,33,Diploma,10,50,1,36,29,5.0,3,65,Semi-Urban,Data Analyst,77475,0 +54629,Female,42,Bachelors,1,50,63,15,4,9.0,5,28,Rural,Manager,132677,0 +54630,Female,30,Masters,12,22,61,97,62,7.0,7,32,Urban,HR Executive,22023,0 +54631,Male,22,Diploma,0,48,31,98,87,5.0,5,52,Rural,Manager,124976,0 +54632,Female,26,Bachelors,2,79,92,72,38,3.0,0,32,Urban,ML Engineer,42533,1 +54633,Male,42,Masters,13,43,78,62,18,3.0,0,70,Semi-Urban,Manager,90754,1 +54634,Female,30,PhD,17,8,22,57,9,6.0,6,42,Rural,Data Analyst,102876,0 +54635,Female,25,Masters,1,71,7,32,75,7.0,2,95,Urban,HR Executive,131224,0 +54636,Male,32,Masters,2,64,97,26,95,0.0,7,89,Urban,Manager,101208,1 +54637,Male,42,Masters,8,16,17,31,2,6.0,0,29,Urban,ML Engineer,30887,0 +54638,Female,54,Bachelors,10,24,26,79,49,4.0,1,14,Urban,HR Executive,46028,0 +54639,Female,50,High School,16,14,84,64,1,0.0,5,62,Urban,Data Analyst,117918,0 +54640,Male,39,High School,4,4,98,25,99,8.0,6,56,Urban,Software Engineer,131727,0 +54641,Female,43,Bachelors,8,61,73,19,33,0.0,5,63,Semi-Urban,ML Engineer,141135,0 +54642,Male,35,Bachelors,18,30,15,46,22,7.0,1,62,Urban,ML Engineer,96108,0 +54643,Female,37,Masters,16,89,41,72,12,3.0,5,12,Rural,Data Analyst,98666,0 +54644,Female,30,Bachelors,3,11,8,99,14,6.0,7,24,Urban,Data Analyst,28715,0 +54645,Male,55,Bachelors,11,30,22,10,58,2.0,5,39,Semi-Urban,Software Engineer,125014,0 +54646,Female,39,High School,19,84,34,64,33,0.0,0,34,Urban,Software Engineer,88844,0 +54647,Female,52,Diploma,12,69,9,20,12,2.0,7,37,Urban,Data Analyst,113756,0 +54648,Male,54,Diploma,9,0,18,88,14,0.0,3,8,Rural,HR Executive,43170,0 +54649,Male,36,Bachelors,0,59,62,62,57,7.0,7,14,Semi-Urban,Data Analyst,41585,0 +54650,Male,29,Bachelors,6,62,16,75,37,4.0,7,7,Urban,ML Engineer,74722,0 +54651,Other,25,High School,0,38,26,64,32,7.0,6,86,Urban,ML Engineer,85972,0 +54652,Male,40,Bachelors,17,36,96,41,59,6.0,3,76,Semi-Urban,HR Executive,94577,1 +54653,Male,30,Bachelors,8,65,7,19,45,1.0,7,9,Rural,Software Engineer,29979,0 +54654,Female,36,Diploma,16,2,75,63,23,0.0,1,71,Urban,Manager,64136,0 +54655,Male,55,Bachelors,11,57,15,38,5,4.0,7,82,Urban,Data Analyst,82446,0 +54656,Male,45,High School,3,61,27,29,87,7.0,2,57,Semi-Urban,Data Analyst,64996,0 +54657,Male,45,High School,0,12,33,42,22,7.0,7,53,Urban,HR Executive,112048,0 +54658,Other,55,Bachelors,1,25,54,1,44,7.0,2,86,Semi-Urban,Manager,77486,0 +54659,Male,51,Diploma,1,24,86,98,39,3.0,0,23,Urban,HR Executive,100282,0 +54660,Female,34,Bachelors,2,22,14,82,38,1.0,4,88,Rural,Software Engineer,142624,0 +54661,Male,49,Bachelors,14,52,48,17,16,4.0,6,71,Urban,HR Executive,51555,0 +54662,Male,23,Masters,17,13,15,60,34,9.0,7,11,Rural,Software Engineer,91673,0 +54663,Male,25,Bachelors,17,69,66,22,89,5.0,3,9,Semi-Urban,HR Executive,35026,0 +54664,Male,57,Bachelors,19,7,51,29,77,4.0,7,79,Urban,Data Analyst,36743,0 +54665,Other,28,Bachelors,5,98,19,85,80,0.0,2,39,Rural,Data Analyst,116240,1 +54666,Female,52,Bachelors,7,21,24,83,16,6.0,0,72,Urban,HR Executive,119808,0 +54667,Female,30,Masters,12,35,26,8,55,9.0,4,76,Urban,HR Executive,92766,0 +54668,Male,50,Diploma,10,71,76,25,7,5.0,6,69,Semi-Urban,HR Executive,39662,1 +54669,Male,34,High School,1,12,8,16,71,7.0,6,25,Urban,Manager,87754,0 +54670,Male,41,Bachelors,11,89,32,57,7,2.0,4,87,Urban,ML Engineer,68889,1 +54671,Female,56,High School,8,50,91,71,48,0.0,0,1,Urban,HR Executive,138224,0 +54672,Female,58,High School,14,35,72,80,61,3.0,5,94,Rural,Manager,97544,1 +54673,Female,26,Masters,8,40,69,99,13,3.0,5,59,Semi-Urban,HR Executive,128773,1 +54674,Female,22,High School,0,85,5,10,26,7.0,0,37,Urban,HR Executive,55274,0 +54675,Male,25,High School,5,66,98,67,39,7.0,1,65,Urban,Manager,59496,1 +54676,Female,33,High School,14,34,80,73,84,3.0,3,41,Rural,Software Engineer,119412,0 +54677,Female,55,Bachelors,16,66,65,76,42,0.0,3,21,Semi-Urban,Data Analyst,46625,0 +54678,Male,34,Bachelors,16,47,82,16,29,0.0,3,63,Rural,ML Engineer,37384,0 +54679,Female,47,Bachelors,3,87,65,14,77,0.0,7,1,Urban,HR Executive,73022,0 +54680,Female,59,Bachelors,2,38,23,50,13,6.0,0,7,Semi-Urban,Manager,30836,0 +54681,Male,39,Bachelors,3,94,23,26,60,3.0,1,51,Urban,HR Executive,43386,0 +54682,Male,21,High School,14,60,88,67,86,2.0,1,62,Urban,ML Engineer,72118,1 +54683,Male,43,Masters,13,95,96,36,85,6.0,1,8,Urban,HR Executive,41488,1 +54684,Female,23,Masters,15,33,37,84,47,3.0,2,37,Urban,Software Engineer,36976,0 +54685,Female,31,Bachelors,15,80,70,21,96,7.0,1,21,Rural,Manager,45895,0 +54686,Male,39,PhD,2,97,7,99,58,8.0,0,54,Urban,Software Engineer,28861,1 +54687,Female,40,Diploma,18,56,87,39,53,0.0,7,24,Urban,HR Executive,34224,0 +54688,Male,39,Diploma,13,67,1,26,92,3.0,6,31,Semi-Urban,Data Analyst,105929,0 +54689,Male,55,PhD,18,0,16,14,58,2.0,4,53,Semi-Urban,Software Engineer,139829,0 +54690,Male,59,Diploma,4,59,36,90,41,1.0,1,53,Urban,Software Engineer,101728,1 +54691,Male,43,Masters,14,77,88,22,68,1.0,5,91,Rural,HR Executive,133356,1 +54692,Male,48,Diploma,18,16,7,68,36,6.0,2,18,Semi-Urban,HR Executive,37356,0 +54693,Female,51,Diploma,11,94,21,94,52,8.0,6,15,Urban,Software Engineer,125137,0 +54694,Female,59,Bachelors,10,76,5,48,46,6.0,6,49,Urban,Data Analyst,90909,0 +54695,Male,26,Bachelors,14,67,10,1,84,0.0,6,4,Urban,Manager,48489,0 +54696,Male,54,PhD,17,81,76,69,30,1.0,0,85,Urban,HR Executive,135200,1 +54697,Male,33,High School,14,87,37,8,94,1.0,2,26,Urban,Data Analyst,60813,0 +54698,Male,28,PhD,13,85,50,20,70,1.0,2,68,Semi-Urban,Software Engineer,133259,0 +54699,Male,27,Bachelors,14,75,44,33,66,6.0,6,89,Semi-Urban,Data Analyst,98450,1 +54700,Female,39,Diploma,1,1,38,60,16,5.0,4,3,Urban,ML Engineer,99372,0 +54701,Male,27,Masters,17,37,44,13,14,9.0,0,78,Urban,ML Engineer,81331,0 +54702,Male,36,Bachelors,10,41,14,50,23,1.0,3,72,Rural,Software Engineer,89322,0 +54703,Male,32,Masters,1,20,46,0,97,6.0,4,13,Urban,ML Engineer,74197,0 +54704,Female,42,High School,0,61,38,29,4,6.0,3,5,Urban,Data Analyst,70345,0 +54705,Male,44,Diploma,13,19,0,6,68,5.0,0,24,Semi-Urban,Software Engineer,27334,0 +54706,Male,28,Masters,5,75,72,27,8,1.0,6,73,Urban,Data Analyst,118837,1 +54707,Male,59,Bachelors,8,43,63,69,14,4.0,2,34,Semi-Urban,HR Executive,43638,0 +54708,Male,32,Masters,10,90,81,29,43,9.0,0,11,Urban,ML Engineer,131635,0 +54709,Other,34,Masters,8,40,64,2,15,0.0,1,51,Urban,ML Engineer,70423,0 +54710,Male,34,Bachelors,0,59,36,36,71,5.0,4,5,Semi-Urban,HR Executive,118789,0 +54711,Female,49,Diploma,7,91,28,52,4,4.0,6,88,Urban,Manager,89051,1 +54712,Male,47,Diploma,15,42,71,32,71,7.0,6,98,Urban,Software Engineer,119699,1 +54713,Male,45,High School,16,26,59,28,86,2.0,0,77,Urban,Manager,82257,0 +54714,Female,48,Bachelors,9,10,72,40,17,0.0,4,90,Urban,HR Executive,122246,0 +54715,Female,50,Diploma,16,88,93,54,83,1.0,3,38,Rural,ML Engineer,107763,1 +54716,Male,36,Bachelors,0,98,41,17,47,1.0,7,37,Semi-Urban,Software Engineer,32049,0 +54717,Male,36,PhD,5,56,13,73,85,3.0,7,3,Semi-Urban,Data Analyst,132303,0 +54718,Male,30,Bachelors,18,78,71,6,77,5.0,2,46,Urban,Data Analyst,142353,0 +54719,Other,29,Bachelors,7,87,78,64,86,4.0,0,39,Urban,ML Engineer,47725,1 +54720,Female,52,Bachelors,1,94,46,45,95,6.0,5,73,Urban,Software Engineer,79815,1 +54721,Male,33,Bachelors,4,78,23,16,97,0.0,0,63,Urban,ML Engineer,133318,0 +54722,Male,38,Masters,15,90,41,79,10,2.0,3,7,Urban,Software Engineer,127595,0 +54723,Male,36,PhD,1,70,71,91,28,4.0,2,41,Urban,HR Executive,37622,1 +54724,Female,43,Diploma,17,29,44,30,34,2.0,4,2,Urban,Software Engineer,60453,0 +54725,Male,55,Bachelors,0,24,58,72,19,0.0,5,43,Urban,Data Analyst,94417,0 +54726,Male,35,Masters,18,7,25,2,31,8.0,0,23,Rural,Data Analyst,139673,0 +54727,Female,43,Bachelors,2,73,38,90,43,2.0,1,40,Semi-Urban,Software Engineer,36580,1 +54728,Male,54,Bachelors,9,16,13,77,71,1.0,5,14,Urban,Manager,55069,0 +54729,Male,38,Masters,8,85,96,53,46,3.0,6,57,Rural,Manager,52919,1 +54730,Male,55,Diploma,9,36,4,55,48,1.0,3,50,Urban,Data Analyst,40769,0 +54731,Male,56,Bachelors,0,22,28,90,22,1.0,6,45,Rural,Manager,52501,0 +54732,Male,54,Bachelors,11,58,88,6,99,5.0,6,21,Urban,Manager,102603,0 +54733,Female,47,High School,0,16,93,43,87,7.0,6,1,Rural,Software Engineer,101981,0 +54734,Male,23,Diploma,10,73,97,29,43,7.0,6,28,Semi-Urban,HR Executive,121580,0 +54735,Male,22,Bachelors,8,7,23,65,95,1.0,7,66,Semi-Urban,Manager,129454,0 +54736,Male,58,Masters,18,12,21,56,36,0.0,7,16,Urban,Software Engineer,125118,0 +54737,Male,51,Bachelors,9,47,41,6,40,8.0,4,51,Urban,HR Executive,60921,0 +54738,Male,48,Diploma,6,12,17,13,27,1.0,0,23,Urban,HR Executive,32756,0 +54739,Male,35,Bachelors,19,5,16,98,84,1.0,3,79,Rural,ML Engineer,149869,0 +54740,Male,44,Masters,3,47,53,17,85,3.0,7,44,Urban,ML Engineer,40077,0 +54741,Female,39,Diploma,11,24,54,10,16,9.0,6,47,Rural,Data Analyst,71603,0 +54742,Male,57,Masters,18,48,22,26,15,0.0,6,13,Urban,ML Engineer,62042,0 +54743,Female,45,High School,10,50,60,72,7,9.0,7,90,Urban,HR Executive,96937,1 +54744,Male,54,PhD,6,71,51,88,88,9.0,6,69,Semi-Urban,HR Executive,117879,1 +54745,Female,38,Masters,3,61,25,21,60,8.0,7,12,Urban,Manager,52850,0 +54746,Female,41,High School,1,91,60,89,48,9.0,0,50,Urban,ML Engineer,27187,1 +54747,Female,45,High School,13,71,18,39,88,2.0,7,2,Urban,Software Engineer,50274,0 +54748,Male,32,PhD,15,2,90,33,54,1.0,3,80,Urban,Manager,52857,0 +54749,Male,46,High School,4,70,65,85,63,8.0,2,68,Urban,Data Analyst,131614,1 +54750,Female,34,Bachelors,16,58,20,88,66,0.0,1,80,Urban,HR Executive,135636,1 +54751,Male,48,PhD,13,72,9,13,55,0.0,0,44,Urban,HR Executive,119727,0 +54752,Male,54,PhD,12,39,41,24,39,9.0,7,44,Urban,ML Engineer,92185,0 +54753,Female,45,Masters,11,69,18,25,32,1.0,4,51,Urban,HR Executive,45994,0 +54754,Female,40,Diploma,10,47,22,84,42,8.0,6,1,Urban,HR Executive,81097,0 +54755,Female,29,Diploma,15,52,90,48,50,5.0,3,88,Urban,Data Analyst,67317,1 +54756,Male,30,Bachelors,4,63,58,81,7,6.0,6,35,Semi-Urban,Manager,42454,1 +54757,Male,25,Masters,18,81,27,67,85,7.0,2,64,Semi-Urban,ML Engineer,129399,1 +54758,Male,51,Masters,18,7,69,67,78,1.0,3,48,Urban,HR Executive,148420,0 +54759,Male,24,Diploma,6,85,75,59,35,9.0,2,85,Semi-Urban,ML Engineer,115617,1 +54760,Male,54,PhD,4,95,99,36,83,7.0,2,66,Semi-Urban,Software Engineer,64330,1 +54761,Male,57,Masters,17,4,27,71,59,4.0,5,10,Rural,Software Engineer,94813,0 +54762,Female,47,Diploma,16,21,31,67,61,2.0,2,88,Semi-Urban,HR Executive,105810,0 +54763,Male,36,Masters,4,43,41,87,32,0.0,5,32,Urban,Data Analyst,133776,0 +54764,Female,38,High School,12,89,96,54,94,0.0,1,96,Urban,ML Engineer,74377,1 +54765,Male,31,Diploma,7,62,93,33,50,8.0,4,16,Urban,Data Analyst,62053,0 +54766,Male,44,High School,8,3,88,29,23,5.0,0,11,Semi-Urban,Manager,46758,0 +54767,Male,26,Bachelors,13,19,88,1,80,2.0,2,91,Urban,Manager,41487,0 +54768,Female,44,High School,3,99,20,60,55,1.0,2,5,Rural,Data Analyst,46063,0 +54769,Male,21,Bachelors,4,9,92,64,14,6.0,3,71,Rural,Data Analyst,62976,1 +54770,Female,35,Bachelors,1,91,67,82,29,5.0,0,41,Urban,Software Engineer,102419,1 +54771,Male,49,Diploma,8,46,23,76,99,0.0,6,1,Urban,Software Engineer,129920,0 +54772,Male,21,Masters,1,4,63,36,66,8.0,2,92,Urban,Software Engineer,31872,0 +54773,Female,39,High School,16,74,89,79,94,9.0,1,18,Urban,Manager,113644,1 +54774,Male,41,Diploma,2,6,28,65,45,4.0,4,92,Urban,HR Executive,30218,0 +54775,Male,46,Bachelors,13,53,69,94,60,3.0,1,5,Urban,HR Executive,65635,0 +54776,Male,53,Bachelors,13,29,15,71,9,6.0,3,14,Semi-Urban,Manager,105766,0 +54777,Other,22,Diploma,14,96,43,4,19,9.0,3,42,Urban,Software Engineer,24398,0 +54778,Female,58,Diploma,6,75,99,50,22,6.0,4,73,Rural,Manager,65256,1 +54779,Female,21,High School,9,18,30,39,9,2.0,1,68,Semi-Urban,Manager,30219,0 +54780,Male,51,Bachelors,4,43,98,55,18,6.0,1,60,Urban,Data Analyst,89845,1 +54781,Male,36,Bachelors,3,89,81,14,9,7.0,2,94,Urban,Data Analyst,108096,1 +54782,Male,55,Bachelors,14,75,63,74,56,5.0,3,66,Rural,Software Engineer,148948,1 +54783,Female,47,Masters,1,33,97,4,4,7.0,1,63,Urban,Software Engineer,113134,0 +54784,Male,32,Masters,11,26,89,91,0,5.0,6,82,Urban,Software Engineer,41813,1 +54785,Male,54,Diploma,19,65,43,99,24,8.0,4,40,Semi-Urban,Software Engineer,36057,1 +54786,Female,45,Bachelors,18,11,73,79,18,9.0,2,47,Semi-Urban,HR Executive,129301,0 +54787,Female,37,Diploma,11,29,83,10,85,4.0,2,99,Urban,Data Analyst,96320,0 +54788,Male,29,Bachelors,0,54,3,49,45,4.0,3,69,Urban,ML Engineer,92657,0 +54789,Female,46,Masters,5,5,58,15,67,4.0,7,21,Urban,ML Engineer,68041,0 +54790,Male,59,Diploma,4,33,49,77,6,2.0,2,54,Semi-Urban,Manager,97487,0 +54791,Male,42,Bachelors,16,55,39,28,73,3.0,3,6,Semi-Urban,ML Engineer,135678,0 +54792,Female,45,Bachelors,16,84,3,0,35,8.0,7,52,Semi-Urban,Manager,88937,0 +54793,Male,25,Bachelors,19,80,19,67,68,1.0,5,59,Urban,Manager,114748,0 +54794,Female,56,Bachelors,6,24,82,43,26,4.0,2,55,Urban,Manager,126012,0 +54795,Male,36,PhD,12,0,16,80,40,2.0,2,68,Urban,Software Engineer,115677,0 +54796,Female,37,Bachelors,18,23,1,70,68,6.0,6,43,Urban,Data Analyst,145747,0 +54797,Male,32,Bachelors,4,68,52,5,0,9.0,5,46,Semi-Urban,HR Executive,54864,0 +54798,Female,22,High School,9,48,50,97,96,6.0,4,35,Urban,Software Engineer,33366,0 +54799,Other,54,Bachelors,7,36,57,11,86,8.0,0,35,Urban,Manager,39139,0 +54800,Male,39,Bachelors,7,74,38,97,15,3.0,7,44,Urban,Data Analyst,121880,1 +54801,Male,23,Bachelors,10,56,34,41,83,3.0,4,86,Urban,Manager,104499,0 +54802,Male,25,Diploma,16,6,74,74,1,1.0,2,38,Urban,Data Analyst,48071,0 +54803,Female,38,Bachelors,13,5,52,37,2,4.0,5,60,Urban,Data Analyst,85116,0 +54804,Male,25,Masters,10,48,68,41,63,5.0,4,12,Urban,Software Engineer,30209,0 +54805,Male,50,Bachelors,15,85,3,64,26,6.0,0,35,Semi-Urban,HR Executive,101835,0 +54806,Female,48,Masters,8,35,47,78,25,9.0,0,58,Semi-Urban,Software Engineer,66058,0 +54807,Female,46,Bachelors,19,49,49,14,32,6.0,4,79,Urban,HR Executive,24025,0 +54808,Male,38,Masters,9,59,56,21,40,0.0,2,26,Urban,ML Engineer,51495,0 +54809,Female,52,Bachelors,1,52,91,59,21,6.0,0,50,Urban,ML Engineer,30771,1 +54810,Male,48,Diploma,0,63,14,83,55,3.0,3,14,Urban,Data Analyst,64308,0 +54811,Female,26,Bachelors,1,73,65,35,77,0.0,2,26,Semi-Urban,Software Engineer,79954,0 +54812,Male,30,PhD,12,79,48,0,24,5.0,6,91,Urban,Software Engineer,72813,0 +54813,Male,22,Bachelors,5,24,22,74,19,8.0,6,1,Urban,ML Engineer,131102,0 +54814,Female,50,Diploma,3,82,28,27,63,9.0,6,68,Semi-Urban,ML Engineer,23680,0 +54815,Male,35,Bachelors,17,59,67,68,38,0.0,4,43,Urban,Data Analyst,133677,1 +54816,Male,58,Bachelors,5,83,98,29,18,5.0,7,5,Semi-Urban,Manager,81790,0 +54817,Female,38,High School,18,45,90,85,88,1.0,2,90,Rural,Manager,121307,1 +54818,Male,54,Bachelors,17,14,39,16,25,9.0,6,97,Urban,Manager,75725,0 +54819,Male,46,Bachelors,19,8,57,42,68,1.0,5,60,Rural,Software Engineer,107881,0 +54820,Female,49,Masters,0,8,19,38,2,9.0,4,21,Semi-Urban,Manager,99039,0 +54821,Female,29,Bachelors,13,87,52,2,97,0.0,3,83,Urban,HR Executive,100760,0 +54822,Female,42,Masters,15,86,54,81,68,4.0,0,68,Semi-Urban,Data Analyst,111150,1 +54823,Male,57,Diploma,19,46,24,14,80,5.0,7,31,Rural,ML Engineer,98837,0 +54824,Male,31,High School,16,64,74,47,79,1.0,7,27,Urban,HR Executive,39156,0 +54825,Male,44,Bachelors,9,53,96,1,34,8.0,2,62,Rural,Data Analyst,124124,0 +54826,Male,49,Bachelors,16,56,80,7,1,1.0,7,41,Rural,Software Engineer,145448,0 +54827,Male,33,Bachelors,8,17,50,43,4,0.0,1,15,Urban,Data Analyst,141247,0 +54828,Male,56,Bachelors,5,76,96,15,3,2.0,3,25,Urban,Manager,68645,0 +54829,Female,36,Masters,0,42,52,95,59,0.0,7,83,Semi-Urban,ML Engineer,59415,1 +54830,Female,35,Bachelors,1,94,22,90,91,8.0,5,64,Urban,ML Engineer,78930,1 +54831,Male,30,PhD,0,96,44,76,99,3.0,6,90,Rural,Manager,102534,1 +54832,Male,28,Bachelors,8,53,10,29,13,2.0,5,96,Urban,HR Executive,26518,0 +54833,Male,51,Masters,13,23,13,65,95,2.0,5,6,Semi-Urban,HR Executive,48429,0 +54834,Male,56,High School,0,59,21,66,83,0.0,5,89,Semi-Urban,Manager,64696,1 +54835,Female,49,Bachelors,16,61,32,91,60,7.0,1,84,Semi-Urban,Data Analyst,149863,1 +54836,Male,55,High School,19,9,57,83,60,7.0,5,75,Urban,Software Engineer,76470,0 +54837,Female,32,Masters,0,8,77,81,85,3.0,3,77,Rural,HR Executive,30904,1 +54838,Male,34,Diploma,3,8,44,40,85,3.0,1,10,Urban,Data Analyst,78566,0 +54839,Female,46,Diploma,6,88,34,26,79,4.0,2,11,Urban,ML Engineer,59664,0 +54840,Female,47,Bachelors,13,94,52,89,18,1.0,0,68,Semi-Urban,ML Engineer,112712,1 +54841,Male,24,Bachelors,4,7,9,61,67,9.0,7,84,Urban,Software Engineer,131179,0 +54842,Male,58,High School,17,42,95,58,99,5.0,2,35,Urban,HR Executive,147898,0 +54843,Female,54,Bachelors,5,1,54,4,57,5.0,3,15,Rural,Software Engineer,78005,0 +54844,Male,53,Masters,3,17,16,0,98,9.0,1,18,Urban,Software Engineer,76964,0 +54845,Male,39,Bachelors,5,27,6,65,96,8.0,6,18,Urban,Manager,109656,0 +54846,Male,30,High School,12,86,75,11,22,2.0,7,40,Urban,HR Executive,142667,0 +54847,Male,27,Masters,18,76,83,50,84,4.0,2,82,Urban,Software Engineer,119478,1 +54848,Male,59,Bachelors,0,31,23,48,45,3.0,0,53,Semi-Urban,Manager,118756,0 +54849,Male,31,PhD,7,77,81,89,99,4.0,0,76,Urban,ML Engineer,105634,1 +54850,Other,24,Bachelors,14,26,54,8,8,3.0,0,44,Urban,HR Executive,134285,0 +54851,Male,51,High School,15,99,16,56,82,7.0,2,11,Urban,Manager,96122,0 +54852,Male,42,Masters,17,46,5,10,45,1.0,3,34,Urban,Manager,120104,0 +54853,Male,53,Bachelors,8,6,49,4,48,0.0,6,53,Rural,HR Executive,48727,0 +54854,Male,39,High School,0,14,17,6,55,6.0,1,82,Semi-Urban,HR Executive,116229,0 +54855,Female,50,Masters,3,14,61,47,24,4.0,3,5,Rural,ML Engineer,112509,0 +54856,Other,48,Bachelors,3,88,25,78,98,1.0,4,6,Urban,Data Analyst,25024,0 +54857,Female,54,Masters,8,96,26,56,2,7.0,7,95,Rural,Software Engineer,69588,1 +54858,Male,57,PhD,17,65,14,77,28,0.0,2,99,Urban,Data Analyst,46646,1 +54859,Male,22,High School,9,23,51,95,15,1.0,7,80,Urban,ML Engineer,126561,1 +54860,Male,55,Bachelors,19,8,98,97,37,0.0,6,92,Rural,Software Engineer,89749,1 +54861,Male,52,Diploma,14,26,61,19,96,0.0,1,25,Urban,HR Executive,91935,0 +54862,Male,38,PhD,9,87,37,55,77,8.0,3,93,Semi-Urban,ML Engineer,60336,1 +54863,Female,28,Bachelors,6,83,30,35,58,8.0,5,20,Semi-Urban,Software Engineer,139907,0 +54864,Male,34,Diploma,3,49,28,38,24,7.0,2,87,Urban,Software Engineer,59830,0 +54865,Male,34,Masters,19,28,48,91,20,3.0,5,10,Rural,Manager,149223,0 +54866,Female,41,Masters,7,38,70,1,18,9.0,1,40,Semi-Urban,Software Engineer,56518,0 +54867,Female,46,PhD,13,68,65,15,55,3.0,5,66,Urban,HR Executive,117212,0 +54868,Male,37,Masters,13,54,69,8,76,9.0,3,27,Urban,Software Engineer,48153,0 +54869,Male,30,Bachelors,10,11,24,83,40,0.0,7,89,Urban,ML Engineer,37398,0 +54870,Female,53,Diploma,7,72,24,66,84,1.0,7,66,Urban,Manager,131161,0 +54871,Male,57,Bachelors,14,42,23,77,77,0.0,2,36,Urban,HR Executive,105975,0 +54872,Female,45,High School,7,28,44,27,76,9.0,7,97,Rural,HR Executive,46796,0 +54873,Male,58,Masters,16,58,8,26,43,2.0,6,89,Semi-Urban,Software Engineer,91054,0 +54874,Male,57,High School,15,80,19,39,34,6.0,4,61,Rural,Data Analyst,104161,0 +54875,Male,47,Bachelors,1,28,15,85,9,0.0,3,37,Urban,Software Engineer,93608,0 +54876,Male,29,Bachelors,4,99,40,48,34,8.0,1,28,Urban,Manager,47077,0 +54877,Female,46,Bachelors,15,83,69,66,82,1.0,5,43,Semi-Urban,Software Engineer,45491,1 +54878,Female,40,High School,8,76,77,51,1,0.0,0,23,Semi-Urban,Manager,78836,0 +54879,Female,31,Diploma,14,50,69,90,42,8.0,2,40,Urban,Software Engineer,134555,1 +54880,Male,49,Bachelors,14,24,63,76,32,4.0,3,28,Urban,Manager,42942,0 +54881,Female,27,Masters,7,56,38,5,83,8.0,7,59,Urban,ML Engineer,109181,0 +54882,Female,39,Diploma,3,89,15,14,8,2.0,1,34,Rural,HR Executive,133077,0 +54883,Female,54,Diploma,15,2,3,65,28,2.0,6,49,Urban,HR Executive,52460,0 +54884,Male,43,Diploma,9,0,74,84,97,4.0,7,64,Rural,Manager,44960,0 +54885,Female,40,Bachelors,9,51,95,46,99,6.0,2,60,Rural,HR Executive,65189,1 +54886,Male,50,PhD,12,59,60,15,65,3.0,2,17,Urban,Manager,33608,0 +54887,Male,21,Diploma,12,58,49,66,60,9.0,0,50,Urban,ML Engineer,55025,0 +54888,Male,31,Bachelors,16,98,5,64,74,2.0,2,86,Semi-Urban,ML Engineer,122753,1 +54889,Female,56,Diploma,0,53,23,39,88,0.0,7,76,Semi-Urban,ML Engineer,70556,0 +54890,Female,42,Masters,19,62,82,46,16,1.0,4,66,Urban,Data Analyst,65941,1 +54891,Male,36,Bachelors,5,70,30,16,42,1.0,3,38,Urban,Data Analyst,35195,0 +54892,Male,33,Bachelors,19,73,76,37,13,7.0,5,32,Urban,ML Engineer,142709,0 +54893,Male,50,Bachelors,16,44,27,39,75,1.0,7,38,Urban,HR Executive,28751,0 +54894,Female,52,Diploma,18,60,12,33,22,7.0,6,26,Urban,Manager,115386,0 +54895,Female,55,Bachelors,8,50,56,24,88,2.0,2,72,Semi-Urban,Software Engineer,99874,0 +54896,Male,45,Diploma,16,89,68,63,94,6.0,1,84,Urban,Software Engineer,65633,1 +54897,Female,42,Bachelors,14,54,62,82,5,3.0,3,86,Urban,HR Executive,59713,1 +54898,Male,21,PhD,18,39,53,77,95,5.0,6,99,Urban,Manager,107406,1 +54899,Male,37,Bachelors,4,78,96,46,38,8.0,0,18,Rural,Manager,79838,1 +54900,Male,58,High School,16,98,11,95,26,6.0,5,7,Urban,Data Analyst,108167,0 +54901,Male,35,Diploma,14,98,64,49,28,8.0,2,1,Urban,ML Engineer,84252,0 +54902,Female,23,PhD,14,62,10,58,87,4.0,0,32,Urban,HR Executive,51305,0 +54903,Other,36,Diploma,2,27,71,24,6,2.0,4,36,Urban,Manager,93156,0 +54904,Male,36,Diploma,9,18,72,65,27,3.0,1,69,Urban,Data Analyst,61688,0 +54905,Female,42,Bachelors,2,16,62,77,0,6.0,6,2,Semi-Urban,HR Executive,43673,0 +54906,Female,23,Bachelors,18,61,70,23,8,3.0,7,28,Rural,ML Engineer,23808,0 +54907,Male,21,Bachelors,16,98,18,26,64,3.0,4,7,Urban,Software Engineer,105085,0 +54908,Male,37,Masters,11,6,11,86,17,3.0,3,53,Urban,ML Engineer,75196,0 +54909,Female,49,Diploma,10,89,47,96,49,6.0,0,45,Rural,Software Engineer,35661,1 +54910,Female,52,Masters,2,80,61,14,19,1.0,7,69,Urban,HR Executive,60080,0 +54911,Male,43,Diploma,12,92,3,63,16,2.0,3,61,Semi-Urban,ML Engineer,72244,0 +54912,Male,45,Bachelors,11,23,14,20,91,2.0,2,80,Rural,Manager,60646,0 +54913,Female,39,PhD,18,4,80,51,17,7.0,6,40,Semi-Urban,HR Executive,57998,0 +54914,Male,46,Bachelors,10,0,4,15,14,2.0,5,28,Rural,Manager,41287,0 +54915,Female,54,Masters,13,79,11,77,40,5.0,5,60,Urban,Data Analyst,71783,0 +54916,Male,43,Diploma,0,77,92,82,69,1.0,2,74,Rural,Manager,93960,1 +54917,Male,32,High School,8,57,50,9,53,3.0,4,13,Semi-Urban,HR Executive,89096,0 +54918,Male,55,Diploma,15,19,86,76,3,8.0,1,49,Semi-Urban,HR Executive,112689,0 +54919,Male,48,Bachelors,14,8,14,9,16,3.0,3,92,Semi-Urban,HR Executive,37640,0 +54920,Male,40,Masters,8,31,42,74,53,1.0,5,59,Urban,Data Analyst,52837,0 +54921,Male,25,Diploma,13,19,51,25,45,7.0,4,86,Urban,ML Engineer,26385,0 +54922,Female,56,Masters,19,98,37,2,84,0.0,3,16,Urban,HR Executive,117246,0 +54923,Male,21,PhD,13,40,22,49,75,7.0,1,32,Urban,HR Executive,25376,0 +54924,Female,26,Diploma,3,66,85,98,69,6.0,4,50,Semi-Urban,Data Analyst,148885,1 +54925,Female,49,High School,8,1,79,41,52,3.0,5,85,Urban,Manager,143656,0 +54926,Female,36,Diploma,14,59,76,55,83,4.0,4,83,Urban,ML Engineer,35260,1 +54927,Male,53,Bachelors,9,24,39,33,73,8.0,1,27,Semi-Urban,HR Executive,38992,0 +54928,Female,42,Bachelors,8,59,81,19,18,1.0,3,33,Rural,HR Executive,89051,0 +54929,Female,54,Diploma,10,6,65,35,85,3.0,0,8,Semi-Urban,Data Analyst,109521,0 +54930,Male,23,Diploma,17,55,92,22,10,7.0,6,47,Urban,ML Engineer,139428,0 +54931,Male,59,Bachelors,5,65,66,36,23,0.0,6,98,Rural,HR Executive,133523,1 +54932,Male,58,Bachelors,9,14,97,59,64,4.0,4,76,Urban,Data Analyst,93985,1 +54933,Male,50,Masters,11,92,96,9,32,3.0,4,26,Urban,HR Executive,33069,0 +54934,Female,46,Bachelors,13,11,99,26,22,4.0,2,91,Urban,ML Engineer,142587,0 +54935,Female,44,Bachelors,18,78,49,27,46,2.0,1,57,Rural,Software Engineer,79951,0 +54936,Female,32,Diploma,7,73,53,58,61,8.0,1,87,Urban,Software Engineer,63783,1 +54937,Male,38,Bachelors,10,81,31,31,83,1.0,2,83,Urban,HR Executive,95503,0 +54938,Other,30,High School,9,56,86,71,74,1.0,0,92,Urban,Software Engineer,51931,1 +54939,Male,46,PhD,12,71,62,39,38,8.0,2,20,Rural,Data Analyst,87241,0 +54940,Male,21,Bachelors,7,12,96,32,17,1.0,0,78,Rural,HR Executive,140164,0 +54941,Female,23,Masters,3,33,45,20,81,1.0,2,78,Urban,Software Engineer,63001,0 +54942,Male,21,High School,2,61,70,56,55,7.0,7,3,Urban,Software Engineer,138632,0 +54943,Male,24,High School,4,7,52,62,67,2.0,5,4,Rural,Data Analyst,23357,0 +54944,Female,22,Bachelors,1,13,84,15,0,9.0,3,15,Rural,Software Engineer,114659,0 +54945,Female,34,High School,11,51,19,74,26,9.0,5,57,Urban,ML Engineer,85632,0 +54946,Male,50,Bachelors,7,18,47,60,20,5.0,2,96,Urban,Software Engineer,140710,0 +54947,Female,25,Bachelors,15,46,40,81,30,5.0,6,7,Urban,HR Executive,49819,0 +54948,Male,53,Masters,14,68,82,90,48,9.0,3,62,Rural,Data Analyst,117906,1 +54949,Female,27,PhD,0,11,96,42,73,1.0,6,83,Rural,HR Executive,91273,0 +54950,Male,29,High School,18,43,55,19,72,1.0,2,17,Urban,ML Engineer,71201,0 +54951,Other,21,Masters,19,18,38,94,53,3.0,0,92,Urban,Software Engineer,24269,1 +54952,Female,40,Bachelors,0,6,0,62,71,6.0,1,17,Semi-Urban,Data Analyst,56831,0 +54953,Male,43,Bachelors,0,39,24,95,18,5.0,0,78,Semi-Urban,Software Engineer,36347,1 +54954,Female,36,Diploma,19,99,72,28,62,7.0,1,52,Urban,ML Engineer,27115,1 +54955,Female,31,Bachelors,3,98,23,9,85,7.0,3,26,Semi-Urban,Software Engineer,72213,0 +54956,Male,32,Bachelors,18,40,51,0,62,2.0,2,7,Urban,Data Analyst,101697,0 +54957,Female,25,Bachelors,17,91,33,13,95,3.0,3,1,Semi-Urban,ML Engineer,71393,0 +54958,Other,52,Bachelors,11,95,98,48,1,4.0,0,56,Urban,Manager,131686,1 +54959,Male,55,Masters,1,11,43,77,21,3.0,1,61,Urban,Software Engineer,105030,0 +54960,Male,28,Bachelors,18,0,11,23,27,3.0,7,1,Urban,Data Analyst,114134,0 +54961,Male,21,Masters,0,34,51,43,16,5.0,0,20,Rural,ML Engineer,115801,0 +54962,Male,42,Bachelors,13,53,21,78,88,8.0,2,31,Urban,HR Executive,66899,0 +54963,Male,45,Masters,4,11,22,95,59,7.0,5,36,Urban,Software Engineer,102021,0 +54964,Male,23,Bachelors,2,78,65,39,17,3.0,6,64,Semi-Urban,ML Engineer,58591,1 +54965,Other,54,Bachelors,1,35,9,69,76,2.0,1,25,Urban,ML Engineer,56686,0 +54966,Female,41,Diploma,16,28,11,0,73,2.0,0,51,Urban,ML Engineer,103060,0 +54967,Female,56,Diploma,6,66,47,4,7,6.0,6,1,Semi-Urban,Software Engineer,117207,0 +54968,Other,32,Diploma,18,88,32,70,91,0.0,3,58,Urban,HR Executive,129544,1 +54969,Male,47,Diploma,8,32,96,84,98,0.0,0,89,Urban,ML Engineer,50579,1 +54970,Female,37,Masters,10,62,51,94,82,1.0,4,79,Semi-Urban,Data Analyst,65432,1 +54971,Male,57,Masters,5,33,69,70,9,4.0,4,98,Urban,Manager,130005,1 +54972,Male,36,Bachelors,4,72,58,16,90,9.0,5,85,Semi-Urban,Software Engineer,145229,0 +54973,Male,21,Bachelors,1,44,15,49,17,4.0,4,39,Urban,HR Executive,113351,0 +54974,Male,21,Masters,0,18,1,21,23,8.0,7,49,Semi-Urban,ML Engineer,130299,0 +54975,Male,47,PhD,1,89,10,30,48,5.0,0,26,Urban,Manager,130399,0 +54976,Male,29,Diploma,4,10,2,83,83,0.0,4,14,Semi-Urban,HR Executive,25608,0 +54977,Female,52,Bachelors,11,89,36,98,12,0.0,6,78,Rural,Software Engineer,127469,1 +54978,Male,44,High School,14,49,54,81,18,8.0,3,74,Rural,ML Engineer,123604,1 +54979,Male,28,Masters,5,65,83,86,35,4.0,1,14,Urban,Manager,143634,1 +54980,Female,21,Diploma,9,56,94,26,49,2.0,4,57,Rural,Software Engineer,57240,0 +54981,Male,32,Diploma,6,75,17,42,35,2.0,5,40,Urban,Data Analyst,64197,0 +54982,Female,57,Diploma,18,28,64,78,67,7.0,5,80,Urban,Manager,81467,1 +54983,Male,36,Masters,11,26,10,32,88,0.0,0,7,Urban,Data Analyst,102820,0 +54984,Male,36,Masters,5,60,58,33,26,4.0,7,71,Urban,ML Engineer,20864,0 +54985,Male,53,Bachelors,3,75,86,15,56,9.0,1,0,Rural,HR Executive,55565,0 +54986,Male,21,Diploma,12,79,21,61,7,3.0,6,70,Urban,Manager,40106,0 +54987,Male,44,Diploma,4,96,87,91,34,5.0,2,48,Semi-Urban,Software Engineer,28795,1 +54988,Male,48,Bachelors,19,40,69,93,57,5.0,4,88,Urban,HR Executive,145854,1 +54989,Female,25,Masters,10,53,84,59,12,9.0,6,88,Urban,ML Engineer,104171,1 +54990,Male,32,Masters,16,84,61,94,26,4.0,2,72,Urban,ML Engineer,45775,1 +54991,Male,25,Bachelors,17,20,82,12,47,0.0,1,79,Urban,HR Executive,53265,0 +54992,Other,29,Bachelors,14,76,57,69,73,3.0,6,66,Urban,Software Engineer,137069,1 +54993,Female,28,Bachelors,1,72,19,95,50,6.0,6,41,Urban,ML Engineer,125104,0 +54994,Male,59,Masters,15,24,81,97,10,0.0,5,51,Urban,Data Analyst,51012,1 +54995,Male,34,Bachelors,2,77,32,96,17,6.0,4,23,Semi-Urban,Data Analyst,61608,0 +54996,Male,52,Masters,3,99,0,41,60,3.0,3,29,Urban,Manager,80499,0 +54997,Female,55,Bachelors,12,21,46,5,70,3.0,1,57,Urban,Manager,71093,0 +54998,Female,22,Bachelors,7,41,37,67,76,3.0,7,33,Urban,ML Engineer,112855,0 +54999,Female,49,Bachelors,17,71,1,18,94,3.0,6,8,Urban,HR Executive,20543,0 +55000,Female,53,Masters,3,67,68,18,10,3.0,1,86,Rural,Software Engineer,113173,0 +55001,Male,42,High School,12,82,57,64,0,8.0,2,76,Urban,Software Engineer,87513,1 +55002,Male,54,Bachelors,17,61,23,44,36,7.0,2,86,Rural,Manager,83904,0 +55003,Female,32,Bachelors,12,46,42,34,92,3.0,5,56,Semi-Urban,Software Engineer,52042,0 +55004,Male,30,High School,13,31,77,46,46,4.0,3,57,Urban,Manager,98606,0 +55005,Female,49,Bachelors,13,19,80,30,41,6.0,2,63,Urban,HR Executive,143558,0 +55006,Male,42,High School,15,77,6,93,8,6.0,7,2,Semi-Urban,ML Engineer,143847,0 +55007,Male,34,Diploma,15,99,48,68,9,3.0,7,70,Urban,Data Analyst,98700,1 +55008,Female,54,Masters,17,38,46,11,10,4.0,7,16,Rural,ML Engineer,42560,0 +55009,Female,34,Bachelors,12,10,26,96,41,3.0,1,69,Urban,Data Analyst,127479,0 +55010,Female,28,Bachelors,12,5,97,71,8,4.0,7,94,Urban,HR Executive,34965,1 +55011,Female,59,Masters,5,38,72,33,98,6.0,4,91,Semi-Urban,Manager,110100,0 +55012,Male,35,Masters,16,41,76,21,18,7.0,6,4,Rural,ML Engineer,66958,0 +55013,Female,37,Bachelors,5,23,36,44,72,8.0,4,63,Urban,ML Engineer,51115,0 +55014,Female,46,Masters,0,51,51,31,41,3.0,4,0,Urban,ML Engineer,55310,0 +55015,Male,35,Diploma,11,95,59,61,78,2.0,4,62,Rural,Data Analyst,107398,1 +55016,Female,37,Diploma,5,16,96,1,99,7.0,2,14,Urban,HR Executive,77249,0 +55017,Female,31,Bachelors,13,88,42,60,16,1.0,0,48,Urban,Data Analyst,89528,0 +55018,Female,53,Bachelors,12,39,45,69,80,3.0,5,21,Rural,Manager,65527,0 +55019,Male,56,Diploma,19,68,20,21,93,7.0,0,93,Urban,ML Engineer,41952,0 +55020,Female,28,PhD,6,37,28,42,26,3.0,0,85,Urban,HR Executive,136425,0 +55021,Male,47,Bachelors,9,90,76,92,47,2.0,0,27,Urban,HR Executive,28390,1 +55022,Male,51,Diploma,4,21,9,52,78,1.0,3,78,Rural,Manager,116679,0 +55023,Female,42,Masters,11,47,79,96,13,8.0,4,67,Semi-Urban,Software Engineer,129097,1 +55024,Male,21,Bachelors,2,73,76,83,23,4.0,1,64,Semi-Urban,ML Engineer,95569,1 +55025,Male,32,High School,0,93,51,14,58,6.0,1,25,Urban,HR Executive,130144,0 +55026,Male,36,Bachelors,0,60,62,72,87,2.0,4,41,Rural,Software Engineer,72513,1 +55027,Male,22,Bachelors,13,55,75,4,2,2.0,0,22,Urban,Data Analyst,28005,0 +55028,Female,41,Masters,8,42,50,19,74,3.0,5,1,Rural,HR Executive,79686,0 +55029,Male,56,Masters,15,17,6,61,0,0.0,5,26,Rural,HR Executive,28190,0 +55030,Male,32,Masters,13,43,74,15,22,2.0,3,52,Urban,ML Engineer,115693,0 +55031,Male,22,Bachelors,0,22,12,28,97,4.0,7,35,Urban,Data Analyst,86779,0 +55032,Female,39,Bachelors,16,93,85,48,24,5.0,0,18,Semi-Urban,Software Engineer,59991,1 +55033,Female,47,High School,10,76,41,38,51,5.0,0,87,Urban,ML Engineer,129971,1 +55034,Female,43,Bachelors,9,56,87,80,73,1.0,7,52,Urban,Software Engineer,136669,1 +55035,Male,22,PhD,6,0,84,66,47,1.0,2,42,Rural,Software Engineer,82465,0 +55036,Female,55,Masters,13,28,1,27,15,9.0,2,84,Rural,Manager,40579,0 +55037,Male,45,Bachelors,18,14,10,11,90,5.0,7,50,Semi-Urban,HR Executive,21317,0 +55038,Male,24,Bachelors,10,65,75,39,21,8.0,2,26,Urban,Software Engineer,111695,0 +55039,Male,48,Masters,6,22,91,31,93,0.0,1,42,Urban,Software Engineer,107760,0 +55040,Male,52,Masters,6,2,50,34,7,2.0,1,30,Rural,Software Engineer,148676,0 +55041,Male,39,Bachelors,0,61,66,46,41,3.0,3,85,Urban,Software Engineer,41722,1 +55042,Male,38,Bachelors,2,52,82,80,69,1.0,2,44,Urban,HR Executive,29728,1 +55043,Male,43,Diploma,3,0,24,79,1,5.0,3,79,Urban,Software Engineer,90332,0 +55044,Female,22,Diploma,11,37,78,13,85,8.0,4,15,Urban,ML Engineer,97231,0 +55045,Male,30,Bachelors,4,63,69,36,46,9.0,2,95,Semi-Urban,HR Executive,76406,1 +55046,Other,49,High School,1,79,31,8,19,3.0,0,62,Semi-Urban,Software Engineer,85744,0 +55047,Male,33,PhD,0,76,85,94,55,4.0,0,48,Semi-Urban,Manager,50355,1 +55048,Male,34,Diploma,0,16,69,76,89,5.0,6,9,Urban,HR Executive,55787,0 +55049,Male,31,Bachelors,14,49,29,84,81,4.0,7,32,Urban,ML Engineer,100596,0 +55050,Male,47,Masters,6,50,42,89,60,1.0,7,58,Urban,ML Engineer,61230,1 +55051,Other,36,Bachelors,1,59,26,11,58,1.0,3,51,Urban,Data Analyst,72627,0 +55052,Female,59,High School,15,49,15,45,52,5.0,1,21,Urban,Software Engineer,139234,0 +55053,Male,53,Masters,8,62,89,76,43,6.0,0,10,Urban,Data Analyst,66776,1 +55054,Male,58,High School,18,96,18,12,40,6.0,2,58,Urban,ML Engineer,71778,0 +55055,Male,22,Diploma,11,72,96,77,8,2.0,3,42,Urban,Software Engineer,87093,1 +55056,Male,23,Bachelors,8,99,24,25,27,3.0,7,59,Semi-Urban,HR Executive,118653,0 +55057,Female,56,Bachelors,19,71,79,76,29,2.0,5,68,Rural,HR Executive,54544,1 +55058,Male,38,Bachelors,8,1,75,80,29,7.0,0,68,Rural,Software Engineer,99159,0 +55059,Male,59,Bachelors,6,58,14,88,8,4.0,4,54,Semi-Urban,Data Analyst,137478,0 +55060,Male,36,Bachelors,7,93,65,87,4,9.0,3,53,Urban,HR Executive,125655,1 +55061,Male,29,Diploma,3,52,37,75,12,7.0,6,53,Urban,Manager,76451,0 +55062,Female,42,Bachelors,0,42,68,95,58,8.0,5,71,Urban,HR Executive,86446,1 +55063,Male,31,Bachelors,9,93,55,65,11,0.0,1,64,Urban,HR Executive,57568,1 +55064,Male,36,Bachelors,1,44,72,29,78,0.0,3,58,Urban,Data Analyst,57366,0 +55065,Female,42,Bachelors,1,26,14,88,3,8.0,6,25,Semi-Urban,Manager,33999,0 +55066,Male,28,High School,13,77,5,80,17,9.0,6,17,Urban,Data Analyst,129299,0 +55067,Male,27,Bachelors,6,43,12,76,46,6.0,1,79,Urban,HR Executive,134476,0 +55068,Male,21,Masters,4,26,44,63,18,2.0,7,63,Urban,Manager,34732,0 +55069,Other,55,High School,9,78,30,23,23,1.0,6,37,Urban,ML Engineer,78121,0 +55070,Female,31,Bachelors,14,21,18,7,16,1.0,3,11,Semi-Urban,Manager,55943,0 +55071,Other,25,Bachelors,3,95,82,96,90,2.0,1,94,Semi-Urban,Software Engineer,34459,1 +55072,Female,30,PhD,13,54,89,93,1,2.0,5,27,Urban,Data Analyst,62997,1 +55073,Male,49,Masters,11,79,16,53,60,2.0,5,55,Semi-Urban,Software Engineer,55763,0 +55074,Male,58,Bachelors,11,87,51,68,64,6.0,0,69,Urban,Software Engineer,85415,1 +55075,Female,36,Masters,1,72,85,90,30,2.0,4,29,Semi-Urban,Software Engineer,28114,1 +55076,Male,59,Bachelors,6,21,84,79,41,1.0,2,13,Urban,Manager,80020,0 +55077,Male,43,Diploma,19,35,28,18,8,6.0,5,12,Rural,HR Executive,143390,0 +55078,Female,25,Bachelors,2,49,20,75,68,5.0,5,40,Rural,HR Executive,24713,0 +55079,Male,53,Diploma,9,22,39,19,89,2.0,2,6,Urban,Software Engineer,108232,0 +55080,Male,31,Masters,7,21,3,15,77,0.0,1,1,Urban,HR Executive,118627,0 +55081,Female,43,Masters,3,48,34,43,27,9.0,6,37,Rural,ML Engineer,128183,0 +55082,Female,57,Masters,11,28,16,51,72,5.0,6,60,Urban,Software Engineer,98677,0 +55083,Male,30,Bachelors,13,30,33,21,92,3.0,1,9,Urban,ML Engineer,62250,0 +55084,Male,26,Diploma,5,97,65,24,84,4.0,4,63,Urban,HR Executive,131201,1 +55085,Male,49,Diploma,0,19,96,90,51,1.0,2,80,Rural,ML Engineer,30086,1 +55086,Male,55,Diploma,5,68,5,17,54,1.0,5,57,Urban,Data Analyst,141487,0 +55087,Male,41,Masters,7,69,93,92,84,9.0,5,35,Urban,Data Analyst,92156,1 +55088,Female,56,Bachelors,7,78,43,64,24,8.0,0,32,Urban,Manager,66097,0 +55089,Male,49,Bachelors,2,1,99,82,88,8.0,3,6,Urban,HR Executive,149668,0 +55090,Female,47,Bachelors,18,63,34,28,49,6.0,3,5,Urban,ML Engineer,123815,0 +55091,Female,59,High School,10,62,64,85,14,6.0,2,82,Rural,ML Engineer,31021,1 +55092,Female,57,Bachelors,9,39,23,47,7,5.0,6,61,Urban,Manager,90573,0 +55093,Male,49,Bachelors,1,64,98,33,34,6.0,6,99,Semi-Urban,ML Engineer,115669,1 +55094,Male,42,High School,17,54,4,57,7,4.0,4,99,Urban,ML Engineer,82276,0 +55095,Female,52,High School,13,49,99,21,50,6.0,5,64,Semi-Urban,Software Engineer,73778,0 +55096,Other,50,Diploma,8,68,1,63,35,3.0,3,51,Urban,HR Executive,80037,0 +55097,Male,54,Diploma,1,36,10,57,98,4.0,0,76,Urban,Manager,148126,0 +55098,Female,28,Diploma,11,96,67,8,12,1.0,7,59,Urban,HR Executive,90075,0 +55099,Male,27,Bachelors,9,36,90,89,6,6.0,6,71,Urban,Manager,103391,1 +55100,Female,33,Bachelors,3,31,13,98,11,8.0,6,48,Rural,Software Engineer,143825,0 +55101,Male,31,Masters,5,3,82,41,6,9.0,5,49,Semi-Urban,Software Engineer,39690,0 +55102,Female,58,Bachelors,11,0,78,53,42,3.0,7,75,Urban,Data Analyst,84147,0 +55103,Female,41,High School,18,19,23,26,87,5.0,6,75,Rural,Data Analyst,30630,0 +55104,Female,26,High School,8,82,45,91,96,3.0,5,37,Urban,ML Engineer,135105,1 +55105,Female,44,Bachelors,18,76,49,99,4,6.0,2,5,Urban,ML Engineer,25920,0 +55106,Male,58,Masters,0,48,85,9,6,0.0,2,51,Semi-Urban,Data Analyst,98391,0 +55107,Male,21,Masters,4,98,25,1,55,5.0,7,52,Urban,Software Engineer,35322,0 +55108,Male,59,Masters,15,24,34,30,76,6.0,2,2,Urban,Software Engineer,100669,0 +55109,Male,22,Bachelors,5,85,19,47,9,7.0,5,97,Urban,HR Executive,129290,1 +55110,Male,47,Diploma,11,53,21,28,69,7.0,2,27,Urban,Software Engineer,39108,0 +55111,Male,49,Bachelors,15,81,99,96,8,0.0,6,15,Semi-Urban,HR Executive,104376,1 +55112,Female,43,Bachelors,4,59,66,4,34,1.0,5,17,Rural,HR Executive,69835,0 +55113,Female,34,High School,10,8,43,51,43,9.0,0,66,Urban,ML Engineer,83379,0 +55114,Male,34,Diploma,11,59,99,51,79,0.0,3,40,Urban,HR Executive,57132,1 +55115,Female,27,Bachelors,11,45,75,57,12,2.0,1,71,Rural,Manager,147056,1 +55116,Male,33,Bachelors,7,35,88,2,47,7.0,5,87,Rural,ML Engineer,139451,0 +55117,Male,34,Diploma,7,33,26,62,7,2.0,6,41,Urban,Software Engineer,43382,0 +55118,Female,37,PhD,12,10,39,63,30,6.0,1,81,Urban,Data Analyst,147652,0 +55119,Male,53,Bachelors,12,48,51,74,58,6.0,4,67,Urban,Software Engineer,120674,1 +55120,Male,48,Bachelors,2,85,40,55,31,6.0,5,0,Urban,ML Engineer,22511,0 +55121,Male,58,High School,9,6,94,18,11,8.0,0,5,Urban,Data Analyst,42182,0 +55122,Female,55,Bachelors,18,49,75,79,65,0.0,1,20,Urban,HR Executive,52655,0 +55123,Male,53,Masters,12,52,45,61,20,3.0,4,30,Semi-Urban,HR Executive,65780,0 +55124,Male,21,Bachelors,0,56,31,85,31,1.0,6,52,Rural,ML Engineer,50367,0 +55125,Male,53,Diploma,13,11,10,43,47,0.0,3,1,Semi-Urban,Software Engineer,93936,0 +55126,Female,44,Bachelors,19,49,97,1,99,1.0,1,50,Rural,ML Engineer,34428,0 +55127,Male,35,Bachelors,4,49,67,65,83,8.0,7,34,Urban,HR Executive,143298,0 +55128,Male,35,Diploma,1,99,16,5,59,9.0,7,2,Urban,ML Engineer,108625,0 +55129,Male,25,PhD,17,87,25,16,86,6.0,2,11,Urban,ML Engineer,32419,0 +55130,Male,57,Diploma,7,50,60,52,45,5.0,4,8,Urban,Data Analyst,41693,0 +55131,Male,35,Masters,1,56,47,45,45,5.0,2,41,Semi-Urban,Manager,25077,0 +55132,Male,48,Diploma,12,47,92,8,55,2.0,4,31,Urban,HR Executive,86328,0 +55133,Other,21,Masters,14,67,43,49,45,7.0,7,23,Urban,ML Engineer,118100,0 +55134,Male,51,Bachelors,14,38,38,32,33,7.0,3,49,Urban,Data Analyst,30632,0 +55135,Male,26,PhD,3,70,50,44,40,0.0,3,99,Rural,Manager,91320,1 +55136,Other,54,High School,1,99,42,46,96,5.0,7,16,Semi-Urban,HR Executive,58977,0 +55137,Male,26,High School,6,74,16,77,30,8.0,7,75,Urban,Manager,137726,1 +55138,Female,39,Bachelors,14,54,5,48,98,6.0,2,7,Semi-Urban,ML Engineer,120142,0 +55139,Male,31,Bachelors,6,86,24,5,7,4.0,3,51,Semi-Urban,Data Analyst,73881,0 +55140,Female,45,Bachelors,17,12,48,74,14,2.0,7,91,Semi-Urban,ML Engineer,144408,0 +55141,Female,58,Diploma,4,8,64,25,4,0.0,0,33,Semi-Urban,HR Executive,113032,0 +55142,Male,57,Bachelors,16,36,15,28,21,9.0,0,33,Urban,Software Engineer,38418,0 +55143,Male,50,Bachelors,2,67,3,3,78,5.0,0,41,Semi-Urban,Manager,27292,0 +55144,Male,28,Masters,7,93,87,60,97,8.0,1,26,Urban,Software Engineer,95906,1 +55145,Other,40,Diploma,0,7,86,90,2,5.0,7,37,Urban,ML Engineer,76946,0 +55146,Male,24,Diploma,11,97,75,83,18,2.0,7,20,Urban,Data Analyst,92187,1 +55147,Other,23,High School,18,81,75,92,91,3.0,5,18,Urban,HR Executive,26278,1 +55148,Female,48,Bachelors,11,79,70,46,35,4.0,3,40,Urban,ML Engineer,105479,0 +55149,Male,22,Masters,5,81,29,55,59,9.0,7,56,Urban,HR Executive,79545,0 +55150,Female,57,Diploma,12,52,98,32,88,3.0,7,77,Urban,ML Engineer,25287,1 +55151,Male,46,Masters,16,57,98,87,57,6.0,7,78,Urban,ML Engineer,36438,1 +55152,Male,59,Bachelors,14,93,57,7,41,2.0,3,83,Semi-Urban,Data Analyst,95910,1 +55153,Male,23,Bachelors,4,72,94,61,18,4.0,2,33,Urban,Data Analyst,55038,1 +55154,Male,58,Diploma,8,13,96,95,24,8.0,1,26,Urban,Data Analyst,104069,0 +55155,Male,51,Diploma,1,73,44,83,29,6.0,5,6,Urban,ML Engineer,129644,0 +55156,Male,40,Masters,10,98,5,33,13,3.0,3,78,Urban,Manager,50299,0 +55157,Female,34,Bachelors,4,45,68,62,28,2.0,6,6,Semi-Urban,Data Analyst,131644,0 +55158,Female,25,Masters,2,19,30,9,81,4.0,6,67,Urban,Software Engineer,88541,0 +55159,Other,54,Diploma,18,23,33,85,44,8.0,2,8,Semi-Urban,Software Engineer,26542,0 +55160,Female,35,Masters,14,11,49,49,43,8.0,0,0,Urban,ML Engineer,115868,0 +55161,Female,23,Bachelors,16,77,38,78,45,6.0,2,63,Urban,Manager,107434,1 +55162,Male,26,Bachelors,10,77,84,39,86,9.0,1,45,Urban,Data Analyst,75872,1 +55163,Male,42,Masters,11,99,83,98,70,8.0,0,72,Rural,Manager,67261,1 +55164,Male,41,Bachelors,6,18,81,86,71,0.0,3,87,Semi-Urban,Manager,89594,1 +55165,Male,22,Diploma,2,97,32,78,58,6.0,5,37,Urban,Manager,145904,1 +55166,Female,25,Masters,11,99,21,39,5,6.0,5,30,Urban,HR Executive,120417,0 +55167,Female,56,Bachelors,13,2,1,8,88,5.0,6,11,Urban,ML Engineer,40993,0 +55168,Other,32,Masters,11,11,64,74,19,6.0,2,86,Semi-Urban,HR Executive,66397,0 +55169,Male,51,Bachelors,15,32,30,85,82,2.0,4,91,Urban,Manager,25130,1 +55170,Female,35,Bachelors,2,38,71,97,43,8.0,0,6,Semi-Urban,ML Engineer,117327,0 +55171,Female,21,Diploma,11,67,19,56,73,4.0,0,30,Urban,HR Executive,91496,0 +55172,Male,42,Bachelors,16,12,65,92,14,6.0,7,87,Urban,ML Engineer,107375,1 +55173,Male,48,Bachelors,1,97,69,59,52,0.0,7,25,Urban,Software Engineer,64884,1 +55174,Female,45,Bachelors,9,55,24,11,67,2.0,6,22,Rural,ML Engineer,85679,0 +55175,Male,35,Diploma,10,37,84,15,80,6.0,1,89,Urban,ML Engineer,86194,0 +55176,Female,48,Bachelors,15,43,20,97,89,4.0,7,67,Urban,Manager,116898,0 +55177,Female,24,High School,11,82,0,47,75,8.0,4,6,Urban,Manager,84681,0 +55178,Male,37,High School,13,92,66,2,90,8.0,2,17,Urban,Software Engineer,80450,0 +55179,Male,50,Bachelors,15,3,18,98,91,1.0,3,83,Semi-Urban,HR Executive,135539,0 +55180,Female,43,Diploma,12,62,95,38,8,4.0,6,13,Urban,Manager,46705,0 +55181,Female,30,Masters,11,44,88,88,79,4.0,6,14,Urban,HR Executive,22916,0 +55182,Male,35,High School,1,57,2,99,2,9.0,2,56,Semi-Urban,Data Analyst,114551,0 +55183,Male,26,Bachelors,14,9,42,62,61,7.0,0,56,Rural,Manager,38267,0 +55184,Male,51,Bachelors,12,22,28,61,8,8.0,4,13,Urban,Data Analyst,84025,0 +55185,Female,29,Masters,1,81,85,95,58,0.0,4,72,Rural,Manager,83343,1 +55186,Male,57,Bachelors,2,15,68,21,49,1.0,1,22,Semi-Urban,HR Executive,122677,0 +55187,Male,24,Bachelors,0,47,37,31,82,8.0,7,0,Urban,Manager,44465,0 +55188,Female,59,PhD,3,99,35,86,4,1.0,5,16,Rural,Software Engineer,100599,0 +55189,Male,25,High School,15,68,42,11,86,5.0,4,67,Semi-Urban,HR Executive,40413,0 +55190,Other,35,Bachelors,17,83,70,76,80,5.0,2,55,Rural,Data Analyst,93894,1 +55191,Other,51,High School,5,67,83,39,65,1.0,7,12,Urban,ML Engineer,20751,0 +55192,Male,56,Bachelors,3,32,97,86,56,6.0,1,91,Rural,ML Engineer,74070,1 +55193,Male,54,Diploma,3,9,94,24,2,7.0,7,87,Urban,Software Engineer,69374,0 +55194,Male,39,Masters,13,62,12,24,71,1.0,7,98,Rural,HR Executive,73897,0 +55195,Male,58,Bachelors,14,50,16,59,57,6.0,6,80,Urban,Software Engineer,55840,0 +55196,Female,23,Bachelors,2,61,12,65,24,4.0,0,30,Semi-Urban,Data Analyst,79006,0 +55197,Male,46,Masters,7,47,9,56,30,4.0,4,14,Semi-Urban,Software Engineer,27738,0 +55198,Male,54,Bachelors,8,25,2,61,30,1.0,0,92,Semi-Urban,ML Engineer,40957,0 +55199,Male,58,High School,8,55,77,31,37,9.0,4,69,Semi-Urban,Data Analyst,80744,0 +55200,Male,33,High School,19,97,26,40,11,3.0,2,90,Urban,Manager,69926,1 +55201,Male,22,Bachelors,13,84,72,15,60,7.0,7,14,Urban,Software Engineer,23798,0 +55202,Female,56,Masters,19,46,48,82,34,6.0,0,22,Urban,ML Engineer,73992,0 +55203,Male,34,Bachelors,8,12,24,18,84,1.0,5,4,Urban,Data Analyst,119844,0 +55204,Male,23,Diploma,4,46,84,13,16,8.0,5,36,Urban,HR Executive,40965,0 +55205,Female,59,Diploma,19,61,5,99,20,6.0,2,92,Rural,ML Engineer,112603,1 +55206,Female,27,Diploma,18,28,59,33,80,5.0,6,51,Rural,Data Analyst,25135,0 +55207,Male,55,Masters,16,55,92,6,23,3.0,4,16,Urban,Data Analyst,94692,0 +55208,Male,58,Bachelors,13,99,34,54,3,4.0,5,67,Semi-Urban,Manager,24423,1 +55209,Male,35,Masters,19,33,37,14,37,1.0,0,60,Urban,Data Analyst,37769,0 +55210,Male,26,High School,5,85,18,10,10,1.0,1,76,Urban,Software Engineer,113583,0 +55211,Female,58,Bachelors,11,83,87,18,61,8.0,0,34,Urban,ML Engineer,123689,0 +55212,Male,41,Bachelors,10,7,58,0,90,6.0,1,71,Semi-Urban,Manager,118953,0 +55213,Female,43,Diploma,8,86,28,98,21,5.0,3,31,Semi-Urban,Software Engineer,30496,1 +55214,Female,29,Masters,3,77,71,21,53,6.0,5,83,Rural,Data Analyst,38157,1 +55215,Female,49,Bachelors,13,83,99,54,91,1.0,5,50,Urban,Manager,98365,1 +55216,Male,39,Diploma,13,26,90,27,38,8.0,1,45,Urban,Manager,93921,0 +55217,Male,55,Bachelors,14,15,46,21,60,7.0,4,88,Urban,HR Executive,139565,0 +55218,Male,35,Masters,14,47,69,20,80,7.0,4,26,Semi-Urban,Data Analyst,54532,0 +55219,Female,44,High School,4,75,36,28,81,2.0,3,36,Urban,Data Analyst,57314,0 +55220,Male,39,PhD,3,20,97,93,97,8.0,4,36,Rural,Data Analyst,131497,1 +55221,Male,48,High School,7,67,28,18,0,3.0,1,1,Semi-Urban,HR Executive,66502,0 +55222,Male,32,Bachelors,10,52,3,84,79,3.0,4,57,Semi-Urban,Manager,43934,0 +55223,Male,41,Bachelors,4,67,64,67,13,0.0,1,44,Urban,Software Engineer,88793,1 +55224,Female,52,Diploma,15,81,99,96,5,6.0,7,98,Urban,Data Analyst,95388,1 +55225,Female,54,Diploma,9,10,87,15,30,4.0,1,20,Urban,Manager,23523,0 +55226,Other,47,Bachelors,19,49,48,1,82,2.0,1,64,Urban,Manager,25686,0 +55227,Female,37,High School,0,76,48,65,27,0.0,7,28,Rural,HR Executive,89073,0 +55228,Male,40,High School,0,21,57,67,70,5.0,0,62,Semi-Urban,Data Analyst,92561,0 +55229,Male,41,Diploma,10,43,83,36,38,4.0,3,65,Rural,Manager,38779,0 +55230,Male,53,High School,5,20,71,11,71,4.0,2,12,Rural,HR Executive,106727,0 +55231,Male,26,Bachelors,9,2,53,7,43,7.0,4,53,Semi-Urban,ML Engineer,142534,0 +55232,Male,46,Bachelors,12,71,98,48,12,4.0,4,12,Semi-Urban,HR Executive,133693,0 +55233,Female,53,Bachelors,2,94,29,22,66,2.0,6,71,Semi-Urban,ML Engineer,94522,0 +55234,Female,41,Masters,18,50,17,98,33,6.0,4,72,Semi-Urban,HR Executive,92599,0 +55235,Female,43,Bachelors,11,55,71,60,4,6.0,7,8,Urban,Manager,104636,0 +55236,Male,47,Bachelors,18,22,20,36,81,3.0,2,96,Urban,HR Executive,35557,0 +55237,Male,43,Masters,12,73,36,87,65,5.0,0,52,Urban,Manager,108651,1 +55238,Female,39,Diploma,0,56,75,3,88,2.0,2,49,Urban,HR Executive,140706,0 +55239,Female,23,Bachelors,13,24,24,90,94,1.0,3,8,Urban,Software Engineer,83690,0 +55240,Male,26,Bachelors,3,0,13,29,22,8.0,3,65,Rural,HR Executive,79591,0 +55241,Male,55,Masters,11,39,67,92,46,7.0,3,93,Semi-Urban,ML Engineer,137350,1 +55242,Male,47,Diploma,19,43,22,88,75,8.0,2,49,Urban,Software Engineer,71821,0 +55243,Female,31,Bachelors,9,91,31,79,26,1.0,0,93,Semi-Urban,Software Engineer,141202,1 +55244,Male,34,Diploma,10,59,93,41,15,6.0,0,76,Semi-Urban,Data Analyst,136619,1 +55245,Male,50,High School,9,66,92,96,84,2.0,1,4,Urban,Data Analyst,33434,1 +55246,Female,58,Bachelors,19,25,59,26,15,8.0,2,90,Urban,Software Engineer,132409,0 +55247,Female,54,Bachelors,17,68,87,17,66,9.0,6,35,Urban,Manager,41371,0 +55248,Male,50,Diploma,8,0,42,24,55,1.0,1,1,Semi-Urban,Manager,78637,0 +55249,Male,55,Bachelors,18,80,67,73,46,2.0,6,80,Urban,HR Executive,108371,1 +55250,Female,25,High School,14,50,44,72,89,0.0,6,81,Urban,Data Analyst,50340,1 +55251,Male,52,Bachelors,19,73,67,26,13,2.0,6,61,Urban,Data Analyst,105570,0 +55252,Male,24,Bachelors,13,15,4,1,81,1.0,2,85,Urban,Software Engineer,105744,0 +55253,Other,53,High School,14,53,32,13,17,8.0,2,89,Urban,Manager,29905,0 +55254,Female,39,Bachelors,3,94,67,3,38,9.0,1,34,Urban,Data Analyst,128143,0 +55255,Male,21,Diploma,9,24,80,9,49,3.0,1,10,Semi-Urban,ML Engineer,27154,0 +55256,Female,32,High School,7,50,71,57,77,0.0,3,80,Urban,Manager,142357,1 +55257,Male,30,Bachelors,5,89,8,28,80,6.0,7,41,Semi-Urban,Manager,100376,0 +55258,Other,52,Masters,6,7,21,83,81,1.0,3,25,Urban,ML Engineer,119217,0 +55259,Other,38,Diploma,19,25,90,34,91,8.0,3,14,Rural,Manager,22612,0 +55260,Female,46,Diploma,3,42,1,47,71,8.0,4,88,Urban,HR Executive,112839,0 +55261,Female,56,Bachelors,3,54,80,58,45,1.0,5,93,Urban,Data Analyst,63962,1 +55262,Female,59,High School,0,77,32,74,72,1.0,1,34,Urban,ML Engineer,141293,0 +55263,Female,24,Diploma,5,94,14,67,50,2.0,7,71,Urban,Software Engineer,116309,1 +55264,Male,40,Diploma,4,12,60,45,6,0.0,6,29,Urban,ML Engineer,112144,0 +55265,Male,43,Bachelors,7,52,94,39,28,6.0,1,10,Rural,Data Analyst,140871,0 +55266,Male,48,Masters,19,40,64,17,95,8.0,5,42,Urban,Software Engineer,146020,0 +55267,Male,21,High School,5,87,81,56,63,3.0,2,12,Semi-Urban,Software Engineer,140865,1 +55268,Male,30,Bachelors,13,75,98,70,2,9.0,2,10,Rural,Software Engineer,102640,1 +55269,Male,37,Masters,9,35,35,75,80,8.0,5,26,Rural,Software Engineer,134277,0 +55270,Female,59,Bachelors,11,92,25,1,36,9.0,3,48,Rural,Data Analyst,115540,0 +55271,Male,42,Bachelors,9,89,76,89,49,3.0,5,48,Rural,HR Executive,134653,1 +55272,Male,24,High School,3,49,27,45,16,4.0,2,63,Urban,Data Analyst,80376,0 +55273,Male,23,Diploma,17,85,13,52,14,5.0,3,45,Urban,Data Analyst,87535,0 +55274,Male,43,Bachelors,15,66,46,1,72,8.0,5,85,Semi-Urban,HR Executive,102816,0 +55275,Female,33,Masters,19,76,13,83,76,1.0,0,27,Urban,Manager,26612,0 +55276,Male,49,Bachelors,3,49,95,45,99,5.0,3,92,Urban,HR Executive,85502,1 +55277,Male,58,Bachelors,3,74,0,48,68,6.0,2,36,Urban,HR Executive,122505,0 +55278,Female,35,Bachelors,7,98,2,3,15,2.0,5,42,Urban,HR Executive,141857,0 +55279,Male,36,Masters,7,50,37,84,53,5.0,0,91,Urban,Data Analyst,26108,1 +55280,Male,38,Bachelors,15,95,69,45,29,9.0,7,62,Urban,Manager,39711,1 +55281,Male,39,Diploma,19,78,69,11,48,9.0,4,85,Urban,Software Engineer,33991,1 +55282,Male,36,Diploma,5,0,16,85,75,8.0,4,64,Semi-Urban,ML Engineer,61711,0 +55283,Female,37,Masters,11,75,19,80,27,8.0,3,47,Urban,HR Executive,23301,0 +55284,Male,52,PhD,6,35,60,23,16,6.0,1,85,Semi-Urban,ML Engineer,102606,0 +55285,Male,59,Diploma,9,82,98,17,97,3.0,2,95,Urban,Manager,131924,1 +55286,Male,38,Bachelors,0,79,95,31,36,2.0,0,61,Semi-Urban,ML Engineer,89940,1 +55287,Male,27,Diploma,17,70,71,66,26,0.0,3,98,Semi-Urban,ML Engineer,21680,1 +55288,Male,28,Diploma,0,90,6,46,90,7.0,5,98,Semi-Urban,Data Analyst,52018,1 +55289,Male,43,High School,2,21,19,52,26,6.0,0,9,Semi-Urban,Data Analyst,130471,0 +55290,Male,49,Masters,13,91,60,1,34,4.0,6,54,Urban,Data Analyst,64454,0 +55291,Female,42,Masters,19,66,23,71,45,7.0,3,22,Rural,Data Analyst,124250,0 +55292,Other,51,Masters,4,27,18,72,90,2.0,6,83,Urban,Data Analyst,23842,0 +55293,Male,36,Bachelors,19,72,55,33,54,5.0,6,92,Semi-Urban,ML Engineer,121219,1 +55294,Female,30,Bachelors,0,92,66,29,35,0.0,6,42,Semi-Urban,ML Engineer,49097,0 +55295,Female,26,Diploma,11,60,70,84,40,6.0,3,76,Urban,Software Engineer,72713,1 +55296,Female,50,Bachelors,14,78,71,11,34,5.0,5,92,Urban,Manager,79307,1 +55297,Male,37,Diploma,5,42,21,94,73,1.0,2,19,Urban,HR Executive,59714,0 +55298,Female,47,Diploma,18,89,8,25,26,0.0,6,69,Urban,Software Engineer,71941,0 +55299,Other,37,Masters,12,70,53,29,51,0.0,5,58,Semi-Urban,ML Engineer,66913,0 +55300,Female,28,High School,10,90,38,29,54,8.0,5,33,Urban,Data Analyst,82103,0 +55301,Female,22,Diploma,13,24,99,29,24,6.0,1,66,Urban,Data Analyst,50977,0 +55302,Male,31,Bachelors,2,60,15,78,76,0.0,4,60,Semi-Urban,Software Engineer,71085,0 +55303,Male,30,Masters,9,55,20,59,27,3.0,5,56,Rural,Software Engineer,136256,0 +55304,Female,37,Masters,17,4,23,41,66,6.0,3,31,Urban,Software Engineer,138742,0 +55305,Male,37,Bachelors,6,4,25,93,22,7.0,0,95,Urban,HR Executive,40694,0 +55306,Male,38,Bachelors,17,37,78,71,10,7.0,4,28,Urban,Software Engineer,132031,0 +55307,Male,50,PhD,1,88,67,30,21,9.0,1,66,Semi-Urban,Software Engineer,81990,1 +55308,Female,53,Bachelors,7,61,97,11,95,9.0,3,92,Semi-Urban,Data Analyst,106863,1 +55309,Male,42,High School,7,26,37,23,46,7.0,1,45,Urban,HR Executive,66117,0 +55310,Other,56,Masters,18,79,63,81,24,0.0,2,79,Semi-Urban,ML Engineer,136677,1 +55311,Female,55,Diploma,7,67,39,58,19,1.0,7,42,Urban,HR Executive,28719,0 +55312,Male,33,Diploma,12,63,78,33,21,0.0,4,52,Semi-Urban,ML Engineer,108856,0 +55313,Female,27,Bachelors,6,70,12,84,74,9.0,2,15,Urban,Data Analyst,125612,0 +55314,Male,51,Masters,0,72,45,54,35,8.0,3,41,Urban,Software Engineer,126301,0 +55315,Male,29,Bachelors,2,53,23,37,34,9.0,2,64,Semi-Urban,Software Engineer,70871,0 +55316,Female,59,Masters,10,3,34,14,4,1.0,1,90,Rural,Manager,34016,0 +55317,Male,43,Bachelors,8,82,61,7,5,4.0,7,42,Urban,HR Executive,120765,0 +55318,Male,55,High School,16,21,22,62,38,2.0,3,19,Rural,Manager,149702,0 +55319,Male,25,High School,0,56,16,8,9,3.0,4,73,Rural,HR Executive,137367,0 +55320,Female,54,Masters,7,83,6,11,64,0.0,2,64,Urban,ML Engineer,83845,0 +55321,Male,36,Masters,13,9,73,41,13,2.0,5,65,Urban,Software Engineer,64338,0 +55322,Male,34,Masters,16,38,29,85,94,6.0,5,28,Rural,ML Engineer,130537,0 +55323,Female,49,Diploma,18,63,92,12,17,8.0,7,75,Urban,HR Executive,135536,1 +55324,Male,59,Bachelors,12,38,77,73,26,6.0,5,73,Urban,Data Analyst,34826,1 +55325,Male,56,Diploma,4,62,59,82,73,3.0,6,85,Rural,Software Engineer,29692,1 +55326,Female,32,Masters,14,88,31,51,8,6.0,0,64,Rural,ML Engineer,41229,0 +55327,Female,46,Diploma,10,86,41,27,6,8.0,3,38,Urban,ML Engineer,59816,0 +55328,Female,41,Bachelors,1,12,53,47,3,9.0,6,57,Semi-Urban,Manager,34507,0 +55329,Female,31,PhD,6,4,87,92,13,8.0,2,35,Urban,Data Analyst,79775,0 +55330,Male,54,Diploma,4,3,97,44,41,2.0,3,3,Urban,Software Engineer,50603,0 +55331,Female,49,Bachelors,18,85,32,73,30,4.0,7,16,Semi-Urban,Software Engineer,93737,0 +55332,Male,39,Masters,16,56,10,57,46,2.0,3,4,Rural,Manager,67348,0 +55333,Male,38,Bachelors,10,22,46,64,52,7.0,1,9,Urban,Software Engineer,72696,0 +55334,Male,58,High School,11,5,70,8,98,0.0,6,92,Urban,ML Engineer,146351,0 +55335,Female,49,Diploma,1,82,7,87,60,5.0,2,75,Rural,Data Analyst,37009,1 +55336,Male,51,Masters,19,50,35,96,95,0.0,1,95,Urban,Software Engineer,41873,1 +55337,Male,49,Diploma,5,25,95,0,85,4.0,4,44,Rural,ML Engineer,107548,0 +55338,Male,32,Masters,16,87,59,80,26,3.0,5,59,Urban,ML Engineer,56150,1 +55339,Male,23,Bachelors,9,59,45,78,74,8.0,7,90,Rural,Data Analyst,100009,1 +55340,Female,34,Bachelors,15,0,24,93,36,5.0,6,10,Urban,ML Engineer,77063,0 +55341,Male,59,PhD,18,15,4,94,60,0.0,2,6,Semi-Urban,Manager,90764,0 +55342,Male,57,Diploma,0,4,97,27,20,1.0,1,9,Semi-Urban,HR Executive,126546,0 +55343,Female,27,Masters,4,29,62,75,53,0.0,4,1,Urban,ML Engineer,85576,0 +55344,Female,36,High School,2,73,24,31,98,8.0,7,79,Urban,Data Analyst,137800,0 +55345,Female,27,Bachelors,8,67,88,1,57,0.0,6,1,Semi-Urban,HR Executive,122552,0 +55346,Male,51,Diploma,13,4,5,83,95,3.0,6,42,Semi-Urban,Data Analyst,92517,0 +55347,Male,21,Diploma,13,60,67,7,43,9.0,5,61,Urban,HR Executive,51103,0 +55348,Female,40,Masters,6,72,6,59,22,8.0,7,28,Semi-Urban,Manager,146368,0 +55349,Female,31,Diploma,1,10,74,39,93,5.0,1,52,Semi-Urban,Manager,72716,0 +55350,Male,58,Diploma,16,96,69,48,61,2.0,0,82,Urban,Software Engineer,38259,1 +55351,Female,55,High School,8,67,48,73,43,4.0,4,91,Urban,HR Executive,118756,1 +55352,Male,32,Diploma,13,82,59,48,70,0.0,6,41,Rural,Manager,54161,0 +55353,Male,56,Bachelors,12,43,10,23,5,8.0,5,9,Rural,Manager,72895,0 +55354,Male,54,PhD,10,52,31,30,63,2.0,2,30,Urban,Manager,54660,0 +55355,Male,56,High School,2,0,57,24,58,7.0,3,68,Urban,Manager,59690,0 +55356,Male,47,High School,9,90,82,30,35,7.0,5,4,Semi-Urban,ML Engineer,50525,0 +55357,Male,56,Bachelors,11,63,40,0,20,0.0,0,32,Rural,ML Engineer,73847,0 +55358,Male,47,High School,19,74,68,72,18,0.0,5,57,Rural,HR Executive,101984,1 +55359,Female,22,Diploma,10,44,28,17,56,8.0,3,62,Semi-Urban,Manager,66556,0 +55360,Male,58,Diploma,6,98,55,2,8,3.0,5,90,Urban,Manager,38515,1 +55361,Male,35,Bachelors,5,77,93,79,35,4.0,3,39,Urban,Manager,120073,1 +55362,Other,24,Masters,17,26,64,76,39,6.0,0,28,Urban,Manager,145454,0 +55363,Male,55,Masters,4,97,32,79,24,8.0,1,31,Urban,Software Engineer,39178,1 +55364,Male,47,Masters,17,50,24,58,59,4.0,6,35,Semi-Urban,Software Engineer,147257,0 +55365,Female,46,Diploma,5,34,57,54,15,6.0,2,92,Urban,Manager,132167,0 +55366,Male,41,Bachelors,14,28,75,1,85,8.0,1,59,Urban,ML Engineer,107438,0 +55367,Male,57,Bachelors,15,41,87,80,52,8.0,4,93,Urban,HR Executive,59746,1 +55368,Male,27,Bachelors,5,78,79,82,44,9.0,1,41,Urban,Manager,135443,1 +55369,Female,47,Bachelors,1,5,21,88,70,6.0,4,29,Semi-Urban,ML Engineer,50989,0 +55370,Female,51,Bachelors,5,43,41,18,3,4.0,4,64,Urban,Manager,70151,0 +55371,Male,50,Diploma,11,36,28,43,48,1.0,2,36,Urban,ML Engineer,101099,0 +55372,Male,41,Masters,8,50,68,92,4,1.0,3,61,Semi-Urban,Software Engineer,50646,1 +55373,Male,53,Masters,9,89,38,81,17,6.0,3,58,Rural,Data Analyst,53888,1 +55374,Male,42,Bachelors,0,16,17,33,34,8.0,0,28,Semi-Urban,HR Executive,90252,0 +55375,Male,34,Bachelors,4,0,47,14,70,7.0,0,83,Urban,Data Analyst,66443,0 +55376,Female,24,Bachelors,7,5,58,76,93,2.0,6,13,Urban,ML Engineer,115403,0 +55377,Other,24,Bachelors,8,34,3,5,91,7.0,1,28,Urban,Software Engineer,57866,0 +55378,Female,58,High School,13,67,7,80,88,9.0,1,22,Urban,Software Engineer,82163,0 +55379,Other,49,Bachelors,15,60,70,96,97,4.0,0,6,Urban,Data Analyst,53976,0 +55380,Male,35,High School,10,26,31,62,41,8.0,6,42,Semi-Urban,ML Engineer,23423,0 +55381,Female,44,Masters,13,44,45,53,37,9.0,0,6,Semi-Urban,Manager,71314,0 +55382,Female,43,Diploma,18,59,63,38,2,6.0,6,41,Urban,Data Analyst,78718,0 +55383,Male,54,Bachelors,10,23,63,21,62,5.0,0,20,Rural,HR Executive,142990,0 +55384,Male,31,Bachelors,6,58,26,41,82,2.0,7,93,Urban,Data Analyst,115354,0 +55385,Male,40,Masters,4,68,68,9,48,6.0,0,96,Semi-Urban,Manager,79120,1 +55386,Female,32,Masters,6,74,14,90,19,8.0,6,86,Urban,Software Engineer,24165,1 +55387,Female,49,Bachelors,18,77,47,11,83,5.0,5,80,Urban,HR Executive,115962,0 +55388,Female,29,Bachelors,18,27,2,27,74,1.0,2,5,Urban,Manager,110316,0 +55389,Female,50,High School,17,27,42,30,41,8.0,6,40,Urban,HR Executive,131370,0 +55390,Male,34,Bachelors,14,72,32,81,14,0.0,0,24,Rural,Software Engineer,95832,0 +55391,Female,58,PhD,1,99,46,39,10,2.0,5,31,Urban,ML Engineer,32916,0 +55392,Female,23,Bachelors,18,64,10,97,68,6.0,6,16,Urban,Manager,29695,0 +55393,Male,26,High School,4,70,14,3,70,2.0,6,86,Urban,Manager,38232,0 +55394,Other,56,Masters,14,29,44,24,87,7.0,0,93,Rural,Software Engineer,30871,0 +55395,Male,29,Bachelors,10,58,40,53,57,5.0,4,76,Urban,HR Executive,71658,0 +55396,Female,24,Bachelors,0,9,54,64,97,5.0,5,31,Urban,Data Analyst,115725,0 +55397,Male,38,Diploma,18,92,12,6,10,4.0,5,14,Urban,HR Executive,122516,0 +55398,Female,23,Diploma,2,94,89,73,46,4.0,7,73,Semi-Urban,Data Analyst,46263,1 +55399,Male,50,Masters,17,24,3,16,28,3.0,2,15,Semi-Urban,HR Executive,60729,0 +55400,Male,31,High School,18,88,80,49,77,3.0,2,81,Rural,HR Executive,69430,1 +55401,Male,36,Bachelors,8,39,90,77,96,8.0,2,84,Urban,ML Engineer,103131,1 +55402,Male,46,Bachelors,1,54,93,12,68,5.0,7,79,Semi-Urban,Manager,85710,1 +55403,Male,41,Masters,15,62,1,68,72,8.0,4,63,Semi-Urban,ML Engineer,116461,0 +55404,Male,43,Diploma,5,24,91,78,57,3.0,1,93,Urban,ML Engineer,46856,1 +55405,Female,23,Bachelors,0,95,59,43,95,7.0,2,19,Semi-Urban,HR Executive,84934,0 +55406,Male,48,High School,10,90,34,31,88,3.0,5,58,Urban,ML Engineer,126218,0 +55407,Male,57,High School,9,10,16,29,96,7.0,4,14,Semi-Urban,Software Engineer,91969,0 +55408,Female,39,Diploma,8,44,69,74,15,4.0,2,39,Urban,Manager,130174,0 +55409,Female,46,Diploma,0,36,82,20,96,1.0,3,84,Rural,Data Analyst,148868,0 +55410,Male,22,Bachelors,3,3,19,67,49,8.0,2,61,Urban,Software Engineer,36724,0 +55411,Male,24,Masters,10,81,59,47,9,6.0,6,14,Urban,Data Analyst,85434,0 +55412,Male,25,Bachelors,19,55,81,31,74,3.0,6,41,Semi-Urban,Manager,56265,0 +55413,Male,38,High School,17,87,47,83,96,7.0,4,12,Semi-Urban,Software Engineer,105334,0 +55414,Male,45,Masters,5,53,56,29,86,2.0,6,46,Semi-Urban,HR Executive,117279,0 +55415,Female,22,High School,6,94,13,54,75,4.0,1,79,Rural,Data Analyst,28276,0 +55416,Male,32,Masters,6,55,31,93,17,9.0,5,53,Rural,HR Executive,67967,0 +55417,Male,23,Bachelors,5,70,25,58,77,2.0,7,89,Urban,HR Executive,127784,1 +55418,Male,43,Diploma,9,45,29,41,1,4.0,2,13,Semi-Urban,Data Analyst,74056,0 +55419,Male,30,Masters,14,29,17,97,92,3.0,4,1,Urban,Software Engineer,51860,0 +55420,Female,47,Bachelors,5,43,67,66,28,4.0,6,80,Semi-Urban,Software Engineer,139523,1 +55421,Other,23,Bachelors,2,40,18,98,36,6.0,3,32,Urban,Manager,23853,0 +55422,Female,57,PhD,4,62,3,52,27,6.0,3,53,Rural,HR Executive,65407,0 +55423,Male,56,Bachelors,5,47,89,86,63,6.0,1,80,Rural,Manager,91577,1 +55424,Female,38,Bachelors,1,46,70,40,81,9.0,3,73,Rural,Manager,45482,0 +55425,Female,33,Bachelors,11,30,78,4,41,4.0,5,39,Semi-Urban,ML Engineer,131804,0 +55426,Male,57,Bachelors,16,57,55,45,33,7.0,4,3,Semi-Urban,Manager,36755,0 +55427,Female,21,Bachelors,1,34,95,49,76,1.0,3,8,Rural,Software Engineer,68812,0 +55428,Male,34,Masters,13,7,25,75,38,6.0,3,79,Urban,Manager,50071,0 +55429,Other,40,Bachelors,14,68,57,40,68,5.0,4,78,Urban,Software Engineer,65345,1 +55430,Male,37,PhD,5,70,93,73,29,6.0,0,89,Semi-Urban,Manager,23440,1 +55431,Male,25,Bachelors,2,2,78,73,24,4.0,6,69,Semi-Urban,Data Analyst,70517,0 +55432,Male,41,High School,16,11,54,21,62,0.0,6,32,Rural,Software Engineer,34847,0 +55433,Female,53,Diploma,12,21,68,44,30,6.0,4,73,Urban,Software Engineer,84971,0 +55434,Male,28,Bachelors,5,38,77,15,28,2.0,1,29,Urban,ML Engineer,134993,0 +55435,Male,22,High School,5,7,87,62,38,7.0,3,25,Urban,Data Analyst,54337,0 +55436,Female,58,Masters,12,47,44,16,38,4.0,3,70,Urban,Data Analyst,55683,0 +55437,Female,53,Bachelors,13,64,67,90,57,0.0,7,81,Urban,Manager,127507,1 +55438,Male,36,High School,13,18,28,89,97,0.0,7,31,Urban,Software Engineer,94945,0 +55439,Male,31,Bachelors,0,37,32,60,63,1.0,0,63,Urban,HR Executive,55591,0 +55440,Female,23,Masters,7,88,9,13,48,4.0,0,26,Rural,Software Engineer,144148,0 +55441,Female,22,Diploma,7,61,98,95,10,5.0,6,15,Semi-Urban,Manager,93145,1 +55442,Female,50,Masters,12,84,15,18,5,9.0,1,57,Urban,Data Analyst,71304,0 +55443,Female,27,Diploma,15,72,66,19,17,7.0,6,28,Urban,Software Engineer,21259,0 +55444,Male,46,PhD,14,96,60,42,18,3.0,7,57,Urban,Manager,118140,1 +55445,Female,24,Diploma,16,1,98,58,15,6.0,0,32,Rural,ML Engineer,123586,0 +55446,Male,23,Bachelors,19,92,22,65,52,8.0,2,52,Semi-Urban,ML Engineer,113148,0 +55447,Male,25,Masters,16,74,51,55,75,5.0,0,88,Urban,ML Engineer,145597,1 +55448,Male,47,Masters,17,60,87,84,13,7.0,0,75,Urban,HR Executive,68563,1 +55449,Female,27,Bachelors,19,41,56,85,17,4.0,5,68,Urban,Data Analyst,76391,1 +55450,Male,32,Bachelors,4,51,25,33,50,6.0,3,7,Semi-Urban,HR Executive,43042,0 +55451,Female,51,Diploma,12,44,19,48,86,4.0,3,94,Urban,Data Analyst,20252,0 +55452,Male,25,Bachelors,3,63,50,38,62,6.0,3,51,Urban,Data Analyst,21766,0 +55453,Female,33,Diploma,8,1,97,51,73,7.0,6,2,Urban,HR Executive,90736,0 +55454,Male,57,High School,9,54,31,67,28,7.0,5,21,Rural,Data Analyst,36590,0 +55455,Female,43,Masters,7,96,44,53,93,3.0,6,34,Rural,ML Engineer,50005,0 +55456,Female,29,Diploma,4,52,67,89,32,7.0,0,13,Urban,Software Engineer,72448,0 +55457,Male,30,Bachelors,15,88,68,47,18,9.0,6,31,Semi-Urban,Manager,149596,0 +55458,Female,32,Masters,17,55,88,44,19,3.0,5,35,Rural,Data Analyst,49140,0 +55459,Female,43,Diploma,15,73,50,10,2,1.0,2,30,Semi-Urban,HR Executive,92659,0 +55460,Male,26,Bachelors,15,85,89,18,72,4.0,4,20,Urban,Manager,131601,0 +55461,Male,25,PhD,4,61,31,4,94,5.0,7,94,Urban,Data Analyst,75278,0 +55462,Female,25,Bachelors,18,91,5,38,72,1.0,4,26,Urban,ML Engineer,104749,0 +55463,Male,26,Bachelors,10,53,45,19,7,0.0,5,37,Urban,Data Analyst,39300,0 +55464,Male,50,High School,7,27,24,6,74,3.0,1,39,Semi-Urban,HR Executive,123703,0 +55465,Female,29,Diploma,16,90,80,23,33,7.0,7,29,Semi-Urban,Software Engineer,139814,0 +55466,Male,59,Diploma,16,7,50,75,7,0.0,2,17,Urban,HR Executive,89470,0 +55467,Female,45,Bachelors,2,20,11,58,40,1.0,0,30,Semi-Urban,Software Engineer,72489,0 +55468,Male,27,Bachelors,2,88,80,28,92,6.0,6,84,Urban,HR Executive,22049,1 +55469,Male,43,Diploma,9,75,0,72,69,1.0,6,3,Urban,ML Engineer,130236,0 +55470,Female,49,Bachelors,7,49,96,74,22,6.0,1,28,Rural,HR Executive,78037,1 +55471,Female,51,Masters,11,85,18,65,21,8.0,5,12,Urban,Data Analyst,107344,0 +55472,Male,56,Diploma,7,23,38,85,34,4.0,1,5,Semi-Urban,Data Analyst,130663,0 +55473,Male,48,Bachelors,11,57,6,76,57,6.0,0,38,Rural,ML Engineer,124755,0 +55474,Male,28,Bachelors,13,2,76,35,49,2.0,3,49,Urban,Data Analyst,28887,0 +55475,Other,54,High School,15,94,67,27,31,1.0,7,75,Urban,ML Engineer,113991,1 +55476,Male,59,Bachelors,8,52,27,71,70,7.0,4,19,Semi-Urban,Software Engineer,69726,0 +55477,Male,42,Bachelors,1,34,50,28,30,3.0,3,2,Urban,Data Analyst,72589,0 +55478,Other,49,Diploma,19,57,37,99,88,4.0,0,8,Rural,Software Engineer,74119,0 +55479,Female,44,Bachelors,12,35,77,21,23,2.0,7,92,Urban,Data Analyst,77803,0 +55480,Female,44,Bachelors,19,47,2,60,23,3.0,6,23,Semi-Urban,Manager,148825,0 +55481,Male,43,Masters,1,79,38,42,66,1.0,1,35,Urban,Manager,134013,0 +55482,Male,33,Masters,6,59,59,13,5,8.0,5,25,Semi-Urban,Software Engineer,98142,0 +55483,Male,50,Diploma,16,15,68,11,15,0.0,2,89,Semi-Urban,Software Engineer,84216,0 +55484,Female,25,High School,9,57,24,13,98,0.0,6,78,Urban,ML Engineer,91462,0 +55485,Male,38,High School,16,29,64,54,57,3.0,1,96,Semi-Urban,HR Executive,123899,1 +55486,Male,26,Masters,8,57,47,51,97,5.0,5,71,Rural,Data Analyst,130839,0 +55487,Male,59,Diploma,0,12,60,91,63,3.0,4,40,Rural,Software Engineer,61257,0 +55488,Female,41,Diploma,18,79,13,33,73,9.0,3,34,Rural,HR Executive,103286,0 +55489,Female,27,Masters,15,38,26,86,89,0.0,3,96,Urban,ML Engineer,54516,1 +55490,Female,32,High School,10,44,32,49,63,2.0,4,82,Urban,ML Engineer,100918,0 +55491,Male,38,Masters,13,59,62,78,75,6.0,2,31,Urban,Software Engineer,56781,0 +55492,Female,46,High School,11,90,82,9,4,0.0,0,54,Urban,Data Analyst,115402,0 +55493,Male,58,Masters,4,10,73,52,64,1.0,5,22,Semi-Urban,Data Analyst,24000,0 +55494,Male,23,Bachelors,15,74,1,68,93,1.0,4,92,Urban,Manager,115778,1 +55495,Female,36,Diploma,7,13,46,41,63,0.0,7,41,Urban,HR Executive,84408,0 +55496,Male,53,High School,0,79,67,64,52,0.0,6,53,Rural,Data Analyst,144205,1 +55497,Male,48,Bachelors,9,79,29,59,70,2.0,1,58,Rural,Software Engineer,96076,0 +55498,Female,38,Bachelors,9,26,29,82,0,9.0,6,62,Rural,Software Engineer,108979,0 +55499,Male,52,Bachelors,7,0,95,98,96,9.0,4,11,Semi-Urban,ML Engineer,99132,0 +55500,Male,56,High School,0,85,99,55,53,2.0,1,24,Semi-Urban,HR Executive,106174,1 +55501,Other,21,Bachelors,7,93,87,7,14,2.0,3,12,Urban,Manager,26894,0 +55502,Male,36,Bachelors,19,22,55,72,79,2.0,0,1,Urban,Manager,60263,0 +55503,Male,38,Bachelors,8,51,54,64,74,9.0,3,25,Rural,ML Engineer,131911,0 +55504,Female,26,Bachelors,9,82,16,37,75,2.0,6,54,Semi-Urban,Software Engineer,41971,0 +55505,Male,37,Bachelors,19,77,96,31,44,3.0,6,56,Semi-Urban,ML Engineer,40868,1 +55506,Male,29,High School,11,78,74,9,72,8.0,0,53,Urban,Data Analyst,76788,0 +55507,Male,43,Bachelors,13,0,81,56,10,1.0,1,43,Urban,HR Executive,74767,0 +55508,Male,33,Bachelors,10,18,96,95,38,9.0,6,29,Semi-Urban,HR Executive,101282,1 +55509,Female,24,Bachelors,12,20,41,18,12,3.0,4,31,Urban,HR Executive,56101,0 +55510,Female,21,Diploma,17,21,7,18,80,9.0,3,77,Semi-Urban,ML Engineer,24875,0 +55511,Male,29,Diploma,12,31,47,33,57,0.0,4,94,Urban,ML Engineer,130808,0 +55512,Male,21,High School,7,36,0,36,93,1.0,0,56,Urban,Data Analyst,56279,0 +55513,Male,37,Bachelors,1,26,26,55,46,4.0,0,53,Semi-Urban,HR Executive,96648,0 +55514,Male,40,Bachelors,0,89,36,76,28,0.0,7,57,Semi-Urban,Manager,49602,1 +55515,Female,31,Diploma,18,0,82,77,12,0.0,6,25,Semi-Urban,ML Engineer,143336,0 +55516,Male,44,Diploma,10,5,2,50,73,0.0,4,43,Rural,HR Executive,137466,0 +55517,Female,21,Bachelors,8,56,74,47,47,0.0,3,42,Urban,HR Executive,115497,0 +55518,Male,30,Bachelors,10,62,68,0,41,5.0,1,60,Semi-Urban,HR Executive,81757,0 +55519,Female,34,Bachelors,5,80,49,48,65,9.0,4,47,Urban,Data Analyst,46980,0 +55520,Male,59,Bachelors,14,78,11,68,89,5.0,0,64,Urban,ML Engineer,105876,0 +55521,Female,48,High School,4,46,0,90,84,9.0,3,60,Rural,Software Engineer,20559,0 +55522,Female,39,Bachelors,19,93,63,20,87,1.0,5,67,Urban,Software Engineer,137483,1 +55523,Male,43,Bachelors,11,84,55,8,40,4.0,5,62,Urban,Data Analyst,85999,0 +55524,Female,53,Masters,9,91,38,49,93,1.0,3,72,Semi-Urban,Software Engineer,66320,1 +55525,Female,31,Bachelors,9,86,84,29,17,6.0,4,93,Rural,ML Engineer,118657,1 +55526,Male,37,Masters,3,6,62,16,11,8.0,2,12,Urban,Data Analyst,72209,0 +55527,Male,35,High School,17,44,30,74,61,4.0,3,14,Urban,Data Analyst,98586,0 +55528,Male,22,Masters,7,19,58,97,58,3.0,1,95,Semi-Urban,HR Executive,44019,1 +55529,Male,41,Bachelors,12,56,68,93,12,9.0,5,81,Rural,Software Engineer,28393,1 +55530,Male,38,Bachelors,19,16,16,94,75,2.0,0,85,Semi-Urban,HR Executive,97099,0 +55531,Male,48,Diploma,3,0,20,21,43,8.0,3,57,Urban,ML Engineer,149623,0 +55532,Female,21,Masters,2,45,48,76,37,2.0,1,89,Urban,HR Executive,45754,1 +55533,Female,54,PhD,3,23,4,67,7,0.0,6,41,Rural,Manager,89035,0 +55534,Male,52,Masters,15,96,39,11,45,4.0,6,90,Urban,Data Analyst,87811,1 +55535,Male,53,High School,18,9,37,76,57,7.0,6,66,Urban,Manager,149484,0 +55536,Female,31,Bachelors,13,2,82,43,24,5.0,0,98,Rural,HR Executive,21017,0 +55537,Male,46,Diploma,18,4,81,65,81,1.0,5,56,Urban,Software Engineer,100968,0 +55538,Female,48,Bachelors,0,66,39,7,99,4.0,3,46,Urban,HR Executive,58353,0 +55539,Male,22,Diploma,4,65,50,88,5,4.0,1,71,Urban,ML Engineer,98246,1 +55540,Female,49,Diploma,17,60,47,19,63,8.0,7,67,Semi-Urban,Data Analyst,94451,0 +55541,Male,37,Bachelors,8,17,34,0,70,5.0,6,37,Urban,Data Analyst,126195,0 +55542,Female,30,Masters,10,12,97,17,16,7.0,3,94,Semi-Urban,Manager,123680,0 +55543,Male,58,Masters,12,87,48,94,85,9.0,5,99,Rural,Manager,48119,1 +55544,Male,41,Bachelors,6,69,15,31,49,1.0,6,18,Urban,HR Executive,122701,0 +55545,Male,40,Diploma,3,19,86,89,30,9.0,7,53,Semi-Urban,Data Analyst,46925,1 +55546,Male,44,High School,0,47,72,51,40,1.0,0,20,Urban,Manager,128317,0 +55547,Male,26,Diploma,11,31,97,30,69,7.0,6,95,Urban,HR Executive,112103,1 +55548,Male,25,Diploma,0,44,1,31,20,7.0,5,57,Urban,Manager,101418,0 +55549,Male,31,Bachelors,2,27,40,75,41,6.0,6,52,Urban,HR Executive,138277,0 +55550,Female,30,PhD,10,55,71,69,32,2.0,7,69,Urban,Software Engineer,63263,1 +55551,Male,50,Masters,8,38,33,67,42,8.0,7,29,Rural,Data Analyst,66742,0 +55552,Other,45,Diploma,17,41,19,57,37,9.0,6,87,Rural,HR Executive,128929,0 +55553,Male,41,Masters,18,96,7,57,83,2.0,3,15,Urban,HR Executive,63637,0 +55554,Male,48,Bachelors,15,11,82,43,79,1.0,6,99,Urban,Software Engineer,22125,1 +55555,Female,21,High School,17,10,80,62,32,0.0,6,27,Urban,Data Analyst,69829,0 +55556,Male,54,Diploma,9,79,14,70,13,1.0,1,89,Urban,Software Engineer,62466,1 +55557,Female,21,Bachelors,0,12,15,43,57,6.0,3,56,Urban,ML Engineer,93693,0 +55558,Female,33,Bachelors,5,5,0,99,41,8.0,6,98,Urban,Manager,95690,0 +55559,Male,27,Masters,6,48,59,62,36,8.0,6,62,Semi-Urban,Manager,39704,0 +55560,Male,46,Masters,4,50,20,61,33,1.0,4,18,Urban,ML Engineer,29064,0 +55561,Female,31,Diploma,13,54,23,93,75,0.0,1,44,Semi-Urban,HR Executive,125774,0 +55562,Female,32,Diploma,5,87,62,2,49,2.0,7,31,Semi-Urban,Data Analyst,114316,0 +55563,Male,33,Bachelors,19,62,68,89,54,4.0,6,24,Urban,Data Analyst,93121,1 +55564,Male,52,Diploma,16,30,58,56,14,0.0,7,3,Urban,Manager,72415,0 +55565,Other,34,Bachelors,9,72,91,8,56,0.0,3,47,Urban,ML Engineer,134066,0 +55566,Male,54,Bachelors,7,84,37,89,25,6.0,1,1,Urban,Data Analyst,48745,0 +55567,Male,33,Bachelors,0,31,17,57,8,9.0,5,88,Urban,ML Engineer,146543,0 +55568,Other,28,Bachelors,19,35,25,76,72,1.0,6,82,Urban,Data Analyst,99231,0 +55569,Female,50,Diploma,15,38,43,0,33,1.0,2,67,Urban,HR Executive,122743,0 +55570,Male,38,Bachelors,0,19,75,16,74,1.0,6,25,Urban,ML Engineer,146415,0 +55571,Male,47,PhD,19,55,0,59,95,9.0,4,8,Semi-Urban,Manager,53217,0 +55572,Female,31,Masters,6,7,66,4,92,9.0,7,65,Semi-Urban,Software Engineer,22035,0 +55573,Male,39,Diploma,2,23,32,93,35,0.0,3,68,Urban,HR Executive,47915,0 +55574,Male,34,Bachelors,3,86,24,4,64,7.0,6,11,Semi-Urban,Manager,117663,0 +55575,Other,31,Diploma,8,12,17,95,18,4.0,1,14,Urban,Manager,28058,0 +55576,Male,21,Bachelors,4,83,35,78,90,1.0,7,96,Urban,Software Engineer,27924,1 +55577,Female,57,High School,9,6,78,62,87,0.0,2,83,Semi-Urban,HR Executive,45122,0 +55578,Female,25,Bachelors,15,44,4,81,0,6.0,2,50,Urban,Software Engineer,85470,0 +55579,Female,30,Bachelors,13,72,36,23,53,6.0,1,32,Urban,Manager,38130,0 +55580,Female,32,Bachelors,1,56,97,13,36,4.0,7,30,Urban,HR Executive,133727,0 +55581,Male,57,Bachelors,14,86,8,81,79,4.0,0,99,Rural,ML Engineer,93561,1 +55582,Female,23,Bachelors,9,24,71,14,43,3.0,4,85,Urban,Data Analyst,28119,0 +55583,Female,48,Masters,8,75,80,67,3,6.0,2,40,Semi-Urban,HR Executive,30253,1 +55584,Female,23,Bachelors,2,84,78,0,49,1.0,3,53,Urban,Data Analyst,148133,0 +55585,Female,51,Bachelors,8,38,41,98,63,9.0,7,67,Rural,HR Executive,68455,1 +55586,Female,26,Masters,0,26,86,42,36,2.0,5,82,Semi-Urban,Data Analyst,40450,0 +55587,Male,40,Bachelors,15,47,56,53,68,6.0,4,90,Rural,Manager,29848,1 +55588,Male,58,Bachelors,3,87,59,15,28,3.0,5,80,Semi-Urban,Manager,37889,1 +55589,Male,35,High School,10,37,28,3,77,3.0,0,59,Urban,Data Analyst,39250,0 +55590,Male,57,High School,16,97,41,33,6,2.0,2,23,Semi-Urban,HR Executive,79406,0 +55591,Male,27,Bachelors,3,59,51,0,25,9.0,0,38,Urban,ML Engineer,48840,0 +55592,Male,26,Bachelors,13,31,44,87,31,2.0,3,65,Urban,Data Analyst,136121,0 +55593,Other,24,Bachelors,8,73,27,50,16,8.0,3,27,Rural,HR Executive,91384,0 +55594,Male,47,Bachelors,14,92,68,61,12,1.0,6,58,Urban,Data Analyst,67127,1 +55595,Male,54,Diploma,19,37,42,43,85,3.0,4,24,Rural,Data Analyst,54447,0 +55596,Female,57,Bachelors,13,23,45,47,6,3.0,4,77,Rural,Data Analyst,25117,0 +55597,Male,53,Bachelors,4,12,23,69,43,8.0,4,26,Rural,Manager,69634,0 +55598,Male,45,High School,8,0,87,90,99,0.0,1,51,Urban,Manager,122666,0 +55599,Male,37,Masters,12,37,30,74,31,2.0,6,22,Urban,HR Executive,62987,0 +55600,Male,40,Diploma,4,97,5,46,72,4.0,5,53,Semi-Urban,Data Analyst,60172,0 +55601,Other,21,Bachelors,17,88,88,54,93,3.0,1,5,Urban,Manager,75626,0 +55602,Female,28,Masters,17,74,9,88,39,4.0,0,78,Urban,HR Executive,56402,1 +55603,Female,23,Masters,9,62,84,14,10,7.0,2,28,Urban,Data Analyst,47667,0 +55604,Female,54,Masters,19,32,26,23,6,2.0,7,57,Urban,Manager,32617,0 +55605,Male,54,Masters,18,4,2,4,39,9.0,5,48,Urban,Software Engineer,70868,0 +55606,Female,35,Diploma,4,64,35,18,29,1.0,3,68,Urban,HR Executive,123369,0 +55607,Female,23,Masters,13,76,54,1,92,3.0,4,26,Urban,ML Engineer,141874,0 +55608,Female,56,Masters,12,84,65,20,95,9.0,2,50,Rural,Data Analyst,31365,0 +55609,Male,34,Masters,5,31,70,81,5,9.0,6,10,Urban,Data Analyst,35518,0 +55610,Male,26,Bachelors,12,26,69,25,79,9.0,6,48,Urban,HR Executive,135684,0 +55611,Male,21,High School,6,5,44,33,24,1.0,1,9,Semi-Urban,HR Executive,113516,0 +55612,Male,41,Diploma,2,69,79,82,78,2.0,0,12,Urban,Data Analyst,49374,1 +55613,Female,36,Bachelors,1,33,21,59,73,8.0,1,30,Rural,ML Engineer,141839,0 +55614,Male,55,Bachelors,3,40,63,13,90,3.0,7,19,Rural,Data Analyst,82121,0 +55615,Male,52,Bachelors,4,20,35,94,10,1.0,2,45,Urban,HR Executive,127987,0 +55616,Female,51,PhD,14,58,32,83,58,7.0,0,33,Urban,ML Engineer,50819,0 +55617,Male,30,High School,2,47,87,98,39,5.0,4,38,Urban,ML Engineer,51437,1 +55618,Male,24,PhD,13,69,69,69,29,7.0,0,81,Urban,Software Engineer,89775,1 +55619,Other,53,High School,10,41,5,61,85,7.0,0,35,Urban,Data Analyst,139554,0 +55620,Female,41,Masters,5,30,61,98,96,8.0,5,18,Urban,Manager,39370,0 +55621,Female,42,Diploma,1,19,6,66,36,8.0,6,58,Semi-Urban,Data Analyst,43475,0 +55622,Female,59,Bachelors,13,33,42,12,74,2.0,4,20,Urban,Data Analyst,66978,0 +55623,Male,51,Bachelors,3,2,49,54,88,8.0,4,88,Semi-Urban,Manager,109930,0 +55624,Male,22,Diploma,5,65,31,90,82,0.0,7,60,Semi-Urban,Data Analyst,132461,1 +55625,Male,59,Masters,19,11,24,0,62,2.0,3,69,Urban,Software Engineer,70484,0 +55626,Male,53,Bachelors,17,6,99,63,5,2.0,0,91,Urban,ML Engineer,101991,1 +55627,Male,46,PhD,6,27,71,97,40,1.0,1,44,Rural,Manager,43823,1 +55628,Male,30,High School,14,65,51,32,5,7.0,1,45,Urban,Data Analyst,77301,0 +55629,Male,40,PhD,16,82,85,20,23,5.0,5,38,Rural,HR Executive,142196,0 +55630,Female,35,Bachelors,14,52,84,38,71,6.0,1,10,Semi-Urban,Software Engineer,93494,0 +55631,Male,45,Bachelors,15,16,42,3,63,4.0,2,33,Semi-Urban,ML Engineer,123117,0 +55632,Other,50,Bachelors,18,35,5,85,74,4.0,0,13,Urban,Data Analyst,76200,0 +55633,Male,23,PhD,19,42,99,61,36,7.0,2,46,Rural,HR Executive,31662,1 +55634,Female,43,Bachelors,17,84,39,32,96,6.0,6,13,Semi-Urban,Data Analyst,100095,0 +55635,Female,29,Masters,6,32,71,4,1,5.0,6,60,Urban,ML Engineer,46089,0 +55636,Female,40,Bachelors,4,64,0,29,48,0.0,3,21,Urban,HR Executive,144566,0 +55637,Male,47,Diploma,18,64,34,39,3,8.0,6,72,Rural,ML Engineer,41199,0 +55638,Male,54,Bachelors,5,80,94,28,52,3.0,7,62,Urban,HR Executive,122778,1 +55639,Male,34,Masters,12,72,20,20,73,4.0,2,20,Semi-Urban,Data Analyst,148554,0 +55640,Female,38,Masters,13,91,56,86,95,2.0,6,6,Urban,HR Executive,62623,0 +55641,Male,48,Masters,6,66,56,58,83,8.0,4,65,Urban,ML Engineer,30258,1 +55642,Male,56,Diploma,0,17,39,76,49,8.0,4,35,Semi-Urban,Data Analyst,107750,0 +55643,Male,47,Diploma,0,86,96,47,18,3.0,1,57,Rural,Data Analyst,35253,1 +55644,Male,27,Diploma,8,66,90,83,88,2.0,3,0,Urban,Manager,57500,1 +55645,Male,55,Diploma,12,90,9,31,42,5.0,7,9,Urban,HR Executive,121433,0 +55646,Female,57,Bachelors,1,11,56,46,0,4.0,3,15,Urban,Software Engineer,92421,0 +55647,Female,36,Bachelors,3,60,24,1,12,0.0,0,55,Rural,Software Engineer,38920,0 +55648,Male,32,Bachelors,12,82,91,3,86,5.0,2,54,Urban,Manager,129411,0 +55649,Female,37,High School,11,36,14,96,92,3.0,7,20,Rural,Data Analyst,64356,0 +55650,Male,54,Bachelors,16,58,94,7,72,4.0,6,81,Rural,Data Analyst,24990,1 +55651,Female,24,Bachelors,11,61,89,86,36,6.0,0,82,Semi-Urban,Software Engineer,90239,1 +55652,Male,26,Bachelors,0,55,55,54,24,9.0,3,20,Semi-Urban,ML Engineer,83965,0 +55653,Female,37,High School,12,11,61,36,8,2.0,4,6,Urban,Manager,41033,0 +55654,Male,41,Diploma,11,76,57,64,22,9.0,1,91,Semi-Urban,Data Analyst,149281,1 +55655,Male,54,Masters,17,59,2,39,10,8.0,0,3,Urban,Manager,106358,0 +55656,Male,22,Bachelors,14,12,2,84,82,5.0,3,93,Urban,HR Executive,90781,0 +55657,Male,51,Bachelors,1,72,96,22,90,5.0,3,62,Urban,Software Engineer,105765,1 +55658,Male,40,Masters,10,60,92,76,62,0.0,7,99,Rural,ML Engineer,119169,1 +55659,Other,49,High School,7,60,95,41,34,2.0,5,9,Urban,Data Analyst,47324,0 +55660,Male,50,Bachelors,2,24,19,45,86,2.0,6,98,Urban,ML Engineer,29159,0 +55661,Male,29,Bachelors,2,65,48,21,9,1.0,3,89,Urban,Data Analyst,61080,0 +55662,Female,35,Bachelors,5,22,65,22,52,9.0,1,64,Urban,ML Engineer,69099,0 +55663,Male,43,Masters,6,24,75,16,20,9.0,7,47,Urban,HR Executive,25381,0 +55664,Male,55,Bachelors,3,32,48,8,90,7.0,4,31,Urban,Software Engineer,116945,0 +55665,Male,45,Diploma,6,82,69,53,24,6.0,1,4,Urban,Data Analyst,84444,0 +55666,Female,52,Masters,19,94,50,14,58,7.0,0,49,Semi-Urban,Manager,74495,0 +55667,Female,39,Masters,2,31,13,20,91,1.0,0,53,Urban,Manager,26875,0 +55668,Female,56,Masters,8,66,40,31,59,8.0,3,1,Urban,Data Analyst,37262,0 +55669,Male,25,Masters,13,61,51,47,0,3.0,5,56,Semi-Urban,Data Analyst,119732,0 +55670,Male,43,Masters,0,62,3,25,46,3.0,7,42,Semi-Urban,ML Engineer,60346,0 +55671,Female,38,High School,15,66,39,17,41,6.0,2,90,Urban,ML Engineer,50728,0 +55672,Female,58,Bachelors,9,94,25,87,42,7.0,2,84,Rural,Manager,76577,1 +55673,Other,26,High School,12,70,27,40,96,3.0,6,12,Urban,HR Executive,87716,0 +55674,Male,34,Bachelors,12,83,13,17,92,8.0,7,57,Urban,ML Engineer,93449,0 +55675,Male,37,Bachelors,12,72,33,41,7,0.0,0,38,Urban,Data Analyst,42366,0 +55676,Male,44,High School,16,29,57,16,70,1.0,3,25,Urban,Software Engineer,126235,0 +55677,Male,31,Bachelors,4,5,70,70,40,9.0,4,66,Semi-Urban,HR Executive,100673,0 +55678,Male,25,Bachelors,9,6,98,11,20,4.0,7,69,Urban,Software Engineer,76773,0 +55679,Male,57,Bachelors,15,26,66,6,70,8.0,1,17,Urban,Software Engineer,107509,0 +55680,Male,43,Bachelors,2,90,29,4,17,4.0,1,9,Urban,HR Executive,122481,0 +55681,Female,46,Diploma,0,41,34,7,53,4.0,2,45,Urban,ML Engineer,96712,0 +55682,Male,58,Bachelors,11,90,84,27,98,7.0,4,89,Urban,Data Analyst,75676,1 +55683,Male,49,Masters,0,41,16,23,90,2.0,1,33,Semi-Urban,Data Analyst,47394,0 +55684,Other,52,Diploma,13,95,16,88,61,8.0,6,67,Urban,ML Engineer,37350,1 +55685,Male,23,Masters,6,7,38,18,77,9.0,1,81,Urban,ML Engineer,43217,0 +55686,Male,22,Diploma,10,83,73,24,67,3.0,6,84,Semi-Urban,Manager,60098,1 +55687,Female,25,Diploma,10,93,27,45,87,0.0,0,94,Urban,Manager,80030,1 +55688,Male,21,High School,14,64,72,63,2,3.0,3,9,Urban,Software Engineer,32743,0 +55689,Female,32,Bachelors,2,21,69,62,99,7.0,5,45,Urban,Manager,110034,0 +55690,Male,35,Diploma,7,80,32,39,74,2.0,3,11,Rural,Data Analyst,117595,0 +55691,Male,48,Masters,13,17,31,84,83,9.0,6,86,Semi-Urban,ML Engineer,141263,0 +55692,Female,46,PhD,1,31,18,72,69,1.0,3,87,Rural,Manager,67928,0 +55693,Female,40,Masters,7,77,41,33,87,4.0,4,21,Urban,Manager,36999,0 +55694,Female,29,Bachelors,16,59,68,72,12,7.0,1,2,Rural,Manager,113171,0 +55695,Male,56,Bachelors,4,44,71,70,10,4.0,3,73,Rural,Software Engineer,47725,1 +55696,Male,45,PhD,14,76,1,54,53,6.0,2,25,Urban,HR Executive,113824,0 +55697,Male,53,Bachelors,0,5,65,1,16,8.0,4,79,Semi-Urban,Software Engineer,93948,0 +55698,Male,32,Diploma,2,69,6,79,9,0.0,0,70,Urban,Data Analyst,82320,0 +55699,Male,42,Diploma,7,68,53,33,96,3.0,6,23,Urban,Data Analyst,111009,0 +55700,Male,29,Masters,12,44,86,35,91,0.0,6,98,Urban,Manager,74518,1 +55701,Male,22,Bachelors,6,88,33,22,96,5.0,5,8,Semi-Urban,Data Analyst,144548,0 +55702,Male,26,Bachelors,8,39,12,87,61,6.0,7,78,Urban,Manager,55150,0 +55703,Male,23,Bachelors,17,42,81,91,24,6.0,2,56,Urban,HR Executive,36424,1 +55704,Female,35,Masters,8,3,63,10,12,4.0,7,95,Rural,Software Engineer,105059,0 +55705,Male,45,Bachelors,19,77,17,65,17,9.0,5,27,Semi-Urban,ML Engineer,140191,0 +55706,Male,21,Bachelors,11,28,16,49,58,9.0,1,15,Urban,ML Engineer,93585,0 +55707,Male,50,Bachelors,14,18,65,67,75,7.0,6,46,Rural,Data Analyst,63889,0 +55708,Female,52,Diploma,13,86,89,30,80,8.0,6,18,Urban,Data Analyst,36246,0 +55709,Female,39,Diploma,9,23,93,87,47,2.0,3,75,Urban,Software Engineer,138863,1 +55710,Female,50,Bachelors,9,5,61,82,6,1.0,1,72,Rural,Manager,50529,0 +55711,Female,59,Masters,11,66,48,16,49,4.0,5,81,Rural,Data Analyst,75524,0 +55712,Male,24,Bachelors,16,27,49,77,54,7.0,2,28,Rural,Software Engineer,101448,0 +55713,Male,21,Masters,6,97,25,7,49,3.0,5,87,Urban,HR Executive,141170,0 +55714,Female,53,Bachelors,10,21,47,4,9,5.0,4,79,Urban,Manager,88985,0 +55715,Male,59,PhD,14,38,39,21,96,1.0,0,40,Urban,Manager,119337,0 +55716,Male,47,High School,15,29,39,51,40,9.0,6,77,Rural,Software Engineer,126305,0 +55717,Female,51,Bachelors,4,64,83,84,69,1.0,5,14,Urban,Manager,70811,1 +55718,Male,51,Diploma,15,81,82,47,29,9.0,7,30,Rural,Manager,146046,1 +55719,Female,24,Bachelors,18,62,21,21,57,3.0,7,15,Rural,Data Analyst,93864,0 +55720,Male,24,Masters,14,67,8,90,62,3.0,2,69,Semi-Urban,Manager,87920,0 +55721,Female,22,Masters,12,93,3,75,20,1.0,6,25,Urban,Manager,46718,0 +55722,Other,54,PhD,16,61,51,65,3,8.0,2,43,Urban,Software Engineer,68906,0 +55723,Female,42,Masters,15,12,49,57,98,8.0,3,15,Semi-Urban,Data Analyst,51151,0 +55724,Male,28,Bachelors,13,28,74,31,21,8.0,2,64,Semi-Urban,Software Engineer,75248,0 +55725,Female,51,Diploma,0,80,94,2,62,1.0,0,53,Rural,Software Engineer,48812,0 +55726,Male,43,Masters,6,75,98,10,52,4.0,5,32,Rural,HR Executive,29885,0 +55727,Male,27,Bachelors,18,42,28,62,33,9.0,0,51,Urban,Manager,101308,0 +55728,Female,50,Diploma,5,87,35,76,70,8.0,6,34,Semi-Urban,Software Engineer,80398,0 +55729,Male,39,Bachelors,1,11,19,58,33,6.0,6,64,Rural,ML Engineer,138687,0 +55730,Male,41,Bachelors,9,4,39,91,18,9.0,7,34,Semi-Urban,Manager,94580,0 +55731,Male,41,Masters,17,48,11,80,67,3.0,0,32,Semi-Urban,ML Engineer,111890,0 +55732,Female,43,Diploma,15,86,67,66,52,0.0,3,85,Semi-Urban,HR Executive,111402,1 +55733,Male,21,Bachelors,13,31,17,55,58,5.0,0,65,Semi-Urban,Data Analyst,36197,0 +55734,Female,22,Bachelors,1,12,92,82,69,1.0,3,46,Urban,Manager,93519,0 +55735,Male,38,Bachelors,14,92,69,33,97,5.0,1,39,Urban,Software Engineer,51349,0 +55736,Male,23,Bachelors,4,91,79,34,41,8.0,1,91,Rural,Software Engineer,136287,1 +55737,Other,27,Masters,11,82,13,39,21,2.0,5,54,Urban,Manager,117726,0 +55738,Male,55,Masters,0,75,23,16,13,1.0,6,91,Urban,Software Engineer,37151,0 +55739,Male,36,Diploma,11,83,59,96,69,9.0,4,74,Rural,Software Engineer,148877,1 +55740,Male,30,High School,1,29,39,87,43,0.0,2,61,Urban,Data Analyst,102595,0 +55741,Female,59,Bachelors,3,41,2,22,23,4.0,6,27,Urban,HR Executive,52998,0 +55742,Female,56,High School,17,6,63,47,20,8.0,2,51,Rural,HR Executive,40719,0 +55743,Female,48,High School,19,81,7,66,41,4.0,6,82,Urban,ML Engineer,126043,0 +55744,Male,53,Diploma,1,89,77,75,11,4.0,6,30,Urban,Manager,33235,1 +55745,Male,47,High School,6,93,12,84,28,6.0,1,35,Semi-Urban,Software Engineer,22806,0 +55746,Female,27,Bachelors,6,41,16,8,32,3.0,6,29,Urban,ML Engineer,87960,0 +55747,Female,47,High School,1,36,9,24,59,0.0,3,51,Urban,HR Executive,124785,0 +55748,Female,35,Bachelors,19,40,85,90,21,7.0,0,89,Rural,Data Analyst,31920,1 +55749,Female,30,Bachelors,19,89,40,89,99,8.0,0,72,Urban,ML Engineer,66363,1 +55750,Male,28,Bachelors,10,18,15,47,11,0.0,7,53,Urban,HR Executive,46839,0 +55751,Male,44,Masters,11,69,21,23,72,3.0,5,20,Rural,Software Engineer,57180,0 +55752,Female,41,Bachelors,5,47,59,28,62,2.0,5,33,Urban,HR Executive,72024,0 +55753,Male,23,High School,5,84,62,65,77,1.0,1,19,Urban,Software Engineer,86277,0 +55754,Male,53,Diploma,11,88,33,99,96,6.0,6,98,Urban,Software Engineer,147326,1 +55755,Male,24,High School,1,85,98,91,69,3.0,5,87,Semi-Urban,HR Executive,118374,1 +55756,Male,51,Bachelors,1,94,90,42,96,7.0,5,80,Urban,Data Analyst,113640,1 +55757,Male,59,Diploma,2,77,32,95,35,6.0,6,94,Semi-Urban,Manager,128119,1 +55758,Male,25,Masters,3,22,84,32,27,5.0,5,13,Rural,Software Engineer,74667,0 +55759,Female,30,Bachelors,18,21,80,84,46,0.0,2,89,Semi-Urban,Software Engineer,135671,1 +55760,Male,37,Masters,15,2,1,52,80,4.0,6,36,Rural,Manager,74930,0 +55761,Female,37,High School,14,4,52,75,11,9.0,0,29,Urban,Software Engineer,120224,0 +55762,Female,37,PhD,19,49,18,45,61,6.0,5,52,Rural,Data Analyst,20504,0 +55763,Male,55,Bachelors,15,15,52,30,46,2.0,0,57,Urban,Manager,80768,0 +55764,Male,30,Bachelors,11,10,58,26,71,0.0,7,45,Semi-Urban,ML Engineer,76087,0 +55765,Male,44,Diploma,18,26,90,79,51,6.0,7,87,Urban,Data Analyst,135625,1 +55766,Male,51,High School,18,97,52,75,72,6.0,4,78,Semi-Urban,Software Engineer,146333,1 +55767,Male,59,Masters,15,46,32,50,95,0.0,3,42,Rural,ML Engineer,133717,0 +55768,Male,50,Masters,11,14,85,46,47,0.0,3,95,Semi-Urban,Manager,85981,1 +55769,Female,36,Bachelors,3,79,94,73,40,6.0,1,26,Urban,Software Engineer,141072,1 +55770,Other,43,Masters,14,52,97,79,29,3.0,6,43,Urban,Data Analyst,138595,1 +55771,Male,39,Bachelors,4,94,17,44,64,3.0,2,67,Urban,Software Engineer,138157,0 +55772,Male,27,Bachelors,8,93,21,55,40,4.0,1,33,Rural,ML Engineer,141757,0 +55773,Female,53,Bachelors,2,50,0,90,95,7.0,1,93,Semi-Urban,HR Executive,74908,0 +55774,Female,29,High School,12,70,90,79,96,7.0,6,5,Urban,Software Engineer,88248,1 +55775,Male,29,Bachelors,16,34,44,0,85,7.0,1,16,Urban,Data Analyst,67814,0 +55776,Other,37,Diploma,9,38,22,29,74,1.0,4,31,Rural,Data Analyst,59632,0 +55777,Male,28,PhD,17,73,42,60,47,1.0,7,21,Urban,HR Executive,134285,0 +55778,Female,47,High School,12,7,99,22,7,2.0,4,9,Urban,Manager,106307,0 +55779,Female,49,Masters,5,14,37,88,71,3.0,0,21,Urban,ML Engineer,27084,0 +55780,Male,43,Bachelors,14,90,53,50,77,6.0,3,33,Urban,ML Engineer,21867,0 +55781,Male,41,High School,16,88,67,7,60,7.0,3,34,Urban,Software Engineer,118594,0 +55782,Male,44,High School,6,81,82,3,75,6.0,1,97,Urban,Manager,142292,1 +55783,Male,23,Bachelors,16,81,11,60,72,6.0,4,45,Semi-Urban,Manager,89112,0 +55784,Male,33,Masters,14,90,74,48,7,9.0,4,85,Urban,HR Executive,125409,1 +55785,Male,22,Diploma,15,9,38,53,80,7.0,4,44,Semi-Urban,HR Executive,98422,0 +55786,Male,38,Diploma,12,36,91,59,1,2.0,4,50,Urban,Software Engineer,44934,1 +55787,Male,58,Bachelors,13,98,32,10,62,3.0,2,59,Semi-Urban,Data Analyst,97769,0 +55788,Male,56,Bachelors,6,98,10,65,23,3.0,4,11,Urban,Data Analyst,113460,0 +55789,Female,29,High School,0,52,55,20,27,9.0,2,41,Urban,HR Executive,141588,0 +55790,Male,39,Bachelors,3,52,72,5,3,1.0,2,56,Urban,Software Engineer,61641,0 +55791,Female,33,Diploma,17,45,62,86,86,8.0,0,92,Urban,ML Engineer,38845,1 +55792,Female,57,Masters,7,32,22,91,29,1.0,2,98,Urban,Manager,125454,1 +55793,Male,27,Bachelors,19,75,67,50,46,8.0,4,11,Urban,Data Analyst,140756,0 +55794,Male,31,Bachelors,17,59,64,2,27,4.0,4,62,Urban,Software Engineer,143502,0 +55795,Female,47,Masters,2,73,22,65,6,8.0,3,22,Urban,HR Executive,140196,0 +55796,Male,27,Diploma,10,93,45,67,52,7.0,6,74,Rural,Manager,40378,1 +55797,Female,34,Masters,12,95,89,44,97,8.0,3,6,Semi-Urban,Data Analyst,111023,0 +55798,Male,23,Masters,15,93,83,41,2,0.0,2,80,Rural,ML Engineer,149154,1 +55799,Female,58,Masters,7,63,45,78,35,8.0,7,77,Rural,ML Engineer,32836,1 +55800,Female,57,Bachelors,4,44,25,67,69,0.0,1,14,Urban,ML Engineer,61150,0 +55801,Male,42,Bachelors,15,62,84,64,42,1.0,4,77,Urban,Software Engineer,78535,1 +55802,Male,32,Masters,7,84,26,14,45,5.0,1,33,Urban,ML Engineer,75451,0 +55803,Male,33,Masters,18,51,50,8,16,6.0,7,64,Urban,Data Analyst,95625,0 +55804,Male,59,Bachelors,5,88,8,30,63,8.0,1,62,Rural,ML Engineer,94816,0 +55805,Male,49,Bachelors,7,91,49,34,84,2.0,6,17,Urban,Software Engineer,21951,0 +55806,Male,31,Diploma,8,23,36,20,26,9.0,5,95,Semi-Urban,Manager,42355,0 +55807,Female,30,Diploma,14,99,2,65,79,2.0,4,58,Rural,HR Executive,73807,0 +55808,Male,25,Masters,0,5,31,53,90,6.0,1,84,Urban,Manager,104589,0 +55809,Female,35,High School,10,51,96,86,4,1.0,7,33,Urban,ML Engineer,133108,1 +55810,Male,36,Bachelors,4,68,40,92,41,2.0,0,79,Urban,HR Executive,108452,1 +55811,Male,55,Bachelors,3,15,0,10,93,0.0,5,57,Urban,ML Engineer,27718,0 +55812,Female,34,High School,15,79,20,90,69,7.0,2,66,Urban,ML Engineer,114998,1 +55813,Male,23,Masters,4,92,91,45,87,9.0,3,41,Semi-Urban,Software Engineer,135150,1 +55814,Male,46,Diploma,10,34,12,22,82,0.0,6,11,Rural,HR Executive,32591,0 +55815,Male,26,Bachelors,5,70,79,94,18,7.0,3,73,Semi-Urban,HR Executive,111246,1 +55816,Male,23,PhD,2,45,81,22,70,1.0,1,79,Rural,ML Engineer,103187,0 +55817,Male,40,Bachelors,14,47,71,29,33,9.0,1,60,Rural,Manager,67285,0 +55818,Male,24,PhD,4,76,93,77,66,8.0,5,77,Urban,ML Engineer,109434,1 +55819,Male,32,PhD,9,11,0,76,98,2.0,5,64,Semi-Urban,Software Engineer,50974,0 +55820,Male,50,Diploma,14,72,92,83,29,1.0,3,3,Urban,Data Analyst,68056,1 +55821,Female,53,Bachelors,2,92,8,12,26,6.0,7,64,Urban,HR Executive,110910,0 +55822,Female,29,Masters,5,66,17,99,16,0.0,6,25,Urban,Software Engineer,84884,0 +55823,Male,29,High School,19,69,86,5,53,4.0,4,87,Urban,Data Analyst,89917,1 +55824,Male,34,Bachelors,4,71,1,95,82,7.0,2,6,Urban,Data Analyst,124157,0 +55825,Male,38,PhD,6,15,86,99,84,3.0,4,96,Urban,Software Engineer,76932,1 +55826,Male,42,High School,11,58,91,48,93,7.0,1,65,Urban,Manager,127926,1 +55827,Female,59,PhD,7,63,23,95,77,8.0,0,38,Urban,Software Engineer,64163,0 +55828,Female,48,Bachelors,18,31,30,41,81,2.0,4,86,Urban,HR Executive,117091,0 +55829,Male,31,Masters,3,40,81,71,84,2.0,3,48,Urban,Manager,146929,1 +55830,Male,36,Diploma,3,86,67,96,80,0.0,3,73,Semi-Urban,Manager,90109,1 +55831,Male,53,Masters,18,57,62,54,16,5.0,0,33,Urban,Manager,99955,0 +55832,Female,22,Bachelors,0,47,30,88,51,1.0,6,27,Urban,Manager,145042,0 +55833,Female,52,Bachelors,17,33,97,11,82,4.0,1,34,Rural,Software Engineer,126086,0 +55834,Male,26,Diploma,0,73,65,6,67,3.0,6,72,Urban,Software Engineer,138235,0 +55835,Male,40,Masters,1,61,78,61,39,8.0,7,41,Urban,Manager,135165,1 +55836,Male,50,High School,18,86,7,80,60,7.0,4,69,Urban,ML Engineer,104937,1 +55837,Female,30,Masters,3,40,81,54,12,4.0,1,27,Urban,ML Engineer,99199,0 +55838,Male,28,High School,2,88,60,29,89,0.0,7,66,Rural,Software Engineer,134704,1 +55839,Male,32,Masters,3,76,0,62,17,8.0,1,80,Semi-Urban,HR Executive,121572,0 +55840,Male,38,Diploma,10,38,54,41,20,5.0,1,2,Semi-Urban,ML Engineer,53832,0 +55841,Male,58,Masters,19,28,16,2,78,2.0,0,23,Semi-Urban,ML Engineer,104881,0 +55842,Male,28,Diploma,10,13,22,73,39,4.0,4,56,Semi-Urban,Data Analyst,110470,0 +55843,Female,56,Diploma,19,8,5,38,18,4.0,4,80,Urban,ML Engineer,107582,0 +55844,Male,50,Bachelors,3,26,81,42,84,9.0,6,7,Urban,Data Analyst,126738,0 +55845,Female,47,High School,0,40,80,21,78,2.0,4,99,Urban,Manager,67550,0 +55846,Female,40,High School,8,12,10,60,26,7.0,6,57,Semi-Urban,HR Executive,20722,0 +55847,Male,26,High School,17,80,67,66,18,7.0,6,83,Urban,Data Analyst,121358,1 +55848,Female,48,Bachelors,13,7,95,76,17,5.0,7,51,Urban,ML Engineer,87328,0 +55849,Male,53,High School,16,28,76,51,98,7.0,6,31,Semi-Urban,Data Analyst,92684,0 +55850,Male,58,Masters,2,56,51,74,66,0.0,1,31,Semi-Urban,Data Analyst,91848,0 +55851,Other,38,Bachelors,9,61,84,78,19,1.0,4,85,Urban,Software Engineer,30373,1 +55852,Male,49,High School,18,35,92,87,31,3.0,2,28,Urban,Data Analyst,115002,1 +55853,Male,22,Masters,12,80,44,39,45,5.0,0,28,Rural,Software Engineer,126688,0 +55854,Male,59,Bachelors,3,47,94,56,36,4.0,6,76,Semi-Urban,Data Analyst,47636,1 +55855,Male,46,Masters,4,49,10,35,34,0.0,2,83,Urban,Software Engineer,115617,0 +55856,Male,23,Diploma,12,19,93,60,68,9.0,4,93,Semi-Urban,HR Executive,95749,1 +55857,Male,38,Bachelors,12,15,13,91,22,1.0,6,95,Urban,Software Engineer,59639,0 +55858,Male,29,High School,4,11,18,19,98,4.0,2,54,Rural,ML Engineer,149892,0 +55859,Female,59,Bachelors,7,41,75,84,76,5.0,2,4,Semi-Urban,Data Analyst,68447,0 +55860,Female,39,Diploma,0,12,9,22,22,8.0,5,6,Rural,ML Engineer,80418,0 +55861,Male,51,Bachelors,12,63,66,64,99,0.0,2,33,Rural,ML Engineer,132423,0 +55862,Male,53,Diploma,15,72,41,63,32,4.0,0,14,Semi-Urban,Software Engineer,29079,0 +55863,Male,27,Diploma,7,36,6,63,81,9.0,4,26,Urban,ML Engineer,33521,0 +55864,Male,21,Masters,18,36,80,61,37,3.0,6,25,Semi-Urban,HR Executive,77484,0 +55865,Male,46,Masters,2,11,62,8,50,6.0,1,18,Semi-Urban,Data Analyst,31173,0 +55866,Female,48,High School,3,97,89,53,65,5.0,0,85,Semi-Urban,ML Engineer,46361,1 +55867,Male,31,Bachelors,15,86,0,43,58,7.0,6,1,Rural,Manager,127598,0 +55868,Male,43,Masters,4,72,44,24,27,9.0,1,17,Rural,Software Engineer,90802,0 +55869,Other,24,Masters,18,1,95,30,82,3.0,2,92,Semi-Urban,Manager,132625,0 +55870,Female,53,Bachelors,19,81,67,97,15,8.0,4,44,Semi-Urban,Data Analyst,52392,1 +55871,Male,23,Diploma,2,92,7,20,92,0.0,3,60,Semi-Urban,Software Engineer,53286,0 +55872,Male,51,Bachelors,17,77,25,61,41,3.0,3,5,Semi-Urban,Software Engineer,121208,0 +55873,Female,56,Masters,11,2,90,68,96,9.0,3,48,Urban,Software Engineer,109078,0 +55874,Male,35,High School,9,89,46,48,79,3.0,2,0,Rural,Software Engineer,66223,0 +55875,Male,31,Bachelors,10,78,65,38,47,6.0,2,12,Urban,HR Executive,83810,0 +55876,Male,41,Bachelors,7,84,21,45,7,1.0,6,75,Urban,Data Analyst,77874,0 +55877,Male,47,Bachelors,18,27,29,43,37,7.0,1,41,Rural,Software Engineer,49012,0 +55878,Male,41,Masters,13,16,88,91,3,6.0,4,65,Urban,Software Engineer,130488,1 +55879,Female,28,Diploma,10,91,22,4,6,1.0,1,27,Semi-Urban,Software Engineer,44574,0 +55880,Male,59,Diploma,3,76,65,48,89,2.0,4,28,Semi-Urban,HR Executive,27135,0 +55881,Female,39,Bachelors,6,65,96,82,94,9.0,3,30,Semi-Urban,Data Analyst,78529,1 +55882,Male,45,Bachelors,15,94,5,47,0,0.0,1,22,Urban,Data Analyst,58040,0 +55883,Male,37,Diploma,12,80,87,42,97,6.0,7,23,Urban,ML Engineer,68239,0 +55884,Female,37,Masters,1,8,55,58,13,2.0,6,95,Urban,HR Executive,145239,0 +55885,Other,44,High School,5,10,92,41,68,2.0,4,97,Semi-Urban,Software Engineer,62101,0 +55886,Female,23,High School,17,50,52,30,52,2.0,0,26,Urban,Data Analyst,136441,0 +55887,Male,27,Masters,0,71,15,3,70,5.0,6,54,Semi-Urban,Manager,74166,0 +55888,Male,57,Bachelors,2,61,78,77,89,7.0,7,24,Semi-Urban,Software Engineer,147450,1 +55889,Female,53,Bachelors,15,98,25,9,26,9.0,6,22,Semi-Urban,HR Executive,47067,0 +55890,Male,22,High School,5,8,12,56,91,3.0,0,95,Semi-Urban,ML Engineer,47405,0 +55891,Female,49,Bachelors,17,53,72,76,36,9.0,7,45,Urban,HR Executive,34224,1 +55892,Other,26,High School,9,55,99,81,77,2.0,5,43,Urban,Manager,61244,1 +55893,Male,28,Bachelors,18,21,21,5,23,7.0,1,22,Urban,Manager,24358,0 +55894,Female,50,Masters,11,65,32,25,67,8.0,7,68,Semi-Urban,Data Analyst,135679,0 +55895,Male,49,Masters,7,29,88,21,44,5.0,1,15,Semi-Urban,Data Analyst,21191,0 +55896,Female,39,Masters,17,97,67,56,54,9.0,1,55,Urban,Software Engineer,75475,1 +55897,Female,34,Bachelors,13,11,67,71,32,4.0,6,92,Urban,Manager,92975,1 +55898,Male,41,Bachelors,11,67,93,32,44,9.0,7,8,Urban,Data Analyst,21166,0 +55899,Female,37,Masters,18,70,73,44,0,6.0,2,43,Urban,Data Analyst,48922,0 +55900,Female,42,Diploma,13,77,32,91,23,6.0,4,3,Rural,HR Executive,98794,0 +55901,Male,41,Diploma,16,13,69,23,93,2.0,6,51,Rural,HR Executive,97411,0 +55902,Female,50,Bachelors,18,10,88,59,0,0.0,5,64,Urban,HR Executive,50316,0 +55903,Male,50,Diploma,17,18,95,64,92,3.0,6,52,Urban,Manager,146200,0 +55904,Other,21,Bachelors,9,49,39,97,82,7.0,0,80,Rural,Manager,129806,1 +55905,Male,50,High School,14,27,74,91,23,5.0,3,50,Urban,HR Executive,102921,1 +55906,Male,35,High School,1,37,73,98,94,1.0,0,13,Urban,Software Engineer,140888,0 +55907,Male,50,Diploma,16,0,67,83,18,4.0,6,50,Semi-Urban,HR Executive,101323,0 +55908,Male,44,High School,0,91,37,79,24,4.0,4,39,Urban,ML Engineer,143304,1 +55909,Female,58,Bachelors,7,8,3,46,54,4.0,4,13,Rural,Software Engineer,20750,0 +55910,Male,42,Masters,5,11,73,45,98,8.0,5,30,Semi-Urban,Software Engineer,27188,0 +55911,Female,23,Bachelors,1,34,29,25,78,8.0,5,15,Urban,ML Engineer,59408,0 +55912,Male,42,High School,17,41,39,27,32,7.0,4,48,Urban,Data Analyst,36911,0 +55913,Male,46,Masters,1,20,35,9,9,5.0,1,75,Rural,HR Executive,141242,0 +55914,Female,50,Bachelors,16,97,17,89,33,3.0,6,5,Urban,Manager,118373,0 +55915,Female,39,Bachelors,9,63,98,58,87,7.0,2,25,Semi-Urban,Software Engineer,113922,1 +55916,Female,50,Bachelors,9,96,1,56,36,3.0,3,68,Rural,HR Executive,122932,0 +55917,Male,39,Masters,9,87,30,98,57,5.0,6,13,Rural,HR Executive,125101,0 +55918,Female,40,Diploma,1,61,38,0,99,9.0,6,72,Urban,Data Analyst,148981,0 +55919,Male,38,Diploma,19,61,38,22,57,9.0,5,70,Semi-Urban,Manager,51479,0 +55920,Other,41,High School,12,31,99,62,69,3.0,7,21,Semi-Urban,ML Engineer,57763,0 +55921,Female,50,Diploma,18,5,80,19,92,9.0,6,65,Semi-Urban,ML Engineer,133504,0 +55922,Female,55,Bachelors,1,26,50,31,44,5.0,0,72,Urban,HR Executive,68775,0 +55923,Female,51,Diploma,17,84,96,85,5,4.0,2,21,Semi-Urban,Data Analyst,137044,1 +55924,Male,49,PhD,8,41,94,49,3,1.0,5,98,Urban,HR Executive,59359,1 +55925,Female,47,Diploma,17,63,38,7,51,2.0,6,65,Urban,ML Engineer,56497,0 +55926,Male,22,PhD,14,18,18,49,76,7.0,5,45,Urban,ML Engineer,46466,0 +55927,Male,57,Diploma,3,58,73,97,50,6.0,4,76,Urban,Data Analyst,104799,1 +55928,Male,23,Bachelors,5,16,7,49,30,3.0,3,36,Rural,Manager,112277,0 +55929,Male,23,Bachelors,8,32,13,95,52,9.0,2,53,Urban,Software Engineer,31368,0 +55930,Female,30,Diploma,19,52,43,17,45,1.0,2,23,Semi-Urban,HR Executive,127229,0 +55931,Male,28,Bachelors,10,85,43,24,83,7.0,7,20,Semi-Urban,Data Analyst,96137,0 +55932,Female,56,Bachelors,13,94,26,21,75,2.0,5,95,Semi-Urban,ML Engineer,35619,0 +55933,Female,57,High School,0,1,83,9,15,4.0,2,10,Rural,Data Analyst,110218,0 +55934,Male,44,Bachelors,19,63,47,59,8,4.0,7,31,Semi-Urban,Manager,123708,0 +55935,Male,47,Diploma,0,71,57,65,53,0.0,1,12,Semi-Urban,HR Executive,137886,0 +55936,Male,32,High School,1,93,6,80,67,9.0,6,60,Semi-Urban,ML Engineer,63056,1 +55937,Male,34,Bachelors,12,77,50,34,89,6.0,7,30,Semi-Urban,Software Engineer,44439,0 +55938,Male,32,Masters,13,14,6,86,59,7.0,4,12,Semi-Urban,Software Engineer,62105,0 +55939,Male,57,Masters,16,90,61,15,87,6.0,5,12,Rural,HR Executive,66736,0 +55940,Female,37,Diploma,14,15,21,22,48,5.0,3,8,Rural,Manager,22649,0 +55941,Male,40,High School,18,6,99,19,12,4.0,4,1,Urban,Software Engineer,97537,0 +55942,Male,39,Masters,16,78,73,19,30,9.0,7,82,Urban,ML Engineer,110705,1 +55943,Other,23,Bachelors,16,17,28,28,99,5.0,1,61,Semi-Urban,Data Analyst,22155,0 +55944,Other,55,Masters,3,79,51,92,92,2.0,2,92,Rural,HR Executive,20316,1 +55945,Female,27,Masters,4,19,62,43,95,1.0,5,63,Rural,HR Executive,50234,0 +55946,Male,33,Diploma,6,70,57,18,55,0.0,2,96,Urban,Software Engineer,50042,1 +55947,Female,39,Bachelors,3,33,51,93,75,5.0,4,42,Urban,Manager,31487,0 +55948,Male,25,Bachelors,17,83,49,0,36,6.0,1,28,Urban,Software Engineer,96688,0 +55949,Male,40,High School,14,48,71,1,16,8.0,3,65,Urban,HR Executive,31727,0 +55950,Male,23,PhD,2,30,59,66,32,3.0,1,65,Rural,ML Engineer,130067,0 +55951,Male,27,Masters,19,95,14,66,89,4.0,6,62,Urban,HR Executive,30096,1 +55952,Other,21,Masters,9,6,47,80,42,3.0,4,36,Urban,Manager,108910,0 +55953,Female,42,Diploma,8,52,46,85,51,3.0,5,61,Rural,ML Engineer,129093,1 +55954,Male,49,Bachelors,7,0,45,31,19,9.0,2,94,Rural,ML Engineer,90177,0 +55955,Male,37,High School,1,87,47,17,11,5.0,7,74,Urban,Software Engineer,131980,0 +55956,Male,56,Diploma,18,85,24,67,87,0.0,3,35,Rural,ML Engineer,21889,0 +55957,Female,50,Masters,6,53,75,94,89,7.0,2,33,Urban,Data Analyst,102148,1 +55958,Male,35,Diploma,2,41,66,33,10,9.0,2,52,Urban,Software Engineer,74740,0 +55959,Male,34,Bachelors,0,53,60,19,87,6.0,5,68,Urban,Software Engineer,22007,0 +55960,Male,45,Diploma,18,7,74,57,57,1.0,1,24,Rural,HR Executive,63653,0 +55961,Male,56,High School,7,34,31,67,83,1.0,2,3,Semi-Urban,Software Engineer,135053,0 +55962,Female,30,Masters,18,16,33,42,48,2.0,2,38,Urban,ML Engineer,117938,0 +55963,Female,56,Diploma,7,83,12,14,43,5.0,5,29,Urban,HR Executive,92440,0 +55964,Male,39,Diploma,12,40,89,88,44,5.0,7,19,Semi-Urban,Data Analyst,122305,1 +55965,Male,38,Diploma,6,30,53,16,0,9.0,5,56,Rural,Software Engineer,59243,0 +55966,Male,34,Bachelors,8,66,92,17,75,1.0,0,11,Semi-Urban,Software Engineer,75980,0 +55967,Female,54,High School,1,66,52,8,94,4.0,3,45,Urban,Software Engineer,27265,0 +55968,Male,34,Diploma,6,83,10,57,76,5.0,1,42,Semi-Urban,Data Analyst,70715,0 +55969,Male,38,Diploma,8,72,0,83,65,7.0,2,70,Urban,HR Executive,98792,0 +55970,Male,40,High School,1,20,56,73,53,1.0,5,83,Urban,Manager,86498,0 +55971,Male,40,PhD,5,69,80,64,35,2.0,4,13,Semi-Urban,HR Executive,69586,0 +55972,Female,24,Diploma,14,11,47,79,14,9.0,3,99,Semi-Urban,Software Engineer,85702,0 +55973,Male,44,Bachelors,5,11,21,63,43,3.0,1,48,Urban,HR Executive,47400,0 +55974,Male,30,Bachelors,1,8,40,66,3,3.0,4,2,Urban,Manager,34421,0 +55975,Female,45,Bachelors,5,59,87,83,28,3.0,7,53,Urban,ML Engineer,136684,1 +55976,Female,24,High School,16,52,38,97,48,5.0,2,40,Urban,Manager,125002,0 +55977,Male,40,Diploma,14,84,49,20,37,6.0,1,74,Urban,Software Engineer,79802,0 +55978,Male,32,High School,9,55,3,80,75,6.0,6,68,Rural,ML Engineer,119732,0 +55979,Female,44,Diploma,9,67,30,81,47,2.0,3,70,Semi-Urban,Data Analyst,78746,1 +55980,Male,43,Bachelors,1,74,79,47,84,0.0,2,79,Semi-Urban,Software Engineer,43535,1 +55981,Female,55,PhD,18,69,8,96,23,5.0,3,68,Rural,Software Engineer,79401,1 +55982,Male,32,Bachelors,6,91,51,46,7,3.0,0,45,Urban,Manager,94541,0 +55983,Male,25,Bachelors,17,76,98,94,28,9.0,4,74,Urban,Software Engineer,70875,1 +55984,Male,32,High School,15,0,88,75,63,6.0,6,76,Rural,ML Engineer,35894,1 +55985,Male,41,Masters,0,67,99,49,76,8.0,0,74,Urban,ML Engineer,96179,1 +55986,Male,34,Bachelors,13,26,58,14,87,9.0,4,66,Semi-Urban,ML Engineer,37749,0 +55987,Female,36,High School,17,43,29,80,44,2.0,6,65,Urban,Data Analyst,46588,0 +55988,Male,59,High School,3,54,14,38,7,5.0,1,86,Urban,Manager,119735,0 +55989,Female,53,Bachelors,10,70,37,30,76,2.0,2,77,Urban,Data Analyst,134524,0 +55990,Female,35,Bachelors,15,77,32,11,8,7.0,4,93,Urban,Software Engineer,128468,0 +55991,Male,56,Bachelors,4,64,56,90,74,7.0,3,16,Rural,Manager,67872,0 +55992,Female,50,Masters,19,5,90,90,67,3.0,6,70,Rural,Software Engineer,100026,1 +55993,Female,37,Bachelors,17,28,72,34,86,5.0,0,7,Urban,HR Executive,82725,0 +55994,Male,46,High School,7,35,73,39,55,3.0,0,96,Urban,Data Analyst,32945,1 +55995,Male,44,Masters,1,15,1,60,81,0.0,5,29,Urban,ML Engineer,43459,0 +55996,Other,29,Diploma,1,41,25,99,69,2.0,0,20,Semi-Urban,Manager,42620,0 +55997,Female,29,Bachelors,1,96,35,50,89,6.0,4,20,Urban,Software Engineer,85447,0 +55998,Female,41,Bachelors,9,69,14,95,67,3.0,2,54,Urban,HR Executive,101992,0 +55999,Female,49,Diploma,0,8,1,87,31,2.0,4,81,Semi-Urban,Data Analyst,73832,0 +56000,Female,56,Bachelors,1,90,95,60,0,5.0,7,11,Rural,ML Engineer,90652,1 +56001,Male,48,High School,15,2,63,31,41,4.0,0,26,Semi-Urban,Data Analyst,46937,0 +56002,Other,32,Diploma,0,62,15,61,49,1.0,6,25,Semi-Urban,Data Analyst,25470,0 +56003,Female,39,High School,10,72,20,28,43,4.0,5,84,Rural,ML Engineer,102168,0 +56004,Female,56,Diploma,10,50,96,71,90,7.0,2,19,Urban,Data Analyst,134844,0 +56005,Male,57,High School,9,25,39,98,38,4.0,3,19,Semi-Urban,Data Analyst,35798,0 +56006,Female,29,Masters,11,35,87,55,20,2.0,0,39,Urban,HR Executive,23948,0 +56007,Female,29,Diploma,18,80,67,51,48,7.0,6,62,Semi-Urban,Software Engineer,115258,1 +56008,Female,26,Diploma,15,59,67,32,6,5.0,6,36,Urban,Manager,136329,0 +56009,Male,34,High School,18,64,53,0,5,4.0,4,41,Urban,ML Engineer,22168,0 +56010,Female,33,Diploma,9,89,35,78,8,9.0,0,16,Semi-Urban,Software Engineer,50830,0 +56011,Male,58,Diploma,9,24,25,0,39,7.0,2,24,Semi-Urban,Software Engineer,133978,0 +56012,Female,36,Diploma,11,41,23,64,57,7.0,7,92,Urban,ML Engineer,123185,0 +56013,Male,59,High School,4,96,98,40,98,0.0,0,59,Semi-Urban,ML Engineer,141542,1 +56014,Male,53,High School,19,27,71,75,96,5.0,6,43,Semi-Urban,HR Executive,104728,0 +56015,Male,48,High School,7,66,18,64,70,3.0,7,61,Semi-Urban,Data Analyst,114616,0 +56016,Male,44,Masters,14,39,49,88,39,0.0,3,30,Urban,Manager,66496,0 +56017,Female,22,Bachelors,7,21,67,4,74,9.0,6,31,Urban,Software Engineer,108025,0 +56018,Male,52,High School,12,61,52,73,52,5.0,0,62,Semi-Urban,ML Engineer,63200,1 +56019,Male,40,Bachelors,8,58,96,22,70,7.0,0,56,Semi-Urban,Software Engineer,69049,0 +56020,Female,33,Masters,15,9,41,33,73,1.0,4,65,Urban,ML Engineer,82429,0 +56021,Female,48,Masters,0,30,11,98,11,5.0,7,22,Urban,Data Analyst,98546,0 +56022,Other,27,High School,6,28,46,90,87,5.0,6,26,Rural,Software Engineer,104855,0 +56023,Male,53,Bachelors,9,7,57,2,28,2.0,5,53,Semi-Urban,HR Executive,131777,0 +56024,Female,22,Bachelors,16,77,82,38,30,5.0,7,24,Urban,Software Engineer,53364,0 +56025,Male,57,High School,4,53,13,5,87,6.0,4,46,Rural,HR Executive,63989,0 +56026,Female,54,High School,1,7,52,41,50,7.0,4,69,Urban,ML Engineer,51676,0 +56027,Female,28,Bachelors,0,64,46,12,58,7.0,6,41,Urban,Software Engineer,103511,0 +56028,Female,56,Diploma,6,83,21,12,90,2.0,6,14,Urban,Manager,29147,0 +56029,Male,25,Masters,14,99,85,72,25,4.0,2,63,Urban,Data Analyst,65395,1 +56030,Other,22,Bachelors,8,89,84,18,89,7.0,6,4,Urban,Data Analyst,121511,0 +56031,Female,32,Bachelors,10,10,29,72,8,9.0,0,92,Semi-Urban,ML Engineer,147252,0 +56032,Male,59,Bachelors,1,63,4,21,5,9.0,0,56,Semi-Urban,Software Engineer,68093,0 +56033,Male,50,Bachelors,13,14,22,5,73,9.0,0,79,Urban,Software Engineer,54335,0 +56034,Female,26,Diploma,9,32,77,5,51,8.0,5,70,Urban,HR Executive,33410,0 +56035,Male,27,Bachelors,0,57,92,15,71,5.0,3,32,Urban,Manager,80316,0 +56036,Male,59,Bachelors,8,40,55,88,41,6.0,7,64,Urban,Manager,106501,1 +56037,Female,38,Diploma,3,67,16,26,8,2.0,2,1,Semi-Urban,HR Executive,42498,0 +56038,Female,22,Bachelors,0,83,0,33,27,9.0,4,59,Semi-Urban,ML Engineer,138091,0 +56039,Male,24,Bachelors,13,13,11,96,36,6.0,7,9,Urban,Data Analyst,23496,0 +56040,Male,55,Bachelors,12,93,55,77,16,0.0,7,54,Urban,Software Engineer,66841,1 +56041,Male,23,PhD,15,29,56,65,30,2.0,2,47,Semi-Urban,Software Engineer,134976,0 +56042,Female,31,Diploma,18,73,74,77,18,4.0,4,20,Urban,ML Engineer,67281,1 +56043,Female,50,Bachelors,18,75,81,76,83,5.0,0,58,Urban,Manager,50241,1 +56044,Female,28,High School,15,73,50,21,10,8.0,4,47,Urban,Data Analyst,41291,0 +56045,Male,30,Masters,10,28,69,84,5,2.0,3,79,Rural,Software Engineer,119144,1 +56046,Female,39,Bachelors,14,57,21,72,39,9.0,3,25,Urban,Manager,120072,0 +56047,Male,41,High School,11,94,56,84,24,4.0,6,48,Rural,ML Engineer,136332,1 +56048,Female,28,Bachelors,11,68,37,16,20,5.0,2,20,Rural,HR Executive,148346,0 +56049,Male,27,Bachelors,18,95,62,66,38,8.0,1,33,Semi-Urban,Data Analyst,114354,1 +56050,Male,57,High School,11,88,60,86,44,9.0,5,89,Semi-Urban,ML Engineer,62247,1 +56051,Male,57,Diploma,18,73,96,25,38,4.0,7,32,Semi-Urban,HR Executive,95457,0 +56052,Female,22,Masters,3,19,47,26,7,1.0,5,63,Semi-Urban,Data Analyst,92595,0 +56053,Female,47,High School,18,19,31,47,5,1.0,6,7,Urban,ML Engineer,67183,0 +56054,Male,46,Diploma,19,5,64,6,95,3.0,2,45,Rural,Data Analyst,87109,0 +56055,Male,42,Diploma,9,44,97,37,52,5.0,7,87,Semi-Urban,Data Analyst,43838,1 +56056,Male,57,Diploma,13,54,1,58,57,3.0,5,29,Urban,Manager,74679,0 +56057,Male,32,Diploma,19,80,59,73,28,1.0,7,43,Semi-Urban,HR Executive,117915,1 +56058,Other,47,Diploma,17,95,2,65,58,8.0,1,16,Rural,Manager,99833,0 +56059,Male,22,Bachelors,18,19,80,76,77,8.0,1,45,Urban,ML Engineer,88161,0 +56060,Female,59,High School,3,16,43,98,20,1.0,1,62,Semi-Urban,ML Engineer,22595,0 +56061,Female,31,Bachelors,6,34,80,28,9,3.0,2,9,Semi-Urban,ML Engineer,38916,0 +56062,Male,51,High School,18,68,93,28,36,7.0,1,34,Semi-Urban,HR Executive,28438,0 +56063,Female,54,Diploma,3,26,12,21,41,8.0,2,92,Urban,ML Engineer,97889,0 +56064,Female,29,Masters,14,9,9,48,46,3.0,1,47,Urban,HR Executive,37002,0 +56065,Female,52,High School,2,57,27,4,29,6.0,6,29,Urban,ML Engineer,140366,0 +56066,Male,45,Masters,17,16,41,51,82,8.0,4,10,Urban,Software Engineer,57059,0 +56067,Male,38,Bachelors,16,57,85,67,33,1.0,2,2,Urban,Manager,101352,0 +56068,Female,54,Masters,5,54,57,84,95,8.0,1,12,Urban,Software Engineer,95373,0 +56069,Male,49,Bachelors,12,68,14,15,81,6.0,7,6,Semi-Urban,ML Engineer,102536,0 +56070,Female,39,Bachelors,10,94,48,63,4,2.0,1,25,Urban,Software Engineer,60291,0 +56071,Male,25,High School,16,80,63,8,67,7.0,3,28,Rural,Software Engineer,53733,0 +56072,Male,30,Bachelors,6,38,33,13,75,1.0,1,80,Urban,ML Engineer,61573,0 +56073,Female,45,Bachelors,15,79,36,34,70,6.0,1,88,Semi-Urban,ML Engineer,143325,0 +56074,Male,58,Masters,5,99,28,85,40,5.0,2,97,Semi-Urban,Software Engineer,87563,1 +56075,Male,31,Masters,18,57,51,33,33,8.0,2,57,Semi-Urban,HR Executive,29053,0 +56076,Male,33,Diploma,19,49,74,70,51,0.0,5,11,Urban,Software Engineer,79192,0 +56077,Male,44,Bachelors,11,7,50,84,21,7.0,1,98,Urban,ML Engineer,34105,1 +56078,Male,22,Bachelors,10,54,85,41,64,1.0,4,93,Semi-Urban,Software Engineer,94324,1 +56079,Male,31,PhD,10,47,51,66,89,7.0,2,65,Urban,Software Engineer,94365,0 +56080,Female,50,Masters,2,91,24,9,27,3.0,6,36,Urban,Data Analyst,70293,0 +56081,Male,22,Bachelors,12,24,17,49,69,8.0,5,76,Urban,Data Analyst,134627,0 +56082,Female,59,Diploma,5,19,29,10,28,7.0,4,18,Rural,Manager,49910,0 +56083,Female,30,Bachelors,17,95,82,49,18,5.0,1,20,Urban,Software Engineer,68818,1 +56084,Female,40,Masters,16,23,64,92,46,0.0,1,25,Rural,Software Engineer,44961,0 +56085,Female,27,Diploma,7,11,10,4,5,2.0,1,86,Urban,ML Engineer,37250,0 +56086,Male,54,Masters,14,24,96,78,59,2.0,4,73,Rural,ML Engineer,60882,1 +56087,Male,27,Bachelors,0,57,46,99,41,5.0,6,20,Urban,Software Engineer,103695,0 +56088,Male,26,Bachelors,10,17,49,67,1,2.0,5,18,Urban,Data Analyst,94311,0 +56089,Female,51,Bachelors,16,39,34,64,13,4.0,1,24,Semi-Urban,Data Analyst,55293,0 +56090,Female,54,Diploma,5,44,64,28,1,0.0,3,11,Rural,Data Analyst,89702,0 +56091,Other,41,Bachelors,14,8,1,66,76,9.0,6,1,Urban,Software Engineer,77165,0 +56092,Female,55,Diploma,17,11,18,64,65,9.0,2,23,Rural,Manager,142452,0 +56093,Male,45,Diploma,16,95,49,28,73,2.0,6,98,Rural,Data Analyst,36946,1 +56094,Female,35,Masters,16,56,6,8,29,5.0,0,30,Rural,ML Engineer,32442,0 +56095,Male,25,Bachelors,18,2,99,6,14,6.0,3,57,Rural,Manager,101756,0 +56096,Female,27,Masters,5,18,97,10,42,9.0,1,47,Urban,Software Engineer,144683,0 +56097,Male,44,Diploma,11,59,30,72,0,2.0,2,1,Urban,Software Engineer,95780,0 +56098,Male,44,Bachelors,3,17,3,57,31,9.0,0,21,Urban,HR Executive,41418,0 +56099,Male,39,Masters,12,66,80,63,47,0.0,4,1,Urban,Software Engineer,63250,0 +56100,Other,46,PhD,4,72,32,87,64,4.0,4,42,Urban,Data Analyst,132194,0 +56101,Female,34,High School,0,12,68,86,54,7.0,6,86,Rural,Data Analyst,110397,1 +56102,Male,53,Bachelors,10,12,12,90,42,5.0,0,34,Urban,ML Engineer,73666,0 +56103,Male,47,Masters,17,73,50,6,2,2.0,6,55,Urban,Data Analyst,64750,0 +56104,Male,59,Bachelors,13,75,31,12,25,8.0,6,33,Semi-Urban,Manager,117799,0 +56105,Male,58,Diploma,10,94,90,78,84,3.0,2,4,Urban,ML Engineer,36970,1 +56106,Male,53,Masters,17,93,55,77,40,9.0,2,16,Urban,Software Engineer,104926,1 +56107,Female,27,Bachelors,5,61,83,69,7,7.0,0,59,Rural,Data Analyst,141001,1 +56108,Female,39,Diploma,3,76,45,92,75,2.0,3,82,Rural,HR Executive,74021,1 +56109,Other,23,Bachelors,5,59,21,28,7,1.0,6,94,Urban,HR Executive,63788,0 +56110,Male,33,Bachelors,18,44,85,86,50,7.0,4,27,Urban,ML Engineer,37431,1 +56111,Female,46,Bachelors,7,70,7,41,73,3.0,7,81,Semi-Urban,Manager,98190,0 +56112,Male,31,Masters,5,39,66,88,42,4.0,2,22,Urban,HR Executive,128534,0 +56113,Male,27,High School,7,22,9,41,29,9.0,6,38,Urban,Software Engineer,47766,0 +56114,Male,58,Bachelors,12,3,16,4,85,2.0,4,3,Rural,Data Analyst,52311,0 +56115,Other,26,Masters,2,88,77,8,94,8.0,2,35,Semi-Urban,Software Engineer,23046,0 +56116,Other,31,Bachelors,3,30,72,27,7,3.0,2,55,Urban,Manager,56204,0 +56117,Female,36,Bachelors,12,82,84,91,6,0.0,6,85,Urban,ML Engineer,40140,1 +56118,Male,34,High School,12,67,14,51,80,2.0,4,83,Rural,Software Engineer,56455,0 +56119,Female,30,Diploma,17,36,11,87,2,7.0,3,88,Urban,Data Analyst,99548,0 +56120,Female,27,Diploma,15,36,22,16,71,5.0,1,26,Rural,Software Engineer,39588,0 +56121,Male,25,Bachelors,17,21,56,96,42,0.0,6,55,Semi-Urban,HR Executive,29087,0 +56122,Male,23,Bachelors,17,82,74,84,8,9.0,1,92,Urban,Data Analyst,76692,1 +56123,Female,34,Diploma,3,27,44,11,27,5.0,3,66,Semi-Urban,Software Engineer,91668,0 +56124,Female,36,Bachelors,13,7,21,9,60,8.0,3,80,Semi-Urban,Data Analyst,113534,0 +56125,Female,52,Diploma,15,38,4,62,60,0.0,1,65,Rural,ML Engineer,113190,0 +56126,Male,25,Diploma,3,37,7,83,2,4.0,5,31,Semi-Urban,HR Executive,108399,0 +56127,Male,56,Bachelors,13,72,53,19,32,9.0,5,15,Urban,Data Analyst,74552,0 +56128,Female,24,Bachelors,16,21,74,87,82,0.0,0,68,Semi-Urban,HR Executive,56609,1 +56129,Female,59,Bachelors,1,3,62,75,31,7.0,1,7,Rural,ML Engineer,40574,0 +56130,Male,57,Bachelors,14,46,37,72,96,7.0,4,47,Semi-Urban,HR Executive,50693,0 +56131,Female,43,Masters,9,76,57,81,2,1.0,7,51,Rural,ML Engineer,63726,1 +56132,Male,45,Diploma,10,20,10,13,82,1.0,4,35,Urban,Data Analyst,105249,0 +56133,Male,42,Bachelors,18,10,51,69,78,5.0,1,8,Urban,Data Analyst,94738,0 +56134,Male,39,High School,0,82,7,86,97,3.0,5,84,Urban,Software Engineer,109807,1 +56135,Male,59,Masters,0,64,61,18,19,0.0,6,92,Rural,Manager,102520,1 +56136,Male,30,Bachelors,0,36,71,17,70,6.0,0,91,Semi-Urban,Data Analyst,97235,0 +56137,Female,53,Bachelors,17,84,56,74,50,8.0,1,50,Urban,ML Engineer,61610,1 +56138,Female,49,PhD,4,99,10,43,58,8.0,6,35,Urban,HR Executive,146222,0 +56139,Other,54,Bachelors,7,59,72,84,6,8.0,2,33,Urban,Manager,28613,1 +56140,Male,43,Bachelors,8,87,52,32,39,0.0,1,65,Urban,Data Analyst,28496,1 +56141,Female,52,Bachelors,14,86,40,23,68,4.0,0,15,Urban,Data Analyst,70341,0 +56142,Other,25,Diploma,7,65,9,92,56,8.0,3,48,Semi-Urban,ML Engineer,146409,0 +56143,Male,59,Masters,3,73,53,71,69,1.0,5,82,Semi-Urban,Software Engineer,49464,1 +56144,Male,56,Masters,11,35,78,61,27,1.0,6,38,Semi-Urban,HR Executive,139793,0 +56145,Female,46,Masters,13,58,72,65,58,3.0,5,15,Rural,ML Engineer,93083,0 +56146,Male,30,Bachelors,4,17,47,8,93,9.0,2,93,Rural,Manager,31475,0 +56147,Male,42,Masters,2,93,46,10,40,0.0,7,91,Semi-Urban,Data Analyst,130591,1 +56148,Other,46,Masters,8,52,62,55,27,7.0,4,22,Rural,Manager,50773,0 +56149,Female,25,High School,14,3,89,96,78,8.0,5,67,Urban,Software Engineer,32834,1 +56150,Male,37,Bachelors,0,7,91,5,18,0.0,1,28,Urban,Manager,129570,0 +56151,Male,46,Bachelors,15,81,59,2,19,4.0,3,5,Urban,Manager,91814,0 +56152,Male,34,Diploma,10,5,42,98,75,8.0,3,86,Urban,ML Engineer,73604,0 +56153,Male,30,Bachelors,17,31,91,13,40,1.0,5,12,Rural,HR Executive,122965,0 +56154,Male,30,Masters,16,47,35,84,54,2.0,4,30,Urban,HR Executive,145282,0 +56155,Male,28,PhD,16,46,17,36,63,1.0,2,29,Urban,Data Analyst,77346,0 +56156,Male,46,Bachelors,5,11,68,15,34,8.0,0,74,Urban,Data Analyst,106572,0 +56157,Female,27,Masters,7,48,36,39,29,6.0,7,0,Urban,ML Engineer,26988,0 +56158,Male,55,High School,2,87,92,69,81,8.0,5,72,Urban,Software Engineer,123908,1 +56159,Male,33,Diploma,1,40,4,94,51,6.0,1,75,Urban,Data Analyst,108054,0 +56160,Female,26,PhD,8,83,40,38,34,1.0,6,97,Semi-Urban,ML Engineer,134392,1 +56161,Male,48,Diploma,2,41,4,46,70,6.0,7,42,Urban,ML Engineer,124611,0 +56162,Female,28,High School,4,53,26,82,61,7.0,0,61,Urban,Data Analyst,36473,0 +56163,Female,22,Bachelors,15,1,87,81,90,1.0,2,38,Urban,Manager,63924,0 +56164,Other,46,Diploma,10,53,46,98,66,5.0,3,95,Rural,Manager,20873,1 +56165,Male,30,High School,14,46,98,58,14,8.0,6,50,Rural,Data Analyst,81936,1 +56166,Male,53,Diploma,9,86,75,58,45,3.0,7,51,Rural,ML Engineer,140276,1 +56167,Male,38,PhD,7,78,98,32,53,4.0,5,67,Semi-Urban,Data Analyst,105159,1 +56168,Male,25,Bachelors,18,89,77,59,16,0.0,5,37,Urban,Software Engineer,33137,1 +56169,Female,46,Masters,12,49,63,65,68,4.0,7,36,Rural,Software Engineer,107862,0 +56170,Female,55,Masters,12,39,80,37,10,6.0,1,40,Urban,Data Analyst,57095,0 +56171,Other,25,Diploma,4,59,96,84,95,1.0,1,46,Urban,ML Engineer,31484,1 +56172,Male,43,Bachelors,5,25,64,19,13,2.0,2,33,Urban,Manager,36168,0 +56173,Female,22,Bachelors,13,58,66,27,37,3.0,2,53,Semi-Urban,Manager,97282,0 +56174,Male,32,Masters,3,39,93,82,53,8.0,4,37,Urban,ML Engineer,41646,1 +56175,Female,53,Masters,0,57,42,21,2,4.0,5,51,Urban,Manager,110682,0 +56176,Male,54,Bachelors,15,85,14,80,98,9.0,3,11,Rural,ML Engineer,38427,0 +56177,Female,45,Masters,1,69,20,12,21,2.0,3,64,Urban,Software Engineer,139737,0 +56178,Male,57,Bachelors,16,42,93,0,85,4.0,3,2,Semi-Urban,ML Engineer,110063,0 +56179,Male,21,High School,1,80,24,11,33,6.0,4,10,Urban,Manager,144909,0 +56180,Female,38,Bachelors,7,72,95,86,32,6.0,1,14,Semi-Urban,ML Engineer,61409,1 +56181,Female,34,Bachelors,3,76,40,27,60,4.0,4,83,Semi-Urban,Data Analyst,65139,0 +56182,Female,34,Bachelors,14,90,2,76,15,3.0,6,96,Urban,ML Engineer,91118,1 +56183,Male,22,Bachelors,10,96,14,57,83,8.0,6,15,Semi-Urban,Data Analyst,62801,0 +56184,Male,25,Bachelors,13,23,81,35,33,1.0,1,29,Urban,ML Engineer,58003,0 +56185,Male,37,High School,16,3,90,41,86,3.0,3,45,Rural,Manager,33798,0 +56186,Female,43,Diploma,12,13,39,15,88,9.0,6,62,Rural,ML Engineer,108473,0 +56187,Male,39,Bachelors,9,24,96,88,33,6.0,2,34,Urban,Software Engineer,34767,1 +56188,Female,21,Bachelors,3,88,54,38,74,2.0,7,60,Urban,Software Engineer,64121,0 +56189,Female,37,Diploma,10,96,26,0,71,8.0,5,53,Semi-Urban,Software Engineer,27696,0 +56190,Male,41,Bachelors,15,86,40,71,94,9.0,1,65,Urban,Data Analyst,136248,1 +56191,Female,21,Bachelors,17,77,56,34,15,1.0,7,40,Semi-Urban,ML Engineer,135915,0 +56192,Female,40,Bachelors,5,41,20,58,29,5.0,3,56,Urban,Software Engineer,86367,0 +56193,Male,56,Bachelors,18,98,14,14,32,1.0,1,53,Urban,HR Executive,125756,0 +56194,Male,21,Bachelors,19,88,26,19,42,1.0,1,77,Semi-Urban,ML Engineer,145453,0 +56195,Male,40,Bachelors,0,62,83,36,84,9.0,6,0,Urban,Software Engineer,125906,0 +56196,Male,26,Bachelors,11,55,77,93,37,8.0,5,31,Urban,Software Engineer,119038,1 +56197,Male,30,Bachelors,3,31,71,77,38,8.0,1,85,Rural,Software Engineer,42212,1 +56198,Female,47,Masters,19,2,43,82,4,9.0,5,13,Urban,HR Executive,117712,0 +56199,Male,25,Masters,8,18,90,70,93,4.0,4,96,Rural,ML Engineer,55127,1 +56200,Female,48,Bachelors,16,89,15,16,9,1.0,0,80,Urban,Data Analyst,72009,0 +56201,Female,39,Diploma,14,0,78,84,94,1.0,6,79,Rural,Manager,23461,1 +56202,Female,38,Diploma,15,99,68,75,55,9.0,1,85,Urban,Software Engineer,109909,1 +56203,Male,21,Masters,8,93,57,74,59,9.0,4,42,Urban,Software Engineer,37897,1 +56204,Female,34,Bachelors,13,36,8,62,32,3.0,2,51,Semi-Urban,HR Executive,129230,0 +56205,Female,54,Masters,4,69,76,28,57,2.0,3,60,Semi-Urban,Software Engineer,104094,0 +56206,Male,44,High School,8,7,44,77,16,1.0,1,40,Urban,Manager,78925,0 +56207,Other,31,Bachelors,19,98,8,36,12,3.0,4,3,Urban,ML Engineer,29913,0 +56208,Male,54,Diploma,9,73,64,24,52,3.0,0,26,Rural,ML Engineer,92265,0 +56209,Male,34,Bachelors,5,75,83,88,75,4.0,3,28,Urban,Manager,149437,1 +56210,Male,36,Bachelors,13,17,41,90,43,3.0,3,23,Urban,Software Engineer,99180,0 +56211,Male,44,High School,8,90,70,95,18,7.0,7,50,Urban,Software Engineer,48529,1 +56212,Female,43,Diploma,4,17,32,37,6,3.0,4,41,Urban,HR Executive,97490,0 +56213,Male,53,Bachelors,19,15,2,37,34,1.0,5,78,Rural,Data Analyst,38808,0 +56214,Male,55,Bachelors,5,3,78,77,86,8.0,3,45,Rural,Data Analyst,104065,0 +56215,Female,43,Masters,1,61,91,14,49,6.0,7,40,Semi-Urban,Data Analyst,68528,0 +56216,Female,39,Masters,7,59,72,49,7,4.0,0,62,Urban,Manager,62074,1 +56217,Male,28,Bachelors,16,88,89,61,56,2.0,1,87,Urban,ML Engineer,33890,1 +56218,Female,21,Bachelors,8,2,22,11,67,3.0,3,84,Semi-Urban,Manager,89459,0 +56219,Male,33,PhD,16,72,93,2,94,0.0,6,19,Urban,Data Analyst,110106,0 +56220,Female,32,Masters,4,33,32,7,7,8.0,6,59,Rural,Data Analyst,89004,0 +56221,Female,33,Diploma,5,11,84,69,0,6.0,4,54,Urban,Data Analyst,23788,0 +56222,Male,44,Diploma,9,52,57,32,34,5.0,3,90,Urban,HR Executive,77789,0 +56223,Male,22,Bachelors,8,74,52,86,11,4.0,3,69,Urban,Software Engineer,57237,1 +56224,Male,22,Bachelors,18,17,30,65,33,5.0,7,70,Rural,Manager,121559,0 +56225,Male,29,Bachelors,11,12,25,71,85,9.0,1,94,Semi-Urban,Data Analyst,35145,0 +56226,Male,44,Masters,8,14,73,33,51,9.0,6,91,Urban,Data Analyst,27022,0 +56227,Male,44,Bachelors,19,90,52,81,58,3.0,5,90,Urban,ML Engineer,107581,1 +56228,Male,22,Diploma,10,66,71,16,47,1.0,7,74,Urban,Manager,64055,0 +56229,Male,25,PhD,7,71,24,13,56,0.0,4,71,Urban,ML Engineer,126548,0 +56230,Male,50,Masters,9,18,76,87,78,2.0,5,43,Semi-Urban,Manager,129875,0 +56231,Male,33,Diploma,2,39,40,70,39,3.0,7,40,Semi-Urban,HR Executive,54842,0 +56232,Female,41,PhD,5,20,71,71,70,9.0,3,16,Semi-Urban,Manager,68377,0 +56233,Female,51,Masters,14,20,48,15,43,5.0,4,34,Urban,ML Engineer,103708,0 +56234,Male,33,Diploma,6,94,72,41,60,1.0,3,5,Urban,Software Engineer,129119,0 +56235,Male,35,Bachelors,3,95,41,32,88,9.0,6,62,Semi-Urban,Data Analyst,74680,0 +56236,Male,55,Masters,4,16,6,58,65,0.0,1,51,Semi-Urban,Manager,28578,0 +56237,Female,33,High School,16,78,50,6,93,4.0,3,74,Semi-Urban,Data Analyst,129048,0 +56238,Female,23,Masters,10,48,54,82,0,8.0,3,1,Semi-Urban,Data Analyst,48728,0 +56239,Female,50,Masters,4,3,63,22,30,2.0,2,20,Semi-Urban,Data Analyst,97731,0 +56240,Male,22,PhD,5,86,24,65,90,7.0,5,44,Rural,Software Engineer,128430,0 +56241,Female,28,Masters,11,32,34,91,93,7.0,1,13,Semi-Urban,ML Engineer,109753,0 +56242,Female,27,High School,10,68,17,64,77,3.0,5,81,Semi-Urban,Data Analyst,58294,0 +56243,Male,37,Diploma,4,62,71,33,23,8.0,1,74,Rural,HR Executive,140055,1 +56244,Female,52,Masters,9,30,60,35,53,8.0,7,49,Urban,Manager,142936,0 +56245,Male,25,Masters,17,91,13,11,69,1.0,2,34,Urban,Software Engineer,111350,0 +56246,Male,31,PhD,1,85,73,4,55,3.0,1,80,Urban,Software Engineer,87140,1 +56247,Male,53,High School,15,52,2,72,11,5.0,7,99,Rural,Manager,126886,0 +56248,Male,32,Bachelors,11,79,17,11,18,2.0,4,34,Semi-Urban,HR Executive,132831,0 +56249,Female,40,Diploma,16,45,2,22,93,2.0,0,28,Rural,HR Executive,136657,0 +56250,Female,54,High School,8,34,90,67,73,6.0,5,91,Urban,ML Engineer,48818,1 +56251,Male,40,Diploma,1,84,76,29,24,6.0,1,50,Urban,ML Engineer,102370,1 +56252,Male,31,Bachelors,18,19,64,4,83,5.0,4,59,Urban,HR Executive,68028,0 +56253,Male,24,High School,11,18,0,18,6,6.0,7,78,Semi-Urban,Manager,137398,0 +56254,Female,51,Bachelors,0,4,60,39,67,1.0,4,65,Semi-Urban,HR Executive,40184,0 +56255,Male,28,Masters,2,43,12,86,78,4.0,2,97,Semi-Urban,Manager,136904,1 +56256,Female,41,Diploma,5,83,22,50,59,8.0,4,94,Urban,HR Executive,54872,1 +56257,Female,51,Bachelors,8,26,22,91,23,9.0,6,3,Urban,Software Engineer,105096,0 +56258,Male,49,Bachelors,16,54,95,2,92,6.0,4,62,Urban,Manager,48460,0 +56259,Male,21,Bachelors,17,66,42,76,99,2.0,2,57,Urban,Manager,39458,1 +56260,Male,54,High School,11,89,22,74,64,2.0,0,57,Urban,Data Analyst,143374,1 +56261,Male,39,Diploma,12,25,72,60,21,7.0,4,12,Semi-Urban,Software Engineer,144104,0 +56262,Male,37,Masters,0,8,90,20,80,5.0,1,0,Urban,HR Executive,31198,0 +56263,Female,21,Bachelors,9,80,0,8,31,4.0,5,44,Urban,HR Executive,58271,0 +56264,Male,34,Masters,6,58,32,6,20,9.0,5,38,Semi-Urban,Software Engineer,141117,0 +56265,Male,45,High School,12,32,62,45,10,3.0,5,58,Semi-Urban,Data Analyst,84879,0 +56266,Male,23,High School,1,77,55,39,32,4.0,2,10,Rural,Data Analyst,81709,0 +56267,Female,28,Bachelors,12,97,57,89,40,1.0,5,67,Urban,HR Executive,27608,1 +56268,Male,46,Bachelors,13,86,43,25,39,1.0,4,34,Urban,Software Engineer,100269,0 +56269,Female,39,Bachelors,10,33,59,54,2,5.0,1,32,Urban,Software Engineer,95184,0 +56270,Male,51,High School,9,80,47,47,72,8.0,0,53,Urban,HR Executive,99691,0 +56271,Female,25,PhD,0,2,96,97,89,4.0,1,30,Semi-Urban,ML Engineer,111013,0 +56272,Female,53,PhD,18,12,46,68,58,4.0,6,91,Rural,Data Analyst,92601,0 +56273,Male,39,Masters,13,9,71,90,59,9.0,5,16,Urban,Data Analyst,97473,0 +56274,Male,21,Diploma,1,66,37,34,93,9.0,2,51,Urban,Data Analyst,70166,0 +56275,Female,36,High School,2,6,88,43,92,2.0,3,73,Rural,Software Engineer,132328,0 +56276,Female,54,High School,10,39,37,71,96,4.0,0,86,Rural,Manager,96731,0 +56277,Male,37,Masters,4,86,8,43,15,8.0,5,71,Rural,ML Engineer,107442,0 +56278,Male,57,High School,1,65,84,4,33,0.0,3,13,Urban,Software Engineer,48533,0 +56279,Male,29,Bachelors,3,85,94,73,99,2.0,6,43,Urban,Software Engineer,56986,1 +56280,Female,24,Diploma,10,50,89,87,58,9.0,1,72,Semi-Urban,ML Engineer,124067,1 +56281,Female,42,High School,4,98,67,65,55,1.0,6,33,Urban,Software Engineer,108673,1 +56282,Male,36,High School,1,73,98,47,39,7.0,4,2,Urban,ML Engineer,62387,0 +56283,Male,43,Masters,11,20,91,37,46,8.0,2,14,Urban,Data Analyst,44331,0 +56284,Male,38,Bachelors,2,36,75,83,37,9.0,3,25,Rural,ML Engineer,56015,0 +56285,Female,25,High School,16,41,8,41,72,8.0,0,78,Urban,Data Analyst,91470,0 +56286,Other,40,Bachelors,15,38,89,14,45,2.0,4,83,Semi-Urban,ML Engineer,131584,0 +56287,Female,45,Bachelors,8,49,73,40,11,8.0,4,35,Urban,HR Executive,62552,0 +56288,Female,31,High School,6,97,90,68,10,6.0,5,31,Urban,Data Analyst,81487,1 +56289,Male,34,Diploma,4,82,53,9,47,2.0,6,19,Urban,Software Engineer,88372,0 +56290,Other,21,Diploma,13,83,89,27,35,8.0,7,44,Urban,Software Engineer,30264,1 +56291,Female,48,High School,19,30,39,19,73,0.0,2,97,Rural,Software Engineer,75058,0 +56292,Male,37,Masters,12,50,88,34,56,4.0,6,41,Rural,ML Engineer,143616,0 +56293,Female,52,Diploma,13,40,36,87,37,2.0,0,26,Semi-Urban,Software Engineer,29915,0 +56294,Male,51,Masters,0,79,69,43,24,5.0,1,58,Rural,Manager,81702,1 +56295,Female,36,Diploma,3,1,8,4,47,6.0,6,14,Urban,HR Executive,76041,0 +56296,Other,37,Bachelors,4,74,73,28,46,0.0,4,67,Urban,Software Engineer,63055,1 +56297,Male,34,Bachelors,19,10,17,73,11,6.0,0,12,Urban,Manager,114013,0 +56298,Female,59,Diploma,1,45,77,83,36,7.0,5,47,Rural,Manager,119979,1 +56299,Male,29,Bachelors,4,76,80,69,70,0.0,5,66,Urban,ML Engineer,102130,1 +56300,Female,53,Bachelors,15,23,62,28,86,1.0,0,53,Urban,Manager,149544,0 +56301,Male,38,Bachelors,18,52,73,26,76,0.0,1,16,Semi-Urban,ML Engineer,130683,0 +56302,Female,47,Bachelors,11,1,23,16,66,8.0,6,92,Rural,Software Engineer,148398,0 +56303,Male,41,Diploma,18,75,41,79,13,2.0,3,20,Rural,Data Analyst,88431,0 +56304,Male,54,High School,1,60,15,49,51,6.0,0,98,Rural,Manager,129549,0 +56305,Male,51,Diploma,19,87,99,28,13,6.0,6,35,Urban,Data Analyst,87947,1 +56306,Male,35,Bachelors,17,85,96,44,83,7.0,1,91,Urban,Software Engineer,80878,1 +56307,Other,49,Bachelors,17,12,58,21,81,5.0,7,72,Urban,ML Engineer,28803,0 +56308,Male,57,Diploma,16,67,3,48,95,2.0,0,72,Urban,Manager,41169,0 +56309,Male,46,Bachelors,2,82,86,18,0,9.0,5,13,Urban,Manager,66687,0 +56310,Male,45,Masters,18,24,50,34,18,3.0,0,63,Semi-Urban,HR Executive,138707,0 +56311,Male,43,High School,11,14,20,29,49,8.0,7,72,Rural,ML Engineer,127501,0 +56312,Male,48,Bachelors,11,89,36,66,17,0.0,2,65,Urban,Manager,52198,1 +56313,Other,24,Diploma,2,45,62,28,58,0.0,0,42,Urban,Manager,42588,0 +56314,Male,28,High School,4,9,70,10,52,2.0,2,12,Rural,Manager,56821,0 +56315,Female,49,High School,8,57,10,65,3,4.0,3,74,Rural,HR Executive,56686,0 +56316,Female,35,High School,13,82,33,99,83,1.0,7,14,Urban,Data Analyst,55764,0 +56317,Female,26,High School,17,8,5,72,20,7.0,3,82,Urban,ML Engineer,118498,0 +56318,Female,23,Bachelors,0,70,78,60,42,6.0,6,17,Urban,ML Engineer,32325,0 +56319,Female,44,Bachelors,6,68,11,62,93,2.0,2,11,Rural,Data Analyst,35807,0 +56320,Male,55,Diploma,10,41,38,0,81,6.0,6,56,Urban,Data Analyst,91970,0 +56321,Female,35,Bachelors,7,99,54,81,68,2.0,0,50,Urban,Software Engineer,24041,1 +56322,Male,26,Bachelors,16,76,31,2,50,0.0,2,90,Urban,HR Executive,62594,0 +56323,Male,54,High School,6,74,35,49,43,9.0,0,83,Urban,Data Analyst,78446,1 +56324,Female,30,Masters,19,94,5,99,3,8.0,2,63,Urban,Software Engineer,39110,1 +56325,Male,52,Bachelors,3,66,12,89,66,4.0,6,28,Semi-Urban,HR Executive,59431,0 +56326,Male,59,High School,9,24,76,58,38,7.0,7,19,Semi-Urban,HR Executive,97177,0 +56327,Female,50,High School,1,96,9,69,89,6.0,7,66,Urban,ML Engineer,135551,0 +56328,Male,48,Diploma,13,25,19,97,39,3.0,4,84,Semi-Urban,Software Engineer,101969,0 +56329,Male,31,Bachelors,11,21,83,68,82,1.0,1,59,Urban,Data Analyst,27866,0 +56330,Other,21,Masters,10,68,5,83,76,4.0,3,20,Semi-Urban,Manager,121765,0 +56331,Male,35,Diploma,13,37,74,84,57,8.0,7,39,Urban,HR Executive,129495,0 +56332,Male,39,PhD,11,64,13,53,61,1.0,5,2,Urban,ML Engineer,94136,0 +56333,Female,46,Diploma,15,62,5,32,52,9.0,5,2,Urban,Software Engineer,81266,0 +56334,Female,38,Bachelors,16,65,29,74,62,1.0,4,58,Urban,Data Analyst,99040,0 +56335,Male,43,High School,1,99,82,43,70,5.0,6,44,Urban,ML Engineer,28252,1 +56336,Male,33,Masters,8,62,82,60,26,5.0,4,20,Urban,ML Engineer,78541,0 +56337,Female,55,Masters,19,42,41,2,91,9.0,2,65,Urban,HR Executive,149093,0 +56338,Male,51,Bachelors,0,89,30,4,80,9.0,1,21,Urban,Software Engineer,34212,0 +56339,Male,59,Masters,11,95,67,36,85,2.0,5,15,Rural,ML Engineer,148508,0 +56340,Male,40,Masters,4,53,55,32,57,8.0,0,71,Rural,Data Analyst,53634,0 +56341,Female,39,Bachelors,18,79,16,68,64,8.0,4,3,Urban,HR Executive,86954,0 +56342,Male,45,Bachelors,7,88,89,89,84,9.0,2,10,Urban,Data Analyst,106361,1 +56343,Male,53,Diploma,15,75,82,21,90,3.0,0,83,Semi-Urban,Software Engineer,60848,1 +56344,Male,49,High School,13,24,60,66,0,9.0,7,20,Rural,Manager,124930,0 +56345,Male,41,Bachelors,11,48,90,6,92,0.0,5,45,Urban,Data Analyst,149114,0 +56346,Male,21,Bachelors,17,4,30,44,6,5.0,6,9,Rural,Manager,78161,0 +56347,Male,59,High School,16,22,22,62,19,2.0,0,41,Semi-Urban,Manager,34964,0 +56348,Female,34,PhD,15,54,1,74,81,4.0,0,54,Urban,ML Engineer,117325,0 +56349,Female,49,Diploma,10,14,29,90,93,9.0,1,48,Urban,Manager,21084,0 +56350,Female,45,Masters,17,70,40,42,21,8.0,5,82,Urban,HR Executive,114136,0 +56351,Male,35,Bachelors,7,57,30,57,54,7.0,2,41,Urban,HR Executive,96090,0 +56352,Male,27,PhD,1,15,54,50,97,0.0,0,79,Urban,ML Engineer,73170,0 +56353,Male,28,Diploma,12,48,15,23,32,3.0,6,70,Urban,Manager,24824,0 +56354,Male,58,Bachelors,19,63,88,35,82,9.0,1,89,Urban,Software Engineer,58691,1 +56355,Female,33,PhD,17,34,74,83,15,5.0,7,18,Semi-Urban,Software Engineer,113386,0 +56356,Male,30,High School,7,19,11,10,95,1.0,6,92,Urban,Software Engineer,54289,0 +56357,Other,22,PhD,4,46,64,73,76,3.0,2,12,Semi-Urban,HR Executive,147089,0 +56358,Female,38,Masters,16,70,35,56,56,2.0,6,37,Urban,Software Engineer,103549,0 +56359,Other,34,Masters,5,71,6,22,68,6.0,6,90,Rural,ML Engineer,50189,0 +56360,Male,57,Bachelors,6,14,54,67,83,6.0,4,85,Urban,HR Executive,116458,0 +56361,Male,59,Masters,8,69,20,2,61,0.0,7,2,Rural,HR Executive,109902,0 +56362,Male,38,Bachelors,4,50,89,71,74,2.0,1,92,Urban,HR Executive,148882,1 +56363,Female,39,Diploma,8,51,10,21,95,4.0,4,40,Rural,Data Analyst,46426,0 +56364,Other,33,High School,0,26,15,35,44,8.0,6,49,Urban,HR Executive,94439,0 +56365,Male,56,Diploma,11,9,68,41,61,3.0,5,80,Semi-Urban,Software Engineer,126321,0 +56366,Male,24,Masters,7,37,97,9,36,4.0,7,28,Urban,Software Engineer,97932,0 +56367,Male,32,High School,17,6,79,99,29,9.0,7,4,Urban,Manager,133062,0 +56368,Other,59,Bachelors,13,56,97,31,91,5.0,0,82,Semi-Urban,HR Executive,65598,1 +56369,Male,52,High School,9,61,63,11,23,8.0,4,18,Urban,Manager,100170,0 +56370,Female,39,Bachelors,14,35,99,92,51,4.0,4,9,Rural,Software Engineer,65769,0 +56371,Male,44,Bachelors,10,12,50,50,5,5.0,3,14,Semi-Urban,Manager,30224,0 +56372,Female,37,Diploma,1,11,11,13,10,1.0,6,57,Urban,HR Executive,103102,0 +56373,Male,45,Diploma,4,4,50,75,45,4.0,4,35,Urban,Data Analyst,91034,0 +56374,Male,50,Bachelors,17,95,60,9,81,8.0,2,54,Urban,HR Executive,38486,0 +56375,Female,21,Masters,13,29,0,61,20,3.0,0,48,Urban,ML Engineer,26697,0 +56376,Female,22,High School,11,19,43,57,49,8.0,5,88,Urban,Software Engineer,30850,0 +56377,Male,48,Masters,9,6,97,21,96,2.0,6,37,Semi-Urban,HR Executive,106640,0 +56378,Female,33,High School,4,64,81,15,10,2.0,3,94,Rural,Data Analyst,79704,1 +56379,Male,40,Diploma,18,69,4,28,22,5.0,6,56,Urban,Software Engineer,123077,0 +56380,Female,51,Bachelors,18,19,57,30,25,4.0,1,89,Urban,Software Engineer,74286,0 +56381,Male,31,Masters,14,52,53,57,96,9.0,3,51,Urban,Manager,123398,0 +56382,Male,59,Diploma,9,25,88,34,28,5.0,6,88,Urban,ML Engineer,129499,1 +56383,Male,43,Bachelors,18,85,15,42,38,4.0,4,56,Rural,HR Executive,25009,0 +56384,Male,57,Bachelors,3,68,91,42,74,5.0,3,67,Urban,Software Engineer,138329,1 +56385,Male,34,High School,7,62,96,49,31,3.0,2,22,Urban,Manager,22060,0 +56386,Male,34,Bachelors,7,70,98,51,9,6.0,2,4,Urban,ML Engineer,71010,0 +56387,Male,46,Bachelors,1,72,45,42,88,3.0,3,18,Semi-Urban,Software Engineer,117887,0 +56388,Male,37,High School,1,95,98,18,42,7.0,7,63,Urban,HR Executive,84781,1 +56389,Male,42,Diploma,11,68,89,23,42,2.0,1,71,Rural,Data Analyst,121079,1 +56390,Female,43,Diploma,18,27,7,4,78,2.0,2,83,Rural,ML Engineer,73623,0 +56391,Female,51,Bachelors,11,91,72,92,43,1.0,1,94,Urban,Manager,142350,1 +56392,Male,43,Bachelors,2,76,22,46,16,7.0,5,79,Rural,ML Engineer,100759,0 +56393,Male,50,Diploma,4,61,15,98,69,5.0,2,30,Rural,Manager,94961,0 +56394,Male,25,Bachelors,5,40,16,92,41,5.0,2,10,Semi-Urban,Manager,57247,0 +56395,Female,27,High School,2,72,73,34,67,8.0,3,52,Urban,Data Analyst,137127,0 +56396,Other,33,Masters,14,7,11,28,28,7.0,0,0,Urban,Manager,98835,0 +56397,Male,47,Bachelors,7,81,94,77,47,6.0,6,69,Urban,Software Engineer,46476,1 +56398,Female,30,High School,14,45,88,73,54,1.0,4,10,Rural,Manager,144457,0 +56399,Male,21,Diploma,16,2,61,49,24,8.0,0,87,Rural,Manager,40405,0 +56400,Male,50,Masters,12,27,53,96,70,2.0,5,68,Urban,HR Executive,104647,1 +56401,Male,43,High School,13,71,37,2,71,9.0,2,88,Urban,ML Engineer,103089,0 +56402,Male,53,Bachelors,19,44,72,67,19,8.0,3,95,Rural,Manager,149998,1 +56403,Female,36,Diploma,2,92,72,99,49,9.0,3,13,Urban,Data Analyst,36081,1 +56404,Female,26,Bachelors,15,35,90,49,19,6.0,4,34,Urban,Software Engineer,111232,0 +56405,Female,39,PhD,0,49,64,70,7,2.0,7,37,Rural,Manager,43222,0 +56406,Male,44,Bachelors,15,39,5,20,36,3.0,6,64,Semi-Urban,Manager,61831,0 +56407,Male,36,Diploma,18,5,5,22,24,3.0,5,73,Urban,HR Executive,123607,0 +56408,Male,24,High School,12,15,75,32,98,4.0,3,62,Urban,Data Analyst,122053,0 +56409,Male,31,Masters,8,35,2,29,70,5.0,6,62,Semi-Urban,Software Engineer,139933,0 +56410,Female,28,Masters,6,84,12,91,19,9.0,3,81,Rural,Data Analyst,61038,1 +56411,Female,29,Bachelors,5,98,78,39,6,0.0,4,95,Semi-Urban,Data Analyst,79624,1 +56412,Male,22,Diploma,16,61,18,25,14,0.0,4,68,Urban,ML Engineer,61371,0 +56413,Other,29,Bachelors,6,83,10,44,18,7.0,2,69,Urban,Manager,77902,0 +56414,Female,47,Masters,17,26,44,23,87,7.0,2,85,Urban,Software Engineer,56115,0 +56415,Female,25,Masters,2,10,90,7,66,0.0,0,24,Urban,Data Analyst,76214,0 +56416,Other,36,Masters,2,50,59,54,91,1.0,3,39,Urban,Data Analyst,66892,0 +56417,Male,53,Bachelors,3,71,8,77,21,4.0,5,32,Urban,ML Engineer,147856,0 +56418,Male,47,Bachelors,18,92,24,90,43,4.0,5,5,Urban,Data Analyst,129823,0 +56419,Female,52,Diploma,15,14,88,12,30,0.0,6,50,Urban,Manager,103260,0 +56420,Female,53,High School,0,0,97,89,19,9.0,2,43,Rural,ML Engineer,98874,0 +56421,Male,46,High School,0,25,5,20,17,3.0,5,26,Semi-Urban,ML Engineer,60681,0 +56422,Male,45,Masters,13,98,47,50,55,7.0,0,20,Urban,Software Engineer,76346,0 +56423,Male,51,Diploma,9,34,48,10,2,2.0,0,61,Urban,Data Analyst,94288,0 +56424,Male,28,Diploma,6,94,27,27,15,0.0,7,29,Urban,Software Engineer,140200,0 +56425,Female,23,Masters,3,80,62,88,98,0.0,0,9,Urban,HR Executive,113845,0 +56426,Male,53,Diploma,17,12,50,92,98,2.0,0,27,Semi-Urban,Data Analyst,102814,0 +56427,Female,59,Masters,15,86,80,59,41,7.0,5,48,Semi-Urban,Software Engineer,127528,1 +56428,Female,42,Bachelors,15,76,14,28,33,4.0,5,72,Urban,Software Engineer,108336,0 +56429,Female,33,Bachelors,12,35,8,74,82,6.0,2,84,Urban,Manager,24936,0 +56430,Male,54,Bachelors,19,85,98,0,8,8.0,5,25,Urban,ML Engineer,134284,0 +56431,Female,29,Masters,6,27,46,6,43,9.0,1,57,Semi-Urban,Manager,107150,0 +56432,Other,57,Bachelors,7,10,76,51,53,2.0,1,20,Semi-Urban,Software Engineer,113925,0 +56433,Male,42,Bachelors,17,92,96,31,80,3.0,5,39,Semi-Urban,Software Engineer,78227,1 +56434,Male,23,Diploma,18,50,80,67,18,3.0,0,38,Rural,Manager,149718,1 +56435,Female,38,Diploma,12,36,87,69,50,5.0,5,31,Semi-Urban,HR Executive,75883,0 +56436,Female,21,Diploma,4,67,93,69,59,6.0,5,25,Urban,ML Engineer,24074,1 +56437,Female,41,Diploma,2,76,81,63,24,0.0,2,73,Urban,Software Engineer,51353,1 +56438,Other,35,Bachelors,16,86,39,5,88,5.0,5,93,Rural,Data Analyst,147958,0 +56439,Female,22,High School,5,35,46,26,76,8.0,4,76,Urban,HR Executive,40784,0 +56440,Male,32,Masters,5,13,81,17,49,8.0,1,39,Urban,Software Engineer,40079,0 +56441,Male,27,Bachelors,2,80,0,8,97,0.0,3,92,Semi-Urban,Software Engineer,33056,0 +56442,Male,31,Masters,2,8,11,56,14,8.0,2,19,Urban,ML Engineer,113167,0 +56443,Male,22,Bachelors,17,72,97,28,4,5.0,1,33,Urban,Data Analyst,131193,0 +56444,Male,35,Diploma,14,96,33,24,23,2.0,3,43,Semi-Urban,Data Analyst,39248,0 +56445,Male,53,Bachelors,2,51,43,76,1,3.0,4,93,Urban,Data Analyst,143161,1 +56446,Female,39,High School,10,88,67,49,32,2.0,0,38,Urban,ML Engineer,97778,1 +56447,Male,49,Bachelors,14,50,19,45,28,9.0,1,5,Urban,ML Engineer,47871,0 +56448,Male,38,Diploma,1,8,80,26,24,4.0,5,55,Urban,Software Engineer,82915,0 +56449,Female,58,High School,5,22,24,79,29,2.0,3,90,Rural,ML Engineer,53610,0 +56450,Female,21,Bachelors,18,48,62,87,49,4.0,6,83,Urban,ML Engineer,112480,1 +56451,Female,33,Masters,3,84,15,6,50,0.0,3,32,Urban,Software Engineer,143691,0 +56452,Male,25,Masters,17,80,85,11,74,7.0,3,90,Urban,ML Engineer,121645,1 +56453,Female,21,Bachelors,15,19,84,6,28,2.0,5,21,Rural,HR Executive,71402,0 +56454,Male,47,Bachelors,13,73,27,48,48,6.0,1,25,Semi-Urban,Manager,68068,0 +56455,Female,27,Bachelors,18,57,54,50,47,7.0,2,29,Urban,HR Executive,140983,0 +56456,Female,45,Bachelors,3,95,12,18,87,7.0,6,25,Semi-Urban,ML Engineer,54748,0 +56457,Male,31,Bachelors,11,18,50,58,93,6.0,5,2,Urban,Manager,110319,0 +56458,Female,43,Bachelors,15,64,42,60,52,3.0,0,40,Urban,Data Analyst,133482,0 +56459,Female,32,Masters,13,75,49,4,7,6.0,2,89,Semi-Urban,Data Analyst,105152,0 +56460,Female,22,Masters,9,29,19,24,30,4.0,1,71,Urban,Software Engineer,29493,0 +56461,Male,58,High School,14,79,59,49,47,9.0,6,74,Semi-Urban,HR Executive,91277,1 +56462,Female,38,Diploma,19,8,53,52,8,5.0,0,90,Semi-Urban,Data Analyst,131755,0 +56463,Male,57,Masters,19,49,10,81,25,4.0,6,42,Urban,Software Engineer,101660,0 +56464,Male,47,High School,19,66,97,44,14,2.0,2,81,Urban,HR Executive,84372,1 +56465,Female,57,Diploma,9,45,36,72,81,4.0,6,69,Urban,HR Executive,76475,0 +56466,Female,40,PhD,2,97,14,30,53,9.0,6,40,Urban,Software Engineer,109110,0 +56467,Male,46,Masters,3,80,77,75,73,6.0,1,31,Urban,Software Engineer,64806,1 +56468,Male,26,Bachelors,1,93,44,34,39,5.0,1,56,Semi-Urban,Data Analyst,40938,0 +56469,Female,36,Bachelors,1,93,67,40,2,2.0,4,50,Urban,Manager,70824,1 +56470,Male,31,Diploma,9,66,87,90,42,7.0,2,60,Urban,Manager,70371,1 +56471,Male,26,High School,1,52,53,68,7,5.0,0,33,Rural,Data Analyst,24299,0 +56472,Male,58,Masters,18,74,90,41,67,5.0,6,72,Urban,Software Engineer,147774,1 +56473,Female,53,Masters,8,51,83,86,57,7.0,4,0,Urban,ML Engineer,56045,0 +56474,Male,59,Bachelors,16,57,46,65,5,1.0,6,31,Urban,ML Engineer,117515,0 +56475,Female,55,High School,1,53,36,22,4,9.0,1,3,Semi-Urban,ML Engineer,93304,0 +56476,Male,48,Bachelors,4,83,84,63,36,7.0,3,52,Urban,Manager,122442,1 +56477,Female,28,Bachelors,18,59,45,84,81,2.0,1,49,Urban,Data Analyst,117622,0 +56478,Female,48,Bachelors,10,84,36,13,26,4.0,3,39,Urban,ML Engineer,49570,0 +56479,Male,54,Bachelors,18,95,16,48,65,0.0,1,69,Urban,ML Engineer,57699,0 +56480,Male,45,Diploma,3,72,58,76,29,1.0,1,24,Urban,Software Engineer,23881,0 +56481,Female,23,Masters,19,17,34,13,45,7.0,2,6,Urban,Manager,77876,0 +56482,Male,29,Masters,3,94,86,93,93,7.0,2,75,Urban,Software Engineer,29707,1 +56483,Male,32,Diploma,5,32,4,85,41,0.0,6,97,Urban,ML Engineer,78596,0 +56484,Male,37,Diploma,19,37,89,39,12,9.0,0,74,Urban,HR Executive,140640,1 +56485,Female,52,Masters,7,54,74,86,79,6.0,7,39,Urban,Manager,113410,1 +56486,Male,33,Bachelors,3,46,60,47,41,7.0,7,46,Rural,Manager,81745,0 +56487,Male,29,Diploma,8,57,76,98,84,5.0,7,9,Urban,Data Analyst,95642,1 +56488,Female,55,High School,15,36,82,26,58,6.0,4,61,Urban,HR Executive,38891,0 +56489,Other,40,Masters,15,77,17,76,77,0.0,2,35,Urban,Software Engineer,22662,0 +56490,Male,47,Bachelors,18,63,5,18,23,7.0,6,94,Urban,Manager,73691,0 +56491,Male,36,Masters,11,69,44,32,92,9.0,5,99,Urban,Data Analyst,120720,1 +56492,Female,21,Diploma,5,52,20,47,34,7.0,6,45,Semi-Urban,HR Executive,87802,0 +56493,Female,23,Diploma,7,71,36,53,92,6.0,6,72,Semi-Urban,ML Engineer,147749,0 +56494,Male,41,Diploma,1,36,82,52,51,3.0,0,68,Urban,Manager,87684,1 +56495,Male,28,Bachelors,2,13,47,53,67,7.0,0,26,Urban,HR Executive,101230,0 +56496,Male,30,PhD,3,93,54,89,0,6.0,7,91,Urban,Manager,122200,1 +56497,Female,48,Masters,15,73,8,7,88,7.0,7,89,Urban,Data Analyst,130763,0 +56498,Female,55,High School,19,19,38,3,25,0.0,6,39,Urban,Software Engineer,85952,0 +56499,Male,40,Diploma,8,49,53,61,97,8.0,7,35,Urban,Data Analyst,82752,0 +56500,Male,34,Bachelors,5,1,79,55,76,9.0,2,80,Urban,Data Analyst,149603,0 +56501,Male,47,Diploma,18,28,29,76,99,6.0,7,58,Urban,HR Executive,127241,0 +56502,Female,36,Bachelors,1,87,30,63,77,9.0,5,5,Urban,ML Engineer,51923,0 +56503,Female,42,Diploma,15,28,36,41,4,6.0,3,95,Semi-Urban,Data Analyst,137211,0 +56504,Male,37,Diploma,13,8,98,81,84,2.0,5,82,Rural,ML Engineer,147456,1 +56505,Male,21,Masters,0,11,86,91,88,8.0,4,17,Urban,Manager,94404,0 +56506,Female,32,Bachelors,1,60,53,93,11,6.0,0,76,Rural,Software Engineer,118518,1 +56507,Male,33,Bachelors,12,35,66,14,22,7.0,7,11,Urban,Manager,69760,0 +56508,Male,43,Diploma,9,14,45,58,32,5.0,4,51,Rural,ML Engineer,112945,0 +56509,Female,21,High School,7,77,44,1,12,7.0,7,79,Rural,HR Executive,58995,0 +56510,Male,50,Masters,13,16,8,27,41,3.0,6,45,Semi-Urban,Software Engineer,51325,0 +56511,Female,57,Bachelors,15,5,39,10,65,1.0,5,99,Urban,ML Engineer,93635,0 +56512,Female,58,Bachelors,12,41,76,92,97,8.0,5,50,Semi-Urban,Manager,26629,1 +56513,Female,55,Bachelors,15,75,11,86,77,1.0,4,75,Semi-Urban,Software Engineer,34482,1 +56514,Male,32,PhD,19,36,45,69,99,8.0,0,26,Urban,Manager,95509,0 +56515,Male,23,Masters,12,22,84,69,25,6.0,1,25,Urban,Software Engineer,148584,0 +56516,Male,23,PhD,14,44,35,72,44,3.0,6,40,Rural,Software Engineer,90530,0 +56517,Male,49,PhD,14,25,85,82,66,4.0,7,54,Semi-Urban,Manager,43772,1 +56518,Female,56,Bachelors,1,42,59,96,75,7.0,1,31,Urban,HR Executive,68518,0 +56519,Male,22,PhD,14,16,25,51,90,1.0,6,66,Urban,Manager,49500,0 +56520,Female,51,Masters,9,27,79,26,39,8.0,3,99,Rural,HR Executive,93770,0 +56521,Male,30,Masters,11,62,64,60,97,9.0,6,89,Urban,ML Engineer,138988,1 +56522,Male,55,Masters,12,4,98,55,33,4.0,6,74,Rural,Software Engineer,100942,0 +56523,Male,52,Masters,7,75,19,71,80,2.0,4,49,Semi-Urban,ML Engineer,58463,0 +56524,Female,35,Masters,18,24,53,92,69,0.0,6,14,Semi-Urban,Data Analyst,74046,0 +56525,Female,59,Bachelors,19,73,9,43,0,3.0,3,63,Semi-Urban,ML Engineer,126634,0 +56526,Male,33,Bachelors,6,68,61,16,75,2.0,1,87,Rural,Software Engineer,91551,0 +56527,Female,42,Bachelors,18,73,99,14,8,5.0,7,15,Urban,Software Engineer,59209,0 +56528,Male,51,Masters,11,40,29,18,13,4.0,2,20,Semi-Urban,Software Engineer,95084,0 +56529,Male,30,Bachelors,5,18,44,49,71,1.0,2,78,Urban,Data Analyst,45472,0 +56530,Male,59,Bachelors,16,86,23,27,11,3.0,1,94,Urban,ML Engineer,60440,0 +56531,Male,39,PhD,3,44,30,88,58,1.0,1,16,Urban,Manager,101440,0 +56532,Female,57,Masters,14,39,5,28,73,3.0,1,58,Rural,HR Executive,56313,0 +56533,Male,30,Diploma,14,14,67,40,95,1.0,0,40,Semi-Urban,Software Engineer,21583,0 +56534,Female,28,High School,3,73,43,2,25,6.0,3,11,Urban,HR Executive,134134,0 +56535,Male,57,Bachelors,3,28,91,99,40,8.0,2,51,Rural,ML Engineer,60661,1 +56536,Other,51,Masters,16,70,98,85,61,8.0,0,94,Urban,Data Analyst,34253,1 +56537,Male,48,Bachelors,12,72,80,90,71,3.0,6,89,Rural,Data Analyst,38704,1 +56538,Male,44,Bachelors,11,79,84,26,65,6.0,6,55,Urban,HR Executive,138142,1 +56539,Other,25,Masters,0,88,12,37,86,5.0,6,69,Urban,HR Executive,78254,0 +56540,Male,43,Masters,12,55,27,2,45,1.0,3,6,Semi-Urban,Software Engineer,116990,0 +56541,Female,44,Diploma,7,4,4,83,95,2.0,4,8,Semi-Urban,Manager,52487,0 +56542,Male,58,Bachelors,12,42,87,93,23,6.0,6,90,Rural,HR Executive,148225,1 +56543,Female,30,High School,14,93,0,88,20,7.0,0,5,Urban,HR Executive,112559,0 +56544,Male,48,High School,19,56,92,16,16,6.0,7,53,Urban,Data Analyst,44824,0 +56545,Female,41,Masters,6,16,34,32,14,4.0,7,73,Semi-Urban,HR Executive,101551,0 +56546,Male,52,Diploma,9,57,70,77,71,3.0,3,35,Urban,Data Analyst,130894,1 +56547,Female,30,High School,9,50,38,59,99,9.0,0,76,Rural,HR Executive,39809,0 +56548,Male,41,Diploma,13,7,84,69,46,2.0,2,76,Urban,ML Engineer,45406,1 +56549,Male,40,Bachelors,17,58,26,76,74,1.0,5,64,Semi-Urban,Software Engineer,103736,0 +56550,Male,25,Bachelors,11,16,33,37,12,5.0,3,20,Semi-Urban,Data Analyst,91404,0 +56551,Other,57,High School,7,5,76,87,94,1.0,0,94,Semi-Urban,HR Executive,76311,1 +56552,Female,23,Bachelors,6,76,60,50,6,3.0,6,5,Semi-Urban,Software Engineer,144441,0 +56553,Male,43,Masters,6,0,76,49,99,7.0,4,24,Rural,ML Engineer,20819,0 +56554,Female,55,Bachelors,3,65,42,62,8,1.0,2,91,Semi-Urban,Data Analyst,133442,1 +56555,Male,42,Masters,9,50,70,9,84,8.0,2,36,Urban,Software Engineer,123557,0 +56556,Female,41,Masters,10,19,81,21,72,9.0,6,50,Urban,ML Engineer,130227,0 +56557,Male,27,Masters,13,5,72,25,22,7.0,0,76,Urban,Data Analyst,47395,0 +56558,Male,39,Diploma,16,36,60,81,74,1.0,5,9,Urban,Software Engineer,119592,0 +56559,Male,58,Bachelors,7,71,59,17,98,4.0,5,90,Urban,Manager,101285,1 +56560,Female,27,Bachelors,13,1,96,92,17,9.0,7,36,Semi-Urban,Data Analyst,42893,0 +56561,Male,50,Diploma,12,19,8,56,83,2.0,6,85,Urban,Data Analyst,145416,0 +56562,Male,55,Bachelors,11,80,16,9,77,6.0,1,62,Urban,Data Analyst,116929,0 +56563,Female,28,Bachelors,16,23,26,53,44,1.0,7,41,Urban,Data Analyst,90838,0 +56564,Male,45,PhD,10,34,77,81,26,4.0,1,65,Rural,HR Executive,38227,1 +56565,Male,58,Diploma,12,51,79,10,43,2.0,0,24,Rural,Manager,56262,0 +56566,Female,56,Masters,17,34,90,68,19,7.0,1,50,Rural,Data Analyst,20801,1 +56567,Female,32,Masters,16,20,2,78,47,6.0,2,78,Urban,Software Engineer,143137,0 +56568,Female,55,Masters,12,40,41,67,7,8.0,1,12,Semi-Urban,Manager,61293,0 +56569,Male,35,PhD,1,54,10,62,8,3.0,2,69,Rural,Data Analyst,109198,0 +56570,Male,55,Bachelors,15,60,21,50,24,4.0,7,94,Semi-Urban,ML Engineer,111199,0 +56571,Female,53,Bachelors,8,84,0,63,79,8.0,7,7,Rural,Manager,66351,0 +56572,Male,58,PhD,6,70,69,1,38,5.0,3,1,Urban,ML Engineer,122057,0 +56573,Male,24,Diploma,10,59,19,40,60,1.0,6,75,Rural,Software Engineer,84054,0 +56574,Male,40,Masters,17,74,98,38,93,4.0,6,71,Semi-Urban,ML Engineer,31717,1 +56575,Female,31,Bachelors,3,2,86,45,9,8.0,5,26,Semi-Urban,Manager,62079,0 +56576,Male,57,Diploma,10,19,1,60,7,1.0,5,38,Urban,ML Engineer,64981,0 +56577,Female,40,Diploma,6,37,10,45,80,0.0,4,7,Urban,Data Analyst,79022,0 +56578,Male,55,Bachelors,13,3,15,95,52,8.0,5,41,Urban,Software Engineer,109960,0 +56579,Female,31,Masters,19,4,42,35,81,3.0,3,97,Rural,Software Engineer,48714,0 +56580,Male,59,Bachelors,16,6,39,77,87,4.0,5,74,Rural,Data Analyst,42726,0 +56581,Male,46,Diploma,4,94,16,72,96,3.0,7,90,Urban,Data Analyst,74254,1 +56582,Female,56,Bachelors,2,26,62,93,58,0.0,3,9,Urban,Manager,79245,0 +56583,Female,41,Masters,18,34,17,3,99,1.0,5,42,Urban,ML Engineer,71214,0 +56584,Male,28,Bachelors,9,93,41,90,33,8.0,2,55,Urban,Software Engineer,83548,1 +56585,Male,27,Masters,16,52,39,75,16,6.0,1,5,Semi-Urban,Data Analyst,31924,0 +56586,Female,31,Bachelors,17,10,36,15,46,8.0,7,76,Urban,Data Analyst,93853,0 +56587,Male,50,Bachelors,2,47,21,8,70,3.0,5,3,Semi-Urban,HR Executive,45256,0 +56588,Other,42,Diploma,3,89,8,45,94,8.0,3,91,Urban,HR Executive,118641,0 +56589,Female,45,Diploma,1,59,61,51,82,1.0,6,59,Urban,Manager,50142,0 +56590,Female,54,Masters,15,61,31,19,38,9.0,7,84,Urban,ML Engineer,52343,0 +56591,Male,51,Bachelors,0,5,78,57,27,9.0,4,0,Urban,Manager,23572,0 +56592,Male,31,Diploma,8,64,51,31,78,9.0,0,78,Urban,HR Executive,26923,0 +56593,Male,41,PhD,13,62,17,75,3,1.0,3,35,Urban,Data Analyst,21502,0 +56594,Male,27,Bachelors,16,53,34,15,68,3.0,4,46,Urban,Manager,94000,0 +56595,Male,30,Masters,5,86,31,99,39,8.0,2,74,Rural,Manager,95562,1 +56596,Male,57,Bachelors,4,68,90,1,81,3.0,7,7,Semi-Urban,HR Executive,27348,0 +56597,Male,34,High School,16,79,44,80,34,9.0,7,32,Urban,Data Analyst,35583,1 +56598,Male,22,Diploma,17,15,8,42,48,5.0,3,71,Urban,Data Analyst,114813,0 +56599,Male,56,Diploma,15,99,99,88,85,1.0,7,47,Semi-Urban,Manager,72500,1 +56600,Female,26,Diploma,5,6,99,2,17,4.0,4,24,Rural,ML Engineer,48316,0 +56601,Female,58,Bachelors,17,88,66,29,44,6.0,4,36,Rural,Manager,136917,0 +56602,Female,21,Bachelors,4,30,83,97,98,2.0,6,35,Urban,HR Executive,117617,1 +56603,Male,55,Masters,13,90,68,52,20,4.0,3,45,Urban,ML Engineer,23035,1 +56604,Female,57,Masters,3,16,47,75,22,7.0,6,53,Semi-Urban,Software Engineer,48524,0 +56605,Male,22,Bachelors,17,13,80,71,93,2.0,2,58,Rural,Software Engineer,62304,0 +56606,Female,56,High School,16,65,56,33,79,5.0,4,37,Rural,ML Engineer,135265,0 +56607,Male,41,High School,12,87,18,49,48,4.0,5,4,Urban,HR Executive,22964,0 +56608,Female,50,Diploma,12,6,17,3,89,3.0,5,90,Semi-Urban,Software Engineer,91250,0 +56609,Male,51,Bachelors,12,14,42,59,54,9.0,0,96,Urban,Manager,141597,0 +56610,Male,37,Diploma,9,61,70,75,13,2.0,0,27,Rural,ML Engineer,73913,0 +56611,Male,46,Bachelors,4,32,32,74,10,1.0,1,87,Rural,Manager,135525,0 +56612,Male,51,Masters,2,62,23,43,88,6.0,7,13,Rural,Data Analyst,27452,0 +56613,Male,56,Bachelors,17,9,87,13,41,6.0,0,70,Semi-Urban,HR Executive,139968,0 +56614,Female,59,High School,6,75,84,11,24,4.0,3,51,Urban,Manager,122172,0 +56615,Female,21,Masters,17,14,49,43,72,9.0,1,70,Urban,Software Engineer,60733,0 +56616,Male,53,Bachelors,16,41,4,7,90,9.0,6,37,Semi-Urban,ML Engineer,115285,0 +56617,Female,56,PhD,17,85,70,10,18,7.0,1,61,Rural,Data Analyst,111792,0 +56618,Male,44,High School,6,60,14,52,3,0.0,3,80,Urban,Software Engineer,75911,0 +56619,Male,48,Bachelors,0,16,61,30,46,7.0,0,99,Urban,ML Engineer,36272,0 +56620,Female,41,Diploma,19,80,10,85,7,5.0,0,18,Urban,Data Analyst,67215,0 +56621,Female,27,Diploma,11,95,9,63,80,8.0,2,40,Semi-Urban,HR Executive,56082,0 +56622,Female,36,High School,11,80,43,62,5,6.0,6,18,Rural,Data Analyst,38379,0 +56623,Male,23,High School,14,5,14,48,38,5.0,1,27,Rural,Software Engineer,37790,0 +56624,Female,51,Bachelors,0,74,65,11,2,7.0,2,41,Rural,Software Engineer,81259,0 +56625,Female,40,High School,11,43,6,19,15,4.0,5,28,Urban,Data Analyst,115950,0 +56626,Male,45,Diploma,15,68,94,61,91,7.0,1,18,Urban,ML Engineer,21141,1 +56627,Other,23,Diploma,16,35,51,34,51,8.0,6,9,Semi-Urban,Software Engineer,132549,0 +56628,Male,42,PhD,5,23,12,8,97,6.0,6,81,Urban,Manager,129607,0 +56629,Male,22,Bachelors,5,79,72,93,95,7.0,6,69,Semi-Urban,ML Engineer,36363,1 +56630,Female,39,Masters,5,23,96,93,40,9.0,0,26,Urban,Software Engineer,76625,0 +56631,Male,57,Masters,16,38,70,72,66,2.0,2,4,Urban,Manager,23580,0 +56632,Male,50,High School,13,26,63,52,95,3.0,6,8,Urban,Data Analyst,47347,0 +56633,Male,30,Bachelors,11,20,10,32,45,4.0,3,25,Urban,Data Analyst,73578,0 +56634,Male,24,Diploma,19,90,31,90,58,9.0,6,77,Semi-Urban,Data Analyst,55135,1 +56635,Male,48,High School,4,79,64,41,94,3.0,4,20,Urban,Manager,29739,0 +56636,Male,23,Bachelors,15,72,42,17,81,5.0,6,70,Semi-Urban,ML Engineer,35438,0 +56637,Male,52,Bachelors,2,64,3,89,51,4.0,0,39,Urban,HR Executive,76831,0 +56638,Male,21,Bachelors,5,98,79,89,38,0.0,5,26,Semi-Urban,ML Engineer,144115,1 +56639,Male,35,Diploma,7,6,38,68,21,7.0,3,17,Urban,Software Engineer,100956,0 +56640,Female,33,Diploma,11,26,12,29,56,2.0,3,74,Urban,ML Engineer,70928,0 +56641,Female,22,Bachelors,14,26,7,74,63,0.0,0,91,Urban,HR Executive,55716,0 +56642,Female,49,High School,12,48,6,81,90,2.0,7,48,Rural,HR Executive,146451,0 +56643,Male,53,Diploma,1,68,21,73,86,4.0,3,93,Urban,Data Analyst,56181,1 +56644,Male,46,Bachelors,1,33,61,65,12,5.0,4,38,Urban,ML Engineer,76494,0 +56645,Female,49,Masters,9,83,2,99,45,8.0,7,29,Urban,Manager,54798,0 +56646,Male,58,Bachelors,11,76,56,31,66,2.0,7,11,Rural,HR Executive,100662,0 +56647,Female,50,Masters,18,17,19,40,29,5.0,0,37,Semi-Urban,Software Engineer,96365,0 +56648,Male,56,Diploma,0,45,53,88,6,3.0,6,12,Urban,HR Executive,46546,0 +56649,Male,28,PhD,10,64,7,51,56,7.0,6,88,Urban,HR Executive,128022,0 +56650,Male,38,Bachelors,0,64,86,32,77,8.0,5,18,Urban,Data Analyst,21420,0 +56651,Male,41,PhD,12,61,98,27,77,3.0,6,41,Semi-Urban,HR Executive,52904,0 +56652,Male,33,Bachelors,0,85,49,77,89,9.0,2,22,Urban,Data Analyst,116074,0 +56653,Male,59,Bachelors,6,44,33,91,92,8.0,7,27,Urban,Software Engineer,140700,0 +56654,Other,21,Masters,2,88,45,93,59,5.0,2,27,Urban,HR Executive,95399,1 +56655,Female,52,High School,12,72,47,15,90,9.0,1,43,Urban,HR Executive,60895,0 +56656,Female,36,Masters,8,64,47,93,56,1.0,3,54,Rural,Manager,145261,1 +56657,Female,22,Bachelors,3,49,42,75,81,3.0,0,86,Urban,ML Engineer,30645,1 +56658,Female,53,Bachelors,6,82,58,6,80,1.0,1,48,Urban,Manager,62641,0 +56659,Male,42,Diploma,11,4,55,57,37,9.0,7,68,Urban,Software Engineer,122154,0 +56660,Female,41,Bachelors,8,27,17,32,66,7.0,0,36,Urban,HR Executive,86146,0 +56661,Male,25,Bachelors,6,66,15,31,67,1.0,0,57,Urban,Manager,58793,0 +56662,Female,21,Bachelors,4,7,26,35,70,0.0,5,5,Semi-Urban,Software Engineer,46529,0 +56663,Male,51,Diploma,0,89,4,68,80,3.0,3,82,Semi-Urban,HR Executive,142900,1 +56664,Female,22,Bachelors,16,65,45,47,24,5.0,3,74,Urban,Data Analyst,60400,0 +56665,Male,25,Masters,12,17,10,65,91,0.0,7,53,Rural,Data Analyst,43518,0 +56666,Male,32,Masters,15,30,80,51,55,4.0,1,79,Urban,Software Engineer,127420,1 +56667,Female,23,Bachelors,11,88,12,88,66,4.0,7,84,Urban,ML Engineer,133943,1 +56668,Female,48,High School,5,96,34,3,8,4.0,5,61,Urban,Data Analyst,111370,0 +56669,Female,41,High School,18,59,6,18,55,5.0,6,54,Urban,Manager,35491,0 +56670,Female,56,High School,15,99,36,51,36,4.0,0,1,Semi-Urban,HR Executive,98241,0 +56671,Female,47,Bachelors,13,78,25,35,15,8.0,5,52,Urban,ML Engineer,69794,0 +56672,Male,37,Diploma,13,15,49,87,66,4.0,5,74,Urban,HR Executive,140787,0 +56673,Male,49,Bachelors,14,8,40,0,56,0.0,3,6,Rural,Data Analyst,23642,0 +56674,Male,24,High School,9,15,35,72,58,2.0,7,64,Urban,HR Executive,105706,0 +56675,Male,23,Bachelors,9,9,11,56,78,0.0,4,65,Urban,HR Executive,132838,0 +56676,Male,43,PhD,16,85,78,33,0,4.0,2,15,Urban,Manager,109805,0 +56677,Male,22,PhD,4,77,15,29,44,8.0,3,2,Semi-Urban,Software Engineer,63914,0 +56678,Male,38,High School,11,19,69,31,24,2.0,5,83,Semi-Urban,Data Analyst,143116,0 +56679,Male,47,Diploma,3,79,29,87,65,6.0,1,77,Urban,Manager,94949,1 +56680,Female,33,Masters,18,71,87,6,77,0.0,5,19,Rural,Data Analyst,146094,0 +56681,Male,34,Masters,11,56,91,48,37,2.0,3,77,Rural,Software Engineer,26384,1 +56682,Male,46,Masters,13,13,31,13,3,3.0,5,28,Urban,Software Engineer,42570,0 +56683,Male,33,Bachelors,18,14,64,56,90,0.0,0,37,Urban,ML Engineer,131313,0 +56684,Male,42,PhD,6,44,63,74,69,7.0,6,83,Urban,Software Engineer,130457,1 +56685,Other,51,Bachelors,0,43,10,86,85,4.0,0,1,Urban,Data Analyst,57231,0 +56686,Female,38,Masters,15,30,62,6,34,1.0,5,23,Rural,HR Executive,47168,0 +56687,Male,22,Bachelors,17,17,83,0,87,6.0,0,45,Urban,Software Engineer,40336,0 +56688,Male,25,Bachelors,13,55,11,72,44,4.0,0,83,Urban,HR Executive,112149,0 +56689,Male,48,PhD,4,31,38,94,56,4.0,1,27,Rural,Data Analyst,37824,0 +56690,Female,45,Masters,12,96,52,35,51,7.0,7,33,Semi-Urban,Manager,73068,0 +56691,Other,52,Bachelors,3,61,4,43,75,4.0,6,95,Urban,ML Engineer,73794,0 +56692,Male,44,Masters,12,1,73,29,13,8.0,6,13,Urban,HR Executive,44175,0 +56693,Female,41,Bachelors,0,80,67,88,24,6.0,4,42,Rural,ML Engineer,100493,1 +56694,Male,35,Diploma,7,50,19,67,8,1.0,2,12,Urban,HR Executive,38367,0 +56695,Female,32,Masters,12,14,35,11,89,8.0,7,13,Urban,Software Engineer,58721,0 +56696,Male,52,Bachelors,7,12,69,45,58,0.0,3,62,Rural,Manager,63036,0 +56697,Male,39,Bachelors,3,72,50,18,26,0.0,4,99,Urban,Data Analyst,104220,1 +56698,Male,32,Masters,12,5,64,63,21,6.0,3,64,Urban,Software Engineer,65339,0 +56699,Male,39,Masters,18,44,20,27,69,9.0,4,34,Urban,Data Analyst,55904,0 +56700,Female,50,Bachelors,0,47,11,35,15,9.0,6,13,Semi-Urban,Manager,86541,0 +56701,Female,54,Diploma,7,8,88,79,20,6.0,1,11,Urban,Manager,50362,0 +56702,Male,39,Masters,0,5,25,67,27,3.0,6,35,Urban,Data Analyst,86175,0 +56703,Male,29,High School,2,94,25,37,63,3.0,6,77,Rural,Software Engineer,136640,0 +56704,Male,34,Masters,6,6,37,37,7,9.0,5,99,Semi-Urban,Data Analyst,101991,0 +56705,Male,26,Masters,11,95,74,40,48,3.0,3,74,Rural,Software Engineer,83357,1 +56706,Male,35,High School,15,48,15,89,90,4.0,0,59,Semi-Urban,HR Executive,141380,0 +56707,Male,59,Bachelors,8,31,96,17,77,9.0,7,85,Semi-Urban,ML Engineer,93112,0 +56708,Female,24,Bachelors,17,43,42,53,4,6.0,3,44,Urban,ML Engineer,94816,0 +56709,Female,53,Diploma,4,81,14,39,9,1.0,0,46,Urban,Data Analyst,131307,0 +56710,Male,28,Masters,11,67,37,66,11,0.0,6,54,Urban,ML Engineer,73110,0 +56711,Female,57,Bachelors,6,0,13,30,84,6.0,4,17,Urban,Software Engineer,54145,0 +56712,Female,22,Masters,17,25,29,4,83,6.0,1,54,Urban,Software Engineer,117658,0 +56713,Male,50,High School,9,83,81,88,45,5.0,6,49,Semi-Urban,Manager,89562,1 +56714,Male,40,Bachelors,12,23,82,99,26,1.0,3,98,Urban,Manager,113565,1 +56715,Female,51,Diploma,11,43,76,34,38,5.0,4,0,Rural,Data Analyst,52555,0 +56716,Female,57,Masters,7,11,9,52,50,7.0,1,84,Urban,ML Engineer,145375,0 +56717,Male,28,Bachelors,4,38,33,78,6,9.0,7,20,Semi-Urban,ML Engineer,77895,0 +56718,Female,24,Masters,5,90,57,22,69,5.0,7,5,Urban,Software Engineer,21742,0 +56719,Male,45,Bachelors,14,7,80,45,47,1.0,6,20,Semi-Urban,Data Analyst,118442,0 +56720,Male,55,Bachelors,14,19,20,34,35,8.0,3,75,Urban,Software Engineer,92747,0 +56721,Female,48,Bachelors,1,38,8,62,34,2.0,0,84,Semi-Urban,Data Analyst,101383,0 +56722,Female,35,Bachelors,2,87,36,83,36,1.0,1,54,Semi-Urban,Data Analyst,43769,1 +56723,Female,21,Diploma,16,0,94,43,77,6.0,5,74,Semi-Urban,Data Analyst,130781,0 +56724,Female,52,High School,2,87,12,7,64,9.0,6,96,Semi-Urban,Data Analyst,111351,0 +56725,Male,41,Diploma,14,72,28,57,4,6.0,1,4,Urban,Data Analyst,94278,0 +56726,Male,38,High School,12,19,65,89,39,8.0,4,69,Urban,Data Analyst,57684,1 +56727,Male,48,Bachelors,14,48,56,23,30,5.0,7,99,Urban,Manager,146283,0 +56728,Male,50,Bachelors,10,87,48,64,44,4.0,5,0,Urban,Manager,133904,0 +56729,Female,38,High School,17,20,86,17,85,8.0,3,58,Urban,Data Analyst,26270,0 +56730,Male,28,Diploma,13,64,58,84,38,0.0,3,70,Urban,Data Analyst,116650,1 +56731,Male,48,Diploma,19,88,97,93,18,8.0,1,64,Rural,Manager,79124,1 +56732,Female,45,Masters,2,29,48,91,15,4.0,2,91,Semi-Urban,Software Engineer,127564,1 +56733,Male,22,Diploma,2,3,94,38,67,7.0,3,90,Urban,ML Engineer,100926,0 +56734,Male,59,Bachelors,17,96,63,57,21,3.0,6,31,Rural,ML Engineer,98107,1 +56735,Female,58,Bachelors,8,90,30,97,94,8.0,3,84,Urban,Software Engineer,34405,1 +56736,Female,52,Bachelors,2,6,54,58,86,5.0,3,42,Urban,HR Executive,58475,0 +56737,Female,58,High School,4,76,5,80,71,5.0,1,4,Urban,Data Analyst,60341,0 +56738,Female,51,Bachelors,13,44,43,81,19,4.0,2,76,Urban,Manager,90356,1 +56739,Male,36,Bachelors,14,71,0,5,87,1.0,6,46,Urban,ML Engineer,126989,0 +56740,Male,21,Diploma,5,36,59,56,89,2.0,1,99,Semi-Urban,ML Engineer,114952,1 +56741,Male,33,Bachelors,10,91,88,83,1,7.0,5,37,Urban,Manager,59722,1 +56742,Female,58,Diploma,12,46,61,67,19,1.0,2,75,Urban,Data Analyst,22202,1 +56743,Male,55,Masters,17,75,20,20,9,5.0,7,69,Semi-Urban,Software Engineer,72362,0 +56744,Female,23,Bachelors,7,89,67,19,19,9.0,5,66,Semi-Urban,Software Engineer,146850,1 +56745,Male,55,Bachelors,0,53,37,1,56,7.0,0,56,Urban,Manager,70727,0 +56746,Female,26,Bachelors,7,45,6,36,26,0.0,0,15,Semi-Urban,ML Engineer,54977,0 +56747,Male,54,Diploma,5,49,37,6,9,9.0,6,30,Urban,Software Engineer,108247,0 +56748,Female,48,Bachelors,15,6,36,61,72,4.0,3,73,Urban,Data Analyst,32955,0 +56749,Female,42,Bachelors,19,86,27,77,44,2.0,7,60,Semi-Urban,Software Engineer,128072,1 +56750,Female,29,Diploma,13,79,50,68,5,5.0,0,50,Urban,HR Executive,54026,1 +56751,Female,39,Diploma,14,32,98,18,81,6.0,4,66,Urban,Data Analyst,93294,0 +56752,Male,24,Diploma,11,17,66,37,40,5.0,3,46,Urban,Software Engineer,91125,0 +56753,Male,57,Bachelors,3,68,45,38,80,2.0,3,25,Urban,ML Engineer,74985,0 +56754,Male,51,Diploma,4,8,53,45,78,2.0,7,79,Urban,Data Analyst,140871,0 +56755,Male,54,Bachelors,18,29,49,57,70,0.0,2,31,Urban,ML Engineer,79793,0 +56756,Female,22,PhD,3,11,53,27,57,9.0,2,28,Semi-Urban,Software Engineer,54344,0 +56757,Female,52,Diploma,9,16,8,11,61,2.0,0,49,Urban,Software Engineer,105407,0 +56758,Male,26,Bachelors,0,46,17,15,91,9.0,3,98,Semi-Urban,Manager,84059,0 +56759,Female,37,Bachelors,10,44,95,74,85,4.0,6,32,Semi-Urban,HR Executive,109775,1 +56760,Female,55,Bachelors,4,12,65,55,27,8.0,6,46,Urban,Software Engineer,87607,0 +56761,Other,24,Bachelors,0,93,87,79,36,1.0,7,28,Urban,Software Engineer,117691,1 +56762,Female,56,Masters,4,11,27,86,7,7.0,6,33,Urban,Data Analyst,146624,0 +56763,Female,54,High School,16,7,18,59,1,3.0,7,11,Urban,ML Engineer,30978,0 +56764,Male,23,High School,11,57,36,18,53,5.0,4,52,Urban,Data Analyst,49847,0 +56765,Male,31,Masters,16,22,0,80,46,2.0,2,92,Urban,HR Executive,45598,0 +56766,Male,30,High School,0,14,21,47,1,5.0,1,62,Urban,HR Executive,43818,0 +56767,Female,28,Bachelors,3,38,67,67,24,2.0,4,86,Urban,Data Analyst,45671,1 +56768,Male,51,High School,14,82,89,80,91,5.0,1,75,Semi-Urban,Software Engineer,31302,1 +56769,Male,59,Bachelors,8,85,60,79,23,6.0,3,4,Semi-Urban,ML Engineer,123285,0 +56770,Other,37,Diploma,7,91,45,75,0,1.0,1,94,Urban,Manager,94301,1 +56771,Female,34,High School,11,83,55,46,57,9.0,1,93,Urban,Manager,59580,1 +56772,Female,25,High School,11,29,31,9,46,5.0,2,5,Urban,Manager,23157,0 +56773,Male,36,Masters,18,28,56,47,29,0.0,4,40,Urban,Data Analyst,131314,0 +56774,Male,45,Diploma,11,40,94,31,8,5.0,5,7,Semi-Urban,ML Engineer,72030,0 +56775,Male,29,Masters,3,68,30,0,11,3.0,0,53,Urban,HR Executive,114816,0 +56776,Female,44,Masters,17,38,14,20,8,4.0,6,24,Semi-Urban,Software Engineer,142653,0 +56777,Male,47,High School,5,82,23,4,48,8.0,7,99,Urban,Software Engineer,34252,0 +56778,Male,50,Diploma,5,25,71,16,6,6.0,6,99,Urban,ML Engineer,46440,0 +56779,Female,25,Diploma,12,29,21,65,24,4.0,1,43,Urban,Manager,138319,0 +56780,Male,50,High School,5,62,42,33,93,4.0,5,52,Urban,ML Engineer,130822,0 +56781,Male,46,High School,3,43,55,23,7,7.0,1,66,Rural,ML Engineer,140318,0 +56782,Female,50,Bachelors,1,83,14,88,22,8.0,4,30,Semi-Urban,ML Engineer,29149,0 +56783,Female,29,Bachelors,1,0,16,62,93,9.0,1,27,Rural,Software Engineer,37214,0 +56784,Other,26,Masters,13,0,21,5,12,2.0,1,54,Semi-Urban,Data Analyst,100783,0 +56785,Male,54,Bachelors,15,52,34,84,76,4.0,1,2,Urban,Manager,70006,0 +56786,Male,28,Diploma,11,18,18,65,70,9.0,2,81,Urban,HR Executive,36178,0 +56787,Male,40,High School,13,22,2,54,70,4.0,0,18,Rural,HR Executive,145781,0 +56788,Male,37,Diploma,1,65,7,41,62,3.0,3,67,Urban,ML Engineer,115984,0 +56789,Female,37,Bachelors,16,61,83,47,31,6.0,3,10,Urban,Software Engineer,28845,0 +56790,Female,35,Bachelors,0,48,8,16,62,2.0,7,86,Rural,Data Analyst,124314,0 +56791,Other,53,Masters,16,63,3,65,44,1.0,2,32,Urban,Data Analyst,127117,0 +56792,Male,43,Bachelors,8,91,49,32,89,3.0,7,98,Rural,ML Engineer,83523,1 +56793,Female,57,Masters,13,93,33,15,26,0.0,7,73,Urban,Software Engineer,104810,0 +56794,Male,25,Masters,1,86,83,61,99,0.0,6,70,Urban,ML Engineer,147293,1 +56795,Male,46,High School,13,68,90,20,99,0.0,4,29,Urban,Software Engineer,74002,0 +56796,Male,33,Bachelors,11,26,86,85,2,8.0,0,44,Urban,Data Analyst,82221,1 +56797,Male,44,Diploma,8,82,52,85,6,4.0,2,7,Urban,Data Analyst,119246,0 +56798,Male,31,Bachelors,4,76,90,6,46,4.0,4,91,Urban,Software Engineer,34981,1 +56799,Male,53,Diploma,11,94,8,43,54,6.0,1,56,Semi-Urban,Manager,89937,0 +56800,Female,31,Bachelors,16,96,69,61,43,6.0,2,13,Semi-Urban,Manager,77672,0 +56801,Female,23,Bachelors,9,60,36,25,46,8.0,5,66,Urban,Manager,130803,0 +56802,Female,31,Bachelors,11,24,60,42,55,3.0,6,82,Urban,ML Engineer,136453,0 +56803,Male,44,PhD,19,16,14,93,25,1.0,3,3,Urban,Software Engineer,130675,0 +56804,Female,43,PhD,19,57,64,14,51,9.0,1,13,Semi-Urban,HR Executive,123855,0 +56805,Female,32,Diploma,0,11,11,62,83,1.0,3,31,Urban,Software Engineer,106826,0 +56806,Male,38,Diploma,1,88,91,35,97,1.0,6,97,Urban,ML Engineer,126934,1 +56807,Female,40,Bachelors,0,44,64,27,18,7.0,2,53,Urban,HR Executive,82936,0 +56808,Female,37,High School,10,53,48,59,38,5.0,7,72,Urban,Data Analyst,111377,0 +56809,Female,29,Bachelors,6,57,40,17,5,9.0,2,85,Urban,Manager,29303,0 +56810,Male,39,Diploma,10,51,84,83,19,8.0,5,43,Urban,Manager,112369,1 +56811,Male,35,Bachelors,4,40,99,75,7,7.0,7,25,Semi-Urban,Manager,45742,1 +56812,Male,30,Diploma,0,27,17,3,11,9.0,6,39,Rural,ML Engineer,24928,0 +56813,Female,50,High School,8,94,54,68,62,5.0,4,11,Rural,Manager,56555,0 +56814,Female,30,Bachelors,19,60,34,74,97,4.0,5,72,Urban,Software Engineer,106670,0 +56815,Male,54,Diploma,4,83,23,42,67,2.0,1,80,Semi-Urban,Manager,113974,0 +56816,Female,54,High School,1,28,19,94,4,4.0,2,23,Semi-Urban,Manager,110757,0 +56817,Male,55,Bachelors,2,74,36,57,95,7.0,3,11,Rural,Manager,27529,0 +56818,Male,32,Diploma,17,16,89,82,74,2.0,3,67,Urban,ML Engineer,76338,1 +56819,Female,42,Bachelors,19,44,64,55,42,0.0,7,2,Urban,Manager,132126,0 +56820,Male,51,Bachelors,15,51,39,94,14,3.0,1,87,Urban,ML Engineer,104524,1 +56821,Male,48,High School,0,23,41,0,15,4.0,3,95,Urban,Data Analyst,34174,0 +56822,Male,56,High School,11,89,62,42,10,5.0,4,58,Urban,HR Executive,47231,1 +56823,Male,36,Diploma,14,45,51,24,5,7.0,4,68,Urban,Manager,88467,0 +56824,Female,22,High School,10,73,97,42,58,8.0,0,69,Semi-Urban,Data Analyst,106959,1 +56825,Female,35,Bachelors,5,52,72,16,89,0.0,7,99,Urban,HR Executive,119377,0 +56826,Female,29,Masters,17,78,84,43,36,0.0,4,88,Urban,Manager,86511,1 +56827,Male,24,High School,11,51,30,72,39,8.0,3,33,Urban,Software Engineer,65680,0 +56828,Female,30,Diploma,14,33,57,92,32,9.0,6,90,Urban,Software Engineer,34781,1 +56829,Male,55,Bachelors,4,75,77,69,23,1.0,7,22,Urban,Manager,108187,1 +56830,Male,42,High School,14,48,56,69,89,7.0,5,31,Urban,Software Engineer,132513,0 +56831,Male,56,Bachelors,13,84,0,32,14,4.0,5,24,Urban,Manager,51085,0 +56832,Male,23,Masters,1,52,21,1,96,4.0,6,56,Semi-Urban,ML Engineer,65528,0 +56833,Male,48,Bachelors,17,20,57,44,56,2.0,5,96,Urban,ML Engineer,119479,0 +56834,Male,28,PhD,7,20,43,62,42,9.0,7,58,Urban,ML Engineer,27979,0 +56835,Female,45,Bachelors,14,97,29,51,71,3.0,4,1,Urban,Manager,121467,0 +56836,Male,33,Bachelors,11,22,54,70,17,8.0,5,65,Urban,Software Engineer,124104,0 +56837,Male,58,Masters,11,80,51,57,50,5.0,0,31,Urban,Data Analyst,49191,0 +56838,Male,34,Diploma,5,27,80,30,16,8.0,1,51,Semi-Urban,ML Engineer,92554,0 +56839,Male,21,Bachelors,18,30,59,54,33,8.0,1,38,Urban,Data Analyst,93652,0 +56840,Male,36,Diploma,8,96,80,39,11,5.0,2,58,Urban,Manager,86588,1 +56841,Female,37,Bachelors,9,51,13,89,64,1.0,0,30,Urban,Software Engineer,30732,0 +56842,Male,45,Masters,12,73,19,2,68,1.0,4,59,Urban,ML Engineer,87401,0 +56843,Other,35,Masters,3,23,33,48,45,5.0,5,35,Semi-Urban,Manager,63290,0 +56844,Male,31,Bachelors,12,64,82,79,47,9.0,2,78,Rural,HR Executive,135055,1 +56845,Male,33,High School,3,72,78,76,64,3.0,4,93,Urban,Manager,124300,1 +56846,Female,23,Diploma,1,33,14,63,25,1.0,4,35,Rural,HR Executive,32355,0 +56847,Female,48,Masters,11,18,53,67,46,5.0,3,68,Urban,Manager,142958,0 +56848,Male,57,Bachelors,7,15,76,46,35,6.0,0,89,Urban,Data Analyst,87023,0 +56849,Male,46,Bachelors,6,1,48,70,5,2.0,6,49,Urban,Software Engineer,39299,0 +56850,Female,50,Bachelors,5,48,53,27,92,7.0,3,67,Semi-Urban,Software Engineer,39676,0 +56851,Other,35,High School,5,72,53,67,35,0.0,5,44,Urban,Data Analyst,125482,0 +56852,Other,43,Diploma,1,55,71,38,99,4.0,4,34,Semi-Urban,ML Engineer,106514,0 +56853,Female,26,PhD,0,98,58,95,2,5.0,3,47,Semi-Urban,HR Executive,129917,1 +56854,Female,51,Masters,0,64,7,99,96,2.0,0,99,Rural,HR Executive,80464,1 +56855,Female,57,Masters,0,51,68,26,60,0.0,5,49,Semi-Urban,Data Analyst,84611,0 +56856,Female,42,Bachelors,12,17,90,79,25,9.0,7,90,Semi-Urban,HR Executive,136136,1 +56857,Other,38,Bachelors,6,27,76,35,97,1.0,2,74,Urban,Software Engineer,137902,0 +56858,Female,26,Masters,7,18,18,82,50,8.0,1,47,Semi-Urban,HR Executive,114673,0 +56859,Female,23,Diploma,19,56,48,44,82,0.0,4,16,Semi-Urban,Manager,103150,0 +56860,Male,32,Bachelors,3,41,17,50,73,1.0,6,26,Rural,Data Analyst,106493,0 +56861,Male,56,Bachelors,14,10,18,53,85,7.0,5,41,Urban,Manager,28649,0 +56862,Female,55,Bachelors,12,96,23,95,19,9.0,0,94,Rural,HR Executive,120522,1 +56863,Male,38,Bachelors,18,81,9,30,31,3.0,7,6,Urban,Software Engineer,68668,0 +56864,Male,33,Bachelors,5,99,89,57,64,0.0,4,2,Semi-Urban,Data Analyst,34317,1 +56865,Male,41,High School,10,94,82,2,62,5.0,6,76,Urban,HR Executive,85321,1 +56866,Other,31,Bachelors,2,81,45,66,7,0.0,0,2,Rural,Software Engineer,23508,0 +56867,Female,53,High School,18,52,12,70,35,5.0,3,35,Urban,Data Analyst,70621,0 +56868,Male,47,Bachelors,0,72,27,70,25,6.0,3,72,Urban,HR Executive,84889,1 +56869,Male,39,Bachelors,9,83,71,24,4,1.0,1,64,Urban,Software Engineer,124957,1 +56870,Female,31,Bachelors,5,33,45,82,63,9.0,4,42,Urban,HR Executive,107814,0 +56871,Male,53,High School,5,98,20,27,1,0.0,3,48,Urban,Manager,88830,0 +56872,Male,27,Diploma,7,69,64,80,82,4.0,4,86,Urban,HR Executive,127627,1 +56873,Other,43,High School,12,13,27,61,90,3.0,1,78,Semi-Urban,ML Engineer,52660,0 +56874,Female,22,PhD,15,72,72,53,15,0.0,5,86,Semi-Urban,ML Engineer,36992,1 +56875,Female,57,PhD,16,88,54,95,19,6.0,1,38,Urban,Manager,85619,1 +56876,Female,21,Bachelors,14,80,82,73,79,9.0,0,32,Urban,Data Analyst,97543,1 +56877,Male,37,Bachelors,3,7,45,3,95,0.0,5,3,Rural,HR Executive,31625,0 +56878,Male,26,Masters,12,79,72,9,1,4.0,6,74,Semi-Urban,Software Engineer,122451,0 +56879,Male,59,Bachelors,3,88,64,97,68,4.0,0,79,Semi-Urban,Manager,34535,1 +56880,Other,42,Bachelors,16,69,67,84,6,8.0,5,47,Urban,HR Executive,139181,1 +56881,Male,50,Bachelors,11,48,93,34,31,7.0,2,22,Urban,HR Executive,22761,0 +56882,Female,56,Diploma,18,9,26,10,83,0.0,5,51,Urban,HR Executive,120550,0 +56883,Male,56,Bachelors,13,37,98,52,12,5.0,6,14,Urban,Data Analyst,145340,0 +56884,Female,31,Bachelors,3,90,87,71,91,2.0,4,3,Urban,Manager,30610,1 +56885,Female,21,Bachelors,1,20,66,20,82,0.0,3,33,Rural,Manager,38378,0 +56886,Male,53,Masters,3,27,74,7,90,8.0,0,97,Urban,Manager,103161,0 +56887,Male,47,Bachelors,19,58,88,12,94,6.0,7,82,Semi-Urban,HR Executive,67895,1 +56888,Male,59,High School,8,36,62,66,7,3.0,4,14,Semi-Urban,HR Executive,95133,0 +56889,Male,59,Bachelors,12,5,32,17,76,1.0,2,25,Urban,Manager,103379,0 +56890,Female,36,Diploma,12,57,80,56,60,6.0,5,64,Urban,HR Executive,31701,1 +56891,Male,37,Masters,17,35,70,67,42,9.0,0,82,Semi-Urban,HR Executive,86341,1 +56892,Male,47,Bachelors,14,52,79,86,63,3.0,3,17,Rural,ML Engineer,42819,0 +56893,Female,40,Bachelors,6,99,49,66,55,6.0,1,32,Rural,HR Executive,101711,1 +56894,Female,59,Bachelors,11,94,34,45,97,6.0,6,89,Urban,Data Analyst,55671,1 +56895,Female,53,Diploma,19,24,19,58,60,2.0,5,86,Urban,Manager,111501,0 +56896,Female,30,Masters,9,77,42,54,81,7.0,4,97,Urban,HR Executive,90538,1 +56897,Male,59,Bachelors,13,12,49,39,49,1.0,7,78,Urban,ML Engineer,29947,0 +56898,Male,26,Bachelors,11,71,46,1,29,0.0,6,35,Urban,Software Engineer,69154,0 +56899,Male,55,Masters,7,66,38,80,33,8.0,3,46,Urban,Data Analyst,138824,0 +56900,Male,47,Masters,14,29,77,16,51,7.0,2,25,Semi-Urban,Data Analyst,46425,0 +56901,Male,25,Bachelors,2,20,44,89,83,5.0,3,87,Urban,Manager,26034,1 +56902,Male,33,Masters,6,92,43,20,23,6.0,7,41,Urban,Software Engineer,118637,0 +56903,Male,37,Bachelors,9,30,77,92,19,9.0,3,48,Rural,Software Engineer,130843,1 +56904,Male,43,Bachelors,10,8,22,0,61,6.0,0,72,Urban,ML Engineer,134821,0 +56905,Male,36,Diploma,19,61,28,26,28,0.0,4,95,Rural,ML Engineer,106192,0 +56906,Female,31,Bachelors,19,53,70,70,83,2.0,7,83,Urban,Software Engineer,57208,1 +56907,Other,27,Bachelors,19,97,37,46,33,4.0,5,68,Semi-Urban,Manager,49252,1 +56908,Male,25,Diploma,18,11,38,97,72,6.0,0,72,Semi-Urban,Manager,41829,0 +56909,Male,58,High School,4,58,40,64,35,4.0,0,40,Urban,Manager,24585,0 +56910,Female,54,Masters,7,86,1,17,24,7.0,4,29,Rural,Data Analyst,122630,0 +56911,Male,50,PhD,11,96,32,76,27,1.0,5,90,Semi-Urban,Software Engineer,112289,1 +56912,Female,25,Masters,7,73,38,36,10,1.0,3,11,Semi-Urban,Manager,75357,0 +56913,Male,57,Bachelors,18,69,49,40,73,8.0,0,60,Semi-Urban,ML Engineer,118470,0 +56914,Male,29,PhD,1,48,51,96,85,2.0,5,0,Semi-Urban,HR Executive,59057,0 +56915,Female,23,Masters,6,81,83,60,6,1.0,4,27,Urban,ML Engineer,50713,1 +56916,Male,47,High School,16,22,23,92,45,1.0,3,65,Semi-Urban,ML Engineer,38226,0 +56917,Male,36,Masters,13,68,22,46,20,2.0,5,47,Semi-Urban,Data Analyst,68116,0 +56918,Female,45,Bachelors,13,94,23,28,60,1.0,6,57,Urban,ML Engineer,44776,0 +56919,Other,59,Bachelors,17,41,84,25,3,9.0,6,48,Semi-Urban,Software Engineer,95193,0 +56920,Female,45,High School,19,85,73,65,25,1.0,1,81,Semi-Urban,Software Engineer,129699,1 +56921,Female,39,Bachelors,3,92,95,34,74,4.0,1,67,Urban,Data Analyst,84104,1 +56922,Female,46,Diploma,7,57,76,73,51,0.0,0,30,Urban,ML Engineer,112308,0 +56923,Male,43,Bachelors,17,42,52,18,97,7.0,5,62,Urban,Data Analyst,84754,0 +56924,Male,54,Bachelors,15,44,21,50,76,5.0,1,41,Rural,HR Executive,79649,0 +56925,Male,27,Diploma,0,64,76,4,11,4.0,5,63,Semi-Urban,Manager,120929,0 +56926,Male,30,Diploma,3,97,30,19,71,1.0,0,71,Semi-Urban,Software Engineer,30571,0 +56927,Female,38,Diploma,15,65,23,54,21,8.0,6,98,Urban,Data Analyst,149894,0 +56928,Male,34,Bachelors,5,64,61,59,77,0.0,1,65,Rural,Data Analyst,38324,1 +56929,Male,50,Diploma,10,22,97,93,84,8.0,1,26,Urban,ML Engineer,30182,1 +56930,Male,51,Bachelors,13,1,96,82,5,3.0,6,92,Semi-Urban,HR Executive,38175,1 +56931,Male,38,Bachelors,1,82,77,56,31,1.0,4,96,Urban,HR Executive,22655,1 +56932,Male,30,PhD,19,78,98,58,79,2.0,6,97,Urban,ML Engineer,147687,1 +56933,Male,23,Bachelors,2,99,34,84,98,4.0,0,24,Urban,Software Engineer,53673,1 +56934,Female,24,Masters,15,62,54,25,74,9.0,5,82,Urban,Data Analyst,48388,0 +56935,Female,54,Bachelors,8,57,80,54,1,6.0,1,13,Urban,ML Engineer,145195,0 +56936,Female,28,High School,13,63,60,14,67,9.0,5,65,Urban,Software Engineer,38982,0 +56937,Female,22,Diploma,11,48,92,24,90,4.0,0,56,Semi-Urban,Software Engineer,66708,0 +56938,Female,54,Masters,7,24,22,38,33,2.0,2,57,Rural,HR Executive,63978,0 +56939,Male,25,High School,16,38,67,99,37,7.0,2,88,Rural,ML Engineer,25587,1 +56940,Female,27,Masters,4,51,60,34,7,8.0,4,53,Urban,Data Analyst,67062,0 +56941,Male,33,Diploma,7,90,3,85,45,5.0,7,64,Semi-Urban,Software Engineer,117366,1 +56942,Male,39,Bachelors,14,40,65,64,26,8.0,4,93,Urban,Software Engineer,64523,1 +56943,Female,30,Masters,1,95,36,56,91,8.0,0,86,Rural,HR Executive,87187,1 +56944,Male,50,High School,3,6,96,68,14,8.0,5,89,Urban,Manager,141790,1 +56945,Male,33,Bachelors,14,48,54,79,30,2.0,6,13,Urban,ML Engineer,22679,0 +56946,Male,36,High School,3,41,41,24,82,2.0,2,90,Urban,Manager,142257,0 +56947,Male,38,High School,12,37,86,71,65,8.0,1,40,Urban,Software Engineer,29966,0 +56948,Female,46,PhD,7,8,0,4,68,1.0,5,86,Rural,Data Analyst,38222,0 +56949,Male,25,Diploma,12,55,36,36,52,5.0,3,41,Semi-Urban,ML Engineer,21489,0 +56950,Female,44,Diploma,16,24,38,72,96,7.0,5,72,Rural,Data Analyst,47218,0 +56951,Male,38,Bachelors,7,98,77,88,48,4.0,1,93,Semi-Urban,HR Executive,59250,1 +56952,Male,53,Bachelors,10,76,58,53,45,9.0,1,45,Semi-Urban,Software Engineer,144500,0 +56953,Male,59,Masters,16,84,87,98,54,1.0,2,64,Rural,Manager,97690,1 +56954,Female,56,Bachelors,12,54,37,61,38,9.0,7,20,Urban,Data Analyst,89127,0 +56955,Other,31,High School,9,44,28,42,96,2.0,7,19,Urban,Data Analyst,67157,0 +56956,Male,28,Bachelors,12,62,18,86,0,8.0,1,75,Urban,Software Engineer,146010,1 +56957,Other,54,Masters,12,9,19,21,68,5.0,4,90,Urban,Manager,80238,0 +56958,Female,44,Diploma,15,13,82,66,87,5.0,3,10,Urban,HR Executive,57047,0 +56959,Male,37,Diploma,13,76,88,92,78,1.0,5,0,Semi-Urban,Data Analyst,27569,1 +56960,Male,40,High School,18,97,66,7,79,9.0,1,53,Semi-Urban,Data Analyst,147945,0 +56961,Female,31,Diploma,13,1,84,96,78,4.0,1,40,Urban,Data Analyst,32840,0 +56962,Male,45,High School,19,11,89,95,29,4.0,0,36,Rural,Manager,137232,0 +56963,Male,58,Bachelors,19,78,5,23,45,5.0,3,7,Semi-Urban,Data Analyst,28598,0 +56964,Male,50,Bachelors,17,94,19,62,27,0.0,7,20,Urban,Data Analyst,88111,0 +56965,Male,21,Bachelors,16,2,61,72,23,5.0,3,34,Urban,Manager,123474,0 +56966,Male,27,Bachelors,1,6,41,98,7,4.0,1,28,Rural,Data Analyst,120448,0 +56967,Female,47,Bachelors,12,0,61,41,71,6.0,2,88,Semi-Urban,HR Executive,128477,0 +56968,Female,25,Bachelors,2,85,69,87,24,3.0,1,8,Rural,Manager,40707,1 +56969,Female,52,High School,10,30,49,98,97,7.0,6,31,Semi-Urban,Software Engineer,81830,0 +56970,Female,26,Bachelors,12,76,23,63,53,0.0,7,89,Urban,Manager,94319,1 +56971,Male,39,Bachelors,16,84,83,34,62,3.0,5,85,Urban,Software Engineer,68355,1 +56972,Male,54,Masters,7,31,93,74,54,9.0,7,21,Semi-Urban,Manager,21515,0 +56973,Female,43,Diploma,0,51,40,54,63,7.0,4,80,Rural,Software Engineer,55306,0 +56974,Male,29,Masters,7,33,69,98,76,6.0,0,56,Urban,ML Engineer,61990,1 +56975,Female,56,Masters,10,86,81,41,49,6.0,4,91,Rural,Data Analyst,87648,1 +56976,Male,35,Bachelors,3,19,0,2,35,3.0,2,84,Urban,Software Engineer,89070,0 +56977,Male,53,Bachelors,4,71,90,98,8,1.0,1,7,Semi-Urban,HR Executive,123928,1 +56978,Male,32,Bachelors,16,34,6,13,11,7.0,2,2,Rural,Manager,92638,0 +56979,Female,47,Bachelors,11,48,16,58,99,6.0,4,76,Urban,ML Engineer,45886,0 +56980,Female,31,Masters,16,27,57,69,56,0.0,7,15,Urban,Data Analyst,67963,0 +56981,Female,57,Diploma,2,71,5,66,89,4.0,3,95,Rural,ML Engineer,32271,0 +56982,Female,26,Diploma,17,89,97,90,28,6.0,1,72,Semi-Urban,Manager,108710,1 +56983,Male,47,PhD,3,56,11,97,69,2.0,1,58,Rural,HR Executive,110005,0 +56984,Male,55,Bachelors,17,89,12,42,24,8.0,3,35,Urban,ML Engineer,22841,0 +56985,Male,28,Masters,18,95,14,54,22,3.0,0,93,Rural,ML Engineer,117847,1 +56986,Male,25,PhD,4,38,28,61,12,2.0,3,24,Urban,Software Engineer,90709,0 +56987,Female,25,High School,13,6,81,7,70,8.0,2,79,Urban,HR Executive,83702,0 +56988,Female,29,Bachelors,2,75,77,32,67,8.0,2,38,Urban,Software Engineer,149767,0 +56989,Male,35,Bachelors,11,60,20,63,54,7.0,7,56,Semi-Urban,Software Engineer,29015,0 +56990,Female,39,Diploma,10,60,66,22,10,4.0,0,55,Urban,HR Executive,149209,0 +56991,Female,31,Bachelors,10,13,1,79,96,1.0,6,87,Urban,ML Engineer,68621,0 +56992,Female,21,Masters,14,36,37,54,24,9.0,1,45,Urban,Software Engineer,114951,0 +56993,Male,36,Bachelors,12,74,21,86,50,0.0,1,78,Urban,Software Engineer,107160,1 +56994,Female,58,Masters,16,11,69,60,70,9.0,4,73,Rural,Data Analyst,24635,0 +56995,Female,23,Bachelors,6,53,15,67,16,2.0,5,13,Semi-Urban,Data Analyst,32484,0 +56996,Female,50,Masters,12,69,34,63,65,6.0,3,84,Urban,ML Engineer,65128,1 +56997,Male,58,Bachelors,19,42,66,52,35,3.0,1,96,Urban,HR Executive,38757,1 +56998,Male,36,Bachelors,11,51,30,16,1,8.0,2,16,Semi-Urban,Data Analyst,95889,0 +56999,Male,30,Diploma,9,98,7,55,46,3.0,2,64,Urban,Manager,136252,0 +57000,Male,34,Bachelors,19,63,49,44,7,3.0,7,25,Semi-Urban,Manager,93892,0 +57001,Male,35,Bachelors,5,36,69,54,64,5.0,6,34,Urban,ML Engineer,82221,0 +57002,Male,36,Bachelors,6,6,59,64,99,4.0,0,79,Rural,Manager,149739,0 +57003,Male,47,Bachelors,2,2,94,98,53,4.0,5,11,Semi-Urban,Software Engineer,138098,0 +57004,Male,32,Masters,3,3,71,3,2,0.0,6,1,Rural,Data Analyst,86096,0 +57005,Female,49,Bachelors,15,86,14,66,56,8.0,0,71,Semi-Urban,Data Analyst,84046,0 +57006,Male,43,Bachelors,5,87,27,70,8,6.0,2,83,Urban,ML Engineer,144410,1 +57007,Male,33,Diploma,6,5,3,88,13,1.0,3,11,Semi-Urban,HR Executive,51250,0 +57008,Male,21,Bachelors,16,96,96,8,17,7.0,0,27,Urban,Manager,148370,0 +57009,Male,31,High School,16,89,12,16,23,8.0,3,35,Semi-Urban,Manager,132288,0 +57010,Female,33,Diploma,13,97,16,33,40,2.0,5,6,Semi-Urban,Data Analyst,92300,0 +57011,Male,29,High School,0,35,97,80,45,4.0,1,81,Semi-Urban,ML Engineer,48115,1 +57012,Female,44,Diploma,9,51,70,51,81,3.0,7,60,Urban,HR Executive,40985,0 +57013,Male,23,Bachelors,11,10,3,57,58,2.0,3,52,Semi-Urban,Manager,141548,0 +57014,Male,49,High School,12,38,55,43,54,7.0,0,19,Urban,Manager,99469,0 +57015,Female,25,Bachelors,10,71,82,41,8,9.0,1,61,Semi-Urban,Data Analyst,88172,1 +57016,Female,43,Masters,10,37,23,79,40,5.0,2,55,Urban,Data Analyst,97226,0 +57017,Male,37,High School,10,75,59,82,44,2.0,5,63,Urban,HR Executive,81697,1 +57018,Female,36,Diploma,1,30,40,55,22,1.0,0,92,Urban,Software Engineer,110076,0 +57019,Female,46,Masters,13,24,25,74,23,6.0,0,28,Urban,HR Executive,127045,0 +57020,Male,32,Bachelors,8,39,86,92,52,6.0,3,27,Urban,HR Executive,22229,1 +57021,Female,33,Diploma,14,11,54,18,90,6.0,0,16,Semi-Urban,Software Engineer,118313,0 +57022,Female,27,Bachelors,18,4,8,40,2,2.0,0,33,Rural,HR Executive,120254,0 +57023,Male,47,High School,2,42,13,96,74,1.0,7,8,Urban,ML Engineer,127947,0 +57024,Female,55,Bachelors,5,40,61,49,74,3.0,0,98,Urban,Software Engineer,99832,1 +57025,Male,21,High School,9,72,18,60,58,0.0,4,61,Urban,Software Engineer,74964,0 +57026,Male,31,Masters,4,39,22,36,83,0.0,6,54,Rural,ML Engineer,52880,0 +57027,Male,52,High School,12,71,80,36,93,5.0,2,59,Urban,ML Engineer,134921,1 +57028,Female,22,Masters,10,89,55,23,77,4.0,7,93,Semi-Urban,HR Executive,110627,1 +57029,Female,21,PhD,5,21,94,20,4,2.0,5,71,Urban,HR Executive,33972,0 +57030,Male,57,Masters,15,63,9,21,64,5.0,7,2,Urban,Data Analyst,70338,0 +57031,Male,46,Bachelors,15,66,29,82,52,6.0,3,55,Urban,ML Engineer,84885,0 +57032,Male,46,Diploma,4,97,87,6,41,7.0,4,37,Semi-Urban,HR Executive,101119,0 +57033,Male,47,Bachelors,13,31,96,32,6,2.0,2,29,Semi-Urban,Data Analyst,46293,0 +57034,Female,41,High School,5,56,98,51,64,7.0,2,67,Urban,HR Executive,39904,1 +57035,Female,56,Diploma,10,14,35,90,61,7.0,7,31,Rural,HR Executive,27658,0 +57036,Male,38,Masters,9,31,0,95,58,1.0,6,36,Urban,ML Engineer,132225,0 +57037,Male,54,Diploma,4,43,62,93,17,7.0,7,46,Urban,Data Analyst,134523,1 +57038,Male,43,Bachelors,15,56,40,11,30,0.0,5,36,Urban,HR Executive,21271,0 +57039,Male,23,Bachelors,13,24,40,58,16,2.0,7,78,Semi-Urban,HR Executive,44901,0 +57040,Female,48,Bachelors,13,98,27,98,56,3.0,0,33,Rural,Software Engineer,131487,1 +57041,Male,38,High School,15,21,96,85,42,3.0,3,26,Urban,HR Executive,30699,0 +57042,Male,48,Bachelors,6,15,42,39,94,6.0,7,91,Urban,HR Executive,133469,0 +57043,Male,56,High School,19,97,41,64,34,1.0,7,84,Semi-Urban,ML Engineer,98363,1 +57044,Other,24,Bachelors,6,22,37,12,10,3.0,1,41,Urban,HR Executive,50990,0 +57045,Male,43,Bachelors,11,21,97,54,54,0.0,3,11,Urban,Manager,123898,0 +57046,Male,31,Bachelors,1,1,38,77,14,3.0,1,40,Rural,Manager,132753,0 +57047,Other,52,Bachelors,8,73,30,2,76,6.0,4,56,Urban,Manager,88823,0 +57048,Male,38,Diploma,16,61,31,72,75,0.0,3,87,Semi-Urban,ML Engineer,97636,1 +57049,Female,42,Masters,4,41,5,20,70,6.0,3,99,Urban,Software Engineer,77100,0 +57050,Female,29,Bachelors,4,76,24,70,4,9.0,0,48,Urban,Software Engineer,39479,0 +57051,Male,33,Masters,0,67,15,99,78,3.0,7,92,Urban,HR Executive,98994,1 +57052,Male,40,Bachelors,15,69,17,96,47,7.0,2,76,Urban,Software Engineer,71488,1 +57053,Male,58,Masters,6,33,10,39,87,3.0,1,63,Semi-Urban,ML Engineer,125902,0 +57054,Female,42,High School,5,93,80,5,17,0.0,4,77,Rural,Data Analyst,112054,1 +57055,Female,50,Bachelors,15,51,48,48,11,7.0,4,88,Rural,HR Executive,110198,0 +57056,Female,29,Bachelors,1,86,54,79,37,0.0,6,9,Rural,Software Engineer,96258,0 +57057,Male,58,Diploma,7,84,80,38,10,2.0,7,30,Urban,Manager,90100,0 +57058,Male,59,Bachelors,19,80,62,38,22,7.0,2,80,Urban,ML Engineer,87619,1 +57059,Male,45,Bachelors,14,51,66,89,10,8.0,2,2,Urban,ML Engineer,92328,0 +57060,Female,23,Bachelors,6,64,1,60,65,2.0,7,17,Rural,Manager,38546,0 +57061,Female,25,Bachelors,12,71,95,93,2,7.0,3,72,Semi-Urban,Software Engineer,143578,1 +57062,Male,55,Bachelors,17,80,91,95,81,6.0,2,85,Semi-Urban,Data Analyst,137797,1 +57063,Male,50,Bachelors,8,3,42,44,0,3.0,2,75,Urban,Manager,66760,0 +57064,Female,53,Masters,9,98,16,33,48,7.0,3,79,Urban,Data Analyst,136749,0 +57065,Male,43,Diploma,18,74,59,64,38,9.0,7,28,Rural,Data Analyst,56596,0 +57066,Male,52,Diploma,4,30,16,2,80,3.0,3,52,Urban,ML Engineer,68557,0 +57067,Male,56,High School,3,2,30,5,2,8.0,0,22,Urban,Data Analyst,138096,0 +57068,Male,42,Bachelors,8,59,26,16,91,5.0,3,24,Rural,ML Engineer,144979,0 +57069,Male,51,Masters,16,96,18,97,97,5.0,2,96,Semi-Urban,ML Engineer,134944,1 +57070,Male,47,Bachelors,18,28,45,4,82,2.0,5,19,Rural,Data Analyst,60696,0 +57071,Male,57,Diploma,12,83,6,45,14,6.0,6,48,Urban,Data Analyst,20158,0 +57072,Male,33,High School,2,17,4,63,78,5.0,6,95,Urban,Manager,22791,0 +57073,Male,35,Diploma,8,34,61,60,94,2.0,7,11,Urban,Data Analyst,110623,0 +57074,Male,44,Masters,16,70,18,34,11,1.0,5,42,Rural,HR Executive,122682,0 +57075,Male,48,Diploma,4,27,9,48,14,2.0,5,40,Semi-Urban,Manager,84366,0 +57076,Male,57,High School,17,63,99,80,11,9.0,4,54,Urban,Data Analyst,52902,1 +57077,Male,53,Bachelors,10,67,64,32,20,1.0,2,82,Urban,HR Executive,96674,1 +57078,Female,23,High School,19,38,67,69,57,5.0,7,47,Rural,ML Engineer,71391,0 +57079,Male,26,High School,13,56,62,78,75,7.0,5,23,Rural,Data Analyst,38891,0 +57080,Male,57,Diploma,10,70,99,82,43,1.0,3,78,Urban,Data Analyst,146408,1 +57081,Male,26,Diploma,0,88,60,34,79,2.0,2,50,Semi-Urban,ML Engineer,83541,0 +57082,Female,22,PhD,17,33,3,15,56,2.0,1,71,Semi-Urban,Data Analyst,23087,0 +57083,Male,55,Masters,14,26,11,60,17,1.0,5,71,Urban,ML Engineer,125248,0 +57084,Male,21,Masters,15,29,37,88,60,2.0,5,15,Rural,Software Engineer,33501,0 +57085,Female,43,Masters,9,66,96,99,60,5.0,5,43,Semi-Urban,Software Engineer,127078,1 +57086,Male,50,Diploma,5,34,75,96,13,2.0,0,34,Urban,Software Engineer,133205,1 +57087,Other,54,Masters,19,90,55,89,9,4.0,6,68,Rural,Data Analyst,73509,1 +57088,Female,59,Bachelors,3,63,13,60,27,7.0,0,44,Urban,ML Engineer,38398,0 +57089,Female,54,Bachelors,3,86,28,5,11,3.0,5,70,Semi-Urban,Software Engineer,98562,0 +57090,Male,53,High School,1,9,78,0,45,3.0,6,39,Urban,Manager,115703,0 +57091,Male,36,Bachelors,15,8,0,0,77,4.0,3,45,Rural,ML Engineer,119648,0 +57092,Female,49,Bachelors,16,54,83,88,6,6.0,5,99,Rural,Manager,127518,1 +57093,Male,36,Masters,9,99,13,55,71,7.0,1,52,Urban,HR Executive,80309,0 +57094,Male,31,Bachelors,1,74,52,3,8,9.0,3,14,Rural,ML Engineer,50849,0 +57095,Male,29,PhD,11,15,9,2,25,8.0,2,59,Urban,Data Analyst,45133,0 +57096,Male,39,PhD,12,98,90,49,42,8.0,4,57,Rural,Data Analyst,95768,1 +57097,Male,59,Diploma,9,34,58,7,15,5.0,2,30,Urban,HR Executive,99955,0 +57098,Male,35,Diploma,14,46,23,7,37,2.0,0,76,Urban,Manager,41605,0 +57099,Male,26,Bachelors,18,23,52,31,37,3.0,4,58,Semi-Urban,HR Executive,38727,0 +57100,Male,59,Bachelors,15,52,32,11,92,5.0,7,69,Rural,Manager,142163,0 +57101,Female,24,Diploma,18,55,73,57,65,8.0,7,6,Rural,Data Analyst,72578,0 +57102,Male,25,Diploma,19,71,67,83,66,5.0,3,36,Urban,Data Analyst,45568,1 +57103,Male,28,PhD,9,35,41,86,96,0.0,6,23,Semi-Urban,Software Engineer,97317,0 +57104,Female,22,Bachelors,12,25,78,71,20,9.0,4,6,Semi-Urban,ML Engineer,113856,0 +57105,Female,56,Diploma,7,86,23,48,55,7.0,5,29,Semi-Urban,Manager,143405,0 +57106,Male,40,Bachelors,17,79,58,48,59,6.0,5,89,Urban,Software Engineer,133434,1 +57107,Female,39,Masters,13,44,32,56,42,0.0,4,18,Urban,Data Analyst,107105,0 +57108,Male,27,Bachelors,15,63,64,37,16,5.0,4,33,Urban,Software Engineer,20157,0 +57109,Male,52,Bachelors,2,49,58,33,98,3.0,4,81,Semi-Urban,HR Executive,109787,0 +57110,Female,44,Masters,11,36,49,73,61,0.0,7,57,Urban,Data Analyst,119985,0 +57111,Male,50,Bachelors,18,76,53,44,86,0.0,3,60,Semi-Urban,Data Analyst,103898,0 +57112,Female,55,Bachelors,14,93,15,54,79,3.0,4,91,Urban,Manager,60780,1 +57113,Male,28,Bachelors,9,9,82,55,96,2.0,5,7,Urban,ML Engineer,78552,0 +57114,Female,57,Bachelors,1,31,10,4,60,5.0,7,72,Urban,Manager,132764,0 +57115,Male,38,High School,0,46,54,17,21,2.0,7,51,Urban,HR Executive,149068,0 +57116,Male,57,Diploma,2,0,38,25,52,7.0,6,15,Urban,Data Analyst,71697,0 +57117,Female,25,Masters,17,34,34,74,80,5.0,2,67,Urban,HR Executive,89350,0 +57118,Female,30,PhD,4,8,81,25,7,0.0,0,68,Urban,ML Engineer,111144,0 +57119,Other,55,Diploma,19,58,86,54,35,0.0,3,11,Rural,HR Executive,64576,0 +57120,Male,48,PhD,7,63,14,41,5,0.0,0,17,Rural,HR Executive,82748,0 +57121,Male,33,Masters,6,97,57,98,56,5.0,0,54,Urban,Software Engineer,124729,1 +57122,Female,56,High School,12,23,81,40,1,8.0,6,73,Urban,Software Engineer,58505,0 +57123,Male,33,Masters,6,68,2,67,89,0.0,7,51,Urban,Software Engineer,40470,0 +57124,Male,43,Bachelors,4,44,95,78,74,6.0,4,13,Urban,ML Engineer,99852,0 +57125,Male,21,Diploma,17,56,56,49,0,2.0,5,74,Semi-Urban,ML Engineer,105407,1 +57126,Other,47,Bachelors,18,88,92,50,0,7.0,7,39,Urban,ML Engineer,49216,1 +57127,Male,41,PhD,3,28,37,4,61,8.0,1,88,Urban,ML Engineer,45364,0 +57128,Female,32,High School,1,19,35,85,94,0.0,1,14,Semi-Urban,Manager,21535,0 +57129,Male,29,Bachelors,4,53,23,92,64,7.0,5,67,Urban,HR Executive,80398,1 +57130,Male,27,Bachelors,16,85,68,99,13,4.0,7,42,Urban,HR Executive,57604,1 +57131,Female,26,Masters,8,64,27,13,49,7.0,6,9,Semi-Urban,Software Engineer,69493,0 +57132,Male,58,Bachelors,14,9,98,32,14,1.0,4,39,Semi-Urban,Software Engineer,69039,0 +57133,Male,47,Bachelors,8,5,50,39,89,9.0,5,37,Rural,ML Engineer,37713,0 +57134,Male,41,Diploma,12,84,95,28,4,0.0,5,86,Urban,HR Executive,147609,1 +57135,Male,47,Diploma,16,84,88,94,11,3.0,4,82,Urban,Manager,43647,1 +57136,Female,46,Diploma,7,5,25,42,80,5.0,0,40,Rural,Manager,53058,0 +57137,Male,52,Masters,5,89,91,80,31,9.0,1,69,Urban,ML Engineer,26147,1 +57138,Male,40,High School,8,48,9,16,16,0.0,5,44,Rural,HR Executive,26728,0 +57139,Male,22,Bachelors,11,64,27,95,90,9.0,5,62,Urban,Data Analyst,147996,1 +57140,Female,34,Bachelors,14,57,94,99,28,2.0,7,21,Urban,Manager,71886,1 +57141,Female,28,High School,9,94,47,95,90,6.0,1,58,Urban,Data Analyst,38886,1 +57142,Female,46,High School,4,37,52,73,40,9.0,7,28,Rural,ML Engineer,95860,0 +57143,Male,43,Bachelors,19,96,17,89,55,7.0,6,55,Rural,Data Analyst,133312,1 +57144,Male,45,Masters,19,36,40,38,71,4.0,6,93,Urban,HR Executive,38418,0 +57145,Male,57,High School,8,29,23,81,14,9.0,7,19,Urban,Manager,101058,0 +57146,Male,40,Bachelors,13,61,11,38,79,4.0,3,1,Semi-Urban,Data Analyst,122744,0 +57147,Male,42,Bachelors,14,42,93,82,79,5.0,4,57,Urban,Data Analyst,140700,1 +57148,Female,55,Bachelors,17,17,53,42,70,4.0,3,9,Semi-Urban,Data Analyst,47594,0 +57149,Other,32,Bachelors,19,8,46,81,84,0.0,7,12,Semi-Urban,HR Executive,116560,0 +57150,Female,35,Bachelors,9,26,29,37,19,1.0,5,0,Urban,Software Engineer,60967,0 +57151,Male,46,Diploma,0,9,19,66,45,5.0,5,94,Urban,Software Engineer,90982,0 +57152,Male,48,Diploma,6,19,80,7,36,0.0,2,8,Urban,Data Analyst,87250,0 +57153,Male,28,Bachelors,15,44,59,43,39,6.0,3,91,Urban,Software Engineer,139306,1 +57154,Female,21,Bachelors,15,1,84,41,96,4.0,4,89,Urban,ML Engineer,105745,0 +57155,Female,53,Bachelors,9,86,14,57,21,2.0,6,76,Rural,HR Executive,55264,0 +57156,Female,21,High School,19,1,60,5,66,4.0,3,77,Urban,ML Engineer,52254,0 +57157,Female,58,High School,15,45,9,62,17,1.0,0,16,Rural,Manager,119250,0 +57158,Female,21,Bachelors,14,52,63,51,70,3.0,4,62,Semi-Urban,Manager,32571,0 +57159,Male,29,Bachelors,6,25,34,26,16,4.0,4,75,Semi-Urban,HR Executive,139408,0 +57160,Male,35,Masters,11,58,87,90,13,0.0,3,28,Urban,Data Analyst,118244,1 +57161,Other,50,Masters,3,39,70,27,57,4.0,6,65,Urban,Manager,22120,0 +57162,Female,33,Bachelors,18,16,0,6,87,6.0,1,45,Rural,Software Engineer,99076,0 +57163,Female,24,Bachelors,11,31,72,39,68,7.0,7,32,Urban,Manager,36050,0 +57164,Male,32,Bachelors,13,78,54,76,55,4.0,7,14,Urban,Manager,72200,0 +57165,Male,59,Bachelors,0,48,24,57,79,0.0,6,27,Semi-Urban,HR Executive,94122,0 +57166,Male,41,Diploma,13,72,76,74,40,2.0,4,84,Urban,ML Engineer,138943,1 +57167,Male,54,Masters,12,54,6,67,48,8.0,0,87,Urban,Data Analyst,91744,0 +57168,Female,41,Bachelors,17,26,62,15,79,9.0,4,30,Urban,Manager,106959,0 +57169,Male,47,Masters,9,42,28,27,79,5.0,1,94,Urban,Software Engineer,128515,0 +57170,Other,58,Bachelors,1,27,67,13,59,0.0,3,70,Rural,Data Analyst,124280,0 +57171,Male,57,Bachelors,16,86,16,53,86,7.0,2,90,Urban,Data Analyst,77326,1 +57172,Male,21,Diploma,1,83,62,67,10,9.0,4,40,Rural,HR Executive,102691,1 +57173,Male,50,Bachelors,4,70,15,82,76,0.0,2,15,Urban,Software Engineer,121092,0 +57174,Male,30,Bachelors,2,39,54,97,17,8.0,3,84,Urban,ML Engineer,88002,1 +57175,Female,39,Diploma,13,88,54,90,27,4.0,7,13,Rural,ML Engineer,54787,1 +57176,Male,28,Diploma,8,11,94,61,11,3.0,3,65,Urban,Data Analyst,105756,0 +57177,Male,22,Bachelors,9,75,67,21,17,7.0,0,17,Semi-Urban,Software Engineer,103399,0 +57178,Female,33,Masters,1,40,37,96,23,1.0,3,10,Urban,Manager,87844,0 +57179,Male,24,Bachelors,11,50,17,2,79,6.0,0,20,Urban,HR Executive,106613,0 +57180,Male,55,High School,13,38,35,51,84,8.0,6,30,Urban,Manager,24798,0 +57181,Male,53,Diploma,18,32,21,62,13,2.0,0,11,Rural,ML Engineer,58290,0 +57182,Female,30,Bachelors,0,2,8,17,7,7.0,0,77,Urban,HR Executive,119430,0 +57183,Female,26,Bachelors,8,39,43,91,91,8.0,5,60,Semi-Urban,Manager,45340,0 +57184,Female,57,Bachelors,0,52,81,22,93,0.0,7,90,Urban,HR Executive,57590,1 +57185,Female,37,Masters,16,36,57,6,75,7.0,4,79,Urban,Data Analyst,94999,0 +57186,Male,56,High School,19,52,94,45,16,8.0,3,89,Semi-Urban,HR Executive,85269,1 +57187,Male,40,Bachelors,15,3,27,1,91,8.0,3,34,Semi-Urban,Data Analyst,127764,0 +57188,Female,43,Bachelors,15,56,10,73,89,9.0,1,53,Rural,Data Analyst,28482,0 +57189,Female,45,Bachelors,2,6,73,14,20,7.0,1,34,Semi-Urban,Manager,83151,0 +57190,Female,46,PhD,4,23,96,39,21,6.0,4,41,Rural,Software Engineer,36906,0 +57191,Male,50,Bachelors,7,41,49,31,11,7.0,0,79,Urban,ML Engineer,123366,0 +57192,Male,54,Diploma,10,80,26,41,59,7.0,2,94,Semi-Urban,ML Engineer,122670,1 +57193,Male,29,Bachelors,12,27,30,88,70,3.0,2,90,Urban,Manager,137177,1 +57194,Male,26,Masters,13,25,99,79,89,4.0,4,19,Urban,Software Engineer,138314,0 +57195,Male,26,Masters,12,31,91,94,37,1.0,5,63,Semi-Urban,HR Executive,124680,1 +57196,Female,25,Diploma,0,54,44,10,21,9.0,7,11,Rural,Data Analyst,76781,0 +57197,Male,23,Bachelors,18,81,40,94,36,8.0,1,90,Urban,Manager,79659,1 +57198,Male,57,Bachelors,2,50,2,17,45,9.0,4,42,Semi-Urban,ML Engineer,27718,0 +57199,Other,46,Masters,13,44,34,74,53,4.0,1,86,Semi-Urban,Software Engineer,38019,0 +57200,Male,56,Masters,0,59,45,99,1,6.0,1,8,Urban,Software Engineer,134831,0 +57201,Male,38,Bachelors,4,29,8,99,2,8.0,0,37,Rural,ML Engineer,34998,0 +57202,Female,38,Bachelors,3,8,98,84,72,5.0,5,74,Urban,ML Engineer,140890,1 +57203,Female,50,Bachelors,11,25,64,40,35,2.0,6,15,Urban,ML Engineer,51901,0 +57204,Male,37,High School,13,85,62,4,91,1.0,6,0,Semi-Urban,ML Engineer,27545,0 +57205,Female,39,Bachelors,18,65,12,56,19,9.0,0,1,Semi-Urban,Software Engineer,89284,0 +57206,Male,34,Masters,3,98,43,98,18,9.0,3,43,Semi-Urban,Manager,71570,1 +57207,Female,45,Diploma,5,10,58,24,56,5.0,5,69,Urban,HR Executive,71147,0 +57208,Male,36,Bachelors,8,74,2,9,16,1.0,5,57,Urban,HR Executive,52889,0 +57209,Male,45,Bachelors,5,0,65,99,24,8.0,3,72,Urban,HR Executive,147132,1 +57210,Male,42,Masters,7,41,53,96,14,2.0,0,53,Semi-Urban,ML Engineer,51576,1 +57211,Female,52,Masters,4,9,0,51,6,9.0,6,45,Urban,ML Engineer,49961,0 +57212,Female,32,Bachelors,10,40,5,42,33,2.0,6,45,Urban,HR Executive,48078,0 +57213,Female,47,Diploma,2,69,26,21,19,8.0,1,42,Rural,Data Analyst,72846,0 +57214,Male,35,Masters,5,68,36,1,86,3.0,4,26,Urban,HR Executive,108695,0 +57215,Female,51,Masters,18,81,46,71,31,3.0,3,3,Rural,Software Engineer,115696,0 +57216,Male,39,Bachelors,4,80,36,34,93,8.0,5,10,Urban,ML Engineer,86949,0 +57217,Male,49,Bachelors,1,76,94,10,0,0.0,3,50,Rural,Data Analyst,40820,0 +57218,Male,50,Diploma,19,29,58,68,22,8.0,1,57,Urban,ML Engineer,149962,0 +57219,Male,46,Bachelors,11,83,18,55,19,3.0,2,69,Rural,HR Executive,74463,0 +57220,Male,45,High School,15,39,8,12,78,7.0,5,38,Urban,Data Analyst,115508,0 +57221,Female,51,Bachelors,4,31,34,35,96,7.0,7,62,Urban,ML Engineer,126527,0 +57222,Male,59,High School,8,66,24,69,3,2.0,4,3,Semi-Urban,Manager,58728,0 +57223,Male,22,Bachelors,3,83,10,11,93,8.0,4,16,Urban,HR Executive,134415,0 +57224,Female,51,High School,18,16,34,66,71,6.0,0,41,Urban,Manager,115024,0 +57225,Male,34,Masters,0,1,70,54,93,6.0,2,51,Semi-Urban,Software Engineer,139565,0 +57226,Male,36,High School,3,15,87,37,28,1.0,7,92,Urban,Manager,70575,0 +57227,Male,58,Diploma,12,16,88,80,45,8.0,7,50,Rural,Software Engineer,68002,0 +57228,Male,51,Diploma,8,35,11,55,63,4.0,6,10,Semi-Urban,ML Engineer,48260,0 +57229,Female,27,High School,3,93,7,21,40,2.0,1,77,Rural,HR Executive,60471,0 +57230,Female,45,Diploma,1,21,32,48,99,6.0,0,49,Semi-Urban,Software Engineer,20483,0 +57231,Male,42,Bachelors,7,19,3,47,77,1.0,1,33,Urban,HR Executive,126832,0 +57232,Male,32,Bachelors,5,10,3,71,33,2.0,4,24,Rural,Manager,47979,0 +57233,Male,27,Masters,7,98,6,91,12,7.0,7,45,Semi-Urban,Software Engineer,22975,1 +57234,Male,25,Bachelors,8,27,40,48,76,1.0,6,60,Urban,Data Analyst,53928,0 +57235,Male,45,High School,14,10,79,45,51,0.0,1,13,Semi-Urban,Software Engineer,73258,0 +57236,Male,55,High School,16,44,77,28,99,6.0,5,61,Rural,ML Engineer,94491,0 +57237,Female,38,Bachelors,4,88,30,4,19,0.0,6,6,Urban,Data Analyst,84355,0 +57238,Male,39,High School,12,49,20,48,97,4.0,4,79,Urban,HR Executive,125261,0 +57239,Male,52,High School,1,11,83,48,97,7.0,5,6,Urban,Software Engineer,143216,0 +57240,Male,56,Bachelors,16,78,1,46,46,7.0,1,43,Rural,Software Engineer,126273,0 +57241,Male,33,High School,3,86,67,64,26,7.0,1,44,Semi-Urban,Manager,44907,1 +57242,Male,26,Diploma,10,58,59,14,64,1.0,5,25,Urban,ML Engineer,86351,0 +57243,Female,26,Masters,15,69,26,36,87,3.0,1,77,Urban,Data Analyst,46803,0 +57244,Male,22,Masters,16,27,8,6,58,6.0,0,29,Semi-Urban,Data Analyst,36620,0 +57245,Male,28,Bachelors,2,91,11,64,80,9.0,2,65,Semi-Urban,Software Engineer,93042,0 +57246,Male,49,Masters,13,28,97,91,22,6.0,5,6,Semi-Urban,Manager,113108,0 +57247,Male,51,High School,7,26,77,73,23,6.0,3,85,Rural,Manager,28482,1 +57248,Male,22,Diploma,8,91,32,79,1,3.0,0,5,Urban,Data Analyst,121846,0 +57249,Male,29,Bachelors,5,17,2,16,23,3.0,1,68,Semi-Urban,ML Engineer,79157,0 +57250,Male,32,Bachelors,9,30,60,97,55,4.0,4,85,Semi-Urban,Software Engineer,35687,1 +57251,Male,55,Masters,1,45,98,87,83,7.0,2,74,Urban,Manager,140092,1 +57252,Female,33,Bachelors,5,85,85,61,38,5.0,6,8,Rural,Manager,58491,0 +57253,Male,46,Bachelors,9,26,40,52,1,0.0,4,64,Rural,HR Executive,110193,0 +57254,Female,48,Masters,6,7,65,83,36,2.0,7,44,Urban,ML Engineer,90416,0 +57255,Female,59,Bachelors,1,50,0,87,40,7.0,7,71,Urban,Software Engineer,57665,0 +57256,Other,42,Masters,6,51,89,59,52,3.0,5,68,Urban,Software Engineer,29973,1 +57257,Male,50,Diploma,1,43,69,54,91,4.0,7,33,Rural,Data Analyst,77258,0 +57258,Female,59,Bachelors,1,52,23,58,5,2.0,3,64,Rural,Software Engineer,32160,0 +57259,Male,47,Bachelors,4,18,74,70,79,3.0,2,31,Urban,Data Analyst,77052,0 +57260,Male,43,Masters,19,73,47,37,15,6.0,0,0,Urban,ML Engineer,46417,0 +57261,Female,32,Bachelors,16,53,7,40,58,1.0,7,13,Urban,Data Analyst,138987,0 +57262,Male,55,Bachelors,10,99,58,28,99,1.0,5,90,Urban,Manager,128147,1 +57263,Male,44,Bachelors,14,16,50,73,52,9.0,2,58,Urban,Manager,81339,0 +57264,Male,41,Diploma,16,38,40,25,24,5.0,6,52,Urban,Software Engineer,38955,0 +57265,Male,43,High School,17,30,20,76,63,1.0,7,72,Semi-Urban,Data Analyst,131921,0 +57266,Female,21,Bachelors,8,98,28,49,31,4.0,4,11,Rural,Manager,77717,0 +57267,Male,47,PhD,1,22,66,18,91,6.0,5,0,Urban,ML Engineer,23313,0 +57268,Female,36,Masters,14,33,84,87,50,4.0,5,28,Urban,Data Analyst,124802,0 +57269,Female,58,Masters,7,37,54,67,55,0.0,6,81,Rural,Manager,45602,0 +57270,Female,40,PhD,3,19,97,8,42,3.0,2,31,Urban,ML Engineer,142053,0 +57271,Female,28,Masters,0,86,86,43,39,9.0,3,4,Rural,ML Engineer,132442,0 +57272,Male,54,High School,8,95,17,79,55,5.0,0,63,Urban,HR Executive,58325,1 +57273,Male,34,Diploma,3,99,75,2,29,6.0,4,18,Urban,HR Executive,33656,0 +57274,Male,22,Diploma,14,1,75,30,94,8.0,5,0,Urban,Manager,34278,0 +57275,Female,24,High School,12,9,33,61,69,4.0,6,91,Semi-Urban,ML Engineer,32279,0 +57276,Male,32,High School,17,72,93,90,73,0.0,7,73,Semi-Urban,ML Engineer,40207,1 +57277,Female,47,Masters,4,78,47,93,66,6.0,5,45,Rural,Software Engineer,53662,1 +57278,Male,54,Bachelors,17,34,37,15,9,4.0,3,65,Urban,Software Engineer,87146,0 +57279,Male,25,Masters,17,59,95,65,92,0.0,3,53,Urban,Data Analyst,109948,1 +57280,Male,53,Masters,11,74,85,83,21,0.0,5,5,Semi-Urban,ML Engineer,72332,1 +57281,Female,47,Bachelors,7,31,53,90,62,1.0,4,81,Rural,Manager,100091,1 +57282,Other,38,Diploma,17,13,74,47,22,7.0,5,42,Rural,Manager,103026,0 +57283,Female,56,Bachelors,11,50,82,33,4,5.0,6,21,Rural,ML Engineer,79487,0 +57284,Male,25,Masters,16,12,41,84,74,8.0,4,76,Urban,Data Analyst,145655,0 +57285,Male,45,Diploma,0,66,56,64,98,5.0,0,31,Rural,Manager,141941,0 +57286,Male,54,Bachelors,6,2,88,24,68,1.0,3,61,Semi-Urban,ML Engineer,112680,0 +57287,Female,31,Masters,15,46,0,93,71,5.0,5,50,Urban,HR Executive,29417,0 +57288,Male,34,Masters,1,9,2,90,32,4.0,5,70,Urban,HR Executive,56164,0 +57289,Female,38,Masters,2,56,16,47,31,6.0,0,71,Urban,ML Engineer,145494,0 +57290,Male,41,High School,2,52,13,25,51,1.0,2,93,Semi-Urban,Manager,124208,0 +57291,Male,32,Bachelors,1,59,38,63,74,7.0,4,85,Rural,Software Engineer,43524,1 +57292,Female,46,Diploma,11,16,30,90,42,9.0,4,8,Semi-Urban,HR Executive,65072,0 +57293,Female,39,Bachelors,16,86,6,23,9,8.0,4,53,Semi-Urban,HR Executive,27058,0 +57294,Male,42,Bachelors,1,50,28,5,22,9.0,7,99,Urban,Software Engineer,143135,0 +57295,Male,59,Bachelors,0,91,98,53,38,0.0,0,78,Rural,Software Engineer,77687,1 +57296,Other,21,Masters,2,69,29,58,23,5.0,7,74,Rural,Data Analyst,35291,0 +57297,Female,47,PhD,12,91,51,81,23,1.0,1,1,Urban,Manager,126471,0 +57298,Female,22,Masters,2,35,26,20,52,7.0,4,46,Rural,Data Analyst,62918,0 +57299,Male,29,Bachelors,10,38,34,71,28,1.0,1,39,Rural,Manager,134685,0 +57300,Male,27,Bachelors,6,44,4,69,92,2.0,6,18,Semi-Urban,Data Analyst,58524,0 +57301,Male,48,High School,6,90,88,2,2,3.0,0,15,Urban,Manager,29770,0 +57302,Male,25,Diploma,18,1,11,59,45,3.0,5,20,Urban,Manager,132880,0 +57303,Male,23,Bachelors,18,19,47,39,57,2.0,0,65,Urban,Software Engineer,83191,0 +57304,Male,36,Diploma,16,47,95,10,58,1.0,3,35,Semi-Urban,Manager,43989,0 +57305,Other,53,Bachelors,6,89,28,89,80,7.0,1,90,Urban,Manager,39730,1 +57306,Male,34,Diploma,8,68,31,46,4,0.0,7,81,Semi-Urban,HR Executive,52728,0 +57307,Female,31,Masters,8,4,15,60,18,5.0,2,10,Rural,Software Engineer,52970,0 +57308,Female,32,Bachelors,3,50,90,98,92,1.0,1,14,Urban,Data Analyst,69050,1 +57309,Male,32,Masters,11,71,46,0,13,1.0,6,56,Urban,Manager,105922,0 +57310,Male,47,Diploma,13,3,76,89,1,1.0,1,12,Rural,Software Engineer,24747,0 +57311,Male,30,Bachelors,5,74,5,87,11,5.0,2,38,Urban,ML Engineer,76733,0 +57312,Female,34,Masters,7,70,30,5,37,3.0,4,94,Urban,HR Executive,109700,0 +57313,Female,53,Masters,5,45,77,50,18,4.0,5,42,Urban,Manager,137623,0 +57314,Male,33,Bachelors,19,27,15,4,96,9.0,0,9,Semi-Urban,ML Engineer,31117,0 +57315,Female,45,Diploma,9,15,84,48,46,9.0,3,91,Semi-Urban,Manager,147091,0 +57316,Male,53,High School,15,19,62,69,32,5.0,0,46,Urban,Software Engineer,80895,0 +57317,Male,59,Diploma,11,28,51,87,45,3.0,6,51,Semi-Urban,HR Executive,67140,0 +57318,Male,49,Masters,5,51,66,45,62,0.0,7,30,Rural,Software Engineer,120516,0 +57319,Female,30,Bachelors,5,92,1,18,92,5.0,0,24,Urban,HR Executive,20727,0 +57320,Male,34,Bachelors,2,12,30,4,69,5.0,7,42,Urban,Data Analyst,139945,0 +57321,Male,36,Diploma,0,80,52,59,30,5.0,6,43,Urban,HR Executive,132027,0 +57322,Male,35,Masters,6,83,57,70,13,9.0,6,25,Semi-Urban,ML Engineer,84840,1 +57323,Male,29,Bachelors,1,5,98,73,59,0.0,0,84,Urban,HR Executive,30544,1 +57324,Female,54,Diploma,3,23,45,13,58,9.0,2,91,Urban,HR Executive,110918,0 +57325,Male,22,Bachelors,17,26,71,30,69,3.0,6,42,Urban,Data Analyst,136727,0 +57326,Male,57,Bachelors,10,9,44,33,33,4.0,5,97,Urban,HR Executive,141969,0 +57327,Female,30,Bachelors,17,72,53,6,33,9.0,2,1,Semi-Urban,Data Analyst,105192,0 +57328,Female,36,Masters,8,54,13,50,2,8.0,3,19,Rural,Data Analyst,77494,0 +57329,Male,23,Masters,16,94,19,49,73,2.0,5,31,Urban,ML Engineer,129366,0 +57330,Male,53,High School,10,55,18,9,59,8.0,4,74,Rural,HR Executive,136700,0 +57331,Male,35,Bachelors,16,71,46,68,2,2.0,6,54,Rural,Software Engineer,117917,1 +57332,Female,35,Bachelors,14,52,95,4,86,7.0,1,6,Semi-Urban,Software Engineer,142490,0 +57333,Female,57,Bachelors,11,97,42,99,7,2.0,2,27,Urban,Manager,67253,1 +57334,Male,50,Masters,3,16,13,59,86,6.0,4,27,Semi-Urban,Manager,21450,0 +57335,Female,35,Masters,10,21,48,68,7,6.0,0,32,Semi-Urban,Software Engineer,22073,0 +57336,Male,26,High School,12,47,22,32,70,4.0,3,63,Rural,HR Executive,127068,0 +57337,Female,22,Diploma,2,94,11,50,17,0.0,4,35,Urban,Software Engineer,117730,0 +57338,Male,43,High School,17,72,7,90,89,5.0,6,24,Semi-Urban,ML Engineer,90408,0 +57339,Male,55,Diploma,14,72,45,54,16,0.0,1,5,Rural,Software Engineer,137927,0 +57340,Female,22,Masters,0,72,75,52,61,9.0,3,17,Urban,HR Executive,87390,0 +57341,Male,21,Bachelors,13,44,73,5,64,1.0,1,36,Urban,Manager,109540,0 +57342,Female,37,Bachelors,17,12,82,8,20,9.0,6,64,Rural,Software Engineer,129296,0 +57343,Female,55,Bachelors,6,56,81,78,95,4.0,2,55,Urban,Manager,127065,1 +57344,Female,42,High School,12,0,14,98,3,1.0,2,8,Urban,Data Analyst,74745,0 +57345,Female,26,Diploma,8,77,4,60,54,3.0,5,50,Semi-Urban,Manager,77807,0 +57346,Male,43,High School,14,75,1,15,8,1.0,0,51,Urban,Manager,33465,0 +57347,Female,35,Bachelors,3,85,79,20,18,5.0,0,47,Rural,HR Executive,135942,0 +57348,Male,57,Diploma,12,97,47,44,12,0.0,2,67,Semi-Urban,HR Executive,112997,1 +57349,Male,44,Diploma,16,83,78,85,31,1.0,5,19,Semi-Urban,ML Engineer,95137,1 +57350,Male,31,High School,14,5,52,3,25,6.0,3,51,Urban,Software Engineer,149615,0 +57351,Female,22,Bachelors,12,83,22,78,3,0.0,5,45,Rural,HR Executive,84411,0 +57352,Male,58,High School,12,75,22,15,63,4.0,6,3,Urban,Software Engineer,122728,0 +57353,Female,52,High School,5,65,33,67,30,5.0,3,49,Urban,Manager,60669,0 +57354,Male,58,Bachelors,9,32,50,98,30,8.0,7,63,Urban,Software Engineer,136076,1 +57355,Male,23,Bachelors,1,72,75,81,33,7.0,2,25,Semi-Urban,HR Executive,110951,1 +57356,Other,52,Masters,13,12,92,33,24,2.0,2,82,Semi-Urban,HR Executive,102616,0 +57357,Male,29,Bachelors,9,92,55,74,66,2.0,2,44,Rural,ML Engineer,60691,1 +57358,Female,55,Diploma,6,69,56,86,77,3.0,2,63,Urban,Data Analyst,33411,1 +57359,Male,37,Bachelors,8,64,71,1,87,7.0,2,46,Urban,Data Analyst,25093,0 +57360,Female,42,Bachelors,16,88,72,87,31,4.0,2,65,Rural,ML Engineer,128516,1 +57361,Female,30,High School,12,13,40,35,39,6.0,6,78,Urban,Data Analyst,75480,0 +57362,Male,23,High School,7,27,76,66,78,7.0,1,45,Semi-Urban,HR Executive,59217,0 +57363,Male,29,High School,1,95,62,41,54,2.0,4,46,Rural,HR Executive,111441,1 +57364,Male,31,Bachelors,16,37,67,78,64,2.0,2,78,Rural,Software Engineer,145567,1 +57365,Male,33,High School,11,16,1,2,26,9.0,3,20,Urban,Software Engineer,72154,0 +57366,Female,26,Bachelors,1,30,59,18,49,0.0,1,46,Semi-Urban,Software Engineer,81492,0 +57367,Male,24,Masters,14,44,31,34,60,6.0,0,23,Urban,HR Executive,148051,0 +57368,Female,53,High School,3,45,27,15,17,8.0,0,2,Semi-Urban,HR Executive,29117,0 +57369,Male,24,Diploma,0,30,95,9,37,5.0,5,71,Urban,ML Engineer,119585,0 +57370,Male,27,Diploma,9,65,7,58,10,2.0,4,86,Semi-Urban,Data Analyst,144523,0 +57371,Male,41,Bachelors,13,63,32,29,92,3.0,2,35,Urban,Manager,112414,0 +57372,Male,21,Bachelors,5,7,38,3,19,9.0,3,78,Urban,HR Executive,53869,0 +57373,Male,25,Masters,11,25,4,44,74,2.0,5,54,Rural,HR Executive,144735,0 +57374,Male,45,Diploma,10,48,94,66,56,5.0,2,44,Semi-Urban,Manager,141509,1 +57375,Other,49,High School,13,87,28,67,66,8.0,6,20,Rural,HR Executive,88022,0 +57376,Other,29,Bachelors,17,98,4,30,73,9.0,4,23,Urban,Data Analyst,145818,0 +57377,Male,52,Diploma,2,50,84,42,16,0.0,3,87,Urban,HR Executive,145738,1 +57378,Male,53,Diploma,9,54,25,95,6,5.0,3,77,Urban,ML Engineer,77539,1 +57379,Female,55,Diploma,17,35,71,27,6,1.0,0,15,Urban,Software Engineer,92995,0 +57380,Female,23,High School,15,84,66,52,31,9.0,4,68,Urban,Data Analyst,59000,1 +57381,Male,35,Diploma,1,16,31,68,60,3.0,7,48,Rural,Data Analyst,95988,0 +57382,Female,42,High School,16,59,6,32,62,7.0,2,72,Rural,Software Engineer,35981,0 +57383,Male,30,Bachelors,4,55,20,32,53,8.0,6,72,Urban,ML Engineer,59901,0 +57384,Male,36,Masters,5,94,69,24,15,8.0,0,56,Urban,HR Executive,31691,1 +57385,Male,36,Masters,12,22,25,30,84,6.0,5,27,Semi-Urban,HR Executive,101618,0 +57386,Female,24,Diploma,9,56,47,86,30,8.0,5,25,Semi-Urban,HR Executive,32709,0 +57387,Male,42,Bachelors,15,73,69,49,89,7.0,7,7,Urban,Software Engineer,47710,0 +57388,Male,51,Masters,10,59,48,89,72,3.0,5,88,Rural,Software Engineer,35840,1 +57389,Female,24,Masters,19,78,39,64,33,7.0,2,96,Rural,Manager,120269,1 +57390,Female,45,High School,16,91,62,27,44,2.0,3,82,Semi-Urban,Software Engineer,37508,1 +57391,Male,35,Bachelors,3,0,53,51,51,3.0,5,76,Rural,HR Executive,28133,0 +57392,Female,55,Masters,17,1,44,20,24,0.0,1,22,Urban,ML Engineer,80487,0 +57393,Female,46,Masters,16,81,72,61,17,7.0,5,3,Semi-Urban,Data Analyst,93830,0 +57394,Male,40,Masters,19,3,38,91,28,8.0,2,60,Semi-Urban,HR Executive,65567,0 +57395,Male,41,Diploma,6,48,4,16,22,6.0,2,59,Rural,Data Analyst,78340,0 +57396,Male,34,Diploma,3,8,15,81,57,4.0,3,51,Urban,Data Analyst,66463,0 +57397,Other,22,Bachelors,4,62,97,17,44,1.0,7,78,Rural,Data Analyst,26735,1 +57398,Female,49,Diploma,6,96,51,19,22,1.0,6,47,Urban,Data Analyst,101328,0 +57399,Male,29,High School,13,96,82,53,97,2.0,3,96,Urban,HR Executive,70583,1 +57400,Male,47,Masters,18,29,20,51,38,3.0,1,89,Urban,HR Executive,89619,0 +57401,Female,21,Bachelors,19,0,27,71,91,3.0,4,60,Urban,ML Engineer,71107,0 +57402,Female,59,Diploma,8,40,28,67,55,4.0,5,15,Urban,Manager,147595,0 +57403,Male,59,High School,6,86,41,6,80,1.0,5,8,Semi-Urban,Manager,26885,0 +57404,Male,44,Diploma,14,65,57,77,31,5.0,5,7,Urban,ML Engineer,38154,0 +57405,Female,26,Diploma,16,10,59,89,98,1.0,1,92,Rural,Manager,70773,1 +57406,Male,40,Masters,14,2,37,62,74,4.0,6,7,Urban,Manager,62339,0 +57407,Female,51,Bachelors,2,18,59,41,71,1.0,5,93,Urban,ML Engineer,96431,0 +57408,Male,48,Masters,10,26,7,96,58,0.0,1,22,Urban,Software Engineer,98932,0 +57409,Female,39,High School,11,82,46,14,97,0.0,3,7,Rural,Software Engineer,116971,0 +57410,Male,53,Diploma,18,70,21,9,10,2.0,2,62,Urban,ML Engineer,93311,0 +57411,Female,47,Bachelors,14,3,93,2,17,0.0,4,61,Rural,Manager,38374,0 +57412,Male,55,High School,11,1,22,59,81,0.0,3,49,Urban,Software Engineer,85608,0 +57413,Female,21,PhD,8,80,90,73,91,6.0,6,9,Semi-Urban,Data Analyst,129274,1 +57414,Male,30,Diploma,3,11,59,90,9,5.0,2,35,Urban,Manager,81505,0 +57415,Male,33,Diploma,1,39,19,62,7,5.0,1,82,Urban,HR Executive,110298,0 +57416,Male,23,Bachelors,10,81,54,73,77,7.0,0,46,Rural,Software Engineer,24565,1 +57417,Female,51,Bachelors,10,87,18,51,69,6.0,2,58,Urban,Manager,129960,0 +57418,Female,26,Bachelors,1,84,90,3,88,8.0,4,30,Rural,HR Executive,78127,0 +57419,Female,50,Bachelors,2,95,21,35,44,8.0,7,95,Urban,ML Engineer,35614,1 +57420,Male,50,Bachelors,17,53,64,94,10,6.0,2,73,Rural,Manager,127492,1 +57421,Male,37,Masters,18,25,68,85,47,8.0,6,0,Rural,Data Analyst,35697,0 +57422,Male,47,Bachelors,3,49,91,58,4,7.0,4,0,Semi-Urban,Software Engineer,58814,0 +57423,Male,37,Bachelors,12,0,46,78,82,4.0,6,13,Urban,ML Engineer,131204,0 +57424,Female,35,Bachelors,12,44,5,28,59,2.0,3,39,Urban,Data Analyst,70742,0 +57425,Male,56,Bachelors,8,55,78,53,0,2.0,4,3,Urban,Manager,31960,0 +57426,Male,43,PhD,5,0,35,0,3,0.0,4,90,Semi-Urban,ML Engineer,69757,0 +57427,Female,28,Bachelors,17,43,68,84,38,2.0,6,55,Semi-Urban,Data Analyst,107469,1 +57428,Female,24,Bachelors,16,95,69,17,31,6.0,0,74,Urban,HR Executive,90390,1 +57429,Female,41,Bachelors,17,58,20,43,54,4.0,6,55,Urban,Data Analyst,85424,0 +57430,Female,42,Bachelors,5,43,0,63,76,6.0,0,59,Urban,ML Engineer,61295,0 +57431,Male,31,Bachelors,10,72,60,27,20,0.0,1,41,Urban,Software Engineer,105286,0 +57432,Female,46,Bachelors,7,81,3,13,1,2.0,3,56,Semi-Urban,HR Executive,139959,0 +57433,Male,46,Bachelors,19,18,11,38,72,8.0,4,97,Rural,Software Engineer,71755,0 +57434,Male,55,Masters,3,49,41,34,93,7.0,0,34,Urban,Data Analyst,133084,0 +57435,Male,58,Masters,19,80,83,83,10,4.0,3,78,Semi-Urban,HR Executive,64028,1 +57436,Male,31,Bachelors,19,10,20,28,2,8.0,0,76,Urban,Manager,76729,0 +57437,Male,51,High School,7,12,19,41,63,5.0,5,47,Urban,ML Engineer,149757,0 +57438,Male,22,Bachelors,18,31,0,83,9,5.0,3,17,Urban,Manager,32267,0 +57439,Other,44,Diploma,4,5,44,34,60,2.0,1,76,Urban,HR Executive,52220,0 +57440,Female,53,PhD,9,70,81,95,75,7.0,3,4,Semi-Urban,Manager,25904,1 +57441,Other,43,Diploma,15,31,87,64,32,3.0,6,18,Urban,Software Engineer,149308,0 +57442,Female,52,Bachelors,8,57,86,88,38,6.0,6,66,Urban,Data Analyst,22469,1 +57443,Other,58,Masters,0,41,85,72,79,0.0,4,52,Urban,ML Engineer,119420,1 +57444,Male,56,Diploma,12,89,44,62,11,3.0,7,91,Urban,Manager,143616,1 +57445,Male,27,Diploma,7,83,23,98,37,4.0,5,33,Urban,Software Engineer,76493,1 +57446,Male,57,Masters,10,74,39,77,71,8.0,0,51,Rural,Software Engineer,84741,1 +57447,Female,54,High School,3,82,89,27,51,2.0,1,65,Urban,Data Analyst,53390,1 +57448,Female,22,Masters,6,96,13,46,85,7.0,0,35,Rural,Software Engineer,50357,0 +57449,Male,26,Bachelors,19,67,82,74,1,7.0,4,90,Urban,Data Analyst,139386,1 +57450,Male,28,High School,13,78,10,23,33,0.0,4,57,Urban,Manager,35005,0 +57451,Male,37,Diploma,2,78,39,13,24,0.0,2,53,Urban,Data Analyst,101310,0 +57452,Male,23,Diploma,18,80,67,7,53,9.0,7,41,Semi-Urban,Software Engineer,58201,0 +57453,Female,25,Masters,9,55,59,82,61,9.0,2,58,Urban,Manager,144874,1 +57454,Male,22,High School,0,59,27,10,50,1.0,4,15,Semi-Urban,ML Engineer,134772,0 +57455,Female,33,PhD,11,14,47,86,4,7.0,4,29,Urban,Manager,43390,0 +57456,Female,23,Bachelors,10,31,10,5,23,0.0,6,63,Rural,Manager,52739,0 +57457,Male,32,Diploma,2,99,22,1,11,2.0,4,0,Rural,Data Analyst,33102,0 +57458,Other,45,Bachelors,9,3,86,99,9,1.0,7,97,Urban,Manager,76348,1 +57459,Other,57,Bachelors,14,60,74,71,13,2.0,1,84,Semi-Urban,Software Engineer,69039,1 +57460,Female,34,High School,12,3,10,67,71,4.0,4,26,Rural,ML Engineer,94937,0 +57461,Female,29,Masters,16,43,41,46,1,5.0,1,87,Rural,HR Executive,146726,0 +57462,Male,48,Bachelors,9,57,14,84,37,4.0,1,54,Urban,Software Engineer,119765,0 +57463,Other,51,Bachelors,4,60,40,9,88,6.0,7,64,Urban,Data Analyst,64052,0 +57464,Male,22,Masters,11,17,18,36,41,4.0,2,12,Urban,Software Engineer,59972,0 +57465,Female,37,Bachelors,7,60,11,85,27,3.0,4,74,Urban,ML Engineer,134026,0 +57466,Male,34,Diploma,3,6,82,40,41,2.0,6,8,Semi-Urban,ML Engineer,89371,0 +57467,Female,26,Diploma,9,45,21,43,49,5.0,1,57,Rural,Software Engineer,38039,0 +57468,Male,21,Bachelors,18,68,54,94,13,1.0,2,49,Urban,ML Engineer,138459,1 +57469,Male,29,Bachelors,11,44,29,27,11,7.0,5,79,Urban,Software Engineer,33306,0 +57470,Female,44,High School,14,54,5,16,17,1.0,6,70,Urban,HR Executive,46651,0 +57471,Female,44,Diploma,19,43,99,99,46,0.0,5,9,Rural,Software Engineer,127729,1 +57472,Female,32,Diploma,1,58,11,33,2,9.0,3,72,Semi-Urban,Software Engineer,67572,0 +57473,Male,31,High School,4,33,98,55,68,4.0,7,6,Urban,Software Engineer,58155,0 +57474,Female,56,High School,1,15,39,33,76,8.0,6,62,Urban,Software Engineer,87547,0 +57475,Female,46,Bachelors,0,71,70,77,36,7.0,4,37,Rural,Manager,142911,1 +57476,Male,43,High School,10,22,36,32,42,7.0,0,33,Urban,Data Analyst,26959,0 +57477,Female,59,Bachelors,10,88,81,93,43,7.0,1,71,Rural,Data Analyst,113630,1 +57478,Male,53,Bachelors,19,12,93,97,27,5.0,0,2,Rural,Manager,26832,0 +57479,Female,56,Bachelors,13,42,43,47,82,3.0,2,43,Rural,Data Analyst,53063,0 +57480,Male,52,Masters,7,55,57,84,35,7.0,4,41,Semi-Urban,Manager,107456,1 +57481,Male,46,PhD,6,29,18,19,62,8.0,7,77,Semi-Urban,Data Analyst,28816,0 +57482,Female,57,Diploma,18,21,3,64,17,7.0,4,56,Urban,Software Engineer,68559,0 +57483,Female,44,Bachelors,16,33,86,34,4,2.0,5,45,Urban,HR Executive,103026,0 +57484,Female,43,Bachelors,11,3,88,82,0,9.0,2,33,Urban,Data Analyst,146323,0 +57485,Female,50,Bachelors,10,40,60,59,29,7.0,5,58,Urban,ML Engineer,47629,0 +57486,Male,48,Bachelors,15,70,86,98,51,7.0,6,68,Urban,Manager,134263,1 +57487,Male,46,Bachelors,16,3,53,75,12,6.0,4,0,Semi-Urban,ML Engineer,119225,0 +57488,Male,55,Masters,5,36,89,10,32,5.0,7,58,Semi-Urban,Software Engineer,101568,0 +57489,Male,42,Diploma,12,91,19,59,54,1.0,6,33,Urban,HR Executive,55808,0 +57490,Male,47,Bachelors,9,21,70,90,0,3.0,5,6,Urban,Manager,50457,0 +57491,Female,22,Diploma,7,91,91,89,24,0.0,1,81,Urban,Data Analyst,73986,1 +57492,Male,54,Bachelors,15,82,74,98,80,2.0,5,62,Rural,HR Executive,113763,1 +57493,Female,31,Masters,0,43,58,89,47,4.0,2,15,Urban,HR Executive,82380,0 +57494,Male,43,Masters,3,31,62,3,8,1.0,1,13,Urban,Software Engineer,104016,0 +57495,Male,24,High School,8,49,83,56,59,2.0,7,13,Urban,Manager,33372,0 +57496,Male,29,Bachelors,1,91,59,25,73,2.0,4,74,Semi-Urban,Software Engineer,73678,1 +57497,Male,46,Masters,2,18,99,96,12,4.0,7,80,Urban,Data Analyst,77143,1 +57498,Male,48,Diploma,13,24,18,98,13,3.0,7,53,Semi-Urban,Software Engineer,107718,0 +57499,Female,53,Masters,19,35,47,14,87,8.0,1,0,Urban,HR Executive,131340,0 +57500,Male,41,High School,0,42,67,55,51,4.0,1,61,Semi-Urban,Manager,99082,0 +57501,Male,47,PhD,18,75,34,87,73,7.0,6,16,Urban,HR Executive,38491,0 +57502,Male,50,Bachelors,1,77,22,99,40,9.0,0,8,Urban,HR Executive,121492,0 +57503,Male,22,High School,1,51,17,35,90,8.0,4,7,Urban,ML Engineer,35150,0 +57504,Female,47,Bachelors,8,71,60,68,58,2.0,1,99,Urban,Software Engineer,24235,1 +57505,Male,41,Diploma,13,91,58,32,55,3.0,4,17,Semi-Urban,ML Engineer,137252,0 +57506,Male,35,Bachelors,6,4,54,49,89,9.0,0,55,Urban,HR Executive,139918,0 +57507,Male,27,High School,7,29,32,96,43,9.0,5,84,Rural,Software Engineer,101785,1 +57508,Other,38,Bachelors,13,14,96,2,41,9.0,3,13,Urban,Software Engineer,141953,0 +57509,Male,22,Bachelors,10,52,62,47,1,3.0,6,75,Urban,Software Engineer,83296,1 +57510,Male,52,Masters,2,62,41,25,19,4.0,0,62,Rural,Software Engineer,149971,0 +57511,Male,49,Diploma,18,10,99,20,43,4.0,3,48,Urban,HR Executive,75023,0 +57512,Female,44,Diploma,0,73,62,68,12,8.0,3,91,Urban,HR Executive,125208,1 +57513,Male,25,Masters,14,97,90,1,37,5.0,1,45,Urban,Manager,49266,0 +57514,Male,38,Masters,3,39,34,46,64,1.0,6,60,Urban,Software Engineer,33006,0 +57515,Female,39,Diploma,8,53,4,19,51,0.0,6,93,Semi-Urban,Data Analyst,33410,0 +57516,Male,44,Diploma,4,68,13,84,35,0.0,4,4,Urban,HR Executive,88680,0 +57517,Female,37,Diploma,17,61,26,45,16,5.0,3,85,Urban,Software Engineer,144040,0 +57518,Male,24,Masters,6,89,66,31,81,9.0,3,16,Semi-Urban,HR Executive,89785,0 +57519,Male,57,Diploma,1,95,50,39,60,1.0,7,66,Urban,Data Analyst,78272,1 +57520,Other,38,Bachelors,5,16,94,67,27,4.0,1,31,Urban,Manager,21576,0 +57521,Male,47,Bachelors,2,45,44,63,91,7.0,2,8,Semi-Urban,Manager,111425,0 +57522,Female,54,Bachelors,0,62,8,88,59,4.0,2,34,Rural,ML Engineer,45448,0 +57523,Female,22,Bachelors,0,81,60,43,0,5.0,2,50,Rural,Manager,75876,0 +57524,Male,37,High School,4,15,23,34,76,8.0,4,42,Semi-Urban,Software Engineer,82365,0 +57525,Male,54,Bachelors,16,73,75,45,30,2.0,2,73,Urban,Software Engineer,142807,1 +57526,Male,24,Diploma,17,35,75,23,2,5.0,1,81,Urban,Software Engineer,111721,0 +57527,Male,25,Masters,19,9,27,11,65,1.0,6,52,Urban,Data Analyst,142205,0 +57528,Male,32,High School,14,14,51,8,61,7.0,4,4,Semi-Urban,Manager,89220,0 +57529,Female,38,High School,6,9,38,9,33,4.0,4,98,Urban,Data Analyst,122429,0 +57530,Male,57,Diploma,16,61,27,44,95,0.0,7,89,Semi-Urban,Data Analyst,45396,0 +57531,Female,52,Bachelors,4,61,52,90,87,2.0,5,93,Semi-Urban,HR Executive,111008,1 +57532,Male,37,Bachelors,5,87,75,53,21,9.0,7,36,Urban,Data Analyst,126433,1 +57533,Male,57,Diploma,11,93,58,12,84,6.0,6,17,Urban,Software Engineer,130054,0 +57534,Female,41,Masters,12,40,67,75,76,1.0,7,14,Urban,HR Executive,103176,0 +57535,Male,46,PhD,13,0,84,12,11,2.0,3,29,Urban,Data Analyst,138275,0 +57536,Male,54,Diploma,17,89,45,10,81,1.0,2,42,Urban,Data Analyst,142393,0 +57537,Female,57,Bachelors,14,4,77,6,78,5.0,5,55,Rural,Software Engineer,42330,0 +57538,Male,58,Masters,3,46,98,17,78,6.0,7,42,Urban,Software Engineer,110352,0 +57539,Female,43,Diploma,0,11,62,32,64,8.0,4,92,Rural,Software Engineer,124022,0 +57540,Male,25,Diploma,6,45,27,50,52,3.0,7,5,Urban,Data Analyst,125670,0 +57541,Male,59,Bachelors,0,29,76,54,27,7.0,3,67,Semi-Urban,Software Engineer,34092,0 +57542,Male,33,Diploma,18,13,44,29,15,9.0,6,66,Semi-Urban,HR Executive,85990,0 +57543,Female,43,Bachelors,7,91,35,2,91,6.0,0,48,Semi-Urban,HR Executive,96877,0 +57544,Other,49,Bachelors,15,62,42,68,22,1.0,5,1,Semi-Urban,HR Executive,63864,0 +57545,Male,43,Diploma,18,98,31,29,81,2.0,2,99,Urban,ML Engineer,75702,1 +57546,Male,58,Bachelors,17,89,65,29,15,8.0,6,96,Urban,ML Engineer,32364,1 +57547,Male,38,Bachelors,18,45,15,26,95,4.0,3,14,Urban,Software Engineer,49604,0 +57548,Male,51,Bachelors,6,22,22,67,58,5.0,5,94,Semi-Urban,Software Engineer,145920,0 +57549,Male,28,High School,9,74,31,8,11,2.0,7,21,Rural,Software Engineer,122172,0 +57550,Male,36,Bachelors,14,98,25,99,42,5.0,1,72,Urban,Data Analyst,55431,1 +57551,Male,55,Bachelors,0,64,79,67,29,8.0,7,1,Urban,Software Engineer,26527,0 +57552,Male,46,Bachelors,6,7,32,52,50,0.0,5,98,Urban,Software Engineer,42230,0 +57553,Other,55,High School,7,40,56,91,52,2.0,1,97,Semi-Urban,ML Engineer,37454,1 +57554,Male,25,Bachelors,5,80,49,41,75,8.0,1,52,Urban,ML Engineer,138267,0 +57555,Male,44,Masters,2,33,94,69,26,9.0,5,20,Urban,Software Engineer,35364,0 +57556,Male,39,Bachelors,1,16,89,68,3,7.0,0,94,Urban,Data Analyst,114945,1 +57557,Female,38,Masters,15,5,26,81,28,8.0,5,63,Urban,HR Executive,137843,0 +57558,Female,53,High School,19,33,33,92,13,6.0,3,60,Semi-Urban,Software Engineer,136833,0 +57559,Female,26,Diploma,18,23,45,75,35,6.0,0,78,Urban,Data Analyst,96843,0 +57560,Male,53,High School,13,25,22,24,70,3.0,0,68,Semi-Urban,Software Engineer,148123,0 +57561,Female,45,Masters,2,33,39,36,99,3.0,0,36,Semi-Urban,Software Engineer,127707,0 +57562,Female,38,Bachelors,2,2,91,6,82,4.0,6,63,Semi-Urban,ML Engineer,74780,0 +57563,Male,29,Bachelors,5,15,46,58,67,2.0,4,71,Rural,Software Engineer,59506,0 +57564,Female,51,Masters,6,65,46,31,30,0.0,4,82,Rural,Manager,40995,0 +57565,Female,46,Diploma,8,75,39,54,54,9.0,3,3,Rural,Manager,95468,0 +57566,Male,26,Bachelors,17,35,84,98,15,6.0,6,86,Semi-Urban,Software Engineer,29454,1 +57567,Male,46,Bachelors,6,1,40,21,98,6.0,1,87,Urban,Manager,116095,0 +57568,Male,33,Masters,14,17,94,38,96,1.0,7,6,Rural,ML Engineer,124123,0 +57569,Male,44,Masters,14,81,62,59,38,8.0,6,17,Rural,Software Engineer,117138,0 +57570,Male,36,Bachelors,17,89,59,60,94,4.0,5,59,Urban,ML Engineer,77554,1 +57571,Other,54,Bachelors,13,20,66,27,77,0.0,6,61,Urban,HR Executive,26351,0 +57572,Male,52,Bachelors,13,4,63,11,48,7.0,1,38,Urban,HR Executive,61295,0 +57573,Male,27,Masters,12,50,50,42,51,7.0,2,87,Urban,HR Executive,138323,0 +57574,Male,21,Diploma,1,30,68,82,53,0.0,6,65,Semi-Urban,Data Analyst,51929,1 +57575,Male,34,Diploma,14,37,73,99,94,4.0,1,56,Urban,ML Engineer,61637,1 +57576,Female,23,Diploma,15,8,30,31,39,6.0,3,29,Semi-Urban,ML Engineer,132993,0 +57577,Male,28,Masters,16,41,80,91,77,8.0,3,23,Urban,Manager,108922,1 +57578,Male,23,Masters,6,78,97,72,61,5.0,0,73,Urban,Manager,33555,1 +57579,Male,28,Bachelors,6,14,80,34,37,4.0,3,99,Semi-Urban,Data Analyst,39040,0 +57580,Male,26,Bachelors,5,20,70,7,44,5.0,6,8,Urban,Software Engineer,120483,0 +57581,Female,51,High School,2,59,82,53,14,4.0,1,41,Urban,Software Engineer,133420,0 +57582,Male,54,Masters,13,64,64,39,55,4.0,2,90,Urban,ML Engineer,29879,1 +57583,Male,39,Bachelors,0,15,66,14,17,2.0,7,20,Urban,Data Analyst,99417,0 +57584,Male,56,Diploma,9,49,74,25,64,6.0,1,2,Rural,HR Executive,58348,0 +57585,Male,33,Diploma,8,31,79,93,46,9.0,6,81,Semi-Urban,ML Engineer,121170,1 +57586,Male,58,High School,15,42,3,14,94,7.0,7,65,Urban,Data Analyst,109560,0 +57587,Female,22,High School,13,26,10,93,40,8.0,6,96,Urban,Manager,87361,0 +57588,Male,52,Diploma,0,28,22,80,37,8.0,1,26,Urban,ML Engineer,126562,0 +57589,Male,37,Diploma,2,93,29,64,57,0.0,4,56,Urban,Manager,88326,1 +57590,Male,30,Bachelors,10,79,32,73,50,6.0,4,54,Urban,Manager,146294,1 +57591,Male,31,Bachelors,3,39,78,93,96,4.0,3,72,Semi-Urban,HR Executive,108929,1 +57592,Male,54,High School,0,52,24,73,86,8.0,7,82,Urban,Manager,83370,0 +57593,Male,47,Diploma,14,50,64,28,5,2.0,7,54,Semi-Urban,ML Engineer,37430,0 +57594,Male,25,Diploma,2,56,58,80,60,1.0,1,86,Urban,Data Analyst,115281,1 +57595,Male,40,High School,5,16,74,32,23,6.0,7,87,Urban,Data Analyst,87450,0 +57596,Female,32,Diploma,1,81,11,68,18,4.0,6,15,Rural,Manager,116956,0 +57597,Male,37,Diploma,6,10,10,7,96,7.0,6,79,Urban,Data Analyst,100202,0 +57598,Male,37,Bachelors,5,24,31,62,75,8.0,3,93,Urban,Manager,79108,0 +57599,Male,54,Bachelors,11,51,38,69,48,0.0,1,86,Semi-Urban,HR Executive,95106,1 +57600,Female,26,Diploma,12,71,50,55,29,5.0,7,10,Urban,Data Analyst,134289,0 +57601,Male,36,Bachelors,10,70,73,44,94,9.0,1,72,Urban,Manager,86598,1 +57602,Male,46,Bachelors,15,18,79,52,11,7.0,7,85,Rural,ML Engineer,63045,0 +57603,Male,28,Bachelors,6,0,70,97,86,8.0,4,45,Urban,Manager,38146,0 +57604,Female,58,Diploma,5,76,58,14,59,3.0,7,99,Semi-Urban,Software Engineer,96342,1 +57605,Female,58,High School,2,80,10,48,54,3.0,3,15,Semi-Urban,HR Executive,137036,0 +57606,Female,29,Bachelors,14,5,30,60,90,1.0,2,65,Urban,Data Analyst,69238,0 +57607,Male,53,Bachelors,12,35,95,59,54,9.0,3,77,Urban,ML Engineer,98577,1 +57608,Female,50,Bachelors,8,37,9,31,57,1.0,4,71,Rural,Manager,117948,0 +57609,Female,41,Bachelors,5,36,4,36,24,8.0,6,52,Rural,Data Analyst,48543,0 +57610,Male,40,High School,11,10,5,63,66,8.0,4,2,Urban,HR Executive,49967,0 +57611,Female,34,PhD,17,1,24,94,38,0.0,4,7,Urban,ML Engineer,66585,0 +57612,Other,21,Diploma,9,12,97,48,35,5.0,2,62,Urban,Software Engineer,106496,0 +57613,Male,56,High School,12,21,6,5,2,9.0,0,86,Semi-Urban,Manager,83271,0 +57614,Female,44,Masters,10,71,31,76,96,3.0,4,57,Semi-Urban,ML Engineer,36165,0 +57615,Male,47,Bachelors,7,68,64,79,89,2.0,3,65,Semi-Urban,HR Executive,123310,1 +57616,Male,38,Diploma,18,89,72,38,64,3.0,4,93,Urban,Manager,114196,1 +57617,Male,59,Masters,2,47,56,26,66,3.0,2,7,Urban,ML Engineer,149796,0 +57618,Male,59,Bachelors,0,31,53,54,11,4.0,7,39,Semi-Urban,HR Executive,122156,0 +57619,Female,47,Masters,2,73,97,62,27,4.0,6,48,Rural,Data Analyst,41906,1 +57620,Female,37,High School,18,29,99,18,30,1.0,5,25,Semi-Urban,ML Engineer,130053,0 +57621,Male,23,High School,2,50,73,67,13,5.0,4,75,Rural,Manager,121238,1 +57622,Female,41,Bachelors,5,70,14,29,31,8.0,4,88,Urban,Manager,89040,0 +57623,Female,24,PhD,0,93,14,87,91,7.0,0,93,Urban,ML Engineer,121683,1 +57624,Male,34,Bachelors,18,98,96,90,54,4.0,7,99,Urban,Data Analyst,145816,1 +57625,Male,36,Diploma,9,12,78,35,56,1.0,5,8,Semi-Urban,Software Engineer,90802,0 +57626,Female,39,High School,0,70,27,99,29,5.0,0,74,Rural,HR Executive,135137,1 +57627,Female,48,Diploma,6,97,25,17,8,2.0,7,19,Urban,Manager,42146,0 +57628,Other,39,Diploma,10,4,58,90,14,4.0,3,70,Urban,Data Analyst,70060,0 +57629,Male,58,Bachelors,18,88,0,81,26,8.0,0,97,Urban,Data Analyst,90385,1 +57630,Male,43,Bachelors,16,99,32,69,49,6.0,1,28,Urban,Data Analyst,144102,0 +57631,Female,53,Bachelors,2,84,38,66,21,5.0,5,89,Urban,Manager,97794,1 +57632,Male,33,Bachelors,8,22,65,8,37,3.0,7,26,Semi-Urban,Software Engineer,125164,0 +57633,Female,32,Bachelors,16,20,39,82,86,0.0,2,3,Urban,HR Executive,115987,0 +57634,Male,28,Diploma,15,29,95,35,30,8.0,1,78,Urban,Data Analyst,109540,1 +57635,Male,46,Bachelors,1,82,33,19,18,0.0,2,2,Urban,Software Engineer,22056,0 +57636,Male,29,Masters,1,32,74,50,40,6.0,3,62,Urban,Software Engineer,85756,0 +57637,Male,48,Bachelors,5,77,28,39,48,5.0,0,63,Urban,Software Engineer,48439,0 +57638,Male,55,Bachelors,0,57,14,51,98,5.0,1,12,Urban,Software Engineer,103461,0 +57639,Female,49,Bachelors,18,58,53,92,40,1.0,5,89,Semi-Urban,HR Executive,124638,1 +57640,Male,53,Masters,19,19,37,85,57,4.0,5,45,Semi-Urban,ML Engineer,55756,0 +57641,Male,34,Bachelors,8,51,50,9,49,9.0,2,48,Semi-Urban,Software Engineer,39407,0 +57642,Other,35,Diploma,4,26,28,60,70,9.0,7,81,Urban,Software Engineer,50957,0 +57643,Male,39,Bachelors,13,82,57,67,82,8.0,7,99,Rural,HR Executive,105715,1 +57644,Male,53,High School,17,3,67,70,34,5.0,6,70,Urban,Software Engineer,113556,0 +57645,Male,28,Bachelors,18,26,27,53,47,3.0,7,39,Urban,Manager,59425,0 +57646,Female,54,Diploma,8,48,8,99,83,0.0,2,10,Semi-Urban,ML Engineer,23798,0 +57647,Male,47,Bachelors,11,23,84,74,8,3.0,7,87,Urban,Software Engineer,127755,1 +57648,Other,50,Bachelors,9,87,68,90,1,3.0,6,72,Semi-Urban,Manager,79808,1 +57649,Male,44,Bachelors,8,50,8,64,92,6.0,7,39,Rural,Software Engineer,39148,0 +57650,Female,52,Diploma,19,84,24,71,21,6.0,1,26,Semi-Urban,Software Engineer,96453,0 +57651,Male,56,Masters,11,32,51,99,14,0.0,3,8,Semi-Urban,HR Executive,44964,0 +57652,Other,57,Masters,18,69,75,27,40,2.0,5,45,Urban,HR Executive,135849,0 +57653,Male,23,Bachelors,11,30,52,25,0,0.0,2,37,Urban,Manager,85168,0 +57654,Female,57,Bachelors,11,61,51,46,31,7.0,2,59,Semi-Urban,Manager,29634,0 +57655,Female,21,Masters,11,85,32,91,33,2.0,3,94,Semi-Urban,HR Executive,147662,1 +57656,Female,23,Diploma,19,40,88,72,11,2.0,0,97,Urban,Software Engineer,55866,1 +57657,Male,47,Masters,12,13,33,57,56,0.0,3,83,Semi-Urban,HR Executive,93132,0 +57658,Male,52,Bachelors,2,3,59,2,40,2.0,3,3,Urban,Manager,101198,0 +57659,Male,52,Diploma,1,43,72,60,60,9.0,5,17,Rural,HR Executive,84077,0 +57660,Male,37,High School,5,69,83,9,8,1.0,6,47,Semi-Urban,HR Executive,82358,0 +57661,Female,55,Bachelors,12,6,61,25,7,0.0,5,67,Urban,ML Engineer,66315,0 +57662,Male,52,Bachelors,7,99,26,36,78,9.0,3,51,Urban,HR Executive,36290,0 +57663,Male,38,Diploma,8,61,85,7,85,4.0,1,88,Semi-Urban,HR Executive,53940,1 +57664,Male,56,Bachelors,17,5,93,35,92,2.0,4,85,Rural,Data Analyst,122095,0 +57665,Other,48,High School,19,45,75,63,13,6.0,6,61,Urban,Data Analyst,99289,1 +57666,Female,59,Bachelors,0,21,28,30,50,5.0,4,78,Urban,Manager,114006,0 +57667,Male,56,Bachelors,11,23,3,45,61,1.0,7,44,Urban,HR Executive,134440,0 +57668,Female,27,Masters,3,61,16,43,61,1.0,3,42,Rural,HR Executive,113839,0 +57669,Female,52,Masters,2,96,61,2,49,6.0,2,23,Urban,ML Engineer,72899,0 +57670,Female,31,Bachelors,2,53,52,9,26,1.0,2,77,Semi-Urban,Software Engineer,131614,0 +57671,Male,48,Masters,17,41,98,99,53,9.0,5,55,Urban,Data Analyst,139625,1 +57672,Female,46,PhD,8,42,54,91,36,7.0,5,55,Urban,Software Engineer,38238,1 +57673,Male,34,High School,17,38,35,85,16,5.0,4,32,Semi-Urban,Data Analyst,43788,0 +57674,Female,45,Bachelors,10,92,25,0,94,5.0,2,41,Urban,Data Analyst,35943,0 +57675,Male,43,PhD,7,60,82,51,42,0.0,4,82,Semi-Urban,ML Engineer,67318,1 +57676,Other,35,Diploma,16,98,2,7,57,1.0,0,79,Urban,Manager,72937,0 +57677,Female,51,High School,19,53,1,45,83,8.0,3,47,Rural,Manager,66132,0 +57678,Male,50,Diploma,19,26,98,1,86,1.0,3,57,Urban,Data Analyst,79716,0 +57679,Female,49,Diploma,15,54,34,90,30,0.0,2,19,Urban,ML Engineer,119680,0 +57680,Male,49,Diploma,6,56,93,26,10,8.0,0,36,Rural,Data Analyst,147667,0 +57681,Male,31,Bachelors,7,77,90,38,31,1.0,7,14,Semi-Urban,HR Executive,24980,0 +57682,Male,39,Bachelors,11,70,39,0,10,8.0,0,80,Semi-Urban,ML Engineer,39321,0 +57683,Male,55,Diploma,15,43,18,10,69,7.0,1,16,Urban,Manager,115619,0 +57684,Male,39,Masters,17,81,95,8,65,7.0,3,31,Urban,ML Engineer,58536,0 +57685,Female,33,High School,17,38,49,43,54,5.0,2,53,Semi-Urban,Data Analyst,139284,0 +57686,Female,45,Bachelors,11,86,13,77,56,4.0,5,47,Urban,HR Executive,119097,0 +57687,Male,59,Bachelors,6,50,32,73,70,9.0,7,55,Semi-Urban,Data Analyst,106367,0 +57688,Male,30,High School,19,21,12,12,54,2.0,1,26,Urban,HR Executive,48442,0 +57689,Male,28,Masters,18,47,49,67,5,1.0,5,77,Semi-Urban,ML Engineer,98500,1 +57690,Female,27,Bachelors,3,77,14,19,9,8.0,1,79,Semi-Urban,ML Engineer,29522,0 +57691,Female,44,Bachelors,16,54,29,57,98,3.0,6,36,Urban,HR Executive,81097,0 +57692,Male,57,High School,8,41,50,12,75,0.0,3,22,Semi-Urban,Manager,72502,0 +57693,Female,50,Masters,10,51,95,4,81,4.0,5,43,Semi-Urban,ML Engineer,61263,0 +57694,Male,38,Bachelors,3,53,68,91,56,7.0,1,14,Semi-Urban,HR Executive,130863,0 +57695,Male,30,PhD,15,38,44,6,64,2.0,6,33,Urban,Data Analyst,147542,0 +57696,Male,25,PhD,5,35,40,53,44,4.0,3,87,Urban,Data Analyst,82073,0 +57697,Male,56,Diploma,10,59,72,88,73,4.0,2,23,Urban,Software Engineer,146165,1 +57698,Male,59,High School,17,26,21,22,46,0.0,2,49,Urban,HR Executive,131965,0 +57699,Female,49,High School,17,68,0,81,8,9.0,2,62,Urban,Manager,99242,0 +57700,Male,29,High School,15,8,47,98,44,8.0,7,18,Semi-Urban,Software Engineer,145762,0 +57701,Male,56,High School,14,4,5,4,38,5.0,7,4,Urban,Manager,128547,0 +57702,Male,53,Bachelors,5,59,73,80,1,2.0,4,38,Semi-Urban,Software Engineer,93588,1 +57703,Female,52,Diploma,14,63,7,73,94,3.0,3,10,Semi-Urban,ML Engineer,67641,0 +57704,Male,30,Diploma,11,14,72,10,76,9.0,0,16,Semi-Urban,Software Engineer,58138,0 +57705,Female,38,Diploma,11,87,24,18,37,0.0,3,15,Semi-Urban,Data Analyst,114488,0 +57706,Male,37,High School,19,7,8,73,54,5.0,7,31,Urban,Data Analyst,38220,0 +57707,Male,30,Bachelors,16,20,97,21,74,8.0,6,79,Urban,Software Engineer,57536,0 +57708,Male,22,Masters,7,29,7,88,88,8.0,5,42,Urban,Data Analyst,145730,0 +57709,Female,34,Bachelors,13,55,0,56,68,1.0,5,6,Urban,Data Analyst,28441,0 +57710,Male,41,High School,1,79,89,79,41,0.0,3,87,Urban,ML Engineer,96448,1 +57711,Male,53,PhD,18,23,13,38,24,2.0,3,17,Urban,Manager,83647,0 +57712,Male,25,Bachelors,18,98,9,68,23,3.0,7,50,Semi-Urban,Software Engineer,87051,0 +57713,Male,54,Diploma,13,92,11,21,29,9.0,6,28,Urban,ML Engineer,102765,0 +57714,Female,31,Bachelors,12,33,89,29,61,3.0,6,98,Rural,ML Engineer,109658,1 +57715,Male,33,Bachelors,10,68,49,53,31,1.0,4,62,Urban,Software Engineer,44794,0 +57716,Male,49,Masters,11,19,56,39,26,8.0,7,2,Rural,ML Engineer,39407,0 +57717,Female,31,Bachelors,4,36,19,14,4,7.0,0,82,Urban,Software Engineer,31381,0 +57718,Male,58,High School,15,9,37,56,49,2.0,7,51,Rural,Manager,75240,0 +57719,Female,28,Bachelors,7,80,24,64,97,5.0,6,15,Urban,Manager,62989,0 +57720,Female,53,Diploma,12,84,72,41,25,8.0,6,66,Urban,HR Executive,55298,1 +57721,Male,52,Bachelors,1,29,94,99,31,4.0,4,42,Semi-Urban,HR Executive,39901,1 +57722,Female,26,PhD,2,68,82,45,22,8.0,0,88,Semi-Urban,Software Engineer,62495,1 +57723,Male,22,PhD,7,27,3,81,86,5.0,3,46,Urban,ML Engineer,62059,0 +57724,Male,49,Bachelors,8,13,34,5,50,7.0,2,82,Urban,HR Executive,67434,0 +57725,Male,55,Masters,12,92,14,56,26,7.0,4,24,Rural,Data Analyst,110610,0 +57726,Female,52,Diploma,14,74,36,59,76,7.0,3,23,Semi-Urban,HR Executive,84168,0 +57727,Male,42,High School,12,70,16,49,52,8.0,1,57,Urban,HR Executive,74454,0 +57728,Male,24,Bachelors,2,70,55,65,33,7.0,2,79,Rural,ML Engineer,146742,1 +57729,Male,54,Bachelors,10,57,27,92,82,6.0,2,42,Semi-Urban,ML Engineer,52678,0 +57730,Female,46,Bachelors,7,3,64,94,89,8.0,3,82,Urban,HR Executive,149078,1 +57731,Male,54,Bachelors,5,87,66,73,68,5.0,4,34,Semi-Urban,Data Analyst,108018,1 +57732,Male,25,Bachelors,8,92,32,75,5,0.0,5,52,Semi-Urban,Data Analyst,111302,1 +57733,Male,55,Diploma,0,81,77,41,8,5.0,5,67,Urban,ML Engineer,26666,1 +57734,Male,59,Masters,15,45,58,7,73,7.0,1,39,Rural,Software Engineer,29240,0 +57735,Male,56,High School,4,87,16,33,51,9.0,3,16,Urban,ML Engineer,113052,0 +57736,Male,35,Masters,12,61,62,1,24,7.0,1,73,Urban,HR Executive,28985,0 +57737,Male,57,High School,19,13,90,37,66,7.0,3,1,Semi-Urban,HR Executive,60762,0 +57738,Male,31,High School,16,0,81,60,2,1.0,7,35,Urban,Manager,77960,0 +57739,Female,39,High School,5,28,80,79,36,4.0,7,72,Urban,Software Engineer,34202,1 +57740,Female,31,Masters,11,9,54,28,14,3.0,1,82,Semi-Urban,Data Analyst,76437,0 +57741,Male,51,Diploma,5,17,65,34,1,8.0,0,60,Urban,HR Executive,63032,0 +57742,Male,22,Masters,9,16,81,99,97,7.0,2,58,Semi-Urban,Data Analyst,75704,1 +57743,Male,45,Masters,10,79,49,27,20,6.0,7,69,Rural,Manager,123906,0 +57744,Male,51,Masters,18,10,14,9,40,4.0,0,9,Semi-Urban,Software Engineer,148080,0 +57745,Male,57,PhD,0,1,13,97,37,3.0,0,31,Urban,Data Analyst,104963,0 +57746,Female,29,PhD,12,86,56,5,60,8.0,5,26,Rural,Manager,86643,0 +57747,Male,30,High School,15,12,76,36,27,5.0,7,9,Urban,Software Engineer,26168,0 +57748,Female,21,Bachelors,12,50,73,7,48,6.0,5,96,Semi-Urban,HR Executive,78610,0 +57749,Male,41,Masters,9,23,58,19,14,8.0,2,33,Urban,HR Executive,109503,0 +57750,Male,51,Bachelors,1,87,97,67,98,3.0,4,39,Urban,Data Analyst,74977,1 +57751,Female,42,Bachelors,10,66,77,74,16,0.0,4,61,Semi-Urban,HR Executive,22866,1 +57752,Male,21,Diploma,12,28,71,63,10,4.0,4,5,Semi-Urban,Data Analyst,97120,0 +57753,Male,48,Bachelors,0,47,20,59,84,8.0,3,64,Rural,Software Engineer,122954,0 +57754,Male,23,Bachelors,16,8,78,40,6,1.0,2,28,Urban,HR Executive,143248,0 +57755,Male,36,Masters,12,48,9,1,12,9.0,4,81,Rural,Software Engineer,21398,0 +57756,Female,28,Diploma,17,64,90,94,89,5.0,3,56,Urban,Data Analyst,94317,1 +57757,Male,44,Bachelors,15,21,50,36,1,2.0,1,46,Urban,ML Engineer,81404,0 +57758,Female,24,PhD,4,12,15,78,25,3.0,1,3,Semi-Urban,Data Analyst,109364,0 +57759,Female,58,High School,12,61,22,87,27,3.0,2,91,Semi-Urban,Data Analyst,83634,1 +57760,Male,27,Diploma,17,90,89,17,96,6.0,7,22,Semi-Urban,Software Engineer,51219,0 +57761,Male,21,Diploma,17,15,71,11,97,1.0,5,18,Urban,HR Executive,53279,0 +57762,Other,32,Bachelors,11,32,28,81,72,0.0,2,87,Urban,HR Executive,91385,0 +57763,Male,25,Bachelors,3,27,78,78,17,5.0,3,17,Urban,Data Analyst,54271,0 +57764,Male,53,Bachelors,3,87,74,22,75,4.0,0,3,Rural,HR Executive,50993,0 +57765,Female,45,High School,7,27,49,31,49,7.0,2,60,Urban,Software Engineer,123767,0 +57766,Male,45,Bachelors,7,33,72,95,22,6.0,5,47,Semi-Urban,Manager,71718,1 +57767,Female,46,Bachelors,8,26,47,77,98,6.0,6,17,Rural,Software Engineer,47428,0 +57768,Male,41,Diploma,17,25,7,52,68,8.0,2,95,Urban,Manager,102232,0 +57769,Female,50,Bachelors,1,4,94,59,90,8.0,2,58,Urban,ML Engineer,41730,0 +57770,Female,50,Bachelors,16,22,95,45,21,1.0,0,24,Semi-Urban,HR Executive,56025,0 +57771,Male,44,PhD,9,75,74,6,63,5.0,1,27,Rural,Data Analyst,126986,0 +57772,Male,55,Diploma,0,94,95,64,47,0.0,2,57,Semi-Urban,Manager,137432,1 +57773,Male,38,Bachelors,5,12,40,4,69,9.0,7,93,Semi-Urban,HR Executive,132312,0 +57774,Male,39,Bachelors,5,28,31,4,68,9.0,4,1,Urban,HR Executive,128675,0 +57775,Female,39,Bachelors,14,50,57,4,2,7.0,1,80,Urban,ML Engineer,121887,0 +57776,Female,29,High School,17,29,58,53,40,6.0,4,19,Semi-Urban,Software Engineer,72300,0 +57777,Female,23,Bachelors,7,65,29,29,42,7.0,2,60,Urban,Data Analyst,34021,0 +57778,Female,38,Bachelors,7,3,67,58,68,8.0,6,85,Semi-Urban,Manager,66009,0 +57779,Female,56,Masters,17,75,71,76,21,7.0,7,62,Urban,HR Executive,49167,1 +57780,Female,44,Bachelors,6,10,71,18,97,0.0,5,46,Urban,Data Analyst,39410,0 +57781,Female,28,Bachelors,11,87,38,26,86,8.0,6,65,Urban,Software Engineer,114629,0 +57782,Male,42,Diploma,19,60,71,4,20,8.0,5,20,Urban,Data Analyst,32328,0 +57783,Female,43,Bachelors,14,45,99,60,9,8.0,7,48,Urban,ML Engineer,116540,1 +57784,Female,28,Bachelors,9,90,53,58,90,7.0,1,45,Urban,Software Engineer,71278,1 +57785,Male,57,Masters,8,38,78,27,36,9.0,4,86,Urban,Manager,96946,0 +57786,Female,39,Bachelors,14,62,99,81,50,1.0,3,96,Semi-Urban,Manager,50856,1 +57787,Male,30,PhD,19,81,97,77,62,8.0,7,13,Semi-Urban,Data Analyst,121483,1 +57788,Male,40,Bachelors,11,58,44,70,88,2.0,2,92,Urban,Manager,23139,1 +57789,Male,47,Bachelors,19,89,29,68,60,4.0,6,24,Urban,Data Analyst,110591,0 +57790,Male,25,Diploma,5,84,21,72,94,1.0,5,71,Semi-Urban,Manager,121678,1 +57791,Male,40,Diploma,3,82,19,52,26,3.0,7,19,Urban,HR Executive,92547,0 +57792,Female,22,PhD,15,6,19,19,26,2.0,1,49,Semi-Urban,Data Analyst,23048,0 +57793,Female,36,PhD,9,4,82,26,83,5.0,1,20,Urban,Manager,132732,0 +57794,Female,51,Bachelors,13,7,17,96,23,9.0,7,41,Semi-Urban,ML Engineer,117402,0 +57795,Female,37,Masters,7,88,9,88,65,8.0,4,26,Rural,Manager,47276,0 +57796,Male,42,Bachelors,11,84,49,56,3,9.0,0,28,Semi-Urban,ML Engineer,62410,0 +57797,Male,36,Masters,9,70,50,93,96,2.0,1,17,Rural,Software Engineer,78894,0 +57798,Female,31,Bachelors,5,99,43,64,78,4.0,1,90,Rural,Manager,23375,1 +57799,Female,31,Bachelors,0,10,70,11,76,6.0,7,38,Rural,Software Engineer,44300,0 +57800,Female,21,Masters,7,33,15,56,98,6.0,2,51,Urban,Software Engineer,148586,0 +57801,Male,48,Bachelors,15,6,80,56,66,8.0,1,21,Semi-Urban,Software Engineer,47598,0 +57802,Male,47,Diploma,12,12,77,63,51,3.0,6,12,Urban,Data Analyst,29225,0 +57803,Other,24,Bachelors,18,26,59,86,74,6.0,4,28,Semi-Urban,Manager,129276,0 +57804,Female,40,Bachelors,17,32,50,59,37,7.0,4,83,Urban,HR Executive,118842,0 +57805,Male,26,Bachelors,0,22,76,64,26,5.0,4,95,Urban,ML Engineer,142606,1 +57806,Male,33,Masters,19,8,5,31,40,9.0,3,9,Urban,HR Executive,137585,0 +57807,Male,41,Diploma,7,53,53,19,59,1.0,5,68,Semi-Urban,Software Engineer,113933,0 +57808,Male,51,Bachelors,8,54,67,89,83,3.0,4,58,Urban,Software Engineer,129800,1 +57809,Male,52,Masters,13,65,73,0,20,0.0,5,95,Rural,ML Engineer,143269,0 +57810,Female,32,PhD,4,50,38,92,23,7.0,1,89,Urban,Data Analyst,30863,1 +57811,Other,43,Bachelors,10,81,9,57,5,2.0,3,50,Urban,Software Engineer,44654,0 +57812,Female,56,Diploma,16,37,72,4,25,7.0,2,13,Urban,Manager,121034,0 +57813,Female,52,Bachelors,6,33,83,62,96,4.0,2,37,Urban,Manager,67729,0 +57814,Female,59,Masters,6,19,42,26,31,3.0,6,14,Semi-Urban,Manager,133341,0 +57815,Male,58,Diploma,3,76,45,72,7,9.0,0,74,Urban,ML Engineer,53869,1 +57816,Male,59,Masters,6,63,61,43,57,4.0,1,61,Urban,Manager,21363,0 +57817,Male,44,Masters,14,78,10,39,98,4.0,5,55,Semi-Urban,ML Engineer,136524,0 +57818,Female,28,PhD,9,6,69,75,74,3.0,0,9,Urban,ML Engineer,21117,0 +57819,Female,52,Diploma,12,91,58,59,63,8.0,6,93,Semi-Urban,Manager,119953,1 +57820,Male,44,Diploma,12,99,98,90,31,4.0,6,80,Urban,Software Engineer,63194,1 +57821,Male,25,Masters,19,94,39,54,0,3.0,0,33,Urban,Software Engineer,55807,0 +57822,Male,32,Bachelors,9,89,53,79,5,2.0,2,81,Urban,Manager,126930,1 +57823,Male,52,Masters,6,47,61,34,14,7.0,3,39,Rural,ML Engineer,24711,0 +57824,Male,21,Bachelors,1,79,12,47,33,4.0,1,93,Urban,Data Analyst,76220,0 +57825,Female,55,PhD,13,52,63,70,23,1.0,1,51,Urban,Software Engineer,76416,0 +57826,Male,52,Diploma,17,47,0,29,0,0.0,5,36,Semi-Urban,Manager,128037,0 +57827,Other,35,Bachelors,19,49,22,63,11,7.0,7,47,Urban,HR Executive,96528,0 +57828,Male,54,Diploma,15,40,72,99,78,7.0,0,64,Semi-Urban,Manager,114168,1 +57829,Male,54,Bachelors,13,0,15,10,52,2.0,4,7,Semi-Urban,Manager,77520,0 +57830,Male,28,Diploma,4,57,97,30,44,7.0,2,52,Urban,Data Analyst,123235,1 +57831,Female,35,Diploma,9,48,79,27,30,0.0,2,66,Urban,Software Engineer,134813,0 +57832,Male,22,Bachelors,14,27,0,55,36,6.0,1,30,Urban,HR Executive,114242,0 +57833,Female,45,Bachelors,1,20,54,23,20,4.0,3,68,Semi-Urban,Manager,137616,0 +57834,Male,34,Bachelors,17,82,14,50,7,1.0,6,78,Rural,Manager,68986,0 +57835,Female,45,Bachelors,10,0,90,49,36,2.0,6,4,Urban,ML Engineer,21174,0 +57836,Male,22,Bachelors,15,31,45,96,14,4.0,0,7,Urban,Manager,57602,0 +57837,Male,47,High School,10,4,89,58,82,6.0,0,77,Semi-Urban,HR Executive,134745,0 +57838,Male,37,Bachelors,12,89,30,82,56,8.0,3,56,Urban,ML Engineer,117806,1 +57839,Male,28,Masters,8,87,17,42,20,0.0,4,43,Urban,HR Executive,115604,0 +57840,Male,28,High School,6,93,98,48,75,7.0,3,5,Semi-Urban,ML Engineer,47416,1 +57841,Male,44,Masters,2,43,77,81,56,8.0,0,44,Semi-Urban,Manager,116772,1 +57842,Female,53,Bachelors,13,27,18,39,11,1.0,2,87,Rural,Manager,58841,0 +57843,Female,48,Masters,15,73,9,11,18,4.0,1,58,Urban,ML Engineer,36694,0 +57844,Male,34,Diploma,18,88,53,12,54,4.0,6,6,Urban,Data Analyst,97763,0 +57845,Other,29,High School,13,58,66,39,46,9.0,0,66,Semi-Urban,Manager,82706,0 +57846,Other,37,High School,4,3,83,77,50,5.0,6,21,Urban,Data Analyst,57412,0 +57847,Female,58,Bachelors,4,51,87,13,35,8.0,5,88,Urban,HR Executive,77972,0 +57848,Male,58,Bachelors,12,88,36,93,33,7.0,4,46,Urban,ML Engineer,80434,1 +57849,Male,23,Bachelors,14,25,40,23,59,1.0,7,70,Semi-Urban,Data Analyst,52984,0 +57850,Male,31,Diploma,15,63,39,95,60,5.0,7,5,Rural,Software Engineer,133771,0 +57851,Male,43,Bachelors,1,53,50,91,75,7.0,6,79,Urban,Data Analyst,43088,1 +57852,Female,58,Diploma,6,86,87,70,47,5.0,6,73,Urban,Software Engineer,109466,1 +57853,Male,39,PhD,5,91,83,59,62,2.0,7,77,Urban,Data Analyst,75287,1 +57854,Female,28,Diploma,14,66,4,70,85,9.0,6,26,Urban,Manager,99748,0 +57855,Male,28,High School,7,52,91,85,95,0.0,3,15,Semi-Urban,ML Engineer,112128,1 +57856,Male,38,Bachelors,10,1,86,19,68,7.0,1,77,Urban,HR Executive,55309,0 +57857,Female,42,PhD,10,70,60,81,56,2.0,0,33,Semi-Urban,Manager,98175,1 +57858,Male,27,PhD,9,73,35,5,13,9.0,0,81,Semi-Urban,Data Analyst,25468,0 +57859,Male,40,PhD,6,97,73,87,37,9.0,6,99,Urban,Software Engineer,128193,1 +57860,Male,29,Bachelors,7,3,29,18,50,0.0,2,76,Semi-Urban,Data Analyst,110407,0 +57861,Male,58,Masters,4,96,42,64,44,8.0,6,98,Semi-Urban,Software Engineer,111551,1 +57862,Female,23,Bachelors,7,42,89,70,71,8.0,4,7,Urban,Data Analyst,115229,0 +57863,Male,47,Bachelors,7,96,31,76,66,8.0,0,56,Urban,ML Engineer,116101,1 +57864,Male,51,Bachelors,1,57,49,15,38,5.0,3,21,Urban,Software Engineer,124495,0 +57865,Female,21,Masters,13,26,73,52,12,2.0,4,7,Semi-Urban,Manager,129065,0 +57866,Male,32,Diploma,4,76,60,30,59,6.0,2,49,Semi-Urban,HR Executive,146111,0 +57867,Male,31,High School,7,49,82,46,63,1.0,1,14,Urban,HR Executive,134245,0 +57868,Male,27,Bachelors,7,5,52,85,88,6.0,1,2,Urban,HR Executive,116486,0 +57869,Male,33,Bachelors,17,14,98,73,9,8.0,4,18,Urban,ML Engineer,92054,0 +57870,Male,58,Bachelors,12,96,81,71,35,1.0,6,72,Urban,HR Executive,140456,1 +57871,Male,54,Bachelors,18,65,64,16,4,0.0,5,75,Semi-Urban,Manager,108261,0 +57872,Male,49,Bachelors,6,65,43,19,71,3.0,0,85,Urban,Manager,30707,0 +57873,Male,27,Diploma,5,53,36,76,15,6.0,0,32,Semi-Urban,HR Executive,146983,0 +57874,Male,53,Bachelors,18,32,73,48,90,2.0,2,92,Urban,HR Executive,35065,1 +57875,Female,56,High School,19,30,92,80,87,7.0,4,36,Rural,Manager,58266,0 +57876,Female,57,Bachelors,1,29,25,33,78,1.0,3,15,Urban,Manager,131664,0 +57877,Male,32,Diploma,5,31,72,50,79,3.0,3,25,Semi-Urban,Software Engineer,142281,0 +57878,Female,22,Bachelors,1,62,9,43,24,9.0,7,87,Rural,Software Engineer,132664,0 +57879,Male,23,Bachelors,12,36,10,16,25,4.0,1,3,Urban,Manager,80676,0 +57880,Male,43,Masters,12,22,9,32,38,2.0,6,38,Semi-Urban,Manager,100758,0 +57881,Male,48,Bachelors,8,54,36,89,67,8.0,7,20,Urban,Manager,147096,0 +57882,Male,42,Diploma,13,97,42,66,47,6.0,4,78,Semi-Urban,ML Engineer,100311,1 +57883,Male,32,High School,4,51,19,98,96,5.0,2,24,Urban,Manager,45591,0 +57884,Male,54,High School,18,23,8,51,71,1.0,1,51,Urban,ML Engineer,33778,0 +57885,Female,38,High School,8,84,16,29,8,8.0,7,39,Urban,Manager,77548,0 +57886,Other,53,High School,9,56,39,68,36,0.0,1,39,Rural,Manager,132134,0 +57887,Male,57,Diploma,5,31,59,28,76,9.0,2,76,Semi-Urban,Software Engineer,59550,0 +57888,Male,39,Masters,18,16,96,56,22,3.0,6,91,Semi-Urban,Manager,100211,1 +57889,Female,56,Bachelors,15,50,69,21,60,9.0,7,73,Urban,Software Engineer,138520,0 +57890,Male,44,Bachelors,4,70,41,3,82,1.0,0,80,Rural,Data Analyst,45084,0 +57891,Male,53,Masters,6,92,81,77,73,7.0,7,46,Urban,Manager,26049,1 +57892,Female,45,High School,1,15,25,14,16,9.0,5,11,Urban,Manager,32665,0 +57893,Female,22,Bachelors,19,65,97,98,98,5.0,3,75,Semi-Urban,Manager,133429,1 +57894,Male,26,Bachelors,0,89,49,21,5,9.0,4,99,Rural,HR Executive,44770,1 +57895,Female,21,Bachelors,10,76,37,17,51,4.0,0,33,Urban,Data Analyst,127360,0 +57896,Female,41,Masters,9,90,18,44,96,8.0,5,94,Semi-Urban,ML Engineer,93319,1 +57897,Male,38,Bachelors,0,34,21,44,58,6.0,4,18,Urban,HR Executive,86013,0 +57898,Male,33,Bachelors,6,41,1,48,56,0.0,1,90,Urban,ML Engineer,57719,0 +57899,Male,33,Diploma,0,81,19,10,22,2.0,6,56,Urban,Manager,130935,0 +57900,Female,39,High School,13,38,55,13,26,9.0,1,75,Semi-Urban,Software Engineer,61438,0 +57901,Female,54,PhD,17,97,19,43,4,4.0,1,66,Urban,Software Engineer,145711,0 +57902,Male,35,Diploma,0,33,90,37,22,8.0,7,6,Semi-Urban,ML Engineer,90445,0 +57903,Female,26,Bachelors,12,36,54,47,9,2.0,2,94,Semi-Urban,ML Engineer,45858,0 +57904,Female,42,Diploma,2,21,92,42,77,8.0,2,76,Urban,Data Analyst,104666,0 +57905,Male,23,Bachelors,13,3,79,29,92,9.0,2,3,Urban,Data Analyst,148374,0 +57906,Male,54,Diploma,13,26,69,92,91,7.0,3,25,Urban,Data Analyst,121899,0 +57907,Female,58,Diploma,9,28,49,80,6,4.0,5,63,Urban,Data Analyst,129008,0 +57908,Male,51,Masters,10,64,8,28,8,3.0,0,39,Rural,ML Engineer,86473,0 +57909,Female,43,Masters,16,43,53,92,15,3.0,7,72,Urban,Data Analyst,81233,1 +57910,Male,21,Bachelors,8,84,30,65,90,1.0,6,92,Semi-Urban,Software Engineer,120782,1 +57911,Male,23,Bachelors,0,28,49,87,83,1.0,0,56,Urban,Data Analyst,89321,0 +57912,Female,26,Bachelors,14,59,26,69,15,9.0,5,85,Rural,HR Executive,109943,0 +57913,Female,48,PhD,9,52,10,72,66,5.0,2,50,Urban,Software Engineer,130420,0 +57914,Other,26,Masters,11,95,52,66,26,9.0,3,91,Semi-Urban,HR Executive,135133,1 +57915,Male,46,Masters,5,59,85,94,80,5.0,0,24,Urban,ML Engineer,129436,1 +57916,Male,45,High School,0,62,95,1,66,4.0,4,85,Urban,Manager,42340,1 +57917,Male,29,PhD,14,23,40,24,25,9.0,4,67,Urban,HR Executive,79668,0 +57918,Female,35,High School,19,30,13,77,81,0.0,3,27,Urban,Manager,26585,0 +57919,Male,53,High School,7,21,63,16,68,6.0,6,0,Urban,ML Engineer,69019,0 +57920,Female,54,High School,18,18,30,45,24,0.0,1,67,Semi-Urban,Data Analyst,115734,0 +57921,Male,42,Masters,17,66,15,65,48,4.0,1,45,Urban,ML Engineer,21676,0 +57922,Male,37,Bachelors,19,56,70,99,49,8.0,4,15,Urban,Manager,125062,1 +57923,Male,27,High School,14,24,18,42,62,8.0,4,77,Urban,Software Engineer,23580,0 +57924,Female,37,Bachelors,18,91,65,72,22,0.0,2,57,Urban,HR Executive,67277,1 +57925,Male,26,Bachelors,11,77,67,27,21,0.0,7,14,Urban,ML Engineer,36272,0 +57926,Male,35,PhD,19,79,94,46,5,6.0,5,50,Urban,HR Executive,93328,1 +57927,Male,25,Bachelors,11,98,20,66,49,9.0,1,88,Semi-Urban,Software Engineer,117297,1 +57928,Female,25,Masters,5,35,12,25,22,3.0,3,23,Rural,Manager,95519,0 +57929,Female,59,Bachelors,8,58,95,45,0,2.0,1,55,Rural,Software Engineer,62652,1 +57930,Other,45,Bachelors,19,23,81,88,55,0.0,1,81,Urban,Software Engineer,125992,1 +57931,Male,39,Bachelors,2,1,75,29,61,5.0,2,33,Urban,ML Engineer,64260,0 +57932,Male,51,Bachelors,17,6,99,4,62,3.0,7,44,Rural,Manager,46407,0 +57933,Male,22,Bachelors,19,50,45,32,50,0.0,4,63,Urban,Data Analyst,72309,0 +57934,Female,42,Masters,6,90,27,63,58,9.0,4,91,Urban,ML Engineer,23036,1 +57935,Male,28,Diploma,8,89,41,67,62,7.0,2,10,Urban,HR Executive,51514,0 +57936,Female,49,Diploma,10,16,47,98,40,3.0,2,57,Urban,HR Executive,32987,0 +57937,Male,33,Bachelors,12,47,37,73,90,4.0,7,80,Urban,Data Analyst,35844,1 +57938,Female,28,Diploma,1,73,81,27,1,0.0,3,4,Rural,Data Analyst,97048,0 +57939,Male,31,Diploma,13,74,61,99,1,4.0,3,22,Urban,Software Engineer,99006,1 +57940,Male,45,Diploma,19,87,16,25,89,2.0,3,25,Semi-Urban,Manager,41846,0 +57941,Male,38,Masters,0,42,59,0,53,9.0,0,64,Semi-Urban,Manager,100595,0 +57942,Male,37,High School,3,54,23,69,64,5.0,7,71,Urban,Data Analyst,81064,0 +57943,Female,54,Bachelors,9,97,22,77,16,7.0,6,44,Urban,Software Engineer,55205,0 +57944,Female,35,Bachelors,1,49,80,6,21,9.0,5,24,Urban,ML Engineer,124742,0 +57945,Male,42,High School,9,78,35,94,36,1.0,0,3,Urban,HR Executive,79759,0 +57946,Male,54,Bachelors,5,93,53,20,64,8.0,2,29,Urban,HR Executive,141782,0 +57947,Male,37,High School,7,54,19,38,17,0.0,2,96,Rural,Manager,115670,0 +57948,Male,29,High School,8,60,66,80,24,3.0,7,96,Urban,ML Engineer,58675,1 +57949,Male,23,Bachelors,8,78,42,39,50,5.0,6,4,Semi-Urban,HR Executive,38073,0 +57950,Male,31,Bachelors,13,47,5,36,89,4.0,2,93,Urban,Manager,140806,0 +57951,Female,38,Bachelors,6,45,83,12,91,0.0,3,96,Semi-Urban,HR Executive,137659,0 +57952,Male,48,Bachelors,14,89,54,97,4,1.0,3,76,Urban,Manager,91494,1 +57953,Male,35,Bachelors,6,67,94,77,25,5.0,3,43,Rural,ML Engineer,91144,1 +57954,Male,34,Bachelors,12,91,56,75,31,2.0,0,9,Semi-Urban,ML Engineer,49490,0 +57955,Female,49,PhD,4,69,2,4,81,0.0,7,53,Semi-Urban,HR Executive,121658,0 +57956,Male,54,Bachelors,7,60,54,9,60,2.0,5,90,Semi-Urban,Software Engineer,70811,0 +57957,Male,48,High School,9,16,16,42,15,4.0,4,51,Semi-Urban,HR Executive,95811,0 +57958,Male,32,Masters,3,76,54,14,18,4.0,4,47,Urban,HR Executive,77662,0 +57959,Female,22,Masters,3,35,71,67,43,0.0,2,57,Semi-Urban,HR Executive,146814,0 +57960,Male,33,Bachelors,5,68,20,41,66,6.0,0,29,Urban,Manager,48216,0 +57961,Female,58,Diploma,8,73,33,71,54,0.0,5,81,Semi-Urban,ML Engineer,63929,1 +57962,Male,58,Masters,0,62,24,50,67,9.0,0,41,Rural,Data Analyst,26148,0 +57963,Female,22,PhD,14,1,74,0,4,3.0,2,17,Urban,ML Engineer,149698,0 +57964,Female,31,Diploma,4,44,79,10,60,1.0,7,47,Urban,HR Executive,143712,0 +57965,Female,24,High School,5,15,49,9,62,3.0,7,11,Semi-Urban,Data Analyst,118535,0 +57966,Female,22,Masters,14,24,11,43,25,8.0,4,41,Urban,Data Analyst,127586,0 +57967,Male,46,Masters,14,40,46,83,58,5.0,4,81,Semi-Urban,HR Executive,126441,1 +57968,Male,47,Diploma,15,37,15,30,22,9.0,3,46,Urban,HR Executive,124030,0 +57969,Female,46,Masters,8,60,93,93,87,9.0,3,7,Urban,Data Analyst,55398,1 +57970,Male,41,Diploma,12,16,83,66,37,7.0,3,97,Rural,HR Executive,117829,1 +57971,Male,50,Bachelors,12,45,6,5,87,2.0,3,70,Rural,Data Analyst,34818,0 +57972,Female,38,High School,14,93,82,57,81,0.0,2,92,Urban,ML Engineer,143499,1 +57973,Male,51,Masters,15,91,38,28,23,8.0,5,81,Urban,Data Analyst,100868,1 +57974,Male,32,Masters,1,58,86,2,78,9.0,2,13,Urban,Manager,55440,0 +57975,Female,49,Bachelors,14,73,45,86,58,1.0,4,68,Urban,HR Executive,128573,1 +57976,Female,28,Bachelors,5,49,14,25,21,5.0,7,46,Semi-Urban,Data Analyst,95763,0 +57977,Female,23,Bachelors,17,26,13,16,80,6.0,6,21,Semi-Urban,Manager,38364,0 +57978,Male,39,High School,3,93,1,81,8,1.0,0,93,Rural,Data Analyst,20858,1 +57979,Male,56,Diploma,4,93,27,55,43,2.0,3,61,Semi-Urban,ML Engineer,87127,1 +57980,Female,27,High School,5,74,78,14,66,0.0,2,64,Semi-Urban,Software Engineer,26954,0 +57981,Female,26,Masters,7,88,75,34,1,5.0,7,42,Urban,HR Executive,103471,0 +57982,Male,35,Diploma,14,64,31,18,81,1.0,6,41,Rural,HR Executive,101545,0 +57983,Female,45,High School,12,2,28,34,31,7.0,7,85,Urban,Software Engineer,69065,0 +57984,Male,48,Masters,1,77,93,8,86,0.0,2,36,Urban,HR Executive,67373,0 +57985,Male,52,Bachelors,9,46,36,20,50,7.0,4,57,Semi-Urban,ML Engineer,67125,0 +57986,Male,21,High School,19,6,5,34,2,6.0,0,78,Rural,HR Executive,35461,0 +57987,Female,55,Diploma,1,0,50,71,69,0.0,2,51,Urban,Software Engineer,82374,0 +57988,Male,46,Bachelors,9,51,25,90,66,5.0,2,97,Urban,Data Analyst,83565,1 +57989,Male,57,Bachelors,1,41,1,88,30,7.0,2,86,Semi-Urban,Data Analyst,100221,0 +57990,Female,59,Masters,9,74,64,63,8,0.0,7,42,Rural,HR Executive,143559,1 +57991,Male,43,Bachelors,13,77,28,9,81,4.0,7,74,Rural,ML Engineer,44021,0 +57992,Male,39,Masters,6,9,48,14,25,9.0,2,27,Urban,Data Analyst,103088,0 +57993,Male,47,Diploma,4,28,94,10,22,3.0,7,4,Semi-Urban,Data Analyst,32560,0 +57994,Male,30,Diploma,6,70,24,72,35,2.0,2,0,Urban,Software Engineer,122489,0 +57995,Male,55,Masters,12,6,51,48,81,9.0,6,61,Urban,Data Analyst,142634,0 +57996,Female,58,Bachelors,13,25,40,16,55,4.0,7,45,Urban,Software Engineer,92833,0 +57997,Male,28,Bachelors,13,56,27,13,42,6.0,4,79,Semi-Urban,HR Executive,55779,0 +57998,Female,31,Diploma,18,52,78,90,22,0.0,7,46,Rural,ML Engineer,96092,1 +57999,Other,31,Masters,15,74,60,31,62,8.0,1,79,Urban,Data Analyst,67411,1 +58000,Female,59,Bachelors,0,83,0,70,95,0.0,2,77,Urban,Data Analyst,80651,0 +58001,Female,34,Masters,1,68,91,83,5,5.0,4,39,Urban,Manager,40898,1 +58002,Female,51,Bachelors,14,23,25,3,3,9.0,2,24,Urban,ML Engineer,87229,0 +58003,Other,49,Diploma,2,11,78,90,52,0.0,0,53,Rural,ML Engineer,29660,0 +58004,Male,28,High School,2,60,61,19,78,6.0,2,51,Urban,HR Executive,76295,0 +58005,Male,38,PhD,5,77,11,28,85,0.0,6,4,Urban,Data Analyst,38257,0 +58006,Female,36,High School,1,50,19,6,82,4.0,0,39,Semi-Urban,HR Executive,105706,0 +58007,Female,40,Masters,0,30,95,39,45,9.0,7,46,Urban,Data Analyst,90613,0 +58008,Male,59,High School,5,13,24,4,50,6.0,7,62,Rural,Data Analyst,27485,0 +58009,Female,32,Bachelors,6,7,71,44,32,5.0,6,15,Urban,HR Executive,53813,0 +58010,Male,33,Diploma,17,41,60,51,50,3.0,1,54,Urban,Software Engineer,139655,0 +58011,Male,51,Bachelors,9,44,61,71,31,9.0,2,22,Urban,Software Engineer,28738,0 +58012,Male,50,High School,4,89,74,80,77,3.0,7,93,Urban,HR Executive,53026,1 +58013,Male,38,Diploma,8,81,2,72,30,4.0,6,39,Semi-Urban,Manager,58733,0 +58014,Male,50,Masters,16,60,6,0,64,3.0,2,20,Urban,Software Engineer,71579,0 +58015,Male,50,Bachelors,2,33,83,89,79,5.0,0,21,Semi-Urban,Data Analyst,24148,0 +58016,Male,54,Bachelors,5,34,97,29,72,4.0,1,7,Urban,HR Executive,34240,0 +58017,Male,32,High School,15,86,40,50,73,0.0,4,49,Urban,Data Analyst,34610,0 +58018,Female,36,PhD,7,84,96,31,39,7.0,6,41,Urban,Manager,39674,1 +58019,Male,56,Bachelors,17,90,49,73,10,1.0,7,64,Semi-Urban,Software Engineer,117413,1 +58020,Female,45,High School,8,38,95,81,39,9.0,3,91,Urban,HR Executive,104451,1 +58021,Female,44,Bachelors,15,74,57,8,54,8.0,1,49,Urban,Manager,95142,0 +58022,Female,39,Masters,18,3,37,83,43,6.0,5,94,Urban,Manager,134954,0 +58023,Male,41,Bachelors,3,87,70,94,94,3.0,2,83,Rural,Software Engineer,124180,1 +58024,Other,51,Bachelors,0,89,74,90,81,3.0,3,46,Semi-Urban,Software Engineer,88409,1 +58025,Male,49,Bachelors,6,17,6,57,24,7.0,5,29,Urban,Manager,128428,0 +58026,Male,50,Masters,3,76,30,77,50,2.0,4,80,Urban,Data Analyst,122400,1 +58027,Female,44,Masters,14,29,28,21,43,8.0,7,82,Rural,Data Analyst,69075,0 +58028,Female,58,Bachelors,10,18,87,33,84,2.0,0,3,Urban,HR Executive,99745,0 +58029,Male,24,Bachelors,17,64,54,52,34,9.0,4,92,Urban,Data Analyst,70339,1 +58030,Male,23,Bachelors,10,18,53,8,88,9.0,1,39,Rural,ML Engineer,77670,0 +58031,Male,47,Bachelors,17,3,21,77,73,1.0,7,6,Urban,Data Analyst,64461,0 +58032,Male,56,PhD,1,11,12,58,47,1.0,7,76,Urban,Software Engineer,30954,0 +58033,Male,31,Diploma,18,97,62,78,16,7.0,3,94,Semi-Urban,Software Engineer,125980,1 +58034,Other,31,Bachelors,12,73,47,33,96,1.0,0,57,Urban,HR Executive,38813,0 +58035,Other,30,Diploma,3,5,32,71,26,9.0,3,51,Urban,Software Engineer,53122,0 +58036,Other,53,Bachelors,9,33,0,31,81,2.0,0,91,Semi-Urban,Data Analyst,126220,0 +58037,Male,42,Bachelors,0,66,86,38,58,9.0,6,37,Urban,Manager,97609,0 +58038,Male,28,Diploma,5,84,8,43,63,8.0,0,0,Rural,HR Executive,26704,0 +58039,Male,45,Diploma,15,74,16,61,54,7.0,0,17,Rural,Software Engineer,119888,0 +58040,Female,28,Masters,17,57,57,30,10,5.0,0,17,Urban,Data Analyst,126305,0 +58041,Male,45,Masters,12,9,76,43,18,5.0,7,43,Semi-Urban,Manager,34523,0 +58042,Female,44,Bachelors,11,81,58,72,99,8.0,0,71,Urban,Manager,84982,1 +58043,Female,57,Masters,1,26,42,26,40,8.0,4,89,Semi-Urban,Software Engineer,111473,0 +58044,Female,38,Diploma,16,79,38,4,1,3.0,3,27,Semi-Urban,ML Engineer,92736,0 +58045,Male,45,High School,1,6,97,27,3,9.0,2,86,Semi-Urban,Software Engineer,146633,0 +58046,Female,56,High School,11,56,65,96,33,5.0,0,59,Urban,Data Analyst,124608,1 +58047,Male,45,Bachelors,10,84,27,35,97,8.0,6,63,Semi-Urban,Software Engineer,25365,0 +58048,Male,32,Bachelors,17,14,19,92,47,8.0,7,70,Urban,HR Executive,45003,0 +58049,Male,26,Bachelors,0,21,80,47,12,3.0,2,72,Semi-Urban,Manager,40638,0 +58050,Male,21,Bachelors,9,60,51,60,76,7.0,0,55,Urban,HR Executive,68369,0 +58051,Male,44,Bachelors,7,85,11,13,78,8.0,7,84,Semi-Urban,Manager,93686,0 +58052,Male,43,High School,19,62,55,97,55,8.0,6,82,Urban,Data Analyst,32666,1 +58053,Female,48,Bachelors,11,92,13,27,70,7.0,3,32,Rural,ML Engineer,117641,0 +58054,Male,59,Bachelors,2,83,26,49,21,5.0,6,71,Rural,HR Executive,51774,0 +58055,Female,24,PhD,11,79,8,33,35,1.0,6,14,Semi-Urban,Manager,133545,0 +58056,Female,23,Masters,15,44,44,88,78,7.0,2,66,Semi-Urban,ML Engineer,21490,1 +58057,Male,58,Diploma,9,90,99,19,30,0.0,5,18,Urban,Software Engineer,146440,0 +58058,Male,25,High School,18,85,32,95,21,6.0,3,48,Semi-Urban,Software Engineer,89687,1 +58059,Male,39,Diploma,13,37,54,79,48,1.0,7,63,Urban,Manager,39191,0 +58060,Male,28,Masters,11,86,28,46,27,7.0,0,12,Semi-Urban,Software Engineer,72360,0 +58061,Male,23,Bachelors,18,11,12,89,79,3.0,4,31,Rural,Software Engineer,107274,0 +58062,Male,48,High School,18,8,26,51,91,5.0,0,25,Urban,Software Engineer,130452,0 +58063,Male,53,Bachelors,11,65,70,3,27,4.0,1,30,Rural,HR Executive,115746,0 +58064,Female,46,Bachelors,8,52,49,69,68,4.0,2,75,Semi-Urban,Manager,112167,1 +58065,Male,43,High School,10,87,33,28,95,6.0,2,50,Urban,Manager,29927,0 +58066,Female,52,Masters,10,65,59,48,36,3.0,3,10,Urban,Software Engineer,118734,0 +58067,Male,26,Bachelors,15,46,46,23,80,0.0,6,48,Urban,Data Analyst,99117,0 +58068,Male,38,Masters,8,57,96,18,95,2.0,4,19,Rural,ML Engineer,50993,0 +58069,Male,40,High School,4,43,27,97,73,7.0,7,24,Urban,HR Executive,140007,0 +58070,Female,38,Diploma,9,21,61,18,21,9.0,3,29,Urban,ML Engineer,84336,0 +58071,Female,36,Bachelors,17,32,12,7,19,7.0,3,76,Urban,Data Analyst,42123,0 +58072,Female,37,Diploma,11,78,59,15,14,4.0,3,12,Semi-Urban,HR Executive,87447,0 +58073,Male,47,High School,3,91,79,25,10,5.0,6,17,Urban,Software Engineer,109183,0 +58074,Female,41,Diploma,3,77,18,61,27,7.0,6,46,Urban,ML Engineer,100233,0 +58075,Male,48,Diploma,17,24,93,50,34,0.0,6,53,Rural,Software Engineer,119020,0 +58076,Male,25,Bachelors,6,7,43,73,19,9.0,7,26,Semi-Urban,ML Engineer,138628,0 +58077,Male,22,Diploma,7,86,86,27,72,1.0,5,60,Semi-Urban,Manager,127424,1 +58078,Male,49,High School,15,83,15,7,12,7.0,1,1,Urban,Software Engineer,101354,0 +58079,Female,40,Masters,5,89,2,9,98,1.0,4,31,Urban,HR Executive,143399,0 +58080,Female,27,Masters,13,66,85,5,2,1.0,6,10,Rural,Data Analyst,77695,0 +58081,Male,25,Bachelors,5,32,8,80,74,8.0,0,90,Urban,Software Engineer,144111,0 +58082,Other,29,Bachelors,8,87,87,68,56,2.0,0,3,Rural,Software Engineer,107772,1 +58083,Male,31,Diploma,5,70,16,15,31,3.0,7,15,Urban,HR Executive,93797,0 +58084,Male,24,Masters,9,69,70,5,13,0.0,3,17,Rural,Manager,47281,0 +58085,Female,42,Bachelors,18,3,14,21,17,7.0,1,32,Rural,Manager,65856,0 +58086,Male,49,Diploma,8,75,73,74,77,4.0,2,26,Rural,Software Engineer,98349,1 +58087,Female,29,Diploma,9,82,51,7,95,9.0,4,20,Semi-Urban,Software Engineer,123586,0 +58088,Male,51,Bachelors,1,73,64,4,74,7.0,6,41,Urban,Software Engineer,127433,0 +58089,Female,37,Masters,8,28,73,30,30,9.0,2,42,Urban,Software Engineer,65066,0 +58090,Female,25,PhD,6,76,88,98,50,7.0,6,78,Urban,ML Engineer,126642,1 +58091,Male,32,High School,9,91,58,22,98,9.0,3,71,Urban,Software Engineer,79446,1 +58092,Female,46,Bachelors,11,81,75,4,97,3.0,5,83,Urban,Manager,57733,1 +58093,Other,55,Bachelors,14,25,44,9,48,1.0,1,28,Urban,Manager,39563,0 +58094,Male,28,High School,10,89,66,75,32,2.0,0,59,Semi-Urban,HR Executive,138734,1 +58095,Male,35,Diploma,2,78,35,39,89,0.0,3,85,Urban,ML Engineer,50612,1 +58096,Female,48,Bachelors,11,5,35,49,58,8.0,5,63,Urban,Software Engineer,93993,0 +58097,Male,40,Bachelors,7,78,81,92,83,0.0,3,36,Urban,HR Executive,138539,1 +58098,Other,32,High School,4,88,50,12,80,4.0,2,65,Urban,Software Engineer,57155,0 +58099,Male,24,Bachelors,8,47,32,63,36,7.0,3,63,Urban,Software Engineer,67240,0 +58100,Male,46,Bachelors,1,94,50,8,13,5.0,6,27,Semi-Urban,Manager,25956,0 +58101,Female,21,High School,18,20,26,47,34,2.0,2,53,Urban,HR Executive,26452,0 +58102,Male,21,Diploma,17,13,81,22,58,2.0,0,42,Rural,ML Engineer,125706,0 +58103,Male,46,High School,8,66,18,83,25,9.0,2,71,Rural,ML Engineer,121049,1 +58104,Male,46,Masters,7,95,16,26,89,7.0,7,46,Urban,Software Engineer,99775,0 +58105,Female,27,Bachelors,11,22,33,56,78,2.0,7,40,Semi-Urban,ML Engineer,48651,0 +58106,Male,36,Bachelors,9,39,50,70,13,6.0,5,0,Urban,ML Engineer,79718,0 +58107,Male,22,Bachelors,2,68,7,48,74,7.0,0,57,Urban,Manager,61346,0 +58108,Female,59,Bachelors,0,9,99,49,45,5.0,3,19,Urban,ML Engineer,94189,0 +58109,Female,49,Masters,0,43,34,32,2,9.0,0,76,Urban,Manager,42382,0 +58110,Male,38,High School,11,47,4,90,83,6.0,5,67,Rural,HR Executive,35398,0 +58111,Male,25,High School,19,12,10,4,41,3.0,3,65,Urban,Software Engineer,111194,0 +58112,Male,37,Bachelors,3,28,65,45,77,7.0,2,88,Urban,HR Executive,84320,0 +58113,Female,42,Masters,18,89,33,22,66,8.0,6,5,Urban,Manager,97436,0 +58114,Male,50,Bachelors,13,80,2,86,96,9.0,2,3,Urban,HR Executive,23477,0 +58115,Male,32,Masters,12,80,70,27,68,9.0,4,17,Rural,ML Engineer,41243,0 +58116,Male,52,Diploma,5,67,62,74,5,4.0,0,51,Semi-Urban,Data Analyst,34468,1 +58117,Male,53,High School,13,25,38,72,13,2.0,4,98,Urban,HR Executive,92858,0 +58118,Female,46,Diploma,18,21,66,24,94,5.0,0,99,Urban,HR Executive,67075,0 +58119,Male,59,Diploma,13,47,48,94,27,1.0,7,22,Semi-Urban,HR Executive,40930,0 +58120,Male,42,Masters,18,92,86,90,58,9.0,2,16,Rural,HR Executive,20057,1 +58121,Male,42,Diploma,6,11,38,88,54,0.0,6,9,Semi-Urban,ML Engineer,85806,0 +58122,Male,51,Bachelors,11,6,89,59,53,0.0,5,44,Urban,Software Engineer,57069,0 +58123,Male,25,Diploma,15,25,38,16,61,3.0,6,48,Rural,Data Analyst,124139,0 +58124,Female,32,High School,11,84,38,47,5,5.0,3,33,Semi-Urban,ML Engineer,62674,0 +58125,Male,40,Bachelors,16,20,58,72,38,4.0,4,15,Urban,HR Executive,60130,0 +58126,Male,36,Bachelors,16,47,81,74,65,9.0,7,38,Semi-Urban,Software Engineer,100585,1 +58127,Male,40,PhD,19,70,73,39,72,1.0,4,62,Rural,Software Engineer,47291,1 +58128,Male,32,Masters,2,38,23,40,68,1.0,1,86,Urban,Software Engineer,139343,0 +58129,Female,56,Bachelors,16,30,62,10,82,7.0,5,6,Urban,Manager,95360,0 +58130,Female,58,Bachelors,13,37,5,10,6,2.0,1,88,Urban,Software Engineer,59189,0 +58131,Female,50,Diploma,14,71,5,83,63,9.0,3,60,Urban,HR Executive,112149,0 +58132,Male,50,Diploma,18,35,62,11,22,2.0,1,31,Urban,Manager,64811,0 +58133,Male,24,Bachelors,14,67,18,69,87,2.0,5,8,Urban,Manager,49700,0 +58134,Male,36,Bachelors,12,69,90,43,26,4.0,4,39,Urban,Manager,35447,1 +58135,Female,28,PhD,2,82,37,55,41,2.0,3,37,Urban,ML Engineer,51900,0 +58136,Male,47,Masters,5,63,94,95,26,7.0,2,73,Urban,Data Analyst,59873,1 +58137,Male,35,High School,1,14,91,99,37,6.0,6,39,Urban,Manager,125920,1 +58138,Male,59,Masters,19,9,87,4,11,6.0,2,96,Urban,Data Analyst,109893,0 +58139,Male,34,Diploma,8,99,22,87,33,4.0,6,15,Rural,ML Engineer,54586,0 +58140,Female,54,Masters,0,65,94,86,28,7.0,6,9,Urban,Manager,66969,1 +58141,Male,30,High School,5,30,3,22,9,5.0,6,63,Urban,Software Engineer,133887,0 +58142,Male,57,Bachelors,2,60,61,46,7,4.0,2,7,Urban,Manager,94823,0 +58143,Male,36,Diploma,12,58,90,35,16,3.0,0,85,Rural,HR Executive,41436,1 +58144,Female,29,Diploma,13,74,16,27,16,3.0,2,6,Urban,HR Executive,26348,0 +58145,Male,46,Masters,0,59,77,12,48,4.0,3,64,Urban,Data Analyst,82043,0 +58146,Male,39,Bachelors,19,14,90,3,33,9.0,3,24,Urban,Software Engineer,146646,0 +58147,Other,38,High School,6,9,59,59,35,2.0,1,83,Urban,HR Executive,128702,0 +58148,Male,35,Diploma,6,10,17,7,1,9.0,5,63,Urban,HR Executive,49266,0 +58149,Male,38,Bachelors,6,70,16,45,79,6.0,1,47,Rural,Manager,41050,0 +58150,Female,32,Masters,3,53,63,42,80,4.0,3,29,Semi-Urban,Data Analyst,102042,0 +58151,Male,59,Masters,16,87,3,77,36,2.0,2,29,Semi-Urban,ML Engineer,78099,0 +58152,Male,58,Bachelors,0,80,56,44,10,2.0,7,1,Semi-Urban,Data Analyst,103253,0 +58153,Male,40,Diploma,3,88,1,46,56,2.0,5,21,Rural,Software Engineer,112360,0 +58154,Male,58,Masters,13,16,24,73,94,9.0,4,68,Semi-Urban,ML Engineer,144929,0 +58155,Female,58,Bachelors,9,78,26,20,20,0.0,1,55,Urban,ML Engineer,109187,0 +58156,Female,53,High School,16,66,59,43,99,4.0,1,58,Urban,HR Executive,94979,0 +58157,Male,29,Diploma,19,72,7,74,67,9.0,1,49,Urban,HR Executive,75567,0 +58158,Female,56,Bachelors,1,90,34,4,30,0.0,1,93,Urban,Software Engineer,109060,0 +58159,Female,25,Bachelors,8,44,1,33,87,0.0,1,42,Urban,Software Engineer,149512,0 +58160,Male,40,Diploma,8,12,71,71,50,6.0,6,55,Urban,Software Engineer,25284,0 +58161,Male,21,Diploma,1,11,76,36,30,4.0,7,71,Urban,Data Analyst,87637,0 +58162,Female,41,Bachelors,12,67,32,27,87,4.0,5,70,Rural,Manager,146845,0 +58163,Male,45,Bachelors,17,14,3,97,46,1.0,0,89,Urban,Software Engineer,148870,0 +58164,Male,49,High School,9,53,61,52,33,7.0,6,14,Urban,ML Engineer,61033,0 +58165,Male,34,High School,8,38,7,12,56,4.0,4,17,Urban,Manager,117495,0 +58166,Male,34,Bachelors,1,91,43,7,35,9.0,5,46,Urban,Data Analyst,81068,0 +58167,Female,45,Diploma,7,76,8,45,85,7.0,2,97,Urban,Manager,148075,0 +58168,Male,33,Diploma,5,27,68,99,34,9.0,3,63,Semi-Urban,Manager,119601,1 +58169,Male,55,Bachelors,9,26,42,57,77,3.0,2,8,Rural,ML Engineer,58423,0 +58170,Male,44,Masters,1,13,40,24,20,7.0,4,1,Semi-Urban,HR Executive,43053,0 +58171,Female,50,Bachelors,2,70,16,55,93,0.0,0,95,Semi-Urban,Manager,113840,0 +58172,Male,58,High School,17,19,38,78,8,1.0,6,18,Rural,HR Executive,66232,0 +58173,Female,55,Masters,12,14,23,99,72,4.0,1,75,Urban,Software Engineer,39178,0 +58174,Male,32,Diploma,7,68,92,93,92,3.0,7,30,Urban,Software Engineer,118430,1 +58175,Male,33,Masters,12,82,37,87,98,5.0,5,46,Rural,HR Executive,60531,1 +58176,Male,48,PhD,1,19,68,72,90,9.0,6,39,Rural,Manager,49876,0 +58177,Female,56,Bachelors,1,36,41,22,41,5.0,3,28,Semi-Urban,Data Analyst,148929,0 +58178,Male,46,High School,11,31,83,10,34,2.0,4,71,Semi-Urban,HR Executive,110237,0 +58179,Female,57,Masters,8,61,46,36,43,1.0,0,83,Urban,HR Executive,54375,0 +58180,Male,48,Bachelors,1,95,6,59,56,8.0,3,26,Rural,ML Engineer,51566,0 +58181,Female,50,Bachelors,19,71,70,99,19,5.0,5,49,Rural,Manager,47043,1 +58182,Male,40,High School,11,41,17,51,96,7.0,1,51,Urban,Manager,138866,0 +58183,Male,32,Bachelors,9,20,75,84,1,7.0,4,43,Semi-Urban,Manager,123166,0 +58184,Male,25,Bachelors,16,28,53,11,57,6.0,3,98,Rural,HR Executive,130177,0 +58185,Male,39,High School,18,21,41,57,8,9.0,0,71,Urban,Software Engineer,109451,0 +58186,Female,42,Diploma,13,55,18,85,27,0.0,3,19,Rural,Data Analyst,42367,0 +58187,Male,24,Diploma,8,39,77,96,65,3.0,7,16,Rural,Software Engineer,54603,0 +58188,Female,31,Masters,12,88,61,32,32,1.0,4,62,Rural,HR Executive,100010,1 +58189,Male,44,Diploma,6,20,82,65,57,8.0,7,15,Rural,Manager,114301,0 +58190,Female,33,Masters,15,26,64,87,16,8.0,5,22,Urban,ML Engineer,65286,0 +58191,Female,36,Bachelors,4,46,8,98,31,3.0,0,69,Semi-Urban,ML Engineer,41949,0 +58192,Other,55,Masters,15,21,2,96,65,8.0,2,3,Rural,Software Engineer,93871,0 +58193,Male,40,Bachelors,7,15,53,26,50,5.0,1,8,Rural,Data Analyst,146071,0 +58194,Female,21,Bachelors,17,80,22,33,42,4.0,0,65,Rural,ML Engineer,57061,0 +58195,Male,47,Bachelors,16,10,44,45,82,3.0,6,77,Semi-Urban,Software Engineer,148877,0 +58196,Male,37,High School,13,2,38,22,80,7.0,5,97,Urban,HR Executive,73140,0 +58197,Female,43,Bachelors,13,66,54,65,3,3.0,1,11,Urban,ML Engineer,63491,0 +58198,Male,23,Diploma,3,83,98,18,1,7.0,1,64,Rural,HR Executive,29277,1 +58199,Male,47,Masters,17,93,4,60,37,0.0,2,99,Semi-Urban,HR Executive,134412,1 +58200,Other,22,High School,5,65,42,23,96,8.0,3,15,Urban,Software Engineer,73029,0 +58201,Female,27,Bachelors,15,85,19,72,66,0.0,2,85,Urban,Software Engineer,31847,1 +58202,Male,24,High School,15,35,86,77,9,1.0,6,56,Urban,Manager,38303,1 +58203,Male,45,Masters,13,80,67,65,24,0.0,4,8,Rural,Software Engineer,123379,0 +58204,Male,22,PhD,4,39,4,96,16,1.0,3,76,Rural,HR Executive,26783,0 +58205,Male,59,Masters,7,24,97,53,46,5.0,3,83,Semi-Urban,ML Engineer,27427,1 +58206,Female,26,Bachelors,11,75,31,95,48,3.0,1,76,Urban,Manager,23622,1 +58207,Female,32,Diploma,18,38,96,14,9,1.0,6,50,Urban,HR Executive,124881,0 +58208,Female,29,Masters,9,19,14,21,16,7.0,0,45,Rural,Data Analyst,71503,0 +58209,Male,51,High School,14,5,48,93,93,0.0,2,58,Urban,Software Engineer,47362,0 +58210,Female,33,Masters,7,0,14,13,69,8.0,7,13,Urban,ML Engineer,145662,0 +58211,Female,33,Bachelors,8,72,40,31,73,9.0,4,84,Semi-Urban,ML Engineer,115982,0 +58212,Male,45,Bachelors,6,86,89,95,53,7.0,3,34,Urban,Data Analyst,52687,1 +58213,Male,47,Bachelors,14,35,11,6,43,0.0,3,0,Semi-Urban,ML Engineer,21457,0 +58214,Male,56,Diploma,11,49,8,52,86,4.0,5,87,Rural,Software Engineer,88231,0 +58215,Male,27,Diploma,4,95,65,73,83,9.0,1,45,Semi-Urban,Software Engineer,149595,1 +58216,Male,35,Diploma,16,33,91,33,75,8.0,1,48,Urban,Software Engineer,66437,0 +58217,Male,39,Bachelors,13,17,52,53,77,7.0,0,85,Urban,HR Executive,125926,0 +58218,Male,54,High School,19,59,33,98,63,3.0,7,18,Semi-Urban,Manager,121218,0 +58219,Female,59,Bachelors,13,53,38,73,48,3.0,3,75,Semi-Urban,ML Engineer,108383,0 +58220,Female,25,Bachelors,7,69,81,72,31,1.0,3,56,Semi-Urban,ML Engineer,75887,1 +58221,Male,42,Bachelors,19,50,67,22,25,4.0,7,1,Rural,Manager,59253,0 +58222,Male,54,Masters,16,80,3,71,84,3.0,3,10,Urban,Software Engineer,147730,0 +58223,Male,42,Diploma,12,31,86,15,53,7.0,7,92,Rural,HR Executive,144226,0 +58224,Male,54,Bachelors,15,9,2,29,72,5.0,1,44,Semi-Urban,ML Engineer,44863,0 +58225,Female,41,Diploma,6,73,17,56,15,8.0,2,13,Rural,Software Engineer,89187,0 +58226,Male,59,High School,5,83,97,35,30,4.0,7,90,Urban,HR Executive,75143,1 +58227,Female,49,High School,5,81,81,71,54,2.0,3,45,Semi-Urban,Software Engineer,32678,1 +58228,Male,55,Masters,18,90,25,61,65,9.0,1,32,Urban,Software Engineer,24564,0 +58229,Male,43,Bachelors,2,58,38,73,18,9.0,6,20,Urban,Manager,124557,0 +58230,Male,39,Diploma,7,12,22,89,23,2.0,2,59,Semi-Urban,ML Engineer,61623,0 +58231,Female,24,High School,5,68,57,38,16,1.0,2,31,Rural,Software Engineer,91235,0 +58232,Male,47,Bachelors,19,79,3,31,45,9.0,7,68,Urban,Manager,105935,0 +58233,Other,59,Bachelors,4,26,94,33,68,5.0,5,78,Urban,HR Executive,147995,0 +58234,Female,33,Bachelors,8,49,76,17,21,1.0,4,48,Urban,HR Executive,61203,0 +58235,Male,55,High School,18,35,40,73,32,0.0,7,23,Urban,Software Engineer,132284,0 +58236,Female,44,Bachelors,4,99,7,78,51,3.0,6,70,Urban,HR Executive,82907,1 +58237,Male,41,Masters,11,37,43,4,17,8.0,1,90,Urban,Data Analyst,34204,0 +58238,Female,33,Masters,12,78,99,15,50,0.0,5,1,Rural,HR Executive,93293,0 +58239,Male,57,Diploma,11,8,48,86,95,7.0,2,55,Semi-Urban,ML Engineer,29755,0 +58240,Male,23,High School,15,46,84,45,18,3.0,4,18,Urban,Software Engineer,62991,0 +58241,Female,26,Bachelors,9,61,27,61,96,9.0,4,2,Urban,Manager,96344,0 +58242,Male,37,Diploma,1,84,81,93,97,2.0,4,83,Urban,ML Engineer,115922,1 +58243,Male,34,Diploma,15,17,43,87,59,8.0,6,90,Urban,Data Analyst,71998,1 +58244,Female,29,Bachelors,13,24,12,37,87,2.0,1,99,Rural,HR Executive,39191,0 +58245,Male,55,Diploma,18,88,29,92,94,3.0,2,99,Rural,Data Analyst,32462,1 +58246,Male,29,Bachelors,19,74,96,34,96,3.0,3,33,Semi-Urban,Data Analyst,118601,1 +58247,Male,24,Bachelors,9,55,85,47,24,9.0,4,15,Urban,Software Engineer,23577,0 +58248,Male,29,Masters,0,24,22,56,24,8.0,3,92,Urban,Manager,48802,0 +58249,Male,45,Diploma,1,28,18,9,96,7.0,4,39,Urban,HR Executive,37418,0 +58250,Female,48,Diploma,7,17,7,19,41,7.0,6,56,Urban,Manager,106111,0 +58251,Male,21,Bachelors,13,38,28,94,19,8.0,4,4,Rural,Data Analyst,25833,0 +58252,Male,29,High School,10,45,28,74,34,2.0,0,49,Semi-Urban,HR Executive,102641,0 +58253,Male,58,Diploma,9,16,94,36,23,8.0,2,54,Urban,ML Engineer,79620,0 +58254,Male,50,Bachelors,9,53,65,81,76,8.0,1,70,Semi-Urban,Software Engineer,83171,1 +58255,Male,54,Bachelors,15,30,36,63,28,9.0,7,71,Semi-Urban,Manager,87911,0 +58256,Male,43,PhD,3,21,66,55,34,5.0,2,30,Semi-Urban,Software Engineer,107932,0 +58257,Female,46,Bachelors,15,26,23,49,1,5.0,6,5,Semi-Urban,Software Engineer,26728,0 +58258,Male,59,Masters,8,74,84,69,65,1.0,1,89,Urban,HR Executive,29180,1 +58259,Male,47,Masters,5,30,63,35,7,5.0,0,71,Semi-Urban,HR Executive,67406,0 +58260,Female,59,PhD,9,26,35,51,44,8.0,0,11,Urban,Data Analyst,76993,0 +58261,Male,46,Bachelors,14,11,44,33,94,6.0,2,55,Urban,Manager,105255,0 +58262,Male,22,Bachelors,14,64,26,95,75,5.0,1,49,Rural,Manager,92906,0 +58263,Female,29,Bachelors,18,39,9,20,70,3.0,5,13,Urban,ML Engineer,147586,0 +58264,Male,45,High School,4,95,44,69,82,0.0,2,20,Semi-Urban,Software Engineer,70133,0 +58265,Male,52,High School,12,95,6,27,90,1.0,6,73,Rural,Software Engineer,34094,0 +58266,Female,41,Diploma,14,77,56,22,2,3.0,6,84,Urban,Software Engineer,41994,0 +58267,Female,57,High School,8,15,14,79,97,3.0,0,38,Semi-Urban,Software Engineer,93541,0 +58268,Female,45,Diploma,3,7,38,33,93,9.0,7,11,Semi-Urban,HR Executive,101226,0 +58269,Male,40,Bachelors,9,51,75,32,10,4.0,7,73,Urban,HR Executive,136328,0 +58270,Male,57,Masters,3,72,58,89,62,5.0,7,83,Urban,Data Analyst,60505,1 +58271,Female,46,Masters,13,24,0,37,91,7.0,0,38,Semi-Urban,Data Analyst,106646,0 +58272,Female,47,Bachelors,1,98,18,32,51,6.0,2,14,Rural,ML Engineer,69190,0 +58273,Male,24,Diploma,16,37,62,42,23,6.0,5,21,Urban,Manager,85994,0 +58274,Female,21,Bachelors,5,99,3,87,79,5.0,5,72,Urban,HR Executive,40150,1 +58275,Male,23,Masters,0,92,73,41,37,5.0,6,96,Semi-Urban,ML Engineer,77978,1 +58276,Male,37,Masters,10,10,49,97,97,9.0,2,84,Semi-Urban,ML Engineer,72665,1 +58277,Female,51,Bachelors,8,23,35,34,20,3.0,3,98,Urban,ML Engineer,29059,0 +58278,Female,53,High School,5,28,42,14,63,0.0,1,28,Urban,Data Analyst,108230,0 +58279,Female,21,Bachelors,13,88,24,38,24,4.0,0,46,Urban,ML Engineer,93564,0 +58280,Male,50,Bachelors,1,14,97,14,64,6.0,4,1,Urban,ML Engineer,46374,0 +58281,Male,33,Diploma,11,24,67,71,44,0.0,0,24,Rural,Software Engineer,143154,0 +58282,Male,32,Bachelors,17,15,24,36,41,3.0,3,48,Urban,HR Executive,66971,0 +58283,Female,23,PhD,11,58,12,28,43,6.0,0,68,Urban,ML Engineer,62965,0 +58284,Male,32,Diploma,1,0,56,28,24,1.0,7,96,Rural,Manager,135231,0 +58285,Female,29,Masters,7,28,69,80,1,3.0,4,27,Semi-Urban,ML Engineer,108862,0 +58286,Female,56,Bachelors,5,17,19,3,57,7.0,5,20,Rural,Manager,20653,0 +58287,Female,54,Masters,1,83,0,14,61,1.0,7,15,Rural,ML Engineer,107365,0 +58288,Female,45,Bachelors,6,57,42,71,26,7.0,4,8,Urban,ML Engineer,116135,0 +58289,Female,54,Bachelors,10,49,61,63,89,4.0,3,34,Rural,Manager,64730,0 +58290,Female,46,Masters,8,4,2,82,88,6.0,5,97,Urban,ML Engineer,113813,0 +58291,Male,47,Bachelors,19,32,84,16,59,4.0,6,44,Urban,Data Analyst,110988,0 +58292,Female,32,High School,4,37,43,97,21,5.0,0,93,Semi-Urban,Data Analyst,114365,1 +58293,Male,57,Bachelors,11,43,61,72,92,8.0,6,25,Urban,HR Executive,57700,0 +58294,Male,50,Bachelors,1,33,74,54,81,8.0,2,48,Urban,ML Engineer,63937,0 +58295,Female,32,Bachelors,2,2,31,89,63,5.0,0,36,Semi-Urban,Data Analyst,36604,0 +58296,Male,51,Bachelors,4,27,96,35,49,3.0,6,85,Urban,HR Executive,81367,1 +58297,Female,48,Bachelors,19,56,68,78,45,9.0,5,1,Urban,HR Executive,90160,0 +58298,Male,31,Bachelors,2,97,91,8,64,1.0,1,30,Urban,Manager,66545,0 +58299,Female,22,High School,0,52,95,37,57,1.0,1,79,Urban,HR Executive,43941,1 +58300,Other,55,Diploma,17,78,40,70,8,7.0,6,92,Urban,ML Engineer,124922,1 +58301,Female,29,High School,8,66,43,95,49,1.0,6,3,Semi-Urban,HR Executive,82296,0 +58302,Male,41,Masters,10,18,8,1,73,3.0,1,81,Urban,ML Engineer,69715,0 +58303,Male,26,PhD,10,84,85,16,55,7.0,5,51,Urban,Software Engineer,148391,1 +58304,Other,28,Diploma,19,48,49,32,9,8.0,2,97,Rural,HR Executive,118016,0 +58305,Male,26,Masters,9,85,81,73,85,1.0,2,33,Semi-Urban,Data Analyst,145386,1 +58306,Male,56,High School,4,85,77,41,74,3.0,4,52,Rural,Software Engineer,53038,1 +58307,Female,37,Masters,10,55,11,55,86,6.0,5,99,Urban,Manager,139242,0 +58308,Male,42,Bachelors,7,88,8,79,8,7.0,4,90,Semi-Urban,ML Engineer,23785,1 +58309,Male,35,Masters,6,3,12,95,82,9.0,7,63,Urban,HR Executive,135806,0 +58310,Female,42,Bachelors,0,44,5,47,98,8.0,1,21,Rural,Data Analyst,84006,0 +58311,Male,41,Bachelors,3,41,37,16,50,9.0,7,2,Semi-Urban,HR Executive,148308,0 +58312,Male,23,Bachelors,0,86,33,25,22,8.0,7,13,Urban,HR Executive,137704,0 +58313,Female,40,Bachelors,5,96,1,49,16,5.0,4,74,Urban,Data Analyst,117922,0 +58314,Female,56,Bachelors,0,68,21,81,36,7.0,2,16,Urban,ML Engineer,142551,0 +58315,Female,51,Bachelors,6,82,74,16,88,6.0,0,39,Semi-Urban,ML Engineer,126087,0 +58316,Male,50,Bachelors,13,83,83,41,8,5.0,0,69,Semi-Urban,Data Analyst,20073,1 +58317,Female,29,Diploma,7,54,10,85,20,6.0,1,52,Urban,Manager,27301,0 +58318,Female,22,High School,6,84,28,78,90,8.0,6,64,Semi-Urban,Software Engineer,149128,1 +58319,Female,54,High School,4,56,37,50,24,9.0,6,16,Urban,Software Engineer,91110,0 +58320,Male,50,Bachelors,8,5,44,46,51,2.0,6,48,Urban,HR Executive,95813,0 +58321,Male,58,Masters,0,75,44,94,95,2.0,2,19,Urban,Software Engineer,110061,0 +58322,Female,56,Bachelors,2,52,55,22,4,6.0,7,51,Urban,Manager,106799,0 +58323,Male,58,High School,14,76,49,3,18,5.0,1,42,Rural,Software Engineer,104483,0 +58324,Male,21,Bachelors,12,2,38,80,84,6.0,5,83,Semi-Urban,ML Engineer,77842,0 +58325,Male,48,Diploma,7,34,25,96,60,0.0,7,40,Urban,HR Executive,94811,0 +58326,Male,52,Masters,3,60,38,83,71,3.0,4,37,Semi-Urban,Manager,64924,0 +58327,Male,58,Bachelors,11,67,94,4,58,7.0,0,78,Urban,Manager,106712,1 +58328,Female,36,Masters,19,69,22,14,79,1.0,6,66,Urban,Software Engineer,91630,0 +58329,Female,31,Bachelors,2,93,85,8,89,4.0,7,58,Semi-Urban,Data Analyst,79707,1 +58330,Male,24,Masters,1,54,4,5,74,2.0,4,71,Urban,Data Analyst,147652,0 +58331,Female,56,Bachelors,2,55,24,55,31,0.0,7,51,Urban,Software Engineer,62541,0 +58332,Male,30,Diploma,15,32,36,70,92,7.0,0,67,Rural,Data Analyst,140994,0 +58333,Male,42,Bachelors,3,72,79,89,24,2.0,1,12,Urban,Manager,33203,1 +58334,Male,49,Bachelors,4,7,7,41,74,5.0,7,5,Urban,Data Analyst,142330,0 +58335,Male,52,Bachelors,8,81,3,53,89,3.0,5,85,Rural,ML Engineer,64762,0 +58336,Male,21,Diploma,3,83,0,34,77,1.0,2,49,Semi-Urban,ML Engineer,102494,0 +58337,Female,32,Bachelors,8,57,5,27,21,5.0,3,35,Semi-Urban,Software Engineer,100817,0 +58338,Female,32,Diploma,1,30,11,32,38,8.0,4,81,Urban,Manager,93599,0 +58339,Male,44,Bachelors,19,71,93,8,34,9.0,3,22,Urban,Data Analyst,148825,0 +58340,Male,49,Diploma,9,46,66,45,70,4.0,5,96,Urban,ML Engineer,84825,1 +58341,Male,49,Bachelors,5,75,18,99,11,8.0,1,14,Urban,Software Engineer,88332,0 +58342,Other,55,Bachelors,15,11,86,99,14,0.0,2,69,Urban,Data Analyst,92366,1 +58343,Male,32,Masters,12,6,92,50,76,9.0,0,29,Semi-Urban,Software Engineer,30566,0 +58344,Female,58,Bachelors,4,62,39,73,28,6.0,3,29,Semi-Urban,Software Engineer,41249,0 +58345,Male,56,Bachelors,16,29,98,18,79,2.0,0,45,Urban,Software Engineer,85734,0 +58346,Male,23,Bachelors,9,61,22,75,3,8.0,0,35,Urban,ML Engineer,34797,0 +58347,Female,36,Masters,14,92,70,94,30,6.0,1,89,Semi-Urban,HR Executive,145092,1 +58348,Male,59,Bachelors,12,79,47,48,39,8.0,6,51,Urban,Manager,122102,0 +58349,Female,21,Bachelors,5,24,86,76,86,6.0,3,12,Urban,ML Engineer,97210,0 +58350,Female,26,Bachelors,16,79,6,91,8,2.0,2,0,Urban,HR Executive,101678,0 +58351,Female,23,Bachelors,15,82,22,46,0,9.0,6,30,Urban,Data Analyst,108143,0 +58352,Female,56,Diploma,7,24,77,13,83,9.0,2,78,Urban,HR Executive,147970,0 +58353,Female,32,Bachelors,19,43,31,52,11,0.0,3,82,Semi-Urban,Data Analyst,120108,0 +58354,Male,26,High School,4,59,4,55,76,3.0,2,21,Urban,Software Engineer,103305,0 +58355,Female,28,Diploma,3,41,90,94,60,5.0,6,60,Urban,Data Analyst,53077,1 +58356,Female,56,Bachelors,14,30,77,92,94,0.0,7,5,Semi-Urban,Software Engineer,144032,0 +58357,Male,51,Bachelors,9,56,58,13,57,0.0,5,87,Semi-Urban,Data Analyst,141314,0 +58358,Male,50,High School,13,99,26,92,33,6.0,6,61,Urban,Manager,137002,1 +58359,Male,26,Diploma,15,84,81,17,26,5.0,2,82,Semi-Urban,Manager,111936,1 +58360,Male,47,PhD,2,4,0,95,54,8.0,1,63,Urban,ML Engineer,37319,0 +58361,Male,41,High School,2,22,88,92,23,3.0,3,66,Urban,Manager,123216,1 +58362,Male,59,Bachelors,0,14,3,95,93,4.0,4,52,Rural,HR Executive,40364,0 +58363,Female,21,Bachelors,17,11,11,64,65,7.0,2,26,Urban,ML Engineer,90930,0 +58364,Male,45,Diploma,6,90,9,35,45,9.0,2,93,Urban,ML Engineer,72911,0 +58365,Female,45,High School,15,43,3,88,88,7.0,4,38,Urban,ML Engineer,66195,0 +58366,Female,43,Masters,10,2,74,76,43,9.0,7,23,Rural,HR Executive,26943,0 +58367,Male,40,Bachelors,12,17,69,90,56,6.0,7,79,Urban,Data Analyst,119215,1 +58368,Male,36,Diploma,11,57,15,32,88,5.0,3,58,Rural,Data Analyst,56979,0 +58369,Male,51,Masters,16,27,69,6,40,3.0,0,75,Urban,ML Engineer,118016,0 +58370,Female,44,Bachelors,11,69,91,46,83,1.0,3,56,Urban,Software Engineer,111663,1 +58371,Female,53,Bachelors,0,75,28,1,48,9.0,3,33,Urban,HR Executive,32466,0 +58372,Female,28,Bachelors,12,99,35,15,86,6.0,2,9,Urban,Data Analyst,83668,0 +58373,Female,56,Diploma,19,67,42,78,0,9.0,7,43,Urban,Manager,62202,0 +58374,Male,37,High School,3,30,53,2,23,5.0,7,14,Urban,Data Analyst,117652,0 +58375,Male,29,Diploma,7,36,47,81,28,5.0,1,78,Urban,Data Analyst,139615,1 +58376,Male,43,Diploma,13,93,55,80,81,7.0,4,79,Rural,Data Analyst,141716,1 +58377,Male,32,Diploma,16,41,42,34,30,7.0,3,47,Urban,HR Executive,132596,0 +58378,Male,33,Bachelors,18,92,7,41,52,5.0,2,48,Rural,HR Executive,137371,0 +58379,Female,37,Bachelors,7,88,40,41,92,8.0,2,32,Urban,ML Engineer,38350,0 +58380,Male,43,High School,7,4,14,0,84,0.0,6,45,Rural,HR Executive,141570,0 +58381,Male,47,Diploma,9,50,46,10,11,8.0,4,65,Urban,Data Analyst,68444,0 +58382,Female,48,Diploma,6,34,11,73,5,3.0,2,47,Urban,HR Executive,26966,0 +58383,Female,35,Diploma,13,93,6,14,96,4.0,6,22,Semi-Urban,HR Executive,54936,0 +58384,Male,57,Masters,14,70,98,21,72,8.0,4,19,Semi-Urban,Software Engineer,72390,0 +58385,Other,49,Masters,7,61,75,78,61,5.0,6,90,Urban,Software Engineer,62507,1 +58386,Male,50,Masters,16,99,81,42,79,7.0,2,59,Urban,HR Executive,68489,1 +58387,Female,42,Masters,6,37,7,84,61,0.0,0,92,Semi-Urban,HR Executive,40136,0 +58388,Female,58,Bachelors,8,92,88,75,30,3.0,2,44,Urban,Data Analyst,118631,1 +58389,Male,56,High School,3,69,2,72,31,4.0,4,50,Rural,HR Executive,51365,0 +58390,Female,35,Bachelors,11,84,81,49,33,8.0,5,31,Urban,HR Executive,28653,1 +58391,Female,58,High School,0,21,80,40,54,0.0,6,17,Rural,Software Engineer,45444,0 +58392,Male,26,Diploma,11,8,59,40,49,0.0,4,33,Rural,Software Engineer,137595,0 +58393,Female,26,Diploma,11,83,87,77,18,8.0,6,79,Urban,ML Engineer,144570,1 +58394,Female,26,High School,17,50,33,98,33,6.0,4,9,Semi-Urban,Manager,60792,0 +58395,Female,46,PhD,4,61,75,12,16,8.0,2,45,Urban,HR Executive,37488,0 +58396,Female,55,Bachelors,7,90,62,15,91,4.0,5,0,Urban,Software Engineer,111202,0 +58397,Male,59,Diploma,19,68,75,69,10,2.0,6,25,Rural,ML Engineer,76904,1 +58398,Male,24,Bachelors,5,78,11,68,68,1.0,1,15,Semi-Urban,Manager,84588,0 +58399,Male,36,Bachelors,19,8,17,15,0,8.0,1,50,Urban,Software Engineer,133128,0 +58400,Male,42,Bachelors,13,47,80,69,97,8.0,0,73,Urban,Data Analyst,145730,1 +58401,Female,38,Diploma,11,13,58,19,78,7.0,2,98,Rural,ML Engineer,123925,0 +58402,Male,25,High School,6,12,87,61,11,4.0,7,11,Urban,Software Engineer,141537,0 +58403,Male,29,High School,8,76,14,4,43,4.0,6,54,Semi-Urban,ML Engineer,130105,0 +58404,Male,31,Masters,11,65,55,77,42,6.0,7,23,Rural,Software Engineer,54904,0 +58405,Male,56,Masters,4,95,28,48,36,0.0,0,96,Urban,Data Analyst,113870,1 +58406,Male,27,Bachelors,18,50,95,63,94,0.0,5,24,Urban,Software Engineer,94676,0 +58407,Male,53,Masters,18,56,79,12,67,8.0,0,7,Urban,Software Engineer,117560,0 +58408,Male,32,Bachelors,9,7,26,94,9,6.0,2,6,Semi-Urban,ML Engineer,128388,0 +58409,Female,27,Diploma,1,20,20,48,35,9.0,2,35,Urban,Data Analyst,147108,0 +58410,Male,53,Diploma,12,7,75,65,27,9.0,7,46,Urban,Software Engineer,24367,0 +58411,Female,33,Diploma,19,13,99,59,48,7.0,4,88,Urban,ML Engineer,138167,1 +58412,Male,41,Bachelors,3,6,66,39,90,5.0,2,19,Semi-Urban,Software Engineer,147971,0 +58413,Male,30,Masters,11,35,58,57,12,1.0,1,73,Semi-Urban,ML Engineer,125755,0 +58414,Male,39,High School,10,13,76,14,28,2.0,4,92,Urban,HR Executive,113212,0 +58415,Other,38,Diploma,8,70,83,19,15,2.0,5,8,Urban,Software Engineer,76176,0 +58416,Female,28,Masters,17,51,1,58,13,6.0,0,59,Urban,Manager,83314,0 +58417,Male,33,Bachelors,15,71,27,38,41,4.0,6,30,Semi-Urban,ML Engineer,66421,0 +58418,Female,35,Bachelors,5,8,21,96,66,0.0,3,74,Rural,Manager,98701,0 +58419,Male,35,Bachelors,4,9,42,12,88,5.0,3,6,Urban,Software Engineer,52595,0 +58420,Female,31,Masters,7,78,26,76,81,0.0,1,3,Semi-Urban,HR Executive,116376,0 +58421,Other,38,Masters,2,39,11,72,36,2.0,3,28,Rural,Data Analyst,142411,0 +58422,Male,26,Diploma,13,11,1,23,85,8.0,7,91,Urban,HR Executive,82078,0 +58423,Female,43,Bachelors,18,11,6,5,88,4.0,5,9,Urban,Software Engineer,114625,0 +58424,Male,30,Masters,8,6,85,82,8,7.0,4,92,Semi-Urban,Software Engineer,134999,1 +58425,Female,33,Masters,7,70,13,91,89,3.0,0,97,Rural,Data Analyst,56837,1 +58426,Male,49,Bachelors,15,81,12,61,65,9.0,6,40,Semi-Urban,Manager,107018,0 +58427,Male,53,Diploma,12,59,6,60,42,9.0,5,98,Semi-Urban,ML Engineer,40615,0 +58428,Male,45,Masters,11,29,88,65,61,6.0,3,26,Urban,Software Engineer,117812,0 +58429,Male,26,Masters,17,37,61,7,70,8.0,5,52,Urban,Software Engineer,55778,0 +58430,Female,21,PhD,11,21,98,14,53,8.0,3,89,Urban,ML Engineer,49088,0 +58431,Male,25,Masters,5,57,68,78,3,0.0,1,60,Semi-Urban,HR Executive,52927,1 +58432,Female,57,Bachelors,8,32,80,98,91,6.0,6,72,Urban,Manager,60799,1 +58433,Female,46,High School,7,58,42,11,67,9.0,2,44,Urban,Software Engineer,31169,0 +58434,Male,49,Masters,19,29,42,63,12,4.0,1,33,Urban,Data Analyst,23643,0 +58435,Male,33,Bachelors,9,12,76,80,61,2.0,6,72,Urban,Data Analyst,135448,1 +58436,Other,44,Bachelors,14,30,85,82,43,6.0,2,88,Urban,Data Analyst,74269,1 +58437,Female,47,Bachelors,11,92,50,80,47,4.0,2,84,Rural,HR Executive,102984,1 +58438,Male,50,Bachelors,11,3,7,66,37,3.0,6,28,Urban,ML Engineer,132295,0 +58439,Male,31,Bachelors,8,12,39,57,76,9.0,6,55,Urban,Data Analyst,34858,0 +58440,Other,33,Bachelors,17,32,41,37,18,1.0,0,91,Urban,Software Engineer,30116,0 +58441,Male,21,Diploma,7,14,32,89,32,9.0,6,83,Urban,HR Executive,115007,0 +58442,Female,22,Bachelors,0,98,21,86,28,2.0,1,57,Urban,Manager,39159,1 +58443,Male,58,Bachelors,15,95,77,80,49,4.0,1,90,Rural,HR Executive,73390,1 +58444,Male,43,High School,4,97,58,9,53,0.0,5,52,Urban,Manager,126571,0 +58445,Female,42,PhD,14,93,78,50,4,5.0,1,63,Urban,Manager,50402,1 +58446,Male,32,Bachelors,0,55,31,7,8,4.0,4,26,Urban,ML Engineer,118649,0 +58447,Male,27,High School,9,97,33,93,28,2.0,5,16,Urban,ML Engineer,123651,1 +58448,Male,43,Bachelors,10,82,67,29,65,9.0,6,1,Urban,ML Engineer,55270,0 +58449,Female,59,Masters,9,19,18,37,45,4.0,4,98,Urban,HR Executive,61080,0 +58450,Male,27,Bachelors,11,89,87,5,77,3.0,4,39,Urban,Data Analyst,138457,0 +58451,Male,28,Masters,8,95,68,52,72,9.0,7,33,Urban,Software Engineer,110429,1 +58452,Male,49,High School,1,47,47,13,84,6.0,6,20,Semi-Urban,ML Engineer,22499,0 +58453,Male,45,Bachelors,8,63,27,58,83,2.0,7,92,Urban,Data Analyst,44940,1 +58454,Male,41,PhD,14,53,33,26,97,8.0,1,81,Urban,Manager,70798,0 +58455,Female,24,PhD,19,79,72,8,13,0.0,6,16,Urban,Data Analyst,65315,0 +58456,Male,34,Diploma,6,66,99,18,34,8.0,0,46,Urban,Data Analyst,78147,0 +58457,Male,39,Masters,10,55,88,21,11,6.0,6,51,Semi-Urban,ML Engineer,86722,0 +58458,Male,26,Bachelors,18,25,70,93,13,2.0,0,46,Rural,Data Analyst,22733,0 +58459,Male,54,High School,15,37,15,78,26,1.0,2,2,Urban,Data Analyst,22585,0 +58460,Male,59,Bachelors,3,90,8,33,89,9.0,1,50,Urban,ML Engineer,135372,0 +58461,Male,24,Diploma,7,88,50,87,14,6.0,0,71,Urban,Software Engineer,148586,1 +58462,Male,53,Diploma,3,7,9,11,12,2.0,1,66,Semi-Urban,Software Engineer,68780,0 +58463,Female,24,PhD,19,94,3,75,0,4.0,3,46,Urban,HR Executive,98159,0 +58464,Female,24,PhD,19,92,60,49,49,5.0,6,84,Urban,Data Analyst,62838,1 +58465,Male,36,Diploma,15,15,81,67,69,6.0,3,36,Urban,ML Engineer,97281,0 +58466,Female,35,PhD,15,58,78,36,35,3.0,1,61,Urban,Manager,48672,0 +58467,Male,56,Bachelors,2,39,85,85,57,0.0,4,13,Urban,Manager,75726,0 +58468,Male,24,Bachelors,18,0,33,12,7,7.0,2,37,Urban,Data Analyst,53733,0 +58469,Male,27,Diploma,10,25,2,28,25,8.0,2,39,Semi-Urban,Manager,41876,0 +58470,Male,59,Masters,19,92,38,0,56,4.0,5,59,Semi-Urban,Manager,54389,0 +58471,Male,39,Diploma,7,22,12,83,36,9.0,2,29,Rural,ML Engineer,68900,0 +58472,Female,26,Diploma,9,44,72,87,9,7.0,1,54,Urban,HR Executive,137630,1 +58473,Male,55,Diploma,12,88,16,4,11,2.0,2,83,Urban,Data Analyst,38582,0 +58474,Male,46,Bachelors,3,20,56,28,92,8.0,1,52,Rural,Manager,148511,0 +58475,Female,37,Diploma,15,76,3,89,37,5.0,6,62,Semi-Urban,Data Analyst,119542,0 +58476,Male,27,Bachelors,17,66,96,14,52,1.0,2,91,Rural,Data Analyst,136236,1 +58477,Male,57,High School,11,34,92,50,30,9.0,7,16,Urban,Data Analyst,84708,0 +58478,Male,56,Bachelors,19,46,24,69,96,0.0,0,91,Rural,HR Executive,141262,0 +58479,Male,36,Diploma,10,12,58,82,50,4.0,7,13,Semi-Urban,Software Engineer,102605,0 +58480,Female,43,Bachelors,11,73,40,56,8,1.0,4,20,Urban,Data Analyst,38626,0 +58481,Male,39,High School,6,82,22,38,22,5.0,5,95,Urban,Manager,131510,1 +58482,Female,47,Diploma,2,3,45,18,93,5.0,1,26,Urban,ML Engineer,109323,0 +58483,Male,27,High School,18,42,37,5,39,3.0,4,2,Semi-Urban,Software Engineer,148413,0 +58484,Male,27,High School,15,13,14,61,60,9.0,4,14,Semi-Urban,HR Executive,81341,0 +58485,Male,46,Bachelors,18,78,7,14,87,0.0,7,69,Semi-Urban,Software Engineer,37493,0 +58486,Male,43,Bachelors,8,30,74,71,9,1.0,5,39,Semi-Urban,Software Engineer,131600,0 +58487,Male,54,Bachelors,16,6,99,45,78,7.0,5,98,Urban,ML Engineer,107621,1 +58488,Male,23,Masters,18,92,75,69,69,4.0,2,38,Semi-Urban,ML Engineer,114820,1 +58489,Male,39,Bachelors,19,40,27,79,31,9.0,0,49,Rural,Data Analyst,67977,0 +58490,Male,27,Diploma,4,57,15,4,18,5.0,0,64,Semi-Urban,Software Engineer,80638,0 +58491,Female,47,Bachelors,11,58,5,50,85,4.0,1,29,Semi-Urban,Manager,134508,0 +58492,Male,33,Bachelors,17,19,63,17,38,6.0,1,4,Semi-Urban,Software Engineer,135373,0 +58493,Female,56,High School,12,9,40,88,83,3.0,0,56,Urban,Software Engineer,34026,0 +58494,Female,34,Masters,0,75,76,63,92,7.0,0,70,Urban,HR Executive,65190,1 +58495,Male,42,High School,5,69,39,39,3,3.0,1,83,Rural,HR Executive,70323,0 +58496,Male,37,High School,19,71,33,73,55,1.0,5,40,Semi-Urban,Data Analyst,116037,0 +58497,Male,43,High School,11,88,32,11,70,4.0,2,67,Rural,Manager,94928,0 +58498,Male,21,High School,19,60,23,5,10,2.0,4,27,Urban,HR Executive,93528,0 +58499,Male,59,Bachelors,17,34,96,71,44,2.0,5,51,Urban,Data Analyst,56511,1 +58500,Male,47,Diploma,17,93,71,10,59,9.0,0,28,Urban,ML Engineer,81103,0 +58501,Male,33,Bachelors,0,17,58,1,86,8.0,7,99,Semi-Urban,Manager,88506,0 +58502,Male,34,Bachelors,2,97,22,79,81,1.0,2,58,Rural,Data Analyst,96706,1 +58503,Male,52,Bachelors,7,71,72,43,96,6.0,5,30,Semi-Urban,Manager,43410,0 +58504,Male,58,Masters,12,38,75,36,43,0.0,4,43,Rural,HR Executive,119664,0 +58505,Male,45,Diploma,8,57,93,57,5,8.0,5,66,Semi-Urban,Software Engineer,78799,1 +58506,Female,43,Bachelors,5,13,43,85,98,9.0,5,4,Urban,HR Executive,137044,0 +58507,Female,27,High School,2,34,33,22,1,4.0,7,49,Urban,Manager,131226,0 +58508,Male,31,Bachelors,1,59,93,85,74,4.0,2,50,Rural,HR Executive,149272,1 +58509,Female,22,Masters,14,10,83,26,41,3.0,2,19,Rural,ML Engineer,88776,0 +58510,Male,45,High School,13,42,0,45,94,1.0,4,99,Urban,Manager,42817,0 +58511,Male,42,Masters,16,70,19,57,19,3.0,1,27,Urban,Manager,126402,0 +58512,Male,28,Bachelors,11,87,28,71,68,8.0,7,28,Semi-Urban,Software Engineer,25844,0 +58513,Male,49,High School,17,60,65,53,28,8.0,7,28,Urban,ML Engineer,131057,0 +58514,Female,49,Bachelors,9,77,75,37,27,7.0,1,87,Rural,HR Executive,65755,1 +58515,Other,31,Masters,19,40,84,35,94,4.0,4,5,Semi-Urban,HR Executive,125350,0 +58516,Female,45,Diploma,1,78,69,93,41,2.0,5,8,Urban,HR Executive,125523,1 +58517,Male,58,Bachelors,19,9,23,69,38,1.0,7,68,Rural,HR Executive,58510,0 +58518,Male,45,Masters,5,94,64,70,15,1.0,4,90,Rural,Manager,104566,1 +58519,Male,59,Bachelors,16,33,20,58,62,6.0,2,82,Urban,Software Engineer,69669,0 +58520,Female,37,Diploma,12,78,59,18,14,8.0,4,3,Rural,Software Engineer,20151,0 +58521,Male,50,Bachelors,9,97,57,24,23,3.0,3,39,Semi-Urban,ML Engineer,27797,0 +58522,Female,24,Bachelors,13,89,37,98,4,8.0,5,6,Urban,Data Analyst,39435,0 +58523,Male,56,Masters,8,35,20,36,38,6.0,3,66,Semi-Urban,Manager,122188,0 +58524,Female,52,Bachelors,15,16,77,78,79,5.0,1,88,Urban,ML Engineer,27404,1 +58525,Male,21,High School,19,92,41,16,20,6.0,1,15,Urban,Data Analyst,148030,0 +58526,Female,43,Diploma,0,82,9,76,1,8.0,4,82,Urban,ML Engineer,143488,1 +58527,Male,48,Masters,10,34,86,9,84,7.0,2,19,Urban,Manager,94035,0 +58528,Female,34,Bachelors,2,45,63,77,41,1.0,6,90,Semi-Urban,HR Executive,144600,1 +58529,Female,40,Bachelors,12,2,73,25,90,4.0,0,27,Semi-Urban,Data Analyst,109830,0 +58530,Female,41,Bachelors,2,59,41,77,8,9.0,2,70,Urban,Software Engineer,135169,1 +58531,Male,25,Bachelors,15,22,33,17,88,9.0,7,18,Urban,ML Engineer,44533,0 +58532,Female,45,High School,12,31,5,2,88,3.0,5,67,Urban,HR Executive,65894,0 +58533,Other,48,Diploma,11,0,28,77,56,0.0,0,45,Urban,Software Engineer,91944,0 +58534,Male,54,Masters,6,30,8,27,29,4.0,1,51,Rural,ML Engineer,50043,0 +58535,Male,36,Bachelors,0,28,30,15,24,0.0,3,88,Urban,ML Engineer,45588,0 +58536,Female,27,Bachelors,10,29,99,93,44,9.0,1,38,Urban,HR Executive,108953,1 +58537,Male,22,Masters,9,94,74,72,64,2.0,0,84,Semi-Urban,Data Analyst,32596,1 +58538,Male,21,Diploma,7,10,84,92,19,7.0,5,85,Rural,Data Analyst,94376,1 +58539,Male,41,Bachelors,12,68,31,57,93,5.0,0,44,Urban,Manager,61966,0 +58540,Male,42,Bachelors,2,67,95,76,9,6.0,7,13,Urban,Manager,20106,1 +58541,Male,26,High School,16,59,76,70,50,2.0,2,37,Urban,HR Executive,123670,1 +58542,Male,51,Bachelors,15,69,19,22,54,2.0,0,65,Urban,Data Analyst,98792,0 +58543,Female,26,PhD,10,67,68,38,95,9.0,2,81,Rural,Data Analyst,58704,1 +58544,Female,53,High School,5,8,69,40,71,7.0,7,27,Rural,Data Analyst,127831,0 +58545,Female,23,Bachelors,15,98,73,89,86,6.0,3,48,Urban,Software Engineer,55263,1 +58546,Female,23,Diploma,3,24,79,24,7,5.0,1,53,Urban,HR Executive,56668,0 +58547,Male,21,Diploma,11,87,59,95,60,0.0,3,51,Urban,Manager,92336,1 +58548,Male,26,Bachelors,9,7,69,12,81,0.0,3,3,Semi-Urban,ML Engineer,140061,0 +58549,Male,46,Bachelors,7,11,2,36,89,6.0,2,41,Urban,Data Analyst,90947,0 +58550,Female,32,Diploma,8,2,33,5,8,5.0,1,0,Urban,Software Engineer,54331,0 +58551,Male,38,Bachelors,10,10,72,78,15,7.0,5,1,Urban,Data Analyst,127569,0 +58552,Male,51,Diploma,13,21,81,37,17,2.0,3,40,Urban,Manager,74914,0 +58553,Male,21,Diploma,2,20,30,62,72,8.0,6,38,Urban,HR Executive,98485,0 +58554,Male,58,Masters,19,71,68,72,24,4.0,1,85,Semi-Urban,Data Analyst,41655,1 +58555,Male,46,High School,17,60,90,22,40,9.0,1,86,Semi-Urban,Software Engineer,53879,1 +58556,Female,59,Diploma,2,86,83,3,5,3.0,4,35,Rural,ML Engineer,22861,0 +58557,Male,49,Masters,0,44,2,17,98,7.0,7,59,Urban,Data Analyst,145230,0 +58558,Female,21,Bachelors,14,92,67,68,17,4.0,0,8,Rural,ML Engineer,25570,0 +58559,Male,34,Masters,0,69,16,9,39,1.0,2,80,Semi-Urban,Software Engineer,100062,0 +58560,Male,36,Bachelors,2,53,99,23,58,7.0,3,24,Semi-Urban,Data Analyst,125764,0 +58561,Female,34,Bachelors,0,27,70,87,52,9.0,5,54,Urban,Software Engineer,91947,0 +58562,Male,50,Bachelors,13,24,75,5,86,9.0,4,58,Rural,Manager,106934,0 +58563,Male,55,High School,0,95,54,93,63,5.0,7,17,Urban,ML Engineer,72963,1 +58564,Male,49,Bachelors,5,76,29,81,85,7.0,5,57,Semi-Urban,HR Executive,35224,1 +58565,Male,33,Masters,16,31,5,21,30,2.0,6,44,Semi-Urban,HR Executive,148437,0 +58566,Female,31,PhD,12,71,10,28,97,6.0,2,71,Urban,Data Analyst,78845,0 +58567,Male,29,High School,8,14,28,27,40,5.0,2,56,Urban,Data Analyst,85994,0 +58568,Female,59,Bachelors,8,26,77,88,61,6.0,1,88,Urban,Data Analyst,113109,1 +58569,Male,34,Bachelors,7,15,56,48,96,6.0,3,13,Urban,Data Analyst,123581,0 +58570,Male,59,Bachelors,0,49,3,66,22,8.0,5,81,Semi-Urban,Software Engineer,120202,0 +58571,Female,23,PhD,13,23,56,63,27,5.0,2,20,Rural,HR Executive,118296,0 +58572,Male,42,High School,1,18,80,56,3,4.0,0,13,Semi-Urban,HR Executive,50652,0 +58573,Male,31,Bachelors,3,3,44,38,33,6.0,5,5,Urban,Software Engineer,21467,0 +58574,Male,43,High School,16,24,57,18,56,5.0,4,87,Urban,Software Engineer,130296,0 +58575,Female,59,Masters,14,39,7,97,49,1.0,5,48,Rural,ML Engineer,127608,0 +58576,Female,42,Masters,12,53,23,63,96,5.0,5,11,Urban,Data Analyst,137592,0 +58577,Male,27,High School,5,4,49,85,95,5.0,5,36,Rural,Manager,43483,0 +58578,Male,42,PhD,18,83,19,73,61,5.0,0,93,Semi-Urban,HR Executive,69650,1 +58579,Female,58,Bachelors,10,87,91,1,59,1.0,4,37,Urban,Data Analyst,23937,0 +58580,Male,48,High School,16,44,65,66,67,1.0,7,33,Urban,Software Engineer,48574,0 +58581,Female,56,Diploma,10,84,96,97,6,7.0,5,5,Semi-Urban,Software Engineer,139761,1 +58582,Female,34,Bachelors,15,44,91,26,79,9.0,5,98,Urban,Manager,60285,1 +58583,Male,49,High School,11,26,0,22,56,8.0,6,29,Semi-Urban,Data Analyst,46842,0 +58584,Female,38,Bachelors,7,15,63,22,6,8.0,7,14,Semi-Urban,Data Analyst,70472,0 +58585,Male,51,High School,15,47,33,25,79,6.0,7,58,Semi-Urban,HR Executive,147554,0 +58586,Female,45,Bachelors,15,4,87,89,72,1.0,1,1,Rural,Software Engineer,62983,0 +58587,Male,50,High School,10,77,54,93,0,1.0,5,11,Urban,Software Engineer,135920,1 +58588,Male,43,High School,4,8,70,54,50,0.0,4,62,Semi-Urban,Software Engineer,96957,0 +58589,Female,26,Masters,7,39,82,6,4,0.0,2,56,Urban,Manager,105271,0 +58590,Male,51,Bachelors,9,44,34,91,51,8.0,3,74,Semi-Urban,ML Engineer,86148,1 +58591,Female,44,Bachelors,14,7,36,6,32,1.0,6,30,Semi-Urban,ML Engineer,40575,0 +58592,Female,53,Masters,14,76,62,49,27,3.0,0,39,Urban,Manager,117644,0 +58593,Female,51,Bachelors,8,58,27,43,15,9.0,0,82,Urban,ML Engineer,140564,0 +58594,Male,47,Bachelors,15,32,28,44,14,3.0,0,98,Urban,Software Engineer,38370,0 +58595,Female,27,Masters,3,56,9,44,19,6.0,5,53,Semi-Urban,Manager,137067,0 +58596,Male,30,Bachelors,6,96,12,11,75,8.0,0,95,Semi-Urban,Data Analyst,141269,0 +58597,Male,25,Bachelors,12,92,84,8,69,6.0,6,6,Rural,Software Engineer,118673,0 +58598,Female,50,Masters,0,64,44,88,64,9.0,7,79,Urban,HR Executive,42275,1 +58599,Female,41,High School,18,15,4,0,75,3.0,5,7,Urban,HR Executive,88227,0 +58600,Female,49,Masters,4,12,23,99,48,0.0,6,85,Rural,HR Executive,70481,0 +58601,Male,45,Bachelors,6,16,54,77,49,0.0,7,20,Semi-Urban,Data Analyst,139242,0 +58602,Female,49,Bachelors,19,8,18,90,93,5.0,2,43,Urban,Manager,75488,0 +58603,Other,24,Masters,17,63,23,21,43,7.0,1,70,Semi-Urban,HR Executive,128575,0 +58604,Male,48,Masters,9,52,31,9,53,1.0,6,7,Semi-Urban,Data Analyst,101576,0 +58605,Male,50,Bachelors,8,47,17,40,74,4.0,6,48,Urban,Software Engineer,45899,0 +58606,Male,51,Bachelors,3,34,76,1,53,1.0,3,50,Rural,Data Analyst,77205,0 +58607,Male,34,Masters,8,47,46,73,8,2.0,0,32,Semi-Urban,ML Engineer,75018,0 +58608,Male,31,Masters,13,82,63,35,57,0.0,5,14,Semi-Urban,Data Analyst,67735,0 +58609,Male,23,Bachelors,19,9,71,37,4,6.0,1,11,Urban,Data Analyst,39709,0 +58610,Female,42,Masters,0,59,27,17,35,6.0,3,36,Semi-Urban,Data Analyst,24527,0 +58611,Male,35,Masters,4,59,61,31,45,4.0,3,4,Urban,HR Executive,94980,0 +58612,Other,54,Diploma,13,64,10,43,27,6.0,1,1,Urban,Software Engineer,46889,0 +58613,Male,21,Bachelors,18,62,24,70,63,6.0,7,85,Urban,HR Executive,112483,1 +58614,Male,56,Diploma,19,0,58,3,57,3.0,0,67,Urban,Software Engineer,36036,0 +58615,Male,45,Bachelors,19,80,22,57,77,3.0,3,94,Urban,ML Engineer,143214,1 +58616,Female,56,Diploma,19,73,44,66,50,8.0,1,67,Urban,HR Executive,134772,1 +58617,Male,24,Diploma,5,55,89,54,3,7.0,7,5,Semi-Urban,HR Executive,118649,0 +58618,Male,57,Bachelors,12,0,46,74,38,3.0,3,12,Urban,Manager,69581,0 +58619,Female,38,PhD,0,92,56,55,89,7.0,0,97,Semi-Urban,Software Engineer,114176,1 +58620,Male,22,Bachelors,10,57,85,61,22,0.0,2,97,Urban,Manager,113907,1 +58621,Female,38,Bachelors,13,44,65,10,62,6.0,7,61,Urban,ML Engineer,130703,0 +58622,Male,59,Diploma,10,55,92,39,21,8.0,4,31,Urban,Manager,43365,0 +58623,Female,32,Bachelors,9,29,87,94,72,0.0,5,8,Rural,Data Analyst,59227,0 +58624,Male,27,PhD,9,18,86,29,42,3.0,7,17,Semi-Urban,Software Engineer,82017,0 +58625,Male,52,Bachelors,17,24,16,93,75,9.0,1,69,Urban,ML Engineer,147696,0 +58626,Male,36,Masters,9,29,68,15,40,8.0,6,62,Semi-Urban,HR Executive,64674,0 +58627,Male,46,Masters,8,12,48,60,26,0.0,4,5,Rural,Data Analyst,39521,0 +58628,Female,45,Diploma,15,4,34,4,19,4.0,4,69,Urban,Manager,51961,0 +58629,Female,38,PhD,17,49,68,73,76,2.0,3,61,Urban,Data Analyst,61356,1 +58630,Female,40,High School,0,15,46,36,63,1.0,2,5,Urban,ML Engineer,67143,0 +58631,Male,27,Masters,8,70,14,44,39,3.0,0,67,Rural,ML Engineer,59860,0 +58632,Female,50,High School,16,78,57,99,75,4.0,5,57,Urban,Software Engineer,135311,1 +58633,Male,56,Bachelors,17,88,56,46,69,8.0,1,98,Urban,Manager,59811,1 +58634,Male,42,Diploma,6,87,82,84,35,1.0,6,59,Semi-Urban,Software Engineer,102204,1 +58635,Male,56,Diploma,6,72,16,13,59,8.0,7,47,Rural,HR Executive,49995,0 +58636,Female,40,Bachelors,19,49,0,28,83,3.0,7,2,Urban,Manager,128704,0 +58637,Male,43,High School,1,9,47,29,17,7.0,6,63,Urban,Manager,50816,0 +58638,Male,29,High School,0,59,58,72,9,9.0,4,53,Urban,Data Analyst,45476,1 +58639,Female,35,Diploma,11,7,81,23,75,4.0,3,37,Urban,ML Engineer,25119,0 +58640,Male,43,Bachelors,13,28,26,54,15,5.0,4,43,Urban,Data Analyst,47938,0 +58641,Female,36,Diploma,16,88,96,21,92,7.0,5,68,Semi-Urban,Data Analyst,146966,1 +58642,Other,26,Bachelors,15,12,85,35,55,9.0,1,48,Semi-Urban,Software Engineer,69364,0 +58643,Male,21,Bachelors,15,10,11,52,74,0.0,7,13,Urban,Data Analyst,136251,0 +58644,Female,25,Diploma,13,89,62,42,57,5.0,1,5,Rural,Software Engineer,96383,0 +58645,Male,34,High School,0,3,36,88,40,3.0,0,69,Rural,Data Analyst,103522,0 +58646,Male,34,Masters,13,95,89,39,64,8.0,5,43,Semi-Urban,HR Executive,85087,1 +58647,Female,56,Masters,9,52,11,78,10,3.0,5,85,Rural,HR Executive,66745,0 +58648,Female,22,Diploma,2,30,18,5,24,4.0,3,57,Urban,Data Analyst,93246,0 +58649,Male,34,PhD,19,55,59,38,62,3.0,3,56,Rural,Software Engineer,75893,0 +58650,Male,43,Bachelors,9,50,75,85,1,1.0,1,39,Urban,ML Engineer,98297,1 +58651,Male,55,Masters,2,61,10,39,70,5.0,5,65,Semi-Urban,Manager,127087,0 +58652,Other,23,Masters,12,93,88,8,96,9.0,7,57,Urban,HR Executive,51114,1 +58653,Female,41,Masters,9,73,20,41,16,2.0,2,18,Urban,HR Executive,88414,0 +58654,Male,36,Bachelors,2,49,10,14,34,2.0,0,14,Rural,HR Executive,66197,0 +58655,Female,49,Bachelors,9,41,92,52,66,3.0,7,89,Urban,Software Engineer,78227,1 +58656,Female,47,Bachelors,17,1,6,75,94,6.0,0,20,Semi-Urban,ML Engineer,99902,0 +58657,Male,32,Diploma,18,99,81,10,59,6.0,0,75,Rural,HR Executive,101347,1 +58658,Male,30,Bachelors,19,74,70,72,67,2.0,4,59,Semi-Urban,Data Analyst,143841,1 +58659,Male,40,Bachelors,8,90,7,59,38,8.0,0,97,Urban,Manager,60527,1 +58660,Female,58,Diploma,1,45,22,83,34,1.0,5,95,Rural,Software Engineer,22277,1 +58661,Male,38,Diploma,11,51,97,13,11,6.0,1,5,Urban,Data Analyst,90694,0 +58662,Female,54,Bachelors,18,74,59,31,45,4.0,3,38,Semi-Urban,Software Engineer,81844,0 +58663,Female,47,Bachelors,0,93,28,75,38,1.0,3,86,Rural,Data Analyst,149490,1 +58664,Male,50,Masters,11,67,49,53,77,8.0,2,55,Semi-Urban,ML Engineer,22948,0 +58665,Female,57,Bachelors,2,59,12,89,27,4.0,2,27,Urban,Data Analyst,77648,0 +58666,Male,44,Masters,19,94,34,97,31,1.0,5,93,Semi-Urban,HR Executive,83257,1 +58667,Other,24,Masters,17,24,71,49,52,9.0,0,3,Urban,HR Executive,31709,0 +58668,Female,49,Diploma,2,73,82,57,30,6.0,6,13,Urban,Manager,124473,0 +58669,Female,39,Masters,3,44,48,57,80,7.0,2,71,Semi-Urban,Software Engineer,80051,0 +58670,Female,28,High School,10,26,19,2,76,5.0,2,38,Semi-Urban,Data Analyst,140027,0 +58671,Male,30,Diploma,16,80,1,79,28,6.0,4,12,Urban,Manager,121077,0 +58672,Male,46,Diploma,9,85,94,64,34,0.0,5,69,Urban,Software Engineer,147611,1 +58673,Female,45,Bachelors,1,35,97,92,71,9.0,1,91,Rural,ML Engineer,48993,1 +58674,Male,52,Masters,12,47,75,20,24,8.0,6,96,Urban,ML Engineer,62402,1 +58675,Female,56,Masters,4,27,15,92,15,8.0,2,45,Semi-Urban,HR Executive,33551,0 +58676,Female,58,Diploma,9,23,36,49,88,6.0,6,87,Urban,Manager,22530,0 +58677,Male,45,Diploma,0,68,26,8,61,0.0,7,39,Semi-Urban,Software Engineer,68875,0 +58678,Male,59,Bachelors,19,1,60,93,26,1.0,2,36,Rural,HR Executive,111294,0 +58679,Male,59,Bachelors,6,53,70,32,12,4.0,4,60,Urban,Manager,49170,0 +58680,Male,51,Masters,11,12,43,79,50,4.0,1,54,Rural,ML Engineer,73621,0 +58681,Male,39,Masters,9,25,31,6,64,1.0,7,30,Urban,Software Engineer,67149,0 +58682,Female,28,Bachelors,6,79,93,27,77,4.0,1,44,Urban,Software Engineer,90616,1 +58683,Male,27,Bachelors,18,45,49,84,58,9.0,1,29,Semi-Urban,ML Engineer,136970,0 +58684,Male,44,Masters,1,40,59,56,25,5.0,2,91,Urban,Software Engineer,131510,1 +58685,Male,57,Diploma,5,70,51,75,47,2.0,2,71,Urban,Manager,143819,1 +58686,Male,31,Masters,16,53,93,98,11,9.0,2,86,Urban,HR Executive,48962,1 +58687,Other,25,Bachelors,5,1,89,7,52,9.0,3,41,Semi-Urban,ML Engineer,142616,0 +58688,Male,23,Diploma,3,26,70,72,76,0.0,4,87,Rural,Software Engineer,124322,1 +58689,Male,28,Diploma,7,78,49,43,72,6.0,7,60,Semi-Urban,Data Analyst,29330,0 +58690,Female,22,Bachelors,1,29,71,62,33,5.0,6,49,Urban,HR Executive,50309,0 +58691,Male,44,Bachelors,9,42,7,96,67,8.0,4,86,Semi-Urban,Manager,142433,0 +58692,Male,59,Masters,5,95,19,51,85,4.0,5,93,Rural,Software Engineer,124726,1 +58693,Other,38,Bachelors,0,25,99,79,42,1.0,3,41,Urban,Software Engineer,74602,1 +58694,Female,38,Bachelors,6,85,8,50,34,7.0,6,64,Urban,Data Analyst,32802,0 +58695,Male,27,Masters,11,12,47,22,88,7.0,5,97,Rural,Software Engineer,109396,0 +58696,Female,50,Bachelors,9,17,77,46,64,8.0,1,81,Urban,Data Analyst,82853,0 +58697,Male,42,Diploma,12,84,77,10,22,3.0,3,21,Urban,HR Executive,42820,0 +58698,Male,46,Diploma,17,50,92,59,74,3.0,6,87,Semi-Urban,ML Engineer,91657,1 +58699,Female,59,Bachelors,14,65,5,34,46,0.0,6,21,Urban,Software Engineer,68709,0 +58700,Other,22,Bachelors,15,84,11,91,94,1.0,4,36,Urban,ML Engineer,39074,0 +58701,Male,34,Diploma,11,62,57,8,87,9.0,5,16,Semi-Urban,Data Analyst,72104,0 +58702,Male,52,Bachelors,9,67,64,55,70,1.0,4,19,Semi-Urban,Data Analyst,142115,0 +58703,Male,29,Bachelors,16,42,44,84,3,0.0,6,49,Urban,HR Executive,93692,0 +58704,Female,55,Diploma,18,89,56,87,33,4.0,5,63,Urban,ML Engineer,60651,1 +58705,Female,42,Bachelors,17,96,54,31,1,0.0,7,41,Urban,HR Executive,96317,0 +58706,Female,31,Bachelors,15,46,32,72,63,7.0,6,1,Rural,ML Engineer,21191,0 +58707,Male,41,High School,19,64,72,6,82,5.0,5,9,Semi-Urban,Manager,47018,0 +58708,Female,49,Masters,13,53,63,91,42,0.0,5,75,Semi-Urban,HR Executive,39212,1 +58709,Female,32,Masters,17,57,43,81,8,4.0,2,75,Urban,ML Engineer,94423,1 +58710,Male,51,Masters,10,79,99,48,57,9.0,4,59,Urban,Software Engineer,132650,1 +58711,Male,35,Bachelors,1,18,16,58,38,6.0,6,89,Semi-Urban,ML Engineer,129012,0 +58712,Male,27,Masters,15,33,5,29,92,6.0,0,19,Urban,Data Analyst,87828,0 +58713,Male,52,Bachelors,9,95,89,80,63,8.0,4,55,Urban,HR Executive,55420,1 +58714,Male,46,Bachelors,0,72,71,38,81,4.0,6,5,Rural,ML Engineer,72794,0 +58715,Male,52,Bachelors,5,39,25,20,45,6.0,3,24,Urban,Software Engineer,110338,0 +58716,Male,30,Bachelors,14,36,18,91,61,3.0,2,74,Urban,Manager,34039,0 +58717,Female,42,Diploma,12,73,69,44,85,2.0,6,9,Semi-Urban,HR Executive,44931,0 +58718,Male,38,Diploma,5,39,91,63,26,3.0,6,61,Semi-Urban,Data Analyst,91174,1 +58719,Other,57,Diploma,8,61,32,34,1,9.0,7,46,Urban,Data Analyst,37541,0 +58720,Female,37,High School,10,45,34,16,75,8.0,5,98,Semi-Urban,Manager,70727,0 +58721,Male,32,Bachelors,1,56,6,30,51,1.0,2,64,Rural,Manager,90059,0 +58722,Male,42,Bachelors,1,77,43,83,90,1.0,7,54,Rural,HR Executive,97399,1 +58723,Female,24,Diploma,4,4,52,99,56,5.0,7,74,Urban,ML Engineer,104688,0 +58724,Male,23,Bachelors,12,9,93,7,89,8.0,0,49,Urban,Software Engineer,42122,0 +58725,Female,54,Diploma,11,54,86,92,67,1.0,0,90,Urban,Manager,135823,1 +58726,Male,37,Diploma,4,29,66,44,51,9.0,0,39,Urban,Software Engineer,148094,0 +58727,Male,26,Bachelors,8,99,83,45,75,3.0,0,24,Urban,ML Engineer,81184,1 +58728,Male,50,High School,4,59,50,73,13,1.0,3,86,Urban,HR Executive,92067,1 +58729,Female,57,Bachelors,5,78,15,12,70,7.0,1,13,Semi-Urban,ML Engineer,34892,0 +58730,Female,21,Bachelors,16,53,21,9,14,8.0,1,10,Urban,HR Executive,30129,0 +58731,Male,29,Bachelors,16,10,71,8,54,0.0,6,75,Semi-Urban,ML Engineer,67542,0 +58732,Male,58,Bachelors,6,45,39,15,0,9.0,0,56,Urban,HR Executive,122029,0 +58733,Male,48,Bachelors,14,31,28,36,92,5.0,6,6,Urban,ML Engineer,28608,0 +58734,Male,24,Diploma,3,82,21,59,39,1.0,5,60,Urban,Manager,116967,0 +58735,Male,51,Bachelors,15,90,51,60,9,2.0,3,44,Semi-Urban,Manager,121013,1 +58736,Male,51,Bachelors,2,61,6,58,52,9.0,7,6,Urban,Data Analyst,103687,0 +58737,Male,49,Diploma,8,81,76,49,6,8.0,6,55,Urban,Data Analyst,140607,1 +58738,Male,44,Bachelors,19,83,54,54,88,5.0,4,46,Urban,Data Analyst,127355,1 +58739,Female,36,Bachelors,10,45,23,23,68,0.0,2,73,Urban,Manager,26853,0 +58740,Male,45,Diploma,0,78,63,96,30,9.0,3,31,Rural,Software Engineer,52314,1 +58741,Female,57,Diploma,8,71,87,72,7,0.0,5,29,Urban,ML Engineer,42217,1 +58742,Male,28,Masters,17,97,53,42,73,5.0,6,95,Urban,Data Analyst,68276,1 +58743,Female,33,Bachelors,18,35,35,40,9,1.0,0,96,Urban,HR Executive,105687,0 +58744,Male,47,Bachelors,9,20,99,9,40,4.0,7,30,Semi-Urban,Data Analyst,76196,0 +58745,Female,31,Bachelors,9,29,31,26,92,1.0,2,66,Rural,ML Engineer,119838,0 +58746,Female,52,Diploma,3,56,42,86,15,0.0,5,54,Urban,ML Engineer,107586,0 +58747,Female,50,Bachelors,5,57,72,84,13,0.0,0,39,Rural,ML Engineer,118973,1 +58748,Female,22,Masters,18,9,48,88,0,8.0,0,87,Urban,ML Engineer,22282,0 +58749,Female,30,Masters,8,89,20,53,33,7.0,0,84,Semi-Urban,ML Engineer,125635,1 +58750,Male,52,High School,0,78,10,54,86,0.0,3,9,Urban,Manager,43268,0 +58751,Other,33,Bachelors,8,22,89,73,74,2.0,4,96,Urban,Manager,69089,1 +58752,Male,55,High School,17,64,40,6,16,6.0,1,52,Semi-Urban,ML Engineer,54155,0 +58753,Male,30,Diploma,1,49,78,70,99,6.0,6,22,Urban,Manager,109552,0 +58754,Other,58,PhD,13,87,74,27,41,6.0,4,86,Urban,Data Analyst,26681,1 +58755,Male,40,Bachelors,16,7,11,13,94,6.0,2,43,Urban,ML Engineer,24056,0 +58756,Male,23,Bachelors,1,68,48,86,77,5.0,0,16,Urban,Software Engineer,91472,0 +58757,Other,25,High School,19,87,57,79,15,5.0,0,93,Semi-Urban,ML Engineer,55732,1 +58758,Male,48,High School,15,5,59,14,43,4.0,1,59,Urban,Software Engineer,65516,0 +58759,Male,57,Bachelors,14,52,76,54,81,2.0,5,94,Urban,HR Executive,95003,1 +58760,Female,50,Bachelors,10,33,3,77,14,2.0,5,53,Rural,ML Engineer,58727,0 +58761,Female,44,Masters,16,53,28,88,13,8.0,0,54,Urban,Manager,89265,0 +58762,Female,37,Bachelors,6,40,98,76,7,1.0,2,37,Semi-Urban,Software Engineer,148664,1 +58763,Female,45,Masters,18,65,8,34,58,1.0,2,45,Semi-Urban,Data Analyst,36056,0 +58764,Male,52,Diploma,17,74,46,54,14,5.0,2,10,Urban,Manager,30553,0 +58765,Male,32,Masters,16,21,63,9,57,1.0,4,67,Semi-Urban,ML Engineer,92035,0 +58766,Female,45,Masters,3,57,46,92,40,9.0,3,57,Rural,Software Engineer,63131,1 +58767,Female,44,Diploma,10,53,71,45,40,6.0,0,97,Semi-Urban,Data Analyst,102154,1 +58768,Male,33,Bachelors,16,7,80,6,89,7.0,0,27,Semi-Urban,ML Engineer,28796,0 +58769,Male,44,Masters,2,20,24,62,40,3.0,7,34,Rural,Manager,37737,0 +58770,Male,41,Bachelors,1,73,86,36,7,2.0,7,20,Semi-Urban,Software Engineer,93712,0 +58771,Female,50,Masters,16,80,95,13,93,3.0,2,35,Urban,Software Engineer,110117,0 +58772,Female,45,Bachelors,5,95,94,18,21,6.0,3,96,Semi-Urban,HR Executive,33015,1 +58773,Male,45,High School,18,60,68,39,23,7.0,1,24,Urban,Data Analyst,124582,0 +58774,Male,34,Bachelors,4,62,96,45,37,2.0,3,83,Urban,ML Engineer,59331,1 +58775,Male,21,Bachelors,13,60,97,70,0,8.0,5,78,Urban,Manager,117795,1 +58776,Other,32,High School,14,93,51,74,40,7.0,4,55,Urban,Software Engineer,142974,1 +58777,Female,42,Diploma,3,17,61,20,78,9.0,6,69,Urban,Software Engineer,86242,0 +58778,Female,53,Bachelors,1,57,4,55,80,2.0,2,10,Urban,Software Engineer,32180,0 +58779,Male,31,Bachelors,10,26,95,13,47,6.0,4,86,Semi-Urban,Data Analyst,146424,0 +58780,Male,42,Bachelors,2,24,87,97,63,6.0,1,96,Urban,Data Analyst,64660,1 +58781,Male,25,Masters,6,40,38,0,92,0.0,2,11,Urban,Software Engineer,128506,0 +58782,Other,24,Diploma,13,61,57,70,53,2.0,0,72,Urban,Manager,119591,1 +58783,Male,32,Diploma,6,44,1,1,63,1.0,2,69,Rural,HR Executive,24782,0 +58784,Female,56,Bachelors,14,87,56,74,58,2.0,1,19,Urban,Software Engineer,118739,0 +58785,Male,42,Bachelors,0,86,28,49,64,0.0,0,1,Urban,HR Executive,136288,0 +58786,Male,30,Bachelors,8,44,49,97,39,2.0,4,70,Urban,Manager,96856,1 +58787,Female,37,Masters,13,37,75,85,67,8.0,2,46,Urban,Software Engineer,60841,1 +58788,Female,27,Diploma,11,52,80,17,5,7.0,2,92,Semi-Urban,ML Engineer,135535,1 +58789,Female,37,Diploma,8,76,70,97,1,7.0,0,89,Semi-Urban,ML Engineer,42525,1 +58790,Female,47,Bachelors,8,99,75,9,59,8.0,5,81,Semi-Urban,Manager,61399,1 +58791,Male,41,PhD,17,71,77,59,98,8.0,6,99,Urban,Manager,133820,1 +58792,Male,39,Diploma,9,19,78,39,53,7.0,4,34,Rural,Manager,138913,0 +58793,Female,21,PhD,14,38,2,83,61,5.0,3,8,Semi-Urban,HR Executive,124571,0 +58794,Male,39,Bachelors,5,1,96,38,10,0.0,1,97,Urban,Software Engineer,48354,0 +58795,Male,51,Masters,7,77,31,85,11,8.0,5,74,Urban,ML Engineer,74501,1 +58796,Female,47,Bachelors,9,22,60,40,5,9.0,6,56,Urban,Data Analyst,106027,0 +58797,Female,41,High School,12,90,3,73,53,4.0,4,4,Urban,ML Engineer,122478,0 +58798,Female,36,PhD,19,18,85,66,4,4.0,4,78,Urban,Manager,139617,1 +58799,Male,39,Bachelors,1,68,71,47,15,0.0,4,83,Urban,HR Executive,32405,1 +58800,Female,53,Bachelors,1,88,69,85,72,6.0,3,19,Urban,ML Engineer,104749,1 +58801,Female,54,Bachelors,0,40,41,77,13,2.0,3,83,Rural,ML Engineer,22684,1 +58802,Female,38,Bachelors,18,82,12,89,58,8.0,5,29,Urban,HR Executive,115665,0 +58803,Male,38,Diploma,18,95,22,20,49,2.0,3,5,Urban,HR Executive,112876,0 +58804,Male,21,Diploma,14,6,60,71,81,2.0,1,23,Urban,HR Executive,89297,0 +58805,Female,49,High School,12,78,46,24,81,4.0,0,11,Rural,Software Engineer,149469,0 +58806,Female,37,Masters,6,39,60,68,1,8.0,5,53,Rural,HR Executive,55295,0 +58807,Male,55,Diploma,11,21,44,5,46,4.0,1,94,Semi-Urban,Data Analyst,117908,0 +58808,Male,46,Bachelors,2,76,82,14,77,0.0,6,70,Urban,Manager,81414,1 +58809,Female,34,Bachelors,9,69,6,32,11,6.0,3,66,Urban,Manager,108330,0 +58810,Female,43,Masters,13,5,57,39,46,0.0,0,33,Semi-Urban,Manager,138507,0 +58811,Male,33,Masters,12,57,69,71,24,2.0,7,41,Semi-Urban,HR Executive,37977,1 +58812,Male,51,Bachelors,15,73,16,12,89,0.0,4,6,Urban,HR Executive,135225,0 +58813,Female,29,Masters,6,15,3,18,49,4.0,6,65,Urban,Software Engineer,34621,0 +58814,Male,49,Bachelors,10,40,35,92,49,0.0,0,44,Urban,Data Analyst,117515,0 +58815,Male,55,High School,8,2,39,52,37,9.0,6,16,Urban,ML Engineer,145058,0 +58816,Male,36,Masters,15,98,78,54,21,2.0,1,30,Urban,ML Engineer,148343,1 +58817,Male,31,Bachelors,2,13,8,67,95,1.0,5,6,Urban,Manager,149110,0 +58818,Female,26,Bachelors,7,91,70,45,9,3.0,5,80,Urban,Software Engineer,116921,1 +58819,Female,23,Diploma,2,68,87,50,91,9.0,0,66,Urban,ML Engineer,76903,1 +58820,Female,55,Bachelors,11,50,53,76,17,7.0,5,20,Semi-Urban,Manager,101894,0 +58821,Female,53,Bachelors,14,18,6,46,40,0.0,0,91,Semi-Urban,Manager,148580,0 +58822,Male,44,Bachelors,16,81,17,63,93,2.0,0,49,Semi-Urban,HR Executive,138264,0 +58823,Male,44,High School,17,40,24,19,51,1.0,2,90,Urban,Manager,147945,0 +58824,Male,41,Masters,1,7,22,94,99,3.0,7,74,Semi-Urban,HR Executive,97260,0 +58825,Female,35,Diploma,10,15,8,55,76,8.0,1,43,Urban,Data Analyst,149141,0 +58826,Male,56,Masters,15,94,80,75,82,8.0,2,76,Urban,Software Engineer,32007,1 +58827,Male,42,Masters,8,34,72,26,5,6.0,3,63,Urban,Software Engineer,89901,0 +58828,Male,57,Bachelors,2,35,72,25,86,9.0,7,4,Semi-Urban,Software Engineer,22114,0 +58829,Female,58,Diploma,4,14,78,87,87,1.0,6,15,Urban,HR Executive,118810,0 +58830,Female,55,Bachelors,1,88,76,32,3,6.0,4,51,Urban,HR Executive,120812,1 +58831,Male,40,Diploma,18,93,34,36,92,6.0,2,71,Urban,ML Engineer,97583,0 +58832,Other,29,High School,14,86,10,66,77,4.0,3,85,Urban,ML Engineer,50881,1 +58833,Female,22,Diploma,18,58,27,14,8,2.0,6,68,Urban,Manager,62733,0 +58834,Male,23,Diploma,3,26,4,18,75,6.0,3,9,Urban,Manager,130527,0 +58835,Male,53,Masters,9,32,52,65,23,0.0,2,94,Urban,Data Analyst,93358,1 +58836,Male,59,Diploma,13,77,62,84,81,2.0,0,59,Rural,Software Engineer,72046,1 +58837,Female,51,Masters,19,82,1,2,87,8.0,5,1,Semi-Urban,ML Engineer,38961,0 +58838,Male,54,Bachelors,6,75,94,96,84,0.0,4,1,Urban,Software Engineer,64517,1 +58839,Male,52,Bachelors,3,55,74,65,38,5.0,0,91,Urban,Software Engineer,58031,1 +58840,Female,54,Bachelors,17,17,55,46,87,0.0,2,22,Urban,ML Engineer,54290,0 +58841,Female,23,PhD,15,31,90,59,26,6.0,3,96,Urban,Manager,68180,1 +58842,Female,44,Diploma,3,99,30,3,1,4.0,2,92,Urban,ML Engineer,52763,0 +58843,Male,39,Masters,16,3,76,65,87,0.0,6,84,Urban,Data Analyst,107523,0 +58844,Female,44,Diploma,18,57,20,39,19,8.0,0,80,Urban,Software Engineer,25734,0 +58845,Female,36,High School,17,21,75,10,4,6.0,7,67,Semi-Urban,Software Engineer,26409,0 +58846,Female,49,Bachelors,15,75,29,75,78,2.0,2,57,Urban,Software Engineer,63763,0 +58847,Female,51,Masters,10,65,11,35,11,9.0,2,21,Rural,Manager,85062,0 +58848,Female,38,High School,5,15,3,14,7,0.0,3,63,Urban,Software Engineer,93113,0 +58849,Female,22,Bachelors,18,59,23,31,90,8.0,4,97,Urban,HR Executive,129935,0 +58850,Male,56,Masters,19,83,48,57,73,4.0,2,16,Urban,Software Engineer,131938,0 +58851,Male,29,Bachelors,6,14,56,74,19,5.0,6,36,Urban,Manager,100884,0 +58852,Male,49,High School,0,73,64,55,82,0.0,0,15,Rural,HR Executive,74698,0 +58853,Female,44,Bachelors,7,42,64,40,20,3.0,6,24,Urban,Manager,50622,0 +58854,Male,47,Bachelors,9,35,71,80,86,9.0,1,46,Urban,HR Executive,121467,0 +58855,Male,33,Diploma,15,24,63,82,93,5.0,1,65,Rural,Manager,52489,0 +58856,Male,42,Bachelors,5,84,48,60,36,2.0,2,56,Urban,Data Analyst,111623,1 +58857,Other,32,Bachelors,17,94,73,13,60,6.0,5,42,Rural,Manager,95521,0 +58858,Male,57,High School,6,79,25,81,8,7.0,1,80,Urban,HR Executive,78912,1 +58859,Male,22,Diploma,6,49,18,24,40,3.0,0,92,Rural,HR Executive,136127,0 +58860,Male,34,Bachelors,16,29,77,11,15,0.0,7,87,Urban,ML Engineer,30454,0 +58861,Male,24,Masters,2,47,49,55,66,0.0,5,8,Urban,Data Analyst,26199,0 +58862,Female,58,High School,4,40,42,29,7,3.0,6,32,Urban,Data Analyst,110382,0 +58863,Other,45,Diploma,6,30,99,48,44,9.0,2,81,Urban,Software Engineer,25269,1 +58864,Male,31,High School,9,4,31,30,41,4.0,5,96,Semi-Urban,ML Engineer,50379,0 +58865,Female,45,Bachelors,11,39,73,70,43,6.0,4,89,Urban,Software Engineer,128834,1 +58866,Female,47,Bachelors,4,5,27,44,97,7.0,0,13,Urban,Data Analyst,39943,0 +58867,Male,22,Diploma,7,60,4,89,79,3.0,7,45,Rural,HR Executive,138960,0 +58868,Male,56,Bachelors,4,9,89,99,87,2.0,2,47,Urban,HR Executive,38143,1 +58869,Female,28,Bachelors,1,73,90,20,22,5.0,6,70,Urban,HR Executive,55706,1 +58870,Female,24,Bachelors,16,48,4,53,42,4.0,5,39,Urban,ML Engineer,31256,0 +58871,Female,40,Bachelors,18,5,76,21,85,7.0,4,0,Semi-Urban,Software Engineer,96684,0 +58872,Male,41,Bachelors,2,22,94,41,62,4.0,3,24,Urban,Manager,106543,0 +58873,Female,38,Diploma,12,39,53,84,15,7.0,7,50,Urban,HR Executive,57887,0 +58874,Female,54,Bachelors,7,79,93,73,2,3.0,1,24,Urban,ML Engineer,100306,1 +58875,Female,37,Diploma,18,92,61,42,8,6.0,2,43,Urban,HR Executive,106253,0 +58876,Male,33,Diploma,14,50,36,5,26,6.0,0,64,Semi-Urban,Data Analyst,60171,0 +58877,Male,30,Bachelors,5,70,24,70,22,7.0,2,84,Urban,Software Engineer,25140,1 +58878,Male,44,Masters,11,60,86,98,12,9.0,6,74,Semi-Urban,ML Engineer,78974,1 +58879,Female,26,Diploma,18,39,89,28,27,1.0,7,56,Urban,ML Engineer,73649,0 +58880,Male,50,Masters,5,92,59,25,64,4.0,2,84,Rural,Manager,54329,1 +58881,Male,48,Bachelors,5,69,65,57,37,8.0,1,52,Semi-Urban,Data Analyst,88697,1 +58882,Male,31,Diploma,3,25,67,77,35,3.0,4,37,Urban,Software Engineer,51529,0 +58883,Male,53,Bachelors,7,27,36,88,19,6.0,6,76,Rural,ML Engineer,31011,0 +58884,Male,53,Masters,19,92,45,19,14,8.0,6,25,Rural,ML Engineer,87477,0 +58885,Male,59,Masters,7,56,57,32,72,9.0,1,98,Urban,HR Executive,149927,1 +58886,Male,27,Bachelors,4,86,0,46,48,8.0,2,66,Urban,ML Engineer,81336,0 +58887,Male,26,Bachelors,17,51,37,41,72,2.0,1,28,Urban,Data Analyst,99880,0 +58888,Male,43,Bachelors,4,5,84,19,94,6.0,4,90,Urban,HR Executive,131327,0 +58889,Male,22,Bachelors,1,56,77,60,73,9.0,6,11,Rural,Data Analyst,28655,0 +58890,Female,28,Masters,10,11,54,9,81,6.0,6,49,Urban,ML Engineer,29969,0 +58891,Male,41,Masters,0,38,9,32,39,4.0,6,56,Semi-Urban,HR Executive,75732,0 +58892,Male,38,Masters,18,54,25,90,76,8.0,5,89,Rural,Manager,140689,1 +58893,Female,50,High School,1,44,73,59,0,9.0,7,77,Semi-Urban,Data Analyst,112958,1 +58894,Male,28,High School,19,56,77,28,92,0.0,6,90,Urban,Data Analyst,46219,1 +58895,Female,53,Diploma,5,86,97,42,64,6.0,1,21,Semi-Urban,ML Engineer,50830,1 +58896,Male,43,High School,13,91,99,87,80,2.0,5,70,Semi-Urban,Manager,122916,1 +58897,Other,38,Diploma,6,13,64,88,43,0.0,2,81,Urban,Software Engineer,62166,1 +58898,Male,26,Diploma,3,73,85,76,34,9.0,4,35,Urban,Data Analyst,24383,1 +58899,Male,47,Masters,18,61,22,96,60,9.0,7,71,Rural,HR Executive,83958,1 +58900,Male,47,Bachelors,10,27,78,0,74,6.0,7,40,Rural,Data Analyst,110698,0 +58901,Male,28,PhD,13,87,52,8,40,5.0,7,80,Urban,Manager,23966,0 +58902,Male,58,High School,10,66,98,43,55,4.0,4,51,Urban,Data Analyst,148681,1 +58903,Male,22,Masters,16,74,6,23,36,8.0,3,87,Urban,Data Analyst,149700,0 +58904,Male,56,Bachelors,4,65,14,99,90,9.0,2,90,Semi-Urban,Data Analyst,145188,1 +58905,Female,44,High School,16,14,65,97,58,8.0,4,31,Rural,HR Executive,72868,0 +58906,Male,25,Bachelors,2,2,41,26,8,6.0,4,15,Semi-Urban,ML Engineer,55377,0 +58907,Male,46,Diploma,1,76,26,65,18,3.0,5,51,Semi-Urban,Software Engineer,141631,0 +58908,Male,45,Masters,12,52,12,88,3,5.0,0,47,Urban,Software Engineer,92054,0 +58909,Female,23,Diploma,14,79,90,77,47,4.0,5,69,Semi-Urban,Data Analyst,144352,1 +58910,Male,23,Masters,5,46,71,62,61,6.0,6,35,Urban,Manager,25484,0 +58911,Male,38,High School,10,59,2,41,42,6.0,4,52,Semi-Urban,Manager,84172,0 +58912,Male,33,Diploma,11,92,42,10,88,2.0,6,98,Urban,Software Engineer,52445,1 +58913,Other,41,Diploma,18,28,11,99,29,9.0,1,50,Urban,HR Executive,33141,0 +58914,Female,46,Masters,16,53,39,2,77,4.0,6,33,Semi-Urban,Manager,29274,0 +58915,Male,37,Diploma,2,88,77,92,90,9.0,2,42,Urban,ML Engineer,74199,1 +58916,Male,27,Masters,14,15,93,63,58,7.0,4,48,Urban,ML Engineer,126553,0 +58917,Female,48,Diploma,1,11,15,46,96,9.0,7,78,Semi-Urban,Data Analyst,45327,0 +58918,Male,29,Bachelors,3,58,15,9,26,0.0,3,7,Urban,Manager,147909,0 +58919,Male,51,Diploma,10,84,22,96,35,3.0,4,65,Urban,ML Engineer,51214,1 +58920,Male,47,Masters,3,50,33,93,66,9.0,0,40,Urban,Software Engineer,102679,0 +58921,Male,59,Bachelors,6,70,54,71,28,2.0,3,9,Rural,Software Engineer,115053,0 +58922,Male,38,Diploma,19,54,39,36,83,9.0,0,93,Urban,ML Engineer,47811,0 +58923,Female,27,Masters,2,72,52,83,57,6.0,2,28,Semi-Urban,ML Engineer,95421,0 +58924,Female,43,High School,8,86,85,21,81,9.0,3,78,Urban,Data Analyst,56205,1 +58925,Male,57,Bachelors,1,19,30,15,15,8.0,7,80,Urban,Data Analyst,110380,0 +58926,Female,25,Masters,12,35,63,7,7,3.0,3,50,Semi-Urban,Software Engineer,28114,0 +58927,Male,21,Bachelors,11,97,98,20,61,1.0,6,47,Semi-Urban,Software Engineer,40230,1 +58928,Male,30,Masters,8,57,72,56,50,4.0,0,82,Urban,Software Engineer,20626,1 +58929,Female,31,High School,7,7,24,97,40,3.0,5,76,Semi-Urban,Software Engineer,96692,0 +58930,Female,47,Masters,14,5,40,17,99,6.0,4,80,Rural,Manager,141138,0 +58931,Female,35,Diploma,18,13,49,97,20,8.0,1,52,Rural,ML Engineer,124731,0 +58932,Female,21,Bachelors,19,54,29,23,0,6.0,2,49,Semi-Urban,Manager,85099,0 +58933,Male,58,Bachelors,12,22,95,41,36,9.0,1,62,Urban,Software Engineer,84503,0 +58934,Male,42,Bachelors,0,76,85,43,55,7.0,1,9,Semi-Urban,Data Analyst,87097,0 +58935,Female,35,High School,9,50,67,55,79,6.0,6,31,Urban,Data Analyst,114072,0 +58936,Male,51,Bachelors,12,81,86,53,41,3.0,7,39,Semi-Urban,Manager,72741,1 +58937,Female,42,Diploma,18,2,72,27,57,3.0,0,5,Rural,HR Executive,51826,0 +58938,Male,37,Bachelors,9,45,16,32,54,4.0,1,88,Urban,HR Executive,31195,0 +58939,Female,23,Diploma,19,99,55,43,87,8.0,1,30,Urban,Manager,79295,0 +58940,Male,33,Masters,0,62,23,34,37,3.0,1,90,Rural,Data Analyst,41589,0 +58941,Female,41,Diploma,17,7,26,67,34,8.0,6,4,Urban,Data Analyst,138459,0 +58942,Female,53,Bachelors,19,29,20,10,27,0.0,4,16,Semi-Urban,Data Analyst,75053,0 +58943,Male,31,Bachelors,0,31,63,84,40,7.0,2,38,Urban,Manager,113221,0 +58944,Male,51,Bachelors,18,62,50,84,59,5.0,0,95,Urban,Software Engineer,38510,1 +58945,Female,47,Bachelors,9,61,2,35,48,9.0,3,24,Urban,ML Engineer,77761,0 +58946,Male,53,Bachelors,11,71,0,25,4,8.0,7,16,Rural,Manager,70221,0 +58947,Male,53,Diploma,5,75,96,30,7,7.0,2,45,Urban,HR Executive,52566,1 +58948,Male,44,Diploma,16,4,83,76,88,1.0,7,64,Urban,HR Executive,27070,0 +58949,Male,43,High School,0,9,60,11,0,0.0,1,79,Rural,Software Engineer,67353,0 +58950,Male,55,Bachelors,16,98,63,67,11,2.0,7,64,Urban,Manager,113448,1 +58951,Female,46,Bachelors,7,36,38,31,49,7.0,4,47,Semi-Urban,Manager,92719,0 +58952,Male,34,PhD,12,8,41,87,50,3.0,5,30,Urban,Data Analyst,149678,0 +58953,Male,40,Bachelors,2,57,47,61,95,7.0,2,48,Semi-Urban,Data Analyst,33335,0 +58954,Male,43,Diploma,10,90,1,84,56,0.0,1,0,Semi-Urban,Data Analyst,149635,0 +58955,Male,55,Diploma,0,0,29,56,95,7.0,2,66,Urban,Data Analyst,143287,0 +58956,Female,25,Bachelors,9,2,64,1,3,1.0,5,93,Rural,HR Executive,140072,0 +58957,Male,55,Bachelors,0,27,22,43,66,7.0,1,90,Urban,HR Executive,105503,0 +58958,Male,35,Diploma,16,33,2,20,39,0.0,5,70,Urban,Software Engineer,50339,0 +58959,Male,31,High School,2,38,38,56,35,4.0,4,5,Urban,HR Executive,131209,0 +58960,Female,58,Diploma,14,58,15,15,35,5.0,6,52,Semi-Urban,Software Engineer,47567,0 +58961,Other,30,PhD,4,31,77,7,40,6.0,6,45,Rural,ML Engineer,44924,0 +58962,Male,32,Masters,13,12,6,22,39,9.0,4,35,Urban,ML Engineer,123710,0 +58963,Female,23,Bachelors,6,9,33,19,11,3.0,7,84,Rural,Data Analyst,39321,0 +58964,Male,44,Bachelors,4,70,93,12,57,2.0,6,87,Urban,Software Engineer,44161,1 +58965,Male,47,Masters,3,67,53,20,41,8.0,3,41,Urban,Software Engineer,50874,0 +58966,Male,50,High School,8,81,90,9,20,5.0,6,40,Urban,HR Executive,140080,0 +58967,Female,25,Diploma,9,60,6,73,94,3.0,7,43,Urban,HR Executive,22727,0 +58968,Female,46,High School,4,93,68,98,97,9.0,0,21,Rural,ML Engineer,117922,1 +58969,Male,23,Masters,12,62,72,94,68,3.0,7,8,Urban,ML Engineer,149219,1 +58970,Female,31,Masters,3,29,9,10,19,9.0,4,7,Rural,Software Engineer,68612,0 +58971,Male,26,Bachelors,9,21,46,90,38,0.0,3,10,Urban,HR Executive,90424,0 +58972,Male,29,Bachelors,18,42,81,20,42,0.0,7,70,Semi-Urban,Software Engineer,105060,0 +58973,Female,28,Diploma,12,34,92,35,37,0.0,4,74,Semi-Urban,HR Executive,74963,0 +58974,Other,44,PhD,19,54,80,58,12,7.0,0,69,Rural,Software Engineer,58281,1 +58975,Male,39,Bachelors,17,36,18,85,97,6.0,2,60,Urban,ML Engineer,102926,0 +58976,Female,44,Diploma,16,36,70,63,94,7.0,3,63,Semi-Urban,Software Engineer,126737,0 +58977,Female,54,High School,18,77,60,9,56,4.0,0,32,Semi-Urban,Manager,131641,0 +58978,Male,41,Bachelors,8,76,72,43,39,0.0,3,77,Rural,Software Engineer,113427,1 +58979,Male,33,Bachelors,8,86,56,35,61,5.0,7,3,Semi-Urban,HR Executive,33290,0 +58980,Male,46,High School,6,90,14,16,87,9.0,3,38,Rural,Data Analyst,37700,0 +58981,Female,58,High School,13,39,54,46,17,4.0,3,22,Rural,Software Engineer,20184,0 +58982,Male,59,Diploma,14,63,34,71,95,4.0,5,10,Urban,HR Executive,70874,0 +58983,Male,29,PhD,16,79,56,41,48,1.0,2,47,Urban,Data Analyst,107940,0 +58984,Male,34,Masters,3,81,77,28,13,2.0,1,98,Urban,ML Engineer,111333,1 +58985,Male,45,High School,2,6,92,69,47,2.0,6,76,Urban,Software Engineer,63177,1 +58986,Female,46,High School,6,88,41,7,11,9.0,7,85,Urban,Data Analyst,131251,0 +58987,Female,54,High School,3,61,91,68,21,2.0,4,46,Semi-Urban,Software Engineer,61137,1 +58988,Male,26,Diploma,13,47,91,63,92,6.0,0,81,Urban,Data Analyst,124655,1 +58989,Male,26,Masters,1,88,97,63,66,2.0,0,5,Urban,Manager,30978,1 +58990,Male,26,High School,10,50,33,30,67,7.0,1,16,Urban,Manager,136889,0 +58991,Female,54,Bachelors,5,61,78,62,74,3.0,6,80,Rural,HR Executive,34095,1 +58992,Female,34,Masters,7,19,98,5,31,5.0,2,7,Urban,Software Engineer,31450,0 +58993,Female,52,Masters,0,35,53,30,96,4.0,1,35,Urban,Manager,61393,0 +58994,Male,46,Diploma,1,70,78,99,65,3.0,2,33,Urban,Software Engineer,84962,1 +58995,Male,25,PhD,9,20,50,26,44,7.0,7,60,Urban,Data Analyst,73288,0 +58996,Female,43,High School,14,85,67,51,52,9.0,0,29,Rural,Manager,86546,0 +58997,Female,33,Bachelors,3,7,90,83,41,2.0,5,47,Urban,Manager,60963,0 +58998,Female,51,High School,8,10,95,11,30,9.0,7,30,Urban,HR Executive,143039,0 +58999,Male,43,Masters,0,46,2,60,47,7.0,1,2,Urban,Manager,54397,0 +59000,Male,35,Bachelors,9,91,62,5,22,3.0,4,82,Rural,Data Analyst,79627,1 +59001,Male,47,PhD,14,17,40,53,53,3.0,2,27,Urban,HR Executive,21927,0 +59002,Male,29,Bachelors,19,42,1,70,49,5.0,6,80,Urban,Manager,91773,0 +59003,Male,22,Bachelors,15,73,18,63,52,9.0,0,62,Semi-Urban,Software Engineer,133053,0 +59004,Male,58,Masters,4,1,15,69,39,1.0,4,68,Rural,ML Engineer,73813,0 +59005,Female,52,Bachelors,2,70,35,97,82,1.0,7,51,Urban,Data Analyst,103541,1 +59006,Female,48,Bachelors,13,57,85,9,91,1.0,7,20,Semi-Urban,ML Engineer,57723,0 +59007,Male,40,Masters,14,90,76,24,33,2.0,5,94,Urban,ML Engineer,147841,1 +59008,Other,46,Bachelors,17,61,18,10,98,8.0,5,86,Urban,HR Executive,40178,0 +59009,Male,33,Masters,14,86,51,92,88,4.0,1,46,Urban,Data Analyst,74091,1 +59010,Male,39,Bachelors,9,1,31,30,12,2.0,2,58,Urban,ML Engineer,124529,0 +59011,Other,58,Diploma,8,68,36,20,18,7.0,2,85,Rural,Software Engineer,145476,0 +59012,Male,39,Masters,8,41,2,81,59,4.0,0,67,Rural,Manager,108314,0 +59013,Male,47,Bachelors,12,55,24,54,76,3.0,2,4,Semi-Urban,HR Executive,128197,0 +59014,Female,52,Bachelors,9,54,87,39,77,2.0,7,47,Rural,ML Engineer,136240,0 +59015,Male,51,Bachelors,19,38,25,79,59,0.0,1,55,Urban,HR Executive,94834,0 +59016,Female,59,Bachelors,19,16,45,72,19,5.0,5,2,Urban,ML Engineer,98528,0 +59017,Female,36,Bachelors,19,99,77,73,56,1.0,2,91,Urban,Software Engineer,138270,1 +59018,Male,27,Bachelors,1,36,77,2,8,0.0,4,40,Urban,Software Engineer,78009,0 +59019,Male,33,Bachelors,19,66,12,20,72,9.0,2,72,Urban,Software Engineer,91910,0 +59020,Male,21,Bachelors,5,60,20,51,6,9.0,3,16,Urban,Software Engineer,122262,0 +59021,Male,43,Masters,3,52,34,56,26,2.0,5,14,Semi-Urban,HR Executive,49961,0 +59022,Male,54,High School,10,60,24,64,25,2.0,6,10,Rural,Software Engineer,46458,0 +59023,Male,52,Bachelors,6,34,43,99,49,3.0,7,84,Urban,Data Analyst,67839,1 +59024,Female,33,Diploma,11,60,17,62,31,9.0,6,25,Urban,Manager,64550,0 +59025,Male,26,Masters,10,88,76,21,45,2.0,0,82,Rural,Data Analyst,52190,1 +59026,Male,53,High School,2,17,96,10,45,6.0,6,78,Urban,Software Engineer,58280,0 +59027,Female,53,PhD,8,4,22,1,4,4.0,7,50,Semi-Urban,Data Analyst,69741,0 +59028,Female,24,Bachelors,10,71,27,34,47,8.0,0,83,Urban,HR Executive,50743,0 +59029,Male,45,Bachelors,13,94,95,31,99,1.0,2,42,Semi-Urban,ML Engineer,134859,1 +59030,Female,33,Diploma,3,1,35,37,30,7.0,6,77,Rural,ML Engineer,149807,0 +59031,Male,47,High School,19,11,19,39,15,6.0,2,45,Urban,HR Executive,38573,0 +59032,Female,24,Masters,10,96,2,4,2,6.0,6,52,Urban,Data Analyst,116563,0 +59033,Male,51,Bachelors,1,49,73,90,6,1.0,1,1,Semi-Urban,Manager,123860,0 +59034,Male,29,Bachelors,2,6,1,7,54,0.0,0,23,Urban,Manager,60789,0 +59035,Male,39,Diploma,4,44,53,6,20,6.0,3,56,Semi-Urban,Manager,113235,0 +59036,Male,42,Diploma,8,45,41,73,42,7.0,1,98,Urban,Manager,91050,1 +59037,Male,52,Bachelors,1,60,1,35,29,6.0,4,70,Semi-Urban,Manager,40855,0 +59038,Male,28,Diploma,2,81,64,66,96,6.0,6,23,Rural,Manager,58150,0 +59039,Male,50,Diploma,5,82,26,3,67,7.0,2,30,Semi-Urban,Manager,62917,0 +59040,Female,56,Masters,7,15,8,9,53,2.0,6,94,Urban,ML Engineer,27447,0 +59041,Female,37,Bachelors,12,79,13,96,47,9.0,4,64,Urban,ML Engineer,95962,1 +59042,Male,31,Bachelors,14,4,32,44,87,9.0,6,5,Urban,Manager,119951,0 +59043,Other,22,Masters,6,93,67,30,54,9.0,0,6,Urban,Software Engineer,70601,0 +59044,Female,22,Bachelors,13,23,5,46,19,5.0,1,90,Semi-Urban,ML Engineer,57710,0 +59045,Male,23,Bachelors,8,91,82,34,91,5.0,6,47,Urban,ML Engineer,62003,1 +59046,Female,45,Bachelors,18,56,93,10,36,3.0,7,17,Urban,ML Engineer,124514,0 +59047,Female,31,Diploma,3,2,66,19,25,5.0,3,91,Urban,Software Engineer,97206,0 +59048,Male,34,Bachelors,16,5,51,59,34,9.0,7,0,Semi-Urban,Manager,89056,0 +59049,Male,41,Bachelors,7,0,95,32,47,5.0,1,9,Urban,Manager,87355,0 +59050,Male,26,High School,15,22,6,86,53,7.0,7,0,Urban,Software Engineer,145671,0 +59051,Male,45,Bachelors,3,47,93,18,59,2.0,4,24,Semi-Urban,Data Analyst,31063,0 +59052,Other,38,PhD,0,80,38,28,73,0.0,6,37,Rural,Data Analyst,137851,0 +59053,Female,35,Bachelors,12,22,74,5,11,9.0,2,83,Urban,Manager,31444,0 +59054,Male,23,Diploma,11,55,43,9,56,2.0,3,56,Rural,Manager,119231,0 +59055,Female,57,PhD,15,44,92,21,99,6.0,6,45,Semi-Urban,Manager,47061,0 +59056,Male,22,Diploma,11,3,79,68,34,6.0,3,84,Rural,Data Analyst,29156,0 +59057,Male,55,Bachelors,4,11,34,12,65,7.0,6,65,Rural,Data Analyst,36155,0 +59058,Male,34,Bachelors,13,72,40,89,1,0.0,1,31,Semi-Urban,ML Engineer,100873,0 +59059,Male,38,PhD,4,21,67,53,99,8.0,4,91,Urban,ML Engineer,64676,0 +59060,Male,36,Bachelors,3,65,19,37,78,8.0,3,44,Semi-Urban,ML Engineer,79597,0 +59061,Female,23,Bachelors,16,0,14,91,69,8.0,2,66,Urban,HR Executive,134888,0 +59062,Male,54,High School,3,80,93,35,18,5.0,6,12,Rural,HR Executive,97876,0 +59063,Female,58,PhD,19,32,6,91,54,2.0,7,97,Urban,Data Analyst,58161,0 +59064,Male,36,Bachelors,1,48,55,62,77,0.0,6,3,Urban,ML Engineer,100709,0 +59065,Male,51,Bachelors,15,8,66,9,92,9.0,2,64,Urban,ML Engineer,28931,0 +59066,Female,56,Bachelors,8,4,96,9,49,8.0,1,41,Urban,Software Engineer,95151,0 +59067,Male,56,Diploma,15,51,26,52,93,5.0,7,71,Semi-Urban,HR Executive,70518,0 +59068,Female,32,Bachelors,2,44,75,19,18,0.0,3,51,Semi-Urban,ML Engineer,126303,0 +59069,Male,29,PhD,0,71,81,33,42,4.0,0,96,Rural,Manager,103059,1 +59070,Male,48,Bachelors,4,20,59,88,92,9.0,3,96,Semi-Urban,HR Executive,133911,1 +59071,Male,38,High School,13,78,39,97,80,6.0,5,69,Rural,HR Executive,118741,1 +59072,Female,44,PhD,5,80,88,77,91,1.0,5,84,Semi-Urban,Data Analyst,86278,1 +59073,Male,22,Diploma,0,73,41,30,42,9.0,6,37,Urban,Software Engineer,77864,0 +59074,Male,38,Bachelors,12,18,9,68,3,1.0,6,0,Rural,ML Engineer,36599,0 +59075,Female,57,Masters,11,37,88,24,71,4.0,6,12,Urban,ML Engineer,41052,0 +59076,Female,29,Diploma,1,76,6,56,75,6.0,3,31,Rural,HR Executive,92115,0 +59077,Male,52,PhD,4,5,65,10,70,7.0,5,51,Rural,Manager,50192,0 +59078,Female,24,Bachelors,13,79,10,57,32,9.0,4,19,Rural,Data Analyst,30595,0 +59079,Other,37,Masters,0,75,94,66,42,5.0,4,91,Urban,Data Analyst,123964,1 +59080,Male,25,Bachelors,4,83,1,6,81,8.0,0,41,Semi-Urban,HR Executive,140344,0 +59081,Male,48,Masters,3,79,75,66,82,6.0,0,25,Urban,Software Engineer,69933,1 +59082,Male,49,Diploma,16,21,66,44,23,9.0,7,31,Urban,Manager,90318,0 +59083,Female,23,Diploma,4,83,7,66,11,2.0,5,99,Urban,ML Engineer,55636,1 +59084,Male,59,Bachelors,18,17,27,15,37,3.0,1,72,Urban,Data Analyst,133155,0 +59085,Male,38,Diploma,16,68,89,34,74,2.0,5,58,Semi-Urban,Data Analyst,52419,1 +59086,Female,57,Bachelors,13,33,52,44,45,0.0,2,84,Rural,Software Engineer,115185,0 +59087,Female,51,Bachelors,11,82,8,39,3,6.0,7,22,Urban,Software Engineer,82137,0 +59088,Male,26,Bachelors,16,86,7,7,31,8.0,6,37,Rural,Data Analyst,143893,0 +59089,Female,36,Masters,2,57,66,50,51,0.0,1,0,Semi-Urban,Data Analyst,29488,0 +59090,Other,39,Masters,8,55,91,70,26,4.0,2,57,Urban,HR Executive,145815,1 +59091,Female,34,Bachelors,7,69,83,90,49,5.0,0,85,Urban,HR Executive,148335,1 +59092,Female,59,Diploma,12,97,90,21,11,8.0,1,55,Semi-Urban,Data Analyst,117211,1 +59093,Female,32,Bachelors,9,6,22,31,88,3.0,5,34,Rural,Data Analyst,135609,0 +59094,Female,53,PhD,16,66,61,28,54,3.0,5,20,Semi-Urban,Manager,42929,0 +59095,Female,27,PhD,3,8,6,36,44,1.0,2,4,Urban,ML Engineer,124034,0 +59096,Female,55,Bachelors,17,42,23,24,53,6.0,5,16,Semi-Urban,HR Executive,120693,0 +59097,Female,48,Bachelors,6,3,89,18,63,0.0,2,91,Rural,Software Engineer,149546,0 +59098,Male,43,Bachelors,6,33,92,17,14,5.0,1,3,Semi-Urban,ML Engineer,103852,0 +59099,Male,42,Masters,6,72,41,81,46,0.0,3,21,Urban,ML Engineer,113217,0 +59100,Male,25,Bachelors,2,82,33,70,27,6.0,2,86,Urban,HR Executive,100827,1 +59101,Male,25,Bachelors,10,4,1,28,29,0.0,0,39,Semi-Urban,HR Executive,61212,0 +59102,Female,25,High School,10,79,75,46,45,7.0,3,30,Semi-Urban,Manager,87418,0 +59103,Male,46,Bachelors,18,75,25,70,86,6.0,2,4,Urban,HR Executive,132910,0 +59104,Female,51,Bachelors,10,96,98,18,85,4.0,1,23,Rural,Data Analyst,58823,0 +59105,Female,31,Diploma,12,32,13,40,82,1.0,1,75,Semi-Urban,HR Executive,135083,0 +59106,Male,27,Bachelors,12,78,59,59,94,1.0,4,52,Urban,Manager,67033,1 +59107,Male,46,Bachelors,2,41,66,25,24,4.0,0,44,Urban,Data Analyst,131637,0 +59108,Female,23,Diploma,4,87,63,66,23,4.0,6,57,Urban,Manager,120093,1 +59109,Male,22,High School,8,17,96,35,61,9.0,1,8,Urban,ML Engineer,127651,0 +59110,Female,50,Masters,15,55,59,90,34,7.0,3,61,Semi-Urban,Data Analyst,61583,1 +59111,Male,42,Bachelors,19,19,28,64,74,7.0,4,47,Urban,Software Engineer,148626,0 +59112,Female,59,Bachelors,2,84,80,64,69,0.0,3,4,Urban,Data Analyst,37035,0 +59113,Male,51,PhD,11,7,20,20,40,7.0,1,20,Rural,ML Engineer,25666,0 +59114,Male,54,Diploma,16,91,38,32,37,8.0,1,46,Rural,Data Analyst,21453,0 +59115,Male,47,Bachelors,5,45,19,52,4,6.0,3,45,Rural,HR Executive,48274,0 +59116,Female,25,Masters,2,53,76,22,26,4.0,2,85,Semi-Urban,Manager,30544,0 +59117,Male,38,Diploma,2,57,92,98,85,2.0,2,38,Urban,ML Engineer,80655,1 +59118,Male,56,Bachelors,12,3,62,37,68,7.0,7,14,Urban,HR Executive,113883,0 +59119,Male,42,Bachelors,8,85,80,67,79,7.0,7,98,Urban,Manager,32454,1 +59120,Female,49,High School,11,66,85,2,41,3.0,6,5,Urban,Data Analyst,106194,0 +59121,Other,42,Bachelors,19,19,2,71,14,2.0,4,64,Rural,HR Executive,131573,0 +59122,Male,55,Masters,16,97,66,37,82,1.0,1,91,Urban,Manager,51023,1 +59123,Female,22,High School,19,7,7,43,31,4.0,7,82,Rural,Data Analyst,81948,0 +59124,Male,50,Bachelors,11,59,20,26,57,8.0,5,77,Rural,ML Engineer,68637,0 +59125,Female,34,Bachelors,7,89,23,66,4,1.0,4,40,Urban,HR Executive,25616,0 +59126,Male,34,Bachelors,18,71,71,8,90,1.0,3,82,Semi-Urban,Data Analyst,60266,0 +59127,Female,21,High School,8,10,22,96,43,1.0,5,46,Semi-Urban,Manager,111230,0 +59128,Male,33,Bachelors,0,66,19,12,88,2.0,3,43,Urban,ML Engineer,123104,0 +59129,Female,58,Bachelors,17,43,58,71,87,5.0,0,91,Urban,Software Engineer,112333,1 +59130,Male,52,Diploma,17,64,98,17,37,3.0,3,42,Urban,Software Engineer,149183,0 +59131,Female,33,High School,15,10,68,71,42,7.0,2,92,Urban,Manager,64519,1 +59132,Male,25,Bachelors,11,73,36,85,84,1.0,7,64,Rural,ML Engineer,103235,1 +59133,Male,57,Bachelors,14,20,75,98,56,9.0,2,71,Semi-Urban,Data Analyst,67441,1 +59134,Male,37,High School,5,29,64,99,20,6.0,4,95,Urban,Manager,43846,1 +59135,Female,53,High School,5,38,71,57,26,6.0,7,84,Urban,Software Engineer,58874,1 +59136,Male,27,Diploma,5,93,12,44,28,4.0,2,77,Urban,Software Engineer,50112,0 +59137,Male,51,Bachelors,15,56,93,32,73,0.0,4,48,Rural,Software Engineer,92158,0 +59138,Female,53,Bachelors,16,65,45,32,7,3.0,5,11,Urban,ML Engineer,127407,0 +59139,Male,34,Diploma,0,96,71,24,78,2.0,2,41,Rural,Manager,114175,0 +59140,Male,37,High School,3,99,85,57,21,2.0,1,43,Urban,Software Engineer,145219,1 +59141,Male,57,Diploma,17,77,97,99,36,2.0,7,21,Urban,Data Analyst,59056,1 +59142,Female,44,Bachelors,19,60,81,47,60,7.0,2,75,Semi-Urban,Data Analyst,65873,1 +59143,Female,31,High School,1,84,94,55,42,6.0,7,6,Semi-Urban,ML Engineer,77058,0 +59144,Female,53,Bachelors,17,5,30,29,2,3.0,3,89,Semi-Urban,HR Executive,91549,0 +59145,Female,57,Diploma,17,27,86,12,23,8.0,2,27,Urban,Software Engineer,94924,0 +59146,Female,56,High School,14,22,69,83,67,7.0,1,45,Urban,Software Engineer,89755,0 +59147,Female,29,Masters,9,48,92,96,54,5.0,4,97,Semi-Urban,HR Executive,99820,1 +59148,Male,49,Bachelors,19,27,88,36,78,1.0,4,71,Urban,Data Analyst,139708,0 +59149,Female,52,High School,2,25,48,45,31,2.0,4,43,Semi-Urban,Manager,47990,0 +59150,Other,41,Diploma,0,87,75,31,64,3.0,3,4,Urban,Software Engineer,133396,0 +59151,Male,53,High School,5,21,40,58,67,3.0,4,61,Rural,Data Analyst,84694,0 +59152,Female,24,Bachelors,6,41,75,53,11,9.0,1,86,Urban,HR Executive,87982,1 +59153,Female,51,Bachelors,6,30,97,91,94,1.0,3,78,Urban,ML Engineer,139647,1 +59154,Female,23,PhD,4,17,26,69,57,6.0,2,57,Semi-Urban,ML Engineer,112616,0 +59155,Female,21,Bachelors,19,44,38,25,36,7.0,2,44,Urban,Manager,54141,0 +59156,Male,34,High School,9,28,64,41,23,6.0,6,80,Rural,ML Engineer,68943,0 +59157,Male,23,Masters,9,72,81,48,2,8.0,3,38,Urban,Data Analyst,50260,1 +59158,Male,34,Diploma,1,21,78,58,75,0.0,5,24,Semi-Urban,HR Executive,87356,0 +59159,Female,57,Bachelors,3,73,74,30,64,3.0,3,6,Urban,HR Executive,117874,0 +59160,Male,45,Diploma,0,26,88,39,31,9.0,6,50,Urban,Data Analyst,149609,0 +59161,Other,21,PhD,1,69,3,50,46,4.0,6,10,Semi-Urban,Manager,71361,0 +59162,Male,35,Bachelors,12,48,21,87,31,5.0,5,11,Semi-Urban,Manager,88608,0 +59163,Male,50,High School,7,33,45,40,67,9.0,0,40,Semi-Urban,Data Analyst,142365,0 +59164,Male,22,Masters,19,18,29,20,20,1.0,2,55,Semi-Urban,HR Executive,126864,0 +59165,Female,24,Masters,7,41,10,85,5,9.0,3,27,Rural,HR Executive,80050,0 +59166,Male,21,High School,6,13,34,10,99,0.0,7,16,Urban,HR Executive,69668,0 +59167,Male,30,Masters,7,94,76,50,70,1.0,0,32,Semi-Urban,ML Engineer,113546,1 +59168,Male,50,Masters,12,70,23,74,41,2.0,0,94,Rural,ML Engineer,56103,1 +59169,Other,28,Masters,17,52,99,45,58,4.0,2,98,Urban,ML Engineer,127920,1 +59170,Other,25,High School,13,16,68,11,44,8.0,6,99,Semi-Urban,Software Engineer,28825,0 +59171,Male,35,Masters,8,24,82,73,27,0.0,7,47,Rural,ML Engineer,92492,0 +59172,Female,49,Bachelors,7,98,88,25,33,2.0,1,28,Urban,Software Engineer,133515,0 +59173,Female,25,Masters,13,38,83,61,54,4.0,6,97,Urban,Data Analyst,106291,1 +59174,Female,25,Bachelors,2,34,49,72,2,7.0,3,67,Urban,ML Engineer,120521,0 +59175,Male,55,Bachelors,18,38,70,96,30,9.0,0,25,Urban,Software Engineer,71508,0 +59176,Male,48,Bachelors,14,16,25,90,9,0.0,6,49,Urban,Data Analyst,27932,0 +59177,Female,48,Bachelors,14,9,10,13,62,9.0,0,29,Urban,ML Engineer,142438,0 +59178,Male,26,PhD,11,58,90,45,49,3.0,4,41,Rural,ML Engineer,76221,0 +59179,Male,32,Bachelors,6,17,96,38,54,6.0,6,74,Rural,Manager,108467,0 +59180,Male,53,High School,4,35,57,46,10,5.0,3,52,Rural,HR Executive,131640,0 +59181,Female,55,PhD,15,26,91,57,31,7.0,5,48,Urban,Manager,23409,0 +59182,Female,43,Masters,1,96,94,49,92,7.0,7,18,Semi-Urban,HR Executive,137940,1 +59183,Male,28,Diploma,16,79,0,0,6,8.0,5,41,Semi-Urban,HR Executive,84895,0 +59184,Female,41,Bachelors,12,17,67,75,84,8.0,7,98,Urban,Software Engineer,32758,1 +59185,Male,59,Bachelors,1,50,80,59,74,4.0,6,76,Semi-Urban,Manager,22420,1 +59186,Female,45,Bachelors,14,62,80,48,66,1.0,6,35,Rural,Data Analyst,108676,0 +59187,Male,37,Masters,8,2,90,86,82,9.0,5,46,Urban,ML Engineer,70173,0 +59188,Male,44,Bachelors,15,78,47,99,38,8.0,1,92,Semi-Urban,ML Engineer,82273,1 +59189,Female,27,Bachelors,0,99,86,36,50,3.0,4,22,Urban,ML Engineer,44779,1 +59190,Female,22,Masters,10,77,76,40,18,2.0,6,79,Urban,HR Executive,108464,1 +59191,Male,47,Masters,10,77,55,71,24,8.0,0,0,Urban,HR Executive,101690,0 +59192,Male,38,Masters,9,93,74,50,24,6.0,7,49,Semi-Urban,Software Engineer,131988,1 +59193,Female,26,Masters,3,74,89,54,40,9.0,0,40,Rural,Data Analyst,91995,1 +59194,Male,54,Diploma,8,10,10,13,56,6.0,0,46,Semi-Urban,Manager,89711,0 +59195,Female,57,Bachelors,16,43,35,11,93,5.0,5,62,Rural,Data Analyst,129313,0 +59196,Male,21,Diploma,2,83,42,64,54,9.0,5,82,Semi-Urban,ML Engineer,48444,1 +59197,Male,40,Masters,13,76,47,89,60,9.0,2,96,Semi-Urban,Software Engineer,100008,1 +59198,Female,52,Bachelors,7,10,53,66,68,5.0,6,25,Urban,Manager,20484,0 +59199,Female,46,Diploma,12,70,3,15,3,3.0,7,75,Urban,Manager,25753,0 +59200,Male,49,High School,12,34,69,11,6,2.0,1,15,Semi-Urban,Software Engineer,79154,0 +59201,Male,45,High School,9,61,79,80,82,0.0,3,71,Urban,HR Executive,79472,1 +59202,Female,46,Masters,5,25,8,34,41,3.0,7,31,Urban,HR Executive,29875,0 +59203,Male,48,Masters,0,91,78,75,69,4.0,4,20,Rural,Manager,20249,1 +59204,Female,40,Masters,6,55,44,55,96,9.0,7,11,Semi-Urban,Manager,102375,0 +59205,Male,36,Bachelors,7,5,2,67,11,3.0,0,10,Urban,Manager,46916,0 +59206,Male,29,Diploma,14,49,46,56,99,3.0,3,93,Semi-Urban,Manager,111759,1 +59207,Male,52,High School,8,76,41,55,33,7.0,6,29,Urban,Manager,116281,0 +59208,Male,53,Bachelors,8,3,18,34,1,9.0,7,48,Rural,Manager,63387,0 +59209,Male,39,Bachelors,1,47,34,30,75,2.0,0,57,Urban,ML Engineer,70215,0 +59210,Female,21,Masters,3,70,22,22,87,2.0,4,20,Rural,ML Engineer,29503,0 +59211,Male,46,Diploma,11,19,65,63,41,7.0,0,24,Semi-Urban,HR Executive,39448,0 +59212,Female,27,Bachelors,8,13,27,73,50,9.0,1,90,Urban,HR Executive,107531,0 +59213,Female,27,Bachelors,3,33,33,61,2,8.0,2,99,Urban,Software Engineer,41190,0 +59214,Female,28,Diploma,9,90,23,2,51,0.0,6,53,Urban,ML Engineer,42393,0 +59215,Female,48,Bachelors,10,12,49,72,71,2.0,1,87,Rural,Software Engineer,49399,0 +59216,Male,56,Diploma,11,20,42,52,33,2.0,2,5,Urban,HR Executive,116576,0 +59217,Male,44,Bachelors,12,42,62,48,56,7.0,7,69,Urban,HR Executive,20410,0 +59218,Female,29,Masters,17,78,86,37,17,7.0,4,13,Urban,ML Engineer,37159,0 +59219,Female,37,Bachelors,19,7,87,45,45,1.0,3,99,Urban,Manager,28575,0 +59220,Male,50,High School,19,99,66,1,30,8.0,1,16,Rural,ML Engineer,110840,0 +59221,Other,51,Masters,10,88,40,9,16,6.0,7,53,Urban,ML Engineer,60476,0 +59222,Male,44,Masters,6,5,77,56,86,1.0,7,68,Urban,Software Engineer,56763,0 +59223,Female,27,Bachelors,18,18,36,44,29,4.0,2,65,Urban,HR Executive,63168,0 +59224,Male,55,Masters,7,37,61,45,5,4.0,5,43,Rural,HR Executive,32193,0 +59225,Male,38,Masters,18,51,60,30,80,5.0,0,43,Urban,HR Executive,55019,0 +59226,Male,44,Diploma,2,88,48,39,11,5.0,3,95,Urban,Data Analyst,117695,1 +59227,Male,27,Bachelors,2,78,58,59,89,8.0,4,11,Urban,Data Analyst,77808,0 +59228,Other,49,Bachelors,13,84,19,93,20,7.0,0,70,Urban,ML Engineer,117668,1 +59229,Other,29,Bachelors,5,49,39,8,56,5.0,3,13,Urban,ML Engineer,141081,0 +59230,Male,41,Bachelors,10,85,37,49,17,8.0,7,3,Urban,ML Engineer,139100,0 +59231,Male,25,Diploma,6,85,43,6,45,9.0,1,58,Urban,Manager,136601,0 +59232,Male,45,Diploma,1,7,9,40,53,0.0,0,14,Rural,Manager,34131,0 +59233,Male,29,Masters,7,22,91,81,83,5.0,3,97,Urban,ML Engineer,63368,1 +59234,Female,31,Diploma,14,39,98,88,26,5.0,2,29,Semi-Urban,Data Analyst,142925,1 +59235,Male,46,Diploma,1,54,64,75,79,7.0,5,77,Urban,Manager,101588,1 +59236,Male,56,High School,17,92,46,25,68,7.0,4,28,Urban,Manager,120088,0 +59237,Male,46,Bachelors,18,10,60,52,98,6.0,5,5,Semi-Urban,Software Engineer,107767,0 +59238,Female,45,Masters,13,34,61,14,90,8.0,2,80,Urban,Software Engineer,34567,0 +59239,Male,55,Masters,16,32,91,82,18,3.0,2,52,Urban,ML Engineer,24681,1 +59240,Male,24,Bachelors,7,36,15,61,86,3.0,5,29,Semi-Urban,Data Analyst,119666,0 +59241,Female,45,Bachelors,11,95,96,47,60,6.0,2,5,Urban,HR Executive,47975,1 +59242,Other,57,Masters,2,90,48,50,56,1.0,3,18,Rural,HR Executive,48207,0 +59243,Female,25,Diploma,14,34,56,33,49,2.0,4,85,Urban,ML Engineer,102202,0 +59244,Male,25,Bachelors,19,65,76,8,87,0.0,4,12,Rural,Data Analyst,32762,0 +59245,Female,24,High School,5,36,43,57,63,3.0,0,8,Semi-Urban,HR Executive,25260,0 +59246,Other,57,Masters,10,56,16,76,35,0.0,6,14,Semi-Urban,ML Engineer,35749,0 +59247,Female,26,High School,17,82,23,14,70,4.0,0,2,Semi-Urban,ML Engineer,120591,0 +59248,Male,35,Bachelors,11,98,40,87,76,6.0,1,67,Urban,ML Engineer,46715,1 +59249,Male,24,Bachelors,5,95,8,81,60,8.0,7,41,Semi-Urban,Software Engineer,98877,0 +59250,Female,57,High School,10,14,2,43,83,4.0,3,54,Urban,Software Engineer,102401,0 +59251,Female,23,Masters,8,17,56,24,50,1.0,3,45,Urban,Data Analyst,40568,0 +59252,Male,49,Bachelors,2,92,5,93,70,8.0,2,66,Urban,Data Analyst,30030,1 +59253,Male,39,High School,9,37,30,71,73,5.0,2,17,Urban,Data Analyst,102749,0 +59254,Female,54,High School,16,98,58,61,3,5.0,5,4,Semi-Urban,Manager,135185,0 +59255,Male,33,Bachelors,6,84,92,17,56,2.0,2,42,Semi-Urban,HR Executive,127822,1 +59256,Male,31,High School,7,3,32,10,63,4.0,6,45,Urban,Data Analyst,114437,0 +59257,Female,48,Bachelors,3,75,10,67,94,0.0,1,76,Semi-Urban,HR Executive,55238,0 +59258,Male,31,Bachelors,9,28,81,21,3,3.0,6,54,Urban,ML Engineer,128395,0 +59259,Female,22,Bachelors,4,51,78,43,94,7.0,6,36,Rural,Data Analyst,25848,0 +59260,Female,27,Bachelors,0,25,20,8,15,1.0,0,18,Urban,Data Analyst,136388,0 +59261,Female,54,Bachelors,10,36,49,66,6,9.0,7,5,Semi-Urban,Software Engineer,145406,0 +59262,Male,27,Diploma,7,80,59,36,68,5.0,4,37,Rural,Manager,88128,0 +59263,Male,29,Bachelors,10,40,68,24,69,4.0,1,88,Urban,HR Executive,115107,0 +59264,Female,26,Bachelors,16,99,20,97,1,6.0,2,76,Urban,Manager,38614,1 +59265,Other,26,High School,8,15,7,48,52,5.0,2,88,Rural,ML Engineer,21590,0 +59266,Female,38,Diploma,7,98,20,18,55,7.0,5,72,Urban,Software Engineer,139078,0 +59267,Female,41,Diploma,18,56,28,8,94,0.0,4,60,Rural,ML Engineer,104328,0 +59268,Male,56,Diploma,19,59,96,30,97,9.0,3,93,Rural,ML Engineer,107215,1 +59269,Male,54,Bachelors,14,25,18,16,91,2.0,5,26,Urban,Data Analyst,84014,0 +59270,Female,28,Bachelors,17,65,84,95,4,4.0,2,51,Urban,Data Analyst,111169,1 +59271,Male,35,Bachelors,1,97,11,24,42,6.0,4,76,Urban,ML Engineer,112850,0 +59272,Female,40,High School,10,60,64,57,38,9.0,4,39,Urban,Software Engineer,48886,0 +59273,Male,25,Masters,17,38,14,79,12,9.0,5,96,Urban,HR Executive,22031,0 +59274,Male,41,Bachelors,13,84,3,6,17,0.0,1,40,Urban,HR Executive,103794,0 +59275,Male,37,Bachelors,4,53,25,13,10,0.0,3,38,Urban,Manager,67460,0 +59276,Male,50,PhD,16,72,78,92,97,0.0,4,24,Rural,HR Executive,70610,1 +59277,Female,54,Bachelors,10,50,3,25,64,5.0,6,86,Semi-Urban,Manager,44820,0 +59278,Male,24,Bachelors,14,94,91,89,95,3.0,6,4,Semi-Urban,Data Analyst,65903,1 +59279,Female,25,Diploma,16,27,85,32,59,6.0,0,35,Semi-Urban,Data Analyst,79300,0 +59280,Female,58,Bachelors,9,87,71,8,42,8.0,1,75,Urban,Data Analyst,142528,1 +59281,Male,30,Bachelors,3,84,85,48,15,4.0,3,61,Urban,Software Engineer,53891,1 +59282,Male,31,Bachelors,7,76,36,48,36,9.0,2,68,Rural,Software Engineer,95831,0 +59283,Female,56,Masters,6,66,91,79,92,3.0,6,2,Rural,HR Executive,103655,0 +59284,Male,38,Bachelors,14,84,97,49,66,9.0,5,65,Rural,HR Executive,39885,1 +59285,Female,55,Bachelors,12,88,77,88,94,3.0,5,20,Urban,ML Engineer,50609,1 +59286,Male,36,Masters,0,16,49,78,60,0.0,1,2,Urban,HR Executive,134459,0 +59287,Female,44,Bachelors,10,29,30,97,42,5.0,7,6,Semi-Urban,Software Engineer,68037,0 +59288,Male,28,PhD,8,42,20,99,43,4.0,6,85,Urban,Manager,87932,1 +59289,Male,27,Diploma,1,61,85,6,7,1.0,4,71,Urban,Software Engineer,93699,0 +59290,Other,29,Bachelors,18,94,65,99,37,2.0,0,77,Urban,Software Engineer,126158,1 +59291,Male,42,Masters,12,72,21,27,14,2.0,3,99,Semi-Urban,ML Engineer,112557,0 +59292,Male,35,Masters,13,12,23,68,43,1.0,4,30,Urban,ML Engineer,39509,0 +59293,Male,37,Masters,16,50,32,77,43,0.0,1,98,Urban,Manager,46891,1 +59294,Female,34,High School,5,85,6,40,68,9.0,3,66,Urban,Software Engineer,61263,0 +59295,Male,49,High School,12,39,80,28,6,0.0,0,68,Urban,Manager,124798,0 +59296,Male,32,Diploma,17,20,66,6,4,1.0,4,23,Semi-Urban,Software Engineer,90220,0 +59297,Male,24,PhD,2,10,62,42,64,7.0,7,71,Semi-Urban,Manager,63966,0 +59298,Male,42,High School,19,57,29,79,69,8.0,1,10,Semi-Urban,Software Engineer,148352,0 +59299,Female,47,Masters,12,38,48,96,17,7.0,0,87,Urban,ML Engineer,89894,1 +59300,Male,56,Masters,6,94,12,35,95,3.0,4,4,Urban,Manager,35624,0 +59301,Male,26,Bachelors,0,39,12,93,39,2.0,6,13,Urban,ML Engineer,26861,0 +59302,Male,50,High School,9,33,20,74,85,8.0,2,15,Urban,Software Engineer,107045,0 +59303,Female,42,Masters,17,18,90,70,34,8.0,6,77,Urban,Data Analyst,41015,1 +59304,Male,27,Bachelors,7,15,91,20,67,2.0,5,37,Semi-Urban,HR Executive,35267,0 +59305,Female,31,Bachelors,10,50,62,46,31,0.0,4,65,Semi-Urban,HR Executive,47294,0 +59306,Female,43,PhD,8,12,48,96,32,7.0,0,6,Urban,Data Analyst,66760,0 +59307,Male,26,Bachelors,17,59,87,92,14,9.0,7,14,Semi-Urban,HR Executive,60730,1 +59308,Male,47,Masters,14,98,10,80,41,9.0,1,37,Rural,Software Engineer,148822,0 +59309,Male,27,Bachelors,6,3,31,80,16,5.0,5,51,Semi-Urban,ML Engineer,43120,0 +59310,Female,22,Bachelors,15,25,66,3,59,4.0,7,26,Urban,Manager,62442,0 +59311,Female,41,Bachelors,10,26,84,99,42,2.0,4,89,Urban,HR Executive,119510,1 +59312,Female,54,Masters,1,56,64,19,89,3.0,1,31,Semi-Urban,Software Engineer,117700,0 +59313,Male,55,Bachelors,15,71,10,15,87,2.0,2,27,Semi-Urban,Software Engineer,134938,0 +59314,Other,52,Masters,17,57,74,79,10,9.0,6,5,Rural,Manager,73879,0 +59315,Male,56,Bachelors,7,69,42,75,38,4.0,6,61,Urban,Manager,124315,1 +59316,Female,53,High School,4,14,34,51,68,7.0,3,79,Urban,Software Engineer,28888,0 +59317,Male,46,Masters,1,40,94,10,5,1.0,5,40,Urban,HR Executive,77743,0 +59318,Male,30,Diploma,5,83,47,81,45,0.0,1,72,Semi-Urban,Manager,91855,1 +59319,Male,27,Masters,8,83,32,23,18,2.0,0,1,Urban,HR Executive,31555,0 +59320,Male,26,Diploma,4,67,13,39,86,5.0,5,90,Urban,Manager,52820,0 +59321,Male,39,Diploma,2,38,83,89,50,9.0,7,84,Urban,HR Executive,144039,1 +59322,Male,55,High School,19,97,17,83,90,0.0,5,16,Semi-Urban,Software Engineer,81608,0 +59323,Male,32,PhD,8,84,69,78,4,3.0,7,53,Urban,Software Engineer,126446,1 +59324,Male,25,Masters,6,45,27,89,91,4.0,3,9,Urban,Software Engineer,52313,0 +59325,Male,52,Bachelors,13,3,11,82,83,5.0,3,17,Urban,HR Executive,36030,0 +59326,Male,50,Diploma,17,22,14,88,20,3.0,7,2,Semi-Urban,HR Executive,78194,0 +59327,Other,34,Diploma,7,18,9,0,76,2.0,2,4,Semi-Urban,Manager,112442,0 +59328,Male,44,High School,8,46,40,21,13,1.0,6,55,Semi-Urban,ML Engineer,31383,0 +59329,Male,45,Bachelors,8,63,56,48,31,3.0,7,90,Rural,Manager,28087,1 +59330,Male,31,High School,18,51,58,87,71,0.0,6,61,Urban,Data Analyst,116393,1 +59331,Female,49,Masters,8,10,80,42,77,1.0,6,99,Urban,Manager,65386,0 +59332,Male,24,Diploma,7,51,85,48,15,8.0,0,15,Urban,HR Executive,59352,0 +59333,Male,55,High School,0,52,60,74,37,9.0,0,77,Urban,Manager,130375,1 +59334,Female,35,Bachelors,9,17,3,0,31,5.0,7,9,Urban,Software Engineer,83707,0 +59335,Male,34,Bachelors,16,18,29,35,29,6.0,7,33,Urban,Data Analyst,80463,0 +59336,Male,25,Masters,8,12,49,68,99,9.0,5,57,Urban,Manager,141812,0 +59337,Male,29,Bachelors,19,48,91,20,19,6.0,0,52,Urban,ML Engineer,54852,0 +59338,Male,38,Diploma,6,46,72,58,6,1.0,5,74,Rural,Data Analyst,128740,1 +59339,Male,53,Masters,13,55,8,3,8,3.0,2,82,Urban,Software Engineer,98697,0 +59340,Male,46,Bachelors,14,38,44,22,12,0.0,2,67,Semi-Urban,HR Executive,104117,0 +59341,Female,48,Diploma,3,50,53,42,15,4.0,5,14,Urban,ML Engineer,120064,0 +59342,Male,54,Masters,4,4,27,63,30,7.0,7,67,Urban,Software Engineer,95890,0 +59343,Male,26,Bachelors,12,3,57,18,19,2.0,7,98,Rural,HR Executive,90316,0 +59344,Male,39,Bachelors,3,91,21,62,63,5.0,3,39,Semi-Urban,ML Engineer,31800,0 +59345,Male,47,High School,19,36,0,31,94,5.0,1,48,Urban,Manager,101075,0 +59346,Male,25,Diploma,18,11,29,74,96,5.0,2,61,Urban,Software Engineer,66890,0 +59347,Female,49,Bachelors,13,13,92,22,31,9.0,5,8,Rural,Manager,71406,0 +59348,Male,48,Diploma,3,74,9,52,51,9.0,4,39,Semi-Urban,Manager,115469,0 +59349,Female,41,Bachelors,18,31,42,33,40,6.0,2,26,Rural,Data Analyst,116664,0 +59350,Female,39,Diploma,18,64,72,30,54,7.0,5,52,Semi-Urban,HR Executive,131747,0 +59351,Male,23,PhD,9,88,14,70,91,9.0,1,43,Urban,Data Analyst,136164,0 +59352,Female,26,Bachelors,13,40,61,22,97,1.0,6,13,Urban,Manager,101040,0 +59353,Male,52,Bachelors,6,2,69,59,41,9.0,6,38,Rural,HR Executive,106550,0 +59354,Male,45,Bachelors,2,34,49,28,70,5.0,0,12,Urban,Manager,89491,0 +59355,Male,45,Bachelors,3,60,87,43,76,5.0,7,43,Urban,Software Engineer,114067,0 +59356,Male,51,Diploma,3,63,37,95,1,0.0,1,82,Semi-Urban,Manager,27089,1 +59357,Male,23,Bachelors,16,54,72,6,20,2.0,2,66,Semi-Urban,Data Analyst,53064,0 +59358,Female,26,Masters,15,65,3,0,49,0.0,6,75,Urban,HR Executive,98655,0 +59359,Male,36,Diploma,10,66,68,99,78,9.0,3,67,Rural,HR Executive,50813,1 +59360,Female,33,Bachelors,9,6,84,31,92,1.0,4,23,Urban,Data Analyst,73823,0 +59361,Male,32,High School,5,49,19,15,96,1.0,2,99,Semi-Urban,ML Engineer,103715,0 +59362,Female,43,Diploma,18,47,61,88,63,1.0,3,46,Rural,ML Engineer,21177,1 +59363,Male,38,Masters,0,69,9,1,7,9.0,7,22,Semi-Urban,Software Engineer,106069,0 +59364,Male,56,Masters,9,49,76,43,43,5.0,0,23,Urban,HR Executive,108203,0 +59365,Male,56,Diploma,8,89,27,89,60,4.0,6,66,Semi-Urban,Data Analyst,21374,1 +59366,Female,31,Bachelors,16,74,8,69,46,7.0,7,44,Urban,ML Engineer,40533,0 +59367,Male,45,Bachelors,5,99,7,48,63,5.0,2,73,Semi-Urban,ML Engineer,124017,0 +59368,Male,40,High School,8,82,47,79,10,5.0,1,15,Semi-Urban,Data Analyst,59336,0 +59369,Male,34,Bachelors,17,25,85,44,95,5.0,3,49,Rural,Manager,84856,0 +59370,Male,49,Bachelors,18,29,0,7,77,6.0,0,11,Urban,Manager,48743,0 +59371,Male,30,Masters,4,2,1,72,98,0.0,0,84,Semi-Urban,Data Analyst,26830,0 +59372,Male,29,Masters,4,81,24,77,54,2.0,1,21,Urban,Manager,148064,0 +59373,Male,56,Diploma,16,78,91,67,52,8.0,7,1,Urban,ML Engineer,24968,1 +59374,Female,33,Diploma,16,42,73,56,31,3.0,2,99,Semi-Urban,Software Engineer,22571,1 +59375,Male,30,Diploma,10,49,24,7,31,0.0,4,24,Urban,ML Engineer,35733,0 +59376,Male,46,Diploma,3,33,84,72,42,8.0,7,0,Rural,HR Executive,37721,0 +59377,Female,51,Diploma,17,20,64,83,58,3.0,2,36,Urban,Manager,89333,0 +59378,Male,29,High School,16,38,28,70,34,1.0,7,15,Urban,Data Analyst,84105,0 +59379,Male,21,Masters,1,2,17,31,82,3.0,3,22,Semi-Urban,Manager,137455,0 +59380,Female,30,Bachelors,6,15,81,48,59,9.0,6,98,Urban,Manager,52764,1 +59381,Male,21,Bachelors,9,31,7,90,27,6.0,4,53,Urban,Data Analyst,94841,0 +59382,Male,58,PhD,7,2,71,57,29,2.0,7,15,Urban,Software Engineer,147550,0 +59383,Female,27,High School,3,25,64,10,21,2.0,1,64,Urban,ML Engineer,142092,0 +59384,Other,21,Masters,6,69,54,26,90,9.0,4,72,Urban,Data Analyst,46552,0 +59385,Male,39,Bachelors,2,88,94,46,97,0.0,1,20,Rural,ML Engineer,23715,1 +59386,Female,36,Bachelors,2,12,43,1,20,7.0,6,44,Urban,ML Engineer,94245,0 +59387,Male,34,Bachelors,5,35,23,16,91,5.0,7,99,Urban,ML Engineer,37436,0 +59388,Male,52,High School,12,58,49,58,87,7.0,6,8,Urban,Manager,33055,0 +59389,Female,48,Masters,0,40,56,68,48,7.0,2,14,Urban,Data Analyst,65766,0 +59390,Female,28,Diploma,14,37,14,99,28,2.0,3,9,Rural,ML Engineer,22795,0 +59391,Male,53,Bachelors,15,4,59,73,86,8.0,6,14,Urban,ML Engineer,94984,0 +59392,Male,29,Bachelors,6,61,72,5,47,0.0,5,50,Urban,HR Executive,120028,0 +59393,Female,23,Bachelors,3,67,34,98,23,2.0,2,66,Urban,HR Executive,91382,1 +59394,Male,50,Masters,12,1,39,80,0,7.0,5,73,Semi-Urban,Software Engineer,88061,0 +59395,Male,29,Diploma,14,65,5,69,17,4.0,7,77,Semi-Urban,Software Engineer,89869,0 +59396,Other,43,Bachelors,12,51,89,32,37,0.0,0,70,Semi-Urban,Software Engineer,76369,1 +59397,Male,31,Masters,6,28,10,44,9,1.0,5,8,Semi-Urban,Software Engineer,146634,0 +59398,Female,55,Diploma,14,99,28,48,5,6.0,4,88,Rural,ML Engineer,59532,1 +59399,Male,42,Masters,2,52,99,86,74,6.0,6,21,Semi-Urban,Data Analyst,99374,1 +59400,Male,33,High School,12,30,51,70,34,0.0,3,58,Urban,Data Analyst,63308,0 +59401,Male,31,Diploma,12,98,8,62,87,5.0,6,3,Rural,HR Executive,96552,0 +59402,Male,43,High School,9,40,86,42,35,0.0,1,61,Urban,HR Executive,75190,0 +59403,Male,34,Bachelors,16,84,23,11,50,5.0,6,9,Urban,Data Analyst,130250,0 +59404,Female,45,Bachelors,5,66,1,9,26,3.0,5,49,Semi-Urban,ML Engineer,23992,0 +59405,Female,33,Bachelors,17,23,83,91,31,1.0,1,76,Rural,Manager,63630,1 +59406,Female,40,Bachelors,2,37,42,67,78,8.0,5,26,Urban,Manager,69341,0 +59407,Female,24,Bachelors,4,4,90,38,44,6.0,3,62,Urban,ML Engineer,64011,0 +59408,Male,23,Diploma,15,25,29,84,54,8.0,4,63,Semi-Urban,ML Engineer,29634,0 +59409,Other,29,Bachelors,13,62,9,59,91,9.0,2,9,Semi-Urban,ML Engineer,49088,0 +59410,Male,33,Diploma,13,89,17,2,32,2.0,6,88,Urban,HR Executive,28233,0 +59411,Male,45,PhD,5,90,31,89,62,7.0,3,39,Urban,Software Engineer,141520,1 +59412,Female,24,Diploma,9,33,48,51,74,1.0,3,24,Urban,Manager,87973,0 +59413,Male,57,High School,7,97,66,59,78,9.0,2,48,Urban,Data Analyst,67026,1 +59414,Male,26,High School,15,13,75,68,43,4.0,3,8,Rural,Software Engineer,56298,0 +59415,Female,48,Bachelors,1,32,21,88,10,1.0,4,0,Semi-Urban,Software Engineer,129982,0 +59416,Male,47,Diploma,19,28,58,3,47,1.0,0,16,Rural,Software Engineer,37000,0 +59417,Female,53,PhD,5,38,44,3,78,3.0,7,60,Urban,Software Engineer,65449,0 +59418,Female,45,PhD,8,76,7,72,45,2.0,3,1,Urban,HR Executive,66362,0 +59419,Other,31,High School,19,57,65,60,42,0.0,6,90,Urban,Data Analyst,134084,1 +59420,Male,56,Bachelors,19,49,4,18,54,2.0,3,44,Urban,ML Engineer,95717,0 +59421,Male,46,Bachelors,10,5,77,48,5,1.0,4,48,Semi-Urban,Data Analyst,50201,0 +59422,Female,46,Bachelors,2,33,90,53,97,0.0,4,91,Urban,HR Executive,89926,1 +59423,Male,44,Diploma,14,11,49,65,84,5.0,0,46,Semi-Urban,HR Executive,30943,0 +59424,Male,21,Masters,13,0,93,83,74,2.0,2,10,Urban,ML Engineer,87952,0 +59425,Male,33,PhD,7,32,41,53,29,8.0,1,85,Urban,Software Engineer,60921,0 +59426,Male,23,Bachelors,4,19,2,62,15,2.0,7,45,Semi-Urban,Manager,113022,0 +59427,Female,34,Bachelors,2,31,90,98,44,4.0,2,94,Rural,Data Analyst,51665,1 +59428,Female,35,Bachelors,1,75,11,0,86,7.0,0,75,Semi-Urban,Software Engineer,129142,0 +59429,Male,59,Masters,19,26,81,46,29,3.0,2,78,Urban,Software Engineer,127405,0 +59430,Male,57,Masters,12,7,12,90,65,6.0,0,51,Semi-Urban,HR Executive,102559,0 +59431,Male,55,Masters,1,94,40,30,14,4.0,2,42,Semi-Urban,HR Executive,148584,0 +59432,Male,21,Bachelors,18,77,44,52,77,2.0,6,61,Rural,ML Engineer,130961,0 +59433,Male,23,Bachelors,16,71,34,55,67,0.0,5,45,Rural,Software Engineer,51048,0 +59434,Male,32,Masters,17,24,69,2,57,8.0,4,27,Semi-Urban,Data Analyst,86219,0 +59435,Other,31,High School,5,99,3,83,76,5.0,4,92,Semi-Urban,Manager,106976,1 +59436,Female,38,Bachelors,17,55,16,35,31,9.0,5,42,Semi-Urban,Manager,45390,0 +59437,Male,57,Bachelors,6,11,23,98,39,6.0,7,54,Urban,Software Engineer,94742,0 +59438,Female,25,Bachelors,7,44,44,72,5,4.0,4,88,Semi-Urban,Manager,97258,1 +59439,Male,51,High School,12,88,53,30,8,0.0,2,33,Urban,ML Engineer,85321,0 +59440,Female,45,Bachelors,17,54,36,42,22,1.0,7,25,Urban,Data Analyst,30256,0 +59441,Female,41,Bachelors,2,60,6,42,6,5.0,2,22,Urban,Manager,123185,0 +59442,Male,38,High School,1,22,68,75,13,1.0,6,12,Urban,Manager,125569,0 +59443,Male,51,Bachelors,12,27,3,50,2,4.0,6,97,Urban,Data Analyst,142667,0 +59444,Male,44,High School,10,72,94,87,5,3.0,4,14,Urban,Software Engineer,140927,1 +59445,Male,51,Bachelors,9,15,51,30,84,5.0,0,7,Urban,ML Engineer,73074,0 +59446,Female,22,Bachelors,10,98,32,23,49,4.0,0,98,Urban,Manager,144100,1 +59447,Male,30,Bachelors,16,30,66,76,77,0.0,3,31,Semi-Urban,ML Engineer,34283,0 +59448,Male,40,High School,1,1,57,32,80,8.0,2,28,Urban,Data Analyst,63941,0 +59449,Male,55,Bachelors,17,67,63,48,32,5.0,4,89,Urban,ML Engineer,140180,1 +59450,Female,33,Bachelors,7,63,44,52,22,3.0,1,83,Urban,ML Engineer,85336,1 +59451,Male,38,Bachelors,2,91,83,27,76,6.0,6,50,Semi-Urban,Software Engineer,25688,1 +59452,Male,32,Bachelors,1,13,30,63,61,2.0,1,70,Semi-Urban,ML Engineer,142345,0 +59453,Male,42,Diploma,18,42,11,0,6,9.0,5,79,Rural,Software Engineer,119067,0 +59454,Male,32,Diploma,7,56,1,91,31,7.0,1,58,Urban,Data Analyst,82537,0 +59455,Male,51,Diploma,16,73,17,45,47,0.0,1,42,Urban,HR Executive,125123,0 +59456,Other,56,Bachelors,1,19,35,27,33,3.0,3,50,Urban,Software Engineer,127575,0 +59457,Male,22,Masters,9,4,29,45,3,4.0,4,92,Semi-Urban,ML Engineer,93159,0 +59458,Male,51,Masters,8,48,35,36,95,1.0,1,79,Urban,Software Engineer,51300,0 +59459,Male,46,Masters,2,69,72,52,22,0.0,6,0,Urban,Software Engineer,74815,0 +59460,Female,21,Bachelors,13,75,29,27,59,7.0,0,33,Semi-Urban,Manager,78513,0 +59461,Male,50,Bachelors,16,9,19,76,86,1.0,4,38,Semi-Urban,Software Engineer,50275,0 +59462,Female,42,Masters,18,86,36,70,99,2.0,0,94,Urban,Manager,103588,1 +59463,Female,53,Bachelors,12,57,99,41,14,1.0,4,41,Rural,Manager,62090,0 +59464,Female,48,Diploma,9,75,6,56,90,6.0,7,50,Urban,Software Engineer,46257,0 +59465,Male,23,,1,14,0,58,35,9.0,3,30,Urban,Software Engineer,63590,0 +59466,Male,31,Bachelors,2,3,94,8,6,8.0,4,62,Urban,Data Analyst,22127,0 +59467,Female,39,Bachelors,11,47,26,24,67,5.0,5,38,Urban,Software Engineer,67006,0 +59468,Male,53,PhD,16,76,95,45,75,5.0,0,35,Urban,Manager,27202,1 +59469,Female,24,Bachelors,6,80,38,39,83,2.0,0,14,Urban,ML Engineer,118437,0 +59470,Male,42,Bachelors,2,34,42,71,76,4.0,2,8,Urban,ML Engineer,120168,0 +59471,Male,32,Bachelors,0,56,52,0,66,7.0,2,0,Semi-Urban,Data Analyst,68900,0 +59472,Female,49,Bachelors,2,69,87,37,87,6.0,4,29,Urban,HR Executive,30173,0 +59473,Female,55,Bachelors,11,63,44,46,13,4.0,7,25,Urban,Data Analyst,48857,0 +59474,Male,47,Masters,18,81,48,51,90,6.0,3,72,Urban,Manager,135977,1 +59475,Male,55,Bachelors,1,35,68,52,67,1.0,6,36,Urban,ML Engineer,107688,0 +59476,Male,39,Diploma,17,80,8,52,89,2.0,1,63,Semi-Urban,Software Engineer,80475,0 +59477,Male,31,Bachelors,0,35,78,95,14,8.0,2,50,Semi-Urban,ML Engineer,138790,1 +59478,Male,53,High School,2,88,51,47,85,0.0,4,25,Semi-Urban,Software Engineer,73954,0 +59479,Male,40,Bachelors,3,14,10,31,96,2.0,7,16,Semi-Urban,Software Engineer,71790,0 +59480,Other,49,Diploma,9,28,27,66,45,2.0,2,83,Urban,ML Engineer,117455,0 +59481,Male,54,High School,2,9,10,92,11,1.0,6,50,Urban,Data Analyst,81621,0 +59482,Female,48,Diploma,17,62,20,7,52,3.0,1,11,Urban,Software Engineer,27040,0 +59483,Male,43,Bachelors,17,76,0,32,45,2.0,1,79,Urban,Manager,97054,0 +59484,Male,41,Diploma,12,82,65,46,62,4.0,7,80,Semi-Urban,Data Analyst,138579,1 +59485,Male,41,Bachelors,17,39,34,40,48,9.0,4,58,Urban,Data Analyst,99774,0 +59486,Male,29,Bachelors,7,55,8,45,44,5.0,2,88,Rural,ML Engineer,64908,0 +59487,Female,50,Masters,9,25,17,34,68,1.0,0,8,Rural,ML Engineer,32861,0 +59488,Other,24,Bachelors,14,60,46,88,1,0.0,1,65,Urban,Data Analyst,83499,1 +59489,Male,23,High School,18,63,0,65,39,5.0,3,78,Rural,Software Engineer,126496,0 +59490,Female,58,Bachelors,6,69,85,19,67,4.0,6,41,Rural,Software Engineer,56263,0 +59491,Male,25,Masters,14,34,35,43,62,6.0,5,62,Urban,Software Engineer,108111,0 +59492,Male,43,High School,1,46,4,76,15,2.0,6,27,Urban,Software Engineer,132433,0 +59493,Male,59,High School,2,1,44,85,45,4.0,6,36,Urban,HR Executive,88047,0 +59494,Female,54,PhD,11,54,84,87,56,0.0,5,60,Urban,Software Engineer,58295,1 +59495,Male,35,Masters,0,5,46,67,17,1.0,7,92,Semi-Urban,Software Engineer,38348,0 +59496,Male,23,Bachelors,7,69,9,4,85,0.0,7,46,Urban,Manager,112399,0 +59497,Other,54,Bachelors,16,61,81,66,74,3.0,6,12,Urban,Software Engineer,34835,0 +59498,Male,21,Diploma,11,87,77,9,19,3.0,2,33,Rural,HR Executive,25738,0 +59499,Male,31,Bachelors,8,63,18,48,82,5.0,3,42,Urban,ML Engineer,42956,0 +59500,Female,37,Diploma,2,63,68,35,8,6.0,0,82,Rural,ML Engineer,142915,1 +59501,Male,57,Bachelors,5,62,91,22,55,4.0,4,50,Urban,HR Executive,78339,0 +59502,Male,46,High School,12,40,83,84,12,7.0,1,33,Rural,Data Analyst,94681,1 +59503,Male,49,Diploma,13,12,15,80,60,8.0,1,60,Urban,Data Analyst,80413,0 +59504,Female,52,Bachelors,4,49,47,68,93,1.0,0,8,Urban,Data Analyst,126784,0 +59505,Male,34,Bachelors,10,36,46,89,24,2.0,4,97,Urban,Software Engineer,81334,1 +59506,Male,39,Masters,9,7,80,10,0,4.0,0,16,Semi-Urban,Software Engineer,88254,0 +59507,Male,59,High School,1,79,19,87,42,0.0,3,8,Urban,HR Executive,127878,0 +59508,Male,52,Bachelors,15,30,62,49,31,1.0,5,47,Urban,ML Engineer,49432,0 +59509,Female,27,Bachelors,6,99,60,16,23,8.0,0,75,Rural,HR Executive,114468,1 +59510,Male,24,PhD,13,95,2,45,82,5.0,2,64,Urban,Software Engineer,115745,0 +59511,Male,21,Bachelors,6,40,90,30,11,2.0,4,88,Urban,Data Analyst,125841,1 +59512,Male,36,High School,2,63,75,93,41,8.0,0,93,Urban,ML Engineer,32997,1 +59513,Other,44,Diploma,11,19,26,50,56,4.0,2,31,Urban,Data Analyst,85031,0 +59514,Male,45,Bachelors,10,40,83,34,44,0.0,2,16,Urban,Data Analyst,58337,0 +59515,Male,21,Bachelors,8,72,73,9,45,7.0,6,56,Semi-Urban,Manager,53819,0 +59516,Female,57,Bachelors,1,43,71,53,13,0.0,1,90,Semi-Urban,ML Engineer,30986,1 +59517,Female,42,Bachelors,14,84,51,3,72,0.0,5,63,Urban,Manager,125246,0 +59518,Female,42,Diploma,9,73,47,64,22,9.0,5,62,Semi-Urban,Data Analyst,142919,1 +59519,Male,41,Masters,19,68,10,66,52,7.0,4,49,Urban,ML Engineer,70589,0 +59520,Male,59,Bachelors,1,3,74,90,22,6.0,2,10,Urban,HR Executive,112981,0 +59521,Male,53,Bachelors,18,1,70,93,35,8.0,0,45,Semi-Urban,ML Engineer,84642,0 +59522,Female,49,Bachelors,1,67,40,32,54,2.0,4,20,Urban,ML Engineer,67987,0 +59523,Male,45,Masters,3,29,4,52,5,8.0,7,25,Semi-Urban,Software Engineer,23630,0 +59524,Male,51,Masters,17,5,7,81,1,6.0,4,17,Rural,ML Engineer,109209,0 +59525,Male,27,Bachelors,13,21,73,8,86,2.0,5,9,Urban,ML Engineer,95504,0 +59526,Female,50,Masters,12,55,62,74,25,8.0,4,86,Semi-Urban,Data Analyst,101221,1 +59527,Female,29,Bachelors,5,8,73,84,58,6.0,7,3,Urban,ML Engineer,149239,0 +59528,Male,44,Diploma,3,16,14,41,2,7.0,4,84,Semi-Urban,Software Engineer,45506,0 +59529,Male,32,Diploma,5,61,45,92,22,0.0,5,87,Urban,Manager,117894,1 +59530,Male,33,PhD,12,85,22,86,23,5.0,6,69,Rural,Software Engineer,123358,1 +59531,Male,43,Bachelors,14,56,34,30,63,0.0,5,37,Rural,Software Engineer,69100,0 +59532,Female,33,Diploma,6,61,17,15,42,9.0,5,18,Urban,Software Engineer,38704,0 +59533,Female,50,High School,18,55,69,8,0,5.0,1,3,Semi-Urban,Manager,118827,0 +59534,Female,47,PhD,10,70,68,17,4,3.0,1,4,Urban,ML Engineer,55009,0 +59535,Female,53,Bachelors,9,47,27,32,87,7.0,2,56,Rural,Data Analyst,71737,0 +59536,Male,44,Diploma,16,34,6,81,52,5.0,3,50,Rural,Software Engineer,59918,0 +59537,Female,35,Diploma,19,27,59,58,15,5.0,2,40,Urban,Software Engineer,66653,0 +59538,Female,36,Bachelors,1,53,42,74,82,2.0,5,13,Semi-Urban,Software Engineer,42098,0 +59539,Male,40,Bachelors,11,2,0,5,48,1.0,3,63,Rural,Software Engineer,115617,0 +59540,Other,41,Bachelors,12,83,26,45,16,9.0,3,43,Urban,ML Engineer,22703,0 +59541,Female,39,PhD,14,27,24,68,22,0.0,7,50,Semi-Urban,Software Engineer,80853,0 +59542,Female,39,Bachelors,16,18,49,79,55,7.0,3,49,Urban,Manager,97647,0 +59543,Male,45,Bachelors,19,37,40,41,14,4.0,2,27,Urban,Manager,37272,0 +59544,Male,50,Masters,1,30,69,30,94,0.0,4,79,Semi-Urban,Software Engineer,50876,0 +59545,Female,29,Bachelors,18,16,62,81,8,3.0,4,55,Urban,Software Engineer,60570,0 +59546,Male,35,Masters,0,26,41,30,46,4.0,1,16,Semi-Urban,ML Engineer,68359,0 +59547,Female,30,Bachelors,6,59,75,30,26,0.0,5,71,Urban,ML Engineer,76958,0 +59548,Female,52,High School,3,34,60,42,48,6.0,3,94,Urban,ML Engineer,21260,0 +59549,Female,56,Diploma,0,18,68,48,59,1.0,6,33,Urban,ML Engineer,109325,0 +59550,Male,27,Diploma,15,46,34,5,86,9.0,6,47,Urban,HR Executive,130385,0 +59551,Male,53,Masters,2,33,96,34,57,1.0,2,39,Rural,Manager,94390,0 +59552,Female,30,Bachelors,6,50,34,21,78,7.0,3,40,Urban,Software Engineer,33752,0 +59553,Male,57,Masters,17,2,38,96,83,6.0,1,11,Urban,Data Analyst,35912,0 +59554,Female,26,Bachelors,15,94,20,45,24,4.0,1,87,Urban,Data Analyst,93548,1 +59555,Female,35,Bachelors,9,32,1,47,50,3.0,2,75,Rural,ML Engineer,40034,0 +59556,Male,37,High School,18,28,38,4,96,8.0,7,90,Urban,Software Engineer,61630,0 +59557,Male,28,Masters,8,83,19,68,13,8.0,0,8,Rural,Software Engineer,56976,0 +59558,Female,58,Masters,7,45,60,35,2,7.0,0,40,Urban,ML Engineer,99258,0 +59559,Male,29,Bachelors,1,73,65,16,56,4.0,0,58,Urban,Data Analyst,135294,0 +59560,Male,41,Bachelors,5,86,30,78,31,0.0,6,74,Rural,HR Executive,123216,1 +59561,Female,47,Diploma,19,85,45,16,77,6.0,7,45,Semi-Urban,Manager,94127,0 +59562,Male,24,Diploma,0,54,72,32,2,2.0,0,10,Semi-Urban,ML Engineer,76090,0 +59563,Female,37,Bachelors,8,1,28,65,65,2.0,4,96,Rural,Manager,28492,0 +59564,Male,38,Bachelors,16,25,27,23,93,4.0,1,53,Rural,ML Engineer,59369,0 +59565,Female,44,Bachelors,14,48,72,1,83,4.0,1,26,Urban,ML Engineer,115453,0 +59566,Male,50,Diploma,11,21,81,15,22,5.0,2,44,Urban,HR Executive,70008,0 +59567,Male,56,Diploma,8,79,83,49,74,6.0,5,28,Urban,Data Analyst,47837,1 +59568,Other,55,Bachelors,4,78,1,24,34,3.0,1,23,Rural,ML Engineer,123446,0 +59569,Male,31,Bachelors,7,79,9,87,80,1.0,4,81,Semi-Urban,Software Engineer,73202,1 +59570,Male,43,Bachelors,19,73,57,42,60,9.0,3,14,Urban,Data Analyst,135252,0 +59571,Female,55,Bachelors,10,92,44,56,86,0.0,5,64,Urban,ML Engineer,114174,1 +59572,Female,33,Bachelors,10,77,77,40,58,2.0,0,47,Urban,Software Engineer,129605,1 +59573,Other,27,Diploma,18,12,79,90,78,1.0,7,31,Urban,Manager,144139,0 +59574,Male,57,Diploma,1,23,55,9,13,5.0,3,75,Semi-Urban,Manager,74952,0 +59575,Male,32,High School,5,42,90,71,21,6.0,2,10,Semi-Urban,Software Engineer,147958,0 +59576,Male,44,Diploma,12,29,6,27,70,1.0,6,81,Urban,HR Executive,126812,0 +59577,Male,47,Diploma,16,64,0,21,80,7.0,4,52,Urban,HR Executive,34231,0 +59578,Male,42,Diploma,10,89,75,41,45,3.0,6,21,Semi-Urban,Data Analyst,134803,0 +59579,Male,23,PhD,10,43,64,31,2,9.0,6,58,Urban,HR Executive,107655,0 +59580,Female,34,PhD,16,68,54,61,52,0.0,4,50,Urban,Software Engineer,54589,0 +59581,Female,28,High School,11,47,58,47,17,5.0,5,88,Urban,HR Executive,123151,0 +59582,Male,33,Diploma,3,11,32,59,74,6.0,7,52,Semi-Urban,Manager,148939,0 +59583,Female,35,High School,9,67,27,62,77,8.0,0,65,Urban,HR Executive,147346,0 +59584,Male,31,Masters,10,33,39,43,64,4.0,6,8,Semi-Urban,Software Engineer,45740,0 +59585,Female,39,High School,15,36,17,95,13,5.0,2,8,Semi-Urban,ML Engineer,89471,0 +59586,Female,30,Diploma,5,96,5,91,49,7.0,2,36,Urban,HR Executive,105812,0 +59587,Male,54,Bachelors,7,34,63,88,79,4.0,7,46,Urban,Manager,99349,0 +59588,Male,37,Diploma,4,77,35,52,3,4.0,6,66,Urban,HR Executive,44729,0 +59589,Male,21,Bachelors,14,9,30,51,97,2.0,5,72,Rural,HR Executive,66723,0 +59590,Female,27,Bachelors,2,93,22,0,99,4.0,6,18,Semi-Urban,Data Analyst,115651,0 +59591,Male,31,Bachelors,0,7,53,66,14,0.0,6,8,Rural,ML Engineer,55380,0 +59592,Female,26,Diploma,4,34,59,82,21,7.0,7,74,Urban,Data Analyst,33400,1 +59593,Male,53,High School,5,69,59,42,98,8.0,5,94,Urban,Manager,139482,1 +59594,Male,45,Bachelors,17,65,88,55,52,4.0,1,60,Rural,HR Executive,89272,1 +59595,Other,25,Bachelors,13,11,1,39,97,2.0,3,49,Rural,ML Engineer,31032,0 +59596,Female,58,Bachelors,16,14,30,61,73,0.0,5,31,Semi-Urban,Manager,38117,0 +59597,Male,53,Bachelors,2,24,45,87,73,0.0,0,8,Urban,Software Engineer,88075,0 +59598,Male,39,Masters,9,5,27,32,99,5.0,4,63,Urban,Manager,66506,0 +59599,Male,32,Bachelors,16,62,95,57,27,4.0,6,6,Rural,ML Engineer,41833,0 +59600,Female,53,Masters,15,79,37,97,36,0.0,3,55,Urban,Data Analyst,60959,1 +59601,Male,50,High School,2,32,17,1,85,6.0,6,48,Semi-Urban,Manager,58615,0 +59602,Other,43,Bachelors,7,41,77,47,38,5.0,5,69,Urban,ML Engineer,124255,0 +59603,Male,43,Bachelors,19,64,5,60,97,3.0,2,44,Urban,HR Executive,31694,0 +59604,Male,50,Masters,18,27,3,10,67,0.0,3,54,Semi-Urban,Manager,38122,0 +59605,Female,46,Diploma,7,62,14,34,52,7.0,5,29,Urban,HR Executive,72205,0 +59606,Male,49,Bachelors,19,12,43,37,47,3.0,2,56,Semi-Urban,ML Engineer,127854,0 +59607,Female,36,Bachelors,0,97,41,47,42,2.0,2,95,Urban,Software Engineer,143617,1 +59608,Male,59,Diploma,17,17,76,12,7,1.0,1,59,Urban,HR Executive,110562,0 +59609,Other,41,Bachelors,5,64,34,80,90,2.0,7,80,Rural,Software Engineer,63855,1 +59610,Female,29,Bachelors,18,91,71,48,12,6.0,2,73,Urban,Software Engineer,41827,1 +59611,Female,57,High School,16,19,86,26,23,3.0,2,38,Urban,Manager,147030,0 +59612,Male,38,Bachelors,6,3,79,99,92,4.0,6,15,Urban,ML Engineer,60317,0 +59613,Male,23,Bachelors,11,88,69,8,65,3.0,6,27,Urban,Manager,46074,0 +59614,Male,52,High School,5,73,32,12,53,2.0,4,34,Semi-Urban,HR Executive,139993,0 +59615,Other,52,Bachelors,9,37,42,38,51,1.0,0,61,Urban,ML Engineer,96628,0 +59616,Male,56,Bachelors,7,83,90,10,55,6.0,3,96,Urban,HR Executive,102622,1 +59617,Male,26,Masters,0,36,29,12,73,2.0,0,75,Urban,HR Executive,57628,0 +59618,Other,23,Bachelors,19,86,1,21,87,3.0,1,6,Semi-Urban,Data Analyst,46695,0 +59619,Male,40,Masters,11,35,76,91,10,7.0,6,56,Semi-Urban,HR Executive,42672,1 +59620,Male,39,High School,14,11,15,52,80,1.0,2,43,Urban,Software Engineer,139173,0 +59621,Female,25,Bachelors,19,86,44,43,54,6.0,6,4,Rural,Software Engineer,140890,0 +59622,Female,30,Bachelors,18,27,89,60,11,6.0,1,3,Rural,Data Analyst,118636,0 +59623,Male,59,PhD,7,43,8,59,5,4.0,0,60,Urban,Manager,59372,0 +59624,Female,31,Bachelors,2,20,11,91,61,6.0,5,81,Urban,Data Analyst,72677,0 +59625,Male,52,Diploma,17,79,66,8,11,9.0,3,30,Urban,Data Analyst,58745,0 +59626,Female,37,Masters,6,32,1,50,9,9.0,1,12,Urban,Data Analyst,124209,0 +59627,Male,40,Bachelors,7,76,81,45,50,3.0,0,42,Rural,Data Analyst,127557,1 +59628,Male,50,Bachelors,12,98,11,91,16,5.0,0,21,Urban,Software Engineer,25347,0 +59629,Female,36,PhD,2,22,79,12,68,9.0,5,80,Rural,Manager,41485,0 +59630,Male,24,High School,17,92,11,38,68,5.0,4,22,Semi-Urban,Software Engineer,125307,0 +59631,Male,40,Masters,7,0,5,32,24,5.0,1,77,Rural,ML Engineer,148572,0 +59632,Male,55,High School,5,3,56,90,73,9.0,7,93,Semi-Urban,Manager,146738,1 +59633,Female,36,Bachelors,6,64,79,4,49,5.0,4,40,Semi-Urban,Manager,43646,0 +59634,Male,43,Diploma,0,50,39,45,9,4.0,7,73,Urban,ML Engineer,53667,0 +59635,Male,58,Bachelors,14,35,87,47,21,2.0,6,15,Urban,Software Engineer,147725,0 +59636,Male,41,Masters,16,10,23,18,45,6.0,3,18,Urban,ML Engineer,122349,0 +59637,Male,41,Diploma,11,8,2,78,1,9.0,3,26,Urban,Software Engineer,132402,0 +59638,Female,34,Bachelors,10,43,40,53,55,0.0,4,52,Urban,ML Engineer,137861,0 +59639,Female,30,Diploma,18,29,42,50,65,5.0,7,11,Urban,ML Engineer,148413,0 +59640,Female,50,High School,7,78,93,36,74,8.0,7,66,Semi-Urban,ML Engineer,32250,1 +59641,Male,42,Diploma,16,60,12,70,19,2.0,7,93,Rural,Software Engineer,66721,1 +59642,Male,26,Masters,3,11,23,47,50,7.0,4,64,Urban,HR Executive,133541,0 +59643,Male,40,Diploma,9,2,18,76,47,7.0,5,73,Urban,Data Analyst,115150,0 +59644,Female,43,High School,5,35,46,18,98,0.0,7,99,Urban,Data Analyst,118046,0 +59645,Male,40,Diploma,2,70,63,21,5,9.0,2,70,Semi-Urban,Data Analyst,104892,0 +59646,Male,37,Diploma,19,67,87,21,96,0.0,3,19,Urban,HR Executive,31590,0 +59647,Male,33,Bachelors,6,81,89,86,27,4.0,0,22,Urban,Software Engineer,54468,1 +59648,Female,53,Diploma,1,57,75,36,5,8.0,3,60,Urban,HR Executive,134334,0 +59649,Male,44,Bachelors,17,17,32,16,29,6.0,5,97,Semi-Urban,HR Executive,78587,0 +59650,Male,58,Masters,15,85,66,14,58,7.0,5,47,Semi-Urban,Data Analyst,109762,0 +59651,Male,55,Masters,14,53,27,22,71,3.0,3,47,Urban,Data Analyst,31069,0 +59652,Female,54,Bachelors,4,13,23,72,86,2.0,1,81,Rural,Data Analyst,105586,0 +59653,Male,42,High School,6,47,37,8,37,2.0,5,72,Urban,Software Engineer,137348,0 +59654,Male,52,Bachelors,12,30,67,9,15,2.0,0,49,Urban,Manager,21481,0 +59655,Male,36,Bachelors,8,79,98,30,59,9.0,4,90,Urban,ML Engineer,39869,1 +59656,Male,52,Masters,1,50,99,40,56,2.0,1,58,Rural,Data Analyst,99465,1 +59657,Male,56,Diploma,7,98,0,57,66,1.0,3,34,Urban,ML Engineer,51013,0 +59658,Female,50,Bachelors,4,82,37,54,32,5.0,1,63,Semi-Urban,HR Executive,138706,0 +59659,Male,27,Diploma,18,70,31,54,24,0.0,4,94,Rural,HR Executive,29231,1 +59660,Female,25,PhD,15,69,82,75,21,5.0,3,21,Urban,Manager,77446,1 +59661,Female,21,High School,4,50,53,47,55,2.0,7,60,Semi-Urban,HR Executive,27476,0 +59662,Male,59,Bachelors,17,70,76,35,25,6.0,6,75,Urban,Manager,112455,1 +59663,Other,40,High School,0,53,9,9,31,2.0,5,25,Semi-Urban,Manager,73089,0 +59664,Female,58,Bachelors,8,41,47,24,44,8.0,4,31,Urban,HR Executive,100647,0 +59665,Male,49,Bachelors,11,75,63,58,33,2.0,4,73,Urban,HR Executive,63207,1 +59666,Male,30,Diploma,12,64,25,82,50,3.0,2,9,Rural,HR Executive,67327,0 +59667,Male,28,Bachelors,18,95,23,51,61,5.0,6,72,Rural,Software Engineer,51571,1 +59668,Female,49,Bachelors,13,75,81,52,34,0.0,2,72,Urban,Data Analyst,32021,1 +59669,Female,59,Bachelors,8,0,50,33,3,2.0,1,36,Urban,Data Analyst,117989,0 +59670,Female,58,Bachelors,12,90,18,31,17,6.0,6,31,Urban,Software Engineer,24886,0 +59671,Male,24,High School,10,21,32,7,16,5.0,6,22,Semi-Urban,ML Engineer,38666,0 +59672,Female,58,Diploma,4,28,52,15,86,6.0,0,87,Semi-Urban,Software Engineer,82535,0 +59673,Male,51,Diploma,8,94,22,74,28,2.0,6,48,Urban,ML Engineer,124926,1 +59674,Male,36,High School,17,20,8,59,0,7.0,5,40,Urban,Data Analyst,101114,0 +59675,Female,24,Bachelors,11,72,74,35,27,4.0,2,67,Urban,HR Executive,52723,1 +59676,Other,33,Bachelors,15,67,60,65,47,8.0,2,8,Rural,HR Executive,63981,0 +59677,Male,21,Masters,9,29,61,24,25,3.0,4,66,Urban,Data Analyst,148402,0 +59678,Male,42,Bachelors,2,51,71,19,57,5.0,2,78,Semi-Urban,Manager,29983,0 +59679,Male,22,Bachelors,12,72,89,70,46,3.0,6,11,Urban,Software Engineer,136280,1 +59680,Other,45,Masters,11,85,36,75,31,1.0,6,55,Rural,Data Analyst,53608,1 +59681,Female,44,Diploma,2,51,49,83,52,3.0,4,10,Semi-Urban,HR Executive,89031,0 +59682,Female,26,Masters,17,65,94,73,59,8.0,6,83,Rural,ML Engineer,39549,1 +59683,Male,41,High School,10,66,77,76,91,6.0,6,74,Urban,ML Engineer,120235,1 +59684,Male,40,Bachelors,10,36,2,67,57,2.0,4,4,Urban,HR Executive,149059,0 +59685,Male,26,Diploma,8,75,30,86,98,7.0,1,91,Urban,Data Analyst,21149,1 +59686,Male,33,High School,0,52,34,62,42,3.0,4,24,Urban,Data Analyst,48029,0 +59687,Female,43,High School,19,67,2,73,24,7.0,0,72,Semi-Urban,ML Engineer,87999,0 +59688,Male,34,Bachelors,13,5,36,60,12,6.0,2,80,Semi-Urban,Data Analyst,94307,0 +59689,Male,24,Bachelors,1,94,75,51,65,2.0,2,34,Urban,Data Analyst,120280,1 +59690,Female,26,Diploma,8,80,71,78,73,7.0,6,17,Urban,ML Engineer,90567,1 +59691,Male,44,Diploma,2,97,15,5,82,4.0,1,10,Urban,HR Executive,64829,0 +59692,Male,49,Bachelors,6,41,78,26,13,1.0,1,44,Rural,Software Engineer,133304,0 +59693,Male,42,Masters,7,62,89,67,70,0.0,2,21,Urban,ML Engineer,125818,1 +59694,Female,54,High School,19,37,49,83,87,6.0,5,78,Urban,Data Analyst,92714,1 +59695,Male,33,Masters,15,91,31,67,34,8.0,5,46,Urban,HR Executive,39816,1 +59696,Male,25,Bachelors,13,77,53,49,9,4.0,6,56,Semi-Urban,Software Engineer,143352,1 +59697,Female,45,Masters,12,58,86,8,44,0.0,3,96,Urban,Manager,111296,1 +59698,Female,51,Bachelors,13,85,7,34,98,0.0,2,79,Urban,Software Engineer,119096,0 +59699,Male,57,Bachelors,18,9,96,72,96,9.0,0,67,Semi-Urban,HR Executive,47065,1 +59700,Male,40,Bachelors,7,37,60,88,12,5.0,2,64,Urban,Data Analyst,53946,1 +59701,Female,57,High School,8,17,88,41,75,3.0,1,56,Rural,Software Engineer,69989,0 +59702,Male,44,PhD,18,14,10,2,16,5.0,7,84,Urban,Data Analyst,98389,0 +59703,Female,39,Masters,10,51,89,68,92,6.0,1,70,Semi-Urban,Software Engineer,100333,1 +59704,Female,59,Bachelors,19,61,24,40,13,4.0,2,84,Rural,HR Executive,103362,0 +59705,Male,40,Bachelors,1,15,30,23,82,5.0,1,93,Urban,Data Analyst,53148,0 +59706,Male,54,Diploma,6,65,51,70,64,6.0,5,0,Rural,ML Engineer,63414,0 +59707,Male,44,Bachelors,17,57,69,74,86,0.0,3,24,Urban,ML Engineer,65149,0 +59708,Male,27,PhD,11,34,50,2,47,6.0,0,29,Urban,Data Analyst,108332,0 +59709,Male,32,Diploma,16,46,39,73,80,8.0,1,21,Semi-Urban,Manager,124537,0 +59710,Male,32,Diploma,7,87,23,80,64,8.0,5,67,Rural,ML Engineer,96857,1 +59711,Female,46,Diploma,16,78,91,60,75,5.0,4,66,Urban,Data Analyst,41837,1 +59712,Female,47,High School,2,6,43,2,84,2.0,7,83,Semi-Urban,Manager,49553,0 +59713,Male,43,Diploma,1,35,78,3,29,0.0,7,21,Semi-Urban,HR Executive,148142,0 +59714,Female,57,Diploma,3,99,62,63,17,5.0,1,63,Rural,Data Analyst,47627,1 +59715,Male,52,Diploma,4,22,72,94,10,6.0,6,63,Semi-Urban,Manager,52684,1 +59716,Male,39,Bachelors,18,9,9,76,9,1.0,3,83,Rural,Data Analyst,47063,0 +59717,Male,39,Masters,14,26,81,14,43,8.0,3,96,Semi-Urban,HR Executive,144432,0 +59718,Female,24,Bachelors,6,29,44,1,24,3.0,4,90,Urban,HR Executive,103255,0 +59719,Female,26,Masters,14,70,40,75,85,3.0,1,50,Rural,Software Engineer,130706,0 +59720,Female,48,Diploma,18,5,90,26,22,3.0,1,68,Rural,Manager,142708,0 +59721,Male,53,Masters,2,57,27,61,70,9.0,6,14,Rural,Data Analyst,40598,0 +59722,Male,46,High School,19,31,7,47,77,9.0,2,49,Urban,HR Executive,119821,0 +59723,Male,26,Bachelors,3,44,44,27,89,3.0,2,68,Urban,ML Engineer,26568,0 +59724,Male,28,Bachelors,16,35,9,64,21,5.0,0,72,Urban,Software Engineer,50074,0 +59725,Male,21,Masters,8,83,50,4,73,9.0,7,65,Urban,ML Engineer,71947,0 +59726,Male,29,Masters,18,99,32,22,99,8.0,1,75,Urban,Manager,121589,0 +59727,Male,49,High School,16,59,96,12,88,9.0,6,24,Urban,Software Engineer,146815,0 +59728,Male,38,Diploma,6,56,90,97,52,7.0,6,66,Rural,Manager,105194,1 +59729,Male,36,Bachelors,18,81,8,72,22,9.0,3,57,Urban,Manager,73937,0 +59730,Female,44,Diploma,13,35,35,51,83,6.0,5,12,Urban,Software Engineer,131104,0 +59731,Female,39,Masters,6,33,5,32,7,0.0,4,15,Rural,Manager,66581,0 +59732,Female,45,Bachelors,8,24,49,90,42,7.0,1,54,Semi-Urban,Software Engineer,28683,0 +59733,Male,35,Diploma,7,74,72,3,17,5.0,2,97,Urban,Manager,31567,1 +59734,Male,34,Diploma,11,91,32,2,52,9.0,0,40,Rural,ML Engineer,55897,0 +59735,Male,39,Masters,7,40,40,7,24,1.0,2,9,Rural,Software Engineer,57198,0 +59736,Male,42,High School,9,42,65,37,65,4.0,1,59,Rural,ML Engineer,98450,0 +59737,Female,23,PhD,17,82,92,0,57,1.0,5,90,Urban,HR Executive,43795,1 +59738,Male,54,Diploma,12,63,49,85,98,8.0,2,64,Urban,HR Executive,115872,1 +59739,Female,34,Bachelors,6,6,60,84,8,0.0,5,71,Semi-Urban,ML Engineer,109321,0 +59740,Female,32,Masters,5,71,17,21,95,6.0,3,11,Urban,HR Executive,89873,0 +59741,Female,43,Bachelors,16,72,10,31,51,2.0,6,21,Urban,Software Engineer,66525,0 +59742,Female,48,Bachelors,11,39,68,5,74,3.0,1,55,Rural,HR Executive,99781,0 +59743,Female,32,Bachelors,5,82,83,89,63,5.0,1,54,Urban,Software Engineer,21134,1 +59744,Male,25,Bachelors,10,13,67,32,29,4.0,2,15,Rural,Software Engineer,109006,0 +59745,Female,57,Diploma,17,73,88,37,80,9.0,3,75,Rural,Manager,56169,1 +59746,Male,56,Masters,16,37,16,61,50,9.0,6,16,Semi-Urban,Software Engineer,48312,0 +59747,Male,52,Bachelors,13,3,22,98,64,8.0,3,10,Semi-Urban,Software Engineer,112582,0 +59748,Male,41,Masters,15,10,37,32,37,8.0,3,54,Urban,ML Engineer,69907,0 +59749,Male,51,High School,4,15,59,79,14,4.0,7,65,Semi-Urban,Data Analyst,128015,0 +59750,Male,52,Bachelors,2,46,75,91,24,1.0,7,54,Semi-Urban,Data Analyst,44173,1 +59751,Female,45,Bachelors,7,7,59,57,64,3.0,1,98,Rural,Software Engineer,103283,0 +59752,Male,23,Bachelors,4,83,85,63,16,7.0,2,46,Urban,HR Executive,135072,1 +59753,Male,46,PhD,8,34,66,65,29,9.0,5,41,Urban,Data Analyst,95667,0 +59754,Male,21,Diploma,14,83,95,25,12,5.0,1,16,Urban,HR Executive,131114,0 +59755,Female,22,Bachelors,0,6,14,45,96,8.0,4,17,Rural,HR Executive,29789,0 +59756,Male,38,Masters,16,6,76,32,59,7.0,2,17,Rural,HR Executive,100455,0 +59757,Male,54,Bachelors,9,32,42,25,66,8.0,7,57,Semi-Urban,Data Analyst,85156,0 +59758,Male,31,Bachelors,18,34,51,52,46,2.0,3,96,Semi-Urban,Manager,135522,0 +59759,Male,46,Diploma,10,97,35,34,26,1.0,3,85,Semi-Urban,Software Engineer,49001,1 +59760,Female,35,Bachelors,19,84,31,52,72,1.0,0,35,Urban,Manager,101273,0 +59761,Female,44,Masters,12,93,73,64,33,7.0,6,76,Semi-Urban,ML Engineer,94967,1 +59762,Female,48,Bachelors,6,17,74,57,8,8.0,2,67,Urban,Data Analyst,45293,0 +59763,Male,59,Masters,9,28,92,66,35,2.0,5,88,Urban,ML Engineer,89720,1 +59764,Male,56,Diploma,14,78,99,60,79,8.0,4,5,Urban,Software Engineer,46591,1 +59765,Other,33,Masters,0,95,45,32,50,9.0,0,10,Semi-Urban,HR Executive,87923,0 +59766,Male,27,Bachelors,0,82,40,4,99,6.0,0,72,Rural,Software Engineer,99384,0 +59767,Male,33,Masters,18,42,62,49,24,8.0,2,62,Urban,HR Executive,83280,0 +59768,Female,56,Diploma,19,94,12,78,86,1.0,6,78,Semi-Urban,Manager,51016,1 +59769,Male,39,Bachelors,10,16,23,78,48,7.0,0,50,Urban,Software Engineer,104931,0 +59770,Male,40,Bachelors,9,55,17,3,15,1.0,4,67,Semi-Urban,HR Executive,109832,0 +59771,Male,26,Diploma,16,93,50,93,62,5.0,1,23,Rural,ML Engineer,23132,1 +59772,Male,59,High School,15,43,38,69,38,5.0,4,40,Urban,ML Engineer,34682,0 +59773,Female,27,High School,3,73,56,27,72,3.0,2,89,Semi-Urban,HR Executive,92300,1 +59774,Male,39,Masters,9,47,41,53,31,3.0,0,77,Urban,ML Engineer,102985,0 +59775,Male,21,Bachelors,11,94,97,22,89,4.0,4,35,Rural,Software Engineer,27507,1 +59776,Female,40,Bachelors,9,61,8,99,43,7.0,0,26,Semi-Urban,ML Engineer,126890,0 +59777,Female,51,Bachelors,17,98,72,39,8,8.0,2,18,Urban,HR Executive,25253,0 +59778,Female,40,High School,6,56,84,78,30,1.0,0,27,Urban,ML Engineer,85816,1 +59779,Female,37,Bachelors,13,65,30,86,19,6.0,7,53,Urban,Software Engineer,107731,0 +59780,Male,47,Bachelors,10,68,92,42,91,0.0,5,18,Rural,ML Engineer,127277,0 +59781,Female,32,PhD,17,98,96,40,76,5.0,2,75,Urban,HR Executive,45034,1 +59782,Female,48,High School,2,88,54,1,49,3.0,5,96,Rural,ML Engineer,93719,0 +59783,Female,34,Masters,10,50,8,81,24,0.0,2,91,Urban,Data Analyst,133326,0 +59784,Male,25,High School,2,62,84,58,84,7.0,4,32,Urban,ML Engineer,70744,1 +59785,Male,38,PhD,9,55,96,66,50,3.0,3,52,Urban,Software Engineer,29495,1 +59786,Male,41,Bachelors,13,31,32,85,17,5.0,6,42,Urban,ML Engineer,31274,0 +59787,Female,46,Diploma,0,94,1,21,80,3.0,1,79,Urban,Manager,118442,0 +59788,Male,53,Bachelors,19,89,72,18,31,7.0,5,54,Rural,Data Analyst,134344,0 +59789,Female,32,Masters,2,69,60,0,59,8.0,1,21,Semi-Urban,Data Analyst,39853,0 +59790,Male,42,Diploma,13,78,33,44,2,2.0,5,95,Urban,Data Analyst,32591,1 +59791,Male,49,High School,8,93,64,49,97,8.0,5,25,Urban,HR Executive,89323,0 +59792,Female,51,Bachelors,8,81,99,81,39,6.0,3,10,Urban,ML Engineer,74590,1 +59793,Female,50,Masters,8,57,57,77,35,1.0,6,1,Semi-Urban,Software Engineer,33868,0 +59794,Male,40,Bachelors,7,72,42,25,68,7.0,4,71,Urban,ML Engineer,117004,0 +59795,Female,21,Bachelors,13,70,39,73,65,6.0,6,29,Semi-Urban,Manager,149265,0 +59796,Female,34,Bachelors,14,31,88,50,43,1.0,0,37,Urban,ML Engineer,61125,0 +59797,Male,59,Masters,10,2,53,15,85,1.0,6,60,Urban,Software Engineer,132980,0 +59798,Female,27,High School,10,20,81,2,58,7.0,7,38,Semi-Urban,Data Analyst,116894,0 +59799,Male,31,High School,16,4,79,22,19,4.0,1,75,Urban,Manager,22007,0 +59800,Female,40,Diploma,8,23,17,16,93,5.0,2,93,Urban,ML Engineer,34812,0 +59801,Male,43,Masters,14,91,14,95,13,7.0,6,67,Rural,ML Engineer,28209,1 +59802,Male,56,High School,3,45,54,98,11,3.0,4,68,Rural,Data Analyst,100376,1 +59803,Male,22,Masters,1,95,44,96,2,3.0,6,19,Urban,HR Executive,79357,1 +59804,Male,33,PhD,4,81,60,88,63,5.0,2,74,Urban,Software Engineer,112599,1 +59805,Male,49,PhD,12,72,50,76,1,4.0,5,15,Rural,Data Analyst,149182,0 +59806,Male,57,High School,17,29,59,2,57,7.0,5,58,Urban,ML Engineer,58623,0 +59807,Male,33,Bachelors,17,35,48,14,79,1.0,3,22,Semi-Urban,HR Executive,87826,0 +59808,Male,47,Diploma,11,55,26,9,44,8.0,4,64,Urban,HR Executive,57870,0 +59809,Male,56,Bachelors,13,19,19,61,64,9.0,1,84,Semi-Urban,HR Executive,139804,0 +59810,Male,43,Bachelors,2,4,35,76,42,4.0,6,43,Semi-Urban,HR Executive,129571,0 +59811,Male,22,Bachelors,14,35,39,2,34,0.0,5,41,Urban,Data Analyst,145260,0 +59812,Male,28,Diploma,9,3,69,32,25,1.0,2,57,Rural,HR Executive,88950,0 +59813,Male,34,Masters,12,6,28,23,90,0.0,1,36,Urban,Manager,98924,0 +59814,Female,38,Masters,18,88,11,31,46,0.0,6,49,Urban,Data Analyst,129210,0 +59815,Male,28,Masters,5,62,22,28,50,3.0,5,33,Semi-Urban,ML Engineer,123958,0 +59816,Male,21,Masters,19,53,34,99,54,2.0,6,72,Semi-Urban,Software Engineer,52675,1 +59817,Male,44,High School,9,96,72,27,69,4.0,1,86,Semi-Urban,ML Engineer,73213,1 +59818,Male,45,High School,14,79,5,46,81,8.0,7,7,Rural,Manager,110058,0 +59819,Male,33,Bachelors,5,55,69,64,42,7.0,2,28,Urban,Data Analyst,144130,0 +59820,Female,39,High School,12,92,11,37,15,0.0,3,95,Rural,ML Engineer,128175,0 +59821,Male,46,Bachelors,0,33,80,94,96,7.0,4,3,Urban,Data Analyst,52291,0 +59822,Male,35,Bachelors,0,89,53,78,8,8.0,0,53,Urban,Software Engineer,59831,1 +59823,Male,39,Bachelors,0,55,82,94,19,0.0,0,44,Urban,Data Analyst,63575,1 +59824,Male,28,Masters,19,24,71,4,28,4.0,0,20,Semi-Urban,ML Engineer,54110,0 +59825,Male,37,High School,15,26,69,17,27,1.0,5,33,Urban,ML Engineer,59659,0 +59826,Male,59,PhD,15,74,38,96,65,0.0,2,13,Urban,Manager,136229,0 +59827,Female,42,Bachelors,1,67,8,85,81,7.0,1,81,Urban,HR Executive,76503,1 +59828,Female,56,Bachelors,17,13,61,32,35,9.0,3,86,Urban,Software Engineer,121174,0 +59829,Female,53,Bachelors,7,89,31,28,41,3.0,3,68,Urban,Manager,82282,0 +59830,Male,55,High School,1,60,62,38,0,8.0,0,14,Urban,Data Analyst,76533,0 +59831,Male,47,Bachelors,3,52,52,70,90,5.0,6,10,Urban,HR Executive,23789,0 +59832,Male,37,Diploma,13,32,47,19,89,2.0,2,10,Urban,Data Analyst,112417,0 +59833,Female,32,Bachelors,3,93,44,36,30,4.0,2,14,Urban,HR Executive,96434,0 +59834,Male,44,Masters,15,37,20,53,10,2.0,7,46,Urban,Manager,66440,0 +59835,Male,21,High School,15,95,70,58,70,3.0,4,64,Semi-Urban,Data Analyst,34083,1 +59836,Male,36,PhD,9,16,28,0,15,0.0,0,49,Semi-Urban,Manager,131758,0 +59837,Male,46,Masters,11,23,74,99,58,2.0,1,57,Urban,HR Executive,147309,1 +59838,Female,23,Bachelors,4,73,99,49,30,0.0,6,59,Urban,Data Analyst,122930,1 +59839,Male,45,Masters,14,61,21,38,37,7.0,2,61,Urban,Manager,127231,0 +59840,Male,44,Diploma,4,98,37,75,63,0.0,5,86,Semi-Urban,ML Engineer,87870,1 +59841,Female,42,Masters,6,79,96,21,31,9.0,1,88,Rural,Manager,147353,1 +59842,Female,56,Bachelors,7,23,40,36,31,2.0,7,73,Urban,Manager,81639,0 +59843,Female,48,Bachelors,18,51,60,46,77,2.0,4,99,Semi-Urban,ML Engineer,85577,1 +59844,Male,57,Bachelors,6,54,56,72,12,5.0,4,72,Semi-Urban,Data Analyst,67596,1 +59845,Male,43,Bachelors,10,73,58,60,77,5.0,6,80,Urban,ML Engineer,43799,1 +59846,Male,41,Bachelors,5,49,53,6,38,5.0,1,9,Semi-Urban,Software Engineer,117779,0 +59847,Male,51,Diploma,0,99,34,60,65,2.0,1,46,Semi-Urban,HR Executive,106920,1 +59848,Female,50,Bachelors,18,84,64,76,99,0.0,2,22,Urban,ML Engineer,129448,1 +59849,Female,24,High School,17,29,38,85,18,0.0,2,0,Urban,Software Engineer,32296,0 +59850,Male,54,Bachelors,16,81,89,15,83,8.0,3,42,Urban,ML Engineer,104586,0 +59851,Male,44,Diploma,13,74,14,40,0,2.0,5,23,Urban,Data Analyst,20734,0 +59852,Female,36,Diploma,14,70,33,86,80,6.0,7,82,Urban,Manager,24145,1 +59853,Male,37,High School,17,26,19,77,74,9.0,5,19,Urban,Data Analyst,123449,0 +59854,Male,48,PhD,15,26,73,9,86,3.0,5,40,Semi-Urban,HR Executive,111874,0 +59855,Other,41,Masters,15,5,20,96,20,7.0,3,70,Semi-Urban,Software Engineer,141030,0 +59856,Male,50,High School,9,18,4,45,98,9.0,1,6,Semi-Urban,HR Executive,133099,0 +59857,Female,55,Bachelors,16,29,7,98,72,8.0,3,29,Urban,Manager,30642,0 +59858,Female,39,Masters,15,81,60,7,69,3.0,0,34,Urban,HR Executive,140905,0 +59859,Female,37,Bachelors,10,80,84,99,48,4.0,0,77,Semi-Urban,Software Engineer,100724,1 +59860,Male,24,Bachelors,18,35,78,75,31,6.0,0,80,Urban,HR Executive,103015,1 +59861,Other,36,Bachelors,1,72,99,63,28,0.0,3,88,Urban,ML Engineer,109246,1 +59862,Male,27,Bachelors,18,43,4,3,80,7.0,7,28,Urban,HR Executive,132045,0 +59863,Male,41,Masters,5,8,60,26,22,6.0,7,41,Rural,HR Executive,38171,0 +59864,Male,25,Bachelors,12,1,22,58,95,4.0,5,60,Urban,Data Analyst,122279,0 +59865,Male,41,Bachelors,0,25,85,98,60,6.0,0,39,Urban,Software Engineer,84011,1 +59866,Other,24,Bachelors,1,76,96,12,23,2.0,4,57,Urban,Software Engineer,62091,1 +59867,Female,57,Masters,12,77,68,2,64,1.0,2,64,Urban,Manager,143467,0 +59868,Male,43,High School,5,54,62,16,72,1.0,6,61,Semi-Urban,HR Executive,110549,0 +59869,Male,31,Masters,11,74,59,96,90,4.0,6,43,Rural,Manager,58159,1 +59870,Male,27,Bachelors,8,76,64,88,95,8.0,5,93,Urban,Data Analyst,147316,1 +59871,Male,27,Bachelors,11,54,13,50,15,9.0,7,84,Semi-Urban,HR Executive,78765,0 +59872,Male,21,Masters,0,41,35,72,81,2.0,5,96,Rural,HR Executive,76394,1 +59873,Female,46,PhD,14,2,64,70,59,6.0,4,83,Urban,Data Analyst,124217,0 +59874,Female,42,Bachelors,4,53,84,5,18,7.0,7,93,Semi-Urban,Data Analyst,42050,0 +59875,Male,38,Masters,14,84,26,11,32,4.0,5,22,Urban,Software Engineer,110188,0 +59876,Male,45,Bachelors,18,35,32,43,28,8.0,1,61,Urban,Data Analyst,62538,0 +59877,Female,52,Bachelors,18,33,8,70,88,9.0,7,11,Urban,Manager,97232,0 +59878,Male,25,High School,1,91,94,55,71,2.0,5,88,Semi-Urban,Software Engineer,119302,1 +59879,Female,34,PhD,19,87,70,82,53,2.0,3,80,Rural,Data Analyst,31406,1 +59880,Female,57,Masters,6,86,73,92,62,0.0,1,38,Urban,Software Engineer,44174,1 +59881,Male,25,Bachelors,2,61,51,67,58,0.0,3,33,Semi-Urban,Software Engineer,71900,0 +59882,Male,50,Bachelors,15,49,78,54,86,7.0,6,32,Urban,ML Engineer,82333,0 +59883,Male,22,Bachelors,18,96,44,6,62,3.0,1,43,Urban,Manager,143114,0 +59884,Male,36,Bachelors,10,85,17,14,98,5.0,0,53,Rural,HR Executive,144896,0 +59885,Female,32,Bachelors,16,41,91,78,38,5.0,7,53,Semi-Urban,Data Analyst,32083,1 +59886,Male,58,High School,2,40,70,24,44,5.0,0,59,Semi-Urban,HR Executive,60567,0 +59887,Male,49,Bachelors,18,45,35,79,17,3.0,0,85,Semi-Urban,HR Executive,22776,1 +59888,Female,41,High School,5,53,50,26,38,7.0,3,42,Urban,Manager,28217,0 +59889,Male,32,Bachelors,16,36,6,31,94,9.0,1,74,Urban,ML Engineer,94599,0 +59890,Female,26,Diploma,2,14,45,10,14,4.0,5,9,Urban,ML Engineer,46294,0 +59891,Female,54,High School,11,0,0,22,41,0.0,4,51,Urban,ML Engineer,142005,0 +59892,Male,39,Masters,13,39,56,68,98,1.0,7,23,Semi-Urban,HR Executive,67388,0 +59893,Male,33,Bachelors,16,92,25,10,75,9.0,6,96,Urban,Data Analyst,106162,0 +59894,Female,27,Diploma,3,18,44,84,25,9.0,6,25,Semi-Urban,ML Engineer,29680,0 +59895,Female,31,Bachelors,17,29,80,48,23,8.0,2,56,Rural,Software Engineer,104123,0 +59896,Male,34,Bachelors,9,41,43,91,12,2.0,0,41,Semi-Urban,ML Engineer,95255,0 +59897,Male,22,Bachelors,16,80,97,33,91,2.0,0,16,Urban,Software Engineer,131391,0 +59898,Female,41,High School,5,87,81,65,92,9.0,0,55,Semi-Urban,Software Engineer,66725,1 +59899,Other,25,Bachelors,12,55,77,44,63,6.0,5,86,Semi-Urban,HR Executive,107773,1 +59900,Female,43,Masters,11,72,55,62,47,7.0,0,5,Urban,ML Engineer,24236,0 +59901,Female,45,Bachelors,8,45,82,33,66,4.0,2,27,Rural,Data Analyst,30132,0 +59902,Female,26,High School,8,21,60,66,43,7.0,7,48,Urban,ML Engineer,123810,0 +59903,Male,42,Diploma,19,28,41,42,58,0.0,3,2,Urban,HR Executive,21256,0 +59904,Male,39,Diploma,5,17,58,17,45,4.0,2,23,Semi-Urban,Manager,112969,0 +59905,Male,53,Bachelors,8,82,27,59,26,7.0,7,64,Rural,ML Engineer,102294,0 +59906,Other,40,Bachelors,2,1,6,84,55,5.0,6,78,Urban,ML Engineer,69288,0 +59907,Female,34,Bachelors,12,5,67,2,34,9.0,6,58,Urban,Software Engineer,73616,0 +59908,Male,54,Bachelors,12,13,40,28,45,5.0,7,14,Semi-Urban,Manager,47603,0 +59909,Male,45,Bachelors,6,40,62,38,42,3.0,0,96,Urban,Manager,31979,1 +59910,Male,52,Bachelors,18,22,39,64,49,4.0,6,66,Urban,Data Analyst,110402,0 +59911,Female,21,Bachelors,1,43,28,37,65,4.0,5,28,Rural,ML Engineer,37063,0 +59912,Male,39,Diploma,1,71,62,74,21,7.0,0,48,Urban,Manager,47186,1 +59913,Female,29,High School,9,9,86,51,4,1.0,5,17,Urban,Software Engineer,63742,0 +59914,Male,47,Bachelors,4,39,66,59,23,5.0,3,22,Urban,Manager,69682,0 +59915,Female,32,Bachelors,12,82,8,9,48,7.0,4,68,Urban,Manager,70887,0 +59916,Male,50,Bachelors,19,1,13,73,34,2.0,0,29,Urban,Manager,25368,0 +59917,Male,51,Diploma,6,24,93,78,95,4.0,4,84,Semi-Urban,Data Analyst,64881,1 +59918,Male,59,Masters,10,43,5,70,60,1.0,4,78,Urban,HR Executive,87462,0 +59919,Male,51,Diploma,11,43,43,41,50,6.0,4,85,Urban,ML Engineer,136704,0 +59920,Male,46,Bachelors,6,79,33,8,86,3.0,3,78,Urban,HR Executive,45021,0 +59921,Female,25,High School,13,57,83,1,55,5.0,5,48,Urban,ML Engineer,118957,0 +59922,Female,52,Bachelors,18,57,74,45,24,9.0,4,24,Semi-Urban,Software Engineer,137334,0 +59923,Male,58,Masters,5,48,11,23,79,1.0,3,23,Urban,Manager,60725,0 +59924,Male,45,Diploma,12,72,62,3,51,0.0,7,26,Urban,Manager,123571,0 +59925,Female,34,Masters,10,92,36,4,66,1.0,1,80,Rural,Data Analyst,100007,0 +59926,Male,23,High School,0,23,64,90,29,6.0,2,11,Semi-Urban,Manager,128855,0 +59927,Female,24,Bachelors,4,58,35,84,82,3.0,6,67,Urban,Software Engineer,39348,1 +59928,Female,29,Bachelors,7,33,69,0,47,4.0,1,92,Urban,ML Engineer,92354,0 +59929,Female,22,Bachelors,19,92,73,92,46,3.0,0,89,Rural,Manager,42302,1 +59930,Male,21,Bachelors,17,50,62,16,73,3.0,5,51,Urban,HR Executive,21381,0 +59931,Female,36,Bachelors,2,68,48,76,88,2.0,7,45,Rural,Software Engineer,46926,0 +59932,Female,22,Diploma,16,85,48,8,45,6.0,5,61,Urban,Data Analyst,29437,0 +59933,Male,53,Diploma,10,85,84,93,98,1.0,0,8,Semi-Urban,ML Engineer,104966,1 +59934,Male,33,Diploma,16,19,73,11,92,4.0,4,65,Semi-Urban,Manager,127504,0 +59935,Male,41,Bachelors,13,84,73,33,27,0.0,6,82,Semi-Urban,Data Analyst,26322,1 +59936,Male,55,High School,7,20,24,6,23,7.0,0,13,Rural,Software Engineer,147320,0 +59937,Male,46,Diploma,13,82,37,12,94,9.0,0,59,Urban,Software Engineer,78362,0 +59938,Male,30,Bachelors,10,16,91,56,45,5.0,1,31,Rural,Software Engineer,121218,0 +59939,Male,24,Bachelors,11,13,79,24,54,2.0,2,28,Urban,ML Engineer,148341,0 +59940,Male,22,Bachelors,4,12,42,23,4,1.0,1,58,Urban,ML Engineer,45012,0 +59941,Male,34,Bachelors,17,78,8,40,80,0.0,6,94,Semi-Urban,Software Engineer,110176,0 +59942,Male,46,Bachelors,16,75,24,35,81,1.0,7,45,Rural,Data Analyst,95286,0 +59943,Female,39,Diploma,5,78,83,21,30,1.0,0,29,Urban,HR Executive,86666,0 +59944,Male,54,Masters,13,57,36,43,28,3.0,5,87,Rural,Data Analyst,73662,0 +59945,Female,24,Masters,2,81,31,95,55,7.0,4,80,Urban,Data Analyst,119753,1 +59946,Male,44,Bachelors,5,80,69,94,32,1.0,5,67,Semi-Urban,Data Analyst,144905,1 +59947,Male,57,Bachelors,8,18,5,31,70,5.0,2,42,Urban,HR Executive,120615,0 +59948,Female,54,Masters,10,89,82,42,35,2.0,7,67,Semi-Urban,Manager,41772,1 +59949,Female,32,Masters,11,14,89,91,30,4.0,7,81,Urban,HR Executive,143289,1 +59950,Male,46,Diploma,4,1,89,95,57,7.0,6,62,Semi-Urban,Manager,69684,1 +59951,Female,29,High School,1,27,82,2,61,9.0,6,25,Rural,Software Engineer,143659,0 +59952,Male,29,High School,12,39,8,55,46,1.0,3,58,Semi-Urban,Software Engineer,146588,0 +59953,Female,48,Diploma,14,12,85,71,66,4.0,5,31,Semi-Urban,Software Engineer,91320,0 +59954,Male,27,Diploma,13,44,9,83,11,3.0,6,0,Urban,Manager,87223,0 +59955,Female,27,Diploma,11,56,42,61,42,4.0,2,59,Urban,ML Engineer,67345,0 +59956,Male,42,Bachelors,13,33,24,58,90,6.0,6,13,Semi-Urban,Data Analyst,66395,0 +59957,Male,40,Masters,1,73,10,74,87,5.0,2,19,Urban,Software Engineer,129913,0 +59958,Female,24,Bachelors,1,64,50,14,10,5.0,7,5,Urban,ML Engineer,131813,0 +59959,Male,58,Bachelors,13,87,32,68,91,3.0,1,80,Semi-Urban,HR Executive,129136,1 +59960,Male,30,Masters,5,41,30,93,99,4.0,4,58,Urban,Data Analyst,91994,0 +59961,Male,45,Bachelors,7,89,99,13,4,2.0,5,42,Urban,ML Engineer,89065,1 +59962,Male,26,Bachelors,0,82,77,69,45,6.0,5,26,Urban,ML Engineer,127725,1 +59963,Female,54,Masters,8,26,60,20,2,2.0,1,39,Semi-Urban,ML Engineer,113482,0 +59964,Male,34,Bachelors,16,3,14,65,64,0.0,6,63,Urban,ML Engineer,92478,0 +59965,Male,43,PhD,0,62,25,58,30,6.0,6,88,Rural,HR Executive,111776,0 +59966,Female,40,Masters,1,6,82,57,26,5.0,7,38,Urban,Manager,43007,0 +59967,Male,39,Diploma,4,63,10,28,39,5.0,5,65,Rural,Data Analyst,115985,0 +59968,Female,51,High School,5,11,91,19,20,9.0,5,65,Rural,Software Engineer,137625,0 +59969,Male,37,Bachelors,12,37,60,55,18,7.0,5,75,Rural,HR Executive,96262,0 +59970,Female,26,Diploma,3,0,60,44,13,1.0,6,47,Semi-Urban,ML Engineer,103932,0 +59971,Male,38,Bachelors,0,76,33,49,82,4.0,1,4,Urban,ML Engineer,45830,0 +59972,Female,33,High School,10,74,82,71,23,9.0,5,89,Semi-Urban,HR Executive,113596,1 +59973,Male,29,Bachelors,13,70,76,0,97,7.0,3,79,Urban,HR Executive,36647,0 +59974,Male,36,Diploma,18,33,43,47,20,7.0,6,61,Urban,Software Engineer,75880,0 +59975,Male,39,Bachelors,14,47,15,79,52,6.0,0,86,Urban,Software Engineer,77109,0 +59976,Male,45,Diploma,18,74,54,27,98,6.0,7,65,Urban,HR Executive,121269,0 +59977,Male,32,Bachelors,13,36,17,21,11,8.0,4,87,Semi-Urban,Data Analyst,99258,0 +59978,Male,52,Bachelors,14,34,68,7,73,9.0,0,21,Rural,Software Engineer,21620,0 +59979,Other,44,Diploma,7,58,72,27,43,7.0,5,52,Urban,ML Engineer,146825,0 +59980,Male,31,Diploma,2,32,11,91,55,1.0,1,50,Urban,Manager,89779,0 +59981,Female,46,Bachelors,12,87,19,32,60,6.0,2,2,Urban,ML Engineer,28550,0 +59982,Male,36,High School,4,23,26,92,44,2.0,3,30,Semi-Urban,HR Executive,42550,0 +59983,Male,49,Diploma,18,89,68,19,5,0.0,5,33,Semi-Urban,Data Analyst,121704,0 +59984,Male,44,Bachelors,15,59,64,58,81,9.0,0,32,Urban,ML Engineer,31007,0 +59985,Female,59,Masters,19,9,5,40,61,2.0,5,42,Urban,Data Analyst,89455,0 +59986,Male,52,Bachelors,4,28,72,6,87,9.0,2,14,Rural,HR Executive,83834,0 +59987,Female,41,Bachelors,3,31,2,72,13,3.0,0,23,Rural,Software Engineer,27493,0 +59988,Other,36,Bachelors,19,16,6,69,13,2.0,5,9,Rural,ML Engineer,104098,0 +59989,Male,41,Diploma,9,59,36,95,55,3.0,2,9,Urban,ML Engineer,144915,0 +59990,Male,31,Diploma,16,98,30,43,16,8.0,4,74,Urban,Data Analyst,68052,1 +59991,Male,36,Bachelors,4,26,85,6,76,3.0,3,71,Urban,ML Engineer,63758,0 +59992,Male,24,Diploma,15,19,64,16,44,6.0,3,5,Urban,Data Analyst,38766,0 +59993,Male,29,High School,19,69,49,90,41,9.0,6,53,Urban,Software Engineer,71407,1 +59994,Other,26,PhD,3,6,89,33,58,6.0,1,87,Urban,Software Engineer,51885,0 +59995,Female,25,High School,6,9,50,62,73,4.0,3,73,Urban,Data Analyst,20714,0 +59996,Other,40,Bachelors,18,28,92,87,73,5.0,4,16,Semi-Urban,ML Engineer,71034,0 +59997,Male,46,Diploma,2,76,9,91,0,1.0,4,51,Semi-Urban,ML Engineer,93464,0 +59998,Male,29,Bachelors,6,58,19,0,27,6.0,2,7,Urban,Software Engineer,67058,0 +59999,Male,56,Bachelors,0,66,50,51,93,6.0,5,30,Urban,HR Executive,60940,0 +60000,Male,42,Masters,12,73,78,15,51,5.0,2,4,Urban,Data Analyst,126374,0 +60001,Female,58,Bachelors,3,9,30,2,29,3.0,5,68,Urban,ML Engineer,60789,0 +60002,Female,56,Bachelors,9,36,41,91,14,8.0,3,97,Urban,Manager,132509,1 +60003,Male,55,Bachelors,19,71,67,41,47,8.0,1,72,Rural,HR Executive,68345,1 +60004,Male,22,Masters,9,79,92,42,24,8.0,5,30,Rural,HR Executive,26292,1 +60005,Male,33,Diploma,19,67,73,34,50,8.0,6,32,Rural,Data Analyst,64339,0 +60006,Female,44,Bachelors,15,81,52,4,29,6.0,6,50,Urban,Data Analyst,107316,0 +60007,Male,24,Masters,1,13,65,76,15,4.0,1,11,Rural,Software Engineer,111353,0 +60008,Male,27,Bachelors,5,11,77,46,96,1.0,5,20,Urban,Manager,34633,0 +60009,Male,21,Masters,14,31,9,48,34,2.0,7,82,Urban,Manager,36585,0 +60010,Female,56,High School,14,64,6,99,29,1.0,4,34,Urban,ML Engineer,88567,0 +60011,Female,43,Bachelors,2,9,94,31,36,3.0,5,50,Urban,Manager,43981,0 +60012,Male,37,High School,2,71,15,76,85,9.0,6,36,Rural,Manager,50791,0 +60013,Male,39,Bachelors,4,16,92,33,81,6.0,5,61,Semi-Urban,HR Executive,98105,0 +60014,Male,21,Bachelors,17,57,73,58,98,1.0,2,1,Urban,HR Executive,141935,0 +60015,Male,49,Bachelors,11,78,63,97,10,3.0,7,79,Urban,HR Executive,56998,1 +60016,Male,39,Masters,9,27,96,32,30,7.0,4,89,Semi-Urban,Manager,139340,1 +60017,Female,52,Bachelors,2,66,97,20,64,0.0,2,13,Rural,HR Executive,74580,0 +60018,Male,27,Masters,4,35,8,69,72,6.0,0,79,Urban,Manager,89493,0 +60019,Male,46,Diploma,14,17,59,54,95,8.0,3,30,Urban,Software Engineer,82114,0 +60020,Male,51,Bachelors,3,34,43,26,68,8.0,1,70,Semi-Urban,ML Engineer,66922,0 +60021,Male,51,PhD,15,81,17,11,24,4.0,6,34,Semi-Urban,Data Analyst,55854,0 +60022,Male,41,PhD,5,60,82,20,2,7.0,0,16,Urban,HR Executive,125328,0 +60023,Male,47,Diploma,18,73,43,15,48,6.0,3,84,Rural,Software Engineer,63564,0 +60024,Male,45,Diploma,12,24,33,37,21,1.0,7,81,Semi-Urban,Software Engineer,123003,0 +60025,Male,44,Bachelors,5,95,15,37,93,0.0,5,90,Urban,HR Executive,89430,1 +60026,Other,37,Bachelors,15,35,80,87,57,4.0,6,5,Urban,Manager,105895,0 +60027,Female,59,Bachelors,15,89,30,3,13,3.0,0,83,Urban,ML Engineer,23768,0 +60028,Male,21,Diploma,15,84,36,36,91,1.0,1,74,Urban,ML Engineer,85864,0 +60029,Male,43,Diploma,11,41,31,66,15,4.0,7,37,Urban,Manager,91696,0 +60030,Male,28,Bachelors,3,68,91,7,18,6.0,0,90,Urban,HR Executive,140122,1 +60031,Male,48,Bachelors,7,28,74,7,91,6.0,6,59,Rural,Manager,46934,0 +60032,Male,51,Masters,4,79,11,8,82,3.0,3,75,Urban,Data Analyst,37886,0 +60033,Male,21,Masters,13,52,58,88,36,2.0,1,17,Urban,Manager,76933,0 +60034,Male,40,High School,13,14,33,22,4,4.0,6,81,Urban,ML Engineer,106693,0 +60035,Female,47,Masters,13,84,14,37,63,6.0,7,95,Semi-Urban,ML Engineer,117575,0 +60036,Male,50,Bachelors,15,80,71,64,36,9.0,0,13,Rural,ML Engineer,105395,0 +60037,Other,21,Masters,16,3,63,2,87,8.0,0,50,Urban,ML Engineer,141319,0 +60038,Male,56,Bachelors,5,22,63,51,13,2.0,4,53,Urban,Manager,55714,0 +60039,Other,38,Diploma,10,92,35,95,85,0.0,2,39,Urban,HR Executive,87401,1 +60040,Male,22,Diploma,15,98,20,34,15,2.0,3,15,Urban,ML Engineer,97587,0 +60041,Male,52,Masters,2,95,72,19,90,0.0,5,12,Semi-Urban,ML Engineer,27921,0 +60042,Female,58,Masters,13,80,84,44,70,8.0,6,84,Rural,Data Analyst,65394,1 +60043,Male,54,Diploma,12,77,61,54,96,0.0,5,40,Urban,Manager,43122,0 +60044,Male,52,High School,14,85,45,74,3,7.0,7,44,Rural,ML Engineer,86200,1 +60045,Male,32,Masters,13,96,31,25,73,9.0,7,63,Semi-Urban,Data Analyst,121540,0 +60046,Male,55,Diploma,17,20,58,21,6,4.0,7,75,Urban,Software Engineer,72214,0 +60047,Other,26,Bachelors,17,5,69,29,92,8.0,1,9,Rural,Data Analyst,23441,0 +60048,Male,54,Masters,11,8,53,40,33,2.0,7,86,Urban,ML Engineer,113530,0 +60049,Other,50,Masters,4,64,2,56,39,6.0,3,16,Rural,Software Engineer,148767,0 +60050,Male,22,High School,10,23,4,31,80,5.0,3,27,Semi-Urban,HR Executive,133542,0 +60051,Male,38,Bachelors,11,88,61,63,44,1.0,0,84,Urban,Manager,113438,1 +60052,Male,50,Bachelors,19,80,73,74,58,8.0,1,37,Urban,Software Engineer,98004,1 +60053,Male,55,Diploma,10,27,57,2,76,1.0,5,24,Urban,Software Engineer,143942,0 +60054,Male,31,Diploma,19,23,20,90,15,1.0,0,6,Urban,HR Executive,146652,0 +60055,Female,47,Diploma,16,42,37,43,55,1.0,4,33,Rural,HR Executive,139254,0 +60056,Male,50,Bachelors,5,69,2,79,42,9.0,1,48,Urban,Manager,22636,0 +60057,Female,33,Masters,11,14,83,53,59,4.0,7,50,Rural,HR Executive,68521,0 +60058,Female,50,PhD,1,32,47,38,38,4.0,0,66,Urban,Software Engineer,44568,0 +60059,Male,38,Bachelors,7,38,31,44,51,7.0,6,28,Urban,Manager,64060,0 +60060,Female,24,High School,2,7,47,4,72,5.0,6,86,Urban,Software Engineer,77426,0 +60061,Female,40,Masters,18,86,34,79,26,2.0,0,58,Rural,ML Engineer,51938,1 +60062,Male,54,PhD,1,19,49,97,85,0.0,5,75,Semi-Urban,HR Executive,32324,1 +60063,Male,38,Diploma,6,33,12,37,18,4.0,2,24,Urban,ML Engineer,110509,0 +60064,Male,36,Masters,14,88,21,11,64,2.0,0,89,Semi-Urban,Software Engineer,148339,0 +60065,Female,35,PhD,16,36,51,30,48,5.0,6,89,Urban,Data Analyst,45125,0 +60066,Male,24,Bachelors,17,83,5,70,57,4.0,7,5,Semi-Urban,Manager,60443,0 +60067,Male,44,Bachelors,18,35,80,99,42,1.0,1,14,Urban,HR Executive,23397,0 +60068,Male,52,Bachelors,8,47,18,69,29,0.0,7,70,Urban,ML Engineer,80448,0 +60069,Male,51,Bachelors,19,13,20,10,11,9.0,4,96,Urban,HR Executive,117599,0 +60070,Male,26,High School,17,55,56,61,70,8.0,3,37,Rural,HR Executive,72153,0 +60071,Male,35,High School,8,70,57,55,85,4.0,4,66,Urban,Software Engineer,87086,1 +60072,Male,53,Masters,18,74,23,73,12,1.0,7,96,Semi-Urban,Software Engineer,101412,1 +60073,Male,39,High School,2,73,46,48,83,5.0,2,8,Urban,HR Executive,119512,0 +60074,Male,48,Masters,0,83,17,71,51,7.0,3,83,Semi-Urban,Manager,43718,1 +60075,Male,43,Bachelors,17,69,6,5,48,4.0,0,91,Urban,Software Engineer,69119,0 +60076,Female,57,Masters,16,9,5,55,91,2.0,1,88,Semi-Urban,Software Engineer,47596,0 +60077,Male,49,Bachelors,17,61,20,17,57,7.0,4,13,Urban,Data Analyst,109457,0 +60078,Male,37,Bachelors,4,95,64,15,84,9.0,2,73,Urban,HR Executive,144028,1 +60079,Male,38,Bachelors,17,46,83,57,10,5.0,7,99,Semi-Urban,Software Engineer,57197,1 +60080,Female,27,Bachelors,6,11,7,21,97,9.0,3,13,Rural,Data Analyst,84601,0 +60081,Male,29,Masters,15,31,88,79,88,5.0,5,73,Rural,Software Engineer,74945,1 +60082,Male,38,Masters,11,39,24,94,51,1.0,7,79,Urban,HR Executive,64573,1 +60083,Female,49,Bachelors,8,11,7,57,29,9.0,7,49,Semi-Urban,Manager,59859,0 +60084,Male,46,Diploma,10,65,23,93,50,6.0,2,82,Urban,Data Analyst,71444,1 +60085,Male,56,High School,3,38,58,21,18,6.0,3,60,Urban,Data Analyst,109967,0 +60086,Male,24,Bachelors,3,50,97,16,91,6.0,6,70,Urban,ML Engineer,98977,0 +60087,Male,50,Bachelors,2,89,55,34,72,7.0,0,59,Urban,Manager,140454,1 +60088,Female,35,Diploma,16,60,90,17,61,8.0,4,34,Semi-Urban,Software Engineer,38387,0 +60089,Male,28,High School,3,34,5,44,27,4.0,4,45,Urban,Manager,91931,0 +60090,Female,28,Masters,7,32,38,38,96,5.0,0,97,Urban,HR Executive,110450,0 +60091,Male,43,Masters,3,63,28,11,81,5.0,0,50,Semi-Urban,Manager,105514,0 +60092,Male,29,Bachelors,16,35,40,17,19,9.0,6,94,Rural,HR Executive,59705,0 +60093,Male,51,Bachelors,14,26,41,94,29,4.0,7,61,Semi-Urban,Manager,28362,0 +60094,Male,52,Diploma,4,7,55,33,26,0.0,3,13,Semi-Urban,Manager,96210,0 +60095,Male,56,Bachelors,1,39,9,69,95,3.0,3,51,Urban,Data Analyst,55694,0 +60096,Female,43,Masters,4,93,5,62,38,8.0,4,6,Urban,HR Executive,87252,0 +60097,Other,41,Bachelors,3,4,91,36,42,5.0,2,13,Urban,ML Engineer,120038,0 +60098,Male,23,High School,9,24,96,44,86,0.0,4,57,Semi-Urban,ML Engineer,71915,0 +60099,Male,24,High School,9,52,21,67,90,8.0,7,14,Urban,HR Executive,123334,0 +60100,Male,42,High School,8,70,15,70,73,1.0,3,54,Urban,HR Executive,145900,0 +60101,Female,39,Bachelors,16,27,0,19,87,7.0,2,94,Semi-Urban,Data Analyst,89297,0 +60102,Female,57,Masters,12,2,93,1,6,3.0,6,97,Semi-Urban,ML Engineer,95934,0 +60103,Female,47,Bachelors,1,84,26,12,34,3.0,3,17,Rural,Software Engineer,43317,0 +60104,Male,57,Masters,15,2,2,95,97,3.0,5,84,Urban,HR Executive,115092,0 +60105,Female,36,High School,13,76,63,7,85,4.0,2,37,Urban,Data Analyst,119808,0 +60106,Male,49,PhD,17,35,28,94,20,0.0,4,78,Urban,ML Engineer,114360,1 +60107,Male,34,Diploma,2,8,26,6,54,2.0,6,49,Urban,ML Engineer,50201,0 +60108,Male,24,Bachelors,12,21,91,64,90,9.0,6,23,Urban,HR Executive,143368,0 +60109,Female,58,High School,17,45,9,87,62,9.0,4,11,Urban,Data Analyst,126345,0 +60110,Female,55,Bachelors,3,91,88,35,99,7.0,6,26,Rural,Manager,110067,0 +60111,Female,21,High School,3,41,18,64,37,0.0,3,64,Semi-Urban,Data Analyst,42755,0 +60112,Female,36,Diploma,18,18,5,87,55,9.0,4,67,Urban,HR Executive,63832,0 +60113,Male,26,Bachelors,4,96,64,32,92,5.0,2,98,Rural,Software Engineer,34577,1 +60114,Female,37,High School,16,85,70,37,40,8.0,1,42,Urban,HR Executive,92202,0 +60115,Male,32,High School,18,94,49,60,64,0.0,5,12,Urban,HR Executive,116237,0 +60116,Male,41,Bachelors,5,90,19,60,46,7.0,7,2,Urban,Manager,84806,0 +60117,Male,43,High School,2,38,69,51,11,0.0,2,24,Urban,Data Analyst,74041,0 +60118,Female,56,High School,3,42,67,8,55,8.0,0,60,Urban,Software Engineer,97865,0 +60119,Other,53,Masters,17,64,2,35,72,8.0,1,48,Semi-Urban,Manager,85179,0 +60120,Male,41,Masters,11,67,43,6,33,2.0,7,15,Urban,Manager,106229,0 +60121,Male,23,Bachelors,10,10,38,51,83,6.0,6,11,Urban,Data Analyst,140451,0 +60122,Male,29,Diploma,3,24,63,24,31,6.0,3,89,Urban,Software Engineer,37851,0 +60123,Male,24,Masters,11,36,48,46,84,4.0,4,80,Semi-Urban,HR Executive,45517,0 +60124,Male,37,Bachelors,14,3,16,71,11,8.0,4,64,Urban,Data Analyst,104179,0 +60125,Male,41,Diploma,7,70,4,38,24,2.0,1,40,Semi-Urban,HR Executive,23430,0 +60126,Male,24,Bachelors,8,6,5,22,26,3.0,0,77,Rural,Manager,92284,0 +60127,Male,44,Masters,4,26,52,15,26,3.0,7,94,Urban,Manager,45550,0 +60128,Male,54,Diploma,4,65,98,35,95,5.0,7,96,Rural,ML Engineer,26871,1 +60129,Male,38,Diploma,14,35,53,76,50,4.0,7,63,Urban,HR Executive,82039,0 +60130,Male,27,Masters,12,0,32,84,27,0.0,6,39,Urban,Software Engineer,148345,0 +60131,Female,35,Bachelors,7,27,87,5,94,3.0,3,64,Urban,Data Analyst,93561,0 +60132,Female,52,Masters,13,20,85,64,73,0.0,4,28,Semi-Urban,Software Engineer,95677,0 +60133,Female,36,Bachelors,12,59,26,32,90,0.0,6,70,Urban,Software Engineer,83671,0 +60134,Male,40,Diploma,11,97,31,54,8,5.0,6,26,Semi-Urban,Data Analyst,142735,0 +60135,Male,28,Bachelors,1,90,76,89,25,4.0,2,13,Rural,Data Analyst,132915,1 +60136,Other,27,Bachelors,16,51,34,22,74,1.0,3,90,Urban,Manager,83558,0 +60137,Male,26,High School,1,13,42,75,97,9.0,6,93,Urban,ML Engineer,58505,0 +60138,Male,45,High School,12,84,99,44,77,8.0,6,92,Urban,Software Engineer,113449,1 +60139,Female,26,Masters,15,45,89,10,89,3.0,5,12,Semi-Urban,Manager,84057,0 +60140,Male,30,Bachelors,14,16,87,69,74,7.0,5,46,Rural,Data Analyst,31071,0 +60141,Male,49,Bachelors,16,69,36,69,41,6.0,7,53,Urban,Data Analyst,40207,0 +60142,Male,28,Diploma,11,72,7,80,96,1.0,5,3,Urban,Data Analyst,34766,0 +60143,Male,27,Bachelors,19,47,36,63,86,5.0,3,78,Semi-Urban,Manager,101628,0 +60144,Male,58,Diploma,8,13,6,23,65,7.0,2,6,Rural,HR Executive,144300,0 +60145,Male,45,Bachelors,2,55,11,7,87,9.0,0,63,Urban,Software Engineer,113399,0 +60146,Male,53,Diploma,15,59,16,66,47,5.0,7,94,Semi-Urban,Manager,83362,1 +60147,Female,28,High School,15,57,51,12,15,3.0,0,45,Urban,Data Analyst,141769,0 +60148,Other,40,Masters,10,34,0,11,20,9.0,2,71,Urban,Manager,27046,0 +60149,Female,48,Bachelors,4,38,90,94,85,3.0,4,99,Urban,Data Analyst,35703,1 +60150,Male,38,Bachelors,4,5,52,88,71,6.0,1,65,Semi-Urban,Software Engineer,142894,0 +60151,Female,35,Bachelors,6,68,1,52,34,2.0,2,69,Urban,ML Engineer,91804,0 +60152,Male,36,Masters,6,69,61,96,93,5.0,5,58,Urban,Data Analyst,37156,1 +60153,Male,29,High School,5,23,89,32,84,1.0,0,41,Semi-Urban,Software Engineer,119328,0 +60154,Male,56,Bachelors,1,12,60,48,45,5.0,0,14,Rural,Manager,52175,0 +60155,Female,25,Masters,16,97,56,72,42,1.0,0,81,Semi-Urban,Data Analyst,64368,1 +60156,Male,35,Diploma,8,18,34,99,66,7.0,4,14,Urban,ML Engineer,69524,0 +60157,Other,41,Masters,12,17,12,3,76,2.0,0,94,Urban,Software Engineer,55916,0 +60158,Female,37,Bachelors,10,76,26,72,89,4.0,0,43,Semi-Urban,ML Engineer,61508,0 +60159,Male,58,Diploma,14,59,82,43,58,1.0,7,69,Urban,Data Analyst,52338,1 +60160,Female,52,Bachelors,4,51,81,64,23,0.0,7,24,Urban,ML Engineer,81922,0 +60161,Male,50,High School,10,25,32,23,1,0.0,4,78,Urban,Software Engineer,31735,0 +60162,Male,52,Bachelors,9,17,72,48,50,1.0,3,53,Rural,Manager,44679,0 +60163,Male,23,Bachelors,13,21,19,78,66,2.0,0,71,Urban,HR Executive,45929,0 +60164,Female,46,Bachelors,18,70,28,55,82,9.0,0,55,Urban,Manager,110116,0 +60165,Female,34,High School,9,79,99,80,8,1.0,3,7,Urban,Data Analyst,139358,1 +60166,Male,57,Diploma,17,32,62,43,88,1.0,5,57,Urban,HR Executive,144941,0 +60167,Male,48,Diploma,12,47,74,45,18,0.0,1,88,Semi-Urban,Software Engineer,132086,1 +60168,Male,32,Masters,15,44,88,31,89,4.0,7,83,Urban,ML Engineer,123600,1 +60169,Male,47,Bachelors,2,41,62,50,85,7.0,7,98,Urban,Software Engineer,22605,1 +60170,Other,35,High School,1,50,67,81,92,3.0,6,99,Urban,HR Executive,62819,1 +60171,Female,26,Masters,6,69,18,89,14,5.0,5,38,Rural,HR Executive,101896,0 +60172,Female,41,Bachelors,12,82,14,69,27,1.0,7,99,Semi-Urban,Software Engineer,62058,1 +60173,Female,21,Bachelors,12,97,6,18,96,6.0,0,81,Semi-Urban,HR Executive,131138,0 +60174,Female,43,Diploma,8,47,35,37,51,8.0,1,19,Urban,Software Engineer,104497,0 +60175,Male,26,Diploma,0,96,84,25,21,0.0,2,44,Urban,Manager,86297,1 +60176,Male,47,High School,18,29,77,58,0,5.0,1,20,Urban,ML Engineer,135864,0 +60177,Male,35,PhD,9,88,8,59,6,2.0,1,96,Rural,Software Engineer,26031,1 +60178,Female,28,Bachelors,10,24,82,33,6,6.0,7,92,Urban,Software Engineer,116264,0 +60179,Male,45,Bachelors,16,62,31,31,74,8.0,1,11,Urban,Data Analyst,75720,0 +60180,Female,52,Masters,0,95,56,71,47,5.0,2,5,Urban,ML Engineer,32730,0 +60181,Female,52,Masters,16,20,64,37,10,9.0,0,1,Urban,Data Analyst,109784,0 +60182,Female,35,Masters,9,78,66,99,57,7.0,4,95,Urban,ML Engineer,126375,1 +60183,Male,46,Bachelors,15,73,68,55,11,7.0,6,48,Rural,Software Engineer,100295,1 +60184,Male,45,Bachelors,12,17,42,28,67,3.0,2,0,Urban,HR Executive,98779,0 +60185,Male,38,Bachelors,4,1,49,17,34,5.0,4,79,Rural,ML Engineer,43101,0 +60186,Female,39,Bachelors,9,14,39,47,41,5.0,4,87,Urban,ML Engineer,101144,0 +60187,Female,38,Bachelors,7,70,53,25,29,3.0,4,40,Semi-Urban,Manager,117863,0 +60188,Male,46,Bachelors,19,51,11,54,46,5.0,3,53,Semi-Urban,Software Engineer,99005,0 +60189,Male,40,Bachelors,14,75,37,49,85,4.0,1,86,Urban,Data Analyst,78513,1 +60190,Female,34,Bachelors,1,55,15,51,24,5.0,0,23,Rural,Software Engineer,106738,0 +60191,Male,31,PhD,7,83,86,28,45,5.0,0,40,Rural,ML Engineer,146245,1 +60192,Other,45,High School,0,66,9,92,89,3.0,0,60,Urban,Software Engineer,128496,0 +60193,Male,24,Masters,13,34,25,33,81,8.0,5,62,Urban,ML Engineer,51515,0 +60194,Female,50,Diploma,14,97,11,11,66,9.0,2,97,Semi-Urban,ML Engineer,52731,0 +60195,Male,37,Diploma,18,89,88,84,26,3.0,2,45,Rural,Data Analyst,22411,1 +60196,Male,41,Bachelors,17,80,83,17,75,6.0,2,53,Urban,Data Analyst,97584,0 +60197,Male,22,High School,17,63,92,7,44,3.0,1,37,Urban,Software Engineer,95084,0 +60198,Female,35,Bachelors,18,72,77,75,50,0.0,3,80,Semi-Urban,HR Executive,89296,1 +60199,Male,51,High School,9,34,23,41,77,9.0,7,68,Rural,HR Executive,108596,0 +60200,Female,55,Masters,12,56,72,85,60,9.0,2,95,Rural,Software Engineer,79064,1 +60201,Male,55,Masters,4,81,53,20,61,2.0,6,4,Semi-Urban,ML Engineer,40340,0 +60202,Female,32,Bachelors,4,49,0,43,77,7.0,0,90,Semi-Urban,ML Engineer,109986,0 +60203,Male,44,High School,1,80,32,18,33,6.0,2,46,Urban,ML Engineer,21103,0 +60204,Male,21,Bachelors,10,61,20,21,18,8.0,0,5,Urban,Data Analyst,82047,0 +60205,Male,21,Masters,4,83,2,29,64,1.0,7,12,Urban,HR Executive,47948,0 +60206,Male,43,Masters,6,18,72,46,9,9.0,1,23,Semi-Urban,Data Analyst,29671,0 +60207,Male,24,Masters,12,30,4,74,45,8.0,3,31,Urban,Data Analyst,126187,0 +60208,Male,27,Bachelors,14,95,19,35,80,9.0,6,18,Rural,Manager,90210,0 +60209,Female,58,Bachelors,5,52,94,72,9,3.0,5,99,Semi-Urban,Software Engineer,64528,1 +60210,Male,50,Bachelors,15,16,47,54,49,7.0,0,56,Urban,Data Analyst,23933,0 +60211,Male,28,Bachelors,19,46,74,39,20,1.0,4,24,Semi-Urban,HR Executive,115614,0 +60212,Male,50,Bachelors,11,67,18,78,91,0.0,2,21,Urban,HR Executive,140284,0 +60213,Male,38,Bachelors,3,16,71,93,16,1.0,7,2,Rural,Data Analyst,61393,0 +60214,Male,51,Bachelors,8,59,21,37,52,4.0,3,88,Urban,ML Engineer,128471,0 +60215,Female,22,Bachelors,11,52,8,46,51,3.0,4,62,Urban,ML Engineer,145581,0 +60216,Male,22,High School,12,39,78,64,3,3.0,1,21,Urban,Software Engineer,88431,0 +60217,Female,24,Masters,16,25,68,17,8,0.0,0,61,Rural,ML Engineer,64521,0 +60218,Male,30,Masters,11,55,2,19,57,8.0,6,45,Semi-Urban,HR Executive,128170,0 +60219,Male,48,Bachelors,11,64,94,58,55,8.0,7,28,Rural,Software Engineer,42731,1 +60220,Female,52,Bachelors,3,33,53,90,45,6.0,6,21,Rural,Manager,89708,0 +60221,Male,38,High School,14,73,88,84,64,0.0,5,2,Urban,Manager,110625,1 +60222,Male,54,Masters,19,52,31,61,45,1.0,3,3,Rural,Software Engineer,22803,0 +60223,Male,32,Bachelors,5,95,92,98,5,1.0,4,96,Semi-Urban,Software Engineer,28490,1 +60224,Female,48,Bachelors,2,37,33,95,78,0.0,4,36,Rural,Manager,24566,0 +60225,Male,38,Diploma,17,51,77,31,28,1.0,4,48,Urban,HR Executive,122723,0 +60226,Other,36,High School,14,74,70,60,79,1.0,4,82,Urban,ML Engineer,145051,1 +60227,Male,53,PhD,5,93,21,61,94,1.0,5,4,Urban,Data Analyst,36855,0 +60228,Male,59,Masters,12,56,79,76,12,2.0,3,9,Urban,Manager,114715,0 +60229,Male,57,Bachelors,13,57,80,5,43,9.0,0,8,Urban,Software Engineer,20468,0 +60230,Male,37,Bachelors,6,9,0,78,63,1.0,6,53,Urban,Data Analyst,98744,0 +60231,Male,53,Bachelors,6,41,80,62,62,4.0,3,46,Semi-Urban,Software Engineer,109027,0 +60232,Female,51,Bachelors,8,67,69,39,79,8.0,5,60,Semi-Urban,Software Engineer,23045,0 +60233,Female,25,Masters,12,63,50,8,91,0.0,3,38,Semi-Urban,Data Analyst,56972,0 +60234,Male,59,High School,4,41,5,68,8,3.0,6,88,Rural,Software Engineer,75576,0 +60235,Female,42,High School,8,72,47,75,16,9.0,6,49,Rural,Software Engineer,119857,1 +60236,Female,40,Diploma,15,4,80,60,1,5.0,0,5,Semi-Urban,HR Executive,57308,0 +60237,Male,56,Bachelors,0,54,56,63,47,3.0,4,64,Urban,Software Engineer,117553,1 +60238,Male,23,PhD,9,65,78,26,2,3.0,7,74,Semi-Urban,HR Executive,39439,1 +60239,Male,33,High School,6,95,27,11,82,6.0,1,94,Urban,Software Engineer,126318,0 +60240,Male,54,Masters,15,13,18,56,63,5.0,1,51,Urban,HR Executive,108736,0 +60241,Female,33,Diploma,12,83,85,47,17,7.0,1,93,Semi-Urban,Software Engineer,29871,1 +60242,Male,35,Masters,15,51,82,79,91,5.0,1,40,Urban,HR Executive,69386,1 +60243,Female,41,Diploma,19,84,86,64,16,2.0,4,79,Urban,ML Engineer,108709,1 +60244,Female,42,Masters,7,96,71,41,34,2.0,1,22,Rural,HR Executive,131615,0 +60245,Male,27,PhD,3,78,69,99,13,7.0,7,60,Urban,Software Engineer,89124,1 +60246,Male,56,High School,6,60,73,47,97,6.0,2,63,Urban,Software Engineer,71521,1 +60247,Female,51,Bachelors,8,43,95,18,85,7.0,1,22,Urban,HR Executive,144627,0 +60248,Male,44,Bachelors,14,49,65,33,46,2.0,3,43,Rural,Manager,58252,0 +60249,Female,38,Bachelors,11,80,17,33,84,7.0,0,81,Urban,Software Engineer,38628,0 +60250,Male,24,Masters,13,32,93,90,99,7.0,5,49,Urban,ML Engineer,59549,1 +60251,Female,24,Diploma,16,72,13,79,82,2.0,3,77,Rural,HR Executive,84963,1 +60252,Other,39,High School,9,85,44,36,11,6.0,7,53,Rural,ML Engineer,94867,0 +60253,Male,56,Bachelors,1,59,84,45,96,1.0,0,36,Urban,Software Engineer,113189,0 +60254,Male,37,Bachelors,15,86,38,61,7,3.0,3,97,Rural,Manager,116125,1 +60255,Male,53,Masters,12,98,86,61,88,7.0,3,81,Semi-Urban,Software Engineer,89605,1 +60256,Male,54,Masters,11,27,0,33,76,4.0,0,73,Urban,Software Engineer,21343,0 +60257,Female,57,Diploma,8,26,35,54,90,6.0,2,14,Urban,Software Engineer,102389,0 +60258,Male,59,Masters,3,14,99,87,67,8.0,0,0,Urban,Manager,136935,0 +60259,Male,22,Bachelors,7,21,65,72,88,8.0,1,37,Semi-Urban,Manager,122445,0 +60260,Female,59,Bachelors,9,70,37,64,77,0.0,0,49,Urban,Manager,52574,0 +60261,Male,25,Bachelors,17,21,2,67,94,0.0,7,88,Rural,ML Engineer,41382,0 +60262,Female,51,Diploma,14,27,69,78,38,2.0,7,79,Semi-Urban,HR Executive,36395,1 +60263,Male,41,Diploma,0,53,3,40,94,9.0,4,15,Rural,Data Analyst,31957,0 +60264,Male,58,Bachelors,12,75,22,58,81,1.0,0,58,Semi-Urban,ML Engineer,75141,0 +60265,Male,58,Diploma,9,31,9,72,37,8.0,3,35,Urban,ML Engineer,78169,0 +60266,Male,50,Bachelors,18,15,27,26,18,3.0,0,6,Rural,Software Engineer,37848,0 +60267,Female,29,Bachelors,19,70,33,63,84,0.0,6,65,Semi-Urban,ML Engineer,106620,0 +60268,Male,38,High School,10,67,43,71,28,4.0,4,88,Urban,Manager,65313,1 +60269,Male,56,Bachelors,18,84,35,2,1,7.0,4,60,Urban,Data Analyst,83632,0 +60270,Male,24,Masters,5,96,42,8,51,1.0,6,26,Urban,HR Executive,62484,0 +60271,Male,30,Bachelors,17,85,69,53,88,3.0,1,52,Semi-Urban,Data Analyst,134323,1 +60272,Female,57,Diploma,16,52,53,2,54,2.0,1,53,Rural,HR Executive,90117,0 +60273,Male,24,Diploma,15,43,95,90,32,9.0,2,10,Semi-Urban,Software Engineer,143061,1 +60274,Male,57,Diploma,6,56,13,20,90,8.0,0,18,Urban,Software Engineer,79145,0 +60275,Male,33,Diploma,5,51,28,67,61,7.0,2,65,Rural,HR Executive,101426,0 +60276,Male,43,PhD,17,82,35,19,31,7.0,6,66,Urban,HR Executive,144166,0 +60277,Male,22,Masters,12,92,82,95,84,1.0,1,28,Rural,Manager,142322,1 +60278,Male,34,High School,4,67,85,14,76,5.0,2,34,Semi-Urban,Manager,107776,0 +60279,Female,59,Masters,4,3,32,6,3,7.0,1,90,Urban,HR Executive,113446,0 +60280,Male,32,Bachelors,9,19,51,89,61,1.0,5,4,Urban,Manager,100971,0 +60281,Male,37,High School,3,60,22,43,99,2.0,0,99,Semi-Urban,HR Executive,49740,0 +60282,Female,30,Bachelors,1,27,91,95,9,6.0,4,24,Urban,HR Executive,119188,0 +60283,Male,54,Diploma,0,25,64,70,98,6.0,1,87,Semi-Urban,Software Engineer,49677,1 +60284,Male,55,Bachelors,11,50,16,70,42,4.0,7,84,Rural,ML Engineer,112444,0 +60285,Male,23,Diploma,1,96,51,68,48,5.0,1,0,Semi-Urban,Software Engineer,31146,0 +60286,Female,32,Diploma,12,26,82,8,39,7.0,3,9,Urban,Manager,74449,0 +60287,Male,47,Bachelors,8,68,38,16,41,1.0,3,93,Urban,Manager,73030,0 +60288,Male,36,High School,17,65,42,36,35,7.0,6,66,Urban,Manager,97838,0 +60289,Male,28,PhD,5,41,92,93,63,9.0,5,67,Urban,Software Engineer,105035,1 +60290,Male,59,Masters,17,48,90,2,94,3.0,6,45,Urban,HR Executive,119759,0 +60291,Male,35,High School,10,77,88,24,9,9.0,7,96,Rural,HR Executive,62282,1 +60292,Female,57,Diploma,2,95,39,1,31,2.0,5,93,Urban,HR Executive,86692,0 +60293,Male,36,Bachelors,6,11,8,61,31,5.0,7,25,Rural,ML Engineer,98497,0 +60294,Male,32,Masters,18,33,80,70,46,2.0,2,74,Urban,Data Analyst,30372,1 +60295,Male,58,High School,2,80,72,1,32,8.0,0,36,Rural,ML Engineer,149375,0 +60296,Female,59,Bachelors,12,93,70,62,87,1.0,4,56,Urban,Manager,119198,1 +60297,Female,45,Bachelors,4,18,54,54,87,1.0,5,78,Urban,Manager,78128,0 +60298,Female,53,High School,11,76,98,14,36,8.0,5,20,Urban,Manager,56597,0 +60299,Female,42,Masters,5,33,7,4,94,9.0,1,87,Urban,HR Executive,61743,0 +60300,Female,54,Diploma,7,46,32,90,68,8.0,7,63,Urban,Data Analyst,120690,0 +60301,Female,22,Bachelors,11,71,74,81,52,0.0,1,54,Rural,Data Analyst,145175,1 +60302,Female,54,Diploma,9,69,12,68,99,2.0,3,48,Urban,Software Engineer,134637,0 +60303,Male,42,Diploma,11,19,49,78,59,5.0,0,75,Urban,Software Engineer,111059,0 +60304,Other,38,Bachelors,16,77,4,16,34,8.0,7,53,Semi-Urban,Software Engineer,142734,0 +60305,Male,24,Bachelors,9,77,23,39,97,8.0,1,4,Rural,Manager,105358,0 +60306,Male,39,Diploma,13,59,41,72,18,8.0,7,54,Semi-Urban,Software Engineer,124852,0 +60307,Male,21,Masters,10,63,53,82,73,8.0,6,34,Rural,Software Engineer,61309,0 +60308,Female,39,Bachelors,14,53,14,80,51,6.0,4,66,Urban,ML Engineer,29459,0 +60309,Male,51,Bachelors,15,92,23,39,18,5.0,0,39,Rural,HR Executive,97156,0 +60310,Male,27,High School,17,14,89,62,20,3.0,7,47,Semi-Urban,Manager,106456,0 +60311,Male,37,Masters,18,48,3,57,11,7.0,2,75,Semi-Urban,ML Engineer,120743,0 +60312,Female,43,Diploma,10,23,35,25,59,3.0,0,30,Urban,Software Engineer,74407,0 +60313,Male,26,High School,0,34,73,1,2,9.0,7,74,Urban,Data Analyst,56379,0 +60314,Female,26,Masters,12,88,0,2,5,6.0,3,12,Urban,ML Engineer,30406,0 +60315,Female,39,Bachelors,13,59,43,18,22,2.0,2,11,Urban,Manager,51672,0 +60316,Female,56,Bachelors,16,65,19,35,29,1.0,2,8,Urban,ML Engineer,102957,0 +60317,Male,56,Masters,17,96,3,10,73,8.0,4,80,Rural,Manager,38218,0 +60318,Female,35,High School,18,90,63,99,20,7.0,4,94,Urban,Software Engineer,38814,1 +60319,Male,49,Masters,7,68,71,34,64,3.0,5,89,Semi-Urban,Data Analyst,122283,1 +60320,Male,58,Bachelors,19,13,50,57,63,5.0,3,58,Semi-Urban,ML Engineer,113992,0 +60321,Male,31,Diploma,7,52,26,97,83,6.0,4,40,Urban,ML Engineer,27987,0 +60322,Male,55,Diploma,4,76,24,13,84,7.0,5,55,Urban,Software Engineer,30133,0 +60323,Male,29,High School,1,16,50,3,28,7.0,1,8,Semi-Urban,Software Engineer,133749,0 +60324,Male,28,Diploma,4,7,32,27,42,6.0,5,38,Semi-Urban,Data Analyst,36553,0 +60325,Male,34,Bachelors,11,53,86,51,9,6.0,7,31,Urban,Software Engineer,64540,0 +60326,Female,56,Bachelors,8,2,53,22,72,5.0,1,51,Semi-Urban,Manager,91949,0 +60327,Female,48,Bachelors,9,22,90,28,5,4.0,3,51,Rural,Software Engineer,141341,0 +60328,Female,25,Diploma,3,58,24,78,98,9.0,3,31,Semi-Urban,Manager,22295,0 +60329,Male,28,Masters,7,65,84,0,49,8.0,4,72,Urban,Data Analyst,95346,0 +60330,Male,31,Masters,14,2,29,20,69,3.0,5,30,Urban,Data Analyst,74700,0 +60331,Male,29,Bachelors,12,18,90,76,22,8.0,6,28,Urban,Software Engineer,122340,0 +60332,Male,42,Bachelors,16,66,49,88,7,3.0,4,74,Urban,Software Engineer,106723,1 +60333,Male,33,Bachelors,12,24,7,81,49,9.0,4,38,Semi-Urban,Software Engineer,132888,0 +60334,Male,31,Masters,11,2,71,67,64,6.0,1,48,Urban,Data Analyst,29633,0 +60335,Male,43,Bachelors,5,98,27,36,44,0.0,3,34,Urban,Software Engineer,60274,0 +60336,Male,32,Diploma,4,82,38,82,40,2.0,0,13,Urban,Data Analyst,29983,0 +60337,Male,59,Bachelors,12,95,72,78,9,1.0,7,60,Urban,Data Analyst,20998,1 +60338,Female,49,Bachelors,6,79,62,1,18,5.0,0,6,Semi-Urban,HR Executive,22657,0 +60339,Female,31,Bachelors,1,77,65,13,57,6.0,6,77,Semi-Urban,HR Executive,66725,0 +60340,Male,46,Bachelors,17,4,56,64,52,5.0,4,6,Semi-Urban,ML Engineer,92404,0 +60341,Male,43,Masters,18,2,46,19,83,2.0,7,24,Semi-Urban,ML Engineer,104607,0 +60342,Other,58,Masters,0,2,64,97,0,7.0,6,84,Urban,Software Engineer,105238,1 +60343,Female,43,Masters,13,90,29,18,70,4.0,1,34,Rural,Software Engineer,127648,0 +60344,Male,49,High School,19,63,64,36,31,6.0,4,75,Rural,Manager,121133,1 +60345,Male,48,High School,0,2,72,1,7,0.0,1,91,Rural,HR Executive,63098,0 +60346,Male,29,Diploma,3,36,66,67,7,4.0,0,72,Urban,ML Engineer,68665,1 +60347,Female,53,Bachelors,12,26,41,92,31,6.0,7,15,Semi-Urban,ML Engineer,89923,0 +60348,Male,33,High School,19,27,25,29,88,1.0,1,0,Semi-Urban,HR Executive,65573,0 +60349,Male,47,Bachelors,15,65,58,95,90,6.0,0,80,Urban,Manager,98105,1 +60350,Female,59,Masters,7,10,95,44,38,9.0,6,45,Urban,Data Analyst,38911,0 +60351,Female,49,Bachelors,13,36,24,17,60,6.0,2,34,Rural,Software Engineer,73546,0 +60352,Male,54,High School,11,68,10,44,88,2.0,1,51,Semi-Urban,ML Engineer,108686,0 +60353,Male,50,Diploma,6,18,76,99,4,0.0,1,61,Urban,Software Engineer,113762,1 +60354,Female,31,Bachelors,1,11,92,15,35,3.0,5,11,Rural,Software Engineer,60519,0 +60355,Male,25,High School,3,92,7,32,43,7.0,5,47,Urban,ML Engineer,133977,0 +60356,Female,30,Bachelors,14,9,30,90,28,9.0,5,57,Urban,ML Engineer,39249,0 +60357,Male,51,Masters,14,24,56,35,9,0.0,6,69,Urban,ML Engineer,120546,0 +60358,Female,59,Bachelors,16,13,47,16,83,2.0,6,27,Urban,Data Analyst,140480,0 +60359,Male,54,Bachelors,11,72,96,69,22,3.0,0,20,Urban,Software Engineer,41822,1 +60360,Male,32,Masters,1,97,33,23,96,1.0,3,23,Semi-Urban,Software Engineer,75647,0 +60361,Male,32,High School,1,15,0,98,60,5.0,4,16,Urban,HR Executive,106700,0 +60362,Female,28,Bachelors,0,85,63,80,67,6.0,3,83,Urban,Software Engineer,102051,1 +60363,Male,28,Bachelors,0,45,81,9,45,3.0,7,14,Urban,Data Analyst,108257,0 +60364,Male,43,Bachelors,4,78,61,82,75,0.0,3,61,Urban,Software Engineer,33784,1 +60365,Male,34,High School,1,80,32,16,81,1.0,7,4,Urban,Manager,38349,0 +60366,Female,22,Bachelors,9,63,40,30,12,7.0,1,3,Urban,Software Engineer,22916,0 +60367,Male,39,PhD,7,71,98,10,36,4.0,5,3,Urban,ML Engineer,126188,0 +60368,Male,34,High School,15,49,95,57,81,1.0,7,4,Urban,ML Engineer,43996,0 +60369,Male,50,PhD,12,13,27,23,15,7.0,7,82,Urban,Manager,43763,0 +60370,Male,27,High School,10,51,92,62,15,3.0,7,88,Rural,Software Engineer,116501,1 +60371,Male,41,High School,7,81,58,37,38,5.0,6,17,Urban,Manager,104832,0 +60372,Male,43,Bachelors,9,71,77,14,85,5.0,4,86,Semi-Urban,Manager,94160,1 +60373,Female,41,Masters,9,77,6,79,27,4.0,5,41,Rural,Manager,24829,0 +60374,Female,53,High School,16,81,90,27,46,9.0,6,81,Urban,Data Analyst,41197,1 +60375,Female,35,Masters,9,19,79,43,48,2.0,7,83,Urban,ML Engineer,43823,0 +60376,Male,24,Diploma,7,12,6,73,35,8.0,1,72,Urban,Software Engineer,147013,0 +60377,Female,37,Diploma,9,5,58,17,42,6.0,1,50,Rural,ML Engineer,148193,0 +60378,Male,29,High School,16,59,54,98,32,1.0,3,99,Semi-Urban,Software Engineer,65570,1 +60379,Female,38,Diploma,19,30,5,79,33,0.0,6,66,Urban,Manager,30018,0 +60380,Male,36,Bachelors,6,43,2,43,59,0.0,6,12,Rural,Software Engineer,96580,0 +60381,Male,41,Diploma,16,81,4,58,11,5.0,5,29,Semi-Urban,ML Engineer,59528,0 +60382,Female,47,Bachelors,15,57,54,38,20,9.0,6,18,Semi-Urban,Software Engineer,23536,0 +60383,Male,21,Bachelors,10,34,89,76,84,4.0,2,64,Semi-Urban,ML Engineer,112704,1 +60384,Other,57,High School,4,44,17,92,35,0.0,0,65,Semi-Urban,Software Engineer,46534,0 +60385,Female,27,Diploma,14,68,11,65,33,0.0,4,68,Semi-Urban,Manager,112054,0 +60386,Female,23,Bachelors,13,77,9,26,44,7.0,3,79,Semi-Urban,HR Executive,59911,0 +60387,Female,56,Masters,5,50,99,13,99,5.0,5,48,Urban,HR Executive,120355,0 +60388,Male,23,Bachelors,9,85,40,79,83,6.0,7,83,Urban,HR Executive,123450,1 +60389,Male,23,Diploma,19,2,20,85,79,6.0,2,54,Urban,Manager,126866,0 +60390,Female,39,Bachelors,14,11,35,40,9,3.0,1,26,Rural,Software Engineer,72515,0 +60391,Male,34,Masters,7,76,58,77,47,8.0,7,64,Semi-Urban,ML Engineer,54844,1 +60392,Female,57,Diploma,15,58,27,62,17,8.0,7,80,Semi-Urban,ML Engineer,130365,0 +60393,Female,45,Diploma,6,10,6,0,55,2.0,0,90,Urban,Data Analyst,112733,0 +60394,Male,56,PhD,17,19,45,70,84,3.0,3,41,Urban,Data Analyst,137503,0 +60395,Male,33,High School,13,33,29,81,0,0.0,2,51,Urban,Data Analyst,20968,0 +60396,Female,40,Diploma,11,29,73,97,92,1.0,5,23,Urban,ML Engineer,130572,0 +60397,Male,24,Bachelors,3,11,49,34,93,4.0,5,61,Urban,HR Executive,89509,0 +60398,Male,38,PhD,0,15,48,0,63,4.0,0,19,Urban,Data Analyst,86565,0 +60399,Male,56,Masters,10,32,87,86,65,6.0,0,62,Rural,ML Engineer,113381,1 +60400,Female,36,High School,1,46,75,88,72,9.0,5,40,Rural,ML Engineer,120362,1 +60401,Other,37,Diploma,16,97,3,48,33,4.0,4,59,Urban,HR Executive,119118,0 +60402,Male,32,Bachelors,8,35,37,77,48,2.0,6,58,Rural,Software Engineer,136867,0 +60403,Female,48,High School,0,80,54,38,27,5.0,7,67,Urban,HR Executive,49262,0 +60404,Male,58,Masters,17,99,0,97,53,4.0,3,79,Urban,Manager,128612,1 +60405,Female,59,High School,18,54,88,77,20,2.0,1,30,Rural,HR Executive,73460,1 +60406,Male,39,Diploma,6,18,71,71,94,6.0,4,4,Urban,HR Executive,133503,0 +60407,Male,42,High School,18,3,14,2,62,2.0,6,88,Urban,Software Engineer,51602,0 +60408,Female,36,PhD,2,21,55,18,6,8.0,7,8,Semi-Urban,HR Executive,25506,0 +60409,Male,55,Bachelors,0,76,64,12,88,7.0,3,54,Urban,Software Engineer,52853,0 +60410,Male,41,PhD,3,17,8,80,80,5.0,1,56,Semi-Urban,HR Executive,60837,0 +60411,Male,49,High School,9,82,34,23,88,2.0,1,32,Rural,ML Engineer,63614,0 +60412,Male,32,Masters,4,38,90,43,54,3.0,3,40,Urban,ML Engineer,20260,0 +60413,Male,41,Bachelors,10,67,6,75,43,8.0,0,30,Urban,Manager,32620,0 +60414,Female,33,Bachelors,6,27,54,36,54,0.0,4,0,Urban,Software Engineer,126672,0 +60415,Female,28,PhD,7,70,90,13,79,9.0,4,42,Urban,ML Engineer,75295,0 +60416,Male,42,Bachelors,19,13,11,45,43,4.0,1,65,Urban,Manager,41028,0 +60417,Other,47,Bachelors,8,20,38,65,42,1.0,4,2,Urban,Software Engineer,99910,0 +60418,Male,57,Diploma,0,72,71,80,36,0.0,5,72,Rural,Software Engineer,75191,1 +60419,Female,49,Masters,16,88,74,59,1,8.0,1,93,Urban,Data Analyst,53586,1 +60420,Male,52,Masters,12,17,47,76,58,3.0,0,32,Urban,HR Executive,147605,0 +60421,Male,48,Masters,16,88,58,40,30,5.0,5,14,Urban,HR Executive,57357,0 +60422,Male,47,High School,3,39,31,30,95,9.0,5,40,Urban,Manager,111868,0 +60423,Female,40,Bachelors,8,12,64,59,6,3.0,3,86,Semi-Urban,HR Executive,42738,0 +60424,Female,43,Diploma,2,6,18,16,93,1.0,4,73,Semi-Urban,Software Engineer,64515,0 +60425,Male,29,Masters,18,73,43,9,65,1.0,6,77,Rural,Data Analyst,128332,0 +60426,Male,23,High School,16,6,21,46,38,6.0,0,6,Urban,Data Analyst,112031,0 +60427,Female,44,Bachelors,6,86,46,86,81,2.0,7,95,Urban,Manager,113080,1 +60428,Female,21,Masters,8,0,26,44,64,3.0,5,9,Urban,Data Analyst,79633,0 +60429,Female,59,High School,1,99,24,42,11,1.0,4,15,Rural,Manager,92583,0 +60430,Male,53,Masters,13,26,50,39,30,5.0,5,15,Rural,Software Engineer,83873,0 +60431,Male,48,Bachelors,6,20,86,8,55,4.0,6,12,Urban,Manager,142311,0 +60432,Female,32,Bachelors,2,47,44,12,32,6.0,5,36,Semi-Urban,Manager,130234,0 +60433,Male,22,Diploma,10,88,96,48,93,2.0,3,99,Urban,Software Engineer,77677,1 +60434,Male,42,High School,7,92,59,55,46,6.0,5,55,Semi-Urban,Manager,40377,1 +60435,Male,59,Bachelors,6,55,2,53,56,3.0,5,27,Semi-Urban,Data Analyst,37409,0 +60436,Male,35,Bachelors,18,11,78,92,64,1.0,5,46,Urban,Manager,70663,0 +60437,Female,37,High School,8,40,70,94,46,6.0,7,96,Rural,ML Engineer,41771,1 +60438,Female,28,Bachelors,16,50,76,69,27,4.0,6,42,Rural,Software Engineer,129198,0 +60439,Other,49,High School,5,16,64,72,45,3.0,2,35,Urban,Data Analyst,145370,0 +60440,Male,50,Bachelors,15,4,51,44,98,3.0,3,42,Urban,ML Engineer,115537,0 +60441,Male,54,Masters,13,88,63,38,11,3.0,5,72,Urban,Data Analyst,24140,1 +60442,Male,49,Bachelors,8,45,21,4,95,0.0,6,75,Semi-Urban,Data Analyst,91147,0 +60443,Male,41,Bachelors,4,71,59,93,33,7.0,2,85,Urban,HR Executive,23542,1 +60444,Male,27,Diploma,18,55,16,71,57,5.0,6,75,Semi-Urban,ML Engineer,26576,0 +60445,Male,24,High School,0,90,44,43,17,3.0,2,42,Urban,Software Engineer,59495,0 +60446,Male,40,Bachelors,10,15,48,57,99,0.0,5,39,Urban,Manager,47224,0 +60447,Female,23,High School,19,75,95,17,31,2.0,0,37,Urban,Software Engineer,71032,0 +60448,Male,45,High School,10,13,68,92,71,2.0,1,49,Urban,Manager,96220,0 +60449,Female,38,Bachelors,3,50,64,16,14,2.0,6,48,Urban,ML Engineer,84414,0 +60450,Male,22,High School,2,99,36,14,34,0.0,4,55,Semi-Urban,HR Executive,123785,0 +60451,Male,41,Masters,15,5,35,38,71,4.0,3,71,Urban,ML Engineer,127373,0 +60452,Male,29,Bachelors,14,54,66,40,88,3.0,7,49,Urban,Manager,141210,0 +60453,Female,23,Bachelors,9,34,64,35,30,9.0,3,70,Urban,Data Analyst,20588,0 +60454,Male,42,Masters,7,7,22,31,33,7.0,7,89,Semi-Urban,Software Engineer,123455,0 +60455,Male,31,Bachelors,2,57,35,93,16,5.0,6,38,Urban,ML Engineer,115323,0 +60456,Male,31,High School,5,4,20,93,31,1.0,0,99,Semi-Urban,Manager,24646,0 +60457,Female,51,PhD,14,12,87,90,56,5.0,1,0,Urban,ML Engineer,124258,0 +60458,Female,25,High School,7,25,75,51,63,2.0,6,35,Semi-Urban,Data Analyst,88630,0 +60459,Female,31,High School,18,47,54,49,73,5.0,5,30,Urban,ML Engineer,110546,0 +60460,Male,44,Bachelors,16,33,46,23,93,4.0,4,46,Semi-Urban,ML Engineer,44625,0 +60461,Female,38,Bachelors,16,36,4,58,80,6.0,4,85,Urban,Data Analyst,81540,0 +60462,Female,30,Diploma,10,67,42,10,77,5.0,2,66,Urban,Software Engineer,137415,0 +60463,Male,30,Bachelors,8,43,8,28,82,5.0,6,61,Rural,ML Engineer,70809,0 +60464,Male,46,Bachelors,13,61,9,61,37,9.0,7,57,Semi-Urban,ML Engineer,44203,0 +60465,Male,29,High School,5,15,19,79,76,6.0,2,33,Semi-Urban,Software Engineer,148299,0 +60466,Female,36,High School,8,50,85,71,67,8.0,5,10,Urban,ML Engineer,102104,0 +60467,Male,37,Bachelors,2,21,22,43,50,2.0,1,14,Rural,ML Engineer,124516,0 +60468,Male,32,High School,1,17,64,17,11,8.0,3,8,Urban,Manager,105230,0 +60469,Male,58,Bachelors,14,60,26,9,53,6.0,6,96,Urban,Data Analyst,26219,0 +60470,Male,53,High School,12,98,80,78,43,5.0,0,37,Urban,ML Engineer,72985,1 +60471,Male,45,Bachelors,19,13,64,41,46,2.0,2,4,Urban,ML Engineer,149946,0 +60472,Female,25,Bachelors,9,93,84,97,57,3.0,6,31,Semi-Urban,Data Analyst,42066,1 +60473,Male,57,Diploma,3,83,89,2,82,0.0,5,50,Urban,Data Analyst,47215,0 +60474,Male,59,Masters,1,37,91,44,51,2.0,7,52,Urban,HR Executive,67681,0 +60475,Female,50,Bachelors,15,26,52,41,25,4.0,2,61,Urban,Manager,58400,0 +60476,Female,46,Diploma,7,93,31,2,34,7.0,3,29,Semi-Urban,Data Analyst,77793,0 +60477,Female,31,Bachelors,12,61,43,23,39,4.0,3,92,Semi-Urban,HR Executive,109591,0 +60478,Male,30,Diploma,11,35,88,93,86,2.0,2,63,Urban,Software Engineer,80178,1 +60479,Male,35,Masters,3,65,38,27,71,4.0,3,37,Urban,Manager,133395,0 +60480,Male,52,Masters,9,96,60,39,67,2.0,6,5,Urban,Manager,24446,0 +60481,Male,42,Bachelors,1,94,53,10,88,4.0,0,59,Rural,HR Executive,120172,0 +60482,Male,35,Bachelors,1,76,7,93,75,3.0,7,6,Semi-Urban,Data Analyst,37976,0 +60483,Male,30,Diploma,17,86,66,71,36,6.0,6,9,Urban,Software Engineer,24281,0 +60484,Male,46,High School,12,41,90,2,92,3.0,3,67,Urban,Manager,111953,0 +60485,Female,51,Bachelors,17,2,26,33,16,3.0,5,23,Urban,Data Analyst,35912,0 +60486,Male,49,Bachelors,16,97,64,20,81,7.0,7,11,Semi-Urban,HR Executive,144391,0 +60487,Female,25,Bachelors,17,3,39,69,48,8.0,4,73,Rural,Data Analyst,103422,0 +60488,Male,30,High School,8,31,56,67,13,3.0,2,29,Urban,HR Executive,92070,0 +60489,Male,38,Bachelors,16,61,50,26,74,9.0,3,6,Urban,Manager,59504,0 +60490,Female,39,Masters,2,62,34,24,55,8.0,2,12,Rural,Software Engineer,122295,0 +60491,Other,49,Bachelors,16,61,88,2,2,2.0,6,91,Urban,Data Analyst,77315,1 +60492,Female,37,Diploma,18,76,35,92,81,6.0,4,9,Semi-Urban,Software Engineer,72824,0 +60493,Female,40,Diploma,17,8,67,4,90,9.0,4,18,Semi-Urban,Software Engineer,23645,0 +60494,Male,31,High School,12,53,88,7,71,8.0,4,22,Urban,HR Executive,28127,0 +60495,Male,43,Masters,15,71,54,26,8,9.0,2,87,Urban,Software Engineer,130500,1 +60496,Female,53,Bachelors,17,12,45,82,21,9.0,6,40,Urban,Data Analyst,118181,0 +60497,Male,50,Diploma,6,48,46,30,88,0.0,6,91,Urban,Data Analyst,42605,0 +60498,Male,33,High School,16,10,15,84,67,5.0,7,65,Rural,Software Engineer,29736,0 +60499,Male,35,Bachelors,10,85,10,2,37,9.0,7,98,Urban,HR Executive,113698,0 +60500,Female,29,Bachelors,17,12,78,9,81,5.0,0,71,Urban,ML Engineer,138024,0 +60501,Male,48,Diploma,6,2,22,61,16,0.0,3,8,Rural,Software Engineer,142220,0 +60502,Female,38,High School,5,53,34,17,2,3.0,2,14,Urban,HR Executive,21241,0 +60503,Female,52,Masters,7,10,27,72,57,0.0,0,13,Urban,Manager,23362,0 +60504,Male,41,Masters,5,43,97,23,85,2.0,1,29,Urban,HR Executive,125029,0 +60505,Male,54,Bachelors,19,11,33,21,66,0.0,2,49,Semi-Urban,HR Executive,70196,0 +60506,Female,49,High School,17,39,32,24,81,4.0,5,26,Urban,Data Analyst,117709,0 +60507,Female,24,High School,8,86,77,3,46,6.0,3,78,Urban,Software Engineer,67304,1 +60508,Male,55,Diploma,11,52,9,46,29,8.0,6,2,Semi-Urban,Manager,50873,0 +60509,Male,37,Bachelors,5,91,71,37,38,4.0,3,60,Semi-Urban,Manager,76053,1 +60510,Male,33,High School,5,95,12,10,23,9.0,7,0,Semi-Urban,Data Analyst,20641,0 +60511,Other,33,Diploma,1,54,96,77,11,8.0,2,83,Urban,ML Engineer,115514,1 +60512,Female,41,Diploma,15,2,18,80,52,1.0,2,22,Rural,Manager,80499,0 +60513,Female,28,Masters,5,13,19,53,36,2.0,6,41,Semi-Urban,Software Engineer,79245,0 +60514,Male,28,Masters,3,42,88,81,5,8.0,0,45,Rural,ML Engineer,124529,1 +60515,Male,38,Bachelors,2,57,40,4,37,9.0,3,27,Semi-Urban,ML Engineer,21802,0 +60516,Female,36,Diploma,10,35,58,33,54,5.0,3,95,Rural,Manager,43305,0 +60517,Female,48,Bachelors,8,1,9,4,76,1.0,0,1,Rural,ML Engineer,80282,0 +60518,Male,38,Masters,19,87,47,44,85,1.0,7,75,Semi-Urban,Data Analyst,25756,1 +60519,Other,43,Bachelors,2,95,80,94,19,7.0,6,34,Urban,ML Engineer,87180,1 +60520,Male,37,Masters,15,0,68,10,44,9.0,3,8,Rural,Software Engineer,92892,0 +60521,Male,39,Masters,5,68,81,81,58,1.0,3,99,Urban,ML Engineer,123182,1 +60522,Female,50,Diploma,0,34,5,47,3,9.0,0,35,Semi-Urban,ML Engineer,51237,0 +60523,Female,42,Diploma,12,56,12,58,43,2.0,1,54,Urban,ML Engineer,43646,0 +60524,Female,39,Bachelors,12,47,48,25,64,2.0,7,79,Urban,HR Executive,91331,0 +60525,Female,35,Bachelors,1,34,11,31,43,0.0,2,67,Semi-Urban,ML Engineer,39685,0 +60526,Male,32,Bachelors,7,78,74,13,30,5.0,2,75,Semi-Urban,Manager,94113,1 +60527,Male,31,Bachelors,6,63,37,2,67,6.0,0,95,Rural,Manager,23370,0 +60528,Female,38,Diploma,12,27,45,98,21,7.0,0,26,Rural,HR Executive,63261,0 +60529,Male,53,Bachelors,8,73,48,11,38,4.0,1,47,Urban,ML Engineer,138726,0 +60530,Female,44,Bachelors,4,41,31,36,86,3.0,6,88,Rural,HR Executive,61510,0 +60531,Male,36,Masters,8,79,62,62,93,3.0,2,48,Rural,Software Engineer,26014,1 +60532,Female,50,Masters,14,88,7,75,50,6.0,0,71,Urban,Software Engineer,40147,1 +60533,Female,58,Diploma,7,76,99,13,93,0.0,1,35,Urban,HR Executive,116115,0 +60534,Female,57,High School,11,14,73,41,98,6.0,3,70,Rural,HR Executive,139349,0 +60535,Female,27,Masters,2,47,8,65,47,6.0,5,19,Rural,HR Executive,118313,0 +60536,Male,38,Masters,14,70,84,56,44,6.0,1,82,Urban,ML Engineer,143089,1 +60537,Male,37,High School,19,27,63,71,81,4.0,3,20,Rural,Manager,113661,0 +60538,Other,35,Masters,15,6,97,69,20,3.0,7,61,Urban,ML Engineer,70339,0 +60539,Female,50,Bachelors,19,62,43,67,38,6.0,1,81,Rural,Data Analyst,68003,1 +60540,Female,38,Diploma,13,81,3,46,3,4.0,3,46,Urban,Software Engineer,124100,0 +60541,Male,35,Bachelors,11,62,88,70,16,7.0,5,26,Rural,Manager,77265,1 +60542,Male,56,Masters,17,50,61,41,71,1.0,7,79,Semi-Urban,HR Executive,130640,0 +60543,Female,33,Bachelors,2,42,29,57,75,6.0,3,20,Urban,HR Executive,114341,0 +60544,Female,52,High School,2,5,25,22,39,1.0,2,71,Rural,Manager,135613,0 +60545,Male,59,Masters,18,13,14,67,60,9.0,1,73,Semi-Urban,Data Analyst,52499,0 +60546,Male,24,Bachelors,9,6,60,72,2,3.0,6,87,Urban,Data Analyst,52286,0 +60547,Male,54,High School,11,76,50,76,15,7.0,6,90,Urban,Software Engineer,129471,1 +60548,Male,30,Bachelors,10,51,39,83,69,3.0,7,45,Rural,Data Analyst,128577,0 +60549,Male,43,Bachelors,15,74,63,30,83,5.0,0,53,Rural,Data Analyst,81213,0 +60550,Male,47,Diploma,10,55,69,74,33,5.0,1,69,Rural,Data Analyst,114917,1 +60551,Female,54,Diploma,4,1,3,64,60,0.0,2,22,Urban,HR Executive,75789,0 +60552,Other,35,Diploma,2,85,23,4,4,9.0,5,21,Urban,Manager,110157,0 +60553,Male,52,Diploma,6,75,69,7,21,2.0,6,20,Rural,Manager,88816,0 +60554,Male,40,Masters,11,15,21,25,53,1.0,5,10,Urban,Data Analyst,29300,0 +60555,Male,57,Diploma,13,26,15,77,98,6.0,7,53,Urban,Manager,71293,0 +60556,Female,28,High School,2,0,21,50,61,7.0,5,50,Semi-Urban,Manager,55510,0 +60557,Male,48,Bachelors,11,53,90,81,72,7.0,2,73,Semi-Urban,Data Analyst,24312,1 +60558,Male,37,Bachelors,13,88,85,48,57,,0,50,Urban,HR Executive,140629,1 +60559,Male,50,PhD,15,85,30,55,35,4.0,2,63,Urban,Data Analyst,24903,0 +60560,Male,54,Bachelors,12,42,17,31,54,7.0,5,88,Urban,ML Engineer,135898,0 +60561,Male,33,Diploma,12,51,22,80,21,1.0,2,43,Semi-Urban,Software Engineer,78742,0 +60562,Male,23,High School,17,96,20,88,94,7.0,6,64,Rural,Data Analyst,121954,1 +60563,Female,26,Masters,15,31,38,11,44,6.0,7,72,Urban,Manager,106462,0 +60564,Female,38,Masters,0,94,6,35,19,2.0,4,17,Urban,HR Executive,119752,0 +60565,Male,58,Bachelors,19,78,37,98,90,0.0,6,95,Urban,ML Engineer,88347,1 +60566,Male,53,Diploma,18,73,48,1,38,3.0,1,17,Urban,ML Engineer,88215,0 +60567,Male,24,Bachelors,10,61,28,31,16,7.0,0,76,Rural,Data Analyst,36462,0 +60568,Male,42,Masters,12,1,2,65,1,6.0,7,16,Urban,Data Analyst,76700,0 +60569,Female,40,PhD,2,26,94,36,33,0.0,7,21,Semi-Urban,Software Engineer,71419,0 +60570,Male,37,Bachelors,7,12,10,56,7,5.0,6,89,Urban,Software Engineer,136268,0 +60571,Male,55,Bachelors,7,53,7,96,94,0.0,6,49,Urban,ML Engineer,35334,0 +60572,Male,53,Bachelors,7,44,4,79,91,8.0,2,65,Semi-Urban,HR Executive,104423,0 +60573,Male,42,High School,9,19,66,97,14,6.0,3,52,Urban,Software Engineer,61311,0 +60574,Female,52,Bachelors,11,19,43,55,48,2.0,4,43,Urban,Data Analyst,29631,0 +60575,Female,29,Diploma,3,61,21,73,82,1.0,0,59,Rural,Manager,118850,0 +60576,Female,59,Diploma,19,80,50,40,2,6.0,7,81,Urban,Software Engineer,141473,1 +60577,Female,24,Diploma,16,82,87,23,69,2.0,3,77,Urban,Data Analyst,117006,1 +60578,Male,28,Masters,10,8,2,90,90,3.0,3,28,Urban,ML Engineer,110683,0 +60579,Male,54,Bachelors,8,69,90,58,55,4.0,0,44,Semi-Urban,HR Executive,74673,1 +60580,Female,41,High School,7,60,94,70,32,7.0,1,97,Semi-Urban,HR Executive,73187,1 +60581,Female,41,Bachelors,7,43,8,4,14,2.0,4,42,Semi-Urban,ML Engineer,61337,0 +60582,Male,22,Bachelors,6,86,43,51,76,4.0,1,34,Rural,Software Engineer,98588,0 +60583,Male,43,High School,8,59,11,4,57,7.0,5,24,Urban,Software Engineer,124505,0 +60584,Male,51,Bachelors,0,10,3,50,54,6.0,7,86,Semi-Urban,ML Engineer,73805,0 +60585,Female,54,Bachelors,17,32,77,88,53,3.0,3,96,Semi-Urban,HR Executive,105688,1 +60586,Female,22,Bachelors,0,31,13,75,96,0.0,5,96,Urban,HR Executive,115287,0 +60587,Female,48,Bachelors,11,32,83,53,33,0.0,7,58,Urban,Software Engineer,54846,0 +60588,Male,38,Diploma,15,16,26,35,20,9.0,0,9,Semi-Urban,Software Engineer,116719,0 +60589,Female,53,Bachelors,5,37,40,48,52,2.0,1,38,Urban,Software Engineer,111744,0 +60590,Male,52,Diploma,0,23,28,82,23,7.0,2,52,Urban,Manager,44336,0 +60591,Male,56,Bachelors,11,67,4,51,87,7.0,1,48,Urban,ML Engineer,90553,0 +60592,Male,43,Bachelors,1,34,75,29,57,0.0,7,12,Urban,Data Analyst,117204,0 +60593,Male,50,Bachelors,9,73,70,39,33,1.0,4,82,Semi-Urban,Data Analyst,124966,1 +60594,Male,58,Diploma,10,81,91,28,99,3.0,0,71,Urban,Software Engineer,46028,1 +60595,Male,24,Diploma,8,90,16,93,41,6.0,7,78,Rural,ML Engineer,63775,1 +60596,Female,48,Diploma,15,41,94,42,31,0.0,1,95,Semi-Urban,Manager,97095,1 +60597,Female,42,Bachelors,11,23,51,90,34,4.0,4,51,Rural,ML Engineer,149127,0 +60598,Male,58,High School,19,59,83,45,68,8.0,6,68,Semi-Urban,Data Analyst,106209,1 +60599,Male,54,Diploma,11,26,33,19,84,3.0,2,70,Rural,Manager,144303,0 +60600,Male,46,High School,8,83,62,94,67,5.0,1,54,Rural,ML Engineer,81334,1 +60601,Male,54,High School,6,63,46,39,90,3.0,1,64,Urban,Manager,121296,0 +60602,Female,47,PhD,7,59,67,73,40,7.0,2,59,Urban,ML Engineer,125014,1 +60603,Female,56,Diploma,19,16,15,54,35,3.0,6,86,Urban,Software Engineer,108684,0 +60604,Male,56,Diploma,12,62,81,71,78,3.0,6,0,Urban,Manager,31189,0 +60605,Male,56,Diploma,3,52,59,91,52,9.0,3,0,Urban,Manager,89210,0 +60606,Male,48,Masters,2,26,3,16,7,1.0,1,60,Semi-Urban,Software Engineer,62825,0 +60607,Male,35,Diploma,13,32,24,37,20,0.0,3,44,Urban,HR Executive,63112,0 +60608,Male,37,Bachelors,14,48,26,47,80,1.0,1,35,Rural,ML Engineer,43860,0 +60609,Male,33,Bachelors,12,2,6,85,82,7.0,3,49,Urban,HR Executive,61471,0 +60610,Male,47,Bachelors,7,45,74,38,25,8.0,3,77,Semi-Urban,ML Engineer,72063,0 +60611,Female,29,High School,18,14,57,60,23,1.0,5,85,Urban,Manager,22037,0 +60612,Male,34,Bachelors,17,18,88,30,86,3.0,1,67,Rural,Software Engineer,59362,0 +60613,Female,56,High School,0,7,16,90,51,6.0,7,93,Semi-Urban,Manager,51359,0 +60614,Male,48,Diploma,15,57,61,59,74,4.0,6,97,Rural,ML Engineer,140494,1 +60615,Male,35,Masters,5,61,18,36,97,0.0,1,60,Urban,Manager,120527,0 +60616,Male,37,Diploma,1,69,93,22,57,6.0,5,94,Semi-Urban,Data Analyst,68772,1 +60617,Male,46,Diploma,3,10,7,8,86,2.0,0,86,Urban,HR Executive,140928,0 +60618,Male,31,Bachelors,11,54,80,10,92,3.0,4,19,Urban,Software Engineer,70185,0 +60619,Male,49,Bachelors,7,30,19,94,26,1.0,3,17,Urban,Data Analyst,120078,0 +60620,Male,28,Diploma,0,94,11,22,25,7.0,6,49,Semi-Urban,Data Analyst,22966,0 +60621,Male,59,Diploma,8,5,99,12,63,1.0,7,50,Urban,Data Analyst,42395,0 +60622,Female,28,Masters,4,72,92,55,81,3.0,2,28,Rural,Manager,62078,1 +60623,Male,25,Masters,18,9,77,64,3,8.0,6,49,Urban,ML Engineer,71269,0 +60624,Male,45,High School,10,78,43,90,12,2.0,5,96,Urban,Manager,78210,1 +60625,Female,29,Bachelors,3,28,60,89,11,8.0,0,8,Urban,Data Analyst,36219,0 +60626,Female,44,Masters,13,39,28,96,69,4.0,4,12,Urban,HR Executive,102621,0 +60627,Female,28,Masters,17,0,25,62,16,3.0,3,41,Semi-Urban,ML Engineer,137258,0 +60628,Male,38,Bachelors,2,15,46,47,42,0.0,1,28,Rural,Software Engineer,33973,0 +60629,Male,31,Bachelors,10,76,90,65,93,9.0,5,88,Semi-Urban,ML Engineer,139880,1 +60630,Female,40,High School,9,82,80,49,4,6.0,5,0,Urban,Data Analyst,22336,0 +60631,Male,47,Bachelors,6,26,91,6,42,5.0,4,37,Urban,Software Engineer,36810,0 +60632,Female,57,Masters,16,33,76,74,14,9.0,5,80,Urban,ML Engineer,95543,1 +60633,Male,36,Bachelors,8,36,70,58,84,1.0,7,87,Rural,Manager,111927,1 +60634,Female,25,High School,19,57,73,24,54,2.0,1,7,Urban,ML Engineer,80427,0 +60635,Female,50,Bachelors,8,29,74,99,55,5.0,6,75,Semi-Urban,Manager,67574,1 +60636,Male,29,Masters,5,88,53,37,44,4.0,1,33,Urban,ML Engineer,40157,0 +60637,Male,34,High School,19,19,82,67,20,7.0,5,16,Urban,ML Engineer,66873,0 +60638,Other,43,Masters,3,72,59,83,90,9.0,7,51,Urban,Software Engineer,31109,1 +60639,Male,43,High School,17,66,81,72,47,2.0,3,6,Rural,Manager,27758,0 +60640,Male,42,Bachelors,13,57,97,79,36,1.0,4,2,Urban,ML Engineer,76745,1 +60641,Female,44,Diploma,2,33,90,46,31,6.0,6,93,Rural,HR Executive,144845,1 +60642,Female,30,Bachelors,11,36,56,54,44,4.0,7,31,Rural,Data Analyst,135128,0 +60643,Male,58,Masters,0,71,74,33,40,9.0,1,62,Urban,Data Analyst,139648,1 +60644,Female,46,Diploma,7,88,16,35,57,9.0,5,76,Urban,Software Engineer,24393,0 +60645,Male,42,Bachelors,6,74,95,68,19,3.0,7,17,Urban,Data Analyst,102114,1 +60646,Male,33,Bachelors,1,83,59,45,23,9.0,4,86,Rural,Data Analyst,56857,1 +60647,Male,34,Masters,11,70,88,85,47,6.0,1,94,Rural,HR Executive,69205,1 +60648,Male,42,Diploma,19,94,11,40,97,1.0,1,95,Urban,HR Executive,123244,1 +60649,Male,29,Bachelors,5,50,13,3,76,8.0,5,90,Urban,ML Engineer,123503,0 +60650,Male,59,PhD,1,68,10,32,70,6.0,0,20,Urban,Data Analyst,96157,0 +60651,Male,28,Masters,15,81,5,62,6,5.0,5,62,Semi-Urban,Manager,95682,0 +60652,Male,54,Bachelors,0,55,76,8,7,0.0,4,79,Rural,Manager,138265,0 +60653,Male,58,Bachelors,7,73,86,87,31,2.0,6,34,Urban,Software Engineer,55325,1 +60654,Male,29,Diploma,13,68,94,89,11,3.0,0,22,Semi-Urban,ML Engineer,32118,1 +60655,Male,46,Bachelors,18,83,44,27,97,0.0,7,40,Semi-Urban,Software Engineer,114802,0 +60656,Male,55,Diploma,16,52,90,26,37,3.0,0,57,Urban,HR Executive,26095,0 +60657,Male,56,Masters,8,55,84,47,27,7.0,0,65,Urban,Data Analyst,50233,1 +60658,Male,52,Bachelors,19,28,36,37,56,0.0,6,91,Urban,Manager,124814,0 +60659,Male,46,Bachelors,4,55,11,57,64,2.0,7,2,Urban,HR Executive,126159,0 +60660,Female,59,Masters,18,96,18,27,26,8.0,7,32,Rural,Manager,125273,0 +60661,Male,29,Diploma,15,21,74,96,78,3.0,1,77,Semi-Urban,ML Engineer,96954,1 +60662,Other,39,Masters,3,80,50,32,27,9.0,7,69,Urban,HR Executive,86882,0 +60663,Other,51,Bachelors,2,21,56,8,76,4.0,1,79,Urban,HR Executive,20568,0 +60664,Female,22,Bachelors,11,27,89,38,38,0.0,2,85,Urban,ML Engineer,112904,0 +60665,Male,27,Bachelors,18,79,8,22,19,0.0,1,20,Urban,Software Engineer,76162,0 +60666,Female,21,Bachelors,6,58,0,44,91,0.0,7,20,Semi-Urban,ML Engineer,91002,0 +60667,Female,54,Bachelors,14,59,94,40,56,0.0,4,73,Semi-Urban,HR Executive,103433,1 +60668,Female,38,Bachelors,7,71,70,54,24,4.0,5,18,Urban,Data Analyst,77322,0 +60669,Male,56,Masters,9,32,15,12,58,6.0,6,69,Semi-Urban,Software Engineer,40239,0 +60670,Male,43,Masters,17,53,74,38,40,4.0,3,9,Urban,ML Engineer,63410,0 +60671,Male,53,Bachelors,18,73,9,55,11,0.0,2,23,Urban,HR Executive,55254,0 +60672,Male,56,Masters,12,59,37,35,10,8.0,6,51,Rural,HR Executive,83820,0 +60673,Male,22,High School,16,57,26,2,42,2.0,1,0,Urban,HR Executive,60775,0 +60674,Male,39,Bachelors,11,28,66,93,72,7.0,4,87,Urban,Software Engineer,65349,1 +60675,Male,32,High School,13,91,44,75,34,5.0,1,44,Semi-Urban,Data Analyst,83410,1 +60676,Female,49,PhD,8,85,44,52,57,1.0,5,86,Urban,Data Analyst,129614,1 +60677,Male,51,Diploma,15,0,75,86,17,5.0,5,14,Semi-Urban,Software Engineer,106049,0 +60678,Male,45,Bachelors,16,96,6,73,59,2.0,1,58,Urban,Software Engineer,28336,0 +60679,Female,30,High School,19,16,66,6,45,2.0,2,89,Urban,HR Executive,148741,0 +60680,Male,58,High School,9,42,67,33,31,7.0,0,80,Semi-Urban,HR Executive,132816,0 +60681,Female,49,Diploma,2,60,35,27,89,0.0,7,78,Urban,Software Engineer,76284,0 +60682,Male,24,High School,12,84,73,31,33,5.0,6,98,Urban,Data Analyst,79938,1 +60683,Female,27,Masters,8,39,63,57,70,9.0,2,95,Semi-Urban,ML Engineer,42506,1 +60684,Female,47,Diploma,4,13,40,75,51,4.0,1,16,Urban,HR Executive,24860,0 +60685,Female,55,Diploma,12,46,94,13,68,7.0,0,48,Urban,Data Analyst,106177,0 +60686,Male,45,Diploma,5,72,47,27,3,8.0,4,35,Rural,Manager,66905,0 +60687,Female,36,Diploma,12,99,37,34,89,1.0,5,20,Urban,ML Engineer,121839,0 +60688,Male,35,Bachelors,10,92,33,82,12,1.0,0,45,Urban,HR Executive,132374,1 +60689,Male,28,Diploma,16,64,14,49,39,1.0,5,76,Urban,HR Executive,49546,0 +60690,Female,39,Bachelors,7,16,51,43,26,1.0,3,90,Urban,Software Engineer,103888,0 +60691,Male,21,Bachelors,10,43,99,81,91,4.0,4,34,Rural,Manager,146757,1 +60692,Male,36,High School,17,25,60,55,56,5.0,6,27,Semi-Urban,Software Engineer,29335,0 +60693,Female,29,Masters,15,16,39,49,59,7.0,6,17,Urban,Software Engineer,35923,0 +60694,Male,59,Masters,0,40,98,83,70,7.0,1,79,Urban,Data Analyst,60087,1 +60695,Female,59,PhD,11,86,9,34,97,5.0,3,84,Urban,Data Analyst,126040,0 +60696,Female,42,Diploma,18,36,25,28,63,5.0,2,28,Semi-Urban,Software Engineer,131776,0 +60697,Male,47,Diploma,13,65,30,65,89,8.0,7,43,Semi-Urban,Data Analyst,81466,0 +60698,Female,32,Bachelors,7,28,68,29,22,3.0,2,74,Semi-Urban,Software Engineer,83519,0 +60699,Male,47,Bachelors,17,63,42,91,0,4.0,6,37,Semi-Urban,Software Engineer,26970,0 +60700,Male,42,Diploma,6,65,86,69,48,2.0,4,54,Semi-Urban,Software Engineer,86537,1 +60701,Male,30,Diploma,4,65,69,72,42,8.0,4,83,Rural,Data Analyst,27481,1 +60702,Male,25,Masters,16,77,49,65,75,4.0,1,9,Urban,HR Executive,99569,0 +60703,Female,24,Masters,3,52,39,36,41,1.0,0,54,Semi-Urban,ML Engineer,41346,0 +60704,Other,25,Bachelors,5,63,30,95,70,5.0,4,8,Urban,ML Engineer,125479,0 +60705,Male,35,Bachelors,17,95,54,89,74,9.0,2,31,Semi-Urban,HR Executive,117551,1 +60706,Male,26,High School,17,97,16,26,87,4.0,6,35,Semi-Urban,ML Engineer,88672,0 +60707,Male,30,Bachelors,3,51,59,84,21,2.0,6,63,Urban,Software Engineer,144348,1 +60708,Male,42,Diploma,7,59,48,15,83,4.0,1,39,Urban,ML Engineer,145114,0 +60709,Male,49,Diploma,5,88,48,95,48,0.0,1,79,Urban,Software Engineer,76743,1 +60710,Female,26,Bachelors,14,27,14,89,11,0.0,7,47,Urban,Manager,140983,0 +60711,Male,59,Masters,10,5,11,99,23,2.0,0,73,Urban,Data Analyst,92652,0 +60712,Male,38,Bachelors,5,27,38,18,86,9.0,1,35,Urban,ML Engineer,43492,0 +60713,Male,22,Bachelors,8,3,96,0,26,8.0,3,16,Urban,Data Analyst,131596,0 +60714,Male,57,Masters,6,29,50,52,65,2.0,0,25,Urban,HR Executive,52710,0 +60715,Male,33,High School,4,68,58,0,29,0.0,7,9,Urban,Software Engineer,98168,0 +60716,Female,42,Diploma,4,50,50,83,80,5.0,7,6,Semi-Urban,HR Executive,114350,0 +60717,Male,28,Bachelors,6,4,94,59,84,3.0,3,84,Urban,Manager,107823,1 +60718,Female,40,High School,13,25,57,77,13,8.0,6,1,Semi-Urban,Software Engineer,26287,0 +60719,Male,57,Masters,15,18,93,19,8,8.0,4,36,Semi-Urban,Manager,26196,0 +60720,Female,31,High School,18,77,11,58,70,4.0,7,86,Urban,Data Analyst,135548,0 +60721,Male,36,Diploma,1,61,9,35,0,8.0,4,87,Urban,Data Analyst,90371,0 +60722,Male,43,Masters,7,25,19,75,79,7.0,4,43,Rural,Software Engineer,144431,0 +60723,Male,57,Masters,12,47,27,80,65,5.0,3,69,Semi-Urban,ML Engineer,97699,0 +60724,Male,45,Diploma,12,30,44,97,16,1.0,4,81,Rural,Software Engineer,145240,1 +60725,Other,54,Bachelors,10,95,56,78,30,3.0,7,48,Urban,Software Engineer,53753,1 +60726,Male,53,Diploma,12,31,53,20,37,8.0,7,2,Urban,Data Analyst,30062,0 +60727,Female,39,Bachelors,19,22,41,19,54,1.0,6,7,Urban,ML Engineer,98609,0 +60728,Female,26,Diploma,7,54,6,42,30,8.0,7,25,Semi-Urban,Manager,61143,0 +60729,Male,45,Bachelors,13,66,5,14,6,9.0,6,92,Urban,Data Analyst,140059,0 +60730,Female,31,Masters,17,49,67,21,82,2.0,3,78,Semi-Urban,Manager,97543,0 +60731,Female,45,High School,6,51,18,68,3,1.0,4,30,Urban,Manager,82477,0 +60732,Male,59,Masters,6,50,97,51,2,6.0,6,1,Semi-Urban,HR Executive,31663,0 +60733,Female,57,Diploma,6,70,37,56,7,6.0,5,37,Rural,HR Executive,75171,0 +60734,Male,43,Bachelors,14,25,48,65,11,4.0,2,71,Semi-Urban,ML Engineer,57910,0 +60735,Male,46,Bachelors,13,77,42,7,29,2.0,7,59,Urban,ML Engineer,42569,0 +60736,Male,57,Bachelors,5,80,15,47,19,4.0,3,85,Urban,HR Executive,122832,0 +60737,Female,30,PhD,19,71,60,14,24,9.0,7,57,Urban,HR Executive,126204,0 +60738,Male,22,Bachelors,1,15,99,37,3,4.0,2,8,Urban,Data Analyst,74694,0 +60739,Other,32,Bachelors,11,67,95,76,97,5.0,1,11,Semi-Urban,Software Engineer,133179,1 +60740,Male,29,High School,19,15,72,80,72,5.0,1,77,Urban,Data Analyst,89593,1 +60741,Female,38,Masters,15,44,92,79,75,0.0,3,22,Urban,HR Executive,146762,0 +60742,Female,53,Diploma,18,12,24,60,93,3.0,7,71,Urban,Software Engineer,37768,0 +60743,Female,21,PhD,18,64,11,26,6,4.0,7,49,Urban,ML Engineer,129079,0 +60744,Male,47,Bachelors,12,65,37,87,1,8.0,0,12,Urban,ML Engineer,141262,0 +60745,Male,24,Bachelors,4,66,5,74,43,4.0,6,16,Urban,HR Executive,41115,0 +60746,Female,47,Diploma,13,78,22,46,18,3.0,6,98,Urban,Manager,57329,1 +60747,Other,38,Masters,3,57,23,75,45,6.0,6,35,Rural,ML Engineer,134243,0 +60748,Male,40,PhD,5,24,3,91,4,7.0,4,59,Semi-Urban,ML Engineer,89120,0 +60749,Female,35,Bachelors,4,45,67,86,79,2.0,6,39,Urban,ML Engineer,20710,0 +60750,Male,47,Diploma,14,73,88,20,30,4.0,6,56,Rural,HR Executive,31233,1 +60751,Female,28,High School,14,88,3,88,1,5.0,1,26,Urban,ML Engineer,28389,0 +60752,Female,51,PhD,13,56,97,13,80,8.0,1,30,Semi-Urban,HR Executive,86585,0 +60753,Female,32,Masters,19,57,78,27,87,2.0,2,66,Urban,Manager,96931,0 +60754,Male,34,High School,5,68,50,21,39,4.0,2,53,Urban,Software Engineer,23399,0 +60755,Male,57,Masters,3,92,41,93,60,6.0,6,14,Semi-Urban,Software Engineer,67874,1 +60756,Male,48,Bachelors,11,38,22,46,62,0.0,5,21,Urban,Data Analyst,129007,0 +60757,Female,40,Masters,11,62,90,40,51,8.0,3,75,Urban,HR Executive,133755,1 +60758,Female,38,Masters,18,84,62,71,34,1.0,6,90,Semi-Urban,Data Analyst,67485,1 +60759,Male,41,Bachelors,10,47,54,11,41,2.0,7,48,Rural,HR Executive,141559,0 +60760,Male,35,High School,9,17,79,90,26,1.0,1,93,Urban,HR Executive,93879,1 +60761,Male,28,Masters,4,20,24,80,72,5.0,2,80,Urban,HR Executive,74418,0 +60762,Female,46,High School,16,23,5,64,96,1.0,1,63,Urban,Data Analyst,49789,0 +60763,Male,24,Bachelors,9,25,85,79,19,3.0,7,4,Rural,ML Engineer,28148,0 +60764,Female,33,Bachelors,19,15,18,90,9,8.0,7,12,Urban,Data Analyst,102240,0 +60765,Male,30,Masters,7,52,28,33,79,1.0,6,69,Rural,Manager,115479,0 +60766,Male,21,Masters,11,47,31,13,71,0.0,5,81,Semi-Urban,HR Executive,65734,0 +60767,Other,48,Bachelors,10,49,1,29,16,8.0,3,8,Semi-Urban,HR Executive,21926,0 +60768,Female,53,Diploma,2,0,8,56,74,9.0,0,79,Rural,Manager,81136,0 +60769,Male,43,Bachelors,17,19,72,8,45,2.0,7,81,Urban,Data Analyst,58064,0 +60770,Male,58,Masters,0,38,47,21,86,6.0,7,35,Rural,Software Engineer,96139,0 +60771,Female,41,Bachelors,5,76,28,21,61,1.0,5,55,Semi-Urban,Manager,41844,0 +60772,Male,42,Diploma,7,91,31,25,91,4.0,2,59,Semi-Urban,Manager,46345,0 +60773,Female,36,Masters,7,1,86,89,98,1.0,0,12,Rural,HR Executive,67515,0 +60774,Male,53,Diploma,15,51,28,67,99,0.0,4,10,Urban,Software Engineer,61333,0 +60775,Female,31,Masters,3,49,94,92,83,7.0,3,92,Rural,Data Analyst,130393,1 +60776,Male,59,Bachelors,4,57,34,89,38,2.0,3,80,Semi-Urban,Data Analyst,65159,1 +60777,Male,55,Diploma,4,48,73,62,33,3.0,0,46,Urban,HR Executive,113583,0 +60778,Female,28,Bachelors,9,55,20,9,87,8.0,0,18,Semi-Urban,Data Analyst,103124,0 +60779,Male,51,Diploma,15,23,9,71,14,6.0,4,87,Semi-Urban,ML Engineer,96193,0 +60780,Male,59,Diploma,17,30,87,66,62,5.0,7,40,Urban,Data Analyst,42414,0 +60781,Male,21,Masters,4,9,4,51,23,2.0,2,40,Semi-Urban,Software Engineer,45355,0 +60782,Female,35,Diploma,3,19,84,67,4,1.0,1,36,Rural,Data Analyst,81605,0 +60783,Male,29,Bachelors,8,1,34,83,94,6.0,4,39,Urban,HR Executive,32142,0 +60784,Male,52,Bachelors,3,64,61,12,90,3.0,1,75,Semi-Urban,ML Engineer,59499,0 +60785,Male,36,Bachelors,10,45,87,32,78,4.0,3,54,Urban,Software Engineer,59705,0 +60786,Female,45,Bachelors,18,90,80,93,89,3.0,0,0,Rural,Data Analyst,98851,1 +60787,Female,39,Diploma,18,9,63,89,79,8.0,5,52,Urban,Manager,62955,0 +60788,Male,45,Bachelors,7,71,85,4,0,1.0,2,61,Urban,Manager,105874,0 +60789,Male,51,Masters,8,21,23,9,92,1.0,2,9,Urban,Software Engineer,28035,0 +60790,Female,47,PhD,15,88,14,82,77,1.0,0,59,Urban,Software Engineer,45915,1 +60791,Male,54,Bachelors,11,37,83,95,93,5.0,0,94,Urban,Software Engineer,84451,1 +60792,Female,41,High School,12,6,59,48,79,9.0,3,96,Urban,HR Executive,107939,0 +60793,Male,27,Masters,1,23,44,91,5,0.0,5,33,Urban,HR Executive,51415,0 +60794,Male,23,Bachelors,17,76,25,77,5,0.0,4,18,Urban,HR Executive,42848,0 +60795,Male,33,Bachelors,15,47,96,75,34,0.0,6,72,Semi-Urban,ML Engineer,36448,1 +60796,Male,56,Bachelors,19,14,40,33,51,2.0,2,90,Urban,HR Executive,128763,0 +60797,Female,23,Diploma,14,6,50,62,83,3.0,0,5,Urban,Data Analyst,119709,0 +60798,Female,25,Bachelors,9,32,57,8,33,9.0,7,55,Urban,ML Engineer,92875,0 +60799,Male,59,Masters,3,50,21,87,13,0.0,4,77,Rural,Data Analyst,21910,1 +60800,Female,30,Masters,5,4,42,97,3,4.0,4,36,Urban,Data Analyst,21938,0 +60801,Male,54,PhD,5,36,47,58,78,6.0,0,6,Urban,ML Engineer,134681,0 +60802,Female,48,Masters,8,79,50,75,96,3.0,3,5,Semi-Urban,ML Engineer,134610,0 +60803,Male,53,High School,19,75,65,9,54,9.0,5,61,Rural,Data Analyst,99331,0 +60804,Male,30,Bachelors,14,38,12,26,10,7.0,6,17,Semi-Urban,Manager,71763,0 +60805,Female,46,Bachelors,8,4,62,98,56,0.0,5,30,Semi-Urban,ML Engineer,24492,0 +60806,Male,57,Masters,17,66,88,83,71,3.0,3,97,Urban,HR Executive,65750,1 +60807,Female,22,Bachelors,13,0,21,97,47,4.0,2,89,Rural,HR Executive,103647,0 +60808,Female,35,Diploma,14,42,36,28,3,2.0,3,65,Rural,Manager,140684,0 +60809,Female,42,Masters,3,54,26,2,76,5.0,6,80,Urban,Software Engineer,54017,0 +60810,Male,21,Bachelors,19,59,99,58,24,4.0,3,84,Urban,Software Engineer,60886,1 +60811,Male,51,Bachelors,16,83,60,38,57,7.0,6,74,Urban,Manager,108977,1 +60812,Female,37,Masters,1,95,99,77,2,7.0,7,99,Rural,HR Executive,32475,1 +60813,Male,28,Diploma,3,84,40,89,64,9.0,5,55,Urban,Software Engineer,92994,1 +60814,Female,42,Diploma,12,76,41,23,7,0.0,3,53,Rural,Software Engineer,93817,0 +60815,Female,26,Bachelors,17,49,89,76,28,6.0,1,54,Urban,HR Executive,61759,1 +60816,Male,50,Masters,14,34,33,59,6,4.0,2,18,Semi-Urban,Data Analyst,93317,0 +60817,Male,52,Masters,14,55,18,42,63,4.0,3,46,Semi-Urban,Data Analyst,76611,0 +60818,Male,56,High School,14,3,7,42,37,1.0,3,91,Urban,Manager,83046,0 +60819,Male,31,High School,7,59,58,30,50,6.0,6,62,Semi-Urban,Data Analyst,111639,0 +60820,Female,34,Masters,15,32,64,9,15,2.0,1,79,Semi-Urban,Software Engineer,66621,0 +60821,Female,39,High School,1,13,92,35,90,5.0,6,39,Urban,Data Analyst,54402,0 +60822,Female,22,Masters,4,33,49,83,5,2.0,2,43,Urban,Manager,94569,0 +60823,Other,25,Bachelors,3,95,8,49,29,5.0,4,57,Semi-Urban,HR Executive,118823,0 +60824,Other,44,Bachelors,18,12,20,27,86,4.0,4,43,Urban,Data Analyst,114898,0 +60825,Male,55,High School,19,18,21,97,1,6.0,0,20,Urban,Software Engineer,44511,0 +60826,Male,59,Bachelors,9,60,36,99,47,7.0,5,46,Semi-Urban,Data Analyst,89995,1 +60827,Male,40,Masters,2,62,95,79,78,6.0,4,7,Rural,Manager,126216,1 +60828,Female,48,Bachelors,9,38,31,25,25,6.0,1,7,Semi-Urban,ML Engineer,89655,0 +60829,Male,44,High School,13,98,34,17,5,3.0,4,1,Semi-Urban,Manager,31351,0 +60830,Male,22,Bachelors,14,17,89,60,53,4.0,4,68,Urban,HR Executive,112655,0 +60831,Female,24,Bachelors,14,12,14,64,95,2.0,1,72,Urban,HR Executive,122807,0 +60832,Female,40,High School,13,91,61,17,86,4.0,5,14,Urban,ML Engineer,148715,0 +60833,Other,34,Masters,5,39,69,59,81,4.0,3,74,Urban,Data Analyst,73529,1 +60834,Male,58,Bachelors,17,49,11,59,77,9.0,5,6,Rural,Software Engineer,98684,0 +60835,Other,31,Bachelors,4,84,0,2,15,3.0,4,7,Urban,ML Engineer,140756,0 +60836,Male,52,Diploma,10,8,60,50,50,7.0,3,73,Semi-Urban,ML Engineer,141208,0 +60837,Female,21,Diploma,5,75,76,13,16,3.0,0,26,Urban,Manager,107620,0 +60838,Male,52,High School,5,24,16,67,28,9.0,0,65,Semi-Urban,HR Executive,77644,0 +60839,Female,30,Masters,0,57,29,65,41,4.0,3,92,Semi-Urban,Manager,46794,1 +60840,Female,57,Bachelors,11,89,60,66,96,5.0,2,60,Urban,HR Executive,110179,1 +60841,Female,56,Masters,7,26,20,93,49,5.0,1,7,Semi-Urban,ML Engineer,143134,0 +60842,Female,32,High School,7,14,63,88,22,2.0,1,47,Rural,Software Engineer,93147,0 +60843,Other,25,Masters,9,41,98,38,45,7.0,1,75,Semi-Urban,Software Engineer,64424,1 +60844,Male,47,High School,5,66,66,39,99,3.0,2,63,Urban,Software Engineer,103606,0 +60845,Male,40,Bachelors,16,76,85,52,93,5.0,6,37,Semi-Urban,Data Analyst,24594,1 +60846,Female,27,Diploma,1,46,63,83,1,1.0,5,28,Urban,Data Analyst,87166,0 +60847,Female,55,Bachelors,4,77,33,56,5,5.0,5,11,Urban,ML Engineer,102774,0 +60848,Female,42,Bachelors,17,55,19,0,32,5.0,6,53,Semi-Urban,Software Engineer,99241,0 +60849,Female,25,Bachelors,6,60,10,8,60,2.0,1,68,Urban,Manager,33483,0 +60850,Female,22,Bachelors,19,50,39,48,78,0.0,7,33,Urban,Software Engineer,78221,0 +60851,Male,31,High School,10,30,82,96,87,0.0,5,24,Rural,Data Analyst,95158,0 +60852,Male,22,Diploma,7,9,93,15,49,4.0,2,79,Semi-Urban,ML Engineer,48075,0 +60853,Female,26,Bachelors,7,6,84,76,12,1.0,4,8,Rural,ML Engineer,111706,0 +60854,Male,48,Diploma,3,13,62,63,22,4.0,0,34,Urban,HR Executive,34949,0 +60855,Male,27,Bachelors,10,43,40,16,40,5.0,3,15,Urban,Data Analyst,69481,0 +60856,Other,43,Bachelors,12,87,36,83,22,8.0,1,7,Semi-Urban,Data Analyst,137953,0 +60857,Male,44,Bachelors,11,87,27,38,20,6.0,4,8,Rural,Software Engineer,121308,0 +60858,Male,53,Bachelors,12,41,69,69,80,4.0,3,78,Urban,Data Analyst,82318,1 +60859,Male,42,Masters,5,11,76,21,85,9.0,1,1,Urban,Data Analyst,89800,0 +60860,Male,37,PhD,7,22,77,67,64,5.0,1,33,Urban,Software Engineer,96880,0 +60861,Other,46,Masters,16,24,37,30,15,4.0,3,25,Urban,Software Engineer,112168,0 +60862,Female,47,Diploma,0,79,95,21,57,4.0,1,3,Urban,Software Engineer,41002,0 +60863,Male,23,Diploma,10,99,6,93,44,8.0,5,69,Urban,HR Executive,128446,1 +60864,Male,36,Diploma,1,56,76,47,14,2.0,1,39,Semi-Urban,Software Engineer,142229,0 +60865,Female,56,Bachelors,16,85,76,28,58,6.0,3,96,Urban,Software Engineer,27412,1 +60866,Female,53,PhD,10,48,55,6,34,7.0,2,61,Urban,HR Executive,61466,0 +60867,Male,41,PhD,19,34,93,57,19,5.0,7,69,Urban,HR Executive,33173,1 +60868,Male,24,Masters,3,96,97,67,23,5.0,7,43,Urban,ML Engineer,108422,1 +60869,Male,48,Masters,1,50,57,64,73,5.0,7,46,Urban,ML Engineer,31258,0 +60870,Other,30,Bachelors,8,57,57,66,36,7.0,1,88,Semi-Urban,ML Engineer,37170,1 +60871,Female,24,Masters,9,10,27,68,4,6.0,5,80,Rural,HR Executive,100232,0 +60872,Male,35,Bachelors,14,99,98,91,13,7.0,7,92,Urban,ML Engineer,93309,1 +60873,Male,37,Diploma,5,76,11,96,32,3.0,6,33,Semi-Urban,HR Executive,53330,0 +60874,Male,51,Diploma,12,14,22,56,86,7.0,4,6,Rural,Software Engineer,37567,0 +60875,Male,41,Bachelors,18,46,96,29,2,9.0,7,59,Urban,ML Engineer,81649,0 +60876,Male,33,High School,13,36,15,55,89,2.0,0,65,Urban,Software Engineer,122913,0 +60877,Male,47,Masters,11,71,77,51,39,1.0,3,75,Urban,HR Executive,52422,1 +60878,Female,30,Diploma,16,0,33,78,44,1.0,7,74,Urban,HR Executive,84812,0 +60879,Other,59,Bachelors,5,92,52,27,20,5.0,7,19,Urban,ML Engineer,21198,0 +60880,Male,42,PhD,1,54,95,11,81,3.0,0,21,Urban,Software Engineer,92164,0 +60881,Male,32,Bachelors,10,62,2,46,17,2.0,7,81,Urban,ML Engineer,55332,0 +60882,Female,51,High School,3,26,76,26,95,5.0,2,85,Urban,Manager,72779,0 +60883,Male,55,Masters,16,98,99,56,42,0.0,4,16,Semi-Urban,ML Engineer,63354,1 +60884,Male,25,Diploma,1,3,82,87,97,6.0,3,39,Urban,Manager,55910,0 +60885,Male,31,Bachelors,6,6,43,60,37,7.0,5,88,Rural,Data Analyst,92229,0 +60886,Male,53,Bachelors,7,93,84,15,1,3.0,5,57,Rural,Software Engineer,62120,1 +60887,Male,38,Bachelors,13,21,7,36,35,0.0,6,32,Rural,Data Analyst,78705,0 +60888,Female,56,Bachelors,11,83,29,13,85,1.0,5,64,Rural,Manager,38026,0 +60889,Male,21,Bachelors,10,67,2,53,29,4.0,6,0,Urban,Manager,135499,0 +60890,Male,35,High School,8,14,58,34,28,7.0,4,21,Rural,Software Engineer,20390,0 +60891,Male,27,Masters,0,71,40,65,83,2.0,4,4,Rural,ML Engineer,62280,0 +60892,Male,52,Masters,16,22,74,63,83,8.0,2,21,Rural,ML Engineer,60211,0 +60893,Male,56,Bachelors,15,35,61,69,4,7.0,5,55,Urban,Software Engineer,70201,0 +60894,Female,31,Diploma,17,40,0,7,81,0.0,5,60,Urban,HR Executive,85017,0 +60895,Male,34,Bachelors,17,59,42,70,8,6.0,7,46,Urban,HR Executive,129522,0 +60896,Other,49,Bachelors,4,44,76,58,82,9.0,2,88,Urban,HR Executive,106734,1 +60897,Female,56,Masters,15,54,46,96,29,2.0,6,51,Rural,HR Executive,106414,1 +60898,Female,25,Bachelors,8,19,34,82,26,6.0,5,37,Urban,ML Engineer,137390,0 +60899,Male,46,Diploma,12,28,5,72,75,3.0,3,55,Rural,Software Engineer,106996,0 +60900,Male,53,Bachelors,7,51,28,44,86,8.0,7,46,Urban,Data Analyst,38647,0 +60901,Male,35,Bachelors,3,77,14,10,50,9.0,4,62,Urban,Data Analyst,53706,0 +60902,Male,54,Bachelors,15,89,7,26,86,2.0,6,43,Semi-Urban,Software Engineer,45636,0 +60903,Male,44,Masters,5,39,29,57,95,7.0,0,0,Semi-Urban,Manager,39687,0 +60904,Other,57,Diploma,16,15,24,54,1,1.0,2,50,Rural,HR Executive,75422,0 +60905,Female,30,Masters,11,37,14,67,98,2.0,6,82,Urban,HR Executive,125986,0 +60906,Male,25,Masters,6,44,19,49,45,8.0,1,58,Urban,Data Analyst,91205,0 +60907,Female,21,Bachelors,4,65,93,6,37,3.0,1,21,Urban,Software Engineer,94018,0 +60908,Male,21,Diploma,4,83,35,86,95,8.0,5,1,Urban,ML Engineer,122765,0 +60909,Male,52,High School,2,34,18,36,38,9.0,6,75,Urban,Manager,65690,0 +60910,Male,50,Bachelors,4,71,42,65,36,8.0,2,73,Semi-Urban,Data Analyst,72250,1 +60911,Male,41,Bachelors,18,61,2,42,30,3.0,1,15,Urban,HR Executive,131144,0 +60912,Male,47,Bachelors,0,96,73,22,60,3.0,3,97,Urban,ML Engineer,74947,1 +60913,Male,33,Bachelors,13,81,87,91,28,9.0,2,75,Urban,Software Engineer,117981,1 +60914,Male,32,Bachelors,6,48,1,21,49,6.0,2,11,Urban,ML Engineer,129349,0 +60915,Male,49,High School,14,33,15,90,52,0.0,1,28,Urban,Data Analyst,123282,0 +60916,Male,36,Bachelors,6,90,32,22,66,0.0,1,4,Urban,Software Engineer,94860,0 +60917,Male,59,Masters,0,1,28,10,52,0.0,5,66,Rural,Software Engineer,66965,0 +60918,Male,40,Bachelors,5,35,4,29,1,5.0,2,5,Urban,Data Analyst,118152,0 +60919,Male,52,Bachelors,3,72,74,50,55,7.0,5,3,Urban,ML Engineer,134647,0 +60920,Male,24,High School,8,86,4,38,94,8.0,3,7,Semi-Urban,ML Engineer,47139,0 +60921,Female,33,Diploma,13,72,47,19,45,8.0,4,34,Semi-Urban,Software Engineer,20213,0 +60922,Male,39,Diploma,15,31,1,84,82,1.0,2,30,Rural,Data Analyst,90322,0 +60923,Male,54,Masters,15,10,21,25,28,9.0,0,22,Urban,ML Engineer,70264,0 +60924,Female,59,Diploma,4,78,25,28,64,3.0,6,99,Semi-Urban,ML Engineer,63982,0 +60925,Male,29,Diploma,5,59,5,97,38,1.0,7,70,Rural,Manager,80381,0 +60926,Male,44,PhD,5,98,87,80,46,7.0,3,27,Semi-Urban,Software Engineer,21577,1 +60927,Male,57,High School,3,69,60,77,34,2.0,4,81,Urban,Data Analyst,54029,1 +60928,Female,47,Diploma,8,82,33,99,58,0.0,6,57,Urban,HR Executive,109517,1 +60929,Female,53,Bachelors,9,15,84,55,95,5.0,5,95,Semi-Urban,Software Engineer,110265,1 +60930,Male,48,PhD,0,4,36,83,42,7.0,5,56,Urban,ML Engineer,33386,0 +60931,Male,45,Masters,2,37,34,28,13,6.0,5,57,Rural,Manager,94152,0 +60932,Male,55,Diploma,14,8,9,70,18,2.0,2,72,Urban,Data Analyst,82140,0 +60933,Male,35,Bachelors,9,50,30,47,49,8.0,0,74,Rural,ML Engineer,25130,0 +60934,Other,31,Masters,0,19,84,80,79,3.0,7,91,Urban,Manager,126402,1 +60935,Male,53,Bachelors,13,88,15,53,61,7.0,2,55,Urban,HR Executive,134794,0 +60936,Male,23,High School,2,53,57,25,22,9.0,1,22,Urban,Manager,117651,0 +60937,Male,22,Bachelors,19,41,95,17,95,8.0,0,9,Urban,ML Engineer,70671,0 +60938,Male,22,High School,1,31,49,45,5,2.0,4,32,Rural,HR Executive,139836,0 +60939,Male,54,Diploma,0,97,14,51,67,1.0,5,95,Urban,Manager,83605,1 +60940,Female,44,Bachelors,10,55,71,2,1,9.0,6,50,Urban,HR Executive,56786,0 +60941,Male,35,Bachelors,1,26,67,56,76,1.0,0,17,Urban,Manager,39982,0 +60942,Male,39,Bachelors,11,13,11,53,30,4.0,1,78,Urban,Software Engineer,75060,0 +60943,Male,45,Masters,4,45,13,96,61,7.0,0,80,Urban,Data Analyst,60367,0 +60944,Female,50,Masters,8,35,58,8,34,7.0,4,55,Urban,Manager,114201,0 +60945,Male,37,Bachelors,3,32,95,59,61,9.0,4,33,Urban,Software Engineer,57608,0 +60946,Male,58,Bachelors,13,82,1,13,71,7.0,1,44,Urban,ML Engineer,68526,0 +60947,Male,38,Bachelors,10,68,32,72,93,4.0,4,29,Urban,ML Engineer,27804,0 +60948,Male,59,Masters,5,47,7,36,49,6.0,0,65,Semi-Urban,ML Engineer,124105,0 +60949,Female,46,Masters,13,64,95,95,87,9.0,4,30,Urban,Manager,76622,1 +60950,Male,44,Bachelors,19,59,86,82,74,6.0,4,48,Urban,Data Analyst,129357,1 +60951,Male,28,Bachelors,18,4,44,85,53,0.0,5,66,Urban,Data Analyst,58731,0 +60952,Other,52,Masters,10,62,55,58,18,9.0,5,40,Urban,Data Analyst,30705,0 +60953,Male,43,Diploma,18,68,14,36,76,4.0,6,9,Semi-Urban,Manager,133543,0 +60954,Female,58,Bachelors,9,73,98,57,99,0.0,6,43,Urban,ML Engineer,39246,1 +60955,Female,28,Masters,0,36,64,8,56,0.0,5,77,Urban,Manager,56511,0 +60956,Male,46,Bachelors,11,55,24,95,41,0.0,5,1,Urban,ML Engineer,40396,0 +60957,Male,27,Masters,0,93,14,77,22,6.0,7,35,Semi-Urban,HR Executive,50798,0 +60958,Female,48,High School,1,53,1,7,63,0.0,7,30,Rural,ML Engineer,90165,0 +60959,Male,36,Bachelors,2,35,1,46,39,0.0,0,81,Urban,ML Engineer,110984,0 +60960,Male,58,Diploma,0,86,17,42,35,5.0,6,83,Rural,ML Engineer,43960,0 +60961,Male,55,High School,10,96,29,46,95,0.0,7,89,Urban,HR Executive,60572,1 +60962,Male,56,High School,16,71,52,41,39,3.0,4,21,Urban,HR Executive,32249,0 +60963,Male,51,Bachelors,6,89,21,3,19,9.0,0,62,Urban,ML Engineer,36187,0 +60964,Male,57,Diploma,18,62,88,75,9,9.0,5,96,Urban,Software Engineer,44202,1 +60965,Male,44,Masters,11,52,43,98,95,8.0,4,47,Urban,Manager,135334,1 +60966,Male,36,Bachelors,17,29,84,2,80,2.0,2,47,Urban,Data Analyst,20771,0 +60967,Male,58,Bachelors,19,76,18,75,47,8.0,4,55,Semi-Urban,HR Executive,117872,0 +60968,Male,28,Masters,12,50,0,39,57,1.0,1,77,Urban,Manager,129869,0 +60969,Male,39,Bachelors,16,58,96,78,48,2.0,4,63,Semi-Urban,ML Engineer,124559,1 +60970,Male,46,Diploma,7,72,10,34,91,7.0,0,5,Urban,Software Engineer,77976,0 +60971,Male,32,Masters,18,80,26,34,89,8.0,1,27,Urban,Manager,112343,0 +60972,Male,22,Bachelors,6,43,18,31,97,0.0,4,15,Rural,ML Engineer,62967,0 +60973,Male,56,High School,9,85,41,97,35,8.0,5,65,Semi-Urban,Software Engineer,51094,1 +60974,Female,55,Diploma,17,99,70,60,36,2.0,6,3,Urban,ML Engineer,71818,0 +60975,Male,50,Bachelors,17,77,23,1,30,1.0,3,95,Semi-Urban,ML Engineer,117910,0 +60976,Male,24,High School,7,98,2,25,6,8.0,0,12,Rural,Manager,23048,0 +60977,Other,54,Bachelors,15,77,38,48,36,7.0,2,51,Semi-Urban,ML Engineer,59732,0 +60978,Male,31,High School,14,59,18,31,23,4.0,0,4,Semi-Urban,Software Engineer,91064,0 +60979,Male,57,Diploma,16,50,93,97,21,9.0,3,88,Rural,ML Engineer,74493,1 +60980,Female,42,Diploma,5,45,55,85,5,2.0,2,39,Semi-Urban,Data Analyst,130615,0 +60981,Male,41,Bachelors,13,79,14,4,3,8.0,0,66,Urban,Data Analyst,64541,0 +60982,Female,27,Bachelors,7,28,37,24,25,8.0,7,58,Urban,Manager,92852,0 +60983,Male,39,Masters,13,53,98,94,39,2.0,6,80,Urban,Software Engineer,139636,1 +60984,Female,22,Bachelors,4,85,86,7,39,6.0,2,73,Semi-Urban,HR Executive,35944,1 +60985,Male,21,Masters,4,22,25,45,2,8.0,2,62,Urban,ML Engineer,63991,0 +60986,Female,40,Diploma,3,7,45,55,76,7.0,1,69,Urban,Manager,138119,0 +60987,Male,54,Masters,17,91,28,21,38,6.0,5,46,Urban,Software Engineer,38365,0 +60988,Male,28,Masters,15,21,93,13,8,1.0,3,5,Semi-Urban,Manager,46521,0 +60989,Female,52,High School,7,3,66,9,80,6.0,4,89,Urban,Manager,134065,0 +60990,Male,33,Bachelors,12,19,10,55,70,6.0,4,39,Rural,Data Analyst,105455,0 +60991,Female,56,Masters,2,73,71,95,6,3.0,4,23,Urban,HR Executive,38334,1 +60992,Female,42,Masters,9,88,43,7,3,7.0,7,87,Rural,Software Engineer,136716,0 +60993,Female,26,High School,12,80,21,38,5,5.0,6,76,Rural,Software Engineer,114575,0 +60994,Male,55,Bachelors,1,25,22,98,21,5.0,1,57,Urban,Data Analyst,84106,0 +60995,Female,50,Masters,1,58,59,8,20,6.0,4,57,Semi-Urban,Data Analyst,87260,0 +60996,Male,49,Masters,18,86,95,34,47,8.0,5,93,Urban,Data Analyst,77095,1 +60997,Male,30,Masters,12,24,7,1,55,5.0,3,68,Semi-Urban,HR Executive,120964,0 +60998,Male,29,Diploma,2,9,2,54,26,1.0,4,43,Urban,Software Engineer,28641,0 +60999,Female,29,Masters,4,39,97,77,63,6.0,7,35,Rural,HR Executive,146956,1 +61000,Female,36,Bachelors,18,13,0,1,33,3.0,1,95,Semi-Urban,Manager,35843,0 +61001,Female,42,Bachelors,18,89,96,62,26,1.0,6,93,Urban,HR Executive,42012,1 +61002,Male,57,Masters,9,74,96,14,3,8.0,2,52,Semi-Urban,Software Engineer,85307,1 +61003,Male,56,Bachelors,17,82,8,33,43,9.0,1,77,Rural,Software Engineer,133831,0 +61004,Male,44,PhD,10,57,96,97,11,5.0,1,58,Urban,Software Engineer,85345,1 +61005,Male,50,Bachelors,13,18,41,17,94,8.0,5,51,Urban,Manager,131016,0 +61006,Male,27,Bachelors,18,28,72,59,2,2.0,4,78,Rural,HR Executive,112627,1 +61007,Female,45,Masters,9,45,76,49,5,6.0,4,20,Semi-Urban,Data Analyst,75984,0 +61008,Male,55,High School,7,84,19,89,93,3.0,6,88,Urban,Data Analyst,93828,1 +61009,Male,31,Diploma,18,71,65,79,84,2.0,0,77,Rural,Data Analyst,25683,1 +61010,Male,49,Masters,18,19,5,25,21,7.0,1,0,Urban,Software Engineer,115967,0 +61011,Male,55,Masters,17,62,3,55,44,6.0,6,21,Semi-Urban,ML Engineer,114720,0 +61012,Female,48,Diploma,3,40,97,25,68,7.0,3,6,Urban,ML Engineer,56004,0 +61013,Female,29,High School,4,1,98,30,50,0.0,2,66,Semi-Urban,Manager,44797,0 +61014,Female,29,Bachelors,2,98,47,21,16,9.0,4,88,Urban,Data Analyst,51657,1 +61015,Male,22,Masters,1,15,71,12,83,3.0,3,74,Semi-Urban,Manager,112635,0 +61016,Female,54,Bachelors,9,17,23,77,20,4.0,6,38,Urban,ML Engineer,42622,0 +61017,Male,47,High School,15,60,32,32,90,0.0,0,9,Urban,ML Engineer,74305,0 +61018,Female,41,PhD,10,95,69,3,72,6.0,6,36,Urban,Software Engineer,140383,0 +61019,Other,43,High School,3,74,24,1,7,1.0,5,69,Urban,Data Analyst,34197,0 +61020,Male,40,Bachelors,9,50,95,31,21,9.0,4,45,Urban,Data Analyst,138082,0 +61021,Female,24,Bachelors,8,67,3,75,25,8.0,5,16,Semi-Urban,Software Engineer,120683,0 +61022,Male,30,Bachelors,12,13,20,57,85,2.0,3,26,Semi-Urban,ML Engineer,73866,0 +61023,Male,51,High School,19,99,67,14,29,5.0,5,21,Urban,Manager,29082,0 +61024,Male,55,Bachelors,5,4,53,57,96,6.0,6,64,Urban,Manager,42244,0 +61025,Male,49,Diploma,8,93,33,26,22,8.0,3,35,Urban,Software Engineer,85173,0 +61026,Female,52,Bachelors,15,11,12,3,93,9.0,4,96,Urban,HR Executive,139964,0 +61027,Other,42,Masters,6,58,19,92,16,1.0,7,55,Rural,ML Engineer,140259,0 +61028,Male,35,Masters,4,47,18,41,13,4.0,2,58,Semi-Urban,Manager,102502,0 +61029,Female,29,Bachelors,7,11,62,81,55,8.0,7,18,Urban,HR Executive,147462,0 +61030,Female,36,High School,0,72,60,26,52,7.0,7,41,Urban,Manager,120913,0 +61031,Male,29,High School,8,1,5,58,32,2.0,2,82,Rural,Manager,82151,0 +61032,Male,43,High School,18,9,48,64,91,7.0,2,48,Urban,HR Executive,129619,0 +61033,Female,21,High School,2,90,24,49,31,9.0,3,76,Urban,Manager,40002,0 +61034,Male,38,Diploma,14,19,24,63,98,7.0,1,99,Urban,Manager,122162,0 +61035,Female,58,High School,1,14,87,50,45,7.0,5,45,Rural,Data Analyst,29766,0 +61036,Female,42,Masters,15,99,42,93,28,7.0,1,54,Rural,Data Analyst,73172,1 +61037,Male,29,Bachelors,0,99,22,67,8,1.0,0,71,Urban,Software Engineer,95442,1 +61038,Male,40,High School,5,85,40,69,89,8.0,6,31,Rural,Data Analyst,24934,0 +61039,Male,24,Bachelors,0,5,72,20,60,3.0,6,22,Rural,ML Engineer,37721,0 +61040,Male,43,Bachelors,7,80,39,87,66,6.0,4,74,Semi-Urban,Software Engineer,60047,1 +61041,Female,22,Bachelors,8,93,66,7,51,9.0,2,95,Semi-Urban,Manager,134770,1 +61042,Male,26,Bachelors,19,43,34,76,33,5.0,4,91,Urban,Software Engineer,114624,1 +61043,Male,29,Diploma,7,21,83,67,81,2.0,6,31,Semi-Urban,ML Engineer,96581,0 +61044,Male,33,High School,4,57,82,85,84,2.0,6,69,Urban,Software Engineer,104586,1 +61045,Male,59,Diploma,3,82,45,62,92,0.0,5,43,Rural,Data Analyst,36607,0 +61046,Male,53,Bachelors,8,76,61,41,58,5.0,7,98,Semi-Urban,HR Executive,82100,1 +61047,Male,39,Bachelors,10,29,30,26,31,7.0,6,67,Semi-Urban,ML Engineer,143304,0 +61048,Male,32,Masters,8,10,96,17,54,9.0,2,60,Urban,Data Analyst,117006,0 +61049,Male,55,Bachelors,17,75,84,35,19,9.0,4,44,Urban,ML Engineer,24050,1 +61050,Female,24,High School,10,44,55,36,16,2.0,6,11,Urban,HR Executive,67641,0 +61051,Female,24,Bachelors,6,87,48,85,63,7.0,5,12,Urban,ML Engineer,93402,0 +61052,Male,30,Diploma,17,36,48,6,25,2.0,0,80,Urban,Manager,42392,0 +61053,Male,52,PhD,16,13,22,63,54,1.0,5,60,Semi-Urban,HR Executive,25930,0 +61054,Female,34,Bachelors,1,80,13,9,78,9.0,6,74,Urban,Manager,98999,0 +61055,Male,42,Bachelors,15,70,29,6,78,3.0,0,91,Semi-Urban,Data Analyst,97353,0 +61056,Male,26,Bachelors,18,59,83,84,52,8.0,3,88,Semi-Urban,Data Analyst,84075,1 +61057,Male,56,Bachelors,6,52,14,1,44,5.0,7,62,Urban,Software Engineer,105166,0 +61058,Male,36,Bachelors,1,47,94,31,6,1.0,2,18,Urban,Data Analyst,44469,0 +61059,Male,57,Masters,4,8,58,45,57,2.0,3,44,Urban,Software Engineer,83867,0 +61060,Female,48,Diploma,16,91,66,5,22,8.0,1,92,Rural,Manager,89462,1 +61061,Male,58,Bachelors,0,35,11,8,90,3.0,2,44,Urban,HR Executive,68672,0 +61062,Male,52,High School,15,58,84,73,50,5.0,1,3,Semi-Urban,Manager,113298,0 +61063,Female,37,High School,18,43,46,4,79,9.0,5,44,Rural,Data Analyst,114572,0 +61064,Female,48,Masters,3,77,56,44,25,7.0,2,92,Semi-Urban,HR Executive,65517,1 +61065,Male,26,Bachelors,6,94,99,59,0,5.0,5,46,Urban,Software Engineer,139739,1 +61066,Female,44,Masters,14,13,5,94,4,3.0,2,20,Urban,HR Executive,31662,0 +61067,Female,47,Diploma,16,88,81,10,50,1.0,0,36,Semi-Urban,Data Analyst,21326,0 +61068,Male,40,Masters,13,83,24,17,64,9.0,1,40,Urban,Manager,122344,0 +61069,Other,53,PhD,17,55,38,65,27,4.0,3,31,Urban,Software Engineer,46424,0 +61070,Male,43,High School,4,60,56,64,76,2.0,2,55,Rural,Software Engineer,32705,1 +61071,Male,24,Diploma,15,48,52,30,51,3.0,3,46,Urban,Data Analyst,23213,0 +61072,Male,22,High School,14,1,18,66,96,4.0,4,41,Urban,HR Executive,91562,0 +61073,Male,51,Bachelors,11,28,71,88,58,9.0,4,19,Rural,HR Executive,96785,0 +61074,Male,22,Bachelors,0,50,30,27,40,7.0,7,8,Urban,Manager,129783,0 +61075,Female,46,Bachelors,9,67,70,47,12,3.0,4,19,Semi-Urban,HR Executive,47563,0 +61076,Male,54,Bachelors,17,99,28,86,0,4.0,1,46,Semi-Urban,Software Engineer,118858,1 +61077,Other,41,Bachelors,3,85,97,15,90,6.0,6,23,Urban,Data Analyst,70358,0 +61078,Female,26,Diploma,3,63,67,0,1,7.0,0,16,Rural,Data Analyst,128533,0 +61079,Female,39,Bachelors,19,27,18,66,45,0.0,3,39,Rural,HR Executive,44793,0 +61080,Male,27,Bachelors,3,78,98,72,88,2.0,2,29,Rural,Manager,29136,1 +61081,Male,58,Bachelors,1,55,69,38,56,3.0,0,7,Urban,Manager,79120,0 +61082,Male,24,Diploma,4,69,82,21,36,8.0,1,74,Urban,HR Executive,79251,1 +61083,Female,36,Diploma,18,41,90,29,64,9.0,2,18,Urban,Manager,97428,0 +61084,Male,44,Diploma,15,70,7,81,99,4.0,6,6,Urban,Manager,51902,0 +61085,Female,52,Bachelors,1,11,29,63,7,0.0,7,46,Urban,HR Executive,43450,0 +61086,Male,26,High School,9,49,93,16,1,9.0,7,28,Urban,Data Analyst,102308,0 +61087,Female,49,Diploma,0,50,12,91,75,6.0,2,23,Urban,HR Executive,138563,0 +61088,Male,45,High School,6,41,96,35,47,7.0,4,0,Rural,Software Engineer,72411,0 +61089,Male,45,Bachelors,18,89,65,55,96,7.0,0,55,Urban,Manager,40300,1 +61090,Other,28,Masters,7,73,17,36,54,1.0,0,66,Urban,ML Engineer,96274,0 +61091,Female,38,Bachelors,10,51,59,58,38,8.0,0,55,Semi-Urban,ML Engineer,145175,0 +61092,Female,29,Bachelors,3,17,96,0,56,8.0,5,52,Urban,Manager,34599,0 +61093,Male,42,Bachelors,5,52,34,93,42,2.0,4,15,Rural,Data Analyst,127494,0 +61094,Other,33,High School,16,5,2,7,35,9.0,2,97,Semi-Urban,Manager,148698,0 +61095,Female,41,Bachelors,12,10,69,22,34,8.0,5,87,Rural,Software Engineer,78113,0 +61096,Female,56,Bachelors,17,84,69,48,6,9.0,6,88,Semi-Urban,Manager,87660,1 +61097,Female,23,Masters,19,17,76,52,50,1.0,7,58,Urban,ML Engineer,76900,0 +61098,Female,45,Bachelors,19,20,78,55,19,5.0,5,43,Urban,HR Executive,51599,0 +61099,Female,52,Masters,4,15,27,4,78,4.0,2,0,Semi-Urban,HR Executive,88153,0 +61100,Female,49,High School,16,36,99,0,15,0.0,6,1,Semi-Urban,ML Engineer,29749,0 +61101,Male,38,High School,14,84,93,12,41,5.0,2,92,Urban,HR Executive,140984,1 +61102,Female,48,Bachelors,2,79,5,10,97,0.0,5,25,Urban,Manager,149488,0 +61103,Male,55,Diploma,5,88,30,21,32,1.0,2,90,Urban,Data Analyst,64816,0 +61104,Female,39,PhD,17,54,14,51,52,7.0,0,88,Urban,ML Engineer,89817,0 +61105,Male,23,Diploma,0,72,34,67,33,8.0,6,37,Urban,Manager,61546,0 +61106,Female,45,Bachelors,7,53,90,15,26,0.0,2,86,Rural,HR Executive,51112,1 +61107,Female,58,Bachelors,15,75,39,6,65,5.0,1,16,Rural,HR Executive,32993,0 +61108,Male,57,Diploma,7,81,91,50,72,4.0,7,44,Urban,Data Analyst,98258,1 +61109,Male,42,High School,14,99,16,18,69,8.0,6,73,Urban,Data Analyst,48212,0 +61110,Female,57,Bachelors,12,61,73,29,21,4.0,6,69,Urban,Software Engineer,23108,0 +61111,Male,21,Bachelors,10,18,56,8,80,8.0,1,81,Semi-Urban,Data Analyst,101742,0 +61112,Female,39,High School,16,70,17,89,78,9.0,2,14,Urban,ML Engineer,69670,0 +61113,Female,49,Bachelors,2,53,31,92,59,4.0,2,52,Urban,Data Analyst,149266,0 +61114,Male,42,High School,12,59,97,77,96,1.0,7,41,Urban,Software Engineer,35412,1 +61115,Female,30,High School,10,2,38,29,43,3.0,0,34,Semi-Urban,ML Engineer,40422,0 +61116,Male,51,Bachelors,3,46,21,62,20,2.0,4,0,Urban,ML Engineer,22808,0 +61117,Male,41,Bachelors,11,62,19,87,63,8.0,7,9,Urban,Data Analyst,24357,0 +61118,Male,26,Bachelors,17,87,21,48,81,3.0,5,61,Urban,ML Engineer,115963,0 +61119,Other,41,Bachelors,3,49,7,25,5,5.0,3,76,Urban,Data Analyst,38260,0 +61120,Female,21,PhD,0,84,50,80,60,5.0,7,90,Urban,Manager,131848,1 +61121,Female,38,High School,15,37,62,39,83,4.0,1,38,Semi-Urban,Software Engineer,128429,0 +61122,Male,55,Bachelors,11,69,10,83,33,7.0,6,27,Semi-Urban,Manager,63597,0 +61123,Male,57,Bachelors,3,77,88,82,14,6.0,6,38,Rural,Data Analyst,30556,1 +61124,Male,46,Diploma,13,26,3,17,2,5.0,6,25,Urban,Software Engineer,103872,0 +61125,Male,29,High School,10,72,70,93,36,6.0,6,0,Rural,HR Executive,45314,1 +61126,Female,50,Diploma,19,93,18,79,12,0.0,0,66,Rural,Software Engineer,67351,1 +61127,Male,28,Bachelors,17,69,96,38,76,1.0,1,77,Urban,Data Analyst,126716,1 +61128,Male,57,PhD,17,63,15,38,90,2.0,1,20,Urban,Data Analyst,74791,0 +61129,Male,40,PhD,6,40,8,24,14,9.0,4,90,Urban,ML Engineer,90645,0 +61130,Male,26,Masters,4,92,49,31,37,4.0,0,56,Rural,HR Executive,70308,0 +61131,Male,50,Diploma,17,63,49,60,17,6.0,5,33,Urban,ML Engineer,41378,0 +61132,Female,49,Bachelors,19,82,87,19,55,5.0,5,84,Urban,ML Engineer,30984,1 +61133,Female,49,Bachelors,17,58,38,63,62,3.0,7,46,Semi-Urban,HR Executive,40690,0 +61134,Female,56,Masters,14,46,36,64,52,9.0,7,80,Semi-Urban,Software Engineer,34472,0 +61135,Male,22,Masters,6,96,52,1,0,8.0,6,4,Urban,Software Engineer,47877,0 +61136,Male,54,Bachelors,9,68,23,14,66,1.0,2,7,Semi-Urban,Software Engineer,131112,0 +61137,Male,49,Bachelors,17,76,72,92,16,5.0,5,28,Semi-Urban,Data Analyst,28183,1 +61138,Female,30,High School,1,77,78,97,72,2.0,4,50,Rural,Software Engineer,72380,1 +61139,Female,41,Bachelors,5,73,60,55,2,1.0,6,44,Urban,ML Engineer,46016,0 +61140,Female,52,PhD,2,24,45,61,93,2.0,6,12,Urban,Software Engineer,93810,0 +61141,Male,32,Bachelors,15,98,59,43,60,7.0,3,40,Urban,Manager,86224,1 +61142,Other,37,Masters,19,37,11,71,91,9.0,4,12,Semi-Urban,Data Analyst,130152,0 +61143,Male,30,PhD,10,68,56,27,83,6.0,6,95,Urban,ML Engineer,67448,1 +61144,Female,45,Bachelors,15,50,61,40,38,5.0,3,53,Urban,ML Engineer,68845,0 +61145,Male,56,Bachelors,12,96,54,4,97,6.0,2,65,Urban,ML Engineer,92446,0 +61146,Female,35,Diploma,11,91,75,70,82,1.0,7,20,Urban,HR Executive,144484,1 +61147,Female,34,Bachelors,17,31,31,56,44,9.0,1,23,Rural,Software Engineer,124691,0 +61148,Female,55,Masters,10,55,90,66,93,0.0,7,23,Semi-Urban,ML Engineer,116539,0 +61149,Female,32,Diploma,12,18,5,5,21,3.0,7,41,Urban,Software Engineer,28293,0 +61150,Female,39,Masters,1,33,8,76,35,1.0,6,23,Semi-Urban,HR Executive,133666,0 +61151,Male,59,Bachelors,1,27,28,20,95,0.0,7,42,Rural,ML Engineer,118083,0 +61152,Female,34,PhD,9,60,32,59,39,2.0,4,63,Urban,ML Engineer,45051,0 +61153,Other,23,Masters,1,67,42,29,5,7.0,7,54,Rural,ML Engineer,85449,0 +61154,Female,53,Masters,17,52,22,39,86,2.0,2,93,Urban,Software Engineer,116653,0 +61155,Other,36,Diploma,18,7,0,95,7,5.0,0,25,Urban,ML Engineer,23676,0 +61156,Male,58,Masters,4,33,45,96,63,2.0,4,29,Semi-Urban,Software Engineer,126193,0 +61157,Female,50,Bachelors,10,57,2,43,79,7.0,2,75,Semi-Urban,Software Engineer,132547,0 +61158,Male,51,Masters,13,72,37,69,0,2.0,1,2,Urban,Data Analyst,31370,0 +61159,Male,49,Diploma,6,21,78,4,33,6.0,6,36,Semi-Urban,HR Executive,37241,0 +61160,Female,55,High School,7,2,46,73,81,3.0,7,42,Urban,HR Executive,120248,0 +61161,Female,25,Bachelors,18,69,68,97,54,3.0,5,80,Urban,Data Analyst,27492,1 +61162,Female,58,Bachelors,11,1,55,58,43,2.0,7,6,Rural,ML Engineer,123570,0 +61163,Male,45,High School,7,30,60,9,9,8.0,2,14,Semi-Urban,Manager,49290,0 +61164,Other,30,Bachelors,13,39,41,30,68,9.0,0,63,Rural,HR Executive,133478,0 +61165,Male,58,High School,15,31,90,1,40,9.0,6,62,Rural,Software Engineer,115781,0 +61166,Female,33,Bachelors,12,97,21,92,62,2.0,6,87,Semi-Urban,ML Engineer,64088,1 +61167,Female,42,Bachelors,18,5,82,12,89,9.0,4,33,Urban,Data Analyst,89622,0 +61168,Female,29,High School,8,95,56,11,58,7.0,3,7,Rural,Data Analyst,41907,0 +61169,Female,35,Bachelors,12,1,45,50,81,6.0,5,54,Urban,ML Engineer,29367,0 +61170,Male,43,High School,12,97,35,84,48,0.0,6,31,Rural,Manager,130419,1 +61171,Male,24,Bachelors,4,71,8,95,78,5.0,3,18,Urban,ML Engineer,81894,0 +61172,Male,57,Diploma,5,88,19,97,27,0.0,0,54,Rural,HR Executive,83079,1 +61173,Male,36,Masters,19,40,10,30,15,6.0,6,95,Urban,ML Engineer,93727,0 +61174,Female,44,Masters,8,9,42,21,69,1.0,6,10,Semi-Urban,Manager,104735,0 +61175,Female,42,High School,12,35,27,13,41,4.0,1,62,Rural,ML Engineer,126019,0 +61176,Male,51,Bachelors,12,68,72,57,51,9.0,6,89,Urban,Manager,47674,1 +61177,Female,54,Diploma,6,92,40,58,8,6.0,7,27,Rural,HR Executive,107770,0 +61178,Male,52,Bachelors,16,24,31,71,72,7.0,7,79,Urban,Software Engineer,82487,0 +61179,Male,58,Diploma,15,94,90,42,35,5.0,7,43,Semi-Urban,Data Analyst,38294,1 +61180,Female,50,Masters,8,54,46,30,61,9.0,0,62,Semi-Urban,Software Engineer,20855,0 +61181,Female,55,Bachelors,5,83,23,60,27,2.0,5,16,Semi-Urban,Software Engineer,97071,0 +61182,Male,27,Diploma,5,39,47,90,63,9.0,3,80,Urban,Manager,41552,1 +61183,Female,48,High School,4,61,21,47,57,3.0,4,79,Rural,Manager,93579,0 +61184,Male,52,Bachelors,14,28,40,97,85,2.0,4,68,Urban,ML Engineer,74492,0 +61185,Male,46,Diploma,0,35,55,33,29,4.0,1,65,Semi-Urban,ML Engineer,94719,0 +61186,Male,55,Diploma,4,6,70,80,44,6.0,6,21,Rural,ML Engineer,79207,0 +61187,Male,43,Bachelors,10,44,38,58,2,1.0,0,80,Urban,HR Executive,65205,0 +61188,Female,32,Diploma,13,93,8,44,72,1.0,7,3,Semi-Urban,Manager,88790,0 +61189,Male,54,PhD,0,30,51,9,6,9.0,3,85,Urban,Manager,94328,0 +61190,Male,47,Masters,14,86,42,88,80,7.0,4,73,Rural,ML Engineer,126505,1 +61191,Male,29,Masters,13,86,38,16,87,2.0,5,90,Rural,Data Analyst,111621,0 +61192,Male,58,Diploma,2,95,33,56,3,6.0,0,16,Urban,Software Engineer,114050,0 +61193,Female,45,High School,15,46,81,56,67,5.0,5,2,Rural,Data Analyst,128689,0 +61194,Female,35,Masters,6,70,7,66,7,0.0,2,80,Semi-Urban,Manager,33935,0 +61195,Male,51,Bachelors,15,6,65,48,99,3.0,4,64,Semi-Urban,HR Executive,26394,0 +61196,Female,50,Bachelors,15,90,13,86,62,9.0,5,97,Urban,HR Executive,114848,1 +61197,Male,27,Bachelors,16,14,87,98,31,0.0,5,74,Urban,HR Executive,67583,1 +61198,Male,56,Diploma,13,72,68,14,96,4.0,6,75,Rural,HR Executive,122300,0 +61199,Male,41,High School,13,41,7,9,71,5.0,0,3,Urban,Data Analyst,125487,0 +61200,Female,56,High School,13,31,69,33,22,4.0,5,18,Urban,Software Engineer,41965,0 +61201,Male,34,Bachelors,18,13,27,37,97,6.0,3,52,Urban,Manager,90810,0 +61202,Female,52,Masters,2,64,16,2,7,2.0,5,96,Rural,ML Engineer,141765,0 +61203,Male,27,Bachelors,13,82,51,4,45,8.0,5,24,Urban,Data Analyst,23681,0 +61204,Male,57,Diploma,5,73,98,61,25,6.0,4,99,Urban,ML Engineer,142494,1 +61205,Female,37,Masters,10,18,15,88,25,4.0,1,73,Semi-Urban,Manager,144906,0 +61206,Male,55,Bachelors,19,61,28,37,44,1.0,5,79,Urban,Software Engineer,142514,0 +61207,Male,52,Masters,12,33,98,25,92,1.0,3,28,Urban,HR Executive,38700,0 +61208,Male,26,Masters,13,14,39,38,38,9.0,2,86,Rural,HR Executive,49910,0 +61209,Female,41,Bachelors,4,3,22,89,96,9.0,6,99,Semi-Urban,Software Engineer,75920,0 +61210,Male,31,Bachelors,17,58,38,13,48,6.0,3,66,Semi-Urban,HR Executive,21014,0 +61211,Male,55,Bachelors,13,64,87,24,17,2.0,6,73,Rural,HR Executive,132645,1 +61212,Male,22,High School,12,73,64,57,82,8.0,0,31,Rural,Data Analyst,31826,0 +61213,Female,53,Bachelors,11,86,54,33,66,1.0,2,65,Urban,Software Engineer,113110,0 +61214,Male,21,Bachelors,5,60,57,0,4,0.0,4,98,Urban,Manager,69277,0 +61215,Female,26,Bachelors,14,7,20,34,45,9.0,3,78,Urban,ML Engineer,41983,0 +61216,Female,25,Bachelors,17,82,26,11,83,2.0,1,81,Rural,Data Analyst,25307,0 +61217,Other,38,High School,5,38,44,88,8,2.0,3,97,Urban,ML Engineer,43187,1 +61218,Female,35,Bachelors,3,35,8,99,33,6.0,6,8,Urban,Software Engineer,84577,0 +61219,Other,56,Diploma,19,5,25,1,34,7.0,1,6,Semi-Urban,ML Engineer,107446,0 +61220,Female,37,Diploma,9,27,80,88,97,2.0,6,4,Urban,Data Analyst,136950,0 +61221,Male,37,Bachelors,5,70,29,51,1,5.0,1,35,Urban,Manager,45261,0 +61222,Male,57,Masters,5,34,34,34,20,7.0,1,12,Urban,Software Engineer,54614,0 +61223,Male,42,Bachelors,18,58,96,17,32,9.0,5,26,Rural,ML Engineer,123336,0 +61224,Male,47,Bachelors,4,85,73,82,73,4.0,4,97,Rural,ML Engineer,67059,1 +61225,Male,25,Bachelors,3,82,36,72,2,6.0,3,14,Rural,Software Engineer,71037,0 +61226,Female,58,Masters,13,20,95,35,66,0.0,0,17,Urban,HR Executive,41493,0 +61227,Other,48,Masters,18,78,7,16,38,5.0,7,80,Urban,Manager,76800,0 +61228,Male,30,Bachelors,11,50,33,24,39,1.0,1,64,Urban,HR Executive,65152,0 +61229,Male,47,Masters,4,59,70,80,70,7.0,6,54,Semi-Urban,HR Executive,123256,1 +61230,Male,56,Masters,16,33,90,69,87,9.0,6,85,Rural,Data Analyst,60432,1 +61231,Male,44,High School,15,50,21,88,54,7.0,3,6,Semi-Urban,Software Engineer,51045,0 +61232,Male,47,High School,17,25,77,61,14,9.0,2,26,Urban,ML Engineer,73917,0 +61233,Female,48,High School,7,94,90,87,32,0.0,5,82,Urban,Software Engineer,52533,1 +61234,Female,53,Diploma,7,44,75,80,16,6.0,5,50,Urban,Software Engineer,82037,1 +61235,Male,21,Diploma,5,35,11,43,28,4.0,5,76,Semi-Urban,HR Executive,91840,0 +61236,Male,49,Bachelors,17,37,41,81,23,5.0,5,47,Urban,Software Engineer,60005,0 +61237,Female,36,Bachelors,10,76,77,91,20,8.0,3,3,Semi-Urban,Manager,61308,1 +61238,Female,39,Bachelors,3,66,68,40,76,8.0,6,52,Semi-Urban,Software Engineer,21757,0 +61239,Female,26,Masters,5,94,44,20,26,1.0,5,71,Rural,HR Executive,37416,0 +61240,Other,54,Bachelors,14,29,55,61,35,3.0,0,82,Urban,ML Engineer,67374,0 +61241,Male,26,Diploma,0,62,44,69,71,2.0,1,63,Rural,Manager,83583,1 +61242,Male,30,Masters,6,31,41,30,84,7.0,6,20,Urban,ML Engineer,25261,0 +61243,Other,56,Bachelors,8,56,81,96,42,6.0,4,66,Urban,Software Engineer,136320,1 +61244,Female,52,Bachelors,10,17,87,75,78,8.0,4,52,Urban,Software Engineer,131447,0 +61245,Female,29,Diploma,0,27,68,47,67,8.0,6,41,Urban,Software Engineer,77374,0 +61246,Male,35,High School,5,92,61,93,1,6.0,3,36,Urban,Manager,72455,1 +61247,Male,59,Masters,18,29,16,56,4,0.0,6,9,Urban,ML Engineer,104511,0 +61248,Male,38,Bachelors,18,25,47,10,34,5.0,2,4,Semi-Urban,HR Executive,24485,0 +61249,Male,30,Masters,15,6,88,16,80,9.0,4,12,Semi-Urban,HR Executive,132919,0 +61250,Male,29,Diploma,2,11,28,17,3,9.0,0,57,Urban,HR Executive,25412,0 +61251,Female,36,Bachelors,5,65,87,77,14,5.0,7,7,Semi-Urban,Data Analyst,136664,0 +61252,Male,25,High School,15,28,93,6,94,6.0,6,81,Rural,Data Analyst,124765,0 +61253,Male,46,Diploma,10,77,84,79,70,8.0,6,45,Rural,HR Executive,101172,1 +61254,Male,24,Bachelors,3,24,69,87,28,0.0,4,56,Urban,Manager,23024,1 +61255,Female,39,PhD,4,76,52,80,58,0.0,0,23,Rural,ML Engineer,131544,0 +61256,Other,35,Bachelors,16,25,79,11,98,2.0,5,36,Rural,ML Engineer,109955,0 +61257,Female,51,Bachelors,16,13,96,42,40,0.0,4,4,Urban,Data Analyst,125337,0 +61258,Female,29,Bachelors,3,71,33,56,6,5.0,1,7,Urban,ML Engineer,137866,0 +61259,Male,31,High School,10,45,89,89,12,6.0,1,96,Semi-Urban,HR Executive,67308,1 +61260,Male,59,High School,11,75,72,55,44,0.0,2,95,Urban,HR Executive,96976,1 +61261,Female,49,Masters,8,87,63,62,43,3.0,4,5,Urban,HR Executive,53489,0 +61262,Female,59,Diploma,0,86,72,67,35,1.0,4,7,Urban,Manager,34127,0 +61263,Male,35,Bachelors,3,37,58,57,75,7.0,6,85,Urban,HR Executive,54892,1 +61264,Male,57,Diploma,3,76,59,29,38,1.0,3,62,Urban,HR Executive,101234,0 +61265,Male,22,High School,9,0,4,2,43,4.0,0,15,Semi-Urban,Data Analyst,103046,0 +61266,Male,43,Bachelors,4,87,84,98,9,4.0,7,7,Urban,Software Engineer,33935,1 +61267,Female,29,Bachelors,0,54,28,20,45,8.0,1,25,Urban,HR Executive,40933,0 +61268,Male,33,Masters,5,48,99,70,9,0.0,1,89,Urban,Manager,94481,1 +61269,Female,34,Bachelors,7,3,74,88,42,7.0,5,64,Urban,HR Executive,64444,0 +61270,Male,57,High School,5,62,81,62,67,8.0,7,39,Semi-Urban,Manager,113235,1 +61271,Other,41,Masters,19,74,53,98,78,2.0,7,29,Urban,HR Executive,90557,1 +61272,Male,38,Masters,16,4,54,2,32,6.0,5,13,Urban,Data Analyst,30286,0 +61273,Female,22,High School,10,60,2,27,26,1.0,5,91,Semi-Urban,HR Executive,92901,0 +61274,Male,39,Masters,0,9,41,60,50,4.0,5,1,Urban,Data Analyst,71875,0 +61275,Female,54,Bachelors,5,78,60,20,86,3.0,7,86,Semi-Urban,ML Engineer,57918,1 +61276,Male,43,Diploma,15,0,56,24,48,0.0,2,38,Rural,HR Executive,39533,0 +61277,Male,41,Diploma,7,44,69,95,88,4.0,1,55,Urban,HR Executive,31315,1 +61278,Male,56,Masters,1,34,17,15,97,6.0,4,8,Urban,Data Analyst,115566,0 +61279,Female,43,Bachelors,3,46,86,66,0,8.0,0,84,Urban,ML Engineer,69465,1 +61280,Male,24,High School,12,69,31,89,61,8.0,5,12,Urban,Manager,38950,0 +61281,Male,47,Bachelors,10,52,0,56,60,8.0,7,7,Urban,Data Analyst,53851,0 +61282,Female,42,High School,14,2,26,79,77,3.0,7,50,Urban,Data Analyst,107445,0 +61283,Female,33,Diploma,17,32,40,74,84,5.0,1,19,Semi-Urban,HR Executive,137760,0 +61284,Male,38,High School,8,49,22,14,33,5.0,4,29,Semi-Urban,Data Analyst,54087,0 +61285,Male,24,High School,6,27,61,36,29,5.0,7,23,Urban,Data Analyst,112912,0 +61286,Female,58,Diploma,14,11,65,18,79,2.0,5,97,Rural,Software Engineer,72964,0 +61287,Female,41,PhD,1,84,1,45,43,7.0,1,79,Rural,ML Engineer,80258,0 +61288,Female,38,High School,6,94,24,97,68,8.0,2,59,Urban,ML Engineer,31749,1 +61289,Male,36,Diploma,5,84,44,73,73,0.0,4,80,Urban,Software Engineer,130009,1 +61290,Female,40,High School,5,92,9,64,83,6.0,7,24,Urban,Software Engineer,114157,0 +61291,Male,36,Diploma,14,73,94,42,96,3.0,7,28,Urban,Software Engineer,26508,1 +61292,Male,24,Bachelors,19,93,33,94,13,9.0,4,11,Semi-Urban,Software Engineer,112056,0 +61293,Male,50,PhD,12,22,28,88,95,8.0,1,78,Urban,Software Engineer,21913,0 +61294,Female,56,Bachelors,16,45,71,16,80,3.0,5,22,Urban,Manager,131470,0 +61295,Female,32,Bachelors,14,21,2,53,96,1.0,5,91,Semi-Urban,ML Engineer,146736,0 +61296,Female,41,High School,18,58,55,3,97,0.0,5,53,Urban,Manager,130961,0 +61297,Male,29,Bachelors,5,82,20,78,67,1.0,0,42,Urban,HR Executive,139670,0 +61298,Female,58,Bachelors,10,91,1,33,58,0.0,4,25,Urban,Data Analyst,63622,0 +61299,Male,41,High School,8,71,55,12,27,5.0,1,9,Urban,Data Analyst,113330,0 +61300,Other,49,Masters,1,93,18,21,49,5.0,2,42,Urban,Software Engineer,132067,0 +61301,Male,48,Diploma,10,25,93,57,38,5.0,3,38,Urban,Manager,69486,0 +61302,Male,28,Bachelors,11,29,68,97,77,8.0,5,31,Urban,Manager,20756,0 +61303,Male,56,Bachelors,3,85,79,11,6,9.0,2,11,Rural,Manager,66650,0 +61304,Male,26,Diploma,9,38,57,35,46,1.0,1,61,Rural,Data Analyst,147455,0 +61305,Female,31,Diploma,16,23,96,82,64,3.0,1,12,Urban,ML Engineer,141469,0 +61306,Male,24,Masters,4,51,96,48,59,6.0,6,12,Urban,Software Engineer,29794,0 +61307,Female,55,Masters,11,48,84,86,66,3.0,0,70,Urban,Manager,47317,1 +61308,Male,36,Bachelors,10,59,60,54,10,8.0,1,39,Urban,Manager,28760,0 +61309,Female,39,High School,4,87,19,0,38,8.0,3,43,Urban,Manager,68849,0 +61310,Female,42,High School,6,40,37,11,21,6.0,4,86,Urban,Data Analyst,133669,0 +61311,Male,32,High School,10,85,1,90,21,6.0,5,65,Semi-Urban,Manager,120746,1 +61312,Male,59,Masters,11,67,17,71,60,5.0,4,2,Urban,HR Executive,129963,0 +61313,Female,50,Diploma,3,18,40,0,72,5.0,1,49,Semi-Urban,Software Engineer,108319,0 +61314,Male,30,Masters,16,77,37,12,66,6.0,3,54,Urban,HR Executive,99016,0 +61315,Male,21,High School,13,71,55,18,24,6.0,2,50,Urban,ML Engineer,120450,0 +61316,Male,34,PhD,4,63,94,19,12,3.0,7,21,Urban,HR Executive,147930,0 +61317,Male,26,Bachelors,11,86,17,27,27,3.0,5,28,Urban,ML Engineer,130043,0 +61318,Male,56,High School,8,34,37,55,12,9.0,4,73,Urban,Data Analyst,31755,0 +61319,Male,22,High School,13,11,53,52,13,8.0,3,13,Semi-Urban,Data Analyst,52447,0 +61320,Other,59,Bachelors,0,28,92,87,82,9.0,6,87,Urban,Software Engineer,141420,1 +61321,Female,43,Bachelors,14,68,95,97,11,6.0,6,84,Semi-Urban,Software Engineer,79996,1 +61322,Female,36,Bachelors,18,24,66,32,53,7.0,1,35,Urban,Software Engineer,117366,0 +61323,Male,33,High School,11,2,60,20,41,0.0,6,21,Urban,HR Executive,109007,0 +61324,Male,35,Bachelors,0,26,74,73,82,4.0,7,22,Rural,Manager,108401,0 +61325,Male,54,Masters,18,49,63,29,62,4.0,4,6,Semi-Urban,Data Analyst,124930,0 +61326,Other,23,High School,14,29,46,16,28,1.0,1,46,Urban,HR Executive,76162,0 +61327,Female,46,Bachelors,11,72,24,34,98,2.0,3,33,Semi-Urban,Manager,46167,0 +61328,Male,38,Bachelors,13,50,87,55,31,2.0,4,73,Semi-Urban,Software Engineer,95560,1 +61329,Male,29,Masters,12,87,66,79,11,4.0,6,23,Semi-Urban,ML Engineer,129061,1 +61330,Male,31,Bachelors,4,82,54,37,70,3.0,7,57,Urban,ML Engineer,74963,0 +61331,Male,41,Bachelors,4,36,76,65,27,9.0,2,38,Semi-Urban,Software Engineer,96154,0 +61332,Male,43,Masters,19,75,13,72,39,2.0,6,91,Urban,ML Engineer,57805,1 +61333,Male,22,High School,3,79,78,87,23,0.0,7,29,Rural,Software Engineer,129525,1 +61334,Male,50,Masters,18,93,29,75,42,2.0,0,21,Semi-Urban,Software Engineer,60510,0 +61335,Male,34,Bachelors,19,69,43,10,15,3.0,6,64,Urban,Manager,81495,0 +61336,Female,26,Diploma,9,14,89,45,29,9.0,3,39,Urban,ML Engineer,141877,0 +61337,Male,33,Bachelors,3,10,95,6,54,6.0,6,21,Urban,Manager,96599,0 +61338,Male,41,Diploma,8,16,43,56,13,7.0,0,17,Semi-Urban,HR Executive,20582,0 +61339,Male,50,High School,2,7,9,1,49,8.0,4,79,Semi-Urban,ML Engineer,96657,0 +61340,Male,41,High School,19,48,37,19,19,9.0,4,51,Rural,Data Analyst,79909,0 +61341,Female,22,Diploma,1,99,53,5,1,2.0,2,45,Semi-Urban,Data Analyst,121102,0 +61342,Male,21,Bachelors,12,23,20,68,42,5.0,1,22,Rural,ML Engineer,124531,0 +61343,Male,46,Diploma,13,34,73,25,32,7.0,7,28,Rural,Software Engineer,20957,0 +61344,Male,32,PhD,18,62,9,58,8,3.0,1,40,Urban,HR Executive,89260,0 +61345,Male,37,Bachelors,1,89,17,90,60,9.0,1,47,Rural,HR Executive,113010,1 +61346,Other,35,Bachelors,3,54,7,61,62,1.0,4,31,Urban,Data Analyst,145963,0 +61347,Male,33,Masters,1,81,28,66,0,2.0,5,17,Rural,Data Analyst,103110,0 +61348,Male,57,Masters,15,9,3,26,53,1.0,3,20,Urban,ML Engineer,127719,0 +61349,Male,26,Masters,4,7,59,34,51,0.0,2,15,Urban,Manager,128420,0 +61350,Male,37,Bachelors,1,4,56,13,3,9.0,1,97,Semi-Urban,Software Engineer,27802,0 +61351,Male,49,High School,8,15,84,77,65,8.0,0,95,Rural,Data Analyst,44399,1 +61352,Male,32,Bachelors,8,63,31,43,13,6.0,3,99,Urban,HR Executive,58755,1 +61353,Female,52,High School,3,66,32,8,47,5.0,2,47,Rural,Software Engineer,68835,0 +61354,Male,49,Bachelors,17,34,67,96,71,5.0,1,98,Urban,Data Analyst,65925,1 +61355,Female,54,Diploma,17,54,67,97,6,5.0,6,83,Semi-Urban,Data Analyst,40351,1 +61356,Male,47,Bachelors,2,61,47,74,51,0.0,0,70,Urban,HR Executive,54653,1 +61357,Male,21,Diploma,4,2,66,42,92,5.0,6,64,Urban,Manager,93997,0 +61358,Female,50,Bachelors,3,68,45,1,18,4.0,1,64,Urban,Manager,84582,0 +61359,Female,46,Masters,1,2,7,19,54,8.0,2,99,Urban,HR Executive,117357,0 +61360,Male,29,Bachelors,9,49,24,85,40,9.0,6,53,Urban,Data Analyst,35983,0 +61361,Male,37,Bachelors,1,93,11,38,41,4.0,5,54,Urban,Software Engineer,104097,0 +61362,Male,22,Masters,7,11,88,68,82,9.0,7,72,Urban,HR Executive,35387,1 +61363,Male,21,Bachelors,6,31,48,2,57,6.0,1,20,Semi-Urban,ML Engineer,37185,0 +61364,Female,23,Masters,17,0,72,31,53,7.0,0,34,Urban,Manager,26149,0 +61365,Male,30,Diploma,15,21,89,31,32,7.0,2,39,Semi-Urban,HR Executive,85507,0 +61366,Other,47,Bachelors,0,94,31,12,75,3.0,7,94,Rural,ML Engineer,134304,0 +61367,Male,52,Masters,12,40,88,1,0,0.0,5,1,Rural,HR Executive,23580,0 +61368,Male,46,PhD,14,30,37,77,13,1.0,5,58,Urban,Software Engineer,147929,0 +61369,Male,57,Diploma,6,4,8,55,69,1.0,5,37,Urban,ML Engineer,146677,0 +61370,Female,21,Masters,16,35,21,75,81,3.0,4,94,Urban,Software Engineer,24587,0 +61371,Male,22,Masters,8,45,51,66,73,3.0,1,92,Urban,Manager,22537,1 +61372,Female,43,Masters,8,12,51,84,75,1.0,1,1,Semi-Urban,ML Engineer,32021,0 +61373,Male,41,Bachelors,18,26,31,13,57,6.0,7,19,Urban,Manager,149181,0 +61374,Male,28,Masters,6,39,59,14,53,4.0,6,37,Urban,ML Engineer,112808,0 +61375,Male,52,Masters,15,46,3,27,76,9.0,5,13,Urban,Data Analyst,70529,0 +61376,Female,35,Bachelors,16,34,68,99,79,4.0,3,30,Semi-Urban,ML Engineer,92184,0 +61377,Male,38,Bachelors,0,51,3,69,92,7.0,3,44,Rural,Data Analyst,93516,0 +61378,Male,35,Bachelors,6,7,98,7,63,3.0,4,22,Urban,HR Executive,50352,0 +61379,Male,42,Bachelors,14,55,17,43,18,6.0,4,79,Semi-Urban,Software Engineer,79675,0 +61380,Male,27,Masters,3,43,39,39,69,4.0,6,56,Urban,Data Analyst,142253,0 +61381,Male,30,Diploma,8,66,63,61,77,2.0,2,25,Urban,Data Analyst,139599,0 +61382,Other,36,Diploma,4,45,41,67,25,8.0,7,76,Urban,ML Engineer,53278,0 +61383,Female,48,Masters,18,20,19,65,35,5.0,6,51,Urban,Software Engineer,47666,0 +61384,Male,47,Masters,14,34,3,40,16,7.0,2,40,Rural,ML Engineer,122962,0 +61385,Female,22,Masters,6,45,6,77,27,5.0,3,89,Rural,Manager,26594,0 +61386,Female,51,Bachelors,4,27,18,67,78,0.0,1,53,Semi-Urban,ML Engineer,71307,0 +61387,Male,59,Masters,9,58,84,88,61,1.0,5,33,Rural,Software Engineer,99545,1 +61388,Male,40,Bachelors,13,13,97,74,6,9.0,7,90,Semi-Urban,Data Analyst,66610,1 +61389,Female,57,Bachelors,11,91,50,14,34,2.0,6,62,Urban,ML Engineer,74628,0 +61390,Male,25,Bachelors,6,18,59,27,62,4.0,3,79,Urban,HR Executive,59219,0 +61391,Male,49,Masters,13,2,1,76,80,0.0,5,97,Semi-Urban,Manager,47174,0 +61392,Female,25,Bachelors,17,88,15,86,19,5.0,0,50,Rural,HR Executive,104530,0 +61393,Male,29,Masters,9,14,46,95,89,1.0,5,61,Urban,ML Engineer,92498,0 +61394,Male,31,High School,5,56,38,90,80,9.0,6,43,Rural,Data Analyst,52795,0 +61395,Female,25,High School,11,72,11,7,94,3.0,6,16,Urban,Manager,114422,0 +61396,Male,41,Masters,3,85,57,50,25,6.0,6,4,Urban,Manager,33490,0 +61397,Female,51,Bachelors,6,56,97,18,50,6.0,2,63,Semi-Urban,ML Engineer,104264,0 +61398,Male,59,PhD,12,51,98,63,93,3.0,6,39,Urban,ML Engineer,142843,1 +61399,Male,49,Bachelors,1,79,98,52,15,9.0,3,19,Urban,ML Engineer,136077,1 +61400,Male,38,Bachelors,8,33,11,59,10,9.0,1,11,Urban,ML Engineer,108749,0 +61401,Female,31,Bachelors,8,66,86,89,72,5.0,0,19,Urban,Data Analyst,139455,1 +61402,Female,30,Masters,3,77,92,56,82,7.0,5,93,Urban,Software Engineer,97923,1 +61403,Female,51,Diploma,5,25,15,33,86,1.0,7,3,Rural,Software Engineer,141702,0 +61404,Male,41,Bachelors,12,18,58,96,9,0.0,2,27,Urban,Software Engineer,56133,0 +61405,Male,58,PhD,6,98,55,72,6,6.0,2,95,Urban,Data Analyst,25735,1 +61406,Male,56,Diploma,14,49,4,92,5,3.0,6,31,Urban,ML Engineer,40813,0 +61407,Male,22,Diploma,8,73,25,60,20,3.0,2,98,Urban,ML Engineer,80363,1 +61408,Male,51,High School,7,43,99,6,7,4.0,1,40,Semi-Urban,Data Analyst,147974,0 +61409,Male,33,Bachelors,14,25,96,37,41,5.0,5,46,Urban,HR Executive,93928,0 +61410,Male,49,Bachelors,12,25,27,68,84,5.0,3,70,Rural,Manager,67361,0 +61411,Male,41,Bachelors,8,4,96,68,88,0.0,3,25,Urban,ML Engineer,48945,0 +61412,Male,41,Bachelors,4,40,31,69,68,5.0,0,15,Semi-Urban,Manager,75250,0 +61413,Male,23,Bachelors,14,78,86,32,5,4.0,0,68,Rural,Manager,29563,1 +61414,Male,53,Diploma,12,56,59,44,90,0.0,4,79,Semi-Urban,Manager,36246,1 +61415,Male,36,Bachelors,0,44,48,21,34,5.0,0,65,Urban,Software Engineer,131906,0 +61416,Male,42,Bachelors,0,68,24,75,94,4.0,4,26,Urban,HR Executive,117860,0 +61417,Male,31,PhD,1,69,37,0,44,9.0,6,69,Semi-Urban,Data Analyst,89008,0 +61418,Male,38,Diploma,19,85,61,97,69,4.0,2,48,Urban,Manager,86438,1 +61419,Male,32,High School,19,23,90,97,54,9.0,2,39,Urban,ML Engineer,98410,1 +61420,Male,58,Diploma,6,54,76,27,76,9.0,1,44,Urban,Manager,47121,0 +61421,Female,56,Diploma,13,82,6,36,86,7.0,5,75,Rural,HR Executive,140977,0 +61422,Male,49,Bachelors,9,64,22,80,36,9.0,5,59,Urban,Software Engineer,49871,0 +61423,Female,30,PhD,16,15,71,14,27,4.0,2,67,Semi-Urban,Software Engineer,55417,0 +61424,Male,43,Masters,4,27,32,74,23,3.0,5,7,Urban,Manager,44701,0 +61425,Male,34,Bachelors,10,52,87,44,74,2.0,7,15,Rural,Data Analyst,123656,0 +61426,Male,42,Masters,6,95,29,44,92,4.0,6,91,Semi-Urban,HR Executive,98588,1 +61427,Male,21,Diploma,7,5,64,33,58,9.0,3,43,Urban,HR Executive,77006,0 +61428,Male,57,Masters,14,26,4,89,90,7.0,6,82,Urban,HR Executive,60497,0 +61429,Female,41,Bachelors,11,93,46,17,84,6.0,2,26,Urban,HR Executive,134591,0 +61430,Female,58,Diploma,17,86,42,0,64,0.0,6,3,Urban,Manager,133653,0 +61431,Male,52,Diploma,7,23,11,52,45,5.0,4,29,Semi-Urban,Data Analyst,111506,0 +61432,Male,35,Bachelors,19,63,39,19,2,9.0,5,87,Urban,HR Executive,52092,0 +61433,Male,56,High School,4,84,68,18,70,2.0,4,86,Urban,Data Analyst,57825,1 +61434,Male,59,Bachelors,17,89,93,83,69,5.0,5,54,Semi-Urban,ML Engineer,129438,1 +61435,Female,42,Bachelors,4,31,34,26,16,0.0,6,59,Urban,Software Engineer,49152,0 +61436,Other,21,Bachelors,3,53,6,98,1,3.0,1,77,Rural,HR Executive,66037,0 +61437,Male,26,High School,0,64,40,89,65,8.0,7,26,Semi-Urban,Software Engineer,128051,0 +61438,Female,51,Bachelors,11,30,94,5,31,6.0,2,93,Urban,Manager,102062,0 +61439,Female,32,Diploma,13,45,68,23,11,6.0,1,40,Semi-Urban,Manager,54027,0 +61440,Female,40,Diploma,7,88,56,18,85,6.0,3,73,Semi-Urban,ML Engineer,50637,0 +61441,Male,39,Bachelors,4,22,29,31,2,8.0,0,97,Urban,ML Engineer,121795,0 +61442,Male,25,High School,3,51,7,95,4,1.0,5,25,Urban,HR Executive,123783,0 +61443,Male,41,High School,16,20,82,87,6,6.0,4,6,Semi-Urban,Data Analyst,96934,0 +61444,Female,41,Masters,17,12,6,32,1,5.0,4,68,Semi-Urban,ML Engineer,133051,0 +61445,Other,49,Diploma,6,6,70,83,78,1.0,1,0,Rural,ML Engineer,92975,0 +61446,Female,29,Bachelors,5,52,16,58,3,3.0,7,74,Semi-Urban,Software Engineer,134214,0 +61447,Male,31,High School,2,51,11,38,81,0.0,0,51,Semi-Urban,ML Engineer,37196,0 +61448,Other,56,Bachelors,16,56,32,95,10,1.0,5,23,Urban,HR Executive,135375,0 +61449,Male,51,Bachelors,2,66,0,38,80,6.0,5,30,Semi-Urban,Manager,149815,0 +61450,Male,36,Bachelors,8,79,75,80,91,6.0,7,56,Urban,Data Analyst,104110,1 +61451,Female,36,Masters,7,67,28,51,56,5.0,0,25,Urban,ML Engineer,40020,0 +61452,Male,40,Bachelors,0,76,85,0,35,9.0,4,97,Semi-Urban,Data Analyst,117586,1 +61453,Female,48,Bachelors,9,55,70,22,50,1.0,5,57,Rural,Data Analyst,117969,0 +61454,Male,30,Diploma,11,55,41,3,98,9.0,2,12,Urban,HR Executive,111369,0 +61455,Male,46,Bachelors,1,60,53,68,40,2.0,7,36,Rural,Data Analyst,143550,0 +61456,Male,52,PhD,15,23,83,81,0,1.0,3,89,Rural,Data Analyst,25529,1 +61457,Female,55,Bachelors,7,48,8,57,46,5.0,2,56,Semi-Urban,Manager,26210,0 +61458,Male,27,Masters,15,1,16,47,33,0.0,3,3,Urban,Data Analyst,116516,0 +61459,Male,47,Diploma,2,15,0,30,21,5.0,6,19,Urban,Manager,90427,0 +61460,Female,37,Diploma,8,25,36,61,98,5.0,5,10,Urban,Software Engineer,54516,0 +61461,Male,41,Bachelors,18,97,14,79,43,2.0,1,15,Urban,HR Executive,45284,0 +61462,Male,29,High School,19,63,57,11,34,3.0,5,99,Semi-Urban,Software Engineer,59244,0 +61463,Female,35,Bachelors,0,86,77,73,94,7.0,1,97,Semi-Urban,Software Engineer,96949,1 +61464,Male,49,Bachelors,7,21,16,18,78,2.0,0,13,Rural,Manager,67279,0 +61465,Female,21,Bachelors,19,0,38,89,17,3.0,4,27,Urban,ML Engineer,106573,0 +61466,Male,48,High School,0,33,88,95,83,1.0,2,3,Urban,HR Executive,97258,0 +61467,Male,38,Bachelors,19,19,41,96,36,3.0,7,50,Urban,Software Engineer,147132,0 +61468,Male,50,Bachelors,17,36,53,46,77,0.0,7,79,Semi-Urban,Manager,45340,0 +61469,Male,45,Masters,9,29,54,39,55,5.0,0,51,Urban,HR Executive,148907,0 +61470,Female,28,Diploma,8,37,0,62,62,8.0,5,73,Urban,ML Engineer,138342,0 +61471,Male,32,Bachelors,2,76,59,55,22,8.0,6,91,Rural,Data Analyst,94976,1 +61472,Male,32,Bachelors,12,2,3,36,10,1.0,1,3,Urban,Data Analyst,23411,0 +61473,Male,42,Bachelors,2,60,12,40,44,5.0,7,47,Urban,HR Executive,55099,0 +61474,Male,32,PhD,18,91,16,25,25,4.0,3,97,Urban,Manager,148745,0 +61475,Male,34,PhD,7,47,23,25,70,4.0,1,24,Urban,Data Analyst,124837,0 +61476,Female,54,Bachelors,16,51,54,46,86,4.0,3,89,Semi-Urban,ML Engineer,44062,0 +61477,Male,26,Bachelors,17,75,71,31,50,0.0,3,96,Semi-Urban,Software Engineer,72132,1 +61478,Male,55,Diploma,13,6,68,10,17,9.0,5,43,Semi-Urban,Software Engineer,124758,0 +61479,Female,27,Bachelors,16,67,92,23,98,7.0,4,57,Rural,Manager,74159,0 +61480,Female,35,Masters,16,73,36,55,67,4.0,6,36,Urban,Data Analyst,132176,0 +61481,Male,54,Masters,1,12,30,6,56,0.0,6,23,Rural,Data Analyst,139480,0 +61482,Male,36,Masters,0,70,20,67,76,2.0,0,34,Urban,HR Executive,108231,0 +61483,Female,51,Masters,10,16,3,1,59,6.0,3,17,Urban,ML Engineer,96222,0 +61484,Female,28,High School,19,74,44,47,65,8.0,7,74,Urban,ML Engineer,59095,0 +61485,Male,33,Bachelors,15,52,97,87,29,1.0,7,21,Urban,ML Engineer,93360,1 +61486,Male,37,Diploma,18,57,63,93,87,3.0,1,21,Semi-Urban,Software Engineer,88032,0 +61487,Other,23,Bachelors,2,80,10,52,9,5.0,3,1,Semi-Urban,Data Analyst,144535,0 +61488,Male,23,Masters,6,20,19,60,10,9.0,2,0,Urban,Manager,109199,0 +61489,Female,38,Bachelors,4,37,72,62,99,8.0,3,90,Rural,Software Engineer,76404,1 +61490,Male,40,Bachelors,18,48,11,98,61,0.0,1,5,Semi-Urban,HR Executive,87448,0 +61491,Female,35,Diploma,0,30,99,91,95,2.0,4,77,Urban,Manager,29594,1 +61492,Female,37,Bachelors,13,39,60,8,78,0.0,6,77,Urban,Manager,60500,0 +61493,Male,26,High School,6,44,14,38,21,2.0,5,62,Semi-Urban,Manager,134471,0 +61494,Male,47,Bachelors,8,6,75,42,1,6.0,3,43,Rural,Software Engineer,93167,0 +61495,Male,38,Diploma,6,12,41,95,84,9.0,7,70,Urban,ML Engineer,72573,0 +61496,Female,58,PhD,4,37,40,69,58,9.0,1,45,Rural,ML Engineer,106426,0 +61497,Female,54,High School,19,73,13,6,81,4.0,4,68,Semi-Urban,HR Executive,44921,0 +61498,Male,55,Bachelors,5,98,16,51,16,7.0,6,17,Urban,Data Analyst,121148,0 +61499,Male,59,Masters,13,65,67,43,15,6.0,0,28,Urban,Data Analyst,22762,0 +61500,Male,39,Masters,2,51,92,46,78,3.0,4,70,Semi-Urban,ML Engineer,76350,1 +61501,Male,53,Masters,14,91,67,47,55,5.0,2,0,Semi-Urban,Software Engineer,67946,0 +61502,Male,24,Bachelors,2,92,98,17,68,0.0,0,66,Semi-Urban,ML Engineer,88807,1 +61503,Male,37,High School,1,61,98,50,20,7.0,0,48,Urban,ML Engineer,49370,1 +61504,Male,46,Masters,5,83,57,44,45,7.0,3,83,Urban,Data Analyst,134145,1 +61505,Other,45,Bachelors,13,81,57,73,80,1.0,0,65,Urban,Software Engineer,101014,1 +61506,Male,52,Bachelors,15,80,84,46,96,9.0,1,9,Semi-Urban,Data Analyst,66063,0 +61507,Male,46,Bachelors,6,10,60,80,2,7.0,6,46,Urban,Software Engineer,45719,0 +61508,Female,51,High School,14,42,25,34,92,1.0,1,78,Semi-Urban,Software Engineer,42469,0 +61509,Male,38,Masters,16,22,17,46,68,1.0,4,90,Semi-Urban,Manager,56581,0 +61510,Male,46,Bachelors,8,71,84,12,88,4.0,0,43,Rural,HR Executive,97021,0 +61511,Male,23,Bachelors,7,7,47,97,5,0.0,0,72,Urban,Data Analyst,106762,0 +61512,Male,34,Bachelors,2,4,91,99,98,7.0,4,38,Urban,Manager,101690,0 +61513,Male,57,Diploma,13,33,98,44,10,7.0,2,50,Urban,HR Executive,36527,0 +61514,Male,42,Diploma,1,7,36,65,43,9.0,0,4,Semi-Urban,Data Analyst,142169,0 +61515,Male,25,Bachelors,12,93,58,9,80,9.0,6,43,Urban,ML Engineer,27997,0 +61516,Male,22,PhD,2,34,33,50,35,2.0,3,72,Urban,ML Engineer,30002,0 +61517,Female,40,Bachelors,7,25,56,92,36,4.0,1,86,Urban,Software Engineer,122908,1 +61518,Male,36,Masters,8,31,94,79,89,2.0,0,44,Semi-Urban,Data Analyst,112066,1 +61519,Male,25,Bachelors,0,20,18,13,53,0.0,1,90,Urban,ML Engineer,106862,0 +61520,Male,55,Masters,18,33,90,26,13,7.0,2,77,Semi-Urban,HR Executive,32232,0 +61521,Female,59,Bachelors,6,92,25,68,38,7.0,1,87,Rural,Manager,47569,1 +61522,Female,42,Diploma,15,97,85,80,19,7.0,7,34,Semi-Urban,HR Executive,78850,1 +61523,Male,54,Bachelors,14,87,79,51,88,6.0,4,24,Urban,Manager,101546,1 +61524,Female,47,High School,17,21,19,47,30,3.0,6,64,Urban,Data Analyst,54273,0 +61525,Female,24,Masters,8,23,16,97,83,7.0,4,22,Semi-Urban,Data Analyst,98608,0 +61526,Male,26,Bachelors,8,40,74,15,45,6.0,6,36,Urban,ML Engineer,93568,0 +61527,Male,49,Masters,15,13,33,97,59,3.0,2,38,Semi-Urban,Data Analyst,37256,0 +61528,Male,42,Bachelors,16,50,37,84,31,5.0,4,89,Semi-Urban,Software Engineer,38180,1 +61529,Female,56,Diploma,2,72,7,55,12,4.0,5,11,Urban,ML Engineer,89291,0 +61530,Female,26,High School,16,67,28,90,97,8.0,0,3,Urban,ML Engineer,51211,0 +61531,Female,26,Diploma,13,63,74,80,77,1.0,0,52,Urban,Data Analyst,132766,1 +61532,Male,49,Bachelors,12,76,26,33,20,5.0,0,28,Urban,Data Analyst,87578,0 +61533,Male,33,Bachelors,19,48,93,14,26,1.0,4,22,Urban,ML Engineer,120291,0 +61534,Other,30,High School,4,21,2,50,13,7.0,0,13,Rural,Data Analyst,42034,0 +61535,Female,28,Diploma,6,3,42,91,31,3.0,0,86,Urban,HR Executive,63345,0 +61536,Male,31,Bachelors,1,3,32,79,42,4.0,4,32,Urban,Manager,113703,0 +61537,Female,37,Diploma,18,99,5,7,13,7.0,6,26,Urban,Software Engineer,93899,0 +61538,Male,33,Masters,19,94,70,94,68,6.0,7,19,Rural,Data Analyst,78247,1 +61539,Male,39,High School,11,90,87,90,5,9.0,4,54,Semi-Urban,Data Analyst,103715,1 +61540,Female,45,Diploma,15,83,62,8,2,9.0,5,74,Rural,Software Engineer,113984,0 +61541,Male,22,Bachelors,17,8,58,79,38,5.0,1,50,Semi-Urban,Software Engineer,76753,0 +61542,Male,21,Masters,2,39,96,51,67,3.0,0,4,Urban,Software Engineer,77312,0 +61543,Male,53,High School,11,82,99,18,24,7.0,4,85,Urban,ML Engineer,141405,1 +61544,Male,59,Bachelors,4,22,99,85,28,9.0,5,93,Rural,HR Executive,88318,1 +61545,Male,50,Diploma,9,91,64,45,30,8.0,1,0,Semi-Urban,ML Engineer,92982,0 +61546,Male,42,PhD,10,27,52,69,25,9.0,4,79,Urban,Manager,108774,0 +61547,Male,53,Bachelors,12,36,10,23,48,3.0,6,85,Urban,Manager,67004,0 +61548,Male,59,Bachelors,18,97,88,21,27,7.0,2,78,Rural,Data Analyst,116261,1 +61549,Male,27,Bachelors,6,20,55,63,86,4.0,6,81,Urban,Software Engineer,58209,0 +61550,Female,25,Diploma,17,76,48,53,10,5.0,4,10,Urban,Manager,59270,0 +61551,Male,57,Bachelors,2,89,70,93,69,4.0,2,32,Semi-Urban,Software Engineer,52105,1 +61552,Male,38,Bachelors,10,87,36,23,91,9.0,1,46,Urban,Software Engineer,114321,0 +61553,Other,24,Bachelors,12,87,58,61,91,6.0,2,15,Urban,HR Executive,125190,0 +61554,Male,51,Bachelors,17,95,3,58,87,0.0,2,10,Urban,HR Executive,59222,0 +61555,Female,55,PhD,5,27,52,57,26,8.0,5,99,Urban,Software Engineer,95136,0 +61556,Male,56,Diploma,14,31,16,22,61,9.0,4,46,Semi-Urban,Data Analyst,75775,0 +61557,Female,38,Masters,15,20,92,74,7,2.0,6,30,Rural,ML Engineer,82836,0 +61558,Male,37,Masters,19,8,53,22,72,0.0,5,59,Urban,Software Engineer,42620,0 +61559,Other,35,High School,17,43,70,29,91,3.0,4,2,Urban,Data Analyst,119983,0 +61560,Male,23,Masters,5,63,52,76,50,8.0,4,15,Urban,Software Engineer,143686,0 +61561,Female,46,Masters,14,48,31,73,59,7.0,7,1,Urban,Software Engineer,47687,0 +61562,Female,49,Bachelors,10,82,15,97,97,0.0,5,67,Urban,Data Analyst,140553,1 +61563,Female,48,Bachelors,6,49,43,6,57,8.0,4,73,Urban,ML Engineer,147649,0 +61564,Male,38,Masters,7,72,23,51,83,7.0,5,65,Rural,Data Analyst,20855,0 +61565,Male,40,Bachelors,14,57,54,48,51,3.0,3,71,Urban,ML Engineer,85545,0 +61566,Male,44,Diploma,4,10,31,85,52,2.0,1,21,Urban,Software Engineer,86074,0 +61567,Male,49,Masters,17,13,5,5,74,6.0,0,85,Urban,Data Analyst,22607,0 +61568,Female,35,Masters,3,27,25,15,84,3.0,5,35,Urban,ML Engineer,43805,0 +61569,Male,47,Bachelors,19,37,32,72,6,7.0,5,46,Urban,Manager,117928,0 +61570,Female,24,High School,2,27,70,27,40,0.0,3,60,Rural,HR Executive,70909,0 +61571,Male,45,Bachelors,10,67,59,20,77,6.0,7,22,Urban,Manager,118048,0 +61572,Male,46,Masters,15,78,53,23,5,1.0,6,26,Urban,Software Engineer,80426,0 +61573,Male,40,Bachelors,17,7,70,54,14,7.0,7,78,Urban,Manager,51198,0 +61574,Male,41,Masters,9,82,60,36,50,3.0,3,19,Urban,HR Executive,147098,0 +61575,Male,34,Bachelors,4,67,70,35,14,4.0,1,9,Urban,Data Analyst,139563,0 +61576,Male,36,Bachelors,15,79,88,31,19,1.0,4,63,Urban,ML Engineer,43311,1 +61577,Male,25,Bachelors,5,14,18,60,66,0.0,3,32,Urban,Data Analyst,132597,0 +61578,Other,32,Diploma,16,37,43,6,66,9.0,5,79,Urban,Software Engineer,61964,0 +61579,Male,35,High School,10,99,23,97,96,5.0,6,43,Rural,ML Engineer,71449,1 +61580,Female,24,High School,11,28,31,16,98,0.0,5,36,Urban,Software Engineer,68960,0 +61581,Female,49,Masters,0,62,94,96,18,5.0,4,33,Urban,Manager,24187,1 +61582,Male,39,Bachelors,10,92,73,60,59,1.0,2,63,Urban,Data Analyst,45019,1 +61583,Female,30,High School,5,62,50,28,80,8.0,4,85,Urban,Manager,67978,0 +61584,Female,35,Bachelors,12,43,83,65,64,0.0,3,24,Semi-Urban,Data Analyst,82754,0 +61585,Male,21,Bachelors,4,98,51,14,86,0.0,7,82,Urban,ML Engineer,36536,1 +61586,Male,48,Diploma,1,17,92,76,2,3.0,6,31,Urban,Software Engineer,105072,0 +61587,Female,47,Masters,5,99,47,36,14,9.0,4,63,Semi-Urban,ML Engineer,118631,1 +61588,Male,56,Bachelors,10,94,72,98,34,6.0,5,64,Urban,Data Analyst,46725,1 +61589,Female,59,Bachelors,0,50,62,96,37,2.0,5,54,Rural,Data Analyst,77649,1 +61590,Male,27,Diploma,13,18,93,43,83,4.0,5,56,Urban,ML Engineer,74733,0 +61591,Male,36,Diploma,14,72,19,69,23,5.0,1,49,Urban,Software Engineer,70308,0 +61592,Male,41,Bachelors,1,47,20,93,41,4.0,4,10,Rural,Data Analyst,91254,0 +61593,Male,42,Bachelors,5,81,85,2,44,8.0,5,96,Semi-Urban,HR Executive,27879,1 +61594,Female,45,Masters,16,30,76,27,96,5.0,1,37,Rural,Data Analyst,145075,0 +61595,Male,55,Diploma,1,51,3,72,7,6.0,5,28,Urban,Data Analyst,76189,0 +61596,Male,21,Bachelors,10,26,84,50,17,5.0,6,19,Urban,Software Engineer,139402,0 +61597,Male,50,PhD,12,23,9,92,92,2.0,6,82,Rural,Manager,131722,0 +61598,Male,42,Masters,4,14,98,17,45,9.0,1,43,Urban,Data Analyst,38666,0 +61599,Female,55,Bachelors,18,27,15,45,61,2.0,1,95,Urban,Data Analyst,44061,0 +61600,Male,25,Bachelors,14,77,55,99,70,6.0,4,76,Urban,Manager,137917,1 +61601,Female,32,PhD,12,51,57,99,65,1.0,0,32,Urban,ML Engineer,70650,0 +61602,Male,58,Bachelors,8,32,35,45,97,3.0,4,20,Semi-Urban,ML Engineer,51851,0 +61603,Male,23,Diploma,16,25,2,86,92,4.0,0,77,Rural,Manager,71422,0 +61604,Other,32,High School,18,22,85,93,79,0.0,0,40,Semi-Urban,HR Executive,25427,0 +61605,Male,56,Bachelors,10,41,45,59,96,9.0,7,28,Semi-Urban,Data Analyst,102684,0 +61606,Male,52,Bachelors,7,83,81,44,8,5.0,5,12,Urban,Manager,29121,0 +61607,Male,54,Bachelors,13,36,11,34,54,3.0,6,41,Rural,Software Engineer,142829,0 +61608,Male,40,Diploma,5,18,98,67,30,6.0,0,33,Urban,Manager,139542,0 +61609,Male,42,Bachelors,1,59,76,64,17,9.0,4,49,Urban,ML Engineer,108709,1 +61610,Male,50,Bachelors,14,13,19,52,69,0.0,6,32,Urban,Software Engineer,136054,0 +61611,Female,35,Masters,18,80,80,41,88,1.0,0,22,Semi-Urban,Software Engineer,23293,0 +61612,Female,27,Diploma,11,50,79,77,20,0.0,6,57,Semi-Urban,ML Engineer,123204,1 +61613,Male,36,Bachelors,0,19,22,98,65,3.0,0,92,Semi-Urban,Manager,48860,0 +61614,Male,36,Bachelors,17,5,45,8,46,7.0,5,1,Urban,HR Executive,140090,0 +61615,Female,48,Diploma,2,78,50,28,63,7.0,1,75,Urban,Manager,97867,0 +61616,Male,22,Diploma,7,71,4,36,24,7.0,4,2,Urban,Data Analyst,108070,0 +61617,Male,46,High School,14,98,20,48,74,7.0,3,16,Urban,ML Engineer,139287,0 +61618,Male,47,Masters,17,22,42,9,66,1.0,6,6,Urban,Manager,57697,0 +61619,Male,41,Bachelors,17,21,18,48,62,5.0,0,49,Urban,HR Executive,74149,0 +61620,Male,53,Masters,6,71,24,22,52,8.0,2,66,Rural,Manager,38526,0 +61621,Female,21,PhD,14,29,88,3,43,8.0,4,32,Semi-Urban,Manager,47093,0 +61622,Male,51,Masters,4,17,79,8,79,0.0,6,95,Urban,Software Engineer,73383,0 +61623,Other,32,Diploma,8,69,58,19,2,5.0,1,94,Urban,Software Engineer,79821,0 +61624,Male,38,Bachelors,11,58,15,4,24,4.0,7,43,Semi-Urban,Manager,81334,0 +61625,Female,39,PhD,18,5,65,35,13,6.0,6,74,Rural,Manager,135780,0 +61626,Male,42,Diploma,12,78,84,92,65,4.0,7,34,Urban,Software Engineer,25656,1 +61627,Female,31,Diploma,1,7,84,15,26,2.0,0,19,Rural,ML Engineer,94114,0 +61628,Female,25,Diploma,8,80,86,72,80,6.0,6,35,Semi-Urban,HR Executive,27798,1 +61629,Male,26,Masters,12,82,98,51,36,5.0,1,26,Urban,HR Executive,124702,1 +61630,Male,44,Bachelors,15,37,80,55,20,9.0,2,76,Semi-Urban,ML Engineer,128638,1 +61631,Male,37,Diploma,18,82,72,66,39,5.0,4,62,Rural,Manager,107891,1 +61632,Female,31,Masters,15,92,58,57,23,7.0,4,72,Rural,Software Engineer,84606,1 +61633,Female,53,Diploma,18,89,64,73,0,8.0,7,68,Urban,HR Executive,37989,1 +61634,Male,41,Bachelors,9,40,21,96,64,3.0,3,11,Semi-Urban,Data Analyst,136617,0 +61635,Male,40,Bachelors,9,89,19,33,51,2.0,7,81,Urban,ML Engineer,73074,0 +61636,Male,23,Bachelors,0,32,5,34,25,8.0,3,64,Urban,Data Analyst,125032,0 +61637,Male,57,Bachelors,3,19,42,71,6,5.0,2,54,Urban,Software Engineer,33832,0 +61638,Male,48,Diploma,8,2,57,91,70,1.0,2,92,Urban,HR Executive,146879,1 +61639,Male,54,High School,17,56,52,63,5,3.0,6,92,Urban,Manager,108253,1 +61640,Male,33,Diploma,19,18,97,87,88,5.0,6,87,Rural,Data Analyst,56769,1 +61641,Female,22,High School,10,96,96,35,8,2.0,4,51,Rural,Software Engineer,63071,1 +61642,Male,25,Masters,8,35,36,19,96,6.0,5,32,Semi-Urban,HR Executive,111837,0 +61643,Male,52,Bachelors,7,78,73,33,15,2.0,6,93,Urban,HR Executive,139648,1 +61644,Male,24,Bachelors,16,49,66,86,33,7.0,4,61,Urban,Software Engineer,122762,1 +61645,Other,42,Masters,18,28,11,5,73,4.0,4,74,Rural,Software Engineer,115758,0 +61646,Female,38,Diploma,5,79,75,72,2,0.0,3,60,Urban,Data Analyst,121149,1 +61647,Male,46,Masters,8,86,77,77,5,7.0,0,80,Urban,ML Engineer,60217,1 +61648,Female,47,Diploma,10,99,68,64,92,2.0,7,47,Urban,HR Executive,91035,1 +61649,Female,29,Diploma,2,37,60,79,36,5.0,4,42,Urban,HR Executive,103004,0 +61650,Other,46,Bachelors,10,42,92,92,18,1.0,7,28,Urban,ML Engineer,108986,1 +61651,Female,28,Bachelors,6,85,59,53,84,1.0,3,7,Urban,Data Analyst,141724,0 +61652,Male,21,Bachelors,11,41,67,7,2,5.0,5,27,Semi-Urban,Manager,90881,0 +61653,Male,50,Diploma,0,32,73,73,57,7.0,1,59,Urban,Data Analyst,143122,1 +61654,Female,21,Diploma,3,10,76,1,52,1.0,5,59,Rural,HR Executive,140938,0 +61655,Other,58,Bachelors,6,48,44,12,64,9.0,6,57,Rural,Software Engineer,106110,0 +61656,Male,34,Bachelors,18,96,66,74,4,2.0,6,53,Semi-Urban,ML Engineer,104119,1 +61657,Male,56,Masters,0,38,97,79,76,1.0,3,43,Semi-Urban,Data Analyst,50713,1 +61658,Male,37,High School,11,24,28,79,3,8.0,3,24,Semi-Urban,Data Analyst,79977,0 +61659,Male,31,High School,1,50,7,75,89,5.0,4,35,Semi-Urban,HR Executive,78173,0 +61660,Male,38,Diploma,13,39,93,32,98,2.0,1,45,Urban,Manager,149976,0 +61661,Male,56,High School,19,92,26,94,71,2.0,1,87,Urban,Software Engineer,139181,1 +61662,Other,48,Bachelors,15,70,39,96,13,7.0,3,53,Rural,HR Executive,29098,1 +61663,Female,35,Masters,4,3,37,63,64,0.0,2,35,Rural,Manager,105108,0 +61664,Female,25,Bachelors,6,46,45,26,75,1.0,0,82,Urban,Data Analyst,52367,0 +61665,Male,35,Bachelors,4,70,14,33,46,8.0,5,45,Semi-Urban,HR Executive,55796,0 +61666,Female,43,Bachelors,3,95,90,36,49,3.0,2,33,Rural,Software Engineer,118083,1 +61667,Male,44,PhD,18,5,29,55,17,9.0,3,43,Rural,Manager,127715,0 +61668,Male,27,Diploma,0,48,88,64,5,8.0,5,70,Rural,Software Engineer,45227,1 +61669,Other,46,Bachelors,14,40,66,59,12,6.0,0,89,Urban,Software Engineer,108930,1 +61670,Male,22,High School,8,18,81,90,4,3.0,5,67,Rural,Manager,38760,1 +61671,Male,33,Bachelors,17,68,39,80,65,9.0,5,74,Rural,ML Engineer,148900,1 +61672,Female,46,Bachelors,15,47,9,41,99,5.0,5,41,Semi-Urban,HR Executive,40579,0 +61673,Other,42,Bachelors,2,92,37,7,78,4.0,4,43,Urban,ML Engineer,149455,0 +61674,Female,36,High School,3,47,66,99,44,5.0,1,39,Rural,Manager,61291,1 +61675,Male,37,Bachelors,17,44,61,44,54,5.0,4,5,Semi-Urban,ML Engineer,139244,0 +61676,Male,29,Masters,10,34,9,68,7,5.0,7,14,Semi-Urban,Data Analyst,64232,0 +61677,Male,23,High School,19,90,92,89,98,6.0,7,65,Semi-Urban,Software Engineer,26045,1 +61678,Male,42,Bachelors,2,50,31,63,50,7.0,3,14,Urban,Manager,83327,0 +61679,Other,50,Masters,4,25,73,42,6,6.0,2,0,Urban,ML Engineer,59452,0 +61680,Other,29,Bachelors,5,77,62,45,25,8.0,0,50,Semi-Urban,Manager,53379,0 +61681,Female,30,Bachelors,12,24,62,0,93,7.0,3,64,Urban,Data Analyst,33287,0 +61682,Male,39,Bachelors,19,88,80,69,93,0.0,5,96,Urban,Software Engineer,114099,1 +61683,Female,36,Bachelors,10,61,68,35,42,8.0,2,86,Semi-Urban,Software Engineer,34632,1 +61684,Female,46,PhD,4,76,9,57,18,9.0,7,37,Urban,Data Analyst,24423,0 +61685,Male,32,Diploma,13,60,94,61,59,0.0,5,73,Rural,Data Analyst,73088,1 +61686,Male,27,PhD,14,86,67,57,99,1.0,5,75,Urban,Data Analyst,137140,1 +61687,Female,38,Bachelors,18,54,52,62,99,0.0,7,69,Rural,ML Engineer,108003,0 +61688,Male,55,High School,9,69,37,52,31,2.0,6,55,Urban,ML Engineer,118452,0 +61689,Female,31,Diploma,0,2,79,77,42,5.0,2,87,Urban,Data Analyst,31703,1 +61690,Male,39,Masters,15,11,92,52,4,9.0,7,38,Rural,ML Engineer,38963,0 +61691,Male,50,Bachelors,17,58,83,84,35,8.0,4,24,Semi-Urban,Data Analyst,115373,1 +61692,Other,35,Bachelors,12,48,46,14,92,3.0,7,81,Urban,Software Engineer,100933,0 +61693,Other,29,High School,2,6,96,95,54,2.0,4,98,Urban,Data Analyst,88951,1 +61694,Female,29,Diploma,17,40,8,78,13,2.0,3,52,Urban,Software Engineer,129143,0 +61695,Female,37,Bachelors,6,12,92,89,7,8.0,6,98,Semi-Urban,HR Executive,57550,1 +61696,Other,38,Bachelors,3,94,75,16,28,0.0,5,49,Rural,Data Analyst,103286,0 +61697,Female,58,Masters,19,76,33,21,25,4.0,6,25,Semi-Urban,Manager,69531,0 +61698,Female,33,Diploma,0,98,30,59,11,6.0,3,50,Urban,Software Engineer,57590,0 +61699,Female,36,Bachelors,19,4,88,47,35,4.0,1,60,Rural,Manager,130662,0 +61700,Male,42,Masters,7,51,31,16,92,0.0,3,42,Urban,HR Executive,28418,0 +61701,Male,58,High School,17,94,81,76,67,7.0,7,85,Urban,HR Executive,106698,1 +61702,Female,46,Masters,4,79,27,64,15,3.0,6,78,Urban,HR Executive,67840,1 +61703,Female,40,High School,3,24,41,94,9,6.0,5,82,Semi-Urban,Software Engineer,111611,1 +61704,Female,50,Bachelors,16,54,76,55,13,6.0,5,84,Urban,Software Engineer,66368,1 +61705,Male,50,Bachelors,9,17,73,23,44,5.0,3,9,Rural,Manager,108828,0 +61706,Male,44,High School,16,74,98,29,61,6.0,0,88,Urban,HR Executive,111609,1 +61707,Male,30,Bachelors,15,5,50,5,69,9.0,0,2,Urban,Manager,59846,0 +61708,Male,38,Diploma,15,47,7,21,49,4.0,5,82,Rural,Manager,116442,0 +61709,Female,38,Bachelors,11,44,27,25,97,8.0,2,65,Urban,Software Engineer,55241,0 +61710,Female,39,High School,4,24,75,90,94,7.0,6,83,Urban,Manager,55769,1 +61711,Male,58,Masters,6,5,84,73,51,8.0,4,29,Rural,Data Analyst,122663,0 +61712,Male,52,High School,16,90,84,48,53,9.0,2,21,Urban,Manager,122956,1 +61713,Female,30,Diploma,16,12,76,92,34,8.0,2,12,Urban,HR Executive,24211,0 +61714,Other,43,High School,5,62,27,31,40,3.0,0,75,Rural,HR Executive,142776,0 +61715,Male,31,Diploma,15,33,56,65,51,1.0,4,55,Semi-Urban,ML Engineer,69143,0 +61716,Male,46,High School,11,56,53,78,56,6.0,2,30,Rural,Manager,89390,0 +61717,Male,45,Diploma,14,37,75,3,2,4.0,0,98,Semi-Urban,ML Engineer,140480,0 +61718,Female,31,Masters,13,86,85,2,99,8.0,6,19,Urban,Data Analyst,75534,0 +61719,Female,23,Bachelors,19,96,43,57,51,4.0,7,97,Semi-Urban,ML Engineer,137069,1 +61720,Male,34,Diploma,18,75,37,43,99,6.0,5,52,Urban,Manager,99479,0 +61721,Female,39,Diploma,14,48,33,23,20,8.0,6,71,Urban,ML Engineer,106643,0 +61722,Male,23,High School,0,27,77,78,41,5.0,0,70,Urban,Manager,145787,1 +61723,Male,29,Bachelors,15,63,67,51,82,0.0,3,19,Urban,Data Analyst,85520,0 +61724,Female,25,PhD,11,2,54,66,63,1.0,7,23,Urban,Manager,54382,0 +61725,Female,54,Diploma,7,33,66,24,10,0.0,2,35,Semi-Urban,HR Executive,28934,0 +61726,Female,26,High School,11,57,50,63,79,2.0,1,30,Urban,Manager,49122,0 +61727,Other,29,Bachelors,6,26,31,15,46,4.0,3,10,Urban,HR Executive,46395,0 +61728,Female,59,Diploma,10,77,51,3,98,9.0,6,69,Urban,Software Engineer,31149,0 +61729,Male,51,Diploma,3,73,78,35,36,2.0,1,59,Urban,HR Executive,83312,1 +61730,Male,31,Diploma,16,9,42,87,58,7.0,1,77,Semi-Urban,Data Analyst,80952,0 +61731,Female,53,Bachelors,1,47,3,46,38,5.0,2,86,Rural,Manager,39337,0 +61732,Male,29,Bachelors,1,31,43,40,96,4.0,3,45,Urban,ML Engineer,35988,0 +61733,Male,49,Bachelors,11,15,20,84,74,1.0,3,51,Urban,Manager,109436,0 +61734,Male,52,Bachelors,12,65,39,84,0,0.0,0,1,Rural,ML Engineer,105995,0 +61735,Other,26,High School,2,49,50,92,50,8.0,6,7,Urban,Manager,41063,0 +61736,Male,46,Bachelors,17,10,53,60,87,4.0,3,91,Semi-Urban,HR Executive,148070,0 +61737,Male,24,Masters,15,71,24,53,1,3.0,1,8,Urban,Manager,86548,0 +61738,Female,58,Diploma,19,7,33,17,77,8.0,7,50,Rural,Software Engineer,36573,0 +61739,Female,48,High School,10,71,98,77,64,5.0,4,13,Rural,HR Executive,138790,1 +61740,Male,59,Masters,16,39,18,32,47,8.0,6,19,Urban,Manager,85967,0 +61741,Female,34,High School,18,71,97,1,67,3.0,5,47,Semi-Urban,ML Engineer,68588,0 +61742,Male,51,Bachelors,19,11,16,19,11,4.0,0,24,Rural,Software Engineer,63145,0 +61743,Female,41,Masters,12,19,74,47,73,8.0,3,14,Semi-Urban,Data Analyst,111496,0 +61744,Female,48,High School,13,91,1,44,57,1.0,2,69,Rural,Manager,54982,0 +61745,Male,24,High School,19,88,6,21,3,9.0,3,11,Semi-Urban,Software Engineer,119991,0 +61746,Female,44,High School,18,31,70,99,94,0.0,1,36,Semi-Urban,Manager,105466,0 +61747,Male,22,Diploma,19,2,16,26,83,3.0,3,1,Rural,Data Analyst,62653,0 +61748,Female,37,Masters,17,57,89,51,57,9.0,0,70,Rural,Manager,67278,1 +61749,Female,43,Bachelors,12,51,66,91,49,7.0,6,27,Rural,Data Analyst,66686,0 +61750,Male,48,Bachelors,7,45,88,82,26,5.0,1,84,Urban,HR Executive,31686,1 +61751,Male,30,High School,16,49,67,86,99,4.0,3,73,Urban,Manager,109101,1 +61752,Other,41,Bachelors,11,91,31,52,44,8.0,1,47,Urban,Manager,126321,0 +61753,Male,58,Bachelors,13,42,85,81,37,4.0,5,99,Urban,Software Engineer,58815,1 +61754,Male,36,High School,3,60,30,35,20,5.0,1,81,Urban,Manager,142102,0 +61755,Male,31,Diploma,10,7,21,10,31,8.0,3,35,Semi-Urban,Data Analyst,147807,0 +61756,Male,30,Bachelors,12,8,73,33,57,3.0,5,79,Semi-Urban,Manager,107506,0 +61757,Male,41,Bachelors,12,72,4,24,77,7.0,3,37,Semi-Urban,HR Executive,119593,0 +61758,Male,43,Bachelors,9,2,52,76,20,2.0,2,31,Semi-Urban,ML Engineer,114908,0 +61759,Male,21,Masters,16,11,79,8,59,1.0,2,41,Semi-Urban,HR Executive,93938,0 +61760,Female,36,Masters,14,44,70,31,94,1.0,1,80,Semi-Urban,ML Engineer,110787,0 +61761,Male,48,Bachelors,2,47,72,25,73,9.0,7,24,Urban,Manager,88967,0 +61762,Male,47,Bachelors,15,0,55,87,96,8.0,2,81,Urban,Manager,122383,0 +61763,Female,51,Masters,9,44,59,60,65,8.0,2,47,Semi-Urban,Manager,45197,0 +61764,Male,39,Masters,9,6,31,76,67,6.0,5,10,Rural,ML Engineer,78203,0 +61765,Female,56,Masters,6,31,8,11,18,8.0,6,53,Urban,Software Engineer,56068,0 +61766,Male,44,Bachelors,13,73,33,64,57,8.0,6,3,Rural,Data Analyst,29348,0 +61767,Other,33,Masters,12,60,84,40,87,7.0,1,93,Urban,Software Engineer,70030,1 +61768,Other,21,Bachelors,0,4,24,44,23,4.0,1,2,Rural,ML Engineer,96601,0 +61769,Female,32,Bachelors,0,26,2,97,84,1.0,2,0,Urban,Manager,137809,0 +61770,Male,39,Bachelors,16,25,84,79,66,0.0,3,34,Semi-Urban,Software Engineer,38640,0 +61771,Female,30,Bachelors,5,91,56,12,32,9.0,1,69,Rural,Manager,46696,0 +61772,Other,24,Bachelors,18,17,33,8,75,0.0,4,21,Semi-Urban,HR Executive,119258,0 +61773,Male,56,Bachelors,16,51,24,48,12,6.0,3,6,Urban,ML Engineer,49610,0 +61774,Female,29,Diploma,11,74,16,8,86,4.0,3,41,Urban,Data Analyst,138090,0 +61775,Male,24,Bachelors,5,86,72,54,96,5.0,4,20,Semi-Urban,Manager,130678,0 +61776,Male,32,Bachelors,19,21,12,88,9,2.0,0,99,Semi-Urban,ML Engineer,25080,0 +61777,Male,41,Bachelors,8,12,68,40,42,6.0,1,31,Semi-Urban,Software Engineer,89838,0 +61778,Female,59,Diploma,12,94,97,97,37,0.0,4,66,Urban,Software Engineer,115211,1 +61779,Male,39,Masters,11,74,87,63,68,5.0,5,44,Urban,HR Executive,68225,1 +61780,Male,33,Diploma,3,77,7,30,27,3.0,1,12,Rural,Manager,41652,0 +61781,Female,53,Diploma,4,42,34,40,52,4.0,1,68,Urban,HR Executive,142409,0 +61782,Male,25,High School,8,74,28,43,3,7.0,4,63,Urban,HR Executive,149568,0 +61783,Female,29,High School,13,82,5,17,96,1.0,1,61,Urban,ML Engineer,146906,0 +61784,Female,28,Bachelors,11,42,78,31,2,1.0,4,22,Urban,Data Analyst,36828,0 +61785,Male,23,Bachelors,17,85,99,47,39,4.0,7,4,Urban,ML Engineer,88584,1 +61786,Male,56,Masters,1,62,59,6,63,5.0,1,95,Urban,Software Engineer,107244,0 +61787,Female,36,Masters,17,24,84,37,61,5.0,0,63,Urban,Data Analyst,147154,0 +61788,Male,25,Bachelors,18,40,43,27,14,6.0,0,33,Urban,HR Executive,93357,0 +61789,Female,44,Diploma,0,53,88,18,39,4.0,0,87,Rural,Data Analyst,37264,1 +61790,Male,28,Diploma,16,68,99,99,80,7.0,7,96,Rural,ML Engineer,102318,1 +61791,Male,49,Bachelors,19,62,5,92,30,6.0,5,73,Semi-Urban,Software Engineer,117396,0 +61792,Male,55,Bachelors,2,37,74,34,93,3.0,3,89,Urban,ML Engineer,91385,0 +61793,Female,39,Bachelors,10,17,37,45,86,5.0,5,75,Urban,Software Engineer,112427,0 +61794,Female,54,Diploma,15,30,40,92,4,0.0,5,43,Semi-Urban,HR Executive,140405,0 +61795,Male,38,High School,9,41,11,53,85,8.0,2,46,Rural,ML Engineer,82808,0 +61796,Male,59,Bachelors,14,44,81,57,8,3.0,4,60,Rural,HR Executive,65349,1 +61797,Male,42,Diploma,3,51,15,29,49,4.0,1,69,Urban,Data Analyst,96533,0 +61798,Female,31,Bachelors,16,80,84,51,18,1.0,3,62,Urban,Software Engineer,40214,1 +61799,Male,28,High School,4,1,62,86,10,1.0,0,40,Semi-Urban,Manager,58736,0 +61800,Female,21,Masters,8,74,67,36,10,6.0,2,7,Semi-Urban,Manager,128237,0 +61801,Female,21,Masters,16,82,18,63,78,7.0,7,94,Semi-Urban,HR Executive,141314,1 +61802,Other,36,High School,6,61,32,71,82,3.0,6,57,Semi-Urban,Manager,81581,0 +61803,Female,31,Masters,2,77,99,34,35,6.0,5,11,Urban,Software Engineer,43496,0 +61804,Male,33,Diploma,9,11,71,47,55,0.0,2,75,Urban,HR Executive,28852,0 +61805,Male,31,Bachelors,9,43,22,87,20,5.0,2,54,Urban,Software Engineer,66143,0 +61806,Male,31,PhD,4,77,15,1,55,9.0,3,21,Urban,Data Analyst,45034,0 +61807,Male,28,Masters,15,90,38,44,81,3.0,5,52,Urban,ML Engineer,144851,0 +61808,Male,38,PhD,2,18,89,76,27,7.0,7,14,Rural,ML Engineer,95001,0 +61809,Female,57,Masters,16,4,49,71,37,5.0,3,19,Urban,ML Engineer,98403,0 +61810,Male,37,High School,16,42,85,18,67,2.0,7,81,Urban,Manager,33390,0 +61811,Female,22,Masters,10,24,9,12,38,5.0,4,5,Semi-Urban,HR Executive,61290,0 +61812,Male,53,Bachelors,4,67,44,96,34,8.0,4,78,Urban,Data Analyst,73654,1 +61813,Female,21,Bachelors,10,44,80,4,94,5.0,3,84,Urban,ML Engineer,70445,0 +61814,Male,53,Bachelors,17,71,99,1,43,7.0,7,57,Rural,ML Engineer,40387,0 +61815,Female,59,Bachelors,2,43,18,67,81,3.0,0,78,Semi-Urban,Software Engineer,74146,0 +61816,Female,58,Masters,0,99,67,65,92,8.0,1,70,Urban,ML Engineer,73134,1 +61817,Male,39,High School,1,88,61,85,95,4.0,6,83,Urban,Manager,33324,1 +61818,Male,48,Diploma,12,72,97,95,52,2.0,7,26,Semi-Urban,ML Engineer,80315,1 +61819,Male,38,Masters,14,14,16,39,20,8.0,0,85,Urban,Software Engineer,110661,0 +61820,Female,57,Masters,2,94,0,70,8,6.0,0,39,Urban,HR Executive,25416,0 +61821,Male,51,Diploma,13,1,40,40,82,9.0,0,92,Urban,Manager,97392,0 +61822,Female,41,Masters,19,29,52,42,66,7.0,7,3,Urban,Data Analyst,113974,0 +61823,Female,36,Diploma,2,67,56,17,72,0.0,6,20,Semi-Urban,HR Executive,141401,0 +61824,Female,27,Bachelors,0,89,43,84,22,5.0,6,33,Urban,Manager,97146,1 +61825,Female,28,Diploma,19,79,0,74,97,7.0,2,34,Urban,Data Analyst,47499,0 +61826,Female,58,Bachelors,18,23,79,7,92,5.0,2,70,Rural,ML Engineer,29107,0 +61827,Female,59,Masters,18,13,63,16,68,1.0,7,9,Urban,Manager,79472,0 +61828,Male,31,Bachelors,6,61,19,64,64,4.0,2,87,Semi-Urban,Software Engineer,37548,0 +61829,Male,44,Diploma,2,64,2,93,90,9.0,4,43,Semi-Urban,Software Engineer,38396,0 +61830,Male,38,High School,6,7,7,23,5,9.0,6,81,Rural,HR Executive,137662,0 +61831,Other,51,Bachelors,19,77,75,41,84,7.0,4,12,Urban,HR Executive,104526,0 +61832,Female,42,Masters,11,89,37,46,70,2.0,3,78,Urban,ML Engineer,52531,1 +61833,Male,42,Bachelors,17,24,19,76,31,1.0,7,91,Semi-Urban,Software Engineer,46801,0 +61834,Male,41,Bachelors,19,88,44,68,85,1.0,7,34,Urban,Data Analyst,75820,0 +61835,Male,41,PhD,10,2,11,76,73,4.0,4,72,Urban,Manager,47619,0 +61836,Male,40,Bachelors,1,66,17,88,66,1.0,0,27,Urban,HR Executive,86743,0 +61837,Male,50,Masters,0,42,89,66,19,8.0,1,90,Urban,HR Executive,48561,1 +61838,Male,39,Diploma,15,45,37,6,52,0.0,6,32,Semi-Urban,HR Executive,90008,0 +61839,Male,55,Bachelors,7,32,36,35,35,1.0,1,8,Urban,Software Engineer,29417,0 +61840,Female,53,Diploma,10,83,53,14,56,1.0,6,11,Urban,HR Executive,78704,0 +61841,Female,28,Diploma,13,95,61,91,33,5.0,4,75,Semi-Urban,ML Engineer,129521,1 +61842,Female,51,Bachelors,8,12,15,44,55,7.0,1,39,Urban,Software Engineer,84292,0 +61843,Male,38,Bachelors,17,92,71,41,69,2.0,5,90,Urban,HR Executive,90024,1 +61844,Male,27,Bachelors,11,98,56,52,23,8.0,7,3,Urban,Data Analyst,133745,0 +61845,Male,39,High School,6,2,76,74,14,8.0,7,21,Semi-Urban,Data Analyst,79593,0 +61846,Male,41,Masters,16,73,36,22,25,9.0,2,89,Semi-Urban,Software Engineer,122841,0 +61847,Male,31,High School,13,68,43,98,93,2.0,6,52,Rural,HR Executive,136630,1 +61848,Male,44,Bachelors,18,68,9,1,46,5.0,6,97,Urban,ML Engineer,133441,0 +61849,Male,59,High School,18,3,16,15,2,3.0,3,6,Rural,Software Engineer,59805,0 +61850,Male,58,Diploma,6,81,77,66,11,5.0,3,29,Rural,Software Engineer,136038,1 +61851,Male,35,Masters,7,6,33,7,50,6.0,2,83,Urban,Software Engineer,137688,0 +61852,Male,50,High School,15,54,57,74,33,1.0,2,17,Urban,Software Engineer,139737,0 +61853,Female,39,High School,18,63,45,85,25,0.0,4,71,Urban,Software Engineer,120732,1 +61854,Male,28,Diploma,0,33,60,21,22,8.0,1,35,Rural,Data Analyst,142623,0 +61855,Male,39,Bachelors,0,47,85,9,55,2.0,0,28,Semi-Urban,Software Engineer,146429,0 +61856,Male,21,High School,10,36,66,49,59,1.0,2,79,Semi-Urban,Manager,146880,0 +61857,Male,39,PhD,17,90,80,79,5,6.0,4,22,Urban,Manager,61563,1 +61858,Male,45,Diploma,18,28,90,38,35,7.0,5,53,Semi-Urban,Data Analyst,87821,0 +61859,Male,32,Bachelors,10,7,5,96,60,9.0,1,29,Urban,Software Engineer,119129,0 +61860,Male,49,Bachelors,2,68,71,88,33,3.0,1,67,Urban,Software Engineer,83038,1 +61861,Female,50,Bachelors,1,41,84,30,28,3.0,3,31,Urban,Software Engineer,134805,0 +61862,Male,46,High School,13,29,24,10,45,7.0,6,93,Semi-Urban,Manager,68418,0 +61863,Male,29,Diploma,16,29,42,89,77,9.0,7,50,Rural,ML Engineer,143596,0 +61864,Male,48,Bachelors,14,6,95,81,32,5.0,7,79,Urban,Data Analyst,62565,1 +61865,Female,35,Diploma,9,98,6,47,62,1.0,5,58,Rural,Data Analyst,142257,0 +61866,Male,41,Masters,11,22,64,87,28,4.0,2,83,Urban,Manager,32406,1 +61867,Male,46,Bachelors,6,40,27,81,62,9.0,7,80,Urban,Software Engineer,116933,0 +61868,Male,49,Diploma,10,7,39,81,98,0.0,4,56,Semi-Urban,Manager,94316,0 +61869,Male,58,High School,15,40,65,23,56,1.0,0,12,Rural,Manager,117117,0 +61870,Female,29,Diploma,5,58,99,69,81,7.0,7,78,Urban,ML Engineer,47840,1 +61871,Female,34,High School,15,58,93,65,5,1.0,3,88,Urban,ML Engineer,101568,1 +61872,Female,45,Masters,10,54,54,9,22,8.0,1,45,Semi-Urban,Software Engineer,71120,0 +61873,Male,24,Diploma,7,78,14,37,69,7.0,0,68,Semi-Urban,ML Engineer,113311,0 +61874,Female,23,Masters,1,25,57,64,2,9.0,2,98,Rural,Software Engineer,70483,1 +61875,Female,46,High School,7,12,20,2,87,8.0,5,42,Urban,HR Executive,57148,0 +61876,Male,28,Masters,5,17,41,31,41,5.0,5,79,Rural,ML Engineer,64144,0 +61877,Male,31,Masters,14,20,71,12,76,9.0,0,34,Urban,Manager,34507,0 +61878,Female,30,High School,2,93,16,5,33,4.0,3,11,Urban,Data Analyst,99316,0 +61879,Female,54,Bachelors,4,89,34,4,97,6.0,2,45,Semi-Urban,Data Analyst,115749,0 +61880,Male,25,Bachelors,4,6,57,51,84,2.0,2,0,Semi-Urban,Manager,137835,0 +61881,Female,49,Bachelors,10,41,6,54,88,4.0,2,92,Rural,HR Executive,70851,0 +61882,Male,24,Masters,6,92,91,53,57,8.0,5,81,Rural,ML Engineer,27107,1 +61883,Male,29,Bachelors,5,5,26,12,11,4.0,5,18,Rural,Manager,31865,0 +61884,Male,45,Diploma,18,61,92,58,31,2.0,7,18,Urban,Software Engineer,20852,0 +61885,Male,37,Diploma,0,55,28,25,96,8.0,4,18,Urban,Data Analyst,146728,0 +61886,Male,57,Bachelors,7,18,1,11,92,5.0,6,24,Urban,ML Engineer,66490,0 +61887,Male,52,Bachelors,11,48,29,16,75,0.0,2,35,Urban,Manager,46987,0 +61888,Male,57,PhD,14,16,68,6,90,4.0,5,35,Semi-Urban,Software Engineer,94469,0 +61889,Male,58,Bachelors,5,22,23,67,95,6.0,1,85,Semi-Urban,ML Engineer,53296,0 +61890,Female,44,Diploma,17,3,92,35,36,2.0,3,50,Urban,ML Engineer,48707,0 +61891,Male,42,Masters,7,20,32,68,74,4.0,7,90,Urban,Software Engineer,23267,0 +61892,Male,28,Diploma,19,41,42,81,24,5.0,7,4,Urban,HR Executive,31652,0 +61893,Male,36,Bachelors,10,4,72,79,38,4.0,0,7,Semi-Urban,HR Executive,57001,0 +61894,Male,39,Diploma,6,8,57,40,93,1.0,4,86,Urban,HR Executive,28229,0 +61895,Female,41,Bachelors,11,87,1,50,71,9.0,6,52,Rural,ML Engineer,121600,0 +61896,Female,59,Masters,8,47,0,43,21,7.0,4,94,Urban,Data Analyst,129115,0 +61897,Female,39,Bachelors,14,28,63,20,16,9.0,2,75,Urban,Manager,79818,0 +61898,Male,51,Bachelors,1,58,49,26,25,9.0,2,38,Semi-Urban,ML Engineer,77237,0 +61899,Female,40,Masters,11,34,29,99,26,0.0,4,3,Semi-Urban,Data Analyst,34305,0 +61900,Male,28,Bachelors,6,92,93,73,53,4.0,1,51,Urban,ML Engineer,144080,1 +61901,Female,22,High School,8,72,27,3,42,1.0,0,38,Semi-Urban,Manager,33459,0 +61902,Male,38,Masters,8,6,12,18,23,2.0,2,70,Urban,ML Engineer,116876,0 +61903,Male,36,Masters,0,70,90,96,29,6.0,7,85,Semi-Urban,Manager,134113,1 +61904,Male,45,Diploma,15,56,8,69,1,4.0,2,23,Urban,HR Executive,91362,0 +61905,Female,56,Diploma,11,69,46,8,53,7.0,0,89,Rural,ML Engineer,143215,0 +61906,Female,55,Masters,15,16,13,38,0,2.0,6,56,Urban,HR Executive,76258,0 +61907,Male,42,Bachelors,1,93,43,46,31,6.0,5,30,Rural,Software Engineer,147245,0 +61908,Male,21,High School,18,46,10,52,41,3.0,1,85,Urban,Manager,146804,0 +61909,Other,30,Masters,4,67,76,43,27,5.0,7,99,Urban,Manager,80304,1 +61910,Male,59,Bachelors,2,48,0,38,76,2.0,2,69,Urban,Manager,88936,0 +61911,Male,33,Bachelors,10,67,78,0,38,9.0,1,50,Rural,Manager,66970,0 +61912,Male,53,Bachelors,19,12,27,55,0,2.0,6,29,Urban,HR Executive,107509,0 +61913,Male,28,Bachelors,11,53,13,19,79,1.0,1,32,Urban,Manager,38081,0 +61914,Male,37,High School,0,23,30,78,84,0.0,2,91,Urban,HR Executive,23108,0 +61915,Female,44,High School,1,39,39,83,69,0.0,2,41,Urban,Software Engineer,84096,0 +61916,Female,23,Bachelors,16,26,66,65,0,5.0,7,15,Urban,HR Executive,148101,0 +61917,Male,24,Bachelors,17,59,26,77,84,9.0,6,72,Rural,Software Engineer,127698,0 +61918,Other,59,High School,13,14,73,12,58,5.0,2,15,Rural,Data Analyst,136089,0 +61919,Female,32,Masters,17,31,38,14,7,8.0,1,71,Semi-Urban,Data Analyst,122855,0 +61920,Female,32,Masters,6,7,98,67,28,7.0,5,83,Urban,HR Executive,114627,1 +61921,Male,46,Bachelors,8,5,83,27,2,5.0,6,58,Rural,Software Engineer,142323,0 +61922,Male,58,High School,1,5,20,23,2,0.0,6,77,Rural,Software Engineer,117049,0 +61923,Male,43,Bachelors,8,48,42,67,85,7.0,1,29,Rural,Software Engineer,50011,0 +61924,Female,35,Masters,8,12,4,53,53,0.0,3,68,Urban,HR Executive,27190,0 +61925,Female,21,High School,1,95,2,68,74,9.0,5,40,Rural,Data Analyst,114859,0 +61926,Male,53,High School,3,65,64,19,89,3.0,4,32,Urban,ML Engineer,45706,0 +61927,Female,38,Bachelors,10,1,68,21,17,1.0,1,21,Urban,Manager,71250,0 +61928,Male,27,Diploma,7,9,69,14,64,3.0,6,75,Urban,ML Engineer,121229,0 +61929,Male,37,Diploma,5,42,98,84,18,8.0,3,49,Urban,Data Analyst,52512,1 +61930,Female,50,Masters,2,36,31,74,54,7.0,6,65,Semi-Urban,HR Executive,51357,0 +61931,Male,35,Masters,8,81,10,47,59,7.0,3,37,Semi-Urban,HR Executive,67818,0 +61932,Male,50,Masters,13,34,87,28,74,2.0,1,55,Semi-Urban,Software Engineer,34653,0 +61933,Female,26,Masters,5,96,75,28,73,8.0,6,95,Urban,Software Engineer,102416,1 +61934,Male,47,Bachelors,2,80,37,31,77,7.0,2,5,Semi-Urban,HR Executive,143259,0 +61935,Male,38,Bachelors,3,81,73,64,5,5.0,3,57,Urban,HR Executive,94394,1 +61936,Female,56,Bachelors,18,4,94,75,9,6.0,4,72,Urban,Manager,59203,1 +61937,Male,30,High School,13,37,41,82,31,1.0,0,10,Rural,HR Executive,87558,0 +61938,Male,21,High School,4,79,18,83,37,9.0,0,81,Urban,Software Engineer,87003,1 +61939,Other,38,Bachelors,9,79,58,21,91,9.0,6,55,Urban,Manager,60978,0 +61940,Male,37,PhD,11,73,72,39,56,9.0,3,84,Rural,HR Executive,125890,1 +61941,Male,54,Masters,0,91,17,94,91,1.0,3,91,Urban,Software Engineer,53008,1 +61942,Male,27,Bachelors,13,58,78,93,88,2.0,0,47,Rural,Data Analyst,114394,1 +61943,Female,39,Bachelors,1,86,49,51,15,7.0,1,48,Urban,Software Engineer,104777,0 +61944,Other,22,Bachelors,5,91,66,64,39,9.0,0,97,Rural,Data Analyst,25270,1 +61945,Male,35,Bachelors,0,64,43,53,44,2.0,3,17,Urban,Software Engineer,142235,0 +61946,Female,27,High School,7,5,17,28,95,7.0,4,70,Urban,HR Executive,116435,0 +61947,Female,36,Bachelors,17,90,65,82,78,5.0,5,21,Urban,HR Executive,106350,1 +61948,Female,55,Diploma,8,87,76,63,53,9.0,3,3,Semi-Urban,Software Engineer,132670,0 +61949,Male,21,Bachelors,18,22,24,32,7,3.0,6,91,Rural,HR Executive,77236,0 +61950,Male,55,Bachelors,9,78,8,38,32,3.0,1,92,Rural,Data Analyst,76497,0 +61951,Male,23,Masters,12,37,23,55,31,3.0,0,7,Urban,ML Engineer,127114,0 +61952,Female,43,Bachelors,9,53,77,73,86,7.0,4,16,Semi-Urban,Data Analyst,141108,0 +61953,Other,36,Bachelors,0,71,44,14,32,5.0,0,99,Rural,Software Engineer,148261,0 +61954,Male,50,Masters,15,85,98,60,21,5.0,1,48,Semi-Urban,Manager,99945,1 +61955,Male,40,Diploma,4,74,98,39,14,3.0,5,4,Semi-Urban,Software Engineer,34234,0 +61956,Male,49,Bachelors,0,17,56,35,96,7.0,3,35,Urban,HR Executive,52804,0 +61957,Female,56,Bachelors,8,71,10,23,41,3.0,3,63,Semi-Urban,HR Executive,79070,0 +61958,Male,43,Bachelors,3,10,24,28,44,4.0,0,66,Urban,Data Analyst,62698,0 +61959,Female,25,Diploma,15,38,14,78,19,7.0,3,98,Rural,Software Engineer,40130,0 +61960,Female,36,Masters,18,66,86,53,6,4.0,6,13,Rural,Manager,47134,0 +61961,Female,36,Diploma,10,64,7,30,29,0.0,6,14,Semi-Urban,Data Analyst,26158,0 +61962,Male,56,Diploma,15,24,13,20,65,2.0,0,43,Urban,Software Engineer,129403,0 +61963,Male,45,Diploma,12,73,1,12,43,5.0,7,14,Semi-Urban,Manager,149470,0 +61964,Female,39,Diploma,10,63,70,36,38,2.0,4,1,Rural,Data Analyst,149867,0 +61965,Male,36,High School,13,40,24,49,18,5.0,0,65,Semi-Urban,Manager,35069,0 +61966,Male,24,Bachelors,7,73,31,37,15,9.0,6,85,Urban,Manager,70162,0 +61967,Male,49,PhD,14,34,84,22,78,9.0,5,80,Semi-Urban,Data Analyst,54651,0 +61968,Male,41,Diploma,12,6,81,27,41,2.0,3,0,Semi-Urban,Data Analyst,73079,0 +61969,Other,21,High School,19,42,36,62,44,6.0,2,99,Urban,HR Executive,53996,0 +61970,Male,38,High School,0,44,1,7,66,2.0,5,77,Semi-Urban,Software Engineer,31151,0 +61971,Female,50,Bachelors,5,41,26,61,73,2.0,5,6,Urban,HR Executive,65748,0 +61972,Male,41,Bachelors,8,44,13,88,91,1.0,3,63,Urban,Data Analyst,59609,0 +61973,Male,29,,18,25,39,5,69,1.0,2,56,Semi-Urban,Software Engineer,120906,0 +61974,Female,21,Diploma,6,24,92,1,15,5.0,1,3,Semi-Urban,ML Engineer,131782,0 +61975,Female,43,Masters,19,45,28,20,36,5.0,1,78,Rural,ML Engineer,73865,0 +61976,Male,47,High School,11,88,48,22,85,3.0,6,90,Rural,ML Engineer,100503,1 +61977,Male,32,Bachelors,5,11,71,26,19,6.0,7,34,Semi-Urban,ML Engineer,108812,0 +61978,Male,36,Diploma,6,29,81,6,55,9.0,7,18,Urban,HR Executive,111271,0 +61979,Male,57,Masters,12,81,46,38,48,6.0,5,28,Rural,ML Engineer,92941,0 +61980,Female,55,High School,10,76,58,6,43,1.0,3,33,Urban,ML Engineer,143783,0 +61981,Male,56,Bachelors,4,8,21,73,44,0.0,6,68,Urban,Manager,48468,0 +61982,Male,45,High School,3,32,88,86,99,7.0,7,45,Semi-Urban,Manager,113739,1 +61983,Male,50,Bachelors,1,15,52,37,95,2.0,3,48,Semi-Urban,ML Engineer,54856,0 +61984,Male,28,PhD,11,42,19,46,72,4.0,4,0,Semi-Urban,HR Executive,112209,0 +61985,Male,41,Bachelors,0,35,1,64,42,8.0,1,28,Rural,Manager,78415,0 +61986,Male,48,Bachelors,9,90,94,92,20,6.0,2,94,Urban,Data Analyst,35259,1 +61987,Female,25,Bachelors,0,79,89,30,7,6.0,1,24,Semi-Urban,Data Analyst,36769,0 +61988,Female,21,Bachelors,2,10,21,99,67,8.0,6,21,Semi-Urban,ML Engineer,71100,0 +61989,Male,47,PhD,8,72,89,13,59,6.0,3,8,Urban,ML Engineer,48828,0 +61990,Female,49,Diploma,6,1,32,77,23,2.0,4,27,Urban,Manager,25377,0 +61991,Female,59,Bachelors,12,40,74,76,98,7.0,4,96,Urban,ML Engineer,49811,1 +61992,Male,43,Masters,3,18,94,67,24,8.0,4,86,Rural,ML Engineer,61093,1 +61993,Other,35,Bachelors,6,9,92,16,47,6.0,5,23,Urban,ML Engineer,141638,0 +61994,Male,40,Diploma,5,91,99,70,35,3.0,6,49,Urban,Manager,93264,1 +61995,Male,23,Bachelors,4,33,24,43,54,2.0,5,46,Rural,Software Engineer,53546,0 +61996,Male,31,Diploma,2,30,3,45,83,4.0,1,99,Rural,Software Engineer,21737,0 +61997,Other,28,Diploma,13,70,89,24,85,2.0,0,30,Urban,Manager,146209,0 +61998,Male,41,Masters,2,68,53,86,32,8.0,4,76,Urban,Manager,35004,1 +61999,Male,38,High School,5,76,85,82,43,3.0,5,62,Urban,Software Engineer,72911,1 +62000,Female,37,Bachelors,7,98,64,9,2,6.0,3,75,Rural,ML Engineer,103034,1 +62001,Female,39,Masters,17,64,20,59,72,8.0,7,21,Rural,Manager,49281,0 +62002,Female,40,Bachelors,19,30,41,89,73,9.0,4,16,Urban,ML Engineer,21442,0 +62003,Male,39,Diploma,2,39,54,51,72,5.0,2,20,Semi-Urban,Software Engineer,91009,0 +62004,Female,52,Bachelors,9,8,73,57,49,2.0,7,75,Urban,Manager,77089,0 +62005,Male,35,Bachelors,10,5,82,78,61,9.0,5,86,Semi-Urban,HR Executive,42160,1 +62006,Female,21,Bachelors,11,31,37,3,59,2.0,7,59,Urban,Data Analyst,114677,0 +62007,Male,53,Bachelors,6,11,4,55,5,2.0,4,53,Urban,Manager,77251,0 +62008,Female,27,Bachelors,12,94,55,82,29,0.0,7,80,Semi-Urban,Data Analyst,62681,1 +62009,Male,49,Diploma,19,41,67,36,74,1.0,7,67,Semi-Urban,HR Executive,33991,0 +62010,Female,37,Masters,15,77,23,21,78,3.0,7,4,Urban,Manager,20184,0 +62011,Male,30,High School,19,95,79,58,5,3.0,3,24,Rural,HR Executive,111534,1 +62012,Male,34,Masters,17,26,94,52,94,6.0,3,69,Rural,ML Engineer,129097,1 +62013,Male,38,Diploma,0,9,60,88,61,9.0,6,17,Urban,ML Engineer,80999,0 +62014,Male,42,High School,9,99,68,12,64,1.0,2,80,Urban,Data Analyst,36549,1 +62015,Male,42,Bachelors,11,57,29,34,74,5.0,7,36,Rural,Data Analyst,94910,0 +62016,Male,33,Diploma,9,4,63,86,89,6.0,7,17,Rural,Data Analyst,24242,0 +62017,Other,44,Diploma,8,93,45,90,5,4.0,5,69,Semi-Urban,Manager,36051,1 +62018,Female,45,Diploma,18,5,67,1,57,3.0,4,87,Urban,ML Engineer,76293,0 +62019,Male,54,PhD,19,83,4,59,12,7.0,4,85,Urban,HR Executive,85317,0 +62020,Male,45,Bachelors,4,76,30,21,50,4.0,7,9,Rural,Data Analyst,85865,0 +62021,Male,27,Masters,17,84,71,15,13,9.0,0,94,Urban,Software Engineer,92240,1 +62022,Male,35,Bachelors,19,21,81,72,81,4.0,0,57,Urban,Manager,109172,0 +62023,Male,52,Masters,10,39,10,23,39,2.0,7,7,Urban,ML Engineer,112466,0 +62024,Female,37,Masters,14,63,80,11,26,6.0,1,10,Rural,ML Engineer,120640,0 +62025,Female,22,Masters,10,5,37,93,84,2.0,2,97,Rural,Software Engineer,149076,0 +62026,Male,21,Masters,18,15,74,86,37,2.0,1,71,Semi-Urban,ML Engineer,66149,1 +62027,Female,50,High School,15,71,27,54,57,5.0,6,30,Rural,HR Executive,113661,0 +62028,Male,51,Bachelors,15,97,70,90,12,3.0,0,36,Urban,Manager,143947,1 +62029,Male,30,Diploma,6,21,28,22,13,9.0,6,58,Rural,Data Analyst,123805,0 +62030,Female,26,Bachelors,0,95,40,68,38,6.0,6,70,Urban,HR Executive,140491,1 +62031,Female,43,Masters,2,48,89,44,5,2.0,3,77,Urban,Software Engineer,25238,1 +62032,Male,31,Bachelors,18,85,77,34,26,1.0,2,44,Semi-Urban,Software Engineer,134553,1 +62033,Other,48,Bachelors,19,64,15,23,14,1.0,1,10,Semi-Urban,HR Executive,32958,0 +62034,Female,48,Diploma,19,58,69,36,69,2.0,0,9,Urban,Data Analyst,32706,0 +62035,Male,40,Diploma,7,34,38,59,8,0.0,7,37,Urban,Manager,127641,0 +62036,Male,35,Bachelors,8,98,47,31,37,4.0,5,58,Urban,HR Executive,55708,0 +62037,Female,36,Diploma,6,91,19,16,47,7.0,2,95,Rural,ML Engineer,127138,0 +62038,Male,26,Diploma,5,0,64,43,98,3.0,6,72,Rural,Manager,111419,0 +62039,Male,31,Masters,7,31,73,73,69,0.0,3,64,Urban,Manager,47162,1 +62040,Female,28,High School,3,78,69,22,14,7.0,5,82,Urban,ML Engineer,139063,1 +62041,Male,58,PhD,13,31,93,25,57,1.0,2,17,Semi-Urban,ML Engineer,50440,0 +62042,Female,33,Masters,3,96,86,79,43,3.0,7,16,Urban,HR Executive,56350,1 +62043,Male,51,Bachelors,1,12,71,61,29,7.0,7,40,Urban,Software Engineer,66893,0 +62044,Female,26,Masters,1,79,78,34,1,9.0,3,42,Urban,Software Engineer,109772,0 +62045,Female,56,Bachelors,18,3,62,10,47,7.0,4,35,Urban,HR Executive,145863,0 +62046,Other,22,PhD,16,53,81,55,48,0.0,7,21,Urban,Data Analyst,145760,0 +62047,Male,27,Masters,16,40,85,32,15,3.0,3,73,Rural,HR Executive,22895,0 +62048,Male,44,Bachelors,7,44,43,58,69,3.0,4,60,Semi-Urban,HR Executive,51492,0 +62049,Male,33,Bachelors,10,49,45,31,81,3.0,3,72,Urban,Software Engineer,41798,0 +62050,Female,54,Bachelors,2,95,9,57,78,0.0,4,98,Urban,HR Executive,102148,1 +62051,Male,48,Diploma,17,85,62,23,17,4.0,7,96,Semi-Urban,Data Analyst,145586,1 +62052,Male,21,Diploma,3,80,26,45,13,8.0,3,68,Semi-Urban,HR Executive,22287,0 +62053,Male,28,PhD,11,56,32,27,44,0.0,5,87,Urban,Manager,85523,0 +62054,Male,26,Masters,7,89,94,45,73,7.0,1,64,Rural,Data Analyst,132394,1 +62055,Female,30,Masters,16,20,63,7,66,2.0,5,68,Rural,HR Executive,86270,0 +62056,Female,25,Bachelors,0,32,75,30,52,8.0,7,92,Semi-Urban,Software Engineer,68161,0 +62057,Male,50,Diploma,14,23,21,32,48,1.0,6,6,Urban,ML Engineer,52339,0 +62058,Female,32,Bachelors,4,99,58,44,18,6.0,6,28,Urban,ML Engineer,143679,0 +62059,Female,45,Masters,13,43,3,25,64,3.0,2,98,Semi-Urban,Data Analyst,149168,0 +62060,Male,59,Bachelors,2,41,59,66,13,3.0,7,51,Urban,HR Executive,30815,0 +62061,Male,32,Diploma,1,80,97,23,69,2.0,5,74,Rural,Software Engineer,92645,1 +62062,Female,49,High School,7,22,6,0,68,3.0,2,85,Urban,Manager,118452,0 +62063,Male,54,Masters,13,48,39,70,28,0.0,4,67,Rural,HR Executive,91354,0 +62064,Female,48,Bachelors,18,28,21,15,73,3.0,5,56,Semi-Urban,Manager,58234,0 +62065,Male,48,High School,19,23,26,88,63,9.0,0,6,Urban,Software Engineer,59057,0 +62066,Female,30,Bachelors,4,11,70,92,34,5.0,5,7,Urban,HR Executive,149318,0 +62067,Female,22,Diploma,19,32,18,13,62,7.0,7,77,Rural,Manager,104807,0 +62068,Female,27,Diploma,5,84,46,89,44,6.0,1,56,Urban,Software Engineer,148874,1 +62069,Male,53,Masters,9,40,60,48,78,6.0,5,0,Rural,Software Engineer,131911,0 +62070,Female,39,Bachelors,2,86,24,43,50,4.0,3,91,Rural,HR Executive,141721,1 +62071,Male,54,Bachelors,6,34,30,73,82,3.0,5,33,Rural,ML Engineer,87930,0 +62072,Female,47,Bachelors,1,42,49,30,55,1.0,7,51,Urban,Software Engineer,119704,0 +62073,Female,56,Bachelors,12,29,31,66,92,6.0,2,69,Urban,HR Executive,92101,0 +62074,Male,23,Masters,13,96,14,96,79,7.0,0,93,Semi-Urban,Software Engineer,35485,1 +62075,Female,25,High School,18,9,72,50,66,6.0,1,97,Semi-Urban,Data Analyst,117063,0 +62076,Female,28,Masters,14,90,82,7,91,9.0,3,21,Rural,Manager,57155,0 +62077,Female,45,Bachelors,1,62,45,68,39,1.0,4,82,Semi-Urban,Software Engineer,133063,1 +62078,Female,28,Diploma,18,42,77,40,64,3.0,4,20,Semi-Urban,Data Analyst,82085,0 +62079,Male,34,High School,8,73,42,11,96,3.0,1,58,Urban,Manager,64412,0 +62080,Male,42,Masters,9,19,41,83,11,6.0,0,19,Semi-Urban,Manager,59320,0 +62081,Female,46,Bachelors,8,68,65,13,56,8.0,1,33,Urban,HR Executive,132710,0 +62082,Male,25,Bachelors,10,90,59,59,97,5.0,5,82,Semi-Urban,Data Analyst,96689,1 +62083,Male,35,Masters,9,7,17,55,46,5.0,6,49,Rural,Data Analyst,43040,0 +62084,Male,55,Bachelors,19,82,8,86,41,3.0,3,64,Rural,Software Engineer,28268,1 +62085,Male,59,Diploma,19,99,85,42,24,7.0,1,64,Urban,ML Engineer,37595,1 +62086,Male,50,High School,0,89,92,75,59,1.0,0,47,Urban,Data Analyst,22309,1 +62087,Female,31,Masters,12,99,92,21,86,4.0,4,46,Urban,Data Analyst,146880,1 +62088,Male,50,Masters,10,34,85,31,91,5.0,6,29,Semi-Urban,HR Executive,37827,0 +62089,Male,50,Diploma,9,19,42,33,94,7.0,2,6,Urban,Data Analyst,38995,0 +62090,Male,24,High School,4,90,15,62,15,2.0,6,93,Semi-Urban,Data Analyst,50845,1 +62091,Female,43,PhD,10,16,98,26,55,1.0,4,52,Urban,Software Engineer,48433,0 +62092,Male,42,High School,13,10,59,86,32,3.0,5,45,Urban,Software Engineer,85029,0 +62093,Female,22,Bachelors,18,59,21,47,3,5.0,2,91,Urban,Manager,71619,0 +62094,Male,26,Bachelors,9,96,32,58,21,9.0,5,62,Urban,Software Engineer,35658,1 +62095,Male,44,Bachelors,7,30,89,0,91,4.0,4,45,Rural,Data Analyst,40258,0 +62096,Male,52,Bachelors,0,91,20,80,0,4.0,7,70,Semi-Urban,ML Engineer,143657,1 +62097,Male,55,Diploma,2,81,41,25,70,4.0,4,67,Semi-Urban,Data Analyst,22787,0 +62098,Male,37,Diploma,15,39,67,24,22,0.0,0,88,Rural,Data Analyst,20385,0 +62099,Male,32,Diploma,0,69,34,50,9,6.0,4,95,Rural,ML Engineer,82913,1 +62100,Male,21,Bachelors,14,39,11,73,86,1.0,0,41,Semi-Urban,Data Analyst,123010,0 +62101,Female,35,Bachelors,16,67,38,43,29,7.0,1,36,Urban,HR Executive,92199,0 +62102,Male,29,High School,6,14,18,1,82,7.0,0,74,Rural,Data Analyst,97036,0 +62103,Male,47,Bachelors,11,69,93,20,19,5.0,5,24,Urban,Manager,83382,0 +62104,Male,23,Bachelors,17,5,59,36,92,1.0,7,66,Urban,Software Engineer,51400,0 +62105,Female,55,Masters,11,68,10,42,58,8.0,7,80,Urban,Data Analyst,42605,0 +62106,Male,39,Bachelors,9,3,65,62,96,0.0,0,51,Rural,ML Engineer,73877,0 +62107,Female,30,Diploma,2,35,89,39,62,4.0,0,35,Semi-Urban,Manager,91422,0 +62108,Female,59,Masters,1,35,68,67,93,1.0,5,66,Semi-Urban,HR Executive,133492,0 +62109,Male,28,Diploma,6,17,79,74,73,4.0,1,59,Urban,ML Engineer,35336,0 +62110,Male,51,Diploma,15,63,21,54,83,3.0,1,80,Semi-Urban,Software Engineer,86377,0 +62111,Female,26,Bachelors,18,44,86,57,77,5.0,3,67,Rural,Data Analyst,36173,1 +62112,Male,55,Masters,8,84,56,64,65,6.0,7,69,Urban,HR Executive,49464,1 +62113,Female,22,Diploma,3,31,97,16,87,7.0,0,62,Urban,Data Analyst,41640,0 +62114,Male,38,High School,3,49,52,8,64,9.0,2,70,Semi-Urban,HR Executive,103443,0 +62115,Male,29,Bachelors,15,98,22,44,79,4.0,6,59,Rural,ML Engineer,117733,0 +62116,Female,32,Diploma,10,67,62,39,75,1.0,7,58,Urban,Data Analyst,27412,0 +62117,Male,34,Bachelors,14,2,73,30,94,8.0,4,52,Urban,ML Engineer,34814,0 +62118,Female,53,Diploma,17,13,26,98,25,6.0,1,73,Urban,ML Engineer,32288,0 +62119,Male,29,Diploma,9,88,27,3,34,2.0,2,13,Urban,HR Executive,87071,0 +62120,Male,40,Bachelors,17,31,82,54,93,8.0,3,61,Urban,HR Executive,50501,0 +62121,Male,32,Diploma,1,39,94,67,47,5.0,4,82,Urban,HR Executive,107029,1 +62122,Female,22,Bachelors,0,90,10,1,10,2.0,3,47,Urban,Manager,57883,0 +62123,Female,52,High School,13,43,17,60,30,1.0,4,72,Urban,ML Engineer,40889,0 +62124,Male,51,High School,0,83,16,43,99,7.0,3,95,Urban,HR Executive,122434,1 +62125,Male,41,PhD,14,32,24,58,86,2.0,4,77,Urban,ML Engineer,142624,0 +62126,Male,23,Masters,7,21,79,79,3,0.0,3,34,Urban,Manager,120196,0 +62127,Female,36,Bachelors,3,66,22,28,90,3.0,3,6,Semi-Urban,Data Analyst,99967,0 +62128,Male,29,Bachelors,10,98,95,39,67,9.0,1,23,Rural,ML Engineer,119378,1 +62129,Male,28,Diploma,2,65,13,13,8,3.0,4,47,Urban,HR Executive,97459,0 +62130,Male,22,Bachelors,17,41,84,23,38,4.0,0,48,Urban,ML Engineer,94097,0 +62131,Female,31,Diploma,17,11,23,53,10,9.0,6,30,Semi-Urban,Software Engineer,87806,0 +62132,Male,48,Masters,11,17,49,39,46,2.0,3,94,Urban,ML Engineer,86921,0 +62133,Male,29,Bachelors,2,33,54,97,62,1.0,6,70,Semi-Urban,HR Executive,76029,1 +62134,Male,31,Diploma,5,60,65,29,3,7.0,3,14,Urban,HR Executive,26803,0 +62135,Male,50,Bachelors,6,44,61,2,53,0.0,6,77,Urban,HR Executive,26680,0 +62136,Other,51,Masters,3,75,14,94,6,8.0,7,73,Urban,Manager,126836,1 +62137,Female,41,High School,18,23,58,18,11,7.0,0,69,Rural,HR Executive,24823,0 +62138,Female,28,Bachelors,15,36,32,19,19,0.0,3,73,Semi-Urban,ML Engineer,36621,0 +62139,Male,52,High School,1,15,73,17,6,0.0,2,23,Urban,ML Engineer,148398,0 +62140,Female,35,Masters,9,78,13,80,12,7.0,7,71,Urban,Manager,69695,1 +62141,Male,59,Diploma,17,14,50,98,84,8.0,2,58,Urban,HR Executive,119835,0 +62142,Female,31,Masters,15,99,80,1,20,1.0,2,10,Urban,Software Engineer,66053,0 +62143,Female,57,Bachelors,2,65,13,97,89,5.0,4,17,Semi-Urban,Data Analyst,67802,0 +62144,Male,39,Bachelors,15,57,20,11,79,4.0,7,90,Urban,Manager,62332,0 +62145,Male,51,Bachelors,9,44,2,57,24,2.0,7,97,Semi-Urban,ML Engineer,137924,0 +62146,Male,25,Masters,0,32,62,64,66,2.0,6,6,Urban,HR Executive,136848,0 +62147,Male,37,Bachelors,7,27,79,6,77,3.0,5,36,Urban,Software Engineer,84718,0 +62148,Female,44,Masters,1,88,3,95,19,3.0,3,39,Semi-Urban,HR Executive,113268,0 +62149,Male,27,Diploma,2,40,33,6,52,1.0,5,91,Rural,Software Engineer,135351,0 +62150,Female,55,Bachelors,3,12,19,96,72,5.0,7,52,Urban,Manager,120492,0 +62151,Female,30,High School,0,92,97,40,59,4.0,3,38,Semi-Urban,HR Executive,64610,1 +62152,Female,59,Bachelors,10,66,86,84,5,1.0,5,3,Urban,Data Analyst,29579,0 +62153,Female,58,Diploma,0,60,82,61,9,8.0,6,34,Urban,ML Engineer,46775,0 +62154,Male,49,Diploma,1,92,85,22,2,1.0,6,68,Rural,Software Engineer,40641,1 +62155,Male,34,Diploma,11,33,60,94,64,7.0,2,44,Urban,Data Analyst,41024,0 +62156,Male,50,Bachelors,15,72,52,28,46,4.0,5,20,Rural,Software Engineer,28855,0 +62157,Male,26,High School,5,23,47,43,37,0.0,6,10,Urban,ML Engineer,21878,0 +62158,Male,35,Masters,3,13,98,41,57,7.0,5,61,Urban,HR Executive,20895,0 +62159,Female,21,Masters,19,50,71,0,12,9.0,1,34,Rural,Data Analyst,32319,0 +62160,Male,26,Diploma,13,27,48,69,99,0.0,7,70,Semi-Urban,Software Engineer,121830,0 +62161,Female,39,Diploma,6,37,93,11,21,8.0,0,98,Rural,ML Engineer,69383,0 +62162,Female,42,PhD,4,14,22,18,16,5.0,0,53,Urban,Manager,57031,0 +62163,Female,25,Bachelors,17,87,99,70,80,6.0,0,79,Urban,HR Executive,113487,1 +62164,Female,53,Bachelors,17,47,40,59,38,4.0,4,53,Rural,Manager,123404,0 +62165,Male,35,Masters,11,23,24,83,77,2.0,7,47,Semi-Urban,HR Executive,41846,0 +62166,Female,51,Diploma,8,73,10,37,7,8.0,5,61,Urban,ML Engineer,44158,0 +62167,Male,56,Diploma,4,29,49,38,72,5.0,1,65,Urban,ML Engineer,62002,0 +62168,Other,36,Bachelors,2,21,17,55,36,2.0,6,88,Urban,Manager,118129,0 +62169,Female,35,High School,5,88,66,2,53,2.0,2,22,Semi-Urban,Manager,34539,0 +62170,Male,46,Bachelors,18,18,52,47,87,4.0,6,16,Urban,Software Engineer,125839,0 +62171,Female,39,Masters,9,47,65,83,21,9.0,0,4,Rural,HR Executive,52736,0 +62172,Male,28,High School,10,86,61,21,17,8.0,5,19,Rural,Manager,49401,0 +62173,Male,52,Bachelors,13,14,86,10,86,0.0,2,71,Urban,Data Analyst,81033,0 +62174,Female,23,Masters,6,92,83,41,11,4.0,2,63,Urban,Data Analyst,47197,1 +62175,Female,24,Diploma,12,75,87,63,90,5.0,6,93,Urban,ML Engineer,24963,1 +62176,Female,45,Bachelors,16,66,13,42,15,0.0,6,50,Urban,Manager,132497,0 +62177,Male,40,Diploma,12,17,89,87,27,9.0,3,7,Semi-Urban,Software Engineer,27334,0 +62178,Male,24,High School,11,64,0,84,93,4.0,1,80,Urban,ML Engineer,79083,0 +62179,Male,57,Bachelors,1,42,59,32,95,9.0,0,16,Urban,Software Engineer,59270,0 +62180,Male,24,Bachelors,10,18,21,40,67,7.0,0,97,Urban,ML Engineer,20489,0 +62181,Male,51,High School,17,37,82,24,60,4.0,0,92,Semi-Urban,Data Analyst,103817,1 +62182,Female,22,Masters,1,89,33,2,84,4.0,2,65,Urban,Data Analyst,116101,0 +62183,Male,36,Bachelors,3,33,57,87,35,0.0,4,78,Urban,Software Engineer,123814,1 +62184,Female,28,Masters,1,8,85,20,16,0.0,7,71,Urban,Manager,54831,0 +62185,Male,31,Diploma,16,76,89,69,24,9.0,5,81,Urban,ML Engineer,34577,1 +62186,Male,59,Bachelors,6,32,66,73,45,2.0,2,29,Rural,ML Engineer,81750,0 +62187,Male,52,High School,7,34,43,29,34,4.0,7,54,Rural,Data Analyst,146444,0 +62188,Male,41,Bachelors,8,99,81,95,67,6.0,2,99,Urban,Software Engineer,113072,1 +62189,Male,24,Diploma,5,35,99,83,48,1.0,7,96,Urban,Manager,85818,1 +62190,Male,36,Bachelors,10,37,78,39,64,4.0,1,55,Semi-Urban,HR Executive,113918,0 +62191,Male,41,Bachelors,7,73,74,7,81,2.0,6,65,Rural,Manager,133621,0 +62192,Female,33,PhD,2,67,79,90,60,2.0,3,36,Urban,Manager,143211,1 +62193,Male,30,Masters,11,35,85,63,78,0.0,4,38,Rural,Data Analyst,100474,0 +62194,Male,34,Diploma,11,59,75,0,94,2.0,2,12,Rural,HR Executive,42824,0 +62195,Male,25,High School,14,49,70,44,28,0.0,7,40,Semi-Urban,Software Engineer,117099,0 +62196,Male,51,Bachelors,7,19,13,54,68,9.0,3,12,Urban,ML Engineer,132529,0 +62197,Male,34,High School,10,67,34,61,55,9.0,4,46,Semi-Urban,Data Analyst,111840,0 +62198,Male,38,Diploma,10,16,78,31,12,7.0,3,95,Semi-Urban,Software Engineer,111106,0 +62199,Male,39,Diploma,13,91,84,8,16,5.0,4,17,Urban,ML Engineer,24161,0 +62200,Male,49,Bachelors,13,2,67,7,72,1.0,3,84,Rural,Manager,41337,0 +62201,Male,23,High School,16,51,33,71,51,4.0,3,31,Semi-Urban,Manager,126417,0 +62202,Male,36,PhD,4,0,50,22,32,7.0,6,31,Urban,Software Engineer,97868,0 +62203,Male,48,High School,2,63,27,75,20,0.0,1,90,Urban,Manager,111449,1 +62204,Female,58,Masters,19,45,85,22,5,5.0,3,8,Semi-Urban,ML Engineer,46798,0 +62205,Male,45,Masters,16,86,55,21,53,2.0,6,67,Urban,Manager,36975,0 +62206,Male,38,PhD,3,50,27,23,52,8.0,7,60,Rural,ML Engineer,85640,0 +62207,Male,58,Bachelors,11,93,74,75,50,7.0,2,7,Semi-Urban,Manager,118814,1 +62208,Other,27,Bachelors,8,52,21,37,98,2.0,1,20,Urban,HR Executive,57144,0 +62209,Male,54,Diploma,13,19,39,56,22,3.0,6,83,Urban,Software Engineer,116327,0 +62210,Female,30,Diploma,9,96,10,99,8,5.0,6,68,Urban,Manager,36645,1 +62211,Female,44,High School,2,99,69,55,84,6.0,6,63,Rural,Manager,43093,1 +62212,Male,57,Masters,11,55,54,68,34,8.0,6,34,Urban,ML Engineer,49851,0 +62213,Other,30,Diploma,5,89,44,38,82,6.0,7,93,Urban,HR Executive,148851,1 +62214,Male,50,Bachelors,12,39,69,83,89,1.0,0,7,Rural,Software Engineer,123391,0 +62215,Male,25,Bachelors,19,80,86,7,14,5.0,0,64,Urban,Data Analyst,69145,1 +62216,Male,59,Diploma,4,29,92,10,45,8.0,5,3,Semi-Urban,Manager,54030,0 +62217,Female,52,Bachelors,13,82,98,7,82,8.0,5,55,Urban,HR Executive,132705,1 +62218,Male,47,Masters,18,95,30,49,40,9.0,1,49,Semi-Urban,Software Engineer,33161,0 +62219,Male,49,Bachelors,12,14,82,11,14,4.0,2,7,Urban,HR Executive,96456,0 +62220,Male,23,Bachelors,10,73,27,50,95,1.0,2,83,Semi-Urban,HR Executive,30200,0 +62221,Male,51,High School,6,46,48,83,40,5.0,7,0,Urban,HR Executive,55317,0 +62222,Male,49,Bachelors,15,9,73,67,66,5.0,1,51,Semi-Urban,Manager,51807,0 +62223,Female,33,Masters,17,53,59,97,42,5.0,4,80,Urban,Data Analyst,64494,1 +62224,Male,38,Diploma,13,98,7,8,18,8.0,4,57,Semi-Urban,HR Executive,115034,0 +62225,Female,30,PhD,15,83,90,12,6,0.0,3,36,Urban,Manager,31232,0 +62226,Female,32,Bachelors,17,1,15,97,74,4.0,5,59,Semi-Urban,ML Engineer,107379,0 +62227,Female,31,Bachelors,16,37,62,36,19,3.0,7,72,Urban,HR Executive,143401,0 +62228,Female,51,Bachelors,11,45,73,98,20,6.0,6,51,Rural,Software Engineer,101464,1 +62229,Other,57,Masters,13,3,15,62,77,7.0,2,35,Urban,HR Executive,80147,0 +62230,Male,54,Masters,0,54,40,28,76,3.0,1,0,Urban,Manager,144964,0 +62231,Male,32,Bachelors,18,19,16,34,21,0.0,3,38,Urban,HR Executive,109311,0 +62232,Male,36,High School,8,60,37,95,61,6.0,4,87,Urban,Software Engineer,125737,1 +62233,Male,37,Bachelors,7,63,46,9,21,9.0,1,96,Semi-Urban,Data Analyst,105290,0 +62234,Male,22,Bachelors,16,78,17,65,57,8.0,5,1,Rural,Software Engineer,109437,0 +62235,Female,55,Diploma,17,2,65,35,1,5.0,1,23,Urban,Manager,78865,0 +62236,Male,24,Bachelors,19,21,65,45,34,7.0,4,71,Semi-Urban,ML Engineer,39602,0 +62237,Male,23,Bachelors,3,68,74,25,99,3.0,4,16,Urban,ML Engineer,59013,0 +62238,Female,57,Diploma,19,25,98,55,99,9.0,5,17,Semi-Urban,Data Analyst,123986,0 +62239,Female,28,Bachelors,10,64,87,22,5,0.0,5,27,Urban,ML Engineer,68244,0 +62240,Female,33,Bachelors,0,79,18,66,73,7.0,2,58,Semi-Urban,ML Engineer,29191,0 +62241,Male,24,High School,3,93,15,35,77,4.0,4,8,Rural,Data Analyst,91256,0 +62242,Female,57,Diploma,2,60,79,16,37,2.0,5,41,Rural,HR Executive,95921,0 +62243,Male,39,High School,16,55,84,27,39,9.0,3,27,Urban,Data Analyst,20999,0 +62244,Female,31,Masters,2,76,0,6,64,5.0,3,89,Semi-Urban,Data Analyst,69426,0 +62245,Male,27,Masters,8,9,44,52,20,3.0,3,97,Rural,Data Analyst,101604,0 +62246,Male,47,Masters,10,31,9,10,79,6.0,7,80,Semi-Urban,Data Analyst,136961,0 +62247,Male,29,Bachelors,0,86,62,39,73,8.0,6,36,Semi-Urban,Manager,112215,0 +62248,Other,36,Bachelors,14,57,98,42,13,8.0,1,44,Semi-Urban,Manager,51561,1 +62249,Male,55,Bachelors,9,0,7,41,2,1.0,0,68,Urban,Software Engineer,148049,0 +62250,Female,28,PhD,6,92,45,96,23,5.0,2,19,Urban,Manager,77824,1 +62251,Female,51,Bachelors,10,95,73,36,90,9.0,5,96,Urban,ML Engineer,111003,1 +62252,Male,59,Bachelors,10,48,73,30,58,1.0,0,62,Semi-Urban,HR Executive,52578,0 +62253,Male,22,High School,12,59,38,30,52,3.0,4,49,Urban,ML Engineer,37806,0 +62254,Male,57,Bachelors,3,87,89,53,78,9.0,6,8,Semi-Urban,Manager,95084,1 +62255,Female,54,High School,6,60,12,74,90,7.0,7,82,Urban,Software Engineer,142163,0 +62256,Male,38,Bachelors,5,90,67,53,70,1.0,6,43,Urban,ML Engineer,91752,1 +62257,Female,30,Bachelors,19,36,15,75,98,7.0,5,71,Urban,Manager,90441,0 +62258,Female,33,Bachelors,14,65,95,43,5,0.0,0,12,Urban,HR Executive,138005,0 +62259,Male,53,High School,19,11,13,28,95,7.0,6,85,Urban,Data Analyst,133971,0 +62260,Female,28,High School,6,26,40,83,5,2.0,1,69,Urban,HR Executive,142886,0 +62261,Female,30,High School,14,51,8,20,58,8.0,0,91,Urban,Data Analyst,123520,0 +62262,Female,31,Diploma,10,81,50,56,97,7.0,7,98,Urban,Data Analyst,140388,1 +62263,Male,38,Bachelors,3,86,19,54,65,5.0,7,49,Urban,Manager,122306,0 +62264,Male,39,Bachelors,12,75,15,64,89,5.0,6,93,Urban,Manager,132077,1 +62265,Male,52,High School,7,23,73,41,3,8.0,3,25,Rural,Manager,92496,0 +62266,Female,40,Bachelors,11,35,94,69,98,0.0,4,57,Semi-Urban,Manager,23176,1 +62267,Male,59,Diploma,1,58,86,28,60,2.0,7,12,Urban,Manager,65614,0 +62268,Male,22,High School,13,71,24,93,5,5.0,2,86,Rural,ML Engineer,136755,1 +62269,Male,59,Bachelors,14,50,78,6,11,3.0,3,99,Semi-Urban,Software Engineer,110004,0 +62270,Male,25,Bachelors,3,87,25,91,8,4.0,5,15,Rural,HR Executive,65382,0 +62271,Male,51,Bachelors,9,35,92,21,45,7.0,3,19,Urban,HR Executive,51217,0 +62272,Male,57,Diploma,0,98,92,5,66,9.0,3,83,Urban,Data Analyst,67854,1 +62273,Female,32,Bachelors,18,47,60,42,98,0.0,0,32,Urban,Software Engineer,116159,0 +62274,Female,27,Bachelors,1,33,87,9,40,3.0,3,5,Semi-Urban,ML Engineer,65543,0 +62275,Female,51,High School,19,32,14,87,23,7.0,3,1,Semi-Urban,Manager,23571,0 +62276,Male,34,Masters,4,32,48,84,50,2.0,5,1,Semi-Urban,HR Executive,106012,0 +62277,Male,40,Masters,3,21,87,83,6,7.0,6,27,Urban,Data Analyst,135750,0 +62278,Male,52,Bachelors,19,7,72,33,13,8.0,5,4,Semi-Urban,Manager,73126,0 +62279,Female,28,Bachelors,16,40,72,64,7,9.0,1,7,Semi-Urban,ML Engineer,112055,0 +62280,Female,47,Bachelors,14,82,52,68,40,2.0,1,44,Semi-Urban,Data Analyst,83123,1 +62281,Male,55,PhD,18,80,0,80,14,5.0,3,95,Rural,Manager,39642,1 +62282,Male,50,Diploma,2,26,9,29,2,7.0,4,34,Semi-Urban,Software Engineer,88228,0 +62283,Male,47,Diploma,7,88,31,63,61,8.0,7,17,Urban,Software Engineer,61624,0 +62284,Female,41,Masters,6,37,50,19,85,0.0,6,29,Urban,ML Engineer,114638,0 +62285,Male,47,Masters,2,30,70,69,17,5.0,5,29,Urban,Software Engineer,105625,0 +62286,Male,44,Masters,4,65,27,60,1,4.0,5,22,Urban,Software Engineer,52751,0 +62287,Male,48,Bachelors,15,75,54,62,96,5.0,5,43,Semi-Urban,Manager,71496,0 +62288,Male,52,Diploma,17,72,87,65,82,0.0,0,1,Urban,ML Engineer,104184,0 +62289,Other,25,Diploma,17,57,12,41,45,5.0,4,30,Urban,Software Engineer,109623,0 +62290,Male,35,Bachelors,0,10,62,45,79,9.0,2,84,Urban,HR Executive,105227,0 +62291,Male,32,High School,0,55,94,50,14,4.0,5,38,Urban,Manager,34512,1 +62292,Female,38,High School,17,4,94,49,18,2.0,5,29,Urban,Software Engineer,72688,0 +62293,Female,33,High School,12,37,5,77,38,3.0,5,27,Urban,HR Executive,143688,0 +62294,Female,29,High School,10,79,84,22,75,7.0,2,80,Rural,Software Engineer,69574,1 +62295,Female,56,Bachelors,8,88,92,32,62,6.0,3,33,Semi-Urban,Data Analyst,43537,1 +62296,Male,51,Bachelors,13,66,82,41,6,5.0,6,59,Semi-Urban,HR Executive,148204,1 +62297,Male,23,Diploma,1,78,30,53,43,4.0,1,68,Rural,HR Executive,72985,0 +62298,Female,52,Diploma,9,33,19,9,43,8.0,2,4,Urban,HR Executive,24042,0 +62299,Female,49,Bachelors,1,75,37,72,40,5.0,3,67,Urban,HR Executive,34862,1 +62300,Male,37,High School,19,8,1,55,56,7.0,2,3,Semi-Urban,Software Engineer,136745,0 +62301,Female,28,Diploma,10,45,52,99,92,7.0,2,51,Urban,Data Analyst,61007,1 +62302,Male,41,Bachelors,15,7,97,1,61,1.0,1,69,Urban,Manager,140167,0 +62303,Male,50,High School,17,71,45,24,23,4.0,6,35,Urban,Software Engineer,41133,0 +62304,Female,50,Bachelors,16,91,2,70,75,6.0,1,0,Urban,HR Executive,134782,0 +62305,Female,23,Bachelors,0,86,83,34,9,0.0,2,82,Urban,Software Engineer,78581,1 +62306,Male,31,Masters,8,34,34,4,62,1.0,1,19,Semi-Urban,Manager,124838,0 +62307,Male,40,PhD,7,76,41,69,42,6.0,7,21,Urban,Software Engineer,85766,0 +62308,Male,24,Bachelors,2,55,18,31,62,5.0,0,24,Urban,Data Analyst,138399,0 +62309,Male,28,High School,7,83,12,76,71,7.0,0,14,Semi-Urban,Software Engineer,24412,0 +62310,Male,55,Bachelors,12,45,63,62,87,8.0,2,5,Rural,ML Engineer,138178,0 +62311,Female,32,Bachelors,6,72,74,27,80,8.0,0,99,Semi-Urban,Manager,78757,1 +62312,Male,40,Bachelors,6,32,51,5,71,5.0,4,99,Urban,HR Executive,110530,0 +62313,Female,25,High School,1,47,94,25,30,1.0,0,86,Urban,HR Executive,119649,1 +62314,Other,35,Bachelors,18,52,24,11,27,9.0,4,37,Urban,HR Executive,93495,0 +62315,Male,31,Bachelors,6,65,31,96,58,4.0,4,50,Semi-Urban,Manager,65232,1 +62316,Male,50,Masters,6,89,44,95,30,4.0,7,60,Rural,HR Executive,62541,1 +62317,Female,46,Bachelors,19,57,31,62,60,9.0,6,98,Rural,HR Executive,109260,1 +62318,Male,23,Bachelors,2,16,48,84,63,1.0,7,12,Urban,ML Engineer,149996,0 +62319,Female,56,Bachelors,6,99,29,85,53,0.0,2,84,Urban,Software Engineer,101209,1 +62320,Male,30,Bachelors,8,60,4,26,54,4.0,1,89,Urban,Manager,136141,0 +62321,Female,52,Masters,15,92,0,44,91,9.0,7,9,Urban,ML Engineer,105977,0 +62322,Male,30,Masters,3,91,69,91,3,5.0,2,90,Urban,ML Engineer,130000,1 +62323,Female,26,Bachelors,3,15,84,67,96,8.0,2,58,Urban,Manager,30184,0 +62324,Female,46,Masters,4,15,92,77,4,4.0,0,34,Semi-Urban,ML Engineer,35118,0 +62325,Male,34,Diploma,13,80,90,35,3,7.0,2,29,Semi-Urban,HR Executive,123639,0 +62326,Female,57,PhD,18,81,27,24,3,5.0,0,39,Rural,Data Analyst,114803,0 +62327,Male,21,Bachelors,14,16,14,11,4,9.0,1,0,Urban,Software Engineer,102968,0 +62328,Male,26,Masters,12,28,61,46,61,1.0,5,0,Rural,Data Analyst,143964,0 +62329,Male,53,Diploma,10,62,35,45,74,3.0,3,65,Urban,Data Analyst,44370,0 +62330,Male,25,PhD,14,89,78,29,54,6.0,6,96,Semi-Urban,Software Engineer,143382,1 +62331,Female,48,Bachelors,11,57,80,96,49,6.0,3,81,Urban,HR Executive,26537,1 +62332,Male,30,PhD,2,34,14,40,67,4.0,7,53,Rural,Manager,40998,0 +62333,Female,46,Bachelors,10,39,72,95,68,3.0,2,56,Semi-Urban,Data Analyst,55913,1 +62334,Female,58,Bachelors,12,69,94,0,42,9.0,4,63,Urban,Manager,119817,0 +62335,Female,35,Masters,7,83,25,25,2,0.0,5,26,Urban,Manager,59606,0 +62336,Female,37,Masters,0,48,91,84,64,5.0,1,50,Urban,Data Analyst,91305,1 +62337,Other,54,Bachelors,7,13,6,53,0,5.0,7,44,Semi-Urban,Manager,79742,0 +62338,Male,22,Bachelors,9,6,48,17,81,1.0,0,44,Urban,Software Engineer,112129,0 +62339,Male,35,High School,12,43,58,27,60,2.0,2,93,Urban,ML Engineer,136345,0 +62340,Female,36,Diploma,8,76,43,34,77,8.0,3,7,Urban,Software Engineer,97689,0 +62341,Female,37,Bachelors,12,69,13,95,89,3.0,1,46,Urban,ML Engineer,128917,0 +62342,Male,48,PhD,7,50,4,34,2,8.0,1,19,Urban,Software Engineer,54382,0 +62343,Other,21,Bachelors,5,43,92,42,63,2.0,6,24,Rural,Software Engineer,91283,0 +62344,Female,57,Masters,3,91,67,81,58,0.0,0,62,Rural,Data Analyst,35636,1 +62345,Male,42,High School,1,61,97,23,31,0.0,7,42,Urban,ML Engineer,102378,0 +62346,Female,54,Bachelors,6,36,76,13,50,8.0,7,1,Urban,Data Analyst,54381,0 +62347,Female,55,High School,7,32,11,8,67,9.0,6,14,Semi-Urban,Software Engineer,146746,0 +62348,Male,30,Masters,10,43,89,9,20,9.0,3,10,Urban,Manager,133097,0 +62349,Female,27,High School,16,79,89,99,21,2.0,5,75,Urban,HR Executive,32957,1 +62350,Other,31,Masters,9,80,99,38,69,4.0,5,93,Semi-Urban,ML Engineer,66777,1 +62351,Female,45,Bachelors,1,47,39,57,55,5.0,1,90,Urban,HR Executive,80045,0 +62352,Female,29,Diploma,9,17,84,70,34,3.0,4,69,Urban,Manager,38567,0 +62353,Male,56,Bachelors,13,92,85,81,25,0.0,6,87,Urban,Manager,55932,1 +62354,Female,36,Bachelors,11,30,46,34,64,4.0,4,87,Semi-Urban,Manager,44445,0 +62355,Male,58,Bachelors,8,28,89,81,43,3.0,1,33,Rural,ML Engineer,61720,0 +62356,Male,39,Diploma,15,13,55,22,80,1.0,4,72,Urban,Software Engineer,145143,0 +62357,Male,46,Diploma,3,38,20,3,20,7.0,6,18,Urban,Manager,41066,0 +62358,Female,31,Diploma,2,98,32,97,2,6.0,1,18,Semi-Urban,Software Engineer,30424,1 +62359,Male,33,Bachelors,9,68,39,64,34,6.0,1,73,Rural,Data Analyst,109358,1 +62360,Female,45,Bachelors,18,7,47,89,95,0.0,2,54,Urban,Data Analyst,49628,0 +62361,Female,56,Diploma,8,10,18,7,84,3.0,4,34,Urban,Manager,35253,0 +62362,Male,39,High School,3,68,14,57,66,6.0,7,62,Urban,ML Engineer,98825,0 +62363,Female,39,Diploma,3,27,34,39,80,0.0,3,97,Semi-Urban,HR Executive,85053,0 +62364,Male,21,Diploma,3,16,3,98,49,2.0,0,43,Rural,Manager,37548,0 +62365,Female,29,PhD,15,30,73,89,69,4.0,7,28,Urban,HR Executive,61277,0 +62366,Male,49,Diploma,8,18,50,93,37,5.0,7,12,Semi-Urban,Software Engineer,39249,0 +62367,Other,54,Bachelors,19,26,67,52,68,2.0,0,28,Semi-Urban,ML Engineer,74422,0 +62368,Male,45,Masters,13,36,31,5,6,3.0,1,43,Urban,Manager,37720,0 +62369,Male,48,Masters,12,95,95,20,10,1.0,2,4,Urban,Software Engineer,133823,0 +62370,Male,49,High School,13,26,88,57,8,6.0,0,74,Urban,ML Engineer,119291,1 +62371,Male,46,Bachelors,17,14,51,4,94,9.0,3,38,Urban,ML Engineer,106704,0 +62372,Male,38,Bachelors,11,47,2,78,86,5.0,1,52,Rural,Manager,53797,0 +62373,Male,25,Masters,12,26,69,53,42,8.0,3,72,Rural,HR Executive,143964,0 +62374,Female,40,Diploma,2,97,52,15,74,0.0,3,79,Semi-Urban,ML Engineer,74195,1 +62375,Other,25,High School,14,24,16,4,79,2.0,7,81,Urban,Manager,52859,0 +62376,Female,37,Masters,16,98,41,47,49,0.0,5,18,Semi-Urban,Data Analyst,128876,0 +62377,Male,56,PhD,14,20,56,79,66,4.0,4,75,Rural,HR Executive,52636,0 +62378,Male,49,PhD,7,8,60,91,63,8.0,4,16,Urban,HR Executive,112587,0 +62379,Male,35,Diploma,1,99,87,4,96,8.0,1,99,Rural,HR Executive,120493,1 +62380,Male,36,Bachelors,15,26,96,74,50,7.0,4,70,Urban,HR Executive,41079,1 +62381,Female,42,Bachelors,19,90,89,5,56,3.0,3,97,Urban,Software Engineer,64174,1 +62382,Female,30,High School,14,68,79,97,78,1.0,4,37,Urban,Data Analyst,136670,1 +62383,Male,23,Bachelors,3,88,71,88,6,0.0,2,25,Urban,Data Analyst,110096,1 +62384,Other,31,Masters,7,68,99,58,89,1.0,0,36,Semi-Urban,Data Analyst,59349,1 +62385,Male,44,Bachelors,12,78,46,64,2,6.0,7,61,Rural,Software Engineer,43924,1 +62386,Female,54,Bachelors,16,5,34,91,9,8.0,6,8,Semi-Urban,ML Engineer,87718,0 +62387,Male,55,Masters,6,90,23,12,89,7.0,2,33,Urban,Manager,99490,0 +62388,Male,27,Bachelors,0,23,82,44,8,6.0,5,68,Urban,Data Analyst,117163,0 +62389,Female,52,Bachelors,5,43,14,75,88,9.0,6,4,Rural,Data Analyst,119473,0 +62390,Female,42,Bachelors,14,38,55,39,75,0.0,3,63,Urban,Data Analyst,145325,0 +62391,Male,41,High School,4,15,42,18,49,6.0,1,59,Semi-Urban,Manager,71220,0 +62392,Male,21,Bachelors,15,1,37,6,32,6.0,4,46,Urban,Software Engineer,128248,0 +62393,Male,52,Diploma,11,92,68,10,55,3.0,7,47,Urban,Data Analyst,49402,0 +62394,Male,37,Bachelors,18,40,30,41,68,2.0,3,56,Rural,HR Executive,87462,0 +62395,Male,43,High School,0,58,56,17,76,4.0,7,17,Urban,Manager,56549,0 +62396,Male,46,Diploma,8,94,90,8,8,2.0,1,75,Urban,Manager,59924,1 +62397,Male,51,Bachelors,0,40,81,70,84,1.0,1,53,Urban,Data Analyst,92286,1 +62398,Male,47,Diploma,19,44,62,4,41,1.0,3,30,Semi-Urban,Data Analyst,73647,0 +62399,Male,47,High School,11,26,33,21,14,3.0,0,53,Semi-Urban,Data Analyst,126544,0 +62400,Male,55,Bachelors,17,75,65,90,73,0.0,3,86,Rural,HR Executive,57592,1 +62401,Male,53,Masters,10,15,77,3,88,5.0,7,46,Urban,HR Executive,42392,0 +62402,Male,57,Bachelors,4,91,6,20,99,4.0,5,9,Urban,Manager,132135,0 +62403,Female,33,High School,0,86,10,32,34,5.0,1,87,Rural,ML Engineer,103542,0 +62404,Male,39,Masters,6,8,33,92,73,2.0,2,72,Urban,Manager,109552,0 +62405,Male,29,Diploma,9,34,13,16,14,2.0,2,20,Urban,Software Engineer,51807,0 +62406,Other,54,High School,3,77,53,4,85,5.0,7,58,Rural,Manager,80349,0 +62407,Male,30,Masters,14,29,85,64,84,7.0,7,94,Semi-Urban,Manager,116934,1 +62408,Female,34,Bachelors,14,18,39,82,47,2.0,6,29,Urban,ML Engineer,27866,0 +62409,Male,37,Bachelors,9,86,55,48,37,9.0,3,33,Rural,Data Analyst,51516,0 +62410,Female,52,Bachelors,14,67,23,90,26,5.0,2,79,Urban,Software Engineer,56542,1 +62411,Male,27,Masters,7,10,60,26,16,0.0,5,99,Urban,ML Engineer,129681,0 +62412,Male,50,High School,14,2,96,82,44,7.0,5,81,Urban,ML Engineer,26162,1 +62413,Male,46,Bachelors,9,29,60,66,47,3.0,7,90,Urban,HR Executive,62247,1 +62414,Female,55,High School,8,58,70,84,17,1.0,5,2,Urban,Manager,101277,0 +62415,Female,50,High School,19,37,35,28,36,2.0,1,58,Rural,HR Executive,24695,0 +62416,Male,31,Bachelors,4,43,2,24,67,0.0,0,47,Urban,Data Analyst,90184,0 +62417,Female,46,Bachelors,9,99,89,39,32,5.0,2,7,Semi-Urban,Manager,22637,0 +62418,Male,57,High School,14,64,1,69,18,5.0,7,85,Semi-Urban,Data Analyst,72084,0 +62419,Male,56,Diploma,5,6,37,89,41,6.0,3,97,Semi-Urban,Manager,42699,0 +62420,Male,25,Masters,18,35,97,77,81,7.0,1,44,Urban,Manager,128076,1 +62421,Male,21,Diploma,11,42,76,68,57,8.0,4,99,Urban,HR Executive,85190,1 +62422,Female,36,High School,0,43,60,52,99,3.0,1,15,Urban,Software Engineer,142696,0 +62423,Female,29,Bachelors,1,52,63,11,7,9.0,5,36,Semi-Urban,Software Engineer,147552,0 +62424,Other,41,Diploma,10,58,99,99,20,2.0,7,93,Urban,HR Executive,138671,1 +62425,Female,49,Masters,11,18,22,88,4,8.0,5,64,Urban,ML Engineer,98021,0 +62426,Male,36,Bachelors,7,37,16,85,60,6.0,6,18,Rural,Manager,134816,0 +62427,Female,56,Bachelors,8,53,27,26,51,4.0,0,64,Urban,Data Analyst,74981,0 +62428,Female,50,Bachelors,11,61,60,83,19,0.0,2,13,Semi-Urban,HR Executive,21599,0 +62429,Other,29,High School,12,21,26,38,55,0.0,0,13,Urban,Data Analyst,93605,0 +62430,Male,49,High School,2,90,50,27,26,9.0,7,49,Rural,Data Analyst,73254,0 +62431,Female,25,High School,1,62,38,82,95,3.0,7,95,Rural,ML Engineer,86464,1 +62432,Male,36,Masters,9,42,81,12,16,8.0,1,40,Semi-Urban,Data Analyst,46015,0 +62433,Male,57,Masters,12,92,36,62,55,1.0,3,49,Rural,Manager,133982,1 +62434,Male,28,Bachelors,2,0,12,80,72,4.0,5,80,Urban,HR Executive,139826,0 +62435,Female,38,Masters,1,19,71,66,99,4.0,5,31,Urban,ML Engineer,21351,0 +62436,Male,39,PhD,12,97,71,25,66,6.0,1,26,Semi-Urban,HR Executive,33416,0 +62437,Male,50,Masters,7,43,51,63,21,1.0,1,92,Semi-Urban,Software Engineer,34708,1 +62438,Female,55,Masters,6,7,30,14,5,1.0,1,89,Urban,ML Engineer,56677,0 +62439,Male,36,Diploma,11,1,38,29,70,3.0,4,30,Urban,Data Analyst,67293,0 +62440,Male,32,Diploma,12,90,50,69,44,2.0,6,48,Urban,Software Engineer,132317,1 +62441,Male,29,Masters,14,29,66,52,26,3.0,5,3,Urban,Data Analyst,98233,0 +62442,Male,57,Bachelors,19,1,78,9,76,0.0,3,99,Urban,Manager,98967,0 +62443,Male,54,Masters,12,83,54,87,68,7.0,2,93,Urban,HR Executive,129410,1 +62444,Male,37,Bachelors,5,58,80,24,61,5.0,5,0,Urban,ML Engineer,60025,0 +62445,Male,44,Bachelors,7,67,7,84,5,8.0,2,4,Urban,Software Engineer,88595,0 +62446,Female,54,Diploma,11,49,25,52,69,0.0,6,68,Semi-Urban,ML Engineer,122347,0 +62447,Male,53,Bachelors,1,86,64,4,23,3.0,6,74,Semi-Urban,Manager,50070,0 +62448,Male,26,Bachelors,2,79,80,19,27,6.0,5,84,Semi-Urban,ML Engineer,53052,1 +62449,Male,54,Bachelors,14,57,17,26,25,1.0,2,61,Urban,Software Engineer,94646,0 +62450,Female,47,High School,3,44,23,70,41,5.0,3,60,Semi-Urban,Data Analyst,89868,0 +62451,Male,40,Diploma,5,4,9,60,72,2.0,3,42,Urban,Software Engineer,74943,0 +62452,Male,27,Diploma,15,3,36,80,47,3.0,2,34,Urban,ML Engineer,48043,0 +62453,Male,33,Bachelors,1,15,96,15,1,3.0,1,58,Urban,Data Analyst,76129,0 +62454,Female,34,Bachelors,3,70,31,8,89,7.0,7,31,Urban,Data Analyst,47017,0 +62455,Female,47,Bachelors,12,71,65,91,49,0.0,1,58,Urban,HR Executive,143456,1 +62456,Male,34,Masters,12,79,38,93,19,2.0,0,39,Urban,Data Analyst,140261,1 +62457,Female,21,Masters,3,65,56,98,45,7.0,5,56,Urban,Software Engineer,65089,1 +62458,Male,21,Masters,18,81,99,5,58,3.0,6,51,Urban,Software Engineer,46841,1 +62459,Male,35,Masters,13,1,75,62,32,9.0,3,47,Rural,Manager,27199,0 +62460,Male,59,Masters,1,94,84,28,3,9.0,2,29,Rural,Software Engineer,26723,1 +62461,Female,55,High School,18,44,96,86,99,1.0,4,62,Urban,ML Engineer,98426,1 +62462,Female,28,Diploma,1,0,50,90,95,5.0,1,47,Urban,ML Engineer,22308,0 +62463,Male,52,Masters,10,80,31,84,95,8.0,0,85,Urban,Manager,144474,1 +62464,Male,35,Masters,15,39,0,59,43,5.0,7,12,Urban,Manager,78751,0 +62465,Female,58,Bachelors,1,5,16,32,40,3.0,0,81,Urban,HR Executive,46091,0 +62466,Male,39,Masters,16,55,37,71,74,1.0,5,8,Urban,HR Executive,34682,0 +62467,Male,42,Bachelors,10,80,96,66,24,3.0,6,33,Urban,Data Analyst,38733,1 +62468,Female,27,PhD,4,76,2,82,23,4.0,5,87,Urban,ML Engineer,82220,1 +62469,Male,26,High School,14,30,33,63,80,6.0,3,39,Urban,ML Engineer,104663,0 +62470,Female,53,Diploma,3,99,64,43,94,7.0,4,22,Urban,HR Executive,140373,0 +62471,Male,54,Bachelors,5,2,10,13,77,5.0,5,68,Semi-Urban,HR Executive,52423,0 +62472,Male,40,Bachelors,19,78,24,23,11,6.0,3,30,Semi-Urban,Manager,119102,0 +62473,Female,49,Bachelors,10,82,48,74,10,4.0,4,66,Urban,ML Engineer,136167,1 +62474,Female,45,PhD,3,0,45,93,64,8.0,7,63,Urban,Data Analyst,47665,0 +62475,Female,30,Diploma,6,80,7,70,88,2.0,6,74,Urban,HR Executive,94992,0 +62476,Male,34,Diploma,8,35,12,56,91,8.0,1,42,Urban,ML Engineer,37915,0 +62477,Male,59,Masters,9,67,73,69,93,8.0,6,20,Semi-Urban,ML Engineer,144028,0 +62478,Male,41,Masters,14,69,43,4,11,1.0,6,60,Urban,Manager,72548,0 +62479,Female,39,High School,17,76,96,55,98,4.0,3,92,Semi-Urban,ML Engineer,60610,1 +62480,Female,49,High School,18,37,70,11,72,3.0,0,23,Rural,ML Engineer,137375,0 +62481,Female,23,Bachelors,14,18,48,90,15,6.0,6,42,Urban,Manager,102544,0 +62482,Male,26,Masters,15,50,51,23,65,7.0,6,54,Urban,Manager,138738,0 +62483,Female,57,Masters,3,23,58,54,75,6.0,3,69,Semi-Urban,ML Engineer,63112,0 +62484,Male,39,Bachelors,1,2,6,65,31,8.0,1,18,Semi-Urban,ML Engineer,129491,0 +62485,Male,38,Bachelors,12,61,98,94,90,3.0,4,63,Rural,Manager,136012,1 +62486,Female,40,Diploma,12,10,98,3,87,8.0,6,64,Urban,Software Engineer,24903,0 +62487,Male,42,Bachelors,3,44,41,63,82,3.0,4,47,Urban,Software Engineer,65621,0 +62488,Male,26,Bachelors,14,64,33,83,80,8.0,5,4,Semi-Urban,Data Analyst,30528,0 +62489,Female,44,Diploma,19,27,54,97,51,4.0,4,78,Semi-Urban,ML Engineer,55106,1 +62490,Male,48,Diploma,2,77,61,4,10,0.0,3,94,Rural,Software Engineer,21423,1 +62491,Male,47,Bachelors,18,60,28,64,20,4.0,3,72,Urban,HR Executive,144028,0 +62492,Female,34,Diploma,2,47,8,4,95,1.0,1,79,Urban,Software Engineer,137355,0 +62493,Male,26,Bachelors,11,15,78,80,68,6.0,3,58,Urban,HR Executive,126121,0 +62494,Female,44,Bachelors,3,21,22,42,33,3.0,6,11,Urban,Manager,44808,0 +62495,Male,49,Masters,16,54,87,2,75,3.0,1,3,Semi-Urban,Software Engineer,113639,0 +62496,Female,40,High School,18,41,49,7,59,6.0,6,44,Urban,HR Executive,135889,0 +62497,Female,38,Masters,14,8,11,87,33,9.0,7,34,Urban,ML Engineer,40974,0 +62498,Female,55,High School,14,9,26,39,36,5.0,2,63,Semi-Urban,HR Executive,117924,0 +62499,Female,51,Masters,10,70,82,22,90,8.0,7,26,Urban,ML Engineer,47080,0 +62500,Female,39,Bachelors,15,30,13,18,5,4.0,3,70,Semi-Urban,Software Engineer,54680,0 +62501,Male,39,Masters,10,80,47,22,20,5.0,5,37,Semi-Urban,ML Engineer,23721,0 +62502,Male,37,Masters,6,75,45,97,5,4.0,1,92,Urban,ML Engineer,140825,1 +62503,Female,24,PhD,13,54,91,72,76,4.0,6,19,Rural,ML Engineer,94074,0 +62504,Female,48,Diploma,13,77,94,24,1,5.0,6,78,Rural,Manager,119332,1 +62505,Female,33,Bachelors,6,2,17,77,17,4.0,3,24,Semi-Urban,Software Engineer,139607,0 +62506,Female,52,Masters,2,94,28,79,83,3.0,0,48,Rural,Software Engineer,33943,1 +62507,Female,40,Masters,7,12,2,71,98,4.0,0,40,Rural,Manager,95007,0 +62508,Female,51,Bachelors,15,24,78,17,10,7.0,4,43,Urban,Data Analyst,109969,0 +62509,Female,37,Bachelors,12,91,40,53,78,9.0,2,39,Semi-Urban,Data Analyst,114398,0 +62510,Male,45,Bachelors,18,32,79,77,25,6.0,2,83,Urban,ML Engineer,72208,1 +62511,Male,32,Bachelors,4,75,35,95,5,4.0,7,16,Urban,Manager,118643,0 +62512,Other,59,Masters,10,37,85,90,3,0.0,0,68,Semi-Urban,Manager,41647,1 +62513,Male,30,Bachelors,6,55,94,62,91,1.0,4,24,Rural,ML Engineer,93769,1 +62514,Male,52,Masters,14,95,17,43,1,1.0,0,21,Urban,HR Executive,47210,0 +62515,Female,53,Bachelors,6,5,39,24,75,7.0,2,61,Semi-Urban,HR Executive,32796,0 +62516,Female,58,Diploma,12,3,69,41,79,3.0,5,64,Semi-Urban,Manager,129064,0 +62517,Male,58,Diploma,6,28,30,4,61,9.0,7,46,Rural,Software Engineer,143624,0 +62518,Male,43,High School,15,42,36,4,25,3.0,7,22,Rural,Data Analyst,33270,0 +62519,Female,24,Masters,18,64,94,67,56,8.0,6,21,Urban,Manager,35691,1 +62520,Female,32,Bachelors,13,69,82,40,59,8.0,1,29,Semi-Urban,Software Engineer,24213,0 +62521,Male,24,PhD,7,52,66,85,17,0.0,1,72,Rural,Software Engineer,133446,1 +62522,Female,51,Bachelors,12,65,39,52,73,0.0,6,81,Rural,ML Engineer,89051,0 +62523,Male,37,Diploma,12,4,26,67,6,2.0,7,0,Urban,Software Engineer,86583,0 +62524,Male,52,Masters,13,41,56,58,61,3.0,0,5,Urban,Software Engineer,71018,0 +62525,Other,21,High School,6,92,23,20,95,3.0,2,21,Rural,Data Analyst,106080,0 +62526,Male,39,Masters,4,78,48,73,75,1.0,5,61,Urban,ML Engineer,32251,1 +62527,Male,24,Diploma,5,14,73,55,14,1.0,6,40,Semi-Urban,ML Engineer,66437,0 +62528,Male,27,Masters,0,81,36,72,55,7.0,1,56,Urban,ML Engineer,69171,1 +62529,Male,51,High School,0,98,1,39,40,6.0,5,43,Urban,Software Engineer,70809,0 +62530,Other,42,High School,15,83,75,60,44,0.0,2,5,Urban,HR Executive,49923,0 +62531,Male,33,High School,5,17,62,54,62,6.0,1,34,Urban,Software Engineer,21309,0 +62532,Male,48,High School,2,19,79,15,53,0.0,7,95,Urban,Manager,31027,0 +62533,Female,38,Diploma,15,74,50,24,8,3.0,2,91,Rural,Software Engineer,98410,0 +62534,Male,23,Masters,8,88,34,19,91,7.0,0,66,Urban,Data Analyst,29999,0 +62535,Female,42,PhD,6,75,2,32,82,8.0,0,38,Urban,ML Engineer,37749,0 +62536,Male,44,Bachelors,17,43,2,88,45,7.0,5,39,Urban,ML Engineer,99805,0 +62537,Male,34,Masters,0,56,10,59,21,7.0,0,87,Semi-Urban,Data Analyst,69622,0 +62538,Other,27,High School,4,85,50,32,7,6.0,4,67,Urban,Data Analyst,149172,0 +62539,Male,29,High School,6,7,48,94,14,1.0,5,59,Urban,ML Engineer,101913,0 +62540,Female,32,Masters,14,18,86,52,77,5.0,2,39,Urban,ML Engineer,40719,0 +62541,Female,50,Masters,5,13,25,78,2,9.0,5,91,Semi-Urban,HR Executive,49374,0 +62542,Male,59,Diploma,6,24,45,49,4,5.0,0,61,Urban,Data Analyst,136513,0 +62543,Male,23,High School,0,65,70,15,94,1.0,4,28,Urban,HR Executive,84107,0 +62544,Female,24,Bachelors,14,72,48,66,45,3.0,0,6,Urban,Software Engineer,81164,0 +62545,Female,51,Bachelors,12,43,84,18,98,6.0,3,68,Urban,Software Engineer,132913,0 +62546,Male,51,High School,10,40,16,47,94,0.0,4,15,Rural,Data Analyst,126192,0 +62547,Female,27,Masters,11,24,58,67,28,9.0,0,49,Rural,Data Analyst,81064,0 +62548,Female,54,High School,5,19,66,81,33,7.0,3,52,Urban,Data Analyst,43593,0 +62549,Male,41,Bachelors,4,94,87,44,55,4.0,3,20,Urban,Manager,134588,1 +62550,Male,42,Bachelors,11,11,47,86,0,8.0,5,80,Urban,Software Engineer,71338,0 +62551,Male,34,Masters,11,15,57,25,5,5.0,3,81,Urban,Manager,94677,0 +62552,Female,33,Diploma,5,87,67,65,32,9.0,4,51,Rural,Data Analyst,53391,1 +62553,Female,50,Bachelors,12,96,20,79,37,4.0,4,31,Rural,HR Executive,75070,0 +62554,Female,23,Diploma,5,33,92,99,89,7.0,4,28,Urban,ML Engineer,122494,1 +62555,Male,59,PhD,4,67,13,30,22,2.0,2,56,Urban,Manager,116811,0 +62556,Female,23,Masters,11,43,19,14,4,8.0,2,29,Urban,Manager,67755,0 +62557,Female,30,Bachelors,18,43,97,74,63,8.0,1,76,Rural,Data Analyst,80787,1 +62558,Female,38,Diploma,3,76,46,95,39,4.0,0,61,Semi-Urban,Software Engineer,68740,1 +62559,Female,48,Diploma,17,96,41,73,2,0.0,5,69,Rural,Software Engineer,87070,1 +62560,Female,29,High School,10,37,27,33,90,4.0,4,46,Urban,Manager,80975,0 +62561,Female,48,Bachelors,15,40,60,52,76,2.0,0,42,Semi-Urban,HR Executive,143604,0 +62562,Female,54,Bachelors,10,47,98,17,2,9.0,0,44,Semi-Urban,Software Engineer,47023,0 +62563,Male,46,Bachelors,11,47,42,62,65,2.0,4,66,Semi-Urban,Manager,76443,0 +62564,Female,51,Masters,14,6,0,9,31,5.0,2,78,Semi-Urban,Data Analyst,26769,0 +62565,Female,44,Masters,2,4,96,92,53,8.0,7,99,Semi-Urban,Data Analyst,30930,1 +62566,Male,42,High School,18,92,52,49,68,0.0,2,9,Urban,Software Engineer,89718,0 +62567,Male,47,Diploma,3,65,48,45,71,3.0,2,22,Rural,Data Analyst,65495,0 +62568,Female,57,Masters,18,42,17,23,61,4.0,3,94,Semi-Urban,ML Engineer,63920,0 +62569,Male,59,High School,11,89,29,74,97,0.0,5,50,Urban,HR Executive,83300,1 +62570,Male,59,Bachelors,2,7,86,31,95,9.0,2,14,Urban,ML Engineer,137711,0 +62571,Male,47,Diploma,15,26,7,47,54,8.0,2,55,Urban,ML Engineer,64714,0 +62572,Male,33,Bachelors,5,8,97,34,99,1.0,2,38,Urban,ML Engineer,69932,0 +62573,Female,21,High School,13,63,0,65,52,0.0,5,13,Urban,Data Analyst,79350,0 +62574,Female,41,Masters,14,61,42,72,48,2.0,3,57,Urban,Software Engineer,28585,0 +62575,Male,26,Diploma,10,36,62,74,24,7.0,7,15,Rural,HR Executive,31050,0 +62576,Male,58,Diploma,8,68,58,20,86,0.0,4,63,Rural,Data Analyst,38928,0 +62577,Male,31,Masters,18,1,69,54,6,8.0,5,50,Urban,HR Executive,111979,0 +62578,Male,24,Bachelors,16,7,97,56,2,5.0,5,23,Rural,HR Executive,51482,0 +62579,Male,23,Masters,5,12,58,33,86,2.0,6,18,Semi-Urban,Data Analyst,63650,0 +62580,Female,55,Bachelors,3,23,1,30,84,1.0,0,1,Semi-Urban,Data Analyst,51957,0 +62581,Female,39,Diploma,0,13,86,87,36,6.0,2,8,Rural,HR Executive,124457,0 +62582,Female,34,Diploma,17,22,47,61,13,8.0,0,0,Semi-Urban,Manager,139813,0 +62583,Female,54,Diploma,15,75,89,1,24,3.0,3,68,Urban,Software Engineer,92973,0 +62584,Female,53,Masters,3,46,72,74,58,3.0,1,4,Urban,Software Engineer,114748,0 +62585,Female,21,Bachelors,18,56,80,9,19,6.0,2,62,Urban,Manager,40673,0 +62586,Other,50,Masters,19,30,83,84,22,6.0,4,76,Urban,Manager,55195,1 +62587,Female,46,PhD,14,34,97,95,64,8.0,0,90,Rural,Software Engineer,61652,1 +62588,Female,31,Bachelors,9,4,40,69,10,2.0,7,79,Urban,HR Executive,146867,0 +62589,Female,32,Bachelors,16,43,60,25,46,7.0,3,11,Rural,HR Executive,49763,0 +62590,Male,21,Bachelors,10,80,9,49,72,2.0,2,99,Urban,HR Executive,35253,1 +62591,Other,29,Bachelors,4,39,9,74,31,7.0,1,57,Urban,ML Engineer,112295,0 +62592,Male,50,Masters,2,60,83,32,42,5.0,4,49,Urban,Manager,53490,0 +62593,Female,33,Diploma,16,26,36,96,44,1.0,3,76,Rural,HR Executive,89378,0 +62594,Male,50,High School,4,12,36,22,57,0.0,7,93,Urban,Data Analyst,78332,0 +62595,Female,35,PhD,10,40,88,87,85,3.0,0,3,Urban,ML Engineer,135487,0 +62596,Other,49,Bachelors,15,22,90,77,56,2.0,6,22,Rural,Manager,67324,0 +62597,Male,44,Masters,5,50,71,30,81,6.0,0,31,Semi-Urban,Software Engineer,34521,0 +62598,Female,34,High School,6,60,5,63,56,4.0,3,18,Semi-Urban,HR Executive,46529,0 +62599,Male,56,Diploma,7,41,3,80,84,6.0,7,34,Urban,Data Analyst,54775,0 +62600,Male,22,Bachelors,13,78,92,13,76,2.0,3,64,Urban,Manager,65558,1 +62601,Male,21,Bachelors,7,51,96,99,72,1.0,5,34,Urban,Data Analyst,124270,1 +62602,Male,49,Bachelors,3,33,81,89,64,2.0,4,75,Rural,Manager,86347,1 +62603,Female,50,Masters,13,73,47,12,12,6.0,0,65,Semi-Urban,HR Executive,47291,0 +62604,Female,23,PhD,1,71,91,43,96,2.0,1,80,Rural,Software Engineer,27087,1 +62605,Male,35,High School,15,15,6,28,55,5.0,5,42,Rural,HR Executive,68162,0 +62606,Male,27,Bachelors,11,16,68,55,15,7.0,6,53,Urban,Data Analyst,148492,0 +62607,Male,54,Bachelors,19,43,93,31,62,1.0,6,87,Urban,Manager,54784,1 +62608,Male,42,Diploma,0,95,61,27,85,8.0,7,41,Semi-Urban,Manager,99099,0 +62609,Male,35,Masters,19,67,8,92,1,8.0,4,35,Rural,Software Engineer,52121,0 +62610,Male,34,High School,12,34,13,7,91,7.0,2,49,Urban,HR Executive,145044,0 +62611,Male,30,Bachelors,9,48,94,67,51,0.0,0,20,Urban,Software Engineer,33705,0 +62612,Female,34,Diploma,4,63,62,36,53,3.0,2,88,Urban,Software Engineer,112546,1 +62613,Male,39,Masters,3,75,71,47,61,7.0,1,10,Urban,ML Engineer,140791,0 +62614,Female,58,High School,18,1,86,21,75,2.0,4,79,Urban,HR Executive,43335,0 +62615,Male,49,Bachelors,13,51,64,21,75,3.0,2,68,Rural,Data Analyst,110107,0 +62616,Female,42,Bachelors,15,15,67,34,5,9.0,4,92,Urban,Data Analyst,125021,0 +62617,Female,57,Diploma,18,43,65,74,30,5.0,5,94,Rural,ML Engineer,57278,1 +62618,Male,36,Bachelors,4,6,82,80,41,6.0,5,59,Urban,ML Engineer,149728,0 +62619,Other,55,Bachelors,8,51,73,11,55,7.0,0,66,Semi-Urban,Manager,118502,0 +62620,Male,29,Bachelors,15,4,43,10,93,2.0,4,5,Semi-Urban,Software Engineer,39467,0 +62621,Male,46,PhD,3,56,89,44,30,3.0,3,16,Urban,HR Executive,135112,0 +62622,Male,32,Diploma,8,55,20,24,12,1.0,6,28,Semi-Urban,Data Analyst,136294,0 +62623,Male,21,Bachelors,6,98,20,88,47,1.0,3,97,Urban,Software Engineer,140779,1 +62624,Male,58,PhD,15,40,43,92,11,0.0,0,20,Rural,Software Engineer,93001,0 +62625,Female,58,Masters,18,9,49,6,33,1.0,2,82,Urban,Data Analyst,26853,0 +62626,Male,55,Masters,11,79,13,84,48,2.0,7,79,Urban,Software Engineer,53058,1 +62627,Female,26,High School,12,19,59,68,16,4.0,7,65,Urban,Software Engineer,44801,0 +62628,Other,30,Bachelors,15,90,46,70,50,7.0,2,80,Urban,Software Engineer,123127,1 +62629,Male,29,Masters,17,71,61,37,79,7.0,3,39,Urban,HR Executive,42368,0 +62630,Male,55,Masters,11,66,18,33,26,4.0,4,34,Semi-Urban,ML Engineer,67122,0 +62631,Other,44,PhD,13,34,4,96,41,4.0,0,53,Urban,HR Executive,78933,0 +62632,Female,29,High School,11,2,5,69,50,9.0,7,53,Semi-Urban,ML Engineer,70095,0 +62633,Female,36,Diploma,1,80,51,81,47,5.0,0,65,Rural,HR Executive,31900,1 +62634,Male,44,High School,2,9,76,97,11,3.0,6,8,Urban,Manager,85228,0 +62635,Female,30,Bachelors,14,36,54,86,52,7.0,7,16,Semi-Urban,Data Analyst,59079,0 +62636,Male,52,Diploma,0,85,4,1,61,2.0,7,91,Semi-Urban,Data Analyst,147325,0 +62637,Female,51,Bachelors,11,17,29,15,65,7.0,4,57,Semi-Urban,Data Analyst,89426,0 +62638,Female,55,Bachelors,13,33,53,22,23,1.0,2,60,Semi-Urban,Data Analyst,144095,0 +62639,Male,32,Bachelors,0,30,26,6,38,7.0,0,76,Urban,Manager,106804,0 +62640,Male,40,Masters,3,97,72,36,3,8.0,0,61,Urban,Data Analyst,58894,1 +62641,Male,43,Diploma,19,45,36,76,10,2.0,1,41,Urban,Manager,68593,0 +62642,Female,54,Bachelors,4,94,72,44,16,6.0,1,12,Urban,Software Engineer,96145,0 +62643,Male,51,Bachelors,19,47,49,24,8,4.0,1,23,Urban,Manager,85376,0 +62644,Female,27,Bachelors,8,54,63,79,40,1.0,5,70,Urban,Manager,55051,1 +62645,Male,43,Bachelors,11,76,4,70,40,1.0,3,80,Urban,Manager,30931,0 +62646,Female,38,High School,9,58,45,57,51,5.0,2,52,Rural,Software Engineer,98392,0 +62647,Male,55,Bachelors,13,96,31,69,58,9.0,2,70,Rural,HR Executive,77352,1 +62648,Male,30,High School,16,47,79,12,75,4.0,6,34,Semi-Urban,HR Executive,129087,0 +62649,Male,25,Diploma,7,69,53,49,0,0.0,1,58,Semi-Urban,ML Engineer,134694,0 +62650,Male,47,Bachelors,4,13,32,87,49,7.0,1,63,Urban,Software Engineer,98098,0 +62651,Male,54,Bachelors,18,75,79,13,11,6.0,7,3,Rural,Manager,54845,0 +62652,Female,59,Bachelors,19,87,21,9,51,3.0,2,18,Rural,ML Engineer,39550,0 +62653,Other,25,Bachelors,1,46,35,32,37,6.0,0,14,Urban,HR Executive,45358,0 +62654,Male,47,Bachelors,15,79,60,79,62,5.0,0,30,Rural,Software Engineer,56284,1 +62655,Female,57,Bachelors,14,64,23,40,31,7.0,7,2,Urban,HR Executive,24329,0 +62656,Male,50,Masters,8,51,7,33,24,0.0,1,69,Urban,Manager,123158,0 +62657,Female,37,Masters,9,42,81,39,32,9.0,2,77,Urban,HR Executive,54335,0 +62658,Male,48,High School,5,66,94,70,60,6.0,1,28,Urban,Manager,112543,1 +62659,Male,47,Diploma,1,79,62,6,32,0.0,1,27,Urban,HR Executive,117044,0 +62660,Female,56,Bachelors,6,65,25,72,49,1.0,2,95,Urban,HR Executive,83204,1 +62661,Female,38,Masters,17,95,26,87,40,3.0,5,56,Urban,Software Engineer,54373,1 +62662,Male,49,Diploma,8,51,29,54,96,4.0,4,16,Urban,Manager,67968,0 +62663,Male,37,Bachelors,10,67,43,89,95,2.0,4,36,Urban,Data Analyst,25870,1 +62664,Female,51,High School,16,71,89,19,90,5.0,4,17,Urban,Data Analyst,55080,0 +62665,Female,43,Bachelors,15,16,56,11,3,9.0,6,9,Rural,Software Engineer,35376,0 +62666,Female,46,High School,2,38,29,9,88,8.0,1,73,Urban,Manager,134668,0 +62667,Male,53,Bachelors,11,46,67,10,48,6.0,0,93,Semi-Urban,ML Engineer,26771,0 +62668,Female,28,Diploma,11,20,70,12,71,1.0,1,13,Urban,Software Engineer,90406,0 +62669,Male,27,Diploma,11,84,68,6,41,6.0,1,91,Semi-Urban,HR Executive,87606,1 +62670,Female,54,Bachelors,1,17,84,84,96,3.0,0,41,Rural,HR Executive,139673,0 +62671,Male,39,Bachelors,2,69,73,6,16,4.0,7,67,Urban,HR Executive,39927,0 +62672,Female,40,Diploma,13,83,47,75,97,2.0,7,68,Urban,Data Analyst,26122,1 +62673,Female,33,Diploma,4,98,13,40,88,0.0,0,3,Urban,Software Engineer,133408,0 +62674,Male,29,Masters,3,98,63,68,37,8.0,3,92,Rural,HR Executive,76554,1 +62675,Male,31,Diploma,18,48,24,44,67,2.0,1,45,Rural,Manager,32322,0 +62676,Female,29,PhD,1,37,35,37,76,7.0,6,19,Rural,ML Engineer,51568,0 +62677,Male,55,Diploma,0,5,47,75,10,2.0,1,54,Semi-Urban,HR Executive,34868,0 +62678,Female,44,Diploma,10,29,44,21,9,1.0,7,85,Urban,Data Analyst,119603,0 +62679,Female,41,Masters,19,4,77,58,82,3.0,7,5,Semi-Urban,Data Analyst,60519,0 +62680,Male,44,High School,7,98,19,87,19,9.0,3,31,Semi-Urban,Data Analyst,92108,1 +62681,Male,21,High School,11,53,47,58,91,5.0,1,7,Urban,Software Engineer,24028,0 +62682,Female,26,Masters,0,27,47,60,30,7.0,1,28,Urban,Manager,40026,0 +62683,Female,44,Bachelors,8,29,73,24,68,4.0,3,51,Urban,HR Executive,41473,0 +62684,Male,43,Bachelors,15,11,43,92,36,3.0,2,4,Rural,HR Executive,94943,0 +62685,Female,51,Masters,19,21,40,66,85,0.0,3,56,Urban,Data Analyst,146144,0 +62686,Male,25,Bachelors,6,93,99,42,17,3.0,1,47,Urban,HR Executive,81959,1 +62687,Female,58,Bachelors,16,60,78,6,60,9.0,6,79,Urban,Software Engineer,66645,0 +62688,Male,21,Diploma,12,52,15,45,9,3.0,4,29,Semi-Urban,Software Engineer,69490,0 +62689,Other,49,Bachelors,5,69,84,60,98,2.0,3,29,Urban,Software Engineer,40583,1 +62690,Female,45,High School,14,8,65,22,16,0.0,7,94,Semi-Urban,Data Analyst,54766,0 +62691,Male,29,Diploma,8,39,54,78,93,1.0,5,19,Urban,HR Executive,71533,0 +62692,Female,49,Bachelors,1,41,89,63,83,3.0,1,38,Urban,ML Engineer,22011,0 +62693,Female,24,Masters,6,47,53,71,70,3.0,7,14,Semi-Urban,Data Analyst,128761,0 +62694,Female,33,High School,13,43,80,27,51,7.0,3,10,Urban,Software Engineer,40430,0 +62695,Male,34,High School,4,14,29,29,72,4.0,1,34,Urban,ML Engineer,31027,0 +62696,Male,37,High School,13,93,91,60,18,4.0,5,45,Urban,Software Engineer,66743,1 +62697,Female,42,High School,1,88,74,39,24,0.0,6,1,Urban,Manager,124048,0 +62698,Female,57,Masters,11,23,74,32,24,1.0,4,54,Semi-Urban,ML Engineer,50759,0 +62699,Male,50,Bachelors,9,2,44,31,87,1.0,7,10,Semi-Urban,Software Engineer,21383,0 +62700,Male,56,Masters,2,42,1,26,14,6.0,1,46,Urban,Data Analyst,76674,0 +62701,Male,42,Diploma,4,73,92,24,19,7.0,2,4,Semi-Urban,ML Engineer,51973,0 +62702,Male,38,High School,15,94,4,55,1,4.0,5,79,Semi-Urban,Software Engineer,109495,0 +62703,Male,22,Bachelors,16,54,89,65,82,1.0,4,12,Rural,ML Engineer,29489,0 +62704,Male,28,Masters,19,6,84,63,45,0.0,4,23,Semi-Urban,HR Executive,67849,0 +62705,Female,26,Bachelors,8,14,94,70,31,5.0,2,28,Semi-Urban,ML Engineer,98101,0 +62706,Male,43,Masters,6,93,97,83,50,9.0,5,6,Semi-Urban,Data Analyst,120793,1 +62707,Male,23,Bachelors,0,82,45,59,26,8.0,2,43,Rural,Manager,41147,0 +62708,Male,24,Diploma,1,47,34,84,9,6.0,6,58,Urban,Data Analyst,149127,0 +62709,Female,21,PhD,19,32,47,14,47,6.0,5,28,Semi-Urban,ML Engineer,100180,0 +62710,Female,47,High School,3,36,1,34,88,2.0,0,48,Rural,Software Engineer,45096,0 +62711,Female,57,Bachelors,10,4,44,30,64,0.0,7,73,Urban,ML Engineer,22098,0 +62712,Female,27,PhD,15,65,33,99,62,8.0,5,81,Semi-Urban,Data Analyst,61913,1 +62713,Female,51,Diploma,0,82,93,81,61,5.0,7,31,Urban,Manager,79634,1 +62714,Male,47,Masters,1,97,65,67,47,3.0,4,90,Urban,Software Engineer,46105,1 +62715,Male,27,Bachelors,7,55,49,78,54,4.0,3,34,Semi-Urban,ML Engineer,70269,0 +62716,Male,23,Bachelors,18,25,6,1,41,2.0,4,10,Urban,Data Analyst,144167,0 +62717,Male,21,Masters,13,43,70,0,84,2.0,7,50,Urban,Manager,44551,0 +62718,Male,40,Bachelors,9,8,12,79,72,5.0,3,72,Urban,HR Executive,135804,0 +62719,Female,42,Diploma,2,80,75,6,91,8.0,5,49,Rural,HR Executive,60488,0 +62720,Female,34,Masters,15,53,36,70,22,0.0,1,45,Urban,Software Engineer,125845,0 +62721,Male,58,Diploma,6,4,15,17,42,5.0,2,53,Urban,HR Executive,56850,0 +62722,Female,57,Diploma,17,64,4,14,87,8.0,1,16,Urban,Software Engineer,82297,0 +62723,Male,50,Diploma,9,30,17,86,18,6.0,2,3,Rural,Software Engineer,87591,0 +62724,Female,57,Bachelors,9,52,21,40,47,6.0,0,51,Rural,HR Executive,85861,0 +62725,Male,59,Bachelors,1,12,36,87,76,8.0,6,92,Semi-Urban,Software Engineer,74747,0 +62726,Male,54,Bachelors,15,3,89,97,38,2.0,2,82,Semi-Urban,ML Engineer,122018,1 +62727,Male,45,Masters,12,11,85,92,85,9.0,0,87,Rural,Software Engineer,39801,1 +62728,Female,53,Diploma,3,17,27,36,21,9.0,0,44,Semi-Urban,Software Engineer,136148,0 +62729,Male,33,Masters,6,59,18,35,52,4.0,5,0,Urban,ML Engineer,88433,0 +62730,Male,46,Bachelors,18,13,23,65,80,8.0,7,93,Urban,Data Analyst,58418,0 +62731,Female,58,Masters,16,13,43,71,82,0.0,3,12,Rural,HR Executive,80764,0 +62732,Female,52,Masters,7,15,40,64,49,1.0,3,0,Semi-Urban,Data Analyst,58930,0 +62733,Male,38,Diploma,0,29,31,67,26,8.0,1,32,Urban,HR Executive,89895,0 +62734,Male,45,Bachelors,18,72,8,1,88,4.0,7,94,Semi-Urban,Data Analyst,112167,0 +62735,Female,39,Masters,15,81,10,21,21,3.0,2,70,Semi-Urban,ML Engineer,64413,0 +62736,Male,46,Bachelors,3,43,72,81,63,3.0,1,86,Rural,ML Engineer,132187,1 +62737,Female,46,High School,19,38,82,35,28,8.0,4,71,Urban,HR Executive,118747,0 +62738,Female,57,Bachelors,17,2,44,44,25,2.0,7,75,Urban,Software Engineer,22206,0 +62739,Male,44,High School,12,9,98,83,40,0.0,7,11,Urban,ML Engineer,123455,0 +62740,Other,35,Bachelors,7,38,93,98,42,6.0,3,23,Semi-Urban,HR Executive,58688,1 +62741,Female,44,PhD,6,58,17,86,94,1.0,2,42,Urban,Data Analyst,148945,0 +62742,Female,57,High School,3,68,91,44,53,3.0,4,18,Urban,Software Engineer,98910,0 +62743,Male,31,Diploma,18,20,74,1,56,0.0,2,70,Urban,Manager,105083,0 +62744,Female,33,Bachelors,13,62,8,58,44,5.0,5,19,Semi-Urban,Manager,37326,0 +62745,Female,21,Diploma,9,40,59,18,13,8.0,3,44,Urban,HR Executive,104284,0 +62746,Male,37,Bachelors,2,68,99,13,50,0.0,0,64,Urban,Software Engineer,104271,1 +62747,Female,27,High School,9,34,76,43,25,7.0,1,79,Urban,Software Engineer,67758,0 +62748,Male,35,Bachelors,10,41,48,10,64,1.0,4,79,Rural,Data Analyst,119632,0 +62749,Male,33,Bachelors,12,94,18,56,59,2.0,2,33,Urban,Data Analyst,148733,0 +62750,Female,54,Bachelors,9,87,17,91,4,0.0,4,90,Rural,Manager,41627,1 +62751,Male,58,Bachelors,0,12,15,45,9,8.0,5,54,Urban,Data Analyst,80088,0 +62752,Male,50,Bachelors,10,96,34,52,32,7.0,7,23,Semi-Urban,Data Analyst,134975,0 +62753,Male,22,Bachelors,14,3,60,80,33,9.0,2,81,Urban,Software Engineer,129400,0 +62754,Male,56,Masters,12,37,96,64,22,1.0,0,44,Urban,Data Analyst,93137,1 +62755,Male,29,High School,19,54,65,40,38,0.0,7,32,Rural,ML Engineer,102625,0 +62756,Male,44,Masters,13,52,30,4,94,4.0,7,90,Rural,ML Engineer,34275,0 +62757,Female,22,Diploma,6,99,40,30,44,4.0,4,7,Urban,Software Engineer,37684,0 +62758,Female,56,High School,12,82,72,24,43,4.0,6,63,Urban,Data Analyst,113511,1 +62759,Male,24,Diploma,10,69,16,65,51,0.0,2,58,Semi-Urban,Manager,75362,0 +62760,Female,24,High School,11,24,63,64,50,9.0,2,57,Semi-Urban,ML Engineer,95959,0 +62761,Male,37,High School,1,93,55,51,86,9.0,1,46,Rural,ML Engineer,67258,1 +62762,Male,54,High School,6,86,15,0,77,0.0,4,83,Semi-Urban,Software Engineer,53843,0 +62763,Other,26,Bachelors,3,84,97,3,83,8.0,5,0,Urban,HR Executive,83433,0 +62764,Male,36,Masters,11,63,22,80,66,1.0,6,67,Semi-Urban,HR Executive,36386,0 +62765,Male,53,Bachelors,18,67,94,17,48,2.0,0,48,Urban,HR Executive,78288,0 +62766,Male,53,Masters,14,84,15,52,3,5.0,0,9,Semi-Urban,Manager,109258,0 +62767,Other,32,Bachelors,11,70,11,41,91,3.0,5,53,Semi-Urban,ML Engineer,43741,0 +62768,Male,55,Bachelors,2,60,20,18,31,7.0,0,23,Semi-Urban,Software Engineer,32922,0 +62769,Male,32,PhD,16,12,99,87,89,6.0,4,66,Semi-Urban,HR Executive,41331,1 +62770,Female,48,Diploma,19,73,15,64,80,4.0,3,96,Urban,Software Engineer,101059,1 +62771,Male,27,Bachelors,17,44,49,55,14,6.0,2,72,Semi-Urban,Manager,60058,0 +62772,Male,57,Bachelors,19,42,83,0,34,5.0,3,60,Semi-Urban,Software Engineer,41203,0 +62773,Male,43,Masters,1,7,29,26,43,6.0,6,59,Urban,HR Executive,30397,0 +62774,Male,27,Bachelors,12,31,52,27,94,9.0,4,26,Urban,Manager,72390,0 +62775,Male,57,Bachelors,13,46,5,75,43,4.0,2,38,Urban,ML Engineer,78127,0 +62776,Female,21,Diploma,1,19,52,71,91,5.0,7,39,Semi-Urban,Manager,146477,0 +62777,Male,31,Bachelors,10,12,99,31,53,1.0,1,19,Urban,Data Analyst,122514,0 +62778,Male,54,Diploma,0,28,53,98,4,4.0,0,79,Urban,Manager,114541,1 +62779,Female,25,Bachelors,19,51,83,46,25,8.0,1,42,Semi-Urban,Software Engineer,30503,0 +62780,Male,27,Masters,4,55,31,45,40,1.0,1,27,Semi-Urban,HR Executive,93991,0 +62781,Male,47,Bachelors,6,0,26,60,28,1.0,0,93,Urban,HR Executive,92477,0 +62782,Female,28,High School,17,72,23,6,42,4.0,6,76,Semi-Urban,Software Engineer,43644,0 +62783,Other,33,Diploma,18,45,96,77,50,5.0,5,29,Urban,HR Executive,142824,1 +62784,Male,32,Bachelors,19,33,92,63,38,4.0,0,12,Urban,HR Executive,32576,0 +62785,Female,56,Diploma,4,37,97,95,34,9.0,7,19,Urban,ML Engineer,125875,1 +62786,Female,40,Masters,15,50,43,54,37,3.0,2,54,Urban,ML Engineer,88749,0 +62787,Female,58,Masters,17,53,16,72,67,3.0,1,27,Semi-Urban,Manager,59894,0 +62788,Female,47,Bachelors,15,61,11,11,94,9.0,7,91,Urban,Software Engineer,137486,0 +62789,Male,34,Masters,17,77,0,85,92,0.0,1,1,Urban,Data Analyst,86302,0 +62790,Male,45,Diploma,8,32,15,4,83,3.0,5,76,Urban,ML Engineer,79335,0 +62791,Female,26,Diploma,19,68,51,96,91,1.0,5,68,Rural,Manager,32267,1 +62792,Male,26,Diploma,16,72,32,9,2,8.0,4,45,Urban,Manager,63890,0 +62793,Male,49,Bachelors,2,33,50,70,36,5.0,4,38,Rural,HR Executive,98130,0 +62794,Female,56,Bachelors,9,76,49,27,51,6.0,3,29,Urban,HR Executive,132846,0 +62795,Female,21,Masters,0,21,58,24,84,6.0,6,86,Semi-Urban,Manager,34582,0 +62796,Male,29,Bachelors,11,93,72,53,39,9.0,5,67,Rural,Data Analyst,105472,1 +62797,Male,45,Masters,1,38,71,36,89,7.0,7,10,Urban,ML Engineer,30186,0 +62798,Male,31,Diploma,1,37,75,55,73,5.0,0,99,Semi-Urban,Data Analyst,56516,1 +62799,Male,52,Bachelors,3,75,20,21,8,6.0,1,49,Urban,Manager,115351,0 +62800,Male,48,Diploma,2,86,1,97,68,3.0,5,35,Urban,Manager,85401,0 +62801,Female,36,Masters,0,68,44,39,67,0.0,5,69,Urban,HR Executive,57271,0 +62802,Female,39,Masters,11,7,35,15,36,2.0,1,43,Urban,Manager,75646,0 +62803,Female,59,High School,14,88,89,22,2,4.0,4,63,Urban,Manager,110069,1 +62804,Male,29,Bachelors,0,80,34,90,64,7.0,4,38,Urban,HR Executive,115139,1 +62805,Male,33,Diploma,4,65,2,77,69,8.0,3,58,Semi-Urban,ML Engineer,140613,0 +62806,Female,45,Diploma,0,76,84,39,61,0.0,4,1,Urban,Manager,24067,0 +62807,Female,48,Masters,15,28,12,69,99,0.0,2,19,Rural,ML Engineer,59492,0 +62808,Female,59,Bachelors,7,53,9,51,66,9.0,5,27,Semi-Urban,Data Analyst,87511,0 +62809,Male,42,Masters,18,41,22,52,53,0.0,1,80,Urban,Data Analyst,45600,0 +62810,Female,27,Bachelors,3,18,71,70,35,2.0,3,4,Semi-Urban,Data Analyst,65838,0 +62811,Female,59,Masters,0,32,10,8,23,8.0,0,82,Semi-Urban,ML Engineer,105458,0 +62812,Male,54,Bachelors,8,47,8,88,41,9.0,4,87,Semi-Urban,ML Engineer,80937,0 +62813,Female,52,High School,8,74,51,23,65,5.0,6,34,Urban,Data Analyst,106902,0 +62814,Female,27,High School,14,64,88,1,94,3.0,3,41,Semi-Urban,Manager,72751,0 +62815,Female,46,High School,9,72,86,75,48,1.0,0,62,Rural,HR Executive,38614,1 +62816,Male,25,Bachelors,16,9,70,96,49,5.0,1,56,Urban,Manager,140828,0 +62817,Male,48,PhD,11,77,89,35,88,4.0,3,41,Rural,ML Engineer,146986,1 +62818,Female,44,Bachelors,15,89,29,15,4,5.0,2,24,Semi-Urban,Software Engineer,80661,0 +62819,Male,51,Bachelors,8,40,93,72,78,8.0,2,22,Urban,Manager,85559,0 +62820,Female,56,Bachelors,16,78,66,78,81,3.0,0,51,Urban,ML Engineer,92421,1 +62821,Female,26,PhD,16,99,14,47,12,3.0,7,24,Semi-Urban,ML Engineer,30655,0 +62822,Female,52,Bachelors,15,85,45,72,37,0.0,3,23,Urban,Data Analyst,51511,0 +62823,Male,42,High School,0,42,10,90,75,3.0,7,99,Rural,HR Executive,121366,1 +62824,Male,29,Diploma,18,47,75,52,99,1.0,1,76,Rural,HR Executive,118961,1 +62825,Male,58,Bachelors,12,37,67,21,71,5.0,2,58,Urban,Data Analyst,53436,0 +62826,Male,43,Bachelors,5,85,46,62,33,8.0,0,31,Rural,HR Executive,77627,0 +62827,Male,48,High School,13,42,72,88,87,9.0,0,23,Urban,Software Engineer,71696,0 +62828,Male,47,Bachelors,9,55,23,15,43,0.0,0,78,Urban,Manager,108503,0 +62829,Male,37,Bachelors,13,1,73,19,9,4.0,7,33,Urban,ML Engineer,93647,0 +62830,Male,27,Bachelors,10,72,82,9,81,0.0,3,86,Rural,ML Engineer,103000,1 +62831,Male,54,Bachelors,2,77,84,14,87,7.0,2,3,Urban,Software Engineer,108747,0 +62832,Male,46,High School,6,67,5,31,63,5.0,1,58,Urban,Manager,122562,0 +62833,Male,48,Bachelors,19,46,75,7,44,5.0,3,43,Urban,Data Analyst,56796,0 +62834,Female,48,Bachelors,4,78,65,55,48,6.0,3,65,Urban,HR Executive,143900,1 +62835,Male,59,Masters,11,74,10,10,81,2.0,1,3,Urban,Data Analyst,61173,0 +62836,Male,26,Masters,7,78,19,13,38,2.0,2,99,Rural,ML Engineer,51185,0 +62837,Male,36,Bachelors,11,81,94,52,24,0.0,7,4,Semi-Urban,HR Executive,99909,0 +62838,Male,44,Bachelors,16,3,94,43,23,8.0,6,47,Semi-Urban,HR Executive,26931,0 +62839,Male,44,Masters,0,26,98,16,46,6.0,5,59,Urban,Software Engineer,48489,0 +62840,Female,40,Diploma,17,22,9,8,52,9.0,2,62,Urban,Manager,110977,0 +62841,Other,39,Masters,9,67,42,3,85,2.0,7,94,Urban,Data Analyst,50874,0 +62842,Male,30,Bachelors,5,43,58,32,56,5.0,1,56,Rural,HR Executive,91513,0 +62843,Female,47,Masters,5,24,55,77,91,4.0,0,91,Urban,Manager,117309,1 +62844,Female,36,Masters,2,37,80,2,98,5.0,4,28,Rural,Data Analyst,44825,0 +62845,Male,57,Diploma,2,62,39,7,44,0.0,6,68,Urban,ML Engineer,71557,0 +62846,Male,32,Bachelors,18,54,39,94,16,0.0,7,94,Rural,HR Executive,31983,1 +62847,Male,39,Masters,13,35,98,24,76,9.0,3,16,Semi-Urban,ML Engineer,114265,0 +62848,Female,59,Bachelors,19,93,62,41,29,6.0,7,70,Urban,HR Executive,28069,1 +62849,Male,42,Bachelors,11,97,30,26,58,4.0,7,54,Urban,ML Engineer,42823,0 +62850,Male,38,Diploma,12,92,82,21,93,1.0,2,44,Urban,HR Executive,33162,1 +62851,Female,53,Bachelors,16,7,61,89,25,9.0,0,13,Urban,Software Engineer,60833,0 +62852,Female,49,Diploma,5,95,62,60,69,6.0,3,33,Urban,Software Engineer,27315,1 +62853,Male,51,Bachelors,3,50,0,87,87,5.0,1,49,Semi-Urban,Data Analyst,147002,0 +62854,Male,49,Diploma,2,76,50,90,98,2.0,7,49,Semi-Urban,ML Engineer,49895,1 +62855,Female,56,High School,18,48,45,73,54,0.0,3,15,Urban,Software Engineer,102635,0 +62856,Female,22,Diploma,18,4,95,67,33,8.0,6,47,Urban,HR Executive,85612,0 +62857,Male,31,High School,5,58,54,56,69,9.0,5,0,Semi-Urban,Software Engineer,147683,0 +62858,Male,32,Masters,5,14,82,41,10,4.0,6,29,Rural,HR Executive,99910,0 +62859,Male,46,Bachelors,0,24,33,45,21,2.0,5,66,Urban,Data Analyst,87830,0 +62860,Other,27,Bachelors,15,99,72,11,10,1.0,1,66,Semi-Urban,Data Analyst,67622,1 +62861,Male,51,Bachelors,8,11,98,21,47,3.0,1,95,Semi-Urban,HR Executive,40182,0 +62862,Male,27,Bachelors,6,80,45,12,49,5.0,1,24,Urban,Manager,53894,0 +62863,Male,29,Bachelors,7,85,32,46,68,0.0,7,5,Semi-Urban,Software Engineer,100453,0 +62864,Female,40,Masters,19,46,59,63,74,4.0,1,76,Urban,Software Engineer,76540,1 +62865,Female,28,High School,4,28,28,36,99,5.0,3,92,Rural,ML Engineer,52437,0 +62866,Male,31,Masters,0,87,14,67,45,3.0,1,33,Urban,Data Analyst,80231,0 +62867,Female,45,Bachelors,11,19,41,88,60,8.0,4,9,Rural,Manager,145528,0 +62868,Female,23,Masters,6,38,68,45,32,6.0,4,68,Rural,Software Engineer,20288,0 +62869,Male,40,PhD,6,77,97,97,14,9.0,6,6,Urban,ML Engineer,129175,1 +62870,Male,38,High School,12,29,66,18,49,9.0,4,17,Semi-Urban,Manager,132379,0 +62871,Female,25,High School,16,99,98,42,38,7.0,0,99,Urban,Manager,98357,1 +62872,Male,36,Bachelors,16,67,93,2,20,2.0,3,87,Semi-Urban,Manager,142393,1 +62873,Male,48,Diploma,14,33,82,77,53,2.0,3,93,Urban,Software Engineer,52101,1 +62874,Female,33,PhD,13,88,41,68,57,6.0,2,84,Semi-Urban,Data Analyst,51479,1 +62875,Female,28,High School,3,44,90,48,63,1.0,7,31,Rural,HR Executive,94004,0 +62876,Male,29,Masters,12,64,95,10,94,6.0,3,65,Semi-Urban,ML Engineer,54252,0 +62877,Male,55,High School,12,73,19,89,89,4.0,4,6,Rural,ML Engineer,115204,0 +62878,Female,51,Bachelors,7,84,58,38,46,4.0,5,56,Urban,HR Executive,137153,0 +62879,Male,30,Bachelors,11,66,53,12,85,1.0,5,39,Urban,HR Executive,23029,0 +62880,Female,39,Bachelors,16,89,65,91,40,9.0,2,86,Semi-Urban,Software Engineer,148856,1 +62881,Male,58,Bachelors,14,45,72,88,87,8.0,2,9,Urban,Data Analyst,63490,0 +62882,Male,50,Bachelors,6,40,45,67,23,1.0,7,54,Urban,Manager,87033,0 +62883,Male,49,Masters,17,63,29,53,80,8.0,0,18,Semi-Urban,Manager,77388,0 +62884,Male,26,Diploma,13,42,34,93,22,8.0,7,17,Urban,ML Engineer,149251,0 +62885,Male,55,Masters,0,20,70,7,3,1.0,0,56,Rural,ML Engineer,114442,0 +62886,Male,22,Diploma,7,94,16,32,85,1.0,1,74,Urban,Software Engineer,123532,0 +62887,Female,36,Masters,11,26,5,58,39,1.0,3,63,Semi-Urban,Data Analyst,148183,0 +62888,Male,52,PhD,10,58,32,5,49,3.0,3,41,Semi-Urban,Software Engineer,60056,0 +62889,Male,28,Bachelors,8,3,72,17,81,1.0,5,42,Urban,ML Engineer,39223,0 +62890,Male,27,Bachelors,4,29,26,19,56,7.0,1,23,Semi-Urban,Manager,50049,0 +62891,Male,30,Bachelors,2,67,33,67,62,3.0,3,51,Rural,ML Engineer,121128,0 +62892,Male,46,Masters,13,83,73,4,62,0.0,5,22,Urban,Manager,135911,0 +62893,Male,58,Bachelors,9,88,16,80,86,4.0,1,93,Urban,Software Engineer,23107,1 +62894,Male,46,Bachelors,18,33,15,50,79,7.0,7,35,Semi-Urban,Software Engineer,117328,0 +62895,Male,22,Bachelors,6,99,18,92,18,7.0,0,97,Urban,HR Executive,125404,1 +62896,Male,27,Bachelors,15,80,41,66,34,1.0,1,12,Rural,Data Analyst,137020,0 +62897,Male,43,Bachelors,3,62,27,92,58,4.0,5,78,Semi-Urban,Software Engineer,77812,1 +62898,Male,23,Bachelors,13,83,88,41,27,7.0,7,19,Urban,Manager,28822,0 +62899,Female,45,High School,13,25,19,20,36,5.0,1,7,Urban,Manager,101755,0 +62900,Female,36,High School,7,0,37,34,90,7.0,2,95,Semi-Urban,Data Analyst,21557,0 +62901,Male,50,Diploma,6,60,66,59,6,0.0,2,93,Urban,ML Engineer,77320,1 +62902,Male,46,Masters,4,49,1,35,39,9.0,6,16,Urban,Software Engineer,138260,0 +62903,Female,52,Masters,5,50,27,44,94,1.0,5,41,Semi-Urban,ML Engineer,32443,0 +62904,Other,22,PhD,8,58,22,64,14,0.0,3,12,Urban,Manager,84633,0 +62905,Male,28,Bachelors,10,68,68,52,68,6.0,5,28,Rural,HR Executive,136997,0 +62906,Female,31,Bachelors,7,8,5,98,12,7.0,0,78,Urban,ML Engineer,123894,0 +62907,Male,23,Diploma,3,30,5,45,99,9.0,4,68,Urban,ML Engineer,102980,0 +62908,Male,59,Bachelors,13,65,11,28,43,6.0,4,1,Urban,Data Analyst,63920,0 +62909,Female,37,Diploma,16,27,49,76,57,5.0,7,97,Urban,Manager,54219,1 +62910,Male,49,Masters,5,27,50,78,28,8.0,7,52,Urban,ML Engineer,111612,0 +62911,Male,51,Bachelors,15,24,43,10,79,6.0,3,85,Urban,ML Engineer,69386,0 +62912,Male,28,Bachelors,16,53,99,63,7,1.0,3,50,Semi-Urban,Manager,115122,1 +62913,Female,22,Bachelors,18,39,38,21,72,6.0,0,26,Rural,Data Analyst,89804,0 +62914,Female,54,PhD,5,7,89,24,98,4.0,2,21,Urban,Software Engineer,89729,0 +62915,Male,50,Bachelors,6,18,70,55,37,8.0,4,31,Urban,ML Engineer,64747,0 +62916,Female,51,Bachelors,15,29,61,2,7,6.0,5,64,Urban,Data Analyst,84923,0 +62917,Male,53,Bachelors,7,26,63,34,55,1.0,1,66,Urban,Data Analyst,94836,0 +62918,Female,22,Masters,14,93,6,7,35,2.0,6,31,Urban,Data Analyst,41324,0 +62919,Female,46,Masters,6,23,66,38,45,8.0,7,25,Semi-Urban,ML Engineer,48533,0 +62920,Male,42,Bachelors,2,42,62,46,89,4.0,3,11,Urban,Software Engineer,132345,0 +62921,Male,29,Masters,2,12,60,15,87,1.0,3,52,Urban,Manager,65084,0 +62922,Female,31,PhD,4,47,70,87,51,5.0,1,38,Rural,ML Engineer,104540,1 +62923,Female,58,Bachelors,16,67,33,80,73,8.0,3,75,Semi-Urban,ML Engineer,72441,1 +62924,Male,40,High School,17,32,85,73,96,2.0,0,62,Urban,Data Analyst,50104,1 +62925,Female,31,Masters,1,26,17,71,98,6.0,2,20,Urban,HR Executive,72639,0 +62926,Female,59,Bachelors,12,18,66,86,83,5.0,2,25,Semi-Urban,HR Executive,121262,0 +62927,Male,49,Bachelors,13,28,40,36,45,5.0,3,44,Urban,Software Engineer,136158,0 +62928,Male,31,Diploma,4,48,76,50,5,0.0,2,3,Semi-Urban,ML Engineer,61572,0 +62929,Male,55,Bachelors,5,49,71,26,34,2.0,4,66,Urban,Software Engineer,82309,0 +62930,Female,59,Masters,1,93,75,60,25,6.0,6,70,Urban,ML Engineer,128049,1 +62931,Male,34,Bachelors,15,94,75,66,40,2.0,2,44,Urban,Manager,76619,1 +62932,Male,59,Bachelors,3,0,30,7,91,7.0,2,56,Semi-Urban,Manager,111083,0 +62933,Male,59,Masters,7,46,88,26,70,5.0,2,31,Rural,Software Engineer,131324,0 +62934,Male,42,Masters,15,85,2,70,10,8.0,2,58,Urban,HR Executive,35553,0 +62935,Female,57,Diploma,13,54,18,58,93,4.0,0,76,Rural,HR Executive,46806,0 +62936,Male,26,Diploma,1,19,13,64,17,7.0,1,71,Rural,Data Analyst,25026,0 +62937,Female,38,Diploma,4,70,39,35,5,3.0,5,60,Urban,HR Executive,33031,0 +62938,Male,40,Bachelors,17,0,81,54,19,3.0,7,87,Rural,Manager,91536,0 +62939,Other,44,Bachelors,6,8,15,93,22,8.0,3,18,Semi-Urban,ML Engineer,148400,0 +62940,Male,35,Bachelors,2,86,63,0,66,7.0,4,68,Semi-Urban,ML Engineer,52905,0 +62941,Male,33,Diploma,13,31,4,50,95,8.0,4,80,Semi-Urban,Manager,68306,0 +62942,Female,35,Diploma,15,16,41,60,28,6.0,2,75,Rural,Data Analyst,41545,0 +62943,Male,23,Bachelors,15,84,0,29,1,2.0,7,51,Semi-Urban,Data Analyst,129971,0 +62944,Female,56,Masters,18,69,25,57,39,1.0,7,82,Rural,Data Analyst,122756,0 +62945,Other,53,Masters,15,37,6,2,21,6.0,7,54,Urban,Manager,62740,0 +62946,Male,51,Bachelors,11,31,74,65,69,7.0,1,15,Urban,Data Analyst,33943,0 +62947,Female,37,Diploma,8,78,35,18,61,1.0,6,15,Rural,ML Engineer,68509,0 +62948,Male,39,Bachelors,14,27,48,15,48,9.0,0,32,Urban,Manager,116871,0 +62949,Female,41,Diploma,5,43,44,59,22,2.0,7,52,Urban,Software Engineer,128767,0 +62950,Male,32,High School,8,58,50,84,69,0.0,3,41,Urban,Data Analyst,138516,0 +62951,Female,28,Bachelors,5,74,85,8,8,8.0,4,64,Semi-Urban,Software Engineer,68144,0 +62952,Male,28,High School,18,71,39,50,55,6.0,1,99,Urban,ML Engineer,75415,1 +62953,Male,35,Diploma,3,21,20,65,14,7.0,5,69,Semi-Urban,HR Executive,120984,0 +62954,Other,53,PhD,9,96,38,19,20,7.0,4,88,Urban,Manager,133270,1 +62955,Male,58,Masters,9,23,66,74,97,3.0,2,89,Urban,Data Analyst,77835,1 +62956,Male,34,High School,3,86,26,33,3,5.0,4,45,Semi-Urban,Software Engineer,87896,0 +62957,Male,55,Diploma,2,51,53,81,3,2.0,4,44,Urban,HR Executive,90857,0 +62958,Other,49,Bachelors,0,42,6,24,63,9.0,0,6,Urban,Data Analyst,83060,0 +62959,Female,23,Bachelors,8,51,71,13,51,8.0,0,27,Semi-Urban,Manager,23065,0 +62960,Male,25,Bachelors,3,2,35,26,13,5.0,6,70,Urban,Software Engineer,33437,0 +62961,Female,35,Bachelors,7,73,40,4,30,6.0,6,49,Urban,HR Executive,140211,0 +62962,Male,56,Diploma,15,82,55,87,1,0.0,4,86,Urban,HR Executive,79479,1 +62963,Other,51,Masters,19,87,35,86,12,9.0,2,0,Semi-Urban,Manager,63603,0 +62964,Female,27,Bachelors,10,11,99,86,78,5.0,4,88,Urban,Software Engineer,129249,1 +62965,Male,33,Masters,19,62,65,43,65,0.0,2,65,Rural,ML Engineer,137261,1 +62966,Male,59,Masters,0,53,33,40,48,9.0,4,61,Urban,ML Engineer,38070,0 +62967,Female,23,Bachelors,14,88,37,65,37,4.0,0,97,Urban,HR Executive,140064,1 +62968,Female,35,Bachelors,12,22,53,61,50,4.0,5,87,Semi-Urban,Software Engineer,63833,0 +62969,Male,35,Bachelors,15,66,95,32,33,6.0,0,84,Semi-Urban,Data Analyst,107563,1 +62970,Male,29,Bachelors,5,61,89,9,28,0.0,6,91,Rural,Software Engineer,45386,1 +62971,Male,26,Bachelors,11,47,30,37,47,1.0,6,55,Urban,Manager,38528,0 +62972,Male,29,Bachelors,0,13,72,51,7,0.0,0,73,Urban,ML Engineer,87270,0 +62973,Male,32,Masters,19,73,24,59,48,7.0,6,24,Urban,Data Analyst,143793,0 +62974,Male,49,Bachelors,6,32,2,39,65,6.0,5,31,Urban,Data Analyst,49957,0 +62975,Female,38,Diploma,19,13,47,82,47,2.0,4,3,Urban,HR Executive,112692,0 +62976,Male,48,Diploma,13,55,22,48,50,2.0,3,22,Urban,Data Analyst,133690,0 +62977,Female,42,Masters,10,29,71,27,57,2.0,1,51,Urban,Software Engineer,113860,0 +62978,Female,39,Masters,12,63,91,96,15,2.0,6,52,Semi-Urban,Data Analyst,106520,1 +62979,Female,23,Diploma,1,23,95,24,0,0.0,3,17,Urban,Software Engineer,47214,0 +62980,Male,36,Diploma,7,43,16,69,57,7.0,5,10,Urban,Software Engineer,75307,0 +62981,Male,23,Bachelors,2,40,35,79,31,8.0,0,96,Urban,Software Engineer,106362,1 +62982,Other,30,Diploma,7,81,4,64,83,6.0,3,92,Urban,Manager,48054,1 +62983,Female,46,Diploma,13,37,32,46,60,3.0,7,99,Urban,ML Engineer,37698,0 +62984,Other,56,Masters,7,88,83,10,13,1.0,4,78,Rural,ML Engineer,109560,1 +62985,Other,44,Diploma,6,58,33,83,86,2.0,1,25,Urban,Data Analyst,139519,0 +62986,Male,25,Bachelors,7,18,11,75,98,8.0,5,81,Semi-Urban,ML Engineer,86452,0 +62987,Male,39,Masters,17,55,20,47,58,7.0,5,35,Urban,Software Engineer,25826,0 +62988,Female,28,PhD,14,89,84,56,40,8.0,3,8,Semi-Urban,Software Engineer,38882,0 +62989,Male,53,Bachelors,8,59,13,6,32,3.0,6,78,Urban,Data Analyst,65374,0 +62990,Male,31,Bachelors,12,95,42,65,52,6.0,5,66,Semi-Urban,Software Engineer,22528,1 +62991,Male,26,High School,7,80,73,79,39,7.0,7,35,Rural,Manager,64076,1 +62992,Male,24,Bachelors,6,99,50,47,78,8.0,5,86,Urban,Manager,23151,1 +62993,Male,58,Diploma,19,11,67,27,19,4.0,0,6,Rural,ML Engineer,40610,0 +62994,Male,22,PhD,16,92,72,14,11,9.0,4,61,Rural,ML Engineer,52771,1 +62995,Male,24,Diploma,7,56,39,76,9,8.0,2,81,Semi-Urban,Data Analyst,144321,1 +62996,Female,26,Bachelors,19,17,75,17,30,3.0,5,38,Rural,Software Engineer,141477,0 +62997,Male,39,Bachelors,8,63,73,14,35,3.0,6,12,Urban,Software Engineer,134540,0 +62998,Female,52,Masters,12,76,27,7,82,6.0,1,65,Urban,ML Engineer,146548,0 +62999,Female,22,Bachelors,12,10,29,51,74,9.0,5,12,Semi-Urban,Manager,116759,0 +63000,Male,31,High School,11,32,96,38,78,9.0,1,26,Urban,Manager,35578,0 +63001,Male,33,Diploma,8,19,42,27,48,8.0,0,48,Urban,ML Engineer,78488,0 +63002,Male,53,Bachelors,16,33,0,61,0,5.0,6,51,Semi-Urban,Manager,50887,0 +63003,Female,24,Diploma,11,73,50,32,98,2.0,5,17,Urban,HR Executive,148387,0 +63004,Male,32,Bachelors,19,24,70,96,13,1.0,6,6,Semi-Urban,Software Engineer,25046,0 +63005,Male,45,Bachelors,18,27,57,99,61,6.0,0,78,Semi-Urban,Software Engineer,148467,1 +63006,Male,41,Bachelors,16,12,37,30,51,4.0,6,46,Urban,Software Engineer,143868,0 +63007,Male,34,High School,12,7,42,79,11,4.0,1,59,Rural,ML Engineer,136762,0 +63008,Other,26,Bachelors,15,34,37,52,20,9.0,5,85,Urban,HR Executive,45343,0 +63009,Male,39,PhD,7,84,93,29,32,2.0,5,77,Urban,ML Engineer,81921,1 +63010,Male,48,Bachelors,19,89,9,17,35,8.0,1,33,Urban,HR Executive,90392,0 +63011,Male,47,Bachelors,19,36,88,18,8,5.0,0,10,Urban,Software Engineer,144886,0 +63012,Male,33,Diploma,5,99,48,23,69,6.0,6,36,Rural,ML Engineer,122011,0 +63013,Male,40,Masters,2,33,24,38,27,4.0,5,69,Semi-Urban,ML Engineer,20278,0 +63014,Female,44,Bachelors,3,24,28,22,29,4.0,5,66,Urban,HR Executive,72412,0 +63015,Male,53,Masters,13,98,40,64,4,5.0,2,84,Semi-Urban,Software Engineer,21548,1 +63016,Male,57,High School,10,21,47,48,71,3.0,0,13,Semi-Urban,ML Engineer,30815,0 +63017,Female,41,High School,11,30,63,9,44,5.0,5,2,Urban,ML Engineer,24837,0 +63018,Male,48,Masters,0,74,6,88,43,0.0,2,17,Urban,ML Engineer,131975,0 +63019,Female,24,High School,17,32,36,98,23,1.0,3,16,Semi-Urban,ML Engineer,41440,0 +63020,Other,35,Masters,7,72,46,10,13,0.0,4,74,Urban,Data Analyst,77632,0 +63021,Male,43,High School,15,14,6,96,94,0.0,5,49,Urban,ML Engineer,97699,0 +63022,Male,39,Diploma,17,40,64,24,26,5.0,6,25,Urban,HR Executive,21428,0 +63023,Female,37,Masters,17,90,17,71,40,2.0,0,56,Semi-Urban,Software Engineer,142574,0 +63024,Male,44,Diploma,13,84,83,94,15,0.0,3,6,Semi-Urban,ML Engineer,46106,1 +63025,Female,23,Masters,16,92,13,23,56,9.0,1,64,Urban,ML Engineer,134623,0 +63026,Female,50,High School,2,83,84,25,13,3.0,1,51,Urban,Manager,29134,1 +63027,Male,34,Masters,19,51,30,81,35,8.0,1,19,Rural,Manager,103356,0 +63028,Female,48,Bachelors,1,71,31,84,2,7.0,6,69,Urban,Manager,77033,1 +63029,Male,30,Masters,5,89,19,41,77,6.0,2,94,Semi-Urban,ML Engineer,88563,1 +63030,Male,27,Diploma,14,46,54,28,25,5.0,5,29,Rural,ML Engineer,50149,0 +63031,Male,36,High School,12,40,13,26,36,5.0,5,61,Semi-Urban,HR Executive,47222,0 +63032,Male,35,Diploma,3,61,84,21,35,8.0,5,22,Semi-Urban,HR Executive,72042,0 +63033,Male,43,Masters,9,23,80,82,14,9.0,1,20,Urban,HR Executive,69077,0 +63034,Female,52,Masters,15,0,52,26,96,8.0,3,3,Rural,HR Executive,68752,0 +63035,Male,42,Diploma,11,35,0,32,44,7.0,3,79,Urban,HR Executive,58558,0 +63036,Male,39,High School,3,31,45,85,83,5.0,1,54,Urban,Software Engineer,134544,0 +63037,Male,47,High School,15,48,64,58,59,9.0,1,26,Semi-Urban,Software Engineer,101658,0 +63038,Female,22,Bachelors,15,36,40,59,64,3.0,6,38,Urban,Manager,67466,0 +63039,Male,39,Masters,1,7,32,0,19,8.0,1,44,Urban,Software Engineer,59192,0 +63040,Male,59,Masters,17,7,73,31,3,5.0,3,31,Urban,Software Engineer,137813,0 +63041,Male,40,High School,15,79,48,46,63,6.0,4,90,Urban,Software Engineer,122186,1 +63042,Female,42,Bachelors,0,78,94,7,8,5.0,2,98,Urban,Data Analyst,31976,1 +63043,Male,24,Bachelors,13,54,71,6,83,7.0,2,47,Urban,ML Engineer,130811,0 +63044,Male,46,High School,14,10,89,47,35,0.0,7,80,Semi-Urban,Manager,55000,0 +63045,Male,28,Bachelors,16,89,22,77,51,4.0,7,62,Rural,HR Executive,46831,1 +63046,Female,38,Masters,10,26,1,93,28,0.0,7,63,Urban,Data Analyst,77802,0 +63047,Female,54,Masters,2,3,76,38,37,0.0,7,93,Urban,HR Executive,68226,0 +63048,Male,40,Masters,7,27,71,63,81,9.0,6,41,Semi-Urban,Data Analyst,118173,0 +63049,Female,28,High School,12,44,89,30,94,7.0,7,24,Semi-Urban,HR Executive,78038,0 +63050,Male,48,Bachelors,9,70,74,3,25,9.0,3,36,Semi-Urban,Software Engineer,96446,0 +63051,Female,34,Bachelors,3,56,75,50,89,3.0,6,57,Urban,Manager,55011,0 +63052,Female,30,High School,19,95,31,98,96,3.0,1,28,Urban,Data Analyst,20723,1 +63053,Male,50,Bachelors,14,55,15,47,81,0.0,7,30,Urban,Data Analyst,97267,0 +63054,Male,24,Diploma,10,75,86,6,10,2.0,1,36,Urban,Data Analyst,23372,0 +63055,Female,23,Diploma,14,58,86,69,79,3.0,0,55,Rural,Data Analyst,120934,1 +63056,Male,22,Bachelors,3,24,76,4,46,4.0,1,61,Rural,HR Executive,104509,0 +63057,Female,35,Diploma,5,22,39,74,29,0.0,7,18,Rural,HR Executive,110438,0 +63058,Female,53,High School,6,87,77,12,4,2.0,7,50,Rural,HR Executive,57334,0 +63059,Female,25,Bachelors,11,53,18,74,26,5.0,2,38,Urban,Software Engineer,27613,0 +63060,Female,37,High School,8,85,43,21,36,7.0,6,56,Rural,Manager,112407,0 +63061,Male,25,Masters,10,7,88,87,31,6.0,7,39,Urban,Software Engineer,32255,0 +63062,Other,42,High School,15,70,59,84,10,5.0,3,94,Urban,HR Executive,100798,1 +63063,Female,28,Bachelors,2,0,76,39,98,2.0,5,90,Urban,Software Engineer,42926,0 +63064,Male,44,Bachelors,1,44,19,9,86,7.0,0,45,Urban,HR Executive,59297,0 +63065,Female,41,Bachelors,2,3,56,0,48,4.0,5,62,Urban,Data Analyst,109484,0 +63066,Female,28,Masters,6,11,99,79,91,5.0,2,30,Urban,Manager,30134,0 +63067,Female,48,High School,14,54,70,24,77,7.0,2,88,Urban,HR Executive,82867,0 +63068,Male,53,Diploma,15,99,64,19,17,9.0,2,83,Rural,ML Engineer,37150,1 +63069,Male,35,PhD,3,54,60,70,89,2.0,1,29,Urban,HR Executive,122561,0 +63070,Female,23,Bachelors,12,98,98,81,16,2.0,2,94,Urban,HR Executive,20792,1 +63071,Female,32,Masters,19,49,76,11,22,9.0,4,16,Semi-Urban,HR Executive,93110,0 +63072,Male,52,Bachelors,3,42,37,49,98,7.0,3,48,Urban,Data Analyst,141242,0 +63073,Male,56,Diploma,9,92,1,18,80,2.0,4,56,Urban,Software Engineer,32702,0 +63074,Other,35,Masters,14,2,31,9,93,1.0,7,0,Rural,Manager,33710,0 +63075,Male,40,Bachelors,1,26,7,13,46,3.0,0,78,Urban,Software Engineer,116676,0 +63076,Female,55,PhD,11,37,59,69,52,0.0,0,37,Urban,ML Engineer,95114,0 +63077,Male,38,Masters,18,62,21,74,63,8.0,4,40,Rural,ML Engineer,83002,0 +63078,Male,21,Diploma,12,68,55,73,7,0.0,4,34,Urban,Data Analyst,49568,0 +63079,Female,56,High School,5,12,54,32,54,7.0,0,9,Semi-Urban,Data Analyst,71040,0 +63080,Female,52,PhD,0,36,9,47,90,0.0,2,41,Urban,ML Engineer,92938,0 +63081,Other,26,High School,4,69,0,2,72,6.0,7,10,Rural,HR Executive,109188,0 +63082,Male,37,Masters,19,45,28,89,91,8.0,2,6,Urban,Software Engineer,28972,0 +63083,Female,46,Bachelors,1,11,99,52,99,7.0,1,53,Rural,HR Executive,141061,0 +63084,Male,41,Masters,12,66,92,3,53,4.0,6,44,Semi-Urban,HR Executive,101397,0 +63085,Male,39,Diploma,16,21,77,20,14,3.0,7,80,Urban,HR Executive,67363,0 +63086,Female,39,Masters,12,79,89,62,78,3.0,4,57,Semi-Urban,ML Engineer,51692,1 +63087,Male,57,Masters,19,86,84,63,87,3.0,3,40,Semi-Urban,ML Engineer,31553,1 +63088,Female,47,PhD,15,29,15,91,28,6.0,4,37,Urban,Manager,122011,0 +63089,Male,54,High School,3,52,4,26,38,0.0,4,16,Rural,HR Executive,122926,0 +63090,Female,49,Bachelors,6,46,90,51,41,6.0,2,44,Urban,Data Analyst,32631,0 +63091,Male,22,Bachelors,19,56,76,1,87,8.0,2,78,Urban,HR Executive,98057,0 +63092,Male,58,Bachelors,15,36,66,35,91,3.0,2,70,Urban,Software Engineer,91432,0 +63093,Male,39,Bachelors,7,66,54,38,32,7.0,1,55,Urban,Software Engineer,32691,0 +63094,Male,22,PhD,4,0,76,16,92,2.0,0,40,Urban,HR Executive,149766,0 +63095,Male,36,High School,1,96,41,61,35,0.0,4,75,Semi-Urban,ML Engineer,50070,1 +63096,Male,32,Bachelors,5,30,76,4,33,4.0,4,2,Semi-Urban,ML Engineer,42000,0 +63097,Male,49,Bachelors,8,21,2,47,30,7.0,4,75,Urban,Data Analyst,110580,0 +63098,Male,54,Diploma,12,15,17,11,65,8.0,7,1,Semi-Urban,HR Executive,48506,0 +63099,Female,43,Diploma,19,97,85,2,83,1.0,3,50,Rural,Data Analyst,112002,0 +63100,Female,27,Masters,10,45,7,39,87,2.0,0,69,Rural,HR Executive,104873,0 +63101,Male,34,Bachelors,16,93,37,72,38,7.0,6,52,Urban,ML Engineer,67983,1 +63102,Male,49,Diploma,16,66,49,65,33,9.0,2,17,Urban,Data Analyst,145389,0 +63103,Other,50,Diploma,12,94,77,14,27,9.0,0,34,Rural,Software Engineer,107435,0 +63104,Other,23,High School,1,11,47,94,85,8.0,0,43,Urban,ML Engineer,53438,0 +63105,Male,31,Bachelors,15,24,29,26,33,1.0,1,8,Rural,Data Analyst,62913,0 +63106,Male,30,PhD,1,39,64,80,11,5.0,1,66,Urban,Software Engineer,126618,1 +63107,Female,35,PhD,14,2,76,39,67,6.0,3,78,Semi-Urban,ML Engineer,149131,0 +63108,Female,55,PhD,7,36,96,6,84,8.0,0,1,Semi-Urban,HR Executive,92381,0 +63109,Female,58,Masters,18,58,1,48,59,9.0,7,78,Urban,Manager,67691,0 +63110,Male,25,Masters,3,89,31,8,21,4.0,6,69,Urban,Software Engineer,138347,0 +63111,Male,51,Masters,14,4,69,55,32,3.0,2,1,Urban,HR Executive,80040,0 +63112,Female,33,Diploma,10,80,28,13,19,8.0,7,29,Urban,HR Executive,72878,0 +63113,Male,58,Bachelors,3,81,38,95,13,6.0,4,31,Urban,Software Engineer,109182,1 +63114,Male,50,Bachelors,15,31,60,4,5,5.0,7,79,Urban,HR Executive,134605,0 +63115,Male,28,Bachelors,3,69,2,71,60,8.0,3,38,Urban,Data Analyst,70689,0 +63116,Female,48,Bachelors,2,96,71,78,9,1.0,1,9,Urban,Manager,44625,1 +63117,Male,50,Bachelors,12,8,61,62,6,6.0,5,53,Urban,Data Analyst,128502,0 +63118,Male,40,Bachelors,14,81,71,7,80,6.0,2,91,Urban,Manager,53946,1 +63119,Male,31,Masters,8,77,86,85,12,7.0,7,73,Urban,Data Analyst,67302,1 +63120,Female,49,Diploma,0,66,78,42,49,5.0,0,17,Semi-Urban,Data Analyst,86110,0 +63121,Female,35,Bachelors,10,99,47,97,23,7.0,5,51,Semi-Urban,Data Analyst,95697,1 +63122,Female,35,Diploma,1,7,34,29,32,9.0,1,51,Semi-Urban,Manager,103972,0 +63123,Male,47,PhD,0,4,66,20,62,0.0,7,54,Urban,Software Engineer,117028,0 +63124,Male,39,Bachelors,19,83,69,61,54,5.0,5,38,Urban,Manager,50934,1 +63125,Male,41,Bachelors,6,10,34,62,33,4.0,6,6,Urban,Software Engineer,72545,0 +63126,Female,37,Diploma,2,56,38,87,81,5.0,4,93,Semi-Urban,HR Executive,76562,1 +63127,Male,56,Diploma,5,84,56,45,63,0.0,1,55,Urban,HR Executive,74102,1 +63128,Female,53,Bachelors,18,77,30,55,36,7.0,0,19,Urban,ML Engineer,86797,0 +63129,Male,23,Bachelors,13,66,94,15,72,1.0,4,69,Rural,HR Executive,59716,1 +63130,Male,59,Masters,0,16,31,72,86,9.0,5,78,Semi-Urban,Data Analyst,144889,0 +63131,Male,27,Bachelors,14,39,50,40,1,9.0,7,22,Semi-Urban,Manager,22170,0 +63132,Male,49,Bachelors,16,12,51,18,12,8.0,2,89,Semi-Urban,Software Engineer,69406,0 +63133,Female,43,Diploma,6,13,1,84,27,4.0,2,60,Urban,Data Analyst,115051,0 +63134,Male,37,Bachelors,15,50,22,39,58,6.0,7,3,Urban,Data Analyst,90534,0 +63135,Male,36,Diploma,15,5,95,23,74,6.0,7,52,Semi-Urban,ML Engineer,92045,0 +63136,Male,28,Bachelors,12,19,97,15,43,5.0,0,88,Urban,Software Engineer,60397,0 +63137,Female,52,Bachelors,6,1,12,31,60,4.0,3,6,Urban,Data Analyst,41311,0 +63138,Female,44,Diploma,3,6,36,13,20,4.0,0,77,Urban,ML Engineer,85900,0 +63139,Female,52,Bachelors,4,12,9,76,65,1.0,4,51,Semi-Urban,HR Executive,26833,0 +63140,Female,37,Diploma,9,68,84,86,80,7.0,1,56,Urban,Software Engineer,131584,1 +63141,Female,57,High School,10,86,2,19,1,5.0,1,44,Urban,Manager,30957,0 +63142,Male,33,Bachelors,18,19,85,26,46,3.0,6,97,Rural,Software Engineer,33297,0 +63143,Female,47,Bachelors,12,13,10,7,9,6.0,3,63,Urban,Software Engineer,64008,0 +63144,Male,47,Diploma,5,2,92,57,0,9.0,7,33,Urban,ML Engineer,59882,0 +63145,Female,58,Bachelors,0,1,19,1,27,9.0,5,57,Semi-Urban,Software Engineer,122111,0 +63146,Male,39,PhD,2,0,36,36,52,3.0,6,31,Rural,Data Analyst,134895,0 +63147,Female,26,Masters,19,97,84,4,45,7.0,4,93,Semi-Urban,HR Executive,126038,1 +63148,Male,37,Bachelors,7,38,8,64,57,6.0,6,23,Urban,Manager,120473,0 +63149,Male,49,Diploma,17,86,84,5,82,1.0,1,20,Semi-Urban,ML Engineer,112958,0 +63150,Female,48,High School,10,54,80,42,54,4.0,2,45,Rural,Data Analyst,124296,0 +63151,Male,25,Bachelors,14,23,61,69,72,8.0,4,31,Rural,Software Engineer,36725,0 +63152,Male,25,Bachelors,19,28,38,22,80,1.0,5,69,Urban,ML Engineer,116419,0 +63153,Female,23,Masters,10,97,79,10,85,0.0,7,99,Semi-Urban,HR Executive,65276,1 +63154,Male,31,Bachelors,13,12,90,41,8,6.0,2,31,Semi-Urban,HR Executive,55865,0 +63155,Male,29,Masters,4,92,60,99,20,4.0,6,98,Semi-Urban,HR Executive,142125,1 +63156,Male,57,Masters,16,54,61,64,59,6.0,4,78,Urban,Data Analyst,75872,1 +63157,Male,38,Diploma,17,11,83,19,68,0.0,2,91,Urban,Manager,98358,0 +63158,Male,57,PhD,12,88,17,16,24,6.0,3,80,Urban,Data Analyst,58205,0 +63159,Other,54,Masters,6,20,29,28,52,9.0,5,23,Semi-Urban,HR Executive,69986,0 +63160,Male,50,Masters,4,98,70,19,86,5.0,2,1,Rural,Data Analyst,60967,0 +63161,Male,30,High School,7,9,78,33,85,4.0,3,45,Rural,Manager,29391,0 +63162,Male,25,Masters,2,47,24,16,77,8.0,7,24,Urban,HR Executive,134819,0 +63163,Male,28,PhD,2,82,45,93,18,3.0,1,26,Semi-Urban,HR Executive,97839,1 +63164,Male,32,Bachelors,1,86,8,89,65,8.0,5,77,Urban,Data Analyst,116756,1 +63165,Male,49,Diploma,0,19,25,84,19,0.0,6,22,Urban,Manager,143001,0 +63166,Male,30,PhD,5,34,87,66,62,5.0,4,93,Urban,ML Engineer,52069,1 +63167,Female,41,Bachelors,16,20,94,83,41,4.0,0,76,Urban,HR Executive,54297,1 +63168,Female,47,PhD,19,19,39,8,2,8.0,7,43,Rural,Data Analyst,36694,0 +63169,Male,43,High School,0,55,63,73,28,8.0,7,31,Semi-Urban,ML Engineer,71188,0 +63170,Female,57,High School,9,67,62,30,98,8.0,1,3,Semi-Urban,Data Analyst,138521,0 +63171,Female,44,Bachelors,0,63,85,71,20,0.0,7,51,Semi-Urban,Software Engineer,93989,1 +63172,Male,51,Diploma,7,99,78,0,38,8.0,0,92,Rural,Data Analyst,46587,1 +63173,Male,52,Masters,18,9,61,64,60,2.0,7,39,Urban,Manager,77878,0 +63174,Male,31,High School,7,99,75,78,6,6.0,3,51,Urban,Manager,92403,1 +63175,Female,36,Diploma,13,25,33,90,28,9.0,2,7,Urban,HR Executive,76537,0 +63176,Male,46,PhD,0,56,58,99,43,2.0,5,57,Rural,HR Executive,66082,1 +63177,Male,56,Masters,12,62,10,42,20,3.0,3,35,Semi-Urban,HR Executive,38399,0 +63178,Female,53,Masters,11,39,88,3,99,4.0,7,13,Urban,Software Engineer,49056,0 +63179,Female,22,Bachelors,10,70,19,50,73,7.0,1,59,Urban,ML Engineer,53162,0 +63180,Male,21,High School,19,33,18,44,65,8.0,0,78,Rural,ML Engineer,147963,0 +63181,Male,40,Bachelors,9,73,37,67,34,9.0,4,29,Urban,Data Analyst,142716,0 +63182,Male,44,High School,7,82,66,19,92,2.0,5,49,Urban,Data Analyst,82019,0 +63183,Male,46,Masters,8,31,19,86,78,0.0,1,93,Urban,Manager,74707,0 +63184,Male,29,PhD,4,79,35,68,58,6.0,0,17,Semi-Urban,ML Engineer,83781,0 +63185,Female,34,Bachelors,10,51,59,64,18,5.0,4,78,Rural,HR Executive,110288,1 +63186,Other,23,Bachelors,1,33,66,13,38,1.0,3,4,Rural,Manager,139077,0 +63187,Female,25,High School,19,75,92,37,78,8.0,6,13,Urban,Manager,144586,0 +63188,Male,32,Masters,11,2,22,70,92,5.0,3,96,Rural,Data Analyst,20127,0 +63189,Male,48,Bachelors,14,13,0,83,37,0.0,3,13,Urban,HR Executive,39645,0 +63190,Male,32,Masters,9,52,72,48,27,3.0,1,69,Rural,HR Executive,30735,1 +63191,Male,45,Bachelors,7,80,50,43,93,8.0,1,8,Urban,Software Engineer,107343,0 +63192,Female,57,High School,7,87,60,61,55,9.0,3,13,Urban,Software Engineer,118263,0 +63193,Male,23,Diploma,16,89,91,71,57,3.0,6,71,Semi-Urban,Manager,80107,1 +63194,Male,30,Bachelors,6,58,68,3,17,2.0,6,51,Urban,Software Engineer,65953,0 +63195,Male,40,Diploma,3,3,36,57,14,1.0,6,11,Rural,Manager,42528,0 +63196,Male,58,Bachelors,1,39,95,30,95,0.0,2,46,Urban,HR Executive,116052,0 +63197,Female,25,Bachelors,2,35,41,21,70,6.0,5,77,Urban,Data Analyst,38098,0 +63198,Female,55,Bachelors,15,89,46,61,83,7.0,0,42,Urban,HR Executive,124637,0 +63199,Female,44,Bachelors,0,13,12,99,19,4.0,1,6,Urban,Data Analyst,79182,0 +63200,Female,30,Diploma,3,96,54,48,45,0.0,1,25,Semi-Urban,HR Executive,33522,0 +63201,Male,56,Bachelors,3,14,62,3,62,8.0,1,33,Urban,Manager,30457,0 +63202,Male,45,High School,2,93,8,92,22,6.0,7,6,Semi-Urban,ML Engineer,90941,0 +63203,Male,42,Diploma,5,9,40,66,82,5.0,7,67,Urban,Software Engineer,31038,0 +63204,Female,45,Bachelors,6,38,78,90,49,7.0,1,59,Semi-Urban,Software Engineer,80020,1 +63205,Male,47,Bachelors,5,33,33,12,20,5.0,1,58,Rural,HR Executive,29876,0 +63206,Male,49,Bachelors,12,53,35,74,20,2.0,5,49,Urban,Manager,56320,0 +63207,Male,55,Bachelors,19,74,68,87,94,1.0,0,84,Urban,Software Engineer,147327,1 +63208,Female,29,Bachelors,11,0,3,46,45,9.0,7,69,Semi-Urban,ML Engineer,111113,0 +63209,Female,31,High School,7,8,48,21,62,3.0,2,79,Urban,Manager,35814,0 +63210,Male,39,Diploma,13,31,40,45,32,6.0,5,89,Urban,HR Executive,121295,0 +63211,Female,37,Diploma,1,17,9,8,61,0.0,5,64,Rural,HR Executive,108902,0 +63212,Female,28,High School,17,90,22,70,21,4.0,6,62,Urban,Manager,54544,1 +63213,Male,57,Bachelors,9,70,9,34,32,1.0,1,15,Urban,Data Analyst,24470,0 +63214,Male,44,High School,6,61,24,76,65,4.0,1,41,Urban,HR Executive,60745,0 +63215,Female,47,Masters,16,83,31,20,90,4.0,3,17,Urban,Data Analyst,65052,0 +63216,Male,43,Diploma,1,36,75,81,71,8.0,7,86,Rural,Software Engineer,63609,1 +63217,Female,29,Diploma,14,93,3,68,86,7.0,3,16,Urban,Data Analyst,103120,0 +63218,Male,23,Masters,14,59,50,76,19,6.0,5,3,Urban,ML Engineer,89877,0 +63219,Male,55,Bachelors,6,38,14,94,30,2.0,4,54,Semi-Urban,Manager,131390,0 +63220,Male,27,Bachelors,14,47,5,31,50,1.0,2,87,Urban,Manager,139080,0 +63221,Other,42,Bachelors,11,16,0,66,9,8.0,3,93,Semi-Urban,Manager,35545,0 +63222,Male,28,Bachelors,18,25,86,96,21,0.0,1,50,Semi-Urban,Data Analyst,64270,1 +63223,Female,30,High School,1,51,18,85,87,4.0,2,90,Rural,ML Engineer,124597,1 +63224,Male,52,Diploma,16,70,66,4,78,6.0,3,23,Urban,Software Engineer,62044,0 +63225,Male,50,Bachelors,5,98,63,18,43,4.0,4,58,Semi-Urban,Data Analyst,130771,1 +63226,Male,30,Bachelors,8,23,37,37,45,9.0,1,81,Rural,Manager,26621,0 +63227,Male,49,Masters,13,61,58,79,3,7.0,7,65,Rural,Data Analyst,61816,1 +63228,Male,33,Bachelors,10,69,50,71,94,7.0,5,70,Urban,Manager,127355,1 +63229,Female,36,Bachelors,16,9,84,80,88,6.0,6,28,Urban,ML Engineer,24604,0 +63230,Female,24,High School,3,38,18,37,60,3.0,5,37,Rural,Data Analyst,101636,0 +63231,Male,35,High School,8,38,82,7,34,4.0,0,12,Urban,Manager,27517,0 +63232,Female,44,High School,8,37,68,77,10,0.0,1,12,Rural,HR Executive,146876,0 +63233,Male,31,Masters,10,17,6,11,92,0.0,5,67,Rural,ML Engineer,136764,0 +63234,Other,35,Masters,12,59,34,75,25,9.0,2,76,Urban,ML Engineer,104114,1 +63235,Male,41,Bachelors,4,24,86,8,30,9.0,1,53,Urban,HR Executive,100604,0 +63236,Male,54,High School,7,89,39,7,59,9.0,4,18,Urban,ML Engineer,41186,0 +63237,Male,30,Bachelors,13,62,16,46,95,4.0,5,10,Rural,Manager,134772,0 +63238,Female,36,Bachelors,3,36,44,22,72,8.0,2,64,Urban,Data Analyst,108456,0 +63239,Male,45,Masters,13,4,85,51,68,0.0,5,36,Urban,Software Engineer,88157,0 +63240,Female,29,Diploma,19,54,29,99,72,7.0,2,55,Urban,Data Analyst,23365,0 +63241,Female,38,Bachelors,6,15,61,25,12,9.0,7,14,Semi-Urban,Software Engineer,58292,0 +63242,Male,23,Masters,7,44,54,57,84,2.0,4,56,Urban,Manager,27139,0 +63243,Male,59,Masters,14,68,45,28,36,0.0,1,84,Rural,Data Analyst,28132,0 +63244,Male,43,Bachelors,7,95,45,2,55,0.0,1,97,Rural,Software Engineer,44927,1 +63245,Male,58,Bachelors,6,1,51,6,30,0.0,2,30,Rural,Manager,73416,0 +63246,Male,58,High School,13,37,96,85,36,3.0,7,8,Rural,Manager,20079,0 +63247,Male,45,Diploma,10,47,83,16,26,9.0,5,58,Urban,Data Analyst,59753,0 +63248,Other,37,Diploma,12,69,26,37,76,4.0,2,67,Rural,Software Engineer,21877,0 +63249,Male,59,Diploma,18,22,37,73,27,1.0,2,4,Semi-Urban,Data Analyst,72247,0 +63250,Male,38,Bachelors,13,47,60,54,61,5.0,5,30,Semi-Urban,Software Engineer,81682,0 +63251,Male,46,Masters,13,77,41,60,78,0.0,2,15,Rural,Software Engineer,80864,0 +63252,Male,58,Masters,19,7,27,38,88,0.0,3,45,Urban,Data Analyst,145097,0 +63253,Male,53,Masters,12,99,13,92,4,2.0,2,44,Urban,ML Engineer,108015,1 +63254,Female,25,Bachelors,16,86,80,59,96,8.0,7,84,Urban,Manager,116754,1 +63255,Male,38,Bachelors,11,41,84,63,98,3.0,3,74,Urban,Data Analyst,110391,1 +63256,Female,32,Bachelors,15,27,8,37,97,5.0,3,11,Urban,Software Engineer,82428,0 +63257,Male,59,Diploma,6,16,50,4,88,5.0,1,7,Urban,ML Engineer,21736,0 +63258,Male,24,Diploma,17,32,47,70,74,0.0,0,92,Semi-Urban,HR Executive,45337,1 +63259,Male,23,High School,9,36,60,93,47,1.0,0,44,Semi-Urban,Data Analyst,126521,0 +63260,Male,50,Diploma,5,72,72,20,20,5.0,2,81,Rural,ML Engineer,32104,1 +63261,Male,44,High School,19,25,13,71,14,9.0,2,73,Urban,ML Engineer,127907,0 +63262,Female,45,Bachelors,10,74,57,99,26,1.0,1,44,Urban,Software Engineer,55480,1 +63263,Female,52,Diploma,14,47,21,37,90,1.0,7,35,Urban,Software Engineer,137478,0 +63264,Female,59,Bachelors,14,60,23,28,33,7.0,7,46,Semi-Urban,Software Engineer,25815,0 +63265,Female,28,Diploma,14,38,88,52,17,5.0,2,35,Urban,ML Engineer,81626,0 +63266,Male,35,Bachelors,19,84,65,77,68,1.0,2,46,Rural,ML Engineer,91637,1 +63267,Male,26,Masters,3,39,64,35,97,5.0,6,48,Semi-Urban,Data Analyst,31980,0 +63268,Male,41,Bachelors,10,14,47,31,1,9.0,1,27,Rural,ML Engineer,74622,0 +63269,Male,32,Bachelors,6,36,95,76,52,6.0,5,77,Urban,Manager,131148,1 +63270,Male,59,Bachelors,13,5,3,44,79,8.0,5,28,Semi-Urban,ML Engineer,107322,0 +63271,Male,31,Masters,19,38,33,72,77,2.0,2,67,Rural,Manager,98084,0 +63272,Female,27,Bachelors,13,38,37,45,49,3.0,5,80,Urban,Manager,125654,0 +63273,Male,28,Bachelors,14,5,82,94,50,5.0,7,82,Semi-Urban,Manager,49446,1 +63274,Male,34,Bachelors,11,60,79,92,95,2.0,2,38,Semi-Urban,Software Engineer,119257,1 +63275,Male,36,Bachelors,14,99,1,17,21,0.0,7,75,Rural,HR Executive,137780,0 +63276,Female,56,PhD,15,2,98,67,15,0.0,5,76,Urban,Manager,25108,1 +63277,Other,43,Bachelors,17,91,82,1,56,5.0,3,47,Urban,ML Engineer,121476,0 +63278,Male,34,Masters,16,59,24,69,81,1.0,6,39,Urban,HR Executive,25045,0 +63279,Female,25,Bachelors,14,83,35,60,60,5.0,1,86,Semi-Urban,HR Executive,87387,1 +63280,Male,51,Bachelors,19,48,69,84,24,5.0,5,76,Rural,HR Executive,87402,1 +63281,Male,43,High School,19,86,15,13,81,1.0,6,15,Semi-Urban,Software Engineer,89898,0 +63282,Female,41,Bachelors,19,31,54,78,32,6.0,5,24,Urban,Software Engineer,110232,0 +63283,Male,34,Masters,8,90,13,65,1,6.0,0,34,Semi-Urban,Software Engineer,91897,0 +63284,Female,24,Masters,10,82,17,72,61,6.0,7,50,Urban,Data Analyst,71327,0 +63285,Female,28,Masters,1,17,83,26,50,4.0,3,78,Semi-Urban,ML Engineer,128595,0 +63286,Female,38,Bachelors,5,60,75,79,88,3.0,4,9,Semi-Urban,Manager,131283,0 +63287,Male,30,Masters,14,18,12,80,89,6.0,1,66,Rural,HR Executive,67405,0 +63288,Female,42,Diploma,18,27,86,69,1,0.0,6,17,Semi-Urban,Manager,108770,0 +63289,Female,56,PhD,10,3,90,41,40,8.0,1,23,Urban,ML Engineer,90574,0 +63290,Female,48,Bachelors,7,6,64,91,55,4.0,6,78,Rural,Data Analyst,102993,0 +63291,Male,35,PhD,9,42,89,19,80,9.0,7,71,Urban,HR Executive,106719,0 +63292,Male,50,High School,12,15,92,91,35,5.0,1,97,Urban,ML Engineer,83460,1 +63293,Male,27,Masters,7,10,90,80,60,0.0,0,63,Urban,Manager,103258,1 +63294,Male,37,Diploma,5,81,60,69,26,4.0,7,71,Urban,Manager,44991,1 +63295,Male,59,Bachelors,3,33,22,84,77,1.0,4,42,Semi-Urban,Software Engineer,141132,0 +63296,Male,33,Bachelors,6,58,1,77,22,8.0,6,12,Semi-Urban,Manager,59479,0 +63297,Male,46,Bachelors,0,73,8,11,80,3.0,0,17,Urban,ML Engineer,89641,0 +63298,Male,52,Bachelors,4,34,44,83,41,4.0,4,57,Urban,HR Executive,40647,0 +63299,Male,38,Masters,9,15,44,34,46,7.0,5,6,Urban,ML Engineer,95065,0 +63300,Female,23,Diploma,17,30,49,79,44,4.0,6,32,Rural,Software Engineer,24031,0 +63301,Female,27,Bachelors,17,27,39,19,79,8.0,3,87,Urban,ML Engineer,117654,0 +63302,Female,31,Diploma,2,5,12,5,95,8.0,1,72,Urban,ML Engineer,39808,0 +63303,Female,26,Bachelors,13,66,41,58,5,8.0,1,47,Urban,HR Executive,110558,0 +63304,Male,48,Bachelors,18,50,40,97,46,8.0,5,32,Urban,ML Engineer,23948,0 +63305,Male,24,High School,19,60,90,85,61,8.0,0,15,Urban,Data Analyst,48117,1 +63306,Male,24,Bachelors,17,38,59,56,84,5.0,2,70,Urban,Software Engineer,96789,0 +63307,Female,29,Bachelors,7,83,18,38,41,7.0,0,3,Urban,HR Executive,100018,0 +63308,Female,53,Masters,7,99,94,93,78,4.0,6,23,Semi-Urban,ML Engineer,58176,1 +63309,Male,35,Bachelors,14,13,69,36,29,5.0,0,73,Urban,Data Analyst,66582,0 +63310,Female,36,Bachelors,3,62,99,86,9,8.0,2,5,Urban,Software Engineer,75969,1 +63311,Female,56,High School,14,68,18,21,77,0.0,2,3,Semi-Urban,Data Analyst,52748,0 +63312,Male,23,PhD,6,78,6,40,89,2.0,0,67,Rural,Software Engineer,60329,0 +63313,Male,52,High School,13,21,35,65,12,6.0,5,99,Semi-Urban,Data Analyst,58802,0 +63314,Other,51,Diploma,0,27,75,48,95,8.0,4,81,Urban,Manager,40462,0 +63315,Male,56,Bachelors,5,78,69,37,99,7.0,0,71,Rural,Data Analyst,104600,1 +63316,Male,46,PhD,3,84,94,69,69,0.0,2,79,Urban,Data Analyst,30581,1 +63317,Male,59,Bachelors,1,29,24,11,56,3.0,3,58,Rural,Software Engineer,60929,0 +63318,Male,47,Bachelors,4,65,22,5,3,1.0,1,3,Urban,Software Engineer,68211,0 +63319,Female,38,Masters,9,97,60,30,69,6.0,3,98,Semi-Urban,HR Executive,25469,1 +63320,Male,52,Masters,15,37,92,32,39,1.0,3,56,Semi-Urban,Manager,77842,0 +63321,Female,44,Diploma,4,81,44,78,43,9.0,7,84,Urban,ML Engineer,68409,1 +63322,Female,56,Diploma,5,57,87,32,27,2.0,5,43,Rural,Software Engineer,42874,0 +63323,Female,25,Diploma,2,65,95,4,60,5.0,3,6,Urban,HR Executive,57791,0 +63324,Female,38,Bachelors,9,80,37,67,40,9.0,5,22,Rural,Data Analyst,118357,0 +63325,Male,53,Bachelors,0,45,10,39,54,3.0,7,16,Urban,Data Analyst,136559,0 +63326,Male,59,Bachelors,12,26,29,39,79,2.0,7,47,Urban,HR Executive,101463,0 +63327,Male,57,Bachelors,5,48,87,57,9,6.0,7,92,Urban,HR Executive,53762,1 +63328,Female,47,Masters,19,78,45,74,67,2.0,4,78,Urban,Data Analyst,113115,1 +63329,Other,48,High School,12,75,89,94,20,1.0,7,6,Rural,Manager,131596,1 +63330,Male,44,Bachelors,13,84,42,72,81,5.0,3,66,Urban,HR Executive,37196,1 +63331,Male,52,Diploma,0,44,11,75,49,7.0,2,95,Urban,Software Engineer,63877,0 +63332,Male,49,High School,0,21,30,60,71,4.0,7,76,Urban,HR Executive,86094,0 +63333,Male,40,Diploma,8,35,74,33,77,8.0,7,81,Rural,HR Executive,50100,0 +63334,Male,54,Bachelors,2,74,89,73,52,2.0,1,8,Rural,HR Executive,72372,1 +63335,Female,33,Masters,3,11,24,67,14,3.0,5,6,Urban,Data Analyst,49919,0 +63336,Male,49,Bachelors,2,94,95,66,0,4.0,1,78,Urban,ML Engineer,142418,1 +63337,Male,32,Bachelors,17,56,17,39,84,5.0,4,6,Semi-Urban,ML Engineer,101550,0 +63338,Male,25,Bachelors,3,92,17,14,60,2.0,6,17,Urban,ML Engineer,106165,0 +63339,Male,24,Masters,17,47,62,48,33,3.0,6,86,Urban,Data Analyst,56677,1 +63340,Female,37,Masters,19,5,96,6,70,4.0,7,45,Urban,Data Analyst,82802,0 +63341,Male,44,High School,14,1,6,76,10,0.0,0,14,Rural,Software Engineer,50985,0 +63342,Male,32,High School,4,9,84,66,7,8.0,6,83,Semi-Urban,Manager,24192,1 +63343,Female,30,Bachelors,11,92,65,73,86,1.0,5,79,Urban,Manager,49921,1 +63344,Male,37,High School,15,38,75,36,28,1.0,3,37,Urban,Manager,52830,0 +63345,Female,47,Bachelors,6,48,98,9,21,0.0,2,72,Semi-Urban,ML Engineer,101532,0 +63346,Female,58,Bachelors,12,56,1,9,74,8.0,0,92,Urban,Manager,128298,0 +63347,Male,54,Bachelors,0,44,44,33,98,1.0,1,12,Rural,HR Executive,120461,0 +63348,Male,52,Bachelors,17,72,2,87,38,3.0,7,55,Rural,ML Engineer,128104,0 +63349,Female,25,Masters,3,35,59,25,44,4.0,1,62,Urban,Manager,62702,0 +63350,Male,26,Bachelors,3,19,77,10,53,3.0,2,27,Urban,Data Analyst,133917,0 +63351,Male,47,High School,5,44,19,7,7,4.0,7,48,Urban,HR Executive,63519,0 +63352,Female,28,High School,10,93,26,8,89,1.0,4,56,Rural,Data Analyst,45957,0 +63353,Male,48,Masters,3,27,70,5,81,2.0,2,69,Semi-Urban,Manager,132897,0 +63354,Male,22,Diploma,11,36,3,69,64,2.0,3,57,Semi-Urban,ML Engineer,92478,0 +63355,Female,26,Bachelors,3,59,52,68,93,6.0,0,29,Urban,HR Executive,23066,0 +63356,Female,40,Masters,2,5,94,50,87,8.0,0,24,Urban,Manager,20739,0 +63357,Female,31,Diploma,8,9,93,99,98,7.0,3,63,Urban,Manager,91463,1 +63358,Male,39,Diploma,17,26,61,15,64,9.0,4,73,Semi-Urban,HR Executive,122191,0 +63359,Female,56,Masters,15,69,60,58,17,1.0,3,33,Urban,HR Executive,87905,0 +63360,Male,34,Masters,3,20,15,46,41,6.0,1,2,Urban,HR Executive,33329,0 +63361,Male,32,Bachelors,6,78,5,44,71,4.0,7,0,Semi-Urban,ML Engineer,137857,0 +63362,Male,27,PhD,13,25,1,41,13,1.0,5,51,Urban,ML Engineer,132766,0 +63363,Male,36,Masters,0,19,24,54,89,2.0,7,53,Urban,Manager,78329,0 +63364,Female,33,Diploma,7,74,28,38,84,1.0,7,85,Urban,ML Engineer,69040,0 +63365,Male,52,Masters,6,42,80,71,83,1.0,0,78,Semi-Urban,Software Engineer,41106,1 +63366,Male,54,High School,2,53,69,11,87,3.0,3,66,Semi-Urban,Manager,121515,0 +63367,Male,56,Bachelors,10,21,31,65,5,7.0,5,97,Urban,ML Engineer,137959,0 +63368,Male,44,Bachelors,14,10,35,85,46,8.0,5,79,Rural,Software Engineer,20298,0 +63369,Female,23,PhD,19,56,13,35,43,5.0,2,54,Urban,ML Engineer,88490,0 +63370,Female,27,Diploma,17,2,52,63,38,2.0,2,33,Rural,Manager,110002,0 +63371,Female,34,Diploma,12,52,80,44,59,5.0,3,97,Urban,ML Engineer,44462,1 +63372,Female,27,Bachelors,5,56,29,40,88,5.0,3,99,Rural,ML Engineer,109869,0 +63373,Male,37,Masters,3,91,24,39,36,8.0,7,80,Urban,Data Analyst,132922,0 +63374,Other,22,Bachelors,11,72,70,3,12,5.0,2,32,Urban,Software Engineer,49060,0 +63375,Male,54,Bachelors,1,50,83,48,47,7.0,1,69,Urban,HR Executive,32500,1 +63376,Female,58,Masters,5,51,28,1,40,6.0,4,8,Rural,ML Engineer,41853,0 +63377,Other,46,Diploma,10,48,12,31,7,5.0,5,5,Urban,Manager,90725,0 +63378,Male,47,Masters,19,72,54,51,38,3.0,0,53,Urban,Data Analyst,59260,0 +63379,Male,51,Bachelors,6,0,83,42,41,8.0,1,46,Urban,Manager,56161,0 +63380,Male,34,High School,0,50,77,19,77,7.0,6,10,Urban,Manager,105738,0 +63381,Female,43,Bachelors,6,65,43,65,18,3.0,0,84,Urban,Data Analyst,147156,1 +63382,Male,25,Bachelors,1,31,85,31,48,0.0,1,27,Urban,HR Executive,45555,0 +63383,Female,58,Masters,1,45,33,17,80,9.0,0,1,Rural,Data Analyst,58135,0 +63384,Male,34,High School,6,76,73,94,42,8.0,0,5,Urban,ML Engineer,80450,1 +63385,Female,29,Diploma,4,87,4,75,22,5.0,3,44,Semi-Urban,Manager,104665,0 +63386,Male,25,Bachelors,2,20,5,62,69,9.0,7,95,Urban,HR Executive,44716,0 +63387,Female,39,Bachelors,6,3,28,62,52,9.0,6,91,Urban,HR Executive,97998,0 +63388,Male,25,High School,19,48,30,72,87,0.0,5,3,Rural,Manager,119450,0 +63389,Male,32,Diploma,10,69,68,91,51,5.0,6,54,Urban,Software Engineer,100443,1 +63390,Male,21,Diploma,15,17,37,29,25,6.0,6,6,Urban,Data Analyst,96184,0 +63391,Male,45,High School,16,4,97,19,36,0.0,3,82,Urban,Data Analyst,123168,0 +63392,Female,43,Diploma,1,71,12,12,11,0.0,1,89,Semi-Urban,Manager,128793,0 +63393,Female,49,Bachelors,12,1,79,47,17,2.0,0,10,Urban,HR Executive,45292,0 +63394,Male,26,Bachelors,3,84,95,86,15,3.0,7,70,Urban,Software Engineer,128294,1 +63395,Male,37,Masters,8,46,90,41,82,7.0,5,32,Urban,ML Engineer,52414,0 +63396,Female,57,Masters,8,36,63,87,50,8.0,2,96,Semi-Urban,HR Executive,38779,1 +63397,Female,56,Masters,6,35,75,80,33,6.0,0,8,Rural,Manager,43648,0 +63398,Male,50,PhD,3,12,18,26,45,1.0,1,34,Urban,HR Executive,60494,0 +63399,Female,33,Bachelors,15,76,5,3,46,2.0,2,47,Urban,Data Analyst,148190,0 +63400,Male,59,Bachelors,5,8,14,30,33,6.0,6,15,Urban,Data Analyst,43012,0 +63401,Male,47,Masters,7,53,97,7,55,0.0,3,91,Urban,Manager,49082,1 +63402,Male,44,Bachelors,9,34,39,15,70,2.0,0,1,Urban,Software Engineer,60001,0 +63403,Female,44,Masters,8,29,10,77,21,0.0,4,11,Semi-Urban,Manager,102219,0 +63404,Female,35,Diploma,5,34,78,85,95,4.0,1,74,Urban,Manager,44264,1 +63405,Female,31,Masters,3,23,45,68,21,3.0,4,57,Urban,ML Engineer,104883,0 +63406,Male,49,Bachelors,16,90,94,53,33,3.0,0,58,Semi-Urban,ML Engineer,67609,1 +63407,Male,42,Masters,8,12,51,67,97,9.0,4,22,Urban,ML Engineer,98054,0 +63408,Male,56,Bachelors,9,17,54,13,95,3.0,2,34,Urban,HR Executive,146998,0 +63409,Female,42,High School,8,93,32,39,79,7.0,4,95,Rural,Data Analyst,71639,1 +63410,Male,31,Masters,15,13,90,35,32,5.0,3,93,Urban,Data Analyst,46304,0 +63411,Male,55,High School,16,53,92,49,43,8.0,5,37,Semi-Urban,Manager,28904,0 +63412,Female,25,Bachelors,8,81,84,96,76,3.0,4,30,Semi-Urban,Data Analyst,108471,1 +63413,Female,49,Masters,4,9,62,43,87,3.0,7,77,Urban,Software Engineer,144758,0 +63414,Male,51,Bachelors,19,24,27,87,75,1.0,1,39,Semi-Urban,HR Executive,106277,0 +63415,Male,30,Masters,14,52,64,57,60,1.0,7,90,Rural,Manager,138613,1 +63416,Male,41,Bachelors,13,48,61,21,39,6.0,0,52,Rural,Data Analyst,145058,0 +63417,Male,50,Masters,12,32,35,86,46,6.0,5,0,Urban,Manager,120054,0 +63418,Male,37,Masters,10,12,52,62,61,5.0,0,55,Semi-Urban,ML Engineer,38640,0 +63419,Male,37,PhD,10,44,98,22,19,2.0,6,15,Rural,Manager,89849,0 +63420,Other,47,Bachelors,8,39,4,97,88,2.0,2,23,Urban,Software Engineer,53277,0 +63421,Male,38,Bachelors,9,70,39,66,35,8.0,2,7,Semi-Urban,Data Analyst,111396,0 +63422,Male,36,Masters,9,98,44,90,20,1.0,4,18,Urban,ML Engineer,117176,1 +63423,Male,24,Bachelors,9,1,40,99,13,6.0,0,44,Urban,ML Engineer,42410,0 +63424,Male,30,Masters,19,99,65,96,82,5.0,2,94,Semi-Urban,Data Analyst,109862,1 +63425,Male,37,Masters,1,8,90,83,64,6.0,3,74,Urban,Software Engineer,21108,1 +63426,Male,52,Bachelors,12,92,38,72,24,6.0,1,99,Rural,Software Engineer,22887,1 +63427,Male,56,Masters,14,38,94,89,46,8.0,0,29,Semi-Urban,Manager,26181,1 +63428,Other,47,Masters,11,22,67,34,39,3.0,3,87,Rural,Manager,118961,0 +63429,Male,57,Diploma,7,91,50,22,94,1.0,6,7,Urban,Data Analyst,124970,0 +63430,Male,53,Diploma,18,92,79,14,72,7.0,0,25,Urban,HR Executive,30063,0 +63431,Male,30,Bachelors,4,97,20,49,45,0.0,2,96,Urban,Software Engineer,58509,1 +63432,Male,25,PhD,18,87,14,14,56,4.0,0,62,Urban,Software Engineer,118211,0 +63433,Male,36,Bachelors,11,58,34,51,96,2.0,3,98,Semi-Urban,Data Analyst,31643,1 +63434,Female,46,High School,8,55,33,35,37,0.0,4,36,Semi-Urban,ML Engineer,36367,0 +63435,Male,31,Bachelors,5,86,86,85,70,9.0,5,36,Urban,ML Engineer,128224,1 +63436,Male,23,Masters,8,85,2,88,9,9.0,6,77,Urban,ML Engineer,40558,1 +63437,Male,40,Diploma,3,24,50,60,7,8.0,2,72,Urban,Software Engineer,89350,0 +63438,Male,48,Diploma,0,89,66,34,76,6.0,4,55,Semi-Urban,ML Engineer,100389,1 +63439,Male,55,Diploma,13,91,70,34,28,5.0,7,21,Rural,Data Analyst,99091,0 +63440,Male,30,Masters,6,60,66,91,32,9.0,1,24,Semi-Urban,Data Analyst,147650,1 +63441,Male,42,High School,14,65,6,90,58,5.0,7,97,Urban,HR Executive,56388,1 +63442,Male,54,Diploma,8,29,5,83,88,1.0,2,56,Urban,ML Engineer,98835,0 +63443,Male,40,Bachelors,14,78,21,99,77,9.0,5,14,Semi-Urban,Data Analyst,104275,0 +63444,Female,22,Masters,2,26,44,65,95,9.0,7,6,Urban,Data Analyst,39285,0 +63445,Female,24,Masters,3,89,54,83,68,0.0,6,26,Urban,Software Engineer,25495,1 +63446,Female,36,High School,19,97,85,46,20,3.0,0,54,Urban,HR Executive,76376,1 +63447,Female,54,Bachelors,4,51,78,48,72,9.0,0,79,Semi-Urban,HR Executive,121229,1 +63448,Female,23,High School,2,36,66,62,95,7.0,0,93,Urban,ML Engineer,44165,1 +63449,Male,33,High School,8,86,45,54,61,3.0,1,28,Urban,HR Executive,27182,0 +63450,Male,55,Diploma,6,44,92,19,62,2.0,6,67,Semi-Urban,HR Executive,133427,0 +63451,Male,36,High School,8,70,34,49,28,6.0,6,51,Urban,HR Executive,23954,0 +63452,Female,35,PhD,18,86,69,63,98,5.0,4,56,Urban,Data Analyst,46706,1 +63453,Male,58,Bachelors,17,27,23,6,50,9.0,0,97,Urban,Software Engineer,62751,0 +63454,Female,48,Diploma,12,54,11,67,95,2.0,2,37,Urban,Data Analyst,112467,0 +63455,Female,50,Bachelors,11,44,50,35,11,8.0,5,11,Semi-Urban,Data Analyst,122887,0 +63456,Male,33,PhD,0,47,88,58,3,2.0,3,17,Rural,Software Engineer,45344,0 +63457,Male,33,Bachelors,15,50,24,95,10,6.0,1,91,Urban,ML Engineer,26056,1 +63458,Male,32,Diploma,9,92,66,88,49,7.0,2,47,Urban,Software Engineer,120157,1 +63459,Male,25,Bachelors,14,8,98,86,18,1.0,6,39,Semi-Urban,HR Executive,83869,0 +63460,Female,55,Bachelors,19,49,6,7,3,2.0,3,34,Semi-Urban,Data Analyst,46795,0 +63461,Male,23,Diploma,5,19,60,99,98,4.0,3,12,Urban,Data Analyst,72471,0 +63462,Other,46,Bachelors,8,37,47,86,45,7.0,0,91,Urban,HR Executive,59141,1 +63463,Other,39,Bachelors,18,1,53,20,85,4.0,6,80,Semi-Urban,Data Analyst,102631,0 +63464,Male,26,High School,4,4,23,25,32,9.0,3,0,Rural,Data Analyst,76544,0 +63465,Female,27,Diploma,10,58,52,74,89,7.0,1,61,Urban,HR Executive,43278,1 +63466,Male,46,Diploma,2,46,74,26,48,5.0,4,36,Rural,ML Engineer,51871,0 +63467,Female,59,Masters,7,71,75,40,90,1.0,1,1,Semi-Urban,ML Engineer,22532,0 +63468,Female,47,Diploma,2,60,16,71,41,6.0,3,21,Urban,Software Engineer,102434,0 +63469,Female,54,Bachelors,10,41,95,28,78,8.0,0,79,Urban,Software Engineer,145744,1 +63470,Male,47,Diploma,0,60,33,80,54,4.0,3,64,Rural,ML Engineer,53295,1 +63471,Female,58,Diploma,7,4,29,52,70,4.0,1,33,Semi-Urban,HR Executive,60207,0 +63472,Female,35,Masters,18,90,2,44,97,8.0,7,40,Semi-Urban,Manager,129780,0 +63473,Female,49,Masters,8,3,34,25,23,0.0,0,53,Urban,Data Analyst,33337,0 +63474,Male,49,Masters,5,98,35,64,10,9.0,4,71,Urban,HR Executive,99970,1 +63475,Female,53,High School,7,61,98,66,70,3.0,1,6,Semi-Urban,Software Engineer,56978,0 +63476,Female,54,Bachelors,5,7,94,21,66,5.0,4,14,Urban,Data Analyst,122565,0 +63477,Other,22,Masters,0,5,33,80,96,4.0,5,0,Semi-Urban,HR Executive,84899,0 +63478,Male,51,Masters,13,8,36,62,67,8.0,2,60,Urban,Software Engineer,69465,0 +63479,Male,27,Diploma,0,88,17,42,12,9.0,1,69,Rural,Software Engineer,78656,0 +63480,Female,35,High School,16,99,34,99,36,2.0,5,30,Urban,ML Engineer,129124,1 +63481,Male,47,Bachelors,4,61,72,46,87,5.0,6,42,Urban,ML Engineer,59580,0 +63482,Female,22,High School,9,74,95,42,82,6.0,6,59,Urban,Manager,121092,1 +63483,Male,41,Diploma,17,1,67,10,86,4.0,6,56,Semi-Urban,Data Analyst,32903,0 +63484,Female,44,High School,5,83,76,56,13,8.0,1,79,Rural,Software Engineer,72849,1 +63485,Female,57,Bachelors,15,2,75,99,36,3.0,1,45,Rural,Manager,46074,0 +63486,Male,36,Diploma,8,35,36,50,93,6.0,2,35,Urban,ML Engineer,135582,0 +63487,Female,25,Diploma,17,41,92,62,19,4.0,4,95,Rural,ML Engineer,139848,1 +63488,Female,25,Bachelors,10,71,51,33,41,1.0,0,63,Urban,Software Engineer,42043,0 +63489,Female,30,Masters,17,78,73,26,81,9.0,6,55,Urban,Software Engineer,33448,0 +63490,Male,55,Diploma,6,35,12,20,28,4.0,4,77,Semi-Urban,Data Analyst,31767,0 +63491,Female,44,Diploma,0,77,22,69,50,2.0,5,52,Semi-Urban,Software Engineer,65854,0 +63492,Male,40,PhD,1,73,68,93,98,7.0,7,35,Urban,HR Executive,56057,1 +63493,Male,21,Bachelors,2,98,51,67,53,6.0,3,76,Semi-Urban,ML Engineer,47874,1 +63494,Female,36,Diploma,17,13,33,45,59,6.0,2,31,Urban,Manager,135352,0 +63495,Male,41,Bachelors,14,66,38,9,9,7.0,7,56,Urban,Data Analyst,128535,0 +63496,Male,29,High School,0,22,47,23,98,6.0,5,96,Semi-Urban,Software Engineer,113305,0 +63497,Female,52,Bachelors,2,98,14,65,39,7.0,5,65,Urban,ML Engineer,49583,1 +63498,Male,52,Bachelors,9,85,8,79,8,0.0,1,42,Urban,Manager,68618,0 +63499,Female,30,Bachelors,13,84,60,21,89,1.0,6,55,Semi-Urban,HR Executive,62213,0 +63500,Male,41,Diploma,18,37,80,93,7,2.0,2,65,Semi-Urban,ML Engineer,46242,1 +63501,Female,56,High School,14,85,1,67,38,7.0,2,21,Urban,Software Engineer,107030,0 +63502,Male,35,Bachelors,17,68,99,71,88,0.0,3,86,Rural,Software Engineer,35839,1 +63503,Male,32,Bachelors,9,27,4,30,11,3.0,1,61,Urban,Data Analyst,63182,0 +63504,Male,49,Bachelors,18,24,2,62,97,1.0,1,88,Urban,Data Analyst,111292,0 +63505,Male,43,Masters,13,32,47,31,37,4.0,6,80,Urban,Software Engineer,129074,0 +63506,Female,30,High School,9,62,37,16,75,8.0,6,71,Semi-Urban,Manager,29950,0 +63507,Female,39,High School,2,29,73,66,82,1.0,4,32,Urban,HR Executive,31245,0 +63508,Male,47,Bachelors,3,56,50,49,28,5.0,5,75,Rural,Software Engineer,61099,0 +63509,Male,50,Bachelors,15,60,27,84,42,8.0,6,14,Urban,ML Engineer,106820,0 +63510,Male,46,Bachelors,17,51,97,95,20,5.0,7,68,Semi-Urban,ML Engineer,119691,1 +63511,Male,59,Bachelors,8,73,72,92,80,3.0,6,56,Semi-Urban,Data Analyst,88594,1 +63512,Male,23,Diploma,6,72,25,83,94,8.0,2,72,Urban,Software Engineer,71869,1 +63513,Male,33,Bachelors,1,97,55,33,58,6.0,4,87,Urban,HR Executive,43666,1 +63514,Female,38,Masters,2,94,5,73,61,1.0,2,76,Urban,ML Engineer,78207,1 +63515,Female,54,Bachelors,19,31,13,72,72,6.0,3,4,Urban,HR Executive,134120,0 +63516,Male,39,Bachelors,5,59,29,74,38,5.0,2,50,Semi-Urban,Manager,34051,0 +63517,Male,34,Diploma,1,3,17,35,17,5.0,1,30,Semi-Urban,Software Engineer,60712,0 +63518,Female,49,High School,17,35,85,86,24,8.0,3,43,Urban,Data Analyst,23546,1 +63519,Female,44,Bachelors,5,76,45,34,56,6.0,5,23,Semi-Urban,Data Analyst,138188,0 +63520,Male,47,Diploma,1,51,1,71,46,1.0,3,89,Rural,Software Engineer,65269,0 +63521,Female,38,Bachelors,13,8,95,12,7,5.0,1,66,Urban,Data Analyst,58528,0 +63522,Male,36,High School,15,33,37,94,95,0.0,5,60,Rural,Software Engineer,59487,0 +63523,Female,37,Masters,13,11,5,32,73,3.0,5,18,Rural,Data Analyst,57573,0 +63524,Male,46,Masters,18,35,57,95,43,3.0,2,88,Urban,Data Analyst,65518,1 +63525,Female,59,Masters,13,26,93,44,33,1.0,0,54,Urban,ML Engineer,126539,0 +63526,Male,44,Masters,18,80,62,47,54,4.0,0,68,Urban,Manager,68275,1 +63527,Female,49,Diploma,7,35,21,36,67,9.0,5,72,Urban,HR Executive,133577,0 +63528,Male,30,High School,11,61,43,23,95,9.0,5,91,Semi-Urban,Manager,109639,0 +63529,Male,42,Diploma,10,48,26,51,46,2.0,0,75,Semi-Urban,ML Engineer,133990,0 +63530,Female,48,High School,8,0,17,59,41,4.0,0,24,Urban,Data Analyst,26403,0 +63531,Other,53,High School,3,62,54,14,94,8.0,7,46,Urban,Data Analyst,145442,0 +63532,Other,38,Bachelors,10,18,93,85,72,4.0,1,49,Semi-Urban,Manager,57888,1 +63533,Female,43,Bachelors,9,45,22,82,74,3.0,2,23,Rural,ML Engineer,38825,0 +63534,Female,58,High School,15,69,41,92,7,2.0,1,2,Rural,Data Analyst,141749,0 +63535,Other,54,Diploma,11,72,77,28,25,1.0,4,6,Urban,HR Executive,64563,0 +63536,Male,24,PhD,4,96,16,43,74,7.0,2,65,Urban,Software Engineer,106437,0 +63537,Male,31,Bachelors,12,50,0,96,98,8.0,7,86,Urban,Software Engineer,77411,0 +63538,Male,31,Diploma,3,31,32,13,80,3.0,5,90,Urban,HR Executive,148473,0 +63539,Male,27,Bachelors,7,19,19,58,79,2.0,7,67,Rural,HR Executive,31542,0 +63540,Other,41,Masters,16,98,1,49,73,8.0,0,27,Urban,ML Engineer,112407,0 +63541,Male,53,Bachelors,0,97,68,3,4,3.0,6,24,Semi-Urban,Manager,20635,0 +63542,Male,41,Bachelors,12,96,81,40,51,8.0,4,73,Rural,Manager,36306,1 +63543,Female,58,Diploma,16,80,13,51,77,8.0,0,1,Urban,Manager,51927,0 +63544,Female,54,Masters,19,5,73,78,70,1.0,6,51,Urban,Manager,90015,0 +63545,Female,59,Bachelors,11,68,71,21,29,2.0,6,29,Rural,Software Engineer,22820,0 +63546,Female,22,Masters,6,89,61,41,95,3.0,6,68,Urban,HR Executive,66234,1 +63547,Male,38,Diploma,18,97,53,81,78,0.0,2,98,Urban,HR Executive,132074,1 +63548,Male,53,Diploma,6,64,88,0,91,8.0,7,77,Semi-Urban,Manager,119659,0 +63549,Male,36,Bachelors,1,10,86,33,88,1.0,7,85,Semi-Urban,HR Executive,126548,0 +63550,Male,34,Bachelors,13,67,4,98,13,7.0,5,3,Semi-Urban,Data Analyst,146979,0 +63551,Male,42,Bachelors,17,36,75,59,95,1.0,1,43,Urban,ML Engineer,87680,0 +63552,Female,21,Bachelors,18,47,77,54,75,3.0,7,3,Urban,Data Analyst,145394,0 +63553,Male,38,High School,12,54,88,65,97,1.0,0,66,Urban,Manager,39522,1 +63554,Male,58,Diploma,10,60,10,27,62,5.0,7,32,Urban,HR Executive,134309,0 +63555,Male,23,Diploma,1,63,49,19,59,3.0,0,32,Urban,ML Engineer,34106,0 +63556,Other,38,High School,13,49,55,65,51,0.0,3,54,Rural,Manager,93875,0 +63557,Female,25,Diploma,9,70,77,26,86,8.0,6,79,Semi-Urban,Software Engineer,22179,1 +63558,Male,27,High School,14,93,74,95,69,4.0,1,40,Urban,ML Engineer,111023,1 +63559,Male,53,Bachelors,11,84,62,0,30,6.0,2,40,Urban,ML Engineer,119247,0 +63560,Other,57,Diploma,6,12,22,92,45,6.0,0,23,Semi-Urban,ML Engineer,61088,0 +63561,Other,43,Diploma,12,91,36,46,93,0.0,1,92,Urban,HR Executive,149841,1 +63562,Male,25,PhD,11,62,57,19,14,5.0,7,99,Semi-Urban,Software Engineer,114627,1 +63563,Male,44,High School,15,10,48,60,22,7.0,3,69,Urban,Data Analyst,47100,0 +63564,Female,34,Diploma,18,63,42,68,77,1.0,2,45,Rural,Manager,33535,0 +63565,Female,30,PhD,7,42,38,77,92,5.0,5,17,Urban,Software Engineer,82282,0 +63566,Female,44,Diploma,7,83,18,80,78,9.0,2,38,Rural,HR Executive,41556,0 +63567,Male,23,PhD,6,62,23,54,23,4.0,4,69,Semi-Urban,Manager,98141,0 +63568,Other,33,Diploma,4,21,50,4,87,2.0,7,8,Urban,Manager,30078,0 +63569,Male,57,High School,0,31,83,37,44,2.0,7,77,Urban,HR Executive,32510,0 +63570,Female,36,Diploma,13,94,52,88,15,6.0,1,81,Urban,HR Executive,44015,1 +63571,Male,35,Diploma,10,93,47,93,14,4.0,7,13,Semi-Urban,HR Executive,120932,1 +63572,Female,23,Diploma,10,58,38,0,7,5.0,5,44,Urban,Software Engineer,73244,0 +63573,Female,30,Diploma,3,73,14,19,41,6.0,1,1,Semi-Urban,Data Analyst,83085,0 +63574,Male,30,High School,7,74,40,32,2,5.0,1,53,Rural,Manager,109967,0 +63575,Male,23,Masters,12,91,61,65,60,3.0,3,69,Urban,HR Executive,83200,1 +63576,Male,45,Bachelors,9,52,89,76,99,1.0,1,74,Semi-Urban,ML Engineer,143514,1 +63577,Other,40,Bachelors,9,99,6,26,15,6.0,7,17,Rural,Data Analyst,95509,0 +63578,Male,53,Masters,10,1,72,8,22,7.0,5,89,Urban,ML Engineer,98550,0 +63579,Male,36,Diploma,16,29,37,9,47,3.0,5,69,Urban,HR Executive,97882,0 +63580,Male,30,Bachelors,3,47,86,95,16,7.0,3,40,Urban,Software Engineer,54473,1 +63581,Female,54,Bachelors,1,63,14,80,41,4.0,6,32,Urban,Data Analyst,100301,0 +63582,Male,49,High School,17,13,92,17,51,8.0,1,87,Urban,HR Executive,123451,0 +63583,Male,47,Diploma,5,59,42,4,52,7.0,7,2,Urban,Data Analyst,37205,0 +63584,Male,43,Masters,14,58,20,72,1,9.0,1,1,Semi-Urban,HR Executive,65957,0 +63585,Female,30,Masters,12,63,38,72,69,1.0,1,41,Urban,HR Executive,25125,0 +63586,Female,43,Bachelors,1,13,14,51,91,5.0,7,65,Urban,Manager,115157,0 +63587,Male,44,Bachelors,3,59,47,76,31,8.0,6,11,Urban,Data Analyst,65235,0 +63588,Male,31,Bachelors,14,68,13,58,80,2.0,4,63,Urban,Software Engineer,32402,0 +63589,Male,59,Bachelors,0,66,14,11,27,0.0,3,69,Urban,Data Analyst,89205,0 +63590,Female,39,Bachelors,5,97,96,36,85,2.0,7,5,Urban,Software Engineer,62013,0 +63591,Male,42,Bachelors,0,71,70,31,49,3.0,6,46,Urban,Software Engineer,57599,0 +63592,Male,53,Diploma,9,50,12,42,87,3.0,4,48,Urban,Manager,144141,0 +63593,Male,54,Bachelors,3,55,5,31,38,8.0,1,13,Semi-Urban,Software Engineer,23502,0 +63594,Female,49,Diploma,4,72,72,56,75,7.0,7,17,Rural,HR Executive,42431,0 +63595,Female,59,Bachelors,13,78,23,78,39,3.0,2,71,Urban,Software Engineer,54682,1 +63596,Female,48,Bachelors,15,21,71,34,81,8.0,0,55,Rural,Manager,142117,0 +63597,Female,46,Diploma,0,1,41,61,81,5.0,6,2,Urban,ML Engineer,53855,0 +63598,Female,21,Diploma,17,53,75,53,2,0.0,5,53,Rural,Data Analyst,130518,0 +63599,Female,49,Diploma,7,7,17,45,60,0.0,3,54,Urban,ML Engineer,123385,0 +63600,Male,27,Masters,19,83,3,28,99,3.0,4,84,Urban,Manager,43635,0 +63601,Male,46,Bachelors,15,34,56,4,33,4.0,4,43,Urban,Data Analyst,69255,0 +63602,Female,22,Bachelors,10,13,78,61,48,7.0,4,3,Urban,Manager,64998,0 +63603,Male,41,Masters,6,60,64,0,5,4.0,3,72,Semi-Urban,Manager,64531,0 +63604,Male,39,Bachelors,15,83,37,78,29,0.0,6,28,Semi-Urban,Data Analyst,106761,0 +63605,Male,23,Bachelors,0,29,25,58,6,8.0,2,70,Rural,ML Engineer,75028,0 +63606,Other,54,High School,10,47,47,43,96,3.0,5,18,Semi-Urban,HR Executive,65540,0 +63607,Female,28,High School,17,74,59,81,41,1.0,4,17,Semi-Urban,ML Engineer,60937,0 +63608,Female,40,Diploma,0,38,70,34,17,8.0,7,72,Rural,Data Analyst,60847,0 +63609,Female,28,Masters,10,64,88,70,73,1.0,5,87,Semi-Urban,Manager,116464,1 +63610,Male,31,PhD,14,67,45,64,51,7.0,5,49,Urban,HR Executive,84817,0 +63611,Male,53,Bachelors,18,29,26,33,20,6.0,0,88,Urban,Data Analyst,118600,0 +63612,Male,50,Bachelors,9,89,38,48,67,9.0,6,23,Urban,Data Analyst,133647,0 +63613,Male,56,Bachelors,11,58,7,8,45,2.0,5,57,Semi-Urban,ML Engineer,20791,0 +63614,Female,52,Bachelors,11,48,2,98,47,4.0,4,91,Urban,Manager,51826,0 +63615,Male,28,High School,9,28,37,81,75,7.0,1,27,Rural,ML Engineer,115818,0 +63616,Male,26,Bachelors,8,56,35,68,6,4.0,3,43,Urban,Manager,46069,0 +63617,Male,29,High School,8,39,43,78,46,6.0,6,93,Urban,HR Executive,98365,1 +63618,Male,40,Masters,12,66,36,45,4,1.0,6,57,Urban,HR Executive,92102,0 +63619,Male,55,Diploma,12,72,19,41,56,8.0,4,46,Urban,ML Engineer,147533,0 +63620,Male,34,Bachelors,6,73,52,34,63,0.0,7,84,Urban,HR Executive,71499,1 +63621,Male,31,High School,2,70,30,99,93,7.0,4,47,Urban,ML Engineer,33467,1 +63622,Male,56,Masters,11,17,89,20,69,0.0,0,65,Urban,Manager,125645,0 +63623,Male,28,Masters,3,60,67,42,29,8.0,0,30,Urban,Manager,137211,0 +63624,Male,57,Masters,10,67,35,15,8,9.0,3,23,Rural,HR Executive,62835,0 +63625,Male,57,High School,4,29,27,9,35,4.0,6,21,Semi-Urban,Software Engineer,148087,0 +63626,Male,39,Diploma,19,9,65,9,24,4.0,3,69,Semi-Urban,HR Executive,117757,0 +63627,Male,49,Diploma,10,98,51,48,29,9.0,0,51,Semi-Urban,Software Engineer,130744,1 +63628,Female,46,High School,17,10,93,97,21,6.0,5,3,Urban,ML Engineer,57885,0 +63629,Male,46,Bachelors,19,93,69,31,35,1.0,0,0,Rural,HR Executive,32240,0 +63630,Female,58,PhD,13,58,5,6,31,1.0,3,96,Semi-Urban,Software Engineer,110664,0 +63631,Male,39,PhD,4,92,30,74,23,2.0,5,41,Rural,Software Engineer,105564,1 +63632,Male,44,Diploma,12,29,14,4,80,3.0,2,25,Urban,ML Engineer,38923,0 +63633,Male,22,High School,10,82,28,49,11,6.0,1,66,Rural,Software Engineer,61472,0 +63634,Male,42,High School,3,69,75,69,93,4.0,2,62,Rural,Data Analyst,108385,1 +63635,Male,32,Bachelors,18,55,30,50,31,5.0,6,75,Semi-Urban,ML Engineer,117874,0 +63636,Male,28,High School,19,37,74,35,33,5.0,7,45,Semi-Urban,Data Analyst,148378,0 +63637,Female,30,Diploma,18,76,67,54,85,0.0,1,36,Urban,Manager,84652,0 +63638,Female,22,Bachelors,11,38,94,22,12,2.0,4,86,Urban,HR Executive,116950,0 +63639,Male,25,Diploma,7,97,81,84,64,1.0,1,71,Rural,HR Executive,50588,1 +63640,Male,43,Bachelors,13,54,3,48,5,9.0,4,90,Urban,ML Engineer,28191,0 +63641,Female,54,Bachelors,14,51,75,28,82,9.0,3,35,Urban,Data Analyst,57170,0 +63642,Male,22,High School,1,70,29,61,28,4.0,0,9,Urban,Manager,115230,0 +63643,Male,37,Diploma,0,54,78,69,64,0.0,6,48,Urban,HR Executive,117984,1 +63644,Male,28,Diploma,1,33,88,4,79,3.0,2,55,Semi-Urban,Manager,36132,0 +63645,Male,42,Bachelors,19,1,76,29,60,2.0,7,3,Semi-Urban,HR Executive,127619,0 +63646,Male,25,Bachelors,14,33,88,8,13,4.0,1,90,Urban,Manager,81418,0 +63647,Male,47,Bachelors,0,11,10,87,46,4.0,3,56,Urban,Manager,100321,0 +63648,Male,33,Bachelors,18,81,47,14,41,7.0,5,72,Rural,Manager,140454,0 +63649,Male,29,Diploma,10,3,88,0,62,6.0,3,48,Semi-Urban,Software Engineer,133893,0 +63650,Male,59,Masters,10,21,52,61,96,0.0,2,35,Urban,HR Executive,121029,0 +63651,Male,46,Bachelors,10,55,22,79,33,1.0,2,47,Urban,Manager,116080,0 +63652,Male,57,PhD,4,82,23,16,31,2.0,1,20,Rural,ML Engineer,26246,0 +63653,Male,54,Masters,18,24,96,69,98,6.0,1,12,Urban,HR Executive,60508,0 +63654,Male,40,High School,7,81,28,78,1,0.0,5,1,Urban,Software Engineer,33377,0 +63655,Male,45,PhD,14,77,90,15,3,8.0,5,22,Rural,Data Analyst,61633,0 +63656,Male,30,Diploma,6,63,55,31,67,3.0,0,44,Urban,Software Engineer,55458,0 +63657,Male,52,Masters,0,88,27,46,65,0.0,2,88,Semi-Urban,Software Engineer,107123,1 +63658,Male,23,Diploma,7,61,91,31,12,5.0,4,36,Urban,HR Executive,140534,0 +63659,Male,32,Bachelors,2,45,14,20,74,8.0,5,73,Semi-Urban,ML Engineer,125465,0 +63660,Male,51,Bachelors,4,94,66,57,94,4.0,3,34,Rural,Manager,102633,1 +63661,Male,51,Diploma,0,69,44,53,15,1.0,3,21,Urban,HR Executive,65660,0 +63662,Female,52,Bachelors,12,40,95,57,37,6.0,6,45,Rural,HR Executive,24266,0 +63663,Female,59,PhD,3,28,49,60,24,7.0,1,43,Semi-Urban,Data Analyst,149822,0 +63664,Male,51,Masters,10,79,51,7,73,2.0,1,83,Urban,Software Engineer,23990,0 +63665,Male,24,Bachelors,6,76,35,49,75,2.0,0,25,Urban,HR Executive,143426,0 +63666,Male,27,Masters,8,15,89,84,6,6.0,5,98,Semi-Urban,HR Executive,35886,1 +63667,Male,49,Bachelors,13,6,29,33,72,3.0,6,3,Urban,ML Engineer,122645,0 +63668,Male,23,Bachelors,14,89,23,42,22,7.0,0,52,Urban,Manager,63228,0 +63669,Male,39,PhD,11,20,7,76,43,8.0,7,32,Urban,ML Engineer,143723,0 +63670,Male,29,Masters,4,62,72,96,83,6.0,7,30,Rural,Software Engineer,26410,1 +63671,Female,49,Diploma,13,84,92,94,58,7.0,0,81,Rural,Data Analyst,44715,1 +63672,Other,38,Diploma,18,48,73,32,39,2.0,7,62,Urban,Manager,139688,0 +63673,Female,41,Diploma,18,48,51,34,71,6.0,1,26,Urban,Software Engineer,132455,0 +63674,Female,53,Bachelors,8,99,71,50,6,7.0,6,39,Urban,Software Engineer,64894,1 +63675,Male,30,High School,1,29,54,18,81,4.0,5,86,Urban,Manager,116785,0 +63676,Female,49,Bachelors,0,78,43,99,44,3.0,5,47,Urban,Software Engineer,138057,1 +63677,Male,47,Bachelors,9,45,30,40,22,8.0,3,56,Urban,Data Analyst,65840,0 +63678,Other,52,Masters,17,76,99,71,48,4.0,1,6,Urban,Data Analyst,131810,1 +63679,Female,53,Bachelors,9,91,52,68,1,7.0,7,54,Urban,HR Executive,82776,1 +63680,Male,27,Diploma,6,22,52,21,8,0.0,7,68,Urban,ML Engineer,73593,0 +63681,Female,55,Masters,17,33,44,34,92,4.0,5,24,Urban,ML Engineer,64453,0 +63682,Male,38,High School,9,54,83,67,54,1.0,5,82,Rural,Manager,32583,1 +63683,Male,30,High School,8,39,62,84,60,4.0,4,73,Urban,ML Engineer,112651,1 +63684,Female,51,Bachelors,0,79,31,57,30,1.0,3,52,Rural,HR Executive,132619,0 +63685,Male,34,Bachelors,1,83,30,27,82,5.0,0,61,Urban,Manager,82166,0 +63686,Female,21,Bachelors,15,47,51,6,90,0.0,2,6,Urban,Manager,85188,0 +63687,Male,50,Bachelors,12,57,5,20,27,3.0,7,11,Semi-Urban,HR Executive,23645,0 +63688,Male,21,Diploma,11,61,32,12,6,5.0,0,45,Urban,HR Executive,133920,0 +63689,Female,40,Bachelors,15,99,46,23,49,1.0,3,92,Urban,HR Executive,102324,1 +63690,Female,39,Masters,19,30,61,83,40,1.0,2,12,Urban,Data Analyst,26034,0 +63691,Male,39,Masters,8,20,48,65,46,2.0,7,67,Urban,ML Engineer,69356,0 +63692,Male,31,High School,11,47,63,56,70,4.0,4,68,Semi-Urban,HR Executive,100448,0 +63693,Male,33,Diploma,5,97,70,35,19,0.0,3,13,Urban,ML Engineer,101989,0 +63694,Female,34,Diploma,16,3,15,67,70,6.0,3,99,Urban,Data Analyst,137167,0 +63695,Male,44,High School,8,11,16,87,85,3.0,1,14,Semi-Urban,Data Analyst,103719,0 +63696,Female,47,High School,10,82,54,43,36,9.0,4,96,Rural,HR Executive,126629,1 +63697,Female,23,PhD,13,89,64,62,36,1.0,3,20,Rural,Manager,126041,0 +63698,Male,24,Bachelors,15,77,69,18,1,3.0,4,96,Rural,Software Engineer,105886,1 +63699,Male,52,Bachelors,1,3,71,39,4,6.0,1,34,Urban,Data Analyst,58484,0 +63700,Male,51,Bachelors,8,59,5,65,24,4.0,7,36,Urban,Software Engineer,110986,0 +63701,Male,53,High School,7,12,1,99,59,6.0,0,74,Rural,Data Analyst,103628,0 +63702,Female,29,Bachelors,10,91,54,34,72,5.0,0,66,Urban,Data Analyst,123051,1 +63703,Male,50,Diploma,17,71,43,76,50,1.0,3,74,Urban,ML Engineer,119575,1 +63704,Male,49,Bachelors,17,26,52,68,79,3.0,3,76,Semi-Urban,HR Executive,98645,0 +63705,Female,45,Bachelors,7,84,31,71,96,6.0,0,91,Rural,Data Analyst,133983,1 +63706,Male,49,Bachelors,11,70,8,19,94,2.0,0,56,Urban,ML Engineer,138116,0 +63707,Male,58,Bachelors,19,42,88,72,51,0.0,1,34,Urban,Manager,44886,1 +63708,Male,37,Diploma,8,89,51,98,92,4.0,3,15,Semi-Urban,Data Analyst,61553,1 +63709,Other,30,Bachelors,7,6,85,5,94,3.0,3,80,Urban,Manager,126384,0 +63710,Female,48,Masters,0,95,16,14,2,8.0,6,56,Rural,HR Executive,53706,0 +63711,Female,48,Bachelors,16,2,96,53,46,8.0,3,16,Urban,Software Engineer,101762,0 +63712,Male,35,Bachelors,11,73,75,42,1,0.0,6,78,Semi-Urban,ML Engineer,100051,1 +63713,Male,27,Diploma,14,81,28,98,12,1.0,6,51,Urban,Software Engineer,24785,1 +63714,Male,39,Bachelors,3,20,61,7,4,4.0,2,81,Rural,HR Executive,62738,0 +63715,Female,57,PhD,10,21,8,18,68,0.0,6,40,Urban,ML Engineer,146117,0 +63716,Male,43,Bachelors,3,96,41,62,14,6.0,7,71,Semi-Urban,HR Executive,22666,1 +63717,Male,39,Bachelors,17,26,86,47,23,1.0,0,56,Urban,HR Executive,43035,0 +63718,Male,50,Bachelors,5,48,56,54,26,5.0,3,1,Urban,ML Engineer,45098,0 +63719,Female,24,Bachelors,6,44,3,89,76,5.0,2,21,Urban,Manager,47511,0 +63720,Female,36,Bachelors,1,65,99,74,0,6.0,6,21,Urban,HR Executive,141286,1 +63721,Male,37,Diploma,9,91,8,86,73,4.0,7,88,Urban,Software Engineer,33095,1 +63722,Female,28,Bachelors,4,75,3,84,37,4.0,3,73,Urban,Data Analyst,79922,0 +63723,Female,42,Bachelors,9,83,20,62,8,9.0,4,82,Rural,ML Engineer,92125,1 +63724,Female,56,Bachelors,5,69,47,24,8,2.0,3,66,Urban,HR Executive,69445,0 +63725,Female,35,PhD,0,81,16,80,69,8.0,0,97,Rural,Manager,120324,1 +63726,Male,33,Bachelors,11,51,61,6,84,8.0,5,15,Urban,Manager,102988,0 +63727,Female,46,PhD,1,53,39,48,73,3.0,4,14,Urban,Manager,107887,0 +63728,Male,58,Bachelors,17,67,39,74,37,4.0,1,9,Urban,ML Engineer,82960,0 +63729,Male,58,Bachelors,5,24,24,17,35,9.0,3,68,Urban,Data Analyst,72961,0 +63730,Female,27,Diploma,19,76,71,6,12,2.0,1,94,Rural,Data Analyst,79082,1 +63731,Male,43,Bachelors,6,5,80,83,87,4.0,2,4,Semi-Urban,Software Engineer,28283,0 +63732,Female,39,Diploma,19,76,79,34,24,2.0,5,39,Urban,Software Engineer,131277,0 +63733,Male,51,Diploma,7,28,68,41,37,1.0,6,52,Urban,Data Analyst,102171,0 +63734,Male,53,Bachelors,12,7,44,59,45,5.0,6,98,Rural,Software Engineer,25776,0 +63735,Other,32,Bachelors,16,37,4,56,90,1.0,1,51,Rural,Data Analyst,98622,0 +63736,Male,21,Diploma,17,96,6,10,56,4.0,3,17,Rural,Data Analyst,86977,0 +63737,Male,45,Masters,1,26,44,93,13,5.0,3,54,Semi-Urban,Manager,37396,0 +63738,Male,53,Diploma,0,50,77,50,32,2.0,4,37,Semi-Urban,HR Executive,25057,0 +63739,Female,26,Bachelors,0,1,88,74,64,1.0,2,77,Semi-Urban,ML Engineer,144230,0 +63740,Male,42,Bachelors,17,25,86,62,79,6.0,2,74,Urban,Software Engineer,91161,1 +63741,Male,55,Bachelors,5,61,24,18,54,4.0,4,19,Urban,ML Engineer,114592,0 +63742,Male,29,High School,7,97,55,19,88,8.0,7,45,Rural,Data Analyst,71172,0 +63743,Female,49,Masters,13,47,99,10,14,1.0,1,92,Rural,ML Engineer,98830,1 +63744,Male,51,Diploma,17,38,22,25,97,1.0,7,13,Urban,Manager,71968,0 +63745,Male,45,Masters,13,9,38,59,84,6.0,3,37,Urban,Data Analyst,43360,0 +63746,Female,35,Diploma,2,25,20,11,11,9.0,0,83,Urban,Manager,137271,0 +63747,Female,54,Bachelors,3,4,30,43,44,6.0,2,89,Semi-Urban,HR Executive,60932,0 +63748,Male,21,Bachelors,4,17,82,11,98,7.0,1,98,Urban,Software Engineer,45572,0 +63749,Female,51,Bachelors,18,54,34,15,66,8.0,7,28,Urban,HR Executive,56119,0 +63750,Male,45,Bachelors,1,54,4,63,9,9.0,2,23,Urban,Manager,48941,0 +63751,Male,43,Bachelors,14,49,41,40,46,4.0,2,46,Urban,HR Executive,113635,0 +63752,Male,44,Bachelors,9,30,15,82,71,9.0,6,7,Urban,Data Analyst,75254,0 +63753,Male,58,Bachelors,15,29,80,15,65,0.0,3,78,Urban,Data Analyst,100540,0 +63754,Male,48,Bachelors,0,36,95,35,93,3.0,5,41,Rural,Data Analyst,107132,0 +63755,Male,51,Diploma,0,55,24,82,61,2.0,7,60,Urban,ML Engineer,49456,0 +63756,Male,21,Bachelors,2,77,66,6,52,9.0,6,71,Semi-Urban,Software Engineer,77629,0 +63757,Female,36,Masters,8,18,42,43,42,8.0,3,2,Urban,ML Engineer,148199,0 +63758,Female,30,Masters,13,27,81,61,62,2.0,7,77,Semi-Urban,Manager,125186,1 +63759,Male,54,Masters,9,64,17,45,95,2.0,2,56,Urban,Manager,76900,0 +63760,Male,28,High School,3,63,8,10,48,6.0,0,86,Urban,Data Analyst,58601,0 +63761,Male,49,Bachelors,17,87,97,64,23,8.0,1,35,Semi-Urban,HR Executive,30526,1 +63762,Female,47,Masters,6,42,13,22,3,6.0,3,90,Urban,HR Executive,127288,0 +63763,Female,22,High School,17,87,11,4,10,0.0,0,10,Urban,Manager,69216,0 +63764,Female,31,Bachelors,6,23,22,39,70,6.0,6,45,Semi-Urban,ML Engineer,32083,0 +63765,Male,38,Masters,15,39,49,36,30,3.0,1,14,Urban,Manager,70045,0 +63766,Male,29,Masters,16,64,80,32,96,6.0,6,1,Semi-Urban,Data Analyst,108287,0 +63767,Male,58,Bachelors,14,18,29,13,93,3.0,1,5,Urban,Data Analyst,71754,0 +63768,Male,50,Bachelors,18,33,70,52,45,7.0,3,69,Semi-Urban,ML Engineer,115579,0 +63769,Female,41,Bachelors,9,59,43,31,66,3.0,7,7,Urban,Manager,52461,0 +63770,Female,56,Bachelors,16,63,95,5,59,8.0,7,68,Semi-Urban,HR Executive,83387,0 +63771,Female,27,Diploma,18,44,12,58,27,4.0,0,74,Urban,Software Engineer,80619,0 +63772,Female,46,Masters,18,63,77,66,57,2.0,7,49,Urban,HR Executive,115432,1 +63773,Male,52,Bachelors,10,99,42,16,24,9.0,7,86,Urban,Manager,25727,1 +63774,Female,36,Masters,14,39,4,70,5,0.0,6,66,Semi-Urban,ML Engineer,114463,0 +63775,Female,48,Bachelors,6,65,93,83,85,0.0,3,78,Semi-Urban,HR Executive,74116,1 +63776,Male,46,PhD,12,11,99,55,17,4.0,0,93,Urban,HR Executive,23496,1 +63777,Female,31,High School,9,66,96,32,75,5.0,4,79,Urban,ML Engineer,33408,1 +63778,Male,27,Diploma,4,49,33,88,48,8.0,0,84,Urban,HR Executive,148866,1 +63779,Male,51,High School,18,20,39,77,62,8.0,1,34,Semi-Urban,Software Engineer,64328,0 +63780,Male,56,Masters,7,86,84,51,90,0.0,6,55,Rural,ML Engineer,54649,1 +63781,Male,36,Diploma,18,71,27,88,29,9.0,1,42,Urban,Manager,147295,0 +63782,Male,45,Diploma,7,95,96,36,96,9.0,4,31,Rural,Software Engineer,119218,1 +63783,Male,21,Bachelors,11,75,45,57,94,4.0,2,36,Urban,HR Executive,61906,0 +63784,Female,31,High School,10,71,6,56,45,7.0,2,72,Rural,Software Engineer,60613,0 +63785,Male,48,Masters,16,4,82,66,76,3.0,5,98,Rural,Software Engineer,52913,1 +63786,Male,58,Bachelors,3,50,9,2,68,5.0,2,20,Urban,ML Engineer,74779,0 +63787,Male,40,Bachelors,10,76,43,55,51,0.0,5,96,Urban,Data Analyst,67882,1 +63788,Female,45,Bachelors,5,32,15,23,72,5.0,4,28,Urban,ML Engineer,69507,0 +63789,Male,28,Diploma,16,31,67,77,95,5.0,3,68,Urban,HR Executive,91312,1 +63790,Male,26,PhD,17,50,83,35,0,2.0,7,34,Urban,HR Executive,82786,0 +63791,Female,38,Diploma,10,40,17,57,82,6.0,5,70,Rural,Data Analyst,142728,0 +63792,Male,49,Bachelors,4,81,59,83,19,9.0,0,77,Urban,Software Engineer,137714,1 +63793,Female,41,Bachelors,15,26,10,18,70,8.0,7,99,Urban,ML Engineer,126025,0 +63794,Male,48,Masters,6,81,30,66,19,7.0,7,46,Rural,Manager,129297,0 +63795,Male,42,Bachelors,5,16,7,61,96,2.0,5,37,Semi-Urban,ML Engineer,121059,0 +63796,Female,21,High School,6,51,28,83,65,2.0,4,70,Urban,HR Executive,130909,0 +63797,Other,39,Bachelors,16,51,90,91,40,1.0,0,53,Semi-Urban,ML Engineer,128009,1 +63798,Female,52,Bachelors,15,93,13,61,35,9.0,1,1,Semi-Urban,Manager,63277,0 +63799,Male,40,Bachelors,6,51,46,6,28,1.0,1,35,Urban,ML Engineer,125475,0 +63800,Male,30,Diploma,10,81,16,87,8,3.0,4,28,Urban,Software Engineer,29405,0 +63801,Male,48,Bachelors,4,69,37,11,6,0.0,7,36,Semi-Urban,HR Executive,149550,0 +63802,Female,25,PhD,7,42,0,85,9,7.0,6,93,Urban,Software Engineer,126356,0 +63803,Male,38,Diploma,15,76,28,63,74,2.0,0,75,Urban,Data Analyst,104497,1 +63804,Female,53,Bachelors,12,20,71,24,44,6.0,6,75,Urban,Software Engineer,96773,0 +63805,Male,36,Bachelors,6,89,77,20,51,0.0,6,30,Urban,Manager,147324,0 +63806,Male,29,Diploma,7,68,6,1,3,0.0,4,67,Semi-Urban,Manager,21706,0 +63807,Male,51,Bachelors,7,50,35,0,45,6.0,0,18,Rural,ML Engineer,66481,0 +63808,Female,29,Diploma,4,49,87,4,67,1.0,4,30,Urban,HR Executive,122834,0 +63809,Male,48,Bachelors,8,74,76,43,80,0.0,6,59,Semi-Urban,Software Engineer,66330,1 +63810,Male,48,Bachelors,3,58,37,74,32,3.0,3,89,Urban,Data Analyst,136572,1 +63811,Female,57,Diploma,17,15,33,45,50,9.0,4,11,Semi-Urban,Data Analyst,82890,0 +63812,Male,33,Masters,19,20,71,59,17,3.0,2,46,Rural,Software Engineer,114185,0 +63813,Male,58,Bachelors,18,85,73,22,8,0.0,6,93,Urban,HR Executive,86474,1 +63814,Male,23,Bachelors,15,26,51,90,11,4.0,7,64,Rural,Software Engineer,114278,0 +63815,Female,57,Bachelors,9,45,14,15,95,2.0,0,10,Urban,Manager,52750,0 +63816,Female,57,Bachelors,4,27,42,43,27,6.0,3,22,Urban,ML Engineer,131349,0 +63817,Male,53,Masters,15,73,73,29,73,3.0,2,80,Urban,Manager,23710,1 +63818,Male,58,Masters,9,83,20,99,69,0.0,5,45,Semi-Urban,Manager,46291,1 +63819,Female,26,Bachelors,1,4,2,86,8,4.0,3,61,Semi-Urban,ML Engineer,120251,0 +63820,Female,53,Bachelors,19,38,44,30,59,0.0,6,8,Urban,Software Engineer,131956,0 +63821,Male,34,Diploma,5,0,18,0,54,8.0,3,1,Urban,Data Analyst,139900,0 +63822,Male,42,Diploma,16,16,3,34,68,9.0,5,31,Semi-Urban,Data Analyst,84516,0 +63823,Female,52,Bachelors,14,64,88,72,20,1.0,7,49,Urban,ML Engineer,52272,1 +63824,Other,55,Bachelors,3,72,42,84,25,8.0,6,88,Urban,HR Executive,108013,1 +63825,Female,23,Masters,3,32,89,87,71,2.0,0,33,Urban,Data Analyst,120463,1 +63826,Male,33,Masters,12,53,75,64,97,6.0,0,65,Urban,HR Executive,79059,1 +63827,Female,34,High School,0,27,88,71,89,7.0,0,78,Urban,Software Engineer,40367,1 +63828,Male,21,Bachelors,15,45,82,79,40,5.0,5,74,Urban,Manager,24054,1 +63829,Male,57,Diploma,7,92,50,10,73,1.0,6,83,Semi-Urban,Manager,126854,1 +63830,Male,23,Masters,5,78,43,19,42,8.0,2,72,Rural,Manager,42295,0 +63831,Female,40,High School,19,84,62,94,88,8.0,6,73,Urban,Software Engineer,70837,1 +63832,Male,55,High School,7,7,87,86,59,0.0,1,96,Rural,Data Analyst,106092,1 +63833,Female,41,High School,5,73,94,95,71,8.0,4,81,Urban,ML Engineer,59170,1 +63834,Female,55,Bachelors,6,97,97,89,80,0.0,1,37,Urban,Software Engineer,22200,1 +63835,Male,32,Bachelors,7,11,62,31,79,2.0,6,57,Urban,ML Engineer,101271,0 +63836,Male,31,Bachelors,8,62,1,23,68,5.0,4,17,Urban,ML Engineer,40657,0 +63837,Male,30,High School,6,11,20,64,97,0.0,3,64,Rural,Software Engineer,126448,0 +63838,Female,56,Bachelors,0,7,90,12,77,7.0,5,65,Urban,ML Engineer,85550,0 +63839,Male,34,Diploma,0,74,40,13,85,7.0,5,53,Urban,Manager,53370,0 +63840,Male,30,Masters,3,46,72,74,56,0.0,3,70,Urban,ML Engineer,80926,1 +63841,Male,29,PhD,13,35,45,63,67,3.0,4,34,Semi-Urban,Software Engineer,141517,0 +63842,Male,47,Diploma,19,24,49,39,41,1.0,1,27,Urban,Manager,55151,0 +63843,Male,56,Diploma,5,41,67,85,98,4.0,7,3,Rural,HR Executive,116123,0 +63844,Male,45,Bachelors,18,72,4,77,25,3.0,5,66,Urban,Data Analyst,67679,0 +63845,Female,28,Bachelors,3,25,54,23,46,8.0,3,83,Urban,ML Engineer,20644,0 +63846,Female,46,Diploma,13,24,66,5,98,2.0,6,81,Semi-Urban,HR Executive,118741,0 +63847,Male,28,Bachelors,4,24,37,90,61,8.0,2,12,Semi-Urban,ML Engineer,40556,0 +63848,Male,22,Bachelors,13,38,46,99,77,0.0,2,34,Rural,ML Engineer,36949,0 +63849,Male,46,Bachelors,1,60,17,31,49,9.0,0,62,Urban,ML Engineer,34573,0 +63850,Female,39,Bachelors,18,78,16,46,67,2.0,1,50,Rural,HR Executive,52669,0 +63851,Male,43,Masters,18,40,60,72,45,5.0,0,5,Urban,Software Engineer,23055,0 +63852,Male,59,Masters,4,37,25,26,37,8.0,3,60,Semi-Urban,Manager,112756,0 +63853,Male,48,PhD,0,89,96,3,84,3.0,5,86,Urban,Data Analyst,82918,1 +63854,Female,38,Masters,14,75,66,7,28,3.0,1,70,Semi-Urban,ML Engineer,108895,0 +63855,Male,26,Bachelors,12,43,35,56,98,9.0,3,80,Semi-Urban,Software Engineer,66800,0 +63856,Female,27,Masters,19,48,99,64,4,4.0,2,10,Urban,Manager,27139,0 +63857,Male,21,Bachelors,5,60,19,68,56,9.0,4,89,Urban,HR Executive,109628,1 +63858,Female,23,Bachelors,13,42,94,62,65,8.0,4,30,Semi-Urban,ML Engineer,127367,0 +63859,Female,47,High School,13,81,50,38,62,0.0,2,64,Semi-Urban,Manager,70537,0 +63860,Female,45,Diploma,14,43,94,37,89,1.0,7,33,Urban,Software Engineer,107626,0 +63861,Male,53,Diploma,10,47,71,56,55,9.0,0,31,Urban,ML Engineer,29131,0 +63862,Male,32,High School,0,91,66,56,11,6.0,1,29,Rural,Data Analyst,26403,1 +63863,Other,57,Diploma,11,36,58,37,70,5.0,1,64,Urban,ML Engineer,41319,0 +63864,Other,47,Bachelors,13,46,88,84,24,9.0,2,69,Semi-Urban,Software Engineer,47093,1 +63865,Male,31,Diploma,15,64,87,41,52,2.0,4,80,Semi-Urban,Software Engineer,90182,1 +63866,Male,52,Bachelors,5,58,18,56,89,8.0,4,94,Rural,Data Analyst,133860,0 +63867,Male,21,Bachelors,0,77,41,29,40,0.0,7,66,Rural,Data Analyst,26695,0 +63868,Male,44,High School,4,35,77,67,21,4.0,7,68,Semi-Urban,Manager,25809,1 +63869,Male,35,Bachelors,2,13,17,72,87,0.0,5,36,Urban,Data Analyst,134580,0 +63870,Male,38,Masters,17,18,83,31,60,0.0,6,8,Semi-Urban,Software Engineer,34053,0 +63871,Male,57,High School,18,52,86,88,1,6.0,1,24,Urban,Data Analyst,23438,1 +63872,Male,43,High School,15,12,88,59,2,6.0,6,77,Semi-Urban,ML Engineer,55873,1 +63873,Other,48,Masters,11,65,41,53,87,0.0,7,71,Semi-Urban,HR Executive,144493,0 +63874,Male,53,Bachelors,18,63,64,98,44,7.0,6,40,Rural,Data Analyst,58555,1 +63875,Male,38,Bachelors,3,59,23,41,68,5.0,0,58,Semi-Urban,Manager,87746,0 +63876,Female,21,Diploma,19,15,49,68,59,8.0,7,94,Urban,Data Analyst,101583,0 +63877,Female,59,Bachelors,6,72,66,72,35,2.0,1,37,Rural,Manager,23728,1 +63878,Male,53,Bachelors,17,2,9,81,97,9.0,5,56,Semi-Urban,ML Engineer,55711,0 +63879,Male,40,Diploma,13,40,5,54,26,9.0,7,69,Urban,Data Analyst,125422,0 +63880,Male,29,Masters,5,50,83,3,20,8.0,0,55,Urban,Manager,144869,0 +63881,Female,55,High School,0,98,25,7,50,5.0,2,26,Urban,Manager,89802,0 +63882,Female,48,Diploma,15,43,67,18,86,8.0,6,97,Urban,HR Executive,25952,0 +63883,Male,35,Bachelors,16,91,91,82,40,6.0,6,89,Urban,ML Engineer,78920,1 +63884,Male,39,Bachelors,10,97,23,5,51,7.0,1,36,Rural,Manager,128459,0 +63885,Male,40,Bachelors,3,68,82,15,42,3.0,0,40,Urban,HR Executive,108029,0 +63886,Male,28,High School,3,68,20,2,2,3.0,5,86,Urban,Manager,36160,0 +63887,Male,26,Bachelors,7,54,98,21,59,0.0,7,64,Urban,Data Analyst,78072,1 +63888,Female,40,Bachelors,2,57,9,42,6,8.0,3,95,Semi-Urban,ML Engineer,140450,0 +63889,Female,33,Masters,3,37,37,93,31,9.0,0,13,Semi-Urban,ML Engineer,126564,0 +63890,Male,21,Masters,14,74,68,25,60,5.0,3,3,Urban,Software Engineer,88130,0 +63891,Male,49,Bachelors,3,31,91,96,23,5.0,1,64,Semi-Urban,ML Engineer,145742,1 +63892,Male,36,Bachelors,13,53,12,82,27,6.0,7,43,Urban,HR Executive,128469,0 +63893,Male,37,Masters,3,98,41,29,21,0.0,3,89,Rural,Software Engineer,116379,1 +63894,Female,49,Masters,0,98,20,17,9,9.0,1,50,Urban,Data Analyst,136457,0 +63895,Male,42,PhD,10,2,75,2,96,7.0,2,20,Urban,Software Engineer,74092,0 +63896,Male,22,Bachelors,14,7,90,72,79,7.0,5,63,Rural,Manager,27455,0 +63897,Male,44,High School,1,72,75,10,59,6.0,6,69,Urban,Manager,40737,0 +63898,Female,37,Diploma,19,30,67,86,4,5.0,6,26,Urban,Software Engineer,51939,0 +63899,Female,48,PhD,2,28,97,52,38,5.0,4,70,Urban,HR Executive,55445,1 +63900,Female,24,Diploma,12,2,51,82,7,7.0,2,44,Rural,ML Engineer,36589,0 +63901,Male,59,High School,19,3,92,17,86,7.0,1,49,Urban,HR Executive,61404,0 +63902,Female,42,Bachelors,6,80,93,55,64,4.0,4,72,Rural,Data Analyst,36723,1 +63903,Female,34,Bachelors,4,2,9,1,71,3.0,6,9,Rural,Data Analyst,79602,0 +63904,Male,32,High School,16,31,60,65,35,4.0,2,39,Semi-Urban,HR Executive,32992,0 +63905,Female,48,Bachelors,17,43,94,23,10,3.0,2,39,Rural,HR Executive,68221,0 +63906,Female,48,High School,14,26,50,6,7,7.0,3,11,Semi-Urban,HR Executive,58620,0 +63907,Male,50,Bachelors,11,25,41,62,60,0.0,5,69,Urban,HR Executive,131534,0 +63908,Male,35,PhD,19,17,36,33,32,3.0,2,32,Rural,Data Analyst,113939,0 +63909,Female,30,Bachelors,9,66,98,93,97,0.0,4,55,Urban,ML Engineer,118466,1 +63910,Male,53,Masters,17,70,60,30,77,3.0,0,97,Urban,Software Engineer,112862,1 +63911,Female,35,Bachelors,8,89,99,12,42,6.0,3,27,Urban,HR Executive,148475,0 +63912,Male,52,Bachelors,2,43,38,17,2,8.0,4,83,Urban,Data Analyst,58555,0 +63913,Male,22,Bachelors,7,78,80,37,61,0.0,2,2,Urban,Software Engineer,99720,0 +63914,Other,52,Bachelors,6,35,47,91,14,9.0,2,3,Urban,Software Engineer,26298,0 +63915,Male,41,High School,11,95,15,85,64,8.0,2,83,Rural,ML Engineer,46506,1 +63916,Male,58,PhD,4,59,82,19,2,6.0,2,0,Semi-Urban,Software Engineer,118285,0 +63917,Male,39,Diploma,0,34,84,73,85,7.0,6,31,Urban,HR Executive,68058,0 +63918,Female,46,Bachelors,10,12,70,56,48,1.0,6,39,Urban,ML Engineer,103461,0 +63919,Male,31,Bachelors,15,97,68,60,79,6.0,2,72,Urban,Manager,90707,1 +63920,Male,39,Bachelors,7,71,3,30,11,6.0,6,36,Urban,Data Analyst,147973,0 +63921,Female,21,Masters,17,70,46,97,10,4.0,2,34,Urban,Data Analyst,58760,1 +63922,Male,44,Bachelors,2,29,76,54,17,2.0,3,64,Urban,Data Analyst,23280,0 +63923,Female,26,Masters,4,99,82,1,14,6.0,6,91,Urban,Software Engineer,119140,1 +63924,Male,44,Masters,6,39,9,15,55,9.0,7,76,Urban,Manager,101624,0 +63925,Male,24,Bachelors,2,98,82,23,35,5.0,7,71,Urban,Software Engineer,95356,1 +63926,Female,43,Diploma,12,14,89,78,77,2.0,6,19,Rural,HR Executive,148596,0 +63927,Male,37,Bachelors,2,3,54,88,68,8.0,2,60,Semi-Urban,ML Engineer,100011,0 +63928,Male,50,Bachelors,14,88,67,31,48,0.0,3,23,Urban,Data Analyst,144108,0 +63929,Female,32,Bachelors,0,43,76,1,45,5.0,2,52,Urban,ML Engineer,136475,0 +63930,Male,49,Bachelors,10,87,50,79,86,5.0,5,8,Urban,Data Analyst,80277,0 +63931,Female,57,Diploma,18,72,59,62,30,4.0,1,97,Semi-Urban,Data Analyst,78662,1 +63932,Male,33,Bachelors,14,11,65,85,14,0.0,3,65,Rural,HR Executive,119025,0 +63933,Female,24,Masters,14,78,89,36,84,4.0,5,41,Urban,ML Engineer,69841,1 +63934,Male,59,Bachelors,12,81,47,82,4,0.0,1,60,Semi-Urban,Data Analyst,35626,1 +63935,Female,42,Diploma,9,88,27,77,27,6.0,2,89,Urban,ML Engineer,24403,1 +63936,Male,51,PhD,0,99,94,60,10,2.0,2,64,Urban,Manager,83488,1 +63937,Female,26,Bachelors,5,91,4,78,92,1.0,7,48,Semi-Urban,Manager,79916,0 +63938,Male,26,Bachelors,11,78,32,85,83,3.0,2,9,Urban,HR Executive,44956,0 +63939,Male,25,Bachelors,18,2,90,27,62,2.0,3,95,Semi-Urban,Data Analyst,63055,0 +63940,Female,29,Bachelors,19,52,61,26,95,4.0,2,61,Urban,Software Engineer,120023,0 +63941,Female,54,Diploma,9,19,8,5,79,0.0,0,4,Urban,Data Analyst,56756,0 +63942,Male,54,Bachelors,11,29,20,33,85,7.0,4,53,Urban,Software Engineer,96612,0 +63943,Female,58,Bachelors,12,99,16,58,66,5.0,3,52,Urban,Software Engineer,115223,0 +63944,Male,30,Diploma,12,69,62,92,20,7.0,4,42,Rural,ML Engineer,48339,1 +63945,Male,48,Bachelors,9,80,99,57,93,8.0,6,90,Urban,ML Engineer,44476,1 +63946,Female,58,Diploma,4,19,56,91,90,0.0,6,49,Urban,Software Engineer,24578,0 +63947,Female,39,Diploma,9,16,93,79,29,1.0,1,96,Rural,ML Engineer,29801,1 +63948,Male,24,Bachelors,6,79,86,64,61,3.0,2,31,Urban,Manager,24622,1 +63949,Male,49,Masters,12,5,57,43,26,9.0,2,17,Urban,ML Engineer,37179,0 +63950,Male,40,Diploma,10,4,66,33,32,3.0,0,77,Urban,Data Analyst,33297,0 +63951,Male,36,Masters,16,57,78,21,25,1.0,4,42,Semi-Urban,HR Executive,94282,0 +63952,Male,39,Bachelors,4,51,40,71,44,1.0,0,17,Urban,ML Engineer,98542,0 +63953,Male,41,Bachelors,15,79,78,21,77,8.0,6,52,Rural,ML Engineer,115070,0 +63954,Male,27,Bachelors,12,65,70,76,70,1.0,7,66,Urban,ML Engineer,45179,1 +63955,Male,40,Bachelors,0,54,33,94,3,7.0,3,62,Urban,Software Engineer,68510,1 +63956,Female,49,Bachelors,15,11,13,0,95,7.0,1,22,Urban,Manager,133018,0 +63957,Male,45,Bachelors,1,56,43,3,68,1.0,3,99,Rural,Manager,87297,0 +63958,Male,58,Bachelors,2,13,46,88,36,4.0,1,17,Rural,Data Analyst,120243,0 +63959,Female,57,Bachelors,16,31,85,84,46,1.0,7,31,Urban,Software Engineer,59269,0 +63960,Other,54,High School,9,52,23,20,74,4.0,4,53,Urban,Manager,81889,0 +63961,Male,23,High School,17,6,19,73,78,0.0,5,88,Semi-Urban,Software Engineer,99236,0 +63962,Female,42,Bachelors,5,82,7,16,3,4.0,5,17,Urban,Manager,35882,0 +63963,Female,56,Masters,15,64,31,9,76,4.0,7,92,Urban,Software Engineer,76793,0 +63964,Male,34,Bachelors,15,43,64,70,97,1.0,7,17,Rural,Data Analyst,72615,0 +63965,Female,49,Bachelors,3,47,46,75,17,2.0,1,8,Rural,ML Engineer,146164,0 +63966,Male,33,Masters,15,97,41,43,69,5.0,0,18,Urban,Data Analyst,72069,0 +63967,Other,22,Bachelors,13,23,86,76,38,6.0,3,71,Urban,HR Executive,101535,1 +63968,Male,32,Diploma,0,26,27,22,86,7.0,7,69,Urban,Manager,51737,0 +63969,Female,25,Bachelors,5,0,58,41,84,3.0,5,57,Urban,Manager,148262,0 +63970,Male,35,PhD,11,71,70,26,98,7.0,6,81,Semi-Urban,HR Executive,86915,1 +63971,Female,46,Bachelors,10,82,77,18,14,5.0,3,37,Rural,Manager,23635,0 +63972,Male,34,Masters,12,7,31,62,22,8.0,6,80,Urban,Data Analyst,22224,0 +63973,Female,31,Bachelors,6,90,0,72,59,8.0,0,79,Semi-Urban,ML Engineer,53722,1 +63974,Female,45,Diploma,9,1,51,81,8,3.0,0,53,Urban,Software Engineer,62597,0 +63975,Male,59,Bachelors,4,13,15,21,40,4.0,4,17,Rural,Software Engineer,32808,0 +63976,Male,34,Bachelors,12,10,60,53,84,8.0,4,42,Urban,ML Engineer,95093,0 +63977,Female,28,Masters,4,89,0,67,49,9.0,4,33,Semi-Urban,Software Engineer,135406,0 +63978,Male,21,Bachelors,11,70,30,43,57,3.0,3,80,Semi-Urban,Manager,117431,0 +63979,Female,22,Bachelors,13,79,58,0,81,5.0,5,55,Urban,Data Analyst,33926,0 +63980,Male,44,PhD,10,38,37,80,71,8.0,6,37,Urban,HR Executive,128263,0 +63981,Male,51,Diploma,2,2,16,78,35,6.0,7,79,Rural,ML Engineer,82643,0 +63982,Male,36,Bachelors,12,97,58,33,55,6.0,4,14,Urban,Manager,139896,0 +63983,Male,47,Diploma,10,81,23,66,0,6.0,0,17,Urban,ML Engineer,74369,0 +63984,Male,37,Bachelors,9,18,34,60,3,5.0,6,75,Urban,Data Analyst,101047,0 +63985,Female,55,Bachelors,18,16,38,71,61,4.0,6,79,Urban,ML Engineer,44974,0 +63986,Male,51,Masters,16,81,87,34,19,0.0,6,87,Urban,Data Analyst,135644,1 +63987,Male,50,Bachelors,12,8,93,66,71,4.0,7,78,Urban,Manager,141303,1 +63988,Male,52,Masters,4,33,42,52,89,8.0,4,69,Rural,Data Analyst,31803,0 +63989,Female,34,Masters,9,33,93,30,12,5.0,7,27,Urban,Data Analyst,142777,0 +63990,Female,23,High School,4,80,96,94,20,8.0,3,70,Urban,Manager,104193,1 +63991,Male,44,Diploma,3,73,61,17,83,7.0,6,12,Semi-Urban,Manager,92532,0 +63992,Female,23,Diploma,19,17,22,1,70,0.0,2,86,Urban,HR Executive,29142,0 +63993,Female,23,Masters,10,1,15,97,19,4.0,2,99,Urban,Software Engineer,128459,0 +63994,Female,27,High School,19,19,47,14,63,2.0,7,92,Rural,Manager,103601,0 +63995,Male,30,High School,5,7,1,90,64,0.0,0,27,Urban,Manager,102180,0 +63996,Male,48,High School,9,73,60,78,40,1.0,0,23,Urban,Data Analyst,32530,0 +63997,Female,29,Masters,15,45,94,23,30,6.0,5,60,Urban,Data Analyst,81249,0 +63998,Male,53,High School,10,64,7,52,92,3.0,2,78,Semi-Urban,Data Analyst,63978,0 +63999,Male,22,Diploma,12,6,99,39,18,5.0,0,35,Semi-Urban,Software Engineer,49997,0 +64000,Male,46,Bachelors,6,95,24,92,11,9.0,2,92,Semi-Urban,Data Analyst,23030,1 +64001,Male,35,Diploma,10,47,14,46,70,3.0,0,41,Urban,HR Executive,71373,0 +64002,Male,59,Bachelors,3,95,78,48,7,8.0,1,44,Urban,Manager,92527,1 +64003,Male,22,High School,6,27,89,91,14,7.0,2,35,Rural,HR Executive,81303,1 +64004,Female,36,Bachelors,12,4,11,43,8,3.0,0,12,Rural,HR Executive,118226,0 +64005,Male,56,Masters,11,96,58,10,88,0.0,2,14,Rural,HR Executive,53087,0 +64006,Male,48,PhD,13,1,11,1,39,0.0,0,39,Semi-Urban,Software Engineer,66352,0 +64007,Female,57,Bachelors,1,46,53,96,72,9.0,6,13,Urban,HR Executive,88885,0 +64008,Male,41,Bachelors,18,37,71,98,70,6.0,3,92,Semi-Urban,HR Executive,133267,1 +64009,Female,39,Diploma,17,13,22,44,61,5.0,1,18,Urban,HR Executive,142682,0 +64010,Male,28,Masters,5,30,51,38,52,0.0,1,90,Urban,Manager,74207,0 +64011,Female,33,Diploma,13,16,58,70,18,0.0,1,6,Rural,Manager,61952,0 +64012,Male,41,Bachelors,9,33,26,45,49,4.0,0,70,Semi-Urban,ML Engineer,84564,0 +64013,Male,42,Diploma,2,21,25,6,1,4.0,2,36,Rural,ML Engineer,135029,0 +64014,Female,51,Masters,12,23,30,55,84,4.0,1,65,Urban,Software Engineer,95347,0 +64015,Female,44,Masters,18,36,94,4,24,4.0,2,21,Urban,ML Engineer,31652,0 +64016,Female,44,Diploma,6,49,19,20,3,8.0,1,64,Rural,ML Engineer,115833,0 +64017,Female,58,Bachelors,0,19,9,4,73,7.0,4,47,Urban,Software Engineer,54976,0 +64018,Male,27,Bachelors,6,50,6,51,37,3.0,2,39,Rural,ML Engineer,91142,0 +64019,Female,51,Masters,0,93,37,33,64,5.0,0,90,Semi-Urban,Software Engineer,139243,1 +64020,Male,28,Masters,0,74,97,79,81,1.0,7,42,Urban,Software Engineer,20184,1 +64021,Male,57,Diploma,8,59,3,68,91,7.0,4,96,Semi-Urban,Manager,107656,0 +64022,Male,43,Bachelors,9,75,3,86,13,3.0,2,34,Semi-Urban,ML Engineer,114679,0 +64023,Male,32,Masters,11,82,77,74,64,6.0,5,58,Urban,Data Analyst,42423,1 +64024,Female,32,Diploma,17,42,1,47,57,1.0,0,69,Urban,Data Analyst,129129,0 +64025,Male,50,Bachelors,3,61,20,2,94,6.0,1,29,Urban,ML Engineer,48958,0 +64026,Male,43,Diploma,10,49,63,71,69,1.0,1,78,Urban,Manager,52521,1 +64027,Male,38,Diploma,10,75,82,58,50,0.0,6,77,Semi-Urban,Software Engineer,62718,1 +64028,Female,28,Masters,6,50,14,44,2,4.0,1,5,Semi-Urban,Software Engineer,76161,0 +64029,Male,41,Diploma,4,49,46,64,78,5.0,0,89,Urban,Manager,61313,1 +64030,Male,35,Bachelors,17,75,14,31,91,8.0,1,29,Urban,Software Engineer,76429,0 +64031,Male,53,Masters,19,45,58,15,23,0.0,0,45,Urban,ML Engineer,53096,0 +64032,Male,50,High School,18,6,1,6,66,1.0,6,76,Rural,Software Engineer,28686,0 +64033,Male,41,Diploma,14,59,31,19,88,6.0,4,21,Urban,Software Engineer,44760,0 +64034,Male,54,Bachelors,11,5,62,6,32,7.0,5,22,Urban,Manager,20557,0 +64035,Male,47,High School,13,81,25,5,70,1.0,1,13,Urban,Manager,77459,0 +64036,Male,39,High School,12,3,55,21,28,5.0,2,86,Semi-Urban,Manager,140271,0 +64037,Female,48,Diploma,15,63,6,71,90,3.0,5,42,Urban,Manager,84827,0 +64038,Male,56,Bachelors,8,15,80,26,72,9.0,2,24,Urban,HR Executive,52334,0 +64039,Female,28,Diploma,13,94,88,76,65,1.0,3,22,Semi-Urban,HR Executive,110060,1 +64040,Male,55,High School,17,86,5,15,43,3.0,2,0,Urban,HR Executive,41703,0 +64041,Male,23,Masters,14,95,90,21,15,5.0,2,23,Urban,Software Engineer,71898,0 +64042,Male,37,Bachelors,14,4,55,96,20,7.0,5,87,Semi-Urban,Manager,84319,1 +64043,Male,42,Bachelors,8,69,70,18,26,6.0,7,18,Urban,ML Engineer,147319,0 +64044,Female,47,Diploma,12,32,5,42,96,4.0,2,8,Rural,HR Executive,98149,0 +64045,Male,34,Bachelors,6,80,38,97,26,3.0,6,8,Rural,Software Engineer,111283,0 +64046,Male,54,Masters,9,16,12,84,66,7.0,5,81,Rural,Software Engineer,87693,0 +64047,Male,58,Diploma,13,85,79,63,17,6.0,3,99,Semi-Urban,ML Engineer,43833,1 +64048,Male,28,Diploma,3,55,28,28,94,6.0,0,28,Urban,Data Analyst,83216,0 +64049,Female,55,Diploma,10,16,37,92,27,4.0,4,12,Rural,ML Engineer,87375,0 +64050,Female,59,Diploma,2,58,59,45,49,8.0,0,87,Semi-Urban,Data Analyst,72189,1 +64051,Male,24,Bachelors,2,20,85,69,48,1.0,6,65,Urban,ML Engineer,28717,1 +64052,Female,54,Masters,10,40,69,4,68,1.0,5,66,Rural,Software Engineer,96750,0 +64053,Male,29,Masters,2,12,52,2,2,3.0,0,61,Urban,Data Analyst,65569,0 +64054,Female,22,Masters,10,11,73,61,53,2.0,7,45,Urban,Data Analyst,37314,0 +64055,Female,50,High School,16,22,34,58,76,0.0,5,12,Semi-Urban,Software Engineer,25138,0 +64056,Male,49,High School,17,97,18,49,51,6.0,1,24,Semi-Urban,HR Executive,117566,0 +64057,Female,23,Bachelors,4,88,48,22,4,8.0,2,12,Rural,ML Engineer,27946,0 +64058,Female,24,Diploma,14,77,71,79,92,1.0,6,38,Semi-Urban,Manager,77338,1 +64059,Male,32,Diploma,8,11,82,84,96,3.0,2,87,Urban,Manager,120730,1 +64060,Female,43,Bachelors,4,23,13,77,67,2.0,2,32,Urban,HR Executive,59129,0 +64061,Male,45,Bachelors,9,44,15,63,7,9.0,6,61,Semi-Urban,ML Engineer,128982,0 +64062,Male,36,Diploma,0,91,14,29,20,2.0,0,86,Urban,Software Engineer,132995,0 +64063,Male,50,Masters,13,71,40,18,52,8.0,5,77,Semi-Urban,HR Executive,99250,0 +64064,Male,51,Bachelors,10,95,8,98,76,1.0,0,70,Urban,HR Executive,53011,1 +64065,Male,39,High School,2,44,71,29,21,0.0,3,73,Urban,Software Engineer,81218,0 +64066,Male,32,Bachelors,5,15,42,15,99,2.0,7,75,Urban,Software Engineer,40297,0 +64067,Male,23,High School,10,25,2,49,25,6.0,3,90,Urban,Manager,74243,0 +64068,Other,46,High School,3,68,41,50,56,0.0,5,40,Urban,Software Engineer,96036,0 +64069,Male,57,High School,8,56,99,9,92,0.0,5,74,Urban,Data Analyst,71651,1 +64070,Male,21,Masters,18,25,90,34,79,7.0,3,73,Rural,Software Engineer,131269,0 +64071,Male,40,Bachelors,6,74,96,25,88,1.0,0,21,Rural,ML Engineer,86398,0 +64072,Male,56,Bachelors,8,58,32,8,65,9.0,7,31,Semi-Urban,Data Analyst,62812,0 +64073,Female,21,Masters,19,36,0,37,17,8.0,3,7,Urban,ML Engineer,85493,0 +64074,Male,49,Masters,18,91,24,88,40,6.0,0,31,Rural,Manager,99174,0 +64075,Male,53,Diploma,18,48,7,20,96,6.0,7,15,Semi-Urban,HR Executive,141655,0 +64076,Male,50,PhD,15,28,25,48,51,6.0,6,91,Urban,Manager,34178,0 +64077,Male,31,Bachelors,19,57,68,86,66,1.0,1,50,Semi-Urban,HR Executive,116780,1 +64078,Female,49,Diploma,12,90,62,2,62,5.0,3,57,Semi-Urban,Data Analyst,115107,0 +64079,Male,32,High School,8,73,35,74,32,9.0,4,18,Urban,HR Executive,65036,0 +64080,Male,25,High School,0,13,65,37,92,6.0,5,61,Urban,Software Engineer,140315,0 +64081,Male,37,Bachelors,9,34,9,34,61,2.0,4,15,Urban,Manager,20520,0 +64082,Female,57,Diploma,11,33,83,53,59,1.0,0,62,Urban,ML Engineer,63215,0 +64083,Female,33,Masters,19,94,32,90,44,1.0,4,50,Urban,Manager,76658,1 +64084,Female,49,Bachelors,13,95,92,41,53,9.0,5,60,Rural,ML Engineer,26324,1 +64085,Female,33,Diploma,5,57,18,3,69,2.0,1,23,Semi-Urban,Manager,104830,0 +64086,Female,46,Diploma,18,51,91,30,50,4.0,1,88,Rural,HR Executive,32675,1 +64087,Male,51,Masters,15,23,19,83,70,5.0,1,21,Semi-Urban,Data Analyst,59973,0 +64088,Male,53,High School,13,29,49,14,81,1.0,4,29,Urban,HR Executive,41983,0 +64089,Female,52,Masters,2,43,26,22,59,8.0,5,71,Urban,Manager,75235,0 +64090,Male,41,Masters,15,29,18,35,12,0.0,0,25,Semi-Urban,HR Executive,26570,0 +64091,Male,40,High School,12,90,11,17,23,3.0,0,65,Semi-Urban,HR Executive,128375,0 +64092,Male,58,Bachelors,15,81,22,71,39,4.0,5,94,Rural,Data Analyst,49318,1 +64093,Female,49,High School,19,96,94,4,89,7.0,4,49,Semi-Urban,Data Analyst,50968,1 +64094,Male,58,Diploma,5,19,65,61,39,0.0,5,9,Semi-Urban,Software Engineer,48128,0 +64095,Female,27,High School,2,4,59,44,49,1.0,5,74,Rural,Software Engineer,146299,0 +64096,Female,34,Bachelors,3,41,74,17,58,6.0,2,64,Urban,ML Engineer,91063,0 +64097,Male,44,Bachelors,7,56,8,62,81,0.0,4,4,Rural,Software Engineer,37852,0 +64098,Male,49,High School,15,95,18,39,59,6.0,2,34,Urban,Manager,138819,0 +64099,Male,24,High School,2,53,64,38,29,8.0,3,35,Semi-Urban,Software Engineer,82802,0 +64100,Male,39,Diploma,0,4,24,43,98,4.0,4,60,Urban,HR Executive,49408,0 +64101,Male,35,Bachelors,13,52,56,0,84,6.0,2,8,Semi-Urban,Software Engineer,84523,0 +64102,Male,35,Masters,8,29,1,88,61,4.0,3,29,Semi-Urban,Software Engineer,117445,0 +64103,Female,52,Bachelors,12,89,80,81,97,3.0,6,84,Rural,Manager,42632,1 +64104,Male,49,Bachelors,15,46,99,88,10,5.0,4,99,Urban,HR Executive,121771,1 +64105,Female,42,Bachelors,8,25,24,27,82,9.0,0,42,Urban,Data Analyst,98797,0 +64106,Male,56,High School,5,4,2,36,11,9.0,1,86,Semi-Urban,Data Analyst,65118,0 +64107,Female,37,Bachelors,1,25,85,62,65,2.0,7,59,Urban,HR Executive,76756,0 +64108,Male,56,Diploma,6,51,81,94,84,5.0,5,35,Urban,Data Analyst,33494,1 +64109,Male,33,Diploma,9,65,60,88,51,8.0,6,87,Semi-Urban,ML Engineer,131288,1 +64110,Male,53,Masters,16,86,44,81,94,5.0,2,85,Urban,Data Analyst,41448,1 +64111,Male,43,High School,1,80,59,92,16,8.0,7,58,Urban,Manager,119801,1 +64112,Male,42,Diploma,17,47,23,72,28,6.0,3,0,Urban,HR Executive,37423,0 +64113,Male,54,High School,14,27,89,5,13,3.0,5,77,Urban,Software Engineer,115376,0 +64114,Male,37,Masters,14,46,55,35,64,7.0,1,54,Urban,Software Engineer,25054,0 +64115,Female,40,High School,18,91,77,87,72,5.0,6,45,Semi-Urban,HR Executive,143697,1 +64116,Female,21,Masters,18,3,48,78,89,9.0,5,21,Rural,Data Analyst,47732,0 +64117,Male,40,PhD,18,79,55,67,69,2.0,6,71,Semi-Urban,Software Engineer,35200,1 +64118,Male,53,Masters,7,1,86,86,75,4.0,6,11,Urban,Manager,114961,0 +64119,Female,54,PhD,2,42,35,56,49,5.0,6,52,Rural,Manager,65501,0 +64120,Male,25,Bachelors,10,50,85,69,83,1.0,5,70,Urban,Data Analyst,102071,1 +64121,Female,42,Bachelors,16,38,78,21,40,9.0,6,92,Urban,ML Engineer,132849,0 +64122,Male,57,Masters,5,72,40,65,59,5.0,6,86,Urban,HR Executive,42562,1 +64123,Male,58,Masters,19,82,45,30,23,7.0,0,3,Urban,Software Engineer,42438,0 +64124,Male,59,Diploma,2,5,21,21,72,3.0,0,32,Rural,Manager,101231,0 +64125,Male,29,Bachelors,15,6,60,51,30,3.0,7,36,Urban,Manager,53933,0 +64126,Female,39,Diploma,15,74,28,29,93,2.0,4,50,Urban,Software Engineer,30254,0 +64127,Male,53,Diploma,15,27,74,98,40,9.0,0,66,Semi-Urban,Manager,135216,1 +64128,Male,38,Bachelors,2,61,38,53,9,6.0,2,22,Urban,Manager,53664,0 +64129,Male,43,High School,3,95,91,47,63,0.0,3,27,Urban,Software Engineer,140499,1 +64130,Female,26,Bachelors,14,41,83,87,36,1.0,0,6,Rural,HR Executive,115364,0 +64131,Male,29,Bachelors,13,86,70,49,73,2.0,6,26,Rural,Manager,131434,0 +64132,Female,55,Bachelors,18,45,22,26,87,4.0,2,34,Urban,HR Executive,143737,0 +64133,Female,39,Diploma,0,54,66,62,84,0.0,2,58,Semi-Urban,Software Engineer,138139,0 +64134,Female,25,Masters,19,5,35,12,70,3.0,7,38,Urban,Software Engineer,134102,0 +64135,Male,47,Diploma,19,82,81,2,19,8.0,4,9,Rural,ML Engineer,138185,0 +64136,Male,21,High School,11,85,3,35,17,6.0,5,6,Semi-Urban,Manager,36777,0 +64137,Male,35,Diploma,12,2,86,4,19,7.0,6,96,Semi-Urban,Software Engineer,47415,0 +64138,Male,54,Masters,3,17,64,81,68,9.0,4,85,Urban,HR Executive,136592,1 +64139,Female,33,Bachelors,1,51,13,3,41,8.0,4,39,Urban,ML Engineer,146626,0 +64140,Female,37,Bachelors,17,8,20,45,46,0.0,7,75,Rural,Data Analyst,137139,0 +64141,Male,39,Masters,18,79,91,2,25,1.0,3,67,Semi-Urban,HR Executive,124906,1 +64142,Female,47,PhD,15,0,70,9,86,5.0,3,61,Semi-Urban,Data Analyst,138979,0 +64143,Male,56,PhD,7,34,34,12,43,7.0,4,93,Urban,Manager,22009,0 +64144,Male,50,Masters,9,20,86,82,93,4.0,1,35,Rural,Data Analyst,138061,0 +64145,Male,56,Diploma,4,13,57,93,48,8.0,2,6,Urban,Data Analyst,49356,0 +64146,Male,23,Masters,1,56,40,44,64,0.0,3,34,Semi-Urban,Manager,46282,0 +64147,Female,47,Masters,18,18,53,69,41,5.0,1,24,Urban,HR Executive,46818,0 +64148,Male,40,Diploma,7,9,72,17,14,8.0,2,96,Urban,ML Engineer,98205,0 +64149,Female,59,Bachelors,19,53,31,29,25,9.0,6,6,Semi-Urban,Data Analyst,88775,0 +64150,Male,51,Diploma,10,11,28,89,7,0.0,5,29,Rural,Manager,91285,0 +64151,Other,28,Masters,18,14,45,76,83,3.0,4,25,Semi-Urban,HR Executive,78159,0 +64152,Female,54,Diploma,10,11,43,78,21,5.0,7,50,Urban,Manager,62789,0 +64153,Female,39,Diploma,7,6,3,33,98,2.0,6,10,Urban,Data Analyst,98316,0 +64154,Male,49,High School,14,70,96,59,57,4.0,6,46,Rural,Software Engineer,61348,1 +64155,Male,24,Bachelors,1,90,91,59,98,7.0,6,67,Urban,Manager,146126,1 +64156,Male,21,PhD,15,54,87,2,44,8.0,2,12,Urban,Manager,34548,0 +64157,Male,40,Diploma,6,40,40,44,24,2.0,4,50,Rural,Manager,145060,0 +64158,Male,34,Bachelors,4,14,64,29,49,2.0,7,57,Semi-Urban,HR Executive,22100,0 +64159,Female,22,Bachelors,18,38,1,55,91,4.0,5,57,Urban,Software Engineer,55573,0 +64160,Male,42,High School,3,25,27,74,55,0.0,0,27,Rural,HR Executive,129705,0 +64161,Male,48,Diploma,3,88,38,4,74,5.0,7,64,Urban,Data Analyst,47291,0 +64162,Female,55,Diploma,15,84,3,89,36,5.0,5,55,Rural,HR Executive,53508,0 +64163,Male,59,Diploma,11,43,65,66,33,1.0,4,62,Semi-Urban,HR Executive,22766,1 +64164,Female,50,Bachelors,17,81,65,1,12,6.0,7,52,Urban,Software Engineer,54445,0 +64165,Male,46,Bachelors,13,90,71,2,3,2.0,4,44,Semi-Urban,ML Engineer,106031,0 +64166,Male,21,High School,4,17,68,25,23,3.0,5,84,Semi-Urban,HR Executive,94408,0 +64167,Male,59,High School,17,37,93,95,16,1.0,6,95,Semi-Urban,Data Analyst,74356,1 +64168,Male,46,Bachelors,1,90,41,37,3,6.0,5,40,Urban,Manager,129308,0 +64169,Male,41,Diploma,19,52,86,38,25,6.0,5,66,Semi-Urban,ML Engineer,74989,1 +64170,Male,52,Diploma,17,59,78,12,89,1.0,2,68,Rural,Manager,94522,0 +64171,Female,45,Masters,6,41,97,79,14,9.0,2,5,Semi-Urban,ML Engineer,65929,0 +64172,Female,32,Bachelors,2,60,7,79,45,9.0,2,35,Urban,Software Engineer,43094,0 +64173,Male,55,Diploma,19,96,16,26,26,8.0,3,63,Rural,Software Engineer,39990,0 +64174,Female,38,Masters,11,64,58,8,72,8.0,2,36,Semi-Urban,ML Engineer,22754,0 +64175,Other,59,Bachelors,12,98,50,92,24,2.0,7,55,Urban,Data Analyst,112612,1 +64176,Male,25,Bachelors,2,89,24,89,90,5.0,4,75,Urban,Manager,139199,1 +64177,Female,45,Bachelors,14,86,7,18,21,8.0,1,67,Urban,HR Executive,133746,0 +64178,Other,30,Masters,3,19,98,92,71,6.0,5,26,Semi-Urban,HR Executive,43889,0 +64179,Female,24,Masters,6,51,43,75,4,3.0,2,91,Urban,ML Engineer,120692,1 +64180,Male,50,Bachelors,19,30,67,46,40,1.0,3,16,Urban,ML Engineer,138549,0 +64181,Female,27,Bachelors,9,20,53,7,83,4.0,1,99,Semi-Urban,Software Engineer,46091,0 +64182,Male,28,Bachelors,13,97,69,28,16,3.0,1,78,Semi-Urban,Data Analyst,23124,1 +64183,Other,24,Bachelors,3,87,79,50,85,4.0,2,3,Urban,ML Engineer,121657,0 +64184,Male,26,High School,5,50,0,38,61,0.0,7,93,Rural,Software Engineer,39996,0 +64185,Female,57,PhD,3,2,57,9,76,6.0,4,30,Urban,Manager,70207,0 +64186,Male,50,PhD,5,73,39,70,18,8.0,3,1,Rural,ML Engineer,146957,0 +64187,Male,30,Bachelors,8,49,6,5,78,8.0,0,47,Semi-Urban,HR Executive,88576,0 +64188,Female,35,Bachelors,6,68,74,13,46,1.0,3,18,Semi-Urban,Data Analyst,110319,0 +64189,Female,57,Diploma,1,2,12,95,2,0.0,6,10,Semi-Urban,Software Engineer,88314,0 +64190,Male,21,Diploma,4,7,71,62,76,4.0,3,37,Urban,Software Engineer,23147,0 +64191,Other,31,Bachelors,4,35,17,71,3,6.0,4,1,Semi-Urban,Software Engineer,131181,0 +64192,Female,30,Bachelors,14,34,69,5,1,6.0,0,16,Semi-Urban,ML Engineer,118733,0 +64193,Female,32,Bachelors,16,13,72,18,36,6.0,1,85,Semi-Urban,Manager,62797,0 +64194,Male,46,Bachelors,1,2,96,40,76,3.0,6,61,Semi-Urban,Software Engineer,84750,0 +64195,Other,22,Bachelors,0,44,52,84,61,2.0,0,26,Urban,HR Executive,53203,0 +64196,Female,45,Diploma,3,20,62,18,20,6.0,3,69,Urban,Manager,123409,0 +64197,Female,47,Diploma,4,81,19,69,96,3.0,6,60,Urban,HR Executive,123247,0 +64198,Male,52,Diploma,9,11,10,61,57,5.0,1,4,Urban,ML Engineer,45795,0 +64199,Male,36,Masters,5,38,79,27,41,6.0,5,64,Urban,HR Executive,102059,0 +64200,Female,34,Bachelors,14,94,36,79,11,1.0,5,76,Rural,Software Engineer,134650,1 +64201,Male,57,Masters,1,29,0,41,64,3.0,3,11,Urban,ML Engineer,143016,0 +64202,Female,50,Masters,7,80,87,77,67,3.0,1,48,Rural,Manager,144462,1 +64203,Other,55,High School,2,38,72,83,17,2.0,3,90,Urban,HR Executive,128942,1 +64204,Female,36,Bachelors,6,13,57,12,84,8.0,3,97,Semi-Urban,ML Engineer,146791,0 +64205,Male,26,Masters,15,10,39,94,59,8.0,6,33,Semi-Urban,Data Analyst,120683,0 +64206,Male,59,Masters,10,34,14,70,51,5.0,3,48,Urban,Data Analyst,101051,0 +64207,Male,42,PhD,4,66,21,8,73,6.0,7,36,Urban,ML Engineer,38170,0 +64208,Female,44,Bachelors,3,48,71,14,98,6.0,6,85,Rural,Data Analyst,112738,0 +64209,Male,50,Bachelors,9,44,61,8,29,3.0,3,55,Rural,Data Analyst,44287,0 +64210,Male,43,Bachelors,6,9,68,67,97,6.0,4,20,Urban,ML Engineer,35048,0 +64211,Male,38,High School,2,20,80,80,22,8.0,0,70,Semi-Urban,ML Engineer,145549,1 +64212,Female,44,Bachelors,12,55,1,21,18,0.0,5,94,Urban,HR Executive,106937,0 +64213,Male,27,Masters,5,43,54,35,10,4.0,2,59,Urban,Manager,102194,0 +64214,Male,49,Diploma,5,31,48,85,13,3.0,0,2,Urban,HR Executive,130589,0 +64215,Male,49,Diploma,19,60,60,57,46,5.0,6,57,Urban,Data Analyst,103482,0 +64216,Male,53,Masters,2,53,91,57,30,8.0,1,68,Urban,Software Engineer,82974,1 +64217,Male,47,Masters,17,10,71,45,25,2.0,7,94,Semi-Urban,ML Engineer,82742,0 +64218,Male,32,Masters,7,1,94,70,67,2.0,5,37,Semi-Urban,Manager,84522,0 +64219,Male,40,Masters,3,63,53,65,59,5.0,5,47,Semi-Urban,HR Executive,123575,0 +64220,Male,49,High School,12,36,77,57,34,0.0,2,49,Urban,HR Executive,140996,0 +64221,Female,55,High School,12,45,32,82,94,6.0,5,74,Rural,HR Executive,44462,0 +64222,Male,33,Masters,12,72,42,29,84,1.0,2,75,Urban,Data Analyst,45865,0 +64223,Other,37,Bachelors,6,14,55,72,32,9.0,3,73,Rural,Data Analyst,87277,0 +64224,Female,33,Bachelors,2,58,25,85,31,2.0,4,50,Urban,HR Executive,115817,0 +64225,Female,51,Masters,6,34,73,17,91,5.0,7,56,Urban,ML Engineer,32997,0 +64226,Male,52,High School,16,25,37,94,72,3.0,0,43,Urban,HR Executive,59834,0 +64227,Female,48,Diploma,3,77,75,44,14,5.0,6,61,Urban,Data Analyst,102031,1 +64228,Female,37,Diploma,14,77,2,50,91,5.0,4,58,Urban,Data Analyst,126191,0 +64229,Male,48,Bachelors,8,55,73,63,9,4.0,6,28,Urban,ML Engineer,65011,0 +64230,Male,34,Diploma,13,60,63,20,60,0.0,3,21,Rural,Data Analyst,149208,0 +64231,Male,48,Masters,7,48,41,31,73,8.0,4,55,Rural,Manager,51084,0 +64232,Male,28,High School,19,8,55,38,51,8.0,0,62,Urban,HR Executive,54927,0 +64233,Male,37,Bachelors,14,31,39,65,22,2.0,2,46,Urban,Data Analyst,27261,0 +64234,Other,25,Diploma,9,49,10,73,56,0.0,7,55,Semi-Urban,ML Engineer,115145,0 +64235,Female,47,Bachelors,11,61,14,16,84,0.0,1,32,Urban,Data Analyst,67751,0 +64236,Male,59,High School,11,90,41,48,30,2.0,5,46,Urban,HR Executive,142576,0 +64237,Male,23,High School,15,22,45,13,18,8.0,1,85,Rural,Software Engineer,77107,0 +64238,Female,42,Diploma,15,53,52,81,45,2.0,7,41,Rural,ML Engineer,136555,0 +64239,Male,52,Diploma,0,36,68,45,76,0.0,5,2,Urban,ML Engineer,95748,0 +64240,Female,57,PhD,3,14,2,91,28,3.0,3,63,Urban,Data Analyst,35092,0 +64241,Male,38,Diploma,10,29,92,82,24,5.0,1,89,Urban,Software Engineer,132629,1 +64242,Male,43,Masters,13,1,5,68,63,4.0,6,34,Urban,Manager,110112,0 +64243,Female,41,Bachelors,15,71,36,61,84,8.0,7,89,Rural,Manager,144658,1 +64244,Male,49,PhD,7,83,35,80,9,0.0,6,3,Rural,Data Analyst,102333,0 +64245,Male,56,Bachelors,15,81,15,41,5,2.0,5,30,Semi-Urban,HR Executive,91425,0 +64246,Female,46,High School,10,75,69,60,75,4.0,4,42,Rural,Data Analyst,108772,1 +64247,Male,50,Diploma,6,57,62,63,75,9.0,2,43,Urban,Software Engineer,111081,0 +64248,Female,49,Masters,5,56,96,9,74,3.0,2,62,Rural,Manager,27452,0 +64249,Female,26,Masters,0,16,51,48,41,4.0,1,43,Urban,Software Engineer,125134,0 +64250,Male,36,Diploma,19,82,58,30,78,3.0,2,32,Urban,Software Engineer,29209,0 +64251,Male,36,Bachelors,7,56,92,32,43,5.0,3,95,Rural,HR Executive,25622,1 +64252,Female,58,Diploma,7,63,74,30,88,5.0,2,0,Semi-Urban,Data Analyst,141190,0 +64253,Male,28,Bachelors,16,77,28,29,86,1.0,1,21,Urban,ML Engineer,39575,0 +64254,Female,55,High School,16,42,32,39,48,7.0,3,18,Urban,HR Executive,78626,0 +64255,Male,56,Diploma,9,60,80,46,28,0.0,1,98,Rural,Manager,47174,1 +64256,Female,34,Bachelors,16,91,57,98,98,8.0,0,99,Urban,Manager,63982,1 +64257,Male,25,Diploma,4,1,54,95,74,9.0,3,8,Semi-Urban,Software Engineer,20888,0 +64258,Female,25,Bachelors,8,87,38,72,8,5.0,4,77,Rural,Manager,43138,1 +64259,Female,31,Bachelors,9,84,60,25,12,6.0,1,63,Semi-Urban,Data Analyst,130583,0 +64260,Male,49,Bachelors,1,66,17,27,3,8.0,1,83,Rural,Software Engineer,39692,0 +64261,Female,52,Diploma,15,48,51,43,34,4.0,2,9,Urban,Data Analyst,69224,0 +64262,Male,25,Diploma,6,45,2,58,67,8.0,2,91,Semi-Urban,Manager,71420,0 +64263,Male,59,PhD,6,11,98,56,25,1.0,5,79,Semi-Urban,HR Executive,144703,1 +64264,Male,28,Diploma,15,64,33,59,34,7.0,5,2,Urban,HR Executive,147733,0 +64265,Female,55,Bachelors,6,62,61,22,47,5.0,0,72,Urban,ML Engineer,94651,0 +64266,Other,46,Diploma,10,66,70,15,17,0.0,5,97,Urban,ML Engineer,120221,1 +64267,Female,59,High School,3,70,73,20,5,4.0,4,8,Urban,Data Analyst,39166,0 +64268,Male,43,Diploma,3,87,90,55,91,8.0,2,6,Urban,Data Analyst,23690,1 +64269,Female,45,High School,17,52,30,89,39,6.0,0,74,Semi-Urban,Manager,99166,1 +64270,Male,49,Bachelors,7,52,71,11,47,9.0,7,54,Rural,ML Engineer,52838,0 +64271,Male,57,Bachelors,6,38,51,18,62,4.0,7,78,Urban,ML Engineer,136340,0 +64272,Male,44,PhD,8,59,32,87,17,5.0,6,81,Semi-Urban,ML Engineer,105168,1 +64273,Other,34,High School,4,36,3,42,90,9.0,2,28,Urban,ML Engineer,36309,0 +64274,Male,50,Diploma,0,76,58,55,57,9.0,4,50,Urban,Data Analyst,45445,1 +64275,Male,22,Bachelors,0,45,16,19,44,8.0,3,87,Urban,Software Engineer,82218,0 +64276,Male,37,Bachelors,16,69,6,27,58,1.0,2,15,Semi-Urban,Manager,138746,0 +64277,Female,43,Bachelors,4,55,79,97,84,2.0,1,56,Urban,Manager,44500,1 +64278,Male,58,Bachelors,16,70,14,32,5,4.0,5,16,Semi-Urban,Manager,32394,0 +64279,Female,45,Diploma,10,11,19,59,70,2.0,1,32,Semi-Urban,ML Engineer,134973,0 +64280,Male,33,Bachelors,12,99,51,78,38,1.0,4,36,Semi-Urban,ML Engineer,92996,1 +64281,Male,55,PhD,18,86,94,52,27,8.0,5,34,Semi-Urban,HR Executive,63684,1 +64282,Female,37,Bachelors,0,22,6,65,35,3.0,6,10,Urban,Software Engineer,30669,0 +64283,Male,42,Masters,12,56,47,32,44,8.0,4,95,Urban,Manager,81624,0 +64284,Female,43,Masters,6,1,11,66,74,4.0,6,53,Urban,Manager,133769,0 +64285,Female,26,High School,13,88,55,73,11,6.0,3,92,Urban,Software Engineer,89123,1 +64286,Female,35,Bachelors,5,52,10,89,13,6.0,7,56,Rural,Manager,33831,0 +64287,Female,58,Diploma,16,35,55,73,78,2.0,5,96,Urban,Data Analyst,86470,1 +64288,Female,26,PhD,5,96,28,58,58,8.0,5,33,Rural,Manager,52577,0 +64289,Female,49,Bachelors,3,8,52,36,38,4.0,5,82,Rural,Data Analyst,120773,0 +64290,Other,59,Diploma,17,23,86,0,38,9.0,0,66,Urban,Manager,80882,0 +64291,Male,32,Masters,14,69,83,4,15,7.0,1,32,Rural,Manager,20686,0 +64292,Female,49,Bachelors,1,34,7,72,29,3.0,2,41,Urban,Data Analyst,117794,0 +64293,Male,44,Bachelors,6,73,10,22,91,7.0,4,68,Urban,HR Executive,49363,0 +64294,Male,27,Diploma,19,46,14,28,88,5.0,5,29,Semi-Urban,Software Engineer,68338,0 +64295,Female,54,Bachelors,3,29,44,58,96,0.0,7,72,Semi-Urban,Software Engineer,63360,0 +64296,Male,37,Bachelors,17,99,90,30,26,9.0,5,81,Urban,Data Analyst,120637,1 +64297,Male,45,Diploma,7,76,88,96,72,0.0,5,28,Urban,ML Engineer,31180,1 +64298,Male,36,Bachelors,15,98,53,15,12,0.0,7,10,Rural,Data Analyst,123968,0 +64299,Male,42,Diploma,4,76,77,7,58,2.0,2,65,Rural,Manager,123665,0 +64300,Male,39,Masters,4,66,82,82,9,4.0,7,11,Urban,HR Executive,80337,1 +64301,Male,59,Bachelors,1,84,45,72,13,9.0,3,29,Rural,HR Executive,30927,0 +64302,Male,21,Bachelors,12,9,66,70,26,9.0,3,37,Rural,Manager,131538,0 +64303,Female,39,Bachelors,14,91,33,94,39,9.0,7,81,Rural,Software Engineer,114729,1 +64304,Female,43,Bachelors,2,6,13,1,83,1.0,3,25,Urban,HR Executive,99505,0 +64305,Male,54,Masters,5,5,93,70,62,4.0,5,16,Rural,HR Executive,52310,0 +64306,Female,44,Masters,7,81,82,81,66,9.0,2,10,Urban,Manager,147668,1 +64307,Male,43,Bachelors,4,57,35,87,20,0.0,7,27,Urban,Software Engineer,130783,0 +64308,Male,55,Bachelors,19,14,97,76,31,0.0,1,76,Urban,Software Engineer,149873,1 +64309,Female,28,Diploma,10,84,66,9,82,0.0,2,86,Semi-Urban,Manager,87675,1 +64310,Male,35,Diploma,1,12,64,44,0,9.0,3,1,Urban,Manager,94548,0 +64311,Other,56,Masters,14,19,91,5,86,8.0,5,4,Semi-Urban,Data Analyst,23842,0 +64312,Male,28,Bachelors,11,64,32,73,6,2.0,4,43,Semi-Urban,HR Executive,25806,0 +64313,Female,40,PhD,1,29,40,20,0,1.0,0,78,Rural,Software Engineer,92180,0 +64314,Male,24,Bachelors,9,0,65,20,93,9.0,4,36,Semi-Urban,Software Engineer,149805,0 +64315,Female,54,Bachelors,3,40,93,42,66,3.0,3,9,Urban,HR Executive,51587,0 +64316,Male,59,Diploma,13,93,0,94,15,7.0,5,64,Rural,Software Engineer,95060,1 +64317,Male,37,Masters,1,43,49,22,6,2.0,2,4,Urban,Software Engineer,106192,0 +64318,Male,54,Bachelors,5,92,52,51,25,7.0,7,0,Rural,Data Analyst,62721,0 +64319,Male,33,Bachelors,5,49,29,28,22,0.0,4,14,Urban,Data Analyst,115975,0 +64320,Male,29,Diploma,19,93,22,85,49,7.0,4,96,Urban,HR Executive,24030,1 +64321,Other,59,Bachelors,18,72,1,64,14,5.0,2,98,Urban,ML Engineer,66747,0 +64322,Female,23,Masters,15,6,26,86,73,5.0,0,90,Urban,HR Executive,39385,0 +64323,Female,35,Diploma,12,36,75,99,14,6.0,5,48,Rural,Manager,57520,1 +64324,Female,44,High School,10,9,92,18,0,2.0,1,61,Semi-Urban,ML Engineer,141069,0 +64325,Female,40,Bachelors,13,75,3,89,14,7.0,5,1,Semi-Urban,Data Analyst,28391,0 +64326,Female,32,High School,3,62,12,76,41,5.0,6,24,Semi-Urban,HR Executive,139122,0 +64327,Female,34,Bachelors,14,6,97,68,96,0.0,6,24,Urban,Software Engineer,54924,0 +64328,Female,37,High School,8,73,16,20,93,5.0,7,43,Urban,Software Engineer,117074,0 +64329,Male,42,Diploma,5,51,89,69,74,7.0,2,6,Urban,Data Analyst,125600,0 +64330,Male,43,Bachelors,14,45,54,56,9,8.0,3,64,Urban,ML Engineer,102112,0 +64331,Female,44,High School,13,4,71,83,64,0.0,6,8,Urban,Data Analyst,148724,0 +64332,Male,53,High School,2,48,84,63,71,6.0,5,28,Rural,Software Engineer,50388,0 +64333,Male,40,Bachelors,4,1,75,55,52,7.0,0,52,Semi-Urban,ML Engineer,107596,0 +64334,Female,28,Masters,10,31,46,33,10,0.0,4,69,Semi-Urban,Software Engineer,66849,0 +64335,Female,52,Diploma,10,28,28,42,35,2.0,7,46,Semi-Urban,HR Executive,134033,0 +64336,Female,29,Bachelors,12,88,34,64,45,4.0,0,33,Urban,Data Analyst,52394,0 +64337,Other,56,Bachelors,15,25,69,94,49,4.0,6,91,Rural,Software Engineer,126731,1 +64338,Female,30,Diploma,13,68,1,36,19,4.0,1,28,Urban,Data Analyst,74558,0 +64339,Male,38,Diploma,0,89,1,72,99,5.0,7,57,Semi-Urban,Manager,35491,0 +64340,Male,59,Bachelors,19,6,60,54,47,8.0,3,84,Urban,Data Analyst,91110,0 +64341,Male,51,High School,11,63,71,91,75,6.0,1,24,Semi-Urban,ML Engineer,110122,1 +64342,Male,46,Masters,19,89,14,32,81,5.0,2,69,Urban,Data Analyst,55851,0 +64343,Male,36,Bachelors,12,18,96,52,75,1.0,0,26,Urban,Manager,49392,0 +64344,Male,53,High School,9,23,37,41,45,8.0,2,56,Semi-Urban,HR Executive,38287,0 +64345,Female,44,Bachelors,15,1,22,84,10,6.0,3,50,Rural,Data Analyst,133905,0 +64346,Female,54,Bachelors,15,78,94,87,62,6.0,3,31,Urban,Manager,96212,1 +64347,Female,37,High School,16,46,26,46,56,4.0,4,19,Urban,HR Executive,52216,0 +64348,Female,52,Bachelors,10,18,28,79,18,2.0,6,48,Urban,Data Analyst,27991,0 +64349,Male,43,Masters,10,76,22,90,9,6.0,1,8,Urban,Software Engineer,43693,0 +64350,Male,33,Bachelors,8,20,63,42,76,4.0,3,8,Urban,Software Engineer,20390,0 +64351,Male,37,Masters,19,32,11,31,36,9.0,1,66,Rural,Data Analyst,88668,0 +64352,Female,48,High School,18,86,44,1,55,8.0,6,16,Semi-Urban,ML Engineer,94752,0 +64353,Male,28,Diploma,15,19,34,49,53,5.0,2,88,Semi-Urban,Manager,109314,0 +64354,Male,53,Bachelors,14,20,23,25,68,4.0,0,24,Urban,HR Executive,67635,0 +64355,Male,40,Bachelors,8,38,96,62,12,2.0,0,37,Urban,HR Executive,138473,0 +64356,Female,36,Masters,14,70,96,87,9,9.0,6,55,Semi-Urban,Data Analyst,145891,1 +64357,Male,57,High School,10,32,54,78,71,4.0,0,37,Urban,Software Engineer,52475,0 +64358,Female,55,Diploma,7,36,8,76,69,2.0,1,76,Urban,HR Executive,35680,0 +64359,Male,42,Bachelors,16,77,64,90,21,4.0,7,16,Rural,Data Analyst,122664,1 +64360,Male,56,Diploma,0,87,7,40,27,2.0,5,81,Semi-Urban,Software Engineer,108727,0 +64361,Male,43,Bachelors,19,90,11,19,66,1.0,5,71,Urban,Manager,30957,0 +64362,Male,56,Diploma,0,50,99,13,31,9.0,7,6,Urban,Manager,102250,0 +64363,Male,54,Bachelors,4,58,58,45,35,3.0,3,53,Semi-Urban,Manager,38065,0 +64364,Male,41,Diploma,9,85,51,68,99,3.0,4,47,Urban,Manager,140461,1 +64365,Male,52,High School,16,14,41,42,10,2.0,3,76,Urban,ML Engineer,54351,0 +64366,Male,47,Diploma,18,36,83,59,62,6.0,4,79,Urban,ML Engineer,91055,1 +64367,Male,46,Bachelors,8,57,72,41,97,2.0,2,56,Rural,Software Engineer,42601,0 +64368,Male,24,High School,17,1,96,86,97,7.0,3,4,Rural,Data Analyst,143384,0 +64369,Male,40,Bachelors,7,52,77,29,65,0.0,1,32,Urban,Data Analyst,101293,0 +64370,Male,33,Bachelors,13,46,78,12,18,6.0,1,8,Rural,Data Analyst,22308,0 +64371,Male,58,Diploma,5,46,53,70,22,3.0,1,90,Semi-Urban,ML Engineer,26544,1 +64372,Female,46,Bachelors,5,40,0,80,63,4.0,1,79,Urban,Manager,50726,0 +64373,Female,24,Bachelors,0,55,18,23,74,7.0,4,85,Urban,HR Executive,118476,0 +64374,Male,25,Masters,13,38,44,21,76,7.0,1,90,Urban,ML Engineer,104647,0 +64375,Male,52,High School,3,84,66,78,85,6.0,7,57,Rural,HR Executive,90723,1 +64376,Female,44,Masters,15,93,69,25,98,4.0,0,43,Rural,Software Engineer,62258,0 +64377,Male,58,Bachelors,7,18,49,96,99,7.0,0,38,Rural,Software Engineer,133507,0 +64378,Female,31,Diploma,7,12,67,77,23,0.0,2,58,Urban,Manager,101392,0 +64379,Male,43,Diploma,7,11,22,19,24,8.0,5,36,Urban,Software Engineer,140137,0 +64380,Female,51,Masters,10,54,17,5,3,3.0,3,26,Semi-Urban,HR Executive,54211,0 +64381,Female,51,Diploma,18,36,34,87,63,8.0,3,49,Semi-Urban,Manager,142197,0 +64382,Male,36,High School,8,99,7,5,33,7.0,2,22,Urban,HR Executive,64577,0 +64383,Male,54,Bachelors,1,44,18,15,55,3.0,2,98,Urban,Manager,62800,0 +64384,Female,37,Bachelors,1,47,87,10,52,7.0,1,30,Urban,ML Engineer,65765,0 +64385,Female,41,High School,19,71,64,84,11,9.0,0,19,Semi-Urban,HR Executive,81182,0 +64386,Male,53,Bachelors,15,12,54,15,84,7.0,7,61,Urban,Software Engineer,21554,0 +64387,Male,51,Masters,13,9,62,64,0,3.0,1,26,Semi-Urban,HR Executive,57804,0 +64388,Male,48,Masters,3,28,96,76,46,2.0,0,94,Urban,HR Executive,137766,1 +64389,Female,51,PhD,7,53,65,72,56,5.0,4,36,Urban,ML Engineer,93807,0 +64390,Male,28,Bachelors,9,36,3,85,68,0.0,0,86,Urban,Software Engineer,68797,0 +64391,Female,34,Diploma,2,28,1,64,99,8.0,7,38,Semi-Urban,Manager,128678,0 +64392,Male,42,Bachelors,7,54,48,62,46,2.0,6,99,Semi-Urban,Data Analyst,52779,1 +64393,Female,26,Diploma,14,72,89,11,94,2.0,5,88,Semi-Urban,Manager,116623,1 +64394,Male,42,Bachelors,8,69,30,54,42,0.0,5,73,Semi-Urban,ML Engineer,86502,0 +64395,Female,35,Diploma,17,92,93,17,85,8.0,4,83,Urban,HR Executive,73311,1 +64396,Male,52,Bachelors,1,30,14,34,17,5.0,3,15,Urban,HR Executive,81294,0 +64397,Male,36,Diploma,16,88,95,89,57,7.0,2,11,Urban,Manager,35283,1 +64398,Female,54,Masters,2,5,58,59,53,4.0,6,75,Semi-Urban,Data Analyst,45172,0 +64399,Male,22,Masters,6,73,14,12,68,0.0,3,88,Semi-Urban,Data Analyst,76032,0 +64400,Male,46,Bachelors,14,72,41,5,70,0.0,2,45,Semi-Urban,Manager,26975,0 +64401,Male,29,Bachelors,16,85,74,50,90,2.0,6,17,Urban,Manager,87981,0 +64402,Female,51,High School,18,13,0,55,25,2.0,0,21,Semi-Urban,Manager,123394,0 +64403,Male,45,Bachelors,16,37,79,9,95,4.0,3,81,Rural,Data Analyst,120033,0 +64404,Male,53,Bachelors,6,8,16,69,2,6.0,2,29,Urban,Data Analyst,42500,0 +64405,Male,29,Bachelors,0,93,7,9,38,3.0,5,34,Semi-Urban,Software Engineer,43006,0 +64406,Male,29,Diploma,10,15,79,82,53,2.0,4,63,Semi-Urban,Data Analyst,68721,1 +64407,Male,56,Diploma,5,3,58,48,60,6.0,3,67,Semi-Urban,Manager,131841,0 +64408,Male,31,High School,1,78,70,54,63,8.0,4,30,Urban,HR Executive,137533,0 +64409,Male,29,Diploma,19,47,80,98,10,4.0,2,41,Urban,Software Engineer,144472,1 +64410,Male,56,PhD,17,55,47,66,9,5.0,2,80,Semi-Urban,HR Executive,59818,1 +64411,Male,40,Bachelors,7,28,45,35,6,8.0,2,49,Urban,HR Executive,107597,0 +64412,Male,57,Bachelors,11,55,45,80,57,6.0,6,90,Rural,HR Executive,136649,1 +64413,Male,42,PhD,0,7,49,97,55,0.0,2,39,Urban,Software Engineer,112004,0 +64414,Female,56,Masters,17,4,81,97,25,9.0,4,17,Urban,HR Executive,77781,0 +64415,Male,26,Masters,3,55,22,78,80,1.0,6,50,Urban,Manager,55000,0 +64416,Male,46,Masters,19,91,52,86,48,1.0,0,56,Semi-Urban,Manager,96338,1 +64417,Male,23,High School,12,28,12,0,32,2.0,3,97,Urban,HR Executive,50520,0 +64418,Other,21,Bachelors,4,35,56,0,58,4.0,4,83,Urban,HR Executive,138289,0 +64419,Other,35,Bachelors,15,54,43,5,69,7.0,2,88,Urban,Software Engineer,123230,0 +64420,Male,53,PhD,14,45,67,89,91,5.0,4,85,Urban,HR Executive,135212,1 +64421,Male,42,Bachelors,7,68,14,45,62,4.0,4,2,Semi-Urban,HR Executive,48134,0 +64422,Male,45,High School,8,35,90,41,30,4.0,5,1,Urban,Manager,86268,0 +64423,Male,57,Masters,7,9,73,66,82,3.0,6,67,Urban,HR Executive,73127,0 +64424,Male,42,Bachelors,7,72,51,44,70,5.0,2,73,Urban,ML Engineer,135903,1 +64425,Female,26,Bachelors,7,20,60,86,4,0.0,2,48,Rural,Software Engineer,47767,0 +64426,Male,23,Diploma,8,48,11,40,16,5.0,2,0,Rural,Data Analyst,107930,0 +64427,Male,23,Masters,7,94,53,78,59,7.0,7,44,Semi-Urban,HR Executive,139669,1 +64428,Male,42,Diploma,2,85,78,38,87,0.0,6,30,Rural,Manager,105953,0 +64429,Male,25,Bachelors,14,89,7,23,90,3.0,3,12,Urban,Manager,104969,0 +64430,Other,45,Masters,2,2,36,29,32,8.0,3,8,Rural,Software Engineer,27222,0 +64431,Male,44,Bachelors,0,19,95,88,81,0.0,4,83,Urban,HR Executive,26069,1 +64432,Male,47,Diploma,5,81,5,44,92,5.0,3,8,Urban,ML Engineer,21163,0 +64433,Male,37,Bachelors,18,33,30,0,0,3.0,0,51,Urban,Data Analyst,64332,0 +64434,Female,42,Masters,9,6,50,84,98,2.0,2,88,Urban,HR Executive,74146,0 +64435,Male,22,Bachelors,18,47,49,0,73,2.0,6,0,Semi-Urban,Manager,93325,0 +64436,Male,21,High School,18,33,21,5,41,8.0,1,22,Semi-Urban,Manager,141166,0 +64437,Male,45,Bachelors,15,58,74,76,29,4.0,1,7,Rural,Data Analyst,96887,0 +64438,Male,47,Diploma,17,60,75,45,80,7.0,2,60,Urban,HR Executive,144906,1 +64439,Male,22,PhD,5,20,55,86,6,7.0,5,83,Urban,ML Engineer,117105,1 +64440,Male,43,Bachelors,6,30,46,96,3,8.0,3,47,Urban,ML Engineer,63640,0 +64441,Male,48,Bachelors,18,70,51,27,8,2.0,1,84,Urban,ML Engineer,97490,0 +64442,Female,59,Masters,9,24,59,35,88,5.0,4,15,Urban,Data Analyst,70100,0 +64443,Female,27,Bachelors,13,66,30,26,96,5.0,7,12,Rural,ML Engineer,143337,0 +64444,Female,27,Masters,16,63,97,13,91,8.0,0,90,Semi-Urban,Software Engineer,80452,1 +64445,Male,57,Bachelors,3,26,56,9,41,3.0,5,93,Urban,HR Executive,88981,0 +64446,Male,56,Bachelors,7,83,15,53,57,9.0,6,42,Urban,Software Engineer,35905,0 +64447,Male,55,Bachelors,5,8,90,32,61,6.0,6,38,Urban,HR Executive,33972,0 +64448,Female,46,Bachelors,19,73,67,64,31,5.0,0,79,Urban,Software Engineer,120986,1 +64449,Male,42,High School,14,38,63,46,42,9.0,3,35,Semi-Urban,HR Executive,65702,0 +64450,Male,40,High School,18,49,46,31,17,6.0,6,74,Urban,Data Analyst,97921,0 +64451,Male,47,Diploma,12,82,2,15,49,9.0,5,15,Urban,ML Engineer,39873,0 +64452,Female,43,Bachelors,5,42,79,30,67,1.0,7,55,Urban,Software Engineer,101772,0 +64453,Female,57,Diploma,7,9,54,94,0,9.0,1,76,Urban,Software Engineer,94907,0 +64454,Male,43,Bachelors,2,30,34,16,5,0.0,7,3,Urban,Software Engineer,130902,0 +64455,Female,23,Bachelors,19,91,99,3,8,5.0,2,85,Rural,Data Analyst,143909,1 +64456,Male,24,Diploma,0,14,22,69,19,8.0,4,16,Urban,Software Engineer,42582,0 +64457,Male,37,Masters,19,77,31,76,81,9.0,0,82,Semi-Urban,ML Engineer,141642,1 +64458,Male,52,Bachelors,18,27,78,52,16,1.0,5,82,Rural,Data Analyst,36974,1 +64459,Male,40,Diploma,0,80,91,3,5,0.0,4,10,Urban,HR Executive,36686,0 +64460,Female,37,Masters,3,37,69,89,97,9.0,7,36,Rural,Software Engineer,90687,0 +64461,Male,58,Bachelors,11,79,42,13,74,0.0,1,58,Urban,Manager,66120,0 +64462,Male,57,Bachelors,4,39,58,2,7,1.0,5,48,Semi-Urban,Manager,142974,0 +64463,Male,26,Diploma,8,31,79,73,26,2.0,6,43,Urban,Data Analyst,74047,0 +64464,Male,29,Masters,16,69,22,85,69,9.0,5,92,Urban,HR Executive,97601,1 +64465,Other,59,Bachelors,13,97,52,30,9,5.0,4,44,Urban,HR Executive,138887,0 +64466,Female,54,Masters,13,5,78,51,70,7.0,7,61,Urban,HR Executive,107567,0 +64467,Female,51,Diploma,15,10,57,22,14,8.0,2,63,Rural,HR Executive,100539,0 +64468,Male,45,Masters,19,66,17,7,64,2.0,1,42,Semi-Urban,HR Executive,123820,0 +64469,Male,36,Masters,12,23,50,6,23,0.0,2,55,Urban,ML Engineer,139301,0 +64470,Female,25,Diploma,6,98,27,18,17,4.0,4,50,Urban,ML Engineer,89672,0 +64471,Male,44,Bachelors,11,8,61,39,27,7.0,6,56,Urban,ML Engineer,143069,0 +64472,Male,23,Diploma,10,53,86,0,3,3.0,1,94,Rural,ML Engineer,77937,0 +64473,Male,44,High School,5,1,1,97,97,3.0,0,10,Semi-Urban,Manager,93719,0 +64474,Female,48,Bachelors,13,36,11,57,5,0.0,5,40,Rural,HR Executive,62170,0 +64475,Female,38,PhD,13,49,67,87,92,3.0,3,4,Urban,ML Engineer,79780,0 +64476,Male,40,Diploma,4,15,32,24,14,2.0,0,37,Urban,ML Engineer,36439,0 +64477,Female,30,Bachelors,16,65,31,40,66,2.0,4,19,Rural,Manager,123654,0 +64478,Female,31,Masters,0,84,73,82,39,9.0,3,9,Semi-Urban,Manager,83681,1 +64479,Male,39,High School,15,25,60,53,67,0.0,2,72,Rural,Software Engineer,78876,0 +64480,Female,48,PhD,8,11,97,41,98,2.0,6,98,Urban,HR Executive,43477,1 +64481,Male,27,Bachelors,18,90,72,55,46,7.0,5,66,Urban,HR Executive,95922,1 +64482,Female,22,Masters,12,44,77,72,60,8.0,5,61,Urban,Data Analyst,45517,1 +64483,Male,55,Bachelors,9,78,63,40,99,0.0,2,65,Urban,Manager,54433,1 +64484,Male,26,High School,4,62,43,88,85,1.0,0,14,Urban,Software Engineer,109914,0 +64485,Female,40,Masters,10,38,53,41,56,6.0,5,70,Rural,HR Executive,46260,0 +64486,Male,43,Masters,4,1,6,39,51,6.0,7,2,Urban,HR Executive,53251,0 +64487,Female,35,Bachelors,5,74,12,4,26,8.0,0,21,Rural,Data Analyst,58699,0 +64488,Male,30,Masters,6,24,62,29,32,3.0,3,89,Urban,Manager,79902,0 +64489,Male,25,Bachelors,18,86,80,5,84,4.0,4,87,Urban,HR Executive,143897,1 +64490,Male,49,Masters,13,50,44,96,99,7.0,2,46,Urban,Manager,36908,1 +64491,Female,57,Bachelors,17,29,79,39,78,6.0,1,95,Semi-Urban,Manager,129400,1 +64492,Male,59,Diploma,1,59,71,71,80,8.0,2,57,Urban,ML Engineer,137976,1 +64493,Female,21,Bachelors,14,48,90,10,1,0.0,5,92,Urban,ML Engineer,37395,0 +64494,Male,25,Bachelors,2,40,50,89,11,9.0,2,14,Semi-Urban,Software Engineer,86328,0 +64495,Male,43,Bachelors,2,42,8,80,41,5.0,3,69,Rural,Manager,53879,0 +64496,Male,58,High School,0,26,60,4,40,8.0,3,3,Rural,ML Engineer,139794,0 +64497,Other,42,High School,10,12,56,47,99,9.0,1,43,Semi-Urban,Software Engineer,90591,0 +64498,Female,38,High School,14,1,98,48,63,1.0,1,92,Urban,Software Engineer,45668,0 +64499,Male,55,High School,5,23,80,32,40,3.0,0,0,Semi-Urban,Data Analyst,109028,0 +64500,Female,21,Bachelors,13,17,59,6,40,3.0,2,38,Rural,HR Executive,61266,0 +64501,Female,58,Diploma,3,34,57,91,60,3.0,7,45,Urban,ML Engineer,146687,0 +64502,Male,39,Diploma,2,57,60,39,20,1.0,4,31,Semi-Urban,Data Analyst,44828,0 +64503,Male,50,Masters,13,74,42,59,30,6.0,7,87,Urban,Manager,125267,1 +64504,Male,28,Bachelors,1,42,20,88,56,3.0,3,81,Semi-Urban,ML Engineer,85960,0 +64505,Male,26,Masters,2,87,81,35,64,0.0,4,25,Semi-Urban,HR Executive,86636,0 +64506,Male,22,Bachelors,12,44,85,12,14,2.0,7,90,Urban,Software Engineer,104801,0 +64507,Female,52,PhD,17,75,51,88,43,9.0,0,62,Urban,Data Analyst,100188,1 +64508,Male,40,Bachelors,10,83,18,82,61,4.0,6,27,Urban,Manager,61118,0 +64509,Female,41,Diploma,8,45,26,93,79,1.0,2,9,Semi-Urban,Manager,146769,0 +64510,Female,28,Masters,15,76,36,69,19,8.0,4,36,Urban,Software Engineer,38320,0 +64511,Female,44,High School,3,21,29,48,65,9.0,0,42,Urban,Data Analyst,41134,0 +64512,Male,39,High School,9,42,84,41,53,2.0,4,68,Rural,Manager,111953,1 +64513,Male,33,Bachelors,15,80,42,59,40,4.0,1,15,Semi-Urban,Software Engineer,42988,0 +64514,Female,45,Diploma,5,96,26,35,91,1.0,1,71,Urban,Manager,38125,0 +64515,Male,22,Bachelors,10,75,99,52,45,7.0,0,77,Urban,Software Engineer,44989,1 +64516,Female,38,Masters,8,50,70,99,64,1.0,0,62,Urban,Manager,140796,1 +64517,Male,35,Bachelors,13,67,35,78,92,0.0,6,68,Rural,Data Analyst,87356,1 +64518,Male,35,Masters,5,72,6,89,18,3.0,7,63,Urban,Manager,134379,0 +64519,Female,47,Bachelors,13,15,49,50,68,0.0,5,46,Urban,ML Engineer,109277,0 +64520,Male,50,Masters,8,12,32,79,27,1.0,0,96,Semi-Urban,HR Executive,135584,0 +64521,Female,42,Diploma,11,87,13,4,18,7.0,0,63,Semi-Urban,Data Analyst,98596,0 +64522,Female,46,Bachelors,17,85,25,17,1,9.0,2,52,Urban,Data Analyst,99653,0 +64523,Female,31,Bachelors,2,41,73,98,86,0.0,5,41,Rural,Software Engineer,107518,1 +64524,Male,51,Diploma,6,25,18,40,73,8.0,4,30,Semi-Urban,Software Engineer,51013,0 +64525,Male,47,Diploma,4,50,19,15,15,4.0,0,28,Urban,Data Analyst,130114,0 +64526,Female,51,Diploma,4,64,80,77,5,2.0,0,57,Rural,ML Engineer,141165,1 +64527,Female,24,High School,0,87,96,90,88,3.0,0,4,Semi-Urban,Data Analyst,83559,1 +64528,Male,34,Masters,5,74,89,64,13,2.0,3,14,Semi-Urban,Data Analyst,82883,1 +64529,Male,22,Masters,0,15,98,31,76,7.0,4,21,Semi-Urban,Manager,70911,0 +64530,Female,33,High School,2,69,54,99,46,5.0,0,69,Urban,Software Engineer,81615,1 +64531,Female,41,Diploma,8,88,53,96,82,4.0,1,12,Rural,HR Executive,90760,1 +64532,Female,30,Masters,12,58,93,2,28,8.0,1,32,Urban,Software Engineer,33964,0 +64533,Male,40,Diploma,8,37,62,96,75,9.0,4,48,Semi-Urban,HR Executive,86394,1 +64534,Female,22,Diploma,1,60,15,66,29,7.0,7,41,Urban,HR Executive,43360,0 +64535,Female,22,High School,16,68,54,11,96,6.0,6,42,Urban,ML Engineer,32801,0 +64536,Male,24,Diploma,17,52,64,20,5,2.0,3,78,Urban,Software Engineer,50517,0 +64537,Male,28,Masters,5,83,1,56,32,7.0,6,84,Semi-Urban,ML Engineer,94960,0 +64538,Male,31,Bachelors,1,42,94,69,76,7.0,2,61,Rural,Manager,71998,1 +64539,Male,36,Bachelors,18,73,24,85,67,6.0,0,29,Urban,Manager,41449,0 +64540,Female,27,Diploma,18,89,28,32,23,7.0,2,75,Semi-Urban,Manager,58171,0 +64541,Male,45,Masters,12,15,72,70,18,1.0,0,14,Semi-Urban,ML Engineer,24489,0 +64542,Male,47,Diploma,1,24,25,46,9,9.0,0,89,Semi-Urban,ML Engineer,22373,0 +64543,Male,47,Diploma,12,88,26,56,9,2.0,5,87,Urban,Software Engineer,62773,1 +64544,Male,47,Diploma,3,32,55,95,84,1.0,0,26,Semi-Urban,Manager,126467,0 +64545,Male,22,Diploma,7,93,70,17,76,8.0,5,44,Urban,HR Executive,101277,0 +64546,Female,42,Bachelors,19,76,89,31,77,5.0,1,46,Urban,Manager,57681,1 +64547,Female,58,Diploma,2,46,56,92,47,7.0,3,49,Semi-Urban,Data Analyst,54063,1 +64548,Female,55,Diploma,13,7,17,97,0,3.0,2,1,Rural,ML Engineer,44785,0 +64549,Female,35,Diploma,4,61,73,38,63,3.0,2,88,Rural,Software Engineer,80868,1 +64550,Male,40,PhD,5,91,91,50,50,1.0,5,91,Urban,ML Engineer,39021,1 +64551,Female,29,Diploma,1,85,79,13,32,3.0,4,25,Semi-Urban,HR Executive,128876,0 +64552,Female,29,Masters,5,40,42,88,46,8.0,6,13,Urban,Software Engineer,54458,0 +64553,Female,43,Diploma,3,41,67,1,33,1.0,4,63,Urban,HR Executive,135133,0 +64554,Male,46,Masters,13,38,36,60,23,3.0,0,88,Rural,HR Executive,48401,0 +64555,Other,34,Masters,13,14,59,25,85,4.0,6,64,Semi-Urban,HR Executive,94518,0 +64556,Male,48,Masters,6,1,67,88,49,6.0,6,75,Urban,HR Executive,38797,0 +64557,Male,48,Bachelors,18,31,82,99,2,5.0,4,16,Urban,Data Analyst,77430,0 +64558,Female,51,Masters,16,61,99,84,41,8.0,1,65,Rural,HR Executive,39296,1 +64559,Female,26,High School,2,70,6,18,12,3.0,1,9,Semi-Urban,HR Executive,131797,0 +64560,Female,57,Diploma,19,93,11,87,70,6.0,3,72,Semi-Urban,Manager,114738,1 +64561,Female,40,Masters,3,49,60,41,38,4.0,4,95,Urban,HR Executive,56790,1 +64562,Male,42,Masters,15,17,43,47,62,5.0,2,1,Urban,Software Engineer,33966,0 +64563,Female,43,Masters,8,88,74,67,77,4.0,5,60,Urban,Data Analyst,76120,1 +64564,Male,48,Masters,11,21,82,89,1,2.0,0,26,Rural,HR Executive,32828,0 +64565,Female,34,Bachelors,11,31,69,75,29,1.0,0,70,Urban,Manager,124950,1 +64566,Male,32,Bachelors,15,85,59,11,11,4.0,3,24,Urban,Manager,117051,0 +64567,Male,49,Masters,2,46,19,36,34,2.0,6,48,Semi-Urban,Software Engineer,94040,0 +64568,Female,57,Bachelors,16,63,75,36,17,3.0,0,58,Semi-Urban,Data Analyst,114521,0 +64569,Male,40,Bachelors,14,43,4,10,43,8.0,1,17,Urban,HR Executive,51213,0 +64570,Male,35,Diploma,6,62,71,85,93,3.0,4,87,Semi-Urban,Manager,141279,1 +64571,Male,28,Diploma,14,62,79,44,87,1.0,3,71,Rural,Software Engineer,91348,1 +64572,Male,56,High School,6,9,69,89,51,3.0,2,11,Semi-Urban,HR Executive,64920,0 +64573,Female,25,Bachelors,10,16,18,40,93,0.0,7,33,Rural,Data Analyst,59451,0 +64574,Male,43,High School,10,71,31,58,6,7.0,5,5,Semi-Urban,HR Executive,148768,0 +64575,Other,38,High School,6,36,38,1,17,5.0,0,13,Urban,Software Engineer,144080,0 +64576,Male,57,High School,4,58,96,95,37,0.0,0,91,Urban,Manager,112922,1 +64577,Female,52,High School,11,70,58,86,22,4.0,4,64,Rural,HR Executive,79030,1 +64578,Other,43,Masters,12,82,44,28,82,9.0,5,92,Semi-Urban,Manager,22995,1 +64579,Male,48,High School,0,43,35,66,75,4.0,3,76,Rural,HR Executive,109972,0 +64580,Male,36,PhD,8,59,42,47,28,6.0,3,36,Urban,ML Engineer,50353,0 +64581,Male,33,Bachelors,17,27,86,80,41,3.0,3,89,Urban,ML Engineer,26116,1 +64582,Female,29,Bachelors,10,33,97,35,48,9.0,6,25,Urban,Manager,96513,0 +64583,Female,32,Diploma,13,65,48,10,19,9.0,1,62,Rural,Manager,68745,0 +64584,Male,22,Bachelors,11,53,42,56,40,0.0,7,99,Urban,ML Engineer,112420,1 +64585,Male,52,High School,2,11,26,6,23,4.0,2,78,Semi-Urban,ML Engineer,141057,0 +64586,Female,48,Diploma,15,38,32,71,86,5.0,1,51,Urban,HR Executive,40656,0 +64587,Male,59,Bachelors,7,43,26,41,86,6.0,0,41,Urban,Software Engineer,57371,0 +64588,Male,55,Bachelors,3,11,77,97,49,5.0,1,82,Semi-Urban,HR Executive,115039,1 +64589,Female,21,Bachelors,14,98,41,34,42,2.0,1,1,Urban,Software Engineer,86737,0 +64590,Other,28,High School,7,77,2,94,1,7.0,5,86,Rural,Manager,40614,1 +64591,Male,48,Diploma,9,48,27,9,5,9.0,5,2,Semi-Urban,HR Executive,30174,0 +64592,Male,27,Bachelors,7,92,33,98,57,6.0,4,71,Rural,Manager,38684,1 +64593,Female,40,Diploma,3,68,39,6,63,5.0,2,19,Urban,Data Analyst,117455,0 +64594,Male,35,Bachelors,11,5,65,91,53,7.0,3,88,Semi-Urban,HR Executive,104649,1 +64595,Other,47,Bachelors,14,92,14,23,32,3.0,6,74,Urban,Data Analyst,49304,0 +64596,Female,36,High School,16,3,35,63,79,7.0,2,57,Urban,ML Engineer,81931,0 +64597,Male,22,Bachelors,9,67,34,37,34,4.0,7,29,Urban,Data Analyst,142886,0 +64598,Female,46,Bachelors,17,14,5,86,7,9.0,7,24,Urban,HR Executive,34568,0 +64599,Female,39,Bachelors,13,2,99,93,6,1.0,7,39,Semi-Urban,ML Engineer,32472,0 +64600,Male,29,High School,18,25,36,4,37,6.0,3,11,Urban,HR Executive,104578,0 +64601,Male,41,Diploma,10,1,98,2,25,9.0,0,12,Semi-Urban,HR Executive,60414,0 +64602,Male,31,Bachelors,19,88,10,70,47,2.0,7,6,Urban,Software Engineer,97017,0 +64603,Male,39,Bachelors,18,72,38,64,4,8.0,5,51,Rural,HR Executive,90071,0 +64604,Male,26,Masters,16,58,46,29,83,4.0,1,85,Urban,ML Engineer,27267,0 +64605,Male,28,Diploma,13,78,1,10,15,5.0,0,13,Urban,HR Executive,25189,0 +64606,Male,27,Diploma,3,94,9,53,20,3.0,6,73,Urban,ML Engineer,114003,0 +64607,Male,52,High School,6,14,38,19,32,7.0,3,28,Semi-Urban,Software Engineer,65812,0 +64608,Female,30,Masters,0,82,59,4,15,4.0,5,41,Rural,Manager,51524,0 +64609,Male,29,Bachelors,9,4,61,74,28,6.0,7,24,Urban,HR Executive,125646,0 +64610,Female,55,Diploma,16,82,17,98,82,9.0,4,59,Urban,HR Executive,92057,1 +64611,Male,38,PhD,2,59,63,79,74,5.0,4,36,Urban,Manager,86667,1 +64612,Male,25,Bachelors,19,12,7,84,40,6.0,2,17,Rural,Manager,118756,0 +64613,Male,58,High School,16,51,25,24,62,1.0,3,94,Semi-Urban,Software Engineer,64752,0 +64614,Female,27,Diploma,2,64,74,39,96,6.0,2,10,Semi-Urban,Software Engineer,126183,0 +64615,Female,27,Masters,11,6,15,61,63,2.0,7,93,Semi-Urban,Software Engineer,112878,0 +64616,Female,49,Masters,7,61,6,45,41,3.0,4,46,Urban,Software Engineer,74314,0 +64617,Female,39,Diploma,4,81,78,83,8,8.0,7,38,Rural,Data Analyst,145107,1 +64618,Male,23,PhD,7,79,38,92,84,5.0,1,35,Semi-Urban,HR Executive,148349,1 +64619,Female,24,Masters,4,61,76,66,61,8.0,1,11,Rural,HR Executive,83469,0 +64620,Other,53,Bachelors,12,56,20,58,53,3.0,4,74,Urban,Software Engineer,69187,0 +64621,Female,56,Masters,14,51,14,43,32,9.0,3,93,Semi-Urban,ML Engineer,58046,0 +64622,Other,46,Diploma,10,76,30,15,58,0.0,2,97,Semi-Urban,ML Engineer,96874,0 +64623,Male,51,High School,17,76,86,56,47,9.0,4,30,Semi-Urban,Software Engineer,100309,1 +64624,Female,36,Masters,14,91,72,86,48,7.0,1,19,Urban,Manager,110936,1 +64625,Female,51,Bachelors,14,33,49,83,92,7.0,0,47,Urban,Software Engineer,110864,0 +64626,Female,47,Masters,18,47,19,60,76,6.0,2,85,Rural,HR Executive,116374,0 +64627,Female,34,Diploma,16,88,2,53,6,0.0,0,30,Semi-Urban,Software Engineer,72170,0 +64628,Male,35,High School,11,35,98,54,39,6.0,6,18,Rural,Software Engineer,47274,0 +64629,Female,38,Diploma,2,49,45,91,68,1.0,3,77,Semi-Urban,Manager,121153,1 +64630,Female,41,Bachelors,7,48,64,88,67,4.0,4,65,Semi-Urban,ML Engineer,47023,1 +64631,Male,31,PhD,8,39,23,57,28,2.0,3,21,Rural,Data Analyst,41652,0 +64632,Other,23,Bachelors,3,79,94,26,94,9.0,4,32,Urban,ML Engineer,38494,0 +64633,Male,21,Bachelors,11,21,42,53,42,0.0,2,35,Urban,ML Engineer,54124,0 +64634,Male,58,Masters,12,43,14,58,58,9.0,7,28,Urban,ML Engineer,116618,0 +64635,Male,29,Masters,4,15,25,15,7,2.0,3,12,Semi-Urban,HR Executive,147784,0 +64636,Female,48,Bachelors,10,67,95,50,89,3.0,1,44,Semi-Urban,Manager,126503,1 +64637,Male,22,Bachelors,7,30,77,98,20,4.0,1,83,Rural,Data Analyst,74267,1 +64638,Female,54,High School,15,68,29,69,59,8.0,0,91,Semi-Urban,Data Analyst,114489,1 +64639,Male,49,High School,15,8,27,17,13,9.0,3,43,Urban,Software Engineer,66979,0 +64640,Male,30,Diploma,17,47,42,6,18,5.0,5,50,Urban,Data Analyst,89669,0 +64641,Male,51,Diploma,18,24,3,87,88,4.0,4,83,Semi-Urban,Data Analyst,38221,0 +64642,Male,57,Bachelors,6,31,8,43,4,2.0,5,53,Urban,Data Analyst,26550,0 +64643,Male,28,Bachelors,16,22,62,60,1,6.0,7,51,Rural,HR Executive,54069,0 +64644,Male,54,Bachelors,1,5,99,32,85,0.0,6,94,Semi-Urban,ML Engineer,23409,0 +64645,Male,24,High School,15,51,66,13,50,7.0,5,66,Urban,Manager,128770,0 +64646,Other,40,Bachelors,10,48,50,3,41,1.0,5,65,Semi-Urban,ML Engineer,94617,0 +64647,Female,45,Masters,11,74,33,4,15,0.0,3,46,Rural,Data Analyst,26748,0 +64648,Male,52,Masters,8,47,26,71,90,6.0,4,14,Rural,Software Engineer,128342,0 +64649,Male,34,Masters,9,3,85,13,6,7.0,1,28,Semi-Urban,Software Engineer,116622,0 +64650,Male,56,Masters,15,32,50,59,25,8.0,1,55,Urban,ML Engineer,24720,0 +64651,Female,23,Masters,18,31,79,30,47,7.0,3,49,Semi-Urban,HR Executive,143596,0 +64652,Other,21,Bachelors,4,22,85,92,48,8.0,4,94,Urban,Data Analyst,86286,1 +64653,Female,36,Diploma,4,52,44,24,20,9.0,7,69,Semi-Urban,Data Analyst,108639,0 +64654,Male,41,Diploma,7,25,8,80,29,8.0,1,93,Semi-Urban,ML Engineer,136178,0 +64655,Male,27,Bachelors,5,14,81,93,6,2.0,1,4,Rural,Data Analyst,144926,0 +64656,Other,21,Bachelors,5,47,15,9,70,9.0,6,8,Urban,ML Engineer,143574,0 +64657,Male,35,Bachelors,0,24,45,40,38,0.0,5,52,Semi-Urban,Software Engineer,69089,0 +64658,Male,44,Diploma,10,53,16,66,40,5.0,2,72,Urban,Data Analyst,113617,0 +64659,Male,36,Bachelors,3,1,53,85,44,5.0,5,39,Semi-Urban,ML Engineer,130456,0 +64660,Female,42,Bachelors,10,45,69,38,54,8.0,2,83,Urban,Manager,74692,0 +64661,Male,43,Bachelors,7,47,59,47,37,4.0,4,26,Semi-Urban,Software Engineer,38955,0 +64662,Female,49,Bachelors,8,31,59,38,73,1.0,2,72,Urban,ML Engineer,103511,0 +64663,Male,29,Masters,12,20,59,6,46,6.0,3,94,Urban,Manager,96242,0 +64664,Male,57,Diploma,11,64,88,7,39,1.0,4,87,Urban,Manager,61948,1 +64665,Male,29,Bachelors,8,26,9,35,53,0.0,0,60,Urban,Manager,101606,0 +64666,Male,42,Bachelors,6,73,81,26,13,9.0,3,44,Urban,Manager,64385,0 +64667,Male,45,Bachelors,2,23,78,35,57,5.0,2,21,Urban,Software Engineer,105222,0 +64668,Male,52,Diploma,14,86,52,85,55,8.0,0,20,Rural,Data Analyst,122848,1 +64669,Male,59,High School,6,95,9,20,82,4.0,0,41,Urban,HR Executive,125080,0 +64670,Other,45,Bachelors,8,67,89,94,73,9.0,6,74,Rural,Manager,118499,1 +64671,Male,57,Bachelors,2,69,55,70,35,9.0,5,55,Semi-Urban,Manager,89035,1 +64672,Female,51,Bachelors,12,74,22,18,36,5.0,5,52,Urban,Manager,121759,0 +64673,Male,44,Bachelors,6,33,26,83,22,3.0,0,68,Rural,ML Engineer,129239,0 +64674,Male,31,Diploma,8,11,11,45,79,9.0,0,61,Urban,Software Engineer,22969,0 +64675,Female,43,Bachelors,15,96,98,97,98,5.0,3,96,Urban,Software Engineer,42072,1 +64676,Male,43,Bachelors,10,42,84,90,7,3.0,0,99,Urban,Software Engineer,49220,1 +64677,Male,23,Diploma,10,63,60,4,94,9.0,3,46,Rural,ML Engineer,100643,0 +64678,Male,48,Masters,17,96,86,23,59,7.0,7,23,Urban,Manager,116888,0 +64679,Female,30,High School,2,31,64,23,37,4.0,3,37,Semi-Urban,HR Executive,103363,0 +64680,Female,33,Bachelors,3,13,43,91,41,2.0,1,99,Urban,HR Executive,38918,1 +64681,Other,54,PhD,15,80,71,61,0,5.0,1,35,Urban,Software Engineer,123745,1 +64682,Male,30,High School,5,26,4,13,27,1.0,7,93,Urban,Data Analyst,108314,0 +64683,Male,33,Masters,4,87,44,30,96,1.0,5,85,Urban,Software Engineer,139550,1 +64684,Male,27,Masters,9,80,14,86,34,9.0,5,92,Semi-Urban,Software Engineer,112748,1 +64685,Female,59,Masters,6,48,99,4,26,6.0,1,66,Urban,Software Engineer,85191,0 +64686,Other,48,Bachelors,15,9,73,52,77,4.0,5,74,Urban,Software Engineer,112106,0 +64687,Male,33,Masters,9,47,60,1,22,4.0,1,98,Semi-Urban,HR Executive,139842,0 +64688,Female,52,Bachelors,19,7,18,65,9,5.0,7,32,Urban,Data Analyst,71842,0 +64689,Female,24,Bachelors,1,3,62,24,68,3.0,5,12,Urban,ML Engineer,140274,0 +64690,Female,25,Bachelors,16,99,96,19,47,9.0,3,2,Urban,Data Analyst,138155,0 +64691,Female,39,Bachelors,17,99,92,88,58,5.0,5,71,Urban,Software Engineer,42777,1 +64692,Male,53,Bachelors,9,32,95,33,31,1.0,0,47,Urban,Manager,112583,0 +64693,Female,57,PhD,18,26,52,38,45,5.0,0,16,Rural,Data Analyst,149744,0 +64694,Male,23,Diploma,7,12,30,1,34,5.0,1,44,Rural,HR Executive,86827,0 +64695,Female,48,PhD,18,54,44,31,11,9.0,2,39,Urban,Manager,64026,0 +64696,Male,51,Diploma,18,76,71,42,96,3.0,7,66,Urban,Software Engineer,97648,1 +64697,Female,32,Masters,0,77,97,46,66,8.0,6,30,Urban,Data Analyst,57980,1 +64698,Female,45,Bachelors,4,57,81,10,74,5.0,4,78,Rural,Data Analyst,63922,0 +64699,Female,58,Diploma,7,45,41,54,49,5.0,3,82,Rural,Software Engineer,30347,0 +64700,Male,54,Bachelors,13,62,4,16,3,4.0,0,37,Semi-Urban,Manager,136444,0 +64701,Female,48,Diploma,14,51,2,8,77,6.0,5,21,Semi-Urban,HR Executive,67163,0 +64702,Female,51,Bachelors,2,6,33,24,6,4.0,3,59,Urban,Software Engineer,40113,0 +64703,Female,36,High School,18,81,88,22,0,6.0,3,38,Urban,Data Analyst,29451,0 +64704,Other,35,Diploma,3,90,4,84,74,6.0,3,68,Semi-Urban,Data Analyst,146649,1 +64705,Male,26,High School,12,2,61,97,70,9.0,7,66,Urban,Manager,104130,0 +64706,Female,22,Masters,19,69,34,36,64,0.0,2,23,Urban,HR Executive,87762,0 +64707,Male,21,High School,6,97,86,6,63,6.0,1,83,Urban,Data Analyst,67690,1 +64708,Male,58,Diploma,14,13,85,78,78,8.0,4,89,Urban,Software Engineer,101658,1 +64709,Female,46,High School,6,68,75,12,45,9.0,1,90,Urban,Manager,73384,1 +64710,Female,54,Diploma,12,15,55,68,6,4.0,0,49,Urban,Software Engineer,31159,0 +64711,Male,39,Bachelors,4,30,21,82,85,5.0,2,34,Semi-Urban,Manager,115969,0 +64712,Female,38,Bachelors,2,81,89,85,81,5.0,4,55,Semi-Urban,HR Executive,99317,1 +64713,Male,54,High School,17,58,57,97,84,4.0,7,2,Semi-Urban,ML Engineer,87383,0 +64714,Male,32,Bachelors,5,39,32,20,45,2.0,4,47,Urban,HR Executive,76449,0 +64715,Female,38,High School,9,28,43,54,67,7.0,5,69,Semi-Urban,HR Executive,58113,0 +64716,Male,25,Bachelors,11,10,45,29,74,8.0,3,78,Urban,Manager,82396,0 +64717,Male,44,Bachelors,17,86,23,53,43,6.0,5,71,Urban,HR Executive,107878,0 +64718,Male,35,Diploma,15,45,79,17,87,9.0,6,22,Semi-Urban,Data Analyst,63458,0 +64719,Female,21,Diploma,10,76,57,67,99,4.0,3,44,Urban,Software Engineer,138486,1 +64720,Male,54,Masters,19,1,12,91,40,6.0,6,11,Urban,ML Engineer,79600,0 +64721,Male,45,Bachelors,16,48,55,92,51,6.0,1,10,Urban,Data Analyst,75294,0 +64722,Male,23,Masters,13,95,43,34,78,0.0,7,29,Semi-Urban,Manager,84683,0 +64723,Female,30,Bachelors,4,88,88,62,22,4.0,1,26,Semi-Urban,Manager,74030,1 +64724,Male,58,Bachelors,13,38,32,42,9,9.0,2,91,Rural,Manager,141144,0 +64725,Male,44,High School,11,78,97,0,23,9.0,5,84,Urban,Data Analyst,78241,1 +64726,Male,42,Masters,5,34,26,26,18,8.0,1,66,Semi-Urban,Data Analyst,50277,0 +64727,Male,46,Diploma,4,80,0,36,29,4.0,7,78,Urban,ML Engineer,56923,0 +64728,Male,36,Bachelors,9,50,25,49,10,9.0,2,98,Rural,Manager,123000,0 +64729,Male,41,Bachelors,15,35,48,56,49,4.0,3,74,Urban,Data Analyst,111645,0 +64730,Male,58,Diploma,18,93,77,9,38,8.0,3,9,Rural,HR Executive,32345,0 +64731,Male,48,Bachelors,15,2,85,80,14,4.0,0,7,Urban,Software Engineer,146461,0 +64732,Male,55,Masters,9,68,74,84,79,8.0,3,62,Semi-Urban,Data Analyst,91651,1 +64733,Male,49,Bachelors,11,99,21,10,94,8.0,6,16,Urban,Software Engineer,48802,0 +64734,Male,59,Masters,12,24,1,54,23,1.0,5,56,Rural,Data Analyst,73695,0 +64735,Female,55,High School,11,44,66,89,60,2.0,1,91,Semi-Urban,ML Engineer,62469,1 +64736,Female,33,Diploma,19,85,66,46,63,2.0,2,26,Urban,Data Analyst,63772,0 +64737,Male,24,High School,14,64,55,37,27,4.0,2,87,Semi-Urban,HR Executive,113534,1 +64738,Male,22,Bachelors,11,51,17,68,16,1.0,0,46,Urban,Data Analyst,59093,0 +64739,Female,37,Bachelors,4,80,45,38,29,3.0,7,42,Urban,HR Executive,37422,0 +64740,Female,37,Bachelors,12,18,7,29,89,9.0,7,94,Urban,Software Engineer,36021,0 +64741,Female,48,High School,14,3,1,63,0,5.0,3,21,Urban,Data Analyst,93204,0 +64742,Male,22,Masters,16,44,38,2,40,3.0,2,30,Urban,Software Engineer,129581,0 +64743,Male,34,Diploma,16,22,84,29,54,3.0,4,30,Urban,Data Analyst,44820,0 +64744,Male,45,Bachelors,11,69,65,54,22,9.0,0,14,Semi-Urban,Manager,99755,0 +64745,Male,23,Diploma,7,40,24,54,35,3.0,2,44,Urban,HR Executive,74533,0 +64746,Male,34,Masters,6,30,66,95,36,9.0,2,74,Urban,ML Engineer,52685,1 +64747,Female,56,Masters,11,11,34,92,3,2.0,6,8,Urban,ML Engineer,94565,0 +64748,Male,44,Bachelors,10,13,96,24,19,7.0,2,52,Urban,Software Engineer,105332,0 +64749,Male,56,Masters,3,94,91,18,47,4.0,5,1,Semi-Urban,HR Executive,117025,0 +64750,Female,31,Diploma,8,76,19,72,95,2.0,3,21,Urban,ML Engineer,123562,0 +64751,Male,46,Diploma,11,7,74,46,37,8.0,0,67,Urban,Manager,124233,0 +64752,Male,25,Diploma,17,25,1,7,87,5.0,6,5,Semi-Urban,ML Engineer,72945,0 +64753,Female,27,Diploma,2,72,14,76,46,6.0,7,0,Rural,Manager,48463,0 +64754,Female,32,Masters,19,25,99,82,59,2.0,6,58,Urban,ML Engineer,25278,1 +64755,Female,52,Masters,19,98,66,83,67,9.0,1,50,Urban,Manager,116357,1 +64756,Male,21,Bachelors,14,89,38,18,50,6.0,5,76,Urban,Data Analyst,82896,0 +64757,Male,24,Bachelors,1,13,64,61,48,8.0,2,32,Semi-Urban,Manager,93483,0 +64758,Male,21,Bachelors,6,76,46,28,36,4.0,6,95,Urban,HR Executive,136427,1 +64759,Female,45,Bachelors,4,76,81,67,91,8.0,5,85,Rural,Software Engineer,82088,1 +64760,Female,22,Bachelors,16,53,72,81,5,2.0,0,65,Urban,ML Engineer,65695,1 +64761,Male,55,Bachelors,10,33,11,97,46,3.0,2,7,Semi-Urban,Software Engineer,67164,0 +64762,Female,21,Bachelors,18,11,90,84,23,9.0,2,69,Urban,HR Executive,117900,1 +64763,Female,39,Bachelors,6,96,33,56,40,0.0,4,2,Rural,Data Analyst,62228,0 +64764,Male,44,Bachelors,3,15,46,67,47,7.0,1,27,Rural,HR Executive,54528,0 +64765,Male,22,Diploma,4,44,51,43,27,7.0,4,23,Urban,Data Analyst,77901,0 +64766,Female,35,Bachelors,1,35,44,0,4,3.0,2,99,Rural,HR Executive,117462,0 +64767,Male,36,Bachelors,7,75,14,19,54,1.0,7,47,Urban,ML Engineer,125433,0 +64768,Female,25,High School,14,87,54,58,18,6.0,0,78,Urban,HR Executive,118411,1 +64769,Male,45,Bachelors,13,20,12,25,28,5.0,1,85,Urban,Software Engineer,129873,0 +64770,Male,34,Masters,7,1,74,48,1,8.0,6,47,Urban,Data Analyst,98424,0 +64771,Female,57,High School,16,39,65,64,62,0.0,3,93,Urban,Manager,91260,1 +64772,Female,56,Diploma,12,46,68,96,54,6.0,7,97,Urban,ML Engineer,127724,1 +64773,Male,54,Masters,0,18,24,97,44,2.0,0,20,Urban,Manager,115810,0 +64774,Female,37,Diploma,16,95,27,12,43,7.0,7,44,Urban,Manager,104769,0 +64775,Female,59,High School,9,74,9,92,7,3.0,5,78,Semi-Urban,Data Analyst,109328,1 +64776,Male,59,Diploma,10,88,21,60,99,5.0,6,10,Semi-Urban,Data Analyst,82182,0 +64777,Other,52,High School,7,44,28,94,48,6.0,0,31,Rural,Software Engineer,74299,0 +64778,Male,56,High School,13,11,68,50,64,8.0,6,74,Urban,Software Engineer,74115,0 +64779,Female,28,Bachelors,14,80,28,89,7,2.0,1,61,Semi-Urban,Manager,46891,1 +64780,Male,34,Bachelors,9,21,0,38,98,2.0,5,55,Urban,Data Analyst,100190,0 +64781,Female,26,Bachelors,4,78,72,8,58,3.0,2,72,Semi-Urban,HR Executive,55899,0 +64782,Male,43,Masters,9,87,85,58,32,6.0,4,79,Urban,Manager,54570,1 +64783,Other,23,PhD,1,80,33,26,9,9.0,2,44,Semi-Urban,HR Executive,43423,0 +64784,Male,24,Bachelors,2,56,90,5,85,1.0,0,10,Urban,ML Engineer,130579,0 +64785,Male,39,Diploma,19,2,53,85,57,9.0,6,57,Rural,Manager,87060,0 +64786,Female,40,High School,2,3,57,71,68,3.0,0,19,Semi-Urban,Software Engineer,77843,0 +64787,Male,46,Bachelors,4,12,99,85,86,2.0,2,7,Urban,Software Engineer,131438,0 +64788,Female,28,Bachelors,9,84,23,96,71,0.0,5,68,Rural,Software Engineer,112584,1 +64789,Male,21,High School,13,72,48,59,5,7.0,5,82,Urban,Data Analyst,148134,1 +64790,Male,37,High School,12,36,23,9,97,2.0,1,8,Semi-Urban,ML Engineer,96797,0 +64791,Female,28,Masters,10,26,11,84,38,6.0,4,51,Semi-Urban,Manager,130903,0 +64792,Male,33,Bachelors,7,93,12,71,7,2.0,7,98,Urban,Data Analyst,135678,1 +64793,Female,34,Masters,12,99,64,59,64,5.0,0,23,Urban,ML Engineer,28465,1 +64794,Male,56,Diploma,18,11,85,91,49,5.0,3,50,Urban,Manager,121438,1 +64795,Male,38,PhD,3,54,21,81,50,1.0,5,78,Urban,Software Engineer,61429,0 +64796,Male,38,Bachelors,1,29,22,94,44,3.0,2,23,Urban,Software Engineer,21304,0 +64797,Male,48,High School,5,80,18,7,93,9.0,1,43,Rural,ML Engineer,46714,0 +64798,Female,36,Masters,14,1,18,73,92,6.0,7,14,Semi-Urban,HR Executive,93660,0 +64799,Male,37,High School,2,98,7,26,95,9.0,3,69,Semi-Urban,Software Engineer,34705,0 +64800,Male,21,Bachelors,15,48,29,73,68,9.0,5,39,Urban,Data Analyst,148932,0 +64801,Female,24,Bachelors,0,31,18,12,61,3.0,4,2,Urban,HR Executive,26187,0 +64802,Male,55,Bachelors,8,43,38,35,66,4.0,3,81,Semi-Urban,Software Engineer,102480,0 +64803,Female,49,Bachelors,6,48,41,3,11,7.0,4,27,Urban,Software Engineer,146386,0 +64804,Other,43,Masters,15,35,75,55,17,8.0,5,88,Semi-Urban,HR Executive,30572,1 +64805,Female,25,Diploma,3,10,9,58,17,4.0,6,0,Urban,ML Engineer,62907,0 +64806,Male,35,Bachelors,19,5,69,70,81,1.0,1,68,Urban,Software Engineer,96834,0 +64807,Female,37,Diploma,16,83,97,11,4,9.0,6,65,Urban,Data Analyst,87380,1 +64808,Male,22,Bachelors,7,37,2,71,97,5.0,6,19,Urban,Software Engineer,133676,0 +64809,Male,34,Diploma,8,77,2,94,74,0.0,7,89,Rural,HR Executive,133387,1 +64810,Other,36,PhD,18,38,74,48,93,0.0,2,26,Urban,Data Analyst,84064,0 +64811,Male,56,Bachelors,16,87,91,18,5,1.0,1,65,Rural,Data Analyst,110948,1 +64812,Female,58,Diploma,3,30,44,47,10,5.0,0,59,Urban,Manager,41560,0 +64813,Male,40,High School,11,57,47,91,28,1.0,5,16,Urban,Software Engineer,99818,0 +64814,Male,44,Masters,2,71,72,1,84,6.0,3,30,Semi-Urban,Data Analyst,48584,0 +64815,Male,36,Diploma,19,89,47,38,7,5.0,4,59,Urban,Data Analyst,143311,0 +64816,Female,57,Masters,7,96,71,66,64,9.0,0,31,Urban,Software Engineer,32740,1 +64817,Male,35,High School,7,57,73,82,98,5.0,3,87,Urban,HR Executive,41701,1 +64818,Male,44,High School,10,6,82,19,32,2.0,5,3,Semi-Urban,Data Analyst,149208,0 +64819,Male,34,Masters,16,90,19,97,9,8.0,0,31,Rural,Data Analyst,77799,1 +64820,Male,32,Masters,16,44,33,38,64,0.0,6,27,Urban,Data Analyst,96944,0 +64821,Male,41,High School,1,96,37,44,39,2.0,0,49,Urban,Manager,63670,0 +64822,Male,46,Bachelors,10,96,0,32,5,8.0,1,44,Semi-Urban,Software Engineer,133434,0 +64823,Male,45,Bachelors,19,16,15,98,57,2.0,5,81,Urban,Data Analyst,132568,0 +64824,Male,22,Bachelors,3,87,67,11,9,4.0,3,99,Urban,Data Analyst,37821,1 +64825,Male,41,Masters,7,80,6,99,48,7.0,4,64,Urban,Data Analyst,145956,1 +64826,Male,28,Masters,18,94,91,97,75,8.0,5,71,Urban,Manager,59238,1 +64827,Female,35,Bachelors,5,65,40,39,48,7.0,3,63,Semi-Urban,Manager,43792,0 +64828,Male,30,Masters,19,29,76,13,31,3.0,2,62,Semi-Urban,ML Engineer,36069,0 +64829,Male,56,Masters,8,68,34,19,92,0.0,1,49,Semi-Urban,Software Engineer,20505,0 +64830,Female,51,High School,8,51,2,58,90,6.0,5,61,Semi-Urban,Data Analyst,120995,0 +64831,Male,55,Masters,0,33,22,48,12,6.0,1,59,Semi-Urban,Manager,124931,0 +64832,Female,46,PhD,18,76,44,11,35,0.0,6,37,Urban,ML Engineer,69738,0 +64833,Male,37,Diploma,6,4,70,53,50,5.0,0,74,Urban,ML Engineer,35070,0 +64834,Male,39,Diploma,4,31,50,29,48,2.0,4,21,Urban,Software Engineer,100901,0 +64835,Male,24,Bachelors,9,22,5,44,83,8.0,6,52,Semi-Urban,Data Analyst,113073,0 +64836,Male,42,Bachelors,14,70,27,29,8,6.0,4,82,Urban,HR Executive,120327,0 +64837,Male,45,Bachelors,3,49,42,18,6,2.0,2,49,Urban,ML Engineer,61476,0 +64838,Male,45,Bachelors,4,16,91,88,22,6.0,1,43,Urban,Manager,60307,1 +64839,Female,23,High School,14,41,71,77,28,3.0,5,22,Semi-Urban,HR Executive,43681,0 +64840,Male,32,Diploma,1,75,15,89,81,0.0,4,90,Rural,Manager,120935,1 +64841,Female,31,Masters,1,34,33,5,63,6.0,0,41,Semi-Urban,Software Engineer,102145,0 +64842,Female,53,High School,10,20,71,42,91,3.0,6,23,Rural,Data Analyst,132918,0 +64843,Female,53,Diploma,1,3,87,43,80,6.0,1,66,Semi-Urban,Software Engineer,58932,0 +64844,Male,54,PhD,2,27,98,1,12,1.0,1,26,Urban,Software Engineer,35091,0 +64845,Male,27,High School,17,12,81,72,51,8.0,6,3,Semi-Urban,HR Executive,46506,0 +64846,Female,48,Bachelors,16,25,65,19,34,8.0,2,74,Semi-Urban,Manager,110733,0 +64847,Female,21,Bachelors,19,3,61,0,52,8.0,2,35,Rural,Data Analyst,131158,0 +64848,Female,26,High School,17,63,84,93,74,6.0,7,88,Semi-Urban,Manager,146253,1 +64849,Male,53,PhD,17,14,42,95,48,6.0,0,37,Urban,ML Engineer,83204,0 +64850,Male,51,PhD,2,23,46,95,84,1.0,1,12,Rural,ML Engineer,101479,0 +64851,Female,54,Masters,17,14,45,97,22,1.0,0,49,Urban,Software Engineer,123709,0 +64852,Other,33,Diploma,0,14,42,62,86,3.0,5,58,Semi-Urban,Manager,112592,0 +64853,Male,55,Bachelors,13,50,42,72,10,4.0,5,34,Urban,HR Executive,51634,0 +64854,Male,44,High School,0,97,77,6,93,2.0,6,22,Semi-Urban,ML Engineer,137320,0 +64855,Other,55,PhD,9,59,32,72,92,0.0,1,33,Urban,HR Executive,136614,0 +64856,Male,51,Bachelors,16,59,28,31,56,9.0,0,85,Urban,Manager,87202,0 +64857,Female,51,Masters,17,36,11,3,9,4.0,5,55,Urban,Manager,72810,0 +64858,Female,41,Bachelors,1,3,44,70,5,7.0,4,45,Rural,HR Executive,119185,0 +64859,Female,57,Masters,11,36,58,80,7,0.0,6,74,Urban,Software Engineer,99878,1 +64860,Female,53,Masters,8,56,87,33,15,3.0,7,11,Rural,Data Analyst,134162,0 +64861,Male,42,Bachelors,1,36,4,30,33,1.0,2,49,Urban,ML Engineer,110043,0 +64862,Male,56,Bachelors,0,12,44,60,88,2.0,1,76,Semi-Urban,Manager,82986,0 +64863,Female,45,Diploma,5,90,7,28,90,5.0,4,63,Rural,Software Engineer,133074,0 +64864,Female,53,Diploma,14,97,63,66,12,4.0,5,59,Rural,Software Engineer,144644,1 +64865,Male,45,High School,11,98,73,11,79,3.0,3,81,Urban,Data Analyst,89182,1 +64866,Male,38,Diploma,15,44,78,1,29,9.0,4,23,Urban,Data Analyst,51901,0 +64867,Male,53,Diploma,5,33,4,22,62,1.0,6,64,Urban,Data Analyst,94698,0 +64868,Female,30,Diploma,10,21,72,4,94,5.0,0,55,Semi-Urban,HR Executive,31634,0 +64869,Male,44,Bachelors,16,37,52,95,13,6.0,5,76,Urban,ML Engineer,60679,1 +64870,Male,44,Bachelors,6,97,9,7,8,0.0,3,59,Urban,Data Analyst,85709,0 +64871,Male,29,Bachelors,8,2,68,63,37,4.0,4,78,Urban,ML Engineer,25945,0 +64872,Female,36,Bachelors,19,85,30,52,90,3.0,3,9,Rural,ML Engineer,55377,0 +64873,Male,33,Bachelors,2,96,29,97,67,9.0,4,8,Semi-Urban,ML Engineer,132801,0 +64874,Male,55,Diploma,19,37,94,73,33,4.0,3,26,Urban,Software Engineer,116895,0 +64875,Male,54,Bachelors,17,99,83,31,64,3.0,2,84,Urban,ML Engineer,70630,1 +64876,Male,36,Diploma,8,56,44,1,42,9.0,0,86,Semi-Urban,HR Executive,60424,0 +64877,Male,34,Bachelors,3,12,84,38,97,6.0,0,38,Rural,Manager,74031,0 +64878,Female,53,Bachelors,8,20,35,14,66,9.0,1,30,Urban,Manager,31078,0 +64879,Female,30,Diploma,5,84,97,8,66,0.0,3,15,Urban,Data Analyst,77226,0 +64880,Female,40,Masters,14,14,2,23,69,4.0,6,70,Urban,Software Engineer,38971,0 +64881,Male,58,Bachelors,19,68,2,21,55,4.0,2,5,Rural,Manager,21201,0 +64882,Male,31,Bachelors,14,90,31,94,13,2.0,1,46,Rural,Software Engineer,65462,1 +64883,Female,38,High School,8,49,21,48,78,9.0,7,15,Semi-Urban,HR Executive,42888,0 +64884,Male,32,Masters,17,56,43,17,83,5.0,1,67,Urban,HR Executive,102605,0 +64885,Female,21,Bachelors,9,71,56,16,26,9.0,7,4,Urban,Manager,140969,0 +64886,Female,25,Diploma,16,8,4,85,0,6.0,4,54,Rural,Manager,57775,0 +64887,Male,36,Bachelors,17,16,93,31,2,4.0,3,48,Urban,Manager,93574,0 +64888,Male,29,Diploma,8,3,58,45,57,1.0,3,2,Rural,Software Engineer,120012,0 +64889,Male,21,High School,18,80,25,40,63,7.0,5,45,Semi-Urban,Data Analyst,125817,0 +64890,Male,22,Bachelors,2,26,62,65,89,1.0,2,68,Urban,ML Engineer,50437,0 +64891,Female,27,Bachelors,2,33,3,47,48,9.0,2,18,Rural,HR Executive,59747,0 +64892,Male,42,Diploma,19,27,10,36,74,1.0,0,25,Urban,Software Engineer,137436,0 +64893,Male,43,Bachelors,9,20,94,17,48,7.0,2,19,Rural,Software Engineer,71892,0 +64894,Female,48,Bachelors,14,95,7,17,48,8.0,3,62,Urban,Manager,36678,0 +64895,Male,48,High School,8,92,74,10,64,3.0,1,50,Urban,HR Executive,60802,0 +64896,Female,44,Bachelors,19,1,47,16,23,5.0,3,76,Urban,Software Engineer,25827,0 +64897,Male,32,Diploma,8,15,71,9,8,1.0,0,8,Rural,Software Engineer,82370,0 +64898,Female,48,Bachelors,0,46,69,65,23,4.0,2,22,Rural,Software Engineer,103183,0 +64899,Male,22,High School,13,69,36,21,37,1.0,5,36,Urban,Data Analyst,99136,0 +64900,Male,46,Masters,6,26,98,32,24,7.0,4,85,Urban,Manager,120348,1 +64901,Male,26,High School,19,72,33,53,14,6.0,0,3,Semi-Urban,Software Engineer,69245,0 +64902,Male,50,Bachelors,13,67,90,23,58,1.0,4,17,Urban,Software Engineer,77615,0 +64903,Male,57,Masters,16,51,78,96,46,1.0,0,11,Semi-Urban,Manager,66901,1 +64904,Male,26,Bachelors,4,39,50,94,43,0.0,4,64,Rural,HR Executive,141703,1 +64905,Female,54,Bachelors,17,86,26,52,90,3.0,0,73,Semi-Urban,HR Executive,61410,0 +64906,Female,23,Masters,15,46,59,83,56,0.0,6,62,Urban,Manager,146407,1 +64907,Female,58,Bachelors,14,89,76,7,61,4.0,5,14,Urban,Software Engineer,102722,0 +64908,Female,43,Bachelors,12,10,74,64,43,3.0,6,62,Semi-Urban,HR Executive,94484,0 +64909,Male,51,Bachelors,14,85,88,82,9,6.0,6,34,Urban,Manager,124212,1 +64910,Male,30,Diploma,6,36,71,41,88,2.0,3,32,Rural,Data Analyst,79221,0 +64911,Male,44,Bachelors,17,45,43,79,95,1.0,1,64,Semi-Urban,Manager,92755,0 +64912,Male,27,Diploma,5,80,11,43,9,7.0,6,41,Urban,Software Engineer,69775,0 +64913,Female,25,Bachelors,4,67,92,71,83,7.0,3,97,Semi-Urban,Manager,105318,1 +64914,Female,35,Masters,8,76,35,66,18,2.0,7,43,Semi-Urban,ML Engineer,22050,0 +64915,Female,38,High School,3,97,10,34,90,5.0,5,90,Semi-Urban,Data Analyst,34171,0 +64916,Female,43,Bachelors,9,70,85,99,99,5.0,4,32,Urban,Manager,41892,1 +64917,Male,39,Masters,4,19,67,18,95,7.0,2,35,Semi-Urban,Software Engineer,144001,0 +64918,Other,23,Bachelors,16,16,53,48,32,3.0,5,4,Rural,ML Engineer,75894,0 +64919,Male,27,Diploma,4,75,44,50,84,3.0,4,86,Urban,Data Analyst,40665,1 +64920,Female,58,Bachelors,9,42,58,63,4,4.0,7,4,Urban,HR Executive,118075,0 +64921,Male,50,Diploma,2,80,24,50,42,6.0,6,46,Urban,Data Analyst,85021,0 +64922,Male,49,Bachelors,5,65,34,34,12,3.0,4,70,Rural,Data Analyst,122440,0 +64923,Male,34,PhD,15,55,7,60,5,1.0,7,64,Semi-Urban,Software Engineer,54303,0 +64924,Male,26,Diploma,9,30,65,75,71,3.0,7,19,Rural,Manager,56951,0 +64925,Male,35,High School,14,65,39,66,35,4.0,0,82,Semi-Urban,Software Engineer,20647,1 +64926,Male,50,Masters,13,57,85,40,47,3.0,5,24,Urban,ML Engineer,38375,0 +64927,Female,51,Masters,2,15,62,51,24,0.0,0,15,Rural,Software Engineer,130595,0 +64928,Female,33,Masters,8,65,21,5,9,1.0,6,62,Semi-Urban,HR Executive,62147,0 +64929,Male,31,Bachelors,10,6,78,28,37,6.0,4,99,Rural,Software Engineer,71635,0 +64930,Other,29,Bachelors,10,26,16,58,3,1.0,0,4,Urban,HR Executive,110168,0 +64931,Female,22,Bachelors,0,44,82,73,82,6.0,6,16,Urban,Data Analyst,62030,0 +64932,Male,23,Diploma,10,61,86,77,65,2.0,6,12,Urban,Data Analyst,138178,1 +64933,Male,56,Masters,13,4,30,8,48,9.0,5,50,Rural,Manager,74107,0 +64934,Other,48,Diploma,10,69,83,35,93,6.0,3,56,Rural,Manager,95209,1 +64935,Female,59,High School,16,18,35,4,75,7.0,1,64,Urban,Manager,100195,0 +64936,Male,40,Diploma,18,26,95,41,70,3.0,0,26,Semi-Urban,HR Executive,87274,0 +64937,Male,38,Diploma,3,6,60,11,80,0.0,7,77,Urban,Data Analyst,42747,0 +64938,Female,29,High School,2,83,89,87,61,4.0,4,79,Urban,Data Analyst,143164,1 +64939,Male,41,High School,18,44,34,5,26,6.0,4,45,Semi-Urban,HR Executive,134567,0 +64940,Male,38,Diploma,12,62,6,62,24,1.0,1,97,Semi-Urban,Data Analyst,115364,0 +64941,Male,46,Masters,2,0,12,23,43,1.0,6,3,Semi-Urban,Data Analyst,139078,0 +64942,Female,48,Masters,14,99,87,46,14,8.0,7,95,Urban,HR Executive,111347,1 +64943,Male,22,Bachelors,17,0,28,8,27,0.0,5,64,Urban,ML Engineer,101231,0 +64944,Female,44,Masters,13,12,86,25,54,6.0,0,65,Urban,HR Executive,73656,0 +64945,Female,45,Bachelors,17,59,76,77,35,2.0,2,74,Urban,HR Executive,50023,1 +64946,Male,28,High School,18,16,91,53,27,4.0,1,76,Semi-Urban,Data Analyst,113546,1 +64947,Male,51,Masters,7,52,46,54,0,7.0,7,9,Urban,Software Engineer,102408,0 +64948,Female,41,High School,7,9,57,28,48,4.0,0,50,Semi-Urban,Data Analyst,46798,0 +64949,Female,54,Bachelors,1,30,81,24,70,3.0,3,90,Semi-Urban,HR Executive,26377,0 +64950,Female,37,Bachelors,11,36,67,94,6,5.0,1,69,Rural,Manager,90107,1 +64951,Male,32,Bachelors,19,6,16,20,29,7.0,1,3,Rural,Software Engineer,113740,0 +64952,Male,41,Bachelors,4,87,4,41,62,9.0,1,61,Semi-Urban,HR Executive,129362,0 +64953,Male,56,Bachelors,13,9,57,29,26,4.0,5,22,Rural,Data Analyst,93988,0 +64954,Female,58,PhD,11,74,91,49,9,1.0,4,37,Urban,ML Engineer,63601,1 +64955,Male,32,Bachelors,11,91,63,80,78,1.0,5,1,Urban,ML Engineer,34358,1 +64956,Male,50,Bachelors,15,43,98,10,5,3.0,5,22,Semi-Urban,ML Engineer,68446,0 +64957,Male,23,Masters,6,59,9,70,60,8.0,4,20,Urban,ML Engineer,71182,0 +64958,Male,37,Masters,0,96,10,35,54,4.0,7,90,Semi-Urban,Data Analyst,131616,0 +64959,Other,59,Diploma,4,50,77,26,93,8.0,0,98,Urban,Manager,103698,1 +64960,Male,37,Bachelors,12,93,66,44,75,2.0,5,32,Urban,Software Engineer,85070,1 +64961,Male,49,High School,6,80,96,47,98,1.0,0,48,Semi-Urban,ML Engineer,82576,1 +64962,Female,42,Bachelors,10,8,12,76,24,9.0,3,7,Urban,Software Engineer,121798,0 +64963,Female,56,Masters,19,27,87,61,45,8.0,3,26,Urban,Software Engineer,20834,0 +64964,Male,49,Bachelors,5,46,85,16,19,8.0,0,95,Urban,HR Executive,122867,1 +64965,Female,28,Bachelors,11,28,4,18,21,2.0,2,84,Urban,HR Executive,120687,0 +64966,Male,47,Masters,19,98,62,37,4,3.0,0,81,Rural,ML Engineer,46635,1 +64967,Female,47,Masters,13,82,22,80,36,7.0,6,49,Rural,ML Engineer,35783,0 +64968,Male,24,Diploma,2,98,50,2,93,1.0,5,77,Rural,Data Analyst,62392,0 +64969,Male,33,Diploma,1,35,8,2,53,7.0,6,70,Rural,Manager,99405,0 +64970,Male,58,Diploma,3,44,83,10,6,0.0,5,34,Urban,ML Engineer,79223,0 +64971,Female,37,Masters,7,78,96,7,76,0.0,3,33,Semi-Urban,Data Analyst,39235,0 +64972,Male,57,Bachelors,0,42,16,20,69,7.0,3,60,Semi-Urban,HR Executive,64746,0 +64973,Male,26,PhD,11,7,31,15,23,4.0,4,32,Urban,Manager,31609,0 +64974,Male,41,Diploma,9,26,63,93,94,5.0,1,19,Semi-Urban,ML Engineer,34656,0 +64975,Male,39,Diploma,3,56,52,88,79,4.0,6,72,Urban,Software Engineer,32621,1 +64976,Male,41,Bachelors,10,7,63,52,19,8.0,1,50,Semi-Urban,HR Executive,53507,0 +64977,Male,21,Masters,17,48,74,68,41,5.0,0,36,Semi-Urban,Manager,82456,0 +64978,Male,51,Bachelors,12,93,46,99,18,7.0,1,75,Semi-Urban,Manager,74383,1 +64979,Male,46,Bachelors,19,25,85,1,46,6.0,6,21,Urban,Data Analyst,61341,0 +64980,Male,41,High School,15,95,59,78,25,7.0,6,39,Semi-Urban,Data Analyst,145234,1 +64981,Female,24,Bachelors,5,7,34,9,86,1.0,5,73,Semi-Urban,Manager,114553,0 +64982,Male,27,Diploma,8,17,21,8,64,4.0,0,91,Urban,ML Engineer,29930,0 +64983,Male,54,High School,19,79,12,27,16,3.0,5,19,Urban,Manager,96985,0 +64984,Female,54,PhD,19,32,77,85,57,2.0,3,55,Urban,Data Analyst,30087,1 +64985,Other,34,Masters,5,96,33,23,73,5.0,0,77,Urban,Data Analyst,87495,0 +64986,Male,34,PhD,7,41,35,70,93,1.0,6,62,Semi-Urban,Software Engineer,67249,0 +64987,Male,35,Masters,12,46,48,98,90,7.0,2,43,Semi-Urban,Manager,119571,1 +64988,Female,55,PhD,2,61,60,45,41,5.0,6,9,Rural,Manager,24680,0 +64989,Male,34,High School,1,93,9,88,60,5.0,3,83,Semi-Urban,HR Executive,128617,1 +64990,Male,57,Masters,18,36,89,98,13,8.0,6,82,Urban,Manager,26712,1 +64991,Male,59,Diploma,3,71,39,32,6,3.0,1,91,Urban,HR Executive,70391,0 +64992,Other,59,Bachelors,1,44,50,28,8,6.0,7,42,Urban,Manager,144037,0 +64993,Female,36,Bachelors,7,71,32,16,4,1.0,5,56,Urban,HR Executive,24547,0 +64994,Male,53,Masters,5,15,6,55,76,2.0,6,24,Urban,ML Engineer,51824,0 +64995,Female,36,Bachelors,2,70,41,10,2,0.0,6,9,Semi-Urban,Software Engineer,24837,0 +64996,Male,24,Diploma,17,47,81,75,7,6.0,2,69,Urban,Software Engineer,133949,1 +64997,Male,24,Bachelors,11,89,54,87,98,2.0,1,13,Urban,Data Analyst,47408,1 +64998,Female,26,Diploma,6,43,99,56,59,4.0,7,64,Semi-Urban,Manager,118390,1 +64999,Male,45,High School,19,51,63,82,77,3.0,4,51,Semi-Urban,ML Engineer,104974,1 +65000,Male,55,Diploma,18,9,97,67,26,4.0,0,56,Semi-Urban,Data Analyst,46838,0 +65001,Male,52,High School,0,28,75,64,42,3.0,4,3,Urban,Data Analyst,121868,0 +65002,Male,51,High School,13,98,81,40,32,9.0,5,17,Urban,ML Engineer,106495,1 +65003,Female,42,Bachelors,19,23,47,4,25,0.0,1,91,Rural,Software Engineer,96006,0 +65004,Male,37,Masters,9,88,34,39,81,2.0,5,0,Rural,Manager,97055,0 +65005,Female,38,Bachelors,5,87,57,45,51,5.0,0,12,Urban,Manager,90261,0 +65006,Male,41,Bachelors,16,40,5,97,4,9.0,2,7,Urban,Software Engineer,140488,0 +65007,Male,35,Bachelors,13,8,92,47,85,8.0,6,43,Rural,HR Executive,52926,0 +65008,Male,39,Diploma,0,36,66,86,40,3.0,1,49,Rural,HR Executive,146940,1 +65009,Other,38,High School,11,7,32,94,3,9.0,0,55,Semi-Urban,Manager,35258,0 +65010,Male,25,Bachelors,13,74,92,73,98,4.0,1,22,Urban,ML Engineer,45650,1 +65011,Female,30,PhD,6,71,60,92,52,6.0,7,67,Semi-Urban,Manager,87021,1 +65012,Male,22,Diploma,6,49,72,15,69,4.0,1,92,Rural,ML Engineer,110168,0 +65013,Other,38,Diploma,16,72,77,96,42,0.0,3,14,Urban,ML Engineer,35402,1 +65014,Male,36,Masters,8,48,64,5,41,7.0,6,12,Semi-Urban,Software Engineer,55687,0 +65015,Female,53,Bachelors,17,27,66,27,72,5.0,2,89,Semi-Urban,ML Engineer,76572,0 +65016,Female,32,Bachelors,0,68,55,53,21,5.0,7,65,Rural,ML Engineer,132358,1 +65017,Female,35,Bachelors,10,27,29,57,77,0.0,5,26,Urban,Data Analyst,38665,0 +65018,Female,35,Diploma,15,46,28,3,61,9.0,0,41,Urban,ML Engineer,96015,0 +65019,Female,51,Bachelors,16,43,8,66,68,4.0,3,87,Rural,HR Executive,88103,0 +65020,Female,31,Masters,19,89,86,93,26,0.0,5,92,Rural,Software Engineer,34995,1 +65021,Male,25,Masters,14,1,46,54,34,7.0,2,25,Semi-Urban,Data Analyst,53863,0 +65022,Male,33,Bachelors,17,1,68,32,86,9.0,7,26,Urban,ML Engineer,105108,0 +65023,Male,32,PhD,12,89,77,45,94,3.0,0,64,Urban,Software Engineer,62353,1 +65024,Female,26,Bachelors,1,53,15,17,70,6.0,4,22,Rural,Data Analyst,142794,0 +65025,Male,34,Bachelors,7,79,12,27,87,2.0,5,78,Urban,HR Executive,88532,0 +65026,Female,52,Masters,6,30,24,62,96,4.0,2,68,Semi-Urban,HR Executive,53553,0 +65027,Male,31,Bachelors,14,26,89,21,9,4.0,7,89,Urban,Software Engineer,114274,0 +65028,Female,59,Masters,10,85,51,16,33,3.0,4,65,Semi-Urban,Software Engineer,128260,0 +65029,Male,48,Diploma,10,25,94,89,90,5.0,2,17,Urban,Software Engineer,121841,0 +65030,Male,57,Bachelors,18,14,36,40,32,4.0,3,68,Rural,ML Engineer,107429,0 +65031,Male,46,Masters,12,16,61,90,20,5.0,1,8,Semi-Urban,HR Executive,48279,0 +65032,Male,40,Masters,11,73,45,14,47,2.0,4,97,Urban,Data Analyst,85970,0 +65033,Female,39,Bachelors,3,97,98,97,17,9.0,2,68,Semi-Urban,ML Engineer,107478,1 +65034,Male,26,Diploma,11,78,63,96,22,8.0,6,92,Urban,HR Executive,142551,1 +65035,Female,39,Diploma,18,92,85,66,90,2.0,6,60,Semi-Urban,Software Engineer,71393,1 +65036,Male,27,Masters,1,68,28,17,85,1.0,5,36,Semi-Urban,ML Engineer,92277,0 +65037,Female,22,Bachelors,10,83,51,6,57,0.0,4,11,Rural,Data Analyst,133476,0 +65038,Male,41,Diploma,15,26,24,47,37,1.0,6,77,Semi-Urban,Manager,50913,0 +65039,Male,43,Bachelors,11,35,66,90,17,7.0,0,37,Semi-Urban,Data Analyst,78455,0 +65040,Male,51,Masters,3,11,29,74,1,6.0,6,2,Rural,Data Analyst,106126,0 +65041,Female,24,Bachelors,7,33,35,14,60,3.0,6,49,Urban,ML Engineer,72593,0 +65042,Female,21,Bachelors,15,16,34,96,5,5.0,4,88,Urban,Data Analyst,64983,0 +65043,Male,43,Bachelors,17,9,23,95,21,4.0,3,9,Urban,Software Engineer,111191,0 +65044,Female,37,Bachelors,0,8,95,32,86,0.0,0,91,Urban,ML Engineer,68307,0 +65045,Male,59,Bachelors,13,64,80,42,29,2.0,4,79,Urban,Data Analyst,57008,1 +65046,Male,30,Bachelors,18,95,1,94,18,5.0,7,64,Semi-Urban,Data Analyst,40925,1 +65047,Male,25,High School,11,90,96,7,70,2.0,1,36,Urban,Data Analyst,143569,0 +65048,Male,55,Masters,15,39,27,23,84,4.0,6,84,Urban,HR Executive,23726,0 +65049,Male,48,Bachelors,9,65,59,64,20,5.0,0,99,Rural,HR Executive,115396,1 +65050,Male,54,Bachelors,19,28,66,90,73,9.0,1,10,Semi-Urban,Manager,133834,0 +65051,Male,48,Masters,6,29,6,19,76,4.0,3,50,Rural,HR Executive,119188,0 +65052,Female,33,Bachelors,2,19,40,84,81,6.0,4,36,Urban,HR Executive,108729,0 +65053,Male,47,Bachelors,3,44,1,67,49,2.0,3,88,Urban,Data Analyst,39423,0 +65054,Male,57,Bachelors,4,71,42,95,8,3.0,7,48,Rural,HR Executive,86559,1 +65055,Male,42,High School,7,28,82,44,41,0.0,1,94,Semi-Urban,HR Executive,131694,1 +65056,Male,45,Diploma,12,90,91,44,69,8.0,0,10,Rural,HR Executive,140458,1 +65057,Male,21,High School,5,24,84,35,73,6.0,1,74,Urban,HR Executive,28770,0 +65058,Male,27,Diploma,10,35,9,41,10,1.0,4,91,Urban,Software Engineer,126055,0 +65059,Male,37,Diploma,16,91,11,13,27,1.0,7,94,Urban,ML Engineer,135001,0 +65060,Male,54,Diploma,10,69,32,24,64,0.0,4,89,Urban,Manager,55486,0 +65061,Male,26,Bachelors,16,99,19,32,64,5.0,0,85,Semi-Urban,Software Engineer,106867,1 +65062,Male,26,Bachelors,2,96,65,11,1,7.0,4,62,Urban,Manager,133786,0 +65063,Female,44,Masters,7,77,68,59,45,3.0,7,93,Urban,HR Executive,94330,1 +65064,Male,46,High School,18,49,15,38,24,2.0,2,12,Urban,HR Executive,43593,0 +65065,Male,27,Masters,14,5,69,46,30,6.0,2,51,Semi-Urban,ML Engineer,23415,0 +65066,Female,42,Bachelors,7,31,34,26,26,8.0,4,94,Urban,Data Analyst,126820,0 +65067,Male,32,Masters,2,11,65,64,81,3.0,5,31,Urban,HR Executive,51615,0 +65068,Female,44,Diploma,0,64,75,18,99,7.0,1,58,Rural,ML Engineer,114899,0 +65069,Male,45,Masters,4,18,45,39,52,8.0,7,72,Urban,ML Engineer,144141,0 +65070,Female,36,Bachelors,11,73,10,81,76,0.0,3,15,Rural,Manager,90570,0 +65071,Male,37,Diploma,12,97,98,10,65,8.0,2,87,Urban,ML Engineer,36891,1 +65072,Male,40,Bachelors,16,43,30,84,46,9.0,5,21,Urban,Software Engineer,78263,0 +65073,Male,57,PhD,2,35,73,18,75,6.0,4,84,Urban,Data Analyst,133560,0 +65074,Male,54,PhD,19,23,59,90,85,5.0,5,64,Semi-Urban,Manager,39896,1 +65075,Female,48,Bachelors,17,67,60,69,64,1.0,5,99,Rural,Software Engineer,31488,1 +65076,Male,32,Bachelors,11,63,52,14,79,8.0,1,96,Semi-Urban,Manager,133940,0 +65077,Male,39,Masters,3,88,46,40,88,3.0,6,8,Semi-Urban,Manager,70611,0 +65078,Male,56,Bachelors,6,56,66,56,65,5.0,6,55,Semi-Urban,Manager,128232,0 +65079,Male,46,Bachelors,17,36,30,4,94,3.0,7,18,Urban,Software Engineer,135696,0 +65080,Female,29,Bachelors,0,73,37,38,24,9.0,1,75,Urban,HR Executive,32626,0 +65081,Male,26,High School,9,3,43,92,43,0.0,0,10,Urban,Software Engineer,128809,0 +65082,Female,56,Bachelors,3,40,55,62,19,0.0,7,23,Urban,Software Engineer,119425,0 +65083,Male,29,Diploma,7,77,43,40,1,8.0,2,95,Urban,Data Analyst,87240,1 +65084,Male,56,Diploma,10,86,54,80,50,9.0,7,25,Rural,Software Engineer,21257,1 +65085,Male,26,Bachelors,6,19,65,20,28,4.0,1,54,Semi-Urban,Software Engineer,148588,0 +65086,Male,43,Bachelors,5,49,38,11,11,8.0,3,92,Urban,ML Engineer,45402,0 +65087,Male,53,Bachelors,15,14,90,43,55,7.0,6,68,Semi-Urban,HR Executive,92158,0 +65088,Male,37,Masters,10,87,91,37,41,0.0,7,41,Urban,Software Engineer,53116,1 +65089,Other,50,Bachelors,17,64,42,36,8,4.0,3,91,Urban,Software Engineer,103937,0 +65090,Female,31,Bachelors,10,47,74,26,83,8.0,2,81,Urban,Manager,40453,0 +65091,Male,21,Diploma,7,5,51,48,58,9.0,5,13,Urban,Software Engineer,85714,0 +65092,Male,48,Bachelors,9,94,65,30,72,4.0,2,39,Urban,HR Executive,122726,0 +65093,Female,56,Bachelors,13,19,73,29,9,1.0,6,73,Urban,ML Engineer,110151,0 +65094,Female,58,Masters,6,62,19,11,61,2.0,4,37,Rural,Software Engineer,60598,0 +65095,Male,57,Diploma,13,46,92,69,49,5.0,1,46,Rural,HR Executive,100829,1 +65096,Male,35,Bachelors,11,61,16,40,83,5.0,0,14,Semi-Urban,Manager,21819,0 +65097,Female,49,Diploma,17,65,6,45,6,5.0,6,11,Semi-Urban,Software Engineer,69378,0 +65098,Male,39,Bachelors,18,99,57,4,75,9.0,5,12,Rural,HR Executive,66384,0 +65099,Male,49,High School,6,41,4,46,36,6.0,0,75,Rural,Data Analyst,25611,0 +65100,Male,48,Masters,6,73,82,1,16,2.0,2,68,Semi-Urban,Data Analyst,123963,0 +65101,Male,37,Bachelors,18,28,10,36,18,9.0,5,26,Urban,Software Engineer,37679,0 +65102,Male,52,Bachelors,5,88,57,61,72,8.0,7,80,Semi-Urban,ML Engineer,90216,1 +65103,Male,41,Bachelors,16,86,92,45,86,1.0,4,87,Urban,ML Engineer,43865,1 +65104,Female,36,Bachelors,13,62,33,44,52,5.0,2,92,Urban,ML Engineer,71929,0 +65105,Female,21,Bachelors,2,30,44,96,63,4.0,4,64,Urban,Manager,140582,0 +65106,Male,33,Bachelors,17,84,34,26,96,7.0,2,49,Urban,Software Engineer,23947,0 +65107,Male,36,Bachelors,16,22,65,42,71,2.0,5,74,Rural,ML Engineer,54103,0 +65108,Female,47,PhD,15,70,78,0,36,7.0,1,9,Semi-Urban,Data Analyst,91685,0 +65109,Male,25,Bachelors,9,11,73,15,37,1.0,0,56,Rural,Manager,52212,0 +65110,Male,47,Masters,0,52,32,37,17,9.0,3,22,Urban,ML Engineer,126235,0 +65111,Female,53,Bachelors,17,12,12,63,91,8.0,3,58,Urban,ML Engineer,108208,0 +65112,Male,47,PhD,2,48,45,27,19,3.0,4,17,Urban,Data Analyst,133672,0 +65113,Male,26,High School,16,82,33,80,70,8.0,2,90,Semi-Urban,Software Engineer,126537,1 +65114,Female,22,Bachelors,15,43,60,86,86,1.0,2,47,Urban,Data Analyst,104450,0 +65115,Male,46,High School,3,14,21,44,31,5.0,1,37,Rural,Software Engineer,74308,0 +65116,Female,21,Diploma,9,8,3,82,86,4.0,5,25,Urban,Manager,76380,0 +65117,Male,45,Diploma,7,44,55,68,58,0.0,1,62,Semi-Urban,Manager,96483,0 +65118,Other,45,Bachelors,3,69,12,21,94,3.0,7,55,Rural,Software Engineer,63106,0 +65119,Female,57,Bachelors,17,92,24,36,39,4.0,1,63,Urban,Manager,74083,0 +65120,Other,42,Diploma,18,34,24,95,15,8.0,5,36,Urban,Software Engineer,109611,0 +65121,Female,33,High School,11,40,97,77,35,7.0,6,56,Urban,Software Engineer,113649,1 +65122,Male,32,Diploma,15,48,52,35,62,7.0,7,1,Urban,Data Analyst,74600,0 +65123,Female,29,Bachelors,1,44,78,70,71,9.0,6,90,Rural,HR Executive,77710,1 +65124,Female,22,Masters,12,81,63,21,96,3.0,6,54,Semi-Urban,HR Executive,83463,0 +65125,Male,26,Masters,16,52,33,9,66,3.0,7,41,Urban,Data Analyst,88137,0 +65126,Male,39,Bachelors,14,69,79,29,79,9.0,5,0,Urban,Software Engineer,141556,0 +65127,Male,47,Diploma,11,81,76,49,86,1.0,0,84,Rural,HR Executive,93955,1 +65128,Male,56,Bachelors,11,97,88,16,78,6.0,2,43,Rural,Manager,24133,1 +65129,Male,25,Bachelors,3,74,87,23,99,3.0,5,28,Rural,Manager,126040,0 +65130,Female,27,PhD,11,96,63,63,94,2.0,5,36,Urban,HR Executive,119645,1 +65131,Male,32,Bachelors,1,6,87,34,54,2.0,4,28,Semi-Urban,Software Engineer,42905,0 +65132,Male,33,Masters,1,23,81,11,99,5.0,2,59,Semi-Urban,Manager,54906,0 +65133,Female,39,Bachelors,2,39,79,42,8,0.0,1,95,Semi-Urban,HR Executive,118170,1 +65134,Male,35,High School,8,91,23,22,34,4.0,4,41,Urban,ML Engineer,22442,0 +65135,Male,40,High School,0,94,41,93,83,7.0,7,9,Urban,Data Analyst,23520,1 +65136,Male,42,PhD,13,67,47,74,80,4.0,1,87,Rural,ML Engineer,130718,1 +65137,Male,23,Bachelors,1,77,24,77,34,0.0,2,32,Rural,Software Engineer,62682,0 +65138,Male,48,Bachelors,10,61,84,31,70,4.0,1,46,Urban,Data Analyst,132958,0 +65139,Other,24,Masters,16,93,12,14,91,1.0,5,41,Urban,HR Executive,138605,0 +65140,Female,57,Bachelors,19,26,69,0,10,4.0,7,62,Urban,HR Executive,108409,0 +65141,Male,59,Masters,4,71,28,28,56,3.0,4,39,Semi-Urban,ML Engineer,64049,0 +65142,Female,35,Bachelors,8,93,35,29,17,4.0,0,54,Semi-Urban,Software Engineer,102798,0 +65143,Male,34,Diploma,7,37,75,53,94,0.0,0,23,Rural,Software Engineer,58977,0 +65144,Male,53,Bachelors,15,58,7,94,6,0.0,1,7,Urban,ML Engineer,98745,0 +65145,Male,34,Bachelors,11,43,73,57,44,4.0,5,16,Semi-Urban,HR Executive,83163,0 +65146,Male,45,High School,13,52,63,8,21,4.0,3,78,Rural,ML Engineer,74460,0 +65147,Female,24,High School,14,91,44,9,85,6.0,7,41,Rural,HR Executive,127839,0 +65148,Female,27,Diploma,5,53,25,86,68,3.0,6,12,Urban,Software Engineer,64217,0 +65149,Female,34,Bachelors,4,72,11,51,29,6.0,6,46,Semi-Urban,HR Executive,28556,0 +65150,Other,45,Masters,9,31,42,57,31,9.0,0,49,Urban,Data Analyst,97529,0 +65151,Male,56,Bachelors,7,29,83,0,32,2.0,2,3,Rural,Data Analyst,81883,0 +65152,Female,36,High School,3,38,61,35,86,6.0,4,68,Semi-Urban,Software Engineer,80070,0 +65153,Male,25,Bachelors,6,67,2,58,83,5.0,5,84,Rural,HR Executive,100640,0 +65154,Other,44,Bachelors,0,51,37,52,21,5.0,5,63,Urban,Data Analyst,145656,0 +65155,Male,50,High School,12,10,26,71,90,8.0,1,9,Urban,HR Executive,139649,0 +65156,Male,45,Masters,13,6,70,84,57,1.0,2,57,Urban,HR Executive,67880,0 +65157,Male,29,Bachelors,15,82,6,26,4,2.0,1,94,Semi-Urban,Software Engineer,97674,0 +65158,Male,58,High School,4,49,71,92,55,3.0,2,36,Rural,Manager,47910,1 +65159,Male,22,Bachelors,14,7,48,77,50,3.0,1,39,Rural,Software Engineer,106699,0 +65160,Male,40,Bachelors,16,86,28,42,31,6.0,7,17,Urban,Software Engineer,122787,0 +65161,Male,30,Masters,19,64,87,43,41,6.0,5,78,Semi-Urban,HR Executive,36238,1 +65162,Male,35,Bachelors,2,73,26,64,6,5.0,5,77,Urban,HR Executive,113132,1 +65163,Male,48,Masters,9,88,2,19,78,2.0,7,99,Semi-Urban,ML Engineer,45013,0 +65164,Male,55,Bachelors,0,2,66,68,53,0.0,7,4,Urban,Data Analyst,106000,0 +65165,Male,55,Diploma,13,78,10,62,74,5.0,5,52,Semi-Urban,HR Executive,142516,0 +65166,Male,54,Diploma,8,65,55,6,71,7.0,2,71,Urban,ML Engineer,131891,0 +65167,Male,26,Diploma,7,50,38,69,50,2.0,4,7,Semi-Urban,Manager,138103,0 +65168,Male,48,High School,6,95,56,74,56,7.0,4,48,Urban,Manager,86134,1 +65169,Male,27,PhD,1,66,31,95,80,1.0,5,70,Semi-Urban,Manager,26363,1 +65170,Male,53,Bachelors,15,87,57,73,73,0.0,7,51,Urban,HR Executive,137085,1 +65171,Female,41,High School,16,64,14,26,80,2.0,3,17,Urban,HR Executive,55535,0 +65172,Female,59,Masters,10,27,20,69,97,1.0,7,3,Semi-Urban,Manager,87540,0 +65173,Other,52,Diploma,10,92,83,56,35,2.0,7,16,Semi-Urban,Data Analyst,104980,1 +65174,Male,48,Bachelors,17,24,36,38,12,3.0,6,80,Urban,HR Executive,22300,0 +65175,Male,54,Masters,9,27,92,90,98,8.0,5,71,Semi-Urban,HR Executive,127665,1 +65176,Other,36,High School,10,28,77,50,85,4.0,7,86,Urban,Manager,40986,1 +65177,Male,37,Bachelors,11,10,63,37,17,1.0,2,68,Urban,ML Engineer,42807,0 +65178,Male,53,Bachelors,1,15,71,78,64,1.0,3,89,Rural,ML Engineer,135008,1 +65179,Female,49,Diploma,2,66,77,98,66,1.0,4,26,Urban,Software Engineer,53874,1 +65180,Male,30,Bachelors,15,78,3,49,5,8.0,7,55,Semi-Urban,ML Engineer,73098,0 +65181,Female,39,High School,2,68,47,53,83,8.0,1,77,Rural,Manager,40329,1 +65182,Male,34,Masters,3,6,12,58,32,0.0,7,15,Urban,HR Executive,117377,0 +65183,Male,59,Bachelors,2,62,37,83,76,2.0,3,8,Semi-Urban,ML Engineer,32773,0 +65184,Male,51,Bachelors,13,10,8,53,81,9.0,2,97,Urban,HR Executive,77356,0 +65185,Male,47,Bachelors,0,54,54,12,89,3.0,1,51,Urban,Data Analyst,142338,0 +65186,Female,52,Bachelors,19,93,37,76,86,2.0,4,65,Urban,Manager,60754,1 +65187,Female,47,PhD,15,55,30,55,86,2.0,5,58,Urban,Manager,20426,0 +65188,Male,48,Diploma,10,98,2,38,90,0.0,6,36,Semi-Urban,Software Engineer,80804,0 +65189,Male,49,High School,4,89,0,4,8,8.0,7,14,Semi-Urban,Data Analyst,142608,0 +65190,Female,30,Masters,4,74,69,11,90,9.0,4,3,Urban,Manager,145030,0 +65191,Female,59,Diploma,6,67,57,55,7,6.0,6,94,Urban,HR Executive,97364,1 +65192,Male,57,PhD,11,68,4,21,24,4.0,5,92,Urban,Software Engineer,54715,0 +65193,Female,25,Bachelors,13,30,20,25,88,1.0,3,79,Semi-Urban,Data Analyst,142366,0 +65194,Female,26,Bachelors,19,53,16,88,20,1.0,2,36,Rural,Software Engineer,65439,0 +65195,Male,45,High School,3,2,49,41,41,5.0,0,8,Rural,HR Executive,64138,0 +65196,Female,22,Diploma,11,65,25,64,89,4.0,4,99,Urban,Software Engineer,129769,1 +65197,Female,56,Masters,0,95,19,20,22,1.0,0,54,Rural,Data Analyst,71436,0 +65198,Female,27,Bachelors,14,98,85,88,70,4.0,6,77,Semi-Urban,HR Executive,86889,1 +65199,Male,47,Bachelors,5,55,51,35,10,0.0,3,65,Urban,Data Analyst,89458,0 +65200,Female,38,Masters,0,48,35,66,87,7.0,2,68,Rural,Manager,124722,0 +65201,Male,43,Bachelors,10,87,43,15,85,8.0,2,68,Urban,HR Executive,147812,0 +65202,Female,48,Bachelors,15,47,53,91,50,2.0,5,71,Semi-Urban,Data Analyst,72842,1 +65203,Male,26,Diploma,17,24,61,64,96,9.0,0,44,Urban,Data Analyst,130874,0 +65204,Male,29,Diploma,15,17,0,32,58,2.0,4,92,Semi-Urban,Software Engineer,147818,0 +65205,Female,54,Bachelors,1,67,48,91,13,1.0,4,51,Urban,Manager,89599,1 +65206,Male,56,Masters,10,35,27,76,73,4.0,4,74,Rural,ML Engineer,105612,0 +65207,Female,40,Bachelors,6,84,6,35,96,6.0,7,38,Urban,Data Analyst,121447,0 +65208,Female,27,Bachelors,9,57,72,16,58,8.0,7,45,Urban,HR Executive,117466,0 +65209,Female,21,Diploma,5,43,12,77,53,9.0,3,45,Rural,Manager,116427,0 +65210,Male,37,Bachelors,7,40,62,45,66,4.0,0,5,Urban,Data Analyst,74581,0 +65211,Other,48,Masters,3,20,35,47,9,8.0,5,84,Urban,ML Engineer,76975,0 +65212,Female,35,Bachelors,12,91,94,42,37,9.0,6,53,Urban,Software Engineer,137057,1 +65213,Male,59,PhD,3,5,69,85,88,5.0,2,26,Urban,HR Executive,37337,0 +65214,Male,21,Bachelors,1,12,32,88,76,7.0,5,59,Semi-Urban,Data Analyst,35742,0 +65215,Other,28,Bachelors,18,6,5,79,19,7.0,2,82,Rural,HR Executive,87887,0 +65216,Male,21,High School,14,82,74,70,91,2.0,7,63,Urban,Data Analyst,108847,1 +65217,Male,25,High School,10,68,97,79,73,5.0,6,63,Urban,HR Executive,140917,1 +65218,Male,57,Masters,18,73,67,4,27,5.0,1,7,Semi-Urban,Data Analyst,59714,0 +65219,Male,50,Bachelors,15,35,15,77,44,7.0,2,10,Semi-Urban,Software Engineer,108880,0 +65220,Other,25,Masters,15,66,51,37,10,9.0,3,39,Urban,Manager,47236,0 +65221,Male,29,Bachelors,7,94,87,4,96,2.0,3,32,Urban,ML Engineer,130448,0 +65222,Male,40,High School,15,44,81,55,53,5.0,3,86,Rural,Data Analyst,31648,1 +65223,Female,31,High School,3,87,11,75,12,3.0,1,86,Urban,HR Executive,144761,1 +65224,Male,59,Bachelors,13,1,0,43,85,2.0,3,87,Urban,ML Engineer,131655,0 +65225,Male,30,Bachelors,18,55,2,52,98,2.0,4,77,Urban,Data Analyst,26329,0 +65226,Female,32,Masters,7,94,17,23,86,0.0,2,90,Semi-Urban,ML Engineer,112038,0 +65227,Female,44,Bachelors,18,41,24,95,43,9.0,1,52,Urban,Software Engineer,68063,0 +65228,Male,49,Diploma,5,69,81,61,0,0.0,1,69,Urban,Manager,41160,1 +65229,Female,51,High School,10,65,11,95,30,8.0,6,70,Urban,Data Analyst,121625,1 +65230,Male,40,Bachelors,11,28,61,90,94,7.0,5,62,Rural,Manager,46900,1 +65231,Male,25,Bachelors,1,0,49,96,41,6.0,7,37,Semi-Urban,ML Engineer,73878,0 +65232,Male,56,Masters,12,46,31,32,16,1.0,4,73,Rural,Data Analyst,99443,0 +65233,Male,38,PhD,10,76,67,26,24,9.0,2,99,Urban,Data Analyst,21867,1 +65234,Male,37,High School,11,96,92,12,18,8.0,2,19,Urban,HR Executive,23129,0 +65235,Male,26,High School,14,5,95,26,1,5.0,3,69,Rural,Manager,74929,0 +65236,Male,55,Bachelors,14,83,59,75,68,0.0,4,33,Semi-Urban,Manager,101271,1 +65237,Female,36,Bachelors,7,95,28,97,35,1.0,4,24,Semi-Urban,Software Engineer,27949,1 +65238,Female,36,Masters,10,59,56,68,61,1.0,2,7,Semi-Urban,Data Analyst,101835,0 +65239,Female,30,Bachelors,7,29,25,74,69,1.0,7,58,Urban,HR Executive,56231,0 +65240,Male,32,Bachelors,11,63,65,75,95,5.0,3,2,Urban,Data Analyst,60826,0 +65241,Male,23,Bachelors,4,25,2,54,46,9.0,6,5,Urban,Data Analyst,65898,0 +65242,Male,35,Masters,5,6,71,40,62,2.0,3,9,Semi-Urban,HR Executive,122373,0 +65243,Male,30,Diploma,12,86,71,7,36,7.0,6,56,Semi-Urban,ML Engineer,69050,0 +65244,Female,33,Masters,13,6,22,34,95,8.0,0,10,Urban,Manager,108158,0 +65245,Male,27,Bachelors,15,67,97,65,11,9.0,4,35,Urban,HR Executive,48430,1 +65246,Female,36,Bachelors,5,80,71,43,37,5.0,3,63,Semi-Urban,Data Analyst,89775,1 +65247,Male,43,Bachelors,8,7,86,12,65,9.0,7,35,Semi-Urban,ML Engineer,64556,0 +65248,Male,55,Diploma,7,65,72,68,0,9.0,5,94,Urban,Manager,136140,1 +65249,Male,30,Bachelors,18,8,24,92,49,7.0,6,97,Semi-Urban,Software Engineer,38369,0 +65250,Male,34,Bachelors,16,26,6,8,45,6.0,1,13,Rural,Manager,120437,0 +65251,Male,44,Bachelors,0,30,62,5,9,5.0,2,60,Urban,ML Engineer,116360,0 +65252,Male,58,Masters,13,40,26,90,71,5.0,5,15,Semi-Urban,ML Engineer,65054,0 +65253,Female,49,Masters,19,42,23,67,42,7.0,7,8,Semi-Urban,Manager,100430,0 +65254,Male,52,Bachelors,8,87,38,30,37,6.0,4,1,Semi-Urban,Data Analyst,98026,0 +65255,Female,46,Bachelors,19,16,65,38,3,6.0,6,61,Semi-Urban,Manager,107476,0 +65256,Male,36,Bachelors,15,12,8,85,11,0.0,1,43,Rural,HR Executive,102572,0 +65257,Male,38,Masters,12,18,57,69,49,2.0,4,10,Semi-Urban,Manager,97636,0 +65258,Male,36,Bachelors,2,97,84,62,5,5.0,7,57,Urban,Data Analyst,57341,1 +65259,Male,55,Bachelors,14,86,45,20,13,7.0,2,84,Urban,HR Executive,26247,1 +65260,Female,40,Diploma,11,76,98,11,49,3.0,7,69,Semi-Urban,ML Engineer,93156,1 +65261,Female,50,Diploma,15,57,66,8,80,8.0,3,34,Semi-Urban,ML Engineer,95118,0 +65262,Female,31,Diploma,17,90,78,45,5,7.0,1,50,Rural,ML Engineer,87849,1 +65263,Male,28,High School,12,53,83,60,39,0.0,7,70,Urban,HR Executive,60194,1 +65264,Other,36,Bachelors,16,56,89,94,56,6.0,6,20,Urban,Data Analyst,46942,1 +65265,Male,59,High School,4,18,65,13,94,1.0,2,37,Urban,ML Engineer,85560,0 +65266,Male,27,Bachelors,16,7,94,40,71,2.0,1,26,Urban,Manager,118187,0 +65267,Other,33,Bachelors,12,71,84,30,41,0.0,2,42,Urban,ML Engineer,100009,0 +65268,Other,54,Bachelors,7,65,55,73,42,8.0,4,38,Urban,ML Engineer,45663,0 +65269,Male,32,Bachelors,17,94,54,96,2,5.0,7,12,Urban,Manager,84726,1 +65270,Male,53,Bachelors,18,48,82,20,92,9.0,1,54,Rural,Data Analyst,33388,0 +65271,Male,59,Bachelors,15,40,77,85,71,2.0,0,91,Urban,Data Analyst,122256,1 +65272,Male,29,Bachelors,17,97,53,48,82,6.0,1,9,Urban,Manager,26030,0 +65273,Female,26,Diploma,8,75,4,81,15,0.0,6,77,Urban,Manager,21896,0 +65274,Male,39,Diploma,11,86,40,28,91,3.0,4,46,Urban,Manager,135312,0 +65275,Female,33,Diploma,6,7,2,34,68,0.0,3,25,Rural,HR Executive,22421,0 +65276,Male,21,Diploma,2,94,57,50,64,8.0,0,39,Urban,HR Executive,121671,1 +65277,Female,39,Masters,3,60,71,13,69,2.0,0,40,Rural,Manager,73971,0 +65278,Male,35,High School,16,36,63,56,72,2.0,1,31,Urban,Software Engineer,133387,0 +65279,Other,29,Bachelors,19,76,69,23,43,7.0,5,95,Urban,HR Executive,84902,1 +65280,Female,37,Masters,5,95,4,72,1,8.0,0,80,Urban,HR Executive,121871,1 +65281,Male,22,High School,12,69,66,44,90,9.0,7,18,Rural,Software Engineer,57124,0 +65282,Male,50,PhD,0,25,46,54,65,9.0,3,25,Rural,HR Executive,57473,0 +65283,Male,35,Masters,8,66,34,46,75,9.0,4,19,Rural,Software Engineer,127278,0 +65284,Male,28,Bachelors,8,41,84,74,79,8.0,0,3,Semi-Urban,ML Engineer,52850,0 +65285,Female,29,Bachelors,2,32,24,88,29,0.0,4,72,Semi-Urban,ML Engineer,42966,0 +65286,Male,47,High School,4,24,52,91,84,6.0,3,26,Urban,Manager,67059,0 +65287,Female,48,Diploma,19,28,66,30,20,7.0,2,8,Semi-Urban,Manager,55934,0 +65288,Male,44,Diploma,2,44,14,97,81,3.0,1,96,Urban,ML Engineer,82128,1 +65289,Male,24,Bachelors,10,67,41,75,25,9.0,4,55,Urban,Data Analyst,93795,1 +65290,Male,42,Bachelors,19,58,23,22,49,8.0,1,81,Urban,Data Analyst,35254,0 +65291,Female,54,Masters,8,41,74,83,35,9.0,6,54,Semi-Urban,HR Executive,30099,1 +65292,Male,32,Diploma,9,85,60,19,19,3.0,0,1,Urban,Manager,146710,0 +65293,Male,36,Diploma,15,12,74,91,82,6.0,7,39,Semi-Urban,Data Analyst,66386,0 +65294,Male,57,Bachelors,19,83,79,76,20,6.0,5,95,Urban,ML Engineer,51593,1 +65295,Male,22,Bachelors,13,24,29,53,58,3.0,2,76,Urban,Software Engineer,44661,0 +65296,Male,43,Bachelors,17,37,40,81,56,0.0,3,93,Urban,Data Analyst,128336,1 +65297,Female,41,Bachelors,15,28,34,84,45,7.0,4,23,Urban,Manager,68254,0 +65298,Male,33,Bachelors,7,39,59,18,5,7.0,0,84,Semi-Urban,Manager,37266,0 +65299,Male,52,Masters,15,20,45,0,86,7.0,1,52,Urban,ML Engineer,25242,0 +65300,Male,25,Masters,11,69,46,89,40,1.0,0,50,Rural,ML Engineer,29155,1 +65301,Male,54,Masters,15,70,57,35,5,4.0,2,4,Urban,ML Engineer,73532,0 +65302,Female,37,Bachelors,15,68,85,35,26,5.0,2,96,Urban,Data Analyst,65128,1 +65303,Female,31,Diploma,11,31,31,23,29,7.0,1,50,Urban,Data Analyst,46799,0 +65304,Female,47,Diploma,10,62,90,56,59,3.0,3,70,Urban,Manager,30776,1 +65305,Female,22,Masters,19,81,96,45,96,4.0,5,65,Rural,Data Analyst,59928,1 +65306,Male,45,PhD,16,40,12,19,78,6.0,4,42,Semi-Urban,ML Engineer,107857,0 +65307,Other,56,High School,9,44,51,11,38,7.0,3,0,Urban,ML Engineer,96701,0 +65308,Male,28,High School,6,14,96,77,58,1.0,5,51,Semi-Urban,Software Engineer,53745,1 +65309,Female,54,Masters,10,7,97,45,86,3.0,4,94,Urban,Software Engineer,33777,1 +65310,Male,36,Bachelors,13,31,26,3,40,5.0,6,65,Semi-Urban,Data Analyst,142920,0 +65311,Male,34,Masters,11,89,10,30,57,5.0,5,81,Rural,HR Executive,100067,0 +65312,Male,56,Bachelors,19,26,78,65,69,9.0,7,98,Rural,HR Executive,129006,1 +65313,Male,48,Diploma,9,96,50,87,12,2.0,0,11,Semi-Urban,HR Executive,64713,1 +65314,Male,22,High School,16,60,79,52,7,1.0,3,67,Urban,HR Executive,41121,1 +65315,Male,40,Bachelors,6,8,1,93,1,1.0,1,38,Semi-Urban,Data Analyst,53953,0 +65316,Female,40,Masters,9,79,88,25,44,1.0,4,68,Urban,HR Executive,137172,1 +65317,Female,56,Bachelors,19,3,92,92,47,0.0,0,29,Rural,HR Executive,76372,0 +65318,Male,35,Bachelors,0,17,77,32,50,1.0,2,51,Semi-Urban,ML Engineer,143454,0 +65319,Male,33,Diploma,4,90,22,87,60,8.0,4,93,Urban,ML Engineer,96372,1 +65320,Female,42,High School,13,92,72,93,67,8.0,1,48,Semi-Urban,ML Engineer,80541,1 +65321,Male,28,Diploma,14,88,22,82,22,1.0,1,21,Urban,Software Engineer,41200,0 +65322,Male,44,Bachelors,14,32,72,74,97,7.0,3,16,Urban,HR Executive,124597,0 +65323,Other,39,Bachelors,12,45,31,39,91,3.0,6,62,Rural,Manager,68449,0 +65324,Male,53,Diploma,5,24,84,25,48,4.0,7,62,Urban,Manager,47068,0 +65325,Male,31,High School,8,49,69,95,28,1.0,7,70,Urban,Manager,98571,1 +65326,Female,37,Diploma,17,14,81,24,65,4.0,3,5,Rural,Data Analyst,32515,0 +65327,Female,45,Masters,15,3,32,76,80,0.0,6,58,Urban,HR Executive,72133,0 +65328,Male,42,Bachelors,7,42,78,96,18,3.0,7,91,Urban,HR Executive,47617,1 +65329,Female,55,Diploma,19,78,56,20,91,5.0,1,41,Urban,HR Executive,103477,0 +65330,Male,23,Bachelors,9,20,4,8,85,6.0,1,91,Semi-Urban,Data Analyst,104728,0 +65331,Male,59,Bachelors,14,70,29,50,9,9.0,2,46,Semi-Urban,ML Engineer,24694,0 +65332,Male,35,Bachelors,1,86,92,43,36,7.0,5,83,Rural,Data Analyst,37553,1 +65333,Male,44,Diploma,2,24,79,41,1,1.0,4,74,Urban,Software Engineer,31410,0 +65334,Male,51,Bachelors,7,54,50,14,55,7.0,6,47,Urban,ML Engineer,64104,0 +65335,Male,51,Bachelors,11,92,22,44,76,0.0,3,90,Semi-Urban,Data Analyst,98459,1 +65336,Female,43,Masters,11,2,55,68,42,3.0,7,51,Rural,Data Analyst,117921,0 +65337,Male,34,Bachelors,14,53,21,24,66,1.0,1,76,Semi-Urban,Data Analyst,28205,0 +65338,Male,48,Diploma,14,14,99,64,80,1.0,4,7,Urban,Manager,112692,0 +65339,Male,32,Masters,5,35,17,90,91,3.0,2,97,Rural,Software Engineer,39373,1 +65340,Female,56,Bachelors,4,21,45,35,12,2.0,7,16,Urban,Software Engineer,30553,0 +65341,Male,24,High School,8,60,66,66,13,6.0,2,47,Semi-Urban,HR Executive,146177,1 +65342,Female,40,Masters,7,80,15,52,0,9.0,0,10,Semi-Urban,HR Executive,149236,0 +65343,Male,52,Bachelors,17,76,29,51,7,9.0,1,49,Semi-Urban,HR Executive,56650,0 +65344,Male,38,Masters,8,20,9,80,0,2.0,0,49,Urban,ML Engineer,122780,0 +65345,Female,50,High School,17,21,23,46,23,3.0,4,59,Urban,ML Engineer,45181,0 +65346,Female,48,Diploma,18,52,34,33,60,3.0,0,45,Urban,ML Engineer,69658,0 +65347,Male,37,Diploma,6,8,23,43,0,3.0,0,14,Semi-Urban,Manager,92158,0 +65348,Male,40,Bachelors,19,69,96,61,68,0.0,6,69,Semi-Urban,Software Engineer,80687,1 +65349,Female,57,Bachelors,15,4,42,22,22,9.0,1,50,Urban,Data Analyst,23607,0 +65350,Male,42,PhD,11,40,92,32,43,4.0,6,60,Semi-Urban,Manager,116305,0 +65351,Female,31,Masters,2,36,94,30,35,7.0,7,12,Urban,Data Analyst,141112,0 +65352,Male,28,Bachelors,2,7,80,21,78,5.0,6,28,Semi-Urban,ML Engineer,133611,0 +65353,Male,54,Bachelors,5,20,80,88,96,5.0,5,5,Semi-Urban,HR Executive,56164,0 +65354,Male,39,Bachelors,5,46,55,39,76,5.0,6,23,Urban,HR Executive,33996,0 +65355,Male,56,Bachelors,2,90,34,54,66,2.0,1,67,Urban,Manager,54089,1 +65356,Female,59,Diploma,5,24,57,27,59,2.0,4,52,Rural,Manager,48438,0 +65357,Female,43,Diploma,7,13,25,27,79,4.0,3,53,Rural,Manager,92766,0 +65358,Male,33,Bachelors,9,52,56,20,88,2.0,7,54,Semi-Urban,Data Analyst,54095,0 +65359,Male,31,Diploma,14,26,6,64,38,1.0,4,61,Urban,ML Engineer,144716,0 +65360,Male,53,Masters,10,49,84,89,26,2.0,6,69,Urban,Manager,30248,1 +65361,Female,58,Diploma,10,41,11,19,26,6.0,3,4,Urban,HR Executive,149376,0 +65362,Male,21,Masters,17,94,72,73,41,5.0,4,62,Semi-Urban,Software Engineer,69641,1 +65363,Male,35,Diploma,11,15,29,21,31,1.0,0,63,Rural,Manager,38815,0 +65364,Male,37,Masters,6,75,98,19,52,6.0,7,67,Semi-Urban,Data Analyst,84615,1 +65365,Male,24,High School,9,45,92,24,32,8.0,0,7,Semi-Urban,Data Analyst,73234,0 +65366,Female,57,High School,2,53,89,2,17,4.0,7,38,Semi-Urban,Manager,144457,0 +65367,Male,54,Masters,19,11,86,74,23,1.0,1,46,Semi-Urban,Data Analyst,67059,0 +65368,Male,46,Bachelors,16,57,83,64,72,2.0,0,94,Rural,Software Engineer,47212,1 +65369,Male,33,Bachelors,13,44,10,18,91,4.0,6,56,Rural,ML Engineer,143884,0 +65370,Male,25,High School,18,68,91,27,52,2.0,0,87,Semi-Urban,ML Engineer,109052,1 +65371,Male,36,Diploma,5,41,78,96,36,1.0,4,30,Semi-Urban,Manager,62219,1 +65372,Male,38,Bachelors,4,69,81,25,91,5.0,1,40,Urban,ML Engineer,94118,0 +65373,Female,42,Masters,5,36,70,53,12,0.0,3,53,Rural,Manager,116984,0 +65374,Female,23,Bachelors,8,88,72,87,93,6.0,4,60,Rural,Data Analyst,29215,1 +65375,Female,22,Diploma,5,51,41,47,51,8.0,3,30,Urban,HR Executive,145724,0 +65376,Female,30,Bachelors,5,86,49,92,97,8.0,5,76,Urban,ML Engineer,81086,1 +65377,Male,35,Diploma,2,42,87,42,32,0.0,5,77,Rural,HR Executive,41822,1 +65378,Male,39,Masters,1,51,76,43,97,3.0,2,28,Rural,Data Analyst,94477,0 +65379,Female,31,Diploma,11,22,62,11,34,8.0,2,81,Rural,Manager,56520,0 +65380,Male,29,Diploma,12,86,0,50,88,3.0,0,43,Urban,Manager,96946,0 +65381,Female,30,Masters,9,89,52,71,55,2.0,5,82,Rural,Manager,117551,1 +65382,Female,43,Bachelors,11,50,31,95,26,5.0,4,50,Urban,ML Engineer,118122,0 +65383,Female,27,Bachelors,18,33,73,8,24,1.0,3,84,Urban,ML Engineer,93189,0 +65384,Female,56,Bachelors,10,85,78,99,8,9.0,6,33,Urban,Software Engineer,102890,1 +65385,Male,50,Diploma,4,59,47,82,12,1.0,5,27,Urban,Manager,69456,0 +65386,Male,43,High School,9,63,55,96,28,8.0,0,85,Rural,Software Engineer,121036,1 +65387,Male,41,Bachelors,17,85,6,51,41,0.0,7,38,Semi-Urban,Manager,27836,0 +65388,Female,30,Masters,8,53,88,72,52,8.0,2,22,Rural,HR Executive,126808,0 +65389,Male,28,Bachelors,5,13,41,11,85,5.0,2,85,Rural,ML Engineer,128712,0 +65390,Male,46,High School,15,46,68,67,78,0.0,0,7,Semi-Urban,Manager,41682,0 +65391,Other,59,Bachelors,7,87,44,39,13,6.0,7,48,Semi-Urban,HR Executive,52792,0 +65392,Male,24,Bachelors,5,8,53,60,66,6.0,6,64,Urban,ML Engineer,100955,0 +65393,Male,47,Bachelors,16,70,27,56,31,0.0,3,43,Urban,Manager,121211,0 +65394,Male,43,Masters,18,26,72,75,32,7.0,7,59,Semi-Urban,ML Engineer,143408,0 +65395,Female,54,Diploma,4,89,92,46,28,4.0,6,62,Rural,Software Engineer,27103,1 +65396,Female,35,Bachelors,8,31,51,89,62,2.0,4,96,Rural,HR Executive,111936,1 +65397,Female,51,High School,3,76,78,33,3,2.0,5,19,Semi-Urban,Manager,64151,0 +65398,Male,53,Bachelors,0,70,97,56,83,5.0,0,85,Urban,Data Analyst,111111,1 +65399,Other,52,Bachelors,16,99,71,84,30,1.0,2,58,Semi-Urban,ML Engineer,41927,1 +65400,Male,37,Masters,9,30,11,10,17,1.0,4,75,Urban,Data Analyst,52425,0 +65401,Male,59,Bachelors,15,44,3,84,95,8.0,2,78,Urban,ML Engineer,89269,0 +65402,Male,57,Masters,8,71,89,40,43,7.0,5,25,Urban,Software Engineer,49876,0 +65403,Male,30,High School,2,51,8,89,90,9.0,5,66,Urban,Software Engineer,61460,0 +65404,Male,37,Diploma,5,63,28,44,40,0.0,0,24,Urban,Manager,116781,0 +65405,Female,21,Bachelors,3,31,86,6,17,7.0,0,31,Semi-Urban,HR Executive,124372,0 +65406,Male,32,Diploma,3,46,35,36,11,2.0,7,20,Urban,Data Analyst,68819,0 +65407,Female,55,Bachelors,17,83,11,26,81,1.0,4,4,Urban,Software Engineer,130743,0 +65408,Female,42,High School,15,20,51,16,10,5.0,4,52,Urban,Data Analyst,97252,0 +65409,Male,52,Bachelors,15,96,47,1,21,1.0,7,2,Urban,Software Engineer,23359,0 +65410,Other,52,High School,9,11,90,20,73,4.0,6,9,Urban,Data Analyst,38058,0 +65411,Female,40,High School,14,70,77,13,18,0.0,2,43,Urban,HR Executive,130215,0 +65412,Male,43,Diploma,5,50,13,98,8,7.0,3,26,Urban,ML Engineer,146906,0 +65413,Male,25,Bachelors,14,89,74,70,82,1.0,4,7,Urban,HR Executive,75595,1 +65414,Female,49,Diploma,17,88,40,29,77,2.0,6,4,Urban,Manager,49013,0 +65415,Male,58,High School,2,15,43,83,85,2.0,2,61,Urban,Data Analyst,38553,0 +65416,Male,31,Diploma,9,95,30,36,39,1.0,3,60,Rural,HR Executive,117528,0 +65417,Male,47,Bachelors,18,33,70,81,95,8.0,5,94,Semi-Urban,Manager,73559,1 +65418,Male,59,High School,1,74,85,35,59,7.0,7,7,Urban,Data Analyst,129932,0 +65419,Female,56,Bachelors,18,29,37,56,43,7.0,7,45,Urban,Manager,115897,0 +65420,Female,32,Diploma,11,62,15,48,32,3.0,1,22,Semi-Urban,ML Engineer,65323,0 +65421,Male,29,Bachelors,12,23,96,66,85,4.0,7,2,Urban,Software Engineer,68220,0 +65422,Female,55,Bachelors,5,91,4,33,13,0.0,7,19,Urban,Manager,47496,0 +65423,Male,34,PhD,14,33,26,24,93,6.0,5,85,Urban,HR Executive,144265,0 +65424,Male,35,Diploma,7,42,2,55,17,4.0,5,48,Urban,HR Executive,103716,0 +65425,Male,57,Bachelors,7,15,81,92,92,4.0,3,17,Rural,Data Analyst,84554,0 +65426,Female,52,Bachelors,15,25,92,82,82,7.0,3,44,Urban,Data Analyst,82623,1 +65427,Female,55,Diploma,7,9,74,35,25,3.0,5,60,Urban,HR Executive,140790,0 +65428,Male,44,High School,6,36,80,36,9,3.0,7,4,Urban,ML Engineer,107403,0 +65429,Male,21,Diploma,11,60,43,32,65,9.0,3,89,Urban,ML Engineer,103066,0 +65430,Male,36,Bachelors,14,86,62,67,29,5.0,1,23,Urban,HR Executive,58095,1 +65431,Female,39,High School,4,63,59,49,8,5.0,7,26,Urban,Data Analyst,58550,0 +65432,Female,48,Diploma,12,32,14,83,68,5.0,2,4,Urban,Manager,75828,0 +65433,Male,33,PhD,11,14,43,62,76,5.0,1,36,Urban,Data Analyst,65814,0 +65434,Male,23,Bachelors,6,30,92,60,41,2.0,4,14,Urban,Manager,97533,0 +65435,Male,44,Bachelors,17,19,1,8,26,0.0,2,75,Urban,Data Analyst,51021,0 +65436,Other,24,Masters,5,5,42,77,43,6.0,5,54,Urban,Software Engineer,33905,0 +65437,Female,32,Diploma,19,89,11,70,77,9.0,3,69,Rural,Manager,47907,0 +65438,Other,28,Masters,0,80,47,91,6,8.0,0,87,Rural,Data Analyst,51374,1 +65439,Female,30,Diploma,5,79,33,81,74,3.0,5,52,Urban,Software Engineer,35119,1 +65440,Male,22,Bachelors,13,2,2,59,36,0.0,4,19,Urban,Data Analyst,124431,0 +65441,Female,39,Masters,12,10,96,82,45,9.0,1,99,Urban,Software Engineer,139134,1 +65442,Female,56,Diploma,9,78,5,42,53,7.0,7,35,Urban,ML Engineer,139434,0 +65443,Male,59,Masters,9,57,71,95,27,5.0,1,4,Rural,ML Engineer,37035,0 +65444,Female,28,High School,16,83,32,46,83,0.0,6,25,Urban,HR Executive,126147,0 +65445,Female,45,Masters,5,16,17,8,77,0.0,2,23,Urban,Manager,116799,0 +65446,Female,22,High School,0,74,8,55,78,3.0,0,40,Urban,HR Executive,113170,0 +65447,Female,49,Masters,5,79,32,2,5,1.0,3,61,Rural,Data Analyst,74486,0 +65448,Male,46,Bachelors,11,32,74,23,95,1.0,7,7,Semi-Urban,Data Analyst,136997,0 +65449,Female,38,Bachelors,2,75,61,3,40,1.0,3,76,Urban,Data Analyst,58810,0 +65450,Male,31,High School,8,55,78,51,36,3.0,7,26,Semi-Urban,Data Analyst,25609,0 +65451,Male,40,Diploma,5,34,50,90,91,1.0,2,84,Urban,Manager,82553,1 +65452,Male,44,High School,18,50,28,61,63,0.0,6,54,Urban,Data Analyst,70431,0 +65453,Male,22,Bachelors,4,12,63,64,52,1.0,2,67,Rural,Manager,86682,0 +65454,Male,50,High School,15,91,97,0,8,5.0,3,0,Semi-Urban,Software Engineer,42612,0 +65455,Male,31,Diploma,17,50,65,7,5,3.0,3,54,Semi-Urban,Manager,97771,0 +65456,Male,25,High School,9,61,69,53,90,0.0,6,65,Urban,Manager,102942,1 +65457,Male,26,Bachelors,1,53,66,40,63,6.0,2,33,Urban,ML Engineer,50862,0 +65458,Female,32,Diploma,2,21,2,80,11,7.0,4,55,Urban,ML Engineer,22202,0 +65459,Female,25,Masters,18,19,41,47,82,6.0,0,27,Semi-Urban,ML Engineer,141522,0 +65460,Male,24,Bachelors,11,73,36,94,38,8.0,0,14,Urban,Data Analyst,35651,0 +65461,Female,54,Masters,10,1,30,80,6,3.0,0,33,Urban,Manager,135889,0 +65462,Male,35,Masters,17,7,93,7,52,0.0,6,25,Rural,Software Engineer,70135,0 +65463,Male,57,Bachelors,12,94,16,42,16,1.0,4,20,Semi-Urban,HR Executive,114652,0 +65464,Male,21,Diploma,12,49,88,0,58,2.0,3,2,Semi-Urban,ML Engineer,73686,0 +65465,Female,57,Diploma,8,53,77,39,50,3.0,1,57,Urban,Data Analyst,39389,0 +65466,Male,59,Masters,2,14,59,89,77,8.0,1,75,Rural,Data Analyst,60321,1 +65467,Male,32,Diploma,3,1,6,31,75,1.0,1,73,Rural,Software Engineer,124899,0 +65468,Female,47,Bachelors,14,87,97,71,70,2.0,2,33,Urban,HR Executive,47659,1 +65469,Male,37,PhD,12,26,56,78,59,5.0,7,26,Semi-Urban,Data Analyst,98985,0 +65470,Male,43,Bachelors,7,79,19,87,37,9.0,0,72,Semi-Urban,Software Engineer,34622,1 +65471,Male,58,Masters,4,73,26,83,67,2.0,5,11,Urban,Manager,63637,0 +65472,Male,42,High School,1,18,94,57,76,2.0,5,34,Rural,Software Engineer,67430,0 +65473,Male,54,Bachelors,12,18,5,52,66,5.0,4,13,Urban,Manager,95542,0 +65474,Other,38,Bachelors,8,50,72,18,87,1.0,7,95,Semi-Urban,Manager,142701,0 +65475,Male,28,Diploma,10,61,89,98,18,3.0,2,98,Urban,Manager,23774,1 +65476,Male,39,Masters,16,56,10,59,29,1.0,0,23,Rural,HR Executive,46524,0 +65477,Female,49,Bachelors,11,39,76,36,45,3.0,1,88,Semi-Urban,Manager,138566,0 +65478,Male,47,Bachelors,4,76,26,83,65,2.0,7,61,Urban,ML Engineer,27479,1 +65479,Other,45,Bachelors,12,66,49,64,36,0.0,2,29,Urban,ML Engineer,146572,0 +65480,Other,29,High School,6,13,24,70,36,9.0,2,92,Urban,Software Engineer,89133,0 +65481,Female,41,High School,9,32,41,9,98,0.0,7,14,Semi-Urban,Software Engineer,29530,0 +65482,Male,52,Bachelors,11,29,77,43,31,2.0,1,46,Urban,Manager,77527,0 +65483,Female,46,PhD,10,84,54,39,54,5.0,5,97,Urban,ML Engineer,54036,1 +65484,Male,41,Masters,4,50,42,69,61,9.0,3,37,Urban,Data Analyst,22788,0 +65485,Female,46,Bachelors,11,99,75,47,83,2.0,0,17,Rural,ML Engineer,149096,0 +65486,Male,42,Diploma,2,2,82,48,84,7.0,5,48,Urban,Data Analyst,65471,0 +65487,Male,56,Diploma,12,22,31,67,40,8.0,1,18,Rural,ML Engineer,88599,0 +65488,Female,33,PhD,15,20,84,57,17,5.0,5,41,Semi-Urban,ML Engineer,41115,0 +65489,Other,49,High School,3,79,59,33,59,5.0,2,22,Urban,Software Engineer,59169,0 +65490,Female,50,Diploma,8,56,30,19,26,4.0,2,29,Urban,HR Executive,148255,0 +65491,Male,35,Masters,0,79,92,36,13,9.0,7,8,Urban,ML Engineer,81508,0 +65492,Male,24,Masters,2,1,81,67,47,7.0,1,19,Urban,HR Executive,38942,0 +65493,Other,27,Bachelors,10,22,21,13,65,6.0,4,35,Urban,Software Engineer,103954,0 +65494,Male,33,Bachelors,18,51,68,57,98,7.0,5,67,Semi-Urban,Software Engineer,30423,1 +65495,Male,55,High School,9,66,35,58,60,2.0,7,89,Urban,Data Analyst,108532,1 +65496,Male,29,Masters,7,29,54,35,99,4.0,6,19,Urban,HR Executive,117774,0 +65497,Male,51,Bachelors,5,51,45,5,52,8.0,5,2,Urban,Software Engineer,97689,0 +65498,Female,57,Diploma,13,4,0,5,99,0.0,4,56,Urban,ML Engineer,46128,0 +65499,Male,31,Bachelors,3,61,23,23,11,7.0,2,49,Urban,Data Analyst,89265,0 +65500,Male,52,Diploma,7,10,36,23,21,6.0,0,87,Urban,ML Engineer,83286,0 +65501,Male,25,Diploma,3,50,34,94,1,1.0,5,73,Semi-Urban,Manager,66699,1 +65502,Male,58,Diploma,18,22,17,80,31,3.0,6,28,Urban,Data Analyst,73411,0 +65503,Male,39,Bachelors,3,65,21,0,14,6.0,7,37,Rural,ML Engineer,102209,0 +65504,Female,26,High School,11,4,27,29,79,7.0,3,83,Rural,Manager,97301,0 +65505,Other,56,Diploma,19,19,44,48,52,3.0,6,24,Rural,Data Analyst,52280,0 +65506,Female,28,High School,0,18,3,16,50,2.0,3,80,Rural,HR Executive,73427,0 +65507,Female,44,Diploma,13,94,49,4,33,6.0,1,67,Rural,HR Executive,45890,0 +65508,Female,32,Bachelors,5,32,65,53,94,6.0,6,19,Semi-Urban,Software Engineer,111112,0 +65509,Female,48,Masters,10,86,61,78,11,4.0,2,97,Urban,Data Analyst,60533,1 +65510,Male,38,Masters,9,0,77,23,68,8.0,7,4,Urban,Software Engineer,96463,0 +65511,Male,57,Masters,3,34,53,39,94,0.0,7,16,Urban,Manager,47628,0 +65512,Female,47,Bachelors,13,2,11,20,32,8.0,3,51,Semi-Urban,Manager,61290,0 +65513,Female,50,High School,4,31,62,46,49,4.0,2,40,Rural,ML Engineer,142056,0 +65514,Male,46,Bachelors,11,50,2,81,68,8.0,0,93,Rural,Data Analyst,52684,0 +65515,Female,23,Bachelors,18,71,47,30,77,6.0,3,7,Rural,Manager,109601,0 +65516,Male,22,Masters,19,85,79,97,80,4.0,1,48,Rural,ML Engineer,134006,1 +65517,Female,49,Bachelors,17,83,62,52,38,7.0,2,47,Rural,HR Executive,87856,1 +65518,Female,38,High School,12,73,63,56,50,0.0,4,21,Urban,Manager,77892,0 +65519,Female,57,Masters,0,40,29,75,57,3.0,7,34,Urban,Manager,140267,0 +65520,Male,55,Diploma,5,52,86,51,29,3.0,2,43,Urban,HR Executive,78126,0 +65521,Other,36,Bachelors,1,6,6,71,79,4.0,0,41,Semi-Urban,ML Engineer,72144,0 +65522,Female,58,Masters,6,94,80,23,43,3.0,5,47,Semi-Urban,ML Engineer,80109,1 +65523,Female,22,Bachelors,9,72,62,93,14,7.0,4,73,Urban,Software Engineer,70602,1 +65524,Male,44,Bachelors,6,31,22,30,73,3.0,4,84,Semi-Urban,HR Executive,20794,0 +65525,Male,44,High School,4,39,82,44,27,1.0,7,74,Urban,Data Analyst,143330,1 +65526,Male,31,Masters,13,45,60,86,16,8.0,2,21,Urban,ML Engineer,120005,0 +65527,Male,59,Bachelors,8,52,68,71,16,9.0,0,39,Rural,ML Engineer,46302,0 +65528,Male,47,Bachelors,5,29,30,90,87,8.0,0,20,Urban,Manager,67997,0 +65529,Male,38,High School,3,68,84,39,74,1.0,5,7,Rural,HR Executive,69315,0 +65530,Male,44,Diploma,2,64,75,81,21,3.0,3,74,Urban,ML Engineer,107815,1 +65531,Female,56,Bachelors,17,54,48,39,62,2.0,7,60,Semi-Urban,Data Analyst,100811,0 +65532,Male,50,Masters,16,49,27,5,5,8.0,0,32,Semi-Urban,ML Engineer,25996,0 +65533,Male,31,Masters,3,86,20,99,18,9.0,0,57,Urban,Manager,122820,1 +65534,Male,23,Bachelors,3,52,65,10,78,6.0,1,63,Urban,HR Executive,109624,0 +65535,Female,47,High School,1,11,1,31,41,2.0,1,20,Semi-Urban,HR Executive,88229,0 +65536,Male,58,Bachelors,3,51,78,4,11,0.0,5,80,Urban,Data Analyst,115938,0 +65537,Male,47,Bachelors,7,98,51,63,46,1.0,2,96,Urban,Manager,84811,1 +65538,Female,38,Masters,6,87,86,25,91,1.0,0,83,Urban,HR Executive,72889,1 +65539,Female,51,Masters,8,57,82,57,49,3.0,2,15,Semi-Urban,HR Executive,132154,0 +65540,Male,34,Diploma,8,20,58,1,6,8.0,0,74,Urban,ML Engineer,21293,0 +65541,Male,49,High School,3,19,42,83,73,0.0,1,58,Urban,Data Analyst,29194,0 +65542,Male,55,Masters,10,59,63,46,6,1.0,0,73,Urban,Manager,136979,1 +65543,Male,23,Bachelors,19,52,53,16,47,9.0,0,47,Urban,Data Analyst,56962,0 +65544,Male,32,Bachelors,13,57,83,5,89,4.0,2,59,Urban,Manager,61926,0 +65545,Male,58,Bachelors,6,99,30,69,27,7.0,0,42,Rural,Software Engineer,81974,1 +65546,Male,43,Masters,0,77,81,94,25,3.0,3,85,Rural,Manager,59880,1 +65547,Male,24,High School,8,25,5,14,96,6.0,1,30,Urban,Data Analyst,71513,0 +65548,Female,36,Bachelors,4,59,20,30,28,4.0,3,24,Rural,Software Engineer,101453,0 +65549,Male,37,Diploma,18,31,96,32,66,2.0,1,73,Semi-Urban,Data Analyst,40489,0 +65550,Female,50,Diploma,1,74,27,4,4,6.0,1,28,Urban,Software Engineer,100203,0 +65551,Female,36,Masters,16,79,40,7,50,7.0,7,39,Semi-Urban,Software Engineer,71137,0 +65552,Female,34,Masters,5,52,39,88,11,4.0,1,40,Urban,Manager,91706,0 +65553,Male,21,Masters,5,13,63,61,39,6.0,4,75,Urban,HR Executive,105936,0 +65554,Male,46,Diploma,8,10,84,95,64,2.0,0,28,Urban,Manager,89999,0 +65555,Male,50,High School,1,81,72,81,76,1.0,0,95,Semi-Urban,Data Analyst,117482,1 +65556,Female,56,Diploma,13,65,40,58,76,0.0,0,88,Urban,Data Analyst,27227,1 +65557,Male,59,High School,2,87,70,6,90,8.0,5,72,Urban,Data Analyst,141488,1 +65558,Male,42,High School,11,89,91,64,6,1.0,1,97,Semi-Urban,Software Engineer,106681,1 +65559,Male,57,Bachelors,19,99,54,49,16,0.0,0,62,Rural,HR Executive,96560,1 +65560,Male,56,High School,4,6,36,7,61,7.0,2,79,Urban,ML Engineer,111612,0 +65561,Female,56,High School,1,42,45,63,38,5.0,2,3,Rural,Data Analyst,110424,0 +65562,Male,25,Bachelors,17,38,33,59,95,2.0,6,94,Rural,Software Engineer,49537,0 +65563,Female,30,Bachelors,2,3,11,49,15,7.0,4,58,Urban,Software Engineer,69521,0 +65564,Male,41,Masters,16,10,76,63,88,4.0,5,95,Urban,ML Engineer,73576,1 +65565,Male,36,Diploma,13,65,58,86,28,2.0,7,86,Urban,ML Engineer,131820,1 +65566,Male,42,Bachelors,3,49,92,32,62,8.0,0,90,Rural,HR Executive,47223,1 +65567,Female,38,Bachelors,10,19,72,61,79,3.0,2,89,Rural,Manager,42793,1 +65568,Female,46,Bachelors,6,90,43,14,39,6.0,2,69,Rural,Manager,75183,0 +65569,Female,46,Masters,13,95,63,69,50,8.0,1,90,Urban,HR Executive,58686,1 +65570,Male,43,Diploma,8,76,75,73,50,8.0,1,68,Urban,Manager,66910,1 +65571,Female,23,High School,17,32,67,84,71,2.0,4,38,Rural,HR Executive,126890,0 +65572,Male,24,Bachelors,7,20,5,16,84,4.0,1,66,Semi-Urban,HR Executive,40002,0 +65573,Male,48,Masters,5,59,61,39,73,7.0,1,38,Urban,HR Executive,37977,0 +65574,Female,59,PhD,8,43,29,11,72,5.0,2,52,Rural,Data Analyst,33014,0 +65575,Male,48,Diploma,11,60,64,81,47,5.0,6,20,Rural,Data Analyst,82452,0 +65576,Male,56,Diploma,9,23,25,37,95,0.0,7,64,Urban,Software Engineer,110168,0 +65577,Male,39,Masters,18,52,90,55,8,6.0,5,2,Urban,ML Engineer,119890,0 +65578,Female,53,Masters,19,41,1,5,15,6.0,3,88,Urban,ML Engineer,91911,0 +65579,Male,41,Masters,2,50,79,59,60,4.0,6,84,Urban,ML Engineer,95874,1 +65580,Male,56,Masters,19,50,90,84,85,7.0,7,86,Urban,Manager,52280,1 +65581,Male,31,Diploma,4,2,43,76,1,3.0,0,0,Urban,ML Engineer,100595,0 +65582,Female,51,Bachelors,7,61,59,98,10,1.0,2,2,Urban,Software Engineer,40016,0 +65583,Male,37,Diploma,4,39,76,40,95,7.0,0,9,Rural,HR Executive,29617,0 +65584,Other,56,Bachelors,8,9,12,6,3,8.0,3,45,Urban,HR Executive,101930,0 +65585,Female,41,Bachelors,7,51,67,8,59,6.0,0,14,Semi-Urban,ML Engineer,63123,0 +65586,Male,39,High School,19,56,26,38,96,3.0,1,20,Urban,Manager,99773,0 +65587,Male,48,High School,8,91,49,64,58,6.0,1,23,Semi-Urban,Software Engineer,22938,0 +65588,Male,36,Bachelors,6,27,75,86,34,6.0,2,38,Rural,HR Executive,143012,0 +65589,Female,22,Bachelors,15,9,21,8,66,2.0,6,68,Rural,Data Analyst,26836,0 +65590,Male,28,Bachelors,19,48,34,21,95,8.0,6,77,Semi-Urban,ML Engineer,62138,0 +65591,Male,56,Masters,18,44,98,84,74,2.0,0,99,Urban,ML Engineer,138975,1 +65592,Female,41,Bachelors,12,6,69,43,63,2.0,4,81,Semi-Urban,Data Analyst,134250,0 +65593,Male,34,High School,0,10,45,93,52,8.0,4,40,Urban,HR Executive,52107,0 +65594,Male,38,Bachelors,12,78,1,39,67,9.0,1,31,Urban,ML Engineer,140689,0 +65595,Female,56,Masters,2,66,29,12,87,7.0,4,37,Urban,Software Engineer,78969,0 +65596,Female,32,High School,12,69,92,23,38,4.0,1,30,Rural,Software Engineer,27303,0 +65597,Male,48,Bachelors,4,26,99,65,49,8.0,2,13,Urban,Software Engineer,94613,0 +65598,Female,41,Bachelors,13,80,2,67,52,3.0,0,95,Urban,Software Engineer,40931,1 +65599,Male,42,Masters,17,3,48,32,35,6.0,2,4,Semi-Urban,Manager,128524,0 +65600,Male,34,High School,3,98,13,71,48,7.0,6,72,Urban,ML Engineer,73914,1 +65601,Female,50,Masters,18,32,67,74,45,0.0,3,43,Rural,Manager,33661,0 +65602,Male,31,Masters,17,49,6,33,2,7.0,6,54,Urban,ML Engineer,89350,0 +65603,Male,37,Bachelors,16,38,28,96,19,9.0,0,13,Semi-Urban,Manager,89116,0 +65604,Male,40,Bachelors,11,46,61,80,33,4.0,7,41,Semi-Urban,Data Analyst,86300,0 +65605,Female,26,Masters,13,19,2,62,37,5.0,3,12,Semi-Urban,HR Executive,37826,0 +65606,Male,36,Masters,11,74,91,57,86,5.0,6,85,Semi-Urban,HR Executive,43743,1 +65607,Male,22,Bachelors,10,38,5,76,21,9.0,3,26,Urban,Software Engineer,46329,0 +65608,Male,29,Bachelors,0,92,98,38,10,5.0,1,9,Urban,ML Engineer,137565,1 +65609,Female,38,Masters,13,16,26,9,45,8.0,5,47,Urban,Data Analyst,26333,0 +65610,Male,27,Bachelors,18,17,55,67,46,1.0,3,80,Urban,Data Analyst,56468,0 +65611,Male,29,High School,5,56,85,11,50,5.0,4,66,Urban,Software Engineer,54016,0 +65612,Male,58,Masters,4,32,84,64,69,2.0,6,69,Urban,Data Analyst,112917,1 +65613,Male,44,High School,9,55,0,52,1,6.0,1,24,Urban,HR Executive,50592,0 +65614,Female,36,Masters,14,10,89,19,46,2.0,7,34,Semi-Urban,ML Engineer,94777,0 +65615,Female,21,Bachelors,12,96,41,32,93,3.0,6,69,Rural,Data Analyst,87385,0 +65616,Male,35,Bachelors,11,91,62,34,20,5.0,5,26,Urban,Data Analyst,111508,0 +65617,Male,24,Bachelors,5,15,10,19,46,4.0,6,87,Urban,Software Engineer,22334,0 +65618,Male,50,Bachelors,12,86,1,22,49,3.0,5,58,Rural,HR Executive,57850,0 +65619,Male,38,Diploma,1,41,98,88,57,4.0,1,35,Urban,Data Analyst,106055,1 +65620,Male,42,Masters,18,24,19,97,67,5.0,1,2,Urban,Manager,48584,0 +65621,Female,25,Diploma,1,76,80,38,98,9.0,3,57,Semi-Urban,Manager,86188,1 +65622,Male,29,Bachelors,10,3,73,45,51,5.0,7,56,Urban,Manager,62642,0 +65623,Female,44,Bachelors,10,35,16,79,86,8.0,2,33,Urban,Software Engineer,41962,0 +65624,Male,55,Diploma,7,97,0,76,44,2.0,3,39,Urban,Manager,65724,0 +65625,Male,51,Bachelors,7,40,26,71,78,5.0,7,91,Semi-Urban,HR Executive,45503,0 +65626,Other,57,High School,14,64,54,23,65,3.0,3,34,Semi-Urban,HR Executive,49767,0 +65627,Male,57,Masters,4,61,19,71,73,4.0,7,3,Semi-Urban,HR Executive,148485,0 +65628,Female,25,Diploma,6,9,70,11,43,3.0,6,72,Urban,Software Engineer,120087,0 +65629,Male,49,Masters,15,92,87,16,61,5.0,1,64,Semi-Urban,HR Executive,74350,1 +65630,Female,47,Bachelors,9,64,12,9,65,5.0,3,79,Urban,ML Engineer,46837,0 +65631,Male,40,Diploma,18,91,60,73,44,8.0,1,29,Urban,Data Analyst,99094,1 +65632,Male,23,Bachelors,16,77,65,3,52,8.0,1,13,Urban,Data Analyst,124775,0 +65633,Male,23,Bachelors,6,69,34,67,46,1.0,0,14,Urban,HR Executive,59949,0 +65634,Female,58,Bachelors,8,83,88,63,28,3.0,0,86,Urban,HR Executive,64096,1 +65635,Female,25,Bachelors,19,63,11,97,3,1.0,6,24,Semi-Urban,ML Engineer,38127,0 +65636,Other,54,Masters,15,46,23,94,35,5.0,5,90,Urban,HR Executive,99284,1 +65637,Female,26,Bachelors,0,80,56,72,34,7.0,6,58,Semi-Urban,ML Engineer,52985,1 +65638,Male,56,High School,17,13,31,95,92,1.0,4,24,Semi-Urban,Manager,33243,0 +65639,Male,52,Bachelors,8,41,44,56,39,8.0,6,28,Rural,ML Engineer,77944,0 +65640,Female,49,Bachelors,8,76,73,68,66,3.0,2,41,Rural,Manager,48410,1 +65641,Female,39,High School,4,30,75,35,63,8.0,6,33,Urban,HR Executive,80173,0 +65642,Female,22,Masters,6,52,11,61,82,5.0,4,73,Rural,ML Engineer,94897,0 +65643,Male,23,Masters,7,55,66,57,71,8.0,4,60,Urban,Software Engineer,72995,1 +65644,Female,53,Masters,9,49,12,95,91,2.0,6,84,Semi-Urban,HR Executive,94810,0 +65645,Male,34,Bachelors,15,97,16,69,10,3.0,5,73,Urban,ML Engineer,35390,1 +65646,Male,36,Masters,10,78,5,96,77,3.0,5,47,Urban,HR Executive,21419,0 +65647,Male,26,Masters,0,6,93,25,73,9.0,6,49,Rural,Manager,140421,0 +65648,Male,50,Masters,11,77,18,48,12,6.0,7,55,Semi-Urban,HR Executive,28473,0 +65649,Female,59,Bachelors,13,10,67,54,45,3.0,2,85,Semi-Urban,HR Executive,149285,0 +65650,Male,59,High School,15,20,55,46,22,2.0,1,5,Rural,Data Analyst,139417,0 +65651,Male,52,High School,1,17,44,35,53,0.0,0,49,Semi-Urban,Manager,81147,0 +65652,Male,47,Bachelors,19,87,54,38,38,2.0,7,51,Rural,Software Engineer,122154,0 +65653,Female,34,High School,17,87,87,73,15,4.0,0,69,Urban,ML Engineer,111282,1 +65654,Male,35,PhD,8,45,13,78,50,4.0,7,8,Rural,HR Executive,124507,0 +65655,Male,37,High School,16,77,24,61,27,0.0,7,71,Urban,Data Analyst,134594,0 +65656,Male,44,Bachelors,7,89,30,20,97,1.0,6,25,Semi-Urban,Software Engineer,132733,0 +65657,Male,54,Bachelors,2,40,64,52,56,6.0,6,4,Urban,Data Analyst,70530,0 +65658,Female,34,Bachelors,7,17,33,42,96,8.0,3,18,Semi-Urban,ML Engineer,39014,0 +65659,Male,29,High School,6,18,33,43,12,0.0,4,61,Rural,HR Executive,20634,0 +65660,Male,24,Masters,19,82,68,6,98,2.0,4,34,Semi-Urban,ML Engineer,124879,0 +65661,Female,23,Bachelors,0,44,73,56,13,5.0,3,79,Urban,Manager,86269,1 +65662,Male,50,PhD,16,84,66,37,43,3.0,5,8,Rural,ML Engineer,42235,0 +65663,Female,52,Bachelors,12,61,49,77,50,9.0,6,19,Urban,Data Analyst,52772,0 +65664,Female,22,High School,6,86,48,86,92,9.0,3,11,Urban,HR Executive,49610,0 +65665,Male,37,Masters,0,31,80,84,38,2.0,6,86,Rural,Manager,114280,1 +65666,Male,52,High School,19,6,76,96,9,7.0,3,99,Semi-Urban,HR Executive,78578,1 +65667,Female,33,Masters,13,27,13,3,40,4.0,7,69,Semi-Urban,Data Analyst,27810,0 +65668,Female,53,Bachelors,0,74,45,44,80,2.0,3,1,Urban,Software Engineer,95934,0 +65669,Female,58,Diploma,17,16,97,78,70,8.0,2,92,Rural,ML Engineer,113833,1 +65670,Female,29,Diploma,10,11,36,99,36,5.0,0,49,Urban,Data Analyst,88051,0 +65671,Male,52,Bachelors,18,23,12,36,58,9.0,0,65,Urban,Software Engineer,138629,0 +65672,Male,47,Diploma,12,38,62,13,78,1.0,5,49,Urban,Manager,127081,0 +65673,Male,43,High School,16,54,3,93,92,7.0,2,36,Rural,Data Analyst,117214,0 +65674,Female,36,Bachelors,8,76,22,96,27,5.0,0,58,Semi-Urban,HR Executive,72411,1 +65675,Female,27,Bachelors,17,25,98,84,74,5.0,6,52,Semi-Urban,Data Analyst,63677,1 +65676,Male,36,Masters,3,27,93,3,14,9.0,0,67,Urban,Software Engineer,42979,0 +65677,Male,35,Masters,1,39,18,25,80,8.0,2,70,Semi-Urban,Manager,104371,0 +65678,Other,31,Bachelors,1,42,95,31,80,4.0,5,87,Urban,ML Engineer,20206,1 +65679,Male,27,High School,13,40,56,27,39,9.0,0,23,Urban,Data Analyst,79213,0 +65680,Male,24,Bachelors,3,58,27,67,28,5.0,1,7,Semi-Urban,Software Engineer,72842,0 +65681,Male,21,Bachelors,8,56,8,78,20,0.0,4,32,Urban,Manager,142083,0 +65682,Male,59,Diploma,1,30,7,58,43,0.0,5,4,Urban,Software Engineer,82354,0 +65683,Male,50,Masters,16,90,35,83,92,6.0,3,11,Semi-Urban,Manager,38313,0 +65684,Male,34,Bachelors,17,60,39,95,6,3.0,5,9,Urban,ML Engineer,57144,0 +65685,Male,28,Diploma,16,78,3,80,33,5.0,3,55,Urban,Software Engineer,138718,0 +65686,Female,36,Diploma,8,50,56,41,41,2.0,6,22,Urban,Manager,124619,0 +65687,Female,26,Bachelors,15,84,96,33,21,5.0,4,27,Urban,ML Engineer,101625,0 +65688,Female,31,Masters,15,23,28,98,31,4.0,1,7,Rural,HR Executive,129475,0 +65689,Female,40,Bachelors,1,55,74,64,40,9.0,0,4,Semi-Urban,Data Analyst,27103,0 +65690,Female,27,Masters,7,54,19,97,41,9.0,5,90,Urban,Manager,82300,1 +65691,Male,47,Bachelors,2,3,0,82,96,6.0,6,96,Urban,HR Executive,128449,0 +65692,Male,34,Bachelors,1,97,23,60,44,6.0,2,65,Rural,Data Analyst,83632,1 +65693,Male,30,Diploma,9,4,64,79,37,8.0,5,62,Urban,ML Engineer,77244,0 +65694,Male,55,Masters,18,64,30,3,21,0.0,5,50,Rural,Software Engineer,85355,0 +65695,Male,35,Diploma,6,67,99,19,32,3.0,0,88,Semi-Urban,HR Executive,115291,1 +65696,Female,48,Diploma,8,56,7,11,50,6.0,6,27,Urban,ML Engineer,99553,0 +65697,Female,44,PhD,13,5,7,95,49,7.0,4,0,Urban,Manager,82560,0 +65698,Male,22,Masters,9,14,67,95,92,8.0,5,25,Urban,ML Engineer,127767,0 +65699,Female,45,Bachelors,2,69,90,19,30,9.0,5,92,Urban,Manager,21504,1 +65700,Male,46,Masters,10,21,85,60,0,8.0,7,51,Urban,HR Executive,65814,0 +65701,Male,27,Bachelors,3,15,35,52,39,3.0,7,37,Rural,Data Analyst,149447,0 +65702,Male,55,PhD,2,73,22,20,94,6.0,0,41,Urban,Data Analyst,143418,0 +65703,Other,47,High School,5,15,48,19,32,9.0,4,7,Urban,Manager,22985,0 +65704,Female,34,Masters,19,13,51,44,26,6.0,5,60,Semi-Urban,Data Analyst,117183,0 +65705,Male,34,Masters,12,50,8,53,42,8.0,3,40,Semi-Urban,Data Analyst,73110,0 +65706,Female,46,Masters,5,89,63,10,39,0.0,3,75,Urban,ML Engineer,69690,0 +65707,Male,56,Diploma,4,60,49,92,14,1.0,4,5,Urban,Software Engineer,78522,0 +65708,Male,30,Masters,15,61,1,80,50,8.0,7,11,Semi-Urban,Manager,97183,0 +65709,Male,22,Masters,11,69,18,69,4,1.0,5,44,Urban,Software Engineer,54863,0 +65710,Female,23,High School,4,11,61,10,97,7.0,6,2,Urban,Software Engineer,23283,0 +65711,Male,44,Masters,3,39,5,28,2,8.0,1,18,Semi-Urban,HR Executive,121398,0 +65712,Male,38,PhD,15,83,73,25,6,6.0,4,8,Urban,HR Executive,67534,0 +65713,Male,33,Bachelors,11,90,95,99,72,1.0,2,16,Semi-Urban,Data Analyst,36749,1 +65714,Male,57,Bachelors,11,66,16,56,55,6.0,2,35,Semi-Urban,Manager,36684,0 +65715,Male,38,Diploma,5,64,63,0,7,6.0,0,22,Semi-Urban,HR Executive,61762,0 +65716,Female,53,Masters,10,45,27,7,13,5.0,4,97,Urban,ML Engineer,101329,0 +65717,Male,50,Bachelors,4,23,58,42,45,4.0,6,34,Urban,ML Engineer,98764,0 +65718,Other,56,Masters,13,99,46,56,10,9.0,0,7,Urban,Data Analyst,38132,0 +65719,Other,45,PhD,7,73,35,77,49,9.0,1,80,Semi-Urban,ML Engineer,56012,1 +65720,Male,52,Masters,1,44,31,12,23,0.0,6,46,Rural,Software Engineer,142442,0 +65721,Male,54,High School,7,92,39,94,73,4.0,3,1,Urban,ML Engineer,65771,0 +65722,Male,28,Masters,2,82,55,65,55,0.0,3,89,Rural,ML Engineer,24077,1 +65723,Male,33,Bachelors,15,14,21,0,94,8.0,1,23,Urban,Manager,42308,0 +65724,Male,56,Masters,8,0,44,14,16,6.0,6,16,Urban,ML Engineer,29390,0 +65725,Male,35,Masters,9,21,19,57,68,1.0,3,58,Urban,HR Executive,39522,0 +65726,Female,30,High School,0,84,79,2,95,7.0,6,87,Semi-Urban,HR Executive,121124,1 +65727,Male,53,Bachelors,17,44,34,55,93,2.0,4,53,Rural,ML Engineer,93384,0 +65728,Male,37,Diploma,17,52,26,35,39,4.0,1,2,Semi-Urban,Software Engineer,110503,0 +65729,Male,49,Bachelors,17,95,32,90,77,5.0,7,13,Urban,Manager,70254,0 +65730,Other,41,PhD,12,40,26,55,89,6.0,3,92,Urban,Data Analyst,101542,0 +65731,Female,39,High School,0,63,15,83,64,5.0,2,59,Urban,Software Engineer,59340,0 +65732,Male,54,Bachelors,13,32,62,95,58,8.0,1,11,Urban,HR Executive,51157,0 +65733,Male,36,Bachelors,19,26,84,20,60,3.0,4,0,Urban,Manager,66480,0 +65734,Male,59,Bachelors,17,36,61,15,89,7.0,7,52,Urban,Software Engineer,105884,0 +65735,Female,57,Bachelors,8,89,53,78,10,2.0,4,30,Urban,Manager,97878,1 +65736,Male,57,High School,1,8,26,98,61,8.0,6,80,Urban,Manager,47540,0 +65737,Female,33,Diploma,9,6,3,66,50,2.0,1,1,Semi-Urban,ML Engineer,84228,0 +65738,Female,36,Bachelors,2,44,69,18,87,5.0,7,39,Urban,Manager,73146,0 +65739,Male,34,Bachelors,13,56,2,64,72,3.0,5,53,Urban,Software Engineer,108970,0 +65740,Female,37,High School,5,15,78,0,11,5.0,1,88,Urban,ML Engineer,121574,0 +65741,Female,48,High School,11,24,97,81,58,9.0,3,93,Urban,ML Engineer,102639,1 +65742,Female,45,High School,8,70,70,87,85,7.0,3,48,Urban,Software Engineer,21588,1 +65743,Other,39,Bachelors,16,7,17,14,61,4.0,0,62,Rural,Manager,106237,0 +65744,Male,21,Diploma,9,54,80,57,84,0.0,5,23,Rural,ML Engineer,49780,0 +65745,Male,33,Bachelors,8,82,97,60,64,1.0,4,52,Urban,Manager,21220,1 +65746,Male,28,Bachelors,14,63,85,53,31,5.0,3,67,Urban,ML Engineer,107564,1 +65747,Male,50,High School,6,76,57,76,68,8.0,4,2,Urban,Software Engineer,126057,0 +65748,Male,29,Bachelors,17,73,91,12,26,9.0,1,36,Semi-Urban,ML Engineer,149401,0 +65749,Female,42,High School,12,66,7,21,32,7.0,2,83,Urban,Manager,94048,0 +65750,Male,39,Masters,12,13,32,99,64,9.0,5,85,Urban,ML Engineer,115144,0 +65751,Male,50,Masters,7,85,84,91,92,0.0,2,3,Urban,HR Executive,47621,1 +65752,Female,23,Bachelors,18,49,85,73,10,3.0,0,65,Semi-Urban,Software Engineer,108885,1 +65753,Female,31,Bachelors,16,48,36,9,9,4.0,6,64,Semi-Urban,Manager,107736,0 +65754,Female,32,Bachelors,11,82,49,31,42,1.0,6,18,Urban,HR Executive,137006,0 +65755,Male,39,High School,17,24,0,20,94,4.0,5,50,Rural,Manager,127830,0 +65756,Male,27,Masters,7,99,37,35,59,0.0,3,8,Semi-Urban,Software Engineer,147753,0 +65757,Male,52,Bachelors,8,95,84,38,60,5.0,0,13,Semi-Urban,Manager,100432,0 +65758,Other,37,Masters,5,45,49,29,92,4.0,3,48,Semi-Urban,ML Engineer,59529,0 +65759,Other,35,Masters,0,77,69,29,49,4.0,5,87,Urban,Data Analyst,61342,1 +65760,Male,26,Diploma,3,6,21,47,58,5.0,2,41,Semi-Urban,Manager,33412,0 +65761,Female,49,Masters,16,73,78,6,26,3.0,6,37,Rural,Software Engineer,111790,0 +65762,Female,41,Diploma,7,1,21,5,66,8.0,5,18,Semi-Urban,HR Executive,28417,0 +65763,Male,59,Diploma,19,23,74,6,8,6.0,4,50,Rural,HR Executive,74539,0 +65764,Female,49,Masters,6,10,30,74,73,0.0,1,8,Urban,ML Engineer,60203,0 +65765,Male,45,Masters,1,47,15,82,66,3.0,1,96,Semi-Urban,ML Engineer,97777,1 +65766,Male,57,Masters,2,99,89,99,19,7.0,7,61,Semi-Urban,Software Engineer,116603,1 +65767,Female,53,Bachelors,8,45,79,13,97,0.0,4,20,Rural,Software Engineer,130173,0 +65768,Female,24,Diploma,17,49,12,45,61,5.0,2,71,Urban,Manager,96538,0 +65769,Female,32,Bachelors,0,36,64,54,7,2.0,3,33,Urban,HR Executive,97639,0 +65770,Male,33,Diploma,15,12,80,72,23,2.0,4,52,Rural,Manager,46844,0 +65771,Male,59,Bachelors,19,34,46,52,42,0.0,2,94,Urban,Manager,20072,0 +65772,Male,40,Diploma,18,25,65,59,40,5.0,0,10,Semi-Urban,Software Engineer,92904,0 +65773,Female,38,Masters,12,35,45,79,30,1.0,3,97,Semi-Urban,Data Analyst,78218,1 +65774,Male,38,High School,18,9,55,69,70,5.0,5,35,Urban,Manager,130251,0 +65775,Male,34,Masters,6,64,38,99,52,1.0,7,58,Urban,Software Engineer,141826,1 +65776,Male,37,High School,16,96,62,12,0,4.0,7,99,Urban,Data Analyst,75937,1 +65777,Male,41,Bachelors,4,15,32,78,16,8.0,5,29,Semi-Urban,HR Executive,139981,0 +65778,Male,46,Diploma,13,74,48,52,5,4.0,3,12,Rural,ML Engineer,31734,0 +65779,Female,56,Bachelors,18,76,3,92,14,5.0,6,33,Semi-Urban,Software Engineer,107588,0 +65780,Male,46,Diploma,16,3,98,67,90,4.0,0,94,Urban,HR Executive,67350,1 +65781,Female,48,Bachelors,8,44,71,61,22,4.0,7,14,Rural,ML Engineer,86796,0 +65782,Male,54,Masters,7,25,33,27,45,6.0,1,20,Urban,ML Engineer,119696,0 +65783,Male,45,Masters,3,19,40,38,91,7.0,0,49,Urban,Software Engineer,28993,0 +65784,Male,28,Diploma,10,96,75,5,56,4.0,5,26,Urban,ML Engineer,98895,0 +65785,Female,25,Diploma,5,86,68,84,97,2.0,6,87,Urban,Manager,113272,1 +65786,Female,48,Bachelors,15,31,70,28,12,0.0,5,74,Rural,HR Executive,94283,0 +65787,Female,54,Bachelors,8,72,62,83,47,8.0,5,7,Urban,Manager,100927,0 +65788,Female,46,Diploma,3,93,38,13,86,9.0,7,96,Urban,Software Engineer,25237,0 +65789,Male,48,Masters,15,75,30,22,89,4.0,0,34,Urban,Data Analyst,21517,0 +65790,Male,56,Diploma,1,80,29,93,37,6.0,6,77,Urban,Software Engineer,40692,1 +65791,Male,47,Diploma,18,67,31,46,85,0.0,0,88,Urban,Manager,39733,0 +65792,Male,37,High School,14,39,47,79,76,1.0,7,22,Urban,ML Engineer,113730,0 +65793,Male,40,Bachelors,11,36,47,6,62,1.0,3,60,Semi-Urban,Manager,71342,0 +65794,Male,34,High School,16,8,31,69,63,9.0,3,49,Semi-Urban,ML Engineer,21647,0 +65795,Male,41,Bachelors,16,54,48,48,18,0.0,5,74,Urban,Software Engineer,73406,0 +65796,Male,52,High School,3,42,3,25,49,3.0,1,20,Semi-Urban,Manager,104692,0 +65797,Male,43,Masters,3,16,74,73,45,7.0,7,16,Rural,Data Analyst,136141,0 +65798,Female,57,Diploma,9,81,62,78,29,0.0,7,77,Urban,Software Engineer,62334,1 +65799,Male,59,Diploma,3,28,44,89,65,6.0,6,20,Semi-Urban,HR Executive,47890,0 +65800,Male,28,High School,2,68,82,33,45,1.0,3,5,Urban,ML Engineer,79843,0 +65801,Other,39,PhD,6,64,30,75,75,1.0,3,45,Urban,Software Engineer,109906,0 +65802,Female,49,Bachelors,5,1,87,50,6,6.0,7,45,Urban,HR Executive,112562,0 +65803,Female,25,PhD,5,96,92,39,33,9.0,7,0,Rural,ML Engineer,79702,0 +65804,Male,52,Masters,13,33,74,73,46,4.0,4,78,Urban,Manager,33863,1 +65805,Female,40,Bachelors,2,54,66,30,21,2.0,6,69,Urban,Manager,62179,0 +65806,Male,39,Bachelors,12,65,5,51,49,6.0,0,83,Semi-Urban,Software Engineer,143924,0 +65807,Male,44,Masters,3,6,73,75,66,5.0,0,22,Rural,Data Analyst,115153,0 +65808,Female,52,Diploma,4,3,87,6,40,3.0,6,60,Semi-Urban,ML Engineer,142927,0 +65809,Male,45,Bachelors,6,51,28,14,3,1.0,5,73,Urban,Manager,139478,0 +65810,Male,47,Bachelors,13,79,20,39,66,8.0,0,53,Urban,Manager,111657,0 +65811,Female,32,Bachelors,11,20,2,28,74,9.0,2,57,Urban,Data Analyst,112911,0 +65812,Female,31,Bachelors,9,39,8,85,67,6.0,2,17,Urban,ML Engineer,25156,0 +65813,Female,33,Masters,12,52,1,40,4,9.0,1,97,Semi-Urban,HR Executive,94579,0 +65814,Female,23,Masters,11,42,4,20,86,1.0,0,65,Urban,Software Engineer,116856,0 +65815,Female,33,Bachelors,8,26,60,33,35,5.0,1,33,Rural,Software Engineer,141108,0 +65816,Male,41,Diploma,4,69,33,54,10,0.0,6,21,Urban,Software Engineer,47288,0 +65817,Male,24,Bachelors,9,37,78,65,48,4.0,0,67,Semi-Urban,Software Engineer,27069,1 +65818,Male,50,Masters,16,16,76,23,79,7.0,3,31,Semi-Urban,Software Engineer,117615,0 +65819,Male,49,Bachelors,11,48,98,27,35,3.0,5,83,Rural,Manager,127493,1 +65820,Female,59,Bachelors,5,52,8,22,53,6.0,1,2,Urban,HR Executive,143626,0 +65821,Male,49,Masters,11,21,55,44,83,4.0,5,50,Urban,Manager,80850,0 +65822,Female,33,Bachelors,2,46,45,54,31,9.0,5,9,Rural,Data Analyst,136858,0 +65823,Female,49,Masters,14,79,55,95,51,6.0,1,82,Semi-Urban,HR Executive,69461,1 +65824,Male,32,Bachelors,8,18,38,72,73,8.0,0,9,Urban,Data Analyst,71370,0 +65825,Male,47,Masters,6,99,27,4,83,5.0,1,7,Urban,Manager,40012,0 +65826,Male,52,Bachelors,14,9,76,27,70,8.0,1,82,Rural,ML Engineer,41661,0 +65827,Male,22,High School,16,49,31,54,5,3.0,5,69,Rural,Software Engineer,47228,0 +65828,Male,28,High School,14,74,23,72,44,0.0,7,29,Urban,Software Engineer,86891,0 +65829,Female,48,Bachelors,13,84,27,38,71,4.0,5,62,Rural,ML Engineer,114795,0 +65830,Male,52,Diploma,15,17,77,23,10,9.0,7,96,Urban,Manager,96391,0 +65831,Male,42,PhD,19,11,34,4,17,8.0,3,21,Semi-Urban,Manager,48719,0 +65832,Male,38,Masters,11,54,46,39,27,9.0,6,33,Semi-Urban,Data Analyst,42730,0 +65833,Male,27,High School,1,28,62,43,30,9.0,5,74,Semi-Urban,ML Engineer,61646,0 +65834,Female,54,Diploma,8,83,18,95,38,3.0,6,45,Semi-Urban,Manager,100121,1 +65835,Female,38,Bachelors,7,66,86,91,50,6.0,0,16,Urban,Software Engineer,57003,1 +65836,Male,39,Masters,16,42,45,70,68,6.0,5,96,Rural,Data Analyst,41202,1 +65837,Other,58,Bachelors,11,85,53,0,76,5.0,7,62,Rural,ML Engineer,100892,0 +65838,Male,37,Bachelors,5,11,6,2,80,5.0,6,93,Urban,HR Executive,66773,0 +65839,Male,39,Masters,18,61,34,8,66,6.0,7,5,Rural,Data Analyst,125852,0 +65840,Male,35,PhD,15,0,80,66,37,2.0,4,12,Urban,Data Analyst,59558,0 +65841,Male,53,High School,5,76,36,13,97,3.0,6,29,Semi-Urban,HR Executive,143896,0 +65842,Male,21,Diploma,5,30,75,95,87,2.0,2,75,Urban,ML Engineer,28723,1 +65843,Female,54,Diploma,14,76,16,29,71,8.0,1,12,Urban,Manager,63672,0 +65844,Male,23,Masters,12,9,85,56,62,9.0,7,14,Urban,ML Engineer,128111,0 +65845,Female,26,Bachelors,6,45,5,5,23,7.0,7,63,Urban,Manager,87502,0 +65846,Male,41,Bachelors,3,39,45,85,43,2.0,2,86,Semi-Urban,Manager,67125,1 +65847,Female,25,Diploma,7,47,67,22,86,4.0,0,25,Urban,ML Engineer,145998,0 +65848,Female,47,Diploma,13,2,30,42,34,7.0,2,89,Semi-Urban,Software Engineer,48587,0 +65849,Male,28,High School,4,59,19,32,19,0.0,7,1,Semi-Urban,ML Engineer,102799,0 +65850,Male,36,Diploma,19,86,17,50,14,8.0,7,35,Urban,HR Executive,143776,0 +65851,Female,35,Bachelors,3,43,2,72,73,1.0,7,48,Urban,HR Executive,107652,0 +65852,Male,30,Diploma,16,23,8,55,94,5.0,3,87,Rural,Software Engineer,24205,0 +65853,Male,24,Bachelors,6,49,49,57,76,5.0,7,84,Urban,HR Executive,94508,1 +65854,Female,38,Bachelors,9,98,91,89,57,9.0,0,50,Semi-Urban,HR Executive,103305,1 +65855,Other,34,Masters,17,70,74,21,36,3.0,2,57,Urban,HR Executive,146647,0 +65856,Female,27,Masters,7,88,45,22,81,6.0,5,57,Urban,Manager,87258,0 +65857,Female,25,High School,17,58,2,40,34,9.0,4,54,Urban,Data Analyst,131302,0 +65858,Male,25,High School,8,53,73,86,87,4.0,0,58,Urban,Manager,64067,1 +65859,Male,27,Bachelors,0,42,53,65,14,0.0,5,36,Urban,Manager,39686,0 +65860,Female,29,Masters,13,40,8,29,65,2.0,5,92,Urban,Software Engineer,84408,0 +65861,Male,40,Masters,14,95,79,72,89,6.0,0,72,Semi-Urban,Data Analyst,23132,1 +65862,Male,42,Bachelors,3,90,35,64,72,9.0,7,6,Semi-Urban,HR Executive,97005,0 +65863,Female,47,High School,16,19,27,23,50,3.0,6,11,Urban,Data Analyst,91505,0 +65864,Male,23,Masters,11,50,91,94,10,9.0,2,75,Semi-Urban,Software Engineer,73649,1 +65865,Female,48,High School,0,96,58,50,90,3.0,2,41,Semi-Urban,ML Engineer,35180,1 +65866,Male,52,Diploma,16,59,13,66,5,4.0,7,67,Semi-Urban,ML Engineer,82010,0 +65867,Male,56,Masters,9,42,28,5,3,3.0,5,17,Rural,HR Executive,64319,0 +65868,Female,25,Diploma,15,68,74,13,43,8.0,7,31,Urban,ML Engineer,57997,0 +65869,Female,32,Masters,18,18,76,14,32,1.0,4,28,Urban,Manager,130704,0 +65870,Male,50,Diploma,3,39,36,31,54,5.0,3,50,Urban,HR Executive,116198,0 +65871,Female,22,Masters,0,55,59,77,35,6.0,5,33,Urban,Data Analyst,114199,0 +65872,Male,27,Bachelors,10,7,37,56,37,1.0,0,34,Semi-Urban,Manager,102283,0 +65873,Male,51,Diploma,2,34,87,53,58,4.0,3,37,Urban,Software Engineer,89566,0 +65874,Male,25,Bachelors,6,94,27,36,83,1.0,3,74,Rural,Manager,113083,0 +65875,Male,45,Diploma,0,20,34,57,26,6.0,3,40,Urban,HR Executive,130975,0 +65876,Male,37,PhD,19,93,37,27,77,2.0,7,73,Semi-Urban,Software Engineer,40514,0 +65877,Female,50,High School,0,95,70,84,54,7.0,4,20,Urban,ML Engineer,80715,1 +65878,Female,50,Bachelors,17,57,29,38,17,4.0,6,41,Semi-Urban,Data Analyst,87539,0 +65879,Female,47,High School,2,27,42,45,77,8.0,5,81,Rural,HR Executive,83012,0 +65880,Female,47,Bachelors,13,55,72,11,28,4.0,6,88,Semi-Urban,HR Executive,70719,0 +65881,Other,49,Diploma,12,27,18,59,70,8.0,2,98,Urban,ML Engineer,129567,0 +65882,Male,42,Bachelors,9,31,97,57,8,0.0,1,61,Urban,Data Analyst,143316,1 +65883,Male,52,Bachelors,0,81,43,88,71,9.0,5,29,Semi-Urban,Manager,31741,1 +65884,Male,32,Diploma,1,86,33,25,11,2.0,1,74,Urban,Manager,128420,0 +65885,Male,53,High School,12,40,19,9,41,5.0,5,39,Urban,ML Engineer,84227,0 +65886,Male,25,Masters,19,40,9,73,74,7.0,5,79,Urban,HR Executive,107568,0 +65887,Female,39,Bachelors,10,46,96,12,29,9.0,0,6,Rural,HR Executive,144882,0 +65888,Female,54,Bachelors,10,42,36,58,69,8.0,6,4,Urban,HR Executive,55709,0 +65889,Male,48,Diploma,3,73,6,99,92,9.0,2,47,Semi-Urban,ML Engineer,82412,0 +65890,Female,55,Masters,11,45,58,64,39,6.0,5,61,Semi-Urban,ML Engineer,51488,0 +65891,Male,34,PhD,8,0,22,15,56,3.0,6,29,Urban,Software Engineer,37490,0 +65892,Male,26,Bachelors,6,9,93,0,75,6.0,0,74,Urban,Data Analyst,147783,0 +65893,Male,38,Masters,7,40,69,20,21,4.0,0,96,Urban,ML Engineer,49450,0 +65894,Male,41,Bachelors,16,64,44,99,81,1.0,5,61,Rural,Data Analyst,40022,1 +65895,Male,25,Bachelors,16,92,93,76,82,4.0,2,12,Urban,Software Engineer,145443,1 +65896,Female,53,Bachelors,13,83,94,91,46,7.0,0,19,Urban,Manager,113508,1 +65897,Female,26,Bachelors,7,14,64,63,80,3.0,4,82,Urban,Manager,80504,0 +65898,Male,43,Bachelors,5,80,53,35,25,8.0,7,19,Urban,Software Engineer,64756,0 +65899,Male,21,PhD,8,19,93,33,83,4.0,6,66,Rural,Manager,61758,0 +65900,Female,50,PhD,0,99,12,88,6,1.0,5,24,Urban,Manager,88082,0 +65901,Female,40,Diploma,7,18,27,87,7,8.0,4,48,Urban,Software Engineer,52563,0 +65902,Male,27,High School,0,41,21,75,2,2.0,1,72,Urban,Data Analyst,72668,0 +65903,Male,33,High School,0,25,16,21,26,3.0,6,55,Urban,Software Engineer,143945,0 +65904,Female,21,Bachelors,0,71,29,61,78,0.0,0,1,Urban,Software Engineer,71005,0 +65905,Female,34,Masters,12,74,89,40,88,5.0,1,36,Urban,ML Engineer,85396,0 +65906,Female,22,Bachelors,16,80,21,22,61,0.0,7,97,Semi-Urban,ML Engineer,146073,0 +65907,Male,38,Bachelors,0,95,26,49,97,0.0,3,11,Urban,Software Engineer,69815,0 +65908,Female,51,Masters,12,21,4,98,19,5.0,5,28,Rural,ML Engineer,121202,0 +65909,Male,38,High School,14,3,54,34,27,0.0,4,39,Semi-Urban,HR Executive,93387,0 +65910,Female,43,Masters,17,37,94,8,53,4.0,5,76,Urban,Manager,23906,0 +65911,Male,30,Diploma,11,14,40,7,5,0.0,4,90,Rural,ML Engineer,141641,0 +65912,Female,36,Masters,16,63,4,43,70,8.0,4,93,Rural,ML Engineer,57358,0 +65913,Male,28,Masters,0,59,18,26,19,1.0,7,31,Urban,ML Engineer,105833,0 +65914,Female,43,Bachelors,5,40,41,56,68,0.0,5,54,Semi-Urban,ML Engineer,76532,0 +65915,Female,21,Diploma,18,79,42,15,46,0.0,4,17,Rural,Data Analyst,72682,0 +65916,Female,46,Bachelors,18,65,55,79,61,3.0,2,5,Urban,Data Analyst,39113,0 +65917,Female,23,High School,19,4,54,78,66,4.0,2,43,Urban,Software Engineer,26195,0 +65918,Male,39,Bachelors,16,23,18,68,12,0.0,1,50,Rural,Software Engineer,47022,0 +65919,Female,40,Bachelors,1,88,64,93,77,9.0,4,64,Semi-Urban,ML Engineer,87068,1 +65920,Male,56,High School,4,60,71,35,3,4.0,7,6,Urban,Software Engineer,22007,0 +65921,Female,36,Bachelors,7,97,97,7,89,1.0,2,83,Urban,Manager,77865,1 +65922,Female,27,Bachelors,5,39,10,29,75,2.0,4,3,Urban,Data Analyst,30825,0 +65923,Male,33,Bachelors,5,97,55,36,74,4.0,3,57,Urban,Data Analyst,26607,1 +65924,Other,41,Masters,4,0,49,29,72,7.0,5,65,Urban,Manager,40932,0 +65925,Male,32,Diploma,9,49,18,61,25,0.0,0,31,Urban,Manager,130765,0 +65926,Male,47,Bachelors,10,50,67,8,53,6.0,0,27,Urban,Manager,130804,0 +65927,Male,36,Diploma,5,18,37,53,22,1.0,5,1,Urban,Manager,123720,0 +65928,Male,27,Masters,7,8,95,51,84,2.0,6,34,Semi-Urban,Manager,52104,0 +65929,Male,39,Bachelors,18,33,96,11,55,5.0,5,20,Urban,Software Engineer,134320,0 +65930,Male,51,Diploma,19,0,90,54,46,4.0,5,73,Urban,HR Executive,75987,0 +65931,Male,57,Masters,10,48,18,41,29,9.0,4,78,Urban,HR Executive,133218,0 +65932,Female,35,Bachelors,11,84,1,56,86,6.0,5,50,Rural,HR Executive,81314,0 +65933,Male,41,Bachelors,4,64,88,11,41,7.0,6,64,Rural,Manager,47411,0 +65934,Male,54,Bachelors,11,99,69,22,64,0.0,4,5,Rural,HR Executive,112932,0 +65935,Male,39,Masters,3,10,24,54,52,1.0,0,46,Semi-Urban,Software Engineer,146287,0 +65936,Female,52,Diploma,14,31,67,72,61,7.0,6,16,Semi-Urban,Manager,116533,0 +65937,Female,31,Diploma,1,97,45,10,26,1.0,4,77,Semi-Urban,Data Analyst,66673,0 +65938,Male,22,High School,19,48,16,31,77,2.0,5,39,Urban,ML Engineer,104141,0 +65939,Female,53,Bachelors,2,77,15,55,41,9.0,7,0,Rural,Data Analyst,120889,0 +65940,Male,40,Bachelors,16,31,81,30,39,5.0,5,93,Urban,ML Engineer,69135,1 +65941,Male,49,Bachelors,12,18,83,0,34,0.0,3,22,Urban,ML Engineer,94016,0 +65942,Male,46,Diploma,14,18,30,66,50,7.0,0,15,Semi-Urban,Software Engineer,87324,0 +65943,Female,30,PhD,17,51,4,53,32,3.0,5,9,Urban,Data Analyst,105518,0 +65944,Male,22,High School,13,9,53,62,76,1.0,7,17,Rural,Manager,137870,0 +65945,Female,46,Bachelors,5,56,66,32,96,0.0,7,86,Urban,Manager,104347,0 +65946,Other,41,Bachelors,18,61,84,77,6,0.0,0,11,Urban,Manager,87278,0 +65947,Male,58,Bachelors,10,14,41,48,37,5.0,0,54,Urban,HR Executive,137468,0 +65948,Male,25,Bachelors,14,33,20,64,54,4.0,4,26,Semi-Urban,HR Executive,140719,0 +65949,Male,38,High School,13,14,25,46,21,2.0,7,58,Semi-Urban,Data Analyst,108878,0 +65950,Female,51,Diploma,4,32,46,76,50,2.0,3,22,Semi-Urban,HR Executive,55005,0 +65951,Female,46,Bachelors,17,61,94,75,87,0.0,6,51,Urban,Data Analyst,93389,1 +65952,Female,51,Diploma,16,65,89,50,50,8.0,4,33,Semi-Urban,HR Executive,72554,0 +65953,Female,32,Bachelors,18,18,97,23,73,6.0,3,54,Urban,HR Executive,61999,0 +65954,Male,47,Bachelors,18,66,11,4,49,6.0,2,36,Urban,Software Engineer,20267,0 +65955,Other,21,Masters,10,37,83,53,22,1.0,2,50,Urban,HR Executive,113131,0 +65956,Male,23,Bachelors,2,74,39,87,98,3.0,3,63,Urban,Manager,135209,1 +65957,Male,31,Masters,0,16,5,6,9,1.0,3,11,Semi-Urban,ML Engineer,140238,0 +65958,Male,49,High School,7,86,94,54,57,8.0,5,27,Urban,Data Analyst,75254,1 +65959,Male,24,High School,10,24,80,69,56,3.0,4,36,Semi-Urban,Data Analyst,102111,0 +65960,Male,24,Diploma,8,28,14,47,5,4.0,2,45,Urban,Manager,78948,0 +65961,Male,44,Masters,7,53,58,29,23,7.0,2,91,Semi-Urban,HR Executive,118613,0 +65962,Male,43,Masters,10,1,7,14,92,3.0,2,0,Urban,Manager,27418,0 +65963,Male,29,Bachelors,16,12,36,1,44,5.0,5,66,Urban,ML Engineer,132313,0 +65964,Male,28,High School,11,74,38,49,58,0.0,0,22,Rural,Data Analyst,115392,0 +65965,Male,47,Masters,13,97,54,2,50,4.0,3,60,Semi-Urban,Software Engineer,143746,0 +65966,Female,29,High School,16,98,56,2,31,2.0,7,43,Semi-Urban,Data Analyst,67584,0 +65967,Female,52,Masters,3,88,1,62,5,7.0,5,38,Semi-Urban,ML Engineer,98966,0 +65968,Male,26,Diploma,15,29,21,79,21,0.0,5,85,Urban,Manager,66713,0 +65969,Male,43,Diploma,5,6,54,93,80,4.0,5,17,Urban,Software Engineer,44415,0 +65970,Female,33,Bachelors,5,80,83,71,64,7.0,0,49,Urban,HR Executive,132955,1 +65971,Male,24,Bachelors,7,6,90,44,18,8.0,7,3,Semi-Urban,Data Analyst,147320,0 +65972,Male,38,Diploma,11,17,14,82,55,5.0,3,25,Urban,HR Executive,22439,0 +65973,Female,39,Masters,11,70,9,86,34,7.0,7,78,Urban,Manager,101390,1 +65974,Male,46,Bachelors,2,33,8,57,25,0.0,5,48,Urban,Software Engineer,118777,0 +65975,Female,57,Bachelors,12,13,69,18,61,6.0,4,33,Urban,Manager,120117,0 +65976,Male,40,Masters,3,26,58,58,58,2.0,4,38,Rural,Software Engineer,25835,0 +65977,Female,37,High School,11,43,18,8,95,1.0,1,70,Urban,Manager,82471,0 +65978,Male,47,Bachelors,10,98,19,6,64,2.0,3,98,Urban,Data Analyst,112689,0 +65979,Other,42,Bachelors,4,39,91,16,36,4.0,7,19,Urban,ML Engineer,117971,0 +65980,Female,21,Bachelors,3,43,31,94,74,6.0,4,59,Urban,Software Engineer,21956,0 +65981,Male,37,Diploma,9,78,17,14,81,3.0,4,98,Urban,ML Engineer,90586,0 +65982,Female,43,Bachelors,2,84,75,83,68,5.0,0,11,Urban,HR Executive,30406,1 +65983,Female,26,Bachelors,13,15,23,34,79,2.0,4,87,Urban,Manager,42752,0 +65984,Male,37,Bachelors,5,40,63,68,54,2.0,7,84,Semi-Urban,HR Executive,36576,1 +65985,Female,21,Diploma,13,45,45,14,18,9.0,5,32,Semi-Urban,ML Engineer,116525,0 +65986,Male,35,Masters,15,58,50,23,32,0.0,2,95,Urban,Data Analyst,104391,0 +65987,Male,54,Diploma,18,4,52,91,41,0.0,6,44,Urban,ML Engineer,123331,0 +65988,Male,56,Bachelors,8,3,24,71,42,3.0,1,50,Urban,Software Engineer,112779,0 +65989,Female,34,Masters,1,94,69,9,36,0.0,6,35,Semi-Urban,Data Analyst,40210,0 +65990,Other,49,Masters,5,47,57,94,75,9.0,2,85,Urban,Software Engineer,26045,1 +65991,Female,59,Bachelors,13,19,38,44,15,6.0,1,89,Urban,ML Engineer,29089,0 +65992,Male,50,Bachelors,17,2,59,13,82,4.0,7,50,Rural,Software Engineer,35390,0 +65993,Other,49,Diploma,7,88,54,35,9,3.0,2,80,Urban,Data Analyst,116998,1 +65994,Male,49,Bachelors,1,24,20,86,92,7.0,6,48,Rural,Data Analyst,78502,0 +65995,Male,54,High School,13,68,16,46,84,8.0,6,33,Urban,HR Executive,122271,0 +65996,Male,48,Bachelors,3,37,59,11,97,9.0,5,41,Urban,HR Executive,22092,0 +65997,Other,44,Masters,0,99,38,50,79,4.0,3,40,Rural,Software Engineer,118425,0 +65998,Female,33,Masters,5,97,36,0,5,2.0,3,29,Urban,ML Engineer,110296,0 +65999,Male,39,Bachelors,8,33,55,87,14,0.0,4,13,Urban,Manager,125752,0 +66000,Female,59,High School,1,52,77,71,96,5.0,5,21,Rural,ML Engineer,53091,0 +66001,Male,57,Diploma,3,13,78,58,38,2.0,5,43,Semi-Urban,Data Analyst,83762,0 +66002,Male,25,Masters,17,44,0,47,79,0.0,3,20,Urban,HR Executive,146688,0 +66003,Male,32,High School,13,90,99,87,24,7.0,4,61,Semi-Urban,Manager,29592,1 +66004,Male,27,Bachelors,5,17,18,98,78,8.0,0,52,Urban,Data Analyst,33847,0 +66005,Male,43,High School,7,93,44,15,72,3.0,2,44,Rural,ML Engineer,99887,0 +66006,Female,53,Bachelors,11,87,91,34,48,9.0,5,94,Rural,Software Engineer,57028,1 +66007,Male,51,Masters,16,27,44,66,12,4.0,7,29,Urban,ML Engineer,66508,0 +66008,Male,59,Masters,14,43,94,49,15,1.0,4,54,Urban,ML Engineer,111221,1 +66009,Female,24,Masters,10,27,39,79,18,9.0,3,44,Semi-Urban,ML Engineer,105215,0 +66010,Male,22,Bachelors,9,6,42,73,72,6.0,6,79,Rural,Data Analyst,83889,0 +66011,Male,41,Bachelors,4,97,56,21,42,2.0,2,76,Urban,ML Engineer,89058,1 +66012,Male,23,Masters,8,31,37,88,92,0.0,4,8,Rural,Software Engineer,38297,0 +66013,Male,39,High School,2,76,59,35,71,8.0,5,27,Urban,Software Engineer,20039,0 +66014,Male,21,Diploma,10,48,52,79,86,1.0,4,75,Semi-Urban,Data Analyst,120360,1 +66015,Male,44,Masters,18,82,82,59,56,2.0,0,14,Urban,Manager,96899,1 +66016,Male,52,Diploma,17,20,31,28,19,2.0,2,90,Urban,Manager,54779,0 +66017,Male,47,PhD,11,46,98,53,28,5.0,4,66,Urban,Manager,62511,1 +66018,Female,23,Masters,3,64,68,64,45,2.0,5,91,Urban,Software Engineer,131474,1 +66019,Male,45,Bachelors,13,16,71,71,6,5.0,5,21,Urban,Data Analyst,133663,0 +66020,Male,26,High School,14,29,49,63,56,0.0,0,93,Urban,Data Analyst,20189,0 +66021,Female,54,High School,12,62,93,7,55,2.0,2,49,Urban,HR Executive,82612,0 +66022,Female,22,Bachelors,5,6,15,91,25,5.0,5,3,Semi-Urban,ML Engineer,83203,0 +66023,Male,38,High School,3,70,94,21,40,9.0,3,98,Urban,Data Analyst,74916,1 +66024,Female,46,Bachelors,4,24,2,0,48,9.0,1,52,Urban,HR Executive,115091,0 +66025,Female,36,High School,17,96,94,35,17,6.0,3,16,Semi-Urban,Software Engineer,92676,1 +66026,Male,45,Diploma,13,56,99,24,67,6.0,1,2,Semi-Urban,ML Engineer,23938,0 +66027,Female,24,Bachelors,10,67,12,19,50,3.0,7,47,Urban,Data Analyst,109248,0 +66028,Male,34,Bachelors,6,13,60,26,29,5.0,6,91,Rural,HR Executive,58226,0 +66029,Male,24,High School,13,99,8,16,45,3.0,6,11,Urban,Data Analyst,52901,0 +66030,Female,23,High School,14,18,77,70,2,4.0,5,85,Rural,Software Engineer,64196,1 +66031,Female,59,High School,8,37,32,19,98,0.0,2,64,Semi-Urban,ML Engineer,73943,0 +66032,Male,25,High School,9,99,99,53,26,0.0,1,92,Semi-Urban,HR Executive,57297,1 +66033,Male,22,Diploma,2,69,24,39,42,6.0,1,22,Urban,ML Engineer,64229,0 +66034,Male,23,Diploma,16,5,28,93,62,0.0,5,71,Urban,Software Engineer,78128,0 +66035,Male,38,High School,2,48,5,2,61,2.0,1,76,Urban,Data Analyst,32723,0 +66036,Male,23,Diploma,17,69,39,35,47,4.0,0,45,Urban,Software Engineer,121990,0 +66037,Female,23,Diploma,2,7,51,99,38,0.0,7,0,Urban,Software Engineer,32238,0 +66038,Male,45,Diploma,8,61,59,64,25,7.0,6,80,Urban,Software Engineer,142302,1 +66039,Male,28,High School,4,18,9,55,95,7.0,1,27,Rural,HR Executive,147030,0 +66040,Male,58,Bachelors,2,18,19,91,96,8.0,3,54,Rural,ML Engineer,47223,0 +66041,Male,52,Bachelors,6,52,18,26,38,0.0,7,50,Rural,Manager,143134,0 +66042,Male,47,Masters,3,21,51,96,58,4.0,4,47,Rural,Software Engineer,53521,0 +66043,Male,26,Bachelors,4,31,20,53,19,4.0,2,35,Semi-Urban,ML Engineer,65074,0 +66044,Other,47,Diploma,15,89,96,51,68,7.0,7,99,Urban,ML Engineer,131002,1 +66045,Male,24,Bachelors,8,71,39,27,60,4.0,7,44,Semi-Urban,Software Engineer,21711,0 +66046,Male,30,High School,10,48,88,16,48,5.0,5,19,Semi-Urban,Software Engineer,127327,0 +66047,Male,40,Masters,12,51,4,36,88,2.0,3,28,Urban,Data Analyst,140067,0 +66048,Male,37,Diploma,16,59,6,92,23,3.0,2,97,Urban,Software Engineer,131505,1 +66049,Male,33,Bachelors,0,14,80,54,13,8.0,7,16,Urban,ML Engineer,22790,0 +66050,Female,28,High School,11,75,96,99,88,0.0,4,53,Urban,Software Engineer,109462,1 +66051,Female,55,Bachelors,1,84,23,8,4,3.0,4,2,Urban,ML Engineer,60239,0 +66052,Male,48,Bachelors,8,48,95,96,52,2.0,5,28,Urban,Manager,91945,1 +66053,Female,50,Bachelors,1,16,2,19,66,5.0,4,44,Urban,Software Engineer,116719,0 +66054,Female,58,PhD,13,92,91,36,56,8.0,5,48,Rural,HR Executive,32597,1 +66055,Male,59,High School,8,65,23,21,29,7.0,5,20,Urban,Software Engineer,112073,0 +66056,Male,29,Masters,18,98,62,44,14,0.0,5,2,Rural,ML Engineer,102412,0 +66057,Male,39,Bachelors,13,55,54,94,19,7.0,0,14,Urban,HR Executive,111998,0 +66058,Male,40,Bachelors,11,53,58,84,0,6.0,2,45,Semi-Urban,Data Analyst,89043,1 +66059,Male,28,Masters,9,59,97,77,22,5.0,2,68,Urban,ML Engineer,115475,1 +66060,Female,36,Masters,14,33,85,2,69,3.0,6,75,Rural,Software Engineer,60920,0 +66061,Male,41,Bachelors,12,74,10,45,17,6.0,5,38,Urban,Data Analyst,80003,0 +66062,Male,50,Bachelors,13,44,37,95,22,4.0,5,91,Rural,ML Engineer,93204,1 +66063,Male,21,Bachelors,13,69,81,30,47,4.0,4,38,Urban,ML Engineer,78579,0 +66064,Male,49,High School,8,43,26,73,97,6.0,3,87,Semi-Urban,Data Analyst,79729,0 +66065,Female,51,High School,1,42,22,63,38,0.0,2,42,Urban,HR Executive,81816,0 +66066,Female,54,Diploma,5,36,7,46,66,6.0,3,34,Urban,Data Analyst,80360,0 +66067,Female,51,High School,19,58,55,78,9,1.0,5,14,Urban,Manager,127372,0 +66068,Female,39,Diploma,16,91,74,14,81,5.0,6,99,Semi-Urban,Data Analyst,140034,1 +66069,Male,33,Bachelors,2,45,40,87,22,4.0,6,65,Urban,Software Engineer,25984,1 +66070,Female,44,High School,19,0,47,52,16,0.0,5,56,Urban,Data Analyst,33860,0 +66071,Male,50,Diploma,19,52,50,22,2,2.0,7,13,Urban,Data Analyst,68935,0 +66072,Male,55,Bachelors,9,93,29,44,71,7.0,5,83,Urban,Software Engineer,91804,1 +66073,Male,33,Bachelors,14,48,69,3,43,9.0,5,21,Semi-Urban,Data Analyst,83516,0 +66074,Male,23,High School,13,87,97,35,89,9.0,7,65,Urban,HR Executive,88667,1 +66075,Male,57,Masters,19,50,76,27,57,0.0,1,50,Urban,Manager,62971,0 +66076,Female,31,Diploma,9,48,69,18,70,2.0,4,39,Urban,Software Engineer,24006,0 +66077,Female,36,PhD,19,83,48,6,16,1.0,3,15,Semi-Urban,ML Engineer,31927,0 +66078,Male,38,Diploma,16,90,8,18,91,4.0,0,96,Urban,ML Engineer,72531,0 +66079,Male,41,Bachelors,19,31,67,16,15,3.0,6,67,Urban,Software Engineer,86882,0 +66080,Male,52,High School,16,95,69,83,43,8.0,2,48,Urban,HR Executive,77637,1 +66081,Male,49,Masters,14,30,66,87,58,7.0,6,28,Urban,HR Executive,95328,0 +66082,Female,55,Bachelors,6,19,52,21,54,3.0,2,70,Rural,ML Engineer,139356,0 +66083,Male,30,Masters,15,1,56,45,86,5.0,5,63,Urban,Software Engineer,87125,0 +66084,Female,49,Bachelors,15,91,71,12,31,0.0,2,86,Urban,ML Engineer,70291,1 +66085,Male,54,Bachelors,12,9,8,90,69,8.0,3,97,Urban,ML Engineer,45909,0 +66086,Male,29,Bachelors,6,86,38,61,58,5.0,4,60,Semi-Urban,ML Engineer,46559,1 +66087,Female,41,Diploma,8,16,81,38,52,3.0,6,95,Semi-Urban,Manager,40889,0 +66088,Male,39,Bachelors,6,38,15,65,1,6.0,7,39,Semi-Urban,HR Executive,59901,0 +66089,Male,22,High School,1,30,6,35,86,5.0,0,5,Rural,Manager,88260,0 +66090,Female,23,High School,6,70,67,57,90,8.0,0,79,Semi-Urban,Software Engineer,102016,1 +66091,Male,22,Diploma,7,16,81,21,75,8.0,0,15,Semi-Urban,Data Analyst,131662,0 +66092,Male,38,Masters,12,92,19,95,66,7.0,5,75,Semi-Urban,Manager,65403,1 +66093,Female,47,Bachelors,19,27,31,6,11,9.0,5,92,Urban,Manager,106276,0 +66094,Male,42,Masters,9,78,30,63,70,1.0,6,4,Urban,HR Executive,142335,0 +66095,Other,34,Masters,3,2,20,99,7,3.0,4,82,Urban,ML Engineer,83089,0 +66096,Male,37,Masters,9,53,56,23,97,3.0,7,6,Urban,Manager,59162,0 +66097,Female,45,Diploma,12,58,48,27,9,2.0,1,87,Urban,Manager,50859,0 +66098,Male,21,Diploma,14,12,26,23,89,0.0,5,13,Urban,HR Executive,118442,0 +66099,Male,51,Masters,11,17,68,3,56,4.0,0,15,Urban,Data Analyst,94166,0 +66100,Female,43,High School,2,15,67,24,19,8.0,5,2,Urban,HR Executive,105446,0 +66101,Male,46,Masters,0,84,83,7,46,5.0,2,83,Rural,Software Engineer,149272,1 +66102,Female,48,Diploma,19,83,96,60,7,2.0,1,49,Urban,Data Analyst,125224,1 +66103,Male,36,Masters,2,8,58,34,36,8.0,6,34,Urban,HR Executive,64580,0 +66104,Male,44,Bachelors,11,88,32,96,3,0.0,7,60,Urban,HR Executive,24103,1 +66105,Male,59,Diploma,18,80,54,51,35,3.0,5,83,Urban,ML Engineer,106086,1 +66106,Female,58,High School,7,53,56,45,43,0.0,7,34,Urban,HR Executive,22643,0 +66107,Female,30,High School,9,48,47,25,77,0.0,3,91,Semi-Urban,ML Engineer,131579,0 +66108,Male,53,Bachelors,14,19,50,6,74,7.0,7,30,Urban,Data Analyst,84754,0 +66109,Female,32,Diploma,1,61,24,62,54,5.0,0,8,Urban,Manager,88226,0 +66110,Male,36,Bachelors,11,11,27,61,59,2.0,4,57,Urban,Manager,27894,0 +66111,Female,39,Diploma,17,98,45,40,54,3.0,2,33,Rural,Software Engineer,146811,0 +66112,Male,29,Bachelors,19,99,73,4,50,8.0,0,76,Urban,Software Engineer,100913,1 +66113,Male,22,High School,3,25,4,21,11,4.0,6,84,Semi-Urban,Manager,65944,0 +66114,Male,49,Masters,6,95,63,72,72,4.0,3,69,Urban,Software Engineer,25491,1 +66115,Male,31,High School,19,58,84,69,95,4.0,1,94,Urban,ML Engineer,98191,1 +66116,Female,25,Bachelors,7,16,32,29,34,6.0,5,62,Urban,Data Analyst,76776,0 +66117,Female,26,Bachelors,17,34,73,9,28,9.0,2,69,Urban,Data Analyst,36889,0 +66118,Female,54,Bachelors,10,6,56,52,64,6.0,6,68,Urban,Data Analyst,56118,0 +66119,Male,42,High School,10,29,37,2,61,2.0,7,2,Rural,Data Analyst,95574,0 +66120,Female,27,Bachelors,9,55,46,29,78,4.0,2,0,Urban,HR Executive,97296,0 +66121,Male,53,Bachelors,7,42,22,66,84,3.0,4,30,Semi-Urban,ML Engineer,55199,0 +66122,Female,46,High School,9,23,12,87,65,8.0,0,55,Rural,HR Executive,27894,0 +66123,Male,38,Diploma,15,85,67,62,15,2.0,7,90,Urban,ML Engineer,59189,1 +66124,Male,49,Bachelors,13,36,2,37,9,9.0,0,38,Semi-Urban,Software Engineer,67260,0 +66125,Female,44,Bachelors,0,53,91,23,86,9.0,3,82,Urban,HR Executive,69120,1 +66126,Male,31,Diploma,19,11,26,62,50,5.0,1,66,Urban,Software Engineer,103352,0 +66127,Female,36,Masters,13,99,68,64,81,7.0,0,26,Semi-Urban,Manager,65116,1 +66128,Male,22,High School,0,90,58,83,45,3.0,6,50,Semi-Urban,Manager,86077,1 +66129,Female,40,Masters,6,10,11,38,74,7.0,3,71,Semi-Urban,HR Executive,68776,0 +66130,Male,23,PhD,7,19,3,98,33,6.0,7,9,Rural,ML Engineer,124152,0 +66131,Male,51,Masters,7,76,47,94,80,2.0,5,38,Urban,Software Engineer,135070,1 +66132,Male,55,High School,15,67,25,62,5,0.0,1,60,Urban,Data Analyst,94535,0 +66133,Female,57,Diploma,17,96,57,75,53,5.0,4,31,Urban,HR Executive,132887,1 +66134,Male,41,High School,14,54,50,87,60,5.0,0,22,Semi-Urban,Data Analyst,75858,0 +66135,Male,53,Masters,12,36,54,69,55,5.0,6,0,Rural,Manager,50114,0 +66136,Female,31,Diploma,5,77,98,2,23,3.0,7,51,Semi-Urban,HR Executive,100486,0 +66137,Male,57,Bachelors,10,82,23,81,54,0.0,5,19,Urban,Data Analyst,68965,0 +66138,Female,22,Masters,3,59,14,94,22,7.0,0,67,Urban,HR Executive,62161,0 +66139,Male,28,Bachelors,9,89,97,58,15,1.0,1,24,Urban,ML Engineer,102173,1 +66140,Male,29,Masters,6,10,64,36,21,9.0,1,83,Rural,ML Engineer,23263,0 +66141,Male,57,Bachelors,9,7,22,45,52,4.0,1,45,Semi-Urban,Software Engineer,30854,0 +66142,Female,53,Bachelors,5,54,90,42,7,7.0,6,23,Semi-Urban,Data Analyst,88760,0 +66143,Male,51,High School,12,47,58,36,84,7.0,3,66,Urban,HR Executive,31867,0 +66144,Female,34,Diploma,6,42,30,72,13,5.0,7,4,Urban,Manager,97665,0 +66145,Female,46,Diploma,2,34,96,82,37,8.0,0,6,Urban,Data Analyst,27345,0 +66146,Female,29,Masters,2,36,39,95,63,0.0,5,27,Rural,HR Executive,44969,0 +66147,Female,47,Masters,18,49,79,28,33,0.0,7,90,Urban,Software Engineer,68494,1 +66148,Female,48,Bachelors,7,78,85,34,74,7.0,1,97,Urban,Manager,104491,1 +66149,Male,24,Diploma,14,11,7,19,34,4.0,7,8,Urban,Manager,107122,0 +66150,Male,52,Masters,7,81,7,24,10,7.0,5,81,Urban,Software Engineer,131336,0 +66151,Male,29,Bachelors,15,92,4,8,82,6.0,3,8,Urban,Software Engineer,149870,0 +66152,Female,45,High School,5,0,51,31,43,1.0,4,5,Urban,HR Executive,75734,0 +66153,Female,38,Bachelors,19,2,81,6,51,8.0,0,57,Urban,ML Engineer,124345,0 +66154,Female,54,Diploma,4,13,27,1,67,8.0,1,13,Rural,ML Engineer,117078,0 +66155,Male,48,Bachelors,18,33,8,35,26,8.0,2,19,Urban,Data Analyst,133526,0 +66156,Male,32,High School,15,9,20,56,20,7.0,5,7,Urban,Manager,29031,0 +66157,Female,46,Bachelors,0,5,16,40,34,4.0,3,61,Urban,Manager,145431,0 +66158,Male,37,Bachelors,10,18,69,23,14,7.0,6,76,Semi-Urban,Software Engineer,131719,0 +66159,Female,59,Diploma,3,23,19,82,6,8.0,7,60,Urban,Software Engineer,20117,0 +66160,Male,49,Bachelors,16,78,81,70,39,0.0,3,32,Semi-Urban,Data Analyst,131850,1 +66161,Male,57,Bachelors,5,35,97,72,95,5.0,6,1,Urban,Software Engineer,75358,0 +66162,Female,53,Bachelors,0,61,90,76,1,2.0,6,92,Urban,Data Analyst,62445,1 +66163,Male,26,High School,17,60,79,77,48,9.0,7,57,Semi-Urban,Data Analyst,120146,1 +66164,Female,27,High School,16,87,36,96,15,3.0,1,54,Urban,Manager,52457,1 +66165,Male,46,Bachelors,3,78,87,51,35,7.0,3,67,Urban,ML Engineer,47796,1 +66166,Male,28,Bachelors,3,34,99,91,37,1.0,5,48,Urban,Manager,87964,1 +66167,Female,58,Bachelors,8,54,85,28,39,2.0,5,75,Urban,HR Executive,130857,1 +66168,Female,59,PhD,0,57,2,31,90,7.0,5,57,Urban,Data Analyst,63028,0 +66169,Female,58,Bachelors,5,12,29,5,45,3.0,6,96,Rural,ML Engineer,30312,0 +66170,Female,55,Bachelors,10,64,34,7,6,0.0,7,26,Urban,Manager,35650,0 +66171,Female,53,Masters,9,34,6,85,7,4.0,6,15,Urban,Data Analyst,28647,0 +66172,Female,39,Bachelors,8,17,35,16,38,9.0,2,74,Urban,ML Engineer,66907,0 +66173,Male,51,Bachelors,8,31,45,29,11,7.0,4,60,Semi-Urban,Manager,39345,0 +66174,Male,21,Bachelors,16,34,95,15,56,6.0,5,19,Rural,Manager,49091,0 +66175,Male,57,High School,16,67,59,86,57,4.0,3,55,Urban,Data Analyst,113221,1 +66176,Female,32,Diploma,17,34,56,86,33,7.0,5,16,Semi-Urban,Manager,27517,0 +66177,Male,59,High School,15,62,31,82,66,1.0,5,62,Urban,ML Engineer,138478,1 +66178,Male,29,High School,19,4,23,37,38,6.0,5,34,Urban,Software Engineer,140200,0 +66179,Male,49,High School,5,54,62,86,74,2.0,4,9,Urban,HR Executive,20447,0 +66180,Male,38,Bachelors,10,98,35,8,84,8.0,7,5,Urban,Manager,70716,0 +66181,Female,21,Masters,17,11,62,42,75,2.0,1,65,Urban,Software Engineer,130859,0 +66182,Female,58,Bachelors,3,77,52,56,36,8.0,5,16,Semi-Urban,ML Engineer,67455,0 +66183,Female,42,Masters,4,86,72,3,14,2.0,1,87,Urban,Data Analyst,149038,1 +66184,Female,25,Masters,18,47,53,60,21,2.0,0,35,Urban,Manager,20286,0 +66185,Male,46,Masters,11,79,77,27,44,2.0,7,80,Semi-Urban,ML Engineer,35110,1 +66186,Female,53,Masters,15,38,61,77,49,3.0,3,85,Urban,Software Engineer,106697,1 +66187,Male,51,High School,5,71,64,44,57,4.0,6,98,Urban,ML Engineer,78930,1 +66188,Female,51,Bachelors,18,78,62,92,90,5.0,3,90,Rural,ML Engineer,64942,1 +66189,Male,59,Bachelors,9,7,84,85,99,3.0,5,51,Urban,Data Analyst,62227,0 +66190,Male,32,Bachelors,15,87,47,88,10,5.0,3,79,Urban,HR Executive,103820,1 +66191,Male,34,Bachelors,16,5,31,70,69,0.0,1,70,Rural,Software Engineer,140425,0 +66192,Female,36,Masters,10,30,87,66,55,5.0,7,95,Semi-Urban,Manager,75332,1 +66193,Male,58,Masters,4,33,12,48,84,8.0,2,50,Urban,Manager,103116,0 +66194,Male,57,Bachelors,2,42,10,35,90,1.0,0,78,Urban,ML Engineer,54199,0 +66195,Male,47,Bachelors,7,8,95,87,82,3.0,4,27,Semi-Urban,Data Analyst,94016,0 +66196,Male,26,Masters,8,77,1,0,69,8.0,2,2,Urban,Software Engineer,141742,0 +66197,Female,43,Diploma,14,66,23,63,36,1.0,6,20,Urban,Data Analyst,84203,0 +66198,Male,43,PhD,19,59,2,89,29,9.0,4,29,Urban,ML Engineer,139770,0 +66199,Male,45,Masters,16,75,98,34,85,0.0,3,78,Semi-Urban,Software Engineer,66242,1 +66200,Male,56,Diploma,0,87,57,47,63,6.0,3,24,Semi-Urban,Data Analyst,88888,0 +66201,Male,24,Bachelors,2,76,64,71,15,6.0,6,98,Urban,ML Engineer,106964,1 +66202,Male,43,Masters,8,99,3,68,22,7.0,0,39,Urban,ML Engineer,135262,0 +66203,Male,39,Bachelors,11,67,85,47,92,8.0,5,15,Rural,Data Analyst,43200,0 +66204,Female,54,Bachelors,7,20,11,76,72,8.0,0,33,Semi-Urban,ML Engineer,88031,0 +66205,Female,36,Diploma,3,67,96,41,27,1.0,3,40,Urban,Manager,90885,1 +66206,Male,29,Diploma,15,3,72,40,66,6.0,5,32,Urban,Software Engineer,26226,0 +66207,Female,22,High School,16,81,6,89,76,8.0,7,7,Semi-Urban,Manager,25717,0 +66208,Male,23,Masters,3,63,32,82,21,7.0,1,83,Rural,ML Engineer,41795,1 +66209,Male,31,High School,12,21,65,49,69,8.0,7,37,Semi-Urban,Manager,98982,0 +66210,Female,45,Masters,2,63,82,70,4,9.0,7,51,Urban,ML Engineer,68657,1 +66211,Male,35,Bachelors,16,64,2,82,49,8.0,2,75,Semi-Urban,ML Engineer,113890,0 +66212,Female,31,Bachelors,0,58,62,98,25,2.0,3,97,Urban,Manager,68675,1 +66213,Male,58,PhD,12,10,15,64,13,2.0,3,61,Urban,HR Executive,52690,0 +66214,Male,58,Bachelors,10,42,92,88,56,8.0,6,8,Rural,HR Executive,146690,0 +66215,Male,44,Bachelors,17,62,36,83,6,9.0,6,98,Urban,Manager,66404,1 +66216,Female,21,Masters,5,19,80,75,36,1.0,7,57,Urban,Data Analyst,68222,0 +66217,Male,30,High School,15,94,99,8,63,6.0,2,31,Urban,Manager,27895,0 +66218,Female,48,Masters,6,94,49,18,93,0.0,1,53,Rural,Software Engineer,96196,0 +66219,Female,28,Diploma,8,66,89,54,33,4.0,4,32,Urban,HR Executive,119223,1 +66220,Male,47,PhD,16,29,52,39,91,1.0,5,53,Semi-Urban,HR Executive,107783,0 +66221,Female,43,Bachelors,12,32,26,59,3,6.0,4,21,Urban,Software Engineer,46690,0 +66222,Female,51,Diploma,7,59,77,69,64,9.0,6,43,Urban,Manager,69411,1 +66223,Male,48,Diploma,14,89,42,80,93,3.0,1,73,Urban,HR Executive,49284,1 +66224,Male,23,Diploma,4,0,1,24,53,9.0,0,92,Urban,Software Engineer,94320,0 +66225,Female,29,Masters,14,16,65,79,50,7.0,4,27,Urban,Data Analyst,127249,0 +66226,Male,23,Bachelors,12,15,28,51,58,9.0,2,24,Urban,ML Engineer,98399,0 +66227,Male,23,Diploma,10,20,8,91,43,9.0,0,5,Rural,Manager,85169,0 +66228,Female,43,Bachelors,1,40,94,55,22,6.0,3,23,Semi-Urban,Manager,142449,0 +66229,Female,57,Bachelors,12,18,79,63,82,6.0,4,25,Urban,Manager,21890,0 +66230,Male,56,Bachelors,16,51,45,31,53,6.0,5,25,Urban,ML Engineer,50136,0 +66231,Male,24,Bachelors,8,30,99,67,88,3.0,5,98,Urban,ML Engineer,79312,1 +66232,Female,48,Bachelors,8,28,32,0,7,6.0,6,12,Semi-Urban,HR Executive,92599,0 +66233,Female,30,Masters,11,78,66,29,41,0.0,4,79,Rural,Software Engineer,87570,1 +66234,Female,38,Masters,3,68,46,18,50,7.0,4,63,Urban,Manager,95389,0 +66235,Male,26,Masters,17,91,2,65,2,1.0,3,8,Semi-Urban,Data Analyst,79474,0 +66236,Female,23,High School,11,36,49,99,15,6.0,5,69,Urban,Software Engineer,79649,1 +66237,Male,43,High School,18,84,79,9,7,6.0,6,88,Semi-Urban,Data Analyst,103138,1 +66238,Male,53,Bachelors,1,88,19,31,64,8.0,2,82,Urban,Manager,113358,0 +66239,Female,45,Bachelors,15,66,95,24,48,0.0,0,28,Urban,Manager,62090,0 +66240,Male,48,Diploma,9,30,29,98,8,6.0,7,83,Semi-Urban,Software Engineer,35416,1 +66241,Female,31,Masters,3,74,48,78,71,4.0,3,40,Semi-Urban,HR Executive,33982,0 +66242,Male,23,PhD,3,45,24,60,65,8.0,5,11,Rural,Data Analyst,92181,0 +66243,Male,41,Bachelors,18,19,85,51,11,3.0,5,24,Urban,Manager,93090,0 +66244,Male,35,High School,6,80,93,12,62,8.0,5,19,Urban,ML Engineer,42073,0 +66245,Male,56,Masters,7,61,24,89,85,2.0,2,62,Rural,Manager,77097,1 +66246,Male,24,Diploma,17,66,66,10,12,7.0,2,0,Urban,Software Engineer,130396,0 +66247,Male,49,Bachelors,19,68,11,28,58,5.0,5,90,Urban,HR Executive,21818,0 +66248,Female,26,Masters,17,19,51,52,77,8.0,7,85,Urban,Manager,83143,0 +66249,Male,44,Bachelors,12,78,32,30,91,4.0,7,98,Rural,ML Engineer,121831,1 +66250,Male,48,Bachelors,4,32,67,81,80,3.0,4,54,Urban,ML Engineer,39398,0 +66251,Female,37,Masters,16,84,81,25,11,6.0,6,48,Urban,ML Engineer,119034,0 +66252,Male,53,High School,9,91,95,22,43,2.0,1,88,Semi-Urban,ML Engineer,128422,1 +66253,Male,43,Bachelors,9,91,10,81,71,8.0,7,24,Semi-Urban,Manager,140963,0 +66254,Male,25,Diploma,12,75,93,64,67,8.0,7,11,Urban,Manager,29144,1 +66255,Female,40,Bachelors,16,52,59,71,85,7.0,3,71,Urban,Data Analyst,114153,1 +66256,Male,54,Bachelors,18,60,39,90,27,1.0,3,40,Urban,HR Executive,29468,0 +66257,Male,38,High School,8,5,54,83,30,9.0,2,40,Urban,Data Analyst,99549,0 +66258,Female,58,Bachelors,10,99,83,27,55,2.0,5,92,Semi-Urban,HR Executive,62527,1 +66259,Female,21,Diploma,0,88,61,42,98,0.0,0,62,Rural,Data Analyst,141496,1 +66260,Female,39,Diploma,19,56,70,42,23,8.0,7,65,Urban,ML Engineer,79942,0 +66261,Female,31,Diploma,3,16,13,28,41,8.0,5,4,Semi-Urban,Manager,32924,0 +66262,Male,37,Bachelors,7,31,18,51,42,4.0,1,95,Semi-Urban,Data Analyst,65561,0 +66263,Male,43,Bachelors,10,69,1,49,62,5.0,6,59,Semi-Urban,Data Analyst,53670,0 +66264,Male,22,Bachelors,19,88,5,34,47,5.0,5,41,Rural,Data Analyst,86842,0 +66265,Female,50,Masters,17,32,94,58,5,0.0,0,80,Urban,Data Analyst,22181,1 +66266,Male,41,Diploma,4,84,42,53,76,6.0,3,32,Urban,Software Engineer,143109,0 +66267,Female,45,Bachelors,16,25,2,83,72,1.0,4,5,Urban,Data Analyst,98599,0 +66268,Male,57,Bachelors,8,69,68,20,25,9.0,1,84,Urban,ML Engineer,77744,1 +66269,Male,57,Bachelors,10,97,75,7,77,7.0,3,36,Semi-Urban,ML Engineer,64908,0 +66270,Male,33,Diploma,5,86,96,63,86,3.0,7,39,Semi-Urban,Data Analyst,49128,1 +66271,Other,57,Bachelors,12,37,28,62,70,3.0,1,64,Rural,ML Engineer,113022,0 +66272,Male,46,Bachelors,18,0,47,10,50,9.0,2,83,Semi-Urban,Data Analyst,133139,0 +66273,Female,22,High School,6,3,29,55,61,1.0,6,95,Urban,Manager,77173,0 +66274,Male,43,Bachelors,9,67,16,28,78,4.0,4,3,Semi-Urban,Software Engineer,63595,0 +66275,Male,31,Diploma,12,81,92,85,44,3.0,2,19,Urban,ML Engineer,108220,1 +66276,Male,22,Bachelors,0,15,76,37,7,1.0,5,61,Urban,HR Executive,135366,0 +66277,Female,26,Masters,6,74,25,57,25,0.0,3,26,Semi-Urban,Software Engineer,144293,0 +66278,Female,30,Bachelors,1,93,47,14,69,9.0,4,75,Urban,ML Engineer,101717,0 +66279,Female,28,Diploma,7,52,56,5,14,1.0,3,58,Semi-Urban,Data Analyst,117358,0 +66280,Female,33,Bachelors,11,50,35,66,66,0.0,2,36,Urban,HR Executive,104380,0 +66281,Male,25,Bachelors,3,55,36,23,5,3.0,0,54,Semi-Urban,HR Executive,30691,0 +66282,Female,43,Diploma,4,60,32,42,1,6.0,5,6,Urban,HR Executive,94793,0 +66283,Female,42,Bachelors,16,1,15,3,26,1.0,6,36,Urban,ML Engineer,64285,0 +66284,Female,50,Bachelors,5,89,83,83,55,8.0,1,42,Rural,ML Engineer,111748,1 +66285,Male,58,High School,16,14,2,59,27,6.0,1,24,Semi-Urban,Data Analyst,97404,0 +66286,Male,54,Bachelors,5,82,95,71,15,8.0,7,29,Semi-Urban,HR Executive,98933,1 +66287,Female,24,High School,2,32,8,29,24,9.0,4,10,Rural,Software Engineer,32002,0 +66288,Other,30,High School,14,5,52,29,13,7.0,3,73,Urban,Data Analyst,145588,0 +66289,Female,45,Diploma,15,51,31,22,5,1.0,2,44,Urban,Data Analyst,60887,0 +66290,Male,30,Bachelors,6,33,60,5,99,5.0,7,66,Semi-Urban,Software Engineer,35706,0 +66291,Male,54,Bachelors,0,74,47,61,48,9.0,3,63,Urban,Software Engineer,103782,1 +66292,Male,37,Masters,4,3,27,55,27,9.0,2,45,Urban,HR Executive,102008,0 +66293,Male,49,High School,19,36,92,46,2,0.0,6,77,Semi-Urban,Manager,83178,1 +66294,Other,46,Masters,7,7,38,2,57,7.0,4,77,Urban,Data Analyst,112666,0 +66295,Male,21,Diploma,1,35,75,92,70,1.0,3,69,Urban,HR Executive,43826,1 +66296,Male,57,Diploma,6,83,15,76,62,3.0,1,21,Urban,HR Executive,89568,0 +66297,Other,28,Masters,12,59,5,50,65,5.0,5,99,Urban,ML Engineer,63596,0 +66298,Female,45,Bachelors,18,88,77,33,92,4.0,1,22,Rural,Software Engineer,34145,0 +66299,Male,28,High School,10,45,86,41,97,4.0,5,93,Semi-Urban,Data Analyst,133345,1 +66300,Male,34,High School,7,33,81,97,52,4.0,0,30,Rural,Software Engineer,51119,1 +66301,Male,35,Diploma,13,20,58,64,10,3.0,2,61,Urban,Manager,89498,0 +66302,Female,39,Diploma,19,69,41,65,52,7.0,1,25,Urban,HR Executive,45877,0 +66303,Female,51,Diploma,17,99,68,41,16,1.0,1,77,Urban,ML Engineer,58127,1 +66304,Male,32,Bachelors,15,6,96,19,54,7.0,3,19,Semi-Urban,Software Engineer,28833,0 +66305,Male,40,Masters,0,15,78,17,88,7.0,5,11,Semi-Urban,Manager,68716,0 +66306,Female,41,Diploma,2,24,34,32,60,4.0,4,98,Urban,Manager,72505,0 +66307,Male,33,Bachelors,3,38,27,82,41,2.0,0,5,Urban,Manager,21886,0 +66308,Male,51,PhD,9,75,80,74,3,4.0,7,95,Urban,Manager,81723,1 +66309,Female,28,Masters,16,97,61,33,59,3.0,3,93,Semi-Urban,Manager,81179,1 +66310,Male,37,Bachelors,12,19,62,49,37,7.0,1,52,Rural,Data Analyst,103335,0 +66311,Female,46,Masters,10,54,42,47,69,7.0,7,15,Semi-Urban,Manager,28705,0 +66312,Male,31,Diploma,2,89,77,81,95,7.0,6,41,Semi-Urban,Manager,38443,1 +66313,Female,28,Bachelors,7,49,29,81,23,5.0,3,64,Semi-Urban,Manager,114981,0 +66314,Female,24,High School,9,19,45,0,71,7.0,5,26,Urban,Software Engineer,78049,0 +66315,Male,51,Masters,18,33,2,72,6,1.0,5,45,Urban,Manager,125040,0 +66316,Male,49,Diploma,6,98,24,93,28,5.0,6,58,Rural,Data Analyst,148483,1 +66317,Male,24,High School,10,36,63,46,25,9.0,3,32,Urban,Data Analyst,140037,0 +66318,Female,53,Bachelors,14,48,17,75,31,6.0,6,52,Urban,HR Executive,147563,0 +66319,Male,35,Bachelors,4,67,3,46,81,3.0,1,73,Urban,Manager,135518,0 +66320,Male,43,Bachelors,1,66,23,43,91,8.0,7,16,Urban,Manager,141414,0 +66321,Male,27,Bachelors,9,64,58,40,94,7.0,4,67,Urban,HR Executive,37026,0 +66322,Male,21,Bachelors,19,88,45,46,97,3.0,6,32,Semi-Urban,ML Engineer,144267,0 +66323,Male,25,Masters,15,77,68,68,47,4.0,7,68,Urban,ML Engineer,74315,1 +66324,Female,43,High School,12,5,10,50,2,4.0,3,4,Semi-Urban,Data Analyst,66714,0 +66325,Female,27,Diploma,1,83,0,31,2,4.0,2,94,Rural,HR Executive,58722,0 +66326,Male,54,Diploma,3,63,94,66,66,4.0,0,42,Semi-Urban,Manager,128468,1 +66327,Female,27,Bachelors,17,65,84,59,28,7.0,3,93,Semi-Urban,Data Analyst,48218,1 +66328,Male,25,Diploma,19,61,33,19,52,1.0,5,68,Semi-Urban,HR Executive,84419,0 +66329,Female,34,Masters,11,69,80,97,88,5.0,2,34,Semi-Urban,Software Engineer,25908,1 +66330,Female,24,Diploma,13,63,21,84,42,8.0,5,22,Urban,HR Executive,64292,0 +66331,Female,21,Diploma,11,56,28,94,27,6.0,7,9,Urban,Software Engineer,45986,0 +66332,Female,26,Diploma,5,99,44,51,51,0.0,0,28,Semi-Urban,HR Executive,112591,0 +66333,Female,33,High School,11,69,70,99,70,9.0,0,41,Rural,Data Analyst,66003,1 +66334,Female,32,Masters,17,18,23,36,28,0.0,7,98,Rural,ML Engineer,31147,0 +66335,Female,55,Diploma,1,48,23,43,84,6.0,7,40,Urban,Data Analyst,74643,0 +66336,Male,22,Bachelors,11,36,81,48,5,1.0,7,15,Urban,Data Analyst,32342,0 +66337,Male,59,High School,19,17,0,72,66,6.0,2,44,Urban,Data Analyst,82678,0 +66338,Male,52,Bachelors,7,24,42,60,14,9.0,0,34,Urban,Manager,116198,0 +66339,Male,23,Bachelors,11,84,45,59,4,5.0,5,13,Urban,Manager,21320,0 +66340,Female,26,Diploma,8,25,46,59,35,2.0,0,82,Rural,Manager,20848,0 +66341,Female,25,Masters,14,52,93,83,11,2.0,0,2,Urban,Data Analyst,139598,0 +66342,Female,27,Bachelors,10,88,63,59,62,3.0,2,27,Urban,Data Analyst,78416,0 +66343,Female,49,Bachelors,15,73,92,30,44,1.0,4,10,Rural,ML Engineer,111991,0 +66344,Male,25,Bachelors,6,11,86,85,15,6.0,2,88,Urban,Software Engineer,122192,1 +66345,Female,29,Diploma,15,41,79,91,17,0.0,1,80,Semi-Urban,Manager,129115,1 +66346,Male,56,Masters,19,48,78,68,39,1.0,5,59,Urban,Software Engineer,136462,1 +66347,Female,52,Diploma,11,37,80,31,56,0.0,7,57,Urban,Software Engineer,59878,0 +66348,Female,27,Masters,8,75,44,29,55,5.0,2,56,Rural,HR Executive,142910,0 +66349,Other,54,Diploma,18,64,19,83,74,9.0,4,88,Urban,HR Executive,109736,1 +66350,Female,25,Diploma,15,33,9,97,15,0.0,7,60,Urban,Software Engineer,51886,0 +66351,Male,41,High School,13,2,11,18,21,7.0,7,2,Rural,HR Executive,54398,0 +66352,Male,40,High School,6,46,41,86,81,8.0,0,8,Urban,ML Engineer,26871,0 +66353,Female,56,Bachelors,1,74,80,64,86,4.0,7,8,Urban,Software Engineer,20628,0 +66354,Male,21,Diploma,7,64,14,65,15,7.0,6,58,Urban,HR Executive,117905,0 +66355,Female,45,Bachelors,2,29,23,49,30,4.0,3,53,Rural,Manager,119158,0 +66356,Male,46,Bachelors,9,34,86,4,6,9.0,6,96,Semi-Urban,Software Engineer,77845,0 +66357,Male,28,Diploma,12,75,53,67,39,6.0,0,1,Rural,Manager,55054,0 +66358,Male,48,Diploma,17,85,21,52,68,6.0,6,99,Urban,Software Engineer,138743,1 +66359,Female,38,Bachelors,3,75,10,43,47,2.0,5,56,Urban,Data Analyst,25777,0 +66360,Male,33,Diploma,3,77,27,19,60,3.0,5,22,Rural,Software Engineer,145113,0 +66361,Female,57,Masters,12,18,54,98,84,1.0,4,10,Rural,ML Engineer,26385,0 +66362,Male,48,Diploma,18,75,64,31,68,0.0,3,70,Rural,ML Engineer,78130,1 +66363,Male,46,Bachelors,11,26,96,10,11,1.0,0,80,Urban,Data Analyst,94188,0 +66364,Female,53,Bachelors,0,65,55,27,41,9.0,1,7,Urban,Manager,75743,0 +66365,Male,24,PhD,13,22,38,23,59,8.0,4,56,Urban,Data Analyst,92887,0 +66366,Male,32,Diploma,16,58,94,20,17,5.0,4,4,Urban,Manager,121039,0 +66367,Female,28,Bachelors,10,93,61,2,98,5.0,6,93,Semi-Urban,Manager,35377,1 +66368,Female,27,Bachelors,19,70,85,21,87,2.0,7,46,Rural,HR Executive,93427,0 +66369,Male,53,Bachelors,3,66,69,94,50,6.0,4,5,Urban,Manager,51694,0 +66370,Female,58,Masters,12,69,97,23,49,9.0,5,89,Rural,Software Engineer,93744,1 +66371,Other,55,Diploma,16,49,75,19,53,5.0,7,26,Semi-Urban,Data Analyst,39811,0 +66372,Female,39,Bachelors,12,60,6,35,55,9.0,3,61,Rural,Data Analyst,83438,0 +66373,Female,40,Masters,16,10,73,23,32,8.0,1,3,Rural,Software Engineer,70085,0 +66374,Female,45,Bachelors,10,22,28,55,64,7.0,2,17,Urban,HR Executive,25217,0 +66375,Female,43,Bachelors,17,91,1,51,34,8.0,1,95,Semi-Urban,HR Executive,126810,0 +66376,Female,30,Diploma,1,66,1,29,97,5.0,6,92,Semi-Urban,Data Analyst,27431,0 +66377,Male,36,Bachelors,17,89,80,28,97,5.0,4,82,Urban,Manager,113562,1 +66378,Male,51,Diploma,9,32,86,20,17,2.0,7,18,Semi-Urban,Data Analyst,92886,0 +66379,Male,58,Diploma,4,41,53,81,7,1.0,6,28,Urban,ML Engineer,136904,0 +66380,Male,25,Bachelors,15,45,14,35,80,4.0,0,9,Urban,ML Engineer,101298,0 +66381,Male,44,Masters,2,66,35,56,68,9.0,6,23,Urban,Software Engineer,30528,0 +66382,Male,56,Bachelors,3,21,5,10,69,1.0,4,54,Semi-Urban,Manager,64952,0 +66383,Male,28,Bachelors,17,47,14,44,73,5.0,3,84,Urban,Data Analyst,70853,0 +66384,Male,31,Bachelors,5,94,85,37,29,3.0,7,68,Urban,HR Executive,108344,1 +66385,Male,50,Bachelors,11,6,87,58,0,0.0,6,77,Urban,Manager,103579,0 +66386,Male,49,Bachelors,2,88,65,83,46,6.0,7,52,Semi-Urban,HR Executive,62928,1 +66387,Male,42,Bachelors,13,13,16,3,10,1.0,1,36,Urban,ML Engineer,123009,0 +66388,Female,50,Diploma,18,84,23,99,60,7.0,5,10,Rural,Data Analyst,133099,0 +66389,Female,40,High School,17,87,58,89,48,6.0,4,74,Urban,ML Engineer,22817,1 +66390,Female,34,Bachelors,4,4,11,98,52,4.0,3,68,Rural,Manager,90983,0 +66391,Female,46,Bachelors,13,46,74,55,96,9.0,0,39,Urban,Software Engineer,82890,0 +66392,Male,22,Masters,11,44,75,61,95,0.0,5,41,Rural,ML Engineer,102712,0 +66393,Female,53,Diploma,9,34,12,25,31,5.0,6,63,Rural,ML Engineer,36477,0 +66394,Female,25,High School,2,76,22,16,8,7.0,4,77,Urban,Software Engineer,128585,0 +66395,Male,48,Masters,17,13,80,37,77,9.0,0,10,Urban,Manager,118175,0 +66396,Female,40,Bachelors,7,21,15,2,50,6.0,2,62,Urban,Data Analyst,94586,0 +66397,Male,26,Diploma,19,21,35,4,24,0.0,6,47,Urban,Data Analyst,28099,0 +66398,Male,41,Bachelors,10,80,92,41,91,0.0,4,37,Rural,Software Engineer,99704,1 +66399,Male,55,PhD,8,33,79,30,26,4.0,3,4,Semi-Urban,ML Engineer,72522,0 +66400,Female,39,Masters,12,41,19,7,35,8.0,1,48,Urban,Data Analyst,36495,0 +66401,Male,29,Masters,4,61,68,62,52,1.0,6,56,Semi-Urban,Software Engineer,116802,1 +66402,Male,56,Masters,12,77,32,73,73,4.0,0,51,Urban,Software Engineer,76250,0 +66403,Male,29,Bachelors,5,36,94,69,14,5.0,3,66,Semi-Urban,Software Engineer,41517,1 +66404,Female,36,Bachelors,18,73,19,30,90,6.0,5,57,Rural,Data Analyst,148488,0 +66405,Male,57,Bachelors,3,71,77,63,95,8.0,7,10,Rural,Manager,26770,0 +66406,Female,25,Masters,15,98,31,45,50,1.0,0,53,Rural,ML Engineer,97304,0 +66407,Male,32,Diploma,15,42,28,14,0,2.0,0,36,Urban,ML Engineer,62956,0 +66408,Male,43,Diploma,12,81,0,57,87,1.0,2,13,Urban,Data Analyst,82021,0 +66409,Male,47,Masters,0,51,98,79,37,9.0,0,57,Urban,Manager,31888,1 +66410,Male,21,Diploma,16,96,11,17,21,1.0,5,13,Urban,ML Engineer,59438,0 +66411,Female,31,Masters,0,68,93,23,3,3.0,5,4,Rural,Manager,140773,0 +66412,Female,45,Masters,16,12,66,20,12,1.0,2,88,Semi-Urban,Data Analyst,72395,0 +66413,Male,33,PhD,4,0,41,55,93,9.0,3,9,Rural,ML Engineer,102793,0 +66414,Male,44,Diploma,13,54,37,32,26,0.0,0,81,Urban,Data Analyst,26205,0 +66415,Male,57,Diploma,8,67,19,76,91,2.0,0,40,Rural,HR Executive,39689,0 +66416,Female,22,Diploma,18,36,71,87,99,4.0,1,97,Semi-Urban,ML Engineer,38391,1 +66417,Male,22,Bachelors,7,19,78,45,31,5.0,7,0,Urban,Software Engineer,72744,0 +66418,Male,59,High School,10,32,91,23,17,3.0,6,99,Rural,Data Analyst,72666,1 +66419,Female,54,Diploma,14,66,55,46,98,4.0,1,5,Urban,HR Executive,129392,0 +66420,Other,54,Bachelors,6,14,91,76,49,4.0,3,35,Urban,Data Analyst,58616,0 +66421,Male,25,Bachelors,7,51,59,4,45,8.0,7,41,Semi-Urban,HR Executive,115272,0 +66422,Female,35,PhD,13,10,8,99,35,9.0,1,24,Rural,ML Engineer,149318,0 +66423,Male,30,High School,9,64,56,22,24,9.0,5,40,Urban,Data Analyst,99249,0 +66424,Male,26,High School,12,59,85,3,5,0.0,0,7,Semi-Urban,ML Engineer,97182,0 +66425,Female,39,Bachelors,15,64,50,75,3,2.0,2,29,Rural,HR Executive,115585,0 +66426,Male,44,Masters,4,97,41,22,27,1.0,2,86,Semi-Urban,Manager,102207,1 +66427,Male,42,Bachelors,3,1,30,26,38,4.0,1,14,Urban,HR Executive,42447,0 +66428,Female,56,Bachelors,18,7,84,11,3,5.0,2,84,Urban,Manager,82466,0 +66429,Male,58,Diploma,17,15,47,48,52,6.0,6,52,Semi-Urban,ML Engineer,142967,0 +66430,Female,49,High School,12,83,2,62,62,0.0,0,22,Urban,HR Executive,35351,0 +66431,Male,27,Bachelors,3,85,51,47,81,1.0,3,14,Semi-Urban,HR Executive,49360,0 +66432,Male,48,High School,16,11,22,14,52,4.0,0,56,Urban,Manager,121655,0 +66433,Male,36,Masters,9,35,27,73,55,5.0,1,26,Urban,ML Engineer,138607,0 +66434,Male,40,High School,3,35,11,18,62,6.0,5,69,Semi-Urban,HR Executive,106385,0 +66435,Male,57,Masters,14,54,28,68,23,2.0,7,0,Urban,ML Engineer,88295,0 +66436,Female,50,Bachelors,19,15,57,84,94,9.0,5,60,Urban,ML Engineer,76925,0 +66437,Male,54,PhD,16,51,28,82,94,8.0,2,26,Urban,Manager,97506,0 +66438,Male,49,Bachelors,17,83,68,55,94,1.0,3,73,Semi-Urban,Manager,124899,1 +66439,Male,30,Bachelors,11,20,13,18,44,1.0,6,90,Urban,Data Analyst,24575,0 +66440,Female,50,Diploma,18,95,59,15,65,0.0,2,94,Urban,HR Executive,25350,1 +66441,Female,58,Bachelors,18,61,98,97,97,2.0,7,35,Semi-Urban,Software Engineer,104924,1 +66442,Female,25,High School,12,72,1,14,4,7.0,7,0,Semi-Urban,Software Engineer,22823,0 +66443,Other,31,Diploma,2,42,62,81,3,0.0,2,29,Rural,Software Engineer,48200,0 +66444,Female,48,Diploma,19,75,40,21,5,4.0,5,82,Urban,Data Analyst,146340,0 +66445,Female,30,High School,15,54,41,84,22,7.0,3,35,Rural,Software Engineer,144314,0 +66446,Female,46,Bachelors,19,78,25,37,12,4.0,4,13,Semi-Urban,ML Engineer,64907,0 +66447,Male,26,Bachelors,11,65,38,43,69,4.0,0,51,Urban,HR Executive,42160,0 +66448,Male,52,Bachelors,9,11,70,53,61,7.0,3,43,Semi-Urban,Data Analyst,143069,0 +66449,Female,57,Masters,0,52,9,22,9,9.0,6,51,Rural,Manager,118497,0 +66450,Male,49,Diploma,0,34,17,92,53,7.0,6,45,Rural,HR Executive,105840,0 +66451,Male,24,Diploma,0,88,42,14,40,4.0,0,81,Urban,Manager,24113,0 +66452,Male,56,High School,14,59,76,92,84,9.0,7,39,Rural,Software Engineer,130327,1 +66453,Female,54,Diploma,10,70,65,68,26,7.0,6,53,Urban,Software Engineer,59906,1 +66454,Male,50,Diploma,12,51,17,13,77,8.0,0,9,Urban,HR Executive,79626,0 +66455,Male,39,Bachelors,18,32,15,8,48,3.0,5,18,Urban,Software Engineer,41786,0 +66456,Female,32,Bachelors,9,79,45,98,40,4.0,5,84,Urban,Software Engineer,27168,1 +66457,Male,41,Bachelors,5,81,97,89,99,6.0,3,86,Semi-Urban,ML Engineer,122253,1 +66458,Female,44,Bachelors,18,99,62,56,26,0.0,2,26,Urban,Data Analyst,142056,1 +66459,Female,34,High School,7,23,32,77,98,6.0,4,46,Urban,HR Executive,108332,0 +66460,Male,30,Bachelors,19,72,35,90,80,8.0,6,15,Rural,Manager,32969,0 +66461,Female,34,Bachelors,16,2,58,63,92,4.0,1,33,Rural,Software Engineer,143510,0 +66462,Male,23,Diploma,2,86,81,9,47,4.0,4,31,Semi-Urban,Data Analyst,20206,0 +66463,Female,46,Bachelors,1,12,56,70,93,4.0,7,60,Rural,Manager,127787,0 +66464,Male,58,Masters,8,6,91,98,58,5.0,6,39,Rural,HR Executive,122091,0 +66465,Male,32,Masters,7,45,56,13,34,1.0,4,39,Rural,Software Engineer,87732,0 +66466,Male,21,Diploma,3,7,57,65,18,7.0,7,94,Semi-Urban,ML Engineer,131941,0 +66467,Female,28,Diploma,7,52,96,65,60,7.0,7,12,Urban,Software Engineer,80775,0 +66468,Female,32,Bachelors,15,51,27,0,36,7.0,6,62,Urban,Software Engineer,101277,0 +66469,Female,54,Bachelors,11,95,16,68,51,5.0,4,68,Semi-Urban,Manager,56874,1 +66470,Female,55,Bachelors,10,64,93,33,61,8.0,1,15,Urban,Data Analyst,103712,0 +66471,Female,24,Bachelors,12,73,99,99,95,1.0,0,43,Urban,HR Executive,44507,1 +66472,Male,47,Diploma,12,53,34,17,2,7.0,1,29,Semi-Urban,HR Executive,118586,0 +66473,Female,38,High School,0,38,56,88,67,1.0,5,33,Semi-Urban,Manager,125262,0 +66474,Male,30,Diploma,12,31,16,98,67,8.0,5,1,Urban,Software Engineer,106521,0 +66475,Female,39,Masters,19,84,76,7,76,7.0,0,18,Urban,Data Analyst,80191,0 +66476,Female,38,Masters,19,47,42,27,7,2.0,7,11,Rural,ML Engineer,62995,0 +66477,Female,51,Bachelors,13,10,98,20,94,7.0,2,26,Semi-Urban,HR Executive,57181,0 +66478,Female,34,Bachelors,8,30,24,2,74,6.0,2,85,Urban,Data Analyst,103401,0 +66479,Male,23,High School,7,49,25,2,11,1.0,0,2,Urban,Software Engineer,63131,0 +66480,Male,40,Masters,19,34,7,46,48,5.0,2,17,Urban,Data Analyst,100288,0 +66481,Female,40,Bachelors,9,33,60,38,43,2.0,1,17,Semi-Urban,HR Executive,112888,0 +66482,Male,50,Masters,15,92,55,69,79,5.0,5,2,Semi-Urban,Manager,41675,0 +66483,Male,54,Masters,11,60,78,0,32,7.0,7,1,Semi-Urban,HR Executive,103853,0 +66484,Male,51,High School,13,49,25,87,53,4.0,2,11,Urban,ML Engineer,114736,0 +66485,Male,28,Diploma,13,62,48,11,69,4.0,7,43,Semi-Urban,ML Engineer,36619,0 +66486,Male,22,Bachelors,7,22,52,11,15,3.0,1,82,Urban,Data Analyst,52443,0 +66487,Female,46,Masters,14,73,28,17,54,4.0,6,67,Urban,Software Engineer,131942,0 +66488,Male,27,Bachelors,4,75,30,91,45,3.0,0,51,Urban,ML Engineer,106053,1 +66489,Male,42,Diploma,10,83,34,2,56,2.0,3,75,Rural,HR Executive,94355,0 +66490,Female,52,Masters,2,49,95,74,54,0.0,5,40,Rural,Manager,134714,1 +66491,Male,58,Bachelors,2,14,83,96,74,0.0,5,94,Semi-Urban,Manager,71625,1 +66492,Female,54,Bachelors,13,38,43,14,52,2.0,1,76,Urban,Software Engineer,89450,0 +66493,Male,54,Bachelors,6,90,3,68,23,7.0,7,35,Semi-Urban,Manager,139630,0 +66494,Male,22,Masters,5,37,46,34,47,6.0,3,16,Urban,Software Engineer,147385,0 +66495,Male,43,Bachelors,14,71,91,66,22,0.0,6,92,Urban,HR Executive,39673,1 +66496,Female,44,High School,16,40,66,64,52,3.0,6,67,Urban,HR Executive,45424,0 +66497,Male,35,High School,5,70,84,53,92,9.0,4,52,Semi-Urban,Software Engineer,139442,1 +66498,Other,47,Bachelors,2,96,9,84,76,7.0,3,38,Urban,ML Engineer,118725,0 +66499,Female,46,Bachelors,1,64,15,8,13,3.0,7,87,Urban,Software Engineer,79911,0 +66500,Female,54,Masters,16,37,25,98,82,4.0,3,9,Urban,Software Engineer,42719,0 +66501,Male,30,Bachelors,11,42,21,49,75,9.0,3,8,Rural,HR Executive,128096,0 +66502,Male,34,Bachelors,12,50,13,29,61,0.0,1,97,Urban,ML Engineer,44118,0 +66503,Male,57,Bachelors,4,43,66,71,47,4.0,2,33,Urban,ML Engineer,39825,0 +66504,Male,26,Bachelors,4,28,51,90,93,5.0,3,38,Urban,HR Executive,116620,0 +66505,Other,33,Diploma,11,95,79,64,24,1.0,4,6,Urban,Manager,123111,1 +66506,Male,53,Diploma,10,89,52,88,59,3.0,3,55,Semi-Urban,Manager,143664,1 +66507,Male,25,Masters,11,89,73,52,27,9.0,1,75,Urban,ML Engineer,139192,1 +66508,Female,50,Masters,9,98,75,16,31,9.0,1,47,Semi-Urban,Data Analyst,135943,0 +66509,Male,25,Masters,18,36,48,88,24,4.0,1,48,Semi-Urban,Data Analyst,39582,0 +66510,Male,28,Bachelors,12,39,13,99,26,4.0,6,24,Urban,Data Analyst,127522,0 +66511,Other,43,Bachelors,3,91,90,70,35,6.0,3,6,Urban,ML Engineer,63589,1 +66512,Male,26,Diploma,8,89,89,59,5,1.0,6,77,Rural,ML Engineer,118963,1 +66513,Female,53,Bachelors,6,38,71,73,45,2.0,4,82,Urban,Software Engineer,91207,1 +66514,Male,56,High School,17,29,8,27,84,5.0,0,52,Urban,ML Engineer,81249,0 +66515,Female,47,High School,9,11,53,81,40,2.0,7,4,Urban,Data Analyst,101441,0 +66516,Male,50,Bachelors,12,3,79,61,48,4.0,2,18,Semi-Urban,Manager,130991,0 +66517,Female,33,Bachelors,12,62,74,46,56,8.0,6,21,Urban,HR Executive,30035,0 +66518,Male,29,PhD,13,89,79,16,32,0.0,4,1,Semi-Urban,Data Analyst,87057,0 +66519,Male,26,Bachelors,12,92,31,30,50,1.0,4,66,Urban,Data Analyst,138113,0 +66520,Male,21,Masters,6,95,84,74,14,7.0,0,81,Urban,ML Engineer,101113,1 +66521,Male,36,Diploma,15,27,38,38,57,7.0,6,75,Rural,Software Engineer,29905,0 +66522,Female,58,Bachelors,18,93,7,90,81,0.0,6,89,Urban,Software Engineer,35336,1 +66523,Female,50,Masters,8,12,93,35,46,8.0,0,63,Urban,HR Executive,61827,0 +66524,Male,39,Bachelors,19,62,64,20,46,9.0,4,26,Urban,Software Engineer,99318,0 +66525,Male,33,Bachelors,18,46,81,25,70,8.0,3,22,Urban,Software Engineer,60513,0 +66526,Female,33,Masters,6,74,22,71,7,4.0,7,33,Rural,HR Executive,77386,0 +66527,Female,42,Bachelors,19,66,77,62,39,5.0,4,22,Semi-Urban,Data Analyst,61967,0 +66528,Male,45,Masters,3,29,78,6,38,3.0,2,77,Urban,Data Analyst,135950,0 +66529,Female,28,Diploma,10,47,18,13,13,0.0,6,68,Semi-Urban,HR Executive,59680,0 +66530,Female,35,High School,16,18,24,94,23,0.0,7,72,Semi-Urban,Software Engineer,55032,0 +66531,Male,58,High School,16,65,50,75,70,1.0,5,20,Urban,ML Engineer,99970,0 +66532,Male,41,PhD,4,60,64,85,45,2.0,1,77,Rural,Software Engineer,64747,1 +66533,Female,44,Bachelors,0,56,52,82,46,1.0,2,4,Rural,ML Engineer,93676,0 +66534,Male,36,Masters,1,36,38,35,2,5.0,6,51,Urban,ML Engineer,77930,0 +66535,Female,37,High School,14,6,86,92,17,3.0,5,7,Urban,HR Executive,74144,0 +66536,Male,31,High School,5,42,87,27,88,0.0,5,37,Urban,ML Engineer,42487,0 +66537,Male,48,Masters,9,66,41,44,51,6.0,3,7,Rural,Data Analyst,107620,0 +66538,Male,57,Bachelors,18,59,84,30,37,4.0,7,70,Urban,Data Analyst,117515,1 +66539,Male,38,Bachelors,2,31,50,22,89,3.0,7,69,Urban,ML Engineer,67417,0 +66540,Female,58,Bachelors,1,26,43,1,94,4.0,3,32,Urban,HR Executive,38961,0 +66541,Female,39,Bachelors,17,41,2,41,79,8.0,1,22,Semi-Urban,Manager,73671,0 +66542,Female,24,High School,9,42,91,55,13,5.0,6,58,Semi-Urban,Manager,70640,1 +66543,Male,55,Masters,1,50,31,62,6,8.0,4,84,Rural,Data Analyst,99034,0 +66544,Male,52,Masters,18,48,49,44,28,7.0,6,81,Rural,Data Analyst,83613,0 +66545,Male,43,High School,5,95,89,40,74,3.0,0,4,Urban,HR Executive,125806,0 +66546,Female,54,Diploma,13,34,64,79,54,6.0,5,6,Urban,HR Executive,67394,0 +66547,Female,33,Masters,2,87,5,63,0,8.0,6,41,Semi-Urban,Manager,84513,0 +66548,Female,21,Masters,19,42,61,16,48,9.0,1,51,Rural,Data Analyst,130370,0 +66549,Female,36,Masters,17,74,62,66,35,9.0,3,94,Rural,Manager,78996,1 +66550,Male,44,Bachelors,2,92,4,27,81,1.0,0,32,Semi-Urban,Manager,143560,0 +66551,Male,27,Diploma,16,91,25,93,58,8.0,4,29,Urban,Software Engineer,65155,1 +66552,Male,46,Bachelors,19,88,69,43,0,3.0,1,32,Semi-Urban,HR Executive,64112,0 +66553,Male,32,Bachelors,13,83,71,83,69,0.0,6,15,Urban,Data Analyst,95862,1 +66554,Male,59,Masters,6,4,2,31,98,6.0,3,89,Urban,Data Analyst,134907,0 +66555,Female,51,High School,18,55,80,5,40,4.0,1,54,Urban,Manager,21345,0 +66556,Male,45,Diploma,2,40,20,23,64,1.0,2,37,Semi-Urban,Software Engineer,86734,0 +66557,Male,57,High School,14,78,97,66,38,5.0,1,88,Urban,ML Engineer,114671,1 +66558,Male,42,Bachelors,0,85,95,79,98,3.0,3,10,Urban,Data Analyst,33640,1 +66559,Male,22,Bachelors,18,20,64,93,5,3.0,2,95,Semi-Urban,HR Executive,141420,1 +66560,Female,46,Masters,8,99,11,19,96,1.0,4,98,Urban,Manager,84502,0 +66561,Female,50,Masters,19,94,20,49,37,2.0,6,21,Semi-Urban,Data Analyst,145787,0 +66562,Male,51,Bachelors,2,52,37,95,37,5.0,6,49,Urban,HR Executive,125252,0 +66563,Male,49,Diploma,7,90,59,95,60,4.0,6,75,Urban,Data Analyst,79078,1 +66564,Male,42,High School,17,80,95,15,92,1.0,4,5,Urban,Software Engineer,142959,0 +66565,Female,52,High School,19,68,83,25,79,6.0,1,43,Semi-Urban,Software Engineer,136472,0 +66566,Female,23,High School,16,13,31,25,51,6.0,2,25,Urban,Software Engineer,130647,0 +66567,Male,58,Bachelors,11,90,43,58,98,4.0,2,42,Urban,ML Engineer,92370,0 +66568,Male,50,Bachelors,17,60,55,55,71,2.0,4,1,Rural,Data Analyst,92980,0 +66569,Male,27,Masters,4,54,22,8,76,0.0,5,25,Urban,HR Executive,31635,0 +66570,Female,58,Bachelors,12,17,56,58,78,1.0,5,22,Urban,HR Executive,24495,0 +66571,Male,51,Diploma,17,29,90,98,8,8.0,5,89,Urban,ML Engineer,99077,1 +66572,Other,53,Bachelors,14,55,21,15,13,2.0,1,38,Urban,HR Executive,109595,0 +66573,Male,51,Masters,1,95,42,65,34,9.0,0,8,Urban,Software Engineer,63904,0 +66574,Male,24,Diploma,19,58,89,32,7,7.0,6,78,Urban,Software Engineer,136380,1 +66575,Male,25,Masters,7,69,79,84,25,2.0,3,98,Semi-Urban,Software Engineer,73172,1 +66576,Other,32,Bachelors,8,44,93,28,70,7.0,4,90,Urban,Software Engineer,120998,1 +66577,Female,55,High School,5,3,85,68,66,0.0,2,72,Urban,Data Analyst,142850,0 +66578,Male,40,Bachelors,17,80,87,75,1,6.0,2,24,Semi-Urban,ML Engineer,117997,1 +66579,Male,49,PhD,11,65,40,98,91,9.0,5,25,Rural,Software Engineer,47271,0 +66580,Male,36,High School,9,66,45,61,9,9.0,0,31,Urban,Software Engineer,144152,0 +66581,Female,59,Bachelors,17,89,79,98,33,1.0,2,45,Semi-Urban,ML Engineer,83798,1 +66582,Female,37,High School,0,84,37,62,66,4.0,4,19,Urban,ML Engineer,55854,0 +66583,Female,31,Diploma,16,34,45,73,36,4.0,0,80,Rural,Software Engineer,43185,0 +66584,Male,50,High School,11,40,14,15,56,4.0,2,29,Urban,ML Engineer,37912,0 +66585,Female,27,Bachelors,16,95,95,71,15,5.0,3,88,Rural,HR Executive,83701,1 +66586,Male,42,Masters,2,76,97,7,69,1.0,7,0,Semi-Urban,Software Engineer,60086,0 +66587,Male,32,Bachelors,14,94,3,70,67,0.0,2,38,Urban,Software Engineer,144608,0 +66588,Male,35,High School,17,74,27,19,75,5.0,6,6,Urban,HR Executive,42415,0 +66589,Male,30,Bachelors,6,34,34,8,92,0.0,3,51,Rural,Software Engineer,139460,0 +66590,Other,36,Masters,18,14,91,72,15,1.0,0,48,Rural,Manager,44243,0 +66591,Male,51,High School,15,14,22,72,36,2.0,0,2,Urban,HR Executive,122273,0 +66592,Male,59,Masters,9,99,48,96,45,8.0,5,68,Urban,Manager,34000,1 +66593,Female,35,High School,18,48,31,60,45,9.0,1,34,Urban,Manager,62364,0 +66594,Female,31,PhD,11,86,43,41,74,1.0,7,31,Rural,Software Engineer,91313,0 +66595,Male,33,Bachelors,12,18,82,36,21,7.0,7,48,Urban,Data Analyst,86120,0 +66596,Male,54,Diploma,11,36,90,17,61,2.0,5,23,Rural,Software Engineer,47491,0 +66597,Female,24,Diploma,19,19,62,33,6,4.0,2,11,Urban,Data Analyst,37845,0 +66598,Male,53,Masters,8,77,28,11,3,6.0,4,30,Semi-Urban,Manager,22516,0 +66599,Male,27,Masters,8,77,76,53,90,1.0,1,69,Semi-Urban,Data Analyst,81351,1 +66600,Male,45,Masters,4,24,13,67,86,7.0,2,36,Rural,Manager,133356,0 +66601,Male,47,High School,4,61,81,31,72,1.0,2,7,Rural,Software Engineer,116044,0 +66602,Male,23,Bachelors,4,69,48,81,58,3.0,6,52,Urban,Software Engineer,125722,1 +66603,Female,37,Bachelors,7,12,7,93,16,3.0,3,56,Semi-Urban,ML Engineer,46919,0 +66604,Female,38,Masters,16,36,27,10,9,4.0,7,77,Urban,HR Executive,136888,0 +66605,Female,42,Masters,18,95,51,12,86,8.0,0,44,Semi-Urban,ML Engineer,88343,0 +66606,Female,29,Bachelors,11,37,64,12,67,9.0,6,42,Semi-Urban,Manager,118428,0 +66607,Female,58,Bachelors,3,69,44,5,34,2.0,1,12,Semi-Urban,Manager,72746,0 +66608,Female,27,High School,9,90,65,36,86,7.0,6,41,Urban,HR Executive,129633,0 +66609,Female,49,Bachelors,9,45,44,1,60,1.0,3,33,Semi-Urban,Data Analyst,38613,0 +66610,Male,26,Bachelors,0,7,19,48,24,4.0,1,31,Urban,Data Analyst,124334,0 +66611,Male,39,Bachelors,11,96,13,75,47,2.0,6,94,Urban,Data Analyst,60917,1 +66612,Female,54,Masters,16,86,33,0,70,7.0,7,46,Urban,HR Executive,109535,0 +66613,Male,26,Bachelors,7,20,85,51,87,3.0,6,7,Urban,ML Engineer,66686,0 +66614,Female,55,Bachelors,14,74,53,90,66,3.0,6,52,Semi-Urban,Software Engineer,51928,1 +66615,Female,42,Bachelors,16,10,95,22,11,8.0,0,93,Urban,Data Analyst,45749,0 +66616,Male,56,Bachelors,11,1,73,14,9,4.0,1,56,Urban,Software Engineer,87259,0 +66617,Female,42,Bachelors,12,44,57,53,60,6.0,7,63,Urban,Manager,52441,0 +66618,Male,24,Masters,2,36,84,42,49,5.0,0,20,Urban,HR Executive,72224,0 +66619,Female,29,Diploma,19,78,37,28,48,1.0,2,78,Rural,Data Analyst,120145,0 +66620,Male,29,Bachelors,9,0,12,51,32,5.0,4,74,Semi-Urban,HR Executive,86862,0 +66621,Female,27,Masters,19,62,86,98,91,9.0,3,6,Urban,ML Engineer,50295,1 +66622,Male,21,Bachelors,0,92,29,99,18,4.0,3,81,Urban,HR Executive,53902,1 +66623,Female,25,Bachelors,3,13,61,15,11,8.0,2,95,Rural,HR Executive,130138,0 +66624,Male,26,High School,19,68,5,87,46,6.0,7,46,Semi-Urban,Data Analyst,79708,0 +66625,Female,58,Diploma,9,95,15,77,71,4.0,6,15,Rural,Data Analyst,73635,0 +66626,Male,44,Bachelors,8,84,36,21,1,8.0,2,60,Rural,ML Engineer,105601,0 +66627,Female,35,Bachelors,4,27,1,35,4,1.0,0,38,Semi-Urban,ML Engineer,137554,0 +66628,Male,22,Bachelors,10,95,49,89,23,8.0,2,83,Urban,Data Analyst,46657,1 +66629,Female,22,Masters,2,28,5,8,93,4.0,0,85,Urban,Software Engineer,115684,0 +66630,Female,45,Diploma,12,46,15,65,69,1.0,5,81,Semi-Urban,ML Engineer,94442,0 +66631,Male,43,Masters,8,21,91,84,19,2.0,3,29,Urban,Manager,117099,0 +66632,Male,30,Bachelors,5,80,66,31,41,8.0,4,28,Semi-Urban,HR Executive,81186,0 +66633,Male,33,PhD,1,27,52,68,5,5.0,3,43,Semi-Urban,ML Engineer,83979,0 +66634,Female,37,Bachelors,0,2,49,88,39,6.0,2,81,Urban,ML Engineer,145213,0 +66635,Female,24,High School,13,53,12,94,4,8.0,5,73,Rural,Manager,77623,0 +66636,Female,21,Diploma,6,35,90,80,99,5.0,3,57,Urban,ML Engineer,68066,1 +66637,Female,30,High School,7,3,44,67,68,6.0,7,33,Urban,Data Analyst,118968,0 +66638,Male,36,Bachelors,4,30,3,43,90,0.0,4,66,Urban,Manager,100364,0 +66639,Female,55,Masters,11,92,30,0,74,3.0,0,85,Rural,Data Analyst,58983,0 +66640,Female,55,Masters,17,43,94,78,21,9.0,6,94,Urban,ML Engineer,128977,1 +66641,Other,48,Masters,16,98,22,84,27,0.0,0,80,Urban,Manager,139053,1 +66642,Male,56,Diploma,8,40,54,1,58,3.0,5,63,Semi-Urban,HR Executive,84985,0 +66643,Male,54,High School,17,32,14,56,91,3.0,2,9,Urban,Data Analyst,34123,0 +66644,Male,52,PhD,10,97,39,52,89,2.0,5,66,Rural,Data Analyst,23998,1 +66645,Male,34,High School,5,35,40,40,8,2.0,7,13,Urban,Manager,50864,0 +66646,Male,26,Diploma,7,16,87,49,79,5.0,4,37,Rural,Manager,54975,0 +66647,Male,40,Masters,16,36,14,69,90,3.0,0,54,Semi-Urban,ML Engineer,117127,0 +66648,Male,52,Bachelors,1,20,42,96,27,3.0,4,83,Semi-Urban,Software Engineer,114335,1 +66649,Other,37,Bachelors,8,52,22,60,66,3.0,0,83,Semi-Urban,ML Engineer,58642,0 +66650,Other,36,Masters,11,70,35,60,21,2.0,3,74,Semi-Urban,Manager,98657,0 +66651,Male,44,Bachelors,13,80,10,70,97,2.0,5,22,Urban,Software Engineer,75751,0 +66652,Female,48,Masters,4,93,22,88,56,2.0,7,67,Urban,Data Analyst,33846,1 +66653,Female,55,High School,15,23,59,77,8,6.0,6,66,Urban,Software Engineer,129753,0 +66654,Male,32,Bachelors,19,1,99,46,73,2.0,5,19,Urban,ML Engineer,36667,0 +66655,Male,30,Masters,3,5,97,27,83,7.0,7,24,Rural,ML Engineer,141950,0 +66656,Male,29,Bachelors,11,26,67,8,63,8.0,3,32,Urban,Software Engineer,97838,0 +66657,Male,40,High School,4,14,4,43,9,1.0,2,5,Semi-Urban,Manager,33608,0 +66658,Female,49,Masters,0,52,10,80,28,7.0,0,43,Rural,Software Engineer,65251,0 +66659,Male,48,Masters,1,30,72,43,59,6.0,0,40,Urban,ML Engineer,84738,0 +66660,Female,58,High School,4,95,49,21,57,1.0,3,29,Urban,HR Executive,149734,0 +66661,Male,21,Bachelors,14,69,73,48,12,3.0,5,65,Urban,HR Executive,24611,1 +66662,Male,54,Bachelors,18,52,23,6,11,3.0,0,72,Urban,Manager,22035,0 +66663,Male,24,High School,0,99,92,57,11,3.0,5,82,Urban,Software Engineer,76863,1 +66664,Male,45,Bachelors,9,32,32,5,31,8.0,7,47,Semi-Urban,Manager,116260,0 +66665,Female,31,Bachelors,2,32,33,41,1,5.0,1,54,Semi-Urban,Manager,145157,0 +66666,Female,55,Bachelors,2,78,27,82,77,5.0,6,71,Urban,ML Engineer,39314,1 +66667,Male,56,Diploma,13,84,68,34,98,6.0,6,62,Semi-Urban,HR Executive,77333,1 +66668,Male,23,Diploma,5,17,19,5,44,7.0,4,44,Semi-Urban,ML Engineer,25095,0 +66669,Female,57,Diploma,9,4,29,29,4,7.0,1,88,Semi-Urban,Manager,142769,0 +66670,Male,38,Diploma,5,78,96,77,17,5.0,1,39,Urban,HR Executive,71431,1 +66671,Female,31,Diploma,11,58,72,83,73,1.0,5,42,Urban,Software Engineer,149075,1 +66672,Male,32,Masters,4,67,87,86,48,2.0,7,36,Urban,ML Engineer,50704,1 +66673,Female,45,Bachelors,10,80,22,2,18,4.0,1,52,Semi-Urban,HR Executive,138283,0 +66674,Male,51,Bachelors,14,66,14,28,36,6.0,5,57,Urban,Software Engineer,27577,0 +66675,Female,27,High School,9,9,27,88,81,9.0,5,3,Urban,Manager,62988,0 +66676,Male,45,High School,6,80,36,43,18,9.0,2,48,Urban,Software Engineer,105959,0 +66677,Male,23,Bachelors,0,60,27,26,78,5.0,4,56,Semi-Urban,Manager,33468,0 +66678,Male,54,Bachelors,1,2,51,21,84,5.0,3,52,Semi-Urban,ML Engineer,40371,0 +66679,Other,32,Bachelors,2,22,62,74,94,3.0,1,36,Urban,Manager,20062,0 +66680,Male,45,High School,12,80,76,75,97,3.0,1,66,Urban,Data Analyst,23059,1 +66681,Female,34,Bachelors,9,98,15,53,25,9.0,3,88,Urban,Data Analyst,52105,1 +66682,Male,40,Bachelors,1,59,11,43,81,6.0,7,85,Urban,Software Engineer,62582,0 +66683,Male,47,Diploma,12,10,68,48,4,2.0,2,89,Semi-Urban,Manager,43306,0 +66684,Female,58,High School,8,75,10,78,95,2.0,7,47,Semi-Urban,Data Analyst,101516,0 +66685,Female,24,Bachelors,1,85,83,18,6,4.0,6,70,Semi-Urban,HR Executive,145638,1 +66686,Female,56,Diploma,0,22,46,67,87,3.0,0,59,Rural,Manager,87022,0 +66687,Male,54,Diploma,12,5,42,56,75,0.0,0,68,Semi-Urban,ML Engineer,66250,0 +66688,Female,53,High School,14,93,50,90,41,9.0,6,77,Urban,Software Engineer,124430,1 +66689,Male,55,Masters,14,14,93,94,89,4.0,0,4,Urban,ML Engineer,96715,0 +66690,Male,49,High School,16,25,19,47,80,0.0,1,46,Rural,Manager,85739,0 +66691,Male,43,Bachelors,9,46,87,98,15,1.0,5,17,Rural,HR Executive,80537,1 +66692,Male,42,Masters,15,34,1,70,78,0.0,4,53,Urban,Data Analyst,97816,0 +66693,Male,27,Diploma,3,12,21,25,42,7.0,2,47,Semi-Urban,ML Engineer,112186,0 +66694,Male,34,Bachelors,6,46,49,40,98,8.0,0,64,Rural,Software Engineer,66377,0 +66695,Other,58,Bachelors,10,36,62,32,55,2.0,7,17,Urban,Data Analyst,92559,0 +66696,Female,25,Masters,16,48,95,63,8,2.0,3,13,Urban,HR Executive,102986,0 +66697,Male,54,Bachelors,0,32,35,74,49,5.0,5,68,Urban,Data Analyst,73591,0 +66698,Female,29,Masters,4,60,8,60,87,8.0,5,95,Urban,Data Analyst,41705,0 +66699,Male,23,High School,3,13,0,10,25,3.0,3,72,Urban,ML Engineer,75393,0 +66700,Male,42,Bachelors,1,90,71,44,49,2.0,6,75,Rural,ML Engineer,113246,1 +66701,Male,22,PhD,5,13,86,75,7,6.0,7,68,Semi-Urban,HR Executive,53834,1 +66702,Male,44,Diploma,5,57,64,10,94,5.0,1,23,Semi-Urban,Manager,60054,0 +66703,Male,32,High School,7,1,61,45,37,7.0,4,74,Semi-Urban,ML Engineer,101728,0 +66704,Female,25,Diploma,14,33,96,81,54,1.0,5,8,Urban,ML Engineer,112003,0 +66705,Male,22,Diploma,15,37,47,42,72,9.0,4,37,Urban,ML Engineer,111974,0 +66706,Female,42,Masters,2,63,39,71,88,4.0,6,5,Rural,Software Engineer,120537,0 +66707,Female,40,Bachelors,9,47,96,62,80,1.0,3,50,Semi-Urban,Data Analyst,46036,1 +66708,Male,52,Masters,19,87,33,13,73,3.0,2,57,Urban,Data Analyst,53004,0 +66709,Female,30,Masters,3,75,55,6,66,0.0,4,94,Rural,Data Analyst,91192,0 +66710,Male,21,High School,2,51,17,63,98,8.0,3,66,Urban,ML Engineer,21443,0 +66711,Male,53,Bachelors,1,39,77,36,7,8.0,2,90,Rural,Software Engineer,27379,1 +66712,Female,51,Bachelors,15,17,5,5,18,4.0,1,61,Semi-Urban,HR Executive,130099,0 +66713,Male,50,High School,3,64,5,73,36,9.0,2,76,Urban,Software Engineer,66212,0 +66714,Male,30,Diploma,6,68,67,69,77,3.0,1,19,Rural,Software Engineer,96939,0 +66715,Male,46,Diploma,0,80,58,35,83,0.0,5,19,Semi-Urban,Manager,54513,0 +66716,Female,38,PhD,15,47,18,81,67,6.0,7,67,Urban,ML Engineer,80436,0 +66717,Male,55,High School,11,41,33,93,99,6.0,7,33,Rural,HR Executive,49373,0 +66718,Male,32,Masters,3,75,10,84,91,3.0,1,60,Rural,ML Engineer,48389,0 +66719,Female,29,Masters,18,41,86,55,7,5.0,7,28,Rural,HR Executive,22630,0 +66720,Male,55,Bachelors,15,65,79,58,35,5.0,4,10,Rural,ML Engineer,90120,0 +66721,Male,42,High School,18,43,80,90,43,5.0,7,1,Urban,ML Engineer,50203,0 +66722,Male,49,Masters,17,76,91,42,65,9.0,3,18,Urban,Data Analyst,120320,0 +66723,Male,24,Masters,11,22,86,33,14,7.0,6,91,Semi-Urban,ML Engineer,21077,0 +66724,Female,22,Bachelors,0,92,97,78,55,1.0,5,12,Semi-Urban,Data Analyst,54033,1 +66725,Male,26,Masters,10,34,53,29,6,6.0,2,60,Rural,Manager,35114,0 +66726,Male,27,High School,7,20,13,18,83,0.0,5,49,Urban,Data Analyst,115138,0 +66727,Male,54,Bachelors,10,38,85,9,78,0.0,0,21,Urban,Software Engineer,138565,0 +66728,Male,45,Masters,10,73,85,16,5,7.0,3,34,Semi-Urban,ML Engineer,72868,0 +66729,Female,23,Bachelors,1,9,68,67,24,5.0,2,42,Semi-Urban,HR Executive,135553,0 +66730,Female,30,Bachelors,1,97,22,93,35,2.0,5,68,Rural,Software Engineer,62891,1 +66731,Female,49,Bachelors,7,92,20,94,29,1.0,2,76,Semi-Urban,Software Engineer,45614,1 +66732,Male,47,Bachelors,7,67,32,64,0,6.0,0,41,Urban,HR Executive,111602,0 +66733,Male,42,Masters,18,95,97,25,86,1.0,5,15,Urban,Manager,141824,0 +66734,Male,50,Diploma,0,0,53,17,70,6.0,2,6,Urban,Software Engineer,123914,0 +66735,Female,21,Diploma,3,14,85,93,69,0.0,5,89,Urban,Data Analyst,26258,1 +66736,Male,56,PhD,13,68,51,73,65,3.0,1,35,Urban,Manager,127113,0 +66737,Female,48,Bachelors,0,92,73,2,9,5.0,4,20,Semi-Urban,Manager,95015,0 +66738,Male,56,Diploma,3,94,93,55,42,9.0,1,24,Urban,ML Engineer,134313,1 +66739,Male,31,Bachelors,12,76,17,93,65,3.0,1,0,Semi-Urban,Data Analyst,118948,0 +66740,Female,37,Diploma,5,37,67,27,8,5.0,1,77,Urban,HR Executive,101910,0 +66741,Male,56,Bachelors,5,22,59,17,0,9.0,7,48,Urban,Software Engineer,49836,0 +66742,Male,31,Bachelors,19,49,50,77,56,9.0,3,7,Urban,ML Engineer,86371,0 +66743,Male,21,High School,7,94,12,9,89,2.0,7,93,Semi-Urban,Manager,107217,0 +66744,Male,36,Bachelors,12,76,9,61,86,5.0,1,90,Semi-Urban,ML Engineer,124463,1 +66745,Female,34,High School,15,79,2,44,86,9.0,3,28,Rural,ML Engineer,81906,0 +66746,Other,58,Masters,1,71,47,64,39,4.0,6,36,Urban,Manager,80662,0 +66747,Female,37,Bachelors,9,76,16,59,36,2.0,2,76,Urban,Data Analyst,38327,0 +66748,Male,48,High School,11,55,83,30,0,3.0,7,4,Urban,Software Engineer,26688,0 +66749,Female,37,Bachelors,3,54,74,70,1,3.0,2,73,Semi-Urban,ML Engineer,102547,1 +66750,Male,36,PhD,13,22,50,91,15,7.0,3,41,Urban,Software Engineer,123425,0 +66751,Male,41,High School,5,55,64,25,85,0.0,7,26,Urban,HR Executive,64799,0 +66752,Male,36,Bachelors,10,59,29,57,18,0.0,7,17,Semi-Urban,Software Engineer,124111,0 +66753,Male,53,Masters,13,59,15,38,71,2.0,4,49,Urban,Software Engineer,50303,0 +66754,Female,34,Bachelors,13,5,65,79,20,0.0,7,75,Rural,Data Analyst,28216,0 +66755,Male,44,High School,0,21,31,18,83,8.0,0,97,Urban,ML Engineer,104675,0 +66756,Male,37,Masters,2,70,18,86,44,9.0,3,73,Semi-Urban,Software Engineer,149243,1 +66757,Female,51,Bachelors,18,92,99,28,20,1.0,4,39,Semi-Urban,Manager,36052,1 +66758,Male,27,Bachelors,8,14,5,32,1,7.0,7,1,Urban,Manager,131192,0 +66759,Male,56,Bachelors,16,68,17,43,21,7.0,1,73,Urban,ML Engineer,45855,0 +66760,Female,48,Bachelors,10,71,61,79,69,7.0,1,56,Semi-Urban,Data Analyst,101044,1 +66761,Female,37,Bachelors,6,26,19,4,63,9.0,7,80,Semi-Urban,Software Engineer,115413,0 +66762,Male,34,Diploma,10,40,60,85,72,3.0,3,61,Urban,HR Executive,83169,1 +66763,Male,33,Masters,1,61,64,20,13,5.0,1,37,Urban,HR Executive,94920,0 +66764,Female,44,Bachelors,7,78,62,1,17,3.0,4,30,Rural,Software Engineer,114884,0 +66765,Male,43,Diploma,0,38,62,40,29,9.0,6,31,Urban,Manager,35023,0 +66766,Female,55,Diploma,0,42,63,45,88,0.0,7,20,Semi-Urban,Data Analyst,52745,0 +66767,Male,47,Masters,3,64,72,66,84,9.0,3,19,Urban,Data Analyst,50679,0 +66768,Male,29,PhD,1,77,73,8,8,5.0,5,23,Semi-Urban,ML Engineer,79919,0 +66769,Female,22,Bachelors,1,41,93,65,75,7.0,3,33,Urban,ML Engineer,83559,0 +66770,Male,33,Bachelors,1,15,8,43,74,0.0,2,49,Rural,Data Analyst,148146,0 +66771,Male,40,Bachelors,10,49,48,17,66,9.0,5,13,Semi-Urban,HR Executive,121331,0 +66772,Male,21,High School,17,28,3,91,47,0.0,7,37,Semi-Urban,HR Executive,119278,0 +66773,Male,27,Diploma,1,45,49,44,94,7.0,4,83,Urban,Software Engineer,100235,0 +66774,Male,30,Diploma,1,11,95,66,9,1.0,1,24,Urban,HR Executive,132306,0 +66775,Male,28,High School,7,19,26,14,6,3.0,5,15,Rural,Software Engineer,112839,0 +66776,Male,56,Bachelors,7,96,89,59,44,8.0,4,48,Urban,Data Analyst,81264,1 +66777,Female,53,Bachelors,13,7,42,88,81,5.0,3,70,Rural,Data Analyst,90158,0 +66778,Female,34,Bachelors,17,4,97,65,64,6.0,4,26,Semi-Urban,HR Executive,97800,0 +66779,Female,36,Masters,4,2,11,79,67,8.0,3,50,Urban,Manager,74247,0 +66780,Male,44,Diploma,17,52,66,54,12,2.0,7,32,Semi-Urban,HR Executive,58152,0 +66781,Male,51,Diploma,9,68,1,85,51,8.0,1,84,Rural,Software Engineer,65172,1 +66782,Male,27,Bachelors,17,43,27,85,81,4.0,4,73,Urban,HR Executive,73205,0 +66783,Male,35,Bachelors,0,26,88,25,5,0.0,6,80,Semi-Urban,Software Engineer,118675,0 +66784,Male,21,Bachelors,10,1,9,46,29,8.0,0,44,Urban,Manager,52287,0 +66785,Female,24,Masters,13,23,84,21,37,1.0,2,73,Urban,Software Engineer,94856,0 +66786,Male,29,Bachelors,9,32,69,55,71,3.0,7,29,Semi-Urban,HR Executive,53184,0 +66787,Male,22,Bachelors,2,41,17,6,56,4.0,2,63,Urban,Software Engineer,59863,0 +66788,Male,50,Diploma,4,16,88,13,82,6.0,2,30,Urban,Data Analyst,57786,0 +66789,Male,31,High School,2,37,62,47,47,5.0,2,8,Urban,ML Engineer,116565,0 +66790,Male,22,Bachelors,1,46,95,62,91,9.0,3,49,Urban,Software Engineer,38943,1 +66791,Male,42,Bachelors,0,30,21,15,46,2.0,1,51,Urban,Data Analyst,126741,0 +66792,Male,42,Bachelors,16,30,93,96,3,3.0,4,88,Urban,Manager,137068,1 +66793,Male,31,Bachelors,11,56,80,34,36,8.0,1,18,Rural,ML Engineer,107140,0 +66794,Male,23,Bachelors,16,16,7,1,76,6.0,7,10,Urban,Manager,56705,0 +66795,Male,28,Bachelors,15,31,96,71,88,0.0,1,54,Urban,HR Executive,143205,1 +66796,Male,33,Bachelors,6,7,14,97,3,3.0,6,82,Urban,ML Engineer,127633,0 +66797,Male,48,Masters,1,96,22,47,40,4.0,3,63,Rural,Data Analyst,136740,0 +66798,Female,49,Diploma,3,95,53,43,54,1.0,2,79,Rural,HR Executive,144066,1 +66799,Male,39,Masters,12,74,33,28,30,7.0,5,79,Urban,Software Engineer,77844,0 +66800,Female,41,Bachelors,2,67,24,85,87,7.0,6,44,Urban,ML Engineer,130251,0 +66801,Male,59,Diploma,9,7,25,98,65,8.0,4,77,Semi-Urban,HR Executive,131054,0 +66802,Female,58,Diploma,14,35,37,4,82,0.0,7,39,Semi-Urban,Software Engineer,95993,0 +66803,Female,56,High School,12,1,96,4,40,2.0,5,93,Urban,Data Analyst,42728,0 +66804,Female,59,Masters,9,21,52,67,48,8.0,3,20,Urban,Software Engineer,130021,0 +66805,Male,45,Bachelors,4,84,64,46,29,5.0,7,66,Semi-Urban,Manager,70512,1 +66806,Male,35,Bachelors,7,97,29,39,47,3.0,0,95,Urban,HR Executive,125446,1 +66807,Female,23,Masters,8,52,92,29,83,1.0,1,95,Urban,Data Analyst,137103,1 +66808,Male,48,Diploma,5,94,92,96,77,3.0,6,91,Semi-Urban,ML Engineer,23715,1 +66809,Female,31,High School,19,67,30,72,87,8.0,6,80,Urban,Manager,58978,1 +66810,Female,32,Bachelors,12,0,77,18,80,2.0,3,75,Urban,Software Engineer,98734,0 +66811,Female,52,PhD,8,98,28,87,11,2.0,0,54,Urban,Software Engineer,20360,1 +66812,Male,24,Masters,12,98,58,83,95,2.0,3,2,Urban,ML Engineer,35022,1 +66813,Male,32,Bachelors,15,91,81,66,79,2.0,3,48,Urban,Manager,139296,1 +66814,Male,26,Bachelors,13,97,75,90,25,4.0,2,26,Urban,Software Engineer,33388,1 +66815,Female,45,Bachelors,4,62,26,17,69,2.0,7,6,Semi-Urban,HR Executive,145309,0 +66816,Male,52,High School,19,32,66,97,31,9.0,1,72,Urban,HR Executive,68258,1 +66817,Male,46,Bachelors,16,59,95,43,29,4.0,0,21,Urban,ML Engineer,61318,0 +66818,Female,43,Bachelors,2,41,29,53,54,4.0,1,21,Semi-Urban,Software Engineer,105365,0 +66819,Female,52,Bachelors,7,42,41,95,48,3.0,1,78,Semi-Urban,ML Engineer,80244,1 +66820,Male,58,Masters,16,83,98,40,69,4.0,4,20,Rural,HR Executive,120112,1 +66821,Male,22,Bachelors,5,54,46,97,91,7.0,1,49,Semi-Urban,Software Engineer,141088,1 +66822,Male,26,Bachelors,9,81,92,95,64,3.0,0,62,Urban,HR Executive,142984,1 +66823,Male,51,PhD,7,44,51,65,6,2.0,7,92,Urban,HR Executive,68389,1 +66824,Male,45,Bachelors,4,18,93,35,15,3.0,0,99,Urban,Software Engineer,63927,1 +66825,Female,59,Bachelors,14,44,9,88,86,8.0,4,23,Rural,HR Executive,78741,0 +66826,Female,57,Bachelors,4,77,27,90,42,1.0,1,74,Urban,Software Engineer,128415,1 +66827,Other,36,Bachelors,6,14,37,18,34,6.0,2,29,Urban,Software Engineer,97912,0 +66828,Male,47,Diploma,5,11,16,19,9,3.0,1,84,Urban,Software Engineer,137800,0 +66829,Other,37,High School,4,21,88,47,22,5.0,0,15,Semi-Urban,Software Engineer,126710,0 +66830,Male,26,Masters,4,28,56,87,75,4.0,1,61,Semi-Urban,HR Executive,107245,0 +66831,Female,53,Bachelors,8,51,41,36,83,4.0,0,16,Urban,Software Engineer,45363,0 +66832,Other,42,Bachelors,0,59,38,77,1,9.0,6,40,Rural,ML Engineer,46624,0 +66833,Female,27,Bachelors,7,79,84,2,68,4.0,1,8,Urban,ML Engineer,72803,0 +66834,Male,58,Masters,15,39,1,93,58,3.0,7,47,Urban,Software Engineer,64706,0 +66835,Male,59,Bachelors,17,48,66,75,44,4.0,2,35,Rural,Software Engineer,26702,0 +66836,Female,47,High School,6,13,33,4,58,6.0,3,37,Rural,HR Executive,74049,0 +66837,Female,43,Bachelors,18,25,97,35,43,5.0,4,64,Semi-Urban,ML Engineer,112500,0 +66838,Male,39,Diploma,18,69,36,34,36,2.0,5,84,Semi-Urban,ML Engineer,102374,0 +66839,Female,31,Bachelors,11,75,26,77,37,8.0,3,9,Urban,ML Engineer,56009,0 +66840,Female,39,Bachelors,17,19,49,42,37,5.0,5,11,Semi-Urban,Software Engineer,106336,0 +66841,Male,29,High School,8,23,64,9,71,3.0,3,10,Semi-Urban,Manager,126560,0 +66842,Male,59,High School,10,11,70,55,39,3.0,0,0,Rural,ML Engineer,31812,0 +66843,Other,44,Bachelors,14,88,17,74,76,1.0,1,53,Semi-Urban,Data Analyst,131201,0 +66844,Male,40,Bachelors,2,33,73,15,65,2.0,2,31,Urban,Software Engineer,149741,0 +66845,Female,38,Bachelors,12,60,39,33,99,0.0,4,89,Urban,HR Executive,85850,0 +66846,Female,28,Bachelors,7,22,41,64,35,9.0,2,29,Semi-Urban,HR Executive,98302,0 +66847,Male,31,Bachelors,14,68,92,44,87,7.0,0,49,Semi-Urban,HR Executive,87076,1 +66848,Female,28,Diploma,0,33,54,66,66,9.0,5,41,Semi-Urban,ML Engineer,141185,0 +66849,Male,56,Bachelors,1,13,7,94,94,0.0,6,41,Urban,Software Engineer,110976,0 +66850,Male,33,Bachelors,9,66,89,42,14,0.0,0,43,Rural,ML Engineer,133685,1 +66851,Female,21,Bachelors,11,43,72,67,37,6.0,2,3,Semi-Urban,ML Engineer,86949,0 +66852,Male,52,Bachelors,3,22,81,11,53,6.0,0,48,Urban,HR Executive,55720,0 +66853,Male,47,Bachelors,11,63,19,35,95,4.0,5,78,Urban,HR Executive,75978,0 +66854,Male,29,Bachelors,12,74,69,3,36,1.0,6,75,Urban,Data Analyst,98376,0 +66855,Male,27,Bachelors,3,38,81,40,52,8.0,0,13,Semi-Urban,Manager,138358,0 +66856,Male,26,Bachelors,18,4,77,7,1,4.0,0,58,Rural,Data Analyst,108749,0 +66857,Male,37,High School,1,40,25,85,32,8.0,1,41,Semi-Urban,ML Engineer,46427,0 +66858,Female,33,Bachelors,2,19,63,61,90,7.0,2,20,Semi-Urban,HR Executive,138855,0 +66859,Male,46,Bachelors,2,70,32,76,8,5.0,2,5,Semi-Urban,Data Analyst,34568,0 +66860,Male,29,Bachelors,18,62,18,16,71,1.0,7,91,Rural,HR Executive,128616,0 +66861,Female,50,Bachelors,5,30,14,29,71,2.0,2,64,Urban,Data Analyst,36129,0 +66862,Male,52,Masters,10,15,52,65,99,4.0,0,97,Urban,Software Engineer,147846,0 +66863,Male,40,Bachelors,17,26,57,30,80,5.0,3,47,Rural,ML Engineer,85228,0 +66864,Female,35,Bachelors,19,28,30,74,53,3.0,6,66,Semi-Urban,HR Executive,40819,0 +66865,Male,55,Bachelors,16,48,34,71,27,0.0,6,2,Semi-Urban,Manager,48804,0 +66866,Male,36,Bachelors,8,26,32,63,40,0.0,0,79,Urban,Software Engineer,110350,0 +66867,Male,54,Masters,16,16,70,49,58,3.0,0,85,Semi-Urban,HR Executive,140743,0 +66868,Other,59,Bachelors,11,92,27,74,2,6.0,0,61,Semi-Urban,Manager,114372,1 +66869,Female,29,Diploma,2,95,5,54,13,1.0,6,73,Rural,Software Engineer,31454,0 +66870,Male,45,PhD,13,11,58,79,89,5.0,0,55,Rural,Software Engineer,134433,0 +66871,Male,21,Bachelors,8,53,65,8,30,2.0,2,92,Semi-Urban,Manager,76450,0 +66872,Female,39,Diploma,2,28,46,67,81,6.0,1,88,Urban,ML Engineer,127536,0 +66873,Male,33,Bachelors,13,88,49,51,80,1.0,0,91,Semi-Urban,ML Engineer,24849,1 +66874,Male,31,Masters,7,42,40,0,60,3.0,7,95,Urban,Data Analyst,47850,0 +66875,Male,24,Bachelors,18,85,52,37,0,0.0,4,88,Urban,HR Executive,97998,1 +66876,Female,35,Masters,9,98,71,65,11,0.0,1,41,Urban,Manager,68124,1 +66877,Female,32,Bachelors,18,31,46,19,53,4.0,0,51,Urban,HR Executive,101780,0 +66878,Male,43,Masters,0,14,68,19,90,3.0,1,75,Urban,Data Analyst,104407,0 +66879,Male,25,High School,4,13,73,81,17,9.0,6,61,Rural,HR Executive,72490,0 +66880,Male,55,Bachelors,5,38,99,26,38,4.0,6,73,Urban,Manager,84205,1 +66881,Male,43,PhD,1,88,72,21,21,8.0,0,6,Urban,ML Engineer,70457,0 +66882,Male,35,Bachelors,0,38,87,0,66,5.0,5,33,Urban,HR Executive,114649,0 +66883,Male,25,Bachelors,10,52,75,66,66,6.0,3,2,Rural,Data Analyst,31250,0 +66884,Male,26,Bachelors,2,76,41,18,1,7.0,3,48,Semi-Urban,Data Analyst,28860,0 +66885,Male,34,PhD,10,30,82,79,8,8.0,5,99,Semi-Urban,Software Engineer,137067,1 +66886,Male,32,Bachelors,16,21,97,26,99,6.0,1,99,Urban,Software Engineer,85451,1 +66887,Female,37,Diploma,14,58,25,76,82,4.0,6,20,Urban,Manager,105091,0 +66888,Male,27,Diploma,19,86,6,13,83,2.0,5,58,Rural,Software Engineer,39841,0 +66889,Female,41,Bachelors,5,18,58,99,1,6.0,4,24,Semi-Urban,ML Engineer,78461,0 +66890,Male,52,High School,4,20,33,63,15,5.0,1,54,Semi-Urban,ML Engineer,119382,0 +66891,Male,29,PhD,14,22,78,91,82,6.0,7,9,Rural,Software Engineer,103604,0 +66892,Male,27,Bachelors,17,32,88,44,23,5.0,5,35,Urban,ML Engineer,26573,0 +66893,Female,30,High School,5,57,51,27,77,6.0,0,39,Semi-Urban,HR Executive,90417,0 +66894,Male,38,High School,18,73,31,58,31,4.0,1,10,Rural,ML Engineer,103158,0 +66895,Male,48,Bachelors,9,77,51,49,75,1.0,3,27,Semi-Urban,Manager,87293,0 +66896,Male,23,PhD,6,99,50,86,8,8.0,2,40,Rural,ML Engineer,60887,1 +66897,Other,40,Bachelors,13,53,20,96,62,5.0,6,73,Urban,ML Engineer,138091,1 +66898,Other,35,Bachelors,15,68,83,88,74,0.0,1,32,Urban,HR Executive,84996,1 +66899,Female,49,Masters,12,97,23,71,10,5.0,1,94,Semi-Urban,Manager,95296,1 +66900,Male,34,High School,19,79,27,28,62,1.0,6,26,Urban,ML Engineer,76752,0 +66901,Female,51,Masters,1,59,18,15,40,7.0,0,21,Urban,Manager,34583,0 +66902,Male,56,High School,14,37,59,74,79,7.0,4,76,Urban,HR Executive,68934,1 +66903,Female,48,Bachelors,15,14,53,72,22,0.0,0,83,Semi-Urban,HR Executive,135348,0 +66904,Female,48,Bachelors,5,98,2,25,74,1.0,7,32,Rural,ML Engineer,109924,0 +66905,Male,24,Diploma,5,39,77,10,81,0.0,4,17,Urban,Manager,129379,0 +66906,Female,31,PhD,18,92,52,44,99,9.0,0,3,Urban,Software Engineer,75478,0 +66907,Female,35,Masters,6,7,9,16,15,8.0,5,36,Rural,Data Analyst,84488,0 +66908,Male,35,High School,16,13,94,95,15,1.0,1,88,Urban,HR Executive,101555,1 +66909,Female,34,Bachelors,15,69,65,98,47,9.0,0,87,Urban,Manager,119029,1 +66910,Male,22,High School,12,92,14,85,44,4.0,3,86,Urban,Data Analyst,23203,1 +66911,Female,21,Bachelors,1,71,30,13,10,8.0,5,43,Semi-Urban,HR Executive,126279,0 +66912,Male,42,Diploma,3,39,89,76,36,9.0,6,22,Urban,Manager,71575,0 +66913,Male,22,Masters,18,85,2,67,89,9.0,5,16,Rural,HR Executive,35916,0 +66914,Male,21,High School,3,55,46,62,99,8.0,5,95,Urban,Software Engineer,51750,1 +66915,Female,31,Bachelors,12,73,37,27,79,7.0,3,24,Urban,Manager,135741,0 +66916,Other,49,PhD,4,57,33,83,27,2.0,7,20,Urban,Software Engineer,93314,0 +66917,Male,21,High School,16,9,88,92,85,7.0,3,54,Urban,Manager,40998,1 +66918,Male,34,Bachelors,6,60,44,84,70,1.0,0,19,Urban,Data Analyst,25775,0 +66919,Female,55,Masters,0,86,41,53,56,3.0,6,63,Urban,HR Executive,141554,1 +66920,Male,23,Bachelors,8,29,67,59,61,6.0,1,80,Semi-Urban,HR Executive,132752,1 +66921,Other,51,Bachelors,7,91,97,87,75,3.0,2,8,Urban,Manager,116334,1 +66922,Female,58,Bachelors,4,32,14,97,24,7.0,5,78,Semi-Urban,Data Analyst,23598,0 +66923,Female,50,Diploma,4,5,14,19,36,0.0,7,59,Urban,Software Engineer,143389,0 +66924,Female,55,Bachelors,18,21,60,64,7,2.0,5,10,Semi-Urban,Manager,23744,0 +66925,Female,45,Bachelors,16,52,48,59,22,3.0,5,7,Rural,Software Engineer,65445,0 +66926,Male,27,Masters,7,85,47,40,12,4.0,1,50,Urban,ML Engineer,55983,0 +66927,Male,56,Diploma,2,77,15,9,51,2.0,2,73,Rural,Software Engineer,75945,0 +66928,Male,56,Diploma,9,11,40,12,17,5.0,0,27,Urban,Manager,52536,0 +66929,Female,54,Diploma,1,25,58,68,69,4.0,5,15,Urban,Software Engineer,71921,0 +66930,Female,25,Masters,16,37,63,8,23,6.0,3,25,Rural,ML Engineer,66904,0 +66931,Male,36,Bachelors,19,59,67,25,17,3.0,0,8,Urban,Data Analyst,133402,0 +66932,Male,30,Masters,2,1,22,75,39,0.0,5,54,Urban,Data Analyst,131677,0 +66933,Male,27,Diploma,6,30,38,75,87,8.0,5,49,Rural,Data Analyst,35884,0 +66934,Female,42,High School,2,84,38,18,14,3.0,0,1,Semi-Urban,HR Executive,139121,0 +66935,Male,33,Bachelors,7,20,22,74,81,9.0,2,87,Rural,HR Executive,49724,0 +66936,Male,26,Bachelors,10,20,2,81,17,4.0,3,72,Urban,ML Engineer,22385,0 +66937,Male,44,Bachelors,13,11,18,94,45,4.0,1,97,Urban,HR Executive,20108,0 +66938,Male,22,Masters,5,71,62,35,63,6.0,3,63,Urban,ML Engineer,86495,0 +66939,Male,31,High School,13,83,37,56,13,6.0,3,49,Semi-Urban,HR Executive,43185,0 +66940,Male,24,Bachelors,5,30,14,1,14,8.0,4,37,Urban,Data Analyst,130898,0 +66941,Female,55,PhD,0,22,63,9,55,5.0,1,90,Urban,HR Executive,113588,0 +66942,Male,26,Bachelors,8,7,50,39,8,9.0,1,28,Semi-Urban,ML Engineer,64207,0 +66943,Male,51,Bachelors,13,77,35,75,16,4.0,7,32,Urban,HR Executive,127291,0 +66944,Male,46,PhD,19,16,11,64,92,0.0,3,35,Urban,Manager,61426,0 +66945,Female,31,Bachelors,13,0,94,50,11,3.0,3,1,Urban,ML Engineer,21634,0 +66946,Male,51,Diploma,18,68,22,58,20,1.0,4,35,Urban,Manager,28880,0 +66947,Male,38,Masters,11,9,50,48,14,5.0,1,25,Urban,Data Analyst,79974,0 +66948,Male,42,Bachelors,16,68,17,59,36,8.0,6,34,Urban,ML Engineer,39021,0 +66949,Male,37,Masters,7,59,86,19,20,0.0,6,50,Urban,Manager,87116,0 +66950,Male,23,Bachelors,8,26,57,86,81,5.0,1,8,Rural,Software Engineer,20290,0 +66951,Male,46,Masters,11,59,28,85,51,7.0,1,84,Semi-Urban,ML Engineer,141379,1 +66952,Male,48,Masters,13,58,53,56,34,7.0,3,30,Semi-Urban,Manager,148762,0 +66953,Male,31,Bachelors,2,72,84,15,66,6.0,3,66,Urban,Data Analyst,60317,1 +66954,Female,27,Bachelors,2,78,56,45,37,9.0,0,80,Semi-Urban,Data Analyst,147909,1 +66955,Female,32,Diploma,12,5,78,95,99,2.0,6,58,Urban,HR Executive,138158,0 +66956,Male,34,Diploma,11,84,93,22,2,9.0,7,79,Urban,Software Engineer,98368,1 +66957,Male,37,Bachelors,12,44,98,28,66,6.0,5,78,Urban,Manager,59283,1 +66958,Male,40,Bachelors,3,75,22,93,26,6.0,0,94,Rural,Software Engineer,34133,1 +66959,Male,21,Bachelors,19,38,30,80,41,0.0,0,51,Urban,Manager,100509,0 +66960,Male,48,High School,13,27,31,31,91,5.0,0,4,Urban,Software Engineer,119396,0 +66961,Male,37,Bachelors,6,65,44,8,91,0.0,5,26,Urban,Software Engineer,115887,0 +66962,Female,59,Diploma,13,35,35,13,29,2.0,1,58,Rural,HR Executive,106672,0 +66963,Female,32,Masters,1,79,64,74,55,8.0,2,72,Urban,ML Engineer,144630,1 +66964,Other,41,Diploma,12,53,37,44,25,3.0,2,98,Urban,Software Engineer,133844,0 +66965,Male,27,Masters,4,55,84,70,97,2.0,1,84,Rural,Data Analyst,59707,1 +66966,Female,44,Diploma,19,46,66,0,82,2.0,6,62,Urban,Data Analyst,69875,0 +66967,Female,23,High School,11,26,74,29,35,4.0,5,42,Rural,ML Engineer,43263,0 +66968,Female,34,Diploma,17,94,51,48,82,8.0,1,73,Rural,Data Analyst,120691,1 +66969,Male,29,Bachelors,17,64,49,68,88,0.0,2,92,Urban,Data Analyst,60264,1 +66970,Female,40,Bachelors,8,87,88,92,66,8.0,4,54,Urban,HR Executive,96604,1 +66971,Male,58,Masters,19,56,25,86,22,8.0,2,81,Rural,HR Executive,26535,1 +66972,Male,24,Diploma,14,5,50,33,64,9.0,3,4,Semi-Urban,ML Engineer,103903,0 +66973,Male,41,High School,5,55,22,39,17,7.0,5,14,Urban,Software Engineer,121489,0 +66974,Female,27,Bachelors,15,53,90,27,62,1.0,4,27,Urban,Data Analyst,147775,0 +66975,Other,32,Diploma,7,23,39,6,69,5.0,1,95,Urban,Manager,49428,0 +66976,Female,32,Masters,18,68,33,50,2,6.0,7,29,Urban,HR Executive,49671,0 +66977,Female,35,Masters,18,74,62,66,5,1.0,1,97,Semi-Urban,Data Analyst,127530,1 +66978,Male,35,Bachelors,5,40,20,40,29,6.0,2,25,Semi-Urban,Software Engineer,34166,0 +66979,Female,42,Bachelors,10,57,45,69,14,0.0,1,13,Semi-Urban,ML Engineer,63049,0 +66980,Male,22,Bachelors,14,38,61,24,31,9.0,1,10,Urban,HR Executive,87259,0 +66981,Male,43,Bachelors,14,58,42,83,28,5.0,4,59,Urban,ML Engineer,93749,1 +66982,Female,51,Bachelors,3,11,70,36,63,3.0,0,25,Semi-Urban,Software Engineer,142913,0 +66983,Female,53,Diploma,10,39,49,99,7,3.0,2,37,Semi-Urban,Manager,77996,0 +66984,Female,21,High School,4,17,5,73,65,5.0,3,38,Semi-Urban,Manager,72545,0 +66985,Female,23,Masters,1,84,57,37,41,2.0,6,0,Rural,Data Analyst,52753,0 +66986,Male,35,Diploma,10,40,54,80,44,6.0,1,94,Rural,Software Engineer,66135,1 +66987,Male,38,Diploma,12,60,55,45,7,6.0,6,26,Rural,HR Executive,47020,0 +66988,Female,54,Bachelors,17,26,74,56,57,4.0,4,61,Semi-Urban,HR Executive,81741,0 +66989,Male,28,Bachelors,12,32,4,56,97,6.0,0,56,Urban,HR Executive,62840,0 +66990,Male,57,Diploma,1,57,87,29,52,2.0,2,94,Urban,HR Executive,98631,1 +66991,Male,50,Diploma,6,48,44,81,12,1.0,7,30,Urban,HR Executive,89743,0 +66992,Male,54,Diploma,6,60,75,54,22,9.0,5,88,Semi-Urban,HR Executive,83693,1 +66993,Male,22,Bachelors,15,17,87,53,27,9.0,1,25,Rural,HR Executive,50133,0 +66994,Male,56,Diploma,15,64,73,46,91,0.0,0,36,Semi-Urban,Manager,139385,0 +66995,Female,27,Masters,8,4,22,6,3,1.0,3,49,Urban,Software Engineer,84267,0 +66996,Female,56,Masters,1,43,84,35,36,8.0,4,92,Urban,Software Engineer,114445,1 +66997,Male,54,PhD,1,22,42,35,70,0.0,7,69,Semi-Urban,Data Analyst,67001,0 +66998,Female,30,Bachelors,19,62,39,42,21,9.0,1,10,Urban,Manager,147599,0 +66999,Male,36,Bachelors,14,36,57,86,73,8.0,2,41,Urban,Manager,130009,0 +67000,Female,53,Bachelors,8,0,63,55,93,1.0,3,33,Semi-Urban,ML Engineer,80878,0 +67001,Male,49,Bachelors,8,63,24,81,1,4.0,0,64,Urban,Data Analyst,59882,0 +67002,Female,54,Bachelors,13,8,57,30,33,5.0,7,4,Urban,Manager,120132,0 +67003,Female,52,Masters,8,95,71,80,10,1.0,1,91,Urban,Manager,147946,1 +67004,Male,33,Diploma,15,44,84,17,70,5.0,3,82,Semi-Urban,ML Engineer,24928,0 +67005,Female,54,High School,18,25,42,7,62,0.0,2,14,Semi-Urban,Manager,132197,0 +67006,Male,27,Diploma,6,44,74,28,72,8.0,6,50,Urban,Software Engineer,68697,0 +67007,Female,46,Bachelors,18,80,48,82,24,7.0,0,97,Urban,HR Executive,28372,1 +67008,Male,48,Masters,6,39,66,50,52,8.0,3,93,Semi-Urban,ML Engineer,146429,1 +67009,Female,58,Bachelors,16,98,74,46,3,6.0,5,94,Rural,Manager,59469,1 +67010,Male,54,High School,10,84,52,34,28,2.0,5,4,Rural,Manager,25544,0 +67011,Female,30,Bachelors,18,76,30,97,38,2.0,0,29,Urban,Software Engineer,78056,0 +67012,Female,29,Diploma,13,51,61,56,10,0.0,1,21,Urban,Manager,129702,0 +67013,Male,35,Bachelors,10,2,31,60,74,6.0,4,92,Urban,ML Engineer,81643,0 +67014,Female,29,Bachelors,18,17,34,70,40,4.0,1,28,Semi-Urban,Data Analyst,36117,0 +67015,Male,27,Diploma,13,8,47,56,68,4.0,7,26,Urban,Software Engineer,29760,0 +67016,Female,55,Masters,5,95,25,79,84,5.0,3,0,Urban,HR Executive,147595,0 +67017,Male,47,PhD,10,57,79,36,92,3.0,6,91,Semi-Urban,ML Engineer,48752,1 +67018,Male,41,Diploma,18,61,30,33,48,1.0,6,58,Urban,ML Engineer,108460,0 +67019,Male,38,Bachelors,8,4,97,95,67,0.0,2,85,Urban,Software Engineer,51127,1 +67020,Female,47,High School,15,91,89,62,67,3.0,1,2,Urban,HR Executive,89742,1 +67021,Male,29,PhD,2,2,20,83,55,6.0,7,45,Urban,HR Executive,32236,0 +67022,Male,25,Diploma,14,45,21,22,67,4.0,5,86,Urban,ML Engineer,78343,0 +67023,Male,51,Diploma,12,46,78,38,84,9.0,3,41,Urban,ML Engineer,39670,0 +67024,Male,58,Bachelors,2,62,52,68,11,1.0,3,26,Urban,ML Engineer,133312,0 +67025,Male,53,Bachelors,14,36,96,56,58,4.0,3,3,Semi-Urban,Data Analyst,77218,0 +67026,Male,33,Bachelors,3,81,30,89,31,5.0,1,89,Rural,Data Analyst,52565,1 +67027,Female,37,Masters,17,91,39,2,9,8.0,7,38,Urban,HR Executive,149266,0 +67028,Male,29,Masters,4,43,17,29,89,7.0,4,19,Urban,Data Analyst,120266,0 +67029,Female,49,Bachelors,19,53,5,79,57,6.0,3,60,Semi-Urban,Manager,78369,0 +67030,Male,54,Bachelors,9,91,18,29,65,4.0,3,84,Urban,Manager,68089,0 +67031,Female,56,Masters,12,20,29,80,72,2.0,2,75,Urban,Manager,37890,0 +67032,Male,45,High School,7,33,16,22,45,0.0,3,64,Semi-Urban,Data Analyst,141823,0 +67033,Male,46,Bachelors,1,45,71,39,89,8.0,3,70,Semi-Urban,Software Engineer,40754,0 +67034,Male,22,Bachelors,15,78,37,1,13,4.0,4,3,Urban,Manager,82549,0 +67035,Male,26,Diploma,15,33,22,3,28,2.0,5,74,Urban,ML Engineer,119773,0 +67036,Male,55,Bachelors,0,44,37,72,31,6.0,4,18,Semi-Urban,ML Engineer,124846,0 +67037,Male,37,Masters,9,56,31,33,94,4.0,4,63,Urban,Software Engineer,43771,0 +67038,Male,55,Bachelors,10,25,97,87,61,9.0,5,87,Urban,Manager,104917,1 +67039,Male,52,High School,5,30,55,64,9,2.0,1,72,Semi-Urban,Manager,45255,0 +67040,Other,26,Bachelors,4,26,14,73,69,2.0,2,6,Urban,ML Engineer,24447,0 +67041,Male,32,Bachelors,0,55,97,97,7,4.0,3,84,Urban,Manager,123921,1 +67042,Female,45,Masters,6,60,26,84,73,3.0,1,46,Semi-Urban,Manager,62277,0 +67043,Male,59,Bachelors,17,65,3,44,75,9.0,6,9,Urban,HR Executive,36725,0 +67044,Male,52,PhD,9,78,2,82,8,9.0,3,30,Urban,Data Analyst,68572,0 +67045,Male,33,High School,8,81,70,5,91,7.0,3,19,Urban,HR Executive,123025,0 +67046,Female,46,Diploma,8,66,76,7,6,7.0,3,48,Urban,ML Engineer,117343,0 +67047,Female,22,High School,6,71,99,6,16,5.0,7,51,Urban,ML Engineer,72202,0 +67048,Female,25,Bachelors,11,14,45,11,30,5.0,0,3,Semi-Urban,ML Engineer,131599,0 +67049,Male,45,High School,15,25,16,48,94,7.0,2,32,Urban,HR Executive,43572,0 +67050,Other,34,Bachelors,18,21,15,20,14,1.0,1,92,Urban,Manager,89842,0 +67051,Male,27,Diploma,10,1,49,76,80,3.0,6,14,Urban,HR Executive,135668,0 +67052,Male,40,Bachelors,5,75,86,57,60,6.0,1,62,Rural,Software Engineer,54337,1 +67053,Male,33,Diploma,4,92,16,32,33,9.0,0,31,Semi-Urban,Software Engineer,146792,0 +67054,Male,52,Masters,6,30,93,31,90,7.0,4,84,Urban,ML Engineer,48384,1 +67055,Male,34,High School,4,43,63,15,85,2.0,5,96,Urban,Manager,141027,0 +67056,Female,46,Bachelors,18,41,78,82,35,0.0,2,95,Semi-Urban,HR Executive,72399,1 +67057,Male,25,PhD,13,37,10,30,55,1.0,7,94,Urban,Manager,116093,0 +67058,Male,57,High School,15,38,1,26,19,3.0,1,41,Urban,HR Executive,140680,0 +67059,Male,25,Bachelors,18,90,9,38,14,5.0,7,43,Urban,HR Executive,49188,0 +67060,Male,33,Diploma,17,96,69,73,15,1.0,5,65,Urban,ML Engineer,112629,1 +67061,Male,47,Bachelors,9,41,56,60,8,5.0,7,63,Urban,HR Executive,126508,0 +67062,Male,39,Masters,17,61,46,71,19,9.0,3,92,Urban,Data Analyst,145529,1 +67063,Male,30,Diploma,10,41,9,41,52,4.0,2,61,Rural,Software Engineer,145324,0 +67064,Male,56,High School,19,55,60,2,2,4.0,3,8,Urban,Data Analyst,96149,0 +67065,Other,32,High School,14,60,8,74,7,6.0,0,92,Semi-Urban,HR Executive,114308,0 +67066,Female,36,Bachelors,7,68,73,47,72,8.0,4,71,Semi-Urban,HR Executive,46349,1 +67067,Male,24,High School,12,94,0,20,11,9.0,7,21,Urban,HR Executive,35535,0 +67068,Female,57,High School,13,73,98,85,69,2.0,0,97,Urban,ML Engineer,40595,1 +67069,Male,47,Bachelors,1,97,54,58,76,5.0,2,63,Urban,Software Engineer,148094,1 +67070,Male,25,Diploma,9,57,17,14,30,6.0,0,12,Urban,Manager,25461,0 +67071,Female,32,High School,16,44,29,74,17,4.0,2,99,Semi-Urban,HR Executive,23649,1 +67072,Male,28,Masters,11,35,41,21,20,2.0,7,6,Urban,Data Analyst,54309,0 +67073,Female,55,Bachelors,19,66,19,23,83,6.0,0,5,Urban,Data Analyst,122723,0 +67074,Male,29,Bachelors,13,68,56,91,85,0.0,6,75,Urban,Software Engineer,71091,1 +67075,Female,44,Bachelors,14,68,19,56,20,8.0,7,38,Semi-Urban,ML Engineer,54250,0 +67076,Male,52,Diploma,12,56,28,80,55,6.0,4,58,Semi-Urban,Data Analyst,36894,0 +67077,Female,45,High School,3,45,87,60,28,2.0,3,85,Urban,Manager,118938,1 +67078,Male,27,Bachelors,19,67,49,32,20,9.0,3,28,Rural,Software Engineer,48704,0 +67079,Male,25,High School,19,98,6,92,89,1.0,3,98,Urban,Manager,33003,1 +67080,Female,56,Bachelors,18,77,18,23,68,2.0,4,74,Semi-Urban,Manager,63074,0 +67081,Female,43,Bachelors,10,19,86,99,90,7.0,5,54,Rural,HR Executive,28149,1 +67082,Female,48,High School,18,73,82,28,81,8.0,6,80,Urban,Data Analyst,46828,1 +67083,Male,43,Bachelors,12,0,27,82,25,3.0,0,76,Semi-Urban,HR Executive,28835,0 +67084,Female,25,Bachelors,8,6,36,40,41,8.0,0,54,Urban,HR Executive,36127,0 +67085,Female,43,Bachelors,15,3,68,42,84,5.0,7,76,Rural,Software Engineer,112080,0 +67086,Male,30,Bachelors,11,64,28,67,38,9.0,0,18,Urban,HR Executive,137548,0 +67087,Male,28,Masters,15,23,17,32,91,8.0,2,30,Semi-Urban,Software Engineer,126227,0 +67088,Male,35,Bachelors,4,89,1,7,32,1.0,0,98,Rural,HR Executive,90030,0 +67089,Male,44,Masters,6,1,15,4,24,0.0,5,97,Urban,Data Analyst,86831,0 +67090,Female,22,Masters,15,39,92,73,7,4.0,4,44,Urban,Data Analyst,134338,1 +67091,Male,58,Bachelors,19,50,30,20,20,8.0,2,19,Rural,ML Engineer,149819,0 +67092,Male,58,Masters,7,54,50,2,82,1.0,1,85,Urban,Software Engineer,62815,0 +67093,Male,54,Masters,13,55,43,3,18,4.0,1,73,Urban,Data Analyst,20540,0 +67094,Female,25,High School,11,42,41,31,88,8.0,5,8,Semi-Urban,Software Engineer,120244,0 +67095,Male,53,High School,10,12,70,43,77,2.0,0,90,Semi-Urban,HR Executive,32955,0 +67096,Male,42,High School,1,38,22,61,68,7.0,4,30,Semi-Urban,Manager,109923,0 +67097,Female,48,Bachelors,0,36,9,26,56,3.0,7,24,Urban,ML Engineer,52337,0 +67098,Female,47,Diploma,3,44,57,57,16,5.0,2,3,Urban,Software Engineer,120053,0 +67099,Male,59,Bachelors,18,69,66,24,38,1.0,0,13,Urban,Software Engineer,25135,0 +67100,Other,23,Diploma,16,86,95,60,28,6.0,2,40,Semi-Urban,Manager,115242,1 +67101,Female,35,Bachelors,6,97,16,48,99,9.0,1,6,Semi-Urban,Software Engineer,30033,0 +67102,Female,50,Bachelors,11,74,34,3,88,0.0,7,36,Semi-Urban,Data Analyst,105627,0 +67103,Female,58,High School,10,4,3,68,79,1.0,3,92,Urban,HR Executive,58336,0 +67104,Male,50,Diploma,10,44,85,51,66,0.0,5,3,Urban,Manager,95351,0 +67105,Male,42,Masters,1,72,8,91,68,3.0,2,74,Urban,Software Engineer,38749,1 +67106,Female,36,High School,18,11,45,45,66,1.0,7,14,Urban,Data Analyst,36198,0 +67107,Male,51,Diploma,1,83,83,34,72,6.0,3,62,Urban,ML Engineer,74011,1 +67108,Female,25,Bachelors,11,45,99,3,25,8.0,1,86,Urban,HR Executive,27188,0 +67109,Male,57,High School,18,79,21,72,37,1.0,6,65,Urban,HR Executive,123144,1 +67110,Male,45,High School,3,30,54,11,22,9.0,0,37,Urban,HR Executive,105940,0 +67111,Male,27,Bachelors,12,92,27,81,91,4.0,6,71,Rural,Manager,27041,1 +67112,Female,41,Bachelors,11,47,9,10,66,8.0,7,17,Semi-Urban,Software Engineer,146593,0 +67113,Female,30,High School,19,8,56,98,15,6.0,5,95,Rural,Software Engineer,75740,1 +67114,Male,46,Bachelors,18,43,74,11,56,0.0,2,11,Rural,Manager,69230,0 +67115,Male,25,Bachelors,6,10,1,24,73,8.0,4,84,Rural,Data Analyst,108221,0 +67116,Male,25,Bachelors,3,47,20,47,23,1.0,1,84,Urban,Software Engineer,34234,0 +67117,Female,52,Masters,4,68,52,23,40,2.0,7,93,Semi-Urban,Data Analyst,75398,0 +67118,Male,24,Masters,8,52,75,55,31,6.0,6,54,Semi-Urban,Data Analyst,44895,1 +67119,Male,33,Masters,4,69,1,24,12,9.0,0,25,Urban,Manager,20039,0 +67120,Male,57,Bachelors,3,61,63,5,69,2.0,4,67,Rural,ML Engineer,125293,0 +67121,Male,55,PhD,16,79,17,43,12,5.0,4,98,Semi-Urban,HR Executive,31683,1 +67122,Female,57,Masters,4,97,35,57,25,6.0,0,12,Urban,Manager,20529,0 +67123,Male,56,High School,11,42,49,5,50,7.0,3,83,Semi-Urban,Data Analyst,120922,0 +67124,Male,59,Bachelors,3,10,96,8,26,1.0,1,50,Urban,HR Executive,30678,0 +67125,Female,33,Bachelors,10,82,33,99,95,3.0,3,43,Urban,HR Executive,62576,1 +67126,Female,39,Masters,5,9,83,65,21,4.0,6,92,Semi-Urban,HR Executive,103915,1 +67127,Female,30,Bachelors,1,29,52,39,44,5.0,4,78,Urban,ML Engineer,29037,0 +67128,Male,33,Diploma,16,97,66,74,67,7.0,5,27,Urban,HR Executive,90312,1 +67129,Male,37,Bachelors,18,94,74,2,26,7.0,4,68,Urban,Manager,118890,1 +67130,Male,23,Bachelors,13,48,34,66,57,1.0,2,18,Semi-Urban,Manager,37429,0 +67131,Male,39,Bachelors,1,52,11,16,27,2.0,4,66,Semi-Urban,Manager,35365,0 +67132,Female,53,Bachelors,11,64,27,71,8,5.0,0,15,Semi-Urban,Manager,48696,0 +67133,Female,40,Bachelors,17,0,81,86,27,6.0,1,11,Urban,ML Engineer,75807,0 +67134,Female,58,High School,14,81,83,23,29,7.0,1,42,Urban,Software Engineer,80304,0 +67135,Male,40,High School,11,55,64,82,36,4.0,4,50,Semi-Urban,Software Engineer,24458,1 +67136,Female,47,Diploma,9,19,4,66,91,6.0,2,67,Rural,ML Engineer,93806,0 +67137,Male,43,Bachelors,4,78,74,83,31,0.0,3,33,Semi-Urban,Data Analyst,78602,1 +67138,Male,53,PhD,1,8,25,93,30,6.0,7,82,Semi-Urban,Manager,44140,0 +67139,Female,26,Diploma,4,82,2,80,33,9.0,6,89,Urban,HR Executive,77137,1 +67140,Male,29,Diploma,6,28,19,20,86,3.0,2,81,Urban,HR Executive,47138,0 +67141,Male,54,Diploma,15,37,0,36,43,9.0,2,57,Semi-Urban,Manager,86582,0 +67142,Female,46,High School,12,60,18,71,31,7.0,1,0,Urban,Data Analyst,77311,0 +67143,Female,47,Bachelors,4,43,58,95,78,7.0,4,85,Urban,ML Engineer,69325,1 +67144,Female,55,Masters,17,44,13,5,75,7.0,1,10,Urban,HR Executive,114180,0 +67145,Male,35,Diploma,10,92,16,93,96,1.0,0,14,Rural,HR Executive,23767,0 +67146,Male,55,PhD,7,37,74,58,52,1.0,3,96,Urban,Software Engineer,118866,1 +67147,Female,28,High School,1,5,84,10,56,4.0,0,42,Urban,Data Analyst,86552,0 +67148,Male,21,Masters,1,19,40,23,85,2.0,3,81,Urban,Manager,116566,0 +67149,Male,48,Masters,17,77,1,40,16,3.0,1,38,Rural,Manager,117474,0 +67150,Male,28,Bachelors,9,64,48,62,68,2.0,5,93,Rural,Manager,91196,1 +67151,Other,52,Bachelors,15,84,72,40,36,5.0,3,68,Urban,Manager,120281,1 +67152,Male,26,PhD,16,41,75,47,94,3.0,4,34,Semi-Urban,ML Engineer,144892,0 +67153,Female,38,Bachelors,8,18,62,24,18,9.0,5,70,Urban,HR Executive,139158,0 +67154,Female,48,Masters,7,7,76,99,96,4.0,6,35,Urban,Manager,67179,0 +67155,Female,35,Diploma,11,7,23,9,25,3.0,4,6,Semi-Urban,HR Executive,146726,0 +67156,Male,52,High School,11,15,26,61,59,8.0,6,65,Urban,ML Engineer,33180,0 +67157,Male,54,Bachelors,15,14,63,92,31,6.0,6,58,Urban,Manager,46270,0 +67158,Female,37,PhD,7,51,76,50,80,6.0,4,24,Urban,Data Analyst,119635,0 +67159,Female,38,Bachelors,8,4,78,0,23,9.0,6,80,Semi-Urban,Manager,33503,0 +67160,Male,44,Bachelors,10,50,77,22,47,4.0,2,42,Rural,HR Executive,21982,0 +67161,Male,47,High School,18,17,8,88,17,2.0,3,70,Urban,Software Engineer,65170,0 +67162,Male,47,Bachelors,11,50,41,98,14,9.0,1,4,Urban,Data Analyst,76384,0 +67163,Male,21,Masters,0,96,91,19,61,0.0,6,38,Semi-Urban,ML Engineer,59565,1 +67164,Male,30,High School,14,57,45,50,74,3.0,3,15,Urban,Manager,133132,0 +67165,Male,48,High School,4,36,97,37,54,5.0,5,75,Urban,Manager,84886,1 +67166,Female,33,Diploma,8,5,42,39,33,4.0,7,50,Urban,Manager,36511,0 +67167,Male,58,Masters,3,75,9,52,84,6.0,6,91,Urban,Software Engineer,31281,0 +67168,Male,22,High School,11,33,69,45,84,9.0,4,56,Semi-Urban,Data Analyst,22788,0 +67169,Male,29,High School,13,55,24,89,14,0.0,5,90,Urban,ML Engineer,76725,1 +67170,Male,57,Bachelors,16,41,94,46,0,3.0,6,46,Urban,ML Engineer,71882,0 +67171,Female,32,High School,14,58,18,62,43,7.0,4,82,Urban,Data Analyst,53754,0 +67172,Male,40,Diploma,15,84,40,60,94,6.0,4,71,Urban,Data Analyst,86877,1 +67173,Female,58,Diploma,16,23,57,12,39,9.0,3,0,Urban,HR Executive,75470,0 +67174,Male,31,Bachelors,10,54,29,18,49,2.0,4,23,Rural,Software Engineer,64988,0 +67175,Male,45,High School,5,33,65,40,3,9.0,1,32,Urban,ML Engineer,129941,0 +67176,Male,22,Bachelors,16,70,15,56,75,6.0,1,26,Semi-Urban,HR Executive,130096,0 +67177,Male,32,Diploma,13,97,91,50,55,3.0,1,37,Urban,HR Executive,33052,1 +67178,Female,30,Bachelors,15,66,40,84,45,1.0,7,47,Urban,Software Engineer,72571,0 +67179,Male,31,Bachelors,5,66,77,54,62,6.0,1,4,Urban,HR Executive,145312,0 +67180,Female,39,Diploma,10,60,51,61,97,0.0,6,27,Semi-Urban,Software Engineer,98542,0 +67181,Male,59,High School,15,69,78,23,20,4.0,2,59,Rural,HR Executive,77802,0 +67182,Male,45,Bachelors,2,78,41,30,42,4.0,7,13,Urban,Manager,24522,0 +67183,Female,54,Diploma,18,18,5,69,64,5.0,5,87,Urban,Manager,116489,0 +67184,Female,42,Bachelors,19,67,74,51,75,1.0,6,9,Rural,Data Analyst,136154,0 +67185,Male,55,High School,13,12,94,94,39,7.0,3,44,Rural,Software Engineer,116200,1 +67186,Male,56,High School,7,76,70,21,27,2.0,1,55,Urban,ML Engineer,102466,0 +67187,Female,50,Bachelors,9,15,7,55,33,2.0,5,55,Semi-Urban,HR Executive,80577,0 +67188,Other,27,Bachelors,14,35,34,8,81,4.0,4,10,Urban,Manager,40231,0 +67189,Female,38,Masters,8,81,39,62,21,0.0,7,12,Urban,HR Executive,38901,0 +67190,Male,56,Diploma,2,47,70,17,83,8.0,3,4,Semi-Urban,ML Engineer,29860,0 +67191,Female,22,Bachelors,8,41,22,81,54,3.0,2,46,Urban,HR Executive,105087,0 +67192,Female,36,Diploma,4,47,96,33,11,9.0,1,57,Rural,Data Analyst,136758,0 +67193,Female,34,Masters,1,62,8,72,17,5.0,3,32,Urban,HR Executive,37614,0 +67194,Male,41,Masters,2,24,10,68,8,3.0,3,54,Rural,Data Analyst,25160,0 +67195,Male,45,High School,11,72,86,17,68,5.0,4,85,Urban,HR Executive,93466,1 +67196,Female,23,Bachelors,15,26,62,95,99,0.0,4,73,Rural,Data Analyst,65400,1 +67197,Female,44,Bachelors,19,50,41,16,20,9.0,4,21,Rural,ML Engineer,99301,0 +67198,Male,43,High School,16,48,46,0,15,4.0,4,91,Rural,ML Engineer,20691,0 +67199,Male,42,Diploma,12,48,49,21,59,7.0,5,8,Rural,HR Executive,143982,0 +67200,Male,23,Diploma,15,44,16,13,23,9.0,0,89,Urban,Manager,133788,0 +67201,Male,37,Diploma,18,97,32,1,5,4.0,4,22,Semi-Urban,Data Analyst,110610,0 +67202,Male,28,Diploma,15,92,51,1,25,0.0,3,12,Urban,ML Engineer,141332,0 +67203,Male,54,Bachelors,13,8,4,45,86,7.0,0,44,Rural,ML Engineer,118173,0 +67204,Female,49,High School,1,10,42,52,29,0.0,6,61,Urban,Software Engineer,107475,0 +67205,Female,24,Diploma,17,85,55,89,13,4.0,0,40,Rural,ML Engineer,89354,1 +67206,Female,38,Masters,16,93,80,21,18,6.0,0,6,Semi-Urban,Data Analyst,43570,0 +67207,Female,36,Diploma,15,82,7,3,36,2.0,4,53,Rural,ML Engineer,26999,0 +67208,Male,37,Bachelors,0,6,69,7,72,9.0,7,6,Urban,ML Engineer,73986,0 +67209,Male,27,Bachelors,8,63,6,63,24,5.0,0,6,Rural,Manager,131550,0 +67210,Male,21,Bachelors,6,91,61,30,11,2.0,6,86,Rural,HR Executive,23119,1 +67211,Male,56,Bachelors,8,1,85,11,38,0.0,6,39,Urban,Data Analyst,59294,0 +67212,Male,41,Bachelors,18,49,51,29,33,9.0,1,73,Urban,ML Engineer,29724,0 +67213,Female,45,Bachelors,2,34,55,60,51,4.0,4,84,Urban,Manager,87282,0 +67214,Male,23,Bachelors,8,45,87,7,29,3.0,3,27,Urban,Software Engineer,87748,0 +67215,Male,31,Bachelors,12,12,93,26,24,5.0,7,95,Urban,Data Analyst,28391,0 +67216,Male,35,Diploma,10,30,54,90,32,0.0,7,78,Semi-Urban,Data Analyst,108224,1 +67217,Male,59,Bachelors,7,4,90,43,53,7.0,2,64,Rural,Data Analyst,144268,0 +67218,Female,43,Bachelors,6,6,43,29,15,5.0,0,32,Urban,HR Executive,61818,0 +67219,Male,39,Bachelors,19,90,7,18,62,4.0,4,93,Rural,Software Engineer,53076,0 +67220,Male,37,Bachelors,11,36,62,21,23,8.0,2,56,Urban,Manager,107946,0 +67221,Male,42,Masters,16,71,72,25,38,4.0,1,64,Rural,Software Engineer,23484,0 +67222,Male,50,Bachelors,15,61,62,73,62,9.0,0,16,Rural,Manager,74246,0 +67223,Male,54,Diploma,9,84,68,97,74,8.0,3,33,Urban,Manager,135776,1 +67224,Male,59,Diploma,10,2,21,3,90,4.0,2,37,Rural,Software Engineer,112763,0 +67225,Female,25,Bachelors,13,2,44,27,43,4.0,1,67,Semi-Urban,HR Executive,83505,0 +67226,Male,21,Diploma,16,97,69,55,94,8.0,7,81,Semi-Urban,HR Executive,49390,1 +67227,Female,41,PhD,4,60,92,64,28,3.0,7,37,Urban,HR Executive,75396,1 +67228,Female,25,Masters,19,94,54,94,19,9.0,7,23,Urban,ML Engineer,30581,1 +67229,Male,28,Bachelors,2,97,56,5,87,2.0,3,90,Semi-Urban,Manager,98032,1 +67230,Male,47,Bachelors,16,70,30,43,89,7.0,2,99,Semi-Urban,Data Analyst,143115,1 +67231,Male,58,Diploma,19,97,33,5,27,8.0,0,95,Urban,Software Engineer,82138,0 +67232,Male,59,Bachelors,18,28,17,90,93,6.0,6,54,Urban,Manager,37167,0 +67233,Male,44,Bachelors,4,55,91,54,33,6.0,4,73,Semi-Urban,Data Analyst,57671,1 +67234,Male,24,High School,16,67,26,23,69,5.0,3,81,Urban,HR Executive,127143,0 +67235,Male,31,High School,11,59,21,7,18,4.0,7,70,Semi-Urban,ML Engineer,125090,0 +67236,Male,44,Bachelors,12,16,9,20,91,6.0,0,13,Rural,Software Engineer,69060,0 +67237,Female,38,Bachelors,13,97,24,71,2,3.0,0,15,Semi-Urban,ML Engineer,71049,0 +67238,Male,45,Masters,14,89,38,21,35,6.0,3,86,Urban,Manager,102913,0 +67239,Female,30,Masters,9,24,64,40,63,1.0,3,23,Urban,Software Engineer,137258,0 +67240,Female,41,Masters,13,70,70,65,86,5.0,4,8,Urban,HR Executive,61897,0 +67241,Female,22,Diploma,6,24,33,60,63,9.0,3,5,Rural,Data Analyst,45937,0 +67242,Female,47,High School,12,93,64,55,66,3.0,1,59,Urban,ML Engineer,108253,1 +67243,Male,38,Diploma,17,46,13,25,52,1.0,1,92,Urban,Software Engineer,48741,0 +67244,Male,46,Bachelors,14,71,95,5,5,4.0,6,27,Semi-Urban,ML Engineer,137812,0 +67245,Male,39,Diploma,14,15,58,94,98,9.0,3,47,Urban,ML Engineer,120570,0 +67246,Male,40,Bachelors,10,59,38,50,50,2.0,2,93,Urban,Manager,140147,1 +67247,Male,50,Bachelors,12,54,77,47,60,5.0,3,0,Urban,ML Engineer,91200,0 +67248,Male,35,Bachelors,11,33,60,5,88,6.0,0,93,Rural,HR Executive,52593,0 +67249,Female,24,High School,13,51,29,25,34,2.0,5,24,Urban,ML Engineer,21964,0 +67250,Male,52,Masters,15,16,64,68,30,4.0,2,84,Urban,Software Engineer,59104,0 +67251,Male,55,Masters,14,80,72,40,85,1.0,2,1,Urban,HR Executive,110725,0 +67252,Male,33,Masters,15,71,20,17,64,4.0,1,31,Urban,Software Engineer,116500,0 +67253,Male,47,Masters,0,17,53,40,78,6.0,6,92,Urban,Software Engineer,149315,0 +67254,Female,58,High School,16,40,58,3,97,4.0,7,79,Urban,HR Executive,27709,0 +67255,Female,51,PhD,9,13,4,44,41,8.0,4,47,Urban,HR Executive,66047,0 +67256,Male,23,Diploma,9,86,99,74,36,2.0,7,56,Urban,Software Engineer,59573,1 +67257,Male,54,Diploma,0,18,46,70,14,2.0,1,16,Semi-Urban,HR Executive,80126,0 +67258,Male,42,Masters,4,92,28,64,92,2.0,3,46,Urban,ML Engineer,135560,0 +67259,Male,44,Diploma,3,52,70,77,13,1.0,1,50,Rural,Manager,31349,1 +67260,Male,47,High School,13,59,65,97,29,7.0,3,14,Semi-Urban,HR Executive,46720,1 +67261,Female,57,Masters,16,87,2,83,98,1.0,4,46,Semi-Urban,HR Executive,147383,0 +67262,Male,32,Bachelors,2,75,6,12,55,0.0,4,27,Urban,Data Analyst,42041,0 +67263,Male,42,High School,3,83,95,34,26,8.0,3,65,Urban,Software Engineer,68840,1 +67264,Female,23,Masters,16,70,29,81,47,1.0,6,13,Semi-Urban,Manager,42917,0 +67265,Male,38,Diploma,19,95,26,57,31,2.0,5,33,Urban,HR Executive,40099,0 +67266,Other,36,Bachelors,4,60,72,59,40,9.0,1,15,Urban,HR Executive,71132,0 +67267,Female,56,Bachelors,16,93,66,2,98,1.0,7,73,Urban,Data Analyst,107759,0 +67268,Female,23,High School,6,95,49,44,19,1.0,4,83,Urban,ML Engineer,50417,1 +67269,Male,48,Diploma,15,74,45,25,64,6.0,1,54,Urban,HR Executive,82786,0 +67270,Male,58,Masters,10,66,66,70,55,7.0,2,67,Urban,Manager,52009,1 +67271,Male,39,Masters,13,59,24,39,11,9.0,1,57,Urban,Software Engineer,145738,0 +67272,Male,30,Masters,11,63,43,36,99,7.0,1,11,Rural,Manager,88932,0 +67273,Male,59,Masters,9,92,96,82,56,8.0,3,86,Urban,HR Executive,74334,1 +67274,Male,24,Bachelors,5,8,86,5,10,9.0,2,3,Semi-Urban,ML Engineer,105120,0 +67275,Female,28,Bachelors,9,75,37,55,74,0.0,3,46,Rural,HR Executive,94636,0 +67276,Male,35,High School,17,47,81,71,26,0.0,4,93,Semi-Urban,HR Executive,129962,1 +67277,Female,49,Masters,8,19,33,32,17,1.0,5,37,Rural,Software Engineer,52049,0 +67278,Male,30,Masters,12,78,64,10,93,9.0,5,47,Urban,Software Engineer,56891,0 +67279,Female,51,Diploma,5,43,67,63,33,5.0,1,96,Rural,ML Engineer,82244,1 +67280,Female,33,High School,13,73,16,53,89,1.0,3,26,Urban,Data Analyst,76367,0 +67281,Male,51,Diploma,7,72,38,70,14,6.0,2,38,Urban,HR Executive,57220,0 +67282,Female,22,Bachelors,18,28,61,34,48,6.0,0,59,Urban,Software Engineer,53475,0 +67283,Female,49,High School,15,88,58,23,47,1.0,3,68,Semi-Urban,Manager,35980,0 +67284,Female,30,Bachelors,4,64,2,5,25,0.0,6,43,Urban,ML Engineer,50394,0 +67285,Female,21,Diploma,19,13,42,90,51,3.0,3,50,Semi-Urban,Data Analyst,112094,0 +67286,Male,49,Bachelors,9,71,2,37,5,7.0,6,58,Urban,Software Engineer,90663,0 +67287,Male,30,Masters,15,99,5,77,41,9.0,6,36,Semi-Urban,HR Executive,142662,0 +67288,Female,57,Bachelors,19,58,63,51,30,2.0,3,75,Urban,Data Analyst,51367,1 +67289,Female,39,PhD,10,42,77,86,6,1.0,7,61,Urban,ML Engineer,126028,1 +67290,Female,55,Masters,7,56,88,62,78,1.0,7,97,Urban,HR Executive,93067,1 +67291,Male,34,Masters,6,81,67,61,40,9.0,5,88,Urban,HR Executive,61219,1 +67292,Female,34,Bachelors,13,20,22,40,47,3.0,2,48,Urban,HR Executive,63306,0 +67293,Male,36,Bachelors,7,64,5,90,59,6.0,2,7,Urban,Data Analyst,71846,0 +67294,Male,23,Bachelors,5,70,64,33,2,9.0,4,95,Urban,Data Analyst,83865,1 +67295,Male,36,Bachelors,18,97,33,45,43,0.0,0,71,Urban,ML Engineer,36691,1 +67296,Female,53,Diploma,11,12,63,49,53,5.0,0,31,Rural,HR Executive,93218,0 +67297,Male,58,Diploma,5,51,20,93,95,6.0,5,27,Semi-Urban,Data Analyst,38142,0 +67298,Male,23,Bachelors,14,20,0,41,82,2.0,5,45,Urban,Software Engineer,70969,0 +67299,Female,35,PhD,11,54,61,44,92,6.0,5,2,Urban,ML Engineer,66205,0 +67300,Male,59,Diploma,19,94,45,89,35,9.0,3,54,Urban,HR Executive,125137,1 +67301,Male,49,Bachelors,1,81,51,83,80,3.0,2,29,Urban,Software Engineer,58984,1 +67302,Male,26,Bachelors,4,19,94,58,25,9.0,5,6,Urban,Software Engineer,118953,0 +67303,Male,55,Bachelors,10,98,49,28,13,9.0,3,26,Urban,Software Engineer,48720,0 +67304,Male,33,Diploma,18,99,62,20,35,4.0,1,91,Urban,Manager,63858,1 +67305,Female,56,Bachelors,5,69,70,23,91,4.0,4,8,Semi-Urban,ML Engineer,103945,0 +67306,Female,46,Diploma,10,59,27,99,53,2.0,2,97,Urban,Data Analyst,38832,1 +67307,Male,23,Masters,12,49,41,26,23,0.0,5,0,Rural,HR Executive,133172,0 +67308,Male,38,Bachelors,1,49,1,35,50,2.0,3,66,Rural,Software Engineer,64240,0 +67309,Male,59,Bachelors,9,58,4,72,22,6.0,5,97,Urban,ML Engineer,143735,0 +67310,Male,22,Bachelors,12,37,59,14,31,5.0,4,66,Urban,Manager,121275,0 +67311,Male,57,Bachelors,4,30,99,50,28,6.0,1,2,Urban,Data Analyst,147181,0 +67312,Male,45,Diploma,18,40,29,14,75,4.0,5,30,Rural,HR Executive,142858,0 +67313,Female,52,Masters,15,16,66,84,76,9.0,7,97,Urban,ML Engineer,47741,1 +67314,Male,42,Bachelors,11,60,12,17,48,2.0,5,88,Urban,HR Executive,119987,0 +67315,Female,48,PhD,11,94,71,93,0,9.0,6,82,Urban,Manager,124765,1 +67316,Male,27,Masters,16,72,12,92,33,3.0,0,70,Rural,Manager,82805,1 +67317,Male,23,High School,3,34,96,85,65,3.0,2,51,Semi-Urban,ML Engineer,109535,1 +67318,Female,35,Bachelors,14,12,3,68,11,6.0,6,63,Rural,Manager,47105,0 +67319,Male,30,High School,12,59,89,52,50,8.0,1,40,Urban,HR Executive,53156,1 +67320,Female,41,PhD,19,35,74,68,6,2.0,4,80,Semi-Urban,Software Engineer,20468,1 +67321,Male,50,Bachelors,4,40,4,99,38,0.0,4,98,Rural,ML Engineer,33179,1 +67322,Female,50,Bachelors,6,74,35,16,74,7.0,1,31,Urban,Manager,61043,0 +67323,Male,34,Masters,10,25,34,7,19,3.0,5,0,Urban,Software Engineer,61661,0 +67324,Female,26,Bachelors,9,96,37,46,95,8.0,6,73,Urban,Manager,111916,1 +67325,Male,54,Diploma,19,94,48,40,62,5.0,5,49,Rural,ML Engineer,67909,0 +67326,Male,22,Bachelors,0,42,68,73,93,3.0,2,4,Rural,HR Executive,83869,0 +67327,Female,26,PhD,2,88,51,20,58,9.0,1,88,Urban,Software Engineer,148664,1 +67328,Female,41,High School,11,89,71,95,89,8.0,3,50,Semi-Urban,Manager,46135,1 +67329,Female,29,Bachelors,14,23,67,35,11,0.0,0,51,Urban,Data Analyst,106876,0 +67330,Male,22,Diploma,11,42,26,25,81,0.0,2,98,Urban,Software Engineer,54974,0 +67331,Female,49,Masters,14,72,4,56,50,7.0,1,41,Urban,Manager,141071,0 +67332,Male,47,Bachelors,4,58,92,86,26,5.0,0,69,Urban,Software Engineer,32392,1 +67333,Male,41,Masters,18,51,64,86,44,6.0,4,13,Urban,HR Executive,96174,0 +67334,Male,50,Masters,15,95,35,11,93,1.0,2,28,Urban,HR Executive,89031,0 +67335,Male,53,Bachelors,3,39,7,43,82,6.0,4,74,Semi-Urban,ML Engineer,142787,0 +67336,Female,40,PhD,11,95,63,56,77,3.0,6,36,Rural,Manager,65267,1 +67337,Female,50,Diploma,6,69,58,47,71,3.0,3,70,Urban,HR Executive,107439,1 +67338,Male,41,Diploma,8,0,55,11,82,5.0,2,49,Semi-Urban,HR Executive,36811,0 +67339,Male,32,Bachelors,2,29,8,75,30,7.0,0,15,Urban,Software Engineer,20076,0 +67340,Male,53,Diploma,16,99,37,78,79,8.0,6,79,Semi-Urban,Manager,63976,1 +67341,Male,39,Masters,16,29,73,87,4,5.0,5,3,Urban,Data Analyst,38469,0 +67342,Male,49,Bachelors,19,97,48,89,88,4.0,1,28,Urban,HR Executive,85241,1 +67343,Female,57,Bachelors,7,92,23,49,48,4.0,0,86,Urban,Data Analyst,101816,1 +67344,Female,22,Bachelors,17,96,61,29,30,3.0,1,52,Rural,Data Analyst,134234,0 +67345,Male,30,Bachelors,3,47,13,4,19,7.0,4,40,Semi-Urban,Data Analyst,125914,0 +67346,Female,50,Bachelors,18,22,76,69,6,4.0,4,16,Rural,HR Executive,112175,0 +67347,Female,29,Bachelors,8,50,60,64,49,0.0,0,18,Urban,HR Executive,130079,0 +67348,Male,41,Diploma,12,10,50,51,4,2.0,1,11,Urban,Software Engineer,33115,0 +67349,Male,53,Bachelors,14,26,85,84,69,8.0,5,81,Urban,Data Analyst,75843,1 +67350,Male,55,Bachelors,6,30,42,64,23,0.0,1,37,Rural,Manager,103514,0 +67351,Male,44,Masters,4,41,9,7,93,1.0,0,73,Urban,HR Executive,34440,0 +67352,Male,42,Bachelors,1,70,8,38,44,7.0,6,58,Rural,ML Engineer,82086,0 +67353,Female,29,Masters,9,32,13,81,42,1.0,1,17,Urban,Software Engineer,63272,0 +67354,Female,42,Bachelors,2,52,49,55,96,3.0,2,94,Urban,Software Engineer,34218,1 +67355,Female,29,Masters,4,84,99,47,25,2.0,7,77,Semi-Urban,Manager,96319,1 +67356,Female,50,Bachelors,18,62,74,28,71,7.0,6,49,Semi-Urban,HR Executive,109725,0 +67357,Female,27,High School,19,42,92,43,64,0.0,6,2,Semi-Urban,HR Executive,137381,0 +67358,Male,46,Masters,3,72,9,96,15,7.0,4,86,Urban,Software Engineer,35811,1 +67359,Male,44,Masters,15,40,60,81,0,1.0,0,45,Rural,HR Executive,57106,0 +67360,Male,54,Diploma,5,96,35,11,59,6.0,0,60,Semi-Urban,HR Executive,55023,0 +67361,Male,21,Masters,11,2,1,6,0,0.0,7,66,Urban,Data Analyst,111581,0 +67362,Female,38,PhD,8,22,17,71,95,3.0,6,34,Urban,Manager,73435,0 +67363,Male,59,Masters,6,3,47,12,83,5.0,7,79,Semi-Urban,Software Engineer,112699,0 +67364,Male,54,Masters,12,55,29,14,71,5.0,5,54,Rural,Data Analyst,103000,0 +67365,Female,29,Bachelors,12,71,36,2,49,5.0,1,79,Urban,HR Executive,23258,0 +67366,Other,32,High School,10,45,45,95,38,9.0,4,85,Rural,Data Analyst,79137,1 +67367,Male,23,Bachelors,4,25,56,7,42,0.0,4,84,Rural,Manager,53079,0 +67368,Male,26,Bachelors,10,52,62,49,40,5.0,1,50,Urban,HR Executive,83133,0 +67369,Male,54,High School,7,73,53,51,78,1.0,6,89,Urban,Manager,93650,1 +67370,Male,54,High School,1,28,49,13,15,6.0,5,92,Urban,HR Executive,86399,0 +67371,Female,26,Masters,14,76,89,95,25,5.0,0,8,Rural,Data Analyst,50112,1 +67372,Female,22,Masters,12,6,44,91,90,2.0,4,73,Rural,ML Engineer,60154,0 +67373,Male,54,Bachelors,15,18,81,20,9,9.0,0,47,Semi-Urban,Data Analyst,37574,0 +67374,Male,33,Masters,15,34,28,34,43,0.0,7,7,Urban,HR Executive,76430,0 +67375,Male,51,Diploma,5,16,94,71,46,7.0,2,82,Urban,Software Engineer,62952,1 +67376,Other,33,Bachelors,16,17,2,69,28,7.0,1,54,Urban,Software Engineer,108060,0 +67377,Male,53,Masters,17,6,32,25,29,7.0,1,63,Rural,HR Executive,33959,0 +67378,Female,25,Masters,17,78,99,42,17,7.0,0,5,Rural,ML Engineer,97914,0 +67379,Male,33,Masters,12,86,43,39,29,3.0,1,23,Urban,HR Executive,136341,0 +67380,Male,24,Bachelors,15,1,4,80,88,8.0,2,89,Urban,Software Engineer,62559,0 +67381,Male,27,Bachelors,16,79,88,52,99,0.0,0,50,Urban,HR Executive,29820,1 +67382,Female,52,PhD,6,49,89,36,88,9.0,2,43,Semi-Urban,Software Engineer,139063,0 +67383,Male,53,Bachelors,5,87,9,30,74,3.0,6,14,Semi-Urban,HR Executive,84079,0 +67384,Female,37,Masters,10,24,13,46,50,8.0,7,47,Urban,HR Executive,113383,0 +67385,Male,52,Bachelors,6,9,92,80,12,7.0,0,98,Urban,Manager,142764,1 +67386,Male,26,Bachelors,15,23,67,72,68,8.0,6,97,Urban,HR Executive,40352,1 +67387,Male,36,High School,1,21,95,76,80,6.0,2,53,Urban,Manager,121615,1 +67388,Female,34,Masters,8,44,14,46,76,9.0,3,0,Urban,Software Engineer,44794,0 +67389,Female,39,Bachelors,15,57,9,45,35,5.0,4,7,Urban,Software Engineer,83151,0 +67390,Male,25,Bachelors,0,22,69,56,50,2.0,3,89,Urban,ML Engineer,23241,1 +67391,Male,36,High School,15,85,21,15,19,5.0,5,15,Urban,HR Executive,140392,0 +67392,Female,43,Bachelors,7,80,22,9,32,0.0,4,35,Urban,Software Engineer,122166,0 +67393,Male,23,Bachelors,12,58,26,32,69,8.0,6,78,Urban,Software Engineer,63326,0 +67394,Male,46,Bachelors,12,18,3,3,56,2.0,1,47,Semi-Urban,Data Analyst,135738,0 +67395,Male,43,Diploma,18,13,59,37,89,5.0,7,93,Rural,Data Analyst,53527,0 +67396,Female,30,High School,1,17,92,40,66,0.0,3,87,Semi-Urban,ML Engineer,82860,0 +67397,Female,44,Masters,10,22,71,80,33,6.0,1,74,Rural,Manager,88020,1 +67398,Male,25,Bachelors,2,92,12,91,76,8.0,5,94,Semi-Urban,HR Executive,43128,1 +67399,Male,21,Masters,16,34,34,46,25,7.0,5,40,Rural,HR Executive,56040,0 +67400,Male,51,Bachelors,0,74,31,62,46,8.0,3,25,Urban,Data Analyst,122317,0 +67401,Male,50,Bachelors,5,45,17,62,33,0.0,1,22,Urban,Data Analyst,26688,0 +67402,Male,55,Bachelors,3,91,90,80,77,9.0,6,27,Urban,HR Executive,88672,1 +67403,Male,55,Bachelors,5,95,72,70,3,0.0,5,53,Urban,ML Engineer,27087,1 +67404,Female,57,Bachelors,7,54,63,10,35,1.0,0,65,Urban,Data Analyst,31357,0 +67405,Female,46,Masters,3,98,11,72,66,7.0,3,90,Semi-Urban,HR Executive,131393,1 +67406,Male,58,Masters,2,60,92,5,80,4.0,5,99,Urban,Software Engineer,83213,1 +67407,Female,54,Bachelors,3,96,91,34,8,4.0,1,94,Semi-Urban,Software Engineer,38641,1 +67408,Female,37,Bachelors,5,30,13,56,31,5.0,4,40,Semi-Urban,Manager,42675,0 +67409,Male,24,High School,16,49,40,26,6,6.0,2,97,Semi-Urban,HR Executive,127808,0 +67410,Male,43,Bachelors,19,45,65,80,84,3.0,3,64,Rural,HR Executive,25074,1 +67411,Male,36,Bachelors,9,83,20,70,9,7.0,6,86,Semi-Urban,Data Analyst,49772,1 +67412,Female,32,High School,5,95,86,28,56,9.0,4,71,Semi-Urban,Data Analyst,24262,1 +67413,Male,40,Bachelors,9,46,91,23,85,6.0,2,20,Urban,Software Engineer,46365,0 +67414,Female,51,Bachelors,1,11,87,85,88,3.0,6,78,Rural,Software Engineer,33850,1 +67415,Female,58,High School,7,14,12,52,99,9.0,1,9,Rural,ML Engineer,32487,0 +67416,Male,27,Masters,7,31,13,40,49,0.0,4,76,Rural,Manager,105269,0 +67417,Other,29,Diploma,6,80,39,31,98,3.0,3,27,Urban,Software Engineer,77147,0 +67418,Female,52,Masters,19,57,1,80,30,9.0,2,32,Urban,Data Analyst,148543,0 +67419,Male,28,Bachelors,7,18,96,4,80,7.0,5,28,Urban,Manager,41098,0 +67420,Female,57,Bachelors,5,83,6,66,8,9.0,6,39,Semi-Urban,Manager,112723,0 +67421,Male,56,Bachelors,12,15,82,25,54,7.0,3,46,Semi-Urban,HR Executive,39801,0 +67422,Other,43,Masters,17,2,8,97,59,9.0,3,89,Rural,Data Analyst,38397,0 +67423,Male,56,High School,8,55,64,60,92,2.0,1,62,Urban,Software Engineer,61695,1 +67424,Other,51,Bachelors,14,11,33,7,39,2.0,1,57,Semi-Urban,Software Engineer,105432,0 +67425,Male,29,Bachelors,13,12,71,46,80,0.0,3,51,Semi-Urban,HR Executive,110835,0 +67426,Male,21,Bachelors,5,1,52,22,0,7.0,4,58,Urban,Software Engineer,127253,0 +67427,Male,50,Bachelors,14,19,53,62,25,7.0,2,97,Urban,HR Executive,144829,0 +67428,Male,50,High School,8,74,24,67,21,1.0,4,42,Semi-Urban,Data Analyst,134268,0 +67429,Female,27,Bachelors,3,69,72,87,90,8.0,5,67,Urban,Software Engineer,75242,1 +67430,Male,38,Masters,5,9,86,35,15,0.0,3,15,Rural,Manager,147847,0 +67431,Female,37,Masters,12,25,23,44,39,4.0,6,91,Semi-Urban,Software Engineer,82974,0 +67432,Female,42,Diploma,16,31,93,88,25,4.0,7,64,Rural,Software Engineer,145755,1 +67433,Female,40,Bachelors,5,66,98,71,20,6.0,6,30,Urban,ML Engineer,117057,1 +67434,Female,44,Bachelors,16,19,69,41,69,5.0,6,79,Semi-Urban,Data Analyst,88217,0 +67435,Male,28,Masters,11,23,36,8,1,3.0,0,17,Urban,Data Analyst,141790,0 +67436,Male,47,High School,16,36,55,24,17,2.0,5,96,Semi-Urban,HR Executive,53253,0 +67437,Male,42,Diploma,5,84,0,57,44,1.0,1,76,Urban,Manager,132105,0 +67438,Male,47,Diploma,12,25,18,10,52,8.0,2,56,Urban,HR Executive,52451,0 +67439,Male,38,High School,2,7,68,62,11,7.0,3,64,Urban,ML Engineer,59680,0 +67440,Other,43,Diploma,10,25,55,43,0,5.0,3,26,Urban,Manager,95921,0 +67441,Male,30,Masters,10,4,51,21,94,3.0,0,16,Urban,ML Engineer,49087,0 +67442,Male,52,Masters,7,95,11,72,25,2.0,3,99,Urban,HR Executive,34806,1 +67443,Female,42,Bachelors,12,47,5,86,58,7.0,7,23,Rural,Manager,113233,0 +67444,Female,52,Bachelors,10,31,31,55,87,0.0,7,85,Semi-Urban,HR Executive,36422,0 +67445,Other,28,Bachelors,19,79,71,68,11,2.0,3,75,Urban,Software Engineer,80080,1 +67446,Female,36,Diploma,16,94,46,11,12,2.0,4,7,Urban,Manager,21031,0 +67447,Male,25,Bachelors,8,35,51,27,41,4.0,1,26,Semi-Urban,ML Engineer,128199,0 +67448,Male,31,Bachelors,6,70,97,24,23,4.0,5,76,Rural,HR Executive,91865,1 +67449,Male,44,High School,19,20,27,70,40,8.0,0,42,Rural,Data Analyst,102310,0 +67450,Male,47,Bachelors,10,25,78,66,12,5.0,0,77,Semi-Urban,Software Engineer,42058,1 +67451,Male,24,Masters,19,22,30,66,60,8.0,7,83,Urban,Software Engineer,37039,0 +67452,Female,22,Masters,12,4,60,77,56,1.0,1,49,Urban,ML Engineer,43614,0 +67453,Male,41,High School,18,21,49,51,17,2.0,5,90,Urban,Manager,59111,0 +67454,Male,24,High School,17,0,49,61,53,3.0,7,45,Rural,Software Engineer,57719,0 +67455,Female,30,High School,5,63,86,62,92,5.0,4,21,Rural,Software Engineer,52922,0 +67456,Male,50,Masters,14,19,79,77,34,4.0,2,73,Semi-Urban,ML Engineer,123058,1 +67457,Male,38,Masters,8,19,13,89,90,2.0,3,37,Urban,Manager,46805,0 +67458,Female,31,Diploma,0,79,33,37,42,7.0,0,91,Urban,Data Analyst,41767,0 +67459,Female,27,Bachelors,8,5,18,14,63,6.0,2,91,Urban,HR Executive,139510,0 +67460,Male,52,Masters,13,35,16,77,43,8.0,2,38,Rural,HR Executive,137397,0 +67461,Male,59,Masters,6,45,22,78,58,3.0,0,54,Semi-Urban,Data Analyst,45611,0 +67462,Female,59,Bachelors,15,97,38,7,61,1.0,5,54,Urban,HR Executive,83392,0 +67463,Male,30,Bachelors,7,4,37,91,32,4.0,3,89,Urban,Data Analyst,72003,0 +67464,Female,28,Bachelors,9,23,4,60,5,3.0,2,53,Urban,Data Analyst,144623,0 +67465,Female,51,Diploma,9,40,16,45,15,2.0,7,45,Rural,Data Analyst,63061,0 +67466,Female,49,Diploma,17,92,81,41,8,9.0,1,0,Rural,HR Executive,85100,0 +67467,Female,51,Bachelors,7,96,30,97,54,5.0,1,24,Semi-Urban,HR Executive,84096,1 +67468,Female,59,Diploma,12,50,0,18,97,5.0,2,80,Rural,ML Engineer,125562,0 +67469,Male,39,High School,16,40,64,23,14,7.0,1,52,Rural,HR Executive,61270,0 +67470,Female,29,Bachelors,12,88,91,72,97,9.0,4,74,Urban,Manager,145446,1 +67471,Male,24,Masters,15,2,18,75,72,5.0,1,72,Urban,Manager,47855,0 +67472,Female,49,Diploma,6,61,26,86,84,6.0,2,51,Urban,Manager,38310,0 +67473,Female,27,Bachelors,19,97,96,77,1,7.0,1,69,Urban,Data Analyst,24580,1 +67474,Male,35,PhD,0,91,79,6,90,2.0,0,12,Semi-Urban,ML Engineer,119287,0 +67475,Female,30,Masters,12,26,97,78,74,5.0,3,44,Semi-Urban,Software Engineer,44799,1 +67476,Male,29,High School,16,50,94,61,23,1.0,1,32,Urban,Data Analyst,133439,1 +67477,Other,41,Bachelors,6,37,25,3,36,8.0,0,82,Urban,Data Analyst,57169,0 +67478,Male,52,Bachelors,15,15,28,17,2,6.0,0,84,Urban,Software Engineer,36861,0 +67479,Male,22,Diploma,10,26,73,52,42,7.0,5,0,Rural,Manager,99214,0 +67480,Male,50,High School,3,58,11,52,12,6.0,3,27,Urban,Software Engineer,146585,0 +67481,Male,31,Bachelors,17,81,29,62,72,7.0,3,12,Urban,Software Engineer,149956,0 +67482,Male,54,High School,16,60,71,91,86,9.0,2,1,Urban,Software Engineer,33855,0 +67483,Male,39,Diploma,6,95,94,44,49,2.0,2,14,Rural,HR Executive,49004,1 +67484,Male,59,Bachelors,5,78,84,78,28,4.0,7,51,Urban,Data Analyst,49748,1 +67485,Male,41,Bachelors,13,16,87,49,43,1.0,0,78,Urban,ML Engineer,37878,0 +67486,Female,48,High School,14,16,77,36,92,4.0,6,6,Rural,Software Engineer,127902,0 +67487,Male,47,Bachelors,1,33,34,22,0,2.0,7,7,Semi-Urban,Software Engineer,29166,0 +67488,Male,26,Masters,17,6,82,93,67,7.0,4,39,Urban,Software Engineer,69382,0 +67489,Male,42,PhD,5,3,67,47,27,4.0,7,9,Semi-Urban,HR Executive,27387,0 +67490,Female,30,Bachelors,14,9,63,54,13,4.0,7,3,Semi-Urban,Manager,37827,0 +67491,Female,49,Diploma,5,38,79,60,56,1.0,0,78,Urban,ML Engineer,48067,1 +67492,Female,56,Bachelors,15,48,21,71,66,3.0,5,28,Urban,Software Engineer,82521,0 +67493,Male,39,Masters,16,59,2,44,71,2.0,1,32,Urban,Software Engineer,53453,0 +67494,Female,41,High School,14,57,83,68,61,3.0,5,87,Urban,Manager,121549,1 +67495,Male,30,Diploma,17,93,46,69,49,4.0,5,68,Semi-Urban,Software Engineer,58872,1 +67496,Male,35,Diploma,14,74,71,14,81,8.0,6,14,Semi-Urban,Manager,120304,0 +67497,Male,28,Diploma,6,22,2,22,40,9.0,2,99,Urban,ML Engineer,30981,0 +67498,Male,33,Masters,2,61,1,96,8,5.0,2,5,Urban,Software Engineer,99565,0 +67499,Male,34,Bachelors,17,77,47,29,61,8.0,5,98,Semi-Urban,Manager,41851,1 +67500,Female,41,Masters,3,14,34,93,2,9.0,5,50,Urban,HR Executive,109565,0 +67501,Female,32,Diploma,15,0,18,37,99,6.0,0,15,Urban,Manager,44402,0 +67502,Male,36,Bachelors,0,74,47,67,89,8.0,0,84,Urban,ML Engineer,117568,1 +67503,Male,36,Masters,10,12,28,85,34,6.0,3,69,Semi-Urban,HR Executive,63754,0 +67504,Male,25,Masters,6,10,88,12,27,0.0,4,61,Rural,ML Engineer,35657,0 +67505,Male,30,Masters,2,45,22,86,62,7.0,2,96,Rural,Data Analyst,81943,1 +67506,Female,37,Masters,8,93,80,91,15,4.0,7,89,Rural,Software Engineer,62596,1 +67507,Other,38,Masters,14,84,60,17,85,8.0,3,7,Urban,Data Analyst,48250,0 +67508,Male,23,Masters,0,72,66,88,6,5.0,6,7,Urban,Data Analyst,85839,0 +67509,Male,56,Bachelors,0,85,79,71,74,3.0,2,16,Semi-Urban,Data Analyst,25356,1 +67510,Female,32,Masters,6,65,95,51,23,2.0,5,52,Rural,ML Engineer,28277,1 +67511,Male,32,Diploma,8,78,45,44,47,7.0,1,1,Rural,ML Engineer,114999,0 +67512,Male,40,Diploma,13,62,46,98,96,5.0,1,33,Semi-Urban,Manager,57759,1 +67513,Female,33,Bachelors,3,36,17,47,10,7.0,1,51,Urban,ML Engineer,95285,0 +67514,Female,57,Bachelors,3,16,66,69,31,6.0,7,7,Urban,ML Engineer,43979,0 +67515,Female,41,High School,6,79,90,21,0,7.0,6,40,Semi-Urban,Data Analyst,129573,0 +67516,Male,44,Bachelors,3,21,60,15,2,6.0,4,55,Urban,ML Engineer,36756,0 +67517,Male,28,High School,11,77,68,43,68,4.0,0,24,Semi-Urban,Manager,62714,0 +67518,Other,25,Masters,17,88,46,95,0,0.0,2,45,Urban,Data Analyst,118561,1 +67519,Male,32,Masters,8,97,99,22,17,1.0,2,43,Urban,Manager,138862,1 +67520,Male,34,Bachelors,14,99,93,92,74,4.0,3,2,Rural,HR Executive,47436,1 +67521,Male,26,PhD,15,25,41,73,43,5.0,2,0,Semi-Urban,Manager,86640,0 +67522,Male,47,Diploma,18,98,4,19,15,5.0,2,19,Semi-Urban,Software Engineer,50311,0 +67523,Male,38,Bachelors,18,65,9,53,9,1.0,7,21,Semi-Urban,Data Analyst,82344,0 +67524,Male,54,Masters,4,25,80,80,64,0.0,7,19,Rural,ML Engineer,80500,0 +67525,Female,26,High School,2,84,93,50,84,6.0,2,35,Rural,Software Engineer,74391,1 +67526,Male,51,Diploma,8,28,11,83,75,4.0,3,17,Rural,Data Analyst,28148,0 +67527,Female,34,Bachelors,1,40,33,88,53,9.0,5,90,Urban,HR Executive,71821,1 +67528,Female,40,Diploma,6,15,33,60,12,4.0,1,4,Rural,HR Executive,63546,0 +67529,Other,43,Masters,11,96,48,13,20,7.0,0,27,Semi-Urban,Manager,145608,0 +67530,Female,42,Masters,5,48,14,26,38,6.0,1,92,Rural,Data Analyst,49905,0 +67531,Male,24,High School,5,88,62,17,35,2.0,1,46,Urban,ML Engineer,53803,0 +67532,Male,34,Bachelors,8,21,50,66,4,9.0,0,31,Rural,Data Analyst,20290,0 +67533,Female,49,Masters,2,33,24,4,82,9.0,5,98,Rural,ML Engineer,72223,0 +67534,Other,31,Bachelors,9,25,6,28,39,0.0,6,4,Urban,Software Engineer,83075,0 +67535,Male,41,Bachelors,11,37,81,13,85,3.0,1,84,Semi-Urban,Manager,87487,0 +67536,Female,29,Diploma,12,0,90,13,35,8.0,6,75,Urban,ML Engineer,136654,0 +67537,Male,43,Bachelors,19,25,32,11,57,9.0,6,92,Rural,Data Analyst,49375,0 +67538,Male,21,Bachelors,1,36,78,7,27,8.0,1,59,Semi-Urban,Software Engineer,56210,0 +67539,Male,45,Diploma,14,30,50,74,2,4.0,0,78,Rural,Data Analyst,70068,0 +67540,Male,43,Bachelors,2,95,43,34,48,1.0,4,3,Urban,Software Engineer,137731,0 +67541,Female,56,Bachelors,4,79,63,4,84,5.0,7,14,Urban,Software Engineer,93805,0 +67542,Male,36,Diploma,10,71,95,68,13,0.0,4,76,Rural,Manager,34893,1 +67543,Male,46,Masters,18,83,78,59,67,1.0,3,38,Semi-Urban,ML Engineer,88169,1 +67544,Male,55,PhD,9,13,51,90,76,0.0,6,71,Semi-Urban,Software Engineer,44612,0 +67545,Male,58,Bachelors,2,21,70,58,9,4.0,1,12,Urban,Software Engineer,105706,0 +67546,Female,55,Masters,8,9,82,54,28,5.0,4,65,Semi-Urban,ML Engineer,126605,0 +67547,Male,21,Bachelors,12,69,58,86,96,6.0,2,91,Urban,HR Executive,34167,1 +67548,Female,21,Diploma,15,0,81,38,78,9.0,2,75,Urban,Manager,94573,0 +67549,Male,30,Bachelors,1,14,45,2,63,3.0,0,63,Urban,HR Executive,123187,0 +67550,Female,50,Masters,15,8,60,49,49,0.0,6,95,Semi-Urban,ML Engineer,53925,0 +67551,Male,21,High School,1,29,72,95,78,6.0,0,91,Rural,Software Engineer,77995,1 +67552,Male,25,Masters,0,80,69,44,12,6.0,5,75,Semi-Urban,Manager,72123,1 +67553,Male,49,Masters,14,51,20,54,6,4.0,4,11,Urban,Manager,39335,0 +67554,Male,33,Bachelors,1,52,10,5,22,6.0,6,27,Rural,Software Engineer,82830,0 +67555,Male,35,PhD,0,90,62,73,8,6.0,2,57,Semi-Urban,Software Engineer,64870,1 +67556,Male,52,Bachelors,5,2,71,71,59,0.0,2,27,Urban,HR Executive,67181,0 +67557,Female,32,Diploma,3,15,29,96,0,8.0,6,43,Urban,Software Engineer,29520,0 +67558,Female,45,High School,5,95,64,71,14,5.0,7,79,Rural,ML Engineer,31099,1 +67559,Male,31,High School,12,14,47,87,51,2.0,3,60,Rural,ML Engineer,80571,0 +67560,Female,56,Bachelors,0,18,76,75,65,2.0,3,35,Urban,Manager,91758,0 +67561,Male,23,Bachelors,6,11,72,36,33,2.0,6,0,Semi-Urban,HR Executive,68260,0 +67562,Female,57,Masters,4,70,42,68,32,5.0,2,98,Urban,Software Engineer,66595,1 +67563,Female,41,Masters,2,67,31,46,81,6.0,6,66,Rural,Data Analyst,126456,0 +67564,Male,25,Diploma,2,53,55,95,38,1.0,2,12,Urban,Manager,148757,0 +67565,Female,22,High School,3,99,24,44,89,9.0,1,62,Urban,Data Analyst,59719,0 +67566,Male,50,Diploma,0,88,81,13,9,4.0,3,57,Semi-Urban,Data Analyst,142795,1 +67567,Female,31,PhD,11,90,86,77,72,3.0,6,99,Semi-Urban,Data Analyst,94090,1 +67568,Male,30,Bachelors,11,1,16,47,51,9.0,1,47,Urban,Software Engineer,103872,0 +67569,Female,50,Masters,1,55,18,73,90,2.0,2,76,Urban,Manager,63182,0 +67570,Male,48,PhD,0,38,81,13,5,2.0,5,51,Urban,HR Executive,38531,0 +67571,Male,56,Diploma,6,42,36,6,55,3.0,7,98,Semi-Urban,ML Engineer,39070,0 +67572,Male,57,Masters,11,81,6,24,56,0.0,6,35,Semi-Urban,Manager,116834,0 +67573,Male,31,Bachelors,13,28,81,53,53,7.0,2,63,Semi-Urban,ML Engineer,92267,0 +67574,Male,21,Masters,11,7,23,95,29,9.0,2,21,Urban,ML Engineer,120572,0 +67575,Male,41,Bachelors,9,54,21,53,57,5.0,5,27,Urban,HR Executive,38662,0 +67576,Male,46,Bachelors,8,7,40,90,11,7.0,7,68,Urban,Data Analyst,119967,0 +67577,Male,46,Bachelors,9,90,28,4,66,7.0,5,1,Urban,HR Executive,49718,0 +67578,Male,32,Masters,15,85,94,92,69,0.0,4,53,Semi-Urban,Data Analyst,75107,1 +67579,Male,33,Bachelors,3,34,32,17,30,0.0,0,8,Rural,HR Executive,65134,0 +67580,Male,36,Diploma,14,12,62,47,45,1.0,0,55,Rural,Data Analyst,23696,0 +67581,Male,40,Bachelors,2,31,10,75,32,9.0,1,94,Urban,Manager,98012,0 +67582,Female,59,High School,17,41,29,79,51,6.0,3,98,Urban,ML Engineer,46008,1 +67583,Female,33,Bachelors,6,61,40,35,88,5.0,3,77,Semi-Urban,Software Engineer,134901,0 +67584,Female,48,Masters,2,20,17,41,42,0.0,0,47,Urban,Data Analyst,38368,0 +67585,Male,32,Bachelors,19,23,33,83,97,6.0,3,33,Urban,Manager,44171,0 +67586,Female,40,Bachelors,5,32,74,15,99,8.0,4,96,Urban,ML Engineer,22190,0 +67587,Male,36,High School,18,60,25,71,44,6.0,3,98,Urban,ML Engineer,120211,1 +67588,Male,33,High School,19,8,75,17,31,4.0,0,45,Urban,HR Executive,34145,0 +67589,Male,23,Diploma,6,34,15,17,15,2.0,5,11,Urban,HR Executive,119285,0 +67590,Male,26,High School,4,3,58,2,93,8.0,6,35,Urban,Manager,106325,0 +67591,Male,28,Diploma,8,47,48,0,58,2.0,6,12,Semi-Urban,Software Engineer,146777,0 +67592,Male,27,Bachelors,7,8,58,56,41,7.0,0,70,Semi-Urban,Software Engineer,42629,0 +67593,Female,33,Diploma,8,85,99,10,99,9.0,1,55,Semi-Urban,Software Engineer,105676,1 +67594,Male,52,Bachelors,4,30,67,23,55,4.0,4,29,Semi-Urban,Software Engineer,118936,0 +67595,Male,43,Masters,3,74,27,82,13,2.0,0,74,Urban,Data Analyst,113812,1 +67596,Female,25,Masters,8,91,95,25,37,7.0,0,73,Urban,Data Analyst,25731,1 +67597,Male,48,Bachelors,7,14,81,82,86,7.0,7,75,Urban,HR Executive,51890,1 +67598,Female,42,Diploma,15,29,35,66,60,8.0,7,97,Urban,HR Executive,47110,0 +67599,Male,30,Bachelors,14,56,68,60,19,0.0,0,97,Semi-Urban,ML Engineer,47832,1 +67600,Male,36,Bachelors,9,88,72,63,51,1.0,7,51,Urban,Manager,42059,1 +67601,Female,30,Diploma,0,51,84,42,76,4.0,1,19,Semi-Urban,HR Executive,26040,0 +67602,Female,56,Diploma,8,66,67,71,71,1.0,2,55,Urban,Manager,122181,1 +67603,Female,53,High School,8,21,21,84,64,4.0,4,37,Semi-Urban,Data Analyst,149954,0 +67604,Male,59,Diploma,14,85,41,95,29,8.0,1,41,Urban,Manager,28254,1 +67605,Female,35,High School,8,65,97,91,26,5.0,3,23,Semi-Urban,Manager,138087,1 +67606,Male,55,Diploma,3,7,71,11,15,6.0,3,43,Semi-Urban,Manager,100907,0 +67607,Female,57,Bachelors,14,54,80,43,2,1.0,7,8,Semi-Urban,Manager,63427,0 +67608,Female,35,High School,1,13,73,1,0,5.0,4,65,Urban,Data Analyst,135857,0 +67609,Other,24,High School,5,61,10,31,18,5.0,4,43,Semi-Urban,Data Analyst,58423,0 +67610,Male,27,Bachelors,8,70,13,83,68,3.0,2,0,Urban,Software Engineer,28886,0 +67611,Male,51,Bachelors,6,25,75,39,61,8.0,2,72,Urban,Data Analyst,106162,0 +67612,Male,47,Bachelors,17,10,94,33,40,6.0,5,76,Urban,ML Engineer,61067,0 +67613,Female,36,Masters,11,81,78,11,42,8.0,7,9,Urban,Data Analyst,102637,0 +67614,Female,49,High School,15,97,97,7,77,9.0,7,57,Semi-Urban,Data Analyst,97638,1 +67615,Male,57,Bachelors,5,9,92,59,81,0.0,0,23,Urban,Manager,147641,0 +67616,Male,29,Bachelors,2,24,39,39,81,6.0,3,50,Rural,HR Executive,89870,0 +67617,Female,22,Bachelors,6,42,21,93,41,9.0,5,8,Urban,ML Engineer,56397,0 +67618,Female,41,Bachelors,1,57,42,89,5,7.0,6,86,Urban,Software Engineer,53396,1 +67619,Male,22,Bachelors,10,33,65,13,62,5.0,6,33,Urban,Data Analyst,109573,0 +67620,Female,36,Bachelors,15,44,34,73,40,8.0,4,29,Rural,HR Executive,142291,0 +67621,Male,52,Masters,6,16,53,82,37,4.0,0,29,Semi-Urban,ML Engineer,137893,0 +67622,Other,49,Masters,0,59,42,50,84,6.0,7,61,Semi-Urban,Manager,88675,0 +67623,Male,51,Masters,1,30,0,46,4,4.0,7,70,Urban,Software Engineer,117732,0 +67624,Male,33,Masters,12,67,83,68,65,5.0,6,11,Urban,HR Executive,42888,0 +67625,Male,36,Bachelors,11,33,25,3,29,1.0,4,56,Urban,Manager,44900,0 +67626,Female,34,Bachelors,14,12,21,10,99,2.0,0,22,Semi-Urban,Software Engineer,55994,0 +67627,Male,54,Masters,17,55,49,54,50,0.0,5,98,Semi-Urban,Software Engineer,78989,1 +67628,Male,50,Bachelors,3,0,75,15,9,3.0,3,44,Urban,Software Engineer,65853,0 +67629,Other,56,High School,1,80,80,69,7,3.0,5,33,Urban,ML Engineer,120100,1 +67630,Female,43,High School,13,25,39,81,51,2.0,0,28,Semi-Urban,Manager,63365,0 +67631,Male,30,Masters,3,10,11,92,76,3.0,3,64,Semi-Urban,Software Engineer,89788,0 +67632,Male,31,Bachelors,8,50,85,16,4,7.0,4,67,Rural,HR Executive,128340,0 +67633,Male,48,Masters,1,47,27,85,87,9.0,7,5,Urban,Manager,94585,0 +67634,Male,31,Bachelors,18,57,5,80,59,9.0,6,12,Urban,Software Engineer,49989,0 +67635,Male,38,Bachelors,13,43,43,76,4,3.0,3,28,Urban,ML Engineer,75459,0 +67636,Male,58,Bachelors,14,5,3,63,81,9.0,2,60,Urban,Manager,75850,0 +67637,Female,24,Diploma,9,69,23,8,51,9.0,7,50,Rural,HR Executive,56472,0 +67638,Male,53,Diploma,19,67,98,1,40,0.0,1,26,Urban,Manager,60189,0 +67639,Male,36,Bachelors,8,95,64,90,30,8.0,2,69,Semi-Urban,Data Analyst,24864,1 +67640,Female,50,PhD,6,71,83,15,33,4.0,5,58,Urban,Data Analyst,28397,0 +67641,Female,54,Diploma,0,59,25,96,2,3.0,0,48,Urban,HR Executive,87336,0 +67642,Male,21,Bachelors,12,51,90,0,66,5.0,1,41,Rural,Data Analyst,108353,0 +67643,Male,57,High School,4,48,12,78,74,3.0,4,56,Urban,Data Analyst,49260,0 +67644,Female,42,High School,9,10,69,10,20,6.0,4,53,Rural,Manager,60599,0 +67645,Female,34,Bachelors,1,79,92,94,40,2.0,0,40,Rural,HR Executive,139530,1 +67646,Female,47,High School,5,67,66,43,94,1.0,3,84,Rural,ML Engineer,133799,1 +67647,Male,49,Masters,5,55,27,31,57,7.0,7,12,Semi-Urban,Software Engineer,139357,0 +67648,Male,29,High School,14,26,59,23,32,3.0,2,2,Urban,Manager,107526,0 +67649,Female,43,PhD,6,38,61,58,18,2.0,4,73,Urban,Manager,83204,0 +67650,Male,48,Masters,15,12,70,7,64,6.0,0,59,Urban,Manager,34203,0 +67651,Female,45,Masters,9,4,38,50,15,4.0,7,88,Urban,Data Analyst,84572,0 +67652,Male,46,Bachelors,6,29,41,3,10,9.0,7,80,Urban,Manager,85592,0 +67653,Female,34,Bachelors,4,13,33,61,93,5.0,6,64,Urban,Manager,131776,0 +67654,Male,59,PhD,11,22,72,28,43,6.0,7,56,Semi-Urban,Software Engineer,44055,0 +67655,Male,37,Masters,2,39,16,75,72,9.0,7,80,Urban,ML Engineer,29949,0 +67656,Male,58,Bachelors,4,83,9,57,7,4.0,4,57,Urban,Manager,47642,0 +67657,Female,22,Bachelors,5,57,28,45,29,1.0,7,82,Urban,Data Analyst,124164,0 +67658,Male,25,Diploma,13,44,58,20,66,7.0,0,39,Rural,Software Engineer,60045,0 +67659,Male,59,Diploma,15,38,42,10,78,6.0,3,96,Rural,Manager,55440,0 +67660,Male,34,Masters,10,0,99,72,66,0.0,7,96,Rural,Software Engineer,35532,1 +67661,Female,24,High School,1,46,90,4,36,8.0,5,6,Semi-Urban,Data Analyst,138621,0 +67662,Male,25,Diploma,18,34,1,59,19,6.0,7,49,Urban,ML Engineer,108633,0 +67663,Male,56,Bachelors,11,59,86,73,38,2.0,2,81,Semi-Urban,Manager,129179,1 +67664,Male,29,Bachelors,14,80,6,89,18,6.0,1,69,Semi-Urban,Manager,105334,1 +67665,Female,29,Bachelors,8,84,57,1,3,2.0,5,55,Semi-Urban,ML Engineer,84527,0 +67666,Other,56,Bachelors,17,65,7,37,23,7.0,6,97,Urban,Software Engineer,48348,0 +67667,Male,53,Bachelors,0,74,59,84,61,5.0,3,71,Urban,Software Engineer,79496,1 +67668,Other,47,Bachelors,13,7,39,0,20,8.0,5,4,Urban,HR Executive,82541,0 +67669,Female,35,Bachelors,16,71,81,72,18,2.0,0,51,Semi-Urban,HR Executive,63336,1 +67670,Female,47,Masters,12,57,84,77,4,6.0,3,7,Urban,Manager,123643,0 +67671,Female,29,Bachelors,19,98,44,78,19,4.0,3,91,Urban,ML Engineer,112181,1 +67672,Female,56,Bachelors,18,97,67,44,32,3.0,4,99,Semi-Urban,Software Engineer,61206,1 +67673,Female,33,Bachelors,6,91,78,77,60,0.0,3,22,Rural,HR Executive,127424,1 +67674,Male,21,Diploma,10,64,85,56,55,3.0,2,93,Rural,Manager,50200,1 +67675,Female,22,Bachelors,6,53,53,39,44,6.0,0,69,Urban,Software Engineer,122494,0 +67676,Male,37,Bachelors,0,31,30,24,1,6.0,0,56,Semi-Urban,Data Analyst,69361,0 +67677,Female,39,Masters,8,42,67,26,7,0.0,3,95,Urban,Manager,112391,0 +67678,Male,23,Diploma,8,1,45,14,53,0.0,5,1,Semi-Urban,Manager,84005,0 +67679,Male,49,PhD,15,8,65,40,20,8.0,5,2,Urban,Manager,32073,0 +67680,Female,39,Diploma,19,94,11,5,80,8.0,4,12,Urban,Data Analyst,45129,0 +67681,Male,41,PhD,9,86,52,71,52,6.0,5,89,Urban,Manager,136244,1 +67682,Female,27,Bachelors,13,86,71,22,8,1.0,4,76,Semi-Urban,Manager,57878,1 +67683,Female,46,High School,3,9,19,54,44,8.0,1,79,Urban,ML Engineer,129480,0 +67684,Male,27,Masters,9,54,13,63,56,6.0,1,46,Urban,ML Engineer,75870,0 +67685,Male,42,Bachelors,16,95,78,16,96,2.0,1,79,Urban,Software Engineer,69638,1 +67686,Female,45,Bachelors,15,81,99,47,25,0.0,0,18,Urban,Software Engineer,99027,1 +67687,Female,53,Masters,9,69,17,13,17,1.0,4,34,Rural,HR Executive,90543,0 +67688,Male,49,Diploma,10,10,43,72,35,1.0,2,85,Urban,Data Analyst,84948,0 +67689,Female,40,Masters,17,76,12,36,60,2.0,6,39,Urban,Manager,125198,0 +67690,Female,53,Bachelors,18,93,7,70,12,2.0,6,73,Urban,ML Engineer,85372,1 +67691,Male,34,Bachelors,16,3,70,4,95,0.0,2,28,Semi-Urban,HR Executive,27000,0 +67692,Female,41,Bachelors,13,45,40,66,43,8.0,5,63,Urban,Software Engineer,144674,0 +67693,Female,38,Bachelors,14,60,30,26,38,7.0,4,85,Rural,Software Engineer,104599,0 +67694,Male,25,High School,2,39,54,82,91,7.0,7,40,Urban,Data Analyst,58412,0 +67695,Other,37,Bachelors,2,39,50,42,44,8.0,1,47,Rural,Software Engineer,108364,0 +67696,Male,26,High School,16,75,16,76,20,4.0,3,85,Semi-Urban,Data Analyst,69744,1 +67697,Female,41,High School,12,95,36,64,40,8.0,2,75,Urban,ML Engineer,33267,1 +67698,Male,53,Diploma,2,94,62,49,36,2.0,1,91,Rural,Manager,127638,1 +67699,Male,48,Diploma,8,8,1,9,91,9.0,1,12,Urban,HR Executive,33410,0 +67700,Male,47,Masters,12,46,20,19,80,9.0,6,69,Urban,ML Engineer,129034,0 +67701,Male,58,Bachelors,17,6,0,61,96,4.0,6,39,Rural,ML Engineer,37344,0 +67702,Female,41,High School,6,9,60,51,79,0.0,0,97,Semi-Urban,Software Engineer,51660,0 +67703,Male,28,Masters,0,63,88,15,50,2.0,1,35,Semi-Urban,ML Engineer,97968,0 +67704,Male,25,Bachelors,17,70,73,52,24,0.0,4,99,Urban,HR Executive,133339,1 +67705,Female,33,Diploma,15,5,13,81,19,8.0,0,68,Urban,ML Engineer,94959,0 +67706,Male,58,Bachelors,9,11,12,46,29,9.0,0,83,Semi-Urban,ML Engineer,85102,0 +67707,Female,56,Masters,17,96,58,23,83,6.0,0,52,Urban,Manager,125888,0 +67708,Male,42,High School,16,8,56,96,49,4.0,4,56,Semi-Urban,HR Executive,60315,0 +67709,Male,30,High School,3,40,42,72,44,7.0,6,92,Urban,Manager,69801,1 +67710,Female,28,Bachelors,5,46,3,42,76,1.0,2,91,Semi-Urban,Data Analyst,26366,0 +67711,Female,34,High School,0,77,21,0,57,2.0,2,68,Urban,Manager,23841,0 +67712,Male,35,Masters,7,23,74,77,91,5.0,2,77,Semi-Urban,ML Engineer,72283,1 +67713,Female,22,Bachelors,3,74,41,50,81,7.0,0,64,Semi-Urban,Manager,54933,0 +67714,Male,40,Diploma,19,90,61,47,7,1.0,0,67,Rural,ML Engineer,36032,1 +67715,Female,49,Diploma,4,54,10,66,48,7.0,0,3,Rural,ML Engineer,98747,0 +67716,Female,54,Diploma,7,88,86,85,57,9.0,5,56,Semi-Urban,ML Engineer,107125,1 +67717,Male,24,Bachelors,13,2,75,88,53,4.0,7,85,Urban,Software Engineer,81008,1 +67718,Female,39,Bachelors,0,45,51,8,7,1.0,7,89,Rural,Manager,119688,0 +67719,Female,44,Diploma,9,54,53,19,94,3.0,7,22,Urban,HR Executive,27855,0 +67720,Male,35,Bachelors,6,62,29,5,34,7.0,6,24,Semi-Urban,Data Analyst,107654,0 +67721,Male,34,Masters,4,10,41,51,1,5.0,3,35,Urban,Data Analyst,149761,0 +67722,Female,34,High School,19,29,22,91,31,7.0,7,75,Urban,ML Engineer,50917,0 +67723,Female,25,Diploma,9,96,75,16,68,9.0,7,40,Urban,ML Engineer,148344,0 +67724,Male,50,Diploma,19,63,30,35,28,4.0,2,2,Urban,HR Executive,77434,0 +67725,Male,38,High School,12,26,69,95,93,5.0,4,61,Semi-Urban,Data Analyst,143791,1 +67726,Female,23,High School,10,66,42,38,31,2.0,5,84,Semi-Urban,Software Engineer,128691,0 +67727,Male,21,High School,19,91,5,9,95,5.0,2,78,Semi-Urban,ML Engineer,111266,0 +67728,Male,45,Masters,0,37,19,58,79,4.0,4,42,Urban,ML Engineer,66619,0 +67729,Male,49,Diploma,6,7,15,24,76,3.0,0,66,Semi-Urban,HR Executive,47735,0 +67730,Male,42,Diploma,7,43,57,95,86,1.0,7,0,Urban,Software Engineer,95158,0 +67731,Male,36,Diploma,6,65,71,26,43,5.0,7,47,Urban,HR Executive,93845,0 +67732,Male,57,Masters,19,25,3,60,64,9.0,6,70,Rural,HR Executive,134729,0 +67733,Male,25,Diploma,7,63,56,10,52,7.0,0,66,Semi-Urban,HR Executive,43508,0 +67734,Female,51,High School,6,54,1,6,61,5.0,7,4,Semi-Urban,ML Engineer,124804,0 +67735,Male,23,High School,15,9,28,91,11,4.0,1,36,Urban,Data Analyst,59556,0 +67736,Male,34,Diploma,5,92,78,21,29,8.0,7,81,Urban,Data Analyst,35948,1 +67737,Female,40,Bachelors,12,86,2,92,55,3.0,3,25,Urban,ML Engineer,67944,0 +67738,Male,46,Bachelors,5,25,44,99,82,0.0,6,43,Semi-Urban,HR Executive,146024,0 +67739,Male,53,Bachelors,13,13,87,29,16,3.0,7,23,Urban,ML Engineer,39411,0 +67740,Female,27,High School,11,9,74,20,28,3.0,5,6,Rural,HR Executive,43211,0 +67741,Male,55,High School,4,29,23,21,44,3.0,6,62,Rural,Data Analyst,70881,0 +67742,Male,25,Masters,12,47,64,51,57,3.0,4,70,Rural,Manager,49978,0 +67743,Male,23,Diploma,12,10,62,16,11,2.0,5,0,Semi-Urban,Manager,133197,0 +67744,Male,58,Masters,11,99,87,86,30,3.0,2,92,Urban,Data Analyst,75537,1 +67745,Female,42,Diploma,3,36,62,63,13,6.0,7,92,Urban,HR Executive,75322,1 +67746,Male,39,High School,17,44,87,73,97,8.0,5,4,Semi-Urban,Software Engineer,23203,0 +67747,Male,54,Diploma,0,15,75,1,1,4.0,7,80,Urban,ML Engineer,141195,0 +67748,Male,31,High School,16,69,95,73,63,4.0,0,61,Rural,Data Analyst,139217,1 +67749,Female,44,High School,6,48,42,2,13,3.0,6,90,Urban,HR Executive,73129,0 +67750,Female,33,Bachelors,16,82,88,50,69,8.0,5,49,Urban,Manager,22776,1 +67751,Male,27,Diploma,11,46,53,80,49,3.0,5,78,Urban,Data Analyst,75187,1 +67752,Male,31,Bachelors,7,60,92,36,42,2.0,3,43,Rural,Software Engineer,97821,0 +67753,Female,39,Diploma,16,44,33,34,67,5.0,5,24,Urban,Data Analyst,130141,0 +67754,Male,28,Bachelors,5,80,16,52,32,8.0,1,97,Urban,Data Analyst,95345,1 +67755,Female,46,Bachelors,15,20,37,47,46,1.0,2,5,Urban,Data Analyst,47107,0 +67756,Other,38,Masters,11,82,55,8,7,9.0,6,26,Urban,Manager,130023,0 +67757,Female,22,Bachelors,0,27,75,7,37,0.0,7,9,Rural,Manager,107633,0 +67758,Male,29,Masters,5,71,63,50,74,8.0,6,82,Rural,HR Executive,45165,1 +67759,Male,41,High School,2,39,34,88,13,7.0,7,47,Urban,ML Engineer,40125,0 +67760,Male,41,Masters,15,8,92,74,18,0.0,0,38,Urban,Data Analyst,57926,0 +67761,Male,31,Diploma,1,74,75,17,80,4.0,6,26,Urban,HR Executive,105818,0 +67762,Female,47,High School,7,91,27,53,76,7.0,3,5,Urban,Data Analyst,140583,0 +67763,Female,55,Masters,8,83,88,75,62,1.0,6,6,Semi-Urban,Data Analyst,46045,1 +67764,Female,59,High School,17,45,15,24,45,7.0,3,81,Urban,HR Executive,69420,0 +67765,Male,32,Masters,1,5,94,8,61,0.0,3,31,Urban,Software Engineer,85591,0 +67766,Female,28,High School,17,94,95,53,36,4.0,6,8,Rural,HR Executive,85492,1 +67767,Male,59,Masters,16,75,39,97,9,4.0,7,19,Urban,Data Analyst,148553,0 +67768,Male,44,Bachelors,3,61,55,11,75,5.0,6,72,Rural,Manager,34378,0 +67769,Male,27,Masters,19,71,40,49,45,7.0,2,55,Urban,Software Engineer,145909,0 +67770,Male,52,Bachelors,2,69,23,98,11,1.0,2,0,Rural,ML Engineer,96840,0 +67771,Male,51,Diploma,7,6,8,64,81,1.0,1,26,Urban,ML Engineer,104251,0 +67772,Male,30,Bachelors,19,62,72,23,39,4.0,6,91,Urban,HR Executive,124255,1 +67773,Female,44,Masters,10,98,26,46,68,7.0,5,46,Urban,ML Engineer,92375,0 +67774,Male,36,High School,18,22,93,70,57,3.0,6,70,Rural,Data Analyst,45495,1 +67775,Male,45,Diploma,7,58,51,21,85,0.0,6,91,Rural,HR Executive,87133,0 +67776,Female,30,Bachelors,8,56,61,47,40,4.0,7,54,Rural,Manager,90066,0 +67777,Male,52,Bachelors,4,50,84,59,66,1.0,1,81,Urban,Software Engineer,97347,1 +67778,Male,40,Bachelors,18,19,65,52,46,9.0,1,66,Urban,ML Engineer,67281,0 +67779,Female,26,Bachelors,15,20,37,16,63,2.0,7,60,Urban,HR Executive,139237,0 +67780,Female,51,Bachelors,9,22,19,31,67,5.0,3,90,Urban,Software Engineer,139539,0 +67781,Male,45,PhD,0,37,41,10,59,8.0,3,76,Urban,Manager,87790,0 +67782,Male,49,Masters,19,88,52,39,39,1.0,1,61,Urban,HR Executive,119666,1 +67783,Male,58,Diploma,11,21,72,65,47,6.0,4,19,Urban,Data Analyst,115901,0 +67784,Male,48,Bachelors,15,79,37,59,22,8.0,3,66,Urban,HR Executive,39092,1 +67785,Female,46,Masters,7,14,95,99,66,3.0,5,18,Semi-Urban,Data Analyst,111582,0 +67786,Male,50,Diploma,13,55,45,11,53,7.0,1,45,Semi-Urban,Software Engineer,78176,0 +67787,Male,49,Bachelors,7,50,67,1,53,2.0,1,26,Urban,ML Engineer,79244,0 +67788,Male,53,Bachelors,13,39,1,41,50,5.0,0,43,Urban,Software Engineer,102595,0 +67789,Male,23,Diploma,12,9,8,34,19,1.0,1,60,Rural,Manager,93236,0 +67790,Male,42,High School,11,62,90,34,40,9.0,1,26,Semi-Urban,ML Engineer,56767,0 +67791,Male,59,Masters,3,62,75,46,95,4.0,4,79,Urban,ML Engineer,127005,1 +67792,Male,22,Bachelors,14,43,73,70,94,6.0,0,75,Urban,Manager,111245,1 +67793,Other,57,High School,3,69,42,85,50,1.0,2,68,Urban,HR Executive,110003,1 +67794,Male,26,Masters,1,25,46,10,58,0.0,2,24,Urban,HR Executive,49373,0 +67795,Male,32,Masters,3,97,17,58,0,2.0,2,59,Semi-Urban,Software Engineer,61967,0 +67796,Male,39,Masters,11,73,80,87,66,6.0,4,38,Semi-Urban,Manager,94533,1 +67797,Female,43,Bachelors,7,95,60,30,53,9.0,4,6,Rural,Manager,129810,0 +67798,Female,48,High School,13,71,13,47,74,5.0,0,70,Urban,HR Executive,147508,0 +67799,Male,40,PhD,5,18,56,69,77,1.0,6,54,Urban,Software Engineer,118691,0 +67800,Female,21,PhD,11,96,70,78,44,4.0,5,35,Urban,Software Engineer,99093,1 +67801,Female,45,High School,18,56,52,35,53,0.0,0,10,Semi-Urban,HR Executive,32618,0 +67802,Male,23,Masters,14,18,58,20,87,9.0,0,11,Urban,HR Executive,28408,0 +67803,Male,42,Diploma,4,21,7,48,44,5.0,5,7,Rural,Software Engineer,69353,0 +67804,Other,55,Masters,19,99,64,89,31,3.0,0,23,Urban,Software Engineer,46127,1 +67805,Male,29,Bachelors,0,53,33,97,14,1.0,0,85,Urban,ML Engineer,95593,1 +67806,Male,57,Bachelors,2,54,94,88,80,3.0,5,94,Semi-Urban,Manager,139188,1 +67807,Male,49,Diploma,10,83,62,36,94,3.0,7,30,Rural,Manager,50461,0 +67808,Male,34,PhD,16,35,0,62,45,1.0,1,89,Semi-Urban,Data Analyst,62328,0 +67809,Female,46,PhD,17,36,92,95,24,7.0,4,31,Urban,Manager,40692,1 +67810,Male,49,Diploma,10,19,2,89,13,1.0,2,70,Urban,Manager,29078,0 +67811,Male,51,Bachelors,12,81,52,76,11,9.0,5,59,Urban,HR Executive,66148,1 +67812,Male,38,High School,4,51,9,80,55,6.0,4,80,Urban,ML Engineer,51283,0 +67813,Male,38,Masters,14,14,30,82,43,6.0,6,17,Rural,ML Engineer,111101,0 +67814,Male,47,High School,1,20,80,25,30,2.0,6,10,Rural,Manager,110690,0 +67815,Female,24,Bachelors,12,22,47,70,41,0.0,6,30,Semi-Urban,HR Executive,71905,0 +67816,Male,29,High School,9,17,56,53,75,1.0,5,18,Semi-Urban,Manager,79327,0 +67817,Female,49,Diploma,16,66,70,24,88,0.0,4,80,Urban,Data Analyst,93094,0 +67818,Male,22,Masters,3,55,52,69,27,9.0,1,49,Urban,Software Engineer,73903,0 +67819,Male,40,Bachelors,2,12,33,59,71,3.0,0,78,Rural,HR Executive,91283,0 +67820,Male,34,Bachelors,3,11,1,66,6,7.0,3,53,Rural,Manager,25579,0 +67821,Male,24,High School,12,33,47,20,68,3.0,6,5,Urban,HR Executive,77399,0 +67822,Female,34,Bachelors,5,60,21,81,94,5.0,6,44,Urban,ML Engineer,25417,0 +67823,Male,57,Diploma,8,55,37,97,65,2.0,3,31,Semi-Urban,HR Executive,118798,0 +67824,Male,58,Diploma,5,27,75,70,5,2.0,1,24,Urban,Data Analyst,72412,0 +67825,Female,22,Masters,10,2,47,84,1,3.0,2,72,Rural,Software Engineer,111127,0 +67826,Female,57,Bachelors,1,75,88,20,26,8.0,3,9,Semi-Urban,HR Executive,113661,0 +67827,Other,35,Masters,4,94,2,14,58,2.0,1,13,Urban,Manager,37203,0 +67828,Male,26,PhD,8,69,3,69,43,4.0,4,36,Urban,Manager,52375,0 +67829,Female,46,Bachelors,12,12,86,30,81,7.0,5,69,Urban,Software Engineer,96300,0 +67830,Female,27,Bachelors,8,91,52,26,48,8.0,3,18,Urban,HR Executive,148137,0 +67831,Male,45,High School,7,1,75,94,13,8.0,7,13,Urban,Manager,64276,0 +67832,Male,25,Bachelors,17,68,16,16,2,7.0,7,54,Urban,ML Engineer,41863,0 +67833,Female,37,Bachelors,8,61,65,50,11,3.0,3,36,Urban,Software Engineer,115810,0 +67834,Male,26,High School,16,25,76,59,87,0.0,7,34,Semi-Urban,Data Analyst,87757,0 +67835,Female,43,Bachelors,8,22,62,96,2,1.0,5,19,Urban,Software Engineer,44809,0 +67836,Male,32,Masters,7,32,88,92,21,0.0,0,53,Semi-Urban,ML Engineer,60042,1 +67837,Female,40,PhD,11,13,1,54,75,6.0,0,83,Urban,Data Analyst,90278,0 +67838,Male,56,Masters,16,2,66,11,97,1.0,5,39,Semi-Urban,ML Engineer,57989,0 +67839,Male,57,Bachelors,13,23,7,4,25,6.0,1,62,Rural,Data Analyst,135491,0 +67840,Male,59,Masters,0,23,9,56,95,7.0,5,66,Rural,Manager,82474,0 +67841,Female,37,Diploma,9,32,44,5,42,3.0,5,31,Urban,ML Engineer,90272,0 +67842,Male,41,Bachelors,6,18,27,78,16,8.0,1,83,Rural,Software Engineer,66276,0 +67843,Male,43,Bachelors,0,62,33,85,64,8.0,5,31,Urban,HR Executive,138911,0 +67844,Male,55,Bachelors,11,18,44,54,34,1.0,3,50,Urban,Software Engineer,34200,0 +67845,Male,51,Bachelors,14,57,89,11,45,2.0,5,0,Urban,ML Engineer,75991,0 +67846,Male,40,Diploma,7,96,46,6,83,8.0,1,37,Semi-Urban,Manager,98188,0 +67847,Female,45,Bachelors,15,12,81,99,84,0.0,6,67,Urban,ML Engineer,56550,1 +67848,Male,44,Bachelors,15,72,54,3,47,5.0,0,72,Semi-Urban,Manager,71842,0 +67849,Male,46,Masters,5,75,28,38,82,8.0,5,95,Rural,Manager,149725,1 +67850,Female,27,Diploma,9,31,18,59,35,9.0,3,38,Urban,Data Analyst,65622,0 +67851,Other,46,Bachelors,2,24,18,80,58,0.0,3,26,Semi-Urban,Manager,127220,0 +67852,Female,53,Bachelors,8,65,29,40,42,9.0,3,59,Urban,HR Executive,86485,0 +67853,Male,22,Diploma,4,29,68,30,76,0.0,7,4,Urban,Software Engineer,107162,0 +67854,Male,26,Bachelors,9,95,94,45,62,4.0,1,72,Semi-Urban,Manager,133565,1 +67855,Female,22,Diploma,3,48,32,3,59,0.0,1,27,Urban,ML Engineer,64537,0 +67856,Female,31,High School,9,32,83,69,2,5.0,6,73,Urban,Data Analyst,77103,1 +67857,Male,59,Masters,14,91,12,83,4,3.0,3,92,Semi-Urban,Software Engineer,109766,1 +67858,Female,38,Bachelors,1,50,36,35,85,3.0,4,54,Urban,Manager,32768,0 +67859,Female,46,Diploma,6,6,43,93,73,5.0,0,17,Urban,Data Analyst,77802,0 +67860,Other,25,High School,9,62,99,53,96,7.0,2,36,Semi-Urban,Software Engineer,53628,1 +67861,Female,51,Masters,16,66,40,94,38,1.0,2,4,Rural,Data Analyst,36567,0 +67862,Male,26,Bachelors,2,60,8,67,12,6.0,6,84,Urban,Manager,146882,0 +67863,Female,30,Bachelors,17,75,53,56,26,5.0,2,41,Urban,Software Engineer,27078,0 +67864,Male,32,Masters,17,4,58,27,52,8.0,4,62,Urban,Manager,36507,0 +67865,Female,26,Diploma,19,19,10,29,73,2.0,2,67,Rural,ML Engineer,147843,0 +67866,Male,40,Masters,14,74,86,99,39,3.0,1,84,Urban,ML Engineer,133434,1 +67867,Female,21,Masters,10,80,21,73,52,1.0,2,82,Urban,HR Executive,92288,1 +67868,Male,39,Bachelors,19,60,61,11,32,9.0,2,76,Semi-Urban,Software Engineer,38616,0 +67869,Female,42,Bachelors,6,85,5,53,93,7.0,2,48,Semi-Urban,ML Engineer,146408,0 +67870,Male,57,PhD,10,43,88,50,92,8.0,1,61,Rural,Software Engineer,81596,1 +67871,Female,51,Diploma,6,69,5,55,98,9.0,1,25,Rural,Manager,106782,0 +67872,Male,25,Diploma,13,3,16,56,12,2.0,1,71,Urban,Data Analyst,42573,0 +67873,Female,23,Masters,8,94,20,39,37,4.0,3,6,Rural,Data Analyst,72282,0 +67874,Male,51,Diploma,7,85,74,79,83,5.0,6,19,Rural,Manager,145392,1 +67875,Female,40,Bachelors,12,17,56,61,39,8.0,4,29,Semi-Urban,ML Engineer,139506,0 +67876,Female,55,Bachelors,13,11,39,34,65,3.0,5,96,Semi-Urban,Software Engineer,84218,0 +67877,Female,37,Bachelors,18,33,5,54,91,7.0,2,30,Urban,HR Executive,116102,0 +67878,Male,37,Diploma,10,82,8,12,45,6.0,7,91,Urban,Software Engineer,89556,0 +67879,Male,24,Bachelors,14,93,91,55,62,8.0,3,36,Urban,Manager,139500,1 +67880,Female,58,Bachelors,7,52,17,19,32,2.0,2,35,Urban,ML Engineer,40481,0 +67881,Male,27,Bachelors,14,31,82,46,50,1.0,6,24,Urban,Manager,56024,0 +67882,Female,22,Bachelors,10,35,56,42,91,8.0,1,77,Semi-Urban,ML Engineer,147790,0 +67883,Male,35,Bachelors,12,20,87,36,60,1.0,4,98,Urban,ML Engineer,141781,1 +67884,Male,22,Diploma,6,14,40,2,14,4.0,5,81,Semi-Urban,ML Engineer,45843,0 +67885,Female,47,PhD,17,48,80,35,85,8.0,5,88,Urban,HR Executive,53713,1 +67886,Female,55,Diploma,1,2,81,74,22,6.0,3,98,Urban,Software Engineer,54493,1 +67887,Male,43,High School,0,26,78,5,94,8.0,7,6,Semi-Urban,Software Engineer,24781,0 +67888,Male,28,High School,0,82,77,53,96,8.0,1,6,Urban,Manager,66755,0 +67889,Female,25,Bachelors,5,43,91,9,86,9.0,2,85,Urban,Software Engineer,22124,0 +67890,Male,48,Bachelors,18,20,44,84,71,7.0,1,90,Semi-Urban,HR Executive,67428,1 +67891,Male,48,High School,7,29,26,4,72,9.0,6,19,Urban,ML Engineer,135120,0 +67892,Female,32,PhD,10,41,42,78,57,4.0,1,12,Urban,Manager,63153,0 +67893,Male,50,High School,1,32,35,48,59,8.0,7,99,Rural,Manager,49538,0 +67894,Male,42,Bachelors,6,27,13,72,21,7.0,1,73,Urban,Manager,66308,0 +67895,Male,27,Diploma,12,99,12,30,81,4.0,7,10,Semi-Urban,Manager,73512,0 +67896,Female,37,Bachelors,4,7,93,99,30,7.0,5,25,Rural,Software Engineer,92894,0 +67897,Other,29,Diploma,13,94,27,27,97,5.0,7,33,Semi-Urban,Manager,77964,0 +67898,Male,51,Diploma,7,67,76,50,36,8.0,7,3,Semi-Urban,Manager,102675,0 +67899,Male,23,Bachelors,11,66,34,44,46,9.0,7,55,Urban,ML Engineer,78456,0 +67900,Female,27,High School,1,72,0,35,52,4.0,6,94,Urban,Software Engineer,66492,0 +67901,Male,54,Masters,6,90,76,37,47,6.0,0,35,Urban,Manager,83690,1 +67902,Female,31,Bachelors,10,82,70,53,89,0.0,6,84,Urban,Software Engineer,92693,1 +67903,Male,57,Bachelors,15,59,18,9,25,5.0,2,28,Semi-Urban,ML Engineer,123526,0 +67904,Male,58,PhD,14,7,10,7,74,8.0,3,0,Semi-Urban,Manager,85252,0 +67905,Female,58,High School,11,9,0,63,84,5.0,4,40,Urban,HR Executive,124047,0 +67906,Male,31,Bachelors,2,65,21,67,33,5.0,7,31,Semi-Urban,Software Engineer,72712,0 +67907,Male,45,Masters,17,92,10,60,51,4.0,3,74,Urban,Data Analyst,105892,1 +67908,Male,49,Diploma,11,39,20,0,57,7.0,7,86,Rural,ML Engineer,118721,0 +67909,Male,52,PhD,0,24,99,60,6,0.0,6,60,Rural,Manager,120112,1 +67910,Female,54,Bachelors,8,32,20,12,55,4.0,7,87,Urban,ML Engineer,60165,0 +67911,Female,42,Bachelors,11,45,73,58,46,4.0,0,49,Rural,HR Executive,147689,0 +67912,Male,39,Masters,8,64,44,43,19,9.0,5,1,Urban,ML Engineer,78803,0 +67913,Male,35,Masters,11,67,13,72,80,7.0,1,66,Semi-Urban,ML Engineer,112063,0 +67914,Male,21,Diploma,17,68,33,67,6,3.0,1,84,Urban,Manager,23733,1 +67915,Female,50,High School,18,42,68,49,24,9.0,4,65,Semi-Urban,Data Analyst,132372,0 +67916,Female,26,Bachelors,11,97,10,10,29,3.0,7,17,Rural,Data Analyst,68953,0 +67917,Female,34,Bachelors,18,57,78,63,93,9.0,2,2,Rural,ML Engineer,148962,0 +67918,Male,31,Bachelors,2,29,52,80,54,2.0,0,40,Urban,Data Analyst,94378,0 +67919,Female,36,Bachelors,5,89,13,59,21,1.0,6,64,Urban,Data Analyst,58160,0 +67920,Female,59,Diploma,3,28,86,65,80,4.0,3,66,Rural,HR Executive,45620,1 +67921,Female,33,High School,8,24,20,70,41,5.0,2,73,Rural,Manager,122019,0 +67922,Male,59,Bachelors,13,5,95,94,55,1.0,3,60,Rural,Manager,79864,1 +67923,Male,45,Bachelors,10,27,62,11,11,7.0,7,58,Urban,Manager,149244,0 +67924,Male,55,High School,2,61,27,69,37,3.0,7,48,Semi-Urban,Software Engineer,65277,0 +67925,Male,49,Diploma,2,20,47,19,55,2.0,1,63,Urban,HR Executive,105975,0 +67926,Male,40,Masters,0,3,52,61,94,2.0,5,23,Semi-Urban,Manager,61163,0 +67927,Female,30,Masters,2,5,9,97,92,8.0,5,68,Urban,Manager,73427,0 +67928,Other,27,Bachelors,7,46,64,34,18,8.0,6,61,Urban,Software Engineer,48944,0 +67929,Male,57,High School,5,99,32,48,5,8.0,2,33,Urban,Software Engineer,49753,0 +67930,Female,29,Masters,0,97,47,18,30,5.0,2,98,Urban,Software Engineer,115144,1 +67931,Male,31,Diploma,14,16,62,1,55,1.0,2,36,Rural,Software Engineer,33003,0 +67932,Female,49,High School,5,86,62,88,96,4.0,4,13,Semi-Urban,Software Engineer,111762,1 +67933,Male,47,Bachelors,3,63,23,56,54,9.0,7,49,Semi-Urban,HR Executive,133757,0 +67934,Other,34,High School,3,46,12,12,34,8.0,7,53,Urban,ML Engineer,112392,0 +67935,Male,24,Bachelors,11,56,8,22,57,9.0,6,58,Rural,ML Engineer,132924,0 +67936,Male,27,PhD,7,30,21,94,73,0.0,1,11,Urban,Software Engineer,49226,0 +67937,Male,39,Bachelors,18,86,11,87,51,9.0,5,13,Urban,HR Executive,38783,0 +67938,Male,22,Diploma,12,20,48,20,69,6.0,7,27,Urban,Data Analyst,120383,0 +67939,Male,29,Masters,1,92,28,2,46,2.0,1,86,Semi-Urban,ML Engineer,142631,0 +67940,Female,40,Bachelors,12,23,87,48,83,8.0,4,15,Rural,Data Analyst,84311,0 +67941,Female,56,Masters,4,43,16,26,26,0.0,0,23,Semi-Urban,Manager,31517,0 +67942,Female,21,Bachelors,14,25,86,70,26,1.0,5,25,Urban,Manager,22085,0 +67943,Male,51,Diploma,19,50,67,18,24,4.0,7,15,Urban,Manager,82861,0 +67944,Female,33,Diploma,3,69,25,61,10,7.0,1,42,Urban,ML Engineer,126257,0 +67945,Female,36,Bachelors,5,34,86,77,78,3.0,6,35,Urban,ML Engineer,47809,0 +67946,Female,48,Masters,14,84,9,35,86,5.0,4,92,Rural,Software Engineer,102260,0 +67947,Male,43,Masters,11,50,25,76,37,5.0,1,6,Urban,Software Engineer,123393,0 +67948,Male,45,PhD,2,36,22,35,98,3.0,3,95,Urban,Manager,70261,0 +67949,Male,33,Diploma,5,2,80,25,58,4.0,2,26,Rural,ML Engineer,28675,0 +67950,Male,46,Bachelors,3,41,76,3,92,4.0,6,91,Urban,ML Engineer,73783,0 +67951,Female,57,Bachelors,18,30,26,12,26,1.0,2,91,Urban,ML Engineer,108168,0 +67952,Female,48,Bachelors,8,31,53,96,74,9.0,3,78,Rural,Data Analyst,94112,1 +67953,Female,54,Masters,14,24,38,60,43,8.0,7,14,Semi-Urban,Manager,53993,0 +67954,Male,32,Bachelors,17,28,76,47,50,1.0,6,32,Urban,Software Engineer,137846,0 +67955,Male,28,Diploma,3,43,11,95,26,1.0,3,99,Urban,HR Executive,41379,1 +67956,Male,26,PhD,15,49,12,91,25,2.0,4,61,Urban,ML Engineer,43329,0 +67957,Female,30,PhD,16,74,61,84,61,2.0,5,73,Urban,ML Engineer,51998,1 +67958,Male,23,Bachelors,5,83,43,36,36,1.0,5,44,Urban,HR Executive,74742,0 +67959,Male,21,Masters,8,10,55,98,24,5.0,5,18,Semi-Urban,Software Engineer,31799,0 +67960,Male,59,Bachelors,10,7,90,61,52,6.0,6,33,Urban,Manager,108745,0 +67961,Male,42,Bachelors,13,2,76,6,83,2.0,5,10,Urban,Data Analyst,124087,0 +67962,Male,50,Masters,0,93,83,73,19,9.0,6,55,Semi-Urban,ML Engineer,45820,1 +67963,Other,34,Masters,7,33,53,87,78,6.0,3,85,Urban,Data Analyst,40373,1 +67964,Male,22,Masters,6,6,12,54,43,9.0,3,65,Semi-Urban,ML Engineer,38377,0 +67965,Female,54,Bachelors,9,33,57,93,34,8.0,0,60,Semi-Urban,Manager,107750,1 +67966,Other,54,Bachelors,5,96,84,83,31,1.0,4,37,Semi-Urban,Software Engineer,52634,1 +67967,Male,43,Masters,12,28,66,91,94,5.0,7,2,Semi-Urban,HR Executive,149279,0 +67968,Female,40,Bachelors,6,8,83,79,97,0.0,7,90,Semi-Urban,HR Executive,103948,1 +67969,Male,41,Diploma,1,59,45,87,50,2.0,2,19,Semi-Urban,Software Engineer,120318,0 +67970,Other,43,Bachelors,9,16,9,33,95,6.0,2,51,Urban,Manager,86256,0 +67971,Female,23,High School,7,94,4,96,54,5.0,7,17,Urban,ML Engineer,116130,0 +67972,Female,48,Diploma,16,86,85,31,80,8.0,0,63,Urban,Software Engineer,27215,1 +67973,Male,30,Bachelors,18,22,44,71,93,0.0,3,3,Rural,HR Executive,72394,0 +67974,Female,53,High School,10,73,69,17,57,9.0,7,81,Semi-Urban,Manager,110299,0 +67975,Female,36,Masters,13,33,84,77,76,9.0,6,59,Semi-Urban,Software Engineer,144920,1 +67976,Female,38,Bachelors,12,36,97,64,61,0.0,2,29,Semi-Urban,ML Engineer,56900,0 +67977,Male,58,PhD,3,7,97,0,44,5.0,0,2,Urban,Data Analyst,71599,0 +67978,Male,41,Bachelors,1,69,17,86,32,8.0,6,89,Urban,Data Analyst,81148,1 +67979,Male,49,Bachelors,4,86,44,48,14,3.0,2,34,Urban,HR Executive,81492,0 +67980,Female,56,High School,13,89,37,50,94,3.0,5,8,Rural,Manager,118442,0 +67981,Male,59,Bachelors,5,49,99,37,55,5.0,6,58,Urban,ML Engineer,31679,1 +67982,Other,57,Diploma,12,62,90,4,63,1.0,5,49,Urban,Manager,54919,0 +67983,Male,35,High School,17,17,93,63,36,7.0,5,88,Urban,HR Executive,134902,1 +67984,Male,43,Diploma,19,57,44,4,57,5.0,4,57,Semi-Urban,HR Executive,79239,0 +67985,Male,34,High School,14,36,46,20,13,6.0,5,6,Rural,Software Engineer,117031,0 +67986,Female,59,PhD,12,69,34,16,47,3.0,5,39,Urban,Manager,127203,0 +67987,Male,42,Bachelors,6,63,6,45,48,2.0,3,49,Urban,Software Engineer,60233,0 +67988,Male,49,PhD,4,3,57,85,97,0.0,1,90,Rural,Manager,64899,1 +67989,Male,43,Diploma,0,38,69,73,47,5.0,4,96,Urban,ML Engineer,48304,1 +67990,Female,50,Bachelors,12,77,33,56,84,8.0,7,46,Semi-Urban,ML Engineer,131692,0 +67991,Female,27,Diploma,11,75,16,60,37,6.0,6,54,Urban,Software Engineer,139375,0 +67992,Male,23,Bachelors,0,42,92,77,22,3.0,5,23,Urban,ML Engineer,31023,0 +67993,Male,24,Masters,11,17,33,36,1,7.0,0,5,Semi-Urban,ML Engineer,126919,0 +67994,Male,56,Masters,19,13,6,24,13,7.0,7,4,Urban,HR Executive,107398,0 +67995,Male,50,Bachelors,3,67,54,46,59,2.0,0,97,Urban,Data Analyst,85104,1 +67996,Female,59,Diploma,17,34,86,42,69,7.0,1,55,Urban,HR Executive,103887,0 +67997,Female,32,Masters,4,20,52,93,47,9.0,5,28,Urban,HR Executive,129607,0 +67998,Male,59,Diploma,5,47,56,34,22,8.0,3,49,Semi-Urban,Data Analyst,111936,0 +67999,Male,29,Bachelors,0,74,23,65,99,7.0,0,6,Urban,ML Engineer,119374,0 +68000,Male,53,Bachelors,1,73,79,27,67,3.0,5,1,Urban,HR Executive,32988,0 +68001,Female,55,High School,5,75,9,19,45,1.0,1,55,Urban,HR Executive,120625,0 +68002,Male,37,Masters,6,45,82,94,34,4.0,3,66,Urban,Software Engineer,29878,1 +68003,Male,22,Bachelors,17,94,87,73,97,8.0,6,67,Urban,ML Engineer,30546,1 +68004,Male,45,Masters,8,72,16,31,26,5.0,1,21,Semi-Urban,HR Executive,90275,0 +68005,Male,55,PhD,19,72,58,4,31,7.0,2,91,Urban,Data Analyst,80878,0 +68006,Female,46,Bachelors,7,3,54,48,6,1.0,5,92,Semi-Urban,ML Engineer,55682,0 +68007,Male,25,Bachelors,5,95,43,4,80,3.0,4,18,Semi-Urban,ML Engineer,129106,0 +68008,Female,24,Bachelors,5,24,62,52,13,8.0,3,76,Semi-Urban,Software Engineer,49241,0 +68009,Female,38,PhD,10,33,48,4,54,7.0,0,79,Semi-Urban,HR Executive,86798,0 +68010,Male,21,High School,19,95,2,36,21,4.0,1,36,Urban,ML Engineer,33175,0 +68011,Male,49,Masters,1,26,13,90,80,7.0,6,82,Urban,HR Executive,149464,0 +68012,Male,50,Bachelors,8,10,75,41,46,3.0,3,25,Urban,HR Executive,31978,0 +68013,Female,41,Masters,0,24,75,86,74,4.0,2,10,Urban,HR Executive,39227,0 +68014,Other,55,Diploma,13,98,84,96,81,8.0,2,28,Urban,ML Engineer,123578,1 +68015,Female,43,Bachelors,0,79,19,85,77,8.0,6,87,Semi-Urban,Software Engineer,65439,1 +68016,Female,55,Bachelors,18,93,99,41,51,6.0,0,86,Urban,HR Executive,104122,1 +68017,Female,46,High School,1,38,56,63,18,0.0,3,39,Rural,HR Executive,41880,0 +68018,Female,44,High School,16,3,69,17,17,5.0,3,99,Urban,Data Analyst,84035,0 +68019,Female,21,High School,2,58,91,60,26,6.0,1,39,Urban,ML Engineer,52304,1 +68020,Male,33,Diploma,0,53,32,41,7,0.0,1,77,Rural,Software Engineer,43890,0 +68021,Male,36,Bachelors,0,19,8,94,17,2.0,5,81,Urban,ML Engineer,34773,0 +68022,Female,40,Bachelors,14,47,19,40,32,5.0,1,52,Rural,ML Engineer,32167,0 +68023,Male,49,Bachelors,6,28,31,99,20,6.0,5,90,Rural,Software Engineer,130216,1 +68024,Female,50,Bachelors,6,9,36,78,83,5.0,5,96,Rural,Manager,118386,0 +68025,Male,41,Bachelors,7,19,64,36,98,4.0,1,22,Rural,Data Analyst,66380,0 +68026,Male,33,High School,19,84,61,89,0,0.0,3,58,Rural,Data Analyst,119282,1 +68027,Female,30,Bachelors,11,65,71,49,12,0.0,0,76,Semi-Urban,Software Engineer,127752,1 +68028,Male,30,Bachelors,1,82,87,59,52,6.0,7,31,Urban,Data Analyst,133288,1 +68029,Female,25,Diploma,18,54,61,29,34,0.0,7,56,Urban,Software Engineer,45730,0 +68030,Male,41,High School,7,54,27,19,90,0.0,2,62,Urban,Data Analyst,54539,0 +68031,Female,47,Bachelors,13,31,36,23,7,9.0,0,1,Urban,Manager,137826,0 +68032,Male,36,Masters,6,57,91,3,18,6.0,3,10,Urban,Software Engineer,79078,0 +68033,Male,34,Bachelors,8,93,80,11,27,8.0,3,72,Urban,ML Engineer,139999,1 +68034,Female,57,High School,9,83,76,66,48,0.0,5,11,Rural,HR Executive,79575,0 +68035,Male,26,Bachelors,12,4,98,16,85,5.0,7,89,Urban,ML Engineer,25185,0 +68036,Male,23,High School,8,7,96,93,25,5.0,3,69,Semi-Urban,Software Engineer,100666,1 +68037,Male,33,Masters,2,19,57,48,89,7.0,1,50,Semi-Urban,Manager,45293,0 +68038,Male,31,Bachelors,3,23,16,66,0,1.0,6,89,Urban,Software Engineer,148397,0 +68039,Other,33,Masters,5,60,5,88,93,7.0,6,28,Urban,HR Executive,60919,0 +68040,Male,52,Bachelors,18,4,6,6,11,6.0,5,59,Urban,ML Engineer,64277,0 +68041,Male,55,Masters,5,34,63,8,46,1.0,1,21,Urban,HR Executive,147313,0 +68042,Female,30,High School,13,1,95,8,72,7.0,1,91,Urban,Data Analyst,64698,0 +68043,Male,24,Bachelors,0,62,57,91,15,5.0,0,34,Urban,ML Engineer,130335,1 +68044,Male,38,Masters,19,99,16,4,74,6.0,0,64,Urban,ML Engineer,99879,0 +68045,Male,27,Bachelors,14,20,9,58,45,2.0,6,28,Urban,Manager,127064,0 +68046,Male,25,Diploma,5,13,87,39,27,5.0,3,75,Semi-Urban,Software Engineer,113640,0 +68047,Female,30,High School,0,91,13,92,1,9.0,2,1,Semi-Urban,HR Executive,134359,0 +68048,Female,47,PhD,7,89,97,18,8,4.0,7,75,Urban,Data Analyst,132970,1 +68049,Female,38,Diploma,10,77,67,61,28,0.0,2,4,Urban,ML Engineer,130336,0 +68050,Female,33,Diploma,4,20,93,88,26,5.0,4,59,Semi-Urban,ML Engineer,49686,1 +68051,Female,48,Bachelors,6,60,88,74,18,1.0,3,83,Semi-Urban,ML Engineer,146561,1 +68052,Female,40,Masters,8,8,23,69,13,0.0,4,25,Semi-Urban,Manager,71731,0 +68053,Other,38,Masters,6,47,38,6,76,6.0,5,0,Urban,Data Analyst,26459,0 +68054,Male,58,Masters,14,58,54,55,84,9.0,0,96,Urban,HR Executive,96300,1 +68055,Male,34,Masters,14,31,73,14,24,5.0,1,27,Urban,Manager,27698,0 +68056,Male,56,Masters,19,44,50,47,78,1.0,5,59,Urban,ML Engineer,140771,0 +68057,Male,59,Diploma,15,98,41,71,55,5.0,1,96,Semi-Urban,Manager,133843,1 +68058,Male,51,Diploma,17,58,62,80,19,4.0,5,81,Rural,HR Executive,127403,1 +68059,Female,51,Masters,14,98,61,32,64,6.0,2,38,Urban,Software Engineer,102707,0 +68060,Male,23,Bachelors,13,59,6,97,17,9.0,7,16,Rural,Data Analyst,141888,0 +68061,Male,38,Masters,5,14,33,45,21,3.0,0,31,Urban,Data Analyst,92583,0 +68062,Male,43,Bachelors,18,34,21,51,58,8.0,1,24,Semi-Urban,Software Engineer,44463,0 +68063,Male,45,Masters,15,81,92,1,23,2.0,6,9,Urban,HR Executive,52600,0 +68064,Male,47,Diploma,7,70,61,13,29,3.0,5,9,Urban,HR Executive,41762,0 +68065,Male,55,Bachelors,1,34,17,4,19,4.0,4,62,Urban,ML Engineer,71843,0 +68066,Male,32,Diploma,12,90,46,49,35,7.0,2,21,Semi-Urban,Manager,74335,0 +68067,Male,24,Masters,13,74,28,7,55,1.0,1,18,Urban,HR Executive,130505,0 +68068,Female,41,Masters,19,72,41,39,52,8.0,2,99,Rural,ML Engineer,44902,1 +68069,Female,42,Bachelors,3,66,59,46,54,1.0,1,27,Urban,HR Executive,117480,0 +68070,Male,30,Bachelors,16,38,54,10,7,5.0,7,44,Semi-Urban,ML Engineer,102324,0 +68071,Female,40,Diploma,7,6,60,81,1,5.0,3,66,Urban,Software Engineer,61626,0 +68072,Other,32,Masters,0,36,43,1,19,1.0,3,74,Urban,Data Analyst,89716,0 +68073,Male,22,Bachelors,18,69,41,7,51,6.0,6,64,Semi-Urban,Software Engineer,59254,0 +68074,Male,47,High School,1,86,68,70,99,0.0,7,49,Urban,Software Engineer,43115,1 +68075,Other,41,Bachelors,12,2,59,90,27,8.0,4,94,Rural,Data Analyst,66436,1 +68076,Male,46,Masters,13,86,41,37,85,2.0,1,25,Semi-Urban,Software Engineer,22408,0 +68077,Male,49,Bachelors,3,64,58,38,92,5.0,4,27,Urban,HR Executive,100667,0 +68078,Male,36,Bachelors,12,93,89,21,59,8.0,5,4,Urban,Software Engineer,100711,0 +68079,Male,55,Bachelors,3,1,34,30,20,4.0,6,13,Urban,ML Engineer,51704,0 +68080,Male,27,High School,13,39,79,13,97,0.0,5,99,Urban,ML Engineer,107308,0 +68081,Male,30,Bachelors,3,19,93,34,0,1.0,1,83,Semi-Urban,HR Executive,101079,0 +68082,Male,24,High School,5,59,64,35,91,4.0,0,31,Semi-Urban,Data Analyst,136566,0 +68083,Female,30,Diploma,12,29,76,21,97,1.0,3,22,Urban,Manager,64426,0 +68084,Female,57,High School,8,27,93,94,59,6.0,0,26,Rural,Data Analyst,69745,0 +68085,Female,33,Masters,5,68,12,64,9,5.0,2,34,Rural,Software Engineer,52259,0 +68086,Male,40,Bachelors,9,85,65,5,8,4.0,0,46,Semi-Urban,Manager,29487,0 +68087,Male,27,Bachelors,2,94,54,94,98,0.0,2,57,Urban,Data Analyst,42220,1 +68088,Male,22,Masters,10,10,16,78,2,6.0,1,62,Semi-Urban,Manager,147909,0 +68089,Male,39,Bachelors,14,98,77,97,48,7.0,2,33,Urban,ML Engineer,20125,1 +68090,Male,28,Bachelors,9,3,11,69,82,3.0,7,77,Semi-Urban,ML Engineer,59043,0 +68091,Male,55,Masters,11,56,8,65,37,4.0,1,76,Urban,HR Executive,97123,0 +68092,Male,45,Bachelors,10,55,10,16,77,6.0,7,75,Urban,Manager,146812,0 +68093,Male,43,Bachelors,12,10,86,3,22,1.0,2,2,Urban,Software Engineer,82593,0 +68094,Female,50,Masters,12,43,56,0,14,3.0,7,89,Urban,Software Engineer,54229,0 +68095,Male,28,Diploma,6,61,97,81,6,6.0,2,90,Urban,Manager,75345,1 +68096,Female,37,Masters,6,71,34,50,97,9.0,7,36,Urban,Software Engineer,56883,0 +68097,Female,38,Bachelors,14,42,86,4,86,6.0,6,69,Rural,Data Analyst,108702,0 +68098,Male,51,Diploma,1,19,45,61,95,9.0,7,81,Semi-Urban,Data Analyst,22782,0 +68099,Female,36,Bachelors,13,81,94,75,89,6.0,2,90,Urban,Software Engineer,81399,1 +68100,Female,36,Bachelors,0,82,75,78,68,6.0,1,94,Semi-Urban,ML Engineer,43328,1 +68101,Male,56,Bachelors,13,68,81,44,24,3.0,0,82,Semi-Urban,HR Executive,128933,1 +68102,Female,38,Bachelors,17,74,44,29,52,1.0,2,29,Urban,Manager,60107,0 +68103,Female,57,Bachelors,18,18,30,75,49,1.0,7,6,Rural,HR Executive,73296,0 +68104,Male,52,High School,7,18,5,77,25,0.0,6,14,Urban,Manager,21368,0 +68105,Female,54,PhD,19,84,4,74,17,6.0,6,45,Urban,Manager,114842,0 +68106,Male,57,Bachelors,10,55,55,25,99,7.0,2,75,Semi-Urban,Data Analyst,49494,0 +68107,Female,55,Diploma,9,17,77,59,90,6.0,1,73,Semi-Urban,Manager,21549,0 +68108,Female,32,Masters,7,84,26,4,21,0.0,4,11,Urban,ML Engineer,21895,0 +68109,Male,25,PhD,15,52,86,26,84,4.0,6,10,Semi-Urban,HR Executive,106995,0 +68110,Female,51,Bachelors,1,76,45,33,43,3.0,7,36,Urban,Manager,101420,0 +68111,Female,43,High School,8,13,71,45,29,7.0,0,14,Semi-Urban,Software Engineer,53840,0 +68112,Female,50,Masters,4,97,64,26,14,8.0,3,59,Semi-Urban,Data Analyst,29085,1 +68113,Female,57,Bachelors,8,88,96,39,15,6.0,2,61,Rural,Software Engineer,89204,1 +68114,Female,50,Bachelors,6,49,96,27,15,0.0,6,55,Urban,Data Analyst,80383,0 +68115,Other,53,Diploma,13,14,10,68,73,3.0,7,7,Rural,Manager,40110,0 +68116,Female,37,Diploma,8,89,36,5,74,4.0,4,74,Urban,Manager,78024,0 +68117,Female,57,Bachelors,14,64,52,0,25,0.0,5,76,Urban,Software Engineer,95962,0 +68118,Male,24,Bachelors,19,33,75,46,39,8.0,5,12,Rural,Software Engineer,44942,0 +68119,Male,27,Bachelors,2,75,73,52,99,6.0,2,0,Urban,HR Executive,98416,0 +68120,Male,21,High School,19,26,72,7,93,5.0,2,98,Semi-Urban,ML Engineer,99639,0 +68121,Male,56,High School,8,94,96,79,73,4.0,3,21,Urban,Data Analyst,59853,1 +68122,Other,31,Diploma,4,71,3,68,10,5.0,1,36,Urban,ML Engineer,79199,0 +68123,Male,46,Diploma,18,10,2,32,79,2.0,3,22,Urban,Data Analyst,65789,0 +68124,Male,27,Diploma,15,13,79,40,26,5.0,6,27,Semi-Urban,Data Analyst,39392,0 +68125,Male,29,Bachelors,1,0,12,56,93,6.0,4,42,Urban,ML Engineer,122978,0 +68126,Female,25,Masters,1,83,20,57,97,5.0,1,70,Urban,Manager,52444,0 +68127,Male,39,Diploma,0,26,34,20,71,3.0,6,38,Semi-Urban,Manager,66181,0 +68128,Male,35,Bachelors,11,24,19,91,70,4.0,6,58,Urban,ML Engineer,39288,0 +68129,Male,43,Bachelors,8,62,55,18,37,8.0,7,49,Rural,Data Analyst,57063,0 +68130,Male,51,High School,3,70,59,86,88,6.0,4,16,Rural,ML Engineer,54745,0 +68131,Male,54,High School,1,28,69,34,9,2.0,1,38,Urban,HR Executive,120552,0 +68132,Female,40,Diploma,5,18,36,15,84,9.0,3,77,Urban,Manager,67073,0 +68133,Male,40,High School,4,38,46,49,58,8.0,6,68,Rural,Software Engineer,96343,0 +68134,Other,37,Bachelors,7,41,39,78,64,0.0,3,41,Urban,ML Engineer,37692,0 +68135,Male,43,Bachelors,17,16,14,68,78,1.0,1,84,Semi-Urban,HR Executive,146399,0 +68136,Male,30,Masters,6,65,66,9,15,9.0,2,9,Semi-Urban,ML Engineer,78329,0 +68137,Female,37,Masters,0,43,72,26,94,8.0,3,50,Urban,Data Analyst,70689,0 +68138,Male,43,Bachelors,17,76,29,10,34,3.0,6,44,Semi-Urban,ML Engineer,77746,0 +68139,Male,56,Bachelors,3,77,68,24,30,9.0,5,18,Semi-Urban,Software Engineer,82383,0 +68140,Male,29,Bachelors,5,59,75,95,95,3.0,3,83,Urban,Software Engineer,142951,1 +68141,Female,41,Diploma,14,25,97,39,61,2.0,2,13,Rural,ML Engineer,49699,0 +68142,Male,22,Bachelors,0,76,3,0,48,4.0,5,66,Urban,Manager,73649,0 +68143,Female,25,Diploma,10,56,99,66,54,0.0,5,7,Semi-Urban,HR Executive,81033,0 +68144,Male,32,Bachelors,4,79,69,30,58,9.0,5,5,Rural,Software Engineer,21375,0 +68145,Male,37,Diploma,2,14,36,81,98,3.0,1,30,Urban,HR Executive,78362,0 +68146,Female,48,Diploma,12,19,67,19,25,9.0,5,62,Rural,Manager,92204,0 +68147,Female,30,Bachelors,17,93,22,16,70,6.0,2,33,Semi-Urban,HR Executive,68235,0 +68148,Female,29,Masters,5,16,13,32,9,4.0,0,10,Semi-Urban,HR Executive,134348,0 +68149,Female,26,Bachelors,9,61,2,34,4,2.0,2,28,Urban,Data Analyst,63995,0 +68150,Male,34,High School,3,56,73,93,84,5.0,2,88,Rural,ML Engineer,63461,1 +68151,Female,56,Masters,18,16,53,27,94,6.0,3,26,Urban,HR Executive,139287,0 +68152,Male,47,Diploma,14,32,69,18,46,3.0,3,20,Semi-Urban,HR Executive,86014,0 +68153,Male,29,Bachelors,14,76,46,20,59,4.0,4,23,Urban,Data Analyst,85584,0 +68154,Male,52,Bachelors,5,67,37,4,59,0.0,0,77,Semi-Urban,Manager,83845,0 +68155,Female,26,Masters,15,49,20,9,55,9.0,4,99,Urban,ML Engineer,110965,0 +68156,Female,52,Masters,9,59,68,17,44,3.0,5,8,Urban,Software Engineer,83814,0 +68157,Male,32,Bachelors,11,53,82,29,82,3.0,0,91,Urban,Software Engineer,77717,1 +68158,Male,34,Diploma,14,94,16,7,12,9.0,0,91,Semi-Urban,Manager,28454,0 +68159,Male,35,High School,7,92,22,48,7,6.0,3,72,Urban,Data Analyst,105228,0 +68160,Male,30,High School,1,48,8,48,34,3.0,6,28,Urban,HR Executive,109733,0 +68161,Male,46,PhD,9,20,72,37,31,2.0,2,78,Urban,Data Analyst,27396,0 +68162,Male,21,Bachelors,18,86,68,40,81,4.0,3,82,Semi-Urban,Data Analyst,97419,1 +68163,Female,56,Masters,5,76,1,44,80,6.0,3,45,Urban,ML Engineer,59462,0 +68164,Female,40,Bachelors,9,34,32,26,10,0.0,2,95,Urban,Data Analyst,135245,0 +68165,Male,36,Bachelors,14,12,69,90,88,0.0,2,38,Urban,Data Analyst,116504,0 +68166,Female,35,High School,11,24,59,51,30,2.0,2,39,Urban,Data Analyst,141521,0 +68167,Male,22,Masters,4,94,6,73,33,6.0,3,72,Urban,ML Engineer,57368,1 +68168,Male,54,Masters,14,83,10,48,58,1.0,3,66,Urban,HR Executive,87364,0 +68169,Male,22,Masters,0,58,29,81,68,2.0,6,23,Urban,Software Engineer,26067,0 +68170,Male,49,High School,10,73,24,35,82,6.0,0,13,Rural,HR Executive,46519,0 +68171,Other,59,Diploma,3,56,44,88,40,5.0,4,26,Semi-Urban,Manager,140698,0 +68172,Male,30,Bachelors,4,69,86,71,26,5.0,7,22,Urban,Manager,33981,1 +68173,Female,51,Masters,11,83,99,56,38,5.0,0,17,Urban,ML Engineer,96575,1 +68174,Female,34,Bachelors,1,87,20,6,23,8.0,0,58,Semi-Urban,Data Analyst,104821,0 +68175,Male,49,Bachelors,12,98,39,10,58,6.0,6,37,Urban,ML Engineer,46138,0 +68176,Male,25,Bachelors,4,67,56,60,52,1.0,4,26,Semi-Urban,Software Engineer,136679,0 +68177,Male,53,PhD,6,86,23,38,95,8.0,1,48,Semi-Urban,Manager,30800,0 +68178,Male,33,Masters,8,94,49,77,23,4.0,1,40,Semi-Urban,Manager,56711,1 +68179,Other,28,Bachelors,9,66,57,18,12,6.0,1,61,Semi-Urban,Software Engineer,95715,0 +68180,Male,29,Bachelors,16,13,32,99,74,0.0,2,16,Urban,ML Engineer,68874,0 +68181,Other,49,Bachelors,1,36,9,58,53,2.0,5,83,Urban,Software Engineer,76382,0 +68182,Male,50,High School,15,1,77,66,41,3.0,0,21,Semi-Urban,Manager,71475,0 +68183,Male,33,Bachelors,6,16,82,7,32,8.0,6,82,Urban,Software Engineer,132973,0 +68184,Male,25,Bachelors,18,78,47,11,20,8.0,3,28,Semi-Urban,Manager,145193,0 +68185,Female,45,High School,19,87,58,94,51,1.0,7,84,Urban,HR Executive,73126,1 +68186,Male,55,Masters,9,49,74,62,8,0.0,0,3,Semi-Urban,Data Analyst,65831,0 +68187,Male,49,Diploma,0,47,6,56,38,8.0,6,15,Urban,ML Engineer,33370,0 +68188,Male,33,High School,11,79,27,55,90,8.0,6,80,Semi-Urban,Manager,51977,1 +68189,Male,47,Bachelors,7,77,3,74,21,3.0,6,92,Urban,Manager,76277,1 +68190,Male,42,Bachelors,12,70,75,65,32,0.0,4,9,Rural,Data Analyst,52966,0 +68191,Female,40,Masters,0,40,4,58,46,0.0,7,58,Urban,Manager,106999,0 +68192,Male,32,Bachelors,14,18,64,75,51,3.0,2,65,Urban,HR Executive,21193,0 +68193,Female,22,Bachelors,5,39,66,41,65,8.0,5,0,Urban,Software Engineer,126466,0 +68194,Female,53,High School,7,48,71,39,62,6.0,5,1,Semi-Urban,HR Executive,27368,0 +68195,Male,34,Bachelors,10,55,13,51,2,9.0,0,99,Urban,Data Analyst,105063,0 +68196,Male,31,Masters,0,93,70,59,28,3.0,5,50,Urban,Data Analyst,67767,1 +68197,Female,48,Masters,7,29,23,46,33,1.0,1,86,Rural,HR Executive,67106,0 +68198,Male,33,PhD,9,39,97,65,41,8.0,6,72,Urban,Software Engineer,70433,1 +68199,Male,29,Bachelors,13,22,25,95,97,7.0,7,10,Rural,ML Engineer,147158,0 +68200,Male,48,Diploma,11,3,27,14,29,7.0,7,96,Urban,Manager,146115,0 +68201,Male,32,Bachelors,1,64,47,23,58,9.0,1,73,Semi-Urban,ML Engineer,141320,0 +68202,Male,49,Bachelors,15,49,35,19,63,1.0,5,59,Rural,Software Engineer,117706,0 +68203,Male,34,Bachelors,14,33,69,75,27,7.0,4,92,Urban,HR Executive,115017,1 +68204,Male,58,Bachelors,18,30,9,82,9,7.0,6,8,Semi-Urban,Manager,63552,0 +68205,Male,43,Bachelors,3,91,72,83,88,6.0,6,74,Urban,HR Executive,30972,1 +68206,Male,55,Diploma,6,59,54,70,49,5.0,5,39,Urban,Data Analyst,55996,0 +68207,Male,41,PhD,5,69,88,82,47,9.0,0,5,Semi-Urban,Data Analyst,45317,1 +68208,Female,49,Masters,2,8,92,52,78,7.0,0,58,Rural,Manager,26848,0 +68209,Male,51,PhD,12,46,34,25,10,1.0,3,78,Urban,HR Executive,24779,0 +68210,Male,58,PhD,7,2,70,74,20,5.0,4,80,Urban,Manager,86960,0 +68211,Female,51,Bachelors,10,1,53,98,85,8.0,6,27,Urban,Software Engineer,71842,0 +68212,Male,30,Bachelors,3,71,6,57,56,7.0,1,50,Urban,Software Engineer,57865,0 +68213,Female,25,Bachelors,4,61,92,21,88,4.0,6,58,Semi-Urban,ML Engineer,106467,0 +68214,Female,39,Bachelors,17,1,0,51,78,8.0,0,73,Urban,Software Engineer,43622,0 +68215,Male,44,High School,7,56,97,52,32,0.0,4,53,Urban,Software Engineer,93034,1 +68216,Female,56,Bachelors,4,26,1,97,19,6.0,2,11,Semi-Urban,Data Analyst,111254,0 +68217,Male,27,Bachelors,11,16,24,93,76,7.0,3,31,Urban,HR Executive,119935,0 +68218,Female,55,Diploma,10,8,80,40,98,5.0,1,12,Semi-Urban,Manager,72716,0 +68219,Male,22,Bachelors,1,28,6,72,92,0.0,3,73,Rural,Data Analyst,83292,0 +68220,Male,50,Masters,5,42,22,61,43,7.0,6,85,Rural,Data Analyst,101592,0 +68221,Other,59,Bachelors,15,67,59,56,86,1.0,5,78,Rural,Data Analyst,24479,1 +68222,Female,45,Bachelors,7,3,69,77,77,6.0,3,73,Urban,Software Engineer,27544,0 +68223,Male,26,High School,11,12,26,55,36,5.0,0,2,Urban,ML Engineer,109041,0 +68224,Male,50,Diploma,13,86,50,5,88,7.0,4,69,Urban,Manager,131118,0 +68225,Female,52,Masters,5,75,82,19,52,8.0,7,54,Urban,Software Engineer,114054,0 +68226,Male,58,Bachelors,12,2,95,18,65,4.0,2,83,Semi-Urban,ML Engineer,31283,0 +68227,Female,31,Diploma,17,19,13,98,75,2.0,3,39,Urban,HR Executive,137295,0 +68228,Female,49,Bachelors,6,14,39,39,11,8.0,0,56,Semi-Urban,HR Executive,105516,0 +68229,Male,53,Bachelors,15,76,85,48,47,4.0,4,24,Urban,HR Executive,77809,0 +68230,Female,22,High School,8,11,26,26,65,5.0,3,71,Semi-Urban,Data Analyst,79711,0 +68231,Female,33,Bachelors,11,4,81,12,16,4.0,0,30,Urban,ML Engineer,76084,0 +68232,Male,26,Bachelors,1,80,21,95,79,6.0,3,85,Urban,Data Analyst,42050,1 +68233,Male,40,Masters,0,75,93,28,16,7.0,1,3,Semi-Urban,HR Executive,34569,0 +68234,Male,55,Diploma,7,24,57,83,85,8.0,4,9,Urban,ML Engineer,82063,0 +68235,Male,31,Bachelors,3,59,80,98,93,2.0,0,74,Urban,Data Analyst,52092,1 +68236,Other,38,Bachelors,14,92,16,59,46,3.0,7,22,Rural,Data Analyst,65612,0 +68237,Male,32,PhD,19,94,4,41,71,0.0,5,63,Semi-Urban,ML Engineer,43618,0 +68238,Male,30,PhD,2,25,4,88,95,9.0,3,40,Semi-Urban,Manager,59540,0 +68239,Male,32,Bachelors,12,56,36,44,24,5.0,4,60,Urban,Manager,124257,0 +68240,Male,34,Diploma,2,39,39,23,36,8.0,6,29,Semi-Urban,Manager,81922,0 +68241,Male,49,Masters,14,72,52,18,78,1.0,1,18,Urban,HR Executive,27797,0 +68242,Female,29,Masters,13,52,1,91,78,0.0,2,34,Urban,Data Analyst,52356,0 +68243,Male,37,Bachelors,6,47,7,94,1,6.0,4,35,Semi-Urban,HR Executive,52370,0 +68244,Male,23,High School,3,37,44,23,44,5.0,4,59,Urban,Data Analyst,142914,0 +68245,Female,56,Bachelors,2,54,73,40,18,4.0,6,30,Urban,HR Executive,64428,0 +68246,Female,48,High School,16,96,76,8,61,6.0,7,27,Semi-Urban,Software Engineer,45795,0 +68247,Male,36,Bachelors,18,34,22,83,16,8.0,6,8,Urban,Data Analyst,27321,0 +68248,Male,25,Masters,12,81,60,56,94,1.0,7,97,Rural,Manager,78485,1 +68249,Male,27,Diploma,5,98,40,34,21,5.0,2,44,Urban,HR Executive,99912,0 +68250,Male,52,PhD,9,20,29,73,53,7.0,4,90,Urban,Data Analyst,139594,0 +68251,Female,41,Masters,6,67,14,56,87,1.0,7,91,Urban,ML Engineer,57284,0 +68252,Female,23,Masters,14,32,54,91,99,2.0,0,6,Urban,ML Engineer,82270,0 +68253,Male,21,PhD,9,46,1,74,88,8.0,6,52,Semi-Urban,HR Executive,32417,0 +68254,Male,43,Masters,17,5,36,85,48,4.0,2,84,Urban,Manager,116010,0 +68255,Male,21,PhD,8,97,74,40,92,8.0,6,25,Urban,HR Executive,72718,1 +68256,Male,53,PhD,11,72,20,32,98,1.0,3,2,Semi-Urban,Software Engineer,109936,0 +68257,Female,33,Diploma,3,83,1,91,96,2.0,2,51,Urban,Software Engineer,36586,0 +68258,Female,23,Bachelors,18,2,35,30,2,3.0,2,34,Urban,ML Engineer,85255,0 +68259,Male,55,Bachelors,7,0,58,86,58,2.0,3,65,Urban,Manager,55672,0 +68260,Male,28,Diploma,16,14,94,74,43,8.0,4,91,Urban,ML Engineer,64033,1 +68261,Female,51,High School,7,76,22,18,75,5.0,7,25,Urban,Manager,70706,0 +68262,Male,54,Masters,13,74,0,86,16,0.0,3,18,Rural,Data Analyst,141774,0 +68263,Female,42,Bachelors,3,22,65,28,63,4.0,6,49,Urban,Manager,141846,0 +68264,Male,22,PhD,11,98,76,37,84,6.0,4,34,Urban,Manager,118254,1 +68265,Male,35,PhD,18,86,6,44,3,2.0,4,65,Rural,Data Analyst,33726,0 +68266,Female,56,Diploma,19,15,71,32,62,9.0,3,93,Urban,Software Engineer,55913,0 +68267,Male,45,Diploma,4,46,19,66,51,4.0,5,45,Semi-Urban,Software Engineer,52495,0 +68268,Male,47,Bachelors,4,99,43,38,80,6.0,5,91,Urban,Software Engineer,147297,1 +68269,Male,44,Bachelors,17,77,42,41,44,0.0,0,10,Semi-Urban,Data Analyst,95999,0 +68270,Male,22,Masters,9,3,13,72,55,0.0,2,62,Urban,Software Engineer,104192,0 +68271,Female,55,Masters,3,16,61,46,26,9.0,1,19,Semi-Urban,HR Executive,89917,0 +68272,Male,39,Bachelors,17,97,85,29,87,6.0,3,70,Semi-Urban,Software Engineer,25149,1 +68273,Male,32,Bachelors,19,49,30,8,78,0.0,0,30,Semi-Urban,Manager,143195,0 +68274,Male,55,Bachelors,15,2,30,56,30,1.0,5,8,Urban,HR Executive,115139,0 +68275,Female,34,Diploma,15,76,23,22,4,4.0,0,5,Semi-Urban,Manager,147802,0 +68276,Male,57,Bachelors,14,82,21,94,59,9.0,7,25,Urban,HR Executive,80741,0 +68277,Male,35,Bachelors,9,62,15,57,37,4.0,6,68,Semi-Urban,ML Engineer,22901,0 +68278,Male,56,Bachelors,9,8,81,32,70,0.0,1,19,Rural,ML Engineer,20390,0 +68279,Male,41,PhD,6,77,12,0,2,3.0,7,48,Urban,Software Engineer,55063,0 +68280,Male,41,Bachelors,3,18,68,25,19,2.0,2,60,Urban,Data Analyst,144837,0 +68281,Male,39,High School,12,50,5,7,84,7.0,6,13,Semi-Urban,HR Executive,33469,0 +68282,Other,48,Bachelors,11,18,78,37,87,4.0,7,35,Urban,Software Engineer,89189,0 +68283,Male,39,Bachelors,5,77,97,74,12,8.0,5,1,Semi-Urban,Software Engineer,58964,1 +68284,Male,50,Masters,6,94,48,80,74,6.0,5,74,Urban,ML Engineer,62147,1 +68285,Male,40,Bachelors,3,59,74,88,33,9.0,6,32,Urban,HR Executive,48748,1 +68286,Female,45,Bachelors,9,42,45,58,18,1.0,1,29,Urban,Data Analyst,35865,0 +68287,Female,22,Masters,3,66,16,84,51,2.0,7,52,Urban,ML Engineer,131714,0 +68288,Other,58,Masters,2,52,22,91,91,7.0,5,37,Urban,Software Engineer,28073,0 +68289,Female,36,High School,5,30,30,15,19,3.0,2,54,Urban,HR Executive,65652,0 +68290,Male,36,Bachelors,10,76,38,2,84,1.0,3,36,Urban,ML Engineer,82413,0 +68291,Male,51,High School,13,96,5,81,4,6.0,4,11,Urban,Data Analyst,43337,0 +68292,Female,28,Bachelors,1,73,41,81,79,7.0,7,5,Urban,ML Engineer,55860,0 +68293,Female,24,Masters,0,41,22,28,25,1.0,7,45,Urban,Manager,137901,0 +68294,Male,26,Diploma,6,75,8,1,62,2.0,1,32,Urban,Manager,24566,0 +68295,Male,48,PhD,13,93,43,95,20,9.0,3,40,Rural,HR Executive,38423,1 +68296,Other,39,Bachelors,4,98,26,74,26,0.0,1,87,Urban,Manager,46485,1 +68297,Female,28,Bachelors,2,47,37,94,36,2.0,3,6,Urban,Manager,106169,0 +68298,Male,36,Bachelors,16,83,81,44,66,8.0,2,90,Urban,Data Analyst,87709,1 +68299,Male,55,High School,9,53,49,79,6,8.0,4,85,Urban,HR Executive,91811,1 +68300,Female,54,High School,2,51,82,4,55,4.0,2,21,Urban,HR Executive,121989,0 +68301,Male,35,Bachelors,14,61,16,1,21,8.0,3,51,Urban,HR Executive,79649,0 +68302,Female,38,Diploma,13,43,66,16,91,0.0,0,63,Rural,Software Engineer,140230,0 +68303,Male,34,Diploma,18,71,83,32,17,4.0,7,96,Rural,HR Executive,20296,1 +68304,Female,25,Diploma,5,36,52,15,48,1.0,2,31,Rural,HR Executive,20314,0 +68305,Male,32,High School,13,1,66,69,69,7.0,5,56,Urban,Data Analyst,131516,0 +68306,Female,28,Diploma,13,84,63,22,44,9.0,4,1,Urban,Software Engineer,143731,0 +68307,Male,32,Bachelors,7,39,31,82,75,4.0,7,59,Urban,HR Executive,52795,0 +68308,Male,56,High School,7,86,40,45,91,0.0,0,18,Urban,Data Analyst,37842,0 +68309,Male,48,High School,12,67,2,80,39,5.0,4,19,Urban,Manager,61646,0 +68310,Female,50,High School,19,32,53,76,26,8.0,1,46,Urban,Data Analyst,26839,0 +68311,Male,40,Diploma,14,34,84,75,95,5.0,6,16,Rural,Software Engineer,93502,0 +68312,Female,48,Masters,14,37,7,33,8,6.0,3,40,Urban,Manager,57111,0 +68313,Male,50,PhD,12,3,80,31,96,7.0,0,30,Urban,ML Engineer,83508,0 +68314,Female,48,Masters,15,1,1,49,60,9.0,2,62,Urban,Software Engineer,21908,0 +68315,Male,37,Diploma,13,81,14,99,78,2.0,2,53,Rural,Data Analyst,25189,1 +68316,Female,22,Diploma,2,98,92,21,68,5.0,6,88,Urban,ML Engineer,147090,1 +68317,Female,36,Bachelors,3,21,53,76,59,0.0,4,7,Urban,ML Engineer,112201,0 +68318,Male,28,Bachelors,10,53,85,13,56,7.0,5,67,Urban,Software Engineer,132780,0 +68319,Male,40,Bachelors,18,55,24,70,61,2.0,2,63,Rural,HR Executive,147462,0 +68320,Other,47,Bachelors,2,58,20,15,28,1.0,4,61,Semi-Urban,Software Engineer,26791,0 +68321,Male,29,Masters,3,89,25,11,12,6.0,3,26,Urban,Manager,62708,0 +68322,Female,42,Masters,19,42,58,67,51,5.0,7,70,Urban,HR Executive,66308,0 +68323,Male,43,Masters,17,68,66,88,59,6.0,0,42,Urban,Data Analyst,40329,1 +68324,Female,22,High School,18,31,35,29,93,2.0,7,30,Semi-Urban,Software Engineer,63512,0 +68325,Female,55,Bachelors,7,11,12,77,59,1.0,7,46,Semi-Urban,HR Executive,134156,0 +68326,Female,42,Bachelors,4,76,73,83,10,9.0,2,69,Urban,Software Engineer,69433,1 +68327,Female,51,Masters,8,82,91,87,55,1.0,2,42,Urban,HR Executive,56408,1 +68328,Male,42,Bachelors,0,38,35,43,48,6.0,7,0,Semi-Urban,Software Engineer,29531,0 +68329,Male,54,Masters,19,29,86,56,63,6.0,5,95,Semi-Urban,Data Analyst,53019,1 +68330,Male,36,Diploma,19,58,22,34,88,0.0,1,40,Urban,Data Analyst,21668,0 +68331,Male,32,Bachelors,18,29,1,2,11,4.0,4,7,Urban,Manager,77937,0 +68332,Male,59,Masters,14,93,38,2,68,9.0,5,7,Urban,ML Engineer,106028,0 +68333,Male,56,Masters,5,51,96,33,54,5.0,7,45,Semi-Urban,Software Engineer,82667,0 +68334,Female,26,High School,7,43,74,90,23,6.0,6,13,Urban,ML Engineer,89056,0 +68335,Male,48,Masters,18,66,44,85,87,5.0,5,88,Urban,ML Engineer,108022,1 +68336,Male,22,Diploma,1,13,10,53,89,4.0,0,49,Urban,Data Analyst,131386,0 +68337,Male,28,Bachelors,6,25,84,70,19,3.0,2,78,Semi-Urban,Manager,26083,1 +68338,Female,55,Bachelors,11,99,20,39,71,7.0,0,30,Semi-Urban,ML Engineer,55733,0 +68339,Male,42,Masters,12,49,76,74,43,7.0,6,33,Urban,Software Engineer,44544,0 +68340,Male,41,Diploma,13,21,8,1,78,6.0,2,83,Urban,ML Engineer,79418,0 +68341,Male,54,Bachelors,5,55,86,15,87,2.0,1,54,Urban,Manager,34244,0 +68342,Male,54,Bachelors,9,1,93,0,20,8.0,2,85,Urban,Software Engineer,79768,0 +68343,Female,49,Masters,9,33,75,63,88,2.0,4,62,Urban,Manager,48999,0 +68344,Female,53,High School,15,59,34,97,56,0.0,7,3,Urban,Manager,110550,0 +68345,Female,53,High School,13,82,45,18,63,3.0,6,66,Rural,HR Executive,107480,0 +68346,Female,34,Bachelors,17,99,84,17,43,2.0,0,54,Semi-Urban,ML Engineer,46661,1 +68347,Female,37,Bachelors,3,11,43,21,73,6.0,2,64,Urban,Manager,49880,0 +68348,Male,32,Bachelors,8,18,64,48,10,5.0,6,42,Urban,HR Executive,140311,0 +68349,Male,46,Bachelors,5,59,86,62,25,4.0,1,43,Urban,Manager,65811,1 +68350,Male,51,Diploma,9,67,73,24,17,3.0,0,91,Urban,Manager,27447,1 +68351,Male,25,Diploma,11,10,6,22,27,5.0,2,22,Urban,HR Executive,65715,0 +68352,Female,28,High School,12,97,3,78,67,1.0,1,12,Urban,ML Engineer,129219,0 +68353,Male,46,High School,12,31,49,16,24,9.0,0,41,Rural,ML Engineer,60740,0 +68354,Female,23,Diploma,6,62,4,28,30,1.0,4,18,Urban,Manager,139020,0 +68355,Male,36,PhD,8,22,14,62,94,2.0,4,10,Rural,HR Executive,76873,0 +68356,Male,45,Diploma,8,12,15,7,68,1.0,1,9,Semi-Urban,Software Engineer,109494,0 +68357,Female,45,High School,8,19,6,35,38,0.0,2,65,Urban,Manager,84190,0 +68358,Female,51,Bachelors,14,27,93,79,55,6.0,3,14,Urban,Data Analyst,81025,0 +68359,Male,31,Masters,8,30,33,73,83,4.0,3,83,Semi-Urban,Software Engineer,107979,0 +68360,Male,21,Bachelors,3,14,15,98,72,6.0,4,32,Urban,HR Executive,146397,0 +68361,Male,36,High School,9,75,96,63,79,0.0,3,19,Rural,ML Engineer,62132,1 +68362,Male,23,High School,0,66,89,37,54,9.0,1,67,Semi-Urban,Data Analyst,27953,1 +68363,Male,38,Bachelors,11,88,19,6,89,6.0,3,78,Rural,ML Engineer,43842,0 +68364,Male,44,Bachelors,15,84,30,38,48,6.0,5,15,Urban,HR Executive,108918,0 +68365,Male,44,PhD,6,92,91,7,66,2.0,3,4,Urban,Manager,64322,0 +68366,Male,51,Bachelors,12,49,58,7,3,2.0,7,83,Urban,HR Executive,141295,0 +68367,Male,27,Masters,6,96,98,93,16,1.0,4,95,Rural,Software Engineer,144051,1 +68368,Female,58,High School,5,83,30,27,24,0.0,7,36,Rural,Data Analyst,148098,0 +68369,Female,45,Diploma,4,26,14,26,36,1.0,4,60,Urban,HR Executive,145636,0 +68370,Male,24,Masters,15,57,0,89,49,8.0,5,45,Urban,Software Engineer,106502,0 +68371,Male,36,Masters,0,58,18,61,76,9.0,7,19,Semi-Urban,Data Analyst,38617,0 +68372,Male,32,Bachelors,0,17,29,35,57,1.0,1,42,Urban,Data Analyst,111620,0 +68373,Male,31,High School,16,23,92,82,99,9.0,5,84,Urban,Manager,86953,1 +68374,Male,46,PhD,5,37,92,30,31,1.0,1,34,Urban,Data Analyst,38652,0 +68375,Male,41,Diploma,18,31,40,40,76,9.0,3,81,Urban,HR Executive,33263,0 +68376,Male,39,Masters,15,61,84,28,12,3.0,7,65,Semi-Urban,ML Engineer,116003,1 +68377,Female,59,High School,11,53,73,16,63,2.0,0,25,Semi-Urban,Software Engineer,122272,0 +68378,Other,53,Masters,16,9,79,64,49,2.0,5,0,Rural,ML Engineer,125531,0 +68379,Female,37,Bachelors,15,49,65,81,76,1.0,5,86,Urban,Data Analyst,69810,1 +68380,Female,35,Diploma,18,20,5,75,22,1.0,5,44,Semi-Urban,Software Engineer,50791,0 +68381,Female,57,Masters,3,95,6,33,82,6.0,6,67,Urban,Manager,76844,0 +68382,Female,21,Masters,10,22,45,80,16,8.0,2,58,Urban,Software Engineer,86876,0 +68383,Female,39,Masters,16,18,0,16,49,9.0,3,63,Urban,Manager,128478,0 +68384,Male,42,Diploma,6,43,20,55,93,2.0,2,96,Urban,HR Executive,73568,0 +68385,Female,53,Bachelors,19,3,12,39,61,2.0,4,23,Semi-Urban,Data Analyst,136409,0 +68386,Male,40,Bachelors,1,32,44,71,19,4.0,6,64,Urban,Manager,40367,0 +68387,Male,48,Bachelors,3,98,72,57,6,7.0,5,96,Urban,HR Executive,93610,1 +68388,Male,51,Bachelors,16,85,99,9,15,5.0,5,23,Urban,Software Engineer,98449,0 +68389,Male,36,Masters,3,94,98,0,18,0.0,3,94,Urban,Manager,43616,1 +68390,Female,48,Bachelors,5,27,20,90,7,2.0,0,43,Urban,ML Engineer,130024,0 +68391,Female,43,Bachelors,6,5,96,45,47,0.0,5,10,Semi-Urban,Manager,83199,0 +68392,Other,31,Bachelors,15,76,34,64,54,4.0,7,51,Semi-Urban,ML Engineer,38842,0 +68393,Male,59,PhD,10,97,63,37,49,1.0,4,10,Urban,Manager,38703,0 +68394,Other,23,PhD,9,5,55,90,69,1.0,7,82,Rural,Manager,63898,0 +68395,Female,24,Diploma,3,4,76,65,92,5.0,5,3,Urban,Software Engineer,40312,0 +68396,Male,23,Bachelors,14,78,35,85,49,0.0,1,40,Semi-Urban,HR Executive,20602,1 +68397,Male,47,Diploma,17,79,62,63,58,7.0,3,27,Semi-Urban,Software Engineer,85243,0 +68398,Male,47,Diploma,10,3,8,16,47,3.0,3,46,Urban,Data Analyst,29697,0 +68399,Male,52,Diploma,7,76,86,97,15,7.0,2,30,Urban,Data Analyst,67531,1 +68400,Male,55,Bachelors,15,69,52,51,61,3.0,2,38,Urban,Software Engineer,70174,0 +68401,Male,49,Masters,9,77,37,92,35,0.0,3,80,Urban,Data Analyst,88294,1 +68402,Male,34,Diploma,0,51,66,34,28,4.0,2,53,Semi-Urban,Software Engineer,117676,0 +68403,Female,40,Diploma,3,32,19,49,78,9.0,5,7,Semi-Urban,Software Engineer,30261,0 +68404,Female,21,Bachelors,6,0,26,17,27,8.0,4,19,Semi-Urban,Data Analyst,135466,0 +68405,Male,22,Masters,13,48,43,0,48,3.0,1,36,Urban,Manager,59206,0 +68406,Female,47,Bachelors,17,9,91,60,52,9.0,5,85,Semi-Urban,HR Executive,79557,1 +68407,Male,26,PhD,17,44,22,20,69,0.0,1,10,Rural,HR Executive,32684,0 +68408,Male,32,High School,5,19,4,35,22,0.0,6,55,Urban,ML Engineer,83587,0 +68409,Female,53,Masters,16,70,99,14,62,3.0,5,66,Urban,ML Engineer,54259,1 +68410,Male,42,Bachelors,14,76,18,1,0,6.0,7,34,Urban,ML Engineer,78626,0 +68411,Male,53,Bachelors,8,63,42,83,27,1.0,4,26,Urban,Manager,114072,0 +68412,Female,25,High School,10,46,61,64,10,5.0,6,14,Urban,Data Analyst,47344,0 +68413,Female,33,Bachelors,4,15,62,32,19,4.0,5,56,Semi-Urban,Data Analyst,42797,0 +68414,Male,30,Bachelors,10,0,21,8,62,9.0,7,70,Semi-Urban,Manager,64155,0 +68415,Female,31,Bachelors,0,18,47,65,17,1.0,2,5,Semi-Urban,ML Engineer,87295,0 +68416,Female,41,High School,4,5,75,60,73,6.0,7,24,Urban,Manager,50077,0 +68417,Female,47,Bachelors,12,18,68,28,13,8.0,7,67,Rural,HR Executive,83958,0 +68418,Female,22,Bachelors,5,6,21,24,87,9.0,4,62,Urban,ML Engineer,69247,0 +68419,Male,24,PhD,9,47,9,38,95,6.0,2,91,Rural,Software Engineer,52706,0 +68420,Male,35,PhD,7,36,19,59,30,5.0,0,14,Urban,Manager,112209,0 +68421,Male,56,Masters,5,53,24,21,85,8.0,3,26,Rural,Software Engineer,31396,0 +68422,Female,56,Bachelors,5,27,57,30,67,7.0,2,60,Urban,Software Engineer,132642,0 +68423,Female,31,Masters,7,66,40,9,77,7.0,0,15,Urban,Data Analyst,70583,0 +68424,Female,56,Bachelors,2,77,89,3,15,5.0,4,24,Semi-Urban,Data Analyst,49502,0 +68425,Male,28,Diploma,15,88,18,69,12,0.0,1,56,Urban,Software Engineer,26178,0 +68426,Female,41,High School,3,81,44,19,93,7.0,7,23,Semi-Urban,HR Executive,119864,0 +68427,Other,29,Bachelors,7,79,11,57,53,5.0,1,71,Urban,Manager,67974,0 +68428,Male,57,High School,15,14,32,79,97,0.0,5,80,Urban,Manager,118306,0 +68429,Female,23,Diploma,2,56,75,28,61,7.0,5,91,Urban,Data Analyst,136239,1 +68430,Female,28,Masters,14,70,13,38,4,9.0,7,60,Semi-Urban,Manager,32727,0 +68431,Female,59,Bachelors,18,57,94,81,76,3.0,2,40,Urban,HR Executive,147009,1 +68432,Male,35,Bachelors,13,46,42,78,14,3.0,7,23,Semi-Urban,Manager,110456,0 +68433,Male,49,PhD,17,28,74,26,31,3.0,7,21,Urban,HR Executive,137438,0 +68434,Female,52,High School,15,29,9,65,21,4.0,5,95,Urban,ML Engineer,39001,0 +68435,Female,53,Bachelors,2,94,39,66,17,9.0,5,74,Semi-Urban,ML Engineer,114527,1 +68436,Male,57,Bachelors,10,99,94,90,1,3.0,7,47,Urban,Data Analyst,67509,1 +68437,Male,42,Masters,0,51,67,32,39,6.0,1,82,Urban,Manager,123962,0 +68438,Female,33,Bachelors,12,86,49,18,95,7.0,0,21,Urban,HR Executive,102083,0 +68439,Male,33,High School,2,16,53,9,35,6.0,7,92,Rural,HR Executive,106168,0 +68440,Female,38,Bachelors,10,36,58,30,34,3.0,5,84,Semi-Urban,Data Analyst,80636,0 +68441,Male,48,High School,9,9,30,33,59,0.0,3,66,Urban,Software Engineer,111501,0 +68442,Male,43,High School,1,31,59,40,65,3.0,0,36,Urban,Manager,98639,0 +68443,Male,21,Bachelors,19,14,25,12,95,3.0,7,47,Urban,Data Analyst,93270,0 +68444,Male,33,Diploma,9,56,2,86,62,1.0,4,97,Rural,Manager,35344,1 +68445,Female,54,Bachelors,2,25,66,50,60,4.0,1,12,Rural,ML Engineer,84037,0 +68446,Male,38,Diploma,15,28,9,18,61,9.0,1,57,Urban,HR Executive,126532,0 +68447,Male,22,Bachelors,18,49,98,30,96,6.0,3,88,Rural,Software Engineer,89649,1 +68448,Male,28,Diploma,6,98,61,26,12,8.0,1,55,Semi-Urban,Data Analyst,135229,1 +68449,Male,45,Bachelors,12,87,11,61,32,3.0,3,98,Urban,Manager,88619,1 +68450,Male,59,High School,8,35,33,57,41,0.0,0,13,Urban,Manager,92727,0 +68451,Male,49,High School,19,46,76,12,30,1.0,7,54,Rural,Manager,36443,0 +68452,Male,53,Bachelors,3,59,71,53,45,0.0,5,6,Rural,ML Engineer,115770,0 +68453,Male,34,Masters,4,38,15,82,56,8.0,6,2,Urban,ML Engineer,107550,0 +68454,Male,49,Bachelors,11,69,9,78,88,3.0,0,10,Urban,Manager,113530,0 +68455,Female,21,Bachelors,9,80,78,2,66,3.0,5,67,Semi-Urban,ML Engineer,126761,0 +68456,Male,51,High School,0,63,14,95,19,3.0,1,49,Urban,Software Engineer,96423,0 +68457,Male,33,Bachelors,6,71,97,51,62,3.0,7,15,Urban,ML Engineer,137086,0 +68458,Male,22,High School,5,20,45,68,81,1.0,7,56,Urban,Manager,120989,0 +68459,Female,33,Masters,16,32,71,52,65,2.0,3,52,Urban,Data Analyst,27024,0 +68460,Male,48,Diploma,19,96,53,72,10,0.0,5,44,Rural,Manager,104436,1 +68461,Female,23,High School,15,41,82,61,74,3.0,4,13,Urban,Software Engineer,136136,0 +68462,Male,21,Bachelors,0,6,74,24,6,6.0,6,36,Urban,HR Executive,39973,0 +68463,Male,59,Masters,17,58,62,68,27,3.0,2,77,Urban,ML Engineer,73592,1 +68464,Female,27,High School,13,57,70,5,72,2.0,6,67,Urban,Software Engineer,58332,0 +68465,Male,37,Diploma,10,5,68,69,45,3.0,2,9,Urban,HR Executive,110054,0 +68466,Female,47,Diploma,8,59,94,34,86,1.0,7,14,Urban,Manager,48014,0 +68467,Male,37,Bachelors,18,50,24,20,95,1.0,6,72,Semi-Urban,Data Analyst,42165,0 +68468,Male,25,Bachelors,19,78,20,0,46,8.0,6,21,Urban,Data Analyst,95688,0 +68469,Male,39,Bachelors,7,45,86,54,2,0.0,2,27,Rural,Software Engineer,23846,0 +68470,Male,26,Bachelors,7,61,24,8,6,5.0,7,42,Urban,Manager,34934,0 +68471,Male,26,Bachelors,14,25,41,10,0,6.0,0,75,Semi-Urban,Manager,95632,0 +68472,Female,27,High School,3,28,1,97,32,0.0,0,45,Urban,Data Analyst,114855,0 +68473,Other,32,Bachelors,15,52,57,9,43,0.0,1,3,Rural,HR Executive,81646,0 +68474,Male,38,Masters,14,70,39,43,23,1.0,7,63,Semi-Urban,Manager,134505,0 +68475,Male,57,High School,16,62,99,31,15,6.0,0,49,Urban,Software Engineer,21139,1 +68476,Male,31,Diploma,5,18,86,0,39,5.0,7,67,Urban,Software Engineer,52436,0 +68477,Male,38,Bachelors,1,91,53,91,50,5.0,1,95,Rural,HR Executive,114416,1 +68478,Female,56,Diploma,5,21,41,17,60,7.0,1,79,Semi-Urban,Data Analyst,87210,0 +68479,Female,42,Masters,13,93,27,23,76,2.0,1,19,Urban,HR Executive,91032,0 +68480,Female,50,Diploma,18,81,61,10,32,8.0,7,10,Urban,Data Analyst,32760,0 +68481,Male,48,High School,9,89,44,76,94,4.0,0,33,Rural,HR Executive,53888,1 +68482,Male,59,High School,19,92,55,14,51,6.0,6,73,Semi-Urban,Software Engineer,113317,0 +68483,Female,43,Masters,5,96,70,55,75,5.0,4,58,Rural,Software Engineer,137560,1 +68484,Male,30,Bachelors,15,88,30,63,69,6.0,3,52,Urban,Data Analyst,132271,0 +68485,Other,45,High School,13,63,40,72,21,4.0,5,52,Rural,Manager,20809,0 +68486,Male,51,Bachelors,13,39,16,37,84,4.0,4,20,Urban,Software Engineer,147319,0 +68487,Male,22,Diploma,3,65,34,3,60,9.0,0,33,Urban,HR Executive,131936,0 +68488,Female,31,Bachelors,2,64,69,22,65,6.0,5,52,Semi-Urban,HR Executive,108304,0 +68489,Male,32,High School,0,56,30,90,86,9.0,0,39,Urban,Data Analyst,147573,0 +68490,Male,55,Diploma,1,66,28,18,5,2.0,6,32,Semi-Urban,Data Analyst,81042,0 +68491,Female,43,Bachelors,12,19,52,77,79,1.0,3,54,Urban,ML Engineer,42284,0 +68492,Male,32,High School,6,7,50,52,51,0.0,5,11,Urban,Data Analyst,135638,0 +68493,Male,49,Bachelors,11,78,85,71,1,7.0,0,97,Urban,Software Engineer,138818,1 +68494,Male,30,Bachelors,0,21,41,12,71,0.0,3,9,Semi-Urban,Manager,102077,0 +68495,Female,54,Bachelors,5,44,36,22,50,3.0,6,68,Urban,ML Engineer,129652,0 +68496,Male,51,Bachelors,13,99,62,33,60,0.0,0,83,Urban,HR Executive,103842,1 +68497,Male,36,Masters,7,54,63,29,65,2.0,1,64,Urban,ML Engineer,64927,0 +68498,Male,47,Diploma,9,74,56,17,73,0.0,3,46,Urban,Data Analyst,75709,0 +68499,Female,51,Bachelors,1,42,17,84,29,5.0,3,77,Urban,HR Executive,27539,0 +68500,Female,26,Bachelors,9,55,52,52,80,3.0,5,20,Urban,HR Executive,31114,0 +68501,Female,38,Diploma,13,71,82,11,84,2.0,5,57,Urban,Software Engineer,115695,0 +68502,Female,53,PhD,5,98,31,63,23,6.0,4,42,Rural,HR Executive,29250,0 +68503,Female,49,Diploma,8,88,0,90,76,2.0,1,81,Semi-Urban,Manager,40960,1 +68504,Female,26,Masters,7,85,62,97,9,8.0,0,12,Semi-Urban,HR Executive,76019,1 +68505,Male,37,High School,15,96,34,67,88,3.0,2,73,Urban,Data Analyst,20811,1 +68506,Male,57,Diploma,11,79,49,90,84,6.0,6,82,Urban,Manager,118973,1 +68507,Female,45,Masters,12,68,81,29,12,3.0,7,69,Urban,Data Analyst,95547,1 +68508,Female,49,Bachelors,11,50,84,68,78,6.0,2,83,Urban,Software Engineer,46436,1 +68509,Female,26,Bachelors,14,44,2,23,90,5.0,3,10,Urban,ML Engineer,120457,0 +68510,Male,32,Bachelors,11,66,98,45,1,5.0,2,68,Urban,HR Executive,123451,1 +68511,Female,31,Bachelors,7,34,60,66,15,6.0,0,84,Urban,ML Engineer,72442,1 +68512,Female,38,Diploma,0,91,69,22,3,9.0,6,50,Semi-Urban,Data Analyst,85272,0 +68513,Female,28,High School,13,24,4,53,18,5.0,5,99,Urban,Manager,78336,0 +68514,Female,21,Masters,11,43,5,64,96,0.0,2,84,Urban,Data Analyst,110699,0 +68515,Female,45,Bachelors,18,67,53,76,77,4.0,7,37,Urban,Software Engineer,61273,0 +68516,Male,53,Bachelors,15,44,38,8,62,2.0,3,18,Semi-Urban,HR Executive,105744,0 +68517,Male,54,PhD,8,59,11,83,47,8.0,4,46,Semi-Urban,HR Executive,146244,0 +68518,Other,56,Bachelors,8,90,13,89,18,5.0,4,41,Semi-Urban,HR Executive,93459,0 +68519,Male,25,High School,15,22,42,62,71,2.0,2,28,Rural,Manager,83072,0 +68520,Female,30,Bachelors,0,48,34,39,9,4.0,2,76,Urban,ML Engineer,87713,0 +68521,Male,22,Bachelors,9,97,94,84,9,1.0,1,54,Rural,Manager,100617,1 +68522,Female,23,Bachelors,11,19,78,75,33,7.0,5,24,Semi-Urban,Manager,74958,0 +68523,Male,51,Bachelors,11,20,39,8,82,0.0,0,74,Semi-Urban,Manager,73670,0 +68524,Female,37,Diploma,7,58,29,48,40,3.0,6,14,Rural,Manager,143385,0 +68525,Male,30,Bachelors,3,48,16,75,86,9.0,7,55,Urban,Software Engineer,144685,0 +68526,Male,49,Bachelors,15,50,32,54,27,7.0,1,25,Urban,ML Engineer,79683,0 +68527,Female,29,PhD,15,9,9,90,9,2.0,1,23,Urban,Software Engineer,57347,0 +68528,Male,40,PhD,16,64,3,29,78,1.0,3,92,Urban,ML Engineer,93440,0 +68529,Female,30,Masters,10,3,49,24,82,9.0,5,84,Urban,HR Executive,75122,0 +68530,Male,38,High School,2,37,35,35,62,3.0,0,93,Urban,HR Executive,22623,0 +68531,Female,52,Bachelors,4,72,96,31,81,9.0,1,56,Urban,Data Analyst,99293,1 +68532,Male,54,High School,2,78,10,35,83,1.0,0,40,Urban,HR Executive,92611,0 +68533,Male,35,Masters,17,34,3,52,47,5.0,7,29,Rural,Manager,92543,0 +68534,Female,32,Bachelors,9,35,49,91,97,6.0,5,16,Rural,Manager,22428,0 +68535,Male,33,PhD,0,39,4,45,32,5.0,7,12,Semi-Urban,ML Engineer,34895,0 +68536,Female,45,Bachelors,5,49,57,20,76,1.0,7,11,Urban,Software Engineer,95017,0 +68537,Male,47,Masters,15,88,30,69,8,9.0,2,74,Urban,ML Engineer,147694,1 +68538,Male,35,Bachelors,9,86,12,10,3,2.0,6,40,Rural,Software Engineer,92702,0 +68539,Male,36,Masters,1,35,9,16,87,7.0,4,30,Urban,Software Engineer,93975,0 +68540,Male,57,Bachelors,6,97,14,30,14,0.0,3,35,Urban,Data Analyst,71545,0 +68541,Female,24,Bachelors,0,36,65,42,52,1.0,2,77,Urban,HR Executive,133210,0 +68542,Male,35,Bachelors,10,4,45,77,41,4.0,1,44,Urban,Manager,98416,0 +68543,Male,40,Diploma,0,34,81,70,7,4.0,7,3,Urban,Manager,82994,0 +68544,Male,26,Bachelors,1,88,95,15,32,5.0,0,9,Semi-Urban,Data Analyst,126074,0 +68545,Female,57,PhD,1,14,57,79,29,6.0,0,65,Urban,Software Engineer,82845,0 +68546,Female,55,Bachelors,18,92,96,30,84,0.0,0,56,Rural,Software Engineer,120488,1 +68547,Male,34,Bachelors,5,0,15,5,11,2.0,7,48,Semi-Urban,ML Engineer,99669,0 +68548,Male,51,High School,7,46,87,17,40,6.0,0,2,Urban,Data Analyst,36223,0 +68549,Female,54,High School,11,5,53,20,18,6.0,1,41,Semi-Urban,Data Analyst,68316,0 +68550,Male,59,High School,4,52,66,53,14,3.0,4,2,Urban,ML Engineer,57236,0 +68551,Male,47,Bachelors,5,71,45,59,26,2.0,7,82,Urban,Data Analyst,122411,1 +68552,Male,30,PhD,5,18,68,50,64,1.0,5,43,Semi-Urban,ML Engineer,116365,0 +68553,Male,34,Bachelors,10,51,32,23,84,3.0,6,59,Urban,ML Engineer,89100,0 +68554,Female,28,Masters,6,17,49,12,73,9.0,6,86,Urban,ML Engineer,113980,0 +68555,Male,50,Bachelors,9,65,30,61,67,2.0,1,54,Semi-Urban,ML Engineer,102505,0 +68556,Male,37,Diploma,2,83,61,62,8,6.0,7,40,Semi-Urban,Software Engineer,42953,1 +68557,Male,51,Diploma,17,48,58,87,63,1.0,5,74,Rural,Manager,144711,1 +68558,Male,45,Masters,1,42,30,54,36,5.0,2,20,Rural,Data Analyst,149923,0 +68559,Female,26,Diploma,15,36,71,34,78,2.0,5,5,Urban,Software Engineer,80220,0 +68560,Male,54,Bachelors,5,37,0,9,16,5.0,1,42,Urban,Software Engineer,31908,0 +68561,Other,34,Bachelors,3,48,70,78,20,2.0,6,83,Urban,Data Analyst,131391,1 +68562,Male,58,Bachelors,15,71,75,6,40,1.0,5,85,Semi-Urban,ML Engineer,120118,1 +68563,Female,55,Bachelors,3,79,97,79,92,8.0,1,81,Semi-Urban,Data Analyst,109825,1 +68564,Male,41,High School,0,88,92,81,20,1.0,6,94,Semi-Urban,Software Engineer,130109,1 +68565,Male,41,Masters,17,92,49,2,29,1.0,7,42,Urban,ML Engineer,20852,0 +68566,Female,59,Bachelors,19,74,57,50,85,7.0,3,13,Urban,ML Engineer,134237,0 +68567,Male,55,Diploma,4,41,45,30,20,0.0,2,27,Urban,HR Executive,33281,0 +68568,Female,59,High School,13,66,2,23,87,5.0,0,46,Semi-Urban,Manager,53649,0 +68569,Male,43,Bachelors,3,81,28,63,63,7.0,0,92,Rural,HR Executive,131988,1 +68570,Male,56,Diploma,12,43,71,9,53,5.0,1,58,Urban,Software Engineer,107009,0 +68571,Male,26,Bachelors,13,16,70,50,67,2.0,6,74,Semi-Urban,Software Engineer,79350,0 +68572,Female,27,Bachelors,3,51,1,50,36,0.0,5,15,Urban,ML Engineer,120918,0 +68573,Female,59,Bachelors,12,48,22,7,71,7.0,7,99,Urban,Data Analyst,47760,0 +68574,Female,56,Diploma,13,63,54,39,33,2.0,0,80,Urban,Software Engineer,44293,0 +68575,Male,23,High School,4,17,93,46,82,5.0,2,41,Urban,ML Engineer,72157,0 +68576,Female,35,Diploma,5,99,21,22,90,1.0,4,15,Semi-Urban,HR Executive,115221,0 +68577,Male,38,High School,7,84,48,58,8,2.0,1,72,Semi-Urban,Software Engineer,105574,1 +68578,Male,53,Bachelors,14,62,24,26,55,8.0,5,52,Urban,ML Engineer,140653,0 +68579,Male,40,High School,1,3,51,94,50,9.0,1,64,Rural,Data Analyst,142811,0 +68580,Female,27,Masters,14,3,10,51,64,9.0,2,36,Urban,Data Analyst,33347,0 +68581,Male,34,Bachelors,12,32,87,90,12,9.0,7,12,Urban,Data Analyst,146831,0 +68582,Male,39,Diploma,9,22,80,77,12,6.0,0,38,Rural,HR Executive,34005,0 +68583,Male,43,Masters,7,92,17,28,0,3.0,7,56,Semi-Urban,Software Engineer,52968,0 +68584,Female,50,Bachelors,15,95,36,11,86,7.0,1,14,Urban,ML Engineer,21391,0 +68585,Female,54,Bachelors,8,88,20,86,25,8.0,5,10,Urban,ML Engineer,43856,0 +68586,Male,34,Diploma,9,48,44,23,3,6.0,7,43,Urban,Manager,78094,0 +68587,Other,43,Diploma,8,66,29,23,34,1.0,6,33,Urban,HR Executive,45984,0 +68588,Female,26,Masters,6,32,91,49,76,6.0,5,97,Rural,ML Engineer,30373,1 +68589,Male,56,Bachelors,6,92,46,51,88,9.0,6,75,Urban,Manager,60219,1 +68590,Female,33,Diploma,19,59,98,94,56,6.0,0,41,Urban,Data Analyst,76113,1 +68591,Male,42,Bachelors,8,22,11,2,68,9.0,3,60,Urban,ML Engineer,58214,0 +68592,Male,56,Bachelors,4,54,72,76,37,3.0,3,48,Urban,ML Engineer,35247,1 +68593,Male,44,Masters,16,56,94,86,92,6.0,2,83,Urban,Data Analyst,125198,1 +68594,Female,53,PhD,15,89,74,25,33,1.0,4,96,Semi-Urban,Software Engineer,22616,1 +68595,Male,45,Diploma,7,31,61,34,27,1.0,4,31,Semi-Urban,ML Engineer,89584,0 +68596,Male,25,Bachelors,7,50,48,85,26,0.0,4,27,Urban,Data Analyst,136864,0 +68597,Male,31,Masters,19,17,46,87,52,4.0,1,92,Semi-Urban,HR Executive,23905,1 +68598,Female,37,Masters,8,24,46,21,72,0.0,3,98,Urban,Software Engineer,137438,0 +68599,Female,25,Bachelors,5,35,9,48,88,9.0,5,9,Urban,ML Engineer,39446,0 +68600,Female,41,Bachelors,18,50,68,92,93,1.0,1,66,Semi-Urban,ML Engineer,77247,1 +68601,Male,31,Bachelors,18,91,85,36,72,2.0,4,82,Urban,Data Analyst,59204,1 +68602,Male,26,Bachelors,2,66,68,10,17,0.0,4,62,Urban,HR Executive,112144,0 +68603,Female,48,Bachelors,13,3,98,16,62,9.0,1,73,Urban,Software Engineer,44624,0 +68604,Male,54,Masters,12,72,71,44,12,3.0,1,56,Urban,HR Executive,93691,1 +68605,Male,48,Bachelors,18,33,8,93,60,0.0,2,49,Urban,Data Analyst,122701,0 +68606,Male,58,High School,1,97,98,48,38,4.0,2,18,Urban,HR Executive,103829,1 +68607,Other,49,Bachelors,7,85,98,41,9,6.0,2,1,Rural,Software Engineer,104812,0 +68608,Male,53,Diploma,11,47,8,7,29,1.0,4,17,Urban,ML Engineer,80584,0 +68609,Male,45,Bachelors,8,53,8,53,42,4.0,4,63,Urban,Data Analyst,135877,0 +68610,Female,21,Bachelors,3,46,12,27,48,6.0,2,65,Semi-Urban,ML Engineer,51144,0 +68611,Female,31,High School,8,55,94,55,14,8.0,0,57,Semi-Urban,Manager,20891,1 +68612,Male,37,High School,5,1,68,1,1,7.0,6,20,Semi-Urban,HR Executive,118822,0 +68613,Other,41,Masters,7,93,81,53,90,3.0,3,7,Urban,Manager,123095,0 +68614,Female,59,High School,4,37,48,57,13,8.0,4,21,Semi-Urban,Software Engineer,107159,0 +68615,Male,37,Bachelors,6,74,87,90,32,9.0,6,17,Semi-Urban,Software Engineer,57229,1 +68616,Female,21,Masters,0,49,43,62,17,7.0,1,2,Urban,Manager,22716,0 +68617,Female,42,Diploma,9,82,96,59,58,6.0,1,96,Rural,HR Executive,149195,1 +68618,Male,39,Bachelors,18,16,40,75,17,4.0,2,52,Urban,Data Analyst,127738,0 +68619,Female,57,Bachelors,5,76,9,70,61,6.0,3,68,Rural,HR Executive,51853,0 +68620,Female,37,High School,8,49,98,49,5,9.0,3,16,Urban,Software Engineer,49583,0 +68621,Female,58,Masters,4,6,65,87,83,9.0,2,56,Rural,ML Engineer,27705,0 +68622,Male,28,Diploma,0,89,50,66,96,9.0,0,55,Urban,Software Engineer,116272,1 +68623,Male,54,Bachelors,14,97,61,40,6,4.0,6,82,Semi-Urban,Software Engineer,143294,1 +68624,Male,56,Bachelors,8,0,29,81,33,6.0,4,69,Urban,Data Analyst,85018,0 +68625,Male,40,Masters,0,52,12,50,74,2.0,1,15,Semi-Urban,HR Executive,139737,0 +68626,Female,35,High School,7,29,97,90,41,4.0,7,12,Urban,Data Analyst,30212,0 +68627,Female,21,Bachelors,15,49,78,37,39,4.0,3,95,Semi-Urban,ML Engineer,137768,1 +68628,Male,36,Bachelors,19,90,43,46,39,3.0,0,13,Urban,Software Engineer,72259,0 +68629,Female,34,High School,0,25,79,20,55,1.0,3,48,Urban,HR Executive,76892,0 +68630,Male,41,Bachelors,11,71,33,80,75,4.0,0,25,Urban,ML Engineer,148956,0 +68631,Male,45,Diploma,4,16,3,87,47,5.0,2,5,Rural,Manager,68843,0 +68632,Male,24,Bachelors,2,4,88,21,71,2.0,3,27,Urban,Manager,26252,0 +68633,Male,35,Masters,16,66,27,44,66,2.0,7,94,Semi-Urban,ML Engineer,69730,0 +68634,Male,47,Bachelors,15,92,74,88,4,5.0,6,36,Urban,HR Executive,52172,1 +68635,Male,22,Bachelors,2,33,36,81,85,2.0,1,29,Urban,Data Analyst,129379,0 +68636,Female,49,Diploma,14,22,94,24,28,4.0,3,81,Urban,Software Engineer,56161,0 +68637,Male,42,Diploma,13,94,70,76,11,1.0,2,15,Urban,Data Analyst,132331,1 +68638,Male,56,Masters,1,93,21,12,81,1.0,0,12,Urban,ML Engineer,124361,0 +68639,Female,39,Bachelors,9,77,97,17,64,2.0,5,67,Urban,Manager,35096,1 +68640,Male,39,Masters,7,51,39,93,51,6.0,3,29,Urban,Manager,133514,0 +68641,Female,58,Diploma,11,31,57,53,82,4.0,6,74,Rural,ML Engineer,80355,0 +68642,Male,42,Diploma,0,73,28,53,16,6.0,1,33,Urban,Software Engineer,124016,0 +68643,Male,29,Bachelors,0,11,8,68,93,8.0,3,86,Semi-Urban,HR Executive,75351,0 +68644,Male,33,PhD,9,68,75,12,83,6.0,6,49,Rural,Manager,120376,0 +68645,Male,59,Diploma,7,88,48,1,59,1.0,4,64,Rural,Manager,36479,0 +68646,Female,51,Bachelors,2,92,83,41,90,8.0,3,48,Rural,ML Engineer,139010,1 +68647,Male,23,Bachelors,3,10,94,18,75,0.0,3,51,Urban,ML Engineer,54282,0 +68648,Male,21,Bachelors,14,52,10,23,79,7.0,2,90,Urban,Software Engineer,95919,0 +68649,Male,42,Bachelors,19,88,66,42,50,0.0,1,8,Rural,HR Executive,39455,0 +68650,Male,53,Diploma,5,16,72,21,88,8.0,7,19,Semi-Urban,Manager,142718,0 +68651,Male,37,Diploma,0,80,24,33,18,2.0,6,73,Semi-Urban,Manager,43365,0 +68652,Male,36,Masters,12,20,45,24,89,0.0,0,32,Urban,Data Analyst,134885,0 +68653,Male,49,Bachelors,8,8,93,73,22,6.0,6,8,Urban,Manager,32038,0 +68654,Male,48,Bachelors,9,1,10,47,61,7.0,2,90,Urban,HR Executive,135854,0 +68655,Female,42,Masters,14,39,75,6,3,9.0,1,16,Urban,ML Engineer,133627,0 +68656,Male,24,Bachelors,0,57,98,96,62,4.0,4,71,Urban,Manager,48933,1 +68657,Female,27,Bachelors,16,95,24,8,95,5.0,5,24,Urban,HR Executive,46999,0 +68658,Female,41,Bachelors,8,49,32,52,33,8.0,2,11,Urban,Manager,135427,0 +68659,Female,47,Bachelors,9,6,12,7,71,6.0,1,44,Rural,Software Engineer,116252,0 +68660,Male,46,Diploma,2,61,30,48,2,7.0,4,12,Rural,ML Engineer,97266,0 +68661,Female,49,Bachelors,14,38,23,14,75,5.0,6,33,Urban,Data Analyst,64761,0 +68662,Male,52,Bachelors,1,52,61,51,7,9.0,6,51,Urban,HR Executive,125896,0 +68663,Female,21,Bachelors,0,37,45,45,44,1.0,6,84,Urban,HR Executive,28579,0 +68664,Female,47,High School,5,18,0,23,24,4.0,3,12,Urban,HR Executive,128042,0 +68665,Female,35,Bachelors,8,4,8,44,14,1.0,5,53,Semi-Urban,HR Executive,52052,0 +68666,Male,47,Masters,7,12,92,57,38,4.0,1,19,Urban,ML Engineer,50070,0 +68667,Male,53,Masters,4,73,82,76,64,3.0,2,93,Rural,Manager,148939,1 +68668,Male,49,High School,1,54,20,42,68,9.0,2,4,Urban,Data Analyst,71328,0 +68669,Female,40,Bachelors,8,16,71,5,59,6.0,4,14,Semi-Urban,Manager,82580,0 +68670,Male,42,High School,18,68,85,52,9,6.0,2,1,Rural,HR Executive,85235,0 +68671,Male,27,High School,2,85,43,66,58,1.0,1,41,Urban,HR Executive,54430,1 +68672,Female,29,Bachelors,19,28,80,49,24,7.0,4,19,Rural,Manager,39548,0 +68673,Other,57,Diploma,8,47,88,17,92,5.0,6,17,Urban,Software Engineer,49968,0 +68674,Male,34,PhD,1,59,63,28,32,6.0,7,59,Semi-Urban,Manager,118535,0 +68675,Female,25,Bachelors,19,20,27,8,46,0.0,4,97,Urban,ML Engineer,147717,0 +68676,Female,24,Masters,8,24,36,17,79,4.0,6,17,Rural,Data Analyst,57486,0 +68677,Male,48,Masters,5,34,14,28,30,6.0,4,35,Rural,Data Analyst,66963,0 +68678,Male,54,High School,12,31,24,63,97,1.0,7,94,Urban,Data Analyst,74421,0 +68679,Female,45,Bachelors,9,87,42,8,40,0.0,0,64,Urban,Software Engineer,70314,0 +68680,Male,36,Bachelors,9,74,39,83,44,4.0,1,9,Urban,Software Engineer,39517,0 +68681,Female,23,High School,9,60,26,17,18,5.0,1,44,Semi-Urban,ML Engineer,116803,0 +68682,Male,49,Bachelors,11,21,3,10,92,7.0,3,62,Urban,HR Executive,111758,0 +68683,Female,27,Masters,17,12,15,5,22,6.0,7,43,Rural,Manager,53952,0 +68684,Male,31,Bachelors,9,66,29,51,94,6.0,3,61,Rural,Data Analyst,109354,0 +68685,Male,41,Bachelors,19,27,43,43,97,9.0,3,55,Urban,ML Engineer,147343,0 +68686,Female,32,Masters,6,54,45,77,43,6.0,7,71,Urban,Manager,130266,1 +68687,Male,32,Bachelors,7,8,32,85,28,7.0,0,30,Rural,HR Executive,33262,0 +68688,Female,47,Bachelors,13,72,91,58,80,3.0,2,59,Semi-Urban,Software Engineer,117701,1 +68689,Female,46,Masters,2,18,2,45,82,0.0,1,62,Urban,Manager,39737,0 +68690,Female,58,Masters,2,19,78,18,83,2.0,7,68,Semi-Urban,Manager,64125,0 +68691,Female,22,Bachelors,19,64,24,5,9,4.0,0,45,Rural,HR Executive,49458,0 +68692,Male,46,Diploma,0,69,91,57,70,6.0,5,29,Urban,ML Engineer,57569,1 +68693,Female,48,Bachelors,10,84,73,60,60,4.0,2,93,Urban,Software Engineer,145138,1 +68694,Male,50,High School,15,56,6,7,46,5.0,5,62,Semi-Urban,Data Analyst,141891,0 +68695,Male,35,Diploma,14,86,67,36,6,9.0,6,76,Rural,Manager,110597,1 +68696,Male,52,Bachelors,7,41,82,91,82,7.0,4,12,Urban,Data Analyst,46766,0 +68697,Male,54,Bachelors,12,24,84,9,22,5.0,6,73,Urban,ML Engineer,108217,0 +68698,Male,41,Bachelors,13,6,81,53,24,0.0,4,80,Semi-Urban,ML Engineer,33093,0 +68699,Male,21,High School,19,87,20,45,59,1.0,3,38,Urban,ML Engineer,61565,0 +68700,Male,41,Masters,2,52,84,22,16,5.0,6,37,Rural,Software Engineer,139621,0 +68701,Male,58,Bachelors,1,49,32,22,92,4.0,3,8,Urban,Software Engineer,145573,0 +68702,Male,45,Bachelors,1,90,31,18,67,5.0,3,43,Semi-Urban,ML Engineer,132350,0 +68703,Male,36,Diploma,14,22,49,85,61,4.0,0,83,Urban,Manager,95765,1 +68704,Female,54,Bachelors,9,32,78,8,98,3.0,4,38,Semi-Urban,Software Engineer,88288,0 +68705,Male,59,Masters,1,88,2,38,44,1.0,5,15,Urban,ML Engineer,140924,0 +68706,Male,46,Bachelors,14,67,53,93,41,8.0,7,44,Urban,ML Engineer,142028,1 +68707,Male,46,High School,0,90,27,94,34,1.0,6,3,Urban,ML Engineer,41832,0 +68708,Male,46,Bachelors,19,6,41,62,85,7.0,6,68,Urban,Data Analyst,134356,0 +68709,Female,42,Bachelors,3,71,22,83,70,1.0,6,39,Urban,ML Engineer,53201,0 +68710,Male,44,Bachelors,6,86,98,27,12,8.0,7,33,Rural,Data Analyst,55508,1 +68711,Other,28,Bachelors,2,79,75,41,79,2.0,7,54,Urban,ML Engineer,47765,1 +68712,Female,27,Bachelors,10,77,6,39,40,1.0,1,15,Urban,ML Engineer,106137,0 +68713,Other,45,Bachelors,3,59,78,69,26,0.0,3,9,Semi-Urban,Data Analyst,33175,0 +68714,Male,59,Bachelors,12,57,41,47,76,2.0,6,87,Urban,Software Engineer,55727,0 +68715,Female,39,Masters,18,98,71,66,19,0.0,1,41,Rural,HR Executive,47898,1 +68716,Male,32,High School,0,10,37,73,38,1.0,4,70,Urban,HR Executive,36536,0 +68717,Female,36,Masters,10,10,1,60,93,2.0,1,34,Semi-Urban,ML Engineer,144670,0 +68718,Female,59,Bachelors,3,85,29,38,22,4.0,0,74,Rural,Data Analyst,125400,0 +68719,Male,55,High School,12,26,24,92,36,0.0,4,45,Urban,Data Analyst,147051,0 +68720,Male,36,Masters,14,29,35,47,35,0.0,2,3,Urban,ML Engineer,121133,0 +68721,Male,22,High School,19,26,1,0,21,6.0,2,3,Urban,Software Engineer,107594,0 +68722,Female,29,High School,2,16,83,13,89,5.0,4,4,Rural,HR Executive,40930,0 +68723,Female,45,Masters,0,22,72,37,26,0.0,3,66,Semi-Urban,ML Engineer,119838,0 +68724,Male,52,Bachelors,2,17,23,59,19,9.0,6,26,Semi-Urban,Data Analyst,148151,0 +68725,Female,25,Diploma,14,6,56,6,47,2.0,3,95,Semi-Urban,ML Engineer,70617,0 +68726,Female,48,Bachelors,18,92,94,83,41,5.0,1,37,Semi-Urban,Data Analyst,108555,1 +68727,Female,58,Bachelors,15,48,79,37,59,2.0,1,83,Urban,ML Engineer,123615,1 +68728,Male,59,Bachelors,12,23,4,35,33,3.0,0,18,Urban,Software Engineer,129691,0 +68729,Male,45,Diploma,12,36,25,43,97,5.0,7,85,Semi-Urban,Manager,45508,0 +68730,Female,44,Bachelors,14,29,42,52,56,5.0,1,73,Semi-Urban,Manager,26033,0 +68731,Male,54,Diploma,9,54,65,97,93,5.0,5,36,Rural,Software Engineer,126332,1 +68732,Male,36,Masters,7,33,18,30,86,1.0,6,36,Urban,Data Analyst,56045,0 +68733,Female,51,Masters,5,44,1,42,94,4.0,4,70,Urban,ML Engineer,123504,0 +68734,Female,27,High School,1,49,11,25,22,4.0,1,84,Semi-Urban,HR Executive,28251,0 +68735,Male,40,Bachelors,8,71,11,54,63,9.0,3,88,Rural,Data Analyst,107956,0 +68736,Male,24,Bachelors,13,31,63,78,78,8.0,7,99,Urban,Data Analyst,126251,1 +68737,Female,45,Bachelors,14,93,47,35,25,4.0,1,43,Semi-Urban,ML Engineer,85998,0 +68738,Male,53,Masters,1,61,74,41,70,1.0,1,71,Rural,HR Executive,123818,1 +68739,Male,26,Bachelors,15,11,9,16,33,0.0,0,54,Urban,Data Analyst,54770,0 +68740,Female,34,Bachelors,1,73,55,70,21,9.0,2,7,Rural,HR Executive,80267,0 +68741,Male,50,High School,9,2,8,21,2,4.0,0,4,Urban,Software Engineer,31376,0 +68742,Female,48,Diploma,19,25,21,54,36,9.0,7,97,Rural,Data Analyst,124415,0 +68743,Male,31,Masters,2,35,58,46,52,8.0,5,53,Semi-Urban,Manager,61275,0 +68744,Male,47,Bachelors,7,49,78,45,7,3.0,4,36,Urban,Software Engineer,47691,0 +68745,Female,22,Diploma,3,92,27,56,87,5.0,7,6,Rural,Manager,77265,0 +68746,Female,58,High School,4,84,48,10,44,3.0,2,75,Semi-Urban,HR Executive,131087,0 +68747,Male,50,Bachelors,5,27,33,84,97,7.0,0,92,Urban,Data Analyst,103175,1 +68748,Male,38,Diploma,11,29,80,22,80,9.0,2,73,Urban,Data Analyst,114337,0 +68749,Male,25,High School,14,62,91,62,21,0.0,6,83,Urban,Software Engineer,29394,1 +68750,Male,56,Masters,14,8,81,54,77,0.0,2,50,Urban,Data Analyst,122934,0 +68751,Female,43,Bachelors,15,40,85,83,91,7.0,2,17,Semi-Urban,Software Engineer,69093,0 +68752,Male,31,Bachelors,2,35,77,97,1,4.0,3,36,Semi-Urban,Software Engineer,100723,1 +68753,Female,45,Masters,17,90,67,92,11,2.0,2,63,Urban,ML Engineer,94695,1 +68754,Male,35,Bachelors,0,38,59,1,23,6.0,3,57,Semi-Urban,HR Executive,128540,0 +68755,Male,53,Diploma,17,36,37,83,26,7.0,7,2,Urban,Software Engineer,123344,0 +68756,Male,34,Bachelors,14,70,51,84,63,0.0,7,87,Semi-Urban,Software Engineer,24782,1 +68757,Female,52,Diploma,7,48,23,86,73,0.0,6,15,Semi-Urban,HR Executive,75010,0 +68758,Male,56,Masters,8,43,34,81,4,5.0,0,56,Semi-Urban,Manager,24167,0 +68759,Male,40,Bachelors,2,83,64,23,16,0.0,6,44,Semi-Urban,Software Engineer,145681,0 +68760,Male,54,Masters,0,64,75,11,9,5.0,3,54,Rural,Data Analyst,70895,0 +68761,Other,50,Masters,8,66,69,87,50,6.0,1,8,Rural,Manager,23646,0 +68762,Female,53,Masters,10,9,50,1,38,5.0,0,27,Urban,Manager,92299,0 +68763,Male,53,Bachelors,14,51,2,75,10,6.0,5,79,Urban,ML Engineer,123809,0 +68764,Male,54,Bachelors,10,91,68,48,10,1.0,5,78,Semi-Urban,ML Engineer,85655,1 +68765,Female,24,Bachelors,4,28,32,55,71,0.0,2,42,Urban,Manager,59516,0 +68766,Other,28,Bachelors,3,38,11,54,56,2.0,0,17,Rural,ML Engineer,50139,0 +68767,Female,28,Bachelors,11,77,42,60,7,9.0,4,66,Urban,Manager,33867,1 +68768,Male,59,Bachelors,9,20,89,51,2,6.0,0,92,Urban,Manager,136706,1 +68769,Other,57,Masters,11,34,18,17,67,9.0,5,85,Rural,ML Engineer,70632,0 +68770,Male,58,Bachelors,9,19,49,58,92,5.0,7,78,Urban,HR Executive,85017,0 +68771,Male,25,Bachelors,7,19,80,7,17,6.0,6,30,Urban,Data Analyst,47890,0 +68772,Female,27,Bachelors,15,43,38,55,55,8.0,0,21,Semi-Urban,Software Engineer,24191,0 +68773,Male,27,High School,0,30,39,9,3,6.0,3,79,Urban,HR Executive,114611,0 +68774,Other,54,Bachelors,15,14,4,57,79,6.0,1,17,Semi-Urban,Manager,144623,0 +68775,Male,22,Masters,8,4,9,78,34,8.0,5,35,Urban,Data Analyst,92482,0 +68776,Male,22,High School,2,44,2,95,4,1.0,7,7,Semi-Urban,Software Engineer,48166,0 +68777,Male,48,Masters,7,72,25,5,68,6.0,1,90,Semi-Urban,Manager,107073,0 +68778,Female,25,Bachelors,18,59,20,17,4,3.0,3,77,Semi-Urban,ML Engineer,101043,0 +68779,Male,48,Masters,10,52,13,12,84,2.0,4,4,Rural,Manager,96986,0 +68780,Male,57,Bachelors,3,87,70,86,60,5.0,1,43,Urban,Data Analyst,46292,1 +68781,Male,45,Bachelors,19,14,96,5,20,0.0,0,16,Urban,ML Engineer,46951,0 +68782,Male,46,Diploma,9,26,5,39,75,4.0,5,42,Semi-Urban,Data Analyst,71241,0 +68783,Male,33,High School,5,94,75,11,53,2.0,5,35,Rural,Software Engineer,105608,0 +68784,Male,28,Bachelors,0,48,90,19,63,1.0,2,42,Urban,Software Engineer,65985,0 +68785,Male,32,High School,1,17,78,95,10,1.0,1,7,Urban,ML Engineer,41524,0 +68786,Male,43,Bachelors,13,99,23,39,95,1.0,6,50,Urban,ML Engineer,69108,0 +68787,Female,24,Masters,4,55,26,86,91,6.0,5,6,Rural,Manager,72821,0 +68788,Male,58,PhD,19,49,99,61,49,3.0,7,97,Semi-Urban,Data Analyst,57157,1 +68789,Male,35,Bachelors,15,82,53,21,21,1.0,6,25,Urban,Software Engineer,95878,0 +68790,Male,32,Bachelors,2,95,74,60,32,2.0,7,37,Semi-Urban,Manager,52544,1 +68791,Female,56,Masters,17,93,45,30,80,2.0,2,70,Urban,ML Engineer,39969,0 +68792,Male,34,Diploma,13,40,95,28,10,4.0,6,93,Urban,HR Executive,85462,1 +68793,Female,30,Bachelors,19,19,20,26,52,0.0,2,54,Urban,HR Executive,116499,0 +68794,Female,28,Bachelors,17,69,8,17,77,0.0,0,35,Rural,Manager,129553,0 +68795,Other,53,PhD,0,53,7,60,73,6.0,1,2,Urban,Software Engineer,132313,0 +68796,Female,37,Masters,16,96,56,53,67,6.0,4,6,Semi-Urban,Software Engineer,95744,0 +68797,Male,56,High School,13,33,93,49,90,3.0,6,98,Rural,Data Analyst,98072,1 +68798,Male,36,Diploma,7,66,80,22,56,1.0,6,89,Urban,Software Engineer,114374,1 +68799,Male,37,Diploma,15,73,15,56,12,6.0,0,5,Urban,Data Analyst,134190,0 +68800,Female,44,Diploma,0,43,99,21,80,6.0,4,27,Urban,HR Executive,140577,0 +68801,Male,58,Masters,3,41,2,68,25,3.0,4,5,Urban,HR Executive,141544,0 +68802,Female,35,Bachelors,7,26,78,33,71,9.0,5,68,Rural,Manager,75616,0 +68803,Male,40,Diploma,4,38,81,89,59,6.0,6,51,Semi-Urban,Data Analyst,40234,1 +68804,Female,35,Masters,16,57,99,16,0,1.0,5,89,Urban,Data Analyst,107919,1 +68805,Female,33,Masters,15,9,72,93,97,0.0,6,72,Semi-Urban,Software Engineer,145879,1 +68806,Male,31,Diploma,0,16,83,27,43,4.0,3,76,Semi-Urban,Manager,135453,0 +68807,Female,56,Bachelors,19,11,85,99,46,3.0,6,54,Semi-Urban,Data Analyst,57373,1 +68808,Male,29,High School,19,31,89,52,51,3.0,1,85,Urban,ML Engineer,59670,1 +68809,Female,21,Masters,15,97,45,12,3,0.0,5,36,Urban,ML Engineer,84577,0 +68810,Female,34,Masters,3,20,43,26,39,3.0,3,50,Urban,ML Engineer,90440,0 +68811,Female,53,Bachelors,13,24,56,29,63,0.0,1,45,Urban,Data Analyst,128374,0 +68812,Male,56,Masters,12,15,28,92,49,4.0,1,46,Semi-Urban,HR Executive,26193,0 +68813,Male,48,Bachelors,9,11,56,90,48,2.0,5,3,Urban,Manager,21878,0 +68814,Female,32,Bachelors,12,14,94,90,48,8.0,2,97,Semi-Urban,Data Analyst,73023,1 +68815,Female,21,Diploma,16,14,73,23,13,9.0,2,67,Urban,Software Engineer,60340,0 +68816,Male,22,Masters,10,57,57,9,14,9.0,6,60,Urban,Manager,104487,0 +68817,Female,41,Masters,17,27,53,79,99,2.0,2,13,Rural,ML Engineer,147647,0 +68818,Male,24,Bachelors,19,61,95,16,75,3.0,3,69,Urban,Manager,71328,1 +68819,Female,59,Masters,3,42,16,91,27,6.0,7,43,Semi-Urban,Software Engineer,142984,0 +68820,Female,52,High School,9,85,24,14,25,4.0,3,49,Urban,HR Executive,55874,0 +68821,Female,25,Diploma,3,79,50,82,41,5.0,0,90,Rural,ML Engineer,50708,1 +68822,Male,26,Bachelors,4,36,69,49,64,5.0,6,73,Urban,ML Engineer,90269,0 +68823,Other,48,Diploma,7,67,19,93,84,4.0,5,88,Urban,Data Analyst,32342,1 +68824,Male,22,High School,13,27,94,90,35,4.0,6,3,Urban,Software Engineer,104849,0 +68825,Male,41,Diploma,15,48,54,44,57,5.0,6,47,Urban,Data Analyst,115432,0 +68826,Male,55,Diploma,0,52,11,58,30,2.0,3,37,Semi-Urban,ML Engineer,54129,0 +68827,Male,40,Bachelors,18,45,69,62,11,0.0,6,7,Urban,Software Engineer,95265,0 +68828,Male,47,Bachelors,12,13,44,67,34,8.0,7,11,Urban,Software Engineer,54662,0 +68829,Female,41,Masters,4,42,1,17,48,1.0,0,10,Urban,HR Executive,142571,0 +68830,Female,40,PhD,4,1,83,4,92,7.0,0,37,Rural,HR Executive,104644,0 +68831,Male,52,Bachelors,6,80,17,6,5,2.0,7,26,Semi-Urban,HR Executive,83370,0 +68832,Female,29,Diploma,0,40,24,95,75,6.0,1,76,Urban,Data Analyst,123667,0 +68833,Other,30,Bachelors,19,43,82,79,12,9.0,3,72,Urban,Manager,68487,1 +68834,Male,41,PhD,12,32,89,29,76,4.0,7,71,Urban,Data Analyst,54965,0 +68835,Male,29,Masters,15,10,55,10,73,1.0,6,34,Semi-Urban,Data Analyst,52965,0 +68836,Female,57,High School,9,8,95,17,63,0.0,4,96,Urban,ML Engineer,126918,0 +68837,Female,35,Bachelors,10,64,81,92,64,4.0,6,11,Semi-Urban,Data Analyst,147442,1 +68838,Male,30,Bachelors,7,18,5,46,65,7.0,1,40,Urban,ML Engineer,72788,0 +68839,Female,24,Diploma,13,10,92,70,26,1.0,0,39,Urban,Software Engineer,32032,0 +68840,Female,51,Diploma,12,60,8,12,37,5.0,4,76,Semi-Urban,HR Executive,29594,0 +68841,Other,44,Bachelors,18,47,56,24,45,6.0,2,7,Urban,HR Executive,93821,0 +68842,Male,50,Bachelors,2,14,65,29,61,3.0,2,67,Urban,Manager,93997,0 +68843,Female,43,Bachelors,17,46,73,85,38,0.0,3,3,Urban,HR Executive,132049,0 +68844,Female,35,High School,17,1,88,21,8,2.0,2,52,Semi-Urban,Manager,103658,0 +68845,Male,28,Diploma,7,76,37,59,17,1.0,2,5,Urban,HR Executive,69194,0 +68846,Female,26,Bachelors,19,10,41,77,39,7.0,4,13,Urban,Manager,133220,0 +68847,Male,31,Masters,17,36,45,68,33,1.0,6,91,Semi-Urban,Manager,84934,1 +68848,Male,27,Bachelors,3,57,77,75,72,7.0,2,58,Urban,HR Executive,25083,1 +68849,Female,33,Bachelors,8,65,48,30,61,5.0,1,21,Semi-Urban,Manager,66937,0 +68850,Male,32,Bachelors,0,70,0,95,4,5.0,1,67,Semi-Urban,Manager,103655,0 +68851,Male,42,Masters,17,38,32,2,99,4.0,3,75,Rural,ML Engineer,83721,0 +68852,Male,55,Diploma,0,83,95,73,88,9.0,0,30,Rural,HR Executive,72419,1 +68853,Male,36,Diploma,7,11,59,4,18,3.0,2,79,Urban,ML Engineer,145143,0 +68854,Male,58,Bachelors,18,39,77,15,35,2.0,4,64,Urban,Manager,20698,0 +68855,Male,42,High School,8,13,64,33,28,9.0,6,72,Rural,Data Analyst,23077,0 +68856,Male,44,Bachelors,18,7,45,70,5,7.0,0,67,Urban,Software Engineer,27710,0 +68857,Male,37,Bachelors,5,15,52,53,6,9.0,4,98,Urban,Manager,48053,0 +68858,Male,23,Diploma,8,49,29,34,7,4.0,5,45,Urban,Software Engineer,100361,0 +68859,Female,25,Bachelors,16,68,71,40,84,4.0,3,72,Rural,Data Analyst,31674,1 +68860,Female,29,Bachelors,8,8,19,99,41,7.0,4,77,Urban,Software Engineer,145443,0 +68861,Male,55,Bachelors,11,53,17,42,94,2.0,2,87,Urban,Data Analyst,75955,0 +68862,Male,52,Diploma,12,30,56,91,81,1.0,0,0,Rural,Data Analyst,41242,0 +68863,Male,30,High School,14,73,65,18,47,2.0,0,97,Semi-Urban,Manager,20091,1 +68864,Male,26,Diploma,19,68,48,13,37,8.0,4,25,Urban,Data Analyst,33913,0 +68865,Other,52,Bachelors,9,91,67,10,73,5.0,6,30,Urban,Manager,48300,0 +68866,Female,36,Diploma,4,67,9,21,33,3.0,3,55,Semi-Urban,HR Executive,59724,0 +68867,Male,34,Masters,4,64,64,72,95,2.0,5,11,Urban,Software Engineer,31005,0 +68868,Male,26,Bachelors,0,98,17,53,46,4.0,6,99,Urban,Data Analyst,142332,1 +68869,Female,28,Bachelors,15,13,15,20,7,6.0,7,70,Rural,Data Analyst,55130,0 +68870,Male,34,Bachelors,15,69,66,81,64,1.0,7,69,Urban,ML Engineer,131101,1 +68871,Male,50,PhD,17,64,53,21,6,1.0,3,86,Rural,Manager,71260,0 +68872,Female,47,Bachelors,1,24,25,10,6,7.0,1,76,Urban,HR Executive,54573,0 +68873,Male,33,Masters,18,6,34,92,49,4.0,4,63,Semi-Urban,ML Engineer,111890,0 +68874,Female,52,High School,15,93,10,43,36,8.0,3,80,Urban,Data Analyst,38304,0 +68875,Female,33,PhD,6,49,17,92,63,5.0,0,0,Urban,Manager,83367,0 +68876,Male,56,Diploma,10,7,79,9,29,4.0,1,58,Semi-Urban,Software Engineer,111221,0 +68877,Male,40,Bachelors,1,5,13,74,10,2.0,0,6,Urban,ML Engineer,130481,0 +68878,Female,34,Bachelors,8,68,79,46,32,2.0,0,41,Urban,Data Analyst,30155,0 +68879,Male,50,Bachelors,8,78,43,57,91,0.0,1,53,Urban,Software Engineer,101813,0 +68880,Male,49,Masters,10,59,54,66,89,5.0,4,56,Urban,Data Analyst,128729,1 +68881,Female,41,Masters,4,90,20,21,27,7.0,0,5,Urban,Software Engineer,141133,0 +68882,Male,44,High School,12,76,85,68,5,5.0,5,21,Urban,HR Executive,26167,1 +68883,Male,58,PhD,18,99,82,86,3,0.0,3,91,Urban,HR Executive,42926,1 +68884,Male,22,High School,16,30,64,19,4,7.0,5,47,Urban,ML Engineer,135284,0 +68885,Female,46,High School,3,97,5,82,73,2.0,7,42,Semi-Urban,Data Analyst,62060,0 +68886,Female,26,High School,3,98,93,95,8,3.0,0,13,Urban,Data Analyst,31954,1 +68887,Male,56,Bachelors,12,91,73,97,81,1.0,5,83,Semi-Urban,Software Engineer,143681,1 +68888,Male,52,PhD,6,85,83,24,82,2.0,6,68,Urban,Manager,91537,1 +68889,Male,32,Bachelors,11,41,67,64,80,0.0,3,97,Urban,Manager,99851,1 +68890,Female,56,Masters,6,5,52,29,29,0.0,1,31,Urban,Software Engineer,125968,0 +68891,Female,51,High School,17,43,65,22,93,5.0,7,41,Rural,HR Executive,105890,0 +68892,Male,33,High School,15,52,80,87,62,9.0,5,83,Rural,Data Analyst,61208,1 +68893,Female,53,Bachelors,2,66,98,70,55,1.0,4,48,Rural,Software Engineer,67579,1 +68894,Female,27,Masters,5,58,75,14,14,8.0,7,98,Semi-Urban,HR Executive,126058,1 +68895,Female,36,Masters,16,41,49,94,65,9.0,3,16,Rural,Data Analyst,115961,0 +68896,Other,36,High School,6,91,81,41,5,8.0,5,14,Urban,ML Engineer,81400,0 +68897,Male,57,Bachelors,17,34,46,60,34,8.0,7,17,Urban,Data Analyst,143345,0 +68898,Female,37,Bachelors,16,13,8,17,4,1.0,1,5,Rural,Manager,32114,0 +68899,Male,27,Bachelors,10,5,24,82,34,7.0,6,11,Rural,Software Engineer,70636,0 +68900,Female,48,Bachelors,12,67,93,44,4,5.0,1,4,Urban,Data Analyst,91012,0 +68901,Female,41,Masters,14,4,72,46,26,2.0,2,57,Urban,Data Analyst,40108,0 +68902,Male,58,Diploma,15,96,39,52,53,9.0,7,78,Semi-Urban,HR Executive,62212,1 +68903,Female,27,Bachelors,11,26,31,59,2,0.0,7,83,Semi-Urban,ML Engineer,26377,0 +68904,Male,36,Diploma,7,6,58,72,5,1.0,4,44,Urban,HR Executive,83936,0 +68905,Female,26,Diploma,10,82,94,53,75,3.0,2,28,Urban,HR Executive,136504,1 +68906,Male,55,Bachelors,11,16,52,19,66,7.0,1,35,Urban,Manager,141766,0 +68907,Male,38,Bachelors,11,13,56,30,18,3.0,7,54,Semi-Urban,Data Analyst,78871,0 +68908,Female,58,Masters,7,14,60,68,37,0.0,6,85,Urban,Data Analyst,78114,0 +68909,Male,40,High School,19,79,86,10,93,7.0,6,83,Urban,ML Engineer,29495,1 +68910,Male,46,Bachelors,2,80,7,10,8,6.0,6,34,Urban,ML Engineer,145964,0 +68911,Male,27,Masters,8,37,18,4,38,1.0,1,79,Semi-Urban,ML Engineer,48830,0 +68912,Female,36,High School,17,76,26,98,79,1.0,1,95,Urban,Data Analyst,75230,1 +68913,Female,52,High School,15,97,43,9,7,3.0,2,21,Urban,HR Executive,27290,0 +68914,Male,53,Bachelors,12,65,36,51,36,2.0,3,89,Semi-Urban,Manager,83438,1 +68915,Female,38,High School,14,97,1,59,59,4.0,7,47,Urban,Data Analyst,20280,0 +68916,Female,45,Bachelors,14,11,1,49,84,7.0,5,8,Semi-Urban,ML Engineer,102036,0 +68917,Female,42,Masters,7,13,42,37,75,6.0,2,64,Urban,ML Engineer,23120,0 +68918,Female,47,PhD,0,37,94,35,33,4.0,7,78,Semi-Urban,Manager,107288,1 +68919,Male,53,Bachelors,16,18,89,47,80,1.0,5,98,Urban,Software Engineer,88273,1 +68920,Female,35,Bachelors,3,77,27,38,78,7.0,7,21,Urban,Manager,36866,0 +68921,Other,29,High School,16,68,51,25,73,3.0,0,98,Urban,Software Engineer,90355,1 +68922,Female,32,PhD,14,26,55,18,27,0.0,0,42,Rural,HR Executive,64297,0 +68923,Male,33,Bachelors,2,48,37,98,10,3.0,2,30,Urban,ML Engineer,62208,0 +68924,Male,39,Masters,18,17,55,74,59,1.0,1,39,Rural,HR Executive,82902,0 +68925,Female,40,Bachelors,2,68,13,77,47,3.0,2,12,Rural,Data Analyst,83508,0 +68926,Male,21,Masters,7,83,7,46,73,7.0,0,26,Urban,HR Executive,63198,0 +68927,Male,36,Bachelors,9,90,35,28,28,7.0,7,38,Rural,Manager,33233,0 +68928,Female,22,Masters,18,39,41,50,51,7.0,4,88,Rural,Data Analyst,118494,0 +68929,Male,56,PhD,13,69,4,45,50,3.0,3,67,Semi-Urban,Software Engineer,133334,0 +68930,Male,52,Bachelors,6,28,64,79,53,2.0,2,22,Urban,Software Engineer,64216,0 +68931,Other,56,Bachelors,5,66,19,32,32,6.0,6,17,Rural,Software Engineer,88249,0 +68932,Female,55,Bachelors,17,65,97,29,74,2.0,3,89,Urban,Manager,62344,1 +68933,Male,58,High School,1,47,82,9,86,4.0,4,44,Semi-Urban,HR Executive,79309,0 +68934,Male,39,Masters,0,42,8,71,9,8.0,0,36,Semi-Urban,HR Executive,98204,0 +68935,Female,55,Bachelors,14,80,50,32,17,3.0,7,90,Semi-Urban,Data Analyst,97780,1 +68936,Female,22,Bachelors,7,33,19,66,12,2.0,6,97,Urban,ML Engineer,45184,0 +68937,Female,39,Bachelors,7,22,44,71,83,0.0,0,13,Rural,ML Engineer,39916,0 +68938,Male,30,Bachelors,12,29,14,15,65,2.0,0,31,Rural,Data Analyst,120438,0 +68939,Female,24,Masters,4,63,54,16,54,2.0,3,31,Urban,Manager,136979,0 +68940,Male,32,High School,15,98,42,2,82,1.0,5,33,Urban,Manager,118258,0 +68941,Female,58,Bachelors,2,48,87,56,74,8.0,1,5,Semi-Urban,Software Engineer,103453,0 +68942,Female,51,Masters,2,6,59,49,93,1.0,6,49,Urban,Manager,132749,0 +68943,Male,24,High School,9,84,95,22,41,6.0,4,91,Rural,HR Executive,148339,1 +68944,Male,58,High School,4,11,33,67,53,4.0,4,34,Urban,Data Analyst,129023,0 +68945,Female,21,Bachelors,14,83,84,38,14,5.0,1,4,Urban,Manager,115715,0 +68946,Female,38,Diploma,12,18,51,65,70,6.0,4,73,Urban,Data Analyst,130469,0 +68947,Male,52,Bachelors,11,2,17,47,68,6.0,7,81,Urban,Data Analyst,26583,0 +68948,Male,48,Bachelors,17,83,10,28,3,2.0,7,86,Rural,Manager,50529,0 +68949,Male,27,High School,5,88,91,10,6,5.0,0,7,Semi-Urban,ML Engineer,111135,0 +68950,Male,24,Bachelors,15,45,73,69,25,6.0,2,36,Rural,Manager,89392,0 +68951,Male,23,Diploma,8,37,34,95,67,4.0,2,84,Urban,Manager,138154,1 +68952,Female,40,Diploma,15,24,3,77,98,4.0,1,15,Urban,HR Executive,132753,0 +68953,Female,33,High School,5,43,47,42,72,8.0,4,84,Urban,ML Engineer,71053,0 +68954,Other,41,Bachelors,2,98,96,55,29,5.0,6,80,Urban,Data Analyst,23045,1 +68955,Female,41,High School,11,3,45,98,59,1.0,0,57,Urban,Manager,91008,0 +68956,Female,21,Diploma,12,50,64,7,29,3.0,1,77,Semi-Urban,Manager,56664,0 +68957,Male,45,Bachelors,2,40,92,52,83,4.0,5,4,Semi-Urban,Manager,92283,0 +68958,Female,59,Bachelors,4,91,26,29,37,6.0,5,9,Urban,Data Analyst,119969,0 +68959,Male,44,Masters,18,32,37,29,82,4.0,4,68,Urban,Software Engineer,67841,0 +68960,Male,42,Bachelors,14,47,81,57,44,9.0,0,25,Urban,HR Executive,38934,0 +68961,Male,36,Masters,19,51,26,40,34,0.0,4,41,Urban,Data Analyst,67584,0 +68962,Male,38,Masters,19,9,1,43,83,0.0,1,90,Urban,Data Analyst,45802,0 +68963,Male,41,Diploma,16,57,78,23,55,4.0,2,35,Urban,Software Engineer,104739,0 +68964,Male,37,High School,2,68,10,41,10,5.0,2,27,Urban,Software Engineer,75903,0 +68965,Male,46,Bachelors,16,76,13,4,55,4.0,3,54,Rural,Data Analyst,92716,0 +68966,Male,33,Masters,3,42,14,60,3,3.0,0,37,Rural,Software Engineer,60992,0 +68967,Female,21,Bachelors,1,89,3,71,44,3.0,4,89,Urban,Manager,37768,1 +68968,Male,46,Masters,4,9,21,47,61,9.0,0,72,Urban,Software Engineer,75382,0 +68969,Male,46,Diploma,10,10,16,29,98,0.0,0,41,Urban,Data Analyst,128933,0 +68970,Male,36,PhD,0,77,57,31,62,3.0,4,15,Semi-Urban,ML Engineer,51086,0 +68971,Male,41,Bachelors,14,49,47,32,56,1.0,3,81,Rural,Manager,71529,0 +68972,Female,43,Bachelors,15,99,10,96,51,8.0,4,68,Urban,ML Engineer,43855,1 +68973,Female,28,Diploma,13,50,73,79,22,4.0,0,3,Rural,Software Engineer,149384,0 +68974,Male,39,Masters,10,96,0,86,77,5.0,4,78,Urban,HR Executive,57640,1 +68975,Male,59,Bachelors,15,1,49,93,39,2.0,5,96,Urban,Software Engineer,39943,1 +68976,Male,42,Diploma,9,35,66,0,94,4.0,2,58,Urban,HR Executive,94251,0 +68977,Male,31,High School,7,0,38,80,72,8.0,3,52,Urban,HR Executive,47084,0 +68978,Male,39,High School,5,37,16,9,16,9.0,1,17,Urban,Manager,129885,0 +68979,Male,54,Bachelors,13,87,79,81,10,8.0,1,63,Urban,HR Executive,95424,1 +68980,Male,26,Masters,13,35,7,88,93,0.0,2,24,Rural,Data Analyst,122862,0 +68981,Other,56,Bachelors,5,80,29,58,56,7.0,1,62,Urban,HR Executive,105895,0 +68982,Female,57,Bachelors,13,14,62,71,59,9.0,0,53,Rural,HR Executive,97487,0 +68983,Female,44,High School,13,37,54,25,84,1.0,0,6,Semi-Urban,Data Analyst,104960,0 +68984,Female,49,Bachelors,13,28,86,74,23,7.0,6,42,Rural,HR Executive,100428,0 +68985,Male,44,PhD,6,1,16,11,67,8.0,0,78,Urban,ML Engineer,63016,0 +68986,Male,39,Masters,11,82,97,71,44,2.0,0,26,Rural,HR Executive,144404,1 +68987,Male,40,Bachelors,15,92,78,31,39,2.0,4,33,Rural,Manager,59523,0 +68988,Female,59,Masters,16,50,88,74,86,2.0,2,12,Urban,HR Executive,125990,0 +68989,Female,44,Masters,7,5,90,51,95,7.0,6,83,Urban,HR Executive,37172,0 +68990,Male,28,Bachelors,1,74,98,92,78,5.0,7,79,Urban,Data Analyst,82484,1 +68991,Male,52,Masters,10,7,79,59,7,3.0,5,33,Semi-Urban,Software Engineer,73338,0 +68992,Female,25,High School,18,51,8,39,76,7.0,2,47,Urban,Software Engineer,132218,0 +68993,Male,27,High School,19,30,81,52,7,2.0,0,4,Urban,Manager,64799,0 +68994,Female,38,Bachelors,17,34,82,54,32,5.0,5,55,Semi-Urban,Software Engineer,105120,0 +68995,Male,29,High School,16,35,40,76,62,4.0,0,66,Semi-Urban,Software Engineer,131121,0 +68996,Male,51,PhD,12,0,71,7,74,3.0,2,1,Semi-Urban,Data Analyst,44351,0 +68997,Female,47,Diploma,3,70,23,26,67,5.0,0,62,Semi-Urban,Manager,107158,0 +68998,Male,24,Masters,13,49,65,55,24,3.0,3,14,Urban,Manager,20717,0 +68999,Male,22,Bachelors,8,73,73,23,47,5.0,7,1,Urban,ML Engineer,34449,0 +69000,Female,34,PhD,9,94,82,96,39,0.0,7,49,Semi-Urban,Data Analyst,149609,1 +69001,Male,27,Masters,16,91,20,13,41,5.0,7,49,Urban,ML Engineer,87164,0 +69002,Male,55,Bachelors,14,73,17,24,20,7.0,0,66,Urban,Software Engineer,113840,0 +69003,Male,38,Diploma,3,10,16,65,85,6.0,2,50,Urban,ML Engineer,46884,0 +69004,Male,21,Masters,16,29,40,32,2,3.0,1,63,Semi-Urban,ML Engineer,94497,0 +69005,Male,58,Bachelors,8,80,84,96,55,6.0,2,83,Urban,ML Engineer,128240,1 +69006,Male,51,Bachelors,11,98,85,76,57,7.0,6,63,Rural,Manager,91481,1 +69007,Male,39,Bachelors,17,16,36,87,49,4.0,7,76,Urban,ML Engineer,77462,0 +69008,Male,32,Bachelors,18,92,18,98,1,7.0,0,30,Urban,ML Engineer,54091,1 +69009,Female,46,Bachelors,19,43,72,20,75,8.0,7,26,Semi-Urban,HR Executive,47314,0 +69010,Male,25,Diploma,8,19,21,76,37,1.0,1,48,Urban,ML Engineer,61176,0 +69011,Female,52,High School,17,35,87,47,19,2.0,6,11,Urban,HR Executive,21803,0 +69012,Male,37,Diploma,12,56,59,2,12,7.0,0,87,Urban,Manager,64671,0 +69013,Male,32,Bachelors,4,73,71,47,89,5.0,2,79,Rural,ML Engineer,74357,1 +69014,Male,28,Diploma,4,74,78,71,56,0.0,0,65,Semi-Urban,Manager,130961,1 +69015,Female,41,Bachelors,18,69,93,72,63,1.0,4,32,Semi-Urban,Manager,69335,1 +69016,Male,36,High School,18,24,87,68,43,6.0,7,7,Urban,Data Analyst,35178,0 +69017,Male,31,Diploma,19,50,16,1,79,6.0,3,12,Semi-Urban,ML Engineer,41393,0 +69018,Male,43,Bachelors,15,61,55,30,27,6.0,2,58,Semi-Urban,HR Executive,59667,0 +69019,Female,31,Masters,1,92,24,58,73,8.0,2,13,Urban,Manager,143830,0 +69020,Female,34,Bachelors,15,59,47,94,38,9.0,1,58,Semi-Urban,Manager,117444,1 +69021,Male,27,Bachelors,15,81,96,25,57,7.0,3,48,Urban,HR Executive,94615,1 +69022,Male,52,High School,7,32,54,55,91,1.0,4,76,Rural,ML Engineer,26714,0 +69023,Male,32,Bachelors,18,74,68,76,73,2.0,0,78,Rural,Manager,139566,1 +69024,Other,55,High School,1,45,11,80,49,8.0,3,16,Urban,Manager,90279,0 +69025,Female,45,Diploma,1,71,9,88,69,2.0,5,24,Rural,Manager,77892,0 +69026,Male,54,Masters,3,26,59,12,21,3.0,3,35,Rural,Manager,79728,0 +69027,Male,23,Bachelors,2,17,44,19,19,5.0,6,94,Semi-Urban,HR Executive,65987,0 +69028,Male,59,Diploma,19,92,2,39,40,5.0,6,0,Rural,Data Analyst,101364,0 +69029,Female,38,Bachelors,19,25,85,3,87,3.0,4,15,Urban,Software Engineer,28080,0 +69030,Male,41,Masters,13,1,20,46,64,1.0,3,75,Urban,Manager,120870,0 +69031,Female,52,Bachelors,12,89,94,70,36,1.0,4,41,Semi-Urban,Data Analyst,59087,1 +69032,Male,46,Bachelors,19,92,62,81,97,1.0,4,65,Rural,Software Engineer,95639,1 +69033,Male,37,Masters,13,73,22,33,11,9.0,0,68,Rural,Manager,140791,0 +69034,Male,46,Bachelors,9,67,1,24,26,6.0,6,76,Semi-Urban,Software Engineer,130256,0 +69035,Female,24,High School,18,88,88,20,95,4.0,7,20,Semi-Urban,Data Analyst,140013,0 +69036,Male,55,High School,6,17,17,54,63,9.0,1,8,Urban,Manager,78327,0 +69037,Female,35,Bachelors,13,97,47,54,94,8.0,1,39,Urban,HR Executive,136961,0 +69038,Male,55,Bachelors,9,6,66,43,62,8.0,4,28,Urban,Software Engineer,115809,0 +69039,Male,45,Bachelors,7,55,22,89,25,8.0,4,54,Urban,Data Analyst,70233,0 +69040,Female,28,Masters,2,51,97,42,18,3.0,4,72,Semi-Urban,ML Engineer,39067,1 +69041,Female,27,Bachelors,12,89,66,19,3,8.0,6,92,Urban,Software Engineer,65253,1 +69042,Female,48,Diploma,13,22,49,39,3,7.0,0,98,Urban,HR Executive,87493,0 +69043,Male,40,Bachelors,18,75,79,71,13,1.0,5,69,Urban,ML Engineer,100829,1 +69044,Male,57,Masters,10,6,10,74,50,6.0,5,27,Semi-Urban,Manager,39112,0 +69045,Male,31,Bachelors,19,82,63,75,26,3.0,5,47,Urban,Software Engineer,148586,1 +69046,Male,43,Masters,2,62,97,22,42,5.0,7,39,Urban,Software Engineer,27619,0 +69047,Female,56,Diploma,8,56,83,52,65,9.0,7,19,Urban,HR Executive,37500,0 +69048,Male,29,Masters,7,31,49,51,5,8.0,6,78,Rural,HR Executive,143685,0 +69049,Male,32,Diploma,13,9,71,30,32,1.0,2,80,Urban,Software Engineer,47912,0 +69050,Male,54,High School,4,0,20,45,73,6.0,1,62,Urban,Software Engineer,108712,0 +69051,Other,51,Masters,8,3,46,72,94,9.0,4,64,Urban,ML Engineer,144552,0 +69052,Male,29,High School,6,6,10,16,30,8.0,5,17,Urban,Manager,96432,0 +69053,Male,34,Diploma,9,61,21,92,50,5.0,1,48,Urban,ML Engineer,82508,0 +69054,Female,34,Diploma,15,3,87,58,3,5.0,1,36,Rural,ML Engineer,50601,0 +69055,Male,58,Bachelors,8,51,37,25,13,7.0,5,0,Urban,Software Engineer,111765,0 +69056,Male,37,Bachelors,11,78,38,29,2,1.0,7,71,Semi-Urban,Software Engineer,68471,0 +69057,Male,54,Masters,11,94,28,39,83,8.0,1,21,Urban,Manager,145724,0 +69058,Female,35,Bachelors,1,5,61,96,60,3.0,7,18,Urban,Data Analyst,144734,0 +69059,Female,41,Diploma,11,81,58,86,16,6.0,3,28,Semi-Urban,ML Engineer,93821,1 +69060,Male,30,Bachelors,14,39,98,62,2,8.0,4,80,Rural,Data Analyst,27846,1 +69061,Male,40,Bachelors,4,98,84,76,32,0.0,4,4,Urban,Software Engineer,95133,1 +69062,Male,38,Bachelors,10,63,57,51,73,2.0,7,68,Urban,Manager,88624,1 +69063,Male,30,High School,12,91,43,2,38,2.0,0,28,Semi-Urban,Manager,58045,0 +69064,Male,22,PhD,1,81,64,83,62,7.0,7,45,Rural,Data Analyst,77836,1 +69065,Male,32,High School,14,58,65,81,74,0.0,3,98,Semi-Urban,HR Executive,74320,1 +69066,Female,48,Diploma,7,29,35,63,5,9.0,0,4,Urban,Data Analyst,22029,0 +69067,Male,26,High School,18,32,8,88,31,4.0,6,68,Rural,Software Engineer,105642,0 +69068,Male,57,Masters,5,13,96,61,49,4.0,2,93,Semi-Urban,Software Engineer,94642,1 +69069,Female,26,Diploma,7,79,87,29,23,7.0,5,45,Urban,Data Analyst,98892,0 +69070,Female,52,High School,11,73,69,89,76,6.0,6,84,Urban,Manager,89539,1 +69071,Male,48,Diploma,16,68,18,78,37,5.0,6,35,Rural,Data Analyst,66556,0 +69072,Other,56,Bachelors,10,55,88,65,83,5.0,1,24,Urban,HR Executive,64740,0 +69073,Male,39,Masters,13,48,24,27,72,4.0,1,38,Urban,HR Executive,131293,0 +69074,Male,39,High School,18,22,57,11,30,5.0,0,63,Semi-Urban,Data Analyst,102655,0 +69075,Male,33,Bachelors,19,29,19,2,9,9.0,2,61,Rural,Manager,25362,0 +69076,Female,24,Bachelors,4,70,54,13,19,5.0,4,93,Urban,ML Engineer,122842,0 +69077,Female,58,Bachelors,10,19,31,11,70,3.0,7,36,Semi-Urban,HR Executive,67023,0 +69078,Female,21,Masters,5,26,29,70,86,4.0,3,78,Urban,ML Engineer,41380,0 +69079,Male,25,Diploma,2,49,5,82,98,8.0,1,73,Urban,HR Executive,43172,0 +69080,Female,41,High School,4,10,42,41,0,6.0,5,52,Rural,Data Analyst,51238,0 +69081,Male,29,Masters,10,64,78,15,57,9.0,3,49,Urban,Manager,127419,0 +69082,Female,33,High School,11,31,94,89,72,1.0,5,83,Rural,Data Analyst,83448,1 +69083,Male,42,Bachelors,4,7,15,72,61,2.0,6,46,Semi-Urban,Software Engineer,71484,0 +69084,Male,36,Masters,13,53,61,43,25,0.0,7,53,Urban,Data Analyst,68877,0 +69085,Other,28,High School,10,6,42,42,45,3.0,0,76,Urban,Manager,58967,0 +69086,Male,59,Diploma,1,43,95,8,28,8.0,3,48,Semi-Urban,HR Executive,143956,0 +69087,Male,58,High School,11,33,83,30,16,2.0,3,72,Urban,HR Executive,115642,0 +69088,Male,59,High School,5,62,31,29,82,8.0,4,27,Urban,ML Engineer,99938,0 +69089,Female,44,Diploma,0,53,88,13,67,9.0,1,97,Urban,Data Analyst,69190,1 +69090,Male,32,High School,6,89,5,28,71,5.0,6,8,Urban,Data Analyst,57156,0 +69091,Male,43,PhD,1,91,16,83,37,7.0,1,42,Urban,Data Analyst,20691,0 +69092,Male,58,Bachelors,17,80,6,2,39,1.0,1,25,Semi-Urban,Manager,75016,0 +69093,Male,41,Bachelors,2,94,78,48,64,9.0,7,40,Urban,Data Analyst,142113,1 +69094,Female,47,Diploma,18,59,11,19,72,7.0,3,41,Semi-Urban,Manager,87385,0 +69095,Other,57,Bachelors,16,75,48,80,64,3.0,6,25,Semi-Urban,Data Analyst,124293,0 +69096,Other,44,Masters,1,58,84,57,89,4.0,3,27,Urban,Manager,113880,0 +69097,Male,29,Diploma,7,83,84,77,0,2.0,5,41,Semi-Urban,Data Analyst,136326,1 +69098,Female,40,Diploma,13,43,4,18,6,3.0,0,20,Rural,HR Executive,109940,0 +69099,Male,53,Diploma,7,76,98,40,45,1.0,4,17,Rural,Software Engineer,64219,0 +69100,Male,51,Masters,17,13,36,23,58,0.0,1,23,Urban,Data Analyst,82660,0 +69101,Female,32,Masters,2,96,26,86,89,2.0,4,10,Urban,Software Engineer,118174,0 +69102,Female,41,Diploma,15,91,59,88,67,0.0,3,68,Semi-Urban,Data Analyst,44366,1 +69103,Male,34,Diploma,8,92,4,31,58,9.0,2,52,Urban,HR Executive,116671,0 +69104,Female,52,Bachelors,2,18,2,45,16,1.0,4,43,Semi-Urban,Data Analyst,125896,0 +69105,Female,30,Masters,7,56,86,50,14,4.0,6,36,Urban,ML Engineer,36866,0 +69106,Female,49,Diploma,11,9,9,90,66,0.0,7,78,Semi-Urban,ML Engineer,106490,0 +69107,Female,55,Bachelors,0,42,3,78,37,6.0,3,82,Urban,Software Engineer,41946,0 +69108,Male,56,Diploma,15,5,40,74,81,2.0,7,52,Semi-Urban,Software Engineer,58596,0 +69109,Female,50,High School,13,23,33,74,88,7.0,7,51,Urban,ML Engineer,92843,0 +69110,Male,21,Bachelors,5,28,31,11,60,4.0,1,95,Urban,HR Executive,58369,0 +69111,Male,50,Bachelors,16,41,16,72,52,4.0,4,83,Urban,HR Executive,30170,0 +69112,Male,40,Bachelors,3,99,42,58,50,2.0,7,15,Semi-Urban,Data Analyst,70332,0 +69113,Female,44,Bachelors,8,60,8,61,37,4.0,5,52,Urban,Manager,89879,0 +69114,Female,29,Bachelors,18,75,54,31,32,7.0,2,35,Semi-Urban,Data Analyst,23530,0 +69115,Other,50,Diploma,14,46,86,73,39,1.0,3,77,Urban,HR Executive,93499,1 +69116,Male,37,Masters,15,46,31,39,88,7.0,0,60,Urban,Data Analyst,44335,0 +69117,Male,42,Diploma,12,54,21,3,86,3.0,6,47,Urban,Data Analyst,28362,0 +69118,Female,31,Masters,14,18,53,21,27,6.0,2,84,Urban,HR Executive,98505,0 +69119,Female,38,Bachelors,16,99,14,35,63,6.0,3,49,Urban,Data Analyst,80052,0 +69120,Female,53,Bachelors,11,0,78,22,53,9.0,3,30,Semi-Urban,Manager,118491,0 +69121,Male,31,High School,1,85,60,93,50,4.0,7,18,Urban,Software Engineer,62676,1 +69122,Female,43,High School,12,75,97,40,90,1.0,2,92,Urban,ML Engineer,143163,1 +69123,Male,25,High School,0,18,91,97,51,1.0,6,97,Rural,Data Analyst,104490,1 +69124,Female,33,PhD,3,86,57,56,57,5.0,6,45,Semi-Urban,Manager,62266,1 +69125,Male,29,Masters,15,36,92,40,53,8.0,4,11,Urban,ML Engineer,53097,0 +69126,Male,58,High School,0,8,65,31,63,4.0,4,54,Urban,HR Executive,81432,0 +69127,Female,41,Diploma,1,12,87,12,26,9.0,2,56,Urban,ML Engineer,22671,0 +69128,Male,31,PhD,15,94,96,60,5,8.0,2,10,Urban,HR Executive,103872,1 +69129,Male,46,High School,8,78,19,32,2,9.0,2,24,Semi-Urban,Software Engineer,136464,0 +69130,Male,32,Masters,15,96,10,2,76,3.0,1,63,Rural,Manager,118061,0 +69131,Male,23,Bachelors,9,48,72,9,40,1.0,6,91,Urban,Data Analyst,116441,0 +69132,Male,44,High School,2,87,62,43,22,0.0,6,34,Urban,HR Executive,22839,0 +69133,Male,27,Bachelors,15,35,67,61,84,1.0,5,89,Urban,Data Analyst,29031,1 +69134,Male,40,Bachelors,0,55,8,18,6,9.0,1,71,Urban,Data Analyst,56986,0 +69135,Male,41,Diploma,17,81,69,17,97,6.0,6,94,Urban,Data Analyst,126900,1 +69136,Male,52,Bachelors,1,2,11,63,71,0.0,5,29,Urban,Software Engineer,30830,0 +69137,Male,49,Bachelors,15,92,24,39,93,4.0,0,74,Semi-Urban,Data Analyst,118224,0 +69138,Male,34,Bachelors,5,77,77,87,26,9.0,1,66,Rural,Manager,148918,1 +69139,Male,26,Bachelors,14,54,5,80,62,5.0,7,63,Rural,Data Analyst,52725,0 +69140,Female,52,Bachelors,11,69,4,89,39,6.0,2,11,Urban,Software Engineer,44455,0 +69141,Female,38,Bachelors,15,59,87,54,11,0.0,6,30,Rural,Data Analyst,81916,0 +69142,Female,57,Bachelors,4,95,72,13,27,4.0,4,83,Semi-Urban,HR Executive,144006,1 +69143,Male,31,Masters,0,47,76,29,20,9.0,1,69,Rural,ML Engineer,85947,0 +69144,Male,24,High School,17,9,84,21,35,3.0,7,95,Urban,Software Engineer,50279,0 +69145,Male,44,Masters,9,62,25,64,72,1.0,4,70,Rural,HR Executive,127252,0 +69146,Female,33,Diploma,15,29,27,46,44,6.0,2,79,Rural,ML Engineer,97923,0 +69147,Male,26,Diploma,14,67,84,96,48,8.0,0,61,Semi-Urban,Manager,101703,1 +69148,Female,37,Bachelors,18,82,8,96,50,7.0,2,33,Urban,Software Engineer,111731,0 +69149,Female,47,Diploma,8,26,51,62,85,3.0,3,69,Urban,HR Executive,108346,0 +69150,Female,46,Bachelors,15,51,58,21,82,0.0,0,9,Rural,HR Executive,20490,0 +69151,Female,29,Masters,9,28,80,37,27,8.0,5,53,Rural,Manager,136129,0 +69152,Female,55,Bachelors,2,11,46,99,96,3.0,4,19,Urban,Data Analyst,38034,0 +69153,Male,44,Bachelors,1,87,95,74,25,8.0,6,17,Urban,ML Engineer,59427,1 +69154,Other,54,Diploma,13,4,71,30,81,6.0,5,76,Urban,Data Analyst,45571,0 +69155,Female,48,High School,4,25,41,16,47,7.0,0,73,Semi-Urban,Software Engineer,43110,0 +69156,Female,55,High School,14,60,41,5,80,3.0,5,58,Urban,HR Executive,122074,0 +69157,Male,24,Bachelors,14,64,45,35,29,5.0,5,84,Urban,Data Analyst,68432,0 +69158,Male,43,Bachelors,8,73,57,21,73,0.0,6,4,Urban,HR Executive,116336,0 +69159,Female,31,Bachelors,2,68,50,64,41,3.0,6,75,Urban,HR Executive,92197,1 +69160,Male,52,Bachelors,1,88,38,60,40,1.0,1,40,Semi-Urban,HR Executive,59407,0 +69161,Male,33,Bachelors,1,29,14,75,6,5.0,3,61,Semi-Urban,HR Executive,100468,0 +69162,Male,29,Bachelors,1,40,49,81,15,9.0,1,38,Semi-Urban,Manager,71051,0 +69163,Male,41,Diploma,6,87,75,63,84,3.0,2,39,Urban,Data Analyst,37117,1 +69164,Male,34,Diploma,2,18,96,6,1,9.0,2,22,Semi-Urban,Software Engineer,112374,0 +69165,Male,23,Masters,13,70,72,46,61,2.0,4,57,Urban,Manager,23323,1 +69166,Male,39,Bachelors,4,59,77,22,11,4.0,3,6,Semi-Urban,Software Engineer,55572,0 +69167,Male,55,High School,10,44,15,48,10,1.0,7,0,Rural,HR Executive,120536,0 +69168,Male,28,Diploma,13,33,84,37,56,5.0,1,81,Urban,Software Engineer,115891,1 +69169,Other,49,PhD,2,0,10,59,8,2.0,3,44,Urban,Software Engineer,85174,0 +69170,Male,42,Masters,16,6,84,69,53,3.0,5,10,Urban,HR Executive,146869,0 +69171,Male,46,Bachelors,7,57,78,94,7,8.0,5,65,Urban,Software Engineer,130080,1 +69172,Male,31,Masters,18,66,33,28,38,1.0,5,35,Urban,ML Engineer,97345,0 +69173,Male,30,High School,0,49,63,32,66,3.0,5,86,Urban,Data Analyst,118036,0 +69174,Male,50,Masters,5,95,26,98,7,9.0,3,57,Urban,HR Executive,146298,1 +69175,Other,47,Masters,17,52,35,41,64,4.0,5,47,Rural,ML Engineer,33706,0 +69176,Male,33,High School,8,23,33,63,30,3.0,7,4,Rural,Manager,130155,0 +69177,Male,53,Bachelors,13,53,83,37,75,8.0,6,91,Semi-Urban,ML Engineer,23145,1 +69178,Female,39,Bachelors,9,4,99,15,63,1.0,1,72,Urban,Manager,85074,0 +69179,Female,47,Bachelors,10,26,78,26,24,8.0,4,85,Rural,Data Analyst,135624,0 +69180,Female,58,Bachelors,4,48,75,89,77,1.0,0,16,Rural,Manager,49728,0 +69181,Male,49,Masters,12,90,53,9,34,9.0,4,11,Semi-Urban,Data Analyst,48759,0 +69182,Male,30,Diploma,9,93,41,19,92,1.0,5,95,Urban,Manager,85589,1 +69183,Other,58,Masters,4,70,10,84,94,0.0,0,35,Semi-Urban,Software Engineer,87131,0 +69184,Female,47,High School,12,53,40,99,73,6.0,5,73,Urban,Manager,141166,1 +69185,Male,51,High School,5,56,3,36,94,9.0,6,11,Urban,Manager,59887,0 +69186,Male,52,Masters,1,74,62,4,20,3.0,0,41,Semi-Urban,ML Engineer,50459,0 +69187,Male,39,Bachelors,4,27,11,85,7,4.0,1,90,Semi-Urban,Software Engineer,104611,0 +69188,Male,36,Bachelors,1,23,84,83,96,1.0,1,48,Rural,Manager,110371,1 +69189,Male,22,Masters,15,81,92,19,63,9.0,7,45,Urban,ML Engineer,41806,1 +69190,Male,53,High School,19,95,78,21,1,7.0,5,16,Rural,Software Engineer,102235,0 +69191,Male,36,Masters,19,95,64,68,27,7.0,7,54,Rural,Data Analyst,108536,1 +69192,Male,26,Bachelors,11,37,3,8,54,4.0,4,7,Urban,HR Executive,23275,0 +69193,Male,31,PhD,18,25,31,17,86,7.0,0,67,Urban,Data Analyst,109946,0 +69194,Male,47,PhD,13,1,72,48,64,0.0,4,97,Semi-Urban,Manager,20892,0 +69195,Other,56,Masters,0,35,45,86,29,2.0,4,41,Rural,HR Executive,36771,0 +69196,Female,37,Bachelors,4,14,23,53,76,3.0,5,64,Semi-Urban,Data Analyst,125274,0 +69197,Male,35,Masters,1,50,20,28,83,8.0,0,44,Urban,Software Engineer,71437,0 +69198,Male,33,Masters,9,77,26,6,69,8.0,6,26,Semi-Urban,Manager,65119,0 +69199,Male,40,Masters,6,97,85,81,82,6.0,3,0,Urban,Data Analyst,53628,1 +69200,Female,45,Diploma,3,93,0,38,58,1.0,6,58,Urban,ML Engineer,80934,0 +69201,Male,21,Bachelors,0,30,5,59,49,5.0,2,89,Urban,HR Executive,88057,0 +69202,Other,38,Bachelors,17,61,34,12,24,5.0,6,68,Rural,Manager,109943,0 +69203,Female,46,Masters,6,20,3,78,47,2.0,1,58,Semi-Urban,Software Engineer,100924,0 +69204,Other,54,PhD,10,6,88,30,3,9.0,2,73,Rural,ML Engineer,93044,0 +69205,Male,37,High School,8,67,62,22,33,1.0,0,2,Semi-Urban,Software Engineer,117879,0 +69206,Female,25,Masters,7,36,8,30,67,0.0,0,89,Urban,Data Analyst,56632,0 +69207,Male,31,Masters,12,3,14,60,60,1.0,7,71,Urban,Software Engineer,75826,0 +69208,Male,36,High School,7,97,71,30,45,6.0,4,45,Semi-Urban,Software Engineer,78643,1 +69209,Female,35,PhD,8,4,56,82,79,8.0,3,29,Urban,Manager,37374,0 +69210,Male,31,Bachelors,5,55,32,48,16,8.0,7,57,Urban,Software Engineer,29395,0 +69211,Male,53,Bachelors,3,88,25,73,54,3.0,1,71,Urban,Manager,121613,1 +69212,Male,43,Bachelors,12,83,69,59,78,4.0,3,21,Semi-Urban,HR Executive,57467,0 +69213,Male,24,Masters,5,45,21,79,40,6.0,3,16,Urban,HR Executive,139572,0 +69214,Female,59,High School,0,88,91,95,94,0.0,1,1,Urban,Manager,87744,1 +69215,Female,50,Diploma,10,94,68,29,99,0.0,1,87,Urban,HR Executive,95258,1 +69216,Female,55,Bachelors,18,38,88,99,36,0.0,1,45,Rural,HR Executive,83624,1 +69217,Other,46,Bachelors,1,88,15,16,11,5.0,7,7,Urban,ML Engineer,130659,0 +69218,Male,34,PhD,2,76,86,85,60,6.0,5,50,Urban,Manager,64972,1 +69219,Male,23,PhD,8,55,47,16,87,1.0,4,62,Urban,HR Executive,21519,0 +69220,Male,34,Masters,13,40,95,33,29,9.0,7,38,Urban,ML Engineer,70435,0 +69221,Male,54,High School,8,67,65,42,46,5.0,3,84,Urban,Software Engineer,127656,1 +69222,Female,33,Bachelors,3,32,77,49,54,6.0,6,12,Urban,ML Engineer,94121,0 +69223,Male,57,Masters,9,29,84,19,76,0.0,2,28,Rural,HR Executive,132476,0 +69224,Male,54,Diploma,18,11,67,93,44,8.0,4,17,Urban,ML Engineer,88689,0 +69225,Female,52,High School,10,61,18,50,86,6.0,4,88,Semi-Urban,Manager,24744,0 +69226,Female,32,Bachelors,5,88,12,98,0,1.0,1,71,Semi-Urban,Data Analyst,144317,1 +69227,Male,42,Diploma,10,35,96,19,84,2.0,7,4,Rural,Manager,57816,0 +69228,Male,54,Diploma,10,66,24,68,5,5.0,3,36,Rural,Data Analyst,146208,0 +69229,Female,38,Diploma,0,45,99,23,70,3.0,0,17,Urban,ML Engineer,90243,0 +69230,Male,59,Masters,4,49,17,87,49,1.0,6,24,Urban,Software Engineer,103499,0 +69231,Other,50,Diploma,4,49,39,75,37,6.0,1,80,Urban,ML Engineer,132241,1 +69232,Male,38,Diploma,13,5,43,47,51,5.0,3,39,Rural,Data Analyst,109041,0 +69233,Male,42,Diploma,11,35,78,20,67,2.0,6,75,Rural,Data Analyst,48898,0 +69234,Male,22,High School,17,65,89,95,82,4.0,0,45,Urban,Data Analyst,144003,1 +69235,Male,38,Bachelors,5,80,25,75,82,6.0,0,91,Urban,Data Analyst,145915,1 +69236,Female,53,High School,18,70,91,15,21,2.0,6,22,Rural,Software Engineer,119654,0 +69237,Female,25,Masters,13,27,57,56,7,5.0,1,25,Rural,Software Engineer,147366,0 +69238,Other,37,Diploma,11,66,86,91,40,7.0,4,92,Urban,ML Engineer,22643,1 +69239,Female,33,High School,1,49,17,46,3,6.0,7,79,Semi-Urban,Manager,57629,0 +69240,Male,47,Bachelors,0,26,73,44,27,1.0,4,9,Rural,ML Engineer,117498,0 +69241,Male,50,Bachelors,19,0,74,91,63,1.0,7,80,Rural,Manager,116778,1 +69242,Male,33,High School,11,62,47,19,21,2.0,1,28,Urban,Manager,34002,0 +69243,Female,41,High School,2,62,64,30,40,9.0,5,82,Urban,ML Engineer,91574,0 +69244,Male,49,Bachelors,2,70,33,83,56,5.0,7,21,Urban,Data Analyst,55340,0 +69245,Male,40,Diploma,16,90,12,55,38,7.0,1,1,Rural,Data Analyst,132679,0 +69246,Male,22,PhD,5,42,2,91,2,6.0,4,35,Urban,ML Engineer,39741,0 +69247,Male,36,Masters,6,80,59,95,10,6.0,4,45,Urban,Data Analyst,20518,1 +69248,Male,24,Bachelors,12,99,11,11,75,6.0,5,51,Rural,HR Executive,93683,0 +69249,Female,33,Diploma,13,52,55,45,71,3.0,3,40,Rural,HR Executive,78052,0 +69250,Male,29,Bachelors,0,27,99,6,44,2.0,1,78,Urban,Software Engineer,113524,0 +69251,Male,55,Bachelors,6,45,71,9,4,4.0,4,83,Urban,Data Analyst,38301,0 +69252,Male,44,Bachelors,3,84,93,94,41,1.0,3,34,Semi-Urban,Data Analyst,78213,1 +69253,Female,26,Bachelors,1,0,50,55,64,2.0,4,20,Urban,HR Executive,45470,0 +69254,Male,24,Bachelors,5,89,43,90,26,6.0,0,84,Urban,Manager,82943,1 +69255,Male,37,Diploma,6,86,14,60,73,5.0,3,60,Urban,HR Executive,62891,0 +69256,Male,29,High School,17,63,52,5,10,0.0,2,29,Urban,Data Analyst,129574,0 +69257,Male,36,Bachelors,19,30,45,44,50,5.0,4,23,Semi-Urban,Data Analyst,49579,0 +69258,Male,58,Masters,14,77,14,56,84,6.0,1,38,Urban,Manager,82864,0 +69259,Female,45,PhD,5,50,85,90,45,2.0,1,61,Urban,ML Engineer,143417,1 +69260,Male,37,Diploma,14,49,89,57,44,4.0,3,20,Urban,HR Executive,67535,0 +69261,Female,58,Bachelors,11,44,0,93,56,4.0,7,29,Semi-Urban,HR Executive,86289,0 +69262,Female,52,Bachelors,12,94,64,54,12,3.0,6,65,Urban,ML Engineer,124247,1 +69263,Male,22,High School,13,37,38,86,7,0.0,2,70,Urban,ML Engineer,142563,0 +69264,Male,44,Bachelors,1,54,88,24,50,7.0,7,67,Urban,Software Engineer,24489,0 +69265,Female,38,PhD,10,16,20,74,90,0.0,1,48,Urban,ML Engineer,59347,0 +69266,Male,25,High School,10,57,55,65,38,3.0,0,9,Urban,HR Executive,72383,0 +69267,Male,39,Masters,0,88,71,59,94,9.0,5,8,Semi-Urban,ML Engineer,23074,0 +69268,Male,49,Masters,6,45,74,28,75,6.0,2,10,Rural,Data Analyst,89548,0 +69269,Male,40,Bachelors,5,27,16,80,9,4.0,2,23,Rural,ML Engineer,70327,0 +69270,Female,36,Bachelors,15,36,14,86,51,8.0,6,15,Urban,ML Engineer,75996,0 +69271,Male,31,High School,3,81,1,54,58,5.0,3,7,Rural,Manager,106301,0 +69272,Male,50,High School,6,88,61,11,29,5.0,4,19,Urban,Manager,97679,0 +69273,Male,23,Diploma,13,93,53,13,25,3.0,2,41,Urban,Software Engineer,143583,0 +69274,Female,44,Diploma,7,54,21,45,13,4.0,5,56,Urban,Manager,123291,0 +69275,Male,53,Bachelors,14,27,89,5,45,3.0,5,85,Urban,HR Executive,72445,0 +69276,Female,46,High School,9,14,18,17,1,6.0,3,24,Rural,Data Analyst,133197,0 +69277,Male,58,Bachelors,5,37,28,68,29,3.0,1,3,Urban,HR Executive,146590,0 +69278,Female,47,Masters,1,57,60,63,90,9.0,2,27,Urban,Data Analyst,63158,0 +69279,Male,57,PhD,8,15,46,45,92,6.0,3,33,Urban,Software Engineer,66428,0 +69280,Male,26,Bachelors,7,44,5,98,56,5.0,3,8,Urban,ML Engineer,43504,0 +69281,Female,24,Diploma,11,55,74,39,51,6.0,4,5,Urban,Data Analyst,85060,0 +69282,Male,55,Bachelors,12,29,72,69,51,1.0,6,29,Urban,HR Executive,76839,0 +69283,Female,38,PhD,3,81,42,57,4,1.0,1,20,Semi-Urban,Software Engineer,30136,0 +69284,Female,47,High School,8,52,17,63,72,5.0,1,75,Semi-Urban,ML Engineer,27528,0 +69285,Male,45,Bachelors,0,11,2,26,64,2.0,0,82,Semi-Urban,Data Analyst,147194,0 +69286,Female,31,Bachelors,8,61,70,49,31,2.0,4,1,Urban,Manager,94781,0 +69287,Male,36,Bachelors,3,21,44,99,30,3.0,5,72,Rural,ML Engineer,40249,1 +69288,Male,58,Diploma,5,13,69,25,69,9.0,2,31,Urban,Manager,81201,0 +69289,Male,52,Bachelors,15,39,99,96,50,7.0,1,18,Urban,HR Executive,26032,1 +69290,Female,29,Masters,14,93,37,77,31,0.0,1,86,Semi-Urban,Software Engineer,135549,1 +69291,Male,44,High School,13,59,2,90,66,0.0,5,2,Rural,Software Engineer,93088,0 +69292,Female,46,Bachelors,16,92,11,80,30,9.0,1,86,Urban,HR Executive,20746,1 +69293,Male,21,Masters,12,64,23,16,8,8.0,5,58,Urban,ML Engineer,89206,0 +69294,Female,50,Masters,4,67,75,13,89,2.0,4,0,Urban,Manager,30069,0 +69295,Female,26,Diploma,11,27,1,40,91,2.0,4,78,Urban,Data Analyst,145012,0 +69296,Male,29,Bachelors,19,16,7,68,19,1.0,6,85,Urban,Manager,140989,0 +69297,Female,30,Bachelors,15,36,68,11,3,9.0,5,95,Semi-Urban,Data Analyst,47669,0 +69298,Male,40,Diploma,19,5,1,70,61,8.0,7,74,Urban,Data Analyst,83423,0 +69299,Male,32,Diploma,0,55,88,59,83,3.0,2,7,Urban,Data Analyst,130782,0 +69300,Female,29,Bachelors,12,11,21,11,25,2.0,6,79,Urban,HR Executive,140426,0 +69301,Other,55,Diploma,18,88,31,73,4,0.0,5,65,Urban,ML Engineer,137403,1 +69302,Male,37,Masters,5,80,21,96,46,7.0,4,22,Semi-Urban,Data Analyst,26083,0 +69303,Male,21,Masters,2,80,99,99,23,6.0,3,91,Urban,ML Engineer,65544,1 +69304,Male,28,Bachelors,12,83,33,50,26,0.0,1,8,Urban,Data Analyst,45862,0 +69305,Female,43,Diploma,10,32,37,3,79,1.0,2,28,Rural,ML Engineer,73947,0 +69306,Female,53,Diploma,4,49,26,63,22,6.0,4,13,Urban,Manager,127299,0 +69307,Male,53,Bachelors,13,38,58,24,89,9.0,4,17,Rural,Manager,45054,0 +69308,Male,57,High School,5,81,59,80,49,0.0,3,35,Urban,Software Engineer,86119,1 +69309,Female,55,Diploma,16,85,88,8,80,6.0,4,25,Semi-Urban,Data Analyst,63444,0 +69310,Male,34,High School,2,77,80,74,80,2.0,1,99,Urban,Data Analyst,27832,1 +69311,Male,33,Masters,7,17,11,38,28,9.0,3,82,Semi-Urban,Manager,68743,0 +69312,Male,48,Bachelors,5,41,28,19,88,1.0,0,95,Semi-Urban,ML Engineer,116549,0 +69313,Female,21,Diploma,0,47,29,3,78,3.0,5,28,Urban,Software Engineer,65009,0 +69314,Male,59,Bachelors,10,92,52,45,58,2.0,7,70,Urban,Manager,57523,1 +69315,Female,53,Masters,6,49,95,25,1,1.0,7,16,Rural,Data Analyst,23101,0 +69316,Female,31,Masters,5,98,13,36,48,8.0,1,75,Urban,Manager,21454,0 +69317,Male,38,Bachelors,16,14,24,59,61,8.0,5,34,Urban,HR Executive,26733,0 +69318,Female,55,Bachelors,9,98,61,19,43,6.0,3,73,Urban,Software Engineer,130372,1 +69319,Female,21,High School,14,15,51,68,3,3.0,2,70,Rural,Data Analyst,87617,0 +69320,Male,35,High School,16,95,43,85,81,1.0,0,67,Urban,Software Engineer,95788,1 +69321,Other,47,Masters,7,7,69,34,5,6.0,4,47,Urban,Software Engineer,141860,0 +69322,Male,21,Bachelors,13,21,34,65,60,8.0,0,81,Semi-Urban,Manager,93927,0 +69323,Male,51,Bachelors,4,63,36,63,63,7.0,3,80,Rural,Manager,144123,1 +69324,Female,59,Bachelors,15,12,66,92,82,5.0,0,41,Rural,Data Analyst,67370,0 +69325,Male,51,Diploma,17,52,91,45,44,8.0,6,49,Semi-Urban,Data Analyst,42925,1 +69326,Female,29,High School,9,44,26,30,81,2.0,6,59,Urban,Manager,113859,0 +69327,Male,40,Diploma,16,8,16,4,40,0.0,6,62,Rural,HR Executive,46155,0 +69328,Female,53,Bachelors,17,67,92,38,89,1.0,0,88,Urban,HR Executive,126265,1 +69329,Male,22,Diploma,10,43,45,25,78,0.0,1,88,Urban,ML Engineer,45192,0 +69330,Male,39,Diploma,13,36,6,42,28,2.0,5,55,Rural,Manager,132199,0 +69331,Female,45,Masters,12,82,65,24,6,9.0,6,46,Urban,Data Analyst,55271,0 +69332,Male,52,High School,4,19,9,47,84,2.0,7,34,Urban,Data Analyst,37233,0 +69333,Female,43,High School,4,15,12,19,16,4.0,6,42,Semi-Urban,ML Engineer,81814,0 +69334,Other,51,Bachelors,3,84,69,4,84,4.0,3,87,Urban,HR Executive,101587,1 +69335,Male,27,Bachelors,9,50,55,88,2,9.0,2,85,Urban,HR Executive,83522,1 +69336,Female,52,Masters,8,44,50,75,4,2.0,2,84,Urban,HR Executive,95316,1 +69337,Male,39,Bachelors,11,79,60,39,77,4.0,2,32,Urban,Data Analyst,29688,0 +69338,Female,26,Diploma,9,51,38,25,29,2.0,0,98,Semi-Urban,Data Analyst,71323,0 +69339,Female,58,Diploma,13,43,80,1,33,3.0,1,65,Semi-Urban,Software Engineer,54620,0 +69340,Male,52,Masters,11,54,99,69,90,0.0,0,92,Urban,Data Analyst,26245,1 +69341,Male,44,Masters,7,77,63,15,48,9.0,1,15,Urban,ML Engineer,127282,0 +69342,Female,30,Bachelors,13,21,41,1,40,7.0,3,46,Urban,Software Engineer,84391,0 +69343,Female,34,Diploma,18,22,5,30,7,5.0,6,13,Rural,Manager,106515,0 +69344,Male,28,Bachelors,9,87,65,88,43,8.0,2,80,Semi-Urban,Data Analyst,56456,1 +69345,Male,42,Bachelors,15,78,62,1,85,8.0,3,72,Rural,Data Analyst,72652,0 +69346,Male,23,Bachelors,16,32,86,59,0,7.0,4,96,Rural,Manager,108206,1 +69347,Female,21,High School,1,84,6,64,54,5.0,6,92,Semi-Urban,HR Executive,50221,1 +69348,Male,45,Diploma,0,30,51,32,36,9.0,6,5,Rural,HR Executive,147241,0 +69349,Female,23,Diploma,12,14,54,65,0,8.0,1,89,Urban,ML Engineer,90488,0 +69350,Male,57,Diploma,16,67,48,9,46,4.0,5,46,Urban,ML Engineer,70359,0 +69351,Female,58,Bachelors,12,91,38,25,43,5.0,7,40,Semi-Urban,Data Analyst,126678,0 +69352,Male,38,Bachelors,11,88,19,59,93,7.0,2,23,Semi-Urban,Software Engineer,76085,0 +69353,Other,47,Masters,2,99,33,25,10,4.0,5,86,Urban,Software Engineer,107688,1 +69354,Male,40,Diploma,4,31,12,22,29,5.0,0,64,Rural,Data Analyst,61139,0 +69355,Male,23,Diploma,18,55,64,17,53,1.0,2,40,Urban,Data Analyst,73773,0 +69356,Male,27,Diploma,11,26,60,71,41,7.0,6,27,Urban,Manager,134198,0 +69357,Male,31,Masters,3,69,67,32,17,9.0,2,73,Semi-Urban,Data Analyst,114719,1 +69358,Female,53,Bachelors,17,81,3,38,73,8.0,4,34,Semi-Urban,ML Engineer,146062,0 +69359,Female,26,Masters,7,57,14,82,66,3.0,5,93,Rural,ML Engineer,84720,1 +69360,Female,54,Bachelors,8,62,17,77,36,3.0,0,29,Rural,Manager,108308,0 +69361,Other,21,High School,8,82,36,50,12,3.0,3,83,Urban,Data Analyst,95377,1 +69362,Male,32,Diploma,7,88,14,88,93,2.0,7,1,Urban,HR Executive,31075,0 +69363,Other,35,Bachelors,11,94,13,5,17,9.0,2,28,Rural,Software Engineer,35786,0 +69364,Male,44,High School,10,77,32,11,93,9.0,1,74,Semi-Urban,Manager,81416,0 +69365,Female,42,Masters,6,8,72,73,24,0.0,5,42,Urban,Software Engineer,38197,0 +69366,Male,23,High School,1,26,3,13,81,2.0,7,28,Urban,Manager,66177,0 +69367,Male,34,Masters,8,33,72,88,52,7.0,5,28,Urban,Data Analyst,82286,0 +69368,Male,47,Bachelors,11,23,71,81,85,2.0,5,25,Rural,Data Analyst,20847,0 +69369,Female,50,Bachelors,14,41,20,63,17,0.0,3,67,Rural,Software Engineer,41715,0 +69370,Female,52,Diploma,13,65,27,51,66,1.0,1,72,Urban,ML Engineer,21258,0 +69371,Male,41,Bachelors,19,5,3,32,11,6.0,0,75,Rural,HR Executive,29140,0 +69372,Female,34,Bachelors,15,0,97,70,11,1.0,4,13,Urban,Data Analyst,23571,0 +69373,Female,54,Bachelors,2,70,95,4,13,2.0,3,18,Rural,Data Analyst,119470,0 +69374,Male,28,Masters,2,54,35,64,10,7.0,0,55,Urban,Manager,49879,0 +69375,Female,53,Bachelors,11,22,44,3,81,9.0,6,79,Rural,Manager,20682,0 +69376,Male,33,High School,6,74,72,49,55,5.0,5,16,Urban,Manager,110963,0 +69377,Female,28,Masters,18,25,78,72,71,8.0,1,6,Urban,Manager,137296,0 +69378,Male,40,Masters,16,18,82,79,27,9.0,4,14,Semi-Urban,Manager,49157,0 +69379,Male,21,High School,0,57,62,62,74,7.0,1,63,Urban,Software Engineer,140661,1 +69380,Female,45,Bachelors,16,24,70,47,23,5.0,1,98,Urban,Data Analyst,49300,0 +69381,Male,40,High School,13,0,34,44,22,1.0,7,97,Urban,Data Analyst,68679,0 +69382,Male,53,Diploma,17,90,69,36,73,8.0,7,20,Semi-Urban,ML Engineer,55938,0 +69383,Female,43,High School,15,17,84,40,9,5.0,2,20,Urban,Data Analyst,58328,0 +69384,Female,42,High School,6,63,49,12,43,9.0,2,71,Rural,Software Engineer,77220,0 +69385,Female,30,Masters,3,43,96,62,66,4.0,3,11,Urban,ML Engineer,90410,0 +69386,Female,54,High School,16,57,4,23,96,8.0,4,13,Urban,ML Engineer,103177,0 +69387,Male,48,Bachelors,4,84,27,49,20,9.0,1,9,Urban,Software Engineer,110725,0 +69388,Male,30,High School,7,93,54,77,62,3.0,1,43,Semi-Urban,Data Analyst,33571,1 +69389,Female,54,Masters,19,5,63,70,55,2.0,7,81,Urban,Data Analyst,93245,0 +69390,Female,59,Bachelors,11,94,23,22,12,5.0,5,24,Semi-Urban,HR Executive,63052,0 +69391,Male,42,Bachelors,14,17,20,70,17,7.0,1,41,Urban,Manager,97707,0 +69392,Female,42,Masters,2,51,27,59,47,1.0,7,45,Urban,HR Executive,64480,0 +69393,Male,51,Bachelors,4,90,6,78,3,7.0,6,85,Semi-Urban,ML Engineer,98572,1 +69394,Male,41,Bachelors,10,32,94,41,2,6.0,5,78,Urban,Data Analyst,112451,1 +69395,Male,29,High School,11,37,75,62,88,4.0,1,42,Rural,HR Executive,69108,0 +69396,Female,34,High School,8,42,7,37,55,9.0,4,90,Semi-Urban,Software Engineer,128292,0 +69397,Male,49,Masters,0,88,36,84,32,1.0,5,41,Urban,ML Engineer,111868,1 +69398,Female,23,Diploma,12,70,67,52,78,3.0,3,81,Urban,Software Engineer,107442,1 +69399,Female,52,Masters,9,66,72,51,34,1.0,1,64,Semi-Urban,Data Analyst,143816,1 +69400,Other,47,High School,3,32,22,70,61,2.0,3,79,Urban,Manager,99396,0 +69401,Male,30,High School,18,67,4,28,41,6.0,4,94,Urban,Software Engineer,49143,0 +69402,Female,21,Bachelors,17,74,71,98,43,6.0,4,60,Urban,Data Analyst,48471,1 +69403,Male,59,Diploma,17,46,5,46,10,4.0,6,34,Urban,HR Executive,141310,0 +69404,Female,33,Masters,12,26,11,57,87,1.0,7,48,Urban,Data Analyst,115160,0 +69405,Female,51,High School,9,64,44,5,30,6.0,0,7,Urban,Manager,142597,0 +69406,Female,32,Bachelors,13,7,28,42,72,8.0,6,37,Rural,Software Engineer,148944,0 +69407,Male,46,Bachelors,12,93,57,62,19,4.0,0,53,Rural,HR Executive,23009,1 +69408,Male,38,PhD,5,94,39,92,12,1.0,2,71,Urban,Manager,72171,1 +69409,Female,39,Masters,6,41,85,95,3,5.0,4,43,Semi-Urban,Data Analyst,64399,1 +69410,Female,22,High School,3,93,63,11,33,0.0,2,78,Rural,Software Engineer,40386,1 +69411,Female,56,Diploma,2,13,86,77,16,1.0,1,80,Urban,Software Engineer,24827,1 +69412,Male,48,Masters,19,61,61,90,30,6.0,0,24,Rural,HR Executive,91924,1 +69413,Male,40,Masters,7,61,33,93,78,3.0,1,79,Rural,HR Executive,118406,1 +69414,Male,21,High School,5,71,23,35,33,1.0,1,78,Urban,Data Analyst,68442,0 +69415,Male,21,High School,16,63,64,21,18,6.0,3,6,Rural,ML Engineer,20812,0 +69416,Male,29,Bachelors,17,5,41,23,19,2.0,7,4,Semi-Urban,ML Engineer,125927,0 +69417,Female,28,Bachelors,10,58,44,47,77,0.0,6,96,Urban,Data Analyst,37071,1 +69418,Female,45,PhD,19,66,89,96,46,3.0,0,81,Semi-Urban,Software Engineer,55516,1 +69419,Male,32,Bachelors,1,95,58,24,50,1.0,7,85,Urban,ML Engineer,30047,1 +69420,Female,24,Masters,3,7,39,69,18,5.0,1,6,Urban,HR Executive,66546,0 +69421,Female,26,Masters,4,96,84,6,97,2.0,1,58,Urban,ML Engineer,27609,1 +69422,Male,49,High School,15,43,39,55,96,5.0,7,81,Semi-Urban,HR Executive,121258,0 +69423,Female,51,Bachelors,4,64,48,64,32,6.0,1,3,Rural,Manager,83260,0 +69424,Female,31,High School,5,8,69,73,97,0.0,5,65,Rural,Software Engineer,122451,0 +69425,Male,43,Bachelors,14,20,95,65,74,6.0,5,77,Semi-Urban,HR Executive,120227,1 +69426,Male,46,Bachelors,19,33,59,89,15,0.0,2,20,Semi-Urban,ML Engineer,47666,0 +69427,Male,38,Bachelors,17,55,25,63,24,7.0,0,9,Semi-Urban,Data Analyst,45834,0 +69428,Male,53,Masters,11,83,67,82,91,4.0,0,31,Urban,Data Analyst,62504,1 +69429,Female,54,Bachelors,12,78,4,25,38,9.0,3,55,Urban,Software Engineer,143851,0 +69430,Male,48,Diploma,5,74,19,39,57,3.0,3,92,Semi-Urban,Data Analyst,112834,0 +69431,Female,39,Bachelors,8,9,79,84,19,3.0,5,1,Rural,Software Engineer,84510,0 +69432,Female,22,Masters,9,2,14,32,64,3.0,6,5,Urban,Data Analyst,54237,0 +69433,Female,29,High School,8,31,41,2,4,4.0,5,39,Rural,Manager,29994,0 +69434,Male,37,Masters,19,33,49,51,39,9.0,1,43,Semi-Urban,HR Executive,66193,0 +69435,Female,56,Bachelors,10,98,52,56,31,0.0,2,74,Urban,Manager,127360,1 +69436,Female,41,Bachelors,6,20,41,28,21,7.0,1,66,Urban,HR Executive,47042,0 +69437,Male,59,Bachelors,9,44,88,26,65,6.0,1,33,Urban,Data Analyst,74557,0 +69438,Female,38,PhD,11,66,61,74,27,0.0,4,61,Urban,Data Analyst,22742,1 +69439,Female,32,High School,6,13,21,92,55,8.0,6,65,Urban,Data Analyst,75574,0 +69440,Male,59,Masters,8,25,13,58,41,6.0,6,36,Urban,Manager,86903,0 +69441,Female,58,Bachelors,12,59,68,73,48,9.0,5,7,Urban,Data Analyst,131504,0 +69442,Male,28,High School,1,18,45,13,72,7.0,7,14,Urban,ML Engineer,87275,0 +69443,Male,44,High School,6,60,64,95,41,4.0,7,55,Urban,ML Engineer,123365,1 +69444,Male,42,Diploma,16,24,31,20,13,3.0,6,1,Semi-Urban,Software Engineer,71565,0 +69445,Female,47,Masters,11,94,14,25,62,9.0,1,60,Rural,Software Engineer,87310,0 +69446,Male,36,Diploma,15,74,66,55,71,4.0,1,47,Urban,HR Executive,37110,1 +69447,Male,33,Diploma,4,4,7,44,19,4.0,5,1,Urban,HR Executive,78326,0 +69448,Male,59,Diploma,8,50,81,22,23,2.0,7,38,Semi-Urban,Manager,83718,0 +69449,Female,53,Diploma,9,66,35,92,49,7.0,6,49,Rural,Data Analyst,27082,1 +69450,Male,28,Bachelors,3,62,43,99,68,8.0,5,72,Semi-Urban,Manager,56057,1 +69451,Female,57,Bachelors,0,25,30,31,48,5.0,4,30,Urban,Data Analyst,38003,0 +69452,Female,51,Bachelors,3,46,70,81,58,1.0,1,68,Urban,Manager,112558,1 +69453,Male,57,High School,2,69,78,73,70,3.0,1,28,Semi-Urban,HR Executive,88295,1 +69454,Male,55,Bachelors,16,10,75,38,84,7.0,1,33,Rural,Data Analyst,29580,0 +69455,Male,58,High School,2,20,65,72,40,3.0,4,65,Urban,Manager,149939,0 +69456,Male,29,PhD,12,8,84,4,26,4.0,5,87,Urban,ML Engineer,92540,0 +69457,Female,57,Masters,12,17,16,54,86,1.0,7,65,Semi-Urban,Data Analyst,26890,0 +69458,Male,59,Masters,15,30,18,13,13,1.0,2,2,Urban,Manager,111512,0 +69459,Female,34,Bachelors,5,75,86,43,38,8.0,1,51,Urban,ML Engineer,76845,1 +69460,Female,45,Diploma,15,65,92,80,64,9.0,3,0,Urban,Software Engineer,83148,0 +69461,Male,21,Masters,16,80,72,59,57,5.0,0,73,Semi-Urban,Software Engineer,142086,1 +69462,Female,23,Masters,13,72,83,67,55,0.0,2,20,Urban,HR Executive,35219,1 +69463,Female,31,Bachelors,19,62,26,64,32,2.0,1,53,Rural,HR Executive,104929,0 +69464,Male,31,Bachelors,3,54,97,6,94,8.0,6,84,Urban,Software Engineer,139725,1 +69465,Male,45,PhD,2,15,54,63,14,0.0,0,80,Urban,Software Engineer,112173,0 +69466,Male,57,Diploma,10,71,75,53,57,9.0,4,95,Urban,Manager,143016,1 +69467,Female,42,High School,2,14,7,49,29,1.0,2,91,Urban,Data Analyst,46750,0 +69468,Male,41,Masters,8,27,84,19,12,8.0,4,20,Semi-Urban,Manager,75039,0 +69469,Male,49,Diploma,16,24,70,18,21,2.0,6,26,Rural,Data Analyst,40381,0 +69470,Female,46,Masters,7,24,80,82,54,3.0,0,36,Semi-Urban,Manager,142692,0 +69471,Male,47,PhD,6,34,66,81,23,5.0,5,3,Rural,HR Executive,28643,0 +69472,Male,33,Bachelors,19,78,88,68,83,2.0,5,58,Urban,Software Engineer,110408,1 +69473,Male,41,Bachelors,17,3,15,91,62,8.0,5,5,Rural,Software Engineer,98203,0 +69474,Male,21,Diploma,2,72,6,33,89,3.0,2,69,Rural,Data Analyst,42310,0 +69475,Male,31,Bachelors,0,22,55,39,15,2.0,7,43,Semi-Urban,ML Engineer,49593,0 +69476,Male,54,Bachelors,11,86,70,69,42,2.0,1,79,Urban,ML Engineer,61601,1 +69477,Male,27,PhD,9,1,31,76,67,1.0,2,56,Semi-Urban,Software Engineer,72014,0 +69478,Male,22,Bachelors,18,0,88,75,51,4.0,1,76,Urban,Manager,59196,1 +69479,Male,28,Masters,4,91,43,58,10,1.0,2,17,Urban,ML Engineer,81609,0 +69480,Male,49,High School,17,93,9,48,91,3.0,2,93,Semi-Urban,Manager,144112,1 +69481,Male,21,Bachelors,10,17,70,29,45,8.0,5,75,Urban,ML Engineer,22284,0 +69482,Female,55,Diploma,1,69,24,71,67,7.0,5,27,Rural,Software Engineer,78017,0 +69483,Male,28,Diploma,7,86,23,69,68,8.0,5,93,Urban,ML Engineer,101390,1 +69484,Male,50,Bachelors,0,26,88,48,1,2.0,6,26,Urban,Manager,82697,0 +69485,Female,40,Diploma,6,33,7,69,53,9.0,2,45,Urban,Data Analyst,129706,0 +69486,Male,23,High School,10,83,29,30,30,1.0,4,67,Urban,Manager,31439,0 +69487,Male,24,High School,10,11,66,19,94,4.0,4,38,Urban,Data Analyst,102021,0 +69488,Female,47,Bachelors,11,82,41,48,77,8.0,5,63,Rural,HR Executive,130745,0 +69489,Male,59,Bachelors,13,60,7,19,9,5.0,4,39,Urban,HR Executive,112637,0 +69490,Male,32,Bachelors,12,46,22,92,13,4.0,3,24,Urban,ML Engineer,77342,0 +69491,Male,29,Bachelors,14,88,34,98,99,6.0,7,78,Urban,Manager,46038,1 +69492,Male,45,Masters,10,85,60,36,13,1.0,0,8,Urban,Manager,125258,0 +69493,Male,37,Diploma,13,62,95,83,35,3.0,4,27,Semi-Urban,Software Engineer,43209,1 +69494,Male,46,Bachelors,5,44,80,79,39,8.0,4,27,Urban,HR Executive,31065,0 +69495,Male,27,High School,7,55,14,62,61,8.0,3,76,Urban,Software Engineer,103824,0 +69496,Other,52,Masters,0,74,90,32,66,3.0,3,6,Urban,Manager,69275,0 +69497,Male,21,Bachelors,8,6,47,44,76,7.0,4,69,Urban,Data Analyst,145117,0 +69498,Male,46,Bachelors,3,37,57,24,57,3.0,4,54,Urban,Software Engineer,42770,0 +69499,Male,41,High School,7,55,57,5,2,1.0,7,49,Urban,Software Engineer,101789,0 +69500,Male,49,Masters,15,60,89,17,87,9.0,2,37,Urban,Manager,68097,0 +69501,Male,31,Masters,14,58,18,81,68,7.0,1,7,Semi-Urban,ML Engineer,62339,0 +69502,Female,27,High School,0,74,64,6,82,3.0,1,44,Urban,Manager,52123,0 +69503,Female,54,Diploma,17,10,84,36,59,4.0,5,99,Urban,HR Executive,61255,0 +69504,Male,46,Bachelors,0,96,83,68,24,4.0,4,80,Urban,Software Engineer,58900,1 +69505,Male,59,Masters,1,6,81,96,96,5.0,3,78,Urban,HR Executive,75829,1 +69506,Other,55,Bachelors,4,21,86,90,75,6.0,6,49,Urban,HR Executive,47477,1 +69507,Female,31,Bachelors,13,42,9,81,30,7.0,4,5,Urban,Manager,133725,0 +69508,Male,29,Bachelors,19,80,77,51,4,4.0,4,81,Urban,ML Engineer,28782,1 +69509,Female,57,Bachelors,9,14,86,14,68,3.0,3,70,Urban,Data Analyst,24763,0 +69510,Female,28,Bachelors,10,92,32,81,35,1.0,0,97,Semi-Urban,Manager,21703,1 +69511,Male,44,Diploma,8,15,72,90,59,8.0,3,69,Rural,Data Analyst,90291,1 +69512,Female,58,Bachelors,17,45,19,24,60,6.0,1,81,Urban,Manager,55041,0 +69513,Female,56,Bachelors,5,29,52,25,74,0.0,5,88,Urban,Data Analyst,115258,0 +69514,Female,54,Diploma,11,5,95,13,20,7.0,7,34,Urban,Manager,94834,0 +69515,Male,44,Diploma,4,80,36,70,61,0.0,1,73,Rural,ML Engineer,38438,1 +69516,Female,37,Diploma,11,98,24,84,60,3.0,7,2,Rural,Software Engineer,62908,0 +69517,Male,33,Diploma,2,55,20,33,56,9.0,7,86,Rural,HR Executive,48229,0 +69518,Female,22,Bachelors,3,19,77,53,69,2.0,0,22,Rural,Data Analyst,36774,0 +69519,Male,46,Masters,7,58,8,0,14,3.0,2,55,Urban,Data Analyst,111842,0 +69520,Male,31,Bachelors,15,26,10,2,65,0.0,0,29,Urban,Manager,135356,0 +69521,Female,57,PhD,13,70,45,87,25,5.0,3,32,Urban,HR Executive,131891,0 +69522,Male,57,High School,12,10,79,61,26,4.0,0,4,Semi-Urban,Software Engineer,137479,0 +69523,Female,51,Diploma,15,86,2,51,39,0.0,2,66,Semi-Urban,Manager,86084,0 +69524,Male,53,Bachelors,13,51,77,37,80,7.0,4,99,Urban,Data Analyst,135823,1 +69525,Female,35,Bachelors,4,80,23,43,48,8.0,5,34,Semi-Urban,HR Executive,98788,0 +69526,Male,58,Bachelors,16,78,66,69,55,6.0,4,21,Rural,Software Engineer,22382,0 +69527,Female,34,Diploma,1,57,8,34,65,6.0,6,53,Rural,ML Engineer,129888,0 +69528,Female,28,Bachelors,18,91,65,6,17,2.0,2,35,Urban,Data Analyst,117744,0 +69529,Female,28,Diploma,8,69,71,48,97,7.0,7,54,Semi-Urban,Manager,64714,1 +69530,Female,28,Bachelors,4,28,77,53,24,8.0,4,93,Urban,HR Executive,140287,1 +69531,Male,22,Diploma,18,12,7,25,40,8.0,3,88,Urban,Data Analyst,67734,0 +69532,Female,53,Masters,3,74,41,2,66,7.0,7,39,Rural,Data Analyst,80290,0 +69533,Female,46,Bachelors,2,16,35,38,24,4.0,6,64,Urban,Software Engineer,98916,0 +69534,Female,56,PhD,17,96,83,53,22,7.0,4,28,Semi-Urban,Manager,54080,1 +69535,Female,57,Diploma,7,95,8,73,22,1.0,5,75,Semi-Urban,ML Engineer,87622,1 +69536,Female,55,Masters,11,50,44,57,3,2.0,2,16,Urban,HR Executive,119682,0 +69537,Female,51,Masters,12,18,72,21,50,2.0,0,13,Urban,Manager,46459,0 +69538,Female,52,Masters,15,27,14,62,29,6.0,2,13,Semi-Urban,Software Engineer,117272,0 +69539,Female,55,Bachelors,17,57,33,73,38,1.0,7,48,Rural,Manager,71812,0 +69540,Female,29,Masters,13,22,24,99,92,3.0,0,39,Urban,ML Engineer,73016,0 +69541,Male,55,Masters,11,67,70,82,77,5.0,6,43,Semi-Urban,HR Executive,110907,1 +69542,Female,23,Masters,14,1,8,10,51,9.0,1,34,Urban,Data Analyst,102624,0 +69543,Female,43,Diploma,15,44,62,33,67,0.0,0,68,Semi-Urban,Data Analyst,26678,0 +69544,Male,25,Masters,16,27,78,7,48,3.0,5,62,Semi-Urban,Software Engineer,122386,0 +69545,Male,36,PhD,4,39,18,57,42,6.0,5,1,Rural,ML Engineer,97789,0 +69546,Male,24,Bachelors,9,19,15,77,6,7.0,1,80,Urban,ML Engineer,124379,0 +69547,Male,58,Masters,1,4,20,22,18,6.0,2,77,Urban,HR Executive,63042,0 +69548,Female,54,Bachelors,2,78,27,0,95,5.0,3,18,Urban,Data Analyst,92468,0 +69549,Male,38,Diploma,2,96,10,71,41,2.0,1,66,Rural,ML Engineer,27318,1 +69550,Female,45,Bachelors,3,52,11,66,96,3.0,0,11,Rural,Data Analyst,131590,0 +69551,Female,28,Bachelors,14,75,95,21,82,2.0,5,13,Semi-Urban,HR Executive,46550,0 +69552,Female,35,Diploma,8,52,23,55,3,0.0,6,67,Urban,Data Analyst,132114,0 +69553,Male,52,Bachelors,5,10,3,19,81,7.0,1,29,Rural,Data Analyst,129197,0 +69554,Male,36,Diploma,11,69,69,68,13,9.0,2,81,Urban,HR Executive,79500,1 +69555,Male,29,High School,7,26,90,65,10,6.0,5,84,Semi-Urban,Data Analyst,124629,1 +69556,Male,44,Bachelors,1,39,53,64,64,5.0,4,11,Urban,Manager,30971,0 +69557,Male,52,Bachelors,1,81,8,36,28,6.0,3,1,Urban,Manager,129947,0 +69558,Male,36,Bachelors,11,87,43,26,66,8.0,2,93,Semi-Urban,Data Analyst,116033,1 +69559,Male,54,Masters,15,31,51,86,58,3.0,1,32,Urban,Software Engineer,72165,0 +69560,Male,30,Masters,11,18,85,94,51,2.0,6,84,Urban,ML Engineer,67162,1 +69561,Male,43,Bachelors,5,74,28,87,23,0.0,7,74,Semi-Urban,Manager,62358,1 +69562,Female,36,High School,2,47,79,77,88,6.0,1,96,Semi-Urban,ML Engineer,112741,1 +69563,Female,24,Bachelors,10,51,53,58,94,4.0,6,30,Urban,Software Engineer,78223,0 +69564,Female,44,Diploma,5,86,54,70,63,1.0,0,68,Urban,Software Engineer,83289,1 +69565,Female,23,Diploma,18,99,22,14,88,8.0,0,30,Rural,Manager,74091,0 +69566,Male,34,Diploma,19,43,9,21,75,7.0,2,84,Semi-Urban,Manager,25889,0 +69567,Female,48,Masters,14,29,23,68,93,0.0,3,99,Urban,Manager,141138,0 +69568,Male,22,Bachelors,10,97,94,80,14,2.0,6,25,Urban,ML Engineer,84340,1 +69569,Male,23,Diploma,13,97,57,25,88,2.0,7,54,Semi-Urban,Manager,96246,0 +69570,Male,50,Diploma,4,24,9,38,10,6.0,2,55,Urban,Data Analyst,138969,0 +69571,Male,25,Diploma,17,25,63,82,53,5.0,4,83,Semi-Urban,Software Engineer,149074,1 +69572,Male,35,Bachelors,17,5,55,6,10,9.0,2,62,Urban,Software Engineer,74404,0 +69573,Other,23,Diploma,14,69,44,31,57,2.0,0,23,Semi-Urban,Software Engineer,113264,0 +69574,Female,46,Diploma,4,76,39,34,20,9.0,5,22,Urban,ML Engineer,100626,0 +69575,Male,43,Masters,2,2,89,14,96,8.0,6,65,Rural,Data Analyst,82534,0 +69576,Female,35,Diploma,12,57,26,68,69,8.0,7,33,Urban,Manager,80165,0 +69577,Female,36,Masters,7,93,95,90,60,2.0,2,95,Urban,Software Engineer,32798,1 +69578,Male,29,Bachelors,19,73,87,61,86,9.0,0,55,Semi-Urban,Manager,81852,1 +69579,Female,26,Masters,3,31,2,60,19,9.0,4,15,Urban,Software Engineer,119698,0 +69580,Female,31,Masters,10,99,40,54,82,4.0,0,82,Rural,Software Engineer,93200,1 +69581,Male,33,Bachelors,14,36,97,19,39,6.0,4,5,Semi-Urban,HR Executive,145979,0 +69582,Female,25,Bachelors,8,0,17,52,58,0.0,5,1,Semi-Urban,Data Analyst,115458,0 +69583,Female,44,High School,17,20,5,70,57,1.0,4,31,Urban,ML Engineer,128418,0 +69584,Female,53,High School,2,83,9,31,31,0.0,6,55,Rural,Software Engineer,75879,0 +69585,Other,34,Bachelors,0,86,48,83,90,7.0,3,33,Urban,HR Executive,92202,1 +69586,Male,21,Masters,14,7,83,47,58,9.0,0,23,Semi-Urban,HR Executive,33957,0 +69587,Female,49,High School,9,16,10,14,1,3.0,1,26,Urban,HR Executive,25830,0 +69588,Female,27,Bachelors,7,14,40,83,15,7.0,7,12,Semi-Urban,Software Engineer,125422,0 +69589,Male,35,Bachelors,11,55,25,15,42,6.0,4,80,Urban,Software Engineer,57134,0 +69590,Female,42,Masters,7,49,25,2,58,0.0,4,29,Urban,ML Engineer,136951,0 +69591,Other,21,Masters,9,9,3,64,78,3.0,4,54,Urban,Software Engineer,33439,0 +69592,Male,37,Diploma,11,25,55,99,53,5.0,1,74,Semi-Urban,HR Executive,30069,1 +69593,Female,37,High School,16,33,65,71,79,8.0,0,99,Urban,Manager,27098,1 +69594,Male,34,Masters,13,10,1,20,75,5.0,6,1,Rural,Data Analyst,71944,0 +69595,Male,38,Diploma,19,14,20,26,62,3.0,6,8,Urban,Data Analyst,45916,0 +69596,Male,44,Bachelors,3,41,91,3,38,8.0,0,55,Urban,Manager,117281,0 +69597,Female,37,Masters,8,31,26,39,54,2.0,2,86,Rural,Manager,50698,0 +69598,Female,40,Diploma,6,3,71,7,28,6.0,1,35,Urban,Manager,48290,0 +69599,Male,41,High School,2,5,22,15,7,1.0,7,1,Urban,Software Engineer,104452,0 +69600,Female,58,Diploma,7,24,88,76,5,0.0,4,73,Rural,Manager,124660,1 +69601,Male,22,Diploma,13,51,50,37,78,5.0,1,60,Semi-Urban,Data Analyst,134296,0 +69602,Female,31,Bachelors,15,43,15,56,20,6.0,0,43,Urban,Manager,103298,0 +69603,Male,45,Bachelors,12,13,93,24,0,3.0,4,85,Urban,ML Engineer,41850,0 +69604,Male,46,Diploma,18,56,1,13,94,0.0,6,73,Urban,HR Executive,33003,0 +69605,Female,59,Masters,14,2,50,47,71,8.0,1,14,Urban,HR Executive,120618,0 +69606,Male,55,Diploma,0,43,93,63,91,3.0,1,1,Urban,Software Engineer,29504,0 +69607,Female,24,Bachelors,17,6,63,55,46,2.0,6,7,Urban,Software Engineer,97281,0 +69608,Female,43,High School,19,88,31,53,39,2.0,3,18,Rural,Software Engineer,59923,0 +69609,Male,53,High School,13,34,26,55,46,8.0,6,60,Rural,Software Engineer,141970,0 +69610,Female,51,Masters,6,2,12,3,30,3.0,7,58,Urban,ML Engineer,144808,0 +69611,Male,29,High School,3,69,53,81,89,3.0,1,3,Urban,Software Engineer,148577,0 +69612,Male,51,Diploma,13,65,14,50,12,8.0,2,12,Rural,Manager,129504,0 +69613,Female,59,Bachelors,3,57,5,13,12,5.0,7,56,Urban,Manager,90883,0 +69614,Female,29,Masters,3,21,2,64,11,8.0,7,63,Urban,Data Analyst,142711,0 +69615,Female,45,Bachelors,0,4,84,38,54,2.0,4,75,Urban,Manager,102167,0 +69616,Female,41,High School,19,16,15,18,30,7.0,3,81,Rural,Data Analyst,119311,0 +69617,Female,30,Bachelors,19,32,79,35,36,4.0,4,85,Urban,HR Executive,65270,0 +69618,Male,37,PhD,15,10,5,8,24,2.0,6,57,Semi-Urban,HR Executive,32036,0 +69619,Male,38,Bachelors,2,48,46,57,92,9.0,0,11,Urban,ML Engineer,140091,0 +69620,Male,44,Diploma,19,59,28,37,92,5.0,3,72,Urban,Manager,37084,0 +69621,Female,58,Bachelors,4,29,70,65,72,2.0,0,78,Rural,Software Engineer,92642,1 +69622,Female,32,Bachelors,1,26,69,4,80,9.0,7,16,Rural,ML Engineer,147351,0 +69623,Male,31,High School,0,46,43,20,40,3.0,4,26,Semi-Urban,ML Engineer,148429,0 +69624,Male,27,Bachelors,10,20,64,12,32,8.0,0,1,Urban,Manager,104587,0 +69625,Male,34,Bachelors,12,24,9,80,64,7.0,7,37,Rural,HR Executive,29443,0 +69626,Male,56,Bachelors,1,44,78,45,15,4.0,7,18,Urban,Data Analyst,149023,0 +69627,Male,39,Bachelors,17,73,79,49,62,1.0,2,91,Rural,Manager,50878,1 +69628,Male,52,Bachelors,15,27,57,29,24,0.0,4,50,Urban,Manager,142603,0 +69629,Female,27,Bachelors,1,52,12,12,88,9.0,7,97,Urban,ML Engineer,78151,0 +69630,Female,47,High School,19,84,81,97,73,8.0,2,24,Urban,ML Engineer,147560,1 +69631,Female,57,Bachelors,10,6,99,44,81,9.0,5,9,Urban,Manager,43413,0 +69632,Female,43,Masters,15,60,21,52,40,9.0,4,42,Semi-Urban,HR Executive,36881,0 +69633,Male,55,Diploma,3,70,99,8,66,1.0,4,90,Urban,HR Executive,21899,1 +69634,Female,58,Bachelors,8,11,75,58,70,8.0,4,32,Semi-Urban,HR Executive,129087,0 +69635,Male,45,Masters,19,95,1,99,9,9.0,4,24,Urban,Software Engineer,49189,0 +69636,Male,25,Bachelors,18,81,22,87,15,8.0,1,84,Rural,Data Analyst,136556,1 +69637,Male,37,Masters,14,50,56,15,33,6.0,3,50,Semi-Urban,Data Analyst,51320,0 +69638,Male,44,Bachelors,10,3,55,51,42,2.0,7,93,Urban,Manager,43155,0 +69639,Male,45,Diploma,6,40,11,40,48,6.0,2,5,Semi-Urban,Data Analyst,55822,0 +69640,Male,33,Bachelors,10,82,44,82,59,8.0,1,34,Semi-Urban,Data Analyst,95721,1 +69641,Female,57,Bachelors,1,60,62,11,29,9.0,6,47,Urban,ML Engineer,36613,0 +69642,Female,52,High School,14,31,3,97,19,9.0,5,10,Semi-Urban,Manager,118504,0 +69643,Male,26,Diploma,9,21,96,89,38,5.0,5,96,Urban,Manager,128883,1 +69644,Male,40,Masters,4,27,86,39,72,6.0,5,66,Semi-Urban,Data Analyst,53015,0 +69645,Female,43,Bachelors,5,91,30,83,20,2.0,7,20,Urban,Data Analyst,21402,0 +69646,Male,30,Bachelors,12,62,87,42,71,7.0,2,49,Urban,HR Executive,145443,1 +69647,Male,29,Bachelors,0,59,10,68,29,2.0,2,8,Urban,Data Analyst,123664,0 +69648,Male,55,Bachelors,17,30,30,34,19,8.0,3,10,Urban,Data Analyst,74797,0 +69649,Female,54,Bachelors,14,95,94,87,33,3.0,5,50,Urban,Data Analyst,32782,1 +69650,Female,45,Bachelors,5,31,70,82,95,7.0,2,85,Semi-Urban,ML Engineer,118703,1 +69651,Male,37,PhD,2,87,53,84,78,5.0,1,60,Semi-Urban,Data Analyst,78570,1 +69652,Male,45,High School,2,62,55,80,38,2.0,6,21,Urban,HR Executive,55724,0 +69653,Male,56,Bachelors,4,68,43,1,33,8.0,3,87,Urban,ML Engineer,49367,0 +69654,Male,32,Bachelors,7,23,69,71,55,9.0,2,88,Semi-Urban,Data Analyst,91764,1 +69655,Male,21,Bachelors,2,62,61,9,21,0.0,2,10,Rural,HR Executive,99551,0 +69656,Male,46,PhD,4,86,47,11,89,3.0,0,79,Urban,Manager,94521,0 +69657,Male,42,Masters,0,18,93,83,56,5.0,1,22,Rural,ML Engineer,144258,0 +69658,Male,58,Diploma,2,11,33,17,16,8.0,5,91,Urban,Software Engineer,73894,0 +69659,Male,32,Bachelors,3,52,85,88,20,1.0,6,60,Urban,Software Engineer,104580,1 +69660,Female,55,PhD,0,14,29,90,64,6.0,2,23,Urban,HR Executive,60179,0 +69661,Male,49,Bachelors,11,30,53,1,42,9.0,1,29,Semi-Urban,Data Analyst,54488,0 +69662,Male,33,Diploma,13,58,48,80,39,4.0,3,80,Semi-Urban,Manager,36765,1 +69663,Other,22,Diploma,6,33,21,95,90,2.0,0,79,Semi-Urban,HR Executive,70711,0 +69664,Male,42,Masters,6,23,70,91,20,2.0,1,97,Urban,Data Analyst,110257,1 +69665,Male,25,Bachelors,13,34,81,7,81,2.0,2,2,Semi-Urban,Data Analyst,30980,0 +69666,Male,22,High School,16,1,89,55,8,1.0,4,96,Urban,Manager,66530,1 +69667,Male,23,Bachelors,9,95,85,73,95,1.0,6,24,Urban,Manager,148660,1 +69668,Male,49,Bachelors,13,61,83,26,42,3.0,0,65,Urban,Data Analyst,44632,1 +69669,Male,37,Diploma,8,33,89,83,59,0.0,4,5,Semi-Urban,ML Engineer,71263,0 +69670,Male,33,High School,18,88,30,3,83,2.0,0,77,Urban,Software Engineer,21529,0 +69671,Other,43,PhD,8,43,40,45,77,2.0,6,36,Semi-Urban,ML Engineer,67513,0 +69672,Male,22,High School,13,17,56,16,51,1.0,5,72,Urban,Manager,118195,0 +69673,Female,45,Masters,5,39,79,48,22,5.0,6,92,Semi-Urban,Software Engineer,134684,1 +69674,Female,50,High School,9,12,12,81,10,6.0,6,31,Urban,HR Executive,60750,0 +69675,Female,27,PhD,16,62,78,11,53,1.0,4,64,Urban,Data Analyst,94825,0 +69676,Male,37,High School,4,70,76,52,79,3.0,4,12,Semi-Urban,HR Executive,21337,0 +69677,Other,25,Diploma,1,14,93,98,54,7.0,6,25,Urban,Manager,105953,0 +69678,Female,58,High School,6,27,55,67,0,5.0,2,91,Rural,HR Executive,42066,0 +69679,Male,45,Bachelors,0,30,18,71,73,9.0,0,99,Urban,HR Executive,39620,0 +69680,Female,22,PhD,18,83,9,30,96,2.0,3,97,Urban,Manager,122682,0 +69681,Male,31,Bachelors,7,7,2,39,87,5.0,0,3,Urban,Software Engineer,23075,0 +69682,Male,23,High School,13,16,32,49,90,8.0,0,33,Urban,Data Analyst,56818,0 +69683,Male,33,Bachelors,15,23,61,82,46,9.0,3,59,Urban,HR Executive,58472,0 +69684,Male,40,Bachelors,12,41,72,7,92,6.0,7,81,Urban,Data Analyst,87374,0 +69685,Female,44,Bachelors,13,65,67,57,30,0.0,0,89,Urban,Manager,92742,1 +69686,Male,22,Masters,10,94,76,46,83,9.0,4,77,Urban,Software Engineer,116246,1 +69687,Female,47,Masters,2,29,63,90,16,7.0,7,27,Semi-Urban,ML Engineer,102802,0 +69688,Male,46,Bachelors,15,32,18,48,74,5.0,1,1,Semi-Urban,ML Engineer,67510,0 +69689,Male,55,Bachelors,19,4,84,63,94,3.0,1,78,Urban,Manager,65190,0 +69690,Female,27,Diploma,16,23,27,63,95,3.0,5,30,Rural,Manager,55736,0 +69691,Male,44,High School,3,16,2,54,46,9.0,7,24,Urban,Data Analyst,55333,0 +69692,Female,35,Diploma,18,23,6,76,52,7.0,7,64,Semi-Urban,Manager,52631,0 +69693,Female,35,High School,19,86,66,39,13,8.0,2,68,Urban,Data Analyst,40530,1 +69694,Male,44,Bachelors,9,52,64,94,84,6.0,7,57,Urban,Software Engineer,115271,1 +69695,Male,21,Masters,9,61,49,16,80,0.0,2,58,Rural,Data Analyst,33351,0 +69696,Male,37,Bachelors,7,68,9,48,52,1.0,4,48,Semi-Urban,Data Analyst,63120,0 +69697,Female,43,Bachelors,9,9,33,77,38,1.0,2,21,Urban,Manager,147316,0 +69698,Female,56,Bachelors,2,5,58,57,27,6.0,5,38,Semi-Urban,HR Executive,63125,0 +69699,Male,39,High School,17,42,55,35,59,1.0,1,17,Semi-Urban,Data Analyst,134950,0 +69700,Male,41,Bachelors,14,28,52,63,46,8.0,7,46,Urban,Software Engineer,41977,0 +69701,Male,50,Bachelors,19,37,0,82,69,9.0,6,41,Semi-Urban,Manager,103502,0 +69702,Male,59,Bachelors,9,22,36,75,77,2.0,7,19,Urban,ML Engineer,128894,0 +69703,Other,35,Bachelors,17,26,19,95,29,4.0,0,88,Urban,Data Analyst,32084,0 +69704,Male,51,Bachelors,3,10,7,33,72,5.0,3,62,Semi-Urban,Manager,137292,0 +69705,Male,29,PhD,3,96,99,79,26,3.0,6,42,Urban,Manager,114504,1 +69706,Female,38,Masters,9,8,65,7,10,8.0,7,52,Semi-Urban,Data Analyst,82006,0 +69707,Female,41,Bachelors,10,76,0,11,62,8.0,0,86,Urban,ML Engineer,41780,0 +69708,Male,48,Bachelors,5,42,84,24,72,5.0,4,41,Urban,Manager,136586,0 +69709,Male,21,Diploma,4,63,10,48,37,5.0,4,64,Urban,Software Engineer,24330,0 +69710,Female,34,Masters,17,68,68,59,32,4.0,4,44,Urban,ML Engineer,54953,0 +69711,Female,21,High School,7,33,59,16,24,8.0,2,40,Urban,Data Analyst,79081,0 +69712,Male,27,Masters,6,6,30,12,52,6.0,3,69,Semi-Urban,Software Engineer,55890,0 +69713,Male,37,Bachelors,0,53,9,89,91,2.0,5,58,Semi-Urban,Data Analyst,107614,0 +69714,Female,30,Masters,12,87,61,23,26,3.0,0,58,Urban,HR Executive,108565,0 +69715,Male,33,Bachelors,10,86,28,9,45,6.0,6,23,Urban,Data Analyst,55765,0 +69716,Male,38,Bachelors,3,31,55,60,1,0.0,6,3,Rural,ML Engineer,80989,0 +69717,Female,24,Bachelors,0,59,46,1,29,7.0,1,4,Semi-Urban,Data Analyst,143014,0 +69718,Female,50,Bachelors,0,3,58,31,16,5.0,5,80,Urban,ML Engineer,105430,0 +69719,Female,38,Diploma,9,2,96,87,85,4.0,7,67,Rural,Manager,132195,1 +69720,Female,36,Bachelors,7,37,92,41,49,4.0,3,57,Semi-Urban,ML Engineer,116469,0 +69721,Female,58,PhD,4,81,92,27,68,9.0,0,65,Semi-Urban,Manager,87220,1 +69722,Male,28,Bachelors,11,43,18,16,49,8.0,0,97,Urban,Data Analyst,130597,0 +69723,Female,30,Bachelors,6,90,7,20,89,3.0,6,87,Semi-Urban,HR Executive,39585,0 +69724,Female,32,PhD,5,61,70,51,21,9.0,5,89,Semi-Urban,Software Engineer,58302,1 +69725,Male,55,PhD,2,42,94,41,3,1.0,2,87,Urban,ML Engineer,119532,1 +69726,Female,47,Masters,1,26,4,35,20,5.0,7,63,Semi-Urban,ML Engineer,100915,0 +69727,Female,23,Bachelors,2,44,73,91,31,4.0,2,39,Urban,ML Engineer,96574,1 +69728,Male,47,High School,16,49,69,5,77,3.0,0,12,Urban,Software Engineer,69457,0 +69729,Female,23,Diploma,0,77,25,52,24,3.0,5,73,Rural,ML Engineer,129839,0 +69730,Male,53,Masters,5,5,40,94,73,4.0,2,77,Rural,Manager,28962,0 +69731,Male,37,Diploma,2,96,34,70,34,6.0,2,50,Urban,Data Analyst,108902,1 +69732,Male,51,Bachelors,8,3,58,69,43,2.0,5,4,Semi-Urban,ML Engineer,44415,0 +69733,Male,52,Masters,4,75,31,54,13,3.0,2,70,Urban,ML Engineer,131095,0 +69734,Female,37,High School,2,41,52,72,12,0.0,4,45,Urban,Data Analyst,133024,0 +69735,Male,30,Bachelors,16,49,56,80,74,8.0,0,98,Urban,Data Analyst,46224,1 +69736,Female,35,Masters,17,44,31,65,3,4.0,4,25,Urban,Data Analyst,89234,0 +69737,Female,26,Bachelors,8,12,43,91,53,2.0,3,59,Urban,Manager,36596,0 +69738,Male,28,Masters,1,72,16,78,35,7.0,6,82,Urban,Software Engineer,54199,1 +69739,Male,50,Diploma,10,52,27,40,29,6.0,1,68,Rural,Data Analyst,48330,0 +69740,Male,32,Masters,5,35,59,90,7,4.0,6,76,Rural,ML Engineer,30473,1 +69741,Female,51,Bachelors,0,20,58,61,91,7.0,4,80,Urban,Data Analyst,50026,0 +69742,Male,49,Bachelors,10,21,26,19,68,9.0,5,79,Semi-Urban,ML Engineer,64515,0 +69743,Male,56,Masters,11,5,49,2,62,9.0,0,66,Rural,HR Executive,79702,0 +69744,Male,37,Diploma,7,56,84,5,10,4.0,2,95,Urban,HR Executive,128650,1 +69745,Female,35,High School,12,43,8,54,7,2.0,1,52,Semi-Urban,ML Engineer,76160,0 +69746,Male,30,Diploma,15,10,68,26,98,0.0,3,22,Semi-Urban,HR Executive,29326,0 +69747,Female,27,Bachelors,6,0,66,49,52,2.0,5,91,Rural,ML Engineer,44913,0 +69748,Male,28,Bachelors,19,3,38,72,67,5.0,7,44,Urban,Data Analyst,122158,0 +69749,Male,36,Masters,14,84,30,86,19,8.0,6,65,Urban,Software Engineer,135245,1 +69750,Male,22,High School,15,23,84,43,78,3.0,5,74,Urban,HR Executive,60270,0 +69751,Female,59,Masters,2,61,46,29,81,8.0,2,69,Rural,ML Engineer,96584,0 +69752,Other,48,Diploma,10,62,12,86,43,2.0,6,30,Rural,ML Engineer,45729,0 +69753,Male,32,Diploma,1,77,77,87,89,3.0,1,81,Urban,Software Engineer,68974,1 +69754,Female,36,Bachelors,7,70,15,67,69,9.0,7,17,Rural,Data Analyst,41727,0 +69755,Male,57,Bachelors,17,12,44,62,71,4.0,3,44,Rural,ML Engineer,97768,0 +69756,Male,29,Diploma,0,57,78,39,34,6.0,1,84,Urban,ML Engineer,33965,1 +69757,Male,36,Bachelors,5,66,97,53,20,2.0,0,15,Semi-Urban,HR Executive,61556,0 +69758,Male,27,Bachelors,16,64,37,45,82,0.0,4,46,Rural,Manager,134489,0 +69759,Male,26,Bachelors,12,66,79,81,65,6.0,3,41,Urban,Manager,134263,1 +69760,Female,54,Diploma,18,76,92,94,38,3.0,1,83,Urban,Manager,58204,1 +69761,Male,59,High School,16,11,56,29,78,8.0,5,66,Rural,HR Executive,140411,0 +69762,Female,43,Bachelors,19,20,32,38,5,3.0,0,16,Urban,ML Engineer,28825,0 +69763,Male,36,Bachelors,15,29,13,17,27,7.0,0,8,Rural,ML Engineer,58825,0 +69764,Male,30,Masters,18,2,85,96,86,5.0,7,91,Urban,Data Analyst,146434,1 +69765,Male,57,High School,10,2,86,36,31,5.0,6,98,Semi-Urban,Manager,65300,0 +69766,Female,46,PhD,14,10,1,49,8,5.0,0,74,Urban,Data Analyst,58797,0 +69767,Male,25,Masters,8,55,20,27,24,9.0,6,90,Urban,Manager,136602,0 +69768,Female,23,Diploma,16,22,9,50,13,0.0,6,88,Urban,HR Executive,122573,0 +69769,Male,21,Masters,7,61,16,93,33,4.0,3,51,Semi-Urban,HR Executive,103906,0 +69770,Male,58,Diploma,16,8,57,79,48,9.0,1,66,Urban,Manager,148221,0 +69771,Female,28,Masters,19,2,30,7,62,5.0,5,32,Urban,Manager,107038,0 +69772,Other,36,Bachelors,15,18,3,0,31,3.0,5,99,Urban,Software Engineer,30422,0 +69773,Female,34,Bachelors,11,99,39,15,6,8.0,6,88,Semi-Urban,Manager,148625,1 +69774,Female,23,High School,2,14,17,19,57,2.0,5,81,Urban,ML Engineer,85893,0 +69775,Female,34,Bachelors,9,79,94,44,55,9.0,2,65,Semi-Urban,Software Engineer,113203,1 +69776,Male,57,Bachelors,2,93,97,64,44,8.0,2,78,Semi-Urban,Data Analyst,132261,1 +69777,Male,21,Diploma,14,46,49,5,39,3.0,5,2,Semi-Urban,Manager,128486,0 +69778,Other,43,Masters,3,51,77,19,74,9.0,7,69,Semi-Urban,ML Engineer,105897,0 +69779,Female,55,Bachelors,14,89,3,73,53,7.0,7,74,Rural,Manager,77121,0 +69780,Female,28,Diploma,14,58,93,95,95,2.0,5,49,Rural,Software Engineer,45566,1 +69781,Male,28,PhD,15,99,60,48,42,7.0,6,3,Urban,Software Engineer,21900,0 +69782,Other,49,Bachelors,19,86,51,94,83,4.0,4,31,Urban,Manager,118030,1 +69783,Male,28,High School,12,67,22,53,11,7.0,5,54,Rural,ML Engineer,61421,0 +69784,Female,22,High School,16,34,34,59,54,3.0,6,22,Urban,HR Executive,70039,0 +69785,Female,59,Masters,12,13,53,40,80,5.0,4,78,Rural,Manager,95607,0 +69786,Male,24,High School,1,35,40,66,71,2.0,3,10,Urban,Data Analyst,128246,0 +69787,Male,58,Bachelors,11,33,0,62,81,1.0,4,5,Urban,Data Analyst,43777,0 +69788,Female,53,Diploma,2,41,70,29,98,8.0,1,65,Urban,Data Analyst,144325,0 +69789,Male,49,Bachelors,17,45,16,75,61,8.0,0,52,Urban,Software Engineer,147977,0 +69790,Female,27,Diploma,7,68,99,90,49,8.0,2,97,Urban,HR Executive,36709,1 +69791,Female,38,High School,4,88,80,80,66,7.0,2,70,Urban,ML Engineer,33152,1 +69792,Male,41,Diploma,7,25,6,97,3,1.0,2,23,Urban,Data Analyst,141914,0 +69793,Male,56,PhD,11,98,42,6,5,4.0,6,59,Urban,Software Engineer,65392,0 +69794,Male,35,Diploma,10,17,53,28,45,1.0,6,6,Rural,Data Analyst,53360,0 +69795,Male,29,PhD,4,92,98,64,13,8.0,4,29,Rural,Manager,77973,1 +69796,Female,48,Bachelors,6,19,53,32,37,1.0,0,87,Rural,HR Executive,114758,0 +69797,Female,25,Masters,17,27,77,82,9,2.0,5,59,Rural,Data Analyst,136820,1 +69798,Male,47,High School,0,91,39,28,11,3.0,3,65,Urban,Manager,125745,0 +69799,Male,50,Bachelors,11,0,72,92,7,9.0,7,4,Rural,Data Analyst,100699,0 +69800,Male,28,High School,3,69,61,26,18,6.0,5,10,Urban,Software Engineer,113307,0 +69801,Female,58,Bachelors,0,56,11,25,54,3.0,4,40,Semi-Urban,HR Executive,61568,0 +69802,Female,23,Masters,19,64,1,89,45,2.0,3,43,Semi-Urban,Manager,44390,0 +69803,Male,41,Bachelors,9,71,61,1,55,9.0,2,96,Urban,Manager,107023,0 +69804,Female,39,Bachelors,4,94,1,43,2,4.0,2,49,Semi-Urban,Manager,140030,0 +69805,Other,55,Diploma,4,34,31,69,79,7.0,0,72,Urban,Manager,139412,0 +69806,Female,26,High School,5,28,37,66,34,6.0,1,17,Urban,Manager,71167,0 +69807,Male,32,Diploma,8,61,68,79,50,5.0,5,68,Urban,Software Engineer,86052,1 +69808,Female,42,Diploma,12,35,7,37,34,5.0,2,54,Semi-Urban,Manager,49177,0 +69809,Female,41,PhD,13,61,31,62,97,6.0,3,28,Semi-Urban,Software Engineer,112232,0 +69810,Male,57,Bachelors,8,69,28,48,9,9.0,7,51,Urban,Data Analyst,85410,0 +69811,Female,23,Diploma,12,1,78,90,0,4.0,3,10,Semi-Urban,Software Engineer,54471,0 +69812,Female,33,Bachelors,19,98,70,92,66,5.0,0,67,Urban,Manager,74842,1 +69813,Male,37,High School,13,94,69,18,95,1.0,6,43,Urban,Data Analyst,113902,0 +69814,Male,52,Bachelors,5,15,21,45,46,6.0,5,37,Urban,Manager,98629,0 +69815,Male,30,Bachelors,1,22,9,59,11,8.0,7,21,Semi-Urban,Software Engineer,124530,0 +69816,Female,37,Masters,6,23,96,51,97,9.0,7,1,Urban,Data Analyst,72275,0 +69817,Male,37,Bachelors,1,80,2,97,53,2.0,4,11,Semi-Urban,Software Engineer,83305,0 +69818,Male,47,High School,1,66,16,47,51,2.0,1,77,Urban,Data Analyst,81253,0 +69819,Male,36,Masters,11,99,78,95,16,1.0,4,16,Semi-Urban,Data Analyst,147612,1 +69820,Male,26,High School,4,0,7,8,55,0.0,2,69,Urban,Software Engineer,21515,0 +69821,Other,29,Bachelors,19,83,67,11,7,9.0,0,89,Urban,Data Analyst,29114,1 +69822,Male,46,Bachelors,9,21,75,13,76,8.0,7,2,Urban,ML Engineer,114635,0 +69823,Female,54,Masters,19,2,36,0,48,0.0,3,39,Urban,HR Executive,43318,0 +69824,Female,56,Masters,9,10,16,99,22,1.0,5,4,Rural,Manager,139978,0 +69825,Other,34,Masters,5,43,78,43,53,0.0,4,79,Semi-Urban,HR Executive,46811,1 +69826,Other,52,PhD,14,63,2,9,33,3.0,5,66,Urban,Data Analyst,60895,0 +69827,Male,44,Diploma,15,18,54,43,69,1.0,1,29,Urban,ML Engineer,41040,0 +69828,Other,30,Bachelors,12,5,32,15,48,5.0,2,34,Urban,ML Engineer,92652,0 +69829,Male,24,Bachelors,3,49,20,53,3,7.0,1,8,Semi-Urban,HR Executive,105008,0 +69830,Female,47,Masters,12,37,57,57,51,3.0,5,67,Semi-Urban,ML Engineer,99015,0 +69831,Female,26,Bachelors,16,91,8,75,42,8.0,6,50,Semi-Urban,Data Analyst,97015,0 +69832,Female,40,Diploma,18,8,37,81,93,2.0,0,72,Rural,Data Analyst,40565,0 +69833,Male,34,High School,18,1,41,77,54,0.0,7,31,Rural,HR Executive,43328,0 +69834,Male,29,Bachelors,4,17,50,13,94,4.0,3,27,Urban,ML Engineer,129313,0 +69835,Female,38,Bachelors,13,95,62,94,90,7.0,3,7,Urban,Manager,81289,1 +69836,Male,39,High School,18,6,60,12,51,6.0,3,88,Rural,HR Executive,46739,0 +69837,Female,30,Diploma,12,98,21,65,13,5.0,0,61,Urban,HR Executive,106484,1 +69838,Female,47,PhD,4,82,93,16,1,3.0,7,60,Urban,HR Executive,105988,1 +69839,Female,52,Bachelors,18,2,77,14,21,9.0,4,31,Urban,Software Engineer,29298,0 +69840,Male,23,High School,16,87,34,11,93,6.0,7,2,Urban,Data Analyst,30785,0 +69841,Male,49,Diploma,3,22,29,69,48,2.0,7,83,Urban,Software Engineer,134798,0 +69842,Male,43,Bachelors,7,76,16,68,47,5.0,1,16,Urban,ML Engineer,134539,0 +69843,Female,28,Masters,0,5,67,26,24,3.0,1,55,Urban,Data Analyst,149953,0 +69844,Male,27,Masters,10,27,84,46,1,5.0,7,91,Semi-Urban,Data Analyst,50022,1 +69845,Female,57,Masters,19,54,19,88,27,2.0,5,98,Urban,Data Analyst,105072,1 +69846,Male,59,High School,6,48,69,6,20,3.0,6,9,Urban,ML Engineer,30644,0 +69847,Male,47,High School,12,68,10,50,86,9.0,3,59,Urban,Data Analyst,45596,0 +69848,Female,49,Bachelors,12,54,72,38,37,4.0,2,41,Semi-Urban,HR Executive,33555,0 +69849,Male,25,Bachelors,3,47,5,51,42,4.0,5,59,Semi-Urban,Data Analyst,35903,0 +69850,Male,54,Diploma,19,75,68,88,68,3.0,4,56,Urban,Manager,47069,1 +69851,Male,32,Diploma,2,42,70,62,38,3.0,1,88,Urban,HR Executive,115844,1 +69852,Male,46,Masters,14,10,31,17,65,0.0,0,99,Semi-Urban,HR Executive,149384,0 +69853,Male,38,PhD,8,42,2,24,15,5.0,1,36,Urban,Software Engineer,91386,0 +69854,Male,44,Masters,11,43,28,24,16,7.0,7,17,Rural,ML Engineer,20503,0 +69855,Male,49,Diploma,19,16,42,4,42,0.0,1,85,Semi-Urban,HR Executive,117909,0 +69856,Female,23,Diploma,16,73,84,29,26,1.0,5,50,Semi-Urban,ML Engineer,53373,0 +69857,Male,53,High School,18,26,80,77,59,8.0,4,46,Rural,ML Engineer,37602,0 +69858,Male,55,Masters,6,63,6,42,25,8.0,6,8,Semi-Urban,Data Analyst,72696,0 +69859,Male,45,Masters,18,75,45,85,54,6.0,0,79,Urban,Software Engineer,143616,1 +69860,Female,39,Bachelors,5,76,60,62,9,9.0,2,90,Urban,ML Engineer,115330,1 +69861,Male,58,Diploma,2,52,83,8,4,9.0,6,9,Urban,Data Analyst,99348,0 +69862,Female,43,Masters,0,25,61,23,27,1.0,6,66,Rural,HR Executive,50432,0 +69863,Male,57,Masters,2,72,0,25,55,4.0,0,35,Semi-Urban,HR Executive,27512,0 +69864,Female,56,PhD,6,11,16,93,16,7.0,4,18,Urban,Software Engineer,50622,0 +69865,Male,56,Bachelors,0,18,52,37,79,6.0,3,90,Rural,Software Engineer,146111,0 +69866,Other,52,Bachelors,4,61,47,58,12,6.0,1,52,Urban,ML Engineer,43560,0 +69867,Female,44,Diploma,4,17,10,5,5,9.0,0,90,Semi-Urban,Manager,87494,0 +69868,Male,50,Masters,9,33,35,86,16,9.0,4,85,Urban,ML Engineer,57755,1 +69869,Male,57,Bachelors,2,12,19,10,97,4.0,7,0,Rural,Data Analyst,28109,0 +69870,Male,44,Masters,19,30,88,17,40,9.0,0,81,Urban,ML Engineer,109640,0 +69871,Male,40,Masters,7,96,40,22,65,8.0,4,71,Urban,HR Executive,87845,0 +69872,Female,22,Masters,17,95,29,13,49,0.0,2,66,Rural,Manager,141276,0 +69873,Male,28,Masters,0,84,81,84,5,4.0,4,66,Rural,ML Engineer,120051,1 +69874,Female,42,Bachelors,13,26,69,37,14,5.0,1,90,Urban,HR Executive,53888,0 +69875,Male,34,Diploma,18,29,83,92,32,4.0,1,14,Urban,Data Analyst,137675,0 +69876,Male,45,Bachelors,7,96,70,79,63,7.0,1,22,Urban,HR Executive,110288,1 +69877,Male,39,Masters,16,99,5,62,56,3.0,2,52,Urban,HR Executive,99351,0 +69878,Male,27,Masters,0,88,88,32,24,0.0,5,45,Rural,Software Engineer,108456,1 +69879,Male,30,Bachelors,10,24,92,7,38,2.0,5,54,Urban,Manager,31298,0 +69880,Female,55,Diploma,18,55,97,40,19,2.0,4,93,Rural,ML Engineer,99660,1 +69881,Female,27,Bachelors,2,27,85,19,66,2.0,0,89,Urban,HR Executive,124886,0 +69882,Male,39,Bachelors,0,26,73,86,30,0.0,3,79,Urban,HR Executive,149160,1 +69883,Male,45,Diploma,16,50,80,86,32,8.0,0,85,Semi-Urban,ML Engineer,114270,1 +69884,Male,55,High School,10,7,70,6,53,7.0,3,98,Rural,Software Engineer,107497,0 +69885,Other,21,Diploma,5,94,67,64,91,2.0,7,2,Semi-Urban,ML Engineer,107205,0 +69886,Female,22,Bachelors,5,63,12,49,86,9.0,3,17,Semi-Urban,Manager,47083,0 +69887,Female,28,High School,0,27,60,34,30,3.0,2,75,Semi-Urban,HR Executive,29194,0 +69888,Male,37,Bachelors,9,85,15,13,16,4.0,3,17,Urban,ML Engineer,137981,0 +69889,Male,58,High School,7,74,23,4,83,7.0,3,53,Semi-Urban,Manager,121216,0 +69890,Male,26,High School,15,7,41,3,4,7.0,6,80,Urban,Data Analyst,136029,0 +69891,Female,36,High School,19,23,73,17,40,6.0,6,76,Urban,ML Engineer,62257,0 +69892,Female,33,Masters,5,92,73,15,18,4.0,1,48,Urban,Software Engineer,69630,0 +69893,Male,58,Masters,13,40,84,71,36,3.0,6,29,Urban,Manager,61217,0 +69894,Male,50,High School,14,67,8,53,70,7.0,0,10,Urban,ML Engineer,148115,0 +69895,Male,51,Masters,3,29,21,11,58,4.0,4,84,Urban,ML Engineer,41711,0 +69896,Female,57,Diploma,2,61,8,29,35,2.0,4,99,Urban,Manager,93616,0 +69897,Male,26,Masters,3,95,79,28,57,3.0,3,79,Urban,ML Engineer,123033,1 +69898,Male,38,High School,2,50,15,24,23,4.0,4,1,Urban,HR Executive,37945,0 +69899,Female,55,Bachelors,4,84,11,25,55,3.0,4,57,Urban,Data Analyst,132119,0 +69900,Male,41,Diploma,17,18,80,33,79,2.0,6,81,Urban,Data Analyst,113447,0 +69901,Female,36,Masters,7,97,2,44,92,3.0,5,27,Semi-Urban,ML Engineer,53480,0 +69902,Male,31,Diploma,2,50,78,37,93,0.0,6,13,Urban,Software Engineer,40179,0 +69903,Male,51,Bachelors,7,34,52,1,83,6.0,2,53,Semi-Urban,Manager,33500,0 +69904,Male,23,Diploma,5,45,31,81,71,8.0,3,70,Semi-Urban,Software Engineer,70689,0 +69905,Female,24,Bachelors,8,10,55,56,21,1.0,5,92,Semi-Urban,Software Engineer,28976,0 +69906,Male,36,High School,19,78,79,77,25,9.0,5,35,Rural,Software Engineer,33124,1 +69907,Male,40,Bachelors,14,28,46,81,25,4.0,1,4,Urban,HR Executive,78063,0 +69908,Male,53,Masters,13,2,30,53,4,0.0,2,98,Urban,HR Executive,27711,0 +69909,Male,41,PhD,8,99,42,34,61,1.0,3,5,Semi-Urban,Manager,96048,0 +69910,Male,23,Masters,0,91,1,39,43,9.0,4,33,Urban,Manager,27275,0 +69911,Female,51,Bachelors,5,20,23,63,84,9.0,4,31,Rural,Manager,75996,0 +69912,Other,51,Diploma,1,56,63,38,31,2.0,7,89,Urban,ML Engineer,117318,1 +69913,Female,29,Bachelors,10,88,16,18,96,9.0,1,55,Rural,ML Engineer,42467,0 +69914,Male,23,High School,5,66,91,22,18,1.0,7,64,Semi-Urban,ML Engineer,145309,1 +69915,Male,54,Bachelors,3,64,91,69,41,5.0,7,1,Semi-Urban,Software Engineer,51582,0 +69916,Male,43,Bachelors,4,52,23,84,75,4.0,7,9,Urban,Data Analyst,53882,0 +69917,Female,46,PhD,2,40,83,80,47,8.0,6,49,Urban,HR Executive,53689,1 +69918,Male,58,Diploma,2,3,42,97,7,8.0,4,42,Urban,Software Engineer,130012,0 +69919,Male,31,Diploma,10,49,42,77,26,3.0,7,53,Urban,Manager,75554,0 +69920,Female,50,Bachelors,11,96,5,79,36,4.0,6,89,Urban,Manager,84465,1 +69921,Male,28,Bachelors,18,22,19,95,54,7.0,6,3,Semi-Urban,ML Engineer,83276,0 +69922,Male,53,Bachelors,2,78,37,56,4,5.0,0,43,Urban,Software Engineer,21510,0 +69923,Male,50,Masters,2,49,47,60,22,2.0,0,80,Urban,Manager,47317,1 +69924,Male,56,Bachelors,5,6,30,60,13,1.0,5,18,Urban,Manager,114009,0 +69925,Male,50,Bachelors,2,82,48,2,45,7.0,2,78,Urban,Manager,24019,0 +69926,Male,30,Bachelors,1,92,37,22,14,2.0,3,18,Semi-Urban,HR Executive,21558,0 +69927,Male,27,Masters,19,53,4,63,92,1.0,3,97,Urban,HR Executive,20332,0 +69928,Female,41,Masters,11,36,86,72,88,1.0,0,1,Urban,Software Engineer,107972,0 +69929,Female,58,Bachelors,8,74,76,4,74,0.0,7,89,Rural,Software Engineer,88326,1 +69930,Female,30,Bachelors,6,57,55,32,71,3.0,1,82,Urban,Data Analyst,143927,0 +69931,Male,59,Diploma,16,34,93,57,31,3.0,2,10,Urban,Manager,146256,0 +69932,Male,45,Bachelors,8,99,53,91,26,7.0,3,97,Urban,HR Executive,56906,1 +69933,Male,42,Masters,13,15,49,51,3,9.0,7,29,Semi-Urban,ML Engineer,69635,0 +69934,Female,28,Bachelors,12,98,55,40,76,0.0,3,67,Urban,Data Analyst,62901,1 +69935,Male,37,Diploma,11,35,66,28,37,7.0,2,25,Semi-Urban,HR Executive,73030,0 +69936,Male,49,Diploma,8,47,51,58,77,5.0,6,67,Urban,HR Executive,117649,0 +69937,Male,31,Bachelors,2,46,37,5,20,6.0,5,73,Semi-Urban,Data Analyst,133124,0 +69938,Male,37,High School,7,69,3,89,76,5.0,4,97,Rural,Software Engineer,149481,1 +69939,Male,54,Masters,12,60,28,11,87,3.0,4,42,Rural,HR Executive,139406,0 +69940,Other,57,Bachelors,10,37,97,74,10,1.0,6,43,Urban,HR Executive,42532,1 +69941,Female,32,PhD,12,89,85,68,93,4.0,4,69,Urban,Software Engineer,76548,1 +69942,Male,42,Masters,1,11,76,27,22,3.0,5,79,Urban,Manager,21386,0 +69943,Male,40,Masters,3,47,9,27,51,5.0,5,59,Rural,Data Analyst,130016,0 +69944,Male,40,Bachelors,1,45,12,49,69,1.0,3,59,Urban,Data Analyst,126614,0 +69945,Male,29,Bachelors,9,32,57,24,82,7.0,7,69,Semi-Urban,HR Executive,64700,0 +69946,Male,45,High School,6,97,65,60,35,8.0,1,15,Urban,ML Engineer,95601,1 +69947,Female,27,Bachelors,11,0,90,86,91,2.0,7,67,Urban,ML Engineer,64351,1 +69948,Female,46,High School,14,57,68,48,58,8.0,1,55,Rural,Data Analyst,71757,0 +69949,Male,42,High School,10,63,78,18,19,1.0,5,32,Urban,Software Engineer,96311,0 +69950,Male,34,Masters,14,56,8,63,40,0.0,1,65,Urban,Data Analyst,35825,0 +69951,Other,22,Diploma,2,75,49,1,98,5.0,2,69,Rural,ML Engineer,62844,0 +69952,Female,23,Diploma,6,54,9,39,28,9.0,6,48,Semi-Urban,HR Executive,71582,0 +69953,Other,54,High School,15,44,93,49,23,1.0,3,84,Urban,ML Engineer,46097,1 +69954,Male,45,Diploma,18,18,74,90,88,4.0,0,29,Semi-Urban,Manager,54300,0 +69955,Male,59,PhD,14,81,21,19,51,7.0,4,99,Urban,Manager,124433,0 +69956,Male,27,Masters,10,25,18,82,45,9.0,2,22,Urban,ML Engineer,59192,0 +69957,Female,25,Masters,19,54,85,61,14,4.0,2,82,Urban,Software Engineer,76667,1 +69958,Male,46,Masters,1,17,0,1,9,7.0,4,29,Urban,Software Engineer,134060,0 +69959,Other,54,Bachelors,9,4,69,85,24,6.0,2,73,Urban,Manager,43562,0 +69960,Male,42,Bachelors,8,23,38,76,77,8.0,5,62,Rural,ML Engineer,63937,0 +69961,Male,55,Diploma,16,72,52,6,87,1.0,7,26,Semi-Urban,HR Executive,95404,0 +69962,Male,33,Bachelors,1,66,26,12,90,6.0,5,52,Rural,ML Engineer,22990,0 +69963,Male,41,Masters,14,74,9,59,45,9.0,4,73,Semi-Urban,Data Analyst,138048,0 +69964,Male,48,High School,3,74,70,14,41,8.0,6,17,Urban,HR Executive,127710,0 +69965,Female,27,Bachelors,11,7,81,71,83,8.0,5,28,Urban,Data Analyst,70053,0 +69966,Male,58,Masters,13,83,13,2,51,3.0,6,71,Semi-Urban,Software Engineer,142068,0 +69967,Female,54,Bachelors,10,43,8,9,16,5.0,0,23,Semi-Urban,Data Analyst,123944,0 +69968,Female,35,High School,10,27,6,67,51,5.0,3,59,Urban,HR Executive,113607,0 +69969,Female,56,Bachelors,11,63,65,87,12,2.0,4,74,Urban,Data Analyst,85564,1 +69970,Male,55,Bachelors,4,38,5,95,77,0.0,1,4,Semi-Urban,Manager,103707,0 +69971,Male,59,Bachelors,12,88,30,3,57,6.0,4,78,Urban,Manager,92373,0 +69972,Male,50,Diploma,17,33,39,91,43,1.0,2,84,Rural,HR Executive,86909,1 +69973,Male,23,Masters,8,59,58,53,85,6.0,7,0,Urban,Manager,139883,0 +69974,Male,36,PhD,17,70,69,33,17,6.0,5,88,Urban,Manager,110717,1 +69975,Female,28,Bachelors,19,34,19,54,44,8.0,6,36,Urban,HR Executive,68414,0 +69976,Female,35,Bachelors,5,93,69,17,61,0.0,0,47,Semi-Urban,HR Executive,103457,0 +69977,Female,23,Masters,16,44,54,52,96,5.0,6,0,Semi-Urban,Data Analyst,89574,0 +69978,Female,50,Masters,17,54,17,95,20,7.0,2,90,Semi-Urban,Data Analyst,112693,1 +69979,Male,57,High School,19,22,93,87,63,2.0,4,85,Urban,ML Engineer,76593,1 +69980,Other,30,Diploma,0,56,38,3,36,9.0,1,89,Urban,ML Engineer,131706,0 +69981,Male,35,Bachelors,12,38,10,1,64,0.0,7,32,Urban,ML Engineer,124367,0 +69982,Female,54,Diploma,1,40,2,78,13,1.0,6,71,Urban,Manager,97684,0 +69983,Male,24,Bachelors,7,20,99,84,91,4.0,3,92,Rural,Software Engineer,66358,1 +69984,Female,47,Bachelors,9,34,50,64,60,7.0,6,57,Urban,Software Engineer,83265,0 +69985,Male,41,Bachelors,1,15,66,66,27,4.0,5,20,Urban,Data Analyst,98187,0 +69986,Female,30,Bachelors,4,47,33,79,0,1.0,7,14,Urban,Data Analyst,55062,0 +69987,Male,31,Masters,1,72,39,55,94,0.0,5,97,Rural,Data Analyst,93996,1 +69988,Male,31,Diploma,5,79,43,70,97,6.0,3,55,Urban,HR Executive,123182,1 +69989,Male,21,Diploma,18,15,40,51,85,7.0,0,40,Rural,Software Engineer,59383,0 +69990,Female,52,High School,16,50,86,20,15,3.0,1,39,Urban,Data Analyst,144678,0 +69991,Male,29,Masters,19,4,1,87,79,9.0,3,83,Urban,ML Engineer,82218,0 +69992,Male,57,Bachelors,11,47,50,71,80,9.0,4,9,Urban,Data Analyst,127347,0 +69993,Male,36,High School,10,60,98,50,66,8.0,5,70,Rural,ML Engineer,67043,1 +69994,Female,52,High School,4,70,91,70,79,1.0,7,20,Semi-Urban,Manager,57259,1 +69995,Male,56,Diploma,7,1,85,97,94,6.0,7,41,Urban,Data Analyst,77166,0 +69996,Male,27,Masters,16,3,15,63,61,1.0,3,81,Urban,Software Engineer,58962,0 +69997,Female,21,Masters,18,34,99,87,34,6.0,6,14,Urban,HR Executive,34902,0 +69998,Female,56,High School,4,49,33,7,61,0.0,0,55,Rural,Data Analyst,144302,0 +69999,Male,26,Bachelors,9,75,55,95,3,9.0,7,2,Urban,HR Executive,54460,0 +70000,Male,23,Diploma,4,58,63,75,11,8.0,4,4,Semi-Urban,ML Engineer,138448,0 +70001,Male,53,Masters,14,63,34,28,48,4.0,4,18,Urban,ML Engineer,119963,0 +70002,Female,39,Masters,5,80,97,30,61,2.0,3,99,Urban,Manager,108813,1 +70003,Male,21,Bachelors,16,4,17,53,53,1.0,6,73,Urban,Software Engineer,39810,0 +70004,Male,26,Bachelors,12,20,32,37,23,0.0,4,45,Rural,Manager,25315,0 +70005,Male,47,Diploma,15,94,75,85,29,5.0,4,9,Urban,Data Analyst,109011,1 +70006,Female,56,Masters,6,66,81,19,85,7.0,6,74,Rural,Manager,127674,0 +70007,Other,53,Diploma,11,83,20,36,60,9.0,0,98,Urban,ML Engineer,40013,0 +70008,Female,45,Bachelors,9,85,16,22,90,7.0,0,34,Semi-Urban,ML Engineer,39624,0 +70009,Female,37,High School,13,42,43,41,43,9.0,3,19,Urban,Data Analyst,138149,0 +70010,Female,54,High School,3,49,72,72,46,8.0,0,39,Rural,HR Executive,95335,0 +70011,Male,53,Bachelors,5,89,40,24,99,5.0,5,80,Urban,ML Engineer,34383,0 +70012,Female,25,Masters,10,48,32,79,30,2.0,7,49,Rural,Manager,80920,0 +70013,Male,53,Bachelors,16,7,87,11,18,8.0,4,5,Urban,ML Engineer,120116,0 +70014,Male,39,Masters,13,39,79,66,79,0.0,5,70,Urban,Manager,79059,1 +70015,Female,43,Bachelors,17,66,56,28,24,8.0,3,83,Urban,Software Engineer,67608,0 +70016,Male,58,PhD,13,4,67,32,70,5.0,7,14,Urban,Manager,81613,0 +70017,Male,26,Bachelors,15,50,6,22,38,4.0,5,63,Rural,HR Executive,95953,0 +70018,Female,23,Bachelors,14,39,52,50,82,9.0,7,74,Urban,Data Analyst,23961,0 +70019,Male,28,Bachelors,19,27,78,57,55,1.0,2,84,Semi-Urban,Data Analyst,37107,1 +70020,Female,38,PhD,7,30,21,80,76,3.0,1,48,Rural,Software Engineer,122668,0 +70021,Male,24,Bachelors,8,46,38,71,16,8.0,4,50,Urban,Software Engineer,59606,0 +70022,Male,56,Diploma,6,48,52,88,43,4.0,3,27,Urban,Data Analyst,80726,0 +70023,Male,49,Bachelors,13,4,5,28,89,9.0,4,84,Rural,HR Executive,125913,0 +70024,Male,45,Bachelors,18,75,83,2,43,0.0,4,57,Semi-Urban,Software Engineer,67079,0 +70025,Male,57,PhD,2,71,1,84,43,6.0,5,98,Urban,ML Engineer,140273,1 +70026,Male,27,Bachelors,18,17,60,44,8,5.0,4,38,Urban,Data Analyst,123360,0 +70027,Male,25,High School,17,23,22,24,55,2.0,5,90,Semi-Urban,Manager,48542,0 +70028,Male,26,PhD,0,94,42,59,11,0.0,1,5,Semi-Urban,HR Executive,139190,0 +70029,Male,59,PhD,5,60,43,71,56,5.0,7,11,Semi-Urban,HR Executive,21474,0 +70030,Male,48,Masters,7,18,31,82,32,3.0,3,88,Semi-Urban,Software Engineer,129800,0 +70031,Female,30,Masters,1,62,2,22,61,7.0,5,53,Urban,Manager,119222,0 +70032,Male,30,High School,5,41,47,78,92,6.0,6,33,Urban,ML Engineer,20107,0 +70033,Female,48,PhD,13,78,29,7,57,8.0,2,46,Semi-Urban,ML Engineer,23692,0 +70034,Male,46,Diploma,16,91,4,92,58,1.0,1,9,Urban,Data Analyst,80763,0 +70035,Other,29,Masters,1,63,29,6,95,5.0,7,88,Rural,ML Engineer,43398,0 +70036,Male,22,Diploma,15,81,44,44,62,1.0,5,29,Urban,ML Engineer,68267,0 +70037,Female,40,Bachelors,15,93,68,72,33,7.0,2,1,Urban,HR Executive,146726,0 +70038,Male,41,Bachelors,2,34,4,51,50,7.0,5,35,Urban,ML Engineer,53236,0 +70039,Other,29,Bachelors,9,57,57,34,52,0.0,5,59,Urban,Software Engineer,98221,0 +70040,Female,32,Bachelors,16,4,48,6,78,2.0,6,67,Semi-Urban,ML Engineer,46018,0 +70041,Male,22,Masters,9,89,75,80,92,7.0,5,3,Semi-Urban,Data Analyst,66339,1 +70042,Male,24,Bachelors,14,23,82,57,85,4.0,3,20,Semi-Urban,Software Engineer,32487,0 +70043,Male,39,Masters,4,38,86,16,59,5.0,6,45,Rural,Software Engineer,68543,0 +70044,Male,28,Masters,13,87,72,96,8,3.0,6,55,Urban,Manager,74388,1 +70045,Male,48,PhD,3,69,32,87,27,8.0,2,28,Urban,HR Executive,65418,0 +70046,Male,46,Diploma,2,27,25,42,28,8.0,3,23,Semi-Urban,HR Executive,115984,0 +70047,Male,58,High School,11,78,64,32,8,6.0,3,73,Semi-Urban,HR Executive,136054,1 +70048,Male,52,Diploma,11,53,62,87,8,7.0,4,90,Urban,Data Analyst,116073,1 +70049,Female,48,Diploma,14,92,97,17,44,4.0,5,29,Urban,Data Analyst,58682,0 +70050,Male,59,Masters,18,37,43,84,55,4.0,0,62,Urban,ML Engineer,42237,0 +70051,Male,56,Bachelors,1,38,51,13,84,5.0,0,99,Semi-Urban,Software Engineer,98939,0 +70052,Male,23,PhD,8,35,77,45,18,1.0,2,57,Urban,ML Engineer,85182,0 +70053,Male,28,High School,14,42,4,37,98,4.0,7,35,Semi-Urban,Data Analyst,133015,0 +70054,Male,38,Bachelors,10,18,40,9,74,4.0,3,1,Urban,ML Engineer,132917,0 +70055,Male,32,Bachelors,13,80,12,22,87,5.0,4,32,Urban,Data Analyst,126028,0 +70056,Male,36,Diploma,14,25,61,32,17,9.0,0,57,Urban,Software Engineer,107168,0 +70057,Male,24,Masters,11,75,19,1,88,1.0,2,35,Semi-Urban,HR Executive,135048,0 +70058,Female,42,Bachelors,4,55,90,39,52,0.0,2,6,Urban,ML Engineer,96381,0 +70059,Female,26,Diploma,16,46,68,66,3,4.0,1,34,Urban,Data Analyst,64814,0 +70060,Female,37,High School,6,25,22,4,77,8.0,4,87,Urban,Software Engineer,114956,0 +70061,Male,42,Bachelors,4,90,94,8,72,8.0,0,38,Urban,Data Analyst,73417,0 +70062,Male,57,Masters,8,29,28,84,11,7.0,5,33,Rural,Software Engineer,121447,0 +70063,Female,34,Bachelors,14,83,8,34,52,8.0,1,50,Rural,HR Executive,101268,0 +70064,Other,43,Masters,13,73,71,62,72,1.0,6,9,Rural,HR Executive,65739,0 +70065,Male,39,Bachelors,17,3,10,30,37,1.0,4,27,Urban,Manager,29978,0 +70066,Female,41,Diploma,2,65,98,29,91,5.0,2,94,Urban,Manager,127701,1 +70067,Female,38,High School,3,79,58,46,74,1.0,6,46,Urban,HR Executive,92330,0 +70068,Other,40,Bachelors,18,68,56,67,0,0.0,3,51,Urban,HR Executive,30691,1 +70069,Male,44,PhD,3,26,92,59,13,3.0,4,59,Semi-Urban,ML Engineer,51996,1 +70070,Male,52,Diploma,2,14,71,77,12,7.0,1,72,Urban,HR Executive,93846,0 +70071,Male,35,High School,19,20,32,50,16,9.0,5,97,Semi-Urban,Software Engineer,129794,0 +70072,Female,51,Bachelors,1,73,0,84,10,5.0,7,46,Semi-Urban,Manager,80033,0 +70073,Female,33,Diploma,5,63,65,36,11,7.0,1,50,Urban,HR Executive,131394,0 +70074,Female,27,Bachelors,2,12,14,20,49,3.0,6,51,Semi-Urban,ML Engineer,91842,0 +70075,Female,45,High School,6,20,9,92,87,4.0,1,72,Semi-Urban,ML Engineer,84883,0 +70076,Male,37,Bachelors,10,0,98,8,0,7.0,1,63,Urban,Manager,84856,0 +70077,Male,49,High School,5,93,42,64,10,8.0,4,61,Semi-Urban,Data Analyst,33651,1 +70078,Male,43,Masters,8,64,33,74,35,0.0,1,88,Semi-Urban,ML Engineer,122557,1 +70079,Other,57,Bachelors,7,6,88,62,3,8.0,4,61,Rural,HR Executive,119430,0 +70080,Male,41,Diploma,13,72,63,5,13,7.0,1,67,Urban,Manager,125102,0 +70081,Female,59,Bachelors,14,22,51,35,8,0.0,6,94,Rural,Manager,149222,0 +70082,Male,49,Bachelors,8,68,58,94,93,6.0,4,52,Urban,Manager,147818,1 +70083,Female,48,High School,3,74,10,37,61,5.0,5,93,Urban,ML Engineer,106023,0 +70084,Male,39,Diploma,16,98,20,52,37,4.0,7,14,Urban,HR Executive,124225,0 +70085,Female,48,Bachelors,16,14,80,58,20,2.0,7,85,Urban,Software Engineer,60893,0 +70086,Female,41,Masters,17,2,55,71,84,2.0,5,71,Urban,ML Engineer,68780,0 +70087,Male,38,Diploma,1,6,37,84,32,2.0,4,24,Semi-Urban,ML Engineer,25115,0 +70088,Male,54,PhD,9,54,5,29,94,0.0,1,17,Urban,HR Executive,33868,0 +70089,Other,24,High School,9,24,39,29,7,3.0,5,31,Semi-Urban,HR Executive,57772,0 +70090,Male,36,Diploma,7,95,20,50,81,0.0,0,20,Urban,Software Engineer,50469,0 +70091,Male,22,Bachelors,10,97,10,93,14,9.0,7,56,Semi-Urban,HR Executive,39134,1 +70092,Male,53,Bachelors,18,14,49,44,2,4.0,7,97,Urban,ML Engineer,51773,0 +70093,Female,44,Diploma,7,1,3,88,20,1.0,1,28,Urban,ML Engineer,136120,0 +70094,Male,58,Bachelors,13,71,93,31,83,0.0,0,62,Urban,HR Executive,123122,1 +70095,Male,40,Diploma,8,25,60,12,95,5.0,7,45,Urban,ML Engineer,123978,0 +70096,Male,45,Masters,11,5,7,30,3,6.0,5,56,Urban,Manager,145400,0 +70097,Other,32,Masters,10,10,69,37,2,6.0,2,76,Urban,ML Engineer,116914,0 +70098,Male,48,Diploma,15,18,51,7,4,1.0,2,98,Urban,HR Executive,57377,0 +70099,Male,30,Bachelors,16,36,21,51,34,6.0,7,15,Urban,Data Analyst,125833,0 +70100,Male,21,Bachelors,14,38,35,6,63,6.0,7,97,Semi-Urban,HR Executive,31900,0 +70101,Male,40,Diploma,6,2,4,17,85,6.0,5,59,Urban,HR Executive,117736,0 +70102,Male,58,Diploma,10,55,92,29,84,5.0,6,81,Urban,Software Engineer,87078,1 +70103,Female,32,High School,13,53,85,73,15,5.0,2,63,Urban,HR Executive,39919,1 +70104,Female,26,High School,0,86,9,23,69,3.0,6,97,Semi-Urban,ML Engineer,120367,0 +70105,Male,24,Bachelors,6,19,18,24,80,1.0,7,74,Urban,ML Engineer,130989,0 +70106,Male,36,Masters,4,64,48,55,68,9.0,6,60,Urban,Manager,96172,0 +70107,Male,27,Masters,3,20,91,92,3,3.0,6,64,Urban,Data Analyst,58873,1 +70108,Male,25,Bachelors,0,75,39,37,48,1.0,2,41,Urban,HR Executive,46092,0 +70109,Female,29,Masters,0,69,56,66,67,1.0,0,44,Urban,Software Engineer,111282,0 +70110,Male,39,High School,6,86,5,9,6,6.0,6,46,Urban,Data Analyst,102320,0 +70111,Male,43,Bachelors,2,86,70,60,76,1.0,1,47,Semi-Urban,Data Analyst,110473,1 +70112,Male,29,Masters,11,87,49,85,37,5.0,3,8,Urban,Manager,30304,0 +70113,Male,53,Masters,1,13,20,33,95,5.0,6,65,Rural,Manager,86111,0 +70114,Male,58,Bachelors,19,25,82,38,9,6.0,5,25,Urban,Data Analyst,118161,0 +70115,Male,42,Masters,11,53,24,17,18,9.0,6,56,Urban,HR Executive,30286,0 +70116,Female,42,High School,6,21,46,33,23,7.0,2,76,Urban,ML Engineer,65896,0 +70117,Male,49,Bachelors,19,37,36,0,34,2.0,5,62,Rural,Manager,107945,0 +70118,Female,57,PhD,5,29,79,96,79,7.0,0,27,Urban,ML Engineer,141456,0 +70119,Male,28,Masters,16,0,95,84,73,4.0,0,28,Semi-Urban,HR Executive,84879,0 +70120,Female,54,High School,14,11,89,60,11,4.0,4,81,Semi-Urban,HR Executive,123648,1 +70121,Male,25,Masters,17,21,31,20,37,5.0,6,78,Urban,Manager,84344,0 +70122,Male,54,Bachelors,18,39,84,7,24,9.0,0,10,Urban,HR Executive,106987,0 +70123,Male,48,Bachelors,3,64,10,62,39,8.0,3,38,Urban,Manager,139292,0 +70124,Male,21,Masters,8,34,24,2,71,6.0,6,89,Semi-Urban,HR Executive,63861,0 +70125,Male,22,Bachelors,2,32,76,71,56,4.0,4,58,Urban,HR Executive,75212,1 +70126,Male,21,Diploma,2,51,4,52,12,3.0,4,78,Urban,ML Engineer,51707,0 +70127,Male,57,Masters,2,32,49,22,16,0.0,4,78,Semi-Urban,Data Analyst,118492,0 +70128,Female,56,Bachelors,0,1,34,87,67,7.0,7,43,Urban,Manager,133148,0 +70129,Male,31,PhD,6,29,4,44,24,2.0,7,96,Urban,HR Executive,47713,0 +70130,Male,59,Diploma,11,11,35,89,64,5.0,7,24,Urban,Data Analyst,130565,0 +70131,Male,24,High School,14,75,45,38,99,5.0,7,57,Urban,Data Analyst,95889,0 +70132,Male,21,High School,16,39,72,86,79,4.0,2,69,Semi-Urban,HR Executive,69415,1 +70133,Other,33,Bachelors,10,35,9,46,47,7.0,3,66,Semi-Urban,Software Engineer,24672,0 +70134,Male,36,Bachelors,11,17,83,30,55,3.0,6,45,Urban,Manager,126063,0 +70135,Male,43,Bachelors,4,13,46,14,71,1.0,6,16,Urban,Data Analyst,36996,0 +70136,Male,57,Bachelors,7,67,45,79,69,0.0,4,70,Semi-Urban,ML Engineer,146134,1 +70137,Female,21,Masters,4,77,15,47,56,8.0,1,78,Rural,Software Engineer,76082,0 +70138,Male,49,Bachelors,9,75,4,37,71,4.0,5,60,Rural,ML Engineer,39702,0 +70139,Female,30,Diploma,19,66,32,27,58,6.0,1,17,Urban,Data Analyst,104106,0 +70140,Female,37,Diploma,3,56,45,25,6,6.0,5,12,Urban,Data Analyst,31283,0 +70141,Female,28,Bachelors,11,53,43,54,17,8.0,3,17,Urban,ML Engineer,124267,0 +70142,Female,36,Diploma,1,24,33,73,62,7.0,1,11,Urban,Manager,146199,0 +70143,Female,50,Diploma,17,52,31,39,80,6.0,1,53,Urban,Software Engineer,136873,0 +70144,Male,56,Bachelors,5,8,34,11,87,1.0,5,54,Rural,Data Analyst,51977,0 +70145,Male,57,Bachelors,18,0,25,67,62,7.0,7,8,Rural,ML Engineer,24041,0 +70146,Female,38,High School,3,45,12,80,49,6.0,4,50,Semi-Urban,Data Analyst,135161,0 +70147,Male,37,Diploma,18,58,93,98,28,1.0,1,54,Semi-Urban,Data Analyst,146129,1 +70148,Female,43,Bachelors,14,11,46,68,7,5.0,3,36,Rural,Manager,39718,0 +70149,Male,31,Bachelors,16,16,5,38,55,9.0,1,21,Urban,Data Analyst,122624,0 +70150,Male,51,High School,17,38,98,47,60,2.0,3,49,Urban,Software Engineer,63020,0 +70151,Female,54,Diploma,19,41,72,75,32,5.0,1,13,Semi-Urban,Data Analyst,29675,0 +70152,Male,32,Bachelors,1,32,18,50,84,7.0,6,90,Urban,HR Executive,30627,0 +70153,Female,34,Bachelors,6,20,86,81,41,6.0,1,75,Rural,HR Executive,128939,1 +70154,Other,40,Masters,1,64,10,19,75,1.0,4,85,Urban,Software Engineer,84945,0 +70155,Female,21,Bachelors,16,46,7,26,54,3.0,2,42,Urban,HR Executive,143680,0 +70156,Male,34,Masters,8,87,38,6,97,3.0,4,97,Urban,Manager,32020,0 +70157,Female,34,Diploma,6,44,71,17,30,5.0,7,21,Urban,Software Engineer,39914,0 +70158,Male,58,Masters,0,62,56,84,2,8.0,4,81,Urban,ML Engineer,105780,1 +70159,Male,41,PhD,9,9,72,54,87,7.0,5,19,Urban,Manager,149962,0 +70160,Male,52,Bachelors,3,58,23,91,27,9.0,7,14,Urban,Data Analyst,122770,0 +70161,Male,52,Bachelors,0,7,12,7,53,8.0,6,62,Semi-Urban,Manager,35532,0 +70162,Male,27,Bachelors,2,37,65,78,63,3.0,7,36,Urban,Software Engineer,81231,0 +70163,Male,32,Bachelors,4,87,60,19,78,4.0,0,24,Urban,HR Executive,119167,0 +70164,Other,33,Diploma,4,56,89,60,86,7.0,5,91,Urban,Manager,32305,1 +70165,Female,58,Bachelors,9,31,14,14,91,7.0,4,16,Rural,Manager,123425,0 +70166,Female,49,Bachelors,12,3,48,10,63,8.0,3,64,Urban,Manager,142576,0 +70167,Male,42,Diploma,8,24,25,20,41,7.0,7,19,Urban,HR Executive,51595,0 +70168,Male,34,Masters,7,60,49,74,73,9.0,4,7,Urban,ML Engineer,34645,0 +70169,Male,33,Bachelors,11,22,57,84,27,0.0,5,95,Urban,HR Executive,107220,1 +70170,Female,25,Masters,12,30,68,35,47,8.0,5,22,Urban,Software Engineer,113432,0 +70171,Other,34,High School,2,66,92,8,31,5.0,0,96,Urban,ML Engineer,71925,1 +70172,Female,23,High School,13,36,64,60,58,3.0,5,2,Urban,Data Analyst,93995,0 +70173,Female,22,PhD,0,63,67,14,77,6.0,1,42,Urban,HR Executive,97199,0 +70174,Male,36,Bachelors,16,26,57,8,65,4.0,1,50,Urban,Data Analyst,128571,0 +70175,Male,22,Diploma,4,0,45,13,9,1.0,0,62,Urban,ML Engineer,94599,0 +70176,Male,21,Diploma,13,39,11,10,14,2.0,7,61,Urban,Data Analyst,112195,0 +70177,Male,48,High School,7,94,99,9,74,1.0,4,70,Urban,Software Engineer,104538,1 +70178,Female,32,Diploma,2,24,40,86,13,3.0,5,89,Urban,ML Engineer,29697,0 +70179,Female,27,High School,2,90,12,81,17,2.0,0,49,Urban,Manager,94430,0 +70180,Male,57,Masters,10,25,91,5,55,0.0,5,74,Rural,ML Engineer,62133,0 +70181,Female,28,Masters,17,75,18,2,12,1.0,3,40,Semi-Urban,Manager,119439,0 +70182,Male,31,PhD,18,18,16,89,59,7.0,3,4,Semi-Urban,Manager,28220,0 +70183,Female,29,Bachelors,1,24,20,48,9,3.0,4,44,Urban,Software Engineer,113899,0 +70184,Male,52,High School,16,66,16,4,44,6.0,5,78,Semi-Urban,Data Analyst,52470,0 +70185,Male,48,Bachelors,5,88,64,91,70,1.0,1,4,Rural,Software Engineer,143575,1 +70186,Female,58,Masters,0,37,18,67,69,4.0,4,0,Urban,Software Engineer,33119,0 +70187,Male,21,Bachelors,15,92,49,69,33,6.0,3,40,Semi-Urban,Manager,140882,1 +70188,Male,48,Masters,12,83,56,57,56,8.0,7,54,Urban,HR Executive,74811,1 +70189,Female,49,Bachelors,8,19,43,90,54,8.0,3,36,Rural,Software Engineer,112586,0 +70190,Male,25,Diploma,1,41,11,68,68,4.0,4,87,Urban,Software Engineer,148623,0 +70191,Female,39,Bachelors,8,82,37,57,4,3.0,2,26,Urban,Data Analyst,110082,0 +70192,Female,21,Bachelors,17,12,75,15,3,4.0,0,15,Rural,Manager,114842,0 +70193,Male,56,High School,12,8,48,75,66,8.0,0,58,Rural,Manager,123123,0 +70194,Male,38,Bachelors,17,6,44,78,94,1.0,7,1,Urban,Data Analyst,54537,0 +70195,Male,55,PhD,12,72,45,54,35,1.0,1,77,Semi-Urban,HR Executive,35609,1 +70196,Male,22,PhD,17,5,95,45,94,5.0,5,15,Semi-Urban,Software Engineer,149448,0 +70197,Male,36,Bachelors,13,0,35,94,61,7.0,6,41,Urban,ML Engineer,73361,0 +70198,Male,42,Diploma,11,15,80,25,76,5.0,6,80,Semi-Urban,Manager,69430,0 +70199,Female,43,Bachelors,2,25,98,3,53,1.0,7,89,Urban,ML Engineer,148414,0 +70200,Male,42,Bachelors,2,98,48,54,15,1.0,6,29,Urban,HR Executive,118593,0 +70201,Male,30,PhD,6,70,10,5,87,3.0,4,96,Urban,HR Executive,116131,0 +70202,Female,45,Bachelors,18,24,34,66,36,8.0,3,30,Urban,HR Executive,91994,0 +70203,Female,33,Bachelors,15,1,90,17,97,5.0,5,16,Rural,Manager,102802,0 +70204,Other,53,PhD,12,15,42,81,77,1.0,5,70,Urban,Software Engineer,22893,0 +70205,Female,43,Bachelors,5,48,7,8,6,5.0,7,15,Urban,Data Analyst,128834,0 +70206,Male,52,Diploma,18,33,7,58,44,2.0,7,94,Rural,Data Analyst,91368,0 +70207,Other,46,High School,14,80,52,58,23,0.0,6,1,Urban,ML Engineer,20204,0 +70208,Male,39,Diploma,17,81,64,23,92,6.0,2,29,Urban,Software Engineer,129134,0 +70209,Female,25,Bachelors,15,97,63,31,88,1.0,7,35,Semi-Urban,ML Engineer,91266,0 +70210,Male,57,Bachelors,1,7,74,18,11,5.0,6,42,Semi-Urban,Data Analyst,48626,0 +70211,Male,36,Masters,4,36,63,79,71,3.0,2,87,Urban,ML Engineer,42380,1 +70212,Female,59,Bachelors,17,83,75,22,27,6.0,6,86,Urban,HR Executive,122043,1 +70213,Male,33,Masters,7,19,46,6,50,1.0,3,43,Semi-Urban,Data Analyst,38239,0 +70214,Male,49,Masters,16,33,82,68,15,4.0,5,67,Urban,ML Engineer,89109,1 +70215,Female,48,Diploma,12,55,25,75,23,8.0,6,8,Urban,ML Engineer,74938,0 +70216,Male,58,High School,2,0,6,2,35,7.0,1,86,Urban,ML Engineer,68585,0 +70217,Male,30,Diploma,9,86,19,61,34,8.0,6,45,Semi-Urban,Data Analyst,142862,0 +70218,Male,57,Bachelors,14,71,12,48,79,4.0,2,56,Urban,Data Analyst,32537,0 +70219,Female,38,High School,18,67,83,85,76,3.0,7,21,Urban,Software Engineer,35378,1 +70220,Male,26,Diploma,14,61,67,61,19,2.0,6,70,Urban,HR Executive,67096,1 +70221,Male,53,Masters,9,83,22,11,54,4.0,4,91,Urban,Data Analyst,94395,0 +70222,Male,58,Bachelors,11,53,12,55,9,5.0,0,3,Semi-Urban,ML Engineer,115672,0 +70223,Male,48,Bachelors,8,14,87,89,31,9.0,0,57,Urban,HR Executive,59855,1 +70224,Male,36,Bachelors,18,28,49,81,89,8.0,0,31,Urban,Data Analyst,139042,0 +70225,Female,47,Bachelors,3,69,21,83,20,1.0,5,58,Urban,HR Executive,115651,0 +70226,Male,28,Diploma,3,95,45,51,55,7.0,7,50,Urban,Software Engineer,53477,1 +70227,Male,46,Diploma,6,54,2,49,8,9.0,2,66,Urban,ML Engineer,45047,0 +70228,Male,58,High School,3,59,64,71,70,1.0,5,83,Rural,Software Engineer,145394,1 +70229,Female,41,Bachelors,19,73,52,52,77,1.0,6,69,Rural,HR Executive,65008,1 +70230,Female,53,Bachelors,8,7,50,0,92,2.0,2,83,Urban,Manager,38324,0 +70231,Male,48,Bachelors,11,73,43,53,20,8.0,0,59,Urban,Manager,143311,0 +70232,Male,51,Masters,19,33,58,33,77,0.0,5,20,Urban,Software Engineer,139215,0 +70233,Female,27,Diploma,9,65,77,0,51,2.0,6,52,Urban,Data Analyst,76004,0 +70234,Female,30,Bachelors,6,95,11,97,62,1.0,0,61,Urban,ML Engineer,76832,1 +70235,Male,56,High School,16,10,76,80,10,2.0,4,19,Urban,Data Analyst,51093,0 +70236,Female,31,Bachelors,13,44,65,34,13,5.0,7,3,Semi-Urban,HR Executive,86524,0 +70237,Female,41,Bachelors,5,71,33,30,33,9.0,2,57,Semi-Urban,Software Engineer,106861,0 +70238,Male,44,Diploma,15,34,30,71,86,9.0,3,99,Urban,HR Executive,81609,0 +70239,Male,34,Diploma,9,92,76,52,68,3.0,3,18,Urban,Data Analyst,83622,1 +70240,Male,52,Bachelors,17,6,72,30,47,0.0,5,32,Semi-Urban,Manager,116144,0 +70241,Other,37,Bachelors,13,80,91,95,13,1.0,4,52,Urban,ML Engineer,107925,1 +70242,Female,38,Diploma,19,79,64,29,69,6.0,3,40,Semi-Urban,Data Analyst,114932,0 +70243,Male,24,High School,4,46,5,64,38,8.0,0,47,Urban,HR Executive,111875,0 +70244,Male,57,Masters,14,6,15,32,63,2.0,0,81,Urban,Manager,81275,0 +70245,Male,49,PhD,0,40,51,64,52,1.0,0,29,Semi-Urban,Software Engineer,43929,0 +70246,Male,36,High School,1,58,67,3,95,6.0,5,22,Urban,Data Analyst,121455,0 +70247,Male,39,Masters,3,33,18,51,82,2.0,4,54,Rural,Data Analyst,94189,0 +70248,Male,50,Bachelors,5,87,96,18,57,1.0,6,53,Semi-Urban,Software Engineer,114138,1 +70249,Male,26,Bachelors,7,21,67,14,73,0.0,3,31,Urban,HR Executive,53889,0 +70250,Male,39,Bachelors,0,36,53,83,46,1.0,3,88,Urban,Manager,114787,1 +70251,Female,40,Diploma,16,11,24,83,13,5.0,6,11,Urban,Manager,101835,0 +70252,Female,30,Bachelors,5,15,47,83,0,1.0,5,95,Rural,Manager,80674,0 +70253,Female,40,Bachelors,3,90,78,82,8,8.0,6,10,Urban,Data Analyst,84286,1 +70254,Female,29,High School,2,27,59,71,85,0.0,7,37,Rural,ML Engineer,82730,0 +70255,Male,43,Bachelors,13,2,51,84,81,4.0,5,89,Urban,Data Analyst,90820,0 +70256,Male,59,High School,9,41,4,53,50,6.0,4,78,Urban,ML Engineer,24884,0 +70257,Male,23,Bachelors,18,77,89,67,97,3.0,7,16,Semi-Urban,HR Executive,115404,1 +70258,Male,47,Bachelors,1,40,35,89,87,5.0,1,85,Urban,ML Engineer,69679,1 +70259,Female,41,High School,6,29,45,75,97,3.0,2,9,Urban,Manager,141196,0 +70260,Male,31,Masters,6,89,76,62,17,6.0,4,21,Urban,Data Analyst,40657,1 +70261,Male,38,Diploma,4,13,49,23,55,9.0,6,96,Semi-Urban,Manager,121022,0 +70262,Male,55,Diploma,10,66,2,60,36,6.0,0,52,Rural,Manager,132484,0 +70263,Male,53,Masters,11,84,77,2,0,5.0,2,87,Urban,Software Engineer,38588,1 +70264,Male,56,High School,2,38,31,30,3,9.0,7,43,Urban,ML Engineer,53244,0 +70265,Male,55,Bachelors,6,32,11,0,53,5.0,5,20,Semi-Urban,Software Engineer,32235,0 +70266,Male,37,Masters,13,36,52,67,36,2.0,2,84,Urban,HR Executive,115377,1 +70267,Male,35,High School,9,26,65,0,1,7.0,5,79,Urban,HR Executive,40897,0 +70268,Male,38,Diploma,2,42,67,5,64,9.0,5,95,Semi-Urban,Software Engineer,98612,0 +70269,Female,47,High School,2,9,18,60,10,4.0,0,32,Urban,Data Analyst,97254,0 +70270,Male,36,High School,3,49,55,33,71,0.0,3,64,Urban,HR Executive,105037,0 +70271,Female,43,Bachelors,13,30,22,3,73,6.0,3,63,Urban,HR Executive,100716,0 +70272,Male,51,Bachelors,2,12,22,67,23,3.0,4,77,Rural,Manager,54157,0 +70273,Male,57,Bachelors,19,74,20,76,27,9.0,1,22,Rural,Data Analyst,80325,0 +70274,Male,40,Bachelors,12,91,65,23,6,8.0,7,67,Urban,Data Analyst,125996,1 +70275,Other,53,Masters,19,77,83,54,60,3.0,6,5,Rural,ML Engineer,68310,0 +70276,Male,30,Masters,13,46,95,19,64,1.0,7,24,Semi-Urban,Data Analyst,23558,0 +70277,Female,26,High School,15,18,9,53,56,4.0,0,61,Urban,Manager,116932,0 +70278,Female,22,Diploma,11,72,44,4,92,3.0,5,46,Semi-Urban,Software Engineer,96602,0 +70279,Male,43,Bachelors,0,72,7,34,59,2.0,6,13,Urban,HR Executive,94692,0 +70280,Male,52,Diploma,11,22,61,50,75,2.0,6,89,Urban,HR Executive,145856,0 +70281,Female,41,Masters,8,76,69,78,98,9.0,1,66,Semi-Urban,ML Engineer,95431,1 +70282,Male,56,Masters,18,78,85,36,64,8.0,3,42,Urban,Manager,71446,1 +70283,Male,21,Bachelors,1,65,22,59,54,1.0,3,57,Urban,Software Engineer,72881,0 +70284,Female,54,Masters,12,25,14,40,43,6.0,4,67,Semi-Urban,Data Analyst,81619,0 +70285,Female,58,High School,19,4,5,9,59,3.0,1,64,Urban,HR Executive,50483,0 +70286,Female,54,Bachelors,2,15,24,89,59,1.0,1,73,Rural,HR Executive,67580,0 +70287,Male,23,PhD,9,31,85,56,40,0.0,6,42,Semi-Urban,HR Executive,83924,0 +70288,Male,32,Diploma,19,61,98,74,39,0.0,6,84,Urban,Data Analyst,115288,1 +70289,Male,58,Bachelors,4,95,81,1,19,0.0,1,1,Urban,Data Analyst,35791,0 +70290,Male,33,Bachelors,12,23,17,91,31,5.0,1,79,Urban,Manager,113582,0 +70291,Male,31,Masters,7,89,80,29,81,4.0,4,15,Semi-Urban,ML Engineer,91238,0 +70292,Male,28,Masters,4,8,6,41,29,1.0,2,9,Urban,Software Engineer,36713,0 +70293,Male,34,Masters,2,92,58,32,9,9.0,1,3,Urban,Manager,51419,0 +70294,Female,51,Bachelors,5,45,19,98,96,3.0,4,98,Urban,Data Analyst,109693,1 +70295,Male,32,PhD,18,89,91,16,72,8.0,2,22,Semi-Urban,Manager,84462,0 +70296,Male,45,Diploma,15,79,64,13,71,6.0,6,41,Rural,HR Executive,58792,0 +70297,Female,34,Diploma,18,20,7,90,55,0.0,5,92,Urban,ML Engineer,145949,0 +70298,Male,51,Bachelors,1,21,19,88,45,6.0,3,62,Rural,ML Engineer,119264,0 +70299,Male,24,Bachelors,5,79,93,92,94,2.0,7,66,Urban,HR Executive,138749,1 +70300,Male,32,Diploma,4,69,19,87,52,3.0,1,59,Semi-Urban,HR Executive,20564,0 +70301,Female,47,Diploma,11,60,9,27,66,0.0,1,69,Urban,Software Engineer,109668,0 +70302,Male,38,Diploma,3,17,68,67,23,9.0,0,43,Urban,Data Analyst,87958,0 +70303,Male,32,High School,17,50,90,1,56,3.0,2,71,Semi-Urban,Data Analyst,48738,0 +70304,Other,29,Bachelors,18,5,87,45,63,1.0,7,68,Rural,HR Executive,119743,0 +70305,Female,24,High School,9,14,94,44,13,5.0,0,38,Semi-Urban,ML Engineer,40239,0 +70306,Female,41,Diploma,13,71,18,68,56,5.0,5,83,Semi-Urban,Software Engineer,94520,0 +70307,Male,25,Masters,15,70,74,88,51,3.0,6,88,Rural,HR Executive,106228,1 +70308,Male,44,Bachelors,5,54,75,57,69,9.0,0,19,Urban,HR Executive,107894,0 +70309,Other,38,High School,5,41,10,13,19,4.0,0,93,Rural,Software Engineer,45224,0 +70310,Male,54,High School,13,23,51,23,96,9.0,0,44,Urban,HR Executive,25768,0 +70311,Male,24,High School,16,5,59,77,21,8.0,3,55,Semi-Urban,Software Engineer,133904,0 +70312,Other,44,Masters,13,9,29,83,20,6.0,2,33,Urban,Data Analyst,134065,0 +70313,Male,37,Diploma,4,80,97,68,55,2.0,2,5,Rural,ML Engineer,93122,1 +70314,Male,34,High School,4,87,53,51,78,6.0,3,85,Urban,Data Analyst,80139,1 +70315,Male,22,Bachelors,6,39,72,73,0,8.0,6,22,Rural,Data Analyst,35690,0 +70316,Male,39,Diploma,13,52,16,6,69,8.0,1,31,Rural,Software Engineer,96656,0 +70317,Male,38,Bachelors,14,54,92,85,18,5.0,6,46,Urban,Software Engineer,122145,1 +70318,Female,39,Masters,18,36,51,64,15,4.0,2,96,Urban,ML Engineer,103041,1 +70319,Male,33,Masters,0,57,53,12,37,4.0,4,42,Urban,Manager,102878,0 +70320,Male,35,Bachelors,13,67,66,20,63,4.0,6,31,Urban,Data Analyst,56189,0 +70321,Female,23,Diploma,10,52,68,77,86,0.0,5,49,Urban,Manager,80637,1 +70322,Female,56,Bachelors,13,73,90,36,93,2.0,7,20,Urban,ML Engineer,34211,0 +70323,Male,32,Bachelors,1,36,41,12,84,7.0,2,99,Semi-Urban,Software Engineer,94721,0 +70324,Male,36,Masters,7,3,95,15,58,5.0,3,31,Urban,Software Engineer,116165,0 +70325,Other,25,Masters,7,83,47,88,44,9.0,0,62,Urban,Manager,118510,1 +70326,Male,34,Bachelors,1,98,55,31,59,0.0,2,18,Urban,Software Engineer,95971,0 +70327,Male,55,Bachelors,16,4,48,43,98,1.0,1,85,Urban,ML Engineer,102405,0 +70328,Male,23,Bachelors,1,80,40,60,54,9.0,5,96,Semi-Urban,Manager,137242,1 +70329,Male,22,Bachelors,7,60,76,92,75,4.0,3,11,Semi-Urban,Software Engineer,106174,1 +70330,Male,35,High School,6,70,47,5,3,3.0,1,69,Urban,Data Analyst,64648,0 +70331,Male,32,Bachelors,10,54,47,93,96,8.0,2,17,Rural,HR Executive,113144,0 +70332,Male,57,Diploma,9,50,97,15,35,3.0,0,54,Urban,Data Analyst,69680,0 +70333,Female,50,Diploma,14,61,4,39,97,3.0,3,34,Rural,HR Executive,112360,0 +70334,Male,27,Masters,0,66,68,31,46,9.0,2,47,Urban,Data Analyst,89814,0 +70335,Male,21,Bachelors,19,75,41,55,45,3.0,5,45,Rural,Software Engineer,49924,0 +70336,Female,58,Diploma,4,45,44,61,33,0.0,3,4,Urban,Data Analyst,82086,0 +70337,Male,58,High School,13,9,33,68,82,7.0,7,37,Rural,Data Analyst,76371,0 +70338,Female,37,Bachelors,14,29,94,98,87,2.0,6,23,Urban,ML Engineer,61080,1 +70339,Male,48,Masters,11,6,4,95,34,6.0,0,34,Rural,ML Engineer,91718,0 +70340,Male,35,Bachelors,7,33,82,24,38,1.0,1,75,Urban,Manager,72631,0 +70341,Male,50,Bachelors,3,91,25,95,29,8.0,3,48,Rural,HR Executive,143902,1 +70342,Female,27,Diploma,12,91,86,50,31,5.0,2,97,Urban,Manager,96303,1 +70343,Male,35,Bachelors,3,78,27,81,48,1.0,1,0,Urban,Data Analyst,102562,0 +70344,Other,57,Bachelors,18,78,62,73,11,5.0,4,45,Urban,ML Engineer,61870,1 +70345,Female,31,Diploma,1,8,22,56,66,3.0,4,40,Urban,HR Executive,139012,0 +70346,Male,35,High School,4,80,50,81,64,4.0,7,38,Urban,Software Engineer,81455,1 +70347,Female,39,High School,11,71,45,32,16,6.0,3,42,Urban,HR Executive,95005,0 +70348,Male,39,Bachelors,0,34,25,79,61,0.0,2,43,Urban,Software Engineer,96787,0 +70349,Male,33,Bachelors,3,12,4,59,81,4.0,6,27,Urban,ML Engineer,113410,0 +70350,Male,28,Diploma,3,34,99,8,22,5.0,1,90,Urban,Data Analyst,23298,0 +70351,Male,24,Bachelors,4,83,71,69,85,2.0,6,56,Urban,Data Analyst,129771,1 +70352,Male,39,Masters,11,2,47,31,55,9.0,0,20,Urban,Software Engineer,100333,0 +70353,Male,59,Bachelors,19,19,99,80,72,7.0,2,66,Urban,Data Analyst,58206,1 +70354,Female,23,Bachelors,1,85,31,16,37,6.0,3,79,Urban,Data Analyst,95299,0 +70355,Male,51,Bachelors,19,76,12,19,3,0.0,7,97,Rural,ML Engineer,45215,0 +70356,Male,46,Bachelors,18,50,49,3,74,4.0,5,88,Urban,ML Engineer,47082,0 +70357,Male,50,High School,5,97,67,5,28,9.0,1,48,Urban,HR Executive,38555,0 +70358,Female,46,High School,0,86,96,53,56,1.0,5,23,Urban,Manager,28107,1 +70359,Male,45,Bachelors,11,97,1,30,23,0.0,0,37,Urban,ML Engineer,102807,0 +70360,Female,21,PhD,14,35,65,52,68,8.0,0,30,Urban,Software Engineer,65110,0 +70361,Other,21,High School,3,65,62,86,84,9.0,4,83,Urban,Manager,23258,1 +70362,Female,26,Bachelors,16,15,53,41,40,7.0,1,52,Urban,Software Engineer,61564,0 +70363,Male,51,Bachelors,13,44,45,64,73,8.0,5,68,Urban,HR Executive,50470,0 +70364,Male,44,Diploma,4,47,19,24,39,0.0,3,70,Semi-Urban,HR Executive,55227,0 +70365,Male,54,Diploma,8,93,58,51,70,1.0,7,6,Semi-Urban,Software Engineer,41690,0 +70366,Female,26,Masters,19,89,77,81,74,1.0,1,84,Urban,Manager,56382,1 +70367,Male,48,PhD,19,48,92,32,80,3.0,4,57,Urban,Software Engineer,38708,0 +70368,Male,36,Masters,14,22,8,4,37,3.0,6,14,Urban,Software Engineer,132798,0 +70369,Female,46,Diploma,15,12,68,58,35,9.0,1,18,Rural,HR Executive,132238,0 +70370,Male,45,Masters,11,89,45,70,99,0.0,0,75,Rural,HR Executive,30833,1 +70371,Male,29,High School,2,32,78,56,52,4.0,2,55,Urban,Manager,89679,0 +70372,Male,46,Bachelors,2,95,11,72,64,2.0,6,61,Urban,Data Analyst,71071,1 +70373,Male,57,Masters,9,85,5,21,40,7.0,5,69,Urban,Data Analyst,25971,0 +70374,Male,56,High School,5,0,49,65,11,7.0,0,51,Urban,HR Executive,59714,0 +70375,Male,47,Masters,2,60,83,41,64,0.0,3,57,Semi-Urban,Software Engineer,103976,1 +70376,Male,54,Bachelors,3,69,53,81,0,9.0,4,31,Urban,Software Engineer,95364,0 +70377,Female,26,High School,0,58,78,55,55,9.0,1,54,Semi-Urban,HR Executive,56367,1 +70378,Female,52,Bachelors,15,36,84,1,80,8.0,4,51,Rural,Data Analyst,133264,0 +70379,Female,22,Masters,12,16,17,90,33,7.0,2,90,Urban,Data Analyst,97447,0 +70380,Male,51,Masters,6,25,87,86,99,1.0,1,7,Urban,Manager,146371,0 +70381,Male,25,Bachelors,16,26,89,83,77,6.0,3,88,Semi-Urban,HR Executive,80143,1 +70382,Male,54,Bachelors,15,73,66,73,80,7.0,3,3,Urban,Manager,30582,0 +70383,Female,53,Masters,13,61,19,34,47,4.0,6,66,Semi-Urban,Software Engineer,99844,0 +70384,Male,42,Bachelors,7,25,87,99,82,1.0,0,95,Urban,Data Analyst,89119,1 +70385,Male,43,Diploma,10,0,60,39,17,6.0,3,74,Urban,Data Analyst,28106,0 +70386,Male,56,Bachelors,14,80,97,9,49,5.0,3,50,Rural,Manager,99074,1 +70387,Female,43,High School,15,57,83,72,10,2.0,6,93,Semi-Urban,Data Analyst,126174,1 +70388,Male,55,High School,13,3,38,78,12,6.0,4,65,Urban,Software Engineer,76303,0 +70389,Female,55,Bachelors,4,83,84,11,23,2.0,2,33,Urban,Software Engineer,138110,0 +70390,Male,26,Masters,6,18,34,84,42,6.0,0,21,Urban,Data Analyst,109841,0 +70391,Male,52,High School,0,92,40,82,3,9.0,6,32,Urban,HR Executive,140593,1 +70392,Female,39,Diploma,8,8,3,37,13,4.0,2,12,Urban,Software Engineer,37300,0 +70393,Female,47,Bachelors,17,58,69,43,22,8.0,3,91,Urban,Manager,142771,1 +70394,Female,34,Bachelors,3,71,20,25,75,8.0,4,56,Urban,ML Engineer,133332,0 +70395,Male,22,Bachelors,18,32,78,96,42,0.0,3,29,Urban,Manager,102510,1 +70396,Male,45,Diploma,3,13,5,32,8,8.0,3,32,Urban,Manager,95166,0 +70397,Male,48,PhD,15,99,10,60,20,7.0,6,45,Rural,Data Analyst,69919,0 +70398,Female,25,High School,14,31,11,11,66,8.0,5,11,Rural,Manager,89761,0 +70399,Female,54,Bachelors,15,31,90,75,52,7.0,5,71,Urban,Data Analyst,107969,1 +70400,Female,42,Masters,2,89,98,92,81,0.0,2,92,Urban,HR Executive,22073,1 +70401,Male,30,High School,14,74,14,57,24,6.0,7,25,Urban,Data Analyst,65866,0 +70402,Female,26,Diploma,18,36,82,29,17,2.0,4,31,Urban,HR Executive,98502,0 +70403,Male,23,Masters,11,71,16,93,99,4.0,7,4,Rural,Manager,126852,0 +70404,Male,22,Bachelors,9,3,22,71,85,9.0,6,72,Rural,HR Executive,94822,0 +70405,Male,50,Bachelors,14,46,76,83,41,5.0,5,88,Rural,Data Analyst,62313,1 +70406,Female,29,Diploma,2,21,48,56,90,9.0,3,0,Urban,Data Analyst,130080,0 +70407,Female,27,Diploma,12,93,72,13,62,7.0,4,61,Urban,ML Engineer,128811,0 +70408,Male,47,Masters,6,55,94,49,41,5.0,7,20,Urban,Data Analyst,125495,0 +70409,Female,54,Bachelors,12,6,90,33,90,4.0,4,96,Rural,ML Engineer,131024,0 +70410,Male,26,Masters,12,52,89,21,87,9.0,3,3,Urban,HR Executive,139113,0 +70411,Male,51,Bachelors,8,27,78,37,57,4.0,1,32,Urban,Data Analyst,125289,0 +70412,Female,49,Bachelors,4,25,9,50,97,7.0,3,52,Rural,HR Executive,75018,0 +70413,Male,47,Bachelors,10,76,69,46,57,0.0,7,21,Urban,Software Engineer,119547,0 +70414,Male,43,Bachelors,19,51,95,2,87,9.0,3,21,Semi-Urban,Data Analyst,78261,0 +70415,Female,29,Bachelors,8,80,54,13,76,8.0,7,66,Semi-Urban,Manager,24058,0 +70416,Male,51,Diploma,13,46,65,90,15,6.0,0,0,Rural,Software Engineer,44531,0 +70417,Female,22,Diploma,10,60,59,33,41,8.0,2,89,Rural,Data Analyst,23010,1 +70418,Female,44,Bachelors,12,51,26,15,61,4.0,4,62,Rural,HR Executive,131386,0 +70419,Female,46,Bachelors,8,68,37,14,21,7.0,3,35,Urban,ML Engineer,79714,0 +70420,Male,59,Bachelors,8,1,92,86,20,9.0,1,4,Urban,ML Engineer,56594,0 +70421,Other,46,Bachelors,18,59,82,16,84,8.0,0,95,Rural,Software Engineer,102779,1 +70422,Female,51,Masters,18,29,71,83,45,6.0,6,54,Urban,Data Analyst,98023,0 +70423,Male,59,Diploma,12,61,36,85,52,8.0,1,93,Semi-Urban,Data Analyst,93702,1 +70424,Female,48,Bachelors,10,5,72,12,30,0.0,3,87,Semi-Urban,Data Analyst,65912,0 +70425,Female,27,Diploma,16,55,42,15,94,0.0,0,58,Urban,Software Engineer,144276,0 +70426,Female,31,Diploma,12,84,67,61,26,0.0,5,61,Semi-Urban,Manager,96562,1 +70427,Male,25,Bachelors,3,38,93,91,79,2.0,3,64,Urban,ML Engineer,102055,1 +70428,Male,36,Bachelors,1,23,77,1,71,4.0,6,31,Urban,Manager,82099,0 +70429,Female,42,Bachelors,8,39,51,33,49,1.0,7,19,Rural,HR Executive,47904,0 +70430,Male,54,Bachelors,4,55,8,64,88,1.0,3,48,Urban,HR Executive,28465,0 +70431,Male,22,PhD,9,54,96,84,76,4.0,1,43,Rural,ML Engineer,48716,1 +70432,Male,24,Diploma,4,85,22,78,16,4.0,0,10,Urban,Software Engineer,148321,0 +70433,Female,51,High School,3,39,32,79,71,0.0,7,89,Semi-Urban,Software Engineer,146440,0 +70434,Male,42,Bachelors,14,71,98,72,92,9.0,1,38,Semi-Urban,Software Engineer,72297,1 +70435,Female,44,Diploma,12,30,88,72,17,4.0,1,89,Urban,Data Analyst,130243,1 +70436,Female,58,Bachelors,16,16,72,88,33,0.0,4,10,Rural,Manager,38102,0 +70437,Male,22,Bachelors,13,94,88,58,49,9.0,3,86,Rural,Data Analyst,97427,1 +70438,Male,32,Bachelors,6,6,81,46,14,3.0,6,72,Urban,Software Engineer,126342,0 +70439,Male,56,Diploma,8,31,92,49,17,5.0,4,95,Urban,Software Engineer,139126,1 +70440,Other,31,High School,2,79,67,79,11,0.0,0,21,Urban,Data Analyst,40554,1 +70441,Male,49,High School,12,26,18,34,32,5.0,5,82,Urban,ML Engineer,80625,0 +70442,Male,22,Diploma,3,64,86,57,58,5.0,5,95,Urban,ML Engineer,88431,1 +70443,Female,21,Bachelors,14,48,7,43,95,9.0,6,56,Semi-Urban,Manager,99635,0 +70444,Male,55,Bachelors,17,61,19,27,95,8.0,3,83,Rural,Data Analyst,79986,0 +70445,Female,48,Masters,10,64,33,30,43,0.0,2,99,Urban,Software Engineer,34940,0 +70446,Male,44,Bachelors,2,70,94,41,99,4.0,1,66,Semi-Urban,ML Engineer,60208,1 +70447,Male,44,Bachelors,13,62,62,74,83,1.0,5,53,Urban,Data Analyst,49394,1 +70448,Male,30,Bachelors,6,60,30,24,74,3.0,3,37,Semi-Urban,ML Engineer,105771,0 +70449,Male,51,High School,0,22,97,76,63,8.0,3,1,Semi-Urban,Data Analyst,112907,0 +70450,Male,22,Masters,4,43,27,95,55,0.0,7,10,Rural,Software Engineer,83370,0 +70451,Male,50,Bachelors,17,22,53,44,90,7.0,7,39,Rural,Data Analyst,22962,0 +70452,Female,36,Bachelors,6,56,99,83,23,5.0,3,56,Urban,Data Analyst,58823,1 +70453,Male,47,High School,3,46,7,16,32,2.0,1,31,Urban,Manager,75867,0 +70454,Female,31,Bachelors,15,96,41,28,42,0.0,0,37,Urban,Data Analyst,113221,0 +70455,Male,24,Diploma,1,41,19,15,48,1.0,7,50,Semi-Urban,ML Engineer,149236,0 +70456,Male,42,Masters,16,99,13,95,64,7.0,5,16,Urban,Manager,53605,0 +70457,Female,23,Bachelors,12,99,81,98,27,0.0,4,52,Rural,Data Analyst,99345,1 +70458,Female,38,Diploma,0,97,70,99,10,4.0,2,77,Urban,Software Engineer,41256,1 +70459,Male,52,Bachelors,9,1,96,30,80,6.0,2,32,Urban,ML Engineer,50348,0 +70460,Female,30,Diploma,1,63,25,77,84,3.0,7,22,Urban,Software Engineer,144706,0 +70461,Male,43,Bachelors,3,41,38,75,59,9.0,0,33,Semi-Urban,ML Engineer,81387,0 +70462,Male,44,Diploma,8,90,44,41,35,2.0,5,76,Urban,ML Engineer,127601,1 +70463,Female,47,Bachelors,4,24,77,43,24,3.0,4,49,Urban,Data Analyst,108214,0 +70464,Male,29,Masters,10,13,78,22,70,1.0,5,19,Urban,Manager,51777,0 +70465,Male,38,Masters,0,64,11,93,15,2.0,1,28,Rural,Software Engineer,107377,0 +70466,Male,57,High School,5,32,19,55,42,4.0,6,68,Semi-Urban,Manager,131097,0 +70467,Male,52,Masters,1,42,53,29,2,1.0,4,33,Urban,HR Executive,99174,0 +70468,Female,43,Diploma,8,22,50,42,4,3.0,1,55,Rural,ML Engineer,142005,0 +70469,Male,46,PhD,8,9,26,61,39,9.0,6,33,Semi-Urban,ML Engineer,36475,0 +70470,Female,22,Diploma,6,53,23,18,63,7.0,3,35,Urban,ML Engineer,23061,0 +70471,Male,46,Bachelors,18,82,3,51,13,8.0,7,79,Urban,Software Engineer,20119,0 +70472,Male,39,Diploma,12,4,47,43,86,4.0,7,14,Urban,Data Analyst,67058,0 +70473,Female,50,Diploma,2,19,16,61,25,8.0,4,46,Urban,Manager,43979,0 +70474,Male,39,Diploma,11,88,28,52,44,5.0,6,65,Urban,Manager,30747,0 +70475,Female,22,Bachelors,19,52,35,45,45,5.0,2,31,Urban,Software Engineer,42811,0 +70476,Female,54,Bachelors,17,48,98,18,80,6.0,0,39,Urban,ML Engineer,147894,0 +70477,Male,55,Diploma,16,78,53,32,62,1.0,7,5,Urban,ML Engineer,66211,0 +70478,Male,50,High School,3,96,30,55,60,6.0,0,51,Semi-Urban,Manager,51036,0 +70479,Male,21,Bachelors,2,84,10,90,43,2.0,4,96,Urban,ML Engineer,58011,1 +70480,Female,23,Masters,13,75,17,52,39,3.0,3,6,Urban,Data Analyst,47896,0 +70481,Male,47,Bachelors,14,68,49,25,35,2.0,1,24,Rural,Data Analyst,83823,0 +70482,Male,24,Diploma,12,96,82,78,62,9.0,1,95,Urban,Manager,61593,1 +70483,Male,50,Bachelors,7,64,82,97,32,6.0,0,37,Rural,Manager,24707,1 +70484,Male,55,Diploma,1,64,64,55,58,1.0,6,88,Rural,Manager,127398,1 +70485,Male,56,Masters,8,92,22,10,56,0.0,0,93,Urban,Data Analyst,70620,0 +70486,Female,27,Masters,9,48,86,64,8,9.0,5,58,Urban,HR Executive,149958,1 +70487,Female,56,Diploma,0,91,47,77,32,8.0,6,33,Rural,HR Executive,113070,1 +70488,Female,22,Bachelors,18,57,13,75,0,2.0,6,46,Urban,Manager,37931,0 +70489,Female,37,Bachelors,9,31,43,15,25,2.0,3,73,Urban,Software Engineer,54668,0 +70490,Male,31,Masters,6,5,84,51,60,6.0,5,44,Urban,Software Engineer,74419,0 +70491,Other,41,Masters,5,20,19,49,92,3.0,3,58,Urban,HR Executive,134281,0 +70492,Male,55,Masters,7,38,31,43,98,5.0,0,68,Urban,Data Analyst,127724,0 +70493,Male,22,Diploma,13,63,18,19,86,2.0,4,79,Urban,Software Engineer,52653,0 +70494,Male,35,High School,3,47,88,80,84,8.0,3,11,Semi-Urban,Manager,146671,0 +70495,Male,41,High School,5,69,26,82,12,1.0,1,51,Rural,Software Engineer,73646,0 +70496,Male,40,Diploma,3,77,70,74,66,5.0,5,14,Urban,Manager,39098,1 +70497,Female,54,Masters,19,96,64,81,15,8.0,4,95,Urban,HR Executive,30207,1 +70498,Male,35,High School,18,45,66,61,59,6.0,7,18,Urban,Data Analyst,50823,0 +70499,Male,38,Bachelors,6,48,24,82,97,1.0,5,53,Urban,ML Engineer,65812,0 +70500,Female,34,Bachelors,11,25,17,73,48,2.0,1,86,Semi-Urban,Software Engineer,66731,0 +70501,Female,55,Bachelors,5,55,57,57,97,6.0,0,26,Rural,Software Engineer,51606,0 +70502,Female,24,PhD,5,60,67,99,6,3.0,3,61,Urban,HR Executive,23456,1 +70503,Male,52,Diploma,3,86,77,24,87,7.0,0,1,Rural,ML Engineer,46541,0 +70504,Other,53,Bachelors,7,78,85,30,51,9.0,6,28,Semi-Urban,HR Executive,54473,0 +70505,Male,48,High School,16,63,94,70,79,1.0,2,9,Urban,ML Engineer,137304,1 +70506,Male,34,Bachelors,17,99,62,8,6,5.0,5,24,Urban,Manager,95003,0 +70507,Male,34,Diploma,3,20,3,99,28,5.0,7,81,Urban,Manager,25024,0 +70508,Male,57,Masters,12,74,19,16,26,5.0,0,69,Rural,HR Executive,55984,0 +70509,Male,43,Masters,18,92,45,8,19,7.0,0,5,Urban,Software Engineer,75359,0 +70510,Male,40,Bachelors,15,89,35,34,14,4.0,0,56,Semi-Urban,HR Executive,93163,0 +70511,Male,26,Diploma,11,15,57,8,20,9.0,1,19,Rural,ML Engineer,110614,0 +70512,Male,53,Masters,7,54,65,55,48,7.0,3,32,Semi-Urban,ML Engineer,131172,0 +70513,Male,25,Diploma,11,15,85,10,56,7.0,2,58,Urban,ML Engineer,127285,0 +70514,Male,54,Bachelors,11,72,69,47,45,8.0,5,7,Rural,Manager,113529,0 +70515,Male,44,Bachelors,8,28,77,76,26,8.0,0,92,Rural,Manager,92508,1 +70516,Female,36,Masters,3,44,66,52,77,9.0,3,86,Urban,HR Executive,51998,1 +70517,Male,58,Masters,10,18,61,71,32,8.0,5,82,Semi-Urban,Manager,101116,0 +70518,Male,47,Bachelors,8,8,18,14,56,1.0,1,19,Rural,Manager,42679,0 +70519,Male,31,Masters,14,56,0,14,78,7.0,1,80,Urban,HR Executive,142413,0 +70520,Male,50,Diploma,8,80,96,69,33,7.0,5,62,Urban,Data Analyst,71768,1 +70521,Male,59,Bachelors,12,75,38,41,15,8.0,3,75,Urban,Data Analyst,77796,0 +70522,Male,32,Masters,8,31,83,15,18,3.0,5,82,Urban,ML Engineer,124573,0 +70523,Male,28,Bachelors,13,27,14,10,83,5.0,7,32,Rural,Data Analyst,100238,0 +70524,Male,52,High School,17,66,97,64,17,0.0,7,23,Rural,Data Analyst,72123,1 +70525,Male,58,Bachelors,9,73,59,95,96,3.0,7,58,Rural,Software Engineer,135354,1 +70526,Female,31,Diploma,6,77,20,28,93,3.0,3,98,Urban,Manager,108200,0 +70527,Male,46,PhD,1,89,80,98,86,5.0,3,42,Urban,Software Engineer,133802,1 +70528,Female,56,High School,11,67,47,29,92,2.0,5,91,Rural,Manager,129729,0 +70529,Female,39,Bachelors,16,33,83,25,1,3.0,2,50,Semi-Urban,Software Engineer,142901,0 +70530,Male,31,Bachelors,10,12,84,80,7,0.0,0,50,Urban,Data Analyst,58730,0 +70531,Male,55,Masters,4,27,80,11,27,3.0,0,36,Urban,ML Engineer,59632,0 +70532,Male,22,Bachelors,13,95,60,76,88,5.0,7,15,Urban,HR Executive,116156,1 +70533,Male,54,Masters,15,37,57,79,45,3.0,4,32,Urban,ML Engineer,90437,0 +70534,Male,50,Diploma,11,18,18,35,29,9.0,5,91,Urban,Manager,124930,0 +70535,Female,52,Diploma,6,12,13,57,56,1.0,7,62,Rural,HR Executive,116110,0 +70536,Female,25,Bachelors,1,69,19,85,69,3.0,6,16,Urban,Data Analyst,37765,0 +70537,Male,37,High School,1,97,40,39,2,2.0,3,8,Rural,Data Analyst,100626,0 +70538,Female,46,Diploma,13,73,26,54,89,4.0,0,7,Urban,ML Engineer,84477,0 +70539,Male,27,Diploma,5,68,93,61,10,0.0,5,91,Rural,HR Executive,53782,1 +70540,Male,21,Bachelors,4,78,26,7,64,6.0,5,24,Urban,ML Engineer,42873,0 +70541,Female,25,Diploma,12,20,97,39,22,1.0,7,21,Rural,Software Engineer,79796,0 +70542,Other,50,Masters,3,44,81,0,93,3.0,6,80,Semi-Urban,Manager,21966,0 +70543,Female,33,Masters,12,28,47,53,1,6.0,6,55,Urban,Manager,53417,0 +70544,Female,42,Masters,0,89,56,60,80,3.0,7,46,Rural,Software Engineer,54935,1 +70545,Male,27,Bachelors,16,7,46,78,30,1.0,3,62,Urban,Data Analyst,144731,0 +70546,Male,52,Bachelors,9,28,69,84,30,2.0,2,74,Rural,HR Executive,61418,1 +70547,Male,44,Bachelors,0,62,69,63,60,1.0,2,26,Urban,HR Executive,118771,0 +70548,Female,37,Bachelors,18,20,4,22,74,7.0,5,43,Urban,Software Engineer,24880,0 +70549,Male,41,Diploma,16,42,87,88,80,1.0,6,33,Urban,ML Engineer,86401,1 +70550,Male,36,Diploma,7,28,11,73,23,4.0,0,87,Semi-Urban,ML Engineer,48653,0 +70551,Male,58,Masters,7,23,19,11,94,4.0,5,15,Urban,Data Analyst,112383,0 +70552,Female,41,PhD,4,45,56,56,26,3.0,4,86,Urban,Software Engineer,35444,1 +70553,Female,26,PhD,0,70,41,22,49,2.0,0,45,Urban,HR Executive,91880,0 +70554,Male,57,Bachelors,8,61,66,93,84,8.0,1,72,Urban,Manager,123229,1 +70555,Male,25,Masters,3,94,33,89,6,0.0,0,25,Semi-Urban,Data Analyst,116126,1 +70556,Male,31,Masters,7,38,53,22,15,9.0,7,7,Urban,Software Engineer,129865,0 +70557,Male,29,Masters,3,66,90,99,66,7.0,2,30,Semi-Urban,Software Engineer,108662,1 +70558,Male,47,Masters,10,71,52,69,6,3.0,6,13,Urban,Software Engineer,102606,0 +70559,Female,21,Masters,7,69,3,26,82,2.0,6,7,Urban,Software Engineer,149210,0 +70560,Female,56,Bachelors,9,1,60,77,15,6.0,0,33,Semi-Urban,Manager,41964,0 +70561,Male,29,Bachelors,13,58,7,70,5,5.0,6,47,Urban,ML Engineer,101619,0 +70562,Male,31,High School,2,25,93,80,58,6.0,4,24,Urban,Manager,54576,0 +70563,Male,45,High School,8,14,4,59,78,5.0,7,82,Rural,Data Analyst,119335,0 +70564,Male,55,High School,9,32,26,64,20,8.0,0,12,Urban,Manager,72150,0 +70565,Male,26,Masters,9,63,34,71,20,8.0,2,42,Rural,ML Engineer,109118,0 +70566,Male,25,Bachelors,13,95,85,35,16,5.0,1,37,Urban,Software Engineer,68666,1 +70567,Male,42,Masters,19,41,14,22,81,9.0,4,80,Urban,Data Analyst,54670,0 +70568,Male,32,Bachelors,1,49,35,71,50,4.0,6,75,Urban,HR Executive,42534,0 +70569,Female,29,Bachelors,1,52,88,14,15,3.0,7,12,Rural,HR Executive,114925,0 +70570,Male,31,High School,17,55,78,41,73,4.0,6,29,Semi-Urban,Software Engineer,55653,0 +70571,Female,46,PhD,13,5,65,7,73,4.0,4,9,Urban,Data Analyst,43633,0 +70572,Male,25,Bachelors,17,70,46,44,56,4.0,6,99,Urban,ML Engineer,32406,1 +70573,Male,24,Diploma,3,25,11,37,50,8.0,5,21,Urban,Software Engineer,30581,0 +70574,Female,28,Bachelors,1,85,19,87,24,1.0,4,35,Urban,HR Executive,136536,0 +70575,Male,41,Masters,2,50,65,32,65,6.0,6,32,Rural,Data Analyst,143485,0 +70576,Female,22,Diploma,7,30,64,67,35,1.0,1,27,Rural,Software Engineer,128348,0 +70577,Female,45,Bachelors,19,89,57,33,12,4.0,5,55,Semi-Urban,Data Analyst,59175,0 +70578,Male,41,Diploma,7,90,71,29,90,3.0,4,9,Rural,Software Engineer,87535,0 +70579,Male,57,Masters,18,97,90,40,72,8.0,1,55,Urban,Data Analyst,92712,1 +70580,Male,57,Bachelors,10,65,94,65,16,8.0,5,78,Rural,Manager,107617,1 +70581,Male,48,Bachelors,6,28,83,18,99,1.0,0,71,Urban,HR Executive,82400,0 +70582,Male,55,Bachelors,19,30,13,94,40,3.0,4,28,Urban,Manager,34276,0 +70583,Female,23,Diploma,19,80,79,97,88,0.0,3,88,Urban,Data Analyst,80830,1 +70584,Male,31,Diploma,7,11,78,93,56,3.0,6,70,Urban,Data Analyst,110547,1 +70585,Male,55,Bachelors,4,59,2,62,73,3.0,6,12,Rural,Data Analyst,74150,0 +70586,Male,39,High School,14,44,44,1,82,3.0,0,29,Semi-Urban,HR Executive,41966,0 +70587,Male,52,Bachelors,6,50,5,76,91,0.0,2,72,Rural,Data Analyst,119509,0 +70588,Male,26,Bachelors,12,25,86,54,53,6.0,3,14,Rural,Data Analyst,133859,0 +70589,Female,28,Bachelors,9,51,11,72,33,7.0,1,85,Semi-Urban,ML Engineer,72690,0 +70590,Other,33,Masters,11,93,92,82,76,2.0,2,68,Rural,Software Engineer,56961,1 +70591,Male,54,Bachelors,3,37,65,37,30,2.0,2,1,Urban,Manager,28770,0 +70592,Female,50,Bachelors,18,13,66,84,85,1.0,2,72,Rural,HR Executive,84132,0 +70593,Female,45,Masters,8,65,73,60,2,2.0,4,58,Urban,Software Engineer,34949,1 +70594,Male,59,PhD,10,28,14,63,72,1.0,5,95,Urban,ML Engineer,26803,0 +70595,Male,32,Bachelors,0,25,47,91,27,8.0,1,35,Urban,HR Executive,124166,0 +70596,Other,39,Diploma,1,18,45,1,0,4.0,5,91,Semi-Urban,Software Engineer,118564,0 +70597,Female,36,Bachelors,16,68,42,21,35,4.0,6,33,Semi-Urban,Manager,104090,0 +70598,Male,57,Diploma,0,36,0,9,5,1.0,4,28,Urban,Data Analyst,52374,0 +70599,Female,42,Bachelors,11,48,2,42,73,9.0,6,8,Urban,Software Engineer,91868,0 +70600,Female,50,Bachelors,9,30,85,82,91,2.0,2,51,Rural,Manager,41174,1 +70601,Female,59,Bachelors,0,92,40,66,41,7.0,4,59,Semi-Urban,ML Engineer,46875,1 +70602,Female,30,Masters,13,64,59,71,79,5.0,0,85,Urban,Data Analyst,114482,1 +70603,Female,37,Bachelors,12,47,31,71,20,3.0,4,96,Semi-Urban,HR Executive,60979,1 +70604,Male,24,Diploma,0,6,40,87,10,6.0,0,91,Urban,HR Executive,136939,0 +70605,Female,40,Masters,15,55,75,4,57,0.0,1,10,Urban,Manager,37922,0 +70606,Male,26,Bachelors,0,27,76,63,42,4.0,1,64,Urban,Software Engineer,93096,0 +70607,Female,38,Bachelors,1,68,1,31,6,4.0,1,82,Semi-Urban,Data Analyst,144879,0 +70608,Female,41,Bachelors,7,22,21,78,12,5.0,7,59,Rural,HR Executive,135180,0 +70609,Female,41,Diploma,4,79,28,25,88,8.0,2,48,Urban,ML Engineer,73428,0 +70610,Other,25,Bachelors,18,73,65,2,0,8.0,5,75,Urban,ML Engineer,103684,0 +70611,Male,46,Bachelors,4,4,36,1,95,2.0,2,18,Urban,Software Engineer,145271,0 +70612,Male,29,Masters,19,2,87,29,25,2.0,5,61,Urban,Data Analyst,137358,0 +70613,Female,58,Bachelors,5,20,20,74,88,7.0,3,33,Urban,Manager,108111,0 +70614,Female,34,Bachelors,15,28,45,97,82,9.0,7,17,Urban,Manager,78102,0 +70615,Female,38,Bachelors,19,99,0,23,18,2.0,1,84,Semi-Urban,ML Engineer,109321,0 +70616,Male,54,Diploma,18,49,95,78,1,9.0,6,65,Urban,Data Analyst,141560,1 +70617,Male,38,Masters,3,23,90,41,23,4.0,3,86,Semi-Urban,Data Analyst,111111,1 +70618,Male,35,High School,14,86,95,27,62,6.0,4,72,Urban,ML Engineer,60307,1 +70619,Male,35,Bachelors,12,97,75,59,74,3.0,0,81,Semi-Urban,HR Executive,49053,1 +70620,Female,30,Bachelors,17,66,12,42,38,0.0,5,47,Urban,HR Executive,49326,0 +70621,Female,57,PhD,10,58,39,59,67,1.0,1,1,Semi-Urban,Manager,58508,0 +70622,Female,33,Diploma,13,25,23,14,77,8.0,1,33,Semi-Urban,ML Engineer,93716,0 +70623,Male,55,High School,15,40,29,48,75,2.0,5,29,Urban,Software Engineer,72482,0 +70624,Female,57,Diploma,9,13,31,22,9,6.0,5,75,Urban,HR Executive,46822,0 +70625,Female,55,Diploma,17,87,41,68,84,4.0,3,42,Urban,Data Analyst,87105,0 +70626,Male,52,Diploma,8,11,69,52,59,5.0,2,49,Urban,Data Analyst,32210,0 +70627,Male,58,Diploma,4,11,76,66,84,7.0,4,34,Urban,ML Engineer,139472,0 +70628,Female,56,Diploma,9,45,64,25,26,2.0,0,29,Semi-Urban,Manager,41310,0 +70629,Male,29,Diploma,8,8,38,79,90,3.0,4,82,Urban,HR Executive,104227,0 +70630,Male,33,Bachelors,4,36,39,45,50,3.0,0,89,Semi-Urban,HR Executive,98344,0 +70631,Male,53,High School,14,72,9,59,7,5.0,7,43,Urban,ML Engineer,131124,0 +70632,Female,58,Masters,9,58,64,63,34,3.0,1,66,Urban,Manager,135134,1 +70633,Female,29,Diploma,16,10,93,0,38,5.0,7,94,Semi-Urban,Data Analyst,136972,0 +70634,Female,33,Diploma,16,20,1,47,91,6.0,7,5,Semi-Urban,Manager,43679,0 +70635,Female,26,Bachelors,1,15,69,32,16,0.0,5,25,Rural,Data Analyst,135939,0 +70636,Other,29,Bachelors,0,49,94,0,96,0.0,5,59,Semi-Urban,Data Analyst,45650,0 +70637,Female,25,Bachelors,5,47,68,48,82,1.0,3,44,Urban,Data Analyst,106870,0 +70638,Male,35,Bachelors,19,9,97,2,68,0.0,1,34,Rural,Data Analyst,55443,0 +70639,Other,53,Diploma,4,69,60,12,74,2.0,1,63,Rural,ML Engineer,115900,0 +70640,Male,45,High School,8,82,10,71,99,8.0,0,59,Semi-Urban,Manager,120552,0 +70641,Female,42,Diploma,7,8,32,75,44,7.0,6,76,Rural,Software Engineer,125869,0 +70642,Female,45,High School,5,50,50,90,42,5.0,1,78,Urban,ML Engineer,98465,1 +70643,Male,54,Masters,11,10,32,48,48,0.0,2,66,Urban,Manager,86407,0 +70644,Female,48,Masters,13,80,38,65,60,6.0,0,0,Urban,HR Executive,144259,0 +70645,Other,31,Masters,19,26,33,84,94,4.0,1,22,Urban,Manager,74305,0 +70646,Female,57,Bachelors,16,25,58,18,5,6.0,5,86,Rural,Software Engineer,61230,0 +70647,Female,53,High School,12,36,71,45,51,5.0,2,17,Rural,HR Executive,33982,0 +70648,Male,31,High School,5,45,98,84,84,7.0,0,12,Urban,Software Engineer,38820,1 +70649,Male,53,High School,1,10,46,20,25,9.0,4,71,Urban,HR Executive,67808,0 +70650,Female,22,High School,0,65,0,66,49,1.0,4,62,Urban,Software Engineer,135041,0 +70651,Male,51,Bachelors,8,74,25,24,82,3.0,4,3,Rural,HR Executive,57963,0 +70652,Female,51,High School,7,93,67,35,77,6.0,7,48,Urban,Data Analyst,31980,1 +70653,Male,57,High School,3,12,34,23,41,9.0,5,19,Urban,Data Analyst,66291,0 +70654,Male,40,PhD,7,8,59,55,91,5.0,5,23,Urban,Software Engineer,27617,0 +70655,Male,56,Diploma,19,45,93,43,67,6.0,2,26,Semi-Urban,Data Analyst,113387,0 +70656,Male,47,Bachelors,0,64,20,62,52,1.0,2,3,Urban,HR Executive,129303,0 +70657,Male,39,Bachelors,8,3,47,46,8,0.0,4,82,Urban,HR Executive,120699,0 +70658,Female,40,Bachelors,1,40,84,29,31,9.0,1,74,Rural,Manager,95734,0 +70659,Male,35,High School,15,90,88,34,25,3.0,3,67,Urban,ML Engineer,123722,1 +70660,Male,49,High School,2,95,68,99,54,4.0,3,32,Urban,Data Analyst,83081,1 +70661,Male,42,Diploma,10,69,65,78,36,8.0,5,85,Urban,ML Engineer,143864,1 +70662,Female,35,Diploma,13,78,80,81,32,5.0,6,17,Urban,Manager,32154,1 +70663,Male,32,Bachelors,16,51,20,89,72,7.0,6,5,Urban,Manager,96221,0 +70664,Female,46,High School,19,0,96,55,29,4.0,4,56,Urban,Software Engineer,144589,0 +70665,Male,52,PhD,8,60,66,49,43,0.0,5,40,Urban,Software Engineer,115416,0 +70666,Female,24,Masters,13,0,17,6,59,4.0,5,45,Urban,Software Engineer,61538,0 +70667,Male,27,High School,15,95,11,75,9,2.0,5,99,Urban,HR Executive,149791,1 +70668,Male,42,High School,8,23,17,94,45,9.0,1,37,Rural,Software Engineer,91858,0 +70669,Male,56,Bachelors,17,58,34,12,11,8.0,2,32,Urban,Data Analyst,99454,0 +70670,Female,41,High School,12,88,61,73,64,7.0,6,60,Semi-Urban,Software Engineer,113193,1 +70671,Female,47,High School,1,56,79,98,7,5.0,7,24,Urban,Manager,117329,1 +70672,Female,32,PhD,8,79,16,40,2,0.0,4,17,Urban,Software Engineer,121971,0 +70673,Female,22,PhD,9,43,42,11,91,3.0,7,65,Rural,Manager,71793,0 +70674,Male,26,Diploma,3,6,11,52,95,9.0,4,29,Semi-Urban,Manager,135569,0 +70675,Male,41,High School,18,65,18,71,17,8.0,4,20,Urban,Software Engineer,100218,0 +70676,Female,58,Masters,19,86,1,27,32,4.0,1,49,Rural,Manager,77159,0 +70677,Female,57,High School,19,86,79,90,83,7.0,6,79,Semi-Urban,Software Engineer,24594,1 +70678,Male,25,Bachelors,12,97,78,56,72,3.0,5,39,Urban,ML Engineer,39956,1 +70679,Female,46,Bachelors,19,78,5,54,68,7.0,5,13,Urban,ML Engineer,91393,0 +70680,Male,34,Bachelors,2,63,75,20,60,1.0,7,71,Urban,Software Engineer,90879,0 +70681,Female,58,Masters,19,28,8,74,40,8.0,2,6,Rural,HR Executive,124236,0 +70682,Female,35,High School,12,63,55,18,93,0.0,1,57,Urban,Software Engineer,142351,0 +70683,Male,55,Bachelors,7,40,33,61,4,0.0,3,21,Semi-Urban,Data Analyst,71697,0 +70684,Male,37,Diploma,9,20,33,24,92,6.0,3,84,Urban,ML Engineer,86553,0 +70685,Female,47,Bachelors,13,8,62,50,7,0.0,0,46,Semi-Urban,Software Engineer,22677,0 +70686,Male,24,Masters,13,20,87,15,21,4.0,2,47,Semi-Urban,Data Analyst,64141,0 +70687,Male,23,Bachelors,4,60,49,38,27,2.0,7,87,Urban,Software Engineer,61651,0 +70688,Male,32,Diploma,4,52,67,62,41,2.0,6,32,Rural,Software Engineer,106602,0 +70689,Male,42,Bachelors,13,50,87,18,79,9.0,4,72,Urban,Manager,103290,0 +70690,Male,34,Bachelors,8,46,83,40,7,9.0,6,61,Urban,Software Engineer,79164,0 +70691,Female,35,Masters,0,47,87,22,97,6.0,7,46,Rural,Software Engineer,139487,0 +70692,Female,45,Masters,4,0,38,51,69,3.0,1,2,Urban,Software Engineer,141925,0 +70693,Female,47,Diploma,3,89,45,68,66,7.0,3,52,Urban,Manager,96765,1 +70694,Male,52,High School,17,93,79,21,14,3.0,0,30,Semi-Urban,HR Executive,41500,0 +70695,Female,29,Masters,5,13,31,9,98,1.0,6,94,Rural,Manager,106898,0 +70696,Female,22,High School,5,46,56,79,33,8.0,0,33,Rural,ML Engineer,146423,0 +70697,Female,28,Masters,18,89,27,51,12,6.0,2,20,Semi-Urban,ML Engineer,59962,0 +70698,Male,56,Bachelors,0,39,15,25,68,7.0,2,16,Rural,HR Executive,55274,0 +70699,Male,50,Masters,8,91,84,48,54,1.0,7,94,Rural,Data Analyst,115406,1 +70700,Male,38,Bachelors,10,79,52,58,73,4.0,5,32,Urban,Data Analyst,87903,0 +70701,Other,39,Bachelors,1,7,1,83,79,4.0,6,56,Rural,Manager,149889,0 +70702,Male,41,Bachelors,2,59,92,79,8,2.0,2,41,Urban,Data Analyst,26498,1 +70703,Female,33,Masters,0,77,90,21,54,0.0,2,39,Rural,HR Executive,111203,0 +70704,Female,30,Masters,6,91,58,45,13,0.0,2,17,Rural,Software Engineer,42750,0 +70705,Female,32,Diploma,17,0,59,65,57,9.0,1,4,Urban,Manager,98355,0 +70706,Male,31,Diploma,18,95,80,26,55,0.0,5,58,Urban,Data Analyst,139410,1 +70707,Male,25,Masters,17,31,94,84,25,5.0,0,86,Semi-Urban,Data Analyst,120576,1 +70708,Female,35,Masters,4,37,81,77,19,3.0,6,31,Rural,Manager,128274,0 +70709,Female,56,PhD,4,53,48,15,4,5.0,0,3,Semi-Urban,Software Engineer,34457,0 +70710,Male,36,Masters,16,22,9,15,79,1.0,7,78,Urban,Data Analyst,42743,0 +70711,Male,24,Bachelors,5,53,41,46,78,2.0,7,70,Semi-Urban,Manager,132104,0 +70712,Male,35,Masters,18,47,39,23,33,2.0,6,78,Urban,HR Executive,92158,0 +70713,Male,57,High School,19,98,93,97,80,2.0,4,39,Urban,HR Executive,131685,1 +70714,Male,59,Bachelors,1,59,60,56,57,6.0,4,24,Urban,Software Engineer,25277,0 +70715,Male,49,High School,16,93,42,46,95,3.0,0,84,Semi-Urban,Data Analyst,54966,1 +70716,Female,57,PhD,10,94,0,56,11,2.0,1,45,Urban,ML Engineer,136230,0 +70717,Other,29,Masters,14,12,11,76,52,6.0,0,57,Urban,Data Analyst,55692,0 +70718,Male,26,Bachelors,6,83,22,62,49,1.0,7,52,Urban,Software Engineer,124025,0 +70719,Female,28,Diploma,19,14,10,56,61,0.0,6,60,Urban,HR Executive,32352,0 +70720,Female,24,High School,4,52,4,54,75,0.0,6,50,Urban,Software Engineer,56080,0 +70721,Female,35,High School,9,57,84,75,87,1.0,5,53,Urban,Manager,131633,1 +70722,Male,28,Bachelors,14,21,50,50,75,4.0,4,12,Semi-Urban,HR Executive,33982,0 +70723,Male,46,Diploma,16,14,18,69,1,6.0,7,64,Rural,Manager,137198,0 +70724,Male,38,Bachelors,1,84,63,58,5,4.0,4,76,Urban,Data Analyst,57707,1 +70725,Female,45,Bachelors,14,7,4,85,56,9.0,0,45,Urban,Software Engineer,103497,0 +70726,Female,28,Masters,9,73,28,53,63,7.0,7,67,Urban,Data Analyst,28343,0 +70727,Male,55,Diploma,1,92,31,82,96,6.0,4,42,Semi-Urban,ML Engineer,57828,1 +70728,Male,41,Bachelors,5,75,41,93,56,8.0,4,83,Urban,HR Executive,94737,1 +70729,Male,48,Masters,14,43,92,34,82,8.0,2,97,Urban,Software Engineer,143288,1 +70730,Male,57,High School,15,50,34,32,52,3.0,0,82,Rural,Data Analyst,124913,0 +70731,Male,32,Masters,2,42,71,93,1,6.0,4,3,Rural,HR Executive,40338,0 +70732,Female,57,Masters,7,92,27,60,3,8.0,6,12,Rural,Manager,97887,0 +70733,Male,21,Bachelors,7,19,21,62,16,7.0,4,45,Semi-Urban,Data Analyst,44199,0 +70734,Male,23,Bachelors,4,50,86,41,64,4.0,7,23,Urban,Data Analyst,32723,0 +70735,Female,40,Bachelors,2,51,78,60,74,9.0,4,42,Urban,ML Engineer,54643,0 +70736,Female,24,Bachelors,18,34,25,31,95,4.0,5,67,Urban,HR Executive,22303,0 +70737,Male,45,High School,14,16,32,50,61,5.0,2,12,Semi-Urban,HR Executive,85723,0 +70738,Female,26,Masters,4,12,3,26,87,9.0,4,82,Rural,Data Analyst,72930,0 +70739,Female,41,Diploma,17,95,56,25,43,8.0,6,88,Urban,Manager,22950,1 +70740,Male,26,Diploma,1,81,75,92,48,3.0,1,39,Semi-Urban,Software Engineer,106782,1 +70741,Male,48,Masters,6,22,67,7,51,0.0,0,76,Semi-Urban,HR Executive,49746,0 +70742,Male,45,Bachelors,9,50,6,44,32,6.0,3,77,Urban,HR Executive,101388,0 +70743,Female,22,Diploma,17,43,2,22,39,9.0,3,29,Urban,Data Analyst,109294,0 +70744,Female,38,Diploma,7,17,83,19,46,2.0,4,8,Urban,ML Engineer,22415,0 +70745,Male,33,Bachelors,19,44,66,79,20,5.0,6,36,Rural,HR Executive,65998,0 +70746,Male,46,Diploma,1,78,70,33,93,9.0,1,61,Semi-Urban,ML Engineer,109901,1 +70747,Female,35,Bachelors,10,65,63,61,54,4.0,4,25,Urban,Software Engineer,36643,0 +70748,Male,34,Diploma,3,47,82,13,31,7.0,1,33,Urban,Manager,21998,0 +70749,Female,50,Masters,13,15,38,76,9,1.0,5,51,Rural,Manager,49865,0 +70750,Male,26,Bachelors,5,30,35,22,2,3.0,5,74,Urban,Manager,145972,0 +70751,Male,27,Bachelors,18,61,86,13,7,3.0,7,67,Urban,Software Engineer,104108,0 +70752,Male,32,Bachelors,4,98,39,84,51,4.0,0,28,Rural,Software Engineer,135179,1 +70753,Other,43,Bachelors,9,45,18,16,59,2.0,3,45,Urban,ML Engineer,40051,0 +70754,Female,54,Diploma,0,65,20,35,73,8.0,0,74,Urban,Software Engineer,101268,0 +70755,Female,42,PhD,13,52,73,62,38,2.0,5,33,Rural,HR Executive,98969,0 +70756,Female,27,Diploma,10,88,82,70,71,8.0,3,37,Urban,Data Analyst,102029,1 +70757,Male,28,Diploma,16,99,83,15,80,1.0,3,6,Urban,ML Engineer,95479,0 +70758,Female,38,Diploma,15,86,93,46,49,5.0,0,85,Semi-Urban,Software Engineer,39842,1 +70759,Male,32,Bachelors,2,1,11,6,98,3.0,2,49,Urban,Software Engineer,114761,0 +70760,Female,58,Bachelors,6,86,77,5,61,8.0,5,25,Semi-Urban,Software Engineer,45319,0 +70761,Male,50,Masters,9,19,42,30,51,3.0,6,14,Rural,ML Engineer,118250,0 +70762,Male,25,Bachelors,18,29,70,74,37,0.0,0,46,Rural,Data Analyst,132720,0 +70763,Male,58,Bachelors,16,53,43,9,31,4.0,1,57,Semi-Urban,Software Engineer,78575,0 +70764,Male,59,Bachelors,18,36,64,23,52,5.0,4,14,Semi-Urban,Software Engineer,35636,0 +70765,Female,31,Bachelors,13,5,15,85,95,0.0,4,51,Semi-Urban,Software Engineer,24793,0 +70766,Female,53,Bachelors,1,24,23,39,33,7.0,0,49,Rural,Data Analyst,52966,0 +70767,Female,55,Masters,18,14,83,73,39,3.0,1,94,Urban,ML Engineer,39968,1 +70768,Male,21,High School,16,29,48,1,45,7.0,4,76,Urban,HR Executive,117403,0 +70769,Female,43,Masters,16,16,0,29,61,6.0,2,27,Semi-Urban,HR Executive,78075,0 +70770,Female,35,Masters,9,79,45,26,84,2.0,6,75,Urban,Data Analyst,38579,0 +70771,Male,45,Diploma,16,26,11,30,30,8.0,4,69,Urban,ML Engineer,119414,0 +70772,Male,58,Masters,7,12,83,8,63,5.0,1,67,Semi-Urban,Manager,31888,0 +70773,Female,42,Bachelors,3,11,34,45,30,0.0,7,29,Semi-Urban,Software Engineer,30784,0 +70774,Female,43,Masters,13,66,23,47,93,3.0,4,73,Rural,ML Engineer,53848,0 +70775,Male,39,Bachelors,10,66,22,37,12,2.0,1,92,Urban,ML Engineer,127229,0 +70776,Male,22,PhD,4,47,11,86,60,4.0,2,9,Rural,ML Engineer,34844,0 +70777,Male,56,Bachelors,18,58,56,9,49,0.0,1,0,Urban,Software Engineer,146142,0 +70778,Male,42,Masters,16,21,28,4,29,0.0,3,20,Rural,Manager,111568,0 +70779,Male,39,Bachelors,14,13,78,74,60,0.0,7,34,Semi-Urban,HR Executive,53968,0 +70780,Male,46,Masters,1,65,38,30,84,1.0,3,65,Urban,Software Engineer,142776,0 +70781,Male,54,PhD,10,0,69,35,31,9.0,0,30,Rural,ML Engineer,52303,0 +70782,Male,38,Masters,19,74,77,6,25,2.0,4,91,Semi-Urban,HR Executive,138028,1 +70783,Female,50,High School,10,57,59,13,40,8.0,0,91,Urban,Manager,111435,0 +70784,Male,48,High School,4,77,18,80,21,2.0,4,10,Urban,Software Engineer,133800,0 +70785,Male,53,Bachelors,7,7,71,28,1,4.0,2,99,Urban,ML Engineer,64245,0 +70786,Male,23,Bachelors,12,95,73,72,29,0.0,7,33,Semi-Urban,ML Engineer,40485,1 +70787,Male,43,High School,4,95,86,28,71,4.0,3,39,Urban,Software Engineer,29898,1 +70788,Male,36,Diploma,9,95,96,48,21,1.0,7,91,Rural,ML Engineer,42429,1 +70789,Male,39,Bachelors,18,11,76,33,62,1.0,1,63,Urban,HR Executive,98062,0 +70790,Other,28,Bachelors,5,94,57,17,47,0.0,2,7,Urban,ML Engineer,149995,0 +70791,Male,36,High School,0,71,38,0,66,5.0,4,63,Semi-Urban,ML Engineer,28751,0 +70792,Male,54,Bachelors,5,80,35,5,28,4.0,3,37,Urban,ML Engineer,144862,0 +70793,Male,47,Bachelors,16,41,17,36,9,7.0,3,39,Urban,ML Engineer,38993,0 +70794,Male,57,Masters,10,12,39,50,22,1.0,1,81,Urban,Data Analyst,26876,0 +70795,Female,59,High School,12,43,73,58,22,9.0,4,7,Semi-Urban,Data Analyst,143631,0 +70796,Male,47,Bachelors,7,8,56,68,68,1.0,7,33,Semi-Urban,Manager,86257,0 +70797,Male,38,Bachelors,8,18,75,78,21,3.0,4,92,Semi-Urban,Manager,54095,1 +70798,Male,42,Bachelors,0,9,71,22,34,4.0,0,24,Urban,HR Executive,40133,0 +70799,Male,54,High School,18,77,32,48,77,6.0,3,24,Urban,ML Engineer,143890,0 +70800,Female,40,Masters,12,93,61,62,78,4.0,5,4,Urban,Software Engineer,78669,0 +70801,Male,23,Bachelors,13,69,34,80,17,7.0,1,40,Urban,HR Executive,57613,0 +70802,Male,58,Masters,15,80,61,3,81,0.0,2,62,Semi-Urban,Manager,121585,0 +70803,Male,46,High School,19,80,69,95,69,7.0,1,50,Urban,Manager,59951,1 +70804,Male,39,Bachelors,0,48,45,78,9,5.0,2,66,Semi-Urban,HR Executive,59345,1 +70805,Female,55,High School,7,22,14,75,97,6.0,5,32,Urban,Data Analyst,68837,0 +70806,Male,30,Bachelors,19,85,74,87,67,7.0,6,37,Urban,Data Analyst,141698,1 +70807,Male,58,High School,16,35,28,74,96,6.0,7,63,Urban,ML Engineer,79112,0 +70808,Male,25,Diploma,10,43,21,62,99,3.0,5,99,Urban,HR Executive,121776,0 +70809,Male,49,Masters,1,28,84,42,30,1.0,6,77,Urban,Software Engineer,73865,0 +70810,Male,54,Bachelors,15,95,7,76,26,9.0,0,88,Semi-Urban,HR Executive,146137,1 +70811,Female,50,Bachelors,4,40,30,19,31,4.0,2,7,Urban,HR Executive,130506,0 +70812,Female,59,Masters,10,81,99,35,50,6.0,7,95,Urban,Software Engineer,126925,1 +70813,Female,38,Diploma,12,36,57,86,76,1.0,3,95,Rural,Data Analyst,103489,1 +70814,Male,37,High School,2,14,2,83,22,6.0,2,25,Semi-Urban,HR Executive,31761,0 +70815,Female,36,Bachelors,1,65,3,9,66,1.0,3,46,Semi-Urban,ML Engineer,76172,0 +70816,Male,51,Bachelors,10,38,7,55,68,2.0,3,78,Semi-Urban,Manager,66973,0 +70817,Other,44,Diploma,11,39,15,28,54,9.0,4,96,Semi-Urban,ML Engineer,115088,0 +70818,Male,36,Masters,5,50,18,30,73,2.0,6,48,Urban,HR Executive,124877,0 +70819,Male,31,Bachelors,7,52,11,99,51,7.0,2,33,Semi-Urban,ML Engineer,120226,0 +70820,Male,50,Masters,7,51,67,64,0,9.0,5,60,Urban,Data Analyst,128531,1 +70821,Male,30,Masters,14,88,38,76,6,6.0,5,60,Urban,ML Engineer,139132,1 +70822,Male,46,Bachelors,7,17,39,35,72,2.0,5,80,Rural,ML Engineer,117798,0 +70823,Male,37,Bachelors,1,5,84,54,68,2.0,0,41,Semi-Urban,Software Engineer,51666,0 +70824,Male,43,Masters,16,22,13,34,23,6.0,3,95,Urban,Manager,132841,0 +70825,Female,48,High School,17,67,20,69,92,1.0,1,3,Urban,Data Analyst,112352,0 +70826,Male,23,Bachelors,13,56,57,57,92,1.0,3,23,Urban,Software Engineer,92167,0 +70827,Male,29,Diploma,15,14,84,23,89,9.0,1,81,Rural,Data Analyst,103278,0 +70828,Female,52,Bachelors,8,31,60,44,5,8.0,5,11,Urban,Software Engineer,32665,0 +70829,Male,29,Masters,0,48,59,97,82,7.0,2,37,Urban,ML Engineer,68086,1 +70830,Female,34,Diploma,14,40,29,4,57,7.0,4,10,Rural,Software Engineer,117760,0 +70831,Female,41,High School,1,25,1,20,89,1.0,1,64,Rural,Software Engineer,26865,0 +70832,Male,28,Diploma,3,78,54,56,47,1.0,3,16,Semi-Urban,Software Engineer,55653,0 +70833,Male,49,Masters,18,4,90,39,98,8.0,1,74,Urban,ML Engineer,105985,0 +70834,Male,59,Bachelors,2,0,52,31,54,3.0,1,94,Urban,Software Engineer,117389,0 +70835,Male,33,Bachelors,0,95,25,62,20,4.0,2,9,Urban,HR Executive,92028,0 +70836,Female,30,Bachelors,18,31,2,56,77,5.0,3,14,Urban,HR Executive,122483,0 +70837,Female,34,Masters,12,98,97,17,16,9.0,5,5,Urban,Software Engineer,36957,0 +70838,Female,23,Masters,7,86,71,24,62,7.0,7,29,Urban,HR Executive,40964,0 +70839,Male,42,Diploma,6,32,91,60,9,6.0,5,61,Semi-Urban,Data Analyst,106112,1 +70840,Other,35,Bachelors,13,91,73,65,25,1.0,0,36,Urban,ML Engineer,108596,1 +70841,Female,21,Diploma,15,93,81,85,19,7.0,1,85,Urban,Software Engineer,61158,1 +70842,Female,21,High School,9,30,22,77,76,0.0,1,7,Rural,Software Engineer,98081,0 +70843,Male,28,Masters,15,4,1,71,63,3.0,4,94,Urban,Software Engineer,77961,0 +70844,Male,36,Masters,17,95,68,49,98,8.0,4,30,Urban,Data Analyst,92489,1 +70845,Male,34,PhD,19,86,36,5,2,2.0,7,99,Urban,Manager,20845,0 +70846,Male,34,Bachelors,1,58,83,6,77,0.0,4,50,Rural,Software Engineer,146593,0 +70847,Male,46,Bachelors,12,1,69,24,1,7.0,0,19,Semi-Urban,ML Engineer,127244,0 +70848,Female,40,Masters,3,56,33,65,9,6.0,7,20,Urban,ML Engineer,45160,0 +70849,Female,34,Diploma,11,74,88,32,88,6.0,0,16,Urban,ML Engineer,146546,0 +70850,Female,57,Bachelors,18,70,68,77,14,8.0,3,79,Semi-Urban,HR Executive,101463,1 +70851,Male,59,Diploma,17,87,10,78,66,5.0,0,13,Urban,Software Engineer,146695,0 +70852,Male,50,Diploma,12,23,28,48,83,2.0,6,32,Urban,ML Engineer,48493,0 +70853,Male,51,Bachelors,5,1,87,6,32,8.0,1,98,Urban,ML Engineer,91022,0 +70854,Male,27,Bachelors,6,45,28,34,22,7.0,6,44,Urban,Manager,137114,0 +70855,Male,24,Diploma,15,87,59,67,1,6.0,7,77,Semi-Urban,Software Engineer,127714,1 +70856,Male,43,Diploma,5,79,62,18,26,5.0,0,89,Urban,HR Executive,53418,1 +70857,Male,52,Masters,8,93,81,62,65,1.0,6,87,Semi-Urban,HR Executive,59962,1 +70858,Male,24,Bachelors,18,72,8,3,42,1.0,1,49,Rural,HR Executive,127731,0 +70859,Male,43,Bachelors,0,39,21,54,17,0.0,3,20,Semi-Urban,Data Analyst,35293,0 +70860,Male,53,Bachelors,16,10,24,26,11,2.0,6,0,Semi-Urban,ML Engineer,29599,0 +70861,Female,23,Masters,14,38,1,43,74,9.0,4,12,Semi-Urban,ML Engineer,93212,0 +70862,Female,53,Bachelors,19,76,66,40,75,3.0,7,76,Rural,HR Executive,66990,1 +70863,Male,35,Diploma,14,40,15,36,7,2.0,6,88,Urban,Manager,145467,0 +70864,Male,55,Bachelors,17,95,89,7,1,9.0,1,77,Urban,Manager,37672,1 +70865,Female,47,Diploma,12,99,82,77,83,5.0,0,20,Urban,HR Executive,66784,1 +70866,Female,36,Diploma,14,28,75,65,8,5.0,1,50,Semi-Urban,Data Analyst,117021,0 +70867,Female,21,Diploma,11,16,13,48,75,8.0,0,94,Semi-Urban,HR Executive,110165,0 +70868,Male,32,Bachelors,9,4,58,25,10,3.0,3,86,Urban,Manager,124578,0 +70869,Female,38,Masters,5,13,59,39,42,4.0,2,79,Urban,ML Engineer,41924,0 +70870,Other,57,High School,2,25,83,54,61,0.0,0,7,Rural,Software Engineer,20341,0 +70871,Male,41,Masters,2,60,38,61,17,0.0,3,1,Semi-Urban,Data Analyst,20261,0 +70872,Male,43,Bachelors,13,13,22,30,53,6.0,5,28,Semi-Urban,Manager,62843,0 +70873,Male,55,Diploma,1,28,71,9,82,3.0,7,77,Rural,HR Executive,61270,0 +70874,Female,32,High School,1,26,4,96,30,9.0,0,58,Urban,Manager,88231,0 +70875,Male,23,Bachelors,15,96,0,10,4,7.0,1,20,Rural,Manager,100294,0 +70876,Male,24,Bachelors,16,90,36,82,68,6.0,0,29,Urban,Data Analyst,44230,1 +70877,Female,58,Bachelors,11,10,80,50,19,8.0,1,89,Semi-Urban,Manager,59858,0 +70878,Male,23,Masters,0,56,9,32,16,5.0,2,59,Rural,HR Executive,67741,0 +70879,Male,34,Bachelors,17,92,87,13,67,5.0,6,67,Urban,Data Analyst,146439,1 +70880,Other,22,Diploma,1,54,32,3,45,1.0,1,67,Urban,HR Executive,30580,0 +70881,Female,45,Diploma,18,17,27,62,82,9.0,4,21,Urban,ML Engineer,93837,0 +70882,Female,42,Bachelors,10,10,32,27,34,4.0,0,79,Urban,Manager,56814,0 +70883,Male,49,High School,16,82,71,11,26,5.0,7,63,Urban,Data Analyst,143356,0 +70884,Female,21,Masters,5,88,48,61,52,2.0,5,42,Semi-Urban,Software Engineer,77185,0 +70885,Female,43,High School,10,31,99,73,24,4.0,1,74,Rural,HR Executive,89183,1 +70886,Female,53,Diploma,10,74,87,32,29,9.0,2,10,Rural,Data Analyst,53460,0 +70887,Male,57,Masters,5,39,56,92,17,4.0,2,15,Urban,Manager,136346,0 +70888,Male,43,Masters,14,99,14,52,98,5.0,6,77,Rural,Manager,61478,1 +70889,Male,32,Bachelors,4,29,24,39,37,8.0,4,61,Rural,HR Executive,49989,0 +70890,Male,51,High School,13,43,35,68,90,6.0,6,8,Urban,ML Engineer,86465,0 +70891,Female,59,Masters,5,54,5,74,86,3.0,5,43,Semi-Urban,HR Executive,43193,0 +70892,Male,46,Diploma,18,26,14,72,24,6.0,1,53,Semi-Urban,ML Engineer,89170,0 +70893,Male,40,Diploma,1,77,77,38,99,7.0,3,99,Urban,Software Engineer,49945,1 +70894,Male,33,Diploma,9,40,66,44,44,5.0,6,98,Rural,ML Engineer,87301,1 +70895,Male,50,Masters,16,51,71,22,25,8.0,1,8,Urban,ML Engineer,35235,0 +70896,Male,55,Masters,17,11,10,50,22,9.0,6,94,Rural,HR Executive,53696,0 +70897,Male,53,Bachelors,9,17,50,11,25,3.0,5,90,Urban,Manager,60907,0 +70898,Male,57,Masters,14,86,8,60,56,8.0,1,95,Rural,ML Engineer,113097,1 +70899,Male,31,Masters,4,60,70,59,10,0.0,5,16,Semi-Urban,HR Executive,20350,0 +70900,Male,52,Bachelors,13,66,78,12,44,8.0,7,38,Urban,HR Executive,132536,0 +70901,Male,53,Bachelors,3,51,95,1,60,5.0,2,82,Urban,Software Engineer,147214,0 +70902,Male,51,PhD,6,48,15,12,35,2.0,2,61,Urban,ML Engineer,43139,0 +70903,Female,56,Diploma,18,63,15,53,92,2.0,3,94,Urban,ML Engineer,85501,0 +70904,Male,37,High School,12,53,70,70,33,3.0,5,5,Rural,HR Executive,45072,0 +70905,Female,43,Diploma,2,19,51,39,1,6.0,7,97,Semi-Urban,Software Engineer,122987,0 +70906,Male,34,Masters,10,91,13,78,21,5.0,6,29,Rural,Software Engineer,124123,0 +70907,Male,46,Diploma,1,83,63,1,24,2.0,5,93,Urban,ML Engineer,35504,1 +70908,Male,55,Diploma,7,22,96,52,35,0.0,7,32,Urban,HR Executive,36135,0 +70909,Female,29,Bachelors,4,21,2,6,75,0.0,3,36,Urban,HR Executive,106087,0 +70910,Male,22,Diploma,1,49,58,18,36,5.0,2,76,Urban,Software Engineer,130278,0 +70911,Male,35,Masters,10,15,5,58,14,9.0,2,45,Urban,HR Executive,130113,0 +70912,Female,52,Bachelors,15,7,0,8,17,1.0,5,85,Urban,HR Executive,36023,0 +70913,Male,31,Bachelors,8,46,76,58,27,8.0,0,88,Rural,Software Engineer,135602,1 +70914,Female,21,Masters,13,95,41,53,41,4.0,1,76,Urban,Software Engineer,100920,1 +70915,Male,29,PhD,10,9,10,50,80,4.0,0,66,Semi-Urban,Manager,68975,0 +70916,Male,51,PhD,14,37,90,96,31,8.0,0,20,Urban,Manager,108751,1 +70917,Female,37,Bachelors,5,92,99,77,97,5.0,2,1,Urban,Software Engineer,116768,1 +70918,Male,30,PhD,18,46,60,84,92,1.0,1,10,Urban,ML Engineer,123571,0 +70919,Male,48,Diploma,5,27,87,39,48,2.0,2,22,Semi-Urban,Data Analyst,118943,0 +70920,Female,51,Bachelors,19,90,88,39,12,9.0,7,94,Semi-Urban,Data Analyst,69812,1 +70921,Female,24,Diploma,2,86,11,84,92,9.0,7,48,Urban,Software Engineer,38084,0 +70922,Male,45,Masters,9,94,21,79,80,5.0,1,77,Urban,Software Engineer,79991,1 +70923,Male,35,Diploma,3,26,64,25,11,5.0,0,66,Urban,Data Analyst,145051,0 +70924,Male,22,High School,16,69,40,6,14,0.0,6,17,Semi-Urban,Manager,33823,0 +70925,Female,27,Bachelors,18,80,56,48,27,3.0,4,88,Urban,Manager,124635,1 +70926,Female,27,Bachelors,1,74,93,1,60,9.0,7,6,Semi-Urban,ML Engineer,36104,0 +70927,Female,38,Bachelors,1,28,59,25,70,6.0,7,13,Urban,Manager,119957,0 +70928,Female,36,Bachelors,17,68,20,86,3,8.0,7,94,Urban,ML Engineer,36892,1 +70929,Female,43,Bachelors,19,88,93,10,45,7.0,1,79,Urban,Software Engineer,86385,1 +70930,Male,21,PhD,1,96,69,3,81,1.0,2,43,Semi-Urban,Software Engineer,113967,0 +70931,Male,55,PhD,19,72,90,66,6,4.0,0,7,Urban,Data Analyst,43101,1 +70932,Male,25,PhD,2,42,80,83,72,7.0,7,55,Urban,Software Engineer,56524,1 +70933,Male,40,High School,12,25,70,71,63,2.0,5,81,Semi-Urban,HR Executive,39027,1 +70934,Male,45,Masters,15,82,68,7,45,5.0,6,88,Urban,Manager,76409,1 +70935,Male,44,Bachelors,9,84,87,5,94,5.0,3,35,Semi-Urban,Software Engineer,111479,0 +70936,Male,47,Diploma,3,75,29,5,25,7.0,6,83,Urban,Data Analyst,137467,0 +70937,Female,35,High School,4,54,74,36,88,0.0,0,60,Urban,Data Analyst,91513,0 +70938,Other,31,Bachelors,9,5,63,94,36,1.0,3,57,Semi-Urban,HR Executive,64565,0 +70939,Male,54,Bachelors,16,76,12,71,17,4.0,6,43,Urban,Data Analyst,58764,0 +70940,Male,51,High School,2,44,75,32,20,7.0,0,15,Urban,Data Analyst,89564,0 +70941,Female,26,Bachelors,5,98,16,89,91,1.0,7,85,Rural,Data Analyst,46488,1 +70942,Male,37,Masters,3,66,93,8,84,5.0,7,25,Rural,ML Engineer,64818,0 +70943,Male,30,Diploma,15,57,41,30,15,2.0,2,47,Semi-Urban,Software Engineer,113500,0 +70944,Female,36,Diploma,7,48,75,64,4,5.0,5,43,Urban,Data Analyst,129233,0 +70945,Female,25,Diploma,10,18,46,53,72,6.0,3,34,Urban,ML Engineer,112585,0 +70946,Male,42,Bachelors,17,21,83,95,97,0.0,0,54,Rural,HR Executive,77044,1 +70947,Female,36,Diploma,2,29,14,79,86,8.0,3,12,Urban,Data Analyst,145988,0 +70948,Other,27,Bachelors,10,92,99,92,90,3.0,5,37,Semi-Urban,ML Engineer,85364,1 +70949,Female,44,Bachelors,3,66,37,46,79,5.0,4,18,Semi-Urban,ML Engineer,130567,0 +70950,Male,39,Masters,10,73,85,49,75,9.0,2,37,Semi-Urban,Data Analyst,35403,1 +70951,Male,33,Masters,7,62,78,18,70,0.0,7,75,Semi-Urban,HR Executive,140790,0 +70952,Female,55,High School,0,32,64,19,31,9.0,5,19,Urban,Data Analyst,149957,0 +70953,Female,22,High School,7,94,7,56,97,7.0,3,92,Rural,ML Engineer,21516,1 +70954,Male,40,High School,0,53,18,19,92,0.0,7,69,Urban,Software Engineer,45472,0 +70955,Male,54,Diploma,17,47,36,16,98,5.0,5,64,Semi-Urban,Manager,21956,0 +70956,Female,53,High School,17,1,9,56,67,9.0,6,84,Semi-Urban,Manager,73283,0 +70957,Male,27,Bachelors,5,6,90,32,96,3.0,7,19,Urban,HR Executive,95283,0 +70958,Female,49,Diploma,5,12,95,82,50,2.0,5,44,Urban,Data Analyst,39871,0 +70959,Female,22,Masters,16,51,39,23,79,2.0,7,40,Urban,Data Analyst,52392,0 +70960,Female,51,Bachelors,12,41,16,87,60,6.0,5,26,Rural,Data Analyst,49952,0 +70961,Male,40,High School,9,50,76,52,97,5.0,4,68,Urban,Manager,119303,1 +70962,Male,21,Bachelors,11,57,79,73,42,8.0,0,5,Rural,Manager,103043,0 +70963,Female,25,High School,9,76,5,84,85,8.0,1,35,Semi-Urban,Software Engineer,132376,0 +70964,Male,52,Bachelors,4,38,1,42,42,2.0,0,96,Rural,Manager,24937,0 +70965,Male,57,Bachelors,9,66,9,70,56,1.0,7,72,Rural,Software Engineer,26746,0 +70966,Male,23,Bachelors,13,1,93,20,14,8.0,4,17,Rural,Manager,30523,0 +70967,Male,54,Bachelors,3,59,96,21,67,3.0,7,65,Urban,ML Engineer,146763,1 +70968,Female,42,Bachelors,18,86,60,57,39,8.0,4,65,Semi-Urban,Software Engineer,127131,1 +70969,Female,21,Bachelors,4,28,56,39,31,7.0,0,35,Urban,Manager,31674,0 +70970,Male,25,Masters,17,12,79,70,15,8.0,1,46,Rural,ML Engineer,69456,0 +70971,Female,58,Bachelors,3,63,12,1,98,3.0,0,23,Urban,Data Analyst,50866,0 +70972,Female,30,Diploma,3,9,34,38,43,6.0,1,18,Urban,Data Analyst,73054,0 +70973,Male,54,Masters,6,84,95,21,67,7.0,6,40,Rural,HR Executive,92306,1 +70974,Male,53,Bachelors,11,96,77,25,89,5.0,6,2,Rural,Software Engineer,22574,0 +70975,Male,55,Bachelors,10,20,98,98,30,9.0,4,14,Urban,Software Engineer,149554,0 +70976,Male,25,High School,1,68,20,81,26,3.0,2,94,Rural,Data Analyst,104617,1 +70977,Male,26,Bachelors,14,29,38,6,74,0.0,5,5,Urban,ML Engineer,146901,0 +70978,Male,54,Diploma,14,9,97,71,33,9.0,4,20,Semi-Urban,ML Engineer,135217,0 +70979,Male,46,Masters,17,70,42,94,95,6.0,5,46,Rural,Software Engineer,95945,1 +70980,Female,54,Masters,2,71,54,15,66,5.0,4,68,Semi-Urban,ML Engineer,56619,0 +70981,Female,22,Bachelors,17,70,15,45,99,0.0,5,73,Urban,Manager,122116,0 +70982,Other,59,Masters,17,77,8,93,95,9.0,0,84,Urban,HR Executive,25844,1 +70983,Male,36,Bachelors,15,29,19,15,87,4.0,0,2,Urban,Software Engineer,24677,0 +70984,Male,39,Bachelors,6,8,46,83,71,6.0,3,89,Urban,Software Engineer,74609,0 +70985,Male,46,Diploma,0,71,27,93,93,9.0,1,56,Rural,Software Engineer,35550,1 +70986,Male,31,Diploma,9,9,8,20,44,0.0,7,72,Urban,HR Executive,118845,0 +70987,Female,52,Bachelors,6,6,54,4,67,7.0,0,79,Rural,Software Engineer,145958,0 +70988,Male,28,High School,19,86,41,61,47,0.0,0,24,Rural,HR Executive,44849,0 +70989,Male,30,Bachelors,13,29,15,93,92,5.0,3,22,Urban,Manager,61474,0 +70990,Female,36,Diploma,15,45,93,4,26,6.0,4,12,Urban,Manager,56785,0 +70991,Male,43,PhD,1,55,26,56,61,1.0,2,93,Urban,Data Analyst,109030,0 +70992,Male,40,Diploma,11,73,2,98,38,0.0,0,43,Semi-Urban,ML Engineer,23556,0 +70993,Female,31,Diploma,16,72,14,32,18,3.0,5,97,Urban,Software Engineer,130218,0 +70994,Female,46,High School,4,59,54,32,33,7.0,3,11,Urban,HR Executive,27092,0 +70995,Male,41,Bachelors,7,85,65,75,62,2.0,1,65,Semi-Urban,ML Engineer,29022,1 +70996,Female,50,PhD,14,71,21,96,4,9.0,3,36,Urban,ML Engineer,142781,0 +70997,Male,57,High School,10,44,39,56,15,3.0,2,25,Urban,Manager,62915,0 +70998,Male,50,High School,18,6,47,20,31,1.0,4,2,Urban,ML Engineer,117221,0 +70999,Male,40,Bachelors,15,29,72,9,49,5.0,1,10,Rural,Manager,78786,0 +71000,Female,26,Masters,0,75,79,78,49,9.0,1,63,Urban,Manager,32096,1 +71001,Male,31,Bachelors,18,34,93,70,45,0.0,1,80,Urban,HR Executive,110654,1 +71002,Male,56,Bachelors,19,74,82,36,99,4.0,1,64,Urban,ML Engineer,99757,1 +71003,Other,59,Bachelors,1,71,51,43,43,3.0,1,83,Semi-Urban,Data Analyst,109148,1 +71004,Female,36,Bachelors,1,3,26,92,54,6.0,3,15,Urban,HR Executive,32300,0 +71005,Female,40,High School,12,6,62,90,88,3.0,1,61,Urban,Software Engineer,113927,0 +71006,Male,35,Diploma,15,54,38,90,48,5.0,6,84,Semi-Urban,Data Analyst,29723,1 +71007,Male,39,PhD,11,55,68,44,59,6.0,1,70,Semi-Urban,ML Engineer,74245,1 +71008,Male,48,Bachelors,18,6,66,36,7,7.0,2,33,Semi-Urban,Data Analyst,95001,0 +71009,Male,45,Bachelors,1,51,70,21,21,0.0,4,56,Urban,Data Analyst,149343,0 +71010,Male,35,Bachelors,7,47,86,52,56,2.0,3,15,Semi-Urban,Software Engineer,42610,0 +71011,Female,39,Bachelors,10,26,31,49,36,6.0,1,96,Urban,ML Engineer,54866,0 +71012,Male,43,Bachelors,17,10,96,57,73,7.0,5,71,Urban,Data Analyst,57169,0 +71013,Male,44,Bachelors,7,75,79,30,14,0.0,2,87,Rural,Manager,79599,1 +71014,Male,21,Diploma,6,65,21,14,20,8.0,6,40,Urban,Software Engineer,78509,0 +71015,Male,52,Bachelors,4,47,10,86,23,5.0,0,5,Urban,Manager,37697,0 +71016,Male,49,Diploma,16,32,62,26,35,9.0,2,81,Semi-Urban,ML Engineer,119009,0 +71017,Male,55,Bachelors,3,24,65,18,24,0.0,7,46,Semi-Urban,HR Executive,130647,0 +71018,Other,30,Bachelors,1,23,83,13,94,3.0,1,71,Semi-Urban,ML Engineer,144134,0 +71019,Male,28,Diploma,14,50,29,57,55,8.0,3,84,Urban,ML Engineer,75088,0 +71020,Female,56,Bachelors,19,46,66,74,19,9.0,7,90,Urban,HR Executive,88513,1 +71021,Female,32,Bachelors,5,79,74,84,9,0.0,7,19,Semi-Urban,Manager,129060,1 +71022,Male,23,High School,0,23,85,85,85,3.0,5,80,Urban,Software Engineer,45535,1 +71023,Female,23,High School,17,25,78,9,65,9.0,0,93,Urban,HR Executive,82070,0 +71024,Male,31,Bachelors,14,46,53,65,78,0.0,1,88,Semi-Urban,HR Executive,136391,1 +71025,Other,47,Bachelors,0,19,74,26,27,4.0,6,10,Urban,ML Engineer,39772,0 +71026,Male,39,Masters,5,28,91,77,98,8.0,7,54,Urban,ML Engineer,91116,1 +71027,Female,32,Masters,7,92,39,91,32,7.0,0,25,Urban,Data Analyst,77491,1 +71028,Female,56,Bachelors,5,11,98,60,48,7.0,4,16,Urban,HR Executive,87366,0 +71029,Male,54,High School,1,42,92,5,92,9.0,7,8,Urban,HR Executive,39826,0 +71030,Male,23,Bachelors,8,17,64,11,4,8.0,0,30,Urban,Data Analyst,28886,0 +71031,Male,43,Bachelors,11,18,25,63,99,1.0,5,85,Urban,Software Engineer,42857,0 +71032,Male,57,Diploma,2,59,73,3,74,8.0,7,95,Urban,Manager,94159,0 +71033,Male,41,Masters,8,68,44,66,31,8.0,6,50,Urban,Software Engineer,120436,0 +71034,Female,58,High School,2,85,95,90,78,6.0,6,75,Semi-Urban,Manager,32107,1 +71035,Male,27,High School,5,57,7,53,26,9.0,6,25,Urban,HR Executive,117698,0 +71036,Male,26,Diploma,14,98,39,10,93,0.0,1,23,Urban,ML Engineer,20268,0 +71037,Male,30,Diploma,3,72,17,56,35,6.0,4,26,Rural,HR Executive,34282,0 +71038,Male,55,Diploma,1,35,5,42,68,3.0,2,45,Rural,Manager,96957,0 +71039,Female,34,Masters,18,11,74,38,47,1.0,7,58,Urban,HR Executive,41285,0 +71040,Male,58,Masters,8,78,23,5,29,8.0,5,76,Urban,Software Engineer,30745,0 +71041,Male,25,Diploma,16,59,8,76,13,2.0,6,19,Rural,Software Engineer,92872,0 +71042,Male,22,High School,12,84,34,83,39,8.0,4,53,Urban,ML Engineer,122441,1 +71043,Male,23,High School,10,16,76,32,95,0.0,4,50,Urban,HR Executive,107945,0 +71044,Male,32,Masters,14,68,93,28,39,2.0,2,17,Semi-Urban,Software Engineer,23990,0 +71045,Male,57,Masters,19,87,94,61,39,5.0,5,88,Urban,Software Engineer,25845,1 +71046,Male,47,Masters,7,30,57,12,71,2.0,4,71,Semi-Urban,Data Analyst,123213,0 +71047,Female,48,Bachelors,7,46,15,71,28,8.0,6,95,Urban,HR Executive,60100,0 +71048,Male,58,Bachelors,2,54,34,12,20,8.0,7,48,Semi-Urban,Software Engineer,137885,0 +71049,Male,36,Masters,1,10,93,79,11,4.0,4,64,Rural,Manager,47091,1 +71050,Male,35,Bachelors,18,59,80,44,71,0.0,2,5,Urban,Manager,26928,0 +71051,Male,43,High School,15,27,90,29,85,5.0,4,58,Urban,HR Executive,138852,0 +71052,Male,45,Bachelors,17,75,17,7,73,3.0,2,18,Urban,Software Engineer,101745,0 +71053,Male,52,Masters,13,11,59,39,47,6.0,7,86,Urban,Manager,139802,0 +71054,Male,59,Diploma,18,25,29,46,27,4.0,5,17,Rural,Software Engineer,31869,0 +71055,Female,49,Diploma,3,8,10,72,7,2.0,7,92,Semi-Urban,ML Engineer,96085,0 +71056,Male,21,PhD,19,88,58,24,80,3.0,2,88,Urban,Data Analyst,125938,1 +71057,Male,22,Masters,1,73,64,68,45,9.0,6,88,Semi-Urban,ML Engineer,119922,1 +71058,Male,26,High School,5,12,66,57,73,4.0,7,45,Rural,Data Analyst,86968,0 +71059,Male,22,Bachelors,0,69,88,20,6,8.0,6,75,Urban,ML Engineer,87019,1 +71060,Female,25,Bachelors,14,68,24,82,42,3.0,1,28,Urban,Data Analyst,103361,0 +71061,Male,38,Diploma,17,71,99,80,73,9.0,2,24,Rural,ML Engineer,48569,1 +71062,Male,33,Bachelors,4,27,83,8,24,0.0,4,0,Semi-Urban,Software Engineer,66857,0 +71063,Female,34,Masters,11,23,43,97,31,1.0,6,48,Urban,HR Executive,71594,0 +71064,Male,41,PhD,2,76,35,56,76,2.0,6,42,Rural,Software Engineer,136059,0 +71065,Other,38,Diploma,17,29,92,56,84,0.0,5,76,Semi-Urban,Manager,136413,1 +71066,Male,34,Masters,16,4,40,92,45,8.0,5,79,Semi-Urban,Software Engineer,116309,0 +71067,Female,57,Bachelors,5,42,71,97,12,4.0,4,18,Semi-Urban,Manager,103099,0 +71068,Male,57,Bachelors,17,3,90,25,86,9.0,7,0,Urban,Data Analyst,26958,0 +71069,Female,28,Bachelors,4,69,96,18,10,8.0,7,86,Urban,HR Executive,128237,1 +71070,Male,40,Diploma,17,36,76,49,70,6.0,2,26,Semi-Urban,Manager,121088,0 +71071,Female,48,High School,9,83,50,71,53,3.0,6,72,Semi-Urban,Data Analyst,52396,1 +71072,Male,58,Diploma,10,81,33,29,63,7.0,3,21,Urban,Manager,132790,0 +71073,Female,26,Bachelors,13,50,95,47,10,7.0,0,92,Rural,HR Executive,51101,1 +71074,Female,34,Diploma,11,34,33,20,38,1.0,4,32,Urban,Data Analyst,118027,0 +71075,Female,26,Diploma,11,32,72,96,96,9.0,7,98,Rural,Manager,46077,1 +71076,Male,51,Masters,6,46,10,32,89,7.0,2,95,Urban,HR Executive,48199,0 +71077,Male,28,Masters,9,5,64,71,33,6.0,1,68,Rural,Manager,60350,0 +71078,Female,46,Masters,14,83,95,62,51,5.0,4,16,Urban,Manager,52359,1 +71079,Male,26,Diploma,11,96,22,99,53,0.0,2,4,Rural,ML Engineer,143714,0 +71080,Female,34,Diploma,17,6,27,33,27,7.0,6,45,Semi-Urban,ML Engineer,142073,0 +71081,Other,53,Bachelors,9,12,56,45,18,7.0,6,75,Urban,ML Engineer,114934,0 +71082,Male,59,Diploma,10,20,90,67,90,8.0,7,55,Urban,Data Analyst,35452,0 +71083,Male,44,Bachelors,1,38,53,79,38,9.0,2,98,Urban,Data Analyst,56577,1 +71084,Male,48,Masters,11,85,49,79,31,2.0,1,64,Urban,Manager,100967,1 +71085,Male,56,Diploma,6,97,14,74,63,9.0,3,73,Urban,Data Analyst,139455,1 +71086,Female,45,High School,19,74,59,44,37,4.0,6,55,Urban,HR Executive,28463,0 +71087,Male,41,High School,18,33,89,34,70,8.0,3,62,Urban,HR Executive,126254,0 +71088,Male,42,High School,15,17,42,90,95,1.0,5,80,Urban,Manager,40432,0 +71089,Other,42,Masters,16,86,3,29,99,5.0,2,32,Semi-Urban,ML Engineer,139206,0 +71090,Male,27,High School,17,21,22,2,68,6.0,7,67,Urban,Manager,99273,0 +71091,Female,35,Masters,7,95,54,38,22,9.0,4,15,Urban,Software Engineer,90668,0 +71092,Male,25,Bachelors,9,96,34,18,21,5.0,4,16,Urban,HR Executive,125669,0 +71093,Male,58,Masters,10,55,18,51,94,4.0,1,69,Semi-Urban,Manager,100196,0 +71094,Male,45,Diploma,8,44,92,6,71,3.0,6,99,Rural,Software Engineer,37845,1 +71095,Male,29,Bachelors,11,56,37,93,92,0.0,6,33,Urban,ML Engineer,87056,0 +71096,Female,23,Masters,7,93,64,4,69,2.0,5,33,Semi-Urban,HR Executive,26117,0 +71097,Male,23,Bachelors,8,74,81,9,96,7.0,4,14,Urban,Data Analyst,86582,0 +71098,Female,44,Diploma,4,36,40,91,29,5.0,5,27,Urban,HR Executive,121795,0 +71099,Male,54,High School,19,34,53,53,36,7.0,2,30,Rural,Software Engineer,116855,0 +71100,Female,36,Masters,2,90,49,6,72,5.0,3,37,Semi-Urban,HR Executive,26460,0 +71101,Male,55,Masters,9,36,30,35,20,8.0,2,5,Urban,ML Engineer,47788,0 +71102,Female,29,Masters,16,48,67,2,68,3.0,2,43,Urban,Software Engineer,66680,0 +71103,Male,54,Bachelors,9,3,25,62,70,9.0,0,58,Urban,HR Executive,53937,0 +71104,Male,59,Bachelors,3,16,74,23,16,3.0,5,28,Urban,ML Engineer,132826,0 +71105,Female,48,Diploma,5,11,78,38,48,3.0,6,42,Urban,HR Executive,131610,0 +71106,Female,40,Bachelors,12,7,36,37,43,3.0,4,89,Semi-Urban,ML Engineer,86115,0 +71107,Female,21,Bachelors,15,36,49,84,40,1.0,6,64,Urban,ML Engineer,41091,0 +71108,Male,48,Diploma,6,85,54,44,85,3.0,5,95,Urban,Data Analyst,44561,1 +71109,Female,56,Bachelors,6,35,20,9,19,0.0,5,2,Semi-Urban,Software Engineer,93327,0 +71110,Male,54,High School,8,12,99,53,64,7.0,0,17,Urban,Data Analyst,28748,0 +71111,Male,41,Diploma,0,13,90,50,60,7.0,7,87,Urban,ML Engineer,52325,1 +71112,Female,29,Masters,6,63,79,31,45,7.0,7,70,Urban,Manager,70397,1 +71113,Female,31,Diploma,9,38,68,85,53,5.0,0,75,Urban,Data Analyst,27172,1 +71114,Female,41,Masters,0,77,81,55,18,5.0,3,5,Urban,Manager,103846,0 +71115,Female,40,Bachelors,14,73,0,58,69,3.0,4,15,Rural,Manager,131448,0 +71116,Male,57,Masters,10,52,64,62,24,5.0,2,68,Urban,ML Engineer,133362,1 +71117,Female,32,Bachelors,6,28,44,4,34,3.0,5,9,Urban,ML Engineer,79895,0 +71118,Male,52,Diploma,11,37,99,37,53,0.0,0,94,Urban,ML Engineer,31616,1 +71119,Male,24,Bachelors,12,18,54,28,75,0.0,7,70,Urban,Data Analyst,58306,0 +71120,Female,49,Bachelors,15,93,42,88,55,1.0,3,83,Urban,Manager,65966,1 +71121,Female,27,Bachelors,3,55,36,80,57,7.0,0,13,Semi-Urban,HR Executive,110110,0 +71122,Male,51,Bachelors,10,42,48,14,30,2.0,3,87,Urban,ML Engineer,27072,0 +71123,Other,57,Diploma,10,59,87,32,25,8.0,2,2,Urban,Data Analyst,130939,0 +71124,Male,53,Diploma,10,18,97,37,88,0.0,3,5,Semi-Urban,Software Engineer,40006,0 +71125,Male,51,Masters,0,3,58,6,62,6.0,4,69,Urban,ML Engineer,121697,0 +71126,Female,24,Masters,19,44,9,84,86,4.0,6,57,Semi-Urban,Data Analyst,134179,0 +71127,Female,37,Diploma,5,81,20,20,66,5.0,3,6,Rural,ML Engineer,62321,0 +71128,Female,42,High School,5,15,42,88,25,7.0,0,33,Rural,ML Engineer,121117,0 +71129,Female,37,High School,9,71,64,94,97,1.0,2,45,Semi-Urban,HR Executive,135450,1 +71130,Male,31,Masters,3,37,70,42,83,5.0,0,38,Semi-Urban,Software Engineer,136997,0 +71131,Male,40,Diploma,5,73,65,53,81,2.0,3,95,Semi-Urban,Manager,132590,1 +71132,Other,38,Bachelors,2,55,1,56,55,2.0,7,8,Urban,HR Executive,148337,0 +71133,Female,39,Diploma,4,14,16,59,18,1.0,7,29,Rural,Software Engineer,130418,0 +71134,Female,27,Diploma,6,33,67,35,22,1.0,5,94,Urban,Software Engineer,30077,0 +71135,Female,28,Bachelors,9,74,76,37,40,7.0,0,88,Urban,Manager,75323,1 +71136,Female,27,Bachelors,8,67,57,52,7,5.0,0,67,Rural,Data Analyst,149440,1 +71137,Female,45,High School,10,89,56,49,5,4.0,0,79,Urban,Software Engineer,149248,1 +71138,Male,37,Bachelors,5,63,38,7,57,9.0,6,12,Urban,ML Engineer,65350,0 +71139,Male,21,Diploma,11,11,99,83,34,2.0,2,21,Urban,Data Analyst,78161,0 +71140,Female,59,Bachelors,6,70,27,2,86,2.0,1,55,Urban,Data Analyst,66562,0 +71141,Female,21,Diploma,18,48,84,83,68,0.0,3,76,Semi-Urban,ML Engineer,137937,1 +71142,Male,42,Bachelors,18,64,13,27,81,2.0,6,45,Urban,Manager,95123,0 +71143,Male,56,Diploma,2,44,1,64,64,1.0,0,43,Rural,HR Executive,139818,0 +71144,Male,35,PhD,1,75,83,20,43,8.0,3,44,Semi-Urban,Software Engineer,135257,0 +71145,Male,38,High School,6,82,91,89,93,8.0,1,18,Urban,Software Engineer,33663,1 +71146,Female,59,Bachelors,9,62,30,30,77,6.0,7,99,Rural,ML Engineer,37983,0 +71147,Male,30,High School,15,97,70,65,83,3.0,5,14,Semi-Urban,Manager,31281,1 +71148,Male,55,Masters,8,97,88,86,2,3.0,3,83,Urban,Data Analyst,42890,1 +71149,Male,29,Diploma,18,13,34,76,80,4.0,6,54,Rural,Data Analyst,102883,0 +71150,Male,22,Masters,18,62,24,40,56,6.0,7,26,Rural,ML Engineer,64015,0 +71151,Female,57,Masters,8,6,2,2,91,2.0,3,84,Urban,ML Engineer,47684,0 +71152,Male,42,Bachelors,19,34,59,17,57,6.0,4,44,Semi-Urban,Manager,78503,0 +71153,Female,47,High School,9,10,87,86,22,2.0,5,71,Urban,ML Engineer,45678,1 +71154,Male,25,High School,16,65,88,37,14,7.0,7,88,Urban,Data Analyst,47282,1 +71155,Male,52,Masters,1,33,36,82,11,0.0,3,46,Rural,Data Analyst,103567,0 +71156,Male,24,Bachelors,18,78,40,53,61,7.0,4,71,Semi-Urban,ML Engineer,126296,1 +71157,Other,22,Diploma,7,55,93,94,17,0.0,0,38,Urban,Manager,74841,1 +71158,Male,29,Bachelors,1,13,28,71,2,4.0,0,66,Semi-Urban,ML Engineer,148309,0 +71159,Male,48,Diploma,2,53,79,9,65,0.0,0,16,Rural,HR Executive,94367,0 +71160,Male,41,Diploma,11,66,64,25,79,3.0,0,37,Rural,Software Engineer,85885,0 +71161,Female,45,Bachelors,14,15,94,97,5,4.0,3,57,Urban,HR Executive,117741,1 +71162,Male,23,Bachelors,18,35,51,66,99,8.0,4,21,Urban,Manager,69635,0 +71163,Male,47,Masters,13,16,54,70,56,6.0,5,17,Rural,ML Engineer,56870,0 +71164,Male,45,Bachelors,15,83,11,5,40,9.0,0,9,Urban,Data Analyst,141813,0 +71165,Other,55,Diploma,19,30,9,41,8,5.0,1,17,Urban,Data Analyst,122484,0 +71166,Other,58,Bachelors,8,66,7,79,89,0.0,1,84,Urban,Data Analyst,77352,0 +71167,Male,54,Bachelors,19,59,33,55,0,4.0,1,80,Rural,Data Analyst,142147,0 +71168,Female,53,Masters,8,69,14,53,70,7.0,6,3,Urban,Software Engineer,124921,0 +71169,Male,33,High School,15,88,13,91,75,8.0,5,36,Urban,Data Analyst,23713,0 +71170,Male,33,High School,10,75,50,51,32,8.0,1,0,Rural,Data Analyst,123009,0 +71171,Female,45,Masters,11,89,87,37,41,1.0,1,0,Semi-Urban,ML Engineer,113778,0 +71172,Male,40,High School,3,78,78,68,16,3.0,3,7,Urban,HR Executive,52239,0 +71173,Male,29,Diploma,6,43,82,92,19,0.0,0,84,Urban,Manager,37315,1 +71174,Female,34,Diploma,11,40,59,63,92,2.0,1,26,Rural,Manager,49950,0 +71175,Male,58,Diploma,10,54,71,68,17,2.0,7,86,Urban,HR Executive,44856,1 +71176,Male,39,Bachelors,6,69,66,70,71,8.0,0,50,Urban,Manager,35416,1 +71177,Female,44,Masters,1,66,2,67,40,4.0,4,79,Urban,ML Engineer,143832,0 +71178,Male,42,High School,11,59,31,69,52,6.0,4,25,Urban,HR Executive,136626,0 +71179,Male,45,High School,8,33,80,32,1,1.0,4,14,Urban,Data Analyst,130352,0 +71180,Male,26,Diploma,8,45,89,91,71,9.0,7,70,Semi-Urban,Software Engineer,120896,1 +71181,Male,23,Bachelors,13,26,49,12,18,7.0,7,26,Urban,Software Engineer,129825,0 +71182,Male,52,PhD,16,53,59,20,52,8.0,6,99,Urban,Manager,93763,0 +71183,Male,27,Bachelors,14,80,53,12,4,2.0,4,28,Urban,HR Executive,113749,0 +71184,Male,50,Bachelors,18,96,90,28,44,5.0,5,73,Urban,ML Engineer,30946,1 +71185,Other,34,PhD,19,34,99,16,78,6.0,7,5,Urban,Data Analyst,30253,0 +71186,Male,46,Bachelors,2,2,44,22,76,2.0,5,64,Urban,Data Analyst,82169,0 +71187,Female,27,Bachelors,13,62,9,37,1,5.0,6,23,Urban,Data Analyst,137301,0 +71188,Male,35,Bachelors,5,29,78,89,58,1.0,1,87,Semi-Urban,Manager,109638,1 +71189,Female,28,PhD,3,81,43,84,0,8.0,0,27,Semi-Urban,Software Engineer,53745,0 +71190,Female,35,Bachelors,13,83,41,26,25,7.0,0,54,Semi-Urban,Manager,84683,0 +71191,Male,36,Diploma,16,93,35,65,88,8.0,3,93,Urban,Software Engineer,121169,1 +71192,Male,26,Bachelors,14,64,3,33,38,7.0,4,41,Semi-Urban,HR Executive,40765,0 +71193,Male,37,Diploma,9,13,54,86,82,0.0,5,92,Urban,Data Analyst,86461,1 +71194,Male,38,High School,3,76,16,21,59,7.0,7,65,Rural,Software Engineer,32014,0 +71195,Other,55,Masters,11,21,73,2,79,9.0,3,87,Rural,Manager,33268,0 +71196,Male,21,Diploma,15,54,66,88,6,2.0,1,17,Semi-Urban,Manager,100125,0 +71197,Male,41,Bachelors,2,44,77,5,64,8.0,2,39,Urban,Data Analyst,114087,0 +71198,Male,48,Masters,0,60,60,68,85,2.0,1,66,Semi-Urban,Data Analyst,132283,1 +71199,Male,33,PhD,19,99,12,84,55,0.0,1,71,Semi-Urban,Data Analyst,106697,1 +71200,Female,43,Diploma,17,68,28,44,55,1.0,2,83,Urban,ML Engineer,136557,0 +71201,Male,52,Diploma,1,25,56,37,17,7.0,3,60,Semi-Urban,Software Engineer,66196,0 +71202,Male,48,Masters,5,42,20,72,58,6.0,5,39,Urban,Data Analyst,85428,0 +71203,Male,48,Diploma,3,91,85,44,25,5.0,1,80,Urban,Software Engineer,23153,1 +71204,Male,50,High School,17,23,10,1,64,9.0,1,2,Urban,Software Engineer,149409,0 +71205,Male,36,Bachelors,18,25,39,44,22,0.0,6,62,Urban,Manager,109715,0 +71206,Other,22,Bachelors,2,19,72,24,84,3.0,0,31,Urban,Software Engineer,140575,0 +71207,Female,37,High School,6,34,54,0,51,7.0,0,66,Urban,Data Analyst,127576,0 +71208,Female,39,Masters,11,32,74,48,28,8.0,6,69,Urban,HR Executive,92334,0 +71209,Male,21,Bachelors,19,84,70,24,9,7.0,5,86,Urban,Manager,53724,1 +71210,Female,47,High School,1,45,53,77,49,2.0,4,93,Urban,Data Analyst,144496,1 +71211,Male,52,Bachelors,1,67,98,12,79,9.0,2,8,Urban,Data Analyst,25191,0 +71212,Male,21,Masters,11,93,98,74,21,8.0,4,23,Semi-Urban,HR Executive,65543,1 +71213,Male,32,Bachelors,18,85,15,80,72,7.0,0,63,Semi-Urban,Software Engineer,32350,1 +71214,Female,58,Diploma,4,13,5,4,56,8.0,0,52,Urban,Data Analyst,145027,0 +71215,Male,34,Bachelors,15,63,88,42,10,2.0,7,68,Urban,Manager,122699,1 +71216,Male,26,Bachelors,14,58,43,20,52,9.0,7,10,Urban,Data Analyst,66697,0 +71217,Female,50,Masters,15,38,46,3,97,3.0,4,95,Urban,ML Engineer,74703,0 +71218,Female,41,Diploma,0,69,36,80,19,5.0,5,71,Urban,ML Engineer,96008,1 +71219,Other,29,Bachelors,7,90,64,18,40,7.0,0,54,Semi-Urban,Manager,34941,0 +71220,Male,28,PhD,11,3,52,56,3,4.0,0,4,Rural,Software Engineer,84160,0 +71221,Male,48,High School,10,34,17,61,10,9.0,1,22,Urban,Data Analyst,106024,0 +71222,Female,47,High School,12,76,27,12,17,4.0,2,39,Urban,HR Executive,82244,0 +71223,Male,36,Bachelors,9,51,47,15,30,2.0,4,74,Urban,Software Engineer,123226,0 +71224,Male,29,Bachelors,16,64,98,33,87,4.0,5,94,Rural,Software Engineer,125852,1 +71225,Male,31,Masters,1,64,33,97,87,0.0,4,7,Rural,Manager,54410,0 +71226,Female,54,High School,13,31,1,57,86,6.0,6,57,Urban,Software Engineer,79015,0 +71227,Male,48,Bachelors,15,46,24,25,28,9.0,5,16,Semi-Urban,ML Engineer,60173,0 +71228,Female,51,Diploma,15,0,54,49,33,7.0,3,5,Urban,HR Executive,47440,0 +71229,Male,47,Masters,6,22,94,74,13,8.0,3,36,Urban,ML Engineer,130125,0 +71230,Male,35,Bachelors,0,10,99,20,92,1.0,3,73,Urban,HR Executive,31587,0 +71231,Male,38,Bachelors,19,69,69,57,43,5.0,1,49,Urban,Software Engineer,94596,1 +71232,Male,41,High School,17,88,51,52,90,5.0,3,78,Urban,Software Engineer,130668,1 +71233,Male,55,Bachelors,1,1,92,34,3,6.0,6,57,Urban,HR Executive,35181,0 +71234,Female,33,Bachelors,1,42,68,43,40,6.0,7,63,Urban,ML Engineer,72419,0 +71235,Female,36,Bachelors,0,46,85,82,31,3.0,3,81,Urban,ML Engineer,62459,1 +71236,Female,51,High School,5,97,19,97,83,2.0,2,7,Urban,Manager,76671,0 +71237,Male,48,Diploma,5,85,3,80,58,1.0,6,2,Semi-Urban,Software Engineer,113409,0 +71238,Male,58,Masters,9,71,34,20,65,0.0,4,70,Semi-Urban,HR Executive,53720,0 +71239,Female,31,Bachelors,11,13,14,25,98,7.0,3,91,Urban,Manager,62117,0 +71240,Male,36,Diploma,4,97,30,31,43,9.0,3,82,Urban,Manager,81036,1 +71241,Female,52,Masters,15,58,82,84,40,8.0,5,84,Rural,HR Executive,70371,1 +71242,Female,41,Bachelors,3,57,43,10,37,3.0,4,69,Urban,Manager,93039,0 +71243,Male,40,Masters,4,75,93,62,51,4.0,3,84,Urban,HR Executive,85246,1 +71244,Male,33,Bachelors,8,34,64,43,59,2.0,5,60,Semi-Urban,Software Engineer,26524,0 +71245,Female,22,Bachelors,0,94,13,16,41,1.0,5,44,Rural,Manager,124133,0 +71246,Male,26,Diploma,1,11,97,70,54,3.0,3,84,Urban,Manager,23401,1 +71247,Female,34,Diploma,10,64,2,88,83,0.0,4,57,Semi-Urban,Software Engineer,129745,0 +71248,Female,51,Masters,11,96,63,19,81,5.0,6,45,Semi-Urban,ML Engineer,95367,0 +71249,Female,53,Bachelors,3,91,37,96,92,6.0,6,20,Semi-Urban,Software Engineer,51713,1 +71250,Female,55,Diploma,3,48,39,21,70,4.0,4,54,Rural,HR Executive,112570,0 +71251,Female,28,Masters,19,93,76,1,31,3.0,2,63,Urban,Software Engineer,96367,0 +71252,Female,31,Bachelors,8,31,14,63,98,8.0,4,21,Urban,Manager,100364,0 +71253,Male,46,PhD,11,36,91,11,45,7.0,6,90,Urban,Manager,32753,0 +71254,Female,43,High School,17,96,7,26,49,9.0,1,54,Urban,ML Engineer,80888,0 +71255,Male,32,High School,13,8,58,54,36,0.0,2,3,Semi-Urban,ML Engineer,86688,0 +71256,Male,26,Masters,7,34,65,23,70,6.0,1,34,Urban,HR Executive,28070,0 +71257,Female,34,High School,18,24,58,55,9,7.0,2,6,Semi-Urban,Data Analyst,38537,0 +71258,Female,57,Diploma,5,31,17,70,34,8.0,6,52,Rural,HR Executive,34208,0 +71259,Male,47,Masters,16,13,55,26,79,2.0,0,30,Urban,Data Analyst,121954,0 +71260,Male,58,Bachelors,1,48,4,24,36,0.0,2,60,Urban,Manager,145082,0 +71261,Male,22,Bachelors,8,89,90,7,8,8.0,4,26,Urban,Software Engineer,26413,0 +71262,Male,57,Bachelors,13,36,98,13,8,6.0,6,9,Rural,Data Analyst,95284,0 +71263,Male,30,Bachelors,17,91,48,55,69,9.0,4,84,Urban,HR Executive,137289,1 +71264,Male,23,Masters,0,0,38,16,6,0.0,2,7,Rural,ML Engineer,41446,0 +71265,Female,38,High School,13,7,97,19,51,8.0,1,8,Semi-Urban,ML Engineer,84838,0 +71266,Male,43,Diploma,11,74,99,62,85,9.0,6,44,Rural,HR Executive,46627,1 +71267,Male,23,Bachelors,19,49,44,67,74,7.0,4,67,Rural,Manager,28437,0 +71268,Female,35,Bachelors,14,8,81,26,5,8.0,7,95,Urban,Manager,109448,0 +71269,Female,37,High School,1,83,94,43,31,6.0,7,80,Rural,Data Analyst,63661,1 +71270,Male,33,Bachelors,19,50,43,96,1,2.0,0,49,Semi-Urban,Manager,102655,1 +71271,Male,35,Diploma,12,52,10,72,70,3.0,5,93,Urban,Data Analyst,139751,0 +71272,Female,54,High School,11,83,14,43,41,1.0,4,52,Urban,Software Engineer,142052,0 +71273,Male,22,High School,19,9,50,77,6,7.0,0,12,Semi-Urban,Manager,29686,0 +71274,Female,35,Masters,0,6,78,31,82,5.0,1,8,Urban,ML Engineer,86578,0 +71275,Male,28,Diploma,6,83,84,82,83,6.0,5,62,Semi-Urban,HR Executive,52509,1 +71276,Male,33,Diploma,19,34,23,14,61,7.0,6,19,Urban,Software Engineer,90145,0 +71277,Female,31,Diploma,1,81,98,24,91,5.0,3,72,Urban,ML Engineer,65784,1 +71278,Male,55,Masters,18,21,57,78,75,2.0,5,50,Semi-Urban,ML Engineer,123098,0 +71279,Male,47,Masters,6,93,72,36,37,7.0,3,69,Rural,Manager,130351,1 +71280,Female,56,Masters,19,76,28,59,14,4.0,5,9,Semi-Urban,Software Engineer,32666,0 +71281,Other,37,Diploma,14,86,17,22,47,6.0,7,19,Semi-Urban,Data Analyst,125097,0 +71282,Male,26,Masters,6,25,96,24,64,1.0,7,52,Urban,Data Analyst,41619,0 +71283,Male,46,Bachelors,14,52,12,78,53,6.0,2,7,Rural,HR Executive,115452,0 +71284,Female,41,High School,10,82,75,43,33,0.0,3,53,Semi-Urban,ML Engineer,147696,1 +71285,Male,50,Masters,1,17,24,13,39,6.0,6,63,Urban,Software Engineer,62858,0 +71286,Female,50,Bachelors,7,43,81,8,26,8.0,5,94,Urban,ML Engineer,24845,0 +71287,Female,49,Bachelors,3,35,97,92,43,3.0,4,97,Urban,Data Analyst,116914,1 +71288,Male,52,Masters,17,60,83,83,31,5.0,2,79,Rural,Software Engineer,113320,1 +71289,Male,51,Diploma,0,58,73,51,75,0.0,2,7,Rural,Data Analyst,35153,0 +71290,Male,32,Diploma,17,23,1,81,18,5.0,0,25,Urban,Software Engineer,131169,0 +71291,Female,44,Bachelors,9,88,86,59,1,0.0,7,40,Urban,ML Engineer,23127,1 +71292,Male,21,High School,3,3,83,96,66,6.0,1,77,Urban,Data Analyst,75659,1 +71293,Female,59,Bachelors,10,50,71,16,39,6.0,5,80,Rural,ML Engineer,29499,0 +71294,Male,24,Bachelors,13,61,1,85,73,4.0,3,78,Semi-Urban,Software Engineer,92914,0 +71295,Male,44,Diploma,16,87,17,18,93,4.0,5,70,Urban,Manager,103861,0 +71296,Male,29,High School,2,80,77,22,31,5.0,2,48,Urban,Software Engineer,120455,0 +71297,Male,24,Bachelors,16,63,64,78,74,6.0,3,58,Urban,ML Engineer,148254,1 +71298,Female,32,Bachelors,4,15,42,60,19,1.0,3,51,Semi-Urban,Manager,58525,0 +71299,Male,33,Bachelors,17,46,1,17,68,7.0,7,75,Urban,HR Executive,120187,0 +71300,Male,31,High School,8,56,46,99,27,1.0,3,44,Urban,Manager,92407,1 +71301,Male,44,High School,6,61,78,59,9,6.0,7,70,Urban,Software Engineer,63591,1 +71302,Male,55,Masters,17,96,20,17,13,8.0,4,59,Urban,HR Executive,143055,0 +71303,Female,53,Masters,14,68,35,39,52,5.0,5,33,Rural,Data Analyst,113259,0 +71304,Female,47,High School,16,68,42,80,88,3.0,4,24,Urban,Software Engineer,128177,0 +71305,Male,27,Diploma,16,80,9,30,95,0.0,4,71,Urban,Manager,82289,0 +71306,Male,31,Masters,13,56,23,4,92,9.0,3,21,Urban,HR Executive,45451,0 +71307,Female,49,Diploma,10,36,79,32,75,6.0,3,80,Rural,Manager,134272,0 +71308,Male,30,Bachelors,0,43,41,14,27,9.0,7,50,Urban,HR Executive,132068,0 +71309,Female,57,Bachelors,7,54,88,95,56,5.0,4,45,Urban,HR Executive,85833,1 +71310,Male,23,Bachelors,11,71,1,68,45,7.0,7,2,Semi-Urban,Data Analyst,117942,0 +71311,Female,48,Bachelors,19,11,33,69,84,6.0,0,33,Semi-Urban,ML Engineer,136335,0 +71312,Male,56,Diploma,16,69,90,64,69,2.0,7,74,Urban,Manager,105811,1 +71313,Male,37,Diploma,19,0,0,11,31,5.0,4,29,Urban,Software Engineer,123017,0 +71314,Male,37,Diploma,13,61,84,38,63,6.0,7,99,Urban,Data Analyst,28507,1 +71315,Female,53,Diploma,8,67,48,59,57,1.0,5,86,Rural,Software Engineer,116647,1 +71316,Female,55,High School,0,96,49,94,85,2.0,4,23,Urban,HR Executive,21310,1 +71317,Male,58,Masters,10,6,51,51,24,3.0,2,86,Urban,Data Analyst,96970,0 +71318,Female,30,Bachelors,8,49,88,50,68,3.0,3,18,Urban,Software Engineer,24076,0 +71319,Female,26,Bachelors,17,56,44,49,33,9.0,5,73,Urban,HR Executive,83702,0 +71320,Male,57,Diploma,1,41,67,58,53,0.0,6,28,Urban,HR Executive,71223,0 +71321,Other,31,Masters,6,43,73,64,20,5.0,1,48,Rural,HR Executive,94016,0 +71322,Male,30,PhD,9,13,0,72,55,7.0,4,13,Semi-Urban,ML Engineer,23331,0 +71323,Male,23,High School,18,80,1,51,36,5.0,5,3,Semi-Urban,HR Executive,66437,0 +71324,Female,31,Bachelors,6,32,20,5,36,5.0,6,39,Urban,Data Analyst,79891,0 +71325,Female,54,Bachelors,7,13,8,60,69,0.0,1,84,Semi-Urban,HR Executive,104849,0 +71326,Male,40,High School,3,64,13,46,9,3.0,3,78,Urban,Data Analyst,67378,0 +71327,Female,36,Diploma,19,91,51,6,76,7.0,2,44,Semi-Urban,HR Executive,22440,0 +71328,Female,28,Bachelors,4,19,51,29,6,0.0,5,82,Urban,Manager,49448,0 +71329,Female,32,Bachelors,16,91,69,80,49,2.0,6,18,Semi-Urban,HR Executive,105642,1 +71330,Male,35,Bachelors,16,17,85,13,30,9.0,6,87,Urban,Software Engineer,127716,0 +71331,Female,56,Masters,18,74,1,76,4,5.0,4,30,Urban,Data Analyst,125291,0 +71332,Male,49,High School,0,86,82,68,44,7.0,7,40,Semi-Urban,Software Engineer,99721,1 +71333,Male,58,Diploma,11,58,81,1,55,2.0,4,51,Urban,Data Analyst,140384,0 +71334,Male,40,Masters,11,8,28,83,31,2.0,2,85,Semi-Urban,Manager,22365,0 +71335,Male,51,Diploma,8,17,4,6,90,7.0,3,17,Rural,Software Engineer,121109,0 +71336,Male,37,Bachelors,0,17,0,58,29,3.0,4,0,Rural,Manager,145526,0 +71337,Male,57,Bachelors,15,12,67,15,22,0.0,2,29,Rural,Software Engineer,115095,0 +71338,Male,22,High School,5,21,72,62,53,2.0,3,26,Rural,ML Engineer,28383,0 +71339,Male,34,High School,1,92,34,2,69,6.0,0,94,Urban,Data Analyst,88674,0 +71340,Male,27,Bachelors,7,91,52,78,36,3.0,6,63,Semi-Urban,Software Engineer,147630,1 +71341,Male,33,High School,19,33,92,73,39,4.0,4,67,Urban,HR Executive,117771,1 +71342,Male,25,Diploma,11,44,39,49,27,0.0,0,11,Semi-Urban,Manager,45217,0 +71343,Male,45,Bachelors,15,59,25,69,77,7.0,5,27,Rural,HR Executive,138475,0 +71344,Male,57,Masters,9,51,86,1,61,4.0,2,23,Urban,Software Engineer,70920,0 +71345,Female,22,High School,11,53,75,51,86,5.0,1,32,Urban,Data Analyst,126562,0 +71346,Female,45,High School,11,99,93,38,9,4.0,3,55,Urban,Data Analyst,141277,1 +71347,Male,21,PhD,12,97,72,61,61,0.0,6,33,Urban,ML Engineer,33207,1 +71348,Other,56,Diploma,18,90,88,0,29,9.0,4,80,Urban,HR Executive,142687,1 +71349,Female,25,Masters,18,62,43,62,36,8.0,5,71,Urban,Data Analyst,53337,0 +71350,Male,33,Bachelors,10,70,24,23,4,3.0,2,46,Semi-Urban,ML Engineer,147256,0 +71351,Female,58,Diploma,10,55,26,40,9,1.0,7,40,Semi-Urban,Data Analyst,73113,0 +71352,Female,28,Bachelors,10,27,65,4,1,6.0,4,22,Rural,Data Analyst,92865,0 +71353,Male,39,Diploma,14,61,25,48,18,4.0,0,45,Urban,HR Executive,83202,0 +71354,Female,56,Masters,1,81,36,74,62,4.0,0,93,Urban,Software Engineer,76631,1 +71355,Male,58,High School,8,98,5,46,80,1.0,3,28,Semi-Urban,Software Engineer,145365,0 +71356,Female,26,High School,1,35,3,89,2,0.0,5,84,Semi-Urban,HR Executive,63835,0 +71357,Male,24,Bachelors,4,1,57,40,49,6.0,4,1,Urban,Data Analyst,42003,0 +71358,Female,30,PhD,15,15,45,34,10,5.0,4,33,Urban,Manager,147870,0 +71359,Male,47,Diploma,0,17,89,12,92,5.0,2,91,Urban,HR Executive,68901,0 +71360,Male,44,Masters,3,14,37,69,97,4.0,0,22,Semi-Urban,Data Analyst,142485,0 +71361,Female,52,PhD,8,73,97,72,74,7.0,2,37,Urban,Data Analyst,50236,1 +71362,Male,55,PhD,16,56,70,80,85,2.0,1,23,Urban,HR Executive,139466,0 +71363,Female,23,Diploma,6,38,80,49,33,7.0,0,96,Urban,ML Engineer,30574,1 +71364,Male,30,Diploma,12,63,43,33,85,0.0,0,6,Urban,ML Engineer,129166,0 +71365,Female,35,High School,19,12,15,24,51,2.0,1,34,Semi-Urban,Software Engineer,54465,0 +71366,Male,27,Masters,11,34,67,41,69,9.0,3,67,Semi-Urban,Software Engineer,40506,0 +71367,Male,37,Bachelors,8,25,88,9,85,3.0,3,19,Urban,Manager,30345,0 +71368,Female,22,Bachelors,4,72,46,35,19,4.0,4,54,Urban,HR Executive,114778,0 +71369,Male,32,Diploma,9,37,31,1,61,4.0,1,57,Semi-Urban,ML Engineer,145369,0 +71370,Male,28,Bachelors,16,11,25,87,67,7.0,1,35,Semi-Urban,HR Executive,55964,0 +71371,Male,23,Bachelors,2,68,68,65,32,0.0,7,14,Semi-Urban,HR Executive,40302,0 +71372,Male,47,Diploma,12,94,8,86,79,4.0,7,52,Rural,HR Executive,113004,1 +71373,Female,30,Bachelors,3,82,31,56,18,0.0,6,31,Urban,Manager,61634,0 +71374,Female,22,Diploma,15,18,19,64,85,0.0,3,92,Urban,ML Engineer,119147,0 +71375,Male,31,Diploma,19,60,5,49,11,7.0,5,11,Semi-Urban,Manager,144573,0 +71376,Male,35,Bachelors,14,78,88,92,7,0.0,7,20,Urban,Data Analyst,126693,1 +71377,Male,26,High School,9,49,58,80,7,5.0,1,41,Semi-Urban,HR Executive,115920,0 +71378,Female,28,Masters,3,47,2,29,96,5.0,2,98,Urban,ML Engineer,131820,0 +71379,Male,39,Masters,19,35,11,92,10,1.0,0,0,Urban,HR Executive,64295,0 +71380,Male,34,Bachelors,9,51,16,51,86,4.0,3,4,Urban,ML Engineer,39933,0 +71381,Male,34,Diploma,9,98,66,19,8,7.0,7,12,Urban,Manager,29242,0 +71382,Female,38,Bachelors,1,20,5,70,68,4.0,2,65,Semi-Urban,HR Executive,108969,0 +71383,Female,49,Bachelors,14,25,9,40,55,4.0,0,89,Urban,ML Engineer,146766,0 +71384,Male,35,Bachelors,16,31,34,64,10,7.0,5,37,Urban,Software Engineer,144847,0 +71385,Male,47,Masters,3,73,75,63,34,2.0,4,55,Semi-Urban,ML Engineer,29097,1 +71386,Male,56,Bachelors,18,73,12,28,4,6.0,7,83,Semi-Urban,ML Engineer,70744,0 +71387,Male,35,Bachelors,19,29,63,25,33,3.0,2,84,Semi-Urban,Software Engineer,115290,0 +71388,Male,42,Masters,4,45,29,67,77,8.0,2,94,Rural,Manager,65633,1 +71389,Male,41,Bachelors,3,13,73,5,86,6.0,2,85,Urban,ML Engineer,132204,0 +71390,Male,35,Bachelors,16,47,26,41,81,3.0,6,63,Semi-Urban,Manager,83237,0 +71391,Female,50,Masters,11,65,77,56,36,3.0,6,76,Urban,HR Executive,101450,1 +71392,Female,27,Bachelors,1,82,51,54,9,5.0,3,76,Urban,Manager,50068,1 +71393,Male,21,Bachelors,0,11,29,58,45,2.0,6,82,Rural,ML Engineer,62444,0 +71394,Male,47,Diploma,6,76,1,6,0,3.0,3,44,Rural,ML Engineer,37000,0 +71395,Male,51,Bachelors,16,97,42,49,46,2.0,2,17,Rural,Software Engineer,145738,0 +71396,Male,28,Masters,17,17,32,55,33,6.0,2,17,Rural,Manager,114209,0 +71397,Female,25,PhD,2,32,3,42,38,8.0,1,16,Semi-Urban,Software Engineer,128316,0 +71398,Female,24,Diploma,9,20,33,46,41,9.0,6,56,Semi-Urban,Manager,37416,0 +71399,Male,28,Bachelors,12,15,50,87,50,2.0,7,15,Urban,HR Executive,95091,0 +71400,Male,42,Diploma,2,27,99,83,96,1.0,3,86,Semi-Urban,HR Executive,37675,1 +71401,Male,33,PhD,7,23,72,63,78,0.0,0,52,Rural,Software Engineer,119946,0 +71402,Male,21,Masters,11,45,53,47,94,3.0,0,95,Semi-Urban,Data Analyst,82033,1 +71403,Female,58,Bachelors,6,42,40,0,17,0.0,5,11,Urban,Manager,149843,0 +71404,Male,37,PhD,7,77,48,1,69,9.0,6,50,Semi-Urban,HR Executive,48905,0 +71405,Female,35,PhD,16,20,8,74,61,8.0,7,33,Semi-Urban,HR Executive,124801,0 +71406,Male,59,PhD,4,99,58,14,58,6.0,7,59,Urban,Manager,44126,0 +71407,Female,49,Bachelors,19,50,50,26,33,6.0,5,54,Rural,Software Engineer,34807,0 +71408,Female,55,Bachelors,19,31,3,37,61,3.0,3,39,Rural,Data Analyst,60327,0 +71409,Male,42,Masters,6,46,50,68,20,3.0,7,10,Urban,Manager,130020,0 +71410,Male,55,Diploma,16,51,28,8,84,3.0,2,98,Urban,ML Engineer,117674,0 +71411,Female,43,PhD,10,80,50,39,97,5.0,3,31,Semi-Urban,Software Engineer,90597,0 +71412,Male,57,Diploma,17,62,9,82,29,9.0,6,12,Urban,Software Engineer,50670,0 +71413,Female,33,Diploma,11,3,82,19,91,7.0,0,11,Semi-Urban,HR Executive,38510,0 +71414,Male,43,Bachelors,10,78,35,65,81,8.0,6,93,Urban,Manager,101197,1 +71415,Female,35,High School,5,80,83,43,89,1.0,4,43,Urban,Software Engineer,32635,1 +71416,Male,41,Bachelors,18,79,5,8,31,3.0,5,34,Rural,Software Engineer,46793,0 +71417,Male,23,Masters,19,98,52,59,95,7.0,0,49,Semi-Urban,Data Analyst,32685,1 +71418,Male,25,Masters,17,73,57,41,43,1.0,2,85,Urban,ML Engineer,113189,1 +71419,Male,35,Diploma,2,35,0,92,4,8.0,0,26,Urban,ML Engineer,74795,0 +71420,Female,52,Bachelors,19,27,87,14,53,8.0,6,62,Rural,Software Engineer,28893,0 +71421,Female,53,Masters,14,69,44,92,50,7.0,3,66,Rural,Data Analyst,107376,1 +71422,Female,22,PhD,7,97,67,93,98,5.0,3,89,Urban,Data Analyst,148303,1 +71423,Male,37,Masters,11,4,76,46,61,8.0,2,47,Rural,ML Engineer,136682,0 +71424,Female,34,Bachelors,10,40,5,6,45,9.0,5,42,Rural,Software Engineer,79535,0 +71425,Male,59,Bachelors,3,22,58,47,94,9.0,5,80,Urban,Data Analyst,143730,0 +71426,Male,36,PhD,1,99,11,52,39,3.0,3,94,Semi-Urban,ML Engineer,75816,1 +71427,Male,38,High School,16,95,97,71,66,0.0,4,79,Semi-Urban,Manager,88042,1 +71428,Male,23,Masters,10,27,1,59,39,0.0,0,53,Urban,Manager,127142,0 +71429,Female,25,Masters,10,97,93,11,8,7.0,2,36,Urban,ML Engineer,20929,0 +71430,Female,35,Diploma,6,75,72,48,58,9.0,4,67,Rural,ML Engineer,94196,1 +71431,Male,48,Masters,18,84,58,15,29,3.0,1,5,Semi-Urban,Manager,82991,0 +71432,Male,22,Bachelors,19,37,25,18,5,9.0,4,33,Urban,Data Analyst,139339,0 +71433,Male,50,High School,3,79,67,18,54,2.0,4,88,Urban,HR Executive,90502,1 +71434,Male,29,Masters,19,99,58,67,19,0.0,7,31,Semi-Urban,HR Executive,47417,1 +71435,Male,35,Diploma,11,57,32,76,4,5.0,7,98,Urban,ML Engineer,21861,1 +71436,Female,31,Masters,12,21,50,43,92,1.0,4,55,Urban,Data Analyst,34785,0 +71437,Female,35,Bachelors,2,40,19,43,35,3.0,4,21,Semi-Urban,ML Engineer,73130,0 +71438,Male,52,Diploma,19,41,82,34,17,1.0,5,3,Urban,HR Executive,63936,0 +71439,Female,27,Masters,18,50,36,35,77,9.0,5,47,Urban,HR Executive,142805,0 +71440,Female,24,Diploma,6,67,47,90,46,1.0,4,34,Urban,Data Analyst,100720,0 +71441,Male,47,Masters,10,53,35,84,60,1.0,3,18,Rural,Manager,33456,0 +71442,Male,51,Diploma,19,40,13,3,59,9.0,4,38,Urban,Software Engineer,31476,0 +71443,Male,52,Bachelors,10,75,42,69,8,4.0,5,87,Rural,Data Analyst,79102,1 +71444,Female,58,Diploma,14,19,14,7,77,0.0,5,18,Urban,Software Engineer,120560,0 +71445,Female,42,High School,3,57,92,4,70,4.0,3,74,Rural,HR Executive,49051,0 +71446,Female,51,Masters,9,55,17,84,53,2.0,4,24,Urban,ML Engineer,36962,0 +71447,Female,31,Bachelors,7,72,57,58,20,6.0,5,62,Rural,Software Engineer,64316,1 +71448,Female,35,Masters,3,91,54,98,37,6.0,2,83,Semi-Urban,Manager,90600,1 +71449,Female,49,Bachelors,2,30,45,49,30,2.0,3,55,Semi-Urban,ML Engineer,133262,0 +71450,Female,32,High School,18,75,69,40,57,4.0,4,12,Rural,Software Engineer,110544,0 +71451,Male,56,Diploma,7,13,13,94,81,0.0,5,40,Semi-Urban,Software Engineer,57524,0 +71452,Female,28,Bachelors,7,37,98,58,2,7.0,6,72,Urban,ML Engineer,104740,1 +71453,Other,41,Bachelors,16,90,99,19,19,9.0,4,6,Urban,ML Engineer,123009,0 +71454,Female,23,Diploma,6,76,46,31,53,2.0,5,83,Semi-Urban,HR Executive,115244,0 +71455,Female,59,Masters,10,86,24,14,0,3.0,0,92,Urban,Software Engineer,94995,0 +71456,Female,39,PhD,6,49,28,65,34,9.0,1,7,Urban,Software Engineer,26058,0 +71457,Male,21,Masters,10,4,95,80,11,6.0,5,47,Rural,ML Engineer,45469,0 +71458,Male,43,Masters,5,66,41,52,77,9.0,4,8,Urban,Manager,95521,0 +71459,Male,39,Bachelors,2,17,18,54,18,3.0,0,91,Rural,HR Executive,146798,0 +71460,Male,47,Masters,1,24,26,41,3,4.0,3,85,Urban,Software Engineer,77831,0 +71461,Male,36,Masters,12,73,78,3,4,0.0,1,42,Semi-Urban,Manager,147882,0 +71462,Female,24,High School,5,21,48,63,26,8.0,6,2,Rural,Software Engineer,139971,0 +71463,Female,32,Bachelors,4,62,39,16,54,6.0,6,54,Urban,HR Executive,83268,0 +71464,Male,49,Bachelors,9,88,29,34,9,7.0,3,89,Urban,ML Engineer,101144,1 +71465,Male,34,Diploma,7,62,97,66,55,2.0,7,92,Rural,Manager,103455,1 +71466,Female,24,High School,17,30,79,57,82,4.0,7,44,Semi-Urban,Data Analyst,110970,0 +71467,Male,26,Bachelors,7,13,25,18,30,0.0,3,89,Urban,Manager,40035,0 +71468,Male,42,Masters,13,18,93,70,57,7.0,1,39,Semi-Urban,ML Engineer,140854,0 +71469,Male,55,High School,13,76,1,75,0,3.0,2,59,Urban,Manager,103180,0 +71470,Male,51,PhD,5,63,20,20,85,7.0,7,13,Urban,ML Engineer,130053,0 +71471,Male,58,High School,1,61,4,28,16,1.0,1,37,Urban,Data Analyst,22030,0 +71472,Female,53,Bachelors,9,22,5,43,91,8.0,1,35,Urban,HR Executive,69107,0 +71473,Female,39,Diploma,19,21,33,14,28,5.0,1,17,Rural,Data Analyst,41541,0 +71474,Male,52,High School,12,18,23,68,66,1.0,5,37,Semi-Urban,Data Analyst,40518,0 +71475,Male,43,Masters,14,38,57,35,27,0.0,3,14,Semi-Urban,Manager,44133,0 +71476,Female,56,Bachelors,16,8,17,69,65,8.0,3,17,Rural,HR Executive,129600,0 +71477,Male,49,Bachelors,12,78,27,74,50,0.0,2,92,Urban,ML Engineer,84366,1 +71478,Male,26,Diploma,3,0,16,97,48,7.0,4,6,Urban,ML Engineer,88476,0 +71479,Male,50,Diploma,8,86,76,33,7,5.0,7,41,Urban,Software Engineer,80465,1 +71480,Male,59,Masters,19,28,70,49,25,2.0,7,69,Urban,HR Executive,112560,0 +71481,Female,46,Bachelors,11,99,84,53,56,9.0,7,35,Urban,HR Executive,109047,1 +71482,Female,26,High School,3,57,4,10,53,7.0,4,4,Semi-Urban,ML Engineer,24724,0 +71483,Male,26,High School,17,2,37,88,94,5.0,1,78,Semi-Urban,Manager,149314,0 +71484,Male,57,Bachelors,18,2,90,77,72,2.0,0,61,Urban,Data Analyst,72359,0 +71485,Male,41,Bachelors,9,38,92,15,31,1.0,7,41,Urban,Software Engineer,144380,0 +71486,Female,39,Bachelors,10,0,90,16,5,5.0,5,12,Urban,Manager,100943,0 +71487,Male,30,Bachelors,17,38,5,75,68,9.0,5,63,Semi-Urban,ML Engineer,50626,0 +71488,Male,48,Diploma,3,34,27,33,56,1.0,7,15,Urban,Data Analyst,146001,0 +71489,Female,55,Masters,8,63,49,66,26,6.0,4,62,Rural,Manager,86005,0 +71490,Male,44,Diploma,16,63,2,52,63,4.0,1,35,Urban,ML Engineer,138695,0 +71491,Male,32,Bachelors,8,49,11,55,36,8.0,6,23,Urban,HR Executive,85809,0 +71492,Female,46,Bachelors,8,53,24,77,53,6.0,6,80,Rural,Software Engineer,63008,0 +71493,Male,32,High School,0,14,26,45,55,6.0,7,82,Urban,Data Analyst,136790,0 +71494,Male,24,High School,15,63,94,38,3,1.0,6,49,Semi-Urban,Software Engineer,58481,1 +71495,Male,52,High School,2,5,83,28,42,0.0,7,74,Urban,Manager,97302,0 +71496,Other,47,Diploma,18,69,19,53,18,7.0,5,77,Urban,Manager,93025,0 +71497,Other,54,Masters,11,99,23,3,92,4.0,1,96,Urban,Manager,75799,0 +71498,Female,33,Bachelors,18,4,38,7,81,8.0,2,54,Semi-Urban,Software Engineer,116967,0 +71499,Male,29,High School,13,97,42,96,73,5.0,1,1,Urban,HR Executive,141431,1 +71500,Female,57,Bachelors,7,47,59,61,89,0.0,1,11,Urban,Software Engineer,79187,0 +71501,Male,25,Bachelors,12,63,28,16,9,3.0,6,65,Urban,Software Engineer,131134,0 +71502,Female,42,Diploma,4,28,96,9,55,8.0,4,7,Semi-Urban,HR Executive,72634,0 +71503,Male,37,High School,19,14,25,26,19,0.0,3,88,Urban,HR Executive,110133,0 +71504,Female,49,High School,11,87,76,10,51,6.0,6,46,Urban,Data Analyst,124192,0 +71505,Male,33,High School,8,7,28,19,70,6.0,6,5,Semi-Urban,ML Engineer,137303,0 +71506,Female,34,Diploma,9,53,40,28,92,2.0,6,5,Rural,ML Engineer,127100,0 +71507,Male,21,Masters,8,6,11,48,59,3.0,3,12,Urban,Data Analyst,22028,0 +71508,Male,24,Bachelors,19,46,12,98,70,4.0,6,89,Semi-Urban,ML Engineer,84210,1 +71509,Female,46,Bachelors,13,33,16,64,55,4.0,4,66,Urban,HR Executive,89078,0 +71510,Male,59,Bachelors,13,76,33,29,13,3.0,2,54,Urban,HR Executive,48934,0 +71511,Female,41,Diploma,13,63,3,4,99,9.0,0,0,Urban,HR Executive,44595,0 +71512,Female,26,Masters,17,3,40,51,18,1.0,2,41,Urban,Data Analyst,110232,0 +71513,Male,31,Masters,4,84,96,1,74,6.0,2,90,Semi-Urban,Data Analyst,37011,1 +71514,Male,41,Bachelors,8,86,11,20,86,4.0,4,49,Rural,ML Engineer,53898,0 +71515,Female,44,Diploma,15,47,40,9,17,1.0,0,26,Urban,Manager,40970,0 +71516,Female,36,Diploma,17,3,94,81,25,5.0,2,16,Semi-Urban,ML Engineer,104004,0 +71517,Other,34,Bachelors,8,55,33,36,99,6.0,4,37,Rural,Manager,20278,0 +71518,Female,29,High School,13,40,83,52,68,1.0,6,76,Urban,Data Analyst,102413,1 +71519,Male,41,PhD,15,33,2,29,17,2.0,7,52,Urban,Data Analyst,126331,0 +71520,Male,40,Bachelors,18,47,4,63,28,2.0,3,88,Rural,Manager,53273,0 +71521,Male,46,Bachelors,4,78,73,75,72,6.0,6,56,Urban,Manager,105350,1 +71522,Male,44,Bachelors,19,87,25,49,2,6.0,7,45,Urban,HR Executive,75621,0 +71523,Male,53,Masters,18,81,71,48,1,2.0,0,45,Urban,Data Analyst,33038,1 +71524,Female,24,Bachelors,6,42,84,76,44,9.0,3,53,Rural,HR Executive,46777,1 +71525,Male,55,Masters,14,72,48,27,32,9.0,5,32,Urban,ML Engineer,81969,0 +71526,Male,32,Masters,9,91,18,3,12,6.0,2,2,Urban,ML Engineer,140707,0 +71527,Female,57,Masters,14,90,87,42,80,9.0,3,83,Semi-Urban,Software Engineer,134233,1 +71528,Male,57,Bachelors,2,51,45,41,76,4.0,6,71,Urban,HR Executive,42062,0 +71529,Male,33,Diploma,17,51,91,29,20,0.0,5,7,Urban,HR Executive,69086,0 +71530,Male,40,High School,8,90,94,20,83,9.0,7,9,Urban,Manager,106864,0 +71531,Female,38,Bachelors,18,39,48,1,38,0.0,6,92,Urban,Manager,64111,0 +71532,Female,23,Masters,19,95,42,86,95,9.0,2,90,Semi-Urban,HR Executive,86933,1 +71533,Male,41,PhD,1,69,2,3,23,0.0,6,11,Semi-Urban,Manager,136427,0 +71534,Male,41,Bachelors,16,46,21,7,2,9.0,7,55,Rural,Software Engineer,79952,0 +71535,Male,30,Masters,0,79,52,30,55,2.0,7,55,Semi-Urban,ML Engineer,66498,0 +71536,Male,40,Diploma,3,47,38,38,42,0.0,3,4,Urban,HR Executive,144785,0 +71537,Male,42,High School,1,7,0,98,35,5.0,2,13,Urban,Manager,144530,0 +71538,Male,30,Masters,0,6,78,29,57,8.0,5,71,Semi-Urban,ML Engineer,23984,0 +71539,Male,31,Bachelors,16,46,24,82,31,4.0,5,53,Urban,Data Analyst,130589,0 +71540,Female,53,Diploma,10,77,76,0,30,2.0,4,75,Urban,Software Engineer,22683,0 +71541,Male,49,Bachelors,11,96,69,78,18,2.0,6,37,Rural,HR Executive,112624,1 +71542,Male,36,PhD,7,39,94,0,3,9.0,7,68,Urban,Manager,62892,0 +71543,Female,26,Diploma,17,26,60,78,25,1.0,4,95,Urban,Manager,71583,1 +71544,Male,47,High School,11,1,26,3,7,8.0,3,8,Semi-Urban,ML Engineer,103469,0 +71545,Female,46,Bachelors,3,44,13,81,20,0.0,0,16,Rural,Manager,87155,0 +71546,Female,56,High School,17,8,48,75,31,1.0,3,43,Rural,HR Executive,134953,0 +71547,Male,52,Bachelors,19,16,10,76,22,2.0,1,64,Urban,Software Engineer,78704,0 +71548,Male,42,Bachelors,6,44,72,35,27,2.0,4,48,Urban,Data Analyst,30632,0 +71549,Male,51,Masters,12,23,24,47,76,9.0,4,14,Urban,Data Analyst,106936,0 +71550,Male,32,Bachelors,0,5,13,69,18,3.0,4,44,Semi-Urban,Software Engineer,48149,0 +71551,Male,32,PhD,15,86,96,14,36,7.0,2,46,Semi-Urban,HR Executive,86792,1 +71552,Male,37,Diploma,10,42,73,90,50,0.0,0,34,Semi-Urban,Manager,108333,1 +71553,Female,55,Bachelors,17,42,23,93,96,2.0,4,43,Semi-Urban,ML Engineer,143464,0 +71554,Male,45,Bachelors,7,14,29,4,65,2.0,7,74,Urban,HR Executive,81579,0 +71555,Other,54,Diploma,18,26,38,53,39,7.0,2,60,Urban,Software Engineer,69564,0 +71556,Female,32,Bachelors,11,61,81,66,29,7.0,6,15,Semi-Urban,ML Engineer,149861,0 +71557,Male,54,Bachelors,19,51,28,2,74,2.0,2,22,Urban,ML Engineer,103855,0 +71558,Male,59,Diploma,3,33,70,90,47,2.0,5,28,Urban,Manager,30234,0 +71559,Female,59,Bachelors,8,35,7,70,26,1.0,7,43,Semi-Urban,Manager,123863,0 +71560,Male,37,Bachelors,14,99,22,76,65,5.0,7,51,Semi-Urban,HR Executive,88267,1 +71561,Female,55,High School,17,23,32,19,91,1.0,1,43,Urban,Manager,118130,0 +71562,Male,31,Bachelors,12,61,29,59,73,2.0,0,2,Urban,HR Executive,45658,0 +71563,Female,44,Diploma,13,76,74,36,73,0.0,2,44,Semi-Urban,Data Analyst,119241,0 +71564,Female,45,Bachelors,15,89,68,92,64,1.0,6,96,Semi-Urban,Data Analyst,107142,1 +71565,Male,52,Masters,16,23,3,74,78,7.0,3,11,Rural,ML Engineer,86097,0 +71566,Female,35,Diploma,3,20,78,15,47,1.0,5,94,Rural,Manager,144614,0 +71567,Male,35,Diploma,8,13,78,4,19,1.0,5,43,Semi-Urban,ML Engineer,29293,0 +71568,Male,50,Diploma,6,20,80,58,81,1.0,4,21,Rural,Manager,59729,0 +71569,Female,44,Bachelors,19,17,39,55,70,5.0,5,70,Urban,Manager,23861,0 +71570,Female,41,Masters,5,77,58,49,35,6.0,4,20,Semi-Urban,ML Engineer,36618,0 +71571,Male,59,Bachelors,17,76,94,16,20,7.0,0,30,Urban,Software Engineer,39759,0 +71572,Female,31,Masters,19,13,9,22,94,8.0,0,98,Urban,Manager,88045,0 +71573,Male,36,High School,9,35,68,94,49,5.0,0,8,Urban,HR Executive,26300,0 +71574,Male,28,Bachelors,7,83,78,76,39,0.0,2,95,Urban,Data Analyst,77774,1 +71575,Male,26,Bachelors,3,51,70,96,15,3.0,5,73,Urban,Software Engineer,40103,1 +71576,Female,48,High School,12,73,85,58,69,3.0,5,2,Urban,Software Engineer,107104,0 +71577,Male,49,Diploma,5,82,14,61,89,8.0,4,59,Rural,Manager,132528,0 +71578,Male,43,Masters,5,58,84,15,22,8.0,6,45,Urban,HR Executive,134254,0 +71579,Other,52,Masters,3,86,26,83,6,5.0,7,79,Semi-Urban,Manager,102791,1 +71580,Male,54,PhD,19,58,15,70,42,1.0,1,7,Urban,Data Analyst,81791,0 +71581,Male,43,Masters,8,72,57,39,92,0.0,6,21,Urban,Data Analyst,47516,0 +71582,Female,54,Bachelors,1,75,90,2,30,5.0,3,39,Urban,Software Engineer,147094,0 +71583,Male,38,Bachelors,2,35,85,77,55,3.0,6,47,Urban,Software Engineer,135370,1 +71584,Male,55,Diploma,7,94,77,63,48,8.0,0,26,Urban,ML Engineer,33849,1 +71585,Female,28,Bachelors,13,6,52,51,46,5.0,6,0,Urban,Software Engineer,121753,0 +71586,Female,37,High School,16,45,14,51,81,8.0,5,43,Urban,ML Engineer,48008,0 +71587,Female,57,Diploma,0,82,86,65,21,0.0,3,16,Semi-Urban,Data Analyst,144970,1 +71588,Male,38,Diploma,5,90,56,22,13,1.0,7,51,Rural,ML Engineer,131617,0 +71589,Female,25,Masters,7,63,27,6,53,5.0,6,85,Rural,Data Analyst,113780,0 +71590,Female,40,Bachelors,9,31,87,26,70,3.0,3,38,Urban,Data Analyst,111316,0 +71591,Male,22,Bachelors,19,23,4,0,74,5.0,0,89,Urban,HR Executive,113418,0 +71592,Male,51,PhD,17,70,66,61,21,0.0,5,27,Semi-Urban,HR Executive,100735,0 +71593,Male,25,Diploma,9,84,18,95,75,4.0,7,57,Semi-Urban,Data Analyst,30656,1 +71594,Male,52,Bachelors,8,3,24,45,34,6.0,3,69,Urban,Manager,35221,0 +71595,Female,36,Bachelors,18,96,12,58,98,3.0,7,66,Urban,Software Engineer,123766,0 +71596,Female,52,Masters,1,75,88,99,9,7.0,7,44,Urban,Software Engineer,132193,1 +71597,Male,46,Bachelors,0,31,93,47,30,5.0,6,68,Urban,ML Engineer,36374,1 +71598,Male,55,Diploma,9,40,79,2,24,6.0,5,22,Semi-Urban,HR Executive,85532,0 +71599,Female,57,High School,3,77,36,79,93,3.0,3,47,Urban,ML Engineer,66843,0 +71600,Male,27,Diploma,15,98,71,78,51,6.0,4,79,Urban,HR Executive,37745,1 +71601,Male,29,PhD,16,37,9,54,62,2.0,2,21,Rural,Data Analyst,84536,0 +71602,Female,49,PhD,5,26,65,98,31,4.0,5,0,Urban,Data Analyst,113343,0 +71603,Other,29,High School,16,18,87,31,0,8.0,2,11,Urban,ML Engineer,53323,0 +71604,Male,37,Bachelors,17,51,14,87,32,0.0,6,97,Urban,ML Engineer,108999,1 +71605,Other,27,Masters,9,42,19,88,78,4.0,4,38,Urban,Software Engineer,79845,0 +71606,Male,59,Bachelors,12,82,56,43,74,5.0,6,76,Urban,ML Engineer,73766,1 +71607,Male,48,Bachelors,15,23,20,59,25,9.0,4,26,Urban,Manager,134514,0 +71608,Male,54,Bachelors,14,45,6,18,62,8.0,5,27,Urban,Manager,67904,0 +71609,Female,52,Bachelors,17,3,68,97,52,7.0,4,53,Urban,ML Engineer,40003,0 +71610,Female,29,Bachelors,18,93,98,72,57,6.0,2,7,Semi-Urban,HR Executive,61990,1 +71611,Male,25,Bachelors,19,24,33,91,92,6.0,0,34,Urban,ML Engineer,124029,0 +71612,Male,29,Masters,12,0,29,47,48,8.0,7,56,Rural,HR Executive,142699,0 +71613,Female,48,PhD,18,70,43,53,76,3.0,1,89,Urban,Software Engineer,110471,1 +71614,Female,58,Diploma,14,74,45,42,1,1.0,7,41,Urban,HR Executive,116042,0 +71615,Male,34,PhD,15,3,2,76,1,2.0,4,19,Urban,Manager,55042,0 +71616,Male,55,Diploma,9,43,11,95,34,9.0,1,44,Semi-Urban,Manager,109437,0 +71617,Other,26,Masters,5,32,69,93,90,7.0,0,17,Rural,Manager,64765,0 +71618,Male,38,High School,1,79,86,87,79,4.0,2,50,Urban,Software Engineer,71775,1 +71619,Male,50,Masters,14,71,83,82,8,6.0,1,40,Urban,Software Engineer,93957,1 +71620,Female,37,Bachelors,16,79,43,1,16,8.0,5,73,Semi-Urban,HR Executive,122744,0 +71621,Male,21,Bachelors,2,55,25,56,17,4.0,7,33,Urban,Data Analyst,127306,0 +71622,Male,46,Bachelors,1,58,9,33,65,4.0,1,79,Semi-Urban,HR Executive,58848,0 +71623,Male,46,Masters,10,28,84,21,34,7.0,2,97,Urban,Data Analyst,130073,0 +71624,Male,31,Bachelors,18,74,58,15,73,2.0,6,70,Rural,Manager,105723,0 +71625,Female,47,Bachelors,11,26,13,92,18,8.0,2,0,Urban,HR Executive,50871,0 +71626,Female,34,Diploma,7,99,95,95,55,5.0,5,7,Urban,HR Executive,118894,1 +71627,Male,21,Diploma,5,11,84,11,34,1.0,2,73,Urban,ML Engineer,78413,0 +71628,Female,52,Bachelors,1,5,36,5,25,2.0,0,82,Semi-Urban,ML Engineer,107145,0 +71629,Male,32,Bachelors,0,38,51,83,69,6.0,2,39,Urban,Software Engineer,81180,0 +71630,Female,59,PhD,13,27,68,77,92,1.0,2,2,Urban,Manager,54595,0 +71631,Male,57,High School,7,62,34,43,71,5.0,0,47,Urban,Manager,70542,0 +71632,Male,55,High School,6,39,53,43,73,2.0,3,27,Urban,Data Analyst,84091,0 +71633,Female,50,Masters,19,91,70,65,21,9.0,1,26,Urban,Manager,33155,1 +71634,Male,33,High School,1,59,87,17,59,0.0,1,95,Semi-Urban,Manager,67521,1 +71635,Male,52,Bachelors,0,44,95,91,5,1.0,4,72,Semi-Urban,Software Engineer,30252,1 +71636,Male,35,Diploma,16,64,31,14,72,0.0,7,86,Rural,Software Engineer,149305,0 +71637,Male,58,Masters,4,75,53,5,11,7.0,3,77,Urban,HR Executive,62295,0 +71638,Male,49,Bachelors,17,81,95,93,16,2.0,4,37,Urban,Software Engineer,142102,1 +71639,Male,54,Masters,11,66,35,13,85,1.0,3,59,Rural,HR Executive,138371,0 +71640,Female,50,PhD,19,75,32,76,75,9.0,6,80,Urban,HR Executive,85033,1 +71641,Female,23,Masters,9,1,89,57,31,8.0,2,56,Urban,Data Analyst,118334,0 +71642,Male,46,High School,1,74,81,57,23,4.0,7,40,Rural,ML Engineer,108188,1 +71643,Male,50,Bachelors,18,80,1,5,33,7.0,7,72,Urban,Data Analyst,92753,0 +71644,Male,45,High School,12,69,62,94,83,7.0,6,16,Rural,Data Analyst,24876,1 +71645,Male,24,Diploma,4,13,76,68,33,1.0,3,94,Urban,ML Engineer,122879,1 +71646,Male,47,Bachelors,10,23,98,69,23,3.0,7,87,Urban,Software Engineer,90180,1 +71647,Female,26,Bachelors,17,30,57,45,55,2.0,4,4,Urban,Software Engineer,124322,0 +71648,Male,38,PhD,4,62,66,93,32,8.0,1,20,Urban,Data Analyst,53820,1 +71649,Male,48,High School,7,18,98,95,58,5.0,1,98,Semi-Urban,HR Executive,113302,1 +71650,Male,31,High School,18,74,52,80,89,7.0,6,99,Semi-Urban,ML Engineer,53230,1 +71651,Female,36,Bachelors,5,84,86,32,14,2.0,0,77,Rural,HR Executive,23190,1 +71652,Female,56,Masters,8,4,59,45,68,2.0,5,69,Urban,Manager,122686,0 +71653,Other,51,PhD,16,58,41,31,12,7.0,1,63,Semi-Urban,ML Engineer,146793,0 +71654,Male,43,Bachelors,2,99,44,41,71,2.0,5,83,Urban,Software Engineer,65613,1 +71655,Male,36,High School,7,41,55,25,14,1.0,1,4,Semi-Urban,Software Engineer,55865,0 +71656,Male,49,High School,8,52,48,43,63,2.0,2,32,Urban,Manager,62663,0 +71657,Male,58,Diploma,18,70,56,96,76,3.0,4,94,Rural,Manager,103490,1 +71658,Female,30,Masters,15,58,87,5,68,3.0,6,4,Urban,ML Engineer,54981,0 +71659,Male,26,High School,2,58,44,57,51,2.0,4,80,Urban,ML Engineer,47955,1 +71660,Female,59,Diploma,11,82,80,95,12,7.0,1,56,Semi-Urban,Data Analyst,110901,1 +71661,Male,42,Masters,13,79,10,70,43,6.0,2,12,Urban,Data Analyst,128928,0 +71662,Female,23,Bachelors,2,50,62,58,77,6.0,1,66,Urban,HR Executive,58123,0 +71663,Female,54,Bachelors,9,33,45,70,50,3.0,4,80,Rural,HR Executive,65175,0 +71664,Female,36,Masters,13,28,11,47,91,4.0,4,70,Semi-Urban,Software Engineer,49888,0 +71665,Male,43,Bachelors,9,73,26,48,52,2.0,4,85,Rural,HR Executive,78182,0 +71666,Male,41,Bachelors,12,7,72,59,93,8.0,5,79,Rural,Software Engineer,48977,0 +71667,Female,53,Diploma,5,16,79,65,2,3.0,0,18,Rural,Software Engineer,69914,0 +71668,Male,52,Masters,8,24,38,72,96,5.0,0,62,Semi-Urban,ML Engineer,104632,0 +71669,Male,57,Masters,13,29,67,73,95,8.0,3,84,Rural,HR Executive,75930,1 +71670,Female,34,Bachelors,18,75,6,51,37,8.0,0,97,Urban,Manager,133714,0 +71671,Male,51,Masters,18,32,39,32,72,2.0,1,76,Urban,Software Engineer,42531,0 +71672,Male,54,Bachelors,1,3,5,88,32,8.0,1,68,Urban,Software Engineer,55486,0 +71673,Female,40,Bachelors,18,37,78,84,14,8.0,3,52,Urban,Data Analyst,24341,1 +71674,Male,59,Diploma,4,4,49,6,81,0.0,5,58,Urban,ML Engineer,71060,0 +71675,Male,52,Diploma,4,40,10,52,84,5.0,5,87,Urban,ML Engineer,143246,0 +71676,Male,41,High School,10,31,84,26,67,0.0,4,59,Urban,Manager,32328,0 +71677,Female,27,Masters,4,93,11,34,65,0.0,7,63,Urban,Software Engineer,81900,0 +71678,Male,43,Bachelors,13,34,81,41,22,2.0,2,25,Semi-Urban,Software Engineer,110101,0 +71679,Male,59,Bachelors,10,15,83,68,81,4.0,4,86,Urban,ML Engineer,31072,1 +71680,Male,26,Bachelors,6,35,15,58,86,0.0,1,69,Urban,HR Executive,72321,0 +71681,Male,48,Masters,9,67,83,0,12,7.0,0,22,Rural,ML Engineer,29407,0 +71682,Male,49,Diploma,18,19,67,81,85,0.0,5,16,Urban,ML Engineer,48210,0 +71683,Male,52,Masters,14,14,30,74,4,5.0,1,23,Semi-Urban,HR Executive,105755,0 +71684,Male,27,Bachelors,13,54,42,79,96,3.0,0,81,Semi-Urban,Manager,34859,1 +71685,Female,58,High School,14,43,37,76,42,4.0,4,62,Rural,ML Engineer,143380,0 +71686,Male,45,High School,16,69,18,56,13,9.0,6,67,Rural,ML Engineer,41563,0 +71687,Male,37,Bachelors,12,3,75,3,93,1.0,4,0,Urban,Manager,99706,0 +71688,Male,38,High School,18,21,53,94,15,2.0,7,34,Semi-Urban,HR Executive,149843,0 +71689,Male,39,Bachelors,18,94,59,16,6,7.0,0,70,Urban,HR Executive,103811,1 +71690,Other,58,Bachelors,18,11,53,79,29,5.0,1,32,Urban,ML Engineer,69267,0 +71691,Other,32,Masters,19,32,45,47,46,5.0,4,54,Semi-Urban,Data Analyst,107127,0 +71692,Female,26,Bachelors,6,42,39,56,41,5.0,3,4,Urban,Data Analyst,55828,0 +71693,Male,57,Bachelors,2,51,28,55,75,8.0,2,58,Urban,ML Engineer,87009,0 +71694,Female,57,Bachelors,0,73,66,68,64,0.0,0,16,Rural,Software Engineer,70881,0 +71695,Female,49,Bachelors,18,23,30,35,5,0.0,3,51,Urban,HR Executive,100259,0 +71696,Male,21,High School,6,34,81,35,45,4.0,7,39,Rural,HR Executive,53477,0 +71697,Male,54,Masters,15,49,17,31,72,8.0,6,76,Semi-Urban,Manager,87919,0 +71698,Other,23,Diploma,11,68,47,59,52,5.0,3,96,Rural,Manager,44303,1 +71699,Male,31,Masters,12,50,50,30,64,9.0,0,86,Urban,Data Analyst,91909,0 +71700,Female,31,Diploma,13,49,29,45,51,0.0,4,2,Urban,HR Executive,51732,0 +71701,Female,46,Masters,14,44,83,24,62,5.0,4,36,Urban,Data Analyst,36751,0 +71702,Male,26,Masters,9,51,44,29,28,0.0,1,4,Rural,Manager,104457,0 +71703,Male,41,Diploma,3,74,24,60,89,2.0,2,38,Semi-Urban,ML Engineer,95013,0 +71704,Male,47,Masters,3,20,64,18,99,0.0,6,37,Semi-Urban,ML Engineer,149767,0 +71705,Male,26,High School,0,92,55,79,26,1.0,3,67,Semi-Urban,ML Engineer,45942,1 +71706,Male,51,Bachelors,10,87,86,53,6,2.0,1,92,Urban,HR Executive,134753,1 +71707,Female,30,Bachelors,0,64,1,44,39,9.0,5,96,Semi-Urban,ML Engineer,87695,0 +71708,Female,58,Masters,7,92,68,98,10,6.0,2,64,Urban,Software Engineer,100748,1 +71709,Other,46,High School,10,63,67,90,37,5.0,3,21,Rural,ML Engineer,101708,1 +71710,Male,28,PhD,8,61,51,60,74,6.0,5,83,Semi-Urban,HR Executive,76807,1 +71711,Male,47,Bachelors,13,56,99,49,9,0.0,4,49,Urban,HR Executive,61561,1 +71712,Male,35,Bachelors,7,4,20,27,97,2.0,0,64,Urban,ML Engineer,141007,0 +71713,Male,39,Diploma,1,43,61,65,33,0.0,1,61,Semi-Urban,Data Analyst,117968,0 +71714,Male,44,Bachelors,18,65,96,65,66,3.0,6,33,Semi-Urban,Software Engineer,81054,1 +71715,Male,45,Bachelors,6,57,6,63,21,1.0,5,20,Urban,Manager,101370,0 +71716,Female,54,Bachelors,17,90,45,33,7,0.0,4,16,Rural,Data Analyst,86236,0 +71717,Male,24,Bachelors,12,87,33,43,24,0.0,4,36,Urban,Data Analyst,36127,0 +71718,Female,25,Bachelors,12,37,85,20,73,2.0,6,68,Rural,HR Executive,26307,0 +71719,Female,45,Masters,2,65,8,24,40,5.0,4,76,Urban,Manager,49436,0 +71720,Male,50,High School,10,34,0,43,20,7.0,5,21,Urban,ML Engineer,94233,0 +71721,Female,30,Diploma,9,95,46,39,18,5.0,1,66,Urban,ML Engineer,101598,1 +71722,Male,36,Diploma,6,17,49,97,33,6.0,0,40,Urban,Manager,54813,0 +71723,Female,25,High School,3,39,92,17,90,0.0,5,31,Rural,ML Engineer,125331,0 +71724,Female,41,Diploma,6,6,68,26,13,2.0,6,3,Urban,Data Analyst,128920,0 +71725,Male,21,Bachelors,0,89,51,53,91,2.0,4,37,Urban,ML Engineer,134759,0 +71726,Female,33,Diploma,14,35,59,38,25,2.0,5,93,Urban,Data Analyst,96829,0 +71727,Male,48,Masters,8,2,66,94,25,6.0,5,10,Semi-Urban,Manager,119169,0 +71728,Other,56,Bachelors,13,66,59,0,15,1.0,3,24,Urban,Manager,101270,0 +71729,Male,30,Bachelors,0,42,75,86,38,1.0,1,31,Semi-Urban,ML Engineer,32501,0 +71730,Male,53,Diploma,3,79,6,45,27,4.0,6,78,Urban,HR Executive,85788,0 +71731,Male,35,Masters,6,42,45,71,3,2.0,3,85,Urban,ML Engineer,32530,1 +71732,Female,53,Diploma,19,89,8,51,72,7.0,4,78,Urban,ML Engineer,100252,0 +71733,Male,52,Diploma,18,69,89,33,62,6.0,5,5,Rural,Manager,41406,0 +71734,Other,35,Masters,15,4,24,68,35,0.0,0,42,Rural,Software Engineer,55872,0 +71735,Female,30,Bachelors,0,2,49,3,69,3.0,5,86,Semi-Urban,Software Engineer,123671,0 +71736,Male,37,High School,18,65,13,56,67,1.0,4,32,Urban,Software Engineer,53520,0 +71737,Female,49,PhD,17,3,78,77,2,7.0,1,59,Rural,HR Executive,124909,0 +71738,Male,48,Masters,15,94,62,95,26,3.0,5,99,Urban,HR Executive,133754,1 +71739,Male,55,PhD,17,4,29,54,36,7.0,3,3,Urban,Manager,33714,0 +71740,Male,33,Diploma,5,90,96,20,94,8.0,1,14,Urban,ML Engineer,142320,0 +71741,Male,32,Bachelors,8,48,43,10,40,5.0,3,85,Urban,ML Engineer,145498,0 +71742,Male,28,Diploma,16,80,24,80,77,1.0,0,21,Rural,ML Engineer,27300,0 +71743,Male,31,Bachelors,14,36,32,30,59,1.0,2,15,Semi-Urban,HR Executive,42188,0 +71744,Male,22,Bachelors,10,80,26,71,68,2.0,5,58,Semi-Urban,Data Analyst,101515,1 +71745,Male,45,Diploma,12,99,25,77,79,5.0,1,50,Rural,HR Executive,26442,1 +71746,Male,37,Bachelors,18,96,13,55,32,8.0,7,24,Urban,HR Executive,129924,0 +71747,Female,36,Bachelors,3,13,11,94,59,1.0,1,50,Urban,ML Engineer,107672,0 +71748,Male,51,Bachelors,15,6,94,75,76,8.0,3,58,Urban,ML Engineer,28832,0 +71749,Female,56,Masters,15,46,60,74,81,2.0,2,43,Urban,HR Executive,27584,0 +71750,Male,42,Diploma,14,25,54,35,90,2.0,2,53,Urban,HR Executive,26946,0 +71751,Female,48,Bachelors,13,3,30,79,10,5.0,5,53,Semi-Urban,HR Executive,104106,0 +71752,Male,38,Bachelors,6,48,12,8,80,4.0,7,71,Semi-Urban,HR Executive,77949,0 +71753,Female,36,PhD,7,25,65,82,46,1.0,7,79,Semi-Urban,HR Executive,86230,1 +71754,Male,35,High School,14,92,52,72,81,9.0,2,13,Urban,ML Engineer,41630,0 +71755,Male,56,High School,19,40,81,80,34,5.0,6,46,Urban,Software Engineer,79850,1 +71756,Female,26,High School,4,56,3,40,86,4.0,7,92,Urban,Software Engineer,121398,0 +71757,Male,57,Bachelors,17,28,55,98,59,1.0,2,5,Rural,Manager,74485,0 +71758,Male,36,Bachelors,0,71,30,2,43,2.0,1,72,Rural,Software Engineer,91215,0 +71759,Other,36,Bachelors,5,40,8,17,9,6.0,2,91,Urban,Manager,80366,0 +71760,Male,44,Diploma,10,36,48,78,33,7.0,0,66,Urban,Manager,108717,0 +71761,Male,48,Masters,18,72,79,35,31,8.0,5,13,Urban,HR Executive,148349,0 +71762,Male,59,PhD,13,60,67,10,13,5.0,2,3,Semi-Urban,Software Engineer,68414,0 +71763,Male,51,Bachelors,19,84,77,45,10,4.0,4,16,Rural,Data Analyst,89224,0 +71764,Female,22,Bachelors,9,30,50,80,72,0.0,7,94,Semi-Urban,Manager,49370,1 +71765,Other,38,Bachelors,15,99,17,74,50,8.0,5,15,Rural,Manager,70216,0 +71766,Male,38,Bachelors,2,35,70,92,0,5.0,1,38,Urban,ML Engineer,53667,1 +71767,Female,22,Bachelors,3,52,37,35,26,0.0,3,28,Urban,HR Executive,55438,0 +71768,Male,55,Masters,5,75,1,63,92,1.0,2,61,Urban,ML Engineer,126032,0 +71769,Female,36,Bachelors,7,11,97,40,63,9.0,2,43,Semi-Urban,HR Executive,56806,0 +71770,Male,57,Bachelors,1,3,39,26,58,7.0,5,51,Urban,HR Executive,144739,0 +71771,Male,47,Bachelors,10,76,37,28,99,6.0,1,61,Semi-Urban,ML Engineer,96722,0 +71772,Male,43,Masters,18,50,35,37,48,7.0,1,79,Rural,HR Executive,41897,0 +71773,Male,36,High School,3,21,74,73,10,2.0,2,97,Urban,ML Engineer,27568,1 +71774,Male,46,Masters,9,9,48,81,36,6.0,2,33,Rural,ML Engineer,26358,0 +71775,Other,40,Bachelors,1,13,40,62,78,8.0,1,4,Urban,Manager,117868,0 +71776,Male,56,Diploma,13,5,5,73,96,6.0,2,7,Rural,ML Engineer,33994,0 +71777,Male,33,Bachelors,14,68,10,2,83,3.0,3,62,Rural,Software Engineer,109739,0 +71778,Other,48,High School,1,70,81,20,28,5.0,0,37,Semi-Urban,Manager,144468,0 +71779,Male,43,Diploma,11,80,95,87,99,9.0,4,49,Urban,Manager,127273,1 +71780,Female,59,Diploma,5,87,45,21,29,9.0,6,25,Urban,HR Executive,51479,0 +71781,Male,49,Diploma,3,1,80,89,47,5.0,6,56,Urban,Data Analyst,108915,0 +71782,Female,23,High School,1,16,68,32,37,3.0,6,93,Urban,Software Engineer,100522,0 +71783,Male,44,PhD,12,64,76,3,64,4.0,4,14,Semi-Urban,Data Analyst,29067,0 +71784,Female,37,Bachelors,19,2,98,50,0,0.0,5,18,Rural,HR Executive,84988,0 +71785,Female,22,Masters,4,88,91,30,36,1.0,3,84,Semi-Urban,Data Analyst,136529,1 +71786,Male,46,Bachelors,16,92,9,20,28,8.0,5,1,Urban,HR Executive,89544,0 +71787,Female,56,Masters,5,48,65,40,29,4.0,7,15,Urban,Software Engineer,31051,0 +71788,Male,52,Masters,13,57,0,50,88,2.0,6,68,Urban,Data Analyst,25285,0 +71789,Male,49,Masters,12,78,1,80,26,8.0,5,60,Rural,HR Executive,135701,0 +71790,Male,26,PhD,19,38,55,15,10,5.0,5,71,Semi-Urban,Software Engineer,24438,0 +71791,Male,53,High School,11,50,69,61,68,2.0,0,62,Urban,ML Engineer,134127,1 +71792,Female,38,Masters,10,10,41,75,53,3.0,3,86,Urban,Data Analyst,31446,0 +71793,Female,46,Diploma,3,57,0,44,38,5.0,3,29,Urban,ML Engineer,23860,0 +71794,Male,33,Masters,8,99,18,26,12,3.0,0,2,Urban,HR Executive,33834,0 +71795,Male,40,High School,19,71,66,37,17,0.0,7,50,Rural,HR Executive,100704,0 +71796,Male,30,Bachelors,9,19,51,20,76,8.0,6,16,Rural,HR Executive,126226,0 +71797,Male,30,Masters,0,57,64,97,30,9.0,3,24,Semi-Urban,Manager,136460,1 +71798,Male,40,PhD,3,9,96,29,4,9.0,6,44,Urban,Manager,105356,0 +71799,Male,34,Bachelors,13,18,16,84,80,4.0,0,69,Urban,Data Analyst,79739,0 +71800,Male,53,Diploma,4,25,72,13,56,4.0,5,60,Urban,HR Executive,46208,0 +71801,Female,22,Masters,14,57,65,25,56,3.0,7,1,Urban,HR Executive,117145,0 +71802,Female,40,Masters,17,1,4,45,36,8.0,6,24,Urban,Data Analyst,89678,0 +71803,Male,38,Bachelors,1,44,96,91,88,4.0,1,19,Rural,ML Engineer,47780,1 +71804,Female,36,Bachelors,8,56,86,63,6,5.0,4,67,Urban,Software Engineer,108288,1 +71805,Male,58,Masters,3,43,36,0,28,5.0,5,0,Urban,Data Analyst,140367,0 +71806,Male,58,Bachelors,4,9,45,1,54,9.0,1,79,Semi-Urban,Manager,66444,0 +71807,Male,40,Masters,3,42,40,51,80,1.0,0,28,Urban,HR Executive,123195,0 +71808,Female,37,Diploma,7,24,30,19,54,6.0,0,59,Urban,Manager,48867,0 +71809,Male,44,High School,5,88,13,4,31,3.0,1,78,Urban,Software Engineer,41617,0 +71810,Male,59,Diploma,16,18,28,28,75,4.0,1,18,Urban,Data Analyst,95647,0 +71811,Male,57,Bachelors,17,32,86,9,84,9.0,6,30,Rural,Software Engineer,105286,0 +71812,Male,59,Bachelors,1,49,76,95,79,4.0,0,70,Urban,Manager,43735,1 +71813,Female,53,Masters,18,44,76,29,57,7.0,6,40,Semi-Urban,ML Engineer,88954,0 +71814,Male,51,Diploma,5,16,3,72,92,3.0,4,30,Semi-Urban,ML Engineer,35999,0 +71815,Female,59,Masters,15,42,32,81,78,9.0,6,47,Semi-Urban,ML Engineer,47568,0 +71816,Female,56,Bachelors,14,93,16,88,58,0.0,5,56,Urban,Software Engineer,118301,1 +71817,Male,22,Bachelors,16,5,14,29,67,9.0,4,17,Rural,ML Engineer,53047,0 +71818,Female,40,Bachelors,17,20,74,61,28,3.0,7,13,Rural,Software Engineer,79790,0 +71819,Male,57,Masters,7,58,82,40,59,3.0,7,66,Urban,Software Engineer,68871,1 +71820,Female,46,Masters,4,76,45,53,98,5.0,2,91,Rural,HR Executive,71591,1 +71821,Male,57,Bachelors,0,99,16,67,19,6.0,1,90,Urban,Data Analyst,86929,1 +71822,Male,42,Bachelors,8,72,81,95,29,6.0,2,43,Urban,ML Engineer,143837,1 +71823,Male,35,Masters,6,1,54,77,69,4.0,5,49,Urban,Software Engineer,60332,0 +71824,Female,46,Diploma,10,2,87,42,79,4.0,6,29,Semi-Urban,Data Analyst,64832,0 +71825,Male,59,Bachelors,19,58,45,22,98,5.0,6,48,Rural,HR Executive,143498,0 +71826,Female,44,Bachelors,4,33,43,86,15,7.0,7,67,Semi-Urban,Manager,144778,0 +71827,Male,27,Bachelors,16,77,61,8,24,1.0,1,33,Urban,Manager,47430,0 +71828,Male,55,High School,6,76,35,26,74,9.0,4,46,Urban,Manager,91357,0 +71829,Male,56,Bachelors,10,80,39,35,62,4.0,6,78,Urban,Software Engineer,44552,0 +71830,Female,23,Diploma,13,0,66,47,10,7.0,7,67,Rural,HR Executive,139320,0 +71831,Female,22,Bachelors,7,20,32,96,74,2.0,2,41,Rural,Manager,34236,0 +71832,Female,32,Bachelors,14,53,94,77,47,5.0,7,33,Urban,ML Engineer,30286,1 +71833,Male,49,Masters,1,26,56,15,27,8.0,0,61,Urban,Data Analyst,54373,0 +71834,Male,30,High School,14,34,4,78,19,7.0,1,24,Semi-Urban,Data Analyst,114799,0 +71835,Female,31,Masters,0,50,91,72,32,6.0,6,89,Urban,Software Engineer,129304,1 +71836,Female,39,Masters,11,19,74,1,99,0.0,4,38,Urban,HR Executive,111843,0 +71837,Male,49,Diploma,4,23,61,82,77,9.0,6,59,Urban,Manager,142941,0 +71838,Female,57,Diploma,8,38,49,52,98,6.0,0,51,Rural,Manager,21568,0 +71839,Male,59,Masters,19,52,51,83,69,8.0,6,23,Urban,Manager,134384,0 +71840,Female,55,Masters,14,42,29,55,96,8.0,6,51,Semi-Urban,Manager,106095,0 +71841,Male,32,Diploma,2,65,98,14,5,9.0,7,90,Urban,Software Engineer,108934,1 +71842,Male,59,High School,9,46,19,33,15,7.0,0,34,Rural,Software Engineer,65412,0 +71843,Male,54,PhD,16,65,78,71,53,1.0,4,79,Urban,Manager,109736,1 +71844,Other,36,Bachelors,5,28,21,99,66,9.0,7,98,Semi-Urban,Software Engineer,29517,1 +71845,Male,45,Masters,13,43,22,30,84,3.0,2,32,Semi-Urban,HR Executive,89896,0 +71846,Other,36,PhD,10,86,46,83,36,1.0,5,41,Rural,HR Executive,39586,1 +71847,Male,58,Bachelors,7,10,13,75,57,4.0,5,58,Urban,Data Analyst,81757,0 +71848,Female,26,Bachelors,7,48,91,8,13,6.0,3,98,Urban,Data Analyst,43786,1 +71849,Female,48,Bachelors,12,27,96,51,13,0.0,5,42,Urban,Manager,65953,0 +71850,Female,31,Bachelors,15,36,29,70,87,1.0,5,17,Urban,ML Engineer,32293,0 +71851,Female,22,Diploma,2,17,57,3,51,6.0,2,13,Urban,HR Executive,136786,0 +71852,Female,23,Masters,6,83,28,86,52,8.0,6,27,Urban,Software Engineer,90333,0 +71853,Female,31,Bachelors,11,61,79,63,12,1.0,0,26,Urban,HR Executive,69747,0 +71854,Other,47,Bachelors,14,0,76,44,24,0.0,5,91,Semi-Urban,Software Engineer,48759,0 +71855,Male,41,Bachelors,1,82,53,2,48,4.0,4,63,Rural,HR Executive,72378,0 +71856,Male,53,Masters,6,35,3,88,38,5.0,1,52,Urban,ML Engineer,96878,0 +71857,Female,34,Bachelors,14,70,13,87,8,8.0,4,18,Urban,ML Engineer,85764,0 +71858,Male,38,Bachelors,13,6,17,32,26,4.0,6,17,Urban,Manager,116459,0 +71859,Female,59,Diploma,18,90,69,93,88,1.0,3,27,Urban,Manager,32525,1 +71860,Male,45,High School,11,25,88,7,99,9.0,0,71,Urban,Data Analyst,28602,0 +71861,Male,59,Diploma,19,23,77,48,44,6.0,0,8,Urban,Software Engineer,141257,0 +71862,Female,36,Diploma,14,50,2,5,11,5.0,7,33,Urban,ML Engineer,29811,0 +71863,Male,56,High School,6,40,43,70,84,4.0,4,50,Urban,Manager,32526,0 +71864,Male,52,Masters,12,65,66,1,81,4.0,1,39,Urban,Data Analyst,128065,0 +71865,Male,57,Masters,10,73,82,3,68,1.0,0,53,Rural,HR Executive,96639,0 +71866,Male,21,Diploma,11,69,83,69,24,0.0,5,25,Semi-Urban,HR Executive,25348,1 +71867,Female,24,Masters,15,91,58,28,60,5.0,4,4,Urban,Data Analyst,72030,0 +71868,Female,50,High School,1,18,73,47,11,5.0,7,57,Urban,Software Engineer,24017,0 +71869,Female,28,Bachelors,3,34,45,74,44,4.0,0,99,Urban,Software Engineer,118636,1 +71870,Female,35,Diploma,18,97,24,34,13,4.0,5,39,Urban,Manager,61306,0 +71871,Other,34,Diploma,14,23,23,49,89,7.0,4,44,Urban,Manager,82066,0 +71872,Male,28,Bachelors,7,28,5,59,70,6.0,6,34,Rural,Data Analyst,60085,0 +71873,Male,37,Bachelors,17,52,41,32,44,5.0,4,16,Urban,Software Engineer,81625,0 +71874,Male,53,High School,1,92,94,7,81,9.0,3,39,Semi-Urban,Software Engineer,99374,0 +71875,Male,30,Diploma,2,85,60,82,29,2.0,3,78,Urban,ML Engineer,116098,1 +71876,Male,39,Bachelors,17,65,45,73,58,8.0,1,3,Urban,ML Engineer,103348,0 +71877,Male,29,Bachelors,1,2,95,76,96,6.0,3,2,Urban,Manager,147868,0 +71878,Male,51,Bachelors,13,48,33,6,44,1.0,5,63,Urban,ML Engineer,63385,0 +71879,Male,32,Masters,5,27,78,25,4,8.0,2,51,Urban,Software Engineer,43265,0 +71880,Male,50,Bachelors,4,73,26,20,48,8.0,3,28,Semi-Urban,Data Analyst,31751,0 +71881,Female,37,Masters,13,69,89,74,32,5.0,2,64,Urban,HR Executive,84700,1 +71882,Male,59,High School,5,18,83,7,11,6.0,4,70,Rural,Manager,27176,0 +71883,Male,56,High School,3,38,55,2,84,2.0,1,51,Urban,Data Analyst,78887,0 +71884,Male,38,Bachelors,8,7,78,83,57,0.0,4,87,Semi-Urban,HR Executive,48224,1 +71885,Male,38,Bachelors,4,57,38,32,80,1.0,2,47,Rural,Manager,55377,0 +71886,Female,43,High School,0,30,0,75,50,8.0,5,54,Urban,HR Executive,108202,0 +71887,Male,32,High School,10,50,65,15,47,4.0,5,50,Semi-Urban,ML Engineer,111219,0 +71888,Male,23,Diploma,13,85,27,56,0,1.0,2,5,Urban,Data Analyst,104830,0 +71889,Female,51,Diploma,15,41,35,2,68,8.0,0,36,Urban,Software Engineer,46490,0 +71890,Male,49,Bachelors,18,99,81,15,64,9.0,2,51,Urban,Software Engineer,24700,1 +71891,Male,46,Bachelors,18,62,66,3,91,5.0,1,16,Rural,ML Engineer,103369,0 +71892,Male,59,Bachelors,1,2,12,46,79,6.0,5,13,Rural,Manager,97964,0 +71893,Male,31,PhD,14,56,15,5,11,7.0,4,30,Urban,ML Engineer,71158,0 +71894,Male,58,PhD,17,73,29,83,73,1.0,6,79,Rural,Data Analyst,137760,1 +71895,Male,30,Bachelors,0,4,72,49,87,2.0,0,96,Urban,ML Engineer,140276,0 +71896,Male,53,Diploma,6,2,17,76,41,5.0,2,36,Urban,Manager,87430,0 +71897,Male,37,Bachelors,3,96,32,73,29,7.0,4,97,Semi-Urban,ML Engineer,127041,1 +71898,Male,53,High School,15,90,16,39,63,7.0,3,89,Rural,HR Executive,89516,0 +71899,Male,47,Masters,11,33,18,3,81,5.0,0,67,Semi-Urban,Software Engineer,90979,0 +71900,Male,29,Diploma,8,28,56,3,5,7.0,7,65,Semi-Urban,HR Executive,84616,0 +71901,Male,32,Diploma,12,33,31,41,23,0.0,7,86,Urban,Software Engineer,149736,0 +71902,Female,36,Bachelors,8,7,41,34,82,5.0,2,37,Urban,Data Analyst,58865,0 +71903,Male,55,Bachelors,13,35,92,50,19,2.0,2,13,Urban,HR Executive,93014,0 +71904,Female,35,Bachelors,8,4,40,99,82,8.0,7,51,Semi-Urban,HR Executive,122810,0 +71905,Male,23,Masters,15,45,38,65,52,7.0,5,44,Urban,Data Analyst,60086,0 +71906,Male,52,Diploma,12,28,32,45,90,5.0,0,63,Urban,Software Engineer,114895,0 +71907,Female,24,Masters,19,39,86,18,81,3.0,3,12,Urban,ML Engineer,90539,0 +71908,Male,39,Bachelors,10,35,35,10,23,2.0,3,6,Urban,Manager,118051,0 +71909,Male,25,Bachelors,6,52,67,18,21,3.0,7,55,Urban,ML Engineer,46264,0 +71910,Female,42,Diploma,10,55,79,29,32,2.0,2,54,Urban,Software Engineer,63106,0 +71911,Female,46,Diploma,18,24,64,13,56,0.0,3,69,Urban,HR Executive,115519,0 +71912,Male,54,High School,16,47,74,28,54,3.0,3,64,Urban,HR Executive,136807,0 +71913,Female,26,Diploma,18,22,47,24,78,9.0,5,83,Urban,Software Engineer,38890,0 +71914,Female,34,Diploma,5,39,72,21,84,1.0,3,0,Semi-Urban,Software Engineer,44617,0 +71915,Male,48,Diploma,10,66,57,69,33,2.0,6,67,Urban,Software Engineer,72620,1 +71916,Male,42,PhD,8,77,83,67,60,1.0,6,88,Urban,HR Executive,23023,1 +71917,Female,26,Diploma,8,31,35,64,37,6.0,5,51,Rural,HR Executive,61710,0 +71918,Male,57,PhD,9,45,17,40,89,6.0,2,51,Urban,Manager,49424,0 +71919,Female,28,High School,18,82,53,91,96,2.0,7,66,Urban,Software Engineer,59410,1 +71920,Male,56,High School,2,92,33,75,61,7.0,4,87,Rural,ML Engineer,34919,1 +71921,Male,24,Diploma,4,75,79,63,23,5.0,3,63,Semi-Urban,Software Engineer,51923,1 +71922,Female,37,Bachelors,10,79,2,33,65,7.0,0,52,Urban,Data Analyst,51900,0 +71923,Female,44,Masters,1,0,45,37,73,2.0,1,47,Urban,ML Engineer,54126,0 +71924,Female,30,Diploma,2,49,95,92,7,1.0,2,11,Semi-Urban,Data Analyst,116463,1 +71925,Male,31,PhD,3,64,30,21,54,5.0,5,60,Urban,Manager,145058,0 +71926,Female,35,Masters,16,57,36,93,16,5.0,3,53,Urban,HR Executive,127233,0 +71927,Male,52,Bachelors,4,38,45,69,63,7.0,4,50,Semi-Urban,HR Executive,26325,0 +71928,Female,27,Diploma,0,44,92,14,2,5.0,3,80,Urban,Manager,101591,0 +71929,Female,31,PhD,4,96,22,49,79,4.0,2,42,Urban,Manager,147283,0 +71930,Male,56,Bachelors,8,93,28,91,9,0.0,7,54,Urban,Software Engineer,70244,1 +71931,Male,36,High School,6,31,54,1,10,9.0,5,65,Urban,HR Executive,60714,0 +71932,Female,53,Bachelors,16,12,67,98,56,8.0,2,76,Rural,Software Engineer,143714,1 +71933,Male,55,Masters,17,63,38,64,0,4.0,4,18,Rural,HR Executive,57051,0 +71934,Female,51,High School,10,80,10,42,18,3.0,3,63,Rural,Data Analyst,35403,0 +71935,Male,59,High School,18,63,14,60,71,3.0,5,57,Urban,ML Engineer,61525,0 +71936,Male,53,Bachelors,7,16,45,92,20,1.0,5,13,Semi-Urban,Manager,119142,0 +71937,Male,57,Masters,2,47,33,87,91,1.0,5,39,Urban,Data Analyst,87537,0 +71938,Female,28,Bachelors,5,94,29,73,22,9.0,4,50,Semi-Urban,HR Executive,113071,1 +71939,Male,26,Diploma,16,1,78,56,62,0.0,1,35,Urban,ML Engineer,91144,0 +71940,Male,56,High School,7,83,89,83,39,7.0,3,35,Rural,Software Engineer,27736,1 +71941,Female,32,Bachelors,8,68,43,45,6,4.0,7,26,Urban,Data Analyst,148308,0 +71942,Male,30,Masters,19,18,56,34,63,1.0,3,63,Urban,HR Executive,78753,0 +71943,Male,34,Bachelors,13,61,88,19,4,0.0,7,33,Rural,Software Engineer,35290,0 +71944,Female,34,Bachelors,1,82,28,36,82,2.0,2,16,Urban,Manager,110650,0 +71945,Male,49,Bachelors,7,61,23,50,30,5.0,6,82,Urban,Data Analyst,39019,0 +71946,Female,45,Diploma,7,41,9,19,70,2.0,7,20,Urban,Manager,72489,0 +71947,Male,37,Masters,19,7,38,21,68,0.0,2,36,Urban,ML Engineer,142078,0 +71948,Male,30,High School,2,62,15,0,47,4.0,3,73,Urban,HR Executive,147442,0 +71949,Male,51,Bachelors,9,71,58,38,30,2.0,4,13,Urban,ML Engineer,111092,0 +71950,Male,56,Bachelors,10,48,48,88,8,0.0,4,41,Urban,ML Engineer,83391,0 +71951,Female,39,Bachelors,6,87,27,3,32,5.0,2,74,Rural,Data Analyst,139085,0 +71952,Female,54,Bachelors,0,45,48,27,44,2.0,4,66,Semi-Urban,ML Engineer,145013,0 +71953,Male,42,Bachelors,7,25,36,34,17,7.0,2,76,Urban,Software Engineer,95217,0 +71954,Male,40,Diploma,6,19,42,47,46,9.0,2,9,Rural,ML Engineer,56268,0 +71955,Female,56,Masters,15,56,7,38,37,8.0,2,91,Semi-Urban,Manager,91135,0 +71956,Male,22,High School,11,81,43,2,92,2.0,3,79,Urban,Data Analyst,115414,0 +71957,Female,57,Bachelors,9,93,87,21,5,5.0,6,10,Urban,HR Executive,52347,0 +71958,Male,46,Diploma,9,12,12,50,17,4.0,2,68,Urban,ML Engineer,146003,0 +71959,Female,47,Bachelors,5,63,17,79,96,6.0,1,20,Rural,Data Analyst,76496,0 +71960,Male,49,High School,15,59,67,14,15,2.0,2,63,Semi-Urban,Software Engineer,56350,0 +71961,Male,38,PhD,1,72,40,20,20,9.0,6,77,Urban,Manager,121764,0 +71962,Female,21,Masters,4,49,61,76,82,7.0,7,29,Rural,HR Executive,39320,0 +71963,Male,56,Diploma,7,65,95,77,95,7.0,4,85,Semi-Urban,Software Engineer,44720,1 +71964,Male,43,Bachelors,19,56,96,14,43,7.0,3,82,Urban,Software Engineer,48055,1 +71965,Male,58,High School,16,13,29,76,58,2.0,5,10,Urban,Manager,101591,0 +71966,Male,59,Diploma,1,7,10,79,75,0.0,2,38,Urban,ML Engineer,113258,0 +71967,Male,33,PhD,11,84,83,57,48,5.0,6,85,Semi-Urban,Manager,141793,1 +71968,Male,55,High School,4,95,51,54,93,9.0,5,79,Urban,Data Analyst,55337,1 +71969,Female,47,Diploma,11,4,96,66,90,4.0,1,17,Semi-Urban,HR Executive,58206,0 +71970,Female,52,Bachelors,8,0,25,34,29,5.0,2,9,Semi-Urban,Manager,25242,0 +71971,Female,27,Masters,6,48,42,9,87,3.0,1,23,Urban,Software Engineer,22795,0 +71972,Male,42,High School,8,97,78,74,20,4.0,0,26,Urban,Software Engineer,100858,1 +71973,Male,55,Bachelors,8,10,22,54,67,1.0,3,99,Semi-Urban,Data Analyst,134955,0 +71974,Female,51,High School,0,86,7,77,56,5.0,7,7,Urban,Manager,128942,0 +71975,Male,35,Diploma,11,77,82,21,32,7.0,4,82,Semi-Urban,Software Engineer,35401,1 +71976,Female,41,Masters,2,47,23,44,68,0.0,4,88,Semi-Urban,ML Engineer,94967,0 +71977,Male,38,Masters,19,12,89,16,27,5.0,7,48,Rural,HR Executive,43985,0 +71978,Female,32,PhD,16,98,36,12,4,7.0,6,32,Semi-Urban,ML Engineer,127003,0 +71979,Female,40,Bachelors,3,3,16,2,65,0.0,2,90,Urban,Data Analyst,145491,0 +71980,Male,44,Bachelors,17,26,37,86,72,4.0,1,45,Urban,Manager,124250,0 +71981,Male,51,High School,7,46,84,41,93,0.0,2,17,Urban,Manager,146393,0 +71982,Female,25,Bachelors,19,94,86,67,75,2.0,2,53,Rural,Data Analyst,20140,1 +71983,Male,49,Masters,14,40,80,2,30,7.0,1,40,Urban,Manager,41877,0 +71984,Male,30,Bachelors,10,33,10,28,40,5.0,4,59,Urban,HR Executive,114894,0 +71985,Female,48,Bachelors,9,56,89,25,63,3.0,5,87,Urban,Data Analyst,102169,1 +71986,Female,46,Diploma,9,57,93,24,74,0.0,1,44,Rural,Software Engineer,84812,0 +71987,Male,48,Masters,14,57,58,49,39,0.0,4,40,Urban,Software Engineer,34634,0 +71988,Male,45,Bachelors,19,38,42,57,58,2.0,6,31,Semi-Urban,HR Executive,77313,0 +71989,Male,39,Masters,15,14,41,82,2,1.0,3,61,Urban,ML Engineer,24000,0 +71990,Male,54,Bachelors,17,64,15,48,79,6.0,3,61,Urban,Data Analyst,91261,0 +71991,Male,46,PhD,12,69,1,37,29,0.0,3,11,Rural,Manager,112658,0 +71992,Male,51,Diploma,2,73,51,39,96,5.0,1,57,Urban,Data Analyst,96192,0 +71993,Male,35,Bachelors,11,19,39,26,19,4.0,6,9,Urban,Data Analyst,105543,0 +71994,Male,32,Diploma,16,89,76,34,96,5.0,6,27,Rural,HR Executive,66451,0 +71995,Male,36,High School,1,67,29,98,98,1.0,1,6,Semi-Urban,HR Executive,140720,0 +71996,Female,36,Masters,16,98,36,83,90,3.0,4,73,Semi-Urban,ML Engineer,54659,1 +71997,Female,59,Bachelors,12,92,73,9,20,0.0,3,21,Rural,Data Analyst,78725,0 +71998,Female,38,Bachelors,2,90,84,39,86,6.0,0,63,Semi-Urban,Data Analyst,102510,1 +71999,Female,56,Bachelors,8,68,87,1,9,4.0,3,63,Rural,Software Engineer,96907,0 +72000,Male,36,High School,14,94,46,9,28,4.0,4,65,Semi-Urban,Data Analyst,130300,0 +72001,Male,22,Bachelors,17,98,86,90,85,0.0,2,29,Urban,Data Analyst,149291,1 +72002,Other,25,Bachelors,9,83,49,30,92,0.0,4,97,Semi-Urban,Software Engineer,134691,1 +72003,Female,46,Bachelors,7,2,79,94,17,2.0,0,99,Urban,Data Analyst,142692,1 +72004,Female,45,Bachelors,13,30,36,37,25,8.0,4,27,Urban,Manager,50666,0 +72005,Male,43,Masters,14,25,12,9,90,6.0,2,93,Urban,ML Engineer,106865,0 +72006,Male,48,Bachelors,0,22,37,8,27,8.0,7,3,Rural,Data Analyst,101559,0 +72007,Female,47,Bachelors,13,12,40,3,48,6.0,1,37,Urban,Manager,142767,0 +72008,Female,49,Diploma,6,42,63,54,22,5.0,1,1,Semi-Urban,HR Executive,61764,0 +72009,Male,46,Bachelors,18,68,27,90,88,7.0,5,28,Urban,ML Engineer,78102,0 +72010,Male,35,Bachelors,15,59,88,96,98,5.0,6,12,Urban,ML Engineer,98977,1 +72011,Male,22,Masters,5,32,14,56,57,3.0,4,31,Urban,HR Executive,54902,0 +72012,Male,42,Diploma,19,99,8,75,43,6.0,4,45,Rural,HR Executive,59675,0 +72013,Male,38,High School,4,53,17,15,96,7.0,6,51,Urban,ML Engineer,87045,0 +72014,Male,58,Masters,15,69,6,75,69,0.0,7,2,Urban,Manager,32183,0 +72015,Male,47,Masters,4,89,28,26,8,5.0,4,46,Urban,HR Executive,33044,0 +72016,Male,39,Masters,3,99,1,50,21,0.0,2,92,Urban,Manager,95547,1 +72017,Female,57,Diploma,12,99,94,70,14,6.0,1,90,Rural,Manager,107010,1 +72018,Male,43,High School,6,2,50,29,28,3.0,5,52,Semi-Urban,ML Engineer,72772,0 +72019,Female,54,High School,8,92,9,16,77,2.0,5,40,Rural,Data Analyst,28186,0 +72020,Male,26,High School,9,55,60,18,43,9.0,6,10,Semi-Urban,Manager,43627,0 +72021,Female,34,Diploma,2,5,21,4,15,2.0,2,40,Semi-Urban,ML Engineer,123149,0 +72022,Female,21,Bachelors,2,93,33,74,52,3.0,4,17,Urban,ML Engineer,94892,0 +72023,Female,49,Diploma,2,28,31,6,70,5.0,5,40,Urban,ML Engineer,54620,0 +72024,Female,56,Diploma,6,73,8,46,95,0.0,0,75,Rural,Software Engineer,25979,0 +72025,Male,31,High School,9,40,65,61,87,3.0,5,43,Semi-Urban,Data Analyst,121380,0 +72026,Other,49,High School,9,36,32,17,29,6.0,6,77,Urban,HR Executive,113984,0 +72027,Male,47,Bachelors,0,54,94,57,41,6.0,2,71,Urban,Data Analyst,101434,1 +72028,Female,41,Bachelors,0,12,99,6,85,5.0,4,5,Urban,Software Engineer,141451,0 +72029,Male,29,Bachelors,5,33,36,49,38,3.0,2,33,Semi-Urban,Manager,123432,0 +72030,Male,59,High School,10,67,39,24,25,2.0,6,66,Urban,HR Executive,116417,0 +72031,Female,49,Diploma,10,52,58,45,47,6.0,4,3,Semi-Urban,Data Analyst,76133,0 +72032,Female,54,High School,12,81,82,26,85,5.0,1,91,Semi-Urban,HR Executive,52987,1 +72033,Male,36,Bachelors,9,12,97,85,92,2.0,3,90,Semi-Urban,Manager,47394,1 +72034,Female,27,High School,6,0,7,11,2,7.0,2,14,Urban,ML Engineer,63380,0 +72035,Male,58,High School,18,74,40,37,48,5.0,6,64,Urban,Data Analyst,79300,0 +72036,Male,30,High School,15,85,38,33,26,3.0,6,60,Urban,Software Engineer,50964,0 +72037,Female,23,Bachelors,4,28,6,79,80,6.0,1,50,Urban,Data Analyst,48117,0 +72038,Male,44,Bachelors,12,61,32,19,6,1.0,0,40,Rural,Software Engineer,50725,0 +72039,Male,36,Masters,19,55,14,62,7,2.0,0,19,Urban,Manager,145531,0 +72040,Other,55,Bachelors,14,32,25,72,77,3.0,0,82,Semi-Urban,Manager,29664,0 +72041,Male,32,High School,12,0,24,44,41,0.0,3,9,Urban,Manager,64877,0 +72042,Male,47,Masters,18,6,1,59,98,7.0,2,45,Semi-Urban,Software Engineer,54647,0 +72043,Male,55,Masters,7,24,63,1,18,0.0,2,22,Urban,ML Engineer,85193,0 +72044,Female,41,Masters,3,29,59,92,37,3.0,1,12,Urban,HR Executive,73083,0 +72045,Female,27,Masters,7,77,94,19,11,6.0,5,99,Urban,Software Engineer,133721,1 +72046,Female,54,Diploma,14,69,4,12,67,3.0,3,82,Semi-Urban,Manager,86901,0 +72047,Female,25,Diploma,13,4,11,36,82,2.0,3,1,Urban,HR Executive,129603,0 +72048,Male,35,Masters,3,57,59,19,3,0.0,6,48,Semi-Urban,Software Engineer,106278,0 +72049,Male,21,Bachelors,16,87,94,56,82,9.0,1,70,Urban,Data Analyst,36174,1 +72050,Male,29,Bachelors,15,22,34,66,75,4.0,7,44,Urban,Manager,93219,0 +72051,Female,50,High School,12,28,15,64,57,2.0,1,92,Rural,Software Engineer,147309,0 +72052,Male,44,High School,18,75,7,33,79,5.0,5,47,Urban,HR Executive,137778,0 +72053,Other,45,Bachelors,8,11,9,42,46,0.0,5,22,Urban,HR Executive,50951,0 +72054,Male,27,Bachelors,12,52,2,50,53,7.0,1,66,Urban,Software Engineer,140747,0 +72055,Male,34,Bachelors,9,80,88,28,8,1.0,0,79,Urban,Data Analyst,111130,1 +72056,Male,57,High School,6,25,11,34,96,5.0,2,21,Urban,Manager,30983,0 +72057,Female,44,Diploma,12,50,20,33,18,3.0,5,20,Urban,HR Executive,41636,0 +72058,Male,28,Masters,18,78,43,37,58,5.0,1,84,Urban,Software Engineer,101952,1 +72059,Other,45,Masters,7,58,28,8,17,0.0,3,26,Urban,HR Executive,123265,0 +72060,Other,45,Bachelors,19,76,91,23,79,2.0,2,22,Urban,ML Engineer,59601,0 +72061,Male,23,High School,6,87,9,99,92,8.0,3,98,Urban,Manager,94789,1 +72062,Male,44,Masters,8,91,68,58,37,3.0,5,10,Urban,Software Engineer,72812,0 +72063,Male,30,Masters,17,42,11,85,6,1.0,1,58,Rural,Data Analyst,147929,0 +72064,Male,28,Bachelors,16,21,35,22,34,5.0,7,34,Urban,HR Executive,93703,0 +72065,Male,39,Diploma,19,30,76,24,31,4.0,0,23,Rural,Software Engineer,57542,0 +72066,Female,43,Bachelors,19,35,3,84,75,8.0,4,3,Urban,ML Engineer,27040,0 +72067,Male,22,Diploma,8,90,4,6,81,7.0,4,99,Urban,ML Engineer,23289,0 +72068,Other,30,Diploma,12,73,49,59,21,2.0,5,64,Urban,Data Analyst,100606,1 +72069,Female,57,PhD,17,8,42,23,95,4.0,0,80,Urban,Data Analyst,76611,0 +72070,Male,44,Masters,6,83,26,36,86,4.0,7,55,Semi-Urban,ML Engineer,44956,0 +72071,Male,31,Masters,18,69,74,40,33,2.0,6,55,Urban,Manager,44334,1 +72072,Male,48,High School,5,84,12,50,56,4.0,5,11,Urban,Software Engineer,107687,0 +72073,Male,29,Masters,4,60,23,75,85,9.0,1,61,Urban,Manager,117969,0 +72074,Female,33,Bachelors,12,61,86,28,9,8.0,3,81,Rural,HR Executive,28408,1 +72075,Male,58,Masters,19,11,56,93,0,1.0,1,43,Semi-Urban,Software Engineer,97845,0 +72076,Male,48,Bachelors,14,97,37,53,30,7.0,6,80,Urban,Software Engineer,20202,1 +72077,Male,55,Bachelors,19,42,41,57,67,8.0,3,13,Semi-Urban,Software Engineer,81538,0 +72078,Male,57,Diploma,12,21,13,48,34,2.0,6,57,Urban,Data Analyst,113202,0 +72079,Female,58,Diploma,19,15,84,98,64,8.0,5,94,Urban,Data Analyst,44960,1 +72080,Female,41,Diploma,3,4,43,25,71,8.0,1,20,Urban,HR Executive,88101,0 +72081,Male,25,High School,15,82,57,78,55,6.0,0,96,Urban,HR Executive,130279,1 +72082,Male,40,High School,17,91,29,38,62,6.0,4,67,Urban,Software Engineer,32523,0 +72083,Female,57,Bachelors,17,55,92,95,83,2.0,3,5,Rural,Manager,29781,1 +72084,Female,32,Diploma,12,19,72,59,3,9.0,4,91,Semi-Urban,Software Engineer,145105,1 +72085,Female,22,Bachelors,5,20,43,17,64,9.0,7,27,Urban,ML Engineer,114103,0 +72086,Female,23,Masters,6,11,66,32,23,4.0,0,96,Urban,Data Analyst,37317,0 +72087,Male,48,Bachelors,4,29,42,10,16,3.0,2,54,Semi-Urban,HR Executive,147822,0 +72088,Male,39,Diploma,14,26,91,69,47,3.0,7,30,Semi-Urban,HR Executive,28238,0 +72089,Male,38,Diploma,5,3,75,68,53,7.0,0,63,Rural,Manager,87196,0 +72090,Female,49,Bachelors,6,34,95,67,14,7.0,7,60,Urban,HR Executive,140972,1 +72091,Male,25,High School,17,71,90,34,76,2.0,2,39,Rural,Software Engineer,93244,0 +72092,Female,45,Diploma,6,10,28,81,88,4.0,3,86,Urban,Data Analyst,131797,0 +72093,Male,23,PhD,18,53,40,35,82,3.0,2,92,Urban,Software Engineer,127390,0 +72094,Female,25,Bachelors,0,46,81,79,3,4.0,1,76,Urban,Data Analyst,109022,1 +72095,Male,28,Bachelors,19,15,36,55,80,0.0,4,15,Urban,Manager,115438,0 +72096,Male,23,,1,25,52,82,53,5.0,4,5,Rural,HR Executive,103515,0 +72097,Male,42,High School,1,0,66,24,37,2.0,7,29,Semi-Urban,Software Engineer,142478,0 +72098,Female,39,Bachelors,5,89,53,74,91,4.0,2,40,Urban,ML Engineer,55492,1 +72099,Male,40,Bachelors,5,96,96,95,63,6.0,5,47,Semi-Urban,Manager,107214,1 +72100,Male,40,Diploma,11,72,1,63,87,4.0,3,8,Semi-Urban,Software Engineer,44374,0 +72101,Male,41,High School,12,68,19,5,51,2.0,3,32,Urban,Software Engineer,147881,0 +72102,Male,48,Bachelors,16,50,85,4,22,1.0,5,33,Urban,Manager,79717,0 +72103,Male,39,Diploma,4,7,82,34,0,0.0,0,12,Urban,Data Analyst,82548,0 +72104,Male,59,Diploma,11,48,14,82,56,3.0,3,83,Urban,Software Engineer,122540,0 +72105,Male,42,Diploma,1,90,12,7,64,8.0,3,49,Urban,Data Analyst,67275,0 +72106,Male,21,Bachelors,18,64,70,67,59,4.0,6,4,Semi-Urban,Data Analyst,64462,0 +72107,Male,46,Bachelors,16,87,34,0,46,0.0,4,59,Urban,Software Engineer,72826,0 +72108,Male,32,Masters,17,28,49,77,32,5.0,6,19,Semi-Urban,HR Executive,52652,0 +72109,Male,41,Masters,8,73,68,70,54,1.0,4,58,Urban,HR Executive,108630,1 +72110,Male,26,High School,3,45,96,88,87,9.0,0,54,Urban,ML Engineer,58650,1 +72111,Other,22,High School,5,6,71,38,70,7.0,0,7,Rural,Manager,26382,0 +72112,Female,50,High School,16,93,54,7,12,8.0,2,37,Urban,ML Engineer,32447,0 +72113,Male,25,Diploma,16,76,33,75,68,2.0,3,82,Rural,Manager,73432,1 +72114,Female,59,Bachelors,19,40,71,70,2,9.0,7,7,Urban,ML Engineer,25029,0 +72115,Female,53,Bachelors,3,90,56,65,86,5.0,6,72,Urban,Software Engineer,146250,1 +72116,Male,57,,18,77,56,25,7,7.0,7,95,Urban,Software Engineer,30889,1 +72117,Male,28,Bachelors,19,67,59,39,27,9.0,7,86,Rural,Manager,106848,1 +72118,Male,55,Masters,7,96,25,5,92,2.0,2,63,Urban,ML Engineer,89087,0 +72119,Male,56,Bachelors,17,36,11,73,8,3.0,1,59,Urban,HR Executive,26327,0 +72120,Female,41,Masters,14,54,97,95,75,2.0,3,84,Rural,Manager,63849,1 +72121,Male,48,High School,15,28,67,14,30,8.0,2,20,Semi-Urban,Data Analyst,20289,0 +72122,Female,28,Bachelors,7,26,84,53,94,2.0,7,4,Semi-Urban,Data Analyst,130962,0 +72123,Male,52,Masters,15,13,31,19,28,8.0,6,21,Rural,Data Analyst,142770,0 +72124,Female,22,Masters,18,95,85,20,69,1.0,0,50,Rural,ML Engineer,115863,1 +72125,Male,29,Diploma,16,24,74,0,11,2.0,0,68,Urban,Software Engineer,98812,0 +72126,Female,54,Diploma,10,15,36,82,35,8.0,5,24,Semi-Urban,ML Engineer,83518,0 +72127,Female,29,Bachelors,15,56,9,63,63,3.0,4,26,Urban,Data Analyst,88951,0 +72128,Female,29,Diploma,13,68,82,37,36,2.0,4,44,Rural,Data Analyst,136775,0 +72129,Female,47,Diploma,6,14,30,27,77,1.0,0,32,Rural,HR Executive,66286,0 +72130,Male,57,Masters,16,0,89,20,35,3.0,6,91,Rural,ML Engineer,53818,0 +72131,Male,40,High School,13,26,66,0,71,9.0,4,42,Urban,Software Engineer,56930,0 +72132,Male,32,Diploma,7,89,58,45,55,2.0,2,87,Semi-Urban,Software Engineer,97180,1 +72133,Female,22,High School,12,32,84,49,7,6.0,3,73,Rural,HR Executive,68704,0 +72134,Male,31,Bachelors,16,82,69,41,67,2.0,4,19,Rural,HR Executive,48018,0 +72135,Male,24,High School,3,98,66,27,64,9.0,7,43,Rural,ML Engineer,110932,0 +72136,Female,48,Bachelors,17,74,66,48,31,6.0,2,24,Rural,ML Engineer,58449,0 +72137,Male,40,Diploma,16,86,18,37,15,5.0,7,34,Semi-Urban,Manager,143330,0 +72138,Male,47,High School,14,83,47,69,75,2.0,1,8,Urban,ML Engineer,118280,0 +72139,Female,22,Diploma,10,93,70,42,24,3.0,7,2,Semi-Urban,Data Analyst,98113,0 +72140,Other,45,High School,10,85,27,91,82,7.0,1,43,Urban,ML Engineer,54663,1 +72141,Male,26,Bachelors,5,99,71,0,66,1.0,4,76,Urban,Data Analyst,127650,1 +72142,Female,48,Bachelors,14,62,89,26,85,0.0,7,20,Urban,Data Analyst,100565,0 +72143,Male,59,Bachelors,15,57,58,34,21,0.0,1,12,Rural,HR Executive,136100,0 +72144,Male,46,Bachelors,5,75,96,13,89,9.0,6,29,Urban,HR Executive,130107,0 +72145,Male,23,Bachelors,18,74,75,15,5,5.0,5,68,Semi-Urban,ML Engineer,98933,0 +72146,Female,52,High School,6,47,90,79,6,6.0,3,45,Urban,Software Engineer,117503,1 +72147,Female,56,Bachelors,5,42,55,95,64,1.0,7,88,Urban,Software Engineer,105062,1 +72148,Male,28,Masters,2,4,3,6,93,1.0,7,70,Rural,Data Analyst,62170,0 +72149,Female,47,Bachelors,2,83,31,12,71,3.0,0,63,Urban,Manager,88393,0 +72150,Male,30,Bachelors,5,8,88,57,71,9.0,6,85,Urban,HR Executive,68254,1 +72151,Female,45,Diploma,14,57,6,23,76,1.0,7,16,Urban,Software Engineer,132843,0 +72152,Male,26,Diploma,16,85,1,50,23,7.0,1,18,Urban,Data Analyst,23175,0 +72153,Female,58,Diploma,6,76,41,93,2,8.0,5,21,Semi-Urban,ML Engineer,48915,0 +72154,Male,25,PhD,8,79,40,99,22,7.0,2,93,Urban,Data Analyst,97596,1 +72155,Other,48,Diploma,12,72,25,39,1,4.0,1,71,Semi-Urban,HR Executive,33654,0 +72156,Male,23,Bachelors,4,40,10,4,57,3.0,7,26,Urban,ML Engineer,113468,0 +72157,Male,54,Bachelors,1,11,92,26,94,3.0,7,69,Urban,HR Executive,125812,0 +72158,Female,47,Bachelors,16,79,0,99,85,9.0,2,53,Semi-Urban,Software Engineer,131142,0 +72159,Female,30,Masters,13,73,37,88,38,8.0,0,10,Urban,ML Engineer,88414,0 +72160,Other,54,High School,17,22,77,68,5,1.0,4,86,Urban,Manager,128039,1 +72161,Male,56,Bachelors,11,10,81,78,46,4.0,7,40,Rural,Manager,110025,0 +72162,Male,29,High School,14,43,53,82,19,5.0,7,15,Semi-Urban,Manager,131582,0 +72163,Female,30,Diploma,6,93,85,90,98,8.0,1,27,Rural,Manager,22361,1 +72164,Male,24,Bachelors,17,37,37,96,5,5.0,0,55,Urban,Software Engineer,113633,0 +72165,Female,59,Bachelors,11,8,85,37,58,8.0,5,11,Urban,Manager,101381,0 +72166,Male,47,Bachelors,17,71,25,60,95,7.0,4,42,Urban,HR Executive,27279,0 +72167,Female,54,Masters,8,7,1,30,6,2.0,1,72,Urban,Software Engineer,87076,0 +72168,Male,52,High School,16,47,9,35,65,4.0,3,66,Urban,Manager,43638,0 +72169,Female,55,Bachelors,2,79,64,68,58,1.0,2,3,Urban,Manager,23299,0 +72170,Female,47,Masters,1,68,30,67,12,3.0,3,54,Urban,Data Analyst,99007,0 +72171,Female,52,High School,19,24,18,22,45,7.0,4,90,Urban,Data Analyst,112609,0 +72172,Female,37,Bachelors,9,30,66,95,75,1.0,2,4,Urban,Data Analyst,42839,0 +72173,Male,51,Masters,2,90,91,60,95,7.0,3,19,Rural,Software Engineer,148861,1 +72174,Female,31,Bachelors,2,84,88,62,6,3.0,1,99,Semi-Urban,Software Engineer,59403,1 +72175,Female,32,Bachelors,1,9,62,49,74,2.0,1,32,Urban,Manager,142489,0 +72176,Female,53,High School,7,63,61,27,54,8.0,5,34,Semi-Urban,ML Engineer,42641,0 +72177,Female,25,Bachelors,14,59,52,45,5,6.0,3,95,Urban,Software Engineer,99685,1 +72178,Male,30,Masters,3,15,83,57,25,6.0,1,15,Urban,Data Analyst,35293,0 +72179,Female,40,High School,15,55,98,91,53,9.0,6,26,Urban,Software Engineer,144122,1 +72180,Female,44,Masters,16,49,29,87,12,3.0,4,70,Semi-Urban,Manager,20200,0 +72181,Male,26,High School,3,67,71,55,86,3.0,5,39,Urban,Manager,49832,0 +72182,Female,32,Bachelors,17,49,30,79,44,3.0,7,58,Semi-Urban,Software Engineer,60723,0 +72183,Male,45,PhD,11,14,42,45,57,6.0,3,17,Rural,Data Analyst,66722,0 +72184,Male,45,Bachelors,7,70,9,51,90,8.0,4,7,Semi-Urban,Software Engineer,108191,0 +72185,Male,46,Bachelors,1,96,7,41,86,4.0,4,36,Urban,ML Engineer,124165,0 +72186,Female,27,High School,11,99,81,22,36,1.0,2,60,Urban,Manager,33324,1 +72187,Male,23,PhD,19,24,38,44,71,1.0,5,90,Rural,HR Executive,26714,0 +72188,Male,40,Diploma,8,80,34,38,59,3.0,2,21,Urban,Software Engineer,79445,0 +72189,Male,26,Bachelors,17,80,97,87,26,0.0,4,35,Rural,Data Analyst,125388,1 +72190,Male,39,Masters,4,52,60,94,35,9.0,4,21,Urban,HR Executive,102108,0 +72191,Female,59,Diploma,3,21,39,33,17,6.0,5,56,Rural,Software Engineer,149627,0 +72192,Male,41,Bachelors,10,98,82,60,54,0.0,7,0,Urban,Software Engineer,123224,1 +72193,Female,21,Bachelors,6,89,51,70,37,2.0,2,91,Urban,HR Executive,145834,1 +72194,Male,33,Masters,2,5,13,91,47,1.0,4,34,Semi-Urban,Software Engineer,34843,0 +72195,Male,51,Bachelors,15,17,34,58,42,2.0,6,36,Semi-Urban,Software Engineer,120049,0 +72196,Male,54,Masters,18,9,0,96,65,9.0,3,85,Semi-Urban,ML Engineer,106927,0 +72197,Other,28,PhD,10,10,96,89,11,8.0,0,24,Semi-Urban,ML Engineer,75174,0 +72198,Male,57,Masters,17,19,96,15,96,4.0,7,65,Urban,HR Executive,138294,0 +72199,Male,30,Masters,13,29,25,50,46,7.0,6,89,Semi-Urban,Manager,73449,0 +72200,Female,41,Bachelors,6,44,6,4,92,1.0,7,77,Urban,Software Engineer,92761,0 +72201,Male,44,Masters,2,50,90,32,97,3.0,4,13,Rural,HR Executive,145130,0 +72202,Male,34,PhD,7,57,37,87,1,9.0,6,51,Semi-Urban,Manager,80850,0 +72203,Male,37,Masters,16,20,28,6,62,2.0,0,81,Urban,HR Executive,122508,0 +72204,Male,36,Bachelors,2,66,16,34,46,3.0,4,51,Semi-Urban,Manager,120939,0 +72205,Male,40,Diploma,0,30,82,4,60,3.0,1,63,Rural,Manager,93041,0 +72206,Male,26,High School,1,81,22,66,44,5.0,0,55,Rural,Software Engineer,72445,0 +72207,Female,59,Diploma,2,73,32,50,73,0.0,6,16,Urban,Manager,131252,0 +72208,Other,54,Bachelors,2,44,43,38,74,8.0,5,95,Urban,Manager,96581,0 +72209,Female,30,Masters,8,60,65,66,38,9.0,0,15,Urban,Data Analyst,22843,0 +72210,Male,56,High School,4,39,59,40,95,8.0,5,60,Urban,Data Analyst,61725,0 +72211,Male,55,Masters,19,79,55,59,9,2.0,6,95,Rural,HR Executive,68681,1 +72212,Male,49,Diploma,13,92,94,57,28,5.0,1,0,Urban,Data Analyst,29869,1 +72213,Male,32,Bachelors,7,5,3,96,17,1.0,0,7,Semi-Urban,HR Executive,39465,0 +72214,Male,59,Bachelors,2,99,69,1,28,6.0,6,66,Semi-Urban,Manager,56325,1 +72215,Female,54,High School,6,48,18,89,64,8.0,4,1,Urban,Manager,40225,0 +72216,Female,49,Diploma,9,38,10,83,76,4.0,5,15,Semi-Urban,Data Analyst,47080,0 +72217,Female,40,Diploma,6,65,99,64,26,1.0,4,71,Urban,Data Analyst,102572,1 +72218,Male,45,Diploma,15,67,92,1,84,2.0,0,67,Rural,Data Analyst,62875,0 +72219,Male,55,High School,17,94,38,93,5,6.0,6,24,Urban,Software Engineer,61039,1 +72220,Male,58,Bachelors,17,1,95,30,59,4.0,4,69,Urban,Software Engineer,82387,0 +72221,Female,36,Masters,19,52,11,70,88,2.0,1,95,Semi-Urban,Data Analyst,47145,0 +72222,Female,32,High School,0,72,76,90,20,1.0,6,96,Urban,Software Engineer,76366,1 +72223,Male,44,Diploma,6,21,14,34,30,8.0,1,34,Urban,ML Engineer,26937,0 +72224,Male,52,High School,3,76,23,40,54,5.0,3,47,Urban,Data Analyst,77315,0 +72225,Male,33,Bachelors,8,44,79,68,0,6.0,3,49,Urban,Manager,70159,1 +72226,Other,22,High School,7,17,52,73,20,7.0,0,69,Urban,ML Engineer,145705,0 +72227,Male,25,Diploma,11,95,81,22,90,8.0,1,16,Urban,Data Analyst,65131,0 +72228,Male,37,Diploma,2,54,69,77,99,6.0,1,55,Urban,Manager,136092,1 +72229,Male,36,PhD,5,3,75,33,37,7.0,0,74,Rural,ML Engineer,28851,0 +72230,Male,40,High School,2,4,85,22,98,9.0,1,27,Semi-Urban,HR Executive,133154,0 +72231,Other,54,High School,16,24,54,87,59,8.0,2,41,Urban,ML Engineer,129354,0 +72232,Male,48,Masters,12,25,77,47,45,8.0,5,45,Urban,HR Executive,149003,0 +72233,Male,59,Bachelors,8,18,7,92,52,0.0,7,48,Urban,Data Analyst,119674,0 +72234,Male,43,Bachelors,2,33,50,92,17,2.0,0,76,Urban,ML Engineer,51674,1 +72235,Male,45,Bachelors,8,21,34,28,32,9.0,6,73,Urban,Software Engineer,119535,0 +72236,Female,27,Diploma,9,63,74,95,18,0.0,1,55,Urban,Software Engineer,90215,1 +72237,Male,39,PhD,8,15,63,67,30,6.0,3,32,Semi-Urban,Manager,32872,0 +72238,Male,26,High School,9,72,86,61,64,1.0,5,78,Urban,Software Engineer,122999,1 +72239,Female,30,Bachelors,11,93,84,78,59,8.0,5,18,Urban,Data Analyst,143166,1 +72240,Male,48,Bachelors,3,94,67,8,20,1.0,6,54,Urban,Data Analyst,109346,0 +72241,Female,55,High School,3,22,65,18,92,4.0,7,15,Urban,Manager,34535,0 +72242,Male,39,High School,17,86,1,57,52,1.0,2,26,Urban,Data Analyst,27554,0 +72243,Male,23,Masters,9,61,98,99,33,1.0,6,77,Semi-Urban,HR Executive,95075,1 +72244,Male,46,Masters,12,0,50,43,16,2.0,2,60,Semi-Urban,Manager,38702,0 +72245,Male,44,Masters,9,38,27,37,64,3.0,0,35,Urban,Manager,33438,0 +72246,Male,22,Diploma,13,17,22,54,14,7.0,7,86,Rural,Data Analyst,119809,0 +72247,Male,29,Masters,10,24,59,79,38,4.0,4,23,Semi-Urban,Manager,91369,0 +72248,Female,57,Masters,4,23,38,67,89,7.0,4,2,Urban,HR Executive,22580,0 +72249,Male,41,Diploma,10,38,70,37,13,0.0,2,58,Urban,HR Executive,121380,0 +72250,Female,43,Masters,2,25,43,99,63,4.0,4,63,Rural,Data Analyst,76825,0 +72251,Female,25,Bachelors,12,91,12,67,81,1.0,4,30,Urban,Data Analyst,25105,0 +72252,Male,32,Diploma,0,37,98,2,7,3.0,6,11,Rural,Data Analyst,88496,0 +72253,Male,21,Bachelors,14,6,51,93,81,9.0,1,97,Urban,Data Analyst,145886,1 +72254,Male,57,Diploma,18,70,38,72,75,7.0,1,35,Urban,Data Analyst,97841,0 +72255,Male,31,Diploma,12,53,39,42,10,2.0,4,76,Urban,Manager,147775,0 +72256,Female,45,Diploma,5,33,91,17,20,4.0,6,13,Urban,Software Engineer,48043,0 +72257,Male,34,Masters,5,16,86,81,27,6.0,3,71,Urban,ML Engineer,49187,1 +72258,Male,57,Bachelors,13,9,24,7,56,3.0,0,15,Urban,Software Engineer,100113,0 +72259,Female,59,Masters,18,36,28,48,65,5.0,0,69,Semi-Urban,HR Executive,148678,0 +72260,Female,28,Bachelors,2,80,63,76,61,7.0,4,34,Urban,Software Engineer,50268,1 +72261,Male,25,PhD,5,19,98,57,89,6.0,1,81,Urban,Data Analyst,137420,1 +72262,Male,38,Masters,10,19,93,83,96,6.0,6,35,Urban,Data Analyst,65974,0 +72263,Male,53,High School,6,21,63,26,9,9.0,6,59,Urban,Software Engineer,24526,0 +72264,Male,54,Bachelors,0,70,9,53,42,1.0,3,18,Urban,Software Engineer,80583,0 +72265,Male,37,Bachelors,9,62,22,40,67,0.0,3,32,Urban,Software Engineer,133501,0 +72266,Female,21,Bachelors,17,21,83,87,54,5.0,7,27,Urban,ML Engineer,81221,0 +72267,Male,46,Bachelors,19,52,61,55,61,6.0,2,50,Rural,Data Analyst,148270,0 +72268,Female,45,Diploma,15,99,89,41,56,1.0,7,62,Semi-Urban,Data Analyst,105267,1 +72269,Male,42,Diploma,6,51,0,45,1,2.0,6,35,Semi-Urban,Manager,102819,0 +72270,Male,40,Diploma,14,24,42,13,22,1.0,0,50,Urban,ML Engineer,63775,0 +72271,Male,45,Bachelors,13,60,71,78,10,9.0,4,76,Rural,Data Analyst,81013,1 +72272,Male,58,Masters,10,49,47,54,3,2.0,7,96,Urban,HR Executive,86110,1 +72273,Female,27,High School,13,79,11,89,24,1.0,2,47,Semi-Urban,Software Engineer,48411,0 +72274,Male,23,High School,0,60,41,16,33,8.0,0,42,Urban,Software Engineer,40985,0 +72275,Male,28,Bachelors,7,7,29,97,42,6.0,4,83,Rural,HR Executive,148135,0 +72276,Male,55,Diploma,8,5,88,38,45,5.0,1,33,Rural,Manager,29374,0 +72277,Female,48,Bachelors,14,50,63,55,32,3.0,0,58,Urban,HR Executive,36013,0 +72278,Female,25,PhD,3,43,13,82,84,7.0,6,18,Urban,ML Engineer,41658,0 +72279,Female,22,Masters,16,59,1,10,29,6.0,3,64,Semi-Urban,HR Executive,58420,0 +72280,Male,29,Bachelors,14,93,80,69,78,1.0,5,72,Semi-Urban,ML Engineer,82198,1 +72281,Male,41,Bachelors,16,30,90,36,39,4.0,4,39,Rural,Data Analyst,128279,0 +72282,Male,53,High School,19,19,50,30,45,2.0,1,33,Urban,ML Engineer,65446,0 +72283,Female,23,Diploma,13,20,22,70,89,3.0,2,17,Semi-Urban,HR Executive,60790,0 +72284,Other,58,Masters,1,47,1,6,33,9.0,0,11,Rural,HR Executive,131269,0 +72285,Male,34,Bachelors,8,57,99,44,5,4.0,7,14,Rural,Manager,44604,0 +72286,Male,26,Masters,5,65,73,53,84,0.0,5,59,Urban,HR Executive,63406,1 +72287,Male,29,High School,9,38,70,36,14,4.0,4,85,Semi-Urban,Manager,33555,0 +72288,Male,44,High School,6,89,34,3,19,0.0,0,80,Urban,Data Analyst,103772,0 +72289,Male,35,Bachelors,12,35,65,73,16,0.0,4,49,Urban,Data Analyst,87285,0 +72290,Female,42,Masters,14,59,13,51,3,7.0,2,29,Urban,Manager,29661,0 +72291,Male,33,High School,14,53,74,85,41,2.0,6,32,Rural,ML Engineer,133061,1 +72292,Female,33,High School,9,99,91,13,80,7.0,3,65,Rural,Software Engineer,21440,1 +72293,Male,44,Bachelors,2,19,10,12,28,6.0,1,38,Urban,Manager,65372,0 +72294,Female,44,Bachelors,8,77,94,65,22,8.0,2,74,Semi-Urban,Manager,20918,1 +72295,Female,55,Bachelors,11,3,61,35,36,1.0,6,4,Semi-Urban,ML Engineer,63261,0 +72296,Female,52,Bachelors,16,1,54,27,69,0.0,1,19,Urban,ML Engineer,122971,0 +72297,Male,34,Bachelors,1,34,50,40,0,2.0,0,25,Urban,Manager,60392,0 +72298,Female,36,Masters,18,2,41,20,70,0.0,2,29,Semi-Urban,Software Engineer,29113,0 +72299,Female,36,Bachelors,9,10,99,22,20,8.0,3,4,Urban,Manager,68025,0 +72300,Male,34,Bachelors,17,76,50,93,40,9.0,1,81,Rural,HR Executive,99688,1 +72301,Male,55,Diploma,8,19,47,82,12,6.0,2,19,Urban,ML Engineer,140298,0 +72302,Other,52,Diploma,2,17,54,92,99,3.0,6,75,Semi-Urban,HR Executive,40092,0 +72303,Female,47,Masters,11,29,31,73,94,1.0,2,55,Urban,Software Engineer,118702,0 +72304,Male,46,High School,10,93,78,82,18,1.0,7,17,Semi-Urban,ML Engineer,77980,1 +72305,Male,23,Masters,13,28,59,71,82,1.0,0,79,Urban,Software Engineer,132728,1 +72306,Male,59,Masters,18,35,20,35,79,9.0,4,56,Semi-Urban,Data Analyst,146491,0 +72307,Male,54,High School,1,41,5,74,59,0.0,3,27,Rural,Data Analyst,133428,0 +72308,Female,50,Diploma,0,46,40,85,77,9.0,3,0,Urban,Software Engineer,134231,0 +72309,Male,26,Bachelors,5,66,34,9,91,0.0,0,68,Semi-Urban,ML Engineer,53137,0 +72310,Male,38,High School,6,69,77,99,13,8.0,7,45,Semi-Urban,Data Analyst,77681,1 +72311,Male,42,Bachelors,12,1,16,40,2,7.0,6,73,Urban,HR Executive,137127,0 +72312,Female,44,Bachelors,11,33,76,67,89,0.0,0,30,Semi-Urban,Data Analyst,117226,0 +72313,Other,34,Bachelors,3,27,37,10,53,2.0,3,54,Urban,Manager,26717,0 +72314,Male,45,Diploma,6,94,59,39,96,3.0,4,39,Semi-Urban,HR Executive,96179,0 +72315,Female,59,Diploma,11,71,87,22,57,6.0,4,1,Urban,Manager,76000,0 +72316,Other,56,Bachelors,6,79,69,10,46,9.0,1,70,Rural,ML Engineer,117244,0 +72317,Male,36,Bachelors,12,41,83,94,74,7.0,6,2,Urban,ML Engineer,44251,0 +72318,Male,34,Masters,7,86,20,53,14,3.0,3,91,Rural,Data Analyst,136372,1 +72319,Male,27,Diploma,9,36,57,71,16,8.0,2,60,Rural,ML Engineer,77871,0 +72320,Male,52,Bachelors,8,59,75,76,12,7.0,2,40,Urban,ML Engineer,125000,1 +72321,Male,51,Bachelors,16,4,54,81,38,3.0,1,94,Urban,ML Engineer,132937,0 +72322,Female,30,Masters,16,80,49,55,64,2.0,4,49,Urban,Data Analyst,82051,0 +72323,Other,51,High School,16,88,42,55,85,0.0,5,13,Semi-Urban,Data Analyst,25350,0 +72324,Male,53,Diploma,11,47,20,61,59,6.0,6,81,Semi-Urban,Manager,73559,0 +72325,Male,53,Bachelors,7,86,66,42,82,5.0,6,76,Urban,ML Engineer,67759,1 +72326,Male,44,Bachelors,14,23,65,77,80,1.0,4,11,Urban,Software Engineer,92077,0 +72327,Male,24,Masters,17,6,69,97,29,7.0,6,86,Urban,ML Engineer,58816,1 +72328,Male,48,High School,4,79,97,28,83,7.0,5,46,Urban,Data Analyst,63526,1 +72329,Male,22,High School,8,69,75,18,31,1.0,7,64,Semi-Urban,HR Executive,111069,0 +72330,Male,55,Masters,15,61,24,56,72,5.0,4,56,Semi-Urban,Manager,22239,0 +72331,Male,44,Diploma,18,64,47,58,21,4.0,2,56,Rural,ML Engineer,85777,0 +72332,Male,55,Diploma,0,82,69,72,18,1.0,1,75,Urban,Software Engineer,97289,1 +72333,Male,58,High School,5,57,62,41,92,3.0,5,96,Rural,HR Executive,122462,1 +72334,Female,48,Bachelors,10,31,61,13,40,1.0,4,84,Rural,Manager,99910,0 +72335,Male,27,Masters,5,97,92,94,6,8.0,2,62,Rural,HR Executive,65140,1 +72336,Male,29,PhD,0,6,10,91,21,4.0,5,60,Urban,Software Engineer,74137,0 +72337,Male,28,Bachelors,13,92,21,13,3,3.0,4,37,Semi-Urban,ML Engineer,149946,0 +72338,Male,29,Bachelors,6,55,81,6,97,6.0,4,71,Rural,ML Engineer,132857,0 +72339,Male,35,Masters,1,55,59,17,96,1.0,5,51,Urban,HR Executive,98558,0 +72340,Male,25,Bachelors,0,55,89,45,52,3.0,6,79,Urban,ML Engineer,82411,1 +72341,Male,36,Bachelors,5,91,7,69,96,1.0,1,6,Urban,Manager,144848,0 +72342,Male,39,Diploma,18,6,15,26,41,9.0,5,93,Urban,HR Executive,43725,0 +72343,Female,45,Bachelors,6,73,65,11,43,9.0,6,69,Urban,Data Analyst,25096,0 +72344,Female,29,Bachelors,13,84,11,56,37,2.0,2,26,Rural,Data Analyst,22696,0 +72345,Male,46,Bachelors,12,24,45,0,12,4.0,1,63,Urban,ML Engineer,26530,0 +72346,Male,44,High School,3,70,31,63,44,8.0,1,34,Rural,Software Engineer,105854,0 +72347,Male,55,Masters,13,55,94,1,84,5.0,2,4,Rural,Data Analyst,80499,0 +72348,Male,59,Diploma,5,86,5,69,50,6.0,0,1,Urban,Data Analyst,93806,0 +72349,Male,46,High School,1,76,42,56,35,3.0,5,72,Urban,Software Engineer,84434,1 +72350,Male,29,Bachelors,16,60,60,81,95,1.0,3,25,Urban,ML Engineer,48386,0 +72351,Male,32,High School,9,58,41,48,59,6.0,2,63,Rural,Data Analyst,100255,0 +72352,Female,38,Bachelors,14,84,31,29,84,8.0,6,97,Urban,Software Engineer,88234,1 +72353,Male,23,Bachelors,17,19,35,81,60,2.0,4,32,Rural,Data Analyst,59031,0 +72354,Male,35,PhD,5,80,12,48,81,3.0,6,68,Urban,Manager,103812,0 +72355,Male,28,Diploma,12,94,61,96,98,2.0,3,12,Urban,Data Analyst,112599,1 +72356,Male,29,Masters,12,39,29,87,20,7.0,3,16,Rural,Data Analyst,148851,0 +72357,Female,21,PhD,7,0,8,96,65,1.0,7,82,Urban,Software Engineer,35598,0 +72358,Male,48,Bachelors,3,21,30,33,73,5.0,0,15,Urban,Data Analyst,106581,0 +72359,Female,25,Diploma,7,64,56,46,18,5.0,7,70,Rural,ML Engineer,47540,0 +72360,Male,59,Bachelors,6,80,22,72,10,6.0,0,83,Semi-Urban,Data Analyst,27098,1 +72361,Female,43,Masters,1,16,82,60,34,9.0,4,22,Urban,Software Engineer,25446,0 +72362,Male,28,PhD,2,53,1,56,68,9.0,6,66,Urban,ML Engineer,38293,0 +72363,Male,42,High School,18,37,75,53,33,4.0,0,11,Urban,Data Analyst,42879,0 +72364,Female,54,High School,8,86,68,37,19,6.0,1,58,Rural,Data Analyst,44241,1 +72365,Female,27,Bachelors,13,80,26,79,35,9.0,7,49,Rural,Data Analyst,48198,0 +72366,Female,32,High School,11,14,4,6,60,8.0,6,68,Urban,HR Executive,43090,0 +72367,Male,49,High School,6,53,16,52,97,9.0,0,0,Rural,HR Executive,41136,0 +72368,Female,41,Masters,10,9,68,16,21,0.0,4,37,Urban,Data Analyst,145976,0 +72369,Male,51,Bachelors,17,60,58,99,76,3.0,5,9,Urban,Manager,88690,0 +72370,Male,47,Bachelors,8,54,15,85,38,6.0,5,96,Semi-Urban,HR Executive,42346,1 +72371,Male,37,Bachelors,14,92,40,92,61,6.0,1,51,Urban,ML Engineer,70638,1 +72372,Male,22,Bachelors,9,40,43,76,78,2.0,6,12,Urban,Manager,117489,0 +72373,Male,24,Diploma,10,58,14,73,37,1.0,6,27,Semi-Urban,ML Engineer,36251,0 +72374,Male,23,Bachelors,2,4,21,93,72,7.0,7,1,Urban,ML Engineer,113599,0 +72375,Male,44,Bachelors,5,29,10,30,54,8.0,5,61,Semi-Urban,HR Executive,64551,0 +72376,Male,59,Masters,16,82,89,12,49,8.0,0,1,Urban,Manager,50067,0 +72377,Female,32,Bachelors,16,50,81,41,38,4.0,0,84,Urban,Manager,108556,1 +72378,Male,58,High School,2,26,25,58,59,0.0,6,8,Urban,Manager,34725,0 +72379,Male,35,Diploma,6,76,16,32,81,5.0,2,95,Urban,Manager,118386,0 +72380,Male,47,Masters,15,76,37,60,82,0.0,1,61,Urban,Software Engineer,72715,0 +72381,Male,56,Diploma,4,39,19,55,7,9.0,0,84,Rural,HR Executive,34617,0 +72382,Female,59,Bachelors,7,39,77,43,22,7.0,7,18,Urban,HR Executive,32496,0 +72383,Male,50,Masters,11,48,45,99,70,4.0,7,33,Rural,Software Engineer,98521,0 +72384,Male,29,Bachelors,7,80,97,54,79,9.0,4,50,Rural,Software Engineer,74842,1 +72385,Female,56,Masters,16,5,88,41,25,5.0,7,39,Semi-Urban,Data Analyst,89766,0 +72386,Female,40,Bachelors,0,35,86,71,26,8.0,2,86,Semi-Urban,ML Engineer,69578,1 +72387,Female,57,Diploma,18,21,43,4,72,8.0,2,45,Urban,Manager,77327,0 +72388,Female,45,Masters,3,28,5,19,18,2.0,0,29,Rural,Data Analyst,58160,0 +72389,Female,43,Masters,3,80,20,75,46,3.0,4,12,Semi-Urban,HR Executive,41848,0 +72390,Female,23,Bachelors,0,96,62,56,64,4.0,4,9,Urban,HR Executive,105351,0 +72391,Male,42,Diploma,8,14,4,9,53,8.0,1,21,Urban,HR Executive,106880,0 +72392,Female,21,Bachelors,18,28,48,95,85,2.0,1,87,Urban,Data Analyst,125170,1 +72393,Male,31,Diploma,8,71,30,85,11,4.0,7,83,Urban,HR Executive,132630,1 +72394,Female,41,Masters,7,9,49,49,90,6.0,4,31,Urban,HR Executive,130767,0 +72395,Male,52,Bachelors,12,34,21,25,83,7.0,4,8,Urban,Data Analyst,90574,0 +72396,Male,34,High School,9,43,72,66,21,3.0,0,50,Semi-Urban,Data Analyst,138745,0 +72397,Male,47,High School,3,25,65,13,43,5.0,7,53,Urban,ML Engineer,90220,0 +72398,Female,38,Diploma,1,51,55,49,58,6.0,4,73,Rural,Data Analyst,72705,0 +72399,Male,59,Bachelors,19,49,6,30,59,1.0,5,32,Urban,HR Executive,102829,0 +72400,Female,37,Diploma,18,26,68,73,95,6.0,5,17,Urban,Data Analyst,148943,0 +72401,Male,58,Bachelors,5,39,62,71,45,5.0,6,72,Urban,HR Executive,131837,1 +72402,Male,22,High School,18,0,33,24,33,2.0,4,86,Rural,Manager,97922,0 +72403,Male,57,Masters,19,53,97,59,78,7.0,6,85,Semi-Urban,Software Engineer,127486,1 +72404,Male,28,Bachelors,17,17,37,88,63,5.0,0,34,Rural,Data Analyst,69547,0 +72405,Male,33,Diploma,19,22,66,96,89,4.0,0,22,Rural,ML Engineer,59447,0 +72406,Male,37,Masters,12,4,51,53,46,7.0,6,48,Urban,ML Engineer,52955,0 +72407,Male,39,High School,12,45,41,63,45,9.0,1,88,Urban,ML Engineer,96658,1 +72408,Female,57,PhD,4,7,78,60,0,6.0,0,61,Urban,ML Engineer,110157,0 +72409,Male,36,Bachelors,10,80,37,44,28,5.0,7,4,Semi-Urban,Software Engineer,48008,0 +72410,Female,42,Bachelors,18,4,60,95,36,0.0,5,78,Urban,Software Engineer,20883,0 +72411,Male,43,Masters,14,67,94,48,3,8.0,2,87,Rural,ML Engineer,133095,1 +72412,Female,42,Bachelors,1,16,15,97,95,5.0,3,13,Urban,Manager,39240,0 +72413,Female,21,Diploma,2,49,93,74,45,3.0,2,41,Rural,Data Analyst,116603,1 +72414,Female,51,Bachelors,4,82,41,73,2,7.0,6,61,Urban,Manager,21953,1 +72415,Male,44,Bachelors,18,28,11,59,15,7.0,2,75,Urban,Manager,105120,0 +72416,Female,59,Masters,7,63,52,54,12,1.0,0,87,Semi-Urban,Manager,97003,1 +72417,Male,38,Bachelors,10,44,94,61,40,4.0,2,23,Urban,Manager,80623,0 +72418,Female,49,High School,9,70,47,3,25,8.0,3,26,Urban,Software Engineer,118231,0 +72419,Female,44,Diploma,4,4,62,85,89,1.0,0,25,Rural,Software Engineer,79148,0 +72420,Other,46,High School,10,96,43,27,34,2.0,3,54,Urban,ML Engineer,143867,0 +72421,Male,43,Bachelors,15,21,53,22,78,2.0,0,37,Semi-Urban,Software Engineer,124631,0 +72422,Male,27,Bachelors,17,29,43,84,47,5.0,2,45,Semi-Urban,Manager,108828,0 +72423,Male,32,Bachelors,19,39,67,57,39,4.0,3,13,Semi-Urban,Manager,126599,0 +72424,Female,41,High School,14,84,23,39,70,4.0,5,59,Urban,Data Analyst,144169,0 +72425,Male,41,Bachelors,9,34,90,67,68,0.0,5,23,Rural,Software Engineer,42237,0 +72426,Male,58,High School,16,68,23,12,75,5.0,0,50,Urban,ML Engineer,136175,0 +72427,Male,59,Bachelors,14,57,20,28,81,5.0,7,60,Semi-Urban,ML Engineer,76606,0 +72428,Male,36,Bachelors,18,89,82,64,20,6.0,1,21,Urban,ML Engineer,110137,1 +72429,Male,36,Bachelors,0,5,66,28,49,7.0,0,9,Urban,ML Engineer,39584,0 +72430,Female,58,Masters,13,41,67,20,13,6.0,4,87,Urban,Software Engineer,106043,0 +72431,Male,55,Bachelors,16,42,3,4,22,0.0,2,24,Rural,Data Analyst,57876,0 +72432,Male,46,Bachelors,7,31,25,86,75,0.0,5,7,Rural,Software Engineer,85751,0 +72433,Male,34,Bachelors,19,11,11,59,28,5.0,5,41,Rural,Software Engineer,39934,0 +72434,Female,22,Bachelors,19,52,54,34,0,1.0,3,66,Urban,ML Engineer,72497,0 +72435,Female,38,Diploma,17,46,77,71,15,3.0,4,35,Urban,Manager,107461,0 +72436,Female,44,Masters,2,88,52,18,18,0.0,3,81,Urban,Data Analyst,94065,0 +72437,Female,35,Bachelors,2,63,33,38,87,6.0,1,2,Semi-Urban,Data Analyst,35047,0 +72438,Female,21,Bachelors,4,14,85,72,82,8.0,5,14,Urban,ML Engineer,78687,0 +72439,Male,49,Bachelors,2,11,15,54,0,4.0,4,15,Semi-Urban,Manager,80926,0 +72440,Female,52,Masters,18,80,76,68,72,9.0,5,26,Rural,HR Executive,122734,1 +72441,Male,27,Bachelors,0,79,95,6,41,3.0,7,84,Semi-Urban,Software Engineer,103633,1 +72442,Male,42,Bachelors,1,4,33,75,76,2.0,6,13,Urban,Data Analyst,120980,0 +72443,Male,21,High School,11,62,71,27,10,2.0,4,10,Urban,Data Analyst,82412,0 +72444,Male,23,Bachelors,10,6,76,59,24,1.0,6,87,Semi-Urban,Data Analyst,75425,0 +72445,Male,37,Bachelors,1,5,29,64,18,8.0,7,80,Urban,Data Analyst,73312,0 +72446,Female,51,Diploma,13,0,68,75,26,9.0,1,94,Rural,Manager,122384,0 +72447,Male,23,Masters,19,87,36,14,76,0.0,2,30,Urban,HR Executive,42587,0 +72448,Female,48,High School,3,63,73,28,91,2.0,2,32,Urban,Manager,52911,0 +72449,Female,46,Bachelors,19,30,20,18,23,8.0,1,62,Rural,Data Analyst,83608,0 +72450,Male,25,Diploma,1,28,72,51,95,7.0,0,9,Urban,Data Analyst,25315,0 +72451,Male,56,Diploma,0,16,21,99,3,2.0,5,57,Rural,HR Executive,24380,0 +72452,Male,38,Bachelors,10,94,38,61,3,8.0,4,79,Rural,Manager,41107,1 +72453,Male,58,PhD,13,73,46,23,29,9.0,5,74,Urban,Manager,139261,0 +72454,Female,58,High School,3,43,26,34,61,0.0,3,60,Urban,HR Executive,24062,0 +72455,Male,45,High School,19,3,4,57,65,0.0,1,69,Semi-Urban,Data Analyst,136464,0 +72456,Male,23,Diploma,10,99,14,56,33,8.0,3,80,Rural,ML Engineer,145611,1 +72457,Female,45,Diploma,17,93,70,33,31,1.0,5,30,Urban,Manager,112165,0 +72458,Other,59,High School,11,44,74,84,68,9.0,6,48,Semi-Urban,Manager,64670,1 +72459,Male,32,Masters,9,32,12,19,76,4.0,7,27,Rural,ML Engineer,106176,0 +72460,Female,41,Bachelors,19,20,31,4,95,3.0,0,90,Rural,ML Engineer,86572,0 +72461,Male,52,High School,2,35,45,7,44,9.0,4,61,Urban,HR Executive,110889,0 +72462,Female,29,Diploma,16,56,29,27,54,0.0,2,29,Rural,ML Engineer,39988,0 +72463,Male,40,Masters,1,51,10,47,34,4.0,3,10,Urban,Software Engineer,82302,0 +72464,Other,35,Bachelors,8,22,54,22,48,6.0,3,70,Urban,Software Engineer,132846,0 +72465,Male,54,PhD,17,10,37,5,60,3.0,2,69,Semi-Urban,Manager,115926,0 +72466,Other,32,Bachelors,8,56,20,93,73,1.0,3,30,Urban,Software Engineer,29710,0 +72467,Female,57,PhD,17,46,50,70,45,0.0,3,78,Rural,HR Executive,81252,1 +72468,Female,51,Bachelors,3,38,95,25,87,1.0,5,84,Semi-Urban,ML Engineer,121802,1 +72469,Female,52,Masters,4,80,46,84,23,6.0,6,22,Rural,Data Analyst,79357,0 +72470,Female,58,Bachelors,15,66,9,30,53,3.0,5,40,Rural,Data Analyst,40247,0 +72471,Female,24,Masters,18,21,10,5,41,0.0,2,8,Urban,ML Engineer,89226,0 +72472,Female,53,Bachelors,11,24,87,89,72,9.0,5,28,Urban,Manager,49889,0 +72473,Male,39,Bachelors,16,77,60,18,82,1.0,1,73,Semi-Urban,Software Engineer,116543,0 +72474,Female,27,Bachelors,3,43,97,19,47,8.0,0,41,Urban,Manager,52989,0 +72475,Male,59,Masters,0,53,56,39,69,7.0,2,80,Semi-Urban,HR Executive,35929,0 +72476,Female,21,Bachelors,4,62,7,65,69,3.0,7,46,Semi-Urban,Software Engineer,54944,0 +72477,Female,21,Masters,4,9,90,13,94,4.0,5,75,Semi-Urban,Software Engineer,63067,0 +72478,Female,59,Bachelors,14,48,53,56,13,8.0,5,41,Urban,Manager,63339,0 +72479,Female,31,PhD,1,80,59,69,70,2.0,3,27,Urban,HR Executive,122415,0 +72480,Male,51,Diploma,16,85,98,66,12,1.0,7,54,Semi-Urban,Data Analyst,88129,1 +72481,Female,27,Diploma,16,5,27,78,1,1.0,7,25,Urban,Data Analyst,90879,0 +72482,Male,31,Bachelors,16,30,36,68,74,1.0,5,88,Urban,Manager,93245,0 +72483,Male,52,Masters,6,14,17,40,11,3.0,3,55,Urban,HR Executive,76043,0 +72484,Female,54,Bachelors,10,47,88,22,76,1.0,2,80,Urban,Software Engineer,51365,0 +72485,Female,29,Bachelors,9,6,41,60,52,9.0,7,67,Urban,Data Analyst,103886,0 +72486,Female,38,Masters,8,5,73,62,65,6.0,0,10,Urban,ML Engineer,22127,0 +72487,Female,39,Bachelors,1,0,19,87,99,7.0,2,10,Urban,Software Engineer,125210,0 +72488,Male,40,Bachelors,2,7,10,18,88,8.0,3,42,Rural,ML Engineer,143267,0 +72489,Male,52,Bachelors,18,74,86,32,32,9.0,2,16,Rural,Data Analyst,63714,0 +72490,Male,27,Bachelors,16,60,58,90,53,1.0,7,85,Rural,Software Engineer,34887,1 +72491,Male,52,Masters,13,42,88,61,63,5.0,1,66,Urban,Manager,114279,1 +72492,Male,37,Bachelors,15,64,68,25,9,4.0,5,53,Urban,Manager,29426,0 +72493,Female,40,Bachelors,2,5,23,93,79,0.0,3,17,Semi-Urban,Software Engineer,81567,0 +72494,Male,29,Bachelors,18,43,57,93,81,8.0,2,35,Urban,Manager,116419,0 +72495,Female,21,PhD,10,95,14,79,8,1.0,7,5,Urban,Manager,106918,0 +72496,Male,25,Masters,18,98,39,62,20,3.0,0,21,Urban,ML Engineer,75394,0 +72497,Female,30,Bachelors,9,96,88,24,87,9.0,5,2,Urban,Manager,91366,0 +72498,Male,56,Bachelors,10,15,8,56,2,5.0,1,35,Urban,Software Engineer,36900,0 +72499,Female,23,Masters,19,51,75,18,54,2.0,4,55,Rural,Data Analyst,64112,0 +72500,Male,21,Bachelors,10,9,1,92,49,2.0,0,43,Urban,Data Analyst,52133,0 +72501,Female,47,Diploma,0,51,13,12,64,5.0,2,18,Urban,Manager,104319,0 +72502,Female,54,Bachelors,3,11,64,54,24,8.0,4,80,Rural,Manager,129824,0 +72503,Female,39,Diploma,0,74,35,38,75,7.0,3,69,Urban,ML Engineer,109752,0 +72504,Male,27,Diploma,10,14,84,82,64,8.0,1,55,Rural,Software Engineer,32599,1 +72505,Female,23,Masters,5,62,28,78,65,1.0,6,63,Urban,Manager,108087,0 +72506,Female,32,Diploma,7,65,13,75,2,9.0,2,87,Urban,Data Analyst,69513,0 +72507,Female,29,Bachelors,12,52,53,42,58,6.0,1,63,Rural,Manager,129071,0 +72508,Male,21,Bachelors,12,75,41,66,29,6.0,5,16,Semi-Urban,Data Analyst,64111,0 +72509,Female,39,High School,0,0,84,72,93,4.0,5,79,Rural,Manager,85114,0 +72510,Male,56,High School,12,92,65,22,6,9.0,4,13,Urban,HR Executive,135281,0 +72511,Male,34,Bachelors,5,92,48,84,7,5.0,2,98,Urban,Software Engineer,24050,1 +72512,Female,34,Bachelors,9,75,3,90,79,6.0,2,62,Urban,Software Engineer,98319,0 +72513,Female,44,Masters,16,50,68,95,25,4.0,2,4,Urban,Data Analyst,32961,0 +72514,Male,35,High School,6,57,30,53,39,1.0,7,8,Rural,Manager,101974,0 +72515,Male,33,Diploma,13,4,18,67,92,0.0,0,84,Urban,ML Engineer,134092,0 +72516,Female,35,Bachelors,11,52,37,95,67,1.0,0,30,Rural,ML Engineer,72344,0 +72517,Female,23,Bachelors,12,72,41,47,91,0.0,5,4,Urban,Software Engineer,20558,0 +72518,Female,31,Bachelors,13,14,85,62,37,2.0,6,45,Semi-Urban,Software Engineer,136741,0 +72519,Female,23,Diploma,6,44,1,91,14,5.0,2,58,Urban,HR Executive,133157,0 +72520,Male,40,PhD,19,66,7,77,75,7.0,5,27,Urban,ML Engineer,146985,0 +72521,Male,41,High School,7,94,95,74,89,8.0,0,99,Urban,Manager,127822,1 +72522,Male,35,Bachelors,14,1,87,81,16,7.0,2,83,Urban,ML Engineer,40359,1 +72523,Male,42,Bachelors,9,4,57,42,3,7.0,3,8,Urban,Data Analyst,128870,0 +72524,Male,34,Bachelors,2,62,71,82,77,5.0,1,12,Rural,Software Engineer,127100,0 +72525,Male,28,Bachelors,9,57,9,75,85,3.0,3,6,Urban,ML Engineer,26561,0 +72526,Male,35,Bachelors,14,64,40,74,19,5.0,6,78,Rural,ML Engineer,116912,1 +72527,Female,21,Bachelors,18,88,1,92,97,4.0,3,83,Urban,ML Engineer,45483,1 +72528,Male,22,Masters,4,78,58,98,2,1.0,7,59,Semi-Urban,ML Engineer,119267,1 +72529,Male,49,Masters,17,35,38,84,99,6.0,3,51,Urban,Software Engineer,123404,0 +72530,Male,36,High School,12,26,3,95,96,0.0,7,63,Rural,HR Executive,38314,0 +72531,Male,40,Diploma,5,46,18,24,7,0.0,5,9,Urban,ML Engineer,89159,0 +72532,Female,32,Diploma,3,49,50,17,18,1.0,7,5,Rural,Manager,66091,0 +72533,Male,54,PhD,5,78,30,85,83,0.0,2,23,Urban,ML Engineer,84680,0 +72534,Male,50,Masters,19,98,56,88,17,3.0,0,63,Semi-Urban,Manager,127846,1 +72535,Female,49,Masters,14,24,47,49,81,6.0,5,8,Urban,Data Analyst,91876,0 +72536,Male,54,Bachelors,14,93,47,34,36,4.0,2,88,Urban,Data Analyst,131341,1 +72537,Female,49,Masters,12,90,47,8,66,9.0,0,27,Semi-Urban,Software Engineer,147913,0 +72538,Male,53,Bachelors,1,48,94,46,97,9.0,4,55,Urban,HR Executive,43228,1 +72539,Male,42,PhD,16,40,14,70,60,6.0,6,97,Urban,Data Analyst,50551,0 +72540,Male,37,High School,10,80,81,71,44,9.0,1,10,Urban,Manager,58191,1 +72541,Male,37,Diploma,2,57,9,80,28,1.0,6,63,Rural,Software Engineer,38732,0 +72542,Male,57,Bachelors,1,64,87,69,30,5.0,2,70,Semi-Urban,Manager,86313,1 +72543,Male,46,Diploma,8,63,35,21,60,6.0,1,55,Urban,Software Engineer,83438,0 +72544,Male,32,High School,0,47,24,21,62,6.0,0,7,Urban,ML Engineer,60726,0 +72545,Female,24,Bachelors,0,63,3,8,81,8.0,5,86,Urban,HR Executive,56501,0 +72546,Male,43,Bachelors,18,19,93,90,12,3.0,1,73,Urban,HR Executive,84895,1 +72547,Male,43,High School,11,53,83,12,22,8.0,2,12,Rural,ML Engineer,139698,0 +72548,Other,27,Diploma,12,98,96,70,58,5.0,3,98,Semi-Urban,HR Executive,121623,1 +72549,Male,58,Bachelors,18,11,74,33,14,9.0,5,58,Semi-Urban,HR Executive,93013,0 +72550,Male,51,High School,15,55,17,82,32,2.0,1,79,Rural,Manager,120776,0 +72551,Female,40,Bachelors,10,69,94,39,23,4.0,1,99,Urban,Data Analyst,109871,1 +72552,Male,31,Diploma,7,23,64,9,18,5.0,5,45,Semi-Urban,Data Analyst,88371,0 +72553,Female,52,Bachelors,6,78,54,50,40,0.0,0,25,Urban,Manager,103462,0 +72554,Male,30,High School,16,8,63,82,72,2.0,2,24,Urban,Data Analyst,44285,0 +72555,Male,24,Masters,16,89,53,7,96,7.0,1,25,Urban,Software Engineer,145730,0 +72556,Male,49,Diploma,16,25,26,22,57,5.0,3,46,Rural,Data Analyst,130454,0 +72557,Female,56,Bachelors,1,78,4,8,15,9.0,6,73,Urban,ML Engineer,25169,0 +72558,Male,51,Bachelors,16,68,16,10,72,7.0,0,77,Urban,HR Executive,110617,0 +72559,Male,33,Diploma,18,76,45,27,22,5.0,7,35,Urban,Data Analyst,109070,0 +72560,Other,45,Diploma,17,3,40,71,33,5.0,0,30,Urban,Data Analyst,61537,0 +72561,Male,56,High School,3,85,39,44,64,0.0,0,49,Urban,ML Engineer,136363,0 +72562,Female,34,PhD,19,89,40,4,82,7.0,5,70,Semi-Urban,Data Analyst,107447,0 +72563,Female,28,High School,15,84,22,59,50,1.0,1,79,Urban,Software Engineer,86068,1 +72564,Male,33,Bachelors,4,44,99,2,91,3.0,1,0,Rural,Manager,105193,0 +72565,Male,38,High School,11,38,19,18,61,2.0,3,60,Semi-Urban,ML Engineer,83835,0 +72566,Other,53,High School,15,24,67,84,42,6.0,0,18,Urban,Data Analyst,99674,0 +72567,Female,36,Bachelors,1,69,93,37,30,6.0,1,61,Semi-Urban,Software Engineer,108842,1 +72568,Male,26,Masters,7,70,7,50,24,7.0,4,57,Rural,Data Analyst,147485,0 +72569,Male,28,Bachelors,16,56,88,56,2,1.0,6,66,Semi-Urban,Software Engineer,29825,1 +72570,Male,41,Diploma,12,62,89,39,52,3.0,5,62,Urban,Data Analyst,75902,1 +72571,Female,26,Bachelors,1,41,48,74,40,1.0,5,92,Urban,Software Engineer,106823,1 +72572,Male,30,Bachelors,10,32,32,2,67,7.0,5,2,Semi-Urban,HR Executive,117747,0 +72573,Male,47,High School,14,6,70,90,80,9.0,4,98,Urban,ML Engineer,146817,1 +72574,Male,43,Bachelors,18,28,23,40,71,1.0,7,74,Semi-Urban,HR Executive,137018,0 +72575,Male,24,High School,6,95,15,83,3,9.0,6,96,Rural,Manager,61302,1 +72576,Female,31,Bachelors,12,64,90,78,39,1.0,4,67,Semi-Urban,Manager,21763,1 +72577,Female,46,Diploma,16,55,79,89,7,4.0,1,65,Semi-Urban,Data Analyst,27924,1 +72578,Male,40,Masters,16,24,69,66,45,4.0,3,33,Rural,ML Engineer,31205,0 +72579,Male,26,Bachelors,19,84,32,47,30,0.0,3,17,Semi-Urban,Data Analyst,52754,0 +72580,Female,58,Bachelors,6,60,37,79,67,2.0,1,97,Rural,Manager,72272,1 +72581,Female,58,Masters,15,19,91,5,22,2.0,4,67,Rural,ML Engineer,23739,0 +72582,Female,42,Bachelors,14,86,0,84,7,1.0,3,17,Semi-Urban,ML Engineer,120317,0 +72583,Male,49,Masters,11,81,77,16,84,3.0,5,23,Urban,Manager,51345,0 +72584,Male,46,Bachelors,13,58,83,99,4,5.0,0,66,Rural,ML Engineer,58924,1 +72585,Male,37,Diploma,0,6,65,6,65,9.0,4,94,Urban,Software Engineer,119403,0 +72586,Female,47,Bachelors,1,25,44,15,13,7.0,7,29,Urban,Manager,54812,0 +72587,Male,57,High School,18,69,39,17,92,7.0,6,42,Semi-Urban,Manager,91190,0 +72588,Female,58,Masters,12,71,50,31,75,7.0,7,75,Urban,Data Analyst,65774,0 +72589,Male,40,Bachelors,8,85,42,97,18,9.0,2,71,Urban,Data Analyst,148092,1 +72590,Male,57,Bachelors,6,51,86,52,77,6.0,5,61,Urban,Data Analyst,85298,1 +72591,Male,50,Bachelors,6,87,29,1,67,0.0,5,87,Semi-Urban,ML Engineer,21413,0 +72592,Male,38,Bachelors,3,99,22,71,73,0.0,4,22,Urban,Software Engineer,129789,0 +72593,Female,58,Diploma,1,73,63,73,92,7.0,5,94,Urban,Manager,115594,1 +72594,Male,25,Diploma,13,48,45,1,82,8.0,5,28,Urban,Data Analyst,74279,0 +72595,Male,35,Bachelors,13,68,69,47,10,1.0,0,96,Semi-Urban,ML Engineer,101920,1 +72596,Male,58,Bachelors,2,7,12,89,42,9.0,7,34,Rural,ML Engineer,22717,0 +72597,Male,51,Masters,12,3,23,79,69,8.0,7,54,Urban,HR Executive,54810,0 +72598,Male,37,High School,6,45,70,77,46,5.0,4,66,Semi-Urban,Manager,44031,1 +72599,Male,35,Bachelors,6,82,79,90,75,7.0,0,67,Semi-Urban,Software Engineer,125781,1 +72600,Male,34,Bachelors,16,80,56,14,44,9.0,5,33,Urban,Data Analyst,93390,0 +72601,Male,40,Diploma,1,58,50,65,6,7.0,2,35,Urban,Manager,61691,0 +72602,Other,57,Diploma,15,95,23,96,57,7.0,6,17,Urban,Manager,106575,0 +72603,Male,21,Bachelors,1,67,37,88,11,2.0,7,22,Semi-Urban,Manager,53549,0 +72604,Female,33,High School,4,55,8,83,25,2.0,7,38,Urban,ML Engineer,142783,0 +72605,Female,49,Bachelors,6,25,69,31,64,0.0,4,14,Urban,Manager,52078,0 +72606,Female,21,Bachelors,19,37,84,56,3,4.0,0,41,Rural,Data Analyst,40803,0 +72607,Male,36,High School,4,91,5,55,93,6.0,7,53,Semi-Urban,HR Executive,52977,0 +72608,Male,34,High School,7,91,44,10,89,7.0,7,21,Urban,Software Engineer,85635,0 +72609,Male,30,High School,4,3,13,23,62,7.0,0,4,Urban,Manager,63595,0 +72610,Male,42,High School,3,93,27,49,52,6.0,1,5,Urban,Data Analyst,71203,0 +72611,Male,28,Bachelors,14,13,62,74,84,2.0,3,47,Urban,Software Engineer,28871,0 +72612,Male,57,High School,6,3,49,57,11,5.0,5,15,Urban,Manager,104166,0 +72613,Female,49,Bachelors,4,97,23,96,92,4.0,4,86,Urban,Manager,87430,1 +72614,Male,40,High School,16,24,69,31,68,5.0,1,82,Urban,ML Engineer,139479,0 +72615,Female,27,Diploma,11,50,67,50,56,7.0,5,13,Urban,ML Engineer,48104,0 +72616,Male,34,Diploma,9,23,88,54,22,8.0,1,68,Rural,ML Engineer,72352,0 +72617,Female,53,Bachelors,10,96,34,10,46,9.0,4,6,Rural,Manager,120482,0 +72618,Female,54,Bachelors,2,99,27,10,72,8.0,4,58,Urban,Manager,25854,0 +72619,Male,53,PhD,6,45,77,97,46,8.0,4,28,Rural,ML Engineer,89556,1 +72620,Female,38,Bachelors,12,26,22,15,24,6.0,3,6,Semi-Urban,ML Engineer,118708,0 +72621,Male,38,Bachelors,10,66,95,8,72,5.0,3,85,Rural,HR Executive,145561,1 +72622,Other,32,Bachelors,2,1,42,24,41,0.0,6,43,Rural,Software Engineer,144782,0 +72623,Male,57,Bachelors,7,30,73,96,77,5.0,0,87,Urban,Data Analyst,23332,1 +72624,Female,34,Bachelors,4,78,11,8,21,3.0,5,62,Semi-Urban,Software Engineer,100780,0 +72625,Male,36,Bachelors,0,63,75,27,69,6.0,6,70,Rural,Data Analyst,136700,1 +72626,Male,45,Bachelors,0,76,2,0,78,5.0,3,58,Semi-Urban,ML Engineer,73670,0 +72627,Male,57,Masters,8,55,46,64,48,9.0,6,79,Semi-Urban,ML Engineer,98072,1 +72628,Male,21,Masters,1,44,66,54,91,5.0,5,21,Urban,Data Analyst,75372,0 +72629,Male,35,Diploma,12,6,40,28,64,4.0,6,0,Urban,Software Engineer,118339,0 +72630,Female,45,Masters,3,54,80,59,23,5.0,2,98,Semi-Urban,Software Engineer,117298,1 +72631,Female,48,Diploma,15,60,30,38,96,0.0,7,50,Urban,HR Executive,65756,0 +72632,Male,44,Bachelors,14,6,76,23,88,8.0,2,18,Rural,Data Analyst,73269,0 +72633,Male,47,Bachelors,10,24,40,1,67,9.0,6,54,Rural,Manager,20769,0 +72634,Male,46,Diploma,13,14,94,87,26,4.0,3,43,Rural,Manager,37960,1 +72635,Male,47,Bachelors,0,15,23,77,97,5.0,7,79,Rural,HR Executive,93982,0 +72636,Male,41,Bachelors,17,71,80,45,30,6.0,0,13,Rural,Data Analyst,46471,0 +72637,Female,52,Bachelors,8,83,39,77,28,1.0,1,3,Semi-Urban,Manager,119017,0 +72638,Female,44,Diploma,1,32,45,43,26,9.0,3,14,Urban,Data Analyst,114310,0 +72639,Male,21,Bachelors,1,76,69,77,75,8.0,6,23,Urban,ML Engineer,42007,1 +72640,Female,34,Bachelors,3,27,69,58,85,0.0,4,22,Urban,HR Executive,73732,0 +72641,Other,24,Bachelors,6,46,96,48,49,3.0,2,68,Rural,Software Engineer,89900,1 +72642,Female,24,Diploma,5,57,13,53,53,9.0,7,85,Rural,Data Analyst,91485,0 +72643,Female,36,Bachelors,12,42,77,59,54,4.0,0,59,Urban,Data Analyst,117815,0 +72644,Male,40,Masters,7,45,13,51,55,2.0,0,48,Semi-Urban,Manager,89633,0 +72645,Male,52,Masters,5,83,7,19,53,7.0,4,57,Urban,Software Engineer,40273,0 +72646,Male,58,Bachelors,19,93,23,89,62,6.0,3,74,Rural,Software Engineer,65957,1 +72647,Male,53,Masters,2,48,46,37,56,4.0,7,27,Urban,ML Engineer,121075,0 +72648,Female,33,Diploma,14,17,74,12,22,8.0,4,17,Semi-Urban,Data Analyst,147475,0 +72649,Other,37,Diploma,8,24,13,28,48,5.0,2,91,Semi-Urban,HR Executive,87533,0 +72650,Male,48,Bachelors,7,1,37,6,52,6.0,0,7,Urban,Data Analyst,125589,0 +72651,Male,47,Bachelors,11,45,11,60,73,1.0,2,77,Urban,Software Engineer,148970,0 +72652,Male,37,Diploma,0,27,44,27,56,4.0,6,12,Urban,Data Analyst,91670,0 +72653,Female,29,PhD,7,15,89,65,13,1.0,6,39,Urban,Software Engineer,94172,0 +72654,Male,49,Masters,3,82,99,34,82,2.0,1,43,Urban,Manager,103665,1 +72655,Male,22,Masters,6,38,68,45,45,4.0,2,30,Rural,Software Engineer,72764,0 +72656,Male,47,Bachelors,15,12,33,18,56,1.0,3,13,Rural,Data Analyst,67344,0 +72657,Female,51,Bachelors,18,41,24,9,82,7.0,3,46,Rural,HR Executive,41259,0 +72658,Male,46,Bachelors,9,61,43,0,50,1.0,6,70,Urban,Software Engineer,24948,0 +72659,Female,31,Masters,13,4,5,16,4,2.0,0,56,Urban,HR Executive,61583,0 +72660,Male,30,Masters,2,79,4,73,77,3.0,0,92,Semi-Urban,ML Engineer,91675,1 +72661,Female,59,Bachelors,12,30,91,82,8,9.0,6,83,Urban,HR Executive,126034,1 +72662,Male,31,Bachelors,2,34,98,51,91,8.0,4,45,Semi-Urban,Software Engineer,117937,0 +72663,Female,47,Bachelors,10,47,29,55,85,5.0,0,5,Urban,Software Engineer,77952,0 +72664,Female,39,Bachelors,6,7,36,83,36,4.0,0,0,Urban,HR Executive,61263,0 +72665,Male,36,Bachelors,17,95,44,70,72,8.0,1,13,Urban,Data Analyst,29326,0 +72666,Male,45,High School,12,94,90,40,32,4.0,6,18,Urban,Data Analyst,109286,1 +72667,Male,48,Bachelors,12,66,98,1,78,5.0,7,20,Semi-Urban,Manager,27617,0 +72668,Male,57,Bachelors,11,96,90,37,58,6.0,0,52,Rural,HR Executive,39047,1 +72669,Female,41,Bachelors,1,74,13,95,26,0.0,0,47,Rural,Data Analyst,28343,0 +72670,Other,59,Bachelors,1,58,26,33,9,4.0,0,86,Semi-Urban,HR Executive,124639,0 +72671,Female,51,High School,0,92,46,50,94,1.0,6,57,Urban,Software Engineer,103850,1 +72672,Male,32,High School,1,38,35,7,44,4.0,3,71,Rural,Manager,133731,0 +72673,Male,39,Masters,17,14,2,49,33,5.0,2,82,Urban,Data Analyst,61081,0 +72674,Female,34,Diploma,4,86,6,64,62,2.0,5,5,Urban,HR Executive,69632,0 +72675,Other,50,High School,8,41,80,12,18,6.0,3,96,Rural,Data Analyst,29026,0 +72676,Male,53,PhD,3,5,46,64,97,2.0,4,22,Urban,Software Engineer,137479,0 +72677,Male,53,Bachelors,2,39,65,56,11,7.0,7,33,Semi-Urban,HR Executive,72806,0 +72678,Male,45,High School,15,38,26,96,49,8.0,1,52,Rural,HR Executive,54422,0 +72679,Male,49,High School,17,90,24,9,70,6.0,7,44,Semi-Urban,HR Executive,68904,0 +72680,Male,43,PhD,12,10,31,62,13,1.0,7,52,Semi-Urban,Data Analyst,99430,0 +72681,Male,58,Masters,17,8,56,19,97,6.0,4,17,Urban,HR Executive,87790,0 +72682,Male,27,Diploma,13,6,92,28,98,6.0,1,0,Urban,ML Engineer,28244,0 +72683,Male,34,PhD,3,93,38,77,45,0.0,7,76,Semi-Urban,HR Executive,137715,1 +72684,Male,41,Masters,2,31,68,52,14,6.0,4,9,Rural,Software Engineer,31100,0 +72685,Female,51,High School,11,89,62,69,73,7.0,2,73,Urban,Software Engineer,129182,1 +72686,Male,23,Masters,16,79,83,31,18,6.0,4,65,Semi-Urban,Data Analyst,100602,1 +72687,Female,59,Diploma,3,11,25,2,3,7.0,0,40,Semi-Urban,ML Engineer,66510,0 +72688,Male,38,PhD,17,15,2,91,25,7.0,6,87,Semi-Urban,HR Executive,25066,0 +72689,Male,36,Bachelors,11,59,40,25,64,7.0,5,81,Semi-Urban,Data Analyst,116619,0 +72690,Other,35,Bachelors,4,71,46,24,65,5.0,1,5,Urban,HR Executive,43854,0 +72691,Female,22,PhD,13,71,90,85,44,0.0,3,3,Urban,HR Executive,96415,1 +72692,Female,47,High School,17,89,77,3,96,9.0,6,41,Urban,HR Executive,86271,0 +72693,Female,45,Diploma,17,36,48,4,7,9.0,6,35,Urban,Software Engineer,54531,0 +72694,Male,46,Bachelors,0,0,98,64,10,5.0,1,24,Urban,ML Engineer,121656,0 +72695,Female,25,High School,5,52,34,15,72,2.0,2,17,Semi-Urban,ML Engineer,113658,0 +72696,Male,56,Diploma,18,9,87,91,26,7.0,1,54,Semi-Urban,HR Executive,23026,1 +72697,Female,59,Bachelors,11,81,0,68,78,9.0,2,42,Rural,ML Engineer,119762,0 +72698,Male,56,High School,1,37,19,37,98,9.0,7,66,Urban,Software Engineer,52745,0 +72699,Female,53,Diploma,4,86,26,12,84,5.0,3,74,Urban,Data Analyst,52102,0 +72700,Female,34,High School,19,85,71,67,41,7.0,2,54,Rural,Data Analyst,105431,1 +72701,Female,50,Bachelors,17,62,33,61,10,8.0,2,55,Urban,Software Engineer,25132,0 +72702,Male,25,High School,4,42,17,64,6,1.0,4,88,Urban,Data Analyst,69405,0 +72703,Male,54,Bachelors,11,56,45,82,93,4.0,6,31,Urban,HR Executive,140223,0 +72704,Female,24,Masters,7,90,41,13,10,3.0,0,43,Semi-Urban,Software Engineer,147572,0 +72705,Male,47,Bachelors,16,66,53,91,33,5.0,4,81,Rural,Manager,92935,1 +72706,Male,36,High School,18,87,67,43,37,6.0,6,9,Semi-Urban,Data Analyst,99513,0 +72707,Male,32,Bachelors,8,71,35,84,70,9.0,0,94,Urban,Software Engineer,79877,1 +72708,Male,48,Masters,11,31,88,48,34,9.0,5,20,Urban,ML Engineer,45609,0 +72709,Female,32,Bachelors,6,8,20,93,34,2.0,7,16,Rural,Manager,121826,0 +72710,Female,32,Masters,10,47,94,37,57,5.0,1,88,Urban,Software Engineer,114144,1 +72711,Male,49,Bachelors,5,7,3,75,87,7.0,1,3,Urban,HR Executive,128451,0 +72712,Female,56,Masters,15,73,99,58,17,9.0,2,11,Urban,Software Engineer,40785,1 +72713,Male,53,Diploma,14,90,63,37,41,0.0,3,5,Semi-Urban,Software Engineer,71202,0 +72714,Female,56,High School,1,26,21,2,49,6.0,2,37,Urban,Software Engineer,45612,0 +72715,Female,25,Bachelors,11,62,84,89,65,1.0,4,72,Urban,Data Analyst,71295,1 +72716,Female,23,Masters,14,86,37,76,10,3.0,1,37,Rural,Software Engineer,80537,0 +72717,Male,23,Masters,5,91,78,44,88,1.0,4,97,Semi-Urban,Data Analyst,48929,1 +72718,Male,44,Bachelors,6,5,53,41,85,6.0,4,21,Rural,HR Executive,50834,0 +72719,Female,46,Diploma,5,32,3,46,28,6.0,6,70,Urban,HR Executive,24888,0 +72720,Male,52,Bachelors,7,93,52,39,14,5.0,3,56,Urban,HR Executive,118361,1 +72721,Male,40,Masters,12,48,1,49,29,7.0,7,90,Urban,Manager,31923,0 +72722,Male,46,Bachelors,12,30,36,6,51,3.0,3,1,Rural,ML Engineer,42111,0 +72723,Female,55,Diploma,9,67,60,75,7,2.0,6,28,Urban,Data Analyst,65336,0 +72724,Female,33,Diploma,12,26,10,50,95,4.0,4,60,Rural,ML Engineer,60992,0 +72725,Male,25,PhD,19,24,85,2,45,2.0,2,67,Semi-Urban,ML Engineer,101356,0 +72726,Female,40,Bachelors,16,60,98,1,31,8.0,6,46,Semi-Urban,Software Engineer,20228,0 +72727,Female,40,Bachelors,5,15,6,6,58,3.0,5,96,Urban,Data Analyst,32943,0 +72728,Male,27,Masters,17,65,30,25,57,9.0,4,0,Urban,HR Executive,48339,0 +72729,Male,59,Masters,19,22,25,35,36,1.0,4,20,Semi-Urban,HR Executive,47209,0 +72730,Male,27,Masters,10,4,2,87,62,8.0,7,75,Urban,ML Engineer,93989,0 +72731,Male,27,Bachelors,8,2,50,40,33,9.0,5,27,Urban,Data Analyst,40232,0 +72732,Male,35,Bachelors,2,85,57,2,35,5.0,1,1,Semi-Urban,HR Executive,43620,0 +72733,Female,28,Masters,17,78,83,40,30,2.0,6,89,Urban,HR Executive,91015,1 +72734,Female,41,High School,13,12,48,51,50,8.0,1,43,Urban,Software Engineer,103676,0 +72735,Female,26,High School,13,39,46,19,71,4.0,7,0,Rural,Data Analyst,46134,0 +72736,Male,29,Diploma,13,99,36,38,44,5.0,2,75,Urban,HR Executive,113237,1 +72737,Female,30,Bachelors,17,19,38,68,56,3.0,5,67,Semi-Urban,Software Engineer,41421,0 +72738,Male,52,Masters,9,99,46,41,92,9.0,1,42,Urban,HR Executive,65805,0 +72739,Female,49,Masters,6,54,62,89,58,9.0,0,43,Urban,Software Engineer,124545,1 +72740,Female,52,Diploma,19,12,5,27,1,7.0,4,1,Urban,Data Analyst,93216,0 +72741,Female,29,Bachelors,13,12,29,37,48,4.0,3,61,Semi-Urban,Data Analyst,84390,0 +72742,Male,36,Masters,10,94,1,75,49,3.0,7,22,Rural,Software Engineer,66456,0 +72743,Male,50,Bachelors,13,71,36,81,46,4.0,2,46,Semi-Urban,HR Executive,96503,0 +72744,Female,53,High School,11,26,6,44,79,3.0,5,57,Urban,HR Executive,132250,0 +72745,Male,55,Masters,1,83,67,1,36,2.0,6,72,Rural,Data Analyst,46455,0 +72746,Male,28,Diploma,16,2,83,1,12,6.0,4,37,Semi-Urban,Manager,86935,0 +72747,Male,27,Bachelors,5,98,98,17,98,6.0,5,0,Urban,HR Executive,38788,0 +72748,Female,30,Masters,18,35,46,4,91,7.0,4,44,Urban,Software Engineer,78876,0 +72749,Male,40,Masters,8,42,96,46,52,4.0,2,30,Urban,Software Engineer,141255,0 +72750,Male,26,High School,18,70,81,20,98,1.0,2,53,Semi-Urban,Data Analyst,138130,0 +72751,Male,42,Diploma,10,69,25,83,47,7.0,4,76,Rural,ML Engineer,134899,1 +72752,Male,31,Bachelors,16,68,40,96,71,6.0,0,84,Rural,ML Engineer,63955,1 +72753,Male,42,Masters,17,90,98,24,56,2.0,6,17,Urban,HR Executive,96101,0 +72754,Female,28,Diploma,9,57,96,35,64,3.0,0,63,Urban,HR Executive,33924,1 +72755,Female,49,Bachelors,15,83,54,31,24,3.0,2,56,Urban,Data Analyst,48742,0 +72756,Female,59,Bachelors,14,21,70,54,47,6.0,4,9,Urban,Data Analyst,145309,0 +72757,Male,38,Masters,8,44,35,56,52,6.0,7,91,Rural,Software Engineer,148179,0 +72758,Male,57,Diploma,13,82,44,89,96,9.0,2,38,Urban,Data Analyst,24064,1 +72759,Male,55,Bachelors,5,42,7,96,65,2.0,4,70,Urban,Data Analyst,78806,0 +72760,Male,45,Bachelors,12,87,91,94,82,7.0,5,17,Urban,Software Engineer,58342,1 +72761,Male,57,PhD,8,33,49,25,78,8.0,2,16,Rural,HR Executive,125850,0 +72762,Male,57,Bachelors,15,33,16,80,8,6.0,4,42,Rural,Software Engineer,31307,0 +72763,Female,33,Masters,16,6,34,15,46,4.0,0,11,Urban,HR Executive,99339,0 +72764,Male,52,Masters,8,37,88,71,51,4.0,0,9,Urban,ML Engineer,23576,0 +72765,Male,56,PhD,2,82,5,90,51,6.0,0,50,Rural,ML Engineer,31980,0 +72766,Female,32,Diploma,0,14,96,70,52,1.0,6,6,Rural,Data Analyst,27965,0 +72767,Male,24,Masters,1,22,35,6,62,1.0,2,34,Urban,Data Analyst,143589,0 +72768,Male,32,Bachelors,11,8,20,11,92,1.0,0,19,Urban,HR Executive,111503,0 +72769,Female,39,Masters,13,31,81,1,57,5.0,4,31,Rural,Software Engineer,30160,0 +72770,Male,40,Masters,9,33,2,35,21,4.0,0,48,Urban,HR Executive,112209,0 +72771,Male,50,Diploma,18,9,58,91,82,9.0,1,36,Rural,Software Engineer,55984,0 +72772,Male,50,PhD,1,55,48,76,87,8.0,7,10,Rural,Data Analyst,121987,0 +72773,Male,34,PhD,18,95,39,69,88,0.0,1,93,Urban,Manager,141440,1 +72774,Male,28,Bachelors,19,45,26,92,82,0.0,2,8,Urban,HR Executive,139718,0 +72775,Male,47,High School,0,17,79,82,85,9.0,4,93,Urban,ML Engineer,142280,1 +72776,Female,33,PhD,5,8,74,44,43,3.0,2,68,Semi-Urban,Software Engineer,75549,0 +72777,Male,40,High School,9,36,41,5,64,9.0,2,68,Urban,Manager,108072,0 +72778,Male,59,Diploma,18,43,39,10,46,7.0,6,30,Urban,Manager,58531,0 +72779,Female,33,Masters,14,84,45,61,89,9.0,2,49,Semi-Urban,HR Executive,72337,0 +72780,Male,21,Bachelors,0,49,84,69,67,8.0,2,21,Semi-Urban,Software Engineer,142243,0 +72781,Male,34,Bachelors,2,0,61,47,67,3.0,3,93,Urban,HR Executive,89517,0 +72782,Male,33,Masters,4,36,15,76,65,7.0,6,90,Urban,HR Executive,56147,0 +72783,Male,54,Bachelors,0,81,44,59,49,9.0,0,75,Urban,Software Engineer,59875,1 +72784,Male,58,Masters,14,81,66,11,18,8.0,0,79,Urban,Software Engineer,115848,1 +72785,Male,32,Bachelors,11,22,66,92,26,9.0,4,39,Semi-Urban,ML Engineer,105837,0 +72786,Male,36,Bachelors,2,56,82,94,41,6.0,1,93,Urban,Software Engineer,146109,1 +72787,Other,28,Bachelors,12,98,16,89,44,9.0,5,95,Urban,Data Analyst,145296,1 +72788,Male,24,Bachelors,11,70,93,52,57,0.0,3,51,Semi-Urban,Manager,115315,1 +72789,Female,22,Diploma,7,6,89,43,78,4.0,7,76,Semi-Urban,Software Engineer,28271,0 +72790,Male,27,Diploma,5,29,50,13,24,4.0,6,49,Urban,Data Analyst,99752,0 +72791,Male,50,Diploma,10,96,45,33,55,3.0,2,56,Rural,Data Analyst,40855,0 +72792,Male,28,Bachelors,16,40,63,11,6,5.0,3,15,Rural,Manager,22643,0 +72793,Female,33,Bachelors,16,68,21,0,37,1.0,5,67,Semi-Urban,Software Engineer,107362,0 +72794,Female,49,Diploma,13,39,63,30,77,5.0,6,68,Rural,ML Engineer,99609,0 +72795,Male,21,High School,12,46,41,23,32,3.0,7,1,Urban,Manager,88624,0 +72796,Other,58,Diploma,18,50,21,83,41,7.0,4,55,Semi-Urban,Software Engineer,132197,0 +72797,Female,23,Bachelors,1,15,28,96,41,1.0,3,34,Semi-Urban,Manager,149510,0 +72798,Other,45,Bachelors,18,96,99,11,92,0.0,5,59,Semi-Urban,ML Engineer,97000,1 +72799,Female,38,Bachelors,19,17,89,27,34,0.0,3,68,Rural,Software Engineer,62755,0 +72800,Male,27,Bachelors,16,86,2,92,70,0.0,4,59,Urban,HR Executive,70380,1 +72801,Female,35,PhD,14,4,10,96,46,5.0,0,39,Rural,Data Analyst,62454,0 +72802,Other,49,Masters,7,13,26,19,80,9.0,4,15,Rural,Data Analyst,136189,0 +72803,Male,50,Masters,7,33,76,38,1,4.0,3,46,Urban,Manager,23286,0 +72804,Female,37,Masters,19,9,81,31,83,7.0,6,96,Urban,Manager,52685,0 +72805,Male,38,PhD,11,0,55,8,11,9.0,6,83,Urban,Manager,49017,0 +72806,Male,57,Bachelors,6,99,30,84,1,8.0,7,41,Urban,HR Executive,48574,1 +72807,Male,37,Diploma,18,38,22,40,96,1.0,5,79,Urban,ML Engineer,98854,0 +72808,Male,28,Masters,19,24,26,30,99,8.0,7,22,Urban,HR Executive,141116,0 +72809,Female,26,Masters,16,5,7,12,33,1.0,7,95,Urban,HR Executive,135554,0 +72810,Male,43,Masters,4,73,36,87,9,3.0,3,96,Urban,Data Analyst,66393,1 +72811,Male,59,Bachelors,5,53,4,32,95,5.0,4,51,Semi-Urban,ML Engineer,90869,0 +72812,Female,44,Masters,2,59,60,64,83,4.0,2,52,Urban,Manager,31732,0 +72813,Female,38,Bachelors,17,10,84,49,96,6.0,1,34,Rural,Software Engineer,110237,0 +72814,Male,43,Diploma,14,49,23,96,54,2.0,4,35,Semi-Urban,HR Executive,124653,0 +72815,Male,53,PhD,10,35,31,64,85,1.0,0,62,Rural,Manager,48290,0 +72816,Male,26,Diploma,9,69,82,23,86,3.0,1,26,Urban,Manager,60875,0 +72817,Male,51,Diploma,6,21,78,9,37,7.0,6,14,Urban,ML Engineer,63125,0 +72818,Female,36,Bachelors,8,73,18,7,19,5.0,7,78,Urban,Software Engineer,47474,0 +72819,Other,53,Masters,12,58,40,74,54,0.0,5,17,Urban,Manager,51042,0 +72820,Male,51,Masters,7,74,67,42,38,9.0,2,88,Urban,ML Engineer,120104,1 +72821,Male,52,Bachelors,17,56,89,16,3,9.0,4,89,Rural,ML Engineer,121644,1 +72822,Female,51,Masters,17,59,96,96,48,4.0,0,64,Rural,Data Analyst,136943,1 +72823,Male,50,Bachelors,2,19,76,74,1,7.0,7,29,Urban,Software Engineer,22791,0 +72824,Male,59,High School,11,59,50,32,21,7.0,0,11,Urban,ML Engineer,96462,0 +72825,Female,54,Masters,18,74,47,20,45,1.0,3,88,Semi-Urban,Data Analyst,20693,0 +72826,Male,54,Diploma,7,82,30,4,23,3.0,7,16,Urban,Software Engineer,45631,0 +72827,Male,41,PhD,18,41,56,37,76,0.0,3,84,Urban,Manager,28026,0 +72828,Male,29,Bachelors,3,83,4,71,78,4.0,1,35,Rural,Data Analyst,71180,0 +72829,Female,42,Bachelors,19,42,13,85,26,1.0,1,17,Urban,Data Analyst,113969,0 +72830,Male,45,Bachelors,9,88,90,81,38,5.0,1,66,Rural,HR Executive,28453,1 +72831,Male,35,Masters,16,89,28,56,7,7.0,3,86,Urban,ML Engineer,54278,1 +72832,Male,54,High School,9,44,57,48,92,4.0,6,1,Urban,Manager,54945,0 +72833,Male,33,High School,0,93,97,61,1,1.0,6,42,Urban,Software Engineer,24582,1 +72834,Male,58,Bachelors,17,72,97,18,20,0.0,3,77,Rural,Data Analyst,99225,1 +72835,Female,53,Bachelors,12,47,61,54,0,1.0,1,41,Urban,Software Engineer,103700,0 +72836,Male,59,Bachelors,14,53,85,3,53,7.0,4,82,Urban,HR Executive,47016,0 +72837,Female,45,High School,12,29,55,35,67,2.0,7,7,Semi-Urban,Data Analyst,140653,0 +72838,Male,32,Masters,16,55,54,94,6,6.0,7,94,Urban,Manager,124469,1 +72839,Male,57,High School,2,57,74,16,6,3.0,4,26,Urban,Data Analyst,141159,0 +72840,Male,27,Bachelors,6,72,82,14,7,2.0,7,77,Semi-Urban,Data Analyst,44812,1 +72841,Male,55,Diploma,18,29,11,69,82,8.0,1,60,Urban,Data Analyst,39437,0 +72842,Female,30,Diploma,8,89,48,24,73,6.0,5,75,Urban,ML Engineer,144822,0 +72843,Male,50,Diploma,7,60,44,77,10,1.0,7,29,Urban,ML Engineer,26272,0 +72844,Female,55,Bachelors,1,87,45,40,37,1.0,3,93,Urban,Data Analyst,140912,1 +72845,Female,47,Bachelors,7,60,87,87,24,5.0,0,48,Rural,HR Executive,65720,1 +72846,Male,50,Masters,17,59,95,20,26,3.0,3,41,Urban,ML Engineer,132090,0 +72847,Male,53,Bachelors,16,72,54,26,31,1.0,4,44,Rural,Data Analyst,87089,0 +72848,Male,44,Masters,0,33,89,98,67,6.0,4,37,Urban,Manager,74014,1 +72849,Male,26,Diploma,14,85,87,85,85,5.0,5,37,Urban,HR Executive,49684,1 +72850,Female,25,Bachelors,15,79,67,91,71,2.0,0,32,Rural,Software Engineer,135733,1 +72851,Female,27,Diploma,8,14,91,44,70,9.0,5,77,Rural,Software Engineer,73541,0 +72852,Female,33,Bachelors,10,9,28,4,81,7.0,7,71,Urban,HR Executive,65314,0 +72853,Male,46,Diploma,3,77,91,32,70,2.0,7,84,Urban,ML Engineer,32630,1 +72854,Male,48,Bachelors,4,0,60,4,2,2.0,1,55,Urban,ML Engineer,138641,0 +72855,Female,34,Diploma,6,40,71,10,20,6.0,1,59,Rural,ML Engineer,99586,0 +72856,Female,56,Bachelors,11,96,65,36,1,1.0,7,9,Urban,HR Executive,26123,0 +72857,Female,32,Bachelors,6,10,70,39,55,3.0,4,43,Urban,ML Engineer,144482,0 +72858,Male,40,Bachelors,19,54,14,20,16,6.0,5,76,Rural,Software Engineer,143522,0 +72859,Male,39,Masters,4,89,53,61,25,7.0,5,41,Rural,Software Engineer,129897,1 +72860,Female,46,Bachelors,13,90,90,70,61,3.0,0,70,Urban,Manager,143864,1 +72861,Male,46,Bachelors,14,4,38,12,6,8.0,4,85,Urban,ML Engineer,135793,0 +72862,Male,55,Diploma,19,72,17,9,10,8.0,2,23,Semi-Urban,Data Analyst,104693,0 +72863,Male,45,High School,0,51,62,70,8,7.0,0,87,Semi-Urban,Software Engineer,56215,1 +72864,Male,54,Diploma,2,45,73,99,44,0.0,1,86,Urban,Manager,142699,1 +72865,Male,57,Diploma,8,0,71,23,69,3.0,5,67,Rural,ML Engineer,79851,0 +72866,Male,47,PhD,2,64,22,90,11,5.0,5,47,Rural,Data Analyst,104099,0 +72867,Female,26,Bachelors,3,82,58,75,45,9.0,7,55,Semi-Urban,ML Engineer,24687,1 +72868,Male,50,Bachelors,8,93,53,9,76,2.0,7,44,Rural,ML Engineer,29531,0 +72869,Female,31,Masters,16,46,29,97,44,5.0,2,63,Rural,Data Analyst,89096,0 +72870,Male,24,Masters,2,29,10,47,66,8.0,6,56,Rural,Manager,23522,0 +72871,Female,51,Diploma,6,36,26,69,71,4.0,5,8,Urban,Software Engineer,61095,0 +72872,Female,48,Bachelors,12,67,61,95,27,4.0,5,33,Rural,Data Analyst,59803,1 +72873,Male,44,Bachelors,11,34,81,98,36,0.0,5,53,Urban,HR Executive,147631,1 +72874,Female,26,Bachelors,6,3,7,64,28,8.0,4,73,Rural,ML Engineer,120084,0 +72875,Male,45,High School,10,47,68,69,49,3.0,3,97,Urban,ML Engineer,45794,1 +72876,Male,38,Bachelors,13,17,61,53,93,8.0,0,6,Urban,Data Analyst,118487,0 +72877,Male,38,High School,12,84,22,73,95,1.0,4,56,Semi-Urban,ML Engineer,44995,1 +72878,Female,28,Bachelors,1,79,51,51,52,1.0,4,64,Urban,ML Engineer,49136,1 +72879,Female,54,Diploma,3,22,29,74,45,8.0,7,34,Urban,Software Engineer,148201,0 +72880,Male,32,Bachelors,18,57,26,91,74,7.0,2,23,Rural,HR Executive,48472,0 +72881,Male,49,High School,4,40,13,12,16,2.0,3,79,Semi-Urban,Data Analyst,122299,0 +72882,Female,41,Diploma,8,8,78,74,42,2.0,2,9,Urban,ML Engineer,132532,0 +72883,Male,24,High School,6,75,83,70,52,2.0,3,63,Urban,Manager,135111,1 +72884,Male,32,Bachelors,18,90,86,82,7,9.0,2,87,Urban,Data Analyst,25397,1 +72885,Male,32,High School,14,4,91,32,63,0.0,1,30,Rural,Software Engineer,77344,0 +72886,Male,24,Bachelors,0,97,95,6,72,6.0,1,87,Semi-Urban,HR Executive,61744,1 +72887,Male,39,Bachelors,1,1,86,30,51,0.0,3,80,Urban,Software Engineer,90651,0 +72888,Female,59,Masters,1,53,49,84,87,3.0,0,64,Urban,Software Engineer,35441,1 +72889,Female,36,Bachelors,15,10,13,97,79,4.0,4,35,Semi-Urban,Data Analyst,49018,0 +72890,Male,50,Bachelors,4,17,50,10,32,0.0,5,78,Semi-Urban,ML Engineer,123741,0 +72891,Female,41,Bachelors,15,66,92,61,19,4.0,5,37,Rural,HR Executive,127626,1 +72892,Male,46,High School,18,99,7,52,48,3.0,7,64,Urban,ML Engineer,58594,0 +72893,Male,42,High School,9,46,69,42,76,7.0,2,74,Rural,Software Engineer,88743,0 +72894,Female,45,PhD,14,20,19,53,33,4.0,5,5,Urban,HR Executive,50590,0 +72895,Other,51,Bachelors,17,43,6,11,74,8.0,5,29,Urban,Manager,43001,0 +72896,Male,58,Bachelors,13,84,46,15,37,5.0,7,91,Rural,ML Engineer,75612,1 +72897,Other,34,Bachelors,17,26,4,31,39,9.0,5,17,Rural,Data Analyst,67251,0 +72898,Other,38,Bachelors,17,20,49,53,80,1.0,3,9,Rural,Manager,148517,0 +72899,Male,38,Diploma,2,33,14,77,82,0.0,2,51,Semi-Urban,Software Engineer,77253,0 +72900,Female,22,Masters,3,83,34,1,19,9.0,2,84,Urban,Data Analyst,63759,0 +72901,Female,40,Diploma,7,93,34,15,60,6.0,7,88,Rural,Manager,82672,0 +72902,Male,26,Masters,15,19,72,40,68,2.0,7,59,Rural,Data Analyst,95078,0 +72903,Male,21,Bachelors,9,43,28,76,48,8.0,2,18,Rural,Data Analyst,133457,0 +72904,Female,26,High School,2,64,17,63,88,1.0,7,87,Urban,ML Engineer,148883,0 +72905,Female,39,Diploma,12,73,24,75,81,1.0,0,57,Urban,ML Engineer,136024,0 +72906,Male,26,Masters,1,77,4,2,94,5.0,7,12,Urban,HR Executive,30315,0 +72907,Male,30,Bachelors,4,81,16,39,58,9.0,7,79,Semi-Urban,HR Executive,72432,0 +72908,Female,34,Masters,14,66,79,63,19,4.0,1,34,Urban,HR Executive,139679,1 +72909,Male,56,Masters,9,25,43,97,91,5.0,1,35,Semi-Urban,Data Analyst,113848,0 +72910,Female,46,Bachelors,16,79,14,0,66,0.0,5,9,Urban,Software Engineer,145858,0 +72911,Other,59,Bachelors,5,99,91,61,95,7.0,6,15,Urban,Data Analyst,71678,1 +72912,Female,25,PhD,0,49,8,35,36,2.0,4,46,Urban,HR Executive,72598,0 +72913,Male,21,Diploma,16,24,78,10,32,4.0,3,50,Semi-Urban,Manager,135834,0 +72914,Female,37,Diploma,10,61,55,78,5,3.0,0,44,Urban,ML Engineer,121125,0 +72915,Female,35,High School,12,11,75,2,23,5.0,5,64,Semi-Urban,Software Engineer,60600,0 +72916,Male,21,Bachelors,9,25,22,12,26,4.0,2,34,Semi-Urban,Data Analyst,63616,0 +72917,Male,47,Bachelors,3,86,14,98,83,7.0,3,5,Urban,Software Engineer,60353,0 +72918,Male,50,Diploma,11,24,38,69,36,3.0,4,71,Semi-Urban,Data Analyst,55135,0 +72919,Male,59,Diploma,17,36,96,35,5,0.0,3,5,Urban,Data Analyst,23288,0 +72920,Male,22,Bachelors,7,76,66,45,21,3.0,6,57,Semi-Urban,ML Engineer,50539,1 +72921,Male,43,Bachelors,18,5,2,76,35,3.0,0,15,Semi-Urban,HR Executive,61205,0 +72922,Female,44,Diploma,19,19,83,90,95,9.0,6,28,Urban,HR Executive,21932,0 +72923,Male,39,Masters,7,77,8,13,69,1.0,5,87,Urban,HR Executive,120188,0 +72924,Female,39,Bachelors,16,57,48,49,89,2.0,6,51,Rural,HR Executive,130112,0 +72925,Other,30,Masters,10,62,55,25,20,6.0,7,50,Rural,HR Executive,81572,0 +72926,Female,57,High School,7,17,1,57,12,4.0,0,32,Semi-Urban,Data Analyst,132761,0 +72927,Female,26,Masters,18,54,71,31,18,8.0,1,55,Rural,HR Executive,95099,0 +72928,Female,22,High School,4,63,61,2,61,5.0,3,86,Urban,Manager,23115,0 +72929,Female,54,PhD,14,8,66,90,59,2.0,7,99,Semi-Urban,ML Engineer,36349,1 +72930,Female,47,Masters,3,74,19,19,47,9.0,4,40,Urban,Manager,44688,0 +72931,Male,47,Bachelors,6,95,15,80,7,6.0,7,28,Urban,Manager,57561,0 +72932,Male,39,High School,19,18,78,40,87,7.0,3,73,Rural,Software Engineer,53504,0 +72933,Male,37,Bachelors,1,37,79,82,45,5.0,2,73,Urban,HR Executive,96699,1 +72934,Male,54,Bachelors,19,31,36,39,36,2.0,3,38,Semi-Urban,HR Executive,59166,0 +72935,Male,52,Masters,15,82,44,54,21,2.0,4,98,Semi-Urban,Software Engineer,110626,1 +72936,Female,55,High School,16,70,15,64,52,3.0,0,67,Rural,HR Executive,96537,0 +72937,Female,30,Diploma,3,75,25,55,69,6.0,6,35,Rural,Software Engineer,73728,0 +72938,Male,36,Masters,18,35,39,56,12,6.0,4,8,Urban,Manager,73505,0 +72939,Male,25,Bachelors,9,40,87,92,94,5.0,1,42,Urban,Manager,104669,1 +72940,Other,31,High School,19,36,97,84,23,7.0,5,10,Semi-Urban,Data Analyst,58026,0 +72941,Male,42,High School,14,21,14,7,82,7.0,4,94,Semi-Urban,Software Engineer,52638,0 +72942,Female,40,Bachelors,5,94,49,32,42,4.0,4,32,Semi-Urban,Manager,91680,0 +72943,Male,24,Bachelors,13,86,57,90,18,5.0,1,52,Urban,Software Engineer,105541,1 +72944,Male,55,Diploma,8,8,20,19,38,2.0,3,72,Urban,Software Engineer,107375,0 +72945,Male,24,Bachelors,17,62,12,20,50,4.0,1,35,Urban,Software Engineer,115915,0 +72946,Male,32,Diploma,9,6,44,72,68,1.0,1,45,Rural,HR Executive,147912,0 +72947,Female,47,Bachelors,3,28,89,26,8,4.0,2,78,Rural,Data Analyst,67819,0 +72948,Male,52,High School,16,12,15,11,20,0.0,6,91,Urban,ML Engineer,98536,0 +72949,Male,41,Bachelors,5,66,34,39,90,0.0,7,5,Urban,ML Engineer,140265,0 +72950,Female,52,Bachelors,11,94,58,59,8,0.0,6,67,Urban,ML Engineer,139236,1 +72951,Male,42,Bachelors,14,61,54,5,89,7.0,4,78,Rural,ML Engineer,123125,0 +72952,Male,34,Diploma,6,89,34,0,80,5.0,4,69,Urban,ML Engineer,31868,0 +72953,Female,38,Diploma,0,90,2,29,66,3.0,2,78,Urban,Manager,95815,0 +72954,Female,22,Bachelors,11,66,87,80,5,1.0,3,72,Urban,ML Engineer,49773,1 +72955,Other,54,Bachelors,10,20,98,31,73,5.0,2,8,Semi-Urban,Data Analyst,76680,0 +72956,Female,27,Bachelors,9,7,99,15,90,2.0,4,93,Rural,Manager,108363,0 +72957,Female,22,Diploma,14,44,92,58,17,6.0,2,88,Urban,Software Engineer,138284,1 +72958,Male,23,Diploma,2,32,45,9,97,2.0,6,88,Rural,ML Engineer,119371,0 +72959,Male,35,Bachelors,16,78,5,26,50,5.0,7,69,Semi-Urban,Manager,96620,0 +72960,Male,35,Bachelors,5,74,36,48,2,3.0,5,94,Urban,Manager,149961,1 +72961,Female,57,Diploma,4,37,52,57,3,1.0,7,83,Semi-Urban,HR Executive,91080,0 +72962,Male,34,Diploma,6,5,4,65,43,7.0,3,97,Urban,Manager,92286,0 +72963,Female,52,Bachelors,7,39,17,98,5,4.0,3,49,Urban,Data Analyst,50981,0 +72964,Female,49,Masters,6,67,3,73,62,8.0,2,97,Rural,Data Analyst,83397,0 +72965,Male,39,Bachelors,18,98,23,27,17,4.0,0,28,Semi-Urban,Manager,28317,0 +72966,Male,21,Bachelors,14,6,85,27,23,6.0,0,84,Urban,HR Executive,148820,0 +72967,Female,29,Bachelors,4,23,22,35,83,9.0,4,28,Rural,ML Engineer,89793,0 +72968,Female,35,Masters,16,93,8,22,8,0.0,0,51,Urban,HR Executive,49026,0 +72969,Female,26,Masters,2,66,33,97,95,4.0,4,71,Urban,Data Analyst,129283,1 +72970,Female,55,PhD,12,59,71,61,97,9.0,0,10,Rural,Manager,129590,0 +72971,Male,28,Bachelors,3,81,87,46,47,3.0,4,5,Semi-Urban,Manager,124445,0 +72972,Female,44,High School,18,13,57,51,60,4.0,7,57,Urban,HR Executive,122997,0 +72973,Female,25,PhD,15,29,2,89,8,2.0,1,36,Urban,ML Engineer,131189,0 +72974,Female,42,Diploma,18,82,43,67,31,8.0,2,58,Rural,Manager,38607,1 +72975,Male,21,High School,16,74,34,89,78,0.0,5,82,Urban,HR Executive,42613,1 +72976,Female,23,Bachelors,12,24,61,0,27,9.0,7,17,Rural,Manager,71260,0 +72977,Other,39,Bachelors,0,13,38,95,7,7.0,1,71,Semi-Urban,HR Executive,115453,0 +72978,Male,49,Masters,12,89,71,36,43,5.0,0,84,Urban,Data Analyst,35958,1 +72979,Female,23,Diploma,14,31,12,38,55,1.0,0,25,Urban,Data Analyst,137921,0 +72980,Male,33,Bachelors,19,21,98,96,96,8.0,3,32,Semi-Urban,Data Analyst,92023,1 +72981,Male,46,Bachelors,12,18,35,80,13,4.0,6,76,Urban,Software Engineer,105768,0 +72982,Male,46,Bachelors,7,60,55,42,69,1.0,0,92,Semi-Urban,ML Engineer,111215,1 +72983,Female,32,High School,15,90,35,72,70,0.0,1,55,Urban,Data Analyst,110580,1 +72984,Male,26,Bachelors,13,29,26,95,29,7.0,5,58,Urban,HR Executive,43692,0 +72985,Other,52,High School,0,0,99,53,68,2.0,3,46,Rural,HR Executive,64319,0 +72986,Female,45,High School,6,57,64,67,62,1.0,0,39,Semi-Urban,ML Engineer,68252,0 +72987,Male,51,Masters,17,64,39,44,21,9.0,6,93,Rural,HR Executive,116551,1 +72988,Male,23,Masters,16,82,15,69,35,8.0,0,19,Urban,HR Executive,139947,0 +72989,Male,45,Diploma,17,24,67,12,80,9.0,0,80,Urban,HR Executive,95744,0 +72990,Female,27,Bachelors,9,18,38,34,40,5.0,4,10,Urban,HR Executive,120276,0 +72991,Male,54,Bachelors,9,99,39,86,38,1.0,7,83,Semi-Urban,HR Executive,90692,1 +72992,Male,33,PhD,15,82,7,55,88,8.0,4,81,Urban,Data Analyst,33540,0 +72993,Male,39,Masters,2,77,56,59,45,9.0,4,43,Rural,Data Analyst,68974,1 +72994,Male,36,Diploma,14,7,83,74,99,8.0,7,16,Semi-Urban,Data Analyst,48732,0 +72995,Female,56,Bachelors,9,0,68,32,26,9.0,1,22,Semi-Urban,Data Analyst,73990,0 +72996,Male,35,Bachelors,17,16,33,32,19,3.0,3,46,Semi-Urban,Software Engineer,75868,0 +72997,Male,40,High School,13,78,82,27,87,0.0,6,60,Urban,HR Executive,145249,1 +72998,Male,52,PhD,11,60,16,43,46,5.0,0,91,Semi-Urban,Data Analyst,125004,0 +72999,Male,56,Bachelors,12,64,14,87,42,1.0,7,47,Semi-Urban,Software Engineer,52789,0 +73000,Female,40,Bachelors,19,33,0,82,77,0.0,2,41,Semi-Urban,HR Executive,101887,0 +73001,Female,22,Diploma,19,0,81,31,9,7.0,5,59,Urban,HR Executive,54410,0 +73002,Female,29,Diploma,12,96,86,39,70,0.0,3,17,Rural,Data Analyst,118895,0 +73003,Male,41,Bachelors,6,25,83,56,64,8.0,3,31,Urban,Manager,92039,0 +73004,Male,51,High School,19,46,87,80,64,8.0,6,57,Rural,Software Engineer,29742,1 +73005,Female,22,PhD,10,91,66,43,31,0.0,4,5,Semi-Urban,Data Analyst,78455,0 +73006,Male,23,PhD,11,28,68,67,46,9.0,2,73,Urban,Software Engineer,81651,1 +73007,Male,22,Diploma,15,9,16,26,55,8.0,3,43,Rural,ML Engineer,26270,0 +73008,Male,45,Bachelors,2,11,86,39,32,0.0,1,19,Urban,Software Engineer,115084,0 +73009,Male,27,High School,3,10,7,10,33,8.0,5,14,Rural,ML Engineer,128694,0 +73010,Female,40,Diploma,4,58,27,35,60,3.0,5,11,Rural,ML Engineer,74283,0 +73011,Male,33,Bachelors,7,41,90,16,79,0.0,0,55,Urban,Software Engineer,46612,0 +73012,Male,37,Bachelors,14,89,72,43,79,6.0,4,98,Urban,ML Engineer,53017,1 +73013,Female,52,Bachelors,14,67,91,16,17,2.0,0,5,Rural,Manager,22974,0 +73014,Female,21,Masters,0,4,57,76,17,4.0,4,54,Urban,Software Engineer,98566,0 +73015,Male,24,Diploma,18,25,77,52,96,8.0,1,58,Rural,Software Engineer,32843,0 +73016,Male,27,Bachelors,11,65,15,57,53,0.0,6,13,Urban,Manager,122810,0 +73017,Male,58,Masters,15,75,84,46,67,9.0,2,23,Rural,Software Engineer,55634,0 +73018,Male,33,High School,1,25,85,62,30,7.0,6,28,Urban,ML Engineer,114291,0 +73019,Male,46,High School,1,59,16,13,26,1.0,3,28,Rural,Manager,115230,0 +73020,Male,28,PhD,11,72,74,18,8,8.0,4,47,Rural,Data Analyst,103360,0 +73021,Male,47,Bachelors,13,56,99,77,68,8.0,5,70,Urban,Software Engineer,117215,1 +73022,Female,35,Bachelors,8,66,93,52,87,5.0,3,55,Urban,HR Executive,116700,1 +73023,Male,28,Masters,19,56,0,77,76,0.0,7,9,Semi-Urban,Software Engineer,57241,0 +73024,Female,24,Bachelors,6,8,88,12,45,4.0,6,40,Semi-Urban,Software Engineer,136755,0 +73025,Male,36,Masters,6,42,27,25,61,5.0,3,21,Urban,Data Analyst,129555,0 +73026,Female,51,Masters,1,73,99,15,74,3.0,1,30,Urban,Software Engineer,88320,0 +73027,Other,56,Masters,12,11,62,96,82,4.0,7,75,Rural,Software Engineer,96271,1 +73028,Other,54,High School,13,48,26,15,54,6.0,1,26,Semi-Urban,ML Engineer,64548,0 +73029,Male,30,Diploma,19,94,57,67,51,6.0,4,79,Urban,Data Analyst,148493,1 +73030,Male,53,Masters,16,16,78,57,74,6.0,5,5,Urban,Manager,136596,0 +73031,Female,32,Masters,14,34,20,15,92,6.0,6,25,Rural,Software Engineer,64024,0 +73032,Male,22,Bachelors,14,87,68,30,79,9.0,0,1,Urban,Data Analyst,60737,0 +73033,Female,32,Bachelors,6,8,24,60,1,2.0,4,26,Urban,Data Analyst,104576,0 +73034,Female,42,High School,11,0,52,45,29,4.0,0,27,Urban,Manager,67724,0 +73035,Female,31,Bachelors,18,74,68,8,82,7.0,2,93,Urban,Software Engineer,73978,1 +73036,Female,25,Bachelors,12,8,67,90,91,7.0,3,49,Rural,Manager,46411,0 +73037,Other,21,PhD,2,48,13,58,82,1.0,2,48,Urban,ML Engineer,115040,0 +73038,Male,28,Bachelors,14,97,17,46,12,4.0,4,36,Urban,Data Analyst,138684,0 +73039,Male,57,Bachelors,2,93,44,81,62,4.0,7,29,Urban,Data Analyst,57705,1 +73040,Male,28,Bachelors,19,84,47,28,6,8.0,7,79,Urban,Manager,102515,1 +73041,Male,27,Masters,16,96,55,98,97,8.0,4,64,Rural,Manager,51420,1 +73042,Male,57,High School,17,53,87,70,66,6.0,1,60,Urban,Data Analyst,37924,1 +73043,Female,26,Masters,13,18,89,25,49,7.0,7,95,Semi-Urban,Data Analyst,131297,0 +73044,Male,27,Bachelors,7,96,29,99,52,7.0,0,47,Urban,ML Engineer,121621,1 +73045,Female,56,Masters,14,82,57,50,23,9.0,7,69,Urban,ML Engineer,90072,1 +73046,Male,27,Masters,13,13,39,22,16,3.0,0,42,Semi-Urban,Data Analyst,41337,0 +73047,Other,32,PhD,1,98,5,55,17,9.0,0,42,Urban,Manager,99389,0 +73048,Male,42,Bachelors,14,26,8,88,47,3.0,4,77,Semi-Urban,Manager,144202,0 +73049,Male,30,Bachelors,9,89,95,27,14,1.0,2,88,Semi-Urban,HR Executive,54890,1 +73050,Female,32,Bachelors,18,44,7,24,90,6.0,4,52,Semi-Urban,Software Engineer,111163,0 +73051,Female,39,Bachelors,18,46,72,22,54,3.0,4,32,Rural,HR Executive,72451,0 +73052,Male,38,Diploma,16,11,78,83,48,5.0,6,30,Semi-Urban,HR Executive,148634,0 +73053,Male,36,Bachelors,3,73,86,31,91,5.0,1,51,Urban,Data Analyst,91533,1 +73054,Male,49,High School,19,97,30,82,82,9.0,6,61,Rural,Manager,40208,1 +73055,Male,44,High School,19,66,93,85,72,1.0,1,67,Rural,Manager,135057,1 +73056,Female,56,Diploma,11,22,81,97,91,3.0,6,77,Rural,Manager,97991,1 +73057,Female,25,High School,14,18,36,35,10,2.0,7,45,Urban,Software Engineer,22748,0 +73058,Male,43,Bachelors,15,74,68,20,82,3.0,3,20,Urban,HR Executive,50158,0 +73059,Male,32,Diploma,11,70,47,80,12,1.0,6,67,Rural,HR Executive,55791,1 +73060,Male,35,Bachelors,11,29,88,95,39,5.0,0,60,Urban,Manager,52319,1 +73061,Female,56,Masters,13,96,36,16,45,0.0,4,51,Rural,Software Engineer,65628,0 +73062,Female,53,Bachelors,14,14,22,36,81,3.0,5,91,Urban,ML Engineer,24134,0 +73063,Female,48,High School,13,38,30,8,80,4.0,6,97,Urban,Software Engineer,25554,0 +73064,Male,36,High School,7,4,78,14,12,5.0,3,59,Rural,ML Engineer,91798,0 +73065,Male,35,Bachelors,9,90,32,95,23,4.0,0,93,Urban,Manager,104365,1 +73066,Female,32,PhD,3,66,22,97,60,1.0,6,55,Semi-Urban,Software Engineer,47881,0 +73067,Male,25,High School,14,10,98,49,13,4.0,5,60,Urban,ML Engineer,127967,0 +73068,Male,46,High School,10,65,24,22,55,6.0,7,94,Urban,Manager,130372,0 +73069,Male,54,Diploma,13,30,75,23,24,1.0,3,79,Semi-Urban,Software Engineer,46728,0 +73070,Male,41,Bachelors,0,28,33,55,13,0.0,1,55,Rural,Data Analyst,54005,0 +73071,Other,29,Diploma,3,90,2,8,92,0.0,6,0,Semi-Urban,HR Executive,132755,0 +73072,Male,48,Bachelors,5,0,91,98,96,8.0,6,5,Rural,HR Executive,61696,0 +73073,Female,39,Masters,14,10,69,18,59,1.0,0,35,Urban,ML Engineer,44042,0 +73074,Male,48,Diploma,18,90,87,54,77,7.0,3,33,Semi-Urban,Manager,116029,1 +73075,Male,30,High School,9,63,68,82,33,9.0,2,50,Urban,ML Engineer,107680,1 +73076,Female,46,Diploma,17,71,49,66,10,5.0,0,32,Urban,HR Executive,103823,0 +73077,Female,35,Bachelors,16,27,70,96,74,6.0,2,85,Semi-Urban,Manager,38048,1 +73078,Male,35,High School,3,97,64,9,62,4.0,7,84,Urban,HR Executive,80064,1 +73079,Female,28,Diploma,16,88,28,47,21,4.0,0,30,Rural,ML Engineer,52435,0 +73080,Female,58,Bachelors,0,6,65,20,43,0.0,2,25,Rural,HR Executive,115543,0 +73081,Female,28,Diploma,11,30,45,18,99,4.0,0,27,Urban,HR Executive,142118,0 +73082,Male,33,Diploma,0,85,77,70,13,1.0,5,72,Urban,HR Executive,64314,1 +73083,Male,46,Bachelors,1,73,41,55,74,8.0,3,71,Urban,Software Engineer,35754,1 +73084,Female,37,High School,12,8,98,91,7,0.0,4,93,Urban,Manager,25555,1 +73085,Female,31,Bachelors,14,97,81,60,75,5.0,1,42,Rural,ML Engineer,68810,1 +73086,Male,41,Bachelors,13,7,5,42,37,8.0,2,83,Semi-Urban,Data Analyst,142362,0 +73087,Male,43,Bachelors,4,17,19,29,97,1.0,2,59,Semi-Urban,Data Analyst,106714,0 +73088,Female,37,Masters,16,26,19,65,36,0.0,6,28,Rural,ML Engineer,130189,0 +73089,Male,56,Bachelors,17,94,8,57,34,4.0,1,79,Urban,Data Analyst,144870,1 +73090,Male,44,Bachelors,0,43,9,86,63,8.0,6,92,Rural,ML Engineer,37929,0 +73091,Female,48,Bachelors,13,13,94,52,11,6.0,7,32,Urban,HR Executive,46732,0 +73092,Female,50,Bachelors,7,83,69,62,37,1.0,1,77,Urban,Manager,77830,1 +73093,Male,29,Masters,13,53,81,95,66,9.0,4,42,Urban,ML Engineer,33683,1 +73094,Female,52,Bachelors,17,63,43,75,21,5.0,3,29,Semi-Urban,Software Engineer,117790,0 +73095,Male,41,Diploma,5,54,11,15,9,2.0,2,89,Urban,Manager,61408,0 +73096,Male,48,Diploma,5,14,77,80,97,7.0,4,39,Semi-Urban,ML Engineer,113723,0 +73097,Other,37,Bachelors,5,47,38,97,17,9.0,2,55,Semi-Urban,Data Analyst,138271,0 +73098,Male,32,Bachelors,18,39,98,7,54,5.0,5,2,Semi-Urban,Manager,108828,0 +73099,Male,44,Masters,9,5,3,73,49,5.0,1,66,Semi-Urban,Data Analyst,117076,0 +73100,Male,52,Masters,4,7,62,92,26,0.0,6,29,Semi-Urban,ML Engineer,128304,0 +73101,Male,38,Masters,15,33,47,17,65,3.0,5,81,Urban,ML Engineer,65861,0 +73102,Male,31,Bachelors,16,75,2,55,32,3.0,4,23,Urban,Software Engineer,72575,0 +73103,Female,47,Diploma,14,41,78,9,96,5.0,6,7,Semi-Urban,ML Engineer,64055,0 +73104,Male,37,High School,1,24,9,77,57,7.0,0,93,Urban,ML Engineer,47632,0 +73105,Male,28,Masters,6,47,48,92,73,3.0,7,97,Rural,Manager,91640,1 +73106,Female,53,Bachelors,14,28,22,44,27,6.0,7,44,Urban,HR Executive,67662,0 +73107,Male,42,Masters,13,76,45,25,50,5.0,5,86,Semi-Urban,HR Executive,105731,0 +73108,Female,27,High School,5,23,99,28,18,1.0,1,90,Semi-Urban,ML Engineer,23546,0 +73109,Male,47,Bachelors,8,1,32,2,46,9.0,5,13,Semi-Urban,Software Engineer,117629,0 +73110,Female,45,High School,1,71,20,89,17,4.0,4,30,Urban,HR Executive,39545,0 +73111,Male,43,Bachelors,0,13,47,59,79,0.0,1,19,Rural,ML Engineer,134077,0 +73112,Female,30,High School,16,45,50,64,31,7.0,1,67,Urban,Data Analyst,123362,0 +73113,Female,38,High School,15,91,83,46,73,5.0,4,21,Semi-Urban,Software Engineer,92014,1 +73114,Male,44,Bachelors,16,17,23,33,9,9.0,5,29,Urban,Manager,24737,0 +73115,Female,52,Masters,1,61,13,92,59,2.0,1,13,Urban,Data Analyst,109558,0 +73116,Female,33,Bachelors,10,59,13,60,23,9.0,6,69,Urban,Data Analyst,47772,0 +73117,Other,59,Masters,2,82,67,34,73,7.0,6,18,Urban,ML Engineer,76531,0 +73118,Female,30,Diploma,0,30,37,30,74,4.0,6,11,Urban,Software Engineer,128279,0 +73119,Male,24,Bachelors,16,26,67,50,17,6.0,3,31,Semi-Urban,Software Engineer,121209,0 +73120,Male,21,Diploma,14,41,82,88,58,4.0,6,47,Semi-Urban,Software Engineer,38463,1 +73121,Female,40,Masters,19,88,52,1,5,5.0,1,56,Semi-Urban,HR Executive,72814,0 +73122,Male,22,Diploma,15,94,17,3,99,6.0,3,64,Semi-Urban,ML Engineer,55402,0 +73123,Female,50,High School,15,85,62,12,78,8.0,1,57,Urban,Data Analyst,135297,0 +73124,Male,55,PhD,9,9,48,88,87,7.0,6,82,Semi-Urban,HR Executive,106606,0 +73125,Female,43,Masters,17,91,28,58,2,2.0,3,72,Urban,ML Engineer,88475,1 +73126,Female,26,Bachelors,17,52,95,72,2,0.0,1,36,Semi-Urban,Software Engineer,123505,1 +73127,Female,21,Bachelors,8,90,63,3,95,4.0,2,2,Urban,ML Engineer,127201,0 +73128,Other,46,Bachelors,6,90,53,97,84,1.0,2,40,Urban,HR Executive,128498,1 +73129,Male,33,Masters,14,81,51,44,0,5.0,5,19,Semi-Urban,Software Engineer,126213,0 +73130,Male,54,High School,0,21,13,44,28,4.0,3,89,Urban,Data Analyst,38896,0 +73131,Male,53,Bachelors,3,5,9,17,64,4.0,7,50,Semi-Urban,ML Engineer,138009,0 +73132,Other,53,Masters,18,70,36,48,35,0.0,2,35,Urban,Software Engineer,51521,0 +73133,Female,57,Diploma,7,49,24,0,12,0.0,6,46,Rural,ML Engineer,135998,0 +73134,Other,25,PhD,14,29,27,76,25,7.0,5,56,Rural,Software Engineer,139100,0 +73135,Other,44,Bachelors,19,13,30,7,69,6.0,1,85,Urban,Software Engineer,61335,0 +73136,Female,26,Bachelors,16,87,5,66,38,8.0,2,95,Semi-Urban,Software Engineer,97571,1 +73137,Female,21,Masters,2,30,50,28,57,3.0,3,34,Semi-Urban,Data Analyst,34458,0 +73138,Male,38,Masters,7,59,59,71,77,1.0,5,86,Urban,ML Engineer,138843,1 +73139,Male,41,Bachelors,13,27,18,36,11,1.0,6,89,Urban,Software Engineer,47546,0 +73140,Female,45,Masters,6,99,66,84,95,1.0,0,55,Semi-Urban,Software Engineer,27578,1 +73141,Female,56,Masters,19,12,70,24,39,7.0,6,5,Urban,Manager,53680,0 +73142,Female,30,Bachelors,16,44,40,35,81,2.0,4,14,Urban,Data Analyst,63417,0 +73143,Female,39,Diploma,1,50,28,83,27,1.0,1,6,Semi-Urban,HR Executive,137811,0 +73144,Male,50,Bachelors,0,7,99,34,49,5.0,6,36,Rural,Software Engineer,101413,0 +73145,Female,44,High School,11,67,65,72,81,7.0,3,94,Urban,HR Executive,109298,1 +73146,Female,30,Bachelors,16,21,12,70,41,2.0,7,18,Rural,Software Engineer,21766,0 +73147,Male,43,Bachelors,10,19,48,60,30,1.0,5,5,Urban,Software Engineer,105264,0 +73148,Male,41,Bachelors,6,93,37,3,75,9.0,1,5,Semi-Urban,Manager,58294,0 +73149,Male,35,Bachelors,19,12,16,22,66,3.0,7,91,Urban,HR Executive,113452,0 +73150,Male,56,High School,13,75,82,91,56,2.0,7,36,Rural,Manager,50854,1 +73151,Female,26,Bachelors,6,66,46,73,17,9.0,2,90,Urban,Data Analyst,141487,1 +73152,Female,36,PhD,14,42,26,9,94,5.0,4,66,Urban,Data Analyst,116636,0 +73153,Male,49,Diploma,6,86,96,96,64,3.0,7,29,Rural,Manager,86245,1 +73154,Male,30,Diploma,8,42,8,81,13,1.0,2,41,Urban,Software Engineer,124134,0 +73155,Male,40,High School,17,65,89,36,92,9.0,2,38,Rural,ML Engineer,33897,0 +73156,Female,27,Bachelors,4,21,96,5,50,0.0,4,10,Urban,Manager,147462,0 +73157,Female,23,Diploma,15,62,90,32,46,4.0,3,23,Semi-Urban,Software Engineer,70091,0 +73158,Male,44,Bachelors,15,2,50,28,52,0.0,0,71,Semi-Urban,Software Engineer,38786,0 +73159,Male,41,Bachelors,9,65,40,18,32,3.0,1,64,Urban,Data Analyst,114013,0 +73160,Female,40,Bachelors,17,95,75,73,83,9.0,2,99,Semi-Urban,Manager,55258,1 +73161,Male,22,Diploma,1,30,19,50,55,9.0,4,10,Rural,Manager,66607,0 +73162,Male,49,Bachelors,6,35,48,76,61,2.0,1,46,Rural,ML Engineer,147552,0 +73163,Male,36,Diploma,11,73,7,33,45,0.0,1,31,Urban,HR Executive,108427,0 +73164,Female,50,Bachelors,0,96,21,97,29,6.0,4,32,Rural,Data Analyst,100456,1 +73165,Male,50,Masters,15,51,33,60,99,6.0,0,8,Urban,Data Analyst,66626,0 +73166,Male,28,Bachelors,9,1,22,14,56,6.0,0,94,Urban,HR Executive,71295,0 +73167,Other,56,Masters,9,25,13,58,91,9.0,0,46,Semi-Urban,Software Engineer,48735,0 +73168,Male,34,Bachelors,19,51,15,28,98,1.0,1,41,Rural,ML Engineer,44155,0 +73169,Female,45,Bachelors,4,10,79,70,75,0.0,7,79,Urban,Software Engineer,61832,0 +73170,Male,46,Masters,8,1,99,72,26,4.0,1,49,Semi-Urban,Data Analyst,149360,0 +73171,Female,33,Bachelors,11,63,39,62,23,9.0,1,88,Rural,Data Analyst,98971,1 +73172,Male,42,Bachelors,5,4,63,48,17,2.0,3,2,Rural,ML Engineer,86053,0 +73173,Female,43,Diploma,5,65,69,98,2,9.0,4,54,Urban,HR Executive,128018,1 +73174,Male,23,Bachelors,7,11,49,35,25,4.0,6,93,Urban,Data Analyst,58060,0 +73175,Female,26,Masters,7,74,68,93,83,1.0,7,58,Urban,Data Analyst,113759,1 +73176,Female,28,Bachelors,8,56,21,55,85,0.0,0,79,Rural,Manager,144398,0 +73177,Female,25,High School,1,84,92,4,84,5.0,0,65,Semi-Urban,Manager,105941,1 +73178,Male,41,Bachelors,19,7,9,6,70,7.0,6,41,Urban,Software Engineer,149057,0 +73179,Female,46,Bachelors,3,53,54,35,17,9.0,3,66,Rural,Data Analyst,148602,0 +73180,Other,43,High School,3,69,83,97,32,6.0,0,89,Semi-Urban,HR Executive,75102,1 +73181,Male,38,Bachelors,19,73,66,33,11,3.0,5,62,Urban,Manager,54477,0 +73182,Male,47,Bachelors,4,53,99,23,36,9.0,3,91,Semi-Urban,Software Engineer,89004,1 +73183,Female,59,Diploma,1,28,33,15,1,4.0,7,43,Semi-Urban,Software Engineer,114206,0 +73184,Male,38,High School,5,76,7,90,58,3.0,4,19,Semi-Urban,Manager,87825,0 +73185,Male,31,High School,7,37,60,53,97,0.0,2,61,Urban,Software Engineer,69225,0 +73186,Male,58,Bachelors,8,22,64,62,14,4.0,1,26,Rural,Software Engineer,120283,0 +73187,Female,42,Diploma,16,62,75,96,62,2.0,7,84,Rural,ML Engineer,38521,1 +73188,Male,52,Masters,18,62,14,4,12,3.0,1,16,Rural,Data Analyst,51612,0 +73189,Male,59,Diploma,13,46,58,38,68,3.0,1,2,Urban,HR Executive,36083,0 +73190,Male,32,Diploma,2,48,24,66,27,8.0,5,7,Rural,ML Engineer,81024,0 +73191,Female,29,High School,19,71,25,4,37,5.0,2,13,Semi-Urban,Software Engineer,74771,0 +73192,Male,21,Masters,7,22,49,53,25,9.0,7,62,Semi-Urban,ML Engineer,40629,0 +73193,Male,50,Bachelors,6,1,9,2,65,2.0,5,44,Rural,ML Engineer,26707,0 +73194,Other,49,Bachelors,14,41,91,89,61,1.0,4,18,Urban,Manager,126095,0 +73195,Male,56,Bachelors,19,47,77,48,36,5.0,6,99,Urban,HR Executive,50893,1 +73196,Female,23,High School,3,28,75,11,14,2.0,1,49,Urban,Data Analyst,44355,0 +73197,Male,24,PhD,7,0,46,74,7,8.0,4,81,Rural,Software Engineer,21449,0 +73198,Male,29,Bachelors,12,91,62,19,8,7.0,7,62,Rural,Manager,90281,0 +73199,Female,48,Masters,19,56,89,75,97,0.0,6,87,Urban,Manager,30189,1 +73200,Other,42,Bachelors,11,91,99,7,75,8.0,1,0,Urban,Manager,38415,0 +73201,Female,27,Masters,6,30,67,66,70,7.0,5,15,Urban,Manager,43868,0 +73202,Female,46,Masters,0,55,81,3,45,5.0,5,1,Urban,Software Engineer,77451,0 +73203,Female,51,PhD,8,38,41,60,96,7.0,4,10,Semi-Urban,Software Engineer,33423,0 +73204,Male,36,Masters,1,73,89,83,6,6.0,3,29,Urban,Manager,29684,1 +73205,Female,49,High School,11,84,91,97,38,6.0,3,45,Semi-Urban,Manager,34379,1 +73206,Male,45,Bachelors,4,24,93,80,64,1.0,6,29,Urban,ML Engineer,117942,0 +73207,Female,52,Diploma,0,9,3,73,5,5.0,3,50,Semi-Urban,ML Engineer,31150,0 +73208,Male,54,Masters,10,71,47,1,46,4.0,5,58,Semi-Urban,HR Executive,72719,0 +73209,Male,27,Bachelors,13,31,91,60,96,8.0,3,12,Urban,Manager,30632,0 +73210,Female,26,Bachelors,12,75,70,18,44,2.0,2,42,Rural,Software Engineer,43583,0 +73211,Female,23,Bachelors,7,12,78,16,89,8.0,0,0,Rural,Data Analyst,38574,0 +73212,Male,28,Bachelors,9,22,10,15,21,9.0,1,0,Rural,ML Engineer,144195,0 +73213,Male,58,Masters,14,60,91,58,81,4.0,2,66,Urban,Data Analyst,64013,1 +73214,Female,46,Bachelors,13,6,13,98,35,5.0,1,19,Semi-Urban,HR Executive,67892,0 +73215,Male,46,Bachelors,17,55,51,78,8,6.0,5,96,Urban,Data Analyst,126711,1 +73216,Male,39,Masters,10,39,44,21,91,0.0,7,37,Urban,HR Executive,51261,0 +73217,Male,35,Diploma,5,93,52,90,34,6.0,3,33,Rural,Software Engineer,71784,1 +73218,Male,32,Masters,5,38,87,64,57,9.0,3,32,Semi-Urban,Manager,34699,0 +73219,Female,22,Bachelors,10,73,74,94,93,0.0,6,45,Urban,Data Analyst,43804,1 +73220,Male,46,High School,17,21,32,17,33,6.0,2,77,Semi-Urban,Manager,144767,0 +73221,Female,51,Bachelors,6,59,51,69,56,2.0,5,70,Urban,Manager,52537,1 +73222,Male,24,Masters,19,20,29,1,73,0.0,3,44,Urban,Manager,122877,0 +73223,Female,25,High School,17,9,12,90,66,0.0,1,51,Urban,Manager,45252,0 +73224,Male,22,Masters,15,27,27,89,6,6.0,3,1,Semi-Urban,HR Executive,55546,0 +73225,Male,51,Diploma,19,60,35,27,78,3.0,4,8,Urban,Manager,26443,0 +73226,Male,51,Masters,14,73,41,7,45,6.0,4,36,Rural,ML Engineer,79972,0 +73227,Male,36,Bachelors,7,58,36,82,87,2.0,2,51,Semi-Urban,Software Engineer,83282,0 +73228,Male,30,Bachelors,1,10,85,88,70,7.0,4,21,Urban,Data Analyst,96683,0 +73229,Male,45,Masters,14,64,81,96,54,5.0,4,18,Rural,ML Engineer,20706,1 +73230,Male,55,PhD,10,31,58,57,98,4.0,1,95,Rural,Manager,119138,1 +73231,Female,25,Bachelors,3,10,33,20,44,7.0,2,76,Urban,Manager,123310,0 +73232,Male,28,Bachelors,14,55,1,9,34,6.0,6,63,Semi-Urban,HR Executive,143529,0 +73233,Male,49,Masters,1,53,15,12,52,1.0,2,83,Rural,ML Engineer,92358,0 +73234,Female,33,Bachelors,17,79,89,81,90,9.0,1,24,Urban,Data Analyst,67646,1 +73235,Female,25,Bachelors,19,19,95,51,38,2.0,1,90,Urban,Software Engineer,85215,1 +73236,Male,34,Masters,12,27,15,10,3,3.0,4,65,Semi-Urban,HR Executive,87847,0 +73237,Male,42,Masters,3,97,5,18,62,8.0,5,22,Rural,Software Engineer,31024,0 +73238,Male,56,Bachelors,1,17,49,21,29,9.0,5,24,Semi-Urban,Software Engineer,118985,0 +73239,Male,34,Bachelors,1,62,37,78,6,0.0,4,48,Urban,HR Executive,88738,0 +73240,Female,44,Bachelors,2,73,30,91,73,3.0,2,5,Rural,Manager,49983,0 +73241,Female,39,Masters,12,88,84,4,34,0.0,4,66,Urban,Software Engineer,116022,1 +73242,Female,49,Bachelors,7,53,1,74,94,1.0,0,11,Semi-Urban,Software Engineer,29265,0 +73243,Female,29,Bachelors,7,41,27,18,95,8.0,0,80,Rural,Data Analyst,141150,0 +73244,Male,45,High School,6,27,21,61,23,2.0,1,72,Rural,ML Engineer,118856,0 +73245,Male,28,Bachelors,5,11,21,49,1,9.0,0,53,Rural,HR Executive,96921,0 +73246,Other,57,High School,16,26,76,50,15,2.0,7,34,Urban,HR Executive,33398,0 +73247,Male,56,Diploma,14,61,2,41,96,8.0,5,22,Rural,Data Analyst,62327,0 +73248,Male,33,Bachelors,9,71,13,46,30,9.0,5,24,Semi-Urban,Data Analyst,28624,0 +73249,Male,29,Diploma,3,51,59,4,67,8.0,1,96,Semi-Urban,Data Analyst,59709,0 +73250,Male,39,Masters,15,23,57,5,60,8.0,5,41,Rural,Software Engineer,28416,0 +73251,Male,48,Masters,13,12,72,77,3,7.0,1,42,Urban,ML Engineer,44029,0 +73252,Male,29,High School,3,51,95,75,28,8.0,3,73,Urban,Software Engineer,58342,1 +73253,Male,36,Bachelors,19,87,11,12,3,9.0,5,62,Semi-Urban,Software Engineer,140349,0 +73254,Male,40,Bachelors,5,32,49,29,72,9.0,2,43,Rural,HR Executive,121486,0 +73255,Male,53,Masters,5,94,40,25,3,0.0,3,20,Urban,Manager,102467,0 +73256,Male,51,Bachelors,19,27,32,58,98,8.0,0,1,Urban,Software Engineer,60445,0 +73257,Male,42,High School,14,1,15,61,62,9.0,6,54,Rural,HR Executive,122000,0 +73258,Male,21,High School,17,32,73,28,87,3.0,3,59,Urban,Manager,72041,0 +73259,Female,36,Diploma,1,6,63,16,64,3.0,4,34,Semi-Urban,Manager,41605,0 +73260,Female,53,Diploma,11,84,92,7,87,2.0,0,11,Urban,Data Analyst,78025,0 +73261,Female,45,Bachelors,7,25,90,74,99,0.0,2,28,Semi-Urban,Manager,142998,0 +73262,Female,43,Masters,8,30,14,85,33,9.0,1,28,Urban,Data Analyst,67730,0 +73263,Other,42,Bachelors,12,42,91,62,52,3.0,0,52,Semi-Urban,Software Engineer,113764,1 +73264,Other,57,Masters,3,9,70,60,21,9.0,3,13,Rural,ML Engineer,101985,0 +73265,Female,56,Bachelors,10,97,83,34,22,4.0,3,88,Urban,Data Analyst,22028,1 +73266,Female,42,Diploma,1,16,78,74,18,2.0,1,5,Urban,ML Engineer,135238,0 +73267,Male,33,Masters,2,43,73,49,3,2.0,1,63,Semi-Urban,Data Analyst,75933,0 +73268,Male,23,PhD,19,99,38,8,66,4.0,7,50,Urban,Software Engineer,100909,0 +73269,Male,21,Diploma,15,18,11,5,8,0.0,1,47,Urban,Software Engineer,133793,0 +73270,Female,28,Bachelors,9,85,27,9,99,5.0,5,83,Urban,Software Engineer,125253,0 +73271,Male,54,Diploma,9,35,64,99,53,9.0,1,80,Urban,Software Engineer,45104,1 +73272,Female,28,Bachelors,13,14,84,13,66,8.0,0,28,Semi-Urban,Software Engineer,23469,0 +73273,Male,49,PhD,8,31,78,94,68,6.0,3,54,Urban,Manager,93414,1 +73274,Male,23,Masters,0,10,97,49,20,0.0,4,66,Semi-Urban,ML Engineer,72591,0 +73275,Male,23,Masters,0,72,84,84,51,5.0,6,17,Rural,Software Engineer,79474,1 +73276,Female,47,High School,8,6,67,3,86,8.0,3,11,Urban,Data Analyst,36548,0 +73277,Male,51,Bachelors,17,69,41,71,39,6.0,6,55,Rural,Manager,84685,1 +73278,Male,38,Bachelors,14,83,41,90,81,7.0,7,30,Urban,Manager,95901,1 +73279,Female,36,Bachelors,5,78,86,99,31,9.0,2,82,Semi-Urban,ML Engineer,113317,1 +73280,Female,50,Bachelors,1,52,17,78,70,5.0,0,95,Urban,HR Executive,77402,1 +73281,Male,32,Bachelors,10,76,70,39,85,5.0,2,87,Semi-Urban,Software Engineer,120762,1 +73282,Male,26,Diploma,0,42,41,29,18,4.0,7,74,Urban,Manager,120433,0 +73283,Female,49,High School,12,81,45,80,51,3.0,7,58,Urban,Manager,64959,1 +73284,Female,50,High School,10,55,59,92,21,4.0,0,95,Rural,Manager,45263,1 +73285,Male,45,Bachelors,17,71,21,41,38,1.0,2,44,Rural,Software Engineer,33991,0 +73286,Male,56,Bachelors,9,93,10,11,19,7.0,4,98,Semi-Urban,HR Executive,48324,0 +73287,Female,45,Masters,1,24,15,0,16,3.0,1,37,Rural,Software Engineer,91273,0 +73288,Other,42,Bachelors,17,82,49,80,42,2.0,6,25,Rural,HR Executive,125155,0 +73289,Male,47,High School,10,0,25,32,78,8.0,3,47,Urban,HR Executive,40103,0 +73290,Male,40,Bachelors,15,41,35,78,39,0.0,7,68,Semi-Urban,HR Executive,58378,0 +73291,Male,32,Bachelors,8,30,85,41,78,8.0,0,85,Semi-Urban,Software Engineer,136017,1 +73292,Female,40,High School,18,12,90,51,41,4.0,0,93,Semi-Urban,Data Analyst,100561,1 +73293,Male,52,Bachelors,4,38,96,45,26,5.0,3,98,Rural,HR Executive,31230,1 +73294,Male,49,Masters,19,9,44,68,34,6.0,1,93,Urban,ML Engineer,35493,0 +73295,Male,32,Diploma,12,20,51,39,61,6.0,3,82,Urban,Data Analyst,129453,0 +73296,Female,39,Bachelors,19,28,54,8,33,7.0,7,92,Urban,Data Analyst,41293,0 +73297,Male,34,Diploma,6,93,77,79,18,4.0,1,97,Rural,Software Engineer,99817,1 +73298,Male,35,High School,7,86,72,6,60,1.0,6,73,Urban,Software Engineer,54286,1 +73299,Female,56,Masters,8,67,31,13,20,0.0,2,3,Rural,Manager,102576,0 +73300,Female,56,Diploma,17,30,23,41,92,9.0,1,94,Semi-Urban,Manager,97957,0 +73301,Female,57,Bachelors,4,0,6,94,96,7.0,0,92,Semi-Urban,HR Executive,65853,0 +73302,Male,48,Bachelors,6,34,72,90,45,1.0,4,26,Semi-Urban,ML Engineer,36988,0 +73303,Female,23,Bachelors,17,50,8,32,27,7.0,5,71,Urban,HR Executive,134122,0 +73304,Female,56,Diploma,8,23,60,88,21,6.0,5,70,Semi-Urban,Manager,75296,1 +73305,Female,27,Diploma,11,5,88,93,31,6.0,5,51,Urban,HR Executive,77124,0 +73306,Male,24,Bachelors,8,65,91,37,85,3.0,6,78,Urban,Manager,60106,1 +73307,Male,31,Diploma,10,49,24,73,46,4.0,6,12,Urban,Manager,30699,0 +73308,Female,34,Diploma,4,34,71,50,73,9.0,3,35,Urban,Data Analyst,109956,0 +73309,Male,44,Bachelors,17,71,79,58,12,0.0,1,17,Urban,Software Engineer,67301,0 +73310,Female,57,Bachelors,3,66,71,28,13,5.0,0,83,Urban,ML Engineer,81382,1 +73311,Female,44,Bachelors,15,1,60,55,4,6.0,5,53,Urban,Software Engineer,78760,0 +73312,Female,46,High School,1,34,4,48,25,6.0,3,37,Rural,ML Engineer,84971,0 +73313,Female,36,Masters,7,94,87,37,97,9.0,0,92,Urban,Software Engineer,66498,1 +73314,Male,26,Diploma,0,88,2,18,1,5.0,6,33,Semi-Urban,ML Engineer,122302,0 +73315,Male,56,Diploma,8,6,51,8,94,4.0,1,67,Urban,Manager,33051,0 +73316,Female,46,Diploma,11,33,74,74,89,9.0,6,76,Semi-Urban,ML Engineer,27928,1 +73317,Female,30,Bachelors,18,80,67,43,24,6.0,6,79,Urban,Manager,61834,1 +73318,Male,39,Masters,3,26,82,92,31,2.0,4,60,Rural,Data Analyst,83809,1 +73319,Male,37,Masters,13,41,37,85,36,7.0,5,21,Urban,HR Executive,89101,0 +73320,Male,45,High School,12,22,52,38,74,1.0,1,67,Semi-Urban,Manager,76558,0 +73321,Female,42,Diploma,4,13,14,3,33,9.0,2,73,Urban,Manager,76553,0 +73322,Male,35,Bachelors,4,43,92,38,48,9.0,5,72,Urban,Manager,38856,1 +73323,Male,23,Bachelors,16,30,78,54,77,8.0,1,88,Urban,Data Analyst,147393,1 +73324,Male,23,Diploma,19,57,68,18,92,8.0,4,80,Semi-Urban,HR Executive,121848,0 +73325,Female,45,High School,16,34,5,46,92,6.0,2,64,Urban,HR Executive,45953,0 +73326,Male,58,Bachelors,4,61,12,88,0,9.0,7,16,Urban,Manager,42665,0 +73327,Male,27,Bachelors,18,26,75,66,31,2.0,1,95,Urban,Data Analyst,49739,1 +73328,Male,50,Bachelors,6,58,7,5,69,3.0,0,68,Urban,Software Engineer,48748,0 +73329,Female,40,High School,14,27,54,17,33,0.0,3,61,Urban,ML Engineer,52642,0 +73330,Male,44,High School,3,88,99,94,17,6.0,2,82,Urban,Manager,86901,1 +73331,Male,49,High School,2,15,40,17,57,1.0,5,95,Semi-Urban,Data Analyst,48729,0 +73332,Male,47,Bachelors,12,75,1,77,39,5.0,7,92,Urban,Software Engineer,80556,1 +73333,Male,53,Bachelors,13,0,4,1,39,1.0,4,65,Urban,HR Executive,106443,0 +73334,Female,37,PhD,2,43,41,24,76,0.0,6,72,Urban,Manager,40618,0 +73335,Male,51,Bachelors,17,60,30,95,4,2.0,4,44,Rural,Software Engineer,25606,0 +73336,Female,59,Masters,0,66,74,40,53,5.0,4,14,Rural,Software Engineer,112560,0 +73337,Female,53,Bachelors,3,99,41,90,17,1.0,4,55,Urban,ML Engineer,131176,1 +73338,Female,27,Masters,16,6,77,3,76,7.0,6,54,Urban,Data Analyst,70292,0 +73339,Male,51,High School,7,30,42,15,64,5.0,4,88,Urban,Software Engineer,101902,0 +73340,Male,46,Masters,4,3,17,92,94,4.0,5,23,Semi-Urban,Data Analyst,105607,0 +73341,Female,23,Bachelors,17,76,54,75,61,1.0,3,15,Urban,Software Engineer,55832,0 +73342,Male,21,Masters,7,66,13,64,41,9.0,0,99,Urban,ML Engineer,52720,1 +73343,Male,37,Diploma,10,31,86,47,52,6.0,2,38,Urban,HR Executive,76585,0 +73344,Male,31,Bachelors,7,8,46,88,12,5.0,6,56,Semi-Urban,Software Engineer,128707,0 +73345,Male,50,Bachelors,16,95,4,78,27,4.0,5,42,Urban,Manager,60868,0 +73346,Male,32,Diploma,16,21,44,15,26,5.0,0,73,Urban,Software Engineer,141255,0 +73347,Male,28,Bachelors,15,86,92,44,17,2.0,7,27,Urban,Data Analyst,38919,1 +73348,Male,52,Bachelors,8,13,46,64,19,3.0,3,35,Semi-Urban,Data Analyst,76810,0 +73349,Female,34,Bachelors,17,10,88,86,49,5.0,1,89,Urban,Manager,45635,1 +73350,Female,52,Masters,13,69,44,81,46,2.0,2,33,Urban,Software Engineer,39179,0 +73351,Male,53,Diploma,2,7,71,52,2,2.0,2,25,Urban,Data Analyst,26363,0 +73352,Female,33,Masters,10,32,19,27,58,3.0,1,24,Urban,HR Executive,136351,0 +73353,Other,37,Bachelors,6,92,94,96,42,3.0,2,92,Rural,ML Engineer,68727,1 +73354,Female,37,Bachelors,2,42,17,19,92,1.0,1,17,Rural,Software Engineer,73783,0 +73355,Female,55,Bachelors,16,58,4,83,20,9.0,4,46,Urban,ML Engineer,29371,0 +73356,Male,46,Bachelors,15,14,16,69,25,5.0,3,79,Rural,Data Analyst,94828,0 +73357,Other,44,Bachelors,11,33,35,29,4,3.0,5,33,Urban,Data Analyst,113793,0 +73358,Male,23,Bachelors,3,53,4,78,7,2.0,5,53,Rural,HR Executive,126049,0 +73359,Female,31,Diploma,13,56,2,91,39,6.0,6,90,Urban,Data Analyst,127839,0 +73360,Male,52,Bachelors,0,31,2,2,66,6.0,4,85,Semi-Urban,ML Engineer,114109,0 +73361,Male,26,High School,7,63,16,55,6,8.0,6,37,Semi-Urban,Manager,27669,0 +73362,Male,41,Diploma,9,86,21,56,73,8.0,4,55,Urban,ML Engineer,75690,0 +73363,Male,36,Masters,14,41,63,39,34,1.0,1,95,Urban,ML Engineer,76639,1 +73364,Female,50,Diploma,14,95,54,1,19,2.0,0,26,Semi-Urban,Software Engineer,74670,0 +73365,Female,27,High School,1,79,44,56,40,7.0,4,15,Semi-Urban,HR Executive,98480,0 +73366,Male,58,PhD,15,26,5,42,15,8.0,3,58,Semi-Urban,Manager,147116,0 +73367,Female,33,Bachelors,9,73,26,99,6,2.0,1,11,Urban,Data Analyst,89613,0 +73368,Female,50,Masters,14,98,69,5,38,9.0,2,32,Semi-Urban,Data Analyst,108196,0 +73369,Male,40,Diploma,13,19,37,93,28,4.0,6,62,Semi-Urban,Data Analyst,75577,0 +73370,Other,36,Bachelors,3,76,84,2,12,2.0,1,2,Urban,Software Engineer,22779,0 +73371,Male,35,Bachelors,15,74,85,93,74,8.0,1,1,Urban,Manager,116809,1 +73372,Female,52,Diploma,19,48,76,61,94,4.0,7,99,Semi-Urban,Manager,27855,1 +73373,Other,43,Bachelors,9,8,38,40,84,9.0,1,88,Rural,Manager,81586,0 +73374,Male,38,High School,10,10,36,96,35,6.0,5,70,Urban,ML Engineer,115241,0 +73375,Female,53,Bachelors,4,26,60,72,2,3.0,3,10,Urban,ML Engineer,56692,0 +73376,Female,57,High School,12,43,97,31,19,5.0,1,0,Urban,ML Engineer,116333,0 +73377,Female,41,Masters,5,49,87,32,49,0.0,1,29,Urban,Manager,82880,0 +73378,Male,43,Diploma,9,33,66,47,16,1.0,0,98,Rural,Manager,21646,1 +73379,Female,41,Masters,11,37,81,40,34,5.0,7,18,Urban,Data Analyst,124284,0 +73380,Female,27,Bachelors,13,89,26,66,42,1.0,0,31,Urban,Data Analyst,130165,0 +73381,Male,47,Masters,12,96,91,1,88,7.0,6,45,Rural,Data Analyst,33797,0 +73382,Male,40,Diploma,4,2,56,91,59,3.0,4,85,Semi-Urban,Software Engineer,35998,0 +73383,Female,28,Diploma,16,32,15,12,87,2.0,0,74,Rural,ML Engineer,76212,0 +73384,Male,33,Masters,4,54,81,39,15,7.0,5,12,Urban,Manager,107110,0 +73385,Female,27,High School,18,89,68,78,8,8.0,0,44,Rural,Manager,71054,1 +73386,Male,57,High School,4,24,90,56,67,5.0,4,38,Urban,Manager,83119,0 +73387,Female,47,Bachelors,8,38,37,15,90,7.0,0,62,Semi-Urban,HR Executive,62198,0 +73388,Male,47,Masters,15,52,73,26,49,8.0,2,18,Urban,ML Engineer,36514,0 +73389,Female,24,Diploma,18,25,63,4,51,2.0,1,15,Urban,Software Engineer,79780,0 +73390,Female,25,Masters,3,92,49,25,25,9.0,2,8,Semi-Urban,HR Executive,112920,0 +73391,Male,59,PhD,4,62,76,29,15,6.0,6,37,Urban,ML Engineer,102236,0 +73392,Female,59,Diploma,3,3,21,26,23,0.0,0,88,Rural,Data Analyst,97256,0 +73393,Male,53,Diploma,15,72,53,93,22,2.0,0,68,Urban,Manager,110260,1 +73394,Male,47,High School,8,82,91,12,81,2.0,5,43,Urban,Manager,142678,0 +73395,Male,34,Diploma,16,54,37,56,71,6.0,4,24,Semi-Urban,HR Executive,132012,0 +73396,Male,49,Masters,3,92,16,86,88,1.0,2,76,Semi-Urban,HR Executive,38648,1 +73397,Other,24,Masters,7,64,33,3,77,7.0,6,33,Urban,ML Engineer,130331,0 +73398,Male,23,Bachelors,17,96,53,29,29,7.0,7,38,Urban,Manager,39682,0 +73399,Male,35,Bachelors,18,60,68,35,12,1.0,4,19,Rural,Software Engineer,55489,0 +73400,Male,43,Bachelors,7,45,80,99,85,0.0,0,59,Urban,Manager,39382,1 +73401,Other,43,Bachelors,3,82,70,94,71,4.0,7,89,Urban,Data Analyst,126292,1 +73402,Male,49,High School,10,61,25,10,2,8.0,3,43,Semi-Urban,Manager,106169,0 +73403,Male,29,Bachelors,4,55,27,76,78,3.0,2,93,Semi-Urban,Software Engineer,74364,1 +73404,Female,48,Bachelors,9,60,70,52,3,5.0,1,11,Urban,HR Executive,40892,0 +73405,Female,47,Diploma,6,33,23,64,26,0.0,3,96,Semi-Urban,HR Executive,45197,0 +73406,Female,35,Masters,18,83,45,54,55,5.0,2,69,Semi-Urban,Data Analyst,46983,1 +73407,Female,36,Diploma,6,37,11,22,19,5.0,5,2,Urban,Data Analyst,25745,0 +73408,Male,49,Bachelors,13,50,3,63,47,0.0,2,11,Urban,Data Analyst,27929,0 +73409,Female,36,Bachelors,4,62,58,63,64,2.0,2,37,Urban,HR Executive,31949,0 +73410,Female,43,Masters,6,35,32,24,16,4.0,7,83,Urban,HR Executive,85845,0 +73411,Female,27,High School,16,95,47,38,44,8.0,5,91,Urban,ML Engineer,107364,1 +73412,Male,31,Diploma,6,96,81,61,86,6.0,0,51,Semi-Urban,HR Executive,31946,1 +73413,Male,45,High School,15,55,60,92,16,9.0,2,56,Semi-Urban,Manager,97165,1 +73414,Male,25,High School,0,56,38,5,54,8.0,0,22,Rural,Data Analyst,43926,0 +73415,Female,41,Bachelors,13,80,75,32,71,4.0,5,60,Urban,HR Executive,35755,1 +73416,Female,32,Masters,15,86,42,25,76,6.0,0,76,Urban,Software Engineer,40157,0 +73417,Male,30,Masters,3,6,56,23,46,2.0,6,50,Urban,Data Analyst,29932,0 +73418,Male,39,Bachelors,19,17,87,94,46,1.0,3,9,Urban,HR Executive,142709,0 +73419,Other,22,Diploma,8,82,81,82,99,5.0,6,53,Urban,HR Executive,65775,1 +73420,Male,52,Masters,9,67,34,21,5,0.0,6,3,Urban,Software Engineer,139075,0 +73421,Female,39,PhD,9,2,44,2,94,9.0,6,7,Urban,ML Engineer,36404,0 +73422,Male,56,Bachelors,16,32,87,43,97,1.0,4,39,Urban,ML Engineer,80924,0 +73423,Female,21,Diploma,2,85,6,99,18,5.0,6,46,Rural,Manager,72704,0 +73424,Male,41,High School,17,56,3,3,91,6.0,5,25,Semi-Urban,ML Engineer,99836,0 +73425,Female,41,Diploma,4,14,48,99,17,7.0,5,39,Rural,HR Executive,65443,0 +73426,Female,26,Bachelors,10,86,75,11,79,3.0,6,96,Urban,Data Analyst,94309,1 +73427,Female,34,Bachelors,3,83,38,18,15,3.0,1,9,Urban,Data Analyst,106185,0 +73428,Male,26,Masters,10,64,67,63,30,4.0,1,69,Semi-Urban,Data Analyst,131716,1 +73429,Female,30,Masters,10,92,11,1,5,4.0,3,13,Urban,ML Engineer,62915,0 +73430,Male,36,High School,17,90,66,30,21,8.0,7,93,Urban,HR Executive,93793,1 +73431,Other,41,Bachelors,2,7,27,16,92,6.0,4,3,Urban,Data Analyst,38483,0 +73432,Male,41,Bachelors,17,37,62,34,4,9.0,4,57,Rural,HR Executive,77849,0 +73433,Female,26,Bachelors,4,26,18,71,92,4.0,5,99,Rural,Software Engineer,140916,0 +73434,Male,51,Masters,8,78,72,76,73,7.0,6,74,Urban,ML Engineer,132515,1 +73435,Male,52,Bachelors,1,71,71,77,83,6.0,2,80,Rural,Software Engineer,68183,1 +73436,Male,49,Diploma,5,29,93,59,81,0.0,5,99,Urban,Manager,23344,1 +73437,Male,28,Diploma,5,49,19,67,23,2.0,5,74,Urban,Data Analyst,98294,0 +73438,Male,47,Bachelors,18,55,72,52,31,6.0,4,0,Urban,ML Engineer,76465,0 +73439,Male,27,PhD,9,84,32,82,82,8.0,0,12,Urban,ML Engineer,36488,0 +73440,Male,48,High School,15,99,5,80,83,5.0,5,60,Urban,Data Analyst,86680,1 +73441,Male,21,Bachelors,2,44,86,70,56,9.0,2,87,Rural,ML Engineer,83627,1 +73442,Male,33,Diploma,9,43,21,5,84,2.0,2,30,Urban,Data Analyst,40498,0 +73443,Male,51,High School,12,39,24,90,37,8.0,2,29,Semi-Urban,Software Engineer,70614,0 +73444,Female,39,Diploma,0,41,78,9,0,5.0,4,41,Urban,HR Executive,105634,0 +73445,Female,40,Bachelors,9,35,9,67,75,3.0,1,86,Urban,ML Engineer,72653,0 +73446,Male,37,Bachelors,10,79,17,62,34,4.0,3,83,Urban,Data Analyst,29702,1 +73447,Female,22,Bachelors,7,68,8,32,29,0.0,6,55,Urban,Manager,61759,0 +73448,Female,34,Diploma,5,96,2,64,87,3.0,1,15,Urban,Manager,46563,0 +73449,Male,36,PhD,13,34,68,17,42,7.0,6,7,Urban,HR Executive,74872,0 +73450,Female,59,Diploma,4,19,84,12,0,6.0,4,60,Rural,Manager,125048,0 +73451,Female,25,PhD,19,28,20,79,95,4.0,0,79,Semi-Urban,HR Executive,26640,0 +73452,Male,58,Masters,16,62,20,9,6,2.0,2,29,Urban,Manager,69843,0 +73453,Male,53,Bachelors,6,64,37,21,61,1.0,3,6,Semi-Urban,HR Executive,69925,0 +73454,Male,45,High School,2,51,52,31,11,4.0,4,74,Rural,Software Engineer,131446,0 +73455,Male,51,Bachelors,16,80,75,85,93,9.0,0,22,Urban,HR Executive,37217,1 +73456,Female,41,Bachelors,6,29,56,35,36,4.0,6,35,Rural,Data Analyst,121704,0 +73457,Female,23,Bachelors,2,87,21,86,36,9.0,0,63,Urban,Software Engineer,94424,1 +73458,Male,57,Bachelors,3,24,53,39,60,9.0,6,97,Urban,HR Executive,132257,0 +73459,Male,34,Diploma,12,69,96,64,74,6.0,1,44,Urban,HR Executive,132081,1 +73460,Male,21,Masters,0,8,98,15,86,1.0,6,24,Urban,HR Executive,137164,0 +73461,Male,54,Bachelors,19,83,29,1,89,4.0,7,41,Semi-Urban,Software Engineer,20970,0 +73462,Male,58,Masters,19,42,90,29,2,5.0,3,9,Urban,Data Analyst,50630,0 +73463,Male,55,Masters,5,68,53,31,68,8.0,0,93,Rural,Software Engineer,108048,1 +73464,Male,24,Bachelors,1,49,55,17,85,9.0,7,52,Urban,Manager,23392,0 +73465,Male,30,Diploma,12,39,99,21,66,1.0,3,56,Semi-Urban,HR Executive,141585,0 +73466,Male,24,Bachelors,18,48,94,39,0,5.0,3,67,Rural,Software Engineer,93208,1 +73467,Female,22,Bachelors,16,6,84,62,88,8.0,5,53,Rural,ML Engineer,140953,0 +73468,Other,30,Diploma,4,61,24,95,73,3.0,0,25,Urban,Software Engineer,149632,0 +73469,Female,55,Diploma,6,52,68,37,90,3.0,3,28,Urban,HR Executive,56074,0 +73470,Female,58,PhD,2,74,11,50,84,4.0,2,85,Semi-Urban,ML Engineer,40468,0 +73471,Female,30,High School,9,49,30,89,79,0.0,0,42,Urban,ML Engineer,24431,0 +73472,Male,50,Masters,15,74,68,37,43,2.0,3,4,Rural,Manager,102148,0 +73473,Male,30,Bachelors,5,87,78,43,63,6.0,7,52,Urban,Software Engineer,126793,1 +73474,Male,53,High School,8,91,7,70,3,9.0,0,29,Rural,Data Analyst,140234,0 +73475,Male,50,Bachelors,18,75,50,34,11,2.0,5,35,Urban,Data Analyst,46282,0 +73476,Male,22,High School,2,13,40,54,47,0.0,6,36,Urban,ML Engineer,130614,0 +73477,Male,36,Masters,15,67,8,15,10,3.0,5,68,Urban,Software Engineer,84316,0 +73478,Male,28,High School,14,76,16,70,68,0.0,1,44,Urban,Software Engineer,21197,0 +73479,Female,33,Masters,16,32,5,21,67,8.0,0,13,Rural,Data Analyst,24106,0 +73480,Male,49,Diploma,16,12,23,89,67,9.0,1,83,Rural,ML Engineer,32287,0 +73481,Male,23,Bachelors,9,43,0,60,0,9.0,2,6,Semi-Urban,ML Engineer,72182,0 +73482,Female,30,Bachelors,0,50,82,73,53,1.0,5,23,Urban,Data Analyst,118796,0 +73483,Male,49,High School,15,13,51,93,45,4.0,0,62,Urban,ML Engineer,119978,0 +73484,Male,39,High School,13,26,14,16,26,7.0,1,86,Semi-Urban,Software Engineer,79699,0 +73485,Male,47,Bachelors,0,10,15,79,47,6.0,5,63,Urban,Data Analyst,39577,0 +73486,Female,26,Bachelors,10,35,13,18,57,5.0,1,68,Semi-Urban,HR Executive,56383,0 +73487,Male,26,Diploma,1,16,6,82,9,1.0,2,16,Rural,Software Engineer,95588,0 +73488,Female,56,High School,11,74,40,51,99,5.0,1,62,Semi-Urban,HR Executive,23820,0 +73489,Male,52,PhD,12,95,52,33,1,6.0,1,68,Rural,Manager,39973,1 +73490,Male,21,Bachelors,11,92,55,15,24,0.0,5,59,Urban,Software Engineer,36127,0 +73491,Male,46,Masters,3,37,59,12,13,6.0,2,37,Semi-Urban,Data Analyst,105743,0 +73492,Male,49,Diploma,5,64,50,55,25,9.0,1,20,Urban,HR Executive,93476,0 +73493,Female,46,High School,15,6,15,21,62,6.0,6,93,Rural,HR Executive,136645,0 +73494,Male,54,Masters,14,2,11,56,54,9.0,3,26,Rural,Software Engineer,97039,0 +73495,Male,44,Bachelors,13,44,87,40,28,7.0,3,79,Semi-Urban,HR Executive,24166,1 +73496,Male,55,Masters,7,16,46,63,63,6.0,5,25,Semi-Urban,ML Engineer,125582,0 +73497,Female,21,Masters,9,76,37,17,11,7.0,2,57,Semi-Urban,ML Engineer,39429,0 +73498,Male,34,Bachelors,15,80,48,3,42,0.0,3,49,Semi-Urban,ML Engineer,101357,0 +73499,Female,43,Bachelors,8,10,45,70,33,5.0,7,17,Rural,Software Engineer,114602,0 +73500,Male,35,Masters,8,11,83,18,13,9.0,1,93,Semi-Urban,ML Engineer,22091,0 +73501,Female,36,Bachelors,7,4,34,2,76,5.0,7,17,Semi-Urban,Software Engineer,98714,0 +73502,Female,32,High School,3,49,33,80,81,0.0,7,34,Urban,Data Analyst,81722,0 +73503,Male,38,PhD,3,91,67,91,37,6.0,6,89,Urban,Software Engineer,73985,1 +73504,Female,25,Diploma,11,44,34,57,13,1.0,5,25,Urban,Software Engineer,32772,0 +73505,Female,33,Diploma,1,86,37,88,57,6.0,4,18,Urban,HR Executive,67141,0 +73506,Other,23,Bachelors,12,95,6,58,19,1.0,3,73,Urban,HR Executive,69644,0 +73507,Female,59,Masters,13,20,87,77,74,0.0,2,24,Semi-Urban,ML Engineer,28961,0 +73508,Female,59,Diploma,2,19,96,20,34,3.0,7,3,Semi-Urban,Data Analyst,70900,0 +73509,Female,59,Bachelors,8,29,58,64,12,2.0,2,29,Semi-Urban,HR Executive,113822,0 +73510,Male,34,Bachelors,13,83,46,25,1,1.0,5,47,Semi-Urban,Data Analyst,147109,0 +73511,Male,29,Diploma,12,7,37,33,24,7.0,0,95,Semi-Urban,Software Engineer,87049,0 +73512,Male,54,Bachelors,7,19,11,19,54,8.0,2,94,Semi-Urban,HR Executive,91861,0 +73513,Male,41,High School,2,1,44,76,14,4.0,5,46,Urban,HR Executive,97759,0 +73514,Female,53,Masters,3,43,9,62,55,2.0,2,59,Urban,Manager,49297,0 +73515,Male,24,Diploma,14,62,62,48,40,6.0,5,57,Rural,Manager,36981,0 +73516,Male,51,Masters,13,84,13,54,71,4.0,5,5,Semi-Urban,Manager,135264,0 +73517,Male,55,High School,7,61,44,27,95,2.0,1,70,Urban,Manager,132245,0 +73518,Female,37,Diploma,0,39,76,31,34,8.0,0,46,Semi-Urban,HR Executive,50891,0 +73519,Female,39,Masters,10,65,96,31,95,3.0,5,22,Urban,Software Engineer,115757,0 +73520,Female,49,Bachelors,5,50,36,86,70,0.0,7,96,Urban,Data Analyst,122037,1 +73521,Female,53,PhD,12,51,83,77,23,0.0,7,74,Urban,ML Engineer,102490,1 +73522,Male,59,Diploma,3,28,21,45,3,8.0,6,31,Urban,Software Engineer,79804,0 +73523,Other,54,PhD,7,98,27,23,6,8.0,1,45,Urban,HR Executive,39504,0 +73524,Male,23,High School,3,5,12,7,36,8.0,5,6,Semi-Urban,Manager,69591,0 +73525,Male,43,High School,16,16,17,63,63,0.0,4,83,Semi-Urban,Manager,46501,0 +73526,Female,21,Masters,10,49,35,54,86,9.0,7,29,Urban,Software Engineer,24058,0 +73527,Male,40,Diploma,18,22,30,4,42,2.0,5,18,Semi-Urban,Manager,116999,0 +73528,Female,49,Diploma,0,12,12,5,45,1.0,0,76,Urban,Software Engineer,116287,0 +73529,Male,40,Masters,13,26,42,76,42,5.0,1,79,Urban,HR Executive,31129,0 +73530,Male,29,Bachelors,13,36,54,81,50,3.0,3,49,Urban,HR Executive,123541,0 +73531,Male,26,Masters,8,98,84,35,35,1.0,0,28,Rural,ML Engineer,101609,1 +73532,Female,36,Bachelors,5,19,29,76,19,3.0,3,48,Semi-Urban,Data Analyst,103838,0 +73533,Male,46,Masters,12,23,78,74,74,8.0,1,7,Semi-Urban,Software Engineer,147779,0 +73534,Male,26,Masters,3,48,61,63,40,7.0,3,0,Rural,Software Engineer,127226,0 +73535,Female,40,Bachelors,19,11,42,6,11,5.0,1,58,Urban,HR Executive,27222,0 +73536,Female,30,PhD,17,20,8,51,10,0.0,4,79,Semi-Urban,HR Executive,133491,0 +73537,Male,35,High School,10,28,48,74,21,6.0,0,83,Urban,Software Engineer,132207,0 +73538,Male,55,Bachelors,3,72,98,56,71,1.0,1,65,Urban,Manager,148851,1 +73539,Female,32,Diploma,6,57,5,92,38,6.0,3,68,Urban,HR Executive,89813,0 +73540,Male,30,Diploma,8,10,22,56,95,0.0,5,20,Urban,ML Engineer,60544,0 +73541,Other,36,Bachelors,14,89,93,63,13,9.0,2,21,Urban,Manager,83496,1 +73542,Male,51,Bachelors,5,79,9,53,4,2.0,0,62,Urban,ML Engineer,42836,0 +73543,Male,41,Bachelors,12,23,3,97,32,0.0,6,87,Urban,Data Analyst,23965,0 +73544,Male,35,Diploma,13,69,70,20,72,0.0,5,3,Urban,Manager,149436,0 +73545,Male,49,Masters,5,36,91,91,16,9.0,4,85,Rural,Data Analyst,120782,1 +73546,Female,31,Bachelors,13,95,60,58,0,9.0,7,79,Urban,HR Executive,43854,1 +73547,Female,28,Bachelors,7,74,78,83,3,9.0,1,74,Urban,Manager,45297,1 +73548,Male,23,Bachelors,18,50,14,65,90,6.0,2,22,Semi-Urban,Data Analyst,147866,0 +73549,Female,38,High School,11,65,72,42,6,9.0,6,39,Rural,HR Executive,149450,0 +73550,Female,47,Bachelors,9,20,3,19,49,1.0,2,54,Urban,Data Analyst,62545,0 +73551,Male,27,High School,5,63,23,24,7,7.0,2,44,Urban,Data Analyst,123523,0 +73552,Male,21,Bachelors,5,51,76,84,91,0.0,6,14,Urban,ML Engineer,20972,0 +73553,Male,25,High School,1,42,89,13,4,0.0,1,91,Urban,Software Engineer,124172,1 +73554,Female,59,Bachelors,19,29,17,51,2,7.0,7,34,Urban,Data Analyst,22616,0 +73555,Female,38,Bachelors,13,15,74,80,73,0.0,7,97,Semi-Urban,Data Analyst,103440,1 +73556,Male,36,Masters,5,11,43,9,77,1.0,7,27,Semi-Urban,ML Engineer,32315,0 +73557,Female,44,Masters,1,22,8,1,66,5.0,2,7,Semi-Urban,HR Executive,101263,0 +73558,Other,32,Masters,13,54,42,67,7,1.0,5,95,Urban,Software Engineer,133643,1 +73559,Female,47,Bachelors,19,24,82,79,32,8.0,1,30,Urban,Data Analyst,146828,0 +73560,Female,36,Masters,11,10,54,68,9,1.0,7,21,Urban,HR Executive,72105,0 +73561,Male,50,Bachelors,9,99,59,96,10,7.0,4,84,Urban,ML Engineer,71830,1 +73562,Male,37,Bachelors,16,39,40,0,87,2.0,4,38,Urban,Software Engineer,105630,0 +73563,Other,22,Masters,17,82,97,81,60,2.0,7,72,Urban,Software Engineer,26708,1 +73564,Female,59,Masters,16,19,55,13,12,0.0,6,50,Urban,ML Engineer,30597,0 +73565,Female,24,Diploma,13,25,75,79,99,4.0,2,28,Urban,ML Engineer,89359,0 +73566,Male,48,Diploma,3,95,99,28,48,9.0,5,11,Semi-Urban,Data Analyst,134953,0 +73567,Female,57,Diploma,14,41,87,3,53,0.0,6,68,Urban,HR Executive,60674,0 +73568,Female,22,Bachelors,13,63,29,98,44,2.0,3,5,Urban,Manager,125274,0 +73569,Male,23,Diploma,0,39,22,19,52,6.0,6,44,Semi-Urban,ML Engineer,91923,0 +73570,Female,23,High School,16,17,32,35,50,9.0,0,64,Urban,HR Executive,89810,0 +73571,Female,25,Bachelors,2,10,35,36,36,1.0,4,42,Semi-Urban,ML Engineer,74837,0 +73572,Male,59,Bachelors,19,20,36,67,29,5.0,6,88,Semi-Urban,Software Engineer,58263,0 +73573,Male,32,Diploma,10,28,55,67,52,0.0,7,65,Semi-Urban,Data Analyst,93693,0 +73574,Female,34,Bachelors,4,85,27,50,73,3.0,4,46,Urban,Data Analyst,22178,0 +73575,Male,23,Bachelors,1,33,85,34,58,9.0,6,88,Urban,ML Engineer,113285,1 +73576,Female,50,Bachelors,3,19,76,31,96,6.0,2,64,Semi-Urban,ML Engineer,123855,0 +73577,Male,40,Masters,4,86,75,9,20,4.0,2,96,Rural,Software Engineer,45425,1 +73578,Female,39,Bachelors,4,85,99,78,78,2.0,1,10,Semi-Urban,HR Executive,102409,1 +73579,Female,48,Bachelors,4,92,95,80,75,3.0,0,38,Urban,HR Executive,118258,1 +73580,Female,24,Masters,7,28,83,48,28,9.0,2,82,Urban,Software Engineer,74738,1 +73581,Female,50,Bachelors,10,74,17,81,86,4.0,4,97,Rural,Data Analyst,88447,1 +73582,Male,38,Diploma,13,54,68,88,32,2.0,5,6,Urban,Software Engineer,33143,0 +73583,Male,52,Masters,3,95,37,23,29,3.0,3,42,Semi-Urban,Software Engineer,97928,0 +73584,Female,22,Diploma,10,51,22,13,2,8.0,5,57,Semi-Urban,HR Executive,41038,0 +73585,Female,40,Bachelors,0,81,11,94,33,3.0,2,91,Urban,Data Analyst,42328,1 +73586,Male,33,Diploma,12,45,12,41,78,3.0,3,7,Urban,Software Engineer,143665,0 +73587,Female,53,Diploma,3,85,96,95,1,3.0,2,94,Rural,Software Engineer,28341,1 +73588,Male,52,Diploma,6,11,59,34,50,7.0,1,70,Semi-Urban,ML Engineer,103145,0 +73589,Male,41,High School,8,39,45,46,52,1.0,0,50,Urban,Software Engineer,77437,0 +73590,Male,36,Diploma,3,31,5,14,53,1.0,2,84,Urban,HR Executive,36094,0 +73591,Male,44,Bachelors,1,61,71,67,61,8.0,2,37,Urban,ML Engineer,116852,1 +73592,Male,51,Bachelors,10,57,46,83,92,7.0,3,59,Semi-Urban,ML Engineer,120572,1 +73593,Female,42,Masters,18,66,80,48,98,5.0,4,80,Urban,HR Executive,40012,1 +73594,Female,45,Bachelors,11,41,36,27,10,0.0,5,91,Urban,Software Engineer,55755,0 +73595,Male,23,Bachelors,13,37,7,97,40,2.0,6,84,Rural,Software Engineer,111703,0 +73596,Male,57,Masters,1,66,97,65,37,2.0,6,95,Rural,ML Engineer,93490,1 +73597,Male,56,Bachelors,4,60,0,4,12,3.0,4,56,Urban,HR Executive,110317,0 +73598,Male,24,Bachelors,16,33,5,12,4,6.0,7,61,Urban,Manager,91498,0 +73599,Female,39,Diploma,16,57,65,17,10,6.0,7,39,Rural,ML Engineer,62984,0 +73600,Female,21,Bachelors,12,93,10,30,28,3.0,0,1,Semi-Urban,Software Engineer,100557,0 +73601,Female,48,Masters,12,90,1,10,16,5.0,4,74,Urban,Data Analyst,35791,0 +73602,Male,57,Diploma,0,17,89,38,40,5.0,7,69,Rural,ML Engineer,60162,0 +73603,Female,41,High School,7,80,49,41,38,4.0,2,88,Rural,Software Engineer,124583,1 +73604,Male,43,Bachelors,16,52,48,54,0,5.0,2,26,Urban,ML Engineer,106948,0 +73605,Male,47,High School,5,83,25,28,59,3.0,1,78,Urban,HR Executive,41978,0 +73606,Female,53,Bachelors,12,60,41,92,47,0.0,6,7,Urban,Software Engineer,20154,0 +73607,Male,45,Masters,4,9,34,68,72,7.0,6,39,Rural,Software Engineer,124322,0 +73608,Male,48,High School,2,89,1,48,82,0.0,0,23,Urban,Data Analyst,110296,0 +73609,Male,34,Bachelors,13,30,78,35,59,5.0,2,71,Rural,ML Engineer,47999,0 +73610,Male,31,Bachelors,13,64,89,21,59,7.0,2,85,Semi-Urban,ML Engineer,49418,1 +73611,Male,39,Diploma,14,32,41,40,33,7.0,2,33,Semi-Urban,Manager,48456,0 +73612,Female,50,Bachelors,12,6,37,84,3,8.0,4,52,Urban,Manager,40985,0 +73613,Male,40,Bachelors,4,49,37,27,45,5.0,1,96,Semi-Urban,Manager,106376,0 +73614,Male,45,Masters,7,59,73,83,8,5.0,7,23,Urban,Data Analyst,41301,1 +73615,Female,54,Masters,13,87,42,73,29,6.0,1,9,Urban,ML Engineer,52963,0 +73616,Other,31,Diploma,1,4,82,8,12,0.0,4,16,Urban,HR Executive,133648,0 +73617,Female,21,Masters,12,50,95,77,76,2.0,6,98,Semi-Urban,HR Executive,97654,1 +73618,Male,33,Bachelors,18,13,49,85,43,1.0,2,61,Rural,Manager,22900,0 +73619,Female,37,High School,1,79,99,45,12,2.0,6,91,Urban,HR Executive,104326,1 +73620,Female,38,Bachelors,18,21,77,13,63,2.0,6,37,Urban,Software Engineer,113814,0 +73621,Male,32,Bachelors,12,24,2,64,78,8.0,0,85,Urban,Data Analyst,83651,0 +73622,Male,52,High School,9,44,47,59,98,0.0,0,94,Urban,ML Engineer,34651,1 +73623,Female,32,Bachelors,18,61,43,93,38,2.0,6,67,Urban,ML Engineer,29266,1 +73624,Female,33,Diploma,3,22,28,17,93,3.0,3,56,Rural,Data Analyst,52922,0 +73625,Female,39,Bachelors,4,81,21,69,35,7.0,3,44,Semi-Urban,ML Engineer,79022,0 +73626,Female,33,Bachelors,16,92,70,35,81,5.0,2,83,Urban,ML Engineer,47419,1 +73627,Female,23,Bachelors,16,14,56,89,50,9.0,3,76,Urban,ML Engineer,125845,0 +73628,Male,32,Diploma,13,15,67,22,65,3.0,4,30,Urban,HR Executive,94802,0 +73629,Male,23,PhD,9,86,51,85,53,5.0,0,90,Semi-Urban,Manager,23096,1 +73630,Male,34,High School,8,95,73,82,29,8.0,7,0,Urban,Data Analyst,131444,1 +73631,Male,36,Masters,4,24,22,9,63,7.0,6,68,Rural,Manager,107227,0 +73632,Female,45,Diploma,19,97,74,9,19,1.0,0,49,Urban,ML Engineer,121962,0 +73633,Male,59,Masters,3,12,34,98,4,0.0,3,90,Semi-Urban,Manager,108056,0 +73634,Female,31,Bachelors,8,59,41,13,51,5.0,5,85,Rural,HR Executive,77784,0 +73635,Female,28,Masters,10,91,6,29,74,7.0,5,25,Urban,Data Analyst,133124,0 +73636,Male,50,PhD,4,2,47,96,14,6.0,5,57,Urban,ML Engineer,113027,0 +73637,Male,52,Bachelors,15,26,30,71,77,0.0,4,29,Urban,Manager,53161,0 +73638,Male,41,Bachelors,15,82,47,9,5,4.0,6,78,Urban,ML Engineer,74149,0 +73639,Male,34,Bachelors,5,21,8,14,81,4.0,0,69,Urban,Manager,149349,0 +73640,Male,46,Diploma,2,78,47,3,48,7.0,6,33,Semi-Urban,Software Engineer,111156,0 +73641,Male,46,Bachelors,14,64,67,70,50,4.0,6,47,Semi-Urban,Manager,20234,1 +73642,Female,43,High School,1,17,43,27,40,7.0,5,57,Semi-Urban,Data Analyst,25177,0 +73643,Male,48,Bachelors,11,95,49,74,63,7.0,4,29,Semi-Urban,ML Engineer,54269,1 +73644,Male,43,Bachelors,16,79,34,51,0,4.0,0,72,Urban,ML Engineer,115245,1 +73645,Female,31,Masters,14,32,95,46,63,1.0,5,48,Urban,ML Engineer,83862,0 +73646,Male,31,Diploma,0,84,19,84,7,9.0,0,39,Urban,Data Analyst,105465,0 +73647,Male,52,Masters,6,80,35,12,36,8.0,4,88,Semi-Urban,Software Engineer,104273,0 +73648,Female,25,Masters,16,60,56,29,43,7.0,0,35,Semi-Urban,Software Engineer,137668,0 +73649,Male,35,Masters,4,1,16,16,46,3.0,6,88,Urban,Software Engineer,31758,0 +73650,Male,37,Bachelors,1,90,11,29,56,8.0,1,45,Semi-Urban,Manager,104986,0 +73651,Female,34,Bachelors,19,78,36,9,20,3.0,5,16,Urban,Software Engineer,112461,0 +73652,Male,29,Masters,17,94,73,27,99,6.0,7,59,Urban,ML Engineer,146619,1 +73653,Female,34,Masters,14,55,14,90,56,4.0,7,96,Semi-Urban,Software Engineer,99177,1 +73654,Male,35,Bachelors,15,25,49,62,4,3.0,2,49,Semi-Urban,Software Engineer,79389,0 +73655,Female,36,Bachelors,11,96,47,88,26,4.0,7,52,Urban,Manager,127861,1 +73656,Female,32,Diploma,8,32,53,40,93,1.0,6,31,Urban,Manager,49237,0 +73657,Male,36,Bachelors,19,64,59,34,74,1.0,5,82,Urban,Manager,60978,1 +73658,Female,42,Bachelors,1,65,4,25,48,9.0,1,95,Urban,Data Analyst,139302,0 +73659,Other,58,Bachelors,12,83,31,71,74,7.0,2,91,Urban,Data Analyst,52172,1 +73660,Female,31,Bachelors,2,8,65,20,19,3.0,2,28,Semi-Urban,Manager,119630,0 +73661,Female,52,Bachelors,19,26,72,54,84,6.0,1,70,Urban,Software Engineer,70702,0 +73662,Male,28,Bachelors,5,17,57,3,1,0.0,6,58,Semi-Urban,Software Engineer,136154,0 +73663,Male,52,Bachelors,15,70,91,12,82,8.0,7,35,Semi-Urban,Manager,134349,0 +73664,Male,54,High School,13,4,36,97,76,1.0,2,77,Semi-Urban,Data Analyst,27211,0 +73665,Female,59,Bachelors,12,12,39,27,53,5.0,6,74,Urban,HR Executive,90519,0 +73666,Male,48,Bachelors,6,2,89,16,46,5.0,3,33,Semi-Urban,Software Engineer,22844,0 +73667,Female,35,PhD,10,18,85,16,83,8.0,5,79,Urban,Software Engineer,114387,0 +73668,Male,53,Bachelors,3,56,90,15,40,7.0,2,49,Urban,ML Engineer,112272,0 +73669,Male,32,Diploma,7,78,68,92,6,6.0,2,19,Urban,Software Engineer,52855,1 +73670,Male,49,Bachelors,4,74,88,8,97,4.0,7,82,Rural,Data Analyst,21273,1 +73671,Male,38,Bachelors,8,91,90,62,30,2.0,5,0,Rural,Manager,131891,1 +73672,Male,58,Masters,5,75,70,9,28,2.0,3,85,Urban,HR Executive,121948,1 +73673,Male,46,Diploma,19,54,14,36,71,1.0,0,75,Urban,Software Engineer,73297,0 +73674,Male,52,Masters,17,17,22,57,99,9.0,1,70,Urban,HR Executive,104453,0 +73675,Male,56,Masters,16,76,30,72,72,2.0,3,48,Urban,ML Engineer,144881,0 +73676,Male,45,Masters,6,32,89,32,85,1.0,0,39,Urban,Data Analyst,128526,0 +73677,Male,34,PhD,0,2,13,52,23,2.0,3,96,Urban,HR Executive,99822,0 +73678,Female,37,PhD,9,15,70,81,17,9.0,2,32,Urban,Software Engineer,76765,0 +73679,Male,53,Bachelors,13,12,1,79,20,9.0,4,26,Urban,HR Executive,43644,0 +73680,Male,22,Diploma,13,75,82,72,59,3.0,1,12,Urban,Software Engineer,146219,1 +73681,Male,27,Diploma,11,2,29,49,85,7.0,0,37,Urban,Data Analyst,65791,0 +73682,Male,44,High School,17,77,4,58,85,3.0,4,24,Urban,ML Engineer,31780,0 +73683,Male,59,High School,11,27,18,71,24,6.0,3,83,Semi-Urban,ML Engineer,45237,0 +73684,Female,48,PhD,0,7,21,79,38,1.0,7,5,Urban,ML Engineer,106100,0 +73685,Male,58,PhD,18,43,84,96,67,8.0,7,98,Rural,Manager,31660,1 +73686,Male,24,Diploma,0,16,8,30,18,7.0,5,84,Urban,Software Engineer,115067,0 +73687,Male,29,Masters,16,50,69,23,88,4.0,3,55,Semi-Urban,ML Engineer,39196,0 +73688,Male,41,Masters,17,52,66,19,79,5.0,2,81,Semi-Urban,ML Engineer,87703,0 +73689,Male,59,Diploma,16,50,37,5,93,6.0,1,40,Semi-Urban,ML Engineer,77159,0 +73690,Male,46,Diploma,6,3,58,19,30,6.0,2,61,Urban,Data Analyst,47330,0 +73691,Male,29,High School,0,5,18,38,1,7.0,7,61,Semi-Urban,Data Analyst,66168,0 +73692,Male,49,Diploma,8,66,47,24,72,8.0,2,33,Urban,Software Engineer,64866,0 +73693,Male,53,Diploma,6,10,46,60,62,7.0,6,74,Urban,HR Executive,43986,0 +73694,Female,46,Diploma,10,49,31,90,32,4.0,7,89,Semi-Urban,Data Analyst,27631,1 +73695,Female,38,Diploma,9,27,83,30,28,4.0,2,95,Urban,Manager,133164,0 +73696,Male,39,Bachelors,14,46,96,6,91,2.0,3,74,Urban,HR Executive,101746,0 +73697,Male,51,Masters,18,33,57,97,47,3.0,1,59,Rural,HR Executive,62179,1 +73698,Male,24,PhD,7,81,7,39,9,2.0,4,29,Urban,ML Engineer,70836,0 +73699,Male,36,Bachelors,5,21,17,93,72,1.0,0,31,Urban,HR Executive,63095,0 +73700,Female,45,Diploma,6,38,17,86,74,8.0,1,6,Urban,HR Executive,109984,0 +73701,Male,45,Bachelors,18,25,85,55,76,4.0,7,52,Semi-Urban,Data Analyst,36585,0 +73702,Female,53,Diploma,19,76,60,68,36,3.0,2,59,Semi-Urban,Data Analyst,78124,1 +73703,Male,51,High School,15,69,51,53,99,0.0,4,76,Urban,Software Engineer,131038,1 +73704,Male,26,Bachelors,17,72,56,97,30,7.0,0,70,Semi-Urban,Manager,20991,1 +73705,Female,45,Masters,0,41,71,13,1,0.0,3,90,Rural,Data Analyst,142620,0 +73706,Male,30,Masters,3,55,66,52,5,3.0,1,21,Urban,Manager,92321,0 +73707,Male,34,Bachelors,0,93,16,36,24,0.0,3,56,Urban,Software Engineer,125318,0 +73708,Female,56,Bachelors,14,89,55,14,3,0.0,0,97,Semi-Urban,Manager,91816,1 +73709,Female,49,Masters,0,78,1,21,32,2.0,5,77,Urban,ML Engineer,91217,0 +73710,Female,48,Masters,12,13,62,51,83,9.0,1,92,Semi-Urban,Software Engineer,98437,0 +73711,Male,38,Masters,15,73,47,68,92,0.0,2,63,Urban,Manager,24119,1 +73712,Male,21,Bachelors,0,32,61,84,64,0.0,5,58,Urban,HR Executive,68454,1 +73713,Male,59,Diploma,9,3,85,28,54,3.0,4,68,Semi-Urban,ML Engineer,148842,0 +73714,Female,23,Masters,12,47,84,52,47,5.0,2,19,Semi-Urban,Data Analyst,20666,0 +73715,Male,32,Bachelors,19,50,13,51,89,8.0,5,34,Semi-Urban,Software Engineer,58570,0 +73716,Male,56,Masters,19,45,30,4,18,5.0,1,33,Urban,Manager,93573,0 +73717,Female,30,Diploma,7,44,78,22,35,5.0,2,52,Urban,Manager,88673,0 +73718,Female,39,Diploma,11,78,58,71,23,8.0,6,77,Semi-Urban,Manager,55652,1 +73719,Female,23,High School,11,28,13,91,72,8.0,1,68,Urban,Data Analyst,21445,0 +73720,Male,49,Bachelors,6,67,22,52,21,1.0,4,62,Semi-Urban,HR Executive,86715,0 +73721,Male,27,Bachelors,4,68,26,68,6,5.0,3,63,Rural,ML Engineer,100876,0 +73722,Female,55,Bachelors,17,28,7,8,97,6.0,6,59,Rural,Data Analyst,138009,0 +73723,Female,45,Bachelors,0,27,59,97,77,8.0,7,35,Semi-Urban,Data Analyst,53162,0 +73724,Male,40,Bachelors,8,63,65,56,38,7.0,4,37,Urban,Manager,127701,0 +73725,Male,53,Masters,9,21,88,52,40,9.0,7,19,Semi-Urban,ML Engineer,83315,0 +73726,Male,47,Bachelors,17,63,22,23,27,6.0,3,73,Semi-Urban,Manager,61532,0 +73727,Male,57,Bachelors,2,29,16,67,8,1.0,6,88,Semi-Urban,HR Executive,101518,0 +73728,Male,21,Bachelors,12,73,0,17,86,7.0,5,45,Urban,Data Analyst,24487,0 +73729,Male,25,High School,3,12,26,42,53,5.0,2,35,Rural,ML Engineer,59582,0 +73730,Male,44,Bachelors,17,48,8,96,26,7.0,6,92,Semi-Urban,HR Executive,32504,1 +73731,Male,51,Diploma,19,49,4,91,67,3.0,7,30,Urban,Data Analyst,69739,0 +73732,Male,53,Bachelors,10,23,86,49,60,5.0,7,88,Semi-Urban,ML Engineer,63264,1 +73733,Male,38,Masters,18,72,98,32,82,0.0,6,14,Urban,ML Engineer,112153,0 +73734,Female,22,Diploma,10,96,56,28,62,2.0,5,58,Semi-Urban,Software Engineer,91607,0 +73735,Male,37,Masters,6,10,62,92,47,0.0,6,92,Rural,ML Engineer,68653,1 +73736,Female,57,High School,14,47,15,95,61,3.0,0,20,Rural,HR Executive,132077,0 +73737,Female,59,Diploma,10,8,39,92,19,1.0,0,93,Semi-Urban,Software Engineer,68693,0 +73738,Male,25,Diploma,7,88,70,29,68,0.0,1,28,Urban,Manager,87252,0 +73739,Male,34,Masters,12,33,0,66,1,6.0,4,32,Urban,Data Analyst,104618,0 +73740,Male,39,Masters,3,87,24,95,57,9.0,4,87,Urban,Data Analyst,79352,1 +73741,Male,35,Diploma,17,97,45,68,45,8.0,6,78,Semi-Urban,ML Engineer,67114,1 +73742,Male,25,High School,4,96,16,0,52,8.0,2,66,Urban,Software Engineer,141883,0 +73743,Male,51,Bachelors,1,53,43,18,48,2.0,5,53,Urban,Software Engineer,129873,0 +73744,Male,43,Masters,10,62,41,71,37,7.0,7,50,Urban,ML Engineer,82070,0 +73745,Female,54,Bachelors,6,15,54,22,28,9.0,0,62,Semi-Urban,HR Executive,112008,0 +73746,Male,48,High School,3,88,38,76,55,1.0,6,36,Urban,Manager,143271,1 +73747,Female,50,Bachelors,14,27,22,66,82,7.0,0,99,Semi-Urban,Data Analyst,20534,0 +73748,Male,28,Bachelors,19,14,67,8,40,4.0,1,92,Urban,Software Engineer,114906,0 +73749,Female,39,Diploma,15,71,86,45,83,8.0,7,54,Rural,Data Analyst,117976,1 +73750,Male,55,Masters,4,42,5,95,25,8.0,2,80,Urban,Software Engineer,75206,0 +73751,Male,31,Diploma,13,56,94,36,44,4.0,7,56,Semi-Urban,ML Engineer,91233,1 +73752,Male,59,Diploma,15,6,61,3,79,7.0,5,48,Urban,Software Engineer,107263,0 +73753,Male,54,High School,6,93,19,62,30,7.0,2,10,Semi-Urban,HR Executive,67547,0 +73754,Male,44,Masters,12,12,55,26,10,1.0,3,25,Semi-Urban,HR Executive,32882,0 +73755,Male,31,Bachelors,6,59,40,59,58,5.0,1,39,Urban,Data Analyst,72008,0 +73756,Male,27,Bachelors,9,22,76,65,65,4.0,0,18,Rural,Software Engineer,85561,0 +73757,Female,32,High School,2,26,77,30,24,6.0,5,73,Rural,HR Executive,76762,0 +73758,Male,34,Diploma,18,24,92,11,25,6.0,1,18,Rural,Data Analyst,71571,0 +73759,Female,40,Diploma,1,89,92,88,47,1.0,7,23,Urban,Manager,35995,1 +73760,Male,52,High School,14,17,54,25,46,2.0,2,10,Semi-Urban,Data Analyst,60425,0 +73761,Male,54,High School,8,38,28,64,56,9.0,7,40,Urban,Data Analyst,31317,0 +73762,Male,44,High School,7,8,9,40,81,9.0,3,34,Rural,Software Engineer,26453,0 +73763,Male,57,Bachelors,18,32,44,50,10,9.0,2,5,Semi-Urban,Data Analyst,95583,0 +73764,Female,49,Diploma,13,72,5,99,76,2.0,1,31,Urban,Manager,54966,0 +73765,Male,45,Diploma,4,49,18,11,73,9.0,5,5,Rural,HR Executive,142063,0 +73766,Male,41,High School,17,77,44,80,93,3.0,0,98,Rural,Software Engineer,63840,1 +73767,Female,46,Diploma,9,53,78,49,12,6.0,4,22,Urban,ML Engineer,84759,0 +73768,Female,56,Masters,6,31,44,95,42,7.0,5,32,Rural,Data Analyst,99803,0 +73769,Male,50,Bachelors,12,16,78,63,18,1.0,1,68,Urban,Manager,35341,0 +73770,Female,30,Bachelors,6,34,74,25,93,6.0,3,37,Rural,Software Engineer,141979,0 +73771,Male,38,High School,9,29,72,98,43,6.0,0,84,Urban,Manager,70374,1 +73772,Male,59,Masters,2,95,25,9,99,0.0,6,49,Urban,Software Engineer,44946,0 +73773,Female,44,Bachelors,12,34,63,73,43,2.0,3,46,Semi-Urban,Data Analyst,36261,0 +73774,Female,39,High School,4,49,51,73,55,3.0,4,80,Semi-Urban,Manager,33154,1 +73775,Female,43,Masters,4,50,64,85,5,6.0,4,86,Urban,HR Executive,131197,1 +73776,Male,24,Bachelors,1,45,36,85,36,9.0,0,52,Rural,ML Engineer,72459,0 +73777,Male,29,High School,9,70,21,12,30,8.0,1,86,Urban,HR Executive,119402,0 +73778,Female,36,Bachelors,8,46,19,89,24,4.0,3,6,Urban,HR Executive,129749,0 +73779,Male,39,Bachelors,19,9,48,3,24,0.0,5,85,Rural,HR Executive,127083,0 +73780,Female,25,Masters,10,73,49,4,50,8.0,6,45,Semi-Urban,Software Engineer,136547,0 +73781,Male,58,PhD,19,50,72,89,5,4.0,2,63,Semi-Urban,ML Engineer,81747,1 +73782,Male,41,Masters,17,49,51,68,97,4.0,5,42,Urban,ML Engineer,48942,0 +73783,Male,46,Masters,3,97,65,90,63,6.0,0,37,Rural,Software Engineer,127528,1 +73784,Female,45,Masters,17,75,21,4,65,1.0,0,98,Urban,Data Analyst,117219,0 +73785,Male,43,Diploma,13,55,71,48,13,9.0,2,91,Semi-Urban,Software Engineer,77141,1 +73786,Male,43,Diploma,17,45,30,52,72,3.0,3,8,Urban,Data Analyst,98551,0 +73787,Male,57,Masters,6,41,10,75,94,9.0,3,46,Rural,Manager,96015,0 +73788,Male,57,Bachelors,16,15,12,34,89,8.0,1,31,Rural,ML Engineer,29664,0 +73789,Female,39,Bachelors,13,46,59,68,94,4.0,2,62,Rural,Software Engineer,113726,0 +73790,Female,54,Diploma,1,43,8,2,34,0.0,1,47,Rural,ML Engineer,117665,0 +73791,Female,53,Bachelors,7,24,57,99,87,7.0,5,37,Rural,ML Engineer,83540,0 +73792,Male,56,Masters,17,74,72,80,27,5.0,6,86,Urban,Manager,39651,1 +73793,Male,26,Bachelors,4,46,30,5,7,2.0,4,91,Urban,Manager,138526,0 +73794,Female,25,High School,13,18,66,96,66,9.0,1,4,Urban,Manager,91017,0 +73795,Female,51,PhD,4,9,87,94,52,7.0,7,24,Semi-Urban,HR Executive,51926,0 +73796,Other,44,Bachelors,7,81,81,95,53,9.0,7,23,Semi-Urban,ML Engineer,141806,1 +73797,Male,24,Masters,15,17,21,87,56,3.0,5,14,Semi-Urban,HR Executive,95074,0 +73798,Male,55,Bachelors,4,44,26,28,59,5.0,3,78,Urban,HR Executive,143973,0 +73799,Female,46,Masters,2,61,23,59,5,8.0,4,97,Urban,ML Engineer,41442,0 +73800,Other,46,High School,8,56,96,30,76,7.0,2,66,Rural,ML Engineer,145029,1 +73801,Female,49,Bachelors,12,6,23,23,97,1.0,0,27,Urban,Manager,99630,0 +73802,Female,42,Masters,5,7,88,14,92,3.0,2,53,Rural,Data Analyst,117273,0 +73803,Male,38,Bachelors,2,50,23,63,41,4.0,5,28,Urban,Manager,97011,0 +73804,Male,57,Masters,16,43,20,52,86,9.0,1,68,Urban,HR Executive,126606,0 +73805,Female,32,Diploma,2,72,13,8,29,1.0,6,75,Semi-Urban,HR Executive,67227,0 +73806,Male,59,Masters,15,58,71,49,33,6.0,5,90,Semi-Urban,Manager,84161,1 +73807,Other,28,Masters,15,45,18,31,36,0.0,4,93,Semi-Urban,Software Engineer,87172,0 +73808,Male,48,Diploma,12,63,4,56,58,8.0,3,48,Urban,Data Analyst,45948,0 +73809,Male,23,Bachelors,15,33,78,94,78,0.0,4,12,Urban,Software Engineer,88142,0 +73810,Male,43,Bachelors,14,16,86,16,90,2.0,6,44,Rural,HR Executive,47881,0 +73811,Male,39,PhD,16,58,4,24,6,3.0,4,44,Semi-Urban,Data Analyst,119509,0 +73812,Female,58,Bachelors,10,41,3,99,23,9.0,0,53,Urban,Manager,105708,0 +73813,Female,36,Bachelors,13,86,18,74,22,6.0,2,7,Urban,Software Engineer,113854,0 +73814,Male,33,High School,14,96,44,12,32,9.0,2,44,Rural,Manager,37151,0 +73815,Female,46,Bachelors,0,13,2,71,22,4.0,0,97,Rural,Data Analyst,20818,0 +73816,Male,47,Bachelors,16,28,28,40,97,4.0,1,77,Urban,Software Engineer,78761,0 +73817,Male,40,Bachelors,12,0,77,14,11,7.0,1,31,Semi-Urban,Manager,94598,0 +73818,Male,29,Bachelors,9,46,79,51,42,3.0,4,61,Urban,Software Engineer,46784,1 +73819,Female,39,Bachelors,1,31,80,96,14,0.0,4,62,Urban,Software Engineer,23187,1 +73820,Female,47,Bachelors,7,70,81,94,56,2.0,2,67,Semi-Urban,HR Executive,127028,1 +73821,Male,39,High School,10,10,78,81,32,3.0,7,96,Urban,Data Analyst,73143,1 +73822,Male,32,Masters,9,21,91,67,96,1.0,0,67,Urban,Software Engineer,106155,1 +73823,Female,40,Bachelors,1,77,73,96,31,0.0,7,96,Urban,Software Engineer,36400,1 +73824,Male,50,Masters,11,57,72,1,71,3.0,6,58,Urban,HR Executive,24230,0 +73825,Male,50,Bachelors,18,77,88,28,11,1.0,0,92,Urban,ML Engineer,26064,1 +73826,Female,28,Diploma,6,7,59,94,81,7.0,0,27,Urban,HR Executive,88305,0 +73827,Male,29,Bachelors,3,23,79,84,11,9.0,4,45,Semi-Urban,Manager,97979,0 +73828,Male,26,Masters,6,55,34,32,94,6.0,6,18,Rural,HR Executive,32317,0 +73829,Male,32,High School,18,55,53,45,76,2.0,5,96,Urban,ML Engineer,95812,1 +73830,Female,23,High School,3,58,27,55,43,5.0,1,43,Urban,HR Executive,115395,0 +73831,Female,31,Bachelors,19,6,61,16,48,9.0,3,23,Rural,ML Engineer,78237,0 +73832,Male,27,Diploma,6,7,84,3,77,1.0,4,66,Rural,Software Engineer,125880,0 +73833,Male,34,Bachelors,12,52,5,99,20,5.0,3,75,Semi-Urban,Data Analyst,68427,0 +73834,Female,53,Bachelors,1,53,59,68,38,5.0,7,54,Semi-Urban,Data Analyst,97878,0 +73835,Male,45,High School,4,11,78,67,91,7.0,7,98,Urban,ML Engineer,72370,1 +73836,Male,46,Diploma,10,58,98,96,82,4.0,7,11,Urban,Software Engineer,42355,1 +73837,Male,54,Masters,19,13,75,64,92,3.0,7,21,Urban,ML Engineer,86733,0 +73838,Female,58,Bachelors,4,13,41,75,70,2.0,6,77,Urban,Software Engineer,27532,0 +73839,Female,37,Bachelors,13,56,14,46,51,0.0,6,50,Urban,Software Engineer,97713,0 +73840,Male,27,Masters,11,60,44,15,6,8.0,2,93,Rural,Manager,75885,0 +73841,Male,36,High School,10,14,79,44,94,5.0,6,62,Urban,Software Engineer,92153,0 +73842,Female,28,Bachelors,2,94,85,46,49,9.0,7,96,Semi-Urban,ML Engineer,88338,1 +73843,Male,34,Bachelors,6,76,90,24,34,5.0,0,49,Rural,Manager,46921,1 +73844,Male,53,High School,15,87,43,28,90,9.0,5,91,Urban,Manager,141881,1 +73845,Female,24,Diploma,16,30,69,71,95,2.0,3,7,Urban,ML Engineer,27511,0 +73846,Male,38,High School,6,48,84,4,65,2.0,2,86,Urban,Data Analyst,73242,0 +73847,Female,43,Bachelors,12,52,44,95,53,6.0,3,67,Urban,Manager,60699,1 +73848,Male,28,Bachelors,11,94,13,32,11,9.0,1,25,Semi-Urban,Manager,113362,0 +73849,Male,58,Bachelors,19,23,55,2,68,3.0,6,32,Rural,Manager,95042,0 +73850,Male,32,High School,6,98,54,42,41,1.0,6,38,Rural,Data Analyst,33779,0 +73851,Female,59,Bachelors,8,42,1,14,51,5.0,6,77,Rural,Software Engineer,120269,0 +73852,Female,24,Diploma,8,14,19,75,78,3.0,6,32,Urban,Manager,146158,0 +73853,Female,59,Masters,15,41,28,88,47,0.0,0,57,Urban,Software Engineer,69446,0 +73854,Male,52,Masters,2,70,46,77,22,2.0,0,47,Rural,ML Engineer,101353,1 +73855,Female,54,Bachelors,10,43,77,77,39,3.0,0,64,Urban,ML Engineer,37455,1 +73856,Male,31,Masters,19,56,52,32,2,0.0,6,81,Urban,Software Engineer,96705,0 +73857,Female,40,High School,2,26,30,62,27,9.0,3,66,Urban,ML Engineer,49457,0 +73858,Male,56,Bachelors,16,19,46,5,35,6.0,5,79,Urban,Data Analyst,46325,0 +73859,Male,39,High School,19,53,79,78,59,2.0,5,31,Urban,Software Engineer,21549,1 +73860,Male,22,Bachelors,16,17,10,13,7,6.0,4,45,Rural,Data Analyst,55263,0 +73861,Male,48,Masters,5,17,37,32,54,0.0,5,27,Urban,Data Analyst,144872,0 +73862,Male,39,High School,9,80,94,94,25,7.0,0,82,Rural,Manager,39944,1 +73863,Male,32,Diploma,3,17,76,42,31,1.0,0,12,Rural,ML Engineer,25269,0 +73864,Male,29,High School,16,25,99,69,67,6.0,5,14,Urban,Data Analyst,115441,0 +73865,Male,21,High School,2,35,36,29,57,6.0,1,4,Semi-Urban,Software Engineer,43314,0 +73866,Male,42,PhD,9,2,53,86,22,1.0,0,62,Rural,HR Executive,117007,0 +73867,Male,33,Bachelors,5,97,75,27,10,6.0,0,42,Urban,Manager,132157,1 +73868,Male,27,High School,14,94,72,84,13,7.0,7,77,Urban,Manager,100676,1 +73869,Female,35,Bachelors,19,27,23,53,47,3.0,3,64,Semi-Urban,HR Executive,83369,0 +73870,Other,50,Diploma,14,74,35,39,55,8.0,4,44,Semi-Urban,HR Executive,110471,0 +73871,Male,45,Masters,11,11,72,35,27,4.0,4,48,Semi-Urban,HR Executive,23748,0 +73872,Female,40,Bachelors,16,36,79,4,47,6.0,5,90,Urban,Manager,143869,0 +73873,Male,59,Bachelors,2,60,45,45,0,1.0,7,0,Urban,Data Analyst,149711,0 +73874,Female,23,Masters,12,88,28,36,6,5.0,7,79,Urban,HR Executive,127897,0 +73875,Female,42,High School,7,19,0,21,12,4.0,7,82,Semi-Urban,Manager,49499,0 +73876,Male,49,Bachelors,14,59,16,60,39,7.0,7,43,Urban,Manager,101474,0 +73877,Female,56,High School,19,31,56,56,82,6.0,0,54,Semi-Urban,Data Analyst,136805,0 +73878,Female,57,Masters,10,29,11,21,68,6.0,5,62,Rural,Data Analyst,68273,0 +73879,Female,36,Diploma,19,65,16,56,95,2.0,4,99,Urban,Manager,129137,0 +73880,Female,53,Bachelors,15,93,2,61,49,9.0,3,86,Semi-Urban,HR Executive,48822,1 +73881,Female,34,Bachelors,8,36,59,86,38,8.0,6,56,Urban,Software Engineer,127444,0 +73882,Male,25,Bachelors,11,5,71,69,58,9.0,2,86,Urban,ML Engineer,81211,0 +73883,Male,31,High School,9,87,8,34,96,1.0,6,62,Semi-Urban,Software Engineer,62629,0 +73884,Male,27,PhD,0,29,12,77,43,8.0,1,43,Urban,Software Engineer,41576,0 +73885,Male,37,Masters,7,80,76,90,83,0.0,6,81,Semi-Urban,Manager,99128,1 +73886,Male,31,Masters,12,82,58,23,82,5.0,2,24,Semi-Urban,ML Engineer,149060,0 +73887,Female,56,High School,12,94,33,6,96,2.0,1,13,Urban,ML Engineer,103564,0 +73888,Male,44,Diploma,0,87,48,99,15,3.0,1,87,Urban,Software Engineer,113919,1 +73889,Female,40,Diploma,17,97,34,17,81,4.0,6,19,Urban,HR Executive,41863,0 +73890,Female,34,High School,8,43,11,66,72,2.0,6,6,Rural,Software Engineer,121107,0 +73891,Female,24,Bachelors,4,65,93,96,60,1.0,7,17,Urban,ML Engineer,126032,1 +73892,Female,57,High School,12,33,68,20,52,1.0,7,72,Semi-Urban,Data Analyst,74646,0 +73893,Female,27,Bachelors,1,44,72,27,57,0.0,6,14,Rural,Data Analyst,75508,0 +73894,Female,28,High School,2,16,37,85,76,4.0,3,92,Urban,Data Analyst,106001,0 +73895,Male,28,PhD,3,90,74,24,24,9.0,1,22,Semi-Urban,HR Executive,92306,0 +73896,Female,26,Diploma,14,15,70,88,6,1.0,5,62,Semi-Urban,HR Executive,110312,0 +73897,Male,36,Bachelors,17,65,85,41,93,6.0,1,26,Rural,Manager,73548,0 +73898,Female,52,Bachelors,14,28,43,71,16,0.0,4,17,Urban,HR Executive,63069,0 +73899,Male,44,Masters,2,4,24,54,37,8.0,7,53,Urban,HR Executive,31355,0 +73900,Other,41,Bachelors,3,24,67,50,28,4.0,1,28,Urban,Data Analyst,20170,0 +73901,Female,46,Diploma,11,30,43,32,93,6.0,7,76,Urban,HR Executive,77978,0 +73902,Male,41,Bachelors,0,77,73,6,34,7.0,4,66,Urban,ML Engineer,62389,0 +73903,Male,42,PhD,4,31,21,77,88,1.0,7,20,Urban,Manager,129424,0 +73904,Female,37,Bachelors,0,64,52,5,21,5.0,1,4,Semi-Urban,Data Analyst,123089,0 +73905,Male,34,Bachelors,11,18,61,59,27,3.0,4,13,Urban,Software Engineer,97929,0 +73906,Male,31,Bachelors,6,12,84,41,68,4.0,1,17,Semi-Urban,Software Engineer,42718,0 +73907,Male,28,Bachelors,17,63,86,35,82,8.0,3,44,Urban,Manager,66849,0 +73908,Female,49,Bachelors,4,88,21,59,81,9.0,3,67,Semi-Urban,Manager,144770,0 +73909,Male,25,PhD,0,69,94,99,86,6.0,7,9,Rural,HR Executive,135004,1 +73910,Male,39,Masters,9,92,59,34,26,6.0,6,64,Semi-Urban,ML Engineer,96527,1 +73911,Male,21,Diploma,9,0,92,67,14,9.0,4,92,Rural,Data Analyst,149168,1 +73912,Male,22,Bachelors,15,90,46,67,54,3.0,7,69,Rural,ML Engineer,142729,1 +73913,Female,37,Diploma,13,23,68,81,26,0.0,7,28,Semi-Urban,ML Engineer,65198,0 +73914,Male,40,Bachelors,6,96,37,75,43,8.0,7,59,Urban,ML Engineer,96368,1 +73915,Male,53,PhD,7,58,87,19,30,5.0,2,48,Urban,Software Engineer,105669,0 +73916,Female,58,Diploma,10,88,20,60,55,6.0,0,76,Urban,HR Executive,141804,1 +73917,Female,51,Diploma,9,71,89,20,77,9.0,6,31,Urban,ML Engineer,80006,0 +73918,Female,31,Diploma,7,73,60,82,73,7.0,0,34,Urban,Software Engineer,68253,1 +73919,Male,34,Bachelors,16,0,21,6,41,7.0,1,10,Urban,Data Analyst,35834,0 +73920,Male,50,Masters,2,71,89,3,83,8.0,7,67,Urban,Software Engineer,20138,0 +73921,Female,31,High School,12,57,32,45,38,5.0,5,36,Urban,Manager,42377,0 +73922,Male,47,Diploma,12,50,37,87,65,4.0,2,30,Rural,ML Engineer,122291,0 +73923,Female,24,Bachelors,18,74,24,0,39,9.0,4,58,Urban,Data Analyst,117756,0 +73924,Male,36,Diploma,4,83,29,51,53,6.0,3,30,Urban,ML Engineer,45545,0 +73925,Male,42,Masters,10,94,98,48,93,3.0,3,85,Rural,HR Executive,22156,1 +73926,Other,25,Masters,7,52,28,59,38,2.0,4,50,Urban,Manager,132180,0 +73927,Male,49,Diploma,8,13,87,93,88,3.0,7,35,Urban,ML Engineer,22405,0 +73928,Male,32,Bachelors,6,90,65,25,6,6.0,1,83,Semi-Urban,ML Engineer,64401,1 +73929,Male,57,Bachelors,5,97,93,94,78,6.0,3,25,Urban,ML Engineer,66765,1 +73930,Male,29,Bachelors,17,65,38,18,96,8.0,1,88,Urban,Software Engineer,147107,0 +73931,Male,27,Masters,15,5,51,64,47,2.0,3,50,Urban,Manager,57275,0 +73932,Female,21,Masters,9,44,54,71,0,7.0,6,58,Urban,Data Analyst,65356,0 +73933,Female,47,Diploma,2,44,0,80,42,2.0,0,79,Rural,Data Analyst,55089,0 +73934,Male,53,Bachelors,11,74,26,53,82,1.0,3,45,Urban,ML Engineer,122668,0 +73935,Male,30,Bachelors,18,41,96,13,48,5.0,0,59,Rural,Manager,131932,0 +73936,Female,29,Bachelors,14,64,99,27,98,0.0,6,55,Semi-Urban,HR Executive,88529,1 +73937,Male,49,Masters,18,78,19,21,38,1.0,3,56,Semi-Urban,Software Engineer,121111,0 +73938,Male,33,Diploma,4,37,91,48,22,0.0,6,98,Urban,Data Analyst,46415,1 +73939,Male,25,High School,1,4,60,94,67,7.0,2,37,Semi-Urban,Manager,77642,0 +73940,Male,51,Masters,13,26,11,48,86,2.0,0,83,Urban,Manager,49445,0 +73941,Male,55,Bachelors,2,8,80,63,79,3.0,5,61,Semi-Urban,ML Engineer,89044,0 +73942,Other,28,High School,1,98,98,47,87,3.0,4,97,Urban,Manager,129065,1 +73943,Male,24,Diploma,4,45,53,4,80,0.0,4,69,Urban,Software Engineer,58962,0 +73944,Female,58,Diploma,0,48,41,75,70,2.0,0,34,Rural,Data Analyst,115747,0 +73945,Female,34,High School,1,86,52,86,95,9.0,4,81,Urban,Manager,24500,1 +73946,Male,31,Diploma,13,92,60,44,59,2.0,7,12,Rural,Data Analyst,26910,0 +73947,Female,54,Bachelors,8,34,78,81,29,2.0,7,71,Urban,Data Analyst,55154,1 +73948,Male,29,Bachelors,10,46,75,15,23,6.0,1,96,Rural,Software Engineer,30998,0 +73949,Female,31,Masters,17,0,73,81,43,2.0,6,90,Urban,Software Engineer,133639,1 +73950,Male,46,Diploma,2,98,41,24,34,4.0,0,10,Rural,Manager,64629,0 +73951,Other,22,High School,0,66,11,86,71,2.0,0,52,Semi-Urban,Software Engineer,65171,0 +73952,Female,23,Diploma,0,2,25,44,65,0.0,3,30,Rural,Data Analyst,73688,0 +73953,Male,37,Diploma,8,22,35,39,76,3.0,1,52,Semi-Urban,ML Engineer,142933,0 +73954,Male,25,Masters,0,89,81,90,20,9.0,6,68,Semi-Urban,Software Engineer,57775,1 +73955,Male,55,Bachelors,19,32,11,61,43,2.0,1,94,Urban,Software Engineer,136942,0 +73956,Male,35,High School,5,55,68,47,99,4.0,4,78,Urban,Software Engineer,95582,1 +73957,Female,55,Masters,19,57,9,37,25,8.0,1,35,Semi-Urban,Manager,106143,0 +73958,Male,34,PhD,6,0,27,60,45,5.0,4,10,Urban,Software Engineer,105833,0 +73959,Female,38,Bachelors,1,24,17,77,61,1.0,6,25,Urban,Data Analyst,28450,0 +73960,Male,38,Bachelors,18,1,7,13,81,2.0,0,93,Urban,Data Analyst,87068,0 +73961,Male,32,Masters,0,93,38,22,53,1.0,0,13,Urban,ML Engineer,40702,0 +73962,Female,45,Diploma,2,10,1,32,19,3.0,7,76,Urban,Software Engineer,99702,0 +73963,Female,52,Diploma,7,37,52,89,83,9.0,7,99,Semi-Urban,Data Analyst,123908,1 +73964,Male,40,Masters,11,8,5,17,66,4.0,1,16,Urban,Software Engineer,96805,0 +73965,Male,45,Masters,3,74,71,69,31,5.0,5,23,Semi-Urban,Data Analyst,112395,1 +73966,Male,32,Bachelors,10,10,7,77,68,2.0,4,36,Urban,Manager,135653,0 +73967,Male,31,Diploma,17,87,73,72,92,6.0,0,47,Rural,Data Analyst,120905,1 +73968,Female,23,Diploma,9,77,97,32,56,7.0,6,41,Rural,ML Engineer,139021,1 +73969,Male,48,Diploma,7,53,8,88,52,5.0,0,39,Semi-Urban,ML Engineer,45373,0 +73970,Female,41,Diploma,10,60,92,25,52,7.0,0,36,Rural,ML Engineer,84131,0 +73971,Male,46,Bachelors,0,87,73,76,55,0.0,3,27,Urban,Software Engineer,51322,1 +73972,Male,49,Bachelors,19,46,50,7,2,8.0,1,9,Urban,Software Engineer,29326,0 +73973,Male,22,Bachelors,17,2,37,23,2,8.0,4,59,Urban,Manager,93823,0 +73974,Male,41,Bachelors,6,40,14,22,7,7.0,5,79,Rural,Manager,96923,0 +73975,Female,25,High School,12,79,98,85,77,5.0,6,26,Urban,Manager,35287,1 +73976,Female,21,Bachelors,2,52,89,55,28,3.0,0,86,Urban,Data Analyst,140319,1 +73977,Male,46,Diploma,6,85,85,74,91,1.0,0,2,Semi-Urban,HR Executive,70164,1 +73978,Male,32,Masters,9,79,60,38,89,9.0,3,96,Rural,HR Executive,87312,1 +73979,Female,50,Diploma,4,93,3,58,51,4.0,4,56,Urban,Data Analyst,59852,0 +73980,Male,46,PhD,2,93,21,54,4,3.0,1,9,Semi-Urban,ML Engineer,52111,0 +73981,Female,44,High School,1,87,63,95,4,8.0,3,28,Urban,HR Executive,131697,1 +73982,Male,26,Diploma,11,56,58,45,70,1.0,7,15,Urban,Data Analyst,27383,0 +73983,Male,43,Diploma,16,17,63,64,93,9.0,0,43,Urban,HR Executive,33311,0 +73984,Male,22,Bachelors,12,15,3,6,3,4.0,3,94,Urban,Software Engineer,114106,0 +73985,Female,42,Bachelors,14,81,25,85,48,6.0,4,5,Urban,Software Engineer,81222,0 +73986,Female,24,Diploma,13,81,29,76,36,5.0,3,85,Urban,Data Analyst,102553,1 +73987,Male,21,Bachelors,1,53,12,94,55,9.0,6,15,Semi-Urban,ML Engineer,20397,0 +73988,Male,42,Diploma,0,8,18,71,14,1.0,4,41,Urban,Software Engineer,54850,0 +73989,Female,25,High School,12,67,34,98,96,1.0,2,42,Urban,HR Executive,25830,1 +73990,Male,41,Bachelors,19,72,77,91,43,8.0,3,68,Rural,ML Engineer,149344,1 +73991,Female,49,Masters,0,73,45,86,99,5.0,2,17,Urban,Software Engineer,22398,0 +73992,Male,49,Bachelors,7,81,33,49,53,6.0,6,18,Semi-Urban,Manager,68342,0 +73993,Female,22,High School,19,66,92,31,94,4.0,5,57,Rural,Data Analyst,106731,1 +73994,Male,51,Bachelors,7,53,77,57,95,8.0,7,99,Rural,Software Engineer,21020,1 +73995,Male,54,Bachelors,5,93,9,50,77,4.0,6,69,Urban,ML Engineer,122437,0 +73996,Male,55,High School,14,3,19,52,59,5.0,0,54,Urban,Manager,121509,0 +73997,Female,49,Bachelors,14,21,36,81,35,0.0,7,45,Rural,HR Executive,56532,0 +73998,Male,39,Bachelors,5,53,66,11,53,8.0,3,80,Rural,Manager,114920,0 +73999,Other,25,Bachelors,16,78,16,45,73,9.0,7,17,Urban,HR Executive,110899,0 +74000,Male,55,High School,2,54,20,16,81,4.0,2,6,Rural,ML Engineer,77383,0 +74001,Female,33,PhD,15,69,22,51,4,6.0,2,52,Urban,ML Engineer,58488,0 +74002,Female,42,High School,4,96,64,58,90,1.0,5,34,Rural,ML Engineer,33575,1 +74003,Male,57,Bachelors,7,93,16,58,69,2.0,5,82,Urban,HR Executive,95504,1 +74004,Female,32,Bachelors,13,13,37,62,41,0.0,0,30,Urban,HR Executive,110235,0 +74005,Female,35,Diploma,3,9,52,22,68,2.0,1,81,Semi-Urban,Manager,148694,0 +74006,Male,49,Diploma,8,37,27,5,43,5.0,7,46,Rural,HR Executive,43327,0 +74007,Female,43,Bachelors,10,94,54,74,24,5.0,4,36,Urban,Software Engineer,106686,1 +74008,Female,21,Bachelors,2,18,1,66,3,8.0,4,52,Semi-Urban,Data Analyst,74026,0 +74009,Male,57,Masters,17,2,0,61,81,7.0,4,52,Urban,Manager,90083,0 +74010,Male,21,Masters,15,86,49,61,0,1.0,2,34,Urban,HR Executive,101130,0 +74011,Male,58,High School,15,84,28,98,75,3.0,7,75,Semi-Urban,Software Engineer,93546,1 +74012,Male,48,Bachelors,16,72,83,79,36,5.0,0,69,Rural,Software Engineer,90531,1 +74013,Male,31,Masters,10,86,2,61,8,0.0,4,33,Rural,ML Engineer,110233,0 +74014,Other,36,Bachelors,19,6,73,84,75,3.0,1,90,Urban,ML Engineer,54001,1 +74015,Male,43,High School,7,86,92,69,87,4.0,2,81,Semi-Urban,ML Engineer,38685,1 +74016,Female,47,Bachelors,13,46,58,99,81,7.0,5,49,Urban,Data Analyst,114820,1 +74017,Male,32,Diploma,0,44,2,68,68,0.0,5,94,Urban,Software Engineer,41373,0 +74018,Male,59,Bachelors,12,54,32,63,53,4.0,6,37,Semi-Urban,Software Engineer,40719,0 +74019,Male,53,Masters,3,78,53,95,51,8.0,6,93,Rural,HR Executive,39861,1 +74020,Female,31,Bachelors,16,47,30,96,15,4.0,0,90,Urban,Data Analyst,79577,1 +74021,Female,50,Bachelors,15,31,79,77,29,9.0,4,74,Rural,Manager,79880,1 +74022,Male,58,Diploma,14,18,90,96,3,6.0,0,36,Urban,HR Executive,85886,1 +74023,Male,36,PhD,13,14,6,34,75,7.0,1,66,Urban,Software Engineer,125871,0 +74024,Female,48,Bachelors,2,87,66,16,81,6.0,4,85,Semi-Urban,ML Engineer,71654,1 +74025,Male,49,Bachelors,15,20,99,40,88,9.0,4,83,Semi-Urban,Manager,53246,1 +74026,Female,59,Diploma,10,96,86,22,89,5.0,6,36,Urban,Manager,108738,0 +74027,Male,53,Masters,16,22,75,30,27,6.0,2,25,Rural,Data Analyst,140225,0 +74028,Female,49,Bachelors,0,2,34,41,42,6.0,0,28,Urban,Manager,44181,0 +74029,Female,25,Bachelors,6,28,58,98,40,5.0,3,77,Urban,Manager,91682,1 +74030,Male,45,Masters,15,94,16,51,52,1.0,3,84,Rural,Software Engineer,119110,1 +74031,Female,42,Bachelors,17,92,30,69,73,7.0,7,79,Semi-Urban,Manager,40288,1 +74032,Female,53,High School,1,64,56,77,40,9.0,3,69,Rural,HR Executive,104474,1 +74033,Male,42,PhD,14,49,20,57,20,5.0,6,0,Urban,Manager,60723,0 +74034,Female,55,Bachelors,7,71,41,92,7,8.0,3,4,Urban,Software Engineer,82872,0 +74035,Female,55,Masters,0,44,12,58,78,5.0,3,20,Urban,Software Engineer,139617,0 +74036,Male,27,Bachelors,10,71,73,31,71,3.0,7,33,Urban,Software Engineer,109938,0 +74037,Male,45,Bachelors,17,44,65,57,74,0.0,3,20,Rural,Manager,115798,0 +74038,Male,25,Bachelors,8,9,2,42,16,1.0,5,53,Urban,Software Engineer,122978,0 +74039,Male,54,Bachelors,7,29,27,57,59,6.0,5,48,Rural,Software Engineer,92862,0 +74040,Male,49,Bachelors,8,42,20,42,17,6.0,1,60,Semi-Urban,Manager,54253,0 +74041,Female,48,Masters,6,12,61,0,99,0.0,6,28,Urban,ML Engineer,37902,0 +74042,Female,45,Diploma,6,28,38,55,22,2.0,6,16,Urban,Data Analyst,65680,0 +74043,Female,34,Bachelors,15,94,20,90,20,1.0,2,44,Rural,Manager,108819,1 +74044,Male,25,Masters,1,36,17,44,71,5.0,5,72,Rural,HR Executive,88584,0 +74045,Male,38,PhD,17,75,14,79,49,8.0,3,3,Urban,Software Engineer,81218,0 +74046,Male,55,Diploma,5,1,94,82,76,9.0,6,57,Urban,Manager,93587,0 +74047,Female,32,Diploma,17,36,57,92,11,7.0,4,89,Urban,Software Engineer,59843,1 +74048,Male,38,High School,17,96,21,53,25,7.0,3,16,Semi-Urban,Manager,87391,0 +74049,Male,50,Masters,17,48,39,8,61,1.0,2,64,Urban,ML Engineer,147336,0 +74050,Female,58,PhD,10,59,40,2,43,1.0,7,53,Rural,ML Engineer,101283,0 +74051,Female,45,Diploma,11,81,1,9,18,5.0,0,57,Urban,Data Analyst,41219,0 +74052,Female,44,Diploma,15,73,17,64,21,9.0,7,11,Urban,HR Executive,80175,0 +74053,Male,57,Bachelors,18,12,90,62,11,8.0,3,5,Urban,HR Executive,103672,0 +74054,Male,43,Diploma,8,35,26,93,29,1.0,3,86,Semi-Urban,Software Engineer,109189,1 +74055,Male,27,High School,6,42,49,32,99,0.0,0,44,Rural,ML Engineer,110907,0 +74056,Female,35,Bachelors,17,78,58,62,60,0.0,6,96,Semi-Urban,Manager,112985,1 +74057,Male,37,Masters,1,52,38,58,59,3.0,6,38,Urban,HR Executive,121543,0 +74058,Female,40,Bachelors,15,88,66,50,76,5.0,5,92,Urban,HR Executive,74823,1 +74059,Male,57,Diploma,8,12,68,80,2,7.0,7,51,Urban,HR Executive,71504,0 +74060,Female,59,Bachelors,1,0,70,15,95,2.0,0,23,Urban,Software Engineer,121538,0 +74061,Male,50,Bachelors,2,46,86,1,43,2.0,0,91,Urban,HR Executive,64280,0 +74062,Male,54,Masters,19,72,6,26,45,0.0,0,68,Rural,Data Analyst,81028,0 +74063,Male,46,Bachelors,4,76,60,42,44,0.0,7,11,Urban,ML Engineer,31293,0 +74064,Male,25,Diploma,9,22,9,41,90,8.0,3,95,Urban,ML Engineer,42454,0 +74065,Male,51,Bachelors,3,27,4,34,21,7.0,1,11,Semi-Urban,Data Analyst,60790,0 +74066,Male,39,Bachelors,10,59,29,58,31,6.0,2,85,Urban,Data Analyst,131923,0 +74067,Male,23,High School,15,31,79,6,74,7.0,5,85,Rural,Manager,72222,0 +74068,Male,28,Diploma,14,86,48,30,91,9.0,0,86,Urban,ML Engineer,126254,1 +74069,Male,36,High School,18,11,9,2,50,6.0,1,60,Urban,HR Executive,51293,0 +74070,Male,37,Bachelors,7,44,41,33,19,6.0,3,72,Semi-Urban,ML Engineer,78650,0 +74071,Male,58,Bachelors,2,69,53,85,1,8.0,3,84,Urban,Manager,40491,1 +74072,Female,37,Masters,16,27,98,87,54,9.0,3,70,Urban,Data Analyst,71502,1 +74073,Male,24,Bachelors,9,19,83,51,64,5.0,7,30,Urban,ML Engineer,74950,0 +74074,Male,50,Bachelors,15,54,65,27,63,2.0,2,86,Rural,ML Engineer,71340,0 +74075,Female,54,Diploma,6,40,69,27,4,9.0,7,94,Rural,Manager,105941,0 +74076,Male,28,Bachelors,16,75,52,98,30,5.0,6,17,Rural,Data Analyst,72636,1 +74077,Male,45,Diploma,16,96,16,4,14,8.0,5,54,Semi-Urban,Data Analyst,86724,0 +74078,Female,54,Bachelors,14,0,21,2,56,7.0,6,62,Rural,HR Executive,149879,0 +74079,Male,29,Diploma,5,26,36,60,38,6.0,6,51,Urban,Manager,146407,0 +74080,Male,33,Bachelors,3,12,44,85,27,3.0,5,80,Semi-Urban,Software Engineer,85796,0 +74081,Female,32,Bachelors,3,5,57,64,70,4.0,3,12,Urban,HR Executive,77227,0 +74082,Other,30,High School,9,65,91,84,64,5.0,7,17,Semi-Urban,Software Engineer,85090,1 +74083,Male,57,Diploma,5,41,70,37,97,8.0,6,28,Semi-Urban,Manager,86373,0 +74084,Male,51,Diploma,4,34,6,86,85,0.0,5,35,Semi-Urban,Software Engineer,84369,0 +74085,Male,41,Bachelors,2,79,5,6,9,7.0,5,74,Semi-Urban,ML Engineer,147834,0 +74086,Male,34,Masters,14,3,60,29,57,6.0,5,53,Urban,Manager,53809,0 +74087,Male,31,Masters,13,58,11,6,34,9.0,0,52,Rural,Data Analyst,70632,0 +74088,Male,59,High School,9,28,27,35,17,8.0,0,23,Urban,Software Engineer,120813,0 +74089,Male,45,Masters,6,55,58,72,55,2.0,4,93,Rural,Manager,97682,1 +74090,Female,22,Diploma,10,85,74,71,98,8.0,3,94,Semi-Urban,Software Engineer,65062,1 +74091,Male,27,High School,5,44,79,8,3,8.0,7,51,Semi-Urban,Software Engineer,24154,0 +74092,Male,51,High School,10,88,67,12,6,0.0,3,75,Urban,Manager,113930,1 +74093,Female,49,Diploma,6,9,29,61,93,7.0,2,91,Urban,ML Engineer,86724,0 +74094,Male,47,Diploma,0,70,36,18,66,1.0,5,5,Urban,Software Engineer,60332,0 +74095,Female,58,High School,18,3,14,80,44,4.0,1,66,Urban,ML Engineer,78588,0 +74096,Male,56,Bachelors,17,39,16,87,90,8.0,1,29,Urban,HR Executive,49527,0 +74097,Male,53,Bachelors,10,25,32,5,27,6.0,2,95,Urban,ML Engineer,78674,0 +74098,Female,37,Masters,17,49,92,56,81,9.0,3,32,Semi-Urban,Software Engineer,76302,0 +74099,Male,28,High School,16,14,81,93,44,5.0,0,92,Urban,Software Engineer,56789,1 +74100,Male,30,Masters,5,87,29,69,40,1.0,4,14,Rural,ML Engineer,138631,0 +74101,Female,29,Bachelors,6,11,38,43,7,9.0,4,40,Urban,HR Executive,57888,0 +74102,Male,42,Bachelors,15,4,12,65,98,2.0,6,48,Urban,Manager,149237,0 +74103,Male,38,High School,19,50,6,74,57,3.0,5,69,Semi-Urban,ML Engineer,78570,0 +74104,Other,36,High School,12,83,30,39,89,8.0,7,43,Semi-Urban,ML Engineer,127863,0 +74105,Female,41,Bachelors,4,78,93,27,55,2.0,5,31,Semi-Urban,Data Analyst,101399,0 +74106,Male,33,Bachelors,1,53,53,89,38,9.0,3,38,Semi-Urban,Manager,123756,0 +74107,Male,52,High School,3,21,42,74,77,2.0,3,44,Rural,Data Analyst,74619,0 +74108,Male,33,Diploma,7,39,7,13,62,5.0,1,98,Rural,Data Analyst,37221,0 +74109,Male,45,Diploma,7,56,28,23,92,2.0,4,35,Rural,Software Engineer,93282,0 +74110,Male,48,Bachelors,1,88,38,4,51,2.0,0,8,Urban,Data Analyst,55993,0 +74111,Male,30,Masters,5,52,93,48,37,1.0,7,50,Urban,Manager,125453,1 +74112,Male,26,Bachelors,19,97,45,57,85,1.0,3,39,Urban,Manager,83690,1 +74113,Female,32,Bachelors,10,25,96,57,21,3.0,4,73,Rural,Data Analyst,142064,1 +74114,Male,38,Masters,4,0,72,1,14,5.0,1,23,Semi-Urban,Software Engineer,94032,0 +74115,Female,27,High School,10,72,6,67,41,3.0,0,24,Semi-Urban,Software Engineer,56242,0 +74116,Female,38,Bachelors,19,90,23,99,60,8.0,4,71,Rural,Manager,111808,1 +74117,Female,42,Bachelors,19,17,95,48,14,8.0,0,1,Rural,ML Engineer,64500,0 +74118,Male,59,High School,17,64,1,38,74,2.0,5,68,Urban,Software Engineer,104712,0 +74119,Other,39,High School,1,60,13,66,32,6.0,2,12,Rural,Manager,20481,0 +74120,Male,33,Diploma,13,77,9,31,21,5.0,1,33,Urban,HR Executive,43651,0 +74121,Male,31,Bachelors,19,31,22,52,16,3.0,5,33,Rural,ML Engineer,117619,0 +74122,Male,45,Diploma,6,82,89,84,78,7.0,5,29,Semi-Urban,Manager,43691,1 +74123,Male,31,Masters,9,38,79,68,64,9.0,3,81,Urban,Manager,111622,1 +74124,Male,49,Bachelors,1,17,36,11,17,3.0,6,45,Urban,ML Engineer,113450,0 +74125,Male,24,Diploma,13,60,8,85,1,5.0,2,93,Urban,ML Engineer,117270,1 +74126,Male,22,Masters,4,90,99,95,80,8.0,7,71,Rural,HR Executive,48230,1 +74127,Female,33,Diploma,4,60,81,42,88,8.0,1,95,Urban,ML Engineer,46234,1 +74128,Female,42,Masters,2,32,47,33,0,8.0,4,77,Semi-Urban,Manager,21552,0 +74129,Male,34,Diploma,9,13,48,45,40,8.0,6,60,Urban,HR Executive,125574,0 +74130,Male,37,Bachelors,4,93,29,13,55,3.0,7,77,Urban,Data Analyst,79714,0 +74131,Female,35,Diploma,19,71,86,84,86,7.0,3,38,Rural,Software Engineer,110412,1 +74132,Female,59,Bachelors,2,89,51,26,68,9.0,0,5,Semi-Urban,HR Executive,99005,0 +74133,Male,23,Diploma,12,95,2,54,41,6.0,2,41,Rural,Software Engineer,77770,0 +74134,Female,38,High School,3,79,71,57,49,4.0,2,8,Urban,Software Engineer,78542,0 +74135,Other,41,Bachelors,11,63,31,47,23,1.0,5,82,Urban,ML Engineer,136971,0 +74136,Male,40,Bachelors,10,58,51,50,47,9.0,1,5,Urban,Manager,100293,0 +74137,Other,41,High School,9,16,48,38,43,6.0,6,81,Urban,Data Analyst,103811,0 +74138,Other,22,Bachelors,10,22,60,3,29,7.0,6,87,Urban,Data Analyst,108385,0 +74139,Female,58,Masters,2,47,68,29,42,2.0,5,19,Semi-Urban,Data Analyst,101510,0 +74140,Female,37,PhD,19,66,53,48,83,4.0,2,35,Rural,HR Executive,94883,0 +74141,Male,23,Bachelors,3,68,97,17,57,2.0,4,36,Urban,Manager,39870,0 +74142,Female,28,Masters,1,65,37,19,4,6.0,6,46,Urban,Software Engineer,31410,0 +74143,Male,25,Diploma,11,41,81,32,83,5.0,5,38,Urban,ML Engineer,78476,0 +74144,Male,24,PhD,18,86,31,69,23,1.0,4,79,Urban,HR Executive,64086,1 +74145,Female,24,Diploma,7,0,73,65,94,1.0,3,80,Urban,Software Engineer,32453,0 +74146,Female,27,Bachelors,13,1,67,66,55,7.0,6,16,Semi-Urban,Data Analyst,99590,0 +74147,Female,40,Diploma,6,30,7,8,91,0.0,2,49,Semi-Urban,Software Engineer,79153,0 +74148,Male,46,High School,4,8,54,29,48,2.0,4,66,Rural,Manager,131259,0 +74149,Male,38,Diploma,4,60,57,69,14,3.0,1,96,Urban,Software Engineer,123765,1 +74150,Female,54,High School,4,94,56,48,66,2.0,0,99,Semi-Urban,Software Engineer,114531,1 +74151,Male,40,Bachelors,16,54,46,46,46,7.0,0,48,Urban,ML Engineer,104656,0 +74152,Female,52,Diploma,6,6,40,11,30,5.0,5,80,Urban,ML Engineer,109477,0 +74153,Female,23,Bachelors,1,92,35,81,75,9.0,0,85,Urban,Manager,135703,1 +74154,Male,39,Bachelors,17,40,34,12,40,2.0,6,19,Semi-Urban,Manager,96331,0 +74155,Male,21,Masters,18,2,63,26,69,9.0,0,44,Semi-Urban,HR Executive,87354,0 +74156,Male,41,Bachelors,5,27,45,11,59,8.0,7,63,Semi-Urban,Manager,128306,0 +74157,Female,51,Bachelors,16,20,79,41,96,4.0,0,72,Rural,ML Engineer,96774,0 +74158,Male,23,Diploma,0,99,66,92,93,4.0,7,3,Semi-Urban,ML Engineer,21614,1 +74159,Female,58,Diploma,9,44,65,45,4,0.0,3,91,Urban,Data Analyst,59713,1 +74160,Female,59,Bachelors,7,99,14,0,74,6.0,1,27,Rural,HR Executive,30762,0 +74161,Male,22,Masters,10,56,69,84,94,7.0,6,90,Semi-Urban,Software Engineer,49895,1 +74162,Male,49,Bachelors,8,2,53,86,64,2.0,5,98,Urban,Software Engineer,139717,1 +74163,Female,43,Bachelors,14,53,94,99,9,9.0,3,37,Semi-Urban,Data Analyst,54886,1 +74164,Male,35,Diploma,5,82,53,35,21,5.0,5,93,Urban,Data Analyst,134495,1 +74165,Male,55,Bachelors,4,90,30,91,84,0.0,4,51,Urban,Data Analyst,32489,1 +74166,Female,39,High School,13,78,71,90,57,8.0,0,84,Semi-Urban,Manager,118166,1 +74167,Female,43,Bachelors,6,71,7,3,21,2.0,0,21,Semi-Urban,Data Analyst,30111,0 +74168,Male,58,High School,6,26,0,46,71,9.0,6,11,Urban,HR Executive,143519,0 +74169,Female,38,Bachelors,16,40,72,76,84,0.0,2,4,Urban,HR Executive,30076,0 +74170,Male,37,Diploma,9,18,84,61,71,0.0,7,53,Semi-Urban,Manager,94948,0 +74171,Female,48,Bachelors,11,22,24,46,95,6.0,4,82,Rural,Manager,36117,0 +74172,Female,30,Bachelors,3,87,62,28,45,8.0,1,60,Semi-Urban,ML Engineer,61714,0 +74173,Male,45,High School,9,23,78,88,83,4.0,4,80,Semi-Urban,Software Engineer,90024,1 +74174,Female,43,Diploma,12,64,99,65,40,6.0,4,51,Urban,ML Engineer,104188,1 +74175,Female,54,PhD,17,87,48,7,17,8.0,3,44,Urban,ML Engineer,112695,0 +74176,Male,35,Bachelors,9,64,69,17,82,5.0,0,88,Urban,Manager,50088,1 +74177,Male,44,Bachelors,15,5,94,45,32,2.0,2,46,Urban,Manager,24390,0 +74178,Female,36,Diploma,2,58,94,5,95,0.0,7,53,Urban,ML Engineer,33236,0 +74179,Male,39,Bachelors,0,32,75,95,71,2.0,2,74,Urban,Software Engineer,64239,1 +74180,Male,31,Diploma,4,58,7,5,16,8.0,3,2,Semi-Urban,HR Executive,31417,0 +74181,Male,26,High School,14,26,85,14,75,2.0,4,61,Rural,HR Executive,90077,0 +74182,Male,50,Bachelors,17,85,65,45,76,3.0,7,80,Semi-Urban,HR Executive,119640,1 +74183,Male,52,Bachelors,12,55,69,42,11,4.0,7,23,Rural,ML Engineer,142580,0 +74184,Female,32,Diploma,6,12,12,78,18,9.0,1,3,Semi-Urban,Manager,43479,0 +74185,Female,56,Bachelors,14,30,50,21,0,1.0,7,6,Urban,Data Analyst,93083,0 +74186,Male,53,Diploma,12,93,91,92,48,3.0,6,47,Urban,Software Engineer,138111,1 +74187,Male,41,Bachelors,18,62,8,15,30,5.0,5,95,Rural,Software Engineer,59838,0 +74188,Female,45,Bachelors,4,65,70,18,91,1.0,6,36,Urban,Software Engineer,41742,0 +74189,Female,45,Diploma,15,91,66,9,2,6.0,3,26,Urban,HR Executive,147620,0 +74190,Female,49,High School,3,71,76,68,51,6.0,0,97,Urban,ML Engineer,106603,1 +74191,Male,31,Masters,18,50,66,84,73,3.0,2,30,Semi-Urban,Manager,148013,0 +74192,Male,50,Bachelors,11,98,41,82,69,5.0,4,81,Urban,ML Engineer,139893,1 +74193,Female,30,Bachelors,2,67,37,49,94,7.0,6,57,Semi-Urban,Manager,129668,0 +74194,Female,54,Bachelors,2,80,71,46,26,2.0,5,77,Urban,Manager,25758,1 +74195,Female,31,Bachelors,6,12,4,17,34,5.0,4,51,Semi-Urban,Software Engineer,108505,0 +74196,Female,37,Masters,13,53,68,12,90,7.0,6,2,Urban,HR Executive,44324,0 +74197,Male,38,Masters,12,94,49,88,63,6.0,3,49,Urban,ML Engineer,62100,1 +74198,Male,47,Masters,11,99,72,16,55,6.0,4,98,Urban,Data Analyst,112607,1 +74199,Male,40,Bachelors,4,52,41,28,80,3.0,7,0,Urban,Software Engineer,128827,0 +74200,Male,40,High School,13,63,96,2,60,9.0,3,81,Semi-Urban,ML Engineer,23616,1 +74201,Female,56,Bachelors,2,31,47,49,98,9.0,2,71,Urban,Data Analyst,109491,0 +74202,Female,56,Bachelors,1,61,67,2,73,2.0,7,32,Urban,Manager,118067,0 +74203,Male,38,Bachelors,13,82,99,55,64,6.0,1,25,Rural,ML Engineer,83708,1 +74204,Male,34,Bachelors,18,27,25,2,77,6.0,6,16,Rural,Data Analyst,28916,0 +74205,Female,41,Diploma,8,27,9,46,47,8.0,6,56,Rural,Manager,117666,0 +74206,Male,33,Bachelors,4,11,1,31,36,5.0,4,36,Urban,ML Engineer,131824,0 +74207,Other,30,Bachelors,11,44,26,21,10,0.0,5,91,Semi-Urban,HR Executive,67418,0 +74208,Female,32,Bachelors,7,57,96,6,0,4.0,7,50,Rural,Software Engineer,64411,0 +74209,Male,45,Masters,18,73,78,50,9,9.0,2,6,Semi-Urban,HR Executive,24966,0 +74210,Male,55,Masters,8,22,49,54,48,2.0,4,48,Urban,Data Analyst,113726,0 +74211,Female,29,Bachelors,8,19,23,78,96,3.0,0,4,Rural,Manager,145850,0 +74212,Female,50,Diploma,1,0,50,76,84,4.0,2,55,Rural,ML Engineer,114352,0 +74213,Male,36,Bachelors,0,73,12,38,99,1.0,1,39,Urban,Software Engineer,45480,0 +74214,Male,41,High School,4,58,52,23,33,8.0,6,52,Urban,HR Executive,54456,0 +74215,Male,44,Bachelors,11,23,74,12,93,7.0,5,49,Urban,ML Engineer,22670,0 +74216,Female,58,High School,17,55,87,72,19,1.0,6,66,Semi-Urban,Data Analyst,137310,1 +74217,Male,31,Masters,5,95,91,57,41,0.0,5,33,Urban,ML Engineer,116353,1 +74218,Female,32,Masters,12,40,89,82,26,0.0,6,19,Urban,Data Analyst,120518,0 +74219,Female,47,Bachelors,14,95,68,1,0,1.0,0,52,Urban,Software Engineer,131168,0 +74220,Male,54,Bachelors,17,98,34,20,53,9.0,4,45,Urban,Data Analyst,92427,0 +74221,Male,22,Bachelors,18,40,28,81,75,3.0,6,0,Rural,ML Engineer,88958,0 +74222,Male,28,Bachelors,4,43,87,65,1,6.0,1,71,Urban,Manager,60088,1 +74223,Male,46,Bachelors,5,78,98,24,24,4.0,4,61,Semi-Urban,ML Engineer,74129,1 +74224,Male,24,Bachelors,4,8,46,37,86,7.0,2,94,Urban,ML Engineer,30720,0 +74225,Male,41,Bachelors,14,81,24,34,26,2.0,6,47,Semi-Urban,HR Executive,62505,0 +74226,Male,40,High School,16,77,21,94,59,8.0,4,69,Urban,Software Engineer,142391,1 +74227,Male,28,Bachelors,13,71,6,33,27,2.0,1,6,Semi-Urban,Manager,60329,0 +74228,Male,45,Diploma,11,58,32,77,19,0.0,4,26,Urban,HR Executive,107775,0 +74229,Female,49,Masters,2,21,63,76,62,7.0,4,36,Urban,Manager,78116,0 +74230,Male,56,Masters,16,47,5,75,77,3.0,7,99,Urban,ML Engineer,105963,0 +74231,Female,49,High School,0,88,92,94,68,8.0,2,79,Semi-Urban,Software Engineer,109890,1 +74232,Male,37,Masters,15,64,14,73,73,0.0,2,22,Urban,ML Engineer,89602,0 +74233,Male,35,Masters,6,89,70,57,16,5.0,1,33,Urban,Software Engineer,134599,1 +74234,Female,50,PhD,11,86,66,12,56,2.0,2,78,Urban,Data Analyst,81058,1 +74235,Male,37,High School,16,57,53,47,40,4.0,1,6,Semi-Urban,HR Executive,82512,0 +74236,Female,50,Bachelors,15,54,38,16,57,3.0,1,28,Rural,Software Engineer,134784,0 +74237,Female,41,High School,11,19,25,95,45,1.0,7,63,Semi-Urban,Software Engineer,111555,0 +74238,Male,22,Diploma,3,25,59,64,95,5.0,6,12,Semi-Urban,Data Analyst,121303,0 +74239,Male,34,Masters,4,59,91,6,86,0.0,0,4,Semi-Urban,Software Engineer,138977,0 +74240,Female,21,Bachelors,12,27,32,94,83,0.0,4,79,Rural,Software Engineer,66369,0 +74241,Female,33,PhD,1,50,35,81,98,8.0,3,62,Urban,Manager,143471,0 +74242,Male,58,Masters,2,13,55,52,2,4.0,1,49,Rural,HR Executive,53439,0 +74243,Female,50,Bachelors,17,88,83,36,4,8.0,1,91,Urban,Manager,90000,1 +74244,Female,54,Bachelors,1,98,82,87,35,6.0,5,56,Semi-Urban,Data Analyst,100844,1 +74245,Female,43,Bachelors,17,13,18,47,89,5.0,7,70,Semi-Urban,Software Engineer,65865,0 +74246,Female,44,Diploma,14,23,75,36,87,1.0,5,38,Urban,ML Engineer,55129,0 +74247,Male,22,Bachelors,8,37,64,32,3,0.0,4,70,Urban,Manager,86982,0 +74248,Female,48,Masters,16,19,78,60,11,4.0,3,50,Urban,Manager,100000,0 +74249,Female,41,Bachelors,9,85,63,96,29,8.0,6,26,Urban,ML Engineer,72478,1 +74250,Male,47,Bachelors,14,40,90,96,64,4.0,2,58,Rural,Software Engineer,32485,1 +74251,Male,57,Bachelors,0,48,22,68,53,2.0,1,72,Urban,HR Executive,137713,0 +74252,Male,30,High School,5,66,45,54,29,4.0,6,99,Urban,Software Engineer,92894,1 +74253,Male,36,Bachelors,3,58,86,35,60,5.0,7,70,Rural,Data Analyst,112067,1 +74254,Female,57,Diploma,19,32,54,59,51,6.0,6,29,Urban,ML Engineer,148339,0 +74255,Male,39,High School,14,56,47,38,48,7.0,2,32,Semi-Urban,HR Executive,116770,0 +74256,Female,49,Bachelors,3,79,96,39,81,8.0,0,93,Urban,Software Engineer,76840,1 +74257,Male,35,Bachelors,1,9,89,78,67,5.0,3,32,Rural,Software Engineer,63266,0 +74258,Male,38,Masters,4,32,75,13,1,3.0,3,15,Semi-Urban,Data Analyst,120887,0 +74259,Male,38,Masters,7,81,7,64,22,7.0,6,15,Semi-Urban,HR Executive,113529,0 +74260,Female,50,Bachelors,10,28,57,25,82,9.0,0,77,Rural,Software Engineer,122413,0 +74261,Male,27,High School,1,49,54,38,95,7.0,1,44,Semi-Urban,Software Engineer,110287,0 +74262,Other,22,Masters,12,24,96,12,10,9.0,4,24,Semi-Urban,Data Analyst,77402,0 +74263,Female,52,Diploma,18,19,6,31,44,6.0,6,25,Urban,Software Engineer,32282,0 +74264,Male,41,Bachelors,1,97,31,49,41,2.0,5,48,Urban,Manager,79188,0 +74265,Male,32,Diploma,15,24,77,44,97,1.0,3,65,Urban,Data Analyst,148274,0 +74266,Male,46,High School,16,89,96,51,22,0.0,3,63,Urban,Software Engineer,96987,1 +74267,Female,48,Bachelors,10,45,56,2,25,3.0,0,34,Semi-Urban,Software Engineer,112049,0 +74268,Male,59,High School,3,50,66,1,4,2.0,6,67,Urban,Software Engineer,52600,0 +74269,Male,30,Bachelors,17,66,42,27,22,7.0,4,90,Rural,Data Analyst,38740,0 +74270,Female,30,High School,2,82,49,52,77,7.0,4,92,Urban,ML Engineer,75207,1 +74271,Male,57,Masters,18,21,87,24,85,6.0,3,5,Urban,Software Engineer,72624,0 +74272,Male,36,PhD,10,61,94,2,86,6.0,4,5,Urban,Data Analyst,92994,0 +74273,Female,54,Masters,10,28,37,46,14,7.0,7,24,Rural,ML Engineer,66752,0 +74274,Male,27,High School,17,16,19,35,43,7.0,3,15,Urban,Software Engineer,50112,0 +74275,Male,26,Diploma,15,14,67,3,87,0.0,0,78,Urban,Manager,65746,0 +74276,Female,45,Bachelors,19,83,29,32,58,6.0,3,51,Urban,HR Executive,74084,0 +74277,Female,47,Masters,19,97,8,15,35,4.0,5,38,Urban,Manager,34314,0 +74278,Male,56,PhD,6,0,55,64,34,1.0,5,80,Urban,HR Executive,65902,0 +74279,Male,33,Masters,12,47,60,76,60,5.0,4,33,Urban,Data Analyst,51629,0 +74280,Female,42,Diploma,14,83,8,26,43,7.0,4,27,Semi-Urban,ML Engineer,70170,0 +74281,Female,48,Diploma,19,55,51,49,44,1.0,2,70,Semi-Urban,Data Analyst,147339,0 +74282,Male,27,Diploma,11,42,52,25,46,7.0,3,60,Semi-Urban,HR Executive,25160,0 +74283,Male,59,Bachelors,7,38,52,51,42,2.0,2,87,Semi-Urban,Manager,125704,0 +74284,Male,38,Bachelors,15,0,37,38,87,2.0,1,38,Rural,ML Engineer,61103,0 +74285,Male,47,Masters,18,20,97,5,14,4.0,4,14,Urban,Software Engineer,124942,0 +74286,Female,41,Bachelors,11,62,18,48,8,3.0,5,29,Urban,HR Executive,72652,0 +74287,Male,43,Diploma,6,92,28,74,93,9.0,6,60,Urban,HR Executive,54015,1 +74288,Male,30,High School,3,85,86,26,73,9.0,5,31,Semi-Urban,HR Executive,128607,0 +74289,Male,53,High School,12,20,95,46,12,3.0,4,33,Rural,HR Executive,53155,0 +74290,Male,58,Masters,17,96,26,61,68,9.0,3,66,Urban,ML Engineer,104415,1 +74291,Male,50,Masters,0,32,41,32,56,8.0,4,73,Urban,HR Executive,40750,0 +74292,Female,21,High School,16,19,94,93,67,5.0,5,46,Urban,Software Engineer,42417,1 +74293,Male,49,Masters,17,81,98,32,93,8.0,6,80,Rural,Software Engineer,72870,1 +74294,Female,25,Masters,16,57,77,73,66,3.0,6,3,Urban,Manager,98741,0 +74295,Other,57,Diploma,3,59,86,33,56,4.0,0,41,Semi-Urban,HR Executive,114278,0 +74296,Female,54,Diploma,18,26,88,71,16,6.0,0,8,Rural,Data Analyst,87350,0 +74297,Male,55,Bachelors,11,64,67,9,69,3.0,3,80,Semi-Urban,Software Engineer,97520,0 +74298,Male,28,Diploma,5,64,53,42,87,5.0,2,65,Semi-Urban,Software Engineer,118227,0 +74299,Male,52,High School,4,20,55,25,21,7.0,6,34,Urban,HR Executive,122640,0 +74300,Male,41,Diploma,5,67,9,56,4,0.0,4,50,Rural,Software Engineer,100713,0 +74301,Male,22,Masters,5,91,83,53,23,8.0,5,27,Urban,Data Analyst,34195,1 +74302,Male,59,Diploma,7,45,63,73,76,1.0,3,93,Semi-Urban,Data Analyst,133035,1 +74303,Male,42,Diploma,12,11,11,44,60,4.0,5,53,Semi-Urban,HR Executive,104460,0 +74304,Male,37,High School,7,97,99,66,56,6.0,7,92,Rural,Software Engineer,58877,1 +74305,Male,56,Masters,4,11,11,90,80,1.0,0,91,Rural,Data Analyst,26883,0 +74306,Male,52,Bachelors,13,48,11,82,7,5.0,5,59,Urban,Manager,88521,0 +74307,Male,57,PhD,11,84,37,19,84,8.0,6,22,Urban,HR Executive,119838,0 +74308,Female,45,Bachelors,2,41,12,57,67,1.0,6,77,Rural,Data Analyst,30666,0 +74309,Male,40,Diploma,7,81,76,5,43,3.0,2,31,Urban,Manager,73327,0 +74310,Female,47,Bachelors,8,26,4,51,32,6.0,7,64,Urban,Manager,29117,0 +74311,Male,49,High School,13,67,61,88,82,8.0,4,15,Urban,HR Executive,34784,0 +74312,Female,24,Bachelors,14,56,52,67,86,1.0,4,82,Rural,Data Analyst,127647,1 +74313,Male,37,Diploma,2,33,23,14,82,5.0,3,10,Urban,HR Executive,118878,0 +74314,Female,43,Masters,1,58,68,68,25,6.0,7,87,Rural,Manager,123670,1 +74315,Male,52,Masters,19,81,73,39,42,9.0,3,93,Semi-Urban,Manager,33184,1 +74316,Female,44,Bachelors,17,77,18,68,38,1.0,3,79,Rural,ML Engineer,122312,1 +74317,Male,35,Diploma,5,1,37,76,75,0.0,5,91,Urban,ML Engineer,117167,0 +74318,Female,27,Bachelors,4,87,53,1,11,2.0,3,98,Semi-Urban,Manager,86580,0 +74319,Male,57,Bachelors,15,90,57,94,75,1.0,5,92,Urban,HR Executive,43880,1 +74320,Male,54,Masters,15,30,83,24,91,7.0,4,41,Rural,ML Engineer,138157,0 +74321,Male,46,Diploma,11,83,91,45,35,6.0,7,71,Semi-Urban,Software Engineer,99590,1 +74322,Female,22,PhD,7,4,28,25,52,8.0,5,23,Semi-Urban,HR Executive,63912,0 +74323,Male,52,High School,4,64,66,7,34,1.0,3,99,Semi-Urban,Software Engineer,86861,1 +74324,Male,55,Bachelors,9,33,82,6,37,3.0,1,87,Urban,Manager,147870,0 +74325,Female,54,Diploma,15,42,9,34,18,2.0,2,36,Semi-Urban,ML Engineer,68219,0 +74326,Male,39,High School,3,98,61,63,12,3.0,2,83,Urban,ML Engineer,123701,1 +74327,Male,48,Bachelors,10,64,87,92,39,8.0,6,44,Semi-Urban,HR Executive,119515,1 +74328,Female,46,Masters,3,7,30,26,87,0.0,5,4,Urban,ML Engineer,132668,0 +74329,Male,26,Masters,7,91,9,70,4,6.0,7,85,Semi-Urban,ML Engineer,144088,1 +74330,Female,39,Bachelors,2,67,24,67,33,9.0,2,25,Urban,Data Analyst,78724,0 +74331,Male,27,Bachelors,5,44,46,17,30,3.0,7,38,Rural,Manager,31072,0 +74332,Male,32,High School,6,66,83,19,62,2.0,7,0,Semi-Urban,Data Analyst,54947,0 +74333,Male,49,Bachelors,2,80,50,64,45,8.0,7,40,Urban,HR Executive,35174,0 +74334,Female,36,Diploma,6,82,8,45,1,3.0,3,53,Urban,Software Engineer,61593,0 +74335,Female,33,Bachelors,13,71,26,19,9,0.0,2,39,Urban,Data Analyst,103952,0 +74336,Male,28,Masters,14,61,19,75,67,2.0,4,18,Semi-Urban,Data Analyst,127127,0 +74337,Male,42,Bachelors,5,63,73,21,95,8.0,5,5,Urban,Data Analyst,68867,0 +74338,Other,52,Diploma,11,83,85,40,38,0.0,4,80,Urban,Manager,110605,1 +74339,Female,39,Bachelors,5,75,81,19,32,5.0,0,9,Urban,Data Analyst,114257,0 +74340,Male,56,Diploma,0,76,45,56,15,8.0,2,23,Urban,ML Engineer,89485,0 +74341,Male,27,High School,18,45,60,68,92,3.0,7,0,Urban,Software Engineer,138761,0 +74342,Female,28,Bachelors,0,93,35,69,17,1.0,3,27,Urban,ML Engineer,51225,0 +74343,Female,29,Bachelors,3,53,87,26,1,3.0,7,97,Rural,HR Executive,67725,1 +74344,Male,28,Diploma,3,5,53,82,52,5.0,4,31,Urban,Manager,47896,0 +74345,Male,27,High School,8,93,60,25,38,8.0,2,85,Rural,ML Engineer,56272,1 +74346,Female,34,Bachelors,14,46,49,65,60,3.0,1,50,Semi-Urban,HR Executive,72664,0 +74347,Male,24,High School,10,60,42,75,18,6.0,6,59,Semi-Urban,Manager,95361,1 +74348,Male,41,Bachelors,16,43,42,68,0,2.0,5,70,Urban,Manager,93388,0 +74349,Female,23,Bachelors,18,16,26,57,27,6.0,0,31,Rural,Manager,70020,0 +74350,Male,44,Diploma,9,10,90,21,53,1.0,3,79,Urban,ML Engineer,146836,0 +74351,Male,56,High School,15,33,60,4,11,1.0,4,23,Semi-Urban,HR Executive,114419,0 +74352,Female,38,Diploma,19,53,6,91,40,0.0,7,33,Rural,Software Engineer,46569,0 +74353,Male,31,Masters,13,31,81,25,96,0.0,3,26,Rural,Data Analyst,94663,0 +74354,Male,59,Bachelors,6,59,69,79,35,3.0,0,58,Semi-Urban,HR Executive,115555,1 +74355,Male,38,Diploma,11,72,94,11,45,1.0,6,95,Urban,Software Engineer,92551,1 +74356,Male,53,High School,1,65,26,47,24,9.0,6,99,Rural,Software Engineer,143113,1 +74357,Male,35,Bachelors,15,37,58,75,68,6.0,4,78,Rural,ML Engineer,119087,1 +74358,Female,27,Bachelors,1,4,74,67,71,2.0,0,21,Urban,HR Executive,34770,0 +74359,Male,49,PhD,0,16,54,83,96,4.0,5,70,Rural,Software Engineer,87368,0 +74360,Female,55,Masters,3,90,44,87,20,3.0,2,58,Semi-Urban,HR Executive,101979,1 +74361,Female,39,Masters,11,86,82,76,19,2.0,3,49,Urban,ML Engineer,20921,1 +74362,Male,43,Bachelors,14,65,78,36,39,5.0,7,62,Urban,ML Engineer,73582,1 +74363,Male,27,Bachelors,0,41,78,44,44,4.0,4,38,Semi-Urban,ML Engineer,147862,0 +74364,Male,54,Diploma,5,27,20,37,46,8.0,3,58,Rural,Software Engineer,148930,0 +74365,Male,46,Bachelors,10,98,22,63,54,8.0,5,7,Rural,ML Engineer,112467,0 +74366,Male,37,PhD,5,62,0,98,12,4.0,2,84,Urban,Manager,68958,1 +74367,Female,47,Bachelors,11,24,14,34,14,2.0,7,81,Urban,HR Executive,119085,0 +74368,Female,59,Diploma,17,63,50,15,47,2.0,5,44,Urban,Manager,29498,0 +74369,Male,35,Bachelors,8,10,75,15,10,2.0,7,24,Semi-Urban,Manager,30799,0 +74370,Male,45,Bachelors,19,71,46,48,97,4.0,1,16,Rural,HR Executive,84875,0 +74371,Male,26,Diploma,4,38,93,59,86,7.0,1,76,Semi-Urban,HR Executive,144400,1 +74372,Male,42,Masters,6,27,9,20,5,4.0,0,62,Semi-Urban,HR Executive,31638,0 +74373,Male,59,Diploma,0,55,9,41,86,3.0,3,96,Urban,Manager,116386,0 +74374,Male,57,Bachelors,19,30,97,25,1,4.0,6,35,Urban,ML Engineer,127317,0 +74375,Male,47,Bachelors,2,41,56,12,87,8.0,0,44,Rural,Data Analyst,29085,0 +74376,Male,23,Diploma,19,94,53,82,18,9.0,4,44,Rural,ML Engineer,84032,1 +74377,Male,31,Diploma,14,49,15,26,6,7.0,4,68,Semi-Urban,HR Executive,47016,0 +74378,Female,23,Diploma,8,62,86,18,55,3.0,6,84,Rural,Data Analyst,109884,1 +74379,Male,33,High School,9,66,82,73,8,7.0,5,93,Urban,ML Engineer,27890,1 +74380,Female,24,Masters,2,53,97,64,24,7.0,2,24,Semi-Urban,Manager,89777,0 +74381,Female,47,Masters,15,93,49,66,68,2.0,2,97,Urban,Manager,69776,1 +74382,Male,34,Bachelors,8,92,6,83,95,5.0,6,89,Semi-Urban,HR Executive,97716,1 +74383,Male,24,Masters,1,74,32,57,40,3.0,2,74,Semi-Urban,Software Engineer,54133,1 +74384,Female,52,High School,11,33,43,67,2,0.0,0,9,Rural,Software Engineer,96875,0 +74385,Male,39,High School,19,93,22,46,62,8.0,6,12,Urban,Data Analyst,60267,0 +74386,Female,54,High School,1,14,37,3,65,2.0,6,57,Semi-Urban,Data Analyst,134195,0 +74387,Female,28,Bachelors,7,7,87,48,16,6.0,3,98,Urban,Software Engineer,93080,0 +74388,Female,24,Masters,17,75,7,13,77,1.0,3,28,Semi-Urban,Software Engineer,94548,0 +74389,Male,54,Masters,1,29,57,52,88,6.0,0,76,Rural,Manager,52480,0 +74390,Other,44,Bachelors,10,33,79,58,12,6.0,4,81,Rural,HR Executive,42856,1 +74391,Other,24,Bachelors,16,97,84,49,25,1.0,4,32,Urban,HR Executive,78641,1 +74392,Male,52,Diploma,9,68,9,38,77,7.0,3,43,Urban,Software Engineer,45675,0 +74393,Female,24,Diploma,4,67,69,30,69,1.0,1,12,Semi-Urban,Manager,70078,0 +74394,Male,52,Bachelors,2,99,57,52,11,1.0,4,64,Semi-Urban,HR Executive,27158,1 +74395,Male,40,Masters,1,87,46,77,82,9.0,6,89,Urban,Manager,101783,1 +74396,Male,24,Bachelors,7,50,98,83,63,3.0,5,56,Urban,Data Analyst,81418,1 +74397,Female,43,Bachelors,13,74,28,18,6,5.0,1,50,Urban,HR Executive,111658,0 +74398,Male,46,High School,17,55,69,70,94,8.0,4,33,Urban,Software Engineer,133392,0 +74399,Female,58,Diploma,17,87,16,64,82,8.0,5,0,Semi-Urban,Manager,122240,0 +74400,Female,43,High School,5,37,66,57,71,6.0,0,97,Urban,ML Engineer,94248,1 +74401,Male,44,High School,7,3,42,33,47,5.0,5,89,Semi-Urban,Data Analyst,93606,0 +74402,Female,45,Bachelors,8,61,17,69,86,7.0,3,46,Urban,Manager,94164,0 +74403,Male,25,Diploma,13,14,56,49,83,8.0,3,88,Semi-Urban,Software Engineer,35350,0 +74404,Male,36,Bachelors,15,59,84,63,9,9.0,6,51,Urban,Manager,97077,1 +74405,Male,25,Diploma,0,59,41,63,77,9.0,4,86,Semi-Urban,Data Analyst,143532,1 +74406,Male,50,Masters,18,54,29,32,9,9.0,3,62,Semi-Urban,Software Engineer,130253,0 +74407,Female,43,Diploma,2,95,47,67,69,3.0,0,10,Rural,ML Engineer,119047,0 +74408,Male,32,Bachelors,6,11,76,68,37,8.0,7,42,Semi-Urban,Data Analyst,77765,0 +74409,Male,25,Diploma,5,25,80,49,72,5.0,2,14,Semi-Urban,ML Engineer,80196,0 +74410,Female,34,Bachelors,4,38,20,26,67,1.0,4,94,Semi-Urban,HR Executive,100222,0 +74411,Other,45,Diploma,18,5,8,72,18,0.0,4,59,Urban,Data Analyst,140685,0 +74412,Male,21,Bachelors,18,2,61,46,89,3.0,5,26,Urban,Software Engineer,67202,0 +74413,Male,40,Diploma,2,35,23,9,49,5.0,5,15,Semi-Urban,Data Analyst,26609,0 +74414,Male,47,Masters,15,66,20,23,76,4.0,5,85,Urban,Software Engineer,132123,0 +74415,Male,48,Bachelors,13,62,51,16,48,8.0,0,92,Urban,Software Engineer,115330,0 +74416,Male,37,Bachelors,0,97,12,73,42,5.0,0,47,Urban,Manager,24542,0 +74417,Male,56,Masters,7,91,4,26,67,2.0,6,54,Urban,ML Engineer,30566,0 +74418,Male,32,Bachelors,1,74,66,71,89,5.0,6,85,Urban,Data Analyst,149016,1 +74419,Other,58,Bachelors,7,97,50,9,33,5.0,1,3,Urban,ML Engineer,140395,0 +74420,Female,38,Masters,11,20,54,9,80,9.0,4,94,Urban,Manager,29690,0 +74421,Female,56,High School,15,66,41,2,61,4.0,0,66,Semi-Urban,Manager,96940,0 +74422,Male,28,Diploma,15,30,44,51,62,6.0,3,19,Semi-Urban,Data Analyst,50995,0 +74423,Female,43,Bachelors,14,72,25,46,52,6.0,6,11,Urban,Software Engineer,35286,0 +74424,Male,23,Bachelors,5,20,47,7,40,4.0,0,76,Urban,Data Analyst,140508,0 +74425,Male,53,High School,10,87,39,75,56,2.0,4,55,Urban,HR Executive,121263,1 +74426,Male,39,Masters,18,39,6,66,85,1.0,5,56,Rural,HR Executive,99969,0 +74427,Male,36,Masters,2,98,43,61,98,0.0,0,11,Urban,HR Executive,97289,0 +74428,Female,22,Diploma,17,68,46,14,48,6.0,4,16,Urban,Software Engineer,39383,0 +74429,Female,36,Bachelors,11,43,81,12,95,9.0,5,73,Urban,ML Engineer,70243,0 +74430,Female,49,Diploma,9,21,46,3,31,2.0,5,77,Rural,Data Analyst,41791,0 +74431,Male,43,Diploma,4,89,14,93,10,6.0,1,29,Urban,HR Executive,58379,0 +74432,Female,35,High School,17,18,35,99,20,0.0,6,0,Rural,Software Engineer,83814,0 +74433,Other,29,Bachelors,14,90,7,51,50,7.0,0,45,Semi-Urban,ML Engineer,41401,0 +74434,Female,24,Bachelors,17,28,29,69,17,8.0,7,60,Urban,ML Engineer,148432,0 +74435,Female,25,Masters,18,1,0,72,7,8.0,1,5,Urban,HR Executive,65086,0 +74436,Other,45,Masters,14,76,4,82,40,4.0,7,69,Urban,HR Executive,123357,0 +74437,Male,44,Bachelors,17,54,65,75,38,7.0,4,43,Semi-Urban,Data Analyst,105280,1 +74438,Female,31,Bachelors,10,63,56,77,29,8.0,2,76,Urban,Data Analyst,79965,1 +74439,Male,58,Diploma,0,20,22,64,56,9.0,7,62,Urban,Manager,78264,0 +74440,Male,42,Masters,0,53,98,24,42,7.0,0,41,Urban,Software Engineer,74161,0 +74441,Female,21,Diploma,7,43,43,74,98,9.0,7,49,Semi-Urban,Data Analyst,93055,0 +74442,Male,55,Bachelors,13,92,70,78,50,0.0,5,12,Semi-Urban,Data Analyst,38500,1 +74443,Other,26,Bachelors,15,1,93,15,59,6.0,5,99,Semi-Urban,Manager,131693,0 +74444,Male,46,Bachelors,13,0,25,50,41,4.0,5,6,Urban,ML Engineer,51955,0 +74445,Male,36,Bachelors,15,28,76,63,41,4.0,5,65,Urban,Data Analyst,57072,0 +74446,Male,27,Masters,4,32,52,26,19,3.0,5,22,Urban,HR Executive,78841,0 +74447,Female,27,Bachelors,16,26,42,28,23,1.0,1,24,Semi-Urban,ML Engineer,75413,0 +74448,Male,22,PhD,13,21,8,35,15,3.0,2,12,Urban,Data Analyst,132155,0 +74449,Female,45,High School,1,47,69,35,60,0.0,6,20,Semi-Urban,Data Analyst,104557,0 +74450,Female,27,High School,18,94,57,15,93,1.0,4,43,Rural,HR Executive,106405,0 +74451,Male,29,High School,5,85,61,73,35,1.0,2,59,Rural,Manager,141697,1 +74452,Male,44,Bachelors,11,95,26,72,2,4.0,5,58,Rural,HR Executive,133398,1 +74453,Male,46,Bachelors,13,92,45,41,68,5.0,7,98,Urban,ML Engineer,147251,1 +74454,Male,28,Bachelors,6,68,86,64,8,4.0,1,75,Urban,Software Engineer,41084,1 +74455,Male,47,Masters,12,88,17,81,95,0.0,1,62,Urban,Software Engineer,90937,1 +74456,Male,40,Bachelors,17,9,58,82,42,6.0,5,56,Semi-Urban,Software Engineer,35708,0 +74457,Female,21,Bachelors,1,78,66,23,61,9.0,3,47,Urban,ML Engineer,145389,0 +74458,Female,21,High School,5,72,88,5,7,2.0,6,6,Urban,HR Executive,139825,0 +74459,Male,24,Diploma,6,71,76,48,15,4.0,6,98,Semi-Urban,Data Analyst,37777,1 +74460,Female,33,Bachelors,4,77,64,41,21,8.0,6,46,Semi-Urban,HR Executive,32963,0 +74461,Male,26,Bachelors,14,70,77,51,84,8.0,3,95,Rural,Software Engineer,128691,1 +74462,Female,57,Bachelors,1,15,79,2,80,0.0,7,21,Semi-Urban,HR Executive,130248,0 +74463,Male,40,Diploma,18,88,12,33,40,0.0,6,19,Urban,Data Analyst,87175,0 +74464,Male,49,Masters,2,61,69,47,76,7.0,7,13,Semi-Urban,Manager,59829,0 +74465,Male,30,Masters,9,66,13,39,43,5.0,6,95,Semi-Urban,Software Engineer,139236,0 +74466,Male,56,High School,16,82,47,74,32,5.0,2,5,Urban,Data Analyst,89704,0 +74467,Female,39,PhD,5,93,47,99,49,9.0,4,30,Urban,Manager,140025,1 +74468,Male,29,Bachelors,12,58,54,95,69,7.0,5,77,Urban,Software Engineer,70679,1 +74469,Male,50,Bachelors,7,80,1,34,37,3.0,7,18,Urban,Data Analyst,106238,0 +74470,Male,43,Diploma,10,91,79,2,16,5.0,4,79,Semi-Urban,ML Engineer,53135,1 +74471,Male,47,High School,18,13,10,88,13,0.0,7,65,Urban,Data Analyst,53081,0 +74472,Male,49,Diploma,10,2,41,53,91,9.0,2,86,Urban,HR Executive,50042,0 +74473,Female,25,Bachelors,8,41,32,88,25,9.0,1,84,Semi-Urban,Data Analyst,95361,1 +74474,Male,46,Masters,19,36,63,84,68,8.0,2,56,Urban,Software Engineer,36381,1 +74475,Female,31,Masters,14,77,24,68,99,9.0,6,40,Semi-Urban,Software Engineer,63217,0 +74476,Male,28,High School,8,90,60,72,30,4.0,1,43,Urban,Manager,148538,1 +74477,Male,47,Bachelors,7,57,52,5,42,0.0,6,35,Rural,Software Engineer,75841,0 +74478,Male,34,Bachelors,12,15,4,63,7,3.0,6,99,Rural,HR Executive,85660,0 +74479,Male,26,Masters,5,24,9,64,67,2.0,2,64,Semi-Urban,Data Analyst,31450,0 +74480,Male,45,Bachelors,5,82,83,0,25,6.0,0,79,Urban,Data Analyst,52179,1 +74481,Male,50,PhD,11,68,40,28,97,6.0,2,62,Rural,Software Engineer,84265,0 +74482,Male,40,Diploma,9,91,43,88,77,8.0,0,76,Semi-Urban,Data Analyst,139685,1 +74483,Female,56,Bachelors,8,81,16,31,25,9.0,6,5,Rural,Software Engineer,96783,0 +74484,Female,26,Diploma,5,36,1,63,5,6.0,0,19,Urban,Manager,96063,0 +74485,Male,27,Bachelors,18,36,68,66,8,3.0,7,56,Semi-Urban,Data Analyst,140808,0 +74486,Male,50,PhD,4,66,87,83,11,9.0,1,78,Urban,Software Engineer,76646,1 +74487,Male,52,Masters,6,8,73,21,81,9.0,6,63,Rural,ML Engineer,130014,0 +74488,Female,29,High School,9,92,33,40,2,2.0,4,70,Rural,HR Executive,122902,0 +74489,Male,31,Bachelors,10,22,53,33,24,8.0,1,6,Urban,HR Executive,71694,0 +74490,Female,31,Bachelors,0,6,32,2,74,1.0,7,92,Rural,Manager,80376,0 +74491,Male,35,Masters,2,16,25,35,45,4.0,7,39,Urban,ML Engineer,109582,0 +74492,Female,28,Bachelors,13,58,70,91,71,6.0,7,41,Urban,Manager,30783,1 +74493,Other,47,Masters,11,72,9,57,30,8.0,5,59,Urban,Data Analyst,23211,0 +74494,Male,45,Bachelors,11,63,15,25,67,4.0,0,59,Urban,Software Engineer,30737,0 +74495,Female,27,Masters,1,71,43,21,53,6.0,1,97,Urban,ML Engineer,20006,0 +74496,Female,40,High School,7,70,4,82,21,8.0,1,91,Urban,HR Executive,44031,1 +74497,Male,36,Diploma,14,55,87,40,81,5.0,1,5,Urban,ML Engineer,35753,0 +74498,Male,42,Bachelors,15,6,76,59,66,8.0,6,97,Rural,Data Analyst,144845,1 +74499,Female,57,Masters,15,32,73,28,49,7.0,0,46,Urban,Software Engineer,60849,0 +74500,Female,28,Diploma,2,55,59,27,43,4.0,2,19,Semi-Urban,Software Engineer,109305,0 +74501,Female,52,Diploma,6,34,68,80,40,4.0,4,19,Rural,Software Engineer,115157,0 +74502,Other,37,Bachelors,6,73,79,98,45,9.0,0,4,Urban,HR Executive,70697,1 +74503,Female,59,Bachelors,16,31,28,27,25,9.0,6,68,Semi-Urban,Data Analyst,113054,0 +74504,Male,37,Bachelors,5,14,56,15,23,1.0,1,29,Urban,ML Engineer,137221,0 +74505,Male,52,Bachelors,2,62,41,69,71,1.0,1,23,Urban,ML Engineer,130503,0 +74506,Male,57,High School,19,59,11,34,16,5.0,3,15,Urban,ML Engineer,148840,0 +74507,Male,47,Bachelors,14,16,55,0,98,5.0,6,49,Urban,ML Engineer,52107,0 +74508,Female,52,Bachelors,16,4,58,29,62,3.0,0,50,Urban,Data Analyst,113742,0 +74509,Female,28,Bachelors,7,40,12,24,46,7.0,7,69,Rural,ML Engineer,60870,0 +74510,Female,22,Bachelors,16,58,16,19,81,7.0,5,2,Rural,Manager,92522,0 +74511,Male,34,Bachelors,9,58,27,97,96,7.0,2,91,Urban,Manager,94396,1 +74512,Female,40,Masters,9,13,6,52,20,6.0,6,87,Urban,Manager,82106,0 +74513,Male,38,Masters,13,72,77,31,95,7.0,6,72,Urban,ML Engineer,61094,1 +74514,Female,27,Bachelors,12,47,81,15,52,9.0,0,76,Urban,Manager,33493,0 +74515,Male,38,Masters,8,77,68,10,85,5.0,3,57,Urban,Software Engineer,57497,0 +74516,Male,44,Diploma,16,35,33,16,9,0.0,6,81,Urban,HR Executive,52134,0 +74517,Male,45,PhD,7,88,4,16,70,2.0,7,18,Urban,Data Analyst,110954,0 +74518,Male,54,Diploma,5,52,78,44,24,6.0,4,9,Urban,ML Engineer,51338,0 +74519,Female,40,Bachelors,10,16,83,46,73,3.0,5,92,Urban,ML Engineer,30852,0 +74520,Female,32,Masters,18,29,17,25,2,9.0,5,51,Urban,Software Engineer,135727,0 +74521,Female,50,Bachelors,1,33,98,64,61,3.0,3,18,Urban,Manager,125811,0 +74522,Male,35,Bachelors,18,44,33,23,70,0.0,3,42,Urban,Manager,133200,0 +74523,Male,43,PhD,17,98,86,76,40,5.0,7,27,Semi-Urban,Data Analyst,21483,1 +74524,Male,25,Masters,2,33,2,26,28,0.0,2,71,Semi-Urban,Manager,133984,0 +74525,Female,35,Bachelors,9,29,87,7,68,0.0,1,62,Urban,Data Analyst,77049,0 +74526,Male,47,Masters,9,49,0,70,16,3.0,0,44,Urban,Data Analyst,36645,0 +74527,Male,31,Bachelors,2,30,46,11,67,1.0,4,76,Urban,ML Engineer,68716,0 +74528,Male,25,Diploma,9,83,73,62,90,4.0,5,11,Rural,Data Analyst,76442,0 +74529,Male,56,Bachelors,9,22,2,56,45,4.0,7,6,Urban,ML Engineer,114322,0 +74530,Female,31,Bachelors,10,22,92,82,83,1.0,4,82,Urban,Manager,102149,1 +74531,Male,43,Bachelors,7,57,78,25,5,4.0,0,57,Rural,Manager,122150,0 +74532,Male,59,Diploma,17,31,25,49,10,4.0,2,32,Semi-Urban,Manager,50288,0 +74533,Male,54,Bachelors,18,19,72,19,57,5.0,2,6,Semi-Urban,Data Analyst,113605,0 +74534,Male,57,Bachelors,12,73,94,29,34,7.0,0,11,Urban,HR Executive,27832,0 +74535,Male,48,PhD,5,21,22,15,7,8.0,3,54,Semi-Urban,Data Analyst,110288,0 +74536,Male,34,Bachelors,16,8,77,81,99,7.0,3,52,Rural,HR Executive,108657,0 +74537,Male,21,Bachelors,5,77,92,61,81,1.0,2,33,Urban,Manager,114881,1 +74538,Female,49,Masters,3,48,71,61,69,7.0,0,66,Urban,ML Engineer,108064,1 +74539,Male,21,Bachelors,17,50,63,66,14,8.0,2,44,Urban,Manager,148576,0 +74540,Male,25,High School,13,17,47,12,65,8.0,3,97,Rural,ML Engineer,50295,0 +74541,Male,34,Bachelors,10,70,36,96,76,1.0,2,21,Urban,Software Engineer,93938,0 +74542,Male,34,Diploma,13,86,44,67,87,3.0,3,32,Semi-Urban,HR Executive,99338,0 +74543,Male,36,Bachelors,13,57,46,45,55,4.0,0,93,Urban,Data Analyst,65594,1 +74544,Male,53,Masters,3,88,34,9,80,6.0,7,40,Urban,ML Engineer,97727,0 +74545,Male,58,Diploma,6,69,29,13,64,8.0,0,75,Urban,Manager,65654,0 +74546,Female,25,Bachelors,2,30,11,5,53,3.0,4,34,Semi-Urban,Data Analyst,115221,0 +74547,Male,45,Bachelors,8,68,59,61,73,2.0,0,33,Urban,Manager,126644,0 +74548,Male,23,Bachelors,3,98,45,44,36,6.0,1,27,Urban,Manager,78273,0 +74549,Female,48,Masters,5,70,7,32,41,2.0,1,56,Urban,Software Engineer,35851,0 +74550,Female,26,Bachelors,10,0,30,19,98,6.0,1,87,Urban,HR Executive,28668,0 +74551,Male,59,Bachelors,1,36,51,91,81,4.0,1,12,Rural,HR Executive,144454,0 +74552,Female,25,PhD,15,64,1,12,73,7.0,6,31,Urban,HR Executive,137440,0 +74553,Male,26,High School,1,76,96,26,16,3.0,6,7,Urban,ML Engineer,38785,0 +74554,Male,28,PhD,4,41,14,43,65,3.0,2,5,Urban,Software Engineer,83350,0 +74555,Male,52,Bachelors,3,69,19,42,18,8.0,0,52,Semi-Urban,Software Engineer,53667,0 +74556,Other,21,Bachelors,2,25,86,9,78,6.0,0,75,Rural,Data Analyst,55321,0 +74557,Female,51,Masters,18,12,51,48,29,8.0,2,80,Semi-Urban,Software Engineer,117836,0 +74558,Male,36,Bachelors,7,53,1,72,4,3.0,2,32,Urban,Manager,106225,0 +74559,Male,58,Bachelors,1,11,13,39,34,7.0,4,28,Semi-Urban,Data Analyst,69020,0 +74560,Female,21,Masters,19,39,50,0,52,9.0,7,17,Semi-Urban,Manager,41155,0 +74561,Male,24,Bachelors,15,71,92,56,33,1.0,0,92,Rural,Manager,82978,1 +74562,Male,44,Masters,1,59,7,9,74,3.0,7,27,Rural,ML Engineer,41290,0 +74563,Male,43,High School,0,85,63,48,38,0.0,6,60,Semi-Urban,HR Executive,98897,1 +74564,Male,45,Bachelors,10,24,50,41,97,1.0,0,2,Urban,Manager,73698,0 +74565,Male,59,Diploma,6,9,91,83,25,1.0,3,3,Urban,Data Analyst,90514,0 +74566,Female,48,Diploma,5,65,98,51,32,0.0,1,41,Urban,HR Executive,33528,1 +74567,Male,30,Bachelors,15,30,29,19,52,3.0,1,99,Rural,Software Engineer,128728,0 +74568,Female,25,High School,8,73,39,1,35,5.0,7,9,Urban,Data Analyst,41937,0 +74569,Male,25,Bachelors,3,34,0,85,57,5.0,2,17,Semi-Urban,Data Analyst,110067,0 +74570,Female,58,High School,0,77,65,36,46,8.0,1,6,Urban,ML Engineer,105907,0 +74571,Female,49,High School,14,40,12,27,44,1.0,2,96,Urban,HR Executive,93921,0 +74572,Male,27,Bachelors,14,83,48,0,49,1.0,3,1,Semi-Urban,ML Engineer,82565,0 +74573,Female,53,Bachelors,12,77,97,67,51,9.0,3,58,Urban,Software Engineer,120768,1 +74574,Female,47,Masters,12,60,89,65,3,8.0,1,9,Rural,Manager,98477,0 +74575,Female,31,PhD,2,78,88,31,41,6.0,5,18,Semi-Urban,Manager,87550,0 +74576,Male,59,Bachelors,8,73,94,50,51,1.0,5,19,Semi-Urban,Manager,121604,1 +74577,Male,27,PhD,7,10,2,69,75,8.0,7,78,Semi-Urban,Data Analyst,55111,0 +74578,Male,25,Bachelors,7,37,85,4,67,5.0,2,40,Urban,Data Analyst,68374,0 +74579,Male,48,Bachelors,8,99,87,32,31,2.0,1,48,Semi-Urban,ML Engineer,51937,1 +74580,Other,57,Bachelors,3,22,80,34,16,2.0,1,11,Urban,HR Executive,135850,0 +74581,Male,51,High School,1,59,89,98,22,3.0,3,10,Rural,ML Engineer,93303,1 +74582,Female,49,Diploma,15,78,1,29,28,6.0,7,65,Semi-Urban,HR Executive,72668,0 +74583,Female,56,High School,2,29,32,19,33,8.0,3,92,Semi-Urban,Manager,22362,0 +74584,Male,51,Bachelors,10,2,67,20,78,0.0,2,0,Urban,ML Engineer,41722,0 +74585,Other,29,Masters,18,26,16,37,67,3.0,6,90,Urban,HR Executive,114871,0 +74586,Female,24,Bachelors,1,80,25,22,43,7.0,4,14,Urban,Software Engineer,101178,0 +74587,Male,22,Masters,17,29,77,83,27,5.0,6,72,Rural,ML Engineer,85426,1 +74588,Male,55,Bachelors,6,46,75,57,29,9.0,2,45,Rural,Software Engineer,79655,0 +74589,Male,37,Bachelors,0,59,28,21,51,9.0,5,36,Rural,HR Executive,40317,0 +74590,Male,21,Bachelors,7,35,97,85,11,9.0,1,93,Urban,Data Analyst,34683,1 +74591,Male,40,Masters,13,8,0,94,43,0.0,5,18,Rural,Data Analyst,107861,0 +74592,Female,29,Diploma,8,1,44,97,56,1.0,3,98,Semi-Urban,HR Executive,21113,0 +74593,Male,58,Bachelors,0,18,33,98,2,4.0,0,91,Rural,Software Engineer,55585,1 +74594,Female,40,Bachelors,5,95,88,62,12,5.0,0,5,Rural,Software Engineer,129521,1 +74595,Male,56,Masters,4,71,39,68,75,8.0,6,69,Rural,Manager,123456,1 +74596,Male,31,Diploma,5,46,94,95,99,7.0,3,54,Semi-Urban,HR Executive,141106,1 +74597,Male,38,Diploma,19,49,3,77,55,8.0,7,69,Urban,Manager,41895,0 +74598,Female,40,Diploma,14,52,41,85,66,1.0,4,45,Urban,Software Engineer,129898,0 +74599,Male,32,Masters,8,59,27,83,52,1.0,7,19,Urban,ML Engineer,105744,0 +74600,Female,41,Masters,2,44,88,89,76,7.0,7,52,Urban,Software Engineer,90725,1 +74601,Male,39,Masters,18,19,37,62,50,8.0,4,59,Urban,Software Engineer,42486,0 +74602,Male,56,Bachelors,7,80,77,21,47,7.0,4,26,Rural,ML Engineer,41705,0 +74603,Female,46,Diploma,1,22,41,10,37,3.0,4,24,Rural,Manager,28109,0 +74604,Other,36,High School,15,49,19,40,38,9.0,6,97,Rural,Manager,128975,0 +74605,Female,44,Bachelors,13,70,53,7,6,8.0,0,62,Semi-Urban,Software Engineer,130431,0 +74606,Female,31,Bachelors,3,66,48,44,39,8.0,4,57,Urban,HR Executive,110219,0 +74607,Male,25,Diploma,15,85,89,55,16,8.0,6,83,Urban,Data Analyst,53702,1 +74608,Male,53,Bachelors,6,54,56,83,70,0.0,3,89,Urban,ML Engineer,124390,1 +74609,Male,22,Bachelors,4,85,99,14,49,2.0,5,85,Urban,Data Analyst,45429,1 +74610,Male,35,Masters,6,82,79,8,36,2.0,3,1,Urban,ML Engineer,146377,0 +74611,Male,53,Masters,12,4,71,90,61,5.0,1,4,Urban,HR Executive,67120,0 +74612,Male,56,High School,8,84,15,28,13,6.0,5,25,Urban,HR Executive,112058,0 +74613,Male,47,PhD,3,46,75,87,17,7.0,4,44,Urban,HR Executive,67528,1 +74614,Female,59,Masters,2,75,85,57,69,3.0,1,76,Rural,Data Analyst,139205,1 +74615,Male,40,Bachelors,12,96,39,69,98,5.0,5,71,Urban,Software Engineer,123870,1 +74616,Male,57,Masters,6,53,84,61,95,0.0,4,17,Semi-Urban,Data Analyst,40391,0 +74617,Male,55,Bachelors,4,78,98,92,52,9.0,3,64,Rural,ML Engineer,99055,1 +74618,Female,53,Diploma,15,68,34,12,68,3.0,6,10,Urban,ML Engineer,49377,0 +74619,Male,21,Bachelors,17,56,55,37,10,0.0,6,16,Rural,Data Analyst,33286,0 +74620,Male,52,High School,0,69,77,54,82,4.0,4,47,Urban,Manager,149058,1 +74621,Male,42,Masters,16,11,93,2,55,4.0,3,41,Urban,Data Analyst,120923,0 +74622,Male,47,Bachelors,4,63,2,32,58,6.0,5,51,Semi-Urban,Data Analyst,132920,0 +74623,Male,42,Bachelors,7,27,83,55,74,9.0,7,37,Urban,Data Analyst,77743,0 +74624,Male,58,Bachelors,10,24,53,30,79,4.0,3,46,Urban,ML Engineer,104080,0 +74625,Male,29,Masters,7,17,60,42,55,9.0,3,93,Semi-Urban,Software Engineer,142106,0 +74626,Male,30,Diploma,4,47,72,12,57,6.0,4,49,Urban,Software Engineer,72660,0 +74627,Male,44,PhD,1,41,45,25,41,7.0,1,90,Semi-Urban,Manager,135386,0 +74628,Male,43,Bachelors,18,45,8,98,75,4.0,4,45,Urban,Data Analyst,102706,0 +74629,Male,58,Bachelors,5,60,32,64,92,2.0,6,92,Urban,Software Engineer,129115,1 +74630,Male,54,Bachelors,13,65,98,3,37,5.0,1,37,Urban,Data Analyst,51054,0 +74631,Male,38,Bachelors,18,31,95,19,81,1.0,0,5,Rural,Manager,47367,0 +74632,Female,36,High School,9,93,88,93,64,8.0,7,43,Urban,Data Analyst,149651,1 +74633,Female,55,Diploma,4,43,98,59,10,0.0,1,84,Rural,HR Executive,49708,1 +74634,Male,35,Bachelors,0,72,14,2,49,8.0,2,5,Semi-Urban,Data Analyst,81321,0 +74635,Male,48,Diploma,1,94,28,41,67,4.0,6,0,Urban,HR Executive,52934,0 +74636,Female,51,Masters,2,33,99,34,38,5.0,4,13,Urban,Data Analyst,29628,0 +74637,Female,30,Bachelors,16,50,98,17,65,3.0,6,49,Urban,ML Engineer,132159,0 +74638,Male,23,Bachelors,1,85,9,60,58,5.0,2,34,Rural,ML Engineer,47103,0 +74639,Male,35,Bachelors,0,69,1,4,8,7.0,4,14,Urban,Data Analyst,130811,0 +74640,Female,41,Bachelors,7,44,58,53,76,6.0,5,12,Rural,HR Executive,21708,0 +74641,Male,59,Masters,16,1,48,80,98,7.0,6,22,Urban,Software Engineer,59696,0 +74642,Male,23,PhD,14,41,45,67,70,8.0,1,98,Semi-Urban,Manager,118191,1 +74643,Female,49,Masters,3,85,20,28,9,2.0,1,54,Urban,HR Executive,82447,0 +74644,Male,53,Bachelors,12,15,99,43,56,2.0,4,84,Semi-Urban,HR Executive,61057,1 +74645,Male,58,Masters,9,64,35,57,61,4.0,2,87,Urban,ML Engineer,134946,1 +74646,Male,54,High School,17,67,7,70,81,2.0,7,64,Urban,Data Analyst,122565,0 +74647,Female,48,High School,5,51,95,19,51,5.0,4,7,Urban,Data Analyst,131696,0 +74648,Male,49,Bachelors,4,12,97,26,18,4.0,0,93,Urban,HR Executive,27329,0 +74649,Female,28,Diploma,2,42,68,28,76,4.0,4,95,Urban,Data Analyst,138275,0 +74650,Male,28,Bachelors,7,31,80,99,78,6.0,6,53,Rural,HR Executive,122760,1 +74651,Female,52,Masters,5,90,39,50,0,3.0,5,78,Semi-Urban,Software Engineer,62616,1 +74652,Male,28,High School,2,1,48,37,4,9.0,2,48,Urban,Manager,136384,0 +74653,Female,51,Bachelors,5,38,29,85,65,4.0,1,18,Rural,HR Executive,121375,0 +74654,Male,56,High School,16,54,40,32,21,2.0,0,33,Semi-Urban,HR Executive,64735,0 +74655,Male,39,Bachelors,1,68,71,68,18,8.0,4,21,Urban,Software Engineer,83881,0 +74656,Female,43,PhD,19,5,32,46,19,1.0,0,56,Urban,HR Executive,36696,0 +74657,Female,48,Diploma,0,16,77,92,44,1.0,1,83,Semi-Urban,Manager,89645,1 +74658,Male,21,Masters,7,31,33,62,53,8.0,4,2,Semi-Urban,Data Analyst,149848,0 +74659,Female,26,Bachelors,5,21,69,48,60,3.0,7,18,Urban,ML Engineer,125140,0 +74660,Female,54,Bachelors,19,55,33,74,2,7.0,2,21,Urban,ML Engineer,109427,0 +74661,Male,35,PhD,1,11,92,24,88,6.0,2,72,Rural,Data Analyst,145021,0 +74662,Other,51,Bachelors,19,63,22,80,99,2.0,2,7,Semi-Urban,Manager,128738,0 +74663,Male,57,Diploma,12,23,7,18,28,5.0,5,70,Rural,Data Analyst,100943,0 +74664,Male,35,Bachelors,9,15,47,43,95,2.0,7,29,Urban,Software Engineer,55530,0 +74665,Male,29,Bachelors,14,24,40,2,6,0.0,3,91,Rural,Software Engineer,106275,0 +74666,Female,58,Masters,4,46,21,47,11,5.0,0,96,Urban,Data Analyst,34058,0 +74667,Male,22,High School,2,85,32,76,97,9.0,3,35,Semi-Urban,ML Engineer,71688,0 +74668,Female,30,Masters,5,69,12,42,1,0.0,1,11,Urban,ML Engineer,112046,0 +74669,Female,57,Masters,12,73,94,70,98,7.0,1,85,Rural,Software Engineer,90964,1 +74670,Male,47,High School,18,81,9,82,59,7.0,6,34,Urban,Manager,35864,0 +74671,Male,49,Masters,4,75,40,5,58,2.0,0,98,Semi-Urban,HR Executive,39914,0 +74672,Male,54,High School,1,13,11,98,9,2.0,3,20,Urban,Data Analyst,143702,0 +74673,Male,32,Bachelors,1,48,4,96,92,9.0,4,43,Rural,ML Engineer,142422,0 +74674,Female,52,High School,3,78,89,85,44,6.0,7,92,Semi-Urban,Manager,112930,1 +74675,Female,46,Bachelors,0,81,30,21,73,7.0,1,33,Semi-Urban,Software Engineer,31136,0 +74676,Female,30,Bachelors,0,65,30,56,91,9.0,6,53,Urban,ML Engineer,42286,0 +74677,Male,32,High School,4,7,44,4,71,8.0,1,19,Urban,HR Executive,60905,0 +74678,Female,59,Diploma,10,75,27,11,52,6.0,6,93,Semi-Urban,HR Executive,105355,0 +74679,Female,21,Bachelors,7,55,59,82,0,4.0,4,31,Semi-Urban,Data Analyst,26298,0 +74680,Female,28,Masters,7,54,54,40,98,8.0,4,19,Urban,Data Analyst,51218,0 +74681,Male,57,Diploma,6,57,11,1,20,8.0,6,69,Urban,HR Executive,146027,0 +74682,Male,33,High School,12,68,24,13,11,0.0,0,14,Semi-Urban,ML Engineer,56553,0 +74683,Female,32,PhD,1,37,48,90,0,4.0,3,4,Semi-Urban,Manager,85157,0 +74684,Female,35,Bachelors,12,11,78,15,92,9.0,1,86,Urban,Software Engineer,43523,0 +74685,Female,50,Masters,18,83,37,31,1,3.0,0,85,Semi-Urban,HR Executive,65053,0 +74686,Male,23,Masters,0,23,0,42,37,1.0,0,93,Urban,Data Analyst,109134,0 +74687,Male,56,Bachelors,2,48,64,90,46,8.0,1,36,Urban,Software Engineer,142546,1 +74688,Female,53,Masters,12,6,83,13,38,8.0,3,50,Urban,Manager,113116,0 +74689,Male,40,High School,16,41,91,70,37,0.0,4,67,Urban,Manager,59056,1 +74690,Male,28,Bachelors,9,22,89,17,61,6.0,5,36,Semi-Urban,HR Executive,45333,0 +74691,Male,51,Bachelors,9,76,59,43,84,3.0,6,66,Urban,Manager,94225,1 +74692,Male,42,Bachelors,14,35,85,56,75,2.0,4,8,Rural,Manager,44136,0 +74693,Male,34,Diploma,5,54,22,67,49,0.0,4,8,Rural,HR Executive,115273,0 +74694,Male,42,Diploma,3,3,22,57,31,9.0,1,72,Urban,Software Engineer,21409,0 +74695,Male,59,Bachelors,16,90,74,51,85,8.0,4,82,Rural,ML Engineer,55730,1 +74696,Male,51,Bachelors,16,62,54,94,19,3.0,5,93,Semi-Urban,ML Engineer,141490,1 +74697,Female,30,Masters,18,99,79,12,40,2.0,5,9,Urban,ML Engineer,23792,0 +74698,Female,23,Diploma,0,52,22,0,1,1.0,7,93,Rural,Software Engineer,90164,0 +74699,Male,56,Masters,17,13,72,14,75,2.0,7,8,Urban,Data Analyst,63626,0 +74700,Male,56,Diploma,4,88,51,90,68,2.0,5,37,Urban,ML Engineer,106582,1 +74701,Female,25,Bachelors,0,48,21,44,73,9.0,5,18,Semi-Urban,Manager,147355,0 +74702,Male,26,Bachelors,1,57,96,52,22,3.0,0,70,Urban,Software Engineer,85396,1 +74703,Male,56,Diploma,0,96,31,56,43,1.0,5,71,Semi-Urban,Software Engineer,143218,1 +74704,Female,31,High School,14,66,51,70,43,1.0,6,75,Urban,Data Analyst,66711,1 +74705,Male,24,High School,6,92,87,98,43,7.0,4,69,Urban,ML Engineer,75840,1 +74706,Female,57,Bachelors,16,88,74,19,85,4.0,6,73,Urban,ML Engineer,109766,1 +74707,Male,55,Bachelors,16,12,46,85,88,0.0,0,3,Semi-Urban,Software Engineer,32994,0 +74708,Male,40,Bachelors,5,83,67,55,52,6.0,7,0,Semi-Urban,Software Engineer,46080,0 +74709,Male,57,High School,16,46,85,46,16,6.0,5,65,Urban,HR Executive,104098,1 +74710,Female,55,Bachelors,7,53,84,22,32,0.0,2,44,Urban,HR Executive,23419,0 +74711,Male,30,Masters,3,40,57,82,77,2.0,7,87,Urban,HR Executive,36233,1 +74712,Female,28,Diploma,10,98,36,66,70,5.0,4,82,Rural,Manager,29647,1 +74713,Female,33,Diploma,14,28,4,63,80,6.0,6,80,Rural,Software Engineer,117992,0 +74714,Male,56,Bachelors,16,75,49,60,32,5.0,7,62,Rural,Manager,33074,1 +74715,Female,50,Bachelors,4,90,95,22,2,8.0,7,41,Urban,Software Engineer,91239,1 +74716,Female,53,High School,0,45,18,11,67,6.0,7,44,Rural,Software Engineer,46829,0 +74717,Male,45,Diploma,19,48,40,88,53,9.0,1,51,Semi-Urban,Data Analyst,33240,0 +74718,Male,36,Bachelors,2,32,16,50,12,1.0,1,8,Urban,HR Executive,103134,0 +74719,Male,24,Diploma,18,62,58,55,32,7.0,6,83,Rural,Data Analyst,109913,1 +74720,Male,56,Masters,11,55,15,79,31,1.0,2,73,Urban,Data Analyst,40619,0 +74721,Female,35,Masters,5,7,97,7,98,8.0,7,94,Urban,Data Analyst,143205,0 +74722,Female,55,High School,1,96,93,62,87,2.0,4,65,Semi-Urban,ML Engineer,146989,1 +74723,Male,24,Bachelors,0,52,58,94,15,9.0,7,70,Urban,HR Executive,90993,1 +74724,Other,50,Masters,13,98,71,62,5,7.0,2,42,Urban,Software Engineer,128101,1 +74725,Female,25,High School,5,14,42,16,41,9.0,5,25,Rural,Software Engineer,57675,0 +74726,Male,44,Masters,16,66,16,33,90,4.0,7,5,Semi-Urban,ML Engineer,53709,0 +74727,Female,29,Bachelors,15,78,31,77,20,3.0,5,1,Semi-Urban,Manager,144449,0 +74728,Male,27,Diploma,14,47,94,92,62,9.0,1,23,Urban,Software Engineer,78974,1 +74729,Male,35,High School,19,78,16,33,11,0.0,2,79,Semi-Urban,HR Executive,139686,0 +74730,Female,47,PhD,8,38,23,7,8,7.0,1,90,Urban,Manager,43113,0 +74731,Male,53,Diploma,14,48,53,78,83,7.0,1,78,Urban,HR Executive,77470,1 +74732,Male,53,Bachelors,16,23,59,96,4,6.0,4,65,Urban,ML Engineer,123735,1 +74733,Male,52,Bachelors,12,82,96,90,63,8.0,0,93,Urban,Software Engineer,90111,1 +74734,Female,25,Diploma,17,3,4,29,44,9.0,2,3,Urban,ML Engineer,128418,0 +74735,Male,31,Bachelors,14,46,28,60,84,5.0,1,40,Urban,HR Executive,68697,0 +74736,Male,52,Bachelors,14,84,52,26,72,9.0,4,29,Urban,Manager,76635,0 +74737,Female,27,PhD,13,19,84,35,10,0.0,5,67,Urban,ML Engineer,53682,0 +74738,Female,43,Bachelors,0,32,44,82,58,3.0,6,20,Urban,Data Analyst,122169,0 +74739,Male,53,Bachelors,4,58,60,73,5,8.0,4,14,Urban,Manager,35748,0 +74740,Male,41,Masters,1,59,52,99,63,8.0,1,15,Urban,Software Engineer,42197,0 +74741,Male,32,Bachelors,11,49,79,25,18,0.0,2,49,Rural,Data Analyst,67686,0 +74742,Male,40,Bachelors,6,85,75,74,62,0.0,2,66,Urban,ML Engineer,143696,1 +74743,Other,51,Diploma,1,31,43,91,6,3.0,0,40,Urban,Manager,35661,0 +74744,Male,53,Bachelors,18,23,18,17,81,9.0,0,42,Semi-Urban,Manager,129705,0 +74745,Male,48,Bachelors,2,41,19,98,85,9.0,7,17,Urban,Manager,134788,0 +74746,Female,26,Bachelors,14,52,43,18,87,9.0,2,16,Semi-Urban,HR Executive,110697,0 +74747,Female,28,Masters,10,81,93,75,72,8.0,1,89,Semi-Urban,HR Executive,57766,1 +74748,Female,23,High School,4,15,75,80,0,3.0,4,20,Urban,Software Engineer,71585,0 +74749,Female,45,Masters,0,74,58,40,10,2.0,2,48,Urban,Software Engineer,89607,0 +74750,Other,48,Bachelors,7,80,3,24,89,7.0,0,55,Rural,HR Executive,35749,0 +74751,Male,35,Masters,19,62,26,88,62,4.0,3,33,Rural,Data Analyst,70236,0 +74752,Male,59,Diploma,15,67,10,34,40,9.0,1,33,Urban,ML Engineer,84910,0 +74753,Female,29,Bachelors,4,95,6,11,77,7.0,6,66,Semi-Urban,Manager,37212,0 +74754,Male,54,High School,6,33,50,55,36,9.0,5,1,Urban,HR Executive,145563,0 +74755,Female,51,Bachelors,0,70,6,51,42,3.0,7,8,Urban,ML Engineer,53400,0 +74756,Male,58,Bachelors,15,6,74,32,0,9.0,7,59,Urban,ML Engineer,30566,0 +74757,Male,52,Bachelors,14,68,29,65,60,5.0,3,47,Rural,Software Engineer,74274,0 +74758,Female,34,Bachelors,6,73,40,4,75,1.0,3,65,Semi-Urban,HR Executive,106460,0 +74759,Male,58,PhD,12,35,58,64,97,9.0,5,46,Rural,ML Engineer,34813,0 +74760,Female,36,PhD,4,69,64,51,24,4.0,2,66,Semi-Urban,Data Analyst,70741,1 +74761,Male,30,Diploma,7,42,99,47,83,9.0,0,7,Urban,HR Executive,30924,0 +74762,Male,38,Diploma,4,91,76,34,2,4.0,2,42,Semi-Urban,Software Engineer,109949,1 +74763,Male,47,High School,2,61,15,55,32,6.0,1,49,Urban,Software Engineer,144772,0 +74764,Male,31,Bachelors,19,69,26,49,45,4.0,5,33,Semi-Urban,HR Executive,123146,0 +74765,Male,53,Bachelors,5,59,46,0,41,0.0,4,14,Urban,HR Executive,39880,0 +74766,Male,57,Diploma,19,92,43,67,21,4.0,0,75,Semi-Urban,HR Executive,83736,1 +74767,Male,40,Bachelors,10,32,94,66,13,9.0,3,59,Urban,Manager,128386,1 +74768,Male,23,PhD,15,57,65,73,10,2.0,6,60,Urban,Data Analyst,102228,1 +74769,Female,41,Diploma,17,83,86,20,3,3.0,7,84,Urban,HR Executive,41056,1 +74770,Female,32,Bachelors,8,17,23,88,90,3.0,0,10,Rural,Manager,66387,0 +74771,Female,28,Bachelors,9,54,52,60,64,7.0,0,90,Semi-Urban,HR Executive,68873,1 +74772,Female,57,Diploma,2,60,69,54,6,2.0,6,43,Rural,Data Analyst,70089,0 +74773,Male,52,Masters,1,86,81,59,53,8.0,5,62,Semi-Urban,Data Analyst,61573,1 +74774,Female,28,Bachelors,14,17,15,11,45,1.0,1,46,Semi-Urban,Software Engineer,40289,0 +74775,Male,35,Diploma,12,11,44,41,91,9.0,5,92,Urban,Manager,47583,0 +74776,Male,23,Bachelors,17,76,79,24,21,5.0,6,20,Semi-Urban,Software Engineer,105980,0 +74777,Male,43,Masters,8,71,33,33,27,4.0,1,82,Semi-Urban,Software Engineer,86349,0 +74778,Female,31,Bachelors,3,33,59,11,84,9.0,5,66,Semi-Urban,Data Analyst,113246,0 +74779,Female,42,Bachelors,15,21,88,59,66,6.0,0,5,Urban,ML Engineer,98556,0 +74780,Male,27,Diploma,5,48,84,12,3,1.0,5,56,Semi-Urban,Software Engineer,107324,0 +74781,Male,24,Diploma,9,63,15,2,74,2.0,6,82,Urban,Software Engineer,83085,0 +74782,Male,38,Bachelors,9,49,10,93,46,1.0,7,82,Semi-Urban,ML Engineer,129212,0 +74783,Female,48,Masters,0,14,39,89,6,8.0,3,36,Rural,HR Executive,99552,0 +74784,Male,52,PhD,2,38,32,2,52,0.0,0,41,Semi-Urban,ML Engineer,69458,0 +74785,Male,34,Masters,4,95,2,12,70,4.0,1,99,Urban,Software Engineer,103698,0 +74786,Male,25,Masters,17,48,83,52,66,0.0,5,7,Urban,HR Executive,93938,0 +74787,Male,38,PhD,18,2,76,12,12,1.0,1,82,Urban,Data Analyst,145757,0 +74788,Male,49,Bachelors,18,71,55,47,94,4.0,5,92,Urban,Data Analyst,114668,1 +74789,Male,37,Bachelors,8,1,23,29,31,6.0,3,75,Rural,ML Engineer,22883,0 +74790,Male,41,Bachelors,12,93,36,58,85,1.0,5,74,Semi-Urban,ML Engineer,110616,1 +74791,Male,54,Bachelors,6,2,62,57,43,9.0,5,59,Urban,ML Engineer,79144,0 +74792,Male,41,Masters,7,7,48,31,53,2.0,3,88,Urban,Manager,37323,0 +74793,Male,54,Diploma,8,62,61,47,92,9.0,2,84,Semi-Urban,Data Analyst,97128,1 +74794,Male,27,Bachelors,3,89,49,13,78,0.0,0,47,Semi-Urban,ML Engineer,120969,0 +74795,Male,38,Masters,8,42,60,79,91,0.0,2,75,Rural,Software Engineer,63961,1 +74796,Female,38,PhD,19,58,86,72,69,5.0,3,33,Urban,Software Engineer,59055,1 +74797,Female,33,Bachelors,10,56,12,15,28,8.0,2,75,Rural,Software Engineer,70582,0 +74798,Male,59,PhD,11,49,92,72,54,2.0,3,44,Rural,ML Engineer,126643,1 +74799,Male,49,Bachelors,13,92,18,40,72,3.0,1,0,Urban,ML Engineer,58754,0 +74800,Male,59,Masters,14,72,9,96,89,4.0,0,38,Semi-Urban,Manager,61776,0 +74801,Other,45,Bachelors,16,42,77,21,66,7.0,6,23,Urban,ML Engineer,125639,0 +74802,Other,38,Diploma,4,66,25,13,56,0.0,2,50,Rural,Software Engineer,97964,0 +74803,Male,26,Bachelors,6,39,22,44,24,8.0,2,69,Urban,ML Engineer,147675,0 +74804,Female,29,Bachelors,6,76,58,46,40,4.0,5,48,Rural,ML Engineer,90265,0 +74805,Male,32,Diploma,4,52,35,47,14,5.0,1,0,Urban,Manager,38909,0 +74806,Female,31,Masters,8,51,7,49,45,3.0,7,51,Semi-Urban,ML Engineer,61094,0 +74807,Male,41,Bachelors,11,6,36,77,49,3.0,3,88,Urban,HR Executive,51300,0 +74808,Male,27,Bachelors,9,17,62,83,43,2.0,0,75,Urban,Manager,123809,1 +74809,Male,35,PhD,18,51,54,46,85,5.0,3,41,Urban,ML Engineer,148772,0 +74810,Male,40,Diploma,18,21,62,69,64,6.0,7,61,Urban,HR Executive,59185,0 +74811,Male,51,Bachelors,11,13,92,93,30,2.0,3,95,Semi-Urban,ML Engineer,26495,1 +74812,Male,42,Masters,6,20,22,3,95,4.0,6,57,Semi-Urban,HR Executive,115715,0 +74813,Male,42,Bachelors,5,59,80,65,53,4.0,4,42,Urban,HR Executive,58110,1 +74814,Male,29,Diploma,13,22,26,82,94,8.0,5,10,Urban,Manager,147879,0 +74815,Male,50,High School,12,54,18,99,93,5.0,1,43,Urban,Software Engineer,36987,0 +74816,Female,46,Bachelors,0,42,66,61,14,7.0,2,3,Urban,Software Engineer,147117,0 +74817,Male,39,Masters,1,25,99,44,45,6.0,6,51,Rural,Data Analyst,28432,0 +74818,Female,38,Masters,19,30,94,2,52,6.0,5,47,Urban,HR Executive,91110,0 +74819,Male,42,Bachelors,5,68,31,11,34,7.0,7,35,Semi-Urban,HR Executive,114483,0 +74820,Male,33,High School,12,2,48,17,84,1.0,7,3,Urban,Manager,84125,0 +74821,Male,30,Masters,14,13,29,29,38,9.0,6,86,Semi-Urban,HR Executive,103995,0 +74822,Male,29,Diploma,6,44,4,41,68,2.0,3,6,Urban,Data Analyst,23403,0 +74823,Female,24,Diploma,6,16,78,37,90,7.0,7,5,Urban,Manager,73718,0 +74824,Male,46,PhD,5,68,43,85,16,1.0,5,67,Rural,HR Executive,33451,1 +74825,Male,37,Diploma,16,53,33,6,11,5.0,5,92,Semi-Urban,Manager,76022,0 +74826,Male,34,Bachelors,11,20,69,62,47,0.0,0,44,Urban,Software Engineer,123013,0 +74827,Female,43,Bachelors,5,55,12,44,14,3.0,0,42,Urban,Software Engineer,50693,0 +74828,Female,41,Masters,14,1,34,55,28,1.0,3,26,Urban,Data Analyst,45168,0 +74829,Female,58,Masters,1,91,17,2,36,0.0,1,30,Urban,Manager,61681,0 +74830,Male,24,Bachelors,14,42,77,96,15,2.0,7,93,Urban,Software Engineer,138678,1 +74831,Female,48,Masters,16,33,28,20,10,9.0,6,1,Semi-Urban,HR Executive,22664,0 +74832,Female,45,Bachelors,1,76,25,66,55,2.0,7,63,Rural,Data Analyst,104674,0 +74833,Male,23,Diploma,5,12,21,36,9,4.0,6,74,Rural,ML Engineer,92799,0 +74834,Male,28,High School,4,15,57,20,91,2.0,2,3,Urban,ML Engineer,85387,0 +74835,Female,46,Diploma,19,44,93,79,99,6.0,2,21,Rural,ML Engineer,114592,0 +74836,Female,55,Diploma,13,28,18,42,48,9.0,0,91,Urban,ML Engineer,36784,0 +74837,Male,33,Bachelors,17,28,91,41,6,9.0,5,88,Semi-Urban,Data Analyst,75754,1 +74838,Male,28,Diploma,1,89,80,29,8,0.0,1,56,Urban,ML Engineer,113327,1 +74839,Male,32,Bachelors,13,96,21,68,58,3.0,6,44,Rural,ML Engineer,111752,0 +74840,Female,21,High School,19,98,50,59,95,6.0,3,45,Urban,ML Engineer,74196,1 +74841,Female,21,Masters,13,19,28,10,66,5.0,4,24,Urban,Manager,92978,0 +74842,Male,59,Bachelors,9,80,6,36,75,3.0,7,38,Urban,Software Engineer,147860,0 +74843,Female,47,High School,9,46,3,16,22,1.0,2,45,Urban,ML Engineer,106185,0 +74844,Female,49,Diploma,16,45,6,18,23,8.0,6,53,Semi-Urban,ML Engineer,96993,0 +74845,Male,41,Bachelors,6,56,53,69,12,0.0,6,88,Urban,HR Executive,63033,1 +74846,Male,33,Bachelors,19,48,93,13,24,6.0,0,62,Urban,HR Executive,145220,0 +74847,Male,35,Bachelors,9,70,59,55,74,5.0,4,44,Urban,Data Analyst,34025,0 +74848,Male,29,PhD,7,91,23,89,77,1.0,3,50,Urban,Software Engineer,75270,1 +74849,Female,44,Masters,14,36,87,18,41,9.0,6,86,Semi-Urban,Software Engineer,98376,0 +74850,Male,58,Diploma,6,27,8,34,29,1.0,2,19,Semi-Urban,ML Engineer,136854,0 +74851,Female,32,Masters,19,12,42,22,85,7.0,6,90,Rural,ML Engineer,60199,0 +74852,Male,41,High School,15,87,36,54,35,1.0,6,56,Urban,Data Analyst,95016,0 +74853,Male,51,Bachelors,11,59,0,25,39,7.0,1,55,Urban,Software Engineer,73119,0 +74854,Male,40,Masters,1,1,81,17,20,4.0,1,9,Rural,Software Engineer,138183,0 +74855,Male,43,Masters,7,10,49,29,75,5.0,1,43,Semi-Urban,Data Analyst,30895,0 +74856,Male,38,Bachelors,19,82,36,41,9,0.0,4,43,Rural,Software Engineer,66962,0 +74857,Male,40,Diploma,19,64,34,34,78,5.0,7,48,Rural,ML Engineer,93815,0 +74858,Male,39,Bachelors,7,18,22,20,33,2.0,5,22,Rural,Data Analyst,128299,0 +74859,Male,27,Bachelors,18,80,45,85,28,3.0,6,53,Urban,Software Engineer,24241,1 +74860,Female,42,PhD,19,56,7,70,46,9.0,4,32,Urban,ML Engineer,89106,0 +74861,Male,57,Masters,12,97,56,77,81,9.0,4,8,Urban,Software Engineer,31800,1 +74862,Female,37,Diploma,18,17,71,18,69,8.0,3,90,Semi-Urban,Software Engineer,117221,0 +74863,Male,31,Diploma,15,3,95,46,91,4.0,0,43,Urban,Manager,66452,0 +74864,Male,29,Diploma,16,49,9,76,36,5.0,4,29,Urban,Data Analyst,139625,0 +74865,Female,54,Masters,18,95,24,57,63,9.0,5,17,Semi-Urban,ML Engineer,90106,0 +74866,Male,36,Masters,14,35,9,52,97,7.0,4,62,Urban,Manager,125757,0 +74867,Female,49,Diploma,18,22,49,30,75,8.0,7,7,Semi-Urban,ML Engineer,60277,0 +74868,Male,44,Diploma,0,92,96,17,44,9.0,2,9,Rural,Manager,102673,0 +74869,Male,34,Masters,18,47,42,48,11,4.0,0,44,Urban,Manager,81143,0 +74870,Female,39,PhD,5,2,82,32,69,9.0,1,78,Semi-Urban,Manager,121797,0 +74871,Female,50,Diploma,15,52,28,1,64,8.0,4,24,Urban,ML Engineer,87010,0 +74872,Female,52,PhD,3,88,54,39,3,4.0,0,68,Urban,Data Analyst,64767,1 +74873,Male,46,High School,11,42,37,46,36,9.0,7,27,Rural,ML Engineer,146793,0 +74874,Male,52,High School,17,93,50,68,26,0.0,0,32,Rural,Software Engineer,87495,1 +74875,Male,24,Diploma,10,80,50,64,55,5.0,5,40,Urban,Data Analyst,81947,0 +74876,Other,40,Bachelors,9,50,21,79,39,6.0,7,69,Semi-Urban,ML Engineer,115558,0 +74877,Female,47,Bachelors,2,27,64,88,74,6.0,6,92,Urban,HR Executive,48867,1 +74878,Male,33,Masters,15,30,0,52,98,5.0,4,20,Urban,Software Engineer,142034,0 +74879,Male,55,Diploma,4,32,85,57,68,2.0,3,67,Semi-Urban,Software Engineer,59074,1 +74880,Male,37,Diploma,2,84,49,14,22,6.0,5,0,Rural,Software Engineer,94471,0 +74881,Female,32,Diploma,1,38,0,89,51,5.0,2,95,Urban,HR Executive,95313,0 +74882,Female,46,Bachelors,11,25,30,58,81,7.0,2,39,Urban,Manager,105578,0 +74883,Male,54,Bachelors,17,3,80,6,21,8.0,3,50,Semi-Urban,Data Analyst,108194,0 +74884,Male,37,Bachelors,1,48,4,42,50,2.0,7,24,Semi-Urban,ML Engineer,98735,0 +74885,Male,45,Masters,17,12,37,67,94,6.0,0,94,Semi-Urban,Data Analyst,89919,0 +74886,Male,36,Bachelors,6,68,72,38,40,3.0,5,97,Semi-Urban,HR Executive,34004,1 +74887,Male,25,Bachelors,5,86,85,30,78,9.0,3,29,Rural,HR Executive,49272,0 +74888,Male,54,Bachelors,18,10,48,13,61,0.0,4,27,Urban,Software Engineer,29324,0 +74889,Male,32,High School,13,46,0,16,71,3.0,7,41,Urban,Data Analyst,58983,0 +74890,Female,53,Bachelors,15,61,91,85,9,1.0,4,10,Semi-Urban,Software Engineer,39612,1 +74891,Male,40,Diploma,14,65,93,44,58,4.0,7,2,Rural,ML Engineer,22859,0 +74892,Other,52,Masters,7,84,39,55,44,4.0,7,55,Urban,Software Engineer,46346,0 +74893,Male,37,Diploma,3,68,11,26,3,7.0,6,6,Urban,ML Engineer,137731,0 +74894,Male,56,Diploma,9,25,20,67,28,4.0,5,87,Urban,ML Engineer,61520,0 +74895,Male,59,Bachelors,1,84,31,38,94,3.0,0,6,Urban,Software Engineer,80587,0 +74896,Male,56,Bachelors,2,31,34,3,32,1.0,5,37,Semi-Urban,Manager,99712,0 +74897,Male,32,Diploma,2,42,19,87,98,4.0,2,6,Urban,Software Engineer,37237,0 +74898,Female,25,Diploma,8,43,7,66,38,2.0,4,38,Rural,ML Engineer,67728,0 +74899,Female,21,Masters,3,36,98,94,22,2.0,7,14,Urban,Software Engineer,130217,1 +74900,Male,22,Bachelors,0,31,19,29,75,7.0,5,4,Rural,Manager,114073,0 +74901,Male,27,Bachelors,10,29,69,30,88,9.0,6,4,Urban,HR Executive,71490,0 +74902,Female,45,Masters,1,53,92,30,12,4.0,6,13,Semi-Urban,Software Engineer,46538,0 +74903,Male,53,Diploma,10,80,30,43,52,3.0,1,44,Urban,HR Executive,63987,0 +74904,Male,31,Bachelors,19,10,86,65,4,3.0,5,34,Rural,Manager,34515,0 +74905,Male,25,Bachelors,8,63,83,50,57,0.0,5,49,Rural,Manager,48702,1 +74906,Male,50,High School,3,76,93,42,15,6.0,5,95,Rural,HR Executive,147450,1 +74907,Male,45,PhD,0,45,84,71,29,7.0,4,20,Semi-Urban,Manager,33318,0 +74908,Male,33,PhD,6,29,66,67,62,5.0,1,54,Semi-Urban,HR Executive,80249,0 +74909,Male,57,Bachelors,6,11,27,50,19,7.0,6,52,Rural,Manager,102420,0 +74910,Male,54,Diploma,1,25,1,63,57,2.0,1,52,Urban,HR Executive,102764,0 +74911,Male,36,Masters,12,31,30,9,12,6.0,6,93,Urban,ML Engineer,136787,0 +74912,Male,24,Bachelors,8,86,8,82,2,9.0,4,42,Urban,Manager,111870,0 +74913,Female,50,High School,15,55,43,86,34,7.0,4,70,Semi-Urban,ML Engineer,91935,1 +74914,Female,33,Bachelors,10,76,86,50,36,4.0,5,94,Semi-Urban,HR Executive,24250,1 +74915,Other,43,Diploma,0,40,16,76,1,9.0,6,58,Semi-Urban,ML Engineer,85227,0 +74916,Male,52,Diploma,18,3,50,71,82,3.0,6,25,Rural,Data Analyst,21226,0 +74917,Female,54,Bachelors,14,57,8,94,23,4.0,1,50,Semi-Urban,Data Analyst,60496,0 +74918,Female,44,Diploma,11,10,74,42,72,7.0,3,46,Urban,Data Analyst,56797,0 +74919,Female,43,Bachelors,14,27,71,39,85,4.0,2,40,Urban,Manager,119489,0 +74920,Female,41,PhD,5,40,46,35,86,8.0,1,83,Urban,ML Engineer,114059,0 +74921,Male,40,Diploma,17,32,97,69,22,9.0,6,28,Rural,ML Engineer,30349,0 +74922,Male,31,Diploma,15,16,43,0,61,5.0,1,35,Semi-Urban,ML Engineer,71693,0 +74923,Male,52,Bachelors,5,45,23,67,95,0.0,1,52,Semi-Urban,Data Analyst,91405,0 +74924,Female,47,Diploma,1,26,62,56,80,8.0,7,35,Urban,ML Engineer,74852,0 +74925,Male,57,Masters,19,96,46,77,46,1.0,4,96,Urban,ML Engineer,61396,1 +74926,Female,48,Bachelors,8,97,77,53,55,7.0,3,97,Urban,Manager,98148,1 +74927,Female,49,Diploma,17,49,94,5,11,2.0,6,13,Urban,Software Engineer,73982,0 +74928,Male,47,Diploma,12,79,42,62,50,5.0,7,29,Rural,Manager,22398,0 +74929,Female,34,High School,14,66,86,10,67,0.0,4,87,Semi-Urban,Software Engineer,149919,1 +74930,Other,51,High School,14,14,48,93,86,9.0,2,28,Semi-Urban,ML Engineer,39242,0 +74931,Female,21,Bachelors,9,29,7,65,40,4.0,5,50,Urban,Manager,63143,0 +74932,Female,37,High School,18,37,23,64,48,9.0,6,31,Urban,Data Analyst,92461,0 +74933,Male,59,Diploma,11,94,25,85,0,8.0,2,45,Semi-Urban,ML Engineer,98395,1 +74934,Male,39,Bachelors,7,52,93,47,73,0.0,1,67,Urban,HR Executive,110800,1 +74935,Male,41,Bachelors,9,50,13,22,90,4.0,6,54,Rural,Manager,110428,0 +74936,Female,32,Masters,7,27,42,82,95,0.0,2,28,Urban,Manager,109841,0 +74937,Female,58,Diploma,4,63,45,78,50,1.0,1,12,Semi-Urban,HR Executive,88675,0 +74938,Male,54,High School,6,89,48,35,75,7.0,0,69,Urban,HR Executive,62330,1 +74939,Other,47,Bachelors,6,78,39,34,40,1.0,3,67,Urban,Software Engineer,97402,0 +74940,Male,39,High School,3,6,2,19,84,7.0,7,85,Urban,Manager,105880,0 +74941,Female,34,Bachelors,15,61,98,91,85,3.0,4,39,Urban,Software Engineer,75430,1 +74942,Female,48,Bachelors,9,10,2,21,42,2.0,0,24,Urban,Software Engineer,103633,0 +74943,Male,22,Masters,13,9,67,50,97,2.0,5,87,Urban,Manager,26803,0 +74944,Male,58,Masters,12,31,64,38,33,1.0,1,27,Rural,HR Executive,39967,0 +74945,Male,59,High School,1,30,40,89,47,4.0,1,25,Semi-Urban,HR Executive,21610,0 +74946,Female,34,Bachelors,10,61,22,75,62,7.0,3,40,Urban,HR Executive,86054,0 +74947,Male,39,Bachelors,8,93,81,86,68,6.0,4,17,Rural,ML Engineer,94853,1 +74948,Male,23,Diploma,4,67,57,73,11,1.0,0,43,Semi-Urban,ML Engineer,124275,1 +74949,Other,42,Diploma,17,30,62,94,84,3.0,5,51,Semi-Urban,Manager,66459,0 +74950,Male,30,High School,0,72,55,54,37,9.0,0,73,Urban,HR Executive,43241,1 +74951,Female,37,PhD,18,13,77,51,92,8.0,6,85,Rural,Software Engineer,47990,0 +74952,Male,24,Masters,10,24,64,30,66,4.0,4,72,Urban,HR Executive,51009,0 +74953,Male,53,Diploma,18,21,59,81,2,1.0,1,88,Semi-Urban,Data Analyst,118675,1 +74954,Female,50,Masters,11,28,56,1,51,8.0,0,81,Urban,HR Executive,98267,0 +74955,Male,53,High School,19,3,36,24,35,2.0,5,47,Urban,Software Engineer,91919,0 +74956,Male,52,Bachelors,9,68,42,25,96,9.0,2,20,Rural,HR Executive,77570,0 +74957,Male,53,Masters,19,73,49,15,3,7.0,3,72,Urban,Data Analyst,149814,0 +74958,Male,55,High School,2,26,52,57,50,6.0,3,52,Urban,HR Executive,88210,0 +74959,Female,45,PhD,4,4,59,15,71,0.0,4,40,Semi-Urban,Manager,60341,0 +74960,Male,45,Masters,18,51,98,25,99,0.0,7,84,Rural,ML Engineer,95124,1 +74961,Male,40,Masters,1,6,13,55,83,7.0,1,18,Rural,Manager,67163,0 +74962,Female,36,Bachelors,16,56,46,27,35,0.0,1,49,Semi-Urban,Data Analyst,57778,0 +74963,Male,35,Diploma,9,77,69,65,13,1.0,2,45,Rural,HR Executive,56234,1 +74964,Female,57,High School,14,97,50,90,87,2.0,0,28,Urban,ML Engineer,61665,1 +74965,Female,42,Bachelors,10,24,26,95,18,5.0,6,68,Urban,HR Executive,55380,0 +74966,Male,43,Bachelors,14,86,56,15,89,5.0,0,54,Urban,Software Engineer,88337,0 +74967,Male,23,Bachelors,11,87,72,97,50,6.0,5,94,Rural,Software Engineer,95856,1 +74968,Female,30,Diploma,12,93,72,60,48,2.0,0,74,Urban,Data Analyst,64141,1 +74969,Male,51,Diploma,5,68,50,91,61,6.0,5,36,Urban,ML Engineer,67364,1 +74970,Male,45,High School,8,64,99,51,58,8.0,5,0,Urban,ML Engineer,141804,0 +74971,Female,41,Bachelors,8,6,36,44,91,9.0,3,76,Urban,ML Engineer,116085,0 +74972,Female,53,Bachelors,7,84,87,76,26,9.0,7,28,Urban,ML Engineer,135688,1 +74973,Female,31,Diploma,13,98,71,24,89,0.0,7,97,Urban,ML Engineer,41410,1 +74974,Male,27,Diploma,6,0,87,85,67,3.0,1,28,Urban,HR Executive,82450,0 +74975,Male,42,Bachelors,16,83,17,81,35,8.0,0,29,Urban,Manager,143617,0 +74976,Female,29,Bachelors,3,49,45,20,56,0.0,7,42,Rural,Manager,28886,0 +74977,Female,24,High School,10,25,74,91,73,7.0,3,54,Semi-Urban,Manager,52309,1 +74978,Female,25,High School,11,31,87,99,50,9.0,1,26,Rural,HR Executive,39138,1 +74979,Male,38,Bachelors,4,29,47,47,3,0.0,2,52,Urban,HR Executive,148214,0 +74980,Male,21,High School,3,99,47,28,16,7.0,0,15,Semi-Urban,ML Engineer,110350,0 +74981,Male,40,Masters,10,48,88,45,55,3.0,3,0,Semi-Urban,Data Analyst,112138,0 +74982,Female,30,Diploma,10,81,78,57,28,3.0,7,50,Urban,Software Engineer,114720,1 +74983,Female,50,Masters,3,56,19,32,16,1.0,4,64,Urban,HR Executive,94202,0 +74984,Female,24,High School,14,60,55,37,35,6.0,2,52,Rural,Manager,46342,0 +74985,Male,49,Diploma,8,72,65,11,53,8.0,4,31,Urban,Data Analyst,24073,0 +74986,Male,31,High School,8,49,26,33,99,2.0,5,40,Urban,Data Analyst,38147,0 +74987,Female,53,Diploma,4,66,75,85,3,9.0,4,20,Semi-Urban,HR Executive,49508,1 +74988,Female,58,High School,3,50,63,31,86,2.0,5,56,Semi-Urban,Software Engineer,25719,0 +74989,Male,55,Bachelors,10,25,30,26,8,4.0,5,16,Semi-Urban,ML Engineer,61890,0 +74990,Male,59,Bachelors,18,60,82,57,92,3.0,2,54,Urban,HR Executive,44310,1 +74991,Male,31,Diploma,8,75,71,10,54,2.0,7,55,Urban,Software Engineer,72524,0 +74992,Male,40,Diploma,3,31,55,12,21,0.0,0,13,Rural,HR Executive,112172,0 +74993,Female,44,Bachelors,19,78,46,40,46,4.0,0,71,Rural,HR Executive,77843,0 +74994,Female,48,Masters,6,77,60,62,66,6.0,7,54,Rural,HR Executive,33994,1 +74995,Female,25,Bachelors,2,50,10,26,80,4.0,0,14,Urban,HR Executive,102180,0 +74996,Male,30,Diploma,19,54,65,55,7,6.0,6,21,Urban,HR Executive,43941,0 +74997,Female,54,PhD,17,89,92,1,34,1.0,3,2,Rural,HR Executive,28405,0 +74998,Other,29,Bachelors,10,77,28,6,6,7.0,6,5,Urban,ML Engineer,52490,0 +74999,Other,39,High School,6,83,11,13,13,0.0,3,9,Urban,Data Analyst,53654,0 +75000,Male,33,Diploma,0,96,77,37,25,4.0,0,31,Semi-Urban,HR Executive,108387,1 +75001,Male,30,Diploma,16,42,10,40,79,6.0,2,79,Urban,HR Executive,25714,0 +75002,Other,32,Diploma,19,75,89,99,89,5.0,5,96,Urban,Data Analyst,75856,1 +75003,Male,38,Diploma,8,61,67,19,57,1.0,2,83,Urban,ML Engineer,118775,0 +75004,Female,34,Bachelors,14,42,16,36,27,8.0,2,49,Urban,Data Analyst,23813,0 +75005,Female,55,Bachelors,13,39,17,2,76,0.0,3,6,Urban,Manager,58007,0 +75006,Male,35,PhD,7,29,45,98,15,9.0,3,10,Urban,Data Analyst,85654,0 +75007,Male,58,Bachelors,13,28,40,12,59,8.0,2,20,Urban,ML Engineer,66867,0 +75008,Male,22,Diploma,11,74,92,22,27,4.0,1,51,Urban,HR Executive,78057,1 +75009,Female,45,Bachelors,2,54,14,35,95,6.0,0,18,Rural,Software Engineer,52344,0 +75010,Female,53,High School,9,66,60,54,71,9.0,7,41,Urban,Manager,104376,0 +75011,Male,44,Bachelors,13,68,75,10,48,7.0,4,77,Rural,Software Engineer,64139,0 +75012,Male,40,High School,12,58,63,70,92,7.0,0,27,Urban,HR Executive,41881,0 +75013,Male,40,Bachelors,18,49,85,70,2,8.0,3,14,Urban,ML Engineer,21470,0 +75014,Male,24,Masters,3,8,41,6,47,1.0,5,39,Urban,Data Analyst,57730,0 +75015,Male,38,Masters,3,41,19,18,51,1.0,4,60,Urban,Manager,84402,0 +75016,Male,59,Bachelors,0,15,34,91,48,9.0,3,13,Semi-Urban,Manager,137700,0 +75017,Male,58,High School,13,52,2,13,30,5.0,2,91,Urban,ML Engineer,51438,0 +75018,Female,40,Bachelors,16,89,94,51,50,7.0,3,87,Urban,HR Executive,72125,1 +75019,Male,32,Bachelors,4,20,12,62,2,6.0,4,36,Urban,ML Engineer,39430,0 +75020,Female,33,Bachelors,19,66,65,85,17,0.0,2,97,Rural,Manager,79729,1 +75021,Male,28,High School,9,53,67,68,59,2.0,2,28,Semi-Urban,HR Executive,70677,0 +75022,Male,30,Masters,9,78,64,55,85,9.0,7,93,Urban,Manager,122185,1 +75023,Male,42,Diploma,9,45,72,80,58,3.0,2,59,Urban,ML Engineer,43590,1 +75024,Female,21,Bachelors,10,88,38,99,81,5.0,4,75,Rural,Manager,34255,1 +75025,Male,23,High School,8,68,29,62,87,2.0,5,17,Rural,ML Engineer,92767,0 +75026,Female,56,Bachelors,5,91,67,9,22,3.0,0,94,Rural,ML Engineer,61796,1 +75027,Male,49,Bachelors,7,79,73,3,54,0.0,4,52,Urban,Data Analyst,54917,0 +75028,Female,33,Masters,15,55,24,15,1,6.0,2,19,Rural,HR Executive,36361,0 +75029,Male,54,Diploma,8,4,7,2,7,0.0,4,53,Urban,Software Engineer,125777,0 +75030,Female,28,Bachelors,19,98,96,20,0,8.0,7,12,Urban,ML Engineer,149708,0 +75031,Female,27,Masters,13,17,32,27,65,1.0,3,85,Urban,Data Analyst,46062,0 +75032,Female,47,Diploma,5,49,93,22,9,7.0,4,28,Urban,Manager,90917,0 +75033,Female,28,Diploma,18,51,48,20,39,6.0,0,67,Rural,Data Analyst,70689,0 +75034,Male,23,High School,17,99,64,75,29,9.0,0,7,Urban,ML Engineer,49110,1 +75035,Female,59,Diploma,12,87,49,57,77,9.0,2,42,Urban,Manager,63326,0 +75036,Male,43,Masters,4,12,86,4,83,1.0,3,4,Rural,HR Executive,58071,0 +75037,Male,52,High School,12,4,76,25,45,9.0,4,44,Urban,HR Executive,34140,0 +75038,Male,58,Bachelors,19,89,83,20,12,0.0,0,58,Urban,Data Analyst,83111,1 +75039,Female,26,Masters,5,53,54,63,60,5.0,6,55,Semi-Urban,ML Engineer,73356,0 +75040,Male,54,High School,3,65,40,39,77,6.0,6,85,Semi-Urban,Data Analyst,119386,0 +75041,Male,38,Masters,3,77,30,61,58,4.0,4,89,Rural,Data Analyst,128753,1 +75042,Male,51,Diploma,17,39,49,36,13,2.0,0,91,Semi-Urban,Data Analyst,95619,0 +75043,Other,45,Diploma,14,25,5,58,85,2.0,1,53,Urban,ML Engineer,89281,0 +75044,Other,36,Masters,14,54,29,38,87,6.0,6,39,Rural,ML Engineer,89642,0 +75045,Male,45,High School,8,50,37,49,67,1.0,6,22,Semi-Urban,Software Engineer,146531,0 +75046,Male,48,Masters,3,79,0,14,46,4.0,4,19,Urban,Data Analyst,22645,0 +75047,Female,40,Masters,0,28,23,0,66,0.0,3,84,Urban,ML Engineer,122509,0 +75048,Male,31,High School,13,91,85,63,0,4.0,3,74,Rural,Software Engineer,94848,1 +75049,Male,28,Bachelors,10,43,93,70,86,1.0,1,56,Urban,HR Executive,113816,1 +75050,Male,21,Bachelors,14,30,51,65,25,4.0,1,91,Urban,HR Executive,89971,1 +75051,Other,51,Bachelors,8,9,99,97,87,4.0,3,84,Semi-Urban,Manager,49115,1 +75052,Male,43,High School,19,74,7,54,90,0.0,7,56,Urban,Data Analyst,141939,0 +75053,Male,37,Masters,2,8,91,82,42,2.0,7,11,Urban,Software Engineer,58952,0 +75054,Male,40,Bachelors,8,86,82,21,84,1.0,3,89,Urban,Software Engineer,101437,1 +75055,Female,32,Bachelors,14,10,24,98,1,9.0,3,65,Urban,ML Engineer,78793,0 +75056,Other,41,High School,14,6,53,24,77,1.0,6,97,Semi-Urban,ML Engineer,129381,0 +75057,Male,39,Diploma,19,87,94,9,1,6.0,6,46,Semi-Urban,HR Executive,109172,1 +75058,Female,45,Bachelors,14,84,3,35,98,5.0,2,28,Urban,Data Analyst,117186,0 +75059,Male,31,Diploma,7,17,92,57,80,2.0,5,76,Urban,ML Engineer,45361,1 +75060,Male,33,Diploma,15,77,84,44,38,5.0,5,13,Semi-Urban,HR Executive,129164,0 +75061,Male,23,Bachelors,19,95,41,87,75,4.0,0,46,Urban,Software Engineer,55189,1 +75062,Other,27,Masters,10,44,56,88,23,9.0,2,25,Semi-Urban,Data Analyst,128811,0 +75063,Male,22,Masters,9,65,27,82,90,2.0,6,69,Urban,Manager,130245,1 +75064,Male,53,PhD,5,50,70,24,96,6.0,7,52,Semi-Urban,Manager,111146,0 +75065,Female,41,Bachelors,0,4,43,31,83,0.0,3,28,Rural,Manager,127201,0 +75066,Female,50,High School,5,90,49,58,23,5.0,0,31,Urban,HR Executive,21673,0 +75067,Male,54,Diploma,17,59,53,88,8,7.0,6,6,Urban,Manager,96722,0 +75068,Male,23,Diploma,10,3,77,77,13,0.0,2,32,Rural,Manager,93965,0 +75069,Female,45,Bachelors,3,18,93,62,1,6.0,7,92,Rural,HR Executive,83250,1 +75070,Male,56,Masters,1,19,96,16,48,5.0,4,49,Rural,Software Engineer,126614,0 +75071,Male,44,Masters,8,92,63,21,83,9.0,1,95,Rural,Software Engineer,56616,1 +75072,Male,45,Bachelors,2,62,0,1,60,7.0,6,19,Semi-Urban,HR Executive,60965,0 +75073,Male,25,Bachelors,14,77,36,54,99,7.0,6,78,Semi-Urban,HR Executive,125815,1 +75074,Male,42,Diploma,14,76,65,33,85,0.0,3,38,Semi-Urban,HR Executive,39083,0 +75075,Female,59,Diploma,2,48,60,7,82,0.0,6,62,Urban,HR Executive,67558,0 +75076,Male,49,Bachelors,13,37,38,44,16,2.0,0,64,Semi-Urban,Manager,32355,0 +75077,Female,55,High School,13,35,18,22,58,9.0,6,33,Urban,Software Engineer,49749,0 +75078,Other,56,High School,2,14,2,86,3,5.0,0,9,Urban,Manager,24377,0 +75079,Male,47,Masters,14,21,8,90,32,5.0,2,11,Semi-Urban,Data Analyst,32984,0 +75080,Male,29,Masters,4,56,0,44,59,9.0,1,67,Rural,Manager,100218,0 +75081,Male,38,Diploma,1,69,88,34,24,8.0,7,40,Urban,ML Engineer,47229,0 +75082,Male,56,Bachelors,5,80,30,34,46,3.0,1,12,Urban,Manager,124873,0 +75083,Male,26,Masters,11,30,4,53,31,1.0,2,22,Urban,HR Executive,120800,0 +75084,Male,37,Bachelors,13,37,81,54,33,6.0,4,75,Urban,Data Analyst,113403,1 +75085,Male,25,Masters,9,40,77,93,49,0.0,7,75,Semi-Urban,Software Engineer,77805,1 +75086,Male,31,Masters,18,70,21,16,46,3.0,6,52,Rural,HR Executive,31956,0 +75087,Female,50,Bachelors,13,77,36,42,90,0.0,2,5,Urban,Manager,132372,0 +75088,Male,33,Bachelors,11,89,77,76,73,5.0,6,34,Urban,ML Engineer,89534,1 +75089,Male,24,Bachelors,18,56,57,58,37,6.0,3,48,Semi-Urban,ML Engineer,145386,0 +75090,Male,35,Diploma,19,29,71,36,45,3.0,6,3,Urban,Software Engineer,80878,0 +75091,Male,21,Bachelors,8,10,56,2,30,3.0,6,70,Urban,ML Engineer,41858,0 +75092,Female,55,Masters,2,63,50,33,85,0.0,6,50,Urban,HR Executive,127701,0 +75093,Male,55,Bachelors,6,71,15,98,82,4.0,0,30,Urban,HR Executive,43169,0 +75094,Male,58,Bachelors,4,32,71,31,45,7.0,2,38,Semi-Urban,Manager,25555,0 +75095,Other,58,Diploma,13,82,70,53,1,7.0,4,79,Urban,HR Executive,62887,1 +75096,Male,52,High School,19,73,23,25,77,8.0,3,73,Rural,HR Executive,66363,0 +75097,Male,37,Bachelors,18,52,11,58,77,3.0,6,16,Urban,HR Executive,22205,0 +75098,Male,57,PhD,3,38,0,86,9,8.0,3,15,Urban,Data Analyst,144322,0 +75099,Male,41,PhD,10,21,15,54,17,4.0,0,37,Rural,Data Analyst,80546,0 +75100,Other,35,High School,1,68,89,16,6,7.0,0,8,Urban,ML Engineer,101587,0 +75101,Male,41,Diploma,15,81,60,24,46,9.0,1,56,Semi-Urban,Data Analyst,57005,0 +75102,Female,37,Masters,12,34,50,58,74,7.0,3,47,Semi-Urban,Software Engineer,111830,0 +75103,Male,35,High School,7,25,58,60,56,3.0,7,2,Urban,ML Engineer,51777,0 +75104,Male,50,Masters,14,45,5,10,52,0.0,7,5,Urban,Manager,113887,0 +75105,Female,59,Masters,19,66,51,82,96,9.0,2,1,Semi-Urban,Software Engineer,84910,0 +75106,Male,49,Masters,14,50,44,27,9,4.0,5,97,Rural,Data Analyst,79802,0 +75107,Male,46,High School,10,2,87,14,11,7.0,4,51,Semi-Urban,ML Engineer,74638,0 +75108,Female,31,High School,9,7,71,99,2,7.0,5,50,Urban,HR Executive,51034,0 +75109,Male,27,Diploma,15,33,61,75,32,4.0,0,14,Urban,Software Engineer,62825,0 +75110,Male,50,Bachelors,5,17,76,8,42,7.0,5,81,Semi-Urban,Data Analyst,122448,0 +75111,Male,52,Diploma,16,70,37,0,28,2.0,7,69,Urban,Data Analyst,61611,0 +75112,Male,56,Masters,7,85,24,82,85,3.0,1,75,Rural,HR Executive,139968,1 +75113,Female,24,Bachelors,3,9,96,12,11,6.0,2,55,Semi-Urban,ML Engineer,140860,0 +75114,Female,26,Bachelors,9,78,32,64,79,8.0,5,71,Urban,Data Analyst,51218,1 +75115,Other,27,Diploma,3,9,88,4,49,1.0,0,6,Rural,Data Analyst,74172,0 +75116,Female,51,Bachelors,2,62,47,21,19,4.0,5,31,Urban,Software Engineer,53882,0 +75117,Male,50,Masters,15,85,53,42,36,3.0,0,87,Urban,HR Executive,136498,1 +75118,Female,32,Bachelors,12,86,62,66,21,3.0,4,72,Rural,Data Analyst,20274,1 +75119,Female,56,Bachelors,9,51,52,46,65,2.0,7,49,Urban,Data Analyst,61399,0 +75120,Male,25,High School,3,15,64,15,16,4.0,4,45,Semi-Urban,Manager,109607,0 +75121,Male,37,Diploma,13,38,59,15,81,6.0,2,84,Rural,Software Engineer,21832,0 +75122,Female,53,Masters,3,13,24,95,23,8.0,5,8,Semi-Urban,Manager,22521,0 +75123,Male,40,Bachelors,13,48,43,43,25,9.0,3,74,Urban,Manager,57491,0 +75124,Female,59,Bachelors,0,15,57,65,67,9.0,4,18,Urban,Data Analyst,146157,0 +75125,Male,49,Masters,12,4,15,0,92,8.0,7,50,Rural,HR Executive,42390,0 +75126,Female,28,Masters,3,13,55,8,35,7.0,1,9,Urban,Software Engineer,50009,0 +75127,Male,26,Masters,0,70,42,57,12,6.0,4,19,Urban,Data Analyst,63298,0 +75128,Female,37,Bachelors,7,73,58,69,72,2.0,1,46,Semi-Urban,Data Analyst,132427,1 +75129,Female,58,Masters,7,24,58,98,41,9.0,2,98,Urban,Software Engineer,42543,1 +75130,Male,34,Bachelors,3,83,68,58,54,9.0,6,38,Rural,Manager,116931,1 +75131,Male,47,High School,7,5,39,31,12,0.0,5,60,Urban,Software Engineer,98004,0 +75132,Male,48,Diploma,1,32,0,16,83,5.0,7,64,Semi-Urban,ML Engineer,94006,0 +75133,Male,26,Bachelors,12,58,59,15,7,3.0,5,40,Rural,HR Executive,91808,0 +75134,Male,26,Diploma,12,18,59,40,46,0.0,3,85,Urban,HR Executive,33155,0 +75135,Male,44,High School,5,93,63,38,48,6.0,3,71,Urban,Manager,124350,1 +75136,Female,27,High School,3,94,7,33,31,8.0,6,50,Rural,Software Engineer,23586,0 +75137,Male,23,Bachelors,8,59,95,89,45,3.0,6,54,Urban,Software Engineer,35495,1 +75138,Male,21,High School,6,76,10,74,64,7.0,5,19,Urban,HR Executive,127517,0 +75139,Female,29,Masters,0,96,49,30,50,0.0,3,12,Urban,Data Analyst,110273,0 +75140,Female,24,High School,4,75,19,82,52,4.0,0,99,Urban,Software Engineer,100130,1 +75141,Male,50,Masters,18,3,80,14,7,4.0,1,76,Urban,Manager,46396,0 +75142,Male,34,Bachelors,2,6,43,42,44,2.0,2,48,Urban,Manager,121093,0 +75143,Male,35,Diploma,10,60,18,74,72,1.0,3,77,Semi-Urban,ML Engineer,63758,0 +75144,Female,42,Diploma,2,60,36,84,54,4.0,1,58,Urban,Software Engineer,28260,0 +75145,Female,59,Bachelors,12,38,91,74,68,1.0,6,66,Urban,Manager,83032,1 +75146,Female,53,High School,6,87,10,53,53,4.0,0,21,Rural,Data Analyst,36712,0 +75147,Female,34,Masters,9,71,33,17,82,8.0,5,77,Rural,Data Analyst,149760,0 +75148,Other,44,Masters,14,32,56,39,33,6.0,3,10,Urban,Data Analyst,122377,0 +75149,Male,42,Bachelors,5,76,99,82,68,3.0,1,67,Urban,Software Engineer,40967,1 +75150,Male,58,Bachelors,4,88,62,55,30,7.0,4,70,Rural,HR Executive,132128,1 +75151,Female,56,Masters,6,63,97,7,77,4.0,7,94,Urban,Data Analyst,138166,1 +75152,Male,42,Bachelors,17,28,5,30,46,4.0,4,65,Rural,Software Engineer,25522,0 +75153,Male,36,Masters,9,71,98,80,17,4.0,2,70,Rural,ML Engineer,60500,1 +75154,Male,47,Masters,1,0,55,58,56,6.0,1,18,Urban,Software Engineer,121621,0 +75155,Male,58,High School,7,10,72,14,32,5.0,1,0,Urban,Software Engineer,124098,0 +75156,Male,46,Diploma,19,64,92,66,69,4.0,6,66,Urban,HR Executive,75703,1 +75157,Male,40,Masters,8,69,46,81,24,7.0,5,80,Urban,Software Engineer,135130,1 +75158,Female,39,Bachelors,11,28,6,86,80,2.0,0,82,Rural,HR Executive,103006,0 +75159,Female,30,Masters,15,75,13,4,18,1.0,5,93,Semi-Urban,Software Engineer,50276,0 +75160,Other,29,Bachelors,6,69,48,34,9,6.0,1,79,Semi-Urban,Data Analyst,48637,0 +75161,Male,46,Masters,9,9,85,14,35,4.0,4,83,Urban,ML Engineer,39833,0 +75162,Male,45,Masters,8,29,48,74,3,6.0,4,3,Rural,HR Executive,89608,0 +75163,Male,53,Bachelors,2,90,0,45,32,5.0,0,63,Semi-Urban,HR Executive,109814,0 +75164,Male,49,Diploma,0,8,94,80,20,6.0,6,68,Urban,HR Executive,115826,1 +75165,Male,56,Masters,14,67,26,33,68,0.0,5,81,Semi-Urban,Manager,122425,0 +75166,Male,50,Diploma,13,8,10,63,68,0.0,3,28,Urban,Manager,94141,0 +75167,Male,54,Bachelors,19,8,47,85,7,6.0,4,67,Rural,ML Engineer,125759,0 +75168,Female,51,High School,16,81,64,60,99,9.0,3,36,Urban,ML Engineer,93284,1 +75169,Male,25,Bachelors,16,74,20,12,41,8.0,0,76,Urban,ML Engineer,50442,0 +75170,Male,23,High School,4,25,51,36,85,9.0,5,43,Urban,HR Executive,47624,0 +75171,Male,59,Diploma,5,44,59,57,64,5.0,2,99,Urban,Data Analyst,103293,1 +75172,Male,27,High School,8,19,60,71,47,0.0,1,70,Urban,ML Engineer,81776,0 +75173,Male,36,Masters,9,93,80,69,57,5.0,2,40,Rural,HR Executive,96311,1 +75174,Male,53,Bachelors,6,94,32,86,10,0.0,0,89,Urban,Manager,139803,1 +75175,Female,29,Diploma,8,15,31,66,27,1.0,1,59,Semi-Urban,Manager,134621,0 +75176,Other,48,High School,13,50,65,6,6,9.0,2,67,Urban,Data Analyst,42042,0 +75177,Male,24,Bachelors,19,94,45,53,64,6.0,5,92,Urban,Data Analyst,25997,1 +75178,Female,29,Bachelors,16,96,95,19,39,7.0,5,48,Urban,Software Engineer,22894,1 +75179,Male,23,Bachelors,4,71,49,60,58,5.0,2,95,Semi-Urban,Data Analyst,59816,1 +75180,Female,29,Bachelors,19,32,24,32,1,3.0,3,16,Urban,HR Executive,142944,0 +75181,Female,41,Diploma,18,34,28,70,9,1.0,5,83,Rural,HR Executive,30386,0 +75182,Female,59,Diploma,7,71,8,45,51,6.0,1,72,Urban,Manager,143939,0 +75183,Female,54,Bachelors,11,84,58,25,11,1.0,1,36,Urban,Manager,28952,0 +75184,Female,26,Diploma,4,11,32,27,81,4.0,6,62,Urban,ML Engineer,84621,0 +75185,Male,21,Masters,2,18,49,56,25,2.0,7,75,Semi-Urban,ML Engineer,31228,0 +75186,Male,44,Diploma,2,50,12,81,69,5.0,3,52,Urban,Manager,76481,0 +75187,Male,51,Bachelors,18,88,76,81,81,1.0,0,21,Semi-Urban,ML Engineer,50201,1 +75188,Male,26,Masters,12,71,85,23,46,4.0,2,56,Semi-Urban,Software Engineer,32919,1 +75189,Male,33,Diploma,15,46,35,43,9,8.0,0,25,Rural,Manager,55835,0 +75190,Male,29,Bachelors,7,29,91,28,48,3.0,3,0,Urban,ML Engineer,33618,0 +75191,Female,59,Masters,5,67,68,53,86,5.0,0,60,Urban,Manager,20612,1 +75192,Female,24,Bachelors,9,8,19,85,12,8.0,3,4,Semi-Urban,HR Executive,59276,0 +75193,Female,35,PhD,13,90,53,2,28,8.0,3,13,Rural,HR Executive,146525,0 +75194,Male,47,Masters,16,80,29,73,77,7.0,6,90,Urban,Manager,88753,1 +75195,Male,33,Bachelors,0,66,69,53,28,8.0,0,22,Urban,Data Analyst,57882,0 +75196,Female,54,Bachelors,7,16,65,88,90,4.0,1,52,Urban,Software Engineer,41318,0 +75197,Female,58,Bachelors,9,39,84,57,28,7.0,6,52,Urban,ML Engineer,66432,0 +75198,Male,44,Bachelors,10,54,67,58,95,5.0,7,27,Urban,HR Executive,20797,0 +75199,Female,25,Bachelors,16,23,67,82,10,7.0,1,16,Urban,Data Analyst,147559,0 +75200,Male,35,Bachelors,5,66,46,62,38,7.0,1,16,Rural,HR Executive,96705,0 +75201,Female,52,Diploma,15,18,61,49,45,7.0,1,94,Semi-Urban,Manager,74380,0 +75202,Male,41,Masters,1,83,10,84,43,4.0,6,15,Urban,ML Engineer,83560,0 +75203,Female,58,High School,1,42,14,41,4,6.0,5,72,Urban,Manager,58472,0 +75204,Female,25,Masters,17,77,75,88,48,7.0,1,97,Urban,Data Analyst,36397,1 +75205,Male,22,Diploma,0,4,71,1,16,2.0,7,34,Rural,Manager,114942,0 +75206,Male,42,Bachelors,11,65,63,85,63,7.0,1,10,Semi-Urban,Manager,28162,0 +75207,Female,42,Bachelors,8,99,13,4,8,9.0,4,18,Urban,Data Analyst,22249,0 +75208,Male,49,Diploma,11,2,0,97,37,1.0,5,20,Urban,Software Engineer,109249,0 +75209,Male,47,Bachelors,11,42,7,9,76,4.0,5,17,Semi-Urban,Data Analyst,61171,0 +75210,Male,49,Diploma,14,35,63,43,93,3.0,4,20,Rural,HR Executive,101757,0 +75211,Female,46,Bachelors,7,54,69,17,3,7.0,0,75,Urban,ML Engineer,74876,0 +75212,Male,49,Masters,4,79,13,19,46,7.0,5,49,Semi-Urban,HR Executive,63930,0 +75213,Female,25,Diploma,2,60,46,54,35,3.0,5,60,Urban,HR Executive,93616,0 +75214,Male,51,PhD,2,18,70,31,79,1.0,7,80,Rural,HR Executive,24664,0 +75215,Male,47,High School,13,1,25,88,92,9.0,1,2,Urban,HR Executive,52891,0 +75216,Male,22,Bachelors,0,15,19,40,70,0.0,5,58,Semi-Urban,Software Engineer,92713,0 +75217,Male,59,High School,10,98,24,60,9,2.0,5,76,Semi-Urban,Manager,83212,1 +75218,Male,59,Masters,13,87,65,10,38,8.0,6,63,Urban,Data Analyst,91669,0 +75219,Female,30,Bachelors,2,12,66,70,69,8.0,1,43,Semi-Urban,HR Executive,24212,0 +75220,Female,43,Bachelors,1,34,18,6,53,6.0,7,21,Urban,HR Executive,26607,0 +75221,Male,34,Bachelors,12,17,10,8,92,7.0,4,91,Semi-Urban,HR Executive,79879,0 +75222,Female,27,Diploma,18,18,81,51,81,4.0,5,58,Rural,ML Engineer,63163,0 +75223,Male,28,Diploma,2,53,65,94,72,4.0,0,6,Urban,Manager,134884,0 +75224,Female,43,Bachelors,14,36,88,2,35,9.0,3,93,Urban,ML Engineer,83908,0 +75225,Male,32,High School,2,93,89,88,34,8.0,6,96,Rural,Manager,63757,1 +75226,Male,53,High School,8,55,11,16,56,3.0,4,48,Urban,Data Analyst,111526,0 +75227,Female,29,Diploma,5,87,53,70,81,1.0,3,6,Urban,ML Engineer,101549,0 +75228,Male,56,High School,5,23,36,48,99,3.0,6,30,Urban,ML Engineer,68210,0 +75229,Female,43,Bachelors,11,7,71,85,58,5.0,2,46,Semi-Urban,Software Engineer,132925,0 +75230,Male,40,Bachelors,2,39,6,63,77,9.0,6,69,Urban,Software Engineer,76837,0 +75231,Female,50,PhD,19,13,29,94,20,4.0,0,20,Semi-Urban,Data Analyst,100259,0 +75232,Other,41,Diploma,14,85,20,87,17,7.0,4,99,Urban,Data Analyst,21847,1 +75233,Male,24,Bachelors,8,15,28,45,60,1.0,5,47,Rural,Data Analyst,67223,0 +75234,Female,53,High School,19,90,82,0,66,4.0,2,19,Rural,Software Engineer,45307,0 +75235,Male,39,Bachelors,14,40,34,35,46,3.0,7,61,Urban,ML Engineer,43970,0 +75236,Male,41,Diploma,1,21,23,55,56,0.0,0,41,Urban,Data Analyst,59232,0 +75237,Female,30,Bachelors,15,13,49,48,9,2.0,1,54,Semi-Urban,Software Engineer,120884,0 +75238,Male,24,Bachelors,14,77,7,11,87,5.0,7,8,Rural,HR Executive,80718,0 +75239,Male,45,Masters,13,78,73,76,31,3.0,6,47,Urban,Software Engineer,78534,1 +75240,Female,30,Bachelors,8,15,13,47,26,2.0,7,66,Urban,ML Engineer,76124,0 +75241,Male,33,Bachelors,6,5,96,90,70,0.0,5,57,Rural,Data Analyst,136691,1 +75242,Female,27,Bachelors,14,98,70,59,13,7.0,2,71,Urban,Data Analyst,64454,1 +75243,Female,49,High School,10,58,72,78,49,4.0,3,5,Rural,Manager,92746,0 +75244,Female,44,Bachelors,3,92,96,39,67,1.0,1,47,Rural,HR Executive,142693,1 +75245,Male,35,Masters,10,12,11,78,28,0.0,7,90,Urban,Data Analyst,34152,0 +75246,Male,32,PhD,7,7,44,57,91,8.0,5,41,Urban,ML Engineer,37725,0 +75247,Male,59,Masters,4,89,84,96,52,8.0,0,99,Urban,Data Analyst,95560,1 +75248,Male,52,Diploma,7,82,30,11,14,9.0,5,21,Rural,HR Executive,72779,0 +75249,Male,47,Masters,19,34,52,1,21,2.0,7,35,Semi-Urban,Data Analyst,33571,0 +75250,Male,21,Bachelors,17,22,44,5,84,4.0,7,25,Urban,Software Engineer,76781,0 +75251,Male,52,Diploma,18,79,35,53,32,0.0,3,90,Rural,Data Analyst,22053,1 +75252,Female,53,Bachelors,17,9,25,74,32,7.0,3,40,Urban,HR Executive,90934,0 +75253,Female,55,Bachelors,7,12,23,50,26,1.0,6,18,Urban,ML Engineer,98331,0 +75254,Other,52,Masters,5,8,74,84,65,1.0,2,33,Urban,ML Engineer,67542,0 +75255,Female,49,Bachelors,14,78,10,83,33,9.0,0,8,Urban,Manager,36128,0 +75256,Male,58,Masters,10,20,31,40,79,4.0,6,8,Urban,Software Engineer,21771,0 +75257,Male,52,Bachelors,0,38,89,77,3,1.0,7,5,Rural,Manager,107026,0 +75258,Male,42,Diploma,9,25,89,76,17,2.0,5,57,Urban,Data Analyst,129289,1 +75259,Male,27,Bachelors,11,86,8,75,47,7.0,0,34,Urban,Data Analyst,134672,0 +75260,Male,52,Bachelors,15,49,51,51,7,6.0,5,37,Rural,Manager,73514,0 +75261,Female,45,Bachelors,14,39,84,22,26,3.0,4,95,Urban,ML Engineer,82421,0 +75262,Male,26,Diploma,8,27,46,6,76,5.0,3,48,Urban,Data Analyst,139278,0 +75263,Male,21,Bachelors,5,77,89,52,21,7.0,7,95,Urban,Manager,40040,1 +75264,Female,25,Bachelors,8,69,87,20,54,5.0,1,1,Urban,ML Engineer,32453,0 +75265,Female,57,Bachelors,18,13,96,59,68,4.0,1,0,Rural,Manager,112130,0 +75266,Male,54,High School,8,51,5,59,46,9.0,7,62,Urban,HR Executive,87236,0 +75267,Male,21,Diploma,13,90,57,21,91,3.0,2,22,Urban,Software Engineer,72295,0 +75268,Female,34,High School,5,75,80,16,67,9.0,4,89,Urban,HR Executive,137674,1 +75269,Male,38,High School,9,29,77,99,16,7.0,2,32,Semi-Urban,ML Engineer,85700,1 +75270,Male,30,Diploma,15,55,80,84,69,8.0,4,24,Semi-Urban,ML Engineer,137712,1 +75271,Female,43,Bachelors,1,65,61,17,5,7.0,4,43,Rural,ML Engineer,54023,0 +75272,Male,22,Diploma,16,40,9,13,12,8.0,2,31,Semi-Urban,Manager,34327,0 +75273,Male,42,High School,7,68,88,91,49,3.0,1,2,Urban,HR Executive,61738,1 +75274,Male,46,Bachelors,9,5,54,71,24,8.0,5,6,Rural,HR Executive,116187,0 +75275,Male,43,Bachelors,17,17,40,31,7,4.0,7,7,Urban,Manager,35325,0 +75276,Male,40,High School,14,43,55,80,28,6.0,1,4,Semi-Urban,Software Engineer,106024,0 +75277,Female,51,High School,1,75,19,85,81,9.0,5,24,Semi-Urban,Data Analyst,42409,0 +75278,Female,35,Masters,2,8,58,76,51,9.0,4,68,Urban,Manager,85749,0 +75279,Female,55,Masters,18,6,60,91,69,6.0,5,99,Urban,Data Analyst,62182,1 +75280,Female,27,High School,16,30,11,91,73,1.0,6,28,Urban,Manager,61956,0 +75281,Male,48,Bachelors,6,90,68,1,22,5.0,4,17,Semi-Urban,Data Analyst,85803,0 +75282,Female,48,Diploma,8,22,17,18,6,2.0,4,44,Urban,HR Executive,88359,0 +75283,Female,43,Bachelors,16,47,10,50,53,4.0,7,73,Urban,ML Engineer,102871,0 +75284,Female,39,Masters,7,19,54,61,73,8.0,4,57,Rural,Data Analyst,110426,0 +75285,Female,29,High School,13,45,88,71,31,4.0,3,32,Rural,Data Analyst,114091,0 +75286,Male,24,Bachelors,19,62,29,19,29,5.0,4,91,Rural,Manager,23750,0 +75287,Male,27,Diploma,16,93,53,61,84,5.0,6,17,Urban,ML Engineer,48771,0 +75288,Male,43,Bachelors,7,50,62,33,8,1.0,0,26,Semi-Urban,Software Engineer,113528,0 +75289,Male,59,Bachelors,14,88,29,72,86,3.0,6,27,Urban,Software Engineer,86169,0 +75290,Male,24,High School,10,35,13,17,59,5.0,1,37,Urban,ML Engineer,28976,0 +75291,Male,27,Bachelors,12,29,77,43,51,3.0,4,94,Rural,HR Executive,110983,1 +75292,Other,30,High School,0,90,77,81,62,0.0,2,46,Semi-Urban,Data Analyst,92782,1 +75293,Male,21,Diploma,18,40,86,83,14,1.0,0,72,Urban,Manager,59695,1 +75294,Female,33,Bachelors,17,82,17,6,2,3.0,7,42,Urban,Manager,40884,0 +75295,Other,24,Bachelors,8,58,99,10,31,3.0,3,86,Rural,HR Executive,141860,1 +75296,Other,54,PhD,16,0,55,48,77,9.0,7,48,Semi-Urban,Manager,105213,0 +75297,Female,25,Bachelors,1,19,75,53,46,5.0,1,5,Urban,HR Executive,76028,0 +75298,Male,27,Diploma,18,8,48,1,5,6.0,0,81,Semi-Urban,ML Engineer,44571,0 +75299,Male,35,Masters,7,40,5,17,70,6.0,1,55,Semi-Urban,ML Engineer,72189,0 +75300,Female,36,Bachelors,5,17,45,84,65,7.0,2,70,Semi-Urban,Data Analyst,106830,0 +75301,Male,50,High School,7,63,67,96,21,2.0,6,79,Urban,HR Executive,119029,1 +75302,Male,49,Bachelors,1,83,0,49,30,5.0,1,50,Rural,ML Engineer,22336,0 +75303,Male,51,High School,2,30,74,66,4,0.0,1,58,Semi-Urban,Software Engineer,41541,0 +75304,Male,27,Bachelors,17,64,99,68,54,4.0,4,56,Semi-Urban,Data Analyst,143602,1 +75305,Female,26,High School,9,40,18,39,44,1.0,0,65,Urban,Data Analyst,148094,0 +75306,Male,42,Bachelors,4,92,14,8,71,3.0,3,93,Semi-Urban,Manager,70750,0 +75307,Male,25,Bachelors,9,78,19,79,47,3.0,7,78,Urban,HR Executive,34957,1 +75308,Male,35,Bachelors,7,17,50,17,51,1.0,5,64,Urban,ML Engineer,76914,0 +75309,Female,33,Masters,3,46,23,83,5,8.0,1,51,Urban,Software Engineer,57519,0 +75310,Female,25,Diploma,5,63,9,0,92,4.0,4,52,Urban,Software Engineer,102552,0 +75311,Male,42,Bachelors,18,3,17,42,23,1.0,3,9,Urban,HR Executive,117850,0 +75312,Male,54,Diploma,12,44,74,62,29,9.0,7,24,Urban,Data Analyst,84581,0 +75313,Male,29,Bachelors,9,31,22,35,40,0.0,1,31,Urban,Software Engineer,52913,0 +75314,Male,35,Diploma,3,20,58,17,50,5.0,7,43,Semi-Urban,HR Executive,136834,0 +75315,Female,26,Diploma,14,11,92,95,3,3.0,7,54,Urban,Software Engineer,63727,1 +75316,Male,27,Masters,6,81,38,73,69,8.0,0,73,Rural,Data Analyst,119220,1 +75317,Female,26,Bachelors,6,65,91,32,23,6.0,4,39,Semi-Urban,Software Engineer,75643,0 +75318,Male,33,Diploma,12,98,58,74,57,6.0,1,42,Rural,Manager,120018,1 +75319,Male,57,Masters,15,35,3,21,5,1.0,4,72,Semi-Urban,HR Executive,101811,0 +75320,Female,56,Bachelors,13,16,83,29,51,1.0,1,68,Urban,Manager,82595,0 +75321,Male,30,Bachelors,6,59,70,79,10,8.0,2,58,Semi-Urban,ML Engineer,57766,1 +75322,Female,24,Bachelors,12,26,24,94,30,9.0,0,67,Rural,Software Engineer,77051,0 +75323,Male,58,Diploma,14,81,53,98,92,6.0,2,3,Urban,HR Executive,129941,1 +75324,Female,48,Bachelors,9,13,88,17,29,1.0,3,35,Urban,ML Engineer,145058,0 +75325,Female,43,Bachelors,13,47,16,65,54,0.0,0,58,Urban,Software Engineer,66916,0 +75326,Female,38,Bachelors,14,95,58,85,89,6.0,0,46,Semi-Urban,ML Engineer,72198,1 +75327,Male,52,Masters,16,5,5,94,10,0.0,5,51,Semi-Urban,Data Analyst,80716,0 +75328,Female,55,Bachelors,6,73,73,5,83,1.0,0,9,Urban,Software Engineer,106964,0 +75329,Male,44,Diploma,1,54,15,29,95,9.0,7,77,Rural,Software Engineer,57670,0 +75330,Female,51,High School,5,8,35,21,82,7.0,0,73,Urban,Data Analyst,118218,0 +75331,Male,23,Bachelors,4,35,63,63,69,0.0,4,72,Semi-Urban,HR Executive,73317,0 +75332,Male,41,High School,7,35,55,27,95,2.0,5,47,Rural,Software Engineer,29465,0 +75333,Female,41,Diploma,13,67,20,99,92,4.0,4,53,Rural,Manager,146718,0 +75334,Female,35,Diploma,3,37,14,71,4,3.0,1,12,Urban,Data Analyst,134492,0 +75335,Female,27,Bachelors,1,95,96,0,10,7.0,7,22,Urban,Software Engineer,63486,0 +75336,Male,47,Bachelors,0,27,23,99,13,0.0,3,17,Urban,Data Analyst,120398,0 +75337,Male,32,Bachelors,2,97,98,88,3,4.0,4,44,Urban,Software Engineer,87340,1 +75338,Male,24,Masters,18,63,54,40,10,5.0,4,99,Urban,HR Executive,117728,1 +75339,Male,45,PhD,2,67,2,78,54,5.0,4,75,Rural,Software Engineer,38596,0 +75340,Male,52,Bachelors,1,89,47,73,88,7.0,1,22,Urban,Software Engineer,126561,0 +75341,Other,31,Diploma,10,52,57,11,0,6.0,3,78,Urban,Data Analyst,48450,0 +75342,Male,53,Masters,17,31,68,93,6,7.0,3,9,Urban,Software Engineer,57052,0 +75343,Male,58,PhD,9,86,12,22,75,8.0,5,25,Rural,Manager,97283,0 +75344,Female,58,High School,12,47,82,80,69,7.0,0,87,Urban,ML Engineer,78001,1 +75345,Female,23,Bachelors,5,46,10,39,25,2.0,3,81,Urban,HR Executive,100904,0 +75346,Female,26,High School,12,93,73,26,15,3.0,4,35,Semi-Urban,Manager,32106,0 +75347,Female,53,Masters,3,90,89,68,31,5.0,1,70,Urban,Data Analyst,57949,1 +75348,Male,21,High School,4,27,37,10,46,2.0,5,95,Rural,Manager,141791,0 +75349,Male,58,Bachelors,16,42,27,48,95,1.0,7,53,Semi-Urban,HR Executive,69063,0 +75350,Male,53,High School,4,60,55,73,95,6.0,7,42,Urban,HR Executive,55766,0 +75351,Male,42,Bachelors,9,96,61,58,66,4.0,4,51,Urban,ML Engineer,79878,1 +75352,Other,28,Bachelors,15,85,47,1,19,4.0,5,37,Urban,Data Analyst,24994,0 +75353,Female,28,Bachelors,6,71,52,38,9,2.0,7,3,Urban,ML Engineer,31213,0 +75354,Female,22,Diploma,1,7,57,13,7,5.0,3,13,Urban,Software Engineer,107894,0 +75355,Male,34,Masters,18,5,62,23,60,6.0,4,46,Urban,ML Engineer,37067,0 +75356,Male,25,Masters,7,66,58,64,55,9.0,3,16,Semi-Urban,Manager,51940,0 +75357,Male,34,Masters,5,42,53,96,53,2.0,3,90,Semi-Urban,Data Analyst,149377,1 +75358,Male,44,Bachelors,12,88,84,10,78,4.0,0,80,Semi-Urban,HR Executive,149932,1 +75359,Female,28,Bachelors,9,82,98,0,98,6.0,5,86,Urban,Data Analyst,62602,1 +75360,Male,28,High School,15,64,97,49,83,0.0,6,38,Rural,HR Executive,128164,1 +75361,Female,59,Bachelors,19,52,5,70,67,5.0,7,17,Urban,Software Engineer,70160,0 +75362,Male,45,Diploma,13,45,12,84,55,4.0,4,23,Rural,ML Engineer,129624,0 +75363,Female,28,Masters,13,10,84,61,77,4.0,5,72,Rural,HR Executive,61571,0 +75364,Male,57,Bachelors,16,43,75,45,4,0.0,6,19,Semi-Urban,Manager,92400,0 +75365,Male,32,PhD,16,22,98,87,42,4.0,1,18,Urban,Software Engineer,110804,0 +75366,Female,31,Bachelors,14,98,66,95,84,3.0,6,40,Rural,ML Engineer,130689,1 +75367,Male,21,Bachelors,19,22,47,20,31,9.0,6,3,Urban,HR Executive,136321,0 +75368,Female,39,Bachelors,19,97,42,21,78,5.0,2,54,Urban,Software Engineer,63628,0 +75369,Male,38,Bachelors,16,6,90,71,6,9.0,4,29,Rural,Data Analyst,62984,0 +75370,Female,22,Bachelors,4,92,8,59,86,9.0,2,97,Semi-Urban,Software Engineer,98658,1 +75371,Female,37,Masters,0,13,11,34,60,3.0,4,4,Rural,Software Engineer,71882,0 +75372,Female,22,High School,19,28,67,41,62,4.0,7,70,Urban,Data Analyst,42613,0 +75373,Male,38,Diploma,12,54,64,52,98,6.0,4,69,Urban,ML Engineer,77492,1 +75374,Male,59,PhD,10,98,66,91,28,0.0,1,31,Urban,Software Engineer,138776,1 +75375,Male,31,Bachelors,0,25,69,82,13,8.0,3,25,Semi-Urban,Software Engineer,55184,0 +75376,Male,33,Masters,7,65,57,72,28,2.0,0,87,Rural,Data Analyst,23366,1 +75377,Male,33,Diploma,3,54,94,79,17,4.0,0,45,Rural,HR Executive,89108,1 +75378,Male,48,Masters,19,64,54,36,42,0.0,0,22,Urban,HR Executive,52143,0 +75379,Male,36,Bachelors,0,44,4,62,63,4.0,4,97,Semi-Urban,Manager,30457,0 +75380,Male,46,Bachelors,2,28,45,66,44,3.0,2,32,Urban,Software Engineer,91641,0 +75381,Female,23,High School,11,51,79,1,46,4.0,0,7,Semi-Urban,HR Executive,96489,0 +75382,Male,30,Diploma,4,89,80,30,69,3.0,6,66,Semi-Urban,Data Analyst,103004,1 +75383,Other,37,Diploma,6,29,31,88,33,1.0,6,78,Urban,Software Engineer,101157,0 +75384,Male,23,Bachelors,4,65,56,63,22,2.0,6,32,Rural,Software Engineer,29858,0 +75385,Male,26,High School,14,55,39,39,40,6.0,2,40,Urban,Manager,39249,0 +75386,Male,39,Bachelors,0,3,44,31,72,4.0,5,64,Rural,ML Engineer,130891,0 +75387,Female,50,PhD,7,13,84,25,45,3.0,6,72,Semi-Urban,Software Engineer,148370,0 +75388,Male,35,Bachelors,9,69,74,62,29,4.0,2,49,Rural,ML Engineer,25560,1 +75389,Male,45,High School,9,53,67,12,72,6.0,1,4,Semi-Urban,Data Analyst,141647,0 +75390,Male,31,Bachelors,18,87,34,83,16,4.0,6,61,Rural,Data Analyst,39654,1 +75391,Female,46,Bachelors,6,5,70,21,65,0.0,0,73,Rural,Data Analyst,37656,0 +75392,Male,42,Bachelors,11,76,0,11,51,4.0,1,31,Urban,Manager,60667,0 +75393,Male,53,Diploma,8,19,38,69,61,7.0,5,18,Urban,Manager,96305,0 +75394,Female,35,High School,4,95,16,3,35,3.0,0,47,Rural,Software Engineer,91548,0 +75395,Male,55,High School,4,62,58,33,50,6.0,0,25,Urban,ML Engineer,89816,0 +75396,Male,45,Diploma,17,24,89,51,62,0.0,2,86,Urban,ML Engineer,138614,1 +75397,Male,42,Bachelors,2,70,6,89,89,5.0,2,71,Urban,HR Executive,98381,1 +75398,Male,30,Diploma,4,78,29,16,84,2.0,5,93,Urban,Data Analyst,132824,0 +75399,Male,36,Masters,11,3,53,8,84,1.0,4,20,Urban,Manager,20303,0 +75400,Male,45,Bachelors,7,77,52,12,79,3.0,5,22,Rural,Data Analyst,73196,0 +75401,Female,29,PhD,19,72,10,78,82,2.0,4,57,Urban,Manager,76872,0 +75402,Male,42,Bachelors,2,18,93,2,45,1.0,6,30,Rural,Manager,60655,0 +75403,Female,34,High School,16,7,22,73,54,0.0,5,30,Urban,Data Analyst,112566,0 +75404,Male,56,Bachelors,2,65,12,86,92,6.0,6,16,Rural,Manager,77710,0 +75405,Female,22,High School,16,65,66,96,33,6.0,0,51,Urban,Software Engineer,66339,1 +75406,Male,42,PhD,10,1,85,27,8,0.0,6,91,Rural,Data Analyst,59209,0 +75407,Female,41,PhD,10,35,97,19,26,5.0,1,80,Semi-Urban,Manager,136206,0 +75408,Female,27,Bachelors,1,11,73,7,18,3.0,4,58,Urban,Data Analyst,130848,0 +75409,Male,53,PhD,7,32,80,21,45,3.0,2,40,Urban,Data Analyst,81764,0 +75410,Female,55,High School,13,75,41,70,51,1.0,6,21,Urban,Software Engineer,148615,0 +75411,Male,46,Bachelors,13,55,61,88,92,0.0,1,91,Urban,HR Executive,126680,1 +75412,Male,26,High School,2,65,46,57,41,8.0,2,61,Semi-Urban,HR Executive,121484,0 +75413,Female,35,Bachelors,3,19,45,60,5,0.0,1,11,Urban,Manager,132370,0 +75414,Male,54,Bachelors,5,66,93,32,98,8.0,4,4,Urban,Software Engineer,115403,0 +75415,Female,21,High School,11,3,49,64,55,0.0,1,6,Urban,Software Engineer,123831,0 +75416,Male,59,Bachelors,0,17,43,51,73,0.0,3,15,Urban,Manager,129347,0 +75417,Female,48,Diploma,10,31,81,60,36,6.0,3,41,Urban,HR Executive,137622,0 +75418,Female,37,Diploma,8,91,55,43,79,2.0,6,53,Urban,Software Engineer,133948,1 +75419,Male,51,Masters,3,33,54,77,48,2.0,2,52,Urban,Manager,24014,0 +75420,Male,38,Bachelors,4,46,66,35,71,7.0,2,39,Semi-Urban,ML Engineer,62423,0 +75421,Male,36,High School,11,91,64,43,75,9.0,0,51,Rural,ML Engineer,94525,1 +75422,Female,35,High School,14,27,72,99,45,8.0,7,24,Urban,Data Analyst,132557,0 +75423,Male,29,Masters,11,39,50,22,29,0.0,1,66,Semi-Urban,Manager,38967,0 +75424,Male,53,Masters,13,43,73,15,65,8.0,3,69,Rural,Software Engineer,144274,0 +75425,Male,53,High School,5,10,47,57,8,0.0,1,45,Urban,ML Engineer,116747,0 +75426,Male,28,High School,8,3,45,32,94,8.0,1,92,Rural,ML Engineer,94923,0 +75427,Male,33,Bachelors,4,83,62,57,3,6.0,0,92,Rural,Data Analyst,28928,1 +75428,Female,36,Bachelors,10,78,55,6,71,2.0,0,59,Urban,HR Executive,66373,0 +75429,Male,32,Masters,16,32,61,83,88,8.0,6,66,Urban,Data Analyst,89990,1 +75430,Male,49,Bachelors,16,43,35,36,20,9.0,2,33,Urban,Data Analyst,20360,0 +75431,Male,42,Bachelors,12,57,52,83,12,5.0,2,93,Rural,HR Executive,76187,1 +75432,Male,46,Masters,15,55,1,57,74,0.0,0,26,Urban,Software Engineer,20961,0 +75433,Male,48,Masters,8,18,30,53,70,7.0,2,36,Rural,Software Engineer,140118,0 +75434,Male,47,Diploma,5,34,68,77,78,8.0,4,99,Semi-Urban,Software Engineer,58343,1 +75435,Male,32,High School,7,42,98,6,44,9.0,2,70,Rural,Data Analyst,62266,0 +75436,Female,43,Bachelors,16,32,21,65,21,3.0,3,18,Semi-Urban,HR Executive,37400,0 +75437,Male,22,Diploma,12,47,22,64,64,5.0,2,58,Urban,Data Analyst,104488,0 +75438,Female,35,Bachelors,7,19,42,14,66,1.0,3,37,Semi-Urban,Manager,114004,0 +75439,Male,24,Bachelors,3,91,58,44,19,0.0,6,56,Semi-Urban,Manager,73596,1 +75440,Female,30,Masters,4,41,79,84,60,7.0,2,32,Semi-Urban,Data Analyst,107631,0 +75441,Male,47,Bachelors,17,96,11,93,75,1.0,1,17,Urban,ML Engineer,130482,0 +75442,Male,39,Bachelors,19,74,69,3,82,6.0,7,29,Semi-Urban,Software Engineer,84741,0 +75443,Female,49,High School,19,23,77,30,19,2.0,1,71,Urban,HR Executive,88323,0 +75444,Male,27,Bachelors,5,30,97,90,62,2.0,7,95,Rural,ML Engineer,134382,1 +75445,Female,56,Masters,0,85,94,33,89,6.0,2,8,Urban,HR Executive,70749,0 +75446,Female,24,Masters,12,90,64,77,52,3.0,4,88,Urban,Software Engineer,72420,1 +75447,Male,43,Bachelors,8,83,53,6,33,2.0,7,32,Semi-Urban,Data Analyst,38949,0 +75448,Male,34,Masters,14,77,17,26,83,6.0,4,88,Urban,Software Engineer,61116,0 +75449,Female,41,Diploma,1,54,20,49,62,8.0,6,49,Urban,ML Engineer,47349,0 +75450,Male,25,Bachelors,8,75,14,51,84,0.0,6,97,Rural,ML Engineer,46965,1 +75451,Male,27,High School,1,51,49,68,74,3.0,2,91,Semi-Urban,ML Engineer,148422,1 +75452,Female,35,Bachelors,11,57,44,95,17,2.0,4,33,Semi-Urban,ML Engineer,129471,0 +75453,Male,57,Diploma,10,14,46,13,52,5.0,0,48,Urban,ML Engineer,65786,0 +75454,Male,22,Bachelors,3,23,60,95,5,8.0,0,94,Semi-Urban,Software Engineer,29617,1 +75455,Male,56,Bachelors,11,13,39,94,50,3.0,3,94,Urban,Data Analyst,66587,1 +75456,Male,44,Bachelors,8,69,67,18,49,5.0,0,44,Urban,ML Engineer,90408,0 +75457,Male,54,Bachelors,12,74,57,52,68,6.0,2,18,Rural,Software Engineer,78316,0 +75458,Female,56,Bachelors,11,71,74,22,37,6.0,1,43,Rural,ML Engineer,75602,0 +75459,Male,50,High School,19,36,5,18,83,8.0,3,6,Urban,Data Analyst,103633,0 +75460,Female,35,High School,18,39,42,1,27,3.0,2,68,Urban,Manager,144065,0 +75461,Female,34,Masters,16,82,89,6,8,0.0,3,92,Urban,Software Engineer,77831,1 +75462,Male,23,Bachelors,1,69,94,91,69,2.0,7,35,Urban,Data Analyst,99173,1 +75463,Female,32,Bachelors,17,79,3,47,16,7.0,3,69,Urban,ML Engineer,86318,0 +75464,Male,32,Diploma,10,92,70,44,60,6.0,3,81,Urban,HR Executive,85245,1 +75465,Male,34,High School,1,82,81,63,13,6.0,4,17,Semi-Urban,Software Engineer,23887,1 +75466,Male,56,High School,14,96,82,18,6,9.0,1,88,Urban,HR Executive,147934,1 +75467,Male,46,Masters,8,0,6,54,91,8.0,4,80,Urban,HR Executive,115239,0 +75468,Male,22,Bachelors,6,22,99,17,74,3.0,5,21,Rural,HR Executive,43934,0 +75469,Female,48,Diploma,4,2,1,11,74,3.0,3,13,Urban,HR Executive,80887,0 +75470,Male,25,Bachelors,11,46,63,83,9,4.0,7,99,Urban,HR Executive,37308,1 +75471,Female,44,PhD,19,68,54,94,43,5.0,3,14,Semi-Urban,Software Engineer,83617,0 +75472,Male,47,Bachelors,1,35,62,11,44,8.0,5,98,Urban,ML Engineer,85863,0 +75473,Male,52,Diploma,5,43,0,50,97,4.0,6,28,Semi-Urban,Software Engineer,103330,0 +75474,Female,39,Bachelors,2,53,78,62,0,8.0,6,63,Rural,Software Engineer,139400,1 +75475,Female,57,Masters,14,66,78,63,21,4.0,0,81,Urban,ML Engineer,125467,1 +75476,Female,42,Masters,19,55,1,42,40,8.0,7,89,Semi-Urban,Data Analyst,149539,0 +75477,Female,49,Bachelors,16,86,31,39,30,2.0,5,18,Urban,Data Analyst,99576,0 +75478,Female,28,Diploma,10,28,88,44,85,9.0,5,6,Urban,Manager,106393,0 +75479,Male,32,High School,18,61,50,58,84,6.0,3,16,Urban,ML Engineer,124712,0 +75480,Male,49,Masters,4,21,83,29,52,0.0,3,4,Urban,Data Analyst,72548,0 +75481,Female,29,Bachelors,6,86,77,87,73,9.0,1,89,Semi-Urban,ML Engineer,83414,1 +75482,Male,33,Bachelors,8,44,22,66,48,8.0,1,95,Urban,Manager,89123,0 +75483,Female,48,Bachelors,5,80,86,45,2,9.0,5,29,Rural,ML Engineer,113925,0 +75484,Female,27,Diploma,8,1,58,24,40,6.0,3,2,Urban,Data Analyst,133950,0 +75485,Male,41,Bachelors,17,26,25,63,84,5.0,3,84,Urban,Software Engineer,37077,0 +75486,Male,44,Diploma,14,50,46,48,29,6.0,2,51,Semi-Urban,Software Engineer,62643,0 +75487,Male,35,Masters,6,39,8,63,5,7.0,4,42,Urban,Data Analyst,69772,0 +75488,Female,49,High School,16,84,10,6,6,5.0,5,95,Urban,Data Analyst,140042,0 +75489,Male,49,Bachelors,0,55,43,86,75,1.0,7,66,Semi-Urban,Software Engineer,137062,1 +75490,Male,51,High School,19,22,18,13,45,2.0,7,69,Urban,Manager,27693,0 +75491,Male,57,Bachelors,11,60,81,61,49,5.0,5,22,Semi-Urban,ML Engineer,33619,0 +75492,Male,30,Bachelors,12,8,71,43,74,3.0,5,94,Rural,HR Executive,129370,0 +75493,Female,28,Bachelors,12,36,76,33,74,3.0,0,66,Urban,Software Engineer,130338,0 +75494,Female,29,Masters,0,6,91,57,46,4.0,6,69,Urban,HR Executive,61484,0 +75495,Male,25,Bachelors,17,2,2,31,67,8.0,3,61,Urban,HR Executive,59078,0 +75496,Female,39,Masters,9,31,47,62,61,7.0,6,7,Urban,Software Engineer,72699,0 +75497,Male,28,Bachelors,12,93,71,54,79,1.0,7,47,Semi-Urban,HR Executive,111213,1 +75498,Female,44,High School,1,55,88,8,61,0.0,6,14,Rural,Manager,59717,0 +75499,Other,21,Bachelors,10,16,77,16,64,3.0,7,68,Urban,Manager,23169,0 +75500,Male,34,Masters,5,70,68,78,78,2.0,4,92,Semi-Urban,Manager,101247,1 +75501,Male,42,Bachelors,5,80,39,22,91,4.0,6,71,Semi-Urban,Data Analyst,127084,0 +75502,Male,26,Bachelors,16,12,5,17,40,4.0,0,96,Urban,Data Analyst,94992,0 +75503,Male,45,High School,10,75,15,26,76,8.0,7,13,Urban,ML Engineer,60342,0 +75504,Male,54,High School,2,50,71,98,8,9.0,7,77,Semi-Urban,Data Analyst,114681,1 +75505,Female,24,Bachelors,6,17,17,89,47,4.0,2,88,Semi-Urban,HR Executive,77053,0 +75506,Male,38,Bachelors,19,32,19,2,44,6.0,0,86,Urban,Manager,89236,0 +75507,Female,24,PhD,11,94,4,7,46,1.0,6,15,Rural,ML Engineer,22977,0 +75508,Male,37,Masters,11,7,96,61,45,6.0,0,19,Urban,Manager,77953,0 +75509,Male,49,Bachelors,11,1,83,99,2,2.0,4,45,Semi-Urban,ML Engineer,147854,0 +75510,Female,46,Bachelors,4,28,4,42,49,0.0,7,74,Urban,Manager,24561,0 +75511,Male,26,Diploma,2,7,71,83,94,8.0,3,78,Urban,HR Executive,32046,1 +75512,Male,48,Bachelors,2,88,71,82,99,8.0,7,50,Urban,ML Engineer,136511,1 +75513,Male,55,Diploma,1,55,6,38,88,6.0,3,0,Urban,Software Engineer,48659,0 +75514,Male,41,Bachelors,12,53,24,90,14,5.0,0,80,Urban,HR Executive,122034,1 +75515,Male,23,Diploma,19,94,43,16,13,0.0,6,41,Urban,Data Analyst,131052,0 +75516,Female,54,Masters,11,41,76,70,71,7.0,6,43,Semi-Urban,Manager,21345,0 +75517,Male,52,Diploma,5,87,66,40,0,2.0,5,15,Rural,HR Executive,100172,0 +75518,Female,30,Diploma,18,20,7,45,47,5.0,2,19,Semi-Urban,Software Engineer,35066,0 +75519,Female,48,Masters,3,92,82,59,93,6.0,5,79,Urban,ML Engineer,78542,1 +75520,Male,21,Bachelors,5,57,91,80,49,5.0,3,20,Urban,Manager,86875,1 +75521,Male,32,Masters,12,32,54,33,33,9.0,5,60,Semi-Urban,HR Executive,64189,0 +75522,Female,46,Bachelors,14,59,80,78,12,7.0,4,1,Rural,HR Executive,131206,0 +75523,Female,22,High School,18,73,6,77,49,9.0,1,82,Semi-Urban,HR Executive,84215,0 +75524,Male,41,Diploma,10,5,0,77,10,0.0,1,92,Rural,HR Executive,118426,0 +75525,Male,27,Masters,19,57,57,72,23,7.0,2,3,Rural,Data Analyst,141067,0 +75526,Male,52,Bachelors,4,71,15,97,42,1.0,6,90,Urban,Data Analyst,103494,1 +75527,Male,42,Diploma,4,92,19,6,13,8.0,5,90,Urban,HR Executive,72173,0 +75528,Male,29,Masters,2,85,40,44,90,7.0,2,12,Urban,Software Engineer,97317,0 +75529,Female,46,Masters,8,33,20,91,94,3.0,5,67,Urban,Software Engineer,36523,0 +75530,Male,26,Diploma,5,51,16,86,89,4.0,7,60,Semi-Urban,ML Engineer,33891,0 +75531,Female,45,Diploma,11,23,38,52,66,1.0,1,71,Urban,HR Executive,123801,0 +75532,Female,40,High School,17,25,58,51,39,1.0,4,85,Urban,HR Executive,103487,0 +75533,Female,26,Bachelors,2,14,43,67,2,7.0,0,28,Urban,ML Engineer,29485,0 +75534,Female,47,Bachelors,3,46,55,40,37,3.0,7,89,Urban,Manager,118824,0 +75535,Male,26,Bachelors,19,73,66,90,51,2.0,7,21,Rural,Software Engineer,74284,1 +75536,Male,33,Bachelors,2,99,27,62,27,9.0,1,58,Rural,ML Engineer,67710,1 +75537,Male,50,Diploma,15,75,57,57,56,1.0,2,95,Semi-Urban,ML Engineer,125265,1 +75538,Female,49,PhD,11,42,81,49,5,1.0,7,62,Rural,Data Analyst,83056,0 +75539,Male,59,Bachelors,4,97,95,14,75,7.0,7,45,Urban,Manager,127748,1 +75540,Male,22,Diploma,2,24,85,42,29,8.0,3,22,Rural,ML Engineer,129832,0 +75541,Female,29,Masters,1,87,90,42,6,3.0,5,32,Urban,HR Executive,111383,1 +75542,Male,27,Bachelors,7,36,1,99,66,9.0,1,33,Semi-Urban,Manager,21204,0 +75543,Male,52,Diploma,18,90,68,45,2,7.0,1,69,Rural,Manager,23667,1 +75544,Female,53,High School,5,23,98,99,41,1.0,5,20,Urban,Manager,31280,0 +75545,Male,45,Diploma,12,65,48,55,95,2.0,1,82,Rural,HR Executive,128143,1 +75546,Male,59,PhD,7,70,4,60,37,8.0,4,65,Rural,Data Analyst,114475,0 +75547,Female,44,Diploma,2,14,12,84,14,9.0,3,15,Urban,Software Engineer,95605,0 +75548,Male,42,Bachelors,13,43,28,46,65,8.0,5,67,Semi-Urban,ML Engineer,55629,0 +75549,Male,57,Bachelors,13,32,9,42,89,9.0,1,53,Rural,Software Engineer,63587,0 +75550,Male,25,Bachelors,4,73,50,42,57,6.0,1,38,Rural,Data Analyst,125977,0 +75551,Female,39,High School,6,94,43,98,59,3.0,0,9,Semi-Urban,Data Analyst,87851,1 +75552,Male,35,Bachelors,16,24,88,58,20,2.0,0,62,Semi-Urban,Manager,136200,0 +75553,Male,47,Bachelors,17,33,74,6,89,4.0,0,99,Rural,HR Executive,53024,0 +75554,Male,37,Masters,7,33,69,99,65,1.0,2,21,Rural,Data Analyst,21415,0 +75555,Male,21,Masters,10,85,68,46,45,8.0,7,32,Semi-Urban,HR Executive,37384,0 +75556,Male,54,Diploma,4,83,64,73,97,7.0,3,90,Semi-Urban,Manager,58840,1 +75557,Male,51,Masters,6,66,49,23,57,3.0,3,80,Rural,HR Executive,79310,0 +75558,Other,40,High School,15,58,12,43,77,0.0,6,60,Rural,Software Engineer,126699,0 +75559,Male,38,Bachelors,14,2,94,61,36,1.0,3,42,Semi-Urban,ML Engineer,21312,0 +75560,Male,52,PhD,7,32,66,68,73,1.0,6,32,Semi-Urban,Manager,21282,0 +75561,Male,37,PhD,7,50,63,34,53,2.0,3,68,Urban,Manager,30629,0 +75562,Male,57,Bachelors,14,16,54,19,82,2.0,7,6,Urban,Data Analyst,34299,0 +75563,Male,28,Diploma,9,51,37,0,59,9.0,1,17,Semi-Urban,Manager,73045,0 +75564,Male,55,Bachelors,0,57,95,74,64,8.0,5,30,Urban,Data Analyst,98219,1 +75565,Female,48,Diploma,18,97,42,66,42,6.0,3,11,Urban,Manager,37906,0 +75566,Male,39,Bachelors,13,48,67,71,43,0.0,6,85,Urban,Data Analyst,138439,1 +75567,Male,40,Bachelors,3,42,39,78,43,1.0,5,82,Rural,Data Analyst,115612,1 +75568,Male,53,High School,2,8,95,69,11,1.0,7,93,Semi-Urban,HR Executive,34306,1 +75569,Male,28,Masters,7,35,50,52,57,3.0,4,23,Rural,ML Engineer,87786,0 +75570,Female,52,Diploma,12,19,30,42,56,8.0,4,98,Urban,HR Executive,137247,0 +75571,Male,55,Masters,12,12,54,31,21,1.0,0,42,Urban,ML Engineer,113188,0 +75572,Female,42,Masters,9,17,48,84,47,9.0,2,6,Urban,ML Engineer,106775,0 +75573,Female,56,Diploma,13,77,92,82,41,4.0,7,58,Urban,ML Engineer,143674,1 +75574,Male,58,Masters,8,30,31,14,53,6.0,7,27,Urban,HR Executive,98574,0 +75575,Female,44,Bachelors,19,87,84,96,60,9.0,4,65,Urban,Manager,113100,1 +75576,Male,54,High School,11,61,0,86,67,1.0,4,93,Semi-Urban,ML Engineer,142558,1 +75577,Female,54,Masters,15,10,30,16,50,7.0,1,80,Urban,Manager,125383,0 +75578,Male,28,Diploma,11,70,52,8,93,7.0,7,37,Semi-Urban,Software Engineer,141202,0 +75579,Male,45,PhD,19,56,12,25,64,9.0,4,34,Urban,ML Engineer,108267,0 +75580,Male,37,Bachelors,2,28,97,42,44,8.0,5,21,Urban,HR Executive,52717,0 +75581,Male,59,Masters,10,2,72,12,24,3.0,7,46,Urban,Manager,72145,0 +75582,Other,47,Bachelors,3,50,11,37,62,9.0,5,4,Urban,Data Analyst,49112,0 +75583,Male,51,High School,10,22,74,46,31,1.0,6,43,Urban,ML Engineer,108918,0 +75584,Female,42,Diploma,2,11,75,64,53,2.0,5,65,Urban,HR Executive,54186,0 +75585,Female,23,Diploma,13,49,41,0,14,5.0,1,64,Urban,HR Executive,22436,0 +75586,Male,24,Masters,14,94,49,58,87,2.0,5,24,Rural,Software Engineer,61397,0 +75587,Male,44,Bachelors,7,46,63,10,96,3.0,2,94,Semi-Urban,Data Analyst,115860,0 +75588,Male,38,Bachelors,18,49,58,88,39,9.0,0,54,Urban,HR Executive,20596,1 +75589,Female,56,Masters,1,96,26,60,20,0.0,4,67,Urban,HR Executive,121833,1 +75590,Male,55,High School,5,61,47,33,57,9.0,3,70,Semi-Urban,Software Engineer,68759,0 +75591,Male,36,Bachelors,11,16,69,42,94,2.0,0,48,Urban,HR Executive,101388,0 +75592,Male,40,PhD,11,66,61,83,15,8.0,6,12,Urban,Manager,119240,0 +75593,Female,30,High School,6,92,15,36,93,7.0,4,3,Rural,Data Analyst,82772,0 +75594,Male,23,Bachelors,1,9,78,29,18,8.0,0,17,Urban,ML Engineer,105063,0 +75595,Female,31,Bachelors,17,30,30,37,55,2.0,6,0,Semi-Urban,HR Executive,47925,0 +75596,Male,48,Masters,19,39,53,38,48,8.0,4,44,Urban,Manager,80500,0 +75597,Female,49,Diploma,12,74,16,22,17,9.0,0,28,Urban,Software Engineer,116710,0 +75598,Female,31,Diploma,0,97,85,13,62,8.0,6,80,Urban,HR Executive,44481,1 +75599,Male,37,Masters,4,68,67,27,4,2.0,0,36,Urban,Manager,29245,0 +75600,Male,36,Diploma,8,15,62,33,38,8.0,0,20,Semi-Urban,Data Analyst,76400,0 +75601,Female,33,Diploma,2,5,23,88,74,9.0,7,90,Rural,Manager,72095,0 +75602,Other,31,Diploma,19,92,67,6,82,4.0,7,30,Urban,HR Executive,128957,0 +75603,Female,57,Bachelors,4,86,95,6,6,2.0,0,63,Rural,Manager,85950,1 +75604,Female,48,Diploma,14,78,47,16,31,3.0,6,22,Semi-Urban,Manager,35240,0 +75605,Female,33,Bachelors,5,46,11,63,42,9.0,5,44,Urban,Data Analyst,20318,0 +75606,Male,32,Diploma,7,73,46,67,78,7.0,7,90,Semi-Urban,HR Executive,138744,1 +75607,Female,41,Bachelors,18,50,5,25,92,3.0,4,74,Urban,Software Engineer,81550,0 +75608,Male,25,PhD,13,19,29,75,24,3.0,3,13,Rural,HR Executive,95344,0 +75609,Male,51,Diploma,12,59,37,56,3,1.0,1,87,Urban,ML Engineer,64194,1 +75610,Male,34,Bachelors,10,16,45,37,25,8.0,0,22,Urban,Software Engineer,102578,0 +75611,Female,27,Bachelors,0,46,15,37,84,3.0,3,80,Urban,ML Engineer,104787,0 +75612,Female,34,Masters,16,78,56,97,74,4.0,3,81,Urban,Data Analyst,133661,1 +75613,Male,34,Masters,15,51,84,67,96,1.0,6,75,Urban,Software Engineer,106484,1 +75614,Female,59,PhD,2,33,17,73,49,4.0,3,72,Urban,ML Engineer,28576,0 +75615,Female,49,Masters,15,66,17,46,11,2.0,5,70,Urban,ML Engineer,36431,0 +75616,Male,37,High School,5,8,32,82,4,5.0,2,28,Urban,Software Engineer,129300,0 +75617,Male,22,PhD,13,17,64,26,57,6.0,7,60,Rural,Manager,91256,0 +75618,Male,34,Masters,17,59,2,45,68,2.0,5,73,Rural,ML Engineer,107644,0 +75619,Male,22,Bachelors,4,52,48,82,97,3.0,2,5,Semi-Urban,Data Analyst,121724,0 +75620,Female,26,Diploma,9,99,86,99,88,1.0,1,57,Urban,Software Engineer,127288,1 +75621,Male,48,Bachelors,19,78,33,27,12,2.0,4,88,Semi-Urban,Software Engineer,74298,0 +75622,Male,31,Bachelors,11,7,97,59,15,1.0,1,17,Rural,HR Executive,21329,0 +75623,Male,46,Masters,19,99,31,76,37,6.0,7,16,Urban,ML Engineer,91412,0 +75624,Male,23,Bachelors,8,73,68,45,84,0.0,5,14,Urban,Manager,26832,0 +75625,Male,27,Diploma,15,5,85,21,8,2.0,0,56,Semi-Urban,Manager,117135,0 +75626,Male,54,Masters,2,96,12,71,5,7.0,3,76,Semi-Urban,Manager,108463,1 +75627,Female,54,Diploma,18,54,27,71,27,6.0,6,69,Urban,Software Engineer,56791,0 +75628,Male,37,Bachelors,0,63,64,15,53,5.0,7,85,Rural,HR Executive,136477,0 +75629,Male,24,Diploma,12,29,7,15,16,1.0,1,60,Semi-Urban,HR Executive,81847,0 +75630,Female,26,Bachelors,18,26,21,24,74,7.0,0,78,Rural,Software Engineer,24204,0 +75631,Female,57,High School,8,54,16,72,92,7.0,2,39,Semi-Urban,ML Engineer,46956,0 +75632,Female,59,Masters,11,99,87,42,34,7.0,7,83,Urban,HR Executive,76722,1 +75633,Female,53,Bachelors,7,56,67,70,27,3.0,1,89,Urban,Manager,30598,1 +75634,Other,26,Bachelors,14,12,74,54,54,1.0,2,17,Rural,Data Analyst,34068,0 +75635,Female,33,High School,13,45,69,81,13,8.0,2,47,Semi-Urban,HR Executive,44198,1 +75636,Other,25,Masters,11,26,16,25,20,5.0,4,17,Semi-Urban,Software Engineer,80683,0 +75637,Female,37,Masters,16,53,84,46,85,3.0,3,46,Urban,Data Analyst,83565,0 +75638,Female,34,High School,16,41,97,52,54,8.0,2,52,Semi-Urban,ML Engineer,108368,1 +75639,Male,43,Bachelors,13,84,64,35,67,5.0,2,33,Urban,ML Engineer,31440,0 +75640,Male,57,Diploma,12,41,59,57,16,2.0,4,83,Semi-Urban,Software Engineer,142278,1 +75641,Other,53,Bachelors,4,97,74,44,9,9.0,5,0,Urban,Manager,82322,0 +75642,Male,29,Bachelors,16,18,79,71,57,7.0,2,51,Urban,Data Analyst,86255,0 +75643,Other,54,Masters,14,8,48,24,93,5.0,1,28,Semi-Urban,Software Engineer,101811,0 +75644,Male,53,Masters,16,91,70,89,33,3.0,1,6,Urban,ML Engineer,130851,1 +75645,Male,27,Bachelors,10,2,33,1,80,9.0,4,19,Urban,Manager,82786,0 +75646,Female,37,Diploma,12,57,91,81,56,0.0,4,2,Semi-Urban,Software Engineer,92234,0 +75647,Male,57,Bachelors,8,55,37,85,8,9.0,5,97,Urban,ML Engineer,110244,1 +75648,Female,59,Bachelors,0,48,8,71,32,8.0,4,4,Rural,ML Engineer,77849,0 +75649,Male,23,Masters,3,49,15,61,77,8.0,3,79,Urban,Manager,62150,0 +75650,Other,28,Masters,19,33,14,57,48,5.0,6,49,Semi-Urban,Manager,59761,0 +75651,Female,21,Masters,4,97,35,30,2,8.0,1,81,Rural,HR Executive,69181,1 +75652,Male,23,Bachelors,3,92,39,75,24,5.0,7,18,Urban,ML Engineer,32500,0 +75653,Male,28,Masters,1,70,10,16,75,5.0,4,21,Urban,Data Analyst,40034,0 +75654,Male,24,Bachelors,12,97,91,79,80,0.0,0,67,Urban,HR Executive,71804,1 +75655,Other,57,PhD,19,66,67,1,86,4.0,2,72,Rural,ML Engineer,128045,0 +75656,Male,29,High School,2,49,50,93,89,4.0,4,90,Urban,Manager,24635,1 +75657,Male,23,Bachelors,15,53,28,4,80,7.0,7,7,Rural,HR Executive,85924,0 +75658,Female,42,PhD,16,74,10,49,54,6.0,6,22,Urban,Software Engineer,105322,0 +75659,Other,28,High School,12,92,13,84,81,6.0,1,31,Rural,Manager,113712,0 +75660,Female,57,Bachelors,9,72,11,0,21,1.0,0,73,Semi-Urban,Manager,125240,0 +75661,Female,34,Bachelors,17,32,80,76,70,9.0,5,26,Rural,Software Engineer,52082,0 +75662,Male,26,High School,5,40,10,65,95,4.0,3,78,Semi-Urban,HR Executive,42391,0 +75663,Male,40,Diploma,9,99,6,91,54,4.0,0,33,Urban,Software Engineer,82653,0 +75664,Female,41,Bachelors,6,36,47,98,54,4.0,2,72,Urban,Software Engineer,148845,1 +75665,Male,38,High School,17,75,36,72,87,8.0,7,5,Rural,Software Engineer,119544,0 +75666,Male,50,Masters,15,35,43,75,9,6.0,4,8,Urban,HR Executive,100640,0 +75667,Male,24,Masters,5,0,55,62,13,7.0,2,81,Urban,HR Executive,67587,0 +75668,Male,21,Bachelors,0,96,79,33,93,6.0,5,93,Urban,ML Engineer,69572,1 +75669,Female,51,Bachelors,14,28,0,64,74,8.0,6,29,Urban,Manager,59851,0 +75670,Male,49,High School,18,7,56,44,52,4.0,7,33,Urban,Manager,108986,0 +75671,Female,31,Masters,6,94,13,30,69,1.0,0,4,Rural,ML Engineer,70936,0 +75672,Female,51,Bachelors,19,16,7,83,92,6.0,2,89,Urban,HR Executive,77523,0 +75673,Female,31,Masters,4,73,67,79,69,2.0,0,32,Semi-Urban,Data Analyst,130967,1 +75674,Male,42,Masters,3,55,95,15,12,0.0,0,51,Semi-Urban,ML Engineer,94636,0 +75675,Male,21,High School,8,50,68,72,7,2.0,7,90,Urban,ML Engineer,103987,1 +75676,Female,26,Bachelors,10,26,43,90,16,7.0,7,35,Semi-Urban,Manager,103826,0 +75677,Female,52,Masters,11,81,34,70,67,6.0,7,20,Rural,HR Executive,107870,0 +75678,Male,37,Bachelors,15,84,99,2,51,9.0,4,43,Urban,Data Analyst,86269,0 +75679,Male,53,Bachelors,10,16,38,16,67,2.0,5,91,Rural,Data Analyst,91930,0 +75680,Male,36,Diploma,13,4,5,42,43,2.0,4,32,Semi-Urban,Manager,31755,0 +75681,Male,27,Bachelors,1,30,40,81,84,7.0,2,22,Semi-Urban,Data Analyst,107286,0 +75682,Female,49,High School,3,21,98,44,52,6.0,2,70,Urban,HR Executive,74743,0 +75683,Male,40,Bachelors,19,44,51,13,95,8.0,7,95,Semi-Urban,Data Analyst,113982,0 +75684,Male,28,High School,11,66,66,19,41,2.0,7,78,Urban,ML Engineer,66281,0 +75685,Male,56,Masters,11,14,71,42,42,2.0,6,10,Urban,HR Executive,49672,0 +75686,Other,51,Diploma,15,67,75,50,9,9.0,1,86,Urban,HR Executive,65389,1 +75687,Female,49,Bachelors,10,72,93,48,33,9.0,4,80,Rural,Data Analyst,107180,1 +75688,Male,46,High School,15,80,80,94,48,1.0,5,55,Urban,Software Engineer,77374,1 +75689,Male,43,Bachelors,16,97,30,0,82,9.0,7,58,Urban,ML Engineer,63647,0 +75690,Female,39,Masters,16,88,91,63,12,7.0,4,20,Urban,Data Analyst,64315,1 +75691,Male,35,Bachelors,15,85,10,2,19,5.0,1,16,Semi-Urban,HR Executive,65005,0 +75692,Female,27,Bachelors,7,88,57,94,11,9.0,1,55,Semi-Urban,ML Engineer,136710,1 +75693,Female,52,Bachelors,0,56,80,17,88,6.0,5,97,Urban,Software Engineer,59233,1 +75694,Male,53,High School,13,16,11,29,79,7.0,3,12,Urban,HR Executive,101076,0 +75695,Male,29,Bachelors,18,30,39,32,17,2.0,0,2,Urban,ML Engineer,118895,0 +75696,Male,25,High School,8,79,19,62,79,7.0,4,18,Urban,HR Executive,142774,0 +75697,Other,41,Bachelors,7,26,38,97,50,3.0,7,55,Rural,Software Engineer,31083,0 +75698,Female,40,Bachelors,13,60,65,58,46,5.0,7,87,Urban,Manager,105601,1 +75699,Female,53,PhD,3,17,32,80,88,7.0,3,97,Urban,Data Analyst,97729,0 +75700,Male,41,Masters,8,22,51,57,15,6.0,0,64,Urban,ML Engineer,20477,0 +75701,Male,46,Bachelors,18,2,82,61,46,6.0,6,80,Urban,HR Executive,109986,0 +75702,Female,51,Masters,3,4,83,56,30,1.0,2,78,Urban,Software Engineer,67711,0 +75703,Male,45,Diploma,10,65,91,64,47,6.0,3,74,Urban,Software Engineer,61608,1 +75704,Female,28,High School,13,98,16,28,5,0.0,5,84,Urban,ML Engineer,115130,0 +75705,Female,22,Bachelors,0,55,55,8,30,8.0,4,94,Rural,Data Analyst,88021,0 +75706,Other,49,Diploma,5,51,30,3,0,5.0,5,11,Semi-Urban,Manager,104998,0 +75707,Male,57,Bachelors,17,23,1,85,30,9.0,5,81,Rural,Manager,103302,0 +75708,Female,39,Masters,14,23,10,60,75,0.0,0,46,Rural,Data Analyst,102663,0 +75709,Female,29,High School,5,50,87,48,63,7.0,5,41,Urban,HR Executive,93997,0 +75710,Female,47,Diploma,17,45,98,47,45,8.0,2,36,Urban,HR Executive,136413,0 +75711,Male,56,High School,5,97,10,55,25,4.0,0,65,Rural,Data Analyst,133936,0 +75712,Male,51,High School,5,79,48,83,36,9.0,5,55,Urban,ML Engineer,100625,1 +75713,Other,24,Diploma,18,2,61,39,58,1.0,5,47,Urban,HR Executive,35778,0 +75714,Male,42,Diploma,0,66,42,28,65,8.0,0,57,Urban,ML Engineer,127563,0 +75715,Other,35,Bachelors,5,46,17,6,2,4.0,1,5,Urban,ML Engineer,46129,0 +75716,Male,36,Masters,9,47,33,74,88,4.0,0,69,Semi-Urban,ML Engineer,147769,0 +75717,Female,36,High School,19,84,64,11,11,0.0,3,26,Rural,Data Analyst,111592,0 +75718,Male,48,Bachelors,0,93,16,96,41,7.0,5,42,Rural,Manager,67257,1 +75719,Female,37,PhD,14,3,7,20,95,4.0,7,82,Semi-Urban,ML Engineer,111960,0 +75720,Male,38,High School,7,45,51,86,91,1.0,0,70,Urban,Software Engineer,45016,1 +75721,Female,23,Bachelors,13,33,53,15,95,9.0,4,31,Urban,Data Analyst,23657,0 +75722,Male,58,High School,18,5,64,62,53,8.0,0,85,Urban,Data Analyst,145319,0 +75723,Male,28,Masters,9,40,22,80,33,8.0,2,86,Urban,ML Engineer,134423,0 +75724,Female,44,Bachelors,4,3,38,14,72,6.0,6,23,Urban,Manager,62085,0 +75725,Male,22,PhD,18,50,36,54,20,8.0,7,81,Urban,HR Executive,136393,0 +75726,Female,39,Diploma,12,74,38,63,23,3.0,3,35,Urban,HR Executive,22727,0 +75727,Male,48,PhD,14,41,87,28,83,2.0,7,70,Urban,ML Engineer,117253,0 +75728,Male,43,Diploma,14,21,90,98,10,5.0,3,35,Rural,ML Engineer,44436,1 +75729,Male,43,High School,8,99,88,60,90,0.0,6,29,Semi-Urban,HR Executive,43777,1 +75730,Male,24,Masters,5,95,48,21,65,8.0,5,75,Rural,HR Executive,73171,1 +75731,Male,57,PhD,6,86,50,6,73,9.0,2,30,Urban,ML Engineer,70557,0 +75732,Male,56,Diploma,4,98,15,17,86,0.0,4,46,Semi-Urban,Manager,138269,0 +75733,Male,32,Masters,0,88,84,72,14,2.0,5,19,Urban,Manager,133396,1 +75734,Male,30,Diploma,2,31,86,9,99,0.0,6,40,Semi-Urban,HR Executive,50535,0 +75735,Female,52,Diploma,17,94,93,2,24,3.0,2,47,Urban,Manager,95323,0 +75736,Female,55,PhD,0,79,40,60,60,5.0,2,64,Rural,Manager,130150,1 +75737,Male,58,Bachelors,4,88,85,1,1,6.0,6,60,Rural,HR Executive,109194,0 +75738,Female,38,Masters,3,72,87,99,16,4.0,7,84,Rural,ML Engineer,141724,1 +75739,Male,57,Masters,4,40,26,53,9,0.0,1,45,Urban,HR Executive,33892,0 +75740,Male,22,Bachelors,0,77,3,83,34,8.0,4,68,Semi-Urban,HR Executive,134514,0 +75741,Female,35,Bachelors,9,26,21,96,57,3.0,3,67,Semi-Urban,Data Analyst,67300,0 +75742,Male,31,Bachelors,6,10,78,49,36,0.0,4,59,Semi-Urban,ML Engineer,36193,0 +75743,Male,36,Bachelors,5,69,17,32,40,2.0,1,91,Rural,ML Engineer,85039,0 +75744,Male,53,High School,18,12,18,59,7,3.0,5,1,Urban,ML Engineer,110177,0 +75745,Female,55,Diploma,2,81,22,94,91,7.0,3,97,Semi-Urban,Software Engineer,59901,1 +75746,Male,34,PhD,19,33,3,69,10,0.0,1,52,Semi-Urban,Manager,37736,0 +75747,Male,50,Bachelors,11,89,95,63,38,0.0,0,14,Urban,ML Engineer,144022,1 +75748,Male,40,Bachelors,9,57,83,82,69,2.0,0,87,Rural,ML Engineer,110242,1 +75749,Male,34,Bachelors,19,5,63,70,77,8.0,3,28,Rural,HR Executive,45738,0 +75750,Female,38,Bachelors,6,7,65,75,49,0.0,7,33,Urban,Software Engineer,79373,0 +75751,Female,55,Diploma,3,66,77,78,92,7.0,1,10,Semi-Urban,Data Analyst,50706,0 +75752,Male,42,Bachelors,6,98,40,74,66,4.0,4,89,Rural,Data Analyst,44554,1 +75753,Male,55,Masters,10,82,26,39,11,6.0,2,88,Semi-Urban,Manager,38957,1 +75754,Male,35,Bachelors,0,95,76,40,67,9.0,4,66,Semi-Urban,HR Executive,72681,1 +75755,Other,49,Bachelors,10,58,21,30,49,6.0,6,44,Urban,Manager,43500,0 +75756,Male,50,Diploma,4,83,10,18,59,4.0,7,63,Semi-Urban,HR Executive,47291,0 +75757,Female,41,Bachelors,1,25,53,69,88,0.0,0,48,Urban,HR Executive,135270,0 +75758,Male,56,High School,10,11,92,7,0,4.0,0,0,Semi-Urban,HR Executive,43540,0 +75759,Male,31,High School,10,86,21,40,3,2.0,2,90,Semi-Urban,ML Engineer,28553,1 +75760,Female,41,Masters,7,97,69,91,22,2.0,4,58,Rural,HR Executive,133145,1 +75761,Male,49,High School,1,42,99,59,1,4.0,0,49,Urban,Manager,57433,1 +75762,Female,25,High School,17,19,83,90,25,4.0,1,10,Urban,ML Engineer,39026,0 +75763,Other,40,Masters,1,73,61,30,65,6.0,2,23,Rural,Software Engineer,139491,0 +75764,Male,31,PhD,18,59,1,3,14,8.0,0,52,Rural,HR Executive,91714,0 +75765,Male,42,High School,10,36,58,47,94,4.0,3,83,Semi-Urban,HR Executive,63091,0 +75766,Male,45,PhD,3,95,4,55,67,0.0,6,55,Urban,HR Executive,81193,0 +75767,Female,25,Masters,2,83,75,88,66,5.0,4,27,Rural,Manager,58396,1 +75768,Female,51,Masters,7,22,6,73,52,2.0,4,69,Semi-Urban,Software Engineer,96366,0 +75769,Female,46,Bachelors,15,89,39,15,38,8.0,6,61,Urban,Data Analyst,124487,0 +75770,Male,39,Diploma,5,15,47,17,82,1.0,3,14,Urban,Manager,61224,0 +75771,Male,34,Masters,16,65,77,11,56,8.0,2,18,Urban,Software Engineer,69584,0 +75772,Female,45,PhD,16,2,14,1,45,4.0,3,40,Urban,Manager,38321,0 +75773,Female,24,Bachelors,19,97,9,78,18,5.0,7,9,Rural,Data Analyst,48044,0 +75774,Male,26,Bachelors,11,19,8,73,15,0.0,2,91,Rural,Software Engineer,28021,0 +75775,Female,21,Masters,1,70,14,77,9,8.0,3,71,Rural,HR Executive,122889,0 +75776,Other,36,Bachelors,5,90,29,73,96,6.0,0,52,Rural,HR Executive,105285,1 +75777,Female,44,PhD,12,46,37,35,25,7.0,0,95,Urban,Manager,69425,0 +75778,Male,58,Diploma,19,91,38,60,35,0.0,5,33,Urban,ML Engineer,88803,0 +75779,Male,31,Bachelors,7,23,62,89,58,1.0,4,56,Urban,Manager,85776,0 +75780,Male,40,PhD,10,9,79,51,21,6.0,7,52,Semi-Urban,Software Engineer,147413,0 +75781,Female,26,Bachelors,1,84,16,65,17,1.0,6,41,Semi-Urban,Software Engineer,49888,0 +75782,Male,44,Bachelors,19,41,20,88,1,7.0,2,27,Urban,Data Analyst,68234,0 +75783,Male,47,Bachelors,15,69,61,57,33,8.0,6,70,Urban,ML Engineer,67092,1 +75784,Female,25,Bachelors,3,16,67,18,47,5.0,3,79,Rural,Data Analyst,146074,0 +75785,Female,57,PhD,4,43,6,72,24,9.0,7,23,Urban,Software Engineer,135997,0 +75786,Male,41,PhD,15,87,7,3,94,1.0,0,58,Urban,Data Analyst,81316,0 +75787,Male,28,Diploma,7,54,71,59,61,8.0,1,56,Semi-Urban,Manager,138231,1 +75788,Female,38,Diploma,7,0,77,6,35,4.0,5,58,Urban,HR Executive,80295,0 +75789,Female,38,Diploma,6,41,89,31,35,4.0,1,49,Semi-Urban,ML Engineer,74102,0 +75790,Female,45,PhD,15,37,5,24,24,8.0,6,37,Semi-Urban,Software Engineer,77620,0 +75791,Male,56,Bachelors,8,56,90,63,2,5.0,2,32,Urban,ML Engineer,149963,1 +75792,Male,45,Bachelors,18,32,17,47,42,4.0,3,29,Urban,Manager,92298,0 +75793,Other,26,Masters,8,69,10,5,87,7.0,3,72,Urban,Data Analyst,64809,0 +75794,Female,50,Bachelors,6,76,2,25,39,1.0,2,91,Semi-Urban,Data Analyst,93917,0 +75795,Male,34,Masters,12,69,76,23,18,0.0,4,5,Semi-Urban,Software Engineer,110738,0 +75796,Female,43,Masters,3,28,3,29,46,5.0,6,36,Urban,HR Executive,31110,0 +75797,Other,37,Masters,15,71,22,26,90,6.0,4,81,Semi-Urban,Manager,37183,0 +75798,Male,32,Bachelors,19,93,23,29,11,0.0,5,98,Rural,Software Engineer,64226,1 +75799,Female,28,Masters,4,5,13,10,16,3.0,2,93,Urban,Data Analyst,59728,0 +75800,Male,36,Bachelors,17,38,60,53,2,6.0,5,47,Urban,Manager,98721,0 +75801,Male,24,Masters,15,64,62,90,59,2.0,3,67,Urban,Data Analyst,43073,1 +75802,Male,21,High School,15,61,86,73,11,0.0,5,14,Semi-Urban,HR Executive,87086,0 +75803,Male,36,Bachelors,16,37,55,47,19,7.0,4,27,Urban,ML Engineer,46718,0 +75804,Male,54,Bachelors,11,65,3,2,55,9.0,3,38,Urban,HR Executive,22956,0 +75805,Female,24,High School,18,42,31,32,21,9.0,1,99,Urban,Manager,34652,0 +75806,Female,24,Bachelors,2,93,87,0,36,5.0,3,74,Urban,ML Engineer,21120,1 +75807,Male,39,Bachelors,15,99,75,60,97,8.0,6,82,Urban,Data Analyst,137151,1 +75808,Male,40,Diploma,10,83,14,0,40,7.0,2,87,Semi-Urban,ML Engineer,25098,0 +75809,Male,49,Bachelors,1,36,70,29,51,6.0,3,61,Urban,Data Analyst,57146,0 +75810,Male,38,Masters,5,48,35,47,11,9.0,2,95,Urban,Data Analyst,136399,0 +75811,Female,37,Bachelors,15,72,32,1,57,2.0,5,89,Rural,Manager,98427,0 +75812,Male,47,Bachelors,1,56,76,10,36,2.0,2,27,Urban,ML Engineer,106959,0 +75813,Male,58,High School,6,44,74,56,38,6.0,0,7,Semi-Urban,Software Engineer,110561,0 +75814,Female,43,Bachelors,1,21,26,18,60,7.0,6,0,Semi-Urban,ML Engineer,63959,0 +75815,Female,28,High School,6,16,74,51,27,5.0,0,93,Urban,HR Executive,65899,0 +75816,Male,23,Bachelors,19,40,51,25,52,8.0,3,44,Urban,Data Analyst,75699,0 +75817,Male,47,High School,15,8,80,0,50,9.0,5,17,Urban,HR Executive,70737,0 +75818,Other,41,High School,18,73,43,68,40,9.0,5,29,Urban,HR Executive,72255,0 +75819,Female,46,High School,2,72,81,98,32,3.0,4,27,Urban,HR Executive,92689,1 +75820,Female,57,Bachelors,11,86,16,55,61,1.0,2,40,Urban,Software Engineer,63895,0 +75821,Male,58,Diploma,16,12,0,27,48,0.0,5,9,Urban,ML Engineer,74664,0 +75822,Female,44,Masters,9,72,26,3,97,5.0,4,46,Rural,Software Engineer,33520,0 +75823,Female,46,Bachelors,11,52,18,14,17,3.0,4,65,Urban,ML Engineer,77555,0 +75824,Female,39,Diploma,11,14,85,63,84,5.0,2,66,Semi-Urban,ML Engineer,53395,0 +75825,Male,36,Diploma,15,0,61,7,56,2.0,5,16,Semi-Urban,Data Analyst,80458,0 +75826,Female,26,Bachelors,19,53,72,65,87,9.0,0,91,Rural,HR Executive,74000,1 +75827,Male,54,Masters,0,80,51,43,84,8.0,4,30,Urban,Data Analyst,30253,0 +75828,Male,33,High School,15,12,84,57,44,5.0,0,45,Urban,Manager,147252,0 +75829,Male,33,Bachelors,19,58,24,82,95,6.0,5,98,Semi-Urban,Manager,108459,1 +75830,Male,55,Diploma,10,46,22,35,61,4.0,7,47,Rural,Manager,84639,0 +75831,Male,49,Bachelors,8,84,7,3,42,2.0,7,35,Urban,HR Executive,96850,0 +75832,Female,24,PhD,7,24,0,8,81,5.0,6,41,Urban,Data Analyst,144285,0 +75833,Female,54,Bachelors,0,20,47,64,17,0.0,4,99,Semi-Urban,HR Executive,78634,0 +75834,Male,59,Bachelors,10,42,45,58,12,9.0,7,74,Urban,Data Analyst,109353,0 +75835,Female,23,Bachelors,9,98,32,14,55,6.0,1,81,Rural,HR Executive,103863,0 +75836,Male,48,Bachelors,13,28,85,92,20,2.0,6,88,Urban,Data Analyst,141097,1 +75837,Other,23,Bachelors,11,38,25,89,17,2.0,1,34,Rural,Manager,120803,0 +75838,Male,45,Masters,10,67,47,29,64,0.0,0,34,Urban,Manager,129216,0 +75839,Male,57,PhD,4,88,69,52,9,4.0,3,96,Urban,Software Engineer,129762,1 +75840,Female,22,High School,14,56,31,6,97,6.0,2,24,Semi-Urban,HR Executive,41805,0 +75841,Male,25,Bachelors,6,11,93,39,82,6.0,2,28,Semi-Urban,Software Engineer,103020,0 +75842,Male,23,PhD,8,51,72,30,73,3.0,7,29,Rural,Manager,29081,0 +75843,Male,22,Masters,3,7,51,78,63,0.0,2,5,Urban,Software Engineer,32449,0 +75844,Female,45,Diploma,18,33,37,59,54,6.0,5,36,Urban,Data Analyst,32720,0 +75845,Male,47,Diploma,11,79,70,68,56,1.0,5,89,Semi-Urban,Manager,64632,1 +75846,Male,21,High School,3,32,68,57,93,4.0,0,48,Urban,Software Engineer,107367,0 +75847,Male,51,High School,6,23,67,46,16,6.0,7,58,Semi-Urban,Manager,71385,0 +75848,Male,58,Bachelors,13,42,48,42,64,3.0,7,12,Urban,Software Engineer,139670,0 +75849,Male,37,Bachelors,11,63,25,59,14,7.0,5,4,Rural,HR Executive,99267,0 +75850,Female,28,Masters,13,49,96,50,27,2.0,7,75,Urban,ML Engineer,101880,1 +75851,Male,41,Bachelors,15,99,63,3,63,4.0,5,8,Urban,ML Engineer,108835,0 +75852,Male,59,High School,6,81,4,94,68,5.0,6,78,Urban,ML Engineer,102699,1 +75853,Male,38,Masters,17,65,46,43,10,9.0,1,64,Urban,HR Executive,50869,0 +75854,Female,46,Masters,19,19,71,83,90,3.0,4,18,Urban,ML Engineer,99240,0 +75855,Male,34,High School,12,47,44,67,16,6.0,3,55,Rural,Data Analyst,68737,0 +75856,Female,43,Bachelors,17,85,47,6,0,6.0,3,24,Urban,Data Analyst,99251,0 +75857,Male,47,Masters,4,72,58,73,0,3.0,7,69,Urban,ML Engineer,146149,1 +75858,Female,43,Bachelors,0,23,21,34,39,4.0,6,8,Urban,ML Engineer,61088,0 +75859,Male,38,Bachelors,3,62,53,43,86,8.0,4,99,Urban,Software Engineer,78691,1 +75860,Male,56,PhD,15,13,78,18,80,6.0,7,3,Semi-Urban,Manager,90998,0 +75861,Female,21,Masters,17,51,75,57,93,1.0,5,19,Urban,Software Engineer,140815,0 +75862,Female,55,Bachelors,8,5,56,20,15,0.0,4,1,Semi-Urban,HR Executive,50692,0 +75863,Female,57,High School,18,31,14,41,85,2.0,5,21,Semi-Urban,HR Executive,86946,0 +75864,Male,27,Diploma,6,95,97,8,21,6.0,0,16,Semi-Urban,ML Engineer,49036,0 +75865,Male,49,High School,11,70,26,79,19,5.0,7,47,Urban,Data Analyst,53211,0 +75866,Female,35,Bachelors,8,91,78,31,31,3.0,5,78,Rural,Software Engineer,127684,1 +75867,Male,23,Diploma,0,63,15,30,23,2.0,7,50,Rural,Software Engineer,116903,0 +75868,Male,49,Diploma,14,11,53,37,92,9.0,3,9,Semi-Urban,HR Executive,118842,0 +75869,Female,55,High School,17,3,85,48,80,1.0,0,87,Semi-Urban,ML Engineer,131990,0 +75870,Male,58,Bachelors,6,59,19,77,73,6.0,0,49,Semi-Urban,HR Executive,66549,0 +75871,Male,57,Bachelors,14,88,89,56,90,8.0,2,69,Urban,ML Engineer,33738,1 +75872,Female,21,Masters,19,62,52,94,83,0.0,6,9,Rural,Software Engineer,103146,0 +75873,Other,52,Diploma,3,42,68,50,12,8.0,0,30,Rural,Data Analyst,71352,0 +75874,Male,49,Bachelors,7,10,56,61,31,5.0,5,0,Rural,HR Executive,42693,0 +75875,Male,24,Masters,7,27,84,94,11,6.0,4,66,Urban,ML Engineer,48096,1 +75876,Male,38,Masters,15,0,47,80,36,4.0,4,0,Urban,Manager,53592,0 +75877,Male,40,Diploma,15,77,98,73,55,8.0,6,55,Rural,Manager,135937,1 +75878,Female,58,Masters,13,5,75,26,38,1.0,0,73,Urban,HR Executive,97806,0 +75879,Male,24,Masters,9,65,28,8,90,5.0,2,29,Semi-Urban,ML Engineer,98241,0 +75880,Male,49,Bachelors,5,86,32,42,73,8.0,1,24,Semi-Urban,Data Analyst,141755,0 +75881,Male,35,High School,8,29,66,78,73,9.0,0,14,Urban,Manager,90171,0 +75882,Male,36,Bachelors,18,1,42,23,52,3.0,7,19,Urban,HR Executive,127379,0 +75883,Male,41,Diploma,14,36,77,13,25,3.0,2,41,Urban,HR Executive,149968,0 +75884,Male,51,High School,15,67,88,28,18,2.0,5,94,Urban,ML Engineer,24461,1 +75885,Female,53,Bachelors,3,33,33,19,66,6.0,2,99,Urban,ML Engineer,147927,0 +75886,Male,39,Diploma,14,60,51,93,55,0.0,5,38,Urban,Manager,109065,1 +75887,Male,38,Bachelors,17,99,37,73,51,5.0,3,80,Rural,HR Executive,51437,1 +75888,Male,25,Diploma,7,60,64,21,86,2.0,2,17,Urban,Data Analyst,40992,0 +75889,Other,37,Bachelors,2,9,9,33,17,2.0,5,6,Urban,Software Engineer,34177,0 +75890,Male,35,Bachelors,10,44,21,48,57,9.0,0,76,Urban,Manager,76143,0 +75891,Male,31,High School,6,92,96,45,72,8.0,6,5,Rural,HR Executive,46681,1 +75892,Male,36,Diploma,17,23,57,33,25,1.0,6,9,Semi-Urban,ML Engineer,117113,0 +75893,Other,55,Diploma,15,98,28,6,27,9.0,6,29,Rural,Manager,43423,0 +75894,Male,34,Diploma,18,78,39,87,63,8.0,6,35,Urban,ML Engineer,115979,1 +75895,Male,30,Bachelors,1,15,40,78,52,6.0,5,28,Urban,Manager,32279,0 +75896,Male,21,Diploma,12,53,76,33,59,3.0,3,96,Rural,Data Analyst,67564,1 +75897,Male,58,Bachelors,6,58,23,49,54,6.0,6,29,Urban,ML Engineer,125341,0 +75898,Male,50,Bachelors,3,42,87,89,45,8.0,1,32,Urban,Manager,109452,1 +75899,Female,35,Bachelors,15,17,5,32,59,2.0,4,79,Rural,ML Engineer,58573,0 +75900,Female,34,Diploma,4,66,82,18,65,3.0,0,63,Rural,HR Executive,116730,0 +75901,Female,37,Bachelors,1,50,66,28,17,8.0,5,32,Semi-Urban,Data Analyst,107401,0 +75902,Female,32,Bachelors,12,87,44,58,7,3.0,1,80,Rural,Manager,104452,1 +75903,Male,31,High School,9,68,77,43,46,9.0,7,12,Semi-Urban,ML Engineer,113145,0 +75904,Male,43,Bachelors,12,25,66,36,43,4.0,0,35,Rural,HR Executive,81675,0 +75905,Female,29,High School,1,79,63,97,31,8.0,7,9,Urban,Software Engineer,112295,1 +75906,Male,51,Masters,7,40,94,92,38,9.0,3,97,Urban,ML Engineer,43591,1 +75907,Female,31,Diploma,1,1,69,73,17,2.0,2,5,Urban,Manager,84892,0 +75908,Female,30,Masters,1,35,28,88,95,6.0,1,62,Urban,Manager,69372,0 +75909,Male,27,Bachelors,9,79,50,70,86,7.0,6,71,Urban,HR Executive,57279,1 +75910,Female,54,Bachelors,1,84,34,47,88,0.0,4,68,Semi-Urban,ML Engineer,67990,0 +75911,Male,26,High School,10,67,55,66,73,6.0,5,11,Semi-Urban,ML Engineer,148743,0 +75912,Male,52,Masters,8,20,90,54,28,7.0,3,61,Urban,Data Analyst,132599,0 +75913,Female,48,Diploma,15,33,29,98,52,5.0,5,89,Urban,ML Engineer,70191,1 +75914,Male,46,Masters,2,85,6,53,28,7.0,7,15,Semi-Urban,Data Analyst,118834,0 +75915,Male,29,Masters,15,40,41,37,64,4.0,6,94,Urban,ML Engineer,64976,0 +75916,Male,54,Bachelors,10,82,88,97,80,6.0,1,11,Urban,ML Engineer,44881,1 +75917,Male,35,Diploma,12,97,50,35,60,6.0,0,56,Semi-Urban,ML Engineer,109106,1 +75918,Male,31,Masters,6,59,21,53,66,7.0,4,88,Urban,Software Engineer,25886,0 +75919,Female,23,High School,4,86,71,2,1,9.0,6,48,Urban,Manager,28375,0 +75920,Female,48,Bachelors,11,14,64,17,89,4.0,1,26,Urban,HR Executive,73769,0 +75921,Female,38,Masters,8,17,43,50,24,9.0,1,91,Urban,Manager,20008,0 +75922,Male,35,Diploma,13,34,16,85,65,0.0,6,6,Semi-Urban,Manager,117034,0 +75923,Male,32,Diploma,18,93,44,22,11,8.0,3,30,Urban,Manager,147735,0 +75924,Male,34,Masters,2,74,50,38,46,3.0,6,37,Semi-Urban,HR Executive,50723,0 +75925,Female,21,Bachelors,17,59,70,11,39,9.0,3,34,Urban,Data Analyst,110757,0 +75926,Male,38,High School,10,48,29,41,5,7.0,2,15,Urban,Manager,99876,0 +75927,Male,59,Bachelors,12,68,14,11,45,6.0,1,18,Urban,Software Engineer,97478,0 +75928,Male,29,PhD,2,53,95,80,1,4.0,6,15,Urban,HR Executive,55730,1 +75929,Male,36,High School,5,54,75,91,7,1.0,7,55,Semi-Urban,HR Executive,35890,1 +75930,Female,45,Masters,7,6,35,94,63,3.0,4,75,Semi-Urban,Data Analyst,52953,0 +75931,Male,34,PhD,5,73,95,39,70,5.0,6,47,Urban,HR Executive,96115,1 +75932,Female,44,High School,18,27,59,15,91,4.0,3,48,Rural,ML Engineer,120503,0 +75933,Other,29,Diploma,15,42,97,60,9,4.0,6,99,Urban,ML Engineer,23668,1 +75934,Female,54,Diploma,14,58,11,78,43,5.0,7,53,Semi-Urban,Data Analyst,85502,0 +75935,Male,58,Diploma,11,88,57,92,36,7.0,3,17,Semi-Urban,Software Engineer,91348,1 +75936,Male,34,Diploma,12,77,64,75,18,8.0,5,70,Urban,Manager,71796,1 +75937,Female,39,Bachelors,14,62,50,50,81,3.0,5,97,Urban,ML Engineer,143001,1 +75938,Other,46,Diploma,19,87,22,65,3,1.0,0,9,Semi-Urban,ML Engineer,110539,0 +75939,Female,25,Bachelors,9,58,54,95,79,3.0,0,68,Urban,Software Engineer,91260,1 +75940,Male,33,Masters,12,14,93,41,20,7.0,6,8,Urban,ML Engineer,141000,0 +75941,Male,36,High School,9,30,5,97,27,0.0,3,99,Urban,Manager,60621,0 +75942,Male,39,Masters,2,0,91,11,53,7.0,3,13,Urban,HR Executive,118999,0 +75943,Male,47,High School,3,33,8,97,17,0.0,6,26,Rural,Data Analyst,140732,0 +75944,Male,46,Masters,2,96,72,53,48,2.0,0,7,Urban,Data Analyst,133345,0 +75945,Female,56,High School,1,72,75,38,94,5.0,3,69,Urban,HR Executive,98213,1 +75946,Male,33,Bachelors,17,47,25,18,43,1.0,2,24,Rural,ML Engineer,112275,0 +75947,Male,46,Diploma,4,41,93,57,64,3.0,4,97,Urban,Manager,147411,1 +75948,Male,56,Masters,15,21,63,20,20,1.0,2,97,Urban,Data Analyst,42021,0 +75949,Male,47,Bachelors,12,96,73,92,6,3.0,3,66,Semi-Urban,Data Analyst,70196,1 +75950,Male,33,Masters,12,42,0,18,12,7.0,3,71,Urban,ML Engineer,98579,0 +75951,Female,43,Masters,1,65,83,47,29,4.0,5,98,Urban,HR Executive,47461,1 +75952,Female,55,Diploma,13,82,8,46,62,3.0,4,4,Semi-Urban,HR Executive,139261,0 +75953,Male,50,Diploma,14,28,10,71,5,4.0,4,38,Semi-Urban,Manager,35161,0 +75954,Female,46,Masters,12,10,86,20,35,3.0,0,9,Semi-Urban,Software Engineer,70822,0 +75955,Male,25,Diploma,17,32,26,84,28,6.0,3,65,Urban,ML Engineer,23753,0 +75956,Female,37,Bachelors,11,14,97,9,66,1.0,4,35,Urban,Software Engineer,81430,0 +75957,Male,40,Masters,2,1,5,86,82,1.0,3,4,Rural,ML Engineer,106302,0 +75958,Male,41,High School,16,5,29,19,47,1.0,4,44,Semi-Urban,Manager,125933,0 +75959,Male,28,Masters,6,54,50,92,43,3.0,2,71,Semi-Urban,Data Analyst,142224,1 +75960,Male,38,Bachelors,3,50,22,67,38,2.0,7,69,Semi-Urban,HR Executive,106607,0 +75961,Male,23,PhD,2,29,79,40,84,1.0,5,45,Urban,Software Engineer,96743,0 +75962,Female,35,Bachelors,2,6,75,16,43,3.0,4,11,Urban,ML Engineer,88746,0 +75963,Male,41,Masters,3,53,44,46,51,6.0,2,26,Urban,Software Engineer,75383,0 +75964,Male,30,Diploma,4,87,84,94,27,3.0,4,54,Urban,HR Executive,136377,1 +75965,Female,38,PhD,5,65,50,71,50,1.0,3,75,Urban,Software Engineer,147697,1 +75966,Female,26,Diploma,16,18,1,29,80,9.0,1,17,Rural,Manager,144435,0 +75967,Male,22,Bachelors,17,6,78,10,1,6.0,1,81,Semi-Urban,HR Executive,49305,0 +75968,Male,29,Masters,0,81,76,29,41,1.0,4,62,Urban,ML Engineer,83267,1 +75969,Female,52,High School,14,20,32,9,29,6.0,4,68,Urban,Data Analyst,38147,0 +75970,Female,24,Bachelors,13,27,3,87,12,2.0,6,96,Urban,HR Executive,140282,0 +75971,Female,46,High School,8,47,74,50,81,1.0,7,18,Urban,Manager,79897,0 +75972,Male,55,Diploma,9,24,49,13,42,2.0,7,53,Urban,ML Engineer,116262,0 +75973,Male,40,Masters,15,86,38,1,58,7.0,3,16,Semi-Urban,ML Engineer,97575,0 +75974,Male,29,Bachelors,2,87,89,55,15,5.0,7,14,Semi-Urban,HR Executive,28612,1 +75975,Male,53,High School,11,3,57,52,33,2.0,4,41,Semi-Urban,ML Engineer,38961,0 +75976,Female,34,Masters,9,36,96,9,56,6.0,0,17,Urban,Data Analyst,127752,0 +75977,Female,55,Masters,9,83,57,43,26,2.0,3,47,Urban,ML Engineer,42488,0 +75978,Female,30,High School,12,5,89,3,86,1.0,1,50,Rural,Data Analyst,92694,0 +75979,Male,32,High School,18,42,32,32,30,0.0,3,38,Urban,ML Engineer,25969,0 +75980,Male,31,Bachelors,11,82,36,65,75,7.0,6,84,Urban,Data Analyst,49704,1 +75981,Female,40,Bachelors,12,86,23,10,61,1.0,7,31,Rural,HR Executive,51509,0 +75982,Female,32,Diploma,3,11,30,30,72,8.0,2,40,Urban,ML Engineer,101653,0 +75983,Male,56,Bachelors,10,92,21,69,59,5.0,7,56,Urban,ML Engineer,86539,1 +75984,Female,50,Masters,1,67,42,99,1,8.0,4,78,Urban,Data Analyst,24243,1 +75985,Male,39,Bachelors,13,82,97,50,12,1.0,7,36,Urban,Software Engineer,28933,1 +75986,Male,46,Masters,0,16,84,49,97,1.0,1,29,Urban,Manager,148407,0 +75987,Male,49,Masters,1,98,96,28,9,5.0,3,97,Semi-Urban,HR Executive,139999,1 +75988,Male,31,Masters,2,91,9,29,70,0.0,7,94,Urban,Manager,104249,0 +75989,Male,35,Bachelors,17,52,89,82,64,4.0,5,51,Urban,Data Analyst,89748,1 +75990,Female,51,Bachelors,6,23,99,42,45,9.0,1,71,Semi-Urban,Data Analyst,129655,0 +75991,Female,34,Masters,18,54,18,33,99,3.0,3,51,Rural,Manager,138619,0 +75992,Male,39,Bachelors,6,29,21,79,11,3.0,4,13,Urban,Software Engineer,79373,0 +75993,Female,46,Diploma,4,12,63,85,7,2.0,3,83,Semi-Urban,Data Analyst,112191,1 +75994,Male,45,PhD,6,71,40,72,13,0.0,7,31,Urban,ML Engineer,133452,0 +75995,Female,48,Diploma,4,97,97,76,28,9.0,0,26,Urban,Data Analyst,102188,1 +75996,Male,25,Bachelors,3,43,91,85,96,4.0,4,43,Urban,Manager,68304,1 +75997,Male,44,Masters,14,38,14,52,73,8.0,3,62,Rural,Data Analyst,123305,0 +75998,Female,52,High School,9,41,50,29,57,3.0,2,49,Semi-Urban,Software Engineer,123845,0 +75999,Female,46,Masters,5,34,87,54,61,6.0,7,67,Semi-Urban,Data Analyst,125847,1 +76000,Male,40,Masters,17,26,99,69,95,0.0,7,70,Urban,HR Executive,63526,1 +76001,Female,29,Bachelors,13,60,38,67,34,2.0,1,33,Rural,Manager,48791,0 +76002,Male,27,High School,7,58,70,4,63,7.0,5,80,Urban,Manager,131411,0 +76003,Female,24,Diploma,0,27,38,75,80,0.0,3,23,Semi-Urban,ML Engineer,123609,0 +76004,Female,27,Bachelors,5,62,32,41,76,3.0,6,90,Rural,Data Analyst,113445,0 +76005,Male,48,Diploma,12,2,41,1,55,3.0,6,72,Semi-Urban,Manager,47352,0 +76006,Female,40,High School,3,49,70,15,88,3.0,0,68,Urban,Data Analyst,148110,0 +76007,Male,51,Bachelors,1,29,44,30,22,9.0,3,26,Semi-Urban,Software Engineer,94205,0 +76008,Male,22,Masters,8,18,47,45,83,9.0,2,17,Urban,Manager,89105,0 +76009,Male,30,Bachelors,9,90,59,95,39,9.0,0,74,Rural,Software Engineer,130156,1 +76010,Female,57,Masters,18,4,49,58,63,5.0,1,63,Semi-Urban,Data Analyst,37129,0 +76011,Male,23,Masters,7,24,23,15,15,8.0,6,91,Rural,Software Engineer,115004,0 +76012,Male,56,Masters,17,29,87,52,29,9.0,4,29,Urban,ML Engineer,38133,0 +76013,Female,49,Masters,9,69,31,27,77,7.0,0,88,Urban,ML Engineer,136540,0 +76014,Female,44,Bachelors,12,57,9,37,53,3.0,2,88,Urban,ML Engineer,124283,0 +76015,Female,40,Bachelors,16,46,28,91,50,6.0,2,52,Urban,Data Analyst,48527,0 +76016,Female,22,Bachelors,4,94,29,29,73,5.0,5,84,Urban,ML Engineer,35467,0 +76017,Male,42,Bachelors,12,66,68,87,60,8.0,4,98,Urban,ML Engineer,109396,1 +76018,Female,59,PhD,9,13,19,43,23,7.0,7,21,Urban,Manager,127787,0 +76019,Female,42,High School,16,18,8,5,82,1.0,6,1,Urban,HR Executive,136599,0 +76020,Female,32,Bachelors,19,78,96,19,72,5.0,2,61,Semi-Urban,HR Executive,78938,1 +76021,Male,21,Masters,11,57,43,84,75,0.0,0,70,Urban,Data Analyst,99910,1 +76022,Male,35,High School,16,49,3,45,46,2.0,0,66,Urban,HR Executive,57514,0 +76023,Male,57,Bachelors,1,24,73,60,44,5.0,4,11,Urban,Data Analyst,131267,0 +76024,Female,47,Bachelors,0,93,65,99,36,9.0,2,88,Rural,Manager,22666,1 +76025,Male,53,Bachelors,10,73,38,69,91,5.0,5,12,Urban,ML Engineer,132758,0 +76026,Male,29,Bachelors,9,34,76,37,71,4.0,4,30,Semi-Urban,Software Engineer,23718,0 +76027,Female,44,Diploma,11,66,44,62,51,0.0,4,68,Semi-Urban,Manager,48024,0 +76028,Female,51,Bachelors,3,69,84,73,71,5.0,2,48,Rural,ML Engineer,103408,1 +76029,Male,42,High School,19,27,93,36,66,2.0,3,31,Rural,Manager,55386,0 +76030,Male,51,Diploma,9,87,49,23,54,3.0,2,18,Semi-Urban,HR Executive,33850,0 +76031,Female,43,Diploma,12,16,52,69,2,9.0,5,5,Urban,Manager,45240,0 +76032,Male,25,Masters,7,6,30,74,78,1.0,7,37,Rural,Software Engineer,120140,0 +76033,Female,46,Bachelors,1,53,57,17,91,1.0,4,48,Rural,ML Engineer,147264,0 +76034,Female,33,Bachelors,15,30,39,15,95,3.0,1,46,Semi-Urban,ML Engineer,86350,0 +76035,Female,54,Masters,10,52,95,64,8,1.0,6,32,Rural,Software Engineer,62315,1 +76036,Male,52,Diploma,19,36,75,56,45,5.0,7,48,Urban,Data Analyst,120947,0 +76037,Male,41,Bachelors,1,17,72,7,46,2.0,0,54,Urban,Software Engineer,34753,0 +76038,Female,35,Masters,6,61,25,52,9,9.0,0,6,Urban,HR Executive,69903,0 +76039,Male,38,Masters,16,11,46,85,65,8.0,1,75,Urban,HR Executive,20775,0 +76040,Female,46,Masters,0,34,61,98,21,0.0,0,22,Urban,HR Executive,73610,0 +76041,Male,58,High School,18,92,14,36,64,3.0,4,24,Semi-Urban,Data Analyst,109728,0 +76042,Female,43,Bachelors,16,1,96,13,0,7.0,7,21,Semi-Urban,Data Analyst,72479,0 +76043,Male,50,Masters,18,67,92,21,4,5.0,2,49,Rural,Data Analyst,75870,0 +76044,Male,32,Masters,1,91,73,10,55,8.0,0,69,Urban,HR Executive,139286,1 +76045,Female,26,High School,11,84,18,27,69,4.0,5,72,Semi-Urban,HR Executive,78336,0 +76046,Female,56,Diploma,1,58,99,78,86,6.0,7,86,Semi-Urban,Manager,95445,1 +76047,Female,21,PhD,1,94,96,72,64,8.0,3,43,Urban,HR Executive,145758,1 +76048,Male,25,Diploma,10,5,34,33,49,9.0,0,60,Urban,Data Analyst,95836,0 +76049,Male,53,PhD,4,39,64,34,33,8.0,1,75,Rural,Manager,37088,0 +76050,Female,56,Bachelors,1,21,39,9,18,9.0,2,37,Urban,ML Engineer,73399,0 +76051,Male,33,Bachelors,2,75,2,57,24,5.0,2,53,Urban,Data Analyst,125521,0 +76052,Female,39,Masters,7,19,46,10,27,1.0,1,79,Semi-Urban,ML Engineer,42978,0 +76053,Other,33,Masters,2,88,11,0,77,7.0,4,16,Rural,Software Engineer,136577,0 +76054,Female,22,Masters,15,63,45,22,73,2.0,1,26,Semi-Urban,Manager,126623,0 +76055,Male,52,Bachelors,0,71,12,77,75,6.0,1,8,Urban,Data Analyst,62802,0 +76056,Female,54,Diploma,5,91,13,8,62,4.0,1,25,Urban,ML Engineer,63530,0 +76057,Male,55,Bachelors,15,47,50,17,39,0.0,6,72,Semi-Urban,Software Engineer,60170,0 +76058,Male,42,High School,2,60,45,63,17,7.0,4,0,Urban,Software Engineer,142878,0 +76059,Male,24,Bachelors,12,43,76,94,31,9.0,2,51,Urban,HR Executive,131339,1 +76060,Male,32,Diploma,18,89,22,60,95,3.0,1,86,Urban,Data Analyst,96354,1 +76061,Female,29,Bachelors,7,25,25,38,71,4.0,2,45,Semi-Urban,ML Engineer,45345,0 +76062,Male,48,Bachelors,13,98,16,44,53,2.0,3,38,Semi-Urban,ML Engineer,93416,0 +76063,Male,47,Bachelors,12,6,7,94,54,8.0,7,29,Urban,Manager,93991,0 +76064,Male,24,Bachelors,9,35,83,61,86,6.0,2,19,Urban,HR Executive,78627,0 +76065,Female,35,High School,8,95,18,30,88,5.0,5,71,Urban,Software Engineer,109034,0 +76066,Male,25,Bachelors,9,49,98,29,7,3.0,3,73,Urban,Data Analyst,115559,1 +76067,Male,23,High School,5,57,60,93,96,6.0,7,26,Semi-Urban,HR Executive,124038,1 +76068,Male,36,High School,4,5,21,37,43,2.0,7,35,Semi-Urban,ML Engineer,104898,0 +76069,Male,37,Masters,18,96,31,88,14,8.0,1,68,Urban,Software Engineer,90925,1 +76070,Male,40,Diploma,2,82,6,18,23,7.0,3,20,Urban,Software Engineer,94880,0 +76071,Other,37,Masters,10,95,71,79,85,3.0,1,58,Urban,Software Engineer,38475,1 +76072,Female,31,Diploma,17,94,3,62,63,3.0,0,97,Rural,Manager,37936,1 +76073,Male,38,Bachelors,2,53,7,4,3,2.0,3,6,Urban,Manager,115156,0 +76074,Female,27,Bachelors,1,67,98,25,47,5.0,5,47,Semi-Urban,Software Engineer,116524,0 +76075,Male,33,High School,10,72,29,45,35,6.0,5,41,Urban,Manager,120318,0 +76076,Female,22,Bachelors,1,53,79,15,85,9.0,6,48,Urban,ML Engineer,132308,0 +76077,Male,22,Masters,7,18,12,57,52,8.0,1,91,Rural,Manager,131906,0 +76078,Male,52,Diploma,6,54,89,49,73,6.0,0,75,Urban,HR Executive,116362,1 +76079,Female,47,Bachelors,2,4,30,7,11,1.0,6,4,Urban,HR Executive,118817,0 +76080,Female,41,Diploma,1,89,82,25,75,6.0,4,87,Urban,Data Analyst,51230,1 +76081,Male,58,Masters,0,78,43,26,61,4.0,2,80,Urban,Software Engineer,41146,0 +76082,Male,50,Bachelors,18,45,50,3,95,8.0,6,70,Urban,HR Executive,32277,0 +76083,Female,31,Bachelors,17,11,87,89,78,2.0,1,30,Urban,Data Analyst,83837,0 +76084,Male,39,Bachelors,10,2,18,55,41,0.0,0,10,Urban,Data Analyst,148586,0 +76085,Male,30,Bachelors,3,39,81,79,72,0.0,4,25,Urban,ML Engineer,33277,0 +76086,Female,32,Masters,7,82,89,3,88,1.0,7,6,Urban,HR Executive,106838,0 +76087,Male,24,Bachelors,2,13,94,84,82,1.0,6,19,Urban,ML Engineer,82597,0 +76088,Male,36,Masters,16,21,46,11,19,9.0,0,90,Urban,Data Analyst,49655,0 +76089,Female,25,Bachelors,3,66,80,88,46,2.0,6,46,Semi-Urban,Software Engineer,103356,1 +76090,Male,25,Bachelors,9,51,91,84,23,4.0,4,4,Urban,Software Engineer,84690,0 +76091,Female,52,Bachelors,13,62,8,33,7,4.0,7,59,Rural,Manager,145744,0 +76092,Female,23,Masters,13,91,97,14,95,6.0,3,79,Urban,Data Analyst,123028,1 +76093,Male,48,Bachelors,9,30,49,66,64,7.0,7,90,Urban,Data Analyst,142887,1 +76094,Male,33,Masters,7,62,95,15,52,1.0,1,9,Urban,HR Executive,73516,0 +76095,Other,52,High School,9,8,5,4,77,2.0,7,66,Semi-Urban,Manager,103701,0 +76096,Male,30,Bachelors,9,18,29,86,2,8.0,2,83,Urban,Manager,144291,0 +76097,Other,34,Bachelors,16,53,21,94,19,2.0,0,89,Urban,Software Engineer,114223,1 +76098,Male,28,Masters,14,3,3,66,34,8.0,0,84,Urban,Manager,28285,0 +76099,Male,37,Diploma,13,10,91,43,2,8.0,7,90,Urban,Manager,51093,0 +76100,Female,21,Diploma,7,55,24,45,42,2.0,1,77,Semi-Urban,ML Engineer,89513,0 +76101,Female,55,Masters,5,36,63,23,75,6.0,2,90,Urban,ML Engineer,61088,0 +76102,Female,21,Bachelors,16,61,23,69,87,4.0,7,28,Urban,Software Engineer,127779,0 +76103,Male,24,Masters,9,92,51,72,33,3.0,0,99,Rural,Manager,121787,1 +76104,Male,56,High School,11,71,50,55,59,5.0,5,69,Semi-Urban,ML Engineer,57826,1 +76105,Male,49,High School,15,25,96,88,93,4.0,4,36,Urban,ML Engineer,84515,1 +76106,Male,39,Diploma,15,8,60,98,88,6.0,6,39,Urban,ML Engineer,114767,0 +76107,Female,31,Bachelors,11,26,80,91,18,7.0,7,36,Semi-Urban,Data Analyst,63967,0 +76108,Female,40,Bachelors,18,71,81,26,41,8.0,1,78,Urban,Data Analyst,80503,1 +76109,Female,48,Diploma,18,66,32,58,76,3.0,1,60,Semi-Urban,Software Engineer,87801,0 +76110,Male,54,Bachelors,19,90,91,82,86,0.0,3,66,Urban,Software Engineer,35010,1 +76111,Male,49,High School,15,38,27,92,38,2.0,1,78,Semi-Urban,Software Engineer,103145,1 +76112,Male,32,Masters,14,86,41,9,68,3.0,5,9,Rural,Manager,41628,0 +76113,Female,36,Bachelors,6,19,76,19,15,7.0,6,53,Semi-Urban,Manager,58935,0 +76114,Female,49,Bachelors,9,64,0,95,18,7.0,3,44,Rural,Manager,40869,0 +76115,Female,35,Diploma,19,59,22,19,57,5.0,6,82,Urban,Software Engineer,45409,0 +76116,Female,31,High School,15,99,86,80,65,6.0,3,11,Semi-Urban,Software Engineer,41974,1 +76117,Other,31,High School,8,67,69,36,78,8.0,0,37,Urban,ML Engineer,86405,0 +76118,Female,43,Bachelors,14,94,51,1,62,1.0,1,48,Urban,ML Engineer,111293,0 +76119,Female,51,Diploma,5,14,6,87,47,4.0,2,24,Semi-Urban,Data Analyst,44502,0 +76120,Male,55,Bachelors,8,23,35,16,47,1.0,1,89,Urban,ML Engineer,52963,0 +76121,Female,57,Diploma,5,44,99,34,51,1.0,2,89,Rural,Software Engineer,145982,1 +76122,Male,49,Bachelors,9,19,73,91,44,4.0,5,43,Urban,ML Engineer,95728,0 +76123,Female,37,Bachelors,12,16,43,63,79,0.0,3,57,Urban,ML Engineer,66583,0 +76124,Female,54,Bachelors,6,29,6,91,6,5.0,2,53,Urban,ML Engineer,101600,0 +76125,Female,46,PhD,3,4,42,22,74,4.0,6,9,Urban,Data Analyst,61771,0 +76126,Female,54,Bachelors,10,92,98,17,50,2.0,3,59,Rural,ML Engineer,124712,1 +76127,Female,31,Bachelors,3,91,60,86,24,8.0,5,20,Urban,Manager,61239,1 +76128,Female,46,Bachelors,15,84,63,3,91,7.0,1,27,Urban,Software Engineer,26635,0 +76129,Female,47,Diploma,8,86,97,56,79,8.0,5,13,Semi-Urban,HR Executive,64400,1 +76130,Female,21,Bachelors,15,99,70,89,46,8.0,4,27,Urban,ML Engineer,130033,1 +76131,Male,54,Bachelors,4,62,84,10,22,1.0,7,51,Semi-Urban,Manager,60206,0 +76132,Male,52,Diploma,6,0,68,15,3,3.0,5,3,Semi-Urban,HR Executive,85712,0 +76133,Male,27,High School,10,59,57,15,37,3.0,7,78,Urban,Manager,148177,0 +76134,Male,21,High School,14,72,69,19,34,7.0,4,11,Semi-Urban,HR Executive,71956,0 +76135,Male,56,Bachelors,14,24,62,76,53,3.0,1,58,Urban,ML Engineer,138278,0 +76136,Female,31,Diploma,15,92,7,34,12,0.0,4,78,Semi-Urban,HR Executive,115343,0 +76137,Female,21,Bachelors,13,1,81,24,83,4.0,2,40,Urban,ML Engineer,94690,0 +76138,Male,30,Bachelors,3,97,60,40,64,7.0,5,90,Urban,HR Executive,135369,1 +76139,Female,55,Bachelors,16,21,48,96,93,1.0,7,37,Rural,Data Analyst,35859,0 +76140,Male,56,Bachelors,4,38,39,30,67,7.0,0,87,Urban,HR Executive,54526,0 +76141,Female,33,Bachelors,1,3,15,88,71,2.0,0,38,Rural,Software Engineer,34018,0 +76142,Female,27,Bachelors,2,97,52,39,39,3.0,4,60,Urban,ML Engineer,126317,1 +76143,Female,35,Bachelors,16,54,67,93,15,5.0,7,84,Urban,Manager,100259,1 +76144,Male,52,Masters,2,50,55,50,45,3.0,7,86,Urban,Data Analyst,95935,1 +76145,Male,32,PhD,8,48,53,27,80,6.0,5,7,Urban,Manager,120988,0 +76146,Female,45,Bachelors,3,80,3,67,54,0.0,1,8,Rural,ML Engineer,47034,0 +76147,Male,33,Bachelors,3,28,93,54,10,0.0,5,16,Urban,Data Analyst,70273,0 +76148,Male,23,Bachelors,1,52,61,74,13,5.0,0,46,Urban,Data Analyst,106339,0 +76149,Male,29,Bachelors,5,80,33,82,30,8.0,7,85,Urban,ML Engineer,135188,1 +76150,Female,49,Bachelors,18,82,85,62,29,7.0,5,7,Semi-Urban,Manager,141840,0 +76151,Male,36,Bachelors,16,91,29,61,15,7.0,2,57,Rural,Manager,103146,1 +76152,Female,57,Diploma,0,4,50,19,77,3.0,3,34,Urban,Data Analyst,27326,0 +76153,Female,25,Diploma,8,1,91,80,10,1.0,7,97,Urban,ML Engineer,22918,1 +76154,Female,30,High School,18,21,72,51,34,1.0,4,79,Urban,Data Analyst,42713,0 +76155,Male,25,Bachelors,18,20,38,91,6,0.0,1,80,Urban,ML Engineer,26249,0 +76156,Female,33,Diploma,3,9,7,24,17,3.0,3,74,Semi-Urban,Data Analyst,139535,0 +76157,Male,56,Masters,12,67,31,5,91,6.0,2,3,Semi-Urban,ML Engineer,113675,0 +76158,Male,46,Bachelors,8,1,63,29,89,1.0,0,34,Urban,ML Engineer,140327,0 +76159,Male,54,Diploma,15,12,25,1,58,6.0,6,52,Urban,ML Engineer,119780,0 +76160,Male,52,Masters,17,93,6,53,69,8.0,5,3,Urban,Data Analyst,141948,0 +76161,Female,34,Bachelors,13,81,13,34,82,0.0,0,44,Rural,ML Engineer,69313,0 +76162,Male,46,High School,0,27,53,52,53,5.0,5,78,Urban,Software Engineer,103691,0 +76163,Female,46,PhD,5,86,58,21,6,6.0,6,46,Urban,Manager,135326,0 +76164,Female,23,High School,9,87,40,59,99,0.0,2,90,Urban,Data Analyst,29535,1 +76165,Male,58,Masters,7,15,55,63,27,9.0,7,58,Urban,ML Engineer,122546,0 +76166,Male,26,Masters,8,12,92,54,88,9.0,5,59,Urban,ML Engineer,79413,0 +76167,Female,24,Bachelors,15,76,91,87,51,2.0,7,88,Urban,Manager,61148,1 +76168,Male,57,High School,11,36,38,51,67,9.0,5,35,Semi-Urban,Data Analyst,94479,0 +76169,Male,56,Masters,9,59,38,52,64,3.0,3,2,Urban,HR Executive,94797,0 +76170,Male,35,Bachelors,3,77,66,26,39,0.0,2,19,Urban,ML Engineer,133207,0 +76171,Male,24,High School,16,14,50,32,49,0.0,0,34,Rural,Software Engineer,103274,0 +76172,Male,40,High School,16,60,9,44,53,5.0,3,62,Semi-Urban,Data Analyst,49438,0 +76173,Male,21,High School,13,33,78,28,57,1.0,0,12,Semi-Urban,Data Analyst,22944,0 +76174,Female,23,High School,3,73,15,85,59,5.0,5,55,Rural,ML Engineer,57990,0 +76175,Female,25,Bachelors,5,5,33,12,93,9.0,6,17,Semi-Urban,Manager,58064,0 +76176,Male,28,Masters,17,13,84,40,55,3.0,1,60,Semi-Urban,Data Analyst,92451,0 +76177,Male,35,Diploma,7,42,67,7,21,7.0,0,37,Urban,HR Executive,68449,0 +76178,Male,51,Bachelors,13,24,82,60,92,6.0,2,83,Rural,Data Analyst,21468,1 +76179,Male,32,Masters,8,26,3,84,90,6.0,4,2,Semi-Urban,Data Analyst,75343,0 +76180,Male,28,Bachelors,11,58,50,67,25,4.0,2,25,Semi-Urban,Software Engineer,82216,0 +76181,Male,46,Bachelors,6,80,2,57,66,8.0,2,78,Urban,Data Analyst,25177,0 +76182,Female,46,Bachelors,7,22,38,99,9,8.0,5,12,Semi-Urban,Manager,89173,0 +76183,Other,24,Bachelors,11,71,68,90,87,9.0,4,46,Semi-Urban,Software Engineer,135346,1 +76184,Male,22,Bachelors,11,74,8,69,85,7.0,2,42,Urban,Software Engineer,126719,0 +76185,Male,28,Diploma,9,45,67,66,73,0.0,7,80,Rural,HR Executive,71447,1 +76186,Male,26,Masters,3,17,58,76,93,3.0,3,15,Urban,Software Engineer,60752,0 +76187,Female,50,High School,4,59,66,98,84,7.0,5,8,Semi-Urban,Data Analyst,104840,0 +76188,Male,39,Masters,18,90,58,90,30,8.0,5,86,Urban,Software Engineer,57391,1 +76189,Male,26,Bachelors,14,44,13,72,3,4.0,6,44,Semi-Urban,HR Executive,133969,0 +76190,Female,45,Bachelors,2,79,32,70,36,9.0,7,17,Rural,ML Engineer,41945,0 +76191,Female,31,Bachelors,15,62,16,7,71,0.0,5,3,Urban,Software Engineer,21172,0 +76192,Male,42,High School,18,34,18,72,65,8.0,6,62,Semi-Urban,Manager,87126,0 +76193,Female,30,Diploma,11,71,61,34,78,0.0,3,15,Urban,HR Executive,147556,0 +76194,Female,45,Masters,13,30,50,30,62,3.0,2,90,Semi-Urban,Data Analyst,116547,0 +76195,Male,48,High School,18,12,37,94,61,4.0,2,20,Urban,HR Executive,44148,0 +76196,Male,40,High School,3,57,42,50,25,9.0,5,24,Semi-Urban,Manager,75181,0 +76197,Other,50,High School,3,11,13,39,82,6.0,6,56,Semi-Urban,Manager,79282,0 +76198,Female,49,Masters,19,26,68,60,60,0.0,6,54,Urban,Data Analyst,38367,0 +76199,Male,39,PhD,11,73,87,83,51,4.0,2,59,Urban,Data Analyst,72462,1 +76200,Male,45,Bachelors,9,4,20,20,79,0.0,4,36,Semi-Urban,ML Engineer,45895,0 +76201,Male,42,Diploma,1,89,1,97,36,9.0,0,48,Urban,Software Engineer,76875,1 +76202,Female,39,Bachelors,12,12,52,53,18,6.0,2,97,Urban,Software Engineer,62061,0 +76203,Male,25,Diploma,0,96,18,43,48,5.0,1,38,Rural,Software Engineer,128400,0 +76204,Male,35,Masters,5,75,71,46,3,9.0,2,98,Urban,ML Engineer,58057,1 +76205,Male,52,Bachelors,1,2,13,75,41,6.0,0,35,Urban,HR Executive,133207,0 +76206,Other,24,Bachelors,7,17,15,1,4,2.0,5,26,Urban,Manager,24624,0 +76207,Female,27,Masters,12,83,4,81,27,9.0,4,14,Urban,Data Analyst,20210,0 +76208,Male,58,High School,3,65,70,36,70,5.0,6,58,Rural,Software Engineer,61918,0 +76209,Male,44,Diploma,1,71,31,89,33,6.0,1,88,Urban,HR Executive,69722,1 +76210,Male,50,Bachelors,18,98,86,25,89,2.0,7,9,Semi-Urban,ML Engineer,38473,0 +76211,Male,56,Masters,13,66,95,4,9,1.0,1,68,Semi-Urban,ML Engineer,76386,0 +76212,Female,49,High School,4,27,49,64,99,5.0,5,92,Semi-Urban,HR Executive,29836,0 +76213,Female,41,Bachelors,5,52,78,36,0,3.0,0,1,Urban,Manager,28752,0 +76214,Male,25,Bachelors,12,39,17,52,85,3.0,0,21,Semi-Urban,HR Executive,37076,0 +76215,Female,47,Bachelors,12,27,88,98,14,4.0,6,4,Urban,ML Engineer,87217,0 +76216,Female,28,High School,15,15,52,33,42,7.0,0,35,Semi-Urban,Software Engineer,30874,0 +76217,Male,31,Diploma,18,93,41,55,70,2.0,6,86,Rural,ML Engineer,98767,1 +76218,Female,47,Bachelors,10,54,67,68,78,5.0,0,69,Urban,ML Engineer,70489,1 +76219,Female,29,Bachelors,7,82,18,50,19,4.0,5,41,Rural,Data Analyst,98571,0 +76220,Male,29,Bachelors,2,9,75,51,74,8.0,5,42,Rural,Manager,61357,0 +76221,Female,37,High School,11,95,18,13,63,6.0,4,94,Urban,Software Engineer,98585,0 +76222,Male,45,High School,16,79,82,94,6,9.0,1,24,Urban,Software Engineer,135257,1 +76223,Female,33,Bachelors,16,45,52,95,68,1.0,6,25,Rural,ML Engineer,77295,0 +76224,Male,56,Bachelors,2,49,82,64,72,3.0,3,6,Urban,Manager,110829,0 +76225,Female,39,Masters,16,40,78,54,23,7.0,6,64,Semi-Urban,Software Engineer,58832,0 +76226,Male,52,High School,1,1,13,81,22,1.0,0,54,Urban,Data Analyst,35819,0 +76227,Male,37,Masters,16,53,86,59,4,2.0,7,62,Semi-Urban,Manager,91347,1 +76228,Female,34,Bachelors,17,70,41,0,30,9.0,7,33,Semi-Urban,HR Executive,95036,0 +76229,Female,58,Bachelors,14,34,22,73,61,5.0,6,54,Urban,Manager,95213,0 +76230,Male,24,Masters,9,80,63,97,69,2.0,5,33,Semi-Urban,HR Executive,90366,1 +76231,Male,42,Masters,8,62,65,81,49,7.0,6,30,Urban,Manager,87524,1 +76232,Male,21,Diploma,16,79,49,47,91,5.0,2,40,Urban,Software Engineer,144956,0 +76233,Male,25,Bachelors,7,51,26,57,47,1.0,2,23,Urban,Data Analyst,71994,0 +76234,Female,25,Masters,11,2,28,85,59,2.0,0,62,Rural,HR Executive,110621,0 +76235,Male,58,Diploma,14,4,68,63,51,2.0,1,4,Urban,Software Engineer,63988,0 +76236,Male,22,Bachelors,18,35,98,23,83,8.0,7,97,Urban,Data Analyst,122796,1 +76237,Female,30,High School,14,79,78,69,69,1.0,5,64,Urban,ML Engineer,21628,1 +76238,Female,45,Bachelors,5,92,62,1,35,4.0,4,89,Urban,Software Engineer,36601,1 +76239,Female,54,High School,17,45,60,88,93,7.0,5,93,Rural,Data Analyst,62387,1 +76240,Male,51,Diploma,8,15,71,15,1,1.0,0,60,Semi-Urban,HR Executive,106056,0 +76241,Female,47,High School,2,16,67,50,67,4.0,7,12,Rural,Data Analyst,20307,0 +76242,Female,54,Bachelors,17,60,10,95,59,5.0,3,19,Rural,HR Executive,75238,0 +76243,Male,24,PhD,6,71,17,29,33,5.0,1,19,Rural,Software Engineer,25025,0 +76244,Female,39,Bachelors,8,48,61,92,80,3.0,3,30,Rural,ML Engineer,20200,0 +76245,Female,39,Masters,4,77,48,65,23,9.0,0,40,Semi-Urban,ML Engineer,104516,0 +76246,Male,36,Bachelors,14,24,34,86,71,3.0,6,40,Urban,HR Executive,139011,0 +76247,Male,37,High School,13,76,41,67,78,8.0,0,99,Semi-Urban,Software Engineer,47207,1 +76248,Female,27,High School,0,27,91,28,75,3.0,5,43,Rural,ML Engineer,105760,0 +76249,Male,42,High School,18,11,89,57,7,1.0,5,14,Semi-Urban,Software Engineer,127096,0 +76250,Male,28,PhD,15,69,96,83,33,6.0,7,11,Semi-Urban,HR Executive,57742,1 +76251,Other,23,Bachelors,16,9,68,18,75,8.0,1,53,Urban,HR Executive,131570,0 +76252,Male,53,Diploma,6,44,73,13,91,4.0,7,91,Urban,HR Executive,95951,0 +76253,Female,43,Bachelors,1,39,62,32,77,1.0,5,94,Semi-Urban,Manager,128819,0 +76254,Female,36,Masters,4,46,9,34,25,4.0,1,20,Semi-Urban,Software Engineer,41228,0 +76255,Male,31,Masters,3,6,31,22,90,9.0,2,73,Rural,Manager,78561,0 +76256,Male,46,Bachelors,14,0,30,54,47,6.0,2,10,Rural,HR Executive,129797,0 +76257,Male,54,Bachelors,5,32,19,33,88,1.0,1,37,Urban,ML Engineer,95609,0 +76258,Male,33,Bachelors,15,16,96,42,86,1.0,4,20,Semi-Urban,ML Engineer,83901,0 +76259,Male,22,Bachelors,17,90,29,15,67,5.0,3,53,Urban,Manager,124007,0 +76260,Female,25,Masters,6,95,90,21,93,7.0,5,31,Urban,Manager,85568,0 +76261,Female,49,Masters,4,64,60,20,23,8.0,1,34,Urban,Software Engineer,114127,0 +76262,Male,24,Masters,4,47,37,21,82,9.0,0,91,Urban,Data Analyst,132347,0 +76263,Male,35,High School,14,19,21,30,42,9.0,4,42,Urban,Manager,121630,0 +76264,Female,54,Bachelors,6,43,5,49,22,5.0,3,22,Urban,Data Analyst,35749,0 +76265,Female,33,PhD,3,34,94,98,4,3.0,5,49,Semi-Urban,Data Analyst,103434,1 +76266,Male,36,Bachelors,17,89,14,18,41,9.0,1,57,Semi-Urban,Data Analyst,110276,0 +76267,Male,32,Masters,17,75,47,78,45,8.0,4,14,Rural,Software Engineer,30595,0 +76268,Female,54,Bachelors,7,15,72,66,15,0.0,5,18,Semi-Urban,Software Engineer,144751,0 +76269,Male,24,Bachelors,17,5,33,45,20,6.0,2,39,Urban,Software Engineer,104777,0 +76270,Male,29,Masters,8,81,87,25,95,2.0,7,81,Rural,Software Engineer,58628,1 +76271,Male,50,High School,3,34,9,45,11,9.0,5,44,Rural,Data Analyst,57420,0 +76272,Male,36,High School,15,50,19,71,35,2.0,1,97,Urban,Manager,146648,1 +76273,Male,56,Masters,2,38,22,74,37,6.0,7,95,Semi-Urban,ML Engineer,144921,0 +76274,Female,57,Diploma,18,34,9,89,93,5.0,0,95,Urban,ML Engineer,72966,0 +76275,Female,22,PhD,10,10,86,58,7,0.0,1,75,Semi-Urban,ML Engineer,69171,0 +76276,Male,53,Masters,12,18,84,7,75,4.0,4,21,Urban,Manager,45566,0 +76277,Male,23,Diploma,8,79,16,47,75,5.0,3,1,Rural,Software Engineer,127580,0 +76278,Male,36,Bachelors,6,56,49,25,75,9.0,1,99,Rural,Manager,50014,0 +76279,Male,31,Diploma,1,16,87,96,93,3.0,7,55,Rural,ML Engineer,130775,1 +76280,Male,33,Masters,17,67,72,52,98,8.0,5,54,Semi-Urban,ML Engineer,138223,1 +76281,Male,39,Bachelors,14,9,46,79,21,0.0,3,83,Semi-Urban,Data Analyst,90945,0 +76282,Male,38,Bachelors,14,13,89,84,32,3.0,0,75,Urban,HR Executive,82991,1 +76283,Female,56,Masters,18,43,74,47,97,3.0,4,45,Urban,HR Executive,128038,0 +76284,Female,51,Bachelors,15,8,83,82,7,5.0,2,72,Urban,ML Engineer,38628,1 +76285,Male,46,High School,0,84,21,95,60,5.0,2,37,Semi-Urban,Software Engineer,143409,1 +76286,Male,47,Diploma,18,21,45,53,38,1.0,0,14,Semi-Urban,Manager,52197,0 +76287,Male,35,High School,0,22,3,25,75,1.0,2,76,Urban,HR Executive,134099,0 +76288,Male,28,Bachelors,2,61,87,5,69,1.0,7,36,Urban,Data Analyst,101308,0 +76289,Female,40,Masters,9,25,70,82,74,0.0,0,91,Semi-Urban,Software Engineer,144135,1 +76290,Male,41,Bachelors,3,94,64,63,2,6.0,6,89,Urban,ML Engineer,89418,1 +76291,Male,36,Diploma,0,35,55,16,48,0.0,0,27,Urban,Data Analyst,69514,0 +76292,Male,41,Bachelors,15,7,46,85,36,5.0,7,43,Urban,Software Engineer,119308,0 +76293,Male,27,Bachelors,2,86,59,43,90,2.0,2,37,Urban,Software Engineer,147696,0 +76294,Female,56,Bachelors,12,41,79,28,92,9.0,3,79,Urban,ML Engineer,142050,0 +76295,Other,40,Bachelors,13,12,93,22,56,3.0,3,60,Urban,Software Engineer,44313,0 +76296,Male,51,Masters,14,46,66,5,89,7.0,1,99,Rural,HR Executive,116360,0 +76297,Male,51,Bachelors,8,62,8,8,14,0.0,5,22,Urban,ML Engineer,127925,0 +76298,Male,33,Diploma,15,65,13,40,80,1.0,5,38,Rural,Manager,148680,0 +76299,Female,26,Bachelors,8,89,26,49,58,5.0,5,99,Urban,Software Engineer,137573,1 +76300,Female,51,Masters,2,40,73,21,8,7.0,2,42,Urban,Manager,56158,0 +76301,Male,32,Diploma,2,40,19,98,43,6.0,7,10,Urban,Data Analyst,148940,0 +76302,Male,58,High School,19,96,78,94,21,1.0,4,39,Urban,Software Engineer,97939,1 +76303,Male,51,High School,3,82,41,0,86,7.0,7,41,Semi-Urban,Data Analyst,41852,0 +76304,Female,50,High School,5,13,84,76,97,4.0,4,99,Urban,ML Engineer,119035,1 +76305,Female,57,Bachelors,14,31,26,89,51,7.0,1,78,Urban,ML Engineer,148263,0 +76306,Female,51,Masters,12,39,26,65,57,0.0,0,76,Urban,Manager,62420,0 +76307,Male,47,Bachelors,12,60,58,66,19,6.0,0,70,Semi-Urban,Software Engineer,92905,1 +76308,Female,56,Bachelors,14,44,0,23,82,3.0,7,79,Urban,Manager,84874,0 +76309,Male,35,Bachelors,4,15,3,9,60,0.0,5,70,Rural,HR Executive,44345,0 +76310,Male,31,Masters,2,60,57,83,28,5.0,5,39,Semi-Urban,Data Analyst,144911,1 +76311,Female,42,High School,17,87,34,96,73,2.0,0,47,Urban,Manager,36973,1 +76312,Female,34,High School,2,80,7,19,53,2.0,1,89,Urban,Software Engineer,107884,0 +76313,Male,38,High School,16,72,64,65,65,5.0,5,28,Semi-Urban,Manager,26826,0 +76314,Male,28,Bachelors,19,25,75,79,27,0.0,0,91,Urban,Data Analyst,128712,1 +76315,Male,50,Bachelors,6,93,92,81,88,9.0,7,27,Urban,ML Engineer,148036,1 +76316,Female,55,Masters,14,43,45,91,95,6.0,6,48,Rural,Data Analyst,55416,0 +76317,Male,44,Diploma,13,8,46,68,23,2.0,7,18,Urban,Software Engineer,31553,0 +76318,Male,49,Diploma,6,13,71,12,52,6.0,2,12,Semi-Urban,Manager,141819,0 +76319,Other,36,Diploma,18,16,32,0,77,1.0,6,24,Urban,Data Analyst,60274,0 +76320,Female,41,Diploma,16,71,50,56,56,9.0,5,18,Rural,Software Engineer,75836,0 +76321,Male,51,Bachelors,14,64,74,95,5,0.0,3,9,Semi-Urban,ML Engineer,130092,1 +76322,Male,36,Masters,18,80,10,29,40,7.0,6,97,Rural,HR Executive,56238,0 +76323,Male,27,Bachelors,0,40,49,41,94,9.0,6,88,Semi-Urban,Software Engineer,104620,0 +76324,Female,24,Bachelors,19,80,45,36,54,1.0,5,72,Rural,ML Engineer,96435,0 +76325,Female,43,High School,16,76,36,11,88,8.0,2,44,Urban,Manager,130403,0 +76326,Male,50,Diploma,13,87,3,83,63,1.0,1,49,Urban,Manager,64194,0 +76327,Male,49,High School,0,68,85,50,85,6.0,3,63,Urban,ML Engineer,121797,1 +76328,Male,42,Masters,7,5,73,84,97,5.0,0,57,Urban,HR Executive,43631,0 +76329,Male,57,Bachelors,17,89,31,47,23,2.0,5,60,Semi-Urban,HR Executive,80782,0 +76330,Female,56,Bachelors,3,31,24,89,65,8.0,0,55,Semi-Urban,ML Engineer,111353,0 +76331,Male,33,Bachelors,0,88,13,20,37,5.0,6,44,Rural,ML Engineer,37150,0 +76332,Female,50,Diploma,18,5,68,91,46,5.0,0,13,Urban,Data Analyst,124034,0 +76333,Female,57,High School,9,30,33,12,33,8.0,0,48,Urban,Data Analyst,134814,0 +76334,Female,23,Bachelors,12,87,58,64,34,8.0,5,74,Urban,Software Engineer,39603,1 +76335,Male,23,Masters,9,44,29,83,3,5.0,7,77,Semi-Urban,Data Analyst,50214,0 +76336,Male,41,Masters,19,47,24,97,0,8.0,0,89,Urban,ML Engineer,101859,1 +76337,Female,53,Diploma,10,61,97,56,4,3.0,7,25,Urban,Software Engineer,48386,0 +76338,Male,53,Bachelors,17,19,19,1,48,3.0,1,69,Semi-Urban,Data Analyst,125065,0 +76339,Other,28,Bachelors,7,31,42,81,97,1.0,2,89,Urban,Data Analyst,60992,1 +76340,Male,34,Masters,3,57,24,45,52,7.0,3,57,Rural,Manager,148689,0 +76341,Male,22,High School,12,83,12,92,29,1.0,7,65,Urban,Data Analyst,144765,1 +76342,Female,55,High School,13,3,73,78,37,9.0,2,50,Rural,Manager,80362,0 +76343,Female,43,Masters,5,44,65,23,92,5.0,0,53,Rural,Software Engineer,71090,0 +76344,Male,29,Masters,13,0,45,97,72,8.0,2,9,Rural,HR Executive,118903,0 +76345,Male,31,High School,10,10,68,9,27,9.0,3,39,Urban,ML Engineer,107215,0 +76346,Female,27,Bachelors,9,92,78,59,58,4.0,1,92,Urban,HR Executive,117369,1 +76347,Male,49,High School,15,1,80,39,62,4.0,1,36,Urban,ML Engineer,97403,0 +76348,Male,35,Bachelors,5,37,45,76,41,5.0,3,40,Semi-Urban,Data Analyst,24327,0 +76349,Male,56,Bachelors,14,34,21,7,7,9.0,4,10,Semi-Urban,HR Executive,59628,0 +76350,Female,47,PhD,1,76,32,24,98,1.0,1,29,Urban,HR Executive,59447,0 +76351,Female,51,Bachelors,2,52,54,3,19,6.0,1,23,Rural,Software Engineer,96837,0 +76352,Male,52,Diploma,18,66,42,72,7,5.0,6,91,Semi-Urban,HR Executive,75078,1 +76353,Male,32,Bachelors,8,96,94,90,25,2.0,3,15,Semi-Urban,HR Executive,54639,1 +76354,Male,30,Masters,10,70,96,77,64,1.0,7,71,Urban,ML Engineer,100353,1 +76355,Female,52,Bachelors,8,29,62,17,9,3.0,0,18,Urban,Data Analyst,95269,0 +76356,Female,47,Bachelors,13,77,95,85,39,5.0,1,68,Urban,ML Engineer,145792,1 +76357,Male,44,High School,13,12,87,78,68,2.0,0,71,Urban,Software Engineer,139925,1 +76358,Male,58,Bachelors,1,72,65,6,43,6.0,6,20,Urban,ML Engineer,56903,0 +76359,Male,54,Diploma,3,68,69,23,71,0.0,3,94,Semi-Urban,ML Engineer,109884,1 +76360,Male,37,Bachelors,5,54,41,99,58,8.0,7,99,Semi-Urban,ML Engineer,110067,1 +76361,Male,44,Bachelors,1,9,48,1,48,1.0,3,74,Urban,HR Executive,105221,0 +76362,Other,25,Masters,4,6,78,57,97,9.0,5,41,Rural,Software Engineer,54240,0 +76363,Male,36,Masters,12,27,88,43,32,6.0,3,87,Urban,Manager,32147,1 +76364,Female,48,Bachelors,17,36,75,82,22,8.0,2,23,Urban,Software Engineer,141866,0 +76365,Male,36,Bachelors,19,67,58,57,64,9.0,2,14,Urban,HR Executive,130414,0 +76366,Other,49,Bachelors,17,99,99,97,64,9.0,2,18,Urban,Software Engineer,62817,1 +76367,Male,26,PhD,6,5,7,93,98,0.0,6,49,Urban,Software Engineer,80709,0 +76368,Male,38,Diploma,10,74,66,9,1,0.0,0,42,Semi-Urban,ML Engineer,74107,0 +76369,Male,39,Diploma,15,75,36,55,57,6.0,2,16,Semi-Urban,Manager,100662,0 +76370,Female,55,Bachelors,1,9,68,22,18,2.0,4,32,Semi-Urban,ML Engineer,67887,0 +76371,Male,25,Diploma,1,77,16,39,9,6.0,7,86,Semi-Urban,ML Engineer,32595,0 +76372,Female,41,Bachelors,15,30,83,55,52,2.0,0,75,Semi-Urban,Manager,122746,1 +76373,Female,37,High School,5,66,12,84,96,5.0,6,37,Urban,HR Executive,108695,0 +76374,Male,31,Bachelors,15,40,50,40,20,1.0,0,53,Urban,HR Executive,40741,0 +76375,Male,59,High School,9,50,66,99,81,9.0,6,81,Urban,HR Executive,39622,1 +76376,Male,48,Diploma,15,22,7,57,52,6.0,7,52,Urban,Software Engineer,101724,0 +76377,Male,29,Bachelors,19,61,13,90,33,0.0,2,6,Rural,Software Engineer,41000,0 +76378,Male,25,Masters,14,84,91,58,6,3.0,3,38,Urban,ML Engineer,133519,1 +76379,Male,38,Bachelors,19,37,72,89,48,7.0,4,80,Semi-Urban,HR Executive,96509,1 +76380,Female,44,High School,9,67,75,66,40,6.0,3,88,Rural,HR Executive,76235,1 +76381,Female,34,Masters,19,30,59,85,80,3.0,2,66,Urban,Manager,124565,0 +76382,Female,26,Diploma,1,18,63,5,47,3.0,3,64,Semi-Urban,Software Engineer,131749,0 +76383,Male,28,Bachelors,13,90,11,10,90,1.0,5,32,Urban,ML Engineer,60616,0 +76384,Male,34,Diploma,7,20,55,4,52,1.0,6,68,Rural,Software Engineer,89733,0 +76385,Male,58,High School,0,2,72,5,95,3.0,2,88,Semi-Urban,Software Engineer,105510,0 +76386,Female,48,High School,16,54,22,14,51,9.0,7,81,Urban,Software Engineer,103579,0 +76387,Male,38,Bachelors,18,25,14,0,12,6.0,7,91,Urban,HR Executive,113425,0 +76388,Male,44,Bachelors,2,14,8,59,5,5.0,5,25,Rural,ML Engineer,64785,0 +76389,Female,50,Masters,5,74,58,30,99,1.0,5,5,Urban,HR Executive,134522,0 +76390,Male,22,Diploma,8,73,96,81,55,2.0,5,92,Rural,Manager,90306,1 +76391,Male,58,Bachelors,16,10,40,93,99,4.0,1,59,Urban,ML Engineer,46149,0 +76392,Male,37,High School,1,95,41,78,72,8.0,6,68,Rural,Software Engineer,124200,1 +76393,Female,45,Bachelors,3,66,96,18,77,6.0,3,79,Urban,Data Analyst,107328,1 +76394,Female,34,Bachelors,11,42,62,17,41,2.0,0,96,Rural,Data Analyst,138669,0 +76395,Female,40,Masters,11,27,29,74,75,2.0,6,79,Rural,Software Engineer,123949,0 +76396,Female,36,Diploma,17,4,38,33,84,6.0,0,67,Semi-Urban,HR Executive,85816,0 +76397,Other,39,Masters,6,21,68,99,91,8.0,2,86,Rural,HR Executive,148248,1 +76398,Male,33,High School,13,82,74,3,14,3.0,6,21,Semi-Urban,Software Engineer,46076,0 +76399,Male,28,Bachelors,14,30,71,60,98,6.0,1,81,Rural,ML Engineer,60889,1 +76400,Male,34,Diploma,13,65,73,92,32,1.0,7,1,Rural,Software Engineer,100879,0 +76401,Male,31,Masters,9,50,83,62,73,0.0,6,51,Urban,Data Analyst,106905,1 +76402,Male,51,Bachelors,4,59,6,99,74,6.0,6,13,Urban,HR Executive,108100,0 +76403,Male,22,Bachelors,10,43,67,21,92,0.0,5,26,Urban,HR Executive,115937,0 +76404,Male,38,Bachelors,16,75,4,81,24,1.0,6,5,Semi-Urban,ML Engineer,62676,0 +76405,Male,21,Bachelors,2,61,89,86,63,0.0,7,97,Urban,Manager,105938,1 +76406,Female,49,Bachelors,7,50,37,10,74,2.0,7,15,Urban,Software Engineer,114719,0 +76407,Male,22,Diploma,4,55,3,20,99,5.0,6,12,Rural,HR Executive,110540,0 +76408,Other,58,Masters,16,62,81,39,89,7.0,5,68,Urban,Data Analyst,86068,1 +76409,Female,23,High School,3,11,72,35,22,8.0,1,57,Urban,Data Analyst,55128,0 +76410,Female,46,Bachelors,12,82,3,71,0,0.0,2,14,Urban,Manager,119535,0 +76411,Female,29,High School,14,15,57,98,69,0.0,0,83,Semi-Urban,Data Analyst,94608,1 +76412,Female,21,Diploma,7,57,0,29,55,3.0,3,57,Urban,Software Engineer,77840,0 +76413,Male,53,High School,14,93,30,34,0,9.0,1,14,Urban,HR Executive,139890,0 +76414,Female,50,Masters,16,51,77,54,45,5.0,6,51,Rural,HR Executive,115724,0 +76415,Female,48,Bachelors,11,93,83,43,52,4.0,5,59,Rural,Data Analyst,57749,1 +76416,Male,32,Diploma,0,95,58,8,21,6.0,0,91,Urban,Software Engineer,35653,1 +76417,Female,57,Masters,8,43,49,18,10,8.0,2,75,Urban,Manager,29885,0 +76418,Male,51,PhD,10,46,32,51,11,4.0,1,28,Urban,Manager,24129,0 +76419,Male,53,Bachelors,0,80,80,35,0,0.0,5,94,Urban,HR Executive,97007,1 +76420,Male,37,Bachelors,12,73,97,16,67,4.0,6,12,Rural,Manager,77032,0 +76421,Female,50,High School,4,39,81,85,98,3.0,3,44,Urban,Software Engineer,60822,1 +76422,Female,26,High School,9,38,61,82,26,1.0,2,95,Rural,Data Analyst,71422,1 +76423,Female,57,Diploma,7,53,29,85,52,2.0,1,25,Urban,Data Analyst,59891,0 +76424,Male,40,Bachelors,3,14,32,46,62,6.0,6,73,Semi-Urban,Data Analyst,101492,0 +76425,Other,44,Diploma,9,61,83,4,47,4.0,4,27,Semi-Urban,HR Executive,118651,0 +76426,Male,28,Bachelors,4,30,96,28,44,5.0,6,39,Urban,HR Executive,114864,0 +76427,Male,36,Bachelors,16,96,80,38,48,6.0,0,74,Semi-Urban,ML Engineer,131301,1 +76428,Other,43,Diploma,10,97,60,0,15,5.0,3,38,Urban,HR Executive,109577,0 +76429,Female,27,Diploma,15,13,46,3,73,1.0,7,36,Semi-Urban,ML Engineer,68302,0 +76430,Female,43,Bachelors,4,51,70,2,93,1.0,0,28,Urban,Manager,98086,0 +76431,Male,49,Masters,1,39,53,3,4,0.0,6,2,Urban,Data Analyst,130912,0 +76432,Male,49,Bachelors,3,90,84,95,35,5.0,3,49,Urban,Software Engineer,24430,1 +76433,Male,32,High School,8,30,7,86,17,3.0,0,93,Rural,Data Analyst,90033,0 +76434,Female,53,Diploma,7,81,62,12,6,0.0,1,39,Urban,Data Analyst,101352,0 +76435,Male,41,High School,16,76,53,91,94,2.0,4,3,Urban,ML Engineer,84209,0 +76436,Male,55,Bachelors,2,72,52,24,16,5.0,7,34,Urban,Software Engineer,41197,0 +76437,Male,28,High School,12,40,26,42,72,4.0,3,32,Semi-Urban,Software Engineer,23074,0 +76438,Female,54,Masters,15,90,90,82,40,9.0,7,93,Semi-Urban,Data Analyst,25465,1 +76439,Male,59,Diploma,13,86,19,22,68,2.0,5,3,Urban,Software Engineer,139635,0 +76440,Female,49,High School,5,28,47,99,90,4.0,3,80,Semi-Urban,HR Executive,58044,1 +76441,Male,48,Bachelors,16,31,51,0,45,2.0,1,73,Semi-Urban,Manager,91586,0 +76442,Female,43,Bachelors,7,76,95,85,50,8.0,0,41,Semi-Urban,Data Analyst,50401,1 +76443,Male,56,Diploma,17,60,58,72,45,6.0,6,4,Urban,Software Engineer,117318,0 +76444,Female,23,Bachelors,16,41,98,49,49,3.0,6,73,Semi-Urban,HR Executive,64922,1 +76445,Male,32,Masters,2,80,38,70,83,2.0,5,77,Semi-Urban,Data Analyst,115814,1 +76446,Female,45,Bachelors,0,5,98,27,5,9.0,5,97,Semi-Urban,Software Engineer,131085,0 +76447,Male,59,Masters,10,9,40,90,70,0.0,4,33,Urban,Manager,145071,0 +76448,Female,41,Bachelors,15,14,91,56,9,2.0,1,49,Urban,HR Executive,125719,0 +76449,Male,32,High School,7,46,43,70,29,4.0,4,38,Rural,Manager,76517,0 +76450,Male,31,Masters,3,88,27,3,88,3.0,1,97,Rural,Software Engineer,42181,0 +76451,Male,55,Diploma,14,10,1,62,79,8.0,2,57,Urban,HR Executive,78100,0 +76452,Female,56,Diploma,17,10,89,41,49,4.0,5,87,Rural,Manager,98413,0 +76453,Male,48,Masters,18,40,5,46,96,9.0,6,97,Urban,ML Engineer,125331,0 +76454,Male,31,Diploma,4,84,57,67,27,5.0,0,47,Semi-Urban,Manager,47268,1 +76455,Male,23,PhD,7,15,29,5,94,2.0,1,96,Urban,HR Executive,20243,0 +76456,Female,41,High School,1,27,31,67,40,0.0,6,1,Rural,HR Executive,45654,0 +76457,Male,29,Diploma,15,46,20,80,38,1.0,2,59,Semi-Urban,ML Engineer,129098,0 +76458,Male,26,Bachelors,4,2,52,12,93,6.0,2,12,Rural,Manager,48470,0 +76459,Male,49,High School,19,65,56,31,69,8.0,4,47,Urban,Software Engineer,30720,0 +76460,Male,37,High School,5,45,53,42,51,4.0,5,26,Semi-Urban,ML Engineer,65196,0 +76461,Male,41,Masters,11,44,32,77,76,7.0,3,73,Urban,HR Executive,109910,0 +76462,Female,28,Diploma,16,62,82,40,80,5.0,1,80,Urban,HR Executive,50723,1 +76463,Male,31,Bachelors,11,8,77,39,2,7.0,1,30,Urban,HR Executive,38684,0 +76464,Male,41,Bachelors,15,92,5,26,52,9.0,4,35,Urban,HR Executive,88423,0 +76465,Other,38,High School,12,75,90,88,69,6.0,6,40,Rural,Data Analyst,124516,1 +76466,Female,22,Diploma,10,54,69,51,90,9.0,4,31,Urban,Software Engineer,139289,0 +76467,Male,49,Diploma,10,68,88,74,64,5.0,3,32,Semi-Urban,ML Engineer,38629,1 +76468,Male,42,Diploma,3,58,7,93,25,8.0,3,89,Rural,Data Analyst,48039,1 +76469,Female,26,Bachelors,8,71,70,46,10,2.0,0,78,Urban,Manager,88873,1 +76470,Male,26,PhD,16,55,30,89,92,1.0,4,62,Urban,Software Engineer,112846,1 +76471,Female,23,Bachelors,10,58,98,46,56,5.0,3,84,Urban,HR Executive,66843,1 +76472,Other,52,High School,18,99,40,40,5,8.0,6,74,Urban,ML Engineer,123916,1 +76473,Male,49,High School,5,98,94,64,59,0.0,4,92,Urban,HR Executive,39214,1 +76474,Male,33,Bachelors,17,86,17,89,78,0.0,7,27,Urban,Data Analyst,30418,0 +76475,Female,35,Bachelors,10,24,86,59,62,2.0,0,43,Urban,Software Engineer,130413,0 +76476,Female,49,Bachelors,18,18,93,87,62,0.0,0,95,Rural,Software Engineer,109924,1 +76477,Female,33,Bachelors,16,13,95,25,13,7.0,3,17,Urban,HR Executive,84298,0 +76478,Male,43,Diploma,13,31,82,56,1,8.0,1,51,Semi-Urban,Software Engineer,49560,0 +76479,Female,26,Bachelors,7,32,34,22,54,6.0,4,44,Urban,Software Engineer,33030,0 +76480,Female,57,Masters,3,62,28,92,76,2.0,0,27,Urban,Data Analyst,23359,0 +76481,Male,57,Masters,18,68,11,18,27,7.0,7,60,Urban,Data Analyst,67622,0 +76482,Male,50,Bachelors,15,99,17,14,55,1.0,6,46,Urban,HR Executive,56281,0 +76483,Male,43,Diploma,15,99,68,27,15,3.0,5,19,Urban,HR Executive,24239,0 +76484,Male,33,High School,3,33,67,89,99,9.0,1,67,Rural,HR Executive,72085,1 +76485,Other,44,Masters,13,77,27,63,19,7.0,7,27,Urban,Software Engineer,113909,0 +76486,Male,54,Bachelors,18,54,57,3,17,9.0,2,49,Urban,Software Engineer,57571,0 +76487,Male,36,PhD,7,33,21,39,25,5.0,1,20,Urban,Data Analyst,114893,0 +76488,Male,31,Masters,2,67,0,57,21,7.0,6,68,Urban,HR Executive,58160,0 +76489,Male,58,Diploma,15,11,59,18,77,0.0,4,14,Urban,Manager,44291,0 +76490,Female,48,Masters,0,47,36,35,37,4.0,1,34,Urban,Software Engineer,52105,0 +76491,Male,58,Bachelors,17,93,67,69,47,9.0,2,32,Urban,Software Engineer,36745,1 +76492,Male,24,Masters,17,62,66,65,63,5.0,2,73,Rural,ML Engineer,132321,1 +76493,Female,35,High School,0,95,55,51,3,6.0,6,51,Rural,ML Engineer,46859,1 +76494,Male,28,Bachelors,13,89,85,91,79,4.0,4,39,Urban,Manager,143228,1 +76495,Male,59,Bachelors,12,43,92,47,46,7.0,7,69,Rural,Software Engineer,67112,1 +76496,Female,35,Bachelors,13,72,27,67,19,6.0,2,95,Urban,Data Analyst,91340,1 +76497,Male,53,Masters,6,73,82,61,35,5.0,6,75,Semi-Urban,Software Engineer,51541,1 +76498,Male,58,Bachelors,13,55,37,11,57,5.0,1,18,Urban,Manager,141517,0 +76499,Male,32,Bachelors,19,70,77,6,15,6.0,1,44,Urban,Manager,29174,0 +76500,Male,26,Bachelors,2,34,89,98,54,0.0,2,1,Semi-Urban,Manager,66043,0 +76501,Male,42,Bachelors,14,42,6,20,42,8.0,4,25,Rural,ML Engineer,56865,0 +76502,Male,40,Bachelors,15,91,82,25,54,5.0,6,11,Semi-Urban,Software Engineer,88467,0 +76503,Other,48,Bachelors,13,66,93,69,31,4.0,4,65,Urban,HR Executive,63515,1 +76504,Male,53,Bachelors,14,16,56,17,22,1.0,6,80,Rural,Data Analyst,26474,0 +76505,Male,59,Bachelors,2,34,78,87,8,6.0,4,54,Semi-Urban,HR Executive,38277,1 +76506,Female,42,Bachelors,9,15,5,76,47,4.0,7,77,Urban,HR Executive,66096,0 +76507,Female,35,Diploma,0,5,50,9,40,7.0,4,91,Semi-Urban,HR Executive,104375,0 +76508,Male,29,Masters,6,21,23,52,12,3.0,7,31,Urban,ML Engineer,113046,0 +76509,Male,55,High School,16,55,88,33,17,2.0,4,20,Semi-Urban,ML Engineer,81020,0 +76510,Male,54,Masters,13,82,96,18,99,0.0,1,41,Urban,Software Engineer,105798,1 +76511,Male,31,High School,18,92,33,41,77,1.0,0,54,Semi-Urban,ML Engineer,106262,0 +76512,Female,50,Masters,18,64,2,66,15,6.0,3,32,Rural,ML Engineer,96149,0 +76513,Male,41,Masters,19,87,72,23,12,5.0,5,58,Rural,Software Engineer,86207,1 +76514,Male,31,Diploma,1,47,75,74,75,7.0,1,16,Rural,ML Engineer,64802,0 +76515,Other,34,Masters,19,2,7,73,58,2.0,6,44,Urban,Software Engineer,124369,0 +76516,Male,34,Bachelors,7,43,63,31,72,8.0,3,26,Semi-Urban,Data Analyst,41969,0 +76517,Female,57,Diploma,12,31,21,99,48,7.0,0,75,Urban,Manager,149423,0 +76518,Male,38,High School,2,58,80,23,7,0.0,4,7,Urban,HR Executive,57704,0 +76519,Male,48,Diploma,14,11,47,6,98,5.0,5,86,Urban,Software Engineer,61588,0 +76520,Male,51,Bachelors,7,54,19,76,47,4.0,0,55,Rural,ML Engineer,122047,0 +76521,Male,32,Bachelors,8,31,55,70,84,5.0,2,86,Semi-Urban,ML Engineer,28582,1 +76522,Male,55,Masters,3,51,23,85,43,4.0,0,14,Semi-Urban,ML Engineer,33188,0 +76523,Other,57,Bachelors,9,44,1,92,32,8.0,1,6,Urban,Data Analyst,141071,0 +76524,Male,29,High School,3,57,10,38,72,4.0,5,90,Rural,ML Engineer,85110,0 +76525,Male,33,Diploma,14,21,94,13,8,7.0,7,90,Rural,Manager,44633,0 +76526,Male,57,Masters,11,71,15,61,70,6.0,6,85,Semi-Urban,HR Executive,113593,0 +76527,Other,42,Bachelors,17,15,38,93,53,1.0,0,95,Urban,Data Analyst,80483,1 +76528,Male,54,High School,13,9,67,90,58,3.0,3,22,Urban,Software Engineer,96898,0 +76529,Female,49,High School,18,40,35,1,13,7.0,4,59,Semi-Urban,Data Analyst,23257,0 +76530,Male,59,Bachelors,1,60,60,56,7,4.0,4,7,Rural,ML Engineer,67083,0 +76531,Female,27,Masters,15,72,92,24,5,6.0,6,61,Urban,Software Engineer,135179,1 +76532,Male,32,Masters,10,89,54,71,76,9.0,2,51,Urban,Manager,144490,1 +76533,Male,43,Bachelors,4,71,77,44,25,5.0,2,62,Rural,Data Analyst,124745,1 +76534,Male,59,Bachelors,5,14,18,51,41,5.0,5,80,Urban,Manager,66396,0 +76535,Male,35,Masters,13,64,7,22,29,4.0,0,20,Semi-Urban,Software Engineer,58322,0 +76536,Male,37,Bachelors,15,7,8,91,98,1.0,5,67,Semi-Urban,ML Engineer,69972,0 +76537,Other,47,Masters,4,71,21,94,70,8.0,4,97,Rural,Data Analyst,142851,1 +76538,Female,37,Bachelors,11,24,77,97,26,2.0,3,11,Urban,Manager,111911,0 +76539,Female,57,High School,1,81,6,46,82,0.0,1,65,Semi-Urban,Software Engineer,127073,0 +76540,Male,26,Bachelors,11,92,27,23,7,0.0,1,44,Urban,Data Analyst,119955,0 +76541,Male,36,Masters,19,30,93,56,23,9.0,1,2,Urban,HR Executive,63723,0 +76542,Male,45,Bachelors,10,44,48,6,73,4.0,6,82,Semi-Urban,HR Executive,129016,0 +76543,Female,49,High School,1,26,78,49,53,3.0,2,12,Rural,Software Engineer,43982,0 +76544,Female,29,Bachelors,4,59,43,33,78,4.0,7,47,Semi-Urban,Software Engineer,86479,0 +76545,Female,50,Masters,6,89,15,94,19,5.0,1,14,Urban,ML Engineer,54147,0 +76546,Male,36,Bachelors,6,20,49,47,4,3.0,3,63,Urban,Manager,52984,0 +76547,Male,51,Masters,14,31,15,44,16,6.0,3,95,Rural,Software Engineer,115618,0 +76548,Female,35,Diploma,0,73,98,89,23,0.0,7,5,Urban,Manager,40308,1 +76549,Female,32,Bachelors,19,95,2,94,51,4.0,2,98,Urban,Data Analyst,96074,1 +76550,Male,26,High School,17,29,76,39,80,6.0,2,99,Rural,ML Engineer,58187,1 +76551,Male,45,Bachelors,4,21,70,41,10,9.0,4,4,Urban,ML Engineer,137666,0 +76552,Male,55,Masters,3,11,10,66,67,6.0,4,83,Rural,ML Engineer,90487,0 +76553,Male,31,Masters,13,60,13,82,25,8.0,7,28,Urban,Data Analyst,120532,0 +76554,Male,31,Masters,12,15,37,45,67,0.0,7,75,Semi-Urban,Manager,35069,0 +76555,Female,40,High School,19,50,82,80,8,1.0,1,41,Urban,Manager,30962,1 +76556,Male,37,Bachelors,9,65,99,22,32,4.0,2,5,Urban,Software Engineer,58505,0 +76557,Female,32,Diploma,1,30,92,98,38,4.0,0,87,Urban,HR Executive,31357,1 +76558,Male,21,Bachelors,11,80,93,21,5,6.0,5,23,Urban,Manager,147041,0 +76559,Female,31,Masters,19,69,16,58,16,8.0,1,71,Rural,Manager,78046,0 +76560,Male,28,Bachelors,12,53,94,56,33,6.0,2,15,Rural,ML Engineer,31837,0 +76561,Female,48,Bachelors,10,96,98,73,14,4.0,3,67,Rural,HR Executive,84417,1 +76562,Male,54,High School,17,44,94,27,53,3.0,0,88,Urban,HR Executive,74181,1 +76563,Male,43,Diploma,13,45,91,62,30,7.0,4,27,Urban,Software Engineer,127381,0 +76564,Female,41,Bachelors,17,80,29,29,81,5.0,0,46,Urban,Software Engineer,73893,0 +76565,Female,32,Bachelors,9,77,23,6,46,3.0,5,5,Urban,HR Executive,112774,0 +76566,Male,36,Diploma,19,50,11,66,68,8.0,1,59,Urban,HR Executive,106697,0 +76567,Male,34,Masters,16,56,18,0,34,6.0,7,25,Urban,Software Engineer,31615,0 +76568,Male,27,Bachelors,9,0,65,2,59,5.0,0,97,Urban,Data Analyst,42404,0 +76569,Female,49,Bachelors,5,63,19,24,46,9.0,7,13,Semi-Urban,Data Analyst,123497,0 +76570,Male,31,Bachelors,9,70,48,43,80,7.0,6,22,Semi-Urban,Manager,29872,0 +76571,Male,36,Masters,10,6,81,43,89,7.0,7,81,Rural,ML Engineer,66840,0 +76572,Female,28,Bachelors,9,26,56,21,93,0.0,6,54,Urban,ML Engineer,34264,0 +76573,Female,56,High School,10,90,77,53,86,0.0,2,27,Urban,Software Engineer,96732,1 +76574,Female,54,Bachelors,11,5,69,26,44,8.0,4,19,Urban,HR Executive,100844,0 +76575,Male,23,Bachelors,18,36,40,36,52,5.0,4,6,Rural,HR Executive,69439,0 +76576,Male,25,Masters,19,45,53,3,22,9.0,5,83,Urban,Manager,56952,0 +76577,Male,29,Bachelors,9,15,16,7,46,5.0,4,90,Semi-Urban,HR Executive,111661,0 +76578,Female,51,High School,0,82,39,45,29,7.0,3,0,Urban,ML Engineer,80704,0 +76579,Male,55,Diploma,4,83,8,58,98,4.0,2,5,Semi-Urban,Manager,126294,0 +76580,Male,52,Bachelors,17,60,73,62,44,5.0,2,31,Urban,Software Engineer,100452,0 +76581,Male,36,Masters,12,51,40,93,22,8.0,4,41,Urban,Manager,21524,0 +76582,Female,35,High School,19,24,76,36,19,9.0,1,10,Urban,Data Analyst,87383,0 +76583,Female,25,Bachelors,5,55,67,64,30,4.0,6,90,Urban,Data Analyst,82465,1 +76584,Male,26,High School,0,78,40,9,77,3.0,3,27,Urban,ML Engineer,70294,0 +76585,Male,40,Diploma,9,71,41,55,11,8.0,2,57,Urban,HR Executive,63764,0 +76586,Female,29,Diploma,16,60,11,73,13,2.0,3,44,Rural,Data Analyst,128751,0 +76587,Female,50,Bachelors,1,96,49,60,0,0.0,1,84,Semi-Urban,HR Executive,78218,1 +76588,Male,40,Bachelors,17,29,25,44,94,8.0,7,95,Urban,Data Analyst,21542,0 +76589,Male,31,Diploma,15,98,49,4,98,6.0,5,62,Semi-Urban,Data Analyst,81488,0 +76590,Male,55,Bachelors,16,43,54,28,2,1.0,7,64,Urban,HR Executive,47331,0 +76591,Male,56,High School,18,25,12,26,88,9.0,5,68,Rural,ML Engineer,73770,0 +76592,Female,23,High School,6,17,14,46,11,1.0,5,56,Urban,ML Engineer,133449,0 +76593,Female,56,High School,3,47,67,56,37,6.0,3,79,Semi-Urban,Data Analyst,148077,1 +76594,Female,37,Masters,3,39,47,6,88,2.0,7,64,Rural,Manager,143885,0 +76595,Female,59,Masters,9,99,89,29,55,4.0,0,92,Urban,ML Engineer,104068,1 +76596,Male,53,Bachelors,14,19,51,86,73,4.0,4,38,Semi-Urban,Manager,126827,0 +76597,Male,41,Bachelors,19,68,5,42,50,0.0,3,56,Rural,HR Executive,47201,0 +76598,Male,29,Masters,1,2,20,91,74,1.0,3,69,Urban,Software Engineer,108170,0 +76599,Female,41,Bachelors,8,0,85,46,23,9.0,4,45,Urban,ML Engineer,29561,0 +76600,Male,50,Masters,19,42,98,27,81,7.0,1,87,Urban,HR Executive,142836,1 +76601,Male,47,Diploma,8,19,67,19,85,7.0,5,29,Urban,Software Engineer,32150,0 +76602,Male,28,Diploma,3,65,35,85,59,3.0,7,79,Urban,Software Engineer,99885,1 +76603,Female,41,Diploma,15,33,68,14,26,5.0,1,34,Rural,Software Engineer,71311,0 +76604,Male,27,Bachelors,16,41,94,74,41,5.0,4,79,Semi-Urban,ML Engineer,115057,1 +76605,Male,22,High School,15,16,11,29,51,3.0,2,30,Urban,Data Analyst,106163,0 +76606,Female,28,Diploma,1,49,75,82,99,1.0,6,32,Urban,Software Engineer,37442,0 +76607,Female,29,Masters,15,81,16,9,70,6.0,5,89,Rural,HR Executive,70365,0 +76608,Male,49,High School,15,37,66,31,31,2.0,3,3,Urban,Manager,110112,0 +76609,Male,26,Bachelors,11,19,82,91,63,3.0,2,4,Semi-Urban,HR Executive,145831,0 +76610,Female,28,Bachelors,13,79,94,17,52,5.0,6,7,Urban,ML Engineer,70058,0 +76611,Male,27,Diploma,18,36,55,72,35,0.0,4,6,Rural,ML Engineer,125367,0 +76612,Female,54,Bachelors,5,91,24,58,95,5.0,7,23,Semi-Urban,Manager,20334,0 +76613,Male,54,Bachelors,7,14,20,83,73,4.0,0,41,Semi-Urban,ML Engineer,145407,0 +76614,Female,44,Masters,1,25,10,62,31,1.0,6,94,Urban,Manager,90921,0 +76615,Female,53,Diploma,10,3,34,88,42,3.0,4,98,Rural,HR Executive,55285,0 +76616,Female,33,Masters,18,39,13,8,22,1.0,5,70,Semi-Urban,Data Analyst,77164,0 +76617,Male,50,Bachelors,11,32,28,70,31,3.0,3,63,Rural,Software Engineer,32120,0 +76618,Male,33,Bachelors,9,36,33,38,15,4.0,3,58,Rural,ML Engineer,32794,0 +76619,Male,53,Bachelors,3,67,42,44,2,0.0,3,85,Rural,Software Engineer,131154,1 +76620,Male,46,Bachelors,5,92,39,30,20,5.0,0,74,Urban,HR Executive,24421,1 +76621,Other,36,Bachelors,3,42,55,12,92,4.0,5,26,Urban,Software Engineer,108558,0 +76622,Male,35,Bachelors,14,34,70,3,36,9.0,4,47,Semi-Urban,ML Engineer,96642,0 +76623,Female,37,High School,12,51,94,76,51,7.0,3,26,Semi-Urban,ML Engineer,58639,1 +76624,Other,58,High School,4,99,62,37,95,8.0,4,3,Rural,Software Engineer,130377,0 +76625,Other,52,Bachelors,13,59,98,23,95,5.0,3,78,Semi-Urban,Data Analyst,49734,1 +76626,Female,33,Masters,8,17,94,18,77,2.0,2,71,Rural,HR Executive,43908,0 +76627,Male,54,Diploma,18,78,81,14,43,0.0,2,75,Urban,Data Analyst,46736,1 +76628,Male,37,Diploma,15,15,95,51,75,9.0,0,64,Urban,Software Engineer,87516,0 +76629,Female,35,Masters,19,6,14,42,12,8.0,6,71,Urban,Software Engineer,116582,0 +76630,Female,49,High School,3,72,95,45,25,2.0,7,47,Urban,ML Engineer,27421,1 +76631,Male,54,Bachelors,16,96,63,26,21,3.0,1,64,Rural,HR Executive,27425,1 +76632,Female,29,Bachelors,6,36,24,57,78,7.0,7,11,Urban,HR Executive,22606,0 +76633,Male,54,High School,14,86,3,72,82,5.0,5,75,Urban,Data Analyst,77159,1 +76634,Female,48,Bachelors,11,50,3,96,85,0.0,5,46,Urban,ML Engineer,139454,0 +76635,Female,33,High School,8,10,37,81,8,9.0,4,80,Urban,HR Executive,79349,0 +76636,Male,41,Bachelors,4,12,50,26,15,5.0,0,21,Rural,HR Executive,125275,0 +76637,Female,58,Bachelors,0,83,17,13,21,3.0,2,34,Urban,HR Executive,144724,0 +76638,Female,32,Diploma,9,58,22,98,8,4.0,5,48,Semi-Urban,ML Engineer,70367,0 +76639,Male,56,Bachelors,10,66,58,54,57,2.0,3,21,Semi-Urban,HR Executive,61457,0 +76640,Male,58,Bachelors,12,1,78,52,9,2.0,0,48,Semi-Urban,HR Executive,43209,0 +76641,Female,34,Diploma,17,89,86,52,64,3.0,7,56,Urban,Manager,80452,1 +76642,Male,40,High School,7,0,27,67,22,3.0,0,89,Semi-Urban,Manager,25365,0 +76643,Other,50,Bachelors,3,99,37,95,68,9.0,1,13,Urban,HR Executive,142940,1 +76644,Female,26,Diploma,17,65,74,1,23,8.0,2,62,Urban,Software Engineer,67465,0 +76645,Male,31,Masters,12,73,25,85,49,7.0,0,15,Rural,Data Analyst,45636,0 +76646,Male,51,Bachelors,2,3,43,1,6,1.0,2,97,Rural,HR Executive,73132,0 +76647,Female,30,High School,11,31,19,42,54,9.0,0,44,Urban,Manager,45011,0 +76648,Female,47,Bachelors,18,60,24,85,14,5.0,0,55,Semi-Urban,Software Engineer,42157,0 +76649,Male,44,Masters,0,34,48,80,4,1.0,6,30,Semi-Urban,Data Analyst,91071,0 +76650,Male,51,Bachelors,16,17,16,35,74,5.0,4,45,Rural,HR Executive,118435,0 +76651,Female,40,Bachelors,15,43,71,79,4,3.0,2,1,Rural,Data Analyst,60025,0 +76652,Female,47,High School,18,73,46,57,17,7.0,0,80,Urban,Manager,40433,1 +76653,Male,28,Bachelors,7,72,30,82,52,6.0,5,86,Urban,Manager,55863,1 +76654,Female,39,Bachelors,11,93,25,24,8,1.0,7,23,Semi-Urban,Data Analyst,49264,0 +76655,Female,59,Bachelors,10,0,34,72,28,5.0,7,22,Semi-Urban,Data Analyst,110585,0 +76656,Male,41,Bachelors,9,39,83,68,44,0.0,3,87,Urban,Data Analyst,21848,1 +76657,Male,21,Diploma,11,76,16,31,14,3.0,7,14,Urban,ML Engineer,134280,0 +76658,Female,28,Masters,16,74,63,99,99,9.0,5,87,Urban,HR Executive,94953,1 +76659,Male,55,Masters,2,51,6,78,14,3.0,6,61,Rural,ML Engineer,60908,0 +76660,Male,45,Bachelors,0,8,30,14,98,2.0,0,75,Rural,Manager,69063,0 +76661,Female,55,Bachelors,4,49,31,90,0,1.0,4,42,Urban,Data Analyst,31043,0 +76662,Male,32,Diploma,11,92,23,88,86,9.0,7,23,Urban,HR Executive,33405,0 +76663,Female,26,Diploma,1,8,7,60,52,6.0,6,36,Urban,ML Engineer,105273,0 +76664,Male,40,Diploma,14,23,35,63,26,8.0,2,95,Semi-Urban,HR Executive,76693,0 +76665,Male,40,Bachelors,0,48,18,40,41,8.0,6,62,Urban,Manager,106509,0 +76666,Male,55,Bachelors,16,61,96,6,58,2.0,5,47,Semi-Urban,ML Engineer,24426,0 +76667,Other,21,Bachelors,17,82,0,74,96,5.0,6,3,Urban,Software Engineer,135608,0 +76668,Male,52,Bachelors,1,38,53,1,5,5.0,6,15,Urban,Data Analyst,63286,0 +76669,Female,59,Masters,3,78,63,90,86,3.0,1,0,Urban,Data Analyst,23363,0 +76670,Male,57,Masters,18,13,67,78,9,6.0,6,67,Semi-Urban,HR Executive,95496,0 +76671,Other,45,Bachelors,7,13,84,50,99,3.0,1,4,Semi-Urban,Data Analyst,124535,0 +76672,Male,26,Diploma,2,2,77,79,34,3.0,0,16,Semi-Urban,Manager,43313,0 +76673,Male,55,Masters,15,45,47,54,76,7.0,3,41,Urban,Data Analyst,90627,0 +76674,Male,30,Bachelors,18,50,17,70,99,7.0,6,67,Urban,ML Engineer,29668,0 +76675,Female,57,Bachelors,1,31,54,24,22,1.0,3,16,Urban,ML Engineer,86309,0 +76676,Female,28,Bachelors,15,61,79,40,65,8.0,5,80,Semi-Urban,Data Analyst,97329,1 +76677,Other,28,Bachelors,3,62,90,52,81,8.0,5,25,Urban,Data Analyst,121351,0 +76678,Male,25,High School,12,67,53,15,39,5.0,4,43,Urban,ML Engineer,71504,0 +76679,Female,58,Masters,5,3,13,39,77,6.0,0,19,Urban,Manager,39813,0 +76680,Male,57,Diploma,14,83,28,86,70,6.0,1,50,Urban,HR Executive,92753,1 +76681,Female,42,PhD,11,19,33,77,77,0.0,3,3,Urban,Software Engineer,86571,0 +76682,Male,48,Masters,19,66,19,0,56,1.0,3,51,Urban,ML Engineer,144825,0 +76683,Female,52,Diploma,2,52,2,35,97,0.0,1,12,Urban,Software Engineer,61777,0 +76684,Female,47,Bachelors,10,55,15,90,58,9.0,6,68,Urban,Software Engineer,149172,0 +76685,Male,51,High School,16,52,36,37,27,7.0,7,25,Urban,Software Engineer,35005,0 +76686,Female,32,Diploma,1,19,55,77,76,1.0,2,43,Rural,ML Engineer,146749,0 +76687,Female,21,PhD,9,18,56,95,98,2.0,5,70,Rural,Software Engineer,144337,0 +76688,Female,27,Diploma,1,25,80,46,38,8.0,5,11,Urban,Software Engineer,43650,0 +76689,Female,55,Bachelors,12,93,87,8,66,9.0,7,30,Rural,Manager,69222,0 +76690,Male,40,Masters,5,13,51,36,81,0.0,0,42,Semi-Urban,HR Executive,132325,0 +76691,Male,45,High School,12,51,86,91,14,7.0,1,31,Rural,Software Engineer,126122,1 +76692,Female,59,Bachelors,1,67,0,75,27,2.0,6,77,Urban,Manager,145653,0 +76693,Male,42,Bachelors,12,36,23,31,48,8.0,5,65,Urban,Software Engineer,147251,0 +76694,Male,28,Masters,0,25,10,61,33,2.0,0,45,Urban,Software Engineer,30079,0 +76695,Male,29,Bachelors,15,39,98,54,97,2.0,1,31,Urban,Manager,110614,0 +76696,Female,47,Masters,18,48,57,85,26,8.0,5,48,Semi-Urban,Software Engineer,101306,0 +76697,Female,39,High School,3,85,64,32,23,0.0,7,80,Semi-Urban,Software Engineer,55853,1 +76698,Female,34,High School,3,61,41,97,22,7.0,4,37,Urban,ML Engineer,116553,0 +76699,Female,50,Masters,7,2,2,64,15,3.0,0,87,Semi-Urban,Manager,87086,0 +76700,Female,47,PhD,0,77,53,98,24,9.0,7,40,Semi-Urban,Data Analyst,117211,1 +76701,Female,50,Bachelors,15,29,63,42,63,7.0,1,36,Urban,ML Engineer,127622,0 +76702,Female,38,Masters,7,41,3,10,45,0.0,7,93,Semi-Urban,Manager,80818,0 +76703,Male,58,Diploma,0,36,32,53,22,1.0,5,51,Urban,ML Engineer,127246,0 +76704,Male,46,Diploma,8,76,1,16,47,0.0,2,1,Urban,Software Engineer,142010,0 +76705,Female,58,Bachelors,6,24,81,56,91,0.0,6,87,Semi-Urban,HR Executive,57115,1 +76706,Male,57,Bachelors,18,60,81,18,45,9.0,2,92,Urban,Software Engineer,141775,1 +76707,Female,55,High School,14,64,91,27,48,7.0,3,22,Rural,Manager,82694,0 +76708,Female,22,Bachelors,1,76,20,60,65,8.0,4,3,Rural,ML Engineer,122222,0 +76709,Female,48,Diploma,13,40,17,50,76,0.0,3,38,Rural,HR Executive,94593,0 +76710,Male,22,High School,12,36,43,43,41,9.0,6,24,Urban,Manager,87207,0 +76711,Female,30,Bachelors,4,29,91,25,72,1.0,3,55,Rural,HR Executive,63435,0 +76712,Male,57,Diploma,7,31,97,50,90,3.0,7,12,Semi-Urban,Manager,113297,0 +76713,Male,26,Bachelors,1,12,3,82,35,0.0,2,46,Semi-Urban,ML Engineer,123108,0 +76714,Female,46,Masters,2,73,68,93,16,8.0,6,66,Urban,Manager,32611,1 +76715,Male,46,Bachelors,8,8,27,72,18,8.0,6,60,Urban,HR Executive,34028,0 +76716,Male,24,High School,5,98,58,85,71,2.0,5,20,Semi-Urban,Data Analyst,148158,1 +76717,Male,51,Masters,11,18,23,92,24,0.0,0,50,Urban,ML Engineer,45968,0 +76718,Male,29,Bachelors,10,35,78,83,18,3.0,5,27,Urban,Manager,146812,0 +76719,Male,38,Masters,14,22,78,97,61,7.0,0,7,Semi-Urban,ML Engineer,35583,0 +76720,Male,59,Diploma,18,17,41,9,71,0.0,4,22,Urban,Manager,112959,0 +76721,Male,53,Bachelors,0,3,10,55,79,5.0,2,59,Urban,Data Analyst,124728,0 +76722,Female,33,Diploma,8,30,14,61,50,6.0,5,73,Semi-Urban,ML Engineer,144092,0 +76723,Other,45,Bachelors,11,31,16,24,74,2.0,2,24,Urban,HR Executive,128959,0 +76724,Male,47,Bachelors,2,67,87,76,11,8.0,3,98,Urban,Software Engineer,144172,1 +76725,Male,56,Bachelors,8,36,16,77,72,1.0,1,42,Rural,Manager,147616,0 +76726,Male,47,Masters,11,4,23,38,4,3.0,5,60,Rural,Data Analyst,130688,0 +76727,Male,30,High School,8,7,96,91,11,3.0,2,15,Urban,Software Engineer,117967,0 +76728,Male,54,Bachelors,16,89,16,59,32,9.0,4,47,Urban,ML Engineer,129168,0 +76729,Male,28,Bachelors,1,96,41,9,55,8.0,3,99,Semi-Urban,ML Engineer,69101,1 +76730,Male,28,Bachelors,17,51,94,96,21,0.0,2,39,Rural,Manager,149245,1 +76731,Male,28,Bachelors,15,29,66,48,86,0.0,6,83,Urban,Data Analyst,48834,0 +76732,Male,53,Masters,1,26,75,14,12,4.0,6,97,Urban,HR Executive,70975,0 +76733,Male,58,Bachelors,14,8,98,35,13,6.0,4,32,Urban,Data Analyst,46293,0 +76734,Male,39,High School,9,90,56,32,33,3.0,0,61,Semi-Urban,Software Engineer,112277,1 +76735,Female,53,Diploma,15,54,91,11,60,3.0,4,52,Urban,Software Engineer,62430,0 +76736,Male,21,Bachelors,19,49,95,36,75,9.0,5,53,Urban,Manager,113214,0 +76737,Male,48,High School,2,30,3,36,47,1.0,7,30,Urban,ML Engineer,33371,0 +76738,Male,26,Bachelors,17,50,9,43,19,8.0,3,56,Semi-Urban,Manager,81214,0 +76739,Male,59,Bachelors,8,0,33,82,88,1.0,6,59,Semi-Urban,ML Engineer,52536,0 +76740,Female,41,Diploma,16,53,77,94,79,2.0,7,7,Urban,Software Engineer,114910,0 +76741,Other,35,Diploma,10,61,42,48,0,2.0,1,42,Rural,Software Engineer,52530,0 +76742,Male,39,Bachelors,7,77,2,12,1,9.0,6,69,Rural,ML Engineer,113819,0 +76743,Male,46,Diploma,19,14,7,31,80,1.0,1,40,Urban,ML Engineer,40630,0 +76744,Female,38,Diploma,1,49,35,93,59,9.0,7,75,Urban,ML Engineer,61331,1 +76745,Male,31,High School,10,6,98,72,52,1.0,3,13,Rural,ML Engineer,96740,0 +76746,Male,57,High School,16,60,8,20,82,9.0,3,17,Urban,Manager,36265,0 +76747,Male,47,Masters,11,12,21,0,62,2.0,0,70,Urban,Data Analyst,80768,0 +76748,Male,32,Masters,19,41,33,75,19,4.0,0,58,Semi-Urban,Software Engineer,63041,0 +76749,Male,39,Masters,17,37,98,21,20,3.0,6,6,Rural,ML Engineer,138236,0 +76750,Male,22,Bachelors,5,22,53,76,0,3.0,7,32,Rural,Manager,134830,0 +76751,Female,21,Masters,16,68,26,11,45,5.0,0,67,Semi-Urban,Data Analyst,136712,0 +76752,Female,27,Bachelors,3,63,28,8,32,4.0,1,65,Urban,Data Analyst,98239,0 +76753,Other,36,Bachelors,5,30,91,49,48,4.0,4,84,Urban,HR Executive,131711,1 +76754,Male,34,Bachelors,19,37,91,93,21,7.0,2,65,Semi-Urban,HR Executive,22762,1 +76755,Female,28,Bachelors,2,86,2,15,5,9.0,5,67,Urban,Data Analyst,37838,0 +76756,Male,53,Masters,16,1,21,83,8,9.0,3,64,Urban,HR Executive,105181,0 +76757,Male,41,Diploma,7,95,22,21,12,8.0,7,96,Rural,HR Executive,104989,0 +76758,Male,45,Bachelors,5,70,5,64,94,6.0,2,42,Semi-Urban,HR Executive,144314,0 +76759,Male,52,High School,5,81,67,80,42,2.0,6,46,Urban,Manager,52009,1 +76760,Female,23,Masters,19,94,12,53,36,1.0,0,51,Urban,Data Analyst,21639,0 +76761,Male,27,Bachelors,4,11,17,72,33,4.0,0,19,Semi-Urban,Manager,41312,0 +76762,Female,37,Diploma,17,18,91,67,53,9.0,4,93,Urban,Data Analyst,87481,1 +76763,Female,49,High School,15,21,32,21,98,7.0,6,47,Rural,Manager,30343,0 +76764,Male,25,Diploma,15,70,43,18,78,7.0,5,78,Rural,Manager,145227,0 +76765,Male,48,Masters,1,51,15,19,82,3.0,7,19,Rural,Manager,87677,0 +76766,Male,54,Diploma,2,67,84,14,34,6.0,6,17,Semi-Urban,Data Analyst,135544,0 +76767,Female,25,Diploma,5,72,98,4,19,4.0,2,50,Urban,HR Executive,40567,0 +76768,Male,43,Masters,2,55,99,34,16,4.0,3,71,Semi-Urban,ML Engineer,39396,1 +76769,Male,31,Bachelors,1,25,78,30,77,2.0,6,25,Urban,ML Engineer,84008,0 +76770,Male,32,High School,17,80,12,52,68,5.0,6,7,Urban,ML Engineer,58328,0 +76771,Male,48,High School,12,89,35,44,34,8.0,0,59,Rural,Manager,51531,0 +76772,Female,26,Diploma,18,7,57,22,99,9.0,1,24,Urban,ML Engineer,99695,0 +76773,Male,29,PhD,16,60,13,42,48,4.0,7,32,Semi-Urban,Software Engineer,33345,0 +76774,Female,31,Masters,4,90,74,22,99,5.0,6,82,Semi-Urban,Data Analyst,120310,1 +76775,Male,32,Masters,12,50,90,83,4,4.0,1,49,Semi-Urban,ML Engineer,65842,1 +76776,Female,49,Bachelors,17,8,72,64,51,4.0,5,73,Urban,ML Engineer,123163,0 +76777,Male,55,Bachelors,14,61,7,72,3,4.0,3,19,Urban,ML Engineer,70465,0 +76778,Male,34,Masters,11,46,81,69,18,9.0,7,43,Semi-Urban,ML Engineer,100230,1 +76779,Male,57,Diploma,0,75,35,57,90,2.0,4,87,Urban,ML Engineer,68053,1 +76780,Female,54,Masters,7,11,76,16,78,7.0,2,34,Rural,Software Engineer,106734,0 +76781,Male,24,Diploma,7,3,36,79,80,6.0,5,82,Urban,ML Engineer,72128,0 +76782,Male,30,Bachelors,16,44,84,74,89,3.0,7,49,Urban,HR Executive,47886,1 +76783,Male,32,Masters,17,74,36,90,32,6.0,1,42,Semi-Urban,Manager,111621,1 +76784,Male,44,High School,13,36,26,77,40,3.0,6,73,Rural,Data Analyst,109126,0 +76785,Female,21,Bachelors,13,5,84,86,96,3.0,5,17,Rural,Data Analyst,86597,0 +76786,Male,49,Bachelors,14,17,81,36,31,6.0,4,69,Urban,Data Analyst,82392,0 +76787,Other,59,PhD,14,91,10,65,67,0.0,1,87,Urban,HR Executive,24475,1 +76788,Male,29,Masters,11,37,40,44,79,1.0,5,13,Rural,ML Engineer,20309,0 +76789,Female,36,Masters,11,29,14,69,32,1.0,7,73,Urban,HR Executive,131534,0 +76790,Male,24,Diploma,18,82,64,42,51,8.0,5,52,Urban,HR Executive,115259,1 +76791,Male,42,Masters,4,13,82,64,62,3.0,5,94,Urban,Software Engineer,22274,1 +76792,Male,34,Diploma,6,78,84,47,5,0.0,7,98,Rural,Data Analyst,146096,1 +76793,Male,58,Diploma,13,42,71,9,85,8.0,3,58,Urban,Manager,126572,0 +76794,Female,47,Bachelors,15,61,16,41,47,6.0,5,35,Semi-Urban,Software Engineer,93605,0 +76795,Male,41,High School,17,82,97,47,86,0.0,7,70,Urban,Manager,97385,1 +76796,Female,46,PhD,4,66,81,19,80,4.0,1,59,Semi-Urban,HR Executive,122717,0 +76797,Male,34,Diploma,1,60,53,56,69,8.0,7,19,Urban,HR Executive,121351,0 +76798,Female,26,High School,2,7,91,52,43,9.0,1,7,Urban,Data Analyst,117446,0 +76799,Male,56,High School,12,97,77,52,59,9.0,0,58,Urban,ML Engineer,59953,1 +76800,Male,40,High School,13,31,59,41,43,4.0,6,94,Urban,Data Analyst,73835,0 +76801,Male,56,Bachelors,2,59,27,68,91,4.0,7,50,Rural,Manager,71363,0 +76802,Male,36,Diploma,6,63,79,75,35,5.0,6,10,Urban,Manager,53288,0 +76803,Male,33,Bachelors,3,25,17,60,61,6.0,3,57,Urban,Data Analyst,144095,0 +76804,Male,42,Bachelors,3,65,50,66,48,1.0,0,61,Rural,Manager,62869,1 +76805,Male,55,Bachelors,5,90,0,54,66,3.0,7,9,Urban,Data Analyst,22236,0 +76806,Male,50,Bachelors,10,6,64,84,39,0.0,6,9,Rural,Software Engineer,35173,0 +76807,Female,32,PhD,18,94,31,5,19,2.0,4,89,Urban,Software Engineer,116222,0 +76808,Female,33,PhD,17,44,11,38,42,4.0,5,5,Rural,HR Executive,118063,0 +76809,Male,25,Masters,11,94,54,22,63,8.0,2,26,Rural,Software Engineer,122287,0 +76810,Male,30,Bachelors,8,33,64,70,19,2.0,2,8,Rural,Data Analyst,64331,0 +76811,Other,48,Bachelors,9,93,5,75,10,6.0,5,26,Urban,Software Engineer,65351,0 +76812,Male,49,Diploma,19,59,2,44,24,9.0,2,9,Urban,Manager,120390,0 +76813,Other,51,High School,8,57,52,30,5,6.0,4,90,Rural,ML Engineer,112035,0 +76814,Male,55,High School,8,75,62,31,70,5.0,3,31,Urban,Software Engineer,51493,0 +76815,Female,24,High School,8,19,53,16,45,2.0,5,87,Urban,ML Engineer,113427,0 +76816,Male,32,Bachelors,8,66,60,78,4,4.0,7,5,Rural,HR Executive,21325,0 +76817,Female,29,Bachelors,3,99,16,39,17,7.0,2,5,Urban,HR Executive,84366,0 +76818,Male,27,Diploma,16,23,48,39,25,9.0,7,73,Rural,Software Engineer,93756,0 +76819,Male,24,Bachelors,7,79,2,12,98,2.0,6,63,Urban,Data Analyst,114094,0 +76820,Female,40,High School,17,25,87,61,80,1.0,6,44,Urban,Software Engineer,71234,0 +76821,Male,46,Bachelors,7,52,61,80,19,3.0,5,76,Rural,Manager,114879,1 +76822,Male,31,Diploma,16,83,68,44,49,2.0,3,51,Urban,Data Analyst,121919,1 +76823,Female,24,Diploma,1,78,38,8,14,3.0,5,14,Urban,HR Executive,48124,0 +76824,Male,24,Bachelors,0,84,24,37,8,0.0,0,11,Semi-Urban,HR Executive,24951,0 +76825,Male,22,Bachelors,0,75,68,19,37,1.0,5,24,Urban,HR Executive,132248,0 +76826,Male,26,Masters,0,10,37,74,68,6.0,4,60,Urban,Manager,88080,0 +76827,Male,24,Masters,8,73,90,7,9,5.0,4,25,Semi-Urban,HR Executive,43096,0 +76828,Male,28,Bachelors,1,42,72,36,43,7.0,7,79,Urban,HR Executive,48505,0 +76829,Male,32,High School,17,36,88,92,15,1.0,2,42,Urban,Software Engineer,37833,1 +76830,Female,28,Masters,6,54,12,48,88,7.0,2,45,Urban,HR Executive,65428,0 +76831,Female,38,Bachelors,17,12,76,8,81,9.0,7,19,Urban,Data Analyst,91382,0 +76832,Male,40,Diploma,11,72,24,56,56,4.0,2,22,Rural,Software Engineer,134297,0 +76833,Male,56,PhD,5,22,80,25,26,7.0,0,76,Urban,Data Analyst,69686,0 +76834,Male,55,Diploma,0,60,19,3,1,1.0,7,44,Urban,HR Executive,112837,0 +76835,Male,51,High School,8,43,72,18,78,2.0,1,41,Urban,Manager,85229,0 +76836,Male,56,Bachelors,9,94,55,53,67,7.0,5,87,Semi-Urban,Software Engineer,56405,1 +76837,Female,31,Masters,3,64,73,94,74,3.0,2,42,Urban,Data Analyst,87379,1 +76838,Female,47,Diploma,19,26,9,84,96,2.0,3,34,Urban,ML Engineer,85805,0 +76839,Male,21,High School,6,45,65,39,77,4.0,5,94,Semi-Urban,HR Executive,88506,1 +76840,Male,30,Masters,12,76,6,15,7,9.0,5,88,Semi-Urban,Manager,60613,0 +76841,Male,29,High School,14,32,56,93,22,1.0,1,57,Urban,HR Executive,110259,1 +76842,Male,29,High School,10,57,50,8,42,4.0,6,25,Semi-Urban,Software Engineer,97124,0 +76843,Male,22,Diploma,4,94,85,90,82,5.0,1,10,Semi-Urban,Software Engineer,145569,1 +76844,Male,28,Bachelors,8,0,99,68,22,3.0,3,18,Rural,Manager,147304,0 +76845,Male,23,Masters,15,0,45,96,31,5.0,7,54,Urban,Data Analyst,138300,0 +76846,Male,42,Masters,6,63,77,42,72,6.0,0,56,Semi-Urban,Manager,82821,1 +76847,Male,29,Bachelors,6,12,8,57,50,4.0,5,20,Urban,Software Engineer,33863,0 +76848,Female,46,Bachelors,4,37,73,72,55,8.0,1,74,Urban,Data Analyst,104869,1 +76849,Female,38,Diploma,1,99,36,17,70,3.0,1,63,Semi-Urban,HR Executive,126716,0 +76850,Female,26,Diploma,16,12,95,39,59,3.0,3,14,Urban,Manager,33534,0 +76851,Other,27,Diploma,0,15,75,50,64,6.0,4,53,Urban,Data Analyst,44715,0 +76852,Female,39,High School,18,21,62,14,89,2.0,7,5,Urban,HR Executive,34668,0 +76853,Female,24,Bachelors,7,28,9,81,14,5.0,5,26,Rural,Data Analyst,144391,0 +76854,Female,26,Diploma,13,76,27,64,63,8.0,6,6,Urban,ML Engineer,38266,0 +76855,Male,30,Bachelors,15,77,50,18,37,2.0,6,15,Urban,Data Analyst,25928,0 +76856,Male,59,Masters,9,65,61,69,4,3.0,0,79,Rural,ML Engineer,82272,1 +76857,Male,37,Bachelors,12,78,49,84,70,5.0,3,87,Rural,Data Analyst,86826,1 +76858,Male,47,Bachelors,14,86,80,36,46,7.0,7,33,Semi-Urban,Data Analyst,53570,1 +76859,Male,43,Diploma,18,49,76,59,76,9.0,2,93,Urban,ML Engineer,108375,1 +76860,Female,30,Masters,0,77,80,86,90,5.0,6,31,Urban,Data Analyst,93627,1 +76861,Male,58,Diploma,0,79,17,75,64,8.0,5,61,Urban,Software Engineer,63034,0 +76862,Female,30,High School,10,37,44,12,45,4.0,3,22,Semi-Urban,ML Engineer,50569,0 +76863,Female,34,Bachelors,13,5,93,24,51,8.0,2,21,Rural,HR Executive,147236,0 +76864,Male,35,Masters,4,82,91,49,53,7.0,7,51,Urban,Software Engineer,102240,1 +76865,Male,55,Bachelors,7,33,11,44,55,4.0,7,91,Semi-Urban,HR Executive,97879,0 +76866,Female,37,Bachelors,17,98,93,80,29,8.0,2,6,Rural,Data Analyst,119958,1 +76867,Male,44,Bachelors,16,69,91,84,26,8.0,0,6,Rural,HR Executive,115802,1 +76868,Male,25,High School,3,30,4,26,61,7.0,7,19,Urban,Data Analyst,109951,0 +76869,Male,30,Bachelors,4,34,68,57,30,0.0,3,6,Urban,Software Engineer,89818,0 +76870,Male,37,Bachelors,12,92,73,32,27,2.0,3,63,Urban,Data Analyst,131642,1 +76871,Female,48,Masters,4,63,18,41,96,4.0,1,26,Semi-Urban,Software Engineer,144158,0 +76872,Female,48,High School,6,39,49,21,32,6.0,5,86,Semi-Urban,HR Executive,81988,0 +76873,Male,51,Masters,14,9,23,33,5,7.0,6,52,Urban,HR Executive,33461,0 +76874,Male,21,PhD,16,47,46,68,72,4.0,3,78,Semi-Urban,HR Executive,20950,1 +76875,Male,38,Bachelors,13,49,49,18,16,8.0,5,22,Rural,Data Analyst,107229,0 +76876,Male,42,Masters,12,97,29,93,17,3.0,7,84,Urban,Manager,82692,1 +76877,Male,35,Diploma,10,57,29,33,46,1.0,2,46,Semi-Urban,Manager,127701,0 +76878,Female,50,Diploma,11,36,22,70,30,1.0,2,93,Urban,HR Executive,41865,0 +76879,Male,39,Diploma,7,37,14,72,74,1.0,0,92,Urban,Software Engineer,144301,0 +76880,Female,52,Masters,7,20,91,52,1,2.0,0,60,Semi-Urban,ML Engineer,82821,0 +76881,Female,54,Bachelors,13,25,37,79,58,8.0,1,79,Semi-Urban,ML Engineer,61726,0 +76882,Female,50,Masters,13,43,38,27,33,8.0,2,1,Semi-Urban,Manager,50932,0 +76883,Female,44,Diploma,18,15,90,43,85,0.0,7,24,Urban,Data Analyst,111990,0 +76884,Male,48,Bachelors,8,49,79,18,8,4.0,5,2,Urban,Software Engineer,40953,0 +76885,Female,27,Bachelors,12,0,15,95,39,5.0,0,9,Urban,HR Executive,106145,0 +76886,Male,46,Bachelors,6,26,63,46,85,9.0,6,83,Urban,Software Engineer,145526,0 +76887,Male,52,High School,3,39,32,6,20,4.0,0,36,Urban,ML Engineer,78196,0 +76888,Female,51,High School,10,83,44,5,68,6.0,6,77,Semi-Urban,Data Analyst,74004,0 +76889,Female,54,Bachelors,10,12,26,25,16,7.0,6,35,Semi-Urban,HR Executive,108536,0 +76890,Male,42,Masters,11,39,54,40,2,6.0,7,59,Semi-Urban,HR Executive,72480,0 +76891,Male,43,Bachelors,14,25,89,21,26,6.0,6,90,Rural,ML Engineer,85946,0 +76892,Female,57,Diploma,0,52,0,61,71,7.0,6,12,Semi-Urban,ML Engineer,52594,0 +76893,Female,21,Bachelors,18,18,88,2,83,4.0,2,35,Rural,Data Analyst,27881,0 +76894,Male,41,Bachelors,6,4,26,6,59,0.0,2,20,Semi-Urban,HR Executive,23488,0 +76895,Female,36,Diploma,8,8,74,23,34,9.0,6,46,Urban,Manager,65394,0 +76896,Female,43,Diploma,0,82,81,16,43,8.0,2,70,Urban,Software Engineer,70541,1 +76897,Male,43,Bachelors,13,52,44,19,51,0.0,1,41,Urban,HR Executive,128026,0 +76898,Female,47,High School,4,74,93,42,0,7.0,2,0,Rural,ML Engineer,49823,0 +76899,Female,50,Diploma,9,30,61,55,92,1.0,0,44,Rural,HR Executive,142929,0 +76900,Female,57,Bachelors,18,78,58,99,49,6.0,3,86,Urban,ML Engineer,93620,1 +76901,Male,38,Diploma,14,30,32,8,4,5.0,6,97,Urban,Manager,29634,0 +76902,Female,25,High School,10,67,32,95,30,7.0,5,40,Semi-Urban,Manager,104047,0 +76903,Male,27,Bachelors,17,93,42,67,57,3.0,4,29,Urban,Data Analyst,94381,0 +76904,Female,35,Bachelors,11,69,72,91,35,6.0,4,40,Urban,Data Analyst,101709,1 +76905,Male,59,Bachelors,3,84,83,15,82,6.0,0,36,Urban,Software Engineer,139156,0 +76906,Male,50,PhD,9,48,62,71,39,8.0,4,38,Rural,Data Analyst,80959,0 +76907,Female,59,Bachelors,3,45,76,35,28,7.0,2,82,Rural,Software Engineer,94410,0 +76908,Male,27,High School,5,97,53,39,59,3.0,5,74,Urban,Manager,127521,1 +76909,Male,36,Bachelors,11,92,76,33,10,2.0,0,33,Rural,Data Analyst,105476,0 +76910,Female,26,High School,16,16,35,34,99,8.0,4,46,Semi-Urban,Software Engineer,81336,0 +76911,Male,32,Masters,15,85,27,50,81,2.0,7,79,Rural,Manager,74574,1 +76912,Male,27,High School,18,54,47,97,28,1.0,7,29,Urban,Software Engineer,75162,0 +76913,Female,58,Bachelors,2,13,69,29,76,4.0,4,89,Urban,Software Engineer,48889,0 +76914,Female,21,Diploma,18,90,27,23,22,0.0,2,31,Urban,Software Engineer,116134,0 +76915,Male,23,Diploma,0,96,16,38,20,1.0,2,76,Semi-Urban,Manager,30716,0 +76916,Male,29,Bachelors,16,32,33,69,72,2.0,4,76,Urban,Manager,30605,0 +76917,Male,34,Diploma,12,20,63,7,14,1.0,2,55,Semi-Urban,Data Analyst,89764,0 +76918,Male,32,PhD,10,42,93,72,4,1.0,2,90,Urban,HR Executive,125447,1 +76919,Male,26,Masters,5,17,13,16,31,5.0,4,15,Urban,ML Engineer,58850,0 +76920,Male,34,High School,0,11,82,90,53,1.0,2,82,Urban,ML Engineer,62265,1 +76921,Male,28,Bachelors,12,39,39,86,5,1.0,5,82,Urban,ML Engineer,107287,1 +76922,Other,53,Masters,1,27,49,48,84,5.0,4,90,Rural,ML Engineer,84704,0 +76923,Female,33,PhD,13,67,29,79,38,5.0,0,89,Urban,ML Engineer,87791,1 +76924,Male,51,Diploma,4,46,59,40,64,3.0,0,46,Semi-Urban,HR Executive,30959,0 +76925,Female,21,Diploma,6,34,85,81,7,3.0,0,75,Rural,ML Engineer,76800,1 +76926,Male,31,Diploma,4,64,90,53,25,2.0,3,51,Semi-Urban,Data Analyst,78769,1 +76927,Male,59,PhD,1,68,74,33,29,6.0,5,61,Urban,Manager,137067,1 +76928,Female,51,Masters,19,89,35,43,69,2.0,3,53,Semi-Urban,Data Analyst,51873,0 +76929,Female,56,Bachelors,3,24,48,19,6,4.0,7,98,Urban,HR Executive,106665,0 +76930,Male,42,High School,15,29,57,17,50,7.0,5,41,Urban,ML Engineer,39053,0 +76931,Other,36,Diploma,1,95,46,43,99,2.0,6,68,Rural,Manager,59980,1 +76932,Female,32,Bachelors,12,49,25,84,36,1.0,3,34,Urban,Manager,94309,0 +76933,Male,55,Bachelors,4,90,72,32,99,6.0,3,61,Urban,HR Executive,47834,1 +76934,Male,23,Masters,11,45,85,24,85,4.0,6,24,Urban,HR Executive,47576,0 +76935,Male,27,Bachelors,14,90,33,48,82,6.0,5,37,Semi-Urban,Data Analyst,56420,0 +76936,Female,52,Diploma,18,62,73,76,37,4.0,7,29,Urban,Software Engineer,65998,0 +76937,Male,30,Bachelors,16,55,4,49,66,3.0,4,79,Rural,Data Analyst,147786,0 +76938,Male,33,Diploma,0,14,99,34,82,3.0,3,96,Rural,HR Executive,134204,1 +76939,Female,35,Masters,0,62,85,10,19,0.0,0,93,Semi-Urban,ML Engineer,62469,1 +76940,Male,44,Diploma,3,51,36,89,38,7.0,6,50,Urban,Software Engineer,131443,0 +76941,Male,44,Bachelors,0,5,12,18,31,5.0,4,64,Rural,Manager,107519,0 +76942,Female,27,Diploma,12,89,5,50,89,2.0,7,36,Urban,Software Engineer,115826,0 +76943,Male,40,Bachelors,13,96,93,1,8,0.0,7,11,Semi-Urban,Software Engineer,89877,0 +76944,Male,31,Masters,7,76,93,37,0,2.0,3,28,Urban,Software Engineer,106010,0 +76945,Male,38,Masters,14,64,79,97,37,9.0,3,32,Rural,Manager,45268,1 +76946,Female,39,PhD,18,14,22,29,13,1.0,3,64,Urban,HR Executive,25353,0 +76947,Female,42,Bachelors,2,36,76,79,59,6.0,2,39,Urban,HR Executive,118781,0 +76948,Female,41,Diploma,18,11,8,87,75,1.0,5,20,Urban,Data Analyst,135714,0 +76949,Female,35,Masters,2,22,44,19,46,5.0,4,30,Semi-Urban,ML Engineer,78140,0 +76950,Male,40,Bachelors,17,59,4,9,19,0.0,2,73,Rural,Data Analyst,57749,0 +76951,Female,22,Bachelors,6,1,86,40,81,6.0,7,75,Urban,Data Analyst,42332,0 +76952,Male,50,Bachelors,5,87,41,11,89,9.0,6,11,Rural,Software Engineer,27998,0 +76953,Female,46,Diploma,5,3,69,55,66,4.0,7,26,Rural,Data Analyst,74692,0 +76954,Male,27,Diploma,12,24,26,53,33,4.0,5,42,Semi-Urban,Software Engineer,36856,0 +76955,Female,38,Bachelors,14,72,65,30,55,5.0,4,30,Semi-Urban,HR Executive,84295,0 +76956,Female,32,Bachelors,2,23,99,86,28,6.0,2,27,Urban,ML Engineer,39028,0 +76957,Male,22,Diploma,3,95,36,52,9,1.0,7,62,Urban,ML Engineer,32475,1 +76958,Other,51,Bachelors,9,59,88,51,78,1.0,5,8,Urban,Data Analyst,22352,0 +76959,Male,54,Masters,9,90,67,1,93,3.0,1,6,Urban,Manager,28313,0 +76960,Male,34,Diploma,8,56,65,43,7,8.0,5,96,Urban,HR Executive,130244,1 +76961,Female,41,Masters,0,9,11,83,16,0.0,4,48,Rural,Manager,140814,0 +76962,Male,37,Masters,7,29,65,6,47,5.0,5,88,Urban,Data Analyst,146079,0 +76963,Female,29,Diploma,13,26,81,44,87,6.0,3,33,Urban,ML Engineer,53801,0 +76964,Male,42,Diploma,15,87,17,37,68,8.0,3,90,Semi-Urban,Manager,37029,0 +76965,Male,41,High School,2,80,45,55,83,2.0,7,32,Semi-Urban,ML Engineer,52179,0 +76966,Female,31,Masters,0,26,91,93,25,2.0,6,3,Semi-Urban,Data Analyst,61180,0 +76967,Male,53,Bachelors,16,30,2,18,10,0.0,4,4,Semi-Urban,Software Engineer,72496,0 +76968,Male,43,Bachelors,17,78,70,89,9,9.0,2,85,Rural,Data Analyst,43583,1 +76969,Female,43,Diploma,1,36,56,7,25,4.0,1,6,Urban,ML Engineer,116892,0 +76970,Female,55,Diploma,8,7,16,66,36,5.0,5,36,Urban,Manager,135564,0 +76971,Female,47,Masters,1,66,81,61,16,5.0,3,26,Urban,Software Engineer,137547,0 +76972,Male,25,High School,11,31,80,27,85,5.0,0,7,Rural,HR Executive,107031,0 +76973,Female,40,Masters,0,96,32,20,73,4.0,2,23,Urban,ML Engineer,72369,0 +76974,Other,43,Diploma,5,77,73,13,78,8.0,1,52,Urban,HR Executive,62031,0 +76975,Male,25,Diploma,12,22,43,96,78,7.0,3,5,Urban,Manager,42925,0 +76976,Female,44,High School,5,48,92,44,43,2.0,6,63,Urban,HR Executive,67071,1 +76977,Male,56,Diploma,13,0,11,62,40,5.0,1,0,Semi-Urban,HR Executive,140371,0 +76978,Male,49,Bachelors,19,12,24,26,84,2.0,1,45,Urban,Manager,59577,0 +76979,Male,36,Bachelors,0,9,82,22,67,3.0,0,50,Rural,Data Analyst,108468,0 +76980,Male,23,Bachelors,4,25,54,13,5,3.0,6,55,Rural,Manager,102638,0 +76981,Male,44,Bachelors,14,96,99,17,57,7.0,5,81,Urban,HR Executive,97934,1 +76982,Male,30,Diploma,8,74,99,60,19,1.0,5,60,Urban,ML Engineer,43595,1 +76983,Male,42,Diploma,12,9,15,69,31,5.0,6,0,Semi-Urban,HR Executive,105993,0 +76984,Male,36,Bachelors,16,6,75,83,27,2.0,3,63,Rural,Data Analyst,83428,0 +76985,Male,23,Bachelors,6,49,42,40,36,8.0,2,80,Rural,Manager,124704,0 +76986,Male,26,Diploma,15,66,15,38,63,5.0,5,68,Urban,ML Engineer,120255,0 +76987,Female,56,High School,0,9,32,4,47,0.0,3,87,Urban,Manager,67521,0 +76988,Male,52,Bachelors,4,42,39,20,17,2.0,6,29,Urban,Manager,55898,0 +76989,Female,32,PhD,6,89,17,82,37,3.0,4,16,Urban,Data Analyst,78361,0 +76990,Male,58,Bachelors,8,19,14,86,22,0.0,0,46,Rural,ML Engineer,92737,0 +76991,Male,27,High School,17,7,75,91,45,1.0,2,3,Urban,Software Engineer,127307,0 +76992,Male,24,High School,7,5,23,13,21,8.0,7,62,Rural,HR Executive,25738,0 +76993,Female,34,Diploma,0,22,20,78,0,2.0,7,48,Urban,Software Engineer,38092,0 +76994,Female,23,High School,4,87,21,6,31,5.0,6,0,Rural,HR Executive,74907,0 +76995,Male,38,High School,2,88,92,91,56,6.0,2,22,Rural,Manager,40333,1 +76996,Male,27,Bachelors,6,81,33,19,12,5.0,3,44,Urban,HR Executive,78735,0 +76997,Female,24,High School,19,31,36,18,34,6.0,1,91,Urban,ML Engineer,104198,0 +76998,Male,38,Diploma,13,19,50,55,25,4.0,4,37,Urban,HR Executive,136644,0 +76999,Female,26,Masters,5,95,72,39,78,3.0,3,59,Rural,Manager,139853,1 +77000,Female,38,High School,18,32,25,97,34,0.0,3,21,Rural,Data Analyst,38553,0 +77001,Female,45,Masters,3,41,8,67,80,9.0,0,35,Urban,HR Executive,120912,0 +77002,Male,35,High School,3,98,94,19,30,5.0,1,46,Urban,ML Engineer,73376,1 +77003,Male,31,Masters,14,24,6,71,99,4.0,6,28,Rural,Data Analyst,61727,0 +77004,Female,43,Masters,12,54,49,7,9,6.0,4,3,Semi-Urban,ML Engineer,90704,0 +77005,Male,32,Diploma,12,82,18,42,43,1.0,1,18,Urban,HR Executive,51963,0 +77006,Male,52,Diploma,3,84,67,7,82,8.0,7,65,Urban,HR Executive,46757,0 +77007,Female,57,Diploma,12,45,17,45,11,5.0,2,31,Semi-Urban,Data Analyst,134986,0 +77008,Male,34,Bachelors,12,2,13,14,33,7.0,3,52,Urban,ML Engineer,127321,0 +77009,Female,49,Bachelors,10,66,84,48,61,4.0,4,69,Semi-Urban,Data Analyst,121594,1 +77010,Other,47,Diploma,2,7,72,85,99,7.0,5,38,Rural,Manager,132146,0 +77011,Male,59,Masters,9,56,78,45,89,8.0,6,62,Rural,Software Engineer,108605,1 +77012,Male,30,Masters,13,83,54,97,97,7.0,6,4,Urban,HR Executive,49819,1 +77013,Male,36,Bachelors,13,68,61,36,19,2.0,6,81,Rural,Data Analyst,128735,1 +77014,Male,22,Diploma,3,82,87,86,44,1.0,3,43,Semi-Urban,HR Executive,85767,1 +77015,Male,32,Diploma,1,37,7,0,30,3.0,5,19,Urban,Manager,90464,0 +77016,Male,22,Diploma,3,83,27,77,10,5.0,3,43,Rural,Software Engineer,90065,0 +77017,Male,25,PhD,4,51,55,5,82,2.0,0,2,Rural,ML Engineer,74240,0 +77018,Male,56,PhD,17,94,58,61,28,4.0,1,24,Rural,Data Analyst,133111,1 +77019,Female,58,High School,11,22,18,66,66,6.0,3,46,Rural,Manager,130277,0 +77020,Other,56,Masters,12,84,90,50,59,7.0,4,73,Semi-Urban,Manager,82014,1 +77021,Male,42,Bachelors,11,60,63,53,6,0.0,7,47,Urban,ML Engineer,129471,0 +77022,Female,49,Masters,3,65,14,73,94,7.0,2,77,Rural,HR Executive,133248,0 +77023,Male,41,Diploma,9,68,24,53,65,7.0,5,37,Rural,HR Executive,140891,0 +77024,Male,27,Bachelors,9,11,12,68,65,1.0,4,51,Urban,HR Executive,77139,0 +77025,Female,43,PhD,12,91,57,60,33,9.0,1,36,Urban,Data Analyst,137602,1 +77026,Male,36,Diploma,0,91,4,57,39,1.0,6,97,Semi-Urban,Software Engineer,80221,1 +77027,Male,43,High School,3,78,8,5,38,3.0,6,32,Rural,ML Engineer,111594,0 +77028,Male,34,PhD,12,6,90,37,7,2.0,1,87,Rural,Software Engineer,140449,0 +77029,Male,44,Bachelors,12,37,44,20,29,2.0,6,17,Urban,Manager,76422,0 +77030,Male,50,Diploma,0,57,65,37,79,2.0,1,32,Semi-Urban,Manager,84514,0 +77031,Male,43,Diploma,16,92,45,55,53,9.0,4,73,Semi-Urban,Software Engineer,68395,1 +77032,Male,53,Bachelors,7,85,36,90,88,4.0,3,31,Urban,Data Analyst,108095,1 +77033,Male,34,Diploma,15,16,17,99,41,2.0,7,67,Urban,Manager,30499,0 +77034,Male,41,Diploma,6,31,43,64,53,6.0,1,68,Semi-Urban,Software Engineer,144441,0 +77035,Male,27,Bachelors,9,7,54,79,37,6.0,6,61,Rural,Software Engineer,149536,0 +77036,Female,28,Masters,11,49,63,93,73,0.0,7,66,Urban,Data Analyst,114519,1 +77037,Male,49,Bachelors,8,99,83,45,42,1.0,7,94,Urban,Software Engineer,113225,1 +77038,Other,21,High School,3,7,13,69,3,4.0,2,48,Urban,Manager,144876,0 +77039,Male,57,High School,18,86,75,19,34,0.0,2,81,Rural,ML Engineer,60317,1 +77040,Male,34,High School,0,76,20,75,94,7.0,1,67,Urban,ML Engineer,82392,1 +77041,Male,48,Diploma,17,50,38,53,33,3.0,0,95,Semi-Urban,Software Engineer,94940,1 +77042,Female,52,Bachelors,19,27,1,95,11,6.0,0,87,Urban,HR Executive,69801,0 +77043,Female,51,Diploma,5,97,49,89,13,6.0,2,70,Urban,Data Analyst,84420,1 +77044,Female,22,Masters,0,8,58,38,29,3.0,4,46,Semi-Urban,HR Executive,36163,0 +77045,Male,23,Masters,14,59,41,70,92,3.0,6,60,Urban,Software Engineer,55663,0 +77046,Male,33,Bachelors,15,38,18,56,49,1.0,3,87,Urban,Manager,131868,0 +77047,Female,28,High School,0,51,79,84,73,5.0,7,38,Rural,HR Executive,118229,1 +77048,Female,51,Masters,10,76,3,82,69,4.0,0,43,Urban,Software Engineer,129961,0 +77049,Male,31,High School,6,16,83,7,6,2.0,4,10,Semi-Urban,Manager,139622,0 +77050,Female,58,Bachelors,15,4,97,95,19,7.0,6,11,Urban,Data Analyst,40529,0 +77051,Female,44,Diploma,7,63,51,14,89,9.0,6,29,Semi-Urban,Software Engineer,117046,0 +77052,Male,33,Diploma,14,49,30,2,91,9.0,2,29,Urban,Data Analyst,138501,0 +77053,Male,30,Masters,4,82,67,43,61,3.0,0,28,Urban,Data Analyst,26569,0 +77054,Male,46,Bachelors,1,77,22,35,10,5.0,7,26,Semi-Urban,Manager,94933,0 +77055,Female,46,Masters,4,66,56,93,81,9.0,7,39,Urban,Manager,113614,1 +77056,Male,53,High School,5,60,15,79,12,1.0,1,15,Urban,Manager,23408,0 +77057,Male,35,Diploma,14,65,13,85,88,6.0,2,38,Rural,Manager,99179,0 +77058,Male,44,Masters,7,28,62,40,75,7.0,3,14,Urban,Data Analyst,78724,0 +77059,Female,35,High School,7,42,47,72,92,1.0,2,15,Urban,Manager,33872,0 +77060,Male,53,Masters,5,72,46,42,24,7.0,0,30,Semi-Urban,ML Engineer,49426,0 +77061,Female,27,High School,13,84,1,87,52,4.0,1,47,Semi-Urban,Software Engineer,64492,0 +77062,Female,49,PhD,18,55,82,55,16,3.0,6,6,Rural,HR Executive,41674,0 +77063,Female,58,Bachelors,11,54,96,94,1,6.0,6,11,Urban,Manager,50437,1 +77064,Female,39,High School,9,22,96,95,26,2.0,6,84,Urban,ML Engineer,104295,1 +77065,Female,39,Bachelors,8,1,20,78,60,1.0,6,63,Rural,Manager,53949,0 +77066,Male,49,Bachelors,2,71,79,45,2,4.0,2,98,Urban,ML Engineer,45550,1 +77067,Male,53,Masters,19,47,21,94,78,7.0,4,69,Semi-Urban,Software Engineer,68176,0 +77068,Male,39,Bachelors,5,66,11,34,86,6.0,7,41,Rural,Software Engineer,131098,0 +77069,Male,33,Bachelors,17,59,5,76,13,1.0,5,11,Rural,Software Engineer,115275,0 +77070,Male,39,Masters,9,93,21,60,78,9.0,5,25,Semi-Urban,HR Executive,90215,0 +77071,Male,57,Bachelors,5,36,26,98,11,4.0,4,18,Semi-Urban,ML Engineer,118384,0 +77072,Female,22,Masters,5,2,53,0,61,9.0,4,22,Rural,ML Engineer,122834,0 +77073,Male,51,Masters,16,83,75,25,37,4.0,6,43,Semi-Urban,Data Analyst,75877,0 +77074,Male,57,Bachelors,2,61,87,93,86,2.0,0,55,Rural,Software Engineer,135767,1 +77075,Female,29,Bachelors,9,19,56,46,2,7.0,6,96,Semi-Urban,Data Analyst,82960,0 +77076,Female,34,Bachelors,7,69,48,44,54,2.0,4,98,Urban,HR Executive,109014,1 +77077,Male,37,Diploma,0,48,70,34,98,7.0,3,80,Urban,Manager,73428,0 +77078,Male,22,PhD,7,67,50,16,33,8.0,1,0,Urban,Manager,31272,0 +77079,Male,46,PhD,7,12,66,47,34,6.0,6,5,Urban,HR Executive,119437,0 +77080,Male,40,Masters,3,9,47,72,95,3.0,2,26,Semi-Urban,HR Executive,66552,0 +77081,Female,25,Bachelors,4,32,71,11,67,3.0,6,29,Urban,ML Engineer,96313,0 +77082,Male,56,Masters,5,66,42,6,94,9.0,6,26,Urban,Software Engineer,87284,0 +77083,Female,26,Masters,15,39,45,24,47,6.0,3,9,Semi-Urban,Data Analyst,73339,0 +77084,Male,37,Masters,16,65,45,96,21,7.0,3,84,Semi-Urban,ML Engineer,75699,1 +77085,Male,40,Diploma,4,26,23,46,63,0.0,1,3,Rural,Software Engineer,68377,0 +77086,Male,57,PhD,11,31,79,35,82,6.0,5,49,Urban,HR Executive,107508,0 +77087,Male,47,High School,4,75,85,68,38,4.0,0,76,Urban,HR Executive,60768,1 +77088,Male,52,Bachelors,11,68,10,84,41,7.0,1,45,Semi-Urban,Data Analyst,24182,0 +77089,Female,30,High School,15,37,73,19,82,7.0,5,20,Rural,ML Engineer,25714,0 +77090,Male,40,Masters,7,19,62,91,91,0.0,6,93,Urban,HR Executive,61847,1 +77091,Female,21,Diploma,17,4,32,78,2,7.0,7,11,Semi-Urban,Software Engineer,73229,0 +77092,Female,21,Masters,2,54,73,13,14,3.0,0,95,Rural,HR Executive,133438,0 +77093,Male,27,Masters,3,60,17,48,88,4.0,4,23,Rural,HR Executive,61834,0 +77094,Male,50,Bachelors,12,6,66,10,41,4.0,5,92,Urban,Software Engineer,28491,0 +77095,Female,44,Diploma,10,62,76,22,19,9.0,4,19,Rural,ML Engineer,129084,0 +77096,Male,39,Masters,0,27,30,48,68,0.0,4,15,Urban,ML Engineer,130199,0 +77097,Male,53,High School,12,70,97,2,20,0.0,3,36,Semi-Urban,ML Engineer,95646,0 +77098,Female,35,Bachelors,3,21,26,60,49,1.0,5,22,Semi-Urban,ML Engineer,135675,0 +77099,Male,34,High School,19,94,9,93,19,4.0,7,40,Semi-Urban,Data Analyst,90284,1 +77100,Male,45,Bachelors,18,46,48,57,81,6.0,4,51,Urban,ML Engineer,133251,0 +77101,Female,43,Masters,7,97,60,86,65,0.0,3,2,Urban,Software Engineer,85445,1 +77102,Male,45,Bachelors,2,27,84,10,44,2.0,5,52,Urban,HR Executive,112884,0 +77103,Female,57,Bachelors,5,75,72,36,33,2.0,4,60,Urban,Data Analyst,128877,1 +77104,Female,28,Diploma,5,97,91,81,64,8.0,0,19,Urban,Software Engineer,117668,1 +77105,Male,49,Masters,19,60,9,25,45,9.0,3,57,Urban,HR Executive,24801,0 +77106,Male,47,Diploma,7,95,78,79,6,5.0,1,3,Urban,Manager,104910,1 +77107,Male,27,Bachelors,7,72,21,11,83,1.0,1,47,Semi-Urban,Software Engineer,148979,0 +77108,Male,57,Masters,7,79,46,11,2,0.0,2,37,Urban,ML Engineer,46517,0 +77109,Male,30,Bachelors,2,47,25,44,6,5.0,4,76,Rural,Manager,146440,0 +77110,Male,36,Bachelors,18,46,84,4,10,5.0,3,58,Semi-Urban,Software Engineer,45730,0 +77111,Male,34,Bachelors,3,66,21,70,55,3.0,7,40,Urban,Manager,24877,0 +77112,Male,58,High School,7,50,76,98,15,3.0,7,58,Urban,HR Executive,94836,1 +77113,Female,41,Diploma,11,30,72,22,1,7.0,0,20,Rural,Manager,79572,0 +77114,Other,51,High School,11,86,98,87,92,2.0,2,4,Urban,Data Analyst,20087,1 +77115,Male,25,Bachelors,1,71,66,78,53,2.0,2,37,Urban,HR Executive,28119,1 +77116,Male,30,Bachelors,16,94,74,98,46,8.0,1,69,Urban,Software Engineer,29697,1 +77117,Male,54,Diploma,10,22,64,94,50,8.0,4,65,Urban,HR Executive,121851,1 +77118,Female,31,Bachelors,2,15,77,89,60,7.0,4,17,Urban,ML Engineer,108938,0 +77119,Male,34,Masters,5,45,35,3,21,3.0,6,21,Urban,ML Engineer,90082,0 +77120,Female,49,Diploma,15,74,21,6,19,6.0,0,87,Rural,Manager,107791,0 +77121,Female,28,Masters,1,23,33,90,28,7.0,5,48,Urban,Manager,63724,0 +77122,Male,31,PhD,0,36,82,33,63,1.0,5,47,Urban,Manager,98868,0 +77123,Male,32,High School,14,13,37,75,73,3.0,7,85,Urban,Data Analyst,49796,0 +77124,Male,21,Bachelors,8,43,49,45,41,0.0,2,71,Urban,Data Analyst,66202,0 +77125,Male,45,High School,5,20,65,95,72,5.0,2,8,Urban,HR Executive,94183,0 +77126,Male,26,High School,18,49,66,31,55,2.0,7,63,Urban,Manager,141179,0 +77127,Male,33,Bachelors,1,74,31,13,95,9.0,6,94,Urban,HR Executive,47707,0 +77128,Female,46,Diploma,4,36,62,67,1,9.0,3,10,Urban,ML Engineer,120700,0 +77129,Male,49,Bachelors,8,88,71,75,3,8.0,3,19,Urban,Software Engineer,68695,1 +77130,Male,47,Masters,3,30,98,3,6,6.0,7,82,Rural,Data Analyst,85630,0 +77131,Male,38,High School,15,25,7,80,32,5.0,4,29,Urban,ML Engineer,97329,0 +77132,Male,48,Diploma,8,80,64,78,84,4.0,4,68,Urban,Manager,48320,1 +77133,Male,39,Diploma,19,88,41,0,21,8.0,7,94,Urban,Manager,109804,0 +77134,Male,48,Masters,8,87,32,78,40,6.0,6,11,Urban,Software Engineer,57660,0 +77135,Male,23,Masters,15,45,2,96,95,1.0,1,87,Rural,Software Engineer,46735,0 +77136,Female,24,Masters,15,94,86,87,85,6.0,0,6,Semi-Urban,Software Engineer,61100,1 +77137,Female,43,Diploma,2,80,4,18,87,3.0,6,1,Urban,HR Executive,132296,0 +77138,Male,37,Bachelors,4,40,80,96,63,4.0,3,61,Semi-Urban,HR Executive,71614,1 +77139,Male,57,Bachelors,0,88,32,71,9,4.0,4,39,Semi-Urban,HR Executive,141482,0 +77140,Male,45,Diploma,4,47,55,36,89,7.0,3,7,Urban,ML Engineer,101626,0 +77141,Male,57,Bachelors,5,17,67,45,16,8.0,7,58,Urban,Manager,104875,0 +77142,Male,24,Masters,15,17,62,94,59,8.0,6,44,Urban,Manager,137861,0 +77143,Male,28,Diploma,16,70,30,86,74,4.0,5,98,Semi-Urban,ML Engineer,117850,1 +77144,Male,30,High School,12,85,87,95,67,9.0,0,88,Urban,Software Engineer,101250,1 +77145,Male,41,Masters,17,5,88,61,41,7.0,5,83,Urban,Data Analyst,121681,1 +77146,Female,43,Diploma,8,29,56,52,45,7.0,6,67,Rural,Software Engineer,55563,0 +77147,Male,53,Diploma,16,14,18,7,48,9.0,5,16,Rural,HR Executive,49252,0 +77148,Female,46,Masters,0,68,62,14,15,7.0,0,8,Urban,ML Engineer,119974,0 +77149,Male,31,Bachelors,10,57,96,8,0,4.0,1,53,Urban,Manager,110195,0 +77150,Male,54,Diploma,6,72,10,85,98,0.0,7,11,Rural,ML Engineer,61171,0 +77151,Female,32,Diploma,9,7,80,42,29,4.0,4,2,Urban,ML Engineer,76051,0 +77152,Male,49,High School,8,46,72,59,22,2.0,1,56,Urban,Manager,93223,0 +77153,Male,38,Bachelors,5,5,52,49,51,3.0,6,15,Urban,Manager,79690,0 +77154,Male,23,Masters,3,89,22,26,36,2.0,7,69,Semi-Urban,HR Executive,118174,0 +77155,Male,47,Masters,19,10,51,75,70,8.0,5,64,Urban,Software Engineer,96779,0 +77156,Female,23,Bachelors,1,47,60,62,66,3.0,7,82,Urban,Manager,113523,1 +77157,Male,51,Masters,6,48,92,11,49,5.0,7,69,Urban,Data Analyst,86212,0 +77158,Female,39,Diploma,13,69,89,19,44,3.0,5,25,Urban,Data Analyst,125103,0 +77159,Male,28,Bachelors,14,40,28,51,17,8.0,2,24,Urban,HR Executive,98287,0 +77160,Female,46,Masters,4,9,56,17,71,3.0,5,95,Urban,ML Engineer,146580,0 +77161,Female,34,Masters,10,2,42,51,50,5.0,7,49,Semi-Urban,Data Analyst,84213,0 +77162,Male,45,Bachelors,4,7,37,87,34,5.0,5,19,Semi-Urban,Software Engineer,80122,0 +77163,Female,58,Bachelors,3,35,64,78,92,6.0,3,72,Urban,Software Engineer,33950,1 +77164,Male,23,PhD,3,69,84,39,12,5.0,3,87,Urban,Data Analyst,87299,1 +77165,Male,25,Bachelors,11,9,42,61,63,7.0,1,38,Urban,HR Executive,125600,0 +77166,Male,35,Masters,15,1,71,16,3,4.0,7,90,Urban,HR Executive,47348,0 +77167,Other,21,Bachelors,13,38,66,69,13,1.0,4,26,Urban,Data Analyst,104252,0 +77168,Male,57,Bachelors,11,90,91,84,70,4.0,5,64,Urban,Data Analyst,143737,1 +77169,Other,28,Bachelors,9,66,10,52,43,0.0,7,95,Rural,ML Engineer,117863,0 +77170,Male,54,Bachelors,4,38,16,91,18,0.0,5,40,Urban,HR Executive,49139,0 +77171,Female,45,Bachelors,19,85,13,10,49,4.0,3,54,Semi-Urban,HR Executive,121437,0 +77172,Male,42,Bachelors,15,68,28,10,36,9.0,2,70,Urban,HR Executive,101781,0 +77173,Male,53,Bachelors,4,90,14,31,50,5.0,3,93,Rural,Data Analyst,76069,0 +77174,Female,40,Bachelors,6,44,58,55,34,3.0,6,22,Semi-Urban,HR Executive,88979,0 +77175,Male,38,Masters,0,47,4,89,39,2.0,4,13,Urban,Data Analyst,68246,0 +77176,Female,24,Diploma,11,85,78,71,87,7.0,5,23,Semi-Urban,ML Engineer,96760,1 +77177,Female,57,High School,0,81,71,19,70,6.0,0,84,Urban,HR Executive,106392,1 +77178,Female,53,Bachelors,3,60,84,72,3,4.0,0,21,Urban,Manager,71596,0 +77179,Female,49,Bachelors,17,0,16,46,49,3.0,0,35,Rural,ML Engineer,114900,0 +77180,Male,50,Bachelors,8,53,11,51,96,8.0,6,47,Semi-Urban,HR Executive,68145,0 +77181,Male,46,Masters,14,32,45,74,49,2.0,6,22,Urban,Data Analyst,49393,0 +77182,Female,24,Diploma,9,28,26,24,79,6.0,1,89,Rural,Software Engineer,20137,0 +77183,Female,57,High School,1,37,39,58,50,4.0,4,4,Rural,ML Engineer,91811,0 +77184,Male,50,Diploma,14,41,99,4,42,5.0,4,43,Rural,HR Executive,126970,0 +77185,Male,56,Bachelors,1,67,4,44,87,0.0,6,95,Urban,ML Engineer,97215,0 +77186,Male,24,Masters,1,96,37,56,73,1.0,4,73,Urban,Manager,23515,1 +77187,Male,56,Masters,7,38,88,36,92,7.0,1,31,Urban,Data Analyst,80415,0 +77188,Male,44,PhD,16,45,76,77,4,2.0,1,15,Urban,Manager,105443,0 +77189,Male,57,Bachelors,11,58,23,82,51,4.0,3,78,Semi-Urban,HR Executive,46152,1 +77190,Female,40,Bachelors,14,0,5,44,36,4.0,5,36,Rural,Software Engineer,49913,0 +77191,Male,41,Masters,18,39,57,92,15,9.0,6,89,Urban,Data Analyst,59354,1 +77192,Male,28,Bachelors,6,80,82,28,71,6.0,2,17,Urban,ML Engineer,120000,0 +77193,Female,49,Bachelors,2,87,1,85,91,2.0,5,83,Rural,HR Executive,138827,1 +77194,Male,34,PhD,12,90,69,91,99,6.0,7,99,Semi-Urban,Manager,65687,1 +77195,Male,47,Masters,8,25,56,33,47,6.0,3,80,Urban,HR Executive,28970,0 +77196,Male,37,Bachelors,11,37,30,91,10,0.0,0,95,Semi-Urban,Manager,85968,1 +77197,Female,36,Masters,14,97,21,27,41,8.0,6,58,Urban,Manager,64395,0 +77198,Male,55,Masters,4,72,53,92,8,6.0,3,59,Urban,Data Analyst,93632,1 +77199,Male,50,Masters,11,12,19,52,29,5.0,3,47,Urban,ML Engineer,25006,0 +77200,Female,24,Bachelors,9,69,98,64,40,3.0,6,64,Urban,Data Analyst,138603,1 +77201,Male,49,Diploma,14,26,72,4,20,7.0,3,18,Semi-Urban,Software Engineer,75355,0 +77202,Female,58,Masters,5,98,20,78,67,9.0,3,3,Semi-Urban,ML Engineer,142469,0 +77203,Male,21,High School,3,73,8,54,88,2.0,7,0,Urban,Software Engineer,24740,0 +77204,Female,25,Bachelors,7,8,46,31,9,5.0,2,29,Rural,Data Analyst,29660,0 +77205,Male,47,Diploma,2,11,29,19,46,3.0,1,87,Rural,Data Analyst,32439,0 +77206,Male,34,Bachelors,14,83,62,48,52,0.0,5,11,Rural,HR Executive,103808,0 +77207,Female,25,Diploma,15,35,8,96,76,4.0,1,41,Urban,Data Analyst,118731,0 +77208,Male,45,Bachelors,10,22,26,16,27,1.0,4,82,Semi-Urban,Manager,107097,0 +77209,Male,27,High School,17,69,91,38,46,6.0,0,41,Rural,Manager,117771,1 +77210,Female,33,High School,8,42,80,82,69,2.0,2,98,Semi-Urban,Software Engineer,118498,1 +77211,Male,35,Masters,10,94,3,83,5,3.0,3,37,Urban,Data Analyst,108660,0 +77212,Male,32,Bachelors,0,86,72,47,89,5.0,6,4,Urban,Software Engineer,57485,0 +77213,Male,27,Bachelors,8,40,98,13,77,5.0,6,56,Semi-Urban,Manager,56952,0 +77214,Female,55,Masters,4,30,12,53,4,1.0,3,33,Semi-Urban,Manager,123673,0 +77215,Male,59,Masters,0,99,91,15,17,0.0,1,21,Urban,Data Analyst,34394,0 +77216,Male,36,Masters,17,93,68,54,72,7.0,6,46,Urban,Manager,125193,1 +77217,Male,34,Bachelors,12,25,89,53,11,4.0,4,0,Urban,Software Engineer,107060,0 +77218,Male,31,Bachelors,0,7,99,51,50,1.0,2,98,Semi-Urban,Manager,99720,1 +77219,Male,26,Bachelors,7,48,62,65,70,1.0,5,24,Urban,Manager,46068,0 +77220,Male,21,Bachelors,9,89,85,71,23,7.0,3,17,Urban,Software Engineer,149136,1 +77221,Male,49,Masters,8,56,68,35,35,1.0,6,19,Semi-Urban,HR Executive,141366,0 +77222,Male,36,PhD,14,38,38,44,73,7.0,7,17,Urban,HR Executive,94698,0 +77223,Male,46,Bachelors,8,1,54,65,82,4.0,5,16,Urban,Manager,60807,0 +77224,Male,57,Masters,4,49,24,18,87,3.0,6,21,Urban,Manager,95349,0 +77225,Female,25,Bachelors,1,73,71,80,52,6.0,0,32,Semi-Urban,HR Executive,26613,1 +77226,Female,39,PhD,7,79,20,70,33,1.0,1,85,Urban,ML Engineer,109619,1 +77227,Male,53,Bachelors,5,8,15,27,66,0.0,4,98,Urban,Software Engineer,137253,0 +77228,Male,28,High School,1,70,8,71,95,9.0,2,59,Urban,Data Analyst,149097,0 +77229,Female,37,Diploma,6,88,51,55,42,7.0,1,21,Semi-Urban,ML Engineer,41603,0 +77230,Female,27,Bachelors,2,65,52,97,9,9.0,3,6,Semi-Urban,ML Engineer,129045,0 +77231,Female,48,Diploma,7,67,18,56,33,1.0,2,2,Urban,Manager,101690,0 +77232,Male,25,Masters,15,57,32,71,12,5.0,2,68,Urban,Software Engineer,25121,0 +77233,Male,24,High School,15,34,25,48,22,4.0,0,33,Urban,ML Engineer,149670,0 +77234,Male,28,Masters,6,86,83,29,88,1.0,2,76,Urban,Manager,110937,1 +77235,Female,27,Masters,16,17,95,19,94,7.0,7,42,Urban,Software Engineer,91050,0 +77236,Male,58,Masters,11,69,61,43,6,4.0,6,21,Urban,ML Engineer,30353,0 +77237,Male,56,Masters,19,77,32,52,14,9.0,2,62,Urban,Software Engineer,113438,0 +77238,Female,49,Bachelors,10,56,41,13,33,3.0,4,73,Urban,HR Executive,112009,0 +77239,Female,30,Bachelors,8,68,29,3,52,2.0,3,85,Urban,Manager,98901,0 +77240,Female,23,Masters,5,17,24,34,11,7.0,3,0,Semi-Urban,Data Analyst,115997,0 +77241,Male,38,Bachelors,3,35,92,40,14,8.0,4,88,Rural,HR Executive,62115,1 +77242,Female,23,Diploma,15,45,61,3,89,9.0,6,54,Semi-Urban,HR Executive,59850,0 +77243,Female,49,Bachelors,15,49,25,38,69,8.0,2,2,Semi-Urban,Software Engineer,39274,0 +77244,Female,59,Masters,5,10,20,81,27,6.0,3,53,Urban,ML Engineer,49332,0 +77245,Male,23,Diploma,11,18,80,7,42,1.0,4,79,Urban,Manager,54678,0 +77246,Female,25,Diploma,13,17,0,3,12,1.0,3,81,Rural,Data Analyst,44405,0 +77247,Male,42,Diploma,3,91,74,46,69,8.0,1,63,Semi-Urban,ML Engineer,126964,1 +77248,Male,39,High School,9,95,36,70,84,9.0,3,1,Urban,Software Engineer,95230,0 +77249,Male,43,Masters,8,52,93,0,55,9.0,2,45,Semi-Urban,Manager,64059,0 +77250,Female,40,Bachelors,16,83,45,39,8,5.0,2,18,Urban,Manager,99766,0 +77251,Female,29,Masters,10,64,68,76,43,0.0,6,13,Urban,HR Executive,79876,0 +77252,Female,57,Bachelors,12,26,30,79,81,3.0,6,60,Urban,ML Engineer,116848,0 +77253,Male,33,Masters,17,25,62,47,27,5.0,4,71,Rural,Data Analyst,38462,0 +77254,Male,36,Bachelors,4,71,95,28,76,9.0,0,36,Semi-Urban,Software Engineer,103083,0 +77255,Female,51,Masters,6,27,54,68,92,3.0,1,3,Urban,ML Engineer,142744,0 +77256,Male,36,Bachelors,1,87,27,78,24,0.0,7,86,Rural,Manager,71164,1 +77257,Male,51,Bachelors,10,68,41,56,98,6.0,7,98,Urban,Data Analyst,87880,1 +77258,Male,35,Masters,4,67,68,61,23,1.0,7,25,Urban,Data Analyst,76721,0 +77259,Male,33,Bachelors,17,34,85,86,33,8.0,6,69,Rural,Manager,65768,1 +77260,Female,40,Diploma,9,42,98,12,77,4.0,1,25,Rural,ML Engineer,132505,0 +77261,Male,54,Masters,5,58,9,81,53,4.0,2,97,Urban,ML Engineer,124041,1 +77262,Male,58,Masters,10,21,35,6,26,9.0,7,53,Rural,Software Engineer,55452,0 +77263,Male,24,Masters,11,6,49,41,38,0.0,5,63,Urban,ML Engineer,145825,0 +77264,Female,46,Masters,19,63,90,72,41,7.0,6,52,Rural,Data Analyst,35575,1 +77265,Male,56,Masters,9,89,59,91,93,8.0,6,40,Urban,Software Engineer,92120,1 +77266,Female,45,PhD,1,83,34,77,34,4.0,2,94,Urban,Software Engineer,146336,1 +77267,Other,55,Bachelors,12,31,33,62,78,1.0,7,20,Urban,Software Engineer,134026,0 +77268,Other,41,Bachelors,4,85,52,29,64,5.0,7,14,Rural,HR Executive,45589,0 +77269,Male,50,Diploma,3,75,75,66,62,9.0,2,0,Urban,Software Engineer,61299,0 +77270,Male,53,Masters,5,57,27,33,65,9.0,2,30,Urban,Manager,66091,0 +77271,Female,41,Masters,8,5,67,40,82,8.0,6,83,Urban,HR Executive,138630,0 +77272,Female,58,Masters,15,71,12,82,42,8.0,0,30,Urban,HR Executive,98047,0 +77273,Female,43,Bachelors,18,49,16,60,20,3.0,7,81,Urban,Software Engineer,58822,0 +77274,Male,37,Diploma,14,40,43,35,7,6.0,7,50,Urban,ML Engineer,112007,0 +77275,Male,58,Diploma,16,24,81,56,4,1.0,3,11,Semi-Urban,Manager,65969,0 +77276,Male,48,Bachelors,2,65,89,9,64,7.0,1,28,Urban,Manager,143777,0 +77277,Male,52,PhD,5,50,18,31,53,2.0,4,84,Rural,Data Analyst,140555,0 +77278,Female,48,Bachelors,9,23,4,69,97,0.0,7,22,Semi-Urban,HR Executive,21525,0 +77279,Male,51,Diploma,10,0,50,30,24,8.0,4,41,Urban,HR Executive,74878,0 +77280,Female,47,Diploma,0,46,92,87,59,6.0,5,14,Urban,ML Engineer,114968,0 +77281,Male,53,Diploma,12,96,57,96,76,7.0,4,9,Urban,Data Analyst,125010,1 +77282,Female,57,Diploma,6,26,24,2,9,3.0,2,18,Rural,ML Engineer,23612,0 +77283,Female,29,High School,12,72,25,39,65,3.0,0,88,Rural,HR Executive,99954,0 +77284,Female,38,Bachelors,12,74,69,32,43,7.0,1,24,Semi-Urban,Manager,96497,0 +77285,Male,42,Masters,4,41,82,90,41,3.0,0,12,Rural,Data Analyst,32882,0 +77286,Male,32,Bachelors,14,61,57,45,7,2.0,2,96,Urban,Manager,44876,1 +77287,Female,35,Masters,15,50,10,29,31,9.0,7,29,Urban,Data Analyst,146133,0 +77288,Female,25,Bachelors,4,15,11,98,90,2.0,2,15,Urban,HR Executive,30250,0 +77289,Male,28,Bachelors,2,51,24,61,48,0.0,7,53,Urban,ML Engineer,96159,0 +77290,Female,28,Bachelors,3,45,70,70,59,9.0,5,28,Urban,ML Engineer,36093,0 +77291,Male,55,Bachelors,11,19,23,48,13,6.0,6,2,Rural,Software Engineer,63383,0 +77292,Female,28,Masters,16,78,71,92,61,6.0,2,54,Urban,Data Analyst,96829,1 +77293,Male,44,Bachelors,11,23,5,51,78,0.0,3,67,Urban,HR Executive,23484,0 +77294,Male,33,Bachelors,8,49,7,16,87,3.0,3,25,Urban,HR Executive,106021,0 +77295,Female,43,Diploma,18,72,25,96,22,8.0,7,7,Semi-Urban,HR Executive,23687,0 +77296,Male,41,Bachelors,5,74,39,76,10,5.0,1,18,Urban,Software Engineer,119990,0 +77297,Female,55,Masters,12,87,32,14,82,5.0,7,60,Urban,HR Executive,145824,0 +77298,Female,55,Bachelors,6,30,25,66,8,3.0,4,36,Semi-Urban,Software Engineer,23970,0 +77299,Female,56,Diploma,4,85,0,45,50,7.0,4,98,Semi-Urban,Data Analyst,97487,0 +77300,Female,31,Bachelors,10,33,66,47,86,1.0,5,59,Urban,HR Executive,33839,0 +77301,Male,50,Bachelors,0,53,61,80,18,8.0,4,32,Urban,Software Engineer,58467,0 +77302,Female,22,Bachelors,0,52,45,13,87,2.0,0,66,Urban,Manager,56429,0 +77303,Female,23,Masters,0,74,23,34,43,0.0,1,90,Urban,ML Engineer,41330,0 +77304,Female,59,Bachelors,9,47,82,50,88,1.0,1,33,Rural,Software Engineer,47146,0 +77305,Male,26,Bachelors,5,65,98,8,79,9.0,4,95,Urban,Manager,100463,1 +77306,Female,25,Bachelors,9,26,3,63,90,9.0,6,54,Semi-Urban,ML Engineer,42865,0 +77307,Male,51,Masters,9,87,90,83,87,4.0,6,74,Urban,ML Engineer,53102,1 +77308,Female,39,Diploma,12,94,50,19,34,7.0,7,0,Urban,Data Analyst,64536,0 +77309,Other,37,Bachelors,2,5,7,28,29,5.0,7,39,Rural,Manager,56466,0 +77310,Male,49,Masters,1,33,38,56,98,4.0,0,52,Urban,ML Engineer,62966,0 +77311,Male,54,Bachelors,11,77,65,77,95,5.0,6,68,Urban,Manager,148081,1 +77312,Male,45,Masters,9,38,49,93,96,4.0,3,22,Urban,Data Analyst,26332,0 +77313,Male,24,Bachelors,7,6,61,40,25,8.0,0,13,Semi-Urban,HR Executive,104218,0 +77314,Male,52,Bachelors,16,79,18,5,51,5.0,4,61,Rural,Data Analyst,39566,0 +77315,Male,52,PhD,9,59,44,89,91,3.0,5,54,Semi-Urban,Software Engineer,65348,1 +77316,Female,49,Diploma,12,30,29,37,59,3.0,7,9,Rural,Manager,139919,0 +77317,Female,41,Bachelors,2,86,21,29,32,7.0,4,36,Urban,HR Executive,147351,0 +77318,Male,54,Diploma,7,25,61,28,70,8.0,2,66,Urban,Data Analyst,53447,0 +77319,Male,31,Bachelors,6,41,20,37,85,2.0,1,67,Semi-Urban,Manager,53263,0 +77320,Female,29,Bachelors,2,45,88,35,21,5.0,5,62,Urban,HR Executive,106194,0 +77321,Male,39,Bachelors,3,88,9,49,17,2.0,0,63,Rural,ML Engineer,32022,0 +77322,Female,23,Bachelors,11,73,59,25,99,7.0,7,79,Urban,Data Analyst,25590,0 +77323,Female,56,Masters,18,71,7,73,41,7.0,4,9,Urban,Manager,36505,0 +77324,Male,39,Bachelors,8,9,52,34,87,6.0,2,7,Semi-Urban,Manager,98409,0 +77325,Female,49,Masters,13,3,68,17,3,7.0,0,62,Rural,ML Engineer,87392,0 +77326,Male,58,Diploma,8,85,60,3,79,8.0,2,42,Semi-Urban,Data Analyst,29065,0 +77327,Male,44,Diploma,14,23,49,65,27,0.0,5,13,Urban,HR Executive,68591,0 +77328,Female,55,Masters,16,52,62,57,59,1.0,0,1,Urban,ML Engineer,47308,0 +77329,Female,58,Masters,15,99,14,26,62,7.0,3,42,Rural,Manager,69510,0 +77330,Female,55,Masters,3,5,80,39,33,9.0,3,35,Semi-Urban,ML Engineer,102597,0 +77331,Female,33,Diploma,9,87,13,28,82,0.0,7,20,Urban,Software Engineer,129168,0 +77332,Other,55,Diploma,8,16,70,40,20,9.0,3,39,Urban,Manager,52381,0 +77333,Female,47,Bachelors,17,10,38,57,97,2.0,6,53,Urban,ML Engineer,132373,0 +77334,Male,31,Diploma,17,4,18,31,57,9.0,3,18,Rural,Software Engineer,62041,0 +77335,Female,45,Bachelors,15,2,74,61,76,0.0,0,46,Rural,Software Engineer,71868,0 +77336,Female,46,Masters,14,67,49,61,6,0.0,7,28,Semi-Urban,ML Engineer,33599,0 +77337,Female,35,Bachelors,15,37,99,55,25,1.0,7,58,Semi-Urban,Data Analyst,88218,1 +77338,Female,34,Diploma,15,4,31,53,17,7.0,5,88,Rural,HR Executive,89891,0 +77339,Female,51,Diploma,11,12,8,18,97,0.0,5,76,Urban,ML Engineer,136421,0 +77340,Male,45,Masters,0,69,32,70,80,7.0,3,63,Rural,ML Engineer,76040,0 +77341,Other,52,Bachelors,5,95,97,8,84,4.0,1,29,Urban,Manager,26027,0 +77342,Male,32,Bachelors,10,56,68,36,93,8.0,3,70,Urban,ML Engineer,146484,0 +77343,Female,29,Bachelors,12,47,16,22,1,8.0,7,74,Urban,Manager,117845,0 +77344,Female,23,Bachelors,10,84,61,43,28,2.0,1,71,Semi-Urban,Data Analyst,86596,1 +77345,Male,32,Bachelors,9,40,33,12,86,8.0,1,72,Urban,ML Engineer,68233,0 +77346,Female,41,Masters,14,92,53,89,38,4.0,2,51,Semi-Urban,Manager,56886,1 +77347,Female,50,Masters,18,82,32,66,9,1.0,5,93,Urban,Data Analyst,56596,1 +77348,Female,54,High School,0,4,68,0,16,4.0,0,66,Urban,Manager,90114,0 +77349,Male,22,Bachelors,13,79,83,93,80,2.0,0,65,Semi-Urban,Software Engineer,116198,1 +77350,Female,27,Diploma,14,32,58,73,57,7.0,3,68,Rural,HR Executive,108301,0 +77351,Male,58,Bachelors,17,68,68,95,13,7.0,1,20,Urban,HR Executive,42654,1 +77352,Male,55,Masters,9,49,20,3,8,7.0,1,33,Urban,Software Engineer,136718,0 +77353,Female,35,Masters,6,37,61,76,36,1.0,2,0,Semi-Urban,Data Analyst,88142,0 +77354,Male,38,Masters,9,88,8,83,32,5.0,1,12,Semi-Urban,Manager,77469,0 +77355,Female,23,Bachelors,3,96,4,75,69,0.0,4,14,Urban,Software Engineer,116360,0 +77356,Female,57,Bachelors,6,10,75,5,17,7.0,5,6,Urban,ML Engineer,144548,0 +77357,Male,21,PhD,0,54,54,36,84,5.0,1,29,Rural,ML Engineer,97356,0 +77358,Male,51,Bachelors,7,1,69,28,60,7.0,3,95,Urban,Software Engineer,89837,0 +77359,Male,22,Bachelors,0,77,0,32,3,3.0,4,87,Urban,ML Engineer,133640,0 +77360,Male,28,Bachelors,11,53,38,95,34,0.0,0,72,Rural,Software Engineer,55130,1 +77361,Female,30,Bachelors,7,82,38,0,28,4.0,1,43,Rural,Manager,95835,0 +77362,Female,40,Diploma,3,38,14,57,40,8.0,6,70,Urban,Data Analyst,62046,0 +77363,Male,34,Diploma,8,81,88,59,51,2.0,1,53,Semi-Urban,ML Engineer,56063,1 +77364,Female,49,High School,15,97,23,32,44,1.0,7,98,Urban,Data Analyst,91460,1 +77365,Male,38,Masters,1,96,69,22,42,4.0,6,18,Semi-Urban,Manager,120190,0 +77366,Male,33,High School,13,29,0,71,50,0.0,2,84,Semi-Urban,Data Analyst,126058,0 +77367,Male,58,Diploma,10,58,67,23,7,5.0,4,4,Semi-Urban,ML Engineer,75482,0 +77368,Female,59,Bachelors,17,33,93,34,24,1.0,6,46,Urban,Manager,72528,0 +77369,Male,49,High School,4,88,34,82,10,6.0,2,93,Urban,Software Engineer,144762,1 +77370,Male,32,Masters,7,9,92,49,43,7.0,2,37,Semi-Urban,HR Executive,90633,0 +77371,Male,39,Diploma,7,66,11,40,56,2.0,6,78,Rural,ML Engineer,116863,0 +77372,Male,36,Bachelors,4,20,5,71,28,4.0,4,31,Semi-Urban,Data Analyst,48907,0 +77373,Other,21,Diploma,2,88,41,58,22,7.0,3,47,Urban,Manager,61400,0 +77374,Male,27,Diploma,13,85,57,76,1,7.0,0,3,Rural,Data Analyst,98540,0 +77375,Female,51,High School,19,28,70,79,42,8.0,4,46,Semi-Urban,Manager,37894,0 +77376,Male,52,Bachelors,18,44,55,63,7,1.0,2,63,Semi-Urban,HR Executive,99217,0 +77377,Male,36,High School,1,52,24,15,50,2.0,0,77,Urban,Data Analyst,48387,0 +77378,Female,38,Masters,12,53,68,72,24,8.0,6,61,Rural,Manager,65340,1 +77379,Male,59,Bachelors,7,68,8,4,37,1.0,6,6,Urban,ML Engineer,134817,0 +77380,Female,33,Masters,16,77,62,33,46,8.0,5,36,Rural,Data Analyst,143340,0 +77381,Female,32,Masters,2,51,28,5,12,2.0,7,51,Semi-Urban,Software Engineer,143142,0 +77382,Female,24,High School,12,78,27,46,63,2.0,7,48,Urban,HR Executive,129601,0 +77383,Female,57,Bachelors,17,97,94,48,27,9.0,6,5,Urban,Software Engineer,73823,1 +77384,Female,37,Masters,15,23,22,91,52,0.0,5,69,Urban,Manager,142048,0 +77385,Female,45,High School,11,82,66,31,9,3.0,1,54,Rural,Data Analyst,117968,0 +77386,Male,53,Masters,14,13,16,53,90,9.0,6,9,Urban,Data Analyst,146132,0 +77387,Male,31,Diploma,1,68,26,47,15,3.0,3,14,Urban,Software Engineer,101705,0 +77388,Female,58,Bachelors,13,62,53,37,44,9.0,2,70,Urban,Data Analyst,96824,0 +77389,Male,51,Bachelors,5,45,31,0,70,2.0,7,6,Urban,Data Analyst,82464,0 +77390,Male,27,Bachelors,13,74,27,17,75,3.0,2,71,Rural,Software Engineer,71998,0 +77391,Male,45,Masters,18,42,68,69,0,3.0,7,34,Urban,ML Engineer,91341,0 +77392,Female,45,Bachelors,3,97,41,4,69,2.0,7,91,Urban,ML Engineer,49578,0 +77393,Male,27,Masters,15,30,44,50,3,5.0,7,91,Urban,Software Engineer,88877,0 +77394,Male,29,Bachelors,19,72,38,32,77,7.0,3,50,Semi-Urban,ML Engineer,43889,0 +77395,Female,55,PhD,6,55,33,76,70,9.0,5,31,Semi-Urban,ML Engineer,45545,0 +77396,Female,59,Masters,1,60,38,19,38,6.0,4,11,Semi-Urban,HR Executive,106069,0 +77397,Male,30,Bachelors,17,15,79,13,16,4.0,4,69,Semi-Urban,ML Engineer,26232,0 +77398,Female,22,High School,16,6,41,67,57,4.0,1,24,Urban,Manager,60822,0 +77399,Male,48,Diploma,13,44,65,81,59,3.0,7,60,Urban,HR Executive,95987,1 +77400,Other,51,High School,19,21,22,40,99,0.0,5,94,Urban,Manager,34271,0 +77401,Male,32,Bachelors,16,94,20,62,73,8.0,4,48,Rural,ML Engineer,75107,0 +77402,Male,38,Diploma,3,10,77,38,35,6.0,6,2,Semi-Urban,Manager,80059,0 +77403,Female,58,Masters,17,82,96,50,74,0.0,0,74,Urban,Software Engineer,144968,1 +77404,Male,23,Bachelors,5,69,83,70,61,0.0,1,7,Urban,ML Engineer,124952,0 +77405,Male,48,Diploma,3,17,0,37,78,2.0,4,0,Urban,Software Engineer,46519,0 +77406,Male,48,Bachelors,15,47,21,39,26,0.0,7,90,Urban,ML Engineer,146841,0 +77407,Male,39,PhD,10,15,45,22,58,5.0,4,51,Semi-Urban,HR Executive,149934,0 +77408,Female,52,High School,11,59,71,21,95,0.0,2,34,Semi-Urban,HR Executive,136534,0 +77409,Female,24,Diploma,4,96,9,20,46,9.0,0,34,Urban,Manager,142197,0 +77410,Male,42,Bachelors,14,20,93,8,17,9.0,7,42,Urban,ML Engineer,116727,0 +77411,Other,47,Bachelors,18,26,79,10,49,5.0,2,38,Urban,Manager,144813,0 +77412,Female,53,Bachelors,14,97,88,68,71,3.0,7,10,Urban,ML Engineer,101584,1 +77413,Female,41,Diploma,9,68,53,1,34,4.0,4,43,Semi-Urban,Manager,100318,0 +77414,Male,23,Bachelors,8,95,74,54,80,1.0,7,43,Urban,Manager,86973,1 +77415,Male,47,Masters,1,52,69,26,51,1.0,3,50,Urban,HR Executive,105261,0 +77416,Male,52,High School,2,57,75,67,94,6.0,3,34,Urban,HR Executive,58191,0 +77417,Male,24,Masters,6,74,37,72,28,8.0,6,65,Urban,ML Engineer,51373,1 +77418,Female,54,PhD,3,96,46,72,33,7.0,1,19,Semi-Urban,Manager,147180,0 +77419,Male,25,Masters,6,15,9,78,76,0.0,0,78,Urban,ML Engineer,119437,0 +77420,Male,27,Bachelors,0,64,23,88,68,6.0,4,53,Urban,Data Analyst,95112,0 +77421,Male,45,Diploma,19,21,78,99,50,7.0,5,31,Semi-Urban,Manager,113171,0 +77422,Male,50,Bachelors,11,34,0,13,84,1.0,5,48,Rural,Manager,120309,0 +77423,Female,53,Masters,12,26,85,77,90,0.0,6,11,Urban,Data Analyst,128611,0 +77424,Female,57,Bachelors,17,76,78,73,88,5.0,0,64,Rural,Manager,39699,1 +77425,Male,31,Masters,9,56,62,52,81,8.0,6,37,Urban,HR Executive,58542,0 +77426,Male,28,Bachelors,6,63,40,94,60,5.0,5,1,Urban,Manager,51344,0 +77427,Female,32,High School,12,67,3,89,36,8.0,0,82,Rural,Data Analyst,27252,1 +77428,Female,36,PhD,16,72,95,81,0,6.0,2,65,Urban,ML Engineer,149798,1 +77429,Male,21,Bachelors,7,15,2,3,20,9.0,0,4,Semi-Urban,Manager,21856,0 +77430,Male,57,Masters,17,10,44,55,12,6.0,6,41,Semi-Urban,Manager,67119,0 +77431,Female,56,Diploma,10,69,54,72,38,3.0,1,49,Semi-Urban,Data Analyst,112134,1 +77432,Female,51,High School,12,85,88,24,51,5.0,0,13,Rural,Software Engineer,143692,0 +77433,Male,45,Bachelors,15,94,84,95,8,7.0,0,27,Semi-Urban,Manager,85592,1 +77434,Male,23,Diploma,16,71,89,2,70,8.0,4,73,Urban,Software Engineer,118324,1 +77435,Female,57,Masters,12,22,32,94,24,2.0,3,30,Semi-Urban,Manager,25956,0 +77436,Female,52,Masters,9,23,18,23,81,3.0,1,23,Urban,Manager,44087,0 +77437,Male,49,Masters,5,40,79,46,62,0.0,2,10,Rural,HR Executive,117823,0 +77438,Other,38,Masters,0,69,11,8,95,4.0,4,86,Semi-Urban,ML Engineer,35454,0 +77439,Male,56,Diploma,9,41,66,18,60,5.0,3,40,Rural,Data Analyst,125010,0 +77440,Male,45,High School,19,29,0,33,27,5.0,6,14,Urban,Data Analyst,75216,0 +77441,Male,32,Diploma,13,65,13,36,95,4.0,4,30,Urban,ML Engineer,63987,0 +77442,Female,46,Masters,19,99,11,20,40,8.0,6,36,Urban,Software Engineer,107443,0 +77443,Other,27,Bachelors,5,82,33,60,2,0.0,4,23,Semi-Urban,HR Executive,36337,0 +77444,Male,53,Masters,13,28,75,51,36,6.0,0,84,Rural,Software Engineer,128628,1 +77445,Male,42,Masters,12,60,18,49,15,3.0,1,19,Urban,Software Engineer,111034,0 +77446,Female,46,Masters,11,93,90,13,90,4.0,4,77,Urban,Data Analyst,86825,1 +77447,Male,24,Masters,3,48,61,28,17,4.0,7,49,Semi-Urban,HR Executive,144376,0 +77448,Male,41,Masters,4,75,75,36,39,8.0,7,93,Urban,ML Engineer,26912,1 +77449,Female,52,Masters,6,92,32,84,98,7.0,2,99,Urban,ML Engineer,28633,1 +77450,Female,56,Bachelors,15,34,58,37,39,7.0,3,24,Rural,Software Engineer,76276,0 +77451,Male,30,Bachelors,4,52,41,24,97,0.0,7,44,Rural,Manager,91434,0 +77452,Male,36,Diploma,15,9,71,25,5,3.0,5,64,Urban,Data Analyst,74377,0 +77453,Male,23,Diploma,16,6,56,52,28,7.0,0,72,Rural,Manager,34936,0 +77454,Male,29,Masters,13,6,33,3,82,1.0,7,69,Urban,Data Analyst,52848,0 +77455,Male,28,Bachelors,3,83,29,60,35,1.0,1,4,Urban,Manager,104858,0 +77456,Male,40,High School,5,87,40,67,45,6.0,0,79,Urban,Data Analyst,50469,1 +77457,Male,35,Masters,17,39,5,21,55,9.0,7,0,Urban,HR Executive,45195,0 +77458,Male,36,Diploma,7,64,3,31,87,9.0,2,68,Urban,Data Analyst,52763,0 +77459,Female,57,High School,7,85,20,88,80,7.0,6,9,Urban,Software Engineer,49008,0 +77460,Female,49,Diploma,1,90,49,85,19,5.0,2,27,Urban,HR Executive,94555,1 +77461,Female,46,Masters,9,13,29,33,23,4.0,6,39,Semi-Urban,Manager,142920,0 +77462,Male,57,Diploma,14,12,18,76,2,9.0,3,49,Urban,ML Engineer,73591,0 +77463,Male,56,Diploma,8,50,96,39,65,4.0,1,47,Semi-Urban,Manager,146986,0 +77464,Other,38,PhD,19,9,28,60,0,2.0,6,99,Urban,Manager,43941,0 +77465,Male,43,Diploma,8,50,60,60,8,3.0,3,28,Urban,Manager,79469,0 +77466,Female,25,High School,14,41,59,16,94,2.0,3,37,Urban,HR Executive,79442,0 +77467,Male,58,PhD,1,64,68,10,55,4.0,0,99,Semi-Urban,ML Engineer,129791,1 +77468,Female,50,Masters,9,74,16,12,17,3.0,7,82,Semi-Urban,HR Executive,144095,0 +77469,Female,29,Diploma,16,29,8,3,19,1.0,0,35,Urban,Software Engineer,38322,0 +77470,Female,42,Masters,9,71,63,94,47,2.0,7,18,Urban,Data Analyst,145343,1 +77471,Other,47,Bachelors,2,0,4,29,57,7.0,7,33,Urban,Software Engineer,22776,0 +77472,Female,50,Bachelors,11,38,21,28,38,2.0,3,83,Urban,Software Engineer,110614,0 +77473,Male,53,Diploma,2,32,86,65,54,0.0,0,89,Urban,Software Engineer,66448,1 +77474,Male,29,Diploma,12,20,20,43,80,2.0,0,75,Urban,ML Engineer,136163,0 +77475,Male,27,Bachelors,0,15,17,48,34,1.0,6,73,Rural,Data Analyst,78695,0 +77476,Male,49,Diploma,3,20,99,22,98,4.0,2,56,Rural,Software Engineer,147167,0 +77477,Male,46,Bachelors,1,52,55,20,68,4.0,1,43,Urban,Data Analyst,69152,0 +77478,Other,41,PhD,16,35,69,84,81,5.0,3,13,Urban,Software Engineer,133754,0 +77479,Male,32,Bachelors,15,64,52,73,79,5.0,2,51,Semi-Urban,Software Engineer,98134,1 +77480,Other,54,Diploma,10,52,94,2,2,6.0,5,16,Semi-Urban,Manager,37558,0 +77481,Male,57,Bachelors,18,34,19,12,6,0.0,3,9,Urban,Manager,131892,0 +77482,Male,41,High School,10,61,55,43,72,8.0,4,18,Rural,HR Executive,105099,0 +77483,Male,21,Bachelors,17,2,0,61,97,1.0,2,81,Urban,Manager,127939,0 +77484,Female,45,Masters,6,3,17,11,97,2.0,5,30,Urban,Manager,118012,0 +77485,Male,36,Bachelors,12,12,37,1,69,4.0,0,92,Rural,Software Engineer,128486,0 +77486,Male,38,Bachelors,0,20,43,57,26,1.0,0,98,Urban,Manager,59611,0 +77487,Female,29,PhD,5,13,29,78,86,5.0,2,87,Rural,Data Analyst,60710,0 +77488,Female,25,PhD,0,18,63,62,87,4.0,0,42,Urban,Data Analyst,43034,0 +77489,Male,42,Masters,1,23,50,28,74,4.0,4,40,Urban,ML Engineer,82527,0 +77490,Male,57,Bachelors,2,32,95,19,65,3.0,7,33,Semi-Urban,ML Engineer,148129,0 +77491,Male,32,High School,8,86,78,73,8,6.0,6,0,Urban,Data Analyst,142750,1 +77492,Female,52,Bachelors,10,96,58,53,98,2.0,0,86,Urban,ML Engineer,75641,1 +77493,Other,22,Bachelors,4,67,49,69,92,7.0,7,51,Urban,HR Executive,34760,0 +77494,Male,25,Diploma,7,5,11,86,80,2.0,4,18,Urban,Data Analyst,78658,0 +77495,Male,46,Diploma,8,65,85,53,48,9.0,1,74,Urban,Data Analyst,149169,1 +77496,Other,36,High School,2,65,73,57,24,8.0,0,69,Urban,Data Analyst,142012,1 +77497,Male,50,Masters,1,49,80,35,54,0.0,0,18,Urban,ML Engineer,27782,0 +77498,Female,44,High School,9,37,1,91,79,8.0,7,25,Semi-Urban,Data Analyst,120724,0 +77499,Male,36,Bachelors,12,96,87,68,18,8.0,1,39,Urban,Software Engineer,88772,1 +77500,Other,43,Diploma,5,47,80,88,74,7.0,7,86,Urban,Software Engineer,22419,1 +77501,Male,40,Bachelors,6,5,1,24,94,1.0,0,81,Rural,HR Executive,111840,0 +77502,Male,30,Diploma,10,30,76,7,95,4.0,1,35,Urban,Manager,144623,0 +77503,Male,46,Bachelors,16,2,10,70,32,1.0,2,71,Urban,Data Analyst,30408,0 +77504,Male,51,Bachelors,3,45,74,59,15,7.0,2,74,Semi-Urban,HR Executive,66300,1 +77505,Other,44,Masters,18,96,48,16,28,1.0,0,40,Semi-Urban,ML Engineer,36676,0 +77506,Male,49,Bachelors,11,65,24,37,13,4.0,2,34,Rural,Manager,29517,0 +77507,Female,45,High School,12,64,67,83,14,1.0,1,52,Semi-Urban,Manager,107459,1 +77508,Female,45,High School,14,29,90,79,96,9.0,5,52,Semi-Urban,Manager,76297,1 +77509,Male,40,Masters,3,56,6,84,7,4.0,0,24,Semi-Urban,Software Engineer,51418,0 +77510,Male,55,Diploma,6,71,44,12,29,1.0,3,13,Semi-Urban,Data Analyst,100107,0 +77511,Female,30,Masters,3,21,90,82,66,0.0,0,24,Urban,HR Executive,60544,0 +77512,Female,54,Bachelors,16,89,66,11,49,2.0,2,39,Urban,ML Engineer,126305,0 +77513,Female,52,Bachelors,18,33,45,81,94,0.0,2,21,Urban,HR Executive,121818,0 +77514,Male,36,Masters,15,33,62,31,45,3.0,5,93,Urban,Software Engineer,88035,0 +77515,Female,44,Masters,5,47,9,83,95,6.0,3,63,Rural,Software Engineer,96950,0 +77516,Male,22,Diploma,5,40,69,31,10,7.0,2,40,Semi-Urban,Software Engineer,80007,0 +77517,Female,30,High School,8,20,91,82,29,7.0,2,43,Semi-Urban,ML Engineer,88279,0 +77518,Male,57,Masters,2,79,64,55,24,0.0,4,53,Semi-Urban,Data Analyst,46196,1 +77519,Female,22,High School,5,94,65,43,39,0.0,4,58,Semi-Urban,Manager,72146,1 +77520,Male,53,Bachelors,16,15,65,6,93,7.0,0,77,Rural,Data Analyst,67123,0 +77521,Male,48,Masters,6,26,19,36,92,8.0,3,43,Urban,Manager,43872,0 +77522,Male,33,Bachelors,1,75,66,75,7,4.0,5,18,Urban,Data Analyst,26470,0 +77523,Female,50,Masters,5,0,12,53,25,6.0,6,77,Semi-Urban,Manager,32437,0 +77524,Male,45,Masters,0,35,77,87,84,9.0,5,13,Urban,Data Analyst,87193,0 +77525,Male,36,Bachelors,14,73,83,6,16,1.0,5,80,Urban,Software Engineer,26664,1 +77526,Female,29,Diploma,16,22,46,73,34,2.0,7,87,Rural,Data Analyst,34397,0 +77527,Male,58,Bachelors,4,67,46,20,4,6.0,3,31,Urban,Data Analyst,148428,0 +77528,Male,54,Bachelors,1,50,12,14,0,1.0,6,62,Urban,Software Engineer,41691,0 +77529,Male,52,PhD,16,98,42,71,93,3.0,1,24,Urban,Manager,93131,1 +77530,Male,28,Masters,16,51,76,62,71,0.0,2,19,Urban,Data Analyst,95281,0 +77531,Male,59,Diploma,1,90,14,54,29,4.0,3,29,Rural,Software Engineer,110399,0 +77532,Male,41,Bachelors,6,10,31,44,7,9.0,6,48,Urban,Data Analyst,62219,0 +77533,Female,57,Masters,8,58,69,40,87,5.0,0,70,Urban,HR Executive,127295,0 +77534,Male,28,PhD,12,31,59,48,3,7.0,3,9,Semi-Urban,Software Engineer,76293,0 +77535,Male,26,Bachelors,8,57,92,5,61,5.0,0,76,Semi-Urban,Manager,27117,0 +77536,Female,42,High School,15,86,79,28,79,4.0,0,31,Rural,ML Engineer,144998,0 +77537,Female,57,Masters,9,60,89,16,62,8.0,4,45,Urban,HR Executive,22511,0 +77538,Male,26,High School,10,79,68,66,71,7.0,5,23,Rural,Software Engineer,61291,1 +77539,Female,33,Bachelors,10,47,57,96,22,8.0,7,82,Semi-Urban,Data Analyst,82610,1 +77540,Male,22,Masters,8,97,96,13,92,2.0,7,11,Urban,Manager,43753,0 +77541,Male,28,Bachelors,18,21,64,87,63,9.0,3,93,Urban,Manager,99576,1 +77542,Female,45,High School,14,61,79,43,53,6.0,6,49,Urban,Software Engineer,101286,0 +77543,Male,28,High School,3,35,93,86,17,0.0,6,68,Urban,ML Engineer,31702,1 +77544,Female,54,Masters,7,73,3,16,38,8.0,2,48,Urban,HR Executive,62962,0 +77545,Female,32,Bachelors,18,48,15,78,64,1.0,4,77,Urban,ML Engineer,25471,0 +77546,Male,53,Masters,10,14,25,44,69,9.0,1,86,Semi-Urban,Manager,72335,0 +77547,Male,41,Masters,14,37,57,31,7,9.0,5,86,Urban,Manager,141798,0 +77548,Female,31,Bachelors,4,7,44,2,55,7.0,1,73,Rural,ML Engineer,114912,0 +77549,Male,28,Bachelors,4,50,60,51,48,0.0,5,24,Urban,ML Engineer,50167,0 +77550,Male,26,PhD,11,29,87,73,79,7.0,3,69,Rural,Software Engineer,106601,1 +77551,Male,30,Bachelors,16,98,16,55,94,8.0,3,25,Semi-Urban,Software Engineer,35923,0 +77552,Male,57,Bachelors,1,64,41,93,76,5.0,0,82,Rural,Manager,91130,1 +77553,Female,35,PhD,1,96,78,71,45,2.0,0,47,Rural,ML Engineer,127649,1 +77554,Male,42,Bachelors,8,5,87,40,84,6.0,3,76,Semi-Urban,Software Engineer,25439,0 +77555,Male,50,Masters,4,89,18,47,67,3.0,5,38,Rural,Manager,66700,0 +77556,Male,42,Masters,17,31,17,39,42,7.0,2,18,Urban,HR Executive,87360,0 +77557,Female,47,Bachelors,10,1,62,85,25,2.0,2,20,Urban,HR Executive,108673,0 +77558,Female,55,High School,0,87,66,18,96,6.0,3,44,Semi-Urban,Software Engineer,24848,0 +77559,Male,53,High School,17,20,8,97,31,8.0,3,62,Urban,Manager,144199,0 +77560,Male,47,Bachelors,2,73,10,53,51,3.0,4,6,Urban,ML Engineer,61541,0 +77561,Male,51,High School,12,57,98,2,36,0.0,1,22,Urban,HR Executive,51245,0 +77562,Male,39,Diploma,9,67,48,56,54,6.0,2,16,Urban,Manager,57373,0 +77563,Other,51,High School,10,56,13,40,90,1.0,3,76,Urban,Manager,121136,0 +77564,Other,40,Bachelors,16,10,68,58,54,5.0,3,76,Urban,Data Analyst,31612,0 +77565,Male,46,High School,9,19,76,6,74,9.0,6,45,Semi-Urban,Manager,130121,0 +77566,Male,56,High School,4,21,29,66,69,7.0,3,51,Urban,Data Analyst,59431,0 +77567,Male,30,Bachelors,5,84,82,95,23,9.0,6,50,Urban,Manager,104484,1 +77568,Female,23,Bachelors,11,43,19,48,78,5.0,0,88,Rural,ML Engineer,44969,0 +77569,Male,45,Masters,9,33,75,49,58,7.0,7,75,Urban,ML Engineer,89278,0 +77570,Female,38,Bachelors,8,50,8,10,91,2.0,3,37,Urban,HR Executive,39710,0 +77571,Male,42,Diploma,2,14,92,86,69,3.0,2,50,Urban,Manager,128387,1 +77572,Female,59,Bachelors,0,11,21,62,55,3.0,4,41,Semi-Urban,ML Engineer,51636,0 +77573,Female,43,Bachelors,12,29,38,25,14,3.0,2,45,Rural,ML Engineer,114819,0 +77574,Female,58,Bachelors,9,30,4,44,53,2.0,2,23,Semi-Urban,ML Engineer,39020,0 +77575,Female,55,Diploma,0,14,27,10,28,6.0,1,35,Urban,Software Engineer,48868,0 +77576,Male,28,Masters,9,75,60,48,89,4.0,3,89,Urban,ML Engineer,131683,1 +77577,Female,36,High School,19,86,80,47,89,7.0,4,56,Semi-Urban,ML Engineer,36309,1 +77578,Male,45,Bachelors,17,46,31,79,4,6.0,1,31,Semi-Urban,HR Executive,45847,0 +77579,Female,38,Bachelors,0,98,6,48,45,7.0,1,0,Urban,Data Analyst,122492,0 +77580,Other,46,Masters,12,58,59,9,66,0.0,2,41,Urban,Manager,83864,0 +77581,Female,50,Bachelors,3,3,92,14,29,1.0,7,32,Semi-Urban,Data Analyst,117604,0 +77582,Male,28,Masters,4,44,38,70,59,5.0,5,45,Urban,ML Engineer,92620,0 +77583,Other,26,High School,19,4,60,80,44,0.0,4,55,Urban,Data Analyst,80048,0 +77584,Female,32,Bachelors,1,69,37,19,18,0.0,7,54,Semi-Urban,Software Engineer,32651,0 +77585,Male,27,Masters,12,31,4,61,2,2.0,3,85,Urban,Data Analyst,136732,0 +77586,Female,37,High School,11,20,58,81,88,0.0,1,98,Semi-Urban,Data Analyst,77052,1 +77587,Female,59,Masters,3,85,6,23,80,0.0,1,43,Urban,Data Analyst,89474,0 +77588,Male,49,Bachelors,1,42,43,13,72,1.0,5,5,Semi-Urban,Data Analyst,22293,0 +77589,Female,28,Masters,3,17,45,43,3,0.0,2,44,Urban,Software Engineer,46223,0 +77590,Female,43,Masters,13,74,0,12,7,6.0,5,56,Urban,HR Executive,87775,0 +77591,Male,54,Masters,3,28,71,34,14,8.0,5,91,Urban,Manager,63935,0 +77592,Male,57,Bachelors,1,62,23,24,25,9.0,4,34,Urban,Manager,27377,0 +77593,Male,22,Masters,7,88,52,33,39,8.0,3,7,Urban,Software Engineer,149417,0 +77594,Female,43,Bachelors,5,37,6,40,68,0.0,1,45,Urban,Data Analyst,25788,0 +77595,Male,57,Masters,1,28,83,73,7,0.0,5,89,Urban,Software Engineer,109891,1 +77596,Male,35,Diploma,0,89,53,2,18,0.0,7,96,Rural,Data Analyst,117201,1 +77597,Male,53,High School,5,27,92,53,97,6.0,4,60,Semi-Urban,Data Analyst,45841,0 +77598,Female,56,Masters,19,57,89,69,13,5.0,2,40,Urban,Software Engineer,100967,1 +77599,Male,50,Bachelors,10,77,9,49,54,3.0,4,27,Urban,Data Analyst,75762,0 +77600,Female,28,High School,16,52,42,45,46,1.0,7,75,Semi-Urban,Software Engineer,83441,0 +77601,Male,52,Masters,19,28,48,54,82,0.0,6,69,Urban,Manager,117857,0 +77602,Female,21,High School,18,88,79,42,45,8.0,6,29,Rural,Software Engineer,139478,0 +77603,Male,51,Diploma,8,44,7,22,63,0.0,2,60,Urban,Data Analyst,44040,0 +77604,Male,21,Bachelors,1,10,36,15,93,1.0,6,29,Rural,ML Engineer,90963,0 +77605,Male,27,Diploma,10,85,54,6,71,5.0,1,94,Semi-Urban,HR Executive,99785,1 +77606,Male,46,High School,7,33,0,73,17,9.0,0,89,Urban,Manager,73099,0 +77607,Male,39,High School,14,10,32,92,72,3.0,7,1,Rural,HR Executive,52523,0 +77608,Male,23,Bachelors,13,85,92,43,85,1.0,3,57,Urban,Manager,59879,1 +77609,Male,27,Masters,14,60,59,4,22,8.0,7,26,Semi-Urban,HR Executive,30122,0 +77610,Male,34,Bachelors,6,44,0,37,65,7.0,0,14,Rural,Manager,42845,0 +77611,Male,54,Diploma,13,28,17,33,91,2.0,0,56,Rural,HR Executive,36405,0 +77612,Female,43,High School,3,9,84,2,53,4.0,3,88,Urban,HR Executive,37358,0 +77613,Male,54,Masters,19,83,19,45,17,7.0,1,38,Urban,HR Executive,42872,0 +77614,Other,30,Masters,15,68,33,18,86,9.0,2,15,Urban,Manager,39492,0 +77615,Male,44,Bachelors,0,46,5,25,35,9.0,2,4,Urban,ML Engineer,41577,0 +77616,Male,37,Bachelors,0,26,95,35,92,9.0,5,33,Rural,Software Engineer,42391,0 +77617,Male,57,Masters,18,11,1,59,44,9.0,6,26,Rural,Data Analyst,86075,0 +77618,Male,38,High School,10,46,5,28,2,1.0,4,82,Rural,HR Executive,34956,0 +77619,Female,36,Bachelors,10,46,23,43,92,3.0,7,57,Urban,Software Engineer,64582,0 +77620,Male,51,Bachelors,14,40,76,18,54,4.0,2,5,Urban,Software Engineer,104475,0 +77621,Male,48,Bachelors,3,12,4,77,81,6.0,2,54,Semi-Urban,Data Analyst,115075,0 +77622,Male,43,Bachelors,6,85,20,84,40,8.0,1,31,Semi-Urban,Manager,62128,0 +77623,Other,44,Diploma,8,90,90,80,66,7.0,7,85,Urban,HR Executive,53227,1 +77624,Female,27,Bachelors,7,56,66,59,14,7.0,1,72,Semi-Urban,ML Engineer,58668,1 +77625,Male,29,Bachelors,1,14,85,82,78,9.0,1,1,Rural,Manager,88749,0 +77626,Male,40,Diploma,18,12,86,16,6,4.0,1,31,Semi-Urban,ML Engineer,48956,0 +77627,Male,23,High School,12,86,86,59,96,4.0,4,69,Urban,HR Executive,48565,1 +77628,Male,27,High School,0,36,59,41,32,1.0,2,52,Semi-Urban,ML Engineer,105315,0 +77629,Male,29,Diploma,0,29,16,66,54,4.0,6,76,Semi-Urban,ML Engineer,64568,0 +77630,Male,50,Masters,16,95,38,47,22,1.0,7,81,Semi-Urban,HR Executive,22562,1 +77631,Male,47,Bachelors,10,84,33,61,42,5.0,7,46,Urban,Data Analyst,86843,0 +77632,Male,59,Bachelors,8,84,98,58,21,0.0,0,37,Rural,Data Analyst,34339,1 +77633,Male,57,Masters,4,86,41,34,77,8.0,1,59,Semi-Urban,Manager,117735,0 +77634,Male,37,Masters,6,88,76,42,56,7.0,7,66,Urban,Data Analyst,108171,1 +77635,Female,53,Bachelors,3,86,35,23,34,9.0,4,99,Rural,HR Executive,51682,1 +77636,Female,34,Diploma,4,44,26,61,73,4.0,1,93,Urban,ML Engineer,52926,0 +77637,Male,26,Bachelors,5,67,89,23,95,2.0,6,73,Urban,Data Analyst,142228,1 +77638,Male,30,Masters,10,55,7,93,51,2.0,4,57,Semi-Urban,Manager,116286,0 +77639,Male,52,Bachelors,13,18,89,14,40,0.0,2,29,Urban,Data Analyst,60363,0 +77640,Male,46,Bachelors,19,3,42,88,44,2.0,2,67,Semi-Urban,HR Executive,102642,0 +77641,Male,40,Bachelors,19,31,39,35,51,7.0,2,84,Semi-Urban,HR Executive,81454,0 +77642,Female,33,Masters,12,95,6,23,61,9.0,6,43,Urban,Data Analyst,100494,0 +77643,Female,49,Masters,17,66,94,21,12,9.0,5,11,Urban,Manager,59349,0 +77644,Male,54,Diploma,7,47,39,57,53,2.0,2,35,Rural,Data Analyst,116259,0 +77645,Female,56,Bachelors,13,36,33,90,92,6.0,2,63,Rural,HR Executive,139239,0 +77646,Male,23,High School,5,29,57,52,39,9.0,7,28,Rural,ML Engineer,65786,0 +77647,Male,56,Masters,19,66,62,50,21,1.0,6,73,Urban,HR Executive,43054,1 +77648,Female,47,High School,11,12,24,35,25,9.0,7,34,Rural,Data Analyst,147404,0 +77649,Female,55,Masters,8,12,60,75,10,3.0,2,5,Urban,Data Analyst,110371,0 +77650,Male,53,PhD,6,65,21,21,51,6.0,1,55,Urban,Manager,93526,0 +77651,Female,42,Diploma,19,98,93,44,85,3.0,4,2,Urban,ML Engineer,88002,0 +77652,Male,27,Diploma,11,9,75,40,92,1.0,6,10,Urban,Manager,59242,0 +77653,Male,35,Diploma,16,12,2,81,83,2.0,7,30,Semi-Urban,HR Executive,103514,0 +77654,Female,44,Bachelors,2,90,51,52,73,2.0,5,69,Rural,ML Engineer,96568,1 +77655,Female,30,High School,19,40,55,60,44,1.0,4,32,Rural,HR Executive,123734,0 +77656,Male,37,Bachelors,19,92,94,17,47,6.0,0,91,Urban,HR Executive,121510,1 +77657,Male,46,Diploma,14,73,5,25,62,9.0,7,91,Urban,ML Engineer,28278,0 +77658,Male,29,Masters,6,24,23,0,79,4.0,7,23,Urban,Manager,105366,0 +77659,Male,40,Masters,7,7,77,47,63,6.0,5,88,Urban,Data Analyst,96752,0 +77660,Male,53,Bachelors,7,62,96,18,21,1.0,5,58,Semi-Urban,ML Engineer,119009,0 +77661,Female,52,Bachelors,19,67,61,18,89,7.0,2,30,Urban,ML Engineer,31674,0 +77662,Female,56,Bachelors,13,4,9,9,87,2.0,0,6,Rural,Software Engineer,98349,0 +77663,Female,25,Diploma,18,79,10,28,6,2.0,3,22,Urban,Data Analyst,71520,0 +77664,Male,53,Bachelors,13,48,82,74,27,0.0,1,91,Urban,Manager,142774,1 +77665,Female,25,Bachelors,8,34,79,18,67,1.0,5,11,Urban,HR Executive,149952,0 +77666,Other,47,Masters,16,20,6,85,30,2.0,6,36,Urban,Data Analyst,20585,0 +77667,Female,33,Bachelors,9,31,7,15,42,1.0,6,72,Urban,Manager,98534,0 +77668,Male,45,Masters,5,87,26,51,81,5.0,1,82,Semi-Urban,ML Engineer,141391,1 +77669,Male,27,Diploma,3,39,26,99,74,6.0,0,91,Rural,Manager,49622,1 +77670,Female,57,Bachelors,0,4,10,54,45,5.0,6,91,Rural,Data Analyst,87195,0 +77671,Male,30,High School,0,80,27,20,90,3.0,4,75,Semi-Urban,Software Engineer,73267,0 +77672,Male,29,High School,9,29,16,96,53,6.0,2,19,Urban,HR Executive,88835,0 +77673,Female,41,Bachelors,8,78,40,59,34,8.0,4,71,Semi-Urban,Software Engineer,46203,1 +77674,Male,58,Bachelors,10,48,80,62,15,2.0,2,35,Urban,HR Executive,89247,0 +77675,Female,58,Bachelors,13,74,23,77,36,0.0,0,85,Urban,ML Engineer,67830,1 +77676,Male,34,Bachelors,16,2,8,69,77,5.0,2,24,Rural,HR Executive,111136,0 +77677,Male,54,Diploma,17,93,23,92,78,9.0,7,23,Semi-Urban,ML Engineer,112832,0 +77678,Female,37,Bachelors,10,6,50,65,17,1.0,1,47,Urban,ML Engineer,79564,0 +77679,Male,43,High School,14,43,9,96,66,8.0,3,85,Urban,Data Analyst,77919,0 +77680,Female,38,Masters,4,96,79,95,29,9.0,2,29,Rural,Software Engineer,148226,1 +77681,Male,24,Bachelors,3,34,26,53,87,9.0,7,20,Urban,Data Analyst,142138,0 +77682,Male,55,Bachelors,8,76,58,91,77,8.0,6,65,Semi-Urban,Software Engineer,62717,1 +77683,Male,48,PhD,10,77,31,52,79,2.0,5,47,Semi-Urban,Data Analyst,105947,0 +77684,Female,25,PhD,13,57,97,62,22,0.0,7,59,Rural,Software Engineer,109574,1 +77685,Male,29,Bachelors,4,37,14,57,97,7.0,2,74,Rural,Manager,22808,0 +77686,Male,38,Diploma,2,69,10,81,34,8.0,6,92,Urban,Data Analyst,116881,1 +77687,Male,59,Masters,3,77,29,37,52,2.0,6,14,Semi-Urban,Manager,136291,0 +77688,Other,49,Bachelors,16,15,63,25,63,4.0,7,68,Urban,Software Engineer,25302,0 +77689,Male,31,High School,15,66,27,36,88,3.0,2,55,Urban,Manager,28050,0 +77690,Female,32,Masters,15,53,64,84,88,0.0,4,20,Rural,HR Executive,68221,0 +77691,Male,51,Bachelors,10,28,63,82,20,7.0,2,67,Rural,Software Engineer,147584,1 +77692,Male,47,Bachelors,13,0,75,9,19,2.0,7,47,Rural,Data Analyst,34992,0 +77693,Male,51,Masters,9,2,80,63,70,6.0,7,34,Urban,HR Executive,50115,0 +77694,Female,34,Bachelors,2,70,83,37,87,5.0,0,58,Semi-Urban,HR Executive,65952,1 +77695,Female,25,Bachelors,18,30,33,93,40,2.0,3,24,Urban,HR Executive,64991,0 +77696,Female,35,Masters,1,29,33,47,23,3.0,3,70,Urban,Manager,95558,0 +77697,Male,26,High School,6,77,70,32,38,9.0,6,81,Rural,Manager,135620,1 +77698,Other,57,Diploma,3,67,48,87,91,6.0,1,60,Urban,Data Analyst,78774,1 +77699,Male,45,Bachelors,4,27,50,80,85,9.0,0,78,Rural,Data Analyst,107108,1 +77700,Female,51,Bachelors,9,2,96,99,64,5.0,4,23,Urban,HR Executive,23662,0 +77701,Male,42,Bachelors,0,15,65,90,13,6.0,2,93,Rural,Software Engineer,75727,1 +77702,Female,38,Bachelors,6,3,48,2,53,0.0,7,7,Semi-Urban,Software Engineer,145893,0 +77703,Female,32,Bachelors,18,28,14,92,22,2.0,6,48,Semi-Urban,Manager,85067,0 +77704,Male,57,Bachelors,14,94,33,99,91,0.0,3,57,Rural,Software Engineer,45770,1 +77705,Male,34,Bachelors,2,99,8,24,24,7.0,0,56,Rural,Data Analyst,22502,0 +77706,Female,49,Diploma,11,81,83,57,61,8.0,5,72,Urban,Software Engineer,30895,1 +77707,Female,24,PhD,16,14,73,91,82,5.0,7,14,Semi-Urban,Software Engineer,85309,0 +77708,Female,38,Bachelors,2,41,59,36,61,0.0,5,23,Rural,ML Engineer,109387,0 +77709,Female,48,High School,18,55,84,88,9,1.0,1,10,Semi-Urban,Data Analyst,101362,0 +77710,Female,43,Masters,15,56,93,85,38,2.0,1,44,Rural,ML Engineer,95788,1 +77711,Female,44,Bachelors,9,12,72,70,36,0.0,4,89,Urban,Software Engineer,67020,1 +77712,Male,52,Diploma,9,38,77,70,38,0.0,4,31,Semi-Urban,HR Executive,95799,0 +77713,Male,34,Bachelors,19,9,56,77,18,8.0,7,87,Rural,Software Engineer,31641,0 +77714,Female,46,Masters,4,15,79,98,7,9.0,6,54,Semi-Urban,Manager,87187,1 +77715,Male,29,Bachelors,9,29,95,4,85,7.0,6,68,Urban,Manager,88401,0 +77716,Female,59,PhD,13,14,58,36,45,2.0,7,31,Urban,Manager,65569,0 +77717,Female,50,PhD,17,85,22,7,70,1.0,6,81,Urban,Software Engineer,74807,0 +77718,Male,51,Bachelors,10,94,30,3,52,0.0,1,55,Urban,Data Analyst,41419,0 +77719,Male,47,Masters,14,62,20,97,8,7.0,0,12,Urban,ML Engineer,105571,0 +77720,Male,53,Bachelors,14,43,2,95,21,4.0,5,99,Semi-Urban,HR Executive,50491,1 +77721,Male,21,Bachelors,14,56,44,84,10,2.0,5,25,Semi-Urban,Data Analyst,68790,0 +77722,Male,32,Bachelors,12,71,28,25,23,3.0,1,44,Urban,Data Analyst,33384,0 +77723,Female,40,Masters,2,71,47,54,26,5.0,1,63,Urban,Software Engineer,98880,0 +77724,Female,35,Bachelors,16,93,74,65,13,3.0,7,30,Urban,ML Engineer,130109,1 +77725,Female,43,Diploma,14,79,56,90,15,0.0,5,27,Rural,ML Engineer,108236,1 +77726,Male,42,High School,6,39,43,95,77,2.0,4,99,Semi-Urban,Manager,30216,1 +77727,Male,29,Bachelors,0,54,36,30,87,9.0,4,31,Semi-Urban,Manager,143291,0 +77728,Female,41,High School,13,34,29,90,31,2.0,4,9,Semi-Urban,HR Executive,86093,0 +77729,Male,57,Bachelors,14,62,31,22,83,0.0,2,56,Urban,Software Engineer,62154,0 +77730,Female,56,Diploma,1,85,36,30,93,2.0,6,40,Semi-Urban,HR Executive,82457,0 +77731,Female,46,Diploma,1,14,42,3,96,4.0,0,20,Rural,ML Engineer,63640,0 +77732,Male,42,Bachelors,1,21,36,65,93,4.0,7,15,Semi-Urban,ML Engineer,117318,0 +77733,Male,26,Masters,2,22,41,39,34,3.0,0,57,Semi-Urban,ML Engineer,103547,0 +77734,Male,33,High School,1,84,22,11,80,3.0,6,77,Semi-Urban,Data Analyst,121265,0 +77735,Male,28,High School,2,77,73,97,37,4.0,5,47,Semi-Urban,Manager,93732,1 +77736,Male,32,Masters,7,78,61,50,43,1.0,5,65,Rural,HR Executive,149844,1 +77737,Male,44,Bachelors,1,23,92,17,3,1.0,6,59,Semi-Urban,Manager,54721,0 +77738,Male,40,Masters,5,40,88,37,31,3.0,3,77,Rural,HR Executive,87079,1 +77739,Male,43,Masters,16,39,27,98,45,9.0,5,27,Urban,Software Engineer,103503,0 +77740,Male,42,High School,10,76,53,88,28,9.0,4,10,Semi-Urban,ML Engineer,134837,0 +77741,Female,43,Diploma,11,68,31,53,48,5.0,7,65,Semi-Urban,Data Analyst,109211,0 +77742,Other,47,Bachelors,15,31,98,85,52,2.0,2,37,Urban,Data Analyst,136906,1 +77743,Male,47,Diploma,19,48,62,65,42,7.0,6,74,Rural,ML Engineer,70990,1 +77744,Male,53,Bachelors,5,61,22,65,5,0.0,0,54,Semi-Urban,ML Engineer,139753,0 +77745,Male,28,Bachelors,4,5,83,19,30,2.0,5,16,Urban,ML Engineer,95201,0 +77746,Male,41,Masters,8,3,38,74,52,0.0,1,77,Semi-Urban,ML Engineer,64853,0 +77747,Male,55,Diploma,14,10,94,28,48,8.0,7,27,Semi-Urban,HR Executive,101857,0 +77748,Male,41,High School,13,31,86,42,60,1.0,3,2,Rural,Manager,112952,0 +77749,Female,30,Bachelors,9,31,51,54,6,6.0,0,47,Urban,Software Engineer,97914,0 +77750,Female,24,Bachelors,7,52,23,8,88,0.0,4,13,Urban,Software Engineer,82136,0 +77751,Male,54,PhD,7,35,45,81,78,9.0,2,11,Semi-Urban,ML Engineer,91379,0 +77752,Male,37,Bachelors,7,58,35,60,79,8.0,1,77,Semi-Urban,ML Engineer,44975,0 +77753,Male,52,Masters,7,19,17,88,15,5.0,0,45,Urban,ML Engineer,126959,0 +77754,Female,22,Bachelors,14,28,62,0,99,8.0,7,67,Urban,HR Executive,126090,0 +77755,Male,21,Bachelors,12,86,75,89,82,1.0,0,17,Semi-Urban,Manager,103942,1 +77756,Male,50,High School,17,73,42,75,38,9.0,6,90,Semi-Urban,Manager,61689,1 +77757,Male,45,Bachelors,19,88,48,27,61,5.0,6,84,Semi-Urban,Manager,149358,1 +77758,Male,56,Bachelors,15,29,81,65,64,5.0,2,58,Rural,Manager,112047,0 +77759,Male,27,Diploma,4,98,21,70,86,7.0,6,38,Urban,Software Engineer,71363,0 +77760,Male,34,High School,1,86,73,27,3,5.0,6,9,Semi-Urban,ML Engineer,142688,0 +77761,Female,23,PhD,18,80,61,34,53,0.0,3,54,Urban,Manager,115411,0 +77762,Male,43,Bachelors,10,12,51,5,44,3.0,1,75,Semi-Urban,ML Engineer,41001,0 +77763,Other,36,Diploma,1,45,15,14,74,3.0,1,59,Urban,HR Executive,67981,0 +77764,Female,53,Diploma,3,92,35,24,32,4.0,3,10,Urban,HR Executive,83296,0 +77765,Female,32,Bachelors,6,96,97,31,37,7.0,6,83,Rural,HR Executive,25237,1 +77766,Female,25,Diploma,5,13,69,90,66,6.0,7,23,Rural,ML Engineer,128322,0 +77767,Female,52,Bachelors,15,52,95,68,69,7.0,3,65,Urban,Manager,133126,1 +77768,Male,38,Bachelors,1,35,70,49,82,6.0,7,19,Urban,HR Executive,117920,0 +77769,Male,48,Masters,17,20,81,31,40,4.0,6,60,Urban,HR Executive,40084,0 +77770,Male,21,High School,2,16,86,58,69,5.0,4,49,Urban,HR Executive,80427,0 +77771,Male,31,PhD,9,31,62,65,51,3.0,3,33,Urban,Data Analyst,85174,0 +77772,Male,55,Bachelors,16,89,42,57,79,0.0,2,32,Semi-Urban,ML Engineer,39473,0 +77773,Male,56,Bachelors,7,19,97,48,37,0.0,5,51,Urban,Software Engineer,125511,0 +77774,Female,52,Diploma,8,38,22,62,79,8.0,0,96,Urban,Manager,146404,0 +77775,Female,55,Masters,7,99,41,94,22,9.0,7,40,Urban,ML Engineer,39681,1 +77776,Other,38,Bachelors,6,38,79,76,3,4.0,6,70,Urban,Manager,102073,1 +77777,Male,31,Bachelors,3,36,44,51,69,5.0,3,86,Rural,Data Analyst,117240,0 +77778,Male,45,Bachelors,11,75,89,41,83,1.0,7,42,Semi-Urban,Software Engineer,116340,1 +77779,Male,32,Diploma,5,96,89,59,17,5.0,0,32,Rural,Manager,119361,1 +77780,Male,26,Masters,12,35,9,83,98,9.0,6,39,Urban,Data Analyst,59309,0 +77781,Male,50,Bachelors,16,75,88,65,91,2.0,6,78,Rural,Manager,24044,1 +77782,Other,27,High School,15,8,48,44,2,3.0,0,25,Urban,Software Engineer,81987,0 +77783,Male,53,Bachelors,19,94,25,75,40,5.0,4,23,Urban,Manager,145110,0 +77784,Male,42,Diploma,12,10,94,30,42,4.0,7,55,Rural,HR Executive,85682,0 +77785,Male,34,Bachelors,4,88,63,42,22,8.0,2,10,Semi-Urban,Data Analyst,76095,0 +77786,Female,53,High School,8,88,18,94,88,8.0,7,21,Urban,Data Analyst,88796,0 +77787,Female,51,High School,7,15,61,93,82,5.0,3,60,Urban,Data Analyst,101675,0 +77788,Female,35,Masters,8,89,98,7,69,9.0,0,8,Semi-Urban,ML Engineer,59530,0 +77789,Male,42,Masters,16,31,86,51,49,9.0,6,52,Semi-Urban,Data Analyst,83657,0 +77790,Female,37,Bachelors,18,57,27,17,3,1.0,3,77,Rural,HR Executive,143667,0 +77791,Female,59,Diploma,16,1,80,28,7,9.0,3,83,Rural,Data Analyst,108094,0 +77792,Male,44,Masters,9,58,21,82,38,3.0,6,51,Semi-Urban,Software Engineer,45172,0 +77793,Female,30,Diploma,7,17,18,41,3,0.0,0,23,Urban,Manager,61768,0 +77794,Female,45,Diploma,18,99,24,47,91,3.0,5,31,Rural,Data Analyst,102263,0 +77795,Male,51,Masters,10,25,23,17,50,9.0,3,49,Rural,Data Analyst,104918,0 +77796,Male,23,Bachelors,1,63,98,20,16,4.0,7,29,Urban,Software Engineer,100445,0 +77797,Male,49,Bachelors,15,91,17,83,67,1.0,4,46,Rural,HR Executive,54034,1 +77798,Female,37,Diploma,13,76,43,74,19,1.0,5,93,Urban,Manager,79577,1 +77799,Male,49,Masters,3,72,20,51,17,9.0,0,19,Urban,ML Engineer,76940,0 +77800,Male,29,Diploma,14,17,26,75,45,2.0,3,46,Urban,Manager,129812,0 +77801,Male,48,Bachelors,19,19,69,95,98,9.0,7,52,Urban,Software Engineer,71048,1 +77802,Male,38,Bachelors,14,66,4,0,67,9.0,7,50,Urban,HR Executive,50993,0 +77803,Male,31,High School,8,85,45,29,16,0.0,7,71,Urban,Manager,133306,0 +77804,Female,33,Diploma,4,72,77,23,16,4.0,1,79,Rural,ML Engineer,106828,1 +77805,Female,46,Diploma,8,25,13,88,41,6.0,7,56,Semi-Urban,Manager,119126,0 +77806,Male,28,Bachelors,14,61,44,81,69,5.0,5,58,Urban,Data Analyst,99314,1 +77807,Male,36,Diploma,16,20,90,69,71,0.0,6,80,Semi-Urban,Data Analyst,112986,1 +77808,Female,26,Diploma,0,9,32,75,25,9.0,4,38,Urban,HR Executive,77093,0 +77809,Male,40,Bachelors,2,34,25,19,31,6.0,5,81,Urban,ML Engineer,37978,0 +77810,Male,25,High School,12,61,34,31,62,0.0,7,3,Semi-Urban,HR Executive,98366,0 +77811,Male,29,Masters,0,11,38,72,7,4.0,5,94,Urban,ML Engineer,46462,0 +77812,Female,35,Masters,2,93,0,13,75,4.0,5,43,Urban,Software Engineer,125643,0 +77813,Male,28,PhD,15,19,29,35,71,0.0,7,71,Urban,Software Engineer,23496,0 +77814,Male,26,Diploma,15,95,35,95,28,5.0,5,89,Rural,ML Engineer,60625,1 +77815,Female,22,Bachelors,19,53,64,49,3,3.0,0,3,Rural,ML Engineer,78875,0 +77816,Male,44,Bachelors,4,37,60,97,49,2.0,7,44,Semi-Urban,ML Engineer,57440,1 +77817,Male,51,Bachelors,3,82,83,40,52,2.0,6,88,Urban,Data Analyst,91800,1 +77818,Other,28,Bachelors,5,3,87,10,7,5.0,2,20,Urban,Software Engineer,135840,0 +77819,Male,46,Diploma,4,89,48,37,19,9.0,2,86,Semi-Urban,Manager,61533,1 +77820,Male,43,Bachelors,3,26,53,67,76,7.0,7,96,Semi-Urban,Software Engineer,117071,1 +77821,Female,45,High School,7,22,6,87,94,9.0,2,76,Urban,Software Engineer,141226,0 +77822,Female,50,Bachelors,10,87,93,42,96,9.0,5,94,Urban,Manager,106879,1 +77823,Female,23,High School,13,11,5,67,67,3.0,7,57,Rural,Manager,54751,0 +77824,Female,30,High School,0,69,59,11,97,5.0,4,95,Urban,Software Engineer,36772,0 +77825,Female,29,Masters,9,50,13,48,43,8.0,7,66,Semi-Urban,ML Engineer,119558,0 +77826,Male,23,Bachelors,19,30,46,80,55,0.0,7,37,Urban,Data Analyst,58974,0 +77827,Female,51,Bachelors,12,42,17,72,23,7.0,1,73,Semi-Urban,HR Executive,45424,0 +77828,Female,49,Masters,14,7,79,62,67,2.0,1,49,Rural,Manager,36685,0 +77829,Male,28,Bachelors,0,68,3,79,1,2.0,5,56,Semi-Urban,HR Executive,142950,0 +77830,Male,58,Masters,4,48,12,70,37,7.0,5,7,Urban,Software Engineer,42796,0 +77831,Female,34,Masters,10,98,57,89,56,2.0,0,92,Urban,HR Executive,144436,1 +77832,Other,23,Masters,17,50,24,54,33,7.0,4,62,Urban,Data Analyst,148642,0 +77833,Female,55,Masters,17,26,11,52,67,6.0,6,27,Urban,Data Analyst,49558,0 +77834,Female,31,High School,17,74,5,21,2,1.0,5,92,Urban,HR Executive,119057,0 +77835,Male,33,Masters,17,9,57,65,66,3.0,1,33,Urban,Manager,58780,0 +77836,Male,42,Diploma,15,59,94,39,14,4.0,4,45,Urban,HR Executive,134212,1 +77837,Male,47,Diploma,15,99,2,5,33,8.0,3,5,Urban,HR Executive,124988,0 +77838,Male,55,High School,4,57,17,22,60,9.0,6,35,Rural,Data Analyst,58168,0 +77839,Female,21,High School,18,74,97,88,42,0.0,0,76,Urban,HR Executive,140518,1 +77840,Male,48,PhD,9,81,67,75,98,3.0,0,93,Semi-Urban,Data Analyst,50263,1 +77841,Male,38,High School,15,28,46,55,74,6.0,1,43,Urban,ML Engineer,26498,0 +77842,Male,28,Diploma,7,8,65,11,99,2.0,0,54,Urban,Manager,76017,0 +77843,Male,53,Diploma,2,3,66,76,88,8.0,4,90,Rural,HR Executive,20639,1 +77844,Male,24,Masters,11,65,57,81,0,9.0,1,3,Rural,Manager,22536,0 +77845,Male,36,Bachelors,3,31,24,4,71,1.0,6,43,Semi-Urban,ML Engineer,36122,0 +77846,Male,36,Bachelors,3,41,70,56,87,2.0,3,51,Semi-Urban,Manager,65833,0 +77847,Male,43,Diploma,0,93,58,40,29,9.0,6,39,Urban,Software Engineer,130277,0 +77848,Male,28,Diploma,18,14,0,6,54,2.0,0,99,Urban,Manager,97699,0 +77849,Male,26,Diploma,6,78,4,94,23,6.0,6,3,Urban,ML Engineer,27469,0 +77850,Male,57,Bachelors,6,75,49,40,36,1.0,0,75,Rural,ML Engineer,22966,1 +77851,Male,31,Bachelors,17,35,25,46,13,2.0,3,70,Rural,Data Analyst,86529,0 +77852,Male,24,Bachelors,0,44,96,57,76,2.0,4,53,Rural,ML Engineer,78029,1 +77853,Female,59,Diploma,8,59,97,68,69,1.0,2,7,Urban,Data Analyst,42857,0 +77854,Male,49,High School,12,4,41,82,63,6.0,4,96,Urban,ML Engineer,72776,0 +77855,Male,22,Bachelors,8,52,87,15,73,1.0,3,39,Urban,HR Executive,62726,0 +77856,Female,40,Masters,0,50,83,35,15,1.0,1,23,Urban,ML Engineer,118482,0 +77857,Female,50,Masters,4,31,11,8,90,4.0,7,99,Urban,Software Engineer,46669,0 +77858,Male,21,Bachelors,16,82,48,21,85,3.0,1,23,Urban,Data Analyst,42210,0 +77859,Male,46,High School,16,15,6,83,8,6.0,2,35,Semi-Urban,ML Engineer,85673,0 +77860,Male,37,Masters,19,80,52,68,4,1.0,1,83,Urban,Data Analyst,80059,1 +77861,Female,42,Masters,3,58,19,40,29,1.0,7,16,Semi-Urban,HR Executive,141538,0 +77862,Male,52,Diploma,5,55,76,22,99,9.0,0,99,Rural,Manager,126896,1 +77863,Female,42,Bachelors,6,74,47,40,3,6.0,1,58,Urban,Data Analyst,69151,0 +77864,Female,42,High School,18,28,2,16,6,8.0,3,70,Urban,HR Executive,109440,0 +77865,Other,50,Masters,12,8,35,55,99,5.0,6,0,Urban,ML Engineer,70127,0 +77866,Female,54,Bachelors,12,61,3,28,76,4.0,1,57,Semi-Urban,ML Engineer,64752,0 +77867,Male,46,Masters,8,0,86,27,61,1.0,4,45,Urban,ML Engineer,21915,0 +77868,Male,49,Diploma,18,27,48,51,66,2.0,5,9,Urban,ML Engineer,136207,0 +77869,Male,21,Bachelors,19,31,76,37,57,9.0,5,76,Semi-Urban,Manager,125484,0 +77870,Male,36,Bachelors,3,39,9,37,66,7.0,0,78,Urban,HR Executive,105994,0 +77871,Female,42,High School,10,37,68,70,18,1.0,5,54,Urban,HR Executive,69491,0 +77872,Male,37,Masters,1,80,8,78,12,7.0,5,14,Urban,Manager,128889,0 +77873,Female,45,Bachelors,14,25,38,47,50,6.0,7,47,Semi-Urban,Software Engineer,67614,0 +77874,Female,24,Bachelors,6,27,21,22,64,2.0,6,17,Urban,Software Engineer,146005,0 +77875,Male,48,High School,2,17,16,32,80,8.0,6,72,Urban,HR Executive,32921,0 +77876,Female,33,Masters,19,19,29,19,58,5.0,1,69,Urban,ML Engineer,114929,0 +77877,Female,55,High School,11,46,12,76,48,0.0,4,79,Urban,ML Engineer,67929,0 +77878,Male,42,Masters,10,22,87,54,18,8.0,2,40,Semi-Urban,Data Analyst,58980,0 +77879,Male,59,Bachelors,0,53,26,7,96,4.0,3,58,Urban,Manager,115029,0 +77880,Male,59,PhD,16,42,16,48,35,8.0,5,72,Semi-Urban,Manager,87190,0 +77881,Male,46,Bachelors,4,43,56,61,29,2.0,2,5,Rural,ML Engineer,129842,0 +77882,Female,57,Bachelors,10,47,2,6,41,3.0,2,54,Rural,Data Analyst,82713,0 +77883,Other,38,Diploma,7,21,76,85,5,9.0,5,78,Semi-Urban,HR Executive,29799,1 +77884,Male,47,Bachelors,9,17,47,76,90,8.0,5,0,Rural,Software Engineer,43659,0 +77885,Male,59,Masters,19,66,14,57,22,4.0,5,87,Rural,ML Engineer,21423,0 +77886,Male,28,Bachelors,16,96,11,40,31,6.0,6,14,Urban,HR Executive,83591,0 +77887,Female,41,Masters,8,31,55,10,54,0.0,7,88,Rural,Software Engineer,140332,0 +77888,Female,31,Bachelors,4,90,67,43,18,2.0,4,57,Semi-Urban,Data Analyst,105993,1 +77889,Male,38,Bachelors,12,43,69,40,24,8.0,0,57,Urban,Software Engineer,110332,0 +77890,Female,52,Bachelors,19,43,37,67,12,1.0,1,83,Urban,ML Engineer,52001,0 +77891,Female,59,Masters,12,59,84,21,79,9.0,7,63,Urban,HR Executive,122687,0 +77892,Male,57,Bachelors,12,6,12,31,13,5.0,3,61,Urban,Software Engineer,121363,0 +77893,Male,50,Diploma,8,88,85,44,90,2.0,1,72,Semi-Urban,ML Engineer,108411,1 +77894,Male,31,High School,16,23,9,9,33,3.0,5,67,Urban,Manager,104003,0 +77895,Male,25,Bachelors,3,60,99,9,60,8.0,2,28,Urban,Software Engineer,119856,0 +77896,Male,38,Bachelors,9,38,42,88,8,5.0,7,97,Rural,Software Engineer,51860,1 +77897,Male,49,Bachelors,7,15,70,99,87,5.0,4,11,Semi-Urban,Software Engineer,149396,0 +77898,Female,54,Bachelors,4,49,85,53,49,8.0,3,4,Urban,ML Engineer,28205,0 +77899,Male,27,PhD,6,65,46,2,50,0.0,7,96,Semi-Urban,HR Executive,46503,0 +77900,Male,31,Bachelors,2,33,50,39,92,4.0,4,37,Semi-Urban,HR Executive,60298,0 +77901,Male,30,Masters,6,41,37,39,93,9.0,5,71,Rural,Software Engineer,129818,0 +77902,Male,50,Masters,4,96,32,79,27,3.0,4,87,Rural,Data Analyst,125097,1 +77903,Female,53,Masters,11,27,24,75,7,2.0,3,48,Rural,HR Executive,93330,0 +77904,Male,27,Bachelors,13,16,59,12,73,1.0,0,39,Urban,Software Engineer,74614,0 +77905,Other,22,Bachelors,16,63,54,27,94,2.0,7,14,Rural,Manager,94929,0 +77906,Male,28,Masters,19,47,82,73,29,3.0,0,14,Urban,Manager,102701,0 +77907,Male,34,Masters,0,39,78,67,40,5.0,6,21,Urban,Data Analyst,71947,0 +77908,Female,33,Masters,16,16,47,89,65,7.0,2,86,Semi-Urban,Manager,43521,0 +77909,Other,54,Masters,10,12,23,32,44,7.0,2,18,Urban,HR Executive,61904,0 +77910,Other,38,Bachelors,16,27,18,46,16,7.0,0,25,Urban,Software Engineer,87325,0 +77911,Female,37,Bachelors,4,91,24,62,34,8.0,5,59,Rural,Manager,29961,0 +77912,Other,34,Diploma,0,89,86,45,26,3.0,5,56,Semi-Urban,ML Engineer,137509,1 +77913,Female,45,Bachelors,6,81,29,98,14,0.0,0,86,Rural,Data Analyst,74112,1 +77914,Male,23,Masters,11,77,50,9,49,8.0,7,21,Urban,Software Engineer,112080,0 +77915,Female,28,Bachelors,13,47,82,59,46,0.0,2,58,Urban,Software Engineer,118525,1 +77916,Male,24,Diploma,10,58,32,36,9,0.0,5,59,Urban,Software Engineer,65924,0 +77917,Male,38,High School,9,36,4,46,44,1.0,7,21,Urban,HR Executive,81625,0 +77918,Male,31,Bachelors,13,36,7,73,77,5.0,1,18,Rural,ML Engineer,61966,0 +77919,Female,42,Diploma,12,26,82,60,93,6.0,4,58,Semi-Urban,Software Engineer,108456,0 +77920,Female,45,Bachelors,15,41,10,94,17,8.0,1,24,Rural,ML Engineer,79644,0 +77921,Female,30,High School,0,96,95,47,74,6.0,6,80,Urban,Manager,38229,1 +77922,Male,32,Masters,0,4,4,28,10,6.0,6,67,Urban,Manager,49167,0 +77923,Male,56,Bachelors,9,80,92,6,17,3.0,7,13,Semi-Urban,Data Analyst,123616,0 +77924,Male,26,Diploma,18,10,47,85,38,9.0,1,8,Urban,Data Analyst,147689,0 +77925,Male,56,Masters,6,66,3,91,67,7.0,5,71,Semi-Urban,Software Engineer,84784,0 +77926,Female,33,Bachelors,6,57,81,92,18,4.0,1,20,Rural,Software Engineer,86176,1 +77927,Male,32,Masters,2,40,1,16,56,7.0,5,44,Semi-Urban,HR Executive,119730,0 +77928,Male,55,Bachelors,9,19,49,32,1,6.0,5,23,Urban,HR Executive,106418,0 +77929,Male,26,Masters,7,16,75,29,93,9.0,5,61,Urban,HR Executive,55797,0 +77930,Female,59,Bachelors,5,82,35,30,80,4.0,3,61,Rural,ML Engineer,74119,0 +77931,Male,35,Masters,1,24,70,35,31,1.0,2,8,Rural,HR Executive,133428,0 +77932,Male,41,Bachelors,15,56,60,32,51,9.0,0,0,Semi-Urban,Manager,45721,0 +77933,Male,28,Bachelors,10,50,73,94,94,0.0,2,10,Semi-Urban,ML Engineer,40091,0 +77934,Other,34,Masters,13,81,97,20,54,6.0,6,12,Rural,Data Analyst,43794,0 +77935,Other,30,Bachelors,9,50,46,10,94,0.0,4,31,Urban,Software Engineer,146579,0 +77936,Female,57,Bachelors,10,22,52,27,92,1.0,3,4,Urban,ML Engineer,43409,0 +77937,Female,43,Masters,13,38,86,12,22,4.0,5,18,Urban,ML Engineer,97571,0 +77938,Male,45,High School,11,8,75,4,12,9.0,0,60,Urban,Manager,79634,0 +77939,Male,43,Bachelors,19,97,10,72,49,8.0,4,73,Urban,Software Engineer,33094,1 +77940,Female,24,High School,5,51,60,96,82,9.0,6,47,Urban,Software Engineer,99050,1 +77941,Female,23,PhD,19,77,14,70,97,8.0,3,79,Urban,Manager,126011,0 +77942,Male,36,High School,5,92,4,4,27,8.0,5,10,Semi-Urban,Data Analyst,30093,0 +77943,Male,27,Masters,2,56,74,20,78,8.0,5,53,Urban,Data Analyst,115775,0 +77944,Male,27,Bachelors,15,21,63,38,49,9.0,4,88,Urban,Software Engineer,69333,0 +77945,Female,42,Masters,8,66,9,65,13,4.0,5,10,Semi-Urban,Manager,103843,0 +77946,Female,46,Diploma,18,21,73,85,12,3.0,5,42,Rural,Data Analyst,74867,0 +77947,Female,58,Masters,15,22,72,91,43,3.0,7,51,Urban,Data Analyst,22806,0 +77948,Female,37,High School,19,89,75,34,95,2.0,1,45,Urban,Data Analyst,67857,1 +77949,Male,28,Bachelors,3,97,3,48,64,7.0,3,16,Urban,Data Analyst,141488,0 +77950,Female,35,Masters,9,95,29,73,18,2.0,3,66,Urban,Manager,59251,1 +77951,Male,34,Diploma,5,20,51,97,18,0.0,2,10,Semi-Urban,Data Analyst,30933,0 +77952,Female,40,Masters,10,19,96,9,35,7.0,4,30,Urban,ML Engineer,23744,0 +77953,Male,45,Bachelors,17,29,31,35,11,0.0,4,31,Urban,Software Engineer,39565,0 +77954,Male,46,High School,17,69,63,78,77,1.0,0,89,Semi-Urban,Software Engineer,73411,1 +77955,Male,21,High School,13,15,94,57,57,8.0,4,49,Urban,Software Engineer,77912,0 +77956,Male,35,Diploma,8,19,62,45,5,3.0,1,59,Urban,Software Engineer,47261,0 +77957,Female,42,Bachelors,7,16,74,96,33,3.0,4,25,Rural,Software Engineer,81340,0 +77958,Male,43,Bachelors,3,83,47,21,78,7.0,6,46,Urban,HR Executive,142459,0 +77959,Male,27,Diploma,19,19,64,89,67,5.0,3,23,Urban,Data Analyst,94797,0 +77960,Male,25,Bachelors,11,22,85,99,19,2.0,4,78,Urban,Data Analyst,142848,1 +77961,Female,31,Bachelors,6,44,4,73,93,5.0,4,23,Rural,HR Executive,49002,0 +77962,Male,57,Diploma,5,6,86,59,66,9.0,4,81,Rural,Data Analyst,98154,0 +77963,Male,33,High School,10,55,82,11,2,9.0,0,6,Semi-Urban,Software Engineer,128806,0 +77964,Male,55,Bachelors,2,24,30,74,12,9.0,3,93,Rural,Manager,83586,0 +77965,Male,26,Diploma,19,65,57,58,36,7.0,3,17,Semi-Urban,ML Engineer,41081,0 +77966,Male,30,PhD,10,77,46,10,70,3.0,1,97,Rural,Software Engineer,32102,0 +77967,Male,55,Bachelors,0,78,94,95,2,8.0,2,68,Urban,Software Engineer,45464,1 +77968,Male,35,Masters,13,60,57,5,76,9.0,3,18,Semi-Urban,Software Engineer,65161,0 +77969,Male,58,High School,18,79,47,6,29,9.0,3,4,Semi-Urban,Data Analyst,53258,0 +77970,Male,43,Diploma,18,89,20,24,16,7.0,3,39,Semi-Urban,Data Analyst,28727,0 +77971,Male,49,Bachelors,9,58,20,51,10,1.0,3,53,Semi-Urban,HR Executive,44607,0 +77972,Male,39,Bachelors,8,48,10,90,44,4.0,1,85,Urban,ML Engineer,22815,0 +77973,Female,53,Diploma,19,30,84,20,72,4.0,1,94,Urban,Data Analyst,28947,0 +77974,Female,26,High School,13,45,36,76,68,7.0,3,83,Rural,ML Engineer,127300,0 +77975,Male,40,Diploma,9,24,75,27,64,6.0,2,44,Rural,Manager,77378,0 +77976,Male,38,Bachelors,5,5,97,66,55,2.0,7,97,Semi-Urban,Manager,107874,1 +77977,Female,58,Bachelors,4,41,71,52,9,9.0,3,67,Semi-Urban,HR Executive,55386,0 +77978,Male,55,Bachelors,6,62,57,27,6,0.0,2,21,Urban,Data Analyst,120518,0 +77979,Female,40,High School,9,26,77,45,8,8.0,1,89,Semi-Urban,Manager,90147,0 +77980,Female,36,Bachelors,1,8,32,1,14,4.0,5,80,Rural,Data Analyst,146839,0 +77981,Male,34,Bachelors,7,13,53,56,52,0.0,2,91,Semi-Urban,HR Executive,144960,0 +77982,Female,34,Diploma,8,44,51,95,18,2.0,6,44,Rural,HR Executive,28477,0 +77983,Male,54,Bachelors,7,69,39,46,5,1.0,4,1,Semi-Urban,ML Engineer,60887,0 +77984,Female,27,High School,17,23,11,59,82,5.0,3,54,Semi-Urban,Manager,124497,0 +77985,Male,29,Bachelors,11,53,33,96,62,2.0,4,44,Rural,Manager,120571,0 +77986,Male,31,Diploma,3,16,69,30,32,1.0,4,97,Urban,Software Engineer,118693,0 +77987,Male,41,Bachelors,15,30,75,36,89,4.0,3,53,Urban,Data Analyst,54759,0 +77988,Male,33,High School,15,23,36,9,74,5.0,4,75,Semi-Urban,Software Engineer,62320,0 +77989,Male,39,Diploma,3,62,75,4,96,7.0,6,66,Urban,Manager,70524,0 +77990,Male,29,High School,18,48,96,88,11,1.0,2,34,Urban,Data Analyst,144335,1 +77991,Female,26,High School,10,27,21,0,23,9.0,6,95,Semi-Urban,Manager,119444,0 +77992,Male,35,Masters,11,24,13,37,59,3.0,4,45,Urban,HR Executive,123706,0 +77993,Female,36,High School,4,15,20,96,47,4.0,5,15,Urban,ML Engineer,22008,0 +77994,Female,28,Masters,8,5,44,50,59,8.0,2,41,Urban,ML Engineer,99070,0 +77995,Male,33,Diploma,15,40,69,72,7,5.0,5,13,Rural,Manager,46927,0 +77996,Male,44,Bachelors,7,74,82,84,99,9.0,4,64,Urban,Data Analyst,130889,1 +77997,Female,54,Masters,2,74,43,43,24,4.0,2,18,Semi-Urban,Data Analyst,134635,0 +77998,Female,50,Masters,6,97,89,14,28,3.0,6,70,Rural,Manager,108951,1 +77999,Male,31,Bachelors,5,48,3,51,12,5.0,2,52,Urban,Software Engineer,75968,0 +78000,Male,21,Bachelors,10,40,97,80,15,0.0,6,20,Urban,Manager,44894,1 +78001,Male,32,Bachelors,6,20,51,81,13,1.0,6,32,Urban,Software Engineer,94233,0 +78002,Male,46,Bachelors,2,3,61,53,79,8.0,4,1,Urban,Manager,35208,0 +78003,Male,55,Bachelors,10,74,48,41,4,6.0,6,5,Semi-Urban,Software Engineer,63966,0 +78004,Male,31,Bachelors,19,14,7,2,9,3.0,0,40,Urban,HR Executive,108679,0 +78005,Male,24,High School,4,49,4,40,14,6.0,6,79,Urban,Manager,34013,0 +78006,Female,43,Bachelors,11,14,68,61,83,7.0,5,13,Urban,HR Executive,23215,0 +78007,Female,36,Masters,16,20,25,75,11,1.0,2,35,Urban,Software Engineer,44791,0 +78008,Female,23,Bachelors,4,62,28,50,15,7.0,2,97,Urban,Data Analyst,108737,0 +78009,Male,40,Diploma,12,62,32,88,20,9.0,6,75,Urban,HR Executive,33342,1 +78010,Female,48,High School,2,31,4,14,72,1.0,7,8,Urban,ML Engineer,89365,0 +78011,Male,21,Bachelors,12,41,31,8,82,0.0,2,16,Rural,Software Engineer,34743,0 +78012,Female,39,Bachelors,12,88,94,15,51,4.0,4,24,Urban,Data Analyst,103738,0 +78013,Female,24,Diploma,6,21,53,65,36,8.0,1,45,Semi-Urban,HR Executive,56980,0 +78014,Male,38,Bachelors,0,88,28,99,51,6.0,3,14,Urban,ML Engineer,20838,0 +78015,Female,53,Masters,5,41,97,15,8,5.0,4,40,Urban,HR Executive,100541,0 +78016,Male,28,Masters,17,3,66,20,72,4.0,4,9,Semi-Urban,Software Engineer,144665,0 +78017,Male,36,Masters,11,28,40,55,54,2.0,6,67,Urban,ML Engineer,112397,0 +78018,Male,23,Bachelors,13,42,76,51,6,2.0,5,4,Rural,Manager,34642,0 +78019,Female,40,Diploma,3,39,10,4,43,3.0,3,23,Semi-Urban,Manager,120069,0 +78020,Female,26,Bachelors,18,93,18,24,9,6.0,5,78,Urban,Software Engineer,47421,0 +78021,Female,58,Bachelors,14,3,82,50,54,9.0,5,4,Urban,Manager,110277,0 +78022,Female,34,PhD,18,97,96,87,7,4.0,6,28,Semi-Urban,HR Executive,106577,1 +78023,Other,57,Bachelors,6,89,45,23,25,6.0,6,83,Urban,Manager,69087,0 +78024,Male,32,PhD,3,84,9,53,88,3.0,6,45,Rural,ML Engineer,149113,0 +78025,Male,33,Bachelors,15,35,9,67,98,3.0,5,25,Rural,ML Engineer,140079,0 +78026,Female,45,Bachelors,12,11,9,45,34,7.0,7,69,Rural,Manager,55793,0 +78027,Male,49,High School,16,54,70,1,10,2.0,6,72,Semi-Urban,Software Engineer,81146,0 +78028,Male,24,Masters,5,19,79,56,47,9.0,1,78,Rural,ML Engineer,56539,0 +78029,Female,42,Bachelors,17,56,93,49,60,4.0,2,17,Urban,ML Engineer,119025,0 +78030,Male,48,Diploma,17,98,62,24,34,5.0,7,1,Urban,Data Analyst,124721,0 +78031,Male,34,Masters,14,1,86,40,43,2.0,6,84,Rural,ML Engineer,52354,0 +78032,Female,29,PhD,12,22,96,56,39,6.0,3,28,Semi-Urban,Software Engineer,71354,0 +78033,Male,25,High School,17,96,7,6,9,9.0,1,75,Semi-Urban,Manager,146288,0 +78034,Male,25,High School,19,82,19,64,28,3.0,7,57,Semi-Urban,Software Engineer,51342,0 +78035,Male,48,Bachelors,14,37,21,22,8,6.0,5,47,Semi-Urban,Manager,30218,0 +78036,Female,38,High School,7,24,54,66,66,4.0,5,96,Semi-Urban,Software Engineer,88939,0 +78037,Male,50,Masters,13,72,51,23,40,7.0,3,88,Urban,HR Executive,92889,0 +78038,Female,28,Diploma,11,21,71,48,34,9.0,7,43,Urban,ML Engineer,136199,0 +78039,Female,30,Bachelors,17,22,46,41,2,6.0,7,62,Rural,ML Engineer,36181,0 +78040,Female,41,Masters,12,25,77,48,76,2.0,2,7,Rural,HR Executive,112199,0 +78041,Female,29,Bachelors,10,75,86,63,26,4.0,0,91,Urban,Software Engineer,141959,1 +78042,Female,54,Bachelors,8,71,36,51,97,7.0,7,34,Semi-Urban,HR Executive,96158,0 +78043,Male,45,Bachelors,7,83,76,76,45,9.0,4,81,Urban,Software Engineer,34535,1 +78044,Female,31,Masters,18,90,58,72,86,8.0,1,2,Rural,Manager,143908,0 +78045,Male,55,High School,9,16,63,10,91,1.0,5,23,Semi-Urban,Software Engineer,100829,0 +78046,Male,58,Bachelors,12,20,42,16,33,5.0,3,29,Semi-Urban,Software Engineer,80182,0 +78047,Female,34,High School,0,98,7,9,28,2.0,3,87,Urban,HR Executive,146848,0 +78048,Male,27,Diploma,14,37,89,39,23,8.0,5,25,Urban,Manager,59811,0 +78049,Male,51,PhD,17,54,9,16,31,7.0,3,52,Urban,Software Engineer,99186,0 +78050,Female,52,Masters,13,48,16,72,79,0.0,5,83,Semi-Urban,Data Analyst,98067,0 +78051,Male,25,Bachelors,0,63,79,30,38,2.0,0,42,Rural,HR Executive,107589,0 +78052,Male,46,Masters,1,37,27,50,13,7.0,4,72,Semi-Urban,Software Engineer,37895,0 +78053,Female,59,High School,16,98,9,9,36,3.0,3,49,Semi-Urban,ML Engineer,42346,0 +78054,Male,57,High School,15,75,23,77,75,2.0,6,33,Semi-Urban,Manager,22603,0 +78055,Female,24,Masters,15,28,53,8,9,6.0,5,74,Urban,ML Engineer,85675,0 +78056,Male,28,High School,14,17,91,7,20,0.0,5,61,Urban,Data Analyst,134455,0 +78057,Female,33,High School,6,30,28,81,12,7.0,5,1,Urban,Software Engineer,55590,0 +78058,Male,23,Bachelors,8,13,96,29,82,3.0,6,56,Urban,Data Analyst,42449,0 +78059,Male,29,Diploma,11,92,12,91,17,7.0,7,19,Rural,Software Engineer,73386,0 +78060,Male,59,Masters,0,22,29,59,17,0.0,6,10,Urban,Software Engineer,81407,0 +78061,Female,39,Masters,7,11,13,24,80,3.0,1,11,Urban,Software Engineer,142170,0 +78062,Male,30,Masters,8,12,28,74,30,7.0,1,31,Urban,Software Engineer,128061,0 +78063,Female,58,Bachelors,2,39,53,49,2,6.0,5,99,Semi-Urban,Data Analyst,61696,0 +78064,Male,58,Bachelors,7,46,73,99,18,0.0,3,75,Urban,Software Engineer,62734,1 +78065,Female,36,Masters,2,93,28,3,16,8.0,3,93,Rural,HR Executive,77274,0 +78066,Male,28,PhD,17,36,38,34,33,1.0,0,20,Urban,HR Executive,87968,0 +78067,Male,46,Masters,5,36,88,31,68,5.0,0,13,Urban,ML Engineer,139601,0 +78068,Female,51,Diploma,6,89,28,4,61,1.0,0,1,Urban,HR Executive,79080,0 +78069,Female,46,Diploma,5,55,97,75,16,4.0,7,33,Urban,Manager,59738,1 +78070,Female,24,Masters,9,71,4,47,94,8.0,5,44,Rural,Data Analyst,24551,0 +78071,Male,39,PhD,4,27,80,21,84,7.0,0,75,Semi-Urban,Data Analyst,49870,0 +78072,Female,51,Masters,5,60,56,37,78,5.0,5,87,Urban,Manager,89587,0 +78073,Male,56,Masters,10,64,53,32,4,1.0,2,64,Urban,HR Executive,117006,0 +78074,Other,38,Masters,6,3,61,90,71,3.0,1,34,Urban,Manager,72048,0 +78075,Male,27,Diploma,19,80,66,37,18,6.0,7,99,Semi-Urban,HR Executive,130006,1 +78076,Male,33,Bachelors,8,84,89,84,39,5.0,7,49,Urban,ML Engineer,143350,1 +78077,Female,49,Bachelors,10,36,85,25,97,1.0,1,65,Urban,HR Executive,46706,0 +78078,Male,39,Bachelors,17,52,26,5,60,9.0,5,79,Urban,Data Analyst,83926,0 +78079,Other,54,Masters,16,17,95,73,40,4.0,0,8,Urban,ML Engineer,24703,0 +78080,Female,50,Bachelors,2,23,76,54,54,8.0,5,69,Urban,ML Engineer,38833,0 +78081,Female,33,Bachelors,13,18,88,35,3,9.0,2,17,Urban,Manager,50242,0 +78082,Male,26,High School,11,77,47,69,82,9.0,5,73,Urban,Manager,79101,1 +78083,Female,38,Masters,7,53,94,4,38,2.0,5,38,Urban,Manager,101760,0 +78084,Male,23,Bachelors,13,27,56,39,97,2.0,3,61,Urban,Data Analyst,62356,0 +78085,Female,27,Diploma,16,87,73,94,19,8.0,3,99,Urban,Software Engineer,148466,1 +78086,Male,43,Bachelors,13,16,13,1,60,4.0,4,2,Urban,HR Executive,24659,0 +78087,Male,29,Masters,10,16,7,52,62,9.0,5,31,Semi-Urban,HR Executive,117831,0 +78088,Male,54,Masters,19,73,84,39,86,9.0,3,88,Semi-Urban,HR Executive,56832,1 +78089,Female,42,Masters,0,31,95,6,11,9.0,3,67,Urban,ML Engineer,111637,0 +78090,Female,46,High School,14,77,70,30,38,0.0,0,20,Urban,Software Engineer,86423,0 +78091,Female,26,Bachelors,2,86,65,85,87,8.0,0,98,Semi-Urban,HR Executive,46113,1 +78092,Male,29,High School,14,32,72,41,50,5.0,1,63,Semi-Urban,Data Analyst,127104,0 +78093,Male,35,High School,15,50,6,29,52,2.0,4,22,Urban,Manager,43808,0 +78094,Male,25,Masters,7,23,62,9,8,5.0,4,12,Semi-Urban,HR Executive,56726,0 +78095,Male,46,High School,0,52,46,6,61,5.0,6,35,Urban,Manager,54690,0 +78096,Female,34,Bachelors,9,99,55,43,95,4.0,7,70,Urban,HR Executive,87040,1 +78097,Male,55,Diploma,7,18,61,25,90,2.0,4,47,Semi-Urban,Software Engineer,46023,0 +78098,Male,38,Masters,14,43,76,85,44,1.0,0,86,Semi-Urban,Data Analyst,65065,1 +78099,Female,25,Bachelors,7,51,43,14,96,8.0,6,60,Urban,Data Analyst,104125,0 +78100,Other,52,Masters,9,88,71,42,5,1.0,1,94,Urban,Software Engineer,143275,1 +78101,Female,33,High School,8,12,7,43,49,4.0,4,46,Urban,Data Analyst,138782,0 +78102,Male,51,Bachelors,19,63,67,40,12,0.0,6,73,Rural,Data Analyst,106392,1 +78103,Male,33,Diploma,16,57,97,90,9,0.0,6,41,Rural,Software Engineer,101111,1 +78104,Male,22,Bachelors,17,17,84,42,95,7.0,6,2,Urban,Data Analyst,27484,0 +78105,Female,41,Diploma,1,80,96,96,71,4.0,0,33,Urban,Software Engineer,22493,1 +78106,Male,46,Bachelors,0,4,0,16,79,5.0,1,15,Semi-Urban,Data Analyst,73727,0 +78107,Male,31,Bachelors,4,76,81,53,81,8.0,5,48,Rural,Manager,119693,1 +78108,Male,53,Masters,10,3,48,78,45,6.0,2,60,Semi-Urban,ML Engineer,28770,0 +78109,Female,38,Bachelors,7,80,81,48,57,5.0,2,23,Semi-Urban,Manager,68849,0 +78110,Male,27,Masters,0,23,29,76,72,8.0,7,31,Urban,ML Engineer,134742,0 +78111,Male,21,Masters,4,6,39,48,14,4.0,7,94,Rural,HR Executive,82194,0 +78112,Male,28,Bachelors,17,37,33,90,2,2.0,4,97,Rural,ML Engineer,53621,1 +78113,Male,34,Bachelors,3,49,86,95,65,4.0,6,92,Urban,Data Analyst,65376,1 +78114,Male,48,PhD,1,33,1,56,84,8.0,2,56,Semi-Urban,Data Analyst,82023,0 +78115,Male,34,PhD,15,5,10,4,49,5.0,1,36,Semi-Urban,Data Analyst,50995,0 +78116,Female,54,Diploma,4,87,2,87,71,4.0,7,73,Urban,Data Analyst,109646,1 +78117,Female,33,Bachelors,16,75,53,57,23,2.0,5,38,Urban,HR Executive,96694,0 +78118,Female,21,Masters,2,23,18,72,64,4.0,0,87,Urban,Software Engineer,134306,0 +78119,Male,23,Diploma,16,74,88,57,19,2.0,1,38,Semi-Urban,Manager,53452,1 +78120,Other,54,High School,19,74,72,45,57,8.0,7,32,Semi-Urban,HR Executive,59105,0 +78121,Male,35,Diploma,0,10,88,3,77,6.0,1,41,Semi-Urban,Software Engineer,91603,0 +78122,Female,45,Diploma,13,29,14,85,22,3.0,5,75,Urban,Manager,75227,0 +78123,Female,26,Masters,7,93,9,52,74,0.0,6,93,Semi-Urban,Software Engineer,68045,1 +78124,Male,43,Masters,6,25,7,31,45,5.0,2,46,Urban,HR Executive,90624,0 +78125,Male,26,Bachelors,13,41,9,75,13,3.0,2,71,Urban,HR Executive,96716,0 +78126,Female,24,Masters,6,35,96,62,10,6.0,2,29,Semi-Urban,ML Engineer,84682,0 +78127,Female,30,High School,4,13,2,63,20,8.0,4,97,Rural,Data Analyst,101689,0 +78128,Male,58,Bachelors,11,45,5,87,40,4.0,0,3,Urban,Data Analyst,146029,0 +78129,Male,42,Diploma,5,59,88,23,85,8.0,5,96,Urban,Manager,34417,1 +78130,Female,59,Bachelors,10,86,80,21,17,9.0,2,23,Urban,Data Analyst,132028,0 +78131,Other,45,PhD,5,47,26,76,22,6.0,6,42,Urban,Manager,39247,0 +78132,Female,59,Diploma,1,93,67,70,75,1.0,4,37,Urban,HR Executive,62113,1 +78133,Female,27,Bachelors,4,31,83,68,60,6.0,7,33,Urban,Data Analyst,110121,0 +78134,Female,48,Bachelors,3,58,64,54,7,6.0,0,10,Rural,Software Engineer,98725,0 +78135,Female,23,Bachelors,13,28,50,58,31,4.0,6,48,Semi-Urban,Data Analyst,112505,0 +78136,Female,42,High School,7,95,21,17,78,3.0,1,60,Urban,Software Engineer,86409,0 +78137,Male,22,Bachelors,19,60,36,33,17,1.0,2,24,Semi-Urban,ML Engineer,145410,0 +78138,Female,22,Diploma,9,68,76,75,73,0.0,1,49,Urban,ML Engineer,58697,1 +78139,Female,58,Diploma,6,64,56,29,40,8.0,0,19,Urban,Data Analyst,102796,0 +78140,Male,25,Bachelors,12,30,24,82,98,3.0,2,22,Urban,Manager,32703,0 +78141,Male,25,High School,6,24,1,31,94,5.0,7,91,Urban,ML Engineer,72741,0 +78142,Female,55,Bachelors,18,42,92,60,56,3.0,6,68,Urban,ML Engineer,141213,1 +78143,Male,41,Masters,13,7,3,4,89,7.0,5,94,Urban,Software Engineer,66567,0 +78144,Male,45,Bachelors,13,41,4,36,63,7.0,2,62,Urban,Manager,97058,0 +78145,Female,48,Bachelors,1,78,22,18,22,7.0,2,62,Semi-Urban,HR Executive,20874,0 +78146,Male,34,Masters,0,89,85,53,73,4.0,1,31,Semi-Urban,HR Executive,130256,1 +78147,Male,36,Masters,7,27,17,66,0,4.0,7,40,Rural,Manager,74861,0 +78148,Female,48,High School,3,87,98,69,87,5.0,6,25,Urban,HR Executive,29472,1 +78149,Male,49,PhD,1,9,69,34,26,8.0,1,17,Rural,Data Analyst,111077,0 +78150,Male,56,Bachelors,10,49,29,35,7,0.0,2,14,Semi-Urban,Data Analyst,22130,0 +78151,Male,43,Bachelors,11,95,62,6,68,9.0,4,57,Urban,Software Engineer,81490,0 +78152,Female,30,High School,18,18,47,34,84,4.0,5,57,Urban,Manager,23547,0 +78153,Male,48,Bachelors,14,70,42,97,32,0.0,0,24,Urban,Data Analyst,123641,0 +78154,Male,21,High School,3,33,6,4,31,4.0,7,61,Urban,Manager,62815,0 +78155,Male,59,Bachelors,1,40,21,44,57,8.0,4,2,Urban,ML Engineer,78374,0 +78156,Male,26,Bachelors,6,80,44,86,75,7.0,0,85,Urban,Data Analyst,48058,1 +78157,Other,31,High School,1,87,29,49,86,2.0,3,96,Semi-Urban,ML Engineer,146368,1 +78158,Female,59,Bachelors,12,21,31,84,27,7.0,5,4,Urban,Software Engineer,82910,0 +78159,Male,25,Bachelors,11,83,49,39,79,7.0,1,20,Semi-Urban,Manager,56182,0 +78160,Female,43,Diploma,10,93,60,94,71,5.0,4,45,Urban,ML Engineer,61635,1 +78161,Male,43,High School,13,13,24,48,46,0.0,1,0,Semi-Urban,Manager,22572,0 +78162,Male,33,Masters,7,81,87,0,24,9.0,4,28,Urban,HR Executive,49958,0 +78163,Male,48,Bachelors,19,0,17,4,6,5.0,6,41,Urban,Software Engineer,81957,0 +78164,Female,59,Bachelors,18,53,91,0,35,2.0,4,36,Rural,Manager,36858,0 +78165,Male,26,High School,5,97,61,47,11,8.0,6,71,Urban,Manager,24162,1 +78166,Female,46,Bachelors,15,48,21,80,81,6.0,5,44,Urban,Software Engineer,68613,0 +78167,Male,26,Masters,12,13,22,46,47,9.0,6,38,Urban,Software Engineer,83805,0 +78168,Male,52,Bachelors,13,54,66,24,94,5.0,6,42,Semi-Urban,Software Engineer,126469,0 +78169,Female,31,Masters,13,80,90,68,38,9.0,3,83,Rural,Data Analyst,146598,1 +78170,Male,24,Diploma,15,54,20,61,15,0.0,1,12,Urban,Manager,142286,0 +78171,Female,40,Diploma,2,97,42,31,93,0.0,6,56,Urban,ML Engineer,59420,0 +78172,Female,47,Masters,16,41,44,26,19,7.0,0,19,Rural,Data Analyst,74163,0 +78173,Male,37,Diploma,1,78,95,26,56,4.0,7,38,Urban,Manager,82396,1 +78174,Female,57,Masters,4,1,38,97,8,2.0,1,2,Urban,ML Engineer,43454,0 +78175,Female,52,Bachelors,12,6,8,74,67,2.0,2,76,Urban,ML Engineer,89471,0 +78176,Female,21,Bachelors,16,48,7,30,40,7.0,5,27,Urban,Data Analyst,137551,0 +78177,Male,44,Bachelors,11,4,34,43,91,2.0,1,97,Urban,ML Engineer,36278,0 +78178,Female,32,Bachelors,10,74,83,22,23,1.0,0,11,Urban,Software Engineer,42637,0 +78179,Female,31,Diploma,8,92,40,75,20,7.0,5,90,Urban,Manager,24884,1 +78180,Female,33,Bachelors,12,25,56,99,84,2.0,2,44,Urban,HR Executive,71013,0 +78181,Male,53,Diploma,10,19,28,38,36,4.0,6,41,Semi-Urban,Software Engineer,21056,0 +78182,Female,34,PhD,18,53,39,45,10,4.0,4,19,Urban,HR Executive,73764,0 +78183,Other,55,Bachelors,4,70,43,16,15,1.0,5,25,Rural,Data Analyst,101592,0 +78184,Male,38,High School,10,13,22,66,67,2.0,4,6,Rural,ML Engineer,147036,0 +78185,Female,31,Masters,8,85,57,64,56,5.0,1,50,Urban,HR Executive,45772,1 +78186,Female,30,Diploma,19,25,73,12,3,2.0,0,44,Rural,Data Analyst,67850,0 +78187,Female,38,Diploma,1,82,10,61,57,2.0,7,28,Urban,ML Engineer,135802,0 +78188,Male,36,Masters,4,81,96,27,12,4.0,3,41,Semi-Urban,HR Executive,79581,1 +78189,Female,50,Masters,16,8,54,88,45,8.0,2,91,Rural,Manager,54299,1 +78190,Female,27,Bachelors,16,84,39,3,36,5.0,6,48,Urban,Software Engineer,117863,0 +78191,Female,57,PhD,2,49,92,94,75,9.0,3,85,Semi-Urban,Software Engineer,73349,1 +78192,Male,30,Masters,4,13,89,19,97,9.0,4,7,Urban,HR Executive,109521,0 +78193,Male,58,Diploma,11,23,48,54,83,6.0,7,27,Urban,Software Engineer,46065,0 +78194,Male,50,High School,6,31,24,22,1,5.0,6,84,Urban,ML Engineer,135121,0 +78195,Female,28,Bachelors,19,87,57,25,81,9.0,2,41,Urban,Data Analyst,76195,0 +78196,Female,38,Diploma,11,53,80,96,33,0.0,4,77,Semi-Urban,Software Engineer,114259,1 +78197,Male,22,Bachelors,5,30,40,22,50,8.0,0,6,Urban,Software Engineer,51937,0 +78198,Male,46,PhD,13,45,86,21,4,7.0,0,17,Semi-Urban,Data Analyst,23145,0 +78199,Male,56,Bachelors,3,10,12,35,51,6.0,1,22,Semi-Urban,HR Executive,51955,0 +78200,Female,55,PhD,8,33,40,15,43,8.0,7,27,Urban,HR Executive,37715,0 +78201,Male,45,Diploma,11,82,79,34,39,4.0,6,15,Urban,Software Engineer,65835,0 +78202,Male,35,Diploma,2,99,50,36,44,1.0,7,50,Urban,Manager,51797,1 +78203,Male,45,Bachelors,7,77,57,36,35,4.0,7,44,Urban,HR Executive,120811,0 +78204,Female,56,Diploma,15,17,31,67,83,7.0,3,30,Rural,Data Analyst,70354,0 +78205,Male,22,PhD,0,3,30,19,84,6.0,6,14,Rural,Software Engineer,139401,0 +78206,Female,56,PhD,3,21,21,16,96,8.0,0,63,Urban,Manager,147958,0 +78207,Male,30,High School,1,5,45,62,78,0.0,1,71,Rural,ML Engineer,117390,0 +78208,Male,41,PhD,10,59,84,8,94,8.0,5,22,Urban,Software Engineer,121890,0 +78209,Male,27,Diploma,16,13,76,14,91,3.0,6,89,Rural,Software Engineer,145228,0 +78210,Male,22,Bachelors,15,51,18,27,75,2.0,0,0,Urban,ML Engineer,141804,0 +78211,Male,54,Bachelors,9,34,1,69,81,4.0,2,32,Semi-Urban,Software Engineer,28719,0 +78212,Male,34,Diploma,6,95,36,24,61,0.0,2,45,Semi-Urban,Software Engineer,131011,0 +78213,Male,44,Diploma,6,43,40,24,97,6.0,5,35,Rural,Software Engineer,28602,0 +78214,Male,48,Bachelors,12,86,31,83,72,9.0,3,10,Urban,ML Engineer,93006,0 +78215,Female,46,Bachelors,7,64,15,87,81,7.0,6,82,Urban,Manager,57554,1 +78216,Female,22,High School,1,89,42,69,8,2.0,4,4,Rural,Software Engineer,109045,0 +78217,Male,52,Bachelors,19,28,42,64,2,9.0,7,43,Semi-Urban,ML Engineer,139596,0 +78218,Male,49,Bachelors,17,93,13,51,28,5.0,1,98,Urban,ML Engineer,99775,1 +78219,Other,40,Bachelors,9,2,72,73,20,6.0,4,50,Urban,HR Executive,149071,0 +78220,Male,27,Bachelors,1,22,12,68,4,9.0,3,42,Urban,HR Executive,127617,0 +78221,Female,59,Masters,12,8,2,21,43,0.0,0,9,Semi-Urban,Data Analyst,93871,0 +78222,Female,21,Bachelors,17,71,13,18,11,3.0,4,16,Urban,Software Engineer,68963,0 +78223,Male,23,Bachelors,15,91,60,22,39,0.0,0,48,Semi-Urban,Manager,143974,0 +78224,Other,34,Bachelors,19,21,55,45,64,9.0,5,35,Urban,Data Analyst,145163,0 +78225,Male,29,Diploma,11,12,57,39,13,1.0,6,35,Urban,Software Engineer,49691,0 +78226,Male,21,Masters,11,73,25,17,51,8.0,1,71,Semi-Urban,HR Executive,43645,0 +78227,Male,55,Bachelors,6,39,98,70,53,8.0,4,58,Urban,Software Engineer,107585,1 +78228,Female,50,High School,12,69,11,76,6,7.0,0,41,Semi-Urban,ML Engineer,55977,0 +78229,Male,56,High School,8,84,19,80,9,7.0,1,50,Urban,Manager,26974,0 +78230,Male,50,Bachelors,15,44,63,64,27,1.0,4,25,Semi-Urban,HR Executive,31544,0 +78231,Female,37,Bachelors,17,83,31,8,13,7.0,6,51,Urban,Manager,96126,0 +78232,Male,24,Masters,10,13,43,37,8,9.0,5,32,Semi-Urban,Data Analyst,111050,0 +78233,Male,46,Bachelors,17,65,7,4,92,1.0,5,44,Urban,HR Executive,34331,0 +78234,Male,26,Diploma,3,99,47,96,88,8.0,6,8,Urban,ML Engineer,36577,1 +78235,Female,45,Diploma,3,72,46,39,80,0.0,5,66,Urban,Manager,125593,0 +78236,Female,39,Diploma,18,80,39,82,72,1.0,6,44,Semi-Urban,Data Analyst,82665,1 +78237,Female,55,Diploma,19,40,44,47,16,0.0,4,14,Urban,Data Analyst,66917,0 +78238,Male,39,Diploma,11,19,41,53,3,7.0,3,53,Semi-Urban,ML Engineer,78196,0 +78239,Male,26,Bachelors,5,34,95,83,10,6.0,3,96,Urban,HR Executive,127161,1 +78240,Male,30,Bachelors,17,84,78,49,2,8.0,4,56,Urban,HR Executive,26692,1 +78241,Female,38,Masters,18,36,15,64,88,9.0,0,42,Urban,Manager,102439,0 +78242,Female,41,Diploma,18,12,65,72,88,4.0,4,71,Urban,Software Engineer,29807,0 +78243,Male,48,Diploma,13,66,25,12,45,4.0,6,18,Urban,HR Executive,57817,0 +78244,Male,54,Bachelors,10,79,68,19,96,4.0,4,81,Semi-Urban,Data Analyst,57695,1 +78245,Male,31,Bachelors,15,61,90,44,50,6.0,5,65,Urban,Manager,78400,1 +78246,Female,44,Masters,12,34,53,51,52,0.0,2,63,Urban,HR Executive,94120,0 +78247,Female,59,High School,8,80,88,61,17,0.0,6,76,Semi-Urban,Manager,20777,1 +78248,Male,48,Bachelors,2,19,42,77,47,2.0,2,97,Urban,Data Analyst,57458,1 +78249,Female,47,Bachelors,1,82,37,2,26,3.0,0,67,Semi-Urban,HR Executive,133405,0 +78250,Male,34,Bachelors,2,48,49,26,62,6.0,3,39,Urban,ML Engineer,38061,0 +78251,Male,43,Bachelors,1,66,40,71,6,7.0,6,99,Urban,ML Engineer,26815,1 +78252,Male,39,Bachelors,10,57,9,28,85,9.0,5,11,Urban,Software Engineer,61097,0 +78253,Male,21,Diploma,12,45,58,89,36,7.0,2,96,Rural,ML Engineer,142115,1 +78254,Male,50,High School,7,28,53,88,69,3.0,5,46,Semi-Urban,HR Executive,94420,0 +78255,Male,25,High School,8,16,85,72,15,2.0,5,64,Urban,Manager,50795,1 +78256,Female,56,High School,7,57,73,10,40,0.0,6,2,Semi-Urban,Manager,98565,0 +78257,Male,32,Bachelors,18,44,72,28,59,4.0,6,86,Urban,Data Analyst,45147,0 +78258,Male,32,Masters,3,1,98,60,81,4.0,3,53,Urban,Software Engineer,47805,0 +78259,Male,58,Bachelors,3,74,80,36,47,0.0,2,49,Urban,ML Engineer,35912,1 +78260,Other,33,High School,19,24,23,94,89,7.0,2,14,Urban,ML Engineer,32513,0 +78261,Male,22,Masters,6,1,36,22,27,7.0,7,84,Rural,ML Engineer,67017,0 +78262,Male,27,Bachelors,2,89,65,76,90,7.0,4,98,Urban,Software Engineer,76184,1 +78263,Other,25,Diploma,6,34,6,34,59,8.0,0,84,Semi-Urban,Data Analyst,90824,0 +78264,Male,27,Bachelors,2,18,67,22,29,6.0,0,8,Semi-Urban,Manager,83177,0 +78265,Male,48,High School,5,69,79,87,59,6.0,5,80,Urban,HR Executive,119977,1 +78266,Male,38,Bachelors,7,39,82,69,50,4.0,0,69,Semi-Urban,ML Engineer,24500,1 +78267,Male,42,Masters,1,5,25,43,40,1.0,5,31,Semi-Urban,HR Executive,53129,0 +78268,Male,38,High School,3,77,22,36,25,8.0,3,10,Urban,Software Engineer,128822,0 +78269,Female,53,Masters,2,50,34,37,61,9.0,6,44,Rural,Software Engineer,86902,0 +78270,Male,43,High School,12,84,75,88,49,3.0,5,46,Urban,ML Engineer,55819,1 +78271,Female,49,Masters,9,66,95,70,74,2.0,0,68,Semi-Urban,Data Analyst,124181,1 +78272,Male,22,Bachelors,9,39,37,18,69,7.0,2,92,Rural,Data Analyst,94964,0 +78273,Male,31,Bachelors,6,54,35,89,89,1.0,0,85,Semi-Urban,Software Engineer,53169,1 +78274,Male,49,Bachelors,14,15,63,71,88,8.0,5,14,Urban,Data Analyst,31849,0 +78275,Male,43,Masters,13,66,19,42,59,3.0,4,67,Urban,HR Executive,43808,0 +78276,Male,58,PhD,5,43,97,85,64,1.0,1,32,Rural,Data Analyst,95129,1 +78277,Other,25,Bachelors,8,30,44,34,14,2.0,6,58,Semi-Urban,Data Analyst,134290,0 +78278,Male,54,Masters,3,77,92,39,9,8.0,0,57,Urban,ML Engineer,115688,1 +78279,Male,32,Masters,11,11,87,89,11,2.0,6,67,Urban,ML Engineer,71248,1 +78280,Male,30,Diploma,17,4,70,45,28,1.0,1,23,Urban,Manager,30159,0 +78281,Male,24,Bachelors,16,3,89,71,41,5.0,7,63,Urban,ML Engineer,91650,0 +78282,Female,51,Bachelors,0,44,69,10,37,8.0,6,24,Rural,ML Engineer,94534,0 +78283,Male,32,Bachelors,12,44,8,30,20,9.0,0,33,Urban,HR Executive,109568,0 +78284,Male,27,Masters,4,83,44,26,93,4.0,0,58,Rural,ML Engineer,22114,0 +78285,Female,32,PhD,4,16,53,58,7,8.0,0,11,Semi-Urban,Data Analyst,55362,0 +78286,Male,55,Diploma,12,2,61,71,54,7.0,6,24,Semi-Urban,Manager,110754,0 +78287,Male,44,Bachelors,15,78,46,60,17,3.0,5,74,Urban,Software Engineer,46278,1 +78288,Female,30,Diploma,5,48,21,61,86,5.0,6,23,Semi-Urban,Software Engineer,83582,0 +78289,Male,39,Masters,2,51,93,61,96,4.0,0,95,Semi-Urban,Data Analyst,36536,1 +78290,Male,57,Bachelors,1,82,59,71,43,8.0,0,27,Urban,ML Engineer,57739,1 +78291,Male,27,Bachelors,8,44,83,71,50,5.0,0,79,Semi-Urban,Software Engineer,93197,1 +78292,Female,28,Bachelors,0,88,96,36,58,4.0,2,69,Semi-Urban,Software Engineer,54317,1 +78293,Male,26,Bachelors,2,26,29,96,9,2.0,5,96,Urban,Data Analyst,84707,1 +78294,Female,58,Diploma,13,81,41,58,83,2.0,2,15,Rural,Data Analyst,110756,0 +78295,Female,49,Bachelors,18,55,28,61,48,2.0,0,55,Urban,Data Analyst,83988,0 +78296,Female,59,Masters,6,32,23,22,45,7.0,6,70,Semi-Urban,Data Analyst,56324,0 +78297,Other,43,Bachelors,14,69,10,48,33,3.0,0,6,Semi-Urban,Manager,63217,0 +78298,Female,47,PhD,14,11,67,26,19,7.0,0,3,Urban,HR Executive,76997,0 +78299,Male,38,Masters,1,52,70,47,86,8.0,5,20,Urban,ML Engineer,49830,0 +78300,Female,48,Diploma,11,98,12,78,88,9.0,1,8,Urban,Software Engineer,21566,0 +78301,Female,37,PhD,4,14,13,54,67,4.0,5,20,Urban,Manager,44125,0 +78302,Male,30,High School,1,67,69,80,84,6.0,3,52,Urban,Software Engineer,87385,1 +78303,Female,51,Diploma,1,16,44,6,60,5.0,2,40,Urban,Manager,123109,0 +78304,Male,25,Bachelors,5,2,20,17,7,8.0,0,95,Semi-Urban,Data Analyst,99974,0 +78305,Female,39,Bachelors,6,38,67,90,30,5.0,7,20,Semi-Urban,Software Engineer,91018,0 +78306,Female,50,Diploma,18,32,38,13,87,1.0,2,94,Urban,HR Executive,81134,0 +78307,Female,35,Masters,2,13,87,28,35,9.0,1,21,Urban,Manager,88132,0 +78308,Female,52,Masters,1,91,77,14,8,4.0,2,5,Rural,ML Engineer,97622,0 +78309,Female,42,Masters,7,29,12,81,72,2.0,3,31,Urban,Manager,24450,0 +78310,Male,51,Bachelors,2,91,15,52,52,2.0,4,91,Urban,HR Executive,113093,1 +78311,Female,27,Bachelors,14,67,32,9,53,9.0,1,51,Semi-Urban,HR Executive,37208,0 +78312,Other,59,Bachelors,2,49,38,95,34,0.0,7,57,Rural,HR Executive,121598,0 +78313,Female,44,Bachelors,1,5,16,99,5,2.0,6,46,Urban,Manager,33771,0 +78314,Female,36,High School,13,49,84,67,89,9.0,3,50,Urban,Software Engineer,51289,1 +78315,Female,47,High School,16,4,70,76,26,0.0,2,89,Urban,ML Engineer,91543,0 +78316,Male,43,Bachelors,0,74,84,80,31,3.0,6,94,Semi-Urban,Data Analyst,118273,1 +78317,Male,55,Masters,11,22,7,47,83,7.0,7,34,Rural,Software Engineer,136279,0 +78318,Other,33,Diploma,11,13,72,67,13,3.0,7,62,Rural,HR Executive,58041,0 +78319,Female,55,Diploma,3,50,26,92,82,5.0,1,20,Urban,ML Engineer,29425,0 +78320,Male,45,Masters,7,65,52,53,11,9.0,1,4,Semi-Urban,ML Engineer,95011,0 +78321,Male,54,Masters,8,39,92,44,37,3.0,3,89,Urban,Manager,144777,1 +78322,Female,43,Bachelors,4,62,74,15,77,1.0,0,40,Semi-Urban,Data Analyst,124015,0 +78323,Female,56,Masters,5,25,76,62,54,0.0,7,36,Rural,ML Engineer,27470,0 +78324,Male,25,High School,15,45,2,35,71,7.0,1,71,Rural,Manager,81811,0 +78325,Male,58,Masters,9,4,70,50,14,2.0,2,41,Urban,ML Engineer,94792,0 +78326,Female,35,High School,6,34,8,96,89,0.0,3,48,Urban,HR Executive,94333,0 +78327,Other,24,Bachelors,18,83,98,71,95,9.0,3,76,Urban,HR Executive,83952,1 +78328,Female,35,Diploma,6,75,74,65,57,3.0,6,53,Urban,HR Executive,62835,1 +78329,Female,24,Masters,12,73,66,93,0,7.0,1,9,Rural,Data Analyst,50490,1 +78330,Male,24,Bachelors,0,69,57,68,58,7.0,0,42,Urban,Software Engineer,65599,1 +78331,Male,47,Diploma,0,14,84,88,55,3.0,7,88,Urban,Manager,61764,1 +78332,Male,41,Diploma,12,8,25,82,17,4.0,5,3,Semi-Urban,ML Engineer,37539,0 +78333,Male,22,Bachelors,4,6,90,69,35,9.0,7,89,Rural,Software Engineer,136382,1 +78334,Male,52,Masters,10,51,22,72,23,4.0,5,77,Urban,ML Engineer,141138,0 +78335,Male,40,Diploma,8,40,28,7,41,3.0,3,11,Urban,HR Executive,93409,0 +78336,Male,36,Diploma,5,62,12,37,22,7.0,2,14,Urban,HR Executive,46831,0 +78337,Other,35,Bachelors,11,9,71,9,6,9.0,3,65,Semi-Urban,Manager,54481,0 +78338,Male,31,Diploma,10,58,26,29,27,1.0,1,82,Semi-Urban,ML Engineer,123675,0 +78339,Male,49,Bachelors,9,92,44,34,92,4.0,5,13,Rural,Software Engineer,136970,0 +78340,Male,54,Diploma,18,59,57,52,67,8.0,7,17,Urban,ML Engineer,121052,0 +78341,Male,30,Bachelors,9,67,6,36,48,3.0,0,80,Rural,Data Analyst,131673,0 +78342,Female,50,Bachelors,9,92,26,46,20,8.0,4,55,Rural,ML Engineer,44136,0 +78343,Male,46,Masters,14,40,47,49,15,2.0,5,34,Rural,Data Analyst,120084,0 +78344,Female,22,Bachelors,4,26,44,23,75,2.0,3,66,Urban,Manager,71523,0 +78345,Female,24,Diploma,18,64,32,62,93,9.0,3,8,Urban,Software Engineer,136680,0 +78346,Female,32,High School,4,45,9,36,82,7.0,0,75,Semi-Urban,HR Executive,64371,0 +78347,Male,53,Bachelors,0,66,15,66,89,0.0,5,56,Semi-Urban,Manager,27087,0 +78348,Female,36,Masters,14,0,35,31,57,0.0,4,29,Urban,HR Executive,118156,0 +78349,Male,22,Bachelors,0,84,59,21,59,3.0,7,82,Urban,HR Executive,71670,1 +78350,Female,45,Masters,9,85,13,58,37,0.0,6,56,Urban,Data Analyst,124947,0 +78351,Female,59,Diploma,6,48,37,1,26,9.0,3,4,Urban,ML Engineer,110494,0 +78352,Female,45,Diploma,12,55,51,16,87,8.0,5,17,Rural,Software Engineer,95555,0 +78353,Male,25,High School,11,21,77,29,92,5.0,5,34,Urban,HR Executive,92108,0 +78354,Male,25,PhD,13,75,95,92,77,2.0,6,13,Semi-Urban,HR Executive,105170,1 +78355,Male,31,Masters,12,12,82,75,44,1.0,7,70,Urban,ML Engineer,66557,1 +78356,Male,28,Masters,12,46,46,19,61,1.0,4,77,Semi-Urban,Manager,65660,0 +78357,Female,34,High School,3,50,29,32,35,7.0,3,80,Urban,Software Engineer,132820,0 +78358,Male,52,High School,10,20,41,61,8,7.0,1,55,Semi-Urban,Software Engineer,142494,0 +78359,Female,47,Diploma,14,9,37,80,82,6.0,0,35,Urban,HR Executive,128054,0 +78360,Male,42,Masters,19,86,67,51,33,1.0,2,86,Urban,Manager,81599,1 +78361,Female,45,Bachelors,12,81,59,54,23,1.0,7,86,Rural,Software Engineer,126181,1 +78362,Male,58,PhD,9,64,2,33,66,9.0,6,49,Semi-Urban,HR Executive,95033,0 +78363,Female,40,Masters,7,0,55,75,38,4.0,7,45,Urban,Manager,148414,0 +78364,Female,33,Bachelors,1,0,90,24,16,0.0,4,28,Urban,Manager,38600,0 +78365,Male,22,Bachelors,9,31,9,37,43,7.0,3,57,Semi-Urban,Manager,96098,0 +78366,Female,56,Bachelors,3,34,72,86,67,4.0,3,78,Urban,ML Engineer,104370,1 +78367,Female,45,Bachelors,18,76,89,9,82,8.0,0,3,Urban,Software Engineer,126423,0 +78368,Female,55,High School,2,34,15,43,52,3.0,6,60,Urban,Manager,29045,0 +78369,Female,40,Bachelors,16,59,78,24,58,1.0,3,82,Semi-Urban,Data Analyst,52960,1 +78370,Female,40,High School,15,91,70,71,58,5.0,2,74,Rural,Manager,106611,1 +78371,Male,43,Diploma,2,88,9,14,58,7.0,7,80,Rural,Data Analyst,82601,0 +78372,Male,26,High School,13,6,0,42,51,2.0,1,24,Urban,HR Executive,72004,0 +78373,Other,25,Bachelors,4,69,3,1,72,2.0,4,40,Urban,Data Analyst,60179,0 +78374,Female,56,Bachelors,9,51,52,15,42,5.0,1,2,Semi-Urban,Software Engineer,52338,0 +78375,Male,46,Diploma,15,97,72,71,61,2.0,1,91,Rural,HR Executive,98960,1 +78376,Male,48,Bachelors,14,16,22,15,74,8.0,3,92,Rural,Software Engineer,74090,0 +78377,Female,38,Bachelors,8,38,86,54,24,5.0,2,93,Urban,ML Engineer,105644,1 +78378,Female,46,Diploma,18,28,67,44,96,7.0,1,42,Urban,HR Executive,121863,0 +78379,Other,38,Bachelors,14,94,46,73,26,3.0,3,43,Rural,Data Analyst,82325,1 +78380,Male,52,PhD,11,94,9,82,16,0.0,3,66,Semi-Urban,Manager,71631,1 +78381,Male,51,Bachelors,18,74,7,43,88,6.0,7,7,Urban,Software Engineer,21406,0 +78382,Male,52,Diploma,12,12,85,11,25,0.0,7,41,Urban,Software Engineer,29404,0 +78383,Female,42,High School,7,83,13,0,19,3.0,5,28,Rural,Data Analyst,77214,0 +78384,Other,53,Diploma,4,65,33,10,23,8.0,2,58,Semi-Urban,Software Engineer,99346,0 +78385,Male,25,Bachelors,15,40,40,25,84,6.0,7,76,Urban,HR Executive,71466,0 +78386,Male,28,Diploma,8,15,60,35,42,0.0,7,68,Urban,Software Engineer,139506,0 +78387,Male,34,Diploma,9,32,16,98,24,0.0,6,38,Urban,Software Engineer,91079,0 +78388,Female,45,High School,10,4,81,17,10,0.0,5,20,Urban,ML Engineer,31656,0 +78389,Male,37,Diploma,3,81,3,73,58,4.0,1,62,Urban,Manager,77967,0 +78390,Female,31,Masters,7,70,17,76,55,7.0,3,92,Urban,Data Analyst,83539,1 +78391,Male,31,Masters,2,38,10,12,79,1.0,6,35,Rural,Data Analyst,53762,0 +78392,Male,53,High School,9,9,66,84,52,9.0,2,53,Urban,Manager,42080,0 +78393,Female,36,Bachelors,6,45,5,93,88,5.0,3,52,Semi-Urban,Manager,45429,0 +78394,Male,23,Masters,9,40,54,5,94,0.0,6,14,Semi-Urban,Data Analyst,93543,0 +78395,Male,42,High School,11,68,90,32,97,4.0,0,31,Urban,HR Executive,127231,0 +78396,Female,50,Bachelors,15,10,62,56,40,3.0,1,58,Semi-Urban,Data Analyst,59366,0 +78397,Male,21,Bachelors,18,22,25,19,71,7.0,1,44,Rural,Manager,138115,0 +78398,Female,28,Bachelors,19,62,19,96,66,9.0,5,21,Rural,Software Engineer,22320,0 +78399,Male,21,Bachelors,19,74,53,55,60,8.0,6,77,Urban,Data Analyst,132443,1 +78400,Male,29,Masters,17,44,89,2,36,7.0,4,85,Urban,ML Engineer,53266,0 +78401,Male,37,Diploma,15,95,51,61,70,2.0,2,35,Urban,Manager,32418,1 +78402,Male,49,Diploma,7,97,77,13,8,3.0,6,96,Rural,Manager,24701,1 +78403,Male,25,Diploma,10,8,37,32,66,7.0,3,22,Urban,Software Engineer,55793,0 +78404,Female,42,Masters,9,80,86,62,41,8.0,7,83,Rural,HR Executive,23363,1 +78405,Male,54,Masters,12,33,3,24,70,8.0,0,2,Urban,Software Engineer,131786,0 +78406,Male,44,Bachelors,14,62,37,92,76,0.0,3,85,Urban,ML Engineer,111776,1 +78407,Male,48,Diploma,16,91,84,5,75,8.0,5,60,Urban,ML Engineer,117781,1 +78408,Female,50,Diploma,2,2,1,56,42,2.0,2,63,Urban,Data Analyst,71735,0 +78409,Female,59,Masters,10,5,24,67,83,0.0,3,56,Rural,ML Engineer,89576,0 +78410,Female,51,Diploma,14,72,23,16,4,5.0,5,43,Rural,Manager,120549,0 +78411,Male,35,High School,17,13,42,79,21,7.0,4,56,Urban,Manager,108654,0 +78412,Male,59,Bachelors,3,80,14,50,60,6.0,5,84,Urban,Software Engineer,44134,0 +78413,Male,45,Bachelors,3,74,85,49,90,0.0,2,83,Rural,Software Engineer,55022,1 +78414,Male,34,Masters,1,98,21,17,48,0.0,6,81,Urban,HR Executive,28686,0 +78415,Female,41,Masters,0,71,12,47,92,8.0,4,47,Urban,Software Engineer,137865,0 +78416,Male,44,Diploma,8,5,47,86,4,0.0,5,53,Semi-Urban,Manager,64144,0 +78417,Male,42,Bachelors,12,77,66,15,92,4.0,6,65,Urban,Manager,82455,0 +78418,Male,40,Bachelors,5,25,98,46,55,4.0,1,44,Semi-Urban,Manager,32912,0 +78419,Male,31,Bachelors,5,52,39,40,97,9.0,5,29,Semi-Urban,Manager,137401,0 +78420,Female,52,High School,4,6,78,66,4,1.0,1,38,Urban,Manager,138403,0 +78421,Female,35,Diploma,9,22,3,63,95,0.0,5,52,Urban,HR Executive,80695,0 +78422,Male,27,Bachelors,11,14,33,84,35,8.0,7,24,Semi-Urban,Manager,25564,0 +78423,Female,41,Bachelors,14,99,81,4,59,5.0,2,35,Urban,HR Executive,41289,0 +78424,Male,25,Bachelors,0,46,68,31,17,3.0,1,93,Urban,Data Analyst,21815,1 +78425,Female,31,Bachelors,6,40,25,8,69,7.0,6,6,Urban,ML Engineer,102812,0 +78426,Male,49,Diploma,19,23,54,69,42,0.0,6,46,Rural,ML Engineer,148479,0 +78427,Male,30,Masters,18,94,2,57,86,8.0,4,88,Urban,Data Analyst,103399,1 +78428,Male,57,Bachelors,9,20,43,92,50,9.0,2,72,Urban,Software Engineer,25323,0 +78429,Female,53,Bachelors,6,23,46,69,59,4.0,7,36,Rural,Manager,61474,0 +78430,Male,48,PhD,2,81,71,66,73,3.0,7,76,Urban,Data Analyst,43401,1 +78431,Female,56,Bachelors,7,66,84,20,45,2.0,3,72,Urban,ML Engineer,42496,1 +78432,Male,36,High School,5,60,56,59,46,5.0,3,33,Semi-Urban,HR Executive,69325,0 +78433,Female,49,Diploma,4,56,28,39,69,4.0,2,68,Semi-Urban,HR Executive,141092,0 +78434,Male,58,Bachelors,14,73,55,49,35,5.0,0,9,Rural,Manager,45291,0 +78435,Female,27,PhD,2,17,63,75,11,6.0,4,23,Urban,Data Analyst,96433,0 +78436,Male,32,Diploma,16,11,38,45,1,4.0,7,22,Rural,Manager,95322,0 +78437,Female,45,Masters,17,19,85,16,59,2.0,1,73,Urban,ML Engineer,97279,0 +78438,Male,54,High School,7,87,19,54,68,3.0,7,36,Rural,Data Analyst,44243,0 +78439,Male,24,Bachelors,15,14,49,85,81,8.0,5,9,Semi-Urban,Manager,33615,0 +78440,Male,45,Diploma,8,62,34,58,7,5.0,5,44,Urban,HR Executive,109435,0 +78441,Other,27,Masters,11,99,44,97,54,7.0,6,13,Semi-Urban,HR Executive,108101,1 +78442,Male,51,Bachelors,17,55,37,98,13,1.0,2,69,Urban,ML Engineer,129305,1 +78443,Other,44,Diploma,8,1,29,79,57,2.0,3,41,Rural,ML Engineer,35936,0 +78444,Male,36,Masters,9,7,70,53,33,1.0,2,67,Urban,Software Engineer,56777,0 +78445,Male,34,Bachelors,5,19,30,93,54,8.0,7,42,Rural,HR Executive,48473,0 +78446,Male,59,Masters,3,84,78,85,1,8.0,1,41,Urban,Software Engineer,105717,1 +78447,Male,51,Masters,5,86,74,86,89,0.0,5,53,Urban,ML Engineer,87012,1 +78448,Female,34,Bachelors,19,16,58,68,44,0.0,6,43,Semi-Urban,Data Analyst,70132,0 +78449,Male,38,Bachelors,4,83,90,7,17,7.0,6,49,Urban,Data Analyst,26000,0 +78450,Male,22,Masters,1,25,78,48,42,6.0,5,64,Urban,ML Engineer,61316,0 +78451,Male,56,Bachelors,1,58,93,14,58,2.0,0,40,Urban,HR Executive,149670,0 +78452,Male,46,High School,8,26,81,77,81,3.0,7,45,Urban,HR Executive,132480,0 +78453,Female,59,Bachelors,3,29,78,42,97,1.0,7,14,Rural,HR Executive,46690,0 +78454,Male,42,Bachelors,15,24,31,87,89,1.0,6,79,Rural,Software Engineer,146189,0 +78455,Male,22,Bachelors,1,90,34,32,35,1.0,0,85,Urban,HR Executive,86980,1 +78456,Male,28,Diploma,18,17,43,0,71,4.0,3,12,Urban,HR Executive,82043,0 +78457,Female,35,Bachelors,1,22,70,92,11,7.0,7,49,Semi-Urban,Software Engineer,135518,0 +78458,Male,41,PhD,16,40,58,40,1,5.0,5,85,Semi-Urban,Software Engineer,41683,0 +78459,Other,31,Masters,0,68,91,61,54,3.0,4,91,Urban,ML Engineer,62077,1 +78460,Female,46,Diploma,12,30,72,31,71,0.0,7,47,Urban,ML Engineer,130777,0 +78461,Male,43,Bachelors,13,8,94,85,70,3.0,5,30,Urban,ML Engineer,74515,0 +78462,Female,36,Diploma,3,52,53,5,82,9.0,7,74,Urban,Manager,77133,0 +78463,Female,38,Bachelors,18,61,58,94,13,7.0,7,2,Urban,Software Engineer,69032,0 +78464,Female,33,Bachelors,6,18,58,76,92,0.0,6,42,Urban,ML Engineer,96130,0 +78465,Male,27,High School,19,45,67,44,9,6.0,6,51,Rural,Manager,148206,0 +78466,Other,46,Bachelors,1,30,98,62,32,0.0,7,81,Urban,Manager,44272,1 +78467,Male,26,Bachelors,5,20,60,57,41,1.0,1,13,Semi-Urban,Software Engineer,104334,0 +78468,Male,21,High School,14,79,69,39,91,6.0,3,73,Urban,Manager,77981,1 +78469,Male,58,High School,12,92,79,32,76,4.0,6,71,Rural,Software Engineer,22700,1 +78470,Male,40,Bachelors,11,35,10,17,72,0.0,2,38,Semi-Urban,HR Executive,113869,0 +78471,Male,42,Bachelors,3,34,52,16,49,7.0,3,51,Urban,HR Executive,128959,0 +78472,Female,40,Diploma,13,72,56,56,82,6.0,6,33,Urban,Manager,69603,0 +78473,Male,42,High School,0,66,64,65,44,3.0,0,17,Urban,Data Analyst,144134,0 +78474,Female,59,Bachelors,7,42,60,1,11,4.0,5,65,Urban,HR Executive,117118,0 +78475,Male,58,Diploma,15,75,83,79,58,4.0,2,44,Urban,HR Executive,33982,1 +78476,Male,36,Masters,10,58,21,74,10,8.0,0,21,Urban,ML Engineer,67455,0 +78477,Male,47,Bachelors,8,45,55,84,60,8.0,2,5,Urban,ML Engineer,78284,0 +78478,Female,33,High School,12,62,67,11,72,2.0,1,16,Rural,Software Engineer,113117,0 +78479,Male,51,Bachelors,5,2,18,7,51,4.0,3,64,Urban,HR Executive,78283,0 +78480,Female,26,Masters,8,14,29,89,90,5.0,4,52,Urban,Software Engineer,95945,0 +78481,Female,48,Bachelors,12,75,23,80,14,9.0,1,16,Urban,HR Executive,112651,0 +78482,Male,45,Masters,13,47,89,62,42,2.0,1,69,Urban,Data Analyst,131858,1 +78483,Male,24,Masters,19,55,39,81,13,1.0,7,49,Urban,Manager,44961,0 +78484,Male,29,PhD,3,75,95,42,87,4.0,3,44,Urban,Software Engineer,113860,1 +78485,Male,53,Masters,11,91,35,3,4,7.0,7,65,Rural,ML Engineer,37987,0 +78486,Male,22,Diploma,15,58,44,14,92,0.0,6,69,Rural,ML Engineer,68374,0 +78487,Male,25,Masters,2,91,31,0,6,9.0,5,14,Rural,Manager,87482,0 +78488,Female,42,High School,2,17,70,29,32,4.0,6,72,Urban,Manager,139755,0 +78489,Male,24,High School,6,42,53,9,66,6.0,6,33,Semi-Urban,ML Engineer,116900,0 +78490,Female,21,Masters,1,9,53,40,98,1.0,7,31,Rural,Manager,125063,0 +78491,Female,42,Masters,0,15,95,91,73,1.0,7,86,Urban,Manager,132080,1 +78492,Female,35,Bachelors,12,60,41,60,48,5.0,4,10,Urban,Manager,97244,0 +78493,Female,40,Bachelors,2,63,72,99,94,9.0,3,16,Urban,Software Engineer,27084,1 +78494,Male,39,Masters,3,73,24,30,98,0.0,1,68,Rural,HR Executive,26211,0 +78495,Female,38,Bachelors,17,3,1,17,21,5.0,7,92,Urban,HR Executive,136512,0 +78496,Male,34,Bachelors,2,36,51,64,75,8.0,3,27,Urban,Data Analyst,130398,0 +78497,Female,35,Bachelors,15,48,77,13,55,5.0,5,70,Urban,Manager,132157,0 +78498,Male,39,Masters,17,31,0,61,40,5.0,2,32,Semi-Urban,Data Analyst,85539,0 +78499,Other,27,Masters,9,19,36,19,24,4.0,1,24,Urban,Data Analyst,148556,0 +78500,Female,58,Bachelors,2,17,11,58,17,9.0,5,19,Semi-Urban,HR Executive,121870,0 +78501,Female,21,Bachelors,19,1,97,86,80,6.0,3,84,Urban,Software Engineer,100111,1 +78502,Male,45,Bachelors,4,38,85,73,47,8.0,7,76,Urban,ML Engineer,60084,1 +78503,Male,49,High School,16,92,84,87,92,5.0,1,9,Urban,Manager,48357,1 +78504,Male,55,Diploma,5,84,58,16,0,5.0,7,76,Urban,Manager,81741,0 +78505,Female,50,PhD,17,72,26,67,78,1.0,4,6,Urban,Manager,60012,0 +78506,Female,46,High School,5,47,13,43,59,8.0,7,13,Semi-Urban,ML Engineer,129126,0 +78507,Male,30,Diploma,11,73,91,25,70,0.0,7,72,Urban,Software Engineer,142849,1 +78508,Male,38,Masters,15,20,86,75,88,8.0,7,74,Semi-Urban,Data Analyst,123141,1 +78509,Male,52,Masters,17,9,31,80,72,7.0,0,22,Semi-Urban,Software Engineer,32049,0 +78510,Female,53,High School,16,56,41,84,9,2.0,7,71,Semi-Urban,Manager,79268,1 +78511,Male,39,Masters,7,30,48,94,3,2.0,7,95,Urban,Manager,113442,1 +78512,Male,59,High School,19,99,62,92,98,1.0,7,32,Urban,Manager,134204,1 +78513,Male,39,PhD,0,21,64,8,25,5.0,0,98,Urban,Manager,125667,0 +78514,Male,56,High School,9,22,30,17,55,5.0,7,34,Urban,HR Executive,57253,0 +78515,Female,47,Bachelors,13,87,67,93,10,2.0,2,26,Semi-Urban,HR Executive,50363,1 +78516,Female,58,Bachelors,3,69,67,48,85,5.0,4,77,Urban,Data Analyst,73252,1 +78517,Female,48,Masters,18,55,41,72,58,4.0,2,16,Urban,Manager,31513,0 +78518,Female,59,High School,6,72,93,70,93,1.0,4,86,Semi-Urban,HR Executive,21433,1 +78519,Male,40,Bachelors,6,65,78,6,80,3.0,2,4,Urban,ML Engineer,142936,0 +78520,Male,51,Diploma,15,61,83,50,82,5.0,1,25,Semi-Urban,Manager,130535,0 +78521,Male,50,High School,14,11,8,68,27,8.0,1,4,Urban,HR Executive,144572,0 +78522,Male,35,High School,10,98,67,35,88,1.0,6,91,Urban,HR Executive,135038,1 +78523,Female,30,Diploma,10,36,97,75,90,2.0,6,37,Urban,HR Executive,70471,1 +78524,Female,35,Bachelors,6,71,20,87,89,0.0,3,85,Urban,Data Analyst,105285,1 +78525,Female,34,Bachelors,9,80,30,21,19,3.0,4,44,Urban,HR Executive,89428,0 +78526,Male,31,Bachelors,9,97,2,41,28,9.0,5,69,Urban,Software Engineer,85222,0 +78527,Male,24,Bachelors,9,72,41,75,19,6.0,5,44,Rural,Manager,29472,0 +78528,Male,47,Bachelors,9,80,81,75,68,1.0,5,28,Urban,ML Engineer,57874,1 +78529,Male,38,Diploma,16,51,53,93,63,8.0,0,4,Urban,Data Analyst,38085,0 +78530,Male,28,High School,16,81,17,43,87,2.0,3,14,Urban,ML Engineer,105888,0 +78531,Male,51,Masters,11,7,54,66,11,2.0,1,51,Urban,Software Engineer,114664,0 +78532,Male,39,Bachelors,2,97,29,76,48,6.0,5,22,Urban,Data Analyst,119892,0 +78533,Female,21,Bachelors,1,36,94,74,60,4.0,6,3,Semi-Urban,Software Engineer,126672,0 +78534,Other,39,Bachelors,9,71,28,21,54,0.0,0,39,Urban,Data Analyst,135612,0 +78535,Female,34,High School,1,1,4,94,84,0.0,7,76,Urban,Manager,69323,0 +78536,Male,26,Bachelors,9,82,65,61,42,0.0,5,91,Semi-Urban,HR Executive,24382,1 +78537,Other,34,PhD,16,25,11,6,59,0.0,5,33,Urban,Data Analyst,76696,0 +78538,Male,56,Masters,17,8,45,41,33,4.0,0,23,Urban,Data Analyst,116609,0 +78539,Female,59,Bachelors,15,87,33,22,71,6.0,2,30,Rural,Data Analyst,138626,0 +78540,Male,45,PhD,14,30,1,23,64,5.0,7,23,Rural,Manager,118669,0 +78541,Male,37,Bachelors,2,13,64,10,79,9.0,4,78,Semi-Urban,Manager,132431,0 +78542,Male,29,Masters,3,19,24,10,93,9.0,6,21,Semi-Urban,HR Executive,78309,0 +78543,Female,34,Bachelors,2,62,84,32,34,1.0,0,29,Urban,HR Executive,29723,0 +78544,Female,44,High School,0,33,90,16,27,3.0,3,73,Rural,Data Analyst,22755,0 +78545,Male,50,Diploma,10,54,83,28,80,0.0,6,40,Urban,Software Engineer,132580,0 +78546,Male,48,Bachelors,0,86,74,34,14,3.0,5,15,Urban,ML Engineer,35926,0 +78547,Male,34,PhD,11,36,81,15,84,0.0,3,81,Urban,HR Executive,89514,0 +78548,Male,40,Diploma,17,70,28,19,76,6.0,7,45,Urban,ML Engineer,87107,0 +78549,Male,56,Bachelors,5,43,75,31,1,8.0,4,10,Rural,HR Executive,77705,0 +78550,Male,49,High School,1,95,55,14,43,2.0,7,21,Urban,Manager,32420,0 +78551,Female,36,Diploma,11,42,62,41,31,7.0,4,97,Urban,Manager,148549,1 +78552,Male,33,Masters,4,97,36,45,12,0.0,3,82,Urban,Data Analyst,124521,1 +78553,Male,54,Bachelors,3,6,44,7,7,2.0,0,49,Rural,Software Engineer,61407,0 +78554,Female,26,Bachelors,4,69,46,25,70,5.0,5,5,Semi-Urban,Manager,139294,0 +78555,Male,35,Bachelors,5,77,80,54,33,5.0,4,44,Urban,HR Executive,104505,1 +78556,Female,52,Masters,19,64,1,31,99,1.0,3,83,Rural,Manager,90378,0 +78557,Male,50,Bachelors,8,75,62,11,75,0.0,3,67,Semi-Urban,HR Executive,70560,0 +78558,Female,21,Diploma,1,68,33,16,61,3.0,6,92,Urban,ML Engineer,77337,0 +78559,Male,34,High School,11,40,55,11,99,8.0,7,89,Rural,Data Analyst,102755,0 +78560,Male,59,Masters,9,60,2,83,49,0.0,2,36,Urban,Manager,36452,0 +78561,Male,32,Bachelors,10,56,34,0,0,4.0,1,57,Semi-Urban,Data Analyst,43490,0 +78562,Male,50,Diploma,15,29,99,69,27,1.0,1,44,Semi-Urban,Manager,36699,1 +78563,Female,46,Diploma,1,99,90,68,94,5.0,4,18,Urban,ML Engineer,147993,1 +78564,Female,56,High School,18,25,78,27,71,4.0,2,77,Urban,ML Engineer,81806,0 +78565,Male,37,Bachelors,1,32,45,82,56,7.0,3,33,Urban,ML Engineer,52162,0 +78566,Female,57,Bachelors,13,56,92,96,7,4.0,3,35,Urban,Manager,35020,1 +78567,Female,23,Diploma,0,20,15,64,40,9.0,5,43,Rural,Data Analyst,21134,0 +78568,Female,25,Diploma,5,31,63,75,98,4.0,0,60,Semi-Urban,Manager,90653,0 +78569,Male,44,Bachelors,5,84,97,71,7,6.0,7,5,Rural,HR Executive,33831,1 +78570,Male,41,Diploma,5,87,97,80,51,8.0,1,46,Urban,ML Engineer,48953,1 +78571,Female,59,Diploma,13,32,45,83,57,0.0,4,38,Rural,ML Engineer,144789,0 +78572,Female,24,Bachelors,15,26,54,46,78,1.0,0,99,Urban,Data Analyst,50376,0 +78573,Male,37,Diploma,1,84,93,73,28,1.0,3,18,Rural,ML Engineer,140205,1 +78574,Male,52,PhD,7,15,33,23,1,2.0,2,58,Urban,Software Engineer,70605,0 +78575,Female,55,Bachelors,18,98,11,0,25,2.0,4,96,Urban,Software Engineer,104282,0 +78576,Male,41,Bachelors,5,56,24,33,65,1.0,1,55,Urban,Data Analyst,78421,0 +78577,Male,59,Diploma,17,20,52,91,28,7.0,6,39,Urban,HR Executive,119122,0 +78578,Female,41,Bachelors,8,36,89,99,73,9.0,0,63,Rural,Data Analyst,82818,1 +78579,Male,54,Bachelors,13,77,67,12,37,9.0,5,92,Semi-Urban,Software Engineer,110907,1 +78580,Other,33,Bachelors,4,94,75,55,78,0.0,7,63,Rural,Data Analyst,138222,1 +78581,Male,41,Bachelors,10,46,47,17,89,7.0,0,76,Urban,Data Analyst,87990,0 +78582,Male,52,Bachelors,7,26,77,79,55,9.0,2,94,Urban,Manager,95327,1 +78583,Male,37,Bachelors,14,87,61,2,98,3.0,6,43,Urban,HR Executive,94664,0 +78584,Male,43,Masters,10,63,75,14,61,2.0,2,88,Rural,Data Analyst,63687,1 +78585,Male,39,Masters,9,84,19,85,20,8.0,1,26,Urban,ML Engineer,58203,0 +78586,Female,42,Masters,14,57,47,59,54,3.0,0,19,Semi-Urban,Manager,57898,0 +78587,Male,21,Masters,11,97,30,48,32,9.0,7,75,Semi-Urban,Software Engineer,117090,1 +78588,Female,47,Bachelors,6,4,77,83,13,2.0,6,20,Urban,Data Analyst,116979,0 +78589,Male,30,PhD,13,35,36,7,2,4.0,0,32,Urban,Manager,136368,0 +78590,Male,58,Diploma,10,89,53,39,62,7.0,2,32,Urban,Manager,124468,0 +78591,Female,23,Bachelors,7,4,32,94,27,7.0,6,24,Urban,Manager,59827,0 +78592,Female,39,Bachelors,11,46,80,75,85,3.0,7,43,Urban,ML Engineer,135972,1 +78593,Male,48,Bachelors,4,12,88,85,3,7.0,0,58,Urban,HR Executive,132541,1 +78594,Male,47,Bachelors,6,40,70,93,60,6.0,2,31,Urban,Data Analyst,115217,0 +78595,Male,27,Bachelors,4,50,60,3,62,4.0,7,79,Semi-Urban,Manager,90312,0 +78596,Female,28,Masters,2,87,27,35,85,1.0,7,72,Urban,Data Analyst,123255,0 +78597,Male,26,Bachelors,7,58,0,33,73,2.0,7,0,Rural,ML Engineer,41942,0 +78598,Male,36,Bachelors,11,68,86,89,28,6.0,6,85,Rural,HR Executive,76232,1 +78599,Male,55,Masters,16,45,65,79,13,3.0,3,4,Urban,Data Analyst,22895,0 +78600,Male,35,Diploma,14,38,12,8,80,3.0,1,28,Rural,Manager,134497,0 +78601,Other,50,Bachelors,14,63,86,28,60,0.0,6,97,Urban,Data Analyst,95453,1 +78602,Male,30,Masters,5,40,32,66,86,9.0,7,64,Rural,Data Analyst,32157,0 +78603,Male,41,Bachelors,11,21,34,0,94,1.0,1,26,Rural,ML Engineer,144448,0 +78604,Male,49,Diploma,7,87,98,19,23,4.0,1,80,Semi-Urban,Data Analyst,88708,1 +78605,Female,25,Bachelors,2,10,50,70,71,4.0,1,92,Urban,HR Executive,139083,0 +78606,Female,41,Masters,15,40,22,47,89,9.0,3,62,Urban,HR Executive,63956,0 +78607,Female,23,Bachelors,2,25,60,52,95,9.0,5,57,Rural,ML Engineer,127454,0 +78608,Male,50,Masters,16,26,87,43,97,7.0,6,72,Urban,HR Executive,41953,0 +78609,Male,36,Masters,14,24,16,54,52,9.0,1,67,Rural,Data Analyst,122678,0 +78610,Male,29,High School,0,82,12,88,8,8.0,6,40,Urban,Software Engineer,130456,0 +78611,Female,25,Masters,11,20,0,80,47,6.0,6,62,Rural,Software Engineer,56733,0 +78612,Male,24,PhD,19,19,54,30,96,9.0,2,8,Urban,Software Engineer,65736,0 +78613,Male,34,Bachelors,9,94,50,76,12,2.0,0,89,Rural,Data Analyst,115927,1 +78614,Male,51,Diploma,10,86,61,29,21,0.0,2,16,Rural,Manager,46085,0 +78615,Male,40,Diploma,0,5,52,57,81,6.0,0,63,Urban,HR Executive,46969,0 +78616,Male,31,High School,15,12,94,66,86,9.0,5,7,Rural,Data Analyst,138353,0 +78617,Female,23,Masters,10,22,28,47,49,4.0,3,55,Semi-Urban,Data Analyst,43513,0 +78618,Female,26,Bachelors,14,58,38,11,9,3.0,7,32,Urban,HR Executive,33370,0 +78619,Other,54,Diploma,11,92,44,75,92,8.0,3,20,Urban,Software Engineer,135569,0 +78620,Male,59,Diploma,5,69,87,78,23,6.0,7,18,Urban,Software Engineer,141496,1 +78621,Male,57,Bachelors,17,9,79,28,97,2.0,2,21,Urban,ML Engineer,23504,0 +78622,Male,24,High School,9,32,15,56,50,7.0,6,1,Urban,Data Analyst,81124,0 +78623,Male,38,Bachelors,15,30,16,74,60,5.0,0,18,Urban,ML Engineer,91100,0 +78624,Female,36,Masters,19,16,13,17,88,3.0,4,87,Rural,Data Analyst,140779,0 +78625,Male,55,PhD,3,66,28,9,2,7.0,7,68,Urban,Data Analyst,86644,0 +78626,Male,30,Masters,9,54,12,82,9,6.0,6,34,Urban,Data Analyst,75886,0 +78627,Male,21,Bachelors,6,33,69,87,99,9.0,2,99,Rural,HR Executive,78025,1 +78628,Male,56,Bachelors,11,33,57,77,39,4.0,0,15,Urban,Software Engineer,42684,0 +78629,Male,57,Bachelors,3,40,8,57,13,6.0,7,41,Urban,HR Executive,87447,0 +78630,Male,31,Bachelors,9,15,74,58,8,1.0,2,47,Semi-Urban,HR Executive,81058,0 +78631,Female,23,PhD,0,20,56,42,51,3.0,4,99,Semi-Urban,Software Engineer,106616,0 +78632,Female,59,PhD,6,60,22,72,3,9.0,5,92,Urban,Data Analyst,143726,1 +78633,Female,42,High School,15,20,31,51,48,4.0,4,96,Semi-Urban,ML Engineer,117470,0 +78634,Male,52,Bachelors,11,88,35,8,97,2.0,0,9,Urban,Manager,140314,0 +78635,Female,56,Diploma,10,39,99,22,7,1.0,2,20,Urban,Data Analyst,146035,0 +78636,Male,25,Diploma,0,17,69,35,53,4.0,4,59,Urban,Manager,118070,0 +78637,Male,23,High School,10,41,50,65,88,4.0,7,60,Urban,HR Executive,111509,0 +78638,Female,27,Bachelors,0,46,19,28,52,9.0,5,6,Rural,Manager,62348,0 +78639,Male,46,Masters,0,7,32,49,17,0.0,1,64,Urban,Software Engineer,44232,0 +78640,Male,35,Bachelors,8,34,54,82,6,1.0,0,19,Semi-Urban,Data Analyst,67893,0 +78641,Male,28,High School,17,32,28,10,82,1.0,7,46,Urban,ML Engineer,73562,0 +78642,Female,51,Bachelors,1,42,97,38,85,9.0,0,39,Semi-Urban,Manager,27154,0 +78643,Male,57,Masters,13,31,77,87,90,3.0,2,36,Urban,Software Engineer,138441,0 +78644,Male,39,Bachelors,12,17,47,45,7,6.0,4,39,Urban,Data Analyst,134608,0 +78645,Male,30,Bachelors,7,98,41,85,60,6.0,2,1,Urban,HR Executive,23141,0 +78646,Male,32,Bachelors,13,35,45,70,94,3.0,4,21,Urban,ML Engineer,142778,0 +78647,Male,33,Diploma,1,62,87,30,55,8.0,6,96,Urban,HR Executive,36842,1 +78648,Male,24,Diploma,0,69,85,36,38,9.0,3,9,Semi-Urban,ML Engineer,39868,0 +78649,Female,58,Bachelors,9,35,40,65,87,8.0,2,8,Rural,ML Engineer,148808,0 +78650,Female,57,Bachelors,0,20,60,81,28,6.0,4,24,Urban,HR Executive,94877,0 +78651,Female,40,Diploma,14,39,88,28,91,4.0,2,30,Urban,Data Analyst,138454,0 +78652,Other,55,Bachelors,9,40,78,85,12,3.0,0,12,Rural,HR Executive,123464,0 +78653,Female,42,Bachelors,2,95,23,71,62,0.0,0,37,Urban,Software Engineer,105334,0 +78654,Female,48,Bachelors,2,57,15,66,94,1.0,4,20,Semi-Urban,Manager,52594,0 +78655,Male,34,Bachelors,19,28,26,97,79,4.0,4,93,Urban,HR Executive,85586,1 +78656,Male,54,Bachelors,0,51,51,80,89,8.0,1,56,Rural,ML Engineer,59166,1 +78657,Male,59,Bachelors,16,56,55,65,0,9.0,5,99,Urban,Data Analyst,109368,1 +78658,Male,33,Masters,14,25,31,79,74,8.0,5,60,Urban,ML Engineer,78511,0 +78659,Male,41,Bachelors,17,41,54,25,63,2.0,4,38,Semi-Urban,Data Analyst,27212,0 +78660,Female,31,Diploma,3,30,78,16,78,5.0,6,81,Rural,ML Engineer,37837,0 +78661,Female,54,High School,18,76,78,96,99,9.0,6,10,Urban,Manager,25562,1 +78662,Male,57,Bachelors,12,34,92,64,46,7.0,2,98,Rural,Software Engineer,101795,1 +78663,Male,51,Bachelors,16,40,62,84,44,4.0,2,7,Urban,Software Engineer,82990,0 +78664,Male,39,Diploma,1,60,1,59,52,7.0,2,64,Urban,Manager,113408,0 +78665,Other,43,Masters,11,62,96,52,54,2.0,4,6,Semi-Urban,Data Analyst,141676,0 +78666,Female,44,High School,18,76,89,40,29,7.0,7,2,Urban,Data Analyst,148786,0 +78667,Male,59,Bachelors,1,53,7,84,80,1.0,7,0,Semi-Urban,ML Engineer,110805,0 +78668,Female,24,High School,8,96,61,86,78,1.0,7,2,Urban,Data Analyst,112371,1 +78669,Male,51,Bachelors,18,92,55,83,22,1.0,7,43,Rural,Software Engineer,47816,1 +78670,Male,38,Masters,13,95,4,98,20,6.0,6,48,Rural,Manager,111105,1 +78671,Female,30,High School,15,27,1,57,79,3.0,1,88,Semi-Urban,ML Engineer,119939,0 +78672,Female,49,Masters,12,18,21,40,34,9.0,1,48,Rural,Data Analyst,100752,0 +78673,Male,56,Bachelors,13,7,92,98,39,2.0,6,1,Rural,ML Engineer,78727,0 +78674,Male,47,High School,0,88,13,45,33,5.0,4,35,Urban,Data Analyst,94114,0 +78675,Male,30,High School,12,45,89,70,7,2.0,0,45,Urban,Software Engineer,110203,1 +78676,Male,57,Bachelors,0,96,22,94,89,6.0,5,22,Rural,Software Engineer,23184,0 +78677,Female,36,High School,2,70,11,98,81,7.0,4,1,Semi-Urban,ML Engineer,20677,0 +78678,Female,48,Masters,15,26,57,27,51,0.0,0,40,Semi-Urban,HR Executive,122460,0 +78679,Female,43,High School,16,94,36,98,84,4.0,0,24,Semi-Urban,Software Engineer,125736,1 +78680,Male,53,Diploma,19,63,49,27,62,6.0,7,11,Urban,Manager,70474,0 +78681,Female,27,Bachelors,16,14,6,35,6,1.0,1,46,Urban,Manager,30834,0 +78682,Male,27,Diploma,11,59,29,61,39,8.0,5,87,Semi-Urban,Manager,67900,1 +78683,Female,43,High School,18,87,72,47,98,7.0,5,36,Urban,HR Executive,100725,1 +78684,Male,23,High School,13,28,17,17,87,5.0,4,48,Urban,ML Engineer,105619,0 +78685,Male,28,Bachelors,18,94,42,43,4,6.0,6,57,Rural,ML Engineer,80520,1 +78686,Male,46,Bachelors,6,63,37,87,13,6.0,7,25,Urban,HR Executive,97221,0 +78687,Male,58,Bachelors,11,33,23,88,50,0.0,4,19,Urban,Manager,112856,0 +78688,Female,36,Bachelors,9,64,2,58,21,3.0,1,72,Urban,ML Engineer,90024,0 +78689,Female,26,Bachelors,14,34,62,55,15,1.0,7,30,Semi-Urban,Software Engineer,61538,0 +78690,Female,42,Bachelors,5,2,41,67,31,2.0,6,63,Semi-Urban,HR Executive,79659,0 +78691,Male,55,Bachelors,18,50,99,28,65,0.0,2,65,Rural,Data Analyst,131164,1 +78692,Female,52,Diploma,6,63,14,23,31,3.0,5,96,Semi-Urban,Software Engineer,105232,0 +78693,Male,52,Bachelors,19,35,64,21,57,2.0,4,2,Urban,ML Engineer,120681,0 +78694,Male,45,PhD,11,54,37,71,63,6.0,0,83,Urban,HR Executive,78452,1 +78695,Male,39,Bachelors,17,35,43,63,68,8.0,6,83,Rural,Manager,65985,0 +78696,Female,26,Bachelors,4,73,69,55,49,7.0,1,83,Semi-Urban,ML Engineer,21174,1 +78697,Male,44,Diploma,11,33,0,55,59,3.0,2,84,Rural,Data Analyst,91066,0 +78698,Female,48,Diploma,8,56,38,82,11,8.0,2,29,Urban,Manager,43095,0 +78699,Female,24,Masters,7,53,15,21,44,0.0,4,55,Rural,HR Executive,22999,0 +78700,Male,42,High School,9,45,62,60,70,5.0,1,14,Rural,ML Engineer,149770,0 +78701,Other,36,Bachelors,4,93,33,73,74,0.0,4,74,Rural,HR Executive,61682,1 +78702,Other,31,High School,0,38,37,90,16,2.0,6,24,Urban,Data Analyst,72931,0 +78703,Female,22,Masters,7,40,98,81,4,9.0,3,24,Urban,ML Engineer,46695,1 +78704,Male,54,High School,8,23,41,32,82,5.0,6,39,Rural,Data Analyst,78172,0 +78705,Male,35,Diploma,5,55,92,80,14,4.0,6,5,Semi-Urban,ML Engineer,36751,0 +78706,Male,48,Bachelors,12,88,39,94,56,4.0,5,3,Urban,HR Executive,114707,0 +78707,Male,55,Bachelors,2,78,34,59,62,1.0,4,32,Urban,Manager,117475,0 +78708,Female,33,Bachelors,0,48,65,59,27,2.0,4,74,Urban,Software Engineer,59970,1 +78709,Male,43,Diploma,12,27,8,65,87,8.0,6,98,Rural,Manager,42019,0 +78710,Male,37,High School,0,80,16,48,14,3.0,2,8,Urban,HR Executive,95528,0 +78711,Male,39,High School,19,4,98,34,9,8.0,2,29,Urban,HR Executive,106384,0 +78712,Male,21,Diploma,7,95,46,88,49,6.0,0,32,Urban,HR Executive,139060,1 +78713,Other,29,High School,18,47,26,74,99,5.0,0,18,Rural,HR Executive,100239,0 +78714,Female,39,Bachelors,9,55,66,36,7,9.0,5,85,Semi-Urban,Manager,62773,1 +78715,Female,59,Bachelors,0,91,72,46,96,3.0,2,69,Urban,Data Analyst,143750,1 +78716,Male,44,Diploma,11,2,88,30,73,3.0,2,22,Semi-Urban,Software Engineer,82845,0 +78717,Female,23,Diploma,17,14,38,71,92,1.0,7,53,Semi-Urban,Software Engineer,141672,0 +78718,Female,43,Diploma,18,77,70,70,89,4.0,1,48,Urban,Data Analyst,114482,1 +78719,Male,51,High School,1,26,83,3,92,4.0,4,56,Semi-Urban,Manager,63887,0 +78720,Female,29,Bachelors,16,23,3,50,61,0.0,3,17,Semi-Urban,HR Executive,142120,0 +78721,Female,37,Diploma,14,69,55,19,89,3.0,3,21,Urban,Software Engineer,140678,0 +78722,Male,49,Diploma,10,98,82,82,19,5.0,3,77,Semi-Urban,Data Analyst,147751,1 +78723,Male,57,Bachelors,13,19,28,29,56,3.0,4,47,Urban,HR Executive,122331,0 +78724,Other,28,Masters,16,72,88,98,6,8.0,7,81,Semi-Urban,HR Executive,140777,1 +78725,Female,28,Masters,9,45,92,26,23,6.0,5,76,Urban,HR Executive,50087,0 +78726,Female,31,Bachelors,2,46,8,44,79,4.0,6,71,Semi-Urban,Data Analyst,69710,0 +78727,Male,29,Masters,14,82,38,86,60,0.0,5,39,Urban,HR Executive,100117,1 +78728,Male,31,Diploma,3,26,71,37,99,1.0,4,55,Urban,Software Engineer,55704,0 +78729,Female,23,Diploma,17,54,86,7,93,0.0,0,3,Semi-Urban,Data Analyst,68354,0 +78730,Male,39,Diploma,13,40,26,78,24,4.0,5,10,Rural,Manager,130372,0 +78731,Other,54,Bachelors,16,58,17,64,74,7.0,2,65,Urban,HR Executive,31357,0 +78732,Female,22,Diploma,13,83,13,69,27,5.0,7,80,Urban,Data Analyst,120947,1 +78733,Male,48,Bachelors,0,60,40,59,82,2.0,0,41,Rural,Manager,139161,0 +78734,Male,40,Bachelors,10,64,21,59,95,1.0,5,27,Urban,HR Executive,113259,0 +78735,Male,43,Diploma,18,7,91,88,28,3.0,6,51,Urban,Software Engineer,63309,1 +78736,Male,35,Masters,2,34,12,39,50,2.0,7,60,Urban,HR Executive,48720,0 +78737,Male,53,Masters,14,11,76,94,1,3.0,2,68,Urban,HR Executive,129372,1 +78738,Male,31,Masters,0,91,61,15,20,6.0,1,11,Urban,Software Engineer,68436,0 +78739,Female,46,High School,2,9,31,44,58,6.0,2,0,Urban,Manager,81625,0 +78740,Male,58,Bachelors,15,0,70,20,72,3.0,0,13,Rural,ML Engineer,90930,0 +78741,Male,38,Bachelors,2,92,57,11,10,0.0,6,69,Urban,Software Engineer,104813,0 +78742,Male,22,Masters,16,87,77,63,96,0.0,1,13,Rural,Software Engineer,79933,1 +78743,Other,51,Bachelors,18,79,42,85,74,2.0,2,94,Urban,HR Executive,53328,1 +78744,Male,42,Bachelors,17,52,38,89,53,9.0,4,65,Urban,Manager,74191,1 +78745,Male,42,Bachelors,3,31,54,31,90,9.0,5,9,Urban,Manager,74082,0 +78746,Female,30,Bachelors,13,22,30,54,89,8.0,7,14,Urban,ML Engineer,124058,0 +78747,Male,58,Bachelors,3,83,46,42,34,4.0,3,24,Semi-Urban,Manager,62165,0 +78748,Male,21,PhD,13,4,5,38,33,6.0,2,66,Urban,Data Analyst,70649,0 +78749,Female,34,Bachelors,8,88,17,6,31,9.0,1,11,Urban,Data Analyst,74785,0 +78750,Male,22,Bachelors,15,65,59,94,1,6.0,2,38,Rural,ML Engineer,46885,1 +78751,Male,22,Masters,11,34,5,48,73,1.0,1,67,Urban,Data Analyst,94018,0 +78752,Male,27,PhD,5,8,87,53,72,9.0,3,10,Urban,HR Executive,32548,0 +78753,Male,23,Diploma,6,24,37,97,72,5.0,4,49,Rural,Software Engineer,23902,0 +78754,Female,29,PhD,17,35,19,72,64,8.0,4,0,Semi-Urban,Manager,115767,0 +78755,Male,42,Bachelors,9,71,85,2,65,2.0,3,56,Urban,HR Executive,50757,0 +78756,Male,42,Diploma,17,40,51,54,12,2.0,0,80,Urban,Manager,111407,0 +78757,Male,41,Bachelors,2,76,62,30,29,6.0,2,15,Urban,HR Executive,90569,0 +78758,Male,56,Masters,11,84,98,10,40,8.0,1,66,Rural,Software Engineer,44940,1 +78759,Male,36,High School,3,31,59,53,1,4.0,3,68,Urban,Manager,68482,0 +78760,Male,59,Bachelors,13,57,12,89,92,8.0,0,64,Rural,Manager,132679,0 +78761,Male,42,Diploma,17,16,43,94,72,9.0,7,59,Urban,Data Analyst,90818,0 +78762,Male,55,Masters,5,99,98,86,9,2.0,4,79,Urban,ML Engineer,58190,1 +78763,Female,34,Diploma,9,18,69,14,65,4.0,3,2,Urban,HR Executive,75700,0 +78764,Female,56,Bachelors,4,63,90,22,89,0.0,5,1,Semi-Urban,HR Executive,62033,0 +78765,Female,45,Bachelors,11,92,81,58,55,9.0,7,74,Urban,Data Analyst,119911,1 +78766,Male,59,Masters,14,98,50,21,63,0.0,3,35,Rural,ML Engineer,59908,0 +78767,Male,31,Diploma,3,21,76,91,67,4.0,6,28,Urban,Manager,104097,0 +78768,Male,54,Diploma,16,24,35,29,82,9.0,3,58,Rural,Data Analyst,50399,0 +78769,Male,57,Bachelors,0,64,97,94,29,5.0,4,33,Urban,HR Executive,143556,1 +78770,Male,26,High School,17,21,85,74,69,7.0,7,97,Urban,HR Executive,86197,1 +78771,Other,40,Diploma,14,24,21,7,31,3.0,1,49,Semi-Urban,Data Analyst,101642,0 +78772,Female,57,Bachelors,12,15,11,98,58,4.0,5,25,Urban,Data Analyst,149515,0 +78773,Male,50,Bachelors,10,24,21,59,36,2.0,3,13,Urban,HR Executive,40289,0 +78774,Male,54,Bachelors,11,37,97,8,40,2.0,7,73,Semi-Urban,HR Executive,121957,0 +78775,Male,35,Bachelors,12,8,29,77,16,9.0,2,36,Urban,Software Engineer,110304,0 +78776,Male,50,High School,6,59,30,64,28,9.0,4,64,Rural,HR Executive,140846,0 +78777,Male,22,Diploma,15,67,71,61,4,1.0,4,85,Urban,HR Executive,147046,1 +78778,Male,47,High School,3,22,86,25,63,1.0,7,32,Urban,HR Executive,118419,0 +78779,Male,53,High School,16,27,68,89,72,6.0,3,92,Urban,HR Executive,138440,1 +78780,Female,24,Bachelors,7,26,52,29,8,7.0,7,81,Urban,ML Engineer,144218,0 +78781,Male,48,Diploma,13,35,52,94,28,2.0,5,37,Urban,HR Executive,63630,0 +78782,Male,40,Masters,2,86,3,54,21,0.0,7,23,Semi-Urban,Manager,79073,0 +78783,Male,34,Bachelors,10,8,37,77,47,7.0,2,96,Semi-Urban,ML Engineer,34856,0 +78784,Male,21,Bachelors,19,43,66,97,37,1.0,1,2,Rural,Software Engineer,26253,0 +78785,Male,32,Diploma,0,67,45,33,66,1.0,7,44,Urban,Data Analyst,41083,0 +78786,Male,27,Diploma,13,43,96,83,52,8.0,2,24,Urban,HR Executive,20247,1 +78787,Female,52,Bachelors,6,32,41,91,93,1.0,2,81,Semi-Urban,ML Engineer,63891,1 +78788,Male,35,Bachelors,11,72,79,23,22,3.0,5,86,Urban,HR Executive,93843,1 +78789,Male,59,Bachelors,13,73,40,74,56,6.0,3,93,Semi-Urban,Software Engineer,54503,1 +78790,Female,34,Bachelors,2,67,27,52,5,1.0,6,23,Urban,ML Engineer,65911,0 +78791,Male,48,Masters,12,33,28,80,54,8.0,1,32,Rural,Software Engineer,123839,0 +78792,Female,27,Masters,4,76,90,13,16,0.0,4,76,Rural,Software Engineer,116513,1 +78793,Female,30,Bachelors,9,16,84,23,99,8.0,6,12,Semi-Urban,Data Analyst,47387,0 +78794,Male,23,Bachelors,6,22,19,55,59,5.0,7,0,Urban,HR Executive,136531,0 +78795,Male,42,PhD,13,60,43,54,30,3.0,1,58,Urban,ML Engineer,57201,0 +78796,Male,28,Diploma,19,86,4,84,24,0.0,5,6,Urban,Manager,121213,0 +78797,Female,49,Diploma,4,62,72,32,39,8.0,4,34,Semi-Urban,Manager,105423,0 +78798,Male,23,Bachelors,6,51,29,49,35,5.0,4,88,Urban,HR Executive,73053,0 +78799,Other,58,Diploma,1,4,26,43,79,7.0,7,21,Semi-Urban,Software Engineer,37135,0 +78800,Male,30,Bachelors,19,65,1,61,19,2.0,5,61,Urban,Manager,128770,0 +78801,Female,48,Masters,19,53,63,65,77,4.0,6,15,Rural,Data Analyst,45486,0 +78802,Female,29,Bachelors,12,20,83,70,20,5.0,3,63,Rural,HR Executive,144275,0 +78803,Male,44,High School,2,34,8,47,26,1.0,5,10,Urban,ML Engineer,102754,0 +78804,Male,29,Bachelors,13,93,40,58,32,5.0,7,34,Rural,Software Engineer,56051,0 +78805,Male,57,Bachelors,0,61,50,30,1,7.0,3,92,Semi-Urban,Software Engineer,143740,0 +78806,Male,48,PhD,0,14,13,22,8,7.0,6,63,Urban,ML Engineer,149344,0 +78807,Other,44,Bachelors,1,54,94,0,11,2.0,0,86,Semi-Urban,HR Executive,60429,0 +78808,Male,21,Diploma,17,10,75,21,62,5.0,3,29,Semi-Urban,Software Engineer,144137,0 +78809,Female,47,Masters,11,79,97,10,53,1.0,0,86,Urban,Software Engineer,111337,1 +78810,Male,49,Bachelors,14,98,7,59,38,1.0,7,46,Urban,Manager,125053,0 +78811,Male,26,High School,3,82,70,97,22,6.0,3,90,Urban,Manager,45393,1 +78812,Male,24,Bachelors,14,48,0,6,2,2.0,3,59,Urban,Software Engineer,32780,0 +78813,Female,42,Bachelors,6,85,44,93,48,9.0,1,21,Urban,Data Analyst,125889,1 +78814,Female,31,Diploma,14,89,65,12,32,5.0,2,77,Urban,HR Executive,71694,1 +78815,Male,50,Masters,12,48,53,50,48,1.0,0,88,Urban,Data Analyst,50947,1 +78816,Female,30,Masters,17,99,13,15,15,8.0,4,54,Urban,HR Executive,81324,0 +78817,Male,56,PhD,18,14,84,99,73,4.0,4,0,Urban,HR Executive,79748,0 +78818,Male,53,Masters,1,8,12,40,88,8.0,1,51,Rural,Manager,115596,0 +78819,Male,45,Bachelors,9,85,68,60,12,0.0,4,46,Urban,HR Executive,137406,1 +78820,Female,52,Bachelors,6,83,10,42,87,9.0,4,44,Urban,Manager,125416,0 +78821,Male,42,Bachelors,19,82,32,33,26,1.0,5,31,Urban,Software Engineer,59313,0 +78822,Male,57,Bachelors,13,84,87,68,33,6.0,1,51,Urban,HR Executive,109645,1 +78823,Male,57,Diploma,19,67,44,81,1,8.0,1,61,Urban,Manager,72715,1 +78824,Male,47,Masters,0,7,55,27,6,9.0,2,23,Urban,Data Analyst,129546,0 +78825,Female,46,High School,3,70,12,39,61,6.0,4,8,Semi-Urban,Software Engineer,82970,0 +78826,Male,47,Diploma,12,62,70,33,23,4.0,3,81,Rural,Manager,131246,1 +78827,Male,27,Diploma,19,87,73,39,56,2.0,5,79,Urban,Software Engineer,148791,1 +78828,Female,28,Bachelors,10,26,61,27,8,7.0,6,51,Semi-Urban,HR Executive,29420,0 +78829,Male,44,Diploma,12,19,1,87,28,6.0,1,81,Rural,Manager,115861,0 +78830,Female,34,Diploma,17,82,23,16,61,9.0,1,63,Urban,ML Engineer,70157,0 +78831,Female,49,Diploma,6,84,69,43,72,6.0,6,34,Urban,Data Analyst,37798,0 +78832,Male,33,High School,3,65,26,8,57,3.0,0,40,Urban,ML Engineer,78876,0 +78833,Male,31,Bachelors,19,49,32,95,96,3.0,5,88,Semi-Urban,HR Executive,23880,1 +78834,Male,21,Bachelors,8,72,12,13,33,7.0,4,33,Urban,Software Engineer,134131,0 +78835,Female,32,Bachelors,0,41,37,7,32,6.0,5,38,Urban,HR Executive,26530,0 +78836,Male,28,Bachelors,5,31,19,87,98,5.0,1,53,Urban,HR Executive,144479,0 +78837,Female,44,Bachelors,5,89,28,35,8,5.0,4,79,Rural,Manager,123712,0 +78838,Male,39,Masters,9,26,11,34,73,0.0,7,14,Semi-Urban,Software Engineer,68308,0 +78839,Male,22,Masters,12,51,39,17,37,8.0,6,54,Urban,Manager,26940,0 +78840,Female,22,Diploma,16,22,16,11,38,9.0,6,86,Urban,HR Executive,90713,0 +78841,Male,50,Bachelors,12,21,47,1,30,4.0,5,7,Urban,Software Engineer,64420,0 +78842,Male,33,Bachelors,17,98,61,40,89,6.0,7,99,Urban,Manager,107629,1 +78843,Male,27,Bachelors,0,85,93,62,25,4.0,3,42,Urban,HR Executive,78330,1 +78844,Male,59,Masters,9,76,80,65,36,7.0,3,71,Rural,Data Analyst,98731,1 +78845,Male,31,Bachelors,3,49,71,91,42,8.0,2,98,Urban,Software Engineer,85287,1 +78846,Female,55,Bachelors,18,23,82,5,63,7.0,0,92,Rural,Manager,148226,0 +78847,Female,55,Bachelors,5,14,91,55,41,5.0,2,69,Rural,Data Analyst,20986,0 +78848,Female,52,Diploma,12,45,45,78,35,3.0,3,17,Urban,Software Engineer,76404,0 +78849,Male,45,Diploma,18,11,39,37,74,6.0,2,12,Urban,HR Executive,137332,0 +78850,Male,29,Diploma,17,97,58,6,88,1.0,5,37,Urban,Manager,111888,0 +78851,Female,22,High School,16,86,97,24,68,3.0,4,51,Urban,Data Analyst,144728,1 +78852,Female,34,Bachelors,17,23,40,75,3,3.0,3,38,Urban,Software Engineer,62191,0 +78853,Female,21,PhD,8,89,92,91,86,2.0,5,70,Urban,HR Executive,52080,1 +78854,Male,45,Diploma,16,39,15,51,43,8.0,0,2,Semi-Urban,Software Engineer,73919,0 +78855,Male,32,Bachelors,14,19,85,48,43,8.0,2,15,Urban,HR Executive,57662,0 +78856,Male,28,Masters,19,81,21,82,64,3.0,1,42,Urban,Software Engineer,125110,0 +78857,Male,41,Masters,9,41,15,81,40,4.0,3,88,Semi-Urban,ML Engineer,47210,0 +78858,Other,50,Masters,12,93,58,15,98,6.0,2,70,Urban,Software Engineer,55254,0 +78859,Male,40,Diploma,14,42,75,71,7,5.0,3,32,Semi-Urban,ML Engineer,29892,0 +78860,Female,22,Masters,16,6,22,57,47,8.0,2,5,Urban,ML Engineer,130897,0 +78861,Female,40,Diploma,7,17,26,51,15,4.0,7,38,Urban,Data Analyst,83087,0 +78862,Male,21,Masters,12,91,35,35,28,0.0,3,37,Urban,HR Executive,31881,0 +78863,Male,28,Bachelors,15,4,2,49,9,5.0,6,32,Semi-Urban,Software Engineer,22543,0 +78864,Male,35,Bachelors,17,96,70,15,24,5.0,3,60,Urban,Data Analyst,113872,1 +78865,Male,22,High School,12,70,73,4,26,2.0,3,8,Semi-Urban,HR Executive,95544,0 +78866,Male,29,High School,10,57,0,66,91,1.0,5,35,Urban,ML Engineer,139639,0 +78867,Male,51,Bachelors,1,61,65,14,7,0.0,6,40,Semi-Urban,ML Engineer,94537,0 +78868,Male,51,Bachelors,1,86,68,46,87,3.0,7,71,Rural,Manager,43642,1 +78869,Female,36,Diploma,14,51,94,9,20,5.0,6,44,Rural,Software Engineer,65306,0 +78870,Male,44,High School,0,6,42,6,10,5.0,7,35,Semi-Urban,HR Executive,119696,0 +78871,Female,35,Masters,8,62,22,23,84,9.0,0,63,Rural,Data Analyst,77341,0 +78872,Female,50,High School,11,76,79,16,99,5.0,2,58,Rural,HR Executive,113690,0 +78873,Female,51,Bachelors,15,95,17,4,8,6.0,2,78,Urban,Software Engineer,50675,0 +78874,Male,38,Masters,19,41,29,86,50,5.0,2,59,Semi-Urban,HR Executive,43453,0 +78875,Male,38,Bachelors,8,2,54,32,7,1.0,2,10,Semi-Urban,Data Analyst,143687,0 +78876,Male,37,Bachelors,13,53,28,33,52,0.0,7,43,Rural,Data Analyst,120809,0 +78877,Female,45,Masters,10,61,40,3,54,6.0,3,4,Semi-Urban,ML Engineer,23785,0 +78878,Male,50,Bachelors,6,14,10,51,11,6.0,0,97,Urban,Software Engineer,102321,0 +78879,Male,39,Diploma,15,83,26,85,94,0.0,2,92,Rural,ML Engineer,139048,1 +78880,Other,53,Diploma,19,27,35,88,60,9.0,7,13,Urban,ML Engineer,119632,0 +78881,Male,49,Bachelors,0,86,82,7,86,7.0,0,88,Urban,HR Executive,43280,1 +78882,Female,29,Bachelors,7,89,49,27,21,4.0,6,93,Urban,Data Analyst,42646,1 +78883,Male,58,Bachelors,2,97,37,95,70,4.0,2,0,Urban,Data Analyst,99907,0 +78884,Male,22,High School,12,60,22,84,96,1.0,2,20,Semi-Urban,Data Analyst,141683,0 +78885,Male,26,Masters,3,95,69,31,14,4.0,0,36,Urban,Data Analyst,84572,0 +78886,Female,45,High School,4,57,11,27,88,0.0,3,54,Urban,Manager,88148,0 +78887,Female,34,PhD,15,36,41,33,5,1.0,6,40,Rural,ML Engineer,135850,0 +78888,Male,23,Bachelors,6,5,57,0,27,9.0,3,3,Urban,HR Executive,137812,0 +78889,Female,38,Diploma,18,21,90,88,3,9.0,3,28,Rural,Software Engineer,100240,0 +78890,Male,41,Bachelors,9,92,4,85,81,2.0,2,52,Urban,ML Engineer,35356,0 +78891,Male,55,Diploma,3,79,62,11,76,4.0,7,39,Urban,HR Executive,128829,0 +78892,Female,27,Bachelors,13,10,63,78,95,6.0,1,84,Rural,Manager,87040,0 +78893,Female,51,Bachelors,12,53,26,29,2,9.0,7,91,Urban,Software Engineer,130362,0 +78894,Female,25,Bachelors,17,33,47,29,59,4.0,5,74,Urban,ML Engineer,115823,0 +78895,Male,43,Masters,0,19,81,19,85,5.0,4,12,Urban,Software Engineer,65859,0 +78896,Female,48,High School,0,56,43,32,37,9.0,7,75,Semi-Urban,Data Analyst,60020,0 +78897,Male,27,Bachelors,0,38,90,94,82,2.0,2,19,Semi-Urban,HR Executive,44973,1 +78898,Male,21,Diploma,4,63,41,59,81,4.0,2,4,Urban,Software Engineer,72600,0 +78899,Male,27,Bachelors,14,48,89,62,26,9.0,4,97,Semi-Urban,Data Analyst,145063,1 +78900,Male,25,Bachelors,4,39,36,66,23,0.0,3,1,Urban,Software Engineer,125999,0 +78901,Male,29,PhD,7,77,7,14,53,9.0,0,97,Urban,Software Engineer,63546,0 +78902,Male,27,Masters,6,44,67,26,24,7.0,0,84,Semi-Urban,Software Engineer,60602,0 +78903,Male,50,Masters,2,40,6,36,7,5.0,6,98,Urban,ML Engineer,57071,0 +78904,Female,26,Diploma,3,31,62,99,68,9.0,6,33,Semi-Urban,Manager,120642,0 +78905,Female,40,Masters,7,85,93,24,55,4.0,4,17,Urban,Manager,125810,0 +78906,Female,44,Masters,17,7,33,99,21,4.0,0,9,Urban,Data Analyst,64049,0 +78907,Male,54,Bachelors,5,61,94,16,73,6.0,0,39,Urban,Software Engineer,109396,0 +78908,Male,41,Diploma,3,76,78,84,65,5.0,0,41,Urban,Software Engineer,72573,1 +78909,Male,56,Bachelors,18,60,60,89,68,9.0,6,65,Semi-Urban,ML Engineer,73729,1 +78910,Male,41,Bachelors,16,20,49,69,95,2.0,2,48,Semi-Urban,Manager,51574,0 +78911,Female,59,Bachelors,0,31,65,16,93,3.0,0,8,Urban,Manager,94522,0 +78912,Male,56,Diploma,3,53,94,38,50,8.0,7,86,Semi-Urban,HR Executive,34872,1 +78913,Female,22,Bachelors,10,59,29,61,4,1.0,3,18,Urban,Software Engineer,141827,0 +78914,Male,42,Bachelors,13,60,58,47,73,7.0,7,72,Rural,Software Engineer,96273,1 +78915,Female,22,Masters,9,94,43,59,34,0.0,2,91,Urban,Manager,110444,1 +78916,Other,31,Bachelors,13,18,92,0,45,7.0,4,28,Semi-Urban,ML Engineer,107231,0 +78917,Female,29,Bachelors,6,88,42,58,95,6.0,1,77,Urban,HR Executive,96967,1 +78918,Female,55,High School,14,69,24,7,33,0.0,0,26,Urban,Manager,83667,0 +78919,Male,54,High School,4,75,80,8,62,2.0,6,85,Semi-Urban,ML Engineer,101720,1 +78920,Male,40,Diploma,4,63,53,44,47,8.0,0,90,Urban,Manager,31799,1 +78921,Female,48,Masters,10,32,98,15,87,4.0,4,91,Rural,Manager,50633,0 +78922,Male,45,Diploma,9,55,41,1,51,4.0,1,50,Semi-Urban,Software Engineer,90494,0 +78923,Male,57,Masters,11,74,20,95,20,0.0,5,58,Urban,Data Analyst,62002,1 +78924,Male,23,Diploma,10,7,95,33,41,7.0,3,26,Rural,Manager,102500,0 +78925,Male,27,Masters,12,61,3,38,52,4.0,0,59,Semi-Urban,Data Analyst,67384,0 +78926,Female,40,High School,17,26,43,29,31,7.0,3,46,Urban,Data Analyst,40426,0 +78927,Female,34,Bachelors,1,37,20,1,52,5.0,3,74,Urban,HR Executive,141750,0 +78928,Female,50,Bachelors,1,32,48,66,35,1.0,2,88,Urban,Software Engineer,71219,0 +78929,Female,58,Masters,12,49,88,4,96,2.0,4,43,Rural,HR Executive,67806,0 +78930,Male,24,Bachelors,4,6,32,53,46,4.0,2,22,Urban,ML Engineer,108266,0 +78931,Other,58,Bachelors,11,92,75,74,6,8.0,6,82,Urban,Data Analyst,137983,1 +78932,Male,40,Bachelors,14,32,81,5,33,1.0,1,68,Urban,Software Engineer,75012,0 +78933,Female,57,Diploma,6,74,14,60,94,6.0,5,79,Urban,ML Engineer,148218,0 +78934,Female,45,Bachelors,2,53,0,74,25,7.0,1,2,Rural,Data Analyst,72154,0 +78935,Male,48,Diploma,16,39,62,20,31,1.0,1,93,Semi-Urban,HR Executive,66343,0 +78936,Female,26,High School,12,95,21,31,74,6.0,2,60,Rural,HR Executive,76731,0 +78937,Female,47,Masters,19,8,56,4,45,2.0,7,8,Urban,Data Analyst,112179,0 +78938,Other,48,Bachelors,9,7,48,71,43,5.0,3,21,Semi-Urban,HR Executive,138392,0 +78939,Male,53,PhD,10,67,13,66,28,4.0,5,36,Urban,Manager,146413,0 +78940,Male,43,Masters,11,69,47,13,98,1.0,0,96,Urban,ML Engineer,88058,0 +78941,Female,44,Bachelors,15,83,3,72,23,6.0,7,13,Urban,ML Engineer,52904,0 +78942,Male,22,Bachelors,18,66,0,59,50,1.0,6,3,Semi-Urban,ML Engineer,122282,0 +78943,Female,22,Bachelors,0,68,41,29,50,7.0,1,80,Rural,ML Engineer,67970,0 +78944,Male,51,Bachelors,4,0,32,40,37,6.0,2,66,Urban,Manager,48048,0 +78945,Female,24,Bachelors,16,9,35,67,90,1.0,4,72,Urban,Software Engineer,36995,0 +78946,Male,47,Bachelors,11,49,67,38,57,7.0,6,13,Semi-Urban,Data Analyst,120422,0 +78947,Male,46,Bachelors,9,69,94,75,54,1.0,4,47,Urban,HR Executive,113388,1 +78948,Male,33,Diploma,14,65,61,35,81,9.0,3,28,Urban,ML Engineer,127502,0 +78949,Male,56,Masters,16,11,97,2,46,6.0,1,79,Semi-Urban,Manager,137580,0 +78950,Other,38,Diploma,5,74,95,57,82,1.0,5,90,Rural,Software Engineer,62895,1 +78951,Female,37,Bachelors,1,86,84,77,99,9.0,3,46,Semi-Urban,HR Executive,84186,1 +78952,Female,39,Bachelors,12,56,28,2,43,2.0,6,50,Urban,ML Engineer,35548,0 +78953,Male,48,Bachelors,10,32,60,52,65,0.0,6,81,Semi-Urban,ML Engineer,75273,0 +78954,Male,29,Masters,14,80,30,14,49,9.0,6,16,Urban,Manager,97845,0 +78955,Female,45,Masters,15,42,97,42,82,4.0,7,74,Urban,ML Engineer,104464,1 +78956,Male,57,Bachelors,11,62,71,58,18,5.0,2,24,Rural,ML Engineer,119720,0 +78957,Male,43,Masters,5,42,46,40,45,6.0,5,50,Urban,Manager,91929,0 +78958,Male,39,Diploma,9,66,12,89,55,1.0,4,70,Rural,HR Executive,30626,1 +78959,Female,46,Masters,7,93,65,77,9,5.0,3,69,Rural,Manager,99355,1 +78960,Female,50,High School,19,77,21,71,77,4.0,2,30,Rural,ML Engineer,84632,0 +78961,Female,45,Diploma,11,94,84,1,53,4.0,0,46,Rural,Data Analyst,146316,0 +78962,Male,51,High School,0,17,21,45,62,8.0,2,75,Urban,Manager,71171,0 +78963,Male,25,Masters,17,10,45,39,69,2.0,6,31,Semi-Urban,ML Engineer,132772,0 +78964,Female,23,Diploma,15,33,32,40,51,8.0,1,11,Urban,ML Engineer,52640,0 +78965,Female,39,High School,12,83,35,96,15,1.0,7,71,Urban,Software Engineer,36518,1 +78966,Male,49,High School,1,46,0,27,15,9.0,6,51,Urban,ML Engineer,95388,0 +78967,Male,45,Diploma,19,14,22,26,82,1.0,4,19,Semi-Urban,HR Executive,118568,0 +78968,Male,57,Bachelors,11,46,9,58,13,3.0,5,17,Urban,ML Engineer,104851,0 +78969,Female,40,Diploma,18,48,36,79,59,5.0,6,62,Urban,HR Executive,50600,0 +78970,Male,25,Diploma,5,38,66,64,27,3.0,4,97,Rural,HR Executive,38125,1 +78971,Male,54,Diploma,13,1,70,93,4,3.0,3,83,Semi-Urban,Manager,112498,1 +78972,Female,55,Bachelors,13,54,20,68,66,5.0,7,59,Semi-Urban,HR Executive,85727,0 +78973,Male,31,Masters,17,52,63,77,94,9.0,0,63,Rural,Manager,50075,1 +78974,Male,44,Diploma,10,44,81,62,43,9.0,1,1,Semi-Urban,Software Engineer,114304,0 +78975,Male,56,Bachelors,9,36,80,41,83,9.0,6,10,Urban,Software Engineer,60386,0 +78976,Female,56,Bachelors,16,6,94,55,49,5.0,1,66,Rural,ML Engineer,22066,0 +78977,Male,28,Masters,14,63,65,80,23,6.0,4,23,Semi-Urban,Data Analyst,70778,0 +78978,Male,23,High School,7,87,73,11,55,0.0,0,94,Urban,HR Executive,122298,1 +78979,Female,23,Bachelors,1,97,69,83,29,0.0,0,31,Urban,Data Analyst,148516,1 +78980,Male,49,Bachelors,4,66,28,46,30,8.0,6,2,Urban,ML Engineer,136969,0 +78981,Male,21,PhD,13,97,9,78,51,8.0,7,45,Urban,Software Engineer,123277,0 +78982,Male,46,Bachelors,8,54,2,97,26,7.0,0,52,Urban,Data Analyst,26966,0 +78983,Male,45,Bachelors,7,96,59,88,17,6.0,2,21,Rural,HR Executive,69455,1 +78984,Male,59,Bachelors,7,85,73,69,34,0.0,7,78,Semi-Urban,Manager,142370,1 +78985,Male,42,Diploma,16,96,3,79,52,0.0,2,71,Urban,Manager,24386,1 +78986,Female,53,Masters,14,46,81,93,58,9.0,6,81,Rural,ML Engineer,57859,1 +78987,Male,53,Diploma,6,21,5,70,85,5.0,5,73,Urban,Manager,69844,0 +78988,Male,58,Bachelors,6,67,97,32,93,1.0,5,82,Semi-Urban,HR Executive,80675,1 +78989,Female,23,High School,8,23,22,71,47,6.0,2,9,Urban,ML Engineer,61295,0 +78990,Male,51,Bachelors,11,77,96,42,1,4.0,7,65,Semi-Urban,Software Engineer,100342,1 +78991,Female,40,Bachelors,10,15,45,36,83,8.0,1,39,Urban,Data Analyst,45271,0 +78992,Male,41,Masters,3,12,24,1,77,7.0,5,62,Urban,ML Engineer,54928,0 +78993,Female,35,High School,13,58,95,62,92,5.0,4,46,Urban,Software Engineer,44335,1 +78994,Male,24,Bachelors,17,85,99,22,22,4.0,2,6,Urban,Data Analyst,121311,0 +78995,Male,59,High School,6,71,79,25,83,5.0,2,83,Urban,ML Engineer,59093,1 +78996,Male,59,Diploma,4,48,41,42,36,9.0,2,0,Semi-Urban,ML Engineer,57791,0 +78997,Male,53,Diploma,19,10,18,77,95,2.0,6,93,Rural,ML Engineer,52935,0 +78998,Other,54,Bachelors,11,68,64,41,9,6.0,4,6,Semi-Urban,ML Engineer,59345,0 +78999,Female,42,PhD,10,25,59,90,94,2.0,1,57,Urban,Manager,49827,0 +79000,Male,40,PhD,5,72,91,36,96,8.0,6,8,Urban,Data Analyst,100058,0 +79001,Male,45,Bachelors,15,85,81,6,28,3.0,1,47,Rural,ML Engineer,64997,0 +79002,Male,59,High School,2,93,74,71,83,9.0,7,85,Urban,Data Analyst,120906,1 +79003,Male,59,Diploma,19,14,17,26,63,1.0,0,94,Urban,Manager,51105,0 +79004,Male,47,Bachelors,7,27,88,26,9,4.0,0,88,Rural,HR Executive,115927,0 +79005,Male,47,Bachelors,7,51,21,40,45,2.0,2,77,Urban,Data Analyst,87381,0 +79006,Female,55,Diploma,12,32,6,62,21,6.0,1,72,Rural,Software Engineer,125933,0 +79007,Male,50,Bachelors,2,49,93,57,98,2.0,5,39,Urban,Manager,28211,1 +79008,Male,24,Diploma,7,3,91,2,15,2.0,7,74,Urban,HR Executive,90212,0 +79009,Female,53,Bachelors,8,56,16,30,73,2.0,4,56,Rural,HR Executive,98123,0 +79010,Male,46,High School,8,7,17,71,9,4.0,0,24,Rural,Software Engineer,83127,0 +79011,Male,45,Bachelors,3,80,64,59,10,0.0,3,11,Urban,Software Engineer,66492,0 +79012,Male,41,High School,6,1,4,25,36,9.0,7,27,Urban,Data Analyst,86735,0 +79013,Male,33,Bachelors,16,60,11,88,26,8.0,4,96,Urban,Software Engineer,99282,1 +79014,Female,43,Bachelors,4,62,19,70,21,8.0,3,49,Urban,ML Engineer,129283,0 +79015,Female,47,Masters,4,89,95,75,97,6.0,6,30,Urban,Manager,130019,1 +79016,Male,43,Bachelors,15,69,45,14,63,3.0,2,87,Urban,HR Executive,58485,0 +79017,Female,55,High School,19,20,95,85,66,4.0,0,88,Rural,ML Engineer,59350,1 +79018,Other,53,Masters,5,93,93,6,95,4.0,5,80,Semi-Urban,HR Executive,143628,1 +79019,Male,33,Bachelors,18,44,28,24,43,4.0,0,33,Urban,Software Engineer,72374,0 +79020,Female,40,Diploma,2,20,52,91,7,3.0,4,15,Urban,ML Engineer,96842,0 +79021,Male,28,Bachelors,19,0,69,31,62,1.0,4,94,Rural,HR Executive,97082,0 +79022,Male,45,High School,14,14,48,8,86,6.0,1,91,Semi-Urban,ML Engineer,143289,0 +79023,Female,31,PhD,18,16,8,80,8,1.0,0,80,Semi-Urban,ML Engineer,128260,0 +79024,Male,23,Bachelors,17,3,95,66,68,4.0,4,85,Urban,ML Engineer,40942,1 +79025,Female,45,Masters,16,67,61,87,9,6.0,5,62,Rural,HR Executive,91987,1 +79026,Male,33,Diploma,12,35,4,65,37,3.0,5,55,Semi-Urban,ML Engineer,101159,0 +79027,Female,57,Bachelors,6,69,18,84,76,4.0,3,35,Urban,Manager,123718,0 +79028,Male,52,Bachelors,15,81,98,73,59,0.0,5,88,Urban,HR Executive,97055,1 +79029,Male,21,Diploma,18,45,85,26,71,8.0,6,77,Urban,Software Engineer,109388,0 +79030,Male,59,High School,10,86,96,81,59,1.0,6,11,Urban,Software Engineer,22649,1 +79031,Male,29,Bachelors,0,57,76,80,97,1.0,0,45,Semi-Urban,Software Engineer,27049,1 +79032,Female,22,Diploma,5,51,26,82,11,2.0,2,89,Rural,Data Analyst,91722,1 +79033,Female,59,Masters,0,19,56,97,34,7.0,2,55,Urban,Manager,136548,0 +79034,Male,35,PhD,19,52,25,90,3,7.0,0,35,Urban,Software Engineer,97321,0 +79035,Male,34,Bachelors,0,93,31,79,4,9.0,2,61,Urban,Data Analyst,41458,1 +79036,Male,29,Bachelors,7,8,89,77,73,1.0,3,12,Rural,Software Engineer,64339,0 +79037,Male,46,Masters,7,75,34,12,50,1.0,3,58,Urban,Data Analyst,94134,0 +79038,Female,42,High School,18,1,85,5,75,0.0,7,93,Urban,HR Executive,149652,0 +79039,Male,49,PhD,0,34,79,17,37,6.0,4,43,Semi-Urban,Software Engineer,64918,0 +79040,Female,41,High School,16,49,42,7,89,0.0,6,39,Rural,ML Engineer,33606,0 +79041,Male,25,PhD,6,8,27,95,94,1.0,3,93,Urban,ML Engineer,29503,0 +79042,Female,56,Diploma,3,68,7,48,67,3.0,4,82,Rural,ML Engineer,128373,0 +79043,Male,51,Diploma,7,62,7,74,8,2.0,4,84,Rural,Data Analyst,60338,0 +79044,Female,22,Bachelors,12,74,97,53,81,1.0,2,58,Urban,ML Engineer,45599,1 +79045,Male,48,High School,18,87,52,13,46,9.0,2,77,Urban,ML Engineer,93621,0 +79046,Female,40,Bachelors,17,57,16,98,64,9.0,1,25,Urban,Data Analyst,35847,0 +79047,Male,36,Bachelors,10,85,51,7,5,3.0,3,18,Urban,HR Executive,57763,0 +79048,Female,55,Masters,18,92,33,50,39,9.0,2,23,Urban,ML Engineer,71784,0 +79049,Female,57,High School,19,56,43,60,19,2.0,2,19,Semi-Urban,Data Analyst,73435,0 +79050,Female,58,PhD,17,52,22,88,11,2.0,6,46,Semi-Urban,Manager,145626,0 +79051,Male,49,High School,16,44,27,0,5,5.0,4,97,Rural,HR Executive,85325,0 +79052,Female,23,Diploma,16,81,44,37,53,6.0,7,24,Urban,ML Engineer,97231,0 +79053,Male,35,Bachelors,4,93,7,34,75,6.0,1,3,Semi-Urban,HR Executive,27299,0 +79054,Male,35,PhD,15,25,19,58,90,3.0,6,26,Urban,Manager,141678,0 +79055,Male,22,High School,2,76,80,25,79,9.0,6,67,Urban,ML Engineer,80633,1 +79056,Female,26,Bachelors,10,1,7,33,86,2.0,3,42,Rural,Manager,83535,0 +79057,Male,59,Bachelors,6,58,34,85,35,0.0,4,86,Urban,HR Executive,75083,1 +79058,Male,56,Masters,6,1,93,76,83,8.0,3,60,Semi-Urban,Data Analyst,96427,0 +79059,Female,43,Bachelors,14,72,83,78,1,9.0,2,27,Urban,Data Analyst,128613,1 +79060,Female,57,Bachelors,17,8,81,49,65,0.0,7,68,Urban,Data Analyst,95557,0 +79061,Female,56,Masters,15,82,10,21,34,9.0,2,15,Urban,Manager,40329,0 +79062,Male,29,Diploma,16,44,67,81,28,6.0,3,34,Rural,ML Engineer,123056,0 +79063,Female,37,Diploma,18,17,57,43,66,7.0,4,95,Urban,Software Engineer,52521,0 +79064,Male,28,High School,0,69,57,23,70,7.0,3,78,Semi-Urban,HR Executive,101868,0 +79065,Male,40,Bachelors,6,11,70,81,25,6.0,1,35,Urban,Data Analyst,32249,0 +79066,Male,56,Bachelors,6,75,91,43,79,3.0,6,34,Rural,ML Engineer,44310,1 +79067,Male,22,Masters,2,55,65,65,66,0.0,5,16,Urban,Data Analyst,28964,0 +79068,Male,32,Bachelors,19,14,14,3,89,5.0,0,26,Semi-Urban,Software Engineer,123676,0 +79069,Male,24,Bachelors,5,24,69,14,73,5.0,3,38,Rural,HR Executive,24609,0 +79070,Female,32,Masters,15,79,62,25,90,6.0,1,37,Semi-Urban,Manager,103099,0 +79071,Female,58,Masters,7,76,96,47,9,8.0,5,98,Rural,ML Engineer,67339,1 +79072,Female,25,Bachelors,19,74,55,47,31,8.0,6,44,Urban,HR Executive,39076,0 +79073,Female,51,High School,7,22,19,33,2,2.0,5,39,Semi-Urban,Software Engineer,24097,0 +79074,Female,22,Diploma,11,17,63,63,71,3.0,5,50,Urban,ML Engineer,20055,0 +79075,Male,41,Diploma,7,21,76,42,32,2.0,3,64,Semi-Urban,Software Engineer,29563,0 +79076,Male,24,Masters,8,44,59,33,87,2.0,5,17,Urban,Software Engineer,32333,0 +79077,Male,43,Bachelors,17,89,95,5,78,7.0,5,54,Rural,Data Analyst,58764,1 +79078,Male,25,Bachelors,14,36,42,95,76,2.0,7,16,Urban,ML Engineer,72310,0 +79079,Female,46,Bachelors,3,88,39,81,69,8.0,1,67,Semi-Urban,Data Analyst,87409,1 +79080,Female,59,Diploma,17,20,78,68,86,1.0,3,45,Urban,Data Analyst,126867,0 +79081,Female,29,Bachelors,17,16,5,22,29,3.0,7,2,Semi-Urban,ML Engineer,81799,0 +79082,Female,28,Bachelors,18,81,45,39,72,8.0,6,55,Urban,Data Analyst,43555,0 +79083,Male,48,Masters,15,31,33,71,73,6.0,5,53,Urban,Software Engineer,127643,0 +79084,Male,57,Masters,14,71,85,54,87,6.0,2,59,Semi-Urban,Software Engineer,95039,1 +79085,Female,36,Diploma,4,45,43,15,46,8.0,2,56,Semi-Urban,Manager,125043,0 +79086,Female,54,Diploma,7,21,97,33,78,1.0,1,65,Urban,Software Engineer,124479,0 +79087,Male,22,Diploma,15,50,24,7,53,4.0,2,59,Semi-Urban,ML Engineer,122739,0 +79088,Male,37,Diploma,12,2,82,59,46,2.0,2,67,Urban,ML Engineer,50092,0 +79089,Female,34,Bachelors,10,68,36,95,84,1.0,4,43,Urban,HR Executive,130122,1 +79090,Male,33,Bachelors,9,57,19,99,83,5.0,7,97,Urban,HR Executive,29287,1 +79091,Female,44,Masters,9,94,96,30,8,4.0,6,86,Rural,Data Analyst,49773,1 +79092,Male,50,Diploma,8,28,52,24,93,4.0,7,99,Urban,HR Executive,49766,0 +79093,Male,54,Diploma,10,49,60,34,4,5.0,4,23,Urban,HR Executive,76420,0 +79094,Male,53,Diploma,10,72,37,12,5,0.0,0,50,Urban,ML Engineer,80576,0 +79095,Male,38,Masters,5,86,18,90,46,3.0,6,95,Urban,ML Engineer,75700,1 +79096,Male,32,Diploma,10,84,12,21,88,6.0,2,99,Semi-Urban,Manager,84017,0 +79097,Female,36,Bachelors,0,47,89,7,98,1.0,5,63,Semi-Urban,Software Engineer,149228,0 +79098,Male,30,Masters,8,32,72,32,97,9.0,3,76,Rural,Software Engineer,106837,0 +79099,Female,36,Bachelors,0,84,14,43,11,9.0,3,35,Urban,Manager,82942,0 +79100,Male,42,High School,18,96,89,31,25,3.0,4,36,Semi-Urban,Manager,118539,1 +79101,Male,55,Diploma,16,64,56,13,60,5.0,7,67,Urban,Software Engineer,125459,0 +79102,Male,24,Bachelors,10,15,97,44,38,2.0,6,14,Urban,Data Analyst,31861,0 +79103,Male,36,High School,16,14,99,18,15,8.0,3,99,Rural,HR Executive,122569,0 +79104,Male,41,High School,16,60,21,7,84,9.0,4,32,Rural,Software Engineer,51689,0 +79105,Male,21,Diploma,5,77,24,49,17,1.0,5,59,Rural,Manager,132444,0 +79106,Male,59,High School,10,32,5,12,84,9.0,4,47,Urban,HR Executive,102170,0 +79107,Male,59,Bachelors,6,11,80,63,25,0.0,7,99,Urban,HR Executive,25526,1 +79108,Male,26,High School,14,2,50,23,69,1.0,1,10,Urban,ML Engineer,46982,0 +79109,Female,56,High School,18,68,35,14,62,6.0,7,78,Semi-Urban,HR Executive,33150,0 +79110,Male,53,Bachelors,10,33,3,24,25,5.0,6,51,Urban,Manager,106083,0 +79111,Female,45,Bachelors,15,87,4,10,1,0.0,7,60,Urban,Data Analyst,127903,0 +79112,Female,56,Bachelors,9,43,51,7,57,9.0,6,70,Urban,Manager,106769,0 +79113,Female,55,Masters,4,72,88,33,98,9.0,3,54,Rural,Software Engineer,39039,1 +79114,Male,22,Diploma,1,96,83,98,15,1.0,5,43,Urban,Manager,107422,1 +79115,Female,27,Bachelors,2,2,45,10,34,2.0,2,8,Urban,HR Executive,28676,0 +79116,Male,37,PhD,7,87,56,23,0,5.0,5,52,Urban,Software Engineer,77002,0 +79117,Male,46,Masters,0,72,82,78,21,6.0,3,93,Rural,ML Engineer,104517,1 +79118,Male,57,Bachelors,9,81,9,58,17,9.0,5,53,Urban,Data Analyst,95410,0 +79119,Female,39,Bachelors,6,59,51,72,30,0.0,4,96,Semi-Urban,Software Engineer,57890,1 +79120,Female,52,High School,17,20,48,78,95,1.0,3,21,Rural,Software Engineer,103795,0 +79121,Female,53,Diploma,7,17,43,37,35,5.0,6,14,Semi-Urban,Manager,28190,0 +79122,Female,51,Masters,4,98,71,30,17,9.0,7,66,Urban,Manager,120708,1 +79123,Female,55,Diploma,6,59,87,51,67,1.0,7,66,Urban,ML Engineer,52508,1 +79124,Female,45,Bachelors,14,68,23,50,46,8.0,6,89,Urban,HR Executive,23782,0 +79125,Female,54,High School,15,76,41,20,57,3.0,1,76,Urban,Software Engineer,135545,0 +79126,Female,53,Diploma,11,51,92,91,32,9.0,3,58,Urban,ML Engineer,27307,1 +79127,Female,46,Masters,19,11,56,97,34,9.0,2,81,Urban,Data Analyst,101689,1 +79128,Female,59,Bachelors,19,56,34,58,33,1.0,3,25,Semi-Urban,Data Analyst,64229,0 +79129,Female,32,Masters,1,14,36,83,84,0.0,5,52,Urban,Software Engineer,110159,0 +79130,Male,56,PhD,12,87,1,75,6,1.0,0,77,Urban,ML Engineer,136876,1 +79131,Male,36,High School,12,18,13,41,47,2.0,1,10,Rural,Software Engineer,70511,0 +79132,Male,53,Bachelors,8,0,49,63,17,8.0,5,31,Urban,HR Executive,109728,0 +79133,Female,56,Bachelors,13,98,8,34,86,7.0,2,64,Rural,Software Engineer,142442,0 +79134,Male,42,Bachelors,17,28,34,68,33,1.0,6,86,Urban,HR Executive,61577,0 +79135,Male,50,Bachelors,9,13,39,19,94,5.0,4,77,Urban,Manager,82476,0 +79136,Male,36,High School,0,18,49,27,82,5.0,1,61,Semi-Urban,ML Engineer,54833,0 +79137,Male,22,Diploma,8,39,12,40,51,7.0,5,89,Semi-Urban,ML Engineer,42446,0 +79138,Female,34,Masters,8,34,85,68,93,3.0,4,58,Urban,Manager,149871,1 +79139,Male,26,Bachelors,3,44,8,65,44,0.0,2,78,Urban,HR Executive,88765,0 +79140,Female,36,High School,6,20,53,40,2,2.0,6,0,Urban,Data Analyst,127921,0 +79141,Male,27,PhD,7,37,47,40,39,8.0,7,57,Semi-Urban,HR Executive,73385,0 +79142,Male,52,Bachelors,7,83,68,79,64,3.0,7,40,Rural,ML Engineer,27304,1 +79143,Male,49,PhD,6,51,11,69,46,6.0,7,12,Rural,ML Engineer,103581,0 +79144,Male,21,High School,5,32,95,30,27,7.0,5,38,Rural,HR Executive,30858,0 +79145,Female,21,Bachelors,16,21,32,0,97,6.0,1,5,Rural,ML Engineer,86140,0 +79146,Male,48,Bachelors,8,81,4,90,32,8.0,7,5,Semi-Urban,HR Executive,48061,0 +79147,Male,54,Diploma,11,21,63,58,97,0.0,6,58,Rural,HR Executive,67333,0 +79148,Male,33,Diploma,5,55,95,6,29,7.0,1,97,Urban,Data Analyst,54962,1 +79149,Male,33,Masters,13,21,68,55,63,0.0,5,24,Urban,ML Engineer,133053,0 +79150,Female,46,Diploma,4,54,95,83,9,5.0,6,46,Semi-Urban,Manager,55727,1 +79151,Male,40,PhD,19,99,46,63,52,6.0,3,84,Rural,ML Engineer,64760,1 +79152,Male,23,Bachelors,16,27,34,54,0,6.0,7,62,Semi-Urban,HR Executive,147133,0 +79153,Male,21,Bachelors,8,97,38,52,86,6.0,6,40,Rural,ML Engineer,29954,0 +79154,Female,29,High School,11,89,97,70,25,4.0,1,73,Rural,Software Engineer,72050,1 +79155,Male,28,High School,17,39,2,51,99,5.0,0,20,Urban,ML Engineer,129024,0 +79156,Female,51,Bachelors,0,11,96,27,13,6.0,7,2,Rural,ML Engineer,119346,0 +79157,Female,24,Diploma,9,38,66,16,57,8.0,7,99,Rural,Software Engineer,87598,0 +79158,Male,25,Bachelors,17,42,84,78,1,7.0,6,69,Urban,Software Engineer,96581,1 +79159,Male,46,Bachelors,7,40,77,74,33,4.0,1,36,Semi-Urban,Manager,106522,0 +79160,Female,37,Masters,13,55,44,97,33,2.0,6,85,Urban,ML Engineer,62230,1 +79161,Male,34,Bachelors,10,85,31,37,56,4.0,5,62,Rural,Data Analyst,25657,0 +79162,Female,37,Bachelors,1,44,38,91,25,5.0,6,60,Urban,Manager,145359,0 +79163,Male,42,Bachelors,2,36,40,91,6,4.0,4,53,Semi-Urban,HR Executive,113213,0 +79164,Female,59,Diploma,17,78,15,64,39,0.0,5,9,Urban,HR Executive,58941,0 +79165,Male,34,Bachelors,16,38,26,95,94,4.0,4,68,Rural,HR Executive,51372,0 +79166,Male,48,Diploma,4,50,48,0,73,1.0,2,32,Urban,Manager,65132,0 +79167,Other,31,High School,4,25,48,21,46,2.0,2,33,Rural,Software Engineer,114898,0 +79168,Female,45,Diploma,8,10,76,64,28,9.0,3,88,Semi-Urban,Software Engineer,112538,0 +79169,Female,59,Bachelors,0,2,36,37,81,0.0,1,64,Semi-Urban,ML Engineer,61467,0 +79170,Female,35,High School,16,66,79,84,97,9.0,0,92,Rural,Manager,20897,1 +79171,Male,33,Diploma,16,72,44,15,42,1.0,7,38,Semi-Urban,Software Engineer,126424,0 +79172,Male,57,Diploma,3,87,7,12,41,6.0,7,79,Rural,Software Engineer,73516,0 +79173,Female,34,PhD,19,62,42,76,83,0.0,4,85,Rural,Data Analyst,115872,1 +79174,Male,23,Diploma,13,19,97,30,40,3.0,3,99,Urban,HR Executive,58912,1 +79175,Male,53,Diploma,19,4,15,23,19,3.0,5,22,Semi-Urban,Software Engineer,70759,0 +79176,Male,42,High School,10,82,1,6,57,1.0,2,60,Urban,Manager,78203,0 +79177,Female,42,High School,2,98,14,95,40,8.0,3,57,Urban,Manager,65948,1 +79178,Male,40,Bachelors,19,27,67,43,79,5.0,7,52,Urban,ML Engineer,84793,0 +79179,Female,22,High School,18,3,6,23,45,2.0,4,88,Urban,ML Engineer,111141,0 +79180,Male,46,Bachelors,14,12,32,5,6,4.0,6,59,Urban,ML Engineer,21042,0 +79181,Female,27,Diploma,8,85,46,56,19,2.0,1,7,Semi-Urban,ML Engineer,43341,0 +79182,Male,33,Masters,13,22,85,85,67,8.0,0,74,Rural,ML Engineer,50496,1 +79183,Female,39,High School,15,74,49,28,56,2.0,5,34,Urban,Software Engineer,111984,0 +79184,Male,28,Bachelors,5,37,71,46,43,9.0,4,52,Urban,Data Analyst,39654,0 +79185,Male,53,Masters,11,6,38,66,80,6.0,1,41,Urban,Data Analyst,129130,0 +79186,Male,34,Masters,7,75,73,89,74,2.0,5,74,Urban,Manager,32982,1 +79187,Female,58,PhD,16,47,53,99,82,1.0,0,31,Urban,Software Engineer,34396,0 +79188,Female,55,High School,2,76,79,99,33,1.0,1,49,Urban,HR Executive,122075,1 +79189,Male,26,Bachelors,19,76,80,69,57,3.0,2,16,Urban,Software Engineer,85923,1 +79190,Female,53,Diploma,3,44,33,76,80,9.0,4,11,Urban,Manager,36944,0 +79191,Female,51,Bachelors,8,52,90,85,32,5.0,6,26,Rural,Data Analyst,75426,1 +79192,Male,51,Diploma,0,65,92,37,2,4.0,1,8,Semi-Urban,Software Engineer,56471,0 +79193,Female,43,Bachelors,17,89,28,12,96,5.0,4,38,Urban,ML Engineer,24714,0 +79194,Male,38,Masters,11,64,71,81,13,7.0,4,82,Urban,Manager,132779,1 +79195,Male,54,Bachelors,11,67,66,21,91,0.0,1,80,Semi-Urban,Software Engineer,59423,0 +79196,Male,25,High School,5,14,42,99,31,9.0,4,28,Urban,ML Engineer,126941,0 +79197,Female,30,Diploma,3,75,44,42,47,1.0,6,33,Urban,Software Engineer,148082,0 +79198,Male,28,Masters,11,17,95,24,46,7.0,3,18,Semi-Urban,Manager,143507,0 +79199,Male,21,Diploma,14,34,91,26,28,3.0,5,66,Rural,HR Executive,137987,0 +79200,Female,22,Bachelors,6,1,40,25,79,3.0,4,25,Urban,Software Engineer,92992,0 +79201,Other,41,Masters,12,3,71,90,49,9.0,5,78,Urban,HR Executive,40436,1 +79202,Female,35,Masters,16,78,58,6,80,7.0,3,77,Semi-Urban,Manager,80499,0 +79203,Male,23,High School,0,7,21,2,83,5.0,2,68,Rural,Software Engineer,127936,0 +79204,Male,39,High School,5,69,12,92,41,8.0,2,74,Urban,Data Analyst,140629,1 +79205,Female,47,Masters,17,96,55,49,64,1.0,3,80,Semi-Urban,HR Executive,123626,1 +79206,Female,45,Masters,13,81,78,81,30,6.0,5,46,Urban,HR Executive,26953,1 +79207,Female,26,Diploma,19,72,95,10,58,6.0,2,29,Urban,Data Analyst,117478,0 +79208,Female,46,Bachelors,18,90,21,91,57,3.0,0,39,Urban,Software Engineer,103905,1 +79209,Female,51,Bachelors,9,34,61,44,31,0.0,1,6,Urban,ML Engineer,62916,0 +79210,Female,25,High School,15,54,60,56,74,3.0,0,0,Urban,Manager,85199,0 +79211,Male,52,Masters,5,70,48,20,62,8.0,2,76,Semi-Urban,ML Engineer,88636,0 +79212,Male,33,Masters,16,13,77,21,15,8.0,7,89,Urban,Software Engineer,58280,0 +79213,Male,48,Masters,18,32,10,97,67,6.0,5,83,Semi-Urban,Software Engineer,75170,0 +79214,Female,40,High School,18,90,38,9,30,0.0,2,63,Semi-Urban,Software Engineer,120326,0 +79215,Female,37,Diploma,10,57,0,23,23,9.0,6,66,Urban,ML Engineer,71380,0 +79216,Male,29,Bachelors,18,70,46,22,41,8.0,7,81,Rural,HR Executive,48391,0 +79217,Male,24,Bachelors,17,96,31,16,13,2.0,1,97,Semi-Urban,Data Analyst,79969,1 +79218,Female,21,Diploma,8,21,26,53,90,4.0,5,16,Urban,Data Analyst,112479,0 +79219,Male,55,PhD,15,34,10,94,86,2.0,0,8,Urban,Manager,31191,0 +79220,Male,36,Masters,0,83,64,50,94,5.0,6,23,Semi-Urban,HR Executive,70809,0 +79221,Male,25,High School,6,1,37,59,93,4.0,6,46,Rural,ML Engineer,142859,0 +79222,Female,56,Bachelors,9,16,73,9,55,4.0,1,51,Rural,Software Engineer,130819,0 +79223,Male,45,Bachelors,15,71,16,77,43,1.0,1,29,Semi-Urban,HR Executive,80443,0 +79224,Male,55,Diploma,10,8,88,4,32,2.0,6,79,Semi-Urban,ML Engineer,57013,0 +79225,Female,47,High School,2,40,14,26,56,3.0,4,85,Semi-Urban,Data Analyst,128526,0 +79226,Male,51,Bachelors,4,47,11,86,74,6.0,1,29,Urban,Data Analyst,31307,0 +79227,Male,36,High School,17,55,58,21,74,1.0,4,55,Semi-Urban,ML Engineer,104413,0 +79228,Female,29,Bachelors,14,20,77,17,97,5.0,4,72,Urban,Software Engineer,98488,0 +79229,Other,31,High School,10,58,44,31,51,6.0,2,94,Semi-Urban,Software Engineer,135471,0 +79230,Male,30,PhD,7,4,90,32,45,3.0,1,30,Rural,ML Engineer,90711,0 +79231,Male,44,Diploma,2,68,85,20,71,7.0,0,90,Semi-Urban,Software Engineer,127579,1 +79232,Male,28,PhD,1,88,56,23,17,2.0,0,48,Urban,HR Executive,87464,0 +79233,Male,46,Bachelors,6,19,0,39,62,6.0,4,18,Rural,HR Executive,147552,0 +79234,Male,50,Bachelors,7,92,14,77,49,7.0,1,27,Urban,ML Engineer,28227,0 +79235,Male,37,PhD,4,36,55,9,34,6.0,1,45,Urban,Manager,124341,0 +79236,Male,45,High School,13,76,61,21,31,2.0,2,92,Semi-Urban,Data Analyst,70568,1 +79237,Female,21,Diploma,4,88,33,61,89,4.0,0,77,Urban,Software Engineer,107793,1 +79238,Male,50,High School,9,35,59,2,43,4.0,2,29,Urban,Manager,119153,0 +79239,Female,37,Bachelors,8,16,97,43,96,4.0,2,70,Rural,HR Executive,141682,0 +79240,Male,27,High School,5,83,13,55,72,3.0,0,65,Urban,Software Engineer,61803,0 +79241,Female,46,Diploma,11,66,85,59,30,6.0,4,3,Semi-Urban,HR Executive,107561,0 +79242,Male,48,Diploma,5,72,85,3,28,9.0,4,48,Urban,Manager,69413,0 +79243,Male,28,Bachelors,16,18,14,92,55,0.0,1,38,Semi-Urban,HR Executive,143762,0 +79244,Female,41,Bachelors,18,2,50,1,48,2.0,0,0,Urban,HR Executive,88194,0 +79245,Female,31,High School,16,38,25,98,59,1.0,2,5,Rural,HR Executive,123356,0 +79246,Male,35,Bachelors,18,14,12,40,60,9.0,2,77,Rural,Manager,71836,0 +79247,Female,58,Diploma,16,7,45,13,36,9.0,3,88,Semi-Urban,HR Executive,96901,0 +79248,Other,24,Bachelors,4,32,12,55,70,8.0,2,45,Urban,HR Executive,130366,0 +79249,Male,38,Bachelors,9,7,22,69,68,2.0,0,50,Rural,Software Engineer,50236,0 +79250,Male,51,PhD,4,95,87,17,39,0.0,2,29,Rural,Data Analyst,81228,0 +79251,Female,48,Bachelors,9,39,61,46,59,0.0,6,87,Urban,ML Engineer,136986,0 +79252,Male,33,Diploma,11,85,28,29,20,4.0,0,46,Urban,Data Analyst,73284,0 +79253,Male,31,Diploma,19,13,78,47,85,3.0,3,7,Rural,Data Analyst,72266,0 +79254,Male,45,Diploma,13,9,18,54,15,7.0,5,29,Semi-Urban,ML Engineer,129696,0 +79255,Female,36,Bachelors,16,19,89,73,24,1.0,0,2,Semi-Urban,Software Engineer,64587,0 +79256,Female,39,Masters,5,1,8,58,20,3.0,6,89,Semi-Urban,Data Analyst,25823,0 +79257,Female,28,Diploma,4,3,44,44,74,5.0,1,48,Urban,Software Engineer,62036,0 +79258,Male,56,Masters,17,90,81,90,78,5.0,7,68,Rural,HR Executive,61792,1 +79259,Male,49,Bachelors,4,15,73,67,34,0.0,0,93,Urban,ML Engineer,79713,1 +79260,Male,31,Masters,16,54,5,94,74,0.0,5,44,Urban,Data Analyst,71373,0 +79261,Other,21,Bachelors,2,57,9,74,59,5.0,2,57,Semi-Urban,HR Executive,103381,0 +79262,Male,32,Bachelors,8,76,20,44,51,9.0,3,55,Urban,ML Engineer,118430,0 +79263,Male,45,Bachelors,17,34,68,89,23,2.0,7,63,Rural,Manager,107591,1 +79264,Female,36,High School,3,10,37,55,57,3.0,7,54,Urban,ML Engineer,70971,0 +79265,Female,29,High School,7,3,30,72,38,3.0,6,24,Urban,Manager,135509,0 +79266,Female,31,Bachelors,10,54,60,83,29,6.0,4,5,Urban,HR Executive,42585,0 +79267,Male,29,Bachelors,14,2,37,95,3,3.0,7,54,Rural,HR Executive,67543,0 +79268,Male,52,Bachelors,12,98,81,67,71,4.0,4,11,Urban,Data Analyst,144894,1 +79269,Female,43,Bachelors,10,43,9,87,76,1.0,4,27,Semi-Urban,Manager,94639,0 +79270,Male,37,Masters,14,64,87,72,78,9.0,2,30,Urban,Data Analyst,112183,1 +79271,Male,59,Bachelors,15,40,85,51,33,0.0,3,29,Urban,Software Engineer,129586,0 +79272,Male,45,High School,3,38,37,75,62,1.0,1,5,Semi-Urban,HR Executive,128411,0 +79273,Male,33,Bachelors,14,13,36,81,57,3.0,5,43,Urban,Manager,104246,0 +79274,Male,33,Diploma,19,99,16,52,88,5.0,4,90,Urban,HR Executive,50315,1 +79275,Female,57,PhD,11,4,9,21,40,1.0,7,88,Urban,Software Engineer,35937,0 +79276,Male,52,High School,8,85,65,71,89,8.0,2,3,Urban,Software Engineer,49683,0 +79277,Male,47,Bachelors,15,65,42,58,49,1.0,4,64,Urban,Data Analyst,40059,0 +79278,Male,23,Bachelors,1,52,16,99,47,9.0,0,68,Urban,HR Executive,149893,1 +79279,Other,37,Masters,4,32,59,55,44,9.0,5,23,Urban,HR Executive,61350,0 +79280,Female,48,Bachelors,16,48,41,51,57,1.0,2,82,Semi-Urban,ML Engineer,125521,0 +79281,Female,29,Diploma,17,45,22,64,96,4.0,0,32,Urban,ML Engineer,91803,0 +79282,Male,53,Diploma,17,62,87,77,53,0.0,0,74,Semi-Urban,HR Executive,61526,1 +79283,Male,38,Diploma,12,60,2,80,8,8.0,7,11,Semi-Urban,HR Executive,108105,0 +79284,Male,56,Diploma,17,86,66,42,88,8.0,3,62,Rural,HR Executive,25246,1 +79285,Male,41,Bachelors,10,95,62,61,0,6.0,6,53,Rural,ML Engineer,32847,1 +79286,Male,44,Bachelors,19,94,83,20,56,5.0,0,63,Urban,Software Engineer,94224,1 +79287,Male,25,Bachelors,9,92,3,11,16,6.0,7,83,Rural,Software Engineer,93261,0 +79288,Other,44,Diploma,4,19,67,77,71,1.0,1,18,Urban,Manager,36067,0 +79289,Female,52,Masters,7,14,72,3,97,6.0,2,14,Rural,ML Engineer,60066,0 +79290,Male,54,Masters,11,33,54,10,45,8.0,7,56,Urban,HR Executive,38853,0 +79291,Female,36,Diploma,10,42,1,68,34,3.0,1,76,Urban,ML Engineer,142020,0 +79292,Male,54,High School,9,14,55,21,29,7.0,0,6,Rural,Manager,20436,0 +79293,Female,33,Bachelors,11,15,46,31,54,0.0,0,76,Urban,Manager,59954,0 +79294,Female,43,Bachelors,2,54,93,8,70,2.0,0,55,Urban,HR Executive,99293,0 +79295,Male,47,Diploma,2,32,5,57,14,1.0,5,41,Urban,Software Engineer,74658,0 +79296,Male,54,Masters,9,10,62,60,88,3.0,3,86,Urban,Manager,38425,0 +79297,Male,45,PhD,9,56,50,63,25,7.0,0,20,Semi-Urban,Software Engineer,41873,0 +79298,Male,49,Masters,18,32,44,82,92,7.0,5,49,Rural,Software Engineer,24103,0 +79299,Male,45,Diploma,5,77,18,40,16,2.0,5,57,Rural,HR Executive,143679,0 +79300,Male,25,Masters,7,51,36,79,79,1.0,4,14,Urban,ML Engineer,69923,0 +79301,Female,27,Diploma,12,52,53,17,97,2.0,5,53,Rural,Manager,147743,0 +79302,Male,37,Diploma,12,5,24,56,93,3.0,7,31,Urban,HR Executive,88334,0 +79303,Female,56,Bachelors,18,35,80,75,22,7.0,0,90,Urban,Software Engineer,123181,1 +79304,Male,59,Masters,4,55,6,65,45,8.0,3,63,Urban,Software Engineer,83165,0 +79305,Female,55,Bachelors,18,95,52,16,38,0.0,2,69,Urban,Data Analyst,49829,0 +79306,Male,49,Bachelors,12,64,81,37,22,2.0,6,40,Rural,HR Executive,46172,0 +79307,Male,37,Bachelors,5,70,13,15,56,9.0,1,12,Urban,ML Engineer,63723,0 +79308,Male,24,Diploma,7,8,25,33,37,1.0,7,34,Urban,Software Engineer,75369,0 +79309,Male,34,High School,13,89,25,52,61,8.0,1,36,Urban,Manager,137794,0 +79310,Male,52,Bachelors,0,65,6,61,20,0.0,5,29,Rural,ML Engineer,31088,0 +79311,Female,45,Bachelors,14,52,62,28,59,2.0,3,75,Urban,Data Analyst,42123,0 +79312,Male,45,Bachelors,17,45,4,91,25,2.0,4,38,Rural,ML Engineer,122982,0 +79313,Male,48,Bachelors,16,56,83,83,5,3.0,0,4,Semi-Urban,Software Engineer,90816,0 +79314,Male,23,Bachelors,12,74,93,32,35,2.0,1,89,Rural,ML Engineer,66685,1 +79315,Male,42,Diploma,15,45,55,67,23,4.0,5,90,Semi-Urban,Software Engineer,108714,1 +79316,Male,34,Diploma,9,92,88,13,7,6.0,7,45,Rural,Data Analyst,83675,1 +79317,Male,38,Masters,3,68,53,19,10,3.0,7,13,Semi-Urban,Manager,31464,0 +79318,Male,48,PhD,13,26,20,18,35,4.0,7,97,Urban,ML Engineer,106899,0 +79319,Female,22,Diploma,8,14,3,42,63,4.0,4,54,Urban,HR Executive,124402,0 +79320,Male,25,Masters,19,55,92,32,10,0.0,4,92,Semi-Urban,Data Analyst,144929,1 +79321,Male,37,Diploma,14,22,79,85,17,5.0,4,15,Urban,HR Executive,121149,0 +79322,Male,33,Bachelors,2,79,22,12,78,9.0,1,52,Urban,ML Engineer,52785,0 +79323,Other,58,Bachelors,16,16,83,77,51,7.0,0,66,Rural,ML Engineer,25549,1 +79324,Male,51,Bachelors,16,27,92,74,11,0.0,6,40,Urban,Software Engineer,36859,0 +79325,Male,45,Bachelors,11,91,36,53,80,1.0,4,84,Semi-Urban,HR Executive,95652,1 +79326,Male,26,High School,10,9,49,71,89,0.0,0,5,Rural,HR Executive,54123,0 +79327,Male,29,Diploma,11,58,77,29,37,4.0,1,36,Semi-Urban,ML Engineer,86899,0 +79328,Male,45,Masters,17,77,73,48,67,4.0,4,17,Semi-Urban,Data Analyst,118970,0 +79329,Female,33,High School,3,7,91,70,97,2.0,1,93,Urban,HR Executive,137094,1 +79330,Male,33,Bachelors,4,92,3,55,43,7.0,7,6,Semi-Urban,Manager,121139,0 +79331,Female,43,PhD,14,82,67,10,47,0.0,6,60,Urban,Data Analyst,55032,0 +79332,Male,56,Diploma,15,28,44,98,25,4.0,5,81,Urban,HR Executive,85644,1 +79333,Male,32,High School,8,50,55,58,42,4.0,6,50,Rural,Data Analyst,47424,0 +79334,Other,33,Masters,14,82,3,0,66,7.0,1,5,Urban,Data Analyst,123497,0 +79335,Male,26,Bachelors,10,68,13,53,96,2.0,0,48,Rural,Manager,26946,0 +79336,Male,39,Bachelors,19,65,55,33,79,0.0,5,48,Rural,HR Executive,34655,0 +79337,Male,40,Diploma,13,55,69,6,89,5.0,0,79,Rural,ML Engineer,79626,0 +79338,Male,24,Bachelors,6,66,87,54,28,5.0,7,39,Semi-Urban,HR Executive,104139,1 +79339,Female,33,Bachelors,9,38,41,0,5,8.0,6,72,Urban,HR Executive,105333,0 +79340,Male,40,Diploma,0,96,7,51,18,8.0,6,81,Urban,Data Analyst,20191,1 +79341,Female,31,Bachelors,4,61,69,84,89,3.0,5,97,Urban,Data Analyst,137320,1 +79342,Male,53,Diploma,18,27,25,85,91,9.0,7,5,Semi-Urban,Software Engineer,50454,0 +79343,Male,58,Masters,1,49,11,40,94,5.0,1,55,Urban,HR Executive,61880,0 +79344,Male,52,Diploma,0,40,14,61,15,1.0,5,54,Urban,Data Analyst,117534,0 +79345,Female,25,Bachelors,4,86,14,9,10,6.0,6,77,Semi-Urban,Software Engineer,94839,0 +79346,Other,57,Bachelors,18,61,19,3,38,7.0,2,28,Urban,Manager,59498,0 +79347,Male,38,Diploma,8,87,14,60,4,7.0,0,91,Rural,Software Engineer,23317,1 +79348,Male,33,Masters,8,72,11,69,40,5.0,7,71,Rural,HR Executive,53317,0 +79349,Female,32,Masters,15,70,64,29,20,8.0,1,29,Urban,Data Analyst,106246,0 +79350,Male,50,Bachelors,16,98,52,99,94,6.0,6,8,Urban,Software Engineer,93620,1 +79351,Male,36,Bachelors,13,7,82,26,87,6.0,6,57,Semi-Urban,HR Executive,109712,0 +79352,Female,47,Bachelors,0,76,27,30,3,0.0,5,5,Rural,Data Analyst,101606,0 +79353,Other,25,Masters,7,77,14,41,82,4.0,1,40,Rural,ML Engineer,38434,0 +79354,Male,27,High School,9,13,9,30,84,8.0,7,89,Urban,Data Analyst,98196,0 +79355,Male,48,Masters,5,27,79,99,47,4.0,2,98,Urban,Software Engineer,75129,1 +79356,Female,39,Bachelors,9,74,53,87,34,5.0,1,16,Semi-Urban,ML Engineer,30878,0 +79357,Male,50,Bachelors,19,56,25,35,47,5.0,1,34,Urban,Data Analyst,50840,0 +79358,Male,26,Masters,16,32,40,97,26,5.0,7,28,Urban,HR Executive,145256,0 +79359,Male,48,Masters,2,55,69,20,15,5.0,4,0,Urban,Software Engineer,126075,0 +79360,Female,33,Bachelors,7,44,60,85,40,6.0,0,4,Rural,Manager,28261,0 +79361,Male,25,Diploma,5,10,32,6,10,9.0,7,12,Rural,ML Engineer,51297,0 +79362,Male,50,Diploma,18,55,94,85,92,3.0,4,94,Urban,Data Analyst,135533,1 +79363,Male,44,Bachelors,3,89,21,57,16,4.0,0,82,Urban,HR Executive,116980,1 +79364,Female,27,Diploma,13,18,46,70,34,8.0,4,26,Rural,Data Analyst,22613,0 +79365,Female,52,Diploma,18,15,58,71,42,2.0,7,53,Semi-Urban,Software Engineer,67187,0 +79366,Female,24,PhD,6,70,92,3,3,2.0,1,55,Rural,HR Executive,95293,0 +79367,Female,26,PhD,17,11,41,88,66,0.0,7,69,Rural,ML Engineer,70024,0 +79368,Male,25,Bachelors,17,22,80,92,98,3.0,2,10,Urban,ML Engineer,29422,0 +79369,Male,47,Masters,14,54,83,39,60,2.0,4,8,Urban,ML Engineer,69031,0 +79370,Female,29,High School,3,59,96,95,17,8.0,7,40,Urban,ML Engineer,132525,1 +79371,Female,48,Diploma,17,95,49,97,55,0.0,2,15,Rural,ML Engineer,42664,1 +79372,Female,52,Masters,13,38,70,13,95,3.0,2,83,Semi-Urban,HR Executive,40470,0 +79373,Female,37,High School,19,71,8,30,74,8.0,2,69,Urban,ML Engineer,109347,0 +79374,Male,47,High School,9,45,94,56,95,9.0,1,42,Semi-Urban,HR Executive,26368,1 +79375,Male,37,Bachelors,19,56,3,85,8,3.0,2,18,Semi-Urban,ML Engineer,77039,0 +79376,Male,41,High School,7,70,72,84,17,6.0,4,1,Urban,ML Engineer,75915,0 +79377,Male,22,High School,7,48,42,25,57,0.0,3,95,Urban,HR Executive,27258,0 +79378,Male,50,Bachelors,5,25,67,24,25,9.0,3,42,Urban,Data Analyst,77608,0 +79379,Female,58,Masters,16,23,36,64,84,9.0,3,41,Urban,HR Executive,31695,0 +79380,Female,49,Diploma,7,46,41,75,15,1.0,1,30,Semi-Urban,HR Executive,38499,0 +79381,Female,57,PhD,3,14,82,22,77,4.0,4,19,Urban,ML Engineer,112891,0 +79382,Female,57,Diploma,7,44,21,16,84,2.0,7,60,Urban,HR Executive,105656,0 +79383,Male,59,Bachelors,10,16,78,83,51,0.0,5,43,Urban,Data Analyst,25869,0 +79384,Male,59,Bachelors,13,62,23,59,57,4.0,7,51,Semi-Urban,Software Engineer,72378,0 +79385,Male,50,Bachelors,1,54,98,42,48,4.0,2,16,Urban,Software Engineer,100217,0 +79386,Female,25,Bachelors,15,59,1,41,57,8.0,1,41,Urban,Software Engineer,43940,0 +79387,Male,55,High School,15,40,56,50,80,9.0,5,98,Urban,Manager,101904,1 +79388,Female,37,Bachelors,14,90,89,92,58,4.0,0,46,Urban,Data Analyst,125515,1 +79389,Male,54,High School,19,76,70,10,34,0.0,4,9,Semi-Urban,Data Analyst,68423,0 +79390,Male,36,PhD,10,37,59,80,66,0.0,2,27,Semi-Urban,Software Engineer,56713,0 +79391,Female,30,Diploma,18,14,67,58,48,0.0,4,85,Urban,ML Engineer,85475,0 +79392,Female,53,Masters,6,47,80,84,92,2.0,7,7,Semi-Urban,Data Analyst,73653,0 +79393,Male,42,Bachelors,4,24,50,60,89,6.0,3,62,Rural,Data Analyst,33751,0 +79394,Female,42,Diploma,17,79,35,36,3,4.0,0,46,Urban,Software Engineer,26999,0 +79395,Female,30,Bachelors,1,76,10,84,81,1.0,2,3,Rural,Data Analyst,22360,0 +79396,Female,51,High School,11,5,13,34,57,9.0,7,9,Urban,ML Engineer,106297,0 +79397,Male,34,High School,13,22,40,66,31,5.0,4,82,Semi-Urban,HR Executive,74471,0 +79398,Male,40,Masters,2,9,67,30,96,4.0,4,76,Semi-Urban,Data Analyst,88224,0 +79399,Female,28,Bachelors,7,5,98,6,48,3.0,0,36,Semi-Urban,Manager,47247,0 +79400,Male,39,Masters,12,12,46,61,35,8.0,0,4,Urban,Data Analyst,65823,0 +79401,Female,54,Masters,16,72,31,51,97,4.0,2,96,Urban,Manager,141522,1 +79402,Male,30,Bachelors,9,26,69,73,47,0.0,4,14,Rural,HR Executive,122319,0 +79403,Other,55,High School,18,50,23,91,3,9.0,2,40,Urban,HR Executive,128649,0 +79404,Male,41,Bachelors,16,84,98,34,35,9.0,2,46,Semi-Urban,Data Analyst,53510,1 +79405,Male,50,PhD,3,82,3,87,55,2.0,2,18,Semi-Urban,ML Engineer,58009,0 +79406,Male,33,Masters,16,69,22,33,90,4.0,3,79,Urban,Manager,27690,0 +79407,Other,39,Bachelors,17,9,50,30,39,7.0,5,10,Rural,Software Engineer,61195,0 +79408,Male,47,Bachelors,15,50,45,92,68,4.0,5,17,Urban,Data Analyst,124731,0 +79409,Male,48,Diploma,2,20,12,85,6,1.0,7,44,Semi-Urban,Software Engineer,61843,0 +79410,Male,45,Bachelors,12,55,31,48,50,8.0,4,25,Rural,Data Analyst,72414,0 +79411,Male,29,Bachelors,0,83,30,24,7,5.0,1,92,Rural,Data Analyst,41494,0 +79412,Female,40,Bachelors,17,2,95,59,31,3.0,4,12,Semi-Urban,Manager,75159,0 +79413,Female,35,Masters,2,29,20,92,11,6.0,3,26,Urban,ML Engineer,37543,0 +79414,Male,29,Masters,0,75,56,86,3,8.0,2,28,Rural,Manager,50273,1 +79415,Male,21,Bachelors,16,29,89,87,64,1.0,4,85,Urban,ML Engineer,106643,1 +79416,Male,36,Masters,17,20,45,54,13,4.0,0,43,Urban,Software Engineer,46065,0 +79417,Male,31,Diploma,11,46,60,55,36,7.0,3,95,Rural,ML Engineer,109960,1 +79418,Female,41,Masters,13,87,50,9,25,7.0,3,78,Urban,Data Analyst,33080,0 +79419,Male,44,Diploma,19,3,29,71,47,8.0,2,8,Semi-Urban,Software Engineer,120775,0 +79420,Other,26,Diploma,9,43,69,10,44,5.0,6,57,Rural,ML Engineer,143435,0 +79421,Male,41,Bachelors,8,43,9,86,94,1.0,1,87,Urban,HR Executive,124475,0 +79422,Male,27,Bachelors,13,53,61,98,7,6.0,3,86,Urban,Software Engineer,126452,1 +79423,Male,22,Bachelors,1,44,93,77,48,9.0,2,96,Urban,Data Analyst,22628,1 +79424,Female,41,Bachelors,15,99,35,25,43,5.0,4,67,Urban,Manager,121899,0 +79425,Male,35,High School,11,72,0,60,10,2.0,0,63,Urban,Data Analyst,50931,0 +79426,Male,57,Masters,7,22,13,7,53,5.0,3,56,Semi-Urban,HR Executive,90272,0 +79427,Female,35,Bachelors,6,17,77,76,75,3.0,0,2,Urban,Manager,88506,0 +79428,Male,40,High School,11,78,1,24,42,8.0,2,67,Urban,Data Analyst,101399,0 +79429,Female,40,High School,1,69,21,58,97,8.0,6,33,Urban,Software Engineer,43957,0 +79430,Male,59,Bachelors,4,62,50,75,98,2.0,2,91,Urban,ML Engineer,59936,1 +79431,Male,59,Masters,11,34,95,91,50,1.0,2,43,Semi-Urban,HR Executive,148036,1 +79432,Female,44,Diploma,19,65,67,60,16,4.0,6,73,Urban,Manager,125852,1 +79433,Male,55,Bachelors,13,70,81,4,68,9.0,2,58,Urban,Data Analyst,45180,0 +79434,Female,57,High School,2,29,73,38,48,4.0,3,15,Urban,HR Executive,44379,0 +79435,Male,35,Bachelors,16,4,74,53,30,3.0,6,12,Rural,HR Executive,94469,0 +79436,Female,35,Diploma,6,5,2,88,65,6.0,6,29,Semi-Urban,Data Analyst,128044,0 +79437,Male,31,Masters,9,54,49,69,51,4.0,7,26,Urban,Data Analyst,68032,0 +79438,Male,26,Bachelors,15,29,29,81,53,0.0,4,48,Urban,ML Engineer,20758,0 +79439,Female,52,Masters,15,74,19,84,66,2.0,4,46,Semi-Urban,Data Analyst,42565,0 +79440,Male,21,Masters,9,99,60,58,66,1.0,4,28,Urban,Manager,70340,1 +79441,Male,34,Bachelors,16,36,17,36,72,2.0,7,21,Semi-Urban,Manager,86875,0 +79442,Male,56,Bachelors,14,89,52,60,80,0.0,3,17,Urban,Software Engineer,112003,0 +79443,Male,33,Bachelors,13,57,49,70,94,8.0,3,40,Urban,ML Engineer,37040,0 +79444,Male,55,Bachelors,4,65,90,42,30,3.0,2,92,Semi-Urban,Data Analyst,109864,1 +79445,Male,58,Masters,17,28,56,88,71,9.0,5,16,Urban,Manager,103008,0 +79446,Male,31,Bachelors,3,89,5,51,56,9.0,3,23,Urban,ML Engineer,65651,0 +79447,Female,27,High School,10,84,38,25,80,1.0,0,85,Rural,Software Engineer,116782,0 +79448,Male,44,Diploma,8,79,4,95,50,3.0,0,34,Urban,Software Engineer,129453,0 +79449,Male,52,High School,3,30,38,74,20,0.0,2,70,Urban,Data Analyst,118593,0 +79450,Female,47,Diploma,12,52,82,72,18,5.0,3,47,Urban,Data Analyst,107094,1 +79451,Male,56,Bachelors,17,78,42,15,7,7.0,5,20,Urban,ML Engineer,30807,0 +79452,Female,35,Bachelors,12,27,14,90,74,7.0,1,24,Urban,HR Executive,89081,0 +79453,Male,43,Diploma,13,16,74,22,80,0.0,1,4,Semi-Urban,Software Engineer,65105,0 +79454,Female,54,PhD,4,50,84,22,25,7.0,2,33,Urban,HR Executive,64298,0 +79455,Male,48,PhD,12,11,91,95,7,2.0,7,89,Rural,Data Analyst,131494,1 +79456,Male,44,Bachelors,11,89,79,27,89,6.0,5,12,Rural,Software Engineer,21509,0 +79457,Female,21,Diploma,6,8,3,59,79,8.0,2,8,Urban,Manager,28704,0 +79458,Female,58,Bachelors,2,92,19,61,90,1.0,4,27,Urban,HR Executive,56247,0 +79459,Male,36,Diploma,10,64,26,77,3,8.0,0,89,Urban,Software Engineer,93760,1 +79460,Male,59,Bachelors,11,60,43,50,71,5.0,5,84,Semi-Urban,HR Executive,82717,1 +79461,Male,31,Bachelors,5,50,90,29,70,0.0,6,56,Semi-Urban,Software Engineer,41076,0 +79462,Female,50,Bachelors,5,69,84,43,10,6.0,6,18,Urban,ML Engineer,63434,0 +79463,Female,54,Bachelors,9,56,50,68,37,7.0,4,51,Urban,ML Engineer,110481,0 +79464,Male,46,High School,1,15,57,39,80,5.0,5,63,Urban,ML Engineer,107423,0 +79465,Male,31,Masters,19,28,5,39,99,7.0,4,6,Rural,Data Analyst,55883,0 +79466,Male,58,Bachelors,14,47,25,89,7,3.0,5,24,Urban,Data Analyst,69797,0 +79467,Male,25,Diploma,6,60,48,99,39,2.0,7,7,Rural,Manager,96073,0 +79468,Male,32,Bachelors,10,50,57,46,49,3.0,4,31,Semi-Urban,Software Engineer,51798,0 +79469,Male,55,Bachelors,11,45,71,72,71,6.0,6,53,Rural,HR Executive,85402,1 +79470,Male,25,Bachelors,9,86,63,5,38,8.0,6,69,Urban,Data Analyst,128558,0 +79471,Male,58,Bachelors,5,63,89,8,74,3.0,3,37,Urban,Data Analyst,54123,0 +79472,Female,58,High School,2,28,27,25,62,7.0,3,10,Urban,Manager,23273,0 +79473,Female,53,Bachelors,1,15,20,31,91,1.0,0,91,Urban,Data Analyst,77363,0 +79474,Female,34,Bachelors,13,3,68,66,22,0.0,6,81,Urban,Data Analyst,145488,0 +79475,Female,54,Diploma,16,62,62,99,26,6.0,4,10,Urban,Data Analyst,81517,0 +79476,Other,26,Masters,10,96,33,61,30,3.0,7,67,Rural,Software Engineer,23473,1 +79477,Male,25,Diploma,18,55,77,66,12,5.0,3,73,Semi-Urban,Manager,33524,1 +79478,Male,43,Diploma,11,11,48,41,63,6.0,7,11,Rural,Data Analyst,28263,0 +79479,Male,43,Masters,11,75,28,18,67,1.0,6,89,Semi-Urban,ML Engineer,125487,0 +79480,Male,57,Diploma,17,33,8,28,33,0.0,6,39,Semi-Urban,Data Analyst,119960,0 +79481,Female,31,Bachelors,4,96,48,77,63,7.0,0,8,Urban,Software Engineer,52917,0 +79482,Male,27,Bachelors,14,13,18,47,75,2.0,7,6,Semi-Urban,Manager,134531,0 +79483,Male,35,Diploma,5,25,55,88,64,0.0,2,55,Urban,Manager,29613,0 +79484,Female,31,Masters,11,58,16,82,53,1.0,6,1,Urban,HR Executive,56862,0 +79485,Female,46,Masters,4,41,4,22,82,1.0,0,85,Semi-Urban,ML Engineer,98162,0 +79486,Female,26,Diploma,14,64,49,26,20,1.0,0,46,Semi-Urban,Data Analyst,67404,0 +79487,Male,28,Masters,15,60,36,0,41,9.0,0,30,Urban,Data Analyst,38977,0 +79488,Female,43,PhD,18,78,51,96,20,9.0,1,53,Urban,Software Engineer,110633,1 +79489,Male,28,Diploma,0,68,80,28,84,7.0,0,31,Rural,ML Engineer,106262,0 +79490,Male,35,Diploma,17,4,85,86,33,8.0,0,22,Semi-Urban,Data Analyst,88470,0 +79491,Male,49,Bachelors,19,30,41,24,43,9.0,2,24,Semi-Urban,HR Executive,28074,0 +79492,Male,45,Bachelors,17,70,31,40,83,5.0,0,53,Urban,HR Executive,49824,0 +79493,Male,25,PhD,13,56,68,74,4,8.0,4,5,Urban,HR Executive,111548,0 +79494,Male,26,Masters,7,47,99,97,50,9.0,6,87,Rural,Data Analyst,94025,1 +79495,Male,30,Bachelors,19,73,10,39,44,8.0,6,41,Semi-Urban,HR Executive,71400,0 +79496,Male,42,Diploma,1,7,1,59,89,8.0,6,8,Urban,ML Engineer,67181,0 +79497,Other,55,Bachelors,16,1,95,90,44,1.0,0,7,Urban,Manager,113596,0 +79498,Male,33,Bachelors,19,31,4,20,96,7.0,2,9,Rural,Data Analyst,73564,0 +79499,Male,25,Bachelors,11,50,28,91,44,0.0,6,43,Urban,Software Engineer,140545,0 +79500,Male,58,Masters,9,97,23,50,37,5.0,0,42,Urban,HR Executive,96399,0 +79501,Male,24,Diploma,4,94,84,7,44,7.0,7,44,Rural,HR Executive,88337,0 +79502,Male,22,Bachelors,17,3,85,46,76,3.0,3,99,Urban,Data Analyst,67674,0 +79503,Female,23,Bachelors,18,1,86,96,12,1.0,4,56,Urban,Software Engineer,119098,0 +79504,Female,26,Diploma,17,46,67,40,65,0.0,6,74,Semi-Urban,HR Executive,20236,0 +79505,Other,35,Bachelors,9,38,68,75,94,9.0,5,34,Rural,HR Executive,43666,0 +79506,Male,44,Diploma,4,30,83,76,31,2.0,3,25,Urban,HR Executive,80601,0 +79507,Male,21,PhD,17,50,20,58,26,4.0,6,14,Semi-Urban,HR Executive,29605,0 +79508,Female,30,PhD,6,65,4,73,58,7.0,2,40,Urban,Data Analyst,59500,0 +79509,Male,43,Bachelors,19,29,50,71,21,2.0,7,88,Semi-Urban,Data Analyst,30117,1 +79510,Female,44,Masters,15,6,49,25,96,9.0,2,11,Semi-Urban,Manager,132990,0 +79511,Male,37,Diploma,5,74,51,72,35,6.0,4,70,Urban,Data Analyst,75290,1 +79512,Male,50,Masters,15,29,66,21,77,0.0,6,44,Semi-Urban,HR Executive,116175,0 +79513,Female,37,Bachelors,17,78,46,62,69,1.0,4,48,Urban,Data Analyst,126353,0 +79514,Male,35,Diploma,2,42,56,15,61,5.0,7,43,Urban,Data Analyst,33261,0 +79515,Male,33,Diploma,7,18,42,7,70,6.0,3,85,Rural,Manager,127251,0 +79516,Male,55,Masters,10,4,50,31,68,8.0,7,55,Urban,Software Engineer,115565,0 +79517,Male,52,Bachelors,3,66,19,9,75,4.0,7,8,Semi-Urban,ML Engineer,131417,0 +79518,Other,36,Masters,13,96,82,82,94,7.0,6,30,Urban,Software Engineer,55074,1 +79519,Male,36,High School,6,15,79,33,38,9.0,5,0,Semi-Urban,ML Engineer,27215,0 +79520,Male,38,Bachelors,3,71,60,72,97,0.0,2,29,Semi-Urban,HR Executive,78851,0 +79521,Male,58,PhD,14,8,91,79,39,9.0,1,47,Urban,HR Executive,40837,0 +79522,Male,25,Bachelors,17,31,57,81,94,1.0,4,95,Urban,Data Analyst,90414,1 +79523,Male,23,Masters,4,30,66,31,80,8.0,5,32,Rural,Software Engineer,55883,0 +79524,Female,58,PhD,0,60,19,90,56,1.0,2,36,Rural,ML Engineer,56073,0 +79525,Male,49,Bachelors,3,85,11,36,25,3.0,5,48,Rural,Data Analyst,30021,0 +79526,Male,25,Diploma,16,5,64,81,51,7.0,3,34,Rural,Data Analyst,65774,0 +79527,Female,23,Masters,16,27,69,48,34,1.0,1,19,Semi-Urban,Data Analyst,120378,0 +79528,Male,28,Bachelors,0,2,78,89,23,7.0,4,70,Urban,HR Executive,63559,1 +79529,Female,58,High School,14,55,73,67,45,5.0,3,58,Urban,ML Engineer,65582,1 +79530,Female,48,High School,13,1,5,15,29,7.0,1,99,Rural,ML Engineer,67826,0 +79531,Other,40,Masters,4,31,37,67,3,5.0,4,1,Rural,Manager,33401,0 +79532,Male,36,Bachelors,12,46,81,76,68,1.0,2,44,Semi-Urban,HR Executive,133877,1 +79533,Male,55,High School,5,99,41,42,19,4.0,2,50,Urban,Data Analyst,113416,0 +79534,Male,24,Bachelors,8,0,30,17,98,0.0,4,80,Urban,HR Executive,53371,0 +79535,Male,54,Diploma,8,8,3,6,39,9.0,4,3,Rural,Data Analyst,101630,0 +79536,Female,39,High School,12,9,78,24,78,5.0,4,60,Semi-Urban,Manager,108641,0 +79537,Male,54,Diploma,14,52,71,6,56,9.0,0,20,Semi-Urban,HR Executive,34553,0 +79538,Male,49,Bachelors,1,56,63,91,49,1.0,3,83,Urban,Software Engineer,91293,1 +79539,Male,49,Bachelors,7,9,10,93,1,1.0,6,94,Rural,ML Engineer,93241,0 +79540,Female,25,Masters,4,74,77,46,80,7.0,1,43,Urban,Data Analyst,137334,0 +79541,Female,34,High School,3,35,95,50,52,0.0,3,67,Urban,Data Analyst,101829,1 +79542,Female,44,Diploma,12,13,57,27,2,0.0,4,50,Urban,HR Executive,73919,0 +79543,Male,26,High School,13,81,64,75,55,2.0,2,83,Rural,Manager,98055,1 +79544,Female,36,Bachelors,7,4,99,17,85,8.0,5,10,Semi-Urban,HR Executive,33824,0 +79545,Male,30,Bachelors,10,67,65,39,91,1.0,6,24,Urban,Software Engineer,58498,0 +79546,Female,41,Bachelors,16,91,49,84,0,9.0,1,22,Semi-Urban,Manager,107178,1 +79547,Male,36,High School,3,32,70,78,67,1.0,7,98,Urban,Manager,123766,1 +79548,Male,48,Masters,6,71,1,53,38,2.0,0,23,Rural,Software Engineer,122895,0 +79549,Male,39,Diploma,15,27,91,42,29,4.0,5,51,Urban,Manager,41766,0 +79550,Female,39,Bachelors,8,43,13,3,36,1.0,7,18,Urban,Manager,39434,0 +79551,Male,48,Masters,17,71,71,17,73,1.0,5,49,Urban,Data Analyst,47426,0 +79552,Male,32,Diploma,9,43,89,17,63,5.0,3,45,Semi-Urban,ML Engineer,86364,0 +79553,Female,36,Masters,13,94,65,81,2,1.0,0,63,Semi-Urban,Data Analyst,105870,1 +79554,Male,23,Masters,12,53,4,86,29,7.0,4,87,Semi-Urban,Manager,76759,0 +79555,Other,46,High School,7,27,60,8,63,2.0,0,63,Semi-Urban,Software Engineer,37391,0 +79556,Male,27,High School,14,55,74,94,26,9.0,4,67,Semi-Urban,Software Engineer,121512,1 +79557,Male,50,Bachelors,0,21,11,3,65,8.0,6,29,Urban,HR Executive,46189,0 +79558,Female,38,Masters,16,5,26,80,37,8.0,4,32,Urban,Software Engineer,96254,0 +79559,Male,43,Diploma,3,88,86,61,43,9.0,5,43,Urban,Data Analyst,90455,1 +79560,Male,25,PhD,4,62,82,11,11,2.0,4,32,Urban,Software Engineer,33683,0 +79561,Female,48,Diploma,11,11,95,97,17,0.0,5,83,Urban,Software Engineer,145685,1 +79562,Male,48,Bachelors,4,72,75,90,73,1.0,5,73,Urban,Data Analyst,133006,1 +79563,Female,59,Bachelors,16,84,60,10,31,5.0,1,4,Urban,Data Analyst,28902,0 +79564,Male,37,High School,19,33,95,0,19,9.0,2,25,Rural,HR Executive,38074,0 +79565,Male,24,Bachelors,17,84,21,0,84,6.0,6,41,Rural,Data Analyst,65737,0 +79566,Male,42,Bachelors,17,86,23,86,49,4.0,4,22,Semi-Urban,Software Engineer,108133,0 +79567,Female,37,Bachelors,19,2,72,12,81,3.0,3,22,Urban,Data Analyst,111555,0 +79568,Female,30,Masters,12,41,97,49,30,3.0,1,60,Urban,Software Engineer,113617,1 +79569,Male,46,High School,5,70,63,68,82,8.0,1,38,Rural,Data Analyst,88982,1 +79570,Male,46,Diploma,18,52,39,3,69,4.0,7,22,Semi-Urban,Data Analyst,109115,0 +79571,Male,28,Bachelors,2,45,57,6,32,5.0,1,0,Urban,HR Executive,106035,0 +79572,Female,58,Diploma,2,14,59,87,64,4.0,0,80,Rural,HR Executive,84806,0 +79573,Male,33,Masters,2,5,72,26,14,5.0,7,82,Urban,Software Engineer,38186,0 +79574,Male,28,Bachelors,14,16,98,52,20,1.0,4,99,Rural,HR Executive,57432,1 +79575,Other,40,Bachelors,5,69,21,85,34,2.0,5,53,Urban,Data Analyst,121362,0 +79576,Female,21,PhD,18,87,0,35,21,8.0,6,15,Rural,Manager,64101,0 +79577,Male,41,Diploma,12,43,89,90,83,3.0,5,37,Urban,HR Executive,51886,1 +79578,Female,47,Masters,0,90,12,86,65,2.0,1,28,Semi-Urban,HR Executive,86527,0 +79579,Male,27,Bachelors,7,53,85,8,2,1.0,4,69,Urban,ML Engineer,94273,0 +79580,Male,27,Bachelors,6,81,96,82,62,9.0,6,75,Rural,Data Analyst,132928,1 +79581,Female,59,Bachelors,9,48,90,50,30,5.0,5,70,Urban,ML Engineer,41332,1 +79582,Male,29,Masters,16,15,76,49,60,4.0,6,34,Semi-Urban,Software Engineer,138138,0 +79583,Male,25,Bachelors,2,91,20,12,69,7.0,3,68,Urban,Data Analyst,124738,0 +79584,Female,57,Masters,3,72,24,0,88,2.0,4,40,Urban,HR Executive,123325,0 +79585,Male,39,Bachelors,19,47,61,35,66,9.0,0,30,Semi-Urban,ML Engineer,133288,0 +79586,Male,55,PhD,1,14,59,18,90,3.0,3,5,Urban,HR Executive,55494,0 +79587,Male,57,High School,12,83,65,22,51,6.0,0,0,Urban,ML Engineer,65920,0 +79588,Male,25,Bachelors,5,14,73,32,96,3.0,7,21,Urban,Manager,64650,0 +79589,Female,44,Bachelors,17,98,48,18,34,3.0,0,80,Rural,Manager,42735,1 +79590,Male,32,Bachelors,1,22,51,43,79,7.0,0,19,Rural,Software Engineer,115288,0 +79591,Male,50,Bachelors,7,62,67,20,91,6.0,1,70,Rural,Manager,118470,0 +79592,Male,31,Bachelors,10,64,81,61,60,2.0,3,33,Semi-Urban,ML Engineer,133670,1 +79593,Male,39,Masters,8,81,39,41,67,8.0,4,59,Urban,Data Analyst,102288,0 +79594,Male,44,Diploma,14,63,43,81,21,1.0,4,77,Rural,ML Engineer,47513,1 +79595,Male,56,Bachelors,13,84,63,61,86,0.0,3,21,Urban,Manager,21476,0 +79596,Male,47,Bachelors,2,62,79,90,54,2.0,1,95,Urban,HR Executive,123655,1 +79597,Female,30,Bachelors,6,48,4,83,72,5.0,2,0,Semi-Urban,ML Engineer,122146,0 +79598,Female,32,PhD,9,13,41,29,40,6.0,4,87,Urban,HR Executive,49100,0 +79599,Female,37,High School,13,75,66,15,53,6.0,7,81,Rural,Manager,85635,0 +79600,Male,27,Diploma,14,89,44,96,60,0.0,5,43,Urban,Software Engineer,92659,1 +79601,Female,48,Bachelors,9,21,98,71,44,4.0,5,54,Urban,Software Engineer,109435,1 +79602,Female,38,Masters,3,80,2,24,24,2.0,0,56,Urban,Data Analyst,55512,0 +79603,Male,52,High School,9,85,96,15,83,6.0,2,18,Rural,HR Executive,37378,0 +79604,Male,25,Masters,18,13,73,74,6,3.0,4,59,Urban,Manager,115193,0 +79605,Male,26,High School,16,13,84,33,74,5.0,1,72,Urban,Data Analyst,107854,0 +79606,Male,32,PhD,19,27,36,89,54,5.0,7,48,Urban,Data Analyst,74550,0 +79607,Male,53,Bachelors,15,59,39,43,32,2.0,6,79,Rural,ML Engineer,86431,0 +79608,Male,59,High School,0,72,54,46,65,4.0,3,7,Urban,Manager,43900,0 +79609,Male,26,High School,18,99,88,49,50,0.0,5,26,Urban,HR Executive,55962,1 +79610,Female,47,Diploma,12,87,97,21,36,2.0,3,86,Semi-Urban,Manager,32024,1 +79611,Male,31,Bachelors,7,87,54,35,49,0.0,6,70,Urban,HR Executive,120498,1 +79612,Male,23,Bachelors,15,46,43,98,46,1.0,5,29,Rural,Manager,27878,0 +79613,Female,40,Masters,14,83,44,20,69,4.0,0,98,Rural,Manager,103405,1 +79614,Male,58,High School,7,15,76,55,47,1.0,7,13,Rural,Software Engineer,109837,0 +79615,Male,21,High School,19,96,29,50,34,9.0,4,88,Urban,Software Engineer,89984,1 +79616,Male,46,Bachelors,13,74,44,68,24,0.0,1,2,Urban,Manager,30019,0 +79617,Male,37,Bachelors,10,23,95,45,43,1.0,7,62,Urban,Data Analyst,118838,0 +79618,Female,29,Bachelors,8,40,97,24,3,8.0,2,85,Rural,HR Executive,55002,1 +79619,Male,26,Masters,10,20,87,21,97,4.0,4,7,Urban,Software Engineer,81663,0 +79620,Female,55,Bachelors,13,51,11,71,49,3.0,6,36,Rural,Data Analyst,95618,0 +79621,Male,59,Diploma,7,97,30,46,99,0.0,3,68,Rural,Data Analyst,67358,1 +79622,Female,50,High School,15,21,83,73,43,3.0,6,52,Rural,ML Engineer,78964,0 +79623,Female,58,Masters,9,50,59,38,14,4.0,4,23,Urban,HR Executive,137117,0 +79624,Male,43,Bachelors,7,24,3,49,69,0.0,3,50,Urban,ML Engineer,59134,0 +79625,Male,53,Masters,17,81,76,94,46,3.0,5,6,Urban,Software Engineer,47628,1 +79626,Male,42,PhD,6,3,10,92,37,0.0,4,96,Urban,Software Engineer,68398,0 +79627,Male,31,High School,8,29,38,50,84,6.0,0,76,Semi-Urban,Manager,68949,0 +79628,Male,29,Bachelors,11,51,69,54,99,9.0,4,59,Urban,Manager,106553,0 +79629,Male,21,Bachelors,6,90,8,45,49,6.0,1,27,Urban,Data Analyst,33145,0 +79630,Male,52,Bachelors,13,40,56,87,55,2.0,4,24,Urban,ML Engineer,55846,0 +79631,Male,46,Masters,17,28,11,83,68,0.0,0,90,Urban,ML Engineer,109140,0 +79632,Female,51,PhD,8,46,50,81,27,8.0,7,22,Urban,Manager,145074,0 +79633,Male,54,Diploma,7,68,7,44,80,7.0,3,55,Semi-Urban,ML Engineer,148077,0 +79634,Male,46,Bachelors,3,64,59,58,15,2.0,5,72,Urban,HR Executive,131544,1 +79635,Male,53,Bachelors,8,79,17,12,40,9.0,2,9,Urban,Data Analyst,45139,0 +79636,Female,22,High School,16,63,90,11,31,6.0,1,27,Urban,HR Executive,66630,0 +79637,Female,31,Masters,18,18,70,20,72,1.0,5,6,Semi-Urban,Manager,29734,0 +79638,Female,37,Bachelors,9,60,18,61,24,2.0,4,23,Rural,ML Engineer,121626,0 +79639,Other,25,Bachelors,19,23,22,89,76,1.0,2,27,Semi-Urban,ML Engineer,118784,0 +79640,Male,27,Masters,7,98,52,69,36,3.0,1,30,Semi-Urban,Data Analyst,87569,1 +79641,Male,27,High School,4,22,63,58,98,9.0,6,1,Rural,Manager,139980,0 +79642,Female,28,Diploma,19,96,0,92,20,4.0,6,88,Urban,ML Engineer,45956,1 +79643,Male,29,Diploma,15,95,38,87,15,5.0,0,86,Semi-Urban,ML Engineer,66606,1 +79644,Female,45,PhD,15,61,61,37,78,9.0,4,35,Semi-Urban,ML Engineer,74414,0 +79645,Male,48,Bachelors,10,8,47,82,85,6.0,3,72,Urban,HR Executive,90722,0 +79646,Other,55,Bachelors,17,93,15,70,22,0.0,3,33,Urban,ML Engineer,64869,0 +79647,Male,37,Bachelors,1,51,75,83,22,8.0,0,75,Rural,Software Engineer,127895,1 +79648,Male,54,Bachelors,8,19,20,30,33,7.0,3,57,Semi-Urban,HR Executive,64618,0 +79649,Male,42,High School,16,5,89,96,16,8.0,2,22,Urban,ML Engineer,101827,0 +79650,Male,40,Masters,12,20,89,96,75,5.0,1,63,Semi-Urban,Software Engineer,72089,1 +79651,Female,56,Masters,3,98,26,63,84,8.0,0,13,Semi-Urban,HR Executive,92843,0 +79652,Male,40,PhD,14,95,5,9,60,2.0,2,28,Urban,Software Engineer,136652,0 +79653,Female,46,PhD,5,6,88,19,80,3.0,6,99,Urban,Data Analyst,104969,0 +79654,Female,46,High School,12,6,13,39,61,5.0,6,79,Urban,HR Executive,52093,0 +79655,Male,47,Masters,7,46,31,38,45,7.0,4,38,Rural,Data Analyst,145601,0 +79656,Other,24,Bachelors,6,94,14,17,6,2.0,5,61,Rural,ML Engineer,33984,0 +79657,Female,58,Bachelors,10,30,98,54,99,7.0,3,30,Urban,Manager,63930,0 +79658,Female,44,Bachelors,7,98,68,13,99,6.0,2,63,Rural,ML Engineer,75524,1 +79659,Other,42,Masters,10,12,48,63,9,9.0,7,78,Urban,Manager,105557,0 +79660,Male,51,Bachelors,8,5,85,95,89,3.0,3,63,Urban,Data Analyst,39864,1 +79661,Male,56,Masters,4,26,49,22,45,7.0,6,6,Semi-Urban,ML Engineer,148037,0 +79662,Male,25,Bachelors,15,46,74,90,67,4.0,7,56,Semi-Urban,HR Executive,137770,1 +79663,Female,43,High School,1,57,92,78,8,7.0,7,21,Urban,Manager,48822,1 +79664,Female,48,Bachelors,5,14,51,91,15,2.0,3,34,Rural,Software Engineer,122211,0 +79665,Female,59,Bachelors,3,49,6,74,83,2.0,7,47,Urban,Software Engineer,133823,0 +79666,Male,57,Diploma,3,66,7,15,74,3.0,1,60,Rural,ML Engineer,124448,0 +79667,Male,51,Masters,15,30,91,44,3,4.0,7,72,Rural,Data Analyst,26685,1 +79668,Male,40,Bachelors,19,22,2,8,21,6.0,0,81,Urban,Data Analyst,55523,0 +79669,Male,47,Bachelors,14,89,65,13,40,9.0,2,54,Semi-Urban,ML Engineer,67835,0 +79670,Female,37,Bachelors,0,30,9,63,22,7.0,5,28,Urban,Software Engineer,57857,0 +79671,Male,39,Bachelors,8,25,38,9,12,6.0,0,77,Urban,HR Executive,88611,0 +79672,Female,41,Bachelors,4,98,32,0,28,4.0,0,25,Urban,Data Analyst,45105,0 +79673,Male,43,Diploma,10,38,12,72,99,1.0,4,68,Rural,Software Engineer,77100,0 +79674,Male,27,PhD,3,30,19,90,20,4.0,0,93,Rural,Software Engineer,112619,0 +79675,Female,37,Bachelors,8,44,16,64,83,0.0,6,16,Urban,Data Analyst,30105,0 +79676,Male,33,Diploma,6,44,34,29,50,1.0,5,87,Rural,Software Engineer,54061,0 +79677,Female,58,Masters,2,90,38,76,4,2.0,7,26,Semi-Urban,Software Engineer,77418,0 +79678,Male,43,Bachelors,16,21,46,84,69,1.0,3,63,Semi-Urban,HR Executive,132120,0 +79679,Male,40,Masters,0,28,83,38,66,9.0,4,37,Urban,ML Engineer,46282,0 +79680,Female,51,Masters,15,14,81,68,33,0.0,4,75,Urban,Data Analyst,73635,0 +79681,Female,35,High School,16,9,65,69,20,7.0,2,25,Urban,Manager,89168,0 +79682,Other,23,High School,11,37,6,89,15,7.0,0,22,Urban,HR Executive,96315,0 +79683,Female,43,Bachelors,8,61,87,78,41,5.0,5,16,Urban,Data Analyst,49330,1 +79684,Male,37,Bachelors,1,79,2,33,14,6.0,5,30,Urban,Data Analyst,139122,0 +79685,Male,41,Bachelors,1,74,31,68,79,3.0,4,21,Rural,ML Engineer,59002,0 +79686,Male,54,Bachelors,7,56,35,84,81,6.0,7,45,Urban,Manager,89676,0 +79687,Male,35,Diploma,15,62,44,70,59,5.0,3,46,Urban,Software Engineer,27500,0 +79688,Male,34,Diploma,6,62,63,78,57,5.0,6,54,Rural,ML Engineer,128552,1 +79689,Female,26,Masters,13,33,71,41,32,4.0,0,48,Urban,ML Engineer,124875,0 +79690,Female,51,Diploma,12,98,99,15,33,0.0,2,48,Rural,ML Engineer,118922,1 +79691,Other,27,High School,14,16,5,93,35,6.0,1,49,Rural,ML Engineer,27671,0 +79692,Male,31,Bachelors,4,32,68,34,27,1.0,5,64,Urban,Software Engineer,34288,0 +79693,Male,37,Bachelors,5,90,16,21,30,1.0,1,79,Urban,Manager,143919,0 +79694,Female,55,Bachelors,1,20,4,79,35,5.0,7,94,Urban,Manager,126629,0 +79695,Male,38,Masters,3,63,44,73,38,5.0,5,86,Urban,Data Analyst,79665,1 +79696,Male,26,High School,6,82,93,42,39,2.0,2,86,Semi-Urban,Manager,71844,1 +79697,Male,54,Masters,4,46,18,30,51,6.0,5,69,Rural,Manager,25788,0 +79698,Female,53,High School,14,34,41,26,53,6.0,2,55,Urban,Manager,95791,0 +79699,Female,52,Diploma,19,22,75,42,4,2.0,5,45,Urban,Data Analyst,72701,0 +79700,Female,52,Diploma,13,20,9,77,40,7.0,0,41,Semi-Urban,Manager,88789,0 +79701,Female,24,Bachelors,19,72,87,78,13,5.0,5,21,Semi-Urban,Data Analyst,70225,1 +79702,Male,35,High School,7,44,56,91,17,9.0,0,33,Urban,Manager,44000,0 +79703,Male,31,PhD,1,67,82,93,31,8.0,3,18,Semi-Urban,Data Analyst,85281,1 +79704,Male,23,High School,7,76,38,94,30,4.0,7,52,Rural,Manager,112249,1 +79705,Female,55,High School,13,65,28,62,14,4.0,4,69,Urban,Software Engineer,98097,0 +79706,Male,58,PhD,5,8,47,72,51,9.0,7,49,Urban,Manager,74953,0 +79707,Female,54,Bachelors,14,70,97,54,46,8.0,0,15,Rural,ML Engineer,149274,0 +79708,Male,27,Diploma,16,66,72,68,10,5.0,7,11,Semi-Urban,HR Executive,65939,0 +79709,Male,42,Bachelors,2,79,76,30,97,9.0,5,91,Rural,Manager,136391,1 +79710,Female,31,Bachelors,6,16,23,68,64,2.0,2,95,Urban,Manager,147565,0 +79711,Male,48,Diploma,0,48,30,48,8,0.0,0,65,Urban,ML Engineer,124362,0 +79712,Male,50,Masters,7,75,21,86,38,3.0,4,32,Urban,HR Executive,84069,0 +79713,Female,24,Masters,6,23,68,15,85,7.0,5,48,Urban,Data Analyst,57283,0 +79714,Female,27,Bachelors,3,27,69,74,19,9.0,4,86,Urban,Data Analyst,49153,1 +79715,Male,44,Masters,0,67,94,97,37,4.0,4,32,Urban,Data Analyst,69940,1 +79716,Male,40,Masters,7,84,18,9,89,0.0,0,98,Urban,Software Engineer,60310,0 +79717,Male,53,Bachelors,5,67,77,24,17,3.0,1,88,Urban,Software Engineer,53112,1 +79718,Male,48,Masters,3,81,7,60,61,3.0,7,18,Urban,Manager,27084,0 +79719,Male,52,Masters,1,50,3,5,68,9.0,2,92,Semi-Urban,Data Analyst,40706,0 +79720,Female,23,Bachelors,18,82,71,58,49,4.0,3,27,Rural,ML Engineer,28210,0 +79721,Male,43,Masters,15,63,11,14,24,4.0,7,36,Urban,Data Analyst,75196,0 +79722,Male,36,Bachelors,10,74,10,65,70,7.0,7,80,Semi-Urban,Data Analyst,42695,0 +79723,Male,37,Masters,12,95,64,1,38,9.0,2,20,Rural,Manager,86050,0 +79724,Male,25,PhD,13,19,51,3,28,5.0,3,24,Urban,Software Engineer,69736,0 +79725,Male,50,Bachelors,16,87,27,87,40,2.0,3,95,Urban,ML Engineer,25272,1 +79726,Male,37,Bachelors,5,28,25,29,62,1.0,0,48,Urban,HR Executive,42199,0 +79727,Male,53,High School,11,49,11,30,95,5.0,1,5,Urban,Manager,145308,0 +79728,Female,21,Bachelors,8,55,25,9,33,8.0,7,64,Semi-Urban,ML Engineer,48075,0 +79729,Female,30,High School,6,36,17,15,52,3.0,7,58,Urban,Data Analyst,27930,0 +79730,Other,58,High School,18,27,9,8,54,6.0,0,7,Urban,Manager,79537,0 +79731,Female,24,Masters,15,6,54,39,1,3.0,3,52,Semi-Urban,Manager,42487,0 +79732,Other,28,PhD,9,7,73,58,75,5.0,7,37,Semi-Urban,ML Engineer,71713,0 +79733,Male,33,Diploma,8,83,16,68,29,8.0,4,81,Semi-Urban,HR Executive,50033,1 +79734,Male,55,Diploma,5,90,21,8,27,6.0,0,49,Urban,ML Engineer,130858,0 +79735,Male,50,Masters,8,24,34,68,89,1.0,0,17,Semi-Urban,Manager,106118,0 +79736,Male,56,Bachelors,8,5,37,65,43,8.0,3,54,Semi-Urban,HR Executive,59222,0 +79737,Female,39,Bachelors,7,67,58,5,60,5.0,4,50,Urban,HR Executive,141704,0 +79738,Male,23,Diploma,8,73,74,41,35,5.0,2,27,Urban,Manager,25680,0 +79739,Male,37,Bachelors,12,59,31,81,15,9.0,7,97,Rural,Data Analyst,147464,1 +79740,Male,59,Masters,4,87,30,39,29,7.0,7,69,Rural,ML Engineer,71523,0 +79741,Male,39,Masters,19,10,56,37,61,2.0,1,32,Urban,Data Analyst,107465,0 +79742,Male,28,High School,12,98,16,97,18,0.0,5,31,Rural,HR Executive,47295,1 +79743,Male,32,PhD,18,50,21,76,16,4.0,3,60,Rural,Data Analyst,88573,0 +79744,Male,51,Masters,11,22,85,92,83,4.0,1,68,Rural,HR Executive,56782,1 +79745,Female,54,Diploma,15,87,9,54,20,3.0,5,73,Urban,Software Engineer,47011,0 +79746,Male,49,Diploma,2,65,89,5,78,6.0,3,42,Rural,Data Analyst,82800,0 +79747,Male,21,Diploma,12,34,41,28,51,7.0,1,7,Urban,Software Engineer,51254,0 +79748,Male,34,Bachelors,16,61,66,91,41,5.0,2,83,Urban,ML Engineer,73612,1 +79749,Male,29,Masters,9,78,10,3,9,0.0,3,68,Urban,Manager,120627,0 +79750,Male,31,Bachelors,8,49,80,43,15,6.0,6,65,Rural,Software Engineer,61185,1 +79751,Female,52,Diploma,16,19,79,23,90,1.0,7,79,Rural,Software Engineer,85944,0 +79752,Other,30,Diploma,13,4,3,46,30,4.0,6,62,Urban,Software Engineer,108286,0 +79753,Female,25,Bachelors,4,67,5,43,97,1.0,0,35,Rural,Data Analyst,35207,0 +79754,Female,26,Diploma,15,74,45,65,20,6.0,5,65,Semi-Urban,ML Engineer,87126,1 +79755,Female,58,High School,4,75,69,37,18,5.0,6,38,Rural,Manager,125865,0 +79756,Male,57,Bachelors,2,66,47,19,17,7.0,0,97,Urban,Manager,122593,0 +79757,Female,44,Bachelors,3,95,36,31,35,4.0,1,31,Rural,Manager,126320,0 +79758,Female,48,High School,2,51,56,97,99,8.0,5,57,Urban,ML Engineer,40481,1 +79759,Male,33,Bachelors,17,91,86,57,94,3.0,3,71,Semi-Urban,Software Engineer,122652,1 +79760,Female,34,High School,17,26,44,12,53,2.0,5,22,Urban,Data Analyst,113989,0 +79761,Other,50,Bachelors,14,31,93,92,83,3.0,4,50,Urban,HR Executive,101080,1 +79762,Male,55,Bachelors,11,80,98,22,85,1.0,6,37,Urban,HR Executive,40263,1 +79763,Male,57,High School,2,48,92,10,71,4.0,7,82,Urban,HR Executive,127003,0 +79764,Male,36,High School,1,12,15,98,67,6.0,1,58,Urban,Manager,31189,0 +79765,Male,43,Masters,5,64,97,39,8,1.0,3,95,Rural,Software Engineer,23918,1 +79766,Male,55,Diploma,6,18,85,82,50,1.0,7,46,Urban,ML Engineer,52501,0 +79767,Male,28,Bachelors,11,71,62,10,11,4.0,4,27,Semi-Urban,Manager,64177,0 +79768,Male,26,Bachelors,18,14,40,24,80,3.0,5,81,Rural,Software Engineer,109165,0 +79769,Female,47,Bachelors,4,83,11,54,11,9.0,0,72,Urban,Manager,50681,0 +79770,Female,37,Bachelors,14,57,11,86,8,3.0,6,41,Semi-Urban,HR Executive,102708,0 +79771,Male,49,PhD,19,20,14,2,17,3.0,5,62,Rural,Manager,92307,0 +79772,Male,36,Bachelors,9,25,37,68,23,8.0,1,29,Rural,Manager,38974,0 +79773,Female,33,Bachelors,19,58,58,52,69,2.0,5,94,Semi-Urban,Manager,41794,1 +79774,Male,38,Diploma,4,47,99,23,27,0.0,7,32,Semi-Urban,Manager,82154,0 +79775,Male,40,Bachelors,3,54,67,37,66,4.0,3,16,Rural,Manager,52464,0 +79776,Male,46,High School,16,74,7,76,18,3.0,2,93,Urban,ML Engineer,100588,1 +79777,Male,43,Diploma,0,50,98,63,21,2.0,2,37,Semi-Urban,Software Engineer,87581,1 +79778,Female,26,Diploma,13,63,1,60,5,0.0,6,37,Urban,Manager,149611,0 +79779,Female,33,High School,5,1,34,46,82,4.0,7,41,Rural,Manager,100021,0 +79780,Male,45,Bachelors,13,53,22,54,8,0.0,5,13,Urban,ML Engineer,80093,0 +79781,Female,58,Bachelors,6,20,70,87,18,7.0,4,63,Urban,Manager,92261,0 +79782,Male,51,Bachelors,7,25,81,43,14,6.0,2,59,Urban,Manager,64894,0 +79783,Male,31,Bachelors,17,51,23,82,48,1.0,7,46,Semi-Urban,ML Engineer,132730,0 +79784,Male,32,Masters,8,20,11,92,38,2.0,5,60,Rural,Data Analyst,138773,0 +79785,Male,34,Bachelors,13,18,84,91,55,8.0,6,14,Semi-Urban,Manager,79498,0 +79786,Male,38,Bachelors,18,74,14,32,31,6.0,0,57,Urban,Software Engineer,34248,0 +79787,Male,24,Bachelors,0,53,63,72,27,4.0,7,99,Rural,Software Engineer,85748,1 +79788,Male,26,High School,13,5,61,38,51,3.0,5,91,Semi-Urban,HR Executive,111738,0 +79789,Male,23,Masters,10,79,0,66,80,4.0,6,89,Urban,Data Analyst,140915,0 +79790,Male,22,High School,10,37,37,19,61,3.0,3,72,Rural,Manager,70292,0 +79791,Male,39,Diploma,6,9,78,91,53,8.0,2,45,Semi-Urban,Data Analyst,40658,0 +79792,Male,28,Masters,3,51,83,20,66,5.0,7,98,Urban,ML Engineer,35757,1 +79793,Female,28,Bachelors,8,40,9,60,40,0.0,3,23,Urban,Software Engineer,96961,0 +79794,Male,59,High School,7,10,54,55,62,7.0,2,74,Urban,HR Executive,141575,0 +79795,Male,23,Bachelors,15,24,75,9,32,4.0,6,30,Urban,HR Executive,27279,0 +79796,Male,47,High School,3,8,86,92,36,3.0,1,26,Semi-Urban,Manager,73984,0 +79797,Other,43,Bachelors,14,85,65,31,56,0.0,1,22,Semi-Urban,Software Engineer,108013,0 +79798,Male,55,Masters,14,77,16,94,28,4.0,7,46,Urban,Manager,65068,0 +79799,Male,50,Bachelors,6,15,95,30,7,0.0,6,92,Semi-Urban,HR Executive,52303,0 +79800,Male,36,PhD,13,54,0,75,23,6.0,7,34,Urban,Manager,139967,0 +79801,Female,49,Diploma,1,45,74,0,66,4.0,6,0,Semi-Urban,Data Analyst,82398,0 +79802,Male,29,Bachelors,7,8,44,36,77,9.0,1,85,Rural,HR Executive,128561,0 +79803,Female,27,Bachelors,19,15,37,87,7,4.0,5,97,Semi-Urban,HR Executive,41246,0 +79804,Female,43,Masters,3,69,48,48,80,8.0,2,0,Urban,Data Analyst,117984,0 +79805,Male,46,Bachelors,15,32,60,79,0,7.0,1,42,Semi-Urban,HR Executive,104132,0 +79806,Female,55,Bachelors,13,88,34,91,37,3.0,1,36,Semi-Urban,HR Executive,140623,1 +79807,Male,48,PhD,11,18,76,44,84,9.0,1,81,Urban,Manager,110482,0 +79808,Female,43,High School,0,94,21,72,36,6.0,3,6,Urban,ML Engineer,106371,0 +79809,Female,41,Bachelors,18,31,5,61,62,3.0,6,3,Semi-Urban,Software Engineer,23816,0 +79810,Female,55,Bachelors,19,11,50,73,38,5.0,0,33,Urban,Software Engineer,107224,0 +79811,Male,24,Bachelors,11,16,36,10,76,1.0,2,48,Urban,Manager,66341,0 +79812,Male,21,Bachelors,19,80,76,79,3,4.0,4,71,Urban,HR Executive,133931,1 +79813,Male,58,Bachelors,3,98,69,39,16,4.0,7,64,Urban,Data Analyst,70393,1 +79814,Male,59,Bachelors,2,18,36,97,35,3.0,4,1,Rural,ML Engineer,87516,0 +79815,Male,48,Bachelors,2,80,16,68,51,1.0,3,37,Semi-Urban,Manager,128361,0 +79816,Female,57,Masters,12,7,29,50,19,1.0,2,40,Semi-Urban,Software Engineer,84256,0 +79817,Female,37,Bachelors,15,24,39,55,2,9.0,0,53,Urban,ML Engineer,132546,0 +79818,Female,40,Bachelors,6,34,31,61,8,5.0,2,80,Urban,Data Analyst,116518,0 +79819,Male,34,Bachelors,6,66,95,20,33,5.0,4,32,Urban,Software Engineer,135467,0 +79820,Female,39,Bachelors,12,19,4,49,19,5.0,3,95,Urban,Data Analyst,42453,0 +79821,Male,51,Bachelors,14,46,81,46,45,7.0,5,83,Urban,Data Analyst,24363,1 +79822,Female,52,Bachelors,2,4,9,10,86,0.0,2,58,Urban,ML Engineer,22915,0 +79823,Female,51,Bachelors,12,73,81,84,26,9.0,2,19,Urban,Software Engineer,122113,1 +79824,Male,44,Masters,2,25,35,70,26,6.0,5,22,Urban,Data Analyst,69764,0 +79825,Female,41,PhD,9,26,70,22,56,8.0,4,76,Urban,Software Engineer,51634,0 +79826,Female,24,Bachelors,9,62,91,68,13,9.0,5,27,Semi-Urban,Manager,80809,1 +79827,Male,48,Diploma,3,94,75,59,27,6.0,6,64,Urban,ML Engineer,64363,1 +79828,Female,41,Bachelors,15,49,47,87,60,8.0,2,97,Semi-Urban,Data Analyst,126036,1 +79829,Male,26,Masters,16,85,84,50,28,4.0,4,74,Urban,Software Engineer,99513,1 +79830,Male,31,Diploma,17,62,22,17,93,6.0,1,23,Urban,Data Analyst,55343,0 +79831,Male,23,Diploma,12,67,47,51,54,2.0,4,82,Urban,ML Engineer,134069,1 +79832,Female,56,High School,16,16,89,80,44,3.0,0,76,Urban,Data Analyst,48126,1 +79833,Male,32,Masters,12,97,33,36,49,5.0,7,82,Urban,HR Executive,119003,1 +79834,Female,59,Diploma,3,82,31,81,61,4.0,0,98,Rural,HR Executive,138974,1 +79835,Female,34,Bachelors,4,63,81,11,62,9.0,6,13,Urban,Manager,45846,0 +79836,Female,45,Masters,5,45,64,30,53,8.0,0,38,Urban,ML Engineer,102149,0 +79837,Female,57,Diploma,4,2,87,74,24,3.0,3,22,Urban,Software Engineer,104234,0 +79838,Female,22,Masters,16,94,51,70,73,9.0,7,57,Urban,Manager,143661,1 +79839,Male,45,Bachelors,4,78,7,89,99,8.0,5,56,Urban,Software Engineer,126953,0 +79840,Male,34,PhD,2,10,43,61,42,1.0,7,75,Semi-Urban,ML Engineer,116001,0 +79841,Female,41,Bachelors,7,4,67,43,41,3.0,6,2,Rural,HR Executive,146757,0 +79842,Male,58,High School,12,70,47,56,73,1.0,4,81,Rural,Data Analyst,65858,1 +79843,Female,41,Masters,14,95,20,26,63,8.0,6,82,Urban,Data Analyst,115208,0 +79844,Female,41,PhD,0,38,90,29,84,2.0,3,44,Urban,ML Engineer,101947,0 +79845,Male,59,Diploma,18,47,84,53,59,8.0,4,72,Semi-Urban,Data Analyst,81104,1 +79846,Male,48,Bachelors,4,48,61,32,23,0.0,6,14,Urban,Software Engineer,58858,0 +79847,Female,29,Bachelors,9,86,78,59,41,6.0,5,80,Semi-Urban,ML Engineer,39064,1 +79848,Female,25,Bachelors,16,95,43,9,78,6.0,5,52,Semi-Urban,ML Engineer,35852,0 +79849,Male,46,High School,14,1,76,10,61,3.0,0,28,Urban,Software Engineer,44019,0 +79850,Male,30,Bachelors,9,13,85,87,60,4.0,5,50,Semi-Urban,ML Engineer,136289,1 +79851,Male,43,High School,9,92,0,28,56,3.0,7,85,Rural,Data Analyst,57767,0 +79852,Female,36,Masters,3,77,90,86,50,4.0,4,93,Semi-Urban,ML Engineer,73310,1 +79853,Female,47,Masters,10,29,52,3,52,6.0,2,59,Urban,Software Engineer,89848,0 +79854,Male,33,Bachelors,3,81,6,71,17,2.0,1,29,Semi-Urban,Manager,59524,0 +79855,Male,54,Masters,16,70,76,80,92,8.0,4,98,Urban,Data Analyst,46251,1 +79856,Male,23,Masters,7,58,26,23,75,6.0,3,26,Urban,HR Executive,116780,0 +79857,Male,29,Diploma,18,3,44,83,66,0.0,5,16,Semi-Urban,Data Analyst,111008,0 +79858,Female,25,Masters,2,56,94,4,48,3.0,0,32,Semi-Urban,Software Engineer,72055,0 +79859,Male,28,Bachelors,18,41,52,87,77,7.0,7,26,Urban,Software Engineer,132304,0 +79860,Other,48,Diploma,13,48,52,71,48,8.0,5,70,Rural,Software Engineer,32668,1 +79861,Male,59,Diploma,5,73,95,80,31,4.0,4,0,Rural,Software Engineer,50540,1 +79862,Female,21,High School,2,81,27,72,80,5.0,6,65,Urban,Data Analyst,66006,1 +79863,Female,33,High School,5,84,4,54,43,5.0,3,66,Semi-Urban,ML Engineer,54417,0 +79864,Female,30,Masters,6,37,37,64,56,8.0,7,16,Urban,Software Engineer,125534,0 +79865,Male,59,PhD,1,59,98,49,8,0.0,2,85,Urban,HR Executive,121826,1 +79866,Male,44,Bachelors,4,9,98,9,90,8.0,5,82,Urban,Manager,36758,0 +79867,Female,34,Bachelors,4,47,40,96,25,9.0,0,9,Rural,ML Engineer,140954,0 +79868,Female,39,Masters,0,22,33,18,39,7.0,2,77,Urban,Manager,103828,0 +79869,Male,43,Diploma,16,39,74,12,9,5.0,7,57,Rural,Data Analyst,118195,0 +79870,Male,32,Masters,7,13,77,9,49,1.0,7,50,Semi-Urban,Software Engineer,121794,0 +79871,Female,30,Bachelors,0,65,24,93,13,9.0,5,17,Urban,Software Engineer,21298,0 +79872,Female,50,High School,6,51,64,87,17,8.0,4,28,Urban,ML Engineer,113056,0 +79873,Male,22,Bachelors,4,37,29,13,53,6.0,3,61,Urban,Manager,88349,0 +79874,Female,22,High School,12,22,25,73,94,5.0,5,91,Urban,ML Engineer,104596,0 +79875,Female,45,Bachelors,15,20,4,18,19,4.0,5,53,Semi-Urban,HR Executive,90059,0 +79876,Male,44,High School,12,50,51,20,43,7.0,4,90,Urban,ML Engineer,61793,0 +79877,Male,43,Masters,9,42,96,1,81,4.0,1,44,Semi-Urban,Manager,23357,0 +79878,Female,47,Bachelors,14,47,48,58,6,1.0,2,49,Semi-Urban,Software Engineer,77571,0 +79879,Female,43,Bachelors,13,83,18,10,29,8.0,7,70,Rural,Software Engineer,27593,0 +79880,Male,34,Bachelors,19,96,87,43,46,5.0,1,9,Semi-Urban,ML Engineer,77569,1 +79881,Male,47,High School,13,62,11,48,90,6.0,6,90,Semi-Urban,Data Analyst,139713,0 +79882,Female,22,Masters,14,7,4,69,52,2.0,7,41,Semi-Urban,HR Executive,31181,0 +79883,Other,24,Diploma,19,1,7,69,7,3.0,1,75,Urban,Data Analyst,30476,0 +79884,Male,51,Diploma,12,25,65,42,86,3.0,5,40,Urban,Manager,42621,0 +79885,Female,48,Bachelors,15,8,69,78,31,7.0,1,76,Rural,Manager,61998,0 +79886,Male,41,High School,8,72,90,54,9,7.0,4,46,Urban,Manager,103154,1 +79887,Male,24,Bachelors,18,94,9,28,33,0.0,3,59,Rural,ML Engineer,38360,0 +79888,Female,44,Bachelors,14,15,35,51,27,8.0,6,61,Urban,ML Engineer,88991,0 +79889,Male,42,High School,11,20,32,54,19,0.0,2,93,Urban,Software Engineer,75875,0 +79890,Male,39,Diploma,10,95,53,36,14,0.0,7,36,Semi-Urban,HR Executive,79649,0 +79891,Male,48,Masters,3,86,8,77,59,8.0,7,65,Rural,ML Engineer,23134,1 +79892,Male,54,Bachelors,0,5,62,16,97,2.0,0,48,Semi-Urban,Data Analyst,98893,0 +79893,Male,30,Bachelors,6,53,0,33,22,0.0,6,86,Semi-Urban,HR Executive,128619,0 +79894,Male,50,Bachelors,9,61,56,82,15,0.0,3,1,Urban,Manager,117478,0 +79895,Other,28,Masters,18,61,55,51,78,3.0,4,29,Rural,Manager,126092,0 +79896,Female,34,Bachelors,5,64,98,77,92,5.0,3,75,Semi-Urban,Manager,148488,1 +79897,Male,50,Diploma,3,19,67,98,13,8.0,0,35,Urban,Data Analyst,92791,0 +79898,Female,57,Diploma,0,35,88,18,49,7.0,0,50,Urban,Software Engineer,82757,0 +79899,Male,46,High School,5,7,11,69,63,6.0,0,91,Semi-Urban,Data Analyst,143797,0 +79900,Male,39,High School,10,72,40,49,90,2.0,3,66,Semi-Urban,Data Analyst,82559,0 +79901,Female,24,Bachelors,6,1,7,88,74,1.0,3,63,Urban,Data Analyst,87262,0 +79902,Male,25,Masters,11,40,87,61,61,7.0,1,3,Urban,ML Engineer,27854,0 +79903,Female,51,PhD,15,75,87,28,65,8.0,7,96,Semi-Urban,Data Analyst,117539,1 +79904,Female,45,Bachelors,0,35,29,43,44,1.0,1,62,Urban,Software Engineer,134185,0 +79905,Female,31,Bachelors,13,57,89,52,41,2.0,1,63,Rural,Software Engineer,117211,1 +79906,Male,53,High School,14,97,29,8,72,6.0,3,66,Rural,ML Engineer,33094,0 +79907,Male,57,Bachelors,3,89,78,49,75,8.0,0,11,Urban,HR Executive,31732,0 +79908,Female,43,Bachelors,7,5,58,95,21,0.0,4,92,Semi-Urban,Manager,143532,1 +79909,Male,54,High School,11,50,31,35,98,7.0,2,74,Semi-Urban,Software Engineer,87965,0 +79910,Male,34,Masters,12,85,75,35,67,3.0,6,83,Urban,Software Engineer,63887,1 +79911,Male,38,Bachelors,16,45,13,33,38,9.0,0,40,Rural,Software Engineer,75589,0 +79912,Male,57,High School,18,96,26,88,65,5.0,0,11,Urban,Software Engineer,20300,0 +79913,Male,29,Bachelors,11,58,0,28,1,0.0,6,88,Urban,Data Analyst,37316,0 +79914,Male,41,Diploma,11,13,8,20,10,7.0,6,22,Semi-Urban,Manager,142700,0 +79915,Other,25,Masters,8,28,28,46,37,5.0,1,90,Urban,HR Executive,121594,0 +79916,Other,42,Diploma,18,78,4,95,63,7.0,4,21,Urban,Manager,86346,0 +79917,Male,23,Masters,6,57,6,84,67,1.0,2,28,Semi-Urban,ML Engineer,55952,0 +79918,Male,34,Diploma,18,61,59,11,25,2.0,5,54,Urban,Software Engineer,97682,0 +79919,Male,54,High School,14,34,12,39,32,9.0,4,52,Semi-Urban,ML Engineer,54275,0 +79920,Female,38,High School,4,26,65,77,57,3.0,4,32,Rural,ML Engineer,29457,0 +79921,Male,26,Bachelors,11,92,38,66,74,4.0,5,10,Urban,Software Engineer,45516,0 +79922,Male,21,Masters,13,60,84,32,26,8.0,4,10,Semi-Urban,Manager,20246,0 +79923,Male,37,Masters,10,56,41,52,59,7.0,7,26,Urban,Software Engineer,136272,0 +79924,Male,38,Diploma,8,50,43,57,77,0.0,5,64,Urban,Manager,66979,0 +79925,Male,53,Bachelors,7,11,22,81,86,4.0,1,3,Semi-Urban,HR Executive,43451,0 +79926,Male,40,High School,3,27,86,13,5,7.0,7,6,Semi-Urban,Software Engineer,49275,0 +79927,Other,44,PhD,17,17,70,88,50,6.0,2,99,Urban,Software Engineer,95728,1 +79928,Female,38,Bachelors,9,83,22,10,15,9.0,6,88,Semi-Urban,HR Executive,68558,0 +79929,Male,24,Bachelors,9,60,82,13,12,3.0,1,94,Semi-Urban,Software Engineer,73481,1 +79930,Male,28,Diploma,9,95,73,72,77,5.0,1,79,Urban,HR Executive,28433,1 +79931,Male,49,Bachelors,15,27,47,27,54,2.0,6,63,Rural,Data Analyst,140102,0 +79932,Female,44,PhD,19,21,84,7,15,4.0,2,74,Urban,Manager,146906,0 +79933,Female,30,Masters,15,86,78,76,53,3.0,3,19,Urban,ML Engineer,141512,1 +79934,Female,41,Bachelors,8,72,36,90,16,6.0,1,26,Urban,Software Engineer,124900,0 +79935,Male,21,Bachelors,6,62,40,89,57,8.0,7,52,Urban,ML Engineer,148223,1 +79936,Male,55,Masters,13,62,90,57,3,3.0,6,27,Urban,HR Executive,94950,1 +79937,Male,49,High School,10,38,35,6,57,5.0,1,66,Rural,HR Executive,55623,0 +79938,Female,54,Masters,3,79,97,21,87,7.0,3,54,Semi-Urban,Data Analyst,129582,1 +79939,Male,28,Bachelors,3,15,64,67,48,7.0,7,98,Semi-Urban,ML Engineer,136137,1 +79940,Female,55,Bachelors,10,22,24,44,25,2.0,5,58,Rural,Data Analyst,136034,0 +79941,Male,59,High School,3,63,89,20,62,0.0,1,77,Urban,ML Engineer,59401,1 +79942,Female,33,Masters,15,28,11,11,32,5.0,2,66,Urban,ML Engineer,137127,0 +79943,Female,42,Diploma,5,21,69,58,46,5.0,2,92,Semi-Urban,Software Engineer,40833,0 +79944,Male,53,Masters,2,22,75,60,74,9.0,2,98,Semi-Urban,HR Executive,42553,1 +79945,Male,56,High School,1,2,8,13,90,5.0,7,79,Rural,Software Engineer,36718,0 +79946,Female,45,Masters,12,36,69,77,90,6.0,7,61,Rural,Software Engineer,136915,1 +79947,Male,48,High School,9,25,35,76,39,3.0,4,79,Rural,Software Engineer,106180,0 +79948,Male,25,Masters,4,5,88,75,32,5.0,6,77,Rural,Manager,147699,1 +79949,Male,51,Masters,5,90,11,92,52,4.0,7,34,Rural,Manager,56261,0 +79950,Other,26,Diploma,8,38,22,89,46,5.0,5,49,Urban,Manager,36308,0 +79951,Male,43,Bachelors,0,91,97,89,4,8.0,3,45,Semi-Urban,Manager,34505,1 +79952,Male,45,Bachelors,9,24,1,64,80,1.0,2,97,Urban,Data Analyst,45821,0 +79953,Male,40,Diploma,10,25,53,90,30,4.0,2,62,Rural,HR Executive,129273,0 +79954,Male,25,Diploma,13,39,42,81,28,7.0,0,29,Semi-Urban,ML Engineer,70298,0 +79955,Male,53,Bachelors,17,10,0,7,7,1.0,0,15,Urban,HR Executive,42170,0 +79956,Female,21,High School,1,21,82,22,34,2.0,4,0,Rural,Data Analyst,35453,0 +79957,Male,53,PhD,19,68,58,96,39,6.0,0,83,Urban,HR Executive,71105,1 +79958,Male,57,Diploma,7,33,76,45,31,0.0,7,95,Rural,Software Engineer,83379,1 +79959,Male,48,High School,5,6,84,20,39,2.0,6,84,Urban,Data Analyst,94051,0 +79960,Male,41,Diploma,11,67,49,54,51,9.0,4,8,Urban,HR Executive,51061,0 +79961,Male,27,Bachelors,18,78,55,68,54,6.0,4,34,Urban,HR Executive,134070,1 +79962,Female,51,Bachelors,17,99,38,29,14,1.0,2,96,Rural,ML Engineer,82336,1 +79963,Male,32,Bachelors,0,0,20,25,55,9.0,6,83,Urban,Manager,107995,0 +79964,Female,56,Bachelors,6,9,14,64,46,2.0,4,21,Urban,Data Analyst,25173,0 +79965,Male,33,Diploma,3,77,99,58,16,3.0,0,58,Semi-Urban,Data Analyst,141636,1 +79966,Female,37,Bachelors,8,79,59,28,77,0.0,6,68,Semi-Urban,Software Engineer,94919,0 +79967,Female,25,Bachelors,1,64,82,78,35,2.0,0,85,Rural,HR Executive,99644,1 +79968,Male,44,Bachelors,12,77,35,88,67,6.0,4,7,Semi-Urban,Manager,28587,0 +79969,Female,33,Diploma,0,93,73,26,51,1.0,2,82,Semi-Urban,ML Engineer,100588,1 +79970,Female,21,Bachelors,15,49,86,12,83,0.0,4,76,Urban,HR Executive,52000,0 +79971,Male,31,Bachelors,6,5,95,37,85,7.0,4,2,Urban,Software Engineer,104274,0 +79972,Male,45,Bachelors,14,27,63,61,74,6.0,3,13,Urban,Manager,69358,0 +79973,Female,57,Bachelors,15,84,81,5,63,9.0,5,93,Urban,HR Executive,142094,1 +79974,Male,55,Bachelors,1,20,62,10,39,2.0,1,4,Urban,HR Executive,82224,0 +79975,Male,47,Bachelors,16,32,32,39,90,6.0,2,27,Semi-Urban,HR Executive,72357,0 +79976,Male,41,Masters,10,78,25,0,41,9.0,2,23,Urban,Software Engineer,77109,0 +79977,Female,52,Bachelors,6,19,28,95,50,4.0,5,22,Semi-Urban,Software Engineer,58977,0 +79978,Female,30,Bachelors,4,91,59,54,27,5.0,6,29,Rural,Manager,40614,0 +79979,Male,48,High School,16,3,31,14,96,7.0,7,47,Urban,Manager,123130,0 +79980,Female,42,Diploma,2,73,44,1,29,6.0,2,29,Urban,HR Executive,138025,0 +79981,Male,49,Bachelors,11,74,35,9,97,2.0,0,64,Semi-Urban,Software Engineer,85079,0 +79982,Female,31,Diploma,19,57,32,29,75,8.0,1,4,Semi-Urban,Data Analyst,129353,0 +79983,Male,37,Bachelors,2,64,91,4,59,4.0,7,39,Urban,ML Engineer,88221,0 +79984,Female,30,High School,5,21,5,43,84,2.0,0,6,Urban,Manager,92418,0 +79985,Male,59,High School,1,55,74,10,77,9.0,3,27,Rural,ML Engineer,140334,0 +79986,Male,23,Masters,10,67,19,18,32,9.0,5,33,Urban,Software Engineer,123901,0 +79987,Female,27,High School,2,74,72,38,71,3.0,3,35,Urban,HR Executive,70500,0 +79988,Male,45,Bachelors,11,61,58,73,81,3.0,2,95,Urban,HR Executive,132233,1 +79989,Male,37,Diploma,2,26,47,77,44,2.0,6,25,Rural,Manager,103192,0 +79990,Male,22,High School,7,52,99,62,44,6.0,0,97,Urban,Manager,129273,1 +79991,Female,31,High School,12,13,45,81,88,0.0,7,87,Urban,Software Engineer,64244,0 +79992,Female,34,Bachelors,7,5,83,65,53,6.0,0,34,Rural,Data Analyst,149866,0 +79993,Female,35,Diploma,1,33,67,22,68,6.0,4,56,Urban,Data Analyst,111829,0 +79994,Female,53,Bachelors,3,69,54,59,40,7.0,4,81,Urban,Software Engineer,44857,1 +79995,Female,46,PhD,5,85,17,77,74,1.0,3,25,Urban,Software Engineer,99191,0 +79996,Male,56,Masters,0,94,15,32,58,4.0,7,44,Urban,HR Executive,124429,0 +79997,Male,54,Diploma,17,1,77,14,70,3.0,3,15,Rural,Software Engineer,121632,0 +79998,Male,32,High School,6,52,3,94,96,2.0,4,35,Urban,HR Executive,100646,0 +79999,Male,44,Bachelors,5,8,28,56,36,0.0,0,23,Urban,Manager,81668,0 +80000,Female,39,Diploma,12,90,81,31,72,9.0,4,28,Rural,ML Engineer,138733,0 +80001,Female,52,High School,11,5,48,20,0,5.0,4,5,Rural,HR Executive,95529,0 +80002,Male,23,Bachelors,7,36,3,92,23,9.0,7,6,Urban,ML Engineer,48102,0 +80003,Female,44,Diploma,8,58,11,32,17,0.0,2,76,Semi-Urban,Data Analyst,131173,0 +80004,Female,26,Masters,12,60,41,72,51,2.0,7,0,Semi-Urban,HR Executive,27342,0 +80005,Female,48,Masters,6,5,36,27,8,5.0,7,4,Urban,Software Engineer,66725,0 +80006,Male,40,High School,8,97,84,67,50,7.0,4,63,Rural,HR Executive,80918,1 +80007,Male,22,Bachelors,9,13,36,64,96,9.0,0,42,Urban,HR Executive,52931,0 +80008,Male,38,Bachelors,17,96,52,50,11,2.0,0,78,Urban,Data Analyst,101682,1 +80009,Male,25,High School,18,70,31,15,77,4.0,7,82,Urban,Data Analyst,46424,0 +80010,Male,40,Bachelors,16,47,21,92,87,4.0,3,62,Urban,HR Executive,41731,0 +80011,Male,40,Masters,1,34,23,99,65,7.0,1,38,Rural,Manager,37727,0 +80012,Female,30,High School,12,67,10,92,63,5.0,5,20,Semi-Urban,Software Engineer,120279,0 +80013,Male,45,Bachelors,18,55,93,44,71,0.0,2,79,Urban,Manager,112792,1 +80014,Male,47,Diploma,12,81,78,60,25,7.0,7,61,Rural,HR Executive,82815,1 +80015,Female,57,Bachelors,19,47,97,88,53,5.0,6,70,Urban,Manager,126045,1 +80016,Female,47,High School,16,86,19,52,5,6.0,3,81,Urban,ML Engineer,143676,0 +80017,Female,24,Diploma,14,32,23,16,50,1.0,6,20,Urban,HR Executive,94464,0 +80018,Female,47,Bachelors,17,51,50,73,94,8.0,5,26,Urban,Software Engineer,36092,0 +80019,Male,52,Masters,15,98,74,2,3,0.0,3,5,Rural,Software Engineer,112433,0 +80020,Male,46,High School,16,56,87,65,86,3.0,5,80,Urban,HR Executive,58983,1 +80021,Male,38,Bachelors,15,41,44,67,9,9.0,0,76,Semi-Urban,ML Engineer,33681,0 +80022,Male,29,High School,18,17,57,73,17,6.0,1,53,Urban,ML Engineer,131985,0 +80023,Female,36,Diploma,0,66,24,88,3,6.0,2,83,Rural,Software Engineer,90495,1 +80024,Male,28,Masters,11,86,18,90,31,6.0,2,13,Urban,Software Engineer,90072,0 +80025,Male,45,Bachelors,9,54,82,31,53,5.0,7,13,Rural,ML Engineer,38320,0 +80026,Female,55,Bachelors,15,85,81,19,94,2.0,4,20,Urban,HR Executive,98311,0 +80027,Female,35,Masters,17,99,50,46,84,4.0,6,41,Urban,Data Analyst,31373,0 +80028,Male,54,Bachelors,0,29,92,2,91,9.0,6,56,Rural,Manager,125993,0 +80029,Male,32,Bachelors,8,29,79,82,74,2.0,7,63,Semi-Urban,Data Analyst,20402,1 +80030,Male,37,Diploma,11,21,1,88,84,6.0,5,64,Urban,HR Executive,113906,0 +80031,Male,56,High School,17,44,98,76,22,4.0,3,28,Rural,Manager,49219,1 +80032,Male,32,Diploma,10,93,1,34,31,2.0,3,4,Urban,Data Analyst,26498,0 +80033,Male,37,Bachelors,2,97,5,96,11,4.0,3,46,Urban,Data Analyst,74202,1 +80034,Male,37,Masters,7,83,7,12,39,4.0,6,76,Semi-Urban,Software Engineer,126394,0 +80035,Male,28,High School,11,39,39,31,44,0.0,0,17,Urban,ML Engineer,48822,0 +80036,Male,25,Bachelors,17,42,31,36,36,1.0,4,25,Rural,Data Analyst,45984,0 +80037,Male,24,Bachelors,14,59,78,98,59,1.0,4,24,Semi-Urban,ML Engineer,110990,1 +80038,Female,52,Masters,13,27,58,11,10,4.0,1,13,Urban,Software Engineer,94710,0 +80039,Female,48,Diploma,19,62,64,10,25,9.0,4,14,Urban,Manager,66087,0 +80040,Male,31,High School,19,30,7,15,83,4.0,2,88,Urban,Manager,57624,0 +80041,Male,32,High School,15,92,1,75,55,5.0,6,94,Urban,Software Engineer,110716,1 +80042,Male,33,Bachelors,9,31,49,22,72,6.0,5,32,Urban,Software Engineer,130954,0 +80043,Male,28,High School,11,50,69,89,87,7.0,6,49,Urban,ML Engineer,49992,1 +80044,Male,39,PhD,12,83,88,26,35,4.0,0,56,Urban,Data Analyst,129365,1 +80045,Female,51,Bachelors,4,93,79,39,96,8.0,6,12,Urban,Data Analyst,35916,0 +80046,Female,46,High School,3,75,29,24,71,7.0,5,42,Urban,ML Engineer,60472,0 +80047,Female,48,Bachelors,16,25,73,13,69,6.0,7,67,Semi-Urban,Data Analyst,137786,0 +80048,Female,47,High School,6,62,74,56,36,1.0,5,94,Semi-Urban,Software Engineer,73638,1 +80049,Female,38,PhD,1,68,85,91,6,5.0,2,57,Urban,HR Executive,26150,1 +80050,Other,34,High School,7,26,20,40,58,7.0,7,98,Rural,Data Analyst,52970,0 +80051,Other,49,Bachelors,4,32,89,83,22,2.0,1,20,Urban,Software Engineer,28308,0 +80052,Male,54,PhD,16,74,4,1,66,6.0,4,20,Urban,Software Engineer,105604,0 +80053,Male,29,Masters,17,40,94,50,47,4.0,0,56,Semi-Urban,ML Engineer,111675,1 +80054,Male,26,High School,7,5,73,80,76,8.0,5,62,Rural,ML Engineer,140431,0 +80055,Other,28,Bachelors,13,55,36,61,2,0.0,4,35,Urban,Manager,126266,0 +80056,Male,28,Bachelors,11,86,86,72,32,2.0,3,21,Urban,HR Executive,125132,1 +80057,Male,57,High School,14,41,19,25,52,1.0,2,67,Urban,ML Engineer,51603,0 +80058,Male,34,High School,7,64,2,69,55,8.0,2,57,Urban,HR Executive,96904,0 +80059,Female,28,Bachelors,17,61,88,19,32,1.0,2,43,Rural,Data Analyst,94814,0 +80060,Female,39,Bachelors,15,9,40,22,72,7.0,3,26,Rural,Manager,109099,0 +80061,Male,43,Bachelors,12,6,31,7,99,0.0,3,45,Rural,Software Engineer,52918,0 +80062,Male,27,High School,12,19,22,63,24,5.0,4,27,Semi-Urban,HR Executive,49291,0 +80063,Female,54,Diploma,8,72,95,66,12,4.0,0,97,Semi-Urban,ML Engineer,148925,1 +80064,Male,42,Bachelors,4,65,48,45,28,5.0,3,25,Urban,Data Analyst,87165,0 +80065,Male,53,Bachelors,10,89,57,1,18,9.0,4,30,Semi-Urban,Data Analyst,52443,0 +80066,Female,21,PhD,0,96,66,87,35,1.0,0,60,Urban,HR Executive,134414,1 +80067,Female,43,Bachelors,18,16,0,72,2,9.0,2,46,Semi-Urban,Manager,60677,0 +80068,Male,43,PhD,11,30,78,60,16,5.0,3,85,Urban,Software Engineer,49400,1 +80069,Male,49,Bachelors,10,13,47,10,25,1.0,4,1,Semi-Urban,ML Engineer,32520,0 +80070,Male,47,Masters,19,25,57,41,16,4.0,4,11,Urban,Data Analyst,106188,0 +80071,Female,41,Diploma,7,55,76,18,35,6.0,4,54,Semi-Urban,Software Engineer,27031,0 +80072,Male,44,High School,6,55,70,0,2,1.0,1,70,Urban,HR Executive,100128,0 +80073,Male,23,Bachelors,12,38,72,3,63,6.0,6,67,Urban,Data Analyst,37421,0 +80074,Male,40,Bachelors,14,51,27,20,13,6.0,0,8,Rural,Software Engineer,71331,0 +80075,Male,35,Bachelors,1,12,67,11,88,7.0,6,43,Urban,ML Engineer,53565,0 +80076,Male,43,Bachelors,2,80,14,2,24,7.0,3,59,Urban,Manager,63525,0 +80077,Female,29,PhD,8,41,35,6,28,9.0,5,1,Urban,Data Analyst,52154,0 +80078,Male,51,High School,18,15,27,49,76,3.0,2,30,Rural,ML Engineer,22606,0 +80079,Female,32,Diploma,1,91,53,41,98,8.0,1,67,Urban,ML Engineer,134284,1 +80080,Female,47,Bachelors,5,28,88,6,4,2.0,7,10,Semi-Urban,Data Analyst,130378,0 +80081,Male,54,Bachelors,12,23,55,99,96,3.0,2,80,Urban,Manager,41742,1 +80082,Male,28,PhD,13,99,58,25,75,2.0,7,78,Rural,Manager,36220,1 +80083,Male,26,Masters,13,64,82,71,62,2.0,6,72,Urban,ML Engineer,137220,1 +80084,Female,27,High School,8,64,84,85,2,8.0,7,1,Urban,HR Executive,65045,0 +80085,Female,44,Diploma,18,78,66,15,23,2.0,2,57,Urban,Software Engineer,124998,0 +80086,Female,22,Bachelors,14,51,0,49,48,0.0,7,44,Semi-Urban,Software Engineer,63695,0 +80087,Male,49,Diploma,17,10,53,33,43,1.0,5,99,Urban,Software Engineer,55488,0 +80088,Male,47,Diploma,7,42,61,59,27,9.0,4,84,Urban,HR Executive,145756,1 +80089,Female,22,Diploma,16,39,67,96,55,5.0,0,91,Urban,Software Engineer,119778,1 +80090,Female,44,PhD,4,9,36,6,1,9.0,5,38,Urban,HR Executive,121631,0 +80091,Female,28,Masters,12,77,99,4,10,1.0,7,89,Rural,Software Engineer,126230,1 +80092,Male,48,High School,2,55,97,42,22,6.0,6,75,Urban,Data Analyst,58028,1 +80093,Other,28,Bachelors,1,38,85,22,98,5.0,1,57,Urban,HR Executive,63951,0 +80094,Male,28,Masters,2,54,76,10,85,3.0,2,73,Semi-Urban,Software Engineer,103790,0 +80095,Male,41,Bachelors,7,99,47,89,37,1.0,3,44,Semi-Urban,Manager,127998,1 +80096,Male,31,Masters,8,76,64,44,86,8.0,3,6,Urban,ML Engineer,76641,0 +80097,Male,23,High School,14,69,16,77,18,3.0,5,10,Urban,Manager,98437,0 +80098,Female,55,Bachelors,18,80,8,59,66,9.0,0,75,Semi-Urban,Manager,135255,0 +80099,Male,32,Masters,17,88,96,23,9,7.0,6,44,Semi-Urban,Data Analyst,53917,1 +80100,Male,29,Bachelors,4,10,40,0,34,8.0,0,22,Urban,Software Engineer,79373,0 +80101,Male,37,High School,7,69,68,7,46,2.0,1,15,Urban,ML Engineer,61655,0 +80102,Male,25,Diploma,13,5,80,37,91,8.0,2,7,Rural,ML Engineer,85221,0 +80103,Female,53,Bachelors,1,29,59,99,33,1.0,1,64,Urban,ML Engineer,126915,1 +80104,Female,44,Bachelors,11,83,54,51,18,0.0,0,43,Urban,ML Engineer,31804,0 +80105,Male,50,Bachelors,17,85,49,15,96,8.0,0,93,Rural,ML Engineer,39041,1 +80106,Male,32,Diploma,0,70,92,36,47,6.0,0,37,Urban,Software Engineer,85776,1 +80107,Female,55,Bachelors,13,28,55,19,43,2.0,3,9,Rural,HR Executive,27655,0 +80108,Female,48,Bachelors,16,57,5,52,29,5.0,2,99,Urban,Software Engineer,70636,0 +80109,Female,49,Bachelors,3,10,94,57,80,3.0,6,47,Urban,Software Engineer,97121,0 +80110,Male,27,Masters,3,48,63,99,68,5.0,7,42,Rural,Manager,59652,1 +80111,Female,53,Bachelors,11,23,0,87,25,8.0,6,82,Rural,HR Executive,141518,0 +80112,Male,46,High School,6,12,32,93,96,3.0,0,31,Semi-Urban,Data Analyst,136940,0 +80113,Male,34,High School,7,60,64,31,91,4.0,1,35,Semi-Urban,ML Engineer,145890,0 +80114,Male,29,Masters,17,16,93,93,89,0.0,7,11,Rural,Manager,61938,0 +80115,Female,40,Bachelors,5,41,66,26,87,7.0,1,68,Rural,Manager,59863,0 +80116,Male,25,Masters,7,61,38,81,41,4.0,7,54,Rural,Software Engineer,92062,0 +80117,Male,36,Diploma,16,16,99,86,32,0.0,1,45,Rural,Software Engineer,92926,1 +80118,Male,30,Bachelors,4,87,49,3,36,9.0,1,39,Rural,ML Engineer,45945,0 +80119,Male,47,High School,11,88,89,98,66,7.0,1,77,Semi-Urban,Software Engineer,94237,1 +80120,Female,59,Bachelors,6,72,16,67,16,8.0,7,56,Semi-Urban,Manager,126319,0 +80121,Male,45,High School,13,85,34,95,80,7.0,3,15,Urban,Manager,90898,0 +80122,Female,58,Bachelors,7,15,86,81,63,8.0,0,36,Urban,Data Analyst,24680,0 +80123,Female,21,Masters,16,14,7,68,27,7.0,3,58,Rural,HR Executive,89524,0 +80124,Male,37,Bachelors,18,37,69,79,14,0.0,3,50,Rural,Data Analyst,65695,1 +80125,Male,44,Diploma,11,57,42,77,71,2.0,0,87,Semi-Urban,Software Engineer,47186,1 +80126,Female,54,Masters,17,3,83,94,60,1.0,2,0,Urban,HR Executive,63685,0 +80127,Male,44,Masters,14,59,91,43,8,9.0,6,57,Urban,HR Executive,105807,1 +80128,Female,21,Bachelors,18,46,84,69,15,5.0,7,96,Urban,ML Engineer,30278,1 +80129,Female,21,Bachelors,3,99,26,32,88,1.0,5,79,Urban,Manager,117659,0 +80130,Male,35,PhD,8,67,30,80,49,5.0,2,36,Rural,Manager,117149,0 +80131,Male,31,Masters,16,45,88,88,10,0.0,2,92,Semi-Urban,ML Engineer,129492,1 +80132,Male,36,Diploma,8,72,19,38,83,8.0,2,71,Semi-Urban,ML Engineer,40580,0 +80133,Male,39,Bachelors,11,98,12,86,31,9.0,5,46,Urban,ML Engineer,83094,1 +80134,Female,28,Masters,11,48,71,50,93,5.0,1,11,Urban,Data Analyst,111644,0 +80135,Male,34,High School,5,15,16,66,33,0.0,7,20,Urban,Software Engineer,130060,0 +80136,Male,22,Diploma,3,31,32,55,55,1.0,6,24,Rural,Manager,112770,0 +80137,Male,29,Bachelors,9,40,16,16,22,0.0,0,68,Semi-Urban,ML Engineer,48680,0 +80138,Other,46,High School,18,74,83,69,8,1.0,5,55,Rural,Manager,98992,1 +80139,Female,59,Masters,0,74,43,33,37,8.0,2,78,Semi-Urban,Data Analyst,83147,0 +80140,Female,31,PhD,18,36,84,25,64,9.0,6,19,Urban,Software Engineer,114222,0 +80141,Male,39,High School,6,65,44,77,81,5.0,3,6,Rural,Software Engineer,89986,0 +80142,Male,43,PhD,1,77,19,52,45,0.0,2,7,Urban,Software Engineer,30514,0 +80143,Female,48,Masters,1,48,26,16,29,4.0,0,45,Semi-Urban,ML Engineer,126381,0 +80144,Male,27,High School,8,40,91,73,39,1.0,0,66,Urban,Software Engineer,97016,1 +80145,Male,28,Masters,11,24,55,75,17,5.0,2,62,Urban,ML Engineer,132403,0 +80146,Male,35,PhD,17,60,98,37,17,8.0,2,89,Urban,Manager,95486,1 +80147,Male,52,Diploma,3,97,3,83,67,7.0,4,30,Semi-Urban,ML Engineer,61196,0 +80148,Male,56,Bachelors,17,48,53,31,45,2.0,5,2,Urban,Manager,145189,0 +80149,Male,52,Masters,8,92,34,10,47,1.0,6,5,Urban,ML Engineer,125587,0 +80150,Male,39,Bachelors,19,14,9,67,65,0.0,0,12,Semi-Urban,Manager,119175,0 +80151,Female,55,Diploma,10,48,58,88,69,9.0,1,46,Urban,ML Engineer,37628,0 +80152,Female,57,Masters,18,66,21,74,42,4.0,6,29,Urban,ML Engineer,33981,0 +80153,Female,45,Masters,3,72,21,75,57,5.0,0,67,Urban,HR Executive,31882,0 +80154,Male,42,Bachelors,14,73,33,56,15,2.0,5,95,Urban,ML Engineer,31437,1 +80155,Male,30,Diploma,1,60,65,46,58,4.0,0,44,Semi-Urban,HR Executive,30686,0 +80156,Female,28,Bachelors,19,48,62,93,32,4.0,6,87,Rural,Data Analyst,20701,1 +80157,Male,35,Masters,18,6,72,81,51,9.0,1,10,Urban,ML Engineer,121604,0 +80158,Male,22,Bachelors,6,85,32,94,44,7.0,4,93,Semi-Urban,Software Engineer,49726,1 +80159,Male,30,Bachelors,0,4,62,59,73,3.0,2,11,Rural,HR Executive,137540,0 +80160,Male,56,Diploma,12,86,76,32,69,6.0,0,70,Urban,HR Executive,60650,1 +80161,Female,59,Bachelors,14,26,97,57,81,4.0,1,79,Urban,Software Engineer,102311,1 +80162,Male,36,PhD,14,34,21,62,84,8.0,6,13,Semi-Urban,Data Analyst,108779,0 +80163,Female,57,High School,19,77,31,23,46,7.0,0,43,Urban,Manager,124243,0 +80164,Female,28,High School,13,32,76,64,82,9.0,2,6,Urban,Data Analyst,28199,0 +80165,Female,43,Diploma,12,34,16,36,10,5.0,4,16,Urban,Data Analyst,136747,0 +80166,Female,23,Bachelors,1,46,64,91,91,0.0,7,65,Semi-Urban,HR Executive,35032,1 +80167,Male,41,High School,12,64,24,73,52,8.0,5,10,Urban,HR Executive,135683,0 +80168,Female,28,Bachelors,3,61,87,33,56,0.0,2,3,Rural,Software Engineer,69392,0 +80169,Male,52,Diploma,8,71,82,23,98,5.0,4,77,Semi-Urban,Data Analyst,95218,1 +80170,Male,43,Bachelors,6,21,54,9,92,7.0,1,13,Semi-Urban,Data Analyst,93940,0 +80171,Female,45,Bachelors,14,32,81,3,87,4.0,5,3,Urban,HR Executive,133249,0 +80172,Male,30,Diploma,4,13,43,61,61,1.0,7,43,Semi-Urban,ML Engineer,33531,0 +80173,Female,42,Bachelors,7,40,99,62,22,6.0,7,83,Semi-Urban,Manager,52517,1 +80174,Male,38,Bachelors,0,10,81,96,75,2.0,2,84,Semi-Urban,Manager,36646,1 +80175,Other,57,Masters,0,42,42,35,89,2.0,1,95,Urban,Manager,92101,0 +80176,Male,45,Masters,15,32,54,24,51,5.0,2,92,Semi-Urban,Data Analyst,51816,0 +80177,Male,35,High School,12,55,3,16,14,6.0,4,68,Urban,Software Engineer,90057,0 +80178,Male,32,High School,1,57,51,27,50,6.0,1,77,Rural,Data Analyst,133010,0 +80179,Female,56,Bachelors,0,54,83,36,45,4.0,5,76,Urban,HR Executive,117979,1 +80180,Female,56,Bachelors,12,28,79,28,6,9.0,6,76,Rural,Software Engineer,61996,0 +80181,Male,48,High School,2,70,8,2,70,8.0,3,10,Rural,HR Executive,22085,0 +80182,Male,27,High School,12,81,44,46,7,2.0,5,77,Urban,Software Engineer,65904,1 +80183,Female,34,Bachelors,2,91,80,99,72,9.0,2,31,Semi-Urban,ML Engineer,40735,1 +80184,Other,57,Bachelors,8,85,63,84,47,1.0,2,37,Rural,Data Analyst,42973,1 +80185,Male,21,Diploma,7,87,68,25,29,2.0,6,93,Semi-Urban,Manager,94161,1 +80186,Male,49,Bachelors,6,98,84,20,56,4.0,0,46,Urban,Manager,89305,1 +80187,Male,31,Masters,6,91,49,37,65,0.0,6,98,Urban,HR Executive,44025,1 +80188,Male,26,Bachelors,7,84,33,0,11,4.0,0,85,Urban,Manager,124815,0 +80189,Male,37,Diploma,14,25,53,37,70,7.0,5,5,Semi-Urban,HR Executive,48745,0 +80190,Male,52,Bachelors,1,16,49,0,89,1.0,6,17,Rural,Data Analyst,105322,0 +80191,Male,31,Masters,4,46,37,95,14,1.0,3,69,Rural,ML Engineer,117923,1 +80192,Male,46,Bachelors,0,86,53,38,8,0.0,6,10,Rural,Manager,43754,0 +80193,Male,59,Bachelors,16,37,96,29,63,5.0,7,56,Urban,Data Analyst,37232,0 +80194,Male,26,Bachelors,12,94,7,18,30,2.0,2,88,Urban,Data Analyst,56730,0 +80195,Male,21,Bachelors,12,79,90,4,9,9.0,4,64,Semi-Urban,Data Analyst,80432,1 +80196,Male,32,Diploma,13,75,78,28,68,8.0,3,93,Semi-Urban,ML Engineer,32210,1 +80197,Male,58,Diploma,13,41,51,10,29,6.0,6,82,Urban,ML Engineer,125715,0 +80198,Female,35,Diploma,14,12,7,12,84,5.0,2,27,Urban,Data Analyst,33400,0 +80199,Male,30,PhD,6,98,9,2,17,0.0,5,46,Semi-Urban,HR Executive,25284,0 +80200,Female,36,Bachelors,7,95,18,36,52,7.0,3,91,Urban,Software Engineer,81547,0 +80201,Male,43,Bachelors,16,25,99,43,6,9.0,7,21,Urban,HR Executive,88342,0 +80202,Male,37,Bachelors,15,66,33,20,52,6.0,0,69,Urban,HR Executive,72768,0 +80203,Female,25,Masters,15,12,58,25,83,8.0,6,24,Rural,HR Executive,147991,0 +80204,Male,23,Diploma,1,45,21,64,74,2.0,7,61,Semi-Urban,Data Analyst,67618,0 +80205,Male,47,Diploma,19,10,90,62,98,0.0,6,8,Urban,ML Engineer,142107,0 +80206,Male,30,PhD,11,43,92,79,39,3.0,6,51,Semi-Urban,HR Executive,135715,1 +80207,Male,29,High School,4,66,58,71,27,2.0,7,32,Urban,Manager,127462,0 +80208,Male,23,Diploma,16,87,27,33,7,6.0,0,53,Urban,HR Executive,149724,0 +80209,Male,55,High School,0,37,65,18,7,4.0,2,14,Semi-Urban,Data Analyst,122914,0 +80210,Female,57,PhD,11,97,42,5,54,7.0,7,45,Urban,Software Engineer,22791,0 +80211,Male,23,High School,9,11,80,15,25,0.0,0,42,Semi-Urban,ML Engineer,131386,0 +80212,Male,25,Masters,17,18,42,19,60,2.0,6,23,Semi-Urban,Data Analyst,141223,0 +80213,Male,22,High School,1,10,77,27,99,8.0,2,63,Urban,HR Executive,87826,0 +80214,Male,57,High School,16,42,59,0,23,3.0,0,38,Rural,Data Analyst,47553,0 +80215,Other,51,High School,5,62,73,98,88,4.0,2,47,Semi-Urban,Manager,86239,1 +80216,Female,21,Diploma,9,99,59,3,64,7.0,5,63,Rural,Software Engineer,70590,0 +80217,Female,23,Bachelors,16,89,64,71,59,7.0,3,13,Rural,Manager,42301,0 +80218,Male,58,Bachelors,15,67,75,66,61,6.0,6,15,Urban,Manager,72603,0 +80219,Male,54,Bachelors,17,1,84,45,7,9.0,2,3,Urban,Manager,34880,0 +80220,Other,29,Bachelors,11,77,45,13,63,3.0,5,14,Urban,ML Engineer,30099,0 +80221,Male,54,Masters,15,21,54,3,85,6.0,6,86,Semi-Urban,Software Engineer,87711,0 +80222,Male,37,Bachelors,0,11,38,19,18,6.0,6,92,Semi-Urban,Data Analyst,70449,0 +80223,Male,30,High School,13,93,66,71,65,2.0,4,33,Semi-Urban,Manager,149138,1 +80224,Male,29,Masters,1,33,79,86,54,1.0,4,33,Rural,HR Executive,72830,0 +80225,Female,27,Bachelors,6,76,2,76,72,9.0,2,43,Semi-Urban,HR Executive,47940,0 +80226,Male,46,Masters,16,94,0,16,46,8.0,3,25,Semi-Urban,Data Analyst,91408,0 +80227,Female,30,High School,12,13,92,0,99,0.0,1,40,Urban,Manager,20207,0 +80228,Male,32,Bachelors,14,12,65,63,32,9.0,7,55,Rural,HR Executive,23697,0 +80229,Male,22,Bachelors,15,46,51,22,79,1.0,4,68,Urban,Manager,84792,0 +80230,Female,56,PhD,19,35,93,81,47,1.0,3,80,Rural,HR Executive,65633,1 +80231,Female,23,Bachelors,0,41,31,97,82,2.0,1,87,Urban,ML Engineer,68431,1 +80232,Female,51,Masters,10,99,42,86,18,3.0,2,40,Semi-Urban,ML Engineer,78122,1 +80233,Male,41,Bachelors,5,8,99,9,92,2.0,7,16,Semi-Urban,Data Analyst,130319,0 +80234,Male,22,Masters,2,5,24,27,29,6.0,4,0,Urban,Manager,113942,0 +80235,Female,50,Masters,13,52,56,2,37,2.0,6,99,Semi-Urban,HR Executive,104436,0 +80236,Female,22,Diploma,13,14,45,40,5,1.0,2,81,Semi-Urban,ML Engineer,35372,0 +80237,Male,43,Masters,9,83,84,3,4,1.0,3,10,Urban,HR Executive,76181,0 +80238,Male,22,Diploma,7,82,29,66,1,9.0,0,68,Urban,Data Analyst,34335,1 +80239,Male,23,Bachelors,6,5,44,51,73,5.0,7,20,Urban,HR Executive,70985,0 +80240,Female,21,Bachelors,14,20,40,94,12,3.0,6,96,Urban,Data Analyst,107192,1 +80241,Female,21,Diploma,18,97,12,90,75,9.0,3,26,Urban,Manager,48446,0 +80242,Female,33,Masters,5,99,32,23,47,3.0,2,24,Rural,Manager,100132,0 +80243,Female,47,PhD,17,67,16,29,85,9.0,3,26,Semi-Urban,HR Executive,138642,0 +80244,Female,29,Bachelors,9,68,25,41,6,4.0,4,73,Rural,HR Executive,36538,0 +80245,Female,37,High School,16,32,75,28,58,6.0,2,63,Rural,HR Executive,147971,0 +80246,Male,47,Diploma,17,77,80,96,68,4.0,4,15,Urban,HR Executive,72041,1 +80247,Male,50,Bachelors,5,56,91,77,84,1.0,3,21,Semi-Urban,Manager,76616,1 +80248,Female,33,High School,18,62,68,85,35,5.0,3,76,Urban,Manager,28936,1 +80249,Male,59,Bachelors,15,18,31,12,64,1.0,3,60,Urban,Manager,76433,0 +80250,Female,40,Bachelors,18,2,8,10,41,5.0,1,63,Urban,Data Analyst,96688,0 +80251,Male,29,Bachelors,0,22,7,20,87,6.0,5,54,Urban,HR Executive,50341,0 +80252,Male,23,Masters,3,60,20,89,19,3.0,2,18,Rural,ML Engineer,20348,0 +80253,Male,54,Bachelors,11,84,7,8,88,0.0,5,20,Semi-Urban,Manager,46502,0 +80254,Male,29,Bachelors,7,37,58,95,51,0.0,7,98,Rural,Data Analyst,85121,1 +80255,Male,58,Diploma,9,46,80,19,25,8.0,3,98,Urban,Manager,147642,1 +80256,Male,48,Bachelors,9,6,40,97,43,7.0,5,8,Urban,HR Executive,26235,0 +80257,Male,38,Diploma,4,9,7,41,91,0.0,2,50,Rural,Software Engineer,137497,0 +80258,Male,56,Bachelors,17,17,11,90,41,5.0,5,73,Urban,Manager,120065,0 +80259,Female,29,High School,10,37,59,3,60,1.0,5,34,Semi-Urban,Software Engineer,92771,0 +80260,Male,37,PhD,11,49,49,43,44,0.0,2,95,Urban,HR Executive,97845,1 +80261,Male,33,Bachelors,6,53,35,64,93,6.0,2,96,Rural,ML Engineer,66352,1 +80262,Male,27,High School,15,65,86,34,70,0.0,2,32,Urban,Manager,61486,0 +80263,Female,48,High School,4,66,56,86,38,1.0,5,53,Urban,Manager,40655,1 +80264,Male,21,Diploma,4,65,56,96,24,2.0,1,58,Urban,HR Executive,47880,1 +80265,Male,25,Diploma,18,10,51,17,89,3.0,1,19,Urban,ML Engineer,104681,0 +80266,Female,32,Bachelors,16,47,84,46,64,4.0,2,73,Rural,ML Engineer,72337,1 +80267,Male,54,Bachelors,17,28,81,4,43,9.0,5,21,Urban,Data Analyst,34433,0 +80268,Female,44,Masters,3,53,5,87,94,0.0,1,77,Semi-Urban,Data Analyst,122037,0 +80269,Male,43,High School,15,14,85,26,89,6.0,6,38,Semi-Urban,Data Analyst,116948,0 +80270,Male,40,Bachelors,2,67,75,83,7,1.0,3,91,Semi-Urban,Software Engineer,37597,1 +80271,Male,50,Bachelors,10,6,22,79,89,9.0,7,42,Urban,Manager,135611,0 +80272,Male,37,Bachelors,9,36,89,66,88,8.0,7,93,Urban,HR Executive,96264,1 +80273,Male,59,Diploma,5,6,36,96,3,0.0,5,50,Semi-Urban,ML Engineer,39738,0 +80274,Male,26,Bachelors,12,26,83,79,77,3.0,6,21,Rural,Data Analyst,32582,0 +80275,Female,25,Bachelors,1,18,73,95,7,0.0,3,64,Rural,HR Executive,68041,1 +80276,Female,21,Masters,9,30,25,73,3,9.0,6,45,Urban,Data Analyst,43124,0 +80277,Male,37,High School,7,86,35,96,96,6.0,2,64,Urban,Data Analyst,44149,1 +80278,Male,22,Bachelors,4,55,9,68,77,1.0,1,40,Rural,Manager,111844,0 +80279,Male,24,Bachelors,1,32,20,99,87,7.0,5,29,Urban,HR Executive,75752,0 +80280,Male,24,Bachelors,10,20,94,48,91,8.0,1,49,Urban,HR Executive,82576,0 +80281,Male,23,Diploma,16,4,19,28,77,4.0,5,42,Rural,Data Analyst,138460,0 +80282,Female,30,PhD,7,46,79,84,54,7.0,1,61,Semi-Urban,ML Engineer,25007,1 +80283,Female,58,High School,10,63,48,47,28,1.0,6,55,Rural,ML Engineer,87511,0 +80284,Female,56,Bachelors,10,80,81,63,20,0.0,2,15,Urban,ML Engineer,38445,0 +80285,Male,42,High School,11,8,38,63,46,6.0,3,67,Semi-Urban,HR Executive,74141,0 +80286,Male,41,Masters,7,73,95,79,25,8.0,4,9,Urban,HR Executive,123976,1 +80287,Male,25,Diploma,11,98,30,40,54,4.0,5,77,Semi-Urban,Manager,21861,1 +80288,Male,55,Diploma,11,8,31,97,17,1.0,7,87,Urban,HR Executive,73904,0 +80289,Male,45,High School,19,10,81,58,58,5.0,1,22,Rural,Manager,64132,0 +80290,Female,57,High School,13,47,65,41,28,2.0,4,95,Urban,ML Engineer,122146,1 +80291,Female,43,Diploma,16,85,77,15,20,2.0,5,78,Semi-Urban,Software Engineer,53540,1 +80292,Male,36,Bachelors,11,63,29,27,97,5.0,6,71,Semi-Urban,Software Engineer,105214,0 +80293,Male,31,Diploma,11,64,99,37,77,5.0,1,11,Rural,HR Executive,68670,0 +80294,Male,53,Bachelors,7,74,45,44,59,9.0,2,34,Urban,Software Engineer,35708,0 +80295,Male,53,PhD,15,76,28,89,83,1.0,4,74,Urban,Manager,140531,1 +80296,Male,43,Masters,16,44,95,71,97,6.0,0,30,Urban,ML Engineer,136548,1 +80297,Male,52,Diploma,9,77,4,94,19,7.0,2,7,Urban,ML Engineer,149254,0 +80298,Male,45,Diploma,14,31,90,19,59,1.0,0,85,Semi-Urban,Manager,90478,0 +80299,Male,37,Masters,15,49,49,87,23,8.0,1,31,Urban,Data Analyst,52712,0 +80300,Male,55,Bachelors,6,9,54,22,16,9.0,5,31,Rural,HR Executive,35048,0 +80301,Male,35,Bachelors,15,46,32,79,65,6.0,3,55,Urban,HR Executive,33022,0 +80302,Female,34,Bachelors,8,28,5,21,69,0.0,0,36,Rural,Manager,107343,0 +80303,Male,24,Bachelors,18,63,95,17,20,3.0,4,69,Rural,Manager,97171,1 +80304,Male,41,Diploma,17,84,34,23,50,2.0,2,93,Urban,ML Engineer,95279,0 +80305,Male,49,Masters,12,89,28,13,20,7.0,5,31,Urban,Software Engineer,125428,0 +80306,Other,27,Bachelors,16,72,50,59,1,6.0,1,99,Urban,HR Executive,70745,1 +80307,Other,33,Bachelors,0,20,52,27,86,9.0,4,54,Rural,ML Engineer,54727,0 +80308,Male,33,Bachelors,13,47,73,92,24,6.0,1,56,Rural,Software Engineer,110047,1 +80309,Female,26,Bachelors,11,3,62,20,10,7.0,1,6,Rural,ML Engineer,25149,0 +80310,Female,26,Masters,12,45,29,56,22,9.0,1,88,Urban,Data Analyst,141722,0 +80311,Female,26,Bachelors,3,11,10,36,85,2.0,7,67,Urban,Software Engineer,33727,0 +80312,Male,33,Bachelors,3,40,28,65,40,3.0,7,30,Urban,HR Executive,56613,0 +80313,Male,21,Bachelors,11,69,92,84,48,7.0,6,11,Urban,HR Executive,138010,1 +80314,Male,22,Bachelors,6,51,36,38,32,4.0,4,87,Urban,Data Analyst,76535,0 +80315,Male,41,High School,10,88,60,43,97,8.0,1,93,Urban,ML Engineer,74658,1 +80316,Female,41,Diploma,7,40,99,29,32,7.0,7,1,Rural,Data Analyst,133221,0 +80317,Female,43,Bachelors,10,61,23,65,45,6.0,1,34,Urban,Manager,96141,0 +80318,Female,48,Bachelors,9,56,70,61,77,2.0,3,82,Urban,ML Engineer,94857,1 +80319,Male,54,Bachelors,3,22,98,14,94,6.0,1,89,Urban,HR Executive,111827,0 +80320,Male,41,Bachelors,12,48,39,0,10,3.0,3,24,Rural,Software Engineer,80009,0 +80321,Male,37,Diploma,5,87,10,81,42,0.0,5,38,Urban,Manager,32942,0 +80322,Female,40,Bachelors,3,1,28,31,16,1.0,4,12,Urban,ML Engineer,69787,0 +80323,Female,25,Masters,0,48,46,64,5,1.0,6,4,Rural,Manager,147916,0 +80324,Male,32,Bachelors,8,21,50,98,25,9.0,4,98,Semi-Urban,Manager,61264,1 +80325,Male,33,High School,14,27,1,44,72,2.0,3,34,Semi-Urban,Software Engineer,140264,0 +80326,Male,35,Diploma,3,0,15,61,50,2.0,3,73,Urban,HR Executive,25049,0 +80327,Male,29,Bachelors,16,52,60,23,58,2.0,3,10,Urban,ML Engineer,75139,0 +80328,Male,55,Bachelors,6,7,79,77,89,7.0,2,25,Rural,HR Executive,108761,0 +80329,Female,59,Bachelors,12,73,46,56,18,2.0,3,66,Urban,HR Executive,144854,1 +80330,Male,29,Masters,8,19,62,4,55,2.0,6,66,Rural,Manager,52626,0 +80331,Male,24,Masters,18,73,30,50,40,8.0,4,15,Rural,HR Executive,45473,0 +80332,Male,21,Bachelors,8,56,84,86,92,0.0,7,90,Semi-Urban,HR Executive,70871,1 +80333,Male,37,Bachelors,9,8,40,86,70,3.0,6,39,Semi-Urban,Software Engineer,116604,0 +80334,Male,32,PhD,12,64,3,19,45,1.0,6,99,Urban,ML Engineer,93636,0 +80335,Male,24,Masters,12,44,28,85,31,2.0,7,76,Urban,Data Analyst,80400,0 +80336,Male,23,Bachelors,13,78,88,18,44,3.0,5,8,Urban,Data Analyst,25968,0 +80337,Male,25,Diploma,0,7,89,67,33,4.0,4,68,Semi-Urban,Software Engineer,120760,0 +80338,Female,26,Diploma,16,68,21,35,45,5.0,6,18,Semi-Urban,ML Engineer,90303,0 +80339,Male,25,Bachelors,13,70,29,36,70,8.0,4,66,Semi-Urban,Software Engineer,26892,0 +80340,Female,51,High School,3,13,63,47,78,8.0,3,54,Semi-Urban,Software Engineer,149985,0 +80341,Male,30,High School,15,50,72,62,54,8.0,2,78,Semi-Urban,Software Engineer,52691,1 +80342,Female,42,Masters,16,71,60,34,12,6.0,4,18,Urban,Data Analyst,92272,0 +80343,Male,24,Bachelors,7,39,11,24,41,7.0,0,58,Rural,Manager,127168,0 +80344,Female,27,Masters,7,85,99,70,77,0.0,2,3,Urban,HR Executive,58042,1 +80345,Male,47,High School,4,58,81,63,17,0.0,6,69,Urban,Data Analyst,35635,1 +80346,Male,23,Masters,19,26,45,87,87,9.0,7,62,Urban,Data Analyst,133172,0 +80347,Male,38,PhD,14,26,53,16,2,3.0,4,60,Urban,Manager,69902,0 +80348,Male,58,High School,11,65,41,45,17,5.0,6,16,Semi-Urban,Data Analyst,91812,0 +80349,Female,26,Bachelors,11,14,70,70,59,6.0,6,26,Rural,Software Engineer,114905,0 +80350,Male,33,Bachelors,5,90,85,4,18,1.0,0,99,Urban,Manager,137729,1 +80351,Other,52,Masters,10,94,16,92,72,4.0,1,56,Urban,Manager,33833,1 +80352,Female,35,Diploma,5,36,71,40,24,7.0,4,72,Urban,ML Engineer,78964,0 +80353,Female,58,Masters,10,34,24,52,49,1.0,3,0,Urban,HR Executive,33788,0 +80354,Male,35,Masters,19,92,64,91,60,8.0,2,1,Rural,HR Executive,97691,1 +80355,Male,48,Bachelors,14,39,73,40,96,5.0,2,61,Urban,Manager,89331,0 +80356,Male,40,Bachelors,5,27,15,95,60,9.0,5,81,Urban,ML Engineer,129676,0 +80357,Female,34,High School,2,3,63,58,27,9.0,7,10,Semi-Urban,Manager,43421,0 +80358,Other,25,Bachelors,2,96,76,85,21,0.0,5,96,Urban,Software Engineer,42683,1 +80359,Male,26,Masters,13,20,53,41,29,8.0,1,59,Urban,ML Engineer,46472,0 +80360,Female,48,High School,7,95,21,98,6,7.0,2,16,Rural,Software Engineer,105684,0 +80361,Male,47,Bachelors,12,60,0,77,70,8.0,0,80,Semi-Urban,HR Executive,27801,0 +80362,Other,48,Bachelors,4,72,22,14,97,2.0,4,71,Rural,Software Engineer,113730,0 +80363,Female,52,High School,4,58,73,75,35,1.0,2,42,Semi-Urban,Software Engineer,46532,1 +80364,Male,34,PhD,0,97,0,99,61,1.0,7,1,Urban,Manager,84588,0 +80365,Female,25,Diploma,14,3,24,78,18,7.0,2,10,Semi-Urban,Software Engineer,36604,0 +80366,Female,48,Bachelors,0,17,99,43,8,2.0,4,57,Urban,Data Analyst,110546,0 +80367,Female,34,Diploma,6,82,22,58,2,4.0,4,81,Urban,Manager,84292,1 +80368,Male,47,Bachelors,10,40,49,21,41,0.0,0,35,Semi-Urban,Data Analyst,36295,0 +80369,Female,43,High School,4,1,55,75,53,4.0,0,50,Rural,Manager,141574,0 +80370,Male,41,Bachelors,7,87,16,58,69,7.0,3,89,Urban,Manager,64463,1 +80371,Male,44,Diploma,0,96,1,8,27,1.0,7,25,Urban,Data Analyst,107088,0 +80372,Male,42,Bachelors,5,54,26,97,74,2.0,7,35,Rural,Software Engineer,61940,0 +80373,Male,40,High School,10,28,20,77,88,8.0,3,8,Semi-Urban,Software Engineer,60104,0 +80374,Female,22,Bachelors,17,59,50,27,71,5.0,0,78,Urban,Manager,76581,0 +80375,Male,22,Diploma,9,6,98,25,26,6.0,6,76,Semi-Urban,Data Analyst,113029,0 +80376,Female,56,Bachelors,2,55,27,85,67,3.0,5,96,Semi-Urban,HR Executive,75014,1 +80377,Male,56,Bachelors,8,27,77,90,72,8.0,3,84,Urban,ML Engineer,143046,1 +80378,Male,51,High School,8,29,50,96,9,7.0,7,12,Rural,Manager,30614,0 +80379,Male,57,Bachelors,2,70,80,77,96,9.0,0,48,Urban,Software Engineer,88882,1 +80380,Male,30,Diploma,14,25,61,42,2,9.0,4,79,Urban,Software Engineer,30932,0 +80381,Male,40,Bachelors,4,39,25,66,40,7.0,0,41,Urban,Manager,130520,0 +80382,Female,25,Masters,3,83,67,32,18,5.0,6,17,Urban,Manager,78176,0 +80383,Male,30,Masters,19,53,81,81,98,8.0,2,81,Rural,ML Engineer,71233,1 +80384,Male,59,Bachelors,8,87,79,37,13,4.0,3,75,Semi-Urban,Manager,71329,1 +80385,Male,49,Diploma,4,5,98,55,30,9.0,7,40,Urban,Software Engineer,141524,0 +80386,Male,59,Bachelors,7,36,95,58,24,7.0,2,3,Semi-Urban,ML Engineer,149767,0 +80387,Female,41,Diploma,10,93,4,0,97,6.0,1,44,Semi-Urban,Software Engineer,30773,0 +80388,Male,42,Bachelors,1,71,38,25,60,2.0,2,87,Rural,Manager,122346,0 +80389,Female,55,Diploma,12,7,75,7,67,8.0,2,96,Urban,HR Executive,60285,0 +80390,Male,29,PhD,16,40,98,76,85,4.0,7,18,Urban,Data Analyst,51106,0 +80391,Male,27,Masters,7,61,66,9,6,6.0,4,22,Rural,Data Analyst,117740,0 +80392,Female,39,High School,19,57,50,71,16,6.0,6,53,Semi-Urban,Data Analyst,22349,0 +80393,Female,45,Bachelors,5,21,26,64,23,1.0,2,83,Semi-Urban,ML Engineer,38971,0 +80394,Female,45,Bachelors,11,45,6,3,54,8.0,5,54,Semi-Urban,ML Engineer,114985,0 +80395,Male,29,Masters,8,15,68,55,38,9.0,0,53,Urban,ML Engineer,135651,0 +80396,Male,41,High School,14,62,39,98,30,5.0,2,37,Rural,Data Analyst,39790,1 +80397,Female,26,Masters,14,52,71,60,12,0.0,1,47,Rural,Manager,72109,0 +80398,Male,37,Diploma,4,89,72,86,95,5.0,3,78,Rural,Manager,94729,1 +80399,Male,33,Masters,12,32,10,2,36,4.0,5,3,Urban,HR Executive,84761,0 +80400,Male,37,Diploma,19,33,42,4,27,1.0,0,15,Urban,Data Analyst,136604,0 +80401,Female,59,High School,13,17,29,0,24,5.0,3,90,Rural,Software Engineer,42885,0 +80402,Female,38,PhD,13,93,49,37,86,7.0,2,23,Rural,Data Analyst,112447,0 +80403,Male,58,Bachelors,10,89,85,94,68,0.0,7,47,Urban,Software Engineer,64897,1 +80404,Female,33,Bachelors,12,36,56,48,41,3.0,3,17,Urban,Software Engineer,116454,0 +80405,Male,30,High School,1,16,11,2,85,7.0,3,13,Semi-Urban,Software Engineer,24065,0 +80406,Female,39,Diploma,7,75,93,43,3,2.0,1,48,Urban,Manager,41863,1 +80407,Male,41,Bachelors,0,28,66,62,58,1.0,2,93,Urban,HR Executive,25271,1 +80408,Female,25,Masters,8,41,96,45,10,4.0,7,56,Urban,Manager,102613,0 +80409,Male,49,Bachelors,16,96,6,78,0,3.0,1,48,Semi-Urban,ML Engineer,68984,0 +80410,Male,29,Masters,7,12,2,8,12,5.0,6,29,Semi-Urban,ML Engineer,120456,0 +80411,Female,56,Bachelors,17,93,11,19,11,6.0,0,11,Semi-Urban,Data Analyst,122372,0 +80412,Male,55,High School,1,62,58,79,2,7.0,7,29,Semi-Urban,HR Executive,39854,0 +80413,Male,21,Masters,11,56,34,24,62,0.0,1,17,Urban,HR Executive,116978,0 +80414,Male,27,High School,14,19,79,77,23,9.0,1,69,Rural,Data Analyst,140475,1 +80415,Other,31,Masters,0,99,5,12,86,1.0,0,96,Urban,Software Engineer,104035,0 +80416,Female,51,High School,7,44,2,8,95,6.0,2,36,Rural,Software Engineer,30183,0 +80417,Female,30,Masters,9,81,95,57,13,0.0,4,15,Urban,HR Executive,57252,1 +80418,Female,29,Masters,15,63,82,78,10,6.0,5,17,Urban,ML Engineer,37558,0 +80419,Male,41,Diploma,4,24,75,78,81,1.0,7,18,Urban,Data Analyst,39063,0 +80420,Male,57,Masters,18,54,75,28,19,8.0,1,57,Urban,Manager,40952,0 +80421,Female,55,Diploma,8,77,86,92,81,1.0,7,16,Semi-Urban,Manager,32703,1 +80422,Male,47,Masters,18,16,66,34,59,6.0,2,89,Rural,HR Executive,25461,0 +80423,Other,34,Masters,2,90,96,47,3,6.0,1,66,Urban,Data Analyst,35838,1 +80424,Male,42,High School,3,20,10,66,12,2.0,2,65,Urban,HR Executive,58829,0 +80425,Male,22,High School,0,52,92,80,9,3.0,0,95,Urban,Manager,32314,1 +80426,Male,58,Bachelors,17,4,90,6,25,3.0,3,60,Rural,Manager,66100,0 +80427,Male,58,Bachelors,12,72,84,45,92,8.0,1,67,Urban,Software Engineer,122424,1 +80428,Female,50,Masters,13,28,27,20,1,1.0,3,56,Semi-Urban,Software Engineer,70663,0 +80429,Male,39,PhD,11,40,8,84,14,8.0,6,69,Urban,Manager,69536,0 +80430,Male,50,High School,16,35,62,10,5,0.0,4,88,Rural,Data Analyst,68779,0 +80431,Male,26,Diploma,13,2,83,36,95,7.0,2,29,Urban,ML Engineer,88289,0 +80432,Male,41,Diploma,14,79,80,52,32,7.0,5,78,Rural,Data Analyst,26263,1 +80433,Male,58,Masters,14,51,39,89,43,0.0,4,96,Urban,HR Executive,133071,1 +80434,Male,26,Bachelors,12,77,29,0,61,2.0,5,2,Semi-Urban,Manager,30174,0 +80435,Male,51,High School,16,18,80,6,97,7.0,3,12,Rural,Manager,98164,0 +80436,Male,57,Bachelors,17,80,13,5,47,8.0,3,9,Urban,HR Executive,70598,0 +80437,Male,43,Bachelors,18,15,69,14,24,2.0,3,48,Urban,HR Executive,100211,0 +80438,Male,49,Masters,18,52,82,29,87,2.0,5,45,Urban,Software Engineer,22266,0 +80439,Male,40,Diploma,13,76,12,28,88,6.0,1,9,Urban,ML Engineer,77832,0 +80440,Female,58,High School,5,19,97,53,93,4.0,5,26,Urban,ML Engineer,39454,0 +80441,Male,57,Bachelors,0,74,78,57,67,1.0,5,95,Semi-Urban,Data Analyst,83599,1 +80442,Female,37,Bachelors,1,27,57,81,78,0.0,7,5,Semi-Urban,ML Engineer,43378,0 +80443,Female,21,PhD,15,89,40,52,6,9.0,5,0,Rural,Data Analyst,58161,0 +80444,Male,45,High School,1,73,16,13,32,3.0,2,2,Urban,ML Engineer,84822,0 +80445,Male,38,Masters,13,0,22,81,11,6.0,5,24,Urban,Data Analyst,36116,0 +80446,Male,42,High School,18,44,47,21,34,3.0,1,27,Urban,ML Engineer,63809,0 +80447,Other,58,Bachelors,17,22,66,53,10,3.0,0,84,Semi-Urban,Manager,75112,0 +80448,Male,23,Bachelors,6,10,23,2,67,6.0,0,97,Urban,HR Executive,83711,0 +80449,Female,30,Diploma,7,23,95,29,59,1.0,7,81,Semi-Urban,Manager,99169,0 +80450,Female,39,Masters,6,83,10,48,61,8.0,0,6,Urban,ML Engineer,78460,0 +80451,Female,40,Bachelors,6,49,47,88,22,8.0,1,38,Rural,Software Engineer,58887,0 +80452,Male,47,Bachelors,11,9,6,4,18,1.0,6,38,Urban,Manager,48730,0 +80453,Male,22,Masters,5,53,51,13,28,7.0,7,46,Urban,Manager,57863,0 +80454,Male,23,Diploma,15,15,15,95,54,8.0,2,1,Semi-Urban,HR Executive,96770,0 +80455,Male,56,Masters,10,99,66,71,59,8.0,6,16,Urban,Data Analyst,59757,1 +80456,Male,50,High School,14,70,86,53,73,8.0,5,93,Rural,Manager,98602,1 +80457,Female,53,Diploma,11,64,57,54,23,7.0,0,30,Semi-Urban,HR Executive,75186,0 +80458,Male,33,Bachelors,16,92,44,54,87,4.0,1,56,Semi-Urban,HR Executive,26993,1 +80459,Female,32,Masters,18,26,11,61,17,5.0,0,65,Urban,Data Analyst,48774,0 +80460,Female,47,High School,15,92,51,10,19,5.0,4,70,Urban,Data Analyst,83602,0 +80461,Male,52,Bachelors,9,1,54,26,98,2.0,0,10,Urban,HR Executive,89818,0 +80462,Male,30,Bachelors,13,77,14,12,24,2.0,0,59,Rural,HR Executive,114718,0 +80463,Female,35,Bachelors,4,31,85,99,37,2.0,4,54,Semi-Urban,Manager,65834,1 +80464,Male,48,Bachelors,16,19,22,3,37,8.0,4,71,Urban,Data Analyst,131656,0 +80465,Male,33,Masters,6,85,66,81,96,3.0,5,74,Urban,Data Analyst,36493,1 +80466,Male,45,Bachelors,9,18,78,68,37,1.0,5,92,Rural,ML Engineer,124507,1 +80467,Male,36,Masters,14,65,51,92,65,8.0,4,1,Urban,Data Analyst,67482,0 +80468,Female,52,Bachelors,12,84,39,33,31,9.0,4,64,Urban,ML Engineer,117178,0 +80469,Male,48,Bachelors,2,14,97,80,29,7.0,7,50,Semi-Urban,Manager,25211,1 +80470,Male,34,Diploma,4,39,46,49,78,9.0,5,30,Urban,Software Engineer,120464,0 +80471,Male,36,Bachelors,19,37,12,10,0,1.0,4,29,Rural,HR Executive,40646,0 +80472,Female,52,Bachelors,2,28,8,69,26,2.0,3,36,Urban,Manager,135508,0 +80473,Female,52,Diploma,8,14,84,69,76,6.0,6,34,Urban,ML Engineer,116441,0 +80474,Male,53,Masters,19,7,87,25,11,4.0,7,59,Semi-Urban,Manager,20171,0 +80475,Male,29,High School,19,65,29,12,48,4.0,4,59,Urban,Software Engineer,91841,0 +80476,Male,40,Bachelors,7,49,63,8,93,0.0,2,61,Semi-Urban,Software Engineer,47776,0 +80477,Female,58,Bachelors,7,46,33,6,31,6.0,3,19,Rural,Software Engineer,115866,0 +80478,Female,52,High School,3,82,21,35,7,2.0,6,72,Urban,Software Engineer,130288,0 +80479,Male,33,Masters,17,43,47,65,62,8.0,0,85,Urban,Data Analyst,116270,1 +80480,Male,25,Bachelors,10,15,43,37,94,6.0,5,38,Semi-Urban,ML Engineer,122063,0 +80481,Male,48,Diploma,13,71,36,26,98,1.0,5,66,Semi-Urban,Manager,100684,0 +80482,Female,23,PhD,17,45,55,52,18,1.0,7,55,Urban,Data Analyst,40941,0 +80483,Male,53,Bachelors,11,29,27,0,4,2.0,3,43,Urban,Manager,35597,0 +80484,Male,37,Bachelors,16,13,23,86,46,7.0,1,50,Urban,Manager,130382,0 +80485,Female,41,High School,17,5,88,56,9,3.0,5,28,Rural,Data Analyst,73119,0 +80486,Male,55,Masters,0,21,54,5,79,6.0,0,10,Semi-Urban,HR Executive,130240,0 +80487,Male,43,High School,2,11,30,67,79,3.0,0,55,Urban,ML Engineer,146705,0 +80488,Female,29,Diploma,12,32,53,22,62,8.0,6,63,Urban,Software Engineer,117091,0 +80489,Male,52,Masters,9,86,80,62,6,5.0,5,30,Rural,Data Analyst,40971,1 +80490,Other,22,High School,2,41,11,21,91,6.0,6,17,Urban,Manager,87503,0 +80491,Female,59,High School,8,62,99,32,94,2.0,6,46,Urban,ML Engineer,112531,0 +80492,Male,43,High School,19,59,35,53,80,6.0,4,51,Urban,Data Analyst,58974,0 +80493,Female,44,High School,14,28,74,32,71,4.0,5,3,Rural,Software Engineer,69950,0 +80494,Male,34,Bachelors,4,25,44,21,45,4.0,0,91,Rural,Data Analyst,137803,0 +80495,Male,32,Diploma,9,52,2,29,52,2.0,5,28,Urban,Data Analyst,62685,0 +80496,Male,36,High School,17,46,26,68,16,8.0,6,7,Urban,ML Engineer,67559,0 +80497,Male,40,Bachelors,3,4,93,18,35,0.0,6,28,Semi-Urban,ML Engineer,132041,0 +80498,Other,35,Bachelors,9,14,18,90,64,1.0,3,16,Urban,Manager,118124,0 +80499,Male,41,Masters,2,6,34,96,26,2.0,7,82,Urban,Data Analyst,45660,0 +80500,Female,40,Masters,15,73,0,45,56,3.0,3,66,Semi-Urban,HR Executive,115928,0 +80501,Male,59,High School,10,42,24,66,14,7.0,0,14,Rural,HR Executive,145138,0 +80502,Female,59,Masters,0,87,94,78,2,6.0,4,38,Urban,Software Engineer,126806,1 +80503,Male,37,Bachelors,5,6,3,66,45,8.0,3,88,Semi-Urban,Data Analyst,112098,0 +80504,Female,31,Bachelors,15,10,94,65,79,4.0,2,39,Semi-Urban,ML Engineer,54217,0 +80505,Female,50,Bachelors,3,25,29,79,75,2.0,1,46,Semi-Urban,Manager,144401,0 +80506,Male,50,High School,13,80,85,6,91,2.0,7,96,Rural,HR Executive,126193,1 +80507,Male,46,Bachelors,10,61,89,64,74,7.0,6,74,Urban,ML Engineer,68792,1 +80508,Male,50,Masters,13,58,56,42,63,1.0,6,89,Urban,HR Executive,55121,1 +80509,Female,31,Bachelors,6,75,23,84,4,7.0,7,47,Urban,Data Analyst,44570,0 +80510,Female,39,PhD,15,6,64,66,76,6.0,4,70,Urban,Manager,65343,0 +80511,Female,28,Diploma,19,30,37,77,62,0.0,0,80,Semi-Urban,Data Analyst,119732,0 +80512,Female,29,Diploma,10,58,7,89,59,9.0,6,59,Urban,Manager,145744,0 +80513,Female,25,Bachelors,13,64,46,53,98,5.0,3,67,Urban,Software Engineer,129294,0 +80514,Male,43,Diploma,18,96,33,45,83,7.0,5,28,Urban,Data Analyst,144437,0 +80515,Female,59,Masters,14,87,56,97,30,1.0,4,49,Urban,Data Analyst,97876,1 +80516,Female,58,Bachelors,3,58,66,48,48,8.0,3,97,Urban,Manager,118918,1 +80517,Male,21,Diploma,0,29,23,43,91,0.0,7,38,Rural,ML Engineer,97018,0 +80518,Male,59,Bachelors,10,22,32,43,42,1.0,1,19,Urban,Manager,146348,0 +80519,Female,54,High School,10,29,37,65,55,2.0,3,62,Urban,ML Engineer,55297,0 +80520,Female,23,Bachelors,13,3,41,65,69,2.0,2,20,Urban,ML Engineer,64393,0 +80521,Other,43,Bachelors,7,38,11,12,61,1.0,5,88,Urban,Data Analyst,146716,0 +80522,Female,23,Bachelors,4,8,77,55,54,8.0,0,88,Urban,HR Executive,21540,0 +80523,Male,43,High School,6,97,69,80,26,9.0,1,21,Urban,Software Engineer,34084,1 +80524,Male,25,High School,19,46,4,50,4,4.0,7,69,Semi-Urban,HR Executive,56006,0 +80525,Female,54,High School,2,27,0,98,52,9.0,7,18,Semi-Urban,Data Analyst,139673,0 +80526,Female,37,Bachelors,13,78,64,40,53,6.0,4,91,Semi-Urban,Data Analyst,148816,1 +80527,Male,43,High School,1,5,49,72,39,9.0,0,37,Urban,Manager,85360,0 +80528,Male,31,PhD,18,28,4,19,77,5.0,7,80,Urban,Manager,105899,0 +80529,Male,41,Diploma,8,91,46,2,97,4.0,6,68,Urban,ML Engineer,71105,0 +80530,Male,26,Bachelors,7,22,95,81,44,6.0,0,57,Rural,Manager,116680,1 +80531,Female,58,Diploma,11,92,27,38,25,3.0,7,54,Urban,HR Executive,38458,0 +80532,Female,35,Bachelors,17,58,86,79,38,7.0,7,43,Urban,Manager,50734,1 +80533,Female,52,Masters,0,79,7,65,32,3.0,5,72,Rural,HR Executive,32578,0 +80534,Male,21,Bachelors,17,67,31,89,0,7.0,5,72,Semi-Urban,ML Engineer,38104,1 +80535,Male,30,Diploma,15,47,3,19,73,0.0,4,96,Urban,HR Executive,101249,0 +80536,Male,39,PhD,4,54,44,0,21,5.0,0,66,Rural,Data Analyst,144926,0 +80537,Male,53,High School,15,36,78,36,50,2.0,1,96,Rural,HR Executive,90629,1 +80538,Male,47,Bachelors,8,8,96,32,34,2.0,5,42,Urban,Manager,39885,0 +80539,Other,22,Bachelors,15,57,38,73,90,2.0,1,80,Urban,Software Engineer,29297,1 +80540,Female,31,Masters,5,19,76,5,88,3.0,5,25,Urban,Manager,67002,0 +80541,Male,26,Bachelors,6,5,84,57,24,4.0,1,40,Urban,Manager,112144,0 +80542,Male,57,Bachelors,6,76,61,30,36,1.0,5,19,Rural,Manager,86969,0 +80543,Male,48,Bachelors,13,34,60,89,13,6.0,1,38,Urban,ML Engineer,99276,0 +80544,Female,30,Diploma,10,18,76,25,57,3.0,6,39,Urban,HR Executive,69578,0 +80545,Female,54,Bachelors,18,8,56,4,47,3.0,7,96,Semi-Urban,Manager,73261,0 +80546,Female,48,Diploma,9,69,29,85,33,7.0,0,29,Rural,ML Engineer,71045,0 +80547,Female,26,Masters,18,58,95,1,91,3.0,7,20,Semi-Urban,HR Executive,145207,0 +80548,Male,47,Diploma,2,56,62,68,16,8.0,1,26,Semi-Urban,ML Engineer,74321,0 +80549,Male,29,Diploma,1,12,8,62,50,5.0,5,37,Urban,Manager,123639,0 +80550,Male,55,Diploma,3,2,31,51,15,7.0,4,83,Urban,Data Analyst,99259,0 +80551,Male,43,High School,2,44,81,59,68,5.0,1,11,Urban,ML Engineer,93447,0 +80552,Female,26,Diploma,18,46,67,23,47,3.0,2,90,Urban,Manager,113811,0 +80553,Male,59,Masters,15,8,40,27,9,5.0,7,10,Urban,ML Engineer,32258,0 +80554,Male,44,Diploma,10,60,13,65,66,1.0,2,28,Urban,Manager,23471,0 +80555,Female,35,Bachelors,7,84,7,36,5,1.0,3,99,Rural,HR Executive,117780,0 +80556,Male,38,Masters,17,8,25,68,31,8.0,7,51,Semi-Urban,ML Engineer,67104,0 +80557,Male,42,Masters,6,22,66,64,74,8.0,2,72,Rural,Data Analyst,65589,0 +80558,Male,47,Bachelors,9,7,30,10,5,0.0,6,92,Rural,Data Analyst,69393,0 +80559,Male,27,Bachelors,14,18,34,66,66,9.0,7,77,Urban,ML Engineer,48689,0 +80560,Female,42,Bachelors,11,53,61,49,16,9.0,3,88,Urban,ML Engineer,93638,1 +80561,Male,28,Bachelors,12,83,52,75,68,0.0,3,89,Urban,Software Engineer,134221,1 +80562,Male,24,Bachelors,12,85,31,56,30,5.0,7,50,Urban,ML Engineer,26308,0 +80563,Female,48,High School,3,87,86,8,88,0.0,1,98,Semi-Urban,HR Executive,51095,1 +80564,Male,53,High School,2,99,48,90,24,8.0,1,34,Rural,Manager,93483,1 +80565,Male,27,Bachelors,9,31,84,11,75,3.0,3,5,Urban,Manager,135818,0 +80566,Male,31,Bachelors,3,71,97,97,31,4.0,1,51,Urban,ML Engineer,122449,1 +80567,Male,49,High School,3,65,94,36,63,8.0,1,36,Urban,Data Analyst,46928,0 +80568,Other,30,Diploma,12,44,96,42,86,6.0,1,26,Semi-Urban,Data Analyst,72710,0 +80569,Male,46,High School,16,93,15,85,0,6.0,7,30,Semi-Urban,ML Engineer,50698,0 +80570,Male,32,Bachelors,17,56,83,52,93,6.0,4,59,Urban,Software Engineer,93322,1 +80571,Male,45,Bachelors,12,12,77,8,65,4.0,6,6,Semi-Urban,HR Executive,105160,0 +80572,Male,51,Diploma,9,44,55,62,97,2.0,4,56,Semi-Urban,ML Engineer,81532,0 +80573,Male,50,Masters,12,61,45,85,56,7.0,1,36,Semi-Urban,ML Engineer,138437,0 +80574,Male,21,Masters,3,66,25,39,25,2.0,7,4,Semi-Urban,Data Analyst,128565,0 +80575,Female,57,PhD,10,95,83,39,73,5.0,6,28,Urban,Manager,134055,1 +80576,Male,51,High School,15,90,83,90,32,1.0,6,44,Urban,Manager,62941,1 +80577,Male,39,Bachelors,16,63,17,15,56,3.0,3,85,Urban,HR Executive,129054,0 +80578,Female,45,Masters,13,65,68,28,37,2.0,6,22,Rural,Software Engineer,43585,0 +80579,Male,28,Bachelors,2,3,82,8,17,3.0,3,43,Rural,Software Engineer,127971,0 +80580,Male,33,Bachelors,6,23,42,36,9,3.0,1,49,Semi-Urban,HR Executive,55216,0 +80581,Other,49,Bachelors,2,57,84,14,4,7.0,5,96,Rural,Manager,44683,1 +80582,Female,32,High School,8,85,31,28,7,9.0,0,85,Urban,Software Engineer,24795,0 +80583,Male,59,Bachelors,10,22,62,32,0,0.0,6,31,Urban,Manager,89935,0 +80584,Female,37,Bachelors,12,87,46,17,39,2.0,7,91,Semi-Urban,Software Engineer,47257,1 +80585,Male,27,Bachelors,12,4,81,54,83,4.0,0,73,Semi-Urban,Software Engineer,112648,0 +80586,Other,23,Masters,9,49,3,87,42,7.0,6,51,Urban,ML Engineer,122908,0 +80587,Male,52,Bachelors,17,74,4,12,31,5.0,4,68,Urban,ML Engineer,147602,0 +80588,Female,35,Diploma,17,93,7,62,54,1.0,2,0,Semi-Urban,ML Engineer,101728,0 +80589,Male,26,Bachelors,2,5,25,29,18,9.0,2,37,Urban,Manager,51072,0 +80590,Male,25,Diploma,13,80,70,18,59,7.0,7,51,Rural,HR Executive,32747,0 +80591,Female,41,Bachelors,0,50,12,96,52,3.0,3,87,Semi-Urban,HR Executive,118969,1 +80592,Female,50,Diploma,18,6,89,56,74,3.0,3,50,Semi-Urban,Software Engineer,121063,0 +80593,Male,48,Masters,2,28,86,81,71,7.0,1,64,Urban,ML Engineer,128716,1 +80594,Male,57,Bachelors,15,40,31,52,12,3.0,4,60,Urban,HR Executive,67818,0 +80595,Male,36,Diploma,1,4,86,67,76,2.0,4,18,Urban,HR Executive,113494,0 +80596,Female,40,Diploma,11,87,56,97,84,3.0,7,93,Semi-Urban,Data Analyst,32368,1 +80597,Male,41,High School,12,1,73,56,67,0.0,5,55,Semi-Urban,Data Analyst,52757,0 +80598,Male,29,Bachelors,15,15,29,64,35,2.0,2,9,Semi-Urban,Data Analyst,49278,0 +80599,Female,50,High School,15,63,65,22,78,1.0,0,64,Rural,Software Engineer,36460,0 +80600,Female,32,Bachelors,15,30,3,24,83,4.0,0,2,Urban,ML Engineer,70637,0 +80601,Female,41,Bachelors,3,41,62,35,25,5.0,6,96,Semi-Urban,Data Analyst,55625,0 +80602,Female,53,Diploma,15,64,21,59,83,8.0,4,69,Urban,Data Analyst,119451,0 +80603,Male,52,Masters,18,81,26,12,93,5.0,3,51,Urban,ML Engineer,53107,0 +80604,Female,44,High School,10,73,53,42,80,4.0,7,78,Urban,Software Engineer,68607,1 +80605,Male,30,High School,3,13,64,86,62,7.0,7,39,Semi-Urban,Software Engineer,132481,0 +80606,Male,38,Bachelors,10,64,0,39,58,8.0,2,5,Urban,Data Analyst,124109,0 +80607,Female,35,Bachelors,13,95,55,52,44,4.0,4,38,Urban,Data Analyst,60829,0 +80608,Male,44,PhD,19,34,51,13,14,0.0,6,83,Semi-Urban,Data Analyst,99955,0 +80609,Female,24,Masters,2,43,79,90,89,7.0,0,15,Rural,HR Executive,39489,0 +80610,Male,30,High School,15,87,0,23,95,1.0,7,50,Rural,HR Executive,124854,0 +80611,Male,48,Masters,3,98,82,14,14,8.0,5,53,Urban,HR Executive,67191,1 +80612,Male,31,Masters,14,46,58,64,30,3.0,0,56,Semi-Urban,ML Engineer,144267,0 +80613,Male,59,Bachelors,3,73,82,88,68,7.0,2,94,Urban,Data Analyst,78189,1 +80614,Other,42,High School,19,45,6,44,26,1.0,6,16,Urban,Manager,72633,0 +80615,Male,27,Diploma,2,22,1,3,20,3.0,4,50,Semi-Urban,Software Engineer,146271,0 +80616,Female,26,Bachelors,9,1,79,37,42,6.0,5,90,Urban,HR Executive,137810,0 +80617,Male,45,Diploma,16,86,67,24,47,9.0,4,85,Urban,Software Engineer,56698,1 +80618,Male,21,Bachelors,1,53,12,79,24,0.0,6,79,Semi-Urban,ML Engineer,34940,0 +80619,Female,32,Diploma,7,46,53,32,26,7.0,6,36,Rural,Manager,63483,0 +80620,Female,42,Bachelors,9,53,30,40,96,7.0,0,6,Urban,ML Engineer,80697,0 +80621,Male,50,Bachelors,4,60,15,41,65,4.0,1,59,Semi-Urban,ML Engineer,78741,0 +80622,Female,45,Bachelors,11,51,9,59,83,2.0,1,82,Semi-Urban,Data Analyst,120980,0 +80623,Male,39,Bachelors,3,18,7,9,12,6.0,3,25,Urban,Data Analyst,69789,0 +80624,Male,30,Masters,8,79,1,91,87,8.0,3,55,Rural,ML Engineer,51821,0 +80625,Female,25,Masters,18,35,53,50,12,8.0,5,53,Semi-Urban,Software Engineer,89813,0 +80626,Male,23,High School,14,13,54,49,37,4.0,4,83,Urban,Data Analyst,97178,0 +80627,Female,21,Bachelors,17,19,54,39,50,4.0,6,33,Urban,Software Engineer,96421,0 +80628,Female,35,Diploma,3,84,67,89,74,3.0,3,96,Urban,Software Engineer,100554,1 +80629,Female,27,Bachelors,18,65,98,57,91,6.0,3,40,Semi-Urban,Manager,103846,1 +80630,Male,21,High School,9,7,48,4,93,4.0,5,13,Urban,Manager,54912,0 +80631,Male,41,PhD,1,3,60,77,52,6.0,3,38,Urban,Manager,20644,0 +80632,Female,48,Bachelors,13,1,31,52,29,1.0,4,57,Rural,Software Engineer,80922,0 +80633,Male,31,PhD,13,81,9,39,67,1.0,6,50,Semi-Urban,Data Analyst,139948,0 +80634,Male,38,PhD,7,59,43,4,38,0.0,6,26,Urban,ML Engineer,56310,0 +80635,Male,50,Bachelors,11,82,68,85,90,0.0,2,9,Urban,Software Engineer,77199,1 +80636,Male,45,Bachelors,13,49,1,7,50,0.0,2,18,Urban,Data Analyst,115781,0 +80637,Female,41,Masters,5,87,67,0,18,1.0,2,70,Semi-Urban,HR Executive,52802,0 +80638,Female,51,Diploma,6,86,56,8,35,8.0,2,43,Urban,ML Engineer,26432,0 +80639,Male,29,Masters,13,30,11,97,95,4.0,2,76,Rural,Data Analyst,118160,0 +80640,Female,27,High School,3,13,4,85,71,9.0,4,44,Urban,ML Engineer,95179,0 +80641,Female,23,PhD,16,46,20,34,35,0.0,5,28,Rural,HR Executive,45494,0 +80642,Female,27,Bachelors,8,56,65,36,5,6.0,2,96,Semi-Urban,ML Engineer,135564,1 +80643,Male,45,Bachelors,8,8,88,66,54,2.0,5,51,Urban,HR Executive,145002,0 +80644,Male,49,High School,10,61,51,45,44,8.0,0,71,Rural,ML Engineer,144509,0 +80645,Male,37,Masters,13,21,22,42,28,3.0,6,80,Rural,HR Executive,104129,0 +80646,Male,59,Bachelors,0,52,53,58,82,1.0,6,64,Urban,Software Engineer,76282,0 +80647,Male,34,Bachelors,12,3,11,31,31,8.0,4,90,Urban,Data Analyst,101031,0 +80648,Male,22,High School,0,72,80,70,40,3.0,0,12,Urban,Software Engineer,137185,0 +80649,Male,22,Bachelors,11,81,74,84,40,7.0,6,13,Urban,Manager,65044,1 +80650,Female,40,High School,0,11,82,90,73,4.0,2,37,Semi-Urban,HR Executive,49880,0 +80651,Male,22,High School,17,78,3,91,12,0.0,2,84,Semi-Urban,Data Analyst,28056,1 +80652,Male,37,Bachelors,10,99,66,49,10,6.0,6,30,Semi-Urban,ML Engineer,149910,1 +80653,Female,56,Diploma,2,90,93,49,74,2.0,6,31,Rural,Data Analyst,28633,1 +80654,Male,50,Bachelors,15,79,76,56,4,5.0,7,74,Rural,Software Engineer,120446,1 +80655,Female,26,Bachelors,3,43,74,4,47,7.0,6,61,Semi-Urban,Manager,43241,0 +80656,Male,24,High School,1,83,66,26,91,8.0,3,74,Rural,Manager,89298,1 +80657,Male,59,Masters,14,15,14,14,41,1.0,0,0,Rural,Software Engineer,62413,0 +80658,Male,27,Bachelors,6,29,15,90,91,0.0,0,9,Rural,Software Engineer,65991,0 +80659,Male,23,Diploma,12,46,82,37,28,0.0,7,64,Urban,Manager,38759,0 +80660,Male,23,Diploma,12,60,26,29,27,5.0,7,74,Urban,ML Engineer,67883,0 +80661,Female,56,Bachelors,12,15,73,35,59,5.0,7,96,Urban,ML Engineer,65973,0 +80662,Female,36,Diploma,10,66,99,88,40,9.0,3,85,Semi-Urban,HR Executive,72270,1 +80663,Male,27,Diploma,11,88,86,86,40,5.0,1,16,Rural,ML Engineer,79417,1 +80664,Female,34,High School,13,59,31,29,77,3.0,3,47,Urban,Manager,139739,0 +80665,Male,58,Bachelors,8,74,55,87,32,7.0,7,15,Urban,Manager,62254,0 +80666,Female,57,Masters,9,60,76,31,64,3.0,6,5,Urban,ML Engineer,21789,0 +80667,Female,21,Masters,3,54,48,75,30,3.0,2,1,Rural,HR Executive,133266,0 +80668,Male,48,Bachelors,7,24,71,66,77,7.0,1,23,Semi-Urban,ML Engineer,133930,0 +80669,Male,26,Bachelors,6,36,2,31,56,6.0,1,9,Urban,HR Executive,21464,0 +80670,Male,26,Masters,16,92,36,73,79,8.0,3,92,Semi-Urban,HR Executive,55704,1 +80671,Other,44,Diploma,6,29,46,66,55,1.0,2,64,Urban,Data Analyst,147616,0 +80672,Male,54,Bachelors,12,91,72,35,56,5.0,5,31,Rural,HR Executive,91182,0 +80673,Male,59,Diploma,10,21,91,46,44,8.0,5,50,Urban,Manager,140870,0 +80674,Female,54,Diploma,11,37,74,4,76,0.0,2,95,Urban,Manager,52057,0 +80675,Female,50,Bachelors,11,4,41,64,79,6.0,3,81,Rural,Manager,70875,0 +80676,Male,40,Bachelors,0,14,6,68,82,7.0,2,74,Urban,Software Engineer,119808,0 +80677,Female,26,Diploma,9,6,13,55,76,4.0,5,57,Semi-Urban,Manager,107131,0 +80678,Female,23,Bachelors,9,89,25,1,74,7.0,6,84,Semi-Urban,HR Executive,43933,0 +80679,Male,38,PhD,19,78,87,94,2,3.0,2,76,Urban,Manager,149618,1 +80680,Other,51,Bachelors,7,86,87,33,96,4.0,5,60,Urban,Software Engineer,83083,1 +80681,Male,51,Bachelors,18,95,14,50,35,9.0,2,52,Rural,Data Analyst,143582,0 +80682,Male,38,PhD,12,17,60,9,63,3.0,1,12,Rural,ML Engineer,69249,0 +80683,Male,26,Bachelors,13,79,16,81,78,2.0,2,87,Rural,Software Engineer,137577,1 +80684,Male,38,Masters,4,0,19,35,23,4.0,1,31,Rural,Manager,30874,0 +80685,Other,51,Bachelors,14,67,21,73,18,5.0,3,69,Semi-Urban,Manager,80240,0 +80686,Male,24,Bachelors,19,47,72,2,63,3.0,2,73,Urban,Software Engineer,27976,0 +80687,Male,55,PhD,3,69,95,88,87,1.0,1,68,Rural,HR Executive,30396,1 +80688,Male,49,Bachelors,16,16,0,37,86,7.0,7,57,Urban,Software Engineer,35469,0 +80689,Male,56,Bachelors,18,22,2,97,4,7.0,0,8,Urban,Data Analyst,147183,0 +80690,Other,37,Bachelors,14,78,81,18,51,8.0,1,45,Urban,Data Analyst,38416,0 +80691,Female,40,Masters,8,47,45,22,67,7.0,0,71,Semi-Urban,Data Analyst,65253,0 +80692,Female,40,Diploma,16,57,72,3,67,8.0,3,21,Urban,ML Engineer,76380,0 +80693,Female,53,Bachelors,14,4,69,94,37,4.0,5,17,Urban,ML Engineer,92921,0 +80694,Male,38,Bachelors,17,86,91,5,3,7.0,4,72,Urban,HR Executive,44820,1 +80695,Male,22,Diploma,13,91,12,3,53,5.0,7,66,Semi-Urban,Software Engineer,83048,0 +80696,Male,25,Diploma,0,30,54,67,45,6.0,5,63,Urban,Data Analyst,146396,0 +80697,Other,26,Diploma,6,91,22,70,28,3.0,4,12,Urban,HR Executive,121396,0 +80698,Female,47,Bachelors,17,36,42,6,45,7.0,1,44,Rural,Data Analyst,100561,0 +80699,Male,44,High School,3,21,26,35,35,3.0,6,46,Urban,ML Engineer,146518,0 +80700,Male,25,Diploma,6,96,34,65,45,1.0,5,35,Semi-Urban,HR Executive,84584,0 +80701,Female,43,Diploma,17,4,51,8,57,5.0,6,88,Urban,ML Engineer,53541,0 +80702,Male,40,High School,18,2,27,27,20,1.0,0,11,Urban,HR Executive,104279,0 +80703,Male,47,Bachelors,15,44,88,58,98,9.0,7,13,Urban,Software Engineer,120283,0 +80704,Male,57,Bachelors,18,72,53,73,35,2.0,5,91,Rural,HR Executive,30857,1 +80705,Female,30,High School,5,65,98,6,69,0.0,6,42,Semi-Urban,Manager,22017,0 +80706,Female,21,Bachelors,10,69,13,65,76,4.0,1,81,Semi-Urban,HR Executive,102201,0 +80707,Male,33,Diploma,18,18,38,70,51,0.0,6,0,Urban,Manager,71282,0 +80708,Male,56,Masters,8,17,52,0,92,0.0,1,55,Rural,Manager,109444,0 +80709,Male,24,High School,15,32,44,79,6,3.0,5,43,Urban,Data Analyst,142432,0 +80710,Male,45,Diploma,1,46,79,55,84,7.0,1,55,Urban,Manager,124747,1 +80711,Female,36,Diploma,8,40,89,57,47,1.0,7,93,Urban,Data Analyst,133166,1 +80712,Female,59,Masters,7,73,86,88,92,5.0,1,74,Urban,Data Analyst,109403,1 +80713,Male,48,Bachelors,2,72,59,94,18,7.0,7,13,Rural,ML Engineer,109838,1 +80714,Male,58,Diploma,10,98,9,19,27,2.0,5,37,Semi-Urban,ML Engineer,99229,0 +80715,Female,34,Masters,17,7,89,78,58,3.0,0,22,Rural,Software Engineer,141520,0 +80716,Male,59,Masters,13,72,36,99,7,2.0,4,79,Urban,ML Engineer,138883,1 +80717,Male,21,Masters,3,81,90,23,60,0.0,5,59,Semi-Urban,ML Engineer,110813,1 +80718,Male,45,Diploma,7,66,56,15,80,8.0,4,81,Urban,HR Executive,106742,0 +80719,Female,45,Bachelors,7,22,99,37,45,4.0,7,95,Urban,Manager,74933,1 +80720,Female,25,Masters,2,81,43,80,38,1.0,4,61,Urban,ML Engineer,71802,1 +80721,Male,39,Bachelors,9,14,37,54,71,7.0,4,68,Rural,Data Analyst,72071,0 +80722,Male,53,Bachelors,9,72,15,9,2,7.0,1,41,Rural,HR Executive,47978,0 +80723,Male,29,High School,0,28,5,30,78,8.0,6,99,Urban,HR Executive,64834,0 +80724,Male,30,High School,4,89,38,86,28,6.0,1,63,Semi-Urban,HR Executive,33335,1 +80725,Female,55,Diploma,7,17,26,3,86,2.0,6,17,Rural,Software Engineer,38971,0 +80726,Male,55,Bachelors,3,27,27,9,58,6.0,1,10,Rural,Software Engineer,132218,0 +80727,Male,29,Diploma,9,91,17,92,92,0.0,6,38,Urban,Data Analyst,131234,1 +80728,Female,30,Bachelors,1,99,81,98,18,0.0,7,47,Urban,Manager,127566,1 +80729,Male,31,Masters,4,98,8,71,86,3.0,6,24,Rural,Software Engineer,138791,0 +80730,Male,54,Masters,19,78,35,6,82,3.0,2,59,Rural,Manager,106162,0 +80731,Male,42,Masters,9,86,2,47,84,0.0,5,28,Urban,HR Executive,95759,0 +80732,Female,23,Diploma,16,39,23,65,29,0.0,0,21,Semi-Urban,Manager,40594,0 +80733,Male,22,High School,1,7,19,29,39,1.0,3,23,Urban,Manager,100951,0 +80734,Other,32,Bachelors,19,31,22,78,74,2.0,5,35,Semi-Urban,Data Analyst,55182,0 +80735,Male,50,High School,10,58,36,82,87,3.0,5,72,Urban,Software Engineer,58787,1 +80736,Female,47,Masters,5,49,50,18,33,1.0,3,23,Rural,HR Executive,25666,0 +80737,Male,36,Diploma,15,90,80,36,84,5.0,2,72,Urban,HR Executive,74497,1 +80738,Male,59,High School,1,79,71,46,91,3.0,0,7,Urban,HR Executive,41528,0 +80739,Other,48,Bachelors,10,55,60,72,8,6.0,2,82,Rural,Data Analyst,116826,1 +80740,Female,58,Bachelors,1,65,32,99,23,8.0,4,91,Urban,Data Analyst,22622,1 +80741,Male,34,Bachelors,10,55,2,15,33,0.0,5,97,Semi-Urban,Manager,88344,0 +80742,Male,36,Bachelors,17,97,0,52,32,9.0,1,41,Rural,Data Analyst,70009,0 +80743,Male,58,Bachelors,16,66,76,88,69,8.0,7,79,Urban,Software Engineer,69137,1 +80744,Male,33,Bachelors,15,87,51,11,20,3.0,2,19,Urban,HR Executive,140073,0 +80745,Female,59,Masters,13,97,49,12,59,0.0,7,96,Semi-Urban,Software Engineer,128657,1 +80746,Female,51,Diploma,5,0,79,13,18,8.0,3,77,Urban,HR Executive,126342,0 +80747,Male,36,Bachelors,10,14,50,93,31,1.0,2,79,Urban,ML Engineer,132023,1 +80748,Male,43,Masters,12,23,13,58,63,5.0,4,86,Urban,ML Engineer,74646,0 +80749,Male,47,Masters,0,25,94,83,62,6.0,0,38,Urban,ML Engineer,63003,1 +80750,Male,46,Bachelors,5,22,51,60,91,9.0,7,64,Rural,ML Engineer,75288,0 +80751,Male,44,Masters,11,84,87,60,11,2.0,6,13,Urban,Manager,140239,1 +80752,Male,52,Diploma,10,56,95,76,51,8.0,1,4,Rural,ML Engineer,48447,0 +80753,Female,36,Bachelors,19,80,83,26,86,2.0,2,50,Urban,HR Executive,89421,0 +80754,Male,46,Masters,1,14,19,33,86,3.0,6,61,Urban,Data Analyst,135932,0 +80755,Male,42,Bachelors,10,21,64,39,64,2.0,4,32,Semi-Urban,ML Engineer,23385,0 +80756,Female,54,Bachelors,13,71,62,79,93,7.0,3,34,Rural,HR Executive,37156,1 +80757,Female,40,Diploma,17,11,38,49,32,2.0,3,38,Urban,Manager,146721,0 +80758,Male,48,PhD,0,76,53,12,56,5.0,3,56,Rural,Data Analyst,35867,0 +80759,Male,41,Masters,14,66,87,44,66,7.0,0,65,Rural,ML Engineer,115868,1 +80760,Male,29,Diploma,3,94,29,64,34,0.0,7,46,Urban,ML Engineer,59461,0 +80761,Female,45,Diploma,11,87,53,75,24,5.0,4,59,Urban,Software Engineer,61342,1 +80762,Male,28,Bachelors,0,55,57,48,45,8.0,6,19,Urban,HR Executive,107282,0 +80763,Female,37,Bachelors,19,60,43,70,11,6.0,5,91,Urban,HR Executive,24687,1 +80764,Female,49,High School,16,68,44,79,65,8.0,3,7,Urban,Manager,74135,0 +80765,Female,45,Masters,18,96,93,33,74,4.0,3,61,Rural,Manager,82811,1 +80766,Male,32,Masters,17,48,37,22,67,3.0,7,12,Urban,Software Engineer,37418,0 +80767,Male,46,Bachelors,2,57,8,65,37,5.0,6,34,Urban,Manager,74112,0 +80768,Male,28,Bachelors,4,78,26,11,45,5.0,7,50,Rural,ML Engineer,63240,0 +80769,Female,32,Bachelors,0,0,55,31,9,0.0,7,68,Urban,HR Executive,122656,0 +80770,Male,40,PhD,7,87,53,60,25,2.0,3,76,Urban,HR Executive,113578,1 +80771,Female,32,Bachelors,3,81,62,57,36,6.0,2,82,Semi-Urban,HR Executive,87428,1 +80772,Other,21,High School,4,88,21,74,21,3.0,4,60,Semi-Urban,HR Executive,28877,1 +80773,Female,57,High School,11,25,97,27,18,3.0,7,67,Urban,Manager,89747,0 +80774,Male,49,High School,9,22,14,17,68,2.0,3,87,Urban,HR Executive,131441,0 +80775,Female,38,Diploma,4,78,54,27,77,6.0,6,42,Rural,Manager,107097,0 +80776,Female,44,Bachelors,2,66,20,32,12,2.0,7,21,Rural,Software Engineer,140064,0 +80777,Female,21,Bachelors,13,96,98,77,60,0.0,7,91,Semi-Urban,Data Analyst,58591,1 +80778,Male,28,High School,9,40,62,24,70,0.0,4,15,Urban,HR Executive,140791,0 +80779,Female,58,Bachelors,2,22,77,3,90,8.0,0,51,Urban,Software Engineer,142915,0 +80780,Male,24,PhD,1,31,61,38,49,1.0,6,85,Rural,Manager,41717,0 +80781,Male,25,Diploma,17,95,99,37,83,9.0,7,7,Semi-Urban,HR Executive,42505,1 +80782,Female,53,Bachelors,12,59,66,45,38,0.0,7,60,Rural,Software Engineer,99137,0 +80783,Male,39,PhD,15,86,85,75,62,8.0,0,98,Semi-Urban,Manager,57358,1 +80784,Male,51,Bachelors,17,42,45,46,32,1.0,4,96,Urban,Software Engineer,74568,0 +80785,Male,24,High School,12,62,93,49,14,5.0,6,99,Semi-Urban,Data Analyst,113072,1 +80786,Male,37,Diploma,0,21,20,2,68,2.0,3,22,Urban,Manager,129504,0 +80787,Male,23,Masters,16,65,96,91,40,8.0,6,55,Urban,HR Executive,91433,1 +80788,Other,43,PhD,1,35,14,98,90,6.0,0,19,Semi-Urban,Data Analyst,103300,0 +80789,Male,39,Bachelors,3,8,72,63,95,2.0,7,36,Semi-Urban,ML Engineer,141227,0 +80790,Male,27,Diploma,0,5,38,4,62,9.0,4,0,Semi-Urban,Software Engineer,126811,0 +80791,Male,33,High School,11,76,59,98,79,2.0,1,16,Urban,ML Engineer,45574,1 +80792,Male,41,Bachelors,8,26,87,79,66,0.0,6,69,Urban,Manager,126509,1 +80793,Female,23,Masters,10,24,14,48,92,3.0,1,49,Rural,Data Analyst,56524,0 +80794,Male,55,Diploma,16,19,47,80,94,4.0,1,77,Urban,HR Executive,48574,0 +80795,Female,55,High School,18,74,55,95,11,3.0,7,35,Urban,Data Analyst,22024,1 +80796,Male,40,Masters,9,69,76,22,63,6.0,6,43,Urban,Software Engineer,119254,0 +80797,Female,42,Bachelors,8,25,63,86,61,7.0,5,55,Urban,HR Executive,124999,0 +80798,Female,49,Bachelors,3,95,58,99,60,7.0,6,3,Urban,HR Executive,37188,1 +80799,Female,53,High School,14,52,10,13,74,9.0,6,41,Semi-Urban,Software Engineer,137768,0 +80800,Female,58,Bachelors,1,0,34,35,22,1.0,7,33,Urban,Manager,40821,0 +80801,Female,37,Bachelors,3,32,6,59,77,4.0,6,95,Urban,Software Engineer,99521,0 +80802,Other,49,High School,12,51,2,80,75,6.0,3,77,Urban,ML Engineer,68387,0 +80803,Female,33,Bachelors,10,1,46,33,94,6.0,5,99,Urban,HR Executive,82253,0 +80804,Female,35,Bachelors,18,44,17,44,34,8.0,2,5,Semi-Urban,ML Engineer,135829,0 +80805,Male,59,Masters,12,10,65,19,43,8.0,0,10,Rural,ML Engineer,144911,0 +80806,Male,22,Masters,13,67,70,41,31,7.0,5,77,Semi-Urban,Data Analyst,53056,1 +80807,Male,51,Masters,8,93,66,1,83,1.0,6,83,Rural,HR Executive,37484,1 +80808,Female,27,Masters,7,78,57,56,88,1.0,2,98,Rural,Software Engineer,49771,1 +80809,Male,22,Bachelors,0,51,1,83,96,1.0,0,90,Urban,Software Engineer,59660,0 +80810,Male,59,Bachelors,19,15,7,89,7,1.0,2,51,Rural,HR Executive,66007,0 +80811,Female,46,PhD,1,61,80,87,60,7.0,5,39,Rural,HR Executive,131227,1 +80812,Male,39,Bachelors,12,93,66,28,14,3.0,2,58,Urban,HR Executive,97519,1 +80813,Male,46,Bachelors,11,45,4,69,51,5.0,2,11,Rural,HR Executive,105143,0 +80814,Male,24,Bachelors,6,76,1,36,44,2.0,3,36,Semi-Urban,HR Executive,92476,0 +80815,Female,45,Bachelors,6,16,6,51,83,3.0,3,27,Rural,Data Analyst,123716,0 +80816,Male,55,Bachelors,7,84,65,41,51,4.0,5,54,Rural,ML Engineer,75571,1 +80817,Male,58,Bachelors,14,97,56,85,27,9.0,0,87,Urban,Data Analyst,137063,1 +80818,Male,58,PhD,1,93,95,22,15,3.0,6,24,Urban,Software Engineer,133874,0 +80819,Male,46,Bachelors,18,28,44,88,10,3.0,1,11,Urban,Software Engineer,77695,0 +80820,Male,52,Masters,11,59,10,99,44,0.0,1,36,Urban,Manager,121948,0 +80821,Female,41,PhD,13,97,57,88,52,5.0,7,99,Rural,Data Analyst,50454,1 +80822,Male,40,High School,11,81,97,65,91,8.0,6,98,Rural,ML Engineer,41235,1 +80823,Female,51,High School,7,10,49,75,14,7.0,7,75,Urban,HR Executive,76799,0 +80824,Female,29,Diploma,5,85,57,36,42,7.0,5,44,Urban,Manager,119849,0 +80825,Male,49,Bachelors,9,45,5,65,32,3.0,0,24,Urban,Manager,138387,0 +80826,Female,28,Masters,19,40,92,87,47,5.0,5,72,Urban,ML Engineer,58609,1 +80827,Female,32,High School,7,50,46,93,82,1.0,7,65,Urban,Manager,138443,1 +80828,Male,27,Diploma,14,76,64,54,34,8.0,6,60,Rural,Data Analyst,148730,1 +80829,Male,41,High School,7,40,53,92,85,9.0,0,39,Semi-Urban,Data Analyst,37420,0 +80830,Male,46,Masters,12,28,85,7,89,7.0,6,0,Semi-Urban,HR Executive,51668,0 +80831,Female,36,High School,15,59,79,14,85,4.0,7,92,Rural,HR Executive,46017,1 +80832,Male,30,High School,18,45,68,2,76,0.0,3,50,Urban,HR Executive,55901,0 +80833,Female,39,Diploma,0,88,30,76,72,1.0,5,98,Urban,Data Analyst,32608,1 +80834,Male,31,Bachelors,13,24,68,5,76,2.0,1,40,Urban,ML Engineer,73404,0 +80835,Male,32,Bachelors,7,71,6,40,53,2.0,5,96,Semi-Urban,Data Analyst,141122,0 +80836,Male,54,Bachelors,9,34,91,83,26,0.0,7,82,Urban,Manager,42947,1 +80837,Other,55,Bachelors,0,98,54,9,73,6.0,6,21,Urban,Software Engineer,58466,0 +80838,Male,55,PhD,19,75,56,10,78,4.0,2,85,Urban,Manager,41665,0 +80839,Female,47,Diploma,16,37,93,71,58,4.0,5,85,Semi-Urban,ML Engineer,126753,1 +80840,Female,33,High School,12,96,24,48,5,9.0,0,69,Rural,ML Engineer,102685,0 +80841,Male,54,High School,18,11,9,47,2,9.0,0,95,Rural,Data Analyst,112832,0 +80842,Male,38,High School,16,10,53,47,81,7.0,7,89,Rural,Data Analyst,133982,0 +80843,Female,49,Diploma,15,10,17,87,49,2.0,7,73,Urban,Manager,27816,0 +80844,Female,39,Diploma,14,96,5,98,66,9.0,3,44,Rural,HR Executive,123783,1 +80845,Male,51,Diploma,10,24,79,50,2,3.0,6,51,Urban,ML Engineer,92843,0 +80846,Female,57,Masters,2,46,82,16,66,1.0,0,80,Urban,Software Engineer,55468,0 +80847,Male,58,Bachelors,13,31,59,52,54,7.0,2,3,Urban,ML Engineer,98876,0 +80848,Male,27,Diploma,19,85,17,16,48,7.0,7,71,Urban,Data Analyst,142796,0 +80849,Male,46,PhD,4,92,60,87,4,5.0,1,61,Semi-Urban,Software Engineer,104239,1 +80850,Female,40,Masters,19,25,40,79,24,5.0,7,12,Urban,HR Executive,80547,0 +80851,Male,26,High School,0,68,63,62,13,2.0,6,47,Urban,HR Executive,86180,1 +80852,Female,22,Bachelors,19,19,90,53,54,4.0,6,99,Urban,Manager,122679,1 +80853,Male,33,High School,14,69,48,84,51,7.0,6,31,Semi-Urban,HR Executive,116024,0 +80854,Male,45,High School,8,13,9,27,37,2.0,6,62,Semi-Urban,Data Analyst,50396,0 +80855,Female,35,Bachelors,5,65,56,72,9,3.0,0,74,Semi-Urban,Software Engineer,26019,1 +80856,Female,23,High School,15,8,41,51,65,4.0,3,31,Urban,Data Analyst,44876,0 +80857,Male,58,Diploma,18,67,3,21,47,2.0,7,77,Rural,ML Engineer,109495,0 +80858,Male,32,PhD,13,33,99,65,70,7.0,5,8,Urban,Data Analyst,82789,0 +80859,Female,35,Masters,1,44,69,12,36,1.0,7,61,Urban,Data Analyst,135044,0 +80860,Female,37,Masters,10,14,83,21,73,2.0,6,76,Rural,HR Executive,61920,0 +80861,Male,38,PhD,13,18,1,35,39,8.0,6,85,Semi-Urban,ML Engineer,119545,0 +80862,Female,58,Bachelors,16,3,12,38,18,9.0,3,15,Rural,Software Engineer,140702,0 +80863,Female,43,Bachelors,5,52,60,41,93,9.0,3,58,Semi-Urban,ML Engineer,71209,0 +80864,Female,56,Bachelors,5,88,89,0,62,1.0,5,57,Urban,Data Analyst,143510,0 +80865,Male,23,Bachelors,8,51,29,12,85,4.0,3,35,Semi-Urban,Manager,60783,0 +80866,Male,37,Masters,6,60,12,45,16,9.0,3,87,Urban,HR Executive,140599,0 +80867,Male,43,Masters,1,98,97,4,37,0.0,2,28,Rural,HR Executive,99574,0 +80868,Female,38,Diploma,16,3,7,29,7,9.0,2,4,Rural,Manager,38002,0 +80869,Male,36,Bachelors,13,56,31,64,46,7.0,5,35,Urban,ML Engineer,95232,0 +80870,Male,45,Masters,1,53,0,51,28,2.0,0,14,Rural,Data Analyst,100974,0 +80871,Female,38,Bachelors,6,94,87,36,19,9.0,3,93,Urban,Manager,55448,1 +80872,Male,36,Masters,15,46,25,61,10,3.0,4,77,Urban,Software Engineer,24263,0 +80873,Male,24,Bachelors,16,8,91,99,42,9.0,0,34,Rural,Software Engineer,95835,0 +80874,Female,35,Masters,13,50,53,74,35,1.0,0,55,Semi-Urban,Software Engineer,66159,0 +80875,Male,37,Diploma,12,17,1,30,76,4.0,5,28,Urban,ML Engineer,95675,0 +80876,Female,31,Bachelors,5,4,12,26,4,2.0,0,22,Urban,Manager,27362,0 +80877,Male,51,PhD,15,45,38,72,72,6.0,2,97,Urban,ML Engineer,31827,1 +80878,Male,45,Bachelors,6,10,58,26,64,6.0,7,10,Urban,Data Analyst,43843,0 +80879,Male,42,Bachelors,4,36,91,92,93,1.0,5,4,Rural,HR Executive,84661,0 +80880,Female,41,High School,12,24,16,80,26,0.0,3,97,Urban,Software Engineer,135513,0 +80881,Female,35,Bachelors,12,0,79,13,84,9.0,1,53,Semi-Urban,Manager,96577,0 +80882,Male,58,High School,18,93,67,18,9,2.0,2,90,Semi-Urban,HR Executive,54010,1 +80883,Female,35,High School,8,1,17,92,33,8.0,5,46,Urban,ML Engineer,95072,0 +80884,Male,37,Bachelors,6,25,47,30,2,3.0,4,94,Rural,ML Engineer,89688,0 +80885,Male,47,Bachelors,9,48,63,7,23,6.0,7,54,Semi-Urban,HR Executive,24871,0 +80886,Male,23,Diploma,6,72,40,11,69,8.0,1,77,Urban,Software Engineer,90022,0 +80887,Female,48,Diploma,14,81,84,18,9,7.0,4,16,Semi-Urban,HR Executive,146348,0 +80888,Male,41,Masters,11,92,26,64,94,3.0,4,68,Urban,Manager,136333,1 +80889,Female,46,Diploma,0,16,25,9,37,1.0,6,60,Rural,Software Engineer,54721,0 +80890,Male,38,Diploma,0,25,42,10,24,8.0,2,82,Semi-Urban,HR Executive,42947,0 +80891,Male,59,Bachelors,6,38,3,72,37,4.0,6,34,Rural,HR Executive,105328,0 +80892,Female,47,Bachelors,12,82,81,47,36,6.0,2,91,Urban,ML Engineer,109426,1 +80893,Female,55,Masters,10,76,59,81,68,8.0,6,21,Urban,ML Engineer,131230,0 +80894,Male,25,High School,5,91,85,46,33,6.0,5,11,Urban,Software Engineer,146930,0 +80895,Male,24,Bachelors,12,70,76,41,48,0.0,7,18,Semi-Urban,ML Engineer,93525,0 +80896,Female,40,Diploma,16,57,29,4,37,3.0,7,69,Semi-Urban,HR Executive,143757,0 +80897,Male,24,Masters,6,34,81,63,93,4.0,7,52,Rural,Software Engineer,101481,0 +80898,Male,31,Bachelors,14,59,46,70,33,1.0,0,16,Rural,Manager,133464,0 +80899,Male,50,Diploma,14,64,42,48,34,2.0,7,38,Rural,Software Engineer,45322,0 +80900,Female,37,High School,8,65,23,99,4,5.0,7,2,Urban,HR Executive,53228,0 +80901,Male,23,Bachelors,4,10,67,77,6,4.0,1,72,Urban,Manager,117082,0 +80902,Male,31,High School,8,86,15,25,8,2.0,7,41,Semi-Urban,Manager,28944,0 +80903,Male,58,Masters,8,82,5,91,51,4.0,2,29,Urban,HR Executive,57059,0 +80904,Male,48,Bachelors,8,78,72,70,31,9.0,2,55,Urban,ML Engineer,92520,1 +80905,Male,53,Bachelors,13,59,64,92,12,6.0,2,60,Urban,Software Engineer,135019,1 +80906,Female,27,Masters,16,28,10,17,34,0.0,7,71,Rural,Software Engineer,52885,0 +80907,Male,52,Bachelors,7,10,71,78,79,3.0,1,89,Urban,ML Engineer,54971,1 +80908,Male,41,Diploma,15,65,45,17,9,0.0,0,5,Urban,Software Engineer,63182,0 +80909,Female,57,PhD,1,58,69,66,39,4.0,0,25,Semi-Urban,Manager,96337,0 +80910,Other,30,Masters,17,6,55,67,58,1.0,5,13,Urban,HR Executive,22556,0 +80911,Female,58,Bachelors,10,81,16,63,63,0.0,0,12,Urban,Software Engineer,76938,0 +80912,Other,58,High School,12,27,25,49,27,2.0,7,2,Urban,Data Analyst,108575,0 +80913,Male,33,Bachelors,6,76,4,63,16,6.0,7,62,Semi-Urban,Data Analyst,77507,0 +80914,Female,49,High School,2,77,52,10,4,6.0,5,39,Rural,ML Engineer,123509,0 +80915,Female,43,Masters,19,34,4,76,23,2.0,0,63,Semi-Urban,HR Executive,29989,0 +80916,Male,54,High School,12,63,6,28,79,3.0,2,22,Semi-Urban,Data Analyst,35368,0 +80917,Male,53,Diploma,7,46,5,55,54,8.0,2,48,Urban,HR Executive,20080,0 +80918,Female,52,Masters,16,91,99,60,47,8.0,0,77,Semi-Urban,Data Analyst,101141,1 +80919,Male,21,Masters,17,89,5,13,37,9.0,1,45,Rural,HR Executive,68569,0 +80920,Male,26,Bachelors,19,33,24,17,31,0.0,5,81,Urban,ML Engineer,31398,0 +80921,Female,48,Diploma,14,61,30,45,4,9.0,5,75,Urban,HR Executive,79661,0 +80922,Male,36,Diploma,3,20,56,31,4,4.0,1,75,Urban,Manager,61781,0 +80923,Male,35,Bachelors,19,66,17,57,85,4.0,5,66,Urban,HR Executive,88233,0 +80924,Female,55,Bachelors,13,92,38,41,94,3.0,0,99,Rural,Manager,112236,1 +80925,Male,43,Bachelors,1,19,57,60,1,0.0,5,52,Urban,Manager,114011,0 +80926,Female,56,Diploma,5,32,81,4,2,0.0,0,56,Urban,ML Engineer,126171,0 +80927,Male,39,High School,3,32,90,97,65,8.0,6,6,Semi-Urban,HR Executive,47197,0 +80928,Female,51,Masters,16,33,20,6,85,3.0,1,94,Urban,Data Analyst,33160,0 +80929,Female,39,Bachelors,1,69,3,23,20,4.0,5,25,Urban,HR Executive,107392,0 +80930,Male,55,Bachelors,17,60,59,58,45,7.0,6,37,Urban,ML Engineer,114392,0 +80931,Female,36,Bachelors,18,69,50,80,80,5.0,7,48,Semi-Urban,HR Executive,149218,1 +80932,Female,45,High School,9,2,84,64,4,5.0,2,25,Rural,Data Analyst,84253,0 +80933,Male,43,Diploma,15,26,25,2,15,2.0,0,51,Urban,Manager,139289,0 +80934,Male,53,Masters,7,92,16,93,87,9.0,6,56,Semi-Urban,HR Executive,97536,1 +80935,Male,45,Masters,8,97,64,72,19,8.0,7,52,Urban,HR Executive,72224,1 +80936,Female,53,Bachelors,4,79,95,87,21,1.0,2,83,Urban,Data Analyst,72507,1 +80937,Male,51,Bachelors,2,8,34,21,9,2.0,0,68,Urban,HR Executive,105513,0 +80938,Male,27,Diploma,5,58,67,98,17,3.0,5,27,Urban,HR Executive,108476,1 +80939,Female,43,Bachelors,10,44,25,46,41,6.0,1,34,Urban,Software Engineer,134710,0 +80940,Male,58,PhD,5,96,95,49,8,8.0,1,63,Urban,Manager,42033,1 +80941,Male,42,Masters,11,12,22,62,35,7.0,2,75,Urban,HR Executive,21068,0 +80942,Male,50,High School,3,49,89,14,67,0.0,5,17,Semi-Urban,Manager,135447,0 +80943,Male,31,Bachelors,18,38,66,10,12,0.0,0,5,Semi-Urban,Software Engineer,115017,0 +80944,Male,46,Diploma,19,49,90,39,63,7.0,1,76,Urban,Data Analyst,21355,1 +80945,Female,31,Masters,5,24,78,37,54,3.0,3,29,Semi-Urban,Data Analyst,52433,0 +80946,Female,44,Diploma,2,29,24,43,50,3.0,1,26,Urban,Manager,91396,0 +80947,Male,34,Bachelors,3,21,43,73,87,5.0,0,31,Semi-Urban,Manager,67120,0 +80948,Male,31,High School,2,89,24,90,61,0.0,0,68,Semi-Urban,Software Engineer,97525,1 +80949,Male,30,High School,17,77,56,83,66,8.0,4,73,Rural,ML Engineer,82425,1 +80950,Male,23,Masters,2,49,3,87,40,5.0,3,55,Urban,ML Engineer,142574,0 +80951,Female,59,Bachelors,0,50,91,80,95,1.0,2,38,Urban,HR Executive,108058,1 +80952,Male,48,Bachelors,6,28,9,86,48,2.0,5,93,Urban,Data Analyst,93770,0 +80953,Female,51,Bachelors,6,83,28,60,49,7.0,1,73,Semi-Urban,HR Executive,38881,1 +80954,Female,29,High School,8,47,57,54,4,0.0,1,23,Urban,ML Engineer,112326,0 +80955,Male,22,Masters,3,77,80,80,71,0.0,5,50,Semi-Urban,Manager,141126,1 +80956,Female,54,Bachelors,0,65,49,78,34,3.0,3,25,Urban,Software Engineer,50892,0 +80957,Female,22,Bachelors,11,73,98,98,48,9.0,4,9,Rural,Data Analyst,24724,1 +80958,Female,30,Diploma,12,32,19,18,4,2.0,6,20,Urban,HR Executive,146129,0 +80959,Male,36,PhD,12,70,86,35,44,4.0,6,77,Urban,Software Engineer,89160,1 +80960,Male,26,Diploma,10,25,79,58,1,1.0,5,42,Urban,Software Engineer,101013,0 +80961,Male,34,High School,4,53,80,35,21,0.0,7,35,Rural,ML Engineer,132119,0 +80962,Male,48,Bachelors,18,70,90,44,97,8.0,3,26,Urban,Data Analyst,147540,0 +80963,Male,33,Bachelors,12,63,2,59,39,9.0,4,60,Urban,Data Analyst,23582,0 +80964,Male,57,Bachelors,3,43,93,73,10,5.0,2,94,Rural,HR Executive,50270,1 +80965,Male,43,Masters,4,68,43,12,62,4.0,1,54,Rural,ML Engineer,47355,0 +80966,Male,58,Bachelors,18,92,17,1,49,2.0,1,19,Semi-Urban,Manager,78169,0 +80967,Male,21,Bachelors,3,45,46,15,56,7.0,7,87,Semi-Urban,ML Engineer,50981,0 +80968,Male,24,High School,4,63,68,12,19,3.0,7,64,Semi-Urban,Manager,103999,0 +80969,Male,53,Diploma,7,49,53,53,52,0.0,2,30,Semi-Urban,HR Executive,107155,0 +80970,Male,42,Masters,18,41,58,67,40,6.0,2,88,Urban,HR Executive,72320,1 +80971,Male,44,Diploma,10,53,48,37,77,7.0,3,77,Urban,Manager,55773,0 +80972,Male,44,Diploma,10,54,95,91,18,9.0,3,92,Urban,ML Engineer,21675,1 +80973,Male,54,Diploma,9,78,52,52,61,9.0,6,57,Semi-Urban,ML Engineer,143604,1 +80974,Male,45,Bachelors,1,74,16,37,50,1.0,0,8,Semi-Urban,Software Engineer,105530,0 +80975,Male,21,Masters,16,60,0,74,49,1.0,3,98,Semi-Urban,HR Executive,77131,0 +80976,Male,23,Masters,0,19,8,90,60,5.0,4,25,Rural,HR Executive,22886,0 +80977,Female,27,Masters,14,92,16,24,65,9.0,6,66,Rural,ML Engineer,31574,0 +80978,Male,38,Masters,1,77,4,46,92,2.0,4,8,Semi-Urban,Software Engineer,65644,0 +80979,Female,54,Bachelors,17,15,64,62,74,6.0,5,31,Urban,Manager,127564,0 +80980,Female,22,Bachelors,19,55,81,90,48,6.0,5,74,Semi-Urban,HR Executive,54347,1 +80981,Male,41,Masters,15,57,56,57,83,9.0,3,73,Urban,Manager,123191,1 +80982,Male,27,Bachelors,11,10,36,22,53,0.0,7,22,Semi-Urban,Manager,61458,0 +80983,Female,48,Bachelors,13,19,26,49,67,9.0,3,81,Rural,Manager,38308,0 +80984,Female,52,Diploma,10,35,39,26,77,8.0,7,60,Urban,Software Engineer,68346,0 +80985,Male,30,High School,4,84,57,33,26,4.0,4,46,Urban,Data Analyst,87168,0 +80986,Male,50,Bachelors,12,27,64,56,3,0.0,2,46,Semi-Urban,HR Executive,139420,0 +80987,Female,40,Diploma,9,42,17,49,92,9.0,1,74,Urban,HR Executive,52785,0 +80988,Male,52,Masters,2,29,41,30,62,4.0,5,39,Semi-Urban,Data Analyst,32196,0 +80989,Male,21,Diploma,6,7,71,39,90,6.0,2,22,Rural,Data Analyst,78377,0 +80990,Male,27,Diploma,7,97,24,77,79,1.0,2,92,Urban,Software Engineer,105392,1 +80991,Male,50,High School,13,46,95,63,98,0.0,7,88,Semi-Urban,Software Engineer,38810,1 +80992,Female,52,Masters,0,9,11,37,54,7.0,6,92,Urban,Manager,105556,0 +80993,Female,57,Bachelors,19,32,26,29,96,7.0,0,74,Semi-Urban,Manager,124244,0 +80994,Other,29,Diploma,13,53,3,13,78,0.0,7,51,Urban,Software Engineer,125420,0 +80995,Male,50,Masters,8,69,86,58,21,2.0,1,61,Semi-Urban,Manager,69695,1 +80996,Female,25,Bachelors,1,75,79,18,59,3.0,7,31,Semi-Urban,HR Executive,27502,0 +80997,Male,36,Bachelors,11,0,0,88,58,2.0,3,84,Rural,Data Analyst,118861,0 +80998,Female,57,High School,14,90,98,26,64,5.0,1,36,Semi-Urban,Software Engineer,74484,1 +80999,Male,52,Bachelors,3,56,83,79,79,2.0,3,26,Urban,HR Executive,118284,1 +81000,Female,43,Masters,17,79,96,0,62,2.0,0,93,Urban,HR Executive,29675,1 +81001,Female,59,High School,6,49,47,49,24,8.0,0,75,Semi-Urban,ML Engineer,37082,0 +81002,Female,32,Bachelors,9,55,23,54,90,6.0,2,2,Urban,Software Engineer,27973,0 +81003,Female,47,Bachelors,7,86,85,75,69,4.0,1,67,Urban,Data Analyst,71893,1 +81004,Male,53,Bachelors,19,16,1,97,71,1.0,6,69,Semi-Urban,Data Analyst,47494,0 +81005,Female,55,Bachelors,14,40,64,89,83,1.0,2,66,Rural,Manager,45770,1 +81006,Female,59,Diploma,8,64,27,38,36,4.0,6,14,Semi-Urban,HR Executive,24435,0 +81007,Male,58,Masters,4,37,9,2,0,2.0,3,84,Urban,Software Engineer,61003,0 +81008,Male,23,Bachelors,17,72,33,65,19,3.0,5,9,Urban,ML Engineer,83796,0 +81009,Male,25,PhD,16,18,5,17,64,7.0,7,25,Urban,ML Engineer,28034,0 +81010,Female,56,PhD,1,56,5,74,18,6.0,7,87,Urban,ML Engineer,29435,0 +81011,Male,57,Masters,7,32,33,83,41,1.0,3,68,Semi-Urban,HR Executive,27029,0 +81012,Female,58,Bachelors,17,82,87,4,93,7.0,2,59,Urban,Software Engineer,85404,0 +81013,Male,29,Masters,19,20,84,28,82,3.0,6,85,Rural,Manager,80991,0 +81014,Male,44,Diploma,17,63,70,8,34,7.0,4,42,Urban,ML Engineer,96555,0 +81015,Male,47,Bachelors,9,82,84,85,96,1.0,4,77,Urban,HR Executive,50690,1 +81016,Male,43,High School,10,16,35,17,15,7.0,7,0,Semi-Urban,Data Analyst,109937,0 +81017,Male,52,Bachelors,0,46,10,82,6,1.0,5,31,Urban,Data Analyst,110142,0 +81018,Female,27,High School,9,75,9,38,89,9.0,5,2,Urban,Data Analyst,30280,0 +81019,Male,50,High School,2,20,32,65,88,6.0,3,50,Semi-Urban,HR Executive,123513,0 +81020,Male,54,Bachelors,19,98,81,0,25,7.0,0,90,Rural,ML Engineer,96976,1 +81021,Female,27,Bachelors,2,75,40,61,50,9.0,7,62,Urban,Data Analyst,31962,0 +81022,Male,21,Bachelors,13,48,11,87,16,4.0,3,50,Urban,ML Engineer,73094,0 +81023,Female,34,Masters,2,41,92,83,1,4.0,4,91,Urban,Software Engineer,103775,1 +81024,Female,42,Bachelors,4,49,98,4,63,4.0,6,99,Urban,ML Engineer,24922,1 +81025,Female,56,Diploma,11,2,43,89,46,1.0,0,27,Urban,Manager,35702,0 +81026,Female,55,Masters,16,78,27,58,54,2.0,6,94,Semi-Urban,ML Engineer,75453,1 +81027,Male,27,Diploma,14,80,53,35,23,4.0,3,30,Urban,Software Engineer,29984,0 +81028,Female,29,Diploma,13,99,72,96,75,6.0,1,69,Rural,Manager,79409,1 +81029,Other,46,Diploma,3,35,29,72,78,2.0,7,47,Urban,Software Engineer,82355,0 +81030,Female,38,Bachelors,18,81,27,94,13,9.0,0,47,Semi-Urban,HR Executive,99183,1 +81031,Female,59,Bachelors,18,43,94,28,69,4.0,2,45,Semi-Urban,HR Executive,59989,0 +81032,Male,42,Bachelors,0,27,78,98,90,0.0,6,99,Rural,ML Engineer,111678,1 +81033,Other,55,Bachelors,18,18,7,97,7,8.0,4,80,Urban,Data Analyst,29492,0 +81034,Male,57,Bachelors,17,75,98,55,90,6.0,4,17,Semi-Urban,Software Engineer,115500,1 +81035,Male,23,Bachelors,15,37,38,69,14,9.0,1,57,Rural,Data Analyst,76697,0 +81036,Male,50,High School,15,74,74,67,54,3.0,6,12,Urban,Data Analyst,20580,0 +81037,Male,30,Masters,1,1,96,81,38,3.0,0,20,Urban,HR Executive,115221,0 +81038,Female,25,Bachelors,9,48,21,64,2,0.0,2,90,Rural,Data Analyst,38686,0 +81039,Male,48,Bachelors,16,75,15,36,33,6.0,1,57,Urban,Data Analyst,37701,0 +81040,Male,41,High School,11,10,63,77,47,2.0,6,18,Rural,Manager,20303,0 +81041,Male,39,PhD,3,67,54,81,76,1.0,7,25,Urban,Data Analyst,70520,0 +81042,Male,58,Diploma,14,25,73,5,16,3.0,2,16,Urban,Data Analyst,43476,0 +81043,Female,40,Bachelors,0,97,7,99,63,6.0,6,57,Urban,HR Executive,108872,1 +81044,Female,43,PhD,2,63,94,93,62,5.0,3,24,Semi-Urban,ML Engineer,61728,1 +81045,Female,30,Masters,5,72,34,37,43,3.0,5,6,Urban,HR Executive,96674,0 +81046,Female,47,Diploma,15,55,77,59,35,8.0,0,51,Urban,HR Executive,117969,1 +81047,Male,46,Bachelors,19,6,1,50,2,4.0,3,47,Urban,ML Engineer,26859,0 +81048,Female,50,Bachelors,8,54,84,8,29,4.0,2,87,Semi-Urban,HR Executive,126826,0 +81049,Female,55,Masters,19,75,97,34,87,5.0,3,7,Rural,Software Engineer,94509,0 +81050,Male,57,Masters,13,60,73,33,63,5.0,7,39,Urban,HR Executive,96857,0 +81051,Male,27,Bachelors,2,45,74,62,46,2.0,6,84,Urban,HR Executive,148254,1 +81052,Male,48,Diploma,19,71,37,39,95,6.0,6,74,Urban,Software Engineer,115359,0 +81053,Male,49,Diploma,4,17,14,53,43,7.0,5,8,Rural,Manager,40300,0 +81054,Male,54,Bachelors,6,32,76,18,24,4.0,1,32,Urban,HR Executive,70762,0 +81055,Male,47,Bachelors,15,55,36,38,53,9.0,0,0,Urban,Software Engineer,67119,0 +81056,Male,38,Diploma,5,25,46,68,99,4.0,5,17,Urban,Data Analyst,112283,0 +81057,Male,31,Bachelors,11,81,26,1,22,2.0,1,83,Urban,ML Engineer,112894,0 +81058,Male,45,Masters,17,7,64,89,82,1.0,3,38,Urban,HR Executive,102091,0 +81059,Male,49,Bachelors,10,22,62,64,12,7.0,7,45,Urban,Software Engineer,87573,0 +81060,Female,27,Masters,13,9,69,9,92,6.0,7,31,Semi-Urban,Data Analyst,127847,0 +81061,Male,24,Diploma,1,0,11,78,64,5.0,4,64,Semi-Urban,Software Engineer,31403,0 +81062,Female,44,Bachelors,3,59,64,81,65,1.0,4,74,Rural,HR Executive,31112,1 +81063,Female,51,Bachelors,4,79,47,44,78,5.0,0,37,Urban,Manager,108776,0 +81064,Female,22,Bachelors,18,89,49,99,55,8.0,4,2,Urban,ML Engineer,106316,0 +81065,Male,34,Bachelors,6,15,63,34,78,4.0,6,33,Urban,Software Engineer,136552,0 +81066,Female,44,Bachelors,12,24,56,95,84,0.0,6,65,Rural,Manager,95016,0 +81067,Male,36,Bachelors,19,61,49,10,88,2.0,2,54,Semi-Urban,ML Engineer,92736,0 +81068,Male,38,High School,13,37,21,29,10,1.0,0,40,Rural,ML Engineer,134413,0 +81069,Female,57,Bachelors,7,92,32,11,27,8.0,4,26,Urban,Manager,122168,0 +81070,Male,55,Diploma,7,36,11,83,88,6.0,2,59,Urban,HR Executive,95299,0 +81071,Male,38,Bachelors,4,53,58,19,22,6.0,1,56,Semi-Urban,Manager,99623,0 +81072,Female,30,Diploma,13,32,37,96,31,8.0,1,30,Urban,Data Analyst,98926,0 +81073,Male,52,Bachelors,15,76,16,42,2,7.0,5,37,Urban,Software Engineer,73258,0 +81074,Male,50,High School,14,68,64,15,64,3.0,5,93,Urban,ML Engineer,26870,1 +81075,Other,22,Diploma,14,81,92,65,25,3.0,1,40,Semi-Urban,Manager,57219,1 +81076,Female,21,Masters,19,1,49,24,24,2.0,1,84,Semi-Urban,Software Engineer,93077,0 +81077,Male,22,Bachelors,10,20,77,21,75,0.0,6,69,Urban,HR Executive,71909,0 +81078,Male,24,High School,19,53,99,35,6,4.0,2,84,Semi-Urban,ML Engineer,68145,1 +81079,Male,41,Bachelors,19,38,69,0,66,1.0,7,58,Urban,ML Engineer,145605,0 +81080,Female,49,High School,1,24,2,90,8,9.0,0,9,Urban,ML Engineer,57192,0 +81081,Male,36,High School,18,79,88,36,91,7.0,7,30,Rural,Manager,100607,0 +81082,Female,24,Bachelors,11,51,51,17,57,2.0,3,96,Semi-Urban,HR Executive,57266,0 +81083,Other,37,Diploma,0,85,10,22,37,7.0,1,73,Urban,Manager,80757,0 +81084,Other,25,Masters,8,75,1,93,63,7.0,4,18,Urban,Manager,23851,0 +81085,Male,25,Bachelors,1,2,9,2,36,7.0,7,39,Urban,Software Engineer,132825,0 +81086,Female,51,Bachelors,7,86,64,95,13,1.0,4,66,Rural,Manager,75882,1 +81087,Male,24,Masters,11,81,29,79,60,0.0,7,3,Rural,HR Executive,42956,0 +81088,Male,45,Bachelors,16,21,5,65,91,0.0,4,29,Rural,ML Engineer,95891,0 +81089,Male,23,Bachelors,2,19,76,26,93,0.0,2,51,Semi-Urban,HR Executive,144742,0 +81090,Female,46,High School,16,61,3,44,36,9.0,1,26,Urban,Data Analyst,88855,0 +81091,Female,46,High School,7,25,55,38,28,9.0,5,14,Urban,HR Executive,44300,0 +81092,Female,21,Diploma,16,34,77,37,22,0.0,6,42,Semi-Urban,Manager,73255,0 +81093,Female,32,Diploma,1,67,63,4,2,3.0,5,66,Urban,ML Engineer,35705,0 +81094,Male,49,High School,19,94,92,47,31,0.0,3,14,Semi-Urban,Data Analyst,57505,1 +81095,Male,58,Bachelors,13,65,53,97,54,4.0,5,73,Urban,Data Analyst,135896,1 +81096,Female,45,High School,0,3,18,54,46,4.0,1,7,Semi-Urban,HR Executive,95402,0 +81097,Female,21,Bachelors,13,86,89,15,72,8.0,6,98,Semi-Urban,Manager,22413,1 +81098,Male,22,Bachelors,10,67,54,32,0,1.0,7,76,Urban,Data Analyst,110574,0 +81099,Female,25,Bachelors,15,17,92,41,10,8.0,4,41,Semi-Urban,Data Analyst,48237,0 +81100,Male,28,High School,9,56,35,64,18,0.0,6,60,Urban,Software Engineer,67727,0 +81101,Female,25,Diploma,6,85,36,20,70,3.0,5,43,Semi-Urban,ML Engineer,97358,0 +81102,Male,36,Bachelors,3,29,51,9,47,0.0,2,99,Semi-Urban,Data Analyst,77778,0 +81103,Male,52,Masters,3,38,61,78,50,1.0,6,23,Semi-Urban,Data Analyst,56368,0 +81104,Female,38,Bachelors,12,53,97,37,42,3.0,0,97,Rural,Software Engineer,108290,1 +81105,Male,43,Bachelors,19,50,79,83,42,2.0,1,69,Urban,Software Engineer,21990,1 +81106,Female,59,High School,13,2,71,52,15,0.0,6,43,Urban,Data Analyst,141536,0 +81107,Male,30,Bachelors,8,94,47,18,15,6.0,4,20,Semi-Urban,ML Engineer,43794,0 +81108,Female,27,Masters,16,95,14,36,75,1.0,7,38,Urban,Data Analyst,47033,0 +81109,Female,49,Bachelors,15,30,47,30,96,5.0,2,64,Urban,ML Engineer,24432,0 +81110,Male,58,Bachelors,6,54,96,60,38,8.0,4,63,Urban,Data Analyst,80375,1 +81111,Female,46,Masters,8,68,91,25,34,2.0,5,47,Semi-Urban,ML Engineer,105009,0 +81112,Male,49,Diploma,3,91,78,56,26,3.0,7,13,Urban,Data Analyst,30139,1 +81113,Male,36,Bachelors,3,87,28,49,20,5.0,2,10,Semi-Urban,Software Engineer,96728,0 +81114,Female,21,Diploma,11,77,0,59,61,6.0,2,60,Urban,Manager,49630,0 +81115,Male,52,Masters,17,10,67,21,13,5.0,4,27,Urban,Data Analyst,144558,0 +81116,Male,56,Masters,1,16,57,51,69,6.0,5,2,Urban,Software Engineer,41749,0 +81117,Male,34,Bachelors,6,82,45,30,24,3.0,5,6,Semi-Urban,Data Analyst,95456,0 +81118,Male,57,Diploma,8,93,31,91,19,8.0,7,99,Semi-Urban,HR Executive,51991,1 +81119,Male,50,High School,19,96,58,87,23,8.0,1,54,Urban,Manager,132658,1 +81120,Female,56,Diploma,0,9,73,32,13,7.0,5,95,Urban,Software Engineer,93706,0 +81121,Male,51,Diploma,7,64,5,10,29,3.0,2,59,Urban,HR Executive,84030,0 +81122,Male,32,Bachelors,2,18,29,15,65,7.0,2,74,Urban,ML Engineer,50835,0 +81123,Female,24,Bachelors,2,55,97,71,0,2.0,7,10,Semi-Urban,Data Analyst,68205,0 +81124,Male,33,Bachelors,4,97,13,31,52,4.0,6,37,Rural,Manager,142001,0 +81125,Female,52,Diploma,6,98,24,40,24,2.0,6,3,Urban,ML Engineer,38388,0 +81126,Male,44,Diploma,4,24,89,24,64,9.0,2,58,Urban,Data Analyst,121718,0 +81127,Female,41,Diploma,0,44,1,37,76,0.0,5,65,Urban,Manager,105102,0 +81128,Male,58,Bachelors,7,56,92,24,41,0.0,3,53,Urban,HR Executive,39205,0 +81129,Female,42,Bachelors,17,14,21,83,21,6.0,0,90,Rural,Manager,88774,0 +81130,Female,32,Masters,17,12,59,86,56,3.0,1,56,Urban,HR Executive,114706,0 +81131,Male,48,Bachelors,9,69,17,75,58,9.0,3,89,Urban,ML Engineer,34460,1 +81132,Male,23,Bachelors,13,77,58,7,29,4.0,4,12,Semi-Urban,Software Engineer,90086,0 +81133,Other,41,High School,16,58,23,45,56,8.0,7,5,Semi-Urban,ML Engineer,114343,0 +81134,Male,56,Bachelors,15,20,24,10,36,8.0,6,9,Urban,Software Engineer,75497,0 +81135,Male,54,High School,10,42,33,99,28,3.0,6,29,Rural,Manager,105544,0 +81136,Male,53,Masters,1,46,35,9,88,3.0,7,35,Urban,Software Engineer,90109,0 +81137,Male,35,Masters,11,98,12,17,83,5.0,0,39,Semi-Urban,Manager,148207,0 +81138,Male,23,Diploma,9,82,75,5,97,3.0,7,47,Urban,Software Engineer,37402,0 +81139,Male,34,Bachelors,14,41,72,67,33,8.0,5,11,Urban,ML Engineer,58960,0 +81140,Male,23,Bachelors,5,40,88,35,87,7.0,2,88,Semi-Urban,Software Engineer,74338,1 +81141,Female,57,High School,5,1,20,64,52,3.0,1,36,Rural,Manager,108154,0 +81142,Female,25,Bachelors,18,30,65,76,68,3.0,6,22,Urban,Data Analyst,122997,0 +81143,Male,35,High School,10,19,78,82,27,5.0,1,71,Urban,ML Engineer,133477,1 +81144,Male,26,High School,7,18,39,55,36,8.0,1,41,Semi-Urban,ML Engineer,86859,0 +81145,Other,53,Bachelors,6,75,74,49,4,5.0,7,80,Semi-Urban,Manager,42805,1 +81146,Other,40,Masters,8,43,82,70,31,0.0,3,37,Urban,Software Engineer,102041,0 +81147,Other,36,Masters,0,16,4,3,75,8.0,1,75,Urban,Software Engineer,128495,0 +81148,Female,25,Diploma,18,10,86,56,20,2.0,3,4,Urban,Data Analyst,90753,0 +81149,Female,33,Bachelors,3,76,83,34,18,2.0,4,35,Urban,HR Executive,47840,0 +81150,Male,33,Bachelors,10,9,80,10,51,1.0,7,58,Rural,Manager,122126,0 +81151,Other,59,Bachelors,14,15,29,64,97,0.0,2,31,Urban,ML Engineer,138205,0 +81152,Female,38,High School,19,85,5,57,54,8.0,2,52,Rural,Software Engineer,139200,0 +81153,Female,28,Bachelors,19,0,70,49,69,7.0,0,98,Urban,Software Engineer,77519,0 +81154,Female,38,Bachelors,12,52,87,32,5,7.0,7,69,Urban,HR Executive,125181,0 +81155,Male,46,High School,3,45,22,68,83,0.0,1,32,Semi-Urban,ML Engineer,96026,0 +81156,Male,41,Bachelors,11,17,69,78,91,8.0,1,82,Semi-Urban,Manager,96591,1 +81157,Male,34,High School,17,76,97,51,52,5.0,4,3,Rural,Data Analyst,77916,0 +81158,Male,23,Bachelors,16,47,63,89,28,3.0,1,18,Urban,ML Engineer,120606,0 +81159,Male,26,Bachelors,11,15,64,80,4,4.0,0,4,Semi-Urban,Software Engineer,138698,0 +81160,Male,49,Diploma,5,29,6,84,9,8.0,5,75,Rural,Manager,93357,0 +81161,Female,24,Bachelors,9,27,36,18,97,4.0,6,53,Urban,ML Engineer,93179,0 +81162,Male,23,Diploma,1,97,28,51,3,4.0,1,57,Semi-Urban,ML Engineer,24303,0 +81163,Female,38,Diploma,4,94,37,5,94,5.0,6,69,Urban,Data Analyst,65998,0 +81164,Male,22,Diploma,19,6,96,21,64,6.0,3,8,Urban,ML Engineer,28730,0 +81165,Female,33,High School,9,17,20,4,21,7.0,7,66,Semi-Urban,HR Executive,71876,0 +81166,Male,30,High School,19,9,98,30,65,4.0,7,99,Urban,Manager,26686,1 +81167,Male,37,Bachelors,17,36,88,45,32,6.0,0,62,Rural,Software Engineer,111369,0 +81168,Male,58,Bachelors,7,34,97,4,93,5.0,3,33,Urban,Manager,57391,0 +81169,Male,44,Masters,13,9,36,68,3,2.0,0,34,Rural,Data Analyst,37211,0 +81170,Male,26,Masters,14,35,66,41,94,0.0,5,56,Rural,HR Executive,51177,0 +81171,Female,56,Diploma,3,85,6,1,14,9.0,1,13,Semi-Urban,Software Engineer,116405,0 +81172,Male,44,Diploma,0,73,69,31,37,6.0,0,7,Rural,HR Executive,93064,0 +81173,Female,32,Diploma,12,80,85,94,2,4.0,4,30,Semi-Urban,Manager,91828,1 +81174,Female,32,Bachelors,0,5,61,68,93,7.0,2,96,Rural,HR Executive,127478,0 +81175,Male,53,Bachelors,13,37,23,28,36,2.0,7,73,Urban,Software Engineer,108023,0 +81176,Female,42,High School,13,73,23,39,77,3.0,5,30,Semi-Urban,Software Engineer,147124,0 +81177,Male,28,High School,17,47,42,20,32,5.0,3,58,Rural,Software Engineer,42336,0 +81178,Male,47,Masters,1,28,0,23,25,6.0,4,25,Semi-Urban,Data Analyst,76571,0 +81179,Female,30,Masters,4,74,63,89,87,3.0,5,17,Rural,Data Analyst,71475,1 +81180,Male,28,Bachelors,17,5,56,68,78,0.0,6,60,Semi-Urban,Data Analyst,133188,0 +81181,Female,31,High School,4,34,70,2,55,7.0,1,37,Urban,Data Analyst,149552,0 +81182,Male,48,Bachelors,2,66,43,78,36,2.0,0,86,Semi-Urban,Data Analyst,93027,1 +81183,Male,42,Bachelors,18,86,84,48,13,7.0,1,61,Rural,ML Engineer,59363,1 +81184,Female,41,Bachelors,8,89,32,96,60,1.0,1,75,Urban,Software Engineer,46379,1 +81185,Male,24,Bachelors,2,70,41,44,15,3.0,2,38,Urban,Data Analyst,62036,0 +81186,Male,31,Bachelors,5,13,45,27,71,4.0,4,37,Semi-Urban,ML Engineer,119165,0 +81187,Male,34,High School,11,6,32,75,27,2.0,5,28,Urban,Software Engineer,120218,0 +81188,Female,45,High School,5,76,19,74,78,5.0,6,34,Urban,Software Engineer,38508,0 +81189,Male,32,Diploma,17,71,41,82,27,9.0,0,67,Urban,ML Engineer,96730,1 +81190,Female,42,Bachelors,15,58,30,88,2,5.0,2,65,Urban,Software Engineer,78389,1 +81191,Male,26,Bachelors,3,46,61,21,78,8.0,5,15,Urban,Manager,126457,0 +81192,Female,40,Masters,18,58,83,18,97,8.0,0,7,Rural,Software Engineer,89014,0 +81193,Male,37,Masters,8,72,12,19,29,9.0,3,44,Rural,HR Executive,74989,0 +81194,Male,53,Bachelors,6,6,0,45,95,5.0,5,17,Urban,Data Analyst,70110,0 +81195,Female,35,High School,10,56,45,30,49,0.0,1,85,Urban,Data Analyst,66273,0 +81196,Male,32,PhD,7,39,60,54,32,4.0,7,70,Urban,Data Analyst,135261,0 +81197,Male,21,Masters,9,28,88,24,49,0.0,2,54,Semi-Urban,Software Engineer,71839,0 +81198,Male,56,Masters,5,79,30,95,39,4.0,7,86,Urban,ML Engineer,98469,1 +81199,Male,55,Bachelors,14,73,75,90,30,0.0,3,34,Rural,Manager,119527,1 +81200,Male,44,Masters,4,95,77,95,13,3.0,7,73,Urban,Manager,52427,1 +81201,Female,58,Bachelors,0,14,24,15,23,5.0,3,91,Urban,HR Executive,64883,0 +81202,Male,22,Diploma,10,38,15,55,73,3.0,6,30,Urban,ML Engineer,110738,0 +81203,Female,21,Masters,7,25,33,7,7,8.0,2,49,Urban,Data Analyst,91730,0 +81204,Male,29,Diploma,9,64,13,94,70,0.0,6,6,Urban,Software Engineer,26517,0 +81205,Female,35,Diploma,11,82,88,77,3,2.0,1,50,Semi-Urban,HR Executive,102283,1 +81206,Female,57,High School,15,23,94,51,17,4.0,7,76,Urban,Manager,76912,1 +81207,Male,42,Diploma,4,74,52,19,56,7.0,7,33,Rural,Data Analyst,36504,0 +81208,Female,46,High School,15,83,55,62,26,0.0,0,77,Semi-Urban,Data Analyst,137651,1 +81209,Male,25,Bachelors,17,42,56,66,54,0.0,1,50,Urban,Data Analyst,28267,0 +81210,Female,30,Bachelors,11,6,24,33,70,7.0,6,81,Urban,HR Executive,126679,0 +81211,Female,31,PhD,12,15,56,42,87,3.0,0,53,Urban,Manager,32234,0 +81212,Male,31,Bachelors,7,47,93,17,32,7.0,2,53,Urban,Data Analyst,130346,0 +81213,Male,42,Bachelors,0,69,68,20,91,9.0,6,96,Semi-Urban,Manager,146268,1 +81214,Male,58,Bachelors,13,92,41,15,49,7.0,3,67,Semi-Urban,HR Executive,123290,0 +81215,Male,25,Diploma,1,52,13,73,11,9.0,0,7,Urban,Manager,81293,0 +81216,Male,29,Diploma,2,14,16,69,18,3.0,3,79,Urban,Manager,119416,0 +81217,Male,43,High School,6,39,97,47,77,7.0,3,79,Urban,Manager,143534,1 +81218,Female,22,Diploma,19,14,77,41,82,0.0,6,11,Rural,Software Engineer,129129,0 +81219,Male,38,Masters,16,4,5,67,62,5.0,7,12,Semi-Urban,Data Analyst,148276,0 +81220,Male,33,Bachelors,9,22,50,98,69,3.0,0,82,Urban,Data Analyst,40981,1 +81221,Male,58,Bachelors,10,18,99,37,76,6.0,0,8,Urban,Data Analyst,70230,0 +81222,Male,23,Bachelors,18,13,64,60,76,3.0,5,62,Urban,Software Engineer,127492,0 +81223,Female,40,Bachelors,10,34,48,85,13,7.0,2,36,Urban,Manager,62449,0 +81224,Male,38,Masters,2,30,48,7,54,7.0,3,32,Urban,HR Executive,94406,0 +81225,Male,48,PhD,14,68,50,9,66,4.0,4,95,Rural,Software Engineer,114816,0 +81226,Female,26,Bachelors,5,87,59,5,44,1.0,2,15,Urban,ML Engineer,135181,0 +81227,Female,23,Bachelors,16,14,56,86,35,7.0,4,70,Urban,Software Engineer,90648,0 +81228,Male,54,Bachelors,1,28,24,34,6,9.0,2,95,Urban,ML Engineer,80701,0 +81229,Male,52,Diploma,11,48,0,61,91,6.0,4,44,Rural,Data Analyst,29583,0 +81230,Male,32,Bachelors,1,66,77,77,17,7.0,1,32,Rural,HR Executive,125888,1 +81231,Female,24,Masters,16,68,22,52,47,9.0,5,74,Urban,Software Engineer,112926,0 +81232,Male,28,PhD,19,98,19,25,74,7.0,6,40,Semi-Urban,Software Engineer,72631,0 +81233,Male,47,Masters,19,34,83,55,72,0.0,4,20,Rural,Software Engineer,108508,0 +81234,Male,55,High School,11,84,94,77,59,0.0,2,52,Semi-Urban,Software Engineer,65586,1 +81235,Female,57,Masters,10,46,59,28,91,5.0,1,76,Urban,ML Engineer,122466,0 +81236,Male,41,Masters,1,55,38,55,61,2.0,3,93,Urban,ML Engineer,131485,1 +81237,Male,42,High School,15,8,31,82,4,8.0,7,49,Urban,Data Analyst,73569,0 +81238,Female,41,Bachelors,19,15,9,99,28,2.0,5,13,Rural,Software Engineer,114097,0 +81239,Female,25,Masters,11,94,89,62,93,9.0,0,99,Semi-Urban,Software Engineer,133581,1 +81240,Male,22,Diploma,2,4,82,15,46,9.0,6,58,Urban,ML Engineer,95060,0 +81241,Female,57,Bachelors,18,90,8,78,34,6.0,4,1,Urban,Manager,111421,0 +81242,Male,53,Masters,17,71,21,64,7,9.0,5,90,Rural,HR Executive,20782,1 +81243,Female,57,Masters,14,19,76,13,57,2.0,1,89,Rural,ML Engineer,110065,0 +81244,Male,25,Bachelors,16,6,75,74,79,9.0,4,7,Urban,ML Engineer,31851,0 +81245,Female,42,Masters,12,54,13,18,50,8.0,4,47,Urban,Software Engineer,73399,0 +81246,Male,49,Masters,11,77,15,48,10,9.0,2,12,Urban,Manager,127158,0 +81247,Female,39,Bachelors,14,13,93,99,32,1.0,4,61,Semi-Urban,Manager,68228,1 +81248,Female,55,Diploma,6,59,98,61,14,3.0,6,64,Urban,Manager,137279,1 +81249,Female,53,Bachelors,9,9,49,58,52,2.0,5,92,Urban,Manager,116902,0 +81250,Female,36,PhD,18,67,95,65,6,4.0,0,9,Semi-Urban,Data Analyst,127442,0 +81251,Male,41,High School,13,54,65,32,94,4.0,6,80,Urban,ML Engineer,117172,0 +81252,Male,45,High School,16,37,24,14,21,7.0,4,58,Semi-Urban,Manager,145041,0 +81253,Female,34,Masters,3,3,84,34,35,1.0,6,11,Urban,Data Analyst,82895,0 +81254,Female,40,Bachelors,15,19,46,0,44,6.0,0,21,Urban,Software Engineer,39529,0 +81255,Male,26,Diploma,6,94,81,4,68,9.0,1,68,Semi-Urban,Software Engineer,108760,1 +81256,Male,37,Bachelors,8,80,15,86,28,9.0,1,67,Urban,ML Engineer,39295,1 +81257,Female,23,High School,2,91,59,17,36,9.0,5,11,Urban,Data Analyst,67431,0 +81258,Male,49,Masters,6,19,50,28,56,6.0,0,39,Urban,HR Executive,126397,0 +81259,Male,23,Diploma,12,26,13,63,40,3.0,6,40,Rural,ML Engineer,146802,0 +81260,Male,29,Masters,8,27,94,37,48,9.0,0,10,Rural,Software Engineer,68087,0 +81261,Female,24,PhD,11,83,18,89,33,5.0,3,50,Urban,ML Engineer,85552,0 +81262,Female,21,Diploma,17,82,65,9,92,4.0,3,12,Urban,Manager,149708,0 +81263,Male,42,Bachelors,16,45,69,9,17,1.0,2,54,Urban,ML Engineer,84432,0 +81264,Female,58,Bachelors,5,85,45,79,22,9.0,2,44,Rural,Software Engineer,107404,1 +81265,Male,25,Bachelors,4,25,68,28,14,5.0,1,67,Urban,Manager,54741,0 +81266,Female,48,Diploma,5,61,44,18,45,0.0,7,42,Rural,Data Analyst,71084,0 +81267,Male,25,Bachelors,10,76,0,77,17,1.0,6,11,Urban,Manager,43936,0 +81268,Male,48,Masters,3,33,53,56,70,1.0,2,69,Urban,HR Executive,119263,0 +81269,Male,59,Bachelors,11,18,15,92,47,4.0,0,79,Urban,Data Analyst,37818,0 +81270,Male,59,Masters,13,15,7,77,10,1.0,3,53,Urban,ML Engineer,123537,0 +81271,Female,39,High School,15,50,36,91,68,2.0,1,23,Semi-Urban,HR Executive,138518,0 +81272,Female,46,Bachelors,16,53,41,36,9,7.0,3,74,Semi-Urban,Software Engineer,41151,0 +81273,Female,40,Masters,17,79,34,14,78,8.0,2,94,Rural,HR Executive,128841,0 +81274,Male,33,Bachelors,5,98,24,18,14,9.0,4,0,Semi-Urban,Software Engineer,70565,0 +81275,Male,31,Bachelors,2,9,66,4,40,4.0,1,5,Semi-Urban,HR Executive,126502,0 +81276,Male,50,Bachelors,12,75,84,48,28,9.0,7,92,Semi-Urban,HR Executive,85711,1 +81277,Female,28,Bachelors,5,29,0,65,29,4.0,0,85,Urban,HR Executive,37138,0 +81278,Male,41,Bachelors,4,74,21,50,55,2.0,7,32,Urban,HR Executive,25867,0 +81279,Other,34,Bachelors,0,91,18,10,48,2.0,1,43,Urban,Manager,136783,0 +81280,Male,59,Masters,1,90,24,53,44,6.0,7,64,Urban,Software Engineer,137369,0 +81281,Male,34,Bachelors,18,37,29,21,52,8.0,2,78,Rural,Software Engineer,33520,0 +81282,Female,23,Masters,13,79,67,6,80,3.0,4,47,Urban,ML Engineer,28535,0 +81283,Female,27,Bachelors,13,53,6,55,85,4.0,4,68,Urban,HR Executive,110672,0 +81284,Male,21,Masters,12,36,88,39,59,2.0,4,18,Urban,Software Engineer,44126,0 +81285,Female,51,Diploma,15,64,85,35,71,2.0,6,56,Urban,Manager,91525,0 +81286,Female,36,Bachelors,14,32,92,86,12,0.0,7,10,Urban,Data Analyst,32230,0 +81287,Female,31,Masters,10,60,38,4,42,5.0,1,51,Urban,ML Engineer,68071,0 +81288,Female,22,High School,12,40,82,51,43,8.0,0,79,Urban,ML Engineer,62458,1 +81289,Male,38,Bachelors,9,1,70,62,67,8.0,7,14,Urban,ML Engineer,26168,0 +81290,Male,30,Bachelors,5,23,29,18,49,7.0,1,83,Urban,HR Executive,119507,0 +81291,Female,22,Diploma,2,46,6,85,77,7.0,3,7,Urban,Software Engineer,138953,0 +81292,Male,22,Masters,15,39,68,41,60,2.0,5,22,Semi-Urban,HR Executive,79567,0 +81293,Female,52,Masters,11,36,30,63,93,7.0,3,93,Urban,HR Executive,73552,0 +81294,Female,59,High School,7,69,82,20,1,3.0,7,75,Urban,Manager,125188,1 +81295,Male,50,Masters,3,75,45,53,23,1.0,1,32,Semi-Urban,Software Engineer,66155,0 +81296,Male,41,Bachelors,10,70,52,79,81,3.0,4,63,Rural,Manager,23191,1 +81297,Male,46,Bachelors,17,4,87,82,53,0.0,6,33,Urban,HR Executive,24335,0 +81298,Male,33,Masters,12,63,72,87,39,2.0,0,79,Urban,Software Engineer,27044,1 +81299,Male,52,High School,17,94,54,24,8,5.0,0,98,Urban,HR Executive,51948,1 +81300,Female,36,High School,7,42,23,67,27,3.0,4,56,Urban,Software Engineer,145283,0 +81301,Female,53,Bachelors,6,3,21,37,22,4.0,2,25,Rural,HR Executive,51956,0 +81302,Female,23,Masters,19,91,45,83,99,5.0,0,74,Urban,ML Engineer,81371,1 +81303,Male,35,Bachelors,5,6,13,63,10,0.0,4,87,Rural,ML Engineer,22260,0 +81304,Female,41,Bachelors,7,20,59,65,42,8.0,5,34,Urban,HR Executive,37388,0 +81305,Other,55,Bachelors,11,87,92,90,71,3.0,5,5,Urban,Data Analyst,125115,1 +81306,Male,44,Masters,16,60,33,22,10,5.0,1,48,Urban,Data Analyst,46101,0 +81307,Female,43,High School,15,15,72,18,25,9.0,6,90,Semi-Urban,Data Analyst,64051,0 +81308,Male,30,Masters,17,26,80,92,16,4.0,4,27,Urban,Manager,91890,0 +81309,Female,53,Bachelors,14,51,73,6,5,7.0,3,1,Semi-Urban,Data Analyst,27297,0 +81310,Male,46,Masters,18,41,40,30,79,5.0,1,90,Urban,Data Analyst,94191,0 +81311,Other,32,Bachelors,5,95,34,44,81,8.0,7,28,Semi-Urban,Software Engineer,128800,0 +81312,Male,53,Bachelors,0,81,44,98,75,3.0,3,38,Urban,Data Analyst,146563,1 +81313,Male,55,Masters,2,96,4,12,45,1.0,7,6,Semi-Urban,Manager,143905,0 +81314,Male,51,High School,14,42,80,0,68,4.0,1,11,Rural,Manager,20454,0 +81315,Female,56,Masters,4,88,13,48,16,6.0,0,48,Urban,HR Executive,57100,0 +81316,Female,38,Diploma,13,28,95,66,91,1.0,2,89,Urban,Software Engineer,86417,1 +81317,Male,47,Diploma,9,89,90,30,34,1.0,3,5,Urban,HR Executive,78486,0 +81318,Male,36,High School,11,7,16,25,26,3.0,6,1,Semi-Urban,Software Engineer,91754,0 +81319,Male,34,Bachelors,15,80,97,62,38,3.0,6,40,Urban,Software Engineer,77847,1 +81320,Female,58,Bachelors,17,46,77,8,96,0.0,3,89,Urban,Data Analyst,90593,0 +81321,Female,58,Bachelors,10,21,22,51,9,6.0,7,81,Semi-Urban,Manager,137518,0 +81322,Male,59,Bachelors,19,26,1,80,96,0.0,3,60,Urban,ML Engineer,50696,0 +81323,Male,44,Bachelors,18,62,0,10,74,4.0,0,81,Rural,ML Engineer,118207,0 +81324,Male,35,Diploma,17,12,4,7,94,6.0,4,93,Urban,Manager,96009,0 +81325,Male,34,Bachelors,6,92,22,75,33,1.0,7,26,Rural,ML Engineer,78222,0 +81326,Female,36,Bachelors,9,83,79,57,24,6.0,3,68,Semi-Urban,Software Engineer,82212,1 +81327,Male,57,Bachelors,18,1,71,18,56,6.0,6,35,Urban,HR Executive,57025,0 +81328,Male,35,Bachelors,9,50,72,42,28,6.0,0,50,Urban,Manager,112265,0 +81329,Female,34,High School,5,80,58,93,70,3.0,6,86,Semi-Urban,Software Engineer,147959,1 +81330,Female,44,Diploma,15,6,56,17,68,4.0,0,1,Urban,Manager,88785,0 +81331,Other,24,Bachelors,19,84,87,11,75,1.0,5,42,Semi-Urban,Data Analyst,32188,0 +81332,Male,55,Bachelors,13,28,43,96,39,8.0,4,20,Urban,Manager,78854,0 +81333,Male,56,Masters,0,66,7,22,92,1.0,6,8,Semi-Urban,ML Engineer,25759,0 +81334,Female,49,High School,5,34,8,71,70,3.0,6,60,Urban,Software Engineer,110333,0 +81335,Female,51,High School,18,78,92,7,79,6.0,2,79,Rural,Software Engineer,133590,1 +81336,Female,21,PhD,14,45,13,75,84,4.0,0,19,Rural,ML Engineer,80942,0 +81337,Male,47,Bachelors,19,44,29,52,98,0.0,5,52,Urban,Software Engineer,52309,0 +81338,Female,42,High School,14,46,79,71,55,5.0,5,61,Semi-Urban,Software Engineer,49880,1 +81339,Male,56,Masters,14,86,86,34,81,9.0,0,23,Semi-Urban,Data Analyst,47091,0 +81340,Male,30,High School,16,84,51,50,51,4.0,0,85,Semi-Urban,HR Executive,32388,1 +81341,Male,50,Bachelors,17,45,48,11,62,6.0,7,79,Rural,Manager,33460,0 +81342,Female,23,Bachelors,12,52,75,80,3,7.0,2,54,Urban,Data Analyst,144363,1 +81343,Male,53,Diploma,18,40,15,0,34,6.0,7,35,Urban,ML Engineer,90237,0 +81344,Female,30,Bachelors,16,75,82,21,76,8.0,7,70,Urban,Software Engineer,103159,1 +81345,Male,26,Masters,8,17,12,7,28,0.0,0,4,Rural,Software Engineer,138509,0 +81346,Male,27,Bachelors,19,78,88,37,1,0.0,5,90,Urban,ML Engineer,64454,1 +81347,Female,44,Masters,7,54,14,31,16,6.0,2,55,Urban,Manager,110789,0 +81348,Male,41,Masters,3,52,40,93,37,8.0,3,76,Semi-Urban,Manager,33065,1 +81349,Female,39,High School,16,84,4,86,69,5.0,1,16,Rural,Manager,111509,0 +81350,Male,39,High School,2,59,57,60,75,0.0,3,98,Urban,Data Analyst,138548,1 +81351,Male,57,Bachelors,16,2,31,69,18,8.0,7,63,Rural,Manager,79144,0 +81352,Female,52,High School,17,58,46,7,59,9.0,6,74,Rural,Data Analyst,115249,0 +81353,Female,30,Bachelors,19,42,31,40,24,1.0,4,19,Rural,HR Executive,140564,0 +81354,Male,31,High School,17,55,51,30,77,4.0,1,27,Urban,Manager,48613,0 +81355,Male,39,Diploma,4,10,40,5,6,0.0,0,62,Semi-Urban,Manager,62929,0 +81356,Male,52,Masters,8,63,83,64,84,8.0,3,51,Semi-Urban,HR Executive,29666,1 +81357,Female,49,Bachelors,10,51,24,32,88,9.0,4,99,Urban,Manager,31587,0 +81358,Other,22,Bachelors,11,51,2,1,26,4.0,4,29,Rural,Manager,119129,0 +81359,Male,29,High School,9,40,65,6,17,5.0,7,52,Urban,ML Engineer,55964,0 +81360,Male,31,Bachelors,12,17,45,34,12,4.0,5,31,Urban,Data Analyst,20482,0 +81361,Female,34,Bachelors,19,53,24,12,15,9.0,7,58,Rural,Manager,23613,0 +81362,Male,40,Bachelors,12,14,36,91,93,4.0,7,16,Urban,HR Executive,40822,0 +81363,Male,34,Masters,11,64,13,57,92,3.0,0,87,Urban,Manager,63016,0 +81364,Male,47,Bachelors,11,73,6,68,35,9.0,6,7,Urban,HR Executive,70999,0 +81365,Female,25,Diploma,12,20,31,92,84,5.0,7,28,Rural,ML Engineer,50833,0 +81366,Female,32,Bachelors,3,3,85,70,64,1.0,5,96,Semi-Urban,HR Executive,26680,1 +81367,Male,46,Bachelors,0,61,43,44,48,3.0,3,8,Urban,Data Analyst,32672,0 +81368,Male,33,Bachelors,3,46,86,8,62,0.0,6,76,Rural,Manager,29011,0 +81369,Male,24,Diploma,17,2,46,93,35,2.0,2,76,Urban,ML Engineer,126807,0 +81370,Male,52,Masters,12,68,48,50,23,8.0,2,53,Semi-Urban,Manager,89134,0 +81371,Male,30,Bachelors,11,20,88,92,71,7.0,2,93,Urban,Data Analyst,59432,1 +81372,Male,52,High School,10,82,43,24,91,2.0,6,74,Urban,Manager,21581,0 +81373,Male,26,Bachelors,8,91,31,84,91,3.0,6,38,Rural,Manager,84047,1 +81374,Female,58,High School,2,39,4,11,76,2.0,2,8,Urban,HR Executive,112710,0 +81375,Male,40,Diploma,13,70,23,58,55,9.0,6,97,Urban,Manager,103964,1 +81376,Female,58,Diploma,5,35,63,26,58,9.0,4,57,Rural,HR Executive,124789,0 +81377,Male,25,Masters,6,27,47,26,94,2.0,5,4,Urban,HR Executive,83011,0 +81378,Female,46,Bachelors,2,14,61,44,6,3.0,1,8,Urban,Data Analyst,26188,0 +81379,Female,25,Bachelors,3,8,30,49,6,8.0,2,35,Urban,ML Engineer,142913,0 +81380,Male,21,Masters,7,61,90,0,79,8.0,5,26,Urban,ML Engineer,71893,0 +81381,Female,23,Bachelors,4,80,33,84,17,6.0,2,95,Urban,Data Analyst,119278,1 +81382,Female,39,Bachelors,11,91,68,54,38,2.0,2,44,Rural,Data Analyst,71907,1 +81383,Other,42,High School,16,48,86,99,9,2.0,4,56,Urban,Data Analyst,113096,1 +81384,Male,36,High School,16,20,24,55,44,0.0,6,7,Urban,Software Engineer,102275,0 +81385,Male,40,Diploma,6,11,44,47,19,7.0,7,0,Rural,Software Engineer,81276,0 +81386,Other,56,Bachelors,9,18,17,51,12,4.0,2,4,Urban,Data Analyst,23345,0 +81387,Male,58,Bachelors,4,82,49,28,32,9.0,1,58,Rural,Data Analyst,52908,0 +81388,Other,58,Bachelors,14,69,45,68,75,5.0,4,42,Semi-Urban,ML Engineer,47220,0 +81389,Female,50,Bachelors,16,97,73,98,13,5.0,7,72,Urban,Manager,139618,1 +81390,Male,23,Bachelors,11,17,27,37,14,1.0,4,45,Rural,ML Engineer,94664,0 +81391,Male,36,High School,1,91,32,25,41,7.0,0,46,Urban,Software Engineer,79238,0 +81392,Male,21,Bachelors,12,57,0,67,21,3.0,1,30,Rural,Manager,132237,0 +81393,Male,58,Diploma,8,89,24,62,37,0.0,5,40,Urban,ML Engineer,28839,0 +81394,Male,51,High School,9,72,26,59,54,4.0,0,49,Urban,HR Executive,44508,0 +81395,Female,29,PhD,1,66,32,99,58,8.0,7,41,Semi-Urban,Software Engineer,51163,0 +81396,Male,38,Diploma,9,17,19,41,98,2.0,1,44,Urban,Software Engineer,148550,0 +81397,Male,58,High School,1,91,21,3,97,3.0,7,75,Rural,ML Engineer,106203,0 +81398,Male,58,High School,0,60,28,45,86,3.0,4,88,Urban,HR Executive,60062,0 +81399,Female,34,High School,12,3,83,82,4,0.0,2,92,Rural,ML Engineer,119758,1 +81400,Male,43,Diploma,0,80,93,6,15,1.0,2,25,Rural,Software Engineer,63515,0 +81401,Female,45,PhD,2,3,4,71,0,6.0,1,45,Semi-Urban,Manager,85763,0 +81402,Male,56,PhD,14,37,83,90,5,2.0,2,14,Urban,Manager,37883,0 +81403,Female,37,High School,3,19,35,76,18,4.0,2,88,Semi-Urban,ML Engineer,46742,0 +81404,Female,27,Masters,6,22,42,6,31,1.0,0,65,Semi-Urban,Software Engineer,82450,0 +81405,Male,46,Bachelors,14,9,69,98,23,6.0,6,60,Semi-Urban,Manager,84203,1 +81406,Male,52,High School,17,29,27,65,2,4.0,6,14,Semi-Urban,Data Analyst,106341,0 +81407,Male,23,Bachelors,14,18,40,22,47,6.0,6,94,Semi-Urban,Data Analyst,33710,0 +81408,Male,49,Bachelors,7,12,64,77,74,0.0,4,37,Urban,Data Analyst,96633,0 +81409,Male,53,Bachelors,7,56,99,20,69,7.0,5,4,Rural,Manager,114991,0 +81410,Male,28,High School,2,17,10,14,34,7.0,3,65,Urban,Data Analyst,119114,0 +81411,Male,24,Bachelors,18,53,12,27,28,2.0,0,87,Urban,Manager,27129,0 +81412,Male,37,Bachelors,19,18,99,15,27,2.0,7,24,Rural,Manager,92325,0 +81413,Male,38,Bachelors,12,67,13,56,45,3.0,6,31,Semi-Urban,Software Engineer,91474,0 +81414,Male,46,High School,12,98,54,23,74,8.0,1,94,Urban,ML Engineer,135362,1 +81415,Other,38,Diploma,3,71,55,6,15,8.0,7,84,Urban,HR Executive,139511,0 +81416,Female,39,Bachelors,6,41,50,86,5,7.0,5,60,Urban,Software Engineer,66561,0 +81417,Male,23,Bachelors,9,0,14,29,17,2.0,5,80,Urban,HR Executive,46605,0 +81418,Female,21,Masters,12,15,29,58,88,6.0,5,28,Semi-Urban,Data Analyst,49056,0 +81419,Male,25,Bachelors,1,23,89,8,34,6.0,6,82,Urban,Software Engineer,35590,0 +81420,Male,43,High School,15,9,38,33,97,9.0,5,29,Urban,Software Engineer,100026,0 +81421,Other,44,Diploma,19,37,58,4,53,6.0,3,52,Rural,Manager,24553,0 +81422,Female,41,Masters,16,75,81,57,66,6.0,7,62,Semi-Urban,HR Executive,68401,1 +81423,Male,47,Diploma,11,23,15,13,35,9.0,4,29,Urban,ML Engineer,82884,0 +81424,Male,33,Diploma,3,99,41,33,91,7.0,0,15,Urban,Manager,85791,0 +81425,Male,48,Bachelors,3,56,76,15,9,8.0,4,71,Urban,Manager,64552,0 +81426,Female,32,Bachelors,15,87,48,10,6,9.0,2,78,Semi-Urban,ML Engineer,22572,0 +81427,Male,34,High School,7,58,36,3,76,6.0,6,42,Semi-Urban,Software Engineer,88591,0 +81428,Male,38,Bachelors,4,83,68,84,75,0.0,5,16,Urban,Data Analyst,119483,1 +81429,Male,53,Diploma,11,22,83,36,35,8.0,5,91,Semi-Urban,HR Executive,45849,0 +81430,Male,40,Masters,18,97,0,15,92,8.0,4,40,Semi-Urban,ML Engineer,143964,0 +81431,Male,51,PhD,4,82,68,79,85,7.0,4,24,Semi-Urban,ML Engineer,112861,1 +81432,Male,40,Bachelors,18,26,90,84,61,8.0,2,15,Urban,ML Engineer,53815,0 +81433,Male,45,Bachelors,10,23,39,73,8,4.0,5,59,Urban,Software Engineer,55658,0 +81434,Female,32,Bachelors,3,4,75,67,44,4.0,3,34,Semi-Urban,Manager,145998,0 +81435,Female,23,Bachelors,11,47,15,36,95,1.0,3,51,Urban,ML Engineer,146969,0 +81436,Female,31,Bachelors,9,12,50,15,77,7.0,7,27,Urban,HR Executive,32089,0 +81437,Female,28,Diploma,0,34,65,89,33,2.0,7,93,Rural,ML Engineer,109848,1 +81438,Female,40,PhD,1,17,44,8,46,4.0,4,64,Semi-Urban,Software Engineer,148112,0 +81439,Male,47,Diploma,17,92,0,10,79,8.0,0,61,Urban,HR Executive,109187,0 +81440,Male,58,Masters,7,69,96,23,36,8.0,7,11,Rural,Software Engineer,110744,0 +81441,Male,56,Masters,10,86,18,11,81,5.0,4,20,Semi-Urban,Manager,44264,0 +81442,Male,47,High School,11,59,60,48,70,1.0,6,6,Urban,ML Engineer,31916,0 +81443,Male,49,Bachelors,19,12,30,15,48,6.0,0,97,Urban,ML Engineer,81081,0 +81444,Female,37,Bachelors,0,2,54,0,94,4.0,1,98,Urban,Software Engineer,85041,0 +81445,Male,30,Bachelors,3,82,71,47,80,7.0,4,20,Urban,Data Analyst,88549,0 +81446,Male,47,Masters,10,85,23,76,80,3.0,1,70,Urban,ML Engineer,33714,1 +81447,Male,29,Bachelors,13,6,0,64,19,1.0,1,7,Urban,Manager,92023,0 +81448,Male,26,High School,12,15,77,31,33,3.0,4,43,Urban,ML Engineer,72725,0 +81449,Male,31,Diploma,3,94,8,93,93,4.0,7,77,Semi-Urban,Software Engineer,29970,1 +81450,Male,33,Diploma,10,86,7,84,27,2.0,4,61,Urban,Data Analyst,118184,1 +81451,Female,53,Diploma,15,68,84,6,23,2.0,5,48,Semi-Urban,Manager,67349,0 +81452,Male,58,High School,17,86,34,16,80,8.0,4,54,Rural,Data Analyst,68215,0 +81453,Male,37,PhD,19,87,91,91,28,0.0,1,7,Urban,Manager,65216,1 +81454,Female,46,High School,0,54,42,67,30,1.0,1,97,Semi-Urban,HR Executive,101058,1 +81455,Male,50,Masters,9,25,56,36,60,8.0,0,22,Urban,Data Analyst,93567,0 +81456,Male,41,Masters,6,5,92,33,51,4.0,0,74,Urban,ML Engineer,70656,0 +81457,Male,58,Diploma,12,6,47,30,55,3.0,2,55,Semi-Urban,ML Engineer,79922,0 +81458,Female,37,Diploma,13,19,87,6,60,5.0,3,44,Rural,Software Engineer,20653,0 +81459,Female,24,Bachelors,5,41,57,74,3,2.0,2,57,Urban,HR Executive,139622,0 +81460,Male,26,High School,19,83,49,44,18,4.0,0,23,Rural,Software Engineer,101038,0 +81461,Female,48,Masters,14,69,19,58,77,7.0,0,82,Semi-Urban,Manager,118453,0 +81462,Male,33,High School,13,87,19,85,10,0.0,1,39,Rural,HR Executive,44456,0 +81463,Female,35,Bachelors,16,71,65,77,50,5.0,4,74,Rural,HR Executive,117921,1 +81464,Female,45,Bachelors,10,86,45,36,75,9.0,2,25,Rural,ML Engineer,130682,0 +81465,Male,24,Masters,5,10,79,13,22,8.0,7,50,Rural,HR Executive,95189,0 +81466,Female,41,Diploma,18,74,48,31,35,5.0,4,41,Semi-Urban,Manager,86303,0 +81467,Male,40,High School,5,65,60,37,90,7.0,4,92,Urban,HR Executive,56844,1 +81468,Male,31,Masters,6,28,80,0,51,6.0,0,19,Semi-Urban,Data Analyst,27519,0 +81469,Male,21,Masters,6,77,75,7,88,1.0,5,47,Rural,HR Executive,37115,0 +81470,Male,47,Bachelors,12,44,10,95,13,0.0,0,45,Urban,Manager,148080,0 +81471,Other,48,Bachelors,16,51,92,84,57,3.0,4,52,Urban,Software Engineer,145603,1 +81472,Female,32,Bachelors,3,29,98,90,65,7.0,0,32,Urban,ML Engineer,87683,1 +81473,Male,37,Masters,10,68,51,88,73,5.0,5,40,Semi-Urban,Data Analyst,111025,1 +81474,Male,38,Bachelors,10,17,69,41,45,6.0,2,23,Urban,ML Engineer,58140,0 +81475,Male,30,Bachelors,18,98,91,94,56,2.0,7,51,Semi-Urban,Manager,149121,1 +81476,Male,34,Bachelors,15,56,42,38,64,6.0,4,70,Urban,Data Analyst,85613,0 +81477,Female,33,Diploma,19,74,4,38,79,5.0,5,87,Urban,HR Executive,112752,0 +81478,Male,42,Bachelors,2,85,98,63,28,8.0,5,72,Urban,ML Engineer,36320,1 +81479,Male,33,Bachelors,12,47,40,58,23,3.0,5,21,Urban,HR Executive,22051,0 +81480,Female,31,Masters,17,98,22,22,98,6.0,1,14,Urban,Manager,104075,0 +81481,Male,36,High School,4,14,0,58,15,1.0,4,34,Urban,Manager,76708,0 +81482,Male,30,Bachelors,16,40,76,73,11,4.0,2,87,Rural,HR Executive,68724,1 +81483,Male,48,PhD,19,30,40,99,13,1.0,0,26,Semi-Urban,HR Executive,138122,0 +81484,Female,52,High School,11,3,78,57,30,4.0,0,32,Urban,HR Executive,129640,0 +81485,Male,26,High School,12,35,90,64,45,5.0,1,87,Urban,Manager,77988,1 +81486,Female,37,Bachelors,2,57,62,42,51,7.0,5,90,Semi-Urban,Manager,61904,1 +81487,Male,27,Bachelors,9,17,18,41,96,3.0,6,42,Urban,HR Executive,147978,0 +81488,Male,33,High School,1,38,15,35,55,0.0,1,12,Rural,ML Engineer,60571,0 +81489,Male,39,High School,15,78,86,0,68,0.0,2,76,Urban,Software Engineer,128622,1 +81490,Other,31,Diploma,14,91,16,79,38,8.0,0,93,Urban,Data Analyst,21332,1 +81491,Male,25,Bachelors,4,8,95,98,27,7.0,2,65,Semi-Urban,Software Engineer,144475,1 +81492,Male,33,Diploma,3,11,58,95,92,7.0,5,8,Urban,Software Engineer,105097,0 +81493,Other,52,Bachelors,11,33,70,94,45,0.0,3,93,Rural,ML Engineer,64671,1 +81494,Male,55,Diploma,6,6,68,78,53,2.0,5,35,Urban,ML Engineer,23053,0 +81495,Male,59,Diploma,12,70,79,85,45,8.0,5,10,Urban,ML Engineer,77732,1 +81496,Male,44,Bachelors,15,54,57,13,29,6.0,6,11,Urban,ML Engineer,48652,0 +81497,Male,24,Bachelors,6,41,66,20,33,9.0,7,3,Semi-Urban,HR Executive,100625,0 +81498,Female,24,High School,9,43,69,78,9,7.0,4,37,Urban,Software Engineer,65186,0 +81499,Male,59,Masters,11,44,33,73,17,3.0,6,14,Urban,Data Analyst,46541,0 +81500,Male,26,Masters,8,64,39,41,46,1.0,5,75,Semi-Urban,Manager,61701,0 +81501,Female,51,Masters,12,95,52,81,70,1.0,3,49,Urban,Software Engineer,139170,1 +81502,Male,54,PhD,3,25,32,21,70,9.0,3,28,Rural,HR Executive,39952,0 +81503,Male,44,Diploma,2,33,59,57,6,7.0,1,61,Rural,Data Analyst,144683,0 +81504,Other,22,Diploma,3,70,14,35,50,6.0,4,38,Semi-Urban,Manager,80496,0 +81505,Male,43,Diploma,0,94,16,93,91,3.0,0,72,Semi-Urban,Data Analyst,24916,1 +81506,Female,59,Bachelors,5,37,50,80,85,3.0,1,61,Urban,Manager,42982,0 +81507,Female,47,High School,19,33,26,78,91,4.0,0,31,Urban,ML Engineer,103543,0 +81508,Male,38,Bachelors,11,0,50,98,95,1.0,3,80,Rural,Manager,36745,0 +81509,Female,49,High School,8,57,3,11,19,3.0,7,1,Rural,Data Analyst,20648,0 +81510,Male,54,Diploma,6,4,80,1,32,3.0,0,68,Urban,Manager,59503,0 +81511,Male,51,High School,12,5,25,22,19,2.0,1,38,Urban,Data Analyst,21933,0 +81512,Female,58,Diploma,6,4,95,3,40,0.0,5,51,Urban,Software Engineer,126173,0 +81513,Female,42,Diploma,9,62,88,32,45,0.0,7,52,Urban,Data Analyst,61831,0 +81514,Male,37,High School,1,90,46,97,98,4.0,7,20,Urban,Manager,33013,1 +81515,Female,25,Diploma,16,81,44,52,98,6.0,4,52,Semi-Urban,Software Engineer,103190,0 +81516,Male,45,PhD,7,64,98,84,75,1.0,1,5,Semi-Urban,Manager,38106,1 +81517,Male,21,Bachelors,12,72,61,41,27,7.0,5,42,Urban,Software Engineer,89923,0 +81518,Female,30,High School,8,58,70,61,66,8.0,6,25,Semi-Urban,HR Executive,142752,0 +81519,Male,39,Diploma,17,86,22,86,1,2.0,7,68,Urban,Software Engineer,109391,1 +81520,Male,57,Masters,5,46,20,8,58,0.0,2,49,Urban,HR Executive,43362,0 +81521,Male,57,Bachelors,19,82,66,8,90,1.0,6,0,Rural,Manager,83751,0 +81522,Other,46,Bachelors,8,92,67,53,52,5.0,7,84,Urban,ML Engineer,139648,1 +81523,Male,28,Diploma,1,65,4,13,32,9.0,2,94,Urban,HR Executive,119377,0 +81524,Male,37,Bachelors,9,12,86,68,48,6.0,7,26,Semi-Urban,Software Engineer,51462,0 +81525,Male,41,High School,8,47,68,39,78,6.0,4,34,Urban,ML Engineer,120294,0 +81526,Male,26,Masters,6,40,62,13,43,5.0,7,40,Rural,Data Analyst,119576,0 +81527,Male,55,Bachelors,3,6,56,39,44,6.0,7,24,Semi-Urban,HR Executive,45740,0 +81528,Female,48,Bachelors,13,23,74,83,54,0.0,3,48,Semi-Urban,HR Executive,25809,0 +81529,Other,51,Bachelors,2,84,52,56,98,1.0,3,36,Rural,Manager,149036,0 +81530,Female,26,Bachelors,10,57,72,97,92,6.0,0,12,Semi-Urban,Software Engineer,124726,0 +81531,Female,34,Diploma,1,26,31,71,16,6.0,2,10,Urban,Data Analyst,87666,0 +81532,Female,42,Bachelors,13,47,5,31,41,2.0,7,80,Rural,Data Analyst,65111,0 +81533,Male,23,Masters,0,50,9,9,76,3.0,4,26,Rural,HR Executive,50327,0 +81534,Male,41,Bachelors,4,2,27,36,66,7.0,6,3,Urban,ML Engineer,24967,0 +81535,Female,31,Bachelors,14,75,23,5,7,6.0,5,61,Urban,Data Analyst,139840,0 +81536,Male,55,Bachelors,2,64,50,22,56,5.0,0,65,Semi-Urban,ML Engineer,96971,0 +81537,Male,56,Bachelors,15,5,89,63,97,3.0,4,40,Semi-Urban,Data Analyst,62660,0 +81538,Other,29,Bachelors,3,64,78,20,11,5.0,2,86,Urban,Manager,137525,1 +81539,Male,51,Diploma,7,60,15,8,24,6.0,0,80,Urban,Manager,135738,0 +81540,Male,22,Masters,9,64,13,46,70,7.0,4,18,Semi-Urban,ML Engineer,65877,0 +81541,Female,54,Bachelors,18,15,69,2,53,6.0,7,52,Rural,ML Engineer,33523,0 +81542,Female,50,Bachelors,11,61,48,67,68,7.0,1,31,Urban,HR Executive,20258,0 +81543,Male,42,Diploma,2,74,5,68,31,2.0,4,47,Semi-Urban,Software Engineer,22875,0 +81544,Female,36,Diploma,12,34,94,58,60,5.0,3,14,Urban,Data Analyst,20632,0 +81545,Male,51,Diploma,3,51,44,77,76,8.0,6,86,Rural,Manager,62768,1 +81546,Male,34,Bachelors,19,19,63,70,85,2.0,7,95,Urban,HR Executive,133244,1 +81547,Other,43,Diploma,8,54,20,35,74,6.0,0,52,Urban,Data Analyst,53206,0 +81548,Female,56,Masters,2,28,5,10,22,4.0,1,37,Urban,ML Engineer,54828,0 +81549,Female,52,Masters,9,51,75,28,81,1.0,3,52,Urban,Data Analyst,78476,0 +81550,Female,42,Bachelors,13,16,90,9,46,8.0,1,45,Urban,Software Engineer,112104,0 +81551,Male,35,Bachelors,8,17,37,33,28,7.0,0,79,Semi-Urban,HR Executive,71321,0 +81552,Female,33,Bachelors,10,73,99,87,75,3.0,3,48,Urban,Manager,45101,1 +81553,Female,46,Diploma,12,95,85,20,52,0.0,0,22,Urban,ML Engineer,65452,0 +81554,Male,51,High School,9,6,0,62,89,7.0,5,42,Urban,Software Engineer,145542,0 +81555,Female,54,Bachelors,11,63,7,83,21,8.0,1,64,Urban,Data Analyst,116653,0 +81556,Male,28,High School,9,6,75,34,59,2.0,1,75,Urban,Data Analyst,123107,0 +81557,Male,44,Bachelors,14,82,34,30,24,0.0,3,0,Semi-Urban,Data Analyst,73142,0 +81558,Male,21,Masters,9,40,32,56,68,2.0,4,74,Rural,Manager,136406,0 +81559,Male,55,High School,4,34,86,93,50,2.0,2,18,Semi-Urban,HR Executive,48130,0 +81560,Male,50,PhD,0,18,46,96,67,7.0,1,8,Urban,Data Analyst,63226,0 +81561,Male,34,Diploma,7,15,12,66,34,5.0,0,80,Rural,Data Analyst,57723,0 +81562,Female,37,Bachelors,0,87,67,81,26,6.0,6,97,Urban,Data Analyst,36027,1 +81563,Female,46,High School,15,19,97,64,34,3.0,5,24,Rural,ML Engineer,144901,0 +81564,Male,32,Masters,13,63,50,69,21,1.0,2,46,Urban,Data Analyst,86226,0 +81565,Other,28,Bachelors,19,38,46,35,4,3.0,4,90,Urban,ML Engineer,143191,0 +81566,Female,25,Bachelors,8,52,63,24,31,7.0,0,30,Urban,Software Engineer,74347,0 +81567,Female,33,PhD,18,32,8,37,13,6.0,1,28,Semi-Urban,Data Analyst,107447,0 +81568,Male,49,Bachelors,8,33,98,45,38,0.0,7,11,Semi-Urban,Manager,107441,0 +81569,Other,54,Bachelors,6,36,51,52,76,1.0,2,68,Semi-Urban,Software Engineer,146416,0 +81570,Other,33,Bachelors,8,43,4,59,37,6.0,3,36,Urban,Manager,68223,0 +81571,Male,55,Diploma,1,24,93,79,26,0.0,1,33,Rural,HR Executive,53046,0 +81572,Other,50,Bachelors,12,50,57,4,41,9.0,5,40,Rural,HR Executive,121053,0 +81573,Female,29,Bachelors,15,77,34,37,98,1.0,7,40,Rural,Software Engineer,83046,0 +81574,Male,56,High School,5,54,24,58,52,6.0,4,77,Urban,Manager,39858,0 +81575,Female,34,High School,18,53,28,50,22,5.0,7,76,Rural,Manager,38289,0 +81576,Male,43,High School,19,69,44,20,17,0.0,2,75,Rural,ML Engineer,99454,0 +81577,Male,42,Bachelors,1,77,70,44,11,8.0,4,91,Urban,HR Executive,134705,1 +81578,Male,52,Masters,2,70,47,99,94,3.0,3,48,Urban,ML Engineer,51618,1 +81579,Male,44,Diploma,0,91,9,51,18,2.0,0,69,Urban,HR Executive,65617,0 +81580,Female,38,Masters,7,57,39,93,4,3.0,2,59,Urban,HR Executive,134986,1 +81581,Female,52,Diploma,11,58,70,20,49,7.0,2,45,Semi-Urban,Data Analyst,51018,0 +81582,Male,22,Diploma,7,24,98,60,37,1.0,3,32,Urban,HR Executive,62918,0 +81583,Male,53,Bachelors,16,39,89,53,84,4.0,6,17,Semi-Urban,ML Engineer,36582,0 +81584,Female,30,Masters,19,10,40,22,39,6.0,6,95,Urban,Software Engineer,54368,0 +81585,Male,33,PhD,13,66,27,72,58,7.0,5,52,Urban,Data Analyst,79596,0 +81586,Female,50,PhD,2,33,32,93,35,1.0,7,57,Urban,ML Engineer,62860,0 +81587,Female,53,Bachelors,10,67,35,58,28,5.0,4,10,Rural,Manager,113993,0 +81588,Other,50,Diploma,19,45,65,17,41,3.0,7,46,Rural,HR Executive,76541,0 +81589,Female,34,Diploma,10,61,81,67,12,0.0,3,74,Semi-Urban,HR Executive,144347,1 +81590,Female,44,Bachelors,5,48,93,40,74,9.0,7,89,Urban,Software Engineer,122845,1 +81591,Female,33,Bachelors,14,21,50,63,49,4.0,6,89,Urban,Manager,134174,0 +81592,Female,26,Bachelors,1,29,68,0,63,2.0,2,17,Semi-Urban,Software Engineer,27768,0 +81593,Male,53,Masters,14,51,22,75,62,1.0,6,59,Rural,ML Engineer,116303,0 +81594,Male,49,High School,5,62,13,80,68,2.0,7,0,Semi-Urban,ML Engineer,77321,0 +81595,Female,58,Masters,17,77,10,73,95,2.0,2,28,Rural,HR Executive,25494,0 +81596,Other,58,Bachelors,1,52,88,79,47,2.0,3,62,Semi-Urban,ML Engineer,92108,1 +81597,Male,33,Diploma,1,68,50,65,83,3.0,7,56,Urban,ML Engineer,125291,1 +81598,Male,34,Diploma,9,44,59,3,6,6.0,6,15,Urban,HR Executive,125379,0 +81599,Male,23,Masters,14,3,10,46,78,3.0,5,80,Semi-Urban,Software Engineer,75149,0 +81600,Female,50,Masters,8,92,30,36,69,3.0,3,20,Urban,ML Engineer,136789,0 +81601,Female,46,Diploma,4,32,19,55,67,0.0,4,98,Urban,Data Analyst,117977,0 +81602,Male,44,Masters,6,20,7,0,81,1.0,7,74,Rural,ML Engineer,48969,0 +81603,Female,43,High School,15,55,17,25,50,0.0,4,65,Semi-Urban,Data Analyst,32252,0 +81604,Female,49,High School,1,1,2,92,35,5.0,3,95,Urban,Data Analyst,59763,0 +81605,Female,34,High School,7,78,15,59,55,2.0,0,41,Semi-Urban,Manager,94273,0 +81606,Male,36,Bachelors,15,85,7,31,72,6.0,7,74,Semi-Urban,Software Engineer,90241,0 +81607,Female,23,High School,6,33,86,60,4,6.0,5,43,Urban,ML Engineer,49010,0 +81608,Male,24,PhD,17,96,17,28,79,8.0,4,13,Rural,Software Engineer,110549,0 +81609,Female,36,Masters,18,49,28,79,0,7.0,7,99,Urban,Manager,133928,1 +81610,Male,53,Masters,3,61,72,95,68,5.0,3,89,Semi-Urban,Data Analyst,99506,1 +81611,Male,26,Diploma,15,55,86,14,14,0.0,1,48,Urban,Data Analyst,64261,0 +81612,Male,55,Bachelors,1,19,56,70,72,9.0,0,58,Urban,Software Engineer,114097,0 +81613,Male,57,Bachelors,2,34,67,70,75,1.0,6,88,Semi-Urban,ML Engineer,86077,1 +81614,Other,31,Bachelors,19,68,4,50,42,6.0,5,40,Urban,Manager,38658,0 +81615,Male,28,Diploma,15,85,23,32,17,3.0,4,84,Semi-Urban,ML Engineer,77993,0 +81616,Other,22,Masters,14,64,90,17,89,4.0,4,20,Urban,ML Engineer,129058,0 +81617,Male,40,Diploma,11,0,29,90,93,4.0,7,35,Urban,Data Analyst,61254,0 +81618,Other,28,Masters,9,51,55,57,53,7.0,0,89,Urban,Manager,146371,1 +81619,Other,37,Masters,2,82,19,15,13,9.0,1,58,Rural,Data Analyst,65773,0 +81620,Male,32,Diploma,6,92,52,24,29,5.0,4,66,Semi-Urban,HR Executive,113936,0 +81621,Female,31,Bachelors,0,16,67,65,20,7.0,0,86,Urban,Manager,128762,0 +81622,Male,22,Bachelors,2,80,50,28,74,1.0,6,98,Rural,Software Engineer,88363,1 +81623,Female,47,Diploma,17,6,97,21,89,5.0,4,55,Urban,HR Executive,52556,0 +81624,Female,30,Diploma,3,21,70,22,17,3.0,3,90,Urban,Manager,20135,0 +81625,Male,28,Masters,7,11,29,16,58,4.0,6,46,Urban,Manager,93475,0 +81626,Female,54,Bachelors,18,19,91,88,18,6.0,0,8,Urban,ML Engineer,41487,0 +81627,Male,21,PhD,12,78,54,39,68,5.0,1,31,Urban,Data Analyst,98652,0 +81628,Female,51,High School,16,5,38,41,17,8.0,3,85,Rural,Data Analyst,86709,0 +81629,Male,56,Masters,5,6,95,81,81,3.0,6,62,Urban,ML Engineer,114858,1 +81630,Female,40,Masters,17,52,20,79,59,3.0,5,17,Urban,Data Analyst,72926,0 +81631,Female,25,Bachelors,9,29,67,63,24,3.0,2,35,Semi-Urban,Manager,70130,0 +81632,Female,44,Masters,9,5,93,16,46,3.0,3,42,Semi-Urban,HR Executive,120976,0 +81633,Female,45,Bachelors,6,38,92,90,45,8.0,2,49,Urban,Software Engineer,40057,1 +81634,Male,39,Diploma,18,4,56,61,38,6.0,7,42,Rural,ML Engineer,25366,0 +81635,Male,59,Bachelors,2,33,75,94,85,7.0,4,75,Rural,Software Engineer,80762,1 +81636,Male,53,Bachelors,5,34,5,89,44,2.0,3,85,Semi-Urban,ML Engineer,144479,0 +81637,Female,37,Bachelors,15,99,76,22,10,5.0,4,48,Urban,HR Executive,39538,1 +81638,Other,57,High School,17,39,93,63,23,1.0,6,53,Urban,Data Analyst,142202,1 +81639,Male,27,Diploma,7,22,30,33,66,3.0,1,67,Urban,Data Analyst,76609,0 +81640,Male,23,High School,12,12,7,6,65,9.0,2,72,Rural,Data Analyst,66488,0 +81641,Female,24,Bachelors,6,32,77,89,6,7.0,4,89,Urban,Manager,149839,1 +81642,Female,49,Masters,3,83,53,38,30,6.0,1,73,Urban,ML Engineer,145005,1 +81643,Female,52,Masters,19,25,3,64,61,1.0,5,64,Rural,Manager,59644,0 +81644,Male,49,Diploma,15,58,31,29,54,8.0,4,18,Semi-Urban,HR Executive,145337,0 +81645,Female,45,Masters,7,0,63,62,52,0.0,6,21,Urban,Manager,96239,0 +81646,Male,46,High School,4,60,37,68,3,7.0,6,42,Rural,Manager,124234,0 +81647,Male,24,Bachelors,4,57,10,17,83,6.0,4,88,Urban,ML Engineer,54181,0 +81648,Male,26,Bachelors,2,35,96,81,76,0.0,4,11,Rural,Software Engineer,70373,0 +81649,Female,44,Diploma,13,21,85,96,39,9.0,6,51,Urban,Manager,130445,1 +81650,Male,59,Bachelors,18,52,45,85,66,9.0,7,34,Rural,Data Analyst,121235,0 +81651,Male,42,Bachelors,6,12,83,1,81,9.0,2,0,Rural,ML Engineer,143686,0 +81652,Female,52,Bachelors,19,65,66,99,82,4.0,7,69,Semi-Urban,Data Analyst,61521,1 +81653,Male,45,High School,4,21,96,75,66,7.0,7,34,Rural,ML Engineer,139899,0 +81654,Female,45,Masters,11,28,49,86,8,6.0,0,96,Urban,Software Engineer,42004,1 +81655,Female,48,Masters,6,0,3,61,49,3.0,1,14,Rural,ML Engineer,91741,0 +81656,Male,37,Bachelors,18,79,76,79,15,1.0,0,90,Semi-Urban,HR Executive,48664,1 +81657,Male,44,High School,13,94,84,74,75,0.0,0,12,Urban,Manager,44071,1 +81658,Male,26,High School,15,44,89,20,53,3.0,4,84,Urban,Data Analyst,141982,1 +81659,Male,40,Bachelors,8,78,16,25,9,9.0,0,94,Semi-Urban,Data Analyst,117161,0 +81660,Male,27,High School,6,71,39,13,13,4.0,6,93,Urban,Data Analyst,43900,0 +81661,Female,57,Bachelors,18,97,3,37,74,7.0,7,88,Urban,Software Engineer,71714,0 +81662,Male,29,High School,1,62,79,91,5,8.0,4,28,Urban,Software Engineer,45620,1 +81663,Male,35,Masters,15,29,59,55,81,3.0,0,13,Urban,Software Engineer,60714,0 +81664,Female,22,PhD,15,62,96,20,55,1.0,3,56,Semi-Urban,Manager,77250,0 +81665,Male,41,High School,19,75,61,50,88,2.0,7,49,Rural,Manager,120046,1 +81666,Male,47,High School,19,53,12,52,4,4.0,7,94,Urban,Manager,62151,0 +81667,Female,43,High School,17,79,97,5,92,9.0,3,6,Urban,Data Analyst,81153,0 +81668,Female,57,Masters,10,24,91,87,41,9.0,4,41,Urban,Software Engineer,68433,1 +81669,Female,57,Bachelors,18,45,57,80,26,8.0,4,26,Urban,HR Executive,58749,0 +81670,Female,35,Masters,11,72,80,0,22,2.0,0,89,Semi-Urban,Manager,36813,1 +81671,Female,50,Masters,1,36,1,29,28,5.0,1,44,Urban,ML Engineer,103004,0 +81672,Female,21,Bachelors,14,2,20,17,16,7.0,7,51,Semi-Urban,Data Analyst,129085,0 +81673,Male,26,Masters,15,68,94,27,20,3.0,6,92,Urban,HR Executive,135233,1 +81674,Male,53,Bachelors,9,99,26,96,44,2.0,0,70,Semi-Urban,HR Executive,131521,1 +81675,Male,44,Bachelors,14,24,41,51,51,5.0,5,56,Rural,Software Engineer,83459,0 +81676,Male,39,High School,1,45,80,48,33,9.0,2,7,Urban,Software Engineer,123810,0 +81677,Male,56,Masters,5,18,15,67,95,3.0,4,75,Urban,Software Engineer,119068,0 +81678,Male,32,Masters,10,57,62,11,81,1.0,1,49,Rural,Data Analyst,146780,0 +81679,Male,54,High School,13,15,22,84,3,4.0,3,12,Semi-Urban,ML Engineer,21586,0 +81680,Female,49,Masters,13,92,43,28,51,8.0,4,62,Urban,Software Engineer,75114,0 +81681,Female,39,Masters,5,0,82,59,26,7.0,6,12,Semi-Urban,Software Engineer,70810,0 +81682,Female,45,Diploma,12,62,30,52,41,5.0,1,25,Semi-Urban,Software Engineer,80776,0 +81683,Male,31,High School,3,82,83,51,3,2.0,1,8,Urban,Data Analyst,144739,0 +81684,Male,28,Diploma,3,33,66,76,89,2.0,5,85,Urban,HR Executive,128197,1 +81685,Male,41,Masters,8,14,11,83,39,7.0,3,3,Rural,Software Engineer,135730,0 +81686,Female,45,Bachelors,17,51,42,94,85,3.0,5,15,Urban,ML Engineer,108045,0 +81687,Male,38,Masters,4,41,5,95,41,1.0,6,81,Semi-Urban,Software Engineer,123721,0 +81688,Female,52,High School,16,78,48,65,70,5.0,7,24,Urban,HR Executive,34200,0 +81689,Male,26,Masters,1,75,97,40,41,8.0,2,36,Urban,ML Engineer,122206,1 +81690,Female,59,Masters,7,93,26,89,39,3.0,5,9,Rural,Manager,25464,0 +81691,Female,39,Masters,8,76,16,57,61,6.0,1,51,Rural,Data Analyst,56347,0 +81692,Female,22,Bachelors,15,97,42,86,24,4.0,0,39,Semi-Urban,Manager,28791,1 +81693,Male,42,Masters,9,49,74,19,52,8.0,6,49,Urban,HR Executive,78081,0 +81694,Female,34,Masters,18,73,66,4,55,2.0,6,63,Rural,ML Engineer,43116,0 +81695,Female,22,High School,6,61,78,18,18,2.0,3,69,Rural,HR Executive,35508,0 +81696,Other,30,Diploma,10,35,22,82,70,4.0,7,9,Semi-Urban,Software Engineer,115952,0 +81697,Male,41,Bachelors,11,3,25,88,48,3.0,3,18,Semi-Urban,Data Analyst,35406,0 +81698,Female,25,Bachelors,0,79,33,93,8,1.0,4,37,Semi-Urban,Data Analyst,100977,1 +81699,Male,37,High School,5,36,20,80,44,6.0,0,38,Rural,Manager,57203,0 +81700,Female,35,Bachelors,4,96,99,5,58,4.0,0,97,Rural,ML Engineer,45104,1 +81701,Other,44,Bachelors,13,93,57,99,44,3.0,4,88,Urban,Manager,99339,1 +81702,Male,25,Bachelors,9,93,8,46,73,8.0,7,19,Urban,Manager,36128,0 +81703,Other,32,Bachelors,1,38,11,77,41,5.0,0,31,Urban,Software Engineer,133099,0 +81704,Female,22,Bachelors,5,63,25,7,52,4.0,7,48,Urban,Software Engineer,58006,0 +81705,Female,24,Diploma,14,94,47,58,11,2.0,0,33,Rural,Manager,123081,0 +81706,Male,30,Diploma,2,3,12,30,19,0.0,0,23,Semi-Urban,ML Engineer,109156,0 +81707,Male,59,Diploma,3,60,50,10,77,0.0,2,77,Semi-Urban,Manager,130346,0 +81708,Other,27,Bachelors,7,90,71,46,71,3.0,1,8,Urban,Software Engineer,59936,0 +81709,Male,36,Bachelors,5,29,54,13,98,3.0,7,23,Semi-Urban,ML Engineer,40165,0 +81710,Female,22,Bachelors,5,39,9,40,76,6.0,1,65,Semi-Urban,Software Engineer,100765,0 +81711,Male,53,High School,14,5,67,64,27,8.0,0,94,Semi-Urban,Data Analyst,147404,0 +81712,Female,47,Masters,13,8,58,52,51,1.0,2,60,Rural,ML Engineer,79185,0 +81713,Male,31,Bachelors,3,90,20,64,60,2.0,4,24,Semi-Urban,HR Executive,111348,0 +81714,Male,54,High School,4,12,16,25,56,6.0,5,90,Urban,Manager,146096,0 +81715,Female,46,Bachelors,1,68,42,45,58,5.0,6,0,Urban,Manager,127361,0 +81716,Male,26,Diploma,18,80,78,69,80,0.0,5,79,Semi-Urban,HR Executive,143156,1 +81717,Male,44,Bachelors,9,14,16,50,96,4.0,0,34,Semi-Urban,Software Engineer,53538,0 +81718,Female,41,Masters,6,13,40,78,22,7.0,7,54,Urban,ML Engineer,48638,0 +81719,Male,30,High School,4,48,50,92,12,5.0,7,85,Urban,Manager,131442,1 +81720,Male,48,Diploma,11,3,29,10,93,9.0,7,31,Urban,HR Executive,27969,0 +81721,Male,43,High School,10,27,76,71,66,9.0,6,7,Urban,HR Executive,61920,0 +81722,Other,55,Bachelors,1,74,27,85,16,5.0,7,5,Urban,Manager,144489,0 +81723,Female,30,Bachelors,4,32,79,39,37,0.0,6,14,Urban,ML Engineer,147326,0 +81724,Male,41,Bachelors,10,95,62,90,45,4.0,7,84,Urban,Manager,77602,1 +81725,Female,58,High School,8,7,36,50,61,8.0,4,67,Urban,ML Engineer,40427,0 +81726,Male,26,Masters,0,61,43,62,52,3.0,4,88,Urban,Software Engineer,75858,1 +81727,Male,40,Bachelors,5,22,28,33,31,1.0,5,89,Urban,Manager,95333,0 +81728,Female,45,Masters,7,20,56,88,99,6.0,6,10,Rural,HR Executive,66964,0 +81729,Male,25,Bachelors,4,11,71,93,61,1.0,0,46,Urban,Data Analyst,102434,0 +81730,Male,38,Bachelors,0,85,28,9,62,2.0,3,86,Rural,ML Engineer,87198,0 +81731,Male,26,High School,8,44,44,91,96,7.0,4,29,Urban,ML Engineer,36753,0 +81732,Other,40,High School,10,51,93,5,1,2.0,2,7,Urban,Data Analyst,114007,0 +81733,Female,45,Masters,11,90,55,19,12,0.0,1,80,Semi-Urban,HR Executive,79121,1 +81734,Male,30,Bachelors,4,43,85,10,98,7.0,4,96,Urban,HR Executive,123970,0 +81735,Male,27,Bachelors,4,94,87,18,85,7.0,1,13,Urban,HR Executive,132310,0 +81736,Male,22,Diploma,8,23,82,29,98,1.0,6,2,Urban,HR Executive,124340,0 +81737,Male,46,Bachelors,10,97,57,22,41,8.0,6,26,Semi-Urban,Software Engineer,132441,0 +81738,Female,31,Diploma,7,12,40,47,53,7.0,5,7,Rural,Manager,143478,0 +81739,Female,49,Bachelors,4,25,60,60,13,0.0,5,62,Urban,Software Engineer,48152,0 +81740,Other,59,Masters,14,66,18,53,92,5.0,6,73,Rural,HR Executive,135874,0 +81741,Male,43,Masters,13,84,92,39,4,4.0,6,69,Rural,Data Analyst,42584,1 +81742,Female,25,High School,18,54,72,70,9,7.0,6,80,Urban,Data Analyst,120293,1 +81743,Male,24,Bachelors,4,45,36,95,9,9.0,2,96,Semi-Urban,Data Analyst,27359,1 +81744,Male,55,Diploma,2,5,11,79,9,8.0,4,31,Urban,Manager,124708,0 +81745,Female,50,High School,10,6,98,69,65,9.0,4,70,Urban,Data Analyst,68680,1 +81746,Male,54,Diploma,11,85,90,68,2,8.0,7,73,Urban,Data Analyst,54837,1 +81747,Male,42,Diploma,3,46,80,51,13,8.0,6,83,Urban,Software Engineer,87426,1 +81748,Male,38,High School,14,65,23,6,68,5.0,1,67,Urban,ML Engineer,21238,0 +81749,Female,22,Bachelors,7,48,24,88,68,2.0,4,39,Urban,Manager,39998,0 +81750,Male,51,Bachelors,13,94,61,59,49,8.0,5,73,Urban,HR Executive,83985,1 +81751,Male,36,Bachelors,11,85,13,8,84,7.0,5,70,Semi-Urban,ML Engineer,136772,0 +81752,Female,51,Diploma,12,20,22,68,16,8.0,3,50,Semi-Urban,ML Engineer,106746,0 +81753,Female,27,Bachelors,16,28,88,54,66,0.0,4,97,Urban,Data Analyst,99686,1 +81754,Female,25,Masters,19,11,42,40,11,6.0,2,33,Urban,ML Engineer,98308,0 +81755,Male,43,High School,12,5,6,94,70,1.0,7,98,Rural,ML Engineer,60401,0 +81756,Male,45,High School,12,9,38,2,66,4.0,6,57,Urban,ML Engineer,122739,0 +81757,Female,38,Bachelors,16,19,57,55,4,1.0,6,10,Semi-Urban,Manager,134193,0 +81758,Male,32,Bachelors,10,30,19,40,84,8.0,1,70,Urban,HR Executive,94937,0 +81759,Male,42,Masters,18,67,75,68,91,0.0,4,75,Urban,Manager,138072,1 +81760,Male,44,Diploma,4,20,82,80,53,3.0,5,78,Rural,ML Engineer,117307,1 +81761,Male,57,Bachelors,19,98,9,60,85,9.0,6,46,Rural,Data Analyst,130151,0 +81762,Male,33,High School,19,27,33,24,77,6.0,1,73,Urban,Manager,80306,0 +81763,Female,40,Bachelors,6,12,12,27,0,6.0,7,49,Urban,Manager,33461,0 +81764,Male,27,Masters,3,42,98,98,99,7.0,6,22,Semi-Urban,Manager,106497,1 +81765,Male,48,Bachelors,13,74,7,92,90,7.0,7,84,Rural,Manager,132312,1 +81766,Male,58,Bachelors,18,52,83,74,95,7.0,0,84,Rural,Data Analyst,28135,1 +81767,Other,27,Bachelors,6,25,60,7,28,1.0,7,90,Semi-Urban,Data Analyst,110630,0 +81768,Male,33,High School,13,55,38,94,39,2.0,2,96,Semi-Urban,ML Engineer,126582,1 +81769,Male,36,Bachelors,10,58,92,82,45,5.0,3,22,Urban,Data Analyst,75798,1 +81770,Male,46,Masters,8,24,96,39,32,6.0,0,84,Urban,Manager,29192,1 +81771,Male,52,PhD,4,41,97,10,42,7.0,1,90,Urban,ML Engineer,70704,1 +81772,Male,27,Masters,15,35,29,14,43,7.0,6,88,Urban,Manager,108181,0 +81773,Female,57,Bachelors,17,69,22,71,54,0.0,4,20,Urban,Software Engineer,130367,0 +81774,Male,23,Bachelors,0,64,92,5,41,7.0,1,11,Urban,ML Engineer,97870,0 +81775,Female,33,PhD,8,75,67,50,58,5.0,7,0,Urban,Software Engineer,71127,0 +81776,Male,37,PhD,3,67,60,75,12,0.0,3,51,Rural,Software Engineer,69522,1 +81777,Female,46,Bachelors,9,19,63,48,75,9.0,6,94,Rural,Data Analyst,69989,0 +81778,Male,56,Masters,0,47,2,23,12,1.0,2,87,Rural,Data Analyst,61741,0 +81779,Female,23,Bachelors,13,99,91,12,92,5.0,7,82,Urban,Software Engineer,67186,1 +81780,Female,33,Bachelors,5,60,22,33,9,1.0,4,44,Urban,ML Engineer,45348,0 +81781,Other,33,High School,6,33,16,93,32,7.0,7,69,Urban,HR Executive,65684,0 +81782,Female,22,Bachelors,9,6,13,57,19,6.0,7,15,Urban,ML Engineer,70180,0 +81783,Female,47,Masters,3,91,68,71,39,7.0,7,88,Rural,ML Engineer,59442,1 +81784,Female,34,Diploma,7,2,30,30,87,6.0,1,59,Semi-Urban,Manager,97350,0 +81785,Other,56,Bachelors,7,35,51,69,3,8.0,0,13,Semi-Urban,Data Analyst,107313,0 +81786,Female,58,Diploma,1,65,49,97,56,4.0,1,47,Rural,Software Engineer,86819,1 +81787,Male,57,High School,6,61,52,98,24,6.0,3,44,Semi-Urban,Data Analyst,37261,1 +81788,Male,41,Bachelors,12,75,3,15,91,7.0,7,86,Urban,Data Analyst,47830,0 +81789,Male,47,Bachelors,7,73,19,98,59,5.0,4,41,Rural,Manager,132068,0 +81790,Male,58,Bachelors,16,93,43,86,9,1.0,1,88,Semi-Urban,ML Engineer,109506,1 +81791,Male,26,Bachelors,2,17,49,10,47,6.0,6,65,Semi-Urban,Software Engineer,147967,0 +81792,Male,53,Diploma,16,39,32,98,0,3.0,4,0,Rural,Manager,77574,0 +81793,Male,32,PhD,14,72,81,29,95,8.0,5,60,Semi-Urban,Data Analyst,32209,1 +81794,Male,50,Diploma,6,31,48,83,83,5.0,0,70,Urban,Manager,140268,0 +81795,Male,29,Masters,2,77,49,44,56,2.0,3,95,Urban,Manager,120990,1 +81796,Female,34,Diploma,3,71,87,38,83,9.0,0,57,Semi-Urban,Software Engineer,64126,1 +81797,Female,31,Bachelors,10,48,97,55,63,1.0,4,17,Urban,ML Engineer,130940,0 +81798,Other,30,Bachelors,4,45,73,86,43,3.0,5,62,Urban,Data Analyst,67306,1 +81799,Female,23,Masters,6,28,3,52,43,6.0,0,25,Semi-Urban,ML Engineer,125912,0 +81800,Female,40,Bachelors,18,91,89,53,10,2.0,2,40,Semi-Urban,Data Analyst,96642,1 +81801,Male,47,Bachelors,15,19,70,94,86,1.0,4,63,Urban,Software Engineer,136915,1 +81802,Male,54,Bachelors,10,34,19,96,77,1.0,5,14,Urban,Manager,98636,0 +81803,Male,23,Bachelors,4,31,17,77,26,8.0,7,92,Urban,Data Analyst,47596,0 +81804,Female,42,High School,2,24,42,10,16,2.0,1,83,Semi-Urban,HR Executive,74168,0 +81805,Male,38,Diploma,16,95,54,74,21,9.0,6,43,Semi-Urban,HR Executive,107887,1 +81806,Male,22,Bachelors,16,46,7,94,48,8.0,7,5,Urban,Software Engineer,112863,0 +81807,Male,29,Masters,19,52,38,88,36,7.0,4,5,Urban,Software Engineer,28137,0 +81808,Male,29,PhD,14,76,94,89,79,4.0,6,68,Semi-Urban,Software Engineer,123367,1 +81809,Male,41,High School,15,25,63,62,58,6.0,6,56,Rural,Software Engineer,50409,0 +81810,Female,41,Bachelors,13,1,70,2,43,0.0,6,6,Semi-Urban,Manager,141205,0 +81811,Female,59,Bachelors,2,1,63,52,15,8.0,7,47,Urban,ML Engineer,118089,0 +81812,Male,43,Masters,10,14,38,82,54,8.0,6,70,Semi-Urban,Data Analyst,49687,0 +81813,Male,29,High School,11,95,76,44,76,8.0,6,58,Urban,Data Analyst,118418,1 +81814,Male,38,Masters,5,77,13,35,59,5.0,5,78,Rural,Data Analyst,130046,0 +81815,Male,42,Masters,3,41,31,88,32,9.0,6,49,Rural,Manager,67533,0 +81816,Male,32,Masters,11,66,46,91,65,1.0,7,5,Rural,ML Engineer,53737,0 +81817,Female,58,Bachelors,13,74,63,91,61,3.0,5,20,Semi-Urban,HR Executive,33494,1 +81818,Female,28,Bachelors,8,82,10,33,68,0.0,1,96,Semi-Urban,Data Analyst,44449,0 +81819,Male,23,Bachelors,4,91,15,79,83,9.0,5,88,Urban,ML Engineer,35756,1 +81820,Female,42,Masters,15,42,98,33,31,5.0,1,41,Urban,ML Engineer,50112,0 +81821,Male,21,Bachelors,16,93,57,75,53,0.0,2,60,Urban,ML Engineer,46920,1 +81822,Other,59,Masters,14,4,17,75,77,3.0,2,69,Urban,Software Engineer,74479,0 +81823,Female,58,Masters,3,0,37,93,3,2.0,1,97,Urban,ML Engineer,31386,0 +81824,Male,53,Diploma,18,11,34,35,42,2.0,3,68,Semi-Urban,Data Analyst,91562,0 +81825,Female,54,Diploma,8,19,84,69,44,3.0,0,71,Semi-Urban,HR Executive,129825,1 +81826,Male,36,Diploma,7,35,98,35,78,2.0,0,13,Semi-Urban,HR Executive,125118,0 +81827,Female,53,High School,13,97,86,70,13,3.0,6,81,Rural,Manager,43970,1 +81828,Male,50,Bachelors,2,64,79,90,2,4.0,0,45,Urban,Software Engineer,114931,1 +81829,Male,51,High School,11,73,5,31,19,0.0,0,17,Urban,HR Executive,138687,0 +81830,Male,59,Bachelors,15,15,6,53,4,8.0,3,41,Urban,ML Engineer,66650,0 +81831,Male,36,Bachelors,7,90,93,63,93,1.0,5,82,Semi-Urban,ML Engineer,110246,1 +81832,Female,52,Masters,8,65,95,59,20,4.0,5,54,Urban,Software Engineer,78159,1 +81833,Female,25,Bachelors,8,21,49,28,64,3.0,4,59,Semi-Urban,Manager,55740,0 +81834,Male,58,Diploma,5,98,6,0,56,8.0,0,18,Semi-Urban,Manager,31603,0 +81835,Male,34,Bachelors,7,71,62,25,60,7.0,1,48,Urban,ML Engineer,20485,0 +81836,Male,52,PhD,7,80,51,22,15,0.0,4,14,Rural,Software Engineer,40381,0 +81837,Male,33,Bachelors,7,78,4,4,73,8.0,4,20,Urban,Data Analyst,104775,0 +81838,Male,29,Bachelors,17,39,44,23,27,9.0,7,60,Urban,ML Engineer,89044,0 +81839,Female,46,Bachelors,6,40,52,96,36,6.0,0,47,Rural,Data Analyst,30883,0 +81840,Female,24,PhD,12,20,96,69,98,2.0,2,16,Urban,HR Executive,148731,0 +81841,Male,38,Bachelors,2,38,41,83,94,5.0,6,13,Semi-Urban,Software Engineer,58531,0 +81842,Female,30,Bachelors,14,46,30,57,56,0.0,6,2,Rural,ML Engineer,112494,0 +81843,Female,50,Bachelors,8,79,15,54,75,6.0,6,87,Semi-Urban,Manager,62981,0 +81844,Male,59,Bachelors,9,67,11,96,52,2.0,2,6,Urban,HR Executive,108588,0 +81845,Male,23,Diploma,0,38,2,16,82,6.0,4,43,Urban,Data Analyst,104284,0 +81846,Male,31,Bachelors,13,3,97,95,1,1.0,5,54,Urban,ML Engineer,62872,1 +81847,Male,40,Bachelors,9,55,30,20,4,8.0,5,59,Urban,HR Executive,128289,0 +81848,Female,29,Bachelors,3,59,99,34,60,6.0,5,53,Urban,HR Executive,118524,1 +81849,Female,36,Bachelors,9,26,17,52,71,0.0,3,45,Rural,HR Executive,37922,0 +81850,Male,56,Bachelors,12,48,32,15,93,7.0,3,20,Urban,HR Executive,132302,0 +81851,Male,26,Masters,18,94,1,8,13,1.0,5,51,Urban,Manager,146199,0 +81852,Male,59,Diploma,11,80,28,30,60,9.0,7,60,Urban,HR Executive,75219,0 +81853,Male,54,Bachelors,12,76,27,87,38,1.0,0,22,Rural,Data Analyst,44260,0 +81854,Male,52,High School,8,71,80,24,83,2.0,2,31,Urban,ML Engineer,138960,0 +81855,Female,49,High School,6,61,60,11,70,9.0,0,41,Semi-Urban,ML Engineer,130706,0 +81856,Male,59,Bachelors,0,46,73,82,53,2.0,0,53,Urban,ML Engineer,80204,1 +81857,Female,55,Masters,3,87,61,7,88,1.0,4,94,Semi-Urban,Data Analyst,102615,1 +81858,Female,51,Masters,14,13,82,59,44,2.0,4,44,Urban,HR Executive,36328,0 +81859,Female,32,Bachelors,10,20,68,14,30,1.0,0,10,Urban,Data Analyst,68487,0 +81860,Female,35,Bachelors,4,89,49,95,81,0.0,2,35,Urban,Manager,134094,1 +81861,Male,31,Masters,14,95,44,43,50,7.0,2,22,Urban,HR Executive,95406,0 +81862,Female,58,Bachelors,12,46,93,82,32,9.0,7,19,Rural,Manager,120521,0 +81863,Male,56,Diploma,11,50,32,93,21,1.0,5,41,Semi-Urban,Data Analyst,105330,0 +81864,Other,46,Diploma,3,95,67,9,59,5.0,0,40,Urban,Manager,26116,0 +81865,Female,26,Masters,5,50,54,64,37,0.0,0,63,Urban,Data Analyst,115453,0 +81866,Other,32,Bachelors,14,92,46,60,68,4.0,5,77,Urban,ML Engineer,45373,1 +81867,Female,55,Masters,4,15,94,8,24,4.0,6,93,Urban,Data Analyst,26303,0 +81868,Male,59,Masters,14,64,95,91,29,7.0,1,78,Urban,Manager,74932,1 +81869,Female,47,Diploma,3,51,38,21,36,3.0,1,14,Urban,Manager,80875,0 +81870,Male,41,High School,1,46,54,58,95,8.0,6,74,Urban,Software Engineer,110724,0 +81871,Female,41,High School,11,52,51,72,49,2.0,2,94,Rural,Data Analyst,115162,1 +81872,Female,24,Bachelors,4,72,17,74,39,8.0,2,6,Semi-Urban,Data Analyst,135201,0 +81873,Male,42,Bachelors,10,37,25,57,29,4.0,0,95,Urban,ML Engineer,135775,0 +81874,Male,48,Diploma,16,39,25,2,44,7.0,2,41,Urban,HR Executive,77122,0 +81875,Female,52,Bachelors,11,39,3,91,72,9.0,7,5,Urban,Software Engineer,45356,0 +81876,Male,32,Masters,17,51,27,72,18,3.0,0,94,Urban,Data Analyst,125432,1 +81877,Male,40,Diploma,12,40,25,60,73,7.0,1,36,Rural,Data Analyst,141428,0 +81878,Male,47,Bachelors,11,41,21,2,32,7.0,1,57,Urban,Software Engineer,28166,0 +81879,Female,24,Bachelors,0,70,83,45,15,4.0,1,19,Urban,Software Engineer,51380,0 +81880,Female,27,Bachelors,0,21,72,88,69,7.0,6,59,Urban,ML Engineer,38167,0 +81881,Male,59,Masters,0,30,34,95,59,6.0,2,21,Semi-Urban,ML Engineer,126747,0 +81882,Male,24,Diploma,15,77,6,3,20,4.0,3,73,Semi-Urban,Manager,24615,0 +81883,Female,33,Bachelors,5,27,83,4,41,0.0,4,12,Semi-Urban,Software Engineer,40755,0 +81884,Male,58,Bachelors,19,83,4,19,0,0.0,6,15,Urban,ML Engineer,99329,0 +81885,Male,45,Masters,17,97,82,58,36,3.0,7,7,Urban,HR Executive,68169,1 +81886,Male,26,Masters,10,19,7,71,6,5.0,1,26,Urban,ML Engineer,70353,0 +81887,Other,21,Diploma,9,17,16,95,30,5.0,0,71,Rural,Manager,120321,0 +81888,Male,56,Masters,9,71,1,86,91,6.0,7,42,Semi-Urban,Software Engineer,39323,0 +81889,Female,49,Masters,17,72,46,89,36,1.0,2,41,Semi-Urban,ML Engineer,122330,1 +81890,Male,29,Diploma,9,47,11,75,63,0.0,5,70,Semi-Urban,HR Executive,59206,0 +81891,Female,35,Diploma,13,85,8,99,24,5.0,5,96,Semi-Urban,Software Engineer,85858,1 +81892,Male,26,High School,7,77,26,65,0,7.0,6,7,Semi-Urban,Software Engineer,97231,0 +81893,Male,28,High School,14,10,66,31,41,8.0,3,15,Semi-Urban,Software Engineer,46832,0 +81894,Female,36,Diploma,2,73,83,82,53,5.0,4,73,Urban,Software Engineer,59382,1 +81895,Female,53,PhD,9,16,13,14,82,3.0,1,5,Urban,Software Engineer,29497,0 +81896,Male,35,PhD,19,0,48,72,98,0.0,2,41,Urban,HR Executive,97045,0 +81897,Male,34,Diploma,9,17,17,91,42,7.0,5,19,Semi-Urban,HR Executive,73256,0 +81898,Male,34,Bachelors,13,33,2,40,69,5.0,0,31,Rural,Manager,53831,0 +81899,Male,35,Masters,13,14,50,17,66,3.0,2,50,Rural,Software Engineer,121917,0 +81900,Male,29,Masters,5,13,7,61,38,8.0,6,96,Urban,Manager,30069,0 +81901,Female,43,Bachelors,0,60,78,14,4,1.0,6,28,Urban,ML Engineer,108979,0 +81902,Male,34,Bachelors,5,94,25,83,58,3.0,4,94,Semi-Urban,ML Engineer,66279,1 +81903,Male,31,Bachelors,14,47,9,6,26,2.0,7,58,Urban,ML Engineer,148026,0 +81904,Female,58,Bachelors,19,33,94,44,72,7.0,3,85,Rural,ML Engineer,120623,1 +81905,Other,34,PhD,8,19,73,50,47,2.0,0,85,Urban,HR Executive,32637,0 +81906,Female,30,Bachelors,16,12,82,67,4,4.0,1,64,Semi-Urban,Manager,33158,0 +81907,Female,41,Bachelors,15,72,0,4,24,0.0,4,24,Urban,ML Engineer,76674,0 +81908,Male,38,High School,0,21,0,37,4,5.0,7,94,Semi-Urban,HR Executive,28070,0 +81909,Male,48,Masters,11,85,5,91,36,5.0,2,50,Semi-Urban,Software Engineer,24081,0 +81910,Female,29,Diploma,11,29,37,99,42,5.0,3,52,Urban,HR Executive,96081,0 +81911,Male,48,Diploma,7,86,47,12,54,8.0,4,98,Rural,Data Analyst,45560,1 +81912,Male,49,High School,9,82,7,16,29,4.0,5,70,Urban,HR Executive,25865,0 +81913,Other,31,Bachelors,1,21,47,1,14,4.0,6,84,Urban,Data Analyst,83049,0 +81914,Male,40,Bachelors,3,7,24,53,41,3.0,6,41,Semi-Urban,Software Engineer,138747,0 +81915,Female,30,High School,10,34,93,0,49,2.0,3,86,Semi-Urban,Software Engineer,65781,0 +81916,Male,23,Bachelors,12,68,89,65,36,7.0,3,95,Urban,Manager,40747,1 +81917,Male,48,Bachelors,3,49,69,51,7,2.0,4,64,Urban,Data Analyst,148564,0 +81918,Male,44,High School,2,1,8,36,51,1.0,6,17,Urban,ML Engineer,76687,0 +81919,Male,54,High School,1,53,48,14,31,7.0,4,61,Rural,ML Engineer,66098,0 +81920,Other,50,Diploma,15,47,79,5,65,9.0,5,54,Urban,HR Executive,45615,0 +81921,Male,31,Bachelors,7,67,35,97,83,2.0,3,65,Urban,Software Engineer,133808,1 +81922,Female,39,High School,17,87,33,62,11,4.0,4,72,Urban,ML Engineer,42142,1 +81923,Female,47,Masters,3,31,82,4,75,9.0,1,1,Urban,HR Executive,144701,0 +81924,Female,58,Diploma,13,32,17,33,16,9.0,1,78,Urban,Manager,39108,0 +81925,Female,23,Diploma,7,11,64,15,27,5.0,3,51,Semi-Urban,ML Engineer,20412,0 +81926,Male,36,Diploma,15,95,17,5,58,5.0,4,68,Rural,Software Engineer,22835,0 +81927,Female,30,Masters,11,4,38,18,96,6.0,0,33,Urban,Software Engineer,86978,0 +81928,Female,30,High School,15,58,82,80,83,2.0,4,69,Urban,Software Engineer,59338,1 +81929,Female,22,Bachelors,2,64,56,42,8,0.0,2,22,Semi-Urban,Manager,138764,0 +81930,Male,26,Bachelors,6,94,52,61,98,6.0,7,1,Urban,Manager,26346,0 +81931,Male,40,Bachelors,11,56,98,45,88,6.0,4,85,Semi-Urban,Data Analyst,128571,1 +81932,Female,53,High School,7,52,34,66,87,7.0,2,90,Rural,Manager,26335,1 +81933,Male,55,Bachelors,2,25,42,22,54,5.0,7,26,Urban,HR Executive,82957,0 +81934,Male,54,Diploma,1,4,29,23,63,2.0,7,30,Rural,Manager,102937,0 +81935,Male,39,Bachelors,10,94,72,7,55,6.0,2,56,Urban,Software Engineer,146007,0 +81936,Male,38,High School,14,70,68,92,25,8.0,6,71,Rural,HR Executive,48911,1 +81937,Male,21,Masters,5,75,6,67,36,6.0,2,71,Urban,Software Engineer,95684,0 +81938,Male,28,Bachelors,1,29,97,64,84,3.0,2,75,Rural,ML Engineer,95854,1 +81939,Male,33,Diploma,16,60,65,67,30,5.0,0,20,Semi-Urban,Manager,89198,0 +81940,Male,59,Masters,15,80,88,20,82,9.0,3,89,Urban,ML Engineer,120169,1 +81941,Male,53,Masters,17,4,45,55,41,0.0,6,6,Semi-Urban,Data Analyst,108413,0 +81942,Male,29,Bachelors,17,2,52,97,48,7.0,4,82,Urban,HR Executive,27769,0 +81943,Female,45,Masters,0,64,80,72,2,4.0,0,72,Rural,Software Engineer,78390,1 +81944,Male,49,Bachelors,6,24,8,51,39,4.0,3,73,Urban,Manager,102881,0 +81945,Male,59,Diploma,5,79,94,21,0,1.0,2,23,Urban,ML Engineer,20467,0 +81946,Male,42,High School,6,79,75,83,11,4.0,2,63,Semi-Urban,Data Analyst,114016,1 +81947,Female,55,High School,5,68,5,84,36,9.0,0,6,Urban,Manager,137944,0 +81948,Male,33,Diploma,0,4,53,22,9,4.0,6,52,Urban,Software Engineer,125775,0 +81949,Male,57,Bachelors,12,77,73,73,40,8.0,7,11,Semi-Urban,HR Executive,30288,0 +81950,Male,40,Diploma,19,70,24,30,57,1.0,7,53,Semi-Urban,HR Executive,135126,0 +81951,Male,37,Bachelors,7,2,10,23,0,6.0,3,66,Urban,Software Engineer,62144,0 +81952,Other,24,Masters,17,40,60,86,7,1.0,3,54,Urban,Manager,21558,0 +81953,Female,26,Bachelors,13,47,38,70,42,3.0,6,36,Urban,Software Engineer,86112,0 +81954,Female,42,High School,10,14,83,32,65,4.0,7,19,Urban,HR Executive,70102,0 +81955,Male,50,Bachelors,7,95,33,43,78,4.0,0,88,Semi-Urban,Data Analyst,99611,1 +81956,Male,39,Bachelors,9,57,97,88,5,7.0,4,82,Semi-Urban,HR Executive,136883,1 +81957,Female,34,Diploma,8,77,50,27,66,5.0,2,53,Urban,Manager,89909,0 +81958,Male,46,Bachelors,6,93,24,34,0,2.0,2,22,Urban,ML Engineer,49847,0 +81959,Male,32,Bachelors,12,8,67,1,81,7.0,1,97,Rural,ML Engineer,116527,0 +81960,Male,21,Masters,16,95,62,40,61,6.0,2,24,Urban,ML Engineer,85392,0 +81961,Male,34,Diploma,17,68,70,84,98,6.0,3,43,Rural,Software Engineer,133787,1 +81962,Male,38,Bachelors,13,36,1,27,29,7.0,1,32,Semi-Urban,HR Executive,130851,0 +81963,Female,50,PhD,11,87,63,66,16,3.0,3,46,Rural,Data Analyst,93724,1 +81964,Male,22,High School,14,62,96,87,25,4.0,7,87,Urban,HR Executive,44348,1 +81965,Female,41,Masters,16,24,95,67,8,1.0,0,19,Rural,HR Executive,54901,0 +81966,Male,55,Bachelors,14,45,31,76,61,5.0,6,56,Semi-Urban,Data Analyst,55957,0 +81967,Male,54,Bachelors,0,85,81,29,21,6.0,3,48,Semi-Urban,Manager,110593,1 +81968,Female,45,High School,2,6,0,20,2,4.0,2,41,Semi-Urban,ML Engineer,33617,0 +81969,Male,21,Masters,0,29,55,73,95,3.0,4,45,Urban,HR Executive,61567,0 +81970,Male,23,High School,9,91,28,27,85,8.0,2,77,Urban,ML Engineer,122331,0 +81971,Male,22,Diploma,12,69,65,74,30,9.0,2,27,Urban,ML Engineer,40010,1 +81972,Male,35,PhD,15,53,31,47,49,8.0,1,18,Rural,Manager,37863,0 +81973,Female,56,Bachelors,16,50,37,75,58,1.0,6,21,Urban,Manager,121030,0 +81974,Male,54,Diploma,12,16,73,80,90,6.0,2,80,Urban,Data Analyst,24664,1 +81975,Male,58,Diploma,17,79,25,75,34,2.0,3,72,Semi-Urban,Manager,20568,1 +81976,Male,40,Masters,7,56,8,72,60,6.0,7,45,Urban,Manager,25649,0 +81977,Male,23,Masters,9,23,73,2,8,9.0,0,6,Semi-Urban,HR Executive,42104,0 +81978,Female,57,High School,5,43,37,1,54,0.0,3,98,Urban,ML Engineer,98379,0 +81979,Female,40,PhD,11,14,20,48,88,8.0,2,56,Urban,Software Engineer,141894,0 +81980,Female,46,Masters,3,87,30,76,81,8.0,5,13,Urban,ML Engineer,58345,0 +81981,Male,45,Bachelors,16,39,36,28,39,3.0,7,91,Urban,ML Engineer,139404,0 +81982,Other,47,Bachelors,3,83,90,37,55,3.0,6,81,Rural,Data Analyst,98928,1 +81983,Female,33,Bachelors,2,87,10,93,64,4.0,3,22,Urban,Software Engineer,58827,0 +81984,Female,57,Bachelors,8,18,71,83,26,1.0,0,58,Urban,Data Analyst,108530,0 +81985,Female,29,Masters,0,75,96,66,7,9.0,4,4,Semi-Urban,Data Analyst,20176,1 +81986,Female,30,Bachelors,19,5,76,84,7,9.0,6,80,Urban,HR Executive,38183,1 +81987,Female,58,Masters,2,55,55,6,18,0.0,4,77,Urban,Data Analyst,83353,0 +81988,Male,22,Bachelors,6,46,20,44,70,6.0,6,12,Rural,Software Engineer,80360,0 +81989,Male,59,Bachelors,15,6,12,10,21,7.0,2,44,Urban,Data Analyst,42928,0 +81990,Female,44,Masters,18,37,64,15,31,5.0,0,78,Rural,HR Executive,25072,0 +81991,Male,25,Diploma,19,44,87,24,35,2.0,7,51,Urban,HR Executive,130906,0 +81992,Male,30,Masters,2,46,15,30,26,9.0,4,2,Urban,Data Analyst,130831,0 +81993,Male,45,Bachelors,13,45,49,0,3,2.0,4,87,Semi-Urban,Software Engineer,100777,0 +81994,Male,33,Bachelors,18,62,69,58,18,3.0,4,6,Semi-Urban,Manager,136561,0 +81995,Male,29,PhD,12,87,71,63,90,4.0,6,41,Urban,Manager,53264,1 +81996,Female,35,Masters,7,56,90,38,0,0.0,2,32,Semi-Urban,Manager,104431,0 +81997,Female,59,Bachelors,7,27,29,10,57,1.0,4,92,Urban,ML Engineer,101025,0 +81998,Male,33,Bachelors,13,96,26,19,32,3.0,1,1,Semi-Urban,Data Analyst,33978,0 +81999,Male,46,Diploma,0,60,68,16,14,8.0,0,44,Rural,Software Engineer,71922,0 +82000,Male,59,Bachelors,7,28,74,35,29,8.0,3,57,Urban,Data Analyst,74891,0 +82001,Male,45,Bachelors,12,16,6,61,73,9.0,5,34,Urban,Data Analyst,43900,0 +82002,Female,27,Masters,3,95,18,26,7,7.0,4,5,Semi-Urban,HR Executive,93201,0 +82003,Female,53,Bachelors,8,61,16,13,40,8.0,2,40,Urban,Data Analyst,136664,0 +82004,Male,37,Diploma,5,29,31,66,43,4.0,4,4,Urban,ML Engineer,65526,0 +82005,Male,30,Bachelors,14,52,12,27,83,2.0,7,29,Urban,ML Engineer,135361,0 +82006,Female,57,Bachelors,12,41,82,71,92,5.0,5,58,Urban,Data Analyst,93742,1 +82007,Male,39,High School,0,86,2,52,86,3.0,0,40,Rural,Software Engineer,91418,0 +82008,Male,21,PhD,4,15,95,34,22,7.0,1,27,Urban,Data Analyst,84455,0 +82009,Female,59,Diploma,10,30,66,97,32,2.0,5,23,Urban,ML Engineer,49354,0 +82010,Female,22,Bachelors,9,91,3,35,31,7.0,5,92,Semi-Urban,ML Engineer,40198,0 +82011,Male,23,Masters,12,45,49,41,6,7.0,0,66,Urban,Manager,36985,0 +82012,Male,44,Masters,6,74,33,41,51,8.0,6,26,Semi-Urban,Manager,142841,0 +82013,Male,24,Bachelors,4,21,45,69,33,3.0,0,26,Rural,Software Engineer,37765,0 +82014,Female,25,Bachelors,7,91,38,85,4,0.0,2,75,Rural,Software Engineer,143687,1 +82015,Male,57,Masters,16,92,93,48,6,9.0,0,50,Semi-Urban,Manager,87451,1 +82016,Male,55,Masters,6,38,75,73,15,8.0,7,88,Rural,Software Engineer,85022,1 +82017,Female,59,Bachelors,7,62,21,89,64,6.0,5,36,Urban,Data Analyst,67555,0 +82018,Female,32,Bachelors,19,58,64,66,21,0.0,7,78,Urban,Manager,61865,1 +82019,Male,52,Diploma,13,3,63,80,95,6.0,7,90,Urban,ML Engineer,85769,1 +82020,Female,31,High School,15,74,51,29,71,6.0,0,0,Urban,Data Analyst,145766,0 +82021,Other,31,High School,11,89,60,30,33,4.0,0,2,Urban,ML Engineer,54940,0 +82022,Male,27,Bachelors,3,35,92,71,30,5.0,1,24,Rural,Data Analyst,129690,0 +82023,Female,29,Masters,7,44,45,38,19,3.0,7,99,Semi-Urban,Software Engineer,116750,0 +82024,Male,57,Bachelors,5,4,41,6,64,6.0,2,4,Urban,Manager,70172,0 +82025,Male,29,PhD,16,98,70,54,98,7.0,6,73,Urban,ML Engineer,121803,1 +82026,Male,42,PhD,16,19,47,50,88,7.0,5,73,Urban,HR Executive,142057,0 +82027,Female,25,Masters,6,22,10,59,36,6.0,6,10,Semi-Urban,ML Engineer,70440,0 +82028,Male,28,Bachelors,9,77,60,87,18,7.0,1,42,Urban,HR Executive,103200,1 +82029,Male,28,Bachelors,6,60,51,24,4,4.0,2,45,Rural,Data Analyst,126990,0 +82030,Other,43,Diploma,3,77,56,90,26,0.0,1,10,Urban,HR Executive,46206,0 +82031,Female,52,PhD,9,8,75,55,34,5.0,0,80,Urban,Manager,22494,0 +82032,Male,45,Bachelors,15,97,76,90,96,7.0,7,90,Urban,Data Analyst,91486,1 +82033,Female,40,High School,8,25,87,76,95,2.0,4,48,Rural,ML Engineer,136896,0 +82034,Male,34,Bachelors,17,57,47,10,38,7.0,6,12,Urban,Software Engineer,97404,0 +82035,Male,28,Bachelors,1,57,67,82,46,9.0,4,83,Rural,Software Engineer,121501,1 +82036,Male,50,Masters,14,94,85,48,31,7.0,2,55,Urban,Software Engineer,76102,1 +82037,Male,31,Masters,15,9,70,36,62,9.0,3,15,Semi-Urban,Data Analyst,91333,0 +82038,Female,40,Masters,1,33,19,80,34,5.0,6,65,Urban,HR Executive,82018,0 +82039,Male,23,Diploma,11,6,76,80,42,7.0,1,19,Semi-Urban,HR Executive,54081,0 +82040,Male,23,Bachelors,5,15,38,56,81,1.0,2,70,Semi-Urban,Manager,65465,0 +82041,Female,55,Diploma,11,71,88,97,88,5.0,6,50,Urban,HR Executive,82597,1 +82042,Female,41,Bachelors,14,1,14,76,12,8.0,5,95,Semi-Urban,ML Engineer,140827,0 +82043,Male,29,Masters,17,86,57,52,53,4.0,1,77,Semi-Urban,Data Analyst,128347,1 +82044,Female,28,Bachelors,18,16,95,13,11,6.0,3,85,Rural,Manager,45925,0 +82045,Male,55,Bachelors,4,60,94,41,58,0.0,3,21,Urban,HR Executive,52885,0 +82046,Male,22,Diploma,5,60,30,99,94,0.0,5,87,Urban,ML Engineer,131423,1 +82047,Male,27,Masters,1,58,34,29,86,6.0,6,86,Urban,HR Executive,116824,0 +82048,Male,37,Diploma,5,43,81,48,20,6.0,3,74,Rural,HR Executive,90235,1 +82049,Female,32,PhD,2,90,13,58,62,8.0,4,82,Semi-Urban,Software Engineer,41374,1 +82050,Female,22,PhD,8,14,52,80,99,9.0,2,45,Urban,Software Engineer,149070,0 +82051,Female,57,Diploma,16,53,31,36,81,4.0,2,2,Urban,Manager,133690,0 +82052,Male,39,Bachelors,4,30,72,81,68,8.0,4,65,Urban,HR Executive,117186,1 +82053,Male,58,Diploma,12,94,30,58,11,3.0,0,84,Urban,HR Executive,29725,1 +82054,Female,46,Bachelors,13,33,69,49,32,6.0,4,17,Urban,HR Executive,111327,0 +82055,Male,50,Bachelors,17,6,50,90,62,7.0,4,1,Rural,Software Engineer,125640,0 +82056,Male,59,High School,3,27,89,57,96,1.0,5,52,Semi-Urban,Data Analyst,33273,0 +82057,Male,29,Diploma,13,31,38,7,51,4.0,2,6,Urban,Data Analyst,30820,0 +82058,Male,38,Bachelors,12,58,89,48,44,0.0,6,37,Urban,ML Engineer,26635,0 +82059,Male,58,Diploma,12,91,0,31,29,1.0,0,73,Urban,Data Analyst,97587,0 +82060,Male,27,Bachelors,16,17,88,78,8,5.0,0,10,Urban,ML Engineer,64584,0 +82061,Male,34,Bachelors,9,13,29,34,35,3.0,5,80,Urban,Data Analyst,140616,0 +82062,Male,26,High School,1,42,65,90,53,3.0,1,36,Urban,ML Engineer,79858,0 +82063,Male,52,High School,6,4,89,92,88,0.0,7,4,Urban,ML Engineer,28517,0 +82064,Male,43,PhD,15,37,0,74,42,0.0,3,87,Urban,Software Engineer,62922,0 +82065,Male,39,Masters,5,51,97,63,46,2.0,5,13,Urban,HR Executive,33568,0 +82066,Male,27,Bachelors,11,8,63,25,88,6.0,4,0,Semi-Urban,Data Analyst,83048,0 +82067,Female,32,Masters,8,19,42,10,78,4.0,4,17,Rural,Data Analyst,85800,0 +82068,Male,49,Bachelors,19,60,20,30,68,1.0,5,53,Semi-Urban,Software Engineer,107318,0 +82069,Female,36,Bachelors,2,87,79,86,11,3.0,2,46,Rural,HR Executive,53015,1 +82070,Female,50,Masters,17,87,55,31,46,1.0,7,49,Rural,HR Executive,27208,0 +82071,Female,44,High School,0,34,16,44,65,1.0,3,87,Urban,Software Engineer,103020,0 +82072,Female,31,Bachelors,4,48,71,77,85,2.0,4,48,Rural,Data Analyst,63913,1 +82073,Female,36,Bachelors,19,85,63,54,74,0.0,6,2,Urban,ML Engineer,98676,0 +82074,Female,50,Bachelors,10,93,95,23,54,3.0,0,91,Semi-Urban,Data Analyst,111764,1 +82075,Female,58,Bachelors,5,50,66,80,7,2.0,6,74,Urban,ML Engineer,73024,1 +82076,Male,36,Diploma,9,81,40,2,72,6.0,4,15,Semi-Urban,HR Executive,90258,0 +82077,Female,53,Bachelors,13,12,4,54,84,4.0,5,23,Urban,HR Executive,65638,0 +82078,Female,37,PhD,0,60,39,3,0,0.0,1,27,Urban,HR Executive,26843,0 +82079,Male,38,Bachelors,10,17,82,37,29,1.0,5,89,Urban,Manager,49503,0 +82080,Female,44,Masters,4,97,90,7,34,5.0,0,67,Rural,HR Executive,56898,1 +82081,Female,51,Bachelors,15,48,43,43,12,4.0,1,28,Urban,Software Engineer,126528,0 +82082,Male,23,Diploma,1,25,34,67,31,3.0,7,72,Urban,Manager,55067,0 +82083,Male,46,Bachelors,4,32,41,89,79,5.0,7,67,Urban,Manager,66909,0 +82084,Male,24,Bachelors,19,66,59,60,70,1.0,2,57,Urban,HR Executive,59222,1 +82085,Female,21,Diploma,17,66,65,31,23,4.0,7,73,Semi-Urban,Software Engineer,114522,0 +82086,Male,23,Diploma,15,47,16,96,97,2.0,1,84,Semi-Urban,Data Analyst,131392,1 +82087,Female,33,Masters,6,14,56,1,85,7.0,3,39,Urban,Manager,97236,0 +82088,Male,34,Masters,16,90,45,23,87,7.0,4,99,Urban,Software Engineer,23015,1 +82089,Male,40,Masters,19,19,79,89,58,8.0,6,99,Rural,Data Analyst,82132,1 +82090,Female,38,High School,5,29,10,41,13,7.0,3,15,Rural,HR Executive,130325,0 +82091,Male,49,Diploma,6,89,77,7,24,1.0,4,47,Urban,HR Executive,31300,0 +82092,Female,38,Bachelors,4,67,89,61,21,3.0,1,61,Urban,ML Engineer,94905,1 +82093,Other,25,High School,18,97,29,80,67,1.0,0,30,Urban,Data Analyst,140199,0 +82094,Male,57,Masters,1,71,70,32,67,7.0,5,71,Semi-Urban,Data Analyst,96438,1 +82095,Female,23,Bachelors,19,55,99,93,77,0.0,3,27,Urban,Manager,98108,1 +82096,Male,44,Bachelors,18,68,0,22,15,5.0,0,15,Rural,Data Analyst,121938,0 +82097,Male,51,Bachelors,1,50,27,21,91,4.0,4,24,Rural,HR Executive,121897,0 +82098,Male,39,Bachelors,5,83,90,64,2,1.0,4,45,Rural,Manager,106180,1 +82099,Female,28,Bachelors,2,52,42,52,67,2.0,7,19,Urban,HR Executive,111874,0 +82100,Female,32,Masters,15,31,22,74,62,6.0,1,62,Urban,Manager,98837,0 +82101,Male,41,High School,6,28,14,63,63,3.0,4,21,Semi-Urban,HR Executive,43690,0 +82102,Male,53,High School,11,48,17,80,58,3.0,0,53,Semi-Urban,HR Executive,146719,0 +82103,Female,52,Masters,6,60,18,1,23,1.0,5,71,Semi-Urban,Software Engineer,122324,0 +82104,Male,58,Diploma,17,18,28,45,43,4.0,1,79,Rural,Data Analyst,108806,0 +82105,Male,52,Bachelors,1,52,22,34,44,2.0,4,49,Rural,Software Engineer,58673,0 +82106,Female,56,Diploma,12,28,50,87,42,6.0,4,2,Urban,Data Analyst,130555,0 +82107,Male,51,Bachelors,9,3,47,50,71,0.0,7,77,Semi-Urban,Software Engineer,69105,0 +82108,Male,56,Diploma,6,20,59,92,21,9.0,6,88,Semi-Urban,Manager,140488,1 +82109,Female,50,Bachelors,18,74,2,99,29,8.0,4,18,Urban,HR Executive,51146,0 +82110,Male,53,Bachelors,4,50,98,23,80,8.0,4,66,Urban,Manager,135894,1 +82111,Female,47,Bachelors,18,51,18,82,85,5.0,7,30,Semi-Urban,HR Executive,137977,0 +82112,Male,53,High School,17,7,6,32,25,0.0,3,92,Urban,HR Executive,99608,0 +82113,Male,25,Masters,15,9,37,55,3,4.0,6,50,Urban,Manager,129097,0 +82114,Female,28,Bachelors,14,20,7,29,51,2.0,6,19,Semi-Urban,Software Engineer,118855,0 +82115,Male,24,Masters,8,31,58,18,91,6.0,7,55,Rural,HR Executive,107622,0 +82116,Female,54,Masters,16,37,42,53,97,0.0,6,13,Urban,Manager,103087,0 +82117,Female,35,Bachelors,18,73,6,4,25,4.0,1,58,Semi-Urban,Software Engineer,118369,0 +82118,Female,38,Bachelors,4,94,63,7,58,0.0,0,54,Urban,Software Engineer,64190,0 +82119,Female,33,Bachelors,8,93,75,89,59,6.0,2,81,Urban,ML Engineer,145608,1 +82120,Other,33,PhD,6,44,93,73,0,1.0,4,14,Urban,Software Engineer,90930,0 +82121,Male,41,Diploma,2,94,57,67,83,7.0,5,75,Rural,ML Engineer,52886,1 +82122,Male,39,Bachelors,18,71,28,25,81,4.0,6,17,Urban,Data Analyst,135696,0 +82123,Female,53,Masters,11,95,42,68,40,9.0,7,59,Urban,Manager,129478,1 +82124,Female,24,Diploma,15,49,38,86,34,4.0,5,93,Semi-Urban,ML Engineer,83368,1 +82125,Male,42,Bachelors,13,56,15,17,23,4.0,1,10,Semi-Urban,Data Analyst,136364,0 +82126,Male,21,Bachelors,5,7,11,59,40,8.0,1,29,Urban,Software Engineer,120383,0 +82127,Other,28,Bachelors,5,53,6,75,4,2.0,3,92,Urban,HR Executive,145701,0 +82128,Female,21,Masters,1,75,58,81,55,5.0,3,48,Urban,ML Engineer,32161,1 +82129,Male,37,Masters,16,65,92,93,85,6.0,7,4,Urban,ML Engineer,93036,1 +82130,Male,26,Diploma,5,19,89,73,97,7.0,4,63,Urban,HR Executive,132995,1 +82131,Male,44,Masters,15,54,74,32,87,1.0,4,60,Urban,HR Executive,98948,0 +82132,Male,48,Masters,9,47,7,64,79,2.0,6,95,Urban,Software Engineer,146089,0 +82133,Male,38,Diploma,18,6,31,68,97,0.0,7,82,Rural,ML Engineer,98392,0 +82134,Male,25,Diploma,15,57,74,74,79,7.0,1,87,Semi-Urban,Software Engineer,33333,1 +82135,Male,53,Masters,6,4,87,78,15,2.0,6,39,Rural,Manager,120863,0 +82136,Male,42,High School,2,4,52,86,99,4.0,0,47,Semi-Urban,Software Engineer,25380,0 +82137,Female,24,Bachelors,14,84,80,4,98,4.0,7,69,Semi-Urban,HR Executive,20574,0 +82138,Female,37,Diploma,0,63,5,97,75,4.0,6,72,Rural,Software Engineer,130626,0 +82139,Male,34,High School,1,58,96,90,94,6.0,4,88,Urban,HR Executive,146588,1 +82140,Male,30,Masters,10,59,34,12,11,9.0,6,68,Urban,ML Engineer,30980,0 +82141,Other,52,Diploma,2,43,7,18,85,0.0,1,48,Rural,Manager,78174,0 +82142,Male,41,Diploma,11,50,73,70,96,7.0,2,7,Rural,ML Engineer,28670,0 +82143,Male,41,Bachelors,18,16,64,38,49,5.0,6,56,Semi-Urban,ML Engineer,103708,0 +82144,Male,36,PhD,0,15,58,6,63,3.0,5,10,Urban,Data Analyst,121153,0 +82145,Male,30,Bachelors,17,29,94,30,23,6.0,3,26,Semi-Urban,Software Engineer,125208,0 +82146,Female,41,High School,1,33,82,61,13,8.0,0,89,Urban,HR Executive,92287,1 +82147,Male,48,Masters,8,57,7,48,66,5.0,7,63,Semi-Urban,Software Engineer,40077,0 +82148,Other,41,Bachelors,13,36,80,97,71,8.0,6,89,Urban,ML Engineer,114732,1 +82149,Other,32,Bachelors,8,86,25,24,80,8.0,7,71,Urban,ML Engineer,83184,0 +82150,Male,53,High School,3,21,74,77,40,7.0,7,15,Rural,Data Analyst,106546,0 +82151,Other,37,Bachelors,18,28,81,98,72,0.0,3,81,Rural,Manager,69819,1 +82152,Other,56,Bachelors,15,65,86,84,80,8.0,2,74,Urban,ML Engineer,42143,1 +82153,Female,58,High School,2,25,62,47,39,0.0,1,13,Urban,ML Engineer,40401,0 +82154,Male,48,Bachelors,15,50,10,22,90,4.0,7,53,Semi-Urban,Data Analyst,26712,0 +82155,Male,56,Bachelors,7,6,0,99,89,4.0,3,54,Semi-Urban,Data Analyst,77764,0 +82156,Male,40,Bachelors,4,10,19,25,26,4.0,0,39,Urban,ML Engineer,106489,0 +82157,Male,39,Bachelors,16,76,2,11,2,5.0,3,90,Rural,HR Executive,143631,0 +82158,Female,24,Bachelors,3,19,34,70,74,0.0,7,85,Urban,Data Analyst,29108,0 +82159,Female,50,Bachelors,9,65,44,93,73,1.0,6,24,Urban,Data Analyst,33423,0 +82160,Female,29,High School,0,96,84,89,66,2.0,6,27,Rural,Data Analyst,109546,1 +82161,Female,43,Bachelors,11,85,3,83,37,9.0,3,54,Rural,Software Engineer,92014,0 +82162,Male,48,High School,14,34,4,96,44,9.0,7,64,Urban,Manager,24497,0 +82163,Female,35,Masters,14,8,62,34,37,6.0,3,15,Rural,ML Engineer,81675,0 +82164,Female,34,Bachelors,4,7,69,42,87,9.0,7,3,Semi-Urban,HR Executive,20749,0 +82165,Male,42,Bachelors,3,66,49,30,83,7.0,0,5,Rural,Software Engineer,103579,0 +82166,Female,43,Masters,19,46,64,84,26,3.0,5,20,Urban,ML Engineer,20060,0 +82167,Male,47,Masters,9,53,58,63,40,5.0,0,6,Urban,ML Engineer,59391,0 +82168,Male,41,High School,2,92,50,35,90,4.0,5,3,Urban,HR Executive,29700,0 +82169,Male,24,Masters,11,67,25,94,69,8.0,2,51,Urban,HR Executive,117324,1 +82170,Male,52,Masters,7,82,24,45,74,4.0,5,46,Semi-Urban,Manager,140823,0 +82171,Female,31,Masters,18,74,57,98,93,5.0,4,1,Urban,HR Executive,30113,0 +82172,Male,31,Bachelors,0,87,27,54,28,0.0,1,23,Semi-Urban,ML Engineer,118117,0 +82173,Male,53,High School,18,33,46,4,53,5.0,3,52,Urban,Software Engineer,108209,0 +82174,Other,34,Bachelors,10,47,89,48,81,4.0,6,85,Rural,Data Analyst,98543,1 +82175,Female,22,Diploma,19,23,61,41,85,1.0,5,74,Urban,Manager,35838,0 +82176,Female,50,Diploma,2,68,30,62,56,9.0,3,6,Rural,HR Executive,56404,0 +82177,Female,21,High School,4,95,35,87,46,3.0,3,36,Urban,ML Engineer,98595,1 +82178,Male,57,Diploma,8,70,52,34,69,7.0,3,28,Rural,Manager,92684,0 +82179,Female,56,Bachelors,15,99,84,11,67,0.0,4,85,Urban,Manager,64506,1 +82180,Other,29,Masters,11,3,21,52,33,0.0,2,10,Urban,HR Executive,45105,0 +82181,Male,53,Bachelors,2,52,63,82,32,7.0,4,33,Semi-Urban,Software Engineer,24949,0 +82182,Male,22,Diploma,11,64,46,35,47,6.0,2,62,Urban,HR Executive,55074,0 +82183,Other,25,Diploma,14,60,80,98,73,7.0,3,8,Urban,Software Engineer,84967,1 +82184,Male,34,Diploma,6,57,22,82,46,7.0,5,35,Semi-Urban,HR Executive,34035,0 +82185,Female,35,Masters,16,46,12,10,82,6.0,5,22,Urban,Manager,88452,0 +82186,Male,26,Bachelors,1,25,77,92,77,1.0,3,31,Urban,Data Analyst,144794,0 +82187,Female,58,Diploma,13,71,2,1,5,5.0,6,59,Semi-Urban,Manager,145162,0 +82188,Female,34,Diploma,4,40,80,23,58,8.0,5,62,Rural,HR Executive,113830,0 +82189,Female,36,Bachelors,7,36,38,68,46,1.0,2,0,Urban,Manager,90397,0 +82190,Female,23,PhD,3,83,71,53,54,5.0,1,45,Urban,Manager,21129,1 +82191,Male,24,Diploma,3,3,52,66,58,4.0,2,25,Urban,Data Analyst,128727,0 +82192,Male,52,High School,12,57,58,45,96,6.0,1,21,Rural,Software Engineer,24566,0 +82193,Male,49,High School,9,88,39,43,32,7.0,5,80,Urban,ML Engineer,148181,1 +82194,Male,55,Bachelors,0,78,73,56,0,1.0,5,52,Urban,Software Engineer,137598,1 +82195,Male,42,Diploma,14,96,22,26,47,4.0,3,45,Urban,HR Executive,85347,0 +82196,Male,53,Bachelors,1,26,19,42,61,3.0,2,5,Rural,HR Executive,38277,0 +82197,Female,47,Bachelors,5,53,1,22,17,6.0,5,12,Urban,Manager,65258,0 +82198,Male,36,Bachelors,15,23,78,63,54,9.0,3,87,Urban,Manager,47834,1 +82199,Female,50,Masters,13,81,64,77,14,4.0,6,73,Urban,HR Executive,129767,1 +82200,Male,25,Masters,6,79,82,0,5,9.0,3,82,Urban,Manager,22210,1 +82201,Male,25,Bachelors,12,23,93,98,33,6.0,1,10,Rural,Data Analyst,60062,0 +82202,Female,42,Diploma,8,26,42,99,31,3.0,3,25,Semi-Urban,Data Analyst,61801,0 +82203,Female,51,High School,12,14,41,82,32,9.0,4,89,Urban,Data Analyst,20001,0 +82204,Male,42,High School,3,58,56,94,61,7.0,0,95,Rural,ML Engineer,133832,1 +82205,Male,46,Bachelors,5,2,21,80,95,1.0,5,3,Urban,Manager,85667,0 +82206,Male,24,Bachelors,17,61,85,25,8,0.0,4,76,Urban,Data Analyst,130104,1 +82207,Female,44,High School,19,51,96,55,27,6.0,6,89,Semi-Urban,Software Engineer,55288,1 +82208,Male,31,Masters,16,36,24,3,46,0.0,0,87,Urban,HR Executive,147392,0 +82209,Male,28,Bachelors,6,30,38,79,16,7.0,0,95,Urban,Software Engineer,50409,1 +82210,Male,54,Diploma,1,1,8,12,27,5.0,4,87,Rural,HR Executive,75776,0 +82211,Male,30,Masters,18,50,18,5,78,9.0,0,91,Urban,Manager,97749,0 +82212,Male,53,Masters,16,23,87,53,67,8.0,1,71,Urban,Manager,96505,0 +82213,Male,28,Diploma,14,59,33,72,5,8.0,1,77,Urban,Data Analyst,50769,1 +82214,Male,25,Bachelors,6,32,78,74,98,9.0,7,83,Rural,ML Engineer,84768,1 +82215,Male,35,Bachelors,15,46,95,78,25,1.0,4,12,Semi-Urban,HR Executive,148960,0 +82216,Female,28,Masters,10,88,59,6,13,0.0,0,91,Semi-Urban,Software Engineer,109182,1 +82217,Male,41,High School,15,63,7,6,48,2.0,4,80,Urban,Data Analyst,70283,0 +82218,Male,45,Masters,12,45,29,21,23,3.0,5,15,Semi-Urban,HR Executive,51532,0 +82219,Other,29,Bachelors,17,48,13,0,63,5.0,7,47,Semi-Urban,HR Executive,142624,0 +82220,Male,38,Masters,14,3,45,32,25,5.0,5,90,Semi-Urban,Manager,133949,0 +82221,Male,33,Diploma,15,47,77,37,97,8.0,5,56,Urban,Software Engineer,145521,0 +82222,Other,21,Bachelors,0,71,83,88,55,1.0,5,33,Urban,Data Analyst,113658,1 +82223,Male,59,Diploma,18,6,21,21,99,4.0,2,55,Rural,Data Analyst,78726,0 +82224,Other,32,High School,5,99,31,53,87,4.0,4,61,Semi-Urban,HR Executive,109812,1 +82225,Female,47,Bachelors,18,29,41,67,45,2.0,4,24,Rural,Data Analyst,86900,0 +82226,Male,44,Bachelors,18,48,42,52,6,7.0,4,61,Urban,HR Executive,142769,0 +82227,Male,31,PhD,11,24,38,90,20,8.0,5,7,Semi-Urban,HR Executive,105773,0 +82228,Male,33,Masters,19,71,55,69,70,6.0,0,4,Semi-Urban,Software Engineer,89240,0 +82229,Female,46,Masters,15,88,42,87,55,3.0,4,63,Semi-Urban,ML Engineer,27107,1 +82230,Male,45,Bachelors,8,39,10,72,0,0.0,0,68,Semi-Urban,ML Engineer,40916,0 +82231,Female,33,High School,5,19,41,26,29,9.0,7,55,Rural,HR Executive,124641,0 +82232,Other,53,Diploma,16,63,78,48,36,5.0,6,9,Rural,Manager,71228,0 +82233,Male,28,Bachelors,19,47,68,39,34,4.0,0,88,Semi-Urban,ML Engineer,25705,1 +82234,Male,43,Diploma,5,63,76,10,75,2.0,6,15,Urban,Software Engineer,74610,0 +82235,Male,33,Bachelors,4,42,57,19,9,3.0,5,90,Urban,HR Executive,130720,0 +82236,Male,41,Masters,18,30,73,39,91,1.0,2,86,Urban,Manager,34896,0 +82237,Male,37,Bachelors,5,25,65,66,50,6.0,4,5,Urban,Software Engineer,64170,0 +82238,Male,55,Masters,16,16,17,64,21,4.0,5,30,Rural,Data Analyst,147931,0 +82239,Female,53,Bachelors,18,53,82,16,35,1.0,3,46,Semi-Urban,Data Analyst,147535,0 +82240,Male,52,High School,19,31,46,56,3,3.0,3,2,Semi-Urban,ML Engineer,122177,0 +82241,Female,48,Diploma,18,20,34,61,84,9.0,6,35,Semi-Urban,HR Executive,26293,0 +82242,Male,23,Bachelors,16,17,79,73,16,8.0,1,16,Semi-Urban,Software Engineer,54651,0 +82243,Male,47,Masters,1,87,30,68,60,0.0,2,81,Urban,Data Analyst,128523,1 +82244,Male,53,PhD,2,44,34,74,34,8.0,5,29,Rural,HR Executive,55336,0 +82245,Female,56,Bachelors,11,56,90,19,9,1.0,1,63,Urban,Software Engineer,40982,0 +82246,Female,44,High School,11,58,11,45,78,8.0,1,81,Semi-Urban,ML Engineer,142646,0 +82247,Female,36,Diploma,16,7,82,71,76,8.0,1,95,Semi-Urban,Data Analyst,41878,1 +82248,Male,31,Bachelors,4,95,46,38,99,5.0,0,6,Urban,ML Engineer,135884,0 +82249,Female,51,Bachelors,13,18,52,47,48,6.0,6,17,Urban,Manager,84884,0 +82250,Male,42,Diploma,18,36,37,2,62,3.0,5,38,Urban,Software Engineer,33738,0 +82251,Male,53,PhD,12,69,11,12,59,9.0,0,72,Urban,HR Executive,149279,0 +82252,Female,43,Bachelors,1,95,66,64,11,0.0,3,5,Urban,Data Analyst,133317,0 +82253,Female,36,Masters,4,91,79,91,5,7.0,5,89,Semi-Urban,HR Executive,129089,1 +82254,Male,58,Bachelors,7,53,79,82,2,0.0,5,3,Urban,HR Executive,135482,0 +82255,Male,26,Bachelors,6,5,3,72,25,2.0,0,34,Urban,Manager,94568,0 +82256,Male,24,Masters,2,57,44,4,51,7.0,1,92,Urban,Software Engineer,34175,0 +82257,Male,38,Bachelors,6,47,84,37,85,9.0,6,30,Rural,Manager,24846,0 +82258,Female,32,Bachelors,7,20,61,38,28,1.0,6,83,Urban,Software Engineer,123411,0 +82259,Female,58,Diploma,7,72,63,69,28,5.0,3,63,Semi-Urban,Data Analyst,144500,1 +82260,Female,40,Bachelors,7,54,3,63,13,3.0,7,2,Rural,ML Engineer,76107,0 +82261,Female,46,Bachelors,5,54,61,48,62,8.0,4,82,Urban,ML Engineer,65527,1 +82262,Male,52,Bachelors,19,13,88,92,54,7.0,2,42,Urban,Data Analyst,52705,1 +82263,Female,28,PhD,9,14,81,68,92,0.0,1,71,Urban,Software Engineer,106746,0 +82264,Male,50,High School,15,53,33,88,77,5.0,1,34,Semi-Urban,ML Engineer,44716,0 +82265,Male,28,High School,13,6,42,94,60,4.0,6,81,Urban,Manager,147000,0 +82266,Female,35,High School,16,92,32,38,1,6.0,6,43,Rural,ML Engineer,109696,0 +82267,Female,21,Bachelors,0,93,20,24,75,3.0,6,73,Urban,ML Engineer,111517,0 +82268,Male,38,Bachelors,16,31,11,65,70,7.0,1,94,Urban,Manager,79221,0 +82269,Male,55,Diploma,16,32,86,71,98,9.0,2,68,Semi-Urban,HR Executive,75187,1 +82270,Female,45,Bachelors,19,16,83,37,57,8.0,5,93,Urban,ML Engineer,56160,0 +82271,Female,33,High School,19,18,32,95,16,0.0,3,50,Rural,Software Engineer,128404,0 +82272,Male,54,Bachelors,13,82,19,95,74,8.0,7,32,Semi-Urban,ML Engineer,49098,0 +82273,Male,29,High School,9,90,51,93,39,4.0,5,44,Urban,Manager,59644,1 +82274,Male,33,High School,4,40,23,10,44,8.0,4,74,Urban,HR Executive,21744,0 +82275,Female,55,Masters,0,32,94,25,40,3.0,1,96,Urban,Manager,81492,1 +82276,Female,35,Diploma,12,51,15,92,41,4.0,2,99,Urban,ML Engineer,47477,1 +82277,Male,57,Bachelors,1,86,23,88,80,2.0,5,47,Semi-Urban,Manager,28458,1 +82278,Male,49,High School,4,25,63,30,79,8.0,6,84,Urban,HR Executive,131552,0 +82279,Female,45,PhD,7,71,20,49,42,2.0,2,41,Rural,ML Engineer,96785,0 +82280,Male,49,Masters,15,32,41,36,64,0.0,1,30,Urban,Manager,41228,0 +82281,Female,33,Masters,17,87,26,49,4,1.0,6,67,Semi-Urban,Data Analyst,80411,0 +82282,Male,40,Bachelors,13,31,34,24,71,1.0,5,1,Urban,HR Executive,113176,0 +82283,Female,50,High School,11,60,98,42,28,5.0,6,6,Rural,ML Engineer,86473,0 +82284,Male,37,Diploma,11,26,57,49,91,5.0,4,89,Rural,Data Analyst,37621,0 +82285,Male,38,Diploma,11,9,53,43,39,8.0,5,0,Rural,Data Analyst,67704,0 +82286,Male,26,Bachelors,2,36,64,1,55,0.0,3,96,Urban,Manager,57439,0 +82287,Female,53,High School,11,39,18,51,46,7.0,2,81,Urban,Software Engineer,80098,0 +82288,Male,44,High School,17,6,14,75,82,2.0,4,2,Urban,Software Engineer,122493,0 +82289,Male,59,Diploma,2,1,30,41,83,1.0,3,23,Urban,HR Executive,112604,0 +82290,Male,37,Masters,16,57,90,62,12,8.0,2,7,Urban,HR Executive,34346,0 +82291,Male,22,Bachelors,17,85,71,19,13,8.0,4,55,Semi-Urban,Data Analyst,73293,0 +82292,Male,24,Diploma,2,47,63,97,87,3.0,1,1,Urban,Manager,94548,0 +82293,Male,41,Diploma,11,95,52,97,80,9.0,2,22,Semi-Urban,Software Engineer,70937,1 +82294,Female,24,Masters,7,1,23,92,79,9.0,7,42,Semi-Urban,Data Analyst,125139,0 +82295,Male,53,Bachelors,7,67,93,22,1,8.0,0,63,Urban,ML Engineer,105729,1 +82296,Male,55,PhD,6,34,50,50,59,8.0,2,81,Urban,Software Engineer,85362,0 +82297,Male,52,Diploma,3,80,6,53,51,7.0,5,92,Rural,Manager,98070,0 +82298,Male,58,PhD,11,48,0,36,2,1.0,7,4,Urban,ML Engineer,51979,0 +82299,Male,43,Diploma,16,15,59,71,76,3.0,1,23,Semi-Urban,HR Executive,141353,0 +82300,Male,56,Bachelors,10,6,41,54,57,8.0,5,29,Urban,Data Analyst,83116,0 +82301,Male,28,High School,5,55,55,89,61,9.0,7,62,Rural,ML Engineer,129642,1 +82302,Female,47,Diploma,15,93,34,18,44,2.0,1,49,Urban,HR Executive,91966,0 +82303,Male,58,Bachelors,6,71,31,23,19,3.0,1,90,Urban,ML Engineer,80049,0 +82304,Female,21,Bachelors,11,99,39,49,83,0.0,3,72,Urban,Software Engineer,29963,1 +82305,Male,56,Masters,1,99,59,96,88,0.0,7,61,Urban,Software Engineer,68035,1 +82306,Female,46,Masters,9,96,73,80,73,0.0,0,18,Semi-Urban,Manager,22285,1 +82307,Female,35,Diploma,5,73,15,67,95,9.0,6,45,Urban,HR Executive,120316,0 +82308,Male,25,High School,8,82,34,99,6,9.0,5,68,Rural,Software Engineer,111069,1 +82309,Other,43,Masters,14,65,73,61,80,6.0,4,88,Urban,HR Executive,69253,1 +82310,Male,26,Masters,6,3,1,4,40,9.0,1,41,Rural,Software Engineer,147222,0 +82311,Male,35,Bachelors,2,1,31,50,30,9.0,1,1,Urban,ML Engineer,68441,0 +82312,Other,35,Bachelors,14,37,93,9,71,6.0,7,82,Semi-Urban,HR Executive,30037,0 +82313,Male,43,High School,3,55,76,29,70,7.0,1,31,Rural,Software Engineer,37654,0 +82314,Female,44,Masters,9,66,52,4,81,0.0,6,29,Urban,ML Engineer,102745,0 +82315,Other,22,Diploma,12,75,12,26,11,4.0,2,28,Semi-Urban,HR Executive,73606,0 +82316,Female,51,Masters,7,87,44,31,52,2.0,1,5,Urban,ML Engineer,125094,0 +82317,Female,50,Bachelors,17,46,39,56,39,3.0,6,95,Urban,HR Executive,100073,0 +82318,Female,55,Diploma,13,15,84,65,3,0.0,2,82,Urban,Data Analyst,111425,1 +82319,Male,33,Diploma,12,90,3,37,80,1.0,6,47,Urban,Data Analyst,38539,0 +82320,Female,25,Masters,2,76,11,52,72,1.0,3,88,Rural,Software Engineer,61237,0 +82321,Male,43,High School,6,31,46,21,46,0.0,2,23,Urban,ML Engineer,124799,0 +82322,Female,48,Diploma,4,30,84,34,93,8.0,1,22,Urban,HR Executive,63105,0 +82323,Female,26,Bachelors,2,58,11,92,32,4.0,0,84,Rural,Software Engineer,96066,1 +82324,Male,34,Bachelors,8,71,96,52,83,3.0,7,46,Urban,Software Engineer,82092,1 +82325,Female,24,High School,2,54,17,27,25,4.0,2,28,Semi-Urban,ML Engineer,126389,0 +82326,Male,52,Masters,18,59,81,90,74,9.0,4,27,Rural,HR Executive,104075,1 +82327,Male,45,Diploma,0,99,87,94,25,5.0,4,98,Semi-Urban,HR Executive,140842,1 +82328,Female,48,Diploma,5,6,42,33,29,5.0,5,66,Urban,Data Analyst,43096,0 +82329,Male,53,Bachelors,10,90,30,78,32,8.0,0,4,Urban,ML Engineer,105320,0 +82330,Female,34,Diploma,8,1,38,4,89,4.0,5,68,Semi-Urban,Data Analyst,141425,0 +82331,Female,34,Bachelors,19,32,69,24,61,6.0,4,43,Urban,ML Engineer,129566,0 +82332,Male,57,Masters,11,28,64,70,80,9.0,0,19,Urban,Manager,116925,0 +82333,Male,34,Masters,4,10,77,79,44,8.0,3,76,Urban,Software Engineer,93437,1 +82334,Female,53,Masters,4,49,31,4,2,8.0,7,19,Rural,HR Executive,79971,0 +82335,Male,48,Masters,17,60,62,3,72,0.0,3,71,Urban,Data Analyst,91214,0 +82336,Female,59,Bachelors,9,85,72,0,47,8.0,1,26,Rural,Data Analyst,92902,0 +82337,Male,27,Masters,19,17,10,45,63,6.0,3,31,Urban,Manager,92758,0 +82338,Female,39,PhD,1,12,20,33,58,9.0,7,98,Urban,HR Executive,143290,0 +82339,Male,52,Bachelors,8,31,54,45,96,1.0,1,36,Urban,ML Engineer,86424,0 +82340,Male,54,Bachelors,3,33,87,74,1,7.0,2,34,Urban,ML Engineer,145502,0 +82341,Male,38,Masters,1,14,71,10,91,6.0,2,75,Semi-Urban,Data Analyst,98502,0 +82342,Other,53,Bachelors,11,35,77,77,19,3.0,5,66,Urban,HR Executive,149395,1 +82343,Male,28,PhD,1,50,44,76,80,9.0,2,8,Rural,Data Analyst,126460,0 +82344,Male,37,High School,14,68,75,28,17,4.0,6,10,Rural,ML Engineer,86443,0 +82345,Male,51,Bachelors,15,22,72,1,9,1.0,3,3,Urban,Manager,102961,0 +82346,Male,30,Bachelors,4,34,33,84,68,9.0,4,85,Urban,HR Executive,82412,1 +82347,Male,34,Bachelors,11,70,62,5,21,9.0,3,70,Semi-Urban,Software Engineer,34562,0 +82348,Male,50,Masters,6,86,59,75,60,0.0,6,12,Urban,Data Analyst,25002,0 +82349,Female,42,High School,10,75,23,48,59,8.0,4,42,Urban,Software Engineer,72436,0 +82350,Male,47,Masters,1,65,68,97,65,1.0,2,2,Urban,Data Analyst,113912,0 +82351,Male,38,Bachelors,17,64,53,21,64,7.0,2,94,Urban,Data Analyst,34528,0 +82352,Male,54,Bachelors,9,47,37,13,57,9.0,4,8,Semi-Urban,Data Analyst,109897,0 +82353,Male,30,Masters,3,18,11,77,7,2.0,1,21,Urban,HR Executive,62318,0 +82354,Female,44,Diploma,7,26,6,40,82,6.0,5,92,Urban,Manager,134137,0 +82355,Male,52,Masters,7,90,36,1,22,5.0,0,72,Urban,HR Executive,143470,0 +82356,Male,30,Bachelors,6,47,75,66,70,2.0,4,49,Semi-Urban,Software Engineer,48389,1 +82357,Other,27,Bachelors,4,14,51,61,54,7.0,6,31,Urban,Data Analyst,30008,0 +82358,Male,52,Masters,10,60,78,51,43,0.0,3,99,Semi-Urban,Software Engineer,61667,1 +82359,Male,52,Masters,1,47,54,95,74,2.0,6,72,Urban,HR Executive,99321,1 +82360,Female,57,Diploma,10,80,65,33,3,6.0,1,60,Rural,Data Analyst,109826,0 +82361,Male,41,Masters,8,39,63,66,27,0.0,0,16,Semi-Urban,Software Engineer,133713,0 +82362,Male,45,Diploma,15,86,76,97,67,9.0,5,13,Urban,HR Executive,29422,1 +82363,Female,39,Diploma,14,1,71,15,43,5.0,6,80,Urban,Manager,22819,0 +82364,Male,29,Diploma,13,31,1,76,70,0.0,0,91,Semi-Urban,HR Executive,118820,0 +82365,Male,49,Bachelors,8,35,98,73,91,5.0,5,30,Semi-Urban,HR Executive,61075,1 +82366,Female,43,Bachelors,0,13,51,6,61,6.0,7,53,Rural,Software Engineer,43875,0 +82367,Female,24,Masters,14,3,70,62,83,4.0,7,67,Semi-Urban,Data Analyst,43855,0 +82368,Female,49,Masters,3,93,76,76,56,4.0,6,4,Semi-Urban,Data Analyst,123143,1 +82369,Male,29,Diploma,15,52,23,40,59,0.0,4,13,Urban,HR Executive,64270,0 +82370,Male,53,Bachelors,13,37,50,60,22,1.0,7,95,Urban,HR Executive,117969,1 +82371,Female,39,Bachelors,12,37,21,40,23,6.0,1,55,Urban,Data Analyst,91357,0 +82372,Male,50,Masters,4,70,73,55,22,5.0,5,68,Rural,HR Executive,61485,1 +82373,Male,57,Bachelors,2,24,27,2,27,8.0,0,49,Semi-Urban,Software Engineer,24018,0 +82374,Female,52,Bachelors,11,15,75,58,37,9.0,0,22,Urban,Data Analyst,42748,0 +82375,Female,24,Bachelors,4,78,91,94,59,9.0,5,40,Rural,Manager,81481,1 +82376,Male,24,Bachelors,4,28,73,16,48,2.0,2,52,Semi-Urban,Data Analyst,61796,0 +82377,Male,35,Masters,12,39,66,27,37,0.0,1,51,Urban,Data Analyst,31364,0 +82378,Male,27,Masters,12,17,76,37,62,0.0,2,4,Urban,Data Analyst,104593,0 +82379,Male,31,PhD,16,96,52,1,1,6.0,1,56,Urban,ML Engineer,116689,0 +82380,Male,48,High School,16,75,12,53,14,9.0,2,1,Urban,HR Executive,144709,0 +82381,Female,32,Bachelors,15,42,80,87,34,1.0,4,74,Semi-Urban,HR Executive,117742,1 +82382,Female,44,Bachelors,3,48,21,44,48,3.0,2,65,Urban,ML Engineer,34456,0 +82383,Female,44,Bachelors,18,98,45,32,5,3.0,6,31,Urban,Manager,58736,0 +82384,Male,23,PhD,3,66,22,71,53,9.0,2,77,Urban,Data Analyst,85479,1 +82385,Male,26,Masters,14,25,29,98,27,4.0,4,22,Urban,Data Analyst,106810,0 +82386,Male,51,Diploma,2,19,42,45,69,2.0,2,65,Urban,HR Executive,143848,0 +82387,Male,36,Bachelors,3,80,69,40,2,5.0,5,60,Semi-Urban,Manager,116213,1 +82388,Female,25,Bachelors,4,1,5,38,9,2.0,5,14,Urban,Data Analyst,116942,0 +82389,Male,57,Diploma,3,44,65,55,81,0.0,7,68,Urban,Manager,49120,0 +82390,Male,29,Masters,16,79,69,14,40,3.0,4,35,Urban,Manager,32103,0 +82391,Female,43,PhD,19,7,46,85,97,7.0,1,3,Rural,HR Executive,50909,0 +82392,Male,42,Bachelors,14,24,36,18,29,2.0,5,13,Semi-Urban,ML Engineer,138231,0 +82393,Male,28,Bachelors,15,79,56,8,75,9.0,6,38,Rural,ML Engineer,96557,0 +82394,Male,56,Bachelors,7,21,62,97,44,9.0,6,1,Semi-Urban,Data Analyst,97106,0 +82395,Female,26,Masters,13,59,13,5,37,9.0,4,87,Semi-Urban,ML Engineer,44221,0 +82396,Female,37,Masters,19,35,63,72,72,1.0,5,71,Urban,Data Analyst,86374,1 +82397,Male,21,PhD,12,35,84,32,99,0.0,4,49,Urban,Manager,99255,0 +82398,Female,39,PhD,11,45,19,42,74,5.0,0,11,Rural,ML Engineer,70202,0 +82399,Female,41,Masters,2,27,19,51,41,7.0,3,41,Semi-Urban,Manager,57790,0 +82400,Female,59,Masters,3,86,7,40,70,8.0,3,80,Urban,HR Executive,115580,0 +82401,Other,30,High School,1,80,26,61,79,6.0,4,73,Rural,ML Engineer,119585,0 +82402,Male,36,Diploma,8,88,27,96,52,7.0,2,18,Urban,Data Analyst,132582,0 +82403,Male,51,Bachelors,18,77,76,40,52,7.0,5,89,Rural,Manager,137632,1 +82404,Male,50,Bachelors,6,18,99,91,92,0.0,2,70,Rural,Data Analyst,77950,1 +82405,Male,45,Masters,4,76,47,60,16,9.0,5,78,Semi-Urban,Manager,39557,1 +82406,Female,45,PhD,7,33,60,98,52,1.0,2,21,Semi-Urban,Data Analyst,91326,0 +82407,Male,52,Masters,7,5,78,80,26,0.0,4,11,Urban,ML Engineer,148862,0 +82408,Male,30,Bachelors,3,21,81,28,34,7.0,2,37,Urban,Software Engineer,111284,0 +82409,Male,55,Masters,19,68,23,1,35,1.0,2,96,Urban,ML Engineer,85479,0 +82410,Male,50,Diploma,19,56,73,4,59,2.0,2,46,Urban,Software Engineer,42914,0 +82411,Male,23,Masters,10,41,5,31,50,5.0,5,45,Semi-Urban,Software Engineer,20277,0 +82412,Male,48,High School,1,7,69,26,31,7.0,6,92,Urban,HR Executive,144044,0 +82413,Male,32,Bachelors,10,28,26,41,11,7.0,4,45,Urban,Manager,62034,0 +82414,Male,39,High School,17,55,51,30,28,1.0,5,37,Urban,Data Analyst,149282,0 +82415,Male,41,Masters,13,6,96,20,74,9.0,2,77,Rural,ML Engineer,106038,0 +82416,Male,23,Bachelors,8,49,55,95,97,4.0,5,77,Urban,HR Executive,47700,1 +82417,Female,36,Bachelors,12,10,9,4,31,5.0,1,95,Urban,ML Engineer,115829,0 +82418,Female,43,Diploma,18,17,59,14,78,1.0,2,5,Rural,ML Engineer,27371,0 +82419,Male,45,Diploma,8,38,74,89,59,0.0,1,87,Urban,ML Engineer,42756,1 +82420,Female,48,Masters,8,82,39,59,61,0.0,3,58,Rural,Data Analyst,127120,0 +82421,Male,58,High School,11,94,18,67,73,6.0,2,18,Rural,Software Engineer,40292,0 +82422,Female,21,Diploma,3,73,26,8,74,5.0,2,96,Semi-Urban,Data Analyst,44266,0 +82423,Other,34,Bachelors,12,71,59,92,88,5.0,1,33,Urban,ML Engineer,110436,1 +82424,Male,57,Bachelors,17,53,12,62,18,0.0,7,1,Rural,Software Engineer,22699,0 +82425,Female,33,PhD,11,55,66,71,93,2.0,3,63,Urban,Manager,32365,1 +82426,Male,35,Diploma,14,20,17,58,94,6.0,3,96,Rural,ML Engineer,59908,0 +82427,Other,46,Diploma,6,79,36,54,11,1.0,4,57,Urban,ML Engineer,20761,0 +82428,Male,48,Masters,6,1,90,19,83,3.0,2,59,Semi-Urban,Software Engineer,76885,0 +82429,Male,24,Masters,14,7,91,19,71,0.0,4,35,Urban,Software Engineer,93824,0 +82430,Female,58,Masters,14,93,2,54,12,9.0,0,42,Rural,Manager,141917,0 +82431,Male,42,Bachelors,16,7,58,3,12,7.0,6,45,Rural,HR Executive,46006,0 +82432,Male,58,High School,3,60,88,84,68,8.0,3,3,Semi-Urban,Software Engineer,113393,1 +82433,Male,47,PhD,2,42,95,54,5,1.0,2,94,Urban,HR Executive,80776,1 +82434,Female,45,Diploma,5,17,75,54,99,6.0,4,20,Semi-Urban,Software Engineer,97681,0 +82435,Female,44,Bachelors,5,39,7,83,95,8.0,6,17,Urban,Software Engineer,23159,0 +82436,Female,58,Masters,12,36,17,91,73,8.0,1,38,Semi-Urban,Manager,54267,0 +82437,Male,37,Bachelors,8,69,41,32,44,8.0,3,87,Urban,Manager,74711,0 +82438,Female,57,Masters,2,90,28,96,94,2.0,4,37,Urban,Software Engineer,68366,1 +82439,Male,33,Bachelors,5,38,4,44,94,9.0,1,23,Semi-Urban,Data Analyst,118889,0 +82440,Female,47,Bachelors,13,19,14,63,82,5.0,7,99,Semi-Urban,Software Engineer,70788,0 +82441,Male,54,Bachelors,4,2,25,85,8,7.0,1,80,Rural,Software Engineer,122232,0 +82442,Male,40,Diploma,2,39,36,83,93,8.0,7,72,Rural,Manager,110883,0 +82443,Female,38,Bachelors,1,8,60,41,76,2.0,6,32,Urban,HR Executive,78503,0 +82444,Male,53,Diploma,2,59,97,17,44,9.0,4,0,Rural,ML Engineer,106060,0 +82445,Male,45,Bachelors,13,81,71,98,54,8.0,5,14,Semi-Urban,HR Executive,67069,1 +82446,Female,50,Diploma,1,74,86,58,10,0.0,0,75,Semi-Urban,Manager,111115,1 +82447,Male,35,Bachelors,19,51,45,97,10,8.0,6,38,Urban,HR Executive,140033,0 +82448,Male,49,High School,8,58,88,75,14,7.0,7,52,Urban,Data Analyst,98589,1 +82449,Male,27,Bachelors,9,40,15,39,50,3.0,6,75,Urban,HR Executive,36176,0 +82450,Female,42,Bachelors,17,19,63,20,62,3.0,6,99,Urban,Data Analyst,109893,0 +82451,Male,50,Diploma,8,34,16,33,88,1.0,3,10,Semi-Urban,HR Executive,25817,0 +82452,Female,43,Masters,0,18,92,2,75,9.0,1,69,Urban,Data Analyst,36696,0 +82453,Male,25,Masters,16,10,45,31,50,1.0,0,38,Urban,Software Engineer,77074,0 +82454,Male,58,Bachelors,16,92,26,41,9,8.0,5,34,Urban,ML Engineer,88001,0 +82455,Male,32,Diploma,14,11,30,23,90,5.0,3,63,Urban,Manager,98091,0 +82456,Male,28,Bachelors,0,73,9,33,80,4.0,7,56,Semi-Urban,Software Engineer,23808,0 +82457,Male,24,PhD,1,39,15,36,34,6.0,3,40,Rural,Software Engineer,146380,0 +82458,Male,37,Diploma,5,65,92,59,89,9.0,4,60,Urban,Software Engineer,21859,1 +82459,Male,47,Bachelors,14,28,10,13,51,0.0,6,67,Urban,Data Analyst,137537,0 +82460,Male,41,Diploma,18,45,2,59,97,7.0,3,81,Urban,Software Engineer,77222,0 +82461,Female,39,Bachelors,12,81,57,64,9,1.0,1,4,Urban,Software Engineer,130136,0 +82462,Male,40,Masters,4,92,71,82,66,5.0,2,3,Rural,Data Analyst,84968,1 +82463,Male,55,Bachelors,19,41,45,46,65,3.0,3,52,Urban,ML Engineer,24675,0 +82464,Male,36,Bachelors,12,86,44,85,7,5.0,0,56,Urban,HR Executive,122090,1 +82465,Male,57,Bachelors,13,56,20,20,28,4.0,1,95,Rural,HR Executive,116448,0 +82466,Male,43,Masters,8,12,42,69,47,5.0,6,53,Urban,ML Engineer,123231,0 +82467,Female,45,Masters,4,64,47,35,84,7.0,2,20,Urban,Manager,130102,0 +82468,Female,44,Masters,1,80,95,45,79,7.0,5,93,Urban,Data Analyst,73512,1 +82469,Male,43,Masters,12,2,27,22,71,5.0,6,42,Urban,Manager,83604,0 +82470,Other,27,Bachelors,13,34,82,76,13,8.0,1,27,Urban,HR Executive,80897,0 +82471,Male,52,PhD,18,31,2,76,44,2.0,2,43,Urban,HR Executive,133261,0 +82472,Female,43,Bachelors,12,4,93,84,17,1.0,1,5,Semi-Urban,Software Engineer,140256,0 +82473,Male,40,Bachelors,7,22,69,31,5,8.0,6,18,Semi-Urban,HR Executive,108485,0 +82474,Male,34,Diploma,0,81,1,31,33,5.0,3,4,Urban,HR Executive,23943,0 +82475,Female,54,Diploma,4,75,26,98,71,7.0,2,44,Rural,Manager,24005,1 +82476,Male,36,Diploma,3,59,57,10,71,0.0,2,65,Urban,Software Engineer,77612,0 +82477,Male,44,High School,0,60,8,22,77,9.0,6,17,Urban,ML Engineer,65491,0 +82478,Female,29,Masters,3,54,90,9,38,7.0,4,47,Urban,Data Analyst,64943,0 +82479,Female,36,Bachelors,11,96,37,43,99,2.0,3,31,Rural,Software Engineer,95295,0 +82480,Female,46,Diploma,7,39,56,94,46,2.0,1,90,Rural,HR Executive,91727,1 +82481,Male,37,High School,14,97,75,23,68,7.0,5,2,Urban,Manager,31609,0 +82482,Male,50,Bachelors,10,7,10,19,31,5.0,4,55,Semi-Urban,Software Engineer,86254,0 +82483,Other,54,Masters,3,92,24,82,52,5.0,6,49,Semi-Urban,HR Executive,35146,1 +82484,Male,57,Masters,15,92,18,3,92,0.0,3,98,Urban,ML Engineer,50547,0 +82485,Male,41,Bachelors,9,87,30,81,19,1.0,7,2,Urban,HR Executive,64204,0 +82486,Male,36,Bachelors,7,6,7,62,4,1.0,1,70,Urban,Manager,21728,0 +82487,Female,21,Diploma,17,64,18,30,54,7.0,6,66,Urban,Data Analyst,29381,0 +82488,Male,33,Masters,16,78,80,96,78,4.0,7,16,Rural,HR Executive,89193,1 +82489,Male,24,Bachelors,1,34,47,97,22,4.0,3,34,Urban,Manager,91903,0 +82490,Male,57,Bachelors,0,37,37,19,72,4.0,1,76,Urban,Data Analyst,87520,0 +82491,Male,34,High School,13,44,94,31,62,3.0,0,32,Rural,Software Engineer,50643,0 +82492,Male,23,High School,17,65,34,48,76,8.0,7,37,Urban,ML Engineer,112550,0 +82493,Male,50,High School,15,9,78,2,20,0.0,1,7,Urban,Software Engineer,131317,0 +82494,Female,23,Masters,0,68,75,44,24,4.0,3,68,Rural,Data Analyst,59123,1 +82495,Male,44,Diploma,0,58,70,25,54,1.0,7,62,Semi-Urban,Manager,103958,0 +82496,Male,34,Masters,1,3,49,50,27,5.0,5,54,Urban,Data Analyst,26482,0 +82497,Male,47,Masters,5,84,60,90,88,2.0,4,14,Urban,Data Analyst,24039,1 +82498,Female,41,High School,1,4,20,29,23,5.0,4,18,Urban,Manager,68941,0 +82499,Male,22,PhD,8,41,81,53,23,0.0,5,94,Urban,ML Engineer,68443,1 +82500,Male,47,Masters,5,70,67,11,19,0.0,2,35,Rural,Data Analyst,52977,0 +82501,Male,37,Masters,3,65,89,76,10,3.0,7,81,Urban,Data Analyst,62894,1 +82502,Male,41,Diploma,14,84,55,52,5,3.0,4,90,Urban,Software Engineer,23460,1 +82503,Female,50,High School,1,25,86,56,14,5.0,6,26,Urban,Data Analyst,132792,0 +82504,Female,37,Bachelors,11,34,99,53,60,4.0,6,82,Rural,ML Engineer,125816,1 +82505,Male,31,High School,17,76,59,70,24,9.0,0,50,Semi-Urban,ML Engineer,97877,1 +82506,Female,26,Bachelors,1,96,12,33,15,0.0,7,10,Urban,Software Engineer,79588,0 +82507,Female,24,Bachelors,18,10,81,31,43,4.0,3,15,Rural,Software Engineer,70288,0 +82508,Female,29,Bachelors,4,9,19,50,12,3.0,0,60,Urban,Software Engineer,100986,0 +82509,Male,33,Diploma,16,0,58,0,82,7.0,6,0,Urban,Software Engineer,104492,0 +82510,Male,57,Masters,9,73,19,73,85,5.0,1,76,Urban,Data Analyst,26784,1 +82511,Female,52,Bachelors,18,0,93,63,32,6.0,0,38,Urban,Manager,34631,0 +82512,Female,56,Masters,6,56,70,41,59,8.0,5,51,Urban,Manager,149039,0 +82513,Female,38,Masters,7,66,53,44,57,9.0,0,22,Semi-Urban,Data Analyst,31367,0 +82514,Female,30,Diploma,16,69,28,85,24,3.0,1,46,Urban,Data Analyst,33252,0 +82515,Female,28,Diploma,0,33,78,4,9,7.0,2,2,Semi-Urban,Data Analyst,85900,0 +82516,Male,43,Bachelors,16,37,88,6,66,2.0,2,72,Semi-Urban,ML Engineer,146137,0 +82517,Male,48,Bachelors,5,15,4,66,7,0.0,7,37,Urban,Data Analyst,23431,0 +82518,Male,31,Bachelors,7,37,89,56,92,8.0,1,30,Urban,HR Executive,102587,0 +82519,Male,58,Masters,2,2,57,49,47,7.0,4,12,Rural,Software Engineer,78760,0 +82520,Female,46,Bachelors,18,73,66,97,25,9.0,0,4,Urban,Manager,62405,0 +82521,Male,35,Bachelors,10,6,45,22,70,9.0,3,5,Urban,Software Engineer,87404,0 +82522,Male,27,High School,10,50,57,39,57,6.0,5,94,Semi-Urban,Software Engineer,39665,1 +82523,Male,56,Diploma,14,31,87,11,54,8.0,4,11,Semi-Urban,Software Engineer,125978,0 +82524,Female,53,High School,5,31,34,7,19,9.0,3,47,Urban,Manager,23900,0 +82525,Male,34,Diploma,16,50,70,54,50,2.0,6,61,Rural,Software Engineer,110822,1 +82526,Male,51,High School,1,67,74,99,75,5.0,6,43,Urban,ML Engineer,122588,1 +82527,Female,30,Bachelors,9,67,21,93,19,1.0,6,11,Urban,Manager,53680,0 +82528,Male,56,Masters,0,49,21,15,76,1.0,3,8,Rural,Software Engineer,136134,0 +82529,Male,31,Masters,11,88,49,38,89,5.0,2,42,Semi-Urban,Software Engineer,143228,0 +82530,Female,41,Bachelors,11,78,22,67,41,5.0,1,1,Rural,Manager,71832,0 +82531,Male,33,Masters,0,5,67,62,1,2.0,1,6,Urban,Manager,146801,0 +82532,Female,34,Masters,4,52,76,86,45,0.0,1,20,Semi-Urban,HR Executive,54850,0 +82533,Male,28,Masters,16,70,69,42,54,6.0,1,3,Urban,HR Executive,112383,0 +82534,Male,58,Diploma,8,18,71,51,81,7.0,7,7,Urban,ML Engineer,91559,0 +82535,Male,55,Diploma,19,2,15,40,59,1.0,2,96,Urban,Data Analyst,44948,0 +82536,Male,43,Masters,14,91,99,60,30,2.0,4,80,Rural,Manager,87779,1 +82537,Female,46,Masters,3,69,39,22,16,5.0,2,79,Urban,ML Engineer,63485,0 +82538,Female,32,Bachelors,1,10,8,73,97,1.0,7,20,Urban,Data Analyst,111385,0 +82539,Female,42,Bachelors,11,75,60,91,8,5.0,0,27,Rural,Data Analyst,87262,1 +82540,Female,27,High School,5,81,62,65,77,9.0,1,95,Urban,HR Executive,101560,1 +82541,Male,29,PhD,3,37,16,29,2,2.0,2,93,Urban,Data Analyst,107050,0 +82542,Female,52,Diploma,4,28,29,11,84,3.0,5,10,Urban,Manager,102600,0 +82543,Male,45,PhD,2,58,13,89,43,3.0,3,0,Rural,ML Engineer,21261,0 +82544,Female,53,Bachelors,12,99,34,17,91,4.0,2,94,Semi-Urban,HR Executive,82056,1 +82545,Female,29,High School,10,1,8,23,60,1.0,4,72,Semi-Urban,HR Executive,105171,0 +82546,Male,43,Diploma,0,20,19,74,68,7.0,3,62,Urban,Data Analyst,96552,0 +82547,Male,50,Diploma,3,7,77,49,19,0.0,6,72,Rural,Data Analyst,111335,0 +82548,Male,52,High School,0,29,72,66,24,3.0,0,53,Rural,HR Executive,91260,0 +82549,Male,37,Bachelors,4,34,25,23,73,4.0,2,81,Rural,HR Executive,54001,0 +82550,Male,36,Bachelors,8,87,28,45,26,6.0,0,96,Rural,ML Engineer,53959,1 +82551,Female,48,Bachelors,0,62,90,63,94,9.0,0,82,Semi-Urban,Manager,62348,1 +82552,Male,58,Bachelors,2,58,40,51,63,2.0,3,66,Urban,ML Engineer,141679,0 +82553,Male,59,Bachelors,16,6,28,47,98,1.0,1,86,Semi-Urban,HR Executive,92255,0 +82554,Male,35,Bachelors,4,35,15,74,2,0.0,5,52,Rural,HR Executive,122319,0 +82555,Female,42,Bachelors,2,87,33,77,57,3.0,3,61,Rural,HR Executive,135941,1 +82556,Female,35,Masters,16,62,37,44,61,7.0,4,74,Rural,ML Engineer,134041,0 +82557,Male,44,High School,19,65,96,79,54,4.0,2,61,Urban,ML Engineer,66189,1 +82558,Male,57,High School,18,35,66,72,54,3.0,1,20,Rural,Data Analyst,37465,0 +82559,Male,48,Masters,1,11,77,97,80,6.0,4,10,Rural,HR Executive,111848,0 +82560,Other,59,Masters,2,39,12,80,54,1.0,7,80,Semi-Urban,ML Engineer,141701,0 +82561,Male,43,Masters,5,74,86,22,58,3.0,4,35,Urban,Data Analyst,71769,0 +82562,Female,34,Masters,1,66,31,9,92,8.0,2,67,Urban,HR Executive,79026,0 +82563,Female,39,Bachelors,0,74,88,45,45,1.0,4,63,Rural,Manager,61951,1 +82564,Male,28,Bachelors,0,28,34,66,11,0.0,2,19,Urban,ML Engineer,46537,0 +82565,Female,34,Diploma,1,5,10,74,83,0.0,4,93,Semi-Urban,Manager,142607,0 +82566,Male,45,High School,5,47,75,19,89,0.0,2,61,Semi-Urban,HR Executive,128016,0 +82567,Other,38,Bachelors,4,52,65,38,41,7.0,0,7,Urban,Data Analyst,36163,0 +82568,Female,44,Diploma,15,38,33,32,15,2.0,0,24,Rural,HR Executive,134817,0 +82569,Male,57,Bachelors,11,77,24,70,53,3.0,2,5,Urban,HR Executive,122372,0 +82570,Female,56,Masters,12,12,23,5,1,7.0,2,54,Semi-Urban,HR Executive,78281,0 +82571,Male,35,Bachelors,19,39,81,53,50,1.0,6,47,Rural,Data Analyst,122479,0 +82572,Male,41,Masters,14,6,61,29,47,2.0,4,76,Urban,HR Executive,66156,0 +82573,Female,25,Bachelors,5,36,47,83,71,3.0,2,40,Rural,Data Analyst,112884,0 +82574,Male,56,Masters,19,67,6,69,62,7.0,3,78,Urban,Software Engineer,89151,0 +82575,Male,45,Masters,13,62,73,19,89,5.0,7,12,Semi-Urban,Data Analyst,75932,0 +82576,Female,46,Diploma,5,50,14,32,21,5.0,4,95,Urban,HR Executive,48326,0 +82577,Other,27,Masters,7,28,16,8,3,1.0,4,17,Urban,HR Executive,115577,0 +82578,Female,32,Bachelors,6,92,64,72,19,5.0,7,12,Semi-Urban,HR Executive,67081,0 +82579,Female,38,Diploma,11,63,61,25,8,2.0,1,50,Urban,Manager,44009,0 +82580,Male,38,Bachelors,6,31,77,55,50,8.0,6,55,Urban,Data Analyst,55610,0 +82581,Female,33,Bachelors,10,43,85,48,2,7.0,7,5,Urban,ML Engineer,111744,0 +82582,Male,39,PhD,14,88,96,30,1,3.0,5,6,Semi-Urban,Manager,77470,0 +82583,Male,47,Diploma,1,38,86,85,12,8.0,1,1,Rural,Data Analyst,56678,0 +82584,Male,39,Bachelors,13,52,46,80,0,5.0,4,77,Urban,Data Analyst,148892,1 +82585,Other,47,Bachelors,16,3,43,21,75,1.0,7,0,Urban,HR Executive,54893,0 +82586,Male,35,Diploma,0,96,2,53,64,7.0,1,52,Urban,HR Executive,114858,0 +82587,Female,28,Diploma,19,66,14,40,93,8.0,4,31,Rural,Data Analyst,126183,0 +82588,Male,59,Bachelors,14,9,16,32,61,7.0,5,30,Semi-Urban,Manager,103608,0 +82589,Male,52,Diploma,4,16,2,4,23,1.0,1,33,Urban,Software Engineer,146566,0 +82590,Other,50,Bachelors,9,69,32,32,84,5.0,7,76,Urban,Software Engineer,48690,0 +82591,Female,23,High School,1,86,90,33,93,7.0,4,27,Semi-Urban,Manager,93659,0 +82592,Female,58,Bachelors,13,60,81,95,41,4.0,3,23,Rural,Manager,30251,1 +82593,Male,41,Bachelors,11,50,13,0,66,7.0,4,1,Semi-Urban,Manager,144371,0 +82594,Male,54,Masters,17,57,10,45,31,7.0,3,48,Urban,ML Engineer,43389,0 +82595,Male,41,Diploma,12,40,15,91,54,1.0,0,74,Urban,HR Executive,135430,0 +82596,Male,40,Bachelors,6,23,97,11,79,2.0,5,16,Rural,Software Engineer,134514,0 +82597,Male,27,Diploma,0,92,51,88,29,0.0,7,64,Rural,Manager,38733,1 +82598,Male,44,Bachelors,18,66,26,74,75,6.0,7,27,Urban,Data Analyst,99161,0 +82599,Male,39,Diploma,4,66,68,12,45,6.0,4,80,Semi-Urban,Manager,45751,0 +82600,Female,39,Bachelors,7,93,36,5,55,3.0,3,55,Urban,Manager,148172,0 +82601,Female,26,Diploma,6,70,86,90,96,7.0,0,92,Urban,ML Engineer,29031,1 +82602,Male,42,Bachelors,11,32,36,47,62,7.0,4,13,Urban,HR Executive,102192,0 +82603,Female,51,Bachelors,17,23,59,15,61,0.0,2,28,Rural,Data Analyst,137703,0 +82604,Male,28,Bachelors,7,96,23,85,3,7.0,6,8,Urban,ML Engineer,80081,0 +82605,Male,57,Diploma,15,91,74,69,15,0.0,2,61,Urban,Data Analyst,89161,1 +82606,Female,37,Bachelors,13,68,92,0,55,5.0,2,67,Rural,Software Engineer,62927,0 +82607,Male,33,Bachelors,19,56,16,27,41,5.0,7,76,Urban,Manager,118742,0 +82608,Female,23,Bachelors,15,23,25,61,94,8.0,0,37,Urban,Data Analyst,75262,0 +82609,Male,53,Bachelors,12,97,27,57,29,4.0,0,92,Urban,Manager,86176,1 +82610,Female,50,Diploma,10,33,57,14,21,5.0,4,22,Urban,Manager,45293,0 +82611,Female,39,High School,9,31,9,86,66,0.0,5,63,Urban,Manager,116951,0 +82612,Female,53,Diploma,14,0,34,31,71,0.0,3,29,Urban,ML Engineer,20638,0 +82613,Male,38,Bachelors,7,99,77,83,91,5.0,2,70,Urban,Manager,140235,1 +82614,Male,28,Bachelors,7,4,93,29,86,2.0,2,15,Urban,ML Engineer,127379,0 +82615,Male,21,Diploma,15,24,98,93,37,5.0,6,87,Rural,Software Engineer,99339,1 +82616,Female,43,High School,5,79,55,58,17,6.0,3,86,Urban,Manager,39929,1 +82617,Male,23,Diploma,4,38,88,75,56,1.0,6,34,Urban,ML Engineer,70786,1 +82618,Male,52,Bachelors,11,48,65,30,89,8.0,1,56,Rural,ML Engineer,27602,0 +82619,Male,40,Diploma,1,90,7,49,26,4.0,5,8,Urban,ML Engineer,88167,0 +82620,Male,25,Diploma,12,55,39,41,36,4.0,0,69,Urban,Data Analyst,89210,0 +82621,Female,51,Bachelors,3,64,40,46,36,5.0,5,65,Urban,Software Engineer,102691,0 +82622,Male,43,Bachelors,10,72,77,91,11,1.0,4,56,Urban,Data Analyst,109530,1 +82623,Female,48,Bachelors,7,82,98,68,54,2.0,5,6,Semi-Urban,HR Executive,131038,1 +82624,Male,32,High School,13,90,43,53,7,7.0,7,50,Semi-Urban,ML Engineer,65400,1 +82625,Male,30,Masters,13,59,7,85,16,0.0,0,81,Semi-Urban,ML Engineer,39304,0 +82626,Male,50,Bachelors,7,26,25,28,12,9.0,7,0,Urban,HR Executive,138902,0 +82627,Male,48,High School,6,68,20,1,0,4.0,3,87,Rural,HR Executive,124207,0 +82628,Male,51,Bachelors,16,63,71,62,70,6.0,4,14,Urban,Manager,72591,0 +82629,Male,26,Masters,2,68,15,2,42,2.0,2,8,Rural,Data Analyst,88713,0 +82630,Male,55,Bachelors,16,98,4,74,30,1.0,4,99,Urban,Software Engineer,69964,1 +82631,Female,36,Diploma,11,48,95,98,79,2.0,4,52,Urban,ML Engineer,83286,1 +82632,Male,32,Bachelors,11,22,14,91,5,8.0,2,5,Rural,Manager,121003,0 +82633,Female,56,PhD,1,44,21,50,76,3.0,7,39,Rural,ML Engineer,147449,0 +82634,Male,35,Bachelors,2,31,67,93,71,1.0,4,24,Urban,ML Engineer,136197,0 +82635,Female,23,High School,5,30,87,76,14,1.0,1,48,Semi-Urban,HR Executive,136800,1 +82636,Female,43,PhD,2,34,68,82,32,0.0,0,25,Semi-Urban,Manager,94604,0 +82637,Male,37,Diploma,13,81,28,41,34,2.0,0,61,Rural,ML Engineer,110402,0 +82638,Male,58,Masters,7,67,16,7,88,1.0,6,2,Urban,Data Analyst,51041,0 +82639,Male,35,Masters,4,65,1,90,32,0.0,0,39,Urban,Data Analyst,27894,0 +82640,Female,44,Bachelors,17,21,93,4,54,6.0,6,14,Urban,Data Analyst,95222,0 +82641,Male,52,High School,18,52,65,17,59,7.0,3,7,Semi-Urban,Manager,87712,0 +82642,Male,36,Masters,13,19,5,93,57,5.0,4,1,Rural,Manager,54613,0 +82643,Male,51,PhD,6,62,62,66,52,2.0,6,42,Semi-Urban,Manager,71819,0 +82644,Male,56,Bachelors,1,26,91,19,42,8.0,3,26,Semi-Urban,HR Executive,109611,0 +82645,Male,26,Masters,12,49,30,23,66,9.0,5,14,Urban,ML Engineer,103015,0 +82646,Male,33,Diploma,0,10,55,51,72,1.0,5,44,Urban,Data Analyst,114318,0 +82647,Other,32,Diploma,10,47,94,33,98,0.0,3,63,Urban,Data Analyst,127047,0 +82648,Female,35,PhD,18,99,63,28,16,4.0,4,82,Urban,Data Analyst,142689,1 +82649,Male,58,Bachelors,9,27,4,60,91,9.0,4,76,Semi-Urban,Data Analyst,84916,0 +82650,Male,46,Diploma,16,78,72,71,14,1.0,5,45,Rural,Software Engineer,85943,1 +82651,Male,37,High School,6,1,22,95,48,7.0,2,32,Urban,ML Engineer,58112,0 +82652,Male,47,Bachelors,8,13,7,70,80,0.0,7,52,Semi-Urban,Data Analyst,75404,0 +82653,Male,57,Bachelors,1,68,2,80,48,8.0,7,3,Urban,Software Engineer,143300,0 +82654,Male,34,High School,14,12,60,42,44,1.0,2,94,Urban,Software Engineer,132760,0 +82655,Male,54,Masters,17,49,60,62,67,5.0,3,12,Rural,HR Executive,126850,0 +82656,Female,27,Masters,3,62,83,52,74,6.0,5,41,Urban,HR Executive,111929,0 +82657,Male,47,Masters,7,72,63,49,31,9.0,2,24,Urban,Software Engineer,66128,0 +82658,Male,22,High School,2,51,79,9,55,4.0,5,71,Urban,HR Executive,125851,0 +82659,Female,36,Diploma,5,32,64,62,93,1.0,7,73,Urban,ML Engineer,123113,0 +82660,Other,23,Bachelors,13,28,90,46,84,2.0,2,30,Rural,ML Engineer,130561,0 +82661,Male,23,PhD,12,52,92,76,57,9.0,4,24,Urban,Manager,123514,1 +82662,Female,30,Bachelors,16,67,2,46,32,7.0,7,46,Urban,Manager,39266,0 +82663,Female,48,High School,7,0,57,44,36,1.0,1,19,Semi-Urban,Manager,27141,0 +82664,Female,55,Bachelors,7,95,41,86,59,8.0,6,47,Semi-Urban,ML Engineer,33249,1 +82665,Female,55,Diploma,1,49,24,89,41,5.0,0,31,Rural,Manager,40453,0 +82666,Female,55,Bachelors,12,78,30,88,83,9.0,7,27,Semi-Urban,Software Engineer,33123,0 +82667,Male,41,Bachelors,0,15,34,21,21,3.0,2,81,Rural,Manager,110373,0 +82668,Male,34,Bachelors,10,7,66,26,80,9.0,3,71,Semi-Urban,HR Executive,134347,0 +82669,Male,54,Bachelors,13,46,49,0,34,6.0,5,16,Rural,Data Analyst,138558,0 +82670,Male,57,High School,16,91,77,22,1,8.0,4,92,Urban,Software Engineer,28568,1 +82671,Male,53,Masters,14,51,7,16,47,6.0,1,35,Urban,Software Engineer,101903,0 +82672,Female,55,Diploma,10,11,93,83,2,1.0,7,91,Rural,Manager,28579,1 +82673,Female,41,Diploma,14,81,13,76,14,5.0,3,8,Urban,ML Engineer,97895,0 +82674,Male,36,High School,8,7,50,71,90,5.0,4,34,Urban,HR Executive,75394,0 +82675,Other,26,Bachelors,18,14,75,64,88,9.0,5,75,Rural,HR Executive,39397,0 +82676,Male,22,Diploma,15,15,20,87,70,3.0,3,17,Rural,Manager,122593,0 +82677,Male,39,Bachelors,12,53,49,9,87,7.0,0,16,Urban,Data Analyst,61095,0 +82678,Female,53,Masters,11,51,76,7,97,2.0,5,45,Urban,Data Analyst,66422,0 +82679,Male,28,PhD,3,40,60,22,41,4.0,0,10,Semi-Urban,Manager,49606,0 +82680,Male,40,Bachelors,11,47,37,11,94,2.0,6,42,Urban,ML Engineer,35109,0 +82681,Other,40,Bachelors,17,32,47,73,3,5.0,0,31,Urban,Manager,87294,0 +82682,Male,56,Bachelors,0,79,7,33,30,2.0,6,91,Semi-Urban,Software Engineer,124687,0 +82683,Female,39,Diploma,12,97,40,27,92,8.0,6,88,Urban,Data Analyst,80445,1 +82684,Other,54,Bachelors,9,42,82,88,46,0.0,5,29,Semi-Urban,ML Engineer,106853,1 +82685,Female,53,Bachelors,8,14,29,31,34,6.0,0,0,Urban,Data Analyst,71396,0 +82686,Male,26,Masters,11,40,33,91,69,3.0,5,36,Semi-Urban,ML Engineer,31722,0 +82687,Male,59,Masters,13,80,75,67,32,5.0,7,25,Urban,HR Executive,97466,1 +82688,Male,54,Bachelors,4,92,13,31,10,0.0,2,33,Urban,ML Engineer,148748,0 +82689,Male,42,Bachelors,18,59,48,10,54,9.0,0,90,Urban,Software Engineer,128615,0 +82690,Other,44,Bachelors,18,7,99,93,28,7.0,3,78,Semi-Urban,HR Executive,59196,1 +82691,Female,41,Masters,6,43,64,82,4,7.0,7,1,Urban,HR Executive,121921,0 +82692,Male,39,Masters,8,90,76,96,32,6.0,0,28,Urban,HR Executive,89067,1 +82693,Other,56,Masters,16,23,8,99,12,8.0,5,42,Urban,Software Engineer,113003,0 +82694,Male,40,High School,1,98,30,61,56,3.0,4,62,Urban,ML Engineer,136080,1 +82695,Female,48,Masters,16,63,75,8,92,5.0,3,55,Urban,Manager,33721,0 +82696,Male,48,High School,14,32,87,46,15,5.0,4,80,Semi-Urban,Data Analyst,147714,1 +82697,Male,32,Bachelors,9,46,46,2,47,4.0,6,21,Urban,ML Engineer,47145,0 +82698,Male,49,Bachelors,12,50,33,81,28,8.0,1,28,Semi-Urban,Manager,68051,0 +82699,Female,50,Bachelors,18,26,57,36,87,4.0,1,26,Semi-Urban,ML Engineer,140868,0 +82700,Male,52,Diploma,11,39,70,2,40,8.0,3,0,Urban,Data Analyst,70227,0 +82701,Female,26,Masters,0,74,23,58,7,6.0,0,38,Semi-Urban,Data Analyst,144717,0 +82702,Female,21,Masters,9,7,61,59,44,5.0,4,43,Urban,Software Engineer,66562,0 +82703,Male,57,Bachelors,17,36,68,61,30,1.0,3,17,Urban,Software Engineer,49234,0 +82704,Female,36,Diploma,12,42,77,44,21,7.0,5,11,Urban,ML Engineer,36763,0 +82705,Male,40,Bachelors,2,75,6,46,37,9.0,3,15,Urban,Software Engineer,38576,0 +82706,Male,35,Bachelors,10,40,12,39,37,5.0,0,11,Urban,Software Engineer,122158,0 +82707,Female,31,Diploma,3,95,91,83,95,3.0,6,23,Urban,Software Engineer,82992,1 +82708,Male,47,Diploma,10,66,99,81,48,7.0,6,79,Urban,Manager,109948,1 +82709,Female,36,Bachelors,13,52,34,30,9,3.0,3,10,Semi-Urban,HR Executive,147172,0 +82710,Male,56,High School,12,60,90,97,31,6.0,0,8,Urban,Manager,92035,1 +82711,Male,40,Masters,7,62,15,78,74,0.0,4,9,Semi-Urban,Data Analyst,40284,0 +82712,Other,51,Bachelors,17,59,53,72,94,8.0,7,30,Semi-Urban,ML Engineer,115375,0 +82713,Male,57,High School,5,72,8,61,64,1.0,6,39,Semi-Urban,Software Engineer,21306,0 +82714,Female,35,PhD,4,31,10,29,76,0.0,4,8,Urban,Data Analyst,68132,0 +82715,Male,23,PhD,13,62,92,70,58,6.0,2,48,Semi-Urban,HR Executive,108047,1 +82716,Male,45,High School,15,16,16,13,51,9.0,0,44,Rural,Software Engineer,135391,0 +82717,Male,39,Diploma,15,2,33,9,31,4.0,1,82,Semi-Urban,Manager,29724,0 +82718,Male,59,Bachelors,19,83,72,91,81,6.0,1,91,Urban,Software Engineer,51431,1 +82719,Female,59,Bachelors,17,75,77,29,16,8.0,0,79,Urban,ML Engineer,75068,1 +82720,Male,43,Bachelors,3,63,21,35,67,2.0,3,76,Urban,HR Executive,77896,0 +82721,Male,44,Masters,11,34,11,4,21,2.0,3,20,Urban,Data Analyst,84731,0 +82722,Female,46,Diploma,15,94,86,30,22,3.0,7,19,Urban,Manager,75992,0 +82723,Female,36,PhD,14,65,61,25,93,3.0,6,77,Rural,HR Executive,143292,0 +82724,Female,42,Masters,11,50,30,5,42,3.0,1,9,Rural,HR Executive,92794,0 +82725,Male,46,High School,7,71,56,25,14,3.0,7,91,Urban,Manager,30205,1 +82726,Female,34,Diploma,17,96,23,55,79,2.0,2,67,Urban,HR Executive,50189,1 +82727,Male,28,PhD,13,7,62,33,47,8.0,2,27,Urban,Data Analyst,49228,0 +82728,Male,45,Masters,7,99,79,66,69,1.0,0,8,Semi-Urban,Data Analyst,23769,1 +82729,Female,55,Masters,8,22,26,52,18,6.0,6,13,Semi-Urban,Data Analyst,24307,0 +82730,Female,23,Bachelors,11,41,50,8,1,8.0,5,23,Semi-Urban,Software Engineer,55006,0 +82731,Female,40,Diploma,2,53,67,49,55,4.0,3,42,Semi-Urban,HR Executive,136468,0 +82732,Other,51,High School,17,79,34,49,52,1.0,4,85,Semi-Urban,ML Engineer,67863,1 +82733,Female,51,Diploma,16,88,75,91,18,4.0,3,9,Urban,Manager,126686,1 +82734,Male,22,Bachelors,0,87,56,19,71,5.0,0,52,Semi-Urban,Data Analyst,52519,0 +82735,Male,33,Diploma,6,58,68,66,78,7.0,0,33,Urban,ML Engineer,103243,0 +82736,Male,29,Diploma,11,74,34,91,49,5.0,6,88,Urban,Manager,126034,1 +82737,Male,43,High School,0,11,70,82,55,7.0,5,14,Urban,Manager,63515,0 +82738,Male,21,Bachelors,7,68,92,74,79,3.0,0,12,Semi-Urban,ML Engineer,63173,1 +82739,Other,39,Bachelors,1,49,5,5,53,4.0,6,8,Urban,ML Engineer,94028,0 +82740,Female,30,Masters,9,45,26,61,7,9.0,2,15,Urban,HR Executive,97018,0 +82741,Male,49,Bachelors,17,35,17,53,94,9.0,6,18,Semi-Urban,Manager,122683,0 +82742,Male,39,High School,13,58,40,96,20,4.0,6,9,Urban,Data Analyst,61615,0 +82743,Male,40,High School,10,14,17,91,83,5.0,6,87,Rural,Data Analyst,149925,0 +82744,Male,37,High School,10,40,82,25,85,7.0,5,95,Urban,HR Executive,41141,1 +82745,Female,48,Bachelors,17,23,53,58,63,0.0,1,46,Urban,HR Executive,43208,0 +82746,Male,36,High School,7,42,66,22,67,0.0,5,55,Urban,Data Analyst,94830,0 +82747,Female,32,Bachelors,4,17,26,67,74,3.0,6,51,Urban,Software Engineer,85345,0 +82748,Male,40,High School,18,53,29,53,78,0.0,0,74,Urban,Data Analyst,139559,0 +82749,Male,40,Bachelors,9,92,73,98,66,9.0,2,24,Urban,HR Executive,70975,1 +82750,Male,40,Diploma,3,71,34,99,55,8.0,1,8,Urban,Manager,95316,0 +82751,Female,29,Bachelors,11,96,35,75,66,6.0,4,34,Semi-Urban,Software Engineer,84930,0 +82752,Male,41,High School,3,80,5,68,56,7.0,0,87,Urban,Data Analyst,84626,1 +82753,Male,40,Diploma,7,63,61,84,24,7.0,6,99,Rural,Manager,130144,1 +82754,Male,21,Masters,12,99,50,53,87,9.0,6,4,Semi-Urban,Manager,143520,0 +82755,Male,36,Bachelors,17,94,39,50,6,6.0,4,65,Semi-Urban,HR Executive,131161,1 +82756,Other,35,Masters,14,90,54,83,30,1.0,4,48,Urban,Manager,137581,1 +82757,Female,51,Diploma,5,32,52,34,78,0.0,3,91,Urban,ML Engineer,76473,0 +82758,Male,47,Bachelors,2,32,6,19,99,6.0,4,82,Semi-Urban,Data Analyst,70032,0 +82759,Female,45,Bachelors,17,10,81,47,6,8.0,4,24,Urban,Manager,41249,0 +82760,Male,31,Masters,6,88,83,74,19,9.0,3,19,Urban,HR Executive,116187,1 +82761,Male,53,Masters,18,91,29,6,39,5.0,1,16,Urban,ML Engineer,132144,0 +82762,Male,55,Bachelors,10,58,54,9,67,1.0,1,68,Semi-Urban,HR Executive,114090,0 +82763,Female,29,Masters,18,47,18,98,50,5.0,3,31,Urban,Manager,126398,0 +82764,Other,38,Masters,12,43,10,9,1,7.0,4,6,Semi-Urban,Manager,99635,0 +82765,Female,59,Bachelors,18,81,96,86,31,3.0,5,27,Urban,Manager,124193,1 +82766,Male,29,Diploma,8,51,41,69,66,9.0,3,67,Rural,ML Engineer,49317,0 +82767,Female,32,High School,10,72,55,46,55,7.0,7,11,Semi-Urban,HR Executive,138575,0 +82768,Male,53,Bachelors,11,2,46,21,54,0.0,0,26,Rural,Data Analyst,28136,0 +82769,Female,56,Masters,0,75,23,93,90,5.0,6,42,Semi-Urban,Software Engineer,71212,0 +82770,Male,49,Diploma,7,85,77,39,89,4.0,3,53,Urban,Data Analyst,79067,1 +82771,Male,35,High School,15,0,3,55,6,0.0,2,98,Rural,ML Engineer,45045,0 +82772,Female,36,High School,16,46,15,82,31,7.0,5,3,Semi-Urban,Software Engineer,144174,0 +82773,Male,43,Bachelors,5,20,21,93,31,9.0,4,9,Semi-Urban,HR Executive,59072,0 +82774,Male,24,Diploma,17,76,12,86,56,2.0,1,26,Urban,Data Analyst,55439,0 +82775,Male,55,Diploma,11,24,30,44,51,1.0,1,42,Rural,ML Engineer,30945,0 +82776,Female,25,Masters,16,62,0,56,36,8.0,2,82,Urban,ML Engineer,148900,0 +82777,Female,44,Bachelors,7,92,15,84,42,5.0,0,34,Semi-Urban,Manager,82456,0 +82778,Female,40,PhD,13,86,55,40,71,6.0,3,7,Semi-Urban,HR Executive,77292,0 +82779,Male,49,Bachelors,19,67,53,34,60,3.0,0,61,Urban,Manager,47202,0 +82780,Female,46,Masters,0,57,54,34,19,2.0,3,89,Urban,ML Engineer,133566,0 +82781,Male,24,Bachelors,8,54,41,98,38,5.0,5,10,Urban,Software Engineer,41448,0 +82782,Male,31,Masters,12,86,25,58,54,9.0,5,67,Semi-Urban,ML Engineer,53238,1 +82783,Male,28,Masters,10,19,42,2,7,2.0,1,20,Urban,HR Executive,34237,0 +82784,Female,48,Bachelors,2,8,53,70,40,3.0,7,78,Urban,HR Executive,52216,0 +82785,Male,55,PhD,4,73,68,19,64,3.0,0,17,Semi-Urban,Data Analyst,23941,0 +82786,Female,47,Masters,17,81,12,70,51,0.0,1,95,Urban,Software Engineer,132697,1 +82787,Female,32,High School,6,82,21,15,6,8.0,1,81,Urban,Data Analyst,80981,0 +82788,Male,30,Bachelors,10,93,88,89,53,0.0,5,48,Urban,Software Engineer,83064,1 +82789,Female,53,Diploma,0,35,3,19,41,6.0,7,49,Rural,Software Engineer,109392,0 +82790,Male,46,Bachelors,9,46,75,19,97,3.0,0,74,Urban,Software Engineer,57716,0 +82791,Male,39,Bachelors,4,84,99,78,82,9.0,2,87,Semi-Urban,Software Engineer,127625,1 +82792,Female,56,High School,8,26,75,40,38,5.0,6,89,Urban,HR Executive,66820,0 +82793,Female,42,Bachelors,7,96,81,38,39,9.0,6,50,Semi-Urban,ML Engineer,31915,1 +82794,Male,38,Bachelors,7,59,5,9,18,4.0,7,96,Rural,Data Analyst,85419,0 +82795,Male,59,Bachelors,14,37,22,66,29,4.0,1,59,Rural,ML Engineer,128307,0 +82796,Male,38,Bachelors,0,2,72,69,60,9.0,7,13,Urban,Software Engineer,136665,0 +82797,Male,56,Bachelors,4,15,11,2,55,1.0,4,14,Semi-Urban,Software Engineer,78874,0 +82798,Male,57,Diploma,19,11,65,16,74,9.0,0,62,Urban,Software Engineer,109343,0 +82799,Male,41,Diploma,19,27,15,88,82,6.0,7,90,Urban,Manager,117390,0 +82800,Male,55,Diploma,10,68,21,68,54,4.0,0,26,Semi-Urban,HR Executive,74988,0 +82801,Female,38,Bachelors,8,68,48,27,41,3.0,4,85,Rural,Software Engineer,33539,0 +82802,Male,54,Bachelors,14,60,92,3,19,3.0,3,75,Urban,Data Analyst,120058,0 +82803,Male,21,High School,9,44,7,41,91,3.0,2,78,Urban,ML Engineer,46392,0 +82804,Male,39,Masters,10,41,95,55,66,7.0,4,58,Urban,Software Engineer,110280,1 +82805,Male,34,Masters,16,13,78,83,32,4.0,5,70,Rural,ML Engineer,54620,1 +82806,Female,30,Diploma,4,45,8,26,76,4.0,7,94,Rural,Software Engineer,122031,0 +82807,Female,41,Masters,13,75,17,61,41,6.0,6,45,Urban,Manager,57508,0 +82808,Male,21,High School,15,62,31,81,94,2.0,0,47,Urban,Manager,149184,0 +82809,Female,37,Bachelors,7,50,31,33,11,3.0,6,78,Urban,ML Engineer,68296,0 +82810,Male,54,High School,17,38,43,22,76,9.0,6,86,Urban,HR Executive,61059,0 +82811,Male,25,Bachelors,11,81,23,4,42,1.0,3,55,Urban,Software Engineer,125657,0 +82812,Male,59,Bachelors,3,6,70,31,30,2.0,6,20,Urban,ML Engineer,97194,0 +82813,Male,34,Bachelors,2,70,50,80,58,3.0,2,42,Urban,Data Analyst,107664,1 +82814,Female,57,High School,1,12,57,70,83,8.0,0,26,Urban,Manager,83825,0 +82815,Male,26,High School,0,45,60,72,68,7.0,6,5,Semi-Urban,ML Engineer,44455,0 +82816,Male,58,Masters,18,87,87,60,13,3.0,5,26,Urban,Software Engineer,36352,1 +82817,Male,27,PhD,8,94,20,10,19,9.0,7,76,Semi-Urban,Data Analyst,107423,0 +82818,Female,26,Bachelors,14,54,35,25,98,2.0,6,6,Rural,ML Engineer,61878,0 +82819,Other,40,Bachelors,11,11,28,59,33,9.0,4,98,Urban,HR Executive,63845,0 +82820,Female,27,High School,8,79,6,22,79,9.0,6,67,Urban,Data Analyst,24310,0 +82821,Male,54,High School,14,69,7,88,58,7.0,1,78,Urban,Data Analyst,84547,1 +82822,Female,29,Bachelors,9,48,62,6,5,0.0,5,74,Urban,Data Analyst,37576,0 +82823,Male,44,Bachelors,3,73,63,34,50,6.0,3,70,Rural,HR Executive,78311,1 +82824,Male,21,Diploma,14,23,39,11,59,3.0,3,64,Urban,HR Executive,50855,0 +82825,Male,58,Diploma,8,22,51,91,17,8.0,2,75,Urban,Software Engineer,90886,1 +82826,Female,36,High School,13,5,26,64,55,7.0,7,23,Urban,Software Engineer,56188,0 +82827,Male,41,Masters,5,2,24,21,50,6.0,7,91,Semi-Urban,Software Engineer,114938,0 +82828,Female,53,Bachelors,16,0,70,17,40,8.0,1,33,Urban,Data Analyst,61116,0 +82829,Female,33,Masters,19,90,93,66,38,9.0,3,29,Urban,Manager,107237,1 +82830,Male,37,Masters,5,42,18,81,7,1.0,5,15,Rural,Software Engineer,69581,0 +82831,Male,57,Masters,16,68,58,20,67,5.0,7,20,Urban,Manager,35149,0 +82832,Male,27,Bachelors,17,36,8,57,34,0.0,1,46,Semi-Urban,HR Executive,125509,0 +82833,Female,42,Diploma,19,54,54,20,80,4.0,7,20,Semi-Urban,Software Engineer,130384,0 +82834,Female,57,High School,3,71,28,70,14,4.0,1,86,Semi-Urban,Software Engineer,91473,1 +82835,Female,36,Masters,9,93,32,76,68,2.0,4,45,Urban,HR Executive,119854,1 +82836,Female,52,Bachelors,4,39,48,58,25,4.0,0,25,Urban,Software Engineer,25885,0 +82837,Female,45,Bachelors,8,90,56,32,28,0.0,3,24,Rural,Manager,69154,0 +82838,Male,24,Diploma,2,86,73,35,10,9.0,5,40,Urban,Software Engineer,112707,0 +82839,Male,52,Diploma,4,33,83,69,55,8.0,0,73,Semi-Urban,Data Analyst,139854,1 +82840,Male,39,Diploma,11,10,64,77,94,7.0,5,36,Urban,Software Engineer,120531,0 +82841,Female,22,Masters,2,91,73,27,76,6.0,0,65,Semi-Urban,Data Analyst,96660,1 +82842,Male,34,Masters,16,95,56,32,69,6.0,6,7,Rural,Software Engineer,122816,0 +82843,Other,31,Bachelors,17,35,37,20,2,3.0,4,8,Semi-Urban,Data Analyst,79800,0 +82844,Male,21,High School,0,85,70,46,47,0.0,6,8,Urban,ML Engineer,107708,0 +82845,Male,40,Bachelors,4,15,77,27,38,9.0,3,1,Semi-Urban,Software Engineer,109238,0 +82846,Male,47,Masters,1,78,22,76,31,8.0,7,15,Urban,HR Executive,66790,0 +82847,Male,42,High School,13,23,11,72,4,9.0,2,68,Rural,Data Analyst,123059,0 +82848,Female,43,PhD,2,27,46,68,51,4.0,1,53,Rural,ML Engineer,41540,0 +82849,Female,38,Bachelors,10,10,77,85,50,4.0,2,14,Rural,Software Engineer,67635,0 +82850,Male,51,Diploma,18,1,75,50,55,2.0,6,67,Urban,ML Engineer,88483,0 +82851,Other,38,Diploma,13,76,97,36,80,7.0,0,16,Urban,HR Executive,118565,0 +82852,Female,46,Bachelors,9,91,20,36,20,2.0,0,82,Urban,HR Executive,48006,0 +82853,Female,49,Diploma,11,26,43,0,66,4.0,0,32,Urban,Software Engineer,113330,0 +82854,Male,43,Bachelors,13,96,95,61,71,7.0,4,1,Urban,Software Engineer,125084,1 +82855,Male,57,Bachelors,4,50,60,69,16,1.0,2,23,Semi-Urban,Data Analyst,20799,0 +82856,Male,52,Bachelors,8,70,60,28,42,6.0,3,98,Urban,Software Engineer,139789,1 +82857,Male,22,Bachelors,1,6,78,66,36,7.0,5,26,Urban,ML Engineer,99008,0 +82858,Male,53,Diploma,12,87,70,56,4,4.0,4,67,Urban,Data Analyst,33275,1 +82859,Female,56,High School,17,30,73,94,5,2.0,3,34,Semi-Urban,Software Engineer,26634,0 +82860,Male,58,Diploma,18,45,59,43,13,6.0,5,91,Urban,Data Analyst,23835,1 +82861,Male,50,Bachelors,13,25,26,49,24,5.0,7,85,Urban,Manager,59375,0 +82862,Female,31,Masters,13,47,55,54,36,7.0,1,44,Urban,ML Engineer,98860,0 +82863,Male,45,Bachelors,6,16,91,13,74,6.0,3,75,Urban,HR Executive,140772,0 +82864,Female,27,Bachelors,16,40,2,15,72,6.0,6,22,Rural,Software Engineer,106647,0 +82865,Male,54,High School,17,26,82,55,30,8.0,3,15,Semi-Urban,Manager,69345,0 +82866,Female,31,High School,19,2,38,44,51,7.0,7,12,Urban,Manager,135837,0 +82867,Female,54,Masters,6,51,96,47,33,8.0,4,46,Urban,Data Analyst,81114,0 +82868,Female,30,Masters,16,31,0,27,83,4.0,6,1,Urban,Data Analyst,27145,0 +82869,Male,24,Bachelors,8,41,53,84,44,2.0,4,14,Urban,Manager,138192,0 +82870,Male,32,Bachelors,18,63,36,67,72,5.0,4,42,Semi-Urban,HR Executive,49778,0 +82871,Male,52,Diploma,16,1,50,89,0,7.0,0,19,Rural,Data Analyst,137453,0 +82872,Female,23,Bachelors,10,87,39,16,98,8.0,0,61,Urban,Manager,33965,0 +82873,Male,39,Bachelors,9,51,87,12,64,8.0,7,12,Urban,HR Executive,60764,0 +82874,Female,25,Masters,5,68,6,9,86,4.0,4,15,Rural,ML Engineer,128612,0 +82875,Female,32,High School,8,80,87,42,11,6.0,3,67,Urban,Manager,141598,1 +82876,Female,51,Diploma,2,40,29,66,4,5.0,3,98,Urban,Software Engineer,83158,0 +82877,Other,37,Bachelors,5,38,12,32,59,8.0,0,69,Rural,ML Engineer,21930,0 +82878,Male,24,Masters,16,33,19,7,60,2.0,3,97,Urban,Software Engineer,141816,0 +82879,Female,22,High School,19,88,59,2,44,4.0,2,8,Urban,Manager,101475,0 +82880,Female,59,High School,6,68,56,44,51,0.0,3,53,Rural,ML Engineer,33327,0 +82881,Male,32,Bachelors,15,19,48,99,89,4.0,2,66,Rural,HR Executive,125952,0 +82882,Other,38,Bachelors,2,33,32,13,8,2.0,6,90,Semi-Urban,HR Executive,34239,0 +82883,Male,54,Bachelors,16,92,46,75,29,9.0,3,17,Urban,Manager,51948,0 +82884,Female,40,Diploma,17,21,23,63,51,3.0,5,87,Urban,HR Executive,80407,0 +82885,Other,22,PhD,5,94,5,5,72,2.0,6,12,Rural,Manager,123266,0 +82886,Female,47,Bachelors,11,70,47,51,38,4.0,2,49,Rural,HR Executive,46384,0 +82887,Male,25,Masters,0,9,45,35,10,2.0,5,62,Urban,HR Executive,149151,0 +82888,Male,48,Masters,5,3,63,56,12,1.0,2,32,Urban,Manager,55065,0 +82889,Male,57,Masters,19,6,11,60,55,5.0,2,13,Semi-Urban,HR Executive,48773,0 +82890,Male,55,High School,16,16,10,49,71,6.0,0,21,Rural,HR Executive,68080,0 +82891,Female,53,Bachelors,10,51,60,82,67,1.0,0,21,Rural,Data Analyst,102283,0 +82892,Female,56,Diploma,9,90,31,86,15,9.0,4,12,Semi-Urban,Data Analyst,52408,0 +82893,Female,53,Diploma,0,81,19,61,83,6.0,1,42,Urban,Software Engineer,59895,0 +82894,Male,47,Masters,10,67,57,33,9,0.0,6,90,Rural,HR Executive,68250,1 +82895,Male,42,High School,18,56,89,47,23,7.0,4,93,Urban,Manager,82906,1 +82896,Male,21,Bachelors,1,23,67,57,4,7.0,2,56,Urban,HR Executive,145180,0 +82897,Male,54,Bachelors,1,26,32,51,90,8.0,0,95,Urban,Manager,66661,0 +82898,Male,50,High School,9,15,88,30,7,7.0,4,82,Urban,HR Executive,123147,0 +82899,Male,51,Bachelors,8,20,44,3,58,7.0,0,47,Semi-Urban,Manager,58625,0 +82900,Male,26,Bachelors,14,65,50,95,67,9.0,1,76,Urban,ML Engineer,140680,1 +82901,Male,41,Bachelors,2,93,32,43,24,4.0,1,15,Urban,Data Analyst,122099,0 +82902,Male,41,Masters,17,14,64,28,12,6.0,6,59,Urban,Manager,116932,0 +82903,Male,36,Bachelors,8,90,91,29,25,1.0,6,87,Rural,Software Engineer,74798,1 +82904,Female,24,Bachelors,5,56,14,20,27,0.0,4,74,Semi-Urban,Software Engineer,45408,0 +82905,Female,51,Bachelors,9,16,51,75,47,4.0,7,44,Semi-Urban,HR Executive,81242,0 +82906,Male,55,Bachelors,12,42,33,91,21,9.0,6,21,Semi-Urban,ML Engineer,136315,0 +82907,Male,43,Masters,4,29,6,29,41,5.0,5,67,Urban,Manager,35375,0 +82908,Male,42,Bachelors,13,24,3,39,80,4.0,7,16,Urban,Manager,144118,0 +82909,Male,49,Bachelors,12,49,70,68,9,2.0,5,95,Rural,ML Engineer,91488,1 +82910,Female,58,Bachelors,4,86,0,65,55,4.0,4,61,Rural,ML Engineer,89127,0 +82911,Female,56,High School,0,38,46,75,70,6.0,3,26,Semi-Urban,Manager,85018,0 +82912,Male,54,Bachelors,18,64,35,72,63,4.0,2,46,Urban,Data Analyst,58836,0 +82913,Female,33,High School,10,14,71,77,58,8.0,4,76,Urban,Software Engineer,124924,0 +82914,Female,32,High School,13,29,3,48,35,9.0,1,86,Urban,Data Analyst,37429,0 +82915,Female,32,Masters,4,31,25,92,46,6.0,7,40,Urban,Software Engineer,36291,0 +82916,Male,28,High School,4,98,67,75,52,0.0,4,49,Urban,Software Engineer,24145,1 +82917,Male,49,Bachelors,7,60,11,84,20,2.0,5,59,Rural,HR Executive,125158,0 +82918,Male,22,Bachelors,0,45,9,48,74,2.0,4,74,Rural,ML Engineer,132133,0 +82919,Male,46,Bachelors,12,8,45,28,41,5.0,2,81,Urban,ML Engineer,63121,0 +82920,Female,28,Diploma,6,30,26,95,26,8.0,4,15,Urban,HR Executive,30781,0 +82921,Female,42,Masters,19,72,23,95,8,2.0,6,28,Urban,Software Engineer,51335,0 +82922,Female,46,High School,7,90,32,73,12,5.0,6,8,Urban,Data Analyst,38666,0 +82923,Male,57,Diploma,18,28,36,37,67,2.0,6,14,Urban,Manager,130740,0 +82924,Female,54,Bachelors,15,5,6,80,25,1.0,0,16,Urban,Manager,53185,0 +82925,Male,21,High School,15,33,65,46,12,3.0,6,87,Rural,ML Engineer,112538,0 +82926,Other,57,Bachelors,18,82,5,17,42,5.0,1,9,Urban,Manager,99290,0 +82927,Male,23,High School,19,88,78,79,1,9.0,1,89,Rural,Data Analyst,92065,1 +82928,Female,37,Bachelors,17,61,24,10,93,9.0,0,7,Urban,Software Engineer,75404,0 +82929,Male,39,Bachelors,19,92,7,14,18,8.0,4,24,Urban,ML Engineer,96922,0 +82930,Male,35,Diploma,7,93,69,55,22,4.0,4,0,Urban,HR Executive,33700,0 +82931,Female,33,High School,12,99,20,99,99,1.0,0,97,Semi-Urban,Manager,149649,1 +82932,Female,37,Bachelors,2,12,55,21,70,1.0,4,17,Rural,HR Executive,76914,0 +82933,Male,44,Diploma,8,95,62,32,33,5.0,7,59,Urban,Data Analyst,50386,1 +82934,Female,35,Diploma,12,31,63,6,4,1.0,7,83,Urban,Data Analyst,143799,0 +82935,Male,50,Bachelors,6,62,92,39,3,8.0,1,0,Urban,HR Executive,38881,0 +82936,Other,25,Bachelors,3,5,20,88,1,2.0,0,83,Rural,Software Engineer,116979,0 +82937,Female,59,PhD,10,53,71,40,74,4.0,7,12,Urban,HR Executive,33436,0 +82938,Male,59,Bachelors,1,33,36,20,33,4.0,3,19,Urban,Data Analyst,21476,0 +82939,Male,21,Bachelors,4,71,58,73,46,9.0,1,76,Urban,Software Engineer,118322,1 +82940,Male,25,Masters,10,82,31,48,49,9.0,1,42,Semi-Urban,HR Executive,35593,0 +82941,Male,25,Bachelors,6,59,21,31,61,2.0,6,50,Semi-Urban,ML Engineer,83596,0 +82942,Male,49,PhD,5,82,71,70,42,1.0,0,99,Rural,Manager,37106,1 +82943,Male,55,Diploma,6,14,39,65,65,0.0,1,24,Urban,Software Engineer,70437,0 +82944,Male,54,Bachelors,0,83,94,72,37,5.0,4,46,Urban,Data Analyst,88917,1 +82945,Male,40,Masters,12,81,96,16,88,4.0,1,43,Urban,Software Engineer,101156,1 +82946,Female,55,Masters,6,12,61,30,31,8.0,4,49,Urban,HR Executive,91037,0 +82947,Male,38,Diploma,19,42,35,44,66,6.0,2,11,Semi-Urban,Data Analyst,92635,0 +82948,Female,33,Masters,9,52,61,27,28,2.0,3,56,Urban,Manager,46574,0 +82949,Other,37,Bachelors,4,78,77,28,61,4.0,0,31,Urban,Data Analyst,26282,0 +82950,Male,40,Masters,14,22,80,69,52,0.0,6,85,Urban,Data Analyst,131073,1 +82951,Male,47,Bachelors,7,57,93,84,99,0.0,7,85,Urban,Manager,36671,1 +82952,Other,23,Bachelors,13,72,28,91,89,3.0,0,65,Rural,Software Engineer,21761,1 +82953,Male,34,Bachelors,10,40,4,25,7,3.0,1,22,Urban,Manager,93543,0 +82954,Female,31,Masters,3,67,47,79,82,2.0,7,80,Urban,Software Engineer,125183,1 +82955,Male,45,Masters,10,96,61,15,30,1.0,3,38,Urban,ML Engineer,21481,0 +82956,Female,30,PhD,11,9,79,52,84,9.0,3,38,Rural,Data Analyst,126106,0 +82957,Male,30,Bachelors,18,58,40,96,49,4.0,0,21,Semi-Urban,Software Engineer,131480,0 +82958,Female,28,Masters,15,93,0,47,70,0.0,7,30,Urban,HR Executive,21129,0 +82959,Female,47,Bachelors,1,91,55,58,86,4.0,2,91,Semi-Urban,Manager,87858,1 +82960,Male,31,Diploma,17,22,76,92,4,1.0,6,49,Semi-Urban,HR Executive,75549,1 +82961,Female,48,Bachelors,0,68,3,51,74,0.0,2,64,Semi-Urban,Data Analyst,118947,0 +82962,Male,51,Diploma,7,86,3,52,23,9.0,1,20,Semi-Urban,Software Engineer,54976,0 +82963,Male,59,Masters,2,1,24,53,20,7.0,3,97,Urban,Data Analyst,42468,0 +82964,Male,48,Bachelors,16,36,88,22,70,6.0,5,85,Semi-Urban,ML Engineer,124674,0 +82965,Male,45,Diploma,8,77,4,39,54,1.0,7,38,Urban,Manager,24921,0 +82966,Female,46,PhD,4,98,31,47,0,8.0,2,0,Semi-Urban,ML Engineer,140227,0 +82967,Other,54,Bachelors,17,13,69,41,66,7.0,0,12,Urban,Data Analyst,138029,0 +82968,Female,31,Diploma,7,90,94,28,51,5.0,2,60,Semi-Urban,Data Analyst,81040,1 +82969,Female,54,Masters,3,32,48,13,15,5.0,7,57,Semi-Urban,ML Engineer,98870,0 +82970,Female,41,Masters,8,85,19,94,68,4.0,6,29,Urban,Data Analyst,119224,0 +82971,Female,25,High School,8,82,19,45,57,1.0,3,45,Urban,ML Engineer,66815,0 +82972,Male,36,Bachelors,3,21,48,95,81,2.0,6,37,Urban,Manager,121643,0 +82973,Female,34,PhD,5,68,71,72,94,4.0,2,53,Rural,ML Engineer,107163,1 +82974,Male,36,Diploma,4,51,84,15,23,7.0,2,98,Urban,HR Executive,99750,1 +82975,Male,38,Masters,18,16,63,9,61,7.0,5,84,Rural,Software Engineer,133575,0 +82976,Male,33,Bachelors,17,75,25,12,57,5.0,6,71,Semi-Urban,ML Engineer,110361,0 +82977,Male,46,Bachelors,11,2,93,43,54,4.0,4,28,Urban,Data Analyst,105841,0 +82978,Male,29,Masters,11,6,15,90,99,8.0,6,74,Urban,Software Engineer,123450,0 +82979,Other,27,Bachelors,13,42,70,69,27,0.0,1,5,Semi-Urban,ML Engineer,117216,0 +82980,Male,31,Masters,15,67,73,43,72,4.0,5,51,Semi-Urban,Data Analyst,132308,0 +82981,Female,21,Bachelors,16,61,46,35,21,0.0,5,80,Urban,ML Engineer,73456,0 +82982,Female,26,Diploma,11,40,65,69,55,9.0,7,85,Urban,Data Analyst,35339,1 +82983,Male,46,Bachelors,6,45,77,38,16,8.0,4,41,Rural,Manager,139439,0 +82984,Female,36,Bachelors,6,69,47,61,31,7.0,2,32,Urban,HR Executive,48415,0 +82985,Male,52,High School,4,10,69,69,98,1.0,3,18,Urban,Software Engineer,45031,0 +82986,Male,44,Diploma,3,77,5,17,26,7.0,0,39,Rural,ML Engineer,32219,0 +82987,Female,36,Bachelors,9,25,26,45,0,9.0,5,62,Urban,Software Engineer,143614,0 +82988,Male,44,Masters,13,82,39,92,19,5.0,6,16,Rural,Software Engineer,88703,0 +82989,Male,50,Diploma,10,83,16,56,69,6.0,7,19,Rural,HR Executive,67208,0 +82990,Male,39,Diploma,2,75,82,49,67,4.0,2,54,Rural,HR Executive,63665,1 +82991,Male,42,Diploma,19,18,83,86,39,3.0,3,17,Urban,Manager,95671,0 +82992,Female,26,High School,14,2,98,87,4,4.0,6,62,Rural,ML Engineer,38731,1 +82993,Other,38,Masters,4,40,60,70,36,4.0,7,53,Urban,Manager,51773,0 +82994,Male,37,Diploma,2,23,95,88,5,4.0,1,99,Rural,Software Engineer,36214,1 +82995,Male,56,Bachelors,13,33,62,13,88,5.0,0,54,Rural,Data Analyst,111772,0 +82996,Male,21,Bachelors,9,18,56,15,39,0.0,4,93,Urban,HR Executive,51647,0 +82997,Other,57,Masters,14,56,4,7,45,9.0,0,64,Semi-Urban,Data Analyst,78046,0 +82998,Male,51,Bachelors,8,76,36,44,52,1.0,3,81,Urban,Software Engineer,115899,1 +82999,Male,47,High School,7,63,90,20,64,5.0,5,59,Urban,Manager,132644,0 +83000,Female,43,Diploma,17,76,80,54,9,4.0,6,68,Urban,Software Engineer,28572,1 +83001,Male,37,High School,1,81,17,28,76,0.0,4,86,Rural,HR Executive,35969,0 +83002,Male,48,Diploma,15,18,79,27,5,1.0,5,72,Rural,Data Analyst,70346,0 +83003,Male,47,Diploma,8,29,18,37,49,5.0,1,25,Urban,Manager,55319,0 +83004,Other,25,Diploma,9,63,12,57,61,6.0,1,71,Urban,Data Analyst,98123,0 +83005,Male,47,PhD,0,18,49,14,0,7.0,0,73,Rural,Manager,106705,0 +83006,Male,53,Bachelors,4,77,18,31,79,7.0,4,15,Urban,Data Analyst,52990,0 +83007,Female,35,Bachelors,13,66,91,5,34,2.0,0,82,Semi-Urban,Data Analyst,31710,1 +83008,Male,46,Bachelors,7,0,14,4,24,9.0,0,48,Urban,Data Analyst,47698,0 +83009,Female,33,High School,0,55,28,54,14,7.0,2,99,Semi-Urban,Software Engineer,122633,0 +83010,Male,54,Bachelors,18,50,2,17,32,5.0,3,24,Urban,HR Executive,48733,0 +83011,Male,56,Bachelors,2,93,4,75,69,6.0,4,50,Rural,HR Executive,148391,0 +83012,Male,23,PhD,6,0,79,31,5,0.0,2,47,Urban,Manager,46631,0 +83013,Other,52,Diploma,2,74,37,39,66,6.0,0,68,Urban,HR Executive,94818,0 +83014,Female,58,High School,19,68,67,49,70,0.0,3,84,Urban,HR Executive,112462,1 +83015,Other,26,High School,15,89,20,54,43,4.0,2,84,Semi-Urban,Software Engineer,59839,1 +83016,Female,42,Bachelors,17,33,84,17,26,6.0,3,71,Urban,Data Analyst,55845,0 +83017,Female,55,Diploma,7,27,60,18,71,6.0,4,46,Urban,ML Engineer,103963,0 +83018,Male,30,Bachelors,10,52,68,90,86,9.0,5,82,Rural,Manager,44135,1 +83019,Female,39,Diploma,7,58,48,66,66,1.0,0,30,Urban,Manager,99058,0 +83020,Male,28,Diploma,1,58,8,28,94,4.0,5,88,Urban,Manager,114740,0 +83021,Male,47,Masters,8,63,22,51,9,1.0,4,92,Urban,Software Engineer,120264,0 +83022,Female,22,Bachelors,19,36,48,40,4,5.0,2,86,Urban,HR Executive,32916,0 +83023,Male,28,Diploma,13,75,96,0,57,6.0,0,80,Urban,Data Analyst,56266,1 +83024,Male,50,Bachelors,0,71,84,85,13,9.0,3,10,Rural,Software Engineer,101761,1 +83025,Female,51,Bachelors,7,46,33,63,72,3.0,4,35,Semi-Urban,Data Analyst,22050,0 +83026,Female,40,Masters,15,58,7,56,39,8.0,3,30,Rural,Manager,88934,0 +83027,Male,34,High School,2,10,32,55,87,5.0,4,3,Urban,Data Analyst,78455,0 +83028,Male,47,Bachelors,11,28,58,46,67,1.0,0,22,Urban,ML Engineer,35688,0 +83029,Male,53,High School,8,26,88,30,21,3.0,2,2,Urban,Data Analyst,52962,0 +83030,Female,53,Masters,15,30,43,57,39,7.0,5,41,Urban,ML Engineer,108340,0 +83031,Female,35,High School,0,54,85,40,92,5.0,5,46,Urban,Data Analyst,144759,0 +83032,Male,45,Bachelors,7,41,3,78,14,9.0,6,12,Rural,Software Engineer,100824,0 +83033,Male,49,Bachelors,14,93,46,74,18,2.0,2,72,Urban,Software Engineer,78424,1 +83034,Female,41,Bachelors,15,96,48,97,37,6.0,2,12,Urban,Manager,106217,1 +83035,Female,33,High School,16,18,91,57,94,4.0,4,78,Urban,HR Executive,47986,1 +83036,Male,45,High School,17,10,1,56,73,3.0,6,94,Semi-Urban,Manager,125732,0 +83037,Male,57,Bachelors,2,73,1,47,31,7.0,2,8,Urban,ML Engineer,56032,0 +83038,Female,52,High School,17,83,75,59,79,3.0,5,14,Urban,Data Analyst,37148,0 +83039,Male,42,Bachelors,16,91,90,61,47,9.0,2,55,Semi-Urban,Data Analyst,66287,1 +83040,Female,48,Diploma,11,50,12,8,51,0.0,0,8,Urban,ML Engineer,34845,0 +83041,Male,50,Diploma,15,99,50,5,28,7.0,5,69,Semi-Urban,Manager,50096,0 +83042,Male,59,High School,16,61,91,41,93,7.0,0,26,Urban,Manager,131839,0 +83043,Female,42,Bachelors,5,4,13,31,74,8.0,4,85,Rural,Data Analyst,102600,0 +83044,Male,26,Bachelors,10,62,62,56,23,7.0,6,11,Urban,Software Engineer,69280,0 +83045,Female,49,Masters,0,14,91,54,5,0.0,7,17,Semi-Urban,Manager,83223,0 +83046,Male,53,Diploma,3,1,8,10,72,3.0,7,49,Urban,Manager,147876,0 +83047,Male,42,Diploma,3,87,50,52,28,9.0,3,36,Urban,Manager,42987,0 +83048,Male,45,Bachelors,10,18,15,48,77,2.0,0,24,Semi-Urban,HR Executive,35021,0 +83049,Other,33,Diploma,13,45,89,45,54,4.0,5,52,Semi-Urban,Software Engineer,53269,0 +83050,Female,44,PhD,14,96,54,69,25,1.0,2,35,Urban,Manager,30854,1 +83051,Male,30,Diploma,10,70,50,53,29,9.0,6,6,Urban,Data Analyst,131636,0 +83052,Male,47,Bachelors,8,60,98,81,54,2.0,5,1,Semi-Urban,Data Analyst,140947,1 +83053,Male,26,Masters,9,66,95,60,4,4.0,7,48,Urban,Manager,89770,1 +83054,Female,22,High School,1,22,29,37,21,3.0,4,4,Urban,Data Analyst,86278,0 +83055,Female,45,Diploma,12,11,41,93,54,5.0,1,14,Rural,Software Engineer,58741,0 +83056,Female,37,Bachelors,3,26,39,79,1,8.0,6,37,Urban,Manager,123464,0 +83057,Female,35,Bachelors,9,58,24,54,53,1.0,5,13,Urban,Software Engineer,84238,0 +83058,Female,49,Masters,17,55,50,21,79,6.0,2,76,Rural,Data Analyst,116688,0 +83059,Male,31,Masters,8,67,7,92,24,1.0,6,40,Rural,Manager,147550,0 +83060,Female,55,Bachelors,8,1,39,61,20,0.0,1,22,Urban,Data Analyst,55184,0 +83061,Male,56,Bachelors,18,30,81,87,68,7.0,6,41,Urban,Manager,106070,1 +83062,Male,47,Diploma,9,94,84,49,64,1.0,7,51,Urban,Software Engineer,30397,1 +83063,Female,35,Bachelors,7,2,57,82,71,5.0,1,28,Urban,HR Executive,25939,0 +83064,Other,55,Bachelors,0,26,5,83,83,0.0,5,18,Semi-Urban,Software Engineer,95272,0 +83065,Male,58,Masters,2,27,94,11,31,1.0,7,51,Semi-Urban,Data Analyst,112815,0 +83066,Male,39,Masters,4,96,92,85,24,4.0,5,48,Rural,Data Analyst,36913,1 +83067,Male,22,Bachelors,3,3,54,25,65,5.0,5,97,Urban,Manager,34943,0 +83068,Male,35,Bachelors,0,70,74,33,2,1.0,3,0,Urban,ML Engineer,97400,0 +83069,Female,33,Bachelors,17,72,92,46,54,0.0,2,67,Rural,Software Engineer,128985,1 +83070,Female,37,Masters,18,45,53,61,28,3.0,5,33,Rural,Data Analyst,37291,0 +83071,Other,57,Masters,6,78,40,54,76,4.0,3,12,Urban,Manager,113191,0 +83072,Female,23,Bachelors,8,5,88,86,13,3.0,4,0,Urban,Software Engineer,129486,0 +83073,Male,52,Bachelors,5,78,21,12,8,6.0,6,99,Urban,Data Analyst,50698,0 +83074,Male,39,High School,3,67,76,77,23,2.0,1,35,Semi-Urban,HR Executive,149208,1 +83075,Female,23,Bachelors,1,36,73,67,37,8.0,5,47,Rural,Data Analyst,130725,0 +83076,Female,50,Bachelors,7,72,59,86,86,4.0,6,69,Semi-Urban,Data Analyst,25553,1 +83077,Male,21,Diploma,8,18,56,24,28,3.0,0,86,Rural,HR Executive,60320,0 +83078,Male,38,Masters,11,86,19,3,32,2.0,6,29,Semi-Urban,Data Analyst,83006,0 +83079,Male,48,Bachelors,16,82,72,15,29,9.0,7,98,Urban,ML Engineer,106086,1 +83080,Male,56,Diploma,7,61,63,5,81,2.0,7,87,Rural,ML Engineer,128177,0 +83081,Male,24,Masters,9,21,4,18,62,8.0,7,27,Rural,Manager,127572,0 +83082,Male,52,Bachelors,12,25,5,36,51,2.0,2,24,Semi-Urban,Software Engineer,133144,0 +83083,Male,36,Bachelors,4,98,35,8,61,7.0,6,79,Urban,Software Engineer,33242,0 +83084,Male,40,Bachelors,3,95,0,99,68,6.0,7,8,Semi-Urban,Data Analyst,106063,0 +83085,Female,27,Bachelors,14,39,84,52,11,7.0,0,2,Urban,Manager,109028,0 +83086,Male,58,Bachelors,5,11,46,67,6,3.0,3,7,Urban,Software Engineer,53041,0 +83087,Male,36,Bachelors,2,26,60,51,69,8.0,2,55,Urban,Data Analyst,144319,0 +83088,Female,55,Diploma,10,13,16,56,18,1.0,3,22,Urban,HR Executive,41985,0 +83089,Male,26,Bachelors,16,94,11,77,81,7.0,1,90,Urban,Software Engineer,94597,1 +83090,Male,36,Bachelors,11,48,17,5,45,5.0,4,35,Urban,HR Executive,59900,0 +83091,Male,23,Diploma,18,42,67,68,29,9.0,0,5,Semi-Urban,ML Engineer,38966,0 +83092,Male,55,Masters,4,29,57,27,63,9.0,6,25,Rural,Manager,95017,0 +83093,Male,49,High School,1,27,53,16,43,8.0,2,79,Semi-Urban,ML Engineer,67149,0 +83094,Male,55,High School,8,93,8,25,50,2.0,1,85,Urban,Data Analyst,100484,0 +83095,Male,48,Bachelors,1,84,87,9,46,0.0,7,5,Urban,Manager,121231,0 +83096,Male,33,Diploma,14,29,73,19,56,0.0,2,32,Urban,HR Executive,72493,0 +83097,Female,24,Bachelors,8,9,92,45,68,8.0,2,78,Semi-Urban,Manager,108367,0 +83098,Female,52,Bachelors,9,45,66,7,36,2.0,2,51,Urban,Manager,101354,0 +83099,Male,40,Diploma,2,21,27,56,54,7.0,3,14,Semi-Urban,HR Executive,48049,0 +83100,Male,24,PhD,12,46,75,8,49,9.0,6,52,Rural,Manager,135994,0 +83101,Male,28,Diploma,8,19,52,23,87,8.0,6,44,Urban,HR Executive,50798,0 +83102,Female,50,Masters,3,17,46,63,27,6.0,6,85,Semi-Urban,ML Engineer,21754,0 +83103,Male,38,Bachelors,10,40,58,37,48,8.0,1,65,Urban,HR Executive,110906,0 +83104,Male,54,Masters,6,48,72,88,63,2.0,4,47,Semi-Urban,HR Executive,106433,1 +83105,Female,27,Diploma,13,94,59,42,57,1.0,3,24,Semi-Urban,ML Engineer,57145,0 +83106,Male,33,Masters,10,65,31,90,16,8.0,5,75,Semi-Urban,Manager,92580,1 +83107,Male,40,High School,9,87,60,44,26,7.0,6,92,Urban,HR Executive,142123,1 +83108,Male,47,PhD,12,71,56,49,74,0.0,2,33,Urban,Manager,48187,0 +83109,Female,29,Masters,2,72,88,11,36,0.0,5,8,Urban,Data Analyst,145199,0 +83110,Male,58,Masters,5,61,23,0,83,1.0,3,90,Urban,HR Executive,78321,0 +83111,Male,38,High School,5,0,36,68,2,6.0,0,11,Urban,Manager,62471,0 +83112,Female,25,Bachelors,12,68,4,28,22,4.0,6,59,Semi-Urban,Data Analyst,88911,0 +83113,Male,47,Bachelors,7,93,21,40,31,3.0,1,34,Rural,Software Engineer,95636,0 +83114,Male,30,Diploma,15,36,57,99,38,8.0,5,41,Rural,HR Executive,30848,0 +83115,Female,37,PhD,10,81,7,40,34,9.0,4,74,Urban,ML Engineer,143493,0 +83116,Male,35,Bachelors,3,94,24,74,11,4.0,1,32,Urban,Software Engineer,31550,0 +83117,Male,36,Diploma,13,22,32,10,55,7.0,7,34,Urban,Data Analyst,50424,0 +83118,Female,24,Masters,3,72,40,45,75,1.0,3,35,Rural,Software Engineer,111679,0 +83119,Male,41,Diploma,2,54,31,2,37,5.0,5,1,Semi-Urban,Manager,74236,0 +83120,Male,35,Diploma,18,53,34,88,60,4.0,3,0,Urban,Manager,105090,0 +83121,Female,59,Bachelors,14,35,99,30,91,2.0,5,67,Urban,Software Engineer,89536,0 +83122,Male,49,Bachelors,18,83,80,20,14,3.0,5,80,Semi-Urban,Data Analyst,87171,1 +83123,Male,54,Diploma,8,70,32,70,80,6.0,5,69,Rural,ML Engineer,139962,1 +83124,Male,46,Masters,9,31,71,41,66,5.0,1,83,Rural,HR Executive,51387,0 +83125,Male,28,Masters,0,99,90,56,67,0.0,7,65,Rural,ML Engineer,21674,1 +83126,Male,22,Diploma,8,40,59,41,3,0.0,4,85,Urban,Software Engineer,93477,0 +83127,Female,44,Masters,13,95,17,16,93,8.0,5,14,Rural,HR Executive,114186,0 +83128,Female,38,Bachelors,1,35,84,77,4,5.0,0,73,Semi-Urban,Data Analyst,80463,1 +83129,Female,38,Bachelors,17,90,50,62,97,1.0,7,61,Rural,ML Engineer,140205,1 +83130,Male,29,Bachelors,19,33,67,4,34,3.0,1,27,Urban,Software Engineer,68231,0 +83131,Male,34,Masters,4,9,29,99,10,8.0,1,46,Urban,Data Analyst,135991,0 +83132,Male,39,High School,13,30,27,49,63,4.0,3,6,Semi-Urban,Software Engineer,145863,0 +83133,Female,33,Masters,19,63,28,91,80,4.0,1,15,Urban,Software Engineer,98429,0 +83134,Male,34,Bachelors,1,37,58,82,5,9.0,1,29,Urban,ML Engineer,145070,0 +83135,Female,36,Diploma,19,69,23,1,56,1.0,3,68,Semi-Urban,Software Engineer,72303,0 +83136,Male,57,Diploma,9,22,77,16,25,9.0,7,85,Urban,Manager,76644,0 +83137,Male,21,Diploma,11,54,38,65,91,9.0,5,67,Semi-Urban,Data Analyst,54745,0 +83138,Male,47,Bachelors,8,94,29,34,86,0.0,6,34,Urban,HR Executive,141333,0 +83139,Male,21,Bachelors,9,31,8,74,94,7.0,7,31,Semi-Urban,Manager,111607,0 +83140,Female,39,Diploma,9,77,78,49,96,8.0,7,16,Urban,Data Analyst,119491,0 +83141,Male,49,Masters,17,84,76,97,40,2.0,5,86,Urban,Data Analyst,79164,1 +83142,Male,33,Bachelors,13,17,28,72,42,6.0,4,21,Urban,Manager,35414,0 +83143,Male,39,Masters,14,62,21,4,40,2.0,3,37,Urban,Manager,83251,0 +83144,Female,41,Diploma,11,68,96,59,48,2.0,2,27,Urban,Data Analyst,45887,1 +83145,Male,43,Bachelors,7,54,35,83,82,5.0,4,40,Urban,ML Engineer,139757,0 +83146,Female,46,Masters,2,79,75,6,76,2.0,1,22,Urban,Manager,121254,0 +83147,Female,49,Bachelors,0,69,31,79,67,8.0,5,82,Urban,Software Engineer,41334,1 +83148,Male,28,Diploma,7,28,31,46,22,5.0,7,66,Urban,Data Analyst,125378,0 +83149,Female,34,Bachelors,10,9,44,79,71,3.0,7,95,Semi-Urban,Manager,67352,0 +83150,Male,48,Diploma,0,17,77,13,59,4.0,7,87,Urban,Software Engineer,96855,0 +83151,Female,45,High School,18,73,73,78,4,7.0,1,71,Urban,Manager,91788,1 +83152,Male,38,Bachelors,17,92,40,99,39,6.0,0,12,Urban,ML Engineer,89938,1 +83153,Female,57,Masters,5,44,8,67,89,6.0,7,60,Rural,ML Engineer,84594,0 +83154,Male,24,Diploma,4,87,49,98,85,3.0,3,91,Rural,HR Executive,85099,1 +83155,Female,53,Bachelors,3,66,62,61,29,1.0,0,52,Rural,HR Executive,134733,1 +83156,Other,23,Bachelors,18,65,33,3,12,2.0,2,49,Urban,ML Engineer,77498,0 +83157,Female,45,Bachelors,0,56,93,52,5,0.0,5,59,Semi-Urban,Data Analyst,53816,1 +83158,Male,41,Diploma,8,65,13,90,42,0.0,1,29,Urban,Manager,54108,0 +83159,Male,25,Bachelors,13,96,59,72,12,5.0,3,70,Urban,Software Engineer,79094,1 +83160,Female,30,Diploma,4,33,77,68,38,5.0,5,82,Rural,Software Engineer,122460,1 +83161,Female,32,Masters,5,77,47,27,50,5.0,5,18,Rural,Manager,55206,0 +83162,Male,28,Bachelors,5,93,10,44,86,3.0,2,76,Semi-Urban,Manager,68479,0 +83163,Female,30,Diploma,12,91,84,32,42,5.0,6,92,Urban,ML Engineer,66093,1 +83164,Male,32,Bachelors,13,52,63,44,54,8.0,1,30,Semi-Urban,HR Executive,38888,0 +83165,Male,27,Bachelors,0,37,16,53,53,4.0,0,75,Urban,ML Engineer,103686,0 +83166,Male,46,Masters,9,28,33,3,51,3.0,0,44,Urban,Manager,79066,0 +83167,Male,31,Bachelors,7,23,9,88,41,9.0,1,6,Urban,Software Engineer,140948,0 +83168,Male,44,Diploma,1,74,44,3,51,2.0,6,46,Rural,Manager,56559,0 +83169,Female,52,Bachelors,19,82,42,88,54,2.0,1,73,Urban,Manager,64633,1 +83170,Male,44,Masters,5,69,76,57,53,1.0,7,48,Urban,HR Executive,91092,1 +83171,Female,40,Bachelors,2,27,56,51,86,4.0,3,45,Urban,HR Executive,129097,0 +83172,Female,33,Bachelors,3,22,77,85,5,6.0,6,14,Rural,ML Engineer,81782,0 +83173,Male,46,Bachelors,16,96,84,31,7,3.0,1,69,Urban,HR Executive,27576,1 +83174,Female,35,Bachelors,9,3,93,66,97,1.0,3,71,Semi-Urban,HR Executive,56892,0 +83175,Male,58,Bachelors,3,4,71,10,18,6.0,7,92,Urban,ML Engineer,34492,0 +83176,Male,34,Bachelors,16,10,41,66,22,8.0,7,70,Semi-Urban,Data Analyst,100668,0 +83177,Female,53,Bachelors,7,50,77,79,21,5.0,7,37,Urban,Software Engineer,131487,1 +83178,Female,48,Diploma,2,39,84,44,51,8.0,2,40,Rural,Data Analyst,113821,0 +83179,Other,37,High School,4,95,1,29,43,9.0,0,53,Urban,ML Engineer,56094,0 +83180,Female,51,Diploma,11,43,36,1,48,9.0,0,46,Urban,HR Executive,126467,0 +83181,Female,48,Diploma,1,80,28,63,43,8.0,5,49,Urban,Software Engineer,27176,0 +83182,Female,37,High School,17,76,16,31,63,2.0,7,21,Urban,Software Engineer,113647,0 +83183,Male,48,Masters,2,83,92,94,43,5.0,6,52,Semi-Urban,Data Analyst,97794,1 +83184,Male,25,Bachelors,17,19,55,21,56,0.0,6,43,Urban,Software Engineer,107046,0 +83185,Male,36,Diploma,7,84,62,95,97,9.0,3,98,Urban,HR Executive,75450,1 +83186,Male,40,PhD,6,65,52,67,95,3.0,7,52,Semi-Urban,Data Analyst,73413,1 +83187,Female,47,High School,16,15,52,35,31,3.0,5,3,Semi-Urban,HR Executive,120646,0 +83188,Male,36,PhD,2,13,31,93,15,4.0,5,56,Semi-Urban,Data Analyst,77580,0 +83189,Male,39,Bachelors,11,23,95,15,92,8.0,0,83,Urban,HR Executive,44142,0 +83190,Male,35,Bachelors,9,97,58,9,13,2.0,5,70,Urban,Software Engineer,147934,0 +83191,Female,48,Bachelors,17,23,89,11,22,4.0,6,20,Semi-Urban,Manager,137548,0 +83192,Female,25,Diploma,11,56,41,99,99,8.0,4,45,Rural,Manager,84143,1 +83193,Male,54,High School,3,6,6,33,31,0.0,4,77,Urban,Software Engineer,50562,0 +83194,Male,41,High School,15,88,33,22,95,7.0,2,61,Semi-Urban,Manager,67099,0 +83195,Female,34,Bachelors,9,75,60,11,20,3.0,2,3,Urban,Data Analyst,79050,0 +83196,Female,30,Diploma,5,32,8,24,53,2.0,6,9,Urban,HR Executive,59765,0 +83197,Female,26,Bachelors,4,25,75,42,58,9.0,2,31,Semi-Urban,ML Engineer,87480,0 +83198,Male,22,Masters,1,40,44,22,35,0.0,6,15,Urban,Data Analyst,92523,0 +83199,Male,29,Bachelors,14,4,38,68,75,5.0,4,96,Urban,ML Engineer,111668,0 +83200,Male,45,Masters,3,67,16,79,7,2.0,3,55,Urban,Data Analyst,99245,0 +83201,Female,54,PhD,19,15,33,35,49,1.0,0,62,Rural,Manager,34082,0 +83202,Female,51,PhD,7,32,62,32,12,5.0,0,22,Rural,HR Executive,34134,0 +83203,Female,34,Diploma,17,29,76,35,29,9.0,2,49,Rural,ML Engineer,137300,0 +83204,Male,23,Diploma,16,15,85,86,8,1.0,0,91,Rural,Data Analyst,79453,1 +83205,Male,53,Bachelors,17,90,90,53,23,3.0,4,4,Urban,ML Engineer,51455,1 +83206,Female,26,Bachelors,16,96,1,4,87,7.0,4,15,Rural,Software Engineer,46204,0 +83207,Male,22,Bachelors,7,75,5,11,90,1.0,4,47,Urban,Data Analyst,146628,0 +83208,Male,26,High School,7,24,99,55,86,0.0,6,76,Rural,Manager,36562,1 +83209,Male,21,Bachelors,17,15,79,95,21,3.0,3,91,Semi-Urban,Software Engineer,123884,1 +83210,Female,45,Masters,5,74,53,59,60,2.0,4,72,Urban,Data Analyst,69780,1 +83211,Female,45,Diploma,4,28,96,24,41,8.0,0,49,Rural,Software Engineer,53959,0 +83212,Male,54,High School,17,11,82,71,71,5.0,1,46,Semi-Urban,Data Analyst,133654,0 +83213,Male,47,Bachelors,3,21,55,89,15,7.0,2,34,Urban,Software Engineer,68920,0 +83214,Female,56,Bachelors,19,38,34,13,58,3.0,5,79,Rural,Manager,88820,0 +83215,Other,57,High School,7,24,45,36,67,3.0,1,40,Rural,Manager,97788,0 +83216,Female,47,High School,18,20,94,85,30,4.0,0,78,Semi-Urban,Manager,142149,1 +83217,Male,52,Masters,9,21,73,84,31,3.0,5,37,Urban,Data Analyst,65284,0 +83218,Male,46,Masters,5,93,56,74,58,5.0,2,26,Urban,HR Executive,125427,1 +83219,Male,33,Diploma,4,20,47,58,44,5.0,6,81,Urban,Software Engineer,87258,0 +83220,Male,22,Diploma,13,64,20,35,28,4.0,1,67,Rural,ML Engineer,146396,0 +83221,Male,57,Diploma,15,21,58,80,90,6.0,7,14,Urban,Software Engineer,44101,0 +83222,Female,25,Bachelors,14,16,49,10,12,5.0,0,98,Urban,ML Engineer,54596,0 +83223,Male,46,High School,1,54,18,77,81,4.0,1,9,Urban,ML Engineer,20661,0 +83224,Male,44,Masters,18,43,44,47,78,3.0,0,60,Urban,Manager,44909,0 +83225,Female,43,High School,19,59,28,44,88,2.0,1,10,Semi-Urban,HR Executive,122869,0 +83226,Female,50,Bachelors,7,42,34,46,44,4.0,1,40,Urban,HR Executive,79948,0 +83227,Female,48,PhD,1,97,64,65,68,2.0,0,11,Rural,ML Engineer,134082,0 +83228,Female,41,Bachelors,0,8,65,99,37,7.0,1,49,Urban,Manager,146020,0 +83229,Male,35,Diploma,0,86,58,91,32,4.0,7,39,Urban,Data Analyst,99388,1 +83230,Female,37,Bachelors,8,59,46,29,68,0.0,5,49,Rural,Manager,111456,0 +83231,Male,59,Diploma,0,78,79,13,82,9.0,5,66,Urban,ML Engineer,103963,1 +83232,Male,47,Bachelors,1,29,12,90,21,9.0,2,33,Rural,ML Engineer,30673,0 +83233,Male,55,PhD,10,31,63,29,47,0.0,1,2,Semi-Urban,Manager,98786,0 +83234,Male,33,Bachelors,13,77,21,52,81,5.0,7,19,Semi-Urban,Data Analyst,82879,0 +83235,Male,54,Masters,11,2,85,74,21,5.0,3,32,Rural,Manager,49581,0 +83236,Male,24,Bachelors,18,49,82,52,0,2.0,3,95,Urban,Software Engineer,84168,1 +83237,Female,30,Masters,0,99,71,72,45,3.0,1,44,Urban,Data Analyst,67714,1 +83238,Male,30,Masters,5,21,33,7,72,7.0,0,50,Rural,HR Executive,88153,0 +83239,Male,21,Bachelors,4,75,36,83,29,6.0,5,98,Urban,Data Analyst,144809,1 +83240,Female,30,Masters,1,38,35,75,62,7.0,4,84,Rural,HR Executive,143968,0 +83241,Male,25,Bachelors,3,19,51,16,52,2.0,1,72,Rural,HR Executive,83952,0 +83242,Male,59,Bachelors,9,75,76,92,4,9.0,7,4,Semi-Urban,ML Engineer,82275,1 +83243,Male,55,Bachelors,6,49,26,57,23,3.0,2,49,Rural,HR Executive,60388,0 +83244,Male,22,High School,13,62,14,3,2,0.0,7,45,Semi-Urban,Software Engineer,58117,0 +83245,Male,30,High School,17,67,90,35,24,6.0,5,29,Rural,Software Engineer,77015,0 +83246,Female,51,High School,5,46,34,76,9,4.0,6,0,Rural,Data Analyst,144764,0 +83247,Female,35,Bachelors,6,53,13,5,83,4.0,4,75,Rural,ML Engineer,147048,0 +83248,Female,29,Bachelors,7,42,15,2,13,4.0,5,90,Rural,Software Engineer,148604,0 +83249,Male,39,High School,14,20,70,54,47,5.0,6,31,Urban,Data Analyst,85207,0 +83250,Male,30,High School,0,88,87,68,98,9.0,2,26,Semi-Urban,Data Analyst,112217,1 +83251,Male,38,PhD,17,12,41,57,93,9.0,1,25,Urban,Manager,54018,0 +83252,Male,50,Bachelors,18,23,78,52,95,4.0,5,51,Rural,HR Executive,38329,0 +83253,Male,23,Masters,18,99,88,28,20,2.0,4,4,Rural,Data Analyst,73521,0 +83254,Male,50,High School,10,11,89,67,6,2.0,6,37,Semi-Urban,Software Engineer,84620,0 +83255,Female,45,Bachelors,1,52,78,89,85,7.0,0,4,Urban,Manager,137066,0 +83256,Male,40,Masters,19,47,72,42,59,5.0,2,23,Rural,ML Engineer,126398,0 +83257,Female,52,Bachelors,0,83,26,1,71,2.0,0,56,Urban,HR Executive,61529,0 +83258,Female,53,Bachelors,9,7,55,26,57,5.0,0,20,Urban,Data Analyst,50578,0 +83259,Other,24,Bachelors,7,67,66,3,94,3.0,0,99,Urban,Manager,138815,0 +83260,Other,41,High School,18,96,77,18,72,4.0,2,46,Semi-Urban,ML Engineer,110212,0 +83261,Female,44,Masters,7,4,89,81,26,0.0,2,81,Rural,Data Analyst,110103,1 +83262,Male,52,Bachelors,3,57,87,86,83,7.0,1,72,Semi-Urban,Manager,103865,1 +83263,Male,21,Bachelors,4,79,72,84,82,3.0,1,8,Urban,HR Executive,116456,1 +83264,Male,48,Masters,9,18,52,14,46,2.0,3,68,Urban,Manager,40167,0 +83265,Male,23,Masters,11,52,31,48,73,6.0,4,74,Semi-Urban,Manager,111892,0 +83266,Male,24,PhD,16,3,39,5,97,5.0,3,3,Semi-Urban,Manager,79470,0 +83267,Female,23,Bachelors,5,65,20,40,21,1.0,2,62,Urban,Software Engineer,74072,0 +83268,Male,25,Bachelors,14,57,42,58,80,6.0,5,95,Semi-Urban,Manager,149624,1 +83269,Female,27,Bachelors,19,73,16,0,65,5.0,0,85,Urban,Manager,128777,0 +83270,Male,28,Bachelors,12,24,81,77,91,7.0,7,80,Urban,HR Executive,79908,1 +83271,Female,42,Bachelors,15,4,95,32,48,9.0,1,10,Rural,ML Engineer,89860,0 +83272,Male,49,Bachelors,4,40,11,74,16,2.0,1,52,Semi-Urban,ML Engineer,109268,0 +83273,Male,31,Diploma,10,13,70,58,94,9.0,1,69,Semi-Urban,Software Engineer,127234,0 +83274,Male,37,Diploma,18,85,37,30,48,8.0,1,34,Urban,Data Analyst,47692,0 +83275,Male,43,PhD,9,54,95,48,5,4.0,1,13,Urban,ML Engineer,134522,0 +83276,Male,24,Diploma,15,51,6,34,78,4.0,4,25,Urban,Manager,86403,0 +83277,Female,46,High School,18,16,73,74,75,0.0,6,30,Semi-Urban,Software Engineer,55800,0 +83278,Male,27,Diploma,7,91,96,0,61,7.0,3,3,Rural,Data Analyst,103303,0 +83279,Male,34,Diploma,17,88,53,71,24,7.0,5,22,Urban,Data Analyst,98261,0 +83280,Male,41,Diploma,9,84,68,88,42,0.0,6,77,Semi-Urban,Data Analyst,88807,1 +83281,Female,42,Diploma,3,58,5,20,24,4.0,3,2,Urban,ML Engineer,106329,0 +83282,Male,38,Diploma,6,61,65,92,80,9.0,0,92,Urban,Manager,56674,1 +83283,Male,49,Diploma,18,88,4,0,53,7.0,6,25,Rural,Data Analyst,50232,0 +83284,Male,53,High School,18,42,49,35,79,1.0,6,39,Semi-Urban,ML Engineer,95742,0 +83285,Other,47,Diploma,9,54,31,98,71,8.0,6,93,Urban,Software Engineer,102709,1 +83286,Male,56,High School,10,92,41,3,41,3.0,4,72,Semi-Urban,Software Engineer,58035,0 +83287,Male,54,Masters,0,16,70,61,19,4.0,3,19,Urban,Data Analyst,74841,0 +83288,Female,23,Masters,2,79,81,59,78,4.0,2,41,Rural,Data Analyst,85947,1 +83289,Female,53,Diploma,13,92,26,49,12,0.0,3,66,Semi-Urban,HR Executive,72958,0 +83290,Female,52,High School,16,5,56,23,48,9.0,1,10,Urban,Software Engineer,45359,0 +83291,Male,55,Bachelors,12,39,77,92,47,3.0,6,95,Semi-Urban,Software Engineer,147081,1 +83292,Male,56,Bachelors,17,38,11,26,33,4.0,6,87,Urban,ML Engineer,103467,0 +83293,Male,56,Bachelors,6,59,81,84,97,4.0,4,20,Rural,Manager,20525,1 +83294,Male,54,Diploma,5,61,92,64,98,1.0,0,42,Rural,Software Engineer,90155,1 +83295,Other,26,Bachelors,15,37,3,76,17,8.0,6,28,Semi-Urban,Manager,142831,0 +83296,Male,51,High School,6,87,89,35,35,8.0,4,79,Rural,Manager,22689,1 +83297,Male,26,Bachelors,3,90,76,33,13,3.0,0,2,Urban,Manager,120808,0 +83298,Male,25,Bachelors,9,47,16,87,74,9.0,7,21,Semi-Urban,HR Executive,100682,0 +83299,Other,40,Diploma,11,33,60,15,18,6.0,4,57,Semi-Urban,Manager,147509,0 +83300,Male,38,Masters,18,36,13,10,60,8.0,6,50,Semi-Urban,Software Engineer,119201,0 +83301,Male,54,High School,15,94,41,45,48,1.0,1,7,Rural,Data Analyst,81942,0 +83302,Male,47,Diploma,13,67,85,9,12,6.0,3,33,Urban,Software Engineer,84887,0 +83303,Male,34,Bachelors,10,72,71,73,64,3.0,2,37,Urban,Software Engineer,113441,1 +83304,Female,33,Bachelors,16,47,58,48,86,3.0,3,38,Urban,ML Engineer,80085,0 +83305,Female,27,Bachelors,6,18,84,93,11,7.0,6,93,Urban,ML Engineer,125223,1 +83306,Male,24,High School,8,83,37,43,12,3.0,3,3,Semi-Urban,Data Analyst,112587,0 +83307,Female,45,High School,6,61,66,93,10,2.0,2,62,Urban,Software Engineer,106516,1 +83308,Female,54,Diploma,11,96,41,63,7,1.0,1,94,Urban,Software Engineer,86056,1 +83309,Female,59,High School,8,33,95,94,38,9.0,3,93,Semi-Urban,Manager,71144,1 +83310,Female,48,Diploma,11,82,16,41,8,3.0,4,44,Rural,Data Analyst,43885,0 +83311,Female,52,Bachelors,13,25,29,6,2,9.0,1,77,Urban,Software Engineer,37387,0 +83312,Male,50,High School,12,82,34,82,6,0.0,7,7,Semi-Urban,HR Executive,136043,0 +83313,Male,32,Bachelors,8,10,46,45,51,8.0,1,80,Urban,Software Engineer,31239,0 +83314,Male,48,High School,7,46,86,11,62,6.0,5,42,Semi-Urban,HR Executive,61264,0 +83315,Male,22,Diploma,7,63,63,62,1,7.0,6,96,Semi-Urban,Data Analyst,31089,1 +83316,Male,56,Masters,17,99,7,73,84,4.0,3,50,Semi-Urban,ML Engineer,111994,0 +83317,Female,30,High School,17,49,38,80,20,3.0,1,51,Urban,Data Analyst,137876,0 +83318,Male,33,Masters,4,42,7,44,50,2.0,5,79,Urban,HR Executive,66714,0 +83319,Female,28,Masters,15,17,74,31,87,3.0,4,6,Semi-Urban,Manager,86855,0 +83320,Male,39,Bachelors,7,71,85,25,56,1.0,3,26,Semi-Urban,ML Engineer,69201,0 +83321,Other,23,Bachelors,1,51,85,93,31,0.0,0,0,Semi-Urban,Software Engineer,120931,0 +83322,Male,21,Bachelors,3,51,19,76,41,5.0,6,96,Rural,ML Engineer,147441,1 +83323,Male,39,PhD,12,87,5,86,12,6.0,0,86,Semi-Urban,Manager,31998,1 +83324,Male,35,High School,7,69,66,54,12,8.0,1,58,Semi-Urban,Manager,45348,1 +83325,Male,53,Bachelors,3,1,61,96,94,8.0,7,70,Rural,HR Executive,76423,0 +83326,Female,45,High School,14,31,98,52,8,5.0,2,68,Urban,Software Engineer,87119,1 +83327,Female,37,Diploma,1,99,16,32,56,9.0,2,57,Semi-Urban,HR Executive,27489,0 +83328,Female,21,Diploma,8,46,51,18,23,6.0,7,30,Urban,Manager,35127,0 +83329,Male,41,Bachelors,5,79,64,61,52,0.0,1,79,Rural,Software Engineer,126807,1 +83330,Male,45,Bachelors,14,20,92,90,38,6.0,7,38,Semi-Urban,ML Engineer,105452,1 +83331,Female,34,Bachelors,13,42,82,75,92,2.0,4,60,Urban,Data Analyst,126386,1 +83332,Female,39,Bachelors,13,11,36,39,42,4.0,3,99,Semi-Urban,Software Engineer,119472,0 +83333,Other,22,Diploma,12,13,96,3,53,8.0,4,91,Urban,Software Engineer,95759,0 +83334,Female,45,Bachelors,19,89,24,15,73,0.0,4,71,Semi-Urban,ML Engineer,149212,0 +83335,Male,36,Diploma,0,40,69,23,3,9.0,1,31,Urban,Data Analyst,139165,0 +83336,Male,44,Diploma,6,98,97,77,29,6.0,0,81,Rural,Data Analyst,87283,1 +83337,Male,39,Diploma,13,51,8,62,28,0.0,7,21,Semi-Urban,HR Executive,49997,0 +83338,Male,57,Diploma,16,51,95,34,47,9.0,5,70,Urban,HR Executive,87693,1 +83339,Male,58,Bachelors,15,89,65,32,68,8.0,6,2,Urban,HR Executive,83992,0 +83340,Male,54,Diploma,4,44,52,6,87,7.0,2,77,Urban,HR Executive,88928,0 +83341,Male,29,Masters,12,80,89,76,37,8.0,2,57,Urban,HR Executive,31559,1 +83342,Female,50,High School,8,82,51,84,84,0.0,4,26,Rural,Software Engineer,129240,1 +83343,Male,25,High School,10,69,18,87,28,0.0,5,25,Urban,HR Executive,62319,0 +83344,Male,27,Bachelors,14,3,35,14,10,8.0,1,90,Urban,Software Engineer,144174,0 +83345,Female,37,Bachelors,7,52,47,3,73,2.0,3,0,Urban,Data Analyst,69266,0 +83346,Female,47,PhD,6,11,51,85,75,2.0,2,24,Urban,ML Engineer,138381,0 +83347,Male,38,Bachelors,4,34,13,41,69,0.0,2,65,Urban,Data Analyst,26427,0 +83348,Male,54,High School,14,29,54,42,33,9.0,3,33,Urban,HR Executive,148567,0 +83349,Male,37,Masters,10,55,26,5,4,3.0,5,5,Rural,Software Engineer,60302,0 +83350,Female,36,Masters,17,55,64,27,36,2.0,5,19,Urban,Manager,74828,0 +83351,Male,49,Bachelors,13,85,63,23,12,6.0,3,63,Rural,ML Engineer,75325,0 +83352,Male,33,Bachelors,9,31,96,14,68,8.0,5,38,Semi-Urban,Manager,29924,0 +83353,Female,27,Diploma,10,1,47,12,98,0.0,5,57,Rural,Manager,25179,0 +83354,Male,55,Masters,13,17,81,42,4,4.0,2,48,Rural,Data Analyst,64327,0 +83355,Female,58,Diploma,6,45,49,97,28,1.0,2,27,Rural,ML Engineer,51436,0 +83356,Female,46,Bachelors,6,29,81,38,29,4.0,4,19,Semi-Urban,HR Executive,93017,0 +83357,Male,41,Bachelors,1,76,75,32,13,5.0,2,3,Semi-Urban,Data Analyst,141490,0 +83358,Male,23,Masters,6,97,62,38,97,4.0,3,38,Urban,HR Executive,90125,1 +83359,Male,45,Bachelors,12,26,13,18,4,1.0,2,88,Rural,Software Engineer,117556,0 +83360,Male,29,Diploma,13,10,55,77,92,3.0,7,9,Urban,HR Executive,82049,0 +83361,Male,30,Masters,7,32,65,87,53,6.0,5,28,Urban,Data Analyst,90524,0 +83362,Other,57,Bachelors,0,10,2,46,92,0.0,3,56,Urban,ML Engineer,131136,0 +83363,Male,46,Bachelors,4,95,33,89,14,1.0,6,6,Semi-Urban,HR Executive,131647,0 +83364,Male,52,Bachelors,15,56,86,84,94,9.0,1,73,Urban,Data Analyst,130904,1 +83365,Male,34,High School,6,43,55,6,85,5.0,3,63,Urban,ML Engineer,94583,0 +83366,Male,42,Diploma,17,53,74,38,0,7.0,6,70,Urban,Manager,113542,1 +83367,Male,53,Bachelors,17,9,29,9,61,0.0,3,28,Semi-Urban,HR Executive,63999,0 +83368,Male,37,Masters,14,9,83,99,5,5.0,5,18,Urban,ML Engineer,84241,0 +83369,Male,54,Bachelors,12,81,50,25,74,0.0,4,40,Rural,Data Analyst,144153,0 +83370,Male,29,Bachelors,11,84,49,20,92,4.0,0,64,Urban,Software Engineer,66587,0 +83371,Male,28,PhD,19,84,70,88,92,9.0,2,81,Semi-Urban,HR Executive,86812,1 +83372,Male,58,Masters,8,85,63,21,38,7.0,1,88,Urban,ML Engineer,121873,1 +83373,Male,42,Masters,17,82,47,95,95,0.0,3,7,Urban,Software Engineer,33366,0 +83374,Female,41,Masters,0,81,92,37,55,7.0,2,15,Semi-Urban,Data Analyst,101773,0 +83375,Male,21,Bachelors,19,41,5,69,60,8.0,4,28,Urban,Software Engineer,25503,0 +83376,Female,22,Bachelors,0,79,51,11,94,4.0,7,1,Urban,Manager,20342,0 +83377,Male,35,High School,12,49,49,76,26,8.0,4,20,Rural,Manager,90559,0 +83378,Male,21,Bachelors,19,72,5,32,3,1.0,6,35,Urban,Manager,53214,0 +83379,Male,50,Diploma,18,51,64,69,40,2.0,3,5,Urban,ML Engineer,141138,0 +83380,Male,42,Bachelors,18,6,44,97,70,0.0,1,32,Urban,Data Analyst,57484,0 +83381,Male,36,Masters,13,44,87,86,42,1.0,7,80,Urban,ML Engineer,137803,1 +83382,Female,51,Diploma,10,39,24,8,0,3.0,2,43,Semi-Urban,Software Engineer,22082,0 +83383,Female,42,Bachelors,2,5,50,99,30,4.0,6,34,Urban,ML Engineer,57853,0 +83384,Male,41,Masters,13,70,28,24,2,1.0,7,59,Semi-Urban,ML Engineer,77340,0 +83385,Female,42,Diploma,1,16,55,52,56,9.0,0,51,Rural,Data Analyst,65296,0 +83386,Female,41,Diploma,3,32,39,97,56,3.0,3,15,Semi-Urban,Data Analyst,67319,0 +83387,Female,54,Bachelors,7,93,94,56,91,0.0,7,39,Urban,Data Analyst,73380,1 +83388,Male,50,Bachelors,7,77,44,51,4,6.0,4,25,Semi-Urban,Software Engineer,115245,0 +83389,Female,34,Diploma,18,6,64,42,61,7.0,6,49,Urban,ML Engineer,77406,0 +83390,Male,56,Diploma,4,86,28,89,14,7.0,5,79,Urban,HR Executive,31065,1 +83391,Male,33,Diploma,14,5,72,21,22,2.0,5,4,Rural,Software Engineer,131919,0 +83392,Female,28,Diploma,16,56,81,34,73,0.0,6,79,Rural,Manager,131717,1 +83393,Female,40,Bachelors,2,2,61,72,34,4.0,0,58,Urban,ML Engineer,34663,0 +83394,Male,56,Diploma,14,31,61,53,22,6.0,4,79,Urban,Manager,102667,0 +83395,Male,48,Bachelors,19,40,45,83,47,8.0,1,63,Semi-Urban,ML Engineer,33899,0 +83396,Male,30,PhD,10,50,15,37,44,4.0,6,46,Rural,Data Analyst,127705,0 +83397,Male,36,Bachelors,16,10,28,96,94,6.0,2,17,Urban,Manager,20717,0 +83398,Male,41,Diploma,5,0,35,65,39,0.0,3,72,Rural,Software Engineer,107193,0 +83399,Male,36,Masters,0,45,66,96,25,3.0,6,86,Urban,ML Engineer,90075,1 +83400,Female,47,Bachelors,14,41,27,77,60,0.0,7,7,Urban,Software Engineer,91486,0 +83401,Male,42,PhD,17,96,4,80,51,1.0,5,79,Urban,Data Analyst,34224,1 +83402,Male,44,Masters,16,82,54,27,85,4.0,2,25,Urban,ML Engineer,117724,0 +83403,Male,48,Masters,14,86,40,19,44,1.0,4,74,Semi-Urban,Data Analyst,133634,0 +83404,Female,53,Bachelors,19,80,10,4,75,7.0,0,97,Urban,ML Engineer,147847,0 +83405,Female,40,Bachelors,8,41,11,4,19,9.0,4,79,Urban,Manager,113826,0 +83406,Female,44,Bachelors,14,75,75,35,73,4.0,4,55,Rural,HR Executive,131709,0 +83407,Other,27,High School,2,34,58,71,31,8.0,6,52,Urban,Software Engineer,85323,0 +83408,Male,21,High School,7,16,66,45,8,6.0,0,34,Semi-Urban,ML Engineer,44692,0 +83409,Male,39,High School,2,93,25,29,17,5.0,1,94,Urban,ML Engineer,30105,1 +83410,Male,29,Masters,3,54,9,76,83,0.0,7,62,Urban,HR Executive,113851,0 +83411,Female,26,Diploma,7,57,19,12,27,8.0,0,8,Rural,HR Executive,81728,0 +83412,Male,27,Diploma,16,86,3,7,65,7.0,5,99,Urban,ML Engineer,92633,0 +83413,Female,26,PhD,16,8,63,44,39,3.0,5,70,Semi-Urban,Data Analyst,126665,0 +83414,,40,Masters,12,28,42,78,80,2.0,1,30,Urban,HR Executive,106519,0 +83415,Male,21,Diploma,7,11,38,96,46,6.0,4,36,Semi-Urban,Software Engineer,96897,0 +83416,Female,40,High School,3,40,21,37,41,5.0,5,89,Urban,Data Analyst,130794,0 +83417,Male,21,Bachelors,10,10,6,31,82,6.0,7,1,Semi-Urban,Software Engineer,34799,0 +83418,Female,33,Bachelors,3,91,7,9,52,5.0,5,10,Urban,Software Engineer,30935,0 +83419,Male,56,Bachelors,0,53,59,51,73,5.0,3,32,Rural,ML Engineer,145716,0 +83420,Female,27,Diploma,5,94,36,86,20,4.0,7,61,Rural,HR Executive,67188,1 +83421,Male,52,Bachelors,2,20,80,75,56,7.0,5,39,Semi-Urban,HR Executive,129038,0 +83422,Female,24,Diploma,12,15,19,20,99,7.0,7,6,Semi-Urban,HR Executive,114735,0 +83423,Male,25,PhD,7,30,94,46,34,2.0,2,42,Urban,Data Analyst,107509,0 +83424,Male,39,Masters,1,70,49,14,13,8.0,5,94,Urban,HR Executive,97562,0 +83425,Male,23,Diploma,16,29,22,75,24,7.0,7,12,Urban,Software Engineer,132534,0 +83426,Male,45,PhD,19,1,24,7,79,2.0,0,52,Urban,HR Executive,83912,0 +83427,Male,28,Diploma,3,81,54,20,45,4.0,4,19,Urban,Data Analyst,138832,0 +83428,Male,45,Bachelors,9,97,64,17,59,7.0,5,33,Semi-Urban,Software Engineer,71480,0 +83429,Male,56,Masters,6,35,23,88,2,7.0,1,17,Urban,ML Engineer,138151,0 +83430,Male,29,Diploma,4,66,39,99,56,6.0,6,14,Semi-Urban,ML Engineer,118952,0 +83431,Other,56,Bachelors,6,27,88,25,66,5.0,7,21,Urban,Data Analyst,32194,0 +83432,Male,31,Diploma,7,35,33,68,68,4.0,5,63,Urban,ML Engineer,48401,0 +83433,Male,54,Diploma,11,86,12,45,4,9.0,6,14,Urban,Software Engineer,50574,0 +83434,Male,51,Diploma,2,57,57,37,41,8.0,2,62,Rural,Manager,27204,0 +83435,Male,49,Bachelors,1,61,27,75,5,9.0,0,83,Rural,HR Executive,99812,1 +83436,Male,40,Masters,12,76,36,56,38,2.0,2,73,Rural,HR Executive,39428,1 +83437,Female,28,Bachelors,4,72,36,56,67,7.0,4,46,Urban,HR Executive,34057,0 +83438,Other,32,Masters,18,77,92,44,3,6.0,5,73,Urban,Software Engineer,41591,1 +83439,Female,25,Masters,13,69,53,6,14,8.0,3,19,Rural,ML Engineer,108083,0 +83440,Male,29,High School,13,17,88,61,94,6.0,3,8,Urban,HR Executive,91826,0 +83441,Male,36,Bachelors,18,19,88,62,88,1.0,3,50,Rural,HR Executive,130017,0 +83442,Male,56,Masters,15,30,75,56,31,0.0,3,55,Semi-Urban,Software Engineer,85217,0 +83443,Female,43,High School,2,51,22,76,6,8.0,5,70,Semi-Urban,Software Engineer,44140,0 +83444,Female,29,Bachelors,7,27,56,83,41,9.0,6,78,Semi-Urban,Software Engineer,133040,1 +83445,Female,56,Bachelors,6,11,28,91,60,3.0,7,57,Urban,Data Analyst,50026,0 +83446,Male,38,Bachelors,2,98,31,25,56,2.0,0,60,Urban,Software Engineer,50586,0 +83447,Female,24,Masters,6,6,93,55,55,8.0,7,88,Semi-Urban,ML Engineer,123171,1 +83448,Female,35,Bachelors,10,77,41,56,65,1.0,4,72,Urban,Software Engineer,135001,1 +83449,Male,26,Diploma,16,7,11,12,54,7.0,4,42,Semi-Urban,ML Engineer,148909,0 +83450,Female,34,Bachelors,15,76,24,77,17,9.0,3,34,Urban,Software Engineer,22162,0 +83451,Male,40,Bachelors,17,5,98,14,29,9.0,1,0,Urban,HR Executive,87908,0 +83452,Female,51,PhD,15,33,41,94,27,9.0,6,81,Semi-Urban,Data Analyst,34719,1 +83453,Female,24,Diploma,9,30,87,3,10,2.0,3,94,Urban,Data Analyst,121782,0 +83454,Male,34,High School,6,60,26,93,2,6.0,7,36,Urban,Data Analyst,36915,0 +83455,Female,44,High School,10,31,22,11,46,1.0,6,31,Semi-Urban,Manager,136532,0 +83456,Female,58,Diploma,10,17,69,81,7,7.0,5,65,Semi-Urban,HR Executive,78173,0 +83457,Male,26,PhD,0,41,67,11,66,0.0,3,81,Urban,HR Executive,129962,0 +83458,Female,33,Bachelors,8,81,49,13,95,7.0,5,45,Urban,HR Executive,119171,0 +83459,Male,21,High School,3,16,30,52,15,5.0,1,50,Rural,Data Analyst,57709,0 +83460,Male,24,Bachelors,3,58,62,96,80,5.0,6,44,Urban,ML Engineer,103024,1 +83461,Male,55,Masters,13,26,54,93,39,8.0,1,14,Semi-Urban,ML Engineer,23485,0 +83462,Male,56,Diploma,7,48,74,82,85,7.0,3,6,Rural,ML Engineer,129794,0 +83463,Female,53,Masters,3,35,60,56,20,8.0,6,21,Urban,Software Engineer,125323,0 +83464,Male,22,Masters,17,94,6,12,59,2.0,5,77,Semi-Urban,Data Analyst,128519,0 +83465,Female,45,Diploma,14,20,63,73,93,5.0,3,88,Urban,ML Engineer,87854,1 +83466,Male,40,Bachelors,16,45,24,75,51,7.0,5,76,Rural,HR Executive,129886,0 +83467,Male,39,High School,8,71,36,99,54,1.0,7,18,Urban,Software Engineer,88009,0 +83468,Male,30,Diploma,14,2,11,8,81,2.0,4,16,Rural,ML Engineer,61110,0 +83469,Female,31,Masters,7,11,17,67,61,2.0,5,85,Semi-Urban,Manager,83173,0 +83470,Female,23,Bachelors,5,65,16,65,77,8.0,7,64,Urban,Data Analyst,88792,0 +83471,Male,34,Diploma,19,67,53,23,20,3.0,7,30,Semi-Urban,Data Analyst,51549,0 +83472,Female,24,Bachelors,5,28,5,43,21,1.0,6,98,Urban,Manager,109416,0 +83473,Male,58,Bachelors,0,29,67,57,38,6.0,2,9,Urban,Data Analyst,102101,0 +83474,Female,41,Bachelors,14,38,34,22,60,5.0,2,16,Semi-Urban,Software Engineer,63518,0 +83475,Female,29,High School,3,52,41,51,58,1.0,3,65,Urban,Data Analyst,112683,0 +83476,Male,36,Bachelors,1,40,78,91,51,5.0,2,1,Semi-Urban,Data Analyst,20280,0 +83477,Female,50,Masters,14,43,90,28,85,5.0,2,60,Urban,Software Engineer,98266,0 +83478,Male,26,Masters,18,36,48,82,27,7.0,1,95,Semi-Urban,ML Engineer,61958,1 +83479,Female,55,High School,0,48,9,73,92,4.0,6,3,Urban,ML Engineer,22121,0 +83480,Female,28,Masters,12,12,52,24,48,4.0,7,24,Urban,ML Engineer,146451,0 +83481,Male,57,Masters,4,91,9,99,88,2.0,0,21,Semi-Urban,Data Analyst,56072,0 +83482,Male,52,Masters,4,42,4,93,96,8.0,4,15,Urban,HR Executive,142104,0 +83483,Other,31,High School,5,79,7,33,81,5.0,6,27,Semi-Urban,Software Engineer,140644,0 +83484,Male,35,Bachelors,12,76,45,94,53,7.0,5,50,Semi-Urban,HR Executive,38593,1 +83485,Female,26,Bachelors,2,67,8,96,20,7.0,1,22,Urban,Data Analyst,102057,0 +83486,Male,42,Bachelors,9,59,20,93,2,2.0,0,58,Urban,ML Engineer,114604,0 +83487,Female,45,Masters,8,69,82,45,97,9.0,7,38,Urban,Data Analyst,85096,0 +83488,Male,25,Bachelors,2,23,44,19,97,5.0,1,47,Urban,Data Analyst,20492,0 +83489,Male,36,Masters,1,39,72,90,51,6.0,2,59,Semi-Urban,ML Engineer,27954,1 +83490,Male,23,Bachelors,8,61,58,11,40,2.0,3,90,Rural,Manager,135867,0 +83491,Other,50,High School,11,55,27,64,93,6.0,2,99,Urban,ML Engineer,120519,1 +83492,Male,53,Bachelors,7,37,83,19,98,3.0,5,51,Rural,ML Engineer,61169,0 +83493,Male,37,High School,10,2,69,99,76,9.0,0,25,Urban,Manager,35854,0 +83494,Male,39,Bachelors,7,42,1,15,0,3.0,7,27,Urban,ML Engineer,117913,0 +83495,Female,56,Masters,8,85,52,99,17,1.0,1,69,Semi-Urban,ML Engineer,122165,1 +83496,Male,21,High School,0,27,76,14,57,1.0,5,39,Rural,Manager,91819,0 +83497,Male,53,High School,8,86,58,79,56,6.0,5,85,Urban,Software Engineer,24009,1 +83498,Male,36,High School,13,30,3,40,98,2.0,5,38,Semi-Urban,Software Engineer,71489,0 +83499,Male,50,Bachelors,6,17,12,91,74,1.0,4,14,Urban,Manager,136862,0 +83500,Male,25,High School,18,44,75,71,46,9.0,5,60,Semi-Urban,Software Engineer,85957,1 +83501,Male,44,Diploma,14,38,53,59,58,1.0,4,75,Semi-Urban,Software Engineer,83036,0 +83502,Male,54,High School,5,63,17,78,45,0.0,0,88,Semi-Urban,ML Engineer,97997,1 +83503,Male,46,Masters,4,55,41,95,62,0.0,3,56,Semi-Urban,Data Analyst,113260,1 +83504,Male,34,Bachelors,1,78,74,74,57,2.0,5,1,Urban,Software Engineer,95146,0 +83505,Male,35,High School,15,19,72,98,74,5.0,2,81,Rural,Manager,65775,1 +83506,Female,36,Masters,5,65,26,42,95,6.0,6,3,Semi-Urban,ML Engineer,56479,0 +83507,Female,50,High School,4,65,69,99,24,0.0,2,64,Semi-Urban,Manager,128638,1 +83508,Male,48,Bachelors,4,4,25,75,23,2.0,5,38,Urban,Software Engineer,41014,0 +83509,Female,27,Diploma,4,40,58,0,11,2.0,0,93,Urban,HR Executive,132550,0 +83510,Male,47,High School,13,77,38,20,12,8.0,5,61,Rural,Manager,63961,0 +83511,Male,31,Masters,19,36,16,99,67,8.0,3,30,Urban,Software Engineer,81848,0 +83512,Female,52,Bachelors,9,1,68,3,9,7.0,4,88,Rural,HR Executive,116583,0 +83513,Male,41,Masters,15,93,92,88,52,0.0,2,75,Urban,Manager,78377,1 +83514,Male,38,High School,7,65,51,16,33,1.0,1,62,Urban,Data Analyst,107003,0 +83515,Female,23,Bachelors,16,89,42,91,8,5.0,4,63,Semi-Urban,Manager,22357,1 +83516,Male,49,Bachelors,4,35,37,29,66,4.0,3,27,Urban,Software Engineer,96764,0 +83517,Male,34,High School,9,36,32,78,26,4.0,4,42,Urban,Software Engineer,33181,0 +83518,Female,45,Masters,8,74,30,50,80,5.0,7,13,Urban,ML Engineer,24927,0 +83519,Female,39,Diploma,11,71,13,57,64,1.0,6,15,Urban,Manager,39631,0 +83520,Male,37,Bachelors,5,71,36,78,92,0.0,2,34,Urban,Manager,47949,0 +83521,Male,37,Masters,2,78,32,22,77,9.0,5,39,Urban,Software Engineer,100232,0 +83522,Male,46,High School,7,78,84,80,83,6.0,4,9,Rural,HR Executive,113972,1 +83523,Female,48,Masters,11,58,1,19,44,7.0,6,98,Rural,Data Analyst,42541,0 +83524,Male,50,High School,5,49,65,66,26,8.0,2,5,Semi-Urban,ML Engineer,40692,0 +83525,Male,48,Diploma,13,87,47,0,32,5.0,5,73,Rural,HR Executive,57070,0 +83526,Male,35,High School,16,39,74,41,20,9.0,7,27,Urban,Data Analyst,79330,0 +83527,Female,37,Masters,18,10,19,9,41,0.0,2,88,Rural,HR Executive,137645,0 +83528,Female,29,High School,2,39,29,76,94,1.0,1,48,Urban,Data Analyst,78191,0 +83529,Male,48,Diploma,9,30,60,52,33,2.0,0,66,Rural,Manager,143211,0 +83530,Female,39,Bachelors,6,97,41,49,0,9.0,0,2,Rural,HR Executive,133605,0 +83531,Male,52,High School,19,61,69,45,82,3.0,7,55,Urban,HR Executive,86937,0 +83532,Female,29,Bachelors,2,12,59,9,48,0.0,7,33,Urban,ML Engineer,60774,0 +83533,Female,49,Diploma,9,12,24,86,18,9.0,0,38,Urban,ML Engineer,48714,0 +83534,Female,32,Bachelors,6,11,24,44,97,2.0,5,66,Semi-Urban,Software Engineer,107322,0 +83535,Female,56,Bachelors,11,12,49,59,48,0.0,0,70,Urban,ML Engineer,147861,0 +83536,Male,44,Masters,16,14,12,76,45,9.0,7,36,Urban,ML Engineer,145960,0 +83537,Male,58,Bachelors,9,33,46,15,82,7.0,7,51,Semi-Urban,HR Executive,73199,0 +83538,Female,25,PhD,1,33,73,55,54,2.0,6,84,Urban,HR Executive,71779,1 +83539,Male,53,High School,10,60,23,94,72,4.0,4,31,Rural,Data Analyst,42601,0 +83540,Male,24,Bachelors,3,56,51,72,79,6.0,7,19,Rural,Manager,104969,0 +83541,Male,27,Diploma,10,15,49,55,66,1.0,1,41,Rural,HR Executive,59710,0 +83542,Female,52,Masters,5,34,21,2,76,8.0,4,31,Urban,HR Executive,111422,0 +83543,Female,46,PhD,19,3,49,83,15,1.0,1,36,Urban,ML Engineer,31300,0 +83544,Male,23,Bachelors,17,44,53,47,39,1.0,5,44,Urban,Software Engineer,111838,0 +83545,Male,44,Bachelors,17,9,87,20,6,6.0,3,92,Urban,HR Executive,28155,0 +83546,Male,26,Diploma,3,41,32,10,92,6.0,0,71,Urban,HR Executive,125480,0 +83547,Male,55,Bachelors,0,73,32,28,41,9.0,1,69,Urban,HR Executive,57971,0 +83548,Female,50,Masters,16,58,30,89,15,0.0,7,29,Urban,Manager,82651,0 +83549,Male,49,Masters,3,32,56,18,67,1.0,1,13,Semi-Urban,Manager,135937,0 +83550,Male,29,Masters,12,11,34,55,1,7.0,6,65,Urban,Software Engineer,22090,0 +83551,Male,32,Bachelors,1,15,49,77,38,7.0,6,99,Urban,Manager,92607,1 +83552,Male,33,Bachelors,8,72,83,62,47,7.0,0,97,Urban,HR Executive,28352,1 +83553,Male,26,Diploma,6,27,66,6,21,1.0,1,54,Urban,HR Executive,59113,0 +83554,Other,49,High School,6,18,50,74,23,6.0,3,26,Urban,Software Engineer,115709,0 +83555,Female,41,Bachelors,11,59,64,96,35,6.0,3,38,Urban,Data Analyst,91384,1 +83556,Male,54,High School,2,82,43,30,93,2.0,1,58,Rural,Manager,130421,0 +83557,Male,56,High School,18,25,70,12,0,9.0,7,67,Urban,HR Executive,64721,0 +83558,Male,44,Diploma,8,18,0,92,42,8.0,5,17,Urban,HR Executive,124299,0 +83559,Female,31,Diploma,15,93,52,67,26,2.0,5,91,Urban,HR Executive,50001,1 +83560,Female,49,Masters,4,70,44,79,52,2.0,6,89,Semi-Urban,Manager,76128,1 +83561,Male,27,Masters,19,83,18,58,14,6.0,6,86,Urban,Data Analyst,92605,1 +83562,Male,44,Masters,6,93,19,73,57,3.0,7,20,Urban,Data Analyst,140583,0 +83563,Male,47,Diploma,18,87,31,41,32,3.0,5,1,Urban,ML Engineer,119221,0 +83564,Male,58,Masters,9,64,64,66,25,3.0,7,34,Urban,Software Engineer,92299,0 +83565,Male,46,Bachelors,10,90,12,10,53,8.0,3,36,Semi-Urban,ML Engineer,62941,0 +83566,Male,54,Bachelors,7,84,51,59,48,1.0,7,58,Urban,Manager,76741,1 +83567,Other,42,Diploma,1,28,19,44,5,5.0,3,9,Rural,Software Engineer,130479,0 +83568,Female,22,Bachelors,13,65,11,92,44,6.0,5,0,Urban,Manager,96960,0 +83569,Female,56,High School,3,88,90,37,15,2.0,0,65,Urban,Software Engineer,32517,1 +83570,Male,30,High School,15,59,39,93,28,0.0,1,24,Rural,Manager,59078,0 +83571,Female,51,Diploma,16,85,30,82,68,8.0,0,11,Urban,ML Engineer,37372,0 +83572,Female,31,Bachelors,18,20,88,33,89,1.0,4,12,Urban,HR Executive,51687,0 +83573,Male,59,Diploma,2,38,8,83,33,5.0,4,22,Urban,Software Engineer,95825,0 +83574,Female,43,High School,9,38,89,73,63,8.0,1,2,Rural,ML Engineer,93533,0 +83575,Male,24,Diploma,6,82,71,28,35,4.0,2,82,Urban,ML Engineer,111731,1 +83576,Other,27,High School,0,5,31,63,47,9.0,4,17,Urban,ML Engineer,91162,0 +83577,Male,47,Diploma,6,93,55,14,54,1.0,6,49,Urban,ML Engineer,126301,0 +83578,Male,56,Bachelors,17,7,42,11,73,7.0,4,65,Urban,Software Engineer,114472,0 +83579,Male,56,Bachelors,17,56,16,71,88,2.0,2,43,Rural,Data Analyst,90516,0 +83580,Male,47,Masters,3,34,88,16,48,4.0,1,10,Urban,Data Analyst,139488,0 +83581,Female,58,Masters,14,81,66,29,77,3.0,5,64,Semi-Urban,Software Engineer,147365,0 +83582,Male,45,Masters,19,14,56,21,57,0.0,4,62,Rural,Software Engineer,104897,0 +83583,Female,54,Masters,19,12,57,45,92,8.0,4,94,Urban,ML Engineer,96044,0 +83584,Female,36,Bachelors,8,37,72,48,86,6.0,4,62,Urban,Manager,42867,0 +83585,Female,46,Masters,16,27,14,95,55,4.0,0,60,Urban,ML Engineer,112202,0 +83586,Female,56,Bachelors,18,93,57,4,99,8.0,3,19,Semi-Urban,ML Engineer,43205,0 +83587,Other,23,Masters,16,36,78,38,87,0.0,7,63,Urban,Data Analyst,76771,0 +83588,Male,55,Diploma,2,84,72,30,74,5.0,5,55,Semi-Urban,HR Executive,29282,1 +83589,Other,56,Bachelors,17,87,78,76,81,5.0,1,46,Urban,Data Analyst,58998,1 +83590,Male,58,Bachelors,7,50,17,47,60,1.0,0,61,Rural,Software Engineer,50163,0 +83591,Male,49,Diploma,6,48,17,44,48,2.0,5,4,Urban,Manager,47166,0 +83592,Male,42,Bachelors,11,23,55,17,16,1.0,7,70,Urban,Data Analyst,99577,0 +83593,Female,51,Bachelors,4,59,89,48,6,9.0,3,29,Rural,Software Engineer,35414,0 +83594,Male,38,Bachelors,1,34,38,36,26,0.0,4,9,Urban,Data Analyst,22872,0 +83595,Male,36,High School,10,12,91,84,72,5.0,1,60,Urban,Software Engineer,46235,1 +83596,Female,29,High School,10,56,62,27,99,8.0,7,91,Urban,Software Engineer,132152,0 +83597,Male,49,Diploma,4,82,61,71,71,4.0,4,69,Semi-Urban,Data Analyst,85193,1 +83598,Male,22,Diploma,2,5,17,87,49,8.0,7,32,Rural,Data Analyst,51072,0 +83599,Male,26,Masters,4,57,30,63,1,7.0,6,14,Semi-Urban,Software Engineer,56123,0 +83600,Male,42,Bachelors,10,34,93,51,32,4.0,7,88,Rural,Software Engineer,41164,1 +83601,Male,28,Masters,19,72,97,63,35,1.0,3,53,Rural,Manager,71860,1 +83602,Male,23,Bachelors,4,61,24,23,29,2.0,1,28,Urban,Data Analyst,59630,0 +83603,Other,48,Bachelors,11,13,0,39,22,2.0,1,26,Semi-Urban,ML Engineer,99647,0 +83604,Female,48,Masters,4,12,8,94,99,7.0,6,80,Urban,Manager,80826,0 +83605,Male,23,Diploma,1,76,94,39,80,2.0,0,36,Urban,Data Analyst,29832,1 +83606,Male,59,High School,9,68,22,86,67,5.0,5,13,Semi-Urban,Software Engineer,92516,0 +83607,Female,22,Diploma,10,85,53,34,62,5.0,7,11,Urban,ML Engineer,51610,0 +83608,Male,36,Bachelors,11,14,96,75,1,9.0,5,4,Urban,ML Engineer,149256,0 +83609,Female,33,Bachelors,9,77,86,51,40,4.0,2,27,Rural,ML Engineer,41288,1 +83610,Male,50,Bachelors,9,32,56,11,35,3.0,6,39,Urban,Data Analyst,100671,0 +83611,Female,26,Bachelors,10,87,1,40,65,1.0,4,13,Urban,HR Executive,127931,0 +83612,Male,45,Bachelors,9,69,48,50,81,4.0,7,74,Urban,HR Executive,102817,1 +83613,Female,29,High School,13,34,27,60,63,0.0,2,48,Urban,Manager,141089,0 +83614,Female,33,Diploma,12,57,89,5,51,4.0,7,73,Rural,Manager,53225,0 +83615,Male,46,Masters,12,3,0,79,95,0.0,1,76,Urban,Data Analyst,76370,0 +83616,Male,21,High School,11,56,56,22,85,0.0,6,57,Semi-Urban,Software Engineer,133882,0 +83617,Male,58,High School,17,83,45,83,63,8.0,2,35,Urban,Data Analyst,67624,1 +83618,Female,55,Bachelors,1,67,56,45,43,8.0,7,83,Urban,ML Engineer,107050,1 +83619,Female,40,Bachelors,15,15,82,57,34,8.0,2,5,Semi-Urban,Software Engineer,91664,0 +83620,Male,48,Bachelors,14,14,92,13,18,5.0,6,45,Urban,HR Executive,95964,0 +83621,Female,33,Masters,11,63,20,26,40,0.0,1,14,Urban,ML Engineer,110994,0 +83622,Female,25,Masters,6,8,15,88,75,7.0,1,19,Rural,Data Analyst,147005,0 +83623,Male,37,Masters,15,50,27,34,9,3.0,7,99,Semi-Urban,Software Engineer,54079,0 +83624,Female,56,Bachelors,14,76,11,43,69,5.0,3,22,Urban,ML Engineer,62557,0 +83625,Male,46,Bachelors,12,82,35,75,26,4.0,2,92,Urban,Manager,50572,1 +83626,Male,29,Diploma,6,24,3,84,80,7.0,3,31,Urban,ML Engineer,78435,0 +83627,Female,38,Bachelors,15,7,54,15,35,5.0,7,27,Urban,Manager,86563,0 +83628,Male,24,High School,18,5,96,9,96,8.0,5,29,Semi-Urban,HR Executive,96935,0 +83629,Male,53,Masters,9,22,52,22,34,8.0,3,69,Semi-Urban,HR Executive,90134,0 +83630,Female,52,High School,4,58,75,1,64,0.0,6,72,Urban,Manager,48894,0 +83631,Male,58,Bachelors,3,86,57,55,26,4.0,7,69,Rural,Data Analyst,103918,1 +83632,Male,38,Bachelors,9,12,24,85,20,8.0,4,79,Urban,Data Analyst,144645,0 +83633,Male,45,High School,7,18,37,70,82,1.0,3,66,Urban,ML Engineer,121784,0 +83634,Male,58,Bachelors,17,15,93,75,51,9.0,1,51,Semi-Urban,Software Engineer,75281,0 +83635,Male,25,High School,15,14,9,61,59,4.0,1,90,Semi-Urban,Manager,39775,0 +83636,Female,52,Diploma,15,39,4,82,61,0.0,0,93,Rural,Manager,143627,0 +83637,Male,52,Bachelors,18,19,32,56,61,1.0,0,93,Semi-Urban,ML Engineer,66545,0 +83638,Female,53,Diploma,15,99,39,38,53,4.0,2,41,Rural,ML Engineer,58536,0 +83639,Male,37,Bachelors,7,37,16,98,81,4.0,3,25,Rural,HR Executive,148562,0 +83640,Male,53,Bachelors,12,39,94,12,91,2.0,5,78,Urban,Software Engineer,127263,0 +83641,Male,41,Bachelors,10,85,87,73,24,8.0,5,26,Urban,HR Executive,45762,1 +83642,Male,40,High School,10,77,60,42,53,5.0,3,89,Urban,Data Analyst,99263,1 +83643,Female,22,High School,12,37,99,49,35,3.0,4,21,Rural,Manager,93543,0 +83644,Male,35,High School,7,61,20,19,68,8.0,3,54,Urban,Manager,122934,0 +83645,Male,53,Bachelors,17,81,38,61,18,3.0,3,29,Urban,HR Executive,64859,0 +83646,Female,26,Bachelors,7,78,16,26,30,7.0,1,84,Urban,Data Analyst,102072,0 +83647,Female,49,Masters,11,87,91,39,70,0.0,3,17,Urban,Manager,149443,0 +83648,Male,26,Diploma,19,71,24,1,26,9.0,6,51,Semi-Urban,Manager,117289,0 +83649,Male,47,Diploma,8,60,63,89,73,3.0,6,93,Semi-Urban,HR Executive,99085,1 +83650,Male,55,PhD,19,67,50,22,95,0.0,0,45,Urban,Data Analyst,58382,0 +83651,Male,29,Masters,15,99,13,82,9,5.0,2,64,Semi-Urban,HR Executive,119621,1 +83652,Male,39,Bachelors,1,24,64,90,5,4.0,4,83,Rural,Data Analyst,113597,1 +83653,Female,46,Bachelors,4,55,89,40,40,2.0,3,60,Urban,ML Engineer,33212,1 +83654,Female,38,High School,18,9,7,71,75,5.0,2,34,Semi-Urban,Manager,33157,0 +83655,Male,36,Bachelors,16,59,97,81,16,9.0,1,32,Urban,Software Engineer,121155,1 +83656,Female,40,Bachelors,19,39,48,4,99,7.0,6,37,Rural,HR Executive,32305,0 +83657,Male,51,Diploma,12,13,81,5,51,0.0,0,90,Urban,ML Engineer,81172,0 +83658,Female,28,Bachelors,17,13,52,93,74,5.0,3,51,Urban,Software Engineer,96707,0 +83659,Female,43,Diploma,15,68,7,21,15,4.0,5,29,Urban,ML Engineer,76923,0 +83660,Male,48,Bachelors,14,50,53,33,47,6.0,1,32,Semi-Urban,Manager,46850,0 +83661,Male,39,Bachelors,0,8,85,89,99,9.0,7,60,Urban,Data Analyst,131397,1 +83662,Other,59,High School,10,25,4,44,82,1.0,1,93,Urban,ML Engineer,75093,0 +83663,Female,32,Diploma,15,7,73,5,80,5.0,4,44,Urban,HR Executive,100885,0 +83664,Male,36,Bachelors,7,50,29,29,74,8.0,5,68,Rural,Data Analyst,53669,0 +83665,Male,35,Bachelors,9,87,96,84,14,0.0,6,92,Urban,Manager,20878,1 +83666,Male,37,Masters,10,39,59,20,60,0.0,6,48,Rural,HR Executive,131304,0 +83667,Male,24,Diploma,0,58,72,1,36,8.0,7,38,Urban,Software Engineer,104189,0 +83668,Male,40,Bachelors,8,61,99,57,32,6.0,4,49,Urban,Software Engineer,141996,1 +83669,Female,30,Bachelors,10,3,58,11,21,3.0,0,70,Urban,Data Analyst,59043,0 +83670,Male,26,Bachelors,17,2,20,48,85,3.0,4,14,Urban,Manager,39891,0 +83671,Male,50,Bachelors,4,25,98,60,14,9.0,4,83,Urban,HR Executive,111663,1 +83672,Male,48,Bachelors,9,83,53,53,1,6.0,2,79,Semi-Urban,ML Engineer,104957,1 +83673,Male,22,Bachelors,13,96,81,44,44,8.0,7,68,Urban,ML Engineer,46992,1 +83674,Female,29,Bachelors,15,65,43,63,94,7.0,2,77,Rural,ML Engineer,58669,1 +83675,Female,49,Bachelors,16,60,6,25,89,1.0,1,46,Urban,ML Engineer,63666,0 +83676,Male,59,Diploma,4,17,66,31,85,6.0,3,64,Rural,ML Engineer,115208,0 +83677,Male,54,Bachelors,12,41,62,63,52,8.0,7,45,Semi-Urban,Manager,120043,0 +83678,Female,21,Bachelors,16,78,33,56,72,3.0,4,93,Urban,Software Engineer,141877,1 +83679,Female,51,Diploma,9,5,60,91,78,6.0,7,82,Semi-Urban,Software Engineer,103870,0 +83680,Male,31,Bachelors,4,27,17,86,41,0.0,1,45,Semi-Urban,HR Executive,49015,0 +83681,Male,40,Diploma,11,74,91,3,1,8.0,4,61,Urban,ML Engineer,81246,0 +83682,Female,33,Diploma,1,31,75,71,49,0.0,4,98,Urban,Manager,30952,1 +83683,Male,22,Bachelors,3,43,34,96,66,8.0,4,27,Urban,ML Engineer,120103,0 +83684,Male,42,Diploma,16,30,40,52,25,1.0,3,34,Urban,Software Engineer,143601,0 +83685,Male,45,Bachelors,1,37,15,27,63,5.0,4,13,Urban,Manager,113837,0 +83686,Male,43,Bachelors,9,0,72,21,69,8.0,0,32,Urban,ML Engineer,115398,0 +83687,Female,35,High School,10,84,53,37,40,9.0,6,38,Semi-Urban,HR Executive,51175,0 +83688,Female,50,Bachelors,13,7,75,88,37,0.0,4,16,Urban,Software Engineer,51400,0 +83689,Male,24,High School,0,89,10,16,69,5.0,0,33,Urban,ML Engineer,148590,0 +83690,Other,47,PhD,15,67,64,46,45,1.0,2,22,Urban,ML Engineer,142339,0 +83691,Male,33,Diploma,17,96,0,49,50,5.0,6,86,Rural,Data Analyst,109078,0 +83692,Male,34,Masters,2,6,31,41,48,4.0,6,89,Semi-Urban,Manager,31880,0 +83693,Male,34,Bachelors,2,44,78,96,43,2.0,7,44,Urban,ML Engineer,27054,1 +83694,Female,44,High School,9,62,4,87,47,2.0,2,33,Rural,Manager,66548,0 +83695,Male,59,Bachelors,15,18,79,79,40,2.0,6,29,Urban,Data Analyst,74721,0 +83696,Female,56,Masters,11,12,25,96,63,9.0,2,87,Urban,HR Executive,109729,0 +83697,Male,44,Masters,18,77,52,54,82,8.0,2,76,Semi-Urban,Data Analyst,117896,1 +83698,Female,23,Diploma,2,27,41,7,4,2.0,4,31,Semi-Urban,Software Engineer,114025,0 +83699,Female,57,Bachelors,5,93,37,45,84,5.0,2,90,Semi-Urban,HR Executive,84640,1 +83700,Female,38,Diploma,17,58,90,7,43,3.0,7,65,Semi-Urban,ML Engineer,65792,0 +83701,Male,36,Bachelors,12,63,18,51,4,3.0,6,38,Rural,Data Analyst,29532,0 +83702,Female,45,High School,10,28,44,22,72,6.0,3,3,Urban,ML Engineer,115649,0 +83703,Male,54,Bachelors,4,57,25,78,13,9.0,0,15,Rural,ML Engineer,67814,0 +83704,Female,27,High School,9,97,90,41,12,7.0,4,73,Urban,ML Engineer,34593,1 +83705,Female,38,Bachelors,14,69,48,24,96,3.0,6,27,Semi-Urban,Software Engineer,114766,0 +83706,Male,46,Diploma,3,60,98,73,29,0.0,4,65,Semi-Urban,HR Executive,94004,1 +83707,Male,47,Diploma,16,2,52,85,20,4.0,2,0,Urban,Manager,41297,0 +83708,Male,55,Diploma,7,52,21,0,71,8.0,2,26,Urban,ML Engineer,123994,0 +83709,Male,45,Bachelors,5,33,71,94,1,9.0,5,88,Semi-Urban,Manager,77675,1 +83710,Female,41,Bachelors,13,50,46,72,48,1.0,6,75,Urban,Software Engineer,43149,1 +83711,Female,46,Diploma,10,53,22,75,3,2.0,1,5,Urban,Manager,22259,0 +83712,Female,22,Masters,15,5,5,31,82,1.0,2,41,Urban,Software Engineer,84197,0 +83713,Male,48,Bachelors,18,78,5,93,17,7.0,2,83,Semi-Urban,ML Engineer,147396,1 +83714,Other,37,High School,18,2,79,5,66,3.0,0,80,Semi-Urban,Manager,33423,0 +83715,Male,59,Diploma,8,21,1,37,5,3.0,7,57,Rural,HR Executive,22693,0 +83716,Male,44,Bachelors,18,35,53,55,29,2.0,6,69,Semi-Urban,Software Engineer,98627,0 +83717,Female,49,Bachelors,13,86,1,38,52,7.0,7,29,Rural,Software Engineer,108021,0 +83718,Male,37,PhD,15,41,64,61,5,0.0,6,39,Urban,ML Engineer,59769,0 +83719,Other,59,High School,17,43,55,32,27,4.0,1,2,Urban,Manager,129611,0 +83720,Female,31,High School,14,56,61,92,38,9.0,2,21,Semi-Urban,ML Engineer,123888,0 +83721,Female,37,PhD,12,47,75,48,92,8.0,7,44,Semi-Urban,Data Analyst,111034,0 +83722,Male,55,Bachelors,7,96,41,61,60,1.0,4,15,Urban,ML Engineer,135830,0 +83723,Male,30,Bachelors,13,1,29,20,37,1.0,4,43,Urban,Software Engineer,87788,0 +83724,Female,59,Diploma,15,99,52,65,48,9.0,5,37,Semi-Urban,HR Executive,135169,1 +83725,Male,38,Bachelors,0,45,92,97,98,9.0,4,41,Urban,HR Executive,101645,1 +83726,Female,53,High School,5,88,67,25,29,0.0,7,54,Rural,HR Executive,131677,0 +83727,Female,52,Diploma,15,15,19,36,43,5.0,0,29,Semi-Urban,Software Engineer,110318,0 +83728,Female,30,Masters,16,73,45,36,19,5.0,4,70,Urban,Manager,123230,0 +83729,Male,58,Bachelors,2,0,88,46,88,3.0,5,78,Semi-Urban,Data Analyst,67197,0 +83730,Female,37,Bachelors,0,35,26,31,0,0.0,3,90,Urban,ML Engineer,127253,0 +83731,Female,23,Masters,2,62,1,59,10,6.0,5,64,Urban,HR Executive,88394,0 +83732,Female,57,Diploma,9,22,51,58,91,1.0,4,31,Urban,Data Analyst,72081,0 +83733,Female,28,Bachelors,8,7,91,24,6,9.0,5,41,Semi-Urban,ML Engineer,149522,0 +83734,Female,37,Bachelors,8,83,92,92,35,5.0,7,44,Rural,Manager,133205,1 +83735,Male,27,Bachelors,17,95,35,70,82,1.0,0,82,Urban,Software Engineer,76606,1 +83736,Female,44,Bachelors,15,86,81,88,0,9.0,1,12,Urban,HR Executive,134057,1 +83737,Male,29,High School,2,78,26,72,46,3.0,7,47,Rural,ML Engineer,86150,0 +83738,Male,27,Masters,18,65,90,81,89,4.0,6,64,Semi-Urban,Manager,29910,1 +83739,Female,39,Bachelors,17,71,23,53,70,2.0,0,56,Urban,Software Engineer,72340,0 +83740,Female,32,Bachelors,9,18,36,56,77,8.0,4,23,Semi-Urban,Manager,58293,0 +83741,Male,29,PhD,17,59,33,40,81,2.0,1,21,Semi-Urban,Data Analyst,37802,0 +83742,Male,32,Diploma,16,10,50,96,84,5.0,7,17,Urban,ML Engineer,36168,0 +83743,Female,53,Bachelors,18,79,25,46,33,4.0,0,26,Rural,HR Executive,28098,0 +83744,Male,57,Bachelors,19,26,69,47,29,8.0,6,0,Semi-Urban,Software Engineer,62753,0 +83745,Female,42,Masters,13,6,42,86,7,7.0,7,68,Semi-Urban,ML Engineer,67012,0 +83746,Female,58,Diploma,17,53,63,10,77,0.0,2,4,Rural,Software Engineer,31485,0 +83747,Female,47,Bachelors,13,92,35,86,26,9.0,6,1,Rural,Software Engineer,54210,0 +83748,Male,39,Diploma,0,67,45,5,15,6.0,5,73,Urban,HR Executive,97052,0 +83749,Male,43,Diploma,3,41,93,56,30,2.0,2,25,Urban,HR Executive,131180,0 +83750,Male,54,Diploma,12,98,21,14,3,2.0,2,18,Urban,Software Engineer,57428,0 +83751,Male,21,High School,15,33,1,15,74,0.0,1,58,Urban,Software Engineer,23420,0 +83752,Male,25,Bachelors,16,26,98,35,15,0.0,6,83,Urban,Software Engineer,46099,1 +83753,Male,22,Masters,14,23,94,56,42,7.0,2,81,Rural,Data Analyst,133792,1 +83754,Other,42,High School,17,50,66,31,43,6.0,1,89,Semi-Urban,HR Executive,26281,0 +83755,Female,33,Bachelors,12,8,5,58,91,0.0,4,73,Urban,Software Engineer,99144,0 +83756,Male,33,Diploma,17,65,36,93,41,0.0,5,70,Rural,HR Executive,139430,1 +83757,Male,24,PhD,16,78,48,89,8,1.0,2,32,Rural,HR Executive,74512,1 +83758,Female,40,Diploma,3,35,57,56,45,5.0,0,13,Urban,Manager,38459,0 +83759,Female,37,Bachelors,7,51,38,40,13,0.0,1,23,Urban,Data Analyst,44043,0 +83760,Male,51,High School,13,47,76,52,41,1.0,1,13,Urban,Manager,107043,0 +83761,Female,56,High School,11,21,10,20,55,7.0,5,79,Urban,ML Engineer,121767,0 +83762,Male,24,High School,10,2,45,31,7,9.0,6,70,Urban,Manager,38321,0 +83763,Male,27,Bachelors,11,14,80,9,24,4.0,4,23,Semi-Urban,ML Engineer,20613,0 +83764,Female,53,Diploma,0,84,95,65,56,7.0,0,21,Urban,Manager,76784,1 +83765,Male,24,PhD,19,51,84,3,17,0.0,0,72,Rural,Data Analyst,70674,0 +83766,Female,46,Bachelors,17,48,28,67,1,3.0,7,97,Urban,HR Executive,148815,0 +83767,Male,26,Bachelors,13,15,41,95,98,0.0,5,74,Urban,Data Analyst,110671,0 +83768,Male,41,High School,17,59,73,48,90,2.0,7,4,Urban,HR Executive,52963,0 +83769,Male,54,Diploma,15,87,11,78,77,8.0,0,92,Rural,ML Engineer,132212,1 +83770,Male,46,Bachelors,3,63,8,86,28,9.0,3,34,Semi-Urban,Software Engineer,52715,0 +83771,Male,27,High School,6,65,9,71,8,4.0,7,61,Urban,HR Executive,45699,0 +83772,Male,45,Diploma,9,54,54,30,33,0.0,5,61,Urban,HR Executive,99622,0 +83773,Male,35,PhD,15,78,19,44,11,9.0,0,71,Urban,HR Executive,32819,0 +83774,Male,48,Bachelors,12,25,64,69,0,6.0,1,84,Urban,HR Executive,71183,1 +83775,Male,41,High School,18,61,36,73,43,5.0,7,33,Urban,HR Executive,125547,0 +83776,Female,56,Bachelors,9,91,68,34,55,0.0,0,94,Urban,HR Executive,29706,1 +83777,Female,56,Masters,19,66,58,21,79,7.0,1,81,Urban,Data Analyst,87027,0 +83778,Male,22,Diploma,2,3,62,68,94,7.0,1,54,Urban,ML Engineer,91407,0 +83779,Male,50,Diploma,13,24,89,61,30,4.0,2,52,Urban,Software Engineer,41154,0 +83780,Male,39,Bachelors,0,78,36,29,39,9.0,6,88,Semi-Urban,ML Engineer,130566,0 +83781,Male,25,Bachelors,0,91,70,44,25,8.0,2,45,Urban,Software Engineer,24336,1 +83782,Male,29,High School,4,33,5,22,12,2.0,2,52,Urban,Software Engineer,73329,0 +83783,Other,35,Diploma,5,38,9,58,81,2.0,4,90,Rural,HR Executive,79603,0 +83784,Female,28,Bachelors,15,70,1,69,74,2.0,6,23,Rural,HR Executive,54779,0 +83785,Female,42,Masters,4,17,83,38,67,0.0,5,66,Rural,Data Analyst,28018,0 +83786,Male,50,Bachelors,15,82,22,83,72,2.0,7,55,Urban,ML Engineer,69399,1 +83787,Male,56,Bachelors,2,85,32,81,39,1.0,2,12,Urban,Software Engineer,123310,0 +83788,Male,22,Bachelors,13,27,47,50,97,1.0,4,83,Urban,Software Engineer,115798,0 +83789,Female,53,High School,11,28,86,59,34,1.0,7,37,Rural,Manager,144435,0 +83790,Female,51,High School,5,32,41,28,20,3.0,7,10,Urban,Manager,46462,0 +83791,Male,59,Bachelors,5,85,27,85,33,5.0,1,73,Urban,Data Analyst,21757,1 +83792,Male,46,Bachelors,3,3,16,74,36,5.0,5,20,Semi-Urban,Data Analyst,137167,0 +83793,Male,25,Bachelors,6,73,32,15,62,4.0,5,46,Urban,Data Analyst,145181,0 +83794,Female,48,Bachelors,18,93,10,73,99,5.0,2,61,Urban,Manager,54269,0 +83795,Male,27,Bachelors,18,90,97,45,85,1.0,3,16,Semi-Urban,ML Engineer,61109,1 +83796,Male,52,Bachelors,18,55,94,43,68,0.0,0,41,Urban,ML Engineer,99361,0 +83797,Female,31,Diploma,19,76,20,18,15,5.0,1,26,Semi-Urban,ML Engineer,21020,0 +83798,Female,47,Masters,7,59,64,81,35,5.0,4,1,Urban,HR Executive,115014,0 +83799,Male,34,Diploma,18,75,19,58,13,0.0,4,87,Semi-Urban,Software Engineer,84194,1 +83800,Female,27,Masters,13,1,87,13,77,6.0,3,76,Rural,ML Engineer,58927,0 +83801,Male,46,Bachelors,11,65,83,69,41,7.0,0,59,Semi-Urban,Manager,33145,1 +83802,Male,29,Bachelors,0,75,63,45,23,7.0,0,57,Urban,Data Analyst,114447,1 +83803,Male,43,Diploma,15,61,86,27,18,5.0,3,29,Rural,HR Executive,123498,0 +83804,Female,46,Bachelors,8,75,95,5,48,1.0,0,45,Rural,Software Engineer,53866,0 +83805,Male,36,Bachelors,16,63,47,86,77,1.0,7,83,Urban,HR Executive,60845,1 +83806,Male,35,Masters,0,39,93,62,77,0.0,1,76,Urban,Software Engineer,111290,1 +83807,Female,48,Diploma,16,35,99,56,4,7.0,4,50,Urban,Manager,112945,0 +83808,Female,48,Bachelors,6,49,70,58,90,2.0,2,91,Rural,HR Executive,26684,1 +83809,Female,49,Masters,5,81,89,93,19,7.0,5,20,Urban,HR Executive,73844,1 +83810,Male,27,Bachelors,14,85,65,67,29,6.0,6,48,Semi-Urban,Software Engineer,84309,1 +83811,Female,21,Bachelors,9,58,50,91,23,0.0,4,63,Urban,Software Engineer,127549,1 +83812,Male,22,High School,19,55,60,47,12,2.0,6,67,Urban,Software Engineer,23650,0 +83813,Male,37,Masters,17,60,3,0,7,8.0,4,22,Urban,ML Engineer,60182,0 +83814,Female,39,High School,1,22,50,35,79,3.0,3,69,Semi-Urban,Manager,61730,0 +83815,Female,28,Bachelors,1,21,62,79,59,2.0,3,8,Urban,ML Engineer,131693,0 +83816,Female,26,Bachelors,2,8,82,79,57,7.0,7,6,Urban,Data Analyst,26094,0 +83817,Male,26,Bachelors,12,20,32,49,0,8.0,2,26,Urban,Data Analyst,127450,0 +83818,Male,30,Bachelors,18,1,52,73,37,5.0,6,69,Urban,ML Engineer,132139,0 +83819,Other,23,Masters,10,12,29,89,64,4.0,5,21,Semi-Urban,Software Engineer,70180,0 +83820,Male,39,Masters,1,52,80,47,34,2.0,6,76,Urban,HR Executive,122097,1 +83821,Male,41,Diploma,19,3,42,38,10,7.0,6,2,Urban,HR Executive,74728,0 +83822,Male,23,Masters,18,11,98,56,9,4.0,2,57,Urban,ML Engineer,53604,0 +83823,Male,57,Bachelors,11,23,14,46,81,5.0,3,16,Rural,ML Engineer,42023,0 +83824,Female,32,Bachelors,19,35,99,1,4,2.0,5,66,Urban,Data Analyst,26829,0 +83825,Male,43,Diploma,9,62,74,53,42,5.0,5,89,Rural,HR Executive,144937,1 +83826,Male,49,Masters,11,2,30,30,1,2.0,1,49,Urban,HR Executive,137364,0 +83827,Male,30,High School,4,24,74,53,98,4.0,2,99,Urban,HR Executive,122707,1 +83828,Female,48,Bachelors,10,71,2,16,92,6.0,6,43,Urban,Data Analyst,138435,0 +83829,Male,49,Bachelors,1,22,23,22,57,6.0,1,40,Urban,ML Engineer,137092,0 +83830,Male,26,Masters,9,61,25,88,78,6.0,5,62,Urban,ML Engineer,24284,1 +83831,Female,47,High School,16,71,43,10,56,4.0,2,24,Urban,Software Engineer,63637,0 +83832,,40,Diploma,9,97,79,94,17,3.0,7,98,Urban,HR Executive,82783,1 +83833,Female,54,Bachelors,5,63,42,74,31,7.0,1,60,Urban,Data Analyst,112246,0 +83834,Other,53,Masters,6,51,60,48,83,3.0,2,10,Semi-Urban,Manager,93364,0 +83835,Female,54,Bachelors,3,24,28,19,1,7.0,7,98,Urban,Software Engineer,68071,0 +83836,Female,35,High School,16,33,39,97,70,3.0,0,35,Semi-Urban,Manager,109948,0 +83837,Male,52,Bachelors,4,51,91,78,75,5.0,4,25,Urban,HR Executive,107319,1 +83838,Female,22,Diploma,0,47,78,90,46,8.0,1,50,Rural,Manager,105674,1 +83839,Male,22,PhD,19,45,66,37,17,7.0,3,95,Urban,Manager,77803,1 +83840,Female,47,Masters,11,89,35,57,49,0.0,1,78,Rural,HR Executive,20179,1 +83841,Female,48,Bachelors,14,88,1,3,0,7.0,6,12,Semi-Urban,Data Analyst,47945,0 +83842,Male,22,High School,3,23,70,3,23,2.0,2,35,Urban,Data Analyst,44409,0 +83843,Male,23,Bachelors,6,36,28,42,85,6.0,1,3,Semi-Urban,ML Engineer,59587,0 +83844,Female,42,Bachelors,1,28,2,79,35,0.0,7,54,Semi-Urban,ML Engineer,66954,0 +83845,Male,42,Diploma,11,93,17,30,45,8.0,5,15,Semi-Urban,Data Analyst,61261,0 +83846,Male,45,High School,19,47,39,61,79,1.0,1,78,Urban,Software Engineer,136267,0 +83847,Male,53,Bachelors,11,2,48,39,70,9.0,5,73,Semi-Urban,ML Engineer,52505,0 +83848,Female,51,Bachelors,1,54,68,65,83,8.0,0,98,Urban,Data Analyst,37658,1 +83849,Male,48,Bachelors,2,6,91,93,43,7.0,7,59,Urban,ML Engineer,148267,1 +83850,Male,21,High School,1,46,91,71,46,1.0,2,12,Urban,Manager,141598,0 +83851,Female,38,Bachelors,7,85,97,73,83,6.0,2,10,Semi-Urban,ML Engineer,68267,1 +83852,Male,46,Bachelors,0,48,82,78,29,3.0,3,95,Rural,Manager,53001,1 +83853,Female,36,Bachelors,7,21,43,31,92,8.0,6,23,Urban,HR Executive,88298,0 +83854,Female,50,Diploma,10,88,13,40,29,9.0,0,60,Semi-Urban,Manager,126544,0 +83855,Male,21,Bachelors,2,31,59,96,26,9.0,3,75,Urban,Software Engineer,143768,1 +83856,Female,21,Diploma,6,93,1,82,44,8.0,4,77,Urban,HR Executive,26917,1 +83857,Male,38,Masters,0,21,46,95,4,4.0,4,38,Semi-Urban,Data Analyst,149053,0 +83858,Male,29,Bachelors,15,43,39,96,50,5.0,4,38,Urban,Data Analyst,76287,0 +83859,Female,47,High School,1,34,26,45,7,2.0,7,77,Urban,HR Executive,98188,0 +83860,Female,39,Bachelors,2,44,19,90,78,1.0,3,98,Urban,HR Executive,106429,1 +83861,Male,22,Masters,5,66,24,21,1,3.0,7,81,Semi-Urban,Manager,149934,0 +83862,Male,28,PhD,11,3,2,94,4,5.0,1,98,Semi-Urban,HR Executive,145954,0 +83863,Male,49,Bachelors,6,68,44,24,5,6.0,0,7,Semi-Urban,Manager,103498,0 +83864,Other,31,Bachelors,14,46,24,60,97,7.0,5,97,Urban,ML Engineer,137222,0 +83865,Male,42,PhD,3,36,18,40,75,6.0,6,72,Urban,Manager,118464,0 +83866,Female,25,Bachelors,7,98,48,98,96,2.0,4,83,Semi-Urban,ML Engineer,94613,1 +83867,Male,58,Diploma,1,3,44,73,71,3.0,3,71,Semi-Urban,Data Analyst,121657,0 +83868,Female,54,Bachelors,19,81,54,74,81,2.0,4,98,Urban,Manager,127920,1 +83869,Female,31,Masters,17,54,46,70,56,2.0,6,32,Semi-Urban,Software Engineer,114321,0 +83870,Male,50,Diploma,19,30,94,84,72,8.0,7,73,Urban,Manager,60630,1 +83871,Male,28,Bachelors,13,23,50,19,67,2.0,4,43,Rural,Software Engineer,37672,0 +83872,Male,36,Bachelors,15,44,83,85,69,4.0,7,37,Urban,ML Engineer,55664,1 +83873,Male,50,Bachelors,10,65,43,6,71,4.0,0,34,Urban,HR Executive,49730,0 +83874,Female,48,PhD,17,54,48,44,42,4.0,2,19,Rural,Software Engineer,95907,0 +83875,Female,49,Diploma,11,89,83,35,83,0.0,1,85,Rural,Software Engineer,92549,1 +83876,Male,25,High School,6,13,40,12,19,7.0,2,21,Semi-Urban,Software Engineer,113023,0 +83877,Female,34,Bachelors,1,81,40,20,20,7.0,4,93,Semi-Urban,Manager,124869,0 +83878,Male,25,Diploma,16,12,25,95,14,6.0,6,99,Urban,Manager,128276,0 +83879,Female,26,Diploma,2,79,33,4,8,3.0,4,13,Urban,Data Analyst,52125,0 +83880,Female,36,Masters,17,93,27,69,59,7.0,6,43,Urban,HR Executive,77220,0 +83881,Other,30,Bachelors,17,24,42,74,31,6.0,0,38,Urban,Software Engineer,144608,0 +83882,Male,32,High School,15,42,13,71,13,5.0,2,66,Rural,Software Engineer,131200,0 +83883,Female,39,High School,11,99,60,44,29,7.0,6,46,Urban,Software Engineer,140926,1 +83884,Female,42,Bachelors,5,33,52,46,87,4.0,6,13,Rural,HR Executive,45258,0 +83885,Male,31,Masters,11,89,11,97,78,9.0,4,75,Urban,Software Engineer,102542,1 +83886,Other,21,Masters,9,24,68,66,60,5.0,7,60,Urban,HR Executive,145622,0 +83887,Male,53,Bachelors,1,39,60,5,44,9.0,0,24,Semi-Urban,Manager,63967,0 +83888,Other,37,Bachelors,15,28,70,98,72,9.0,5,9,Urban,Manager,47469,0 +83889,Female,56,Masters,7,35,54,61,97,9.0,6,2,Urban,Manager,44282,0 +83890,Female,39,Masters,11,53,68,27,22,5.0,0,51,Urban,Software Engineer,80138,0 +83891,Male,33,Bachelors,13,23,34,44,86,4.0,2,35,Urban,Manager,75345,0 +83892,Male,39,Masters,1,30,76,58,92,0.0,1,19,Urban,Software Engineer,54345,0 +83893,Female,27,Bachelors,14,77,15,12,7,9.0,6,76,Rural,Manager,50504,0 +83894,Female,27,Masters,12,64,82,13,76,8.0,2,22,Semi-Urban,Software Engineer,92875,0 +83895,Other,41,Bachelors,5,67,0,82,47,5.0,2,82,Urban,HR Executive,147723,0 +83896,Male,26,Diploma,4,56,68,1,44,1.0,7,29,Rural,Data Analyst,44291,0 +83897,Female,39,PhD,12,42,61,30,34,7.0,7,76,Urban,Data Analyst,51388,0 +83898,Female,21,Diploma,15,98,67,89,85,9.0,5,73,Urban,HR Executive,38160,1 +83899,Other,33,Diploma,18,97,82,85,89,3.0,6,74,Rural,ML Engineer,116731,1 +83900,Male,51,Masters,15,57,36,43,55,3.0,4,27,Urban,Software Engineer,45637,0 +83901,Male,48,Masters,11,87,70,19,11,6.0,5,59,Urban,Data Analyst,74880,1 +83902,Male,38,PhD,13,27,76,5,75,1.0,7,8,Urban,Software Engineer,36446,0 +83903,Male,21,Diploma,10,71,29,61,79,6.0,5,84,Urban,Software Engineer,139500,1 +83904,Female,36,Masters,9,23,85,61,39,9.0,3,54,Urban,HR Executive,37793,0 +83905,Male,53,Bachelors,15,4,80,64,17,2.0,4,34,Semi-Urban,Manager,82406,0 +83906,Male,48,Diploma,19,82,52,84,24,0.0,5,13,Urban,Software Engineer,114776,0 +83907,Female,43,Bachelors,15,80,51,93,37,0.0,3,88,Rural,ML Engineer,88664,1 +83908,Male,23,Masters,13,42,79,43,43,2.0,2,2,Rural,ML Engineer,138158,0 +83909,Male,26,Bachelors,17,46,74,44,59,7.0,6,39,Urban,Software Engineer,53691,0 +83910,Male,43,Diploma,19,34,30,13,88,5.0,3,25,Urban,ML Engineer,66359,0 +83911,Male,27,Masters,14,65,13,83,82,5.0,0,16,Urban,ML Engineer,108713,0 +83912,Male,55,Diploma,9,56,32,16,35,6.0,3,4,Rural,Software Engineer,109249,0 +83913,Male,35,Bachelors,8,7,71,98,58,2.0,5,96,Rural,Manager,50515,1 +83914,Male,48,Bachelors,19,0,78,82,45,2.0,4,15,Rural,Data Analyst,107823,0 +83915,Male,51,Bachelors,1,81,47,21,14,8.0,3,54,Urban,ML Engineer,148591,0 +83916,Female,54,Diploma,5,78,27,63,86,2.0,6,26,Urban,ML Engineer,42314,0 +83917,Female,22,Diploma,2,65,72,47,65,7.0,2,86,Urban,HR Executive,131266,1 +83918,Male,29,Bachelors,7,13,29,87,98,8.0,6,15,Semi-Urban,ML Engineer,40537,0 +83919,Male,34,PhD,7,61,67,29,25,5.0,5,96,Urban,Software Engineer,128584,1 +83920,Male,25,Bachelors,11,38,3,96,90,1.0,7,65,Urban,ML Engineer,125186,0 +83921,Male,44,Masters,16,60,61,79,37,0.0,5,68,Urban,ML Engineer,70644,1 +83922,Male,31,Bachelors,19,34,95,38,60,6.0,6,18,Rural,ML Engineer,115684,0 +83923,Female,56,Bachelors,1,83,18,56,6,5.0,7,98,Urban,HR Executive,138189,1 +83924,Male,36,Bachelors,1,55,88,19,72,3.0,3,17,Urban,ML Engineer,78150,0 +83925,Male,56,Bachelors,12,10,26,78,4,0.0,1,6,Urban,Data Analyst,117132,0 +83926,Male,48,Bachelors,10,13,97,57,55,3.0,4,60,Urban,HR Executive,140538,0 +83927,Female,27,Bachelors,3,10,24,92,43,8.0,3,50,Urban,Data Analyst,35240,0 +83928,Male,48,Bachelors,2,0,36,24,37,0.0,2,65,Urban,HR Executive,84128,0 +83929,Male,29,High School,10,65,98,86,63,9.0,4,60,Urban,ML Engineer,145250,1 +83930,Male,58,High School,1,86,72,49,87,7.0,7,25,Semi-Urban,Software Engineer,129794,0 +83931,Female,40,Diploma,13,94,52,80,39,9.0,3,21,Semi-Urban,Data Analyst,55396,1 +83932,Female,51,Bachelors,12,51,77,99,23,9.0,7,55,Urban,Manager,59603,1 +83933,Male,32,High School,18,48,79,37,86,3.0,7,76,Urban,Data Analyst,107027,1 +83934,Male,42,Bachelors,11,60,33,62,41,7.0,6,33,Semi-Urban,Software Engineer,46488,0 +83935,Male,34,Masters,8,37,74,16,96,0.0,7,56,Urban,HR Executive,41905,0 +83936,Male,27,Bachelors,6,62,62,2,22,1.0,7,30,Urban,Data Analyst,38812,0 +83937,Other,53,Bachelors,6,64,76,46,85,6.0,7,5,Semi-Urban,HR Executive,101864,0 +83938,Male,53,Bachelors,0,62,47,57,40,1.0,1,61,Urban,Data Analyst,111795,0 +83939,Male,21,Masters,1,55,38,74,5,4.0,2,91,Rural,ML Engineer,84450,1 +83940,Male,39,Diploma,13,65,34,76,73,3.0,0,29,Urban,Software Engineer,72194,0 +83941,Female,53,Masters,14,6,3,40,75,9.0,3,74,Urban,Software Engineer,137685,0 +83942,Female,50,Masters,5,45,85,29,35,2.0,0,91,Rural,Software Engineer,149806,1 +83943,Male,47,Diploma,14,70,94,74,85,2.0,5,78,Rural,HR Executive,89268,1 +83944,Female,53,Diploma,1,80,67,0,0,3.0,5,83,Urban,ML Engineer,69992,0 +83945,Female,37,Masters,3,7,37,31,90,1.0,5,86,Urban,ML Engineer,134536,0 +83946,Male,34,High School,5,88,73,88,50,7.0,6,60,Semi-Urban,Data Analyst,91846,1 +83947,Male,28,Bachelors,9,49,63,32,58,0.0,1,91,Urban,Data Analyst,99279,1 +83948,Other,36,Diploma,13,37,90,18,48,9.0,4,0,Urban,Manager,29226,0 +83949,Male,33,Bachelors,1,13,92,93,85,0.0,3,97,Urban,ML Engineer,98342,1 +83950,Male,55,Bachelors,7,91,80,81,90,2.0,3,4,Urban,Software Engineer,116311,1 +83951,Other,36,Bachelors,10,46,93,22,43,7.0,5,47,Urban,HR Executive,145179,0 +83952,Male,55,Masters,4,88,62,13,52,1.0,4,70,Urban,Software Engineer,140870,0 +83953,Male,55,Bachelors,15,4,51,30,2,5.0,5,55,Urban,ML Engineer,126963,0 +83954,Female,54,Diploma,15,27,8,15,40,3.0,5,50,Semi-Urban,ML Engineer,27216,0 +83955,Male,55,High School,1,6,20,76,9,1.0,4,37,Rural,Data Analyst,130534,0 +83956,Male,57,Masters,1,36,45,62,56,5.0,4,84,Rural,ML Engineer,87662,0 +83957,Male,51,Bachelors,6,64,61,63,84,2.0,6,21,Urban,Data Analyst,35076,0 +83958,Male,46,Diploma,10,26,40,10,35,1.0,4,87,Urban,ML Engineer,141155,0 +83959,Male,33,High School,2,27,44,37,88,0.0,2,58,Urban,Data Analyst,50950,0 +83960,Female,24,Bachelors,14,28,51,51,29,4.0,1,47,Urban,Data Analyst,138038,0 +83961,Female,54,High School,18,57,71,41,18,2.0,0,72,Semi-Urban,ML Engineer,52809,1 +83962,Male,45,Diploma,14,15,36,41,33,7.0,7,46,Urban,Software Engineer,95918,0 +83963,Male,25,Bachelors,7,67,77,9,20,3.0,2,65,Urban,ML Engineer,43528,0 +83964,Female,26,High School,11,3,10,1,86,7.0,5,44,Urban,Software Engineer,79139,0 +83965,Male,49,Bachelors,16,76,61,35,25,6.0,1,43,Urban,Manager,28265,0 +83966,Female,49,Bachelors,2,80,30,30,65,7.0,7,5,Urban,Manager,73924,0 +83967,Female,35,Diploma,5,55,90,32,42,1.0,3,80,Urban,Software Engineer,119873,1 +83968,Male,50,Diploma,18,72,36,88,24,6.0,6,23,Urban,Manager,51625,0 +83969,Male,33,Masters,6,41,36,13,61,9.0,7,50,Urban,ML Engineer,108587,0 +83970,Male,33,Bachelors,8,24,63,1,67,1.0,2,41,Urban,ML Engineer,104241,0 +83971,Female,23,Masters,11,51,53,7,15,2.0,7,98,Urban,Software Engineer,70450,0 +83972,Male,33,Bachelors,2,50,22,13,8,2.0,1,98,Urban,HR Executive,30583,0 +83973,Female,32,High School,5,32,82,17,28,2.0,4,65,Rural,Software Engineer,118505,0 +83974,Female,38,High School,7,82,68,45,4,7.0,0,68,Rural,ML Engineer,120198,1 +83975,Male,42,High School,15,13,39,83,63,7.0,7,34,Urban,ML Engineer,117827,0 +83976,Male,52,Masters,2,6,73,36,83,6.0,3,42,Urban,Manager,26363,0 +83977,Male,44,Diploma,0,81,23,48,1,2.0,1,80,Rural,HR Executive,115627,0 +83978,Female,57,Bachelors,17,43,85,99,22,0.0,4,10,Semi-Urban,Software Engineer,126682,0 +83979,Female,36,High School,11,4,18,16,61,3.0,0,61,Semi-Urban,HR Executive,119226,0 +83980,Male,32,Masters,19,72,85,94,65,1.0,7,88,Urban,Data Analyst,26108,1 +83981,Male,29,Masters,11,87,47,18,95,8.0,1,40,Urban,Manager,145923,0 +83982,Male,49,Bachelors,16,46,74,8,98,1.0,4,67,Urban,HR Executive,56080,0 +83983,Male,53,Masters,11,34,25,71,11,1.0,4,10,Semi-Urban,ML Engineer,132529,0 +83984,Male,31,Bachelors,19,69,29,4,47,5.0,6,46,Urban,Software Engineer,65726,0 +83985,Female,39,Diploma,19,36,18,27,45,5.0,4,39,Semi-Urban,HR Executive,99852,0 +83986,Male,37,High School,13,40,31,96,3,7.0,4,6,Semi-Urban,Manager,66062,0 +83987,Female,29,Bachelors,18,52,81,11,48,7.0,5,12,Rural,Data Analyst,67723,0 +83988,Male,26,High School,19,84,74,31,94,9.0,1,46,Urban,ML Engineer,84746,1 +83989,Female,28,Masters,17,22,51,87,98,8.0,7,44,Urban,Manager,79846,0 +83990,Female,25,Diploma,14,51,8,66,51,5.0,2,69,Semi-Urban,Data Analyst,47594,0 +83991,Male,38,Diploma,13,19,10,81,82,3.0,1,25,Urban,Manager,39689,0 +83992,Male,42,Bachelors,2,68,37,66,6,5.0,5,26,Semi-Urban,ML Engineer,119416,0 +83993,Male,49,Diploma,17,86,94,58,48,9.0,5,52,Semi-Urban,Manager,56591,1 +83994,Female,24,Diploma,8,95,88,46,0,9.0,4,42,Urban,HR Executive,68869,1 +83995,Female,41,Diploma,8,78,9,38,26,9.0,3,8,Semi-Urban,Data Analyst,77961,0 +83996,Male,48,Masters,10,30,21,87,45,0.0,6,38,Urban,Data Analyst,90151,0 +83997,Male,29,Masters,2,13,7,82,3,9.0,0,74,Rural,ML Engineer,48737,0 +83998,Female,42,Diploma,10,1,52,90,34,7.0,7,14,Urban,HR Executive,45473,0 +83999,Male,55,Bachelors,9,81,92,47,10,3.0,0,73,Rural,Software Engineer,116754,1 +84000,Male,38,Diploma,7,37,98,15,3,6.0,7,85,Semi-Urban,HR Executive,136170,1 +84001,Male,25,Bachelors,8,50,18,16,27,2.0,0,52,Urban,HR Executive,139724,0 +84002,Male,41,High School,4,89,84,4,42,8.0,7,81,Urban,Manager,55090,1 +84003,Male,49,Bachelors,9,10,21,17,2,2.0,0,65,Urban,Software Engineer,36391,0 +84004,Male,25,High School,4,55,96,66,45,4.0,2,23,Urban,Software Engineer,137520,1 +84005,Female,58,Masters,15,3,94,39,50,6.0,4,99,Urban,Manager,107530,0 +84006,Female,58,Masters,9,71,86,55,48,0.0,3,86,Urban,Software Engineer,127482,1 +84007,Male,24,Bachelors,5,97,23,28,97,2.0,1,62,Rural,ML Engineer,117852,0 +84008,Male,42,Masters,0,64,84,36,65,7.0,7,86,Semi-Urban,Manager,125596,1 +84009,Male,52,Diploma,12,85,54,85,67,2.0,3,71,Semi-Urban,ML Engineer,79268,1 +84010,Female,58,Bachelors,7,92,96,67,76,2.0,7,97,Urban,HR Executive,135175,1 +84011,Female,37,Bachelors,5,38,18,53,37,1.0,6,66,Urban,Software Engineer,132738,0 +84012,Male,32,Bachelors,7,94,4,49,52,2.0,2,47,Semi-Urban,Manager,58017,0 +84013,Male,47,Masters,9,42,63,13,3,3.0,0,71,Semi-Urban,HR Executive,89065,0 +84014,Female,23,Bachelors,4,2,77,64,79,1.0,2,20,Semi-Urban,Manager,27205,0 +84015,Female,59,Bachelors,13,88,3,93,93,2.0,7,60,Urban,Software Engineer,32285,1 +84016,Male,27,Diploma,7,5,21,28,46,9.0,3,77,Semi-Urban,ML Engineer,48552,0 +84017,Male,45,Bachelors,3,5,88,80,34,0.0,2,74,Urban,ML Engineer,126575,1 +84018,Female,42,Diploma,0,48,77,30,44,3.0,3,60,Urban,Data Analyst,138540,0 +84019,Male,21,Masters,3,62,57,41,66,0.0,1,59,Semi-Urban,Data Analyst,113086,0 +84020,Male,54,Bachelors,0,34,26,96,8,4.0,2,82,Urban,Manager,124445,1 +84021,Male,39,Bachelors,7,69,34,8,70,3.0,0,86,Urban,Manager,85495,0 +84022,Male,51,Diploma,14,76,79,64,82,4.0,3,45,Rural,ML Engineer,114263,1 +84023,Other,31,Bachelors,0,64,3,62,53,8.0,4,88,Urban,Data Analyst,137672,0 +84024,Male,51,PhD,2,70,56,70,42,9.0,3,20,Urban,Software Engineer,113020,0 +84025,Female,27,High School,0,29,76,72,17,5.0,5,66,Urban,Data Analyst,102554,1 +84026,Female,48,High School,6,67,6,34,59,4.0,5,96,Urban,Software Engineer,97285,0 +84027,Male,59,Bachelors,6,4,4,31,49,9.0,3,28,Rural,Software Engineer,103583,0 +84028,Female,35,Bachelors,18,79,99,15,73,3.0,1,72,Urban,ML Engineer,131027,1 +84029,Male,57,Masters,0,61,58,53,52,5.0,1,50,Semi-Urban,HR Executive,117423,0 +84030,Male,35,Masters,16,21,90,12,18,8.0,6,63,Urban,ML Engineer,137394,0 +84031,Male,49,Bachelors,14,64,44,37,62,2.0,2,9,Urban,ML Engineer,61269,0 +84032,Male,42,Bachelors,0,45,5,93,15,9.0,6,22,Urban,ML Engineer,98658,0 +84033,Female,23,Bachelors,2,48,88,36,80,7.0,5,55,Semi-Urban,Software Engineer,130401,0 +84034,Female,51,Diploma,2,47,49,11,27,0.0,6,23,Urban,Manager,20845,0 +84035,Male,57,Bachelors,5,83,56,13,86,2.0,6,27,Urban,Software Engineer,119314,0 +84036,Male,25,Bachelors,14,91,96,79,76,1.0,1,79,Rural,HR Executive,107279,1 +84037,Female,52,Masters,16,3,82,78,80,4.0,4,91,Urban,Manager,73498,1 +84038,Female,59,Bachelors,10,91,66,19,89,3.0,2,35,Urban,HR Executive,85928,0 +84039,Male,34,Masters,9,74,44,67,17,0.0,5,31,Urban,Software Engineer,46739,0 +84040,Male,41,Diploma,6,29,88,64,10,3.0,6,62,Rural,HR Executive,86606,1 +84041,Male,35,Bachelors,7,79,35,71,39,5.0,7,84,Urban,HR Executive,148588,1 +84042,Female,43,Diploma,7,8,31,52,5,0.0,3,1,Urban,Software Engineer,36916,0 +84043,Female,33,High School,11,89,57,27,62,8.0,1,50,Urban,Software Engineer,29982,0 +84044,Male,28,PhD,9,50,22,99,25,6.0,5,54,Semi-Urban,HR Executive,125564,0 +84045,Male,24,Bachelors,4,20,84,59,20,1.0,2,30,Urban,Data Analyst,98978,0 +84046,Male,41,Diploma,7,24,44,4,98,8.0,0,62,Urban,Data Analyst,46889,0 +84047,Female,36,High School,5,80,12,78,44,1.0,6,10,Urban,Manager,85506,0 +84048,Female,32,Diploma,6,79,63,34,37,7.0,2,92,Urban,Data Analyst,116520,1 +84049,Female,35,Masters,11,90,94,1,36,3.0,2,62,Semi-Urban,Data Analyst,143792,1 +84050,Female,34,Diploma,17,18,93,98,35,8.0,7,5,Urban,Software Engineer,132453,0 +84051,Male,24,Bachelors,1,17,38,88,90,6.0,6,47,Semi-Urban,HR Executive,76155,0 +84052,Male,21,Bachelors,7,96,88,20,24,7.0,1,87,Urban,HR Executive,147053,1 +84053,Female,45,Bachelors,5,74,26,25,24,8.0,0,55,Urban,Manager,88208,0 +84054,Female,51,Diploma,6,0,68,32,73,0.0,0,40,Semi-Urban,ML Engineer,112200,0 +84055,Male,30,High School,18,87,67,15,31,0.0,3,24,Urban,Data Analyst,26362,0 +84056,Female,59,High School,4,62,87,54,5,8.0,4,71,Rural,Manager,23090,1 +84057,Male,54,Masters,6,43,17,27,86,1.0,4,92,Urban,Data Analyst,20259,0 +84058,Male,54,Diploma,16,33,21,30,53,6.0,6,55,Semi-Urban,ML Engineer,44204,0 +84059,Male,33,Diploma,17,58,1,67,52,1.0,5,14,Urban,Manager,60129,0 +84060,Other,54,Masters,1,90,54,2,79,9.0,2,89,Urban,ML Engineer,90257,0 +84061,Male,23,Bachelors,16,98,1,23,93,2.0,2,97,Urban,Software Engineer,120844,0 +84062,Other,43,Bachelors,17,39,81,29,67,3.0,1,1,Urban,Data Analyst,31434,0 +84063,Female,41,Masters,8,47,5,68,8,5.0,1,42,Urban,Manager,103647,0 +84064,Male,54,Diploma,7,86,18,26,13,2.0,4,88,Urban,ML Engineer,48131,0 +84065,Male,41,High School,17,91,35,3,49,6.0,3,7,Semi-Urban,ML Engineer,148408,0 +84066,Female,53,Bachelors,16,95,70,34,52,5.0,3,45,Urban,Software Engineer,87856,1 +84067,Male,29,Bachelors,6,13,46,72,44,5.0,3,89,Semi-Urban,Software Engineer,58444,0 +84068,Male,49,Bachelors,7,80,88,43,66,8.0,2,18,Semi-Urban,Software Engineer,33182,0 +84069,Male,46,Diploma,13,66,64,78,91,5.0,2,68,Rural,Manager,139813,1 +84070,Male,29,Bachelors,19,28,41,95,78,6.0,1,41,Urban,Software Engineer,79538,0 +84071,Male,31,Bachelors,0,45,47,20,40,8.0,3,72,Semi-Urban,Software Engineer,94773,0 +84072,Male,43,Diploma,3,90,13,35,20,1.0,2,36,Urban,ML Engineer,32309,0 +84073,Female,32,Bachelors,19,54,33,49,25,0.0,0,50,Urban,Software Engineer,120152,0 +84074,Male,36,Bachelors,9,20,34,17,97,6.0,0,51,Rural,ML Engineer,28113,0 +84075,Male,32,Masters,12,34,30,17,71,3.0,2,62,Urban,HR Executive,34987,0 +84076,Male,45,Bachelors,18,46,58,92,0,8.0,3,31,Urban,HR Executive,20362,0 +84077,Other,51,Bachelors,14,26,34,11,94,6.0,1,56,Rural,ML Engineer,125330,0 +84078,Male,26,Bachelors,8,53,94,5,36,3.0,3,52,Semi-Urban,Data Analyst,90378,0 +84079,Female,22,PhD,1,26,54,73,76,2.0,1,35,Urban,Software Engineer,66366,0 +84080,Male,52,Bachelors,0,49,40,53,54,4.0,5,43,Urban,HR Executive,129181,0 +84081,Male,32,Bachelors,13,80,79,38,81,5.0,3,4,Rural,ML Engineer,65033,0 +84082,Female,35,Bachelors,18,18,45,79,88,2.0,3,60,Semi-Urban,Manager,45021,0 +84083,Female,35,Bachelors,14,66,33,71,63,3.0,5,69,Urban,ML Engineer,85907,0 +84084,Male,53,Masters,4,64,24,91,24,5.0,7,93,Urban,ML Engineer,126007,1 +84085,Female,30,Bachelors,1,35,53,95,99,7.0,0,23,Semi-Urban,Manager,89145,0 +84086,Male,30,Bachelors,16,21,10,72,21,5.0,6,46,Rural,Data Analyst,79150,0 +84087,Male,50,Diploma,11,36,86,40,69,9.0,5,24,Urban,HR Executive,97668,0 +84088,Female,50,High School,5,79,15,57,65,8.0,6,53,Urban,Software Engineer,133374,0 +84089,Female,32,Masters,3,18,31,12,89,7.0,2,89,Urban,HR Executive,149035,0 +84090,Male,42,Bachelors,12,7,71,33,98,5.0,3,33,Semi-Urban,HR Executive,49841,0 +84091,Male,23,Masters,4,48,25,3,41,7.0,4,96,Urban,HR Executive,31692,0 +84092,Female,30,Bachelors,8,80,67,32,81,7.0,1,42,Rural,ML Engineer,73512,0 +84093,Female,23,Diploma,11,32,49,12,2,4.0,3,28,Rural,ML Engineer,33334,0 +84094,Male,55,PhD,13,15,13,50,26,5.0,1,13,Semi-Urban,Manager,92348,0 +84095,Female,59,Bachelors,0,64,76,56,31,0.0,0,72,Urban,ML Engineer,21661,1 +84096,Female,22,Diploma,2,82,67,14,22,8.0,6,46,Urban,ML Engineer,21716,0 +84097,Male,48,Masters,14,8,27,36,21,7.0,2,24,Rural,Software Engineer,63616,0 +84098,Female,21,Diploma,14,85,96,99,72,6.0,1,61,Rural,Manager,91135,1 +84099,Male,51,Bachelors,17,39,59,99,72,3.0,0,14,Urban,Software Engineer,112441,0 +84100,Male,24,Masters,2,52,1,55,91,0.0,1,34,Urban,Manager,85443,0 +84101,Male,35,High School,1,3,41,19,21,2.0,5,71,Semi-Urban,Data Analyst,80725,0 +84102,Female,38,Diploma,8,81,66,25,12,2.0,0,62,Urban,Manager,91879,0 +84103,Male,37,Diploma,15,1,51,84,9,8.0,3,5,Urban,Software Engineer,146350,0 +84104,Female,26,Bachelors,19,43,11,38,13,7.0,5,7,Urban,HR Executive,129844,0 +84105,Male,21,Diploma,6,19,5,28,77,4.0,0,83,Urban,Manager,127892,0 +84106,Female,37,Bachelors,10,84,79,54,34,4.0,7,8,Urban,HR Executive,85563,0 +84107,Female,40,Masters,1,9,64,17,75,2.0,5,36,Urban,ML Engineer,100469,0 +84108,Female,26,High School,19,10,66,26,38,9.0,0,83,Urban,ML Engineer,132307,0 +84109,Male,34,Bachelors,15,95,54,13,99,4.0,4,18,Semi-Urban,Manager,65239,0 +84110,Male,44,High School,15,6,42,43,49,1.0,5,42,Urban,ML Engineer,83190,0 +84111,Female,53,High School,15,8,4,25,49,9.0,2,57,Urban,ML Engineer,78580,0 +84112,Male,42,Bachelors,8,25,1,74,98,8.0,0,94,Semi-Urban,ML Engineer,77296,0 +84113,Male,59,Bachelors,2,27,95,94,19,3.0,0,17,Rural,ML Engineer,107005,0 +84114,Female,31,High School,18,72,70,20,30,7.0,3,43,Urban,Software Engineer,145757,0 +84115,Male,51,High School,16,21,0,93,66,4.0,2,78,Semi-Urban,Software Engineer,94799,0 +84116,Male,48,PhD,4,9,59,1,56,1.0,7,52,Urban,Data Analyst,118914,0 +84117,Female,29,Diploma,1,28,37,32,94,8.0,0,45,Semi-Urban,Software Engineer,72405,0 +84118,Male,28,Bachelors,16,15,53,30,93,7.0,1,79,Urban,Data Analyst,94415,0 +84119,Female,53,High School,6,94,17,23,65,3.0,3,84,Urban,Software Engineer,83933,0 +84120,Male,33,High School,16,76,62,37,4,9.0,4,60,Urban,Data Analyst,116169,1 +84121,Male,55,Bachelors,5,22,81,48,14,6.0,6,41,Urban,Software Engineer,109603,0 +84122,Male,53,Masters,1,13,8,26,21,7.0,1,65,Semi-Urban,ML Engineer,142250,0 +84123,Female,53,Bachelors,18,61,55,39,33,6.0,2,16,Semi-Urban,HR Executive,149564,0 +84124,Male,51,High School,2,5,99,30,33,9.0,6,67,Urban,Software Engineer,53563,0 +84125,Other,45,Diploma,7,68,47,59,67,9.0,3,78,Rural,Software Engineer,82178,1 +84126,Female,35,Diploma,1,2,11,59,83,9.0,7,15,Semi-Urban,Software Engineer,124384,0 +84127,Female,36,Diploma,16,12,96,87,86,4.0,1,16,Urban,Data Analyst,133906,0 +84128,Male,23,Diploma,7,43,6,77,83,8.0,0,33,Rural,Data Analyst,59563,0 +84129,Female,34,Diploma,18,3,26,95,4,3.0,4,24,Urban,Data Analyst,103814,0 +84130,Male,24,Masters,3,0,4,20,36,4.0,4,17,Urban,Data Analyst,116184,0 +84131,Male,23,High School,16,92,68,51,91,7.0,7,46,Urban,HR Executive,37015,1 +84132,Female,44,Masters,10,5,21,67,70,6.0,4,66,Rural,ML Engineer,21878,0 +84133,Other,42,Bachelors,11,34,16,8,81,5.0,6,51,Urban,ML Engineer,49020,0 +84134,Male,57,Bachelors,17,2,0,25,79,9.0,2,4,Semi-Urban,HR Executive,86330,0 +84135,Female,51,Diploma,2,84,49,61,49,6.0,5,18,Semi-Urban,ML Engineer,115490,0 +84136,Female,59,High School,1,27,44,39,8,1.0,6,94,Urban,ML Engineer,132402,0 +84137,Male,27,Masters,18,28,89,13,11,5.0,7,7,Semi-Urban,Data Analyst,142952,0 +84138,Male,45,Masters,11,60,79,36,99,8.0,5,23,Rural,Software Engineer,139316,0 +84139,Female,36,Bachelors,18,0,88,56,42,5.0,5,49,Semi-Urban,ML Engineer,33713,0 +84140,Other,37,Masters,3,72,21,71,88,8.0,6,52,Semi-Urban,Manager,22476,0 +84141,Female,37,Diploma,11,69,33,12,15,6.0,4,46,Urban,Data Analyst,105989,0 +84142,Male,57,Bachelors,7,95,7,27,71,6.0,2,55,Rural,HR Executive,110397,0 +84143,Female,30,PhD,4,7,39,67,71,0.0,3,66,Semi-Urban,Software Engineer,58462,0 +84144,Male,55,Masters,19,40,13,82,23,1.0,6,94,Rural,Software Engineer,119925,0 +84145,Male,24,High School,12,94,68,17,58,7.0,7,41,Semi-Urban,Software Engineer,135107,0 +84146,Female,27,Bachelors,0,84,22,75,46,1.0,3,29,Urban,Manager,23931,0 +84147,Female,51,Bachelors,7,72,4,42,87,7.0,2,53,Urban,Software Engineer,50306,0 +84148,Male,26,Bachelors,1,91,78,93,20,8.0,4,82,Urban,Manager,47825,1 +84149,Male,37,Bachelors,16,8,49,50,51,6.0,4,14,Urban,ML Engineer,68807,0 +84150,Male,49,Diploma,18,58,60,22,1,2.0,7,58,Urban,Software Engineer,54279,0 +84151,Male,43,Bachelors,8,50,91,27,50,7.0,2,83,Urban,HR Executive,98473,1 +84152,Female,38,High School,17,34,93,66,49,5.0,7,54,Urban,ML Engineer,100085,1 +84153,Female,24,Bachelors,6,59,8,10,34,7.0,3,22,Urban,HR Executive,71281,0 +84154,Male,31,Bachelors,12,14,4,59,24,4.0,6,42,Semi-Urban,HR Executive,63740,0 +84155,Female,31,Diploma,13,75,7,90,37,1.0,1,12,Semi-Urban,ML Engineer,21730,0 +84156,Male,33,Bachelors,19,97,32,97,94,1.0,5,77,Rural,HR Executive,26788,1 +84157,Male,35,Masters,15,66,19,9,64,7.0,6,61,Urban,ML Engineer,97794,0 +84158,Male,38,High School,13,82,95,17,84,5.0,4,4,Urban,ML Engineer,61846,0 +84159,Male,45,Bachelors,9,18,18,84,2,9.0,6,2,Urban,ML Engineer,136404,0 +84160,Male,29,Diploma,17,46,99,3,22,3.0,3,57,Urban,Software Engineer,136487,0 +84161,Male,57,Masters,16,66,15,3,68,2.0,7,94,Urban,Data Analyst,118925,0 +84162,Female,32,Diploma,10,31,59,93,48,3.0,5,7,Semi-Urban,Manager,31999,0 +84163,Male,50,Bachelors,1,93,20,68,43,0.0,1,37,Urban,Software Engineer,124154,0 +84164,Other,52,PhD,15,59,55,36,65,8.0,4,82,Semi-Urban,HR Executive,33395,0 +84165,Male,58,Bachelors,9,78,63,0,68,9.0,1,96,Urban,Software Engineer,94035,1 +84166,Female,58,Bachelors,4,23,58,65,99,3.0,6,14,Semi-Urban,Software Engineer,47430,0 +84167,Male,23,Diploma,15,3,74,89,71,0.0,0,24,Urban,HR Executive,104270,0 +84168,Male,55,Diploma,9,75,16,84,13,8.0,5,47,Rural,Manager,105873,0 +84169,Male,53,Masters,7,6,98,14,24,9.0,7,50,Semi-Urban,ML Engineer,95127,0 +84170,Male,32,High School,15,47,46,88,24,5.0,2,90,Rural,Manager,98372,1 +84171,Male,41,PhD,17,95,4,59,47,2.0,5,55,Urban,Manager,62305,0 +84172,Male,46,High School,2,3,52,99,1,5.0,6,53,Urban,ML Engineer,116632,0 +84173,Male,41,Diploma,10,61,11,17,98,5.0,6,29,Rural,Software Engineer,28141,0 +84174,Female,23,High School,4,53,50,58,15,8.0,3,9,Semi-Urban,Data Analyst,64449,0 +84175,Male,50,Diploma,13,28,17,93,55,3.0,1,11,Rural,Data Analyst,118867,0 +84176,Male,45,PhD,8,61,4,85,3,7.0,4,44,Rural,Software Engineer,86332,0 +84177,Male,31,Bachelors,10,67,57,8,6,8.0,2,85,Semi-Urban,Manager,34997,0 +84178,Male,54,Bachelors,16,54,90,16,67,0.0,1,37,Urban,Manager,99304,0 +84179,Male,59,Masters,8,7,85,63,64,5.0,6,8,Rural,ML Engineer,85891,0 +84180,Other,50,High School,5,87,0,4,1,8.0,5,8,Semi-Urban,Software Engineer,138773,0 +84181,Male,51,Diploma,16,16,21,18,19,5.0,5,91,Urban,ML Engineer,118452,0 +84182,Male,42,Bachelors,7,83,98,59,22,5.0,5,61,Urban,HR Executive,74732,1 +84183,Male,48,Bachelors,2,56,50,58,75,6.0,4,33,Rural,Data Analyst,64170,0 +84184,Male,52,Bachelors,17,58,1,44,77,8.0,7,75,Urban,HR Executive,131894,0 +84185,Male,27,High School,18,96,66,76,92,1.0,2,50,Semi-Urban,Data Analyst,95780,1 +84186,Female,21,Diploma,13,50,66,12,26,6.0,0,30,Urban,Manager,117731,0 +84187,Male,59,Bachelors,13,15,13,26,48,9.0,4,29,Urban,Software Engineer,29586,0 +84188,Male,25,Bachelors,2,32,96,12,29,3.0,0,79,Urban,ML Engineer,137453,0 +84189,Female,47,PhD,13,81,4,73,92,9.0,1,72,Semi-Urban,HR Executive,74328,0 +84190,Male,28,Bachelors,8,27,12,35,54,6.0,7,47,Urban,Manager,57960,0 +84191,Male,29,Masters,17,72,69,99,88,6.0,0,5,Semi-Urban,Manager,24764,1 +84192,Female,53,Bachelors,1,91,51,34,48,9.0,4,12,Urban,ML Engineer,146926,0 +84193,Male,48,Bachelors,8,0,79,93,39,2.0,2,19,Semi-Urban,Data Analyst,80991,0 +84194,Male,43,High School,7,89,86,45,57,0.0,6,19,Rural,ML Engineer,109161,1 +84195,Female,35,Diploma,1,91,87,6,74,6.0,1,7,Urban,Data Analyst,62921,0 +84196,Female,52,High School,11,89,60,2,68,8.0,0,86,Semi-Urban,Data Analyst,94562,0 +84197,Male,39,Diploma,4,38,62,20,99,2.0,1,86,Urban,Software Engineer,56887,0 +84198,Female,51,Masters,0,88,8,18,77,4.0,5,49,Urban,Software Engineer,48511,0 +84199,Male,47,Bachelors,19,58,18,74,19,2.0,2,50,Urban,Data Analyst,84891,0 +84200,Male,23,High School,19,49,3,47,33,5.0,4,85,Rural,ML Engineer,128236,0 +84201,Other,26,Bachelors,5,74,95,81,39,0.0,5,30,Rural,Manager,118707,1 +84202,Female,44,Masters,5,41,30,4,7,8.0,0,51,Urban,Data Analyst,112391,0 +84203,Female,34,Diploma,19,84,56,0,80,9.0,7,95,Urban,Manager,72890,0 +84204,Male,28,Bachelors,16,68,16,25,15,7.0,7,90,Urban,Software Engineer,133326,0 +84205,Female,46,Diploma,0,43,12,56,17,7.0,5,15,Rural,HR Executive,127613,0 +84206,Male,45,Bachelors,12,15,18,28,52,0.0,5,84,Urban,Data Analyst,134240,0 +84207,Female,41,Bachelors,17,15,43,42,61,1.0,4,30,Urban,Data Analyst,50676,0 +84208,Male,58,Masters,18,92,59,78,97,5.0,4,90,Rural,Software Engineer,141979,1 +84209,Male,45,High School,8,87,50,53,50,1.0,0,15,Urban,Software Engineer,105018,0 +84210,Male,47,Bachelors,3,88,27,61,6,0.0,4,18,Urban,Manager,23049,0 +84211,Male,32,Diploma,8,85,55,35,44,4.0,0,7,Semi-Urban,HR Executive,45446,0 +84212,Female,38,Bachelors,9,82,93,19,9,2.0,0,48,Urban,Data Analyst,135883,1 +84213,Male,35,Diploma,10,20,10,73,78,3.0,4,93,Urban,Manager,142701,0 +84214,Female,59,Bachelors,11,99,58,98,57,5.0,1,87,Urban,Software Engineer,42862,1 +84215,Female,35,High School,17,74,19,9,84,0.0,7,63,Urban,Data Analyst,63148,0 +84216,Female,46,Diploma,18,66,15,3,75,1.0,7,66,Urban,HR Executive,50311,0 +84217,Female,59,Bachelors,5,10,3,54,5,6.0,6,92,Rural,Manager,149437,0 +84218,Female,38,PhD,16,68,91,80,37,7.0,1,45,Rural,Data Analyst,48154,1 +84219,Female,44,Bachelors,18,90,20,9,46,9.0,1,5,Semi-Urban,Software Engineer,87318,0 +84220,Male,40,Masters,5,34,53,33,20,5.0,6,10,Rural,Manager,69390,0 +84221,Female,58,Diploma,17,71,10,82,93,2.0,3,8,Rural,Manager,128255,0 +84222,Male,37,Diploma,13,46,39,60,30,9.0,4,76,Semi-Urban,HR Executive,90292,0 +84223,Male,21,High School,7,85,63,80,68,3.0,2,12,Semi-Urban,Manager,45969,1 +84224,Male,21,Bachelors,15,48,28,21,85,7.0,1,76,Urban,Software Engineer,92708,0 +84225,Female,26,Bachelors,0,59,9,98,30,4.0,3,41,Urban,Software Engineer,131449,0 +84226,Male,47,PhD,8,93,51,15,72,0.0,4,19,Urban,Software Engineer,73356,0 +84227,Male,45,High School,17,79,8,66,71,7.0,2,13,Semi-Urban,Manager,49673,0 +84228,Male,50,Masters,19,51,92,12,2,5.0,3,89,Urban,HR Executive,38424,1 +84229,Male,36,Diploma,13,37,52,68,56,7.0,4,37,Urban,Data Analyst,25161,0 +84230,Female,45,Masters,0,94,25,76,52,1.0,7,48,Urban,ML Engineer,76865,1 +84231,Other,22,Bachelors,11,37,97,23,75,7.0,3,9,Urban,Data Analyst,72795,0 +84232,Female,46,Diploma,17,54,15,34,53,8.0,0,20,Urban,Software Engineer,27142,0 +84233,Male,35,Masters,9,99,8,52,10,2.0,6,24,Semi-Urban,ML Engineer,96583,0 +84234,Male,51,Masters,17,45,76,1,6,7.0,0,91,Semi-Urban,HR Executive,60680,0 +84235,Male,28,High School,11,60,58,33,73,2.0,7,21,Urban,Manager,52733,0 +84236,Female,26,Diploma,12,25,0,75,32,8.0,5,27,Urban,Software Engineer,80325,0 +84237,Male,41,Bachelors,9,99,54,95,41,1.0,0,61,Rural,Software Engineer,28879,1 +84238,Female,55,Bachelors,19,56,5,68,24,1.0,4,29,Urban,Data Analyst,85450,0 +84239,Female,57,Bachelors,19,6,85,35,51,1.0,3,69,Urban,HR Executive,52848,0 +84240,Male,32,Bachelors,3,67,42,10,37,4.0,2,67,Urban,ML Engineer,30092,0 +84241,Female,48,Masters,1,71,87,77,97,0.0,7,86,Semi-Urban,Software Engineer,23762,1 +84242,Male,35,Bachelors,1,10,18,43,1,4.0,3,38,Urban,ML Engineer,142425,0 +84243,Male,44,Diploma,1,6,72,7,16,4.0,2,80,Semi-Urban,Manager,128848,0 +84244,Male,35,PhD,1,96,64,2,87,4.0,5,99,Semi-Urban,Data Analyst,119387,1 +84245,Female,27,Diploma,15,10,67,85,36,0.0,5,43,Rural,Manager,21759,0 +84246,Female,55,High School,6,45,66,39,1,6.0,1,26,Semi-Urban,Manager,133316,0 +84247,Male,25,Diploma,11,66,94,55,58,6.0,5,73,Urban,Manager,73756,1 +84248,Male,40,High School,10,96,11,47,45,3.0,0,46,Urban,Manager,88636,0 +84249,Female,38,High School,16,49,32,50,31,5.0,0,24,Semi-Urban,Manager,103108,0 +84250,Male,29,Masters,19,21,17,38,34,5.0,4,62,Rural,Software Engineer,68840,0 +84251,Male,53,Bachelors,5,36,83,97,72,4.0,7,52,Urban,Software Engineer,50841,1 +84252,Female,32,PhD,11,96,84,84,71,5.0,7,79,Semi-Urban,Manager,118927,1 +84253,Female,27,Bachelors,5,25,49,0,80,1.0,1,31,Urban,HR Executive,140759,0 +84254,Female,38,Diploma,5,40,67,88,68,8.0,2,36,Semi-Urban,HR Executive,137240,0 +84255,Female,44,Bachelors,11,60,43,21,31,0.0,2,28,Urban,Manager,56506,0 +84256,Male,28,Diploma,10,33,71,16,30,8.0,7,87,Urban,ML Engineer,136632,0 +84257,Female,43,Bachelors,9,58,36,29,81,4.0,2,16,Urban,HR Executive,38996,0 +84258,Male,38,Bachelors,18,5,59,31,73,8.0,2,56,Urban,Manager,45335,0 +84259,Other,23,Bachelors,19,55,50,14,53,2.0,2,59,Rural,HR Executive,94440,0 +84260,Female,45,High School,15,86,21,73,23,5.0,3,41,Rural,ML Engineer,65373,0 +84261,Female,33,Masters,15,1,3,14,29,0.0,3,37,Rural,Software Engineer,70012,0 +84262,Male,29,Diploma,6,48,75,76,41,1.0,5,43,Urban,Manager,128211,1 +84263,Male,58,Diploma,9,93,47,5,52,6.0,6,78,Semi-Urban,ML Engineer,88434,0 +84264,Male,51,Masters,1,84,94,39,51,1.0,3,47,Semi-Urban,Manager,91598,1 +84265,Male,42,Diploma,3,31,67,97,40,8.0,5,87,Urban,Software Engineer,99976,1 +84266,Male,39,Masters,16,66,8,58,69,4.0,4,93,Semi-Urban,HR Executive,139641,0 +84267,Male,22,Bachelors,8,19,23,7,85,7.0,3,96,Urban,Data Analyst,99954,0 +84268,Male,37,Diploma,6,54,27,82,31,8.0,1,49,Rural,HR Executive,93084,0 +84269,Male,31,Masters,19,66,40,16,69,7.0,6,93,Urban,HR Executive,117034,0 +84270,Male,42,High School,18,90,94,30,95,3.0,1,68,Urban,ML Engineer,59792,1 +84271,Male,41,Diploma,17,42,88,27,44,8.0,3,50,Urban,Data Analyst,64425,0 +84272,Male,26,Diploma,9,28,75,12,44,6.0,1,87,Semi-Urban,ML Engineer,71485,0 +84273,Female,41,Diploma,16,21,0,78,85,6.0,4,60,Urban,Software Engineer,27253,0 +84274,Male,49,Bachelors,13,77,13,17,84,9.0,6,73,Urban,Manager,34296,0 +84275,Male,25,Diploma,3,4,1,1,91,9.0,6,52,Rural,ML Engineer,80043,0 +84276,Female,29,Diploma,0,9,34,48,83,4.0,5,59,Urban,ML Engineer,129772,0 +84277,Male,49,Diploma,5,78,33,29,17,7.0,0,77,Semi-Urban,ML Engineer,45277,0 +84278,Female,45,Diploma,15,24,0,0,18,6.0,1,72,Urban,ML Engineer,89581,0 +84279,Male,35,Diploma,19,93,63,73,90,4.0,6,94,Urban,Data Analyst,115156,1 +84280,Male,26,High School,10,44,54,38,21,8.0,3,80,Urban,Manager,111129,0 +84281,Female,59,Masters,5,78,64,77,24,3.0,0,47,Urban,HR Executive,149191,1 +84282,Male,50,Diploma,10,31,64,16,83,8.0,2,21,Urban,Software Engineer,122692,0 +84283,Female,41,Diploma,15,73,25,1,45,3.0,5,13,Semi-Urban,Manager,137769,0 +84284,Female,23,Masters,6,1,89,12,51,1.0,5,70,Urban,Software Engineer,34725,0 +84285,Male,43,Bachelors,16,84,98,49,86,2.0,6,83,Urban,Software Engineer,125103,1 +84286,Female,49,Bachelors,0,60,52,2,4,6.0,5,6,Semi-Urban,Manager,76796,0 +84287,Female,22,High School,2,64,86,99,60,8.0,2,12,Urban,Software Engineer,43140,1 +84288,Female,56,Bachelors,12,37,17,20,92,8.0,0,41,Semi-Urban,HR Executive,138148,0 +84289,Female,33,Masters,13,35,30,96,82,4.0,0,78,Semi-Urban,HR Executive,125161,0 +84290,Male,40,Bachelors,15,77,49,70,97,7.0,2,79,Rural,Data Analyst,90090,1 +84291,Female,24,Bachelors,7,60,71,55,38,8.0,3,36,Urban,Data Analyst,57790,0 +84292,Male,51,Masters,17,58,86,65,33,3.0,5,29,Rural,HR Executive,88596,1 +84293,Female,55,High School,15,66,26,4,47,4.0,4,76,Urban,ML Engineer,48928,0 +84294,Female,40,Bachelors,6,27,74,31,38,5.0,5,71,Urban,HR Executive,109574,0 +84295,Female,45,Diploma,7,3,22,56,31,7.0,7,24,Urban,ML Engineer,97258,0 +84296,Male,28,Bachelors,10,95,36,60,43,4.0,1,74,Urban,HR Executive,21155,1 +84297,Male,55,Masters,6,82,33,62,88,2.0,1,34,Urban,Software Engineer,145843,0 +84298,Female,27,Diploma,0,38,87,92,91,0.0,6,60,Urban,HR Executive,117982,1 +84299,Female,39,Masters,6,45,43,31,74,2.0,3,82,Rural,Software Engineer,29882,0 +84300,Female,31,High School,15,38,42,34,69,9.0,7,28,Semi-Urban,HR Executive,110882,0 +84301,Male,27,Diploma,12,20,57,54,77,1.0,3,58,Semi-Urban,Manager,78426,0 +84302,Male,32,Bachelors,5,79,49,90,95,4.0,5,6,Rural,ML Engineer,50409,0 +84303,Male,28,Diploma,18,5,80,34,80,0.0,2,80,Urban,Data Analyst,45581,0 +84304,Male,52,Diploma,8,76,6,93,57,2.0,4,25,Urban,HR Executive,71024,0 +84305,Male,50,Masters,11,64,30,76,4,2.0,0,92,Urban,ML Engineer,21293,1 +84306,Female,26,Bachelors,15,89,16,21,40,2.0,3,17,Semi-Urban,HR Executive,41950,0 +84307,Male,23,Bachelors,7,39,88,70,99,2.0,6,72,Urban,Manager,131351,1 +84308,Male,49,Masters,10,50,70,19,8,1.0,6,58,Semi-Urban,Software Engineer,44702,0 +84309,Male,40,Bachelors,7,48,60,99,49,4.0,0,15,Urban,Data Analyst,22238,0 +84310,Female,24,Bachelors,15,0,97,46,44,9.0,3,65,Urban,Manager,72218,0 +84311,Female,37,Bachelors,1,28,40,84,69,6.0,6,77,Urban,Data Analyst,27022,0 +84312,Male,44,Bachelors,4,26,54,80,85,7.0,2,86,Urban,ML Engineer,142230,1 +84313,Female,43,Bachelors,0,56,19,81,33,9.0,3,85,Urban,Software Engineer,46473,1 +84314,Female,44,High School,0,67,60,83,85,2.0,4,95,Urban,ML Engineer,134511,1 +84315,Male,59,High School,16,48,37,4,1,7.0,7,87,Rural,Data Analyst,124605,0 +84316,Female,56,Bachelors,18,67,28,68,83,4.0,6,5,Urban,Manager,113884,0 +84317,Male,26,High School,3,83,98,8,23,3.0,7,19,Semi-Urban,Manager,25506,0 +84318,Male,43,Bachelors,4,92,12,2,20,4.0,2,55,Urban,Manager,71909,0 +84319,Male,54,High School,9,15,81,71,30,6.0,0,73,Semi-Urban,ML Engineer,119762,1 +84320,Other,50,Bachelors,1,46,51,98,92,5.0,5,62,Urban,HR Executive,53710,1 +84321,Other,46,Bachelors,18,42,90,31,15,1.0,0,8,Rural,HR Executive,128355,0 +84322,Female,25,Masters,17,77,45,73,8,1.0,7,18,Urban,Software Engineer,63091,0 +84323,Male,56,High School,1,35,96,53,53,9.0,1,57,Semi-Urban,Software Engineer,119078,1 +84324,Female,27,PhD,4,70,23,22,21,7.0,5,78,Semi-Urban,HR Executive,91107,0 +84325,Female,27,Masters,19,16,85,97,70,8.0,0,3,Semi-Urban,Manager,89800,0 +84326,Male,57,Bachelors,9,64,15,35,95,4.0,3,59,Semi-Urban,HR Executive,132691,0 +84327,Male,49,Masters,13,96,23,5,69,3.0,7,55,Rural,Software Engineer,127977,0 +84328,Female,29,Diploma,5,71,43,97,65,1.0,5,56,Rural,ML Engineer,145805,1 +84329,Male,57,Masters,16,61,58,64,41,4.0,5,73,Urban,Software Engineer,25265,1 +84330,Female,41,Bachelors,8,52,41,99,53,9.0,4,6,Semi-Urban,ML Engineer,100295,0 +84331,Female,55,Bachelors,3,94,8,88,67,7.0,3,53,Semi-Urban,Manager,91078,1 +84332,Male,41,Bachelors,10,0,54,11,54,5.0,4,45,Urban,Software Engineer,112072,0 +84333,Female,42,Diploma,7,57,44,58,25,1.0,1,68,Semi-Urban,ML Engineer,59200,0 +84334,Male,22,Diploma,17,41,24,15,44,5.0,6,77,Semi-Urban,Data Analyst,96406,0 +84335,Male,24,Diploma,1,56,10,49,12,0.0,4,47,Rural,Manager,26030,0 +84336,Female,33,Diploma,14,5,57,31,95,2.0,3,64,Urban,HR Executive,93770,0 +84337,Female,55,Masters,5,57,32,61,50,9.0,7,87,Urban,Data Analyst,75372,0 +84338,Male,27,Diploma,9,36,14,21,80,6.0,3,22,Rural,Software Engineer,29851,0 +84339,Male,54,Masters,1,5,73,16,86,5.0,4,84,Semi-Urban,Data Analyst,127922,0 +84340,Male,54,Diploma,13,7,25,47,31,1.0,4,17,Urban,Software Engineer,33695,0 +84341,Female,35,Diploma,17,95,51,4,82,2.0,1,53,Semi-Urban,Software Engineer,57164,0 +84342,Male,51,Bachelors,13,97,40,48,56,3.0,1,57,Urban,HR Executive,146801,1 +84343,Female,59,Masters,4,65,25,82,61,5.0,4,36,Semi-Urban,Data Analyst,32998,0 +84344,Male,35,Diploma,6,97,69,60,88,7.0,0,51,Urban,HR Executive,138843,1 +84345,Female,21,Diploma,1,69,72,0,24,9.0,7,45,Urban,Software Engineer,82799,0 +84346,Male,51,High School,8,29,68,12,50,3.0,0,40,Rural,ML Engineer,36393,0 +84347,Male,29,Diploma,16,51,61,11,16,2.0,3,64,Urban,Manager,61422,0 +84348,Female,35,Bachelors,5,21,67,74,90,2.0,5,44,Urban,ML Engineer,123326,0 +84349,Female,55,Masters,7,38,29,9,82,3.0,7,59,Urban,ML Engineer,43118,0 +84350,Male,30,Bachelors,6,59,17,24,40,8.0,1,80,Rural,Software Engineer,99899,0 +84351,Male,35,High School,2,96,11,46,86,2.0,2,95,Semi-Urban,Data Analyst,116322,1 +84352,Male,39,Bachelors,2,37,87,51,20,1.0,6,52,Semi-Urban,ML Engineer,97523,0 +84353,Male,47,Masters,1,90,77,94,79,9.0,5,28,Semi-Urban,Software Engineer,83898,1 +84354,Female,26,Masters,14,2,71,24,49,2.0,4,41,Urban,Data Analyst,99399,0 +84355,Male,21,Bachelors,11,29,48,1,47,0.0,0,61,Urban,Manager,56719,0 +84356,Male,23,Bachelors,12,84,75,82,59,0.0,3,35,Rural,Data Analyst,145782,1 +84357,Male,59,Bachelors,8,87,72,22,24,9.0,0,65,Urban,Manager,95890,1 +84358,Male,22,High School,18,1,96,68,11,3.0,1,8,Urban,Software Engineer,136117,0 +84359,Male,57,Diploma,2,50,16,88,11,0.0,3,41,Urban,HR Executive,78155,0 +84360,Female,40,Bachelors,3,88,6,64,76,0.0,1,77,Semi-Urban,Software Engineer,36338,0 +84361,Male,49,Diploma,17,17,85,53,25,4.0,2,95,Urban,ML Engineer,106911,1 +84362,Male,48,Diploma,1,30,56,66,21,1.0,5,56,Semi-Urban,Software Engineer,80042,0 +84363,Male,36,Masters,12,16,7,94,40,9.0,3,70,Rural,Manager,121226,0 +84364,Female,53,PhD,11,17,85,83,34,2.0,4,99,Urban,HR Executive,89181,1 +84365,Other,49,Bachelors,11,73,68,19,82,9.0,2,49,Urban,Data Analyst,33682,0 +84366,Female,47,Bachelors,6,70,13,12,23,7.0,7,22,Urban,Manager,54881,0 +84367,Male,28,Bachelors,10,68,65,1,31,2.0,3,43,Urban,Data Analyst,69696,0 +84368,Male,28,Bachelors,14,72,50,3,21,7.0,2,70,Rural,HR Executive,115803,0 +84369,Male,57,Bachelors,5,8,96,25,12,2.0,5,24,Rural,ML Engineer,134027,0 +84370,Male,38,Masters,2,69,94,23,64,0.0,4,59,Urban,ML Engineer,37784,1 +84371,Female,33,Diploma,1,37,44,74,92,7.0,4,73,Urban,Data Analyst,129404,0 +84372,Other,56,Masters,18,58,44,41,16,3.0,2,11,Semi-Urban,Software Engineer,31007,0 +84373,Male,54,Masters,4,37,73,2,23,1.0,2,48,Semi-Urban,Manager,96744,0 +84374,Male,30,Diploma,0,50,64,59,96,1.0,0,60,Urban,HR Executive,149873,0 +84375,Female,59,Bachelors,16,81,40,37,27,6.0,1,72,Semi-Urban,ML Engineer,120571,0 +84376,Female,48,Bachelors,5,64,49,29,75,0.0,7,11,Urban,HR Executive,144584,0 +84377,Female,46,Bachelors,6,55,69,0,91,3.0,7,15,Rural,Data Analyst,129320,0 +84378,Female,55,High School,12,11,44,64,38,4.0,2,71,Semi-Urban,ML Engineer,21483,0 +84379,Male,39,Masters,15,20,77,99,63,0.0,7,15,Urban,Software Engineer,21702,0 +84380,Female,51,Bachelors,16,36,69,29,75,3.0,7,73,Urban,HR Executive,50375,0 +84381,Female,37,Bachelors,17,19,47,42,10,8.0,2,53,Urban,HR Executive,39512,0 +84382,Female,34,Bachelors,13,85,62,36,78,2.0,5,13,Semi-Urban,Software Engineer,102274,0 +84383,Male,52,Bachelors,16,1,70,54,85,0.0,0,16,Semi-Urban,HR Executive,35830,0 +84384,Female,37,Bachelors,13,8,66,91,56,4.0,2,83,Semi-Urban,ML Engineer,122488,1 +84385,Female,43,Diploma,11,51,93,44,7,7.0,3,58,Urban,Manager,27365,1 +84386,Male,58,Bachelors,16,60,18,50,92,8.0,0,2,Urban,HR Executive,139818,0 +84387,Male,25,Bachelors,5,89,28,91,50,7.0,2,67,Semi-Urban,HR Executive,27587,1 +84388,Male,21,Masters,15,96,15,45,41,6.0,0,3,Urban,HR Executive,102963,0 +84389,Female,26,High School,17,75,29,68,87,3.0,6,26,Semi-Urban,Manager,103763,0 +84390,Male,43,High School,0,37,15,17,62,4.0,5,22,Rural,ML Engineer,96767,0 +84391,Male,53,High School,6,14,25,97,11,4.0,0,87,Rural,Data Analyst,24348,0 +84392,Male,37,Masters,18,33,59,74,65,1.0,4,72,Semi-Urban,HR Executive,49129,1 +84393,Female,59,Diploma,12,44,17,16,87,9.0,6,37,Urban,ML Engineer,143945,0 +84394,Male,24,Diploma,15,4,13,74,65,1.0,6,95,Rural,Data Analyst,53496,0 +84395,Male,42,High School,12,21,22,85,65,2.0,4,59,Semi-Urban,Data Analyst,54354,0 +84396,Female,58,Masters,18,36,21,0,26,0.0,6,45,Semi-Urban,Data Analyst,71147,0 +84397,Male,41,Bachelors,1,50,57,21,82,7.0,5,1,Urban,HR Executive,120822,0 +84398,Male,33,High School,19,3,39,92,84,8.0,6,71,Semi-Urban,Data Analyst,45473,0 +84399,Male,38,Diploma,12,89,60,64,66,7.0,1,2,Urban,Software Engineer,144907,0 +84400,Male,23,Masters,14,52,8,42,4,7.0,1,12,Semi-Urban,HR Executive,120863,0 +84401,Male,32,High School,0,50,91,50,56,0.0,4,30,Rural,ML Engineer,105269,0 +84402,Female,51,Bachelors,1,31,97,75,87,5.0,4,4,Urban,Software Engineer,48086,0 +84403,Male,41,Bachelors,10,23,37,9,14,3.0,3,59,Urban,Data Analyst,70876,0 +84404,Female,57,High School,1,57,28,39,60,6.0,2,17,Urban,ML Engineer,145459,0 +84405,Male,51,Masters,12,76,28,79,20,3.0,1,33,Urban,ML Engineer,120468,0 +84406,Male,44,Bachelors,3,2,43,22,50,9.0,4,45,Urban,ML Engineer,141845,0 +84407,Female,26,Masters,11,49,48,98,66,7.0,6,26,Urban,HR Executive,44747,0 +84408,Male,34,Masters,6,3,87,1,40,9.0,1,24,Rural,HR Executive,65060,0 +84409,Other,41,High School,1,61,12,6,62,5.0,0,10,Urban,Software Engineer,85338,0 +84410,Female,42,Diploma,3,66,43,58,78,9.0,5,93,Urban,Manager,75262,1 +84411,Female,33,Diploma,7,79,16,47,28,8.0,3,90,Semi-Urban,Data Analyst,65130,0 +84412,Male,29,Bachelors,5,60,77,90,9,5.0,4,52,Rural,Manager,62983,1 +84413,Male,29,Masters,15,27,81,2,88,6.0,6,84,Urban,HR Executive,32513,0 +84414,Male,34,Masters,15,54,61,3,20,9.0,7,86,Urban,ML Engineer,26882,0 +84415,Male,44,High School,7,63,79,21,99,9.0,0,47,Urban,Data Analyst,33716,0 +84416,Male,51,Bachelors,1,73,90,22,54,7.0,5,0,Urban,ML Engineer,23444,0 +84417,Female,58,Diploma,11,38,88,57,82,3.0,4,58,Urban,Data Analyst,148653,1 +84418,Other,25,High School,2,3,63,32,10,4.0,0,15,Urban,HR Executive,82134,0 +84419,Female,45,Bachelors,5,66,67,40,17,8.0,6,64,Urban,Manager,58082,0 +84420,Female,29,Diploma,19,63,34,85,66,9.0,4,59,Semi-Urban,ML Engineer,92202,1 +84421,Male,23,Bachelors,0,9,9,68,24,8.0,5,48,Urban,ML Engineer,99423,0 +84422,Male,35,Masters,0,8,22,74,80,2.0,1,93,Urban,Manager,40576,0 +84423,Male,38,Bachelors,13,62,73,97,6,8.0,3,35,Urban,Software Engineer,83071,1 +84424,Male,59,Bachelors,6,31,80,15,61,7.0,4,14,Urban,ML Engineer,113762,0 +84425,Male,49,Masters,7,3,4,53,91,7.0,2,56,Semi-Urban,Software Engineer,86964,0 +84426,Male,48,High School,19,42,39,61,93,8.0,3,42,Rural,HR Executive,65752,0 +84427,Male,37,Diploma,14,64,48,51,15,7.0,0,24,Urban,Software Engineer,86533,0 +84428,Male,45,Bachelors,2,77,51,54,44,9.0,0,96,Urban,Manager,134924,1 +84429,Female,52,Bachelors,5,46,79,34,90,2.0,7,49,Urban,ML Engineer,132516,0 +84430,Female,21,Diploma,2,95,9,57,19,3.0,2,99,Semi-Urban,HR Executive,72418,1 +84431,Male,29,Bachelors,2,82,98,57,20,3.0,3,23,Rural,Software Engineer,71446,1 +84432,Other,53,Masters,6,19,19,91,11,6.0,5,55,Urban,Data Analyst,61492,0 +84433,Male,39,High School,6,92,79,54,87,8.0,2,66,Rural,HR Executive,83165,1 +84434,Male,23,Bachelors,13,1,98,6,58,3.0,4,22,Semi-Urban,HR Executive,100178,0 +84435,Male,52,Bachelors,8,67,10,52,90,9.0,6,31,Urban,HR Executive,81400,0 +84436,Other,55,Bachelors,11,5,30,40,38,6.0,3,39,Urban,HR Executive,124287,0 +84437,Female,54,Bachelors,3,16,72,48,29,4.0,2,67,Urban,HR Executive,66380,0 +84438,Male,32,Bachelors,4,68,62,75,84,3.0,0,84,Semi-Urban,ML Engineer,84570,1 +84439,Female,36,Masters,16,60,60,83,48,7.0,6,15,Urban,Manager,39540,0 +84440,Female,57,High School,0,70,30,91,48,3.0,7,74,Rural,Software Engineer,44747,1 +84441,Male,48,PhD,17,16,28,28,52,9.0,3,97,Semi-Urban,HR Executive,44748,0 +84442,Female,33,Diploma,5,18,8,14,59,7.0,0,71,Urban,ML Engineer,78282,0 +84443,Male,48,Diploma,12,61,55,65,74,0.0,4,84,Semi-Urban,Data Analyst,48334,1 +84444,Male,48,Bachelors,12,86,14,61,58,4.0,2,96,Semi-Urban,Data Analyst,24954,1 +84445,Male,26,Diploma,11,57,48,11,64,8.0,2,1,Urban,Software Engineer,32406,0 +84446,Male,39,Bachelors,6,39,21,94,52,9.0,2,3,Rural,Manager,147025,0 +84447,Female,56,PhD,0,21,13,29,44,7.0,3,8,Semi-Urban,Manager,83969,0 +84448,Female,21,Bachelors,4,13,38,49,41,1.0,7,34,Semi-Urban,Manager,46948,0 +84449,Male,59,Bachelors,8,13,5,18,85,6.0,5,99,Semi-Urban,Data Analyst,61246,0 +84450,Female,52,Masters,13,99,11,62,15,5.0,1,16,Urban,Manager,100425,0 +84451,Male,42,Bachelors,15,18,69,31,37,1.0,6,61,Semi-Urban,ML Engineer,118835,0 +84452,Other,48,High School,1,23,77,62,54,0.0,0,60,Urban,ML Engineer,55768,0 +84453,Male,47,Bachelors,4,14,60,7,73,8.0,1,84,Urban,ML Engineer,74109,0 +84454,Male,28,Diploma,16,82,52,19,48,7.0,3,90,Rural,HR Executive,35137,1 +84455,Male,46,Bachelors,5,41,65,38,47,1.0,2,52,Rural,HR Executive,83377,0 +84456,Male,40,Masters,0,90,26,74,33,9.0,6,25,Urban,Manager,131871,0 +84457,Male,40,Bachelors,0,88,42,84,7,7.0,1,29,Urban,ML Engineer,32923,1 +84458,Male,47,Diploma,17,48,11,61,95,2.0,3,99,Urban,Manager,104339,0 +84459,Other,59,Diploma,4,41,7,78,78,5.0,1,1,Rural,Software Engineer,139543,0 +84460,Male,25,PhD,10,3,57,37,36,8.0,0,53,Urban,Data Analyst,97504,0 +84461,Male,25,Diploma,8,14,95,19,47,0.0,6,73,Semi-Urban,Software Engineer,149026,0 +84462,Male,28,Diploma,0,70,92,11,98,4.0,2,61,Urban,Manager,48770,0 +84463,Male,33,Masters,1,16,1,93,89,1.0,1,20,Rural,Manager,101747,0 +84464,Male,54,Bachelors,13,9,18,9,21,0.0,7,0,Rural,Manager,40303,0 +84465,Male,23,Bachelors,4,81,39,4,33,4.0,3,90,Urban,Manager,54809,0 +84466,Female,41,Diploma,6,60,68,21,32,6.0,5,98,Semi-Urban,HR Executive,127942,1 +84467,Male,47,Bachelors,9,69,46,92,76,0.0,2,76,Urban,HR Executive,77027,1 +84468,Male,29,Bachelors,5,5,58,68,57,0.0,3,86,Semi-Urban,Manager,109996,0 +84469,Male,59,Masters,0,92,54,24,94,2.0,4,93,Urban,Data Analyst,55094,1 +84470,Male,52,High School,4,99,30,3,22,3.0,6,70,Urban,Data Analyst,144477,0 +84471,Male,42,Masters,16,46,64,63,28,5.0,7,19,Urban,Manager,102161,0 +84472,Male,29,Bachelors,1,77,76,35,87,3.0,5,57,Rural,HR Executive,41717,1 +84473,Male,59,Masters,17,81,41,14,46,0.0,5,46,Rural,Manager,129649,0 +84474,Female,28,Bachelors,15,24,40,41,63,7.0,3,3,Rural,ML Engineer,64535,0 +84475,Female,46,Bachelors,13,44,6,46,34,5.0,2,63,Semi-Urban,Manager,101661,0 +84476,Male,53,Diploma,12,85,1,82,90,9.0,1,21,Semi-Urban,HR Executive,39636,0 +84477,Male,43,Bachelors,3,99,55,52,89,2.0,7,26,Urban,Manager,24601,0 +84478,Female,31,Bachelors,15,84,85,0,96,0.0,0,94,Urban,Manager,108415,1 +84479,Male,37,High School,9,48,50,91,97,8.0,1,21,Semi-Urban,Manager,114066,0 +84480,Other,34,Diploma,13,14,51,41,53,3.0,6,67,Urban,Data Analyst,41303,0 +84481,Female,29,Masters,13,56,12,17,6,2.0,3,49,Urban,Software Engineer,127893,0 +84482,Male,24,Masters,12,83,46,39,8,2.0,5,77,Rural,Data Analyst,101413,1 +84483,Male,38,Masters,7,96,83,71,93,7.0,0,89,Urban,Software Engineer,64659,1 +84484,Male,53,Bachelors,19,65,50,8,19,1.0,7,26,Urban,Manager,22925,0 +84485,Male,25,Bachelors,3,49,89,30,44,0.0,2,30,Rural,Software Engineer,112842,0 +84486,Male,43,Diploma,12,9,99,15,32,5.0,4,15,Semi-Urban,Manager,90763,0 +84487,Male,31,Masters,3,30,87,28,26,5.0,1,85,Urban,ML Engineer,44062,0 +84488,Male,55,High School,8,36,94,95,26,0.0,2,28,Urban,Software Engineer,96057,1 +84489,Other,21,Bachelors,15,38,59,4,61,8.0,7,42,Semi-Urban,Software Engineer,113165,0 +84490,Male,31,Bachelors,12,89,28,57,16,6.0,3,32,Urban,ML Engineer,20470,0 +84491,Female,57,Masters,2,32,71,63,7,5.0,5,60,Rural,Manager,65762,0 +84492,Female,49,Bachelors,8,59,91,60,28,1.0,3,26,Urban,Software Engineer,120171,0 +84493,Male,58,Bachelors,9,17,66,38,64,6.0,3,86,Urban,Software Engineer,40162,0 +84494,Female,53,Diploma,2,79,58,82,38,0.0,5,72,Urban,ML Engineer,113978,1 +84495,Male,34,PhD,18,69,15,38,7,2.0,1,73,Semi-Urban,Data Analyst,46548,0 +84496,Female,43,Diploma,10,14,49,3,10,1.0,3,75,Urban,ML Engineer,99381,0 +84497,Female,56,Masters,6,33,6,44,76,3.0,2,27,Semi-Urban,Software Engineer,90546,0 +84498,Male,48,Bachelors,9,53,79,55,64,0.0,6,33,Semi-Urban,Data Analyst,26575,0 +84499,Male,36,Diploma,4,96,45,23,19,8.0,1,2,Semi-Urban,HR Executive,25025,0 +84500,Male,35,High School,0,27,56,94,64,2.0,3,56,Semi-Urban,HR Executive,56618,0 +84501,Female,44,Bachelors,19,85,31,1,63,6.0,3,65,Semi-Urban,ML Engineer,136676,0 +84502,Female,34,PhD,11,88,64,13,19,9.0,1,83,Rural,Software Engineer,138814,1 +84503,Male,37,Diploma,2,35,76,69,15,1.0,0,2,Urban,HR Executive,77754,0 +84504,Male,38,Bachelors,8,45,89,49,50,8.0,2,85,Urban,Data Analyst,91591,1 +84505,Male,42,Bachelors,2,58,34,34,40,1.0,0,69,Rural,HR Executive,91521,0 +84506,Male,37,Bachelors,2,5,1,19,2,0.0,1,65,Rural,Software Engineer,108318,0 +84507,Male,39,PhD,10,59,27,94,17,7.0,3,67,Urban,Manager,99585,1 +84508,Male,26,Masters,0,9,18,4,42,2.0,6,49,Urban,Software Engineer,129947,0 +84509,Male,28,Masters,16,33,44,68,17,5.0,2,71,Urban,Software Engineer,123401,0 +84510,Female,28,High School,5,0,75,87,50,4.0,6,7,Urban,Data Analyst,100086,0 +84511,Male,43,Diploma,0,51,41,8,5,3.0,1,69,Urban,ML Engineer,120850,0 +84512,Male,45,Bachelors,2,92,10,42,38,9.0,1,48,Urban,Manager,121533,0 +84513,Male,25,Bachelors,10,30,5,1,58,9.0,4,42,Urban,Software Engineer,95358,0 +84514,Male,41,Diploma,19,38,42,85,56,6.0,5,42,Urban,Data Analyst,136338,0 +84515,Male,36,Bachelors,10,98,10,82,47,7.0,2,63,Semi-Urban,HR Executive,131859,1 +84516,Male,44,Bachelors,13,1,5,36,73,2.0,5,83,Urban,Manager,28919,0 +84517,Male,48,Bachelors,0,90,45,49,7,4.0,0,69,Rural,Software Engineer,95127,1 +84518,Female,24,Bachelors,5,9,57,41,78,6.0,7,3,Rural,Manager,42284,0 +84519,Male,44,Bachelors,11,92,32,60,90,7.0,1,90,Semi-Urban,Data Analyst,63008,1 +84520,Male,43,Bachelors,9,7,78,48,64,8.0,2,45,Urban,HR Executive,126913,0 +84521,Female,33,Masters,12,75,85,18,7,0.0,4,64,Rural,ML Engineer,24375,1 +84522,Male,27,Bachelors,5,76,38,22,33,7.0,1,81,Rural,ML Engineer,93820,0 +84523,Female,53,High School,7,69,6,1,33,2.0,6,12,Urban,HR Executive,88505,0 +84524,Other,45,Diploma,2,15,59,45,62,2.0,1,42,Rural,HR Executive,39122,0 +84525,Female,33,Masters,7,33,60,76,30,2.0,5,86,Urban,ML Engineer,66793,1 +84526,Male,25,Diploma,8,99,42,81,43,4.0,3,91,Rural,ML Engineer,62117,1 +84527,Male,46,Masters,17,14,47,85,91,2.0,1,76,Urban,ML Engineer,62044,0 +84528,Female,28,High School,9,73,76,79,48,5.0,2,99,Semi-Urban,Software Engineer,81000,1 +84529,Male,30,Bachelors,9,73,58,78,77,9.0,1,47,Rural,ML Engineer,53159,1 +84530,Male,44,Diploma,17,47,99,23,75,0.0,0,60,Semi-Urban,Data Analyst,56251,0 +84531,Male,53,High School,3,60,12,17,68,4.0,4,82,Urban,Software Engineer,86483,0 +84532,Male,23,Diploma,9,73,99,12,57,1.0,7,17,Semi-Urban,Data Analyst,68129,0 +84533,Female,56,Bachelors,8,82,34,63,56,7.0,6,1,Rural,HR Executive,105809,0 +84534,Female,27,Bachelors,10,11,76,12,59,3.0,1,10,Urban,HR Executive,57095,0 +84535,Female,32,Bachelors,12,12,31,40,85,3.0,6,27,Urban,Software Engineer,149677,0 +84536,Female,39,Bachelors,10,32,45,21,0,5.0,6,69,Urban,Manager,58256,0 +84537,Female,56,Bachelors,18,96,39,84,81,7.0,5,1,Rural,Software Engineer,43016,0 +84538,Female,36,Bachelors,0,23,56,48,65,9.0,3,15,Urban,Software Engineer,146257,0 +84539,Male,34,High School,13,41,2,60,44,3.0,1,4,Urban,HR Executive,43622,0 +84540,Other,22,Masters,18,14,69,47,81,9.0,5,83,Semi-Urban,ML Engineer,149832,0 +84541,Male,42,Diploma,8,16,35,12,3,1.0,5,6,Urban,Manager,43052,0 +84542,Male,33,Bachelors,17,21,82,22,22,1.0,7,48,Rural,ML Engineer,25728,0 +84543,Male,56,PhD,6,12,56,41,91,2.0,2,2,Rural,Software Engineer,26964,0 +84544,Male,54,Bachelors,6,51,1,31,92,2.0,2,83,Urban,Manager,77459,0 +84545,Male,33,High School,11,63,21,63,7,2.0,6,55,Urban,Data Analyst,41795,0 +84546,Other,39,Masters,13,13,89,36,68,7.0,4,62,Urban,Manager,45723,0 +84547,Male,43,High School,16,29,48,55,36,3.0,5,0,Semi-Urban,Manager,81755,0 +84548,Other,52,Bachelors,18,43,81,71,63,4.0,1,98,Semi-Urban,Software Engineer,48241,1 +84549,Female,55,High School,14,32,0,74,82,3.0,1,16,Urban,Software Engineer,61804,0 +84550,Other,32,Bachelors,17,36,68,41,63,7.0,0,89,Semi-Urban,HR Executive,34378,0 +84551,Female,27,Bachelors,5,55,51,98,1,8.0,6,81,Semi-Urban,Software Engineer,79387,1 +84552,Female,35,Bachelors,16,93,15,15,94,8.0,2,48,Urban,Manager,27288,0 +84553,Male,33,Bachelors,9,12,2,62,63,5.0,5,27,Urban,HR Executive,97499,0 +84554,Other,45,Bachelors,2,78,29,46,97,1.0,1,30,Urban,HR Executive,128300,0 +84555,Male,35,Diploma,17,76,64,8,1,1.0,7,79,Urban,HR Executive,101408,0 +84556,Male,25,High School,4,15,92,28,69,4.0,5,91,Urban,ML Engineer,132454,0 +84557,Other,26,Bachelors,13,37,5,0,53,8.0,1,55,Semi-Urban,Software Engineer,83229,0 +84558,Male,28,Bachelors,4,79,6,66,92,1.0,7,76,Semi-Urban,ML Engineer,89348,0 +84559,Male,21,Diploma,9,30,79,71,9,1.0,0,10,Urban,Data Analyst,86631,0 +84560,Female,58,Bachelors,16,18,0,21,25,9.0,6,54,Urban,HR Executive,64429,0 +84561,Male,59,PhD,6,92,35,91,95,6.0,0,69,Semi-Urban,Manager,148850,1 +84562,Male,24,High School,11,37,2,25,53,5.0,4,41,Urban,Data Analyst,98066,0 +84563,Female,50,High School,1,99,53,11,79,2.0,7,97,Urban,Manager,39848,1 +84564,Male,29,Bachelors,5,94,8,80,51,7.0,0,6,Urban,ML Engineer,117415,0 +84565,Female,53,Bachelors,19,10,40,23,59,3.0,6,58,Semi-Urban,Data Analyst,36770,0 +84566,Male,40,Masters,16,36,55,13,31,5.0,7,78,Urban,ML Engineer,127426,0 +84567,Male,25,Bachelors,17,23,50,92,1,4.0,4,29,Urban,HR Executive,101663,0 +84568,Female,36,Bachelors,3,26,84,34,37,8.0,7,43,Rural,Data Analyst,42497,0 +84569,Female,36,PhD,7,55,26,16,97,7.0,1,48,Urban,Software Engineer,29176,0 +84570,Male,40,Diploma,0,72,99,48,74,2.0,1,57,Urban,Data Analyst,108752,1 +84571,Male,38,Bachelors,8,85,14,98,18,7.0,5,55,Urban,HR Executive,133606,1 +84572,Female,49,Masters,13,44,89,55,27,4.0,1,95,Semi-Urban,ML Engineer,90268,1 +84573,Male,48,Bachelors,3,23,52,60,5,8.0,0,61,Semi-Urban,HR Executive,110702,0 +84574,Female,45,Bachelors,9,3,84,96,38,0.0,0,74,Urban,Manager,114460,1 +84575,Male,48,High School,8,0,12,53,21,5.0,7,25,Rural,ML Engineer,22876,0 +84576,Male,39,Diploma,13,73,38,67,58,4.0,4,11,Urban,Software Engineer,119069,0 +84577,Other,38,Bachelors,11,1,85,22,36,9.0,2,46,Rural,Software Engineer,26276,0 +84578,Male,47,Diploma,0,99,58,1,57,8.0,6,33,Urban,ML Engineer,70069,0 +84579,Male,41,Diploma,9,31,8,64,61,1.0,6,11,Rural,Manager,117075,0 +84580,Female,29,High School,2,3,30,84,98,2.0,6,48,Rural,HR Executive,44440,0 +84581,Female,36,Masters,6,97,49,36,19,2.0,2,11,Urban,ML Engineer,87285,0 +84582,Female,50,Bachelors,17,49,0,16,1,9.0,5,29,Semi-Urban,HR Executive,22956,0 +84583,Male,41,High School,0,95,40,14,56,6.0,3,83,Semi-Urban,Software Engineer,98243,0 +84584,Female,44,Bachelors,6,32,52,67,97,0.0,4,80,Rural,ML Engineer,144243,0 +84585,Male,50,Masters,18,54,22,74,9,0.0,6,50,Semi-Urban,HR Executive,148925,0 +84586,Male,26,Diploma,8,96,52,98,74,0.0,2,80,Urban,Manager,143040,1 +84587,Male,55,Diploma,17,93,28,53,80,4.0,0,99,Urban,ML Engineer,120203,1 +84588,Male,40,Bachelors,1,29,87,60,16,1.0,0,57,Rural,ML Engineer,105559,0 +84589,Female,40,Bachelors,7,47,86,31,40,6.0,2,11,Urban,Manager,56036,0 +84590,Male,37,Diploma,1,80,96,73,12,8.0,6,36,Semi-Urban,Manager,46403,1 +84591,Female,46,Bachelors,16,21,16,45,72,8.0,0,49,Urban,ML Engineer,58945,0 +84592,Male,51,Diploma,12,51,78,43,32,0.0,0,11,Urban,Data Analyst,35542,0 +84593,Male,53,Bachelors,12,43,42,61,93,9.0,5,77,Rural,Software Engineer,44170,0 +84594,Male,57,High School,8,18,34,71,23,8.0,4,3,Urban,Data Analyst,90397,0 +84595,Female,25,Diploma,7,35,32,6,94,9.0,2,70,Urban,HR Executive,61764,0 +84596,Male,56,Masters,11,53,90,78,45,7.0,0,36,Semi-Urban,Data Analyst,73308,1 +84597,Female,48,Diploma,16,33,80,62,15,1.0,0,88,Semi-Urban,Manager,93598,1 +84598,Male,53,High School,14,59,76,78,4,7.0,0,62,Rural,HR Executive,108219,1 +84599,Female,34,PhD,7,37,22,18,74,9.0,5,97,Rural,Data Analyst,121218,0 +84600,Female,29,Bachelors,2,26,60,61,1,9.0,3,63,Urban,ML Engineer,24173,0 +84601,Male,44,Diploma,18,64,4,11,5,4.0,7,4,Urban,Data Analyst,33342,0 +84602,Female,56,Bachelors,9,41,25,96,89,6.0,6,90,Urban,Manager,75631,1 +84603,Male,52,Masters,18,23,63,67,48,8.0,1,54,Urban,Software Engineer,53696,0 +84604,Female,40,Bachelors,11,27,89,12,54,6.0,6,40,Semi-Urban,Software Engineer,97798,0 +84605,Female,47,High School,7,86,31,92,50,6.0,5,60,Urban,Data Analyst,147825,1 +84606,Male,53,Bachelors,19,96,34,53,6,0.0,7,51,Rural,Data Analyst,118782,0 +84607,Male,36,High School,9,29,75,48,41,0.0,1,26,Rural,Software Engineer,20557,0 +84608,Male,34,Bachelors,10,2,87,99,37,4.0,3,17,Urban,Manager,119331,0 +84609,Male,53,Diploma,14,50,65,11,72,1.0,0,48,Rural,HR Executive,139174,0 +84610,Male,28,Diploma,14,44,69,88,44,8.0,1,39,Urban,Data Analyst,59660,1 +84611,Male,59,Masters,5,86,9,24,4,4.0,6,24,Urban,Manager,112715,0 +84612,Female,48,High School,18,73,48,80,59,8.0,3,94,Urban,Software Engineer,101842,1 +84613,Female,44,Diploma,14,31,14,38,46,2.0,6,65,Urban,Manager,103267,0 +84614,Male,43,High School,19,8,94,83,7,0.0,5,23,Semi-Urban,Data Analyst,101487,0 +84615,Male,21,Bachelors,8,53,50,82,1,1.0,6,82,Rural,HR Executive,69531,1 +84616,Female,41,High School,13,18,73,98,44,9.0,7,48,Urban,HR Executive,136326,0 +84617,Female,23,High School,4,59,20,87,36,2.0,7,68,Urban,HR Executive,35708,0 +84618,Female,21,Bachelors,6,72,45,73,37,2.0,0,92,Rural,HR Executive,33691,1 +84619,Male,25,Bachelors,12,28,96,76,91,8.0,0,70,Rural,Manager,53387,1 +84620,Female,41,High School,16,92,76,2,12,8.0,2,94,Urban,Data Analyst,67290,1 +84621,Male,53,Bachelors,4,33,19,92,79,5.0,7,13,Rural,Data Analyst,55125,0 +84622,Male,33,Diploma,11,78,31,75,18,1.0,0,93,Semi-Urban,Software Engineer,40276,1 +84623,Male,48,PhD,11,80,59,84,14,3.0,0,74,Semi-Urban,Software Engineer,71623,1 +84624,Other,42,Bachelors,6,87,62,87,52,8.0,0,8,Urban,Manager,100086,1 +84625,Male,54,High School,18,49,69,45,98,7.0,7,53,Rural,HR Executive,75691,0 +84626,Female,54,Bachelors,15,13,88,53,48,9.0,2,94,Urban,ML Engineer,79148,1 +84627,Male,54,Masters,11,13,92,58,90,9.0,3,68,Semi-Urban,ML Engineer,93570,0 +84628,Male,40,Bachelors,17,89,10,84,73,4.0,7,6,Semi-Urban,Data Analyst,144240,0 +84629,Male,42,PhD,11,90,90,38,3,1.0,0,69,Semi-Urban,Manager,29723,1 +84630,Female,45,Diploma,4,1,40,8,28,1.0,2,31,Urban,ML Engineer,22241,0 +84631,Male,40,Bachelors,17,20,96,45,34,8.0,6,12,Semi-Urban,HR Executive,127998,0 +84632,Male,39,Bachelors,0,54,11,55,32,2.0,7,54,Rural,Data Analyst,116288,0 +84633,Male,25,High School,8,7,1,67,22,5.0,3,18,Urban,HR Executive,36644,0 +84634,Female,51,Masters,9,26,78,82,54,9.0,0,59,Rural,ML Engineer,54426,1 +84635,Male,32,Diploma,18,13,63,70,23,3.0,3,57,Urban,Manager,52405,0 +84636,Male,21,Bachelors,10,81,83,88,71,5.0,0,13,Urban,Data Analyst,69116,1 +84637,Male,27,Diploma,15,36,2,69,68,4.0,2,38,Urban,HR Executive,101345,0 +84638,Male,24,High School,6,59,95,54,47,0.0,7,18,Urban,Data Analyst,29705,0 +84639,Female,40,High School,11,41,58,11,35,8.0,5,29,Urban,ML Engineer,123170,0 +84640,Male,53,High School,16,49,97,38,91,6.0,3,99,Semi-Urban,HR Executive,101578,1 +84641,Female,26,Diploma,14,0,45,26,99,8.0,7,92,Semi-Urban,Manager,92136,0 +84642,Male,43,High School,15,92,9,30,19,2.0,7,22,Semi-Urban,Data Analyst,88639,0 +84643,Female,36,Diploma,7,4,28,34,91,8.0,4,48,Semi-Urban,Software Engineer,141960,0 +84644,Female,38,Diploma,15,50,9,23,36,1.0,7,93,Urban,Software Engineer,92122,0 +84645,Male,47,Bachelors,11,10,58,59,22,3.0,2,70,Urban,ML Engineer,66656,0 +84646,Male,48,Bachelors,8,16,81,53,87,7.0,1,5,Urban,Software Engineer,36684,0 +84647,Male,32,Bachelors,4,13,25,55,13,7.0,0,56,Rural,Software Engineer,135507,0 +84648,Male,48,Bachelors,3,99,58,2,89,4.0,3,64,Urban,Data Analyst,131215,0 +84649,Male,40,Diploma,16,83,75,38,91,0.0,1,54,Semi-Urban,Software Engineer,125258,1 +84650,Male,22,Diploma,3,60,79,38,73,1.0,0,28,Urban,HR Executive,95487,0 +84651,Male,29,Bachelors,10,17,57,25,79,3.0,2,16,Urban,Data Analyst,64849,0 +84652,Male,29,Masters,18,41,8,25,42,6.0,0,38,Urban,ML Engineer,130795,0 +84653,Male,47,PhD,6,97,47,17,22,9.0,2,71,Urban,Data Analyst,69710,0 +84654,Male,40,Bachelors,3,78,78,72,39,0.0,6,77,Urban,HR Executive,109208,1 +84655,Other,31,Bachelors,14,52,76,37,71,6.0,2,76,Rural,Manager,108146,1 +84656,Male,38,Masters,6,11,75,63,26,0.0,7,66,Semi-Urban,HR Executive,145061,0 +84657,Male,37,Diploma,5,80,24,93,83,3.0,5,61,Urban,Manager,66220,1 +84658,Male,51,Bachelors,16,2,16,29,65,0.0,0,6,Semi-Urban,Manager,95231,0 +84659,Male,33,Masters,12,54,75,32,88,4.0,4,24,Urban,HR Executive,136103,0 +84660,Female,43,Bachelors,3,56,63,39,45,1.0,1,88,Rural,HR Executive,77181,1 +84661,Female,58,Masters,1,66,98,79,28,1.0,5,48,Urban,ML Engineer,45195,1 +84662,Male,57,Diploma,2,11,30,51,99,9.0,2,65,Urban,ML Engineer,55241,0 +84663,Female,38,Bachelors,17,13,11,16,36,3.0,2,73,Urban,Software Engineer,131634,0 +84664,Female,29,Diploma,13,53,59,70,2,9.0,0,56,Urban,Manager,84467,0 +84665,Male,37,Bachelors,13,50,39,97,4,7.0,1,89,Semi-Urban,Data Analyst,113612,1 +84666,Female,41,High School,14,43,89,99,42,8.0,2,47,Rural,ML Engineer,106948,1 +84667,Female,45,Bachelors,15,98,17,45,44,1.0,3,93,Semi-Urban,ML Engineer,91744,1 +84668,Male,44,Bachelors,4,56,41,88,42,3.0,7,64,Urban,ML Engineer,61707,1 +84669,Female,44,Bachelors,6,55,9,2,1,4.0,1,99,Urban,Software Engineer,133801,0 +84670,Female,51,High School,12,72,51,29,70,6.0,6,24,Urban,Software Engineer,116077,0 +84671,Female,26,High School,14,77,6,28,70,4.0,6,6,Urban,Data Analyst,39965,0 +84672,Male,55,Masters,16,47,5,35,98,5.0,5,4,Semi-Urban,ML Engineer,27919,0 +84673,Male,38,PhD,12,12,45,18,99,2.0,7,58,Rural,ML Engineer,137824,0 +84674,Other,34,Bachelors,2,38,8,97,25,8.0,1,9,Semi-Urban,Software Engineer,39240,0 +84675,Male,50,Bachelors,4,0,19,69,7,8.0,1,64,Urban,HR Executive,57181,0 +84676,Female,43,Bachelors,0,50,1,86,13,1.0,6,63,Rural,Manager,124110,0 +84677,Female,27,Bachelors,19,58,81,93,28,0.0,7,31,Rural,Software Engineer,125577,1 +84678,Male,28,Masters,7,23,61,93,41,6.0,1,61,Urban,Data Analyst,145809,1 +84679,Male,33,Diploma,3,33,35,54,49,3.0,3,55,Rural,ML Engineer,28554,0 +84680,Male,35,Bachelors,16,96,35,4,5,3.0,2,37,Urban,Manager,146588,0 +84681,Male,45,Bachelors,19,85,40,80,37,3.0,2,22,Urban,HR Executive,38566,0 +84682,Female,37,Masters,8,24,40,81,80,8.0,5,13,Semi-Urban,Manager,26798,0 +84683,Female,47,Masters,8,35,9,43,50,7.0,3,63,Semi-Urban,HR Executive,32802,0 +84684,Male,38,Bachelors,0,22,46,84,63,4.0,0,11,Urban,HR Executive,147401,0 +84685,Female,47,Bachelors,2,51,58,35,95,4.0,3,99,Urban,Software Engineer,31884,1 +84686,Other,50,Masters,5,46,46,84,76,8.0,2,82,Urban,Data Analyst,81004,1 +84687,Female,37,Bachelors,19,15,79,43,49,5.0,6,31,Rural,Software Engineer,41833,0 +84688,Male,30,Bachelors,7,44,62,65,7,6.0,2,94,Semi-Urban,Manager,92392,1 +84689,Female,36,Masters,13,58,97,13,7,4.0,7,28,Urban,HR Executive,124417,0 +84690,Female,52,Bachelors,18,2,28,24,60,7.0,7,59,Urban,Software Engineer,142889,0 +84691,Female,33,High School,14,56,51,12,5,3.0,7,43,Urban,Software Engineer,29857,0 +84692,Male,34,Diploma,4,86,40,33,65,7.0,3,1,Semi-Urban,Software Engineer,57266,0 +84693,Male,36,Masters,15,9,7,37,36,9.0,7,22,Rural,ML Engineer,87398,0 +84694,Male,29,Diploma,18,14,21,86,82,2.0,4,83,Urban,ML Engineer,64866,0 +84695,Male,51,High School,19,21,16,57,24,2.0,2,62,Rural,HR Executive,125889,0 +84696,Male,51,Masters,1,50,69,52,28,8.0,0,82,Rural,ML Engineer,29073,1 +84697,Male,39,Diploma,10,39,89,48,19,1.0,2,83,Semi-Urban,Data Analyst,41211,1 +84698,Male,49,Masters,0,97,28,15,38,7.0,5,77,Urban,Software Engineer,69871,0 +84699,Other,40,Bachelors,4,91,1,37,83,8.0,7,39,Semi-Urban,Manager,142017,0 +84700,Male,22,Bachelors,18,55,66,55,30,8.0,6,62,Rural,ML Engineer,98409,1 +84701,Female,59,Bachelors,10,88,99,12,38,5.0,4,72,Semi-Urban,ML Engineer,76925,1 +84702,Male,25,Diploma,1,91,85,92,83,7.0,1,62,Rural,Manager,149484,1 +84703,Female,43,Bachelors,16,58,27,50,54,5.0,0,14,Urban,HR Executive,111128,0 +84704,Male,23,Diploma,2,7,73,21,13,4.0,0,1,Urban,Data Analyst,38699,0 +84705,Male,50,Diploma,5,57,1,72,43,9.0,6,4,Urban,Software Engineer,60825,0 +84706,Female,52,Diploma,11,65,8,71,29,4.0,5,40,Urban,ML Engineer,136043,0 +84707,Female,27,Bachelors,7,75,43,24,87,6.0,1,10,Rural,Manager,96052,0 +84708,Female,28,High School,6,29,59,33,1,1.0,5,6,Semi-Urban,ML Engineer,60019,0 +84709,Other,52,High School,7,97,51,49,43,6.0,7,49,Rural,Software Engineer,144861,1 +84710,Male,33,Diploma,15,40,71,7,17,3.0,3,94,Rural,HR Executive,39585,0 +84711,Male,48,Bachelors,11,23,12,13,47,3.0,0,15,Rural,HR Executive,94960,0 +84712,Male,48,PhD,10,25,64,65,99,3.0,2,34,Rural,Manager,70259,0 +84713,Male,21,Diploma,2,82,45,36,62,8.0,0,50,Urban,HR Executive,29917,0 +84714,Female,43,High School,18,40,79,95,8,2.0,2,17,Urban,Data Analyst,123335,0 +84715,Female,31,High School,19,99,84,22,92,4.0,2,73,Urban,Manager,28460,1 +84716,Female,38,Masters,8,0,24,72,45,7.0,4,0,Semi-Urban,ML Engineer,77494,0 +84717,Male,28,Diploma,15,83,66,0,8,1.0,1,61,Urban,Software Engineer,93179,0 +84718,Female,40,High School,8,81,86,65,97,9.0,2,72,Semi-Urban,Manager,103178,1 +84719,Male,59,Masters,7,59,33,44,20,5.0,7,60,Urban,ML Engineer,39317,0 +84720,Female,26,Diploma,18,24,40,72,44,4.0,5,84,Semi-Urban,ML Engineer,30012,0 +84721,Male,21,High School,2,28,74,83,6,2.0,1,92,Rural,Manager,30007,1 +84722,Male,35,PhD,14,0,60,4,44,7.0,0,21,Urban,HR Executive,142770,0 +84723,Male,48,High School,14,14,68,83,54,6.0,6,34,Semi-Urban,Manager,69613,0 +84724,Female,40,Diploma,5,3,64,98,77,6.0,4,86,Urban,HR Executive,91112,1 +84725,Male,48,Bachelors,4,21,76,47,87,8.0,5,42,Urban,Software Engineer,71292,0 +84726,Female,44,PhD,0,15,36,82,7,0.0,4,14,Urban,Software Engineer,133587,0 +84727,Male,46,High School,3,22,10,59,13,4.0,3,37,Rural,ML Engineer,57494,0 +84728,Female,21,Diploma,15,15,88,17,74,3.0,5,30,Urban,Software Engineer,103145,0 +84729,Male,46,Masters,18,19,48,92,48,1.0,7,9,Urban,Manager,48752,0 +84730,Female,39,PhD,18,56,15,59,52,3.0,6,57,Urban,HR Executive,138257,0 +84731,Female,57,PhD,3,94,40,3,10,7.0,0,43,Urban,Software Engineer,92365,0 +84732,Male,39,Diploma,19,62,54,26,64,2.0,3,55,Rural,Manager,31345,0 +84733,Male,22,Masters,0,33,14,90,52,3.0,5,56,Urban,Data Analyst,95706,0 +84734,Male,55,High School,12,80,29,60,1,5.0,2,86,Urban,Software Engineer,51293,1 +84735,Male,43,Diploma,7,99,77,10,81,8.0,5,19,Urban,ML Engineer,26335,0 +84736,Male,51,Bachelors,11,28,86,61,50,9.0,2,80,Rural,ML Engineer,149490,1 +84737,Female,24,Bachelors,11,60,28,2,73,0.0,1,12,Rural,Data Analyst,121568,0 +84738,Male,28,Masters,9,15,40,24,54,1.0,6,80,Semi-Urban,ML Engineer,76508,0 +84739,Male,56,Diploma,19,67,62,51,47,4.0,1,23,Urban,Manager,88235,0 +84740,Female,26,Bachelors,16,4,94,45,77,6.0,6,50,Rural,ML Engineer,137087,0 +84741,Male,31,High School,9,32,29,60,73,8.0,5,82,Rural,Software Engineer,114403,0 +84742,Male,41,Diploma,16,60,14,27,80,8.0,7,3,Rural,ML Engineer,83279,0 +84743,Male,35,Bachelors,13,55,89,46,20,6.0,2,21,Urban,Software Engineer,90996,0 +84744,Female,38,PhD,19,10,64,50,10,1.0,1,88,Urban,Manager,62002,0 +84745,Male,58,Masters,19,7,87,4,47,3.0,1,85,Urban,ML Engineer,148466,0 +84746,Male,23,High School,4,18,28,6,82,2.0,6,64,Rural,Manager,29664,0 +84747,Male,31,Masters,11,16,78,76,51,6.0,3,52,Rural,ML Engineer,96226,0 +84748,Male,32,Diploma,12,13,71,99,90,8.0,7,69,Semi-Urban,ML Engineer,33776,1 +84749,Male,50,Bachelors,17,77,26,15,30,1.0,7,99,Semi-Urban,HR Executive,84364,0 +84750,Male,57,Diploma,15,92,24,32,22,1.0,7,92,Urban,ML Engineer,139626,1 +84751,Male,56,Diploma,3,60,72,74,21,9.0,0,48,Urban,HR Executive,135295,1 +84752,Male,26,Masters,6,81,5,34,55,4.0,1,73,Urban,Software Engineer,103107,0 +84753,Female,59,Masters,19,29,49,43,3,2.0,2,16,Urban,Data Analyst,64542,0 +84754,Female,57,Masters,15,51,20,27,69,8.0,5,41,Urban,Manager,114335,0 +84755,Male,52,PhD,13,71,37,75,9,7.0,3,66,Urban,Software Engineer,131610,1 +84756,Male,48,Bachelors,10,16,87,43,29,5.0,5,71,Urban,ML Engineer,57501,0 +84757,Male,26,Diploma,13,36,5,21,71,6.0,7,81,Rural,HR Executive,64011,0 +84758,Female,33,Bachelors,13,50,84,50,75,4.0,7,74,Rural,Data Analyst,69068,1 +84759,Male,33,Masters,3,51,33,15,36,1.0,1,15,Urban,Data Analyst,34800,0 +84760,Female,57,Bachelors,0,72,80,55,5,5.0,7,18,Urban,ML Engineer,34134,0 +84761,Male,49,Bachelors,6,68,67,45,95,9.0,7,31,Urban,ML Engineer,119384,0 +84762,Female,28,High School,7,68,40,73,57,9.0,2,87,Urban,ML Engineer,78091,1 +84763,Male,35,Bachelors,15,53,80,69,23,9.0,0,33,Semi-Urban,ML Engineer,74881,1 +84764,Male,52,PhD,5,70,49,16,79,1.0,7,9,Rural,ML Engineer,118743,0 +84765,Other,55,Diploma,3,19,9,54,2,0.0,7,85,Rural,Manager,29754,0 +84766,Female,27,Bachelors,0,94,25,34,29,5.0,2,67,Semi-Urban,Software Engineer,120132,0 +84767,Male,29,Bachelors,3,20,54,84,54,1.0,1,0,Urban,HR Executive,121391,0 +84768,Female,42,PhD,9,43,60,79,7,3.0,3,64,Urban,Data Analyst,130566,1 +84769,Male,47,Diploma,8,43,21,84,33,3.0,3,47,Semi-Urban,Software Engineer,131932,0 +84770,Female,50,Diploma,19,30,34,70,53,6.0,3,73,Urban,HR Executive,129578,0 +84771,Male,31,PhD,9,65,74,24,91,4.0,4,26,Urban,Software Engineer,98876,0 +84772,Other,21,High School,7,69,10,88,89,6.0,5,58,Urban,ML Engineer,36449,0 +84773,Male,42,Bachelors,9,59,19,34,89,3.0,3,60,Rural,ML Engineer,40964,0 +84774,Male,28,Masters,11,33,23,63,66,5.0,1,59,Urban,Software Engineer,38056,0 +84775,Female,29,Bachelors,19,11,55,9,77,9.0,1,74,Rural,Manager,55739,0 +84776,Female,37,Bachelors,11,73,26,61,7,8.0,3,7,Urban,Software Engineer,49934,0 +84777,Female,57,Bachelors,6,66,27,68,16,8.0,4,71,Urban,HR Executive,90370,0 +84778,Female,22,Bachelors,16,23,69,55,50,1.0,0,80,Semi-Urban,ML Engineer,104365,0 +84779,Female,48,Bachelors,10,39,86,36,47,3.0,4,64,Urban,Software Engineer,95308,0 +84780,Female,53,Masters,1,84,47,55,71,4.0,5,62,Urban,Software Engineer,125422,1 +84781,Female,49,Bachelors,15,21,7,1,68,9.0,4,20,Urban,Data Analyst,58109,0 +84782,Male,32,Diploma,16,4,41,68,65,9.0,7,76,Urban,HR Executive,149903,0 +84783,Female,54,Masters,13,28,30,2,16,6.0,3,62,Urban,Data Analyst,102883,0 +84784,Other,50,Bachelors,9,79,12,66,9,1.0,3,23,Semi-Urban,ML Engineer,63620,0 +84785,Male,44,Bachelors,3,77,76,74,82,5.0,6,76,Rural,HR Executive,100178,1 +84786,Female,24,Masters,7,81,26,92,55,5.0,1,38,Urban,HR Executive,21148,0 +84787,Male,33,Masters,2,47,84,12,91,5.0,5,14,Semi-Urban,ML Engineer,24049,0 +84788,Female,27,Masters,11,95,27,93,62,4.0,0,30,Urban,Data Analyst,79004,1 +84789,Male,21,Diploma,6,77,7,63,44,3.0,5,44,Rural,Software Engineer,140948,0 +84790,Female,48,PhD,4,87,68,99,6,8.0,3,16,Semi-Urban,ML Engineer,117756,1 +84791,Male,52,High School,8,85,80,29,36,1.0,2,69,Urban,Manager,109797,1 +84792,Male,33,PhD,9,1,16,95,64,0.0,1,95,Urban,Manager,69778,0 +84793,Other,26,Diploma,5,34,99,9,77,3.0,1,68,Semi-Urban,Data Analyst,94341,0 +84794,Male,27,Bachelors,17,44,49,88,68,6.0,5,64,Rural,ML Engineer,85671,1 +84795,Male,47,Masters,9,15,34,43,5,0.0,0,17,Semi-Urban,Data Analyst,43406,0 +84796,Female,29,Masters,11,73,55,64,11,3.0,2,82,Urban,Data Analyst,115010,1 +84797,Male,38,Masters,18,94,19,3,15,5.0,0,15,Semi-Urban,ML Engineer,61746,0 +84798,Male,41,Diploma,8,89,94,40,72,7.0,0,1,Semi-Urban,Software Engineer,34004,0 +84799,Female,31,Bachelors,10,60,61,20,9,2.0,2,33,Urban,Data Analyst,48327,0 +84800,Female,40,Diploma,9,47,42,19,14,1.0,5,78,Urban,HR Executive,139993,0 +84801,Male,51,Bachelors,12,80,23,41,15,6.0,1,88,Urban,ML Engineer,143512,0 +84802,Male,24,High School,13,67,34,93,73,3.0,5,32,Semi-Urban,ML Engineer,80673,0 +84803,Female,44,Masters,15,59,37,25,86,4.0,3,78,Urban,ML Engineer,52137,0 +84804,Female,50,Diploma,13,35,79,37,78,2.0,4,92,Semi-Urban,Software Engineer,96165,1 +84805,Female,38,High School,17,96,69,64,59,3.0,3,82,Urban,Software Engineer,115059,1 +84806,Male,57,Bachelors,13,69,60,47,40,3.0,6,43,Semi-Urban,ML Engineer,140833,0 +84807,Female,55,Masters,12,58,13,89,97,7.0,3,28,Urban,Software Engineer,137432,0 +84808,Female,53,Bachelors,2,3,54,81,22,8.0,2,62,Urban,ML Engineer,84674,0 +84809,Male,31,PhD,18,57,47,83,79,5.0,1,94,Urban,HR Executive,31871,1 +84810,Female,49,Bachelors,15,98,90,8,98,7.0,4,71,Rural,ML Engineer,102945,1 +84811,Male,46,Bachelors,12,21,20,18,92,7.0,1,50,Rural,HR Executive,136179,0 +84812,Male,50,Masters,0,72,63,6,73,6.0,2,90,Urban,Data Analyst,70499,0 +84813,Male,56,High School,10,99,95,65,78,5.0,4,52,Urban,HR Executive,34105,1 +84814,Female,57,Bachelors,19,22,66,25,38,8.0,3,65,Urban,HR Executive,55923,0 +84815,Male,56,Bachelors,19,37,63,88,26,1.0,1,39,Urban,Manager,26419,0 +84816,Male,26,High School,17,63,16,40,64,0.0,5,61,Urban,HR Executive,75343,0 +84817,Female,33,Bachelors,14,50,32,68,39,4.0,1,11,Rural,Software Engineer,141962,0 +84818,Female,41,Bachelors,7,75,70,33,27,2.0,3,40,Urban,HR Executive,147719,0 +84819,Male,23,Bachelors,10,81,64,78,22,0.0,5,40,Urban,Manager,100558,1 +84820,Male,41,Bachelors,4,85,78,95,57,4.0,7,90,Rural,Software Engineer,113370,1 +84821,Female,44,Bachelors,16,46,18,30,20,9.0,2,79,Semi-Urban,Manager,117374,0 +84822,Female,38,Masters,5,51,86,18,70,6.0,4,52,Semi-Urban,ML Engineer,142261,0 +84823,Male,21,High School,5,73,95,67,28,0.0,0,47,Semi-Urban,Software Engineer,145555,1 +84824,Female,35,Bachelors,0,21,33,47,69,5.0,1,27,Semi-Urban,Data Analyst,33678,0 +84825,Male,55,Diploma,9,22,95,12,56,1.0,2,37,Rural,HR Executive,20284,0 +84826,Male,53,Bachelors,3,10,43,13,99,4.0,5,60,Rural,HR Executive,65917,0 +84827,Male,44,Bachelors,3,57,82,26,92,4.0,4,16,Semi-Urban,Manager,126513,0 +84828,Female,30,Masters,11,17,9,13,91,6.0,7,39,Urban,Manager,99881,0 +84829,Male,37,High School,7,45,56,49,48,8.0,3,15,Semi-Urban,HR Executive,59545,0 +84830,Male,50,Bachelors,4,30,59,75,36,3.0,3,80,Urban,ML Engineer,83433,1 +84831,Female,45,PhD,5,89,68,91,44,0.0,4,31,Urban,ML Engineer,90231,1 +84832,Male,54,High School,16,35,45,20,62,5.0,5,19,Urban,Software Engineer,105631,0 +84833,Male,27,Diploma,11,18,96,18,4,9.0,5,10,Urban,ML Engineer,134069,0 +84834,Male,26,High School,5,95,40,17,80,0.0,4,44,Urban,Software Engineer,100492,0 +84835,Male,43,Bachelors,12,54,2,25,9,3.0,5,79,Urban,HR Executive,102078,0 +84836,Female,57,Bachelors,11,87,76,45,24,0.0,4,93,Urban,HR Executive,74856,1 +84837,Male,35,Masters,1,27,32,60,3,0.0,7,25,Urban,Software Engineer,27699,0 +84838,Female,37,Diploma,3,94,70,6,82,4.0,2,80,Semi-Urban,Data Analyst,109164,1 +84839,Male,58,Diploma,2,98,85,72,51,0.0,3,67,Urban,Data Analyst,133026,1 +84840,Male,22,Bachelors,9,9,79,64,38,2.0,5,20,Urban,ML Engineer,117546,0 +84841,Male,44,High School,1,18,35,72,2,7.0,1,76,Urban,HR Executive,88372,0 +84842,Other,51,Bachelors,8,1,83,85,85,9.0,3,54,Urban,Data Analyst,93343,0 +84843,Female,38,Bachelors,17,7,76,67,4,1.0,0,3,Rural,Manager,121155,0 +84844,Male,34,Diploma,15,46,30,90,63,8.0,7,40,Urban,HR Executive,92741,0 +84845,Male,50,Bachelors,4,24,24,67,72,4.0,5,59,Urban,Data Analyst,129687,0 +84846,Male,42,Masters,0,57,50,52,92,8.0,0,41,Semi-Urban,Manager,49271,0 +84847,Male,21,Bachelors,11,64,88,11,19,9.0,0,56,Rural,Data Analyst,54037,0 +84848,Male,32,Bachelors,4,34,98,40,57,0.0,0,9,Semi-Urban,ML Engineer,69612,0 +84849,Female,21,Diploma,19,23,65,34,77,0.0,5,44,Urban,Manager,104258,0 +84850,Male,42,High School,15,96,20,16,12,8.0,6,0,Rural,HR Executive,31565,0 +84851,Female,47,Bachelors,5,90,34,28,54,9.0,4,76,Urban,HR Executive,23168,0 +84852,Male,29,Masters,6,49,43,10,8,6.0,6,93,Urban,Software Engineer,87712,0 +84853,Female,50,Bachelors,12,58,76,97,87,7.0,3,75,Urban,Manager,83271,1 +84854,Female,47,High School,19,16,39,22,96,8.0,1,57,Semi-Urban,Manager,127268,0 +84855,Female,32,Diploma,6,33,46,74,24,1.0,2,16,Semi-Urban,Software Engineer,71872,0 +84856,Female,53,Bachelors,19,73,95,14,32,7.0,6,68,Semi-Urban,Software Engineer,116037,1 +84857,Female,53,Bachelors,17,16,97,71,56,7.0,5,25,Urban,Software Engineer,86026,0 +84858,Female,22,High School,13,74,28,32,36,7.0,3,45,Urban,HR Executive,83382,0 +84859,Male,30,Bachelors,16,46,4,50,71,8.0,2,15,Urban,ML Engineer,26454,0 +84860,Male,31,Bachelors,13,19,83,3,51,5.0,6,76,Urban,Software Engineer,38035,0 +84861,Female,59,Bachelors,1,12,64,41,9,3.0,4,27,Urban,Data Analyst,69296,0 +84862,Female,37,Bachelors,0,46,6,8,51,7.0,0,11,Urban,ML Engineer,145113,0 +84863,Male,21,Bachelors,0,68,93,53,54,7.0,7,55,Semi-Urban,Manager,27156,1 +84864,Male,30,PhD,3,59,54,29,69,7.0,1,19,Urban,Manager,124663,0 +84865,Female,57,Bachelors,11,39,14,48,61,0.0,2,16,Urban,ML Engineer,37170,0 +84866,Other,45,Diploma,1,84,61,85,81,7.0,1,18,Urban,HR Executive,30032,1 +84867,Male,28,Diploma,3,95,62,62,96,7.0,6,36,Urban,Software Engineer,92690,1 +84868,Female,52,Diploma,18,8,49,5,95,8.0,4,42,Urban,Software Engineer,141979,0 +84869,Male,25,Diploma,0,56,93,31,84,0.0,4,13,Urban,Manager,48948,0 +84870,Male,59,Diploma,17,6,45,40,17,2.0,6,82,Urban,Software Engineer,140662,0 +84871,Male,49,Bachelors,2,79,16,31,59,2.0,3,78,Urban,HR Executive,44891,0 +84872,Male,37,High School,4,7,11,76,75,4.0,7,68,Urban,HR Executive,135660,0 +84873,Male,43,High School,2,85,55,42,71,9.0,2,31,Semi-Urban,ML Engineer,84013,0 +84874,Male,34,Bachelors,4,23,89,43,16,5.0,3,11,Semi-Urban,Software Engineer,101559,0 +84875,Male,55,Diploma,5,25,24,23,18,8.0,6,57,Urban,Data Analyst,57349,0 +84876,Male,47,Bachelors,6,55,86,83,11,4.0,4,80,Urban,ML Engineer,99664,1 +84877,Male,50,Bachelors,13,37,11,49,42,9.0,7,65,Urban,ML Engineer,85783,0 +84878,Other,36,PhD,18,48,67,51,97,1.0,6,64,Urban,ML Engineer,103596,0 +84879,Male,59,Bachelors,10,48,56,19,64,7.0,7,53,Urban,ML Engineer,45591,0 +84880,Male,39,Masters,19,23,59,10,35,3.0,3,52,Rural,Manager,114587,0 +84881,Male,49,Bachelors,15,20,66,38,33,4.0,7,98,Urban,Data Analyst,96584,0 +84882,Male,53,Masters,13,89,68,46,16,8.0,6,6,Urban,HR Executive,80708,0 +84883,Male,52,PhD,3,99,65,58,65,8.0,6,88,Semi-Urban,Data Analyst,86545,1 +84884,Male,45,Masters,6,24,87,98,37,8.0,7,52,Semi-Urban,ML Engineer,92432,1 +84885,Female,49,Bachelors,6,19,28,19,10,6.0,6,13,Urban,Data Analyst,148533,0 +84886,Male,58,Diploma,14,41,68,32,3,0.0,2,74,Urban,HR Executive,46020,0 +84887,Male,22,Diploma,16,74,97,66,45,8.0,4,67,Urban,HR Executive,135212,1 +84888,Male,23,Bachelors,6,59,21,32,84,9.0,4,6,Urban,HR Executive,129301,0 +84889,Male,52,Bachelors,7,77,87,16,63,4.0,7,29,Urban,HR Executive,99000,0 +84890,Female,56,Bachelors,15,15,0,19,92,9.0,4,48,Rural,HR Executive,83564,0 +84891,Male,50,High School,16,20,51,35,62,0.0,6,89,Urban,Data Analyst,31033,0 +84892,Male,28,Bachelors,3,78,46,89,73,9.0,2,72,Urban,Data Analyst,137869,1 +84893,Male,25,Masters,15,55,53,86,12,1.0,1,38,Rural,Data Analyst,140654,0 +84894,Female,25,Bachelors,16,94,24,27,54,1.0,6,26,Urban,Software Engineer,94584,0 +84895,Male,49,Diploma,17,39,30,30,23,1.0,7,98,Urban,ML Engineer,137160,0 +84896,Male,53,Masters,7,45,67,4,77,0.0,2,29,Urban,Manager,22982,0 +84897,Female,55,Bachelors,2,94,95,56,58,1.0,5,18,Urban,HR Executive,30352,1 +84898,Female,39,High School,17,89,81,77,73,6.0,3,78,Urban,Data Analyst,124342,1 +84899,Male,46,Bachelors,11,63,1,52,20,1.0,0,5,Urban,Data Analyst,121287,0 +84900,Female,52,Masters,5,62,2,87,21,4.0,2,11,Semi-Urban,Data Analyst,54466,0 +84901,Male,58,Bachelors,7,68,77,30,84,3.0,4,60,Semi-Urban,ML Engineer,89084,1 +84902,Male,51,High School,7,17,79,78,55,0.0,5,66,Urban,Data Analyst,86320,1 +84903,Female,47,Bachelors,12,12,88,12,45,6.0,2,27,Urban,HR Executive,101222,0 +84904,Male,56,Bachelors,16,60,27,5,13,3.0,2,22,Urban,Manager,65521,0 +84905,Female,45,Bachelors,6,38,34,28,89,3.0,5,83,Urban,ML Engineer,135090,0 +84906,Female,27,Diploma,1,11,51,34,87,5.0,6,37,Urban,Data Analyst,139975,0 +84907,Female,34,Masters,2,41,38,71,26,5.0,7,62,Urban,Data Analyst,131803,0 +84908,Male,58,Bachelors,2,12,12,91,85,7.0,2,52,Urban,HR Executive,111657,0 +84909,Male,42,Bachelors,0,21,63,16,44,0.0,1,27,Urban,HR Executive,20088,0 +84910,Male,47,Bachelors,3,78,43,36,71,9.0,7,89,Semi-Urban,HR Executive,38271,1 +84911,Female,32,Diploma,5,54,16,25,91,9.0,2,93,Semi-Urban,Manager,36848,0 +84912,Male,55,High School,16,67,69,90,0,9.0,6,59,Semi-Urban,Manager,57265,1 +84913,Male,29,Masters,1,67,47,36,67,1.0,1,45,Urban,Data Analyst,78674,0 +84914,Female,45,Bachelors,18,16,54,7,84,4.0,0,78,Semi-Urban,Software Engineer,33940,0 +84915,Male,23,High School,12,91,94,75,44,1.0,1,10,Semi-Urban,Manager,30843,1 +84916,Male,42,Masters,16,21,23,49,46,9.0,3,58,Rural,Software Engineer,65622,0 +84917,Male,31,Bachelors,14,70,44,0,98,0.0,1,22,Urban,ML Engineer,70991,0 +84918,Male,23,Masters,6,58,5,26,60,8.0,6,61,Semi-Urban,Data Analyst,117398,0 +84919,Female,54,Bachelors,0,97,28,95,49,8.0,2,66,Semi-Urban,Data Analyst,59682,1 +84920,Male,44,Diploma,0,46,1,96,45,5.0,2,8,Urban,Manager,30772,0 +84921,Male,42,Bachelors,11,32,73,40,84,3.0,4,44,Semi-Urban,Data Analyst,41434,0 +84922,Female,55,Bachelors,17,77,44,56,91,8.0,0,63,Semi-Urban,Manager,102164,0 +84923,Male,47,High School,5,78,58,17,77,0.0,0,90,Semi-Urban,HR Executive,106225,1 +84924,Female,34,Bachelors,3,87,36,87,52,0.0,7,76,Urban,ML Engineer,36530,1 +84925,Male,29,Diploma,15,56,86,74,63,9.0,4,49,Semi-Urban,Data Analyst,104283,1 +84926,Male,37,High School,17,43,51,20,4,4.0,5,74,Rural,Software Engineer,50807,0 +84927,Female,32,Diploma,1,9,11,61,2,7.0,5,80,Urban,ML Engineer,75378,0 +84928,Male,28,Bachelors,5,33,24,19,68,9.0,6,29,Semi-Urban,ML Engineer,123053,0 +84929,Male,37,Masters,11,58,31,57,4,5.0,2,0,Rural,Manager,83175,0 +84930,Male,38,Diploma,18,84,81,91,97,9.0,4,26,Rural,Manager,123329,1 +84931,Male,28,Bachelors,0,92,5,75,36,8.0,5,49,Urban,Software Engineer,146553,0 +84932,Male,21,Bachelors,13,5,52,44,52,3.0,6,63,Semi-Urban,Software Engineer,108202,0 +84933,Male,28,High School,12,4,81,36,93,4.0,6,26,Urban,Data Analyst,73308,0 +84934,Male,42,High School,3,53,50,83,48,3.0,3,9,Urban,Software Engineer,45048,0 +84935,Male,44,High School,9,29,80,73,82,4.0,0,33,Semi-Urban,Manager,120077,0 +84936,Other,23,Bachelors,9,32,9,57,30,8.0,6,22,Rural,Software Engineer,86639,0 +84937,Male,34,Bachelors,4,41,96,69,50,4.0,3,31,Urban,HR Executive,72054,1 +84938,Female,43,Bachelors,16,16,71,46,63,9.0,7,62,Semi-Urban,HR Executive,141601,0 +84939,Male,58,Masters,9,30,17,36,87,9.0,4,79,Semi-Urban,Software Engineer,143519,0 +84940,Female,44,Masters,14,75,45,20,47,1.0,2,75,Urban,Data Analyst,83209,0 +84941,Male,58,Bachelors,5,36,34,84,74,5.0,1,25,Urban,Manager,32984,0 +84942,Female,46,Bachelors,7,39,67,46,29,3.0,2,55,Urban,Data Analyst,52473,0 +84943,Female,55,PhD,13,14,35,33,39,1.0,1,37,Semi-Urban,HR Executive,89240,0 +84944,Male,42,Masters,3,62,23,71,43,7.0,5,17,Urban,Software Engineer,40890,0 +84945,Male,56,Masters,18,1,61,76,20,2.0,0,32,Urban,Software Engineer,64545,0 +84946,Female,55,High School,18,0,10,41,90,3.0,7,28,Rural,Software Engineer,134221,0 +84947,Female,55,Diploma,4,89,72,14,28,3.0,5,36,Rural,Manager,115705,0 +84948,Male,28,Bachelors,15,40,78,5,64,7.0,1,63,Semi-Urban,ML Engineer,130621,0 +84949,Male,27,High School,8,79,34,78,21,3.0,0,44,Urban,Software Engineer,40828,1 +84950,Male,34,Masters,15,96,75,43,75,7.0,7,14,Semi-Urban,Software Engineer,38542,0 +84951,Female,33,Bachelors,9,40,11,22,92,3.0,7,74,Semi-Urban,Software Engineer,27808,0 +84952,Male,41,Bachelors,12,18,78,78,81,9.0,0,24,Urban,Manager,63750,0 +84953,Male,56,Masters,0,99,27,22,4,6.0,0,83,Urban,HR Executive,108214,0 +84954,Male,40,Masters,5,2,66,72,90,8.0,5,8,Semi-Urban,Data Analyst,122028,0 +84955,Female,36,Bachelors,0,79,52,91,46,1.0,2,10,Urban,Software Engineer,30591,0 +84956,Female,54,High School,15,38,36,67,3,9.0,6,37,Urban,Software Engineer,124122,0 +84957,Male,59,Diploma,3,89,39,64,22,8.0,2,19,Urban,Manager,79247,0 +84958,Male,28,Bachelors,9,43,3,19,19,3.0,4,12,Rural,Software Engineer,97524,0 +84959,Male,50,Masters,5,10,13,82,54,3.0,6,15,Rural,Data Analyst,55310,0 +84960,Male,31,Masters,6,33,98,62,10,8.0,6,2,Rural,HR Executive,69689,0 +84961,Female,56,High School,12,94,89,8,91,9.0,6,47,Semi-Urban,Manager,140980,0 +84962,Male,22,Bachelors,16,62,10,17,3,1.0,6,61,Semi-Urban,Manager,45437,0 +84963,Male,48,Diploma,15,27,84,86,13,6.0,7,62,Semi-Urban,HR Executive,125056,1 +84964,Male,53,High School,6,29,81,21,90,8.0,0,19,Semi-Urban,ML Engineer,103284,0 +84965,Male,31,Bachelors,13,35,60,4,30,9.0,1,19,Semi-Urban,Data Analyst,103958,0 +84966,Male,34,Bachelors,11,14,52,35,43,8.0,7,19,Urban,HR Executive,132286,0 +84967,Female,38,PhD,2,13,33,70,48,0.0,0,76,Rural,HR Executive,109501,0 +84968,Female,42,Masters,1,21,20,89,58,4.0,6,86,Urban,Manager,63031,0 +84969,Male,27,Bachelors,11,92,16,25,20,4.0,1,60,Rural,Data Analyst,106841,0 +84970,Male,39,Bachelors,4,85,99,29,32,5.0,0,8,Rural,ML Engineer,130380,0 +84971,Male,31,Bachelors,6,73,99,64,26,8.0,5,88,Urban,Software Engineer,45588,1 +84972,Female,28,Masters,5,1,65,84,54,9.0,0,64,Rural,ML Engineer,24423,0 +84973,Other,52,Diploma,1,33,87,69,2,6.0,6,9,Urban,Data Analyst,81154,0 +84974,Male,26,Masters,18,67,31,25,21,0.0,2,37,Urban,Manager,55375,0 +84975,Female,42,Bachelors,0,26,64,76,86,0.0,5,38,Urban,Manager,50281,0 +84976,Male,43,Diploma,12,66,31,15,98,7.0,4,54,Rural,ML Engineer,120356,0 +84977,Male,45,High School,15,37,73,96,23,4.0,3,31,Semi-Urban,Software Engineer,133532,1 +84978,Female,46,Masters,4,24,60,59,41,7.0,6,45,Semi-Urban,Software Engineer,85921,0 +84979,Male,33,Masters,14,72,58,99,52,4.0,7,27,Rural,Data Analyst,86784,1 +84980,Male,46,Bachelors,14,36,93,2,19,4.0,2,64,Urban,Software Engineer,36623,0 +84981,Male,59,Diploma,18,49,59,47,0,0.0,6,37,Rural,Data Analyst,82765,0 +84982,Male,54,High School,19,38,67,78,82,6.0,7,56,Urban,Manager,50741,1 +84983,Male,47,Bachelors,18,28,32,37,71,5.0,3,29,Semi-Urban,ML Engineer,44875,0 +84984,Female,28,Bachelors,12,59,5,65,51,4.0,4,52,Rural,Data Analyst,107185,0 +84985,Female,43,High School,6,84,2,22,51,8.0,3,97,Semi-Urban,Manager,125955,0 +84986,Other,22,Masters,18,62,77,21,60,6.0,3,7,Semi-Urban,Data Analyst,113246,0 +84987,Male,48,Bachelors,2,62,50,94,50,7.0,0,76,Semi-Urban,Data Analyst,146711,1 +84988,Male,53,Diploma,0,55,62,39,41,5.0,1,77,Semi-Urban,HR Executive,84521,0 +84989,Other,42,Diploma,12,18,28,46,22,9.0,4,91,Urban,ML Engineer,21748,0 +84990,Female,55,Bachelors,10,4,38,54,27,7.0,3,79,Urban,Software Engineer,62917,0 +84991,Male,47,Bachelors,4,87,99,72,80,0.0,7,45,Urban,Data Analyst,43964,1 +84992,Male,59,Bachelors,4,96,63,40,93,6.0,6,14,Semi-Urban,ML Engineer,131040,0 +84993,Male,53,High School,16,90,9,90,34,4.0,3,51,Rural,ML Engineer,36218,1 +84994,Other,28,High School,2,57,9,69,46,9.0,0,3,Urban,Software Engineer,138223,0 +84995,Male,27,High School,12,25,29,48,91,2.0,7,52,Semi-Urban,Manager,122434,0 +84996,Male,37,Masters,17,94,54,95,30,1.0,2,79,Semi-Urban,Data Analyst,34740,1 +84997,Female,51,Masters,11,69,2,43,58,1.0,2,92,Urban,Manager,86099,0 +84998,Other,56,Bachelors,12,55,69,7,81,3.0,2,37,Semi-Urban,HR Executive,43084,0 +84999,Male,52,Masters,13,87,7,23,5,8.0,1,56,Semi-Urban,HR Executive,109723,0 +85000,Other,59,Diploma,10,81,38,6,90,6.0,6,44,Urban,Data Analyst,81677,0 +85001,Male,28,Bachelors,2,14,48,20,39,4.0,0,99,Urban,Data Analyst,72108,0 +85002,Female,26,Diploma,10,17,31,79,20,8.0,6,83,Semi-Urban,Data Analyst,121461,0 +85003,Other,48,High School,12,13,16,63,28,7.0,7,54,Urban,HR Executive,91738,0 +85004,Male,21,Bachelors,11,52,3,33,5,7.0,3,8,Semi-Urban,Manager,21085,0 +85005,Male,55,Bachelors,10,54,76,39,2,6.0,2,32,Urban,Manager,41274,0 +85006,Female,23,Masters,11,48,14,24,67,8.0,6,36,Rural,ML Engineer,145612,0 +85007,Male,32,Diploma,4,13,14,71,95,7.0,2,86,Rural,HR Executive,81084,0 +85008,Male,44,Bachelors,2,19,4,11,43,5.0,5,99,Urban,HR Executive,92781,0 +85009,Male,22,Bachelors,1,4,23,13,65,8.0,5,54,Semi-Urban,HR Executive,28678,0 +85010,Female,40,Masters,5,62,2,97,75,0.0,6,92,Urban,HR Executive,28352,1 +85011,Male,31,Diploma,11,9,0,61,79,6.0,7,9,Semi-Urban,Software Engineer,87403,0 +85012,Female,23,Bachelors,16,65,40,14,30,7.0,5,47,Urban,Data Analyst,94358,0 +85013,Male,22,Diploma,1,27,69,99,5,9.0,6,3,Semi-Urban,HR Executive,127138,0 +85014,Female,41,Bachelors,11,29,12,33,99,8.0,5,52,Rural,Manager,95864,0 +85015,Male,37,Diploma,9,6,92,23,96,8.0,7,81,Urban,HR Executive,56086,0 +85016,Male,57,Diploma,3,77,7,96,91,5.0,5,49,Urban,Data Analyst,39606,0 +85017,Male,28,Masters,7,70,99,46,18,1.0,7,87,Semi-Urban,ML Engineer,127772,1 +85018,Female,35,Bachelors,19,9,44,63,14,0.0,4,21,Urban,HR Executive,135443,0 +85019,Female,43,Bachelors,8,58,63,9,78,3.0,0,56,Urban,Manager,48963,0 +85020,Female,23,Bachelors,8,71,60,46,24,6.0,5,29,Urban,HR Executive,71917,0 +85021,Male,51,PhD,9,79,40,56,4,6.0,6,54,Urban,HR Executive,56792,0 +85022,Other,43,Bachelors,5,33,94,41,66,1.0,6,82,Urban,ML Engineer,132574,1 +85023,Male,48,Masters,10,63,62,30,59,6.0,6,88,Semi-Urban,Manager,143011,1 +85024,Male,45,Bachelors,9,21,84,25,65,4.0,3,65,Urban,ML Engineer,139979,0 +85025,Male,51,Bachelors,5,77,34,70,79,8.0,1,39,Urban,HR Executive,29195,0 +85026,Female,24,Diploma,17,86,8,42,46,8.0,5,37,Urban,Data Analyst,117777,0 +85027,Female,53,PhD,6,54,66,54,25,9.0,7,62,Urban,HR Executive,114259,0 +85028,Male,29,Bachelors,7,39,62,33,0,5.0,5,52,Urban,Software Engineer,62558,0 +85029,Male,26,PhD,8,32,29,10,30,4.0,0,19,Urban,Software Engineer,49668,0 +85030,Male,54,Bachelors,2,75,72,98,96,1.0,2,62,Rural,Data Analyst,130985,1 +85031,Female,57,Bachelors,14,65,5,48,54,8.0,4,43,Semi-Urban,Manager,26700,0 +85032,Male,38,Bachelors,19,89,85,71,22,4.0,6,27,Semi-Urban,Data Analyst,32982,1 +85033,Female,39,High School,15,30,76,77,28,6.0,1,71,Rural,ML Engineer,90278,1 +85034,Male,45,Bachelors,4,96,98,83,55,7.0,6,30,Urban,Manager,67680,1 +85035,Female,50,Masters,7,91,1,89,76,7.0,3,76,Semi-Urban,Software Engineer,43788,1 +85036,Female,38,Masters,13,61,95,23,52,6.0,6,62,Urban,ML Engineer,96328,1 +85037,Male,29,PhD,13,10,62,92,97,2.0,6,36,Urban,Manager,74707,0 +85038,Male,56,PhD,6,75,52,54,62,4.0,2,68,Urban,HR Executive,71558,1 +85039,Female,21,Diploma,18,66,24,9,53,7.0,5,98,Urban,ML Engineer,88122,0 +85040,Male,26,Bachelors,12,90,83,68,23,4.0,7,44,Urban,Data Analyst,77209,1 +85041,Male,23,Bachelors,1,0,93,45,55,2.0,2,67,Urban,Manager,102324,0 +85042,Male,36,Diploma,4,46,67,85,83,0.0,0,2,Semi-Urban,ML Engineer,74791,0 +85043,Male,31,Masters,1,55,66,35,41,2.0,7,96,Urban,HR Executive,113301,1 +85044,Female,54,Bachelors,3,75,99,29,51,1.0,1,15,Semi-Urban,Manager,121980,0 +85045,Female,45,Bachelors,5,99,98,62,43,8.0,3,33,Urban,ML Engineer,41375,1 +85046,Female,24,Bachelors,14,63,14,76,68,9.0,3,68,Rural,HR Executive,135348,0 +85047,Male,44,Masters,13,73,70,53,39,0.0,6,91,Semi-Urban,Data Analyst,122565,1 +85048,Male,54,High School,15,29,10,23,31,7.0,6,62,Urban,HR Executive,119084,0 +85049,Female,59,Diploma,18,59,95,56,43,6.0,7,15,Semi-Urban,Data Analyst,27985,0 +85050,Female,58,Bachelors,1,85,1,6,9,2.0,0,86,Rural,Manager,119790,0 +85051,Male,44,Masters,4,23,85,23,1,2.0,6,23,Rural,HR Executive,21092,0 +85052,Female,44,Bachelors,17,41,10,52,93,7.0,3,18,Urban,Software Engineer,69971,0 +85053,Female,51,High School,6,68,11,34,20,7.0,7,47,Urban,Data Analyst,88011,0 +85054,Male,49,Bachelors,13,79,31,94,74,5.0,2,51,Semi-Urban,ML Engineer,72471,1 +85055,Other,28,Masters,4,0,35,94,58,8.0,4,83,Urban,ML Engineer,22573,0 +85056,Other,49,High School,16,3,6,39,39,5.0,0,46,Urban,ML Engineer,121085,0 +85057,Female,44,High School,6,80,74,87,2,1.0,1,93,Rural,ML Engineer,86382,1 +85058,Female,30,Bachelors,19,39,54,63,10,1.0,5,35,Urban,Software Engineer,99369,0 +85059,Male,21,Bachelors,11,20,91,53,32,7.0,6,63,Urban,ML Engineer,81462,0 +85060,Other,58,High School,2,69,34,31,76,6.0,1,37,Urban,Data Analyst,53251,0 +85061,Female,24,Bachelors,9,33,2,10,0,1.0,4,95,Rural,Manager,140831,0 +85062,Female,52,Bachelors,11,54,21,19,34,2.0,5,82,Urban,Data Analyst,53790,0 +85063,Female,44,Bachelors,4,57,8,19,11,9.0,0,27,Semi-Urban,ML Engineer,128304,0 +85064,Male,23,High School,16,54,46,48,32,3.0,7,71,Rural,ML Engineer,121043,0 +85065,Female,45,Diploma,7,85,66,62,88,9.0,0,59,Rural,Data Analyst,119197,1 +85066,Female,51,Bachelors,10,55,40,38,44,7.0,6,37,Urban,Manager,62895,0 +85067,Male,37,Diploma,0,9,55,87,24,2.0,3,67,Urban,Data Analyst,141701,0 +85068,Female,57,Bachelors,19,93,90,30,8,3.0,7,25,Semi-Urban,Software Engineer,20623,0 +85069,Female,43,Diploma,6,76,80,61,74,5.0,0,82,Rural,Data Analyst,117598,1 +85070,Male,43,High School,19,93,29,71,42,5.0,3,51,Urban,Software Engineer,143404,1 +85071,Other,27,Masters,18,61,8,47,77,5.0,2,96,Urban,Manager,141903,0 +85072,Male,25,High School,7,18,39,37,52,7.0,7,76,Semi-Urban,Software Engineer,91435,0 +85073,Female,54,Masters,17,17,61,66,84,6.0,0,60,Semi-Urban,Manager,119293,0 +85074,Female,30,Bachelors,8,4,77,52,85,9.0,4,4,Urban,ML Engineer,58644,0 +85075,Female,25,Bachelors,17,99,32,26,45,4.0,5,37,Urban,Software Engineer,118975,0 +85076,Male,25,Bachelors,13,99,8,85,74,7.0,6,73,Semi-Urban,HR Executive,93300,1 +85077,Female,39,Bachelors,7,37,88,75,69,2.0,2,79,Urban,ML Engineer,95863,1 +85078,Female,56,Bachelors,11,29,97,58,96,2.0,2,94,Urban,Data Analyst,140363,1 +85079,Female,23,Bachelors,8,79,47,73,3,4.0,6,58,Urban,ML Engineer,26143,1 +85080,Male,32,High School,1,19,24,76,92,8.0,3,73,Urban,Software Engineer,110191,0 +85081,Female,48,Masters,9,27,9,26,84,7.0,2,59,Urban,Data Analyst,107170,0 +85082,Female,34,Diploma,9,69,18,42,78,8.0,7,94,Rural,ML Engineer,42633,0 +85083,Male,31,Bachelors,7,64,32,68,18,2.0,2,36,Semi-Urban,Manager,51852,0 +85084,Male,34,Masters,3,21,95,84,90,8.0,0,42,Urban,Software Engineer,127279,1 +85085,Male,48,Bachelors,9,91,67,91,21,5.0,0,2,Rural,Data Analyst,125621,1 +85086,Male,58,Bachelors,4,37,54,38,6,8.0,0,27,Rural,Software Engineer,108912,0 +85087,Male,41,Bachelors,16,58,39,88,89,4.0,7,80,Semi-Urban,HR Executive,77006,1 +85088,Female,33,High School,1,38,96,48,69,0.0,3,27,Rural,Manager,61780,0 +85089,Male,28,Diploma,18,54,7,89,4,9.0,0,0,Urban,Data Analyst,104633,0 +85090,Female,37,High School,5,51,99,77,10,6.0,3,69,Urban,ML Engineer,109901,1 +85091,Female,52,Bachelors,3,17,52,0,61,2.0,4,21,Semi-Urban,HR Executive,93968,0 +85092,Male,35,Diploma,11,12,97,3,35,7.0,4,97,Urban,Manager,148236,0 +85093,Male,49,Masters,19,0,68,1,81,4.0,6,10,Semi-Urban,Manager,95448,0 +85094,Female,22,Diploma,18,79,71,28,86,6.0,6,69,Rural,HR Executive,99849,1 +85095,Male,55,High School,0,39,1,53,39,8.0,6,35,Semi-Urban,HR Executive,69182,0 +85096,Female,40,Bachelors,2,14,21,73,33,9.0,1,77,Urban,ML Engineer,147409,0 +85097,Female,22,Bachelors,9,42,15,51,25,5.0,2,75,Urban,ML Engineer,35622,0 +85098,Male,31,Masters,10,71,31,10,5,7.0,6,6,Semi-Urban,ML Engineer,56286,0 +85099,Male,58,Bachelors,1,94,84,40,33,4.0,2,72,Urban,Data Analyst,73227,1 +85100,Male,47,Masters,10,18,57,78,26,8.0,1,9,Urban,Software Engineer,120026,0 +85101,Male,48,Diploma,6,82,44,60,85,6.0,4,69,Semi-Urban,HR Executive,55025,1 +85102,Female,29,High School,4,69,57,17,18,3.0,0,45,Rural,Manager,71237,0 +85103,Male,51,Diploma,4,74,23,10,97,9.0,3,46,Rural,Manager,80308,0 +85104,Male,35,Bachelors,6,70,79,5,25,3.0,1,65,Rural,HR Executive,74777,0 +85105,Male,40,Bachelors,11,91,93,64,31,6.0,7,64,Urban,Manager,51727,1 +85106,Female,51,Bachelors,16,89,99,39,54,3.0,7,1,Rural,Data Analyst,25891,0 +85107,Male,47,Bachelors,8,35,57,91,47,4.0,1,10,Urban,Manager,89341,0 +85108,Male,37,Bachelors,7,96,84,75,91,5.0,2,12,Rural,ML Engineer,132790,1 +85109,Male,54,Masters,10,82,50,17,14,5.0,1,9,Semi-Urban,Data Analyst,61311,0 +85110,Female,59,High School,6,52,10,93,54,4.0,2,29,Urban,Software Engineer,31538,0 +85111,Male,36,PhD,17,49,28,36,92,4.0,6,3,Rural,ML Engineer,96747,0 +85112,Female,28,Masters,17,50,37,66,97,5.0,3,36,Urban,Software Engineer,114455,0 +85113,Male,42,Bachelors,17,50,12,81,97,4.0,0,42,Urban,Manager,48799,0 +85114,Male,36,Bachelors,0,33,81,48,74,8.0,4,12,Rural,Data Analyst,75616,0 +85115,Female,30,Masters,11,10,40,81,55,7.0,0,46,Urban,Manager,73517,0 +85116,Male,37,Diploma,12,96,28,57,55,0.0,3,77,Rural,Manager,136738,1 +85117,Male,43,Diploma,10,25,44,69,49,8.0,3,41,Rural,Manager,95730,0 +85118,Male,40,Bachelors,10,14,68,22,38,1.0,0,44,Urban,Data Analyst,113567,0 +85119,Male,21,Masters,15,55,65,34,99,8.0,2,93,Urban,HR Executive,114086,1 +85120,Male,52,High School,1,23,63,4,10,2.0,6,88,Urban,ML Engineer,55642,0 +85121,Female,26,Diploma,0,96,5,10,93,4.0,5,34,Urban,ML Engineer,116270,0 +85122,Female,57,Masters,12,33,88,12,27,7.0,6,14,Urban,Software Engineer,119564,0 +85123,Female,43,Bachelors,5,8,8,74,86,6.0,7,38,Semi-Urban,Software Engineer,138937,0 +85124,Female,54,Diploma,4,75,46,95,5,4.0,4,70,Semi-Urban,HR Executive,77440,1 +85125,Male,23,Masters,1,76,6,19,73,9.0,3,30,Semi-Urban,Data Analyst,125122,0 +85126,Male,46,Bachelors,8,27,26,68,78,6.0,5,25,Semi-Urban,Data Analyst,61469,0 +85127,Male,24,Diploma,4,75,37,83,62,0.0,7,7,Semi-Urban,Manager,113291,0 +85128,Male,45,Bachelors,8,57,94,1,4,5.0,3,18,Urban,ML Engineer,35675,0 +85129,Male,42,Diploma,1,39,81,98,96,8.0,2,54,Semi-Urban,HR Executive,63512,1 +85130,Female,53,Diploma,8,99,85,39,98,6.0,5,4,Urban,Software Engineer,61033,0 +85131,Male,32,Diploma,3,98,65,26,34,7.0,3,10,Urban,HR Executive,54993,0 +85132,Male,48,PhD,6,25,97,0,68,2.0,3,66,Urban,Manager,68182,0 +85133,Other,23,Bachelors,8,83,37,93,20,1.0,7,18,Urban,ML Engineer,135500,0 +85134,Male,47,High School,1,13,45,91,95,8.0,0,28,Urban,Manager,141999,0 +85135,Male,23,PhD,8,20,45,67,82,8.0,5,23,Urban,Software Engineer,142838,0 +85136,Other,48,Diploma,12,88,0,0,5,8.0,6,56,Rural,HR Executive,141935,0 +85137,Male,55,Bachelors,5,99,34,38,34,7.0,2,82,Urban,ML Engineer,57085,1 +85138,Male,55,High School,5,68,28,82,86,6.0,6,36,Semi-Urban,HR Executive,60884,0 +85139,Male,57,Bachelors,0,72,42,66,84,1.0,3,42,Semi-Urban,ML Engineer,100127,0 +85140,Male,35,High School,6,49,77,20,11,0.0,7,85,Urban,Software Engineer,81939,0 +85141,Male,49,Masters,3,79,11,86,72,7.0,3,60,Semi-Urban,ML Engineer,53857,1 +85142,Male,58,Bachelors,2,98,99,10,64,3.0,2,66,Urban,ML Engineer,149615,1 +85143,Male,50,Masters,6,17,81,4,97,9.0,3,39,Semi-Urban,HR Executive,52879,0 +85144,Female,25,Bachelors,13,25,47,10,29,3.0,0,69,Rural,Manager,71223,0 +85145,Female,31,Diploma,0,65,98,92,54,3.0,4,36,Semi-Urban,Data Analyst,113170,1 +85146,Male,53,High School,4,95,98,27,84,2.0,2,22,Semi-Urban,Manager,95362,1 +85147,Male,37,Bachelors,5,30,87,71,68,2.0,5,62,Rural,Software Engineer,22124,1 +85148,Female,36,Bachelors,8,19,91,73,58,5.0,1,20,Urban,Software Engineer,43949,0 +85149,Male,23,High School,14,21,96,47,44,1.0,7,64,Semi-Urban,Software Engineer,141540,0 +85150,Female,26,Diploma,0,18,48,38,42,9.0,6,71,Semi-Urban,Data Analyst,105560,0 +85151,Male,47,Diploma,19,75,0,50,35,0.0,0,12,Rural,Software Engineer,87653,0 +85152,Male,28,Diploma,7,98,14,96,0,2.0,5,81,Urban,Manager,50992,1 +85153,Male,53,Masters,8,27,37,68,8,6.0,0,59,Urban,HR Executive,140625,0 +85154,Female,29,Bachelors,4,32,94,53,39,7.0,1,82,Rural,ML Engineer,76136,1 +85155,Male,24,Bachelors,19,85,15,80,56,8.0,6,44,Urban,Software Engineer,143830,0 +85156,Male,56,Masters,5,17,47,55,95,5.0,3,43,Urban,ML Engineer,140462,0 +85157,Male,51,High School,0,0,3,70,66,6.0,1,43,Semi-Urban,Manager,27815,0 +85158,Male,23,Masters,12,64,52,25,89,2.0,5,74,Rural,Software Engineer,94148,0 +85159,Male,49,Bachelors,6,92,66,34,50,5.0,1,79,Urban,Data Analyst,77061,1 +85160,Female,21,Masters,11,62,35,52,52,6.0,5,41,Rural,ML Engineer,140143,0 +85161,Male,47,Bachelors,13,13,51,76,43,0.0,2,85,Urban,Manager,106844,0 +85162,Female,58,Bachelors,9,88,9,38,69,4.0,1,81,Urban,ML Engineer,63880,0 +85163,Male,30,Bachelors,3,92,99,31,52,8.0,0,23,Semi-Urban,Data Analyst,33331,1 +85164,Male,45,Bachelors,9,25,23,79,1,5.0,2,50,Semi-Urban,Data Analyst,126198,0 +85165,Female,54,Masters,17,90,67,46,30,2.0,5,16,Semi-Urban,Software Engineer,25848,0 +85166,Male,27,Diploma,8,52,1,6,10,4.0,2,61,Urban,Software Engineer,39919,0 +85167,Female,36,Masters,10,62,53,82,86,7.0,2,8,Semi-Urban,Manager,127403,0 +85168,Female,32,Diploma,8,66,24,9,45,9.0,5,93,Rural,Software Engineer,63764,0 +85169,Male,47,Bachelors,16,8,55,37,93,2.0,4,74,Urban,HR Executive,64409,0 +85170,Male,48,Masters,3,45,90,36,14,0.0,4,74,Urban,Data Analyst,148151,1 +85171,Female,32,Diploma,17,72,71,24,99,6.0,1,50,Urban,ML Engineer,112409,0 +85172,Female,55,Bachelors,17,71,37,73,23,7.0,0,13,Urban,Data Analyst,126227,0 +85173,Male,46,PhD,7,8,90,83,37,3.0,0,80,Urban,Software Engineer,110292,1 +85174,Male,50,Masters,1,2,12,54,62,6.0,7,86,Urban,Data Analyst,85196,0 +85175,Female,55,Bachelors,12,71,35,25,2,9.0,1,15,Urban,ML Engineer,82075,0 +85176,Female,22,Diploma,1,54,70,13,12,2.0,5,26,Urban,Data Analyst,71444,0 +85177,Male,54,Bachelors,5,21,21,58,2,1.0,5,40,Semi-Urban,HR Executive,46030,0 +85178,Male,58,Bachelors,16,42,19,99,31,7.0,4,52,Urban,ML Engineer,139395,0 +85179,Male,34,Diploma,11,97,45,22,56,5.0,6,93,Urban,HR Executive,142829,1 +85180,Male,59,Bachelors,5,24,67,36,15,0.0,2,72,Urban,Software Engineer,76977,0 +85181,Male,21,Diploma,13,99,89,68,7,3.0,1,52,Urban,Manager,26901,1 +85182,Female,32,Diploma,14,72,12,44,8,5.0,7,34,Urban,HR Executive,53851,0 +85183,Male,42,Masters,14,0,16,61,3,2.0,7,36,Urban,Data Analyst,100998,0 +85184,Female,32,Diploma,19,93,57,86,97,1.0,3,58,Urban,Software Engineer,53218,1 +85185,Other,23,Masters,0,34,37,93,16,5.0,4,8,Urban,ML Engineer,88829,0 +85186,Male,31,Diploma,9,26,96,21,18,9.0,4,43,Rural,HR Executive,129955,0 +85187,Female,46,Diploma,8,75,6,6,59,0.0,3,83,Rural,ML Engineer,92407,0 +85188,Other,58,Bachelors,15,12,32,87,6,7.0,5,93,Semi-Urban,Manager,51505,0 +85189,Female,38,Masters,18,94,13,19,10,5.0,4,74,Semi-Urban,Data Analyst,110141,0 +85190,Male,31,Masters,16,51,24,13,35,5.0,4,97,Urban,Data Analyst,38684,0 +85191,Female,49,High School,1,37,64,60,19,5.0,5,56,Semi-Urban,Software Engineer,94534,0 +85192,Female,27,Bachelors,4,10,28,91,47,8.0,5,37,Urban,HR Executive,143529,0 +85193,Male,27,Diploma,10,67,78,50,19,6.0,6,76,Semi-Urban,Software Engineer,98972,1 +85194,Male,39,Masters,15,67,17,11,5,3.0,4,58,Semi-Urban,Software Engineer,104046,0 +85195,Female,53,Bachelors,15,66,12,82,35,9.0,5,11,Rural,Software Engineer,33821,0 +85196,Male,51,Diploma,4,74,81,81,5,3.0,7,36,Rural,Data Analyst,20710,1 +85197,Female,48,High School,11,43,19,99,80,4.0,5,33,Semi-Urban,Software Engineer,70270,0 +85198,Other,37,Masters,5,44,5,26,98,2.0,6,41,Rural,Manager,120545,0 +85199,Male,24,Masters,4,42,94,64,35,1.0,1,57,Urban,ML Engineer,96637,1 +85200,Female,23,High School,16,90,38,41,86,3.0,5,23,Rural,ML Engineer,130300,0 +85201,Male,26,Bachelors,16,75,77,70,5,0.0,3,77,Rural,Software Engineer,96142,1 +85202,Male,37,Bachelors,15,41,75,87,46,0.0,2,96,Urban,HR Executive,135983,1 +85203,Other,22,Diploma,19,74,36,16,67,9.0,2,2,Urban,Software Engineer,124412,0 +85204,Male,34,PhD,3,39,69,95,58,7.0,2,84,Semi-Urban,ML Engineer,76224,1 +85205,Male,41,Masters,6,57,90,72,68,1.0,2,23,Urban,ML Engineer,20000,1 +85206,Female,45,Masters,0,7,5,18,41,4.0,6,16,Semi-Urban,ML Engineer,62393,0 +85207,Male,38,Bachelors,15,25,31,56,15,6.0,1,0,Semi-Urban,Manager,80243,0 +85208,Female,57,Masters,16,58,59,40,17,8.0,0,61,Urban,HR Executive,119855,0 +85209,Female,23,Diploma,14,36,25,80,8,6.0,2,54,Semi-Urban,HR Executive,79236,0 +85210,Male,29,Masters,9,16,97,22,36,8.0,6,5,Urban,HR Executive,141646,0 +85211,Male,44,Masters,14,68,41,22,7,7.0,0,81,Urban,Software Engineer,125882,0 +85212,Male,43,Bachelors,7,97,49,9,28,0.0,3,72,Rural,Software Engineer,57124,0 +85213,Female,58,Masters,7,85,3,64,24,8.0,5,3,Urban,Software Engineer,52119,0 +85214,Male,26,Masters,1,65,49,66,51,5.0,1,1,Rural,Software Engineer,47598,0 +85215,Male,30,Masters,2,39,48,55,80,8.0,5,19,Rural,Manager,35845,0 +85216,Male,40,High School,11,6,78,55,48,7.0,2,96,Semi-Urban,Software Engineer,139934,1 +85217,Female,24,Masters,5,70,94,57,92,6.0,6,18,Semi-Urban,ML Engineer,123545,0 +85218,Male,21,High School,1,3,13,81,57,3.0,6,58,Urban,HR Executive,136209,0 +85219,Male,52,High School,3,80,15,39,78,8.0,4,95,Rural,Manager,130082,0 +85220,Male,53,Diploma,17,40,76,60,90,0.0,7,54,Urban,HR Executive,29707,0 +85221,Female,46,Masters,5,83,57,16,26,5.0,5,84,Urban,ML Engineer,123717,0 +85222,Male,25,Bachelors,17,7,68,8,84,2.0,7,49,Rural,Data Analyst,96010,0 +85223,Female,46,Masters,13,61,30,79,59,0.0,7,46,Urban,HR Executive,46002,0 +85224,Male,50,Masters,0,55,45,29,87,1.0,5,60,Rural,Manager,35769,0 +85225,Male,55,High School,11,37,10,1,93,6.0,5,31,Urban,Manager,74869,0 +85226,Male,27,Masters,0,26,46,79,81,8.0,5,66,Semi-Urban,HR Executive,37857,0 +85227,Male,37,PhD,16,49,24,8,95,9.0,1,38,Urban,ML Engineer,122696,0 +85228,Male,32,Bachelors,10,66,52,60,56,1.0,6,67,Urban,HR Executive,76267,1 +85229,Male,28,Bachelors,9,10,27,97,57,7.0,1,72,Urban,HR Executive,23497,0 +85230,Male,47,Bachelors,9,44,55,74,74,9.0,1,81,Urban,Data Analyst,105314,1 +85231,Other,23,Diploma,3,30,26,84,2,8.0,7,44,Urban,ML Engineer,26438,0 +85232,Female,26,Masters,17,27,13,87,33,4.0,5,3,Semi-Urban,Software Engineer,111363,0 +85233,Male,23,High School,19,80,0,32,30,6.0,1,33,Urban,ML Engineer,20700,0 +85234,Male,24,Bachelors,5,97,4,3,97,8.0,0,32,Rural,HR Executive,57122,0 +85235,Male,22,Masters,2,94,40,44,5,7.0,2,87,Semi-Urban,ML Engineer,52108,1 +85236,Female,30,High School,4,86,52,47,22,6.0,3,6,Semi-Urban,Data Analyst,80388,0 +85237,Male,25,PhD,15,75,97,3,77,3.0,6,76,Urban,Manager,52987,1 +85238,Male,29,High School,1,23,96,59,64,7.0,6,1,Urban,HR Executive,110236,0 +85239,Male,53,Masters,5,56,86,14,84,9.0,7,42,Semi-Urban,HR Executive,54344,0 +85240,Female,32,Bachelors,1,97,72,20,9,2.0,2,2,Urban,Data Analyst,122868,0 +85241,Female,42,Bachelors,2,39,37,60,9,0.0,2,25,Urban,HR Executive,36357,0 +85242,Male,57,Masters,19,33,92,13,74,5.0,7,97,Urban,Data Analyst,48155,1 +85243,Male,34,Diploma,12,26,53,9,98,4.0,1,33,Semi-Urban,Data Analyst,113555,0 +85244,Female,53,High School,18,39,86,94,93,0.0,7,64,Urban,Data Analyst,74821,1 +85245,Male,41,Diploma,9,26,73,25,53,1.0,7,25,Urban,ML Engineer,115939,0 +85246,Male,59,High School,17,17,82,87,56,3.0,0,31,Urban,HR Executive,145830,0 +85247,Male,37,Masters,12,86,44,87,81,5.0,1,64,Rural,Manager,148160,1 +85248,Male,28,Bachelors,1,28,93,16,33,9.0,2,95,Urban,HR Executive,89467,0 +85249,Male,31,High School,13,88,84,14,15,9.0,5,58,Rural,Manager,51774,1 +85250,Male,22,Masters,11,53,70,53,75,6.0,2,79,Urban,ML Engineer,90825,1 +85251,Male,30,Bachelors,7,14,48,50,79,7.0,2,30,Rural,HR Executive,66150,0 +85252,Male,46,Bachelors,7,98,74,37,79,2.0,1,60,Urban,Software Engineer,26203,1 +85253,Male,55,High School,0,82,66,88,98,1.0,0,23,Urban,ML Engineer,136647,1 +85254,Female,35,PhD,1,71,75,68,27,9.0,2,13,Urban,HR Executive,72911,0 +85255,Male,31,Diploma,11,17,64,43,64,3.0,3,24,Urban,Software Engineer,124698,0 +85256,Male,57,Diploma,0,5,11,5,84,8.0,5,42,Urban,Software Engineer,132665,0 +85257,Male,41,Bachelors,6,77,80,92,48,8.0,5,53,Urban,Data Analyst,25717,1 +85258,Female,22,Masters,2,73,80,5,2,9.0,4,40,Rural,Manager,127911,0 +85259,Female,58,Diploma,13,84,3,31,16,6.0,5,50,Rural,HR Executive,110848,0 +85260,Female,47,Bachelors,18,21,32,94,20,2.0,0,31,Urban,HR Executive,67298,0 +85261,Male,29,Bachelors,17,65,82,18,63,7.0,4,99,Urban,Software Engineer,86701,1 +85262,Male,29,Masters,4,80,72,21,47,9.0,7,47,Semi-Urban,HR Executive,101514,0 +85263,Male,35,Masters,14,46,81,48,47,9.0,7,13,Urban,ML Engineer,26084,0 +85264,Male,25,Masters,14,59,15,30,16,9.0,1,24,Semi-Urban,HR Executive,76091,0 +85265,Male,53,Bachelors,4,95,73,82,64,7.0,0,83,Semi-Urban,HR Executive,148474,1 +85266,Female,37,Bachelors,19,0,92,35,70,5.0,7,1,Semi-Urban,ML Engineer,110871,0 +85267,Male,55,Masters,12,58,24,60,72,0.0,5,31,Urban,ML Engineer,23038,0 +85268,Male,41,Diploma,2,96,24,26,50,0.0,4,1,Urban,Manager,149928,0 +85269,Male,53,Bachelors,10,41,81,47,37,2.0,6,48,Semi-Urban,Software Engineer,42261,0 +85270,Male,21,Diploma,18,92,15,48,92,6.0,1,49,Rural,Manager,113779,0 +85271,Male,22,Bachelors,14,82,50,86,54,5.0,4,7,Semi-Urban,HR Executive,121575,0 +85272,Male,43,High School,0,33,6,63,73,2.0,3,98,Semi-Urban,HR Executive,113120,0 +85273,Female,30,Bachelors,15,48,71,42,2,0.0,3,26,Urban,Data Analyst,88283,0 +85274,Female,39,Diploma,12,7,70,31,3,1.0,2,24,Semi-Urban,HR Executive,46699,0 +85275,Other,43,Masters,1,51,9,26,20,1.0,5,43,Urban,Manager,111210,0 +85276,Other,31,High School,16,78,6,76,74,1.0,6,80,Urban,ML Engineer,82430,0 +85277,Female,46,High School,17,91,32,35,31,9.0,5,21,Urban,Manager,58871,0 +85278,Female,41,High School,0,52,34,64,98,3.0,6,0,Urban,Software Engineer,49997,0 +85279,Male,29,Diploma,1,50,92,98,80,9.0,6,2,Urban,HR Executive,118579,1 +85280,Male,52,Bachelors,7,66,83,46,43,2.0,5,21,Rural,Manager,61691,0 +85281,Female,53,Diploma,15,63,67,2,99,5.0,4,1,Urban,HR Executive,73311,0 +85282,Male,51,Bachelors,10,89,11,82,33,2.0,4,35,Semi-Urban,Data Analyst,62111,0 +85283,Female,39,Masters,8,1,33,11,57,0.0,2,81,Semi-Urban,Data Analyst,104139,0 +85284,Female,39,Bachelors,12,31,8,96,18,9.0,4,69,Urban,ML Engineer,83287,0 +85285,Male,53,Bachelors,12,54,47,12,98,7.0,7,39,Urban,Manager,94657,0 +85286,Female,28,Bachelors,11,95,62,83,40,2.0,4,49,Urban,HR Executive,107980,1 +85287,Male,53,Masters,5,51,38,68,4,1.0,6,48,Semi-Urban,Data Analyst,68223,0 +85288,Female,55,High School,12,18,20,8,27,7.0,6,92,Rural,Software Engineer,108243,0 +85289,Female,21,PhD,4,49,38,17,91,6.0,2,65,Urban,ML Engineer,121107,0 +85290,Male,39,Bachelors,14,46,81,17,34,2.0,1,41,Urban,Data Analyst,105349,0 +85291,Male,24,Masters,14,57,24,46,19,6.0,0,33,Urban,HR Executive,86544,0 +85292,Female,53,Bachelors,2,54,8,59,12,4.0,3,15,Rural,Data Analyst,110014,0 +85293,Male,57,Bachelors,6,39,74,56,43,7.0,5,99,Urban,Software Engineer,45356,1 +85294,Male,44,High School,5,15,65,47,57,6.0,3,73,Semi-Urban,HR Executive,54259,0 +85295,Male,22,Diploma,1,53,32,8,81,7.0,5,5,Rural,Software Engineer,37947,0 +85296,Female,31,Bachelors,1,73,44,40,17,8.0,6,54,Urban,Manager,145230,0 +85297,Female,29,Masters,10,92,70,93,86,2.0,6,87,Urban,ML Engineer,79182,1 +85298,Female,22,Masters,12,94,91,95,93,6.0,7,56,Rural,Software Engineer,38944,1 +85299,Other,30,Bachelors,18,2,83,89,82,1.0,1,79,Urban,Data Analyst,117703,1 +85300,Male,34,Masters,2,96,11,70,42,8.0,0,34,Rural,ML Engineer,67073,0 +85301,Female,32,Bachelors,3,61,88,50,34,1.0,2,91,Urban,HR Executive,106318,1 +85302,Female,29,Diploma,9,64,71,3,72,7.0,3,10,Semi-Urban,HR Executive,55035,0 +85303,Female,37,PhD,17,98,95,76,33,2.0,1,0,Urban,ML Engineer,31651,1 +85304,Female,56,Masters,13,14,12,54,43,5.0,1,66,Urban,HR Executive,81594,0 +85305,Male,32,Bachelors,1,66,31,51,7,5.0,0,80,Urban,HR Executive,95984,0 +85306,Male,48,Masters,9,38,9,97,34,4.0,0,82,Urban,Manager,139009,0 +85307,Female,41,Bachelors,9,61,54,5,77,6.0,3,76,Urban,HR Executive,102615,0 +85308,Male,42,Masters,9,13,8,25,4,7.0,4,0,Urban,Software Engineer,136479,0 +85309,Male,49,PhD,12,59,52,59,44,1.0,4,77,Rural,HR Executive,37443,1 +85310,Male,38,Diploma,7,9,17,90,44,4.0,2,23,Urban,HR Executive,40228,0 +85311,Female,51,Bachelors,18,80,68,71,94,1.0,1,13,Rural,Data Analyst,141080,0 +85312,Female,23,Bachelors,9,66,46,57,1,8.0,2,92,Urban,Software Engineer,50070,1 +85313,Male,35,Bachelors,13,14,49,21,42,8.0,3,62,Urban,ML Engineer,26132,0 +85314,Male,36,Bachelors,1,93,2,12,99,6.0,6,14,Urban,Software Engineer,105100,0 +85315,Male,29,Bachelors,9,9,57,11,96,2.0,1,44,Semi-Urban,ML Engineer,129380,0 +85316,Female,42,Bachelors,6,29,50,94,41,6.0,4,71,Semi-Urban,Manager,144194,1 +85317,Male,40,Bachelors,3,58,2,75,68,9.0,2,96,Semi-Urban,Data Analyst,38016,0 +85318,Male,47,Diploma,9,84,58,13,14,3.0,6,42,Urban,Data Analyst,48912,0 +85319,Male,34,Masters,17,94,98,4,6,9.0,0,55,Urban,HR Executive,64900,1 +85320,Female,46,Diploma,1,24,5,18,36,7.0,5,59,Semi-Urban,ML Engineer,116421,0 +85321,Male,48,Diploma,12,28,39,37,46,7.0,4,69,Urban,Data Analyst,126118,0 +85322,Female,34,Bachelors,8,99,14,99,52,5.0,4,92,Urban,Data Analyst,34272,1 +85323,Male,35,Diploma,7,40,89,26,12,6.0,3,57,Semi-Urban,Manager,105455,0 +85324,Male,56,Bachelors,15,62,75,51,17,7.0,1,19,Rural,Software Engineer,54012,0 +85325,Male,53,Bachelors,19,35,69,32,89,4.0,3,79,Urban,ML Engineer,70745,0 +85326,Male,58,High School,17,31,8,14,3,1.0,6,52,Urban,HR Executive,93097,0 +85327,Male,47,Bachelors,1,7,30,17,96,6.0,2,54,Urban,ML Engineer,77336,0 +85328,Female,54,High School,7,20,38,6,28,0.0,5,51,Urban,Software Engineer,129068,0 +85329,Male,36,Masters,1,25,92,85,86,7.0,2,62,Urban,Software Engineer,82145,1 +85330,Other,24,High School,8,76,47,55,37,2.0,7,8,Urban,Data Analyst,40616,0 +85331,Male,21,Masters,8,59,10,47,85,6.0,0,70,Semi-Urban,ML Engineer,92996,0 +85332,Female,26,Masters,3,82,81,56,82,8.0,1,97,Urban,HR Executive,145863,1 +85333,Female,37,Diploma,14,27,51,36,70,1.0,2,99,Semi-Urban,HR Executive,111075,0 +85334,Male,26,Masters,14,64,42,24,43,0.0,0,57,Urban,Manager,142447,0 +85335,Female,52,Bachelors,0,88,3,16,38,7.0,6,84,Urban,HR Executive,114484,0 +85336,Male,43,PhD,10,73,92,61,96,1.0,6,62,Urban,Software Engineer,31650,1 +85337,Male,45,Masters,17,41,9,18,0,8.0,6,37,Urban,Data Analyst,77984,0 +85338,Female,39,Bachelors,8,49,22,23,11,9.0,6,40,Urban,ML Engineer,149848,0 +85339,Female,51,Diploma,0,30,67,98,98,4.0,6,24,Semi-Urban,ML Engineer,21302,0 +85340,Female,26,PhD,16,89,93,30,81,0.0,0,27,Urban,ML Engineer,72001,0 +85341,Male,37,Bachelors,6,36,37,14,78,1.0,7,70,Semi-Urban,HR Executive,112495,0 +85342,Male,49,Bachelors,7,60,54,0,91,7.0,2,43,Urban,Manager,41206,0 +85343,Male,56,Bachelors,16,28,67,73,72,3.0,1,50,Urban,Data Analyst,67546,0 +85344,Female,58,Bachelors,7,12,75,16,90,9.0,2,28,Semi-Urban,ML Engineer,88170,0 +85345,Male,56,High School,15,48,0,79,16,8.0,1,69,Semi-Urban,Software Engineer,38553,0 +85346,Female,48,Diploma,12,58,85,6,72,7.0,1,21,Rural,Software Engineer,33116,0 +85347,Male,41,Masters,8,10,76,27,43,8.0,5,34,Urban,Data Analyst,148875,0 +85348,Male,59,Bachelors,16,78,0,15,99,2.0,5,44,Rural,Software Engineer,97350,0 +85349,Male,45,Diploma,10,26,2,16,20,9.0,3,66,Urban,Manager,94774,0 +85350,Male,21,Diploma,12,96,15,26,23,8.0,2,32,Urban,ML Engineer,30059,0 +85351,Female,50,Bachelors,7,4,61,8,68,3.0,0,9,Semi-Urban,Data Analyst,56411,0 +85352,Male,41,High School,8,56,58,22,46,9.0,4,50,Urban,Data Analyst,24457,0 +85353,Male,55,High School,4,90,89,66,87,3.0,1,1,Urban,Software Engineer,54937,1 +85354,Female,56,Masters,9,73,75,74,18,2.0,4,39,Semi-Urban,Software Engineer,136461,1 +85355,Male,27,Bachelors,3,0,99,80,50,2.0,3,79,Rural,Data Analyst,86027,1 +85356,Male,41,PhD,1,53,44,58,82,4.0,7,98,Urban,Software Engineer,66008,1 +85357,Male,33,Diploma,11,9,89,12,30,2.0,7,41,Semi-Urban,Data Analyst,22090,0 +85358,Other,57,Bachelors,7,18,52,79,26,5.0,3,3,Semi-Urban,Software Engineer,124470,0 +85359,Male,54,Bachelors,6,32,51,80,4,8.0,6,56,Rural,Data Analyst,50603,0 +85360,Male,49,Masters,0,74,87,34,38,5.0,1,38,Urban,HR Executive,96783,0 +85361,Male,38,High School,18,87,45,5,28,3.0,2,18,Urban,HR Executive,118795,0 +85362,Male,50,Diploma,16,60,24,6,24,4.0,6,36,Semi-Urban,Software Engineer,104985,0 +85363,Male,51,Bachelors,2,9,33,26,64,7.0,5,34,Urban,HR Executive,120961,0 +85364,Male,40,Bachelors,15,41,67,46,64,9.0,2,22,Semi-Urban,Software Engineer,96017,0 +85365,Female,53,Masters,14,29,34,16,0,0.0,7,63,Urban,ML Engineer,68289,0 +85366,Male,41,Masters,3,49,14,84,72,2.0,0,21,Urban,Manager,53656,0 +85367,Female,31,PhD,1,91,64,61,72,6.0,5,50,Rural,Software Engineer,55805,1 +85368,Male,50,High School,6,57,35,51,5,5.0,1,39,Rural,ML Engineer,52486,0 +85369,Male,44,PhD,5,22,70,0,45,3.0,2,77,Rural,Data Analyst,95560,0 +85370,Male,30,Diploma,19,52,64,99,8,0.0,3,15,Urban,Software Engineer,114279,0 +85371,Male,52,Bachelors,5,6,9,12,67,7.0,0,70,Rural,Software Engineer,39214,0 +85372,Male,51,High School,17,0,72,86,29,8.0,6,62,Urban,Manager,112469,0 +85373,Male,30,Diploma,16,57,11,31,77,7.0,1,10,Rural,Software Engineer,70123,0 +85374,Male,25,Bachelors,10,91,62,29,82,8.0,5,62,Urban,ML Engineer,48750,1 +85375,Female,56,Diploma,17,43,51,10,7,1.0,1,16,Urban,Data Analyst,78929,0 +85376,Female,49,High School,16,99,35,58,46,6.0,1,70,Urban,ML Engineer,133563,1 +85377,Male,47,Masters,5,60,89,18,60,0.0,5,82,Semi-Urban,Software Engineer,93875,1 +85378,Male,28,PhD,16,94,27,58,71,1.0,1,24,Semi-Urban,Data Analyst,131893,0 +85379,Male,55,High School,14,40,24,47,18,5.0,2,10,Urban,Manager,142923,0 +85380,Male,31,Masters,17,21,60,2,32,2.0,0,89,Semi-Urban,Data Analyst,134663,0 +85381,Male,53,Diploma,17,45,96,40,82,4.0,1,86,Urban,Manager,26960,1 +85382,Male,41,Diploma,1,90,34,52,45,4.0,6,83,Urban,ML Engineer,20824,1 +85383,Male,40,Diploma,17,72,8,51,74,3.0,7,66,Rural,Software Engineer,90833,0 +85384,Male,28,Masters,8,93,50,74,51,1.0,2,40,Urban,Manager,34170,1 +85385,Male,50,Bachelors,15,89,9,20,62,2.0,5,27,Rural,Software Engineer,86107,0 +85386,Female,42,Bachelors,11,14,93,63,93,4.0,1,16,Urban,Data Analyst,144868,0 +85387,Male,58,Bachelors,6,17,5,66,29,3.0,7,39,Urban,HR Executive,72708,0 +85388,Male,32,High School,12,93,1,27,76,0.0,7,54,Urban,Data Analyst,74156,0 +85389,Male,30,High School,12,68,59,22,9,7.0,5,68,Semi-Urban,Data Analyst,29888,0 +85390,Male,38,Masters,17,14,8,22,79,8.0,0,91,Urban,Data Analyst,127956,0 +85391,Male,29,Masters,13,24,96,30,41,1.0,6,45,Urban,Manager,115477,0 +85392,Female,22,Bachelors,5,33,75,79,69,9.0,2,89,Rural,HR Executive,135001,1 +85393,Male,58,Bachelors,14,84,15,50,28,6.0,0,40,Urban,Software Engineer,146955,0 +85394,Female,27,Diploma,15,4,35,80,17,8.0,2,45,Urban,Manager,134473,0 +85395,Male,35,Masters,17,53,5,2,98,5.0,6,78,Urban,Software Engineer,42344,0 +85396,Male,35,Masters,12,47,2,58,34,0.0,2,84,Urban,ML Engineer,65355,0 +85397,Other,53,Masters,11,51,91,91,29,4.0,2,91,Urban,Manager,75793,1 +85398,Male,26,High School,9,75,63,75,86,0.0,5,57,Rural,Software Engineer,119426,1 +85399,Female,45,Bachelors,9,59,82,78,13,1.0,6,66,Urban,Manager,73544,1 +85400,Female,26,PhD,19,95,44,6,57,7.0,5,82,Urban,Software Engineer,40008,0 +85401,Male,37,Bachelors,0,20,34,1,59,3.0,3,16,Rural,Data Analyst,28616,0 +85402,Female,45,High School,10,34,49,16,20,7.0,3,37,Semi-Urban,Software Engineer,141923,0 +85403,Male,46,Bachelors,12,40,9,77,78,7.0,6,72,Urban,Data Analyst,66815,0 +85404,Male,28,PhD,0,18,83,62,28,6.0,4,18,Urban,ML Engineer,108847,0 +85405,Male,44,Diploma,0,67,3,38,13,3.0,2,87,Urban,ML Engineer,122187,0 +85406,Male,43,Diploma,7,94,60,12,91,6.0,2,72,Urban,HR Executive,113925,1 +85407,Female,44,Diploma,16,79,75,70,30,1.0,7,20,Rural,HR Executive,75975,1 +85408,Female,31,Masters,3,16,53,24,45,5.0,1,90,Urban,HR Executive,106171,0 +85409,Male,35,Bachelors,2,65,90,13,80,0.0,7,18,Semi-Urban,ML Engineer,84895,0 +85410,Male,27,Bachelors,8,97,56,4,56,8.0,1,1,Urban,HR Executive,27869,0 +85411,Male,43,High School,15,28,53,43,10,5.0,1,8,Rural,Manager,41566,0 +85412,Female,36,Diploma,10,43,57,15,10,1.0,0,37,Semi-Urban,ML Engineer,67467,0 +85413,Female,31,High School,9,13,82,30,38,1.0,3,63,Semi-Urban,HR Executive,135860,0 +85414,Female,54,High School,1,17,97,63,49,6.0,0,64,Semi-Urban,Manager,122539,1 +85415,Male,35,Masters,12,79,67,96,9,0.0,3,46,Urban,Software Engineer,123236,1 +85416,Male,55,Diploma,16,69,17,78,30,6.0,6,85,Rural,Data Analyst,89537,1 +85417,Female,46,Bachelors,1,66,47,29,4,0.0,7,97,Urban,HR Executive,27570,0 +85418,Female,49,Diploma,0,49,81,67,41,6.0,7,91,Urban,Manager,98473,1 +85419,Female,38,PhD,4,97,82,4,52,2.0,7,27,Rural,Software Engineer,123486,0 +85420,Female,58,High School,4,77,82,29,76,6.0,1,2,Semi-Urban,Manager,149780,0 +85421,Male,30,Bachelors,4,75,73,44,27,8.0,7,67,Semi-Urban,Software Engineer,113829,1 +85422,Male,34,Masters,3,21,16,12,99,0.0,4,98,Urban,ML Engineer,38928,0 +85423,Female,26,Masters,4,81,8,69,69,1.0,2,23,Urban,Data Analyst,52635,0 +85424,Female,31,Diploma,19,68,90,45,52,7.0,1,98,Rural,Software Engineer,143143,1 +85425,Female,37,Bachelors,19,31,87,17,43,7.0,5,63,Urban,Manager,85035,0 +85426,Male,37,Bachelors,1,26,29,21,58,6.0,3,93,Rural,ML Engineer,108950,0 +85427,Female,42,Bachelors,5,33,6,95,47,5.0,0,89,Urban,ML Engineer,62336,0 +85428,Female,39,Bachelors,10,6,47,99,78,8.0,5,44,Semi-Urban,Data Analyst,71266,0 +85429,Female,26,Diploma,1,22,48,17,61,2.0,1,27,Urban,HR Executive,81024,0 +85430,Female,33,Masters,14,60,97,21,37,6.0,4,39,Urban,Data Analyst,22297,0 +85431,Male,53,Bachelors,3,46,66,15,45,7.0,3,32,Urban,Software Engineer,60425,0 +85432,Other,55,Diploma,1,68,38,46,0,3.0,7,7,Urban,ML Engineer,61626,0 +85433,Male,50,Bachelors,10,11,13,0,78,7.0,5,98,Urban,ML Engineer,28624,0 +85434,Male,55,Bachelors,13,14,97,7,29,8.0,5,6,Semi-Urban,Manager,38980,0 +85435,Male,56,Masters,13,8,28,29,22,3.0,1,42,Semi-Urban,Manager,141282,0 +85436,Other,35,Masters,5,49,59,15,73,8.0,5,44,Urban,Software Engineer,134542,0 +85437,Male,59,Bachelors,15,38,96,83,44,3.0,3,45,Urban,Manager,95434,1 +85438,Male,30,Bachelors,4,59,70,79,60,9.0,1,22,Semi-Urban,Data Analyst,29658,0 +85439,Male,27,Bachelors,12,25,99,39,93,6.0,1,69,Semi-Urban,Data Analyst,133224,0 +85440,Male,57,Masters,3,70,33,31,2,7.0,6,17,Urban,Software Engineer,40971,0 +85441,Male,24,Diploma,1,82,41,63,68,6.0,1,76,Urban,Data Analyst,114383,1 +85442,Other,32,Bachelors,17,99,58,77,10,0.0,6,30,Semi-Urban,HR Executive,86348,1 +85443,Male,26,Masters,12,55,76,71,40,6.0,0,44,Rural,HR Executive,24250,1 +85444,Male,55,Bachelors,18,98,98,16,21,1.0,5,61,Urban,Manager,112486,1 +85445,Female,57,Bachelors,5,76,68,46,63,6.0,6,16,Urban,HR Executive,99289,0 +85446,Female,45,Bachelors,3,95,76,8,99,9.0,5,37,Rural,HR Executive,31373,0 +85447,Other,57,Bachelors,12,36,17,51,14,8.0,7,78,Urban,Software Engineer,39302,0 +85448,Female,37,Bachelors,7,66,15,13,53,4.0,1,20,Urban,Software Engineer,84609,0 +85449,Male,52,Masters,17,2,63,75,64,8.0,4,47,Rural,HR Executive,80340,0 +85450,Other,32,Diploma,16,10,67,26,21,3.0,6,45,Rural,HR Executive,143787,0 +85451,Female,27,Bachelors,1,35,91,6,39,6.0,2,26,Urban,Manager,45845,0 +85452,Male,45,Masters,4,59,24,96,75,9.0,5,21,Urban,Manager,82859,0 +85453,Male,33,Bachelors,9,98,3,53,53,7.0,3,26,Urban,Data Analyst,76857,0 +85454,Other,41,Masters,8,26,45,37,17,6.0,7,14,Urban,Manager,45758,0 +85455,Male,25,Diploma,19,74,97,86,57,0.0,3,78,Urban,HR Executive,110225,1 +85456,Male,30,Bachelors,6,17,11,43,78,7.0,0,55,Rural,Software Engineer,107284,0 +85457,Male,22,Diploma,9,75,41,65,74,6.0,3,39,Rural,Data Analyst,26645,0 +85458,Female,58,Bachelors,12,37,32,68,93,7.0,5,36,Urban,Manager,83890,0 +85459,Male,56,Diploma,0,31,62,59,17,1.0,0,68,Urban,Data Analyst,94054,0 +85460,Male,36,Diploma,6,50,55,38,77,5.0,0,21,Urban,HR Executive,107986,0 +85461,Male,26,Bachelors,15,7,50,86,40,1.0,0,4,Rural,Manager,143553,0 +85462,Male,23,High School,13,12,57,85,7,3.0,3,76,Urban,HR Executive,49954,0 +85463,Male,33,Bachelors,13,34,53,11,90,7.0,6,32,Rural,HR Executive,113131,0 +85464,Male,31,Masters,5,21,17,18,28,3.0,0,23,Urban,HR Executive,21863,0 +85465,Male,22,Diploma,13,30,66,89,14,3.0,5,77,Urban,Data Analyst,102403,1 +85466,Male,32,Bachelors,6,73,52,51,3,5.0,7,75,Semi-Urban,Data Analyst,24437,1 +85467,Male,40,Masters,18,66,88,49,73,9.0,5,13,Rural,HR Executive,123593,0 +85468,Female,46,Bachelors,17,17,87,40,7,0.0,7,18,Urban,Manager,36031,0 +85469,Female,25,Bachelors,4,16,30,33,39,5.0,1,2,Urban,HR Executive,31020,0 +85470,Male,33,High School,7,10,54,82,87,4.0,7,88,Semi-Urban,Software Engineer,73806,0 +85471,Female,35,Bachelors,3,94,87,40,46,5.0,4,68,Urban,HR Executive,26341,1 +85472,Male,22,Masters,6,56,9,27,72,6.0,2,32,Urban,Data Analyst,42230,0 +85473,Female,38,Bachelors,15,44,49,25,89,1.0,1,27,Urban,HR Executive,100107,0 +85474,Female,50,Bachelors,1,96,25,49,83,8.0,5,8,Rural,ML Engineer,60040,0 +85475,Other,22,PhD,12,37,59,18,25,9.0,3,27,Rural,HR Executive,92990,0 +85476,Male,36,Masters,11,40,9,64,28,2.0,1,60,Rural,Data Analyst,130948,0 +85477,Male,30,High School,6,82,14,96,39,4.0,1,42,Rural,ML Engineer,46568,0 +85478,Male,54,Diploma,2,71,99,86,31,3.0,1,95,Urban,ML Engineer,95139,1 +85479,Male,42,Diploma,19,49,45,7,24,2.0,6,18,Urban,Software Engineer,136082,0 +85480,Female,22,Masters,6,22,76,44,25,8.0,1,8,Urban,Manager,54051,0 +85481,Female,49,Bachelors,8,76,12,90,66,8.0,7,8,Rural,Manager,56255,0 +85482,Male,54,Masters,6,21,89,83,28,8.0,6,95,Urban,Software Engineer,80475,1 +85483,Female,35,Bachelors,17,8,55,72,93,3.0,1,16,Semi-Urban,Data Analyst,46894,0 +85484,Male,27,High School,17,70,10,38,50,4.0,4,3,Urban,Manager,142162,0 +85485,Female,36,High School,10,14,88,1,1,4.0,4,31,Urban,ML Engineer,130751,0 +85486,Other,32,Bachelors,18,41,41,19,3,0.0,3,65,Urban,HR Executive,62293,0 +85487,Female,23,Masters,7,74,1,25,48,2.0,2,75,Urban,Data Analyst,97458,0 +85488,Female,35,High School,5,46,89,1,20,8.0,4,51,Urban,HR Executive,101587,0 +85489,Male,44,High School,12,53,25,76,44,8.0,6,75,Rural,Software Engineer,29473,0 +85490,Male,59,Bachelors,5,49,8,68,24,0.0,1,1,Semi-Urban,ML Engineer,142911,0 +85491,Male,34,Masters,10,90,3,92,87,2.0,7,75,Semi-Urban,Manager,94280,1 +85492,Female,36,Bachelors,13,38,93,60,98,5.0,4,78,Urban,Software Engineer,109029,1 +85493,Male,35,High School,3,32,63,8,88,3.0,1,27,Urban,HR Executive,133861,0 +85494,Female,23,Diploma,19,93,49,94,44,0.0,3,71,Rural,Software Engineer,104053,1 +85495,Male,40,High School,8,20,38,13,81,1.0,2,77,Semi-Urban,ML Engineer,83100,0 +85496,Female,48,Diploma,11,53,65,58,52,6.0,1,14,Semi-Urban,Software Engineer,85376,0 +85497,Female,37,Diploma,7,52,67,69,78,2.0,2,26,Semi-Urban,HR Executive,128366,0 +85498,Male,56,Diploma,6,4,19,25,7,0.0,4,43,Urban,Manager,32511,0 +85499,Female,21,Bachelors,2,58,74,9,72,4.0,2,71,Urban,ML Engineer,89436,0 +85500,Female,52,Bachelors,10,25,16,61,73,5.0,7,32,Urban,Data Analyst,111925,0 +85501,Male,53,Masters,19,25,73,52,78,2.0,2,1,Rural,Manager,113370,0 +85502,Female,37,High School,12,60,37,97,49,9.0,0,9,Urban,HR Executive,114927,0 +85503,Male,53,Diploma,9,1,93,41,56,4.0,3,93,Urban,Data Analyst,33498,0 +85504,Male,25,Diploma,11,86,26,94,65,9.0,6,57,Urban,Data Analyst,58106,1 +85505,Male,56,Diploma,11,86,37,54,22,8.0,1,35,Urban,Software Engineer,130624,0 +85506,Male,32,Masters,2,8,13,43,29,0.0,0,27,Urban,Manager,124860,0 +85507,Male,39,High School,7,94,39,31,78,3.0,7,66,Semi-Urban,ML Engineer,68376,0 +85508,Male,54,Bachelors,18,72,87,88,97,0.0,4,22,Urban,Data Analyst,143489,1 +85509,Male,48,Bachelors,4,51,62,67,13,9.0,3,37,Urban,HR Executive,101692,0 +85510,Male,50,High School,9,49,22,53,43,6.0,0,52,Rural,Manager,139295,0 +85511,Male,45,Masters,0,25,46,92,96,9.0,5,77,Urban,Data Analyst,141375,1 +85512,Female,52,Bachelors,2,6,88,85,45,9.0,5,62,Urban,ML Engineer,117605,1 +85513,Male,46,Masters,14,64,72,42,95,9.0,7,19,Urban,Data Analyst,45780,0 +85514,Male,52,High School,12,27,32,7,90,7.0,1,17,Rural,ML Engineer,103140,0 +85515,Other,57,Masters,18,3,76,34,54,8.0,1,70,Urban,Data Analyst,45247,0 +85516,Male,51,Diploma,10,74,51,94,27,6.0,4,98,Urban,Software Engineer,52617,1 +85517,Male,34,Bachelors,11,8,69,82,69,8.0,2,75,Urban,Software Engineer,91992,0 +85518,Female,47,Bachelors,4,14,49,87,28,8.0,3,88,Urban,Software Engineer,45167,0 +85519,Female,35,Diploma,14,79,34,13,22,2.0,5,34,Semi-Urban,Data Analyst,144269,0 +85520,Male,56,Bachelors,8,18,84,78,89,1.0,1,51,Semi-Urban,Manager,24714,0 +85521,Female,21,Bachelors,3,70,50,23,91,3.0,4,5,Semi-Urban,HR Executive,116494,0 +85522,Male,45,High School,10,48,36,44,63,1.0,6,25,Semi-Urban,HR Executive,80396,0 +85523,Male,49,Diploma,0,54,60,95,18,3.0,7,85,Semi-Urban,Software Engineer,45504,1 +85524,Male,28,Bachelors,19,48,23,10,47,8.0,5,26,Urban,Data Analyst,120826,0 +85525,Female,36,Bachelors,0,14,89,10,30,6.0,6,84,Urban,Manager,43906,0 +85526,Male,37,Bachelors,2,31,80,18,75,1.0,2,75,Semi-Urban,Manager,33626,0 +85527,Male,30,Diploma,3,63,66,54,99,5.0,6,7,Urban,Manager,115758,0 +85528,Male,46,Masters,13,82,53,38,35,0.0,2,69,Urban,Software Engineer,111028,1 +85529,Female,27,Bachelors,8,56,0,11,17,2.0,2,71,Urban,HR Executive,67594,0 +85530,Male,44,Bachelors,19,28,62,74,71,4.0,2,11,Urban,Manager,110521,0 +85531,Male,47,Bachelors,19,85,53,17,15,8.0,4,30,Rural,HR Executive,121608,0 +85532,Female,52,Diploma,6,99,54,23,77,9.0,3,79,Urban,Manager,88220,1 +85533,Female,47,Bachelors,1,99,96,99,6,0.0,6,32,Semi-Urban,Data Analyst,110738,1 +85534,Male,51,Bachelors,9,24,94,27,89,8.0,4,54,Rural,Software Engineer,76675,0 +85535,Male,28,Bachelors,7,71,16,74,15,4.0,0,22,Semi-Urban,Data Analyst,147752,0 +85536,Male,32,Diploma,7,74,84,7,29,3.0,7,0,Rural,HR Executive,103607,0 +85537,Female,36,Bachelors,7,39,4,4,91,1.0,3,6,Semi-Urban,Data Analyst,59921,0 +85538,Female,28,High School,4,33,20,7,97,8.0,0,40,Rural,HR Executive,88917,0 +85539,Male,31,High School,16,0,25,42,15,0.0,2,7,Urban,Software Engineer,46366,0 +85540,Female,38,Masters,18,26,66,28,81,5.0,2,33,Urban,HR Executive,71990,0 +85541,Female,55,Diploma,10,64,95,71,81,0.0,4,4,Semi-Urban,Manager,47086,0 +85542,Male,35,Bachelors,17,87,67,0,13,6.0,2,23,Urban,HR Executive,50864,0 +85543,Female,22,Bachelors,9,69,26,42,0,3.0,5,39,Urban,ML Engineer,110023,0 +85544,Male,44,Bachelors,16,96,95,89,56,8.0,1,58,Urban,Data Analyst,118754,1 +85545,Male,57,Masters,12,88,84,37,78,4.0,7,72,Rural,Data Analyst,122688,1 +85546,Male,28,Bachelors,8,87,27,44,23,4.0,4,39,Urban,ML Engineer,101384,0 +85547,Female,45,Bachelors,2,58,29,84,77,3.0,2,14,Semi-Urban,Manager,147846,0 +85548,Other,30,Diploma,13,33,81,69,40,5.0,4,2,Urban,ML Engineer,116762,0 +85549,Female,49,Bachelors,4,17,38,90,2,7.0,4,12,Urban,Data Analyst,58564,0 +85550,Male,22,High School,5,99,72,96,56,6.0,1,46,Semi-Urban,ML Engineer,36183,1 +85551,Male,32,Masters,8,15,11,77,68,0.0,6,26,Rural,Manager,82489,0 +85552,Female,33,Bachelors,11,36,72,87,44,7.0,3,57,Urban,Manager,138489,1 +85553,Female,32,Diploma,17,60,3,38,65,6.0,3,49,Rural,Software Engineer,44007,0 +85554,Male,27,Diploma,17,11,68,54,69,1.0,5,14,Urban,HR Executive,51799,0 +85555,Male,43,Bachelors,2,75,66,85,11,0.0,1,29,Urban,Manager,61281,1 +85556,Other,27,Masters,9,31,80,56,82,6.0,7,72,Rural,HR Executive,25725,0 +85557,Male,52,Masters,6,86,55,89,82,2.0,2,24,Urban,HR Executive,125288,1 +85558,Male,45,Bachelors,14,82,88,46,52,8.0,1,21,Urban,Data Analyst,23126,1 +85559,Female,52,High School,7,36,29,35,17,9.0,1,74,Urban,Software Engineer,94620,0 +85560,Female,29,Diploma,9,35,25,85,7,7.0,5,59,Semi-Urban,ML Engineer,75906,0 +85561,Male,56,Bachelors,18,47,56,41,69,4.0,2,4,Urban,HR Executive,81383,0 +85562,Male,21,Bachelors,9,61,3,97,55,3.0,4,85,Urban,ML Engineer,54351,1 +85563,Female,47,Bachelors,11,58,78,88,59,7.0,5,25,Urban,HR Executive,93835,1 +85564,Male,34,High School,19,88,3,79,20,5.0,2,3,Semi-Urban,Manager,71573,0 +85565,Female,39,Bachelors,17,24,44,64,46,1.0,4,41,Rural,Manager,139718,0 +85566,Male,58,High School,1,91,77,9,52,1.0,5,99,Rural,Data Analyst,122039,1 +85567,Male,39,Diploma,13,23,53,55,65,9.0,2,46,Urban,Data Analyst,120356,0 +85568,Female,48,Diploma,8,18,89,3,34,0.0,7,3,Urban,HR Executive,105180,0 +85569,Male,32,Diploma,2,17,37,24,86,1.0,2,78,Urban,HR Executive,33491,0 +85570,Male,33,Bachelors,10,60,71,97,42,5.0,5,72,Urban,Manager,123740,1 +85571,Female,25,High School,14,20,8,76,56,4.0,0,64,Rural,Data Analyst,108662,0 +85572,Male,52,Diploma,4,6,89,51,68,5.0,1,28,Semi-Urban,HR Executive,101091,0 +85573,Male,33,Masters,6,94,74,61,95,0.0,5,72,Rural,ML Engineer,114519,1 +85574,Female,26,Masters,19,83,90,91,15,1.0,7,16,Semi-Urban,Software Engineer,59435,1 +85575,Female,37,Diploma,2,89,58,51,57,0.0,6,76,Rural,Manager,140743,1 +85576,Female,24,Masters,15,88,26,57,32,8.0,6,90,Urban,Software Engineer,109290,1 +85577,Male,57,Masters,5,90,15,0,69,7.0,4,25,Semi-Urban,Manager,42585,0 +85578,Male,23,Bachelors,4,36,29,92,8,8.0,3,4,Urban,Manager,92313,0 +85579,Female,28,Bachelors,6,50,41,87,80,3.0,4,18,Semi-Urban,HR Executive,49300,0 +85580,Male,30,Masters,8,67,8,70,21,8.0,6,16,Urban,Manager,123409,0 +85581,Female,32,Diploma,2,44,20,82,36,8.0,3,52,Semi-Urban,Manager,136822,0 +85582,Male,30,Bachelors,2,88,84,9,88,9.0,0,96,Urban,Data Analyst,83776,1 +85583,Male,35,Masters,14,6,46,33,25,4.0,7,58,Rural,Data Analyst,82303,0 +85584,Male,41,Masters,14,47,27,22,92,5.0,3,53,Rural,HR Executive,130673,0 +85585,Male,45,Bachelors,16,76,6,63,3,9.0,0,1,Rural,ML Engineer,137544,0 +85586,Male,32,Bachelors,15,97,67,47,57,0.0,6,63,Rural,Data Analyst,39606,1 +85587,Female,49,High School,7,98,58,95,88,2.0,6,81,Rural,Data Analyst,116539,1 +85588,Male,51,High School,12,46,7,26,52,0.0,5,83,Urban,Manager,120283,0 +85589,Female,37,Diploma,16,21,66,9,20,4.0,3,26,Rural,Software Engineer,102120,0 +85590,Male,45,PhD,9,95,81,96,37,3.0,1,24,Semi-Urban,Data Analyst,64020,1 +85591,Male,21,Masters,17,65,67,60,14,7.0,5,0,Semi-Urban,ML Engineer,142590,0 +85592,Female,55,High School,3,33,97,75,10,9.0,3,57,Rural,Software Engineer,35143,1 +85593,Male,32,Bachelors,2,26,36,30,81,9.0,6,23,Urban,Manager,42257,0 +85594,Female,58,Bachelors,16,34,66,70,19,7.0,3,50,Urban,ML Engineer,130791,0 +85595,Other,59,Diploma,16,0,39,58,96,7.0,6,94,Urban,Manager,81905,0 +85596,Male,46,Masters,16,73,48,3,79,7.0,5,79,Semi-Urban,Software Engineer,65619,0 +85597,Male,23,Diploma,15,51,89,91,53,0.0,4,53,Semi-Urban,Data Analyst,100131,1 +85598,Male,49,PhD,1,49,20,64,19,4.0,7,29,Urban,Software Engineer,31654,0 +85599,Female,28,High School,3,28,99,23,82,0.0,4,54,Urban,ML Engineer,125689,0 +85600,Female,31,Masters,15,3,28,70,45,5.0,3,59,Urban,ML Engineer,115321,0 +85601,Female,43,Bachelors,18,20,69,39,57,2.0,2,47,Urban,ML Engineer,31111,0 +85602,Female,52,Diploma,10,25,97,61,93,9.0,5,98,Urban,ML Engineer,53371,1 +85603,Female,46,Diploma,9,34,89,86,9,3.0,1,7,Urban,Software Engineer,24558,0 +85604,Male,49,Bachelors,13,23,33,34,9,6.0,5,0,Semi-Urban,HR Executive,65401,0 +85605,Male,21,Diploma,19,39,35,55,41,5.0,1,63,Rural,Data Analyst,40455,0 +85606,Female,34,Bachelors,13,99,57,75,66,3.0,2,73,Urban,HR Executive,90918,1 +85607,Female,37,Masters,8,42,70,44,13,3.0,4,56,Semi-Urban,Data Analyst,121246,0 +85608,Male,57,Masters,0,54,16,69,12,9.0,2,42,Urban,Manager,117355,0 +85609,Female,29,Masters,16,9,7,56,77,5.0,1,86,Rural,HR Executive,81863,0 +85610,Male,40,High School,4,45,81,86,82,8.0,1,81,Rural,ML Engineer,54665,1 +85611,Male,34,Bachelors,18,99,71,35,86,9.0,7,18,Semi-Urban,Software Engineer,139010,0 +85612,Male,55,Bachelors,3,60,11,65,11,1.0,4,52,Semi-Urban,Manager,109977,0 +85613,Female,27,Masters,17,51,33,16,73,7.0,7,58,Urban,ML Engineer,131334,0 +85614,Male,57,Bachelors,13,5,11,74,11,9.0,2,95,Urban,HR Executive,48122,0 +85615,Other,23,Masters,5,71,28,70,43,2.0,4,23,Urban,Manager,107767,0 +85616,Male,36,Bachelors,16,5,80,60,4,1.0,0,72,Urban,Manager,59621,0 +85617,Female,53,Bachelors,15,97,49,68,24,0.0,4,42,Urban,HR Executive,61486,1 +85618,Male,52,High School,14,55,79,67,64,6.0,6,30,Urban,Data Analyst,60245,0 +85619,Male,30,High School,13,26,74,19,86,2.0,1,50,Urban,ML Engineer,85078,0 +85620,Male,49,Masters,9,80,8,17,84,1.0,6,18,Rural,Manager,21511,0 +85621,Female,33,Masters,16,29,3,3,44,3.0,4,50,Urban,Software Engineer,37557,0 +85622,Male,30,High School,0,0,59,73,5,4.0,0,52,Semi-Urban,Software Engineer,80326,0 +85623,Female,29,Diploma,1,94,9,18,29,7.0,3,76,Semi-Urban,ML Engineer,105789,0 +85624,Female,23,Bachelors,19,85,77,5,99,8.0,7,40,Urban,ML Engineer,24107,0 +85625,Male,34,High School,13,90,73,71,46,9.0,7,93,Urban,Software Engineer,32058,1 +85626,Male,36,Diploma,14,75,15,44,76,1.0,0,95,Urban,Manager,82465,0 +85627,Male,25,Masters,12,60,17,88,56,8.0,5,85,Urban,Manager,85190,1 +85628,Male,40,Bachelors,18,18,72,84,50,7.0,0,6,Urban,Software Engineer,107332,0 +85629,Female,37,High School,0,30,35,46,28,8.0,7,41,Semi-Urban,HR Executive,147600,0 +85630,Male,35,Masters,14,14,44,9,42,1.0,1,40,Urban,HR Executive,106036,0 +85631,Male,31,Masters,8,58,19,12,40,1.0,7,67,Rural,HR Executive,126843,0 +85632,Male,24,Diploma,16,53,35,72,37,0.0,4,92,Urban,HR Executive,49975,1 +85633,Male,40,Masters,17,21,10,90,36,6.0,0,63,Urban,Software Engineer,44453,0 +85634,Male,49,PhD,2,9,88,60,96,8.0,6,8,Rural,ML Engineer,59046,0 +85635,Male,43,Diploma,3,75,18,94,1,2.0,5,59,Semi-Urban,Manager,94289,1 +85636,Male,31,Diploma,2,90,50,94,7,9.0,0,71,Semi-Urban,Manager,100628,1 +85637,Male,35,Diploma,9,32,74,71,16,5.0,3,4,Urban,Manager,107043,0 +85638,Female,49,Masters,1,59,27,85,22,6.0,6,61,Semi-Urban,ML Engineer,84684,0 +85639,Female,45,Bachelors,7,56,75,84,85,7.0,1,47,Urban,ML Engineer,41573,1 +85640,Female,45,Masters,3,23,91,58,72,9.0,5,99,Semi-Urban,ML Engineer,28080,1 +85641,Female,47,Masters,5,43,79,65,15,5.0,4,89,Urban,ML Engineer,144749,1 +85642,Female,27,Masters,19,79,60,68,12,4.0,2,5,Semi-Urban,Manager,140849,0 +85643,Male,40,High School,3,5,55,82,64,5.0,7,12,Semi-Urban,Data Analyst,37919,0 +85644,Male,23,Bachelors,15,32,51,30,75,8.0,7,20,Semi-Urban,Software Engineer,29580,0 +85645,Male,48,Bachelors,1,67,40,95,81,4.0,6,6,Rural,Data Analyst,20509,0 +85646,Female,55,High School,12,3,89,7,25,8.0,0,25,Rural,HR Executive,42578,0 +85647,Female,58,Diploma,8,47,67,14,65,9.0,4,34,Urban,HR Executive,145958,0 +85648,Male,45,High School,11,92,46,52,79,3.0,7,66,Rural,HR Executive,28489,1 +85649,Male,49,High School,0,65,47,6,66,5.0,3,9,Rural,HR Executive,125972,0 +85650,Male,54,High School,4,71,96,94,19,2.0,2,78,Urban,HR Executive,73394,1 +85651,Male,50,Bachelors,10,31,98,67,87,5.0,3,25,Semi-Urban,ML Engineer,132708,0 +85652,Male,31,High School,13,46,55,99,9,9.0,5,65,Semi-Urban,Manager,41014,1 +85653,Male,58,Masters,12,85,45,78,97,4.0,7,1,Semi-Urban,Software Engineer,62418,0 +85654,Female,45,Masters,4,38,5,66,44,5.0,4,11,Urban,HR Executive,98672,0 +85655,Female,50,Bachelors,8,21,6,4,76,7.0,6,11,Semi-Urban,HR Executive,37682,0 +85656,Male,52,Masters,10,38,23,36,86,0.0,1,19,Urban,Software Engineer,34607,0 +85657,Male,57,High School,6,94,14,81,91,2.0,1,70,Urban,Software Engineer,33027,1 +85658,Other,31,Diploma,14,42,94,47,4,9.0,6,28,Semi-Urban,HR Executive,109085,0 +85659,Female,30,Masters,12,43,21,82,62,4.0,3,63,Urban,ML Engineer,41011,0 +85660,Female,29,High School,1,7,9,95,17,6.0,5,53,Urban,Manager,65806,0 +85661,Male,30,Bachelors,6,34,80,66,23,3.0,6,69,Urban,Manager,84989,1 +85662,Male,54,Diploma,0,24,19,94,89,8.0,0,75,Rural,Data Analyst,37594,0 +85663,Female,40,Masters,3,37,92,38,20,7.0,0,4,Rural,Software Engineer,116181,0 +85664,Other,25,Diploma,5,18,16,89,57,7.0,3,42,Semi-Urban,HR Executive,25648,0 +85665,Male,23,Bachelors,8,86,51,16,99,3.0,4,29,Urban,Software Engineer,67196,0 +85666,Female,45,High School,6,37,83,6,46,8.0,5,93,Urban,Data Analyst,35562,0 +85667,Male,40,Diploma,14,65,5,6,43,0.0,0,27,Urban,Manager,35491,0 +85668,Male,34,High School,4,1,14,72,60,1.0,5,90,Semi-Urban,Data Analyst,108089,0 +85669,Male,21,Bachelors,6,74,23,55,70,7.0,3,84,Rural,Software Engineer,81555,1 +85670,Male,28,Diploma,2,91,65,27,58,5.0,6,97,Urban,HR Executive,127920,1 +85671,Male,39,Bachelors,2,66,36,45,85,6.0,5,54,Rural,HR Executive,61370,0 +85672,Male,35,High School,4,12,41,34,75,3.0,2,10,Urban,Manager,89531,0 +85673,Female,23,High School,16,46,0,43,26,2.0,7,95,Urban,Data Analyst,131418,0 +85674,Female,24,Masters,5,76,22,46,36,8.0,4,60,Rural,Data Analyst,96968,0 +85675,Male,55,Bachelors,11,86,87,60,97,5.0,2,29,Semi-Urban,HR Executive,93900,1 +85676,Female,42,Masters,1,51,15,36,68,4.0,7,6,Urban,HR Executive,49345,0 +85677,Male,40,Masters,0,71,31,65,74,0.0,6,66,Urban,Data Analyst,31061,0 +85678,Female,21,High School,19,76,73,25,98,0.0,6,18,Urban,Data Analyst,113576,0 +85679,Male,34,Bachelors,12,99,41,32,59,9.0,3,82,Urban,Manager,138615,1 +85680,Female,22,Bachelors,0,80,41,90,98,4.0,0,6,Urban,ML Engineer,68751,0 +85681,Male,51,High School,19,89,34,30,3,5.0,3,36,Semi-Urban,Software Engineer,46058,0 +85682,Male,48,Diploma,11,6,9,5,31,6.0,6,60,Rural,ML Engineer,114828,0 +85683,Male,42,Bachelors,15,88,89,32,86,8.0,4,27,Semi-Urban,Manager,61060,1 +85684,Male,29,Masters,9,0,44,63,72,6.0,2,31,Urban,Manager,106616,0 +85685,Male,41,High School,8,63,41,95,93,9.0,2,28,Urban,Manager,90571,0 +85686,Male,30,Diploma,14,42,36,22,89,8.0,5,56,Rural,Data Analyst,130066,0 +85687,Male,54,Diploma,3,40,6,16,70,4.0,5,94,Urban,Software Engineer,91493,0 +85688,Male,43,High School,17,70,56,63,93,2.0,4,4,Rural,Data Analyst,25687,0 +85689,Male,48,Bachelors,8,47,9,65,90,4.0,0,78,Semi-Urban,Data Analyst,111423,0 +85690,Male,46,High School,5,50,3,71,33,7.0,1,84,Urban,ML Engineer,37177,0 +85691,Female,25,Bachelors,17,29,16,66,5,3.0,0,19,Semi-Urban,Software Engineer,130002,0 +85692,Male,36,High School,11,29,73,25,64,8.0,4,81,Semi-Urban,HR Executive,69292,0 +85693,Male,32,Diploma,3,21,24,69,62,5.0,7,98,Semi-Urban,ML Engineer,53176,0 +85694,Male,23,PhD,8,76,64,1,80,6.0,4,13,Urban,Software Engineer,41349,0 +85695,Male,47,Masters,6,0,18,14,77,3.0,5,18,Urban,ML Engineer,101529,0 +85696,Male,22,Masters,15,95,26,70,11,4.0,6,63,Urban,HR Executive,59257,1 +85697,Male,41,Bachelors,11,45,59,62,56,3.0,4,53,Semi-Urban,Software Engineer,131073,0 +85698,Male,58,Bachelors,3,82,8,81,35,5.0,4,61,Urban,Manager,28770,0 +85699,Female,25,Masters,3,83,8,79,8,2.0,1,20,Semi-Urban,HR Executive,28570,0 +85700,Male,33,High School,16,16,99,26,96,8.0,5,52,Semi-Urban,ML Engineer,143017,0 +85701,Male,49,Masters,10,95,56,88,97,5.0,2,65,Semi-Urban,Software Engineer,31450,1 +85702,Female,55,Bachelors,5,90,30,58,9,6.0,4,9,Urban,HR Executive,115113,0 +85703,Female,23,Diploma,8,87,65,23,8,1.0,3,81,Rural,HR Executive,116532,1 +85704,Female,55,Masters,10,91,19,45,59,8.0,4,81,Urban,HR Executive,62842,0 +85705,Male,23,High School,10,31,30,64,79,8.0,3,80,Rural,Software Engineer,72324,0 +85706,Female,30,Bachelors,18,43,38,22,5,2.0,5,60,Semi-Urban,Data Analyst,49463,0 +85707,Male,25,Masters,3,21,60,7,64,2.0,0,63,Semi-Urban,Software Engineer,113529,0 +85708,Female,30,PhD,9,24,50,9,67,0.0,7,3,Urban,Software Engineer,79570,0 +85709,Male,44,Bachelors,11,87,13,34,12,5.0,4,80,Urban,Manager,112782,0 +85710,Male,48,Masters,13,26,17,68,40,2.0,4,15,Urban,Manager,44279,0 +85711,Male,31,Diploma,2,10,10,92,49,5.0,4,24,Urban,ML Engineer,79057,0 +85712,Male,55,Bachelors,0,58,22,97,95,8.0,1,33,Urban,Data Analyst,109046,0 +85713,Female,48,Diploma,1,81,58,87,5,6.0,5,32,Semi-Urban,Manager,29469,1 +85714,Male,48,Masters,14,24,75,36,65,5.0,5,28,Urban,ML Engineer,139407,0 +85715,Male,41,High School,5,27,61,59,42,0.0,7,74,Rural,Data Analyst,54365,0 +85716,Male,35,Masters,19,7,73,47,88,3.0,2,22,Urban,Manager,55836,0 +85717,Male,34,Bachelors,12,5,51,63,18,1.0,6,79,Rural,Data Analyst,147382,0 +85718,Male,24,Masters,8,10,41,60,73,2.0,6,33,Urban,Software Engineer,68250,0 +85719,Male,27,Bachelors,13,76,43,59,79,8.0,7,96,Semi-Urban,Data Analyst,104561,1 +85720,Other,23,Masters,8,32,10,73,56,7.0,3,40,Urban,Data Analyst,43562,0 +85721,Male,47,Masters,5,85,0,92,61,8.0,7,65,Semi-Urban,HR Executive,48472,1 +85722,Female,47,High School,15,69,32,8,1,2.0,3,11,Urban,ML Engineer,141290,0 +85723,Male,40,Bachelors,9,39,70,30,46,5.0,0,41,Urban,ML Engineer,132043,0 +85724,Male,58,Masters,6,53,40,86,55,6.0,2,92,Rural,HR Executive,145118,1 +85725,Male,36,Diploma,7,76,50,46,10,1.0,1,18,Urban,Software Engineer,94719,0 +85726,Female,22,Masters,9,81,93,27,84,6.0,5,83,Urban,HR Executive,71331,1 +85727,Male,27,Masters,12,29,95,84,59,9.0,6,81,Semi-Urban,Manager,38398,1 +85728,Male,28,High School,17,74,2,23,28,7.0,6,71,Rural,HR Executive,57178,0 +85729,Female,31,Bachelors,1,88,66,22,60,3.0,2,74,Semi-Urban,Data Analyst,68880,1 +85730,Female,31,Masters,19,13,38,81,43,8.0,1,99,Urban,Data Analyst,47862,0 +85731,Male,25,High School,10,62,51,43,82,9.0,5,59,Urban,ML Engineer,95244,0 +85732,Male,40,Bachelors,15,73,97,86,95,8.0,4,21,Urban,HR Executive,85980,1 +85733,Male,49,Bachelors,11,7,31,4,9,0.0,3,18,Semi-Urban,ML Engineer,146310,0 +85734,Male,37,Masters,7,38,72,60,70,4.0,4,29,Urban,HR Executive,88565,0 +85735,Female,27,Masters,1,94,36,46,83,5.0,0,88,Urban,Data Analyst,106435,1 +85736,Female,58,Bachelors,17,67,86,94,37,4.0,2,51,Urban,Data Analyst,93746,1 +85737,Male,57,Bachelors,6,12,67,24,80,4.0,1,2,Urban,Data Analyst,90610,0 +85738,Female,49,High School,11,21,44,78,75,8.0,2,78,Urban,HR Executive,34392,0 +85739,Male,39,High School,17,20,86,33,25,3.0,4,71,Urban,Software Engineer,106348,0 +85740,Male,29,High School,18,69,47,21,68,2.0,1,22,Urban,Manager,87123,0 +85741,Male,39,PhD,18,65,98,3,30,4.0,1,6,Semi-Urban,Software Engineer,101804,0 +85742,Male,21,PhD,1,64,67,46,60,1.0,6,72,Urban,ML Engineer,76521,1 +85743,Male,31,Bachelors,7,49,59,91,10,0.0,1,0,Urban,Software Engineer,42580,0 +85744,Female,40,Bachelors,11,60,65,0,81,6.0,5,71,Urban,Manager,25625,0 +85745,Female,27,Masters,14,81,69,42,50,3.0,7,48,Urban,HR Executive,144395,0 +85746,Male,41,PhD,0,50,79,22,49,9.0,7,63,Urban,HR Executive,97415,0 +85747,Male,24,Bachelors,15,94,6,32,0,3.0,0,86,Urban,Software Engineer,47426,0 +85748,Male,56,Diploma,2,92,16,19,89,9.0,6,65,Urban,Data Analyst,82884,0 +85749,Male,33,Masters,11,16,55,32,23,4.0,6,28,Urban,Manager,43853,0 +85750,Male,25,High School,4,6,7,84,80,4.0,6,13,Urban,ML Engineer,109691,0 +85751,Male,36,Bachelors,1,67,84,27,88,2.0,4,31,Semi-Urban,HR Executive,135457,0 +85752,Male,27,High School,7,60,25,92,90,4.0,7,65,Semi-Urban,ML Engineer,87056,1 +85753,Male,48,Masters,19,43,85,4,74,3.0,0,77,Urban,Data Analyst,142065,0 +85754,Male,50,Diploma,7,41,33,85,97,3.0,7,26,Urban,Software Engineer,37797,0 +85755,Other,21,Masters,5,18,16,73,37,1.0,7,21,Urban,Manager,108654,0 +85756,Female,48,Masters,5,92,80,15,34,3.0,7,61,Semi-Urban,ML Engineer,137646,1 +85757,Female,26,Masters,9,38,17,83,82,1.0,0,83,Rural,Data Analyst,21932,0 +85758,Male,24,PhD,2,5,91,55,0,5.0,1,88,Urban,Manager,78185,1 +85759,Male,59,Bachelors,13,19,91,78,38,2.0,7,98,Semi-Urban,Software Engineer,96672,1 +85760,Female,25,Masters,13,99,77,98,71,8.0,4,58,Urban,HR Executive,137114,1 +85761,Male,36,Diploma,15,32,10,24,70,2.0,6,14,Urban,Manager,110877,0 +85762,Male,53,Bachelors,12,89,2,43,36,7.0,6,74,Semi-Urban,Data Analyst,30550,0 +85763,Male,54,Bachelors,13,29,89,93,34,8.0,2,13,Semi-Urban,Software Engineer,93475,0 +85764,Female,28,Bachelors,18,36,29,56,63,7.0,1,39,Rural,Manager,136054,0 +85765,Male,57,Bachelors,0,40,87,26,88,4.0,4,33,Urban,HR Executive,50570,0 +85766,Female,38,Masters,4,81,14,68,71,5.0,3,16,Semi-Urban,ML Engineer,124656,0 +85767,Male,51,Bachelors,3,66,40,99,31,3.0,1,3,Urban,Manager,97335,0 +85768,Male,56,Masters,19,62,93,22,8,6.0,0,6,Semi-Urban,Manager,114284,0 +85769,Other,22,Bachelors,12,47,66,55,48,9.0,3,76,Urban,Software Engineer,54161,1 +85770,Male,43,Diploma,12,38,91,53,69,2.0,2,30,Semi-Urban,Manager,37015,0 +85771,Male,28,Masters,0,27,16,57,66,9.0,7,18,Urban,Manager,92221,0 +85772,Male,26,High School,12,72,85,25,18,1.0,2,46,Urban,Software Engineer,100820,0 +85773,Male,29,Masters,19,62,78,71,84,3.0,1,31,Urban,Data Analyst,127658,1 +85774,Male,48,High School,9,37,76,19,88,3.0,6,46,Semi-Urban,Data Analyst,111435,0 +85775,Male,53,Bachelors,18,29,99,17,95,3.0,7,23,Semi-Urban,Data Analyst,21499,0 +85776,Other,28,Diploma,7,78,56,21,4,8.0,0,61,Semi-Urban,Manager,121717,0 +85777,Male,25,PhD,4,37,51,60,13,0.0,7,78,Urban,ML Engineer,117788,0 +85778,Female,53,Diploma,18,20,68,95,73,3.0,1,60,Urban,Manager,56642,1 +85779,Female,45,Masters,9,40,34,18,17,5.0,3,16,Semi-Urban,Software Engineer,26994,0 +85780,Female,54,Diploma,15,0,54,67,43,8.0,5,61,Semi-Urban,Software Engineer,37737,0 +85781,Female,21,Diploma,9,0,38,68,25,3.0,7,22,Semi-Urban,Software Engineer,126686,0 +85782,Male,53,Bachelors,4,4,18,57,14,2.0,4,62,Semi-Urban,Data Analyst,57460,0 +85783,Male,59,Bachelors,1,28,7,11,85,7.0,7,36,Urban,HR Executive,127729,0 +85784,Male,58,Bachelors,13,57,3,51,71,3.0,1,47,Urban,ML Engineer,146457,0 +85785,Male,53,Diploma,1,67,83,36,8,3.0,4,57,Semi-Urban,Software Engineer,45524,1 +85786,Male,55,Bachelors,4,62,86,36,80,9.0,4,31,Semi-Urban,Manager,68812,0 +85787,Female,21,Masters,7,76,30,25,32,0.0,7,22,Urban,Data Analyst,133121,0 +85788,Male,37,Bachelors,16,94,66,83,33,3.0,3,90,Rural,ML Engineer,29181,1 +85789,Female,31,Diploma,6,75,74,74,22,1.0,3,54,Urban,ML Engineer,30404,1 +85790,Male,53,Bachelors,14,39,14,74,3,3.0,5,40,Semi-Urban,Manager,100495,0 +85791,Male,55,High School,4,40,76,50,99,7.0,4,36,Urban,Data Analyst,78266,0 +85792,Female,28,Bachelors,19,55,70,83,31,5.0,1,27,Rural,HR Executive,44365,0 +85793,Male,33,Bachelors,15,61,5,10,41,0.0,5,61,Urban,ML Engineer,94085,0 +85794,Female,47,Bachelors,4,41,85,42,26,3.0,1,46,Semi-Urban,Data Analyst,137919,0 +85795,Male,37,Bachelors,10,43,44,6,88,2.0,5,58,Urban,Manager,74099,0 +85796,Female,26,Diploma,0,97,97,83,44,1.0,0,66,Urban,HR Executive,57066,1 +85797,Male,30,High School,0,79,6,55,37,8.0,4,44,Rural,Software Engineer,50135,0 +85798,Female,52,Diploma,10,91,93,19,73,0.0,1,25,Semi-Urban,HR Executive,107085,0 +85799,Male,24,Bachelors,16,5,61,32,46,1.0,0,59,Semi-Urban,Data Analyst,27379,0 +85800,Female,58,Diploma,5,2,52,70,51,0.0,7,37,Rural,Software Engineer,140127,0 +85801,Female,33,Masters,9,13,63,5,40,6.0,1,1,Semi-Urban,HR Executive,96497,0 +85802,Female,32,High School,9,7,73,44,23,9.0,3,22,Urban,ML Engineer,108985,0 +85803,Male,22,Diploma,10,75,63,9,2,5.0,7,62,Semi-Urban,Data Analyst,102251,0 +85804,Female,55,Diploma,2,39,8,21,32,3.0,4,30,Rural,HR Executive,24007,0 +85805,Female,47,High School,3,86,39,34,24,1.0,3,5,Semi-Urban,Data Analyst,106944,0 +85806,Male,53,Masters,15,52,59,8,72,9.0,3,80,Urban,Manager,81407,0 +85807,Male,59,Bachelors,6,6,97,10,83,8.0,1,70,Semi-Urban,HR Executive,29998,0 +85808,Male,51,PhD,1,75,78,35,48,4.0,7,47,Urban,Manager,123976,1 +85809,Male,48,Bachelors,8,53,51,44,96,6.0,2,16,Urban,HR Executive,32898,0 +85810,Female,45,Bachelors,15,44,89,1,69,7.0,7,27,Rural,Manager,29123,0 +85811,Female,24,Diploma,3,53,35,34,1,4.0,1,81,Urban,ML Engineer,75159,0 +85812,Male,44,Bachelors,1,74,16,9,65,3.0,3,6,Urban,ML Engineer,63948,0 +85813,Male,45,Masters,2,2,68,26,68,3.0,7,21,Rural,Manager,137230,0 +85814,Male,32,Diploma,8,49,74,59,64,2.0,2,39,Urban,ML Engineer,80065,0 +85815,Male,27,Masters,10,15,63,44,70,5.0,5,66,Rural,Manager,30654,0 +85816,Male,41,Bachelors,9,59,1,95,90,8.0,5,48,Urban,Manager,118701,0 +85817,Male,39,High School,11,34,67,25,35,8.0,2,96,Rural,Manager,42759,0 +85818,Female,42,Bachelors,1,6,59,11,79,9.0,5,65,Urban,Manager,104282,0 +85819,Male,21,High School,9,21,32,75,44,5.0,0,74,Semi-Urban,Manager,40361,0 +85820,Other,59,Bachelors,0,51,5,96,69,3.0,5,38,Urban,Data Analyst,113070,0 +85821,Female,52,Diploma,13,19,90,45,16,3.0,3,65,Urban,Software Engineer,29249,0 +85822,Male,31,Bachelors,15,96,41,69,20,5.0,6,47,Rural,ML Engineer,112286,1 +85823,Female,21,High School,19,29,72,50,99,7.0,3,56,Urban,Data Analyst,90988,0 +85824,Male,33,Diploma,6,72,35,44,68,7.0,4,62,Semi-Urban,HR Executive,65742,0 +85825,Other,40,Bachelors,6,80,62,79,17,6.0,2,57,Urban,Software Engineer,141735,1 +85826,Female,51,Masters,17,55,36,54,80,4.0,0,96,Semi-Urban,ML Engineer,82354,1 +85827,Male,25,High School,17,93,8,82,77,8.0,4,5,Semi-Urban,Data Analyst,125516,0 +85828,Male,45,Bachelors,2,8,52,33,19,3.0,7,45,Urban,Manager,80898,0 +85829,Female,54,Diploma,9,94,84,32,89,0.0,1,44,Rural,Data Analyst,97523,1 +85830,Female,36,High School,6,38,35,42,32,7.0,0,55,Urban,Data Analyst,113920,0 +85831,Male,43,Masters,18,44,16,89,26,2.0,2,11,Semi-Urban,Manager,72567,0 +85832,Male,37,Diploma,8,96,84,60,27,9.0,1,36,Semi-Urban,ML Engineer,149633,1 +85833,Female,31,Bachelors,15,53,57,6,96,8.0,0,80,Rural,Software Engineer,100178,0 +85834,Female,31,Bachelors,7,56,53,73,52,4.0,5,69,Semi-Urban,HR Executive,35610,1 +85835,Female,21,Bachelors,2,89,13,83,73,1.0,7,56,Urban,Software Engineer,119635,1 +85836,Female,22,Bachelors,14,19,89,99,74,3.0,2,38,Urban,HR Executive,72246,1 +85837,Male,53,Masters,12,6,26,31,41,9.0,5,45,Urban,ML Engineer,66557,0 +85838,Female,34,Bachelors,2,30,35,90,37,7.0,7,80,Urban,Manager,63537,0 +85839,Male,52,Diploma,11,25,92,17,29,1.0,0,17,Semi-Urban,Data Analyst,137915,0 +85840,Female,57,High School,1,31,11,60,36,4.0,0,58,Urban,ML Engineer,131496,0 +85841,Male,49,Masters,4,20,86,35,97,1.0,3,60,Urban,HR Executive,38372,0 +85842,Female,36,Masters,11,86,88,18,17,7.0,0,28,Urban,ML Engineer,52791,0 +85843,Male,51,Masters,7,97,54,38,45,7.0,7,89,Rural,Manager,21444,1 +85844,Female,28,High School,12,47,11,91,15,1.0,7,74,Urban,HR Executive,42187,0 +85845,Male,21,Masters,8,39,72,98,31,9.0,1,59,Urban,ML Engineer,83096,1 +85846,Female,47,Masters,18,92,8,76,35,4.0,6,8,Rural,Data Analyst,60070,0 +85847,Male,34,Bachelors,8,38,76,98,37,1.0,5,0,Urban,Data Analyst,75906,0 +85848,Male,50,Diploma,8,74,80,32,52,1.0,0,51,Urban,ML Engineer,117159,1 +85849,Female,39,Bachelors,6,55,29,91,38,1.0,2,0,Semi-Urban,Software Engineer,62829,0 +85850,Female,36,Bachelors,12,54,15,31,17,4.0,7,13,Rural,ML Engineer,34887,0 +85851,Other,27,Bachelors,1,16,16,19,78,8.0,6,0,Urban,Data Analyst,125601,0 +85852,Male,25,Masters,11,1,71,83,82,1.0,1,26,Rural,ML Engineer,83886,0 +85853,Male,31,Diploma,3,16,32,19,66,2.0,2,71,Rural,Data Analyst,30394,0 +85854,Other,27,Bachelors,15,7,77,76,96,9.0,3,14,Urban,Software Engineer,112065,0 +85855,Female,40,High School,7,23,51,5,39,9.0,4,83,Rural,Software Engineer,124533,0 +85856,Male,47,Bachelors,12,93,24,30,26,6.0,2,53,Urban,HR Executive,131948,0 +85857,Male,50,Diploma,0,63,8,49,12,5.0,6,48,Semi-Urban,Manager,85344,0 +85858,Female,51,High School,11,69,27,48,68,2.0,0,94,Urban,Manager,85992,0 +85859,Female,43,Diploma,17,84,13,48,41,9.0,6,21,Semi-Urban,Data Analyst,88012,0 +85860,Male,36,Bachelors,6,98,83,89,14,9.0,3,69,Rural,HR Executive,43207,1 +85861,Female,52,Diploma,3,21,39,95,51,4.0,5,17,Semi-Urban,Data Analyst,128455,0 +85862,Male,56,High School,9,11,2,79,10,5.0,3,30,Urban,HR Executive,68038,0 +85863,Male,59,Bachelors,13,1,17,85,7,6.0,2,37,Rural,Software Engineer,42986,0 +85864,Male,44,Bachelors,16,41,77,74,41,2.0,1,69,Urban,Manager,29698,1 +85865,Male,55,High School,11,30,55,8,0,0.0,3,16,Semi-Urban,HR Executive,127729,0 +85866,Male,59,Diploma,14,40,80,68,72,3.0,6,78,Semi-Urban,Software Engineer,141764,1 +85867,Male,33,Bachelors,13,86,85,11,12,6.0,3,68,Urban,Manager,106193,1 +85868,Other,23,Bachelors,17,85,43,85,37,7.0,5,16,Semi-Urban,Data Analyst,67446,0 +85869,Male,51,Bachelors,10,5,72,32,64,9.0,6,63,Semi-Urban,Data Analyst,90953,0 +85870,Male,58,High School,19,26,7,8,5,4.0,4,28,Semi-Urban,Manager,76890,0 +85871,Male,42,Diploma,8,54,42,67,37,9.0,1,38,Urban,Software Engineer,67938,0 +85872,Female,37,Bachelors,3,23,64,47,26,2.0,0,29,Semi-Urban,Manager,77252,0 +85873,Female,50,Bachelors,7,4,81,43,43,8.0,2,42,Rural,Manager,93442,0 +85874,Male,54,Bachelors,1,20,6,22,31,5.0,6,39,Urban,Manager,122444,0 +85875,Male,38,PhD,2,49,94,47,89,6.0,7,63,Semi-Urban,HR Executive,58206,1 +85876,Male,59,Diploma,3,86,66,4,67,8.0,0,49,Rural,Software Engineer,29929,0 +85877,Female,41,Diploma,18,10,32,43,51,4.0,7,7,Urban,Data Analyst,101004,0 +85878,Male,52,Masters,14,69,53,39,47,3.0,7,2,Urban,Data Analyst,49073,0 +85879,Male,52,PhD,12,65,83,66,1,6.0,4,42,Urban,Software Engineer,99308,1 +85880,Male,22,Masters,9,64,28,11,24,6.0,5,8,Urban,HR Executive,112442,0 +85881,Male,53,Diploma,1,81,29,93,23,5.0,2,58,Semi-Urban,HR Executive,63576,1 +85882,Female,42,Bachelors,12,74,67,97,32,9.0,4,25,Urban,ML Engineer,43899,1 +85883,Male,54,Bachelors,10,75,85,87,18,3.0,6,77,Rural,HR Executive,60732,1 +85884,Other,28,High School,18,30,33,89,84,4.0,7,40,Rural,Manager,103960,0 +85885,Male,53,Masters,2,79,41,89,39,3.0,0,43,Urban,ML Engineer,35497,1 +85886,Male,25,Masters,7,63,17,83,55,3.0,6,79,Semi-Urban,Data Analyst,128729,1 +85887,Male,54,Diploma,5,65,5,37,48,8.0,5,86,Rural,Manager,137629,0 +85888,Male,56,Masters,8,4,92,24,74,8.0,6,57,Urban,ML Engineer,62721,0 +85889,Female,57,PhD,16,50,38,61,99,2.0,2,53,Urban,Data Analyst,79718,0 +85890,Male,57,Diploma,4,96,65,88,72,7.0,2,75,Urban,Software Engineer,72635,1 +85891,Male,25,High School,17,74,69,2,26,7.0,3,57,Semi-Urban,Data Analyst,40877,0 +85892,Male,25,High School,1,45,18,84,48,6.0,3,76,Urban,HR Executive,124269,0 +85893,Male,43,Bachelors,4,47,15,78,11,7.0,6,28,Urban,Manager,116623,0 +85894,Male,41,High School,6,91,63,23,0,2.0,5,59,Urban,Software Engineer,109291,1 +85895,Male,31,Bachelors,12,58,3,49,82,7.0,3,37,Urban,Data Analyst,41872,0 +85896,Female,49,Masters,3,8,68,24,66,7.0,1,84,Urban,Manager,34779,0 +85897,Female,24,Diploma,4,98,23,61,94,4.0,6,34,Urban,ML Engineer,107245,0 +85898,Female,41,Bachelors,5,72,98,67,98,0.0,1,39,Urban,Manager,113202,1 +85899,Female,43,High School,14,57,50,21,80,1.0,4,63,Semi-Urban,HR Executive,41616,0 +85900,Male,52,Masters,4,73,30,46,42,1.0,4,64,Urban,Software Engineer,121253,0 +85901,Male,29,Masters,9,92,96,46,55,4.0,2,27,Urban,Manager,53184,1 +85902,Female,58,Bachelors,11,24,1,63,98,8.0,3,40,Urban,Data Analyst,52702,0 +85903,Male,59,High School,18,40,64,2,42,0.0,7,82,Urban,Manager,63825,0 +85904,Female,59,High School,2,87,90,40,29,7.0,6,82,Urban,ML Engineer,120233,1 +85905,Female,24,Diploma,7,97,63,40,38,9.0,0,60,Rural,Data Analyst,31867,1 +85906,Female,44,Masters,11,27,14,31,42,2.0,6,15,Urban,Manager,129451,0 +85907,Male,53,Bachelors,2,94,54,92,23,6.0,2,67,Semi-Urban,Data Analyst,109307,1 +85908,Female,30,Bachelors,9,91,11,7,39,3.0,2,91,Semi-Urban,HR Executive,118204,0 +85909,Male,59,PhD,5,69,14,68,36,7.0,6,59,Semi-Urban,Data Analyst,32349,0 +85910,Male,44,Bachelors,0,52,36,21,4,3.0,7,33,Urban,Software Engineer,49655,0 +85911,Female,44,Bachelors,10,51,14,79,62,7.0,0,54,Urban,HR Executive,79933,0 +85912,Male,56,Bachelors,14,79,50,79,53,9.0,7,84,Urban,Manager,58603,1 +85913,Male,26,Bachelors,5,16,75,70,19,2.0,6,9,Semi-Urban,HR Executive,49147,0 +85914,Male,33,High School,9,4,35,60,16,7.0,6,19,Urban,Data Analyst,110711,0 +85915,Male,41,Masters,4,89,36,23,3,7.0,3,99,Rural,Software Engineer,44982,1 +85916,Female,27,Diploma,18,6,85,22,82,5.0,0,71,Semi-Urban,Data Analyst,21745,0 +85917,Female,42,Masters,12,50,52,74,71,3.0,7,4,Rural,ML Engineer,83587,0 +85918,Female,52,Bachelors,7,65,4,32,71,2.0,1,77,Rural,Data Analyst,110725,0 +85919,Female,28,Masters,10,20,18,73,88,8.0,7,71,Semi-Urban,Manager,41190,0 +85920,Male,48,Bachelors,16,57,55,14,41,6.0,3,33,Semi-Urban,Data Analyst,137467,0 +85921,Female,41,Bachelors,6,16,9,4,41,5.0,3,4,Semi-Urban,ML Engineer,27044,0 +85922,Male,30,Bachelors,15,94,52,39,27,2.0,4,35,Urban,Manager,43943,0 +85923,Male,27,Bachelors,6,93,15,40,49,2.0,7,89,Semi-Urban,ML Engineer,72745,1 +85924,Female,32,Bachelors,3,84,70,96,88,7.0,1,82,Semi-Urban,Data Analyst,26607,1 +85925,Male,44,Bachelors,9,91,40,61,93,3.0,6,89,Rural,Data Analyst,77178,1 +85926,Male,59,Diploma,17,35,23,6,39,1.0,4,0,Urban,Data Analyst,101129,0 +85927,Male,35,Masters,2,43,52,85,58,2.0,2,83,Rural,HR Executive,131099,1 +85928,Male,27,Diploma,2,89,41,13,87,7.0,7,55,Semi-Urban,HR Executive,72211,0 +85929,Female,57,Diploma,6,29,9,54,52,1.0,1,71,Urban,ML Engineer,94851,0 +85930,Female,28,Bachelors,2,19,43,35,24,2.0,1,73,Semi-Urban,Software Engineer,119308,0 +85931,Male,27,Diploma,11,84,71,90,76,2.0,2,33,Urban,ML Engineer,72067,1 +85932,Female,31,Diploma,15,37,65,75,33,8.0,5,46,Semi-Urban,Manager,80674,0 +85933,Female,38,Bachelors,1,7,45,48,73,2.0,1,95,Urban,Software Engineer,90969,0 +85934,Male,44,Masters,12,86,8,11,34,1.0,2,41,Urban,Software Engineer,87895,0 +85935,Female,49,Bachelors,8,78,3,60,91,4.0,6,22,Urban,ML Engineer,48406,0 +85936,Male,22,PhD,4,80,82,90,98,2.0,5,41,Urban,Software Engineer,103902,1 +85937,Female,25,Masters,8,44,56,16,71,2.0,5,80,Urban,ML Engineer,77619,0 +85938,Female,22,High School,8,58,9,81,11,5.0,5,25,Semi-Urban,ML Engineer,51907,0 +85939,Male,50,Masters,2,77,92,90,54,5.0,0,8,Semi-Urban,Software Engineer,31371,1 +85940,Female,24,Bachelors,11,76,44,22,84,8.0,4,85,Rural,ML Engineer,67661,0 +85941,Male,56,Masters,12,13,49,35,86,0.0,0,93,Rural,Manager,35843,0 +85942,Female,58,Bachelors,4,81,46,11,24,6.0,6,24,Urban,Data Analyst,26283,0 +85943,Female,55,Bachelors,0,43,87,97,9,9.0,1,78,Semi-Urban,ML Engineer,126707,1 +85944,Male,26,Masters,2,14,76,75,28,2.0,7,54,Urban,HR Executive,48001,0 +85945,Male,26,Masters,11,48,92,94,64,9.0,2,39,Semi-Urban,Software Engineer,22091,1 +85946,Other,50,High School,14,35,34,56,63,3.0,3,86,Urban,Data Analyst,65453,0 +85947,Female,41,Masters,15,33,57,13,83,5.0,7,30,Urban,HR Executive,84922,0 +85948,Female,44,Bachelors,5,88,77,95,7,9.0,0,72,Urban,Manager,51115,1 +85949,Female,59,High School,15,23,81,60,46,6.0,7,29,Semi-Urban,HR Executive,92237,0 +85950,Male,54,Diploma,4,23,82,19,85,4.0,0,84,Semi-Urban,ML Engineer,112396,0 +85951,Other,59,Bachelors,16,62,25,47,89,6.0,7,27,Semi-Urban,ML Engineer,54874,0 +85952,Female,31,Masters,3,40,81,49,92,4.0,1,0,Urban,HR Executive,45652,0 +85953,Male,23,Bachelors,8,93,99,50,45,2.0,0,45,Semi-Urban,Software Engineer,114851,1 +85954,Female,49,Diploma,4,5,19,94,31,0.0,7,83,Semi-Urban,ML Engineer,99058,0 +85955,Female,53,High School,0,70,2,83,37,7.0,1,72,Urban,ML Engineer,141258,0 +85956,Male,35,PhD,6,91,0,49,14,4.0,0,8,Semi-Urban,ML Engineer,40609,0 +85957,Female,31,Bachelors,5,2,90,68,49,5.0,5,60,Urban,HR Executive,130200,0 +85958,Male,24,Masters,6,34,13,48,55,7.0,6,43,Urban,ML Engineer,103761,0 +85959,Female,57,Diploma,17,40,19,8,39,5.0,6,34,Semi-Urban,Manager,100146,0 +85960,Female,43,Diploma,5,1,41,36,88,5.0,7,44,Urban,HR Executive,53893,0 +85961,Female,28,Bachelors,4,27,64,23,90,3.0,5,85,Semi-Urban,Software Engineer,133323,0 +85962,Male,49,Masters,8,13,10,11,94,4.0,6,16,Rural,Data Analyst,57184,0 +85963,Female,45,Masters,12,4,17,32,20,0.0,5,93,Rural,Data Analyst,141243,0 +85964,Male,26,High School,5,71,76,92,45,0.0,5,53,Semi-Urban,ML Engineer,76051,1 +85965,Female,42,Masters,17,86,48,3,96,7.0,4,8,Urban,Manager,85023,0 +85966,Female,52,Bachelors,15,18,61,24,80,3.0,7,93,Urban,ML Engineer,133409,0 +85967,Male,42,High School,13,73,89,63,60,7.0,3,41,Urban,Data Analyst,75189,1 +85968,Male,23,Bachelors,1,19,94,76,43,7.0,5,81,Rural,ML Engineer,96677,1 +85969,Female,21,Masters,1,98,91,42,51,5.0,3,29,Urban,HR Executive,139822,1 +85970,Male,32,Masters,11,14,72,88,49,3.0,1,12,Semi-Urban,Data Analyst,89696,0 +85971,Male,50,High School,5,84,76,29,16,4.0,7,56,Urban,Manager,131296,1 +85972,Other,33,Bachelors,15,3,27,52,37,2.0,1,83,Semi-Urban,ML Engineer,90346,0 +85973,Female,53,Bachelors,9,22,43,59,4,7.0,4,46,Urban,ML Engineer,114794,0 +85974,Male,29,High School,18,56,46,76,37,6.0,1,50,Rural,Data Analyst,48858,0 +85975,Female,57,Masters,14,17,43,53,18,7.0,5,78,Rural,Data Analyst,87433,0 +85976,Male,48,Diploma,9,41,41,55,25,8.0,6,99,Urban,Data Analyst,82570,1 +85977,Female,39,High School,12,51,87,68,80,5.0,7,80,Semi-Urban,HR Executive,116739,1 +85978,Female,55,Masters,17,80,94,39,71,4.0,6,24,Rural,ML Engineer,68932,0 +85979,Male,45,Bachelors,18,88,92,54,24,1.0,1,96,Rural,HR Executive,105368,1 +85980,Male,52,High School,5,22,32,62,17,8.0,4,8,Rural,Software Engineer,60945,0 +85981,Male,53,High School,15,67,53,3,79,6.0,4,7,Semi-Urban,Manager,47331,0 +85982,Other,27,Masters,15,92,6,91,50,9.0,7,46,Urban,Data Analyst,46053,0 +85983,Male,38,Bachelors,7,20,85,98,45,3.0,3,33,Rural,Manager,54577,1 +85984,Male,34,Bachelors,16,15,33,43,43,0.0,3,45,Semi-Urban,Software Engineer,138375,0 +85985,Male,33,High School,5,35,51,29,87,7.0,5,24,Urban,HR Executive,69784,0 +85986,Male,47,Masters,4,33,93,63,87,5.0,0,44,Rural,Manager,78303,0 +85987,Female,50,Bachelors,14,53,98,27,79,1.0,3,82,Rural,Manager,143655,1 +85988,Female,50,Diploma,2,14,80,77,96,4.0,0,11,Urban,Manager,107557,0 +85989,Male,42,Diploma,5,85,46,59,37,3.0,3,53,Rural,Manager,74439,1 +85990,Male,48,PhD,15,86,15,56,7,3.0,3,97,Urban,HR Executive,97228,1 +85991,Male,29,High School,12,24,55,66,1,1.0,6,71,Urban,Software Engineer,39908,0 +85992,Male,44,Bachelors,1,24,0,38,54,9.0,0,84,Semi-Urban,HR Executive,81565,0 +85993,Male,47,Bachelors,4,12,75,96,73,5.0,1,63,Urban,HR Executive,34376,1 +85994,Female,26,Masters,14,78,32,26,19,1.0,2,18,Semi-Urban,Software Engineer,114950,0 +85995,Female,24,Bachelors,3,32,15,54,37,5.0,0,50,Urban,Data Analyst,20741,0 +85996,Male,40,Masters,12,75,63,28,29,8.0,3,7,Rural,Software Engineer,117989,0 +85997,Male,24,Masters,0,63,0,36,72,7.0,4,39,Semi-Urban,ML Engineer,148900,0 +85998,Male,23,Masters,17,98,38,21,64,2.0,4,74,Rural,Manager,75753,0 +85999,Female,27,Bachelors,8,2,19,80,97,1.0,3,14,Semi-Urban,HR Executive,29814,0 +86000,Female,57,High School,18,80,28,22,32,6.0,5,24,Urban,Data Analyst,108599,0 +86001,Female,49,Diploma,17,27,67,6,14,2.0,4,4,Urban,Manager,147057,0 +86002,Female,36,Masters,19,42,29,89,41,7.0,6,85,Urban,Manager,39942,1 +86003,Female,32,Diploma,7,8,63,3,25,3.0,1,11,Urban,Data Analyst,109840,0 +86004,Female,52,Bachelors,12,25,37,94,13,0.0,2,65,Urban,Manager,117320,0 +86005,Male,48,High School,16,15,11,93,66,8.0,0,78,Urban,Manager,108753,0 +86006,Female,54,Diploma,6,63,40,95,15,6.0,0,85,Semi-Urban,Software Engineer,38256,1 +86007,Male,40,Bachelors,13,30,90,56,76,4.0,6,22,Semi-Urban,Manager,139129,0 +86008,Female,54,Bachelors,14,30,73,25,24,8.0,3,0,Rural,Software Engineer,94550,0 +86009,Female,25,Bachelors,3,63,73,32,78,2.0,5,55,Urban,HR Executive,31790,0 +86010,Female,32,Bachelors,10,71,39,75,89,4.0,7,37,Urban,Manager,145564,0 +86011,Female,47,Masters,17,56,69,23,78,1.0,3,38,Urban,ML Engineer,37711,0 +86012,Male,42,Bachelors,0,58,52,57,31,2.0,4,74,Rural,Data Analyst,93499,1 +86013,Male,51,Bachelors,6,30,52,73,98,6.0,4,74,Semi-Urban,Software Engineer,29890,0 +86014,Male,45,Masters,7,79,78,25,96,6.0,5,39,Urban,ML Engineer,55686,0 +86015,Male,41,Bachelors,8,25,85,84,68,2.0,3,38,Semi-Urban,Software Engineer,120361,0 +86016,Female,22,Bachelors,19,71,73,65,98,3.0,7,22,Urban,Data Analyst,29567,0 +86017,Male,51,High School,3,50,16,94,42,6.0,5,46,Urban,Manager,41676,0 +86018,Female,25,Bachelors,14,21,87,35,33,2.0,3,51,Semi-Urban,HR Executive,72070,0 +86019,Female,35,Diploma,16,82,40,57,30,0.0,4,35,Urban,Data Analyst,44963,0 +86020,Male,36,Bachelors,15,40,98,63,47,4.0,6,98,Semi-Urban,Software Engineer,143586,1 +86021,Female,32,Bachelors,4,57,36,90,31,5.0,5,83,Semi-Urban,ML Engineer,62848,1 +86022,Female,47,Bachelors,7,29,94,13,76,6.0,1,49,Rural,Manager,102559,0 +86023,Male,49,Masters,13,79,84,68,75,2.0,1,27,Urban,Software Engineer,57341,1 +86024,Female,23,Bachelors,4,4,99,49,36,5.0,3,1,Urban,Software Engineer,99648,0 +86025,Female,48,Masters,15,60,15,74,29,9.0,6,19,Urban,Data Analyst,82634,0 +86026,Male,34,Diploma,17,85,66,57,75,3.0,1,39,Urban,Manager,131004,1 +86027,Female,39,High School,5,5,31,0,72,0.0,6,66,Semi-Urban,Manager,44627,0 +86028,Female,21,Bachelors,0,54,4,56,78,3.0,6,3,Rural,ML Engineer,51340,0 +86029,Male,37,Diploma,15,15,78,48,86,8.0,2,92,Rural,Software Engineer,89992,0 +86030,Female,55,Bachelors,7,94,56,57,93,9.0,5,29,Urban,Software Engineer,63652,0 +86031,Male,55,Bachelors,16,42,73,78,72,5.0,2,77,Semi-Urban,Software Engineer,142438,1 +86032,Male,50,High School,10,67,78,54,81,8.0,5,89,Urban,Software Engineer,129302,1 +86033,Male,28,Bachelors,15,63,30,8,48,0.0,2,68,Urban,Data Analyst,66828,0 +86034,Female,36,Diploma,14,30,36,31,53,0.0,1,76,Urban,Software Engineer,112413,0 +86035,Male,31,Bachelors,1,97,38,74,4,0.0,7,43,Urban,ML Engineer,38030,1 +86036,Male,32,Masters,18,93,87,42,35,1.0,0,8,Urban,Software Engineer,73624,0 +86037,Male,29,PhD,17,11,54,17,15,0.0,0,7,Semi-Urban,Software Engineer,36588,0 +86038,Female,22,Masters,8,95,34,18,8,5.0,4,10,Rural,Software Engineer,123408,0 +86039,Female,29,Masters,17,71,61,51,32,7.0,0,38,Urban,Software Engineer,32101,0 +86040,Male,41,High School,7,11,39,22,14,6.0,7,8,Urban,Software Engineer,65429,0 +86041,Male,44,Diploma,15,83,79,1,86,1.0,6,3,Urban,HR Executive,132736,0 +86042,Female,25,Bachelors,13,62,22,4,9,4.0,2,11,Rural,Data Analyst,139629,0 +86043,Male,25,Masters,15,72,14,63,59,1.0,4,38,Urban,ML Engineer,128250,0 +86044,Male,57,Bachelors,15,53,19,21,32,2.0,1,55,Semi-Urban,Manager,97862,0 +86045,Female,42,Masters,12,25,75,38,28,2.0,1,58,Urban,Data Analyst,78466,0 +86046,Female,47,Bachelors,1,56,72,65,99,6.0,5,93,Urban,ML Engineer,137736,1 +86047,Male,43,Bachelors,14,58,54,70,94,1.0,4,79,Semi-Urban,HR Executive,39641,1 +86048,Female,51,Masters,7,62,15,10,73,6.0,3,18,Urban,Data Analyst,137965,0 +86049,Male,47,Masters,15,50,80,35,89,1.0,1,11,Rural,Software Engineer,23840,0 +86050,Male,49,Bachelors,15,85,25,61,64,1.0,7,77,Urban,Software Engineer,124414,1 +86051,Male,40,Bachelors,8,39,56,10,87,8.0,2,94,Urban,ML Engineer,126546,0 +86052,Male,55,Diploma,7,97,39,25,53,8.0,2,22,Urban,ML Engineer,133238,0 +86053,Female,37,Masters,1,67,13,85,45,2.0,2,83,Urban,Data Analyst,66690,1 +86054,Female,36,Diploma,18,74,25,16,74,7.0,2,71,Semi-Urban,Software Engineer,33465,0 +86055,Male,29,Bachelors,11,82,22,46,90,9.0,3,63,Semi-Urban,Data Analyst,83964,0 +86056,Male,25,High School,9,23,87,2,70,1.0,3,51,Semi-Urban,HR Executive,86056,0 +86057,Female,37,Diploma,3,33,55,11,5,4.0,0,36,Rural,Manager,133349,0 +86058,Male,38,PhD,17,6,35,89,63,1.0,3,2,Urban,HR Executive,81001,0 +86059,Male,31,Bachelors,17,75,7,5,44,7.0,1,86,Urban,Software Engineer,75125,0 +86060,Female,30,Bachelors,5,53,11,38,50,5.0,4,40,Semi-Urban,HR Executive,41192,0 +86061,Female,58,Diploma,8,28,92,48,15,8.0,7,86,Semi-Urban,Software Engineer,146700,1 +86062,Male,56,High School,7,70,7,13,54,7.0,6,30,Rural,Software Engineer,84644,0 +86063,Male,58,PhD,15,36,50,64,99,7.0,4,41,Urban,Manager,51117,0 +86064,Male,49,Diploma,17,14,11,16,72,3.0,2,28,Urban,Manager,121703,0 +86065,Male,36,Diploma,18,80,64,16,71,2.0,3,92,Urban,HR Executive,113038,1 +86066,Male,48,Masters,18,42,64,33,32,8.0,5,21,Urban,HR Executive,132086,0 +86067,Male,35,Bachelors,7,87,94,36,4,8.0,7,82,Urban,Data Analyst,84200,1 +86068,Female,38,Diploma,1,66,46,74,55,8.0,2,76,Semi-Urban,Manager,146056,1 +86069,Male,56,Bachelors,17,18,1,88,24,8.0,1,58,Urban,Manager,117537,0 +86070,Female,56,PhD,11,91,17,12,20,9.0,1,39,Urban,Software Engineer,33786,0 +86071,Male,39,Bachelors,4,89,4,78,13,5.0,2,5,Urban,HR Executive,142080,0 +86072,Male,36,Diploma,1,99,17,30,51,4.0,6,29,Urban,ML Engineer,119106,0 +86073,Male,34,Bachelors,9,52,82,75,5,0.0,3,55,Urban,Data Analyst,21316,1 +86074,Female,56,Bachelors,17,26,50,13,81,2.0,0,72,Urban,HR Executive,108981,0 +86075,Other,25,Bachelors,3,81,64,42,4,7.0,1,96,Semi-Urban,Manager,26543,1 +86076,Male,24,Masters,15,60,39,19,4,7.0,4,77,Semi-Urban,Data Analyst,94480,0 +86077,Male,35,Bachelors,19,63,61,80,42,6.0,5,78,Urban,HR Executive,128077,1 +86078,Male,42,Diploma,10,83,4,88,12,2.0,0,4,Semi-Urban,Data Analyst,41271,0 +86079,Male,39,Diploma,3,41,56,57,95,2.0,6,53,Rural,Data Analyst,123650,0 +86080,Other,47,High School,12,49,41,51,81,8.0,0,3,Urban,ML Engineer,135202,0 +86081,Other,36,Bachelors,17,59,21,96,88,1.0,7,35,Urban,Software Engineer,23971,0 +86082,Male,33,Bachelors,16,40,9,16,8,3.0,5,94,Rural,ML Engineer,144984,0 +86083,Female,31,Bachelors,15,20,62,20,42,1.0,0,56,Urban,Data Analyst,25875,0 +86084,Male,57,Diploma,16,48,65,90,77,3.0,4,13,Urban,Data Analyst,118776,0 +86085,Female,47,Diploma,12,88,70,13,20,5.0,4,16,Urban,HR Executive,23540,0 +86086,Female,37,High School,3,17,91,6,20,4.0,5,94,Semi-Urban,Data Analyst,75758,0 +86087,Male,42,Bachelors,1,29,12,69,15,0.0,5,86,Semi-Urban,Software Engineer,63534,0 +86088,Male,48,Diploma,17,83,78,24,46,9.0,5,57,Semi-Urban,HR Executive,134577,1 +86089,Male,21,Bachelors,13,98,57,19,90,9.0,5,88,Rural,Software Engineer,43064,1 +86090,Male,30,Masters,12,18,7,35,33,4.0,4,4,Rural,Manager,20372,0 +86091,Male,35,Diploma,6,47,39,5,95,2.0,2,9,Urban,Data Analyst,73392,0 +86092,Female,34,Bachelors,15,83,80,69,77,2.0,2,14,Urban,ML Engineer,97246,1 +86093,Male,42,Diploma,18,4,86,21,57,6.0,1,73,Semi-Urban,Data Analyst,36597,0 +86094,Male,26,High School,19,8,95,13,70,4.0,5,17,Semi-Urban,ML Engineer,22504,0 +86095,Male,34,Bachelors,16,90,34,88,11,2.0,6,94,Urban,ML Engineer,99320,1 +86096,Other,57,Masters,15,8,37,21,78,4.0,6,8,Rural,HR Executive,139260,0 +86097,Male,49,Bachelors,10,38,66,34,99,7.0,2,43,Urban,ML Engineer,86831,0 +86098,Female,27,PhD,5,22,58,26,23,6.0,7,83,Urban,Manager,33046,0 +86099,Female,21,Diploma,1,41,7,97,54,6.0,7,77,Semi-Urban,Software Engineer,130322,0 +86100,Female,33,PhD,6,69,3,4,47,0.0,1,86,Urban,ML Engineer,95805,0 +86101,Male,38,PhD,4,7,22,87,43,4.0,2,53,Rural,Software Engineer,46104,0 +86102,Male,40,Bachelors,19,78,19,21,37,2.0,3,74,Urban,Software Engineer,122838,0 +86103,Female,53,Bachelors,2,88,86,12,92,1.0,6,53,Rural,Manager,65598,0 +86104,Female,32,Masters,15,90,35,40,16,1.0,7,9,Urban,Software Engineer,43415,0 +86105,Other,26,Diploma,1,13,22,17,85,3.0,3,79,Rural,Data Analyst,46275,0 +86106,Male,24,Masters,5,3,1,43,10,6.0,2,56,Rural,HR Executive,43387,0 +86107,Male,54,Masters,8,72,0,50,94,0.0,3,25,Urban,ML Engineer,118417,0 +86108,Male,57,Bachelors,15,87,67,75,67,6.0,7,36,Rural,Data Analyst,58421,1 +86109,Female,32,High School,19,48,59,74,7,7.0,6,54,Semi-Urban,Data Analyst,97760,0 +86110,Male,47,Bachelors,10,90,49,41,47,5.0,0,97,Rural,HR Executive,111221,1 +86111,Male,33,Bachelors,12,55,5,2,1,0.0,6,46,Semi-Urban,Manager,135178,0 +86112,Male,58,High School,0,13,53,3,16,8.0,3,14,Rural,ML Engineer,48294,0 +86113,Female,28,Bachelors,11,23,30,26,80,6.0,2,51,Urban,HR Executive,63962,0 +86114,Male,45,Bachelors,6,24,46,6,26,8.0,0,84,Rural,ML Engineer,46577,0 +86115,Female,47,Bachelors,4,12,72,33,29,0.0,4,27,Urban,Data Analyst,138170,0 +86116,Male,53,Masters,3,69,85,22,97,0.0,2,74,Urban,Software Engineer,116334,1 +86117,Male,43,Bachelors,12,26,40,23,80,7.0,3,56,Urban,Manager,63438,0 +86118,Male,51,High School,14,97,45,21,92,5.0,3,41,Rural,Manager,118499,0 +86119,Female,51,Bachelors,6,57,40,39,98,0.0,7,33,Rural,Manager,42726,0 +86120,Male,54,Bachelors,8,35,13,9,68,7.0,3,41,Rural,HR Executive,20918,0 +86121,Female,32,Bachelors,16,47,28,77,51,4.0,5,28,Rural,Software Engineer,29920,0 +86122,Other,59,Masters,12,21,31,76,12,1.0,3,69,Semi-Urban,Manager,56603,0 +86123,Male,22,High School,5,88,63,29,98,8.0,3,23,Urban,Manager,144827,0 +86124,Female,22,Masters,16,33,78,21,9,6.0,7,80,Urban,Manager,41884,0 +86125,Female,35,Masters,8,27,41,76,12,4.0,5,52,Urban,Software Engineer,66957,0 +86126,Male,56,Bachelors,5,43,29,53,19,0.0,1,69,Urban,Manager,30580,0 +86127,Male,52,Bachelors,13,41,12,70,78,5.0,0,32,Urban,Software Engineer,121888,0 +86128,Female,41,Bachelors,16,34,66,3,98,5.0,2,59,Urban,HR Executive,117063,0 +86129,Male,42,Bachelors,10,84,48,24,55,4.0,3,34,Urban,Manager,71919,0 +86130,Male,55,High School,1,11,57,37,42,7.0,2,95,Rural,ML Engineer,32694,0 +86131,Female,53,Bachelors,5,85,25,41,42,3.0,4,34,Urban,Manager,71825,0 +86132,Male,41,Bachelors,19,32,72,44,1,8.0,5,88,Urban,HR Executive,127276,1 +86133,Male,21,High School,16,23,52,33,96,8.0,3,58,Urban,HR Executive,81567,0 +86134,Female,57,Bachelors,1,61,90,10,17,6.0,7,98,Urban,ML Engineer,23732,1 +86135,Male,45,Masters,5,59,90,28,31,2.0,1,12,Urban,HR Executive,89049,0 +86136,Male,26,Diploma,19,60,67,15,52,1.0,2,29,Semi-Urban,Manager,34613,0 +86137,Male,25,Diploma,4,17,98,79,9,3.0,2,5,Urban,Data Analyst,149185,0 +86138,Male,50,Bachelors,19,85,70,48,0,7.0,0,48,Semi-Urban,ML Engineer,133439,1 +86139,Other,58,Bachelors,15,97,54,0,2,5.0,6,27,Semi-Urban,Manager,76980,0 +86140,Female,28,Bachelors,6,99,38,81,23,2.0,2,52,Urban,ML Engineer,125914,1 +86141,Female,48,Bachelors,14,40,21,52,10,8.0,1,53,Urban,Software Engineer,127144,0 +86142,Female,30,Diploma,1,85,19,98,69,6.0,6,72,Rural,ML Engineer,112170,1 +86143,Female,44,Diploma,13,41,42,12,26,1.0,0,57,Urban,Manager,42681,0 +86144,Female,48,Bachelors,9,46,68,56,72,2.0,1,14,Urban,HR Executive,118815,0 +86145,Female,33,High School,17,68,98,24,45,4.0,3,18,Urban,Manager,75674,0 +86146,Male,43,Bachelors,7,61,38,18,26,6.0,2,56,Urban,ML Engineer,105465,0 +86147,Male,24,Bachelors,4,92,83,29,56,9.0,4,2,Urban,Data Analyst,31309,0 +86148,Male,48,Diploma,16,6,88,89,10,4.0,1,26,Urban,Software Engineer,44880,0 +86149,Male,22,High School,11,27,90,90,52,1.0,2,0,Semi-Urban,HR Executive,81794,0 +86150,Other,39,Masters,0,98,41,53,12,7.0,3,13,Urban,ML Engineer,96248,0 +86151,Female,26,Masters,1,24,21,85,71,8.0,0,93,Rural,HR Executive,98513,0 +86152,Male,45,Bachelors,1,72,43,98,66,0.0,3,5,Urban,Software Engineer,101364,0 +86153,Male,48,Masters,8,93,69,16,51,5.0,5,48,Urban,Data Analyst,105293,0 +86154,Other,59,Bachelors,18,33,53,27,34,0.0,1,45,Urban,Manager,82906,0 +86155,Female,45,Diploma,18,58,95,62,87,9.0,1,65,Urban,Software Engineer,29523,1 +86156,Male,21,Bachelors,19,15,85,39,97,7.0,6,63,Urban,Data Analyst,35163,0 +86157,Male,42,High School,1,79,33,63,82,9.0,1,39,Urban,HR Executive,126055,0 +86158,Male,32,High School,0,46,75,35,44,9.0,6,73,Semi-Urban,HR Executive,75742,0 +86159,Female,34,Bachelors,2,82,12,30,99,1.0,1,68,Urban,Software Engineer,87714,0 +86160,Female,54,High School,4,53,80,69,11,1.0,1,97,Urban,Manager,21266,1 +86161,Male,59,Bachelors,6,34,27,66,17,1.0,4,37,Semi-Urban,HR Executive,88459,0 +86162,Male,35,Diploma,0,90,81,2,78,9.0,1,57,Semi-Urban,Software Engineer,115787,0 +86163,Male,26,Bachelors,10,65,96,2,16,6.0,2,1,Semi-Urban,Software Engineer,103395,0 +86164,Female,52,Bachelors,3,2,36,81,48,5.0,5,78,Urban,Manager,23401,0 +86165,Female,29,Masters,1,9,69,93,47,3.0,4,72,Urban,Software Engineer,118292,1 +86166,Female,30,Bachelors,14,47,7,97,34,3.0,4,49,Urban,ML Engineer,112702,0 +86167,Female,56,Masters,10,90,39,67,44,3.0,7,43,Urban,Data Analyst,101210,0 +86168,Female,31,Masters,16,57,34,68,76,5.0,6,53,Rural,Data Analyst,49517,0 +86169,Male,43,High School,4,6,59,9,16,5.0,2,18,Urban,Manager,83290,0 +86170,Male,31,PhD,3,24,38,84,73,9.0,7,75,Urban,ML Engineer,87474,0 +86171,Male,51,Masters,2,72,74,87,19,2.0,0,91,Urban,HR Executive,139334,1 +86172,Male,41,Masters,4,5,10,67,62,5.0,2,65,Urban,HR Executive,104236,0 +86173,Other,45,Bachelors,9,0,30,34,82,6.0,6,5,Urban,Software Engineer,76699,0 +86174,Female,52,Masters,4,64,52,43,20,2.0,2,36,Urban,ML Engineer,120112,0 +86175,Male,47,High School,5,0,57,77,89,1.0,4,46,Rural,Software Engineer,76941,0 +86176,Male,44,Bachelors,9,2,24,86,95,3.0,5,38,Semi-Urban,HR Executive,113772,0 +86177,Male,58,Bachelors,19,20,33,42,25,2.0,7,17,Urban,ML Engineer,40675,0 +86178,Female,57,Bachelors,8,61,70,22,24,4.0,2,64,Urban,Manager,61509,0 +86179,Male,24,Bachelors,15,49,18,11,46,8.0,5,70,Rural,ML Engineer,86434,0 +86180,Male,56,Masters,16,88,38,47,98,7.0,5,38,Urban,HR Executive,43196,0 +86181,Female,30,Masters,7,18,37,44,85,3.0,2,91,Urban,Data Analyst,47885,0 +86182,Female,34,Diploma,13,99,4,48,49,0.0,1,78,Semi-Urban,HR Executive,87380,0 +86183,Male,49,Diploma,9,98,19,46,8,6.0,4,55,Rural,HR Executive,82472,0 +86184,Male,37,Bachelors,15,98,77,41,31,1.0,0,45,Urban,Manager,23359,1 +86185,Male,30,Bachelors,5,59,79,2,7,2.0,0,30,Urban,Manager,103211,0 +86186,Female,57,High School,17,86,1,29,93,6.0,6,18,Urban,ML Engineer,71451,0 +86187,Male,32,Diploma,2,24,63,73,55,8.0,4,67,Urban,ML Engineer,66470,0 +86188,Male,37,PhD,11,71,50,0,77,7.0,0,79,Semi-Urban,Software Engineer,57636,0 +86189,Female,53,Diploma,15,35,70,74,80,3.0,3,57,Urban,HR Executive,136377,0 +86190,Male,43,Masters,14,60,23,67,41,8.0,1,1,Urban,Software Engineer,102337,0 +86191,Male,50,High School,16,51,22,63,63,9.0,7,34,Semi-Urban,Data Analyst,90316,0 +86192,Female,23,Bachelors,10,56,65,67,54,6.0,2,7,Urban,HR Executive,79963,0 +86193,Female,54,High School,8,61,59,83,29,0.0,5,28,Urban,Data Analyst,121809,0 +86194,Female,37,Masters,9,17,95,80,13,3.0,3,1,Urban,ML Engineer,97609,0 +86195,Male,33,Bachelors,4,6,15,56,33,9.0,0,51,Semi-Urban,Software Engineer,111326,0 +86196,Female,22,Masters,17,24,37,80,85,9.0,6,41,Urban,ML Engineer,73010,0 +86197,Male,41,Bachelors,15,7,96,38,18,0.0,3,30,Urban,ML Engineer,52811,0 +86198,Male,30,Bachelors,15,35,98,46,99,2.0,3,39,Urban,Data Analyst,123334,0 +86199,Male,27,PhD,18,45,45,43,83,7.0,7,2,Semi-Urban,Software Engineer,63642,0 +86200,Female,45,Bachelors,12,26,71,85,12,4.0,0,10,Rural,Manager,100089,0 +86201,Other,47,Bachelors,4,20,48,78,6,3.0,6,87,Urban,Data Analyst,118275,0 +86202,Female,48,High School,18,65,20,32,25,0.0,0,21,Urban,Software Engineer,49635,0 +86203,Other,40,Bachelors,6,75,17,41,12,6.0,7,9,Rural,Manager,136075,0 +86204,Male,54,PhD,11,68,21,13,81,6.0,0,9,Semi-Urban,HR Executive,108444,0 +86205,Male,23,High School,1,28,10,65,2,7.0,0,90,Urban,HR Executive,98305,0 +86206,Male,26,Masters,17,14,16,17,44,4.0,1,32,Rural,HR Executive,82351,0 +86207,Male,39,Diploma,9,63,72,81,50,8.0,4,32,Urban,Manager,43057,1 +86208,Female,56,High School,1,52,74,17,40,3.0,0,89,Urban,HR Executive,94436,0 +86209,Male,42,Diploma,13,58,12,19,55,8.0,5,25,Semi-Urban,Manager,124604,0 +86210,Male,38,High School,19,0,59,22,41,4.0,5,86,Urban,Software Engineer,43003,0 +86211,Female,51,High School,19,68,32,72,25,7.0,4,15,Semi-Urban,Manager,57419,0 +86212,Male,55,PhD,10,20,86,19,55,3.0,5,38,Semi-Urban,ML Engineer,29981,0 +86213,Male,50,PhD,13,77,67,10,30,8.0,1,65,Rural,HR Executive,40292,0 +86214,Male,28,Diploma,5,9,80,8,94,6.0,6,45,Rural,ML Engineer,59296,0 +86215,Female,26,Diploma,13,23,59,8,22,5.0,4,53,Urban,Data Analyst,131112,0 +86216,Female,26,Bachelors,11,74,43,33,29,7.0,6,79,Rural,ML Engineer,22349,0 +86217,Female,52,Bachelors,13,4,72,28,51,0.0,0,96,Urban,HR Executive,96921,0 +86218,Male,26,Bachelors,17,30,99,52,66,8.0,3,65,Semi-Urban,Manager,130260,1 +86219,Male,43,Bachelors,12,24,19,27,35,1.0,6,97,Urban,HR Executive,88786,0 +86220,Male,25,Diploma,14,13,14,90,46,0.0,0,35,Rural,Software Engineer,77443,0 +86221,Male,25,Bachelors,9,14,84,36,57,7.0,6,75,Rural,Manager,82570,0 +86222,Female,22,Bachelors,12,5,46,13,41,9.0,0,51,Urban,Data Analyst,76630,0 +86223,Male,25,Masters,17,7,90,4,52,7.0,7,3,Rural,ML Engineer,63899,0 +86224,Male,56,High School,0,91,88,45,70,1.0,7,34,Rural,Software Engineer,38146,1 +86225,Male,23,Masters,19,44,85,20,47,7.0,7,92,Urban,ML Engineer,146332,1 +86226,Male,52,High School,16,10,77,16,66,9.0,6,0,Urban,Software Engineer,126867,0 +86227,Male,34,Diploma,9,5,81,79,66,8.0,2,15,Semi-Urban,Manager,137331,0 +86228,Male,35,Diploma,14,23,27,63,65,2.0,1,39,Semi-Urban,HR Executive,112656,0 +86229,Female,29,Diploma,9,69,21,15,30,5.0,5,74,Semi-Urban,ML Engineer,85041,0 +86230,Male,54,Masters,15,98,27,28,70,2.0,0,26,Semi-Urban,Software Engineer,87348,0 +86231,Male,55,Bachelors,18,91,1,36,35,9.0,2,64,Rural,Manager,40234,0 +86232,Male,26,Diploma,8,51,27,64,54,5.0,6,49,Urban,Data Analyst,77130,0 +86233,Female,48,High School,3,15,71,57,69,3.0,2,35,Urban,Software Engineer,122529,0 +86234,Female,58,Masters,10,8,97,26,76,9.0,3,52,Urban,HR Executive,103022,0 +86235,Male,54,Masters,3,41,50,87,27,0.0,6,43,Urban,HR Executive,99967,0 +86236,Male,43,Bachelors,0,45,12,77,97,4.0,2,24,Semi-Urban,Software Engineer,99756,0 +86237,Female,23,High School,14,43,91,92,27,0.0,2,92,Rural,HR Executive,68872,1 +86238,Male,25,High School,12,48,29,99,25,0.0,0,60,Semi-Urban,Data Analyst,88989,1 +86239,Male,44,Bachelors,14,82,50,62,73,0.0,3,50,Semi-Urban,HR Executive,20548,1 +86240,Male,37,Masters,0,36,4,79,25,9.0,5,94,Urban,HR Executive,27562,0 +86241,Female,53,Diploma,17,28,88,28,94,7.0,5,20,Rural,HR Executive,126099,0 +86242,Male,52,Bachelors,2,83,78,1,13,7.0,4,48,Semi-Urban,Data Analyst,29000,0 +86243,Male,37,High School,16,17,41,47,55,6.0,0,39,Rural,ML Engineer,65513,0 +86244,Female,45,Diploma,10,98,5,57,27,4.0,2,59,Urban,HR Executive,24950,0 +86245,Male,31,PhD,18,65,73,3,10,2.0,7,50,Urban,HR Executive,55417,0 +86246,Male,22,High School,19,98,77,9,49,2.0,3,89,Semi-Urban,HR Executive,66724,1 +86247,Female,56,Bachelors,14,25,52,36,93,1.0,1,35,Urban,HR Executive,86402,0 +86248,Male,27,High School,9,50,26,1,88,1.0,3,33,Urban,HR Executive,140220,0 +86249,Other,42,Diploma,15,62,19,47,76,3.0,1,82,Urban,Manager,85117,0 +86250,Female,43,PhD,6,73,46,61,29,5.0,7,63,Urban,Manager,141735,1 +86251,Female,46,Diploma,9,47,15,87,49,6.0,7,11,Urban,Software Engineer,68844,0 +86252,Male,34,Bachelors,18,60,30,4,55,7.0,2,57,Urban,HR Executive,22725,0 +86253,Male,40,Bachelors,11,88,5,58,19,9.0,0,86,Rural,HR Executive,116296,1 +86254,Male,26,Bachelors,0,59,19,40,37,9.0,0,37,Semi-Urban,Manager,130748,0 +86255,Male,21,Diploma,2,57,4,36,1,9.0,4,72,Semi-Urban,HR Executive,115612,0 +86256,Male,45,Bachelors,8,32,10,28,62,3.0,3,17,Rural,Software Engineer,92982,0 +86257,Male,49,Bachelors,4,83,52,53,76,3.0,2,49,Semi-Urban,Manager,78280,1 +86258,Male,46,Bachelors,2,82,91,95,71,0.0,3,75,Urban,Software Engineer,65702,1 +86259,Male,44,Bachelors,19,2,73,92,52,3.0,2,30,Urban,Data Analyst,124542,0 +86260,Female,39,High School,0,40,27,19,74,0.0,3,46,Urban,Manager,111306,0 +86261,Female,34,Bachelors,12,65,40,48,97,3.0,5,62,Urban,ML Engineer,111594,0 +86262,Male,59,Masters,0,98,28,63,97,6.0,2,37,Urban,HR Executive,88556,0 +86263,Female,26,High School,16,89,36,25,26,4.0,0,61,Rural,HR Executive,141919,0 +86264,Male,44,PhD,13,49,89,62,57,0.0,5,37,Urban,HR Executive,21776,1 +86265,Male,43,High School,11,24,76,20,52,8.0,5,13,Rural,Software Engineer,73661,0 +86266,Male,57,Bachelors,7,9,27,16,50,6.0,2,69,Urban,ML Engineer,122056,0 +86267,Female,32,High School,7,29,43,99,57,4.0,6,82,Semi-Urban,Software Engineer,137239,1 +86268,Female,28,PhD,17,1,60,37,21,0.0,6,93,Urban,Manager,135974,0 +86269,Male,51,Diploma,9,4,9,29,64,4.0,7,33,Semi-Urban,Manager,79649,0 +86270,Male,22,Bachelors,0,64,78,61,50,2.0,5,84,Urban,Manager,141255,1 +86271,Female,24,Bachelors,9,52,68,90,92,6.0,6,84,Rural,Software Engineer,30634,1 +86272,Male,45,Masters,9,84,86,10,34,3.0,1,34,Urban,Manager,122787,0 +86273,Male,55,Bachelors,17,37,52,41,23,1.0,3,71,Semi-Urban,Software Engineer,107074,0 +86274,Male,55,Diploma,4,48,92,8,4,6.0,4,67,Semi-Urban,HR Executive,120224,0 +86275,Male,31,PhD,14,25,58,22,85,0.0,2,1,Urban,Manager,120664,0 +86276,Male,40,Bachelors,16,96,77,86,20,1.0,7,10,Rural,Manager,79560,1 +86277,Male,43,Bachelors,12,86,35,21,28,9.0,6,97,Semi-Urban,Software Engineer,59710,1 +86278,Female,32,Diploma,8,25,58,45,19,8.0,1,51,Urban,Manager,139076,0 +86279,Other,22,High School,13,83,95,79,25,3.0,2,67,Semi-Urban,Software Engineer,88497,1 +86280,Female,47,Masters,0,94,49,69,53,5.0,7,21,Urban,HR Executive,80864,0 +86281,Male,56,High School,17,87,12,79,11,4.0,2,60,Urban,Manager,110729,1 +86282,Male,45,Masters,3,17,9,42,76,3.0,1,99,Urban,HR Executive,77170,0 +86283,Male,37,Masters,7,81,4,87,46,0.0,4,62,Urban,ML Engineer,47556,0 +86284,Male,26,Masters,16,7,11,73,85,6.0,2,58,Urban,Data Analyst,96074,0 +86285,Other,52,Diploma,8,45,83,99,70,9.0,5,54,Semi-Urban,Software Engineer,108585,1 +86286,Other,48,Bachelors,9,28,86,89,8,7.0,5,38,Urban,Manager,81639,1 +86287,Female,48,Bachelors,0,44,5,83,47,6.0,0,23,Urban,Data Analyst,111713,0 +86288,Female,45,Bachelors,15,79,4,20,63,5.0,0,22,Rural,ML Engineer,25067,0 +86289,Male,55,Diploma,11,22,70,22,13,6.0,6,6,Rural,Manager,63560,0 +86290,Female,43,Diploma,0,69,9,62,3,4.0,6,74,Rural,ML Engineer,99074,0 +86291,Male,23,Diploma,7,11,85,52,11,1.0,6,13,Urban,ML Engineer,47052,0 +86292,Female,42,High School,10,95,5,99,33,2.0,3,82,Semi-Urban,HR Executive,54818,1 +86293,Male,46,PhD,3,57,74,1,16,7.0,4,63,Urban,Software Engineer,90321,0 +86294,Female,35,Masters,14,23,88,18,85,9.0,2,82,Urban,Manager,122128,0 +86295,Female,58,Bachelors,0,6,6,33,52,8.0,7,36,Semi-Urban,Manager,71213,0 +86296,Male,48,Diploma,3,66,1,40,33,7.0,4,36,Rural,Manager,37452,0 +86297,Male,27,Bachelors,17,87,12,83,4,2.0,6,28,Urban,HR Executive,99691,0 +86298,Female,37,Bachelors,2,8,3,61,38,4.0,7,17,Urban,ML Engineer,115522,0 +86299,Other,56,Bachelors,14,61,11,11,21,5.0,6,5,Rural,HR Executive,98669,0 +86300,Female,58,Bachelors,19,6,19,38,10,8.0,1,40,Urban,ML Engineer,115300,0 +86301,Female,30,High School,2,33,75,46,36,9.0,3,6,Urban,HR Executive,133073,0 +86302,Female,47,Bachelors,19,72,38,65,54,3.0,0,34,Semi-Urban,HR Executive,69898,0 +86303,Other,38,Masters,5,65,2,5,72,4.0,7,71,Urban,HR Executive,68190,0 +86304,Male,45,Diploma,5,62,42,46,94,1.0,0,87,Urban,Data Analyst,40361,1 +86305,Male,26,Masters,14,18,88,43,89,4.0,4,4,Rural,HR Executive,28651,0 +86306,Female,34,Bachelors,5,36,63,8,83,2.0,0,17,Rural,Data Analyst,113180,0 +86307,Male,30,High School,3,30,17,19,62,1.0,5,68,Urban,Software Engineer,146362,0 +86308,Male,34,Bachelors,7,90,14,16,5,6.0,1,37,Rural,Data Analyst,133141,0 +86309,Male,56,Masters,13,56,81,1,57,3.0,5,39,Rural,Data Analyst,84787,0 +86310,Female,33,Bachelors,16,47,4,77,34,8.0,3,78,Rural,HR Executive,85269,0 +86311,Male,58,Diploma,2,69,60,71,12,0.0,0,22,Rural,Data Analyst,32791,0 +86312,Female,36,Bachelors,15,21,8,96,94,1.0,4,87,Urban,ML Engineer,70154,0 +86313,Female,41,Masters,10,80,46,80,45,6.0,2,4,Urban,Software Engineer,109621,0 +86314,Male,50,High School,0,33,45,22,69,1.0,6,86,Urban,Data Analyst,96548,0 +86315,Male,57,Bachelors,6,24,8,0,46,7.0,0,82,Urban,ML Engineer,66741,0 +86316,Female,39,High School,3,58,71,88,76,0.0,7,58,Urban,Software Engineer,149241,1 +86317,Male,37,Bachelors,16,67,26,72,20,9.0,5,44,Semi-Urban,Manager,26570,0 +86318,Male,42,PhD,13,87,46,64,82,6.0,1,66,Rural,Data Analyst,119314,1 +86319,Female,37,Diploma,5,28,91,27,92,5.0,2,59,Urban,Data Analyst,76765,0 +86320,Male,22,PhD,0,49,91,70,59,3.0,3,70,Semi-Urban,Manager,120610,1 +86321,Male,47,Bachelors,15,2,47,75,27,8.0,6,74,Rural,Data Analyst,61651,0 +86322,Female,23,High School,8,8,5,73,86,1.0,3,37,Semi-Urban,ML Engineer,64879,0 +86323,Male,24,Bachelors,18,9,43,25,5,8.0,7,88,Semi-Urban,HR Executive,81558,0 +86324,Other,25,Diploma,10,35,91,67,76,2.0,6,93,Urban,Data Analyst,22724,1 +86325,Male,46,Diploma,10,80,14,61,86,8.0,6,22,Rural,Data Analyst,86912,0 +86326,Male,23,Bachelors,10,4,54,31,63,8.0,0,32,Urban,Manager,43893,0 +86327,Female,39,Diploma,18,60,57,16,64,6.0,3,56,Rural,Data Analyst,90970,0 +86328,Male,27,Diploma,0,18,63,8,23,7.0,7,63,Urban,Manager,29511,0 +86329,Male,26,Bachelors,5,6,38,38,69,7.0,7,65,Urban,Software Engineer,134851,0 +86330,Female,24,Diploma,14,73,8,79,69,6.0,3,50,Semi-Urban,Data Analyst,143889,0 +86331,Female,54,Masters,19,78,30,33,41,5.0,0,79,Rural,Data Analyst,119507,0 +86332,Male,57,Bachelors,10,57,92,83,44,4.0,7,3,Rural,ML Engineer,33825,1 +86333,Male,43,Diploma,15,86,90,59,7,3.0,0,19,Urban,Data Analyst,89573,1 +86334,Male,55,Diploma,2,48,64,54,12,0.0,2,2,Urban,ML Engineer,69074,0 +86335,Female,35,PhD,16,39,27,86,67,3.0,5,39,Urban,HR Executive,63997,0 +86336,Male,50,Diploma,9,55,4,26,66,6.0,0,27,Rural,Data Analyst,122622,0 +86337,Male,50,Bachelors,15,80,41,72,92,6.0,0,55,Urban,Software Engineer,48286,1 +86338,Male,58,High School,18,41,78,6,1,1.0,5,86,Urban,HR Executive,52992,0 +86339,Male,41,Bachelors,1,71,22,33,48,0.0,0,79,Urban,HR Executive,22217,0 +86340,Male,36,Diploma,7,84,87,4,89,0.0,2,99,Urban,Manager,80148,1 +86341,Male,25,Bachelors,10,2,9,2,18,5.0,0,2,Urban,Software Engineer,100258,0 +86342,Male,22,Bachelors,9,14,79,78,60,8.0,0,6,Rural,Manager,26014,0 +86343,Female,39,Diploma,18,3,66,90,94,2.0,0,23,Urban,Manager,95713,0 +86344,Male,27,High School,13,76,21,65,13,5.0,2,20,Urban,Software Engineer,21766,0 +86345,Female,54,Diploma,12,0,77,26,1,7.0,7,34,Urban,Manager,81484,0 +86346,Male,23,Bachelors,3,88,20,40,61,2.0,0,71,Urban,HR Executive,65155,0 +86347,Female,38,Diploma,7,95,50,93,51,2.0,3,22,Semi-Urban,ML Engineer,118561,1 +86348,Male,31,Bachelors,11,61,62,39,10,9.0,1,0,Rural,HR Executive,108006,0 +86349,Other,49,High School,18,40,45,19,42,8.0,0,60,Urban,Software Engineer,137498,0 +86350,Male,28,Diploma,9,96,44,18,49,4.0,4,62,Semi-Urban,Data Analyst,59211,0 +86351,Male,39,High School,14,82,68,77,91,0.0,4,74,Urban,Software Engineer,145467,1 +86352,Female,59,Bachelors,12,44,82,66,71,1.0,3,31,Urban,Manager,57641,0 +86353,Male,50,PhD,2,40,89,64,76,1.0,6,8,Semi-Urban,Data Analyst,72941,0 +86354,Female,39,High School,6,34,46,28,37,5.0,4,16,Urban,Manager,65621,0 +86355,Male,59,Bachelors,5,83,78,34,80,4.0,1,64,Semi-Urban,Manager,126685,1 +86356,Male,24,Bachelors,5,33,15,11,94,1.0,1,67,Rural,Data Analyst,32465,0 +86357,Male,59,High School,12,99,43,42,14,0.0,2,84,Semi-Urban,HR Executive,85262,1 +86358,Male,27,Bachelors,19,5,97,23,78,9.0,1,89,Urban,ML Engineer,49453,0 +86359,Male,43,Diploma,14,86,48,19,19,5.0,0,26,Urban,Data Analyst,136635,0 +86360,Male,48,Bachelors,7,64,97,79,30,5.0,0,34,Urban,Software Engineer,87766,1 +86361,Female,39,Diploma,12,93,48,97,12,6.0,7,76,Semi-Urban,HR Executive,86993,1 +86362,Male,41,Bachelors,14,78,95,65,9,8.0,0,52,Urban,Data Analyst,69829,1 +86363,Female,25,Diploma,7,88,41,75,56,4.0,5,28,Semi-Urban,Software Engineer,89863,0 +86364,Male,55,Masters,0,83,22,5,53,3.0,5,3,Urban,ML Engineer,143933,0 +86365,Female,21,High School,18,65,44,76,86,3.0,4,56,Urban,Software Engineer,144263,1 +86366,Male,34,High School,1,94,87,57,95,1.0,7,83,Urban,Manager,122483,1 +86367,Male,43,Diploma,17,2,51,32,85,9.0,5,0,Urban,HR Executive,40992,0 +86368,Male,34,High School,0,42,9,90,84,1.0,3,46,Rural,Manager,134506,0 +86369,Female,47,Masters,1,34,16,91,3,3.0,5,62,Urban,Software Engineer,90816,0 +86370,Male,57,Masters,11,65,98,50,76,4.0,2,71,Semi-Urban,Manager,28643,1 +86371,Male,45,Bachelors,7,8,94,88,5,8.0,4,45,Urban,HR Executive,73510,1 +86372,Female,56,Diploma,18,81,3,44,89,8.0,0,21,Urban,Manager,49051,0 +86373,Male,56,Diploma,10,99,54,18,3,7.0,3,19,Urban,ML Engineer,141887,0 +86374,Male,41,High School,10,14,17,64,16,9.0,6,9,Semi-Urban,Manager,59605,0 +86375,Female,28,High School,12,11,70,71,20,5.0,6,8,Urban,Manager,102401,0 +86376,Male,34,Bachelors,2,6,65,7,8,9.0,0,81,Urban,Data Analyst,136287,0 +86377,Male,56,Bachelors,8,33,14,47,79,9.0,1,76,Rural,Software Engineer,148289,0 +86378,Male,40,Diploma,0,86,32,30,63,7.0,6,75,Urban,Software Engineer,100059,0 +86379,Female,56,Bachelors,11,49,30,39,91,6.0,7,34,Semi-Urban,ML Engineer,27433,0 +86380,Male,49,Bachelors,2,37,28,40,3,7.0,1,4,Urban,Software Engineer,85917,0 +86381,Male,21,Bachelors,0,3,63,23,51,6.0,1,25,Urban,ML Engineer,142798,0 +86382,Other,56,High School,0,59,74,65,67,4.0,4,14,Urban,ML Engineer,39133,0 +86383,Male,45,Bachelors,18,82,5,45,69,3.0,3,15,Urban,HR Executive,47100,0 +86384,Male,32,Masters,13,24,82,66,23,7.0,2,21,Rural,Software Engineer,20607,0 +86385,Male,43,Diploma,5,7,34,87,40,4.0,4,5,Semi-Urban,HR Executive,108430,0 +86386,Male,41,Bachelors,8,21,76,3,28,5.0,7,97,Rural,HR Executive,44224,0 +86387,Male,42,Bachelors,19,96,48,34,79,5.0,4,34,Urban,Data Analyst,125400,0 +86388,Female,21,Diploma,12,11,69,91,11,3.0,4,33,Semi-Urban,Data Analyst,47821,0 +86389,Male,34,Bachelors,2,71,52,29,29,8.0,2,67,Semi-Urban,ML Engineer,147973,0 +86390,Female,46,High School,6,84,44,3,84,3.0,0,88,Semi-Urban,ML Engineer,95108,0 +86391,Male,51,High School,18,70,26,38,47,5.0,5,59,Urban,HR Executive,80914,0 +86392,Male,48,Diploma,11,96,41,50,7,4.0,2,55,Rural,ML Engineer,115975,1 +86393,Female,40,Diploma,13,56,77,21,47,5.0,6,46,Urban,Manager,63199,0 +86394,Male,34,Masters,17,18,1,24,24,5.0,2,69,Urban,Software Engineer,78964,0 +86395,Male,48,Masters,6,2,21,57,77,7.0,3,89,Semi-Urban,Manager,35732,0 +86396,Other,58,Bachelors,12,10,30,76,57,6.0,6,25,Urban,Manager,42581,0 +86397,Male,59,Masters,2,58,30,39,86,3.0,6,9,Urban,ML Engineer,58256,0 +86398,Female,59,Bachelors,12,15,49,90,61,4.0,1,42,Urban,Manager,23166,0 +86399,Female,35,Bachelors,14,39,95,81,45,6.0,6,97,Urban,HR Executive,46479,1 +86400,Male,50,Bachelors,3,2,56,26,44,3.0,2,98,Semi-Urban,ML Engineer,144627,0 +86401,Female,23,Diploma,9,5,86,20,43,0.0,4,29,Urban,Manager,147786,0 +86402,Male,47,High School,7,84,89,70,36,6.0,7,88,Urban,Software Engineer,87748,1 +86403,Female,53,Bachelors,10,92,13,23,77,7.0,4,46,Urban,HR Executive,77789,0 +86404,Female,34,High School,17,38,10,85,61,6.0,4,96,Urban,Software Engineer,67964,0 +86405,Male,39,Diploma,4,26,35,4,16,7.0,6,27,Rural,Data Analyst,93483,0 +86406,Male,52,Masters,19,3,54,40,11,1.0,7,10,Semi-Urban,Manager,94453,0 +86407,Female,56,Bachelors,1,78,99,66,80,6.0,4,99,Rural,Data Analyst,37591,1 +86408,Other,56,Diploma,12,96,2,37,82,4.0,0,80,Urban,ML Engineer,144661,0 +86409,Other,38,Masters,6,34,1,59,25,8.0,7,92,Urban,Data Analyst,70915,0 +86410,Female,23,Bachelors,10,52,20,67,91,5.0,5,2,Semi-Urban,HR Executive,20875,0 +86411,Male,50,High School,12,58,91,37,92,9.0,3,10,Semi-Urban,Software Engineer,76314,0 +86412,Male,59,High School,11,11,29,33,21,2.0,0,68,Urban,ML Engineer,142915,0 +86413,Female,52,Bachelors,14,20,90,63,84,8.0,0,77,Rural,Manager,33981,1 +86414,Male,29,Diploma,1,58,32,4,71,3.0,5,84,Urban,HR Executive,76633,0 +86415,Female,50,Bachelors,14,8,94,61,99,2.0,0,96,Rural,Manager,55282,1 +86416,Female,57,Masters,14,87,88,72,95,9.0,7,45,Semi-Urban,Software Engineer,38923,1 +86417,Female,33,Masters,13,2,81,24,17,9.0,7,88,Urban,Manager,123643,0 +86418,Male,47,PhD,7,25,11,64,19,9.0,6,71,Urban,Data Analyst,66081,0 +86419,Female,41,Bachelors,13,62,65,7,72,5.0,5,83,Urban,Data Analyst,125233,0 +86420,Male,58,Diploma,9,34,11,28,88,5.0,0,92,Urban,Manager,82248,0 +86421,Male,43,Bachelors,13,61,64,59,68,8.0,7,2,Semi-Urban,HR Executive,81130,0 +86422,Female,39,PhD,4,28,25,62,51,1.0,0,47,Rural,Manager,125285,0 +86423,Female,22,High School,10,39,19,7,14,9.0,2,8,Urban,Manager,135898,0 +86424,Male,40,High School,1,99,68,84,43,0.0,2,48,Rural,HR Executive,130252,1 +86425,Other,58,Diploma,4,66,50,31,50,1.0,3,67,Rural,ML Engineer,78554,0 +86426,Male,54,High School,5,95,40,68,72,9.0,6,74,Urban,Manager,145772,1 +86427,Female,56,Bachelors,1,19,74,16,80,0.0,0,21,Urban,Software Engineer,49676,0 +86428,Female,35,High School,14,75,84,30,2,5.0,4,81,Rural,ML Engineer,88511,1 +86429,Male,58,Bachelors,15,96,97,58,60,9.0,1,65,Urban,Manager,59307,1 +86430,Male,47,Masters,14,69,14,9,26,7.0,1,91,Urban,Manager,128652,0 +86431,Male,50,Diploma,6,20,94,72,50,1.0,5,8,Semi-Urban,Data Analyst,147683,0 +86432,Male,49,Diploma,14,40,92,36,62,6.0,4,93,Urban,HR Executive,113382,1 +86433,Male,37,High School,8,21,10,98,44,6.0,1,80,Semi-Urban,Data Analyst,31232,0 +86434,Male,29,Masters,14,20,16,78,63,4.0,2,83,Urban,HR Executive,20202,0 +86435,Male,54,High School,9,59,37,92,5,0.0,0,85,Rural,HR Executive,91839,1 +86436,Female,24,Bachelors,13,52,41,18,79,5.0,0,78,Urban,ML Engineer,61162,0 +86437,Male,42,Bachelors,15,2,45,98,73,9.0,4,85,Urban,ML Engineer,65117,0 +86438,Female,27,Masters,16,45,10,32,16,2.0,1,2,Semi-Urban,Software Engineer,148764,0 +86439,Female,21,Diploma,10,27,9,18,60,9.0,5,19,Rural,Manager,39616,0 +86440,Female,41,Diploma,16,36,55,57,95,5.0,7,19,Urban,ML Engineer,87436,0 +86441,Male,24,Bachelors,19,50,28,63,54,1.0,1,34,Urban,Manager,149110,0 +86442,Male,31,High School,4,47,18,43,54,3.0,4,95,Urban,HR Executive,25628,0 +86443,Female,39,Diploma,7,45,8,92,63,9.0,3,40,Rural,Data Analyst,49891,0 +86444,Male,49,Bachelors,15,72,39,30,45,6.0,1,0,Urban,HR Executive,121247,0 +86445,Male,56,Bachelors,14,14,27,31,52,9.0,3,4,Semi-Urban,Software Engineer,136018,0 +86446,Other,31,PhD,16,17,39,58,46,8.0,6,24,Urban,Manager,60786,0 +86447,Other,39,Masters,6,31,42,7,7,1.0,5,82,Urban,HR Executive,86988,0 +86448,Male,59,Diploma,11,69,14,36,87,0.0,5,34,Urban,Manager,111400,0 +86449,Female,53,Bachelors,9,34,4,48,96,4.0,5,41,Urban,Manager,34534,0 +86450,Male,43,Bachelors,4,13,13,98,38,3.0,0,49,Rural,Software Engineer,51418,0 +86451,Male,38,Diploma,3,8,99,94,64,6.0,3,50,Semi-Urban,Data Analyst,68698,1 +86452,Male,27,Bachelors,19,79,73,16,11,6.0,7,39,Urban,ML Engineer,146813,0 +86453,Male,26,Masters,19,91,25,19,65,9.0,5,57,Semi-Urban,HR Executive,93845,0 +86454,Male,46,Diploma,18,2,70,76,84,1.0,0,20,Urban,ML Engineer,87417,0 +86455,Male,56,Diploma,4,17,18,71,37,9.0,5,18,Semi-Urban,ML Engineer,94886,0 +86456,Female,59,Bachelors,6,17,3,40,46,8.0,7,49,Urban,HR Executive,134482,0 +86457,Male,47,High School,8,68,66,37,37,1.0,5,11,Semi-Urban,Software Engineer,59842,0 +86458,Male,26,Masters,14,70,82,9,74,5.0,2,12,Rural,ML Engineer,31160,0 +86459,Female,34,Bachelors,2,14,77,53,7,7.0,4,1,Urban,Manager,108956,0 +86460,Other,21,Bachelors,9,92,52,83,29,3.0,6,62,Urban,ML Engineer,116647,1 +86461,Female,42,High School,17,91,56,25,40,7.0,1,90,Rural,Manager,148161,1 +86462,Male,40,Masters,19,60,29,31,6,5.0,0,72,Urban,Manager,50586,0 +86463,Female,23,Bachelors,17,89,45,63,73,6.0,7,81,Semi-Urban,Software Engineer,99752,1 +86464,Male,50,High School,6,53,49,96,89,3.0,7,29,Semi-Urban,Data Analyst,37175,0 +86465,Female,29,Bachelors,12,15,1,57,17,8.0,0,98,Urban,Software Engineer,96761,0 +86466,Male,29,High School,1,53,95,69,68,1.0,5,37,Urban,HR Executive,45007,1 +86467,Female,37,Bachelors,14,76,20,91,0,8.0,6,15,Urban,HR Executive,39220,0 +86468,Female,41,Masters,0,7,8,38,62,8.0,2,98,Urban,Data Analyst,74811,0 +86469,Male,52,High School,3,71,99,29,83,2.0,2,39,Rural,HR Executive,140056,1 +86470,Female,40,High School,7,72,30,5,31,3.0,0,14,Semi-Urban,Data Analyst,112151,0 +86471,Male,34,Diploma,3,91,15,53,13,0.0,2,24,Semi-Urban,ML Engineer,62186,0 +86472,Male,34,Masters,4,62,26,12,69,4.0,6,66,Urban,Data Analyst,54423,0 +86473,Female,52,High School,12,33,72,20,17,0.0,4,63,Rural,Manager,69480,0 +86474,Male,49,Bachelors,10,45,46,36,20,2.0,0,2,Rural,HR Executive,118099,0 +86475,Female,50,High School,5,50,54,77,49,3.0,3,75,Semi-Urban,ML Engineer,55723,1 +86476,Male,44,Diploma,0,75,32,81,75,9.0,1,63,Urban,Software Engineer,126404,1 +86477,Male,49,Bachelors,2,17,75,52,32,2.0,6,80,Urban,HR Executive,56896,0 +86478,Female,44,Masters,15,38,38,79,29,5.0,7,42,Semi-Urban,Data Analyst,29629,0 +86479,Male,52,High School,12,16,31,16,71,2.0,2,5,Rural,ML Engineer,105109,0 +86480,Male,51,PhD,18,56,78,18,77,3.0,2,47,Urban,Software Engineer,129484,0 +86481,Female,46,Diploma,14,89,34,4,95,2.0,6,54,Semi-Urban,ML Engineer,110837,0 +86482,Female,45,Diploma,1,48,99,44,30,7.0,2,20,Urban,Manager,120929,0 +86483,Female,26,Diploma,10,87,57,41,29,1.0,3,88,Semi-Urban,Manager,76917,1 +86484,Male,43,Bachelors,14,24,16,85,76,7.0,5,99,Urban,Software Engineer,27000,0 +86485,Female,22,Bachelors,10,24,7,19,53,8.0,7,0,Urban,HR Executive,41349,0 +86486,Female,23,High School,1,86,83,99,88,6.0,3,44,Semi-Urban,Software Engineer,62501,1 +86487,Female,40,Bachelors,10,78,19,77,65,8.0,6,62,Urban,HR Executive,62104,0 +86488,Male,55,Diploma,8,19,38,51,37,4.0,2,41,Semi-Urban,HR Executive,106019,0 +86489,Female,27,Bachelors,15,71,69,39,73,5.0,2,28,Rural,Manager,33510,0 +86490,Male,49,Masters,10,24,16,83,22,9.0,1,89,Semi-Urban,Manager,35564,0 +86491,Male,57,Bachelors,13,86,35,75,56,7.0,5,11,Urban,ML Engineer,143048,0 +86492,Male,24,Masters,5,76,75,52,99,4.0,4,48,Semi-Urban,ML Engineer,43546,1 +86493,Female,50,Masters,9,38,9,51,21,2.0,1,97,Urban,HR Executive,126246,0 +86494,Male,59,Diploma,0,28,37,54,65,9.0,3,58,Rural,Data Analyst,115327,0 +86495,Male,24,High School,0,21,91,77,8,6.0,1,92,Urban,Software Engineer,104300,1 +86496,Male,43,Masters,10,81,17,63,86,5.0,7,95,Urban,ML Engineer,68011,1 +86497,Male,53,Bachelors,10,42,48,39,74,9.0,4,63,Urban,Data Analyst,144562,0 +86498,Male,36,Masters,11,27,21,46,0,5.0,1,28,Semi-Urban,HR Executive,66737,0 +86499,Female,28,Diploma,14,47,82,68,8,4.0,1,82,Semi-Urban,Software Engineer,86614,1 +86500,Female,45,Masters,4,35,39,12,72,1.0,1,31,Urban,ML Engineer,50801,0 +86501,Male,59,Bachelors,0,70,82,10,1,6.0,2,54,Urban,Manager,56357,0 +86502,Male,33,Bachelors,8,68,65,39,81,4.0,0,62,Urban,Software Engineer,71094,0 +86503,Female,34,Masters,19,9,35,39,99,2.0,7,25,Urban,Manager,87201,0 +86504,Female,59,Bachelors,6,56,35,22,62,6.0,2,1,Rural,Manager,21663,0 +86505,Female,34,Masters,9,72,54,67,24,9.0,3,4,Rural,Manager,92325,0 +86506,Male,35,Bachelors,10,26,0,98,61,8.0,1,23,Rural,Software Engineer,50890,0 +86507,Female,59,Masters,12,34,20,77,74,8.0,3,40,Semi-Urban,ML Engineer,49169,0 +86508,Female,23,PhD,5,55,54,30,34,2.0,7,82,Rural,Software Engineer,92506,0 +86509,Male,31,Diploma,19,33,88,99,56,7.0,1,84,Urban,Software Engineer,149542,1 +86510,Female,46,High School,18,17,20,94,13,0.0,2,99,Urban,Data Analyst,87553,0 +86511,Male,49,Diploma,5,68,5,68,27,8.0,7,25,Urban,HR Executive,70309,0 +86512,Female,26,High School,7,27,74,94,21,6.0,4,91,Urban,HR Executive,80351,1 +86513,Other,21,Bachelors,7,5,48,15,93,7.0,4,51,Rural,HR Executive,131638,0 +86514,Male,52,Diploma,2,79,3,11,75,2.0,7,11,Rural,ML Engineer,70292,0 +86515,Female,41,Bachelors,1,70,96,39,5,3.0,2,20,Urban,ML Engineer,127178,0 +86516,Female,46,Bachelors,18,70,14,66,78,1.0,6,60,Urban,ML Engineer,29917,0 +86517,Female,57,High School,10,7,89,88,11,1.0,4,79,Rural,HR Executive,132449,1 +86518,Female,54,Masters,18,17,41,76,51,0.0,3,93,Semi-Urban,Data Analyst,24359,0 +86519,Male,28,Bachelors,3,27,40,91,19,9.0,7,71,Urban,Data Analyst,144745,0 +86520,Male,28,Bachelors,2,3,10,85,74,5.0,2,16,Semi-Urban,ML Engineer,33528,0 +86521,Male,52,Bachelors,19,43,9,25,10,7.0,3,48,Rural,Software Engineer,132034,0 +86522,Male,46,Diploma,15,40,71,27,80,7.0,1,12,Rural,Data Analyst,133373,0 +86523,Male,53,Diploma,14,54,19,37,26,0.0,3,99,Urban,Data Analyst,100346,0 +86524,Male,54,Masters,11,61,43,62,11,5.0,6,29,Rural,ML Engineer,60780,0 +86525,Male,52,Masters,7,92,82,63,6,7.0,2,56,Rural,Software Engineer,141148,1 +86526,Male,58,Bachelors,18,67,80,81,75,8.0,7,12,Urban,Manager,80881,1 +86527,Male,23,Diploma,3,82,26,40,88,6.0,4,73,Urban,Manager,135719,0 +86528,Male,49,Bachelors,13,93,80,86,89,3.0,1,46,Urban,Data Analyst,122684,1 +86529,Male,36,Masters,15,59,47,71,68,4.0,3,51,Rural,Data Analyst,89665,0 +86530,Female,30,Bachelors,5,33,63,10,7,3.0,3,1,Urban,Software Engineer,47326,0 +86531,Female,57,Bachelors,3,40,42,94,48,4.0,2,83,Urban,Software Engineer,127575,1 +86532,Male,47,Masters,9,59,37,66,99,3.0,0,97,Urban,Manager,132739,1 +86533,Female,51,Bachelors,4,40,58,55,98,1.0,5,45,Urban,ML Engineer,114393,0 +86534,Female,37,Bachelors,18,53,52,61,76,4.0,0,12,Urban,Data Analyst,37140,0 +86535,Male,45,Masters,3,81,22,14,45,3.0,2,93,Rural,ML Engineer,48371,0 +86536,Female,42,Bachelors,9,72,8,66,81,5.0,2,93,Rural,Software Engineer,99648,0 +86537,Other,33,Diploma,15,98,60,25,59,9.0,0,35,Semi-Urban,Data Analyst,95023,0 +86538,Male,51,Bachelors,5,82,53,61,23,7.0,6,76,Urban,HR Executive,106002,1 +86539,Male,52,Bachelors,7,15,57,64,98,0.0,6,80,Rural,Data Analyst,22514,0 +86540,Female,59,Masters,4,48,22,63,36,8.0,4,87,Urban,HR Executive,61626,0 +86541,Male,27,Diploma,1,66,10,58,3,4.0,3,25,Urban,HR Executive,65900,0 +86542,Male,29,Bachelors,7,96,34,98,60,3.0,4,89,Urban,ML Engineer,90207,1 +86543,Female,58,Bachelors,0,40,97,10,74,5.0,7,48,Urban,Software Engineer,57093,0 +86544,Female,40,High School,3,89,59,50,32,0.0,5,40,Semi-Urban,HR Executive,149391,0 +86545,Male,52,Masters,8,89,69,68,44,4.0,6,87,Semi-Urban,HR Executive,125156,1 +86546,Female,53,Bachelors,10,52,20,70,79,8.0,2,42,Urban,Manager,75097,0 +86547,Female,35,High School,6,6,91,98,51,9.0,7,1,Semi-Urban,Data Analyst,46848,0 +86548,Male,50,Bachelors,18,42,88,12,23,5.0,0,52,Rural,HR Executive,94369,0 +86549,Male,36,Masters,12,49,11,19,8,3.0,7,3,Urban,ML Engineer,71697,0 +86550,Female,58,Bachelors,3,97,30,20,72,6.0,7,79,Urban,HR Executive,132955,0 +86551,Male,56,Bachelors,15,7,11,11,27,7.0,6,34,Urban,Manager,42984,0 +86552,Male,36,High School,4,81,0,63,94,4.0,3,74,Semi-Urban,Manager,131858,0 +86553,Male,24,Masters,2,76,23,67,34,9.0,6,59,Urban,HR Executive,79257,0 +86554,Female,46,Bachelors,10,38,20,78,1,4.0,7,27,Semi-Urban,Manager,142727,0 +86555,Male,27,Diploma,0,49,4,68,0,7.0,0,91,Semi-Urban,Data Analyst,104997,0 +86556,Male,22,Diploma,17,72,14,77,38,4.0,3,10,Rural,Data Analyst,98734,0 +86557,Female,39,Bachelors,3,29,12,44,34,7.0,2,23,Rural,Manager,119886,0 +86558,Male,26,Masters,18,89,61,10,11,3.0,3,65,Urban,HR Executive,101944,0 +86559,Male,31,High School,0,92,99,48,38,7.0,7,28,Urban,HR Executive,138188,1 +86560,Male,26,Bachelors,12,82,90,66,95,3.0,0,11,Urban,HR Executive,72724,1 +86561,Male,30,PhD,11,44,52,40,58,9.0,1,11,Semi-Urban,Software Engineer,119756,0 +86562,Male,58,Bachelors,9,62,19,94,91,6.0,7,27,Urban,Data Analyst,50838,0 +86563,Male,21,Bachelors,1,14,11,33,15,6.0,3,36,Urban,Manager,27438,0 +86564,Female,53,Bachelors,6,46,55,31,78,0.0,2,72,Urban,HR Executive,84468,0 +86565,Male,42,Bachelors,3,52,67,76,96,8.0,7,33,Urban,HR Executive,24487,0 +86566,Female,44,Bachelors,14,14,95,70,39,1.0,7,30,Urban,HR Executive,117323,0 +86567,Female,49,Bachelors,3,90,52,87,13,6.0,5,2,Rural,HR Executive,38811,0 +86568,Female,35,Bachelors,10,90,5,28,86,4.0,5,42,Urban,Software Engineer,86891,0 +86569,Male,59,Diploma,9,54,57,56,50,3.0,6,16,Semi-Urban,ML Engineer,117077,0 +86570,Male,23,Diploma,7,2,4,35,32,2.0,5,30,Urban,Manager,81255,0 +86571,Female,47,Diploma,13,99,29,96,38,4.0,1,55,Semi-Urban,Software Engineer,34327,1 +86572,Male,28,Bachelors,2,14,98,22,88,3.0,3,14,Urban,ML Engineer,106636,0 +86573,Female,50,Diploma,2,68,91,69,25,3.0,3,17,Semi-Urban,Manager,47053,1 +86574,Male,49,PhD,3,63,50,14,91,3.0,3,50,Rural,ML Engineer,38255,0 +86575,Male,58,Bachelors,12,2,14,76,42,8.0,6,9,Semi-Urban,HR Executive,68827,0 +86576,Female,52,Bachelors,10,26,40,16,94,1.0,0,64,Semi-Urban,Manager,144443,0 +86577,Female,23,Diploma,16,25,94,42,9,9.0,3,74,Rural,Data Analyst,146510,0 +86578,Female,40,High School,9,11,87,38,75,6.0,3,4,Urban,ML Engineer,93911,0 +86579,Male,29,Diploma,17,35,24,42,85,7.0,3,15,Urban,Software Engineer,101865,0 +86580,Female,43,High School,0,56,18,11,77,7.0,2,99,Semi-Urban,Manager,108292,0 +86581,Male,27,Bachelors,7,80,81,9,49,1.0,7,1,Semi-Urban,ML Engineer,98953,0 +86582,Other,45,High School,15,41,39,80,70,0.0,3,44,Urban,Data Analyst,95761,0 +86583,Male,44,Bachelors,16,64,4,74,49,8.0,0,49,Urban,ML Engineer,72336,0 +86584,Female,45,Bachelors,7,5,86,45,57,8.0,2,29,Urban,Data Analyst,96455,0 +86585,Female,52,High School,17,60,48,62,30,2.0,4,35,Rural,ML Engineer,68676,0 +86586,Male,48,Diploma,0,43,85,86,8,4.0,3,37,Semi-Urban,ML Engineer,58710,1 +86587,Male,32,Diploma,5,48,98,44,92,6.0,3,34,Urban,ML Engineer,104403,0 +86588,Female,27,Diploma,0,23,2,9,55,3.0,7,48,Rural,HR Executive,100461,0 +86589,Female,41,PhD,11,49,80,84,76,5.0,3,99,Rural,ML Engineer,65896,1 +86590,Male,24,Bachelors,5,62,69,33,96,1.0,5,76,Urban,Manager,42439,1 +86591,Female,23,High School,9,43,88,25,61,3.0,0,67,Urban,HR Executive,124191,0 +86592,Female,50,Diploma,1,18,8,27,77,0.0,4,99,Urban,Data Analyst,135774,0 +86593,Male,46,Bachelors,4,59,56,7,5,0.0,1,14,Urban,Software Engineer,61778,0 +86594,Female,29,Bachelors,7,44,67,68,20,5.0,6,27,Rural,Manager,25952,0 +86595,Male,25,Bachelors,1,12,57,38,22,0.0,1,71,Urban,HR Executive,101087,0 +86596,Male,26,Bachelors,1,62,39,53,58,5.0,3,92,Urban,ML Engineer,69082,1 +86597,Male,43,Masters,2,27,36,86,40,1.0,7,74,Urban,ML Engineer,40199,0 +86598,Other,30,Bachelors,5,52,26,76,34,6.0,1,25,Urban,Data Analyst,36311,0 +86599,Male,21,Masters,4,79,91,7,1,6.0,0,50,Urban,Manager,25132,0 +86600,Male,21,High School,9,45,72,57,73,8.0,4,75,Semi-Urban,HR Executive,71936,1 +86601,Female,48,Bachelors,15,99,46,36,51,7.0,1,42,Urban,Manager,141951,0 +86602,Male,23,Masters,17,37,75,53,99,7.0,5,18,Rural,Software Engineer,138190,0 +86603,Male,21,Masters,6,31,89,44,78,8.0,5,20,Urban,Data Analyst,128632,0 +86604,Male,39,Bachelors,11,23,14,38,19,9.0,1,31,Rural,Data Analyst,78238,0 +86605,Male,44,High School,18,94,17,61,99,4.0,0,57,Urban,Data Analyst,121220,0 +86606,Female,36,PhD,11,69,11,13,10,2.0,1,28,Urban,HR Executive,26694,0 +86607,Female,32,Diploma,7,85,52,67,69,1.0,6,13,Urban,Software Engineer,65661,0 +86608,Female,44,High School,12,12,58,56,87,4.0,1,96,Rural,Software Engineer,106792,0 +86609,Female,37,Bachelors,16,67,26,80,18,2.0,6,66,Urban,Manager,132709,0 +86610,Male,55,Bachelors,5,13,95,97,98,8.0,1,81,Semi-Urban,HR Executive,139867,1 +86611,Male,38,Diploma,6,41,72,15,83,9.0,7,93,Urban,Manager,117601,0 +86612,Male,32,PhD,5,86,61,70,8,2.0,2,35,Urban,Software Engineer,134365,1 +86613,Male,34,Bachelors,14,22,89,25,96,4.0,3,20,Rural,ML Engineer,73994,0 +86614,Female,22,Bachelors,12,0,32,65,66,2.0,7,21,Urban,HR Executive,128119,0 +86615,Female,47,Masters,19,91,30,20,69,3.0,4,77,Urban,Manager,135857,0 +86616,Male,56,Diploma,3,14,62,28,82,4.0,1,41,Urban,Software Engineer,141295,0 +86617,Male,28,Bachelors,17,29,35,89,68,8.0,7,20,Urban,HR Executive,27929,0 +86618,Female,22,Diploma,8,78,16,88,92,6.0,3,86,Rural,ML Engineer,73344,1 +86619,Other,48,Bachelors,4,16,87,70,35,8.0,6,42,Urban,Software Engineer,51114,0 +86620,Female,26,Bachelors,6,31,46,43,88,6.0,7,64,Rural,Data Analyst,24207,0 +86621,Male,50,Bachelors,12,97,11,32,79,1.0,4,1,Urban,Manager,74907,0 +86622,Female,44,Bachelors,17,3,87,9,24,1.0,6,89,Rural,Software Engineer,78618,0 +86623,Female,29,Diploma,15,64,67,31,41,2.0,7,51,Rural,Data Analyst,63105,0 +86624,Female,27,Bachelors,8,65,60,10,39,7.0,1,51,Urban,Manager,101476,0 +86625,Female,59,Masters,14,50,66,94,85,9.0,2,67,Urban,Data Analyst,114873,1 +86626,Male,29,Bachelors,15,7,61,41,2,3.0,1,84,Rural,HR Executive,97671,0 +86627,Female,24,Masters,11,58,1,1,32,4.0,6,38,Urban,Manager,62780,0 +86628,Male,29,Diploma,1,94,57,64,49,0.0,1,92,Semi-Urban,ML Engineer,107267,1 +86629,Male,24,High School,19,85,78,96,44,2.0,6,35,Urban,Manager,29211,1 +86630,Female,21,High School,9,74,2,13,66,7.0,3,65,Urban,Manager,99035,0 +86631,Male,30,Masters,19,40,15,28,63,6.0,4,46,Urban,Data Analyst,34876,0 +86632,Male,23,High School,17,47,62,13,22,9.0,1,2,Urban,Data Analyst,80281,0 +86633,Male,29,Diploma,7,36,41,81,33,2.0,4,92,Urban,HR Executive,141100,1 +86634,Other,59,Bachelors,7,15,21,90,97,8.0,2,28,Urban,ML Engineer,128525,0 +86635,Female,48,Masters,16,54,84,47,55,3.0,4,17,Urban,HR Executive,129440,0 +86636,Male,40,Bachelors,19,60,28,43,65,4.0,3,68,Semi-Urban,ML Engineer,42056,0 +86637,Male,51,Masters,0,83,39,87,0,0.0,2,30,Rural,Manager,129642,1 +86638,Female,32,Diploma,4,93,54,1,58,6.0,1,70,Urban,Manager,149400,0 +86639,Female,56,High School,7,51,18,84,27,0.0,3,84,Urban,Software Engineer,143233,0 +86640,Female,35,Diploma,5,53,86,85,51,6.0,7,39,Urban,ML Engineer,92004,1 +86641,Male,45,Diploma,1,98,95,79,45,1.0,6,23,Urban,Software Engineer,24253,1 +86642,Female,53,High School,7,56,80,67,81,8.0,2,59,Semi-Urban,Data Analyst,26709,1 +86643,Male,24,Bachelors,3,83,82,72,86,3.0,7,54,Rural,Data Analyst,29560,1 +86644,Female,26,High School,7,21,2,86,21,3.0,0,47,Urban,Software Engineer,148450,0 +86645,Male,27,High School,6,40,0,17,82,0.0,7,11,Urban,ML Engineer,86143,0 +86646,Female,48,Diploma,15,92,5,2,84,7.0,6,26,Semi-Urban,Manager,90127,0 +86647,Female,41,Bachelors,12,70,93,5,10,4.0,2,61,Urban,Manager,70161,0 +86648,Female,47,Diploma,8,88,76,16,49,1.0,3,34,Urban,Software Engineer,123086,0 +86649,Female,58,Bachelors,1,8,68,78,31,9.0,7,31,Urban,Software Engineer,129522,0 +86650,Female,29,PhD,18,77,93,22,54,8.0,7,93,Rural,Manager,108927,1 +86651,Male,58,Bachelors,8,29,84,44,83,0.0,1,42,Urban,Software Engineer,71275,0 +86652,Male,49,Bachelors,5,5,45,98,39,5.0,3,26,Rural,ML Engineer,44165,0 +86653,Male,44,PhD,12,71,54,32,97,7.0,1,34,Semi-Urban,ML Engineer,34335,0 +86654,Female,53,Diploma,7,51,77,64,95,0.0,0,4,Urban,HR Executive,78136,0 +86655,Male,36,Bachelors,11,88,80,84,58,0.0,7,39,Urban,Manager,84057,1 +86656,Female,46,PhD,8,9,86,59,89,6.0,0,96,Semi-Urban,Software Engineer,128377,1 +86657,Male,59,Bachelors,1,91,95,88,50,8.0,3,70,Semi-Urban,Software Engineer,83505,1 +86658,Female,22,Bachelors,17,45,47,49,80,4.0,4,45,Urban,Software Engineer,96173,0 +86659,Other,56,Bachelors,8,0,15,15,52,0.0,6,62,Urban,HR Executive,67215,0 +86660,Female,47,High School,17,75,57,9,50,4.0,1,53,Urban,Data Analyst,108756,0 +86661,Male,31,Diploma,16,18,88,38,65,4.0,5,85,Urban,Manager,114109,0 +86662,Male,54,Bachelors,1,68,15,19,37,9.0,5,40,Urban,Manager,105047,0 +86663,Female,52,Bachelors,12,89,69,30,94,5.0,7,77,Urban,HR Executive,125821,1 +86664,Female,48,High School,12,38,0,71,78,4.0,0,69,Urban,Manager,24861,0 +86665,Female,34,Diploma,12,98,17,8,22,5.0,5,49,Rural,ML Engineer,129985,0 +86666,Male,25,Bachelors,3,48,59,30,89,4.0,6,72,Urban,HR Executive,85519,0 +86667,Male,24,High School,10,91,84,35,35,1.0,2,75,Urban,ML Engineer,46276,1 +86668,Male,41,Bachelors,9,69,66,0,39,3.0,2,50,Urban,ML Engineer,138821,0 +86669,Male,44,Diploma,16,24,90,34,19,4.0,2,90,Semi-Urban,Data Analyst,39615,1 +86670,Male,30,Masters,9,86,14,68,43,1.0,7,71,Urban,Manager,80323,1 +86671,Female,43,Bachelors,17,29,19,19,26,9.0,0,59,Urban,Manager,41927,0 +86672,Male,30,Bachelors,18,68,85,27,38,7.0,1,98,Urban,Manager,70597,1 +86673,Female,30,Bachelors,2,62,70,62,22,3.0,6,56,Rural,Data Analyst,63234,1 +86674,Female,21,High School,10,65,1,69,8,8.0,2,32,Rural,HR Executive,98778,0 +86675,Male,43,Masters,16,92,13,90,84,8.0,4,91,Semi-Urban,ML Engineer,27031,1 +86676,Male,51,High School,5,71,91,25,82,7.0,3,87,Semi-Urban,Software Engineer,120227,1 +86677,Male,46,Diploma,3,3,56,44,76,5.0,2,7,Urban,ML Engineer,138802,0 +86678,Male,30,Bachelors,10,70,42,80,48,0.0,1,24,Semi-Urban,HR Executive,87159,0 +86679,Male,25,Diploma,7,30,2,58,97,0.0,6,46,Semi-Urban,Software Engineer,97358,0 +86680,Male,22,Diploma,19,20,39,59,1,9.0,0,35,Urban,HR Executive,113450,0 +86681,Male,46,Bachelors,5,96,42,55,54,1.0,3,66,Urban,Manager,111711,1 +86682,Male,24,High School,12,54,1,36,4,9.0,3,37,Semi-Urban,Manager,25725,0 +86683,Other,55,Masters,13,38,9,29,42,9.0,5,97,Urban,HR Executive,141325,0 +86684,Male,53,Diploma,13,9,35,36,59,0.0,5,65,Semi-Urban,Manager,125331,0 +86685,Male,39,Bachelors,18,3,86,17,7,7.0,6,47,Urban,Software Engineer,102698,0 +86686,Male,37,High School,5,14,34,1,22,7.0,1,99,Urban,Data Analyst,102034,0 +86687,Male,57,Bachelors,14,50,13,5,54,8.0,3,98,Urban,HR Executive,79068,0 +86688,Male,29,PhD,11,43,53,6,74,0.0,5,17,Urban,ML Engineer,94167,0 +86689,Male,31,Masters,8,80,79,60,6,7.0,6,55,Semi-Urban,Software Engineer,104194,1 +86690,Female,45,High School,7,23,31,43,29,5.0,1,84,Semi-Urban,ML Engineer,100749,0 +86691,Male,24,High School,16,45,59,66,59,5.0,2,94,Semi-Urban,Data Analyst,83389,1 +86692,Male,53,High School,15,66,94,22,70,2.0,0,84,Semi-Urban,Manager,57912,1 +86693,Female,46,Masters,5,20,3,9,62,3.0,4,53,Urban,HR Executive,25147,0 +86694,Male,28,High School,7,72,6,62,10,0.0,2,17,Semi-Urban,Manager,131064,0 +86695,Male,44,Masters,11,75,94,33,12,9.0,4,41,Rural,ML Engineer,98093,1 +86696,Other,56,Diploma,18,92,93,32,63,0.0,1,99,Urban,Manager,49191,1 +86697,Male,38,High School,17,82,0,92,54,9.0,2,15,Semi-Urban,Data Analyst,116560,0 +86698,Female,54,Masters,12,48,66,47,79,4.0,1,68,Urban,Data Analyst,130917,0 +86699,Female,28,High School,11,36,70,35,86,4.0,0,1,Semi-Urban,ML Engineer,27711,0 +86700,Male,39,Bachelors,1,85,48,99,14,5.0,6,38,Urban,Manager,81396,1 +86701,Male,29,Diploma,0,55,10,77,11,5.0,4,35,Urban,Data Analyst,99740,0 +86702,Male,49,Masters,1,8,65,20,84,3.0,5,20,Rural,HR Executive,140204,0 +86703,Male,21,Bachelors,0,39,99,63,7,6.0,3,63,Urban,Software Engineer,125153,1 +86704,Other,27,Diploma,17,9,49,36,29,2.0,1,46,Urban,HR Executive,118302,0 +86705,Male,39,Bachelors,5,40,1,34,16,3.0,4,77,Semi-Urban,ML Engineer,122665,0 +86706,Female,22,High School,15,19,33,26,32,8.0,0,65,Rural,Data Analyst,71921,0 +86707,Female,38,Masters,5,13,80,74,63,8.0,0,30,Rural,Manager,59686,0 +86708,Female,23,Bachelors,3,99,50,42,24,3.0,0,44,Rural,Data Analyst,110060,0 +86709,Female,24,Masters,8,84,18,50,43,7.0,4,15,Semi-Urban,Data Analyst,78226,0 +86710,Female,47,Bachelors,10,27,38,26,14,8.0,4,17,Urban,Data Analyst,114753,0 +86711,Male,33,Bachelors,14,98,48,5,28,9.0,3,41,Rural,Software Engineer,134655,0 +86712,Female,21,Diploma,17,78,64,58,21,6.0,1,1,Rural,Data Analyst,36093,0 +86713,Male,51,Masters,19,66,29,79,41,5.0,1,16,Urban,ML Engineer,26022,0 +86714,Male,39,,3,18,14,45,82,2.0,0,40,Semi-Urban,Manager,46031,0 +86715,Male,30,Masters,3,64,39,13,16,0.0,3,40,Semi-Urban,ML Engineer,39278,0 +86716,Female,48,Bachelors,4,3,52,4,85,5.0,3,20,Semi-Urban,Data Analyst,111241,0 +86717,Female,37,Diploma,9,5,27,4,79,7.0,5,64,Urban,ML Engineer,75822,0 +86718,Male,27,Diploma,14,8,10,64,62,4.0,3,17,Urban,Software Engineer,21419,0 +86719,Male,51,Bachelors,12,51,15,79,45,4.0,0,3,Semi-Urban,HR Executive,126153,0 +86720,Male,32,High School,3,70,97,18,21,4.0,1,2,Urban,Data Analyst,104622,0 +86721,Male,40,Bachelors,11,72,10,23,35,9.0,5,43,Urban,Software Engineer,120353,0 +86722,Male,24,Diploma,13,99,76,99,18,7.0,2,1,Urban,HR Executive,130006,1 +86723,Male,27,Bachelors,4,44,42,71,42,4.0,7,10,Urban,ML Engineer,142200,0 +86724,Male,30,Bachelors,7,53,73,88,99,6.0,3,80,Semi-Urban,Data Analyst,120833,1 +86725,Female,48,Diploma,12,58,45,65,72,9.0,1,3,Urban,Manager,75251,0 +86726,Female,21,Masters,11,97,64,28,94,4.0,5,23,Urban,HR Executive,94440,0 +86727,Male,42,Diploma,7,37,35,62,12,9.0,2,47,Semi-Urban,Software Engineer,136402,0 +86728,Female,47,Bachelors,14,17,90,60,87,1.0,7,48,Urban,Manager,117048,0 +86729,Male,44,High School,19,35,45,14,1,0.0,6,73,Urban,ML Engineer,83449,0 +86730,Female,50,Bachelors,8,96,57,30,75,7.0,2,86,Urban,Manager,123472,1 +86731,Male,26,Bachelors,5,27,85,12,24,4.0,3,27,Rural,Software Engineer,88477,0 +86732,Female,54,Diploma,8,88,73,39,0,5.0,5,66,Urban,HR Executive,88344,1 +86733,Female,40,Diploma,19,25,28,78,77,9.0,4,6,Rural,Data Analyst,122062,0 +86734,Female,58,Masters,3,84,1,20,46,8.0,1,61,Semi-Urban,Manager,38770,0 +86735,Female,52,High School,4,44,67,12,86,9.0,1,69,Rural,Software Engineer,64986,0 +86736,Male,50,PhD,12,17,45,29,14,0.0,3,72,Rural,Manager,87448,0 +86737,Male,26,Masters,11,75,16,70,26,7.0,0,88,Semi-Urban,Data Analyst,85847,1 +86738,Female,57,Bachelors,4,59,88,56,35,8.0,1,1,Semi-Urban,HR Executive,69231,0 +86739,Female,42,Bachelors,16,94,74,37,14,5.0,7,25,Urban,Software Engineer,113141,0 +86740,Male,29,Bachelors,18,63,32,75,17,9.0,3,76,Rural,Software Engineer,129917,1 +86741,Male,32,Diploma,11,36,47,4,74,1.0,6,54,Urban,Manager,148731,0 +86742,Female,59,Masters,0,99,37,8,74,5.0,3,54,Urban,Manager,141362,0 +86743,Other,33,Diploma,13,21,94,95,74,5.0,1,69,Semi-Urban,HR Executive,134624,1 +86744,Male,32,Bachelors,12,58,81,37,1,0.0,4,8,Rural,Data Analyst,72038,0 +86745,Male,53,High School,1,5,85,70,97,3.0,5,16,Semi-Urban,Data Analyst,142880,0 +86746,Male,30,Masters,1,49,71,50,87,0.0,6,45,Urban,Data Analyst,48401,0 +86747,Female,32,Diploma,8,62,81,54,91,7.0,1,81,Urban,Software Engineer,33462,1 +86748,Male,25,High School,2,88,61,19,18,9.0,4,70,Semi-Urban,HR Executive,23742,1 +86749,Male,35,PhD,10,88,17,25,14,4.0,6,78,Semi-Urban,ML Engineer,119002,0 +86750,Male,29,Diploma,10,37,62,47,76,5.0,2,86,Semi-Urban,ML Engineer,81206,0 +86751,Female,24,Bachelors,15,19,68,26,90,2.0,5,30,Urban,HR Executive,51710,0 +86752,Male,28,High School,9,92,35,16,46,4.0,2,32,Urban,ML Engineer,32420,0 +86753,Male,48,Masters,4,57,41,90,80,6.0,3,12,Urban,ML Engineer,87202,0 +86754,Female,51,Bachelors,10,37,20,81,6,1.0,2,62,Urban,Software Engineer,132238,0 +86755,Other,56,Masters,13,89,46,93,88,7.0,0,68,Urban,Data Analyst,82607,1 +86756,Female,33,Bachelors,14,46,61,52,30,2.0,3,39,Rural,HR Executive,67164,0 +86757,Male,48,High School,10,89,39,82,67,7.0,0,83,Urban,Data Analyst,34725,1 +86758,Male,31,Bachelors,1,12,27,81,94,6.0,2,78,Semi-Urban,Software Engineer,51807,0 +86759,Male,30,Masters,5,25,63,82,60,0.0,0,56,Rural,HR Executive,117057,0 +86760,Male,43,Masters,16,10,4,2,98,1.0,1,91,Rural,Data Analyst,88881,0 +86761,Male,45,Diploma,2,47,48,44,19,1.0,0,47,Rural,Data Analyst,38979,0 +86762,Male,48,Masters,5,25,28,25,32,8.0,5,18,Urban,HR Executive,111674,0 +86763,Female,29,Masters,15,23,33,35,84,3.0,6,6,Urban,ML Engineer,27217,0 +86764,Female,28,Diploma,15,93,77,46,42,0.0,1,73,Urban,Manager,30265,1 +86765,Male,59,High School,18,6,51,76,16,0.0,5,74,Semi-Urban,Manager,77621,0 +86766,Male,42,Bachelors,9,6,47,43,77,6.0,5,54,Semi-Urban,Data Analyst,98253,0 +86767,Female,52,Masters,7,53,56,38,82,8.0,1,92,Urban,Data Analyst,141622,0 +86768,Male,23,Bachelors,18,3,60,57,19,2.0,6,81,Semi-Urban,Data Analyst,59617,0 +86769,Male,34,PhD,0,36,25,4,93,9.0,3,77,Rural,Manager,89790,0 +86770,Male,51,Masters,11,26,83,59,31,2.0,4,56,Urban,HR Executive,43346,0 +86771,Male,59,Diploma,6,77,17,91,52,7.0,0,73,Urban,Software Engineer,62803,1 +86772,Female,43,Bachelors,19,71,29,27,65,5.0,0,47,Urban,Manager,143567,0 +86773,Female,25,Bachelors,9,28,68,22,63,7.0,0,75,Urban,Software Engineer,128587,0 +86774,Male,44,Bachelors,6,82,54,85,62,5.0,4,68,Semi-Urban,HR Executive,122028,1 +86775,Female,52,Bachelors,0,17,54,61,43,1.0,2,12,Urban,HR Executive,67326,0 +86776,Male,46,Diploma,8,13,71,94,36,0.0,3,27,Rural,Data Analyst,65641,0 +86777,Male,42,Diploma,15,96,63,23,9,0.0,3,96,Urban,Software Engineer,53317,1 +86778,Female,39,Bachelors,5,7,48,13,2,6.0,3,75,Semi-Urban,Software Engineer,29788,0 +86779,Female,49,Masters,1,20,60,49,70,0.0,3,44,Semi-Urban,HR Executive,30889,0 +86780,Male,37,Diploma,4,61,62,49,54,6.0,5,74,Semi-Urban,Manager,29922,1 +86781,Male,23,Diploma,9,25,13,40,43,5.0,5,2,Semi-Urban,Manager,146529,0 +86782,Male,44,Bachelors,13,36,28,60,22,8.0,3,63,Urban,ML Engineer,103326,0 +86783,Male,58,High School,19,12,75,19,87,7.0,6,2,Rural,Manager,71711,0 +86784,Male,31,Bachelors,9,33,44,32,59,5.0,4,69,Urban,Data Analyst,104182,0 +86785,Male,41,Bachelors,3,24,85,55,69,1.0,4,65,Rural,ML Engineer,103577,0 +86786,Female,55,Masters,4,32,1,37,38,7.0,1,55,Urban,Data Analyst,57883,0 +86787,Female,23,High School,5,22,77,82,74,0.0,7,98,Urban,Manager,48308,1 +86788,Male,28,High School,13,29,41,17,81,7.0,2,64,Urban,Manager,57835,0 +86789,Male,57,Diploma,2,38,96,19,3,7.0,7,4,Rural,Software Engineer,76715,0 +86790,Female,31,Bachelors,0,98,97,12,54,6.0,5,96,Urban,Software Engineer,67668,1 +86791,Female,48,Masters,19,7,22,95,1,5.0,4,30,Urban,Software Engineer,91775,0 +86792,Male,32,High School,5,69,8,14,65,6.0,2,43,Urban,Software Engineer,54111,0 +86793,Female,36,Masters,18,46,54,88,18,8.0,6,77,Urban,Manager,56137,1 +86794,Female,37,High School,10,26,84,10,30,9.0,2,83,Rural,Data Analyst,34895,0 +86795,Male,59,Bachelors,2,77,9,56,46,5.0,0,85,Semi-Urban,HR Executive,109375,0 +86796,Female,21,Bachelors,10,51,36,14,0,2.0,5,15,Rural,Data Analyst,88435,0 +86797,Male,26,Bachelors,4,12,39,74,77,2.0,6,7,Rural,ML Engineer,93413,0 +86798,Male,25,High School,3,46,52,77,90,6.0,2,57,Urban,Software Engineer,36139,0 +86799,Male,47,Bachelors,16,43,51,41,98,2.0,2,49,Semi-Urban,Manager,134699,0 +86800,Male,39,PhD,4,15,19,71,13,3.0,0,62,Urban,Manager,121851,0 +86801,Female,44,Bachelors,17,83,16,53,90,6.0,2,97,Rural,HR Executive,78931,1 +86802,Female,52,Bachelors,5,50,18,29,48,9.0,7,7,Rural,Data Analyst,80316,0 +86803,Male,57,Bachelors,4,80,80,4,97,3.0,2,29,Urban,Manager,36799,0 +86804,Male,56,High School,15,16,90,76,39,6.0,0,12,Urban,HR Executive,96716,0 +86805,Female,25,Masters,19,12,66,80,7,3.0,1,4,Urban,Manager,141046,0 +86806,Male,37,High School,2,48,4,77,24,4.0,6,1,Semi-Urban,Data Analyst,126455,0 +86807,Male,28,Masters,1,40,16,87,37,9.0,0,12,Urban,Software Engineer,106678,0 +86808,Male,21,Diploma,10,53,18,1,1,6.0,0,25,Semi-Urban,ML Engineer,82129,0 +86809,Male,35,Masters,13,58,72,26,65,8.0,6,40,Urban,ML Engineer,86979,0 +86810,Female,56,PhD,11,72,98,54,11,2.0,6,79,Semi-Urban,Software Engineer,65378,1 +86811,Male,35,Masters,3,55,19,3,40,9.0,2,56,Semi-Urban,Software Engineer,103695,0 +86812,Male,56,Bachelors,8,77,38,50,26,9.0,1,93,Semi-Urban,Software Engineer,145697,1 +86813,Male,52,Masters,1,8,76,61,93,5.0,6,64,Urban,Data Analyst,123271,0 +86814,Male,28,Bachelors,6,18,61,87,16,3.0,2,14,Urban,HR Executive,88130,0 +86815,Female,44,Bachelors,17,39,84,54,49,6.0,7,19,Urban,ML Engineer,105669,0 +86816,Male,39,Diploma,11,81,11,27,8,5.0,5,14,Urban,Software Engineer,97232,0 +86817,Male,27,PhD,1,23,48,22,91,1.0,1,64,Urban,ML Engineer,139686,0 +86818,Male,40,Bachelors,17,8,73,60,25,9.0,4,77,Urban,Software Engineer,115533,0 +86819,Male,30,Diploma,9,85,26,70,37,9.0,6,51,Urban,Data Analyst,68087,0 +86820,Male,30,Bachelors,14,82,12,75,30,1.0,5,65,Urban,HR Executive,88702,0 +86821,Other,58,PhD,1,60,99,52,55,1.0,2,24,Urban,Manager,88909,0 +86822,Female,41,Bachelors,16,65,57,57,10,4.0,5,1,Rural,Data Analyst,34202,0 +86823,Female,22,Masters,7,40,62,44,84,5.0,1,38,Urban,Manager,133841,0 +86824,Male,45,Bachelors,6,40,12,17,68,0.0,1,50,Urban,Software Engineer,45359,0 +86825,Female,32,Bachelors,11,26,38,12,82,0.0,0,61,Semi-Urban,ML Engineer,52568,0 +86826,Female,32,Bachelors,2,62,35,62,89,8.0,6,82,Semi-Urban,ML Engineer,133846,1 +86827,Male,51,Masters,11,26,57,32,20,2.0,2,52,Urban,Data Analyst,57033,0 +86828,Female,59,High School,19,93,3,70,90,1.0,4,5,Urban,Manager,127399,0 +86829,Male,50,Bachelors,3,7,63,68,94,4.0,0,53,Rural,HR Executive,134752,0 +86830,Female,48,Bachelors,14,84,15,62,26,2.0,7,88,Urban,Data Analyst,27339,1 +86831,Female,51,Bachelors,16,21,79,60,56,9.0,4,29,Semi-Urban,Manager,57423,0 +86832,Male,38,Diploma,8,3,83,81,91,4.0,7,79,Semi-Urban,Manager,106029,1 +86833,Other,29,Diploma,1,58,12,78,0,3.0,0,65,Rural,Software Engineer,57864,0 +86834,Female,21,Bachelors,8,42,13,64,69,8.0,5,47,Urban,Software Engineer,64907,0 +86835,Female,33,Bachelors,10,10,16,62,28,4.0,2,52,Urban,HR Executive,32976,0 +86836,Male,29,Bachelors,7,8,14,12,16,9.0,1,66,Semi-Urban,Data Analyst,146286,0 +86837,Male,43,Bachelors,18,37,73,20,74,5.0,3,94,Urban,Software Engineer,134608,0 +86838,Male,47,Masters,19,91,14,19,46,1.0,6,0,Urban,ML Engineer,29072,0 +86839,Female,38,PhD,18,79,30,98,88,5.0,0,72,Urban,HR Executive,98558,1 +86840,Male,42,Bachelors,6,89,16,36,21,6.0,6,27,Urban,ML Engineer,114322,0 +86841,Female,25,Masters,18,88,86,56,71,2.0,2,43,Rural,HR Executive,99398,1 +86842,Female,23,Diploma,17,67,55,40,20,0.0,2,28,Rural,Software Engineer,73525,0 +86843,Male,45,Bachelors,9,5,86,29,72,4.0,4,68,Semi-Urban,Software Engineer,140977,0 +86844,Male,42,Bachelors,8,55,91,59,71,1.0,4,46,Urban,HR Executive,72842,1 +86845,Male,40,Diploma,0,85,3,72,84,5.0,1,51,Semi-Urban,Manager,128907,0 +86846,Male,40,Bachelors,4,98,37,70,1,6.0,0,60,Urban,Manager,69450,1 +86847,Female,36,Masters,1,97,15,45,58,4.0,6,37,Urban,HR Executive,22785,0 +86848,Male,45,Diploma,19,16,93,36,40,0.0,2,84,Urban,HR Executive,137061,0 +86849,Male,34,Diploma,17,48,41,10,53,6.0,0,19,Semi-Urban,Software Engineer,112572,0 +86850,Male,25,Diploma,14,49,37,78,27,0.0,3,73,Urban,Manager,20213,1 +86851,Male,38,Masters,5,23,57,97,21,3.0,2,3,Urban,ML Engineer,131507,0 +86852,Female,21,Diploma,4,88,7,85,30,3.0,1,87,Urban,Manager,27055,1 +86853,Male,47,PhD,0,9,89,22,34,4.0,7,28,Urban,HR Executive,45564,0 +86854,Male,55,Masters,8,92,5,54,54,8.0,2,18,Urban,Data Analyst,93537,0 +86855,Female,24,Masters,10,7,99,34,95,3.0,5,38,Rural,Data Analyst,143415,0 +86856,Female,36,Diploma,5,61,24,1,39,7.0,5,76,Rural,HR Executive,134826,0 +86857,Male,38,Bachelors,11,75,64,60,47,9.0,7,63,Urban,Software Engineer,113139,1 +86858,Other,21,Bachelors,3,55,26,41,65,3.0,6,58,Semi-Urban,ML Engineer,33401,0 +86859,Female,44,Bachelors,19,3,56,72,67,2.0,0,33,Rural,Software Engineer,72531,0 +86860,Male,52,Masters,15,18,70,13,82,0.0,5,47,Urban,Data Analyst,95372,0 +86861,Female,50,Diploma,10,62,37,74,21,0.0,3,73,Urban,HR Executive,137730,1 +86862,Male,31,Bachelors,19,14,46,59,17,2.0,5,56,Semi-Urban,HR Executive,143540,0 +86863,Female,45,Bachelors,10,36,84,73,56,8.0,1,31,Urban,ML Engineer,103969,0 +86864,Other,54,Diploma,18,60,1,3,56,3.0,0,11,Semi-Urban,Software Engineer,128729,0 +86865,Female,47,Bachelors,4,41,83,70,41,4.0,0,53,Urban,ML Engineer,144623,1 +86866,Male,57,Bachelors,10,3,41,76,66,5.0,7,17,Urban,Data Analyst,103016,0 +86867,Female,50,Diploma,6,93,57,14,68,1.0,3,56,Urban,Manager,119443,0 +86868,Male,56,PhD,18,91,55,97,1,5.0,0,98,Rural,Software Engineer,45702,1 +86869,Male,47,Masters,18,38,14,7,27,2.0,6,63,Urban,Manager,131734,0 +86870,Male,43,Diploma,7,2,61,8,85,9.0,3,17,Urban,ML Engineer,60268,0 +86871,Male,34,PhD,15,32,9,0,87,5.0,3,24,Rural,ML Engineer,34334,0 +86872,Female,41,High School,11,51,95,88,51,3.0,4,98,Semi-Urban,HR Executive,102577,1 +86873,Female,59,Bachelors,5,43,10,91,22,0.0,5,16,Urban,ML Engineer,136449,0 +86874,Male,58,Masters,15,5,98,87,18,8.0,3,59,Semi-Urban,Data Analyst,119545,1 +86875,Male,37,Bachelors,15,89,19,40,49,7.0,6,55,Urban,Manager,77574,0 +86876,Male,29,Diploma,10,17,42,91,55,1.0,7,24,Semi-Urban,Manager,38770,0 +86877,Female,22,Masters,1,76,79,69,79,8.0,2,37,Urban,HR Executive,73615,1 +86878,Female,36,Bachelors,2,69,55,71,42,1.0,7,39,Urban,Manager,47324,0 +86879,Male,35,High School,18,61,81,68,86,0.0,6,28,Urban,ML Engineer,81303,1 +86880,Male,55,Diploma,5,30,68,84,65,2.0,4,56,Urban,ML Engineer,92000,1 +86881,Male,43,Bachelors,5,98,74,54,78,5.0,3,7,Semi-Urban,Manager,115135,0 +86882,Male,36,Masters,1,81,50,35,38,3.0,6,35,Urban,ML Engineer,58347,0 +86883,Male,22,Diploma,0,30,3,91,12,1.0,6,54,Urban,Software Engineer,83139,0 +86884,Male,21,Diploma,10,8,27,20,68,3.0,5,91,Urban,HR Executive,92881,0 +86885,Male,29,Diploma,13,86,98,97,10,5.0,6,41,Urban,HR Executive,47776,1 +86886,Male,32,Masters,6,48,91,74,16,5.0,2,91,Rural,Manager,78435,1 +86887,Other,49,Masters,19,63,3,91,91,5.0,7,0,Semi-Urban,ML Engineer,46952,0 +86888,Female,46,Diploma,15,2,28,27,96,3.0,4,61,Urban,Manager,35073,0 +86889,Female,26,Masters,6,29,77,78,11,0.0,1,12,Semi-Urban,Software Engineer,46326,0 +86890,Male,53,Masters,7,23,44,16,75,9.0,1,82,Semi-Urban,HR Executive,118586,0 +86891,Female,23,Bachelors,12,15,77,34,59,2.0,0,75,Urban,ML Engineer,41660,0 +86892,Other,43,Masters,5,83,20,94,53,8.0,2,40,Urban,Manager,49861,0 +86893,Male,31,High School,7,67,20,46,76,0.0,7,28,Semi-Urban,Software Engineer,64956,0 +86894,Male,24,Bachelors,0,10,25,65,76,2.0,4,39,Urban,HR Executive,119150,0 +86895,Female,27,High School,10,33,41,79,34,0.0,7,73,Urban,Software Engineer,99636,0 +86896,Female,28,Bachelors,13,68,48,79,31,1.0,1,70,Urban,Manager,39192,1 +86897,Female,45,Masters,9,73,33,9,86,9.0,2,7,Semi-Urban,ML Engineer,41376,0 +86898,Male,43,Diploma,19,25,4,22,63,8.0,3,34,Urban,Data Analyst,36303,0 +86899,Male,36,Masters,14,79,34,59,33,0.0,5,91,Urban,Manager,41553,1 +86900,Male,42,High School,12,5,98,59,68,5.0,2,86,Urban,Data Analyst,143057,1 +86901,Male,29,Masters,5,80,44,9,32,5.0,6,60,Urban,ML Engineer,63839,0 +86902,Male,37,Bachelors,5,92,92,28,44,1.0,3,95,Urban,HR Executive,114985,1 +86903,Male,28,Bachelors,1,32,32,73,8,9.0,0,70,Urban,HR Executive,130416,0 +86904,Male,22,Bachelors,5,88,66,13,8,9.0,6,30,Urban,Software Engineer,143848,0 +86905,Male,31,Bachelors,12,58,95,89,55,0.0,2,97,Urban,Software Engineer,40502,1 +86906,Female,38,Masters,9,19,27,81,99,2.0,7,94,Rural,Software Engineer,99839,0 +86907,Male,51,Bachelors,1,62,2,98,76,1.0,3,37,Semi-Urban,Manager,21787,0 +86908,Female,38,Bachelors,3,65,45,7,95,8.0,1,12,Semi-Urban,Software Engineer,127768,0 +86909,Male,49,Masters,0,61,24,92,60,4.0,7,23,Semi-Urban,Manager,141313,0 +86910,Male,49,Bachelors,15,0,31,79,37,7.0,1,75,Urban,ML Engineer,95554,0 +86911,Male,46,Bachelors,8,16,39,69,66,1.0,2,66,Urban,Manager,77605,0 +86912,Other,43,Diploma,0,80,40,73,97,6.0,7,51,Urban,Data Analyst,25627,1 +86913,Male,50,High School,2,70,73,56,51,7.0,5,12,Semi-Urban,HR Executive,144312,0 +86914,Male,45,High School,4,86,91,16,25,6.0,2,44,Urban,Manager,126964,1 +86915,Female,40,Bachelors,12,63,54,4,62,0.0,2,36,Rural,ML Engineer,148705,0 +86916,Male,26,High School,13,69,64,79,26,8.0,5,97,Urban,Manager,126758,1 +86917,Female,28,Bachelors,8,91,59,54,9,2.0,4,87,Urban,Data Analyst,74467,1 +86918,Female,42,Bachelors,18,69,7,63,88,1.0,2,79,Urban,Manager,81105,0 +86919,Female,57,PhD,16,33,57,14,71,7.0,1,12,Urban,Manager,80728,0 +86920,Female,42,Diploma,12,73,64,18,1,0.0,4,47,Urban,ML Engineer,61490,0 +86921,Male,54,Bachelors,19,9,5,78,61,3.0,5,40,Rural,Data Analyst,147741,0 +86922,Male,31,Bachelors,3,90,91,40,10,6.0,4,66,Urban,ML Engineer,85763,1 +86923,Male,48,Diploma,5,58,94,5,49,2.0,1,74,Urban,HR Executive,83697,0 +86924,Female,36,High School,2,86,81,73,12,7.0,4,11,Urban,ML Engineer,96261,1 +86925,Female,56,Masters,13,8,25,80,13,2.0,0,89,Rural,Data Analyst,131268,0 +86926,Other,36,Bachelors,6,46,34,90,65,8.0,6,4,Urban,Manager,52827,0 +86927,Female,24,Bachelors,8,90,80,77,68,7.0,3,28,Urban,HR Executive,86404,1 +86928,Male,46,Masters,7,82,75,67,49,3.0,4,95,Semi-Urban,HR Executive,71040,1 +86929,Male,32,Bachelors,16,61,12,66,33,6.0,0,38,Semi-Urban,Data Analyst,31553,0 +86930,Male,52,Bachelors,2,46,32,23,21,7.0,3,56,Urban,HR Executive,97529,0 +86931,Male,27,Masters,15,95,16,1,9,8.0,5,18,Urban,Manager,139510,0 +86932,Female,41,Bachelors,9,49,17,51,90,3.0,5,84,Semi-Urban,HR Executive,71979,0 +86933,Male,38,PhD,14,66,72,26,66,6.0,7,88,Semi-Urban,ML Engineer,55890,1 +86934,Female,54,Masters,1,6,36,51,72,6.0,5,39,Urban,Data Analyst,114358,0 +86935,Female,21,Bachelors,10,21,53,34,71,1.0,0,50,Semi-Urban,Software Engineer,139037,0 +86936,Female,31,Diploma,12,84,46,77,36,3.0,0,69,Semi-Urban,Data Analyst,88974,1 +86937,Other,46,Bachelors,15,92,98,96,57,1.0,0,37,Rural,Software Engineer,20679,1 +86938,Female,39,High School,13,2,87,25,56,3.0,3,78,Urban,ML Engineer,142770,0 +86939,Female,59,Diploma,15,40,98,20,38,8.0,4,56,Urban,ML Engineer,51956,0 +86940,Male,29,Masters,19,48,91,12,55,1.0,5,75,Semi-Urban,Software Engineer,95905,0 +86941,Female,21,Bachelors,10,53,83,84,62,7.0,2,63,Rural,Manager,116546,1 +86942,Male,32,Bachelors,17,48,83,11,67,0.0,3,55,Urban,ML Engineer,75610,0 +86943,Male,56,Bachelors,2,48,94,93,60,9.0,3,50,Urban,HR Executive,130329,1 +86944,Other,36,Masters,11,22,41,20,92,0.0,5,28,Urban,ML Engineer,111996,0 +86945,Male,56,Bachelors,5,4,87,62,64,4.0,0,99,Urban,Software Engineer,46762,1 +86946,Male,26,Bachelors,9,6,29,20,24,1.0,5,10,Semi-Urban,Software Engineer,85104,0 +86947,Male,28,Masters,3,75,93,56,94,1.0,2,31,Semi-Urban,Data Analyst,25965,1 +86948,Male,34,High School,4,86,50,59,51,4.0,6,90,Rural,Manager,70293,1 +86949,Female,46,Diploma,15,88,16,89,16,5.0,5,54,Urban,Data Analyst,101144,1 +86950,Male,30,Bachelors,2,82,8,58,86,9.0,5,18,Semi-Urban,Software Engineer,125666,0 +86951,Male,31,Bachelors,15,15,49,98,17,5.0,3,76,Semi-Urban,Data Analyst,77504,1 +86952,Female,44,Masters,4,91,58,31,50,9.0,3,16,Rural,Data Analyst,134435,0 +86953,Male,25,Bachelors,6,59,92,93,79,1.0,3,12,Rural,ML Engineer,21712,1 +86954,Male,36,Masters,14,65,47,64,72,5.0,1,63,Urban,Manager,76016,1 +86955,Male,59,Bachelors,10,14,98,71,29,8.0,2,89,Urban,ML Engineer,140609,1 +86956,Male,38,High School,15,90,48,87,4,9.0,3,65,Semi-Urban,Data Analyst,131788,1 +86957,Male,24,Bachelors,5,40,60,21,37,2.0,6,36,Semi-Urban,Manager,88208,0 +86958,Female,44,Masters,19,60,83,7,97,2.0,7,90,Semi-Urban,ML Engineer,138742,0 +86959,Male,50,Bachelors,11,34,64,49,64,5.0,1,72,Urban,HR Executive,110653,0 +86960,Male,32,High School,11,36,3,52,90,3.0,7,14,Rural,ML Engineer,72506,0 +86961,Female,39,Bachelors,9,97,4,12,19,3.0,1,98,Rural,HR Executive,91499,0 +86962,Male,53,Bachelors,12,6,93,3,31,6.0,1,82,Urban,Data Analyst,39243,0 +86963,Male,43,Bachelors,15,75,25,80,31,5.0,4,36,Semi-Urban,Data Analyst,72228,0 +86964,Male,32,Bachelors,8,78,31,18,87,4.0,2,69,Semi-Urban,Software Engineer,59007,0 +86965,Male,58,Diploma,19,81,54,50,21,7.0,2,78,Urban,HR Executive,44545,1 +86966,Male,25,Masters,17,78,80,18,87,4.0,7,93,Urban,Data Analyst,43686,1 +86967,Female,27,Bachelors,0,5,64,52,49,7.0,1,32,Urban,Software Engineer,80574,0 +86968,Male,22,Diploma,0,58,98,86,94,2.0,0,49,Urban,Manager,111999,1 +86969,Female,31,Diploma,3,13,6,98,46,3.0,5,38,Urban,Data Analyst,112364,0 +86970,Female,57,Masters,14,56,86,69,74,4.0,5,6,Urban,Data Analyst,56208,0 +86971,Female,44,Bachelors,4,34,66,60,67,4.0,7,0,Rural,Software Engineer,88856,0 +86972,Female,28,Bachelors,15,28,26,10,13,5.0,0,50,Urban,Software Engineer,110112,0 +86973,Male,53,Diploma,12,5,25,13,48,3.0,3,37,Semi-Urban,HR Executive,54103,0 +86974,Other,25,Masters,16,95,80,46,61,6.0,0,38,Urban,ML Engineer,59391,1 +86975,Male,49,Diploma,19,44,30,55,72,1.0,5,66,Semi-Urban,Manager,35164,0 +86976,Male,34,Bachelors,2,74,40,22,22,2.0,2,87,Urban,HR Executive,105582,0 +86977,Male,33,Bachelors,6,12,36,47,43,1.0,5,42,Semi-Urban,HR Executive,38245,0 +86978,Female,22,Diploma,18,6,32,33,53,8.0,4,40,Semi-Urban,HR Executive,45655,0 +86979,Other,21,Diploma,5,2,16,92,95,7.0,6,53,Semi-Urban,Manager,74529,0 +86980,Male,25,Masters,3,62,52,32,55,8.0,6,40,Urban,Software Engineer,144667,0 +86981,Male,56,Diploma,10,95,1,74,45,5.0,4,92,Urban,Manager,122404,1 +86982,Male,44,Bachelors,15,64,44,24,6,1.0,1,4,Rural,ML Engineer,104728,0 +86983,Male,37,Bachelors,5,71,63,59,83,0.0,4,36,Urban,Software Engineer,33308,0 +86984,Male,44,High School,10,92,18,20,83,6.0,0,56,Urban,Data Analyst,21012,0 +86985,Male,22,Diploma,11,69,90,32,72,6.0,2,8,Semi-Urban,ML Engineer,89276,0 +86986,Female,53,Bachelors,3,32,54,90,93,5.0,2,79,Urban,Software Engineer,27049,1 +86987,Male,59,Masters,7,5,77,72,98,7.0,4,57,Urban,Data Analyst,146141,0 +86988,Male,59,High School,10,1,62,92,30,5.0,5,35,Semi-Urban,Data Analyst,132219,0 +86989,Male,52,Diploma,0,76,99,64,54,8.0,4,78,Semi-Urban,Data Analyst,141109,1 +86990,Female,33,Diploma,11,12,56,83,96,4.0,3,81,Rural,HR Executive,103356,0 +86991,Female,38,Bachelors,3,67,86,9,19,4.0,1,81,Urban,Software Engineer,91171,1 +86992,Male,22,Diploma,19,97,10,48,47,7.0,1,82,Urban,Software Engineer,54205,1 +86993,Female,43,Masters,9,84,48,2,0,5.0,3,54,Urban,Data Analyst,134459,0 +86994,Male,48,Bachelors,0,48,92,45,70,0.0,3,57,Rural,Manager,85505,1 +86995,Male,27,Diploma,7,53,89,60,18,0.0,0,35,Semi-Urban,Software Engineer,61347,1 +86996,Male,40,Diploma,10,62,35,48,7,5.0,2,1,Rural,Manager,71626,0 +86997,Female,33,Masters,12,64,24,25,74,6.0,2,11,Urban,Software Engineer,63105,0 +86998,Female,31,Bachelors,13,65,53,95,16,6.0,7,44,Semi-Urban,Manager,30856,1 +86999,Male,47,Bachelors,6,66,92,78,35,2.0,6,3,Semi-Urban,Data Analyst,55169,1 +87000,Female,53,Diploma,5,83,10,33,78,2.0,0,14,Rural,Software Engineer,28496,0 +87001,Female,37,Diploma,3,42,78,4,88,4.0,3,97,Rural,Data Analyst,72628,0 +87002,Female,39,Bachelors,12,89,98,33,47,9.0,5,63,Semi-Urban,Manager,22235,1 +87003,Male,41,Bachelors,15,25,1,62,81,5.0,1,40,Semi-Urban,Software Engineer,102267,0 +87004,Male,53,PhD,0,10,8,24,6,7.0,4,11,Semi-Urban,Manager,71206,0 +87005,Male,33,Diploma,0,74,44,85,54,4.0,2,27,Rural,Manager,92987,0 +87006,Male,28,Masters,13,45,77,15,76,9.0,2,44,Urban,Data Analyst,37378,0 +87007,Female,55,Bachelors,0,5,76,43,14,7.0,4,95,Semi-Urban,HR Executive,75510,0 +87008,Male,55,Masters,19,46,91,37,66,5.0,6,10,Urban,Data Analyst,115018,0 +87009,Male,58,Bachelors,13,14,35,24,28,1.0,1,91,Urban,Manager,34953,0 +87010,Female,39,Diploma,10,19,19,87,13,9.0,0,64,Semi-Urban,Software Engineer,117803,0 +87011,Female,22,Bachelors,0,18,88,25,26,8.0,4,14,Urban,Software Engineer,62503,0 +87012,Male,23,Diploma,0,70,22,3,8,4.0,5,20,Urban,ML Engineer,85547,0 +87013,Male,22,Diploma,11,71,56,87,96,1.0,7,0,Urban,Software Engineer,26728,0 +87014,Male,28,High School,2,61,6,68,48,7.0,3,89,Urban,Software Engineer,59392,0 +87015,Male,27,PhD,11,74,77,47,62,2.0,6,82,Urban,Manager,135064,1 +87016,Female,42,Bachelors,0,9,25,14,60,3.0,2,93,Urban,HR Executive,26092,0 +87017,Male,44,PhD,8,38,19,73,8,2.0,6,18,Urban,Data Analyst,73691,0 +87018,Male,50,Diploma,19,88,49,60,49,0.0,4,98,Rural,Software Engineer,20742,1 +87019,Male,31,Bachelors,18,70,18,12,65,6.0,3,54,Rural,HR Executive,54304,0 +87020,Female,27,Diploma,15,61,10,77,40,4.0,3,9,Urban,Manager,30242,0 +87021,Female,45,Bachelors,10,50,82,95,88,3.0,3,94,Semi-Urban,ML Engineer,56276,1 +87022,Male,35,Bachelors,14,9,20,28,61,8.0,2,51,Urban,Software Engineer,75990,0 +87023,Male,21,Masters,15,70,58,77,3,7.0,4,47,Urban,Manager,126373,1 +87024,Female,38,Masters,0,22,8,54,99,6.0,7,8,Semi-Urban,Software Engineer,65299,0 +87025,Male,39,Masters,5,18,56,99,76,1.0,2,60,Rural,Data Analyst,78125,0 +87026,Male,27,Bachelors,9,73,93,79,17,8.0,5,7,Urban,ML Engineer,49468,1 +87027,Male,34,Diploma,0,87,2,12,63,6.0,6,75,Semi-Urban,Data Analyst,145290,0 +87028,Male,53,Bachelors,12,67,92,5,88,1.0,1,39,Rural,Data Analyst,95443,0 +87029,Male,28,Bachelors,5,62,33,46,81,6.0,3,94,Urban,Manager,84963,1 +87030,Male,53,Bachelors,1,76,56,45,27,8.0,1,92,Urban,Manager,36579,1 +87031,Female,24,Bachelors,3,95,84,5,44,9.0,7,70,Urban,HR Executive,138038,1 +87032,Male,42,Bachelors,11,44,2,13,86,0.0,5,87,Urban,Software Engineer,47374,0 +87033,Male,31,Diploma,14,68,99,72,49,3.0,5,29,Semi-Urban,Software Engineer,108830,1 +87034,Female,38,Bachelors,19,24,55,89,53,6.0,0,71,Rural,HR Executive,126613,0 +87035,Female,23,PhD,18,25,4,58,64,3.0,6,77,Rural,Software Engineer,73182,0 +87036,Other,23,Diploma,19,5,83,28,91,0.0,5,90,Urban,ML Engineer,97648,0 +87037,Other,58,Diploma,8,37,59,53,77,9.0,0,82,Semi-Urban,Software Engineer,55975,0 +87038,Male,52,High School,15,7,81,26,68,5.0,2,50,Urban,HR Executive,149238,0 +87039,Female,33,Diploma,1,3,92,47,9,6.0,5,74,Urban,HR Executive,29573,0 +87040,Male,40,Bachelors,18,60,71,47,88,5.0,7,75,Semi-Urban,Data Analyst,75902,1 +87041,Male,39,Diploma,3,54,28,72,45,6.0,4,55,Rural,Manager,77047,0 +87042,Male,35,Bachelors,2,52,50,7,69,2.0,0,74,Urban,ML Engineer,132496,0 +87043,Female,45,Masters,6,31,79,56,61,1.0,6,41,Urban,HR Executive,65593,0 +87044,Male,50,High School,10,38,23,59,67,2.0,7,56,Urban,Manager,50814,0 +87045,Male,37,Masters,3,52,93,30,60,1.0,1,28,Urban,Data Analyst,40321,0 +87046,Male,26,Masters,9,41,71,11,49,9.0,2,76,Urban,ML Engineer,45753,0 +87047,Female,57,Bachelors,14,39,94,92,44,2.0,2,41,Semi-Urban,Data Analyst,52392,1 +87048,Male,54,Masters,4,95,73,32,99,7.0,5,88,Rural,HR Executive,34084,1 +87049,Female,32,Masters,16,1,9,92,18,3.0,0,86,Semi-Urban,Manager,37271,0 +87050,Female,50,Bachelors,11,68,64,20,95,4.0,4,59,Semi-Urban,HR Executive,55830,0 +87051,Male,24,Diploma,9,46,86,50,42,6.0,3,83,Urban,ML Engineer,98205,1 +87052,Female,28,Bachelors,14,6,19,96,48,0.0,2,18,Semi-Urban,Manager,131465,0 +87053,Male,41,Bachelors,9,53,7,48,86,0.0,2,86,Urban,ML Engineer,20333,0 +87054,Female,55,High School,4,66,92,86,1,2.0,2,42,Urban,Manager,119527,1 +87055,Male,55,Bachelors,15,6,21,86,13,2.0,2,28,Urban,Software Engineer,118274,0 +87056,Female,30,Masters,6,19,52,89,53,8.0,4,56,Urban,HR Executive,102281,0 +87057,Other,22,Bachelors,19,52,90,72,78,3.0,5,64,Urban,HR Executive,123238,1 +87058,Male,39,Bachelors,10,23,91,8,42,7.0,1,37,Semi-Urban,Manager,82083,0 +87059,Male,36,Bachelors,5,13,62,15,86,2.0,6,96,Rural,Manager,106783,0 +87060,Female,53,Diploma,3,34,10,86,85,1.0,1,59,Semi-Urban,HR Executive,86590,0 +87061,Male,45,High School,9,67,12,53,21,1.0,0,36,Semi-Urban,Software Engineer,148901,0 +87062,Other,48,Bachelors,6,67,94,5,70,3.0,7,89,Rural,ML Engineer,49016,1 +87063,Female,39,Masters,10,64,94,88,30,9.0,4,22,Semi-Urban,Manager,33396,1 +87064,Female,39,Bachelors,10,39,14,79,66,3.0,3,74,Urban,HR Executive,24140,0 +87065,Female,25,Masters,0,54,17,8,43,3.0,7,97,Semi-Urban,Manager,46827,0 +87066,Male,49,PhD,18,98,46,81,10,1.0,0,8,Urban,Data Analyst,81276,0 +87067,Female,23,High School,6,11,60,32,47,4.0,5,76,Urban,HR Executive,35299,0 +87068,Male,29,Masters,7,13,95,23,17,9.0,7,96,Urban,Software Engineer,64648,0 +87069,Male,37,Bachelors,18,83,13,29,60,8.0,1,19,Semi-Urban,ML Engineer,141235,0 +87070,Male,45,PhD,3,58,34,12,95,5.0,7,54,Rural,ML Engineer,142598,0 +87071,Male,31,Bachelors,11,34,22,49,41,9.0,5,36,Urban,Software Engineer,47373,0 +87072,Male,56,Bachelors,8,90,69,11,14,7.0,0,12,Semi-Urban,Manager,99140,0 +87073,Female,37,PhD,4,9,10,24,1,2.0,0,18,Semi-Urban,Manager,135422,0 +87074,Female,57,High School,14,82,22,33,68,6.0,3,33,Urban,Software Engineer,63403,0 +87075,Male,45,PhD,4,36,72,55,5,5.0,1,10,Rural,Data Analyst,92847,0 +87076,Other,27,Bachelors,14,64,61,8,29,3.0,6,56,Rural,Manager,121825,0 +87077,Female,48,Diploma,4,65,64,78,77,2.0,0,56,Urban,HR Executive,77951,1 +87078,Male,38,Masters,11,85,87,44,36,0.0,7,54,Urban,HR Executive,48443,1 +87079,Male,59,High School,19,14,38,36,67,4.0,1,83,Urban,Data Analyst,119826,0 +87080,Male,58,Diploma,2,1,12,34,22,9.0,2,8,Semi-Urban,HR Executive,80560,0 +87081,Male,49,Bachelors,6,79,52,2,29,6.0,4,84,Urban,Manager,112000,0 +87082,Male,25,High School,15,96,56,78,7,6.0,6,48,Semi-Urban,Data Analyst,34020,1 +87083,Male,33,Bachelors,19,90,80,62,88,1.0,0,99,Rural,Manager,138148,1 +87084,Male,37,Bachelors,8,11,15,57,42,3.0,2,86,Semi-Urban,ML Engineer,121625,0 +87085,Other,34,PhD,4,68,90,90,53,7.0,3,74,Urban,HR Executive,134103,1 +87086,Male,47,Masters,4,96,28,68,28,7.0,5,74,Urban,HR Executive,114253,1 +87087,Male,39,PhD,9,76,68,6,13,2.0,1,92,Rural,HR Executive,92562,1 +87088,Female,37,Bachelors,5,88,73,13,50,8.0,5,79,Urban,HR Executive,64167,1 +87089,Male,27,High School,5,48,70,20,9,2.0,3,38,Urban,Manager,141092,0 +87090,Female,58,Masters,8,54,48,45,79,9.0,4,81,Semi-Urban,Manager,91352,0 +87091,Female,26,PhD,8,12,41,18,92,1.0,3,49,Semi-Urban,ML Engineer,73401,0 +87092,Male,52,Diploma,15,15,28,75,13,9.0,2,46,Rural,ML Engineer,48229,0 +87093,Male,48,Diploma,16,71,96,83,65,3.0,7,79,Rural,Data Analyst,26156,1 +87094,Male,58,Bachelors,8,47,64,92,58,9.0,7,83,Urban,Data Analyst,20956,1 +87095,Female,47,Bachelors,5,21,41,54,59,8.0,0,39,Urban,Manager,46554,0 +87096,Female,25,PhD,8,97,42,67,89,7.0,3,8,Urban,ML Engineer,147725,0 +87097,Female,41,Masters,16,71,40,5,64,5.0,2,24,Urban,HR Executive,140344,0 +87098,Female,55,Bachelors,5,51,43,70,29,1.0,0,57,Urban,Data Analyst,136265,0 +87099,Male,56,Diploma,17,80,6,10,30,5.0,1,99,Semi-Urban,Manager,125125,0 +87100,Female,28,Masters,8,33,70,70,4,7.0,5,36,Semi-Urban,HR Executive,20774,0 +87101,Female,30,Masters,7,36,34,99,78,6.0,5,82,Semi-Urban,ML Engineer,95381,1 +87102,Female,26,Diploma,11,30,77,79,23,2.0,1,45,Urban,Software Engineer,123139,0 +87103,Male,37,Masters,13,78,80,2,52,9.0,2,82,Urban,Software Engineer,60323,1 +87104,Male,21,Masters,13,64,90,80,51,6.0,7,77,Rural,HR Executive,137268,1 +87105,Male,24,Bachelors,1,59,52,27,58,3.0,2,20,Urban,Software Engineer,99424,0 +87106,Male,38,Masters,0,37,76,63,77,9.0,1,54,Urban,Manager,83730,0 +87107,Male,58,Masters,2,96,52,37,72,6.0,2,18,Rural,Manager,76381,0 +87108,Male,36,High School,4,43,80,62,85,8.0,7,0,Semi-Urban,Software Engineer,59829,0 +87109,Male,42,Bachelors,0,71,96,43,27,1.0,6,21,Urban,HR Executive,119116,0 +87110,Female,38,Masters,13,54,46,9,76,5.0,0,96,Urban,HR Executive,108699,0 +87111,Male,51,High School,13,57,24,81,50,3.0,2,53,Urban,Manager,65847,0 +87112,Male,56,Diploma,14,71,66,5,87,9.0,6,30,Rural,Data Analyst,59815,0 +87113,Female,24,Diploma,7,30,3,40,86,3.0,4,41,Urban,Data Analyst,126706,0 +87114,Female,50,Bachelors,10,12,74,65,99,6.0,2,72,Rural,Software Engineer,33825,0 +87115,Female,29,Masters,9,95,8,41,68,6.0,4,64,Urban,Software Engineer,119354,0 +87116,Female,32,Bachelors,10,49,45,13,17,8.0,5,30,Semi-Urban,Manager,130934,0 +87117,Female,48,Diploma,3,7,59,13,56,0.0,2,21,Rural,Software Engineer,105167,0 +87118,Female,32,Bachelors,0,4,29,12,78,8.0,4,90,Urban,Software Engineer,91587,0 +87119,Female,24,Diploma,12,89,34,59,51,3.0,4,61,Semi-Urban,Manager,34109,1 +87120,Female,56,High School,12,16,36,56,98,9.0,6,16,Urban,ML Engineer,37353,0 +87121,Male,57,Bachelors,14,35,53,70,36,5.0,2,54,Urban,HR Executive,35094,0 +87122,Male,50,Bachelors,2,33,49,50,44,6.0,4,52,Urban,Manager,68982,0 +87123,Female,31,Diploma,10,25,99,4,76,4.0,3,18,Urban,HR Executive,38998,0 +87124,Male,44,Bachelors,10,23,93,30,37,1.0,5,14,Urban,Manager,97372,0 +87125,Female,41,Bachelors,14,48,21,16,40,6.0,3,8,Urban,ML Engineer,103965,0 +87126,Male,50,Bachelors,8,26,75,22,77,8.0,1,91,Urban,HR Executive,126725,0 +87127,Female,40,Masters,10,45,97,74,58,8.0,5,83,Urban,Software Engineer,37363,1 +87128,Male,47,Diploma,8,49,78,69,1,0.0,7,37,Rural,ML Engineer,125474,0 +87129,Male,40,Bachelors,17,33,46,60,88,2.0,1,27,Semi-Urban,Data Analyst,48624,0 +87130,Male,54,Bachelors,12,40,89,15,77,6.0,4,58,Urban,ML Engineer,75253,0 +87131,Male,45,Bachelors,3,83,32,75,10,5.0,2,46,Urban,ML Engineer,48250,1 +87132,Male,24,PhD,14,35,96,51,51,4.0,1,79,Rural,Manager,124276,1 +87133,Male,34,Bachelors,3,94,65,81,60,8.0,5,94,Urban,ML Engineer,142430,1 +87134,Female,53,Bachelors,1,59,1,58,50,5.0,6,97,Urban,HR Executive,124408,0 +87135,Male,52,Bachelors,0,57,10,30,11,5.0,2,80,Semi-Urban,HR Executive,131040,0 +87136,Female,48,Bachelors,3,85,24,6,62,9.0,1,21,Rural,Software Engineer,90970,0 +87137,Other,37,Diploma,10,92,59,29,66,3.0,5,39,Semi-Urban,Software Engineer,86048,0 +87138,Male,29,Bachelors,8,15,49,94,29,2.0,4,81,Urban,ML Engineer,121933,1 +87139,Female,22,High School,18,84,91,40,25,5.0,7,22,Urban,Data Analyst,50865,0 +87140,Male,30,Masters,11,17,84,24,54,1.0,7,15,Urban,Manager,98942,0 +87141,Male,40,High School,3,94,27,77,83,5.0,5,95,Urban,ML Engineer,109108,1 +87142,Male,40,Masters,15,11,84,57,75,4.0,0,21,Semi-Urban,Software Engineer,68503,0 +87143,Male,43,Bachelors,19,95,83,39,15,9.0,4,21,Urban,HR Executive,24317,1 +87144,Female,57,Bachelors,5,57,11,18,30,4.0,6,64,Rural,HR Executive,82138,0 +87145,Male,30,Masters,0,34,38,10,24,6.0,3,79,Semi-Urban,Data Analyst,50320,0 +87146,Male,59,Bachelors,6,69,12,33,88,9.0,6,2,Semi-Urban,HR Executive,118786,0 +87147,Female,39,Masters,16,63,77,99,59,2.0,0,97,Rural,HR Executive,51964,1 +87148,Male,52,Diploma,19,72,57,71,22,0.0,7,53,Semi-Urban,Data Analyst,116399,1 +87149,Female,41,Masters,18,89,38,70,74,2.0,6,29,Rural,ML Engineer,91622,0 +87150,Other,50,Bachelors,9,51,60,81,89,3.0,3,80,Urban,Data Analyst,94753,1 +87151,Female,49,Masters,1,57,78,31,11,2.0,1,6,Rural,ML Engineer,36262,0 +87152,Male,28,PhD,12,64,29,9,87,3.0,1,71,Rural,HR Executive,143882,0 +87153,Male,24,Bachelors,2,20,49,28,28,6.0,1,8,Urban,Software Engineer,83490,0 +87154,Male,40,Bachelors,18,86,53,49,10,2.0,1,62,Rural,Manager,105693,1 +87155,Male,46,High School,2,38,23,36,0,0.0,6,98,Urban,Manager,134668,0 +87156,Female,52,Bachelors,0,2,59,84,24,0.0,4,85,Rural,Software Engineer,83498,0 +87157,Female,30,Bachelors,10,33,36,94,7,9.0,1,70,Rural,Manager,106586,0 +87158,Male,46,Bachelors,6,17,73,27,8,9.0,6,91,Urban,ML Engineer,132506,0 +87159,Male,32,Masters,11,41,44,10,45,8.0,1,51,Semi-Urban,Data Analyst,36490,0 +87160,Female,58,Masters,11,86,48,30,48,8.0,1,27,Urban,Manager,132396,0 +87161,Female,43,High School,13,61,71,4,67,5.0,4,22,Urban,Manager,53876,0 +87162,Male,33,Masters,12,86,97,92,75,7.0,0,70,Urban,Software Engineer,89964,1 +87163,Female,43,High School,18,0,8,87,34,7.0,5,26,Urban,Software Engineer,66967,0 +87164,Other,46,High School,8,13,88,75,88,0.0,4,77,Urban,Data Analyst,37388,1 +87165,Male,37,Bachelors,3,85,99,60,32,8.0,5,68,Urban,Data Analyst,95105,1 +87166,Male,27,High School,13,85,8,59,6,9.0,2,37,Rural,Data Analyst,42938,0 +87167,Female,39,High School,1,5,60,24,1,1.0,4,60,Urban,Manager,70729,0 +87168,Male,59,Bachelors,6,29,77,94,63,6.0,7,34,Semi-Urban,ML Engineer,67335,0 +87169,Female,50,Bachelors,8,93,54,96,55,1.0,3,42,Urban,Software Engineer,133611,1 +87170,Male,55,Bachelors,8,53,17,46,79,7.0,5,69,Rural,Data Analyst,20939,0 +87171,Male,33,Bachelors,19,70,55,87,52,4.0,1,84,Semi-Urban,Data Analyst,119381,1 +87172,Male,21,Bachelors,13,88,88,54,29,9.0,5,14,Urban,Data Analyst,63971,1 +87173,Male,27,Bachelors,0,30,74,33,93,5.0,4,38,Semi-Urban,HR Executive,87574,0 +87174,Male,49,Masters,7,47,28,64,18,6.0,2,32,Urban,Data Analyst,62182,0 +87175,Male,56,Diploma,13,10,8,14,31,5.0,2,66,Rural,Manager,95145,0 +87176,Male,57,Masters,18,9,77,46,79,7.0,0,85,Urban,Software Engineer,49660,0 +87177,Male,33,Bachelors,17,68,44,14,62,2.0,2,13,Urban,Software Engineer,132156,0 +87178,Male,56,Diploma,13,82,1,75,68,9.0,5,0,Rural,Data Analyst,33569,0 +87179,Male,43,High School,15,18,61,65,3,3.0,4,52,Urban,HR Executive,57600,0 +87180,Other,28,Masters,14,1,15,76,90,7.0,5,37,Urban,Data Analyst,77653,0 +87181,Male,28,Bachelors,18,83,24,81,80,2.0,4,68,Urban,Data Analyst,110928,1 +87182,Female,59,Masters,7,0,47,96,80,6.0,0,93,Semi-Urban,Data Analyst,28277,0 +87183,Male,23,Masters,0,45,52,54,87,2.0,1,23,Semi-Urban,Software Engineer,149238,0 +87184,Male,43,PhD,16,89,67,7,26,9.0,3,32,Urban,Software Engineer,54392,0 +87185,Male,50,High School,7,11,84,89,44,8.0,5,83,Urban,Manager,122889,1 +87186,Male,52,Diploma,10,27,40,35,13,8.0,0,5,Semi-Urban,Software Engineer,28940,0 +87187,Female,38,Bachelors,16,41,50,22,38,9.0,3,4,Semi-Urban,HR Executive,125713,0 +87188,Other,40,Masters,19,42,14,37,78,5.0,0,35,Urban,Manager,44848,0 +87189,Male,28,Bachelors,9,77,42,88,49,8.0,4,6,Urban,HR Executive,82267,0 +87190,Male,33,Bachelors,12,47,74,69,55,7.0,5,64,Urban,HR Executive,128287,1 +87191,Male,43,Diploma,6,80,26,27,97,9.0,2,47,Urban,Manager,140020,0 +87192,Female,44,High School,3,65,55,24,78,4.0,6,30,Rural,Software Engineer,147557,0 +87193,Male,24,Bachelors,19,33,95,7,97,6.0,7,77,Urban,Data Analyst,79122,0 +87194,Female,59,Diploma,11,7,19,31,94,4.0,0,11,Urban,HR Executive,92614,0 +87195,Male,41,High School,5,24,87,87,55,5.0,2,82,Urban,ML Engineer,96772,1 +87196,Male,54,Masters,16,27,22,6,6,2.0,3,92,Rural,Manager,101560,0 +87197,Male,33,Bachelors,15,14,7,61,24,8.0,2,65,Semi-Urban,Software Engineer,53552,0 +87198,Female,22,Masters,9,3,13,12,26,4.0,1,77,Semi-Urban,Data Analyst,67086,0 +87199,Female,47,Bachelors,10,63,64,21,25,2.0,5,37,Semi-Urban,Manager,123722,0 +87200,Male,58,High School,4,90,64,42,42,9.0,4,86,Urban,ML Engineer,38746,1 +87201,Male,37,PhD,13,18,64,25,69,9.0,3,90,Rural,Data Analyst,125427,0 +87202,Male,29,Masters,10,12,37,81,0,5.0,1,54,Urban,Manager,129418,0 +87203,Male,29,Masters,10,83,76,60,20,2.0,3,72,Semi-Urban,Software Engineer,20339,1 +87204,Male,27,Bachelors,11,77,39,49,80,4.0,5,52,Semi-Urban,HR Executive,120937,0 +87205,Female,46,PhD,7,34,70,92,66,3.0,6,28,Semi-Urban,Data Analyst,29423,0 +87206,Male,31,Bachelors,1,79,1,9,46,0.0,7,44,Urban,Software Engineer,54054,0 +87207,Female,50,High School,17,9,11,88,75,3.0,5,66,Urban,ML Engineer,113374,0 +87208,Female,29,Diploma,4,94,17,34,78,9.0,4,33,Semi-Urban,Manager,67191,0 +87209,Male,44,Bachelors,8,81,61,93,80,6.0,6,38,Rural,Software Engineer,49570,1 +87210,Female,50,Bachelors,8,28,68,66,29,0.0,4,30,Urban,Manager,115300,0 +87211,Male,40,Bachelors,8,58,19,28,64,2.0,7,61,Urban,Manager,145885,0 +87212,Male,38,Bachelors,16,23,51,57,35,4.0,2,39,Urban,ML Engineer,103601,0 +87213,Female,38,High School,15,1,61,52,66,2.0,3,11,Urban,Manager,96682,0 +87214,Male,29,Masters,1,75,37,64,72,8.0,2,95,Urban,HR Executive,61947,1 +87215,Male,28,Diploma,10,16,54,32,20,8.0,6,42,Rural,Software Engineer,131533,0 +87216,Male,22,Diploma,15,76,85,85,31,0.0,7,43,Urban,Manager,50818,1 +87217,Female,39,Bachelors,1,12,70,82,13,4.0,3,0,Urban,Data Analyst,73430,0 +87218,Other,50,Bachelors,1,15,15,59,84,0.0,6,96,Urban,ML Engineer,130709,0 +87219,Female,27,High School,7,4,65,23,20,9.0,6,33,Urban,Data Analyst,71572,0 +87220,Other,58,Masters,9,64,89,62,90,7.0,1,90,Semi-Urban,HR Executive,40342,1 +87221,Female,29,Diploma,5,59,56,14,87,5.0,2,71,Urban,Data Analyst,133347,0 +87222,Male,55,Bachelors,9,0,36,21,54,8.0,7,75,Urban,Manager,80239,0 +87223,Male,22,Bachelors,19,40,80,28,11,8.0,4,5,Semi-Urban,ML Engineer,62482,0 +87224,Female,47,Masters,14,1,79,41,20,3.0,3,51,Urban,Software Engineer,40681,0 +87225,Male,32,Bachelors,1,5,94,96,78,3.0,5,99,Semi-Urban,ML Engineer,95143,1 +87226,Male,39,Bachelors,15,60,57,44,18,8.0,3,34,Semi-Urban,ML Engineer,34809,0 +87227,Female,33,Diploma,16,45,27,74,76,0.0,2,80,Urban,ML Engineer,146244,0 +87228,Male,25,High School,3,66,41,90,98,1.0,0,88,Urban,Data Analyst,53326,1 +87229,Female,32,High School,4,33,77,0,66,6.0,4,18,Urban,ML Engineer,80872,0 +87230,Male,32,Bachelors,6,2,40,46,65,6.0,7,31,Urban,Manager,65721,0 +87231,Male,49,Diploma,7,28,22,52,72,9.0,0,6,Urban,Software Engineer,141730,0 +87232,Male,31,Diploma,8,3,33,94,45,2.0,7,26,Urban,Manager,148557,0 +87233,Female,39,PhD,14,74,59,99,54,1.0,7,67,Semi-Urban,HR Executive,56608,1 +87234,Male,30,Masters,10,1,88,88,76,1.0,2,42,Urban,ML Engineer,64006,0 +87235,Male,23,Bachelors,4,34,98,97,35,1.0,0,29,Semi-Urban,ML Engineer,141340,1 +87236,Female,34,High School,0,38,27,34,27,6.0,2,39,Urban,Data Analyst,146099,0 +87237,Male,37,Bachelors,4,32,7,48,1,4.0,4,31,Semi-Urban,ML Engineer,70569,0 +87238,Female,25,Bachelors,5,50,72,85,42,4.0,7,89,Urban,Software Engineer,62620,1 +87239,Male,51,Bachelors,3,68,64,9,87,9.0,1,22,Urban,HR Executive,147665,0 +87240,Other,37,Bachelors,14,44,90,80,55,9.0,4,79,Semi-Urban,HR Executive,74218,1 +87241,Male,34,Masters,7,27,55,79,61,9.0,5,98,Semi-Urban,Software Engineer,105099,1 +87242,Male,31,High School,1,76,68,70,84,3.0,4,72,Urban,ML Engineer,108785,1 +87243,Female,34,High School,13,93,29,90,89,8.0,0,37,Urban,HR Executive,74863,1 +87244,Female,43,Bachelors,7,98,79,21,16,1.0,0,95,Urban,ML Engineer,72869,1 +87245,Male,21,Bachelors,1,98,13,42,93,0.0,1,69,Urban,HR Executive,39301,0 +87246,Female,54,Bachelors,11,9,78,79,92,9.0,0,44,Urban,Data Analyst,78228,0 +87247,Male,35,High School,12,2,26,66,14,9.0,5,34,Urban,HR Executive,26095,0 +87248,Other,36,Diploma,2,64,41,89,92,8.0,4,18,Urban,Software Engineer,52342,0 +87249,Male,42,Diploma,12,65,37,44,58,5.0,6,48,Semi-Urban,Manager,109283,0 +87250,Male,50,Masters,18,75,89,15,64,0.0,4,85,Rural,ML Engineer,131004,1 +87251,Male,26,Diploma,4,58,43,90,9,3.0,6,34,Semi-Urban,HR Executive,77950,0 +87252,Female,24,Bachelors,16,58,47,89,55,5.0,3,1,Urban,Data Analyst,70505,0 +87253,Female,57,High School,11,6,69,71,29,8.0,0,56,Urban,HR Executive,29639,0 +87254,Male,45,Bachelors,6,29,98,7,7,1.0,0,68,Urban,ML Engineer,34542,0 +87255,Male,35,Bachelors,17,18,88,51,37,4.0,3,12,Urban,HR Executive,138706,0 +87256,Male,52,PhD,3,69,74,13,44,6.0,6,76,Urban,Software Engineer,115135,0 +87257,Female,59,Bachelors,0,55,63,12,93,0.0,0,28,Urban,Manager,124254,0 +87258,Female,40,Diploma,6,81,94,35,60,8.0,2,37,Rural,HR Executive,73509,1 +87259,Female,40,Bachelors,16,17,79,38,37,6.0,0,20,Semi-Urban,ML Engineer,30481,0 +87260,Female,58,High School,7,45,23,12,58,3.0,7,43,Urban,HR Executive,47762,0 +87261,Male,23,Masters,10,77,64,69,93,3.0,3,24,Urban,Software Engineer,95677,0 +87262,Male,55,Diploma,10,9,85,70,68,2.0,4,50,Semi-Urban,ML Engineer,103983,0 +87263,Female,29,Diploma,11,75,79,24,71,4.0,3,64,Rural,ML Engineer,79579,1 +87264,Male,33,Diploma,13,36,37,89,63,9.0,1,97,Semi-Urban,HR Executive,30879,1 +87265,Female,55,Bachelors,3,75,86,13,22,6.0,3,29,Urban,Data Analyst,40530,0 +87266,Male,32,Bachelors,4,68,4,86,22,3.0,2,44,Semi-Urban,HR Executive,82975,0 +87267,Male,50,Bachelors,1,38,96,14,64,7.0,3,86,Rural,ML Engineer,79290,0 +87268,Male,59,Masters,10,68,20,39,17,5.0,4,28,Urban,Software Engineer,73117,0 +87269,Male,33,Bachelors,3,3,85,93,94,6.0,0,61,Urban,HR Executive,121755,1 +87270,Male,40,Diploma,9,82,44,60,24,1.0,1,7,Urban,Manager,66154,0 +87271,Male,53,Diploma,9,25,98,52,64,3.0,6,39,Urban,HR Executive,63148,0 +87272,Male,32,Diploma,5,22,57,57,16,4.0,2,56,Urban,Manager,43558,0 +87273,Male,33,High School,2,97,53,44,57,6.0,2,76,Semi-Urban,ML Engineer,22734,1 +87274,Male,50,Bachelors,11,18,15,99,97,5.0,0,7,Urban,ML Engineer,79491,0 +87275,Male,35,Bachelors,13,14,57,36,78,2.0,2,17,Rural,Manager,34442,0 +87276,Male,21,High School,14,23,31,69,70,9.0,2,35,Rural,ML Engineer,124056,0 +87277,Female,45,Bachelors,5,96,58,58,89,9.0,3,40,Rural,Software Engineer,82964,1 +87278,Female,26,Bachelors,15,65,1,45,0,0.0,0,38,Urban,Software Engineer,137309,0 +87279,Female,31,Diploma,8,27,12,49,57,7.0,0,61,Urban,HR Executive,71488,0 +87280,Other,58,Bachelors,18,50,52,91,5,8.0,6,20,Urban,Data Analyst,144919,0 +87281,Male,27,Diploma,17,52,10,59,74,8.0,7,52,Rural,Data Analyst,113950,0 +87282,Female,37,High School,9,98,93,76,84,6.0,2,31,Urban,Manager,124530,1 +87283,Male,23,Bachelors,14,92,54,94,3,3.0,2,75,Rural,Software Engineer,130341,1 +87284,Female,53,Diploma,11,65,6,74,85,8.0,2,21,Rural,HR Executive,86954,0 +87285,Male,48,High School,2,88,45,72,64,6.0,4,35,Rural,Software Engineer,28831,1 +87286,Male,54,High School,13,40,42,8,77,2.0,7,21,Urban,HR Executive,56869,0 +87287,Other,46,High School,6,76,87,55,94,1.0,6,76,Urban,Data Analyst,146760,1 +87288,Female,38,Masters,4,68,83,73,86,0.0,1,61,Urban,ML Engineer,70933,1 +87289,Male,24,Bachelors,10,15,0,85,69,6.0,6,25,Semi-Urban,Data Analyst,34560,0 +87290,Male,55,Bachelors,7,64,13,68,34,8.0,5,29,Rural,Manager,46050,0 +87291,Female,45,High School,12,34,61,65,37,7.0,5,9,Rural,Software Engineer,90411,0 +87292,Male,21,Diploma,1,62,14,97,93,8.0,2,98,Urban,Manager,118756,1 +87293,Female,56,Bachelors,8,56,59,19,90,7.0,4,99,Rural,Manager,57578,0 +87294,Female,53,Diploma,12,90,74,23,60,0.0,2,25,Urban,HR Executive,41794,0 +87295,Male,23,Bachelors,8,39,16,7,62,3.0,5,48,Semi-Urban,HR Executive,141043,0 +87296,Male,44,Bachelors,4,86,31,91,98,0.0,4,69,Urban,HR Executive,41332,1 +87297,Male,43,Bachelors,9,67,30,30,59,4.0,4,28,Rural,HR Executive,30814,0 +87298,Male,26,Bachelors,2,51,44,92,75,1.0,6,28,Urban,Data Analyst,87627,0 +87299,Male,29,Diploma,8,6,54,98,36,4.0,7,34,Semi-Urban,Data Analyst,145823,0 +87300,Female,37,Diploma,19,82,5,34,64,7.0,4,44,Urban,ML Engineer,124682,0 +87301,Male,36,Bachelors,14,27,8,95,21,6.0,1,10,Urban,ML Engineer,60852,0 +87302,Male,31,Diploma,10,88,62,88,72,8.0,4,32,Urban,Data Analyst,82779,1 +87303,Male,36,Masters,9,91,1,18,85,3.0,6,11,Urban,HR Executive,32711,0 +87304,Male,47,Masters,9,89,58,49,12,5.0,4,38,Rural,Data Analyst,56179,0 +87305,Male,48,Bachelors,1,97,58,71,8,9.0,4,39,Urban,ML Engineer,106707,1 +87306,Female,48,High School,4,3,8,26,53,1.0,7,72,Urban,Data Analyst,80412,0 +87307,Male,57,Bachelors,3,29,17,60,47,0.0,7,60,Urban,HR Executive,84414,0 +87308,Female,22,Masters,11,54,37,59,82,3.0,5,69,Urban,Software Engineer,49686,0 +87309,Male,55,Bachelors,14,1,59,60,95,1.0,5,72,Urban,HR Executive,95572,0 +87310,Female,44,High School,14,73,34,40,12,5.0,0,50,Urban,ML Engineer,128743,0 +87311,Male,37,Diploma,14,66,58,7,56,0.0,6,34,Urban,HR Executive,52548,0 +87312,Female,37,High School,15,88,77,34,91,3.0,3,92,Urban,ML Engineer,44899,1 +87313,Female,54,Masters,6,66,15,47,85,6.0,6,94,Urban,ML Engineer,72940,0 +87314,Female,45,Diploma,18,19,84,60,69,2.0,4,38,Urban,ML Engineer,93115,0 +87315,Male,23,Bachelors,17,19,62,90,87,0.0,2,52,Urban,Manager,78148,0 +87316,Male,53,Masters,2,42,62,31,73,7.0,1,47,Rural,Data Analyst,134160,0 +87317,Male,32,Bachelors,2,95,5,64,33,5.0,2,98,Urban,Software Engineer,138560,1 +87318,Male,47,Bachelors,3,58,21,50,90,9.0,6,75,Urban,ML Engineer,69257,0 +87319,Female,35,Diploma,17,98,86,93,66,6.0,4,81,Semi-Urban,Manager,26244,1 +87320,Female,58,High School,4,74,66,34,89,9.0,4,33,Urban,Manager,120296,0 +87321,Male,36,Masters,12,67,16,92,67,5.0,5,91,Semi-Urban,Data Analyst,128441,1 +87322,Male,34,Bachelors,15,69,98,58,14,0.0,1,96,Urban,Manager,23272,1 +87323,Male,56,PhD,18,34,38,55,62,1.0,7,65,Rural,Software Engineer,113603,0 +87324,Female,58,Diploma,12,35,2,99,68,3.0,3,76,Urban,Data Analyst,68736,0 +87325,Male,46,Bachelors,3,58,81,41,39,1.0,4,15,Urban,ML Engineer,88532,0 +87326,Male,38,Bachelors,14,69,99,58,93,3.0,0,3,Urban,HR Executive,93874,0 +87327,Male,48,High School,5,68,91,86,24,5.0,7,46,Urban,Manager,29888,1 +87328,Male,37,Bachelors,18,46,5,60,91,9.0,0,90,Semi-Urban,HR Executive,124460,0 +87329,Female,21,High School,6,16,8,90,41,2.0,6,56,Rural,Data Analyst,82269,0 +87330,Female,48,High School,12,34,41,19,76,3.0,2,34,Semi-Urban,ML Engineer,145247,0 +87331,Male,39,Bachelors,6,31,95,98,45,5.0,1,75,Urban,ML Engineer,31507,1 +87332,Female,51,Bachelors,9,87,62,81,81,8.0,7,74,Semi-Urban,HR Executive,129810,1 +87333,Female,27,Masters,14,93,20,83,73,4.0,7,80,Urban,Data Analyst,40591,1 +87334,Male,43,Bachelors,16,81,92,30,88,8.0,5,55,Semi-Urban,HR Executive,41930,1 +87335,Male,37,High School,14,23,40,33,67,4.0,4,92,Urban,ML Engineer,115359,0 +87336,Female,31,Bachelors,19,83,66,72,11,5.0,1,46,Semi-Urban,Software Engineer,139504,1 +87337,Other,57,PhD,8,10,32,73,96,5.0,5,66,Urban,ML Engineer,136343,0 +87338,Male,23,Bachelors,11,29,34,49,83,7.0,7,74,Urban,ML Engineer,44046,0 +87339,Female,27,Bachelors,6,78,55,55,28,9.0,5,58,Urban,Software Engineer,53583,1 +87340,Male,21,High School,11,31,83,39,16,1.0,6,83,Semi-Urban,Manager,114439,1 +87341,Male,52,Diploma,16,66,23,84,83,0.0,6,51,Rural,Software Engineer,98916,0 +87342,Male,50,Bachelors,1,99,46,80,67,8.0,5,24,Urban,Manager,68570,1 +87343,Male,56,PhD,4,43,19,63,44,2.0,3,48,Semi-Urban,HR Executive,75555,0 +87344,Male,33,Bachelors,9,30,96,61,23,4.0,5,95,Rural,Manager,144155,1 +87345,Male,56,Diploma,7,73,49,27,50,8.0,6,36,Urban,ML Engineer,135198,0 +87346,Male,55,Masters,3,16,40,23,83,1.0,3,51,Rural,Data Analyst,65762,0 +87347,Male,36,Bachelors,5,57,31,33,52,2.0,3,13,Semi-Urban,Data Analyst,114613,0 +87348,Female,47,Diploma,18,74,96,17,25,1.0,2,88,Urban,ML Engineer,98357,1 +87349,Male,54,Bachelors,8,36,46,0,17,3.0,6,52,Urban,Manager,75282,0 +87350,Male,51,Diploma,7,38,23,8,25,2.0,4,56,Urban,Manager,89745,0 +87351,Female,46,Bachelors,7,72,83,36,23,9.0,3,24,Semi-Urban,Software Engineer,25978,0 +87352,Female,46,Masters,3,14,53,22,27,5.0,6,7,Urban,HR Executive,45076,0 +87353,Male,28,Bachelors,16,15,47,87,66,0.0,4,47,Semi-Urban,Software Engineer,108630,0 +87354,Male,49,Bachelors,6,27,83,83,16,5.0,5,63,Urban,Data Analyst,26646,1 +87355,Female,46,Masters,3,23,7,2,62,5.0,3,74,Semi-Urban,Data Analyst,53326,0 +87356,Male,23,Masters,11,10,14,67,26,5.0,1,4,Urban,Data Analyst,124088,0 +87357,Male,36,Bachelors,15,24,20,61,84,9.0,6,81,Rural,Data Analyst,103208,0 +87358,Female,26,Bachelors,10,65,59,4,82,2.0,5,94,Rural,ML Engineer,115425,0 +87359,Female,23,Masters,19,98,40,61,17,8.0,1,56,Urban,HR Executive,60320,1 +87360,Female,57,Bachelors,13,54,2,8,35,0.0,4,36,Semi-Urban,Software Engineer,144822,0 +87361,Male,59,PhD,2,97,44,72,20,6.0,2,41,Semi-Urban,Data Analyst,64204,1 +87362,Female,59,High School,14,2,1,76,82,1.0,2,51,Rural,HR Executive,57915,0 +87363,Female,41,High School,19,75,52,0,57,4.0,0,60,Semi-Urban,ML Engineer,58303,0 +87364,Male,21,Diploma,4,49,93,5,13,8.0,4,47,Urban,ML Engineer,72913,0 +87365,Male,59,High School,10,91,12,64,39,0.0,6,79,Semi-Urban,Data Analyst,52856,1 +87366,Male,59,High School,18,50,78,75,51,2.0,2,4,Semi-Urban,Software Engineer,149819,0 +87367,Male,58,Diploma,10,0,78,74,64,8.0,2,52,Semi-Urban,Software Engineer,48542,0 +87368,Other,22,Bachelors,7,96,49,57,29,0.0,7,94,Semi-Urban,HR Executive,133423,1 +87369,Female,21,Bachelors,2,96,41,31,24,0.0,0,79,Semi-Urban,Data Analyst,87176,1 +87370,Male,57,Bachelors,13,8,78,24,74,4.0,4,92,Urban,Software Engineer,128161,0 +87371,Female,59,Bachelors,5,94,50,52,41,5.0,1,60,Urban,Data Analyst,127562,1 +87372,Male,54,Diploma,19,49,51,73,75,4.0,6,43,Urban,Data Analyst,59421,0 +87373,Male,55,Bachelors,11,58,57,35,67,8.0,5,58,Rural,Data Analyst,129911,0 +87374,Male,30,High School,2,32,38,89,84,6.0,6,7,Rural,Software Engineer,147110,0 +87375,Other,35,Masters,2,46,51,46,4,1.0,4,12,Urban,Manager,117746,0 +87376,Female,35,Masters,19,91,37,6,33,1.0,1,26,Semi-Urban,HR Executive,73978,0 +87377,Female,42,Diploma,13,86,37,55,69,4.0,6,34,Semi-Urban,Software Engineer,143994,0 +87378,Male,42,Bachelors,4,40,35,31,66,0.0,1,98,Semi-Urban,Manager,105873,0 +87379,Male,25,Bachelors,11,27,6,14,61,9.0,2,23,Rural,Manager,53184,0 +87380,Male,21,Diploma,4,93,94,30,22,7.0,4,23,Rural,Data Analyst,111758,1 +87381,Female,24,Diploma,19,78,9,89,14,9.0,3,6,Rural,Data Analyst,102120,0 +87382,Male,51,Diploma,11,77,30,54,14,3.0,4,80,Urban,Data Analyst,66413,1 +87383,Male,36,Diploma,2,94,54,19,35,6.0,2,41,Urban,ML Engineer,121475,0 +87384,Male,23,Diploma,8,15,98,56,90,6.0,7,74,Urban,Software Engineer,85785,1 +87385,Female,21,Bachelors,4,5,31,84,66,4.0,1,64,Urban,Manager,96547,0 +87386,Female,54,Diploma,5,92,38,74,37,6.0,4,89,Urban,HR Executive,117246,1 +87387,Female,53,PhD,13,21,97,21,28,8.0,6,59,Rural,ML Engineer,43741,0 +87388,Female,33,Diploma,18,48,24,59,38,5.0,7,54,Urban,HR Executive,44312,0 +87389,Female,29,Diploma,4,56,81,4,77,2.0,1,84,Rural,Manager,97272,0 +87390,Male,56,PhD,16,16,72,59,34,3.0,1,75,Urban,Data Analyst,37031,0 +87391,Male,39,Bachelors,12,36,75,64,53,4.0,4,85,Urban,ML Engineer,86403,1 +87392,Male,41,Bachelors,5,99,71,41,45,4.0,1,71,Urban,Software Engineer,139509,1 +87393,Male,59,Diploma,8,55,89,39,30,0.0,6,84,Urban,ML Engineer,131555,1 +87394,Female,27,Bachelors,7,60,29,91,31,9.0,7,87,Semi-Urban,HR Executive,76465,1 +87395,Male,22,Diploma,13,9,20,60,36,7.0,4,48,Semi-Urban,Software Engineer,103647,0 +87396,Male,44,Bachelors,13,2,1,52,88,4.0,1,7,Urban,Manager,97439,0 +87397,Female,43,High School,7,32,40,24,39,2.0,0,98,Urban,Software Engineer,110843,0 +87398,Male,24,Bachelors,19,32,74,28,56,0.0,4,15,Semi-Urban,ML Engineer,63529,0 +87399,Male,33,Masters,9,69,97,70,26,4.0,4,21,Semi-Urban,Manager,90910,1 +87400,Male,33,Bachelors,7,34,32,99,40,3.0,7,0,Urban,Software Engineer,137845,0 +87401,Male,46,Diploma,15,49,72,50,21,7.0,1,12,Urban,Data Analyst,108371,0 +87402,Male,50,Bachelors,1,84,61,20,76,0.0,1,51,Urban,Data Analyst,37322,0 +87403,Male,32,Masters,14,47,85,63,41,8.0,5,35,Semi-Urban,Software Engineer,80344,0 +87404,Female,46,Bachelors,18,64,59,62,47,8.0,5,63,Urban,Data Analyst,81703,1 +87405,Male,26,High School,9,82,67,49,2,6.0,7,86,Urban,HR Executive,30211,1 +87406,Male,26,Masters,19,20,47,23,52,4.0,3,93,Urban,ML Engineer,103860,0 +87407,Female,26,Bachelors,16,95,83,71,72,4.0,1,20,Urban,Manager,57616,1 +87408,Other,48,Bachelors,17,18,36,52,81,2.0,6,55,Urban,ML Engineer,83811,0 +87409,Female,51,Bachelors,8,65,62,0,5,1.0,0,54,Rural,Software Engineer,61714,0 +87410,Male,24,Diploma,17,42,96,3,86,9.0,2,22,Urban,Manager,23458,0 +87411,Male,38,Diploma,4,68,41,68,30,3.0,2,90,Urban,ML Engineer,39671,1 +87412,Male,59,High School,1,16,70,47,44,7.0,2,44,Urban,Data Analyst,103999,0 +87413,Male,31,Bachelors,14,59,82,90,72,1.0,5,13,Urban,Manager,30614,1 +87414,Male,37,Diploma,0,86,95,30,71,3.0,3,22,Rural,HR Executive,56425,0 +87415,Male,38,PhD,0,81,56,58,64,4.0,4,82,Semi-Urban,Data Analyst,80959,1 +87416,Male,54,Masters,18,2,45,29,94,4.0,7,29,Semi-Urban,ML Engineer,51634,0 +87417,Male,27,Bachelors,14,82,18,29,21,4.0,3,47,Semi-Urban,ML Engineer,88726,0 +87418,Female,31,Diploma,19,43,88,61,69,2.0,5,43,Urban,ML Engineer,147752,0 +87419,Female,51,Bachelors,17,62,95,16,79,4.0,6,17,Rural,Data Analyst,103063,0 +87420,Male,31,High School,16,18,55,37,32,0.0,3,10,Rural,Manager,87902,0 +87421,Female,56,Masters,17,54,21,6,15,8.0,6,44,Urban,Manager,96153,0 +87422,Male,31,Masters,10,57,4,6,78,7.0,7,53,Urban,Data Analyst,134669,0 +87423,Male,40,High School,2,76,37,75,63,7.0,0,47,Rural,HR Executive,94974,1 +87424,Female,44,Diploma,12,75,60,44,50,4.0,2,60,Semi-Urban,Software Engineer,149635,0 +87425,Male,42,Bachelors,13,49,74,40,66,7.0,5,8,Urban,HR Executive,20330,0 +87426,Male,32,Bachelors,14,95,87,2,72,3.0,1,66,Urban,Manager,85273,1 +87427,Male,48,Masters,11,94,7,54,0,0.0,5,44,Urban,Software Engineer,71686,0 +87428,Male,28,High School,19,54,8,68,42,6.0,4,80,Urban,Software Engineer,44690,0 +87429,Female,55,Masters,6,18,83,20,63,7.0,4,48,Urban,Manager,133644,0 +87430,Female,44,Masters,3,53,45,91,51,6.0,7,49,Urban,ML Engineer,30531,0 +87431,Male,51,Bachelors,15,5,16,66,84,4.0,0,71,Rural,Manager,146071,0 +87432,Male,57,Masters,11,72,59,84,33,6.0,4,11,Semi-Urban,Software Engineer,97561,0 +87433,Male,34,Bachelors,18,9,94,57,91,2.0,1,18,Urban,Software Engineer,78314,0 +87434,Female,42,High School,16,52,97,29,32,3.0,7,60,Urban,Manager,60436,0 +87435,Male,48,High School,11,90,32,80,31,3.0,7,41,Semi-Urban,ML Engineer,62578,1 +87436,Male,40,Bachelors,11,20,4,6,65,3.0,7,35,Urban,Manager,91362,0 +87437,Male,51,Diploma,15,27,60,57,24,5.0,6,10,Semi-Urban,HR Executive,50512,0 +87438,Male,45,Masters,0,6,42,85,6,8.0,6,54,Urban,Manager,37972,0 +87439,Female,58,Bachelors,8,82,79,83,97,0.0,4,1,Urban,HR Executive,39369,1 +87440,Female,24,Bachelors,14,33,55,6,41,7.0,7,91,Urban,ML Engineer,119336,0 +87441,Male,53,Masters,8,66,42,74,93,8.0,2,81,Semi-Urban,Manager,79322,1 +87442,Female,47,Bachelors,11,63,40,30,16,6.0,5,19,Urban,ML Engineer,95484,0 +87443,Male,55,Masters,3,84,1,32,74,7.0,0,36,Urban,Software Engineer,94017,0 +87444,Female,38,Bachelors,2,56,84,12,68,7.0,3,80,Urban,Manager,42552,0 +87445,Female,53,Masters,7,54,93,98,80,3.0,4,87,Urban,Software Engineer,88212,1 +87446,Male,51,Bachelors,6,20,20,18,11,8.0,6,65,Urban,Manager,43321,0 +87447,Male,49,Masters,9,49,65,33,22,2.0,6,65,Urban,Software Engineer,70249,0 +87448,Female,49,High School,0,20,79,6,62,2.0,4,30,Urban,HR Executive,26635,0 +87449,Male,55,Bachelors,13,77,13,16,4,0.0,1,64,Urban,ML Engineer,137133,0 +87450,Other,39,High School,1,45,58,70,46,0.0,2,0,Urban,HR Executive,77554,0 +87451,Female,59,Masters,17,19,97,24,78,7.0,1,92,Urban,Software Engineer,90528,0 +87452,Female,21,Masters,5,58,92,6,3,8.0,6,8,Urban,Software Engineer,22897,0 +87453,Male,35,Bachelors,18,13,70,9,97,7.0,7,18,Semi-Urban,ML Engineer,27276,0 +87454,Male,53,Diploma,3,91,8,75,40,0.0,3,88,Semi-Urban,Manager,30736,1 +87455,Female,36,High School,4,2,73,63,13,3.0,5,44,Urban,Manager,35784,0 +87456,Female,33,Masters,11,81,81,15,4,4.0,6,30,Urban,Data Analyst,131238,0 +87457,Male,49,Bachelors,9,99,82,30,44,0.0,1,95,Urban,Manager,77508,1 +87458,Female,40,Bachelors,11,17,98,13,49,2.0,1,53,Urban,ML Engineer,34198,0 +87459,Female,44,Masters,15,82,5,60,47,0.0,4,68,Urban,Manager,90797,0 +87460,Male,30,Masters,6,9,85,85,19,5.0,4,40,Urban,Manager,85306,0 +87461,Female,41,PhD,12,56,89,58,25,8.0,5,40,Semi-Urban,Data Analyst,77315,1 +87462,Male,42,Bachelors,8,77,69,79,14,4.0,4,4,Rural,Software Engineer,131626,0 +87463,Male,43,High School,7,97,44,86,54,8.0,7,18,Urban,ML Engineer,131016,1 +87464,Male,59,Diploma,7,76,29,95,73,3.0,1,13,Urban,Software Engineer,141053,0 +87465,Female,46,Masters,7,66,8,83,97,1.0,2,76,Rural,Data Analyst,80131,0 +87466,Male,53,Bachelors,13,77,28,56,24,7.0,7,13,Rural,HR Executive,69089,0 +87467,Female,49,PhD,12,45,25,7,59,7.0,7,10,Rural,ML Engineer,53687,0 +87468,Female,48,Bachelors,17,93,10,99,3,2.0,3,45,Rural,HR Executive,113636,1 +87469,Male,39,High School,6,24,76,74,48,4.0,5,70,Semi-Urban,Data Analyst,80671,1 +87470,Male,44,Masters,18,80,56,61,65,2.0,1,55,Urban,Software Engineer,79097,1 +87471,Female,42,Diploma,5,5,59,97,89,6.0,6,14,Urban,Manager,46879,0 +87472,Male,33,Masters,2,31,66,0,97,5.0,4,57,Semi-Urban,Software Engineer,22053,0 +87473,Male,59,Bachelors,5,87,71,30,3,6.0,7,64,Urban,ML Engineer,139356,1 +87474,Male,22,Bachelors,3,20,5,3,73,7.0,4,16,Rural,HR Executive,85136,0 +87475,Male,23,Bachelors,10,1,24,73,80,3.0,0,21,Urban,HR Executive,94838,0 +87476,Male,30,Bachelors,8,84,57,79,84,0.0,1,16,Urban,Software Engineer,146711,1 +87477,Male,31,Bachelors,1,71,59,27,90,3.0,2,64,Urban,ML Engineer,104044,0 +87478,Male,59,Bachelors,1,91,3,38,97,0.0,7,73,Urban,Software Engineer,116403,0 +87479,Male,30,Bachelors,13,28,30,27,11,3.0,6,79,Urban,HR Executive,67476,0 +87480,Female,25,Bachelors,17,5,78,97,77,2.0,7,43,Rural,ML Engineer,131668,0 +87481,Male,33,Masters,5,33,33,9,50,5.0,7,97,Urban,Software Engineer,95923,0 +87482,Female,42,Masters,19,78,59,37,45,6.0,2,90,Rural,HR Executive,52865,1 +87483,Female,35,High School,8,1,17,29,66,4.0,4,57,Urban,Software Engineer,85429,0 +87484,Male,46,Diploma,2,88,95,59,21,5.0,2,84,Urban,Data Analyst,57004,1 +87485,Female,40,Masters,4,85,85,72,67,7.0,3,96,Urban,Manager,64209,1 +87486,Male,26,Diploma,0,39,39,95,84,4.0,2,82,Semi-Urban,ML Engineer,74151,1 +87487,Male,41,Bachelors,18,31,62,66,17,8.0,6,86,Rural,Manager,44332,1 +87488,Female,24,Bachelors,11,35,78,53,35,4.0,4,33,Urban,Manager,22234,0 +87489,Female,24,Bachelors,16,77,29,45,82,2.0,6,68,Rural,ML Engineer,36600,0 +87490,Female,39,Bachelors,15,25,33,96,26,0.0,3,69,Urban,ML Engineer,111022,0 +87491,Male,32,Masters,19,35,10,47,53,1.0,6,82,Urban,ML Engineer,90286,0 +87492,Male,53,Diploma,3,67,98,89,25,9.0,0,60,Semi-Urban,Software Engineer,140346,1 +87493,Male,26,Masters,17,16,64,73,69,7.0,7,5,Rural,Data Analyst,85400,0 +87494,Female,25,High School,8,53,59,46,74,0.0,0,34,Rural,HR Executive,28924,0 +87495,Male,25,High School,16,78,28,91,1,2.0,6,19,Urban,Data Analyst,122737,0 +87496,Male,44,Bachelors,16,59,31,8,40,5.0,7,64,Urban,Data Analyst,30145,0 +87497,Female,47,Diploma,17,76,37,52,56,6.0,4,47,Urban,Manager,49942,0 +87498,Male,26,PhD,13,19,39,75,66,1.0,7,78,Rural,HR Executive,137464,0 +87499,Female,22,Masters,14,46,96,76,64,4.0,7,3,Semi-Urban,HR Executive,29149,0 +87500,Female,59,Bachelors,17,54,55,50,29,0.0,6,6,Rural,ML Engineer,138523,0 +87501,Female,57,Bachelors,5,48,77,38,29,9.0,1,44,Urban,Software Engineer,140874,0 +87502,Male,52,Diploma,14,53,79,24,78,3.0,7,49,Urban,HR Executive,113900,0 +87503,Male,40,Bachelors,15,24,77,18,68,9.0,4,30,Urban,Manager,84734,0 +87504,Other,48,Diploma,9,35,18,22,11,0.0,5,95,Urban,HR Executive,46873,0 +87505,Male,31,Diploma,3,67,59,59,47,3.0,1,4,Urban,Data Analyst,29460,0 +87506,Male,55,Bachelors,8,14,18,81,60,7.0,7,64,Rural,ML Engineer,117429,0 +87507,Male,33,Diploma,16,91,70,16,7,9.0,2,36,Urban,Manager,130869,0 +87508,Female,59,Bachelors,7,41,88,16,58,3.0,6,75,Rural,Software Engineer,46778,0 +87509,Male,52,Bachelors,10,66,64,29,75,0.0,3,18,Semi-Urban,Data Analyst,138459,0 +87510,Male,53,Masters,0,67,51,42,15,6.0,3,91,Rural,Data Analyst,96618,1 +87511,Male,43,PhD,16,50,80,93,0,0.0,1,43,Urban,Software Engineer,37484,1 +87512,Male,34,Bachelors,12,10,86,25,48,8.0,6,68,Semi-Urban,Manager,53907,0 +87513,Female,31,Masters,17,13,12,71,51,9.0,1,74,Rural,Software Engineer,89251,0 +87514,Female,28,High School,19,25,6,18,44,8.0,2,83,Urban,HR Executive,26680,0 +87515,Male,40,Diploma,12,12,58,8,52,6.0,2,9,Rural,Manager,91307,0 +87516,Female,40,Masters,7,0,62,39,91,8.0,2,74,Urban,Manager,41347,0 +87517,Female,27,Diploma,1,65,91,55,3,4.0,4,78,Urban,Data Analyst,69539,1 +87518,Male,59,Masters,5,71,7,22,26,6.0,6,40,Urban,ML Engineer,110348,0 +87519,Male,40,High School,13,83,87,93,66,8.0,3,10,Semi-Urban,ML Engineer,42893,1 +87520,Female,45,Diploma,3,28,91,55,69,9.0,1,57,Urban,Software Engineer,77034,0 +87521,Female,46,Masters,7,9,1,47,99,3.0,1,82,Rural,Manager,26993,0 +87522,Female,42,Diploma,13,45,86,9,65,2.0,2,87,Semi-Urban,Software Engineer,143677,0 +87523,Male,22,Bachelors,11,2,55,32,66,9.0,7,36,Urban,HR Executive,43519,0 +87524,Male,36,PhD,0,82,5,47,47,7.0,7,28,Urban,Software Engineer,142437,0 +87525,Male,30,Masters,10,97,80,28,50,1.0,6,35,Semi-Urban,ML Engineer,34868,1 +87526,Male,35,PhD,18,26,72,72,6,0.0,2,4,Semi-Urban,Manager,32147,0 +87527,Male,49,Bachelors,19,12,75,22,28,0.0,5,76,Rural,Software Engineer,36891,0 +87528,Female,59,Bachelors,7,97,67,60,11,5.0,7,8,Rural,Manager,68110,0 +87529,Male,31,Bachelors,10,99,63,47,42,7.0,4,16,Urban,HR Executive,48169,0 +87530,Male,40,Bachelors,14,11,1,19,16,9.0,1,44,Urban,HR Executive,21155,0 +87531,Female,47,Bachelors,8,13,59,65,13,9.0,3,25,Urban,Software Engineer,77481,0 +87532,Male,54,Diploma,11,57,49,17,1,5.0,4,92,Urban,ML Engineer,82001,0 +87533,Male,58,Bachelors,1,68,91,16,99,7.0,5,36,Urban,Manager,116164,0 +87534,Male,52,PhD,15,19,0,15,10,0.0,4,96,Rural,HR Executive,76194,0 +87535,Male,27,Bachelors,4,71,44,44,4,4.0,6,36,Urban,Data Analyst,84631,0 +87536,Male,28,Bachelors,8,48,7,45,73,2.0,1,10,Urban,ML Engineer,34410,0 +87537,Male,47,High School,4,11,64,11,30,7.0,2,47,Urban,HR Executive,129131,0 +87538,Male,48,Masters,2,11,12,62,37,0.0,7,86,Urban,HR Executive,23701,0 +87539,Male,40,Bachelors,1,21,84,48,47,4.0,0,6,Rural,Software Engineer,59933,0 +87540,Female,53,High School,13,69,14,68,39,8.0,1,38,Rural,Data Analyst,105139,0 +87541,Other,42,Bachelors,4,67,19,13,57,7.0,1,6,Urban,HR Executive,132732,0 +87542,Male,55,PhD,18,74,94,98,30,3.0,7,24,Urban,ML Engineer,134500,1 +87543,Female,31,Bachelors,18,24,65,2,7,9.0,3,14,Rural,Data Analyst,132488,0 +87544,Male,42,Bachelors,16,33,73,45,84,8.0,7,40,Urban,Data Analyst,81319,0 +87545,Male,22,Bachelors,8,73,98,97,74,3.0,2,99,Semi-Urban,ML Engineer,130933,1 +87546,Male,24,Diploma,1,1,90,39,24,8.0,1,83,Urban,HR Executive,43664,0 +87547,Male,37,Masters,0,89,7,75,53,7.0,4,99,Urban,ML Engineer,66001,1 +87548,Female,31,Bachelors,0,91,89,70,21,8.0,3,56,Semi-Urban,Data Analyst,138700,1 +87549,Male,35,Diploma,4,79,84,96,53,9.0,0,25,Urban,Software Engineer,143950,1 +87550,Female,27,Masters,5,91,94,63,65,1.0,3,62,Rural,Data Analyst,94959,1 +87551,Male,33,Bachelors,15,68,42,82,69,9.0,0,93,Urban,Manager,149683,1 +87552,Male,38,Masters,13,22,2,59,28,0.0,7,73,Rural,Manager,98079,0 +87553,Male,30,Diploma,4,28,48,8,31,2.0,6,59,Rural,Manager,122783,0 +87554,Female,23,Bachelors,5,73,42,7,7,3.0,0,5,Semi-Urban,Data Analyst,52379,0 +87555,Other,37,Masters,15,64,12,78,67,8.0,1,96,Urban,Software Engineer,133634,1 +87556,Male,56,Bachelors,6,82,21,89,81,0.0,2,8,Urban,Software Engineer,34482,0 +87557,Male,30,Diploma,15,18,0,65,60,5.0,0,86,Urban,Manager,33198,0 +87558,Male,28,High School,12,23,75,6,18,6.0,2,80,Semi-Urban,HR Executive,22587,0 +87559,Female,57,Bachelors,17,2,95,3,45,4.0,1,12,Semi-Urban,Data Analyst,95951,0 +87560,Female,39,Masters,1,99,52,68,48,5.0,4,54,Urban,ML Engineer,124291,1 +87561,Male,31,PhD,2,81,58,73,54,6.0,0,44,Urban,ML Engineer,102289,1 +87562,Male,47,Diploma,0,41,63,78,73,4.0,0,19,Urban,ML Engineer,47443,0 +87563,Male,46,Bachelors,4,76,97,34,24,2.0,3,43,Semi-Urban,ML Engineer,41687,1 +87564,Female,59,Masters,10,98,14,92,1,1.0,5,57,Urban,HR Executive,116836,1 +87565,Male,23,Bachelors,16,43,79,57,79,7.0,2,20,Urban,ML Engineer,124992,0 +87566,Female,26,High School,17,69,48,38,85,2.0,3,30,Rural,Software Engineer,138360,0 +87567,Male,35,Bachelors,1,99,18,31,80,8.0,4,83,Urban,ML Engineer,84918,0 +87568,Female,42,Masters,12,66,80,66,13,0.0,4,66,Rural,Data Analyst,55075,1 +87569,Male,50,Bachelors,11,3,54,75,20,1.0,1,30,Semi-Urban,Data Analyst,102043,0 +87570,Female,37,Masters,11,22,22,2,85,6.0,0,54,Urban,Data Analyst,82796,0 +87571,Female,31,Diploma,13,92,17,79,8,4.0,3,33,Urban,Data Analyst,50240,0 +87572,Male,44,Masters,5,62,60,90,11,9.0,1,5,Urban,Data Analyst,24265,0 +87573,Male,23,Masters,10,81,85,76,86,8.0,4,25,Urban,HR Executive,59625,1 +87574,Male,58,Masters,7,21,90,6,86,0.0,6,74,Urban,ML Engineer,125858,0 +87575,Female,44,Diploma,18,83,71,28,89,7.0,1,44,Rural,HR Executive,38350,0 +87576,Male,44,Bachelors,5,10,55,20,55,7.0,5,30,Urban,Manager,127922,0 +87577,Male,33,Masters,6,99,19,12,55,2.0,0,1,Semi-Urban,HR Executive,79906,0 +87578,Other,59,Bachelors,16,61,66,45,78,5.0,6,15,Urban,ML Engineer,24715,0 +87579,Female,49,Bachelors,1,17,91,1,64,7.0,0,18,Rural,Data Analyst,90719,0 +87580,Female,28,High School,2,42,23,58,56,6.0,4,35,Urban,Data Analyst,88342,0 +87581,Female,28,Masters,15,56,9,31,82,2.0,1,71,Urban,HR Executive,53306,0 +87582,Male,28,Diploma,13,24,80,99,26,2.0,3,70,Rural,Software Engineer,118948,1 +87583,Female,41,Masters,0,3,49,62,12,4.0,5,51,Urban,HR Executive,139208,0 +87584,Male,51,Masters,16,26,5,26,26,5.0,4,33,Semi-Urban,Data Analyst,147608,0 +87585,Female,54,Bachelors,7,61,5,77,26,9.0,1,58,Semi-Urban,Manager,38059,0 +87586,Male,50,Bachelors,6,45,6,87,60,5.0,5,22,Semi-Urban,HR Executive,84799,0 +87587,Other,27,Bachelors,8,54,21,52,78,5.0,2,23,Urban,Software Engineer,107996,0 +87588,Female,54,High School,17,15,5,69,73,6.0,5,40,Urban,Manager,41979,0 +87589,Male,37,Bachelors,19,0,57,75,72,3.0,6,20,Urban,Data Analyst,43615,0 +87590,Male,22,Bachelors,5,8,23,77,40,0.0,0,78,Urban,Software Engineer,94798,0 +87591,Female,41,Bachelors,16,9,99,63,19,1.0,3,17,Urban,Software Engineer,139474,0 +87592,Male,43,Masters,18,72,38,21,10,4.0,7,66,Urban,Software Engineer,146691,0 +87593,Male,57,Diploma,2,35,75,85,12,8.0,1,34,Rural,Manager,99367,0 +87594,Male,29,Bachelors,7,79,43,92,81,7.0,7,17,Rural,HR Executive,45419,0 +87595,Male,45,High School,8,94,13,94,92,6.0,2,77,Urban,Manager,27230,1 +87596,Female,29,Masters,8,86,46,56,70,4.0,1,1,Rural,HR Executive,33017,0 +87597,Female,53,Diploma,14,46,26,2,6,0.0,3,29,Urban,Manager,47790,0 +87598,Other,53,Diploma,17,63,58,47,28,0.0,6,19,Rural,Manager,96116,0 +87599,Male,32,Bachelors,0,26,76,80,28,2.0,7,95,Urban,Software Engineer,124706,1 +87600,Male,56,Masters,13,24,66,33,34,7.0,3,63,Urban,Software Engineer,113877,0 +87601,Male,42,Bachelors,7,69,78,86,70,2.0,3,59,Semi-Urban,Data Analyst,79068,1 +87602,Female,49,Diploma,14,24,29,35,52,2.0,5,38,Urban,HR Executive,93060,0 +87603,Male,34,Bachelors,7,11,23,22,74,5.0,0,61,Urban,Manager,42825,0 +87604,Male,56,Bachelors,14,63,56,38,75,6.0,2,29,Semi-Urban,HR Executive,41671,0 +87605,Male,33,Masters,8,16,36,84,58,4.0,1,45,Urban,Data Analyst,138287,0 +87606,Male,38,Masters,4,76,46,44,40,4.0,5,37,Urban,HR Executive,83682,0 +87607,Male,55,Masters,19,56,35,67,43,5.0,2,18,Semi-Urban,Manager,42853,0 +87608,Male,52,Bachelors,16,8,24,26,72,2.0,7,55,Urban,ML Engineer,68763,0 +87609,Female,42,Bachelors,13,54,17,70,63,0.0,7,68,Urban,HR Executive,141191,0 +87610,Female,31,Bachelors,11,48,80,72,97,4.0,2,77,Urban,HR Executive,116471,1 +87611,Male,52,Diploma,10,70,40,15,45,6.0,1,30,Urban,ML Engineer,42417,0 +87612,Female,26,Diploma,9,18,43,47,15,3.0,0,36,Semi-Urban,ML Engineer,95440,0 +87613,Male,45,Bachelors,12,12,67,75,64,1.0,2,7,Urban,Manager,69363,0 +87614,Female,26,Masters,5,80,77,96,45,3.0,6,86,Semi-Urban,Software Engineer,44387,1 +87615,Male,56,Bachelors,7,36,53,4,15,9.0,6,75,Rural,Software Engineer,128701,0 +87616,Male,23,Bachelors,0,22,60,29,62,9.0,1,96,Urban,ML Engineer,119385,0 +87617,Male,26,Masters,1,68,10,85,14,6.0,3,73,Urban,Manager,81983,1 +87618,Male,34,High School,1,54,86,72,41,3.0,6,95,Semi-Urban,ML Engineer,29991,1 +87619,Male,29,High School,4,56,86,18,87,3.0,0,98,Urban,Manager,109115,1 +87620,Male,40,Bachelors,14,16,77,1,81,8.0,1,65,Rural,Data Analyst,32541,0 +87621,Female,42,Bachelors,15,20,55,69,32,7.0,7,89,Urban,Manager,113948,0 +87622,Female,37,Masters,12,29,55,51,26,0.0,7,12,Urban,Software Engineer,59588,0 +87623,Female,21,Masters,6,42,22,85,12,8.0,7,37,Rural,Software Engineer,27843,0 +87624,Male,55,Masters,19,41,66,9,77,0.0,7,65,Urban,HR Executive,102622,0 +87625,Female,29,Bachelors,14,26,73,46,45,2.0,3,87,Urban,ML Engineer,124546,0 +87626,Other,21,Masters,7,77,35,48,37,7.0,5,56,Semi-Urban,Data Analyst,88017,0 +87627,Male,33,High School,1,2,73,42,41,2.0,6,48,Urban,ML Engineer,93173,0 +87628,Male,24,Bachelors,14,13,18,93,92,0.0,7,43,Rural,Data Analyst,98288,0 +87629,Male,44,Bachelors,13,25,63,44,44,0.0,7,67,Semi-Urban,HR Executive,128673,0 +87630,Male,35,High School,3,56,69,60,56,9.0,1,12,Semi-Urban,Software Engineer,87669,0 +87631,Male,37,Bachelors,18,23,61,44,4,9.0,6,49,Urban,Data Analyst,52169,0 +87632,Male,49,Bachelors,9,96,10,39,32,7.0,1,31,Urban,Software Engineer,31538,0 +87633,Female,40,Diploma,16,63,67,63,68,4.0,4,73,Urban,ML Engineer,128370,1 +87634,Female,31,Masters,19,40,92,67,68,3.0,6,89,Urban,Data Analyst,24570,1 +87635,Male,35,Bachelors,4,45,32,67,27,1.0,2,45,Semi-Urban,Data Analyst,80794,0 +87636,Male,42,Diploma,0,19,86,65,55,9.0,2,93,Urban,Software Engineer,67377,1 +87637,Male,32,Bachelors,2,26,53,89,67,8.0,5,56,Urban,Software Engineer,77787,0 +87638,Female,24,Masters,5,75,84,39,38,6.0,4,16,Urban,Software Engineer,31009,0 +87639,Female,21,Bachelors,7,55,66,60,11,6.0,1,87,Rural,Data Analyst,107055,1 +87640,Male,46,Diploma,12,2,29,60,20,5.0,4,97,Semi-Urban,ML Engineer,74551,0 +87641,Female,31,Diploma,16,87,88,29,22,2.0,0,82,Urban,Manager,134180,1 +87642,Female,41,High School,9,74,61,70,10,9.0,3,50,Urban,HR Executive,60876,1 +87643,Male,38,High School,12,33,30,29,41,2.0,5,99,Urban,Software Engineer,76429,0 +87644,Female,57,High School,18,93,97,8,64,3.0,3,52,Urban,HR Executive,63282,1 +87645,Male,51,Masters,11,15,25,89,19,0.0,3,27,Semi-Urban,ML Engineer,63168,0 +87646,Male,35,High School,8,45,72,31,52,7.0,2,10,Urban,ML Engineer,94323,0 +87647,Male,41,Masters,2,84,92,3,92,3.0,4,45,Rural,ML Engineer,25338,0 +87648,Male,38,Diploma,1,88,23,11,72,0.0,4,79,Urban,Software Engineer,78012,0 +87649,Male,23,Masters,18,92,63,50,44,1.0,5,15,Semi-Urban,Software Engineer,36044,0 +87650,Female,43,Bachelors,4,95,79,48,76,2.0,7,87,Urban,Software Engineer,64649,1 +87651,Male,32,Masters,4,21,19,19,37,6.0,3,44,Urban,ML Engineer,109370,0 +87652,Female,48,Bachelors,14,26,73,45,20,5.0,0,81,Semi-Urban,Data Analyst,75667,0 +87653,Male,41,Diploma,10,52,48,20,0,7.0,2,65,Rural,Data Analyst,73095,0 +87654,Female,42,PhD,9,6,56,32,93,0.0,6,0,Urban,HR Executive,106118,0 +87655,Male,37,High School,1,38,2,30,90,1.0,5,61,Rural,Manager,121683,0 +87656,Male,38,Masters,18,65,17,56,9,1.0,2,36,Urban,Software Engineer,145450,0 +87657,Other,34,Bachelors,7,67,94,6,93,4.0,6,46,Urban,Software Engineer,121681,0 +87658,Male,52,Bachelors,7,33,32,56,94,1.0,5,51,Urban,Software Engineer,64314,0 +87659,Female,27,Diploma,19,97,11,36,39,1.0,4,27,Urban,Manager,34969,0 +87660,Male,25,Masters,9,48,29,36,97,7.0,0,47,Urban,Manager,129199,0 +87661,Female,43,Bachelors,0,22,35,82,96,6.0,1,38,Urban,Data Analyst,103265,0 +87662,Female,24,Bachelors,18,13,21,79,3,9.0,3,66,Rural,Manager,78053,0 +87663,Other,56,Diploma,11,56,57,9,15,9.0,6,38,Urban,HR Executive,24191,0 +87664,Male,44,Masters,5,13,51,0,1,9.0,0,7,Rural,HR Executive,23028,0 +87665,Male,49,Bachelors,13,76,49,63,88,0.0,4,85,Rural,Data Analyst,91858,1 +87666,Male,25,High School,4,54,78,38,50,5.0,7,83,Semi-Urban,ML Engineer,46595,1 +87667,Male,37,Bachelors,12,58,32,31,85,0.0,1,21,Urban,HR Executive,84478,0 +87668,Female,38,Bachelors,15,29,19,18,5,1.0,3,99,Urban,Manager,43340,0 +87669,Other,47,Bachelors,6,80,0,60,56,0.0,7,9,Semi-Urban,HR Executive,111909,0 +87670,Female,50,High School,6,27,58,48,24,3.0,2,22,Rural,Manager,72184,0 +87671,Male,32,High School,9,21,96,51,51,9.0,7,41,Urban,Software Engineer,124232,0 +87672,Female,35,Bachelors,19,46,88,84,30,9.0,0,53,Rural,Software Engineer,134036,1 +87673,Female,45,Bachelors,14,57,17,79,81,6.0,1,89,Urban,HR Executive,106580,1 +87674,Male,59,Diploma,18,0,80,34,42,3.0,5,63,Rural,HR Executive,78648,0 +87675,Male,53,Bachelors,8,79,20,22,11,4.0,6,67,Urban,ML Engineer,32557,0 +87676,Female,50,Diploma,2,60,92,6,69,8.0,5,84,Urban,Data Analyst,135959,1 +87677,Male,22,Bachelors,3,91,80,77,14,4.0,6,93,Urban,ML Engineer,63031,1 +87678,Female,26,Masters,9,84,40,47,53,0.0,6,99,Urban,Data Analyst,124614,1 +87679,Male,44,Bachelors,4,24,33,10,4,6.0,4,6,Urban,HR Executive,74683,0 +87680,Female,39,Bachelors,11,64,78,75,90,1.0,2,34,Urban,HR Executive,75431,1 +87681,Male,37,Masters,11,20,78,66,1,2.0,0,22,Urban,Data Analyst,82900,0 +87682,Female,21,Bachelors,1,65,84,64,32,0.0,6,94,Urban,Data Analyst,28109,1 +87683,Male,39,Diploma,3,17,46,74,77,9.0,0,53,Rural,Manager,24378,0 +87684,Male,28,Bachelors,11,57,15,86,71,5.0,2,75,Urban,ML Engineer,131289,0 +87685,Male,56,High School,15,1,32,78,48,6.0,3,83,Semi-Urban,Data Analyst,51474,0 +87686,Male,29,Bachelors,4,68,0,5,34,7.0,4,83,Urban,ML Engineer,111240,0 +87687,Female,28,Diploma,5,27,71,49,82,0.0,5,94,Rural,Manager,35905,1 +87688,Male,21,PhD,19,90,24,23,91,7.0,0,38,Semi-Urban,Data Analyst,56787,0 +87689,Female,44,Bachelors,2,12,39,86,89,9.0,1,48,Urban,HR Executive,35842,0 +87690,Male,49,Bachelors,5,56,90,3,96,5.0,4,9,Urban,ML Engineer,57206,0 +87691,Male,53,Bachelors,9,82,60,63,16,4.0,2,33,Urban,Data Analyst,117064,1 +87692,Female,30,Bachelors,18,35,3,36,37,6.0,0,25,Urban,HR Executive,53821,0 +87693,Male,56,High School,19,88,65,77,80,5.0,0,93,Urban,Manager,136161,1 +87694,Male,30,Bachelors,6,9,14,30,91,3.0,5,88,Urban,Manager,90465,0 +87695,Male,59,Diploma,15,34,39,17,69,8.0,1,34,Rural,Manager,93618,0 +87696,Female,43,High School,11,20,46,65,93,5.0,3,10,Semi-Urban,Data Analyst,30508,0 +87697,Male,31,Bachelors,9,12,99,58,7,6.0,1,88,Urban,Data Analyst,29846,1 +87698,Male,54,High School,19,59,46,99,93,0.0,0,54,Semi-Urban,Data Analyst,117512,1 +87699,Male,40,Bachelors,18,63,75,73,82,5.0,2,81,Urban,Manager,142868,1 +87700,Male,54,Diploma,17,38,28,51,86,6.0,0,47,Rural,HR Executive,75610,0 +87701,Male,48,High School,9,36,12,85,67,7.0,1,87,Urban,Software Engineer,54550,0 +87702,Male,45,High School,14,73,65,39,57,6.0,4,91,Rural,ML Engineer,113512,1 +87703,Female,49,High School,2,74,92,6,75,9.0,1,45,Urban,Software Engineer,54253,0 +87704,Female,36,Bachelors,8,27,38,46,22,6.0,1,30,Semi-Urban,ML Engineer,59523,0 +87705,Female,49,Bachelors,15,59,78,40,68,0.0,7,99,Urban,Manager,76375,1 +87706,Male,42,Diploma,8,78,81,73,32,9.0,0,26,Urban,ML Engineer,104666,1 +87707,Male,38,Masters,1,94,8,43,33,5.0,0,43,Rural,Manager,123521,0 +87708,Male,21,Diploma,4,77,39,98,80,6.0,4,47,Semi-Urban,Data Analyst,36975,1 +87709,Female,56,Masters,6,89,92,45,23,9.0,5,42,Urban,ML Engineer,147076,1 +87710,Female,31,Bachelors,13,50,68,16,57,1.0,1,22,Semi-Urban,Manager,139403,0 +87711,Male,36,Bachelors,14,4,41,90,78,6.0,7,7,Semi-Urban,ML Engineer,89456,0 +87712,Male,54,High School,6,25,38,89,58,5.0,7,16,Urban,ML Engineer,28072,0 +87713,Female,36,High School,4,1,93,12,91,0.0,6,79,Urban,HR Executive,131054,0 +87714,Female,55,Bachelors,4,90,57,82,52,6.0,5,9,Rural,ML Engineer,90915,0 +87715,Male,53,Masters,5,42,40,87,31,9.0,5,42,Urban,Software Engineer,105513,0 +87716,Male,27,Bachelors,16,28,46,84,6,9.0,5,79,Urban,Data Analyst,78645,1 +87717,Male,34,Bachelors,3,56,75,24,94,9.0,0,69,Urban,Software Engineer,103084,0 +87718,Female,40,Bachelors,9,60,37,78,96,1.0,2,92,Urban,Data Analyst,91880,1 +87719,Male,45,Bachelors,16,95,77,98,80,7.0,4,45,Rural,Data Analyst,129684,1 +87720,Female,33,Bachelors,16,92,22,49,52,8.0,4,55,Urban,HR Executive,76953,0 +87721,Male,23,Diploma,0,56,40,16,80,8.0,7,57,Rural,Software Engineer,25427,0 +87722,Female,43,Bachelors,14,65,5,73,1,2.0,0,29,Urban,ML Engineer,121438,0 +87723,Male,42,Diploma,19,83,11,77,70,0.0,5,44,Urban,Manager,83836,0 +87724,Male,56,Diploma,14,54,50,66,73,5.0,6,54,Rural,Data Analyst,95646,0 +87725,Male,35,Bachelors,12,13,4,39,28,6.0,0,14,Urban,Software Engineer,136155,0 +87726,Female,26,High School,19,2,51,48,60,5.0,0,32,Rural,Manager,84540,0 +87727,Male,30,Bachelors,11,65,35,5,61,1.0,2,37,Rural,Manager,118834,0 +87728,Female,32,Bachelors,13,22,31,53,10,6.0,5,38,Urban,Manager,139382,0 +87729,Male,38,High School,13,83,59,23,24,5.0,2,92,Rural,Manager,76240,1 +87730,Female,35,High School,12,0,75,74,54,9.0,6,42,Urban,Software Engineer,96025,0 +87731,Other,50,Diploma,13,46,52,13,3,9.0,7,30,Rural,Software Engineer,85757,0 +87732,Male,39,Masters,9,53,82,43,74,5.0,3,89,Urban,ML Engineer,118548,1 +87733,Male,51,Bachelors,8,34,78,60,41,5.0,5,20,Rural,Manager,51195,0 +87734,Female,44,Bachelors,13,75,47,58,80,2.0,7,82,Urban,Software Engineer,140155,1 +87735,Other,40,High School,5,73,11,92,75,9.0,1,90,Urban,Software Engineer,139420,1 +87736,Male,29,Bachelors,19,73,83,91,49,6.0,4,29,Urban,ML Engineer,88052,1 +87737,Male,45,Bachelors,17,1,25,14,20,9.0,7,66,Urban,ML Engineer,121271,0 +87738,Male,48,Bachelors,18,45,46,80,11,0.0,0,2,Rural,Manager,27130,0 +87739,Male,58,Masters,4,67,94,52,2,3.0,4,18,Urban,Software Engineer,41053,0 +87740,Female,58,Bachelors,6,35,53,43,91,0.0,4,7,Semi-Urban,HR Executive,43985,0 +87741,Male,58,Bachelors,3,36,4,85,15,9.0,7,71,Urban,ML Engineer,80924,0 +87742,Female,49,Bachelors,8,90,47,10,47,4.0,4,19,Urban,ML Engineer,74417,0 +87743,Female,42,Bachelors,6,28,86,1,78,0.0,6,99,Rural,Software Engineer,72549,0 +87744,Male,56,Bachelors,12,69,36,29,71,5.0,4,13,Urban,ML Engineer,71680,0 +87745,Male,31,Masters,13,2,9,59,69,4.0,0,47,Semi-Urban,Manager,74532,0 +87746,Male,45,Masters,4,40,72,99,31,1.0,6,13,Rural,Manager,34338,0 +87747,Male,59,Masters,11,50,57,24,28,8.0,2,23,Rural,HR Executive,86865,0 +87748,Female,24,Bachelors,1,89,96,25,14,0.0,1,54,Semi-Urban,HR Executive,56876,1 +87749,Female,53,High School,3,42,3,36,96,0.0,1,91,Urban,Data Analyst,125792,0 +87750,Male,53,Diploma,7,32,37,6,69,0.0,5,8,Urban,Software Engineer,71038,0 +87751,Female,31,Bachelors,17,10,60,82,89,1.0,1,93,Rural,HR Executive,44944,1 +87752,Male,54,High School,19,78,19,65,43,2.0,0,88,Semi-Urban,HR Executive,148919,1 +87753,Other,56,Diploma,3,33,25,4,22,7.0,3,27,Semi-Urban,HR Executive,63011,0 +87754,Male,41,Diploma,16,61,10,44,11,4.0,5,63,Rural,Data Analyst,117317,0 +87755,Male,34,Masters,2,99,75,90,1,9.0,7,59,Rural,Manager,82390,1 +87756,Other,39,Diploma,9,50,23,93,40,4.0,1,64,Urban,HR Executive,79477,0 +87757,Male,44,Bachelors,19,45,23,72,73,7.0,4,47,Urban,Manager,26996,0 +87758,Female,43,Masters,16,1,21,89,22,7.0,7,8,Urban,HR Executive,138846,0 +87759,Male,48,Bachelors,4,76,81,94,32,1.0,7,66,Semi-Urban,HR Executive,81933,1 +87760,Male,30,Bachelors,17,11,10,67,36,7.0,7,1,Urban,HR Executive,67503,0 +87761,Male,35,Bachelors,19,49,82,80,66,4.0,2,72,Rural,Manager,73507,1 +87762,Other,24,Bachelors,5,18,66,71,34,7.0,1,51,Urban,Manager,80219,0 +87763,Male,57,Diploma,9,10,17,88,54,3.0,2,71,Urban,HR Executive,123656,0 +87764,Female,33,PhD,19,60,89,35,56,1.0,7,24,Urban,Software Engineer,65184,0 +87765,Male,51,Masters,13,27,36,1,59,3.0,3,9,Urban,Manager,87414,0 +87766,Female,35,Bachelors,7,92,48,86,38,6.0,0,32,Urban,Manager,132893,1 +87767,Male,58,Diploma,11,65,39,12,70,0.0,7,60,Rural,Manager,144772,0 +87768,Male,57,Masters,0,95,71,0,5,6.0,7,9,Semi-Urban,Data Analyst,75196,0 +87769,Female,37,Diploma,8,5,54,81,6,0.0,5,11,Urban,ML Engineer,21604,0 +87770,Male,27,Bachelors,11,94,50,91,15,2.0,4,81,Semi-Urban,ML Engineer,74389,1 +87771,Male,43,Masters,2,9,15,75,16,7.0,2,95,Urban,HR Executive,73782,0 +87772,Male,26,Diploma,18,18,80,43,83,9.0,5,30,Rural,HR Executive,61818,0 +87773,Female,25,Bachelors,8,83,98,51,68,2.0,3,10,Rural,ML Engineer,123261,1 +87774,Male,44,Bachelors,14,80,89,60,96,1.0,2,37,Semi-Urban,Software Engineer,77757,1 +87775,Male,41,Diploma,4,6,35,96,53,6.0,3,65,Rural,Manager,102501,0 +87776,Male,53,High School,19,61,28,48,96,1.0,5,83,Urban,Software Engineer,127946,0 +87777,Male,38,Diploma,8,2,1,38,55,5.0,5,74,Semi-Urban,Manager,28983,0 +87778,Female,24,Bachelors,10,28,50,95,46,7.0,5,91,Rural,Data Analyst,121463,1 +87779,Female,25,Bachelors,0,83,64,70,95,4.0,1,92,Urban,ML Engineer,78067,1 +87780,Male,59,Bachelors,15,20,84,45,23,8.0,1,98,Urban,Data Analyst,49751,1 +87781,Female,58,Diploma,17,71,65,35,70,1.0,0,86,Rural,ML Engineer,86142,1 +87782,Female,37,Diploma,1,2,40,57,81,0.0,6,70,Urban,Data Analyst,114339,0 +87783,Male,52,Bachelors,19,74,31,44,68,8.0,1,78,Urban,Manager,82671,0 +87784,Male,30,Masters,1,38,23,0,13,1.0,7,89,Urban,ML Engineer,118858,0 +87785,Female,45,Diploma,6,88,65,62,22,0.0,0,47,Semi-Urban,HR Executive,45765,1 +87786,Female,26,Masters,0,47,52,57,10,7.0,6,97,Urban,Software Engineer,37809,1 +87787,Male,30,Bachelors,15,88,53,31,97,6.0,5,3,Rural,ML Engineer,120696,0 +87788,Male,54,Diploma,11,87,70,40,55,6.0,5,32,Urban,Software Engineer,28750,0 +87789,Female,24,Diploma,12,85,66,80,60,1.0,0,56,Semi-Urban,Data Analyst,134877,1 +87790,Male,44,Bachelors,16,41,8,28,89,1.0,7,47,Semi-Urban,ML Engineer,147111,0 +87791,Male,26,Bachelors,9,98,16,6,27,6.0,2,96,Urban,HR Executive,35465,0 +87792,Female,42,Masters,0,78,20,52,59,9.0,1,14,Urban,HR Executive,136119,0 +87793,Female,43,High School,17,94,75,57,37,8.0,0,27,Rural,Data Analyst,30433,1 +87794,Female,45,Bachelors,12,70,78,58,52,0.0,3,16,Urban,Data Analyst,136589,0 +87795,Male,53,Diploma,11,69,29,26,27,9.0,7,82,Urban,Data Analyst,83120,0 +87796,Male,38,Bachelors,6,75,14,50,18,3.0,1,77,Rural,Manager,30113,0 +87797,Male,28,Bachelors,9,59,0,64,47,4.0,0,30,Rural,HR Executive,81834,0 +87798,Male,37,Bachelors,16,25,97,87,73,6.0,5,65,Urban,ML Engineer,29162,1 +87799,Female,55,Bachelors,17,47,4,2,15,5.0,5,65,Urban,ML Engineer,118159,0 +87800,Female,52,Bachelors,2,75,78,31,58,2.0,5,51,Semi-Urban,Manager,33753,0 +87801,Male,57,Bachelors,9,32,60,60,63,4.0,2,51,Urban,ML Engineer,28441,0 +87802,Male,31,Diploma,1,29,25,61,22,4.0,3,60,Urban,Software Engineer,120951,0 +87803,Male,43,High School,18,31,69,82,74,7.0,6,46,Rural,HR Executive,51144,0 +87804,Female,25,High School,5,16,30,98,90,4.0,3,40,Rural,Data Analyst,36813,0 +87805,Male,46,Masters,11,41,84,59,15,4.0,2,29,Semi-Urban,ML Engineer,91758,0 +87806,Male,52,Bachelors,10,87,64,19,16,5.0,2,13,Urban,Software Engineer,59805,0 +87807,Female,45,Bachelors,5,28,9,15,88,0.0,0,27,Urban,Manager,33824,0 +87808,Female,40,Masters,10,89,7,92,20,8.0,3,9,Urban,Manager,72783,0 +87809,Female,21,PhD,12,25,85,75,32,7.0,0,87,Urban,Software Engineer,148494,1 +87810,Male,40,Bachelors,14,25,26,20,0,2.0,7,94,Urban,Data Analyst,122508,0 +87811,Female,21,Bachelors,4,74,96,97,53,9.0,1,58,Semi-Urban,Data Analyst,37654,1 +87812,Other,37,Bachelors,16,13,92,77,97,3.0,0,20,Urban,Manager,33756,0 +87813,Female,59,Bachelors,2,94,2,56,22,8.0,5,43,Semi-Urban,Data Analyst,127568,0 +87814,Male,44,Bachelors,4,9,78,83,8,9.0,3,93,Urban,ML Engineer,135376,1 +87815,Male,40,Masters,8,55,29,51,60,4.0,4,83,Semi-Urban,ML Engineer,103380,0 +87816,Male,26,Diploma,1,62,85,92,19,8.0,5,25,Urban,Data Analyst,62362,1 +87817,Male,24,Bachelors,7,91,24,66,12,0.0,7,32,Urban,Manager,97117,0 +87818,Female,22,Diploma,19,38,13,15,62,9.0,1,7,Rural,Data Analyst,127103,0 +87819,Female,41,Bachelors,8,89,79,65,20,5.0,2,87,Urban,ML Engineer,141484,1 +87820,Male,54,Bachelors,8,96,90,51,12,1.0,2,5,Semi-Urban,Manager,109544,1 +87821,Female,23,Masters,14,88,1,75,80,3.0,5,7,Rural,HR Executive,149804,0 +87822,Male,33,Masters,1,73,26,4,93,3.0,5,46,Urban,Data Analyst,127744,0 +87823,Male,53,Diploma,14,69,94,80,30,9.0,0,22,Urban,Software Engineer,119945,1 +87824,Female,52,Bachelors,14,64,55,35,48,1.0,2,77,Urban,Software Engineer,49398,0 +87825,Male,59,Masters,19,7,65,53,33,4.0,6,12,Semi-Urban,Data Analyst,130742,0 +87826,Male,49,PhD,17,61,11,68,42,2.0,5,25,Urban,Manager,79833,0 +87827,Male,21,Masters,2,43,64,91,21,1.0,6,97,Urban,Manager,39971,1 +87828,Female,54,Bachelors,16,57,74,97,18,8.0,2,29,Urban,HR Executive,68312,1 +87829,Female,33,Masters,3,8,54,4,71,4.0,5,52,Rural,ML Engineer,123091,0 +87830,Male,46,Diploma,16,68,4,76,33,0.0,1,61,Urban,Manager,84352,0 +87831,Male,41,Bachelors,18,69,47,40,17,7.0,4,65,Semi-Urban,Software Engineer,48824,0 +87832,Male,30,High School,16,73,49,10,13,9.0,6,93,Urban,ML Engineer,37909,0 +87833,Male,25,Bachelors,2,11,18,89,39,5.0,7,87,Urban,Software Engineer,27219,0 +87834,Male,34,Masters,0,72,18,81,38,2.0,4,4,Urban,Software Engineer,126348,0 +87835,Male,37,Bachelors,2,91,70,81,90,1.0,1,58,Rural,ML Engineer,133448,1 +87836,Male,55,PhD,18,3,75,3,50,4.0,1,80,Urban,ML Engineer,70680,0 +87837,Male,34,High School,7,10,74,56,17,6.0,6,61,Urban,Software Engineer,50349,0 +87838,Female,37,Diploma,7,70,51,4,54,2.0,6,20,Semi-Urban,Software Engineer,116037,0 +87839,Male,33,Masters,3,42,45,12,1,1.0,0,37,Urban,Data Analyst,143161,0 +87840,Female,41,High School,17,16,62,11,71,8.0,1,55,Rural,HR Executive,125644,0 +87841,Female,40,Diploma,9,2,39,46,63,2.0,1,8,Urban,HR Executive,23009,0 +87842,Male,57,Bachelors,11,16,70,69,1,3.0,6,4,Urban,ML Engineer,47654,0 +87843,Male,51,Masters,8,41,35,0,90,0.0,7,35,Rural,HR Executive,73756,0 +87844,Female,34,Masters,10,98,45,95,94,6.0,0,22,Semi-Urban,Software Engineer,76002,1 +87845,Male,22,Bachelors,8,83,26,21,30,8.0,2,88,Semi-Urban,ML Engineer,85368,0 +87846,Male,29,Masters,8,71,60,34,16,4.0,5,65,Urban,Software Engineer,33316,0 +87847,Female,43,Bachelors,12,52,56,45,89,3.0,3,23,Rural,ML Engineer,50252,0 +87848,Male,31,High School,14,31,5,93,84,8.0,4,49,Urban,HR Executive,149214,0 +87849,Male,40,High School,11,82,82,59,64,9.0,1,48,Semi-Urban,Data Analyst,61681,1 +87850,Male,21,Diploma,16,62,3,73,27,6.0,2,65,Urban,Manager,28432,0 +87851,Male,28,High School,8,56,34,73,65,8.0,5,97,Semi-Urban,ML Engineer,65853,1 +87852,Other,23,High School,2,83,50,86,41,2.0,1,30,Urban,Manager,105344,1 +87853,Other,48,Bachelors,18,69,93,80,13,2.0,4,53,Urban,ML Engineer,109322,1 +87854,Female,25,Masters,6,46,39,58,19,0.0,6,58,Rural,Software Engineer,30873,0 +87855,Male,25,High School,2,89,15,49,6,4.0,1,77,Urban,Data Analyst,119493,0 +87856,Male,23,Diploma,12,57,31,74,12,2.0,0,16,Semi-Urban,Software Engineer,142619,0 +87857,Male,22,Masters,10,93,20,36,4,0.0,5,28,Semi-Urban,Data Analyst,38743,0 +87858,Male,53,Diploma,11,85,27,37,89,6.0,2,82,Rural,Software Engineer,27640,0 +87859,Male,51,Bachelors,6,81,7,20,6,0.0,2,32,Urban,Data Analyst,67839,0 +87860,Male,31,Bachelors,4,20,91,94,1,4.0,4,57,Urban,Data Analyst,37268,1 +87861,Male,25,Bachelors,18,87,10,69,97,7.0,1,85,Rural,Data Analyst,25504,1 +87862,Male,32,Bachelors,7,54,55,0,47,9.0,1,3,Rural,ML Engineer,65856,0 +87863,Female,40,Masters,9,49,18,53,73,9.0,1,16,Urban,Data Analyst,27631,0 +87864,Male,38,PhD,5,33,54,25,84,8.0,4,36,Urban,Data Analyst,27357,0 +87865,Male,59,Masters,13,71,68,92,14,7.0,1,85,Semi-Urban,Software Engineer,95240,1 +87866,Male,51,Masters,1,53,34,61,97,2.0,2,0,Semi-Urban,Software Engineer,55294,0 +87867,Male,54,Bachelors,11,40,63,0,19,9.0,3,20,Urban,Software Engineer,137614,0 +87868,Female,26,Diploma,4,82,66,64,6,2.0,7,63,Urban,ML Engineer,95804,1 +87869,Male,48,Diploma,0,46,27,63,10,0.0,4,13,Urban,HR Executive,96834,0 +87870,Male,38,Bachelors,13,15,3,10,6,3.0,6,25,Urban,Manager,21632,0 +87871,Female,59,Bachelors,11,19,93,48,47,0.0,3,26,Rural,Software Engineer,141954,0 +87872,Male,34,Masters,9,22,65,12,35,2.0,2,28,Rural,Data Analyst,82733,0 +87873,Male,52,Masters,6,44,62,70,1,9.0,6,94,Semi-Urban,Manager,141262,1 +87874,Male,54,High School,16,46,71,18,32,8.0,3,29,Rural,HR Executive,32358,0 +87875,Female,26,PhD,8,82,8,58,58,1.0,6,46,Urban,Data Analyst,121998,0 +87876,Male,33,Diploma,5,18,3,15,93,8.0,7,89,Urban,Manager,145757,0 +87877,Female,42,Bachelors,7,4,28,4,85,7.0,0,23,Semi-Urban,ML Engineer,30467,0 +87878,Male,52,Diploma,15,26,96,85,70,2.0,4,71,Semi-Urban,HR Executive,21150,1 +87879,Male,48,Masters,9,3,58,69,58,3.0,1,62,Urban,Data Analyst,27457,0 +87880,Male,53,Bachelors,2,79,26,89,32,2.0,7,38,Urban,HR Executive,133509,0 +87881,Male,57,Bachelors,6,16,15,17,42,0.0,2,29,Rural,Data Analyst,127236,0 +87882,Male,21,Bachelors,9,46,17,38,69,5.0,4,45,Urban,Manager,111112,0 +87883,Female,38,Bachelors,18,68,65,30,10,0.0,7,42,Rural,Software Engineer,102738,0 +87884,Male,28,Bachelors,3,38,92,43,97,4.0,6,97,Semi-Urban,Manager,101718,1 +87885,Male,43,Masters,14,46,73,58,89,0.0,4,28,Semi-Urban,Data Analyst,92145,0 +87886,Female,22,High School,3,69,70,90,0,9.0,2,5,Urban,Software Engineer,46091,0 +87887,Male,41,Bachelors,0,22,28,9,47,3.0,6,38,Rural,HR Executive,48238,0 +87888,Female,26,Bachelors,0,41,41,68,7,1.0,3,68,Semi-Urban,Software Engineer,139592,0 +87889,Female,47,High School,6,14,45,18,31,2.0,5,18,Urban,Manager,59933,0 +87890,Female,51,Bachelors,4,4,93,91,12,7.0,2,42,Semi-Urban,ML Engineer,148386,0 +87891,Male,43,Bachelors,14,87,1,42,78,4.0,7,3,Semi-Urban,Manager,34330,0 +87892,Female,53,High School,18,70,99,18,54,1.0,2,24,Rural,HR Executive,124615,0 +87893,Female,35,Bachelors,13,48,14,36,20,7.0,2,5,Semi-Urban,ML Engineer,38980,0 +87894,Male,22,Masters,2,93,56,21,87,7.0,5,1,Semi-Urban,Software Engineer,39798,0 +87895,Female,29,High School,2,95,27,33,17,4.0,3,68,Urban,ML Engineer,133290,0 +87896,Male,49,High School,9,27,36,22,3,9.0,7,37,Urban,ML Engineer,108269,0 +87897,Male,47,Bachelors,2,21,32,52,64,3.0,4,49,Urban,ML Engineer,49195,0 +87898,Other,29,Diploma,14,18,88,66,12,4.0,6,84,Semi-Urban,ML Engineer,82294,1 +87899,Male,44,Masters,14,39,80,60,15,8.0,0,44,Semi-Urban,Software Engineer,106579,0 +87900,Male,40,PhD,16,44,20,29,39,5.0,2,13,Urban,ML Engineer,119263,0 +87901,Male,38,Masters,6,32,21,97,36,5.0,3,38,Urban,ML Engineer,30489,0 +87902,Male,56,High School,9,31,5,13,64,7.0,4,55,Rural,ML Engineer,79567,0 +87903,Female,48,High School,6,16,79,47,33,3.0,4,75,Rural,Data Analyst,90708,0 +87904,Female,30,Masters,9,2,35,69,81,5.0,5,13,Urban,Software Engineer,101416,0 +87905,Female,25,Masters,12,31,87,34,19,2.0,4,67,Urban,Software Engineer,43761,0 +87906,Male,24,Bachelors,16,44,87,7,43,7.0,1,7,Semi-Urban,HR Executive,92734,0 +87907,Female,36,Masters,4,32,14,57,76,0.0,2,77,Urban,Manager,93254,0 +87908,Female,37,Diploma,12,94,31,69,25,1.0,0,10,Semi-Urban,Software Engineer,23562,0 +87909,Male,35,High School,7,74,69,12,73,1.0,1,75,Rural,HR Executive,46632,0 +87910,Male,37,High School,16,53,17,62,31,2.0,2,0,Rural,Software Engineer,85319,0 +87911,Female,49,Diploma,10,60,30,52,99,3.0,2,94,Semi-Urban,Software Engineer,44212,0 +87912,Male,51,Bachelors,17,21,59,8,87,5.0,5,21,Urban,ML Engineer,136514,0 +87913,Female,57,High School,18,76,72,14,61,0.0,1,3,Semi-Urban,ML Engineer,74503,0 +87914,Female,35,Bachelors,3,83,66,98,7,7.0,5,39,Urban,HR Executive,35705,1 +87915,Female,53,Bachelors,15,40,72,97,39,5.0,0,39,Rural,Data Analyst,80976,1 +87916,Male,54,Bachelors,18,65,28,66,36,0.0,2,25,Rural,Software Engineer,33777,0 +87917,Male,44,Diploma,14,84,17,57,94,4.0,2,13,Urban,Software Engineer,65268,0 +87918,Male,44,Masters,1,54,68,10,84,6.0,1,98,Rural,Data Analyst,114716,0 +87919,Male,31,Bachelors,17,65,36,70,2,8.0,7,77,Urban,Data Analyst,119671,1 +87920,Female,48,Bachelors,11,6,63,80,92,1.0,6,12,Semi-Urban,Software Engineer,63542,0 +87921,Male,40,Bachelors,16,31,82,33,4,4.0,0,25,Rural,Software Engineer,92887,0 +87922,Male,44,Bachelors,18,10,2,55,51,1.0,4,72,Rural,HR Executive,28954,0 +87923,Male,44,PhD,14,67,7,77,77,9.0,1,87,Rural,Software Engineer,47110,1 +87924,Other,41,Bachelors,19,96,68,7,39,1.0,0,75,Semi-Urban,Software Engineer,63826,1 +87925,Female,22,Bachelors,4,30,74,92,91,4.0,5,64,Urban,ML Engineer,121313,1 +87926,Male,51,High School,9,63,85,54,25,1.0,4,46,Rural,ML Engineer,37843,1 +87927,Female,24,PhD,10,15,40,2,0,1.0,5,16,Urban,Manager,104189,0 +87928,Female,41,Bachelors,6,82,91,34,25,5.0,5,8,Urban,Manager,141211,0 +87929,Male,39,High School,7,87,3,35,33,3.0,2,44,Urban,Software Engineer,90710,0 +87930,Female,26,Bachelors,10,30,33,52,6,3.0,4,9,Urban,Manager,140657,0 +87931,Female,43,High School,5,45,73,23,76,1.0,7,22,Urban,Software Engineer,87703,0 +87932,Female,24,High School,14,28,90,43,95,3.0,1,2,Urban,HR Executive,139917,0 +87933,Female,47,Masters,14,53,30,23,29,4.0,4,54,Urban,Software Engineer,81189,0 +87934,Male,25,Diploma,14,25,2,34,45,3.0,0,91,Rural,HR Executive,143848,0 +87935,Male,58,Bachelors,14,8,64,34,32,4.0,5,92,Semi-Urban,Manager,55867,0 +87936,Male,38,Bachelors,14,42,0,65,64,9.0,7,83,Urban,ML Engineer,69861,0 +87937,Female,38,Masters,10,15,16,99,52,2.0,5,76,Semi-Urban,HR Executive,72919,0 +87938,Male,49,Bachelors,13,14,51,63,85,1.0,7,37,Urban,Data Analyst,136221,0 +87939,Male,59,Bachelors,8,29,17,53,77,5.0,6,82,Urban,Manager,32639,0 +87940,Male,37,Diploma,15,97,95,9,3,9.0,4,89,Urban,HR Executive,94170,1 +87941,Female,21,Masters,14,21,26,36,64,9.0,6,5,Urban,Manager,144483,0 +87942,Male,33,Bachelors,2,90,43,30,53,4.0,0,67,Urban,Software Engineer,85918,0 +87943,Female,30,Diploma,16,30,39,15,30,5.0,0,88,Urban,HR Executive,108652,0 +87944,Male,57,High School,14,41,56,86,17,9.0,4,44,Urban,HR Executive,137002,0 +87945,Male,27,Bachelors,15,94,74,97,53,0.0,4,37,Rural,Software Engineer,119836,1 +87946,Male,41,Bachelors,18,53,72,58,68,1.0,7,23,Semi-Urban,Data Analyst,127697,0 +87947,Female,27,Bachelors,10,2,49,40,12,1.0,2,8,Urban,HR Executive,99900,0 +87948,Male,23,Bachelors,5,7,11,53,8,1.0,2,85,Urban,Data Analyst,66656,0 +87949,Male,53,Masters,9,41,11,71,46,4.0,0,76,Rural,Data Analyst,143086,0 +87950,Female,49,Bachelors,14,78,5,58,80,9.0,2,15,Urban,ML Engineer,122463,0 +87951,Male,25,Bachelors,13,64,85,6,78,8.0,1,33,Urban,Software Engineer,145285,0 +87952,Male,49,Bachelors,5,27,90,72,2,4.0,3,77,Semi-Urban,Manager,41754,1 +87953,Male,42,Masters,2,70,12,20,87,2.0,4,73,Rural,Data Analyst,134212,0 +87954,Female,46,High School,11,73,46,61,43,2.0,5,58,Semi-Urban,Data Analyst,134093,0 +87955,Female,37,High School,15,29,85,84,68,1.0,4,50,Urban,ML Engineer,94324,1 +87956,Other,40,Diploma,3,4,86,15,43,1.0,7,0,Rural,HR Executive,101909,0 +87957,Female,54,Masters,12,11,79,50,74,0.0,3,78,Rural,Software Engineer,23598,0 +87958,Male,29,High School,5,96,68,39,99,8.0,7,90,Urban,HR Executive,49522,1 +87959,Male,50,High School,3,99,65,64,36,0.0,6,89,Urban,HR Executive,66035,1 +87960,Female,56,Diploma,12,64,53,28,68,4.0,3,64,Urban,HR Executive,36774,0 +87961,Female,33,Bachelors,11,68,53,36,71,8.0,7,62,Semi-Urban,Software Engineer,136464,0 +87962,Female,22,Bachelors,12,59,40,58,44,0.0,0,60,Semi-Urban,ML Engineer,82009,0 +87963,Female,27,Bachelors,0,76,33,92,72,2.0,5,91,Semi-Urban,Manager,147396,1 +87964,Female,59,Bachelors,10,79,84,66,28,0.0,3,40,Urban,Software Engineer,63247,1 +87965,Female,56,High School,6,53,89,94,58,9.0,1,99,Semi-Urban,ML Engineer,109098,1 +87966,Female,42,Masters,1,74,23,44,72,5.0,1,46,Rural,Data Analyst,94492,0 +87967,Male,23,Bachelors,0,6,82,89,43,3.0,1,32,Urban,Manager,61335,0 +87968,Male,54,Diploma,8,14,67,35,90,5.0,1,69,Rural,Manager,35037,0 +87969,Male,46,High School,9,99,17,61,1,4.0,2,15,Semi-Urban,ML Engineer,72783,0 +87970,Female,40,Masters,9,22,34,76,85,8.0,6,45,Semi-Urban,Data Analyst,71257,0 +87971,Male,37,Diploma,12,24,38,90,31,8.0,3,77,Urban,HR Executive,90030,0 +87972,Male,41,Diploma,13,66,71,39,11,3.0,5,16,Semi-Urban,Software Engineer,71756,0 +87973,Male,58,Masters,17,36,16,53,76,2.0,7,57,Urban,Manager,60978,0 +87974,Male,25,Bachelors,1,95,30,56,65,5.0,6,57,Semi-Urban,Software Engineer,136180,1 +87975,Male,57,Diploma,4,35,18,62,16,5.0,4,38,Semi-Urban,ML Engineer,122623,0 +87976,Other,56,Bachelors,0,18,72,40,63,2.0,2,79,Semi-Urban,Manager,44235,0 +87977,Female,22,Masters,9,52,6,90,93,4.0,1,40,Semi-Urban,HR Executive,105348,0 +87978,Male,46,Bachelors,14,44,6,44,85,2.0,1,94,Semi-Urban,Manager,141860,0 +87979,Male,43,Diploma,14,29,50,4,82,0.0,1,83,Rural,Software Engineer,107565,0 +87980,Female,49,Masters,11,47,44,71,64,8.0,4,33,Urban,Software Engineer,105845,0 +87981,Female,58,Bachelors,3,35,95,38,94,4.0,1,37,Semi-Urban,HR Executive,134047,0 +87982,Male,33,Bachelors,11,23,24,39,58,2.0,3,64,Urban,Data Analyst,75866,0 +87983,Female,50,Diploma,10,34,86,38,64,4.0,5,11,Rural,Manager,77041,0 +87984,Female,51,Masters,9,58,98,29,43,6.0,7,69,Urban,Manager,26137,1 +87985,Male,47,Bachelors,12,26,15,28,49,6.0,1,87,Urban,HR Executive,20008,0 +87986,Female,46,Diploma,12,0,89,48,56,5.0,7,17,Urban,HR Executive,149189,0 +87987,Male,36,Bachelors,9,61,57,55,11,8.0,2,58,Urban,Data Analyst,146490,0 +87988,Male,38,Bachelors,3,34,13,79,42,1.0,3,43,Urban,Software Engineer,132107,0 +87989,Female,47,Masters,2,62,42,72,33,9.0,7,29,Urban,Manager,73521,0 +87990,Male,54,Diploma,7,67,26,64,5,2.0,5,67,Rural,Software Engineer,30392,0 +87991,Male,54,Diploma,16,6,33,44,8,2.0,7,71,Semi-Urban,Software Engineer,23868,0 +87992,Female,29,Diploma,2,20,28,42,76,2.0,4,51,Semi-Urban,Software Engineer,33305,0 +87993,Male,33,Bachelors,1,69,90,19,64,6.0,3,26,Urban,Manager,73617,0 +87994,Male,43,PhD,3,85,44,83,87,4.0,5,97,Urban,Manager,64832,1 +87995,Male,55,High School,15,17,85,69,9,8.0,1,76,Rural,Data Analyst,61492,1 +87996,Female,56,Bachelors,6,78,47,5,82,6.0,7,59,Urban,Data Analyst,42522,0 +87997,Male,54,Bachelors,11,89,80,69,15,6.0,6,18,Semi-Urban,Data Analyst,96863,1 +87998,Female,43,Bachelors,16,81,42,76,25,8.0,0,46,Urban,HR Executive,87104,1 +87999,Male,27,PhD,18,95,8,30,70,0.0,7,88,Rural,HR Executive,133856,0 +88000,Female,32,Diploma,9,99,69,46,63,8.0,7,37,Urban,ML Engineer,52449,1 +88001,Male,22,Diploma,6,6,74,79,11,1.0,5,9,Urban,ML Engineer,64610,0 +88002,Male,31,Bachelors,14,99,60,61,69,9.0,6,55,Rural,ML Engineer,84060,1 +88003,Female,59,Bachelors,16,62,26,82,0,4.0,1,56,Rural,Data Analyst,48099,0 +88004,Male,21,Masters,19,25,29,33,1,7.0,6,59,Urban,Manager,103142,0 +88005,Other,53,Bachelors,3,61,94,46,13,5.0,5,61,Urban,Data Analyst,93405,1 +88006,Female,40,Bachelors,3,42,16,5,63,7.0,4,98,Semi-Urban,Manager,20813,0 +88007,Female,42,High School,12,97,91,40,82,8.0,7,11,Rural,Manager,66203,0 +88008,Male,43,Masters,0,54,50,88,59,2.0,3,34,Rural,Manager,55106,0 +88009,Female,55,Bachelors,9,21,97,32,65,5.0,0,5,Semi-Urban,Software Engineer,58676,0 +88010,Male,47,Bachelors,18,71,69,99,32,9.0,6,67,Rural,ML Engineer,62184,1 +88011,Male,31,Masters,19,95,1,2,9,9.0,0,65,Urban,HR Executive,38506,0 +88012,Female,28,High School,1,65,99,33,7,9.0,2,90,Rural,HR Executive,149495,1 +88013,Female,23,High School,18,65,51,64,42,4.0,2,31,Urban,ML Engineer,107859,0 +88014,Male,25,Masters,3,98,63,42,93,7.0,1,2,Semi-Urban,Data Analyst,39612,0 +88015,Male,43,Masters,9,89,18,43,9,4.0,6,79,Semi-Urban,ML Engineer,88467,0 +88016,Female,49,Masters,1,4,29,73,58,0.0,3,41,Urban,Manager,52905,0 +88017,Male,32,Diploma,18,71,30,29,30,3.0,3,51,Semi-Urban,ML Engineer,119527,0 +88018,Female,55,Bachelors,14,25,80,16,32,8.0,1,21,Rural,HR Executive,120527,0 +88019,Male,32,Masters,5,40,45,6,0,2.0,3,98,Semi-Urban,Data Analyst,29420,0 +88020,Female,32,Bachelors,12,95,17,99,0,7.0,4,57,Urban,Manager,91166,1 +88021,Male,43,High School,19,57,28,98,18,3.0,7,65,Urban,Manager,36920,1 +88022,Male,33,Diploma,16,93,91,86,41,5.0,6,29,Semi-Urban,Data Analyst,61156,1 +88023,Female,39,Bachelors,4,60,82,18,72,2.0,5,41,Rural,Software Engineer,146915,0 +88024,Female,29,High School,8,31,79,30,84,1.0,5,14,Urban,Data Analyst,50837,0 +88025,Female,56,Bachelors,17,28,23,54,80,9.0,6,31,Urban,Manager,133299,0 +88026,Female,58,Masters,16,13,98,49,80,5.0,2,44,Urban,HR Executive,117992,0 +88027,Male,38,Diploma,12,87,47,30,41,1.0,4,97,Semi-Urban,ML Engineer,118462,1 +88028,Male,37,Diploma,7,28,86,53,40,7.0,2,37,Rural,Software Engineer,107208,0 +88029,Female,59,Bachelors,3,27,77,44,58,7.0,5,96,Semi-Urban,ML Engineer,142572,1 +88030,Male,40,Diploma,8,17,15,38,6,2.0,6,13,Semi-Urban,Software Engineer,102151,0 +88031,Female,43,PhD,15,43,79,19,71,5.0,7,30,Urban,Software Engineer,107424,0 +88032,Female,58,Masters,11,74,23,2,39,6.0,2,20,Semi-Urban,Data Analyst,53633,0 +88033,Female,26,Masters,19,39,66,18,0,7.0,4,7,Rural,Software Engineer,126289,0 +88034,Male,42,Bachelors,3,70,56,92,62,7.0,3,49,Rural,Software Engineer,34543,1 +88035,Male,54,Masters,10,53,58,61,85,7.0,0,17,Rural,ML Engineer,35432,0 +88036,Female,21,Diploma,6,8,86,81,5,6.0,2,99,Rural,Manager,35899,1 +88037,Female,31,Masters,11,84,98,54,16,1.0,4,82,Semi-Urban,Data Analyst,125556,1 +88038,Female,47,Bachelors,15,41,81,60,84,3.0,3,15,Urban,Software Engineer,103160,0 +88039,Female,51,High School,3,63,69,74,0,8.0,5,1,Urban,Software Engineer,112132,0 +88040,Male,26,Diploma,3,90,0,96,63,6.0,0,7,Rural,ML Engineer,149322,0 +88041,Male,51,Diploma,2,21,79,89,36,6.0,2,10,Urban,Manager,64964,0 +88042,Male,50,Diploma,16,38,45,91,15,6.0,1,10,Urban,HR Executive,120242,0 +88043,Male,38,Bachelors,6,5,44,92,59,6.0,1,20,Semi-Urban,Data Analyst,65046,0 +88044,Male,32,High School,8,84,17,16,73,0.0,4,35,Rural,ML Engineer,32541,0 +88045,Male,26,Masters,14,8,46,42,31,3.0,0,34,Urban,Software Engineer,132900,0 +88046,Male,23,Diploma,12,57,83,41,2,2.0,4,84,Urban,Software Engineer,110808,1 +88047,Male,33,Diploma,17,19,69,65,45,5.0,5,3,Urban,Manager,95479,0 +88048,Male,39,Bachelors,9,63,46,84,82,6.0,5,15,Urban,ML Engineer,97321,0 +88049,Male,54,Masters,8,91,77,47,0,1.0,1,11,Urban,Manager,125862,0 +88050,Male,33,High School,6,17,22,53,20,0.0,1,73,Semi-Urban,Software Engineer,22124,0 +88051,Female,28,Bachelors,11,98,78,41,18,2.0,1,6,Urban,Data Analyst,103988,0 +88052,Male,49,Bachelors,16,0,45,21,30,6.0,2,65,Rural,Data Analyst,107444,0 +88053,Female,45,Masters,6,47,99,28,39,4.0,0,11,Semi-Urban,HR Executive,146743,0 +88054,Male,32,Bachelors,3,24,60,3,2,9.0,1,47,Semi-Urban,Data Analyst,30321,0 +88055,Male,41,Bachelors,11,97,75,78,38,0.0,5,65,Rural,HR Executive,98688,1 +88056,Male,29,Masters,15,99,60,49,83,5.0,3,54,Semi-Urban,HR Executive,68721,1 +88057,Male,37,Masters,15,64,34,54,65,6.0,1,26,Urban,Software Engineer,100012,0 +88058,Male,50,Bachelors,4,68,77,43,80,7.0,6,39,Rural,Data Analyst,30991,0 +88059,Male,49,Masters,9,11,97,52,79,7.0,4,87,Semi-Urban,Data Analyst,71252,1 +88060,Male,37,Masters,14,58,90,0,48,0.0,7,28,Rural,HR Executive,33626,0 +88061,Male,28,Bachelors,15,14,58,80,82,6.0,2,11,Rural,HR Executive,140437,0 +88062,Male,29,Masters,6,34,86,94,10,1.0,1,7,Urban,ML Engineer,103490,0 +88063,Female,53,Bachelors,18,40,34,49,0,2.0,6,14,Semi-Urban,Manager,118769,0 +88064,Male,26,Masters,18,59,37,53,61,4.0,4,37,Rural,Software Engineer,57881,0 +88065,Male,22,High School,10,3,72,76,76,4.0,5,50,Urban,ML Engineer,26331,0 +88066,Male,46,Masters,15,2,23,86,15,3.0,7,10,Urban,Manager,76721,0 +88067,Other,57,Bachelors,11,97,81,66,14,0.0,3,49,Urban,ML Engineer,100241,1 +88068,Male,42,High School,4,38,89,11,44,6.0,1,27,Urban,HR Executive,38174,0 +88069,Male,28,Masters,19,75,74,98,82,8.0,7,33,Rural,ML Engineer,27875,1 +88070,Male,47,Bachelors,12,60,77,53,68,6.0,5,48,Urban,HR Executive,115326,1 +88071,Other,52,High School,1,9,91,57,53,9.0,2,44,Urban,ML Engineer,111405,0 +88072,Female,28,Masters,5,66,48,43,66,8.0,4,64,Urban,HR Executive,108109,0 +88073,Male,48,Masters,13,72,23,11,29,2.0,1,51,Urban,Manager,112606,0 +88074,Male,36,High School,8,5,45,1,48,2.0,4,50,Urban,ML Engineer,37303,0 +88075,Male,25,Masters,11,10,37,58,40,8.0,5,46,Semi-Urban,Data Analyst,59679,0 +88076,Male,54,Bachelors,10,20,25,97,77,1.0,7,66,Urban,HR Executive,31770,0 +88077,Female,46,Masters,12,36,92,31,37,0.0,0,22,Urban,Manager,47322,0 +88078,Female,49,High School,5,45,62,89,6,3.0,5,50,Urban,Manager,26174,1 +88079,Female,45,Bachelors,2,10,14,41,57,3.0,5,98,Semi-Urban,Manager,96290,0 +88080,Male,56,High School,18,2,27,52,98,1.0,4,85,Semi-Urban,Manager,67138,0 +88081,Male,24,Bachelors,2,67,36,44,20,1.0,3,27,Semi-Urban,Data Analyst,128445,0 +88082,Male,32,High School,15,95,76,16,53,3.0,6,6,Urban,Manager,20103,0 +88083,Male,38,Bachelors,19,21,77,82,79,7.0,0,55,Urban,Software Engineer,124891,1 +88084,Male,51,Bachelors,19,48,11,15,74,6.0,1,88,Urban,HR Executive,145094,0 +88085,Other,37,High School,1,59,41,37,70,9.0,5,16,Rural,Manager,22163,0 +88086,Female,38,Bachelors,13,87,34,28,17,4.0,6,99,Urban,Manager,33302,1 +88087,Male,22,High School,15,71,40,1,36,4.0,1,19,Semi-Urban,HR Executive,101610,0 +88088,Female,32,Bachelors,10,52,82,7,72,1.0,7,57,Urban,Manager,115316,0 +88089,Male,37,Diploma,14,6,6,18,29,7.0,1,90,Rural,HR Executive,66076,0 +88090,Male,40,Masters,15,53,13,51,73,3.0,2,39,Urban,Software Engineer,36564,0 +88091,Female,27,High School,6,14,20,28,9,4.0,0,2,Urban,Software Engineer,97637,0 +88092,Male,24,Masters,10,93,24,94,84,0.0,1,4,Semi-Urban,Manager,90078,0 +88093,Male,31,PhD,11,92,31,56,7,2.0,3,67,Urban,HR Executive,77646,1 +88094,Male,54,High School,8,5,14,47,43,7.0,5,88,Semi-Urban,ML Engineer,33866,0 +88095,Female,41,Diploma,0,39,27,96,17,4.0,4,26,Urban,Software Engineer,99780,0 +88096,Male,44,High School,13,88,71,8,35,0.0,6,42,Urban,Software Engineer,94365,0 +88097,Male,31,Masters,6,76,29,61,75,7.0,5,22,Rural,Data Analyst,34156,0 +88098,Male,28,High School,3,80,43,19,30,4.0,2,64,Urban,Data Analyst,89038,0 +88099,Male,38,Bachelors,10,14,51,67,13,3.0,4,41,Urban,HR Executive,113549,0 +88100,Male,25,Diploma,9,54,86,70,87,5.0,3,88,Semi-Urban,Manager,109527,1 +88101,Female,42,Bachelors,6,8,68,48,47,5.0,5,83,Semi-Urban,ML Engineer,67973,0 +88102,Female,25,Masters,3,78,18,58,98,3.0,4,6,Urban,HR Executive,69957,0 +88103,Male,52,High School,11,96,1,50,19,8.0,1,49,Rural,ML Engineer,71506,0 +88104,Female,25,Diploma,2,52,36,17,81,0.0,4,72,Urban,Manager,135124,0 +88105,Female,29,Masters,7,16,34,20,45,7.0,7,11,Semi-Urban,HR Executive,127250,0 +88106,Male,49,Bachelors,18,47,60,15,79,8.0,1,14,Urban,ML Engineer,90551,0 +88107,Male,40,High School,2,17,37,7,13,2.0,5,78,Urban,Software Engineer,132928,0 +88108,Male,47,Bachelors,10,25,16,85,29,8.0,3,0,Urban,Manager,148188,0 +88109,Female,57,Diploma,15,89,14,61,97,7.0,5,44,Rural,ML Engineer,91139,0 +88110,Male,47,Diploma,17,85,44,27,87,4.0,0,25,Urban,ML Engineer,42607,0 +88111,Female,42,Bachelors,19,61,12,79,41,2.0,4,29,Urban,ML Engineer,61703,0 +88112,Male,36,Bachelors,13,45,22,4,77,0.0,5,27,Urban,Software Engineer,81720,0 +88113,Male,25,Diploma,17,44,32,1,42,2.0,0,74,Semi-Urban,HR Executive,118170,0 +88114,Male,34,Masters,5,51,95,29,64,7.0,1,55,Rural,Data Analyst,22594,0 +88115,Female,45,High School,16,92,20,64,78,0.0,6,18,Urban,Manager,134602,0 +88116,Female,42,PhD,0,30,93,82,13,6.0,5,79,Urban,Data Analyst,131835,1 +88117,Male,57,Masters,12,65,92,92,19,5.0,3,77,Semi-Urban,Data Analyst,79236,1 +88118,Male,49,Bachelors,18,75,89,22,27,3.0,6,24,Rural,Data Analyst,57633,0 +88119,Male,54,Diploma,16,94,8,40,11,6.0,1,32,Rural,HR Executive,60354,0 +88120,Male,33,Masters,1,15,92,42,81,2.0,4,86,Urban,Software Engineer,58325,1 +88121,Female,56,High School,4,53,94,6,89,7.0,6,90,Urban,Manager,109805,1 +88122,Male,33,High School,12,32,68,70,70,2.0,3,64,Urban,Manager,93205,0 +88123,Female,52,Bachelors,1,72,13,69,64,9.0,0,99,Urban,Data Analyst,130779,1 +88124,Male,32,High School,17,99,94,75,98,4.0,4,15,Semi-Urban,Software Engineer,58062,1 +88125,Female,59,Masters,1,41,3,67,93,0.0,2,69,Semi-Urban,Data Analyst,49337,0 +88126,Male,35,Diploma,1,82,93,22,66,8.0,3,7,Semi-Urban,ML Engineer,137450,0 +88127,Male,52,Masters,4,28,17,82,96,4.0,5,92,Semi-Urban,HR Executive,117745,0 +88128,Male,58,Diploma,5,24,8,81,98,8.0,3,41,Rural,Manager,58678,0 +88129,Male,47,Masters,11,48,77,2,60,4.0,0,49,Semi-Urban,HR Executive,73011,0 +88130,Male,26,Bachelors,6,53,12,72,90,5.0,5,70,Semi-Urban,Manager,38506,0 +88131,Female,33,Diploma,15,51,54,5,16,5.0,6,89,Urban,HR Executive,51953,0 +88132,Male,30,Bachelors,4,80,32,98,45,1.0,4,6,Rural,HR Executive,116193,0 +88133,Male,22,Bachelors,16,76,77,13,73,1.0,6,3,Urban,Data Analyst,46204,0 +88134,Female,41,High School,3,62,58,78,44,8.0,6,88,Urban,Data Analyst,118819,1 +88135,Male,32,Masters,17,88,59,36,88,0.0,6,75,Rural,Data Analyst,100298,1 +88136,Female,30,Masters,11,24,42,69,0,9.0,3,74,Semi-Urban,Software Engineer,58289,0 +88137,Female,33,Diploma,16,88,81,63,19,2.0,2,47,Semi-Urban,ML Engineer,29581,1 +88138,Male,34,Bachelors,5,88,3,89,98,6.0,4,6,Semi-Urban,Software Engineer,50387,0 +88139,Female,32,High School,8,43,60,43,30,3.0,7,22,Rural,ML Engineer,51368,0 +88140,Male,57,Masters,9,49,88,28,17,5.0,6,28,Semi-Urban,Software Engineer,28930,0 +88141,Male,23,High School,9,35,21,97,63,2.0,0,17,Urban,HR Executive,64920,0 +88142,Female,42,Bachelors,7,6,23,58,55,3.0,4,41,Urban,ML Engineer,61559,0 +88143,Male,56,Bachelors,2,54,3,68,8,2.0,1,62,Semi-Urban,Data Analyst,67634,0 +88144,Male,26,Masters,9,88,44,72,61,8.0,5,97,Urban,ML Engineer,129230,1 +88145,Other,26,PhD,7,10,21,82,1,5.0,0,58,Urban,Manager,83725,0 +88146,Male,43,Bachelors,9,47,55,77,38,2.0,6,92,Urban,Software Engineer,45213,1 +88147,Male,24,Masters,15,14,76,53,54,6.0,2,34,Semi-Urban,HR Executive,47819,0 +88148,Female,23,Diploma,12,83,35,96,71,2.0,7,59,Urban,Software Engineer,136606,1 +88149,Male,49,Diploma,12,64,22,81,28,8.0,0,69,Urban,Manager,88707,1 +88150,Female,27,Bachelors,4,55,35,39,3,9.0,6,41,Semi-Urban,HR Executive,28781,0 +88151,Male,30,Diploma,0,51,57,65,94,4.0,3,25,Rural,Manager,50308,0 +88152,Male,51,Diploma,4,67,75,32,67,0.0,3,36,Semi-Urban,ML Engineer,106762,0 +88153,Male,36,Bachelors,17,33,39,10,96,3.0,5,23,Rural,ML Engineer,27403,0 +88154,Male,39,Diploma,4,38,81,38,10,2.0,3,32,Urban,Software Engineer,32530,0 +88155,Male,45,Bachelors,11,87,28,9,13,9.0,1,91,Urban,ML Engineer,68527,0 +88156,Male,21,Masters,10,95,67,54,99,4.0,4,15,Semi-Urban,Software Engineer,80326,0 +88157,Female,41,Diploma,16,85,81,86,94,0.0,3,0,Rural,Software Engineer,54493,1 +88158,Male,43,Bachelors,11,76,91,97,42,6.0,0,11,Urban,Manager,88478,1 +88159,Male,42,Masters,18,82,45,57,8,6.0,6,70,Semi-Urban,HR Executive,49144,1 +88160,Male,54,Diploma,7,31,7,80,39,1.0,6,96,Urban,ML Engineer,148898,0 +88161,Other,38,Diploma,10,14,69,15,39,2.0,5,61,Urban,Manager,146712,0 +88162,Male,37,Bachelors,11,9,95,39,94,3.0,4,55,Semi-Urban,Manager,48481,0 +88163,Female,33,Diploma,7,88,61,92,45,5.0,2,70,Urban,ML Engineer,33680,1 +88164,Female,29,Diploma,6,6,73,41,34,6.0,7,91,Urban,ML Engineer,136768,0 +88165,Female,45,Masters,1,96,47,71,14,1.0,2,31,Semi-Urban,ML Engineer,106710,1 +88166,Female,44,Diploma,17,41,77,38,70,0.0,3,95,Semi-Urban,Data Analyst,101801,1 +88167,Male,39,Bachelors,16,56,10,53,32,5.0,6,75,Urban,ML Engineer,72228,0 +88168,Male,56,Masters,19,1,89,91,35,7.0,0,6,Semi-Urban,Software Engineer,74871,0 +88169,Female,33,Bachelors,3,74,66,75,44,2.0,2,24,Rural,Data Analyst,100617,0 +88170,Female,32,Bachelors,0,86,46,20,89,5.0,6,42,Urban,Manager,126753,0 +88171,Male,48,High School,10,3,99,55,14,4.0,4,65,Urban,ML Engineer,111668,0 +88172,Female,21,PhD,14,36,11,91,84,0.0,7,66,Urban,Software Engineer,80138,0 +88173,Female,53,Masters,11,5,72,28,87,5.0,6,79,Urban,ML Engineer,139560,0 +88174,Male,34,Bachelors,19,65,44,78,89,0.0,0,79,Rural,Data Analyst,108634,1 +88175,Female,40,Masters,8,48,14,91,72,1.0,6,48,Urban,Data Analyst,106451,0 +88176,Male,30,Masters,7,24,82,51,61,9.0,1,11,Rural,Data Analyst,117941,0 +88177,Male,56,Bachelors,15,55,42,77,92,7.0,0,70,Urban,HR Executive,117430,1 +88178,Female,23,Masters,9,89,54,96,67,5.0,1,95,Semi-Urban,Manager,71175,1 +88179,Male,25,Diploma,6,63,59,87,68,1.0,3,63,Urban,Manager,55788,1 +88180,Male,56,High School,1,70,66,49,97,3.0,2,67,Urban,Manager,76119,1 +88181,Male,27,Diploma,9,98,95,44,39,9.0,7,42,Urban,HR Executive,143461,1 +88182,Male,41,Masters,3,59,19,65,96,1.0,6,88,Semi-Urban,Data Analyst,64838,0 +88183,Female,22,High School,0,38,46,34,98,6.0,3,34,Urban,ML Engineer,85359,0 +88184,Male,49,Masters,3,28,15,90,62,4.0,2,48,Semi-Urban,Manager,71865,0 +88185,Male,53,Bachelors,12,42,3,33,36,1.0,3,31,Semi-Urban,ML Engineer,127310,0 +88186,Male,52,Masters,13,28,27,66,80,5.0,3,22,Semi-Urban,ML Engineer,148320,0 +88187,Male,24,Diploma,6,8,28,5,93,9.0,1,17,Rural,HR Executive,27710,0 +88188,Female,32,Diploma,12,77,87,44,2,3.0,1,87,Semi-Urban,Software Engineer,140437,1 +88189,Female,36,Diploma,12,12,0,97,20,3.0,2,84,Rural,Manager,141341,0 +88190,Male,51,Masters,7,14,13,23,87,2.0,6,5,Rural,ML Engineer,131432,0 +88191,Female,30,Diploma,7,27,39,61,82,6.0,4,72,Semi-Urban,Data Analyst,101596,0 +88192,Female,31,Bachelors,12,6,68,86,92,4.0,1,66,Semi-Urban,Manager,60855,0 +88193,Male,21,High School,16,26,58,80,6,9.0,4,31,Rural,ML Engineer,55196,0 +88194,Female,37,Masters,19,87,57,42,64,7.0,6,25,Semi-Urban,Software Engineer,86580,0 +88195,Female,29,Diploma,7,50,26,12,67,4.0,2,72,Urban,Data Analyst,39025,0 +88196,Male,27,Diploma,16,79,40,83,32,2.0,1,44,Urban,Manager,119361,1 +88197,Female,21,High School,0,31,7,87,7,4.0,5,49,Urban,Manager,25076,0 +88198,Female,30,Bachelors,0,16,64,70,63,5.0,2,15,Urban,Manager,61675,0 +88199,Male,52,High School,13,10,99,8,56,4.0,1,4,Urban,HR Executive,76822,0 +88200,Female,43,Diploma,12,23,66,22,93,5.0,0,58,Semi-Urban,ML Engineer,61625,0 +88201,Male,25,Bachelors,7,5,74,29,3,0.0,6,43,Urban,HR Executive,125534,0 +88202,Female,32,Bachelors,10,78,1,69,72,6.0,4,3,Urban,Data Analyst,149383,0 +88203,Male,37,High School,4,75,83,55,72,0.0,2,16,Semi-Urban,ML Engineer,84335,0 +88204,Male,41,Bachelors,5,60,94,94,47,6.0,1,35,Semi-Urban,ML Engineer,95882,1 +88205,Female,43,Masters,14,37,12,59,64,9.0,1,94,Semi-Urban,Software Engineer,75769,0 +88206,Male,49,Bachelors,6,45,15,26,33,7.0,3,88,Urban,HR Executive,145801,0 +88207,Male,54,High School,11,71,82,32,93,2.0,0,23,Semi-Urban,HR Executive,55687,0 +88208,Male,47,Bachelors,0,2,1,53,33,8.0,1,89,Urban,Software Engineer,87297,0 +88209,Male,23,High School,16,49,3,92,57,8.0,0,23,Semi-Urban,ML Engineer,89919,0 +88210,Male,34,Bachelors,9,59,98,98,74,9.0,6,89,Semi-Urban,HR Executive,31358,1 +88211,Other,43,Bachelors,9,98,44,79,23,9.0,4,66,Urban,Manager,29593,1 +88212,Female,39,Masters,9,16,73,90,53,8.0,3,75,Semi-Urban,Manager,83074,1 +88213,Male,46,Bachelors,19,13,7,71,41,1.0,4,79,Urban,Manager,22113,0 +88214,Female,40,Bachelors,10,40,15,68,73,1.0,5,2,Urban,Software Engineer,33245,0 +88215,Male,29,Masters,8,14,96,56,2,0.0,6,65,Urban,HR Executive,100110,0 +88216,Male,31,Diploma,16,2,7,14,70,0.0,6,73,Rural,HR Executive,45564,0 +88217,Female,25,Masters,2,34,84,24,9,7.0,0,47,Urban,HR Executive,90397,0 +88218,Male,34,Bachelors,15,15,57,8,41,8.0,3,99,Urban,Manager,120130,0 +88219,Female,44,Masters,18,16,58,18,34,0.0,0,24,Urban,ML Engineer,77971,0 +88220,Female,52,Diploma,3,33,20,98,71,8.0,7,32,Urban,ML Engineer,35435,0 +88221,Female,42,Bachelors,11,53,1,72,4,9.0,3,4,Urban,Software Engineer,88848,0 +88222,Female,56,High School,19,64,75,75,35,5.0,3,61,Urban,Data Analyst,88426,1 +88223,Female,30,Bachelors,11,27,54,79,15,8.0,7,30,Rural,Software Engineer,34014,0 +88224,Female,48,Masters,3,13,5,48,48,1.0,5,3,Rural,Software Engineer,133714,0 +88225,Female,25,High School,7,95,68,62,16,2.0,4,8,Urban,Software Engineer,116372,0 +88226,Male,25,Bachelors,18,72,6,65,79,5.0,1,39,Urban,Data Analyst,105153,0 +88227,Male,55,Masters,11,39,57,51,6,7.0,1,64,Semi-Urban,Software Engineer,32251,0 +88228,Female,27,Diploma,8,92,53,30,9,2.0,2,37,Rural,ML Engineer,138616,0 +88229,Other,53,Masters,15,89,12,45,43,9.0,1,77,Urban,Manager,113076,0 +88230,Female,41,Masters,15,93,81,38,14,5.0,1,72,Urban,Manager,101784,1 +88231,Male,29,Diploma,3,28,81,69,85,8.0,2,16,Urban,Manager,68595,0 +88232,Male,56,Bachelors,19,19,39,17,28,5.0,1,21,Urban,ML Engineer,90138,0 +88233,Female,25,Bachelors,3,72,29,27,79,1.0,3,87,Rural,Software Engineer,59756,0 +88234,Female,26,Bachelors,9,51,75,12,18,4.0,7,7,Rural,Manager,85404,0 +88235,Male,52,Diploma,8,37,64,91,59,3.0,5,70,Urban,ML Engineer,112437,1 +88236,Female,45,Masters,13,47,28,56,47,0.0,6,52,Rural,HR Executive,98090,0 +88237,Other,22,Bachelors,14,87,53,11,23,8.0,1,45,Semi-Urban,Software Engineer,134305,0 +88238,Male,45,Diploma,3,43,67,96,54,4.0,6,83,Semi-Urban,HR Executive,127737,1 +88239,Male,52,Bachelors,4,68,39,73,84,6.0,0,10,Rural,HR Executive,134943,0 +88240,Male,21,Bachelors,6,83,34,79,46,4.0,5,0,Urban,Data Analyst,58643,0 +88241,Other,25,Diploma,2,8,64,44,40,6.0,5,90,Urban,Software Engineer,83182,0 +88242,Male,57,Diploma,9,21,58,61,11,8.0,5,84,Semi-Urban,HR Executive,119362,0 +88243,Female,40,PhD,3,65,56,92,12,1.0,0,80,Rural,Manager,43386,1 +88244,Male,24,Bachelors,8,64,38,45,80,2.0,0,30,Rural,Data Analyst,92052,0 +88245,Female,58,Masters,11,11,54,40,44,9.0,6,44,Semi-Urban,ML Engineer,65404,0 +88246,Male,48,Masters,4,79,65,27,70,6.0,1,5,Urban,ML Engineer,108090,0 +88247,Male,44,Diploma,16,46,10,81,51,6.0,3,42,Urban,Software Engineer,52184,0 +88248,Male,27,Bachelors,11,42,61,73,24,8.0,6,22,Semi-Urban,Data Analyst,60505,0 +88249,Male,22,Diploma,8,24,88,32,54,9.0,2,26,Urban,Data Analyst,43409,0 +88250,Male,52,Diploma,10,6,40,78,31,8.0,7,91,Urban,Manager,38670,0 +88251,Male,31,Bachelors,16,81,4,60,26,7.0,5,76,Urban,Software Engineer,94011,0 +88252,Female,38,Bachelors,6,64,99,69,89,3.0,1,98,Rural,HR Executive,77384,1 +88253,Female,35,Bachelors,13,57,99,93,87,6.0,6,22,Rural,Data Analyst,136319,1 +88254,Male,44,PhD,13,5,68,80,27,3.0,0,90,Urban,ML Engineer,110513,1 +88255,Male,36,PhD,11,1,44,41,9,4.0,6,90,Urban,Software Engineer,31559,0 +88256,Male,48,Bachelors,14,43,60,21,25,1.0,1,99,Rural,Software Engineer,43420,0 +88257,Female,42,Masters,7,87,9,2,71,4.0,4,99,Semi-Urban,Software Engineer,95236,0 +88258,Male,23,Bachelors,5,30,93,39,46,3.0,6,29,Urban,Data Analyst,61637,0 +88259,Male,26,Masters,12,2,49,88,84,1.0,2,21,Urban,Software Engineer,54555,0 +88260,Female,36,Diploma,3,84,76,35,25,5.0,7,14,Rural,Manager,92440,0 +88261,Male,39,Masters,4,26,46,82,58,7.0,3,1,Urban,ML Engineer,106109,0 +88262,Male,58,Bachelors,6,52,44,16,61,7.0,2,15,Rural,HR Executive,65834,0 +88263,Female,24,Bachelors,0,56,51,88,76,3.0,0,24,Urban,Manager,26934,0 +88264,Female,54,Bachelors,0,35,47,66,98,7.0,6,5,Urban,Software Engineer,106361,0 +88265,Male,26,Bachelors,7,92,73,16,69,9.0,7,75,Urban,Software Engineer,124850,1 +88266,Male,44,Bachelors,13,97,57,92,89,8.0,2,97,Urban,HR Executive,94704,1 +88267,Male,35,Bachelors,9,90,45,62,37,2.0,5,65,Urban,Manager,24463,1 +88268,Other,28,Bachelors,1,73,30,32,64,0.0,4,0,Rural,HR Executive,130713,0 +88269,Male,26,High School,14,39,64,50,43,5.0,0,67,Urban,ML Engineer,41684,0 +88270,Male,57,Bachelors,9,25,35,6,53,0.0,2,97,Semi-Urban,Software Engineer,75062,0 +88271,Female,59,PhD,1,65,49,84,49,3.0,3,16,Rural,ML Engineer,134241,0 +88272,Male,57,High School,16,35,51,9,90,9.0,2,38,Urban,ML Engineer,85160,0 +88273,Male,50,High School,6,23,83,17,32,5.0,5,54,Urban,ML Engineer,108454,0 +88274,Male,29,Bachelors,15,83,89,33,62,7.0,1,48,Semi-Urban,Data Analyst,20352,1 +88275,Female,50,High School,18,89,0,49,25,2.0,2,63,Urban,Manager,134026,0 +88276,Female,52,High School,11,69,89,48,66,1.0,4,97,Urban,Software Engineer,38617,1 +88277,Female,39,Bachelors,12,42,72,20,45,2.0,1,48,Urban,Software Engineer,57902,0 +88278,Male,34,Diploma,15,22,74,98,12,4.0,2,51,Semi-Urban,ML Engineer,89700,1 +88279,Male,36,Bachelors,4,90,70,78,12,6.0,7,91,Semi-Urban,ML Engineer,89484,1 +88280,Male,57,Bachelors,16,6,9,5,69,8.0,4,69,Urban,HR Executive,60566,0 +88281,Female,30,Masters,11,3,58,0,58,8.0,0,16,Urban,Manager,85270,0 +88282,Male,53,High School,2,60,45,7,83,2.0,4,22,Urban,ML Engineer,113458,0 +88283,Male,22,Bachelors,7,5,90,21,98,4.0,6,84,Urban,HR Executive,63347,0 +88284,Male,49,Diploma,17,86,3,82,14,8.0,3,12,Urban,ML Engineer,143032,0 +88285,Male,45,Bachelors,3,95,34,16,1,2.0,7,67,Urban,Manager,116077,0 +88286,Male,29,Diploma,10,23,19,0,56,7.0,4,8,Rural,HR Executive,46865,0 +88287,Other,25,Bachelors,11,51,29,76,12,6.0,2,14,Urban,Manager,56676,0 +88288,Male,28,High School,17,29,36,70,44,3.0,6,42,Urban,Data Analyst,59853,0 +88289,Male,54,Diploma,1,1,28,23,17,7.0,1,95,Semi-Urban,Manager,83471,0 +88290,Male,38,High School,18,42,4,64,38,4.0,2,99,Semi-Urban,Software Engineer,134286,0 +88291,Male,49,Bachelors,2,71,94,83,17,8.0,0,76,Urban,Manager,53412,1 +88292,Other,25,PhD,2,91,83,83,19,3.0,6,95,Rural,ML Engineer,98545,1 +88293,Male,39,High School,1,72,55,87,0,5.0,1,39,Urban,Manager,77724,1 +88294,Female,27,Masters,10,69,95,88,56,0.0,7,26,Semi-Urban,ML Engineer,24730,1 +88295,Female,43,Bachelors,0,46,99,88,95,3.0,6,17,Semi-Urban,HR Executive,107061,1 +88296,Male,29,Bachelors,7,2,76,13,53,3.0,2,49,Rural,ML Engineer,38652,0 +88297,Male,38,Bachelors,1,87,30,86,66,5.0,4,67,Urban,Data Analyst,96877,1 +88298,Male,52,Diploma,7,53,72,69,3,2.0,4,50,Rural,Data Analyst,76159,1 +88299,Male,27,High School,3,37,84,32,97,4.0,6,19,Semi-Urban,ML Engineer,106985,0 +88300,Male,38,Bachelors,7,62,15,21,53,5.0,2,69,Semi-Urban,HR Executive,74840,0 +88301,Male,48,Bachelors,2,29,71,2,55,4.0,1,35,Semi-Urban,HR Executive,25850,0 +88302,Other,41,Diploma,6,76,3,15,73,7.0,5,96,Urban,Manager,122097,0 +88303,Male,57,Bachelors,0,96,60,10,0,8.0,4,16,Rural,Data Analyst,94617,0 +88304,Male,39,Masters,2,24,8,61,81,0.0,5,56,Semi-Urban,HR Executive,115252,0 +88305,Female,56,Masters,6,94,35,42,44,7.0,1,81,Semi-Urban,HR Executive,109233,1 +88306,Male,21,Bachelors,9,35,23,11,98,1.0,2,67,Rural,Data Analyst,45116,0 +88307,Male,58,Bachelors,14,10,88,46,50,6.0,2,25,Rural,Software Engineer,138810,0 +88308,Male,28,Bachelors,12,82,43,30,97,2.0,1,60,Rural,Data Analyst,40909,0 +88309,Other,54,Bachelors,0,44,11,46,35,9.0,1,59,Urban,HR Executive,58945,0 +88310,Male,36,Masters,13,58,84,58,30,1.0,5,7,Urban,Data Analyst,59293,0 +88311,Male,39,Diploma,4,52,62,3,31,9.0,0,78,Rural,ML Engineer,112779,0 +88312,Male,31,Masters,18,49,64,44,29,4.0,7,61,Urban,Software Engineer,92458,0 +88313,Male,32,Diploma,6,42,85,90,30,8.0,1,23,Urban,Data Analyst,105531,1 +88314,Female,57,Bachelors,2,13,43,75,21,4.0,6,48,Urban,Manager,133097,0 +88315,Other,57,Bachelors,0,12,14,22,12,5.0,0,86,Urban,HR Executive,80930,0 +88316,Female,43,Bachelors,8,9,35,33,0,5.0,7,47,Urban,Data Analyst,54868,0 +88317,Male,34,Diploma,19,45,31,43,22,7.0,7,61,Rural,Data Analyst,31735,0 +88318,Female,42,Bachelors,4,80,60,76,18,4.0,2,16,Urban,Manager,99471,0 +88319,Male,23,Bachelors,3,73,76,77,3,8.0,7,58,Urban,Data Analyst,96880,1 +88320,Male,51,PhD,7,61,40,79,31,2.0,2,92,Urban,ML Engineer,56062,1 +88321,Female,30,Diploma,7,24,45,4,39,3.0,6,57,Urban,Data Analyst,99551,0 +88322,Female,32,Bachelors,8,25,22,67,51,9.0,6,60,Rural,Software Engineer,110783,0 +88323,Female,54,Masters,3,86,74,4,73,1.0,1,77,Semi-Urban,HR Executive,135136,1 +88324,Female,46,Diploma,12,10,3,58,83,6.0,6,22,Rural,HR Executive,26783,0 +88325,Male,36,Bachelors,13,64,86,64,94,7.0,7,62,Urban,Data Analyst,145868,1 +88326,Male,28,Bachelors,9,56,6,17,89,2.0,1,48,Urban,Manager,59743,0 +88327,Male,50,Bachelors,4,10,25,6,4,0.0,2,36,Urban,Software Engineer,93160,0 +88328,Female,27,High School,10,8,14,31,7,7.0,3,92,Urban,Software Engineer,105931,0 +88329,Male,41,High School,16,2,61,20,42,3.0,0,2,Urban,Manager,111940,0 +88330,Male,50,Diploma,5,49,58,22,49,4.0,3,90,Rural,HR Executive,27949,0 +88331,Male,30,PhD,9,31,41,71,72,4.0,0,69,Rural,Software Engineer,86864,0 +88332,Male,42,Bachelors,12,95,48,11,58,7.0,5,5,Urban,Software Engineer,92199,0 +88333,Male,58,PhD,0,41,43,55,68,7.0,7,39,Urban,Software Engineer,37272,0 +88334,Male,56,Diploma,7,33,52,96,25,9.0,3,63,Urban,Software Engineer,112891,1 +88335,Male,33,PhD,2,43,88,34,47,3.0,3,22,Rural,Data Analyst,88251,0 +88336,Male,39,Bachelors,0,82,8,67,68,1.0,3,89,Rural,Software Engineer,95219,1 +88337,Other,32,High School,10,21,29,97,15,6.0,5,57,Urban,Manager,51350,0 +88338,Male,44,Bachelors,11,0,74,60,7,9.0,2,35,Urban,ML Engineer,145724,0 +88339,Female,57,Bachelors,17,8,83,17,70,4.0,3,75,Urban,Manager,78595,0 +88340,Female,50,Bachelors,11,58,53,67,19,6.0,3,19,Urban,Software Engineer,91280,0 +88341,Female,50,High School,19,43,79,36,47,4.0,0,89,Semi-Urban,ML Engineer,95929,1 +88342,Male,24,Diploma,14,8,3,17,9,4.0,3,81,Semi-Urban,Software Engineer,132019,0 +88343,Male,35,Masters,1,17,59,34,92,1.0,5,39,Urban,HR Executive,105517,0 +88344,Other,37,Diploma,8,2,73,34,18,0.0,7,74,Rural,ML Engineer,109888,0 +88345,Male,53,Masters,2,71,82,67,38,9.0,1,88,Urban,ML Engineer,130235,1 +88346,Male,45,Diploma,10,56,31,79,14,4.0,3,45,Rural,Data Analyst,128286,0 +88347,Female,22,Diploma,3,3,90,2,12,0.0,5,71,Urban,Data Analyst,71287,0 +88348,Male,51,Diploma,9,6,6,13,99,9.0,6,52,Rural,HR Executive,119325,0 +88349,Male,32,Masters,16,6,74,43,37,8.0,6,99,Urban,Data Analyst,39769,0 +88350,Female,28,Bachelors,18,11,18,28,29,2.0,0,22,Semi-Urban,Software Engineer,122304,0 +88351,Female,48,High School,3,42,37,10,67,9.0,6,69,Urban,HR Executive,57155,0 +88352,Male,29,Masters,8,16,65,23,97,6.0,5,51,Semi-Urban,HR Executive,53455,0 +88353,Male,58,Masters,5,19,25,65,72,1.0,5,40,Semi-Urban,Manager,114815,0 +88354,Female,47,Bachelors,18,26,93,81,65,3.0,4,15,Semi-Urban,Manager,59349,0 +88355,Male,52,Bachelors,2,4,7,96,3,1.0,1,10,Urban,ML Engineer,30671,0 +88356,Female,26,Diploma,10,50,71,56,36,9.0,3,73,Urban,ML Engineer,42696,1 +88357,Male,58,Bachelors,14,35,17,38,86,5.0,6,39,Urban,ML Engineer,45675,0 +88358,Female,33,Bachelors,16,39,27,89,82,5.0,5,44,Semi-Urban,ML Engineer,24172,0 +88359,Male,21,Masters,3,1,86,37,80,8.0,1,29,Semi-Urban,HR Executive,40107,0 +88360,Male,32,Diploma,19,35,66,48,36,0.0,4,1,Semi-Urban,Software Engineer,40312,0 +88361,Other,29,Bachelors,8,41,9,70,69,7.0,7,92,Urban,Software Engineer,128117,0 +88362,Male,29,Bachelors,6,5,99,43,85,6.0,1,36,Urban,Data Analyst,64805,0 +88363,Other,53,Bachelors,15,21,14,0,89,5.0,3,0,Urban,ML Engineer,129160,0 +88364,Female,32,Diploma,2,91,1,58,77,1.0,0,85,Semi-Urban,ML Engineer,101153,0 +88365,Female,43,Bachelors,8,76,81,82,21,9.0,7,47,Urban,HR Executive,77882,1 +88366,Male,52,Diploma,19,99,1,28,83,8.0,2,26,Semi-Urban,ML Engineer,86633,0 +88367,Male,52,Bachelors,5,17,15,77,63,6.0,7,10,Urban,HR Executive,58799,0 +88368,Female,21,Masters,11,68,60,95,40,7.0,2,50,Urban,Data Analyst,125063,1 +88369,Female,21,High School,1,7,55,49,16,0.0,5,2,Urban,Manager,108471,0 +88370,Female,28,Masters,1,88,21,78,73,2.0,4,90,Semi-Urban,Software Engineer,87808,1 +88371,Male,36,Bachelors,17,2,73,92,40,6.0,2,17,Urban,HR Executive,40268,0 +88372,Male,49,Bachelors,16,38,34,12,60,2.0,5,18,Urban,HR Executive,57239,0 +88373,Male,50,Bachelors,3,38,27,52,76,6.0,0,66,Urban,HR Executive,130235,0 +88374,Female,24,Bachelors,18,37,72,89,78,4.0,1,22,Urban,Manager,67492,0 +88375,Female,27,Masters,17,59,13,65,76,3.0,5,43,Urban,Manager,99921,0 +88376,Female,37,Masters,15,47,60,65,27,1.0,5,56,Urban,ML Engineer,97971,0 +88377,Male,41,Masters,10,82,99,99,24,3.0,2,43,Urban,ML Engineer,108684,1 +88378,Male,49,High School,9,94,15,96,87,5.0,4,27,Rural,ML Engineer,118023,0 +88379,Male,47,Diploma,18,32,72,95,18,9.0,0,89,Urban,ML Engineer,42466,1 +88380,Male,43,Diploma,5,47,1,47,8,1.0,3,41,Rural,Manager,76557,0 +88381,Male,30,High School,13,15,67,73,35,1.0,4,68,Rural,HR Executive,31723,0 +88382,Male,36,Masters,19,53,2,71,63,3.0,1,14,Semi-Urban,HR Executive,87006,0 +88383,Male,26,Masters,4,49,81,62,84,7.0,1,67,Rural,Software Engineer,143706,1 +88384,Male,37,Bachelors,16,3,49,19,80,9.0,5,58,Urban,HR Executive,72480,0 +88385,Male,25,Masters,9,86,88,48,7,9.0,4,28,Semi-Urban,HR Executive,43522,1 +88386,Female,45,Masters,10,57,43,2,4,0.0,5,80,Urban,HR Executive,71333,0 +88387,Other,22,Bachelors,5,71,96,85,73,1.0,5,82,Semi-Urban,Manager,143468,1 +88388,Male,45,Bachelors,19,78,94,96,6,8.0,7,18,Rural,ML Engineer,106841,1 +88389,Female,39,Masters,16,34,0,99,64,6.0,7,68,Rural,Software Engineer,64393,0 +88390,Male,58,Bachelors,15,78,73,7,8,7.0,5,63,Urban,Data Analyst,92294,0 +88391,Female,29,Masters,10,28,62,44,85,7.0,5,17,Urban,ML Engineer,65089,0 +88392,Male,46,Diploma,16,95,6,95,68,0.0,1,95,Rural,ML Engineer,134085,1 +88393,Female,47,Bachelors,19,26,62,59,89,8.0,7,19,Urban,Manager,90310,0 +88394,Male,32,Bachelors,2,46,39,24,22,4.0,0,22,Rural,ML Engineer,73978,0 +88395,Male,32,High School,6,95,75,98,66,4.0,0,48,Semi-Urban,Manager,111528,1 +88396,Female,56,High School,11,91,24,25,56,9.0,7,22,Urban,Manager,44015,0 +88397,Male,57,Bachelors,13,78,42,71,31,0.0,3,97,Rural,Manager,115569,1 +88398,Male,26,Bachelors,3,43,73,64,53,7.0,4,67,Rural,Manager,79152,1 +88399,Male,32,Bachelors,2,9,82,83,83,6.0,6,6,Urban,Software Engineer,83196,0 +88400,Female,39,Masters,10,37,20,34,90,9.0,2,53,Semi-Urban,Software Engineer,122702,0 +88401,Male,34,Bachelors,15,77,94,43,69,0.0,2,15,Semi-Urban,Manager,88536,0 +88402,Female,51,Bachelors,3,69,16,92,88,3.0,7,60,Semi-Urban,Data Analyst,47692,0 +88403,Female,32,Bachelors,19,38,64,90,96,7.0,5,40,Rural,HR Executive,21885,0 +88404,Male,37,Masters,19,83,20,1,66,9.0,2,73,Urban,ML Engineer,37631,0 +88405,Male,43,Diploma,6,45,49,8,73,5.0,6,24,Semi-Urban,Software Engineer,117098,0 +88406,Male,50,Bachelors,6,53,92,9,54,1.0,4,76,Semi-Urban,Manager,74946,0 +88407,Male,50,Diploma,5,28,33,63,98,5.0,7,62,Urban,Software Engineer,110929,0 +88408,Female,43,Bachelors,6,2,98,89,1,5.0,4,2,Urban,Manager,28743,0 +88409,Male,47,Bachelors,0,3,2,0,64,6.0,5,20,Rural,ML Engineer,126645,0 +88410,Female,41,Masters,16,75,3,25,3,0.0,7,10,Urban,Manager,100887,0 +88411,Male,34,Masters,13,86,99,45,99,6.0,1,75,Semi-Urban,HR Executive,145552,1 +88412,Male,27,Bachelors,15,45,37,98,10,6.0,6,29,Semi-Urban,ML Engineer,20367,0 +88413,Male,58,Bachelors,13,99,36,25,85,1.0,3,72,Urban,ML Engineer,37726,0 +88414,Male,30,PhD,19,12,24,18,64,0.0,1,68,Semi-Urban,Data Analyst,146295,0 +88415,Male,58,Bachelors,6,48,42,66,5,6.0,6,33,Rural,Manager,40089,0 +88416,Female,55,Masters,18,11,38,65,29,3.0,6,54,Urban,ML Engineer,101787,0 +88417,Male,24,Bachelors,2,32,37,79,46,3.0,4,5,Urban,HR Executive,53769,0 +88418,Female,36,High School,14,57,75,74,40,0.0,0,24,Urban,Data Analyst,81906,0 +88419,Male,44,High School,17,45,53,83,61,2.0,3,14,Urban,Software Engineer,128617,0 +88420,Male,49,PhD,19,96,13,1,54,1.0,2,51,Urban,ML Engineer,128779,0 +88421,Male,29,Masters,19,79,46,22,6,4.0,3,46,Urban,Data Analyst,120949,0 +88422,Female,22,Masters,19,91,2,16,23,8.0,4,2,Urban,Manager,84358,0 +88423,Male,50,Bachelors,1,52,71,3,46,6.0,2,72,Urban,Manager,24612,0 +88424,Female,31,Masters,1,39,53,56,80,4.0,0,28,Rural,Data Analyst,76618,0 +88425,Female,41,Diploma,6,54,75,12,96,6.0,3,72,Semi-Urban,Data Analyst,22598,0 +88426,Male,48,Bachelors,17,77,44,46,6,0.0,6,43,Urban,HR Executive,77204,0 +88427,Male,52,High School,9,3,67,70,84,0.0,2,77,Semi-Urban,Software Engineer,148343,0 +88428,Male,45,Diploma,1,28,41,58,97,3.0,7,52,Semi-Urban,Data Analyst,119671,0 +88429,Male,43,Diploma,11,37,34,96,12,2.0,6,18,Urban,Software Engineer,111292,0 +88430,Female,25,Diploma,17,78,36,30,38,2.0,7,2,Rural,Software Engineer,28231,0 +88431,Male,47,Masters,4,63,28,75,66,7.0,3,42,Semi-Urban,ML Engineer,87374,0 +88432,Female,35,Bachelors,3,38,44,30,57,1.0,2,92,Urban,Software Engineer,66564,0 +88433,Male,33,Diploma,1,57,76,56,52,8.0,3,14,Semi-Urban,Manager,86892,0 +88434,Male,47,Diploma,9,81,5,38,74,3.0,0,22,Urban,Data Analyst,84010,0 +88435,Male,43,Bachelors,9,43,51,15,49,0.0,4,28,Rural,HR Executive,63906,0 +88436,Female,35,High School,10,6,14,64,98,4.0,4,90,Semi-Urban,Software Engineer,41218,0 +88437,Female,33,Masters,10,29,31,39,99,0.0,0,70,Urban,Manager,40093,0 +88438,Male,51,Masters,4,55,66,39,6,8.0,3,37,Rural,ML Engineer,76534,0 +88439,Other,32,Masters,6,36,53,92,68,8.0,2,43,Semi-Urban,ML Engineer,96906,0 +88440,Male,59,High School,15,36,28,86,42,4.0,0,39,Semi-Urban,ML Engineer,123774,0 +88441,Female,51,Bachelors,8,73,81,19,30,3.0,4,97,Urban,Manager,86852,1 +88442,Male,45,Diploma,18,74,16,8,99,4.0,5,8,Semi-Urban,ML Engineer,106782,0 +88443,Female,35,Diploma,12,93,57,4,88,2.0,4,59,Urban,HR Executive,81342,0 +88444,Male,59,Masters,7,5,95,24,13,8.0,1,99,Semi-Urban,Manager,116168,0 +88445,Female,47,Diploma,19,13,81,42,25,7.0,0,18,Rural,Data Analyst,29932,0 +88446,Male,22,Bachelors,17,43,47,62,10,5.0,7,70,Rural,Data Analyst,132051,0 +88447,Male,55,High School,13,24,50,88,5,4.0,3,66,Urban,ML Engineer,59213,0 +88448,Female,53,Diploma,16,23,0,21,80,7.0,2,45,Rural,Data Analyst,127056,0 +88449,Male,24,Diploma,11,49,28,98,17,7.0,5,30,Urban,Data Analyst,92743,0 +88450,Male,26,High School,18,36,22,67,38,5.0,1,70,Urban,Software Engineer,43856,0 +88451,Female,37,High School,19,53,70,4,20,0.0,7,97,Rural,ML Engineer,83584,0 +88452,Male,27,Masters,1,11,53,40,95,5.0,7,74,Urban,Data Analyst,134302,0 +88453,Male,52,High School,9,91,67,89,55,0.0,4,3,Semi-Urban,HR Executive,91307,1 +88454,Female,41,Bachelors,13,72,77,2,19,6.0,1,69,Rural,Data Analyst,57879,0 +88455,Male,42,Bachelors,7,55,22,35,14,2.0,5,20,Semi-Urban,HR Executive,43896,0 +88456,Female,22,Bachelors,2,33,10,14,47,0.0,5,13,Semi-Urban,Manager,52057,0 +88457,Female,54,Masters,7,4,18,7,35,9.0,1,99,Semi-Urban,Software Engineer,104994,0 +88458,Male,58,Diploma,14,26,84,87,1,0.0,4,27,Urban,HR Executive,121524,0 +88459,Male,53,Diploma,4,54,21,19,83,3.0,7,51,Urban,ML Engineer,86339,0 +88460,Female,24,Bachelors,19,79,4,67,61,8.0,4,62,Urban,Software Engineer,20712,0 +88461,Female,40,Diploma,3,96,6,22,27,9.0,1,2,Urban,ML Engineer,55822,0 +88462,Male,24,Bachelors,10,93,7,56,5,4.0,6,17,Urban,Manager,89548,0 +88463,Male,26,High School,11,34,0,35,73,5.0,6,76,Semi-Urban,Data Analyst,132558,0 +88464,Female,51,Diploma,2,56,14,0,94,9.0,2,49,Semi-Urban,Software Engineer,127757,0 +88465,Male,43,Masters,18,41,54,95,29,6.0,2,20,Urban,Software Engineer,82672,0 +88466,Female,57,Diploma,8,54,2,40,42,1.0,6,62,Semi-Urban,Software Engineer,20388,0 +88467,Female,50,Bachelors,18,6,67,2,89,6.0,2,31,Semi-Urban,Data Analyst,111119,0 +88468,Male,35,PhD,0,19,96,90,33,3.0,4,74,Semi-Urban,ML Engineer,147618,1 +88469,Other,39,Bachelors,11,73,40,21,51,2.0,3,66,Semi-Urban,Data Analyst,142015,0 +88470,Female,36,Bachelors,14,82,58,63,15,1.0,2,21,Semi-Urban,Data Analyst,20857,0 +88471,Female,29,Bachelors,0,11,53,68,80,0.0,2,35,Urban,Data Analyst,31991,0 +88472,Female,50,Masters,8,5,94,62,36,4.0,2,5,Rural,Manager,101330,0 +88473,Male,30,Bachelors,7,63,73,88,6,2.0,2,35,Urban,ML Engineer,84865,1 +88474,Male,59,High School,12,5,67,91,74,0.0,6,64,Semi-Urban,HR Executive,74635,0 +88475,Male,34,Diploma,5,75,39,79,16,2.0,7,25,Semi-Urban,HR Executive,29318,0 +88476,Female,56,Bachelors,7,77,88,44,16,6.0,4,83,Urban,ML Engineer,99975,1 +88477,Male,29,Bachelors,15,86,68,44,55,9.0,5,78,Semi-Urban,HR Executive,72574,1 +88478,Male,34,Bachelors,12,10,20,27,95,3.0,5,42,Urban,HR Executive,142231,0 +88479,Female,55,High School,7,21,34,79,35,6.0,5,20,Semi-Urban,Data Analyst,43929,0 +88480,Male,37,Bachelors,1,63,15,15,7,0.0,0,23,Rural,Data Analyst,74403,0 +88481,Female,36,Diploma,7,65,93,92,89,2.0,7,51,Urban,Data Analyst,51639,1 +88482,Male,36,Bachelors,17,5,29,90,54,3.0,2,66,Urban,Software Engineer,33155,0 +88483,Other,42,Masters,19,81,92,15,49,0.0,0,60,Urban,Data Analyst,92730,1 +88484,Male,27,Bachelors,15,21,82,21,54,1.0,1,78,Urban,Software Engineer,65676,0 +88485,Male,53,Bachelors,16,2,94,51,79,8.0,3,94,Urban,ML Engineer,105038,1 +88486,Male,30,Bachelors,14,80,12,19,33,2.0,6,89,Urban,HR Executive,64219,0 +88487,Female,23,Diploma,1,62,71,78,52,8.0,0,73,Urban,Manager,23298,1 +88488,Male,54,Diploma,3,9,53,21,85,2.0,5,81,Urban,Software Engineer,139541,0 +88489,Male,57,Diploma,19,53,81,36,59,5.0,1,91,Rural,Data Analyst,80532,1 +88490,Male,35,Diploma,10,87,12,74,92,5.0,6,66,Urban,ML Engineer,127016,1 +88491,Male,45,Bachelors,1,88,98,58,9,8.0,5,26,Urban,Manager,145942,1 +88492,Male,33,High School,9,24,71,49,73,4.0,7,8,Urban,Software Engineer,63921,0 +88493,Female,40,Masters,17,96,98,94,61,0.0,5,28,Rural,ML Engineer,114485,1 +88494,Female,38,Bachelors,2,29,35,73,88,6.0,5,98,Semi-Urban,ML Engineer,107653,0 +88495,Female,33,Bachelors,0,84,72,54,39,2.0,5,10,Urban,Data Analyst,90095,0 +88496,Male,55,Bachelors,9,16,76,7,63,0.0,4,26,Semi-Urban,ML Engineer,123545,0 +88497,Male,47,PhD,16,99,21,15,94,4.0,1,68,Urban,HR Executive,149026,0 +88498,Male,28,Bachelors,16,36,37,23,11,7.0,0,35,Semi-Urban,Data Analyst,64050,0 +88499,Male,27,Bachelors,16,63,49,11,71,7.0,0,4,Urban,Data Analyst,76233,0 +88500,Male,31,Bachelors,2,69,70,31,22,3.0,6,93,Semi-Urban,Manager,114366,1 +88501,Male,47,High School,4,5,81,96,63,1.0,1,37,Rural,HR Executive,85761,0 +88502,Male,36,High School,16,31,97,96,11,6.0,4,58,Semi-Urban,HR Executive,45468,1 +88503,Male,56,Bachelors,15,33,81,5,74,4.0,2,95,Urban,Manager,23159,0 +88504,Female,54,PhD,2,64,99,23,94,1.0,7,13,Urban,Data Analyst,24665,0 +88505,Female,38,High School,18,54,93,87,83,7.0,4,85,Urban,Manager,58482,1 +88506,Female,21,Bachelors,0,77,59,8,95,4.0,2,64,Semi-Urban,Manager,51991,0 +88507,Male,42,High School,15,94,87,88,14,7.0,0,32,Urban,Data Analyst,31946,1 +88508,Male,49,Bachelors,0,32,86,10,28,8.0,5,68,Semi-Urban,ML Engineer,130662,0 +88509,Male,38,Bachelors,17,30,44,33,10,5.0,6,73,Rural,Software Engineer,60088,0 +88510,Male,56,High School,1,16,12,60,46,6.0,4,39,Rural,HR Executive,47463,0 +88511,Male,54,Diploma,4,2,88,66,39,6.0,0,40,Semi-Urban,Manager,107754,0 +88512,Male,33,Diploma,6,40,68,48,81,7.0,2,7,Semi-Urban,Data Analyst,37340,0 +88513,Male,55,Diploma,1,10,27,57,56,4.0,7,78,Urban,HR Executive,122921,0 +88514,Male,46,Diploma,19,26,18,50,41,3.0,2,28,Urban,ML Engineer,69111,0 +88515,Female,47,Bachelors,7,61,8,77,8,3.0,7,88,Rural,Manager,101408,0 +88516,Male,47,Diploma,13,67,8,79,95,4.0,3,78,Semi-Urban,HR Executive,42522,0 +88517,Male,30,Bachelors,13,8,19,98,85,7.0,0,23,Semi-Urban,Software Engineer,80333,0 +88518,Female,38,Diploma,14,1,48,38,23,2.0,7,36,Urban,HR Executive,30457,0 +88519,Male,21,Masters,1,5,32,35,32,7.0,1,37,Semi-Urban,Software Engineer,74234,0 +88520,Male,24,Bachelors,0,60,41,71,54,6.0,3,40,Urban,Software Engineer,48504,0 +88521,Male,29,High School,2,41,86,64,31,8.0,7,45,Urban,Data Analyst,131622,1 +88522,Female,38,Masters,0,78,62,63,56,1.0,1,81,Semi-Urban,Data Analyst,110596,1 +88523,Male,23,Masters,12,59,42,90,60,2.0,6,45,Urban,ML Engineer,89926,1 +88524,Male,35,High School,7,44,69,34,97,8.0,5,80,Urban,HR Executive,66042,0 +88525,Male,38,Masters,4,67,20,10,12,5.0,1,74,Semi-Urban,Software Engineer,40961,0 +88526,Female,59,Masters,15,11,6,4,61,4.0,3,89,Urban,ML Engineer,92538,0 +88527,Male,23,High School,11,33,43,63,35,8.0,3,5,Urban,Data Analyst,113493,0 +88528,Female,40,Masters,6,14,7,17,59,4.0,1,40,Urban,Manager,120078,0 +88529,Male,53,Bachelors,12,58,44,7,80,5.0,2,45,Semi-Urban,Software Engineer,141097,0 +88530,Male,32,Diploma,19,2,9,31,98,1.0,1,58,Semi-Urban,Data Analyst,37551,0 +88531,Male,24,High School,19,30,95,86,82,7.0,0,56,Urban,Data Analyst,71285,1 +88532,Male,50,High School,6,88,95,58,7,9.0,3,5,Urban,Software Engineer,93118,1 +88533,Male,40,Bachelors,2,53,48,23,76,1.0,1,2,Rural,Manager,72572,0 +88534,Male,47,Bachelors,8,76,95,39,28,3.0,3,9,Urban,ML Engineer,95623,0 +88535,Female,38,Masters,7,80,67,31,1,2.0,0,61,Urban,Software Engineer,134760,0 +88536,Other,33,Masters,10,54,3,18,16,5.0,2,89,Urban,Data Analyst,134633,0 +88537,Male,50,Diploma,10,91,37,66,85,9.0,5,19,Rural,Data Analyst,124415,0 +88538,Male,30,Bachelors,8,11,9,35,84,0.0,2,83,Urban,ML Engineer,59047,0 +88539,Other,52,Bachelors,13,18,93,28,5,3.0,5,35,Urban,Software Engineer,39259,0 +88540,Male,27,High School,16,8,13,39,97,9.0,3,30,Urban,Data Analyst,73726,0 +88541,Male,49,Bachelors,19,77,66,65,15,7.0,2,5,Urban,Software Engineer,51078,0 +88542,Other,48,Diploma,7,27,96,13,52,8.0,4,43,Urban,HR Executive,60037,0 +88543,Male,28,Bachelors,14,17,45,69,60,3.0,6,18,Urban,HR Executive,131200,0 +88544,Female,57,Bachelors,0,82,51,31,65,7.0,5,36,Rural,ML Engineer,83240,0 +88545,Male,45,High School,1,65,80,88,75,3.0,1,3,Urban,Data Analyst,90688,1 +88546,Female,27,Bachelors,4,30,67,67,66,5.0,6,51,Urban,Manager,126878,0 +88547,Other,26,Bachelors,19,65,11,50,99,4.0,5,11,Urban,Data Analyst,133988,0 +88548,Other,44,Bachelors,6,3,20,79,61,9.0,3,53,Rural,Software Engineer,72074,0 +88549,Male,56,High School,18,87,63,90,99,3.0,0,0,Urban,Manager,55911,1 +88550,Female,38,High School,5,14,74,32,0,4.0,4,12,Semi-Urban,Data Analyst,80523,0 +88551,Female,31,Bachelors,5,37,61,92,91,1.0,1,79,Rural,Manager,110709,1 +88552,Female,41,Bachelors,10,78,23,51,48,2.0,5,26,Semi-Urban,ML Engineer,116868,0 +88553,Male,31,Bachelors,10,7,56,16,51,6.0,5,68,Semi-Urban,Data Analyst,137603,0 +88554,Male,51,Bachelors,18,67,24,90,85,2.0,1,86,Urban,Data Analyst,137126,1 +88555,Male,56,Diploma,8,94,43,32,74,2.0,1,43,Urban,ML Engineer,83371,0 +88556,Female,46,Masters,18,8,46,43,85,8.0,7,43,Urban,Software Engineer,87058,0 +88557,Female,34,Bachelors,0,23,40,96,91,4.0,3,38,Semi-Urban,Manager,67322,0 +88558,Male,52,Bachelors,0,37,24,46,8,7.0,0,39,Urban,Manager,134417,0 +88559,Male,45,Masters,13,63,1,56,7,3.0,0,30,Urban,ML Engineer,117623,0 +88560,Male,49,Masters,11,68,71,55,87,7.0,6,33,Semi-Urban,Data Analyst,121564,0 +88561,Male,58,Masters,16,48,90,0,30,5.0,2,93,Urban,HR Executive,83120,0 +88562,Female,32,High School,13,44,52,67,37,8.0,4,54,Urban,Data Analyst,137325,0 +88563,Female,36,High School,0,64,4,68,89,5.0,7,82,Urban,ML Engineer,149133,0 +88564,Female,57,Bachelors,5,21,25,32,50,3.0,1,9,Rural,Manager,63108,0 +88565,Female,21,Bachelors,16,54,52,49,76,0.0,7,91,Rural,Data Analyst,35802,1 +88566,Female,39,Bachelors,11,28,10,14,27,7.0,3,65,Urban,ML Engineer,94466,0 +88567,Male,28,Diploma,15,62,36,47,29,1.0,5,73,Urban,Manager,44860,0 +88568,Female,35,Masters,10,44,34,79,32,2.0,3,18,Urban,Software Engineer,32989,0 +88569,Female,32,Diploma,9,22,2,88,25,2.0,1,81,Urban,Manager,97628,0 +88570,Male,34,Masters,18,37,84,75,48,7.0,5,61,Urban,Manager,49402,1 +88571,Male,52,Bachelors,4,88,70,35,43,6.0,3,37,Urban,ML Engineer,99757,0 +88572,Male,45,Bachelors,10,49,0,6,34,2.0,0,66,Urban,ML Engineer,37922,0 +88573,Male,57,Masters,13,33,87,54,11,4.0,7,52,Rural,Software Engineer,51325,0 +88574,Female,54,Masters,8,84,55,80,56,8.0,3,75,Urban,Software Engineer,74663,1 +88575,Male,38,High School,17,85,22,75,26,9.0,4,30,Urban,Software Engineer,80600,0 +88576,Male,42,Diploma,11,90,59,17,37,8.0,4,69,Urban,HR Executive,81475,1 +88577,Male,29,Masters,6,95,34,92,86,3.0,6,38,Semi-Urban,HR Executive,35698,1 +88578,Female,41,High School,13,5,35,14,66,1.0,3,9,Urban,HR Executive,42113,0 +88579,Male,24,Masters,1,85,39,59,82,8.0,0,53,Semi-Urban,Data Analyst,58490,1 +88580,Male,23,PhD,12,49,8,11,44,5.0,1,10,Urban,Software Engineer,64981,0 +88581,Female,23,Diploma,9,86,98,44,44,4.0,2,57,Urban,Data Analyst,100707,1 +88582,Female,36,Diploma,19,51,74,16,87,4.0,7,6,Urban,HR Executive,53791,0 +88583,Male,24,Diploma,11,97,33,91,66,9.0,3,46,Rural,ML Engineer,45393,1 +88584,Male,23,Masters,8,43,97,4,52,7.0,6,3,Semi-Urban,HR Executive,108758,0 +88585,Female,35,Diploma,12,95,99,13,20,8.0,6,13,Rural,Software Engineer,102727,0 +88586,Female,33,Diploma,0,28,32,90,60,8.0,3,90,Urban,HR Executive,28992,0 +88587,Other,36,Bachelors,14,36,20,81,98,9.0,5,5,Urban,ML Engineer,37874,0 +88588,Male,37,Bachelors,1,80,37,36,36,8.0,4,46,Rural,Data Analyst,55584,0 +88589,Female,54,Masters,10,92,27,59,36,3.0,1,78,Urban,HR Executive,44048,1 +88590,Male,24,Bachelors,17,99,77,44,59,0.0,4,40,Semi-Urban,Manager,59589,1 +88591,Male,55,Masters,18,52,72,63,29,0.0,5,38,Semi-Urban,HR Executive,38627,0 +88592,Female,39,High School,10,66,61,88,87,9.0,4,68,Rural,Software Engineer,131510,1 +88593,Female,35,Masters,16,17,45,28,1,7.0,3,77,Semi-Urban,HR Executive,54044,0 +88594,Other,57,PhD,3,26,0,19,35,8.0,5,10,Urban,HR Executive,139803,0 +88595,Male,42,Masters,5,85,78,88,76,6.0,5,4,Rural,ML Engineer,122557,1 +88596,Male,49,Diploma,10,51,78,6,27,8.0,3,82,Urban,HR Executive,117020,0 +88597,Female,32,Bachelors,14,50,72,64,96,1.0,3,92,Semi-Urban,Manager,60307,1 +88598,Male,47,Diploma,9,28,47,58,70,2.0,4,55,Semi-Urban,HR Executive,58406,0 +88599,Male,30,Bachelors,6,57,86,89,57,1.0,6,18,Urban,Data Analyst,92422,1 +88600,Female,45,High School,16,54,91,41,62,6.0,7,24,Rural,ML Engineer,122403,0 +88601,Male,54,PhD,15,70,92,95,4,1.0,6,27,Semi-Urban,Manager,94716,1 +88602,Male,53,PhD,10,32,15,79,50,9.0,6,3,Semi-Urban,ML Engineer,82700,0 +88603,Female,52,Diploma,5,13,79,64,90,9.0,1,48,Semi-Urban,Data Analyst,114100,0 +88604,Male,25,High School,16,39,2,37,35,1.0,5,8,Rural,HR Executive,138247,0 +88605,Other,54,Bachelors,1,9,89,65,40,0.0,3,93,Urban,Data Analyst,26864,1 +88606,Female,24,Bachelors,4,58,96,41,26,4.0,7,46,Rural,Manager,109408,1 +88607,Female,43,Masters,2,7,34,10,78,8.0,5,51,Urban,HR Executive,75036,0 +88608,Other,55,Bachelors,7,78,89,28,90,0.0,5,77,Semi-Urban,Manager,62839,1 +88609,Male,46,Masters,15,21,54,88,48,1.0,4,67,Urban,ML Engineer,95231,0 +88610,Male,35,Bachelors,13,33,62,56,34,9.0,6,3,Rural,Data Analyst,64182,0 +88611,Female,24,High School,15,47,30,72,36,4.0,0,16,Rural,Data Analyst,116310,0 +88612,Female,46,Bachelors,17,92,21,37,61,1.0,1,80,Rural,Data Analyst,133572,0 +88613,Male,52,Masters,15,99,99,62,91,9.0,6,39,Rural,Data Analyst,87177,1 +88614,Female,34,Masters,2,30,9,69,70,9.0,5,1,Urban,ML Engineer,71736,0 +88615,Male,55,High School,3,52,98,15,28,8.0,3,10,Rural,Manager,97411,0 +88616,Male,53,Masters,8,96,60,97,68,7.0,1,52,Semi-Urban,ML Engineer,108346,1 +88617,Female,21,Diploma,0,30,69,41,32,0.0,0,40,Urban,Data Analyst,79134,0 +88618,Male,57,Diploma,5,40,30,57,80,6.0,3,68,Urban,ML Engineer,46026,0 +88619,Male,24,Bachelors,19,8,76,16,69,1.0,5,36,Rural,HR Executive,83029,0 +88620,Male,56,High School,1,6,1,83,61,3.0,2,57,Semi-Urban,Manager,66066,0 +88621,Male,41,Diploma,5,53,67,70,53,2.0,3,15,Rural,Software Engineer,126461,0 +88622,Male,56,High School,16,76,95,25,82,8.0,5,40,Urban,ML Engineer,123278,1 +88623,Male,55,Diploma,15,53,26,2,81,7.0,5,23,Rural,Manager,70227,0 +88624,Male,34,Masters,14,63,41,30,31,6.0,0,54,Semi-Urban,Manager,67356,0 +88625,Male,21,Bachelors,14,44,7,38,98,0.0,1,35,Urban,HR Executive,105020,0 +88626,Male,51,Bachelors,8,35,21,43,51,4.0,0,64,Rural,Manager,25424,0 +88627,Male,48,Bachelors,4,63,1,55,66,5.0,6,27,Semi-Urban,HR Executive,69887,0 +88628,Male,41,PhD,18,89,74,19,40,6.0,3,43,Urban,Manager,123496,0 +88629,Male,27,Bachelors,0,73,35,11,52,6.0,7,81,Rural,ML Engineer,65091,0 +88630,Male,21,Bachelors,18,64,82,31,26,1.0,2,64,Urban,HR Executive,69340,1 +88631,Male,47,Diploma,13,9,6,20,31,2.0,0,46,Rural,HR Executive,149795,0 +88632,Male,33,Masters,14,68,82,77,76,1.0,0,89,Urban,HR Executive,149710,1 +88633,Male,58,Masters,0,83,66,38,97,6.0,1,1,Urban,HR Executive,72722,0 +88634,Male,37,Bachelors,7,79,47,52,24,4.0,2,79,Urban,Software Engineer,57053,1 +88635,Male,38,Diploma,8,26,14,48,9,9.0,6,78,Semi-Urban,Software Engineer,66727,0 +88636,Male,51,High School,6,45,16,22,98,6.0,0,66,Urban,Manager,74685,0 +88637,Male,23,Bachelors,11,16,39,61,55,9.0,5,40,Rural,Software Engineer,82399,0 +88638,Male,31,Diploma,1,10,28,14,25,6.0,0,83,Rural,Manager,68563,0 +88639,Male,44,Masters,8,33,55,27,61,6.0,0,5,Urban,Data Analyst,47583,0 +88640,Female,24,Bachelors,7,50,10,67,61,9.0,5,7,Urban,HR Executive,49610,0 +88641,Male,47,PhD,19,5,73,11,97,8.0,7,24,Urban,HR Executive,72452,0 +88642,Male,33,Bachelors,16,92,65,35,59,5.0,1,94,Semi-Urban,HR Executive,74086,1 +88643,Male,32,Bachelors,19,10,73,66,43,1.0,0,19,Semi-Urban,ML Engineer,84699,0 +88644,Other,23,Bachelors,17,68,41,57,9,2.0,3,58,Urban,ML Engineer,20143,0 +88645,Male,55,PhD,15,83,35,16,51,1.0,5,1,Urban,ML Engineer,124014,0 +88646,Female,24,Masters,11,65,81,38,53,5.0,0,99,Urban,Data Analyst,78368,1 +88647,Male,39,Masters,14,99,98,30,25,0.0,2,81,Urban,Software Engineer,143696,1 +88648,Female,43,Bachelors,12,40,98,21,36,4.0,5,33,Rural,Software Engineer,42078,0 +88649,Male,24,Bachelors,18,41,88,60,67,9.0,0,58,Urban,Software Engineer,78765,1 +88650,Female,31,High School,1,16,93,14,27,0.0,4,57,Semi-Urban,HR Executive,51376,0 +88651,Male,42,Masters,5,41,37,98,68,6.0,4,26,Urban,HR Executive,110777,0 +88652,Female,21,Masters,16,82,2,88,10,1.0,4,83,Urban,Software Engineer,75919,1 +88653,Male,52,Masters,12,25,13,94,43,8.0,2,76,Semi-Urban,Data Analyst,36400,0 +88654,Female,25,Bachelors,5,41,66,17,65,1.0,6,81,Urban,ML Engineer,129284,0 +88655,Male,53,Masters,7,44,8,22,64,7.0,2,98,Urban,ML Engineer,61219,0 +88656,Male,46,Masters,14,31,66,98,97,4.0,4,17,Rural,ML Engineer,120594,0 +88657,Female,48,Bachelors,17,50,77,49,27,6.0,3,75,Rural,Data Analyst,133600,1 +88658,Male,44,Masters,2,63,60,25,77,8.0,1,95,Urban,Software Engineer,105184,1 +88659,Male,21,Bachelors,14,59,99,67,17,9.0,4,41,Urban,ML Engineer,20670,1 +88660,Female,49,Diploma,3,88,16,48,82,1.0,5,92,Urban,Software Engineer,138342,1 +88661,Male,21,Bachelors,17,50,9,6,75,7.0,1,7,Urban,HR Executive,62165,0 +88662,Female,48,Diploma,12,40,73,86,40,7.0,3,84,Rural,ML Engineer,145687,1 +88663,Male,24,Masters,0,93,15,24,66,7.0,0,0,Urban,Manager,111073,0 +88664,Female,58,High School,19,98,95,33,22,1.0,3,79,Urban,Data Analyst,47620,1 +88665,Female,28,Bachelors,19,0,50,64,43,4.0,5,17,Rural,Manager,68030,0 +88666,Female,35,Diploma,7,17,66,52,41,4.0,7,0,Semi-Urban,Software Engineer,136064,0 +88667,Male,36,Masters,13,59,16,95,29,6.0,0,4,Urban,Data Analyst,140087,0 +88668,Male,37,Diploma,15,66,65,12,36,7.0,1,55,Rural,Manager,89478,0 +88669,Other,49,High School,4,0,60,37,74,1.0,2,96,Semi-Urban,Software Engineer,93971,0 +88670,Female,52,PhD,9,70,89,67,3,1.0,7,87,Rural,ML Engineer,75097,1 +88671,Male,56,High School,14,29,65,44,28,3.0,7,20,Urban,Data Analyst,128090,0 +88672,Male,39,Masters,7,98,5,44,35,8.0,2,37,Urban,HR Executive,131720,0 +88673,Female,43,Diploma,6,15,47,24,70,1.0,1,57,Rural,Data Analyst,35256,0 +88674,Female,43,Bachelors,8,83,69,43,47,5.0,4,15,Urban,HR Executive,75501,0 +88675,Male,31,High School,7,95,1,83,48,2.0,2,30,Rural,Manager,122897,0 +88676,Male,36,Diploma,4,68,51,62,99,5.0,1,94,Rural,HR Executive,25359,1 +88677,Male,26,High School,17,47,85,59,55,7.0,4,22,Rural,HR Executive,80239,0 +88678,Male,28,High School,15,6,1,60,17,5.0,3,37,Urban,Software Engineer,121364,0 +88679,Male,29,Masters,8,45,3,82,59,4.0,1,25,Urban,Data Analyst,133158,0 +88680,Male,55,Bachelors,11,23,27,83,1,2.0,0,84,Urban,Manager,63681,0 +88681,Male,59,Diploma,4,44,93,35,68,1.0,5,74,Urban,HR Executive,71137,1 +88682,Male,45,Bachelors,17,96,37,47,85,9.0,2,35,Semi-Urban,Data Analyst,37645,0 +88683,Male,21,Bachelors,10,43,61,35,42,9.0,7,24,Urban,Data Analyst,101556,0 +88684,Male,42,Bachelors,10,80,95,71,56,5.0,0,27,Rural,ML Engineer,138255,1 +88685,Male,28,Bachelors,4,54,97,13,71,4.0,6,13,Semi-Urban,Manager,127483,0 +88686,Male,43,Bachelors,3,18,78,11,51,9.0,4,1,Urban,HR Executive,135697,0 +88687,Male,30,Masters,4,4,26,60,72,8.0,7,19,Urban,Data Analyst,140592,0 +88688,Male,52,Masters,2,69,36,60,36,8.0,3,52,Rural,Data Analyst,62344,0 +88689,Male,34,Bachelors,3,3,48,35,8,1.0,1,63,Urban,ML Engineer,138484,0 +88690,Male,47,Masters,12,72,99,97,72,2.0,3,99,Rural,Manager,70976,1 +88691,Male,30,Masters,3,19,7,44,90,3.0,2,97,Rural,ML Engineer,142261,0 +88692,Male,29,Diploma,1,29,87,92,81,3.0,0,14,Urban,ML Engineer,80270,0 +88693,Female,32,Diploma,6,28,66,33,24,6.0,3,65,Urban,ML Engineer,106098,0 +88694,Male,41,Bachelors,1,43,63,24,93,4.0,7,47,Rural,HR Executive,70933,0 +88695,Male,27,PhD,15,11,54,77,74,7.0,6,58,Urban,HR Executive,62422,0 +88696,Male,48,High School,17,34,62,13,54,4.0,5,50,Rural,ML Engineer,31535,0 +88697,Female,45,Bachelors,13,88,79,20,20,1.0,0,23,Urban,Manager,134868,0 +88698,Female,40,Bachelors,8,21,24,83,89,6.0,4,21,Rural,HR Executive,51409,0 +88699,Male,28,Bachelors,14,22,3,88,94,7.0,1,21,Rural,Data Analyst,93586,0 +88700,Female,25,High School,15,1,30,73,3,9.0,2,29,Urban,Software Engineer,133704,0 +88701,Male,36,Diploma,5,43,39,97,69,6.0,0,35,Urban,Manager,63841,0 +88702,Male,23,Diploma,14,57,67,65,27,9.0,3,93,Rural,ML Engineer,130609,1 +88703,Female,28,Bachelors,2,49,98,92,99,4.0,2,75,Urban,ML Engineer,138482,1 +88704,Female,46,Masters,18,49,32,70,76,5.0,7,73,Urban,Software Engineer,126726,0 +88705,Male,42,Masters,8,62,35,83,54,5.0,3,18,Rural,Manager,141950,0 +88706,Female,21,Masters,5,94,8,28,86,0.0,6,34,Rural,Manager,88128,0 +88707,Male,59,Bachelors,4,23,19,3,5,4.0,7,77,Semi-Urban,Manager,79242,0 +88708,Female,49,Bachelors,7,15,70,36,87,9.0,2,61,Semi-Urban,Manager,46141,0 +88709,Female,52,High School,9,43,76,10,59,2.0,2,86,Rural,ML Engineer,104615,0 +88710,Female,36,Bachelors,8,56,25,73,64,1.0,3,50,Semi-Urban,Data Analyst,68598,0 +88711,Male,32,Bachelors,15,51,14,80,68,7.0,3,73,Urban,Manager,63510,0 +88712,Female,25,Bachelors,6,41,84,56,30,8.0,1,45,Rural,HR Executive,60076,0 +88713,Female,37,Bachelors,15,58,25,34,4,7.0,1,71,Urban,HR Executive,94286,0 +88714,Male,37,Diploma,2,78,76,50,28,7.0,5,24,Semi-Urban,Software Engineer,44060,0 +88715,Male,22,Diploma,15,89,6,8,12,8.0,0,43,Urban,ML Engineer,71408,0 +88716,Male,26,Bachelors,19,68,26,90,66,7.0,6,23,Semi-Urban,Data Analyst,38533,0 +88717,Male,22,High School,0,6,28,51,17,3.0,7,70,Semi-Urban,Manager,85529,0 +88718,Male,41,High School,10,3,98,88,51,0.0,6,20,Semi-Urban,Manager,75264,0 +88719,Male,40,High School,14,76,4,71,35,5.0,2,5,Rural,ML Engineer,129202,0 +88720,Male,25,Diploma,9,49,26,92,10,9.0,6,89,Semi-Urban,Manager,66305,1 +88721,Male,59,Bachelors,18,46,44,24,1,2.0,2,49,Semi-Urban,Data Analyst,118620,0 +88722,Female,31,PhD,6,64,76,34,79,6.0,0,40,Semi-Urban,Software Engineer,22994,0 +88723,Male,52,Bachelors,2,0,17,6,99,8.0,0,33,Urban,Software Engineer,48240,0 +88724,Male,25,High School,13,39,19,75,27,2.0,1,37,Rural,HR Executive,91999,0 +88725,Male,33,Diploma,4,67,11,89,55,6.0,0,15,Urban,Software Engineer,48845,0 +88726,Male,36,Masters,4,49,33,8,81,5.0,0,47,Urban,Manager,78366,0 +88727,Male,46,PhD,8,29,7,40,45,2.0,3,55,Urban,Manager,108800,0 +88728,Male,54,PhD,16,23,36,32,96,4.0,2,63,Urban,ML Engineer,73710,0 +88729,Female,57,Diploma,7,18,63,25,34,2.0,7,38,Urban,Manager,133132,0 +88730,Male,59,Bachelors,6,14,70,1,21,5.0,1,97,Semi-Urban,ML Engineer,137614,0 +88731,Male,47,PhD,13,98,18,48,37,8.0,5,79,Urban,Manager,116743,1 +88732,Female,35,Bachelors,7,45,28,36,39,7.0,0,34,Semi-Urban,Data Analyst,101935,0 +88733,Male,39,Diploma,13,54,90,84,18,4.0,3,92,Urban,Software Engineer,24489,1 +88734,Male,25,High School,14,73,20,57,69,7.0,0,2,Rural,Software Engineer,129678,0 +88735,Male,45,Bachelors,14,31,62,31,88,9.0,5,21,Urban,ML Engineer,58298,0 +88736,Male,51,Bachelors,18,6,72,96,22,6.0,6,2,Urban,Software Engineer,74078,0 +88737,Male,48,Masters,8,63,2,20,79,1.0,2,69,Rural,Manager,95011,0 +88738,Male,59,Bachelors,19,0,21,54,71,2.0,7,94,Rural,Data Analyst,111634,0 +88739,Female,51,High School,10,87,33,74,10,9.0,4,22,Semi-Urban,Software Engineer,63697,0 +88740,Male,59,Diploma,10,7,20,9,0,2.0,3,63,Urban,ML Engineer,146964,0 +88741,Female,45,Bachelors,10,45,89,73,53,2.0,6,94,Semi-Urban,ML Engineer,30396,1 +88742,Other,50,Masters,7,66,93,83,33,7.0,7,50,Semi-Urban,Software Engineer,29335,1 +88743,Male,27,High School,11,41,17,29,94,9.0,0,38,Urban,HR Executive,102795,0 +88744,Other,42,Bachelors,4,37,12,85,65,1.0,5,93,Urban,Data Analyst,140172,0 +88745,Female,59,Diploma,15,80,65,8,48,9.0,3,27,Semi-Urban,ML Engineer,27655,0 +88746,Male,55,Bachelors,18,36,25,46,87,4.0,3,81,Rural,Data Analyst,26214,0 +88747,Female,55,Bachelors,7,84,90,51,94,6.0,4,11,Semi-Urban,HR Executive,97703,0 +88748,Other,23,Bachelors,6,33,50,81,13,9.0,6,11,Semi-Urban,Manager,101332,0 +88749,Other,24,High School,19,27,96,64,48,3.0,7,8,Urban,Data Analyst,29673,0 +88750,Female,34,Bachelors,17,23,91,2,2,1.0,1,32,Rural,Software Engineer,85883,0 +88751,Male,28,Bachelors,16,73,52,49,67,1.0,0,16,Urban,Data Analyst,86093,0 +88752,Male,26,Masters,8,47,3,0,54,3.0,1,2,Rural,ML Engineer,140524,0 +88753,Male,41,Bachelors,16,56,73,37,19,2.0,7,54,Semi-Urban,HR Executive,41099,0 +88754,Female,31,Masters,13,33,73,48,32,0.0,4,34,Semi-Urban,ML Engineer,100136,0 +88755,Male,37,Bachelors,15,47,77,68,18,9.0,4,80,Urban,Software Engineer,49162,1 +88756,Male,45,Diploma,9,21,54,3,94,3.0,6,37,Rural,Software Engineer,148923,0 +88757,Male,30,Masters,3,56,16,40,93,6.0,0,6,Urban,Software Engineer,40630,0 +88758,Female,38,Bachelors,15,53,94,97,75,5.0,5,80,Urban,Manager,75557,1 +88759,Female,37,Bachelors,1,21,17,4,82,7.0,2,93,Semi-Urban,HR Executive,64379,0 +88760,Male,32,Bachelors,7,41,41,6,79,2.0,2,58,Urban,Software Engineer,117257,0 +88761,Female,40,Masters,4,88,27,19,83,8.0,4,63,Urban,ML Engineer,50759,0 +88762,Male,24,Bachelors,9,94,94,37,52,8.0,1,57,Urban,HR Executive,138324,1 +88763,Female,35,Diploma,5,31,44,68,67,8.0,6,10,Rural,ML Engineer,72005,0 +88764,Female,24,Diploma,12,68,41,95,88,2.0,6,74,Urban,Software Engineer,66153,1 +88765,Female,57,Diploma,6,86,36,82,31,4.0,6,36,Urban,Software Engineer,105583,0 +88766,Female,35,High School,10,19,85,70,27,4.0,5,62,Urban,Software Engineer,89430,0 +88767,Other,28,Bachelors,16,90,80,99,36,6.0,6,52,Urban,HR Executive,34555,1 +88768,Male,55,Diploma,18,46,1,13,5,8.0,2,40,Urban,Software Engineer,69539,0 +88769,Male,40,High School,17,63,27,65,23,0.0,6,0,Rural,Data Analyst,75294,0 +88770,Female,54,Bachelors,5,67,93,98,87,4.0,6,96,Semi-Urban,Manager,33086,1 +88771,Female,51,Bachelors,19,77,88,53,84,4.0,4,98,Semi-Urban,Manager,91911,1 +88772,Male,52,Bachelors,3,99,92,93,89,0.0,4,58,Urban,HR Executive,93025,1 +88773,Male,52,Bachelors,16,27,24,81,85,5.0,2,37,Rural,Data Analyst,79318,0 +88774,Female,49,Bachelors,9,33,92,46,0,5.0,7,34,Urban,ML Engineer,73638,0 +88775,Female,27,Diploma,1,79,8,86,4,9.0,5,17,Urban,Data Analyst,137020,0 +88776,Female,46,Bachelors,10,21,77,29,4,9.0,3,11,Urban,ML Engineer,26128,0 +88777,Male,40,Bachelors,3,3,79,56,67,9.0,4,38,Urban,Data Analyst,94094,0 +88778,Male,22,Bachelors,16,61,31,97,93,8.0,0,95,Urban,Manager,137815,1 +88779,Female,41,PhD,10,19,16,76,56,7.0,1,88,Urban,Manager,108175,0 +88780,Male,33,Diploma,14,72,77,76,77,3.0,0,41,Urban,Data Analyst,116850,1 +88781,Male,28,Bachelors,13,26,15,0,12,5.0,1,35,Rural,HR Executive,82972,0 +88782,Female,57,Bachelors,15,53,36,8,85,0.0,0,69,Urban,HR Executive,57389,0 +88783,Male,24,Masters,13,27,23,66,39,0.0,3,49,Urban,Manager,29024,0 +88784,Male,21,Bachelors,9,48,46,74,82,8.0,7,90,Rural,Software Engineer,72868,1 +88785,Male,44,Bachelors,5,52,88,89,93,8.0,2,50,Urban,HR Executive,49726,1 +88786,Male,32,Diploma,11,19,77,61,96,4.0,1,77,Urban,Software Engineer,126380,0 +88787,Female,31,Masters,18,70,67,10,50,7.0,0,15,Urban,ML Engineer,27376,0 +88788,Male,53,Masters,8,12,83,21,32,4.0,4,97,Semi-Urban,HR Executive,26704,0 +88789,Female,47,Masters,6,41,93,10,33,1.0,7,11,Urban,Data Analyst,60469,0 +88790,Male,27,PhD,7,15,79,47,36,8.0,2,59,Semi-Urban,Data Analyst,79393,0 +88791,Male,44,High School,17,77,45,8,45,7.0,7,1,Urban,HR Executive,46388,0 +88792,Male,50,PhD,2,83,11,2,30,9.0,5,44,Semi-Urban,Data Analyst,116088,0 +88793,Male,40,Masters,1,18,14,64,42,6.0,4,13,Urban,ML Engineer,65917,0 +88794,Female,30,High School,16,26,22,32,89,4.0,2,84,Rural,ML Engineer,144205,0 +88795,Male,28,High School,2,95,16,78,46,3.0,4,67,Urban,ML Engineer,71519,1 +88796,Male,50,Bachelors,8,26,40,98,30,0.0,6,54,Urban,ML Engineer,73639,0 +88797,Male,41,Diploma,16,73,43,79,93,4.0,6,68,Rural,Data Analyst,146929,1 +88798,Male,27,Masters,2,51,37,83,54,5.0,3,18,Rural,HR Executive,131273,0 +88799,Male,32,Diploma,1,81,69,50,89,4.0,5,75,Rural,ML Engineer,111578,1 +88800,Male,32,Masters,4,21,79,37,97,9.0,4,60,Rural,HR Executive,117043,0 +88801,Female,43,Bachelors,15,22,52,42,19,3.0,7,21,Semi-Urban,Manager,120399,0 +88802,Male,41,Diploma,11,30,85,90,76,3.0,5,5,Urban,Manager,84085,0 +88803,Male,24,Masters,12,24,79,15,54,0.0,3,67,Urban,ML Engineer,26883,0 +88804,Female,47,High School,6,46,73,87,44,7.0,0,96,Rural,ML Engineer,70848,1 +88805,Male,52,Bachelors,19,18,87,88,94,0.0,1,8,Urban,Manager,47497,0 +88806,Male,45,Bachelors,19,83,1,39,95,4.0,1,86,Rural,HR Executive,69994,0 +88807,Male,54,PhD,8,33,46,88,33,6.0,1,98,Rural,ML Engineer,71936,1 +88808,Male,28,Masters,8,42,22,73,99,6.0,1,14,Rural,Manager,66241,0 +88809,Male,36,Masters,18,44,85,54,10,0.0,4,90,Urban,HR Executive,45471,1 +88810,Male,50,Bachelors,9,78,20,82,19,1.0,7,97,Semi-Urban,Software Engineer,80005,1 +88811,Female,30,Diploma,13,44,47,0,45,2.0,7,94,Urban,ML Engineer,54977,0 +88812,Male,47,High School,13,20,71,7,36,8.0,2,34,Urban,ML Engineer,86464,0 +88813,Female,25,Diploma,7,70,53,98,68,2.0,7,79,Semi-Urban,ML Engineer,132592,1 +88814,Male,21,Bachelors,7,66,28,32,20,3.0,7,15,Semi-Urban,HR Executive,136770,0 +88815,Male,28,Masters,8,64,28,1,98,9.0,6,40,Rural,ML Engineer,117317,0 +88816,Other,41,Bachelors,12,1,86,52,40,0.0,0,33,Urban,Manager,118183,0 +88817,Male,38,Masters,2,92,77,38,85,6.0,3,70,Semi-Urban,Manager,55956,1 +88818,Male,46,Diploma,15,97,98,54,50,3.0,2,99,Urban,Manager,32267,1 +88819,Male,28,Bachelors,18,7,38,46,73,8.0,2,1,Urban,Software Engineer,120883,0 +88820,Female,56,Masters,7,55,10,26,58,4.0,3,78,Urban,ML Engineer,45939,0 +88821,Male,25,Bachelors,2,21,33,43,33,8.0,0,50,Urban,Manager,65076,0 +88822,Female,54,Bachelors,8,64,68,48,39,3.0,6,11,Semi-Urban,Manager,52770,0 +88823,Male,32,High School,8,42,67,82,99,2.0,2,61,Semi-Urban,Data Analyst,65295,1 +88824,Male,36,Diploma,9,83,5,83,97,6.0,3,68,Semi-Urban,Manager,51725,1 +88825,Male,31,Bachelors,4,89,32,6,2,7.0,3,99,Urban,Manager,23904,0 +88826,Male,32,Bachelors,15,42,23,85,16,8.0,0,15,Urban,HR Executive,107799,0 +88827,Male,52,High School,11,7,37,20,63,9.0,6,12,Semi-Urban,Software Engineer,145848,0 +88828,Male,39,Bachelors,2,56,80,16,26,8.0,4,37,Semi-Urban,Software Engineer,107718,0 +88829,Male,36,Bachelors,8,64,89,98,31,5.0,0,0,Urban,Manager,137998,1 +88830,Male,34,Bachelors,15,90,19,62,35,9.0,6,81,Semi-Urban,Manager,71315,1 +88831,Male,54,Diploma,19,28,45,2,44,5.0,1,96,Semi-Urban,Data Analyst,97914,0 +88832,Male,44,Bachelors,3,76,31,16,75,1.0,0,36,Urban,Software Engineer,25887,0 +88833,Male,46,Masters,19,91,98,91,15,6.0,6,64,Semi-Urban,Manager,138982,1 +88834,Male,27,Bachelors,3,18,57,88,69,5.0,3,28,Urban,Manager,81451,0 +88835,Female,21,Bachelors,8,58,17,26,32,1.0,3,30,Rural,Data Analyst,129833,0 +88836,Male,26,High School,6,95,3,14,83,3.0,7,81,Semi-Urban,ML Engineer,133910,0 +88837,Male,57,Diploma,5,35,88,77,92,4.0,6,75,Urban,ML Engineer,128241,1 +88838,Male,29,Masters,6,4,87,77,0,2.0,1,10,Urban,Data Analyst,82428,0 +88839,Male,48,High School,5,38,73,15,35,9.0,6,94,Urban,ML Engineer,52114,0 +88840,Male,51,Bachelors,1,25,47,35,57,9.0,0,57,Urban,HR Executive,141975,0 +88841,Male,38,Bachelors,13,84,58,59,12,6.0,0,51,Urban,Data Analyst,30527,1 +88842,Female,36,Bachelors,11,22,27,9,7,9.0,1,82,Semi-Urban,Data Analyst,96337,0 +88843,Male,55,High School,2,48,89,96,23,5.0,4,69,Urban,Data Analyst,40080,1 +88844,Female,46,Bachelors,1,41,22,33,95,2.0,6,52,Semi-Urban,HR Executive,38674,0 +88845,Male,36,Masters,5,63,13,65,26,2.0,7,59,Semi-Urban,ML Engineer,47027,0 +88846,Female,39,PhD,6,31,51,32,93,8.0,4,44,Semi-Urban,ML Engineer,46328,0 +88847,Female,59,Masters,9,92,9,14,51,7.0,5,7,Urban,Manager,87180,0 +88848,Female,55,Bachelors,9,21,43,56,89,7.0,7,75,Urban,Data Analyst,48192,0 +88849,Male,50,Bachelors,10,52,72,93,82,2.0,4,8,Semi-Urban,Manager,72315,0 +88850,Male,45,Bachelors,19,89,36,19,36,4.0,7,10,Urban,ML Engineer,78264,0 +88851,Female,38,Bachelors,14,98,4,39,18,2.0,1,8,Urban,HR Executive,93250,0 +88852,Male,52,High School,18,40,50,66,51,7.0,0,85,Rural,Manager,77681,1 +88853,Male,41,Bachelors,14,59,52,40,53,2.0,1,26,Urban,ML Engineer,133288,0 +88854,Male,36,Bachelors,9,62,9,59,91,3.0,0,7,Rural,HR Executive,92342,0 +88855,Male,23,Masters,1,32,78,3,86,6.0,6,20,Rural,HR Executive,108555,0 +88856,Other,25,Bachelors,6,67,89,16,86,2.0,3,70,Urban,Manager,37148,1 +88857,Male,23,Bachelors,6,42,76,41,51,5.0,0,88,Urban,Software Engineer,53771,1 +88858,Male,47,Diploma,1,39,58,76,68,2.0,2,36,Urban,Software Engineer,88789,0 +88859,Female,51,Bachelors,13,19,54,66,88,6.0,7,10,Urban,Data Analyst,78875,0 +88860,Male,42,Bachelors,3,62,76,44,80,1.0,0,84,Urban,HR Executive,30535,1 +88861,Male,45,Bachelors,8,56,22,0,67,9.0,2,39,Semi-Urban,Software Engineer,84861,0 +88862,Male,25,Bachelors,13,24,99,67,80,0.0,6,88,Rural,Data Analyst,84508,1 +88863,Male,56,Bachelors,14,6,77,86,11,4.0,0,24,Urban,HR Executive,62688,0 +88864,Male,45,Bachelors,11,91,79,74,99,4.0,0,65,Semi-Urban,Data Analyst,119081,1 +88865,Male,50,Masters,18,59,3,80,27,2.0,0,46,Urban,Manager,29345,0 +88866,Female,45,Bachelors,18,31,85,4,15,3.0,4,33,Semi-Urban,HR Executive,22107,0 +88867,Male,35,Bachelors,6,66,58,59,36,9.0,4,43,Urban,Data Analyst,122190,0 +88868,Female,21,Bachelors,11,92,33,51,39,6.0,5,96,Urban,Software Engineer,133988,1 +88869,Female,28,High School,17,13,22,70,10,7.0,3,94,Rural,Software Engineer,65489,0 +88870,Female,51,Diploma,19,28,11,73,37,2.0,4,82,Rural,Software Engineer,95898,0 +88871,Male,46,Bachelors,8,85,46,17,11,3.0,0,83,Semi-Urban,Data Analyst,73478,0 +88872,Male,54,Bachelors,12,44,65,73,18,2.0,5,85,Rural,Manager,122446,1 +88873,Female,44,Bachelors,1,77,6,42,76,8.0,3,18,Rural,Software Engineer,112727,0 +88874,Female,29,Bachelors,16,68,91,78,69,4.0,5,19,Urban,HR Executive,71611,1 +88875,Male,43,Masters,16,63,16,30,16,9.0,0,84,Urban,Software Engineer,34422,0 +88876,Other,36,High School,4,88,25,84,47,0.0,0,84,Urban,Software Engineer,115628,1 +88877,Male,44,Masters,7,52,79,86,60,5.0,7,19,Urban,Manager,93937,1 +88878,Male,41,High School,16,97,98,71,26,5.0,5,7,Rural,HR Executive,39708,1 +88879,Male,28,High School,2,77,56,90,96,2.0,7,30,Urban,HR Executive,59862,1 +88880,Male,55,Diploma,2,81,11,46,5,5.0,6,6,Semi-Urban,HR Executive,116565,0 +88881,Male,46,Bachelors,18,54,37,5,2,5.0,5,78,Urban,Manager,22631,0 +88882,Female,49,Masters,2,6,11,0,31,7.0,7,38,Semi-Urban,HR Executive,146345,0 +88883,Male,26,Diploma,11,4,16,90,5,4.0,2,41,Urban,Manager,62441,0 +88884,Male,37,Bachelors,8,19,37,50,91,7.0,7,25,Rural,Manager,67118,0 +88885,Male,25,Diploma,5,19,33,19,88,1.0,4,46,Semi-Urban,Data Analyst,55646,0 +88886,Female,40,Masters,7,90,41,10,84,0.0,5,92,Semi-Urban,Software Engineer,120922,0 +88887,Male,45,Masters,13,18,13,54,47,2.0,5,59,Semi-Urban,Manager,147986,0 +88888,Male,46,Masters,9,74,80,70,64,4.0,6,24,Urban,HR Executive,142754,1 +88889,Male,59,Bachelors,19,67,36,0,54,9.0,2,45,Rural,ML Engineer,125667,0 +88890,Male,39,Masters,18,68,28,96,31,8.0,6,47,Urban,Data Analyst,49837,1 +88891,Male,44,Bachelors,13,76,96,56,94,7.0,4,80,Semi-Urban,HR Executive,96088,1 +88892,Male,57,Diploma,4,34,81,38,85,7.0,0,37,Urban,Software Engineer,134814,0 +88893,Male,37,High School,0,81,21,64,33,2.0,7,30,Rural,Data Analyst,133833,0 +88894,Male,57,Bachelors,7,43,38,39,76,4.0,7,23,Urban,Data Analyst,114120,0 +88895,Female,45,Bachelors,9,69,37,59,92,9.0,1,35,Rural,Software Engineer,135159,0 +88896,Male,40,Bachelors,19,13,58,76,96,2.0,3,45,Rural,Software Engineer,61570,0 +88897,Male,41,Masters,9,35,0,20,27,2.0,2,94,Urban,ML Engineer,147535,0 +88898,Female,28,Bachelors,0,52,91,17,25,8.0,6,6,Urban,Software Engineer,108840,0 +88899,Male,42,Masters,11,48,49,72,84,4.0,5,15,Urban,ML Engineer,50869,0 +88900,Female,32,Diploma,17,96,93,38,9,3.0,4,33,Urban,HR Executive,100685,1 +88901,Male,35,Bachelors,5,70,75,43,95,1.0,5,60,Urban,Software Engineer,86250,1 +88902,Female,32,Diploma,8,39,80,55,71,5.0,5,10,Urban,Data Analyst,93467,0 +88903,Male,23,Bachelors,18,84,25,71,97,5.0,7,16,Semi-Urban,HR Executive,40148,0 +88904,Female,39,Bachelors,5,3,46,87,21,3.0,2,48,Semi-Urban,HR Executive,78662,0 +88905,Male,34,Masters,10,36,22,21,61,3.0,2,43,Rural,Manager,49672,0 +88906,Male,25,Masters,19,54,64,43,48,2.0,0,21,Urban,HR Executive,22182,0 +88907,Male,52,Bachelors,17,1,22,84,80,4.0,0,83,Urban,ML Engineer,101342,0 +88908,Male,41,High School,15,41,68,86,56,0.0,7,1,Urban,Software Engineer,124336,0 +88909,Female,35,Diploma,15,3,39,16,23,7.0,4,92,Urban,ML Engineer,40325,0 +88910,Male,45,Bachelors,19,35,86,93,66,5.0,0,32,Urban,Manager,102158,1 +88911,Male,57,High School,18,85,85,52,57,0.0,2,93,Semi-Urban,Software Engineer,98052,1 +88912,Male,28,Bachelors,14,88,17,69,81,9.0,4,12,Urban,ML Engineer,98305,0 +88913,Male,51,Masters,6,4,43,17,96,6.0,0,98,Urban,ML Engineer,44847,0 +88914,Male,49,Bachelors,9,36,6,22,68,1.0,7,89,Urban,Data Analyst,58517,0 +88915,Male,23,Masters,9,87,33,6,89,0.0,2,99,Urban,Manager,101629,0 +88916,Female,39,Bachelors,6,28,90,24,20,4.0,2,86,Urban,Data Analyst,54936,0 +88917,Male,21,Bachelors,15,84,45,60,27,4.0,0,71,Urban,Manager,64631,1 +88918,Female,47,Diploma,11,27,10,36,94,3.0,2,72,Urban,Data Analyst,35660,0 +88919,Male,35,High School,18,54,37,8,59,9.0,6,30,Urban,ML Engineer,126860,0 +88920,Male,43,Diploma,12,40,56,1,85,3.0,0,38,Urban,Data Analyst,40606,0 +88921,Male,56,Bachelors,1,6,75,36,45,8.0,7,95,Urban,Data Analyst,52328,0 +88922,Male,42,Masters,8,9,79,55,66,2.0,0,78,Semi-Urban,Manager,48541,0 +88923,Male,57,Bachelors,16,28,9,58,5,2.0,5,55,Urban,ML Engineer,63477,0 +88924,Female,27,Bachelors,11,16,21,54,60,0.0,7,5,Urban,HR Executive,146734,0 +88925,Female,44,Bachelors,2,18,30,37,84,2.0,3,67,Semi-Urban,Manager,126258,0 +88926,Female,22,High School,9,18,75,38,50,1.0,2,1,Urban,HR Executive,88334,0 +88927,Male,49,PhD,14,63,84,18,55,7.0,3,89,Urban,Data Analyst,53704,1 +88928,Male,47,Masters,18,62,11,96,48,3.0,3,23,Urban,ML Engineer,101870,0 +88929,Female,42,Bachelors,7,80,43,13,7,9.0,4,89,Urban,Manager,97748,0 +88930,Male,56,High School,13,87,83,81,62,7.0,1,59,Semi-Urban,Data Analyst,86466,1 +88931,Female,58,Diploma,7,8,31,82,12,8.0,2,43,Urban,Manager,146797,0 +88932,Male,48,Diploma,4,40,94,28,58,2.0,7,32,Rural,Software Engineer,51460,0 +88933,Other,51,Diploma,5,57,37,31,34,6.0,3,95,Urban,ML Engineer,120263,0 +88934,Male,28,High School,4,34,11,64,61,0.0,3,86,Urban,HR Executive,128633,0 +88935,Male,39,Bachelors,2,20,7,33,26,1.0,0,36,Urban,HR Executive,90689,0 +88936,Male,30,Bachelors,12,80,82,41,44,4.0,7,44,Urban,ML Engineer,41814,1 +88937,Female,26,Bachelors,2,79,93,70,3,9.0,1,15,Semi-Urban,Data Analyst,86295,1 +88938,Male,42,Diploma,8,99,75,18,66,8.0,1,85,Semi-Urban,ML Engineer,131705,1 +88939,Female,28,Masters,8,23,31,90,93,5.0,0,2,Urban,Software Engineer,133306,0 +88940,Female,44,PhD,13,96,6,64,36,4.0,1,16,Urban,HR Executive,56426,0 +88941,Female,53,Masters,4,57,17,21,41,3.0,7,26,Urban,ML Engineer,57233,0 +88942,Female,35,Bachelors,5,17,85,72,8,4.0,4,76,Urban,Software Engineer,55597,1 +88943,Male,51,Bachelors,14,73,25,59,50,9.0,0,54,Urban,Software Engineer,21278,0 +88944,Male,33,Masters,4,53,52,79,27,7.0,1,82,Urban,Data Analyst,121162,1 +88945,Male,48,High School,6,82,32,28,57,9.0,5,18,Rural,Software Engineer,83364,0 +88946,Female,52,Diploma,3,6,60,9,75,5.0,3,8,Urban,ML Engineer,74149,0 +88947,Male,37,Bachelors,13,8,56,86,50,4.0,0,32,Rural,Manager,64631,0 +88948,Male,33,Diploma,19,35,69,22,26,5.0,7,91,Semi-Urban,Manager,81184,0 +88949,Female,36,Diploma,17,48,39,73,59,2.0,5,77,Urban,ML Engineer,81183,0 +88950,Male,45,PhD,3,22,37,95,47,3.0,5,76,Urban,Data Analyst,142404,0 +88951,Male,32,Bachelors,14,60,14,83,99,1.0,0,61,Semi-Urban,Manager,132694,0 +88952,Male,43,Diploma,6,25,48,91,44,7.0,6,37,Rural,Data Analyst,55951,0 +88953,Female,22,Bachelors,3,12,47,84,8,3.0,0,30,Urban,ML Engineer,95049,0 +88954,Female,33,Masters,3,71,23,30,44,6.0,3,82,Semi-Urban,Manager,27398,0 +88955,Male,28,Bachelors,14,83,55,84,56,8.0,4,33,Urban,HR Executive,85080,1 +88956,Male,25,Diploma,16,22,34,22,58,5.0,3,93,Urban,Manager,27768,0 +88957,Female,47,Diploma,11,76,61,66,70,5.0,2,42,Rural,Software Engineer,96293,1 +88958,Male,45,Masters,11,61,11,70,88,1.0,1,79,Urban,HR Executive,73568,0 +88959,Female,21,Masters,11,26,44,76,88,4.0,1,37,Rural,Manager,116815,0 +88960,Male,27,Masters,0,93,81,82,72,8.0,4,37,Semi-Urban,Manager,98918,1 +88961,Female,36,Bachelors,12,31,96,52,22,4.0,3,73,Urban,Data Analyst,56826,1 +88962,Other,50,Bachelors,19,11,32,3,18,5.0,2,11,Urban,Manager,44450,0 +88963,Male,40,Masters,8,65,70,74,49,1.0,2,85,Semi-Urban,Software Engineer,121361,1 +88964,Male,41,Diploma,14,10,8,65,38,1.0,1,95,Rural,Software Engineer,97240,0 +88965,Other,47,Diploma,17,35,87,30,55,0.0,2,3,Urban,ML Engineer,64122,0 +88966,Male,22,Masters,4,3,49,55,98,1.0,7,57,Semi-Urban,HR Executive,96548,0 +88967,Female,28,Bachelors,2,77,53,62,6,5.0,5,11,Urban,Data Analyst,131587,0 +88968,Female,39,Bachelors,15,78,95,70,1,1.0,6,69,Urban,Software Engineer,90325,1 +88969,Male,48,High School,11,89,82,67,27,2.0,3,75,Urban,HR Executive,128695,1 +88970,Male,50,PhD,6,49,84,48,79,2.0,6,37,Urban,ML Engineer,56830,0 +88971,Male,57,Masters,8,92,6,12,59,4.0,1,26,Urban,HR Executive,65569,0 +88972,Male,33,Bachelors,9,64,95,66,61,9.0,5,98,Urban,HR Executive,38317,1 +88973,Male,34,Diploma,18,79,23,10,79,4.0,5,88,Rural,ML Engineer,110580,0 +88974,Male,26,PhD,15,19,50,78,19,5.0,5,28,Rural,Data Analyst,140023,0 +88975,Male,45,Diploma,10,24,67,1,52,2.0,7,45,Urban,Data Analyst,38603,0 +88976,Male,38,Diploma,6,65,88,42,19,6.0,2,9,Urban,Manager,98806,0 +88977,Female,23,Bachelors,1,86,28,70,10,2.0,4,62,Urban,ML Engineer,37847,1 +88978,Male,29,Bachelors,14,87,18,92,7,2.0,5,16,Urban,ML Engineer,124958,0 +88979,Female,26,Bachelors,2,92,5,82,26,9.0,4,71,Rural,Data Analyst,33584,1 +88980,Other,32,Bachelors,1,5,93,37,16,3.0,1,41,Urban,Manager,44845,0 +88981,Female,43,Masters,2,20,54,53,24,4.0,2,3,Urban,Manager,69924,0 +88982,Male,47,Bachelors,11,22,77,34,86,5.0,2,73,Semi-Urban,Data Analyst,51219,0 +88983,Male,24,Bachelors,19,24,57,64,79,2.0,0,66,Urban,Software Engineer,101493,0 +88984,Male,34,Masters,9,91,92,19,23,1.0,4,92,Semi-Urban,HR Executive,129829,1 +88985,Male,41,Masters,12,31,25,16,7,8.0,1,12,Urban,ML Engineer,91720,0 +88986,Female,46,Masters,14,7,96,4,56,8.0,3,23,Semi-Urban,Software Engineer,79951,0 +88987,Male,25,High School,5,58,94,75,67,6.0,0,32,Urban,Data Analyst,41310,1 +88988,Male,42,Bachelors,19,81,18,30,89,4.0,3,30,Rural,ML Engineer,49237,0 +88989,Male,46,Diploma,14,19,67,77,39,8.0,7,96,Urban,Data Analyst,73625,1 +88990,Male,39,Diploma,8,92,59,96,29,3.0,3,15,Urban,Software Engineer,86887,1 +88991,Female,43,Masters,10,17,7,10,25,3.0,3,0,Semi-Urban,HR Executive,133708,0 +88992,Male,37,Masters,1,50,17,17,26,3.0,2,17,Semi-Urban,Software Engineer,116651,0 +88993,Female,27,Masters,1,36,79,59,84,8.0,5,51,Urban,Data Analyst,146628,0 +88994,Male,41,Bachelors,7,48,79,91,47,3.0,0,92,Urban,Manager,71219,1 +88995,Female,53,High School,5,47,73,35,66,4.0,4,60,Urban,Software Engineer,101402,0 +88996,Female,26,Masters,14,24,89,38,69,7.0,2,20,Semi-Urban,Software Engineer,135713,0 +88997,Male,31,Bachelors,19,34,82,49,90,9.0,5,37,Urban,Software Engineer,101746,0 +88998,Female,55,Bachelors,6,22,21,79,83,7.0,6,78,Urban,Manager,130326,0 +88999,Male,40,High School,10,61,15,16,15,6.0,5,60,Semi-Urban,Software Engineer,103826,0 +89000,Female,55,Bachelors,3,37,12,84,67,2.0,3,25,Urban,HR Executive,143208,0 +89001,Male,27,Masters,6,24,31,69,11,9.0,2,20,Semi-Urban,Data Analyst,97406,0 +89002,Female,46,Bachelors,15,35,81,22,23,0.0,6,50,Urban,Manager,50534,0 +89003,Male,50,Bachelors,2,12,65,71,37,9.0,6,50,Urban,Software Engineer,96583,0 +89004,Male,43,Bachelors,7,30,71,26,18,6.0,2,97,Urban,Manager,126771,0 +89005,Male,25,Bachelors,3,53,22,82,98,3.0,6,50,Urban,ML Engineer,88708,0 +89006,Male,37,Diploma,19,88,78,49,44,3.0,1,72,Rural,HR Executive,55618,1 +89007,Female,35,Masters,13,46,22,93,26,0.0,5,7,Rural,ML Engineer,139945,0 +89008,Male,54,Bachelors,8,86,25,87,63,0.0,1,68,Urban,Manager,92131,1 +89009,Female,59,Bachelors,11,20,45,90,94,7.0,1,75,Urban,Software Engineer,138706,0 +89010,Female,51,Bachelors,6,7,47,83,7,9.0,6,45,Rural,HR Executive,43862,0 +89011,Male,23,High School,12,53,27,57,62,1.0,7,62,Urban,HR Executive,143358,0 +89012,Male,39,Masters,19,62,12,2,65,7.0,7,19,Urban,HR Executive,20632,0 +89013,Male,50,Masters,16,9,51,33,22,8.0,1,40,Urban,Data Analyst,90527,0 +89014,Female,21,Diploma,4,15,98,35,92,5.0,2,73,Rural,HR Executive,35144,0 +89015,Female,42,Masters,0,90,54,50,5,9.0,3,91,Semi-Urban,Manager,142335,1 +89016,Male,25,Masters,15,50,47,35,40,7.0,4,41,Urban,Data Analyst,21689,0 +89017,Male,50,Masters,14,4,16,42,2,8.0,7,0,Urban,Software Engineer,40500,0 +89018,Male,31,High School,16,86,73,70,62,6.0,1,71,Urban,Data Analyst,118791,1 +89019,Female,22,Bachelors,6,25,0,19,19,4.0,1,51,Urban,Manager,83625,0 +89020,Other,57,Bachelors,14,81,23,96,77,2.0,3,21,Urban,HR Executive,49279,0 +89021,Male,49,Masters,5,66,82,43,7,7.0,6,55,Urban,Manager,33486,1 +89022,Female,35,Masters,16,60,84,46,52,1.0,1,26,Urban,Data Analyst,51962,0 +89023,Other,30,High School,15,90,21,0,71,4.0,5,38,Urban,Data Analyst,76628,0 +89024,Male,40,Bachelors,18,69,28,6,91,4.0,2,18,Urban,Software Engineer,52548,0 +89025,Male,50,High School,5,33,67,92,76,6.0,3,78,Urban,Manager,113733,1 +89026,Female,57,Bachelors,7,55,71,86,7,9.0,6,4,Semi-Urban,Data Analyst,86995,0 +89027,Female,53,Bachelors,6,85,90,96,46,9.0,4,11,Semi-Urban,ML Engineer,106370,1 +89028,Male,44,Bachelors,8,16,54,79,4,2.0,0,98,Rural,Manager,21862,1 +89029,Male,24,Bachelors,16,24,41,36,29,7.0,0,85,Urban,Software Engineer,81742,0 +89030,Male,27,Bachelors,12,55,46,27,36,7.0,5,43,Rural,Data Analyst,117905,0 +89031,Male,46,Masters,8,11,28,56,7,5.0,4,8,Semi-Urban,Data Analyst,138860,0 +89032,Other,52,High School,15,33,24,91,90,9.0,6,53,Urban,ML Engineer,56874,0 +89033,Male,49,High School,2,73,72,89,41,5.0,2,76,Urban,ML Engineer,101556,1 +89034,Female,58,Bachelors,4,49,35,25,53,7.0,5,38,Urban,Data Analyst,100559,0 +89035,Male,51,Masters,3,29,82,9,64,4.0,7,14,Urban,Software Engineer,24227,0 +89036,Male,44,Bachelors,7,92,2,6,19,4.0,5,24,Urban,Manager,87724,0 +89037,Male,55,Masters,10,71,36,90,65,9.0,2,30,Semi-Urban,Data Analyst,48336,0 +89038,Male,55,High School,3,87,23,15,12,0.0,7,80,Urban,ML Engineer,149789,0 +89039,Other,24,PhD,4,15,4,28,89,8.0,1,44,Semi-Urban,Software Engineer,100772,0 +89040,Male,32,Bachelors,16,27,66,10,3,1.0,1,93,Rural,Manager,105266,0 +89041,Female,28,Bachelors,5,58,95,38,11,6.0,1,2,Semi-Urban,HR Executive,107509,0 +89042,Male,41,Bachelors,7,73,73,74,15,2.0,2,63,Semi-Urban,ML Engineer,110125,1 +89043,Female,33,PhD,3,87,81,25,50,3.0,7,94,Urban,HR Executive,90101,1 +89044,Male,25,Diploma,16,50,24,54,68,5.0,4,1,Semi-Urban,Data Analyst,144519,0 +89045,Male,32,High School,3,89,17,93,7,4.0,5,16,Semi-Urban,ML Engineer,106950,0 +89046,Female,31,Diploma,5,38,40,37,60,1.0,0,19,Urban,Software Engineer,63489,0 +89047,Female,58,Bachelors,18,28,20,52,3,0.0,0,5,Urban,Manager,135441,0 +89048,Male,38,Bachelors,18,91,85,95,65,6.0,4,47,Urban,Data Analyst,64028,1 +89049,Female,44,Diploma,7,64,31,17,5,6.0,1,48,Semi-Urban,Software Engineer,99444,0 +89050,Male,45,Bachelors,0,31,87,75,68,2.0,6,77,Rural,ML Engineer,86486,1 +89051,Male,39,Bachelors,2,40,72,26,63,4.0,4,33,Rural,HR Executive,145495,0 +89052,Female,23,Masters,9,12,14,48,22,3.0,3,97,Semi-Urban,Data Analyst,122953,0 +89053,Female,39,Masters,15,85,81,19,49,6.0,1,78,Urban,Manager,31124,1 +89054,Male,58,High School,19,87,66,90,95,6.0,1,72,Urban,ML Engineer,58553,1 +89055,Male,40,Diploma,19,90,23,78,20,2.0,2,94,Semi-Urban,Software Engineer,63834,1 +89056,Male,21,High School,0,0,23,17,10,8.0,3,97,Urban,HR Executive,64294,0 +89057,Male,45,Bachelors,17,54,36,83,81,5.0,7,42,Urban,Data Analyst,47688,0 +89058,Male,47,Bachelors,2,12,11,83,2,8.0,3,71,Semi-Urban,Manager,95213,0 +89059,Male,21,Diploma,15,26,37,92,36,7.0,4,75,Urban,Software Engineer,96604,0 +89060,Female,52,Bachelors,18,24,44,75,72,9.0,2,73,Rural,Manager,36260,0 +89061,Female,59,Bachelors,10,20,9,41,88,6.0,1,10,Urban,Software Engineer,81645,0 +89062,Male,36,High School,0,18,89,17,19,3.0,2,64,Urban,ML Engineer,95637,0 +89063,Female,37,Diploma,9,34,6,95,92,6.0,6,41,Semi-Urban,HR Executive,52457,0 +89064,Male,39,Bachelors,8,46,72,49,89,3.0,5,98,Urban,HR Executive,130237,1 +89065,Female,51,Diploma,4,52,66,58,18,7.0,7,96,Rural,ML Engineer,139863,1 +89066,Female,53,Bachelors,3,84,95,18,86,7.0,7,18,Urban,HR Executive,119931,0 +89067,Female,40,Bachelors,17,15,40,59,40,4.0,1,96,Urban,Software Engineer,143884,0 +89068,Male,53,Diploma,11,56,51,61,4,8.0,3,81,Urban,Data Analyst,75662,1 +89069,Other,47,High School,19,90,76,25,0,2.0,0,64,Semi-Urban,Manager,98409,1 +89070,Female,22,Bachelors,6,83,74,83,4,8.0,7,97,Urban,ML Engineer,140105,1 +89071,Male,36,Bachelors,9,25,27,92,92,3.0,3,49,Semi-Urban,Data Analyst,127400,0 +89072,Male,23,Diploma,17,91,34,39,62,6.0,5,98,Semi-Urban,HR Executive,102052,1 +89073,Male,27,Bachelors,15,54,21,71,88,6.0,4,85,Rural,HR Executive,47010,0 +89074,Male,34,Masters,5,27,43,69,28,9.0,2,2,Semi-Urban,Manager,89459,0 +89075,Male,46,PhD,15,50,93,29,36,4.0,6,15,Urban,ML Engineer,95423,0 +89076,Other,26,Bachelors,4,73,89,30,95,1.0,3,46,Rural,HR Executive,109039,0 +89077,Female,22,Bachelors,14,81,5,75,27,4.0,4,61,Rural,HR Executive,21829,0 +89078,Male,57,Diploma,2,43,76,69,33,6.0,5,41,Semi-Urban,Data Analyst,105602,0 +89079,Male,55,High School,15,40,22,70,58,7.0,0,11,Urban,Data Analyst,28232,0 +89080,Female,38,Masters,2,18,74,71,40,5.0,6,23,Rural,Software Engineer,22242,0 +89081,Male,48,High School,16,20,1,48,27,9.0,5,95,Rural,Data Analyst,73033,0 +89082,Female,37,Masters,3,84,43,59,35,0.0,4,52,Urban,ML Engineer,76818,0 +89083,Male,38,Bachelors,16,65,8,10,81,3.0,1,72,Urban,ML Engineer,32762,0 +89084,Male,52,Masters,17,19,18,14,79,7.0,1,67,Semi-Urban,ML Engineer,134021,0 +89085,Female,41,Bachelors,3,48,27,50,80,8.0,0,88,Urban,Manager,43623,0 +89086,Male,26,Diploma,4,40,73,71,44,2.0,6,30,Urban,Software Engineer,146304,0 +89087,Male,38,Masters,11,63,41,98,56,1.0,6,11,Urban,Software Engineer,22638,0 +89088,Male,45,Masters,12,96,37,58,87,4.0,7,47,Rural,Data Analyst,129973,1 +89089,Female,29,Bachelors,14,59,29,33,84,9.0,5,62,Rural,HR Executive,130540,0 +89090,Male,41,Bachelors,14,68,64,59,31,4.0,2,99,Semi-Urban,Manager,74316,1 +89091,Male,42,Masters,11,22,51,12,46,5.0,3,93,Rural,Software Engineer,38573,0 +89092,Other,42,Bachelors,7,73,53,66,27,0.0,7,7,Urban,Manager,85416,0 +89093,Male,40,Masters,10,83,96,10,82,1.0,2,74,Semi-Urban,ML Engineer,55300,1 +89094,Male,24,Diploma,9,19,42,96,1,5.0,7,47,Urban,Software Engineer,77258,0 +89095,Male,57,Diploma,15,86,3,33,40,0.0,7,46,Urban,Manager,145645,0 +89096,Male,46,Diploma,17,67,39,70,94,5.0,7,4,Semi-Urban,Data Analyst,81647,0 +89097,Male,42,Masters,19,59,47,47,66,8.0,3,16,Semi-Urban,Software Engineer,67151,0 +89098,Male,44,Diploma,1,68,53,37,49,6.0,7,54,Semi-Urban,Software Engineer,97229,0 +89099,Male,49,Bachelors,18,36,95,34,33,7.0,0,1,Urban,Software Engineer,130256,0 +89100,Female,33,Diploma,10,5,76,67,72,3.0,0,84,Urban,HR Executive,28516,0 +89101,Male,54,Bachelors,18,65,90,49,26,2.0,0,75,Rural,Manager,112739,1 +89102,Other,41,Masters,2,80,64,8,84,4.0,2,32,Semi-Urban,Data Analyst,22281,0 +89103,Female,43,PhD,18,98,29,69,33,8.0,4,71,Semi-Urban,ML Engineer,134749,1 +89104,Male,32,High School,7,62,69,97,9,5.0,4,73,Urban,Data Analyst,66228,1 +89105,Male,43,Diploma,0,51,94,83,13,8.0,4,5,Urban,ML Engineer,101920,0 +89106,Female,36,Bachelors,15,35,4,60,88,5.0,6,89,Semi-Urban,Data Analyst,139393,0 +89107,Female,54,Diploma,19,27,88,93,15,6.0,3,87,Semi-Urban,Data Analyst,91292,1 +89108,Female,51,High School,17,49,58,65,8,3.0,0,15,Urban,HR Executive,136828,0 +89109,Male,59,High School,14,11,30,15,25,2.0,2,11,Semi-Urban,HR Executive,61062,0 +89110,Male,35,Bachelors,10,15,87,67,85,3.0,6,18,Urban,HR Executive,23196,0 +89111,Female,50,Masters,11,25,64,62,36,5.0,5,95,Urban,ML Engineer,88322,1 +89112,Female,51,Masters,13,63,13,26,37,5.0,4,93,Urban,Manager,96474,0 +89113,Other,59,Diploma,10,57,40,94,0,5.0,6,59,Urban,Manager,74208,1 +89114,Female,25,Masters,9,28,2,87,17,3.0,5,76,Urban,HR Executive,99657,0 +89115,Male,22,High School,15,33,42,5,42,7.0,5,35,Urban,HR Executive,28636,0 +89116,Male,50,Bachelors,9,9,37,18,33,6.0,1,91,Urban,ML Engineer,69923,0 +89117,Male,22,Bachelors,4,83,28,2,37,2.0,4,61,Urban,ML Engineer,57190,0 +89118,Male,39,Bachelors,5,45,66,36,19,7.0,3,19,Urban,Manager,127322,0 +89119,Male,55,Masters,14,45,31,20,51,2.0,7,46,Semi-Urban,Data Analyst,74559,0 +89120,Male,43,Diploma,7,25,41,92,95,3.0,1,56,Semi-Urban,HR Executive,115240,0 +89121,Male,31,Masters,16,94,42,78,58,9.0,0,22,Urban,HR Executive,31354,1 +89122,Male,21,Bachelors,2,87,51,94,0,9.0,4,44,Urban,Software Engineer,61033,1 +89123,Female,38,PhD,10,59,84,47,53,6.0,3,34,Semi-Urban,HR Executive,91607,0 +89124,Male,44,Bachelors,12,44,36,29,81,2.0,0,65,Urban,ML Engineer,67701,0 +89125,Male,35,Masters,11,62,22,93,90,9.0,7,56,Urban,ML Engineer,101947,0 +89126,Male,47,High School,10,11,79,12,43,8.0,1,89,Semi-Urban,Data Analyst,41564,0 +89127,Male,27,Diploma,18,48,4,24,42,2.0,1,98,Urban,Data Analyst,28165,0 +89128,Female,21,Bachelors,18,77,8,21,63,2.0,0,58,Rural,HR Executive,65851,0 +89129,Male,39,Diploma,6,84,43,42,65,1.0,3,62,Semi-Urban,Manager,65363,0 +89130,Male,39,Bachelors,14,39,61,93,54,3.0,6,79,Urban,Software Engineer,134779,1 +89131,Female,52,Bachelors,4,43,51,76,22,0.0,3,15,Urban,Software Engineer,99303,0 +89132,Male,30,Diploma,17,56,75,49,3,4.0,7,6,Urban,Data Analyst,147121,0 +89133,Female,24,Diploma,5,5,47,60,69,4.0,2,59,Urban,Manager,24716,0 +89134,Male,41,Diploma,19,9,78,68,62,0.0,7,27,Urban,ML Engineer,136998,0 +89135,Male,56,High School,9,77,49,83,57,8.0,7,26,Urban,HR Executive,122985,1 +89136,Male,23,Masters,0,47,41,1,69,1.0,4,86,Urban,Software Engineer,92567,0 +89137,Female,47,Masters,11,24,49,46,70,2.0,6,70,Urban,Software Engineer,77722,0 +89138,Male,29,High School,18,13,82,61,62,5.0,3,29,Urban,Manager,46414,0 +89139,Female,48,Bachelors,16,37,47,36,30,0.0,7,52,Urban,ML Engineer,101756,0 +89140,Female,52,Masters,1,53,44,40,97,4.0,1,88,Urban,ML Engineer,56798,0 +89141,Male,59,Diploma,10,95,27,33,78,8.0,0,48,Semi-Urban,ML Engineer,35815,0 +89142,Female,41,Bachelors,17,11,40,18,11,7.0,7,31,Urban,HR Executive,29388,0 +89143,Male,38,High School,17,86,21,34,22,6.0,3,70,Urban,Manager,71094,0 +89144,Female,22,Bachelors,0,16,69,23,95,6.0,3,97,Semi-Urban,HR Executive,89205,0 +89145,Female,49,Masters,3,38,42,0,83,6.0,7,27,Urban,HR Executive,118642,0 +89146,Male,52,Masters,18,63,69,45,46,4.0,1,31,Urban,Software Engineer,43228,0 +89147,Female,34,Bachelors,12,73,63,88,74,6.0,6,44,Semi-Urban,Data Analyst,142478,1 +89148,Male,27,Masters,1,7,14,54,92,0.0,5,45,Semi-Urban,HR Executive,95352,0 +89149,Female,25,Diploma,18,57,42,12,5,8.0,3,86,Semi-Urban,Data Analyst,109550,0 +89150,Female,22,High School,5,90,25,74,9,9.0,5,85,Semi-Urban,Manager,38442,1 +89151,Male,54,Bachelors,12,71,52,14,35,0.0,4,27,Urban,HR Executive,112290,0 +89152,Male,41,Bachelors,19,32,66,45,31,2.0,1,80,Semi-Urban,Software Engineer,122237,0 +89153,Female,40,Diploma,11,64,23,53,89,0.0,1,90,Urban,Data Analyst,82805,0 +89154,Female,51,Diploma,16,33,71,58,55,1.0,0,52,Semi-Urban,Software Engineer,108800,0 +89155,Male,22,High School,5,47,57,75,42,8.0,1,38,Urban,HR Executive,72168,0 +89156,Male,40,High School,5,5,28,73,26,7.0,6,46,Semi-Urban,Software Engineer,54033,0 +89157,Male,35,Diploma,5,27,71,36,97,6.0,5,79,Urban,HR Executive,147909,0 +89158,Male,59,Bachelors,13,6,78,89,33,2.0,2,24,Urban,ML Engineer,21960,0 +89159,Male,52,Masters,14,57,21,73,33,3.0,7,26,Urban,ML Engineer,134153,0 +89160,Male,43,Masters,4,80,22,76,47,7.0,4,56,Urban,ML Engineer,40838,0 +89161,Male,29,PhD,8,54,27,93,85,4.0,6,81,Rural,Software Engineer,84642,1 +89162,Female,51,Diploma,13,86,69,55,6,7.0,0,93,Urban,HR Executive,41810,1 +89163,Male,43,Bachelors,17,31,40,72,78,2.0,0,97,Urban,Data Analyst,31940,1 +89164,Male,57,Bachelors,13,39,87,64,8,6.0,3,3,Urban,Manager,31165,0 +89165,Male,43,PhD,6,79,81,13,44,5.0,7,48,Urban,Manager,88765,0 +89166,Male,54,High School,11,1,31,70,56,1.0,0,16,Urban,Software Engineer,65956,0 +89167,Female,38,Bachelors,0,34,64,43,79,3.0,4,38,Semi-Urban,Software Engineer,24394,0 +89168,Male,29,Bachelors,16,50,87,40,6,2.0,1,82,Rural,ML Engineer,116134,1 +89169,Female,50,Bachelors,9,55,48,27,82,7.0,3,82,Urban,Software Engineer,117405,0 +89170,Other,48,Bachelors,14,21,21,24,43,2.0,4,27,Semi-Urban,HR Executive,115411,0 +89171,Male,47,High School,9,45,14,92,4,6.0,0,85,Urban,Data Analyst,121211,1 +89172,Male,43,Bachelors,0,2,24,70,33,5.0,0,38,Urban,Manager,109322,0 +89173,Female,54,High School,9,94,78,66,76,0.0,7,53,Rural,Manager,118434,1 +89174,Female,53,Masters,5,56,7,52,42,3.0,0,60,Urban,ML Engineer,47494,0 +89175,Female,49,Diploma,11,88,34,84,13,4.0,1,77,Urban,Data Analyst,97302,1 +89176,Other,37,Diploma,7,95,92,55,88,9.0,3,56,Semi-Urban,HR Executive,77865,1 +89177,Male,52,Diploma,1,26,69,91,99,4.0,1,44,Urban,HR Executive,143734,0 +89178,Male,28,Diploma,17,35,14,10,58,4.0,5,70,Urban,Manager,103642,0 +89179,Female,44,Diploma,19,17,37,15,7,7.0,5,65,Rural,Data Analyst,113072,0 +89180,Male,35,Bachelors,4,91,91,33,94,2.0,3,56,Urban,Software Engineer,22842,1 +89181,Female,27,Masters,6,80,42,9,86,5.0,1,42,Urban,HR Executive,128422,0 +89182,Male,24,High School,7,17,85,75,75,7.0,0,42,Urban,HR Executive,91780,0 +89183,Female,40,Bachelors,17,38,56,7,35,6.0,7,23,Rural,Data Analyst,110108,0 +89184,Female,36,Masters,12,48,32,79,67,5.0,5,94,Rural,ML Engineer,142557,1 +89185,Male,53,Bachelors,14,6,31,21,49,1.0,1,33,Urban,ML Engineer,100319,0 +89186,Male,40,High School,15,50,99,52,81,4.0,0,46,Urban,Data Analyst,76241,1 +89187,Male,50,Masters,13,54,16,42,94,3.0,0,39,Urban,Software Engineer,121071,0 +89188,Male,45,Bachelors,12,49,36,30,43,2.0,6,19,Urban,Software Engineer,105568,0 +89189,Male,59,Bachelors,13,75,78,14,96,8.0,1,26,Urban,Manager,61299,0 +89190,Male,40,Masters,1,65,82,76,10,1.0,3,81,Urban,ML Engineer,35025,1 +89191,Male,35,Masters,9,89,90,84,39,3.0,4,13,Semi-Urban,HR Executive,43608,1 +89192,Male,28,Bachelors,16,48,13,9,42,2.0,1,96,Semi-Urban,Software Engineer,47151,0 +89193,Male,44,Bachelors,2,61,11,0,87,7.0,7,98,Semi-Urban,Software Engineer,61199,0 +89194,Female,58,Masters,6,38,61,29,50,8.0,3,99,Semi-Urban,HR Executive,44926,0 +89195,Female,54,Bachelors,7,54,61,74,72,8.0,2,73,Rural,ML Engineer,109513,1 +89196,Female,24,Masters,9,37,79,12,25,8.0,1,42,Urban,Manager,89656,0 +89197,Male,49,Masters,9,37,80,40,38,8.0,3,79,Semi-Urban,ML Engineer,34862,1 +89198,Male,23,Masters,10,34,28,68,60,4.0,5,29,Semi-Urban,Manager,95002,0 +89199,Male,52,Diploma,12,81,63,69,63,5.0,6,33,Urban,ML Engineer,45718,1 +89200,Male,46,Masters,5,56,69,43,92,2.0,2,60,Semi-Urban,Data Analyst,80472,0 +89201,Female,57,Bachelors,0,7,27,37,5,7.0,2,59,Rural,Manager,121822,0 +89202,Male,32,Diploma,12,74,49,59,21,5.0,4,13,Rural,HR Executive,83348,0 +89203,Male,29,Masters,9,20,45,21,17,0.0,2,28,Semi-Urban,HR Executive,137879,0 +89204,Female,37,Bachelors,2,37,79,90,94,1.0,0,40,Rural,Manager,101079,1 +89205,Female,58,Bachelors,12,78,33,11,74,2.0,4,93,Rural,ML Engineer,127370,0 +89206,Male,26,Bachelors,0,89,94,91,69,1.0,4,65,Urban,Manager,34554,1 +89207,Male,44,Bachelors,6,48,12,51,74,6.0,7,37,Urban,Software Engineer,114577,0 +89208,Male,58,High School,12,55,8,32,51,7.0,7,49,Urban,Data Analyst,140067,0 +89209,Male,49,Bachelors,0,2,46,40,12,2.0,5,96,Urban,Data Analyst,53239,0 +89210,Male,37,Masters,9,9,14,44,32,0.0,4,84,Rural,Manager,101772,0 +89211,Female,23,High School,19,31,80,73,42,4.0,4,77,Urban,Manager,78771,1 +89212,Male,31,Diploma,9,85,28,53,76,3.0,7,14,Urban,Manager,137171,0 +89213,Male,43,High School,2,85,83,8,86,0.0,7,9,Urban,ML Engineer,124177,0 +89214,Female,30,Diploma,1,98,47,40,23,2.0,6,37,Urban,HR Executive,73452,0 +89215,Male,57,Masters,6,45,57,90,39,8.0,0,26,Urban,Software Engineer,34899,0 +89216,Male,25,Diploma,2,58,8,9,37,2.0,5,1,Rural,ML Engineer,111726,0 +89217,Female,37,Diploma,0,34,73,12,92,5.0,5,70,Semi-Urban,HR Executive,107823,0 +89218,Male,32,Diploma,19,48,50,28,3,3.0,7,67,Semi-Urban,Data Analyst,71034,0 +89219,Male,36,Diploma,19,25,7,51,96,8.0,6,72,Urban,HR Executive,149431,0 +89220,Male,29,High School,13,31,41,11,81,6.0,1,80,Rural,ML Engineer,62764,0 +89221,Male,33,Diploma,13,53,89,90,5,2.0,0,76,Urban,HR Executive,32535,1 +89222,Female,56,Bachelors,1,89,62,80,60,8.0,4,99,Rural,HR Executive,56991,1 +89223,Male,40,Bachelors,0,26,71,23,76,6.0,7,76,Urban,ML Engineer,52711,0 +89224,Male,40,Bachelors,15,87,94,65,20,4.0,7,20,Urban,Software Engineer,56240,1 +89225,Female,45,Masters,7,4,16,43,99,4.0,2,90,Rural,ML Engineer,96451,0 +89226,Female,52,Masters,18,49,27,13,55,8.0,0,43,Semi-Urban,ML Engineer,147149,0 +89227,Female,47,Masters,13,23,36,96,47,2.0,3,31,Semi-Urban,HR Executive,61224,0 +89228,Male,47,Bachelors,1,25,99,21,8,4.0,2,74,Urban,ML Engineer,104977,0 +89229,Female,53,Bachelors,10,41,22,49,62,9.0,0,48,Urban,Manager,129448,0 +89230,Female,31,Masters,18,86,30,2,66,2.0,4,40,Urban,ML Engineer,123261,0 +89231,Female,38,High School,11,11,33,3,52,4.0,5,91,Semi-Urban,HR Executive,58915,0 +89232,Other,25,Bachelors,16,83,44,1,71,3.0,2,19,Urban,Data Analyst,28895,0 +89233,Male,56,Bachelors,15,29,12,7,30,3.0,0,49,Semi-Urban,Data Analyst,56329,0 +89234,Female,46,Masters,8,47,92,62,70,5.0,6,9,Urban,Software Engineer,70376,0 +89235,Male,24,Bachelors,6,94,25,65,36,1.0,5,69,Rural,Data Analyst,141291,1 +89236,Male,30,Diploma,9,66,55,6,35,0.0,0,61,Urban,HR Executive,105484,0 +89237,Female,30,High School,12,16,25,43,26,6.0,5,89,Urban,ML Engineer,141795,0 +89238,Male,28,Diploma,13,74,85,54,56,0.0,7,56,Urban,ML Engineer,106306,1 +89239,Male,58,Masters,6,94,57,85,93,0.0,2,73,Semi-Urban,ML Engineer,133513,1 +89240,Male,51,High School,4,66,54,12,49,1.0,4,78,Urban,Software Engineer,56678,0 +89241,Male,51,Masters,5,75,33,40,45,8.0,5,70,Urban,ML Engineer,20292,0 +89242,Male,24,High School,11,84,11,41,77,1.0,0,97,Urban,Software Engineer,130769,0 +89243,Male,52,Masters,6,76,91,62,99,3.0,5,89,Urban,Data Analyst,36724,1 +89244,Male,22,Bachelors,11,11,66,49,69,3.0,1,81,Semi-Urban,Software Engineer,66000,0 +89245,Male,39,PhD,9,52,34,45,3,5.0,6,25,Urban,Software Engineer,104180,0 +89246,Female,54,Diploma,9,97,20,20,51,9.0,2,41,Urban,HR Executive,72808,0 +89247,Female,47,Bachelors,0,0,77,8,41,8.0,6,3,Urban,Manager,72114,0 +89248,Female,44,Bachelors,4,84,66,80,43,9.0,3,87,Semi-Urban,Software Engineer,148132,1 +89249,Female,42,Bachelors,7,12,94,35,50,3.0,4,60,Rural,HR Executive,93606,0 +89250,Male,44,Diploma,12,82,39,68,67,4.0,2,22,Urban,Software Engineer,99949,0 +89251,Female,44,Masters,6,65,48,19,8,9.0,4,22,Urban,ML Engineer,137334,0 +89252,Male,40,Diploma,16,18,23,31,78,7.0,3,87,Semi-Urban,Manager,106726,0 +89253,Male,45,Bachelors,13,18,65,12,96,4.0,5,10,Urban,HR Executive,35415,0 +89254,Male,37,Bachelors,4,48,19,45,54,9.0,7,65,Urban,Data Analyst,127356,0 +89255,Male,37,Masters,4,29,61,70,67,9.0,1,13,Rural,HR Executive,127742,0 +89256,Female,54,Masters,11,62,62,81,76,4.0,1,97,Urban,ML Engineer,129032,1 +89257,Female,27,Masters,0,9,25,52,42,7.0,4,91,Semi-Urban,Data Analyst,44762,0 +89258,Male,52,Bachelors,11,12,12,19,40,5.0,3,85,Urban,ML Engineer,148571,0 +89259,Male,51,Bachelors,9,49,43,2,73,2.0,2,6,Rural,Manager,35874,0 +89260,Male,31,High School,3,85,74,83,54,2.0,0,39,Semi-Urban,Software Engineer,22568,1 +89261,Female,23,Masters,13,81,43,4,68,1.0,5,80,Rural,Manager,21550,0 +89262,Male,27,Masters,8,57,4,53,27,8.0,5,75,Semi-Urban,Data Analyst,22478,0 +89263,Female,52,Masters,6,51,31,65,60,6.0,0,11,Rural,Data Analyst,66076,0 +89264,Male,51,Masters,0,30,25,54,94,4.0,7,93,Urban,HR Executive,41352,0 +89265,Male,55,Masters,18,49,62,31,7,4.0,5,9,Urban,Manager,25206,0 +89266,Male,36,Bachelors,15,30,96,69,48,2.0,5,57,Urban,Data Analyst,107931,1 +89267,Male,38,High School,12,60,79,17,72,7.0,2,19,Semi-Urban,Software Engineer,111589,0 +89268,Male,37,Bachelors,4,18,9,16,22,1.0,1,45,Urban,Software Engineer,99622,0 +89269,Male,37,Masters,8,50,80,9,53,4.0,3,66,Semi-Urban,Manager,33503,0 +89270,Other,45,High School,9,9,45,31,67,6.0,4,27,Semi-Urban,Data Analyst,85329,0 +89271,Male,32,Bachelors,3,33,79,9,60,4.0,1,13,Rural,HR Executive,92724,0 +89272,Female,35,Masters,15,27,19,44,64,0.0,4,76,Urban,HR Executive,50669,0 +89273,Male,28,Masters,7,43,8,41,58,2.0,6,30,Semi-Urban,Data Analyst,126839,0 +89274,Male,51,Masters,7,53,89,4,58,8.0,0,11,Semi-Urban,Software Engineer,144201,0 +89275,Male,43,Masters,19,33,54,70,59,7.0,4,30,Rural,Software Engineer,135453,0 +89276,Male,35,Masters,8,26,40,51,93,1.0,2,97,Urban,Manager,135539,0 +89277,Male,28,Masters,0,51,55,71,54,0.0,6,4,Urban,Data Analyst,56458,0 +89278,Male,31,Bachelors,8,90,93,76,83,9.0,1,28,Urban,Data Analyst,124780,1 +89279,Male,59,Bachelors,0,41,13,89,78,3.0,7,87,Urban,Manager,121746,0 +89280,Male,37,Bachelors,19,21,22,48,54,1.0,1,26,Urban,ML Engineer,95952,0 +89281,Male,23,Bachelors,15,85,3,69,49,5.0,1,13,Urban,Software Engineer,105073,0 +89282,Male,26,Masters,12,19,8,50,36,6.0,0,31,Urban,Manager,62786,0 +89283,Female,21,Bachelors,3,48,49,62,41,7.0,2,37,Semi-Urban,Software Engineer,71446,0 +89284,Male,31,Bachelors,17,27,9,57,83,9.0,4,14,Rural,HR Executive,137222,0 +89285,Male,21,Bachelors,11,97,25,34,87,5.0,2,30,Urban,Data Analyst,75348,0 +89286,Male,38,Diploma,2,88,35,7,58,2.0,7,82,Urban,Manager,36892,0 +89287,Male,23,Diploma,18,77,76,99,39,5.0,1,5,Semi-Urban,Data Analyst,117237,1 +89288,Female,35,High School,9,31,63,75,72,2.0,4,27,Urban,Manager,142049,0 +89289,Male,24,Bachelors,1,26,18,51,2,8.0,5,77,Urban,HR Executive,114193,0 +89290,Male,52,Bachelors,3,60,93,86,12,9.0,1,32,Urban,Data Analyst,34263,1 +89291,Male,28,Bachelors,19,12,37,93,97,1.0,2,93,Urban,Manager,144373,1 +89292,Male,59,PhD,15,42,99,4,61,7.0,7,80,Urban,Software Engineer,113991,0 +89293,Male,29,Bachelors,9,45,6,63,68,7.0,6,11,Rural,Software Engineer,40913,0 +89294,Female,22,Masters,9,40,38,23,71,6.0,6,57,Urban,HR Executive,83791,0 +89295,Male,28,High School,16,89,80,96,66,4.0,0,21,Urban,Manager,123276,1 +89296,Female,56,Bachelors,10,70,57,28,35,9.0,7,25,Urban,HR Executive,114104,0 +89297,Male,51,Bachelors,17,89,46,52,79,3.0,1,49,Urban,Software Engineer,121202,1 +89298,Male,27,Bachelors,16,44,15,46,53,0.0,6,34,Urban,ML Engineer,77923,0 +89299,Female,53,Masters,11,88,68,10,79,5.0,6,94,Urban,Software Engineer,62839,1 +89300,Female,33,Masters,18,83,66,9,35,4.0,6,22,Urban,HR Executive,128185,0 +89301,Male,45,Bachelors,9,22,87,68,3,5.0,3,39,Rural,Data Analyst,140742,0 +89302,Female,42,Bachelors,1,64,95,46,75,8.0,4,32,Semi-Urban,Manager,77759,0 +89303,Female,36,High School,13,53,39,10,72,4.0,4,33,Rural,Data Analyst,96722,0 +89304,Male,37,Masters,1,43,52,59,22,0.0,2,79,Semi-Urban,HR Executive,39835,0 +89305,Male,36,PhD,4,13,6,49,58,4.0,7,54,Urban,ML Engineer,22335,0 +89306,Female,43,Masters,5,63,55,75,42,4.0,6,51,Semi-Urban,Data Analyst,47594,1 +89307,Male,34,Bachelors,0,18,95,45,25,1.0,4,91,Rural,Software Engineer,79828,1 +89308,Male,38,Bachelors,6,87,47,80,67,2.0,7,1,Semi-Urban,ML Engineer,32461,0 +89309,Other,57,High School,7,26,48,9,90,2.0,1,81,Semi-Urban,ML Engineer,105736,0 +89310,Other,58,Masters,15,64,48,8,89,5.0,7,10,Semi-Urban,ML Engineer,58455,0 +89311,Male,52,Bachelors,2,16,25,6,49,6.0,0,64,Urban,Manager,21842,0 +89312,Male,41,Masters,1,67,79,52,42,1.0,2,28,Urban,HR Executive,123336,0 +89313,Female,40,Diploma,18,59,16,87,61,5.0,3,35,Rural,Data Analyst,82663,0 +89314,Male,39,Diploma,10,69,76,36,15,6.0,1,35,Urban,Data Analyst,114728,0 +89315,Male,57,Masters,11,34,88,67,23,0.0,4,39,Urban,Software Engineer,86906,0 +89316,Male,27,Diploma,13,58,64,66,32,6.0,3,26,Urban,HR Executive,145012,0 +89317,Male,46,Diploma,3,50,50,92,96,2.0,5,55,Urban,Software Engineer,68589,1 +89318,Female,25,Diploma,13,49,34,95,31,7.0,1,18,Urban,Manager,146794,0 +89319,Female,41,Masters,9,17,62,84,34,9.0,4,57,Urban,Software Engineer,120774,0 +89320,Female,25,Bachelors,14,17,40,97,95,6.0,7,18,Semi-Urban,Data Analyst,35741,0 +89321,Female,58,Bachelors,7,75,40,92,11,6.0,7,75,Semi-Urban,Manager,54277,1 +89322,Female,54,Bachelors,7,98,89,88,61,1.0,7,90,Urban,HR Executive,113544,1 +89323,Male,50,High School,11,47,51,64,7,4.0,3,1,Urban,Manager,36145,0 +89324,Male,47,Masters,16,87,63,83,82,6.0,6,84,Semi-Urban,HR Executive,143698,1 +89325,Female,28,High School,7,44,82,82,16,0.0,4,68,Semi-Urban,HR Executive,148883,1 +89326,Female,51,High School,5,77,81,90,83,8.0,4,65,Rural,ML Engineer,49832,1 +89327,Male,55,Bachelors,2,83,96,31,42,8.0,5,52,Urban,Manager,79397,1 +89328,Female,39,Diploma,6,18,50,50,93,1.0,6,61,Rural,ML Engineer,46272,0 +89329,Male,51,Bachelors,3,89,80,80,99,2.0,6,13,Urban,Data Analyst,74950,1 +89330,Male,40,Bachelors,16,68,67,3,76,4.0,5,41,Urban,Software Engineer,124657,0 +89331,Male,34,Diploma,15,45,75,16,50,4.0,7,27,Urban,ML Engineer,126789,0 +89332,Male,21,Bachelors,16,49,93,60,68,3.0,3,70,Urban,Manager,148086,1 +89333,Female,44,Diploma,10,34,63,74,85,0.0,6,98,Urban,Data Analyst,124510,1 +89334,Female,28,Bachelors,6,35,18,37,74,6.0,4,98,Urban,Software Engineer,63765,0 +89335,Male,55,Diploma,8,42,22,21,30,1.0,4,86,Semi-Urban,Software Engineer,36944,0 +89336,Male,51,Masters,11,56,58,19,12,2.0,2,59,Urban,Software Engineer,71673,0 +89337,Female,55,High School,9,16,94,32,8,7.0,7,73,Rural,Software Engineer,42782,0 +89338,Female,56,Bachelors,18,61,20,83,63,8.0,1,89,Semi-Urban,HR Executive,133748,1 +89339,Male,24,Diploma,14,91,0,91,14,0.0,4,40,Semi-Urban,HR Executive,79075,0 +89340,Male,47,High School,12,76,21,27,59,9.0,0,83,Semi-Urban,Data Analyst,25004,0 +89341,Female,48,Diploma,12,77,90,41,72,9.0,3,9,Urban,HR Executive,75580,0 +89342,Female,28,Diploma,7,18,67,2,66,3.0,0,61,Urban,Manager,61101,0 +89343,Male,22,High School,12,72,10,57,59,7.0,5,71,Urban,Software Engineer,72306,0 +89344,Female,44,High School,16,91,91,0,76,9.0,3,45,Semi-Urban,ML Engineer,126553,0 +89345,Male,47,Masters,9,47,28,63,70,6.0,6,90,Urban,Data Analyst,102666,0 +89346,Female,22,Masters,3,26,29,42,57,3.0,1,32,Semi-Urban,Manager,133987,0 +89347,Female,50,Diploma,4,7,56,36,44,1.0,5,76,Urban,HR Executive,131864,0 +89348,Male,59,Bachelors,8,7,24,99,16,0.0,5,82,Rural,Data Analyst,132926,0 +89349,Male,51,Bachelors,5,0,5,89,74,8.0,0,91,Rural,Software Engineer,131180,0 +89350,Female,51,Masters,19,73,22,53,1,6.0,5,32,Urban,ML Engineer,112368,0 +89351,Male,32,Bachelors,10,57,20,36,63,6.0,5,70,Urban,ML Engineer,98678,0 +89352,Male,59,Bachelors,1,12,73,47,90,6.0,5,40,Rural,Data Analyst,33836,0 +89353,Other,43,Bachelors,19,18,68,38,49,5.0,3,3,Urban,Software Engineer,70922,0 +89354,Male,51,Diploma,6,78,0,50,82,8.0,7,5,Urban,Data Analyst,104069,0 +89355,Male,38,Diploma,10,66,69,11,56,0.0,5,73,Urban,Software Engineer,115852,0 +89356,Male,39,High School,18,44,24,61,16,8.0,1,22,Urban,HR Executive,40308,0 +89357,Male,25,Masters,6,37,33,79,10,6.0,1,30,Urban,Data Analyst,112476,0 +89358,Male,39,Diploma,0,44,49,37,77,3.0,2,69,Urban,ML Engineer,47079,0 +89359,Female,33,High School,18,56,28,20,77,9.0,2,34,Rural,HR Executive,46745,0 +89360,Male,38,High School,12,54,49,95,40,7.0,2,42,Urban,ML Engineer,77909,1 +89361,Female,52,Diploma,18,14,95,1,4,1.0,3,34,Urban,Software Engineer,128519,0 +89362,Female,41,Masters,12,30,91,51,1,4.0,0,86,Rural,Software Engineer,102455,1 +89363,Male,36,Diploma,17,21,38,72,8,5.0,1,69,Urban,ML Engineer,47903,0 +89364,Female,24,Bachelors,13,67,33,95,54,3.0,4,22,Urban,ML Engineer,135327,0 +89365,Female,50,Bachelors,6,63,9,1,57,0.0,7,51,Urban,Data Analyst,117171,0 +89366,Male,24,Masters,8,31,29,2,93,5.0,6,91,Urban,Manager,50921,0 +89367,Female,58,Bachelors,15,18,6,12,24,9.0,1,75,Rural,Data Analyst,104780,0 +89368,Male,35,High School,12,45,65,37,57,3.0,4,79,Urban,Software Engineer,76557,0 +89369,Male,36,Diploma,3,92,17,29,35,7.0,6,33,Semi-Urban,ML Engineer,110165,0 +89370,Male,29,Diploma,16,65,35,9,83,2.0,5,51,Urban,Data Analyst,91792,0 +89371,Other,47,Diploma,0,73,72,71,90,7.0,5,80,Urban,Manager,23583,1 +89372,Female,36,Bachelors,19,79,84,18,4,6.0,4,9,Semi-Urban,HR Executive,22127,0 +89373,Male,27,Masters,18,63,5,44,91,3.0,6,56,Semi-Urban,HR Executive,67994,0 +89374,Male,29,Bachelors,11,30,81,70,57,3.0,4,83,Urban,Software Engineer,29354,1 +89375,Female,43,High School,7,77,39,71,29,5.0,7,78,Urban,Manager,132583,1 +89376,Male,21,Masters,18,20,91,90,48,9.0,7,79,Urban,ML Engineer,82536,1 +89377,Male,43,Diploma,17,0,67,65,7,4.0,3,0,Urban,Manager,57572,0 +89378,Male,42,PhD,9,6,60,74,26,1.0,1,5,Rural,Software Engineer,85774,0 +89379,Male,53,Diploma,19,40,98,76,65,7.0,6,47,Rural,Software Engineer,95367,1 +89380,Female,38,Diploma,13,14,2,7,95,1.0,4,79,Semi-Urban,HR Executive,87146,0 +89381,Male,29,Masters,12,32,11,12,19,1.0,4,9,Semi-Urban,HR Executive,106278,0 +89382,Female,26,Bachelors,18,94,70,62,50,1.0,7,36,Semi-Urban,Data Analyst,142797,1 +89383,Male,56,Masters,2,84,73,73,84,8.0,3,45,Semi-Urban,ML Engineer,93986,1 +89384,Female,54,High School,19,34,62,34,16,9.0,2,96,Semi-Urban,ML Engineer,89030,0 +89385,Female,25,Diploma,7,78,34,50,65,8.0,7,13,Urban,Data Analyst,30106,0 +89386,Female,57,Bachelors,12,1,35,43,30,8.0,7,95,Semi-Urban,Data Analyst,34871,0 +89387,Male,58,Bachelors,5,80,37,92,38,4.0,7,41,Semi-Urban,Manager,65232,1 +89388,Female,58,Bachelors,8,12,82,49,14,6.0,6,32,Rural,Software Engineer,126689,0 +89389,Male,43,High School,11,4,28,27,64,3.0,4,64,Rural,Data Analyst,52752,0 +89390,Male,38,Bachelors,10,2,96,29,22,5.0,6,69,Urban,Data Analyst,53971,0 +89391,Female,37,High School,18,92,98,45,9,3.0,6,19,Semi-Urban,ML Engineer,102471,1 +89392,Male,36,Bachelors,9,96,40,92,30,1.0,7,32,Semi-Urban,Software Engineer,68937,1 +89393,Female,42,High School,19,25,92,33,59,1.0,6,98,Urban,Data Analyst,80693,1 +89394,Male,51,High School,11,39,46,46,26,4.0,0,53,Urban,Manager,106955,0 +89395,Male,25,Diploma,1,42,46,99,50,7.0,1,71,Urban,HR Executive,35355,1 +89396,Female,44,Masters,5,22,5,9,42,2.0,0,84,Urban,Manager,107313,0 +89397,Male,31,Masters,2,74,50,46,46,2.0,0,0,Semi-Urban,Software Engineer,118799,0 +89398,Female,58,Bachelors,14,30,8,80,37,9.0,1,54,Rural,HR Executive,134990,0 +89399,Female,25,Bachelors,1,50,9,33,43,5.0,7,69,Urban,Manager,128332,0 +89400,Male,53,Diploma,5,19,37,45,42,7.0,2,77,Rural,HR Executive,48478,0 +89401,Female,44,Bachelors,6,23,37,9,51,6.0,1,58,Urban,Software Engineer,120317,0 +89402,Female,23,High School,3,36,73,14,77,4.0,3,13,Semi-Urban,Manager,37469,0 +89403,Male,30,Masters,19,41,10,71,91,8.0,3,25,Urban,HR Executive,65710,0 +89404,Male,59,Bachelors,18,72,74,64,18,5.0,6,82,Urban,HR Executive,74718,1 +89405,Female,35,High School,0,4,37,88,74,8.0,7,1,Urban,Data Analyst,77268,0 +89406,Male,30,Diploma,18,51,81,82,32,3.0,2,99,Urban,HR Executive,53927,1 +89407,Male,48,PhD,1,29,64,70,37,9.0,5,56,Rural,Data Analyst,67444,0 +89408,Female,50,Bachelors,2,92,16,62,14,0.0,6,22,Urban,HR Executive,32194,0 +89409,Female,27,Bachelors,10,28,97,66,67,2.0,5,74,Semi-Urban,Manager,140208,1 +89410,Female,37,High School,14,23,33,84,28,8.0,3,73,Urban,Software Engineer,98664,0 +89411,Male,24,Diploma,0,47,19,94,39,9.0,4,53,Rural,HR Executive,23683,0 +89412,Female,49,Masters,5,0,16,82,59,5.0,6,59,Urban,Data Analyst,81915,0 +89413,Female,30,Bachelors,4,71,99,85,3,8.0,0,97,Urban,Data Analyst,93533,1 +89414,Male,45,Bachelors,9,92,75,42,4,6.0,3,45,Urban,Software Engineer,46066,1 +89415,Male,57,Bachelors,2,24,90,12,90,1.0,3,73,Semi-Urban,Data Analyst,47744,0 +89416,Other,25,Diploma,15,28,39,74,65,3.0,3,90,Semi-Urban,ML Engineer,105406,0 +89417,Male,27,Diploma,8,86,29,2,42,0.0,0,24,Urban,ML Engineer,33267,0 +89418,Male,27,Bachelors,13,47,6,43,77,1.0,3,90,Urban,Software Engineer,46797,0 +89419,Male,22,Masters,10,90,25,34,38,7.0,6,68,Semi-Urban,Manager,132527,0 +89420,Male,57,Bachelors,13,20,66,73,41,9.0,0,1,Semi-Urban,Software Engineer,77361,0 +89421,Female,55,Bachelors,18,62,62,16,25,0.0,5,84,Rural,HR Executive,52120,0 +89422,Male,24,Diploma,15,30,76,98,94,6.0,0,22,Semi-Urban,Data Analyst,81383,0 +89423,Male,56,Diploma,4,56,2,94,42,1.0,6,12,Semi-Urban,ML Engineer,28021,0 +89424,Other,25,Bachelors,12,3,23,78,85,6.0,3,35,Urban,Software Engineer,77460,0 +89425,Male,54,Diploma,6,31,36,22,33,8.0,0,90,Semi-Urban,HR Executive,147850,0 +89426,Male,23,Bachelors,4,77,44,69,34,7.0,3,70,Urban,Data Analyst,144489,1 +89427,Female,46,Bachelors,4,28,87,54,14,4.0,4,96,Rural,Data Analyst,32598,1 +89428,Male,26,Bachelors,19,10,69,3,11,6.0,6,37,Urban,ML Engineer,73510,0 +89429,Male,27,Bachelors,0,53,57,64,78,5.0,0,47,Urban,HR Executive,90813,0 +89430,Female,31,Bachelors,18,49,55,58,83,0.0,4,37,Semi-Urban,Data Analyst,141197,0 +89431,Male,50,High School,7,14,22,85,28,1.0,5,31,Semi-Urban,ML Engineer,26583,0 +89432,Male,30,High School,1,68,16,68,31,0.0,7,14,Urban,Software Engineer,75523,0 +89433,Male,50,Diploma,12,68,95,80,83,7.0,4,97,Semi-Urban,HR Executive,134541,1 +89434,Male,28,Masters,15,44,50,65,72,6.0,0,57,Rural,Data Analyst,66644,0 +89435,Male,57,Diploma,11,83,5,74,78,3.0,6,94,Rural,HR Executive,147060,1 +89436,Female,47,Bachelors,6,98,25,30,84,3.0,2,95,Urban,Manager,135601,1 +89437,Female,56,Bachelors,0,63,78,6,17,7.0,0,61,Urban,Data Analyst,103232,0 +89438,Male,30,Masters,8,85,30,72,78,7.0,3,94,Rural,ML Engineer,20610,1 +89439,Male,23,Diploma,14,58,63,84,22,0.0,7,47,Semi-Urban,HR Executive,57349,1 +89440,Female,34,Masters,9,20,50,61,23,2.0,2,21,Semi-Urban,HR Executive,73837,0 +89441,Male,44,Diploma,13,8,55,96,44,7.0,5,95,Rural,Manager,136037,1 +89442,Male,58,High School,6,10,71,82,16,9.0,6,6,Rural,Software Engineer,105470,0 +89443,Male,21,High School,17,85,94,84,6,3.0,7,94,Urban,Data Analyst,106397,1 +89444,Female,37,Bachelors,8,89,1,23,6,3.0,3,86,Urban,ML Engineer,37852,0 +89445,Male,37,Bachelors,15,67,84,17,37,5.0,3,47,Urban,Software Engineer,124327,0 +89446,Male,54,Bachelors,19,9,19,20,49,4.0,5,57,Rural,ML Engineer,135295,0 +89447,Female,40,Bachelors,2,55,2,7,96,1.0,0,55,Urban,HR Executive,28071,0 +89448,Female,32,High School,1,54,10,24,24,4.0,4,20,Urban,ML Engineer,34087,0 +89449,Female,37,Diploma,16,84,79,89,3,2.0,0,44,Urban,Software Engineer,21142,1 +89450,Male,53,Bachelors,3,39,46,23,17,4.0,4,73,Semi-Urban,ML Engineer,136350,0 +89451,Female,51,High School,2,88,74,15,32,6.0,4,81,Urban,Software Engineer,137417,1 +89452,Other,40,Bachelors,4,44,84,53,37,5.0,7,93,Rural,Manager,38502,1 +89453,Male,42,High School,3,84,68,54,29,4.0,4,93,Urban,Software Engineer,136224,1 +89454,Female,27,Bachelors,13,55,40,52,18,5.0,5,41,Urban,Data Analyst,61535,0 +89455,Female,22,Masters,13,61,30,2,97,0.0,1,85,Rural,Data Analyst,39020,0 +89456,Other,56,Bachelors,19,2,58,8,83,2.0,3,1,Rural,Software Engineer,136397,0 +89457,Male,26,Diploma,2,21,57,51,2,6.0,1,18,Urban,HR Executive,27298,0 +89458,Female,32,Bachelors,10,80,79,56,36,9.0,2,77,Urban,ML Engineer,75617,1 +89459,Male,35,Bachelors,4,72,51,96,92,6.0,3,87,Rural,HR Executive,48465,1 +89460,Male,49,Masters,0,51,10,43,97,8.0,4,21,Urban,Data Analyst,129425,0 +89461,Male,26,Bachelors,5,49,29,30,62,3.0,0,38,Urban,Software Engineer,129108,0 +89462,Male,54,Bachelors,4,20,83,32,32,8.0,5,45,Urban,ML Engineer,124078,0 +89463,Male,55,Bachelors,12,32,7,96,38,5.0,1,57,Urban,HR Executive,96558,0 +89464,Male,56,Bachelors,0,11,10,37,83,0.0,6,8,Semi-Urban,HR Executive,142503,0 +89465,Female,31,High School,17,94,64,47,19,1.0,0,58,Urban,Software Engineer,117869,1 +89466,Male,22,Bachelors,16,67,70,32,29,0.0,5,71,Urban,HR Executive,48157,1 +89467,Female,35,Bachelors,18,17,92,78,27,0.0,1,79,Urban,HR Executive,28662,1 +89468,Male,34,Bachelors,18,23,96,76,50,9.0,5,21,Semi-Urban,Manager,142101,0 +89469,Male,30,Masters,10,58,90,49,51,9.0,4,47,Urban,Software Engineer,114452,1 +89470,Male,49,High School,13,93,66,35,40,7.0,5,36,Urban,ML Engineer,22988,0 +89471,Male,32,Diploma,3,92,89,38,38,2.0,6,85,Rural,ML Engineer,68754,1 +89472,Female,51,Bachelors,12,23,99,44,6,5.0,0,66,Urban,ML Engineer,90976,0 +89473,Male,57,Diploma,9,50,44,28,94,3.0,0,40,Rural,Manager,51442,0 +89474,Male,31,Bachelors,7,89,58,49,67,9.0,6,52,Urban,Software Engineer,113837,1 +89475,Male,27,Diploma,4,15,57,51,86,7.0,4,70,Rural,Software Engineer,24272,0 +89476,Male,39,PhD,6,49,23,82,85,2.0,3,0,Urban,Software Engineer,131389,0 +89477,Male,58,Masters,7,45,5,47,46,6.0,3,57,Urban,ML Engineer,21776,0 +89478,Male,50,Bachelors,10,44,97,10,41,0.0,4,31,Urban,Manager,140488,0 +89479,Female,57,Bachelors,12,45,32,65,77,3.0,0,16,Semi-Urban,Manager,84720,0 +89480,Female,59,Bachelors,11,11,34,88,89,7.0,1,39,Urban,Data Analyst,45983,0 +89481,Male,31,PhD,12,72,56,4,22,7.0,1,1,Semi-Urban,HR Executive,97976,0 +89482,Female,29,Masters,13,74,85,69,69,9.0,1,77,Semi-Urban,Data Analyst,112689,1 +89483,Male,50,High School,12,30,41,34,89,5.0,0,29,Semi-Urban,Data Analyst,65835,0 +89484,Male,41,Bachelors,12,9,12,72,1,3.0,5,58,Rural,HR Executive,91607,0 +89485,Male,21,Diploma,13,26,90,7,31,2.0,2,20,Urban,Data Analyst,36664,0 +89486,Male,55,High School,10,59,88,87,85,3.0,3,23,Rural,ML Engineer,50651,1 +89487,Male,50,Masters,6,61,39,37,37,7.0,5,2,Semi-Urban,ML Engineer,139810,0 +89488,Male,44,Diploma,16,2,33,4,74,0.0,2,11,Urban,Manager,113812,0 +89489,Male,42,Bachelors,1,20,53,3,2,1.0,4,4,Urban,Data Analyst,109165,0 +89490,Male,41,High School,14,90,0,82,59,4.0,5,17,Urban,HR Executive,76176,0 +89491,Female,30,Bachelors,7,91,33,69,21,6.0,2,32,Urban,Software Engineer,81118,0 +89492,Female,59,Diploma,14,6,13,14,58,3.0,3,80,Urban,ML Engineer,53917,0 +89493,Female,58,High School,17,14,98,26,9,8.0,0,78,Urban,Manager,79537,0 +89494,Male,23,Diploma,13,24,92,77,0,7.0,3,84,Urban,Data Analyst,142637,1 +89495,Female,51,Masters,11,37,30,81,12,7.0,1,5,Urban,Software Engineer,136997,0 +89496,Female,24,Bachelors,3,32,32,53,64,0.0,7,89,Urban,HR Executive,143809,0 +89497,Male,24,Diploma,2,88,30,75,71,3.0,2,54,Semi-Urban,HR Executive,141880,1 +89498,Female,33,PhD,15,42,80,60,67,9.0,4,59,Urban,HR Executive,67878,1 +89499,Other,45,Masters,16,14,22,36,38,4.0,2,81,Urban,Software Engineer,112889,0 +89500,Female,42,Bachelors,15,23,58,24,78,8.0,4,41,Urban,Manager,135965,0 +89501,Male,39,Bachelors,15,69,95,24,88,5.0,7,38,Urban,Software Engineer,131370,0 +89502,Female,47,Bachelors,11,8,92,57,84,7.0,4,53,Semi-Urban,Data Analyst,84419,0 +89503,Male,49,Bachelors,17,91,49,47,32,5.0,7,15,Rural,HR Executive,146858,0 +89504,Male,49,High School,1,26,22,78,93,5.0,1,53,Rural,Data Analyst,146175,0 +89505,Female,53,High School,5,54,75,17,23,0.0,7,66,Urban,ML Engineer,95518,0 +89506,Male,36,PhD,17,19,7,18,30,9.0,3,48,Urban,ML Engineer,143658,0 +89507,Male,54,Masters,6,99,16,90,52,4.0,6,9,Semi-Urban,Software Engineer,114500,0 +89508,Male,25,Bachelors,3,31,97,98,84,0.0,6,6,Urban,HR Executive,143885,0 +89509,Female,50,Diploma,17,99,66,68,60,8.0,1,66,Urban,ML Engineer,78157,1 +89510,Female,47,Bachelors,10,98,37,80,5,4.0,6,78,Urban,Data Analyst,88486,1 +89511,Male,52,Bachelors,12,37,22,78,53,5.0,5,10,Rural,HR Executive,110345,0 +89512,Male,47,Masters,7,89,89,31,24,4.0,0,13,Rural,ML Engineer,123196,0 +89513,Female,32,Masters,0,42,56,30,24,5.0,3,6,Semi-Urban,Manager,47671,0 +89514,Male,45,Bachelors,8,61,98,61,6,3.0,7,8,Rural,Manager,20416,0 +89515,Male,36,Diploma,14,67,73,57,93,8.0,7,99,Urban,Manager,131685,1 +89516,Other,50,Bachelors,11,94,33,2,5,1.0,6,87,Urban,Manager,107315,0 +89517,Male,34,Bachelors,2,25,14,55,60,6.0,4,29,Semi-Urban,Data Analyst,106934,0 +89518,Male,47,PhD,1,48,74,30,18,2.0,3,27,Semi-Urban,ML Engineer,45131,0 +89519,Male,32,High School,19,93,97,94,17,1.0,4,50,Rural,HR Executive,24000,1 +89520,Male,35,Masters,13,28,20,89,7,1.0,5,0,Rural,ML Engineer,113422,0 +89521,Male,27,Bachelors,11,72,40,50,24,7.0,4,42,Semi-Urban,Data Analyst,106539,0 +89522,Male,54,High School,11,87,96,27,69,8.0,4,21,Urban,Software Engineer,143893,0 +89523,Male,27,Diploma,17,57,98,85,87,3.0,6,35,Urban,Software Engineer,56338,1 +89524,Male,56,Bachelors,12,60,43,56,36,3.0,1,39,Rural,Manager,26128,0 +89525,Male,23,Bachelors,2,12,2,22,24,8.0,4,14,Semi-Urban,Data Analyst,46070,0 +89526,Male,35,Diploma,12,51,22,6,31,1.0,7,59,Urban,ML Engineer,24087,0 +89527,Female,37,Bachelors,19,21,80,51,40,3.0,5,53,Urban,Data Analyst,85206,0 +89528,Other,44,Diploma,5,56,51,20,77,4.0,7,15,Urban,Data Analyst,31361,0 +89529,Female,59,Masters,3,1,72,67,80,6.0,1,79,Rural,ML Engineer,75668,0 +89530,Other,26,Diploma,8,27,72,11,59,7.0,5,66,Semi-Urban,Manager,20134,0 +89531,Male,52,Bachelors,16,30,84,5,47,9.0,5,51,Semi-Urban,HR Executive,78018,0 +89532,Male,50,Bachelors,8,92,91,12,92,7.0,6,56,Rural,Software Engineer,115442,1 +89533,Male,51,Masters,9,91,25,65,19,1.0,3,7,Urban,Data Analyst,132991,0 +89534,Female,46,Masters,18,15,80,4,13,6.0,6,29,Urban,Software Engineer,76942,0 +89535,Male,51,Diploma,4,92,93,65,5,6.0,2,99,Semi-Urban,HR Executive,91049,1 +89536,Female,28,Bachelors,15,43,56,6,98,1.0,0,4,Rural,Data Analyst,132697,0 +89537,Female,25,Masters,9,45,55,6,94,2.0,7,65,Rural,ML Engineer,102162,0 +89538,Male,53,Diploma,0,95,14,35,70,4.0,6,24,Rural,Software Engineer,72356,0 +89539,Female,29,Bachelors,16,25,30,27,24,0.0,0,88,Urban,HR Executive,63789,0 +89540,Male,51,Bachelors,0,84,54,33,82,9.0,5,13,Semi-Urban,Data Analyst,105664,0 +89541,Male,52,High School,19,80,55,8,93,3.0,6,64,Semi-Urban,ML Engineer,86788,0 +89542,Other,47,Diploma,5,45,15,81,48,9.0,4,94,Semi-Urban,Data Analyst,43853,0 +89543,Female,37,Diploma,19,57,63,98,77,1.0,5,94,Urban,Data Analyst,98150,1 +89544,Female,52,High School,1,93,97,94,14,2.0,4,42,Urban,Data Analyst,61932,1 +89545,Other,53,Bachelors,19,56,83,0,73,1.0,0,9,Semi-Urban,HR Executive,61676,0 +89546,Female,33,PhD,13,74,27,64,91,8.0,0,83,Urban,Manager,104304,1 +89547,Male,55,High School,9,6,41,65,65,0.0,0,33,Urban,Data Analyst,40415,0 +89548,Other,25,Diploma,5,45,24,23,72,1.0,2,54,Rural,HR Executive,40536,0 +89549,Male,58,Bachelors,16,52,16,31,83,7.0,4,73,Semi-Urban,Software Engineer,49747,0 +89550,Male,39,Bachelors,17,96,34,45,95,2.0,7,54,Urban,Manager,78783,0 +89551,Female,48,Bachelors,2,62,37,59,23,6.0,4,23,Semi-Urban,Software Engineer,106496,0 +89552,Male,23,Masters,2,17,78,66,62,8.0,0,69,Urban,Data Analyst,104513,0 +89553,Female,32,Diploma,15,53,58,66,47,8.0,7,21,Urban,Software Engineer,41456,0 +89554,Male,48,Masters,18,36,12,11,71,9.0,7,9,Urban,Manager,41245,0 +89555,Male,42,Bachelors,7,9,35,88,27,8.0,1,43,Urban,Software Engineer,70360,0 +89556,Male,50,Diploma,10,58,83,93,46,2.0,5,3,Rural,Manager,57063,1 +89557,Male,45,PhD,4,71,62,47,26,4.0,1,57,Urban,ML Engineer,46280,1 +89558,Female,31,Bachelors,16,53,36,26,12,7.0,2,80,Urban,Manager,124672,0 +89559,Male,37,High School,11,16,86,21,64,3.0,1,38,Urban,HR Executive,132729,0 +89560,Female,37,Diploma,7,61,4,30,21,8.0,4,59,Urban,HR Executive,127866,0 +89561,Male,24,Bachelors,0,53,61,67,58,5.0,7,47,Semi-Urban,Data Analyst,63996,0 +89562,Female,48,Bachelors,12,21,61,81,28,6.0,5,56,Rural,Software Engineer,77355,0 +89563,Female,41,Masters,19,81,61,54,16,0.0,1,67,Urban,Data Analyst,112365,1 +89564,Male,29,Diploma,13,95,2,34,53,5.0,1,75,Urban,HR Executive,33745,0 +89565,Male,54,Bachelors,18,22,48,13,63,5.0,2,42,Urban,ML Engineer,78422,0 +89566,Male,29,Bachelors,12,99,24,38,95,2.0,2,70,Urban,Manager,82407,0 +89567,Female,49,Bachelors,0,14,20,56,26,2.0,6,95,Semi-Urban,Data Analyst,21616,0 +89568,Female,35,Bachelors,9,85,71,63,57,3.0,0,69,Rural,HR Executive,141665,1 +89569,Male,29,Bachelors,10,48,70,18,65,0.0,5,10,Urban,ML Engineer,124814,0 +89570,Other,58,Diploma,7,5,76,5,10,4.0,0,54,Semi-Urban,HR Executive,45010,0 +89571,Male,30,Bachelors,17,14,79,32,67,3.0,2,90,Urban,Data Analyst,97697,0 +89572,Male,44,Masters,7,87,97,99,53,2.0,3,37,Urban,HR Executive,124057,1 +89573,Male,49,Bachelors,5,7,7,30,27,4.0,5,70,Urban,Data Analyst,25686,0 +89574,Male,56,PhD,18,19,36,32,65,5.0,1,83,Rural,ML Engineer,108103,0 +89575,Female,53,Masters,14,14,54,40,26,9.0,4,42,Rural,Software Engineer,144309,0 +89576,Male,23,Bachelors,7,97,78,65,13,9.0,3,55,Semi-Urban,Software Engineer,118644,1 +89577,Male,33,Bachelors,10,23,50,24,52,9.0,6,39,Urban,Manager,81985,0 +89578,Other,41,Bachelors,11,34,88,2,4,1.0,1,38,Urban,ML Engineer,26406,0 +89579,Male,33,High School,10,5,42,91,49,5.0,6,31,Urban,HR Executive,97274,0 +89580,Male,44,Masters,15,1,44,2,81,0.0,1,22,Urban,HR Executive,41468,0 +89581,Female,42,High School,4,22,31,70,17,5.0,7,13,Urban,HR Executive,37437,0 +89582,Female,42,High School,0,42,35,16,95,8.0,0,98,Urban,ML Engineer,124852,0 +89583,Female,37,Bachelors,17,62,45,30,56,9.0,6,6,Urban,Software Engineer,127333,0 +89584,Male,41,Bachelors,5,60,42,19,98,9.0,4,38,Semi-Urban,ML Engineer,80724,0 +89585,Female,54,Masters,12,8,20,63,7,1.0,1,23,Urban,Manager,140591,0 +89586,Female,48,High School,13,89,99,22,47,4.0,2,75,Urban,Data Analyst,145453,1 +89587,Male,43,Masters,2,6,76,0,55,7.0,2,11,Rural,ML Engineer,74587,0 +89588,Female,25,Masters,7,48,57,97,69,0.0,4,86,Urban,Software Engineer,139214,1 +89589,Male,40,PhD,1,21,20,77,91,9.0,5,98,Rural,ML Engineer,51144,0 +89590,Male,36,Bachelors,8,62,58,52,65,1.0,4,99,Rural,Data Analyst,140178,1 +89591,Male,28,Diploma,5,74,39,40,8,3.0,3,31,Urban,Manager,72722,0 +89592,Female,53,PhD,1,8,0,72,20,8.0,0,63,Semi-Urban,Data Analyst,47421,0 +89593,Male,30,High School,10,94,66,36,56,0.0,6,38,Urban,ML Engineer,67953,0 +89594,Male,21,Masters,3,21,78,70,15,0.0,6,69,Rural,Software Engineer,149595,1 +89595,Male,32,High School,11,38,27,45,72,9.0,1,97,Urban,HR Executive,30870,0 +89596,Female,27,Diploma,16,39,6,0,0,8.0,7,34,Urban,ML Engineer,25602,0 +89597,Male,55,Masters,0,25,42,45,53,9.0,3,59,Urban,Software Engineer,61926,0 +89598,Male,29,High School,7,95,22,36,54,9.0,5,25,Rural,ML Engineer,54148,0 +89599,Male,42,Diploma,19,94,47,2,92,4.0,5,34,Rural,Data Analyst,141383,0 +89600,Female,30,Masters,15,5,73,30,97,5.0,4,2,Urban,ML Engineer,69853,0 +89601,Male,25,Bachelors,4,93,96,73,23,9.0,5,70,Semi-Urban,Software Engineer,44886,1 +89602,Male,40,Bachelors,8,47,70,54,83,9.0,4,76,Urban,Data Analyst,133883,1 +89603,Male,49,Diploma,9,11,50,75,41,5.0,4,65,Urban,HR Executive,82415,0 +89604,Male,47,High School,2,64,8,11,32,1.0,1,44,Rural,Manager,117194,0 +89605,Female,22,Diploma,3,24,72,64,89,3.0,4,67,Urban,Data Analyst,50794,0 +89606,Female,27,High School,16,6,52,36,0,8.0,3,96,Urban,ML Engineer,46081,0 +89607,Male,36,Masters,9,66,49,62,49,2.0,2,63,Urban,Manager,86070,1 +89608,Male,57,Masters,7,93,10,5,22,7.0,3,52,Urban,ML Engineer,40487,0 +89609,Male,58,High School,18,31,14,90,84,5.0,6,65,Urban,Manager,98241,0 +89610,Female,56,Bachelors,0,69,59,5,37,2.0,6,80,Urban,Data Analyst,118529,0 +89611,Female,28,High School,5,84,16,52,36,1.0,4,9,Urban,Software Engineer,101269,0 +89612,Female,24,Bachelors,11,40,53,59,44,6.0,4,15,Urban,Data Analyst,141069,0 +89613,Male,27,Masters,18,65,65,60,37,3.0,3,71,Urban,ML Engineer,106410,1 +89614,Male,31,Bachelors,3,33,10,22,27,7.0,3,93,Urban,Data Analyst,77876,0 +89615,Male,57,High School,19,5,67,21,41,8.0,1,53,Urban,ML Engineer,105881,0 +89616,Other,22,Masters,10,95,38,81,42,6.0,5,83,Urban,ML Engineer,69625,1 +89617,Male,35,Bachelors,1,30,13,81,69,5.0,1,75,Semi-Urban,Software Engineer,108996,0 +89618,Male,37,Bachelors,15,14,13,56,79,3.0,6,19,Semi-Urban,ML Engineer,36634,0 +89619,Female,27,Diploma,8,77,97,44,35,6.0,0,94,Rural,Software Engineer,67252,1 +89620,Male,35,Bachelors,8,6,40,66,30,4.0,6,34,Urban,Manager,61232,0 +89621,Male,59,Bachelors,14,13,79,33,37,2.0,7,10,Urban,Manager,65472,0 +89622,Female,35,Bachelors,1,68,67,42,9,4.0,6,82,Semi-Urban,ML Engineer,122229,1 +89623,Male,47,Bachelors,5,13,37,55,68,8.0,6,30,Urban,HR Executive,77380,0 +89624,Male,32,High School,19,79,26,95,72,7.0,0,47,Rural,ML Engineer,111093,1 +89625,Male,38,Bachelors,3,26,11,9,17,7.0,6,11,Urban,HR Executive,69404,0 +89626,Male,51,Masters,18,39,1,26,0,7.0,2,72,Urban,Software Engineer,118621,0 +89627,Male,47,Diploma,19,40,0,85,66,6.0,4,15,Urban,ML Engineer,72429,0 +89628,Female,21,Masters,8,91,50,70,52,0.0,6,92,Urban,HR Executive,55151,1 +89629,Male,25,Diploma,17,4,71,89,25,8.0,6,24,Urban,Data Analyst,142278,0 +89630,Female,33,Bachelors,1,4,84,31,96,8.0,6,63,Semi-Urban,Software Engineer,95084,0 +89631,Female,37,Diploma,12,80,86,60,42,8.0,3,7,Rural,HR Executive,71228,0 +89632,Male,28,Bachelors,1,99,38,90,19,9.0,7,91,Semi-Urban,Manager,45373,1 +89633,Male,25,Masters,3,20,48,14,54,6.0,6,8,Urban,ML Engineer,47246,0 +89634,Female,49,Bachelors,8,83,87,11,39,8.0,1,48,Urban,Software Engineer,99925,0 +89635,Female,32,Diploma,16,68,62,92,47,6.0,6,22,Rural,Data Analyst,20526,1 +89636,Female,59,High School,11,98,72,74,68,4.0,3,43,Rural,Manager,41692,1 +89637,Male,26,Diploma,19,35,30,46,93,0.0,4,30,Urban,ML Engineer,142276,0 +89638,Male,26,High School,5,34,1,18,52,2.0,1,49,Semi-Urban,HR Executive,97938,0 +89639,Female,46,Bachelors,16,10,31,8,62,5.0,2,2,Urban,ML Engineer,94406,0 +89640,Male,40,Diploma,0,57,29,57,23,4.0,6,10,Semi-Urban,Manager,119941,0 +89641,Female,39,Masters,9,23,2,6,64,1.0,3,3,Urban,Manager,99225,0 +89642,Male,36,Diploma,9,97,56,32,56,4.0,2,25,Urban,Software Engineer,88022,0 +89643,Female,45,Bachelors,11,62,28,20,77,4.0,2,49,Semi-Urban,Data Analyst,54392,0 +89644,Female,39,Bachelors,0,48,8,30,97,7.0,7,31,Urban,HR Executive,52133,0 +89645,Male,57,Masters,8,83,37,87,22,3.0,6,20,Rural,Software Engineer,114090,0 +89646,Male,35,Masters,10,33,32,92,80,4.0,6,48,Semi-Urban,ML Engineer,23475,0 +89647,Female,34,High School,10,43,26,78,38,5.0,5,11,Semi-Urban,HR Executive,98797,0 +89648,Male,24,High School,9,85,53,13,32,8.0,7,69,Urban,HR Executive,138932,0 +89649,Male,30,Bachelors,1,54,7,79,52,7.0,5,29,Urban,Software Engineer,44501,0 +89650,Female,33,Bachelors,2,8,58,77,37,9.0,1,11,Urban,Manager,28184,0 +89651,Female,53,Masters,11,56,18,72,92,8.0,0,13,Urban,HR Executive,138094,0 +89652,Male,30,Bachelors,5,50,74,10,41,2.0,1,5,Urban,Software Engineer,126039,0 +89653,Female,52,Masters,19,63,1,72,57,9.0,2,79,Urban,ML Engineer,149766,0 +89654,Other,24,Diploma,14,39,44,55,48,4.0,1,82,Urban,Software Engineer,28320,0 +89655,Male,33,Masters,2,17,10,66,51,7.0,6,29,Rural,Data Analyst,105957,0 +89656,Male,57,Diploma,13,70,87,61,70,8.0,3,51,Urban,ML Engineer,75155,1 +89657,Female,40,Bachelors,16,34,77,7,28,8.0,2,51,Urban,Manager,86557,0 +89658,Male,55,Bachelors,16,93,72,7,11,4.0,5,81,Rural,Software Engineer,81043,1 +89659,Male,33,Bachelors,1,84,69,75,56,5.0,1,26,Urban,Software Engineer,91399,1 +89660,Male,58,Bachelors,1,53,33,85,19,8.0,7,59,Semi-Urban,Data Analyst,143681,0 +89661,Female,48,Bachelors,5,55,6,73,10,8.0,5,96,Rural,Data Analyst,132673,0 +89662,Male,26,Diploma,14,93,21,14,41,2.0,1,57,Urban,Software Engineer,70141,0 +89663,Male,26,Diploma,19,17,55,96,55,7.0,2,78,Semi-Urban,ML Engineer,96230,1 +89664,Male,40,High School,17,64,4,45,98,1.0,3,6,Urban,Manager,89783,0 +89665,Male,47,Bachelors,15,37,8,74,51,6.0,0,12,Urban,Software Engineer,144948,0 +89666,Male,29,PhD,9,89,55,33,50,8.0,4,6,Urban,Software Engineer,93469,0 +89667,Female,28,Diploma,9,93,14,37,79,6.0,5,71,Urban,Data Analyst,140821,0 +89668,Female,34,Bachelors,1,62,26,86,85,6.0,3,70,Semi-Urban,Manager,49832,1 +89669,Male,33,High School,9,67,7,15,77,7.0,4,14,Urban,Data Analyst,20377,0 +89670,Male,27,Masters,0,29,15,23,71,6.0,5,91,Urban,Software Engineer,81704,0 +89671,Male,56,Masters,16,10,24,43,45,7.0,6,94,Rural,Software Engineer,79366,0 +89672,Male,55,Masters,19,41,66,5,83,4.0,6,78,Urban,Software Engineer,118197,0 +89673,Female,25,Bachelors,19,77,22,27,39,0.0,6,98,Urban,Software Engineer,43139,0 +89674,Female,51,Bachelors,17,98,31,6,50,5.0,1,62,Urban,HR Executive,55430,0 +89675,Female,31,Bachelors,18,42,98,23,28,1.0,7,52,Urban,Data Analyst,75122,0 +89676,Male,52,Bachelors,3,29,10,12,81,0.0,6,99,Semi-Urban,ML Engineer,61391,0 +89677,Male,32,Bachelors,0,13,52,33,62,2.0,1,2,Semi-Urban,Manager,39192,0 +89678,Female,21,Masters,5,70,7,73,28,9.0,0,50,Rural,ML Engineer,52553,0 +89679,Female,38,Masters,15,55,19,57,86,2.0,0,25,Semi-Urban,ML Engineer,56451,0 +89680,Male,58,Bachelors,13,14,45,42,13,5.0,2,70,Rural,Manager,149550,0 +89681,Female,28,Bachelors,14,14,31,48,14,5.0,7,14,Urban,Data Analyst,128652,0 +89682,Female,38,Bachelors,9,3,31,73,56,4.0,5,2,Rural,HR Executive,146541,0 +89683,Female,35,High School,4,48,71,91,67,3.0,2,21,Semi-Urban,HR Executive,124304,0 +89684,Male,44,Bachelors,12,83,68,2,53,8.0,0,75,Rural,ML Engineer,130021,0 +89685,Other,52,Bachelors,4,48,2,36,50,2.0,1,8,Urban,HR Executive,94116,0 +89686,Female,27,High School,2,65,90,88,66,6.0,1,90,Urban,Manager,23451,1 +89687,Female,28,Diploma,3,36,67,92,39,1.0,0,28,Urban,HR Executive,144888,0 +89688,Other,30,High School,14,92,60,47,93,8.0,1,32,Semi-Urban,Data Analyst,41294,0 +89689,Female,42,Bachelors,8,70,98,51,12,6.0,5,2,Urban,Software Engineer,36848,0 +89690,Male,59,Bachelors,16,44,32,26,11,5.0,4,80,Urban,Manager,61199,0 +89691,Female,24,Bachelors,10,46,96,3,61,7.0,7,13,Urban,ML Engineer,110684,0 +89692,Male,49,PhD,2,72,4,14,88,6.0,4,40,Urban,HR Executive,107984,0 +89693,Female,59,High School,10,1,70,74,76,4.0,3,60,Urban,ML Engineer,64292,0 +89694,Male,47,Masters,11,23,24,68,90,4.0,2,2,Urban,Software Engineer,120580,0 +89695,Male,23,Bachelors,5,13,60,36,87,3.0,6,19,Semi-Urban,Software Engineer,118950,0 +89696,Male,41,Diploma,2,68,66,38,17,2.0,1,55,Rural,ML Engineer,21315,0 +89697,Female,27,Bachelors,18,80,15,65,11,6.0,3,43,Urban,Data Analyst,95805,0 +89698,Male,29,High School,5,29,98,31,69,3.0,1,13,Semi-Urban,HR Executive,144699,0 +89699,Male,27,Bachelors,8,59,73,6,10,9.0,2,16,Urban,ML Engineer,64605,0 +89700,Male,34,Diploma,10,39,8,25,36,7.0,4,9,Urban,Data Analyst,68042,0 +89701,Male,36,Diploma,9,70,24,35,78,6.0,0,41,Urban,Manager,78199,0 +89702,Female,59,Masters,19,56,18,23,62,8.0,5,16,Rural,Manager,108169,0 +89703,Female,55,Diploma,0,57,55,94,18,5.0,3,60,Rural,Data Analyst,90301,1 +89704,Female,35,Bachelors,12,25,47,27,60,3.0,5,37,Semi-Urban,ML Engineer,74344,0 +89705,Male,23,Masters,7,75,76,5,47,7.0,4,41,Urban,Manager,85691,0 +89706,Male,43,Diploma,13,43,53,96,12,6.0,6,42,Urban,Data Analyst,61930,0 +89707,Female,22,Diploma,13,2,70,59,36,6.0,0,83,Semi-Urban,Manager,99260,0 +89708,Male,53,High School,15,39,36,65,93,4.0,4,7,Semi-Urban,HR Executive,98957,0 +89709,Female,39,Bachelors,1,94,70,0,53,5.0,4,77,Semi-Urban,ML Engineer,31276,1 +89710,Female,26,PhD,14,50,34,73,38,8.0,6,48,Urban,Manager,128318,0 +89711,Male,29,Masters,13,72,99,10,59,2.0,6,79,Urban,Manager,41607,1 +89712,Female,38,High School,4,76,34,67,6,6.0,1,11,Urban,HR Executive,92471,0 +89713,Male,33,Bachelors,2,98,22,35,13,3.0,0,99,Urban,Data Analyst,136774,1 +89714,Female,23,Bachelors,16,98,45,45,16,8.0,0,77,Semi-Urban,Data Analyst,100448,1 +89715,Female,48,Bachelors,2,90,64,53,50,7.0,4,40,Urban,Manager,92637,1 +89716,Male,50,Diploma,11,15,42,86,69,4.0,4,50,Semi-Urban,Software Engineer,129039,0 +89717,Male,33,Bachelors,0,89,65,98,92,2.0,2,45,Semi-Urban,HR Executive,119916,1 +89718,Male,48,Masters,8,75,83,3,18,5.0,2,68,Semi-Urban,ML Engineer,39111,0 +89719,Male,50,Diploma,11,95,62,98,47,9.0,1,96,Semi-Urban,Software Engineer,42158,1 +89720,Male,21,PhD,9,58,0,13,86,0.0,7,79,Rural,HR Executive,128037,0 +89721,Male,39,Masters,16,91,91,41,79,2.0,1,88,Urban,Software Engineer,110078,1 +89722,Male,56,High School,3,34,43,25,58,5.0,5,20,Urban,Software Engineer,99168,0 +89723,Female,23,Diploma,8,33,59,99,35,0.0,2,18,Urban,Data Analyst,87359,0 +89724,Male,49,Masters,18,88,57,42,12,7.0,5,14,Urban,Manager,125938,0 +89725,Female,40,Masters,5,1,71,66,20,1.0,6,13,Semi-Urban,Manager,128136,0 +89726,Male,36,Bachelors,16,95,67,41,40,2.0,5,37,Urban,Software Engineer,72713,1 +89727,Male,22,High School,19,1,49,14,52,6.0,2,48,Urban,Software Engineer,111295,0 +89728,Other,40,Bachelors,12,86,45,33,81,0.0,7,84,Urban,HR Executive,80445,1 +89729,Other,43,Bachelors,13,77,38,37,32,7.0,7,12,Rural,Manager,29392,0 +89730,Male,56,Masters,4,72,36,53,16,2.0,5,3,Urban,Software Engineer,54096,0 +89731,Male,54,Diploma,13,88,84,28,17,8.0,2,13,Semi-Urban,HR Executive,84177,0 +89732,Male,21,Masters,18,2,60,0,56,1.0,0,28,Rural,ML Engineer,112990,0 +89733,Male,59,High School,5,87,22,34,23,4.0,3,25,Rural,Data Analyst,110822,0 +89734,Male,57,Masters,12,19,72,43,60,5.0,6,67,Rural,Software Engineer,81370,0 +89735,Male,41,Diploma,11,95,38,6,62,9.0,7,29,Urban,ML Engineer,94418,0 +89736,Female,28,High School,6,20,82,8,94,3.0,1,59,Semi-Urban,ML Engineer,123732,0 +89737,Female,27,High School,13,73,83,18,31,7.0,5,64,Urban,Software Engineer,142728,0 +89738,Other,31,Bachelors,3,62,51,87,24,2.0,1,83,Urban,Data Analyst,91914,1 +89739,Male,27,Bachelors,14,15,48,3,94,2.0,5,50,Urban,Manager,37360,0 +89740,Male,27,Bachelors,16,63,12,62,48,4.0,2,20,Rural,Manager,132868,0 +89741,Male,35,Masters,10,45,91,24,82,6.0,6,29,Urban,Software Engineer,113610,0 +89742,Female,58,High School,1,58,46,44,43,4.0,3,62,Urban,Manager,97929,0 +89743,Male,56,Diploma,4,54,52,81,49,7.0,3,76,Rural,Software Engineer,81940,1 +89744,Female,58,Bachelors,9,73,25,82,57,7.0,2,78,Urban,Software Engineer,42045,1 +89745,Male,30,Masters,7,38,50,43,37,3.0,6,35,Semi-Urban,Software Engineer,97758,0 +89746,Male,30,Masters,3,96,10,29,64,1.0,1,22,Urban,HR Executive,24683,0 +89747,Male,30,Masters,5,76,81,55,2,9.0,2,48,Semi-Urban,ML Engineer,127290,1 +89748,Female,55,Bachelors,12,67,13,2,36,3.0,4,28,Urban,ML Engineer,94468,0 +89749,Male,32,Bachelors,2,76,87,1,84,0.0,5,44,Semi-Urban,HR Executive,31735,0 +89750,Male,35,Masters,7,67,97,74,83,7.0,7,95,Semi-Urban,Manager,137498,1 +89751,Female,53,Bachelors,4,29,76,5,25,4.0,7,92,Semi-Urban,Software Engineer,49796,0 +89752,Female,31,High School,7,45,20,22,34,9.0,4,93,Urban,Manager,84731,0 +89753,Male,51,Bachelors,11,82,45,89,28,9.0,5,16,Urban,Manager,64190,0 +89754,Male,54,Bachelors,10,89,69,74,42,7.0,7,71,Urban,Data Analyst,111422,1 +89755,Female,25,Bachelors,7,79,71,99,6,5.0,7,94,Semi-Urban,Data Analyst,67388,1 +89756,Female,44,Bachelors,18,19,48,89,80,0.0,7,24,Rural,Software Engineer,136047,0 +89757,Female,26,Bachelors,1,35,1,82,48,4.0,6,77,Urban,HR Executive,54068,0 +89758,Female,28,Bachelors,2,74,49,71,0,7.0,7,64,Urban,Manager,148071,1 +89759,Male,37,Masters,8,24,77,20,20,5.0,3,33,Semi-Urban,Manager,37211,0 +89760,Male,21,Bachelors,3,53,39,14,42,1.0,1,6,Urban,HR Executive,32772,0 +89761,Female,42,Diploma,7,28,20,36,77,6.0,5,44,Urban,Manager,134511,0 +89762,Female,43,Bachelors,18,78,43,80,23,0.0,1,40,Rural,Manager,101957,1 +89763,Male,30,High School,6,43,30,98,92,4.0,1,93,Urban,Manager,102066,1 +89764,Female,37,Bachelors,10,65,77,66,65,7.0,3,47,Semi-Urban,ML Engineer,61643,1 +89765,Male,55,Bachelors,3,41,86,18,74,4.0,5,61,Urban,ML Engineer,58699,0 +89766,Male,37,Bachelors,19,19,74,23,6,3.0,2,99,Semi-Urban,Software Engineer,133706,0 +89767,Male,31,High School,1,65,38,71,15,7.0,5,54,Semi-Urban,Software Engineer,32555,0 +89768,Male,53,Bachelors,19,59,5,51,37,4.0,0,26,Urban,ML Engineer,117566,0 +89769,Female,55,High School,15,3,75,49,51,8.0,0,66,Urban,Data Analyst,128791,0 +89770,Female,22,High School,4,25,22,59,61,0.0,2,4,Urban,HR Executive,106226,0 +89771,Female,56,Masters,11,45,40,72,24,2.0,2,0,Urban,HR Executive,66221,0 +89772,Male,30,Masters,6,4,89,58,40,2.0,4,39,Urban,ML Engineer,113207,0 +89773,Male,35,High School,1,3,99,85,70,9.0,6,98,Semi-Urban,HR Executive,100962,1 +89774,Female,51,Masters,1,27,13,9,19,2.0,4,96,Semi-Urban,Data Analyst,130240,0 +89775,Male,27,Bachelors,10,81,13,15,94,9.0,7,1,Urban,Data Analyst,27449,0 +89776,Male,52,Bachelors,1,28,68,7,23,6.0,5,66,Urban,Data Analyst,115623,0 +89777,Female,45,Diploma,10,44,25,72,6,5.0,4,35,Urban,HR Executive,42772,0 +89778,Male,50,Bachelors,7,76,7,18,7,4.0,7,20,Semi-Urban,Data Analyst,64016,0 +89779,Male,31,Diploma,10,59,75,24,90,0.0,4,51,Semi-Urban,Software Engineer,107780,0 +89780,Male,25,Bachelors,2,80,34,43,41,5.0,6,30,Rural,HR Executive,135588,0 +89781,Female,59,Diploma,6,22,71,53,32,9.0,5,78,Semi-Urban,HR Executive,120245,0 +89782,Female,42,Diploma,3,11,3,53,8,1.0,5,30,Urban,HR Executive,47474,0 +89783,Female,29,Bachelors,9,13,70,72,65,9.0,2,42,Rural,ML Engineer,135818,0 +89784,Male,23,Masters,18,19,84,41,11,5.0,7,80,Urban,Manager,67554,0 +89785,Male,29,Bachelors,6,89,64,49,96,2.0,7,62,Semi-Urban,ML Engineer,73633,1 +89786,Male,41,High School,6,24,39,3,94,7.0,4,89,Urban,ML Engineer,88501,0 +89787,Male,24,Masters,12,99,21,53,27,6.0,1,64,Urban,ML Engineer,69532,1 +89788,Male,54,Bachelors,3,86,68,16,40,7.0,7,76,Urban,Data Analyst,59918,1 +89789,Male,48,Diploma,4,49,40,66,12,2.0,5,62,Urban,HR Executive,79414,0 +89790,Male,48,Masters,7,87,35,35,8,4.0,7,19,Rural,Manager,45234,0 +89791,Female,49,PhD,5,16,13,58,69,6.0,5,67,Urban,Data Analyst,34494,0 +89792,Female,52,Bachelors,19,32,31,14,87,1.0,4,26,Rural,HR Executive,82029,0 +89793,Male,41,Bachelors,14,4,19,39,79,6.0,2,70,Urban,Software Engineer,37084,0 +89794,Female,34,Bachelors,10,28,34,79,93,4.0,6,16,Rural,ML Engineer,42782,0 +89795,Male,50,Bachelors,10,72,66,49,71,9.0,4,88,Rural,Data Analyst,28321,1 +89796,Other,23,High School,10,90,36,40,70,4.0,5,94,Urban,Manager,51752,1 +89797,Male,32,Masters,13,43,12,89,95,0.0,4,18,Semi-Urban,Data Analyst,47258,0 +89798,Male,54,Diploma,18,34,63,65,74,3.0,1,53,Rural,HR Executive,91054,0 +89799,Male,22,Bachelors,3,12,65,81,20,2.0,6,91,Urban,Manager,141947,1 +89800,Male,26,Diploma,11,82,3,5,64,1.0,7,70,Urban,Manager,66878,0 +89801,Male,57,Bachelors,0,40,95,30,27,9.0,6,56,Rural,Manager,119752,0 +89802,Female,51,PhD,2,63,93,61,1,0.0,7,90,Rural,Data Analyst,63146,1 +89803,Male,55,High School,14,28,19,66,81,7.0,4,71,Urban,Data Analyst,77765,0 +89804,Male,25,Diploma,17,90,74,40,44,2.0,1,91,Urban,Data Analyst,57384,1 +89805,Male,39,Bachelors,7,66,8,6,22,7.0,3,79,Semi-Urban,Data Analyst,82556,0 +89806,Male,28,Bachelors,17,32,56,9,70,3.0,0,83,Urban,HR Executive,36295,0 +89807,Male,52,Bachelors,19,57,18,38,22,7.0,0,28,Rural,Data Analyst,30011,0 +89808,Male,29,PhD,2,87,54,54,9,3.0,0,66,Urban,Software Engineer,20237,1 +89809,Female,41,High School,12,57,57,94,25,1.0,0,41,Semi-Urban,HR Executive,27408,1 +89810,Female,54,Diploma,10,46,64,56,56,7.0,2,9,Semi-Urban,Data Analyst,58170,0 +89811,Female,34,Diploma,11,16,38,58,0,9.0,4,91,Urban,Data Analyst,98063,0 +89812,Male,54,Masters,8,16,93,62,16,2.0,5,61,Rural,Data Analyst,149695,0 +89813,Female,31,Bachelors,17,17,88,56,27,5.0,2,32,Urban,Software Engineer,133825,0 +89814,Female,51,PhD,17,20,9,13,87,2.0,2,62,Urban,Data Analyst,48572,0 +89815,Male,55,High School,4,55,77,26,60,9.0,3,46,Urban,HR Executive,59761,0 +89816,Female,59,Bachelors,12,82,55,40,81,8.0,5,7,Urban,Manager,140755,0 +89817,Male,52,Bachelors,17,89,2,44,88,5.0,0,28,Rural,Software Engineer,132348,0 +89818,Male,29,Masters,17,29,70,13,25,4.0,3,53,Semi-Urban,Software Engineer,22077,0 +89819,Male,53,Diploma,3,17,28,7,87,8.0,0,57,Urban,Software Engineer,81249,0 +89820,Male,27,Diploma,0,26,43,59,27,4.0,1,65,Rural,Manager,143940,0 +89821,Female,30,Bachelors,5,39,10,26,19,0.0,4,65,Urban,Manager,100226,0 +89822,Male,52,Bachelors,13,0,28,21,95,1.0,3,28,Urban,Data Analyst,114158,0 +89823,Male,32,High School,1,99,79,30,88,8.0,4,32,Urban,Software Engineer,144121,1 +89824,Male,54,Masters,18,88,73,27,85,4.0,7,89,Urban,HR Executive,50582,1 +89825,Male,41,Bachelors,11,83,40,1,60,2.0,3,94,Urban,HR Executive,128395,0 +89826,Male,46,Bachelors,1,67,98,85,56,0.0,6,66,Urban,Manager,103543,1 +89827,Female,45,Bachelors,2,49,0,97,81,3.0,4,34,Urban,ML Engineer,131207,0 +89828,Female,22,Bachelors,4,35,63,39,47,2.0,0,83,Urban,Data Analyst,114908,0 +89829,Male,39,Diploma,0,15,22,7,18,5.0,3,30,Rural,ML Engineer,57520,0 +89830,Male,31,Diploma,5,62,59,62,42,8.0,4,76,Rural,Manager,22721,1 +89831,Male,45,Bachelors,3,84,59,98,5,7.0,0,73,Rural,HR Executive,81022,1 +89832,Male,38,Bachelors,6,97,83,80,88,8.0,2,12,Urban,Manager,29319,1 +89833,Male,57,Diploma,8,16,58,82,2,9.0,5,27,Urban,Software Engineer,126759,0 +89834,Male,59,Bachelors,7,70,29,66,26,1.0,7,73,Semi-Urban,Manager,128061,1 +89835,Female,24,Bachelors,11,7,21,26,5,5.0,6,51,Rural,Software Engineer,123049,0 +89836,Male,43,Bachelors,19,77,84,7,72,3.0,0,22,Semi-Urban,Data Analyst,147848,0 +89837,Female,55,Diploma,9,74,24,23,92,9.0,0,61,Semi-Urban,ML Engineer,130090,0 +89838,Male,34,Masters,12,89,48,11,98,4.0,5,38,Urban,Data Analyst,41290,0 +89839,Male,26,Bachelors,0,54,38,73,56,4.0,5,71,Rural,Software Engineer,91108,1 +89840,Other,56,High School,19,28,80,31,78,2.0,2,95,Urban,Data Analyst,88508,0 +89841,Male,37,High School,18,5,44,7,15,0.0,7,53,Urban,Software Engineer,142003,0 +89842,Male,51,Masters,16,83,28,4,5,9.0,2,86,Urban,ML Engineer,85095,0 +89843,Male,34,PhD,10,88,82,53,73,6.0,6,10,Rural,Software Engineer,122938,0 +89844,Male,37,Bachelors,19,0,71,13,7,2.0,7,23,Urban,HR Executive,112980,0 +89845,Other,41,Bachelors,18,7,44,51,25,1.0,1,86,Semi-Urban,Data Analyst,100454,0 +89846,Male,44,Bachelors,0,94,79,29,97,3.0,4,89,Rural,Software Engineer,52620,1 +89847,Female,37,Bachelors,17,19,45,77,43,1.0,5,49,Rural,Software Engineer,39223,0 +89848,Female,29,Bachelors,8,36,37,77,69,5.0,1,80,Rural,Data Analyst,124488,0 +89849,Male,32,Diploma,12,57,67,55,24,3.0,3,11,Rural,Software Engineer,47574,0 +89850,Female,44,Diploma,13,77,71,84,21,7.0,1,71,Semi-Urban,Data Analyst,42750,1 +89851,Female,34,High School,3,62,45,86,45,1.0,3,91,Urban,ML Engineer,118379,1 +89852,Male,53,Masters,6,47,51,68,94,6.0,1,15,Rural,ML Engineer,87470,0 +89853,Female,31,Masters,4,52,3,42,20,2.0,5,5,Urban,HR Executive,110896,0 +89854,Male,36,High School,18,20,34,3,60,9.0,1,32,Urban,Data Analyst,65488,0 +89855,Male,51,Bachelors,17,69,86,63,77,6.0,2,3,Urban,HR Executive,29587,0 +89856,Other,34,Masters,17,34,76,2,15,4.0,7,65,Semi-Urban,Manager,74188,0 +89857,Male,25,Bachelors,10,84,12,36,49,7.0,2,16,Urban,ML Engineer,134512,0 +89858,Male,26,High School,17,13,92,52,38,0.0,5,9,Urban,Manager,67442,0 +89859,Male,21,Bachelors,15,79,99,94,59,5.0,1,4,Rural,Data Analyst,119579,1 +89860,Female,37,High School,6,26,8,59,26,3.0,5,14,Semi-Urban,HR Executive,75991,0 +89861,Male,48,Masters,16,73,36,70,80,0.0,6,39,Semi-Urban,Software Engineer,133417,0 +89862,Female,58,Diploma,10,91,74,32,9,1.0,4,36,Semi-Urban,Data Analyst,23835,0 +89863,Female,36,Bachelors,1,24,59,42,66,0.0,0,5,Semi-Urban,Manager,49564,0 +89864,Male,23,PhD,8,2,56,74,52,1.0,0,32,Urban,HR Executive,90028,0 +89865,Female,33,PhD,1,61,92,78,12,0.0,1,17,Urban,ML Engineer,50751,1 +89866,Other,25,Masters,13,1,77,64,60,4.0,3,96,Semi-Urban,Data Analyst,119821,0 +89867,Male,50,Diploma,3,38,65,81,47,6.0,2,24,Urban,Manager,104157,0 +89868,Male,27,Masters,19,11,43,53,71,2.0,7,13,Rural,Software Engineer,61086,0 +89869,Male,29,Bachelors,5,97,4,87,27,7.0,1,27,Rural,Software Engineer,118716,0 +89870,Male,28,High School,1,35,99,67,78,0.0,1,26,Urban,HR Executive,43735,0 +89871,Other,25,Diploma,15,11,94,9,41,2.0,1,59,Semi-Urban,HR Executive,51519,0 +89872,Male,23,Bachelors,18,41,15,70,88,4.0,3,27,Semi-Urban,Manager,85935,0 +89873,Male,27,Bachelors,16,78,7,28,14,7.0,4,77,Urban,Data Analyst,29083,0 +89874,Male,36,Masters,7,43,93,7,73,8.0,1,35,Semi-Urban,Data Analyst,86268,0 +89875,Male,21,Bachelors,4,74,24,79,51,9.0,1,80,Rural,Software Engineer,40548,1 +89876,Male,27,Diploma,3,3,85,72,85,5.0,1,75,Urban,Data Analyst,67614,1 +89877,Male,50,Masters,10,34,36,3,23,0.0,6,63,Urban,HR Executive,105137,0 +89878,Male,33,Bachelors,15,47,38,42,18,5.0,3,68,Rural,Manager,62960,0 +89879,Other,25,Masters,4,95,88,24,86,2.0,6,13,Urban,Software Engineer,102157,0 +89880,Male,49,Diploma,11,12,72,21,74,4.0,1,77,Urban,HR Executive,74588,0 +89881,Male,33,Diploma,8,10,71,41,44,0.0,1,71,Urban,ML Engineer,149511,0 +89882,Other,21,Masters,15,32,42,1,25,9.0,6,28,Urban,Manager,101593,0 +89883,Male,39,High School,12,23,37,29,37,3.0,4,80,Urban,HR Executive,78670,0 +89884,Female,30,Bachelors,0,11,49,87,80,0.0,0,54,Urban,Software Engineer,57490,0 +89885,Male,45,Bachelors,1,16,55,37,24,8.0,1,17,Semi-Urban,Software Engineer,147179,0 +89886,Female,46,Diploma,19,93,68,34,13,3.0,0,55,Urban,Data Analyst,44589,1 +89887,Male,47,Masters,12,95,67,83,37,6.0,4,97,Urban,ML Engineer,41299,1 +89888,Female,45,Masters,5,31,16,56,25,0.0,6,9,Rural,Software Engineer,72520,0 +89889,Female,53,Diploma,18,26,18,0,32,4.0,0,77,Urban,Data Analyst,25200,0 +89890,Female,55,Masters,19,68,25,86,5,5.0,1,94,Urban,HR Executive,51559,1 +89891,Male,39,Masters,0,34,12,98,21,0.0,3,17,Urban,Data Analyst,90636,0 +89892,Other,24,Masters,10,74,40,22,31,2.0,6,30,Urban,Data Analyst,149047,0 +89893,Female,22,Bachelors,1,53,58,2,49,7.0,4,57,Rural,Data Analyst,63779,0 +89894,Female,29,PhD,15,21,80,48,26,0.0,7,3,Rural,Data Analyst,72846,0 +89895,Male,54,Diploma,11,57,16,98,39,1.0,7,44,Urban,Software Engineer,30447,0 +89896,Male,34,Bachelors,19,62,25,21,24,9.0,5,89,Urban,HR Executive,67055,0 +89897,Male,49,Diploma,13,23,73,62,66,4.0,6,47,Semi-Urban,HR Executive,57248,0 +89898,Male,45,Diploma,10,38,58,91,26,7.0,1,52,Urban,ML Engineer,109269,1 +89899,Other,47,Bachelors,5,34,10,53,94,8.0,5,25,Urban,HR Executive,120660,0 +89900,Male,59,High School,9,17,58,68,76,1.0,5,95,Urban,ML Engineer,125626,1 +89901,Female,22,High School,9,39,52,18,1,8.0,5,83,Semi-Urban,HR Executive,71302,0 +89902,Male,46,High School,3,58,99,51,77,1.0,2,43,Urban,HR Executive,119937,1 +89903,Male,50,Bachelors,3,24,30,70,96,6.0,4,23,Urban,Data Analyst,46646,0 +89904,Female,28,Diploma,6,9,93,54,2,6.0,7,94,Rural,HR Executive,80400,1 +89905,Male,47,Masters,5,68,44,80,45,7.0,7,11,Urban,HR Executive,136089,0 +89906,Male,34,Bachelors,4,22,44,91,23,7.0,4,99,Semi-Urban,Software Engineer,139148,1 +89907,Male,31,High School,17,25,9,25,20,5.0,4,57,Urban,Software Engineer,118867,0 +89908,Male,33,PhD,12,73,6,41,17,1.0,6,4,Urban,Data Analyst,101572,0 +89909,Female,49,Bachelors,10,85,63,8,33,5.0,2,68,Rural,ML Engineer,33618,0 +89910,Female,59,Bachelors,0,16,96,98,10,8.0,5,51,Urban,ML Engineer,50518,1 +89911,Female,35,Bachelors,13,20,59,70,78,3.0,4,63,Semi-Urban,ML Engineer,35411,0 +89912,Other,46,Bachelors,6,59,3,47,15,8.0,6,6,Urban,Data Analyst,82894,0 +89913,Female,40,Bachelors,9,74,58,70,41,3.0,4,18,Urban,Manager,39525,0 +89914,Male,24,Bachelors,16,31,41,36,42,4.0,7,8,Rural,Manager,122810,0 +89915,Female,39,Bachelors,3,44,27,22,20,3.0,1,6,Semi-Urban,ML Engineer,62312,0 +89916,Male,33,Bachelors,7,51,95,47,71,2.0,6,94,Rural,HR Executive,35154,1 +89917,Male,44,Bachelors,15,39,72,94,73,7.0,7,55,Semi-Urban,HR Executive,64886,1 +89918,Male,30,Bachelors,4,65,15,68,89,6.0,7,7,Semi-Urban,Manager,128836,0 +89919,Male,32,Bachelors,13,17,81,47,40,0.0,6,8,Urban,Software Engineer,76764,0 +89920,Male,58,Bachelors,0,65,83,18,30,3.0,2,84,Urban,Software Engineer,124805,1 +89921,Male,27,Bachelors,2,83,68,32,2,0.0,2,60,Urban,Data Analyst,134671,1 +89922,Female,54,Diploma,9,79,4,73,1,9.0,5,76,Urban,ML Engineer,131199,0 +89923,Male,38,Diploma,1,69,68,33,70,3.0,3,25,Urban,ML Engineer,101877,0 +89924,Male,33,Diploma,4,59,52,2,79,0.0,6,76,Rural,Manager,43592,0 +89925,Female,46,Masters,3,51,80,64,42,4.0,3,59,Semi-Urban,HR Executive,23211,1 +89926,Male,52,Bachelors,18,4,69,87,19,2.0,4,42,Urban,Software Engineer,37535,0 +89927,Female,52,PhD,11,47,15,84,4,9.0,5,67,Rural,Data Analyst,94801,0 +89928,Male,28,Diploma,12,41,17,30,45,6.0,3,71,Urban,Data Analyst,37231,0 +89929,Male,30,High School,17,12,24,86,81,9.0,2,91,Urban,Software Engineer,97187,0 +89930,Female,45,High School,12,50,10,75,28,0.0,1,25,Rural,HR Executive,35233,0 +89931,Male,36,Masters,6,94,35,51,97,0.0,4,1,Semi-Urban,Data Analyst,141607,0 +89932,Female,54,High School,3,2,24,91,25,7.0,7,96,Urban,ML Engineer,84494,0 +89933,Male,51,Masters,7,71,82,5,20,3.0,1,87,Semi-Urban,ML Engineer,75220,1 +89934,Other,29,High School,5,79,56,94,76,3.0,6,29,Urban,HR Executive,63731,1 +89935,Female,37,Diploma,3,21,56,37,74,5.0,0,57,Urban,Manager,96053,0 +89936,Female,32,Bachelors,0,44,36,90,16,3.0,7,61,Semi-Urban,ML Engineer,63683,0 +89937,Male,55,Diploma,3,13,1,89,11,6.0,6,15,Urban,Manager,133684,0 +89938,Female,27,Diploma,15,19,53,13,5,5.0,6,39,Urban,Data Analyst,114412,0 +89939,Female,36,Bachelors,5,40,83,62,88,8.0,6,17,Semi-Urban,ML Engineer,110212,0 +89940,Other,54,High School,10,14,70,99,29,0.0,2,75,Urban,HR Executive,97747,1 +89941,Male,55,Masters,12,63,8,36,40,7.0,7,91,Rural,Data Analyst,148599,0 +89942,Male,45,Bachelors,11,55,83,6,23,1.0,1,49,Urban,Software Engineer,113810,0 +89943,Female,57,Bachelors,11,64,26,11,42,0.0,3,75,Semi-Urban,Data Analyst,29826,0 +89944,Male,23,Bachelors,3,33,63,21,3,5.0,3,27,Rural,Manager,129917,0 +89945,Male,29,Bachelors,8,0,74,24,41,8.0,5,40,Urban,HR Executive,42174,0 +89946,Male,39,Bachelors,11,19,85,1,14,9.0,5,83,Urban,ML Engineer,100545,0 +89947,Male,38,Bachelors,3,85,29,96,78,6.0,1,89,Urban,Software Engineer,125493,1 +89948,Female,50,Masters,14,35,57,29,47,0.0,0,68,Rural,HR Executive,88167,0 +89949,Male,40,Bachelors,7,10,38,39,97,0.0,0,54,Semi-Urban,Data Analyst,30819,0 +89950,Male,36,Bachelors,13,48,65,56,10,0.0,7,57,Rural,Software Engineer,126193,0 +89951,Male,40,High School,17,64,99,60,36,0.0,0,69,Urban,Software Engineer,60594,1 +89952,Female,37,Bachelors,1,64,8,53,31,8.0,6,91,Urban,Manager,140161,0 +89953,Male,57,Bachelors,18,70,84,87,44,9.0,4,28,Urban,Manager,76324,1 +89954,Male,40,Bachelors,3,18,37,31,20,7.0,1,73,Urban,Software Engineer,89762,0 +89955,Female,32,PhD,17,59,54,67,56,6.0,1,28,Urban,Software Engineer,133710,0 +89956,Female,56,Masters,4,85,28,36,66,5.0,5,42,Urban,HR Executive,29309,0 +89957,Male,57,Masters,12,80,18,68,12,5.0,4,36,Semi-Urban,HR Executive,132211,0 +89958,Female,49,Masters,7,95,13,5,45,3.0,7,35,Urban,HR Executive,77004,0 +89959,Female,39,Bachelors,18,96,67,11,45,9.0,6,86,Semi-Urban,Manager,59889,1 +89960,Male,59,High School,0,62,67,43,66,3.0,0,48,Rural,HR Executive,121233,0 +89961,Female,55,Bachelors,2,66,75,46,50,6.0,5,54,Rural,ML Engineer,97237,1 +89962,Male,22,Bachelors,5,90,59,88,11,1.0,1,96,Urban,Manager,136683,1 +89963,Other,38,Masters,3,65,9,94,82,7.0,7,35,Urban,HR Executive,113700,0 +89964,Male,29,Masters,14,56,15,57,96,9.0,2,15,Urban,Manager,110957,0 +89965,Male,45,High School,19,83,10,53,92,1.0,3,78,Urban,Manager,76603,0 +89966,Male,48,Bachelors,8,75,96,32,5,6.0,2,15,Urban,Data Analyst,79271,0 +89967,Female,49,Masters,15,34,84,11,45,6.0,7,61,Semi-Urban,ML Engineer,64019,0 +89968,Male,23,High School,3,99,55,49,11,2.0,6,4,Urban,HR Executive,136895,0 +89969,Other,42,Bachelors,11,27,26,18,7,7.0,1,84,Rural,Data Analyst,119818,0 +89970,Male,40,Masters,17,92,37,77,62,2.0,1,60,Rural,HR Executive,54494,1 +89971,Female,30,Masters,17,63,58,72,39,2.0,3,12,Rural,Data Analyst,129243,0 +89972,Male,52,Diploma,5,14,49,4,96,5.0,1,68,Urban,Manager,24317,0 +89973,Male,46,Masters,17,43,29,73,43,5.0,3,42,Urban,Manager,104218,0 +89974,Female,32,High School,12,97,24,12,68,4.0,3,54,Urban,Manager,70268,0 +89975,Male,37,Diploma,8,99,92,73,19,5.0,7,72,Urban,Software Engineer,36795,1 +89976,Female,58,Diploma,0,44,97,60,47,1.0,1,47,Urban,HR Executive,52625,1 +89977,Male,26,Bachelors,0,86,88,84,44,3.0,1,90,Urban,Data Analyst,63053,1 +89978,Female,41,Bachelors,16,24,14,31,0,4.0,4,55,Urban,Data Analyst,44506,0 +89979,Male,48,Bachelors,14,23,90,4,63,6.0,1,52,Urban,Data Analyst,125232,0 +89980,Other,50,Masters,16,46,83,44,56,4.0,3,63,Semi-Urban,ML Engineer,20648,0 +89981,Male,34,Bachelors,18,81,35,3,73,5.0,2,37,Urban,ML Engineer,100539,0 +89982,Male,32,Bachelors,5,18,71,10,38,0.0,7,1,Semi-Urban,ML Engineer,94510,0 +89983,Male,58,Diploma,18,95,82,33,93,8.0,4,63,Urban,Data Analyst,141982,1 +89984,Female,53,Masters,10,37,1,47,74,1.0,5,59,Semi-Urban,Data Analyst,42042,0 +89985,Male,40,Bachelors,3,94,55,1,65,0.0,3,73,Urban,Data Analyst,25466,0 +89986,Male,56,Bachelors,5,36,24,60,89,4.0,1,45,Rural,Software Engineer,100032,0 +89987,Female,34,Masters,18,47,53,51,27,7.0,2,7,Rural,Software Engineer,95428,0 +89988,Female,55,Bachelors,19,3,13,71,73,9.0,6,37,Rural,HR Executive,68982,0 +89989,Male,35,Diploma,13,37,17,93,71,0.0,5,3,Semi-Urban,Manager,28971,0 +89990,Female,51,Bachelors,3,7,77,86,57,3.0,0,32,Rural,HR Executive,131509,0 +89991,Male,22,Masters,17,87,2,44,45,8.0,0,39,Urban,Manager,49639,0 +89992,Female,53,High School,16,3,34,93,50,1.0,1,14,Urban,HR Executive,60282,0 +89993,Male,28,Diploma,4,80,64,60,58,9.0,5,25,Semi-Urban,HR Executive,89736,0 +89994,Male,26,High School,0,18,89,14,56,0.0,1,98,Rural,Manager,70047,0 +89995,Female,27,Diploma,3,6,67,45,94,1.0,0,84,Urban,HR Executive,129735,0 +89996,Female,53,Bachelors,17,6,26,40,39,7.0,1,33,Rural,Software Engineer,123461,0 +89997,Male,40,Bachelors,12,42,55,59,59,1.0,6,25,Urban,Data Analyst,91176,0 +89998,Male,41,Masters,0,74,72,77,99,6.0,3,76,Rural,ML Engineer,48978,1 +89999,Male,39,High School,5,64,50,48,40,2.0,1,33,Urban,Software Engineer,115868,0 +90000,Female,53,Bachelors,4,80,82,50,77,1.0,1,81,Urban,HR Executive,131225,1 +90001,Female,35,Bachelors,19,50,11,28,9,6.0,4,18,Urban,HR Executive,123378,0 +90002,Female,48,Bachelors,12,5,33,59,58,5.0,2,41,Rural,Manager,123007,0 +90003,Male,47,Bachelors,15,10,41,64,32,0.0,1,74,Urban,HR Executive,124337,0 +90004,Male,39,High School,5,25,12,83,0,7.0,6,98,Urban,ML Engineer,44174,0 +90005,Male,21,Diploma,15,44,99,89,20,6.0,7,37,Semi-Urban,Software Engineer,49948,1 +90006,Female,49,High School,3,67,55,68,28,4.0,0,58,Rural,Data Analyst,29992,1 +90007,Male,47,Bachelors,10,91,55,42,16,5.0,0,15,Urban,Manager,46892,0 +90008,Male,36,Diploma,5,91,99,95,1,8.0,1,44,Urban,Data Analyst,72333,1 +90009,Male,22,High School,17,34,91,0,70,5.0,4,23,Semi-Urban,Data Analyst,83766,0 +90010,Male,28,Bachelors,4,94,58,3,16,6.0,5,51,Semi-Urban,Software Engineer,47983,0 +90011,Male,47,Masters,11,23,31,80,79,6.0,1,92,Semi-Urban,Software Engineer,74488,0 +90012,Male,52,PhD,3,63,49,88,8,4.0,5,23,Urban,Data Analyst,109924,0 +90013,Male,22,Masters,3,48,76,90,34,0.0,6,48,Rural,HR Executive,38775,1 +90014,Male,24,Bachelors,5,98,91,88,1,9.0,7,67,Semi-Urban,ML Engineer,81663,1 +90015,Female,27,High School,2,84,53,15,98,2.0,2,74,Urban,Data Analyst,66340,0 +90016,Male,21,High School,16,36,63,32,78,6.0,0,49,Urban,Manager,94142,0 +90017,Male,42,Diploma,0,26,57,6,49,0.0,6,65,Rural,Software Engineer,87478,0 +90018,Male,28,High School,2,54,58,65,63,5.0,1,9,Semi-Urban,ML Engineer,139281,0 +90019,Male,57,High School,10,19,79,25,97,1.0,5,48,Urban,Software Engineer,118869,0 +90020,Male,35,Diploma,8,75,79,45,52,7.0,3,84,Urban,Data Analyst,81225,1 +90021,Female,31,Diploma,1,37,22,69,45,4.0,4,56,Urban,Software Engineer,65603,0 +90022,Male,47,Bachelors,5,32,24,4,52,6.0,6,7,Urban,Data Analyst,24720,0 +90023,Male,59,Diploma,0,77,9,61,83,8.0,6,2,Semi-Urban,Software Engineer,119674,0 +90024,Male,49,Diploma,2,23,81,45,97,5.0,6,86,Urban,Data Analyst,52570,1 +90025,Female,38,Bachelors,12,79,66,56,95,0.0,1,15,Urban,ML Engineer,44601,0 +90026,Male,42,Bachelors,18,73,47,55,74,4.0,7,65,Semi-Urban,Manager,82008,1 +90027,Male,59,Bachelors,5,41,63,71,22,9.0,2,73,Semi-Urban,Manager,21200,1 +90028,Female,46,Diploma,11,14,70,20,36,1.0,3,84,Urban,Software Engineer,82384,0 +90029,Male,22,Diploma,6,15,78,22,4,2.0,2,14,Urban,Manager,94270,0 +90030,Male,54,Diploma,12,96,61,4,19,1.0,2,54,Rural,HR Executive,52173,0 +90031,Male,33,Bachelors,17,99,57,27,50,8.0,3,88,Urban,Data Analyst,83351,1 +90032,Female,54,Bachelors,19,50,59,98,65,3.0,3,95,Urban,Data Analyst,60718,1 +90033,Male,25,Bachelors,4,70,11,91,71,8.0,2,67,Urban,Data Analyst,51980,1 +90034,Male,51,Masters,0,91,21,56,66,6.0,1,53,Semi-Urban,ML Engineer,120501,0 +90035,Male,45,Masters,8,17,22,0,56,7.0,7,85,Rural,ML Engineer,116091,0 +90036,Male,25,Bachelors,2,62,3,28,59,0.0,3,20,Semi-Urban,Software Engineer,83962,0 +90037,Male,23,High School,10,46,17,58,94,3.0,6,19,Semi-Urban,Software Engineer,38331,0 +90038,Male,27,Bachelors,19,9,99,39,31,6.0,7,70,Urban,Data Analyst,36272,0 +90039,Male,23,Diploma,14,5,23,78,26,1.0,5,25,Urban,HR Executive,90399,0 +90040,Male,48,Bachelors,19,71,76,34,42,1.0,4,67,Rural,ML Engineer,61309,1 +90041,Male,24,High School,4,39,38,20,78,3.0,5,85,Urban,Manager,90330,0 +90042,Male,27,Bachelors,3,20,7,56,19,2.0,2,73,Rural,HR Executive,66799,0 +90043,Male,50,Bachelors,19,13,54,84,52,7.0,1,31,Rural,ML Engineer,42178,0 +90044,Female,30,Diploma,0,67,21,48,96,6.0,4,89,Urban,HR Executive,67964,0 +90045,Male,29,Bachelors,14,97,29,39,30,3.0,1,23,Urban,Data Analyst,117994,0 +90046,Female,33,Masters,11,48,25,48,19,9.0,1,5,Rural,Software Engineer,86797,0 +90047,Male,38,Masters,15,47,35,0,83,8.0,4,64,Urban,ML Engineer,140472,0 +90048,Female,54,PhD,17,63,15,72,15,4.0,6,72,Urban,ML Engineer,120762,0 +90049,Male,52,Bachelors,7,49,76,43,72,4.0,7,84,Urban,HR Executive,55262,1 +90050,Male,42,Bachelors,5,65,27,68,86,6.0,7,92,Urban,HR Executive,78551,1 +90051,Male,58,Bachelors,18,43,51,13,0,4.0,4,75,Urban,HR Executive,22934,0 +90052,Female,37,Masters,5,0,80,95,39,6.0,5,21,Urban,Manager,84198,0 +90053,Male,51,High School,5,25,30,34,69,5.0,7,53,Urban,Manager,124317,0 +90054,Female,32,Bachelors,5,54,85,30,41,0.0,0,19,Rural,Manager,38225,0 +90055,Female,39,Masters,0,60,15,94,10,3.0,4,29,Urban,ML Engineer,111260,0 +90056,Male,42,Bachelors,8,42,86,50,19,3.0,4,81,Semi-Urban,Manager,84166,1 +90057,Male,56,Bachelors,19,8,14,14,21,6.0,2,32,Urban,Manager,32197,0 +90058,Female,46,Bachelors,11,15,5,80,71,3.0,3,43,Urban,HR Executive,25153,0 +90059,Male,42,Diploma,18,7,3,56,48,8.0,3,64,Rural,HR Executive,122945,0 +90060,Male,58,Masters,13,41,21,2,85,1.0,5,59,Semi-Urban,Software Engineer,48056,0 +90061,Other,55,Bachelors,3,50,57,21,68,6.0,3,97,Urban,Data Analyst,21633,0 +90062,Other,52,High School,17,97,7,5,97,1.0,3,49,Semi-Urban,Software Engineer,36418,0 +90063,Male,28,High School,3,0,13,72,24,9.0,2,78,Urban,Manager,145639,0 +90064,Male,39,Bachelors,10,23,98,90,22,7.0,7,1,Rural,Data Analyst,85235,0 +90065,Male,46,Masters,14,68,82,89,63,6.0,3,48,Urban,Manager,104946,1 +90066,Female,28,Bachelors,6,57,54,17,24,9.0,5,65,Urban,Software Engineer,85144,0 +90067,Female,41,Bachelors,1,20,51,74,45,2.0,2,17,Urban,Data Analyst,42094,0 +90068,Male,57,Bachelors,17,43,41,21,75,2.0,0,19,Rural,Software Engineer,72677,0 +90069,Male,45,Bachelors,19,61,55,22,94,8.0,3,76,Urban,Data Analyst,43590,0 +90070,Male,34,Masters,19,58,25,60,98,4.0,3,11,Urban,Data Analyst,34606,0 +90071,Male,22,Diploma,7,88,13,97,70,1.0,3,66,Urban,Manager,68993,1 +90072,Male,27,Masters,6,79,67,33,48,2.0,6,79,Semi-Urban,HR Executive,58903,1 +90073,Male,31,Bachelors,10,84,86,88,92,5.0,2,34,Urban,Software Engineer,61446,1 +90074,Male,33,Masters,7,8,39,66,91,8.0,2,11,Semi-Urban,Manager,107877,0 +90075,Male,34,Bachelors,17,38,23,59,55,2.0,1,3,Rural,Data Analyst,61080,0 +90076,Male,35,Bachelors,5,66,28,4,39,9.0,5,97,Urban,Software Engineer,128401,0 +90077,Male,23,Diploma,14,81,20,10,49,3.0,6,34,Urban,HR Executive,136688,0 +90078,Male,52,Masters,10,86,30,99,10,5.0,1,53,Rural,ML Engineer,121442,1 +90079,Female,52,Diploma,14,53,60,66,91,5.0,6,19,Urban,Data Analyst,66579,0 +90080,Female,27,Bachelors,9,48,72,85,49,1.0,4,74,Rural,Data Analyst,58015,1 +90081,Male,51,Diploma,1,32,15,51,78,0.0,5,3,Semi-Urban,Manager,123968,0 +90082,Female,33,Bachelors,16,96,28,98,97,1.0,6,49,Rural,Data Analyst,75603,1 +90083,Male,48,Bachelors,13,42,81,57,81,1.0,1,75,Urban,Manager,53986,1 +90084,Male,51,Bachelors,8,29,34,78,38,6.0,7,4,Rural,Manager,74550,0 +90085,Female,42,Bachelors,3,56,81,71,80,3.0,4,89,Semi-Urban,Software Engineer,141494,1 +90086,Male,49,Masters,10,55,29,31,67,5.0,4,19,Urban,Manager,83951,0 +90087,Other,42,Bachelors,0,26,75,98,2,8.0,7,2,Urban,ML Engineer,114441,0 +90088,Female,53,Diploma,11,38,2,78,48,6.0,3,70,Semi-Urban,ML Engineer,92275,0 +90089,Other,51,Bachelors,5,27,98,23,39,9.0,6,49,Semi-Urban,HR Executive,35810,0 +90090,Male,33,Masters,3,52,92,86,33,5.0,3,3,Rural,Data Analyst,22495,0 +90091,Male,36,PhD,17,20,64,86,5,0.0,2,24,Semi-Urban,ML Engineer,63677,0 +90092,Male,57,PhD,3,83,55,41,43,8.0,4,19,Semi-Urban,ML Engineer,141283,0 +90093,Female,30,Diploma,5,4,96,97,91,9.0,0,52,Rural,Manager,36716,1 +90094,Female,23,Bachelors,18,54,34,4,45,4.0,2,51,Urban,Data Analyst,33692,0 +90095,Female,38,Diploma,18,35,52,99,70,0.0,0,77,Semi-Urban,Data Analyst,123183,1 +90096,Male,28,Diploma,12,53,19,92,87,6.0,3,74,Semi-Urban,HR Executive,51666,1 +90097,Male,26,Masters,17,72,85,10,97,4.0,7,63,Urban,HR Executive,95732,0 +90098,Male,32,Masters,12,43,7,82,8,7.0,7,99,Rural,HR Executive,81493,0 +90099,Male,44,Masters,8,66,73,89,95,7.0,0,76,Urban,ML Engineer,42347,1 +90100,Female,29,Bachelors,14,18,28,93,73,7.0,4,64,Rural,Data Analyst,136865,0 +90101,Female,50,Masters,16,77,46,19,56,4.0,4,20,Urban,Manager,106917,0 +90102,Male,39,Masters,4,90,2,96,8,4.0,1,54,Semi-Urban,ML Engineer,114093,1 +90103,Male,29,Diploma,19,76,25,96,27,3.0,3,29,Urban,HR Executive,67614,0 +90104,Male,31,Masters,10,45,83,3,0,3.0,6,63,Semi-Urban,ML Engineer,131094,0 +90105,Male,47,High School,19,79,32,21,90,9.0,0,0,Semi-Urban,Software Engineer,133565,0 +90106,Male,47,High School,3,24,83,58,30,3.0,6,48,Urban,Data Analyst,84851,0 +90107,Other,49,Diploma,9,21,2,61,8,0.0,3,17,Urban,ML Engineer,149270,0 +90108,Female,57,Masters,17,12,89,66,67,1.0,7,8,Semi-Urban,HR Executive,96940,0 +90109,Male,27,Diploma,11,93,70,51,42,0.0,2,63,Urban,ML Engineer,75698,1 +90110,Male,35,Masters,11,13,6,45,18,2.0,4,34,Urban,Manager,54871,0 +90111,Male,55,PhD,7,74,0,55,90,1.0,4,57,Urban,Manager,57873,0 +90112,Other,31,Bachelors,0,9,10,71,91,3.0,0,1,Urban,Software Engineer,131493,0 +90113,Female,43,Bachelors,16,95,28,83,98,4.0,1,26,Semi-Urban,ML Engineer,83289,0 +90114,Male,24,Diploma,14,54,62,83,56,9.0,6,72,Urban,Data Analyst,36393,1 +90115,Male,23,Masters,5,10,29,33,4,5.0,1,61,Urban,ML Engineer,54071,0 +90116,Male,40,Bachelors,4,90,89,25,61,9.0,3,90,Urban,Software Engineer,99988,1 +90117,Male,36,Bachelors,9,29,62,11,44,4.0,1,38,Urban,HR Executive,145879,0 +90118,Male,22,Masters,5,58,22,82,36,1.0,7,41,Urban,Manager,83710,0 +90119,Male,36,Diploma,19,27,81,48,68,3.0,5,20,Urban,Data Analyst,116922,0 +90120,Female,51,Bachelors,3,72,20,89,66,3.0,7,89,Urban,Software Engineer,23686,1 +90121,Male,22,Diploma,4,81,27,11,62,8.0,7,70,Urban,Manager,126655,0 +90122,Male,59,Bachelors,18,92,92,89,79,7.0,7,83,Urban,HR Executive,142294,1 +90123,Female,42,Masters,8,31,95,90,54,5.0,2,12,Urban,Software Engineer,72057,0 +90124,Male,49,High School,1,53,9,57,7,7.0,1,66,Urban,ML Engineer,31298,0 +90125,Female,30,Masters,18,44,59,20,88,2.0,0,37,Urban,Software Engineer,136094,0 +90126,Male,45,Diploma,11,24,57,35,1,6.0,0,58,Urban,ML Engineer,148006,0 +90127,Female,50,Bachelors,5,0,84,50,46,0.0,7,44,Urban,ML Engineer,130330,0 +90128,Male,21,Diploma,5,46,22,96,26,8.0,1,7,Rural,Data Analyst,100963,0 +90129,Female,22,Diploma,19,30,80,11,56,3.0,5,38,Semi-Urban,HR Executive,43853,0 +90130,Male,42,Bachelors,2,32,6,91,46,7.0,1,12,Semi-Urban,ML Engineer,39102,0 +90131,Male,30,Diploma,1,56,92,13,84,2.0,0,71,Urban,Data Analyst,103992,0 +90132,Male,43,Masters,1,32,53,8,13,3.0,5,18,Semi-Urban,Data Analyst,66216,0 +90133,Male,44,Bachelors,8,92,93,15,69,2.0,4,58,Semi-Urban,Manager,138606,1 +90134,Male,40,Bachelors,0,78,50,39,72,3.0,3,98,Urban,HR Executive,78224,1 +90135,Female,55,Masters,9,34,93,19,73,9.0,7,59,Urban,Data Analyst,20385,0 +90136,Male,24,Masters,4,87,29,4,54,2.0,6,90,Semi-Urban,Manager,60163,0 +90137,Female,55,High School,6,52,71,44,62,2.0,1,38,Semi-Urban,ML Engineer,92078,0 +90138,Male,38,Bachelors,10,68,86,79,67,1.0,1,33,Urban,Software Engineer,66006,1 +90139,Male,49,Masters,10,98,21,44,58,4.0,1,61,Urban,Data Analyst,146442,0 +90140,Male,45,High School,4,88,6,57,39,8.0,5,11,Semi-Urban,Software Engineer,69047,0 +90141,Male,42,Masters,17,77,18,4,41,3.0,2,79,Rural,HR Executive,69271,0 +90142,Male,47,Diploma,4,21,75,34,41,9.0,3,24,Rural,HR Executive,78275,0 +90143,Other,59,High School,11,16,8,46,69,1.0,7,29,Urban,Software Engineer,47726,0 +90144,Male,51,Diploma,3,20,39,71,25,4.0,4,91,Urban,ML Engineer,110560,0 +90145,Male,43,Bachelors,12,80,51,90,32,5.0,4,30,Semi-Urban,Data Analyst,130096,1 +90146,Male,43,Bachelors,1,95,74,67,45,8.0,0,15,Urban,HR Executive,61411,1 +90147,Male,33,Diploma,6,2,84,63,89,1.0,5,61,Urban,HR Executive,25903,0 +90148,Male,52,High School,5,88,95,65,14,9.0,3,73,Urban,Data Analyst,45393,1 +90149,Male,45,Bachelors,9,53,59,13,34,8.0,1,43,Rural,Manager,63675,0 +90150,Male,29,Bachelors,13,82,39,0,76,9.0,2,54,Urban,Data Analyst,100740,0 +90151,Female,59,Masters,3,47,59,51,66,1.0,6,86,Urban,Manager,125839,1 +90152,Female,40,Bachelors,7,54,4,65,94,8.0,1,20,Semi-Urban,HR Executive,99563,0 +90153,Other,44,Bachelors,4,70,21,24,10,9.0,2,75,Urban,HR Executive,34011,0 +90154,Male,36,Bachelors,12,53,85,2,65,8.0,6,10,Urban,ML Engineer,47855,0 +90155,Male,52,Diploma,3,33,93,39,54,5.0,3,48,Urban,Manager,110757,0 +90156,Female,53,Diploma,17,56,91,3,5,1.0,6,93,Urban,HR Executive,101693,1 +90157,Female,36,Diploma,8,15,87,91,45,3.0,4,46,Rural,Software Engineer,95675,0 +90158,Male,37,Diploma,19,92,50,63,97,4.0,4,89,Urban,Manager,27974,1 +90159,Male,47,Bachelors,4,89,34,37,40,2.0,4,17,Rural,ML Engineer,47679,0 +90160,Female,27,Bachelors,11,97,91,50,42,0.0,2,27,Rural,Software Engineer,102423,1 +90161,Male,40,Masters,18,92,77,53,77,5.0,5,14,Rural,ML Engineer,38392,1 +90162,Male,40,Diploma,18,24,15,90,94,9.0,0,24,Urban,Data Analyst,80793,0 +90163,Male,27,Bachelors,17,26,5,85,37,3.0,3,1,Semi-Urban,ML Engineer,95673,0 +90164,Female,38,Bachelors,1,78,87,62,44,4.0,2,71,Urban,ML Engineer,131443,1 +90165,Male,50,Bachelors,4,65,40,80,24,8.0,4,76,Urban,Manager,86329,1 +90166,Male,55,Diploma,9,47,85,34,6,5.0,4,11,Urban,Data Analyst,101072,0 +90167,Male,22,Bachelors,3,52,49,38,23,0.0,2,8,Urban,Software Engineer,112176,0 +90168,Female,35,Bachelors,18,40,49,45,5,0.0,1,69,Urban,Data Analyst,132754,0 +90169,Male,49,High School,0,42,25,79,5,4.0,5,5,Semi-Urban,HR Executive,44273,0 +90170,Male,59,PhD,3,68,32,84,92,6.0,7,21,Urban,HR Executive,53491,0 +90171,Male,31,Bachelors,5,73,5,17,14,9.0,3,17,Urban,Software Engineer,47938,0 +90172,Female,45,Bachelors,13,27,25,15,63,6.0,7,5,Rural,Software Engineer,141967,0 +90173,Female,21,Masters,0,74,65,65,6,8.0,5,83,Urban,HR Executive,117403,1 +90174,Male,32,High School,17,83,46,49,86,0.0,3,17,Semi-Urban,Data Analyst,77426,0 +90175,Male,43,Bachelors,7,51,3,27,0,8.0,1,58,Urban,Software Engineer,31198,0 +90176,Female,23,Bachelors,15,4,37,51,77,8.0,3,43,Rural,HR Executive,123201,0 +90177,Male,48,PhD,19,18,25,22,16,0.0,0,73,Urban,ML Engineer,135152,0 +90178,Male,57,Bachelors,1,79,51,44,68,3.0,2,42,Semi-Urban,Manager,60102,0 +90179,Male,56,Diploma,2,11,51,60,74,3.0,6,99,Rural,HR Executive,45347,0 +90180,Male,30,Masters,8,75,99,73,9,4.0,4,59,Rural,Software Engineer,74062,1 +90181,Female,36,Bachelors,3,13,85,51,95,3.0,6,99,Urban,Software Engineer,138084,1 +90182,Male,30,Bachelors,1,27,50,74,6,6.0,7,90,Semi-Urban,Software Engineer,130432,1 +90183,Male,54,High School,12,62,13,52,85,4.0,6,38,Rural,ML Engineer,49575,0 +90184,Male,23,PhD,0,29,5,21,75,5.0,1,64,Urban,HR Executive,34460,0 +90185,Male,23,Bachelors,3,28,90,11,18,3.0,2,97,Semi-Urban,Software Engineer,89642,0 +90186,Female,33,Bachelors,4,15,29,18,15,5.0,7,38,Urban,Manager,32972,0 +90187,Male,40,Diploma,6,73,10,57,44,0.0,3,24,Urban,Data Analyst,20849,0 +90188,Male,24,Bachelors,0,27,11,32,67,6.0,3,37,Rural,Data Analyst,121794,0 +90189,Male,39,PhD,1,47,22,67,49,5.0,1,30,Urban,ML Engineer,148093,0 +90190,Male,55,Diploma,19,96,14,92,20,8.0,4,68,Rural,ML Engineer,100779,1 +90191,Female,28,Masters,8,76,16,2,80,1.0,7,69,Urban,ML Engineer,141351,0 +90192,Male,44,Masters,7,61,23,62,70,6.0,6,76,Rural,Manager,76362,0 +90193,Male,44,Bachelors,2,18,95,78,20,3.0,3,84,Rural,ML Engineer,84440,1 +90194,Male,21,Masters,2,66,67,86,44,0.0,3,35,Semi-Urban,ML Engineer,78741,1 +90195,Female,55,Bachelors,17,25,5,67,74,9.0,6,58,Rural,HR Executive,94444,0 +90196,Male,54,Diploma,18,13,58,53,30,9.0,3,96,Urban,ML Engineer,64403,0 +90197,Female,59,Bachelors,18,43,62,65,10,7.0,3,7,Urban,Software Engineer,149897,0 +90198,Female,54,Diploma,15,51,97,5,72,2.0,0,21,Rural,Data Analyst,62880,0 +90199,Male,49,Diploma,11,85,64,84,0,0.0,0,49,Rural,Manager,91432,1 +90200,Male,26,Bachelors,2,8,86,60,22,1.0,3,24,Semi-Urban,Manager,75387,0 +90201,Female,56,PhD,8,30,72,46,18,2.0,7,62,Urban,Software Engineer,41208,0 +90202,Female,25,Bachelors,13,40,93,50,6,0.0,4,98,Urban,Data Analyst,49853,1 +90203,Male,28,Bachelors,4,13,79,81,31,0.0,6,60,Rural,Manager,28177,0 +90204,Female,38,Bachelors,1,65,31,25,15,4.0,7,63,Semi-Urban,Software Engineer,113324,0 +90205,Female,28,Diploma,2,26,84,0,64,3.0,3,5,Urban,ML Engineer,52246,0 +90206,Male,29,Masters,5,35,59,85,93,4.0,7,0,Semi-Urban,Software Engineer,106514,0 +90207,Male,48,Bachelors,0,97,51,76,76,0.0,5,64,Urban,HR Executive,149255,1 +90208,Female,36,Bachelors,3,47,80,64,74,1.0,4,88,Semi-Urban,HR Executive,80485,1 +90209,Male,56,Bachelors,0,36,52,49,57,8.0,5,82,Semi-Urban,Data Analyst,141453,0 +90210,Male,27,Bachelors,16,1,52,69,58,8.0,4,47,Urban,Software Engineer,30466,0 +90211,Female,53,High School,1,11,73,0,40,8.0,1,94,Urban,Software Engineer,45521,0 +90212,Male,50,PhD,1,1,75,38,8,5.0,5,98,Semi-Urban,Software Engineer,67837,0 +90213,Female,41,Masters,16,6,91,31,96,2.0,3,0,Semi-Urban,Data Analyst,62612,0 +90214,Male,44,PhD,13,34,89,1,52,7.0,4,75,Semi-Urban,HR Executive,29243,0 +90215,Female,36,High School,10,54,95,13,15,9.0,0,62,Urban,Manager,108324,0 +90216,Male,47,Diploma,10,20,3,18,42,7.0,0,94,Urban,Data Analyst,45999,0 +90217,Male,36,High School,14,67,59,96,45,0.0,0,16,Urban,HR Executive,102385,1 +90218,Male,23,Masters,11,64,42,20,95,0.0,1,37,Semi-Urban,Data Analyst,93712,0 +90219,Male,48,High School,18,75,33,2,3,8.0,6,12,Rural,Manager,32531,0 +90220,Male,40,Diploma,5,11,99,53,12,8.0,6,90,Urban,HR Executive,120120,1 +90221,Female,59,Bachelors,13,36,65,32,79,8.0,7,16,Rural,ML Engineer,70736,0 +90222,Female,30,Bachelors,10,82,55,79,42,3.0,0,36,Urban,HR Executive,37892,1 +90223,Male,46,Bachelors,10,68,27,77,2,6.0,2,18,Urban,Manager,105916,0 +90224,Male,21,Bachelors,1,64,20,39,50,6.0,6,32,Semi-Urban,Data Analyst,85615,0 +90225,Male,41,High School,5,55,86,48,68,5.0,6,18,Rural,Manager,117699,0 +90226,Male,32,High School,4,27,20,45,62,4.0,6,25,Semi-Urban,Software Engineer,22575,0 +90227,Female,28,Masters,0,19,87,51,27,2.0,4,77,Rural,Manager,110902,0 +90228,Female,52,Diploma,5,99,41,56,57,6.0,6,51,Urban,ML Engineer,48479,1 +90229,Male,51,Bachelors,6,50,0,52,88,3.0,0,20,Urban,ML Engineer,134560,0 +90230,Male,36,High School,5,75,9,56,99,9.0,1,75,Urban,HR Executive,84580,0 +90231,Female,52,Bachelors,12,32,62,85,0,7.0,1,98,Urban,HR Executive,78580,1 +90232,Male,59,Bachelors,9,46,37,69,52,8.0,0,76,Urban,Data Analyst,35218,0 +90233,Male,36,High School,10,52,8,82,31,4.0,2,4,Rural,Data Analyst,116118,0 +90234,Female,49,Masters,15,62,45,43,15,7.0,4,6,Urban,Software Engineer,96329,0 +90235,Male,36,High School,9,4,38,33,86,7.0,4,86,Rural,Software Engineer,23573,0 +90236,Male,27,Masters,17,5,9,54,99,3.0,0,10,Urban,Manager,64838,0 +90237,Female,50,Diploma,9,22,3,8,96,9.0,5,34,Urban,ML Engineer,20047,0 +90238,Male,32,Bachelors,1,77,79,98,39,9.0,7,37,Semi-Urban,HR Executive,92008,1 +90239,Male,26,Bachelors,15,8,64,34,39,3.0,4,32,Urban,Data Analyst,92927,0 +90240,Male,59,Bachelors,6,62,6,43,71,4.0,7,25,Urban,Data Analyst,116655,0 +90241,Male,55,Bachelors,7,30,60,15,23,8.0,7,64,Semi-Urban,Data Analyst,22268,0 +90242,Male,23,Masters,14,77,12,26,17,9.0,4,71,Urban,ML Engineer,106860,0 +90243,Female,49,Bachelors,3,10,65,50,69,8.0,6,49,Semi-Urban,HR Executive,65980,0 +90244,Female,26,Diploma,4,88,28,21,86,1.0,7,39,Semi-Urban,Software Engineer,42907,0 +90245,Male,51,High School,11,83,87,69,19,4.0,5,9,Urban,HR Executive,64425,1 +90246,Male,36,High School,18,54,85,76,55,5.0,2,9,Urban,HR Executive,128866,0 +90247,Male,27,Bachelors,14,75,49,60,21,1.0,0,83,Urban,Data Analyst,116124,1 +90248,Male,48,Bachelors,15,27,83,14,50,1.0,4,73,Urban,Software Engineer,131864,0 +90249,Female,52,Masters,19,66,8,40,24,7.0,3,69,Urban,Manager,72702,0 +90250,Female,31,Masters,14,47,13,51,30,9.0,7,27,Urban,Software Engineer,71089,0 +90251,Male,35,Bachelors,14,32,69,82,49,0.0,0,89,Rural,Manager,35338,1 +90252,Male,52,Bachelors,5,50,92,60,68,7.0,7,81,Urban,HR Executive,106306,1 +90253,Other,50,Bachelors,9,74,23,10,67,3.0,6,88,Rural,HR Executive,98853,0 +90254,Male,46,Masters,3,19,95,36,89,2.0,3,48,Urban,Software Engineer,44118,0 +90255,Female,22,High School,10,74,35,61,27,3.0,5,20,Urban,Manager,139380,0 +90256,Other,55,Diploma,10,96,42,36,81,1.0,7,59,Semi-Urban,Data Analyst,42502,0 +90257,Male,39,Bachelors,1,0,47,97,55,0.0,3,20,Urban,HR Executive,83623,0 +90258,Male,53,Bachelors,14,0,89,8,52,2.0,6,2,Rural,Manager,91233,0 +90259,Female,35,High School,15,27,96,72,56,2.0,0,32,Urban,Manager,131429,0 +90260,Male,58,Masters,4,31,35,47,48,5.0,7,64,Urban,Data Analyst,115288,0 +90261,Male,48,Bachelors,11,47,81,2,98,5.0,5,21,Urban,ML Engineer,25271,0 +90262,Male,41,High School,9,18,83,97,16,4.0,5,22,Urban,ML Engineer,149835,0 +90263,Male,55,High School,11,48,92,72,50,9.0,5,72,Semi-Urban,Software Engineer,137006,1 +90264,Male,46,High School,16,3,22,66,16,5.0,2,16,Semi-Urban,HR Executive,32559,0 +90265,Male,58,High School,19,14,80,59,16,9.0,4,9,Urban,Manager,102719,0 +90266,Male,57,Bachelors,8,25,30,16,44,6.0,2,92,Urban,Data Analyst,70389,0 +90267,Male,30,High School,4,10,62,31,92,4.0,1,52,Urban,Software Engineer,96928,0 +90268,Female,49,Bachelors,4,44,40,8,1,0.0,0,33,Urban,Data Analyst,107125,0 +90269,Male,21,Bachelors,0,96,90,58,31,1.0,7,11,Urban,Data Analyst,136419,1 +90270,Female,51,Bachelors,18,90,23,97,47,9.0,4,26,Rural,Software Engineer,147754,0 +90271,Male,37,Masters,16,10,79,21,90,6.0,7,27,Urban,Software Engineer,118296,0 +90272,Male,54,Bachelors,8,38,70,4,17,6.0,4,32,Urban,Software Engineer,84314,0 +90273,Male,39,Bachelors,3,55,65,72,66,6.0,1,63,Rural,Manager,126560,1 +90274,Male,31,Diploma,16,11,69,30,49,1.0,7,34,Urban,HR Executive,100898,0 +90275,Male,49,Bachelors,7,19,15,56,22,9.0,1,41,Rural,Data Analyst,96670,0 +90276,Female,58,High School,0,37,63,89,17,8.0,3,57,Urban,ML Engineer,116317,1 +90277,Female,44,Bachelors,10,85,4,34,78,6.0,5,86,Urban,Software Engineer,42526,0 +90278,Male,54,Diploma,4,4,75,47,65,5.0,1,57,Urban,ML Engineer,78587,0 +90279,Male,21,Masters,12,10,55,97,67,0.0,2,32,Urban,Manager,26765,0 +90280,Male,48,High School,9,69,60,8,13,8.0,5,47,Rural,Manager,116431,0 +90281,Female,49,Bachelors,13,58,35,9,77,2.0,3,18,Semi-Urban,ML Engineer,77988,0 +90282,Male,36,Bachelors,17,42,37,71,75,1.0,0,3,Rural,Software Engineer,52422,0 +90283,Male,49,High School,8,11,3,52,52,4.0,6,69,Urban,Software Engineer,99054,0 +90284,Female,22,Bachelors,9,59,26,22,45,6.0,4,77,Urban,ML Engineer,48802,0 +90285,Male,23,Masters,5,20,73,84,48,4.0,7,88,Urban,Data Analyst,124193,1 +90286,Male,46,Bachelors,7,85,39,99,91,6.0,0,37,Urban,ML Engineer,86931,1 +90287,Male,59,Diploma,13,17,9,4,32,5.0,4,12,Urban,Data Analyst,125797,0 +90288,Male,58,Masters,2,99,74,8,67,4.0,5,5,Rural,Data Analyst,75533,0 +90289,Male,30,Bachelors,17,61,8,33,54,8.0,6,57,Rural,HR Executive,113657,0 +90290,Female,26,High School,2,70,53,37,94,6.0,7,95,Semi-Urban,ML Engineer,45271,1 +90291,Female,48,Masters,9,64,39,99,11,9.0,1,30,Urban,ML Engineer,84065,0 +90292,Male,43,Bachelors,3,3,95,42,47,8.0,3,6,Urban,ML Engineer,59105,0 +90293,Female,21,Masters,17,4,2,77,72,0.0,5,49,Semi-Urban,Data Analyst,95161,0 +90294,Male,47,Masters,15,26,60,87,77,3.0,4,34,Semi-Urban,Data Analyst,30226,0 +90295,Other,59,Masters,3,42,25,26,38,6.0,6,71,Urban,ML Engineer,142368,0 +90296,Male,59,Bachelors,19,8,41,3,23,5.0,0,12,Semi-Urban,HR Executive,122710,0 +90297,Female,31,Bachelors,3,62,4,89,39,2.0,1,61,Semi-Urban,Data Analyst,113634,0 +90298,Male,35,Bachelors,13,47,81,50,80,1.0,0,49,Rural,HR Executive,25701,0 +90299,Male,25,Bachelors,3,24,23,86,12,7.0,1,26,Rural,Software Engineer,88977,0 +90300,Female,48,Diploma,0,74,91,47,73,1.0,2,41,Urban,HR Executive,46276,1 +90301,Male,36,Diploma,7,95,43,34,55,4.0,6,44,Urban,Software Engineer,87364,0 +90302,Female,56,Bachelors,19,70,48,13,68,4.0,0,61,Rural,Data Analyst,20815,0 +90303,Male,58,High School,19,58,52,23,98,0.0,1,38,Semi-Urban,HR Executive,99458,0 +90304,Male,42,Bachelors,0,20,12,51,14,4.0,3,75,Urban,HR Executive,147468,0 +90305,Male,42,High School,8,81,73,25,70,4.0,4,49,Urban,HR Executive,128564,0 +90306,Female,43,Diploma,12,72,19,19,76,5.0,4,99,Urban,HR Executive,32940,0 +90307,Female,33,Bachelors,19,28,14,54,0,4.0,3,89,Urban,Software Engineer,143848,0 +90308,Male,53,Diploma,17,29,32,2,52,7.0,0,20,Semi-Urban,Software Engineer,103972,0 +90309,Male,27,Masters,13,24,94,90,57,3.0,0,9,Urban,Manager,140338,0 +90310,Female,45,Bachelors,12,20,0,97,8,6.0,2,62,Rural,Manager,26924,0 +90311,Female,25,Masters,16,9,19,39,22,1.0,4,83,Rural,Software Engineer,142580,0 +90312,Female,40,Masters,8,84,21,57,42,0.0,0,88,Urban,ML Engineer,102369,1 +90313,Male,36,PhD,5,21,23,57,68,1.0,4,92,Urban,ML Engineer,136669,0 +90314,Female,59,Masters,9,59,4,45,20,7.0,3,99,Urban,Data Analyst,38501,0 +90315,Male,43,Masters,11,42,11,32,20,9.0,3,79,Semi-Urban,ML Engineer,38489,0 +90316,Female,56,Bachelors,2,48,65,65,58,4.0,6,15,Rural,HR Executive,88988,0 +90317,Male,35,PhD,0,19,70,58,12,2.0,0,6,Urban,Data Analyst,131479,0 +90318,Female,28,Diploma,4,33,35,51,94,7.0,0,1,Urban,Software Engineer,127840,0 +90319,Other,56,Bachelors,1,38,15,81,29,8.0,2,32,Urban,HR Executive,85900,0 +90320,Male,35,Masters,1,68,47,10,34,7.0,7,73,Semi-Urban,Manager,76320,0 +90321,Female,28,Bachelors,5,5,22,62,73,4.0,1,27,Rural,Data Analyst,119348,0 +90322,Male,43,Bachelors,8,43,17,78,10,8.0,5,15,Semi-Urban,ML Engineer,116334,0 +90323,Female,33,Diploma,17,26,22,43,70,2.0,7,7,Rural,Data Analyst,93064,0 +90324,Male,31,Bachelors,15,49,25,76,80,5.0,5,29,Urban,ML Engineer,54208,0 +90325,Male,53,Diploma,12,32,27,2,46,2.0,7,12,Urban,ML Engineer,148956,0 +90326,Male,27,Bachelors,17,56,44,75,17,8.0,4,46,Urban,ML Engineer,88340,0 +90327,Female,40,Bachelors,15,28,61,85,95,3.0,4,96,Urban,Manager,126154,1 +90328,Male,55,High School,2,64,17,87,70,4.0,4,41,Urban,Software Engineer,85415,0 +90329,Male,42,PhD,10,17,99,0,28,8.0,5,37,Urban,Data Analyst,78497,0 +90330,Male,57,Bachelors,16,67,52,76,3,4.0,3,3,Rural,HR Executive,60947,0 +90331,Male,56,Masters,7,55,46,83,35,7.0,2,75,Rural,Software Engineer,112867,1 +90332,Female,30,Bachelors,18,49,0,66,31,6.0,6,16,Urban,Software Engineer,121126,0 +90333,Male,45,Masters,9,27,44,21,19,1.0,3,4,Semi-Urban,Data Analyst,31202,0 +90334,Male,22,Diploma,12,55,51,10,12,1.0,6,66,Rural,Manager,32149,0 +90335,Male,22,Bachelors,13,98,93,62,52,2.0,4,20,Urban,Manager,131937,1 +90336,Male,30,Bachelors,15,25,39,13,34,0.0,6,25,Urban,ML Engineer,25610,0 +90337,Male,58,Bachelors,19,12,18,75,81,2.0,3,84,Rural,Software Engineer,52222,0 +90338,Female,31,Bachelors,8,59,27,41,40,4.0,0,78,Rural,Manager,137980,0 +90339,Female,28,Bachelors,12,62,66,14,85,9.0,6,45,Urban,Data Analyst,119984,0 +90340,Other,21,Bachelors,0,71,12,89,68,7.0,0,3,Semi-Urban,Software Engineer,96845,0 +90341,Female,56,High School,19,88,5,41,40,3.0,1,30,Rural,Manager,147148,0 +90342,Female,25,Masters,19,72,37,61,47,6.0,4,5,Urban,Data Analyst,22723,0 +90343,Female,40,Masters,3,74,11,40,88,8.0,7,45,Urban,Software Engineer,148040,0 +90344,Female,28,High School,13,34,29,22,97,3.0,3,7,Urban,ML Engineer,114589,0 +90345,Male,31,Diploma,3,64,37,41,73,5.0,1,76,Rural,Data Analyst,63363,0 +90346,Male,39,High School,16,70,24,20,53,8.0,6,9,Urban,Data Analyst,101697,0 +90347,Male,33,Masters,10,21,69,41,8,9.0,4,22,Urban,HR Executive,144520,0 +90348,Female,33,Bachelors,10,85,31,43,77,8.0,7,89,Urban,Software Engineer,126305,1 +90349,Male,34,High School,15,65,99,41,41,8.0,5,68,Urban,HR Executive,132965,1 +90350,Male,55,High School,0,28,6,33,74,0.0,7,2,Rural,HR Executive,55966,0 +90351,Female,52,Masters,5,74,80,24,6,9.0,4,35,Rural,HR Executive,145201,0 +90352,Female,55,Diploma,17,80,92,28,93,3.0,2,68,Urban,Software Engineer,127422,1 +90353,Male,33,Masters,10,12,22,33,22,5.0,4,98,Semi-Urban,Manager,24866,0 +90354,Male,23,Bachelors,15,41,96,65,43,4.0,1,46,Urban,HR Executive,29720,1 +90355,Female,38,Bachelors,4,40,64,21,8,9.0,6,14,Urban,ML Engineer,77615,0 +90356,Female,37,Bachelors,11,52,36,32,59,8.0,6,94,Semi-Urban,ML Engineer,112498,0 +90357,Female,28,Diploma,9,61,36,38,69,2.0,0,43,Rural,Data Analyst,84555,0 +90358,Female,33,Diploma,12,94,55,80,5,2.0,6,99,Urban,ML Engineer,95832,1 +90359,Male,24,Diploma,8,55,9,85,64,9.0,0,1,Rural,ML Engineer,41170,0 +90360,Male,31,Diploma,9,72,56,99,55,9.0,1,44,Urban,Data Analyst,127562,1 +90361,Male,49,Masters,2,25,45,45,46,3.0,0,91,Urban,HR Executive,57846,0 +90362,Male,34,Bachelors,10,32,31,1,45,5.0,2,18,Semi-Urban,Manager,90466,0 +90363,Female,55,Masters,2,26,65,86,78,8.0,7,72,Urban,Software Engineer,36426,1 +90364,Male,56,Bachelors,17,33,31,83,72,2.0,2,34,Urban,Manager,82958,0 +90365,Male,36,Masters,2,41,42,39,77,4.0,5,93,Semi-Urban,Manager,123824,0 +90366,Female,21,High School,15,70,31,24,32,6.0,0,69,Semi-Urban,Manager,45304,0 +90367,Female,45,Bachelors,2,70,33,40,81,8.0,5,10,Rural,ML Engineer,99990,0 +90368,Male,48,High School,14,22,47,24,94,4.0,3,14,Semi-Urban,HR Executive,47816,0 +90369,Male,56,Diploma,12,7,10,79,50,7.0,6,91,Urban,Manager,79699,0 +90370,Female,41,Bachelors,8,66,55,6,36,1.0,7,3,Urban,Software Engineer,81432,0 +90371,Male,34,Diploma,8,30,15,7,27,8.0,4,75,Urban,Software Engineer,140947,0 +90372,Male,41,High School,17,32,22,46,71,6.0,7,51,Rural,Software Engineer,132491,0 +90373,Female,59,Masters,17,6,10,13,11,0.0,7,82,Urban,HR Executive,65941,0 +90374,Female,28,Bachelors,13,29,70,80,51,7.0,7,81,Urban,Manager,132774,1 +90375,Male,29,Bachelors,0,24,36,87,3,5.0,4,61,Semi-Urban,Software Engineer,74098,0 +90376,Male,57,Masters,5,1,12,62,62,0.0,0,15,Urban,Software Engineer,145241,0 +90377,Female,57,Masters,19,39,58,69,9,6.0,2,12,Urban,Manager,147755,0 +90378,Female,44,Diploma,5,23,36,49,4,6.0,3,63,Urban,Data Analyst,22892,0 +90379,Male,32,Bachelors,5,61,55,36,59,9.0,0,46,Semi-Urban,Data Analyst,128656,0 +90380,Male,43,Diploma,10,9,15,95,27,1.0,7,83,Semi-Urban,HR Executive,27430,0 +90381,Male,50,Bachelors,1,33,0,84,32,4.0,5,62,Urban,ML Engineer,69253,0 +90382,Male,38,Bachelors,14,31,54,73,53,0.0,4,57,Semi-Urban,Manager,80054,0 +90383,Female,46,Masters,18,85,89,78,1,6.0,4,87,Semi-Urban,Manager,105424,1 +90384,Male,33,Masters,14,58,5,40,81,9.0,2,54,Rural,Data Analyst,66582,0 +90385,Female,53,High School,3,95,54,18,42,9.0,7,52,Urban,ML Engineer,99113,0 +90386,Female,48,High School,8,85,43,90,30,9.0,6,13,Rural,Software Engineer,126220,0 +90387,Female,34,Masters,12,26,45,3,29,5.0,3,27,Semi-Urban,Software Engineer,149047,0 +90388,Male,57,Bachelors,12,51,88,64,38,7.0,5,59,Urban,HR Executive,62145,1 +90389,Male,55,Diploma,12,45,96,91,67,4.0,3,72,Urban,ML Engineer,110047,1 +90390,Male,37,High School,1,16,44,92,98,5.0,3,55,Urban,Software Engineer,102246,0 +90391,Male,48,Masters,11,41,58,80,8,6.0,0,18,Semi-Urban,Data Analyst,85880,0 +90392,Male,55,Masters,3,29,12,53,2,5.0,3,91,Urban,ML Engineer,133328,0 +90393,Male,51,PhD,4,89,16,36,44,6.0,6,25,Semi-Urban,Manager,91569,0 +90394,Female,35,Bachelors,6,0,33,72,18,6.0,1,20,Rural,Manager,121272,0 +90395,Male,34,Diploma,11,26,31,90,61,3.0,6,71,Rural,ML Engineer,122222,0 +90396,Male,47,Diploma,13,23,8,98,48,3.0,3,49,Rural,ML Engineer,39203,0 +90397,Male,59,Masters,12,39,11,55,58,3.0,7,51,Semi-Urban,ML Engineer,25626,0 +90398,Male,51,Bachelors,10,20,43,47,76,4.0,7,67,Urban,ML Engineer,125301,0 +90399,Male,55,Diploma,16,97,46,87,44,2.0,1,38,Urban,Software Engineer,116160,1 +90400,Female,23,Bachelors,19,90,26,1,16,9.0,7,93,Semi-Urban,Manager,46195,0 +90401,Male,55,High School,5,10,48,4,86,7.0,2,1,Urban,Manager,87562,0 +90402,Male,22,Masters,5,10,96,85,31,0.0,0,71,Semi-Urban,Data Analyst,40362,1 +90403,Female,54,High School,15,67,76,82,80,1.0,1,27,Semi-Urban,Manager,139998,1 +90404,Female,44,High School,14,59,34,47,87,9.0,5,86,Urban,Manager,82311,0 +90405,Male,48,High School,8,76,51,48,4,4.0,0,65,Rural,ML Engineer,127410,1 +90406,Female,26,High School,13,70,60,19,65,7.0,7,47,Urban,HR Executive,106240,0 +90407,Female,49,Bachelors,18,10,17,60,82,0.0,3,33,Semi-Urban,Data Analyst,108469,0 +90408,Male,23,Bachelors,1,94,51,16,68,3.0,4,40,Semi-Urban,ML Engineer,121363,0 +90409,Female,36,High School,16,25,15,48,0,8.0,0,57,Semi-Urban,Manager,80336,0 +90410,Female,35,Bachelors,16,6,73,41,31,2.0,6,63,Urban,Manager,143247,0 +90411,Male,39,High School,14,2,68,63,19,8.0,7,91,Semi-Urban,Data Analyst,73158,0 +90412,Male,48,Diploma,2,90,44,22,44,9.0,5,46,Semi-Urban,Software Engineer,81708,0 +90413,Other,44,Bachelors,12,38,75,47,28,6.0,5,40,Urban,Data Analyst,83117,0 +90414,Other,59,Bachelors,1,53,18,34,16,5.0,6,75,Urban,HR Executive,29024,0 +90415,Female,44,Bachelors,17,77,20,80,23,3.0,2,17,Rural,Manager,99093,0 +90416,Male,38,High School,10,63,64,91,2,3.0,4,22,Urban,Manager,57740,1 +90417,Female,35,High School,5,73,30,98,26,4.0,5,3,Semi-Urban,Data Analyst,108807,0 +90418,Female,41,Bachelors,0,6,57,84,83,6.0,5,34,Semi-Urban,HR Executive,102957,0 +90419,Male,39,Bachelors,10,23,56,96,11,8.0,6,30,Semi-Urban,ML Engineer,136036,0 +90420,Male,31,Bachelors,3,52,33,63,7,7.0,0,62,Urban,Manager,82619,0 +90421,Female,34,Bachelors,15,51,48,49,97,4.0,3,96,Rural,HR Executive,130022,1 +90422,Male,57,Bachelors,8,64,48,52,23,5.0,6,99,Semi-Urban,Software Engineer,127542,1 +90423,Male,53,Bachelors,12,58,94,13,80,0.0,7,19,Urban,Manager,110055,0 +90424,Male,36,Bachelors,15,33,25,18,80,0.0,1,14,Urban,HR Executive,147278,0 +90425,Male,31,Diploma,18,79,30,74,34,8.0,7,6,Rural,Manager,41687,0 +90426,Male,56,PhD,5,48,63,99,95,9.0,1,33,Urban,Manager,129852,1 +90427,Female,42,High School,17,57,49,48,28,7.0,5,38,Rural,Data Analyst,67749,0 +90428,Female,26,Diploma,15,5,68,27,74,4.0,6,93,Rural,Data Analyst,41373,0 +90429,Male,54,PhD,14,31,56,61,34,0.0,0,40,Rural,HR Executive,126590,0 +90430,Female,47,PhD,8,17,74,22,11,7.0,5,92,Urban,ML Engineer,38786,0 +90431,Male,27,Diploma,1,92,11,97,92,2.0,6,43,Semi-Urban,Data Analyst,20242,1 +90432,Female,26,Masters,5,64,30,69,46,8.0,0,86,Urban,Software Engineer,103364,1 +90433,Male,32,Bachelors,13,64,87,0,0,8.0,6,91,Rural,Data Analyst,96187,1 +90434,Other,37,Diploma,17,75,18,16,35,3.0,1,43,Semi-Urban,Data Analyst,111843,0 +90435,Male,29,Masters,15,63,89,89,93,1.0,5,14,Urban,HR Executive,138391,1 +90436,Female,38,Bachelors,15,53,64,88,26,5.0,1,14,Rural,ML Engineer,22730,0 +90437,Male,27,Bachelors,7,89,68,46,33,1.0,3,27,Urban,Software Engineer,67397,0 +90438,Female,24,Masters,4,38,39,14,5,2.0,2,2,Urban,Software Engineer,129169,0 +90439,Male,54,High School,12,10,57,92,77,0.0,1,14,Semi-Urban,Data Analyst,31187,0 +90440,Male,26,Diploma,14,7,67,3,14,7.0,4,94,Urban,ML Engineer,102839,0 +90441,Male,58,Bachelors,5,98,49,30,3,8.0,5,55,Urban,Manager,130254,0 +90442,Female,32,Bachelors,4,36,66,85,61,9.0,1,75,Rural,Data Analyst,142338,1 +90443,Female,36,Bachelors,6,13,63,25,95,6.0,0,88,Rural,Data Analyst,56116,0 +90444,Male,39,Bachelors,11,74,84,65,52,6.0,7,37,Urban,ML Engineer,100457,1 +90445,Male,27,Bachelors,5,93,15,98,21,5.0,1,94,Rural,Manager,62710,1 +90446,Male,50,Bachelors,18,75,19,20,2,6.0,3,32,Urban,Software Engineer,48280,0 +90447,Female,56,Bachelors,13,13,11,32,81,9.0,3,8,Urban,ML Engineer,99994,0 +90448,Other,26,Masters,0,44,81,79,67,9.0,5,24,Rural,Software Engineer,58334,0 +90449,Female,37,Bachelors,5,25,27,8,25,3.0,6,90,Urban,HR Executive,78065,0 +90450,Male,31,High School,12,26,57,41,86,5.0,6,94,Semi-Urban,HR Executive,120532,0 +90451,Female,58,Bachelors,7,5,90,25,67,0.0,6,46,Semi-Urban,Data Analyst,119236,0 +90452,Male,26,High School,11,42,86,16,62,1.0,2,75,Rural,Data Analyst,22408,0 +90453,Female,57,Masters,17,15,82,59,0,4.0,0,67,Rural,ML Engineer,98447,0 +90454,Male,54,Bachelors,1,6,15,20,56,0.0,7,92,Urban,Software Engineer,56418,0 +90455,Female,26,Masters,10,48,79,28,95,4.0,1,2,Urban,Software Engineer,59054,0 +90456,Male,30,High School,15,59,5,32,67,5.0,1,76,Rural,ML Engineer,76328,0 +90457,Male,25,Masters,11,26,83,1,16,4.0,7,8,Rural,ML Engineer,137558,0 +90458,Male,27,Bachelors,18,92,65,39,63,5.0,5,17,Urban,Software Engineer,36538,0 +90459,Male,27,Masters,10,60,23,39,79,3.0,5,95,Rural,Data Analyst,114131,0 +90460,Male,54,Masters,11,9,13,94,6,8.0,6,72,Urban,Manager,58040,0 +90461,Female,57,Masters,13,52,15,96,34,7.0,5,7,Urban,Data Analyst,75219,0 +90462,Female,27,PhD,17,51,59,42,92,3.0,2,10,Urban,Manager,73157,0 +90463,Male,50,Diploma,4,73,14,36,71,0.0,4,99,Semi-Urban,Software Engineer,36211,0 +90464,Male,48,High School,11,95,72,73,30,2.0,0,67,Urban,Software Engineer,28352,1 +90465,Male,40,Bachelors,10,96,13,55,28,6.0,6,41,Urban,HR Executive,118486,0 +90466,Female,56,Diploma,13,93,17,76,84,6.0,1,80,Urban,Data Analyst,48983,1 +90467,Male,25,Bachelors,18,76,58,22,1,7.0,6,91,Semi-Urban,Manager,134977,1 +90468,Male,24,PhD,14,18,42,15,58,1.0,2,81,Rural,HR Executive,74733,0 +90469,Male,58,Bachelors,10,9,73,90,82,3.0,0,45,Urban,HR Executive,39760,0 +90470,Female,56,Bachelors,0,43,31,71,8,2.0,1,97,Rural,HR Executive,23075,1 +90471,Female,28,Masters,9,19,62,36,4,2.0,4,92,Rural,ML Engineer,99990,0 +90472,Male,49,High School,0,76,85,74,46,7.0,4,21,Urban,ML Engineer,106340,1 +90473,Female,27,Bachelors,11,0,79,53,63,5.0,1,91,Urban,HR Executive,37617,0 +90474,Female,45,Bachelors,7,75,40,22,94,4.0,7,59,Urban,Data Analyst,129051,0 +90475,Female,52,Diploma,14,36,72,2,21,5.0,5,80,Urban,Data Analyst,121266,0 +90476,Male,39,Diploma,3,90,2,46,55,7.0,7,2,Semi-Urban,Manager,141805,0 +90477,Female,36,PhD,3,11,82,66,77,6.0,3,37,Semi-Urban,ML Engineer,116920,0 +90478,Male,25,Bachelors,10,6,74,11,80,2.0,0,88,Urban,Manager,84582,0 +90479,Female,24,Bachelors,11,13,90,73,2,6.0,2,39,Semi-Urban,ML Engineer,85262,0 +90480,Male,59,Masters,15,31,0,71,1,7.0,0,89,Urban,Data Analyst,91379,0 +90481,Female,27,Masters,9,88,37,2,12,0.0,5,73,Urban,HR Executive,134596,0 +90482,Male,53,High School,12,47,22,20,24,4.0,3,63,Semi-Urban,Manager,97272,0 +90483,Male,58,Masters,6,50,32,23,8,2.0,3,53,Urban,HR Executive,145962,0 +90484,Male,35,High School,18,45,1,84,96,9.0,3,15,Rural,Software Engineer,81327,0 +90485,Male,56,Diploma,17,78,58,77,20,8.0,4,19,Semi-Urban,HR Executive,134342,0 +90486,Female,38,Bachelors,8,15,39,36,24,3.0,0,33,Rural,HR Executive,134388,0 +90487,Female,55,Diploma,17,94,23,44,78,7.0,5,50,Urban,ML Engineer,110946,0 +90488,Female,44,Diploma,4,61,0,4,93,8.0,6,16,Semi-Urban,Manager,59558,0 +90489,Male,39,Bachelors,14,14,9,43,65,0.0,4,83,Semi-Urban,HR Executive,119068,0 +90490,Male,31,Diploma,3,8,17,18,28,0.0,7,97,Semi-Urban,Software Engineer,114236,0 +90491,Male,54,Bachelors,18,70,98,22,69,7.0,6,16,Semi-Urban,Manager,147250,0 +90492,Male,35,Bachelors,1,17,30,5,51,4.0,5,9,Rural,Data Analyst,74012,0 +90493,Male,25,Masters,6,15,5,48,10,5.0,7,26,Urban,Manager,135315,0 +90494,Male,48,PhD,11,84,3,41,88,4.0,6,23,Urban,ML Engineer,90610,0 +90495,Male,39,High School,0,90,71,44,61,6.0,5,90,Urban,Manager,119006,1 +90496,Male,28,Bachelors,11,51,9,60,66,7.0,7,7,Urban,Software Engineer,86573,0 +90497,Male,24,Bachelors,0,9,86,40,34,2.0,3,31,Urban,Manager,58821,0 +90498,Male,53,Diploma,14,90,69,44,99,6.0,1,19,Rural,Data Analyst,89562,0 +90499,Male,38,Masters,6,97,98,33,82,8.0,2,80,Semi-Urban,Software Engineer,116804,1 +90500,Female,38,Bachelors,11,80,60,7,34,0.0,1,46,Semi-Urban,Manager,143293,0 +90501,Other,53,Bachelors,18,29,75,57,79,2.0,1,97,Semi-Urban,Software Engineer,102208,1 +90502,Male,41,Bachelors,15,41,25,41,1,3.0,2,35,Urban,ML Engineer,45808,0 +90503,Other,42,Bachelors,18,57,53,91,81,5.0,1,33,Rural,Data Analyst,109016,0 +90504,Male,42,Diploma,15,68,26,36,47,3.0,2,87,Rural,Manager,139011,0 +90505,Male,21,Bachelors,0,72,59,40,31,1.0,4,83,Urban,ML Engineer,30088,1 +90506,Female,32,Bachelors,18,74,98,65,90,5.0,5,28,Urban,ML Engineer,94686,1 +90507,Female,21,Bachelors,10,69,60,83,86,3.0,4,96,Urban,HR Executive,107313,1 +90508,Male,52,Diploma,16,4,48,52,0,8.0,4,20,Rural,ML Engineer,95558,0 +90509,Female,55,High School,18,52,4,3,64,7.0,1,13,Rural,HR Executive,62495,0 +90510,Female,47,Bachelors,2,61,52,67,0,6.0,4,95,Semi-Urban,Software Engineer,71712,1 +90511,Other,47,Diploma,14,79,45,38,27,8.0,6,56,Urban,Manager,86712,0 +90512,Female,49,Diploma,5,69,84,53,23,8.0,6,81,Urban,HR Executive,121485,1 +90513,Other,32,Diploma,8,8,0,62,75,1.0,1,5,Urban,ML Engineer,144206,0 +90514,Male,45,Bachelors,1,58,95,72,5,5.0,7,18,Urban,ML Engineer,133914,1 +90515,Female,22,Masters,7,37,31,24,98,3.0,0,50,Semi-Urban,ML Engineer,106819,0 +90516,Other,54,PhD,3,47,25,88,89,8.0,6,79,Semi-Urban,ML Engineer,127436,0 +90517,Male,28,Bachelors,1,99,98,18,20,7.0,7,92,Urban,Manager,96426,1 +90518,Female,45,Bachelors,17,40,1,31,94,9.0,5,97,Rural,Data Analyst,81414,0 +90519,Male,37,Bachelors,9,48,19,80,2,4.0,1,33,Urban,ML Engineer,148340,0 +90520,Other,48,Masters,12,79,21,42,43,1.0,2,97,Rural,Manager,108580,0 +90521,Male,21,High School,8,71,31,10,96,9.0,0,0,Semi-Urban,ML Engineer,96059,0 +90522,Male,46,Diploma,7,41,13,85,84,0.0,2,9,Urban,Data Analyst,102349,0 +90523,Male,35,Bachelors,4,51,87,74,16,2.0,0,94,Urban,HR Executive,102252,1 +90524,Male,24,Diploma,6,53,54,54,33,8.0,5,59,Urban,Manager,102767,0 +90525,Female,26,Bachelors,11,0,56,42,70,9.0,2,31,Urban,HR Executive,129005,0 +90526,Male,36,Bachelors,15,9,29,16,24,2.0,4,94,Urban,Software Engineer,112008,0 +90527,Male,27,Masters,18,2,67,24,74,7.0,1,72,Urban,ML Engineer,111250,0 +90528,Male,45,Bachelors,11,51,54,3,93,7.0,6,56,Semi-Urban,HR Executive,95883,0 +90529,Female,28,Masters,18,7,63,17,60,9.0,2,86,Urban,Manager,60396,0 +90530,Male,39,Bachelors,8,99,20,64,37,3.0,5,25,Semi-Urban,Manager,26315,0 +90531,Female,42,Bachelors,13,4,11,7,66,9.0,1,20,Semi-Urban,Software Engineer,106132,0 +90532,Male,49,Bachelors,2,22,47,16,56,4.0,5,28,Urban,ML Engineer,144637,0 +90533,Male,21,Diploma,1,83,96,32,52,8.0,7,23,Urban,ML Engineer,25539,0 +90534,Male,29,Bachelors,16,55,1,29,19,0.0,0,68,Urban,HR Executive,108827,0 +90535,Female,35,High School,16,26,36,11,88,8.0,1,75,Urban,ML Engineer,91607,0 +90536,Male,40,Bachelors,18,29,16,27,2,6.0,0,45,Semi-Urban,HR Executive,62282,0 +90537,Female,29,Masters,13,76,70,32,78,4.0,0,22,Urban,Software Engineer,28161,0 +90538,Female,38,High School,16,89,36,25,15,4.0,0,97,Rural,Software Engineer,123103,1 +90539,Male,55,Masters,6,51,15,2,23,0.0,2,69,Semi-Urban,Manager,37503,0 +90540,Male,33,High School,6,49,76,30,89,4.0,5,48,Urban,Data Analyst,82020,0 +90541,Male,57,Diploma,7,2,71,3,71,8.0,1,64,Urban,Software Engineer,92050,0 +90542,Other,28,Diploma,7,24,31,5,13,4.0,1,62,Rural,HR Executive,24915,0 +90543,Male,24,Bachelors,11,4,60,72,22,7.0,4,10,Semi-Urban,Data Analyst,25460,0 +90544,Female,28,Diploma,14,74,60,40,82,0.0,6,10,Urban,ML Engineer,92560,0 +90545,Female,30,High School,15,13,40,88,79,8.0,4,16,Urban,Software Engineer,43148,0 +90546,Male,52,Masters,2,17,78,22,91,6.0,7,58,Semi-Urban,HR Executive,120359,0 +90547,Male,55,Masters,1,89,8,7,30,7.0,0,4,Rural,ML Engineer,76279,0 +90548,Female,37,Masters,5,32,6,51,19,0.0,6,74,Rural,ML Engineer,25422,0 +90549,Female,30,Masters,1,72,57,87,88,1.0,5,64,Semi-Urban,Manager,27275,1 +90550,Female,42,Bachelors,8,0,13,23,14,4.0,6,92,Urban,Software Engineer,126451,0 +90551,Female,34,High School,1,99,39,97,96,9.0,7,3,Rural,HR Executive,50249,0 +90552,Male,25,Bachelors,5,4,63,81,19,6.0,1,29,Urban,Data Analyst,85179,0 +90553,Male,36,Masters,18,58,6,66,91,7.0,2,43,Urban,Data Analyst,63227,0 +90554,Male,47,Masters,10,54,60,73,38,5.0,7,18,Rural,Software Engineer,119113,0 +90555,Other,22,High School,5,7,92,77,26,0.0,3,47,Semi-Urban,Manager,134627,0 +90556,Other,32,High School,15,77,14,73,58,1.0,2,53,Urban,Manager,118524,0 +90557,Female,51,Bachelors,0,32,98,77,93,4.0,5,52,Rural,HR Executive,137119,1 +90558,Other,48,PhD,7,8,82,14,33,6.0,5,65,Urban,Manager,61904,0 +90559,Male,54,High School,7,42,37,3,17,6.0,6,39,Urban,Software Engineer,87907,0 +90560,Female,35,High School,9,68,98,38,28,9.0,3,86,Urban,Manager,43771,1 +90561,Male,30,Diploma,1,35,58,63,76,7.0,2,70,Semi-Urban,ML Engineer,63132,0 +90562,Female,23,High School,17,85,3,10,31,6.0,2,2,Semi-Urban,Data Analyst,99216,0 +90563,Female,48,Bachelors,13,52,74,56,11,8.0,3,18,Semi-Urban,Manager,102208,0 +90564,Female,48,Bachelors,3,23,60,30,17,0.0,5,87,Rural,Data Analyst,50178,0 +90565,Male,29,Bachelors,0,44,37,12,82,4.0,3,77,Semi-Urban,ML Engineer,99685,0 +90566,Other,24,Bachelors,7,5,57,13,96,8.0,7,21,Urban,Manager,27064,0 +90567,Male,23,High School,5,61,88,21,83,6.0,5,60,Urban,Software Engineer,73056,0 +90568,Female,26,Diploma,19,39,30,37,63,3.0,1,97,Semi-Urban,ML Engineer,82180,0 +90569,Female,31,Diploma,15,25,20,23,77,8.0,7,23,Semi-Urban,Manager,100988,0 +90570,Male,50,Bachelors,9,12,88,16,41,3.0,1,8,Rural,HR Executive,101196,0 +90571,Male,51,Diploma,15,54,87,88,80,0.0,7,34,Rural,ML Engineer,104098,1 +90572,Male,39,Bachelors,17,54,3,2,94,6.0,6,5,Urban,Software Engineer,113691,0 +90573,Male,28,Masters,2,6,17,30,56,4.0,6,40,Urban,Software Engineer,136877,0 +90574,Male,34,High School,5,98,34,58,15,3.0,6,26,Semi-Urban,Software Engineer,47731,0 +90575,Female,46,Diploma,4,1,82,7,66,9.0,0,28,Urban,Manager,72224,0 +90576,Male,46,High School,12,29,58,35,60,2.0,7,84,Semi-Urban,Data Analyst,149912,0 +90577,Female,35,Bachelors,14,75,65,54,90,0.0,2,5,Rural,Data Analyst,78189,0 +90578,Male,39,High School,3,82,9,49,65,5.0,4,58,Urban,Software Engineer,119444,0 +90579,Male,26,Diploma,4,76,28,14,34,9.0,1,73,Urban,Data Analyst,78621,0 +90580,Female,48,Bachelors,4,36,59,59,98,9.0,2,73,Rural,Manager,22575,0 +90581,Other,35,Diploma,3,23,33,17,7,5.0,6,51,Urban,ML Engineer,118670,0 +90582,Male,26,PhD,11,39,76,41,81,1.0,1,9,Urban,Software Engineer,128335,0 +90583,Female,48,Bachelors,1,5,57,22,10,3.0,2,80,Rural,HR Executive,111749,0 +90584,Male,53,Bachelors,14,22,89,94,23,9.0,1,26,Urban,Data Analyst,42455,0 +90585,Female,50,Masters,3,3,41,3,39,4.0,5,79,Urban,Software Engineer,36965,0 +90586,Female,29,PhD,9,61,93,59,34,5.0,2,28,Semi-Urban,Data Analyst,33799,1 +90587,Female,35,Bachelors,11,0,22,50,41,4.0,5,30,Rural,Software Engineer,51028,0 +90588,Female,34,Bachelors,5,6,49,14,35,9.0,2,63,Rural,Manager,80959,0 +90589,Male,23,High School,6,56,48,43,97,1.0,0,11,Urban,Manager,135299,0 +90590,Female,49,Diploma,1,42,77,30,87,5.0,0,78,Rural,Data Analyst,25209,0 +90591,Male,21,High School,11,14,49,43,61,9.0,4,83,Rural,ML Engineer,31611,0 +90592,Female,54,Masters,2,75,17,48,89,9.0,2,13,Semi-Urban,ML Engineer,51351,0 +90593,Male,49,Masters,18,68,22,59,53,9.0,5,27,Rural,Manager,76935,0 +90594,Male,34,High School,19,91,90,59,46,8.0,6,90,Urban,Data Analyst,102134,1 +90595,Male,45,Bachelors,2,65,59,17,24,4.0,3,44,Semi-Urban,Software Engineer,27151,0 +90596,Female,30,Masters,13,31,11,29,97,9.0,6,87,Rural,HR Executive,62196,0 +90597,Male,52,Diploma,8,72,27,57,32,7.0,7,46,Urban,ML Engineer,24842,0 +90598,Female,39,Diploma,3,54,78,74,76,1.0,5,91,Semi-Urban,Data Analyst,107538,1 +90599,Female,57,Bachelors,2,36,93,65,49,9.0,3,36,Urban,Manager,32866,0 +90600,Male,46,Masters,0,98,11,87,62,1.0,7,0,Rural,HR Executive,35504,0 +90601,Female,23,Masters,19,40,33,51,33,1.0,6,10,Urban,Data Analyst,37737,0 +90602,Female,22,Diploma,16,82,1,2,28,0.0,6,47,Urban,Data Analyst,33865,0 +90603,Male,22,Masters,0,91,41,41,12,5.0,7,26,Urban,Data Analyst,86421,0 +90604,Female,53,High School,16,10,10,45,26,9.0,3,66,Rural,ML Engineer,116260,0 +90605,Male,25,Bachelors,13,67,55,48,68,1.0,6,14,Semi-Urban,HR Executive,77412,0 +90606,Male,29,Bachelors,9,50,86,84,95,1.0,5,51,Urban,Data Analyst,105168,1 +90607,Male,26,High School,19,29,60,67,22,4.0,3,57,Rural,Software Engineer,96479,0 +90608,Male,30,Bachelors,5,44,13,54,66,5.0,0,6,Urban,Software Engineer,108848,0 +90609,Other,36,High School,15,27,19,13,50,1.0,4,37,Urban,ML Engineer,108051,0 +90610,Male,43,PhD,15,97,47,10,9,1.0,2,30,Rural,Software Engineer,77380,0 +90611,Male,43,Masters,3,56,94,38,22,1.0,2,26,Urban,Manager,27919,0 +90612,Female,48,Bachelors,17,71,29,23,72,8.0,1,16,Urban,Software Engineer,114914,0 +90613,Male,24,High School,12,87,94,58,99,5.0,2,23,Urban,Data Analyst,60681,1 +90614,Male,54,Bachelors,13,52,64,42,86,9.0,7,18,Semi-Urban,HR Executive,90933,0 +90615,Male,24,High School,6,78,38,79,50,8.0,5,90,Urban,Manager,134047,1 +90616,Male,34,Bachelors,17,2,13,30,28,8.0,5,67,Urban,Data Analyst,55987,0 +90617,Female,58,Masters,17,65,30,8,96,3.0,3,99,Semi-Urban,Manager,24108,0 +90618,Male,47,High School,15,79,97,13,39,8.0,5,16,Semi-Urban,ML Engineer,81179,0 +90619,Male,35,Bachelors,10,58,34,80,44,3.0,3,29,Rural,ML Engineer,99122,0 +90620,Female,57,Diploma,9,79,63,60,0,7.0,1,40,Urban,Software Engineer,94887,1 +90621,Male,23,PhD,8,6,22,26,6,7.0,4,61,Semi-Urban,HR Executive,29350,0 +90622,Female,44,Masters,9,38,40,4,3,3.0,7,2,Urban,HR Executive,144227,0 +90623,Other,44,Bachelors,13,97,26,66,44,8.0,5,93,Urban,Software Engineer,144700,1 +90624,Female,54,High School,15,12,40,90,33,3.0,5,26,Urban,Software Engineer,84610,0 +90625,Female,50,Diploma,19,72,77,15,47,5.0,4,54,Semi-Urban,ML Engineer,48741,0 +90626,Male,56,Diploma,5,89,92,80,56,4.0,5,55,Semi-Urban,HR Executive,42059,1 +90627,Female,30,Bachelors,2,30,50,90,12,8.0,0,78,Semi-Urban,HR Executive,28593,1 +90628,Male,35,Masters,6,55,64,67,30,4.0,2,47,Urban,ML Engineer,81466,0 +90629,Other,38,Bachelors,19,78,13,54,51,2.0,6,63,Semi-Urban,Software Engineer,92822,0 +90630,Female,54,Bachelors,18,48,98,26,45,5.0,2,32,Urban,Manager,39273,0 +90631,Male,49,Bachelors,2,77,27,79,69,0.0,0,75,Rural,Manager,144361,1 +90632,Male,30,Bachelors,10,85,43,74,95,1.0,7,16,Semi-Urban,Software Engineer,21440,0 +90633,Male,54,Bachelors,15,3,43,90,30,6.0,5,17,Urban,ML Engineer,42157,0 +90634,Male,28,High School,8,79,93,67,91,7.0,2,12,Semi-Urban,ML Engineer,82365,1 +90635,Female,29,PhD,12,27,21,11,81,3.0,0,38,Rural,HR Executive,25133,0 +90636,Male,27,Masters,14,35,76,29,51,8.0,2,38,Rural,Data Analyst,40523,0 +90637,Male,23,Bachelors,19,97,16,82,54,6.0,7,43,Semi-Urban,ML Engineer,65347,1 +90638,Male,42,Bachelors,11,67,24,98,61,6.0,4,94,Urban,ML Engineer,86933,1 +90639,Male,27,Bachelors,8,79,31,50,60,2.0,5,10,Semi-Urban,Data Analyst,108009,0 +90640,Male,33,Diploma,16,21,49,35,71,0.0,6,99,Rural,Software Engineer,75639,0 +90641,Male,51,Diploma,0,65,99,60,95,3.0,6,72,Urban,ML Engineer,59095,1 +90642,Male,22,PhD,13,25,32,56,69,1.0,3,54,Urban,Data Analyst,141802,0 +90643,Female,46,Bachelors,3,7,82,77,25,0.0,0,88,Rural,Manager,136862,1 +90644,Other,57,Bachelors,19,48,11,6,1,7.0,1,42,Semi-Urban,Data Analyst,96711,0 +90645,Male,49,Bachelors,8,9,99,71,41,2.0,3,46,Urban,Data Analyst,53470,0 +90646,Male,45,Masters,11,64,80,55,73,8.0,6,21,Urban,Data Analyst,143336,0 +90647,Female,32,Bachelors,19,31,44,29,79,7.0,2,50,Urban,ML Engineer,95830,0 +90648,Male,27,PhD,17,18,28,18,54,1.0,5,17,Rural,Data Analyst,86056,0 +90649,Male,44,Diploma,3,43,83,67,54,0.0,2,82,Rural,Software Engineer,50169,1 +90650,Female,46,Masters,16,20,16,88,62,8.0,3,30,Rural,Manager,137828,0 +90651,Female,39,PhD,1,32,18,83,38,5.0,0,76,Urban,Software Engineer,79956,0 +90652,Female,48,Bachelors,6,56,67,80,54,1.0,4,7,Rural,Manager,107704,0 +90653,Female,58,Masters,13,91,62,23,1,4.0,6,20,Urban,Manager,27833,0 +90654,Male,28,High School,10,47,77,75,61,3.0,3,58,Semi-Urban,ML Engineer,56901,1 +90655,Male,50,Bachelors,8,42,42,68,10,8.0,6,63,Semi-Urban,HR Executive,121365,0 +90656,Other,35,Bachelors,12,81,70,88,91,4.0,1,7,Semi-Urban,Manager,103782,1 +90657,Female,35,Masters,14,86,84,46,46,5.0,6,24,Semi-Urban,ML Engineer,60900,0 +90658,Male,41,Diploma,10,90,92,87,35,8.0,0,89,Urban,Data Analyst,63933,1 +90659,Male,59,Bachelors,13,11,17,70,28,4.0,4,59,Urban,ML Engineer,109817,0 +90660,Female,58,Bachelors,0,91,37,5,19,7.0,4,64,Urban,HR Executive,92161,0 +90661,Male,37,Bachelors,6,79,77,79,37,9.0,7,90,Semi-Urban,Manager,120602,1 +90662,Female,39,Diploma,1,25,0,56,87,7.0,5,17,Rural,ML Engineer,39513,0 +90663,Male,31,Diploma,15,62,6,78,6,4.0,6,65,Urban,HR Executive,26307,0 +90664,Male,42,Diploma,17,96,49,1,87,8.0,6,0,Urban,Data Analyst,105959,0 +90665,Male,31,Bachelors,12,8,45,89,44,2.0,7,44,Urban,Manager,89653,0 +90666,Male,22,Diploma,0,71,72,62,37,0.0,2,25,Urban,Software Engineer,118245,0 +90667,Male,53,Diploma,6,38,95,9,60,4.0,5,59,Rural,Manager,32108,0 +90668,Male,24,Bachelors,13,69,35,44,0,8.0,3,60,Urban,Manager,105602,0 +90669,Female,31,PhD,11,25,40,72,23,4.0,6,11,Urban,ML Engineer,56925,0 +90670,Male,50,Masters,12,84,20,38,97,6.0,5,16,Rural,Software Engineer,122781,0 +90671,Other,49,High School,17,40,69,78,77,1.0,4,79,Semi-Urban,HR Executive,65090,1 +90672,Female,59,Masters,14,60,53,55,17,8.0,2,9,Urban,ML Engineer,77275,0 +90673,Female,22,Diploma,15,23,39,99,16,0.0,6,7,Rural,HR Executive,31918,0 +90674,Male,40,Bachelors,15,93,12,14,91,5.0,6,98,Urban,ML Engineer,70031,0 +90675,Male,50,Masters,5,25,9,37,95,7.0,4,63,Urban,HR Executive,129265,0 +90676,Male,40,High School,19,4,91,44,76,7.0,4,44,Rural,ML Engineer,119268,0 +90677,Male,53,PhD,1,57,16,78,41,0.0,1,55,Urban,ML Engineer,132584,0 +90678,Male,50,High School,17,68,73,82,80,3.0,2,96,Rural,Software Engineer,68220,1 +90679,Female,36,Bachelors,14,22,14,88,83,5.0,5,77,Rural,Manager,22236,0 +90680,Male,22,High School,11,0,22,55,3,6.0,3,63,Urban,Manager,113976,0 +90681,Female,45,Bachelors,17,81,68,70,23,4.0,7,78,Urban,Data Analyst,114835,1 +90682,Other,46,Bachelors,16,94,10,42,49,8.0,0,59,Rural,ML Engineer,127342,0 +90683,Male,45,Masters,18,52,72,86,74,3.0,0,29,Semi-Urban,Software Engineer,31436,1 +90684,Male,21,High School,19,98,50,35,9,1.0,0,26,Urban,ML Engineer,73434,0 +90685,Male,46,High School,2,20,22,43,42,3.0,7,12,Urban,HR Executive,131375,0 +90686,Male,49,Diploma,13,22,66,46,40,3.0,3,80,Urban,HR Executive,107597,0 +90687,Male,30,Diploma,15,83,43,36,90,3.0,4,93,Urban,ML Engineer,115255,1 +90688,Male,30,Bachelors,13,93,57,6,81,2.0,7,5,Urban,HR Executive,103760,0 +90689,Female,42,Diploma,11,24,21,60,63,3.0,0,45,Urban,Manager,34366,0 +90690,Male,36,Diploma,17,12,56,48,59,3.0,1,53,Urban,Software Engineer,110710,0 +90691,Male,38,Diploma,0,78,9,1,8,6.0,7,4,Urban,HR Executive,50572,0 +90692,Other,21,PhD,7,59,65,89,20,1.0,6,31,Urban,ML Engineer,137273,1 +90693,Female,29,Bachelors,6,95,49,61,31,3.0,6,64,Urban,Manager,97747,1 +90694,Male,48,Masters,15,25,87,83,32,1.0,3,98,Semi-Urban,HR Executive,73548,1 +90695,Male,45,Bachelors,11,77,43,77,12,3.0,1,75,Semi-Urban,ML Engineer,30354,1 +90696,Female,34,Masters,3,68,46,6,18,3.0,5,54,Urban,Software Engineer,147062,0 +90697,Female,45,Masters,18,48,78,4,41,2.0,0,80,Semi-Urban,Data Analyst,20383,0 +90698,Male,26,Diploma,6,48,96,81,61,8.0,6,74,Semi-Urban,Manager,22920,1 +90699,Female,22,High School,4,58,98,12,4,7.0,3,10,Rural,ML Engineer,129222,0 +90700,Male,31,PhD,18,69,93,71,67,5.0,2,60,Urban,Software Engineer,40565,1 +90701,Male,38,Masters,13,53,64,4,65,0.0,6,4,Urban,Data Analyst,88890,0 +90702,Female,53,Bachelors,15,23,68,59,95,9.0,5,76,Urban,Software Engineer,108523,0 +90703,Male,56,Masters,0,9,34,4,43,6.0,2,51,Semi-Urban,ML Engineer,84310,0 +90704,Female,24,Bachelors,16,13,95,12,90,7.0,0,55,Urban,Software Engineer,67696,0 +90705,Male,51,Bachelors,13,73,51,21,40,1.0,0,34,Urban,HR Executive,27877,0 +90706,Female,25,Masters,19,23,2,65,73,9.0,7,66,Rural,ML Engineer,90663,0 +90707,Male,49,Bachelors,12,76,61,68,75,7.0,7,40,Rural,ML Engineer,113440,1 +90708,Male,52,Bachelors,2,46,43,61,1,1.0,7,54,Rural,Manager,45941,0 +90709,Other,46,Bachelors,11,18,4,52,3,0.0,0,39,Rural,HR Executive,128511,0 +90710,Male,46,Masters,6,54,20,92,22,4.0,6,24,Urban,Data Analyst,124332,0 +90711,Female,30,Masters,13,5,35,14,66,0.0,2,79,Rural,ML Engineer,30532,0 +90712,Female,23,High School,14,40,28,6,20,4.0,4,5,Semi-Urban,Manager,73481,0 +90713,Female,59,Bachelors,1,47,41,50,89,2.0,0,77,Urban,Software Engineer,90155,0 +90714,Female,40,PhD,10,39,4,88,34,9.0,6,80,Semi-Urban,ML Engineer,133981,0 +90715,Other,52,Diploma,17,90,19,69,25,1.0,3,88,Semi-Urban,Data Analyst,92568,1 +90716,Male,34,Bachelors,18,5,26,94,89,6.0,1,66,Urban,ML Engineer,119841,0 +90717,Male,39,High School,1,61,93,59,28,0.0,7,8,Urban,Manager,55321,0 +90718,Male,42,Diploma,5,16,83,71,15,9.0,6,66,Urban,Manager,134045,1 +90719,Male,28,Diploma,6,15,94,66,44,2.0,6,79,Urban,ML Engineer,81557,1 +90720,Female,24,Masters,7,76,65,81,84,7.0,4,63,Semi-Urban,Software Engineer,49489,1 +90721,Male,55,Bachelors,19,72,28,89,38,4.0,2,43,Rural,Data Analyst,42030,0 +90722,Male,28,Bachelors,10,62,91,12,52,6.0,0,21,Urban,HR Executive,38904,0 +90723,Female,45,Bachelors,11,8,52,77,63,1.0,1,34,Rural,Software Engineer,70398,0 +90724,Male,36,Bachelors,6,78,9,34,66,6.0,4,65,Urban,HR Executive,143244,0 +90725,Male,44,High School,6,85,2,9,95,0.0,6,87,Urban,Software Engineer,91293,0 +90726,Female,50,Masters,6,8,86,67,5,4.0,5,15,Urban,ML Engineer,109457,0 +90727,Female,25,Masters,16,39,75,79,76,1.0,4,11,Urban,Software Engineer,81114,0 +90728,Male,36,Diploma,1,53,82,73,64,1.0,3,40,Rural,Data Analyst,102448,1 +90729,Male,47,High School,3,35,39,89,54,7.0,2,85,Urban,Manager,99605,1 +90730,Male,26,Bachelors,10,75,84,27,72,6.0,5,6,Urban,HR Executive,123760,0 +90731,Male,49,High School,4,84,69,73,73,6.0,3,49,Semi-Urban,Manager,64656,1 +90732,Male,57,Diploma,8,41,76,46,8,4.0,6,64,Urban,Manager,56819,0 +90733,Male,41,Masters,6,90,66,57,90,2.0,6,45,Semi-Urban,ML Engineer,40355,1 +90734,Male,58,Bachelors,14,14,92,65,7,7.0,0,98,Urban,Data Analyst,95509,1 +90735,Male,55,PhD,18,42,41,12,50,8.0,4,16,Rural,Data Analyst,87617,0 +90736,Male,54,High School,9,94,10,63,4,7.0,6,44,Urban,ML Engineer,105413,0 +90737,Male,55,PhD,4,7,93,41,91,0.0,0,83,Urban,Software Engineer,88938,0 +90738,Male,33,Masters,16,4,74,15,43,6.0,7,13,Rural,HR Executive,60825,0 +90739,Male,35,Bachelors,13,91,96,36,21,8.0,5,84,Urban,Software Engineer,25201,1 +90740,Male,25,Bachelors,0,2,25,42,67,7.0,1,49,Urban,HR Executive,63351,0 +90741,Female,22,Diploma,4,23,58,2,85,1.0,4,25,Urban,Manager,142795,0 +90742,Other,35,Masters,19,37,3,3,28,3.0,7,63,Semi-Urban,Software Engineer,58130,0 +90743,Male,58,Diploma,1,92,29,32,44,5.0,2,80,Semi-Urban,Manager,73229,0 +90744,Other,57,Diploma,6,65,37,7,68,9.0,0,88,Rural,Data Analyst,102360,0 +90745,Male,41,Bachelors,12,35,86,19,81,1.0,7,3,Urban,Manager,39695,0 +90746,Female,46,High School,11,27,70,60,69,3.0,0,11,Semi-Urban,ML Engineer,103127,0 +90747,Female,44,Bachelors,12,51,7,24,42,5.0,1,91,Semi-Urban,ML Engineer,112170,0 +90748,Male,30,Masters,5,64,26,31,70,6.0,7,55,Urban,Manager,122601,0 +90749,Male,32,High School,13,6,38,76,36,5.0,1,91,Urban,HR Executive,147256,0 +90750,Male,24,Diploma,19,35,39,21,6,4.0,6,56,Semi-Urban,Software Engineer,145805,0 +90751,Female,24,High School,16,14,59,59,85,8.0,2,50,Urban,Manager,27108,0 +90752,Female,22,High School,17,42,16,19,73,6.0,5,36,Semi-Urban,ML Engineer,111266,0 +90753,Male,36,Bachelors,2,44,6,88,85,8.0,7,48,Urban,Software Engineer,145473,0 +90754,Female,42,Bachelors,7,62,72,80,62,6.0,1,48,Urban,Software Engineer,92723,1 +90755,Male,55,Bachelors,13,52,92,82,52,9.0,0,39,Rural,HR Executive,66594,1 +90756,Female,51,Bachelors,12,29,33,52,74,0.0,0,83,Urban,Software Engineer,75994,0 +90757,Female,38,Diploma,11,30,49,73,15,0.0,4,19,Urban,ML Engineer,68636,0 +90758,Female,33,Diploma,5,95,64,18,4,1.0,6,25,Semi-Urban,Manager,116938,0 +90759,Female,33,Masters,13,86,85,93,96,2.0,3,3,Semi-Urban,Manager,37209,1 +90760,Female,58,Bachelors,6,75,82,0,8,0.0,0,19,Urban,HR Executive,41540,0 +90761,Male,35,Bachelors,14,44,72,20,79,5.0,6,47,Urban,Software Engineer,139525,0 +90762,Female,46,Masters,18,65,14,28,20,1.0,3,35,Urban,ML Engineer,57642,0 +90763,Male,56,Bachelors,12,75,98,0,1,0.0,4,4,Rural,Manager,86264,0 +90764,Male,30,Diploma,9,21,9,49,78,4.0,3,40,Urban,Manager,113645,0 +90765,Male,48,Bachelors,7,29,66,28,62,9.0,2,4,Rural,Manager,135745,0 +90766,Male,52,Bachelors,3,46,11,38,40,8.0,3,16,Rural,Data Analyst,108010,0 +90767,Male,55,Bachelors,6,71,2,95,73,4.0,0,24,Urban,Manager,72759,0 +90768,Female,45,Masters,2,7,18,13,89,5.0,4,85,Semi-Urban,ML Engineer,64240,0 +90769,Male,25,Bachelors,16,53,77,91,56,0.0,0,96,Semi-Urban,Software Engineer,86504,1 +90770,Female,57,Bachelors,9,29,80,92,79,1.0,5,94,Semi-Urban,Manager,49390,1 +90771,Male,43,High School,13,69,4,63,14,7.0,6,14,Urban,HR Executive,132477,0 +90772,Female,36,Diploma,18,40,39,31,60,8.0,4,65,Urban,Data Analyst,48874,0 +90773,Male,36,PhD,11,93,55,5,18,5.0,5,51,Urban,ML Engineer,148823,0 +90774,Female,30,Bachelors,8,13,28,40,26,0.0,3,85,Urban,Manager,21559,0 +90775,Male,41,Bachelors,17,45,87,36,87,7.0,3,67,Rural,ML Engineer,74543,1 +90776,Male,45,Bachelors,10,17,43,26,47,1.0,6,28,Rural,Software Engineer,93809,0 +90777,Male,41,Bachelors,16,45,41,39,60,6.0,0,68,Semi-Urban,Data Analyst,62238,0 +90778,Male,24,Masters,15,71,82,13,68,1.0,6,19,Rural,Data Analyst,62956,0 +90779,Male,42,Bachelors,19,39,55,21,81,2.0,3,61,Urban,ML Engineer,94536,0 +90780,Male,26,Masters,13,2,41,99,79,0.0,2,5,Urban,Data Analyst,122513,0 +90781,Male,32,Diploma,18,89,38,8,0,7.0,2,68,Urban,Data Analyst,41853,0 +90782,Male,56,Bachelors,13,86,94,19,21,6.0,4,20,Rural,Software Engineer,46033,0 +90783,Female,39,Diploma,0,57,51,22,78,2.0,4,88,Semi-Urban,Software Engineer,119405,0 +90784,Male,23,High School,19,48,8,27,21,1.0,4,56,Rural,ML Engineer,113440,0 +90785,Male,50,Masters,5,98,84,28,91,4.0,5,91,Rural,Software Engineer,123772,1 +90786,Male,32,Diploma,12,87,38,84,52,3.0,2,34,Semi-Urban,Data Analyst,100631,1 +90787,Male,31,Bachelors,6,36,86,77,27,6.0,1,42,Urban,HR Executive,39040,1 +90788,Male,21,Bachelors,10,37,61,9,65,5.0,4,86,Urban,Software Engineer,148067,0 +90789,Male,57,High School,18,10,15,65,93,1.0,3,0,Urban,Manager,45321,0 +90790,Male,45,Diploma,14,79,6,63,85,2.0,7,92,Semi-Urban,HR Executive,118234,1 +90791,Male,40,Diploma,19,69,86,69,25,4.0,0,7,Urban,Manager,49640,0 +90792,Female,31,Masters,9,38,37,54,75,7.0,0,57,Urban,Data Analyst,138584,0 +90793,Male,39,Bachelors,1,92,82,27,21,4.0,3,56,Urban,ML Engineer,108831,1 +90794,Female,54,Bachelors,15,36,88,96,88,2.0,3,30,Semi-Urban,ML Engineer,90850,1 +90795,Female,34,Masters,16,57,17,62,43,0.0,4,93,Urban,Data Analyst,136776,0 +90796,Female,25,Bachelors,11,92,50,90,79,7.0,5,70,Semi-Urban,ML Engineer,52064,1 +90797,Female,29,Masters,17,61,33,94,71,8.0,6,89,Urban,Software Engineer,96179,1 +90798,Female,35,Diploma,12,33,68,86,68,3.0,0,34,Urban,Data Analyst,120569,0 +90799,Other,58,Diploma,1,71,16,7,2,7.0,1,81,Urban,Manager,116758,0 +90800,Male,30,Masters,17,7,28,5,31,6.0,5,39,Urban,Software Engineer,147603,0 +90801,Female,30,Diploma,17,37,38,16,41,9.0,2,69,Urban,Manager,20158,0 +90802,Female,24,Bachelors,5,4,27,21,73,4.0,6,78,Rural,Data Analyst,82676,0 +90803,Male,57,Masters,14,83,49,55,20,5.0,6,61,Urban,HR Executive,26834,1 +90804,Male,35,Bachelors,16,60,11,30,88,1.0,2,34,Rural,Manager,55325,0 +90805,Male,27,Bachelors,8,85,68,14,27,8.0,0,52,Urban,ML Engineer,57672,0 +90806,Male,29,Bachelors,2,88,94,65,37,4.0,7,81,Urban,Software Engineer,112277,1 +90807,Male,54,Bachelors,14,68,95,30,89,8.0,0,5,Urban,Data Analyst,125368,0 +90808,Male,30,Bachelors,17,71,54,53,7,0.0,0,79,Urban,Software Engineer,71085,1 +90809,Male,52,PhD,19,46,85,87,36,4.0,1,8,Semi-Urban,Software Engineer,33155,0 +90810,Male,44,Bachelors,13,31,67,65,2,2.0,4,86,Rural,HR Executive,84479,1 +90811,Male,44,Masters,0,69,5,93,31,4.0,1,10,Semi-Urban,HR Executive,54417,0 +90812,Female,36,Diploma,4,31,50,67,49,3.0,1,22,Semi-Urban,Software Engineer,68013,0 +90813,Female,36,Diploma,3,28,92,40,64,9.0,7,96,Rural,Software Engineer,23324,1 +90814,Male,59,Bachelors,14,46,39,83,28,1.0,1,58,Semi-Urban,Data Analyst,111248,0 +90815,Male,29,Bachelors,5,53,75,60,51,4.0,0,1,Rural,Manager,66291,0 +90816,Female,28,Masters,6,90,72,86,73,3.0,5,86,Semi-Urban,Data Analyst,90155,1 +90817,Male,51,PhD,0,89,33,23,3,5.0,0,28,Urban,Manager,45432,0 +90818,Other,55,High School,0,48,9,57,24,8.0,3,78,Rural,Software Engineer,119074,0 +90819,Male,27,Bachelors,2,92,4,59,53,5.0,1,3,Urban,Data Analyst,85016,0 +90820,Male,31,Bachelors,15,41,50,40,7,0.0,0,50,Urban,HR Executive,40618,0 +90821,Male,29,Diploma,8,43,68,37,51,1.0,1,26,Semi-Urban,Data Analyst,51109,0 +90822,Male,57,Bachelors,15,35,10,77,18,6.0,7,34,Semi-Urban,Data Analyst,20324,0 +90823,Male,51,Diploma,5,47,30,90,57,6.0,6,18,Urban,ML Engineer,115555,0 +90824,Male,41,Bachelors,4,82,58,83,12,4.0,4,57,Urban,Manager,128303,1 +90825,Male,37,Bachelors,0,74,33,31,90,8.0,5,4,Urban,HR Executive,89142,0 +90826,Male,21,High School,4,10,70,71,58,2.0,4,30,Rural,HR Executive,39358,0 +90827,Female,21,Diploma,1,54,42,99,68,0.0,6,51,Urban,Software Engineer,128476,1 +90828,Female,36,Diploma,3,71,1,56,1,9.0,5,13,Urban,Manager,122025,0 +90829,Male,29,Bachelors,7,51,27,79,71,2.0,4,73,Urban,Data Analyst,131229,0 +90830,Female,29,Bachelors,7,29,19,80,10,0.0,5,31,Urban,ML Engineer,96616,0 +90831,Male,39,Bachelors,9,58,48,83,6,2.0,0,72,Rural,Software Engineer,39682,1 +90832,Male,27,Masters,3,18,94,46,70,0.0,0,9,Urban,ML Engineer,115912,0 +90833,Male,22,Bachelors,11,24,87,75,91,1.0,1,31,Urban,HR Executive,120064,0 +90834,Male,44,Bachelors,13,34,33,53,97,0.0,1,57,Urban,Software Engineer,78405,0 +90835,Female,45,Masters,7,69,50,67,37,9.0,0,59,Rural,Data Analyst,142912,1 +90836,Male,36,Bachelors,2,85,47,96,74,1.0,7,39,Urban,Data Analyst,96681,1 +90837,Female,50,Diploma,2,99,92,78,21,5.0,1,50,Urban,Manager,42251,1 +90838,Male,48,Bachelors,14,97,28,87,9,9.0,4,85,Urban,Manager,31689,1 +90839,Male,51,Masters,8,92,29,49,44,2.0,3,98,Urban,Data Analyst,107917,1 +90840,Female,59,Bachelors,17,3,53,67,74,5.0,6,46,Urban,HR Executive,141690,0 +90841,Male,28,Bachelors,6,15,28,10,33,1.0,0,96,Rural,HR Executive,100854,0 +90842,Female,49,Bachelors,15,66,27,81,75,0.0,0,31,Semi-Urban,HR Executive,83494,0 +90843,Male,37,Diploma,13,42,8,14,65,5.0,4,8,Urban,HR Executive,69163,0 +90844,Other,40,Bachelors,16,68,51,16,75,7.0,7,29,Rural,Software Engineer,97078,0 +90845,Other,33,Bachelors,9,92,19,31,47,9.0,4,12,Urban,HR Executive,102904,0 +90846,Female,53,Bachelors,13,90,70,3,94,6.0,1,5,Urban,ML Engineer,59976,0 +90847,Female,50,Diploma,14,69,70,42,2,7.0,1,26,Rural,HR Executive,111675,0 +90848,Female,58,Diploma,2,34,33,5,71,7.0,4,29,Rural,ML Engineer,24492,0 +90849,Female,32,Diploma,0,99,10,30,55,4.0,5,35,Rural,Software Engineer,112774,0 +90850,Female,33,Diploma,16,47,90,73,39,4.0,0,13,Urban,HR Executive,38917,0 +90851,Female,38,Bachelors,7,7,21,98,63,7.0,1,28,Urban,HR Executive,40965,0 +90852,Female,54,Bachelors,11,50,31,36,47,0.0,3,10,Rural,ML Engineer,136193,0 +90853,Female,27,Bachelors,16,26,7,30,49,2.0,3,2,Rural,Data Analyst,125258,0 +90854,Female,37,Diploma,5,3,9,19,5,2.0,2,89,Urban,Software Engineer,108394,0 +90855,Other,38,Bachelors,8,47,17,9,4,6.0,7,62,Urban,Software Engineer,46441,0 +90856,Male,44,Diploma,8,88,16,8,95,8.0,4,32,Urban,HR Executive,70829,0 +90857,Female,43,Diploma,1,87,40,37,5,8.0,7,99,Rural,Data Analyst,139122,1 +90858,Male,34,Masters,16,84,77,14,33,4.0,3,81,Semi-Urban,ML Engineer,31005,1 +90859,Male,27,Bachelors,15,74,71,96,95,9.0,4,5,Semi-Urban,HR Executive,121195,1 +90860,Male,59,Bachelors,10,5,25,42,60,5.0,5,38,Urban,HR Executive,125662,0 +90861,Male,34,Bachelors,11,61,25,40,17,6.0,2,88,Urban,Software Engineer,135643,0 +90862,Female,41,Bachelors,12,62,68,53,77,2.0,7,84,Semi-Urban,ML Engineer,32068,1 +90863,Male,53,Diploma,1,57,96,19,82,4.0,7,48,Urban,HR Executive,25364,0 +90864,Male,24,PhD,17,39,19,33,82,5.0,4,35,Urban,Data Analyst,112266,0 +90865,Female,51,Bachelors,10,89,83,78,63,5.0,1,29,Rural,Software Engineer,83529,1 +90866,Male,35,PhD,0,21,97,40,77,7.0,4,2,Rural,Data Analyst,69451,0 +90867,Male,54,Masters,16,32,18,99,64,4.0,2,17,Urban,ML Engineer,141996,0 +90868,Male,38,PhD,19,82,49,66,62,5.0,7,53,Urban,Data Analyst,62356,1 +90869,Male,55,Diploma,8,45,88,44,77,0.0,5,82,Semi-Urban,Software Engineer,117056,1 +90870,Male,25,Bachelors,9,32,16,51,40,1.0,1,18,Urban,ML Engineer,51593,0 +90871,Female,59,High School,4,93,55,19,89,9.0,2,97,Urban,Data Analyst,93214,1 +90872,Male,49,Bachelors,9,19,18,87,90,8.0,1,4,Urban,Software Engineer,110236,0 +90873,Male,52,High School,1,77,75,63,2,0.0,0,62,Urban,Manager,37468,1 +90874,Male,31,High School,3,93,42,7,96,2.0,0,64,Rural,Data Analyst,35781,0 +90875,Male,29,Bachelors,9,31,60,9,47,5.0,4,39,Urban,Manager,37108,0 +90876,Male,26,PhD,10,51,74,94,97,1.0,6,72,Rural,Software Engineer,35828,1 +90877,Male,21,Bachelors,4,63,67,91,7,8.0,2,26,Semi-Urban,ML Engineer,34134,1 +90878,Female,39,Diploma,1,1,90,38,51,1.0,2,29,Semi-Urban,ML Engineer,82895,0 +90879,Male,44,Masters,6,16,71,73,87,7.0,2,20,Urban,ML Engineer,81978,0 +90880,Other,35,Bachelors,6,33,59,97,43,5.0,1,59,Urban,Software Engineer,95352,1 +90881,Male,48,Diploma,19,53,74,0,80,8.0,6,59,Rural,Data Analyst,134252,0 +90882,Female,38,Diploma,3,45,19,63,55,5.0,0,22,Urban,ML Engineer,101235,0 +90883,Male,45,High School,8,26,42,90,71,4.0,0,4,Urban,Manager,91287,0 +90884,Male,59,Bachelors,19,1,35,33,74,7.0,6,78,Urban,Manager,92228,0 +90885,Male,29,Bachelors,11,11,7,88,90,6.0,0,62,Rural,Data Analyst,64544,0 +90886,Male,54,Bachelors,16,52,52,2,1,0.0,7,11,Semi-Urban,Data Analyst,92065,0 +90887,Female,52,Masters,15,11,14,12,22,8.0,5,60,Urban,ML Engineer,129097,0 +90888,Male,23,Diploma,11,35,98,7,49,9.0,4,73,Urban,Data Analyst,148735,0 +90889,Male,45,Diploma,0,45,65,68,19,6.0,5,0,Semi-Urban,Data Analyst,23745,0 +90890,Female,28,Masters,1,72,63,53,54,8.0,6,21,Semi-Urban,ML Engineer,78410,0 +90891,Male,56,Bachelors,19,9,95,95,46,6.0,7,94,Rural,Data Analyst,22930,1 +90892,Male,30,PhD,3,40,22,92,39,2.0,2,73,Urban,Data Analyst,48221,0 +90893,Male,51,Masters,10,39,66,3,30,2.0,5,60,Rural,HR Executive,66065,0 +90894,Other,21,High School,7,37,44,93,62,5.0,6,16,Semi-Urban,Manager,42221,0 +90895,Male,29,Diploma,9,76,22,51,81,5.0,4,80,Urban,Manager,123017,0 +90896,Female,31,Bachelors,15,92,97,24,60,9.0,0,71,Rural,HR Executive,70958,1 +90897,Male,41,Bachelors,18,34,20,77,17,1.0,3,32,Urban,HR Executive,44849,0 +90898,Male,27,High School,19,76,66,48,21,4.0,6,1,Rural,Data Analyst,42252,0 +90899,Female,24,Diploma,9,11,2,73,78,2.0,1,53,Urban,HR Executive,48753,0 +90900,Male,50,Diploma,18,96,24,71,73,3.0,7,18,Semi-Urban,Software Engineer,128601,0 +90901,Male,21,Masters,11,10,83,2,58,8.0,4,99,Urban,ML Engineer,31076,0 +90902,Female,47,PhD,6,86,1,34,85,8.0,3,80,Rural,Manager,130163,0 +90903,Female,51,Bachelors,15,23,26,57,17,4.0,6,47,Urban,ML Engineer,46493,0 +90904,Male,30,Masters,16,75,20,84,66,0.0,3,56,Rural,Software Engineer,134668,1 +90905,Male,47,Bachelors,0,83,68,11,28,3.0,6,28,Urban,ML Engineer,87198,0 +90906,Male,39,Bachelors,18,52,62,96,99,8.0,5,1,Rural,HR Executive,100942,0 +90907,Other,59,PhD,14,32,79,34,65,1.0,6,85,Semi-Urban,Manager,134588,0 +90908,Male,24,Bachelors,0,43,83,3,72,3.0,1,38,Urban,Manager,25446,0 +90909,Male,46,Diploma,12,4,18,57,72,0.0,7,25,Rural,ML Engineer,48336,0 +90910,Female,22,Diploma,15,44,37,4,62,5.0,3,22,Rural,ML Engineer,49762,0 +90911,Male,33,Bachelors,14,62,91,16,93,7.0,0,60,Urban,Data Analyst,142133,0 +90912,Female,24,PhD,7,66,63,70,23,7.0,6,40,Urban,Data Analyst,82288,0 +90913,Female,45,Bachelors,17,26,42,19,52,4.0,2,95,Semi-Urban,ML Engineer,115950,0 +90914,Male,24,Masters,6,19,12,1,16,8.0,0,27,Rural,Manager,116955,0 +90915,Male,37,Diploma,10,26,62,22,53,9.0,3,15,Semi-Urban,HR Executive,95008,0 +90916,Male,45,Masters,3,18,29,97,63,4.0,1,37,Rural,Manager,44321,0 +90917,Male,57,Bachelors,16,94,35,91,33,8.0,2,98,Rural,Software Engineer,84215,1 +90918,Male,31,High School,18,50,98,60,83,0.0,3,34,Urban,HR Executive,117694,1 +90919,Female,40,Bachelors,11,5,38,1,19,6.0,3,40,Urban,Data Analyst,134767,0 +90920,Male,41,High School,4,88,17,68,96,0.0,1,77,Rural,ML Engineer,95228,1 +90921,Female,51,Bachelors,19,93,87,90,7,2.0,7,65,Rural,Data Analyst,33987,1 +90922,Female,56,Bachelors,13,69,42,17,79,5.0,3,48,Semi-Urban,HR Executive,115983,0 +90923,Female,37,Bachelors,1,64,83,16,76,4.0,4,78,Urban,Software Engineer,134701,1 +90924,Male,50,Bachelors,3,25,86,66,20,9.0,1,11,Semi-Urban,ML Engineer,71566,0 +90925,Male,36,High School,1,73,57,21,74,4.0,2,30,Urban,Software Engineer,20551,0 +90926,Female,43,Diploma,10,76,2,12,11,4.0,1,50,Urban,Manager,57684,0 +90927,Male,41,Bachelors,19,3,27,84,1,5.0,3,58,Urban,HR Executive,99594,0 +90928,Male,55,High School,18,23,52,56,16,8.0,1,53,Urban,Software Engineer,60795,0 +90929,Female,27,Diploma,17,10,38,68,2,0.0,3,24,Semi-Urban,Data Analyst,106948,0 +90930,Male,51,Diploma,5,3,84,19,92,6.0,6,16,Semi-Urban,ML Engineer,75994,0 +90931,Male,31,Masters,16,66,35,85,2,1.0,5,22,Rural,ML Engineer,50396,0 +90932,Male,25,Bachelors,1,42,36,9,92,2.0,6,39,Rural,Manager,43569,0 +90933,Female,22,Diploma,7,3,87,67,66,3.0,6,25,Rural,HR Executive,112506,0 +90934,Female,22,Bachelors,14,9,59,11,16,2.0,4,24,Semi-Urban,HR Executive,76548,0 +90935,Male,43,Bachelors,7,38,76,63,96,6.0,2,62,Urban,Manager,87791,1 +90936,Male,37,Bachelors,0,30,55,40,83,4.0,2,56,Urban,Manager,103589,0 +90937,Female,40,PhD,12,71,65,9,64,1.0,7,26,Urban,ML Engineer,108495,0 +90938,Male,23,Diploma,6,53,7,32,16,4.0,3,5,Rural,Software Engineer,99144,0 +90939,Female,50,Masters,5,5,89,70,27,2.0,1,33,Urban,Manager,110009,0 +90940,Male,53,Bachelors,4,79,42,28,26,5.0,6,74,Rural,Data Analyst,24337,0 +90941,Male,54,Bachelors,12,6,97,58,15,9.0,4,42,Rural,Data Analyst,148533,0 +90942,Male,52,Bachelors,1,26,81,47,31,1.0,7,87,Urban,Software Engineer,64044,1 +90943,Female,39,Masters,16,20,9,71,3,9.0,2,38,Urban,HR Executive,105106,0 +90944,Male,58,Bachelors,0,80,55,90,99,8.0,5,2,Urban,Data Analyst,49917,0 +90945,Male,40,Masters,5,85,91,45,10,0.0,1,4,Urban,HR Executive,88879,0 +90946,Male,22,Diploma,4,56,53,17,88,0.0,2,88,Semi-Urban,Data Analyst,133702,0 +90947,Male,42,Bachelors,13,95,35,80,38,4.0,6,12,Rural,Software Engineer,96288,0 +90948,Male,39,Bachelors,0,33,23,32,56,2.0,3,70,Rural,ML Engineer,119721,0 +90949,Male,25,High School,18,28,98,46,68,5.0,6,47,Semi-Urban,HR Executive,69486,0 +90950,Male,52,Bachelors,14,60,21,50,66,1.0,4,40,Urban,Software Engineer,110203,0 +90951,Female,31,High School,9,80,43,15,91,0.0,2,61,Urban,Software Engineer,21196,0 +90952,Male,44,Masters,2,41,89,69,37,5.0,6,29,Semi-Urban,ML Engineer,79620,0 +90953,Male,44,Masters,15,53,66,84,60,4.0,6,20,Rural,ML Engineer,83475,0 +90954,Male,58,Diploma,13,18,42,9,11,2.0,1,74,Semi-Urban,Manager,53343,0 +90955,Female,46,Masters,11,61,95,7,60,0.0,0,36,Urban,HR Executive,102366,0 +90956,Female,27,Diploma,11,97,25,44,50,3.0,6,93,Urban,Software Engineer,132600,1 +90957,Male,44,Bachelors,3,88,40,91,9,5.0,2,34,Semi-Urban,ML Engineer,60215,1 +90958,Male,57,High School,5,99,84,6,22,1.0,1,88,Semi-Urban,Software Engineer,90484,1 +90959,Female,41,Masters,13,29,97,68,90,5.0,1,80,Urban,ML Engineer,55802,1 +90960,Male,33,Bachelors,8,35,54,5,23,8.0,4,17,Urban,ML Engineer,114650,0 +90961,Female,23,High School,12,65,9,84,47,2.0,6,49,Semi-Urban,ML Engineer,135364,0 +90962,Male,43,Bachelors,2,8,7,9,98,2.0,7,22,Rural,Manager,69588,0 +90963,Female,43,Bachelors,0,95,55,93,47,8.0,6,37,Rural,HR Executive,73832,1 +90964,Male,50,PhD,19,63,79,86,57,4.0,5,69,Urban,Manager,28792,1 +90965,Male,44,Bachelors,8,3,32,7,52,0.0,2,6,Urban,HR Executive,112589,0 +90966,Male,52,PhD,4,54,1,54,80,7.0,0,41,Urban,Manager,103365,0 +90967,Male,54,Bachelors,7,99,9,39,19,4.0,1,12,Semi-Urban,Software Engineer,85308,0 +90968,Male,30,Bachelors,19,78,54,81,96,9.0,7,8,Semi-Urban,Data Analyst,56389,0 +90969,Female,55,Bachelors,3,26,28,23,40,2.0,7,1,Semi-Urban,Data Analyst,33504,0 +90970,Male,45,High School,15,72,24,75,48,7.0,6,30,Semi-Urban,HR Executive,42531,0 +90971,Male,31,Bachelors,13,96,57,19,66,2.0,2,58,Urban,Software Engineer,20650,0 +90972,Male,26,Masters,1,69,82,38,45,1.0,7,11,Urban,Manager,57052,0 +90973,Male,24,Diploma,13,87,84,78,21,0.0,2,27,Urban,Software Engineer,34461,1 +90974,Female,21,High School,8,50,87,15,57,3.0,6,27,Semi-Urban,Data Analyst,50417,0 +90975,Male,43,Bachelors,12,85,79,28,13,7.0,6,68,Urban,Manager,69640,1 +90976,Female,55,Bachelors,12,6,31,53,78,3.0,7,23,Urban,Data Analyst,106439,0 +90977,Male,29,Bachelors,17,95,61,58,57,2.0,5,41,Rural,Manager,60792,1 +90978,Male,38,Diploma,13,30,8,56,36,8.0,4,11,Urban,Manager,75700,0 +90979,Male,54,Masters,8,52,49,82,57,1.0,0,72,Urban,Software Engineer,45064,1 +90980,Male,34,Diploma,3,13,49,35,98,7.0,3,77,Semi-Urban,Manager,104737,0 +90981,Male,57,High School,2,44,65,40,73,9.0,5,53,Rural,Data Analyst,80606,0 +90982,Female,59,Bachelors,6,96,72,47,9,3.0,2,65,Urban,HR Executive,41294,1 +90983,Male,40,High School,19,87,50,94,85,2.0,4,2,Semi-Urban,Data Analyst,94314,0 +90984,Male,57,Bachelors,0,2,87,45,55,0.0,0,61,Rural,Manager,124097,0 +90985,Male,42,Masters,0,39,66,91,69,8.0,7,66,Rural,HR Executive,39226,1 +90986,Female,29,Masters,12,56,79,66,48,3.0,7,5,Urban,Manager,86932,0 +90987,Male,46,Masters,2,56,82,59,18,2.0,0,92,Semi-Urban,Manager,103529,1 +90988,Male,24,Diploma,18,95,9,9,40,5.0,4,1,Urban,Data Analyst,46240,0 +90989,Male,57,Masters,10,40,54,4,90,3.0,1,66,Semi-Urban,Data Analyst,117946,0 +90990,Male,44,Bachelors,2,80,17,24,8,0.0,0,61,Semi-Urban,ML Engineer,24373,0 +90991,Male,57,Diploma,9,36,83,52,11,6.0,7,21,Urban,Software Engineer,60269,0 +90992,Female,52,PhD,4,69,3,22,76,6.0,5,55,Semi-Urban,Manager,58485,0 +90993,Male,22,Bachelors,6,81,49,87,38,4.0,5,80,Semi-Urban,Manager,117401,1 +90994,Male,34,Bachelors,11,33,94,88,40,7.0,0,63,Urban,Software Engineer,49702,1 +90995,Female,23,Masters,19,78,59,10,55,5.0,5,23,Urban,Data Analyst,96523,0 +90996,Male,25,Bachelors,5,57,9,77,24,3.0,5,91,Semi-Urban,HR Executive,89367,0 +90997,Male,41,Masters,6,53,54,39,12,8.0,1,11,Urban,ML Engineer,147573,0 +90998,Male,59,High School,5,62,43,58,67,5.0,3,8,Semi-Urban,Manager,46078,0 +90999,Female,53,Bachelors,12,40,25,48,18,0.0,3,78,Semi-Urban,Data Analyst,72512,0 +91000,Female,52,Masters,2,72,16,55,66,0.0,5,38,Urban,ML Engineer,85740,0 +91001,Female,28,Bachelors,1,81,18,81,36,2.0,2,1,Semi-Urban,Data Analyst,64882,0 +91002,Male,48,Bachelors,4,59,18,36,73,1.0,3,34,Semi-Urban,Software Engineer,33783,0 +91003,Male,23,Diploma,0,32,96,34,62,4.0,4,53,Rural,HR Executive,34276,0 +91004,Female,25,Bachelors,19,52,74,67,95,8.0,4,78,Rural,Data Analyst,21514,1 +91005,Female,43,Masters,6,8,8,26,12,9.0,3,79,Urban,Software Engineer,30592,0 +91006,Female,23,Masters,0,71,56,15,7,1.0,4,78,Urban,Manager,96863,0 +91007,Male,42,Diploma,19,19,90,88,50,8.0,4,9,Urban,Data Analyst,24644,0 +91008,Male,21,Masters,10,41,33,96,60,3.0,7,96,Rural,Software Engineer,50785,1 +91009,Male,30,High School,2,53,32,53,95,0.0,1,35,Urban,HR Executive,39428,0 +91010,Male,35,Masters,5,53,34,28,30,8.0,4,97,Rural,Data Analyst,85907,0 +91011,Male,51,PhD,17,91,74,81,81,3.0,5,80,Semi-Urban,Software Engineer,71878,1 +91012,Male,23,Diploma,16,2,23,17,3,6.0,5,60,Rural,HR Executive,118856,0 +91013,Female,50,Bachelors,5,92,72,1,66,6.0,0,70,Semi-Urban,Data Analyst,134206,0 +91014,Male,57,Diploma,11,24,93,90,80,4.0,6,52,Urban,Data Analyst,94686,1 +91015,Other,33,Bachelors,1,6,12,58,10,4.0,2,52,Semi-Urban,ML Engineer,48309,0 +91016,Male,29,Bachelors,3,93,84,87,0,4.0,7,9,Urban,Manager,78626,1 +91017,Female,29,PhD,8,23,32,42,64,0.0,1,96,Rural,HR Executive,122243,0 +91018,Male,37,High School,12,45,76,96,64,7.0,2,47,Urban,HR Executive,134694,1 +91019,Male,52,Masters,18,6,10,54,0,4.0,0,11,Urban,Data Analyst,136453,0 +91020,Female,59,Diploma,7,13,73,83,38,7.0,2,3,Urban,Software Engineer,20911,0 +91021,Male,26,Diploma,1,37,52,26,57,6.0,1,41,Semi-Urban,Data Analyst,43595,0 +91022,Male,39,Bachelors,3,88,57,23,76,6.0,5,71,Urban,HR Executive,89506,1 +91023,Male,40,Diploma,17,51,32,94,38,1.0,4,45,Urban,HR Executive,76767,0 +91024,Male,34,Masters,19,81,38,13,25,0.0,2,51,Urban,HR Executive,69318,0 +91025,Female,40,Masters,11,48,96,24,88,6.0,3,79,Rural,Software Engineer,31293,1 +91026,Male,24,Bachelors,3,46,80,6,11,3.0,5,24,Urban,Manager,30768,0 +91027,Male,29,High School,8,98,75,38,95,7.0,7,92,Semi-Urban,Software Engineer,86511,1 +91028,Female,36,Bachelors,2,66,93,79,21,9.0,2,55,Semi-Urban,Data Analyst,117551,1 +91029,Male,41,Bachelors,5,36,90,65,52,3.0,3,41,Urban,ML Engineer,149446,0 +91030,Female,21,Bachelors,3,50,52,12,69,2.0,7,63,Urban,Manager,22831,0 +91031,Male,35,Masters,2,95,60,65,31,4.0,3,6,Rural,Manager,55589,0 +91032,Male,37,Bachelors,19,95,59,82,99,5.0,0,92,Semi-Urban,Software Engineer,32828,1 +91033,Male,51,Masters,10,75,71,56,89,9.0,1,38,Rural,HR Executive,23384,1 +91034,Male,44,Diploma,15,65,60,48,95,5.0,6,31,Urban,ML Engineer,24355,0 +91035,Male,34,Masters,9,74,42,82,27,0.0,1,29,Urban,HR Executive,143572,0 +91036,Female,37,Bachelors,19,39,33,86,21,4.0,0,23,Urban,ML Engineer,38457,0 +91037,Male,54,PhD,12,13,62,38,67,5.0,0,34,Urban,Data Analyst,66396,0 +91038,Male,24,Bachelors,13,19,96,8,45,9.0,0,15,Urban,ML Engineer,41084,0 +91039,Male,57,Masters,11,95,44,0,96,6.0,4,17,Semi-Urban,Software Engineer,69646,0 +91040,Female,30,Diploma,14,57,52,6,83,4.0,3,36,Urban,ML Engineer,123027,0 +91041,Male,49,Masters,18,76,60,5,66,2.0,1,87,Semi-Urban,ML Engineer,132586,0 +91042,Female,42,Diploma,11,68,61,0,97,1.0,5,49,Semi-Urban,Manager,116081,0 +91043,Female,57,Bachelors,15,70,49,44,62,0.0,7,53,Urban,Software Engineer,22022,0 +91044,Male,43,Masters,7,88,0,12,73,3.0,0,58,Rural,ML Engineer,74740,0 +91045,Male,46,Diploma,13,76,7,52,27,3.0,0,11,Urban,Software Engineer,38950,0 +91046,Female,56,High School,5,79,34,2,59,9.0,4,96,Urban,HR Executive,131923,0 +91047,Male,50,Bachelors,10,9,50,23,61,5.0,4,67,Rural,Manager,43594,0 +91048,Male,41,Masters,14,95,98,31,41,2.0,2,76,Rural,Software Engineer,143198,1 +91049,Female,53,High School,14,57,1,63,89,4.0,5,17,Semi-Urban,HR Executive,141042,0 +91050,Male,29,Bachelors,8,32,96,54,99,1.0,3,5,Rural,Data Analyst,20443,0 +91051,Male,49,Masters,9,1,33,72,75,9.0,4,58,Rural,Data Analyst,56780,0 +91052,Male,31,Diploma,16,36,13,12,52,0.0,3,11,Semi-Urban,Data Analyst,82449,0 +91053,Female,40,Bachelors,5,0,73,80,13,2.0,0,85,Rural,HR Executive,21527,0 +91054,Male,31,High School,17,79,64,7,58,9.0,0,39,Urban,Data Analyst,98222,0 +91055,Male,31,High School,0,52,68,32,92,5.0,1,83,Semi-Urban,Manager,126517,1 +91056,Female,26,Diploma,7,4,13,11,75,5.0,2,98,Urban,Data Analyst,57466,0 +91057,Male,50,Masters,13,87,63,86,37,5.0,0,94,Urban,HR Executive,93144,1 +91058,Male,52,Bachelors,17,10,16,65,3,8.0,2,94,Urban,ML Engineer,130967,0 +91059,Female,31,Masters,17,62,34,9,6,3.0,4,24,Rural,HR Executive,62892,0 +91060,Male,56,Bachelors,2,73,29,16,28,8.0,7,38,Urban,Data Analyst,86446,0 +91061,Male,29,Bachelors,10,64,93,95,25,2.0,5,66,Rural,ML Engineer,56007,1 +91062,Female,48,Masters,2,39,21,1,97,8.0,1,24,Semi-Urban,Software Engineer,113960,0 +91063,Male,56,Bachelors,2,25,22,46,83,0.0,5,33,Semi-Urban,Manager,44799,0 +91064,Other,38,Bachelors,4,8,5,91,57,1.0,7,24,Rural,Manager,144662,0 +91065,Male,24,High School,17,42,31,17,84,3.0,3,88,Urban,Data Analyst,83158,0 +91066,Male,23,Bachelors,12,35,90,52,49,5.0,4,77,Urban,ML Engineer,79164,1 +91067,Other,42,Diploma,10,34,61,38,23,6.0,4,11,Semi-Urban,Data Analyst,43187,0 +91068,Male,41,Bachelors,16,89,28,51,2,9.0,2,11,Urban,Manager,36503,0 +91069,Male,32,Bachelors,18,87,49,6,73,1.0,0,42,Urban,HR Executive,64966,0 +91070,Female,27,High School,4,86,3,61,5,6.0,4,61,Urban,Software Engineer,34727,0 +91071,Male,22,Bachelors,8,22,18,12,34,7.0,6,40,Urban,HR Executive,132908,0 +91072,Male,52,Bachelors,16,50,6,3,31,7.0,2,12,Urban,ML Engineer,73000,0 +91073,Male,38,Diploma,14,50,21,97,48,1.0,1,7,Urban,Data Analyst,95422,0 +91074,Male,27,Diploma,4,16,55,20,54,7.0,5,33,Urban,HR Executive,120993,0 +91075,Male,41,High School,17,32,52,42,96,4.0,0,2,Urban,HR Executive,125609,0 +91076,Male,50,Diploma,18,59,65,67,64,1.0,4,45,Urban,Software Engineer,97432,1 +91077,Male,58,Diploma,4,16,34,28,91,9.0,5,19,Semi-Urban,HR Executive,34114,0 +91078,Male,23,High School,17,51,42,75,33,3.0,1,1,Semi-Urban,Data Analyst,81319,0 +91079,Male,34,Bachelors,5,80,10,18,20,4.0,0,8,Semi-Urban,Manager,147345,0 +91080,Female,28,Masters,16,42,54,37,44,0.0,0,20,Urban,HR Executive,102782,0 +91081,Male,59,Masters,1,94,47,29,19,9.0,2,71,Urban,Software Engineer,83201,1 +91082,Male,47,Bachelors,3,77,70,37,96,5.0,2,29,Rural,HR Executive,33724,0 +91083,Female,52,High School,19,24,1,70,9,2.0,6,20,Semi-Urban,Software Engineer,139193,0 +91084,Female,26,Bachelors,7,56,81,24,8,8.0,5,0,Urban,Software Engineer,111224,0 +91085,Female,56,Bachelors,8,26,44,74,56,3.0,3,2,Rural,Manager,30446,0 +91086,Female,43,Bachelors,1,87,21,70,65,2.0,4,73,Urban,ML Engineer,62871,1 +91087,Female,32,Bachelors,17,58,54,84,50,7.0,6,1,Urban,Manager,136230,0 +91088,Female,46,Diploma,18,75,64,95,76,5.0,5,27,Urban,Software Engineer,149459,1 +91089,Male,45,Bachelors,13,90,39,87,9,5.0,4,71,Urban,Data Analyst,25920,1 +91090,Male,32,Bachelors,1,56,3,52,23,2.0,0,91,Urban,ML Engineer,101622,0 +91091,Male,50,Diploma,17,38,73,46,46,9.0,1,93,Urban,HR Executive,142304,1 +91092,Male,29,High School,15,6,8,96,58,3.0,4,73,Urban,HR Executive,147855,0 +91093,Male,30,Masters,14,75,12,17,65,4.0,1,59,Semi-Urban,Manager,123197,0 +91094,Female,42,Diploma,9,45,17,56,27,4.0,4,50,Urban,Manager,53561,0 +91095,Female,28,Bachelors,11,87,54,22,23,5.0,3,56,Urban,Manager,108234,0 +91096,Female,26,Bachelors,4,24,37,59,15,8.0,4,89,Urban,Data Analyst,84697,0 +91097,Male,35,Bachelors,4,12,48,23,92,9.0,0,96,Urban,Software Engineer,100638,0 +91098,Male,31,Bachelors,15,2,99,46,90,1.0,6,86,Semi-Urban,Manager,72022,0 +91099,Male,35,Masters,3,45,96,61,83,4.0,2,23,Urban,Data Analyst,115916,0 +91100,Female,28,Diploma,18,95,94,5,91,7.0,1,87,Urban,Data Analyst,64207,1 +91101,Female,27,Diploma,19,46,10,23,91,0.0,2,71,Urban,Data Analyst,83727,0 +91102,Other,29,Masters,5,38,54,18,11,2.0,7,49,Semi-Urban,ML Engineer,113183,0 +91103,Male,40,High School,9,63,1,8,68,5.0,0,89,Rural,Software Engineer,92510,0 +91104,Female,29,High School,19,62,25,44,48,1.0,6,41,Urban,ML Engineer,44352,0 +91105,Male,45,Bachelors,7,64,89,86,74,8.0,1,98,Urban,Data Analyst,71596,1 +91106,Male,36,PhD,4,69,45,98,39,7.0,1,35,Urban,Manager,44342,1 +91107,Female,46,Bachelors,15,26,79,93,36,0.0,5,56,Rural,Manager,34637,1 +91108,Other,58,Bachelors,7,30,32,55,48,9.0,0,25,Rural,Software Engineer,64922,0 +91109,Male,37,Diploma,14,32,33,89,48,7.0,2,93,Semi-Urban,Manager,90768,1 +91110,Male,27,High School,13,78,0,87,99,0.0,6,44,Rural,Data Analyst,20328,0 +91111,Male,40,Masters,1,75,1,34,50,7.0,3,17,Semi-Urban,Software Engineer,103293,0 +91112,Female,27,Masters,6,33,72,93,77,6.0,4,66,Urban,Data Analyst,68936,1 +91113,Female,57,High School,14,12,45,2,66,2.0,6,57,Urban,HR Executive,118842,0 +91114,Female,35,PhD,7,96,53,87,52,5.0,4,81,Urban,Data Analyst,109424,1 +91115,Male,28,Bachelors,16,15,12,98,16,0.0,6,59,Rural,Software Engineer,47961,0 +91116,Male,39,PhD,8,54,76,49,35,1.0,1,62,Semi-Urban,Manager,147682,1 +91117,Female,35,Masters,13,41,67,6,78,9.0,3,57,Semi-Urban,Data Analyst,107658,0 +91118,Female,30,Diploma,8,11,57,34,2,2.0,2,25,Urban,HR Executive,126979,0 +91119,Female,32,Bachelors,8,52,38,15,98,4.0,4,40,Urban,Software Engineer,63657,0 +91120,Female,30,Masters,11,14,55,91,90,7.0,6,14,Urban,Data Analyst,21305,0 +91121,Male,31,Diploma,11,0,6,21,54,0.0,5,5,Semi-Urban,HR Executive,93605,0 +91122,Male,47,Bachelors,19,47,82,6,65,1.0,0,4,Rural,Software Engineer,71008,0 +91123,Male,27,Bachelors,6,0,90,86,77,0.0,2,9,Rural,HR Executive,22067,0 +91124,Male,28,Bachelors,18,74,29,16,18,0.0,3,29,Semi-Urban,ML Engineer,116540,0 +91125,Male,45,Bachelors,11,98,59,11,67,5.0,4,94,Urban,HR Executive,82016,1 +91126,Female,32,Diploma,13,65,56,86,50,4.0,7,15,Rural,Data Analyst,47411,0 +91127,Female,29,Masters,10,66,17,96,95,9.0,1,5,Urban,ML Engineer,83828,0 +91128,Male,49,Bachelors,15,25,27,79,48,4.0,6,74,Urban,Data Analyst,124542,0 +91129,Male,56,Masters,14,28,62,0,39,6.0,6,15,Urban,Software Engineer,98702,0 +91130,Other,46,Bachelors,12,65,91,72,2,6.0,0,11,Urban,HR Executive,109143,0 +91131,Male,53,Masters,15,61,13,62,41,7.0,3,94,Urban,Data Analyst,27564,0 +91132,Female,57,Diploma,0,67,61,79,68,7.0,3,32,Semi-Urban,ML Engineer,75509,0 +91133,Male,26,Masters,17,20,27,42,73,8.0,6,24,Semi-Urban,ML Engineer,46649,0 +91134,Male,38,Diploma,7,5,65,88,58,8.0,6,71,Rural,Software Engineer,109195,0 +91135,Male,41,High School,11,5,85,97,22,0.0,7,84,Urban,Manager,105983,1 +91136,Male,33,Bachelors,6,8,99,64,0,3.0,0,15,Rural,Software Engineer,125966,0 +91137,Female,54,Diploma,17,42,68,52,3,2.0,0,63,Urban,ML Engineer,24203,0 +91138,Male,40,Masters,10,99,48,24,13,7.0,2,91,Semi-Urban,Data Analyst,61918,1 +91139,Male,50,Bachelors,9,12,52,7,75,9.0,7,84,Rural,Manager,45138,0 +91140,Female,57,Diploma,19,56,61,86,11,4.0,4,61,Semi-Urban,HR Executive,97918,1 +91141,Male,59,Diploma,5,37,90,61,85,6.0,2,88,Urban,Data Analyst,39645,1 +91142,Female,31,Masters,13,66,1,7,37,7.0,2,95,Urban,Manager,97312,0 +91143,Male,24,Bachelors,4,53,71,52,8,2.0,7,27,Urban,HR Executive,59507,0 +91144,Male,26,Bachelors,2,70,73,88,25,7.0,3,39,Urban,Data Analyst,52723,1 +91145,Male,21,High School,17,79,21,27,19,2.0,5,35,Rural,Manager,75547,0 +91146,Female,24,High School,5,38,88,9,87,7.0,0,98,Urban,Manager,30968,0 +91147,Male,50,Bachelors,10,91,62,9,69,6.0,7,84,Semi-Urban,ML Engineer,129420,1 +91148,Male,49,Masters,18,49,22,74,58,9.0,1,10,Urban,Software Engineer,110222,0 +91149,Male,26,Diploma,3,77,27,10,32,4.0,4,47,Urban,Data Analyst,47679,0 +91150,Other,34,Masters,17,74,29,81,55,8.0,2,69,Rural,Manager,112260,1 +91151,Female,51,Diploma,9,40,50,42,44,4.0,4,17,Urban,Data Analyst,62745,0 +91152,Female,29,Bachelors,2,76,54,92,27,0.0,2,25,Rural,Software Engineer,46059,1 +91153,Male,52,High School,7,48,17,9,75,7.0,0,88,Urban,Manager,35168,0 +91154,Female,44,Diploma,0,36,69,6,58,3.0,4,86,Urban,Manager,52655,0 +91155,Female,35,Diploma,5,21,61,99,82,4.0,3,13,Urban,Data Analyst,21468,0 +91156,Male,41,Diploma,0,72,27,64,94,4.0,5,50,Rural,Data Analyst,141392,0 +91157,Male,49,Diploma,2,66,66,17,10,0.0,5,37,Urban,Manager,31543,0 +91158,Male,41,High School,1,13,87,60,97,2.0,4,56,Urban,Data Analyst,22036,0 +91159,Male,38,Bachelors,4,12,19,70,44,4.0,2,96,Urban,Software Engineer,106908,0 +91160,Male,46,Diploma,18,41,48,2,14,7.0,6,49,Semi-Urban,Data Analyst,45093,0 +91161,Male,44,Masters,1,49,2,89,22,4.0,3,9,Urban,HR Executive,39534,0 +91162,Male,39,PhD,18,38,73,39,83,0.0,6,22,Urban,Manager,49128,0 +91163,Female,21,Diploma,7,1,26,69,67,1.0,2,87,Urban,Software Engineer,110204,0 +91164,Female,42,Masters,2,77,33,42,84,6.0,5,85,Urban,Software Engineer,82991,0 +91165,Male,46,Bachelors,6,5,92,62,36,0.0,3,36,Urban,ML Engineer,36484,0 +91166,Female,29,Masters,3,35,24,90,93,6.0,0,61,Semi-Urban,Manager,128555,0 +91167,Female,24,Bachelors,7,90,58,92,11,4.0,0,81,Urban,Manager,138025,1 +91168,Male,25,Bachelors,12,28,33,48,67,7.0,0,39,Semi-Urban,Manager,109201,0 +91169,Female,29,Masters,7,16,87,80,48,5.0,3,75,Semi-Urban,HR Executive,93349,1 +91170,Male,49,Bachelors,13,61,44,18,73,6.0,3,56,Urban,Manager,127522,0 +91171,Female,24,Bachelors,1,24,98,65,31,5.0,2,84,Urban,ML Engineer,121880,1 +91172,Female,37,Diploma,3,41,12,49,29,7.0,1,1,Urban,Software Engineer,52003,0 +91173,Male,43,High School,3,80,28,97,3,9.0,2,99,Urban,Data Analyst,47215,1 +91174,Male,41,Masters,3,26,82,66,19,8.0,0,15,Urban,ML Engineer,64323,0 +91175,Male,48,Bachelors,6,9,5,85,73,8.0,6,22,Rural,Manager,130980,0 +91176,Male,59,Diploma,1,52,99,43,58,7.0,1,87,Semi-Urban,ML Engineer,127992,1 +91177,Female,45,Masters,3,79,45,51,54,1.0,5,28,Semi-Urban,HR Executive,119453,0 +91178,Female,30,Diploma,7,71,4,59,62,1.0,3,16,Urban,Software Engineer,84031,0 +91179,Male,44,Bachelors,6,95,14,65,32,9.0,0,65,Rural,ML Engineer,121842,1 +91180,Female,49,Bachelors,14,43,65,73,44,7.0,1,81,Urban,ML Engineer,63181,1 +91181,Male,22,Diploma,0,24,52,62,25,5.0,7,5,Semi-Urban,Software Engineer,143279,0 +91182,Male,36,Masters,15,57,0,10,93,3.0,2,45,Urban,ML Engineer,86819,0 +91183,Male,48,Masters,2,52,37,55,73,2.0,3,13,Rural,Data Analyst,114934,0 +91184,Male,39,Bachelors,14,33,77,91,48,2.0,0,19,Semi-Urban,ML Engineer,144707,0 +91185,Female,56,Bachelors,8,38,8,72,98,6.0,2,11,Semi-Urban,Data Analyst,71699,0 +91186,Other,48,Bachelors,18,19,6,17,39,9.0,2,35,Urban,Manager,141669,0 +91187,Male,32,Bachelors,16,93,10,67,28,3.0,1,35,Urban,ML Engineer,146918,0 +91188,Male,24,Masters,11,61,58,16,4,7.0,3,78,Semi-Urban,HR Executive,132846,0 +91189,Male,55,Bachelors,16,65,78,36,11,9.0,6,64,Urban,Manager,69921,1 +91190,Female,53,Bachelors,7,20,37,44,60,8.0,6,93,Rural,HR Executive,121150,0 +91191,Female,31,Diploma,16,58,70,86,67,7.0,2,73,Urban,HR Executive,124818,1 +91192,Male,44,Diploma,19,62,59,37,45,4.0,5,15,Urban,Data Analyst,22013,0 +91193,Female,51,Masters,12,49,78,54,12,0.0,2,97,Urban,ML Engineer,105353,1 +91194,Male,52,Masters,15,41,54,14,66,4.0,3,49,Urban,Manager,69972,0 +91195,Male,47,Bachelors,11,19,37,65,23,5.0,4,73,Semi-Urban,Manager,25485,0 +91196,Male,51,High School,19,3,59,0,24,0.0,5,62,Rural,Data Analyst,56113,0 +91197,Male,54,Bachelors,11,90,41,45,48,8.0,5,58,Urban,Software Engineer,95496,0 +91198,Female,58,PhD,10,4,31,7,72,2.0,7,69,Rural,HR Executive,93520,0 +91199,Female,30,Bachelors,6,86,9,12,26,3.0,6,40,Rural,Software Engineer,130215,0 +91200,Male,49,Bachelors,8,41,95,59,3,8.0,0,35,Rural,Data Analyst,54716,0 +91201,Female,54,Masters,14,7,22,86,95,6.0,6,61,Urban,Software Engineer,23539,0 +91202,Male,48,Masters,11,94,61,21,64,8.0,2,88,Urban,ML Engineer,106093,1 +91203,Female,22,Bachelors,6,43,91,65,22,6.0,3,75,Urban,Manager,142613,1 +91204,Male,48,Diploma,9,38,93,18,62,6.0,6,39,Rural,Data Analyst,60205,0 +91205,Male,59,High School,17,16,86,34,58,8.0,2,66,Semi-Urban,Data Analyst,98899,0 +91206,Male,44,Bachelors,11,81,70,13,30,1.0,6,0,Urban,Manager,63880,0 +91207,Male,31,Masters,18,46,27,70,11,9.0,2,15,Urban,Manager,71879,0 +91208,Male,29,Masters,6,40,64,41,21,9.0,6,18,Rural,Data Analyst,52406,0 +91209,Male,33,Bachelors,4,36,36,45,23,9.0,5,72,Rural,Data Analyst,23744,0 +91210,Male,23,Bachelors,7,87,20,49,78,3.0,7,99,Urban,HR Executive,77159,1 +91211,Male,22,High School,1,7,27,93,25,3.0,1,67,Urban,Software Engineer,83607,0 +91212,Female,39,Bachelors,0,76,21,37,21,5.0,1,35,Semi-Urban,HR Executive,132478,0 +91213,Female,44,Diploma,15,52,98,99,27,7.0,2,94,Urban,Manager,74866,1 +91214,Female,21,PhD,7,62,18,88,5,1.0,5,34,Semi-Urban,Data Analyst,49408,0 +91215,Male,59,Bachelors,10,71,74,75,26,9.0,0,33,Semi-Urban,Software Engineer,72009,1 +91216,Male,21,Bachelors,10,58,36,80,23,6.0,3,9,Semi-Urban,Manager,99003,0 +91217,Female,22,High School,2,55,4,83,14,0.0,4,53,Semi-Urban,Data Analyst,118354,0 +91218,Female,27,Masters,16,12,38,21,80,8.0,2,55,Urban,Manager,102471,0 +91219,Male,42,Bachelors,6,66,50,93,6,7.0,2,64,Urban,Manager,142161,1 +91220,Male,36,Bachelors,3,58,5,7,87,2.0,1,67,Urban,ML Engineer,95598,0 +91221,Male,39,Diploma,2,3,34,27,23,7.0,4,73,Urban,Software Engineer,86864,0 +91222,Female,26,Bachelors,8,41,52,54,23,4.0,0,27,Semi-Urban,Data Analyst,102975,0 +91223,Male,24,High School,15,9,71,84,33,9.0,1,9,Urban,Data Analyst,87022,0 +91224,Male,39,High School,1,37,44,86,72,2.0,3,11,Urban,ML Engineer,85707,0 +91225,Male,53,Diploma,17,32,72,14,15,7.0,0,30,Urban,Software Engineer,145906,0 +91226,Female,39,Masters,0,86,69,33,48,4.0,3,33,Urban,Manager,32571,0 +91227,Male,46,Bachelors,1,27,86,87,81,5.0,4,15,Urban,Software Engineer,42449,0 +91228,Male,28,Bachelors,11,11,14,0,81,4.0,4,87,Urban,ML Engineer,107137,0 +91229,Male,22,Bachelors,17,84,88,81,55,0.0,5,68,Urban,HR Executive,56666,1 +91230,Other,44,Diploma,13,89,15,64,36,4.0,2,68,Urban,Manager,66577,0 +91231,Male,47,Bachelors,19,58,66,53,4,5.0,4,42,Urban,ML Engineer,84546,0 +91232,Female,37,Diploma,14,72,96,40,20,3.0,3,31,Semi-Urban,Software Engineer,75255,0 +91233,Male,44,Diploma,11,91,90,94,53,1.0,6,46,Semi-Urban,Data Analyst,44129,1 +91234,Other,37,High School,8,81,33,2,93,4.0,7,56,Urban,Software Engineer,25597,0 +91235,Male,26,Diploma,4,88,78,97,50,5.0,2,87,Semi-Urban,Data Analyst,81805,1 +91236,Male,52,Bachelors,15,78,15,17,20,5.0,1,45,Semi-Urban,Software Engineer,89316,0 +91237,Male,23,Bachelors,11,94,10,38,89,2.0,5,16,Rural,Manager,56333,0 +91238,Male,39,Bachelors,5,31,33,70,76,4.0,0,73,Urban,HR Executive,118213,0 +91239,Male,48,Bachelors,6,15,10,56,1,6.0,1,69,Rural,HR Executive,149470,0 +91240,Male,47,Bachelors,14,10,62,37,60,4.0,7,61,Urban,ML Engineer,71901,0 +91241,Female,29,Bachelors,11,31,34,22,41,3.0,5,14,Urban,Manager,104309,0 +91242,Male,56,Bachelors,11,43,49,34,78,2.0,2,97,Urban,ML Engineer,50596,0 +91243,Female,32,Bachelors,15,23,47,86,9,1.0,6,9,Urban,Data Analyst,125529,0 +91244,Female,44,Bachelors,15,56,80,42,16,1.0,4,92,Semi-Urban,ML Engineer,52715,1 +91245,Male,47,High School,0,6,69,46,63,6.0,5,61,Rural,Manager,93499,0 +91246,Male,51,Bachelors,8,94,80,34,23,2.0,5,69,Urban,ML Engineer,20376,1 +91247,Other,49,Masters,10,63,58,19,31,9.0,4,30,Semi-Urban,Data Analyst,30516,0 +91248,Male,33,Masters,7,39,43,13,15,0.0,3,83,Urban,Manager,84417,0 +91249,Male,43,Bachelors,12,47,14,54,25,1.0,5,84,Urban,Manager,120367,0 +91250,Female,47,Bachelors,18,75,93,20,85,9.0,7,40,Urban,Software Engineer,21459,0 +91251,Male,31,PhD,3,21,68,3,85,9.0,2,63,Semi-Urban,Data Analyst,126490,0 +91252,Other,53,Bachelors,10,66,12,17,33,8.0,1,67,Rural,Manager,79775,0 +91253,Male,24,Masters,9,85,66,18,94,9.0,2,33,Urban,ML Engineer,76791,0 +91254,Female,56,Bachelors,5,94,68,69,58,7.0,2,56,Urban,ML Engineer,92450,1 +91255,Male,47,Bachelors,13,94,6,31,79,4.0,0,34,Urban,Software Engineer,83759,0 +91256,Male,29,Bachelors,14,83,29,13,38,7.0,3,52,Urban,HR Executive,130823,0 +91257,Female,28,Masters,13,24,42,92,39,5.0,5,12,Urban,Software Engineer,102890,0 +91258,Other,52,Bachelors,16,44,91,82,3,2.0,7,18,Urban,Data Analyst,35078,0 +91259,Male,42,Bachelors,12,64,80,25,94,2.0,6,7,Urban,Software Engineer,32639,0 +91260,Female,28,Bachelors,12,65,65,99,96,2.0,6,38,Urban,ML Engineer,24412,1 +91261,Female,27,Diploma,18,72,44,68,8,7.0,5,41,Urban,Software Engineer,25733,0 +91262,Male,22,High School,1,72,92,39,88,8.0,4,19,Urban,HR Executive,50367,0 +91263,Male,55,High School,13,36,90,97,59,9.0,5,93,Rural,Software Engineer,132027,1 +91264,Male,55,PhD,3,48,74,23,92,6.0,7,45,Urban,Manager,102271,0 +91265,Female,53,High School,5,14,17,44,78,9.0,5,26,Urban,HR Executive,134663,0 +91266,Male,46,Bachelors,16,89,49,29,11,3.0,5,57,Semi-Urban,ML Engineer,107667,0 +91267,Male,54,Diploma,19,78,93,7,71,6.0,0,12,Semi-Urban,Manager,38769,0 +91268,Male,43,Diploma,5,86,65,74,57,5.0,4,79,Semi-Urban,Manager,44315,1 +91269,Female,26,Bachelors,16,85,70,57,93,8.0,4,80,Rural,Data Analyst,42942,1 +91270,Female,53,High School,8,32,4,71,2,2.0,0,59,Urban,ML Engineer,82165,0 +91271,Female,28,High School,11,20,13,35,52,3.0,7,37,Urban,ML Engineer,125220,0 +91272,Male,47,High School,8,97,43,61,75,2.0,1,5,Rural,HR Executive,25423,0 +91273,Female,47,High School,15,48,52,51,22,2.0,0,6,Urban,Data Analyst,111360,0 +91274,Female,52,Diploma,1,90,75,74,92,6.0,6,59,Rural,Data Analyst,142469,1 +91275,Female,35,Bachelors,2,30,61,0,95,2.0,4,69,Urban,HR Executive,146592,0 +91276,Female,39,Masters,6,63,85,50,5,8.0,6,52,Urban,ML Engineer,128023,1 +91277,Female,43,Bachelors,14,86,91,83,27,6.0,5,65,Urban,Manager,92484,1 +91278,Male,25,High School,4,54,60,82,53,6.0,4,89,Rural,HR Executive,49628,1 +91279,Male,41,Bachelors,11,35,86,27,34,9.0,2,28,Urban,Software Engineer,59493,0 +91280,Other,56,Bachelors,3,69,94,87,98,7.0,5,63,Rural,ML Engineer,111507,1 +91281,Male,52,PhD,5,80,88,65,97,3.0,3,73,Semi-Urban,Data Analyst,112074,1 +91282,Male,21,Diploma,18,79,78,14,19,3.0,2,93,Urban,ML Engineer,20199,1 +91283,Male,54,High School,10,87,55,24,79,2.0,7,75,Urban,Manager,122529,1 +91284,Female,55,PhD,5,62,84,38,79,9.0,2,29,Semi-Urban,ML Engineer,134961,0 +91285,Male,45,Bachelors,7,99,40,45,84,1.0,4,32,Semi-Urban,ML Engineer,33139,0 +91286,Female,44,PhD,14,45,99,75,26,6.0,7,16,Semi-Urban,Manager,56242,0 +91287,Male,25,Diploma,12,83,91,7,49,4.0,2,73,Urban,Data Analyst,76488,1 +91288,Male,56,Bachelors,15,75,24,36,57,4.0,0,13,Urban,Data Analyst,66048,0 +91289,Male,50,Bachelors,14,31,46,44,50,0.0,0,92,Rural,ML Engineer,132624,0 +91290,Male,41,High School,1,2,20,27,22,2.0,2,65,Urban,HR Executive,29765,0 +91291,Male,47,Diploma,2,34,46,80,54,2.0,5,3,Urban,Software Engineer,126726,0 +91292,Female,34,Diploma,18,71,0,65,28,5.0,4,27,Semi-Urban,Manager,47048,0 +91293,Male,27,Bachelors,0,14,46,5,4,1.0,1,73,Rural,ML Engineer,129597,0 +91294,Female,47,High School,12,95,53,28,93,9.0,7,50,Urban,ML Engineer,130367,0 +91295,Other,47,Bachelors,7,74,0,77,24,6.0,6,38,Semi-Urban,ML Engineer,147331,0 +91296,Female,28,Bachelors,17,31,61,65,70,9.0,4,18,Urban,Software Engineer,42056,0 +91297,Female,24,Masters,19,52,45,70,62,8.0,7,52,Semi-Urban,ML Engineer,110367,0 +91298,Female,44,Bachelors,15,9,34,70,92,9.0,1,88,Semi-Urban,Software Engineer,98932,0 +91299,Female,56,High School,14,58,51,50,33,0.0,0,7,Rural,Data Analyst,42233,0 +91300,Female,50,Bachelors,19,82,37,65,14,2.0,2,29,Urban,ML Engineer,133649,0 +91301,Female,43,Bachelors,19,3,22,98,4,2.0,1,75,Rural,Software Engineer,120655,0 +91302,Other,50,Bachelors,11,86,22,78,85,1.0,2,4,Urban,Software Engineer,125993,0 +91303,Female,31,Bachelors,13,34,28,56,97,9.0,7,30,Semi-Urban,Manager,90817,0 +91304,Male,56,Masters,12,36,12,32,14,7.0,4,61,Rural,Manager,110611,0 +91305,Male,47,Masters,2,33,22,38,67,7.0,0,84,Rural,ML Engineer,113104,0 +91306,Male,23,Diploma,9,40,50,14,54,1.0,1,47,Semi-Urban,ML Engineer,30412,0 +91307,Female,21,Bachelors,6,39,18,83,85,7.0,2,20,Urban,Manager,137988,0 +91308,Female,49,Masters,2,3,16,29,96,0.0,2,93,Semi-Urban,Data Analyst,148949,0 +91309,Male,37,Bachelors,9,0,98,38,71,0.0,7,11,Urban,Manager,91068,0 +91310,Female,27,Bachelors,1,74,83,20,84,9.0,1,3,Urban,Manager,91005,0 +91311,Other,54,Bachelors,2,86,43,1,16,6.0,1,46,Urban,HR Executive,70177,0 +91312,Female,55,Bachelors,1,55,90,42,32,2.0,0,87,Urban,HR Executive,101595,1 +91313,Male,42,Bachelors,3,3,78,49,72,9.0,3,89,Urban,Software Engineer,87692,0 +91314,Female,55,Bachelors,14,97,65,9,20,0.0,1,9,Rural,ML Engineer,126411,0 +91315,Female,44,High School,13,73,26,96,3,2.0,0,62,Rural,Manager,26280,1 +91316,Male,26,Masters,3,52,79,45,52,9.0,5,89,Semi-Urban,Software Engineer,144744,1 +91317,Male,21,Bachelors,11,41,45,15,55,7.0,4,89,Urban,ML Engineer,67667,0 +91318,Male,58,Bachelors,2,88,49,21,95,5.0,5,20,Semi-Urban,Software Engineer,133591,0 +91319,Female,24,Bachelors,6,40,82,44,22,3.0,7,88,Urban,Manager,121103,1 +91320,Female,44,Masters,17,45,46,45,77,0.0,7,5,Rural,ML Engineer,137836,0 +91321,Male,27,Bachelors,1,58,81,25,55,2.0,3,46,Urban,Software Engineer,72790,0 +91322,Male,33,Bachelors,4,94,3,28,53,6.0,0,56,Urban,ML Engineer,142244,0 +91323,Male,37,High School,11,21,7,43,63,3.0,0,4,Semi-Urban,Manager,85807,0 +91324,Male,42,Bachelors,7,4,72,51,10,9.0,0,34,Semi-Urban,Data Analyst,23417,0 +91325,Female,38,High School,13,39,57,13,15,2.0,3,89,Rural,Manager,138540,0 +91326,Male,59,Bachelors,15,26,59,54,72,3.0,0,28,Rural,ML Engineer,103843,0 +91327,Male,37,Diploma,1,30,40,0,91,6.0,0,71,Semi-Urban,Manager,73198,0 +91328,Female,34,Bachelors,11,92,45,93,70,8.0,0,0,Rural,Manager,101959,0 +91329,Female,31,Masters,10,44,45,93,12,8.0,4,50,Rural,Manager,63709,0 +91330,Other,27,Masters,15,54,67,61,50,3.0,6,6,Semi-Urban,Data Analyst,138893,0 +91331,Male,21,Diploma,17,8,56,9,3,9.0,1,58,Semi-Urban,Manager,131341,0 +91332,Male,56,Diploma,18,13,72,12,16,1.0,3,42,Urban,HR Executive,125966,0 +91333,Female,51,Bachelors,2,45,39,46,73,5.0,3,12,Urban,Manager,88991,0 +91334,Male,28,Masters,6,26,0,47,15,9.0,5,37,Urban,Data Analyst,43357,0 +91335,Male,52,Bachelors,1,80,27,38,39,8.0,3,5,Urban,Manager,63151,0 +91336,Male,39,Bachelors,2,17,35,28,68,9.0,5,8,Semi-Urban,ML Engineer,139968,0 +91337,Male,59,Bachelors,10,48,89,53,45,1.0,3,6,Urban,ML Engineer,27434,0 +91338,Male,22,Bachelors,17,11,49,87,25,0.0,3,2,Rural,HR Executive,66715,0 +91339,Male,34,Diploma,7,14,54,39,75,2.0,3,4,Urban,HR Executive,58816,0 +91340,Female,55,Bachelors,8,66,9,7,48,4.0,2,42,Urban,HR Executive,124911,0 +91341,Female,39,Masters,2,87,60,9,80,6.0,3,94,Urban,Manager,64835,1 +91342,Male,26,Masters,2,1,62,39,64,2.0,4,4,Urban,ML Engineer,94535,0 +91343,Male,24,Diploma,8,52,16,63,85,4.0,3,69,Urban,HR Executive,100748,0 +91344,Male,36,Diploma,3,41,83,74,35,8.0,4,83,Urban,Data Analyst,82006,1 +91345,Male,22,Masters,19,43,50,96,38,1.0,3,72,Semi-Urban,HR Executive,122937,1 +91346,Female,30,Bachelors,3,99,23,95,53,5.0,5,46,Rural,ML Engineer,60362,1 +91347,Female,25,PhD,13,44,23,56,41,8.0,5,10,Semi-Urban,ML Engineer,82978,0 +91348,Male,26,High School,18,63,84,67,15,1.0,3,62,Urban,Manager,112616,1 +91349,Male,47,Masters,14,79,92,77,53,2.0,3,35,Urban,Software Engineer,60399,1 +91350,Male,49,Diploma,8,63,63,81,8,7.0,1,64,Urban,Data Analyst,27394,1 +91351,Female,48,Bachelors,1,8,4,74,94,1.0,2,62,Urban,Manager,67948,0 +91352,Female,50,Diploma,5,8,71,20,93,1.0,4,27,Semi-Urban,Manager,129827,0 +91353,Male,58,Bachelors,7,92,6,31,42,2.0,7,60,Urban,ML Engineer,143329,0 +91354,Other,43,Bachelors,15,94,94,76,22,5.0,5,67,Urban,HR Executive,131858,1 +91355,Male,38,Diploma,12,82,2,94,30,6.0,7,10,Rural,Data Analyst,82068,0 +91356,Male,21,Bachelors,9,64,91,10,2,6.0,3,14,Urban,Manager,27947,0 +91357,Male,55,High School,2,88,45,52,94,6.0,1,57,Urban,ML Engineer,129959,1 +91358,Female,38,Masters,6,6,9,63,3,1.0,2,6,Rural,Data Analyst,82743,0 +91359,Female,50,PhD,19,68,90,41,50,3.0,7,92,Semi-Urban,HR Executive,25781,1 +91360,Male,58,Masters,9,36,75,80,4,7.0,2,44,Semi-Urban,HR Executive,85792,1 +91361,Other,58,Bachelors,19,67,13,90,20,8.0,6,52,Rural,HR Executive,22416,0 +91362,Male,29,Diploma,3,13,39,36,0,6.0,4,76,Semi-Urban,ML Engineer,82071,0 +91363,Female,44,Masters,9,51,79,36,32,4.0,2,88,Urban,ML Engineer,113761,1 +91364,Other,56,Bachelors,9,58,6,69,0,9.0,0,79,Rural,Data Analyst,57875,0 +91365,Male,22,High School,13,62,32,13,79,1.0,1,49,Urban,Data Analyst,40637,0 +91366,Male,25,Diploma,2,19,60,91,23,9.0,7,87,Urban,Manager,120091,1 +91367,Female,36,Bachelors,2,3,2,37,13,2.0,6,97,Rural,ML Engineer,126423,0 +91368,Male,30,Bachelors,6,86,98,47,48,5.0,5,66,Urban,Software Engineer,97125,1 +91369,Male,53,Bachelors,9,31,18,94,69,8.0,0,23,Urban,ML Engineer,80015,0 +91370,Female,24,Masters,16,45,3,43,93,1.0,5,20,Urban,Data Analyst,79828,0 +91371,Male,41,Bachelors,12,69,17,61,91,3.0,5,97,Semi-Urban,HR Executive,30065,1 +91372,Female,48,Masters,0,23,95,1,51,5.0,2,63,Urban,HR Executive,90175,0 +91373,Male,32,High School,4,91,12,63,51,6.0,3,32,Urban,Software Engineer,116891,0 +91374,Female,30,High School,1,84,25,91,63,9.0,4,78,Urban,Data Analyst,139951,1 +91375,Female,50,Bachelors,5,24,40,79,23,8.0,3,96,Urban,Data Analyst,94167,0 +91376,Male,59,Bachelors,11,22,40,53,83,7.0,1,5,Urban,Data Analyst,121053,0 +91377,Male,27,Diploma,16,88,88,46,9,6.0,1,68,Urban,Software Engineer,81455,1 +91378,Female,47,Diploma,11,54,60,33,95,7.0,1,26,Urban,Data Analyst,52706,0 +91379,Male,56,Diploma,8,74,22,91,83,9.0,6,87,Urban,HR Executive,112768,1 +91380,Male,41,Bachelors,8,95,30,61,91,7.0,1,80,Urban,Manager,131171,1 +91381,Female,36,Bachelors,17,24,48,11,10,4.0,4,62,Rural,Software Engineer,123074,0 +91382,Female,54,Masters,15,19,0,15,64,9.0,6,1,Semi-Urban,Data Analyst,41186,0 +91383,Female,26,High School,9,7,86,65,11,9.0,0,28,Urban,Data Analyst,113502,0 +91384,Male,22,Bachelors,4,0,1,97,4,6.0,2,4,Urban,Manager,138291,0 +91385,Male,59,PhD,7,61,96,18,98,2.0,0,16,Urban,Data Analyst,136001,0 +91386,Female,40,Masters,2,51,37,89,12,3.0,4,62,Urban,ML Engineer,105799,0 +91387,Male,32,High School,1,49,63,17,98,8.0,6,99,Semi-Urban,HR Executive,40828,0 +91388,Female,22,High School,12,46,60,81,68,6.0,3,11,Urban,ML Engineer,128640,0 +91389,Male,38,High School,11,21,56,41,35,1.0,5,98,Rural,ML Engineer,144720,0 +91390,Male,52,Masters,16,69,53,51,99,9.0,0,19,Urban,HR Executive,35504,0 +91391,Male,43,Masters,3,81,81,72,56,0.0,1,14,Urban,HR Executive,137914,1 +91392,Male,38,Diploma,2,3,85,2,79,6.0,4,25,Urban,Software Engineer,119644,0 +91393,Male,44,Bachelors,14,53,96,34,36,7.0,4,0,Urban,Software Engineer,105159,0 +91394,Other,55,PhD,16,26,32,51,44,3.0,4,54,Urban,Data Analyst,45492,0 +91395,Male,21,Masters,18,7,50,44,58,2.0,3,28,Urban,HR Executive,92890,0 +91396,Male,41,Diploma,5,90,14,80,81,3.0,4,26,Urban,Software Engineer,107773,0 +91397,Other,36,High School,7,41,82,56,72,0.0,3,16,Urban,HR Executive,42406,0 +91398,Male,55,Bachelors,9,84,89,56,82,9.0,1,51,Urban,Data Analyst,113756,1 +91399,Male,45,High School,6,79,37,62,70,4.0,5,44,Semi-Urban,HR Executive,67198,0 +91400,Female,52,High School,7,15,7,81,71,9.0,5,78,Semi-Urban,Data Analyst,30032,0 +91401,Female,31,Diploma,7,90,15,96,80,4.0,4,22,Semi-Urban,Software Engineer,45202,0 +91402,Male,52,Bachelors,3,60,26,18,27,8.0,7,67,Semi-Urban,ML Engineer,22922,0 +91403,Male,49,High School,2,96,58,16,14,8.0,7,76,Urban,Software Engineer,138420,1 +91404,Other,31,Diploma,3,72,13,19,71,2.0,0,90,Urban,Software Engineer,40798,0 +91405,Male,29,Bachelors,17,42,27,88,21,6.0,1,43,Semi-Urban,Data Analyst,55805,0 +91406,Male,55,Bachelors,19,84,83,79,48,4.0,3,67,Urban,Data Analyst,145201,1 +91407,Male,29,Masters,13,62,55,83,16,6.0,0,79,Urban,Software Engineer,103736,1 +91408,Male,33,Bachelors,0,3,61,24,45,4.0,7,51,Urban,Manager,148506,0 +91409,Male,38,PhD,5,50,52,65,66,8.0,2,93,Urban,HR Executive,35679,1 +91410,Male,59,Bachelors,17,83,44,30,13,8.0,3,76,Semi-Urban,Manager,117458,0 +91411,Other,41,Diploma,14,92,74,99,15,7.0,5,45,Urban,Software Engineer,54593,1 +91412,Male,33,Bachelors,12,15,16,7,75,1.0,4,63,Urban,HR Executive,74854,0 +91413,Female,53,Bachelors,6,35,61,64,32,8.0,7,21,Urban,Software Engineer,100461,0 +91414,Female,27,Diploma,1,74,18,55,41,3.0,5,9,Urban,ML Engineer,36282,0 +91415,Female,28,Diploma,6,45,36,14,54,1.0,6,53,Rural,Manager,132448,0 +91416,Male,31,Masters,18,31,8,25,61,2.0,0,19,Urban,Software Engineer,109557,0 +91417,Male,31,Masters,9,6,94,26,99,7.0,7,52,Urban,HR Executive,97623,0 +91418,Male,52,Diploma,8,27,69,42,71,8.0,0,2,Urban,HR Executive,132798,0 +91419,Male,47,Bachelors,2,61,62,38,83,7.0,0,89,Rural,ML Engineer,49998,1 +91420,Female,48,Bachelors,3,21,61,63,48,1.0,2,93,Urban,Manager,109100,0 +91421,Female,55,Bachelors,18,23,96,35,99,6.0,0,62,Urban,Data Analyst,51626,0 +91422,Female,38,Bachelors,11,77,25,98,64,8.0,2,86,Urban,HR Executive,45215,1 +91423,Male,32,Bachelors,18,89,7,93,76,2.0,7,2,Semi-Urban,HR Executive,60577,0 +91424,Male,39,Bachelors,19,91,11,5,18,6.0,3,61,Urban,HR Executive,114778,0 +91425,Female,57,High School,10,37,93,51,37,9.0,3,18,Urban,Manager,134680,0 +91426,Female,28,Masters,18,33,16,17,3,6.0,0,58,Rural,Software Engineer,85498,0 +91427,Male,41,High School,19,8,34,81,39,0.0,5,33,Urban,Manager,126713,0 +91428,Female,42,High School,14,96,14,97,54,6.0,1,13,Rural,Software Engineer,119244,0 +91429,Male,34,Diploma,14,58,81,78,5,2.0,6,10,Semi-Urban,HR Executive,92238,0 +91430,Female,22,Masters,8,42,99,46,0,4.0,4,14,Urban,Manager,123530,0 +91431,Male,27,High School,10,75,40,78,7,0.0,2,58,Rural,Data Analyst,119236,1 +91432,Male,28,Bachelors,8,34,18,37,23,2.0,6,26,Urban,ML Engineer,104523,0 +91433,Male,36,Bachelors,12,28,16,26,58,2.0,6,79,Urban,HR Executive,85427,0 +91434,Female,44,Masters,11,17,8,41,79,1.0,1,43,Semi-Urban,Data Analyst,116334,0 +91435,Female,32,Masters,7,84,77,50,89,7.0,7,60,Urban,HR Executive,40630,1 +91436,Male,27,Bachelors,15,49,8,73,17,1.0,5,2,Urban,Manager,127616,0 +91437,Male,41,Bachelors,16,68,14,67,44,4.0,3,0,Urban,HR Executive,72153,0 +91438,Male,58,Diploma,14,47,43,83,11,8.0,0,84,Urban,Software Engineer,56800,1 +91439,Male,53,Bachelors,12,51,43,72,90,6.0,0,76,Urban,HR Executive,64557,1 +91440,Male,49,Bachelors,16,95,83,32,51,6.0,6,17,Rural,ML Engineer,51822,0 +91441,Male,42,PhD,1,34,52,29,62,4.0,2,64,Semi-Urban,ML Engineer,31620,0 +91442,Female,37,Bachelors,0,54,70,55,60,5.0,6,20,Urban,Software Engineer,112315,0 +91443,Female,55,Bachelors,14,9,27,70,96,5.0,3,41,Urban,HR Executive,83327,0 +91444,Female,35,Bachelors,10,25,75,30,10,9.0,7,21,Semi-Urban,ML Engineer,29274,0 +91445,Male,31,Bachelors,14,75,75,48,91,7.0,6,11,Semi-Urban,ML Engineer,124439,0 +91446,Male,26,Bachelors,18,0,98,29,68,9.0,4,26,Urban,Software Engineer,101642,0 +91447,Male,42,Bachelors,6,89,75,24,92,2.0,6,72,Semi-Urban,Data Analyst,76490,1 +91448,Male,27,Masters,14,66,77,16,54,3.0,1,33,Urban,HR Executive,48153,0 +91449,Female,47,PhD,4,42,71,97,53,9.0,4,52,Rural,ML Engineer,76820,1 +91450,Male,51,Diploma,16,6,30,52,49,6.0,6,71,Semi-Urban,Manager,44078,0 +91451,Male,48,Bachelors,0,86,6,57,61,1.0,3,8,Semi-Urban,Software Engineer,105958,0 +91452,Female,53,Masters,13,85,29,92,0,5.0,3,17,Urban,Software Engineer,133818,0 +91453,Female,29,PhD,18,60,33,42,24,5.0,2,31,Semi-Urban,HR Executive,122978,0 +91454,Female,48,Diploma,10,33,64,16,20,8.0,2,45,Rural,Software Engineer,93200,0 +91455,Male,49,Bachelors,1,68,30,57,27,8.0,7,73,Semi-Urban,ML Engineer,119711,0 +91456,Male,55,Masters,9,86,63,76,63,2.0,4,53,Semi-Urban,Data Analyst,61807,1 +91457,Male,29,High School,16,83,84,4,96,5.0,3,35,Urban,Data Analyst,69430,0 +91458,Male,40,High School,13,93,29,35,65,3.0,5,36,Rural,HR Executive,111561,0 +91459,Male,48,High School,3,96,24,21,86,4.0,6,62,Urban,Data Analyst,69310,0 +91460,Male,28,Masters,9,22,95,7,14,6.0,4,60,Semi-Urban,HR Executive,144670,0 +91461,Male,47,Diploma,4,97,49,15,31,4.0,0,28,Urban,Manager,144193,0 +91462,Male,27,Diploma,8,55,46,18,92,1.0,3,49,Urban,ML Engineer,62285,0 +91463,Male,46,High School,6,16,80,53,81,7.0,7,33,Urban,HR Executive,88333,0 +91464,Male,54,Masters,16,50,9,76,62,4.0,0,61,Urban,Software Engineer,142990,0 +91465,Male,51,Bachelors,17,20,35,22,76,1.0,5,87,Urban,Data Analyst,129984,0 +91466,Female,29,Masters,12,87,17,90,24,6.0,5,57,Urban,ML Engineer,136645,1 +91467,Male,44,Bachelors,3,81,42,61,48,1.0,5,22,Semi-Urban,HR Executive,27864,0 +91468,Female,51,Diploma,6,28,77,25,90,0.0,5,36,Urban,ML Engineer,46464,0 +91469,Other,58,Diploma,3,12,29,17,46,9.0,2,97,Semi-Urban,Data Analyst,112413,0 +91470,Male,38,Masters,2,41,44,45,61,7.0,2,99,Urban,Software Engineer,84123,0 +91471,Male,31,Bachelors,16,35,22,68,4,9.0,5,35,Semi-Urban,Software Engineer,75379,0 +91472,Male,45,Bachelors,10,44,61,36,87,7.0,7,25,Urban,ML Engineer,137221,0 +91473,Male,39,Bachelors,2,31,13,51,22,6.0,0,93,Semi-Urban,Software Engineer,63440,0 +91474,Female,39,Bachelors,2,16,65,28,47,1.0,4,14,Semi-Urban,Data Analyst,76359,0 +91475,Female,22,Bachelors,6,15,7,60,80,5.0,6,56,Urban,Software Engineer,74744,0 +91476,Female,54,Diploma,14,25,39,49,16,7.0,4,2,Urban,Software Engineer,138742,0 +91477,Female,43,Diploma,14,85,93,78,78,3.0,0,8,Urban,HR Executive,74338,1 +91478,Female,55,High School,10,95,94,83,0,7.0,7,30,Rural,ML Engineer,26628,1 +91479,Male,39,Bachelors,14,20,63,71,46,6.0,5,48,Urban,Manager,103185,0 +91480,Male,53,PhD,15,12,70,59,62,4.0,1,2,Urban,ML Engineer,27776,0 +91481,Male,33,High School,8,95,32,5,29,6.0,5,12,Semi-Urban,Software Engineer,108604,0 +91482,Male,44,Bachelors,12,47,4,16,35,6.0,0,99,Semi-Urban,ML Engineer,24973,0 +91483,Female,43,Diploma,7,5,98,20,34,4.0,4,7,Urban,Manager,29611,0 +91484,Male,59,Bachelors,17,39,57,4,89,3.0,7,32,Urban,ML Engineer,149964,0 +91485,Male,54,Bachelors,19,77,60,16,74,8.0,7,81,Urban,Software Engineer,119335,0 +91486,Male,39,Diploma,11,0,2,54,1,7.0,7,99,Urban,HR Executive,127307,0 +91487,Other,46,Bachelors,13,86,80,84,19,4.0,3,35,Semi-Urban,Manager,90116,1 +91488,Female,23,High School,1,92,5,53,43,6.0,0,38,Urban,Software Engineer,80602,0 +91489,Other,46,Masters,7,4,57,69,24,2.0,0,52,Rural,ML Engineer,87358,0 +91490,Other,41,Bachelors,5,64,47,37,84,7.0,0,8,Semi-Urban,Manager,84609,0 +91491,Female,45,High School,9,7,82,22,63,0.0,0,13,Urban,Software Engineer,141176,0 +91492,Male,57,Masters,4,46,9,82,45,1.0,6,18,Urban,Software Engineer,59018,0 +91493,Male,34,Diploma,17,59,21,51,96,9.0,1,89,Urban,Data Analyst,113048,0 +91494,Male,24,Bachelors,19,52,7,84,54,0.0,0,61,Semi-Urban,Manager,44281,0 +91495,Female,22,High School,17,44,96,27,74,8.0,0,40,Urban,Data Analyst,127688,0 +91496,Female,40,Masters,13,61,23,91,90,5.0,3,76,Urban,ML Engineer,21773,1 +91497,Male,34,Bachelors,16,78,10,30,53,6.0,6,49,Semi-Urban,Software Engineer,94482,0 +91498,Male,43,Masters,10,7,25,5,22,9.0,4,54,Rural,Manager,82282,0 +91499,Male,23,High School,19,70,36,17,38,4.0,6,11,Rural,HR Executive,129535,0 +91500,Male,34,Bachelors,13,99,13,96,46,9.0,7,4,Urban,Software Engineer,129558,0 +91501,Male,26,Diploma,15,58,66,91,8,6.0,5,97,Urban,ML Engineer,52174,1 +91502,Male,25,Masters,15,67,26,46,20,7.0,1,91,Urban,Software Engineer,48098,0 +91503,Male,31,Diploma,19,8,54,49,69,8.0,6,62,Urban,Software Engineer,50764,0 +91504,Female,29,Bachelors,5,57,4,30,84,6.0,3,83,Semi-Urban,Manager,71880,0 +91505,Male,50,High School,19,1,43,26,97,6.0,6,22,Rural,Data Analyst,133307,0 +91506,Male,31,Bachelors,7,38,25,14,90,5.0,4,57,Urban,Manager,53997,0 +91507,Male,26,Diploma,4,26,94,26,18,3.0,1,99,Rural,ML Engineer,64603,1 +91508,Female,47,Bachelors,7,65,57,9,31,0.0,1,99,Urban,Software Engineer,74448,0 +91509,Female,35,Masters,4,22,4,14,22,6.0,7,35,Rural,Data Analyst,83589,0 +91510,Male,41,Masters,15,87,60,38,66,0.0,1,61,Rural,Software Engineer,73609,1 +91511,Male,41,Masters,7,9,13,55,28,0.0,6,94,Rural,Manager,28850,0 +91512,Male,35,Diploma,1,79,77,17,97,3.0,5,86,Rural,ML Engineer,48029,1 +91513,Male,46,Diploma,17,78,30,45,9,8.0,4,44,Urban,Software Engineer,104381,0 +91514,Male,39,High School,2,51,12,25,51,9.0,4,64,Rural,Data Analyst,47022,0 +91515,Female,56,Masters,13,70,90,16,42,2.0,3,25,Semi-Urban,HR Executive,88247,0 +91516,Male,52,Bachelors,7,1,68,89,57,7.0,1,55,Urban,Data Analyst,148329,0 +91517,Female,21,PhD,9,87,91,7,47,8.0,6,80,Urban,Software Engineer,29718,1 +91518,Male,34,Diploma,10,81,10,54,79,1.0,2,45,Urban,ML Engineer,80389,0 +91519,Other,37,Bachelors,5,28,45,8,93,1.0,7,1,Urban,Software Engineer,138890,0 +91520,Female,35,Masters,6,66,62,79,91,7.0,2,84,Urban,Data Analyst,70142,1 +91521,Female,28,Bachelors,19,83,89,7,89,9.0,7,16,Urban,Data Analyst,51834,0 +91522,Other,27,Masters,12,61,83,21,99,7.0,2,10,Urban,Manager,97185,0 +91523,Male,29,High School,0,85,86,82,92,8.0,7,71,Urban,Data Analyst,27992,1 +91524,Female,59,Bachelors,2,32,29,72,45,1.0,3,48,Rural,HR Executive,72090,0 +91525,Female,49,High School,5,77,59,68,62,7.0,2,47,Urban,Software Engineer,87705,1 +91526,Male,38,Masters,19,82,48,46,75,2.0,7,16,Rural,Software Engineer,47139,0 +91527,Male,57,Bachelors,5,7,1,30,63,2.0,7,8,Urban,ML Engineer,124192,0 +91528,Female,41,Diploma,12,7,26,9,5,6.0,7,53,Semi-Urban,Manager,147017,0 +91529,Female,45,Bachelors,3,58,87,90,61,5.0,1,47,Semi-Urban,ML Engineer,140835,1 +91530,Female,52,Masters,18,81,13,57,22,1.0,0,79,Semi-Urban,ML Engineer,20112,0 +91531,Female,30,Diploma,5,63,5,67,30,5.0,5,26,Urban,Manager,97838,0 +91532,Male,32,Diploma,2,4,43,81,50,4.0,6,7,Urban,Data Analyst,139190,0 +91533,Female,21,High School,2,54,32,94,26,8.0,6,66,Rural,Software Engineer,24311,1 +91534,Male,46,Bachelors,18,50,79,0,68,9.0,0,84,Semi-Urban,ML Engineer,56757,0 +91535,Female,39,Bachelors,17,50,16,69,13,9.0,1,33,Urban,ML Engineer,30730,0 +91536,Female,42,Bachelors,7,17,98,94,50,5.0,6,26,Urban,Software Engineer,64601,0 +91537,Other,59,Masters,19,71,37,58,3,4.0,2,4,Urban,ML Engineer,144480,0 +91538,Male,28,Masters,7,18,4,89,92,9.0,5,60,Semi-Urban,Manager,32348,0 +91539,Male,58,Diploma,9,48,12,67,98,9.0,7,99,Rural,Software Engineer,35239,0 +91540,Male,58,Diploma,18,99,47,57,86,3.0,6,18,Urban,Software Engineer,72931,0 +91541,Male,55,Diploma,18,18,9,45,28,8.0,5,84,Rural,Data Analyst,107502,0 +91542,Male,41,High School,9,77,21,62,11,4.0,2,26,Urban,ML Engineer,73814,0 +91543,Other,28,Masters,6,25,69,31,46,7.0,0,22,Urban,Software Engineer,136218,0 +91544,Female,27,Bachelors,4,35,2,75,48,5.0,5,92,Urban,Software Engineer,126715,0 +91545,Female,42,Diploma,15,14,46,40,21,1.0,7,64,Urban,Software Engineer,27909,0 +91546,Female,44,Bachelors,11,6,20,12,34,2.0,5,53,Rural,Manager,44468,0 +91547,Female,27,Bachelors,9,61,56,45,17,2.0,7,75,Urban,ML Engineer,131675,0 +91548,Female,30,Bachelors,10,21,89,21,49,4.0,3,14,Semi-Urban,HR Executive,79669,0 +91549,Female,33,Diploma,3,30,92,38,4,3.0,0,62,Rural,Software Engineer,72315,0 +91550,Female,49,Diploma,1,0,91,96,45,0.0,3,5,Urban,Data Analyst,112182,0 +91551,Other,34,Masters,8,83,99,55,84,6.0,6,62,Semi-Urban,Data Analyst,129826,1 +91552,Female,53,Masters,5,66,51,67,18,2.0,5,91,Urban,ML Engineer,89422,1 +91553,Male,28,High School,5,20,98,16,35,0.0,4,16,Urban,Data Analyst,63216,0 +91554,Male,53,High School,18,88,66,17,99,7.0,5,75,Semi-Urban,HR Executive,149829,1 +91555,Female,30,High School,1,68,45,31,32,9.0,7,34,Urban,Software Engineer,61027,0 +91556,Male,52,Bachelors,3,6,39,25,81,0.0,5,71,Urban,ML Engineer,114273,0 +91557,Male,42,Bachelors,2,12,28,48,7,7.0,2,26,Urban,Manager,128554,0 +91558,Female,40,Masters,19,98,40,89,50,0.0,1,81,Rural,ML Engineer,130147,1 +91559,Male,33,PhD,6,2,46,26,85,4.0,0,36,Urban,Data Analyst,57252,0 +91560,Male,48,Diploma,5,42,66,29,57,4.0,4,61,Urban,HR Executive,128112,0 +91561,Female,59,Bachelors,12,18,58,86,47,6.0,7,2,Semi-Urban,Manager,68791,0 +91562,Male,53,High School,3,38,56,87,30,0.0,3,75,Semi-Urban,HR Executive,112874,1 +91563,Female,44,Diploma,17,96,63,26,85,5.0,6,92,Urban,Data Analyst,42564,1 +91564,Male,23,Bachelors,15,85,46,6,49,7.0,3,20,Urban,ML Engineer,118714,0 +91565,Male,59,Masters,1,17,28,44,93,5.0,6,74,Rural,ML Engineer,31181,0 +91566,Female,35,Bachelors,0,54,19,39,30,6.0,6,15,Urban,ML Engineer,134904,0 +91567,Female,56,Diploma,7,2,0,82,8,6.0,0,26,Semi-Urban,Manager,62540,0 +91568,Other,30,Diploma,4,96,97,28,69,3.0,5,98,Urban,ML Engineer,97192,1 +91569,Male,57,High School,13,86,25,43,48,3.0,4,4,Rural,ML Engineer,25298,0 +91570,Female,56,Diploma,4,71,89,39,9,2.0,2,7,Urban,HR Executive,129679,0 +91571,Female,48,Diploma,16,13,33,35,31,3.0,3,84,Semi-Urban,Software Engineer,145498,0 +91572,Male,30,Bachelors,14,21,19,41,76,5.0,5,67,Rural,HR Executive,56918,0 +91573,Other,57,Bachelors,8,78,58,72,94,3.0,2,62,Urban,Software Engineer,63523,1 +91574,Male,49,High School,6,1,77,65,86,8.0,4,87,Semi-Urban,Manager,82521,0 +91575,Female,43,Diploma,17,43,3,55,66,3.0,0,67,Urban,ML Engineer,46187,0 +91576,Female,40,Bachelors,16,46,58,38,13,7.0,7,81,Semi-Urban,Software Engineer,43873,0 +91577,Male,30,PhD,2,52,35,42,45,6.0,6,4,Semi-Urban,Data Analyst,25564,0 +91578,Male,40,High School,17,7,31,4,65,4.0,7,19,Urban,Software Engineer,76184,0 +91579,Male,49,Bachelors,16,65,49,64,37,3.0,3,94,Urban,Manager,102646,1 +91580,Male,33,Bachelors,3,41,9,78,0,7.0,3,91,Urban,ML Engineer,127407,0 +91581,Female,56,Masters,17,9,31,87,23,5.0,2,19,Urban,Manager,144476,0 +91582,Female,22,High School,1,94,61,62,94,3.0,5,44,Semi-Urban,Manager,86270,1 +91583,Male,45,Diploma,12,76,97,74,5,4.0,3,17,Urban,Data Analyst,48982,1 +91584,Female,40,Masters,15,90,86,44,62,6.0,2,18,Rural,HR Executive,49896,0 +91585,Male,46,Bachelors,16,48,98,68,92,8.0,4,10,Rural,Manager,135461,0 +91586,Male,27,Bachelors,1,98,63,20,83,1.0,4,51,Rural,ML Engineer,61123,0 +91587,Male,32,Bachelors,11,0,84,93,3,5.0,4,46,Urban,Data Analyst,115679,0 +91588,Female,58,High School,0,87,71,29,32,2.0,4,23,Urban,Software Engineer,135907,0 +91589,Female,33,Diploma,13,55,88,34,11,7.0,1,2,Rural,Data Analyst,131946,0 +91590,Male,26,Diploma,18,20,84,44,59,2.0,3,23,Rural,ML Engineer,25253,0 +91591,Male,32,Bachelors,0,88,96,93,50,9.0,5,6,Urban,Software Engineer,136239,1 +91592,Male,23,Bachelors,15,95,21,70,78,1.0,4,68,Semi-Urban,Manager,86301,1 +91593,Male,27,Bachelors,18,2,22,21,18,2.0,1,26,Semi-Urban,Data Analyst,43985,0 +91594,Male,22,Bachelors,3,67,77,53,40,4.0,6,69,Rural,HR Executive,145754,1 +91595,Male,52,Bachelors,7,96,14,59,35,5.0,6,19,Rural,Software Engineer,43812,0 +91596,Female,52,Bachelors,4,24,18,18,45,6.0,2,84,Urban,ML Engineer,135568,0 +91597,Male,26,Masters,2,50,25,49,60,2.0,0,29,Urban,HR Executive,51709,0 +91598,Female,37,Bachelors,7,38,51,90,45,2.0,7,74,Semi-Urban,ML Engineer,144347,1 +91599,Female,43,Diploma,4,16,25,52,37,0.0,6,59,Urban,Software Engineer,33421,0 +91600,Female,45,Masters,3,84,77,15,60,5.0,0,49,Urban,Manager,51543,0 +91601,Female,31,Bachelors,12,71,88,51,92,8.0,2,12,Urban,Data Analyst,117492,0 +91602,Male,33,High School,16,46,35,86,58,4.0,6,36,Semi-Urban,HR Executive,134804,0 +91603,Female,25,Masters,19,69,46,90,17,6.0,2,49,Urban,ML Engineer,25508,1 +91604,Female,50,Bachelors,0,20,17,58,70,1.0,3,99,Semi-Urban,Data Analyst,20804,0 +91605,Male,24,High School,19,20,10,49,22,0.0,3,93,Semi-Urban,ML Engineer,26707,0 +91606,Male,22,PhD,15,51,76,10,86,0.0,7,89,Semi-Urban,Data Analyst,60329,0 +91607,Male,56,Diploma,1,51,15,95,79,9.0,7,20,Urban,HR Executive,64165,0 +91608,Male,28,Bachelors,5,69,82,43,8,6.0,3,23,Rural,HR Executive,137432,0 +91609,Male,49,High School,3,31,85,61,62,1.0,7,87,Urban,Data Analyst,131414,1 +91610,Female,22,Diploma,5,6,50,10,3,8.0,1,76,Semi-Urban,Software Engineer,132838,0 +91611,Male,22,Masters,2,50,98,19,42,6.0,1,35,Rural,Manager,39011,0 +91612,Male,29,Masters,3,27,35,12,22,5.0,7,98,Rural,ML Engineer,33735,0 +91613,Male,51,Bachelors,7,43,58,41,88,9.0,5,47,Semi-Urban,ML Engineer,22757,0 +91614,Female,58,Diploma,4,24,20,83,68,4.0,6,90,Rural,Software Engineer,140920,0 +91615,Female,37,High School,3,50,86,66,84,8.0,0,25,Urban,ML Engineer,102763,0 +91616,Male,35,Bachelors,7,86,73,75,63,4.0,6,45,Semi-Urban,HR Executive,73872,1 +91617,Male,41,Diploma,9,45,58,76,76,9.0,4,47,Urban,Data Analyst,59760,0 +91618,Female,37,Bachelors,5,63,2,39,49,5.0,7,75,Urban,Manager,22705,0 +91619,Male,34,High School,12,16,20,71,6,0.0,4,39,Rural,ML Engineer,45175,0 +91620,Female,50,Bachelors,8,28,82,47,62,7.0,7,25,Urban,ML Engineer,47783,0 +91621,Female,27,Diploma,14,71,84,36,45,0.0,0,50,Urban,Manager,54362,1 +91622,Female,33,High School,17,81,18,49,54,8.0,6,4,Urban,HR Executive,49870,0 +91623,Other,36,Bachelors,2,56,90,39,4,9.0,2,70,Semi-Urban,Software Engineer,41166,1 +91624,Male,35,Bachelors,19,44,47,28,15,5.0,3,84,Urban,Software Engineer,22896,0 +91625,Male,45,Masters,1,62,44,57,60,5.0,6,33,Semi-Urban,ML Engineer,41519,0 +91626,Male,34,Diploma,6,13,88,96,10,6.0,6,85,Rural,HR Executive,50686,1 +91627,Male,21,PhD,15,68,60,60,7,6.0,0,17,Rural,Data Analyst,124493,0 +91628,Male,47,Bachelors,17,11,82,28,13,7.0,0,93,Semi-Urban,Manager,144504,0 +91629,Male,22,Bachelors,19,59,34,41,24,5.0,5,17,Rural,Manager,80188,0 +91630,Male,50,Masters,16,94,57,17,75,9.0,0,21,Urban,Manager,114133,0 +91631,Female,41,Diploma,14,23,72,10,13,8.0,1,29,Rural,Software Engineer,49592,0 +91632,Male,24,Bachelors,15,8,13,11,56,2.0,1,16,Urban,Software Engineer,22436,0 +91633,Female,22,Bachelors,14,56,13,61,81,7.0,5,41,Urban,Software Engineer,42457,0 +91634,Male,22,Bachelors,7,21,40,46,73,1.0,4,3,Urban,Manager,133829,0 +91635,Male,37,Bachelors,9,11,44,17,14,0.0,7,25,Urban,HR Executive,83490,0 +91636,Other,59,Bachelors,10,4,50,96,11,3.0,0,40,Urban,Data Analyst,103574,0 +91637,Male,57,Diploma,16,24,38,9,11,4.0,6,47,Urban,HR Executive,113549,0 +91638,Female,24,Bachelors,15,35,14,6,84,3.0,0,32,Rural,ML Engineer,93188,0 +91639,Female,48,Diploma,10,35,56,11,17,8.0,3,46,Urban,Manager,109418,0 +91640,Male,53,High School,9,45,16,63,54,5.0,0,96,Urban,Software Engineer,115281,0 +91641,Male,46,High School,2,85,86,25,5,5.0,2,73,Urban,Software Engineer,56022,1 +91642,Male,36,Bachelors,8,76,5,74,70,1.0,1,31,Rural,HR Executive,85500,0 +91643,Female,22,Diploma,10,75,44,59,12,2.0,4,2,Urban,Data Analyst,85516,0 +91644,Female,23,Bachelors,8,21,33,0,12,7.0,0,5,Semi-Urban,ML Engineer,137206,0 +91645,Male,25,High School,5,58,19,76,85,2.0,7,53,Semi-Urban,Manager,131325,0 +91646,Male,29,Bachelors,1,6,31,6,32,5.0,6,32,Rural,Manager,27568,0 +91647,Male,26,PhD,6,58,96,48,15,6.0,5,98,Rural,HR Executive,21438,1 +91648,Female,31,High School,1,11,35,26,38,7.0,3,39,Urban,Data Analyst,112355,0 +91649,Female,36,High School,17,20,57,61,48,3.0,1,11,Urban,HR Executive,109781,0 +91650,Female,49,Masters,14,81,74,81,92,7.0,1,73,Urban,ML Engineer,128191,1 +91651,Male,23,Diploma,13,42,8,35,82,4.0,2,15,Rural,Software Engineer,146116,0 +91652,Female,28,High School,0,44,31,83,77,2.0,1,74,Rural,Manager,137639,0 +91653,Male,43,Bachelors,4,27,15,45,72,8.0,2,94,Rural,ML Engineer,147768,0 +91654,Other,53,Masters,13,82,57,69,72,6.0,6,1,Rural,Data Analyst,31952,0 +91655,Female,26,Diploma,18,80,92,14,85,1.0,5,52,Urban,HR Executive,30895,0 +91656,Other,59,Masters,2,68,87,78,84,9.0,5,39,Semi-Urban,ML Engineer,66311,1 +91657,Male,43,PhD,3,51,41,15,64,1.0,2,69,Semi-Urban,ML Engineer,112719,0 +91658,Female,26,Bachelors,3,79,20,88,63,6.0,3,22,Urban,ML Engineer,50393,0 +91659,Female,24,Bachelors,14,36,89,0,24,7.0,5,96,Urban,Manager,77019,0 +91660,Male,59,Bachelors,4,77,29,57,1,7.0,5,24,Semi-Urban,ML Engineer,74457,0 +91661,Female,30,Masters,16,81,28,59,76,9.0,2,20,Semi-Urban,Software Engineer,68899,0 +91662,Female,32,Bachelors,0,28,66,16,46,0.0,2,23,Rural,Data Analyst,60741,0 +91663,Female,47,Masters,14,54,78,45,67,1.0,2,87,Rural,HR Executive,33816,1 +91664,Male,47,Bachelors,1,31,63,90,47,5.0,3,18,Semi-Urban,Software Engineer,123843,0 +91665,Other,59,Bachelors,8,53,18,7,78,3.0,7,72,Urban,Software Engineer,107297,0 +91666,Female,30,Bachelors,2,93,95,98,19,3.0,5,81,Urban,ML Engineer,101690,1 +91667,Other,22,Bachelors,10,52,94,13,44,5.0,1,0,Semi-Urban,Software Engineer,102205,0 +91668,Male,52,Bachelors,11,4,7,7,1,9.0,2,34,Rural,HR Executive,46717,0 +91669,Female,27,Diploma,13,49,41,87,84,7.0,3,41,Semi-Urban,ML Engineer,36328,0 +91670,Female,52,Masters,17,26,26,56,67,9.0,3,27,Rural,Data Analyst,122119,0 +91671,Male,36,Bachelors,0,37,76,1,9,5.0,3,11,Rural,Software Engineer,128341,0 +91672,Male,59,Bachelors,13,59,10,54,72,4.0,4,20,Urban,HR Executive,82596,0 +91673,Female,37,Bachelors,7,80,30,50,88,5.0,7,17,Urban,HR Executive,145233,0 +91674,Female,49,Masters,0,7,60,92,35,5.0,1,98,Urban,Data Analyst,117169,1 +91675,Female,52,PhD,11,52,48,18,10,4.0,0,54,Urban,Software Engineer,42343,0 +91676,Female,48,Bachelors,15,8,82,5,65,5.0,0,78,Semi-Urban,Manager,86166,0 +91677,Male,22,Masters,8,70,62,34,92,2.0,0,39,Urban,ML Engineer,112156,0 +91678,Other,46,Diploma,11,5,82,57,10,2.0,2,84,Semi-Urban,Software Engineer,87155,0 +91679,Male,34,PhD,12,47,2,95,43,7.0,4,43,Urban,Software Engineer,107233,0 +91680,Female,43,PhD,5,15,41,14,80,1.0,6,25,Urban,Manager,66439,0 +91681,Male,53,Bachelors,12,11,57,0,66,0.0,2,84,Semi-Urban,ML Engineer,126135,0 +91682,Male,28,Diploma,9,8,71,76,13,0.0,3,41,Semi-Urban,HR Executive,138098,0 +91683,Female,50,Masters,12,24,27,52,86,7.0,1,19,Urban,Software Engineer,87878,0 +91684,Male,50,High School,12,84,71,3,9,2.0,0,1,Urban,Data Analyst,80606,0 +91685,Male,23,High School,9,19,87,28,16,1.0,1,82,Urban,ML Engineer,78842,0 +91686,Male,39,Diploma,19,61,95,91,38,5.0,3,32,Urban,Manager,112585,1 +91687,Female,59,Bachelors,17,65,26,84,47,1.0,3,4,Rural,Data Analyst,138956,0 +91688,Female,33,Diploma,18,32,81,12,10,4.0,3,6,Rural,HR Executive,113284,0 +91689,Male,31,Bachelors,14,54,4,12,10,4.0,7,57,Semi-Urban,ML Engineer,138824,0 +91690,Male,41,Diploma,14,17,92,86,2,6.0,2,15,Urban,Data Analyst,79204,0 +91691,Male,46,Diploma,17,88,15,75,36,1.0,7,82,Urban,ML Engineer,50659,1 +91692,Male,30,Bachelors,12,13,3,74,3,6.0,7,28,Urban,Data Analyst,106747,0 +91693,Male,41,Masters,11,82,37,13,33,2.0,3,0,Urban,Manager,58537,0 +91694,Male,33,Masters,11,39,73,85,84,9.0,4,70,Urban,HR Executive,117026,1 +91695,Female,59,High School,17,53,87,88,73,4.0,2,91,Urban,Manager,144869,1 +91696,Male,34,Bachelors,0,19,50,58,5,2.0,2,39,Semi-Urban,Manager,114251,0 +91697,Male,33,Bachelors,15,85,21,54,33,0.0,6,70,Semi-Urban,ML Engineer,47131,0 +91698,Male,28,Bachelors,17,58,31,16,88,7.0,0,53,Urban,Manager,108095,0 +91699,Female,36,Masters,10,98,89,94,34,6.0,1,56,Rural,Data Analyst,43993,1 +91700,Male,49,High School,13,14,86,12,98,1.0,5,52,Semi-Urban,Manager,55523,0 +91701,Female,28,PhD,19,56,8,66,56,2.0,7,82,Rural,Manager,108267,0 +91702,Male,22,PhD,16,49,74,72,50,3.0,7,27,Rural,Data Analyst,45221,0 +91703,Male,41,High School,16,66,28,95,16,4.0,1,23,Semi-Urban,ML Engineer,26137,0 +91704,Male,57,Diploma,11,42,24,60,90,1.0,0,69,Urban,Manager,28618,0 +91705,Female,24,Bachelors,18,37,66,16,49,9.0,4,15,Semi-Urban,Data Analyst,102863,0 +91706,Female,32,Masters,6,68,71,68,72,7.0,2,80,Urban,HR Executive,56370,1 +91707,Female,55,Bachelors,19,47,3,55,62,8.0,7,23,Rural,Data Analyst,92118,0 +91708,Female,49,Bachelors,9,84,7,96,92,9.0,6,9,Urban,Software Engineer,49124,0 +91709,Male,30,High School,16,10,90,26,67,6.0,7,28,Semi-Urban,ML Engineer,100835,0 +91710,Female,36,High School,15,77,45,5,43,2.0,4,53,Urban,Software Engineer,145819,0 +91711,Male,49,High School,5,93,20,86,94,3.0,6,82,Urban,ML Engineer,59358,1 +91712,Female,30,Masters,3,5,68,68,51,3.0,6,78,Urban,ML Engineer,111162,0 +91713,Female,23,Bachelors,2,34,36,53,27,4.0,7,37,Urban,Manager,45779,0 +91714,Male,24,Diploma,19,89,55,82,7,3.0,5,99,Urban,Manager,76198,1 +91715,Male,44,High School,4,54,63,56,63,0.0,5,72,Semi-Urban,Data Analyst,78325,1 +91716,Female,30,Bachelors,2,70,1,42,53,2.0,2,11,Urban,HR Executive,45529,0 +91717,Male,54,High School,9,90,21,12,97,6.0,5,66,Rural,HR Executive,134446,0 +91718,Female,47,Masters,19,52,17,0,6,6.0,0,29,Urban,Manager,38281,0 +91719,Male,29,PhD,4,99,41,67,9,3.0,7,33,Rural,HR Executive,128135,1 +91720,Male,54,Bachelors,15,85,35,94,49,1.0,7,52,Rural,ML Engineer,83425,1 +91721,Male,23,High School,9,90,84,42,62,3.0,2,64,Rural,ML Engineer,42500,1 +91722,Male,56,Masters,19,55,82,2,1,5.0,3,51,Rural,HR Executive,126533,0 +91723,Male,53,Masters,2,89,11,86,86,4.0,6,99,Urban,Data Analyst,76225,1 +91724,Male,50,Masters,14,17,3,18,87,3.0,6,66,Rural,Data Analyst,127653,0 +91725,Female,25,Bachelors,2,6,69,59,0,9.0,5,51,Semi-Urban,ML Engineer,137295,0 +91726,Male,38,Diploma,3,0,65,11,5,1.0,4,55,Urban,HR Executive,70881,0 +91727,Female,55,Bachelors,12,81,54,62,9,1.0,4,18,Urban,Software Engineer,122412,0 +91728,Other,26,Bachelors,15,83,90,88,4,3.0,7,95,Semi-Urban,Software Engineer,134729,1 +91729,Female,43,Diploma,7,25,21,48,72,7.0,3,56,Urban,Manager,80048,0 +91730,Male,52,Diploma,4,29,92,97,80,8.0,2,78,Urban,Data Analyst,63366,1 +91731,Male,35,Masters,17,0,14,23,70,4.0,6,3,Urban,HR Executive,99130,0 +91732,Female,46,Masters,17,81,41,12,63,3.0,4,85,Urban,Data Analyst,47500,0 +91733,Other,49,PhD,17,40,60,82,91,9.0,0,70,Urban,HR Executive,74941,1 +91734,Female,24,Bachelors,15,7,81,93,79,7.0,3,3,Semi-Urban,HR Executive,115994,0 +91735,Male,58,PhD,3,99,35,13,10,1.0,2,80,Rural,Data Analyst,102261,0 +91736,Male,45,PhD,8,4,38,66,78,3.0,7,71,Rural,ML Engineer,97192,0 +91737,Female,32,Bachelors,14,19,91,45,70,8.0,7,40,Semi-Urban,ML Engineer,36135,0 +91738,Female,31,PhD,16,84,37,75,52,9.0,7,57,Semi-Urban,HR Executive,72041,1 +91739,Male,32,Bachelors,8,88,8,13,20,1.0,7,97,Urban,ML Engineer,135819,0 +91740,Male,26,Bachelors,7,94,21,40,21,2.0,0,24,Rural,Software Engineer,102029,0 +91741,Female,42,Bachelors,18,75,73,52,17,8.0,4,62,Rural,Software Engineer,144773,1 +91742,Male,41,Bachelors,6,33,17,29,9,7.0,2,46,Urban,HR Executive,143111,0 +91743,Male,42,Diploma,18,63,54,58,7,4.0,6,95,Semi-Urban,Manager,113814,1 +91744,Female,30,High School,11,70,30,74,11,7.0,2,18,Semi-Urban,Manager,65720,0 +91745,Male,38,Bachelors,1,66,87,52,11,5.0,0,32,Urban,ML Engineer,114192,1 +91746,Female,35,Diploma,16,87,50,50,83,0.0,3,34,Semi-Urban,Data Analyst,53863,0 +91747,Female,27,Masters,14,12,10,89,54,4.0,2,59,Urban,ML Engineer,130437,0 +91748,Male,33,Diploma,15,41,4,98,27,0.0,3,43,Rural,Data Analyst,67472,0 +91749,Male,26,High School,5,60,57,82,29,4.0,5,94,Urban,Data Analyst,46394,1 +91750,Female,57,High School,7,81,81,32,35,9.0,1,59,Urban,ML Engineer,102714,1 +91751,Female,48,Masters,0,29,59,30,44,7.0,4,15,Urban,HR Executive,136983,0 +91752,Male,40,Masters,13,14,44,90,33,8.0,1,21,Rural,Data Analyst,29480,0 +91753,Male,53,Bachelors,15,80,91,32,80,3.0,0,40,Urban,HR Executive,58472,1 +91754,Female,31,Masters,1,76,20,34,45,9.0,1,44,Semi-Urban,ML Engineer,130084,0 +91755,Male,59,Bachelors,18,19,9,64,43,9.0,0,42,Urban,HR Executive,76396,0 +91756,Male,43,Bachelors,14,67,55,79,24,8.0,3,72,Urban,ML Engineer,66851,1 +91757,Female,23,High School,16,14,45,95,60,8.0,2,7,Semi-Urban,Manager,52000,0 +91758,Female,45,Bachelors,13,53,64,74,9,1.0,1,65,Urban,Data Analyst,66174,1 +91759,Male,45,Bachelors,4,61,3,54,71,2.0,5,2,Rural,Software Engineer,130777,0 +91760,Male,38,Masters,10,81,9,42,62,9.0,0,0,Urban,Software Engineer,124562,0 +91761,Male,54,Bachelors,18,42,21,35,6,1.0,6,71,Rural,Software Engineer,103846,0 +91762,Male,21,Diploma,15,93,78,59,76,7.0,1,92,Urban,HR Executive,123078,1 +91763,Male,46,Masters,3,64,65,2,28,3.0,6,57,Urban,Data Analyst,66360,0 +91764,Male,46,Bachelors,16,49,78,86,14,2.0,6,55,Urban,ML Engineer,61161,1 +91765,Female,27,Bachelors,5,15,91,9,45,9.0,0,9,Urban,HR Executive,121389,0 +91766,Male,44,Bachelors,5,92,51,7,9,4.0,2,61,Rural,Software Engineer,145350,0 +91767,Male,23,Bachelors,18,43,50,95,1,9.0,6,63,Urban,Software Engineer,54281,1 +91768,Female,41,Diploma,6,95,76,9,20,2.0,1,37,Semi-Urban,Data Analyst,46971,0 +91769,Female,33,Diploma,7,91,10,1,95,5.0,6,88,Urban,Manager,47762,0 +91770,Male,25,Bachelors,3,5,97,92,90,0.0,3,49,Urban,Manager,91266,1 +91771,Male,32,Bachelors,2,30,74,6,79,0.0,4,26,Urban,Manager,106563,0 +91772,Male,27,Bachelors,1,62,16,90,70,4.0,5,90,Urban,ML Engineer,86972,1 +91773,Male,46,Bachelors,10,81,19,42,93,3.0,6,31,Urban,Data Analyst,138018,0 +91774,Male,33,Diploma,19,10,31,96,9,0.0,5,81,Urban,Manager,23285,0 +91775,Other,37,Masters,17,3,30,88,24,1.0,4,39,Semi-Urban,HR Executive,92348,0 +91776,Male,32,Masters,8,66,59,73,45,5.0,3,99,Rural,Manager,62677,1 +91777,Male,29,Bachelors,16,27,52,83,39,9.0,2,55,Urban,HR Executive,147846,0 +91778,Male,23,Bachelors,5,96,60,40,2,0.0,6,18,Urban,Manager,51733,0 +91779,Female,55,Bachelors,6,10,63,4,83,6.0,4,19,Urban,Data Analyst,113813,0 +91780,Female,27,Masters,8,96,33,62,32,2.0,4,72,Urban,Manager,27279,1 +91781,Male,30,Bachelors,19,97,81,99,40,6.0,0,91,Rural,Software Engineer,30728,1 +91782,Female,56,High School,11,24,94,10,76,1.0,0,25,Semi-Urban,ML Engineer,80779,0 +91783,Male,51,Bachelors,0,97,45,15,13,1.0,0,7,Urban,Manager,111886,0 +91784,Male,29,High School,13,47,67,82,67,9.0,0,41,Urban,Software Engineer,142850,1 +91785,Male,57,Bachelors,5,95,23,0,66,7.0,7,14,Urban,Data Analyst,36125,0 +91786,Male,55,Masters,17,14,37,36,28,3.0,7,58,Rural,Manager,22060,0 +91787,Male,35,Bachelors,17,22,77,90,73,1.0,5,24,Rural,Data Analyst,53176,0 +91788,Female,36,Masters,15,34,53,55,53,6.0,3,4,Urban,ML Engineer,147261,0 +91789,Female,56,Masters,19,72,4,43,51,9.0,1,97,Semi-Urban,Software Engineer,103003,0 +91790,Female,37,Masters,15,27,47,15,15,3.0,2,50,Semi-Urban,HR Executive,83658,0 +91791,Male,55,Diploma,2,9,66,51,16,0.0,4,4,Urban,Software Engineer,34062,0 +91792,Male,27,Bachelors,19,42,86,12,2,6.0,7,97,Urban,Manager,74325,1 +91793,Male,52,High School,14,93,18,97,0,7.0,7,99,Urban,Software Engineer,85532,1 +91794,Male,37,Diploma,8,12,77,50,31,1.0,3,7,Semi-Urban,Manager,133419,0 +91795,Male,57,Masters,6,72,3,86,33,6.0,2,7,Urban,Software Engineer,68553,0 +91796,Female,56,Diploma,9,11,96,57,47,9.0,1,51,Rural,HR Executive,79604,0 +91797,Male,58,Bachelors,18,28,33,39,16,3.0,0,21,Urban,ML Engineer,64452,0 +91798,Male,39,Diploma,8,42,6,72,48,0.0,7,58,Urban,Data Analyst,102576,0 +91799,Other,31,Diploma,10,99,61,12,50,1.0,4,85,Semi-Urban,ML Engineer,39711,1 +91800,Male,45,Bachelors,0,60,29,37,22,8.0,4,13,Urban,HR Executive,32797,0 +91801,Male,32,Diploma,2,17,78,8,66,7.0,6,18,Semi-Urban,HR Executive,130059,0 +91802,Male,29,Masters,14,78,2,64,77,1.0,5,23,Urban,HR Executive,85012,0 +91803,Other,55,Bachelors,19,64,50,4,18,9.0,1,74,Urban,HR Executive,123857,0 +91804,Female,25,PhD,2,29,37,93,52,9.0,0,25,Rural,Data Analyst,89883,0 +91805,Male,58,Bachelors,0,82,94,51,83,4.0,0,98,Urban,ML Engineer,45763,1 +91806,Male,50,Diploma,19,32,9,85,56,8.0,5,67,Urban,Manager,113045,0 +91807,Male,56,Diploma,0,78,89,46,5,0.0,5,87,Urban,Software Engineer,106396,1 +91808,Male,53,Diploma,18,63,8,10,57,3.0,7,61,Urban,HR Executive,27417,0 +91809,Male,40,Bachelors,9,9,64,37,43,0.0,7,48,Urban,HR Executive,142835,0 +91810,Male,24,Bachelors,0,85,53,86,85,7.0,1,53,Semi-Urban,HR Executive,44341,1 +91811,Male,56,Bachelors,8,36,30,14,64,2.0,4,80,Semi-Urban,ML Engineer,101036,0 +91812,Other,38,Masters,8,13,45,51,34,1.0,0,14,Urban,ML Engineer,97852,0 +91813,Female,39,Bachelors,0,98,7,8,0,9.0,0,90,Urban,Manager,115301,0 +91814,Male,27,High School,7,99,31,69,59,3.0,3,8,Semi-Urban,Manager,121623,0 +91815,Female,26,Bachelors,11,19,71,61,7,5.0,6,82,Rural,HR Executive,118102,0 +91816,Other,26,High School,14,28,68,58,12,3.0,1,70,Rural,HR Executive,31473,0 +91817,Female,43,PhD,15,28,59,13,37,9.0,4,35,Urban,Data Analyst,59484,0 +91818,Male,56,Bachelors,12,32,77,27,33,2.0,1,2,Rural,ML Engineer,112171,0 +91819,Male,39,Bachelors,0,30,43,56,90,3.0,1,55,Urban,Software Engineer,111710,0 +91820,Female,29,Bachelors,3,14,92,10,62,2.0,2,41,Semi-Urban,HR Executive,135029,0 +91821,Female,28,Bachelors,13,44,72,54,69,6.0,3,96,Urban,HR Executive,44477,1 +91822,Male,48,High School,6,71,70,83,98,9.0,4,0,Urban,HR Executive,146154,0 +91823,Male,25,Diploma,6,0,94,68,88,9.0,4,58,Urban,Manager,57760,0 +91824,Female,59,Masters,14,50,52,14,81,9.0,0,89,Urban,HR Executive,105456,0 +91825,Female,44,Bachelors,1,6,46,93,14,1.0,7,71,Urban,HR Executive,30588,0 +91826,Male,53,Bachelors,10,93,29,24,32,6.0,7,70,Rural,Software Engineer,116962,0 +91827,Other,24,High School,16,38,5,93,73,3.0,2,23,Urban,Manager,136148,0 +91828,Male,44,Masters,11,9,23,13,31,2.0,5,65,Rural,Software Engineer,20590,0 +91829,Male,52,Bachelors,15,87,29,93,6,6.0,7,46,Rural,Software Engineer,83721,1 +91830,Male,50,Bachelors,12,18,96,6,21,1.0,5,27,Rural,Software Engineer,110941,0 +91831,Male,44,Bachelors,3,55,50,17,69,0.0,0,17,Urban,Software Engineer,142886,0 +91832,Male,32,High School,17,29,94,75,73,7.0,3,12,Semi-Urban,Software Engineer,55078,0 +91833,Male,46,High School,8,88,23,21,15,2.0,2,75,Rural,Software Engineer,45738,0 +91834,Female,43,PhD,8,98,95,13,32,3.0,0,38,Urban,ML Engineer,21185,1 +91835,Male,57,Masters,19,37,73,71,6,5.0,6,19,Rural,ML Engineer,136035,0 +91836,Male,36,Bachelors,1,71,82,59,73,2.0,3,54,Semi-Urban,ML Engineer,117613,1 +91837,Male,54,Bachelors,14,20,62,6,21,8.0,1,51,Urban,HR Executive,25993,0 +91838,Other,38,High School,3,91,7,18,9,4.0,7,60,Semi-Urban,HR Executive,65733,0 +91839,Male,21,Masters,7,74,2,49,7,5.0,6,38,Urban,Software Engineer,57149,0 +91840,Male,26,High School,0,42,21,22,16,8.0,7,24,Urban,HR Executive,127928,0 +91841,Male,42,Bachelors,10,12,17,59,80,8.0,4,9,Urban,Software Engineer,48251,0 +91842,Female,38,Bachelors,4,81,74,78,43,4.0,2,92,Urban,Data Analyst,26969,1 +91843,Female,27,Bachelors,14,24,73,91,49,2.0,7,71,Semi-Urban,ML Engineer,57805,1 +91844,Male,58,Bachelors,13,39,3,48,28,7.0,6,13,Semi-Urban,HR Executive,124123,0 +91845,Male,41,Bachelors,1,58,15,39,51,8.0,1,61,Semi-Urban,ML Engineer,56832,0 +91846,Male,24,High School,12,96,45,80,8,5.0,2,97,Semi-Urban,Manager,42480,1 +91847,Female,53,Diploma,17,56,53,9,91,0.0,6,9,Rural,Software Engineer,83994,0 +91848,Male,35,High School,8,57,32,76,15,8.0,3,26,Urban,Data Analyst,101736,0 +91849,Male,47,Diploma,11,23,84,80,95,3.0,6,70,Rural,ML Engineer,142317,1 +91850,Male,57,Bachelors,3,99,94,12,48,8.0,0,93,Urban,Manager,27445,1 +91851,Other,47,Diploma,18,9,73,88,65,3.0,6,16,Rural,Data Analyst,127331,0 +91852,Male,37,Diploma,18,27,51,71,18,0.0,6,33,Urban,Data Analyst,81232,0 +91853,Other,51,Bachelors,11,44,62,84,40,2.0,3,25,Urban,Data Analyst,146647,0 +91854,Female,35,Diploma,15,96,48,44,72,7.0,2,37,Urban,ML Engineer,120027,0 +91855,Male,24,Diploma,11,74,41,90,55,7.0,6,94,Rural,Data Analyst,113801,1 +91856,Female,38,Bachelors,19,97,0,55,15,2.0,0,91,Urban,Manager,23712,1 +91857,Female,55,Masters,10,21,38,50,78,6.0,4,74,Urban,ML Engineer,54745,0 +91858,Male,49,Bachelors,2,77,92,56,67,2.0,7,69,Urban,Data Analyst,28237,1 +91859,Female,33,Diploma,8,57,54,93,32,9.0,6,51,Rural,ML Engineer,100528,1 +91860,Male,41,Bachelors,9,73,36,38,97,8.0,7,53,Semi-Urban,ML Engineer,25365,0 +91861,Female,34,High School,6,29,81,0,5,0.0,4,77,Urban,HR Executive,97403,0 +91862,Female,38,Bachelors,10,19,82,62,85,8.0,4,92,Semi-Urban,Software Engineer,36693,1 +91863,Male,25,Diploma,10,83,0,83,91,2.0,1,25,Rural,ML Engineer,25398,0 +91864,Female,29,High School,5,7,91,40,32,6.0,7,91,Urban,Software Engineer,22361,0 +91865,Female,52,Diploma,11,7,50,74,1,3.0,1,96,Urban,Manager,98518,0 +91866,Male,21,Bachelors,19,73,87,92,67,3.0,1,32,Rural,Manager,76096,1 +91867,Male,59,Bachelors,16,36,52,92,22,6.0,2,25,Urban,Data Analyst,96348,0 +91868,Male,24,Bachelors,15,6,24,34,27,4.0,6,75,Semi-Urban,ML Engineer,83885,0 +91869,Male,41,High School,4,42,24,26,77,9.0,4,3,Urban,Manager,90938,0 +91870,Female,25,Bachelors,12,16,26,95,90,5.0,6,80,Urban,Data Analyst,32444,0 +91871,Male,56,PhD,3,97,85,77,32,9.0,5,96,Urban,Data Analyst,31794,1 +91872,Female,45,Bachelors,7,70,73,7,4,0.0,6,93,Urban,Software Engineer,73561,1 +91873,Male,32,Bachelors,13,40,12,32,12,4.0,0,6,Semi-Urban,Software Engineer,41776,0 +91874,Male,45,Diploma,18,89,35,60,15,4.0,4,18,Urban,Software Engineer,72175,0 +91875,Female,48,High School,12,17,67,33,80,3.0,6,21,Urban,HR Executive,141220,0 +91876,Female,26,Bachelors,18,95,84,91,17,2.0,2,39,Rural,HR Executive,49601,1 +91877,Male,47,Diploma,3,91,53,20,42,1.0,6,97,Urban,Manager,128783,1 +91878,Female,52,Bachelors,18,90,32,1,96,1.0,5,28,Semi-Urban,HR Executive,136682,0 +91879,Female,38,Diploma,12,3,36,81,59,2.0,6,40,Urban,HR Executive,118836,0 +91880,Male,40,PhD,14,18,78,4,37,2.0,6,85,Urban,ML Engineer,80744,0 +91881,Male,41,Bachelors,18,94,87,28,47,4.0,1,17,Urban,HR Executive,44635,0 +91882,Female,40,Bachelors,13,89,88,83,48,4.0,0,91,Urban,Manager,54598,1 +91883,Female,34,Diploma,18,68,76,69,29,9.0,0,72,Semi-Urban,HR Executive,141496,1 +91884,Female,29,Masters,16,43,93,63,77,0.0,2,24,Semi-Urban,Software Engineer,50802,0 +91885,Female,59,Bachelors,11,91,21,3,14,8.0,0,99,Rural,Data Analyst,29940,0 +91886,Male,36,High School,13,84,17,12,56,0.0,4,0,Rural,Data Analyst,92067,0 +91887,Male,23,Masters,2,90,63,62,60,9.0,3,68,Urban,HR Executive,56209,1 +91888,Male,33,PhD,5,41,1,72,15,9.0,3,34,Rural,ML Engineer,130518,0 +91889,Male,54,High School,2,60,60,42,59,8.0,6,87,Urban,HR Executive,105976,1 +91890,Female,50,Diploma,1,65,86,2,8,3.0,6,76,Urban,ML Engineer,38658,0 +91891,Male,28,Bachelors,3,18,20,6,85,8.0,6,9,Urban,ML Engineer,129125,0 +91892,Male,24,High School,7,22,43,43,59,1.0,4,81,Urban,ML Engineer,90251,0 +91893,Male,32,Masters,3,24,74,66,85,1.0,1,17,Urban,ML Engineer,114475,0 +91894,Other,28,PhD,15,32,16,16,9,8.0,2,26,Urban,Software Engineer,70986,0 +91895,Male,56,Bachelors,5,26,83,29,77,3.0,0,55,Rural,Manager,109852,0 +91896,Male,45,Bachelors,0,38,32,44,22,1.0,0,36,Semi-Urban,Software Engineer,44250,0 +91897,Male,29,Bachelors,5,7,1,95,41,0.0,2,25,Rural,HR Executive,90471,0 +91898,Male,48,Masters,11,88,96,14,53,9.0,5,66,Semi-Urban,Manager,123809,1 +91899,Other,48,High School,4,20,6,81,10,0.0,5,12,Semi-Urban,Data Analyst,56726,0 +91900,Female,48,Bachelors,8,34,35,60,49,2.0,2,78,Semi-Urban,ML Engineer,51013,0 +91901,Male,35,Masters,16,50,9,51,0,4.0,7,22,Urban,Software Engineer,127092,0 +91902,Male,31,PhD,18,75,57,54,65,1.0,5,7,Urban,Data Analyst,48665,0 +91903,Male,55,Masters,13,33,77,19,55,4.0,4,55,Urban,Data Analyst,120767,0 +91904,Male,27,Masters,17,48,6,23,18,2.0,3,76,Urban,Manager,99980,0 +91905,Male,47,High School,2,19,59,67,57,5.0,4,49,Urban,Data Analyst,64224,0 +91906,Male,52,Masters,2,86,57,17,81,2.0,3,80,Rural,Software Engineer,62640,1 +91907,Male,47,Masters,4,83,74,25,76,4.0,0,13,Rural,Software Engineer,57820,0 +91908,Male,36,Masters,1,58,27,67,28,7.0,0,31,Rural,Software Engineer,25862,0 +91909,Male,30,Bachelors,17,31,85,40,0,8.0,6,3,Urban,HR Executive,33809,0 +91910,Male,35,Bachelors,7,94,27,49,98,4.0,4,41,Semi-Urban,Manager,86155,0 +91911,Male,21,Diploma,1,50,82,87,75,0.0,1,20,Urban,Software Engineer,142328,1 +91912,Female,33,PhD,5,10,10,18,4,5.0,5,76,Semi-Urban,Data Analyst,91105,0 +91913,Male,36,Diploma,5,2,28,33,96,1.0,7,53,Rural,Software Engineer,36658,0 +91914,Male,46,Diploma,9,43,51,70,21,1.0,3,2,Urban,Manager,63929,0 +91915,Male,48,Diploma,14,42,36,13,53,0.0,2,88,Urban,Software Engineer,55061,0 +91916,Female,27,High School,19,33,95,90,65,1.0,6,86,Urban,Data Analyst,56154,1 +91917,Female,38,Bachelors,3,67,86,94,13,2.0,1,43,Urban,Manager,59130,1 +91918,Male,38,Masters,18,97,61,95,85,7.0,4,45,Urban,ML Engineer,122009,1 +91919,Male,47,Diploma,19,74,60,51,37,7.0,5,84,Semi-Urban,Software Engineer,29533,1 +91920,Female,37,Bachelors,13,7,28,19,89,6.0,2,0,Urban,ML Engineer,144270,0 +91921,Male,39,Masters,13,13,97,58,75,9.0,3,5,Semi-Urban,Data Analyst,109441,0 +91922,Female,58,Bachelors,10,50,58,66,44,2.0,2,24,Urban,Manager,101564,0 +91923,Male,30,Masters,7,62,1,22,39,3.0,0,20,Semi-Urban,Software Engineer,95957,0 +91924,Male,49,Bachelors,1,91,18,23,19,0.0,2,80,Semi-Urban,Manager,108549,0 +91925,Female,30,Bachelors,0,63,40,6,46,8.0,2,97,Urban,Software Engineer,127000,0 +91926,Female,41,Masters,5,51,53,10,90,7.0,1,72,Urban,Data Analyst,135276,0 +91927,Male,51,Masters,16,80,90,60,8,3.0,3,69,Urban,ML Engineer,47301,1 +91928,Female,40,Masters,10,23,36,47,1,5.0,3,1,Urban,Data Analyst,135533,0 +91929,Male,38,Bachelors,1,24,73,83,49,6.0,5,66,Semi-Urban,HR Executive,94302,1 +91930,Male,30,Masters,11,27,61,40,56,5.0,0,87,Urban,Manager,94052,0 +91931,Female,57,Masters,16,29,65,60,47,6.0,1,93,Urban,Data Analyst,130356,1 +91932,Male,24,Bachelors,18,89,44,15,90,0.0,0,79,Rural,Software Engineer,66496,0 +91933,Female,56,High School,0,16,56,13,56,1.0,1,6,Semi-Urban,ML Engineer,80531,0 +91934,Other,57,Masters,16,4,61,28,80,7.0,3,35,Urban,Software Engineer,43707,0 +91935,Male,38,Masters,5,59,70,20,98,7.0,7,94,Urban,Data Analyst,115875,1 +91936,Other,42,High School,18,21,71,17,3,2.0,0,49,Semi-Urban,Software Engineer,83019,0 +91937,Male,35,High School,8,22,12,29,42,8.0,2,59,Semi-Urban,HR Executive,76430,0 +91938,Other,57,PhD,6,82,41,60,41,5.0,1,5,Urban,Data Analyst,64645,0 +91939,Male,57,Diploma,5,99,59,36,4,4.0,3,9,Urban,HR Executive,148752,0 +91940,Male,38,Bachelors,8,41,65,8,64,8.0,3,55,Urban,Manager,148002,0 +91941,Female,23,Masters,19,70,24,70,21,4.0,7,84,Semi-Urban,HR Executive,60348,1 +91942,Male,42,Masters,12,11,79,28,23,1.0,3,48,Urban,Manager,46520,0 +91943,Male,47,High School,16,28,37,61,99,3.0,1,35,Urban,HR Executive,65265,0 +91944,Male,37,Masters,2,37,70,20,94,8.0,4,25,Urban,Data Analyst,145473,0 +91945,Other,46,Diploma,13,98,60,72,90,8.0,3,29,Semi-Urban,ML Engineer,55297,1 +91946,Male,51,Masters,18,69,88,16,17,6.0,2,62,Urban,HR Executive,58160,1 +91947,Male,59,Diploma,6,32,66,80,83,6.0,0,0,Urban,HR Executive,83974,0 +91948,Female,29,Diploma,3,19,24,50,70,8.0,4,93,Urban,HR Executive,115678,0 +91949,Male,54,PhD,18,29,56,94,48,5.0,4,71,Semi-Urban,Software Engineer,59794,1 +91950,Male,47,Masters,6,21,6,37,8,0.0,5,48,Semi-Urban,ML Engineer,77885,0 +91951,Female,28,Diploma,17,48,80,56,18,5.0,0,87,Semi-Urban,Software Engineer,32538,1 +91952,Female,37,Masters,3,65,83,0,61,0.0,3,6,Rural,Manager,51931,0 +91953,Male,32,Bachelors,11,56,27,3,62,3.0,5,58,Semi-Urban,HR Executive,141303,0 +91954,Other,44,Diploma,0,90,32,11,37,8.0,6,6,Urban,Data Analyst,123355,0 +91955,Male,49,Bachelors,7,5,45,62,41,7.0,6,52,Semi-Urban,Data Analyst,132062,0 +91956,Other,57,Masters,2,93,60,88,22,9.0,7,60,Urban,Manager,128537,1 +91957,Male,33,Bachelors,0,76,16,40,84,7.0,7,42,Urban,Manager,135364,0 +91958,Male,25,Bachelors,5,45,64,92,16,1.0,2,72,Rural,HR Executive,37383,1 +91959,Female,38,High School,18,28,37,87,6,0.0,6,74,Urban,Data Analyst,53116,0 +91960,Female,59,Bachelors,18,89,90,44,90,7.0,7,19,Rural,Data Analyst,84956,1 +91961,Male,33,PhD,12,47,61,78,93,9.0,6,26,Urban,ML Engineer,24251,0 +91962,Male,36,Masters,13,34,57,92,91,0.0,4,87,Urban,Software Engineer,91453,1 +91963,Male,59,PhD,5,11,25,1,73,4.0,4,39,Urban,Software Engineer,122908,0 +91964,Other,49,Bachelors,10,95,86,23,83,4.0,4,42,Urban,Manager,85557,1 +91965,Male,34,Masters,15,34,74,64,16,9.0,0,63,Urban,Manager,127158,1 +91966,Male,42,High School,18,3,12,79,21,4.0,6,67,Urban,ML Engineer,36556,0 +91967,Male,40,Diploma,11,86,63,24,54,2.0,3,70,Urban,ML Engineer,148996,1 +91968,Male,49,Bachelors,6,69,31,61,78,5.0,1,80,Rural,Data Analyst,39459,1 +91969,Male,56,High School,14,56,32,81,38,3.0,3,65,Semi-Urban,HR Executive,136146,0 +91970,Female,52,Masters,19,38,21,12,59,6.0,5,73,Urban,Software Engineer,97674,0 +91971,Female,32,High School,18,81,6,63,10,6.0,3,80,Urban,Data Analyst,132744,0 +91972,Male,42,Bachelors,17,23,25,3,19,9.0,5,20,Urban,HR Executive,51929,0 +91973,Female,37,Bachelors,10,66,99,48,37,5.0,0,32,Urban,Software Engineer,122237,1 +91974,Male,48,Masters,11,97,71,87,79,6.0,4,82,Urban,HR Executive,128958,1 +91975,Female,34,Diploma,16,81,50,86,87,2.0,6,90,Rural,Data Analyst,135957,1 +91976,Male,53,Diploma,2,41,67,46,41,1.0,6,42,Urban,Software Engineer,30312,0 +91977,Other,45,Bachelors,16,14,84,39,50,9.0,2,42,Semi-Urban,ML Engineer,51061,0 +91978,Female,33,Masters,19,45,82,29,92,6.0,7,94,Urban,Software Engineer,97666,1 +91979,Male,42,Bachelors,11,9,17,50,33,8.0,2,39,Rural,Manager,113283,0 +91980,Male,23,Masters,9,21,99,56,57,3.0,6,56,Rural,Data Analyst,68692,0 +91981,Male,22,Diploma,0,21,11,50,55,0.0,2,5,Urban,HR Executive,72880,0 +91982,Male,48,Masters,15,53,69,58,13,3.0,7,96,Semi-Urban,Software Engineer,118562,1 +91983,Male,52,Diploma,6,49,93,73,3,4.0,7,37,Urban,HR Executive,24477,1 +91984,Male,26,PhD,19,84,65,98,18,7.0,5,6,Urban,HR Executive,72029,1 +91985,Female,52,PhD,13,9,42,39,25,3.0,5,55,Rural,ML Engineer,144964,0 +91986,Male,41,Bachelors,16,60,8,40,34,5.0,5,1,Urban,Software Engineer,134985,0 +91987,Male,27,Masters,7,27,4,43,81,4.0,4,57,Semi-Urban,Software Engineer,40699,0 +91988,Male,40,PhD,16,43,42,37,97,3.0,0,58,Rural,Data Analyst,108640,0 +91989,Male,36,High School,5,16,11,77,72,0.0,7,87,Urban,HR Executive,142651,0 +91990,Male,57,Diploma,8,15,36,46,41,3.0,2,48,Urban,Software Engineer,124997,0 +91991,Male,51,Bachelors,4,12,80,0,53,9.0,2,98,Rural,Manager,105609,0 +91992,Female,50,Bachelors,11,4,82,21,74,7.0,1,20,Urban,ML Engineer,96620,0 +91993,Male,31,Diploma,4,83,74,28,10,5.0,1,94,Rural,Software Engineer,82592,1 +91994,Female,21,Diploma,14,83,17,15,19,2.0,5,19,Semi-Urban,ML Engineer,73561,0 +91995,Male,47,Masters,2,76,21,96,66,1.0,3,65,Urban,Software Engineer,133308,1 +91996,Female,50,Masters,5,53,58,87,97,8.0,3,56,Urban,HR Executive,140071,1 +91997,Male,58,Bachelors,19,30,42,33,83,7.0,0,15,Urban,ML Engineer,73757,0 +91998,Female,42,Masters,8,76,10,97,53,6.0,6,76,Semi-Urban,HR Executive,75917,1 +91999,Female,21,High School,7,36,99,60,97,5.0,1,64,Rural,ML Engineer,145947,1 +92000,Male,43,High School,5,40,74,93,78,9.0,7,34,Rural,Manager,94836,1 +92001,Female,25,Bachelors,14,30,24,2,49,4.0,0,10,Urban,ML Engineer,121254,0 +92002,Male,53,Bachelors,8,41,22,58,44,8.0,6,50,Urban,Software Engineer,76392,0 +92003,Female,50,Masters,16,11,62,46,57,6.0,3,79,Urban,HR Executive,24065,0 +92004,Male,49,Bachelors,3,72,27,89,41,1.0,0,75,Urban,Software Engineer,80301,1 +92005,Male,31,High School,16,27,4,71,4,4.0,7,35,Semi-Urban,Data Analyst,122747,0 +92006,Female,40,Bachelors,8,55,60,5,42,3.0,4,7,Urban,ML Engineer,65996,0 +92007,Male,54,High School,14,86,65,68,44,7.0,5,10,Urban,Software Engineer,143395,0 +92008,Female,24,Bachelors,6,22,43,6,60,5.0,3,98,Semi-Urban,Software Engineer,114464,0 +92009,Female,37,Bachelors,14,35,96,21,78,7.0,5,8,Rural,ML Engineer,128100,0 +92010,Other,31,Diploma,5,70,49,82,62,3.0,7,60,Semi-Urban,Manager,47055,1 +92011,Other,28,Bachelors,12,40,32,54,24,8.0,3,58,Rural,Manager,104733,0 +92012,Male,42,Bachelors,11,26,55,56,40,7.0,6,61,Semi-Urban,Data Analyst,115944,0 +92013,Female,22,PhD,1,4,78,34,78,3.0,2,98,Semi-Urban,Software Engineer,131171,0 +92014,Male,58,High School,5,93,20,67,64,2.0,7,84,Semi-Urban,Manager,34600,1 +92015,Male,53,Bachelors,5,5,96,67,90,6.0,4,87,Semi-Urban,Manager,54664,1 +92016,Male,55,Bachelors,16,71,57,1,92,7.0,0,62,Rural,HR Executive,68769,0 +92017,Male,31,Bachelors,1,99,48,14,30,4.0,1,12,Urban,ML Engineer,130100,0 +92018,Male,47,Diploma,7,39,72,71,56,8.0,7,99,Urban,Software Engineer,94832,1 +92019,Male,50,Bachelors,0,63,30,5,18,3.0,4,52,Urban,Software Engineer,148379,0 +92020,Male,57,Masters,5,75,60,12,81,3.0,4,14,Urban,Data Analyst,110716,0 +92021,Female,56,Bachelors,11,43,97,42,34,6.0,7,61,Semi-Urban,HR Executive,143225,1 +92022,Male,32,Diploma,2,66,67,96,1,9.0,4,50,Rural,Data Analyst,26822,1 +92023,Female,55,High School,7,5,91,75,82,5.0,2,93,Urban,Manager,98819,1 +92024,Male,53,Diploma,8,97,78,4,53,9.0,7,85,Semi-Urban,Manager,91497,1 +92025,Male,54,Diploma,12,19,94,23,57,5.0,1,82,Urban,HR Executive,125503,0 +92026,Male,32,Bachelors,13,73,83,65,81,4.0,3,97,Semi-Urban,Data Analyst,49283,1 +92027,Female,31,Bachelors,3,98,47,39,71,0.0,3,4,Rural,HR Executive,114702,0 +92028,Female,48,Diploma,10,45,84,89,48,2.0,3,18,Semi-Urban,Data Analyst,133586,0 +92029,Male,36,Bachelors,6,38,63,86,90,9.0,4,18,Semi-Urban,Data Analyst,32669,0 +92030,Male,55,Bachelors,4,11,87,4,84,7.0,0,93,Semi-Urban,HR Executive,44372,0 +92031,Female,56,Masters,5,75,28,39,64,4.0,1,74,Rural,Software Engineer,88353,0 +92032,Male,58,Bachelors,14,29,61,55,62,5.0,5,6,Rural,ML Engineer,81481,0 +92033,Male,22,PhD,18,85,58,71,88,6.0,7,55,Urban,ML Engineer,77232,1 +92034,Female,23,Bachelors,15,88,17,58,44,6.0,3,80,Urban,HR Executive,24717,1 +92035,Male,42,Bachelors,9,1,79,74,9,3.0,3,51,Semi-Urban,Data Analyst,139683,0 +92036,Male,26,Bachelors,4,60,91,8,72,0.0,2,99,Urban,ML Engineer,22160,1 +92037,Female,37,Bachelors,15,97,99,64,59,4.0,4,60,Rural,Data Analyst,78547,1 +92038,Female,46,High School,19,96,21,98,36,2.0,1,49,Semi-Urban,Manager,106406,1 +92039,Male,46,Diploma,1,5,5,80,97,7.0,1,56,Urban,ML Engineer,147470,0 +92040,Male,46,Diploma,5,75,40,50,37,6.0,6,83,Urban,ML Engineer,146917,1 +92041,Female,48,Bachelors,1,84,62,49,54,7.0,0,40,Rural,Software Engineer,21891,0 +92042,Female,35,Masters,8,22,17,37,3,5.0,1,50,Rural,Manager,73778,0 +92043,Female,54,Diploma,4,60,65,64,28,5.0,1,8,Semi-Urban,Manager,48790,0 +92044,Female,59,Bachelors,3,17,51,80,81,6.0,5,32,Semi-Urban,HR Executive,120308,0 +92045,Female,24,High School,0,79,79,48,38,2.0,2,41,Rural,Data Analyst,37390,1 +92046,Female,43,Diploma,16,51,30,64,18,1.0,5,53,Rural,Manager,57457,0 +92047,Female,35,Diploma,6,37,78,23,27,0.0,5,62,Semi-Urban,ML Engineer,122212,0 +92048,Other,37,Diploma,16,51,9,45,93,0.0,0,80,Semi-Urban,ML Engineer,133910,0 +92049,Male,56,Diploma,8,16,44,25,57,7.0,4,54,Rural,Software Engineer,70315,0 +92050,Male,50,High School,13,53,61,41,22,8.0,7,11,Semi-Urban,ML Engineer,80744,0 +92051,Male,54,Bachelors,18,26,77,80,48,0.0,2,33,Urban,Data Analyst,103125,0 +92052,Female,53,Diploma,17,53,78,6,80,5.0,2,60,Urban,ML Engineer,67859,0 +92053,Male,46,High School,1,20,38,53,35,9.0,4,12,Urban,ML Engineer,144079,0 +92054,Female,47,Masters,12,26,17,40,82,8.0,2,58,Urban,Software Engineer,28110,0 +92055,Male,25,Diploma,2,66,51,71,6,7.0,6,27,Urban,HR Executive,27703,0 +92056,Female,31,Bachelors,13,8,13,32,80,2.0,4,7,Urban,HR Executive,35489,0 +92057,Male,23,High School,6,67,93,14,40,3.0,7,38,Semi-Urban,Data Analyst,32232,0 +92058,Female,22,Bachelors,12,15,86,65,63,0.0,7,61,Urban,Manager,58330,0 +92059,Male,33,Masters,13,94,78,96,54,0.0,5,35,Rural,ML Engineer,63704,1 +92060,Other,42,Masters,0,63,76,20,48,2.0,3,8,Rural,HR Executive,68697,0 +92061,Female,24,Bachelors,8,32,73,85,98,1.0,4,3,Rural,Manager,127791,0 +92062,Female,46,Diploma,19,64,48,67,76,1.0,7,27,Urban,Software Engineer,68303,0 +92063,Male,36,Bachelors,17,45,97,8,24,5.0,5,82,Semi-Urban,ML Engineer,28243,0 +92064,Female,30,Bachelors,13,53,54,99,9,7.0,6,44,Semi-Urban,HR Executive,97254,1 +92065,Male,32,High School,13,49,94,56,90,2.0,2,66,Urban,Manager,54873,1 +92066,Male,21,Bachelors,14,76,13,21,52,9.0,7,70,Urban,HR Executive,75132,0 +92067,Female,48,High School,4,84,60,68,25,7.0,4,76,Urban,Software Engineer,45712,1 +92068,Male,32,Diploma,2,28,73,76,57,1.0,2,91,Urban,Data Analyst,124078,1 +92069,Male,45,Masters,19,32,46,47,9,2.0,0,87,Urban,ML Engineer,80910,0 +92070,Male,50,Bachelors,8,47,77,54,60,1.0,7,30,Rural,HR Executive,56814,0 +92071,Female,56,High School,14,4,86,76,35,8.0,1,46,Urban,ML Engineer,40683,0 +92072,Male,39,Bachelors,1,98,42,42,94,2.0,4,3,Rural,HR Executive,123212,0 +92073,Male,47,Diploma,8,90,70,96,53,4.0,2,76,Semi-Urban,Data Analyst,107354,1 +92074,Male,47,Bachelors,9,84,56,52,80,0.0,3,99,Semi-Urban,HR Executive,104199,1 +92075,Male,47,Diploma,4,67,76,68,31,8.0,3,42,Urban,Manager,110636,1 +92076,Male,34,Bachelors,7,50,13,91,87,8.0,3,93,Urban,HR Executive,47250,1 +92077,Male,32,Masters,11,34,1,75,72,8.0,4,85,Urban,ML Engineer,74767,0 +92078,Male,53,Diploma,11,88,59,41,55,6.0,0,80,Urban,Data Analyst,132419,1 +92079,Male,21,Masters,18,55,20,90,83,2.0,6,1,Urban,Software Engineer,126418,0 +92080,Male,50,Diploma,15,31,96,29,87,9.0,2,77,Urban,Software Engineer,68644,0 +92081,Male,31,Bachelors,1,40,8,60,71,3.0,2,40,Semi-Urban,ML Engineer,79957,0 +92082,Male,29,Masters,9,69,67,3,73,0.0,3,81,Urban,ML Engineer,25688,0 +92083,Other,45,Bachelors,8,67,54,42,82,2.0,0,51,Rural,Data Analyst,54993,0 +92084,Female,36,Bachelors,0,14,92,46,77,9.0,7,33,Urban,HR Executive,129664,0 +92085,Male,28,Masters,0,33,20,84,44,4.0,5,24,Semi-Urban,Manager,81460,0 +92086,Male,56,Bachelors,6,78,80,9,74,1.0,3,56,Urban,HR Executive,100920,0 +92087,Male,47,Bachelors,11,51,66,63,15,1.0,0,48,Rural,Manager,107943,0 +92088,Male,22,Bachelors,11,11,49,87,24,5.0,0,9,Urban,Manager,91410,0 +92089,Female,57,PhD,17,97,51,7,47,2.0,5,68,Urban,Manager,148866,0 +92090,Male,36,Masters,14,35,67,46,29,5.0,1,4,Urban,Data Analyst,55563,0 +92091,Male,47,Bachelors,7,82,70,62,86,1.0,2,25,Semi-Urban,Manager,53061,1 +92092,Female,52,Bachelors,13,23,50,31,75,5.0,7,49,Rural,Software Engineer,126805,0 +92093,Female,51,Bachelors,17,22,16,43,71,8.0,6,67,Urban,Manager,148237,0 +92094,Female,46,Diploma,0,33,92,94,1,7.0,0,33,Urban,HR Executive,102510,1 +92095,Male,44,High School,1,45,42,85,76,2.0,6,26,Urban,Manager,119573,0 +92096,Female,30,Diploma,7,34,55,86,98,6.0,6,95,Semi-Urban,HR Executive,109655,1 +92097,Female,43,Diploma,12,13,4,2,99,7.0,5,50,Semi-Urban,Software Engineer,50099,0 +92098,Male,29,Diploma,11,85,14,63,99,8.0,0,12,Urban,Software Engineer,109459,0 +92099,Male,50,Bachelors,2,68,88,52,30,2.0,4,13,Urban,Manager,109332,0 +92100,Female,40,Bachelors,18,2,1,18,63,3.0,7,73,Urban,Software Engineer,126500,0 +92101,Male,59,Masters,7,58,29,63,31,5.0,7,63,Rural,ML Engineer,83200,0 +92102,Male,56,Masters,11,13,68,84,19,6.0,4,28,Semi-Urban,Data Analyst,76058,0 +92103,Male,23,Masters,3,86,47,98,91,1.0,4,7,Urban,HR Executive,65043,1 +92104,Male,56,Bachelors,8,46,0,55,5,3.0,0,7,Urban,Manager,50243,0 +92105,Male,25,Masters,5,29,54,71,15,5.0,2,80,Rural,Manager,119358,0 +92106,Male,42,Diploma,14,29,76,9,15,7.0,2,15,Rural,ML Engineer,100796,0 +92107,Female,40,Bachelors,9,39,80,5,63,9.0,6,75,Rural,Data Analyst,39441,0 +92108,Male,28,Masters,12,64,68,25,80,9.0,2,47,Rural,HR Executive,76333,0 +92109,Female,52,Masters,16,72,3,32,20,5.0,1,10,Semi-Urban,HR Executive,143858,0 +92110,Male,44,Bachelors,10,8,95,0,74,6.0,0,95,Urban,HR Executive,59891,0 +92111,Female,46,Diploma,0,47,45,26,56,0.0,5,60,Rural,Data Analyst,80698,0 +92112,Male,57,Bachelors,11,33,51,31,25,7.0,4,51,Urban,Manager,48694,0 +92113,Male,44,Diploma,15,95,19,68,67,8.0,7,80,Urban,ML Engineer,93784,1 +92114,Male,39,Bachelors,18,20,63,13,36,8.0,3,14,Semi-Urban,Software Engineer,64465,0 +92115,Male,46,Masters,0,73,67,21,16,4.0,5,82,Semi-Urban,HR Executive,83497,1 +92116,Male,40,Bachelors,10,41,35,13,70,9.0,0,48,Urban,ML Engineer,39565,0 +92117,Male,45,Bachelors,6,86,62,99,84,1.0,2,89,Rural,Manager,134761,1 +92118,Male,24,Diploma,9,46,99,32,66,9.0,6,92,Urban,Manager,106072,1 +92119,Male,49,Bachelors,19,26,32,92,26,8.0,7,89,Urban,ML Engineer,119493,1 +92120,Male,21,PhD,15,41,5,67,61,3.0,0,57,Urban,ML Engineer,81628,0 +92121,Female,48,High School,3,15,68,83,71,6.0,6,34,Rural,ML Engineer,85361,0 +92122,Male,35,Masters,6,65,58,9,52,5.0,3,42,Urban,HR Executive,31854,0 +92123,Female,52,Bachelors,14,44,93,89,91,5.0,6,79,Urban,ML Engineer,60850,1 +92124,Female,21,Diploma,4,10,76,16,93,7.0,6,92,Semi-Urban,Manager,64620,0 +92125,Male,49,Diploma,12,43,45,56,42,2.0,1,14,Urban,Software Engineer,57749,0 +92126,Male,54,Bachelors,2,9,99,12,31,8.0,1,70,Urban,Manager,37941,0 +92127,Female,25,High School,13,29,82,41,1,5.0,6,75,Urban,Software Engineer,135156,0 +92128,Male,34,Bachelors,0,14,18,42,68,6.0,0,21,Urban,ML Engineer,22372,0 +92129,Male,58,Diploma,11,68,24,99,67,1.0,1,96,Urban,Data Analyst,96794,1 +92130,Male,41,Bachelors,17,17,19,25,27,5.0,5,42,Urban,Software Engineer,115476,0 +92131,Male,40,Diploma,0,37,75,85,73,6.0,1,96,Semi-Urban,Manager,113663,1 +92132,Female,50,PhD,1,2,54,61,88,9.0,7,29,Urban,HR Executive,24707,0 +92133,Male,47,Masters,15,12,4,69,31,8.0,4,52,Rural,Data Analyst,123487,0 +92134,Female,49,Bachelors,9,7,83,92,13,8.0,2,85,Rural,Data Analyst,41687,1 +92135,Female,39,Bachelors,18,88,35,1,62,4.0,7,76,Urban,Manager,67744,0 +92136,Female,39,Masters,4,78,35,79,29,1.0,5,86,Semi-Urban,Manager,73186,1 +92137,Female,53,Masters,19,91,40,56,39,0.0,7,2,Urban,Software Engineer,48873,0 +92138,Male,24,Masters,1,35,9,74,28,0.0,2,75,Urban,ML Engineer,90065,0 +92139,Male,33,Bachelors,15,36,20,94,99,6.0,3,5,Rural,HR Executive,144213,0 +92140,Female,47,High School,8,92,27,29,61,5.0,7,24,Urban,Software Engineer,39508,0 +92141,Other,45,Diploma,2,74,92,14,82,4.0,5,29,Urban,ML Engineer,51809,0 +92142,Male,52,High School,3,34,52,91,89,7.0,2,67,Urban,Software Engineer,125202,1 +92143,Female,55,Masters,14,41,85,49,40,9.0,4,51,Urban,HR Executive,135279,0 +92144,Male,42,High School,8,46,16,6,91,3.0,7,48,Urban,Data Analyst,126199,0 +92145,Male,55,Bachelors,4,84,3,52,61,9.0,4,75,Urban,Data Analyst,57632,0 +92146,Female,41,Bachelors,1,7,72,57,36,9.0,5,96,Semi-Urban,Data Analyst,110538,0 +92147,Male,47,Masters,3,28,20,85,57,0.0,4,49,Rural,Data Analyst,20781,0 +92148,Female,50,Bachelors,0,77,98,60,12,1.0,6,94,Semi-Urban,ML Engineer,48076,1 +92149,Male,52,Masters,14,39,88,26,87,3.0,7,90,Urban,Data Analyst,39639,1 +92150,Female,46,High School,2,92,71,58,48,6.0,4,33,Rural,HR Executive,84489,1 +92151,Male,50,Diploma,9,3,48,8,79,2.0,1,1,Urban,Software Engineer,119019,0 +92152,Female,34,Diploma,17,91,1,16,62,2.0,0,62,Urban,ML Engineer,140223,0 +92153,Male,57,Diploma,16,89,66,41,77,2.0,2,54,Urban,Software Engineer,141650,1 +92154,Male,55,Bachelors,9,0,37,94,63,8.0,7,70,Urban,Manager,140096,0 +92155,Female,56,High School,16,70,52,24,47,5.0,6,10,Semi-Urban,Data Analyst,49780,0 +92156,Male,48,PhD,8,93,3,45,26,9.0,1,90,Rural,HR Executive,63003,0 +92157,Other,33,Diploma,13,20,56,74,90,9.0,1,85,Urban,HR Executive,144884,0 +92158,Male,55,PhD,9,24,54,33,61,5.0,7,99,Semi-Urban,HR Executive,120047,0 +92159,Female,58,Bachelors,8,53,17,86,69,4.0,0,59,Urban,ML Engineer,83674,0 +92160,Female,32,Bachelors,7,63,76,69,63,0.0,0,57,Semi-Urban,Manager,103542,1 +92161,Male,27,Bachelors,13,69,76,68,94,1.0,7,36,Urban,Manager,108551,1 +92162,Female,35,Bachelors,2,31,16,69,95,9.0,2,96,Urban,Data Analyst,132854,0 +92163,Male,54,High School,5,35,32,64,38,1.0,0,96,Urban,Manager,35968,0 +92164,Male,32,Diploma,1,91,92,62,71,3.0,2,62,Urban,Data Analyst,106393,1 +92165,Male,26,High School,4,99,16,15,26,5.0,0,35,Urban,Data Analyst,40499,0 +92166,Male,48,Bachelors,9,42,34,59,43,9.0,3,41,Semi-Urban,ML Engineer,33702,0 +92167,Female,24,Diploma,17,99,37,12,4,6.0,1,6,Urban,HR Executive,147559,0 +92168,Male,39,Masters,3,78,72,56,5,8.0,3,10,Semi-Urban,HR Executive,62499,0 +92169,Male,56,High School,10,52,26,82,81,6.0,5,42,Semi-Urban,HR Executive,76769,0 +92170,Female,24,Bachelors,4,24,21,28,52,4.0,5,82,Semi-Urban,HR Executive,50881,0 +92171,Other,31,Diploma,2,3,86,54,6,9.0,7,96,Urban,Manager,39576,0 +92172,Female,52,PhD,4,20,2,10,95,4.0,0,48,Semi-Urban,Software Engineer,36325,0 +92173,Male,33,Bachelors,3,65,77,39,73,3.0,1,63,Rural,ML Engineer,29251,1 +92174,Male,42,Masters,1,24,44,35,81,3.0,6,71,Rural,ML Engineer,141128,0 +92175,Male,40,Bachelors,3,33,44,50,39,0.0,6,56,Urban,Data Analyst,135995,0 +92176,Female,28,Diploma,7,96,23,41,49,4.0,0,59,Urban,HR Executive,125013,0 +92177,Male,50,Bachelors,10,21,27,46,4,9.0,7,5,Semi-Urban,Data Analyst,137457,0 +92178,Male,47,Bachelors,9,2,45,54,80,8.0,6,34,Urban,Software Engineer,62889,0 +92179,Male,50,Masters,9,44,0,59,94,1.0,1,71,Urban,Software Engineer,96549,0 +92180,Male,24,Bachelors,12,65,59,3,47,0.0,6,10,Urban,ML Engineer,45116,0 +92181,Male,36,PhD,12,14,75,89,42,9.0,2,23,Urban,Data Analyst,113703,0 +92182,Male,49,Diploma,13,30,72,10,40,7.0,7,87,Semi-Urban,ML Engineer,144667,0 +92183,Female,58,Masters,5,73,14,54,92,1.0,1,33,Urban,ML Engineer,37818,0 +92184,Female,50,Diploma,6,22,10,76,44,5.0,7,0,Urban,Manager,37519,0 +92185,Female,41,Bachelors,10,44,8,92,81,9.0,4,26,Urban,HR Executive,56721,0 +92186,Female,33,Bachelors,19,84,38,2,60,0.0,5,63,Semi-Urban,Manager,111182,0 +92187,Male,21,High School,4,44,60,70,76,0.0,0,49,Urban,HR Executive,63256,0 +92188,Female,26,Bachelors,4,6,44,97,76,8.0,6,30,Urban,Software Engineer,38338,0 +92189,Male,59,High School,18,69,25,41,60,0.0,3,32,Urban,Manager,50697,0 +92190,Male,51,Bachelors,16,93,40,92,28,8.0,2,23,Urban,ML Engineer,131828,1 +92191,Female,33,Bachelors,11,72,45,11,38,5.0,1,98,Rural,Data Analyst,49834,0 +92192,Male,26,Masters,6,15,23,62,37,6.0,1,53,Urban,Software Engineer,137266,0 +92193,Male,41,Diploma,4,22,92,35,55,8.0,3,20,Urban,HR Executive,36164,0 +92194,Male,31,Bachelors,11,96,90,80,99,6.0,1,18,Semi-Urban,Manager,82650,1 +92195,Male,21,Masters,9,66,37,92,90,6.0,0,52,Urban,Software Engineer,91519,1 +92196,Male,38,Masters,19,30,44,51,51,4.0,6,50,Urban,ML Engineer,90585,0 +92197,Female,38,Masters,1,95,17,11,96,7.0,2,48,Rural,Data Analyst,117816,0 +92198,Female,48,Bachelors,12,36,58,79,99,5.0,5,70,Rural,HR Executive,27294,1 +92199,Female,24,Masters,7,37,98,73,89,3.0,2,46,Urban,ML Engineer,106197,1 +92200,Female,31,PhD,19,36,56,49,48,9.0,1,5,Rural,Manager,73448,0 +92201,Female,28,Masters,1,48,10,97,90,5.0,1,8,Rural,Software Engineer,80173,0 +92202,Male,42,Masters,2,7,25,37,53,8.0,3,36,Semi-Urban,HR Executive,35073,0 +92203,Female,56,Diploma,9,10,57,15,11,0.0,5,93,Semi-Urban,Software Engineer,126821,0 +92204,Male,59,High School,19,44,72,86,75,1.0,1,94,Urban,Data Analyst,64855,1 +92205,Male,42,Diploma,14,91,68,59,78,8.0,1,55,Urban,Manager,105341,1 +92206,Female,29,Bachelors,1,58,2,38,77,4.0,1,65,Urban,Data Analyst,81889,0 +92207,Female,46,Bachelors,3,5,20,22,87,9.0,1,3,Urban,Software Engineer,53073,0 +92208,Male,57,Diploma,1,38,42,82,69,7.0,6,57,Rural,Software Engineer,71794,0 +92209,Male,54,High School,19,80,46,8,25,5.0,2,79,Rural,Software Engineer,135068,0 +92210,Female,56,Bachelors,17,33,0,23,59,0.0,4,37,Urban,Software Engineer,86906,0 +92211,Male,41,Bachelors,5,67,80,14,35,8.0,5,99,Rural,ML Engineer,101863,1 +92212,Female,37,Bachelors,6,90,57,82,55,6.0,4,29,Semi-Urban,Manager,25632,1 +92213,Male,35,Bachelors,0,97,54,69,26,5.0,3,82,Semi-Urban,Software Engineer,120651,1 +92214,Female,44,Bachelors,11,86,24,82,49,0.0,1,87,Semi-Urban,Data Analyst,37466,1 +92215,Male,56,Masters,11,63,65,58,74,7.0,6,89,Semi-Urban,Manager,140173,1 +92216,Female,44,High School,13,26,46,32,67,2.0,2,44,Semi-Urban,Data Analyst,35699,0 +92217,Male,46,Masters,3,46,43,65,4,1.0,0,78,Rural,HR Executive,75461,0 +92218,Male,30,High School,3,0,23,21,45,1.0,6,79,Rural,Data Analyst,29543,0 +92219,Female,51,Bachelors,7,84,2,8,50,0.0,3,5,Rural,HR Executive,62172,0 +92220,Male,21,High School,14,93,47,41,10,5.0,7,40,Semi-Urban,HR Executive,130892,0 +92221,Male,58,Masters,9,72,8,89,90,2.0,1,24,Rural,Manager,61898,0 +92222,Male,43,Bachelors,13,76,93,78,60,9.0,2,51,Urban,HR Executive,34065,1 +92223,Male,41,High School,4,20,27,20,29,3.0,4,31,Semi-Urban,Data Analyst,141639,0 +92224,Male,59,Masters,12,92,85,7,72,4.0,7,17,Semi-Urban,Manager,147752,0 +92225,Female,32,Diploma,7,3,88,37,1,9.0,6,24,Urban,HR Executive,138529,0 +92226,Male,38,PhD,12,87,27,98,36,0.0,5,39,Semi-Urban,Data Analyst,41236,1 +92227,Male,42,Diploma,8,41,30,86,81,4.0,4,30,Urban,Software Engineer,41261,0 +92228,Male,26,Bachelors,1,88,74,31,80,8.0,4,31,Urban,Software Engineer,134460,0 +92229,Female,54,High School,19,96,58,66,84,6.0,4,0,Urban,ML Engineer,26297,0 +92230,Male,47,Diploma,11,88,57,78,74,3.0,5,71,Urban,Data Analyst,73354,1 +92231,Female,30,Bachelors,4,84,24,3,94,9.0,0,57,Urban,Manager,144697,0 +92232,Male,35,Diploma,16,44,85,81,96,4.0,4,22,Rural,HR Executive,123942,0 +92233,Female,59,Masters,5,77,36,67,42,8.0,7,40,Rural,ML Engineer,82891,0 +92234,Female,35,Masters,18,21,89,15,66,0.0,3,43,Semi-Urban,Manager,80372,0 +92235,Male,21,High School,17,66,75,35,88,7.0,4,38,Rural,Manager,103769,0 +92236,Male,37,Bachelors,14,37,27,36,29,6.0,4,17,Urban,HR Executive,24424,0 +92237,Male,48,Bachelors,12,48,22,33,64,9.0,5,16,Urban,ML Engineer,78394,0 +92238,Female,30,Masters,2,65,82,2,82,1.0,3,31,Urban,Software Engineer,66609,0 +92239,Male,28,High School,17,99,26,27,36,1.0,0,17,Semi-Urban,Data Analyst,149487,0 +92240,Male,23,Bachelors,7,89,73,65,27,3.0,5,38,Semi-Urban,Data Analyst,89019,1 +92241,Male,47,Masters,17,25,89,9,88,1.0,6,89,Rural,Manager,121400,0 +92242,Other,45,Diploma,3,89,53,8,78,2.0,1,58,Semi-Urban,Manager,122576,0 +92243,Female,32,Diploma,14,10,57,88,84,5.0,2,40,Rural,ML Engineer,81194,0 +92244,Male,41,High School,3,45,20,92,65,7.0,4,32,Urban,Manager,98939,0 +92245,Male,23,Bachelors,18,54,85,75,47,8.0,4,34,Urban,Manager,21785,1 +92246,Male,24,Bachelors,16,24,84,80,48,7.0,2,45,Urban,ML Engineer,28514,0 +92247,Male,38,Bachelors,4,29,11,49,5,7.0,6,63,Rural,HR Executive,54397,0 +92248,Male,50,Masters,0,57,55,78,99,5.0,4,82,Urban,HR Executive,81050,1 +92249,Male,52,Bachelors,8,70,27,20,37,1.0,1,87,Urban,HR Executive,23172,0 +92250,Male,24,Masters,18,82,62,16,27,5.0,6,71,Urban,ML Engineer,49859,0 +92251,Male,50,Diploma,16,2,93,77,9,3.0,3,75,Urban,ML Engineer,55740,1 +92252,Male,42,Bachelors,16,65,8,80,82,2.0,4,17,Urban,Software Engineer,71147,0 +92253,Male,32,Bachelors,15,74,69,19,27,5.0,0,55,Urban,Software Engineer,78593,0 +92254,Male,59,Diploma,3,1,6,75,84,1.0,2,91,Semi-Urban,ML Engineer,81818,0 +92255,Female,36,High School,13,76,49,15,82,4.0,2,58,Urban,Software Engineer,116401,0 +92256,Male,48,Bachelors,14,95,46,52,42,8.0,1,96,Rural,Manager,85968,1 +92257,Male,23,Bachelors,14,50,66,44,86,1.0,5,28,Urban,Manager,29978,0 +92258,Male,45,Diploma,1,46,71,17,30,9.0,2,16,Rural,HR Executive,26782,0 +92259,Male,24,High School,18,50,99,37,2,5.0,5,41,Rural,ML Engineer,86751,0 +92260,Male,52,Bachelors,18,49,58,94,74,3.0,5,76,Urban,ML Engineer,24977,1 +92261,Female,53,High School,15,51,16,47,74,5.0,5,22,Urban,ML Engineer,76731,0 +92262,Male,41,Diploma,6,69,33,18,4,7.0,3,30,Urban,HR Executive,92675,0 +92263,Male,31,High School,1,81,27,44,85,6.0,2,43,Semi-Urban,Software Engineer,47846,0 +92264,Male,35,Diploma,6,36,49,18,80,4.0,7,17,Rural,Software Engineer,84730,0 +92265,Female,33,High School,12,96,39,72,94,1.0,4,55,Urban,Data Analyst,45527,1 +92266,Male,24,Masters,4,38,23,91,22,7.0,6,23,Urban,ML Engineer,121240,0 +92267,Male,38,High School,10,93,66,84,19,8.0,3,12,Urban,Manager,86794,1 +92268,Female,34,Masters,16,82,73,73,8,3.0,1,39,Semi-Urban,HR Executive,100062,1 +92269,Female,53,High School,18,73,11,13,56,5.0,6,25,Urban,Manager,102994,0 +92270,Male,46,Masters,17,70,76,37,3,2.0,1,84,Urban,Manager,61536,1 +92271,Male,24,Bachelors,1,14,89,28,2,4.0,5,56,Semi-Urban,Data Analyst,106126,0 +92272,Male,28,Bachelors,11,68,64,18,95,3.0,7,18,Urban,ML Engineer,111953,0 +92273,Female,27,Masters,11,5,13,8,20,6.0,7,35,Urban,Software Engineer,66336,0 +92274,Female,43,High School,8,94,84,53,78,1.0,1,44,Urban,Data Analyst,59995,1 +92275,Female,50,Masters,14,74,58,65,44,2.0,1,60,Semi-Urban,ML Engineer,104117,1 +92276,Female,58,Masters,19,80,94,99,44,3.0,1,78,Urban,ML Engineer,51475,1 +92277,Male,33,Bachelors,10,46,31,58,55,6.0,7,7,Semi-Urban,ML Engineer,27013,0 +92278,Male,47,Bachelors,19,10,97,42,56,6.0,6,5,Urban,Manager,26289,0 +92279,Male,57,High School,15,53,63,87,6,3.0,7,25,Urban,ML Engineer,91258,0 +92280,Female,45,Bachelors,0,48,11,83,48,1.0,7,56,Semi-Urban,Manager,27279,0 +92281,Male,37,Bachelors,8,24,57,22,28,5.0,7,95,Urban,HR Executive,73673,0 +92282,Male,31,Bachelors,8,82,92,72,31,3.0,5,42,Urban,ML Engineer,31539,1 +92283,Female,41,Diploma,19,14,65,70,10,8.0,7,78,Urban,Manager,113878,0 +92284,Female,29,Bachelors,8,37,89,52,91,9.0,3,7,Urban,Manager,80469,0 +92285,Female,21,Bachelors,8,92,73,13,34,6.0,2,8,Semi-Urban,Manager,125218,0 +92286,Male,49,Bachelors,12,84,80,73,31,9.0,3,29,Urban,HR Executive,65290,1 +92287,Male,55,Bachelors,4,64,34,11,64,9.0,6,32,Urban,ML Engineer,43702,0 +92288,Male,29,Bachelors,7,91,26,84,34,0.0,2,17,Urban,HR Executive,103123,0 +92289,Female,56,Masters,15,4,13,43,54,1.0,2,58,Urban,HR Executive,137653,0 +92290,Male,38,Masters,17,48,37,53,89,7.0,2,0,Rural,Manager,53379,0 +92291,Male,57,Bachelors,16,32,66,53,68,3.0,6,28,Semi-Urban,ML Engineer,73864,0 +92292,Male,46,Bachelors,8,24,35,86,19,0.0,5,48,Urban,Manager,76374,0 +92293,Female,46,Bachelors,11,78,8,96,70,0.0,2,60,Rural,Manager,72654,1 +92294,Female,38,PhD,12,36,18,94,77,0.0,2,35,Urban,Manager,25428,0 +92295,Male,55,Diploma,10,73,98,86,49,2.0,7,76,Urban,HR Executive,95737,1 +92296,Male,23,High School,2,6,99,72,49,7.0,7,21,Rural,Software Engineer,68870,0 +92297,Male,50,Diploma,1,12,43,47,35,2.0,0,19,Rural,Manager,75406,0 +92298,Male,37,Masters,12,60,38,33,76,1.0,1,7,Urban,Data Analyst,90900,0 +92299,Male,52,Bachelors,19,31,19,68,64,2.0,6,90,Urban,ML Engineer,60218,0 +92300,Male,32,Diploma,7,63,88,60,89,2.0,2,15,Semi-Urban,Manager,84430,0 +92301,Male,36,PhD,15,48,24,19,40,2.0,4,0,Rural,HR Executive,130967,0 +92302,Male,42,Masters,9,56,23,63,27,8.0,3,57,Rural,HR Executive,142560,0 +92303,Female,23,Bachelors,12,34,64,53,45,2.0,2,53,Urban,Manager,116706,0 +92304,Male,48,Diploma,7,63,29,48,17,7.0,3,91,Rural,Data Analyst,71069,0 +92305,Female,23,Bachelors,2,2,77,74,79,1.0,3,6,Rural,HR Executive,117842,0 +92306,Male,51,Masters,9,79,72,46,52,6.0,3,84,Urban,Manager,40996,1 +92307,Male,40,Diploma,5,24,42,37,74,5.0,3,99,Urban,Manager,28177,0 +92308,Female,38,Bachelors,6,39,98,24,45,1.0,5,75,Urban,Software Engineer,79820,0 +92309,Female,26,High School,19,17,24,54,84,4.0,4,89,Semi-Urban,ML Engineer,140349,0 +92310,Female,31,Diploma,12,91,37,96,54,3.0,1,25,Urban,Software Engineer,75819,1 +92311,Male,50,High School,4,97,76,28,48,2.0,6,26,Urban,Software Engineer,22547,0 +92312,Female,54,Bachelors,3,79,77,11,62,7.0,0,19,Semi-Urban,Manager,33060,0 +92313,Male,50,Diploma,4,9,55,14,35,9.0,4,53,Urban,Data Analyst,79512,0 +92314,Male,56,Bachelors,9,86,78,55,22,9.0,4,81,Semi-Urban,ML Engineer,137017,1 +92315,Male,48,Masters,4,83,48,35,86,9.0,4,17,Urban,Data Analyst,57325,0 +92316,Male,58,High School,4,9,72,5,52,5.0,6,77,Urban,Software Engineer,103764,0 +92317,Female,27,Diploma,13,24,86,2,40,5.0,7,57,Urban,HR Executive,98434,0 +92318,Female,56,Bachelors,2,88,65,3,70,0.0,4,64,Semi-Urban,Software Engineer,148492,0 +92319,Male,53,Bachelors,3,46,78,41,30,4.0,1,93,Urban,Data Analyst,88160,1 +92320,Male,56,High School,18,75,99,49,37,7.0,3,52,Urban,Data Analyst,73778,1 +92321,Male,36,Bachelors,13,84,17,97,5,1.0,3,33,Urban,Software Engineer,138618,0 +92322,Male,24,Bachelors,8,60,44,84,71,6.0,6,76,Urban,Manager,61042,1 +92323,Male,51,Bachelors,9,67,74,96,91,7.0,3,69,Semi-Urban,ML Engineer,96052,1 +92324,Female,44,Diploma,0,0,93,12,97,4.0,1,47,Urban,ML Engineer,36831,0 +92325,Male,49,Bachelors,7,51,57,22,58,5.0,3,26,Urban,HR Executive,70393,0 +92326,Male,45,Diploma,11,14,41,16,38,4.0,4,49,Urban,ML Engineer,30797,0 +92327,Male,38,Bachelors,18,5,73,99,71,6.0,4,0,Rural,Software Engineer,144350,0 +92328,Female,53,Diploma,15,26,15,97,13,0.0,6,51,Urban,Data Analyst,79551,0 +92329,Male,50,Bachelors,0,54,28,17,34,7.0,1,39,Urban,Manager,73605,0 +92330,Male,27,Bachelors,19,45,68,87,35,1.0,7,0,Semi-Urban,Manager,86292,0 +92331,Male,38,Diploma,6,14,92,29,65,4.0,5,54,Rural,HR Executive,51148,0 +92332,Male,48,Bachelors,7,24,12,63,36,7.0,4,65,Urban,Data Analyst,22584,0 +92333,Male,28,Diploma,7,27,49,55,7,3.0,5,18,Urban,Data Analyst,142967,0 +92334,Other,41,Bachelors,3,23,57,85,35,5.0,3,77,Rural,Software Engineer,52017,1 +92335,Male,30,Bachelors,14,37,10,35,57,3.0,0,37,Rural,Software Engineer,144774,0 +92336,Female,46,High School,19,60,37,61,50,1.0,7,18,Urban,Manager,30761,0 +92337,Male,48,Masters,1,16,46,49,37,1.0,1,59,Urban,Manager,98134,0 +92338,Male,31,Diploma,12,67,38,20,2,6.0,6,89,Urban,HR Executive,99610,0 +92339,Female,41,PhD,12,24,86,40,46,6.0,3,38,Semi-Urban,Manager,122645,0 +92340,Female,26,Bachelors,10,15,87,52,97,4.0,2,64,Semi-Urban,Software Engineer,39573,0 +92341,Male,28,Diploma,3,60,25,8,49,4.0,6,90,Semi-Urban,HR Executive,40350,0 +92342,Male,54,Bachelors,8,94,61,2,30,6.0,6,93,Urban,HR Executive,47374,1 +92343,Male,38,Bachelors,16,36,15,87,17,2.0,5,84,Rural,Manager,95086,0 +92344,Male,34,Masters,9,57,57,62,43,5.0,2,66,Urban,Manager,40748,1 +92345,Male,23,Masters,19,14,6,58,91,4.0,3,72,Urban,Software Engineer,108312,0 +92346,Male,56,Masters,12,14,71,1,70,0.0,5,80,Urban,Software Engineer,107657,0 +92347,Male,50,Diploma,12,74,58,19,28,9.0,4,16,Urban,HR Executive,89308,0 +92348,Male,40,Diploma,4,13,22,52,42,9.0,7,2,Urban,ML Engineer,48296,0 +92349,Female,36,Bachelors,2,46,87,46,41,7.0,6,19,Rural,Manager,135591,0 +92350,Male,21,PhD,6,21,81,37,20,2.0,3,67,Urban,HR Executive,35446,0 +92351,Female,47,Masters,13,66,65,86,91,1.0,2,25,Urban,Manager,43634,1 +92352,Female,26,High School,8,8,28,87,27,3.0,0,61,Urban,Software Engineer,37547,0 +92353,Male,31,Bachelors,13,53,57,14,53,2.0,0,31,Semi-Urban,Manager,101077,0 +92354,Male,38,Diploma,8,29,76,48,40,0.0,7,61,Urban,Software Engineer,78939,0 +92355,Male,59,Bachelors,4,35,3,3,36,0.0,3,23,Urban,HR Executive,141771,0 +92356,Male,45,Bachelors,16,35,40,53,15,9.0,6,40,Urban,HR Executive,113783,0 +92357,Male,41,Masters,8,90,74,73,18,8.0,0,76,Urban,ML Engineer,37426,1 +92358,Male,56,High School,6,19,45,5,3,5.0,2,97,Urban,ML Engineer,67959,0 +92359,Male,55,High School,13,98,64,41,2,3.0,5,49,Urban,Manager,129153,1 +92360,Female,47,High School,4,38,72,88,6,9.0,6,60,Rural,ML Engineer,60097,1 +92361,Other,46,Bachelors,5,23,26,31,86,1.0,2,73,Urban,ML Engineer,111349,0 +92362,Female,33,Masters,7,29,85,2,39,1.0,3,31,Urban,HR Executive,72854,0 +92363,Female,58,Bachelors,14,23,85,67,30,4.0,2,86,Urban,Manager,31781,1 +92364,Female,49,Diploma,5,98,9,22,35,4.0,5,48,Rural,HR Executive,70643,0 +92365,Male,30,High School,3,76,17,81,74,6.0,5,35,Urban,ML Engineer,82337,0 +92366,Female,39,Diploma,4,32,68,6,59,3.0,1,80,Urban,Software Engineer,33304,0 +92367,Male,53,High School,18,69,77,6,36,5.0,4,56,Urban,HR Executive,24088,0 +92368,Female,35,Masters,1,55,44,74,67,5.0,5,14,Rural,Data Analyst,64996,0 +92369,Male,43,Diploma,17,33,64,66,57,3.0,5,59,Urban,HR Executive,88774,0 +92370,Female,53,Diploma,8,89,21,48,76,0.0,2,20,Urban,Software Engineer,32019,0 +92371,Other,21,Bachelors,4,61,94,33,44,9.0,1,29,Urban,Manager,24977,0 +92372,Female,54,Bachelors,14,80,88,72,30,1.0,6,54,Semi-Urban,Data Analyst,70314,1 +92373,Female,55,Masters,4,75,51,65,98,7.0,1,4,Urban,Software Engineer,126770,0 +92374,Male,34,High School,14,9,87,79,58,7.0,3,75,Semi-Urban,ML Engineer,98768,1 +92375,Female,45,Diploma,14,81,87,25,65,4.0,2,71,Urban,Manager,75889,1 +92376,Male,35,Bachelors,6,36,28,81,38,2.0,4,22,Urban,Data Analyst,132279,0 +92377,Male,41,Diploma,18,11,38,49,55,9.0,7,57,Urban,ML Engineer,32713,0 +92378,Male,41,High School,15,22,29,33,90,6.0,3,86,Rural,ML Engineer,22560,0 +92379,Male,22,Diploma,3,7,4,83,89,6.0,7,25,Rural,Software Engineer,57225,0 +92380,Female,23,Masters,4,36,92,9,44,2.0,3,98,Rural,HR Executive,26764,0 +92381,Male,22,High School,11,50,22,30,85,9.0,3,36,Urban,HR Executive,28052,0 +92382,Male,55,Bachelors,10,93,20,24,28,5.0,1,28,Urban,Software Engineer,146654,0 +92383,Female,59,Bachelors,10,33,15,30,0,5.0,5,27,Urban,Software Engineer,82683,0 +92384,Female,41,High School,1,26,67,7,56,2.0,2,53,Semi-Urban,HR Executive,23891,0 +92385,Male,32,Bachelors,13,53,89,23,60,8.0,7,25,Urban,ML Engineer,73487,0 +92386,Male,56,Masters,4,33,62,76,6,6.0,4,22,Urban,Data Analyst,117971,0 +92387,Male,23,Bachelors,7,84,46,75,7,1.0,1,47,Semi-Urban,ML Engineer,51578,1 +92388,Female,40,Masters,4,8,98,52,0,0.0,2,2,Urban,ML Engineer,63474,0 +92389,Female,50,High School,13,50,69,18,65,1.0,0,65,Rural,Data Analyst,101541,0 +92390,Female,56,PhD,0,37,60,27,33,7.0,0,57,Urban,Software Engineer,49674,0 +92391,Male,30,Bachelors,10,56,51,44,90,4.0,2,5,Urban,ML Engineer,119420,0 +92392,Male,49,High School,7,87,87,18,3,6.0,7,17,Urban,HR Executive,26346,0 +92393,Female,21,Bachelors,2,26,1,49,56,1.0,0,30,Semi-Urban,HR Executive,96460,0 +92394,Female,28,High School,13,66,21,56,73,7.0,1,82,Urban,Data Analyst,33234,0 +92395,Male,51,Bachelors,12,63,56,23,22,9.0,1,6,Urban,Software Engineer,63497,0 +92396,Female,37,Diploma,4,8,13,86,89,9.0,6,8,Urban,Manager,66939,0 +92397,Female,56,Bachelors,19,46,38,82,7,7.0,7,98,Urban,HR Executive,41393,1 +92398,Male,31,PhD,9,57,66,61,9,1.0,4,56,Semi-Urban,HR Executive,107350,1 +92399,Female,47,Bachelors,15,7,63,67,32,0.0,3,93,Urban,HR Executive,125272,0 +92400,Female,55,Bachelors,1,76,33,79,8,2.0,2,28,Urban,Manager,21730,0 +92401,Female,40,Masters,10,22,20,29,84,9.0,3,48,Urban,ML Engineer,141108,0 +92402,Male,23,Diploma,1,89,69,54,51,1.0,2,62,Rural,Software Engineer,73122,1 +92403,Other,36,Masters,6,83,4,26,15,0.0,3,84,Urban,Software Engineer,149801,0 +92404,Male,47,High School,12,29,38,62,35,7.0,1,27,Rural,HR Executive,65759,0 +92405,Male,42,Masters,1,14,79,5,10,0.0,0,7,Urban,HR Executive,91947,0 +92406,Male,50,Bachelors,15,75,41,68,76,3.0,4,45,Rural,Manager,103132,0 +92407,Male,40,Diploma,10,59,44,0,82,0.0,7,99,Urban,Data Analyst,58118,0 +92408,Female,39,Masters,13,94,35,67,86,1.0,2,68,Semi-Urban,Data Analyst,50286,1 +92409,Male,59,Diploma,9,78,81,51,70,9.0,4,96,Urban,Software Engineer,61050,1 +92410,Female,27,Masters,10,66,56,14,1,2.0,4,8,Semi-Urban,Data Analyst,29147,0 +92411,Female,28,Diploma,17,19,13,70,16,4.0,2,92,Semi-Urban,Software Engineer,38774,0 +92412,Male,33,PhD,2,91,23,46,52,9.0,6,86,Rural,HR Executive,60271,1 +92413,Male,25,Masters,12,78,17,87,25,3.0,5,11,Rural,Software Engineer,131777,0 +92414,Female,28,Masters,3,51,89,70,30,5.0,4,55,Rural,HR Executive,63500,1 +92415,Female,54,Masters,9,93,59,41,24,3.0,4,48,Urban,Data Analyst,129067,1 +92416,Male,47,Bachelors,14,26,58,54,64,7.0,2,71,Semi-Urban,Manager,64056,0 +92417,Male,29,PhD,5,32,84,4,72,0.0,1,81,Urban,ML Engineer,147835,0 +92418,Female,23,Bachelors,12,30,14,13,62,3.0,0,84,Urban,Data Analyst,118417,0 +92419,Male,35,Bachelors,7,99,26,96,22,3.0,7,74,Urban,Data Analyst,50273,1 +92420,Female,47,Bachelors,17,88,26,11,81,1.0,1,54,Rural,ML Engineer,134140,0 +92421,Male,56,Bachelors,13,10,51,81,40,1.0,2,83,Urban,ML Engineer,124949,0 +92422,Male,32,Masters,15,75,51,73,71,9.0,3,40,Urban,ML Engineer,59356,1 +92423,Female,37,High School,2,29,35,39,54,6.0,6,63,Urban,Manager,25691,0 +92424,Other,33,Masters,14,65,35,24,89,0.0,1,83,Urban,Manager,83616,0 +92425,Male,59,Bachelors,13,21,95,12,67,5.0,2,34,Semi-Urban,Manager,87849,0 +92426,Female,23,Diploma,8,19,86,56,96,6.0,1,32,Urban,Manager,61879,0 +92427,Male,25,Diploma,9,46,91,88,30,1.0,6,90,Rural,Software Engineer,49760,1 +92428,Male,47,High School,3,9,21,48,21,6.0,2,82,Urban,ML Engineer,132145,0 +92429,Male,51,High School,13,87,42,59,84,9.0,0,49,Semi-Urban,Software Engineer,68595,1 +92430,Male,23,High School,2,94,15,68,79,5.0,2,63,Semi-Urban,ML Engineer,31184,1 +92431,Female,36,Diploma,18,31,20,46,4,0.0,6,30,Rural,Data Analyst,102851,0 +92432,Male,46,Bachelors,10,38,83,5,2,4.0,3,17,Urban,ML Engineer,47146,0 +92433,Female,53,High School,0,28,73,84,65,4.0,5,96,Urban,Manager,80027,1 +92434,Male,33,Masters,0,30,87,89,59,2.0,4,14,Rural,Software Engineer,130807,0 +92435,Male,41,Bachelors,19,62,52,29,96,5.0,4,81,Urban,Manager,109990,0 +92436,Male,25,High School,3,8,55,74,69,8.0,6,86,Urban,Data Analyst,51398,0 +92437,Male,47,PhD,2,9,74,73,75,5.0,5,75,Urban,ML Engineer,89090,0 +92438,Male,48,Bachelors,3,4,47,80,13,8.0,5,68,Urban,ML Engineer,117809,0 +92439,Female,54,Bachelors,16,46,46,59,15,3.0,6,25,Urban,Software Engineer,121715,0 +92440,Female,27,High School,5,94,2,91,32,0.0,3,58,Semi-Urban,HR Executive,113566,1 +92441,Male,36,Masters,19,85,47,46,52,0.0,1,74,Semi-Urban,Software Engineer,76305,1 +92442,Male,44,Bachelors,11,15,5,42,75,1.0,2,24,Urban,Manager,122330,0 +92443,Female,30,Diploma,7,46,35,67,51,8.0,1,3,Rural,ML Engineer,39902,0 +92444,Female,52,High School,13,40,50,75,55,0.0,5,39,Semi-Urban,Software Engineer,93958,0 +92445,Male,25,Bachelors,11,1,55,4,54,3.0,7,34,Urban,ML Engineer,52471,0 +92446,Female,40,High School,16,77,97,73,70,7.0,2,16,Semi-Urban,HR Executive,92633,1 +92447,Male,47,High School,7,55,50,80,98,3.0,6,88,Urban,Manager,142211,1 +92448,Male,31,Bachelors,18,69,58,77,57,6.0,6,46,Urban,Software Engineer,132622,1 +92449,Male,59,Bachelors,18,75,2,18,94,4.0,5,20,Urban,Manager,109159,0 +92450,Female,48,Diploma,19,28,90,10,92,1.0,3,95,Urban,Data Analyst,51896,0 +92451,Female,29,High School,1,41,0,23,87,9.0,3,40,Urban,HR Executive,25908,0 +92452,Other,32,Diploma,9,5,13,45,97,0.0,4,77,Semi-Urban,Manager,104251,0 +92453,Female,33,High School,16,29,3,87,63,5.0,4,78,Urban,Data Analyst,127003,0 +92454,Female,26,Diploma,4,61,77,94,13,0.0,5,71,Urban,HR Executive,39050,1 +92455,Male,27,Bachelors,8,80,21,96,36,0.0,4,77,Urban,HR Executive,28301,1 +92456,Male,29,Masters,9,29,50,80,32,4.0,7,98,Urban,HR Executive,32464,1 +92457,Male,50,Diploma,13,16,49,71,50,8.0,6,19,Semi-Urban,ML Engineer,145676,0 +92458,Other,49,Bachelors,19,47,33,64,46,3.0,5,42,Rural,Manager,56416,0 +92459,Male,36,Masters,9,37,26,7,29,7.0,3,79,Semi-Urban,Software Engineer,121541,0 +92460,Female,40,Diploma,15,71,78,28,82,6.0,7,20,Rural,HR Executive,140694,0 +92461,Male,28,Diploma,11,90,43,14,34,9.0,1,77,Urban,ML Engineer,133884,0 +92462,Male,41,Bachelors,6,82,85,28,11,8.0,6,48,Semi-Urban,HR Executive,47993,1 +92463,Male,50,High School,17,18,46,5,44,2.0,3,80,Semi-Urban,Data Analyst,37591,0 +92464,Female,38,PhD,11,40,45,9,89,5.0,2,44,Semi-Urban,Manager,80184,0 +92465,Male,49,Bachelors,15,29,93,87,77,8.0,2,6,Rural,HR Executive,93927,0 +92466,Female,57,Bachelors,8,44,19,31,28,8.0,5,24,Semi-Urban,Software Engineer,56672,0 +92467,Male,57,Bachelors,17,9,27,79,75,1.0,1,15,Urban,HR Executive,32860,0 +92468,Female,53,High School,8,3,27,85,23,1.0,6,7,Urban,ML Engineer,125765,0 +92469,Male,22,Bachelors,0,91,98,67,12,7.0,6,45,Urban,Manager,102945,1 +92470,Male,24,Masters,16,41,50,14,74,7.0,3,92,Urban,ML Engineer,74565,0 +92471,Male,23,Bachelors,6,46,47,44,49,0.0,1,18,Semi-Urban,Data Analyst,116047,0 +92472,Female,30,Bachelors,8,21,47,4,70,2.0,1,54,Semi-Urban,Manager,132981,0 +92473,Male,34,PhD,2,35,0,53,77,8.0,6,23,Urban,ML Engineer,114808,0 +92474,Female,50,High School,17,53,48,15,28,0.0,7,49,Semi-Urban,Software Engineer,96547,0 +92475,Female,39,Bachelors,19,31,36,68,41,3.0,4,48,Urban,Software Engineer,53200,0 +92476,Male,44,Masters,7,36,47,78,48,8.0,1,85,Semi-Urban,ML Engineer,76467,1 +92477,Other,23,Diploma,18,97,61,4,45,8.0,5,59,Semi-Urban,Manager,31496,0 +92478,Female,25,Masters,16,87,77,10,94,6.0,4,96,Urban,HR Executive,65870,1 +92479,Male,59,Masters,18,44,43,4,43,0.0,0,51,Urban,Manager,100517,0 +92480,Female,42,High School,10,61,38,29,40,8.0,5,46,Semi-Urban,Software Engineer,111487,0 +92481,Male,40,Diploma,18,73,69,1,33,5.0,3,94,Urban,Data Analyst,95901,1 +92482,Female,42,Bachelors,17,25,0,35,82,8.0,0,23,Urban,Manager,58934,0 +92483,Male,40,Diploma,10,7,68,13,48,7.0,5,78,Urban,ML Engineer,119737,0 +92484,Other,22,Bachelors,12,46,93,91,56,6.0,5,99,Rural,Data Analyst,110826,1 +92485,Male,41,Bachelors,19,95,17,32,22,1.0,7,16,Rural,ML Engineer,80646,0 +92486,Male,58,Diploma,2,17,2,60,11,3.0,5,6,Semi-Urban,Manager,101483,0 +92487,Male,35,Bachelors,16,69,33,33,37,9.0,1,68,Rural,Manager,70485,0 +92488,Male,51,Bachelors,4,9,76,96,54,6.0,2,16,Urban,Manager,39380,0 +92489,Male,56,Bachelors,11,12,53,22,15,5.0,1,78,Semi-Urban,Software Engineer,66391,0 +92490,Female,23,Bachelors,7,37,32,55,73,1.0,4,19,Urban,Manager,119265,0 +92491,Male,34,Diploma,3,26,32,31,54,7.0,4,1,Semi-Urban,Data Analyst,72948,0 +92492,Male,22,Diploma,19,97,73,4,38,0.0,6,35,Urban,ML Engineer,107788,0 +92493,Female,39,Bachelors,3,74,38,24,44,8.0,5,12,Rural,Manager,147644,0 +92494,Male,32,Bachelors,5,63,12,30,71,4.0,2,18,Rural,Software Engineer,127933,0 +92495,Female,52,Diploma,7,60,9,6,29,0.0,7,37,Urban,Manager,141308,0 +92496,Female,44,Masters,4,25,87,83,46,0.0,3,13,Urban,Manager,101167,0 +92497,Male,31,PhD,4,76,92,81,16,6.0,3,41,Semi-Urban,Manager,148441,1 +92498,Male,33,Masters,14,51,28,68,20,8.0,0,27,Urban,ML Engineer,86252,0 +92499,Male,42,Masters,8,37,77,63,18,1.0,0,81,Rural,HR Executive,89721,1 +92500,Male,33,Masters,19,55,45,87,14,0.0,3,53,Rural,Data Analyst,105014,1 +92501,Female,28,High School,4,74,87,81,1,5.0,7,48,Urban,Manager,47229,1 +92502,Female,24,Bachelors,15,18,72,87,54,9.0,7,44,Urban,Software Engineer,137595,0 +92503,Male,24,Masters,16,86,28,84,75,7.0,2,16,Urban,HR Executive,60851,0 +92504,Male,53,Bachelors,16,72,13,1,21,3.0,7,87,Semi-Urban,Software Engineer,45014,0 +92505,Female,51,Bachelors,18,67,91,6,58,0.0,1,41,Urban,Software Engineer,118351,0 +92506,Female,22,Bachelors,17,70,12,81,24,6.0,7,54,Rural,ML Engineer,76491,0 +92507,Female,32,High School,8,95,84,73,76,3.0,2,79,Urban,ML Engineer,79010,1 +92508,Female,56,High School,19,57,10,61,99,1.0,7,9,Semi-Urban,ML Engineer,70571,0 +92509,Male,59,Bachelors,17,87,44,67,53,6.0,1,57,Semi-Urban,ML Engineer,56237,1 +92510,Female,36,Diploma,2,40,3,75,72,9.0,2,90,Urban,Data Analyst,107618,0 +92511,Female,44,Bachelors,17,32,74,99,51,5.0,1,37,Semi-Urban,ML Engineer,74078,1 +92512,Male,54,Masters,6,27,94,87,86,6.0,4,88,Urban,ML Engineer,41099,1 +92513,Female,30,Masters,6,6,50,90,11,6.0,7,32,Urban,Manager,89395,0 +92514,Male,38,Bachelors,7,78,61,86,65,1.0,4,54,Rural,Data Analyst,27930,1 +92515,Female,55,Bachelors,3,51,75,34,47,2.0,3,75,Urban,Manager,149692,0 +92516,Female,53,Bachelors,2,79,79,44,67,3.0,3,30,Urban,Data Analyst,78277,0 +92517,Female,54,Masters,18,72,8,39,41,7.0,3,78,Semi-Urban,ML Engineer,90724,0 +92518,Female,22,Bachelors,6,80,82,98,14,9.0,2,42,Urban,HR Executive,108589,1 +92519,Male,39,Bachelors,19,13,30,5,64,7.0,3,36,Semi-Urban,Data Analyst,53262,0 +92520,Female,56,Masters,15,23,19,27,62,4.0,1,97,Urban,Software Engineer,145546,0 +92521,Female,48,Masters,0,71,8,35,78,7.0,1,60,Rural,Manager,74269,0 +92522,Male,36,Bachelors,0,75,55,97,20,6.0,1,86,Semi-Urban,Software Engineer,123196,1 +92523,Male,27,High School,5,72,35,57,87,4.0,3,35,Urban,ML Engineer,51906,0 +92524,Male,24,Bachelors,17,99,73,86,60,0.0,3,59,Urban,ML Engineer,96905,1 +92525,Male,34,Bachelors,2,63,85,36,89,2.0,4,88,Rural,Manager,119035,1 +92526,Other,47,Diploma,1,20,37,84,90,1.0,2,96,Rural,ML Engineer,33241,0 +92527,Male,39,Diploma,12,72,96,53,60,4.0,3,30,Urban,ML Engineer,24352,1 +92528,Male,52,Bachelors,5,67,51,7,40,9.0,3,36,Urban,Manager,41321,0 +92529,Male,58,Masters,1,48,94,47,67,0.0,1,78,Semi-Urban,Manager,38567,1 +92530,Female,36,High School,0,75,37,58,76,7.0,6,54,Rural,ML Engineer,54022,0 +92531,Male,44,Bachelors,14,70,94,78,95,5.0,2,21,Semi-Urban,Manager,64661,1 +92532,Female,24,Masters,7,94,64,88,65,9.0,6,54,Semi-Urban,Manager,88328,1 +92533,Female,40,High School,2,61,46,6,47,5.0,1,74,Semi-Urban,Manager,114764,0 +92534,Female,35,Diploma,18,95,58,29,47,6.0,3,82,Semi-Urban,HR Executive,40426,1 +92535,Female,50,Bachelors,7,15,44,96,7,7.0,1,19,Semi-Urban,Software Engineer,109631,0 +92536,Female,30,Masters,11,57,19,67,98,9.0,1,1,Urban,Manager,21437,0 +92537,Male,30,High School,19,84,21,4,38,9.0,4,86,Semi-Urban,ML Engineer,101345,0 +92538,Female,43,Masters,17,35,2,29,61,9.0,5,7,Urban,Software Engineer,66578,0 +92539,Male,37,Masters,6,40,62,62,67,9.0,1,33,Urban,HR Executive,142376,0 +92540,Male,46,Bachelors,7,1,28,84,99,2.0,6,87,Semi-Urban,ML Engineer,145629,0 +92541,Female,24,Diploma,2,70,13,82,43,4.0,7,20,Rural,HR Executive,147501,0 +92542,Male,38,Masters,10,60,20,26,85,0.0,2,28,Urban,Software Engineer,92605,0 +92543,Male,48,Bachelors,15,76,38,62,39,0.0,6,62,Urban,HR Executive,61779,1 +92544,Male,35,Bachelors,6,57,1,75,76,0.0,7,66,Semi-Urban,ML Engineer,70763,0 +92545,Male,41,Diploma,3,51,8,55,50,6.0,6,54,Rural,HR Executive,107327,0 +92546,Female,57,Masters,16,9,41,67,66,4.0,6,95,Urban,Manager,38792,0 +92547,Female,25,Bachelors,9,49,17,17,99,8.0,6,32,Semi-Urban,Data Analyst,116114,0 +92548,Female,45,Masters,18,29,43,99,81,2.0,6,99,Semi-Urban,ML Engineer,110434,1 +92549,Other,52,Bachelors,18,89,88,75,56,2.0,1,23,Urban,Software Engineer,135215,1 +92550,Other,50,Bachelors,11,34,28,68,85,8.0,0,17,Urban,Data Analyst,22880,0 +92551,Female,24,Bachelors,19,54,62,65,86,5.0,7,30,Urban,Manager,50821,0 +92552,Male,25,Bachelors,11,13,42,92,8,8.0,5,48,Urban,Manager,63542,0 +92553,Male,59,Bachelors,15,98,58,7,45,3.0,2,17,Urban,Data Analyst,54348,0 +92554,Female,47,Bachelors,5,48,75,35,7,1.0,3,69,Urban,HR Executive,56823,0 +92555,Female,44,Bachelors,7,71,24,72,25,3.0,3,63,Urban,ML Engineer,51359,0 +92556,Other,29,Masters,15,94,3,36,54,3.0,6,65,Urban,Data Analyst,130304,0 +92557,Female,42,Bachelors,8,76,77,63,27,7.0,1,12,Semi-Urban,Software Engineer,104811,0 +92558,Female,56,Diploma,0,52,79,43,7,5.0,6,64,Urban,ML Engineer,110338,0 +92559,Male,28,Bachelors,5,97,37,90,10,5.0,4,61,Semi-Urban,Data Analyst,134479,1 +92560,Male,50,Masters,0,93,59,1,93,8.0,2,5,Rural,Software Engineer,110055,0 +92561,Female,26,Diploma,10,11,94,61,95,7.0,7,38,Urban,HR Executive,51128,0 +92562,Male,38,Bachelors,12,59,56,46,62,5.0,4,76,Rural,Data Analyst,141158,1 +92563,Male,32,Masters,16,6,68,9,30,2.0,1,58,Urban,HR Executive,115414,0 +92564,Male,39,Diploma,19,23,88,40,57,1.0,6,27,Urban,Software Engineer,95731,0 +92565,Female,21,Bachelors,19,72,3,47,28,4.0,6,62,Semi-Urban,Manager,58275,0 +92566,Other,42,Masters,5,34,9,88,26,7.0,6,31,Urban,Manager,78610,0 +92567,Male,52,Diploma,17,66,23,98,72,9.0,1,87,Rural,HR Executive,132739,1 +92568,Male,35,High School,17,17,47,68,1,3.0,4,58,Rural,Data Analyst,67744,0 +92569,Male,36,PhD,16,18,51,70,52,9.0,2,83,Urban,Data Analyst,145327,0 +92570,Male,45,Bachelors,5,24,97,30,91,7.0,6,19,Urban,HR Executive,25706,0 +92571,Female,21,High School,9,31,23,55,75,1.0,5,1,Urban,ML Engineer,21646,0 +92572,Male,52,High School,2,84,92,1,6,0.0,6,41,Rural,HR Executive,29462,0 +92573,Female,21,Bachelors,2,2,85,22,21,5.0,0,28,Rural,Manager,53834,0 +92574,Female,47,Masters,18,14,78,22,4,4.0,0,98,Urban,Software Engineer,93079,0 +92575,Male,53,Bachelors,2,5,5,36,33,3.0,2,39,Urban,Manager,38713,0 +92576,Female,37,High School,4,9,25,94,67,9.0,5,8,Urban,ML Engineer,128958,0 +92577,Other,31,Bachelors,16,32,44,95,46,6.0,2,40,Urban,Software Engineer,20007,0 +92578,Male,38,Bachelors,2,14,1,1,21,1.0,4,46,Semi-Urban,Manager,72144,0 +92579,Male,49,Masters,9,97,11,14,83,4.0,6,45,Semi-Urban,Manager,147474,0 +92580,Male,48,Bachelors,9,95,24,26,18,1.0,4,89,Rural,Software Engineer,70142,0 +92581,Male,50,Masters,7,19,73,76,62,4.0,0,63,Semi-Urban,Manager,52071,0 +92582,Male,33,Bachelors,1,48,14,97,93,7.0,0,64,Rural,ML Engineer,80204,0 +92583,Male,42,High School,8,25,76,40,80,3.0,3,69,Urban,Data Analyst,144054,0 +92584,Female,54,Masters,17,13,32,70,87,0.0,5,3,Urban,Manager,85089,0 +92585,Male,49,Masters,17,18,71,47,90,7.0,6,70,Urban,ML Engineer,143620,0 +92586,Female,35,Diploma,4,58,24,61,15,7.0,3,55,Semi-Urban,Manager,34751,0 +92587,Female,49,Diploma,5,30,87,15,71,9.0,4,64,Urban,ML Engineer,84988,0 +92588,Female,33,Diploma,6,53,99,49,28,5.0,1,46,Rural,Manager,133951,1 +92589,Male,30,Bachelors,14,4,29,43,21,1.0,0,38,Urban,Software Engineer,146019,0 +92590,Male,58,Bachelors,11,32,53,96,86,4.0,5,26,Rural,Software Engineer,86277,0 +92591,Male,31,Bachelors,4,17,14,90,84,3.0,7,11,Rural,HR Executive,132014,0 +92592,Female,29,Bachelors,0,18,74,79,19,6.0,1,59,Semi-Urban,ML Engineer,56988,0 +92593,Male,47,Bachelors,11,59,72,97,41,9.0,1,6,Urban,HR Executive,77608,0 +92594,Female,42,Bachelors,3,84,70,32,52,7.0,0,19,Urban,Software Engineer,57686,0 +92595,Male,22,PhD,0,64,16,86,11,7.0,1,6,Semi-Urban,Software Engineer,98898,0 +92596,Male,45,Diploma,18,6,6,54,85,8.0,1,43,Semi-Urban,Data Analyst,25205,0 +92597,Male,24,High School,7,80,11,76,84,0.0,5,43,Rural,ML Engineer,103378,0 +92598,Female,37,Masters,12,81,21,84,4,6.0,1,99,Urban,Software Engineer,78783,1 +92599,Female,44,Diploma,16,39,89,56,75,4.0,6,88,Semi-Urban,Data Analyst,92539,1 +92600,Female,39,Masters,12,94,75,78,11,5.0,3,46,Urban,Software Engineer,90851,1 +92601,Male,40,Diploma,10,33,73,84,46,9.0,2,94,Urban,Manager,142835,1 +92602,Female,29,Masters,14,35,44,31,70,1.0,5,42,Urban,Manager,51778,0 +92603,Male,29,Bachelors,17,8,84,47,4,9.0,4,94,Urban,Software Engineer,64616,0 +92604,Male,53,PhD,5,78,13,82,80,0.0,6,31,Urban,Software Engineer,127246,0 +92605,Male,28,Bachelors,1,47,67,36,29,8.0,7,44,Urban,HR Executive,25011,0 +92606,Male,57,Bachelors,12,92,47,70,96,2.0,7,36,Urban,Manager,131484,1 +92607,Male,21,Masters,7,38,97,21,20,2.0,6,46,Urban,Data Analyst,87061,0 +92608,Female,53,Diploma,14,91,48,8,56,3.0,3,67,Urban,Software Engineer,114255,0 +92609,Male,47,Masters,15,8,91,59,34,7.0,0,80,Rural,Manager,74358,1 +92610,Male,24,Masters,5,76,77,29,55,0.0,7,39,Semi-Urban,ML Engineer,145924,0 +92611,Male,45,Diploma,2,20,14,94,43,3.0,7,20,Semi-Urban,Software Engineer,76591,0 +92612,Female,36,Masters,19,65,34,24,95,6.0,3,26,Rural,HR Executive,147783,0 +92613,Male,28,High School,1,13,79,3,5,4.0,3,55,Rural,ML Engineer,69059,0 +92614,Male,39,Diploma,17,69,38,10,46,4.0,3,69,Semi-Urban,Manager,141002,0 +92615,Male,25,Masters,10,34,29,60,75,7.0,2,9,Urban,ML Engineer,85836,0 +92616,Male,26,PhD,13,51,96,28,51,9.0,6,91,Rural,Manager,112848,1 +92617,Female,34,Diploma,6,91,70,66,84,0.0,5,52,Rural,Manager,47377,1 +92618,Male,41,Diploma,5,91,32,94,76,0.0,6,49,Rural,ML Engineer,143960,1 +92619,Male,42,Bachelors,4,54,38,46,10,4.0,4,45,Urban,HR Executive,120488,0 +92620,Female,47,Bachelors,10,62,57,32,17,9.0,1,62,Urban,Data Analyst,96088,0 +92621,Female,54,Masters,6,63,24,37,56,6.0,6,63,Urban,Data Analyst,45992,0 +92622,Male,21,Diploma,10,91,68,7,23,0.0,2,54,Urban,Data Analyst,40829,0 +92623,Female,27,Masters,3,77,23,20,9,6.0,0,48,Semi-Urban,Software Engineer,132377,0 +92624,Female,55,Masters,3,97,55,76,92,0.0,5,96,Urban,ML Engineer,77205,1 +92625,Male,31,PhD,2,81,33,51,37,7.0,6,1,Semi-Urban,Data Analyst,103207,0 +92626,Male,28,PhD,3,71,84,0,67,0.0,3,75,Urban,Manager,27546,0 +92627,Female,49,Masters,10,56,43,18,47,8.0,3,10,Urban,ML Engineer,145821,0 +92628,Female,24,Bachelors,16,53,37,95,31,3.0,5,23,Urban,ML Engineer,21303,0 +92629,Female,52,Bachelors,5,73,59,31,47,6.0,0,42,Urban,Manager,105987,0 +92630,Male,50,Diploma,2,58,73,21,39,3.0,7,88,Urban,Software Engineer,81313,1 +92631,Female,38,Diploma,0,79,97,87,12,4.0,7,82,Rural,HR Executive,36626,1 +92632,Male,33,Bachelors,10,85,61,55,8,9.0,0,86,Semi-Urban,ML Engineer,44534,1 +92633,Female,35,High School,14,84,37,7,45,8.0,6,9,Urban,Software Engineer,48271,0 +92634,Male,27,High School,12,40,51,34,68,9.0,3,90,Urban,Data Analyst,74577,0 +92635,Female,21,PhD,3,82,14,21,18,1.0,0,94,Rural,Manager,34678,0 +92636,Female,27,Bachelors,1,74,1,99,48,8.0,1,29,Urban,HR Executive,149571,0 +92637,Other,41,High School,5,98,77,72,95,2.0,4,7,Urban,Software Engineer,122991,1 +92638,Male,33,Bachelors,2,22,95,82,51,2.0,0,71,Semi-Urban,Manager,138246,1 +92639,Male,54,Diploma,19,42,94,50,89,5.0,6,13,Rural,Manager,148585,0 +92640,Male,42,Diploma,19,30,44,45,52,5.0,3,40,Semi-Urban,Manager,95911,0 +92641,Male,54,Bachelors,18,82,16,40,92,9.0,6,0,Urban,Software Engineer,123084,0 +92642,Female,56,High School,13,30,96,1,47,1.0,6,91,Semi-Urban,HR Executive,116610,0 +92643,Male,45,Bachelors,13,12,80,46,33,8.0,3,38,Semi-Urban,Manager,54626,0 +92644,Male,32,High School,19,80,17,66,37,9.0,3,65,Urban,HR Executive,64610,0 +92645,Male,38,Masters,7,49,61,64,39,5.0,4,58,Rural,Software Engineer,31445,0 +92646,Male,27,Masters,12,68,27,26,89,1.0,6,13,Semi-Urban,Data Analyst,73540,0 +92647,Female,30,Bachelors,9,72,37,81,48,6.0,3,96,Urban,Data Analyst,131533,1 +92648,Male,55,Diploma,9,61,55,36,67,5.0,2,44,Urban,Software Engineer,146750,0 +92649,Male,44,Diploma,9,47,46,18,29,3.0,7,91,Semi-Urban,HR Executive,99718,0 +92650,Male,37,PhD,10,37,78,56,89,7.0,2,75,Semi-Urban,Data Analyst,22083,1 +92651,Male,36,Diploma,11,20,89,35,38,0.0,1,50,Urban,Data Analyst,145953,0 +92652,Male,55,Bachelors,10,75,30,94,4,6.0,4,25,Urban,Software Engineer,149973,0 +92653,Female,24,Bachelors,17,72,31,30,55,6.0,1,89,Semi-Urban,Manager,85849,0 +92654,Female,50,Diploma,11,78,3,38,17,4.0,6,15,Urban,Data Analyst,106692,0 +92655,Female,29,Diploma,1,42,48,50,28,4.0,1,81,Semi-Urban,HR Executive,111808,0 +92656,Male,38,High School,6,98,50,86,48,3.0,6,9,Urban,Manager,52433,1 +92657,Male,32,Bachelors,10,97,70,46,32,2.0,2,3,Urban,Software Engineer,97236,0 +92658,Male,37,Bachelors,2,78,78,23,46,4.0,2,40,Urban,Data Analyst,28036,0 +92659,Male,28,Diploma,4,21,33,37,62,7.0,0,24,Semi-Urban,Manager,82490,0 +92660,Female,33,Diploma,18,4,48,73,53,4.0,2,93,Rural,ML Engineer,89493,0 +92661,Male,42,High School,8,69,17,26,56,2.0,6,0,Urban,Software Engineer,140789,0 +92662,Male,24,Masters,10,97,29,19,68,1.0,3,99,Semi-Urban,HR Executive,47862,1 +92663,Male,33,Bachelors,13,52,28,36,57,4.0,5,0,Urban,Software Engineer,111895,0 +92664,Male,32,Bachelors,2,64,85,77,93,0.0,5,24,Semi-Urban,Software Engineer,94324,1 +92665,Male,50,Bachelors,5,46,83,83,34,2.0,1,79,Urban,Manager,43227,1 +92666,Female,44,Masters,19,10,37,3,1,1.0,7,39,Urban,Manager,92247,0 +92667,Female,29,Diploma,7,89,19,23,29,8.0,3,30,Urban,HR Executive,62552,0 +92668,Female,53,Bachelors,7,36,44,33,87,8.0,6,55,Urban,Software Engineer,82321,0 +92669,Male,47,Bachelors,7,0,16,74,95,8.0,2,22,Urban,Software Engineer,27443,0 +92670,Male,58,Bachelors,11,47,5,72,93,9.0,7,64,Rural,HR Executive,112184,0 +92671,Male,51,Bachelors,7,34,5,14,52,8.0,7,22,Urban,HR Executive,75389,0 +92672,Male,45,Bachelors,5,2,19,55,74,8.0,2,33,Urban,Software Engineer,129767,0 +92673,Female,48,Bachelors,11,22,6,58,18,3.0,2,28,Rural,Software Engineer,42050,0 +92674,Male,24,Bachelors,2,2,96,49,13,7.0,4,19,Urban,ML Engineer,67116,0 +92675,Male,23,Masters,1,17,20,18,89,7.0,3,37,Semi-Urban,Software Engineer,28407,0 +92676,Female,43,Masters,10,59,97,68,25,2.0,0,3,Rural,HR Executive,46838,0 +92677,Male,41,Masters,12,42,94,71,92,9.0,6,55,Semi-Urban,Software Engineer,71841,1 +92678,Female,38,Bachelors,18,98,56,86,48,6.0,2,63,Semi-Urban,HR Executive,46577,1 +92679,Male,44,Bachelors,13,55,34,47,27,6.0,0,29,Urban,Software Engineer,136615,0 +92680,Female,24,Diploma,11,51,63,71,52,7.0,4,73,Rural,ML Engineer,28273,1 +92681,Male,51,Bachelors,0,95,0,26,82,9.0,7,96,Semi-Urban,Data Analyst,59901,0 +92682,Male,59,Bachelors,14,5,37,9,72,3.0,4,91,Semi-Urban,HR Executive,55147,0 +92683,Female,33,Bachelors,0,38,91,13,79,9.0,1,78,Urban,HR Executive,44253,0 +92684,Female,54,Bachelors,9,79,35,1,23,3.0,1,43,Rural,Manager,68420,0 +92685,Female,28,Masters,15,61,8,7,63,7.0,6,73,Urban,HR Executive,117072,0 +92686,Female,54,Masters,7,92,19,31,61,7.0,2,18,Urban,Software Engineer,122958,0 +92687,Male,52,Bachelors,14,35,96,91,98,6.0,4,56,Urban,ML Engineer,116253,1 +92688,Female,56,Diploma,17,7,18,73,19,9.0,2,42,Urban,Data Analyst,124962,0 +92689,Male,50,Diploma,10,91,28,1,25,6.0,0,16,Urban,HR Executive,141007,0 +92690,Male,39,Masters,10,47,45,13,14,5.0,6,53,Rural,HR Executive,55001,0 +92691,Male,55,Diploma,6,71,59,16,65,9.0,1,98,Urban,Data Analyst,117627,1 +92692,Male,38,Bachelors,8,56,36,65,2,7.0,0,78,Urban,Software Engineer,96583,1 +92693,Male,38,Bachelors,10,79,51,52,18,1.0,6,97,Urban,Software Engineer,46766,1 +92694,Female,40,Diploma,7,38,73,54,93,9.0,7,40,Urban,HR Executive,129810,0 +92695,Male,22,Diploma,17,31,23,74,92,7.0,6,86,Urban,Software Engineer,67498,0 +92696,Male,47,Bachelors,11,71,53,51,39,9.0,7,56,Semi-Urban,Software Engineer,96338,0 +92697,Female,29,Bachelors,9,97,0,64,32,4.0,5,50,Urban,Software Engineer,34243,0 +92698,Female,53,Bachelors,19,63,51,56,27,7.0,1,33,Rural,Manager,135832,0 +92699,Female,35,Masters,8,72,42,4,30,0.0,1,13,Urban,Data Analyst,130334,0 +92700,Male,50,High School,16,73,65,82,15,6.0,2,63,Urban,Data Analyst,149788,1 +92701,Male,36,Bachelors,7,32,40,56,91,9.0,4,39,Rural,Software Engineer,48745,0 +92702,Female,39,Diploma,17,28,90,4,47,2.0,2,95,Urban,Data Analyst,62595,0 +92703,Male,24,Bachelors,17,54,19,68,56,7.0,4,20,Urban,ML Engineer,20741,0 +92704,Male,47,Masters,17,28,10,40,41,3.0,3,6,Urban,ML Engineer,100181,0 +92705,Male,26,Bachelors,10,30,57,42,20,9.0,1,43,Rural,Manager,22454,0 +92706,Female,41,Bachelors,9,27,83,78,51,5.0,0,56,Urban,HR Executive,91321,1 +92707,Male,59,Diploma,0,31,49,87,23,1.0,6,69,Urban,ML Engineer,44904,1 +92708,Male,33,Diploma,16,19,65,49,7,7.0,7,42,Urban,HR Executive,24146,0 +92709,Female,48,Bachelors,13,4,24,74,16,7.0,2,87,Urban,Software Engineer,126096,0 +92710,Female,57,High School,3,5,34,53,32,8.0,3,27,Rural,Data Analyst,98444,0 +92711,Female,38,Bachelors,1,45,65,39,38,5.0,4,23,Urban,Manager,40412,0 +92712,Female,22,Diploma,2,6,62,12,42,7.0,4,99,Rural,HR Executive,95407,0 +92713,Male,54,Diploma,0,39,28,25,12,4.0,6,57,Urban,Manager,31825,0 +92714,Male,53,Bachelors,6,32,42,41,8,6.0,2,39,Urban,HR Executive,145134,0 +92715,Female,45,Bachelors,9,37,70,63,66,7.0,4,32,Urban,Software Engineer,71591,0 +92716,Other,23,PhD,9,71,77,21,42,3.0,1,89,Semi-Urban,HR Executive,109713,1 +92717,Female,51,Diploma,18,13,12,77,57,7.0,6,68,Urban,Software Engineer,129780,0 +92718,Male,21,Diploma,14,13,78,57,34,3.0,3,36,Urban,Software Engineer,67926,0 +92719,Male,43,Bachelors,11,94,2,71,98,6.0,1,12,Urban,Data Analyst,44403,0 +92720,Other,24,High School,15,36,54,13,40,7.0,2,8,Urban,ML Engineer,121509,0 +92721,Other,36,Masters,16,74,92,20,39,4.0,5,27,Urban,Software Engineer,36154,0 +92722,Female,28,Masters,17,39,75,85,71,3.0,6,82,Rural,Software Engineer,97751,1 +92723,Male,47,Bachelors,4,24,92,89,97,0.0,5,64,Urban,Software Engineer,44685,1 +92724,Male,28,Bachelors,6,53,81,56,52,9.0,0,62,Urban,ML Engineer,62986,1 +92725,Male,37,Diploma,16,68,1,21,55,3.0,4,95,Urban,HR Executive,33805,0 +92726,Female,21,Bachelors,14,52,41,61,82,1.0,1,35,Urban,ML Engineer,143379,0 +92727,Male,26,Masters,3,9,6,31,70,3.0,2,63,Urban,Manager,102693,0 +92728,Male,59,Bachelors,15,67,3,57,94,8.0,4,19,Rural,ML Engineer,118198,0 +92729,Female,44,High School,1,0,32,69,64,8.0,0,20,Semi-Urban,Manager,72843,0 +92730,Female,51,Bachelors,1,32,52,27,54,3.0,6,89,Semi-Urban,HR Executive,32120,0 +92731,Female,31,Bachelors,7,8,63,57,57,1.0,6,59,Semi-Urban,ML Engineer,70548,0 +92732,Male,35,High School,9,55,39,25,0,6.0,6,17,Urban,Manager,125510,0 +92733,Female,53,Diploma,10,46,67,77,75,3.0,6,57,Semi-Urban,Data Analyst,123933,1 +92734,Male,52,Bachelors,1,82,37,65,80,2.0,1,17,Rural,ML Engineer,81206,0 +92735,Female,37,High School,12,78,6,75,69,1.0,3,67,Urban,Data Analyst,41186,0 +92736,Female,34,Bachelors,16,66,58,5,62,9.0,4,57,Urban,Software Engineer,110792,0 +92737,Male,47,PhD,19,48,97,82,21,0.0,3,49,Urban,Software Engineer,148681,1 +92738,Male,28,Diploma,1,28,14,64,13,8.0,1,12,Rural,ML Engineer,61170,0 +92739,Female,43,Diploma,5,5,65,48,42,1.0,2,78,Urban,HR Executive,90303,0 +92740,Male,55,High School,17,8,76,91,13,0.0,7,91,Urban,HR Executive,20716,1 +92741,Male,35,Bachelors,12,59,24,23,75,7.0,7,2,Semi-Urban,Data Analyst,67378,0 +92742,Female,27,High School,12,21,47,43,57,7.0,0,62,Urban,HR Executive,22322,0 +92743,Male,35,Masters,1,50,72,37,48,7.0,4,18,Urban,HR Executive,41573,0 +92744,Female,43,Bachelors,4,44,17,34,34,1.0,5,19,Rural,Manager,27652,0 +92745,Male,52,Bachelors,0,9,21,89,78,1.0,7,78,Urban,Software Engineer,61095,0 +92746,Female,45,PhD,10,49,56,96,4,9.0,5,67,Semi-Urban,Manager,57740,1 +92747,Male,48,Bachelors,16,29,82,39,23,0.0,2,82,Rural,ML Engineer,98350,0 +92748,Male,37,Bachelors,17,82,93,48,86,5.0,5,46,Urban,Software Engineer,126206,1 +92749,Male,57,Bachelors,0,15,97,71,60,9.0,7,68,Urban,Data Analyst,38562,1 +92750,Female,25,Diploma,10,50,73,56,43,2.0,2,87,Semi-Urban,HR Executive,108185,1 +92751,Male,54,High School,11,81,45,22,62,6.0,1,8,Semi-Urban,Data Analyst,59111,0 +92752,Male,46,High School,1,9,21,56,83,7.0,1,62,Rural,ML Engineer,20536,0 +92753,Male,30,Bachelors,19,22,86,10,11,1.0,1,60,Urban,Manager,43892,0 +92754,Male,36,High School,17,71,30,54,25,8.0,6,48,Rural,Manager,93089,0 +92755,Male,57,High School,14,2,89,59,81,9.0,0,70,Semi-Urban,ML Engineer,34214,0 +92756,Male,52,Masters,14,80,14,74,66,1.0,5,58,Urban,Manager,87985,0 +92757,Female,40,Bachelors,15,82,4,20,20,2.0,6,77,Semi-Urban,Software Engineer,89090,0 +92758,Male,41,Bachelors,7,37,24,78,43,3.0,5,86,Rural,Manager,81885,0 +92759,Male,52,Bachelors,3,87,12,17,12,7.0,1,40,Urban,Software Engineer,130742,0 +92760,Male,55,Bachelors,8,16,34,67,86,0.0,0,73,Semi-Urban,Manager,81492,0 +92761,Male,49,Diploma,4,89,5,45,22,5.0,5,95,Urban,Manager,118296,0 +92762,Male,51,High School,13,72,63,36,75,4.0,4,41,Urban,HR Executive,119946,0 +92763,Male,40,Bachelors,1,1,24,1,62,5.0,1,86,Rural,Manager,105169,0 +92764,Male,27,Diploma,18,15,50,39,12,8.0,1,99,Urban,HR Executive,20260,0 +92765,Male,37,Masters,19,28,22,37,24,5.0,5,41,Urban,Data Analyst,73567,0 +92766,Female,56,Bachelors,16,19,98,8,61,3.0,0,3,Semi-Urban,Software Engineer,27128,0 +92767,Male,58,High School,2,78,78,55,39,3.0,0,91,Urban,Software Engineer,52382,1 +92768,Other,52,Masters,12,10,64,3,94,4.0,2,18,Semi-Urban,ML Engineer,142475,0 +92769,Female,37,Bachelors,19,31,58,77,28,5.0,1,33,Rural,Manager,26332,0 +92770,Male,21,Diploma,1,86,2,95,88,2.0,3,65,Semi-Urban,HR Executive,76777,1 +92771,Male,57,High School,14,22,73,2,15,5.0,0,79,Urban,Data Analyst,37057,0 +92772,Male,43,Masters,5,61,37,63,31,2.0,6,8,Rural,Manager,41762,0 +92773,Male,58,Diploma,4,63,37,64,55,4.0,1,13,Semi-Urban,ML Engineer,119962,0 +92774,Male,58,High School,9,8,60,63,9,0.0,5,25,Semi-Urban,ML Engineer,44192,0 +92775,Male,36,High School,9,48,24,79,33,7.0,3,10,Rural,HR Executive,25214,0 +92776,Female,36,Diploma,15,67,38,24,99,9.0,6,75,Urban,HR Executive,107454,0 +92777,Male,39,High School,19,28,10,63,50,9.0,0,27,Semi-Urban,ML Engineer,128157,0 +92778,Female,41,Bachelors,3,64,91,19,29,4.0,0,70,Urban,Manager,122852,1 +92779,Male,23,Bachelors,15,0,76,16,14,7.0,4,31,Rural,Data Analyst,104391,0 +92780,Female,43,High School,19,25,25,43,85,1.0,0,0,Semi-Urban,Manager,109810,0 +92781,Male,32,Bachelors,1,60,94,94,43,0.0,3,1,Urban,ML Engineer,126138,1 +92782,Female,54,High School,17,48,75,36,60,9.0,5,79,Urban,Data Analyst,129495,0 +92783,Male,32,Bachelors,8,44,50,25,17,5.0,3,48,Semi-Urban,Manager,70954,0 +92784,Female,50,Bachelors,9,47,97,62,26,7.0,4,32,Urban,HR Executive,134615,0 +92785,Male,58,Bachelors,10,93,76,21,26,5.0,4,0,Semi-Urban,Data Analyst,99892,0 +92786,Female,45,Diploma,3,9,93,47,8,7.0,2,47,Urban,Manager,129779,0 +92787,Male,27,Diploma,13,29,15,76,21,1.0,0,96,Urban,ML Engineer,104026,0 +92788,Male,59,Bachelors,4,68,59,41,9,1.0,3,36,Urban,HR Executive,62558,0 +92789,Male,26,Diploma,5,27,72,30,60,3.0,7,51,Rural,Manager,64246,0 +92790,Female,27,Diploma,10,44,77,74,34,2.0,1,96,Urban,ML Engineer,112548,1 +92791,Female,42,High School,10,26,54,96,1,8.0,7,88,Rural,ML Engineer,116595,1 +92792,Male,56,Diploma,16,40,5,16,47,4.0,2,63,Semi-Urban,HR Executive,90002,0 +92793,Male,29,Masters,7,86,21,19,62,3.0,2,37,Rural,HR Executive,41463,0 +92794,Male,34,PhD,9,36,55,2,4,2.0,1,76,Urban,Data Analyst,34945,0 +92795,Male,56,High School,19,0,54,63,90,0.0,4,56,Semi-Urban,Software Engineer,113810,0 +92796,Female,39,PhD,6,85,76,50,88,3.0,1,41,Semi-Urban,ML Engineer,23029,1 +92797,Male,39,Bachelors,6,7,72,42,13,0.0,3,5,Semi-Urban,Manager,145791,0 +92798,Male,38,Bachelors,17,29,98,67,80,8.0,1,12,Urban,Software Engineer,105421,0 +92799,Male,38,Bachelors,9,40,33,69,77,6.0,0,9,Urban,Software Engineer,57594,0 +92800,Male,59,PhD,6,30,80,13,43,6.0,6,82,Urban,ML Engineer,23880,0 +92801,Male,45,Bachelors,18,41,71,61,9,2.0,3,9,Semi-Urban,Software Engineer,87608,0 +92802,Male,54,Bachelors,1,73,21,66,7,8.0,4,81,Urban,ML Engineer,75897,1 +92803,Male,42,Diploma,5,28,83,29,12,1.0,1,67,Urban,Data Analyst,78911,0 +92804,Female,49,Diploma,7,38,97,27,80,4.0,6,37,Urban,Data Analyst,88642,0 +92805,Female,33,High School,16,68,40,39,2,9.0,1,69,Urban,Manager,99749,0 +92806,Male,25,High School,12,1,93,44,72,4.0,5,22,Semi-Urban,ML Engineer,79912,0 +92807,Male,44,Diploma,18,82,55,99,48,5.0,3,54,Urban,HR Executive,84232,1 +92808,Other,59,Diploma,7,87,64,51,90,1.0,3,92,Urban,HR Executive,123821,1 +92809,Male,56,Bachelors,2,28,50,58,24,4.0,2,37,Semi-Urban,HR Executive,30690,0 +92810,Male,22,Bachelors,6,42,5,38,30,1.0,4,15,Urban,ML Engineer,113354,0 +92811,Female,51,Diploma,15,69,94,6,62,1.0,6,43,Urban,Data Analyst,137603,0 +92812,Male,37,Bachelors,1,39,35,23,15,9.0,0,78,Urban,Software Engineer,141242,0 +92813,Female,53,Masters,5,54,90,66,95,4.0,6,4,Semi-Urban,Manager,126385,0 +92814,Female,36,Masters,12,36,63,44,30,0.0,5,64,Semi-Urban,Manager,25120,0 +92815,Male,35,High School,17,64,10,41,78,5.0,3,57,Urban,ML Engineer,98713,0 +92816,Male,56,High School,13,8,40,88,63,7.0,1,52,Urban,Manager,89234,0 +92817,Male,55,Bachelors,16,78,63,60,48,4.0,4,18,Semi-Urban,HR Executive,97481,0 +92818,Other,33,High School,16,21,22,62,80,3.0,3,31,Urban,Manager,42671,0 +92819,Female,31,Masters,15,60,46,36,55,7.0,3,70,Semi-Urban,Manager,80628,0 +92820,Male,34,Bachelors,16,5,5,36,78,3.0,6,65,Semi-Urban,Manager,96266,0 +92821,Male,51,Bachelors,13,90,7,80,32,6.0,4,53,Urban,Software Engineer,82247,0 +92822,Male,58,Masters,16,75,84,81,15,6.0,1,42,Semi-Urban,HR Executive,24228,1 +92823,Male,34,Bachelors,1,30,7,13,17,6.0,1,30,Urban,Data Analyst,68508,0 +92824,Male,51,Bachelors,15,16,55,17,9,0.0,0,8,Urban,ML Engineer,28948,0 +92825,Male,57,Bachelors,4,5,84,49,19,1.0,3,90,Urban,Manager,46334,0 +92826,Male,47,Masters,19,72,2,82,63,8.0,7,43,Rural,Manager,44546,0 +92827,Male,35,Masters,9,62,85,76,70,7.0,1,54,Rural,Software Engineer,31174,1 +92828,Male,51,Diploma,11,46,75,90,44,4.0,3,74,Urban,Data Analyst,40133,1 +92829,Female,22,Masters,12,49,21,72,88,3.0,4,37,Urban,HR Executive,85952,0 +92830,Female,48,Bachelors,5,56,51,84,43,3.0,1,67,Urban,Manager,58360,1 +92831,Male,54,Diploma,3,64,9,58,91,2.0,7,49,Urban,Manager,107462,0 +92832,Male,22,Diploma,10,89,3,20,23,2.0,5,87,Rural,Data Analyst,21980,0 +92833,Other,56,Bachelors,11,23,23,85,61,2.0,2,85,Urban,Data Analyst,107741,0 +92834,Male,22,Bachelors,5,24,17,28,25,7.0,2,8,Semi-Urban,Software Engineer,136568,0 +92835,Male,38,High School,3,80,1,42,11,5.0,4,72,Semi-Urban,Data Analyst,38204,0 +92836,Male,44,High School,13,90,69,40,74,4.0,7,2,Urban,ML Engineer,34761,0 +92837,Female,59,High School,0,50,48,3,70,5.0,5,71,Urban,Manager,130835,0 +92838,Male,46,PhD,0,80,77,44,56,6.0,6,98,Semi-Urban,ML Engineer,121521,1 +92839,Male,55,Bachelors,9,63,50,41,29,0.0,6,89,Semi-Urban,ML Engineer,120547,1 +92840,Male,35,Bachelors,8,47,51,59,36,9.0,2,71,Semi-Urban,ML Engineer,62558,0 +92841,Male,28,High School,1,21,17,31,74,1.0,3,6,Semi-Urban,Manager,132275,0 +92842,Male,50,Bachelors,10,22,47,16,43,7.0,2,18,Semi-Urban,Manager,109913,0 +92843,Male,37,Bachelors,11,93,53,72,57,2.0,4,57,Rural,Software Engineer,42888,1 +92844,Male,37,Diploma,10,11,98,71,53,1.0,1,92,Urban,Data Analyst,109163,1 +92845,Female,46,Bachelors,12,81,94,41,84,6.0,2,75,Semi-Urban,Data Analyst,43485,1 +92846,Female,27,Diploma,16,70,83,80,91,6.0,3,87,Urban,HR Executive,140918,1 +92847,Female,30,Diploma,11,55,52,57,90,8.0,2,88,Semi-Urban,Data Analyst,89404,1 +92848,Female,47,Bachelors,19,21,88,43,24,3.0,2,62,Urban,Manager,61887,0 +92849,Male,41,PhD,14,71,14,46,68,3.0,7,19,Urban,Manager,149747,0 +92850,Male,48,Bachelors,2,97,87,0,70,4.0,7,48,Urban,ML Engineer,49096,0 +92851,Male,25,Masters,5,36,69,59,45,1.0,4,23,Rural,Data Analyst,50474,0 +92852,Male,35,High School,18,88,92,83,5,1.0,7,22,Semi-Urban,Manager,59828,1 +92853,Female,25,High School,9,42,73,33,5,8.0,4,75,Urban,Software Engineer,113590,0 +92854,Female,34,High School,2,29,84,79,27,9.0,2,93,Urban,Data Analyst,40421,1 +92855,Male,46,Diploma,13,12,17,47,33,7.0,3,14,Rural,Software Engineer,47584,0 +92856,Male,36,High School,3,80,66,59,82,1.0,4,34,Urban,ML Engineer,118967,1 +92857,Male,39,Diploma,4,28,85,86,29,2.0,6,49,Urban,Data Analyst,121450,1 +92858,Female,50,Diploma,16,46,66,47,83,7.0,7,90,Rural,Manager,27436,1 +92859,Male,51,PhD,9,84,60,36,94,5.0,1,66,Semi-Urban,Manager,117048,1 +92860,Female,30,Diploma,15,78,19,29,20,7.0,4,42,Urban,Data Analyst,135599,0 +92861,Male,26,Bachelors,10,48,63,50,60,5.0,4,93,Urban,ML Engineer,56200,1 +92862,Female,43,Bachelors,1,24,77,70,72,6.0,2,7,Urban,Software Engineer,92054,0 +92863,Male,46,Bachelors,7,90,32,82,61,2.0,7,72,Urban,Software Engineer,113234,1 +92864,Female,24,Masters,4,92,59,58,39,0.0,2,51,Urban,Data Analyst,115028,1 +92865,Male,38,High School,10,53,26,3,79,9.0,7,68,Urban,ML Engineer,27702,0 +92866,Male,52,Bachelors,8,40,70,97,35,6.0,7,99,Rural,Software Engineer,71504,1 +92867,Male,54,Bachelors,17,57,22,29,78,6.0,2,73,Urban,Software Engineer,40461,0 +92868,Female,36,Bachelors,3,67,98,5,82,8.0,6,16,Rural,Software Engineer,62800,0 +92869,Female,44,Bachelors,3,34,51,91,63,2.0,0,38,Urban,ML Engineer,81159,0 +92870,Male,23,High School,15,85,36,89,64,9.0,7,93,Semi-Urban,HR Executive,70510,1 +92871,Male,31,Diploma,0,23,16,27,71,9.0,4,83,Semi-Urban,Manager,90320,0 +92872,Female,48,Bachelors,7,72,32,81,66,0.0,0,31,Urban,Manager,144078,0 +92873,Male,41,Bachelors,19,57,47,6,29,8.0,2,31,Urban,Manager,27361,0 +92874,Male,46,Bachelors,2,70,20,1,34,5.0,2,18,Semi-Urban,Manager,79566,0 +92875,Male,44,High School,12,38,35,89,34,1.0,4,49,Rural,HR Executive,146284,0 +92876,Female,35,Bachelors,10,34,43,13,35,1.0,6,31,Semi-Urban,Data Analyst,147790,0 +92877,Female,22,PhD,8,86,43,10,37,4.0,4,3,Semi-Urban,Manager,92421,0 +92878,Male,24,Diploma,0,72,52,72,48,4.0,1,30,Urban,Manager,44682,0 +92879,Female,50,Bachelors,10,93,64,41,64,4.0,5,24,Urban,Software Engineer,23900,0 +92880,Male,38,Bachelors,15,9,28,92,60,3.0,0,72,Semi-Urban,Data Analyst,36935,0 +92881,Female,46,Bachelors,15,64,69,73,89,1.0,2,56,Rural,HR Executive,148884,1 +92882,Female,43,PhD,0,70,75,21,57,8.0,5,51,Urban,Manager,39136,0 +92883,Other,29,Bachelors,18,67,91,83,24,4.0,0,25,Urban,ML Engineer,27657,1 +92884,Male,44,Bachelors,13,22,10,76,45,5.0,4,87,Rural,ML Engineer,74712,0 +92885,Female,25,Diploma,9,25,3,61,48,5.0,2,0,Semi-Urban,Software Engineer,91296,0 +92886,Male,44,High School,7,0,50,48,54,5.0,1,33,Urban,Software Engineer,120081,0 +92887,Other,53,Bachelors,0,90,4,62,60,3.0,5,31,Rural,Manager,136036,0 +92888,Male,42,Bachelors,11,65,54,93,89,5.0,6,19,Urban,Data Analyst,117477,0 +92889,Female,22,Diploma,19,75,44,86,97,4.0,5,29,Urban,HR Executive,117190,0 +92890,Other,25,Masters,7,94,28,72,12,1.0,7,62,Urban,HR Executive,81869,1 +92891,Male,59,High School,12,51,98,0,25,6.0,2,97,Urban,Software Engineer,65512,1 +92892,Female,29,Bachelors,11,84,33,68,14,6.0,7,45,Semi-Urban,Data Analyst,108614,0 +92893,Other,27,Bachelors,6,21,14,85,3,6.0,1,72,Urban,Data Analyst,64561,0 +92894,Female,48,Masters,5,66,32,17,36,9.0,1,81,Semi-Urban,Manager,149327,0 +92895,Male,44,Bachelors,16,78,97,82,40,3.0,1,55,Rural,Software Engineer,116009,1 +92896,Male,42,Diploma,14,13,30,14,62,0.0,4,91,Urban,HR Executive,109503,0 +92897,Male,35,High School,4,64,92,10,67,4.0,2,33,Urban,Software Engineer,143939,0 +92898,Female,39,High School,11,39,52,41,44,9.0,5,6,Semi-Urban,Data Analyst,110601,0 +92899,Female,43,High School,0,70,94,0,92,3.0,4,72,Urban,Data Analyst,78532,0 +92900,Female,51,Bachelors,15,15,33,73,90,4.0,1,87,Urban,HR Executive,31394,0 +92901,Female,52,Bachelors,9,32,7,87,65,8.0,5,89,Urban,Software Engineer,75456,0 +92902,Male,58,Masters,15,68,58,24,15,1.0,1,96,Urban,Manager,26908,1 +92903,Male,32,Bachelors,10,68,29,37,6,9.0,7,2,Urban,ML Engineer,32815,0 +92904,Male,44,Bachelors,16,11,59,4,41,2.0,7,29,Rural,Software Engineer,59366,0 +92905,Female,30,Masters,15,57,20,35,63,6.0,1,20,Urban,Software Engineer,115058,0 +92906,Male,29,PhD,1,91,1,14,79,8.0,0,54,Urban,Manager,59999,0 +92907,Female,26,High School,17,93,2,61,24,4.0,4,21,Semi-Urban,Software Engineer,36514,0 +92908,Female,35,Diploma,5,85,95,8,0,1.0,6,48,Rural,Data Analyst,35336,0 +92909,Female,40,Bachelors,16,80,33,78,34,6.0,5,9,Urban,Manager,131736,0 +92910,Female,59,Bachelors,3,51,49,15,55,8.0,7,28,Semi-Urban,HR Executive,83768,0 +92911,Male,56,High School,12,88,14,28,98,3.0,6,29,Urban,Software Engineer,106003,0 +92912,Female,49,Bachelors,10,79,88,53,51,2.0,3,74,Urban,ML Engineer,44075,1 +92913,Female,44,PhD,12,80,93,24,87,5.0,5,44,Urban,Software Engineer,55330,1 +92914,Male,32,Bachelors,9,30,94,77,61,8.0,1,89,Rural,Software Engineer,22356,1 +92915,Female,52,High School,13,50,75,67,64,9.0,3,71,Urban,Manager,49633,1 +92916,Female,32,High School,10,69,61,23,5,2.0,6,2,Urban,Manager,117130,0 +92917,Male,56,Diploma,5,71,90,38,63,7.0,7,38,Rural,Software Engineer,102336,1 +92918,Male,45,Bachelors,9,10,99,47,19,6.0,0,82,Rural,Software Engineer,37578,1 +92919,Male,51,Bachelors,7,69,41,84,13,5.0,5,33,Urban,Software Engineer,66116,0 +92920,Male,38,Masters,8,38,26,73,6,0.0,6,48,Urban,HR Executive,66630,0 +92921,Male,43,Bachelors,16,10,58,82,63,4.0,4,25,Urban,Software Engineer,38210,0 +92922,Male,47,Masters,9,14,19,41,88,9.0,2,77,Urban,Manager,84669,0 +92923,Male,24,High School,9,37,24,35,14,6.0,7,89,Rural,Data Analyst,25368,0 +92924,Female,52,Bachelors,19,9,42,36,57,1.0,7,10,Rural,Data Analyst,121541,0 +92925,Male,36,High School,17,93,46,4,26,3.0,6,67,Urban,Manager,133975,0 +92926,Female,51,Diploma,15,99,32,65,47,2.0,1,31,Urban,ML Engineer,75473,0 +92927,Female,29,Bachelors,18,63,46,3,94,8.0,6,93,Urban,ML Engineer,96970,0 +92928,Female,29,Masters,14,25,24,34,56,4.0,7,62,Semi-Urban,Manager,71092,0 +92929,Male,26,Bachelors,5,46,81,63,11,3.0,7,81,Rural,HR Executive,95785,1 +92930,Female,31,Masters,17,0,74,31,13,7.0,6,54,Urban,ML Engineer,133337,0 +92931,Other,23,Diploma,2,67,52,48,16,2.0,6,27,Urban,HR Executive,67491,0 +92932,Female,42,Masters,10,46,29,65,46,3.0,7,32,Urban,HR Executive,122370,0 +92933,Female,40,Bachelors,9,23,87,9,38,5.0,6,33,Urban,Manager,32047,0 +92934,Male,41,PhD,0,75,41,57,62,1.0,5,59,Urban,Data Analyst,37729,0 +92935,Male,23,High School,4,63,79,34,87,7.0,3,99,Urban,Data Analyst,147980,1 +92936,Male,21,High School,7,13,40,98,60,6.0,7,22,Urban,HR Executive,106457,0 +92937,Male,57,Bachelors,1,95,84,36,91,8.0,0,7,Urban,Data Analyst,24869,0 +92938,Male,42,High School,5,12,66,75,16,9.0,6,81,Rural,HR Executive,54236,0 +92939,Male,21,Diploma,17,26,53,62,46,7.0,1,6,Urban,HR Executive,91185,0 +92940,Female,51,Masters,16,10,22,87,25,2.0,5,8,Semi-Urban,Manager,62270,0 +92941,Female,37,Bachelors,3,91,34,83,41,4.0,0,47,Urban,ML Engineer,104330,1 +92942,Female,53,High School,19,47,52,69,57,3.0,3,65,Semi-Urban,ML Engineer,91517,0 +92943,Female,44,Bachelors,15,31,27,14,29,1.0,7,59,Semi-Urban,Software Engineer,72479,0 +92944,Female,35,Masters,14,83,12,40,51,5.0,3,59,Urban,Manager,75672,0 +92945,Male,34,Bachelors,6,71,48,60,33,1.0,2,47,Urban,Software Engineer,126187,0 +92946,Female,59,Bachelors,10,91,92,9,14,8.0,6,86,Urban,Software Engineer,121350,1 +92947,Female,23,Bachelors,7,27,23,28,44,0.0,7,67,Urban,Data Analyst,27566,0 +92948,Female,55,PhD,0,26,4,86,10,4.0,5,68,Urban,Data Analyst,82328,0 +92949,Female,30,Bachelors,16,27,46,18,38,0.0,0,22,Urban,Software Engineer,65586,0 +92950,Female,54,Bachelors,19,38,12,80,69,5.0,0,20,Semi-Urban,HR Executive,128581,0 +92951,Male,48,Bachelors,13,1,80,64,82,9.0,2,25,Urban,HR Executive,101883,0 +92952,Male,31,Bachelors,0,48,94,54,56,5.0,0,91,Urban,Data Analyst,130950,1 +92953,Female,27,Bachelors,1,81,79,87,80,0.0,2,92,Semi-Urban,HR Executive,145322,1 +92954,Male,52,Bachelors,3,84,35,60,15,3.0,3,8,Urban,ML Engineer,40909,0 +92955,Female,24,Masters,9,89,35,45,10,7.0,2,27,Urban,HR Executive,136708,0 +92956,Female,56,PhD,15,22,97,74,40,4.0,1,25,Rural,HR Executive,107548,0 +92957,Female,43,Bachelors,13,82,26,1,92,5.0,7,41,Urban,Data Analyst,118269,0 +92958,Female,48,High School,14,77,92,70,62,3.0,4,24,Semi-Urban,Manager,76631,1 +92959,Female,39,Bachelors,1,32,5,91,34,8.0,7,24,Semi-Urban,Manager,59924,0 +92960,Female,47,Masters,10,7,39,47,11,3.0,6,12,Urban,HR Executive,52468,0 +92961,Female,25,Masters,13,40,18,72,33,9.0,5,61,Urban,ML Engineer,65110,0 +92962,Male,37,Masters,1,32,72,19,80,9.0,2,99,Urban,Data Analyst,45146,0 +92963,Male,30,PhD,6,38,64,16,61,2.0,5,86,Urban,HR Executive,123555,0 +92964,Male,36,Masters,11,5,35,89,97,1.0,5,58,Urban,Data Analyst,63656,0 +92965,Female,45,Bachelors,13,20,39,76,5,2.0,1,23,Semi-Urban,ML Engineer,139091,0 +92966,Male,41,Masters,1,43,61,86,75,1.0,0,2,Urban,Manager,44744,0 +92967,Male,23,Bachelors,6,63,2,36,86,9.0,3,11,Urban,Software Engineer,120544,0 +92968,Male,49,Diploma,16,77,35,60,52,6.0,6,41,Urban,HR Executive,80925,0 +92969,Male,59,Bachelors,9,3,4,27,91,0.0,1,1,Semi-Urban,ML Engineer,66878,0 +92970,Other,45,High School,16,3,6,2,45,1.0,3,20,Urban,Software Engineer,112311,0 +92971,Female,29,Bachelors,1,98,81,66,71,8.0,3,93,Urban,ML Engineer,73367,1 +92972,Male,23,Bachelors,13,20,4,96,6,0.0,2,76,Rural,ML Engineer,121722,0 +92973,Female,37,Bachelors,4,93,45,46,13,2.0,2,4,Urban,Data Analyst,125040,0 +92974,Male,41,Bachelors,15,24,90,43,58,1.0,2,96,Semi-Urban,HR Executive,34925,1 +92975,Female,44,Bachelors,19,0,52,24,6,7.0,3,80,Urban,HR Executive,37822,0 +92976,Female,23,High School,18,71,68,16,32,7.0,3,89,Rural,Software Engineer,102608,1 +92977,Male,43,Masters,0,81,81,2,90,8.0,5,21,Semi-Urban,Software Engineer,43519,0 +92978,Female,24,Masters,7,93,78,77,60,2.0,4,36,Urban,Software Engineer,119982,1 +92979,Female,36,High School,6,18,88,79,85,7.0,7,43,Semi-Urban,HR Executive,35531,0 +92980,Male,55,High School,4,94,39,80,25,0.0,4,71,Urban,Manager,66256,1 +92981,Male,59,Bachelors,18,75,47,36,22,7.0,2,56,Semi-Urban,Data Analyst,127922,0 +92982,Male,58,Masters,6,71,49,93,81,3.0,6,31,Urban,Manager,102795,1 +92983,Female,23,Masters,11,26,6,13,21,8.0,4,32,Urban,HR Executive,47725,0 +92984,Female,51,Bachelors,12,50,17,84,96,7.0,2,43,Urban,Data Analyst,29109,0 +92985,Other,37,Masters,11,83,78,84,84,2.0,3,99,Semi-Urban,Software Engineer,147747,1 +92986,Female,32,Diploma,12,20,32,2,21,4.0,3,39,Semi-Urban,Data Analyst,124517,0 +92987,Male,32,Masters,3,10,40,29,54,5.0,2,40,Semi-Urban,Data Analyst,114165,0 +92988,Male,50,Masters,13,17,91,35,24,8.0,2,60,Semi-Urban,Data Analyst,34112,0 +92989,Female,58,Bachelors,2,69,37,10,29,7.0,4,45,Semi-Urban,Manager,113687,0 +92990,Male,42,Masters,5,1,3,83,3,7.0,2,55,Urban,Software Engineer,70197,0 +92991,Female,40,Bachelors,1,23,95,30,72,0.0,4,93,Urban,Software Engineer,95356,1 +92992,Male,43,Bachelors,9,28,98,34,93,0.0,3,1,Urban,ML Engineer,89783,0 +92993,Male,31,Masters,4,4,63,5,84,9.0,0,25,Semi-Urban,HR Executive,133146,0 +92994,Female,46,PhD,19,3,22,69,67,0.0,1,44,Urban,ML Engineer,45082,0 +92995,Female,34,Diploma,4,45,80,21,82,7.0,0,54,Rural,Software Engineer,37554,0 +92996,Male,38,Bachelors,12,51,83,26,22,7.0,5,11,Urban,HR Executive,139914,0 +92997,Male,52,Bachelors,5,62,70,24,90,8.0,1,27,Urban,Software Engineer,140021,0 +92998,Other,45,Diploma,1,90,31,98,6,2.0,4,81,Urban,Software Engineer,140801,1 +92999,Male,50,Masters,3,44,99,38,3,7.0,3,2,Urban,ML Engineer,60873,0 +93000,Female,25,Bachelors,7,24,50,32,98,8.0,4,97,Semi-Urban,HR Executive,83064,0 +93001,Male,40,High School,16,97,99,58,11,3.0,2,94,Urban,ML Engineer,32507,1 +93002,Male,37,Bachelors,3,29,94,54,22,9.0,0,21,Rural,ML Engineer,31534,0 +93003,Male,52,Bachelors,1,38,11,42,92,1.0,2,76,Semi-Urban,ML Engineer,149513,0 +93004,Female,24,Bachelors,17,31,78,93,80,6.0,1,43,Semi-Urban,Manager,43032,1 +93005,Female,53,Masters,12,44,71,61,36,0.0,1,68,Urban,HR Executive,95613,1 +93006,Male,55,High School,10,8,25,29,84,0.0,1,12,Semi-Urban,Software Engineer,74164,0 +93007,Male,21,Bachelors,13,73,6,67,5,1.0,6,33,Urban,Manager,83062,0 +93008,Female,30,Diploma,18,42,64,64,98,2.0,6,90,Urban,Software Engineer,34265,1 +93009,Male,50,High School,10,56,91,33,32,1.0,3,32,Urban,ML Engineer,103893,0 +93010,Female,53,Bachelors,13,97,49,44,91,6.0,2,81,Urban,Software Engineer,80705,1 +93011,Male,58,Bachelors,6,4,20,28,27,5.0,1,59,Urban,HR Executive,51433,0 +93012,Male,36,Diploma,4,99,96,77,92,3.0,6,80,Urban,HR Executive,87031,1 +93013,Male,27,PhD,18,40,32,69,40,6.0,6,12,Semi-Urban,ML Engineer,53466,0 +93014,Male,23,Masters,15,98,93,27,48,8.0,1,6,Urban,Data Analyst,55910,0 +93015,Male,37,Masters,11,18,17,44,27,8.0,0,92,Urban,Data Analyst,76067,0 +93016,Female,51,High School,11,78,94,70,94,0.0,5,72,Semi-Urban,Software Engineer,60951,1 +93017,Female,28,Bachelors,19,53,4,37,92,5.0,1,72,Semi-Urban,ML Engineer,89413,0 +93018,Male,54,High School,5,73,68,86,30,3.0,1,65,Urban,Manager,122130,1 +93019,Male,23,High School,9,25,82,32,63,9.0,5,66,Urban,ML Engineer,105347,0 +93020,Male,22,Diploma,19,71,8,13,43,5.0,5,48,Urban,Data Analyst,104319,0 +93021,Male,21,Bachelors,5,23,85,36,79,7.0,2,90,Urban,Manager,28589,0 +93022,Male,35,High School,12,79,30,85,42,2.0,2,87,Urban,HR Executive,37046,1 +93023,Male,40,Bachelors,7,95,71,37,49,4.0,0,12,Urban,ML Engineer,124379,0 +93024,Male,41,Masters,6,45,30,33,1,7.0,6,75,Semi-Urban,Software Engineer,28934,0 +93025,Female,36,PhD,18,81,9,44,63,6.0,3,7,Urban,Software Engineer,65223,0 +93026,Male,39,Bachelors,9,85,43,83,84,0.0,0,78,Urban,Data Analyst,123284,1 +93027,Female,44,High School,5,38,50,81,41,2.0,3,71,Rural,Software Engineer,42740,0 +93028,Other,41,High School,19,83,96,37,19,6.0,5,93,Urban,Data Analyst,86603,1 +93029,Female,21,Diploma,7,44,84,92,15,2.0,7,88,Semi-Urban,HR Executive,128582,1 +93030,Male,45,Bachelors,5,81,7,19,56,9.0,6,78,Rural,ML Engineer,93591,0 +93031,Male,38,Masters,7,35,60,54,36,5.0,7,84,Rural,Data Analyst,64346,0 +93032,Male,23,PhD,15,75,2,44,88,5.0,5,70,Semi-Urban,Software Engineer,24218,0 +93033,Male,23,Bachelors,0,55,91,79,95,3.0,0,96,Semi-Urban,HR Executive,138840,1 +93034,Male,25,Bachelors,15,12,99,63,1,5.0,3,85,Rural,ML Engineer,51063,1 +93035,Male,23,Diploma,2,23,46,12,15,0.0,4,50,Rural,Data Analyst,119199,0 +93036,Male,47,Bachelors,12,98,90,20,36,2.0,4,35,Urban,Software Engineer,120813,1 +93037,Female,21,Masters,6,7,60,63,48,5.0,7,17,Urban,ML Engineer,104315,0 +93038,Male,29,Diploma,19,98,34,86,32,3.0,5,26,Rural,Software Engineer,104157,1 +93039,Male,32,Bachelors,0,37,87,25,10,4.0,2,92,Semi-Urban,ML Engineer,124026,1 +93040,Male,24,Bachelors,1,32,53,37,99,0.0,6,66,Urban,Data Analyst,49297,0 +93041,Female,51,Masters,13,9,13,32,16,4.0,6,69,Semi-Urban,HR Executive,133080,0 +93042,Female,38,Bachelors,2,36,88,58,83,3.0,3,42,Semi-Urban,Software Engineer,144697,0 +93043,Male,52,Bachelors,10,88,77,74,27,8.0,3,28,Semi-Urban,ML Engineer,110368,1 +93044,Female,23,High School,7,15,75,58,48,6.0,4,51,Urban,HR Executive,147931,0 +93045,Male,24,High School,11,81,30,98,7,2.0,0,84,Urban,Software Engineer,79760,1 +93046,Male,45,Bachelors,3,43,1,9,44,2.0,5,93,Semi-Urban,Software Engineer,55729,0 +93047,Male,45,Diploma,11,43,27,21,16,2.0,6,94,Urban,ML Engineer,34156,0 +93048,Female,34,Bachelors,2,6,63,49,83,4.0,7,32,Semi-Urban,Data Analyst,85292,0 +93049,Female,41,Masters,1,72,5,68,7,3.0,2,47,Urban,Data Analyst,110541,0 +93050,Male,31,Bachelors,3,10,10,37,65,4.0,3,31,Rural,Software Engineer,64623,0 +93051,Female,41,Masters,3,20,16,46,62,0.0,2,30,Urban,Data Analyst,59956,0 +93052,Male,24,Diploma,4,31,66,22,99,7.0,7,57,Urban,Data Analyst,55225,0 +93053,Male,43,Masters,18,77,83,23,18,4.0,7,26,Rural,ML Engineer,49026,0 +93054,Male,28,Masters,6,5,66,23,37,7.0,6,19,Urban,Data Analyst,42208,0 +93055,Female,22,PhD,19,86,53,65,21,2.0,5,24,Rural,Software Engineer,107908,0 +93056,Male,46,Bachelors,0,38,31,86,61,1.0,2,13,Rural,Software Engineer,140083,0 +93057,Female,30,High School,2,91,85,66,22,0.0,4,15,Rural,Manager,123398,1 +93058,Male,27,Masters,9,40,46,84,8,8.0,3,28,Semi-Urban,Data Analyst,93026,0 +93059,Male,22,High School,11,25,79,81,69,7.0,1,1,Rural,HR Executive,90312,0 +93060,Male,48,PhD,13,61,70,44,6,1.0,3,72,Rural,HR Executive,30280,1 +93061,Male,54,Bachelors,18,17,90,69,85,5.0,0,65,Rural,ML Engineer,110078,1 +93062,Female,40,Masters,14,14,72,32,85,5.0,5,9,Urban,ML Engineer,143998,0 +93063,Female,35,Masters,17,79,17,99,11,9.0,7,72,Semi-Urban,Software Engineer,22274,1 +93064,Male,49,Bachelors,1,67,90,35,28,7.0,6,47,Semi-Urban,Software Engineer,82533,1 +93065,Female,46,Bachelors,15,15,12,19,48,4.0,7,6,Rural,Manager,79380,0 +93066,Male,51,Bachelors,3,48,8,34,14,9.0,1,13,Urban,ML Engineer,80027,0 +93067,Male,45,Bachelors,4,42,47,45,94,9.0,7,57,Rural,Software Engineer,134294,0 +93068,Female,54,Bachelors,15,37,74,39,54,7.0,0,69,Semi-Urban,ML Engineer,121252,0 +93069,Female,30,High School,13,89,2,39,89,9.0,3,12,Urban,Data Analyst,87456,0 +93070,Male,31,Bachelors,9,58,25,76,40,8.0,4,88,Urban,HR Executive,27903,1 +93071,Male,30,Diploma,1,69,24,0,78,0.0,7,17,Urban,HR Executive,148131,0 +93072,Male,24,Bachelors,12,87,33,71,64,4.0,5,30,Rural,Data Analyst,112398,0 +93073,Male,52,Bachelors,18,99,2,16,22,8.0,2,59,Urban,Data Analyst,70157,0 +93074,Female,24,Bachelors,9,5,88,49,75,0.0,5,8,Urban,Software Engineer,79007,0 +93075,Female,25,Diploma,5,41,12,27,53,0.0,2,47,Urban,Data Analyst,76948,0 +93076,Female,37,Diploma,4,8,16,77,9,8.0,2,51,Urban,ML Engineer,143654,0 +93077,Male,48,Bachelors,19,84,62,77,19,4.0,2,80,Urban,ML Engineer,69389,1 +93078,Male,28,Diploma,1,65,7,79,63,0.0,3,60,Urban,HR Executive,78450,0 +93079,Male,58,Masters,17,73,46,96,60,7.0,1,46,Semi-Urban,Manager,80153,1 +93080,Male,23,High School,18,32,64,59,56,0.0,1,64,Urban,HR Executive,127384,0 +93081,Male,40,Masters,19,76,17,39,93,1.0,7,39,Semi-Urban,Manager,52388,0 +93082,Male,55,Bachelors,7,55,69,62,0,7.0,7,73,Urban,Data Analyst,72714,1 +93083,Male,55,Masters,2,17,86,72,4,5.0,7,66,Semi-Urban,Data Analyst,23039,1 +93084,Female,31,Masters,2,61,93,51,23,7.0,2,74,Urban,Data Analyst,84946,1 +93085,Female,23,Bachelors,7,42,86,98,11,5.0,1,5,Urban,Data Analyst,59799,0 +93086,Female,24,Bachelors,11,32,83,37,86,7.0,0,30,Urban,HR Executive,91898,0 +93087,Female,26,PhD,1,91,24,42,40,1.0,4,17,Urban,Software Engineer,41274,0 +93088,Female,43,Diploma,8,1,95,83,73,8.0,1,43,Semi-Urban,HR Executive,75240,0 +93089,Male,53,High School,13,14,23,66,89,8.0,5,54,Urban,ML Engineer,122057,0 +93090,Male,54,Bachelors,17,87,24,24,37,5.0,2,98,Urban,Software Engineer,96140,0 +93091,Male,54,Masters,15,1,75,42,72,9.0,3,82,Urban,Data Analyst,117256,0 +93092,Female,48,Diploma,15,8,46,94,76,8.0,1,7,Rural,Data Analyst,137083,0 +93093,Female,37,Diploma,19,15,37,2,71,9.0,4,76,Urban,Software Engineer,121654,0 +93094,Female,49,Masters,13,73,66,87,96,7.0,5,65,Urban,HR Executive,103287,1 +93095,Female,39,Bachelors,5,80,42,72,50,4.0,3,27,Semi-Urban,ML Engineer,50468,0 +93096,Female,59,Bachelors,16,62,43,36,32,0.0,5,24,Urban,Data Analyst,135471,0 +93097,Male,38,Diploma,1,99,12,29,23,2.0,2,21,Urban,HR Executive,94602,0 +93098,Male,51,Diploma,0,7,40,11,68,7.0,7,81,Urban,Manager,141970,0 +93099,Female,27,Bachelors,15,12,46,32,64,8.0,4,12,Rural,HR Executive,57303,0 +93100,Other,38,Bachelors,15,82,84,33,3,8.0,4,80,Urban,Data Analyst,48735,1 +93101,Female,55,High School,5,90,95,89,64,4.0,4,2,Urban,HR Executive,119812,1 +93102,Other,58,Bachelors,11,29,52,43,72,7.0,7,14,Semi-Urban,Manager,49964,0 +93103,Male,53,Diploma,10,34,49,97,17,9.0,6,49,Rural,Manager,77719,0 +93104,Male,21,High School,0,28,74,46,85,6.0,3,54,Urban,Data Analyst,106419,0 +93105,Male,29,Bachelors,14,60,11,48,60,4.0,5,88,Urban,Software Engineer,103027,0 +93106,Male,59,Bachelors,7,30,26,31,95,2.0,5,14,Semi-Urban,Data Analyst,57410,0 +93107,Male,48,Diploma,2,31,55,51,37,1.0,1,66,Urban,HR Executive,107372,0 +93108,Female,40,High School,7,92,96,12,96,0.0,4,88,Urban,Data Analyst,119783,1 +93109,Female,57,Bachelors,18,96,13,25,55,2.0,6,26,Urban,Data Analyst,135230,0 +93110,Male,59,Bachelors,17,14,98,67,53,1.0,3,31,Rural,Software Engineer,53866,0 +93111,Male,56,Bachelors,9,89,40,40,3,5.0,5,2,Urban,Manager,103187,0 +93112,Female,52,Diploma,6,26,1,11,44,2.0,3,73,Rural,HR Executive,126531,0 +93113,Female,35,Masters,16,3,82,77,62,5.0,4,95,Urban,HR Executive,119236,1 +93114,Male,58,Masters,7,36,4,62,10,0.0,3,30,Urban,Manager,83021,0 +93115,Male,25,Masters,1,63,27,81,86,4.0,5,91,Semi-Urban,Software Engineer,72880,1 +93116,Male,48,Bachelors,12,37,57,37,61,5.0,1,36,Urban,ML Engineer,115563,0 +93117,Male,54,High School,19,17,49,9,97,1.0,7,25,Urban,HR Executive,87163,0 +93118,Female,25,Bachelors,17,65,43,83,81,9.0,6,50,Rural,Manager,99590,1 +93119,Female,24,Bachelors,13,23,66,99,81,3.0,1,7,Urban,Manager,35980,0 +93120,Female,37,Bachelors,13,51,23,46,71,3.0,2,52,Semi-Urban,Software Engineer,61501,0 +93121,Female,40,Diploma,15,50,55,59,81,8.0,4,8,Urban,Data Analyst,100080,0 +93122,Male,27,Diploma,2,3,28,10,63,1.0,6,21,Urban,HR Executive,106974,0 +93123,Male,39,Bachelors,17,97,10,81,40,3.0,7,51,Semi-Urban,HR Executive,82968,1 +93124,Male,31,Bachelors,1,54,74,0,19,0.0,7,65,Rural,ML Engineer,107186,0 +93125,Male,54,Bachelors,3,55,47,15,24,6.0,3,67,Urban,Manager,86459,0 +93126,Male,49,Bachelors,1,56,96,94,45,2.0,1,32,Urban,ML Engineer,90402,1 +93127,Male,32,Bachelors,8,71,98,32,59,5.0,6,35,Urban,Software Engineer,32870,1 +93128,Female,43,High School,7,79,17,51,84,1.0,6,64,Urban,ML Engineer,80009,0 +93129,Male,38,High School,13,3,36,16,72,0.0,7,99,Urban,Data Analyst,34343,0 +93130,Male,28,Diploma,6,20,81,87,45,5.0,1,61,Urban,ML Engineer,114974,1 +93131,Male,36,Masters,0,26,35,84,7,9.0,6,50,Semi-Urban,Software Engineer,75270,0 +93132,Male,53,High School,6,52,91,99,18,0.0,1,94,Urban,HR Executive,104717,1 +93133,Male,58,Bachelors,5,14,84,47,68,6.0,5,41,Semi-Urban,Data Analyst,20996,0 +93134,Male,35,Diploma,12,41,25,64,60,0.0,0,49,Urban,HR Executive,104612,0 +93135,Male,21,Masters,1,91,48,15,4,4.0,3,23,Semi-Urban,Software Engineer,76841,0 +93136,Female,32,Bachelors,2,44,36,96,81,1.0,2,14,Urban,HR Executive,148033,0 +93137,Male,42,Bachelors,17,99,30,70,73,2.0,5,41,Semi-Urban,Manager,28189,1 +93138,Other,22,High School,3,96,67,86,14,6.0,1,32,Urban,HR Executive,137392,1 +93139,Male,46,Diploma,9,48,5,52,86,8.0,5,91,Semi-Urban,ML Engineer,135388,0 +93140,Male,21,Masters,12,77,95,70,96,1.0,4,46,Urban,ML Engineer,118973,1 +93141,Female,25,Bachelors,19,78,27,38,3,4.0,6,23,Urban,Software Engineer,96576,0 +93142,Male,39,Diploma,15,94,42,42,43,7.0,4,34,Urban,HR Executive,76619,0 +93143,Male,54,Bachelors,3,26,0,17,2,9.0,5,34,Urban,ML Engineer,20010,0 +93144,Male,33,Bachelors,19,54,99,45,10,3.0,3,58,Rural,HR Executive,78754,1 +93145,Male,40,Masters,5,29,66,7,19,0.0,3,82,Urban,Software Engineer,123606,0 +93146,Male,38,Bachelors,16,71,28,64,72,4.0,3,98,Rural,Data Analyst,106337,1 +93147,Female,26,Diploma,10,57,71,77,99,5.0,5,98,Urban,Manager,119955,1 +93148,Male,38,Bachelors,4,44,24,61,48,7.0,5,44,Urban,HR Executive,50183,0 +93149,Male,26,Masters,18,83,83,95,42,3.0,0,52,Semi-Urban,HR Executive,67697,1 +93150,Female,27,Bachelors,4,85,27,78,34,4.0,4,2,Rural,Manager,120601,0 +93151,Male,56,Bachelors,8,22,67,13,49,4.0,6,3,Urban,Data Analyst,116843,0 +93152,Female,33,Bachelors,9,67,64,85,79,0.0,2,67,Urban,ML Engineer,135618,1 +93153,Female,51,Bachelors,10,21,67,75,40,8.0,0,10,Semi-Urban,Manager,26173,0 +93154,Female,39,Diploma,4,22,57,80,57,8.0,7,60,Semi-Urban,HR Executive,58339,0 +93155,Male,38,Bachelors,18,17,69,9,43,3.0,3,84,Urban,Manager,30415,0 +93156,Male,46,Masters,2,27,20,4,77,7.0,2,88,Semi-Urban,ML Engineer,75734,0 +93157,Male,43,Bachelors,2,0,18,4,71,4.0,2,98,Urban,Software Engineer,95351,0 +93158,Female,41,Diploma,13,4,95,79,71,9.0,0,69,Rural,Data Analyst,105064,1 +93159,Male,31,Diploma,5,50,38,31,21,5.0,7,31,Urban,HR Executive,143206,0 +93160,Male,35,High School,8,39,9,68,19,4.0,0,90,Urban,Manager,84257,0 +93161,Female,24,Masters,14,32,96,73,23,0.0,7,55,Urban,ML Engineer,26778,1 +93162,Other,58,Bachelors,0,32,17,27,21,4.0,6,2,Semi-Urban,Manager,33772,0 +93163,Male,48,Bachelors,14,82,49,28,20,2.0,3,28,Rural,Data Analyst,126174,0 +93164,Male,44,Bachelors,0,97,42,19,2,0.0,5,67,Urban,ML Engineer,82986,0 +93165,Male,55,Bachelors,3,28,17,46,81,4.0,7,43,Rural,Software Engineer,57260,0 +93166,Male,39,Bachelors,10,86,97,92,65,8.0,4,62,Urban,ML Engineer,40349,1 +93167,Other,27,Diploma,6,54,12,46,60,8.0,7,0,Semi-Urban,HR Executive,53744,0 +93168,Male,49,High School,16,23,27,60,79,3.0,7,19,Semi-Urban,Data Analyst,39901,0 +93169,Female,50,Bachelors,17,33,54,79,38,4.0,3,93,Semi-Urban,ML Engineer,83829,1 +93170,Male,30,High School,3,17,24,1,36,0.0,7,99,Urban,Manager,69555,0 +93171,Male,55,Diploma,16,14,38,7,13,6.0,5,23,Urban,Data Analyst,113220,0 +93172,Male,27,Masters,18,37,50,93,50,7.0,3,71,Semi-Urban,Manager,30343,1 +93173,Male,57,Bachelors,17,97,47,28,25,4.0,0,87,Semi-Urban,Data Analyst,119695,1 +93174,Male,34,Bachelors,0,50,19,78,17,1.0,4,60,Urban,Manager,48438,0 +93175,Male,46,Bachelors,5,26,73,59,91,2.0,1,45,Semi-Urban,ML Engineer,118794,0 +93176,Female,57,Diploma,7,11,93,93,53,6.0,5,86,Rural,Manager,148457,1 +93177,Male,38,Bachelors,14,30,83,65,7,9.0,0,58,Semi-Urban,Data Analyst,135551,1 +93178,Male,42,Masters,9,99,28,58,51,4.0,0,5,Semi-Urban,HR Executive,35762,0 +93179,Male,22,Bachelors,4,16,84,61,85,3.0,0,68,Urban,Manager,86401,0 +93180,Female,21,Bachelors,12,95,12,31,25,5.0,5,24,Urban,Data Analyst,81235,0 +93181,Male,49,Masters,16,12,69,7,43,2.0,4,20,Urban,Data Analyst,84370,0 +93182,Male,26,High School,17,5,25,3,51,2.0,6,75,Rural,Manager,31857,0 +93183,Male,31,Bachelors,3,35,1,81,47,0.0,2,78,Urban,Manager,87024,0 +93184,Male,26,Bachelors,12,13,66,82,85,5.0,1,22,Urban,HR Executive,97315,0 +93185,Male,23,Bachelors,4,57,66,1,64,0.0,3,98,Semi-Urban,ML Engineer,73610,0 +93186,Female,51,Diploma,4,26,38,86,54,0.0,0,39,Rural,ML Engineer,87271,0 +93187,Male,35,Diploma,13,40,95,49,54,2.0,3,68,Urban,Software Engineer,58008,1 +93188,Male,39,Diploma,2,13,28,62,52,0.0,7,93,Urban,HR Executive,98749,0 +93189,Female,45,Diploma,17,29,90,88,44,0.0,2,24,Semi-Urban,Manager,72566,0 +93190,Male,53,Bachelors,19,4,98,46,79,9.0,1,75,Urban,HR Executive,83352,0 +93191,Male,47,Masters,0,18,81,9,97,3.0,4,14,Rural,ML Engineer,41174,0 +93192,Male,48,Masters,16,49,15,4,71,0.0,1,78,Semi-Urban,HR Executive,94114,0 +93193,Other,50,Diploma,0,37,91,78,1,0.0,5,88,Urban,Manager,143791,1 +93194,Female,54,Masters,0,60,78,81,60,4.0,4,82,Urban,HR Executive,25701,1 +93195,Female,45,Diploma,16,76,67,12,53,8.0,7,76,Urban,Software Engineer,64663,0 +93196,Male,50,PhD,14,3,78,68,22,8.0,5,53,Semi-Urban,ML Engineer,120327,0 +93197,Male,33,Bachelors,7,55,37,31,40,8.0,3,84,Urban,Manager,25502,0 +93198,Female,29,Bachelors,19,67,99,50,34,6.0,2,16,Urban,Software Engineer,145398,0 +93199,Male,55,Masters,12,97,61,40,1,7.0,4,49,Urban,ML Engineer,49747,1 +93200,Female,45,Bachelors,14,88,72,18,98,6.0,2,8,Rural,ML Engineer,107144,0 +93201,Female,36,Bachelors,13,43,54,40,6,7.0,3,13,Urban,Software Engineer,44903,0 +93202,Male,34,High School,9,20,70,6,48,5.0,3,81,Rural,HR Executive,111548,0 +93203,Female,47,Masters,6,85,80,41,10,6.0,5,5,Urban,Manager,138044,0 +93204,Male,59,Masters,5,56,27,13,29,2.0,3,69,Urban,ML Engineer,66258,0 +93205,Female,23,Bachelors,12,23,41,19,2,3.0,5,54,Urban,Manager,100775,0 +93206,Male,23,High School,0,94,25,45,9,8.0,1,61,Urban,HR Executive,80868,0 +93207,Female,37,Masters,5,49,40,45,83,2.0,1,39,Urban,ML Engineer,20139,0 +93208,Male,44,High School,4,44,57,56,96,2.0,5,93,Urban,ML Engineer,128904,1 +93209,Male,56,PhD,4,75,92,84,36,1.0,4,49,Semi-Urban,Data Analyst,119154,1 +93210,Male,27,Bachelors,5,76,57,94,31,3.0,3,92,Urban,Software Engineer,77744,1 +93211,Male,37,PhD,4,82,10,96,81,3.0,0,67,Urban,ML Engineer,37905,1 +93212,Female,33,High School,13,29,61,50,95,3.0,2,7,Rural,Data Analyst,58460,0 +93213,Male,34,Diploma,2,48,38,80,42,7.0,3,24,Urban,Software Engineer,120300,0 +93214,Female,25,High School,10,4,27,73,85,4.0,0,26,Semi-Urban,Data Analyst,29834,0 +93215,Female,24,Masters,9,15,1,33,19,8.0,3,42,Urban,ML Engineer,29012,0 +93216,Male,30,Masters,17,35,22,66,68,4.0,2,93,Rural,Data Analyst,140294,0 +93217,Male,30,Masters,15,26,69,46,12,5.0,3,17,Rural,Software Engineer,81018,0 +93218,Female,59,Bachelors,17,47,40,18,78,8.0,1,16,Urban,Software Engineer,79181,0 +93219,Male,53,Bachelors,14,9,50,77,36,0.0,6,91,Rural,ML Engineer,85977,0 +93220,Male,30,Diploma,0,37,66,34,52,1.0,5,80,Semi-Urban,Data Analyst,106232,0 +93221,Female,52,Diploma,0,13,25,97,63,8.0,2,35,Urban,Software Engineer,76544,0 +93222,Other,41,Bachelors,6,44,49,98,45,3.0,7,82,Semi-Urban,HR Executive,41777,1 +93223,Female,39,Masters,19,70,48,58,53,5.0,5,16,Urban,HR Executive,144037,0 +93224,Female,37,Bachelors,14,3,38,82,83,9.0,1,74,Semi-Urban,Manager,63300,0 +93225,Female,41,High School,10,85,82,49,79,1.0,4,29,Urban,Data Analyst,70806,1 +93226,Female,53,PhD,6,66,47,97,54,8.0,6,36,Semi-Urban,Manager,147031,1 +93227,Male,30,Masters,15,10,7,39,46,9.0,5,72,Urban,Manager,41715,0 +93228,Female,56,Bachelors,14,22,5,65,58,4.0,6,32,Rural,Software Engineer,134097,0 +93229,Male,37,PhD,5,43,96,19,34,5.0,5,36,Semi-Urban,ML Engineer,124289,0 +93230,Other,53,Masters,15,92,0,97,2,5.0,2,11,Semi-Urban,Data Analyst,37050,0 +93231,Male,50,High School,15,71,45,90,13,5.0,2,10,Urban,Data Analyst,26564,0 +93232,Male,46,Masters,6,23,96,0,9,8.0,0,51,Semi-Urban,Data Analyst,123130,0 +93233,Male,55,Masters,9,6,57,3,8,2.0,6,46,Urban,ML Engineer,81855,0 +93234,Female,48,Masters,5,68,78,70,78,3.0,4,14,Rural,ML Engineer,49025,0 +93235,Female,42,Diploma,11,42,33,27,2,1.0,0,88,Urban,HR Executive,138117,0 +93236,Female,49,Masters,17,17,96,83,29,1.0,4,47,Urban,HR Executive,36777,1 +93237,Female,45,Bachelors,14,93,20,33,51,7.0,2,66,Urban,HR Executive,116394,0 +93238,Male,48,Masters,1,50,95,26,53,7.0,6,29,Rural,HR Executive,66022,0 +93239,Male,40,PhD,9,38,55,18,36,1.0,6,94,Rural,Data Analyst,93249,0 +93240,Female,23,Bachelors,6,61,30,3,13,0.0,1,7,Semi-Urban,Data Analyst,90819,0 +93241,Male,52,Bachelors,6,91,54,6,67,3.0,4,21,Urban,Manager,97475,0 +93242,Female,34,Masters,0,37,59,97,44,4.0,5,40,Urban,Software Engineer,75855,0 +93243,Male,43,Masters,9,10,18,73,39,9.0,7,21,Urban,Manager,39935,0 +93244,Male,35,Diploma,4,35,58,24,73,0.0,2,11,Semi-Urban,Manager,24347,0 +93245,Male,47,Masters,8,77,34,99,34,5.0,5,17,Rural,ML Engineer,24213,0 +93246,Female,30,Bachelors,12,38,92,83,33,5.0,7,22,Urban,Software Engineer,115732,0 +93247,Male,31,Diploma,9,37,26,24,80,5.0,2,14,Rural,HR Executive,144218,0 +93248,Male,56,Diploma,1,43,38,18,40,5.0,7,32,Urban,ML Engineer,93607,0 +93249,Male,28,Bachelors,9,78,55,68,29,0.0,6,40,Urban,Data Analyst,112718,1 +93250,Male,44,Bachelors,10,94,59,48,54,1.0,3,49,Semi-Urban,ML Engineer,40124,1 +93251,Male,50,Masters,17,29,62,97,5,6.0,6,76,Urban,Data Analyst,113025,1 +93252,Female,58,Masters,9,70,63,46,57,2.0,1,70,Rural,HR Executive,121506,1 +93253,Other,29,Bachelors,4,4,44,0,77,0.0,2,52,Semi-Urban,Data Analyst,107760,0 +93254,Male,40,High School,11,83,5,89,68,7.0,4,10,Rural,HR Executive,68068,0 +93255,Female,29,High School,6,37,73,63,22,7.0,3,8,Urban,Software Engineer,126508,0 +93256,Female,26,Bachelors,13,8,96,87,26,7.0,7,52,Urban,Manager,69574,1 +93257,Female,23,Bachelors,0,12,86,60,97,8.0,2,41,Semi-Urban,Data Analyst,48768,0 +93258,Male,50,Diploma,15,35,95,69,36,0.0,6,60,Urban,Software Engineer,107671,1 +93259,Female,28,Bachelors,4,52,65,57,17,0.0,0,55,Semi-Urban,Software Engineer,105496,0 +93260,Other,44,Masters,14,7,29,36,38,2.0,6,24,Urban,Data Analyst,134960,0 +93261,Male,48,Bachelors,10,34,94,84,63,8.0,1,56,Semi-Urban,Data Analyst,128062,1 +93262,Male,38,Bachelors,17,5,54,3,86,4.0,5,27,Urban,HR Executive,51411,0 +93263,Female,46,Diploma,4,51,52,67,1,9.0,3,47,Urban,Data Analyst,106184,0 +93264,Male,54,Masters,10,60,57,32,59,4.0,2,13,Urban,Software Engineer,29867,0 +93265,Male,57,Bachelors,16,21,39,89,33,5.0,2,85,Urban,ML Engineer,89946,0 +93266,Male,53,Bachelors,14,11,4,3,90,0.0,3,94,Semi-Urban,Data Analyst,147364,0 +93267,Male,38,Bachelors,6,99,2,87,81,0.0,4,73,Semi-Urban,ML Engineer,69516,1 +93268,Male,27,Masters,3,16,45,1,66,9.0,3,53,Urban,ML Engineer,62413,0 +93269,Male,38,Diploma,4,86,44,69,37,5.0,4,69,Urban,Software Engineer,134945,1 +93270,Male,37,Bachelors,5,48,53,20,7,8.0,7,11,Rural,Software Engineer,131655,0 +93271,Female,24,Bachelors,6,98,83,15,84,7.0,5,35,Semi-Urban,HR Executive,50218,0 +93272,Male,56,High School,10,47,40,22,50,8.0,1,0,Semi-Urban,Data Analyst,138817,0 +93273,Male,33,Diploma,8,54,52,35,36,2.0,2,17,Semi-Urban,ML Engineer,149847,0 +93274,Male,25,Masters,13,63,66,83,95,9.0,4,41,Semi-Urban,Data Analyst,61338,1 +93275,Male,54,Bachelors,9,81,86,55,38,2.0,3,34,Urban,Data Analyst,134913,1 +93276,Male,21,Masters,7,83,10,54,36,7.0,0,93,Urban,HR Executive,81153,1 +93277,Male,55,High School,8,33,8,79,42,0.0,3,17,Rural,ML Engineer,121186,0 +93278,Female,30,Bachelors,10,70,10,29,21,0.0,4,53,Rural,Data Analyst,147643,0 +93279,Male,22,PhD,7,33,73,21,88,2.0,7,34,Urban,Manager,115598,0 +93280,Female,33,Diploma,15,73,42,9,88,1.0,3,0,Semi-Urban,HR Executive,57440,0 +93281,Male,34,High School,17,67,73,61,91,6.0,3,94,Urban,Software Engineer,64244,1 +93282,Female,55,Diploma,17,21,43,37,51,9.0,7,52,Semi-Urban,HR Executive,42923,0 +93283,Female,42,Masters,15,84,41,73,69,4.0,2,45,Urban,ML Engineer,86482,1 +93284,Female,23,Masters,14,20,54,46,57,3.0,4,83,Urban,Manager,140219,0 +93285,Female,39,Masters,10,5,40,27,87,1.0,7,40,Urban,Software Engineer,98481,0 +93286,Male,59,High School,12,77,28,32,79,7.0,0,4,Rural,Data Analyst,24922,0 +93287,Male,35,Bachelors,1,90,77,5,19,5.0,5,37,Semi-Urban,HR Executive,145460,0 +93288,Male,55,PhD,8,55,56,38,8,0.0,0,78,Urban,Software Engineer,48654,0 +93289,Male,27,High School,15,96,31,57,86,8.0,5,79,Semi-Urban,Software Engineer,148496,1 +93290,Male,25,Masters,3,48,39,48,13,6.0,3,63,Urban,Data Analyst,27676,0 +93291,Female,46,Bachelors,17,60,74,57,2,4.0,6,61,Urban,Data Analyst,98972,1 +93292,Male,28,Diploma,12,24,18,37,66,6.0,6,23,Urban,Data Analyst,149278,0 +93293,Male,50,Bachelors,12,87,95,36,3,9.0,6,11,Urban,Software Engineer,131136,0 +93294,Female,39,PhD,7,65,19,7,42,6.0,7,14,Urban,ML Engineer,68837,0 +93295,Male,34,Diploma,6,89,20,52,45,6.0,5,6,Urban,HR Executive,90881,0 +93296,Female,44,Masters,4,84,19,97,91,2.0,7,15,Semi-Urban,Software Engineer,116340,0 +93297,Male,42,Bachelors,9,87,89,37,7,1.0,2,66,Urban,Data Analyst,78272,1 +93298,Male,51,Masters,6,61,35,61,85,0.0,6,70,Semi-Urban,Data Analyst,29242,0 +93299,Female,45,Masters,16,81,89,45,36,4.0,2,15,Urban,HR Executive,105736,0 +93300,Male,31,Diploma,18,78,3,70,86,2.0,2,76,Urban,HR Executive,39009,0 +93301,Female,22,Bachelors,12,37,44,15,60,5.0,1,26,Urban,Data Analyst,138161,0 +93302,Male,27,Bachelors,8,24,63,66,61,2.0,4,36,Urban,Software Engineer,91930,0 +93303,Female,51,Masters,8,8,48,43,16,1.0,6,72,Urban,Manager,20836,0 +93304,Other,58,Diploma,4,38,55,38,33,0.0,1,65,Semi-Urban,Software Engineer,101515,0 +93305,Female,54,Bachelors,8,20,49,25,41,6.0,7,92,Semi-Urban,Manager,44159,0 +93306,Male,39,Masters,4,92,78,6,69,6.0,0,38,Rural,HR Executive,135590,0 +93307,Male,49,Diploma,0,36,77,94,79,6.0,0,92,Rural,HR Executive,120136,1 +93308,Male,46,Bachelors,9,21,97,99,96,1.0,3,67,Urban,ML Engineer,132537,1 +93309,Other,39,Bachelors,11,76,65,6,15,6.0,3,19,Urban,Software Engineer,24106,0 +93310,Male,33,PhD,7,9,77,46,9,1.0,2,36,Urban,Data Analyst,124597,0 +93311,Male,52,Masters,13,58,26,34,77,2.0,1,51,Urban,Data Analyst,134758,0 +93312,Other,37,Bachelors,4,47,71,36,77,6.0,4,51,Urban,Manager,121240,0 +93313,Female,43,Bachelors,4,3,33,91,22,8.0,7,18,Semi-Urban,Software Engineer,128016,0 +93314,Female,24,Masters,0,60,80,7,17,4.0,2,80,Semi-Urban,Data Analyst,148940,0 +93315,Male,44,Bachelors,15,15,10,7,78,9.0,7,43,Urban,ML Engineer,61348,0 +93316,Male,28,High School,11,71,13,96,60,1.0,7,86,Urban,Data Analyst,92646,1 +93317,Male,40,Bachelors,14,26,0,71,43,3.0,3,34,Semi-Urban,HR Executive,134568,0 +93318,Female,58,Bachelors,2,66,78,21,45,3.0,0,41,Urban,Software Engineer,81287,0 +93319,Male,41,Masters,0,25,4,90,73,8.0,6,6,Urban,HR Executive,124328,0 +93320,Male,21,High School,1,34,65,73,58,3.0,7,51,Urban,Manager,102242,0 +93321,Male,58,Diploma,11,90,29,4,52,4.0,4,37,Urban,Software Engineer,130872,0 +93322,Male,21,High School,11,63,45,75,49,9.0,7,60,Semi-Urban,Manager,82736,1 +93323,Female,52,Bachelors,17,88,27,43,8,8.0,6,13,Urban,Software Engineer,90198,0 +93324,Female,40,Bachelors,2,35,4,85,7,8.0,5,64,Rural,ML Engineer,77965,0 +93325,Male,54,Bachelors,11,63,89,62,83,6.0,0,13,Urban,Data Analyst,72167,0 +93326,Male,57,High School,10,77,3,24,19,3.0,4,81,Urban,ML Engineer,74327,0 +93327,Female,42,Bachelors,10,77,13,24,80,0.0,0,1,Urban,Data Analyst,101292,0 +93328,Male,47,Bachelors,16,57,23,62,65,7.0,0,39,Urban,ML Engineer,58261,0 +93329,Male,21,Diploma,0,98,4,52,77,5.0,2,44,Urban,Manager,128878,0 +93330,Female,55,PhD,9,2,59,33,36,8.0,5,56,Rural,Software Engineer,41387,0 +93331,Male,58,Masters,7,0,4,73,19,9.0,6,5,Urban,Data Analyst,100787,0 +93332,Female,50,Bachelors,3,3,40,90,65,6.0,1,71,Urban,ML Engineer,51591,0 +93333,Male,21,High School,14,54,64,58,94,3.0,4,79,Rural,Data Analyst,81595,1 +93334,Male,33,Bachelors,14,89,43,46,41,5.0,0,74,Urban,HR Executive,115576,1 +93335,Female,32,Bachelors,5,52,43,38,11,4.0,1,29,Semi-Urban,ML Engineer,133964,0 +93336,Male,27,Bachelors,4,44,66,19,79,7.0,1,82,Urban,Data Analyst,21848,0 +93337,Male,47,Bachelors,16,86,40,87,43,3.0,6,97,Rural,ML Engineer,43820,1 +93338,Male,28,Masters,10,66,13,6,49,4.0,5,41,Rural,Manager,130101,0 +93339,Male,35,Diploma,17,14,11,70,87,3.0,7,45,Semi-Urban,ML Engineer,68447,0 +93340,Male,33,Diploma,6,32,86,91,84,3.0,4,51,Urban,Manager,118830,1 +93341,Male,25,High School,18,89,12,41,46,6.0,6,45,Semi-Urban,Data Analyst,129955,0 +93342,Male,41,Diploma,9,89,64,57,10,5.0,1,29,Urban,Software Engineer,95898,1 +93343,Male,28,Masters,4,39,96,96,46,3.0,4,37,Urban,Data Analyst,146927,1 +93344,Male,40,Diploma,1,52,98,23,30,5.0,2,34,Rural,ML Engineer,38092,0 +93345,Male,21,Bachelors,2,56,72,45,32,9.0,4,34,Semi-Urban,ML Engineer,130288,0 +93346,Male,22,Masters,16,46,1,10,33,2.0,2,5,Urban,HR Executive,114891,0 +93347,Male,44,Diploma,17,3,31,75,86,5.0,1,90,Rural,Data Analyst,149242,0 +93348,Female,43,Masters,14,25,6,55,30,6.0,4,29,Urban,ML Engineer,128132,0 +93349,Female,46,Diploma,8,61,72,79,85,1.0,0,65,Urban,Data Analyst,58358,1 +93350,Female,48,Bachelors,1,74,58,37,13,4.0,2,88,Rural,Manager,61239,1 +93351,Male,30,Bachelors,15,44,56,26,72,1.0,6,9,Urban,Manager,53380,0 +93352,Male,30,Masters,10,57,33,26,89,4.0,3,91,Urban,Software Engineer,52855,0 +93353,Male,33,Diploma,1,64,40,47,35,1.0,4,63,Urban,HR Executive,89931,0 +93354,Male,30,Bachelors,16,40,32,54,30,9.0,2,68,Urban,Data Analyst,77913,0 +93355,Male,42,Bachelors,10,50,54,29,70,5.0,7,30,Semi-Urban,Software Engineer,40754,0 +93356,Female,50,Bachelors,17,23,76,31,77,2.0,1,83,Rural,Data Analyst,137587,0 +93357,Female,23,Bachelors,8,92,74,30,9,4.0,2,60,Urban,ML Engineer,61664,1 +93358,Male,48,Bachelors,8,70,45,57,54,8.0,1,78,Semi-Urban,Data Analyst,55806,1 +93359,Female,32,Diploma,19,83,82,86,63,1.0,2,56,Rural,Software Engineer,112538,1 +93360,Male,38,Diploma,14,97,69,64,45,7.0,4,46,Rural,Manager,140142,1 +93361,Male,39,Bachelors,7,22,95,90,82,3.0,0,30,Semi-Urban,Data Analyst,42931,1 +93362,Female,57,Bachelors,7,9,69,27,70,4.0,1,23,Rural,Manager,39529,0 +93363,Male,34,Diploma,19,0,16,1,32,0.0,5,78,Semi-Urban,Manager,83326,0 +93364,Male,38,Diploma,11,77,58,73,42,5.0,0,86,Semi-Urban,HR Executive,39171,1 +93365,Male,21,Diploma,16,24,98,53,79,8.0,7,96,Urban,HR Executive,28493,1 +93366,Female,50,High School,3,82,16,27,96,5.0,4,54,Urban,Manager,32926,0 +93367,Female,33,Bachelors,15,8,54,43,10,6.0,5,4,Urban,HR Executive,113662,0 +93368,Male,58,Bachelors,11,23,4,25,42,1.0,5,0,Urban,HR Executive,111483,0 +93369,Male,45,Bachelors,6,79,13,84,8,3.0,1,83,Rural,Manager,79692,1 +93370,Male,49,Bachelors,4,66,11,0,33,6.0,3,5,Rural,ML Engineer,60112,0 +93371,Male,27,Bachelors,9,38,31,72,25,9.0,4,81,Semi-Urban,Data Analyst,32428,0 +93372,Male,28,Bachelors,19,51,60,55,98,1.0,0,93,Urban,HR Executive,115160,1 +93373,Male,59,Diploma,14,73,51,67,42,4.0,6,33,Urban,Manager,57806,0 +93374,Female,42,Bachelors,10,14,67,41,94,8.0,5,47,Urban,HR Executive,106672,0 +93375,Female,34,Masters,8,81,70,85,46,9.0,3,73,Urban,HR Executive,99587,1 +93376,Male,58,Diploma,6,42,85,60,88,5.0,6,42,Semi-Urban,HR Executive,71045,0 +93377,Female,25,Masters,19,66,39,34,90,2.0,7,4,Semi-Urban,ML Engineer,88732,0 +93378,Male,29,Bachelors,19,1,1,63,83,7.0,4,52,Semi-Urban,Software Engineer,141302,0 +93379,Male,54,Bachelors,9,19,12,80,44,7.0,2,84,Urban,Software Engineer,38613,0 +93380,Male,32,PhD,4,89,67,92,51,7.0,4,19,Rural,Data Analyst,92346,1 +93381,Male,34,Masters,6,50,43,41,44,6.0,0,66,Urban,Software Engineer,71069,0 +93382,Male,21,Diploma,9,41,67,49,36,1.0,1,37,Semi-Urban,HR Executive,125592,0 +93383,Male,26,PhD,1,62,39,31,26,1.0,2,65,Urban,ML Engineer,146162,0 +93384,Female,57,Bachelors,0,60,82,50,93,3.0,2,86,Urban,Software Engineer,79404,1 +93385,Male,36,High School,8,45,62,55,11,9.0,1,65,Urban,HR Executive,66673,0 +93386,Male,58,Diploma,13,36,42,78,26,2.0,0,32,Rural,ML Engineer,79768,0 +93387,Female,57,Masters,6,5,88,42,86,5.0,5,66,Urban,Software Engineer,126445,0 +93388,Female,24,Diploma,14,16,19,34,3,8.0,1,92,Rural,Data Analyst,61063,0 +93389,Male,40,Diploma,11,13,53,25,59,3.0,7,88,Urban,Data Analyst,24640,0 +93390,Male,26,Masters,14,76,1,83,29,0.0,0,80,Urban,Software Engineer,132813,1 +93391,Male,52,Bachelors,0,71,42,70,81,3.0,1,94,Urban,Data Analyst,113349,1 +93392,Male,36,Diploma,0,19,34,62,65,6.0,0,30,Urban,HR Executive,138764,0 +93393,Male,57,Bachelors,16,6,58,9,5,7.0,0,0,Urban,Software Engineer,114887,0 +93394,Male,22,Bachelors,16,38,1,72,9,0.0,1,63,Urban,Manager,33284,0 +93395,Male,58,Masters,9,33,61,28,80,2.0,2,58,Rural,HR Executive,99959,0 +93396,Male,29,Diploma,16,75,88,70,33,8.0,3,69,Semi-Urban,Software Engineer,97054,1 +93397,Male,40,Bachelors,14,64,75,6,41,2.0,0,83,Semi-Urban,HR Executive,44710,0 +93398,Female,32,High School,8,41,24,39,61,7.0,4,83,Rural,Manager,138490,0 +93399,Male,34,Diploma,14,48,25,0,54,0.0,1,72,Semi-Urban,HR Executive,36083,0 +93400,Male,24,Diploma,12,52,66,67,7,5.0,0,80,Urban,Software Engineer,33252,1 +93401,Female,45,Bachelors,7,92,58,86,21,3.0,5,40,Rural,Data Analyst,89217,1 +93402,Female,55,Bachelors,13,13,48,3,50,3.0,6,95,Urban,Data Analyst,21458,0 +93403,Male,59,Bachelors,19,7,49,2,35,9.0,1,83,Urban,Software Engineer,85570,0 +93404,Male,27,Masters,17,87,43,36,98,4.0,6,92,Rural,HR Executive,72166,1 +93405,Female,28,Bachelors,15,9,17,55,64,7.0,6,0,Urban,Data Analyst,53202,0 +93406,Female,51,Bachelors,5,66,35,85,53,9.0,5,57,Semi-Urban,ML Engineer,27057,1 +93407,Other,28,Masters,4,89,94,76,79,7.0,0,18,Urban,Manager,126242,1 +93408,Male,47,Bachelors,3,7,57,6,76,4.0,3,78,Urban,Software Engineer,127049,0 +93409,Male,46,Bachelors,10,69,21,46,90,5.0,1,86,Semi-Urban,Software Engineer,108886,0 +93410,Female,23,High School,9,92,15,59,50,8.0,0,64,Rural,Data Analyst,118175,0 +93411,Male,55,Diploma,1,77,32,3,50,4.0,5,38,Urban,Manager,124151,0 +93412,Male,24,High School,4,9,66,14,26,8.0,5,76,Urban,Data Analyst,126485,0 +93413,Female,45,Bachelors,7,98,32,74,66,8.0,2,65,Semi-Urban,ML Engineer,147887,1 +93414,Male,28,Bachelors,9,30,33,92,96,7.0,5,10,Rural,HR Executive,71515,0 +93415,Female,29,Masters,13,44,35,63,61,0.0,7,50,Urban,ML Engineer,130087,0 +93416,Female,22,Bachelors,13,72,11,54,14,0.0,5,32,Semi-Urban,HR Executive,69306,0 +93417,Male,51,Masters,9,54,80,98,42,9.0,3,26,Urban,HR Executive,76628,1 +93418,Male,45,Masters,0,62,15,96,96,7.0,4,95,Rural,ML Engineer,127105,1 +93419,Other,52,Diploma,9,57,10,56,86,0.0,6,25,Urban,Software Engineer,55787,0 +93420,Male,52,High School,17,51,11,50,69,9.0,2,2,Rural,ML Engineer,111392,0 +93421,Male,40,High School,6,74,59,64,29,0.0,6,50,Rural,Software Engineer,35249,1 +93422,Male,59,Bachelors,4,94,75,16,43,9.0,6,76,Urban,ML Engineer,89600,1 +93423,Female,43,Bachelors,16,93,50,76,66,4.0,2,19,Urban,HR Executive,97939,0 +93424,Female,28,Bachelors,6,22,39,4,88,4.0,2,41,Urban,HR Executive,122217,0 +93425,Male,27,Diploma,7,66,89,18,92,9.0,2,41,Urban,Software Engineer,86747,0 +93426,Male,38,Masters,9,49,15,26,45,4.0,6,76,Semi-Urban,Software Engineer,56074,0 +93427,Female,27,Masters,11,56,34,44,1,6.0,5,25,Urban,ML Engineer,104247,0 +93428,Female,54,Bachelors,14,26,46,68,95,6.0,2,38,Urban,HR Executive,108835,0 +93429,Other,40,Diploma,8,79,52,77,35,9.0,2,17,Urban,HR Executive,132036,0 +93430,Female,23,High School,13,87,94,37,87,9.0,7,75,Urban,Data Analyst,139596,1 +93431,Male,51,Bachelors,5,97,62,85,45,9.0,4,0,Urban,HR Executive,95039,1 +93432,Female,49,PhD,6,31,87,34,42,3.0,3,75,Urban,HR Executive,109734,0 +93433,Male,46,Bachelors,18,62,48,54,98,3.0,5,67,Urban,Data Analyst,39193,0 +93434,Male,30,Bachelors,8,2,53,53,37,2.0,0,68,Urban,Manager,132347,0 +93435,Female,46,Diploma,9,26,50,88,50,8.0,1,70,Urban,HR Executive,133126,0 +93436,Male,23,High School,19,41,3,90,35,6.0,2,0,Rural,Software Engineer,104629,0 +93437,Male,59,Masters,3,67,74,50,25,4.0,2,47,Urban,Data Analyst,48607,1 +93438,Male,37,Bachelors,19,51,79,69,70,7.0,5,65,Urban,Manager,144776,1 +93439,Male,25,Bachelors,0,97,38,60,45,9.0,0,10,Rural,Data Analyst,120748,0 +93440,Female,57,Masters,15,14,62,45,99,4.0,2,50,Urban,Manager,116222,0 +93441,Female,53,Bachelors,1,54,55,12,12,1.0,4,72,Urban,Software Engineer,42234,0 +93442,Female,43,High School,10,84,66,79,75,7.0,5,10,Urban,HR Executive,101216,0 +93443,Female,22,Bachelors,8,41,12,74,90,3.0,0,50,Urban,ML Engineer,40957,0 +93444,Male,58,Bachelors,16,93,47,26,58,6.0,3,59,Urban,Data Analyst,54163,0 +93445,Male,40,High School,7,39,46,61,60,9.0,5,71,Semi-Urban,Manager,69012,0 +93446,Female,21,PhD,9,93,93,17,75,0.0,3,29,Semi-Urban,Manager,142124,0 +93447,Female,47,High School,15,21,95,21,63,6.0,1,67,Urban,Manager,45276,0 +93448,Male,46,Bachelors,5,3,7,58,45,0.0,3,38,Semi-Urban,Data Analyst,71551,0 +93449,Female,57,PhD,10,63,99,19,8,0.0,0,89,Urban,Software Engineer,62035,1 +93450,Male,52,Masters,19,46,10,75,59,0.0,4,77,Semi-Urban,ML Engineer,58113,0 +93451,Male,24,PhD,13,95,3,24,78,7.0,7,70,Semi-Urban,Manager,147865,0 +93452,Male,57,Diploma,19,52,85,80,80,3.0,0,86,Urban,Data Analyst,106991,1 +93453,Male,52,Bachelors,6,15,38,97,83,1.0,3,72,Rural,Manager,93642,0 +93454,Female,45,Bachelors,18,30,37,29,7,5.0,5,45,Urban,Data Analyst,116993,0 +93455,Male,26,Bachelors,12,96,84,34,38,1.0,0,81,Urban,Manager,63597,1 +93456,Male,31,Bachelors,6,6,57,26,5,7.0,4,26,Semi-Urban,ML Engineer,103649,0 +93457,Male,52,Diploma,11,88,86,53,37,2.0,6,99,Rural,Software Engineer,31273,1 +93458,Male,51,Bachelors,7,0,83,93,24,7.0,2,30,Rural,Data Analyst,148373,0 +93459,Female,32,Masters,7,66,30,5,99,3.0,0,95,Semi-Urban,ML Engineer,79582,0 +93460,Male,34,Diploma,15,38,63,67,76,8.0,0,42,Semi-Urban,HR Executive,130639,0 +93461,Female,21,Diploma,6,70,37,96,55,0.0,0,38,Urban,HR Executive,55238,1 +93462,Male,38,Bachelors,2,87,82,48,87,3.0,4,33,Urban,Data Analyst,124225,1 +93463,Female,37,High School,8,49,36,76,45,9.0,5,73,Urban,Software Engineer,79031,0 +93464,Male,22,Diploma,12,75,52,3,73,4.0,2,85,Rural,ML Engineer,54363,0 +93465,Male,34,Bachelors,11,30,4,27,23,7.0,1,97,Semi-Urban,Data Analyst,128927,0 +93466,Male,26,Bachelors,10,71,30,93,81,8.0,6,64,Urban,ML Engineer,91279,1 +93467,Male,56,Bachelors,8,5,26,45,85,2.0,6,82,Urban,Software Engineer,58567,0 +93468,Male,41,Bachelors,9,38,69,77,21,7.0,1,96,Urban,ML Engineer,111313,1 +93469,Female,27,Bachelors,11,81,60,55,52,7.0,7,67,Semi-Urban,Manager,99140,1 +93470,Female,48,PhD,4,96,55,94,96,6.0,1,70,Urban,Manager,75899,1 +93471,Other,30,Masters,9,9,65,76,16,2.0,0,40,Urban,Software Engineer,89401,0 +93472,Male,23,High School,16,97,83,15,83,0.0,4,56,Rural,ML Engineer,128604,1 +93473,Male,23,Diploma,14,12,90,89,12,3.0,2,12,Semi-Urban,Software Engineer,140668,0 +93474,Male,54,High School,12,5,4,41,6,6.0,1,89,Urban,Manager,77837,0 +93475,Male,46,Masters,0,63,68,38,57,4.0,1,97,Urban,HR Executive,127994,1 +93476,Male,30,Diploma,19,73,36,79,59,2.0,2,47,Urban,Data Analyst,115707,1 +93477,Female,57,High School,13,84,13,39,65,4.0,7,93,Semi-Urban,Manager,27025,0 +93478,Male,33,Masters,1,6,36,30,80,4.0,7,23,Urban,Software Engineer,46319,0 +93479,Female,40,Masters,15,0,77,95,71,9.0,2,70,Urban,HR Executive,111180,1 +93480,Other,45,Diploma,15,27,73,53,24,4.0,7,98,Urban,HR Executive,56518,1 +93481,Male,22,Diploma,18,44,85,72,56,3.0,2,71,Urban,Software Engineer,37195,1 +93482,Female,50,Bachelors,19,30,66,95,18,6.0,6,88,Urban,Data Analyst,38504,1 +93483,Female,34,Bachelors,17,8,61,91,10,6.0,4,14,Semi-Urban,Manager,81843,0 +93484,Female,44,Bachelors,11,50,73,14,91,4.0,6,10,Rural,HR Executive,75871,0 +93485,Male,57,Bachelors,11,44,0,71,67,7.0,0,46,Semi-Urban,HR Executive,147641,0 +93486,Male,49,Diploma,8,80,15,13,99,9.0,0,62,Urban,Data Analyst,112831,0 +93487,Female,55,Masters,12,97,49,72,27,5.0,7,19,Semi-Urban,ML Engineer,101441,0 +93488,Female,38,Diploma,3,65,50,89,72,5.0,4,92,Rural,Data Analyst,65573,1 +93489,Female,41,Diploma,9,95,59,19,94,2.0,7,31,Semi-Urban,ML Engineer,120030,0 +93490,Male,48,Diploma,4,77,97,50,59,3.0,3,2,Semi-Urban,Software Engineer,34727,0 +93491,Male,55,Masters,4,89,40,96,68,0.0,5,30,Semi-Urban,ML Engineer,144057,1 +93492,Female,54,Masters,7,27,13,35,74,3.0,6,66,Urban,Manager,146643,0 +93493,Male,52,Masters,17,94,24,72,68,2.0,3,95,Semi-Urban,Manager,84772,1 +93494,Male,53,Masters,14,70,91,19,96,1.0,7,51,Semi-Urban,Manager,44644,0 +93495,Male,50,Masters,12,98,87,62,56,9.0,2,79,Urban,ML Engineer,109844,1 +93496,Male,40,PhD,4,24,57,35,36,3.0,0,69,Urban,HR Executive,33617,0 +93497,Female,35,Masters,3,52,24,30,88,5.0,3,48,Urban,Data Analyst,106161,0 +93498,Female,44,Diploma,17,3,87,81,56,9.0,4,44,Urban,HR Executive,94084,0 +93499,Female,53,High School,11,55,34,79,60,2.0,5,22,Rural,Data Analyst,92388,0 +93500,Female,41,Bachelors,19,3,84,40,28,0.0,4,57,Urban,ML Engineer,81905,0 +93501,Male,35,PhD,7,22,90,88,86,0.0,0,86,Semi-Urban,ML Engineer,121891,1 +93502,Female,36,Bachelors,17,92,89,65,91,0.0,3,30,Semi-Urban,Data Analyst,108883,1 +93503,Male,57,Diploma,16,70,97,6,66,3.0,2,55,Urban,Software Engineer,34492,0 +93504,Female,41,Bachelors,18,74,98,26,37,5.0,4,20,Semi-Urban,Data Analyst,95578,0 +93505,Female,32,Masters,7,6,24,51,99,7.0,0,70,Semi-Urban,Manager,27550,0 +93506,Male,43,Bachelors,8,51,36,22,85,8.0,1,54,Urban,HR Executive,97297,0 +93507,Male,27,Bachelors,16,9,7,23,81,5.0,3,96,Urban,Manager,120942,0 +93508,Female,25,Masters,18,15,95,66,64,3.0,1,5,Urban,Manager,63786,0 +93509,Male,38,Masters,5,34,30,67,86,6.0,5,37,Urban,ML Engineer,28204,0 +93510,Male,50,Masters,10,75,10,36,38,7.0,1,41,Semi-Urban,Software Engineer,67875,0 +93511,Male,39,Bachelors,15,62,25,73,54,7.0,7,26,Urban,Manager,98026,0 +93512,Female,55,Bachelors,3,63,91,74,87,5.0,6,91,Semi-Urban,ML Engineer,145172,1 +93513,Male,29,Diploma,7,85,22,5,29,6.0,1,97,Semi-Urban,ML Engineer,40696,0 +93514,Female,52,Diploma,14,74,15,5,26,0.0,0,60,Rural,Software Engineer,50176,0 +93515,Male,44,Bachelors,13,53,63,34,47,9.0,7,74,Semi-Urban,ML Engineer,72200,0 +93516,Male,52,Bachelors,11,58,87,87,70,2.0,4,17,Rural,Data Analyst,78695,1 +93517,Male,57,Diploma,1,47,53,65,89,7.0,7,48,Urban,Manager,28922,0 +93518,Male,37,Diploma,2,41,34,91,82,3.0,4,33,Urban,ML Engineer,146418,0 +93519,Female,47,High School,2,15,42,76,80,2.0,3,1,Semi-Urban,ML Engineer,76315,0 +93520,Male,56,Masters,14,35,40,9,99,8.0,6,40,Semi-Urban,ML Engineer,148874,0 +93521,Male,35,Bachelors,2,84,91,0,62,2.0,0,49,Urban,Software Engineer,138126,0 +93522,Male,43,Bachelors,0,86,67,10,59,6.0,0,90,Semi-Urban,HR Executive,31006,1 +93523,Male,23,Masters,4,83,10,96,59,5.0,1,13,Rural,ML Engineer,140477,0 +93524,Male,46,Bachelors,3,83,77,69,15,7.0,0,85,Urban,ML Engineer,91907,1 +93525,Male,55,Bachelors,3,5,38,46,45,1.0,1,8,Urban,Software Engineer,21755,0 +93526,Male,34,Bachelors,6,32,18,73,73,9.0,0,31,Semi-Urban,Manager,103707,0 +93527,Male,30,High School,18,53,53,76,38,5.0,2,21,Semi-Urban,Manager,106190,0 +93528,Male,44,High School,14,23,69,1,5,8.0,1,18,Urban,Data Analyst,40228,0 +93529,Male,34,High School,12,54,51,14,28,3.0,0,44,Rural,HR Executive,125490,0 +93530,Male,28,Bachelors,1,87,43,64,14,6.0,0,34,Rural,HR Executive,54892,0 +93531,Male,39,Bachelors,9,69,10,7,78,6.0,1,58,Urban,Manager,103913,0 +93532,Male,59,High School,19,37,7,22,82,7.0,0,83,Rural,HR Executive,41204,0 +93533,Female,25,High School,9,55,61,30,55,7.0,4,76,Rural,Software Engineer,28406,0 +93534,Female,36,Diploma,1,52,37,60,23,3.0,4,7,Urban,Software Engineer,62791,0 +93535,Male,59,Masters,13,83,10,47,37,7.0,6,83,Rural,Data Analyst,48420,0 +93536,Female,45,High School,0,4,98,27,18,4.0,5,0,Urban,Data Analyst,31183,0 +93537,Female,32,High School,3,22,3,20,92,9.0,1,70,Urban,Manager,138635,0 +93538,Male,23,Diploma,6,74,13,2,22,6.0,4,60,Urban,HR Executive,124308,0 +93539,Male,49,Bachelors,10,75,9,74,7,7.0,1,23,Urban,ML Engineer,55113,0 +93540,Male,25,Bachelors,3,35,7,74,34,5.0,6,89,Urban,Software Engineer,45406,0 +93541,Female,28,Masters,4,80,9,90,55,1.0,5,28,Urban,Manager,45524,0 +93542,Male,33,Bachelors,14,79,78,5,3,8.0,5,25,Rural,Data Analyst,100436,0 +93543,Female,29,Masters,18,32,24,16,3,8.0,1,69,Urban,Manager,146838,0 +93544,Male,57,Masters,19,13,23,59,55,1.0,3,81,Rural,ML Engineer,118729,0 +93545,Male,21,Bachelors,19,83,0,4,24,6.0,4,52,Semi-Urban,ML Engineer,91410,0 +93546,Male,25,Diploma,15,38,39,68,67,6.0,2,23,Semi-Urban,ML Engineer,110250,0 +93547,Male,42,Bachelors,6,74,17,39,90,7.0,4,34,Urban,Manager,75585,0 +93548,Female,50,High School,8,58,30,50,44,9.0,7,1,Urban,Data Analyst,93400,0 +93549,Male,23,Diploma,14,55,47,82,66,5.0,5,40,Urban,Manager,63679,0 +93550,Male,24,Diploma,16,41,67,88,54,8.0,3,87,Semi-Urban,Data Analyst,86798,1 +93551,Male,36,Bachelors,3,81,37,52,60,6.0,2,11,Rural,ML Engineer,59136,0 +93552,Male,45,Diploma,9,99,53,88,81,3.0,0,82,Urban,Data Analyst,71363,1 +93553,Male,31,Bachelors,2,31,66,63,84,1.0,3,50,Urban,Manager,25876,0 +93554,Female,50,High School,17,43,50,82,35,1.0,5,78,Rural,Manager,20074,1 +93555,Male,52,Diploma,17,49,6,33,65,2.0,1,81,Semi-Urban,HR Executive,23027,0 +93556,Female,56,Masters,3,38,59,6,90,6.0,6,64,Semi-Urban,Manager,143430,0 +93557,Male,21,Diploma,15,94,15,36,44,3.0,0,40,Urban,Data Analyst,146137,0 +93558,Female,58,High School,2,81,14,77,55,8.0,3,43,Rural,HR Executive,104794,0 +93559,Male,43,Diploma,19,75,38,81,73,0.0,2,24,Rural,ML Engineer,28700,0 +93560,Male,55,Masters,8,32,66,50,16,6.0,3,30,Rural,HR Executive,114758,0 +93561,Male,52,Bachelors,3,29,12,66,31,6.0,2,5,Urban,ML Engineer,81128,0 +93562,Female,55,Masters,1,61,9,54,13,0.0,1,5,Semi-Urban,HR Executive,137108,0 +93563,Female,21,Diploma,13,14,47,21,48,8.0,6,49,Urban,ML Engineer,111365,0 +93564,Male,40,Bachelors,8,49,96,3,27,1.0,3,34,Urban,Manager,57084,0 +93565,Female,32,Bachelors,17,82,92,68,92,6.0,1,8,Semi-Urban,Data Analyst,34769,1 +93566,Female,28,Masters,13,4,89,19,11,6.0,3,25,Urban,HR Executive,67804,0 +93567,Male,22,Bachelors,11,20,48,29,62,0.0,5,26,Rural,Software Engineer,42201,0 +93568,Female,43,Diploma,4,28,13,26,22,4.0,1,42,Urban,Manager,35248,0 +93569,Female,21,PhD,13,41,55,78,61,3.0,7,11,Urban,HR Executive,45098,0 +93570,Male,45,Masters,8,8,65,65,79,9.0,1,16,Semi-Urban,Software Engineer,97821,0 +93571,Male,43,High School,3,28,37,94,0,6.0,1,13,Urban,Data Analyst,140599,0 +93572,Male,31,Bachelors,19,14,41,42,17,4.0,4,8,Urban,HR Executive,46024,0 +93573,Male,36,Bachelors,12,84,72,11,55,6.0,5,51,Semi-Urban,Software Engineer,125403,0 +93574,Male,27,High School,9,69,1,44,55,2.0,3,18,Urban,Software Engineer,149592,0 +93575,Male,29,Diploma,13,48,39,92,51,8.0,5,66,Urban,Software Engineer,140516,1 +93576,Male,39,Diploma,12,69,14,43,76,1.0,7,25,Rural,Software Engineer,117540,0 +93577,Male,43,Bachelors,11,46,66,51,33,5.0,6,57,Rural,Data Analyst,145666,0 +93578,Male,36,Diploma,5,5,22,96,24,1.0,4,37,Urban,Data Analyst,137633,0 +93579,Male,50,High School,11,27,41,61,87,4.0,5,54,Urban,Software Engineer,77326,0 +93580,Female,28,PhD,17,75,5,43,72,9.0,5,10,Semi-Urban,Data Analyst,141021,0 +93581,Female,36,Masters,9,55,10,86,32,1.0,7,14,Urban,Software Engineer,121730,0 +93582,Female,49,Bachelors,1,83,92,1,35,4.0,1,9,Urban,ML Engineer,120417,0 +93583,Female,52,Masters,9,62,81,55,24,2.0,0,74,Urban,Manager,76559,1 +93584,Male,40,PhD,4,84,83,37,66,9.0,7,45,Semi-Urban,ML Engineer,108531,1 +93585,Male,24,High School,11,79,58,89,58,2.0,1,27,Urban,ML Engineer,131516,1 +93586,Female,50,Bachelors,15,88,92,10,1,4.0,5,42,Semi-Urban,Manager,50780,0 +93587,Male,50,Masters,17,37,72,68,69,6.0,1,67,Semi-Urban,Manager,109880,1 +93588,Female,43,Diploma,6,41,23,25,50,1.0,2,91,Urban,HR Executive,63731,0 +93589,Male,29,Bachelors,11,12,56,40,13,6.0,7,12,Semi-Urban,Data Analyst,111930,0 +93590,Male,52,Bachelors,11,11,8,83,98,1.0,4,11,Urban,Data Analyst,60475,0 +93591,Other,39,Masters,4,57,95,22,27,9.0,4,65,Rural,Manager,112323,0 +93592,Female,40,Bachelors,16,11,81,29,59,6.0,2,8,Urban,Manager,73122,0 +93593,Male,27,Diploma,19,83,76,11,94,9.0,5,99,Urban,ML Engineer,49889,1 +93594,Female,43,High School,8,63,84,21,16,2.0,2,88,Urban,Manager,104025,1 +93595,Male,21,Bachelors,13,53,79,89,54,8.0,3,63,Urban,HR Executive,67684,1 +93596,Other,35,Bachelors,1,34,43,78,26,2.0,7,33,Urban,ML Engineer,115408,0 +93597,Male,47,Masters,10,75,28,42,35,7.0,1,47,Urban,HR Executive,133892,0 +93598,Other,48,Bachelors,14,5,4,52,98,1.0,3,60,Semi-Urban,Data Analyst,130924,0 +93599,Female,35,High School,16,95,46,85,79,3.0,0,45,Semi-Urban,Data Analyst,27404,1 +93600,Male,45,Bachelors,13,21,41,62,22,9.0,7,21,Urban,HR Executive,123773,0 +93601,Female,48,High School,11,41,40,3,58,3.0,5,83,Rural,Data Analyst,82358,0 +93602,Male,24,Diploma,16,42,43,16,6,1.0,0,43,Semi-Urban,Software Engineer,98685,0 +93603,Female,51,High School,19,12,97,23,77,4.0,6,36,Urban,Data Analyst,80096,0 +93604,Female,21,High School,15,44,98,47,95,8.0,2,29,Urban,HR Executive,43164,0 +93605,Male,37,High School,17,79,75,49,97,7.0,1,26,Urban,Software Engineer,48060,0 +93606,Male,46,Bachelors,18,50,5,76,49,8.0,0,28,Rural,HR Executive,63464,0 +93607,Other,23,Bachelors,16,55,80,40,22,4.0,7,9,Rural,ML Engineer,148329,0 +93608,Male,44,Bachelors,1,45,89,84,49,8.0,0,51,Semi-Urban,Software Engineer,58265,1 +93609,Male,35,Masters,6,70,18,45,0,9.0,5,28,Urban,Data Analyst,100697,0 +93610,Female,46,Bachelors,4,41,32,41,57,8.0,6,13,Urban,HR Executive,141771,0 +93611,Female,55,Masters,12,39,43,55,61,8.0,7,38,Urban,Data Analyst,147086,0 +93612,Female,39,Masters,15,2,3,55,4,7.0,2,67,Urban,ML Engineer,39254,0 +93613,Male,29,Bachelors,1,93,56,79,39,9.0,7,60,Urban,ML Engineer,103931,1 +93614,Male,29,Masters,4,70,3,69,52,3.0,5,2,Semi-Urban,ML Engineer,87640,0 +93615,Male,37,Masters,8,20,61,47,34,6.0,3,73,Rural,ML Engineer,57227,0 +93616,Female,53,Masters,11,94,56,42,77,2.0,2,97,Rural,ML Engineer,87813,1 +93617,Male,39,Bachelors,3,90,47,3,35,0.0,3,89,Rural,Data Analyst,48318,0 +93618,Male,51,Bachelors,3,30,1,62,26,3.0,2,23,Urban,HR Executive,115475,0 +93619,Male,28,Bachelors,1,12,77,64,7,6.0,2,72,Urban,ML Engineer,127022,0 +93620,Female,29,Bachelors,0,67,20,68,91,5.0,6,94,Urban,ML Engineer,122000,1 +93621,Male,34,Bachelors,9,73,61,42,8,9.0,5,96,Rural,Software Engineer,138932,1 +93622,Female,25,Bachelors,0,37,71,47,82,8.0,4,67,Semi-Urban,HR Executive,83197,0 +93623,Female,34,Masters,12,43,62,67,47,2.0,2,95,Urban,ML Engineer,83923,1 +93624,Male,47,PhD,15,60,31,51,24,0.0,0,43,Semi-Urban,Manager,127317,0 +93625,Female,28,Masters,10,3,75,53,98,1.0,5,37,Semi-Urban,Software Engineer,30935,0 +93626,Female,33,Bachelors,8,3,96,77,93,9.0,6,19,Urban,Manager,27315,0 +93627,Female,57,Masters,17,8,77,34,62,5.0,4,33,Urban,Data Analyst,130762,0 +93628,Female,52,High School,10,83,89,70,39,4.0,4,95,Rural,HR Executive,40946,1 +93629,Female,32,Bachelors,7,61,1,98,48,3.0,4,58,Semi-Urban,HR Executive,91531,0 +93630,Male,45,Bachelors,17,14,37,64,63,7.0,1,87,Urban,Data Analyst,136274,0 +93631,Male,45,Bachelors,2,0,73,81,87,7.0,0,69,Rural,ML Engineer,85564,0 +93632,Other,58,Bachelors,13,6,49,85,30,2.0,4,33,Urban,ML Engineer,87542,0 +93633,Male,43,Bachelors,3,13,3,76,46,2.0,1,52,Semi-Urban,HR Executive,135835,0 +93634,Female,59,High School,16,87,42,34,17,4.0,5,38,Urban,ML Engineer,39882,0 +93635,Male,42,Masters,10,40,59,48,57,1.0,5,92,Semi-Urban,HR Executive,46808,1 +93636,Male,39,Bachelors,3,55,6,58,84,7.0,6,92,Urban,Software Engineer,105194,0 +93637,Male,51,Bachelors,14,72,64,74,34,8.0,7,5,Urban,Data Analyst,115173,0 +93638,Male,58,High School,10,24,88,98,96,1.0,4,68,Urban,ML Engineer,101845,1 +93639,Other,29,Bachelors,5,28,25,55,1,7.0,5,74,Rural,Manager,38807,0 +93640,Male,25,High School,13,6,39,35,58,3.0,3,65,Urban,ML Engineer,35890,0 +93641,Male,25,Bachelors,3,85,65,50,1,9.0,7,88,Urban,HR Executive,46717,1 +93642,Female,59,Bachelors,1,59,43,76,77,0.0,3,8,Urban,HR Executive,89247,0 +93643,Male,38,Bachelors,7,99,51,35,26,0.0,5,76,Semi-Urban,Manager,48688,1 +93644,Male,54,Masters,16,18,19,27,84,6.0,5,29,Urban,HR Executive,106635,0 +93645,Male,21,Masters,12,43,72,0,97,1.0,5,58,Rural,Manager,52186,0 +93646,Male,54,Bachelors,9,70,94,19,22,1.0,1,49,Semi-Urban,ML Engineer,115913,0 +93647,Other,53,Masters,16,42,18,98,49,5.0,2,72,Rural,Software Engineer,95828,0 +93648,Male,39,Masters,13,71,93,56,45,7.0,1,94,Semi-Urban,Manager,57094,1 +93649,Male,57,Bachelors,7,39,42,22,53,7.0,4,90,Urban,HR Executive,34345,0 +93650,Female,57,Bachelors,12,26,13,89,69,4.0,6,43,Rural,Manager,130931,0 +93651,Male,24,Bachelors,11,49,51,65,37,5.0,5,26,Rural,HR Executive,83766,0 +93652,Female,37,Bachelors,10,40,26,6,96,9.0,6,82,Semi-Urban,Data Analyst,91112,0 +93653,Female,21,Masters,0,61,61,20,34,0.0,4,83,Urban,HR Executive,78323,0 +93654,Male,47,Masters,5,48,97,98,28,9.0,5,10,Rural,Manager,118738,1 +93655,Male,45,Masters,19,83,80,31,70,1.0,6,50,Urban,Manager,21875,1 +93656,Female,57,Diploma,8,84,18,45,97,1.0,4,40,Urban,HR Executive,131525,0 +93657,Female,31,Bachelors,16,34,66,11,33,7.0,4,52,Urban,ML Engineer,148162,0 +93658,Male,42,Bachelors,18,71,53,6,92,9.0,1,49,Rural,Software Engineer,43870,0 +93659,Male,55,High School,15,35,94,2,66,7.0,2,52,Urban,Data Analyst,91110,0 +93660,Male,50,Diploma,19,38,59,33,83,3.0,3,31,Urban,Software Engineer,78386,0 +93661,Male,24,Bachelors,0,26,50,97,59,8.0,4,80,Semi-Urban,ML Engineer,62527,1 +93662,Male,46,Bachelors,2,39,52,37,50,8.0,2,73,Urban,Manager,32428,0 +93663,Male,35,Masters,4,14,60,30,27,1.0,1,31,Semi-Urban,Software Engineer,46445,0 +93664,Male,35,Bachelors,0,25,96,17,59,4.0,3,40,Urban,ML Engineer,47897,0 +93665,Male,47,High School,16,2,66,39,74,6.0,7,84,Urban,Manager,121733,0 +93666,Male,22,High School,17,66,14,22,30,0.0,3,64,Urban,ML Engineer,26898,0 +93667,Female,46,Bachelors,9,10,98,25,33,1.0,6,80,Rural,Data Analyst,69705,0 +93668,Male,21,Bachelors,2,89,56,78,60,4.0,1,73,Urban,Software Engineer,107102,1 +93669,Male,23,Bachelors,16,42,78,16,14,3.0,2,39,Urban,Data Analyst,136919,0 +93670,Male,22,Diploma,6,60,18,88,0,0.0,4,99,Urban,ML Engineer,109975,1 +93671,Male,24,Diploma,0,43,84,40,63,4.0,5,63,Rural,HR Executive,53060,0 +93672,Male,28,Diploma,19,91,92,2,79,5.0,7,96,Urban,Manager,66314,1 +93673,Male,40,Bachelors,3,68,33,71,84,0.0,1,3,Urban,Data Analyst,109953,0 +93674,Male,49,Bachelors,7,67,45,12,87,4.0,6,60,Rural,Manager,110379,0 +93675,Male,31,Masters,13,32,6,8,16,9.0,5,42,Rural,HR Executive,72813,0 +93676,Male,57,Bachelors,18,15,86,54,4,5.0,6,53,Rural,Data Analyst,130831,0 +93677,Female,23,Diploma,18,86,97,84,66,4.0,3,95,Rural,Manager,76886,1 +93678,Female,46,High School,14,0,79,70,75,9.0,1,61,Urban,ML Engineer,79790,0 +93679,Male,25,Bachelors,8,86,58,19,63,5.0,0,1,Urban,Manager,56897,0 +93680,Male,57,High School,3,68,8,52,27,8.0,3,96,Urban,Manager,32612,0 +93681,Female,24,Bachelors,1,84,96,55,4,6.0,5,85,Urban,Manager,55828,1 +93682,Male,32,Bachelors,12,93,29,48,78,8.0,6,79,Rural,Manager,93168,1 +93683,Male,28,Bachelors,5,14,95,45,72,3.0,6,24,Urban,Manager,143475,0 +93684,Male,24,Masters,18,65,75,35,86,0.0,0,8,Rural,Software Engineer,75083,0 +93685,Female,57,Bachelors,10,25,53,28,20,9.0,0,30,Rural,ML Engineer,147293,0 +93686,Male,36,Bachelors,1,87,70,2,92,3.0,6,15,Semi-Urban,Manager,85765,0 +93687,Female,34,Bachelors,14,25,62,89,69,1.0,0,28,Urban,Software Engineer,37533,0 +93688,Male,50,Bachelors,15,94,0,13,60,0.0,4,3,Urban,Data Analyst,136592,0 +93689,Female,30,Masters,6,20,42,8,87,1.0,6,62,Urban,Manager,140606,0 +93690,Female,45,Masters,6,25,90,90,76,4.0,6,75,Urban,HR Executive,62208,1 +93691,Female,23,Bachelors,9,46,7,6,78,7.0,3,40,Urban,Data Analyst,64807,0 +93692,Male,37,Masters,2,56,70,75,77,9.0,4,4,Urban,ML Engineer,124969,0 +93693,Male,53,Bachelors,6,97,55,28,57,8.0,6,94,Urban,ML Engineer,31905,1 +93694,Male,32,Diploma,1,11,91,75,81,0.0,0,80,Semi-Urban,ML Engineer,52794,1 +93695,Male,28,Diploma,9,11,42,49,32,5.0,2,83,Urban,ML Engineer,71307,0 +93696,Female,42,Masters,14,53,50,50,56,6.0,6,79,Semi-Urban,Manager,109430,0 +93697,Female,21,Bachelors,4,56,70,57,15,5.0,5,58,Urban,Manager,69161,1 +93698,Male,38,Bachelors,5,89,63,49,95,7.0,5,33,Semi-Urban,Data Analyst,65377,0 +93699,Female,42,Masters,4,80,24,83,8,6.0,2,30,Semi-Urban,ML Engineer,33397,0 +93700,Male,24,Masters,13,25,6,64,86,6.0,2,9,Semi-Urban,ML Engineer,89655,0 +93701,Male,39,Bachelors,4,10,13,46,90,9.0,2,50,Urban,Software Engineer,146633,0 +93702,Other,56,Bachelors,18,83,20,3,9,6.0,0,14,Rural,Data Analyst,106407,0 +93703,Male,45,Diploma,10,45,74,57,5,7.0,4,72,Urban,ML Engineer,44178,1 +93704,Male,36,Bachelors,14,28,21,53,31,8.0,6,34,Urban,ML Engineer,97821,0 +93705,Male,33,Bachelors,1,43,29,59,68,8.0,4,10,Urban,HR Executive,69549,0 +93706,Female,26,Diploma,13,23,15,39,36,0.0,7,42,Urban,Data Analyst,92558,0 +93707,Male,36,Bachelors,18,21,86,86,23,7.0,2,6,Urban,HR Executive,79837,0 +93708,Female,42,High School,9,52,79,87,71,3.0,3,18,Rural,Manager,74254,0 +93709,Female,25,High School,6,43,92,62,19,3.0,0,66,Urban,ML Engineer,147172,1 +93710,Female,49,High School,10,5,36,10,78,2.0,3,91,Rural,Manager,65836,0 +93711,Male,35,Masters,3,86,83,3,61,4.0,7,76,Urban,HR Executive,49542,1 +93712,Male,33,High School,15,79,98,11,56,8.0,6,82,Urban,ML Engineer,120280,1 +93713,Female,25,Diploma,5,65,9,3,46,1.0,5,76,Urban,ML Engineer,27057,0 +93714,Male,48,Diploma,1,62,94,66,33,9.0,2,2,Semi-Urban,Manager,68957,0 +93715,Male,35,Bachelors,8,69,95,22,42,1.0,0,40,Urban,Software Engineer,63634,0 +93716,Female,53,Diploma,13,41,50,68,33,4.0,3,18,Semi-Urban,Manager,69442,0 +93717,Female,22,Bachelors,9,59,93,79,86,4.0,2,8,Semi-Urban,HR Executive,81880,0 +93718,Male,39,Bachelors,7,2,28,90,79,1.0,2,54,Rural,Manager,122638,0 +93719,Female,38,Diploma,18,43,77,0,99,4.0,6,44,Semi-Urban,Data Analyst,23940,0 +93720,Female,26,Bachelors,12,61,99,34,35,4.0,7,60,Urban,Data Analyst,125022,1 +93721,Male,32,High School,16,13,2,97,20,8.0,6,93,Semi-Urban,Data Analyst,20338,0 +93722,Male,37,Diploma,14,45,57,35,60,8.0,7,46,Rural,HR Executive,28306,0 +93723,Male,56,Diploma,19,12,52,90,94,2.0,6,36,Semi-Urban,ML Engineer,82256,0 +93724,Other,36,Bachelors,10,0,9,25,21,2.0,1,33,Semi-Urban,HR Executive,77689,0 +93725,Male,58,Masters,7,82,66,63,49,6.0,2,75,Semi-Urban,ML Engineer,63501,1 +93726,Male,22,Masters,4,44,83,48,42,0.0,4,50,Urban,Manager,113215,0 +93727,Female,49,Bachelors,16,76,80,25,16,1.0,2,28,Semi-Urban,Software Engineer,80003,0 +93728,Female,27,Masters,11,45,14,65,56,0.0,3,64,Rural,HR Executive,113822,0 +93729,Female,56,Diploma,11,47,35,73,68,2.0,6,56,Urban,Software Engineer,134447,0 +93730,Male,56,Masters,9,90,86,74,51,5.0,0,82,Urban,ML Engineer,20285,1 +93731,Male,38,High School,7,26,22,18,77,6.0,2,4,Urban,Manager,72698,0 +93732,Male,45,Diploma,11,79,39,65,98,3.0,3,83,Semi-Urban,Data Analyst,70911,1 +93733,Male,54,Masters,1,31,9,89,2,2.0,4,8,Rural,Data Analyst,56483,0 +93734,Male,30,Masters,2,19,84,23,58,8.0,4,62,Urban,Manager,62693,0 +93735,Male,46,Bachelors,17,10,98,10,71,6.0,3,69,Urban,ML Engineer,128207,0 +93736,Male,27,Diploma,13,75,4,86,69,9.0,1,53,Urban,Manager,101171,0 +93737,Female,42,Masters,0,57,19,0,91,7.0,3,42,Urban,Data Analyst,117494,0 +93738,Male,42,Bachelors,11,28,23,10,97,7.0,1,56,Rural,HR Executive,105460,0 +93739,Male,35,Bachelors,2,22,13,13,5,1.0,5,30,Urban,Software Engineer,64776,0 +93740,Female,55,Diploma,17,67,60,71,97,0.0,4,7,Rural,Manager,105172,0 +93741,Female,21,Masters,15,83,22,63,5,7.0,1,61,Urban,Software Engineer,73119,0 +93742,Male,46,Masters,4,55,71,20,25,4.0,2,90,Urban,HR Executive,135092,1 +93743,Female,59,Masters,11,60,80,72,83,0.0,2,15,Urban,ML Engineer,66051,0 +93744,Male,37,Diploma,2,72,11,64,11,1.0,3,79,Urban,ML Engineer,48006,0 +93745,Male,34,Diploma,11,0,78,4,48,3.0,2,50,Semi-Urban,Software Engineer,31685,0 +93746,Male,29,High School,1,5,72,35,21,8.0,1,38,Urban,Software Engineer,60803,0 +93747,Female,42,Bachelors,4,85,6,78,49,2.0,7,76,Urban,Data Analyst,132646,1 +93748,Other,28,High School,6,31,71,64,49,6.0,1,94,Rural,HR Executive,36263,1 +93749,Male,52,High School,9,0,14,68,17,9.0,6,94,Semi-Urban,Data Analyst,22021,0 +93750,Male,50,Masters,17,52,90,15,52,7.0,0,30,Semi-Urban,HR Executive,22184,0 +93751,Male,48,Bachelors,18,24,88,1,47,6.0,3,45,Urban,HR Executive,138893,0 +93752,Male,35,Bachelors,15,62,83,44,12,4.0,3,13,Rural,ML Engineer,43132,0 +93753,Female,51,Bachelors,6,0,18,82,0,8.0,3,83,Urban,Software Engineer,149248,0 +93754,Male,23,Bachelors,14,92,32,99,43,6.0,3,74,Semi-Urban,ML Engineer,61049,1 +93755,Male,26,Diploma,4,58,61,31,80,2.0,6,76,Urban,Data Analyst,25722,0 +93756,Male,32,Bachelors,12,14,32,37,15,7.0,1,33,Semi-Urban,Data Analyst,133060,0 +93757,Male,58,Masters,19,53,50,32,46,1.0,1,16,Urban,Data Analyst,95879,0 +93758,Male,31,PhD,13,94,55,41,67,8.0,6,44,Urban,Software Engineer,28040,0 +93759,Female,44,Bachelors,13,33,38,56,88,9.0,5,14,Rural,Software Engineer,127530,0 +93760,Male,42,Diploma,0,92,16,95,4,5.0,3,35,Rural,ML Engineer,147168,1 +93761,Female,35,PhD,5,94,25,80,79,2.0,4,58,Semi-Urban,Software Engineer,39358,1 +93762,Male,39,High School,17,19,66,98,79,2.0,3,78,Urban,Data Analyst,56124,1 +93763,Male,59,Masters,9,48,1,99,53,6.0,6,22,Urban,Manager,30030,0 +93764,Male,28,Bachelors,13,48,29,70,84,9.0,7,34,Semi-Urban,ML Engineer,142358,0 +93765,Male,56,Diploma,5,95,36,72,62,0.0,6,79,Urban,Software Engineer,56443,1 +93766,Male,51,High School,19,95,5,16,37,9.0,2,37,Rural,ML Engineer,38623,0 +93767,Male,39,High School,0,28,54,61,86,0.0,4,25,Semi-Urban,Manager,41000,0 +93768,Female,55,Diploma,4,5,10,28,64,1.0,5,60,Rural,Data Analyst,135898,0 +93769,Male,41,Masters,18,19,96,9,24,5.0,4,65,Rural,Data Analyst,147114,0 +93770,Male,44,High School,16,0,11,7,6,4.0,0,40,Semi-Urban,Data Analyst,81361,0 +93771,Male,37,Diploma,12,75,68,97,97,2.0,5,50,Rural,Manager,72265,1 +93772,Male,42,Bachelors,9,68,29,1,18,0.0,2,17,Semi-Urban,Software Engineer,133238,0 +93773,Male,41,Diploma,4,60,73,99,46,6.0,0,21,Semi-Urban,ML Engineer,148239,1 +93774,Male,56,Bachelors,10,80,77,53,38,8.0,1,84,Rural,Software Engineer,33726,1 +93775,Male,44,Masters,5,16,56,42,67,0.0,3,3,Rural,ML Engineer,20405,0 +93776,Other,52,High School,12,90,0,45,17,7.0,5,30,Rural,HR Executive,137063,0 +93777,Male,58,High School,17,71,40,43,3,6.0,4,14,Urban,HR Executive,87984,0 +93778,Male,53,Diploma,2,68,98,19,58,2.0,7,60,Semi-Urban,Software Engineer,84157,1 +93779,Male,49,Diploma,10,26,94,16,11,7.0,4,31,Semi-Urban,HR Executive,67514,0 +93780,Female,41,Bachelors,1,93,58,39,69,4.0,3,17,Urban,Data Analyst,52532,0 +93781,Male,26,High School,3,7,24,41,16,5.0,2,39,Urban,Data Analyst,128679,0 +93782,Female,47,Bachelors,3,76,15,41,41,7.0,6,19,Rural,Manager,23480,0 +93783,Male,25,Bachelors,18,91,47,42,62,6.0,7,83,Urban,Data Analyst,56336,1 +93784,Male,35,Masters,15,26,12,27,52,5.0,5,83,Urban,Manager,121607,0 +93785,Male,52,Bachelors,0,28,84,87,93,0.0,1,98,Urban,ML Engineer,28074,1 +93786,Female,57,Masters,3,44,59,41,18,1.0,3,48,Semi-Urban,ML Engineer,45035,0 +93787,Female,40,Diploma,18,2,77,18,39,4.0,0,94,Urban,Data Analyst,133465,0 +93788,Male,23,High School,14,5,62,47,0,4.0,4,29,Urban,Software Engineer,73661,0 +93789,Male,52,Diploma,17,37,65,14,91,0.0,4,90,Urban,Manager,66574,0 +93790,Male,55,PhD,12,56,14,79,49,8.0,2,21,Semi-Urban,HR Executive,29895,0 +93791,Male,22,Bachelors,18,94,72,86,98,8.0,2,75,Rural,Software Engineer,139163,1 +93792,Female,33,Bachelors,2,52,77,31,86,6.0,7,71,Urban,Manager,149260,0 +93793,Male,25,Bachelors,12,96,19,46,18,1.0,1,36,Urban,ML Engineer,20651,0 +93794,Male,22,Bachelors,14,86,65,44,75,8.0,1,63,Urban,ML Engineer,74476,1 +93795,Male,29,Bachelors,2,45,64,45,3,5.0,7,88,Urban,Data Analyst,113191,1 +93796,Male,30,Bachelors,11,61,38,13,62,4.0,0,47,Semi-Urban,Data Analyst,55719,0 +93797,Female,55,Diploma,12,29,39,17,50,3.0,4,75,Rural,HR Executive,56377,0 +93798,Male,36,Bachelors,16,19,91,8,71,9.0,4,17,Urban,ML Engineer,127052,0 +93799,Female,55,Bachelors,0,25,32,15,75,1.0,1,40,Urban,Software Engineer,42098,0 +93800,Male,57,Bachelors,1,0,61,17,43,7.0,3,45,Urban,HR Executive,114932,0 +93801,Male,38,Masters,6,77,97,12,38,4.0,7,33,Semi-Urban,Data Analyst,98710,0 +93802,Male,31,Diploma,2,91,13,34,65,2.0,2,40,Urban,HR Executive,96007,0 +93803,Male,33,Bachelors,16,70,81,4,94,4.0,4,55,Semi-Urban,HR Executive,31244,0 +93804,Female,24,Bachelors,10,70,30,45,46,5.0,7,75,Urban,Software Engineer,52143,0 +93805,Female,37,Masters,7,4,89,67,72,3.0,4,13,Urban,Data Analyst,29946,0 +93806,Male,24,High School,19,4,27,49,96,0.0,2,81,Rural,ML Engineer,136293,0 +93807,Male,55,Masters,13,80,25,5,47,6.0,6,50,Urban,Software Engineer,141172,0 +93808,Other,55,Bachelors,18,73,70,61,18,6.0,7,86,Urban,Manager,87496,1 +93809,Female,25,Masters,3,89,84,49,39,4.0,4,0,Rural,Data Analyst,134552,0 +93810,Male,41,High School,4,27,45,62,83,8.0,1,91,Rural,Data Analyst,43351,0 +93811,Male,49,Diploma,10,36,74,75,70,2.0,4,8,Semi-Urban,ML Engineer,20797,0 +93812,Female,45,Diploma,12,93,14,24,47,7.0,2,1,Rural,Manager,32009,0 +93813,Female,27,Diploma,13,42,83,10,16,7.0,6,67,Urban,Data Analyst,126508,0 +93814,Female,49,Bachelors,10,92,83,44,37,1.0,6,81,Urban,ML Engineer,130032,1 +93815,Female,24,Masters,16,98,56,44,55,0.0,6,42,Rural,Manager,57376,0 +93816,Male,31,Bachelors,10,35,38,52,48,1.0,5,97,Urban,Manager,107040,0 +93817,Male,57,Bachelors,3,34,73,74,17,1.0,2,87,Urban,HR Executive,55186,1 +93818,Male,42,Masters,6,78,36,85,51,8.0,1,61,Urban,Manager,36468,1 +93819,Male,53,High School,3,7,61,67,72,3.0,3,83,Semi-Urban,HR Executive,56332,0 +93820,Male,54,Diploma,3,95,87,59,66,8.0,0,24,Rural,Data Analyst,65861,1 +93821,Male,32,Bachelors,17,25,81,5,73,6.0,3,6,Urban,Manager,61055,0 +93822,Male,41,Diploma,9,61,1,98,26,1.0,1,86,Urban,Software Engineer,45039,1 +93823,Female,52,Bachelors,2,21,9,37,78,4.0,6,36,Urban,HR Executive,65878,0 +93824,Male,48,Masters,8,88,80,46,80,8.0,0,6,Urban,Manager,87169,0 +93825,Female,26,Masters,19,52,28,29,74,0.0,1,54,Urban,HR Executive,138576,0 +93826,Female,22,Diploma,6,91,78,57,82,4.0,5,97,Urban,HR Executive,115935,1 +93827,Male,39,High School,4,61,78,80,56,5.0,4,59,Semi-Urban,Data Analyst,101650,1 +93828,Male,30,Diploma,16,34,67,17,68,0.0,7,98,Urban,Data Analyst,95770,0 +93829,Male,38,Diploma,13,36,59,74,60,5.0,6,91,Urban,Manager,128686,1 +93830,Female,57,High School,4,20,94,10,80,7.0,7,55,Urban,ML Engineer,146657,0 +93831,Female,33,Bachelors,4,17,93,8,63,2.0,7,16,Semi-Urban,ML Engineer,130162,0 +93832,Male,43,Masters,16,14,37,20,32,3.0,4,81,Urban,HR Executive,61141,0 +93833,Male,21,Bachelors,8,59,50,87,68,6.0,7,27,Urban,Data Analyst,108096,0 +93834,Male,48,Bachelors,11,99,65,94,66,8.0,0,42,Rural,Data Analyst,133145,1 +93835,Male,46,Bachelors,18,42,82,45,34,4.0,3,39,Urban,Software Engineer,42005,0 +93836,Male,47,Diploma,5,90,82,44,10,2.0,5,0,Urban,Data Analyst,136126,0 +93837,Female,29,Diploma,13,75,97,64,85,1.0,1,98,Rural,Software Engineer,82222,1 +93838,Female,34,Bachelors,19,78,75,98,32,1.0,5,78,Semi-Urban,Manager,138581,1 +93839,Male,48,High School,18,54,11,15,98,2.0,4,37,Urban,HR Executive,64903,0 +93840,Female,26,High School,14,99,16,73,92,9.0,4,74,Rural,HR Executive,144375,1 +93841,Other,24,Bachelors,13,18,55,33,32,4.0,0,83,Urban,ML Engineer,133758,0 +93842,Female,42,Diploma,3,8,75,69,10,0.0,6,60,Urban,Data Analyst,106117,0 +93843,Male,37,Bachelors,11,78,12,80,16,6.0,6,20,Rural,Data Analyst,28264,0 +93844,Male,32,High School,8,6,17,39,7,4.0,1,10,Urban,Manager,85220,0 +93845,Male,39,Bachelors,18,75,92,16,95,6.0,1,91,Semi-Urban,Software Engineer,126941,1 +93846,Male,42,Diploma,6,60,85,29,93,3.0,7,13,Rural,Data Analyst,145870,0 +93847,Male,34,Masters,9,83,88,63,94,7.0,5,34,Urban,HR Executive,64889,1 +93848,Female,52,Masters,15,39,66,77,32,3.0,4,23,Rural,Software Engineer,34241,0 +93849,Female,53,Bachelors,1,12,1,10,40,5.0,0,98,Semi-Urban,Data Analyst,84731,0 +93850,Male,30,Diploma,13,71,12,3,74,0.0,3,97,Urban,Software Engineer,71297,0 +93851,Male,44,Masters,14,26,47,52,39,8.0,3,15,Rural,ML Engineer,75773,0 +93852,Male,33,Bachelors,2,80,54,77,3,6.0,4,74,Rural,Manager,130592,1 +93853,Male,54,Bachelors,16,63,21,79,91,0.0,4,16,Urban,ML Engineer,131143,0 +93854,Female,50,Diploma,16,31,25,71,76,4.0,6,51,Urban,Software Engineer,57501,0 +93855,Female,50,Diploma,4,86,65,82,79,4.0,7,88,Semi-Urban,ML Engineer,45258,1 +93856,Female,51,Masters,5,55,17,13,46,8.0,0,92,Urban,Software Engineer,129702,0 +93857,Male,25,Diploma,18,70,44,21,1,6.0,0,14,Urban,Data Analyst,137073,0 +93858,Female,47,Masters,7,33,75,85,50,5.0,5,97,Rural,Data Analyst,87337,1 +93859,Male,58,High School,15,53,15,44,29,9.0,5,57,Urban,Manager,62141,0 +93860,Female,31,Bachelors,11,75,72,35,63,6.0,0,99,Urban,Manager,80851,1 +93861,Male,34,Masters,9,28,31,94,70,9.0,3,24,Rural,Software Engineer,65285,0 +93862,Male,45,Bachelors,2,19,0,70,6,4.0,4,54,Urban,ML Engineer,41543,0 +93863,Female,42,Bachelors,1,92,23,46,85,9.0,7,18,Urban,Manager,110169,0 +93864,Male,35,High School,8,68,7,9,48,4.0,2,42,Semi-Urban,ML Engineer,141395,0 +93865,Female,41,PhD,16,99,99,26,9,8.0,1,15,Rural,Manager,35253,0 +93866,Other,21,PhD,10,97,88,29,24,0.0,5,6,Semi-Urban,Data Analyst,76792,0 +93867,Male,43,Bachelors,5,18,74,84,27,7.0,1,68,Urban,Data Analyst,24114,1 +93868,Male,44,High School,3,2,59,10,42,5.0,2,54,Urban,ML Engineer,94729,0 +93869,Male,24,Bachelors,15,59,9,72,19,0.0,3,23,Rural,HR Executive,111165,0 +93870,Male,47,Bachelors,2,8,98,16,80,0.0,6,25,Semi-Urban,Manager,146989,0 +93871,Male,21,Bachelors,6,73,1,33,19,9.0,3,3,Urban,Manager,81418,0 +93872,Female,42,Bachelors,17,78,54,48,74,2.0,1,67,Urban,Software Engineer,33859,1 +93873,Male,42,Bachelors,11,19,46,78,92,0.0,7,7,Rural,Software Engineer,134004,0 +93874,Other,52,Masters,18,63,1,25,97,6.0,1,46,Urban,Manager,46411,0 +93875,Female,57,Diploma,6,37,24,37,50,3.0,1,89,Semi-Urban,Software Engineer,138616,0 +93876,Male,29,Masters,9,91,84,88,15,0.0,1,38,Urban,Data Analyst,80805,1 +93877,Other,51,PhD,6,85,89,35,40,2.0,0,6,Urban,Software Engineer,70300,0 +93878,Male,39,Bachelors,6,96,17,19,35,2.0,6,60,Semi-Urban,HR Executive,75666,0 +93879,Female,56,High School,5,50,30,60,78,5.0,1,69,Urban,Data Analyst,58743,0 +93880,Female,34,Bachelors,14,38,23,71,95,8.0,4,53,Urban,Manager,43268,0 +93881,Male,35,Bachelors,17,84,69,81,7,9.0,0,84,Urban,ML Engineer,89989,1 +93882,Female,59,Diploma,5,68,57,12,9,7.0,0,74,Urban,HR Executive,111001,0 +93883,Female,21,Diploma,13,13,52,10,13,2.0,2,30,Urban,Manager,20725,0 +93884,Female,50,Masters,9,99,45,35,58,7.0,1,27,Semi-Urban,Software Engineer,142400,0 +93885,Female,39,Masters,6,83,5,28,66,8.0,4,19,Urban,Data Analyst,108518,0 +93886,Female,28,PhD,16,99,27,25,34,7.0,0,56,Rural,Manager,96756,0 +93887,Male,24,PhD,12,50,87,92,5,8.0,4,27,Urban,Software Engineer,111615,1 +93888,Male,23,Bachelors,16,88,52,20,28,2.0,7,55,Semi-Urban,ML Engineer,77574,0 +93889,Male,56,Diploma,9,76,98,37,87,6.0,3,70,Urban,HR Executive,99964,1 +93890,Male,41,Diploma,1,95,83,86,99,6.0,7,47,Urban,HR Executive,32018,1 +93891,Male,41,Bachelors,3,63,74,7,74,7.0,3,39,Rural,ML Engineer,118454,0 +93892,Male,41,Masters,18,80,61,80,24,4.0,5,56,Rural,Data Analyst,97282,1 +93893,Other,28,Bachelors,8,76,47,44,18,1.0,4,67,Semi-Urban,Data Analyst,142619,0 +93894,Female,54,Diploma,2,80,35,90,89,5.0,3,49,Semi-Urban,Data Analyst,62002,1 +93895,Male,25,Bachelors,4,24,13,92,33,2.0,3,5,Rural,HR Executive,110052,0 +93896,Female,49,Diploma,1,53,59,17,23,6.0,6,36,Urban,Data Analyst,101520,0 +93897,Male,57,Bachelors,15,84,56,10,52,4.0,1,52,Rural,ML Engineer,147850,0 +93898,Male,48,Masters,8,3,95,34,67,9.0,2,19,Urban,ML Engineer,143818,0 +93899,Female,33,High School,3,71,62,38,3,7.0,5,22,Rural,Software Engineer,73675,0 +93900,Female,45,Diploma,0,76,69,3,21,0.0,3,58,Urban,HR Executive,109373,0 +93901,Female,33,Masters,3,94,65,26,19,5.0,7,81,Urban,HR Executive,146864,1 +93902,Female,24,High School,9,35,68,6,92,1.0,1,2,Urban,HR Executive,23531,0 +93903,Male,38,Masters,14,67,71,11,99,4.0,6,32,Urban,Data Analyst,78919,0 +93904,Female,32,Bachelors,19,18,17,7,39,7.0,3,99,Urban,Software Engineer,133316,0 +93905,Male,41,Bachelors,2,27,57,59,28,9.0,1,55,Semi-Urban,Data Analyst,98755,0 +93906,Female,56,Bachelors,16,14,8,96,69,9.0,7,20,Urban,ML Engineer,136522,0 +93907,Male,34,Diploma,7,78,56,52,73,7.0,2,46,Rural,Manager,139297,0 +93908,Female,30,Masters,7,2,8,56,2,2.0,0,26,Semi-Urban,Software Engineer,120298,0 +93909,Female,55,Diploma,4,91,57,41,57,7.0,4,36,Rural,Data Analyst,72021,0 +93910,Male,32,Bachelors,19,82,48,66,84,2.0,5,8,Rural,Software Engineer,42635,0 +93911,Male,42,Diploma,4,3,80,49,52,0.0,3,2,Rural,Manager,129531,0 +93912,Male,40,High School,15,83,81,32,31,9.0,0,55,Semi-Urban,HR Executive,85010,1 +93913,Female,59,Masters,1,15,33,55,19,6.0,1,52,Rural,HR Executive,61016,0 +93914,Female,22,Masters,11,42,72,72,56,9.0,4,72,Urban,Data Analyst,65416,1 +93915,Male,22,Bachelors,17,90,6,49,43,7.0,1,75,Semi-Urban,Software Engineer,104772,0 +93916,Female,32,Diploma,5,24,52,97,17,4.0,2,65,Urban,Software Engineer,61359,0 +93917,Female,56,High School,7,47,34,49,81,9.0,5,56,Semi-Urban,Manager,106686,0 +93918,Male,53,Diploma,12,88,3,92,25,0.0,5,99,Urban,Manager,55484,1 +93919,Male,28,Bachelors,9,13,36,72,17,9.0,2,93,Urban,Software Engineer,43109,0 +93920,Male,46,High School,4,83,57,61,59,1.0,4,96,Urban,Software Engineer,132544,1 +93921,Male,23,Bachelors,15,48,7,11,16,4.0,5,67,Urban,HR Executive,132931,0 +93922,Female,41,High School,8,83,70,28,96,4.0,3,55,Urban,Manager,118963,0 +93923,Male,22,Bachelors,5,55,69,13,47,3.0,0,79,Urban,Software Engineer,80336,0 +93924,Male,29,Masters,7,52,29,94,7,0.0,3,2,Semi-Urban,HR Executive,83692,0 +93925,Female,50,Bachelors,14,82,38,22,55,0.0,3,95,Urban,Software Engineer,72426,0 +93926,Male,55,Bachelors,10,83,38,11,56,6.0,7,7,Urban,ML Engineer,114004,0 +93927,Male,41,High School,0,47,80,52,79,6.0,5,88,Semi-Urban,Software Engineer,96254,1 +93928,Male,44,High School,4,12,53,25,1,9.0,5,81,Urban,Data Analyst,21469,0 +93929,Female,55,Bachelors,5,94,59,25,90,6.0,7,5,Rural,Manager,62178,0 +93930,Female,57,High School,16,22,89,24,63,7.0,1,98,Urban,Software Engineer,94311,0 +93931,Female,21,Diploma,10,43,36,99,69,0.0,2,99,Rural,Data Analyst,72145,1 +93932,Male,44,Bachelors,16,36,24,0,86,2.0,4,2,Rural,ML Engineer,61049,0 +93933,Male,46,Diploma,5,46,64,86,37,7.0,2,42,Rural,Data Analyst,103966,1 +93934,Male,31,Bachelors,7,39,26,18,61,6.0,4,78,Urban,Manager,126160,0 +93935,Male,48,Bachelors,4,11,30,31,69,6.0,4,28,Urban,HR Executive,131073,0 +93936,Female,32,Bachelors,12,90,93,96,65,7.0,7,96,Rural,Manager,73962,1 +93937,Other,37,Diploma,13,81,77,99,46,6.0,3,19,Urban,Software Engineer,110503,1 +93938,Male,54,Bachelors,13,90,31,11,52,9.0,5,72,Urban,HR Executive,131328,0 +93939,Female,39,Bachelors,1,64,97,10,1,1.0,3,86,Urban,HR Executive,39313,1 +93940,Male,41,Masters,6,67,66,72,52,8.0,6,11,Rural,Data Analyst,84396,0 +93941,Male,52,Diploma,17,77,49,43,45,1.0,2,26,Urban,Manager,22046,0 +93942,Male,51,Diploma,2,60,61,30,86,7.0,5,1,Semi-Urban,Manager,34939,0 +93943,Male,57,Masters,14,73,18,83,1,2.0,7,5,Urban,HR Executive,96603,0 +93944,Male,50,Bachelors,10,37,68,95,12,4.0,3,79,Rural,Manager,55343,1 +93945,Other,31,Bachelors,8,16,37,31,98,4.0,4,33,Urban,Data Analyst,131106,0 +93946,Female,24,Diploma,16,55,61,35,84,1.0,7,37,Urban,HR Executive,133087,0 +93947,Male,36,Bachelors,18,71,4,61,80,3.0,1,24,Urban,HR Executive,77191,0 +93948,Male,36,Masters,1,75,96,5,24,9.0,3,93,Urban,HR Executive,95479,1 +93949,Male,28,Bachelors,4,5,91,99,54,9.0,2,89,Rural,ML Engineer,108412,1 +93950,Male,41,Bachelors,13,79,19,27,18,2.0,4,28,Semi-Urban,HR Executive,39566,0 +93951,Male,47,High School,6,59,69,1,33,0.0,6,94,Urban,Data Analyst,139294,0 +93952,Male,30,PhD,19,70,74,84,5,8.0,5,92,Urban,ML Engineer,20152,1 +93953,Male,46,Bachelors,13,50,8,28,62,7.0,2,81,Semi-Urban,Data Analyst,116650,0 +93954,Female,55,Masters,11,40,58,63,36,1.0,6,72,Urban,ML Engineer,148482,0 +93955,Female,46,Masters,2,41,51,64,23,7.0,3,60,Urban,Data Analyst,94502,0 +93956,Male,51,Bachelors,2,50,57,93,67,1.0,1,23,Urban,Manager,111368,0 +93957,Female,58,Bachelors,14,43,36,5,8,6.0,4,72,Urban,HR Executive,44143,0 +93958,Male,23,Bachelors,8,92,30,58,45,9.0,7,20,Semi-Urban,HR Executive,122069,0 +93959,Female,48,Masters,1,10,61,29,23,0.0,2,46,Rural,Software Engineer,143479,0 +93960,Male,48,High School,1,19,23,26,72,8.0,5,90,Urban,Data Analyst,83908,0 +93961,Male,42,Bachelors,13,50,20,88,23,9.0,3,47,Rural,Manager,44370,0 +93962,Male,56,Masters,17,37,23,87,97,8.0,0,41,Semi-Urban,Software Engineer,106391,0 +93963,Male,44,Bachelors,13,3,67,81,51,6.0,4,75,Urban,HR Executive,66072,0 +93964,Female,23,Masters,4,23,44,96,56,1.0,7,11,Urban,HR Executive,62051,0 +93965,Male,34,Diploma,18,75,32,25,67,5.0,1,88,Urban,Manager,109469,0 +93966,Male,32,Bachelors,3,80,25,36,76,8.0,2,20,Urban,ML Engineer,35709,0 +93967,Male,43,Bachelors,12,31,3,42,22,8.0,3,2,Urban,Data Analyst,102155,0 +93968,Female,34,Bachelors,2,17,95,79,34,8.0,7,29,Semi-Urban,ML Engineer,109158,0 +93969,Female,45,Diploma,6,30,16,75,86,0.0,0,4,Rural,Software Engineer,113813,0 +93970,Other,48,Bachelors,17,79,72,11,99,4.0,5,48,Urban,HR Executive,54464,0 +93971,Female,35,Diploma,10,72,56,91,78,5.0,3,25,Urban,HR Executive,131248,1 +93972,Male,51,PhD,16,56,68,43,96,5.0,4,53,Semi-Urban,ML Engineer,117993,0 +93973,Male,25,Diploma,19,47,28,76,74,4.0,6,15,Semi-Urban,ML Engineer,107634,0 +93974,Male,48,Diploma,0,99,35,92,85,8.0,1,69,Urban,HR Executive,76099,1 +93975,Female,44,High School,3,39,57,31,13,6.0,2,49,Urban,Data Analyst,64143,0 +93976,Female,36,High School,11,27,85,28,6,7.0,5,20,Semi-Urban,Software Engineer,22693,0 +93977,Female,25,Bachelors,16,43,88,24,21,8.0,7,57,Urban,Data Analyst,87971,0 +93978,Male,50,Masters,10,55,33,65,61,0.0,7,35,Urban,ML Engineer,94495,0 +93979,Male,43,Bachelors,8,49,55,57,65,8.0,0,15,Semi-Urban,Software Engineer,120553,0 +93980,Female,23,High School,7,46,93,3,35,9.0,4,91,Urban,HR Executive,35323,0 +93981,Female,54,High School,4,83,74,68,18,1.0,6,62,Urban,Data Analyst,149668,1 +93982,Female,27,Bachelors,6,38,58,44,84,4.0,6,90,Urban,Data Analyst,47996,0 +93983,Male,23,Bachelors,6,64,0,74,16,1.0,4,20,Urban,ML Engineer,61799,0 +93984,Male,53,Bachelors,9,59,95,30,84,8.0,0,55,Urban,Software Engineer,101072,1 +93985,Female,27,Masters,13,16,64,44,63,9.0,5,37,Urban,Software Engineer,89777,0 +93986,Male,23,Bachelors,17,67,60,50,72,4.0,2,20,Urban,HR Executive,127850,0 +93987,Female,35,Bachelors,2,60,43,10,88,4.0,5,33,Rural,Data Analyst,137967,0 +93988,Male,58,High School,19,82,62,26,8,8.0,5,18,Urban,Manager,121324,0 +93989,Male,49,Masters,0,8,99,90,2,9.0,0,20,Semi-Urban,ML Engineer,67066,0 +93990,Male,21,Bachelors,10,56,93,75,3,8.0,6,95,Rural,Software Engineer,110781,1 +93991,Female,23,Bachelors,6,89,31,8,61,5.0,2,94,Urban,Data Analyst,32391,0 +93992,Male,46,Bachelors,12,57,79,23,7,7.0,7,50,Urban,Manager,38202,0 +93993,Female,44,High School,10,76,60,90,89,4.0,6,65,Urban,HR Executive,110236,1 +93994,Male,30,PhD,1,87,53,84,20,0.0,7,7,Semi-Urban,Data Analyst,48436,0 +93995,Male,58,Masters,15,45,55,15,97,9.0,2,2,Urban,ML Engineer,43249,0 +93996,Female,38,High School,2,93,60,96,94,6.0,7,54,Urban,ML Engineer,128255,1 +93997,Female,43,Diploma,2,4,14,59,0,6.0,1,66,Rural,Software Engineer,89088,0 +93998,Female,37,Masters,12,41,38,14,38,3.0,6,89,Semi-Urban,Data Analyst,102186,0 +93999,Male,26,High School,7,52,57,26,25,9.0,1,70,Urban,Software Engineer,121069,0 +94000,Male,25,Bachelors,19,3,4,27,74,6.0,4,50,Semi-Urban,ML Engineer,57094,0 +94001,Male,43,Bachelors,19,35,71,89,16,4.0,3,33,Urban,Data Analyst,96109,0 +94002,Male,22,Diploma,12,12,75,30,67,7.0,4,7,Semi-Urban,Software Engineer,51685,0 +94003,Male,57,Diploma,10,85,98,12,73,8.0,6,1,Semi-Urban,Data Analyst,97469,0 +94004,Female,41,High School,14,5,38,74,79,4.0,5,24,Urban,Manager,68505,0 +94005,Male,22,Diploma,9,0,58,89,39,8.0,6,40,Urban,HR Executive,95654,0 +94006,Female,34,Bachelors,18,19,78,49,71,1.0,1,44,Urban,ML Engineer,79317,0 +94007,Male,49,PhD,12,34,28,89,21,2.0,4,9,Urban,Software Engineer,68324,0 +94008,Female,29,Bachelors,11,6,53,94,54,7.0,7,31,Urban,Software Engineer,65965,0 +94009,Female,51,Diploma,12,42,80,0,34,9.0,3,24,Rural,Software Engineer,90701,0 +94010,Male,24,Diploma,10,60,24,10,99,8.0,5,3,Semi-Urban,HR Executive,75220,0 +94011,Female,25,Masters,19,47,73,36,42,7.0,1,35,Urban,Manager,45025,0 +94012,Female,38,Masters,1,30,66,68,77,4.0,0,15,Urban,Data Analyst,102429,0 +94013,Female,23,Masters,15,69,15,74,18,4.0,3,59,Urban,Manager,68367,0 +94014,Male,32,Diploma,18,32,8,42,45,7.0,2,64,Semi-Urban,HR Executive,72255,0 +94015,Female,39,Bachelors,14,93,41,78,64,6.0,5,85,Urban,Manager,111710,1 +94016,Male,50,Bachelors,5,93,75,86,45,4.0,0,5,Semi-Urban,Manager,113085,1 +94017,Male,50,Diploma,1,56,72,17,92,8.0,1,21,Rural,Software Engineer,92691,0 +94018,Male,59,Diploma,16,46,25,8,83,2.0,0,65,Semi-Urban,Data Analyst,78222,0 +94019,Male,30,Bachelors,11,92,20,19,99,2.0,2,4,Urban,Manager,141791,0 +94020,Male,21,High School,5,37,1,28,17,8.0,4,24,Semi-Urban,Software Engineer,28433,0 +94021,Male,50,PhD,0,3,14,71,85,4.0,5,60,Urban,Data Analyst,50018,0 +94022,Male,52,Bachelors,14,23,9,45,19,0.0,1,30,Urban,ML Engineer,109905,0 +94023,Male,26,Diploma,4,55,52,34,83,1.0,7,66,Urban,HR Executive,66146,0 +94024,Male,37,Bachelors,5,34,23,40,75,9.0,5,32,Urban,ML Engineer,76320,0 +94025,Male,22,High School,3,13,32,85,39,2.0,4,15,Urban,Software Engineer,90154,0 +94026,Female,39,Diploma,9,17,28,56,86,6.0,1,37,Urban,ML Engineer,40320,0 +94027,Male,21,Diploma,17,4,4,87,42,3.0,2,70,Urban,Manager,76561,0 +94028,Female,26,Bachelors,13,81,33,27,64,5.0,2,35,Semi-Urban,Data Analyst,52515,0 +94029,Male,57,High School,13,66,49,53,7,2.0,5,22,Urban,Data Analyst,28902,0 +94030,Female,34,High School,12,52,57,69,14,7.0,2,9,Urban,Software Engineer,84888,0 +94031,Male,23,Masters,2,56,70,52,76,8.0,7,34,Urban,Software Engineer,97462,0 +94032,Male,54,Masters,11,79,21,74,66,6.0,1,5,Urban,Software Engineer,95609,0 +94033,Other,55,PhD,15,42,29,64,6,0.0,6,93,Rural,Manager,92221,0 +94034,Female,30,Bachelors,19,15,78,56,88,5.0,5,77,Urban,Software Engineer,76812,0 +94035,Male,35,Masters,7,49,2,30,80,8.0,7,81,Semi-Urban,HR Executive,116215,0 +94036,Female,30,Diploma,15,4,25,58,53,8.0,2,20,Rural,HR Executive,58524,0 +94037,Female,53,High School,11,66,53,97,47,1.0,5,34,Urban,ML Engineer,133623,1 +94038,Male,41,Diploma,7,95,7,73,46,5.0,4,84,Urban,Manager,112237,1 +94039,Other,29,High School,1,44,14,80,70,6.0,4,28,Rural,Manager,42372,0 +94040,Male,39,Masters,10,18,89,6,71,6.0,4,87,Urban,Manager,115108,0 +94041,Female,30,Masters,9,50,54,83,13,5.0,0,5,Urban,ML Engineer,111919,0 +94042,Female,22,Bachelors,0,92,18,20,87,5.0,1,61,Rural,Software Engineer,49708,0 +94043,Male,32,High School,2,68,47,1,0,6.0,4,87,Urban,Data Analyst,113936,0 +94044,Female,28,PhD,2,35,13,43,9,4.0,7,15,Urban,Data Analyst,141822,0 +94045,Female,51,High School,1,24,25,57,13,4.0,2,11,Urban,HR Executive,46089,0 +94046,Female,53,Masters,18,15,5,6,44,9.0,5,13,Urban,Data Analyst,21948,0 +94047,Female,21,Diploma,15,62,95,94,43,2.0,1,11,Urban,Data Analyst,142609,1 +94048,Male,27,High School,14,85,77,62,81,6.0,7,41,Rural,HR Executive,139120,1 +94049,Male,38,Masters,8,8,48,88,56,3.0,5,52,Urban,Manager,21881,0 +94050,Female,34,Diploma,3,26,35,87,25,9.0,7,32,Urban,HR Executive,119106,0 +94051,Female,56,Bachelors,18,66,98,99,31,4.0,1,2,Semi-Urban,Manager,34658,1 +94052,Male,57,Masters,5,12,46,62,83,3.0,6,86,Rural,Manager,46607,0 +94053,Female,28,Bachelors,4,60,11,87,0,1.0,2,43,Semi-Urban,Manager,120913,0 +94054,Female,41,Masters,16,1,47,81,49,8.0,5,84,Semi-Urban,Software Engineer,36130,0 +94055,Female,57,Bachelors,12,14,28,72,56,7.0,2,37,Urban,Software Engineer,78496,0 +94056,Male,56,Masters,1,63,60,77,81,5.0,3,52,Semi-Urban,ML Engineer,62982,1 +94057,Male,48,PhD,2,6,97,4,92,4.0,7,42,Urban,Manager,54611,0 +94058,Other,54,Bachelors,10,11,47,98,2,7.0,6,64,Urban,ML Engineer,93235,0 +94059,Female,45,Diploma,7,66,91,13,13,9.0,7,23,Urban,Software Engineer,140196,0 +94060,Male,58,PhD,13,35,91,41,61,1.0,4,71,Urban,HR Executive,121223,1 +94061,Female,36,Masters,4,35,8,15,79,9.0,4,23,Urban,ML Engineer,128712,0 +94062,Male,57,Masters,7,88,21,38,48,0.0,7,18,Semi-Urban,Software Engineer,136620,0 +94063,Male,51,Bachelors,3,35,2,96,88,5.0,1,42,Rural,HR Executive,72718,0 +94064,Male,30,High School,13,32,3,23,75,7.0,6,42,Rural,Software Engineer,125500,0 +94065,Other,50,Diploma,11,35,16,80,40,4.0,3,85,Semi-Urban,Data Analyst,43661,0 +94066,Male,43,Masters,14,58,44,88,93,5.0,1,68,Urban,Software Engineer,106237,1 +94067,Male,26,Masters,13,60,30,72,91,7.0,5,6,Urban,Data Analyst,40616,0 +94068,Male,26,Bachelors,11,73,39,2,64,8.0,6,33,Urban,Software Engineer,67090,0 +94069,Female,39,Bachelors,10,19,65,23,68,3.0,3,23,Rural,Software Engineer,21187,0 +94070,Male,28,Diploma,17,48,70,46,68,9.0,4,48,Rural,Software Engineer,103116,0 +94071,Male,35,Bachelors,6,49,35,75,7,0.0,2,42,Urban,Software Engineer,49386,0 +94072,Female,56,Bachelors,6,22,36,84,92,6.0,6,23,Semi-Urban,ML Engineer,72727,0 +94073,Male,42,Masters,16,36,63,77,76,9.0,0,84,Urban,HR Executive,83089,1 +94074,Female,30,High School,6,1,1,27,52,5.0,2,86,Urban,ML Engineer,98688,0 +94075,Other,47,Bachelors,7,16,91,78,98,4.0,0,44,Urban,Data Analyst,121895,0 +94076,Other,39,PhD,7,2,23,78,79,4.0,2,44,Semi-Urban,Manager,72493,0 +94077,Male,29,Masters,13,2,48,37,37,7.0,2,42,Urban,ML Engineer,125928,0 +94078,Male,30,Bachelors,15,25,3,80,0,5.0,4,15,Rural,HR Executive,64657,0 +94079,Male,42,High School,14,3,61,79,23,7.0,3,2,Semi-Urban,ML Engineer,58820,0 +94080,Female,21,Bachelors,12,95,32,86,82,0.0,4,91,Urban,Manager,55422,1 +94081,Male,52,Masters,17,19,31,36,37,3.0,6,54,Rural,HR Executive,108018,0 +94082,Male,43,Diploma,14,11,58,46,19,7.0,5,13,Urban,HR Executive,148261,0 +94083,Female,37,Masters,14,27,7,16,38,6.0,6,41,Semi-Urban,Data Analyst,44093,0 +94084,Female,23,Masters,1,94,82,72,54,2.0,3,97,Semi-Urban,HR Executive,33297,1 +94085,Male,52,Bachelors,5,18,40,37,49,3.0,4,20,Urban,Software Engineer,60447,0 +94086,Male,22,High School,0,3,77,90,59,0.0,0,83,Rural,Manager,41733,1 +94087,Female,52,Bachelors,2,79,93,2,37,5.0,6,28,Semi-Urban,HR Executive,39287,0 +94088,Male,31,Masters,9,62,83,11,5,7.0,3,18,Rural,Data Analyst,108448,0 +94089,Male,55,Masters,10,10,88,78,62,5.0,0,59,Urban,ML Engineer,130348,1 +94090,Female,39,Masters,8,83,96,22,48,6.0,5,36,Semi-Urban,Manager,106512,0 +94091,Male,44,Diploma,16,27,70,35,85,5.0,5,40,Urban,Data Analyst,74974,0 +94092,Female,55,Bachelors,8,43,7,96,57,3.0,0,94,Rural,Data Analyst,146473,0 +94093,Other,58,Bachelors,8,49,5,85,81,8.0,3,15,Semi-Urban,Data Analyst,106499,0 +94094,Female,51,Bachelors,11,24,89,11,76,6.0,0,63,Urban,HR Executive,105867,0 +94095,Male,38,Bachelors,14,68,76,94,98,6.0,3,38,Urban,Software Engineer,104038,1 +94096,Female,56,Bachelors,3,34,53,50,30,2.0,3,73,Semi-Urban,Data Analyst,149352,0 +94097,Male,26,Masters,9,88,79,41,12,9.0,3,95,Semi-Urban,Data Analyst,116685,1 +94098,Male,25,Diploma,16,41,60,76,55,7.0,2,29,Urban,Manager,101936,0 +94099,Female,35,Masters,4,45,75,74,81,0.0,4,33,Urban,Data Analyst,69796,0 +94100,Male,48,PhD,0,91,71,90,31,4.0,3,67,Semi-Urban,ML Engineer,94017,1 +94101,Male,28,Masters,18,89,6,39,75,3.0,4,61,Urban,Software Engineer,126043,0 +94102,Male,42,Diploma,6,94,91,78,89,9.0,7,41,Urban,Manager,103876,1 +94103,Male,28,Diploma,14,33,80,96,72,0.0,3,97,Rural,Manager,110999,1 +94104,Male,24,Bachelors,12,79,68,43,96,4.0,1,28,Rural,Software Engineer,28674,0 +94105,Male,50,Bachelors,4,3,23,98,68,4.0,0,73,Urban,Software Engineer,70666,0 +94106,Female,52,Diploma,14,7,61,63,59,3.0,0,71,Urban,Software Engineer,100570,0 +94107,Female,23,Bachelors,10,78,0,85,73,1.0,1,62,Rural,Manager,124139,0 +94108,Male,22,Masters,18,47,66,17,13,4.0,6,31,Urban,Software Engineer,47783,0 +94109,Male,54,Bachelors,15,49,6,58,55,3.0,1,5,Urban,ML Engineer,104728,0 +94110,Female,35,Bachelors,9,46,58,14,15,0.0,5,49,Urban,Manager,70462,0 +94111,Female,21,Diploma,0,79,47,49,41,3.0,7,12,Semi-Urban,Software Engineer,120307,0 +94112,Male,48,Bachelors,16,36,57,57,21,0.0,4,53,Semi-Urban,HR Executive,141258,0 +94113,Female,43,Bachelors,0,91,44,18,85,5.0,1,8,Rural,Data Analyst,50397,0 +94114,Male,51,Masters,14,67,19,89,17,5.0,2,68,Rural,Software Engineer,115508,1 +94115,Male,27,Bachelors,9,70,22,90,24,9.0,7,96,Rural,HR Executive,26634,1 +94116,Male,45,Diploma,1,89,44,82,65,9.0,2,57,Urban,ML Engineer,149514,1 +94117,Male,54,Bachelors,10,14,31,87,58,0.0,1,45,Semi-Urban,Manager,121907,0 +94118,Male,55,High School,18,86,68,31,19,9.0,6,32,Urban,Manager,63422,0 +94119,Male,37,Diploma,17,70,21,2,40,7.0,7,18,Urban,Software Engineer,74019,0 +94120,Male,54,Masters,6,19,96,80,8,1.0,7,91,Rural,Data Analyst,133324,1 +94121,Male,22,Diploma,0,23,71,92,2,5.0,6,87,Semi-Urban,HR Executive,100634,1 +94122,Female,22,Bachelors,6,23,7,86,15,7.0,4,31,Rural,Data Analyst,133633,0 +94123,Female,56,High School,18,7,72,94,85,1.0,6,43,Urban,Data Analyst,42836,0 +94124,Male,35,Masters,6,36,99,7,87,0.0,6,71,Urban,Data Analyst,47222,0 +94125,Male,39,Bachelors,9,0,26,13,9,8.0,3,22,Urban,Data Analyst,131578,0 +94126,Male,40,Bachelors,15,88,65,42,17,6.0,1,44,Urban,Data Analyst,77150,1 +94127,Female,31,Diploma,18,30,94,59,19,9.0,7,1,Urban,HR Executive,42009,0 +94128,Male,47,Bachelors,10,64,4,86,58,1.0,5,70,Urban,HR Executive,42419,0 +94129,Male,39,High School,11,49,70,37,45,3.0,7,69,Urban,Manager,61501,0 +94130,Female,45,High School,19,79,86,45,8,8.0,5,44,Urban,HR Executive,118659,1 +94131,Male,24,Diploma,19,32,95,88,94,0.0,0,62,Urban,Software Engineer,85435,1 +94132,Male,37,Masters,0,53,19,80,1,4.0,4,12,Semi-Urban,Data Analyst,95903,0 +94133,Male,59,Diploma,14,8,40,79,31,5.0,0,14,Urban,Data Analyst,130041,0 +94134,Male,49,High School,7,4,55,82,48,1.0,7,4,Urban,ML Engineer,134860,0 +94135,Male,44,PhD,17,53,70,5,62,1.0,3,80,Semi-Urban,Manager,62580,0 +94136,Male,43,Diploma,0,96,97,91,24,6.0,1,51,Urban,Software Engineer,85013,1 +94137,Male,58,High School,18,4,76,88,84,4.0,3,38,Urban,Data Analyst,146909,0 +94138,Male,26,High School,9,24,52,28,13,1.0,5,71,Urban,HR Executive,53999,0 +94139,Male,36,Bachelors,5,35,34,89,49,8.0,6,66,Semi-Urban,ML Engineer,46427,0 +94140,Male,32,Bachelors,5,12,33,49,97,7.0,5,57,Urban,ML Engineer,110615,0 +94141,Male,29,Bachelors,17,57,77,61,73,2.0,5,51,Semi-Urban,ML Engineer,94311,1 +94142,Male,42,Diploma,4,96,79,59,37,2.0,1,97,Semi-Urban,Data Analyst,111648,1 +94143,Male,30,Bachelors,1,24,92,15,69,1.0,6,12,Urban,Software Engineer,90133,0 +94144,Male,50,Bachelors,7,5,87,51,69,8.0,4,5,Semi-Urban,Software Engineer,99572,0 +94145,Male,54,Bachelors,9,75,56,69,17,8.0,5,72,Rural,HR Executive,74945,1 +94146,Female,42,High School,0,88,21,19,1,8.0,4,76,Urban,HR Executive,69092,0 +94147,Male,27,Masters,18,64,16,84,23,1.0,7,72,Semi-Urban,Data Analyst,146902,1 +94148,Female,38,Bachelors,13,70,48,95,3,3.0,6,96,Urban,HR Executive,147255,1 +94149,Male,32,High School,7,37,50,55,5,3.0,5,83,Semi-Urban,Manager,73385,0 +94150,Female,49,Bachelors,6,25,1,99,67,7.0,2,78,Urban,ML Engineer,61166,0 +94151,Male,27,Bachelors,2,72,12,55,69,3.0,7,45,Urban,Data Analyst,49237,0 +94152,Male,57,Bachelors,17,93,42,86,81,6.0,5,76,Semi-Urban,Data Analyst,79103,1 +94153,Male,51,Bachelors,4,86,46,12,11,0.0,3,0,Urban,HR Executive,54330,0 +94154,Male,41,Bachelors,18,4,31,19,20,4.0,4,15,Rural,ML Engineer,71967,0 +94155,Male,54,Bachelors,11,89,64,67,6,5.0,0,63,Rural,Data Analyst,22829,1 +94156,Male,26,High School,11,98,31,17,16,4.0,6,94,Rural,Data Analyst,147456,1 +94157,Male,32,High School,13,87,51,27,17,3.0,6,32,Rural,ML Engineer,96330,0 +94158,Male,29,Diploma,18,29,97,48,76,4.0,1,5,Rural,ML Engineer,105272,0 +94159,Female,28,Diploma,13,43,48,16,40,5.0,6,79,Rural,Manager,113373,0 +94160,Female,39,Diploma,18,77,78,34,93,2.0,7,66,Rural,Data Analyst,78115,1 +94161,Male,36,Diploma,9,9,17,96,85,9.0,3,42,Rural,Software Engineer,80384,0 +94162,Female,43,High School,10,51,94,10,83,7.0,3,20,Urban,Manager,22092,0 +94163,Female,25,Bachelors,18,32,82,23,44,2.0,6,47,Urban,Data Analyst,102484,0 +94164,Male,34,Bachelors,11,19,53,76,2,5.0,6,54,Urban,Manager,43636,0 +94165,Male,50,Bachelors,18,59,99,83,14,3.0,2,96,Semi-Urban,Manager,112217,1 +94166,Female,47,Masters,13,49,27,74,72,6.0,4,69,Rural,Manager,149274,0 +94167,Female,48,Masters,6,50,42,4,12,0.0,5,42,Urban,Data Analyst,121235,0 +94168,Male,37,Bachelors,12,92,75,85,25,0.0,5,34,Semi-Urban,Manager,129144,1 +94169,Male,46,Bachelors,13,51,72,67,51,6.0,5,86,Urban,Software Engineer,127704,1 +94170,Female,51,Masters,15,58,35,56,0,0.0,0,86,Rural,ML Engineer,115785,0 +94171,Male,49,Bachelors,9,2,98,61,11,9.0,6,47,Urban,Software Engineer,80192,0 +94172,Female,30,Bachelors,10,9,98,40,45,3.0,0,15,Semi-Urban,ML Engineer,142684,0 +94173,Male,37,Diploma,2,37,39,48,64,9.0,0,97,Urban,ML Engineer,129208,0 +94174,Female,53,High School,10,35,80,16,84,8.0,2,98,Rural,ML Engineer,27168,0 +94175,Female,41,Diploma,10,72,8,88,90,6.0,6,7,Urban,Software Engineer,60824,0 +94176,Female,49,Diploma,3,65,5,80,55,4.0,0,4,Urban,ML Engineer,136669,0 +94177,Male,42,Masters,5,18,85,70,81,3.0,5,6,Urban,ML Engineer,81148,0 +94178,Male,46,Bachelors,13,25,87,79,18,6.0,1,74,Semi-Urban,Software Engineer,131593,1 +94179,Male,48,Bachelors,16,35,12,40,54,1.0,0,2,Urban,Software Engineer,46485,0 +94180,Male,27,Masters,5,52,72,77,16,3.0,6,5,Urban,Data Analyst,120411,0 +94181,Male,52,Bachelors,5,24,67,21,57,3.0,7,77,Urban,Manager,35307,0 +94182,Female,50,Bachelors,2,67,65,88,21,6.0,5,57,Urban,Manager,93593,1 +94183,Male,32,Masters,5,89,82,51,30,9.0,0,6,Urban,Manager,84486,0 +94184,Male,49,Bachelors,7,43,92,32,66,3.0,4,24,Rural,ML Engineer,47164,0 +94185,Female,34,Bachelors,2,27,36,96,67,8.0,2,88,Urban,HR Executive,37307,1 +94186,Male,41,Diploma,10,21,14,4,53,3.0,4,48,Semi-Urban,HR Executive,36475,0 +94187,Male,22,PhD,7,67,60,84,50,5.0,1,91,Rural,Software Engineer,61385,1 +94188,Female,23,Masters,8,66,13,45,32,9.0,0,64,Semi-Urban,Software Engineer,149192,0 +94189,Male,36,Bachelors,12,8,7,0,50,6.0,4,68,Urban,Manager,39763,0 +94190,Male,57,Diploma,13,9,83,31,35,5.0,1,10,Semi-Urban,Manager,128808,0 +94191,Male,29,Bachelors,6,36,77,56,38,2.0,5,82,Semi-Urban,Manager,138667,1 +94192,Female,49,Bachelors,1,42,82,28,92,5.0,0,61,Urban,HR Executive,85630,0 +94193,Female,21,Bachelors,18,91,29,6,88,4.0,4,89,Rural,Software Engineer,114981,0 +94194,Male,33,Bachelors,1,3,67,36,80,7.0,7,31,Urban,Software Engineer,72510,0 +94195,Female,41,Diploma,18,56,78,81,57,7.0,2,63,Urban,Software Engineer,71278,1 +94196,Male,38,High School,3,36,18,7,35,5.0,6,7,Rural,ML Engineer,59572,0 +94197,Male,57,Bachelors,6,0,34,37,92,1.0,7,72,Rural,Software Engineer,36430,0 +94198,Other,50,Bachelors,4,4,43,29,59,1.0,3,39,Urban,HR Executive,48882,0 +94199,Male,24,Diploma,11,55,80,39,8,7.0,2,41,Rural,Manager,80542,0 +94200,Female,47,Bachelors,6,34,96,59,2,8.0,0,42,Urban,Manager,54272,0 +94201,Female,40,Masters,7,33,1,60,67,3.0,6,42,Semi-Urban,ML Engineer,121205,0 +94202,Male,52,Diploma,18,3,53,68,39,3.0,5,96,Urban,Manager,56885,0 +94203,Other,51,Masters,3,4,89,43,3,5.0,7,56,Semi-Urban,ML Engineer,47103,0 +94204,Male,57,Diploma,10,70,15,22,23,1.0,4,35,Urban,ML Engineer,80204,0 +94205,Other,36,PhD,8,77,51,10,76,3.0,1,3,Urban,HR Executive,145840,0 +94206,Male,47,Diploma,13,11,52,0,15,4.0,6,84,Semi-Urban,Data Analyst,40774,0 +94207,Male,55,Masters,2,27,78,65,80,2.0,7,19,Semi-Urban,HR Executive,89151,0 +94208,Female,32,Bachelors,1,98,64,18,62,1.0,1,6,Semi-Urban,Software Engineer,52184,0 +94209,Male,24,High School,17,13,8,11,51,1.0,6,19,Urban,Manager,97602,0 +94210,Male,52,Masters,0,50,67,54,11,4.0,5,5,Rural,HR Executive,58853,0 +94211,Male,53,Diploma,18,24,98,57,45,4.0,0,7,Semi-Urban,Software Engineer,44562,0 +94212,Other,55,Diploma,5,34,60,74,59,5.0,3,16,Semi-Urban,Software Engineer,111576,0 +94213,Male,59,Bachelors,8,0,37,35,6,7.0,5,95,Urban,Manager,80350,0 +94214,Female,21,High School,15,65,93,31,72,9.0,4,34,Urban,Software Engineer,140982,0 +94215,Other,35,Diploma,18,39,91,50,84,1.0,6,81,Semi-Urban,HR Executive,95649,1 +94216,Male,50,Diploma,3,20,92,90,17,0.0,1,87,Rural,HR Executive,96399,1 +94217,Female,45,Masters,16,15,10,44,13,8.0,5,13,Urban,Data Analyst,141521,0 +94218,Male,53,Diploma,1,18,17,85,45,7.0,7,26,Semi-Urban,Manager,81102,0 +94219,Female,56,Diploma,19,37,9,44,16,3.0,0,50,Rural,HR Executive,39087,0 +94220,Male,30,High School,15,61,16,69,42,9.0,5,44,Urban,Software Engineer,140749,0 +94221,Male,55,High School,1,44,10,11,13,0.0,4,92,Urban,Software Engineer,47294,0 +94222,Female,43,Diploma,4,89,55,16,74,7.0,0,34,Urban,HR Executive,91215,0 +94223,Female,34,Bachelors,0,94,60,37,81,1.0,3,47,Rural,Manager,107419,0 +94224,Male,31,Diploma,18,47,22,11,37,5.0,7,45,Semi-Urban,Software Engineer,79478,0 +94225,Male,55,Bachelors,0,56,26,82,0,4.0,0,42,Urban,Software Engineer,43121,0 +94226,Male,41,Diploma,0,50,86,69,57,3.0,5,18,Urban,ML Engineer,88160,0 +94227,Female,29,PhD,10,33,96,35,14,0.0,4,8,Urban,ML Engineer,86188,0 +94228,Female,42,High School,6,38,15,37,97,5.0,6,62,Urban,Manager,28126,0 +94229,Male,52,Diploma,9,81,28,73,0,6.0,3,4,Urban,HR Executive,72311,0 +94230,Male,45,Masters,10,46,26,30,66,3.0,0,33,Semi-Urban,Manager,51011,0 +94231,Female,54,Masters,7,69,15,46,31,5.0,7,29,Rural,ML Engineer,69220,0 +94232,Female,49,High School,0,24,88,97,71,7.0,5,65,Rural,ML Engineer,115964,1 +94233,Male,37,Bachelors,2,14,45,26,26,1.0,5,10,Semi-Urban,HR Executive,113647,0 +94234,Male,21,Diploma,0,15,33,39,90,4.0,6,60,Urban,ML Engineer,56004,0 +94235,Male,35,Diploma,16,71,56,30,45,1.0,7,19,Urban,ML Engineer,74325,0 +94236,Male,39,Bachelors,7,85,7,63,58,1.0,7,53,Rural,Manager,112645,0 +94237,Female,37,Masters,13,20,61,92,88,1.0,0,88,Semi-Urban,Data Analyst,45952,1 +94238,Male,30,Bachelors,16,3,67,9,26,3.0,6,85,Semi-Urban,Manager,20824,0 +94239,Male,31,Diploma,8,34,88,82,13,8.0,0,44,Rural,HR Executive,137456,1 +94240,Male,24,Masters,4,24,89,89,88,2.0,4,54,Urban,ML Engineer,101710,1 +94241,Female,52,Bachelors,10,28,46,65,81,2.0,0,76,Urban,ML Engineer,107319,0 +94242,Female,22,Bachelors,1,61,69,38,95,5.0,6,12,Urban,Software Engineer,65216,0 +94243,Male,59,Diploma,16,72,9,8,34,7.0,0,86,Urban,Software Engineer,91512,0 +94244,Male,38,Bachelors,12,66,65,17,41,9.0,2,99,Urban,HR Executive,76546,1 +94245,Female,28,Bachelors,12,62,20,89,57,3.0,1,56,Semi-Urban,ML Engineer,58968,0 +94246,Male,44,Diploma,3,14,36,99,93,8.0,4,85,Rural,Data Analyst,104474,0 +94247,Male,25,Masters,13,59,70,80,68,6.0,5,76,Urban,Manager,88078,1 +94248,Female,43,Diploma,15,57,16,21,0,7.0,1,48,Urban,Data Analyst,86295,0 +94249,Female,53,Bachelors,18,38,43,32,5,5.0,1,10,Urban,HR Executive,136862,0 +94250,Male,40,Bachelors,19,73,16,52,66,8.0,2,45,Urban,Manager,126816,0 +94251,Male,58,Masters,18,98,12,26,96,0.0,0,32,Semi-Urban,ML Engineer,145997,0 +94252,Female,39,Bachelors,8,14,12,76,8,5.0,0,99,Rural,HR Executive,72682,0 +94253,Male,39,High School,9,0,7,72,36,4.0,7,55,Semi-Urban,Data Analyst,126837,0 +94254,Female,36,Bachelors,16,75,55,98,46,5.0,7,23,Urban,Software Engineer,37148,1 +94255,Male,38,Diploma,18,43,7,43,6,9.0,7,77,Urban,Data Analyst,127026,0 +94256,Male,53,High School,18,18,97,1,72,1.0,7,43,Urban,Software Engineer,74977,0 +94257,Female,50,Bachelors,1,45,63,90,62,6.0,1,51,Urban,ML Engineer,93238,1 +94258,Male,47,Bachelors,0,99,53,18,59,9.0,6,72,Rural,ML Engineer,52857,1 +94259,Male,35,Bachelors,7,33,21,82,92,2.0,1,53,Semi-Urban,Manager,108800,0 +94260,Male,52,Masters,6,53,6,21,19,8.0,0,2,Rural,Data Analyst,146456,0 +94261,Female,51,Masters,4,76,64,49,24,3.0,5,95,Urban,Data Analyst,117644,1 +94262,Male,36,High School,18,28,33,25,44,6.0,5,11,Semi-Urban,ML Engineer,35445,0 +94263,Male,45,High School,14,78,30,99,19,9.0,1,61,Rural,Manager,60430,1 +94264,Female,55,Bachelors,3,41,79,60,2,1.0,6,65,Rural,Manager,98950,1 +94265,Female,48,Bachelors,16,63,26,49,21,7.0,6,51,Urban,Manager,43145,0 +94266,Female,30,Masters,4,73,22,54,32,9.0,4,1,Urban,Software Engineer,22518,0 +94267,Male,47,Diploma,17,79,52,85,90,1.0,0,20,Urban,Manager,86981,1 +94268,Male,58,Diploma,14,31,42,42,38,7.0,6,48,Semi-Urban,ML Engineer,105294,0 +94269,Male,31,Masters,11,20,94,79,29,6.0,5,8,Urban,HR Executive,82022,0 +94270,Female,43,High School,17,9,86,57,87,0.0,7,43,Rural,HR Executive,90608,0 +94271,Male,54,Bachelors,2,60,40,51,34,4.0,5,64,Urban,Software Engineer,93065,0 +94272,Male,38,Diploma,12,46,55,74,98,4.0,3,19,Semi-Urban,Software Engineer,59677,0 +94273,Male,24,Diploma,4,74,96,25,87,5.0,4,77,Urban,Software Engineer,135006,1 +94274,Female,46,Masters,16,9,45,96,90,6.0,3,3,Semi-Urban,Manager,33689,0 +94275,Male,33,Diploma,11,33,73,23,60,4.0,0,23,Semi-Urban,Data Analyst,110327,0 +94276,Male,41,High School,5,92,6,3,2,9.0,4,74,Urban,HR Executive,123633,0 +94277,Male,46,Bachelors,4,21,0,74,75,6.0,2,25,Rural,Software Engineer,124893,0 +94278,Female,42,Masters,11,7,29,33,35,1.0,6,75,Urban,Software Engineer,138643,0 +94279,Female,31,PhD,4,77,70,26,16,0.0,1,71,Rural,ML Engineer,147058,1 +94280,Male,38,Bachelors,15,24,29,80,93,8.0,5,94,Urban,Data Analyst,27255,0 +94281,Male,27,Masters,14,45,78,35,44,7.0,4,87,Semi-Urban,Software Engineer,45158,1 +94282,Female,46,Masters,11,44,94,31,28,8.0,0,46,Urban,Manager,146304,0 +94283,Female,29,Diploma,18,28,99,99,17,8.0,5,29,Urban,ML Engineer,46119,1 +94284,Male,46,Bachelors,5,67,15,78,86,1.0,1,8,Urban,Data Analyst,64426,0 +94285,Male,33,High School,3,20,4,4,74,0.0,2,41,Urban,ML Engineer,133896,0 +94286,Male,22,Bachelors,3,56,62,9,46,3.0,0,97,Semi-Urban,Manager,95831,0 +94287,Male,30,Masters,13,1,25,21,47,9.0,3,58,Semi-Urban,Software Engineer,68430,0 +94288,Female,35,High School,18,15,83,35,59,6.0,6,76,Urban,Software Engineer,61845,0 +94289,Male,46,Bachelors,5,49,92,64,50,7.0,7,12,Urban,Software Engineer,56769,0 +94290,Other,25,Masters,11,40,39,97,37,6.0,1,11,Urban,Data Analyst,125132,0 +94291,Male,51,Bachelors,12,59,21,23,84,7.0,2,33,Rural,HR Executive,75338,0 +94292,Male,26,Diploma,0,49,14,79,78,6.0,1,91,Urban,Software Engineer,79159,0 +94293,Male,25,Masters,7,10,46,29,12,3.0,3,80,Urban,HR Executive,111247,0 +94294,Male,41,Masters,18,86,79,7,88,5.0,0,3,Urban,HR Executive,77463,0 +94295,Female,59,Bachelors,1,63,65,12,80,9.0,5,92,Rural,Manager,44519,0 +94296,Female,27,PhD,17,26,18,16,29,4.0,0,52,Urban,Data Analyst,144531,0 +94297,Male,39,Diploma,16,28,64,33,87,1.0,6,63,Urban,ML Engineer,89298,0 +94298,Female,45,PhD,6,93,37,43,95,0.0,7,90,Urban,Data Analyst,111100,1 +94299,Female,45,Diploma,6,33,67,11,17,3.0,6,48,Semi-Urban,Data Analyst,96066,0 +94300,Male,53,High School,14,32,10,26,54,6.0,4,18,Semi-Urban,Data Analyst,75547,0 +94301,Male,25,Bachelors,4,20,70,6,98,7.0,2,29,Semi-Urban,Software Engineer,27367,0 +94302,Male,59,Masters,5,56,19,30,11,1.0,0,50,Urban,HR Executive,47520,0 +94303,Male,22,Masters,12,77,1,76,79,5.0,2,5,Rural,Software Engineer,77313,0 +94304,Male,56,Diploma,13,39,47,32,33,8.0,4,14,Rural,Software Engineer,46526,0 +94305,Male,29,Bachelors,14,32,43,20,60,2.0,2,52,Urban,Data Analyst,81357,0 +94306,Male,39,PhD,0,21,19,89,69,5.0,7,28,Urban,Data Analyst,124928,0 +94307,Other,46,High School,13,31,64,28,11,4.0,3,37,Semi-Urban,HR Executive,73477,0 +94308,Male,45,High School,9,63,48,86,60,6.0,1,76,Urban,Data Analyst,61738,1 +94309,Female,41,Bachelors,12,67,61,19,78,3.0,2,26,Urban,Manager,69935,0 +94310,Female,31,Bachelors,8,19,31,15,81,6.0,5,82,Rural,Data Analyst,95026,0 +94311,Female,45,Bachelors,15,33,27,56,42,1.0,7,20,Urban,Software Engineer,137638,0 +94312,Male,41,High School,0,84,91,71,82,3.0,5,56,Urban,Software Engineer,62534,1 +94313,Female,21,Bachelors,18,15,11,15,58,1.0,6,70,Rural,Manager,58034,0 +94314,Male,51,Bachelors,15,86,80,42,19,8.0,0,75,Urban,Data Analyst,37054,1 +94315,Other,25,Bachelors,19,31,67,32,81,5.0,1,22,Urban,Data Analyst,112309,0 +94316,Male,28,Bachelors,10,36,92,93,99,3.0,2,72,Urban,ML Engineer,47254,1 +94317,Male,21,Bachelors,7,51,90,90,45,5.0,5,35,Urban,Manager,110040,1 +94318,Female,55,Diploma,11,12,45,76,26,1.0,3,40,Urban,Software Engineer,92544,0 +94319,Female,31,Bachelors,13,73,59,72,31,5.0,2,47,Urban,Manager,25218,1 +94320,Female,24,Masters,4,9,89,49,27,6.0,6,20,Rural,HR Executive,148769,0 +94321,Female,57,Bachelors,12,72,28,20,2,1.0,1,16,Urban,HR Executive,39530,0 +94322,Male,56,High School,15,64,56,29,2,7.0,4,90,Semi-Urban,Software Engineer,140644,1 +94323,Male,40,Diploma,4,53,68,95,76,3.0,3,67,Urban,Software Engineer,114932,1 +94324,Female,39,Bachelors,6,47,76,51,11,8.0,0,36,Semi-Urban,HR Executive,128076,0 +94325,Male,35,High School,15,71,97,41,70,2.0,5,20,Urban,Manager,26203,0 +94326,Male,45,Bachelors,12,78,55,76,79,0.0,2,70,Urban,Software Engineer,93424,1 +94327,Male,21,Diploma,18,14,3,25,35,1.0,0,23,Rural,Software Engineer,129695,0 +94328,Female,41,Bachelors,14,75,90,10,85,1.0,5,38,Urban,Manager,53975,0 +94329,Male,43,Masters,19,99,59,66,61,8.0,6,25,Urban,Manager,96087,1 +94330,Female,48,High School,15,24,29,58,84,2.0,5,22,Semi-Urban,Manager,60372,0 +94331,Female,52,High School,5,81,88,4,45,0.0,6,40,Urban,Manager,64521,0 +94332,Male,22,High School,10,88,13,81,14,4.0,6,99,Semi-Urban,HR Executive,22344,1 +94333,Female,40,Diploma,11,20,32,83,98,1.0,1,79,Semi-Urban,Software Engineer,22859,0 +94334,Female,59,Masters,11,99,15,42,63,1.0,3,96,Semi-Urban,Manager,132457,1 +94335,Female,40,Masters,2,55,12,95,61,9.0,7,68,Semi-Urban,HR Executive,101477,0 +94336,Male,52,Masters,2,67,32,92,26,4.0,7,49,Urban,ML Engineer,83225,1 +94337,Female,38,Masters,12,21,0,13,9,9.0,3,3,Urban,Software Engineer,38379,0 +94338,Male,35,Masters,6,14,97,16,87,6.0,1,72,Semi-Urban,Software Engineer,74118,0 +94339,Male,37,Bachelors,3,15,95,97,87,2.0,7,8,Semi-Urban,Manager,96562,0 +94340,Male,44,Bachelors,19,48,76,99,19,0.0,6,11,Urban,Manager,67372,0 +94341,Male,55,Bachelors,3,4,75,0,71,3.0,3,66,Urban,Data Analyst,28653,0 +94342,Male,53,Bachelors,14,82,23,65,6,8.0,6,16,Urban,ML Engineer,63493,0 +94343,Female,42,Bachelors,1,63,25,90,51,7.0,5,76,Urban,Software Engineer,117011,1 +94344,Female,22,Bachelors,13,17,95,45,80,0.0,6,78,Urban,ML Engineer,143749,0 +94345,Male,41,Masters,4,20,68,27,89,1.0,1,18,Urban,Data Analyst,56728,0 +94346,Male,23,Diploma,2,6,88,97,17,1.0,7,0,Rural,Data Analyst,149852,0 +94347,Male,49,Diploma,9,40,61,55,94,0.0,7,58,Urban,Manager,94869,0 +94348,Male,40,Bachelors,3,90,57,70,78,8.0,7,62,Semi-Urban,ML Engineer,99536,1 +94349,Male,47,Bachelors,13,56,10,73,87,0.0,6,73,Rural,HR Executive,144135,0 +94350,Female,51,High School,5,6,54,85,19,6.0,1,99,Urban,Data Analyst,62673,1 +94351,Male,48,Bachelors,1,7,13,85,87,6.0,6,6,Urban,Manager,27994,0 +94352,Male,46,Bachelors,7,29,18,23,39,2.0,0,64,Urban,Data Analyst,46416,0 +94353,Female,34,Diploma,18,52,95,19,81,7.0,4,86,Rural,HR Executive,127977,1 +94354,Male,52,Bachelors,5,86,27,23,68,3.0,2,32,Semi-Urban,Data Analyst,32320,0 +94355,Male,37,Bachelors,12,71,78,20,22,1.0,2,80,Urban,ML Engineer,52905,1 +94356,Male,25,Bachelors,1,31,46,87,8,6.0,6,27,Semi-Urban,Software Engineer,94620,0 +94357,Other,54,Bachelors,11,33,66,17,7,8.0,0,49,Urban,Data Analyst,52642,0 +94358,Male,23,PhD,4,29,3,94,49,1.0,2,87,Urban,Manager,45297,0 +94359,Female,47,Masters,9,62,55,91,14,6.0,4,24,Urban,HR Executive,95860,0 +94360,Male,37,High School,6,48,27,75,37,1.0,3,82,Urban,Manager,87603,0 +94361,Male,48,Bachelors,3,13,90,2,24,0.0,2,41,Urban,Software Engineer,21332,0 +94362,Other,57,Diploma,4,23,18,45,31,5.0,1,37,Urban,Manager,81997,0 +94363,Female,56,Masters,9,67,46,55,42,5.0,5,33,Urban,HR Executive,131871,0 +94364,Male,56,High School,17,10,45,79,20,4.0,3,37,Urban,ML Engineer,51466,0 +94365,Male,57,Bachelors,19,36,27,32,20,3.0,4,50,Rural,HR Executive,101985,0 +94366,Male,55,Diploma,5,36,33,91,80,1.0,5,47,Semi-Urban,HR Executive,121660,0 +94367,Male,27,Bachelors,19,96,4,69,17,7.0,5,2,Semi-Urban,Data Analyst,45869,0 +94368,Male,25,Diploma,16,94,10,5,5,8.0,2,27,Rural,Data Analyst,83638,0 +94369,Male,34,Bachelors,10,49,15,26,59,0.0,2,90,Urban,Software Engineer,67722,0 +94370,Male,55,Masters,17,64,44,76,55,3.0,1,34,Rural,Data Analyst,65471,0 +94371,Male,59,Diploma,3,23,34,85,96,8.0,7,78,Urban,Data Analyst,136620,0 +94372,Female,36,High School,3,82,12,36,43,7.0,7,38,Urban,Manager,59331,0 +94373,Male,48,Diploma,4,81,75,83,10,4.0,0,87,Semi-Urban,ML Engineer,71158,1 +94374,Male,33,High School,15,51,63,15,63,0.0,5,46,Urban,HR Executive,65683,0 +94375,Female,48,Diploma,5,4,28,7,92,5.0,7,86,Urban,Manager,23970,0 +94376,Female,54,Masters,19,72,20,77,83,5.0,4,58,Semi-Urban,Software Engineer,64665,0 +94377,Male,50,High School,14,74,57,82,2,9.0,5,40,Urban,ML Engineer,92895,1 +94378,Male,31,High School,0,14,33,83,13,1.0,2,91,Semi-Urban,Manager,45422,0 +94379,Male,26,High School,3,89,7,15,93,4.0,4,0,Urban,ML Engineer,50709,0 +94380,Male,33,High School,19,9,43,91,93,7.0,2,70,Urban,Data Analyst,38750,0 +94381,Female,46,PhD,16,21,52,40,6,6.0,7,83,Urban,Data Analyst,114305,0 +94382,Other,38,High School,17,55,38,7,92,4.0,0,37,Urban,Manager,30954,0 +94383,Female,29,Bachelors,17,6,69,69,2,8.0,7,53,Rural,Software Engineer,36369,0 +94384,Male,40,High School,10,19,85,29,55,7.0,1,84,Semi-Urban,HR Executive,25952,0 +94385,Male,51,Bachelors,19,68,41,28,55,3.0,4,32,Urban,Data Analyst,89708,0 +94386,Male,59,Bachelors,8,61,45,7,53,7.0,2,34,Urban,ML Engineer,89928,0 +94387,Male,38,Diploma,4,37,20,43,37,0.0,1,82,Urban,ML Engineer,136567,0 +94388,Male,37,PhD,17,33,67,74,98,1.0,5,59,Urban,Software Engineer,26803,0 +94389,Male,22,Bachelors,8,43,98,54,82,2.0,4,35,Urban,HR Executive,93462,0 +94390,Male,44,High School,9,43,61,86,71,7.0,4,88,Semi-Urban,Manager,112744,1 +94391,Other,58,Masters,19,57,91,11,3,3.0,0,45,Rural,Manager,64226,0 +94392,Female,45,Bachelors,18,14,41,65,15,1.0,7,23,Rural,HR Executive,39727,0 +94393,Male,24,Bachelors,18,95,7,33,75,8.0,0,40,Rural,Data Analyst,42408,0 +94394,Female,39,Bachelors,14,64,62,87,71,5.0,2,12,Urban,Data Analyst,112590,0 +94395,Male,43,Diploma,4,42,79,71,89,9.0,2,46,Urban,ML Engineer,72615,1 +94396,Male,48,Bachelors,9,43,48,49,75,0.0,3,84,Semi-Urban,Data Analyst,110831,0 +94397,Male,21,Masters,10,73,92,97,37,3.0,6,3,Semi-Urban,ML Engineer,100731,1 +94398,Other,31,High School,8,77,41,63,48,3.0,3,16,Urban,HR Executive,63059,0 +94399,Female,26,Diploma,17,76,87,54,8,5.0,2,81,Urban,Manager,37165,1 +94400,Male,36,Masters,5,27,48,51,16,2.0,7,42,Urban,HR Executive,138528,0 +94401,Male,54,Masters,19,75,30,46,97,0.0,4,77,Rural,HR Executive,117292,0 +94402,Other,54,Masters,10,86,76,14,71,3.0,3,37,Rural,Manager,119524,0 +94403,Male,32,Diploma,3,72,98,48,97,7.0,4,4,Rural,Software Engineer,48036,0 +94404,Male,38,Masters,3,76,15,58,89,0.0,6,20,Urban,Data Analyst,127792,0 +94405,Female,59,High School,7,57,35,26,32,8.0,7,51,Rural,ML Engineer,129556,0 +94406,Female,32,Masters,5,96,65,85,43,9.0,2,4,Semi-Urban,Software Engineer,68176,1 +94407,Male,48,Masters,3,68,12,76,2,8.0,6,53,Rural,Software Engineer,128537,0 +94408,Other,39,Diploma,7,56,36,6,70,8.0,7,21,Urban,HR Executive,59121,0 +94409,Male,26,Bachelors,13,9,73,54,25,4.0,1,76,Urban,Data Analyst,136412,0 +94410,Male,58,Bachelors,2,39,58,18,84,0.0,4,8,Rural,Software Engineer,74845,0 +94411,Female,50,Masters,17,22,71,15,15,4.0,2,83,Semi-Urban,HR Executive,88402,0 +94412,Male,24,Masters,11,44,90,22,1,4.0,5,74,Semi-Urban,Software Engineer,70920,0 +94413,Female,40,Bachelors,10,51,17,58,21,8.0,0,94,Urban,HR Executive,93397,0 +94414,Female,59,Bachelors,6,15,43,69,85,0.0,7,52,Urban,Manager,96534,0 +94415,Male,41,Diploma,11,15,81,45,40,1.0,0,85,Urban,HR Executive,35262,0 +94416,Female,34,Bachelors,7,84,65,75,54,1.0,3,99,Rural,HR Executive,111039,1 +94417,Female,50,High School,19,10,57,99,12,7.0,4,29,Semi-Urban,Manager,139829,0 +94418,Other,28,High School,5,16,75,51,29,4.0,0,62,Semi-Urban,Data Analyst,61380,0 +94419,Male,37,High School,15,62,48,96,49,9.0,6,55,Urban,HR Executive,71801,1 +94420,Female,58,Bachelors,6,1,88,19,36,1.0,1,92,Rural,Data Analyst,50725,0 +94421,Male,50,Diploma,19,67,24,96,35,5.0,2,83,Urban,HR Executive,24660,1 +94422,Male,44,Masters,5,92,18,80,34,2.0,4,36,Semi-Urban,ML Engineer,27198,0 +94423,Female,29,Masters,12,62,57,35,9,2.0,6,31,Semi-Urban,HR Executive,134449,0 +94424,Male,37,Diploma,7,83,85,46,76,8.0,0,83,Semi-Urban,Data Analyst,63237,1 +94425,Male,39,Diploma,17,49,20,86,49,0.0,0,0,Urban,Data Analyst,107439,0 +94426,Male,55,Bachelors,12,8,7,95,94,6.0,0,7,Urban,HR Executive,135831,0 +94427,Male,42,Diploma,0,25,87,85,89,0.0,4,28,Semi-Urban,Manager,123162,0 +94428,Male,58,Bachelors,15,50,87,34,5,9.0,6,19,Urban,Manager,37502,0 +94429,Male,23,Bachelors,5,24,14,16,52,9.0,4,82,Urban,HR Executive,141709,0 +94430,Male,22,Masters,2,58,45,47,74,9.0,4,56,Semi-Urban,HR Executive,117571,0 +94431,Male,25,Bachelors,17,72,12,74,91,2.0,0,27,Rural,HR Executive,128018,0 +94432,Male,42,Bachelors,18,73,45,76,52,9.0,1,24,Semi-Urban,Software Engineer,81201,0 +94433,Female,47,High School,10,3,42,71,21,8.0,6,30,Rural,HR Executive,42642,0 +94434,Female,27,Masters,15,32,13,64,52,0.0,4,32,Urban,Software Engineer,55948,0 +94435,Male,43,Masters,17,24,87,36,79,0.0,6,78,Urban,Data Analyst,88977,0 +94436,Male,39,Diploma,3,36,81,46,45,8.0,6,65,Urban,Data Analyst,141318,0 +94437,Male,40,Masters,18,63,92,91,57,8.0,0,29,Semi-Urban,HR Executive,51838,1 +94438,Male,42,Masters,12,60,2,12,27,2.0,7,54,Urban,ML Engineer,40316,0 +94439,Male,38,Masters,8,11,66,91,36,7.0,0,27,Rural,HR Executive,148262,0 +94440,Male,48,High School,7,87,95,56,0,2.0,7,1,Semi-Urban,Manager,94982,1 +94441,Male,44,High School,2,8,25,37,46,7.0,4,45,Semi-Urban,Software Engineer,90780,0 +94442,Male,30,Bachelors,5,52,4,65,17,5.0,5,18,Semi-Urban,ML Engineer,149914,0 +94443,Male,33,Bachelors,2,1,47,59,50,5.0,7,69,Rural,Data Analyst,146452,0 +94444,Male,57,Bachelors,19,0,68,97,41,0.0,5,9,Urban,Software Engineer,39174,0 +94445,Female,35,Bachelors,10,22,36,48,16,7.0,2,47,Rural,Software Engineer,40177,0 +94446,Male,44,Bachelors,19,46,91,71,17,7.0,2,90,Urban,HR Executive,107302,1 +94447,Male,43,Bachelors,4,11,76,27,58,1.0,5,76,Urban,Data Analyst,117145,0 +94448,Female,43,Bachelors,2,35,51,11,29,7.0,0,61,Urban,HR Executive,31449,0 +94449,Male,47,Masters,5,21,43,24,41,6.0,2,14,Urban,Data Analyst,31460,0 +94450,Female,27,Masters,11,2,80,43,22,4.0,5,35,Urban,HR Executive,48074,0 +94451,Male,36,Bachelors,16,10,74,72,1,4.0,2,28,Urban,Software Engineer,47473,0 +94452,Female,48,Bachelors,6,67,19,12,32,9.0,3,76,Semi-Urban,ML Engineer,100201,0 +94453,Male,32,Bachelors,19,29,41,97,76,5.0,3,25,Semi-Urban,Manager,132706,0 +94454,Female,36,Bachelors,5,11,21,99,54,8.0,4,61,Urban,HR Executive,30011,0 +94455,Male,23,Masters,0,45,13,56,86,0.0,5,23,Semi-Urban,HR Executive,39810,0 +94456,Female,21,Diploma,12,62,78,4,96,9.0,2,96,Urban,ML Engineer,25087,0 +94457,Male,21,Diploma,2,19,27,66,59,0.0,5,43,Rural,Manager,140337,0 +94458,Male,58,High School,15,49,41,50,56,5.0,1,75,Rural,Software Engineer,20861,0 +94459,Male,40,Bachelors,3,87,18,91,68,0.0,7,0,Semi-Urban,HR Executive,22374,0 +94460,Female,51,Bachelors,9,4,15,35,54,2.0,6,66,Urban,Manager,38341,0 +94461,Male,38,Bachelors,18,8,72,71,45,8.0,4,62,Urban,Manager,38323,0 +94462,Male,45,Bachelors,0,37,48,82,42,1.0,3,16,Rural,HR Executive,112593,0 +94463,Male,37,PhD,13,11,46,29,35,2.0,3,25,Semi-Urban,HR Executive,70384,0 +94464,Female,45,Bachelors,0,70,63,85,71,0.0,6,53,Urban,Software Engineer,139485,1 +94465,Other,24,Masters,16,89,30,86,21,8.0,2,24,Semi-Urban,Software Engineer,60960,0 +94466,Male,25,Bachelors,2,51,48,89,89,4.0,1,31,Semi-Urban,Manager,49064,0 +94467,Male,46,PhD,3,16,73,91,2,7.0,0,32,Rural,ML Engineer,103833,0 +94468,Male,58,High School,8,30,84,43,73,4.0,4,62,Urban,Software Engineer,129935,0 +94469,Male,58,Bachelors,8,41,80,13,83,0.0,6,17,Semi-Urban,HR Executive,60452,0 +94470,Female,43,High School,10,70,11,51,63,8.0,5,82,Urban,Software Engineer,134822,0 +94471,Male,30,Bachelors,9,88,86,29,82,4.0,4,30,Rural,Data Analyst,116268,0 +94472,Male,32,Bachelors,19,73,4,48,13,1.0,1,31,Rural,HR Executive,97292,0 +94473,Male,22,Masters,7,46,36,74,48,5.0,3,42,Semi-Urban,Manager,86008,0 +94474,Male,21,Masters,15,55,22,2,33,5.0,4,76,Urban,Data Analyst,144867,0 +94475,Other,35,Bachelors,11,1,34,67,54,3.0,6,20,Rural,Manager,110459,0 +94476,Female,43,Bachelors,18,23,44,69,45,8.0,3,63,Urban,Software Engineer,76853,0 +94477,Male,31,Bachelors,17,38,18,94,59,9.0,1,27,Urban,ML Engineer,68293,0 +94478,Male,42,Diploma,1,83,0,51,21,7.0,6,2,Urban,Software Engineer,124628,0 +94479,Male,41,Masters,4,5,7,36,5,2.0,2,89,Urban,HR Executive,72136,0 +94480,Female,28,Diploma,9,71,9,28,42,1.0,6,14,Urban,ML Engineer,24625,0 +94481,Male,39,Bachelors,4,61,50,94,73,6.0,0,94,Semi-Urban,ML Engineer,113142,1 +94482,Male,21,High School,6,63,93,24,51,7.0,6,88,Urban,ML Engineer,99865,1 +94483,Female,38,Diploma,1,44,11,76,58,3.0,7,35,Urban,Data Analyst,129046,0 +94484,Male,22,PhD,5,60,22,10,84,7.0,5,8,Rural,Manager,91724,0 +94485,Male,48,High School,5,35,78,76,62,7.0,5,9,Urban,Software Engineer,128879,0 +94486,Female,59,Masters,15,24,81,91,36,7.0,5,23,Rural,HR Executive,148106,0 +94487,Male,32,Masters,11,16,81,96,54,4.0,1,88,Urban,Manager,60482,1 +94488,Female,39,Bachelors,13,88,25,17,55,4.0,0,63,Urban,Manager,139133,0 +94489,Male,35,Masters,2,88,36,82,94,7.0,3,70,Semi-Urban,Software Engineer,53229,1 +94490,Male,38,Bachelors,16,42,39,8,11,1.0,1,25,Urban,ML Engineer,91947,0 +94491,Male,59,Bachelors,19,92,22,25,55,7.0,4,54,Urban,Data Analyst,38076,0 +94492,Female,55,Bachelors,5,41,73,23,97,2.0,5,13,Semi-Urban,Software Engineer,129546,0 +94493,Male,47,Masters,14,46,46,26,47,9.0,7,48,Urban,ML Engineer,122427,0 +94494,Other,51,Diploma,15,59,72,59,75,3.0,2,99,Semi-Urban,Manager,98926,1 +94495,Male,54,High School,1,83,84,36,76,2.0,7,49,Urban,ML Engineer,53399,1 +94496,Female,34,Masters,5,16,57,64,2,8.0,6,46,Urban,Manager,117938,0 +94497,Male,46,Bachelors,13,55,32,39,26,2.0,1,15,Urban,Data Analyst,137607,0 +94498,Male,46,Masters,3,97,91,84,73,0.0,6,93,Semi-Urban,Software Engineer,71386,1 +94499,Other,32,High School,1,13,68,30,64,3.0,5,16,Rural,Data Analyst,143025,0 +94500,Male,59,Bachelors,9,37,55,60,92,1.0,5,97,Rural,ML Engineer,110815,1 +94501,Male,37,Masters,3,47,99,48,90,6.0,6,78,Urban,Manager,109549,1 +94502,Female,51,Bachelors,16,27,92,44,40,1.0,0,74,Urban,ML Engineer,69103,0 +94503,Female,30,Masters,6,93,38,29,43,4.0,3,70,Urban,HR Executive,28864,0 +94504,Female,41,Diploma,18,32,96,97,63,1.0,1,98,Urban,Software Engineer,91990,1 +94505,Female,32,Diploma,4,57,9,60,60,6.0,0,78,Urban,ML Engineer,119100,0 +94506,Male,35,Masters,12,39,95,54,13,0.0,2,44,Semi-Urban,Data Analyst,54130,0 +94507,Female,22,Masters,1,1,43,21,53,8.0,3,37,Urban,ML Engineer,96298,0 +94508,Female,46,High School,15,8,72,18,51,9.0,7,61,Urban,Software Engineer,26641,0 +94509,Other,55,Bachelors,19,92,1,50,78,3.0,3,54,Urban,Data Analyst,38205,0 +94510,Female,29,Diploma,0,42,55,30,74,7.0,1,1,Urban,HR Executive,72925,0 +94511,Male,24,Bachelors,2,9,90,74,26,3.0,0,11,Semi-Urban,HR Executive,148550,0 +94512,Male,47,PhD,2,68,57,97,5,5.0,0,58,Rural,HR Executive,91446,1 +94513,Female,32,Diploma,12,56,41,75,91,2.0,7,74,Rural,ML Engineer,22848,1 +94514,Female,31,Diploma,4,26,13,57,64,1.0,2,10,Urban,Software Engineer,108606,0 +94515,Male,46,High School,10,40,74,93,37,9.0,2,21,Urban,Data Analyst,25742,0 +94516,Male,58,Bachelors,4,64,23,28,81,8.0,7,61,Semi-Urban,ML Engineer,59111,0 +94517,Male,53,Bachelors,0,0,30,45,42,3.0,3,65,Rural,Data Analyst,37659,0 +94518,Male,33,Masters,14,88,19,18,20,6.0,3,79,Urban,HR Executive,88630,0 +94519,Male,54,Masters,12,82,72,69,25,2.0,3,80,Rural,Data Analyst,94667,1 +94520,Male,37,PhD,18,80,66,15,25,3.0,1,1,Urban,HR Executive,112276,0 +94521,Male,43,Masters,15,63,12,5,98,1.0,3,95,Urban,Software Engineer,117576,0 +94522,Female,54,High School,11,75,86,18,12,9.0,0,37,Urban,HR Executive,36228,0 +94523,Female,43,High School,8,51,61,67,18,1.0,4,21,Urban,ML Engineer,68158,0 +94524,Male,48,Bachelors,14,88,57,20,95,2.0,7,30,Rural,ML Engineer,130614,0 +94525,Male,56,Bachelors,5,76,51,72,92,2.0,0,31,Urban,Software Engineer,87310,0 +94526,Male,28,Bachelors,13,21,91,27,27,3.0,7,36,Urban,Data Analyst,31318,0 +94527,Male,55,Bachelors,14,4,6,40,29,5.0,5,81,Urban,Software Engineer,145090,0 +94528,Female,44,High School,6,16,97,15,9,5.0,2,72,Urban,Data Analyst,54721,0 +94529,Male,25,Diploma,15,30,4,28,67,1.0,0,39,Urban,Manager,134732,0 +94530,Male,57,Bachelors,5,55,1,44,20,7.0,6,75,Urban,Manager,137061,0 +94531,Male,45,Diploma,18,46,61,76,85,1.0,1,4,Urban,HR Executive,117742,0 +94532,Male,53,Bachelors,18,74,95,16,78,6.0,6,46,Rural,ML Engineer,21327,0 +94533,Female,40,Bachelors,10,68,26,22,52,2.0,6,37,Semi-Urban,Data Analyst,33140,0 +94534,Female,56,Bachelors,2,21,61,60,28,8.0,0,39,Urban,Software Engineer,141624,0 +94535,Male,27,Bachelors,13,0,22,3,55,9.0,2,89,Rural,ML Engineer,68424,0 +94536,Female,39,Bachelors,7,5,13,94,29,1.0,6,70,Urban,Data Analyst,108120,0 +94537,Male,26,PhD,17,55,31,37,92,5.0,5,43,Semi-Urban,Manager,81662,0 +94538,Female,36,Bachelors,0,70,13,82,15,6.0,5,35,Urban,Software Engineer,58398,0 +94539,Female,25,High School,3,81,62,33,50,5.0,7,87,Semi-Urban,Data Analyst,69676,1 +94540,Male,40,PhD,10,46,2,96,37,7.0,1,68,Urban,Software Engineer,94033,0 +94541,Female,36,High School,13,22,95,50,57,0.0,7,52,Semi-Urban,ML Engineer,72828,0 +94542,Male,21,High School,2,46,33,31,41,8.0,5,19,Urban,Manager,84914,0 +94543,Female,57,Diploma,5,53,99,79,43,5.0,7,47,Semi-Urban,Manager,24184,1 +94544,Male,25,PhD,11,71,17,45,88,9.0,2,58,Urban,HR Executive,95372,0 +94545,Male,50,Masters,3,11,22,34,39,1.0,7,27,Rural,Data Analyst,42337,0 +94546,Female,36,High School,19,26,90,11,10,5.0,2,75,Urban,Data Analyst,117708,0 +94547,Male,37,High School,4,55,69,12,16,9.0,0,76,Urban,HR Executive,35751,0 +94548,Male,36,Diploma,5,34,76,70,63,7.0,7,11,Semi-Urban,ML Engineer,71335,0 +94549,Other,33,Bachelors,4,98,38,62,5,4.0,7,54,Semi-Urban,Data Analyst,116107,1 +94550,Male,35,Masters,16,79,75,70,59,8.0,7,2,Urban,ML Engineer,74535,0 +94551,Female,57,High School,8,41,39,5,32,3.0,4,71,Rural,ML Engineer,131829,0 +94552,Male,54,Masters,4,20,57,23,50,9.0,3,10,Semi-Urban,Manager,97402,0 +94553,Female,47,Masters,9,84,49,61,38,6.0,1,90,Semi-Urban,HR Executive,82630,1 +94554,Male,58,Bachelors,13,37,95,98,38,9.0,4,23,Urban,Software Engineer,149611,1 +94555,Male,34,PhD,12,78,40,4,30,3.0,3,84,Rural,ML Engineer,102405,0 +94556,Other,56,Masters,1,81,29,3,57,6.0,7,98,Urban,Software Engineer,72133,0 +94557,Female,47,Bachelors,7,72,59,10,90,7.0,6,42,Urban,Software Engineer,122457,0 +94558,Male,42,Masters,13,92,38,16,60,2.0,6,8,Semi-Urban,Manager,107105,0 +94559,Female,21,Diploma,17,4,65,6,66,8.0,6,41,Rural,ML Engineer,29908,0 +94560,Male,33,Diploma,8,34,78,30,9,2.0,6,42,Urban,Software Engineer,93297,0 +94561,Male,22,Diploma,3,19,63,5,17,7.0,0,72,Urban,ML Engineer,34714,0 +94562,Male,42,High School,2,0,40,54,53,2.0,3,57,Urban,Manager,142892,0 +94563,Female,44,Bachelors,7,78,95,69,88,4.0,6,46,Semi-Urban,Data Analyst,33135,1 +94564,Male,23,Masters,10,50,90,9,46,2.0,6,81,Urban,Manager,63518,0 +94565,Male,25,Bachelors,7,30,49,85,23,8.0,6,8,Urban,Manager,104630,0 +94566,Female,29,Masters,7,20,98,0,31,3.0,4,96,Urban,ML Engineer,52604,0 +94567,Other,34,Masters,5,68,69,78,32,1.0,3,10,Rural,Manager,73565,0 +94568,Female,55,Diploma,17,22,35,69,93,2.0,0,44,Urban,ML Engineer,116633,0 +94569,Other,39,High School,12,80,40,47,92,2.0,6,99,Rural,Software Engineer,26225,1 +94570,Female,25,Bachelors,3,83,93,66,9,1.0,6,32,Urban,Data Analyst,124125,1 +94571,Male,37,Bachelors,19,56,1,98,27,4.0,2,50,Urban,Data Analyst,31967,0 +94572,Male,27,PhD,19,33,87,58,72,6.0,3,93,Semi-Urban,Manager,41411,1 +94573,Female,29,Bachelors,11,33,77,71,37,9.0,1,19,Urban,HR Executive,119006,0 +94574,Female,43,Bachelors,7,26,42,49,25,8.0,0,75,Urban,ML Engineer,94797,0 +94575,Female,22,Bachelors,0,32,28,78,40,8.0,1,17,Urban,Software Engineer,86110,0 +94576,Female,23,Masters,17,34,48,44,97,3.0,1,15,Urban,Software Engineer,130330,0 +94577,Male,54,Bachelors,8,95,75,65,57,7.0,2,49,Urban,Software Engineer,57605,1 +94578,Female,40,High School,3,40,75,27,56,8.0,0,75,Urban,Software Engineer,22747,0 +94579,Female,46,High School,12,29,93,34,81,5.0,1,67,Urban,Software Engineer,117328,0 +94580,Male,50,Masters,15,27,11,58,54,1.0,0,25,Urban,Manager,118624,0 +94581,Female,38,PhD,16,19,43,70,85,5.0,3,30,Semi-Urban,Software Engineer,135363,0 +94582,Male,33,High School,10,30,92,36,25,7.0,1,95,Semi-Urban,ML Engineer,111697,1 +94583,Male,41,High School,19,88,37,94,80,0.0,4,30,Semi-Urban,Data Analyst,46619,1 +94584,Male,42,High School,13,91,99,82,96,1.0,7,96,Urban,Data Analyst,61170,1 +94585,Male,52,Masters,8,94,46,36,79,5.0,6,82,Rural,Software Engineer,93259,1 +94586,Male,46,Bachelors,19,48,81,93,25,8.0,5,19,Urban,ML Engineer,37083,1 +94587,Male,36,Diploma,17,39,32,48,59,7.0,4,27,Urban,HR Executive,139896,0 +94588,Female,30,High School,3,27,84,21,82,0.0,5,72,Urban,HR Executive,111340,0 +94589,Female,35,Bachelors,18,34,13,33,48,1.0,1,40,Rural,Manager,87285,0 +94590,Female,31,Diploma,4,34,20,41,22,3.0,0,73,Urban,ML Engineer,78113,0 +94591,Female,43,High School,16,59,78,11,68,3.0,2,53,Urban,ML Engineer,24677,0 +94592,Female,25,Masters,10,68,30,72,34,1.0,7,62,Rural,Data Analyst,111100,0 +94593,Male,22,PhD,17,61,93,96,26,5.0,7,61,Urban,Data Analyst,59594,1 +94594,Male,21,Masters,7,99,33,18,11,6.0,7,69,Urban,ML Engineer,133050,0 +94595,Male,29,Masters,10,66,15,92,47,6.0,2,71,Urban,Software Engineer,29058,1 +94596,Male,23,Bachelors,3,83,71,98,55,5.0,7,90,Rural,Data Analyst,39409,1 +94597,Male,23,Masters,13,24,36,93,39,5.0,3,54,Urban,Manager,66685,0 +94598,Other,57,Bachelors,5,75,93,19,95,0.0,2,48,Rural,ML Engineer,120280,0 +94599,Female,23,Masters,2,5,25,71,69,7.0,2,61,Semi-Urban,Data Analyst,133306,0 +94600,Male,35,Bachelors,5,88,84,48,8,2.0,3,81,Semi-Urban,Software Engineer,30091,1 +94601,Female,48,High School,16,63,59,24,61,0.0,7,16,Rural,Software Engineer,108692,0 +94602,Female,58,Masters,17,60,45,93,25,0.0,1,17,Urban,Software Engineer,48935,0 +94603,Male,52,Bachelors,18,46,38,67,21,6.0,5,19,Semi-Urban,ML Engineer,88892,0 +94604,Female,58,Masters,14,3,72,60,55,6.0,7,8,Urban,Manager,141819,0 +94605,Male,23,Bachelors,15,24,9,29,95,9.0,7,17,Urban,Data Analyst,49225,0 +94606,Female,27,High School,16,33,98,66,4,0.0,0,39,Semi-Urban,Data Analyst,127829,0 +94607,Male,27,High School,11,76,55,20,34,3.0,6,82,Urban,Software Engineer,141571,0 +94608,Male,31,Masters,18,94,2,91,79,2.0,6,64,Urban,Manager,44779,1 +94609,Female,53,Bachelors,7,65,74,39,21,4.0,5,36,Rural,HR Executive,74601,0 +94610,Male,21,High School,6,53,12,34,71,6.0,4,11,Semi-Urban,Manager,111216,0 +94611,Female,22,Bachelors,18,99,34,34,87,4.0,6,92,Urban,HR Executive,48109,1 +94612,Female,29,Bachelors,0,72,15,96,96,6.0,2,82,Urban,Data Analyst,39269,1 +94613,Female,34,Masters,5,32,58,31,39,9.0,1,41,Semi-Urban,Manager,132800,0 +94614,Male,33,Masters,16,98,4,35,70,0.0,2,69,Urban,Manager,111498,0 +94615,Female,27,Bachelors,16,20,30,95,66,0.0,6,85,Semi-Urban,Software Engineer,81228,0 +94616,Female,30,Bachelors,14,88,14,23,99,4.0,6,66,Urban,HR Executive,142636,0 +94617,Female,38,Masters,10,39,90,94,76,6.0,0,50,Urban,Data Analyst,89255,1 +94618,Male,35,Diploma,8,31,0,58,95,7.0,0,57,Semi-Urban,Manager,99612,0 +94619,Female,53,Masters,5,70,23,33,61,1.0,2,93,Urban,HR Executive,93925,0 +94620,Male,59,Bachelors,0,40,67,86,20,6.0,5,18,Urban,Manager,96611,0 +94621,Male,55,Bachelors,17,85,94,63,88,6.0,5,17,Rural,HR Executive,116179,1 +94622,Female,31,Bachelors,9,97,52,84,47,6.0,3,70,Urban,ML Engineer,73379,1 +94623,Male,24,Diploma,16,39,76,44,26,2.0,2,80,Urban,Software Engineer,49790,1 +94624,Male,59,Masters,1,13,92,1,66,7.0,4,97,Urban,HR Executive,26825,0 +94625,Male,35,Diploma,18,25,32,70,12,0.0,7,24,Urban,ML Engineer,134791,0 +94626,Female,52,Bachelors,17,63,7,82,41,4.0,5,74,Urban,ML Engineer,85997,0 +94627,Other,48,High School,18,19,46,30,33,5.0,7,44,Urban,ML Engineer,53551,0 +94628,Female,28,Masters,5,61,0,28,10,7.0,0,59,Semi-Urban,Data Analyst,141456,0 +94629,Male,54,Bachelors,1,98,94,21,94,7.0,7,63,Urban,Software Engineer,111929,1 +94630,Male,33,Bachelors,6,8,8,41,24,0.0,5,8,Urban,Manager,20264,0 +94631,Female,52,Bachelors,16,45,54,67,75,4.0,6,18,Urban,HR Executive,70653,0 +94632,Female,49,High School,17,58,54,1,42,3.0,5,17,Rural,HR Executive,105321,0 +94633,Male,56,High School,0,29,53,3,33,9.0,2,72,Semi-Urban,HR Executive,75870,0 +94634,Male,38,Diploma,8,23,60,25,76,1.0,7,25,Urban,ML Engineer,141246,0 +94635,Male,59,Bachelors,17,98,33,15,36,5.0,6,88,Rural,Data Analyst,30955,0 +94636,Male,40,High School,3,65,80,51,49,1.0,1,5,Rural,Manager,50870,0 +94637,Male,23,High School,1,25,63,71,28,9.0,0,30,Urban,ML Engineer,149336,0 +94638,Male,21,Bachelors,7,84,63,77,43,9.0,3,46,Urban,HR Executive,99673,1 +94639,Male,23,High School,11,14,58,19,79,9.0,4,24,Urban,Data Analyst,38495,0 +94640,Other,25,Bachelors,12,35,67,61,1,8.0,4,96,Semi-Urban,HR Executive,145485,1 +94641,Male,40,Diploma,4,3,46,21,30,2.0,4,5,Rural,Software Engineer,105665,0 +94642,Female,33,Masters,8,14,86,16,43,2.0,1,69,Urban,HR Executive,117557,0 +94643,Male,29,Bachelors,16,49,14,92,26,2.0,3,18,Rural,Software Engineer,40230,0 +94644,Female,39,Bachelors,8,81,21,0,59,4.0,6,85,Urban,Software Engineer,51754,0 +94645,Other,58,Diploma,9,59,53,92,88,1.0,5,21,Urban,ML Engineer,142152,0 +94646,Male,38,High School,4,85,27,81,84,5.0,4,29,Urban,ML Engineer,55136,0 +94647,Male,47,Bachelors,10,63,72,0,26,6.0,3,85,Semi-Urban,Manager,59910,0 +94648,Female,38,Bachelors,4,80,0,44,94,3.0,4,44,Semi-Urban,Data Analyst,79870,0 +94649,Male,32,PhD,10,95,42,30,46,4.0,7,29,Semi-Urban,ML Engineer,80508,0 +94650,Female,48,Masters,4,0,96,92,27,8.0,4,44,Semi-Urban,ML Engineer,96749,0 +94651,Male,49,Masters,18,9,68,19,83,5.0,6,69,Urban,Software Engineer,76919,0 +94652,Male,28,Masters,13,23,30,70,42,6.0,1,47,Urban,ML Engineer,52803,0 +94653,Other,45,Masters,15,35,81,69,8,2.0,4,6,Semi-Urban,ML Engineer,103257,0 +94654,Female,55,Bachelors,12,69,52,42,2,5.0,4,34,Semi-Urban,Data Analyst,144842,0 +94655,Male,36,Bachelors,7,13,44,79,38,5.0,1,53,Semi-Urban,HR Executive,145341,0 +94656,Female,30,Bachelors,8,73,47,17,46,8.0,6,35,Rural,HR Executive,43803,0 +94657,Male,59,Bachelors,19,76,71,37,82,6.0,1,15,Urban,Software Engineer,75726,0 +94658,Male,54,Bachelors,4,49,32,1,15,8.0,3,73,Urban,ML Engineer,34542,0 +94659,Male,47,High School,3,31,63,71,96,0.0,4,74,Urban,Data Analyst,46549,1 +94660,Male,33,Diploma,6,93,18,16,52,0.0,0,43,Urban,Software Engineer,133662,0 +94661,Male,36,Bachelors,9,79,82,16,53,9.0,1,77,Urban,Manager,80298,1 +94662,Male,47,Diploma,5,27,24,62,6,3.0,7,76,Urban,HR Executive,133380,0 +94663,Male,53,Bachelors,12,62,49,71,52,9.0,1,37,Urban,Manager,145150,0 +94664,Female,46,Masters,11,8,4,96,22,6.0,6,88,Urban,Manager,147734,0 +94665,Male,39,Masters,0,73,30,82,87,4.0,3,46,Urban,Software Engineer,40231,0 +94666,Male,38,Bachelors,11,72,99,48,98,8.0,4,24,Rural,Data Analyst,65537,1 +94667,Male,53,Diploma,9,71,75,20,42,2.0,2,10,Semi-Urban,HR Executive,73538,0 +94668,Female,26,Masters,14,72,21,44,66,7.0,7,86,Semi-Urban,HR Executive,24835,0 +94669,Male,21,Masters,3,10,47,85,0,2.0,5,66,Urban,Software Engineer,37297,0 +94670,Male,47,Bachelors,5,53,73,92,42,4.0,6,22,Rural,Data Analyst,31052,1 +94671,Female,48,High School,0,84,75,24,65,9.0,0,4,Rural,Manager,146282,0 +94672,Male,23,Bachelors,10,92,7,71,8,6.0,6,56,Semi-Urban,Manager,118866,0 +94673,Male,45,Diploma,7,17,17,22,67,0.0,0,97,Urban,ML Engineer,137721,0 +94674,Female,37,Masters,1,7,25,8,9,8.0,0,11,Semi-Urban,Manager,27811,0 +94675,Female,32,Diploma,3,73,42,6,89,5.0,1,72,Urban,Manager,141305,0 +94676,Other,56,Bachelors,9,57,40,50,56,3.0,0,76,Urban,Data Analyst,26826,0 +94677,Male,26,Bachelors,7,91,52,6,79,2.0,6,81,Urban,Data Analyst,91924,0 +94678,Male,30,Diploma,10,54,32,89,92,4.0,1,21,Urban,HR Executive,59053,0 +94679,Male,52,Diploma,14,16,91,88,68,1.0,3,91,Rural,ML Engineer,34220,1 +94680,Male,56,High School,15,37,17,76,31,5.0,0,8,Urban,Software Engineer,89082,0 +94681,Female,29,Bachelors,16,56,61,83,26,4.0,2,97,Urban,Manager,118809,1 +94682,Male,44,High School,6,82,2,8,71,2.0,2,28,Urban,HR Executive,65901,0 +94683,Female,51,Diploma,1,34,5,36,88,6.0,2,37,Urban,HR Executive,112048,0 +94684,Other,58,Bachelors,1,32,73,96,20,9.0,5,30,Urban,ML Engineer,129193,0 +94685,Female,23,PhD,4,19,33,19,25,9.0,6,24,Urban,HR Executive,137314,0 +94686,Male,55,Diploma,1,41,33,98,55,6.0,4,79,Semi-Urban,Software Engineer,55371,1 +94687,Male,46,Bachelors,0,44,17,9,3,0.0,7,49,Semi-Urban,ML Engineer,30984,0 +94688,Male,49,Diploma,3,14,6,52,62,8.0,7,45,Urban,HR Executive,37281,0 +94689,Female,34,Diploma,16,52,2,41,23,9.0,0,8,Rural,ML Engineer,101141,0 +94690,Male,47,High School,9,19,41,99,14,6.0,0,32,Rural,Software Engineer,71460,0 +94691,Male,22,Masters,12,70,5,79,41,6.0,2,0,Urban,Data Analyst,74974,0 +94692,Male,42,High School,8,84,2,70,44,1.0,4,25,Semi-Urban,HR Executive,132367,0 +94693,Male,41,Bachelors,0,72,4,11,0,7.0,6,98,Urban,ML Engineer,117149,0 +94694,Female,27,Bachelors,18,58,37,21,84,3.0,7,23,Urban,HR Executive,135792,0 +94695,Male,36,Bachelors,11,61,33,21,23,6.0,6,45,Urban,Manager,86326,0 +94696,Male,42,Bachelors,19,26,25,81,78,1.0,6,8,Urban,ML Engineer,117577,0 +94697,Male,36,Bachelors,9,43,7,61,72,9.0,2,56,Urban,Data Analyst,28498,0 +94698,Male,53,Bachelors,8,37,3,61,66,7.0,1,62,Rural,Manager,142255,0 +94699,Male,21,Diploma,8,92,3,80,58,1.0,3,82,Urban,Data Analyst,97938,1 +94700,Male,47,PhD,19,81,96,64,33,3.0,0,30,Urban,Manager,55656,1 +94701,Male,25,High School,5,79,43,5,98,5.0,7,8,Semi-Urban,HR Executive,148112,0 +94702,Male,43,High School,6,28,56,0,10,2.0,0,8,Urban,Manager,27515,0 +94703,Male,44,Bachelors,19,49,34,71,7,9.0,0,52,Semi-Urban,Manager,106869,0 +94704,Male,23,Bachelors,7,21,60,80,9,8.0,3,45,Urban,ML Engineer,44964,0 +94705,Male,58,Bachelors,18,35,35,56,77,1.0,4,54,Semi-Urban,Software Engineer,133214,0 +94706,Male,51,Bachelors,7,22,25,15,83,3.0,3,38,Semi-Urban,Software Engineer,77106,0 +94707,Female,26,Diploma,9,47,0,13,34,1.0,7,0,Urban,ML Engineer,68739,0 +94708,Male,40,Masters,2,40,64,41,3,8.0,2,46,Urban,ML Engineer,28733,0 +94709,Female,57,Bachelors,9,76,85,65,6,1.0,4,94,Urban,ML Engineer,111523,1 +94710,Male,56,Bachelors,9,74,72,44,42,2.0,0,70,Urban,Software Engineer,126859,1 +94711,Female,58,Bachelors,3,36,25,18,79,7.0,6,22,Semi-Urban,Data Analyst,112716,0 +94712,Female,27,Bachelors,8,89,61,22,92,5.0,6,25,Rural,Data Analyst,140207,0 +94713,Female,35,Diploma,17,68,23,42,4,4.0,6,21,Urban,Manager,133761,0 +94714,Male,56,High School,1,89,23,44,69,9.0,7,84,Semi-Urban,HR Executive,143242,1 +94715,Female,49,High School,11,31,63,88,6,4.0,6,33,Urban,Manager,42185,0 +94716,Male,51,Diploma,15,84,43,0,4,4.0,1,72,Semi-Urban,ML Engineer,92320,0 +94717,Male,32,Bachelors,10,92,28,73,96,9.0,5,34,Semi-Urban,Data Analyst,68137,0 +94718,Male,56,Diploma,4,9,41,60,68,0.0,7,70,Urban,Data Analyst,54800,0 +94719,Female,33,Diploma,3,14,55,52,20,6.0,4,36,Semi-Urban,Software Engineer,80665,0 +94720,Female,47,Diploma,3,47,12,76,4,0.0,6,42,Urban,Manager,86049,0 +94721,Female,56,Diploma,13,14,84,31,10,9.0,1,49,Urban,Data Analyst,92495,0 +94722,Female,49,Masters,2,77,8,31,72,0.0,2,5,Rural,Software Engineer,133198,0 +94723,Female,56,Bachelors,16,16,7,10,9,1.0,7,90,Rural,Data Analyst,39690,0 +94724,Male,38,Diploma,4,18,9,13,98,7.0,6,65,Urban,ML Engineer,43474,0 +94725,Male,56,High School,6,36,79,20,78,1.0,6,20,Urban,HR Executive,35520,0 +94726,Male,53,Bachelors,17,18,30,94,61,0.0,7,39,Urban,Data Analyst,92063,0 +94727,Male,41,Masters,2,35,60,49,37,4.0,5,23,Urban,ML Engineer,97180,0 +94728,Male,22,Masters,17,8,22,74,49,3.0,5,28,Urban,ML Engineer,58906,0 +94729,Male,38,Masters,16,54,2,34,15,6.0,6,48,Rural,ML Engineer,140246,0 +94730,Male,46,Masters,8,92,17,10,39,3.0,6,22,Urban,ML Engineer,69272,0 +94731,Female,34,Masters,9,27,33,6,18,9.0,7,42,Semi-Urban,Manager,96331,0 +94732,Male,35,High School,7,56,39,70,65,0.0,2,9,Urban,Software Engineer,28276,0 +94733,Male,53,Bachelors,16,51,69,57,69,0.0,5,87,Urban,ML Engineer,135474,1 +94734,Female,39,Bachelors,0,52,15,46,87,3.0,3,62,Urban,Manager,105932,0 +94735,Female,38,Bachelors,0,36,61,63,4,6.0,6,85,Urban,ML Engineer,20185,1 +94736,Female,45,Masters,12,55,83,21,77,8.0,2,33,Rural,Data Analyst,60158,0 +94737,Male,30,Diploma,4,2,72,65,39,0.0,6,51,Urban,ML Engineer,37052,0 +94738,Male,35,High School,9,22,40,42,12,7.0,5,9,Urban,Manager,46829,0 +94739,Female,59,Bachelors,6,6,76,44,67,5.0,6,61,Urban,Data Analyst,136120,0 +94740,Male,38,Masters,15,81,53,17,84,2.0,4,72,Semi-Urban,Manager,89620,0 +94741,Female,21,Masters,19,79,42,67,29,8.0,4,48,Urban,Software Engineer,73790,0 +94742,Male,39,Diploma,17,90,22,34,92,3.0,0,77,Urban,Manager,94841,0 +94743,Male,57,Diploma,13,45,56,71,79,6.0,6,32,Rural,Data Analyst,114263,0 +94744,Female,57,High School,5,93,92,10,26,5.0,7,65,Urban,HR Executive,123954,1 +94745,Female,29,Masters,5,68,42,78,17,0.0,4,3,Urban,Software Engineer,141698,0 +94746,Female,44,Masters,11,78,37,2,42,1.0,1,41,Urban,HR Executive,70246,0 +94747,Female,46,Diploma,5,3,18,97,81,9.0,6,92,Urban,HR Executive,127824,0 +94748,Male,34,High School,11,11,24,31,54,6.0,7,34,Semi-Urban,HR Executive,102503,0 +94749,Other,29,Diploma,7,66,91,89,29,8.0,3,37,Semi-Urban,HR Executive,33449,1 +94750,Female,25,Bachelors,3,27,78,5,41,3.0,3,60,Urban,Software Engineer,51491,0 +94751,Male,56,Diploma,12,59,5,73,73,8.0,6,27,Semi-Urban,HR Executive,75634,0 +94752,Female,24,Diploma,4,88,79,75,46,4.0,5,50,Urban,HR Executive,128345,1 +94753,Male,23,Bachelors,15,59,78,64,23,2.0,3,60,Rural,HR Executive,118393,1 +94754,Male,23,PhD,8,46,84,91,55,6.0,1,60,Rural,Software Engineer,121748,1 +94755,Female,34,Masters,19,80,31,64,57,8.0,3,59,Rural,ML Engineer,133979,0 +94756,Male,31,Bachelors,12,83,13,95,63,3.0,4,75,Urban,Data Analyst,20000,1 +94757,Other,48,High School,1,59,69,50,17,1.0,1,77,Urban,HR Executive,81857,1 +94758,Male,26,High School,0,42,50,64,7,4.0,7,23,Urban,HR Executive,99918,0 +94759,Male,45,Bachelors,2,85,32,86,42,1.0,4,25,Rural,HR Executive,66593,0 +94760,Male,38,Bachelors,7,12,28,58,56,8.0,0,35,Urban,ML Engineer,40590,0 +94761,Female,45,Diploma,2,35,82,45,28,9.0,0,35,Rural,Manager,101789,0 +94762,Female,33,Masters,0,56,67,21,34,8.0,7,42,Semi-Urban,Manager,56637,0 +94763,Male,28,Bachelors,9,22,83,50,34,1.0,0,9,Urban,ML Engineer,30552,0 +94764,Male,32,High School,4,63,57,5,39,8.0,0,51,Urban,ML Engineer,77568,0 +94765,Male,36,Bachelors,7,55,28,26,64,3.0,4,37,Semi-Urban,ML Engineer,97489,0 +94766,Female,51,Diploma,13,38,88,61,77,5.0,0,37,Rural,Data Analyst,36780,0 +94767,Female,25,Bachelors,10,18,95,11,56,2.0,3,80,Urban,ML Engineer,61747,0 +94768,Female,39,Diploma,7,25,70,22,25,3.0,2,74,Urban,HR Executive,92594,0 +94769,Female,47,Bachelors,0,64,97,34,85,2.0,5,78,Urban,ML Engineer,31148,1 +94770,Male,33,Masters,12,21,91,90,66,4.0,0,36,Rural,Manager,142157,1 +94771,Male,29,High School,9,55,65,73,57,4.0,2,90,Semi-Urban,HR Executive,91552,1 +94772,Male,35,Diploma,4,79,25,54,97,4.0,6,6,Semi-Urban,ML Engineer,110923,0 +94773,Male,40,Bachelors,4,12,33,63,67,7.0,2,30,Urban,ML Engineer,61551,0 +94774,Male,50,Diploma,2,86,61,89,10,5.0,0,82,Urban,HR Executive,131107,1 +94775,Female,23,Bachelors,14,91,85,41,76,8.0,1,27,Semi-Urban,Manager,104233,1 +94776,Female,44,Masters,11,80,44,97,60,7.0,6,77,Urban,HR Executive,135190,1 +94777,Male,30,Masters,8,52,46,65,78,2.0,2,7,Rural,Software Engineer,24652,0 +94778,Male,29,Masters,12,65,23,24,33,8.0,2,96,Urban,Software Engineer,22361,0 +94779,Male,23,Bachelors,14,71,84,73,65,2.0,4,20,Urban,Manager,147503,1 +94780,Male,35,Diploma,0,29,1,30,2,9.0,5,60,Semi-Urban,ML Engineer,55542,0 +94781,Male,27,Bachelors,6,36,95,73,20,0.0,1,6,Urban,Data Analyst,76856,0 +94782,Female,37,Diploma,15,42,96,42,73,7.0,5,30,Urban,Data Analyst,125885,0 +94783,Female,25,Diploma,12,3,40,58,29,6.0,7,20,Rural,Data Analyst,69000,0 +94784,Male,23,Bachelors,1,87,22,19,65,0.0,4,98,Semi-Urban,Software Engineer,116074,0 +94785,Male,54,Masters,2,37,41,61,41,7.0,0,90,Rural,ML Engineer,63268,0 +94786,Male,48,Diploma,16,17,46,92,15,4.0,0,19,Urban,HR Executive,148766,0 +94787,Male,35,Diploma,13,14,47,37,49,3.0,5,92,Urban,Manager,56577,0 +94788,Female,24,Diploma,8,67,37,62,22,2.0,5,90,Urban,Data Analyst,140770,1 +94789,Male,41,High School,18,82,5,57,61,0.0,5,8,Urban,Manager,105225,0 +94790,Female,27,Bachelors,19,95,59,85,56,8.0,0,52,Rural,Data Analyst,90044,1 +94791,Male,42,PhD,17,47,34,79,51,7.0,4,74,Urban,Data Analyst,24964,0 +94792,Other,56,Diploma,16,27,64,45,27,4.0,5,83,Urban,Manager,85253,0 +94793,Female,45,High School,1,94,6,84,64,8.0,7,82,Urban,Manager,82765,1 +94794,Male,57,Bachelors,11,23,66,16,21,7.0,4,25,Urban,Data Analyst,100556,0 +94795,Male,45,High School,16,97,80,5,51,3.0,3,31,Rural,Software Engineer,60361,0 +94796,Female,56,Bachelors,11,34,6,99,26,6.0,2,21,Urban,HR Executive,41915,0 +94797,Female,38,High School,7,83,28,89,12,5.0,1,93,Urban,HR Executive,136263,1 +94798,Male,29,Bachelors,16,41,9,90,9,9.0,6,22,Semi-Urban,Data Analyst,65018,0 +94799,Male,23,High School,6,87,55,85,91,3.0,5,55,Rural,Software Engineer,40942,1 +94800,Female,24,Masters,16,18,94,8,35,8.0,6,82,Urban,Software Engineer,114658,0 +94801,Female,40,Bachelors,10,80,71,78,95,8.0,7,81,Rural,ML Engineer,138307,1 +94802,Male,30,Masters,12,20,76,13,93,5.0,5,91,Semi-Urban,HR Executive,45982,0 +94803,Female,32,Masters,7,27,17,16,61,5.0,7,13,Rural,Software Engineer,75754,0 +94804,Female,46,High School,10,41,67,49,22,7.0,3,63,Urban,ML Engineer,88090,0 +94805,Male,21,Diploma,2,98,65,64,54,8.0,2,14,Rural,Manager,117123,1 +94806,Male,24,High School,13,8,9,97,91,1.0,4,53,Urban,Data Analyst,58731,0 +94807,Male,25,Bachelors,6,56,71,34,55,1.0,7,55,Urban,ML Engineer,77951,0 +94808,Male,38,High School,1,28,62,6,84,4.0,7,93,Urban,Data Analyst,56641,0 +94809,Male,55,Diploma,6,67,15,70,15,1.0,0,92,Urban,ML Engineer,144248,1 +94810,Male,37,Masters,14,50,61,36,26,4.0,6,41,Urban,ML Engineer,74495,0 +94811,Male,22,Bachelors,11,93,26,17,6,8.0,7,33,Rural,Manager,84108,0 +94812,Male,34,Bachelors,1,14,85,22,45,9.0,1,96,Semi-Urban,ML Engineer,94373,0 +94813,Male,23,Bachelors,8,47,62,40,26,0.0,5,78,Urban,Manager,56249,0 +94814,Male,40,Bachelors,17,55,35,15,1,6.0,3,84,Rural,ML Engineer,76666,0 +94815,Male,26,Diploma,2,24,89,25,77,8.0,3,41,Urban,Manager,82114,0 +94816,Male,42,Bachelors,5,61,78,7,1,3.0,4,96,Urban,ML Engineer,144805,1 +94817,Male,24,High School,8,55,54,30,46,3.0,3,30,Urban,Data Analyst,40100,0 +94818,Male,27,Bachelors,4,15,9,67,8,9.0,5,77,Semi-Urban,Data Analyst,34968,0 +94819,Female,56,High School,4,66,18,29,22,1.0,0,94,Semi-Urban,ML Engineer,62669,0 +94820,Male,46,Diploma,2,71,95,67,47,6.0,7,77,Rural,Software Engineer,56896,1 +94821,Male,32,Bachelors,10,69,31,34,61,0.0,0,8,Rural,ML Engineer,62717,0 +94822,Male,36,Bachelors,7,60,70,36,98,6.0,2,27,Semi-Urban,HR Executive,110601,0 +94823,Male,51,Bachelors,2,57,25,32,2,4.0,6,52,Semi-Urban,Manager,43393,0 +94824,Female,50,Diploma,7,15,49,99,99,6.0,0,64,Semi-Urban,Manager,97165,0 +94825,Male,24,Bachelors,9,36,16,48,21,9.0,4,53,Urban,ML Engineer,125668,0 +94826,Male,57,Bachelors,14,94,17,63,81,4.0,3,17,Rural,Software Engineer,74969,0 +94827,Male,39,Bachelors,17,93,22,34,76,6.0,0,58,Semi-Urban,HR Executive,118266,0 +94828,Male,48,Masters,6,84,88,28,73,7.0,7,46,Urban,Software Engineer,86397,1 +94829,Female,50,Bachelors,13,21,64,92,59,8.0,4,61,Semi-Urban,HR Executive,31307,0 +94830,Male,42,High School,17,78,19,17,31,9.0,2,45,Urban,ML Engineer,98920,0 +94831,Male,38,High School,11,17,35,4,68,3.0,4,75,Urban,Data Analyst,124673,0 +94832,Female,56,Diploma,14,8,96,73,44,4.0,5,77,Urban,Data Analyst,99222,1 +94833,Male,23,Bachelors,16,16,2,12,29,9.0,7,69,Urban,Manager,87284,0 +94834,Male,43,Masters,9,77,29,42,21,2.0,1,61,Semi-Urban,HR Executive,75521,0 +94835,Male,59,High School,10,36,15,84,88,4.0,4,24,Semi-Urban,Data Analyst,97952,0 +94836,Male,49,Masters,4,32,59,25,24,3.0,6,80,Rural,HR Executive,125645,0 +94837,Female,40,Masters,18,78,79,78,89,7.0,4,15,Urban,Software Engineer,92604,1 +94838,Female,44,Masters,3,43,72,60,53,5.0,6,4,Semi-Urban,HR Executive,133513,0 +94839,Male,55,Bachelors,8,69,31,56,34,0.0,1,69,Rural,HR Executive,115521,0 +94840,Male,53,Masters,7,34,38,55,34,5.0,0,83,Rural,ML Engineer,33102,0 +94841,Female,40,High School,15,85,9,25,44,2.0,1,99,Semi-Urban,Manager,20975,0 +94842,Male,49,Bachelors,2,62,5,62,97,9.0,3,62,Rural,HR Executive,85377,0 +94843,Male,21,Masters,6,18,37,91,41,0.0,2,14,Urban,Manager,39373,0 +94844,Male,35,Bachelors,19,28,37,42,11,1.0,7,8,Urban,Data Analyst,25920,0 +94845,Male,44,Bachelors,13,0,68,23,79,9.0,1,16,Urban,Manager,122588,0 +94846,Male,57,High School,8,44,97,80,93,6.0,6,37,Semi-Urban,HR Executive,77310,1 +94847,Male,36,High School,1,71,77,30,10,1.0,3,91,Rural,Software Engineer,117888,1 +94848,Female,45,Diploma,16,64,94,92,87,5.0,1,13,Urban,HR Executive,77376,1 +94849,Male,21,Diploma,18,33,5,13,23,8.0,3,46,Semi-Urban,ML Engineer,136852,0 +94850,Other,35,Masters,12,25,87,63,40,8.0,0,76,Semi-Urban,ML Engineer,46136,1 +94851,Male,41,Diploma,1,13,67,16,33,7.0,6,18,Rural,HR Executive,59864,0 +94852,Male,29,Masters,4,87,6,0,10,9.0,5,62,Urban,ML Engineer,80553,0 +94853,Male,37,Bachelors,19,52,23,70,97,0.0,1,35,Semi-Urban,Manager,137612,0 +94854,Male,55,PhD,5,76,4,36,53,4.0,2,36,Semi-Urban,Data Analyst,56696,0 +94855,Male,42,Diploma,19,15,37,56,27,4.0,0,78,Rural,Software Engineer,33792,0 +94856,Male,46,Bachelors,6,57,3,16,80,8.0,6,50,Semi-Urban,HR Executive,101734,0 +94857,Male,45,Masters,12,62,43,63,84,7.0,5,90,Semi-Urban,ML Engineer,146924,1 +94858,Male,50,High School,14,84,13,64,51,6.0,4,7,Rural,Manager,31505,0 +94859,Female,31,PhD,17,86,78,98,98,2.0,3,65,Semi-Urban,HR Executive,72271,1 +94860,Female,43,Bachelors,19,81,57,50,84,3.0,7,67,Urban,ML Engineer,31516,1 +94861,Female,39,Bachelors,3,52,72,32,47,7.0,5,47,Rural,Software Engineer,129608,0 +94862,Female,41,PhD,5,14,64,96,99,7.0,4,18,Urban,Manager,118566,0 +94863,Male,23,Bachelors,17,60,38,74,64,0.0,5,83,Rural,Software Engineer,115175,1 +94864,Male,23,High School,11,50,26,34,97,5.0,4,74,Rural,ML Engineer,46762,0 +94865,Male,54,Diploma,10,80,95,19,19,1.0,5,34,Urban,Software Engineer,75523,0 +94866,Female,22,Bachelors,2,33,76,63,90,7.0,1,9,Semi-Urban,HR Executive,33438,0 +94867,Male,25,Diploma,7,57,82,11,56,6.0,2,80,Urban,Manager,50769,0 +94868,Male,43,Bachelors,8,28,90,5,53,6.0,7,95,Urban,Data Analyst,97517,0 +94869,Male,28,PhD,8,98,43,20,59,0.0,5,25,Semi-Urban,Manager,76570,0 +94870,Male,23,Diploma,11,35,3,75,36,8.0,0,2,Rural,HR Executive,114723,0 +94871,Male,24,Diploma,14,44,56,8,31,7.0,3,75,Urban,ML Engineer,24261,0 +94872,Female,30,Bachelors,11,73,7,12,31,3.0,3,34,Urban,HR Executive,32240,0 +94873,Female,36,Masters,19,57,61,58,6,1.0,1,47,Urban,Data Analyst,74284,0 +94874,Male,24,Bachelors,13,76,6,33,20,0.0,1,26,Urban,Data Analyst,68132,0 +94875,Male,38,Masters,8,49,57,39,3,1.0,0,60,Urban,Data Analyst,141550,0 +94876,Female,55,Diploma,19,48,28,1,36,8.0,3,38,Urban,ML Engineer,68044,0 +94877,Male,27,High School,10,14,0,4,33,8.0,0,59,Semi-Urban,ML Engineer,144424,0 +94878,Male,43,Bachelors,14,37,68,1,79,3.0,6,81,Semi-Urban,Manager,124554,0 +94879,Female,59,Bachelors,14,85,3,66,24,1.0,4,40,Urban,HR Executive,27379,0 +94880,Male,45,Bachelors,18,96,49,97,68,2.0,4,68,Urban,HR Executive,69569,1 +94881,Male,26,High School,3,21,48,9,89,2.0,3,3,Semi-Urban,ML Engineer,38594,0 +94882,Male,21,High School,12,82,67,15,62,8.0,6,2,Urban,HR Executive,142230,0 +94883,Male,49,Diploma,14,64,7,39,23,0.0,5,54,Rural,ML Engineer,28958,0 +94884,Female,37,Masters,7,55,97,53,1,1.0,4,18,Urban,HR Executive,104378,0 +94885,Male,29,Bachelors,3,91,23,46,11,4.0,1,12,Semi-Urban,Manager,87284,0 +94886,Male,33,Masters,16,11,37,69,70,8.0,0,49,Semi-Urban,Software Engineer,61948,0 +94887,Other,56,Bachelors,3,0,23,96,9,1.0,1,55,Urban,Manager,121552,0 +94888,Female,40,Diploma,12,20,37,48,26,4.0,4,30,Urban,Software Engineer,92366,0 +94889,Male,36,Diploma,0,86,40,42,69,9.0,5,42,Semi-Urban,Software Engineer,82252,0 +94890,Female,27,Bachelors,16,30,93,47,85,5.0,2,27,Urban,HR Executive,142951,0 +94891,Female,26,Bachelors,6,78,45,55,41,9.0,0,34,Semi-Urban,Manager,60859,0 +94892,Male,40,Bachelors,3,9,94,96,93,6.0,5,73,Urban,HR Executive,148381,1 +94893,Male,27,Diploma,19,26,88,65,66,4.0,6,52,Urban,Software Engineer,69559,0 +94894,Female,22,Masters,12,83,5,35,23,5.0,5,14,Urban,Data Analyst,141918,0 +94895,Male,39,Bachelors,11,18,3,6,42,3.0,4,43,Semi-Urban,Data Analyst,28198,0 +94896,Female,47,Bachelors,13,63,60,63,96,3.0,0,39,Urban,Data Analyst,133191,0 +94897,Male,34,Masters,0,47,86,81,93,7.0,3,78,Urban,Data Analyst,68750,1 +94898,Male,24,Diploma,7,81,15,69,51,8.0,2,75,Urban,Manager,131925,1 +94899,Male,52,Bachelors,12,1,69,47,61,7.0,5,2,Urban,Manager,100387,0 +94900,Male,38,Bachelors,1,39,98,27,57,8.0,2,50,Urban,HR Executive,83956,0 +94901,Male,25,Masters,3,45,12,4,93,4.0,4,27,Semi-Urban,HR Executive,28306,0 +94902,Male,50,Masters,10,0,28,72,22,7.0,1,56,Semi-Urban,Manager,126970,0 +94903,Male,34,Diploma,14,17,66,83,7,4.0,6,27,Urban,Software Engineer,67921,0 +94904,Other,22,Masters,6,6,55,86,53,9.0,1,36,Semi-Urban,Data Analyst,114994,0 +94905,Female,54,High School,18,1,59,56,41,5.0,5,28,Urban,ML Engineer,111097,0 +94906,Male,42,Diploma,13,69,27,70,74,9.0,4,62,Semi-Urban,ML Engineer,62886,0 +94907,Male,53,Diploma,19,85,13,29,9,7.0,2,74,Semi-Urban,Manager,80518,0 +94908,Male,23,Bachelors,12,17,21,19,57,7.0,0,35,Urban,Data Analyst,124763,0 +94909,Male,55,Diploma,15,98,49,20,73,8.0,3,17,Semi-Urban,Data Analyst,47658,0 +94910,Male,51,Bachelors,0,44,50,93,62,7.0,5,97,Semi-Urban,HR Executive,106468,1 +94911,Female,36,Masters,3,71,79,48,93,4.0,6,32,Urban,Software Engineer,66444,0 +94912,Female,38,High School,15,86,57,10,70,5.0,5,49,Semi-Urban,Software Engineer,137747,0 +94913,Female,51,Diploma,11,6,62,87,7,3.0,1,36,Rural,HR Executive,43983,0 +94914,Male,37,Bachelors,17,15,56,50,58,9.0,5,53,Semi-Urban,Data Analyst,78699,0 +94915,Male,41,Masters,10,60,3,32,34,8.0,2,91,Rural,ML Engineer,34429,0 +94916,Male,35,Bachelors,17,96,0,74,79,5.0,5,67,Semi-Urban,Software Engineer,110516,1 +94917,Female,35,Bachelors,9,11,81,40,86,8.0,0,9,Urban,Manager,64879,0 +94918,Male,52,Bachelors,2,40,80,23,59,1.0,3,45,Urban,Data Analyst,90741,0 +94919,Male,55,Bachelors,6,91,84,15,81,4.0,7,24,Urban,HR Executive,143663,0 +94920,Male,42,Diploma,8,73,5,23,10,3.0,4,22,Urban,Manager,25559,0 +94921,Female,50,Diploma,18,26,10,98,62,4.0,6,69,Urban,Manager,89153,0 +94922,Male,57,High School,14,37,93,50,77,9.0,1,6,Urban,Software Engineer,43580,0 +94923,Male,44,Masters,8,76,99,14,96,0.0,3,77,Urban,HR Executive,24356,1 +94924,Female,48,Masters,13,97,43,59,74,4.0,1,18,Urban,ML Engineer,63091,0 +94925,Male,39,Masters,17,49,20,17,5,5.0,5,98,Urban,HR Executive,130836,0 +94926,Female,41,Bachelors,8,28,67,60,62,7.0,2,29,Urban,HR Executive,114427,0 +94927,Male,55,Bachelors,8,68,9,31,14,9.0,1,85,Semi-Urban,ML Engineer,20144,0 +94928,Male,32,Masters,6,74,40,80,42,9.0,6,97,Rural,Manager,121315,1 +94929,Male,37,Bachelors,1,15,45,2,53,7.0,5,27,Urban,Manager,68578,0 +94930,Other,33,Bachelors,9,43,49,62,41,4.0,0,30,Semi-Urban,Data Analyst,45683,0 +94931,Male,36,Diploma,1,58,68,5,28,7.0,4,54,Semi-Urban,Software Engineer,136810,0 +94932,Female,43,Diploma,16,93,33,33,79,8.0,0,60,Urban,Software Engineer,41246,0 +94933,Other,57,Masters,19,84,84,62,39,9.0,5,38,Rural,Software Engineer,147114,1 +94934,Male,37,Masters,0,42,87,45,69,9.0,7,69,Semi-Urban,Software Engineer,122408,1 +94935,Male,36,High School,18,4,32,16,77,1.0,2,6,Urban,Software Engineer,109665,0 +94936,Other,46,Bachelors,17,75,54,2,72,3.0,2,15,Rural,Software Engineer,22095,0 +94937,Male,51,High School,18,2,72,46,31,6.0,1,98,Semi-Urban,ML Engineer,78204,0 +94938,Female,30,Masters,12,52,18,9,74,5.0,5,47,Semi-Urban,HR Executive,30358,0 +94939,Female,29,Bachelors,13,17,31,50,52,8.0,2,58,Semi-Urban,HR Executive,110031,0 +94940,Male,58,Bachelors,8,91,85,97,66,4.0,1,91,Urban,Software Engineer,43049,1 +94941,Male,42,Diploma,3,43,52,11,87,8.0,5,38,Semi-Urban,Manager,148514,0 +94942,Female,28,Bachelors,8,75,71,81,0,0.0,4,81,Urban,Manager,88974,1 +94943,Male,45,Bachelors,13,53,41,61,30,0.0,2,1,Semi-Urban,ML Engineer,47980,0 +94944,Male,25,Masters,8,8,40,63,85,4.0,0,29,Urban,Data Analyst,104270,0 +94945,Male,55,Bachelors,9,15,22,49,22,9.0,3,47,Semi-Urban,Software Engineer,51032,0 +94946,Male,32,Bachelors,3,74,34,89,7,0.0,7,86,Urban,HR Executive,133429,1 +94947,Male,24,Masters,11,26,35,47,8,9.0,5,72,Semi-Urban,Manager,84588,0 +94948,Male,29,Diploma,4,64,93,44,35,2.0,4,98,Rural,Data Analyst,98780,1 +94949,Male,51,Masters,4,43,19,76,15,5.0,5,48,Rural,Software Engineer,140938,0 +94950,Female,37,Diploma,18,27,55,5,5,3.0,6,65,Urban,Software Engineer,36039,0 +94951,Male,46,High School,13,21,32,48,67,6.0,1,73,Urban,Software Engineer,124790,0 +94952,Male,33,High School,12,60,17,49,72,6.0,3,28,Semi-Urban,Software Engineer,77324,0 +94953,Male,49,Diploma,14,54,91,33,13,6.0,0,20,Urban,Software Engineer,125604,0 +94954,Male,29,Bachelors,18,10,68,98,96,6.0,7,53,Urban,Data Analyst,26564,0 +94955,Male,28,Masters,11,87,50,99,48,6.0,7,78,Rural,Data Analyst,50980,1 +94956,Male,30,Diploma,14,79,35,45,73,5.0,2,83,Semi-Urban,ML Engineer,124287,1 +94957,Female,22,Bachelors,14,74,59,31,0,2.0,0,19,Urban,HR Executive,101286,0 +94958,Male,55,Bachelors,17,61,37,96,56,9.0,5,35,Urban,Software Engineer,51859,0 +94959,Male,44,Diploma,3,56,71,39,82,3.0,4,24,Rural,Data Analyst,25710,0 +94960,Female,53,Bachelors,2,1,72,12,38,6.0,3,7,Urban,HR Executive,63331,0 +94961,Female,27,Diploma,2,26,10,18,56,0.0,5,98,Urban,Manager,76394,0 +94962,Male,41,PhD,8,17,66,56,31,7.0,7,51,Semi-Urban,Data Analyst,41744,0 +94963,Male,26,Diploma,10,68,55,35,49,1.0,3,97,Semi-Urban,HR Executive,114631,1 +94964,Female,24,Bachelors,4,15,34,58,54,8.0,5,30,Semi-Urban,Software Engineer,74029,0 +94965,Male,29,Masters,4,77,6,96,58,1.0,4,52,Urban,HR Executive,65348,0 +94966,Female,31,Bachelors,17,69,73,92,19,1.0,0,50,Rural,Software Engineer,143752,1 +94967,Female,54,Bachelors,3,91,64,24,45,0.0,1,45,Urban,Data Analyst,80038,0 +94968,Male,45,High School,18,21,87,61,70,0.0,6,95,Urban,Data Analyst,20797,1 +94969,Female,54,High School,0,19,64,71,68,0.0,5,89,Urban,ML Engineer,99232,1 +94970,Male,31,Masters,4,37,82,72,82,0.0,4,66,Semi-Urban,Data Analyst,94908,1 +94971,Female,22,Bachelors,19,6,65,8,68,0.0,2,13,Rural,Manager,27702,0 +94972,Male,36,Bachelors,15,68,31,81,40,0.0,3,34,Rural,Software Engineer,32060,0 +94973,Female,41,Masters,4,61,7,25,66,5.0,1,12,Urban,Manager,122872,0 +94974,Male,38,Masters,14,73,87,2,53,8.0,3,91,Urban,Data Analyst,149089,1 +94975,Male,29,Bachelors,11,72,59,70,96,6.0,5,81,Rural,Software Engineer,121862,1 +94976,Male,36,Bachelors,10,26,16,67,79,7.0,7,49,Urban,Software Engineer,78873,0 +94977,Male,53,PhD,19,99,88,0,52,9.0,7,12,Urban,ML Engineer,88296,0 +94978,Female,53,Bachelors,4,89,45,98,76,4.0,0,63,Rural,ML Engineer,148211,1 +94979,Male,43,High School,6,63,39,79,88,2.0,5,55,Urban,Data Analyst,131820,1 +94980,Male,54,Bachelors,13,44,85,79,72,5.0,0,97,Urban,Manager,136352,1 +94981,Male,47,Bachelors,17,14,32,41,56,4.0,3,50,Rural,ML Engineer,131605,0 +94982,Female,26,Bachelors,10,43,54,39,43,,4,59,Urban,Manager,74394,0 +94983,Male,49,Diploma,0,28,93,79,81,2.0,2,57,Urban,Manager,42013,1 +94984,Male,56,Masters,1,53,1,91,92,9.0,6,35,Urban,Manager,41602,0 +94985,Male,29,Bachelors,7,98,47,43,74,8.0,4,39,Urban,Manager,125500,0 +94986,Female,33,Bachelors,5,10,17,25,93,5.0,7,24,Urban,Data Analyst,115547,0 +94987,Male,24,PhD,4,47,21,63,35,7.0,7,84,Urban,Manager,83560,0 +94988,Female,31,Bachelors,13,80,79,61,73,2.0,6,65,Urban,ML Engineer,96287,1 +94989,Male,45,Diploma,8,53,1,1,65,0.0,4,16,Semi-Urban,Manager,91210,0 +94990,Female,54,Bachelors,4,48,19,5,31,2.0,4,88,Semi-Urban,Manager,22690,0 +94991,Female,34,Masters,7,30,25,32,0,3.0,0,17,Semi-Urban,Data Analyst,32070,0 +94992,Other,42,PhD,14,96,79,77,94,2.0,1,80,Urban,Software Engineer,90404,1 +94993,Female,37,Bachelors,10,86,34,42,95,1.0,0,50,Urban,ML Engineer,59116,0 +94994,Female,53,Diploma,12,4,93,29,41,1.0,3,71,Semi-Urban,Software Engineer,80614,0 +94995,Male,28,High School,3,91,99,57,23,8.0,7,34,Urban,Data Analyst,124030,1 +94996,Other,53,Bachelors,19,41,0,6,18,6.0,2,64,Semi-Urban,ML Engineer,96886,0 +94997,Male,22,Diploma,4,59,20,99,36,9.0,6,56,Rural,HR Executive,92822,0 +94998,Female,29,PhD,19,59,81,26,10,6.0,6,29,Urban,Manager,142018,0 +94999,Male,24,Bachelors,8,75,69,65,6,7.0,1,88,Urban,ML Engineer,73570,1 +95000,Female,36,Diploma,14,53,89,91,9,4.0,0,91,Urban,Manager,63223,1 +95001,Female,58,Masters,16,31,57,7,48,2.0,4,78,Urban,Data Analyst,47334,0 +95002,Male,21,High School,9,21,14,11,4,7.0,4,87,Urban,HR Executive,73887,0 +95003,Male,45,Diploma,8,69,14,58,4,1.0,4,67,Urban,ML Engineer,119990,0 +95004,Female,55,Diploma,3,30,82,66,91,7.0,3,64,Semi-Urban,Manager,29484,1 +95005,Female,59,Bachelors,14,68,7,96,68,8.0,0,53,Urban,Software Engineer,79534,0 +95006,Female,21,Diploma,14,10,29,45,23,9.0,6,26,Urban,Software Engineer,127037,0 +95007,Male,48,Bachelors,17,45,57,68,25,9.0,1,32,Urban,Data Analyst,72630,0 +95008,Male,55,Bachelors,17,91,22,67,13,1.0,2,54,Urban,HR Executive,40838,0 +95009,Female,45,PhD,19,35,20,4,67,7.0,3,52,Rural,HR Executive,20052,0 +95010,Other,44,Masters,12,89,46,20,87,8.0,2,52,Semi-Urban,HR Executive,149121,0 +95011,Male,41,Diploma,9,35,77,20,47,4.0,4,14,Urban,Data Analyst,37753,0 +95012,Female,56,Bachelors,12,9,2,52,91,2.0,6,80,Semi-Urban,Software Engineer,66033,0 +95013,Male,55,Bachelors,18,22,67,10,49,8.0,0,9,Urban,Manager,75180,0 +95014,Female,31,High School,18,13,51,25,3,5.0,4,63,Urban,Manager,52889,0 +95015,Male,44,Diploma,12,97,30,52,19,7.0,2,76,Urban,Manager,68120,1 +95016,Female,58,High School,17,81,48,63,34,7.0,5,20,Urban,Manager,143927,0 +95017,Male,43,High School,12,60,81,82,86,0.0,5,65,Urban,Data Analyst,60283,1 +95018,Female,55,Bachelors,1,41,52,65,37,2.0,1,16,Urban,ML Engineer,119049,0 +95019,Female,21,Bachelors,3,63,11,99,22,1.0,7,39,Semi-Urban,HR Executive,126564,0 +95020,Female,47,Bachelors,0,83,59,7,53,8.0,5,62,Urban,Manager,79051,0 +95021,Male,36,Masters,6,18,52,79,44,5.0,5,47,Semi-Urban,Data Analyst,127210,0 +95022,Male,24,High School,9,84,57,80,78,5.0,0,84,Urban,HR Executive,108911,1 +95023,Female,23,Bachelors,4,75,37,1,9,0.0,5,33,Semi-Urban,Manager,141617,0 +95024,Female,55,High School,9,63,97,94,90,3.0,6,69,Urban,ML Engineer,81989,1 +95025,Male,32,Bachelors,11,68,66,86,70,8.0,4,49,Urban,ML Engineer,47460,1 +95026,Male,41,Diploma,16,85,92,12,94,2.0,1,23,Semi-Urban,Manager,37498,0 +95027,Male,28,Diploma,5,47,76,65,92,4.0,1,95,Urban,Manager,53452,1 +95028,Female,35,PhD,15,36,36,14,54,6.0,1,95,Rural,ML Engineer,104039,0 +95029,Female,26,Diploma,16,21,2,16,94,9.0,4,72,Rural,Manager,48190,0 +95030,Female,26,Bachelors,18,67,58,23,83,0.0,2,71,Semi-Urban,ML Engineer,83118,0 +95031,Female,36,Masters,9,15,52,1,52,1.0,7,99,Urban,Manager,88018,0 +95032,Male,57,Bachelors,6,50,86,73,24,8.0,6,5,Urban,HR Executive,59150,0 +95033,Female,39,Bachelors,0,95,91,50,69,3.0,3,27,Urban,Software Engineer,49053,1 +95034,Female,42,Masters,10,17,86,92,55,6.0,6,26,Urban,ML Engineer,124684,0 +95035,Male,27,Bachelors,0,26,24,76,33,8.0,7,0,Urban,Data Analyst,48383,0 +95036,Male,34,Bachelors,13,63,75,70,24,6.0,0,52,Semi-Urban,HR Executive,61876,1 +95037,Male,28,High School,0,37,53,48,70,9.0,0,97,Rural,Manager,68742,1 +95038,Male,31,Masters,2,97,22,81,40,2.0,3,37,Urban,Software Engineer,54278,1 +95039,Female,58,Bachelors,3,27,8,20,29,9.0,6,17,Rural,Manager,88755,0 +95040,Male,49,Diploma,2,32,22,64,38,5.0,7,11,Semi-Urban,ML Engineer,115219,0 +95041,Male,55,Masters,13,77,85,2,83,5.0,6,8,Urban,Software Engineer,126448,0 +95042,Female,56,Bachelors,19,57,31,68,0,8.0,4,30,Semi-Urban,Manager,117818,0 +95043,Male,53,Bachelors,5,45,91,1,38,2.0,2,73,Rural,Software Engineer,147716,0 +95044,Male,46,Diploma,7,59,81,25,46,4.0,4,60,Urban,HR Executive,116798,0 +95045,Male,39,Bachelors,11,20,48,94,61,1.0,2,86,Semi-Urban,HR Executive,25230,1 +95046,Female,32,Bachelors,10,94,19,90,56,3.0,2,84,Semi-Urban,HR Executive,79570,1 +95047,Male,32,Masters,13,68,5,2,86,6.0,6,46,Semi-Urban,Data Analyst,75212,0 +95048,Male,42,Masters,14,51,31,88,18,3.0,1,12,Urban,HR Executive,128438,0 +95049,Male,26,Bachelors,11,46,93,17,79,9.0,6,37,Semi-Urban,Software Engineer,23717,0 +95050,Male,48,Bachelors,11,89,63,96,16,1.0,6,14,Urban,Data Analyst,124596,1 +95051,Male,31,Bachelors,8,75,1,36,90,9.0,6,1,Urban,Software Engineer,146142,0 +95052,Male,39,Bachelors,17,1,49,31,28,7.0,1,44,Urban,HR Executive,127981,0 +95053,Male,55,Masters,15,27,7,33,67,4.0,6,75,Semi-Urban,HR Executive,30838,0 +95054,Male,48,Bachelors,9,77,4,4,41,8.0,7,1,Urban,HR Executive,119430,0 +95055,Male,38,Bachelors,0,21,94,38,72,7.0,1,95,Rural,HR Executive,102441,1 +95056,Male,37,High School,2,44,45,2,52,3.0,6,85,Rural,HR Executive,68973,0 +95057,Female,21,Masters,16,39,6,42,34,6.0,7,66,Semi-Urban,HR Executive,35032,0 +95058,Male,23,Masters,18,36,10,97,26,0.0,5,14,Urban,Manager,117977,0 +95059,Female,25,Bachelors,8,41,89,21,38,3.0,2,75,Urban,ML Engineer,81407,0 +95060,Female,34,Bachelors,17,65,27,59,57,9.0,5,70,Urban,ML Engineer,127244,0 +95061,Female,29,Diploma,16,58,45,48,75,4.0,2,52,Urban,Manager,115888,0 +95062,Female,42,Bachelors,11,37,24,33,12,2.0,4,25,Semi-Urban,Manager,87503,0 +95063,Female,40,High School,3,72,99,65,39,4.0,6,55,Urban,HR Executive,109155,1 +95064,Male,49,PhD,18,89,9,87,39,9.0,4,32,Semi-Urban,HR Executive,82862,0 +95065,Male,23,Bachelors,1,76,16,16,47,9.0,7,43,Rural,Software Engineer,76054,0 +95066,Male,23,Bachelors,9,6,80,13,73,6.0,5,75,Rural,ML Engineer,146046,0 +95067,Male,32,High School,5,11,69,26,46,0.0,0,27,Urban,Software Engineer,74545,0 +95068,Male,39,Diploma,3,22,80,97,44,6.0,0,62,Rural,Data Analyst,69645,1 +95069,Male,30,Diploma,15,10,41,84,6,6.0,4,28,Rural,Manager,30063,0 +95070,Female,50,Bachelors,14,99,61,45,2,2.0,5,18,Rural,HR Executive,148153,0 +95071,Female,57,PhD,2,47,19,52,36,1.0,6,93,Urban,ML Engineer,37767,0 +95072,Male,42,Diploma,19,9,76,97,40,5.0,0,49,Urban,Software Engineer,39823,0 +95073,Male,28,High School,15,77,43,77,38,9.0,4,18,Urban,Software Engineer,141297,0 +95074,Female,25,Diploma,12,64,9,20,86,2.0,5,2,Urban,ML Engineer,33535,0 +95075,Male,50,Bachelors,17,80,36,62,55,7.0,4,31,Semi-Urban,ML Engineer,24896,0 +95076,Male,29,Diploma,5,63,96,36,28,3.0,6,53,Rural,HR Executive,117439,1 +95077,Female,31,Masters,13,33,2,93,12,2.0,3,8,Urban,Manager,86273,0 +95078,Male,51,High School,4,13,95,1,93,1.0,4,31,Semi-Urban,Software Engineer,86680,0 +95079,Female,44,Diploma,16,1,59,63,82,4.0,1,61,Urban,ML Engineer,40596,0 +95080,Male,54,High School,19,0,67,83,29,8.0,1,54,Urban,Manager,32725,0 +95081,Male,44,High School,18,8,46,4,90,9.0,7,94,Urban,ML Engineer,144561,0 +95082,Male,43,Bachelors,10,99,31,52,53,0.0,5,80,Semi-Urban,Software Engineer,143914,1 +95083,Male,49,Masters,12,37,31,44,58,3.0,2,94,Urban,Software Engineer,149848,0 +95084,Female,36,Bachelors,10,80,72,61,66,7.0,4,67,Semi-Urban,ML Engineer,79639,1 +95085,Male,43,Bachelors,12,87,97,97,90,3.0,6,61,Semi-Urban,ML Engineer,59036,1 +95086,Female,51,High School,19,84,9,93,32,3.0,7,84,Urban,HR Executive,111101,1 +95087,Male,57,Bachelors,17,62,65,0,58,6.0,3,87,Urban,ML Engineer,70367,0 +95088,Male,38,Masters,2,53,73,75,27,6.0,3,26,Rural,Data Analyst,49609,0 +95089,Female,58,Diploma,7,26,38,21,95,4.0,6,12,Rural,Manager,147980,0 +95090,Female,56,Bachelors,11,49,53,71,98,3.0,7,11,Rural,Software Engineer,63734,0 +95091,Male,40,High School,11,44,95,39,80,5.0,7,67,Rural,Data Analyst,138615,1 +95092,Male,59,Masters,17,80,76,16,66,1.0,2,36,Rural,ML Engineer,126248,0 +95093,Female,44,Diploma,3,85,59,97,5,0.0,0,83,Rural,Software Engineer,35597,1 +95094,Female,55,Bachelors,6,94,38,86,46,6.0,5,37,Urban,Manager,55759,1 +95095,Female,43,High School,0,94,30,8,11,7.0,2,45,Rural,Data Analyst,81241,0 +95096,Male,28,Bachelors,15,49,63,51,68,1.0,0,42,Semi-Urban,Data Analyst,102206,0 +95097,Male,53,Diploma,6,85,69,75,54,0.0,4,32,Urban,Data Analyst,108214,1 +95098,Female,27,Masters,13,6,94,71,57,1.0,6,47,Urban,Manager,82991,0 +95099,Female,59,Bachelors,18,99,94,5,39,6.0,6,90,Urban,Data Analyst,132815,1 +95100,Female,24,High School,14,35,44,87,93,3.0,5,80,Urban,Data Analyst,100719,1 +95101,Female,26,High School,1,73,98,11,96,9.0,4,60,Rural,Data Analyst,116156,1 +95102,Male,30,Bachelors,5,15,46,28,34,7.0,6,18,Semi-Urban,HR Executive,46597,0 +95103,Male,45,High School,14,8,0,39,31,4.0,0,26,Semi-Urban,ML Engineer,80164,0 +95104,Male,21,Masters,13,40,60,87,56,7.0,3,59,Semi-Urban,ML Engineer,144391,1 +95105,Male,23,Diploma,2,53,38,98,38,5.0,7,7,Rural,Data Analyst,111553,0 +95106,Male,38,Diploma,3,40,79,28,88,8.0,2,11,Urban,Data Analyst,26141,0 +95107,Female,45,High School,17,73,85,78,44,6.0,2,42,Urban,ML Engineer,70999,1 +95108,Male,34,Masters,8,10,9,3,77,3.0,7,85,Semi-Urban,Software Engineer,127515,0 +95109,Female,33,Diploma,14,95,86,37,99,3.0,3,51,Semi-Urban,Manager,149332,1 +95110,Male,52,Bachelors,14,74,27,31,10,8.0,3,63,Urban,ML Engineer,148911,0 +95111,Male,41,Bachelors,11,88,36,30,42,8.0,6,93,Rural,HR Executive,109779,1 +95112,Male,22,Bachelors,4,86,6,95,63,0.0,6,92,Rural,ML Engineer,60696,1 +95113,Male,47,Bachelors,12,93,88,49,15,4.0,7,50,Semi-Urban,Manager,41307,1 +95114,Male,23,Diploma,9,44,4,67,14,3.0,3,39,Urban,HR Executive,78598,0 +95115,Male,30,Bachelors,4,15,61,73,69,9.0,1,94,Semi-Urban,Manager,112722,1 +95116,Male,33,Bachelors,17,18,0,9,26,6.0,7,40,Rural,Software Engineer,47267,0 +95117,Male,27,Masters,17,9,6,27,68,0.0,7,15,Urban,HR Executive,115916,0 +95118,Female,34,Bachelors,4,76,97,31,3,8.0,4,56,Urban,Manager,137828,1 +95119,Male,23,Masters,5,21,20,68,39,9.0,7,11,Rural,Manager,145555,0 +95120,Female,21,High School,6,32,57,82,17,2.0,0,39,Urban,ML Engineer,147250,0 +95121,Male,33,Bachelors,5,94,33,73,63,8.0,4,84,Rural,Software Engineer,133121,1 +95122,Other,29,Diploma,15,1,57,85,25,9.0,6,63,Urban,ML Engineer,63908,0 +95123,Female,33,PhD,10,79,15,19,88,8.0,3,39,Rural,Data Analyst,91563,0 +95124,Male,40,Bachelors,18,48,82,17,34,1.0,7,30,Semi-Urban,ML Engineer,67418,0 +95125,Male,53,Masters,4,42,93,59,37,8.0,6,0,Semi-Urban,Manager,115085,0 +95126,Female,26,Bachelors,2,49,91,48,5,9.0,4,67,Urban,Manager,23159,1 +95127,Female,43,High School,15,79,80,61,95,8.0,7,21,Urban,Software Engineer,86299,1 +95128,Male,43,High School,13,82,75,6,67,3.0,7,67,Urban,Data Analyst,122518,0 +95129,Male,31,Bachelors,19,21,44,91,8,8.0,0,47,Semi-Urban,Manager,146256,0 +95130,Male,45,Diploma,8,96,61,83,30,5.0,1,95,Urban,HR Executive,54760,1 +95131,Male,35,Masters,19,73,82,49,17,3.0,6,11,Urban,HR Executive,78999,0 +95132,Male,49,Bachelors,2,91,90,96,83,3.0,2,74,Urban,Software Engineer,96568,1 +95133,Female,49,High School,0,89,37,87,26,4.0,1,46,Urban,Manager,88392,1 +95134,Male,49,Masters,12,9,84,79,15,4.0,1,57,Urban,Software Engineer,25823,0 +95135,Female,36,Diploma,3,45,68,69,80,1.0,6,85,Semi-Urban,Manager,22440,1 +95136,Male,51,High School,4,74,35,73,21,9.0,7,12,Semi-Urban,HR Executive,53252,0 +95137,Female,22,Bachelors,17,81,64,47,33,8.0,7,6,Urban,HR Executive,110294,0 +95138,Male,28,Bachelors,6,39,54,64,15,2.0,1,5,Semi-Urban,ML Engineer,74543,0 +95139,Female,56,Bachelors,2,20,97,91,64,0.0,1,13,Rural,HR Executive,51238,0 +95140,Female,36,PhD,0,43,63,66,45,4.0,3,91,Urban,Software Engineer,69321,1 +95141,Female,38,Masters,13,27,40,78,61,4.0,0,93,Rural,Manager,81630,0 +95142,Male,23,Diploma,14,26,99,83,82,0.0,0,38,Semi-Urban,ML Engineer,118119,1 +95143,Female,23,Masters,12,59,52,97,35,0.0,3,76,Urban,Software Engineer,68279,1 +95144,Male,56,Bachelors,2,45,50,0,0,5.0,4,49,Urban,Software Engineer,99075,0 +95145,Male,33,Masters,3,49,61,76,16,9.0,5,85,Urban,Manager,62703,1 +95146,Male,26,Masters,8,48,95,34,82,4.0,2,74,Rural,HR Executive,99631,1 +95147,Male,29,Bachelors,3,64,68,2,9,1.0,7,53,Semi-Urban,Manager,25116,0 +95148,Male,58,High School,14,97,73,88,11,0.0,6,35,Urban,Software Engineer,115450,1 +95149,Male,35,Diploma,11,17,28,24,36,7.0,7,53,Semi-Urban,Manager,98324,0 +95150,Male,31,Bachelors,4,95,98,68,59,9.0,4,67,Urban,HR Executive,95930,1 +95151,Female,32,High School,14,13,81,60,32,1.0,3,88,Semi-Urban,Manager,23413,1 +95152,Female,31,Diploma,14,68,43,62,23,1.0,5,45,Rural,ML Engineer,73259,0 +95153,Male,55,Diploma,12,18,96,8,28,0.0,2,70,Urban,HR Executive,68847,0 +95154,Male,26,High School,18,35,68,0,8,6.0,5,14,Urban,ML Engineer,78292,0 +95155,Other,26,Bachelors,4,84,78,11,16,2.0,1,7,Rural,Manager,58976,0 +95156,Female,37,Bachelors,8,10,96,70,41,8.0,3,47,Urban,ML Engineer,51943,0 +95157,Male,25,Masters,2,48,90,29,63,3.0,5,28,Semi-Urban,Data Analyst,143106,0 +95158,Male,44,Masters,4,27,56,36,1,1.0,6,81,Semi-Urban,Software Engineer,139933,0 +95159,Other,48,Bachelors,18,9,41,47,37,9.0,4,33,Rural,HR Executive,28221,0 +95160,Male,32,Bachelors,2,19,65,45,50,6.0,4,96,Semi-Urban,Data Analyst,147386,0 +95161,Male,22,High School,14,93,54,19,15,8.0,4,87,Semi-Urban,Manager,48685,1 +95162,Male,25,Diploma,8,61,38,95,19,3.0,7,10,Urban,ML Engineer,76032,0 +95163,Male,56,Masters,3,19,45,54,68,9.0,4,8,Urban,Manager,69938,0 +95164,Female,45,Masters,13,0,72,16,51,5.0,5,8,Urban,Manager,118597,0 +95165,Male,44,High School,6,96,65,8,33,5.0,4,99,Semi-Urban,Data Analyst,30659,1 +95166,Male,55,Bachelors,14,73,44,9,60,4.0,0,53,Urban,Manager,133994,0 +95167,Other,49,Bachelors,0,0,50,53,57,2.0,0,38,Semi-Urban,Manager,119719,0 +95168,Male,39,High School,2,7,76,31,96,8.0,5,43,Urban,Manager,90446,0 +95169,Male,41,Bachelors,8,82,2,8,52,2.0,0,24,Rural,HR Executive,80969,0 +95170,Female,34,Diploma,12,14,99,45,3,5.0,2,2,Semi-Urban,Manager,125073,0 +95171,Male,59,High School,17,12,61,37,87,4.0,5,60,Urban,Software Engineer,32246,0 +95172,Female,23,Masters,13,19,84,92,72,5.0,7,89,Urban,Data Analyst,143104,1 +95173,Female,41,Masters,6,47,20,0,65,3.0,3,69,Urban,ML Engineer,30346,0 +95174,Female,43,Bachelors,18,35,40,10,1,6.0,7,0,Urban,Software Engineer,76585,0 +95175,Male,32,Diploma,7,91,9,41,55,7.0,4,68,Rural,HR Executive,68319,0 +95176,Other,23,Bachelors,13,96,3,65,44,8.0,5,2,Rural,Manager,58303,0 +95177,Female,43,Bachelors,7,96,25,50,36,3.0,3,10,Rural,Data Analyst,145341,0 +95178,Male,46,Diploma,16,79,63,50,49,9.0,1,63,Semi-Urban,Data Analyst,83984,1 +95179,Male,52,Masters,13,56,91,48,13,1.0,7,40,Semi-Urban,HR Executive,93012,1 +95180,Male,39,Diploma,9,21,77,6,73,2.0,5,77,Rural,Manager,102875,0 +95181,Female,32,Bachelors,13,54,33,10,99,3.0,4,98,Semi-Urban,Data Analyst,21474,0 +95182,Male,56,Bachelors,2,2,90,65,89,1.0,3,44,Urban,Data Analyst,135260,0 +95183,Male,27,High School,15,59,98,41,37,3.0,5,20,Rural,Software Engineer,58672,0 +95184,Female,55,PhD,2,23,64,38,61,4.0,0,61,Semi-Urban,HR Executive,141808,0 +95185,Female,57,Bachelors,4,51,85,16,81,7.0,6,33,Urban,Manager,149102,0 +95186,Female,45,Bachelors,11,68,76,9,81,4.0,4,39,Semi-Urban,Data Analyst,116944,0 +95187,Male,21,Bachelors,7,92,31,11,91,6.0,6,98,Rural,Software Engineer,88564,0 +95188,Male,22,Masters,16,8,33,18,16,0.0,3,51,Semi-Urban,Data Analyst,63059,0 +95189,Male,31,Diploma,16,93,54,65,48,6.0,2,45,Urban,HR Executive,35042,1 +95190,Male,53,High School,4,51,39,67,33,3.0,3,38,Urban,Software Engineer,63117,0 +95191,Female,38,Bachelors,3,22,42,50,63,2.0,3,86,Urban,Data Analyst,45059,0 +95192,Male,54,Bachelors,19,10,52,55,27,1.0,7,73,Urban,Data Analyst,143134,0 +95193,Male,25,High School,15,54,36,84,51,4.0,0,48,Urban,HR Executive,60661,0 +95194,Male,31,Bachelors,0,60,86,74,54,7.0,2,74,Semi-Urban,Manager,62108,1 +95195,Female,56,Bachelors,2,3,8,34,19,0.0,1,22,Urban,Data Analyst,79820,0 +95196,Female,58,Bachelors,6,60,82,45,93,3.0,3,55,Rural,ML Engineer,28593,1 +95197,Male,43,Diploma,5,3,5,3,74,3.0,2,66,Semi-Urban,HR Executive,145246,0 +95198,Female,39,Bachelors,10,87,15,35,15,9.0,7,24,Semi-Urban,Manager,119708,0 +95199,Female,43,Bachelors,18,67,95,33,86,1.0,4,51,Urban,Software Engineer,60651,1 +95200,Male,28,Diploma,6,72,29,4,49,8.0,4,27,Urban,Software Engineer,32622,0 +95201,Female,56,Bachelors,0,17,66,68,87,7.0,3,79,Urban,HR Executive,86292,0 +95202,Female,30,Bachelors,9,56,52,58,84,9.0,6,68,Rural,Software Engineer,87575,0 +95203,Male,50,Masters,15,53,51,72,46,8.0,7,43,Urban,HR Executive,135601,0 +95204,Male,37,Bachelors,18,2,54,49,1,6.0,6,12,Rural,Data Analyst,86279,0 +95205,Male,50,High School,5,47,51,41,78,1.0,2,9,Semi-Urban,ML Engineer,31040,0 +95206,Male,43,Masters,16,55,75,38,60,2.0,3,95,Urban,ML Engineer,144545,1 +95207,Male,56,Diploma,17,25,25,27,52,4.0,2,40,Urban,ML Engineer,32718,0 +95208,Male,45,High School,7,23,31,14,24,7.0,7,16,Urban,ML Engineer,45851,0 +95209,Male,39,PhD,6,55,58,83,15,6.0,7,77,Semi-Urban,HR Executive,38488,1 +95210,Male,59,Masters,16,79,55,62,55,7.0,0,46,Urban,HR Executive,76779,1 +95211,Male,51,Masters,14,84,60,10,80,6.0,7,3,Semi-Urban,ML Engineer,124108,0 +95212,Male,31,High School,10,35,20,66,6,9.0,1,91,Semi-Urban,ML Engineer,110027,0 +95213,Male,23,Bachelors,0,17,22,5,77,3.0,2,2,Rural,Data Analyst,133237,0 +95214,Male,37,Diploma,12,6,0,62,24,3.0,4,64,Rural,ML Engineer,140280,0 +95215,Female,42,Bachelors,15,71,26,71,47,7.0,7,86,Semi-Urban,ML Engineer,63934,1 +95216,Male,49,Bachelors,14,4,44,13,12,1.0,2,4,Semi-Urban,HR Executive,43399,0 +95217,Male,38,Bachelors,15,2,94,30,69,8.0,6,84,Urban,Data Analyst,32887,0 +95218,Male,28,Masters,2,96,24,57,89,9.0,2,1,Urban,Software Engineer,74183,0 +95219,Female,23,PhD,12,41,57,39,67,0.0,3,70,Rural,Manager,120722,0 +95220,Male,25,Diploma,19,35,91,59,33,5.0,1,99,Urban,ML Engineer,69505,1 +95221,Female,35,Bachelors,3,77,30,21,87,5.0,0,59,Urban,Software Engineer,138088,0 +95222,Other,44,PhD,15,12,79,6,33,3.0,5,83,Urban,Manager,124668,0 +95223,Male,39,High School,1,57,26,19,89,4.0,0,43,Urban,ML Engineer,75883,0 +95224,Male,47,Masters,8,74,50,54,97,3.0,1,23,Rural,Software Engineer,70686,0 +95225,Female,57,Bachelors,13,92,85,73,0,0.0,3,3,Urban,HR Executive,136134,1 +95226,Female,44,Diploma,1,10,40,19,26,8.0,0,36,Semi-Urban,Software Engineer,28656,0 +95227,Female,56,Bachelors,14,66,5,82,6,1.0,0,52,Urban,Manager,74678,0 +95228,Male,50,High School,2,66,90,9,75,3.0,5,15,Urban,HR Executive,99610,0 +95229,Male,35,Bachelors,12,21,12,27,73,1.0,6,80,Urban,ML Engineer,86326,0 +95230,Female,27,Diploma,15,80,95,4,20,6.0,4,53,Urban,Data Analyst,128823,0 +95231,Male,45,Diploma,10,59,1,23,30,9.0,0,87,Urban,Data Analyst,128192,0 +95232,Male,59,Bachelors,12,77,7,50,62,3.0,1,23,Urban,Manager,20840,0 +95233,Female,28,Bachelors,12,94,65,11,74,7.0,7,23,Urban,HR Executive,32502,0 +95234,Other,27,Diploma,12,36,11,28,25,6.0,3,54,Urban,Software Engineer,25060,0 +95235,Female,27,Masters,16,70,47,4,50,8.0,7,28,Urban,Data Analyst,21883,0 +95236,Female,28,Masters,16,45,89,64,58,6.0,3,64,Urban,ML Engineer,149221,1 +95237,Male,49,Bachelors,8,66,43,40,31,8.0,3,46,Urban,Data Analyst,143041,0 +95238,Female,27,Bachelors,0,70,84,93,98,7.0,4,3,Semi-Urban,Manager,66280,1 +95239,Female,46,High School,5,9,25,42,43,9.0,3,7,Rural,HR Executive,91080,0 +95240,Male,44,High School,4,97,26,65,91,5.0,0,26,Rural,HR Executive,81634,0 +95241,Male,56,Masters,18,44,75,80,82,8.0,6,55,Semi-Urban,Data Analyst,40494,1 +95242,Male,53,Bachelors,12,2,75,52,29,5.0,7,49,Urban,Data Analyst,28806,0 +95243,Male,43,Bachelors,7,8,22,53,16,8.0,4,44,Urban,Data Analyst,132031,0 +95244,Male,32,Bachelors,5,39,81,46,74,7.0,5,28,Urban,HR Executive,106944,0 +95245,Other,35,High School,4,32,32,21,84,2.0,0,46,Urban,Data Analyst,27991,0 +95246,Female,25,High School,14,60,70,16,74,6.0,5,14,Urban,HR Executive,93795,0 +95247,Male,33,High School,19,34,83,91,46,1.0,7,76,Urban,Data Analyst,118084,1 +95248,Other,37,Bachelors,12,40,16,74,94,0.0,1,4,Urban,Manager,70557,0 +95249,Male,41,Bachelors,5,51,62,14,36,0.0,1,99,Urban,Software Engineer,25804,0 +95250,Male,41,Masters,16,86,8,83,10,6.0,0,87,Rural,Manager,149707,1 +95251,Female,24,PhD,11,64,27,63,3,6.0,1,16,Semi-Urban,Manager,120616,0 +95252,Female,37,Masters,7,25,4,19,6,8.0,6,46,Urban,ML Engineer,114875,0 +95253,Female,52,Bachelors,17,9,29,71,81,1.0,4,29,Urban,Manager,23562,0 +95254,Female,23,Bachelors,6,68,13,17,38,7.0,7,42,Urban,ML Engineer,83751,0 +95255,Male,52,Bachelors,9,38,38,12,55,7.0,0,9,Urban,Software Engineer,85772,0 +95256,Male,36,Diploma,15,71,15,55,82,3.0,2,89,Urban,ML Engineer,95308,0 +95257,Other,59,Bachelors,14,72,15,43,59,4.0,3,86,Urban,HR Executive,100621,0 +95258,Male,54,Masters,19,73,4,60,46,0.0,4,91,Urban,Software Engineer,83971,0 +95259,Male,29,Bachelors,13,2,61,61,77,8.0,0,4,Urban,HR Executive,143378,0 +95260,Female,54,High School,11,60,36,7,74,1.0,4,75,Urban,Manager,59780,0 +95261,Female,59,Bachelors,0,57,79,99,88,4.0,1,25,Semi-Urban,Manager,70391,1 +95262,Male,33,Bachelors,11,78,8,79,41,2.0,2,56,Urban,Manager,135002,0 +95263,Male,30,Diploma,13,51,35,36,32,0.0,1,93,Urban,HR Executive,100011,0 +95264,Male,34,Bachelors,6,90,17,37,58,4.0,0,97,Urban,Data Analyst,125036,1 +95265,Male,49,Bachelors,5,83,69,8,75,7.0,1,37,Semi-Urban,HR Executive,128217,0 +95266,Female,38,Diploma,7,43,82,17,91,9.0,3,54,Urban,Data Analyst,145203,0 +95267,Male,56,Masters,5,78,87,75,22,5.0,2,47,Rural,Manager,147060,1 +95268,Female,39,Diploma,0,38,73,80,42,1.0,4,16,Urban,ML Engineer,111111,0 +95269,Male,35,Diploma,3,55,49,34,63,7.0,6,51,Rural,Manager,47337,0 +95270,Male,39,Diploma,6,48,48,71,51,0.0,5,42,Urban,ML Engineer,85735,0 +95271,Male,41,Diploma,16,75,1,34,94,6.0,1,65,Semi-Urban,Data Analyst,43110,0 +95272,Male,53,Masters,1,20,65,42,35,6.0,5,25,Rural,Manager,113732,0 +95273,Female,40,Diploma,3,63,51,88,52,1.0,7,98,Rural,Manager,122128,1 +95274,Male,24,Diploma,4,20,15,48,32,7.0,0,95,Rural,Software Engineer,67438,0 +95275,Male,38,PhD,14,42,87,5,28,8.0,7,96,Rural,Manager,23595,0 +95276,Male,25,Bachelors,6,82,47,6,78,3.0,6,82,Semi-Urban,Data Analyst,87790,0 +95277,Female,49,Masters,11,52,13,58,20,6.0,1,7,Urban,ML Engineer,66671,0 +95278,Male,48,Bachelors,15,24,86,95,36,6.0,4,64,Urban,Data Analyst,32014,1 +95279,Male,38,High School,4,68,92,88,44,8.0,2,48,Urban,Data Analyst,137998,1 +95280,Male,40,Diploma,5,36,43,4,54,3.0,3,26,Urban,Data Analyst,74723,0 +95281,Male,57,High School,0,43,91,1,27,0.0,5,23,Semi-Urban,HR Executive,86050,0 +95282,Male,49,Bachelors,10,92,96,17,92,2.0,6,75,Urban,Software Engineer,44331,1 +95283,Male,23,Masters,3,41,41,21,79,2.0,5,90,Rural,Data Analyst,78759,0 +95284,Male,49,PhD,2,18,36,41,41,8.0,5,61,Semi-Urban,HR Executive,126656,0 +95285,Female,34,Diploma,18,22,70,30,90,4.0,3,64,Semi-Urban,HR Executive,56298,0 +95286,Other,34,Masters,13,37,99,68,29,8.0,6,82,Semi-Urban,ML Engineer,25497,1 +95287,Male,58,Bachelors,7,21,24,14,88,2.0,3,56,Rural,Manager,32231,0 +95288,Female,38,Bachelors,8,62,97,51,3,0.0,1,75,Urban,Manager,24553,1 +95289,Male,42,PhD,4,49,68,50,22,4.0,3,5,Urban,Software Engineer,53008,0 +95290,Male,21,Bachelors,17,71,35,16,26,6.0,6,1,Urban,Manager,39856,0 +95291,Male,42,Bachelors,5,5,90,62,4,2.0,4,85,Urban,Data Analyst,78480,1 +95292,Female,52,Masters,14,28,47,38,69,5.0,4,13,Urban,Software Engineer,133172,0 +95293,Male,28,Masters,15,38,41,55,84,8.0,7,60,Semi-Urban,HR Executive,42922,0 +95294,Female,34,Diploma,16,57,68,56,90,4.0,4,36,Urban,ML Engineer,49193,0 +95295,Female,21,High School,18,44,60,75,73,6.0,4,85,Rural,Data Analyst,106195,1 +95296,Male,28,Bachelors,18,45,98,92,84,5.0,3,46,Urban,Software Engineer,67138,1 +95297,Female,48,Bachelors,19,59,18,49,79,6.0,1,97,Semi-Urban,Manager,85059,0 +95298,Male,47,Masters,15,77,92,52,26,8.0,3,69,Urban,Manager,48904,1 +95299,Female,35,PhD,0,32,32,72,70,1.0,7,23,Urban,HR Executive,127974,0 +95300,Male,36,Diploma,14,63,75,37,92,6.0,2,75,Urban,Software Engineer,112602,1 +95301,Male,30,Masters,13,15,83,2,94,4.0,7,23,Semi-Urban,ML Engineer,92310,0 +95302,Female,36,Diploma,16,86,83,18,70,9.0,5,83,Urban,Data Analyst,70565,1 +95303,Female,40,Diploma,4,42,78,75,66,7.0,4,73,Urban,Manager,105904,1 +95304,Male,38,High School,8,18,44,9,99,2.0,5,90,Urban,ML Engineer,118118,0 +95305,Male,50,High School,15,30,24,67,67,0.0,3,33,Urban,Data Analyst,64072,0 +95306,Male,53,Bachelors,7,92,50,82,95,7.0,1,35,Semi-Urban,Data Analyst,22156,1 +95307,Female,37,Bachelors,12,98,16,90,10,3.0,5,27,Semi-Urban,Manager,96312,0 +95308,Male,50,Masters,17,22,39,95,19,7.0,0,69,Urban,ML Engineer,137534,0 +95309,Male,48,Bachelors,16,11,86,34,90,7.0,3,6,Semi-Urban,ML Engineer,133780,0 +95310,Female,34,Bachelors,7,95,20,31,36,9.0,7,23,Semi-Urban,Software Engineer,95071,0 +95311,Male,42,High School,14,69,27,33,42,1.0,5,46,Semi-Urban,HR Executive,141774,0 +95312,Female,55,Diploma,11,54,8,85,24,7.0,0,9,Urban,Software Engineer,87736,0 +95313,Male,40,Diploma,12,27,96,12,4,1.0,4,13,Semi-Urban,Data Analyst,24202,0 +95314,Male,40,Bachelors,5,91,18,25,48,1.0,0,94,Urban,Manager,129432,0 +95315,Female,28,Diploma,11,75,14,49,1,6.0,6,63,Urban,Manager,113500,0 +95316,Male,38,High School,19,80,29,47,61,5.0,0,14,Urban,Manager,75516,0 +95317,Female,46,PhD,18,13,92,83,82,6.0,5,10,Semi-Urban,Manager,48418,0 +95318,Male,57,High School,7,80,20,49,8,9.0,1,2,Rural,Software Engineer,149080,0 +95319,Male,30,Bachelors,13,52,69,38,65,1.0,7,81,Urban,Manager,116319,1 +95320,Female,41,Bachelors,19,77,92,83,53,3.0,0,80,Urban,ML Engineer,34288,1 +95321,Female,44,Bachelors,14,24,22,40,68,0.0,1,32,Rural,Manager,23218,0 +95322,Male,25,Bachelors,9,24,35,38,50,9.0,4,21,Urban,ML Engineer,97633,0 +95323,Male,57,High School,15,91,21,52,48,1.0,6,84,Urban,HR Executive,100643,1 +95324,Male,37,Bachelors,3,54,84,65,97,7.0,1,88,Urban,Manager,26270,1 +95325,Male,54,Bachelors,11,92,66,72,22,5.0,3,28,Urban,Manager,41208,1 +95326,Male,31,Bachelors,17,35,32,38,36,6.0,6,50,Semi-Urban,Software Engineer,143918,0 +95327,Male,32,PhD,11,8,10,70,95,7.0,5,91,Urban,ML Engineer,78367,0 +95328,Male,51,Bachelors,19,76,10,97,89,0.0,5,58,Rural,Software Engineer,105731,1 +95329,Male,46,Diploma,13,98,11,96,25,6.0,1,79,Semi-Urban,Manager,135156,1 +95330,Male,22,Diploma,4,57,6,20,34,3.0,0,91,Urban,Data Analyst,105408,0 +95331,Male,32,High School,19,95,40,43,17,8.0,1,43,Semi-Urban,HR Executive,46403,0 +95332,Female,39,Masters,6,79,42,26,50,1.0,0,81,Urban,ML Engineer,70382,0 +95333,Male,53,Bachelors,18,98,96,0,33,0.0,0,72,Rural,HR Executive,75742,1 +95334,Male,44,Bachelors,13,91,89,56,27,2.0,6,79,Urban,ML Engineer,44122,1 +95335,Female,29,Diploma,15,20,42,54,87,5.0,3,69,Urban,Data Analyst,130051,0 +95336,Other,26,Bachelors,7,95,19,35,13,4.0,3,75,Urban,Software Engineer,146897,0 +95337,Male,26,Bachelors,2,21,87,47,47,9.0,2,18,Urban,Software Engineer,86232,0 +95338,Female,52,Masters,10,68,89,54,93,7.0,7,25,Rural,HR Executive,119361,0 +95339,Male,26,Bachelors,17,37,68,48,41,3.0,2,79,Semi-Urban,Data Analyst,94229,0 +95340,Male,35,Bachelors,12,75,44,35,12,7.0,2,81,Semi-Urban,ML Engineer,47007,1 +95341,Male,58,High School,9,38,17,31,42,1.0,7,87,Rural,Data Analyst,25954,0 +95342,Female,39,Bachelors,10,21,63,95,95,3.0,5,74,Urban,Data Analyst,32920,1 +95343,Female,32,Bachelors,19,25,64,48,15,4.0,4,93,Urban,ML Engineer,48521,0 +95344,Male,58,Bachelors,5,66,62,56,97,6.0,6,95,Urban,Manager,49058,1 +95345,Male,39,Bachelors,3,48,24,0,20,0.0,3,70,Semi-Urban,Software Engineer,48104,0 +95346,Male,24,Diploma,5,68,55,25,95,2.0,2,8,Urban,HR Executive,131391,0 +95347,Other,49,Masters,5,64,23,67,17,7.0,0,71,Urban,Manager,60462,0 +95348,Female,59,High School,4,82,93,92,28,5.0,1,0,Urban,HR Executive,112963,1 +95349,Male,59,Diploma,10,20,30,72,1,0.0,2,47,Rural,Manager,35565,0 +95350,Male,24,High School,18,23,1,46,12,6.0,2,74,Semi-Urban,Software Engineer,80794,0 +95351,Male,56,High School,2,36,14,4,87,5.0,5,69,Urban,Software Engineer,132272,0 +95352,Male,25,Masters,0,52,2,47,51,5.0,0,10,Urban,ML Engineer,110578,0 +95353,Other,43,Masters,4,0,7,98,93,0.0,5,3,Rural,HR Executive,39444,0 +95354,Other,33,High School,12,10,13,37,84,9.0,0,18,Urban,Software Engineer,79057,0 +95355,Male,35,Bachelors,16,80,37,62,23,6.0,2,48,Rural,Manager,63877,0 +95356,Male,53,Bachelors,4,62,7,51,97,1.0,3,91,Urban,HR Executive,76222,0 +95357,Male,56,High School,5,71,24,8,4,9.0,1,16,Semi-Urban,Manager,143794,0 +95358,Male,47,Masters,9,81,56,6,44,3.0,4,48,Urban,Software Engineer,26767,0 +95359,Female,51,Diploma,9,5,33,30,88,0.0,6,33,Urban,Manager,47359,0 +95360,Female,55,Diploma,1,18,22,76,36,2.0,7,51,Urban,Software Engineer,130326,0 +95361,Female,23,Bachelors,12,40,23,63,49,2.0,4,99,Semi-Urban,Manager,92961,0 +95362,Other,39,High School,8,58,79,82,71,8.0,4,82,Rural,Manager,125587,1 +95363,Female,23,High School,4,94,49,58,52,2.0,6,80,Urban,Manager,59970,1 +95364,Male,47,Diploma,15,94,7,52,31,3.0,3,78,Urban,ML Engineer,119907,0 +95365,Female,29,Masters,10,62,29,37,20,7.0,4,29,Semi-Urban,HR Executive,38324,0 +95366,Male,37,Bachelors,4,44,20,27,99,7.0,4,18,Urban,Software Engineer,79588,0 +95367,Male,51,Diploma,16,86,34,83,62,2.0,1,70,Semi-Urban,Software Engineer,129704,1 +95368,Female,45,Bachelors,13,32,19,23,4,7.0,7,11,Urban,HR Executive,95764,0 +95369,Male,24,Bachelors,10,26,66,87,15,3.0,5,80,Urban,HR Executive,45326,1 +95370,Male,57,Bachelors,9,18,74,60,76,7.0,6,83,Urban,Manager,82444,1 +95371,Female,26,High School,4,18,8,10,35,3.0,7,1,Rural,HR Executive,64657,0 +95372,Male,35,Masters,19,80,58,99,40,3.0,1,44,Urban,Software Engineer,62710,1 +95373,Female,48,PhD,3,0,75,88,85,7.0,0,46,Urban,ML Engineer,88691,0 +95374,Female,42,Bachelors,5,26,96,47,67,5.0,6,3,Urban,Software Engineer,143704,0 +95375,Male,31,Diploma,18,80,79,60,18,2.0,4,14,Rural,Manager,47795,0 +95376,Male,31,High School,12,16,55,21,42,9.0,3,91,Semi-Urban,HR Executive,30811,0 +95377,Male,23,Diploma,2,26,58,30,73,9.0,7,97,Semi-Urban,HR Executive,38857,0 +95378,Female,32,Bachelors,1,18,70,3,1,5.0,3,68,Urban,ML Engineer,36418,0 +95379,Female,58,Bachelors,16,75,36,46,44,4.0,1,83,Semi-Urban,Data Analyst,64622,0 +95380,Male,56,Bachelors,9,64,29,29,7,9.0,6,32,Urban,Manager,73713,0 +95381,Female,23,Bachelors,14,89,65,48,98,0.0,0,55,Semi-Urban,Software Engineer,66338,1 +95382,Male,45,Masters,1,35,19,68,10,9.0,0,25,Semi-Urban,Software Engineer,52527,0 +95383,Female,46,Masters,0,72,47,23,15,2.0,7,93,Semi-Urban,ML Engineer,27272,0 +95384,Male,41,Bachelors,7,59,6,84,34,2.0,3,85,Urban,ML Engineer,149613,0 +95385,Male,27,Bachelors,3,82,83,5,13,3.0,2,3,Semi-Urban,Data Analyst,71378,0 +95386,Female,58,Bachelors,8,84,58,47,7,1.0,2,49,Urban,Software Engineer,45677,0 +95387,Male,50,High School,3,97,44,8,96,1.0,0,5,Urban,HR Executive,75164,0 +95388,Male,37,High School,1,44,83,96,94,0.0,3,42,Urban,Manager,27301,1 +95389,Male,26,Bachelors,10,92,31,44,19,4.0,3,81,Urban,HR Executive,111239,1 +95390,Female,35,Bachelors,18,64,43,91,49,8.0,1,98,Rural,Software Engineer,78861,1 +95391,Male,24,Bachelors,12,36,71,75,58,1.0,4,0,Urban,HR Executive,103719,0 +95392,Male,50,Masters,7,82,74,70,6,8.0,4,19,Rural,HR Executive,111764,1 +95393,Male,27,Bachelors,2,18,68,17,23,8.0,1,6,Urban,Data Analyst,83031,0 +95394,Male,31,Masters,10,83,10,34,96,2.0,3,51,Rural,Manager,61453,0 +95395,Male,40,Masters,7,8,17,37,92,0.0,0,17,Urban,Manager,73909,0 +95396,Male,44,Diploma,8,8,16,95,45,4.0,7,51,Rural,HR Executive,63625,0 +95397,Other,21,Diploma,11,14,67,58,2,8.0,0,17,Semi-Urban,HR Executive,41754,0 +95398,Female,47,Masters,6,15,98,13,44,7.0,2,44,Semi-Urban,HR Executive,75811,0 +95399,Male,37,Diploma,15,68,37,10,47,7.0,2,74,Urban,ML Engineer,35989,0 +95400,Male,56,Bachelors,7,15,21,4,14,5.0,2,57,Rural,Manager,88737,0 +95401,Female,53,Diploma,17,71,32,69,60,3.0,1,47,Rural,Software Engineer,27956,0 +95402,Male,28,PhD,11,84,52,21,88,9.0,3,48,Rural,HR Executive,123571,0 +95403,Male,55,Diploma,6,51,53,0,71,3.0,1,69,Semi-Urban,Data Analyst,21753,0 +95404,Female,22,Diploma,13,5,63,32,28,8.0,6,68,Urban,Manager,44175,0 +95405,Male,22,Masters,13,68,45,86,13,2.0,0,18,Urban,Software Engineer,124389,0 +95406,Male,46,Diploma,13,51,69,94,27,9.0,3,48,Urban,ML Engineer,108107,1 +95407,Male,39,High School,13,69,22,51,98,7.0,3,34,Semi-Urban,Software Engineer,73414,0 +95408,Male,23,Bachelors,4,73,61,13,18,5.0,1,44,Urban,ML Engineer,59117,0 +95409,Male,47,High School,6,66,69,70,59,1.0,7,13,Urban,ML Engineer,20977,0 +95410,Male,56,Bachelors,11,8,9,21,21,6.0,6,51,Urban,Data Analyst,60478,0 +95411,Female,42,Masters,4,80,89,77,27,1.0,1,32,Urban,Data Analyst,36741,1 +95412,Female,21,Masters,17,53,45,68,60,7.0,5,8,Urban,Manager,125605,0 +95413,Male,34,Masters,2,65,92,28,90,1.0,4,30,Urban,Data Analyst,90222,0 +95414,Male,42,Bachelors,8,68,29,92,64,5.0,3,85,Urban,ML Engineer,94874,1 +95415,Other,36,PhD,7,58,66,78,70,9.0,3,99,Urban,ML Engineer,132757,1 +95416,Male,45,Diploma,13,50,57,46,88,7.0,7,69,Urban,ML Engineer,101986,0 +95417,Other,59,Bachelors,6,98,37,10,45,9.0,0,76,Urban,HR Executive,139829,0 +95418,Male,36,Masters,16,86,81,91,49,6.0,6,69,Semi-Urban,Manager,142334,1 +95419,Male,27,Masters,5,20,32,62,66,8.0,4,90,Urban,HR Executive,111431,0 +95420,Female,36,Diploma,13,0,30,5,98,9.0,7,55,Urban,Manager,138946,0 +95421,Male,48,PhD,6,51,24,8,72,8.0,0,75,Semi-Urban,Manager,121191,0 +95422,Male,41,Bachelors,19,24,49,62,37,4.0,6,68,Urban,ML Engineer,24978,0 +95423,Male,22,Bachelors,15,4,88,40,63,2.0,2,67,Urban,HR Executive,116724,0 +95424,Male,47,Bachelors,4,15,56,96,49,0.0,7,30,Urban,HR Executive,22902,0 +95425,Male,24,High School,19,71,40,53,90,3.0,5,20,Urban,Manager,56294,0 +95426,Male,35,Masters,1,34,58,20,53,6.0,2,71,Urban,Data Analyst,133405,0 +95427,Male,35,Bachelors,2,73,7,70,66,1.0,7,77,Rural,Manager,128932,0 +95428,Male,51,Bachelors,10,36,57,11,17,4.0,7,82,Urban,Data Analyst,41444,0 +95429,Male,41,High School,0,1,26,32,74,8.0,5,75,Urban,Software Engineer,106373,0 +95430,Male,34,Bachelors,3,29,60,97,28,4.0,0,0,Rural,HR Executive,144678,0 +95431,Male,45,Bachelors,17,46,41,24,37,5.0,1,10,Rural,Manager,97498,0 +95432,Male,31,Masters,4,6,34,99,24,7.0,1,87,Semi-Urban,HR Executive,64182,0 +95433,Male,27,Diploma,19,87,54,96,92,3.0,4,56,Urban,HR Executive,149790,1 +95434,Male,31,Diploma,1,56,21,51,48,1.0,3,73,Semi-Urban,ML Engineer,60570,0 +95435,Male,24,High School,10,44,6,84,63,7.0,2,3,Rural,Data Analyst,114161,0 +95436,Female,25,Masters,11,17,81,48,79,4.0,6,11,Semi-Urban,Software Engineer,69087,0 +95437,Female,44,Bachelors,5,3,83,1,37,0.0,0,36,Urban,Manager,25359,0 +95438,Male,45,Masters,17,86,54,65,17,4.0,7,86,Urban,ML Engineer,97619,1 +95439,Female,22,PhD,6,10,70,24,34,9.0,5,31,Urban,ML Engineer,108043,0 +95440,Male,57,Diploma,3,73,96,47,18,1.0,2,53,Rural,Software Engineer,110562,1 +95441,Male,42,Diploma,3,28,67,92,45,5.0,7,18,Semi-Urban,Data Analyst,67389,0 +95442,Male,36,Masters,7,14,0,81,98,9.0,3,14,Urban,HR Executive,122953,0 +95443,Other,49,High School,11,81,83,28,53,0.0,7,92,Urban,Software Engineer,83802,1 +95444,Male,21,Bachelors,15,23,1,97,22,2.0,7,48,Urban,Software Engineer,44228,0 +95445,Male,52,Bachelors,11,36,94,80,85,4.0,3,66,Urban,Manager,81087,1 +95446,Male,43,Masters,0,34,81,35,26,0.0,5,83,Urban,Manager,54608,0 +95447,Male,45,Bachelors,18,23,17,20,57,6.0,1,88,Urban,ML Engineer,121171,0 +95448,Female,50,Bachelors,16,62,73,45,32,9.0,7,56,Rural,Data Analyst,123580,0 +95449,Male,26,Bachelors,7,13,99,47,9,9.0,1,62,Urban,HR Executive,26841,0 +95450,Male,33,Diploma,7,91,56,84,22,6.0,2,31,Urban,Manager,102695,1 +95451,Female,41,High School,14,33,33,77,89,6.0,7,33,Urban,Data Analyst,136961,0 +95452,Male,33,Diploma,1,18,16,67,26,7.0,4,51,Urban,HR Executive,60298,0 +95453,Female,39,Masters,15,7,88,61,87,8.0,4,78,Urban,Manager,86275,0 +95454,Other,37,Bachelors,14,27,83,62,24,6.0,1,45,Urban,Manager,73181,0 +95455,Female,23,High School,5,77,20,32,46,3.0,1,26,Urban,ML Engineer,148510,0 +95456,Male,34,Bachelors,10,84,61,82,4,1.0,4,91,Urban,Data Analyst,147336,1 +95457,Male,51,Bachelors,9,45,3,7,46,2.0,1,41,Urban,HR Executive,106550,0 +95458,Male,41,Diploma,8,53,23,93,50,3.0,5,46,Rural,ML Engineer,102732,0 +95459,Female,35,Bachelors,18,65,92,93,78,2.0,3,47,Urban,HR Executive,104209,1 +95460,Male,44,High School,0,77,70,92,4,9.0,3,75,Urban,HR Executive,41267,1 +95461,Male,51,Bachelors,16,31,82,94,56,7.0,4,43,Urban,Data Analyst,90860,1 +95462,Male,43,High School,6,17,53,8,21,1.0,2,71,Semi-Urban,HR Executive,60488,0 +95463,Male,56,Masters,5,91,29,5,99,4.0,0,54,Rural,Data Analyst,56564,0 +95464,Male,40,Masters,18,63,50,65,10,8.0,4,21,Urban,ML Engineer,44539,0 +95465,Male,56,High School,12,4,31,40,56,5.0,3,25,Urban,ML Engineer,50200,0 +95466,Male,35,Bachelors,4,21,43,44,49,9.0,4,29,Urban,HR Executive,43074,0 +95467,Male,53,High School,19,34,9,14,35,2.0,3,76,Rural,Software Engineer,108237,0 +95468,Other,59,High School,0,74,73,14,2,5.0,2,12,Semi-Urban,Software Engineer,121859,0 +95469,Female,47,Masters,0,67,77,93,77,4.0,6,10,Rural,ML Engineer,91568,1 +95470,Male,57,Bachelors,3,44,69,70,30,5.0,4,97,Rural,Manager,50052,1 +95471,Male,49,Diploma,2,83,16,89,42,0.0,6,58,Rural,Manager,94440,1 +95472,Female,22,Masters,13,47,49,96,16,4.0,0,71,Urban,Manager,72242,1 +95473,Female,24,Bachelors,1,39,76,76,20,1.0,4,75,Urban,Software Engineer,145960,1 +95474,Male,33,Bachelors,4,12,3,61,16,4.0,5,47,Semi-Urban,Data Analyst,106111,0 +95475,Female,25,High School,10,13,42,36,66,6.0,4,77,Urban,Manager,45471,0 +95476,Male,45,Diploma,6,4,56,67,79,3.0,5,8,Urban,Manager,20281,0 +95477,Male,23,Bachelors,4,47,75,75,50,5.0,1,29,Urban,Data Analyst,39610,0 +95478,Female,52,Diploma,12,22,95,65,11,5.0,1,82,Urban,Software Engineer,105918,1 +95479,Male,22,High School,18,4,19,47,39,6.0,7,31,Rural,Software Engineer,43715,0 +95480,Female,33,Bachelors,6,30,69,77,58,6.0,2,80,Semi-Urban,Software Engineer,63121,1 +95481,Male,41,Diploma,4,93,75,58,97,1.0,7,40,Semi-Urban,HR Executive,30614,1 +95482,Female,42,Bachelors,15,57,66,8,90,7.0,4,3,Semi-Urban,HR Executive,72473,0 +95483,Male,53,Masters,15,97,16,57,0,5.0,2,16,Urban,HR Executive,56182,0 +95484,Male,58,Diploma,11,99,42,1,20,2.0,1,23,Rural,ML Engineer,61696,0 +95485,Male,28,Diploma,4,19,6,29,80,5.0,7,70,Urban,Manager,97488,0 +95486,Female,59,Bachelors,6,46,80,52,70,7.0,5,17,Urban,Manager,34287,0 +95487,Male,38,Bachelors,7,23,88,67,59,9.0,4,70,Rural,Software Engineer,83321,1 +95488,Female,24,Bachelors,3,18,69,15,56,9.0,3,34,Semi-Urban,Data Analyst,32843,0 +95489,Female,55,Bachelors,9,53,97,25,39,7.0,5,61,Urban,HR Executive,41125,0 +95490,Male,44,Bachelors,7,19,4,87,32,0.0,4,41,Rural,Software Engineer,101331,0 +95491,Male,33,High School,17,24,90,61,54,8.0,3,25,Urban,Data Analyst,51654,0 +95492,Female,54,High School,15,64,12,37,16,2.0,2,81,Semi-Urban,Manager,121333,0 +95493,Female,24,Diploma,14,89,65,31,94,8.0,1,55,Urban,ML Engineer,97322,0 +95494,Female,57,High School,13,81,12,28,29,4.0,3,92,Urban,Manager,63308,0 +95495,Male,40,Masters,8,32,89,9,63,5.0,6,72,Semi-Urban,Software Engineer,84240,0 +95496,Female,47,Masters,0,97,85,59,27,6.0,1,22,Rural,HR Executive,72731,1 +95497,Female,39,Masters,12,7,38,57,19,1.0,0,25,Urban,ML Engineer,104510,0 +95498,Male,39,Bachelors,6,63,59,68,35,2.0,2,18,Rural,Data Analyst,143473,0 +95499,Other,40,Diploma,19,73,75,59,73,1.0,7,58,Semi-Urban,HR Executive,66212,1 +95500,Male,43,High School,0,40,61,41,56,7.0,6,45,Semi-Urban,Data Analyst,23055,0 +95501,Female,36,Masters,13,74,34,23,60,9.0,4,92,Urban,HR Executive,76791,0 +95502,Female,23,Diploma,0,82,98,46,9,3.0,1,48,Semi-Urban,ML Engineer,143400,1 +95503,Male,51,Masters,4,94,22,59,11,6.0,5,33,Urban,ML Engineer,22294,0 +95504,Male,29,Diploma,2,3,88,90,67,4.0,4,42,Rural,ML Engineer,65008,0 +95505,Female,41,Diploma,10,93,80,39,73,4.0,0,19,Urban,Data Analyst,62205,0 +95506,Male,46,Bachelors,15,97,76,51,8,3.0,4,58,Rural,Data Analyst,74168,1 +95507,Other,51,Bachelors,13,29,31,16,93,2.0,2,24,Semi-Urban,HR Executive,116271,0 +95508,Male,26,Bachelors,2,40,1,70,98,3.0,0,67,Urban,ML Engineer,128752,0 +95509,Female,52,Masters,19,35,15,47,80,1.0,6,42,Urban,ML Engineer,35650,0 +95510,Male,46,High School,11,81,89,36,32,6.0,7,25,Semi-Urban,ML Engineer,25795,0 +95511,Female,46,Bachelors,3,10,52,82,96,6.0,4,17,Urban,ML Engineer,111521,0 +95512,Male,44,High School,0,49,56,99,61,2.0,5,99,Urban,Data Analyst,59249,1 +95513,Male,46,Bachelors,12,91,27,91,37,5.0,4,8,Semi-Urban,Data Analyst,98184,0 +95514,Male,59,Diploma,18,41,41,17,7,1.0,4,9,Rural,Software Engineer,57462,0 +95515,Other,51,Bachelors,10,20,43,24,3,4.0,6,15,Urban,Manager,119264,0 +95516,Other,37,Masters,8,28,4,62,9,5.0,5,0,Urban,HR Executive,101539,0 +95517,Male,23,Diploma,15,62,18,20,65,0.0,2,66,Urban,Software Engineer,34384,0 +95518,Male,56,Diploma,5,64,15,68,11,4.0,2,97,Rural,Software Engineer,69318,1 +95519,Female,53,High School,17,72,16,34,31,3.0,7,13,Urban,ML Engineer,105540,0 +95520,Male,52,Masters,3,3,30,99,81,7.0,6,60,Semi-Urban,ML Engineer,103049,0 +95521,Other,45,Diploma,15,90,17,80,82,4.0,7,34,Urban,Data Analyst,128235,0 +95522,Male,45,Masters,17,2,20,4,49,4.0,7,3,Urban,Manager,148894,0 +95523,Male,52,Bachelors,6,30,72,19,57,7.0,5,86,Semi-Urban,Manager,66008,0 +95524,Male,42,High School,15,60,77,45,94,6.0,4,15,Rural,Manager,73150,0 +95525,Female,38,Bachelors,15,57,31,95,46,4.0,2,73,Semi-Urban,Manager,79876,1 +95526,Other,48,High School,17,92,73,99,30,5.0,2,95,Urban,ML Engineer,149477,1 +95527,Male,46,Bachelors,10,52,15,88,21,2.0,4,36,Semi-Urban,Data Analyst,31488,0 +95528,Female,32,Bachelors,17,31,38,87,92,0.0,7,33,Rural,Software Engineer,47786,0 +95529,Female,40,Bachelors,10,40,68,65,26,8.0,1,45,Urban,ML Engineer,40925,0 +95530,Female,54,High School,12,44,34,91,6,9.0,0,85,Rural,Data Analyst,125665,1 +95531,Male,45,High School,4,26,5,32,50,5.0,0,91,Urban,Data Analyst,131333,0 +95532,Female,56,High School,15,1,86,13,87,4.0,1,44,Urban,ML Engineer,135800,0 +95533,Male,57,Masters,7,2,70,99,12,1.0,1,79,Semi-Urban,ML Engineer,38625,1 +95534,Female,21,Masters,18,17,22,70,6,0.0,4,86,Urban,Data Analyst,48796,0 +95535,Male,48,Masters,2,10,9,96,20,3.0,0,0,Urban,Manager,58843,0 +95536,Female,25,Masters,12,24,46,49,5,7.0,2,88,Rural,Data Analyst,107422,0 +95537,Male,56,Bachelors,12,28,39,28,84,0.0,0,33,Urban,Manager,99865,0 +95538,Female,57,Diploma,19,5,77,3,65,4.0,5,91,Urban,ML Engineer,78013,0 +95539,Female,34,Bachelors,18,8,33,25,72,4.0,5,81,Rural,Software Engineer,128694,0 +95540,Male,23,Masters,12,48,83,7,58,2.0,0,21,Semi-Urban,ML Engineer,149865,0 +95541,Male,33,High School,8,54,77,70,81,1.0,3,96,Urban,HR Executive,148212,1 +95542,Male,23,Bachelors,1,9,64,38,20,5.0,3,61,Urban,HR Executive,121598,0 +95543,Other,48,Diploma,8,90,47,11,64,2.0,3,85,Urban,ML Engineer,133589,0 +95544,Other,23,Bachelors,17,40,20,91,10,4.0,4,69,Semi-Urban,Software Engineer,128658,0 +95545,Male,43,Diploma,2,82,7,25,21,2.0,7,27,Urban,Software Engineer,138792,0 +95546,Female,24,Bachelors,13,49,88,71,71,3.0,3,50,Urban,Manager,31878,1 +95547,Female,32,High School,5,29,41,30,50,9.0,0,40,Urban,Software Engineer,73893,0 +95548,Female,31,Bachelors,2,44,43,36,84,5.0,0,66,Semi-Urban,Software Engineer,97039,0 +95549,Male,28,Diploma,9,44,72,72,90,0.0,2,79,Urban,Data Analyst,71467,1 +95550,Female,51,High School,17,27,72,98,71,3.0,5,8,Rural,Data Analyst,75059,0 +95551,Male,52,Masters,11,1,68,49,24,5.0,0,10,Rural,Software Engineer,124799,0 +95552,Female,35,Diploma,7,21,91,99,13,2.0,7,75,Rural,HR Executive,106211,1 +95553,Female,49,Masters,0,46,80,73,55,2.0,1,45,Semi-Urban,Data Analyst,28176,1 +95554,Male,38,Bachelors,13,5,65,1,2,3.0,6,65,Urban,Manager,22433,0 +95555,Female,50,PhD,5,54,42,97,73,3.0,1,39,Urban,Data Analyst,55524,0 +95556,Male,36,High School,10,73,87,26,40,5.0,1,22,Urban,ML Engineer,30630,0 +95557,Male,31,Bachelors,10,86,97,91,81,1.0,1,5,Urban,HR Executive,136714,1 +95558,Male,37,Bachelors,10,44,17,32,48,0.0,3,90,Semi-Urban,HR Executive,135244,0 +95559,Male,43,Masters,8,82,34,90,62,5.0,1,72,Urban,Manager,137850,1 +95560,Female,22,High School,5,34,89,84,83,4.0,7,27,Urban,HR Executive,39513,0 +95561,Female,56,Diploma,15,18,0,20,90,6.0,7,22,Urban,Software Engineer,146429,0 +95562,Male,21,Bachelors,9,8,79,32,92,3.0,6,19,Urban,Data Analyst,94068,0 +95563,Male,39,Masters,13,79,59,50,34,8.0,1,93,Semi-Urban,HR Executive,21837,1 +95564,Female,27,Bachelors,2,16,73,39,21,0.0,1,36,Urban,Software Engineer,25932,0 +95565,Female,29,Masters,6,52,46,85,22,2.0,7,71,Urban,Manager,45187,1 +95566,Male,59,Bachelors,8,20,23,31,71,5.0,2,33,Rural,Software Engineer,76209,0 +95567,Male,39,Bachelors,0,52,33,76,10,7.0,6,82,Semi-Urban,Data Analyst,40555,1 +95568,Male,47,Bachelors,5,11,40,13,46,2.0,0,5,Urban,Software Engineer,140923,0 +95569,Female,34,Bachelors,19,26,1,46,32,8.0,7,53,Rural,Data Analyst,141645,0 +95570,Male,39,High School,17,34,58,32,23,8.0,0,45,Semi-Urban,Software Engineer,144877,0 +95571,Male,21,High School,12,17,20,30,18,5.0,2,83,Urban,Data Analyst,25342,0 +95572,Female,28,Masters,2,79,15,16,69,6.0,0,44,Urban,Manager,147176,0 +95573,Female,37,Bachelors,5,42,40,35,95,3.0,4,95,Rural,Software Engineer,134622,0 +95574,Male,39,Bachelors,0,31,76,77,86,1.0,3,21,Urban,Software Engineer,107973,0 +95575,Male,27,Diploma,0,33,29,36,5,5.0,2,39,Urban,Data Analyst,40469,0 +95576,Male,36,Diploma,5,62,10,43,60,7.0,6,28,Rural,HR Executive,59294,0 +95577,Female,36,Masters,8,45,26,64,37,3.0,2,14,Urban,HR Executive,103579,0 +95578,Male,30,High School,9,12,63,43,13,9.0,7,45,Rural,ML Engineer,26304,0 +95579,Male,29,Bachelors,2,39,88,63,41,4.0,1,55,Urban,Manager,97865,1 +95580,Male,46,Bachelors,4,67,88,29,35,9.0,1,46,Semi-Urban,ML Engineer,60304,0 +95581,Other,54,Masters,0,97,21,41,10,0.0,0,90,Urban,Software Engineer,137397,1 +95582,Male,27,Bachelors,6,23,74,2,43,3.0,0,25,Urban,HR Executive,145594,0 +95583,Male,46,Diploma,18,3,56,42,78,8.0,7,33,Urban,HR Executive,114238,0 +95584,Female,47,High School,15,65,0,98,94,4.0,3,93,Urban,Manager,32482,1 +95585,Male,41,Bachelors,19,1,67,96,29,8.0,7,14,Urban,Manager,114208,0 +95586,Female,54,Diploma,4,46,10,69,32,1.0,0,94,Semi-Urban,Software Engineer,81135,0 +95587,Female,33,High School,16,26,78,39,48,0.0,0,0,Urban,Data Analyst,85989,0 +95588,Male,51,Bachelors,3,13,99,48,6,0.0,7,39,Urban,Manager,32215,0 +95589,Male,37,Diploma,0,51,82,95,92,4.0,1,31,Urban,Software Engineer,97310,1 +95590,Male,55,PhD,13,44,74,38,56,7.0,4,37,Urban,Software Engineer,86581,0 +95591,Female,40,Bachelors,4,14,40,57,70,1.0,6,68,Semi-Urban,HR Executive,29682,0 +95592,Female,39,PhD,15,91,98,21,81,3.0,3,55,Rural,Manager,101244,1 +95593,Male,32,Bachelors,1,99,70,47,16,5.0,3,27,Urban,ML Engineer,74074,1 +95594,Female,49,Masters,7,54,38,28,7,0.0,7,78,Rural,Data Analyst,114149,0 +95595,Female,29,High School,8,12,16,30,12,7.0,6,28,Rural,Data Analyst,55657,0 +95596,Male,27,Bachelors,0,94,78,39,11,8.0,1,62,Urban,Manager,43984,1 +95597,Male,35,Masters,15,94,20,18,92,6.0,5,71,Urban,ML Engineer,47651,0 +95598,Male,24,Masters,15,88,40,52,77,2.0,2,3,Urban,Software Engineer,37625,0 +95599,Female,51,High School,10,19,74,91,42,0.0,6,45,Semi-Urban,HR Executive,80138,0 +95600,Male,30,Bachelors,13,54,95,42,66,4.0,2,24,Semi-Urban,HR Executive,65315,0 +95601,Female,52,Masters,0,8,29,8,60,9.0,3,31,Semi-Urban,Data Analyst,20875,0 +95602,Female,36,High School,9,70,57,27,31,6.0,3,11,Urban,Manager,97058,0 +95603,Male,56,High School,11,58,30,85,99,6.0,0,82,Urban,HR Executive,58922,1 +95604,Male,46,PhD,16,56,66,81,69,9.0,6,58,Urban,Software Engineer,49563,1 +95605,Female,52,Diploma,18,43,49,93,5,3.0,1,58,Urban,HR Executive,94106,1 +95606,Female,48,Bachelors,15,32,26,96,17,8.0,6,31,Urban,Data Analyst,84005,0 +95607,Male,29,Diploma,10,44,39,44,19,9.0,0,0,Rural,HR Executive,105753,0 +95608,Male,54,Bachelors,19,92,69,67,87,0.0,1,55,Rural,HR Executive,67579,1 +95609,Male,38,PhD,11,52,21,74,40,8.0,1,14,Urban,Data Analyst,101740,0 +95610,Female,45,Masters,6,99,50,50,63,9.0,1,61,Urban,Software Engineer,46180,1 +95611,Female,51,Bachelors,19,13,70,3,12,1.0,2,2,Semi-Urban,Data Analyst,22314,0 +95612,Other,47,Bachelors,9,76,6,17,91,5.0,1,5,Urban,ML Engineer,110037,0 +95613,Male,33,Bachelors,16,4,16,55,85,8.0,7,84,Semi-Urban,Data Analyst,36648,0 +95614,Male,30,Bachelors,19,82,76,38,38,2.0,1,28,Semi-Urban,HR Executive,38924,0 +95615,Male,48,PhD,14,24,71,27,66,1.0,1,44,Urban,Manager,97523,0 +95616,Male,45,Diploma,15,97,47,66,28,3.0,1,87,Rural,Data Analyst,65273,1 +95617,Female,23,High School,2,60,35,22,99,8.0,2,83,Semi-Urban,ML Engineer,96675,0 +95618,Male,54,Bachelors,10,69,6,65,20,6.0,6,51,Semi-Urban,HR Executive,110569,0 +95619,Male,41,Bachelors,0,26,53,25,71,6.0,5,61,Urban,Data Analyst,33294,0 +95620,Female,58,High School,14,94,67,9,80,6.0,2,88,Urban,Data Analyst,101788,1 +95621,Female,58,Masters,1,9,16,68,33,8.0,4,32,Rural,Software Engineer,32202,0 +95622,Female,48,Bachelors,8,15,17,30,50,7.0,4,47,Urban,HR Executive,25338,0 +95623,Female,33,Bachelors,3,1,78,7,15,7.0,2,22,Urban,ML Engineer,65830,0 +95624,Male,37,PhD,19,67,77,81,35,0.0,0,84,Semi-Urban,Manager,137252,1 +95625,Male,47,Diploma,9,77,14,70,33,6.0,2,53,Urban,HR Executive,26802,0 +95626,Female,39,Masters,0,89,14,27,77,4.0,4,45,Urban,ML Engineer,64045,0 +95627,Female,52,PhD,18,75,76,38,38,5.0,3,77,Urban,Software Engineer,88516,1 +95628,Male,25,Bachelors,4,11,39,30,7,9.0,4,6,Rural,Manager,140223,0 +95629,Male,28,High School,7,87,2,19,23,5.0,5,11,Urban,Data Analyst,113997,0 +95630,Male,43,Masters,2,82,71,83,0,6.0,7,26,Urban,Data Analyst,117435,1 +95631,Male,41,Bachelors,19,55,64,10,88,8.0,1,5,Semi-Urban,Software Engineer,144446,0 +95632,Male,52,Bachelors,14,70,63,96,29,5.0,2,47,Urban,Manager,141037,1 +95633,Male,52,Bachelors,0,99,23,90,4,0.0,1,89,Urban,Data Analyst,93582,1 +95634,Male,40,Bachelors,12,82,22,54,42,8.0,2,47,Urban,ML Engineer,110589,0 +95635,Male,32,Bachelors,12,31,76,87,87,3.0,4,17,Urban,Manager,25031,0 +95636,Male,44,Masters,4,35,14,65,42,0.0,3,76,Urban,Manager,25813,0 +95637,Male,37,Masters,15,55,60,13,57,2.0,3,65,Semi-Urban,Manager,61490,0 +95638,Male,55,Masters,10,19,68,76,47,4.0,7,34,Urban,Software Engineer,49347,0 +95639,Other,29,Bachelors,10,63,68,84,71,0.0,1,70,Rural,HR Executive,62695,1 +95640,Female,43,High School,14,17,72,27,57,3.0,1,23,Urban,ML Engineer,149448,0 +95641,Male,32,Bachelors,3,43,64,12,38,4.0,0,95,Urban,Software Engineer,138254,0 +95642,Male,24,Masters,11,60,10,81,75,0.0,0,79,Semi-Urban,ML Engineer,49453,0 +95643,Male,34,Masters,8,51,26,80,71,3.0,0,96,Urban,ML Engineer,65687,1 +95644,Female,53,Bachelors,4,94,28,76,55,7.0,3,19,Urban,ML Engineer,29365,0 +95645,Male,24,Bachelors,19,6,96,71,89,5.0,5,45,Rural,HR Executive,132173,0 +95646,Male,52,Bachelors,8,27,54,53,63,9.0,6,10,Urban,Manager,41536,0 +95647,Other,26,Diploma,7,4,43,8,75,0.0,3,76,Urban,HR Executive,109922,0 +95648,Male,37,Masters,11,50,88,47,45,9.0,6,81,Rural,Software Engineer,99388,1 +95649,Male,28,Masters,18,19,0,79,52,8.0,3,50,Semi-Urban,Software Engineer,146729,0 +95650,Male,38,Bachelors,17,72,71,62,88,7.0,5,96,Rural,Software Engineer,31239,1 +95651,Male,54,Diploma,17,41,70,31,19,4.0,1,58,Semi-Urban,Software Engineer,149663,0 +95652,Male,56,PhD,6,53,15,63,33,6.0,3,47,Urban,HR Executive,140340,0 +95653,Other,28,Masters,6,26,13,22,76,7.0,0,97,Urban,ML Engineer,84328,0 +95654,Male,39,Diploma,5,58,99,67,51,4.0,5,4,Urban,HR Executive,98319,0 +95655,Male,49,Masters,6,22,52,52,56,1.0,1,6,Urban,Software Engineer,27050,0 +95656,Female,49,Diploma,16,59,95,64,35,7.0,2,6,Urban,Manager,132077,0 +95657,Male,50,Diploma,14,81,74,1,6,6.0,7,23,Rural,HR Executive,42554,0 +95658,Female,49,Diploma,4,78,96,94,19,4.0,2,50,Urban,ML Engineer,130299,1 +95659,Male,38,Bachelors,10,78,49,18,64,1.0,2,8,Semi-Urban,HR Executive,95519,0 +95660,Female,27,Diploma,5,79,5,83,42,6.0,3,6,Semi-Urban,Software Engineer,134543,0 +95661,Male,53,Masters,10,97,70,92,30,1.0,3,99,Semi-Urban,HR Executive,129990,1 +95662,Male,45,Diploma,2,22,52,35,71,0.0,6,36,Urban,Data Analyst,118138,0 +95663,Male,57,PhD,9,41,45,64,38,3.0,0,12,Semi-Urban,Data Analyst,125270,0 +95664,Male,28,Diploma,12,26,81,6,78,8.0,1,80,Rural,Data Analyst,137608,0 +95665,Male,36,Bachelors,17,23,87,16,77,8.0,3,23,Urban,HR Executive,149577,0 +95666,Female,51,Masters,10,88,60,81,49,5.0,5,30,Semi-Urban,Software Engineer,147920,1 +95667,Female,21,High School,18,96,14,77,35,4.0,6,34,Urban,HR Executive,112913,0 +95668,Female,35,PhD,17,37,87,45,23,2.0,3,87,Semi-Urban,ML Engineer,79212,1 +95669,Female,51,Bachelors,18,86,77,57,57,2.0,2,86,Urban,ML Engineer,128576,1 +95670,Male,48,Masters,8,90,35,33,16,8.0,6,84,Urban,Manager,26203,1 +95671,Male,41,Bachelors,10,50,77,55,16,5.0,0,48,Urban,HR Executive,80250,0 +95672,Female,35,Diploma,5,13,39,56,89,8.0,4,1,Semi-Urban,HR Executive,106193,0 +95673,Female,36,Masters,1,3,50,6,16,9.0,3,71,Semi-Urban,Data Analyst,135044,0 +95674,Male,54,Masters,19,82,5,33,76,0.0,1,40,Rural,Data Analyst,94858,0 +95675,Male,42,PhD,2,49,83,0,93,1.0,3,44,Semi-Urban,Data Analyst,72645,0 +95676,Female,33,Diploma,14,54,46,83,88,3.0,7,60,Semi-Urban,Software Engineer,116419,1 +95677,Other,56,PhD,13,85,16,9,39,1.0,5,83,Urban,Software Engineer,52953,0 +95678,Male,25,Masters,6,55,61,81,46,3.0,5,90,Urban,ML Engineer,136419,1 +95679,Female,22,Masters,8,37,12,45,69,3.0,2,88,Urban,HR Executive,28892,0 +95680,Male,48,Masters,1,29,25,23,60,8.0,3,57,Urban,Manager,101897,0 +95681,Male,22,Bachelors,10,13,77,55,57,3.0,6,84,Semi-Urban,Manager,118664,0 +95682,Female,37,Diploma,0,45,37,56,25,4.0,6,34,Semi-Urban,ML Engineer,81936,0 +95683,Female,49,Diploma,5,1,98,43,1,0.0,3,60,Urban,Data Analyst,66575,0 +95684,Female,25,Bachelors,2,64,75,29,27,7.0,5,28,Urban,Software Engineer,125871,0 +95685,Female,58,Diploma,5,43,28,45,56,6.0,1,57,Rural,Data Analyst,56086,0 +95686,Male,24,Bachelors,1,4,66,6,71,0.0,6,36,Urban,ML Engineer,32876,0 +95687,Female,50,Bachelors,4,67,49,89,2,1.0,7,10,Urban,ML Engineer,78642,0 +95688,Male,29,Diploma,7,24,22,24,71,6.0,3,5,Urban,HR Executive,49040,0 +95689,Female,42,Masters,2,21,98,70,60,5.0,7,88,Urban,Software Engineer,94376,1 +95690,Male,57,Masters,8,66,76,79,53,2.0,3,48,Rural,Data Analyst,55666,1 +95691,Female,39,PhD,15,30,10,22,55,0.0,4,27,Urban,Data Analyst,95352,0 +95692,Male,39,Bachelors,18,21,13,10,25,3.0,5,12,Urban,Software Engineer,130284,0 +95693,Female,32,Masters,9,79,9,81,98,5.0,0,36,Rural,ML Engineer,40504,0 +95694,Male,56,High School,14,95,82,92,76,6.0,3,61,Rural,Manager,104788,1 +95695,Male,43,Bachelors,15,67,28,80,17,6.0,1,75,Urban,Manager,108354,1 +95696,Male,53,Bachelors,7,33,31,38,58,0.0,5,10,Rural,Data Analyst,116566,0 +95697,Male,32,Diploma,19,91,75,42,60,3.0,1,54,Semi-Urban,Software Engineer,139400,1 +95698,Male,48,Masters,5,16,89,25,11,7.0,3,68,Urban,ML Engineer,141621,0 +95699,Male,58,Diploma,3,26,78,59,86,5.0,6,90,Urban,Software Engineer,48037,1 +95700,Male,28,High School,13,46,98,7,19,4.0,3,58,Urban,HR Executive,83169,0 +95701,Male,26,Bachelors,9,70,64,29,32,5.0,5,14,Semi-Urban,Data Analyst,35143,0 +95702,Female,44,Bachelors,6,75,86,52,3,6.0,5,93,Urban,HR Executive,109777,1 +95703,Male,54,High School,15,27,42,47,10,5.0,6,41,Urban,Manager,120844,0 +95704,Male,45,Bachelors,6,88,57,20,6,2.0,0,86,Semi-Urban,Manager,46466,1 +95705,Male,22,PhD,13,41,85,6,84,0.0,5,63,Urban,ML Engineer,33205,0 +95706,Female,35,Bachelors,0,57,84,52,88,8.0,5,44,Rural,Data Analyst,25443,0 +95707,Male,38,Masters,18,12,71,75,81,9.0,0,17,Urban,Data Analyst,75086,0 +95708,Male,47,Diploma,4,81,4,28,80,8.0,0,0,Urban,ML Engineer,22491,0 +95709,Male,40,Bachelors,6,10,47,91,5,2.0,4,9,Urban,Software Engineer,119533,0 +95710,Male,27,Bachelors,8,28,52,39,67,9.0,4,14,Rural,Data Analyst,146611,0 +95711,Male,56,Bachelors,8,96,60,61,33,1.0,5,18,Urban,Data Analyst,103722,1 +95712,Female,59,Bachelors,7,89,30,70,60,1.0,0,27,Semi-Urban,Manager,144625,0 +95713,Male,42,Diploma,12,23,37,67,30,2.0,5,39,Urban,ML Engineer,77622,0 +95714,Male,58,Bachelors,0,49,92,46,4,4.0,5,51,Rural,Manager,131655,1 +95715,Female,39,Bachelors,14,51,52,20,23,5.0,5,40,Urban,Manager,66119,0 +95716,Female,51,Bachelors,16,5,15,6,47,5.0,1,29,Urban,HR Executive,57815,0 +95717,Male,58,Bachelors,10,32,3,63,77,0.0,2,75,Semi-Urban,Software Engineer,80399,0 +95718,Female,45,Bachelors,16,48,86,61,37,2.0,1,24,Rural,Data Analyst,69739,0 +95719,Female,42,Diploma,4,92,4,84,58,3.0,0,43,Urban,Manager,102449,0 +95720,Male,26,Diploma,11,36,71,46,95,9.0,1,90,Rural,Data Analyst,102717,1 +95721,Female,43,Bachelors,3,38,75,43,78,7.0,1,20,Semi-Urban,Manager,141031,0 +95722,Male,23,High School,17,29,94,43,86,3.0,4,40,Rural,HR Executive,56847,0 +95723,Other,33,Bachelors,18,1,12,37,74,6.0,0,10,Urban,Software Engineer,120049,0 +95724,Male,21,Diploma,16,40,90,16,29,8.0,2,63,Semi-Urban,Data Analyst,36825,0 +95725,Female,23,Bachelors,11,73,23,61,68,7.0,1,65,Urban,HR Executive,87736,0 +95726,Male,46,Bachelors,18,77,46,5,28,8.0,3,37,Rural,Data Analyst,144184,0 +95727,Male,22,Diploma,2,24,49,8,87,2.0,5,21,Urban,HR Executive,117899,0 +95728,Other,32,High School,10,66,43,30,80,6.0,5,25,Urban,Manager,132539,0 +95729,Other,26,Diploma,17,86,27,34,62,5.0,2,60,Urban,Data Analyst,121263,0 +95730,Male,57,Bachelors,8,68,60,34,81,8.0,6,53,Rural,Manager,27084,0 +95731,Male,58,Diploma,15,31,27,26,23,7.0,4,87,Urban,Manager,77372,0 +95732,Male,37,High School,4,19,3,36,12,6.0,5,0,Rural,Software Engineer,82244,0 +95733,Other,46,Bachelors,4,74,94,9,15,6.0,6,44,Urban,Manager,123622,0 +95734,Female,38,Masters,16,88,46,73,0,9.0,1,64,Rural,HR Executive,82218,1 +95735,Male,43,Diploma,10,26,62,36,33,1.0,1,59,Urban,Data Analyst,80198,0 +95736,Male,45,Bachelors,5,81,16,27,97,3.0,7,57,Rural,ML Engineer,90861,0 +95737,Other,26,Bachelors,7,85,80,34,31,9.0,2,47,Semi-Urban,Data Analyst,124239,1 +95738,Male,30,Bachelors,10,28,85,99,72,0.0,4,12,Urban,ML Engineer,114664,0 +95739,Female,54,Masters,15,96,3,91,3,0.0,4,74,Urban,ML Engineer,148752,1 +95740,Male,26,Bachelors,6,51,76,53,45,0.0,0,76,Urban,Software Engineer,46425,1 +95741,Male,38,Masters,3,19,7,11,29,2.0,3,70,Urban,ML Engineer,86380,0 +95742,Male,36,Bachelors,14,39,49,12,13,6.0,2,74,Semi-Urban,Manager,40507,0 +95743,Female,41,Bachelors,2,16,15,20,64,8.0,1,77,Rural,ML Engineer,27055,0 +95744,Male,27,Bachelors,8,74,61,93,66,8.0,7,88,Urban,ML Engineer,53234,1 +95745,Male,35,Diploma,9,13,55,54,44,3.0,2,34,Rural,ML Engineer,122419,0 +95746,Female,22,Masters,1,59,54,76,22,6.0,5,27,Urban,ML Engineer,94481,0 +95747,Female,24,Diploma,15,57,47,44,38,7.0,7,30,Rural,HR Executive,46685,0 +95748,Female,31,Masters,13,4,77,51,80,3.0,4,88,Semi-Urban,Software Engineer,129506,0 +95749,Male,33,PhD,13,45,15,43,21,1.0,2,35,Rural,HR Executive,92668,0 +95750,Male,54,Diploma,0,16,1,57,69,4.0,7,89,Rural,Data Analyst,59145,0 +95751,Male,25,Masters,17,90,81,88,40,6.0,0,60,Urban,ML Engineer,74461,1 +95752,Female,34,Bachelors,8,73,96,54,68,4.0,7,44,Semi-Urban,ML Engineer,111607,1 +95753,Female,23,Diploma,6,80,10,89,81,2.0,1,95,Semi-Urban,HR Executive,123694,1 +95754,Female,42,Bachelors,12,13,40,2,96,3.0,6,47,Urban,HR Executive,34269,0 +95755,Male,54,Diploma,7,83,58,47,52,8.0,3,18,Semi-Urban,Software Engineer,149345,0 +95756,Female,51,PhD,5,17,65,70,9,2.0,5,33,Urban,Manager,136105,0 +95757,Male,38,Bachelors,1,25,30,55,70,3.0,1,63,Urban,Software Engineer,45910,0 +95758,Female,56,Masters,15,39,69,52,7,8.0,4,31,Urban,ML Engineer,107546,0 +95759,Male,38,Bachelors,2,46,2,36,26,8.0,7,87,Semi-Urban,Data Analyst,117161,0 +95760,Female,28,Diploma,6,85,11,66,67,6.0,6,85,Urban,Manager,103193,1 +95761,Male,39,Bachelors,17,95,19,97,80,7.0,6,96,Urban,Software Engineer,140865,1 +95762,Male,44,Masters,11,33,81,68,8,3.0,7,52,Urban,Software Engineer,44595,0 +95763,Male,31,Masters,17,4,85,28,97,9.0,6,44,Urban,ML Engineer,26553,0 +95764,Female,29,Masters,7,23,90,66,74,8.0,7,0,Urban,Data Analyst,105406,0 +95765,Male,46,Masters,4,98,46,69,29,5.0,5,82,Urban,Software Engineer,118668,1 +95766,Male,46,High School,10,77,76,18,92,1.0,5,7,Urban,Data Analyst,97182,0 +95767,Female,28,Bachelors,0,10,85,24,32,9.0,4,22,Rural,HR Executive,137741,0 +95768,Female,37,Diploma,13,63,16,58,71,5.0,2,16,Rural,Data Analyst,98042,0 +95769,Female,27,Bachelors,3,66,75,62,25,7.0,6,86,Semi-Urban,Software Engineer,85578,1 +95770,Male,34,Diploma,16,91,55,54,90,9.0,6,77,Urban,Manager,108606,1 +95771,Male,29,Diploma,4,47,90,44,30,2.0,1,79,Rural,Software Engineer,70808,1 +95772,Male,31,Bachelors,11,36,86,63,54,9.0,2,86,Urban,Manager,122636,1 +95773,Female,42,Masters,12,39,82,21,69,6.0,6,15,Rural,Software Engineer,51615,0 +95774,Male,44,High School,16,56,60,8,39,7.0,1,66,Urban,Software Engineer,128286,0 +95775,Male,54,Bachelors,15,33,78,3,43,1.0,2,32,Urban,Manager,122678,0 +95776,Female,54,Bachelors,7,71,62,0,58,2.0,5,35,Urban,ML Engineer,27832,0 +95777,Male,24,High School,8,2,58,90,96,2.0,0,93,Urban,Software Engineer,145240,1 +95778,Male,38,Bachelors,2,19,87,65,88,9.0,5,21,Urban,HR Executive,79233,0 +95779,Other,38,Bachelors,4,35,0,71,15,0.0,2,61,Rural,ML Engineer,68942,0 +95780,Male,57,High School,3,36,6,73,93,1.0,2,25,Urban,Software Engineer,147728,0 +95781,Female,30,Masters,14,10,45,63,51,6.0,2,46,Urban,ML Engineer,47983,0 +95782,Female,51,Diploma,12,51,81,72,62,1.0,7,38,Urban,ML Engineer,75912,1 +95783,Male,51,High School,6,22,76,69,83,2.0,4,1,Urban,Manager,124187,0 +95784,Other,46,Bachelors,3,35,5,83,93,9.0,1,93,Urban,Data Analyst,91225,0 +95785,Female,24,Diploma,10,45,69,15,77,7.0,1,3,Urban,ML Engineer,58670,0 +95786,Male,59,Bachelors,15,87,88,83,54,9.0,2,76,Urban,Software Engineer,74108,1 +95787,Female,54,Diploma,14,35,29,63,65,3.0,0,55,Urban,Data Analyst,66217,0 +95788,Male,37,Masters,5,57,3,14,37,8.0,5,59,Semi-Urban,HR Executive,89855,0 +95789,Male,45,Diploma,11,8,4,44,44,0.0,2,6,Rural,Manager,128591,0 +95790,Male,40,Bachelors,11,10,32,75,51,5.0,6,37,Rural,HR Executive,79479,0 +95791,Male,33,Bachelors,0,1,9,87,70,6.0,2,42,Rural,HR Executive,43485,0 +95792,Female,52,Bachelors,0,14,59,66,71,4.0,7,30,Semi-Urban,ML Engineer,33234,0 +95793,Female,42,Masters,17,22,31,57,5,1.0,2,30,Semi-Urban,HR Executive,138484,0 +95794,Male,46,High School,2,91,52,74,95,8.0,6,67,Semi-Urban,Data Analyst,74919,1 +95795,Male,52,Diploma,5,13,82,55,15,0.0,3,28,Urban,HR Executive,26826,0 +95796,Male,24,High School,12,35,83,37,90,0.0,6,68,Semi-Urban,ML Engineer,120287,0 +95797,Male,28,Diploma,9,42,83,0,74,4.0,6,92,Urban,ML Engineer,24539,0 +95798,Male,55,Masters,18,36,33,48,42,6.0,6,74,Urban,Manager,81375,0 +95799,Male,50,Bachelors,6,7,82,7,96,6.0,6,97,Semi-Urban,Software Engineer,138736,0 +95800,Female,41,Diploma,17,75,95,99,55,9.0,7,59,Rural,ML Engineer,65951,1 +95801,Female,38,High School,9,29,13,96,29,0.0,1,93,Urban,Software Engineer,140660,0 +95802,Other,34,Bachelors,17,66,58,27,83,1.0,4,35,Urban,Software Engineer,86560,0 +95803,Male,24,High School,2,63,69,10,60,4.0,2,1,Semi-Urban,Data Analyst,63623,0 +95804,Female,30,Masters,8,90,52,42,1,1.0,3,6,Rural,Software Engineer,84243,0 +95805,Male,29,Diploma,7,10,18,19,87,7.0,4,82,Urban,HR Executive,138357,0 +95806,Female,38,Diploma,0,96,48,2,90,4.0,6,2,Semi-Urban,ML Engineer,101085,0 +95807,Male,28,Bachelors,18,12,24,40,83,0.0,6,69,Semi-Urban,ML Engineer,145726,0 +95808,Female,21,Bachelors,8,36,93,71,8,5.0,2,60,Urban,Manager,66889,1 +95809,Female,57,Bachelors,8,87,32,40,68,1.0,2,8,Urban,Data Analyst,31724,0 +95810,Male,21,Bachelors,3,75,72,4,57,4.0,5,70,Urban,HR Executive,63043,0 +95811,Male,21,Masters,10,78,7,91,29,7.0,3,12,Urban,Software Engineer,135086,0 +95812,Male,54,Bachelors,9,10,40,63,32,4.0,0,6,Semi-Urban,Software Engineer,138058,0 +95813,Male,47,Diploma,5,49,80,2,64,7.0,3,56,Urban,Data Analyst,97385,0 +95814,Male,33,Bachelors,15,56,80,1,48,4.0,4,37,Semi-Urban,HR Executive,49738,0 +95815,Female,59,PhD,0,39,75,26,85,5.0,6,1,Urban,HR Executive,145373,0 +95816,Male,37,High School,5,69,64,59,53,2.0,2,86,Semi-Urban,Data Analyst,87335,1 +95817,Male,59,Bachelors,2,71,44,3,11,6.0,2,40,Semi-Urban,Data Analyst,128447,0 +95818,Female,48,Bachelors,4,95,81,27,88,4.0,6,13,Urban,Software Engineer,104851,0 +95819,Female,47,Bachelors,3,4,80,51,48,7.0,6,43,Rural,Software Engineer,82311,0 +95820,Male,22,Masters,14,70,75,81,47,0.0,3,77,Urban,Data Analyst,101429,1 +95821,Male,22,High School,4,49,25,39,34,9.0,3,28,Urban,HR Executive,108166,0 +95822,Male,26,Diploma,4,99,93,55,11,5.0,0,41,Semi-Urban,Data Analyst,32269,1 +95823,Male,49,Bachelors,4,27,9,68,50,2.0,7,78,Rural,ML Engineer,118855,0 +95824,Female,59,Masters,14,2,74,64,39,2.0,7,69,Urban,ML Engineer,56395,0 +95825,Male,21,Diploma,13,39,41,26,34,2.0,3,18,Rural,ML Engineer,145163,0 +95826,Female,28,Bachelors,11,69,77,21,65,6.0,3,11,Urban,Manager,98293,0 +95827,Male,26,High School,4,31,39,84,84,4.0,2,64,Semi-Urban,ML Engineer,84325,0 +95828,Female,34,Bachelors,3,44,61,40,15,5.0,5,19,Urban,ML Engineer,56043,0 +95829,Male,57,Masters,3,79,92,69,45,8.0,0,19,Semi-Urban,Software Engineer,53996,1 +95830,Male,39,Bachelors,12,67,90,38,52,1.0,2,41,Urban,Manager,92269,1 +95831,Male,44,Diploma,17,84,70,18,68,6.0,7,23,Urban,Manager,148657,0 +95832,Female,46,Bachelors,3,85,19,68,96,6.0,4,39,Urban,Data Analyst,32584,0 +95833,Female,55,Bachelors,17,1,52,76,52,7.0,2,82,Rural,Data Analyst,69275,0 +95834,Female,27,Diploma,0,20,38,57,78,7.0,1,92,Rural,Data Analyst,41128,0 +95835,Male,40,Masters,3,5,70,30,19,5.0,4,54,Urban,HR Executive,74471,0 +95836,Female,51,Diploma,2,67,65,13,45,8.0,2,9,Semi-Urban,Manager,122780,0 +95837,Female,30,Bachelors,6,1,50,12,21,6.0,2,12,Urban,Software Engineer,131511,0 +95838,Female,33,Bachelors,11,82,11,86,85,2.0,1,98,Rural,Software Engineer,34691,1 +95839,Male,35,Bachelors,15,84,37,79,42,7.0,3,63,Semi-Urban,ML Engineer,109251,1 +95840,Male,48,Bachelors,12,32,35,91,54,4.0,0,65,Rural,ML Engineer,114983,0 +95841,Male,56,Diploma,10,88,6,45,43,6.0,2,33,Urban,Software Engineer,60377,0 +95842,Female,30,Masters,16,41,5,97,27,2.0,3,67,Urban,Data Analyst,22770,0 +95843,Female,44,Bachelors,8,24,32,62,16,8.0,3,78,Urban,Software Engineer,79092,0 +95844,Male,54,Masters,10,16,99,59,6,1.0,7,48,Rural,HR Executive,129762,0 +95845,Male,28,Diploma,12,53,35,97,71,0.0,2,82,Rural,Data Analyst,86343,1 +95846,Female,42,Masters,6,82,30,77,38,8.0,2,90,Semi-Urban,HR Executive,54004,1 +95847,Female,33,Diploma,4,19,77,57,72,8.0,2,83,Semi-Urban,HR Executive,63303,0 +95848,Male,35,Bachelors,9,83,63,59,66,4.0,0,73,Rural,Manager,107636,1 +95849,Male,36,Bachelors,14,47,12,82,62,8.0,7,20,Urban,HR Executive,135532,0 +95850,Other,46,Masters,6,25,47,24,90,3.0,0,26,Semi-Urban,Software Engineer,124702,0 +95851,Male,37,Bachelors,0,90,53,84,45,2.0,6,9,Semi-Urban,Manager,68191,1 +95852,Female,43,High School,0,91,4,56,55,9.0,2,37,Semi-Urban,HR Executive,93373,0 +95853,Male,57,Bachelors,9,34,17,99,69,7.0,6,14,Urban,HR Executive,43541,0 +95854,Male,35,Bachelors,3,40,51,2,15,3.0,0,1,Semi-Urban,Manager,57108,0 +95855,Male,55,Masters,17,84,4,85,80,4.0,6,32,Urban,Data Analyst,99600,0 +95856,Female,57,Masters,3,75,64,8,79,7.0,2,36,Semi-Urban,Manager,89466,0 +95857,Male,39,Bachelors,6,94,39,88,85,1.0,7,61,Semi-Urban,Manager,145465,1 +95858,Male,25,High School,6,3,70,26,20,7.0,5,62,Semi-Urban,ML Engineer,141100,0 +95859,Female,22,Masters,2,93,63,96,77,0.0,4,15,Urban,Software Engineer,147015,1 +95860,Female,43,Bachelors,15,62,86,16,0,3.0,3,23,Semi-Urban,Software Engineer,60738,0 +95861,Female,30,Bachelors,16,46,33,58,72,8.0,7,83,Urban,HR Executive,139300,0 +95862,Male,21,Masters,4,17,31,94,45,9.0,6,16,Urban,Manager,132417,0 +95863,Male,27,Diploma,4,96,74,73,80,9.0,1,86,Urban,ML Engineer,61656,1 +95864,Male,47,Diploma,8,50,78,40,97,9.0,6,55,Semi-Urban,HR Executive,85696,0 +95865,Male,40,Masters,19,98,73,66,0,9.0,3,72,Urban,ML Engineer,33849,1 +95866,Male,39,Diploma,8,45,47,12,21,6.0,1,44,Rural,Manager,104652,0 +95867,Female,39,Bachelors,8,94,35,26,31,0.0,0,5,Urban,ML Engineer,86682,0 +95868,Male,45,Masters,16,55,79,28,87,6.0,7,64,Semi-Urban,Software Engineer,31948,0 +95869,Male,41,Bachelors,5,6,58,26,34,2.0,3,47,Urban,Software Engineer,117547,0 +95870,Female,39,Diploma,16,8,83,41,42,8.0,1,0,Urban,Software Engineer,71059,0 +95871,Male,31,Diploma,17,56,82,27,44,6.0,1,42,Urban,Manager,147815,0 +95872,Female,28,Bachelors,13,46,62,90,13,4.0,5,80,Semi-Urban,HR Executive,146986,1 +95873,Female,37,Diploma,2,94,90,76,9,8.0,7,10,Urban,Software Engineer,66824,1 +95874,Male,58,Bachelors,10,51,56,58,62,0.0,1,20,Urban,Manager,82279,0 +95875,Male,40,Masters,13,88,59,62,45,3.0,3,93,Semi-Urban,Manager,30138,1 +95876,Male,51,Bachelors,2,77,57,78,54,7.0,3,15,Urban,Manager,82779,0 +95877,Other,24,Bachelors,18,57,25,2,73,6.0,6,72,Semi-Urban,ML Engineer,29247,0 +95878,Male,32,Bachelors,6,5,8,30,71,4.0,4,85,Urban,Software Engineer,54928,0 +95879,Male,43,High School,1,83,99,10,87,7.0,6,3,Urban,ML Engineer,87346,0 +95880,Male,34,Bachelors,3,30,68,51,37,3.0,7,12,Rural,HR Executive,29313,0 +95881,Male,46,Diploma,1,4,60,97,66,8.0,1,46,Urban,HR Executive,69998,0 +95882,Female,52,Diploma,3,36,45,89,76,1.0,0,10,Rural,Software Engineer,116777,0 +95883,Female,41,Bachelors,3,36,99,8,55,5.0,2,21,Semi-Urban,Data Analyst,66794,0 +95884,Female,47,Masters,1,67,48,95,97,6.0,1,2,Urban,Manager,135640,0 +95885,Male,52,Bachelors,13,14,47,2,89,2.0,3,76,Semi-Urban,Software Engineer,34156,0 +95886,Female,43,Bachelors,4,96,82,70,16,2.0,7,95,Urban,Software Engineer,58032,1 +95887,Female,29,Masters,6,29,82,92,46,2.0,1,10,Rural,Data Analyst,37021,0 +95888,Other,59,Bachelors,3,41,54,69,11,4.0,7,55,Rural,HR Executive,89581,0 +95889,Female,28,Diploma,14,57,28,91,43,0.0,6,62,Urban,ML Engineer,114308,0 +95890,Male,33,Masters,9,23,39,97,69,3.0,1,57,Rural,Manager,97157,0 +95891,Male,33,Masters,14,86,96,97,21,5.0,1,36,Semi-Urban,HR Executive,146541,1 +95892,Male,29,Bachelors,17,24,76,61,50,5.0,4,97,Urban,Data Analyst,87555,1 +95893,Male,53,Masters,1,5,23,81,28,1.0,6,1,Semi-Urban,Manager,101165,0 +95894,Female,25,High School,5,54,12,89,2,7.0,2,89,Urban,HR Executive,70430,1 +95895,Male,42,Bachelors,18,96,7,83,86,2.0,4,89,Rural,Manager,79907,1 +95896,Male,47,Bachelors,7,0,58,95,12,7.0,6,49,Semi-Urban,Software Engineer,49714,0 +95897,Male,59,Bachelors,13,55,7,59,32,9.0,1,82,Rural,Manager,46660,0 +95898,Female,42,Bachelors,11,44,76,19,44,3.0,3,46,Rural,Manager,87631,0 +95899,Male,28,Masters,14,69,57,43,57,2.0,2,2,Rural,Data Analyst,130747,0 +95900,Male,34,Masters,6,36,16,72,43,3.0,2,40,Urban,ML Engineer,36882,0 +95901,Male,35,Bachelors,3,75,54,15,31,3.0,2,57,Urban,ML Engineer,149011,0 +95902,Male,56,Diploma,19,32,98,2,40,6.0,7,72,Urban,Manager,131348,0 +95903,Male,48,Diploma,5,44,49,26,37,5.0,2,49,Rural,HR Executive,87665,0 +95904,Male,59,Bachelors,17,39,77,47,49,4.0,4,11,Urban,HR Executive,38996,0 +95905,Male,30,Masters,14,49,64,65,47,1.0,7,97,Rural,Software Engineer,108454,1 +95906,Male,42,Bachelors,8,72,1,88,44,9.0,0,30,Semi-Urban,Software Engineer,46918,0 +95907,Male,21,Bachelors,2,87,88,57,81,1.0,7,68,Semi-Urban,HR Executive,43677,1 +95908,Female,29,Bachelors,11,69,16,85,8,3.0,4,43,Rural,HR Executive,145714,0 +95909,Female,51,High School,19,18,33,18,79,1.0,3,55,Semi-Urban,Software Engineer,134420,0 +95910,Male,41,Masters,17,49,78,93,81,6.0,2,1,Urban,ML Engineer,86038,0 +95911,Male,25,Diploma,6,47,62,47,61,4.0,1,44,Semi-Urban,Software Engineer,139430,0 +95912,Female,27,Bachelors,10,39,41,48,93,2.0,1,76,Rural,Data Analyst,141477,0 +95913,Male,39,Masters,3,2,56,52,8,6.0,4,51,Semi-Urban,Data Analyst,141316,0 +95914,Male,32,Bachelors,6,48,44,47,51,7.0,3,28,Urban,Software Engineer,86396,0 +95915,Female,32,Bachelors,9,90,42,54,58,3.0,7,39,Urban,Software Engineer,105096,0 +95916,Female,23,Diploma,14,75,93,9,1,2.0,0,71,Semi-Urban,Software Engineer,87198,1 +95917,Male,53,High School,19,53,35,45,6,0.0,1,35,Urban,ML Engineer,79494,0 +95918,Male,23,Bachelors,3,14,68,47,21,9.0,5,3,Urban,Software Engineer,84752,0 +95919,Female,24,Bachelors,12,45,44,92,59,0.0,4,62,Urban,Software Engineer,33412,1 +95920,Male,44,Masters,5,92,7,53,53,3.0,1,30,Rural,Software Engineer,52430,0 +95921,Female,56,High School,5,1,8,76,50,4.0,0,55,Rural,Software Engineer,130088,0 +95922,Male,31,Diploma,6,86,39,97,64,1.0,5,50,Urban,Manager,104368,1 +95923,Female,26,Diploma,13,82,54,73,15,1.0,5,52,Urban,HR Executive,130139,1 +95924,Male,44,Bachelors,4,3,84,32,55,3.0,2,1,Semi-Urban,Manager,137166,0 +95925,Male,32,Bachelors,2,63,31,34,54,8.0,3,25,Semi-Urban,Software Engineer,133446,0 +95926,Female,49,Diploma,4,69,30,65,24,8.0,0,56,Urban,Manager,117837,0 +95927,Male,30,PhD,16,56,69,55,61,1.0,1,19,Semi-Urban,Data Analyst,28017,0 +95928,Male,51,Bachelors,9,80,73,55,86,5.0,4,23,Semi-Urban,Manager,131455,0 +95929,Male,47,Masters,11,87,14,55,18,2.0,5,44,Urban,Software Engineer,21643,0 +95930,Male,42,Bachelors,1,13,53,61,19,2.0,5,50,Urban,Manager,57899,0 +95931,Male,47,Masters,1,86,31,8,68,2.0,3,44,Urban,Manager,42848,0 +95932,Male,39,Bachelors,8,2,65,74,49,4.0,4,80,Urban,ML Engineer,23942,0 +95933,Male,38,Diploma,0,8,27,59,7,6.0,2,65,Urban,ML Engineer,132089,0 +95934,Female,46,Diploma,8,70,11,49,1,1.0,7,64,Urban,ML Engineer,102100,0 +95935,Female,47,Bachelors,19,49,80,41,41,5.0,0,61,Urban,HR Executive,141803,0 +95936,Male,21,Bachelors,16,16,52,75,62,6.0,5,65,Semi-Urban,Data Analyst,74452,0 +95937,Female,54,Bachelors,18,5,48,21,30,3.0,4,13,Urban,HR Executive,66799,0 +95938,Male,28,Masters,4,93,86,35,95,0.0,7,70,Urban,ML Engineer,78004,1 +95939,Female,37,Bachelors,19,90,99,6,97,3.0,3,75,Semi-Urban,HR Executive,43786,1 +95940,Male,53,Masters,16,48,50,8,76,3.0,2,47,Urban,ML Engineer,42102,0 +95941,Other,45,High School,19,66,2,78,71,4.0,1,57,Urban,HR Executive,95550,0 +95942,Female,35,Diploma,0,17,61,84,1,7.0,2,76,Urban,Software Engineer,28319,0 +95943,Male,26,Bachelors,13,77,76,27,62,8.0,0,24,Semi-Urban,Manager,114423,0 +95944,Male,29,High School,11,26,27,16,5,3.0,3,94,Urban,Manager,104909,0 +95945,Male,59,Bachelors,8,53,40,97,20,3.0,4,30,Urban,Data Analyst,49852,0 +95946,Female,27,Diploma,0,85,68,50,49,1.0,3,67,Urban,Data Analyst,49043,1 +95947,Male,53,High School,18,94,46,36,8,1.0,4,10,Semi-Urban,Manager,138117,0 +95948,Female,43,High School,9,97,24,66,25,4.0,4,49,Urban,Manager,52655,0 +95949,Female,24,Bachelors,4,30,85,8,56,6.0,3,37,Urban,HR Executive,74121,0 +95950,Male,49,Bachelors,11,60,79,94,60,5.0,4,1,Rural,Software Engineer,44306,0 +95951,Female,36,Diploma,6,27,25,90,25,5.0,1,65,Urban,Software Engineer,124461,0 +95952,Female,38,Diploma,8,19,66,17,68,5.0,0,60,Urban,Manager,21147,0 +95953,Female,41,High School,14,88,20,92,6,0.0,3,45,Rural,ML Engineer,96599,1 +95954,Male,53,Diploma,12,39,58,49,94,2.0,7,24,Rural,Data Analyst,55453,0 +95955,Male,40,Bachelors,0,99,34,85,74,9.0,2,13,Rural,Manager,145211,0 +95956,Male,46,Bachelors,18,22,74,45,81,8.0,4,96,Urban,HR Executive,26756,1 +95957,Male,50,Diploma,1,43,87,53,42,0.0,3,90,Urban,Data Analyst,32426,1 +95958,Male,58,High School,6,51,85,77,86,3.0,2,76,Urban,HR Executive,75154,1 +95959,Female,40,High School,3,32,55,11,62,5.0,6,22,Semi-Urban,HR Executive,130889,0 +95960,Male,25,Diploma,10,31,31,37,91,0.0,5,38,Urban,Software Engineer,84456,0 +95961,Male,55,High School,14,72,51,20,5,9.0,0,36,Rural,Manager,50869,0 +95962,Female,37,Bachelors,9,80,8,51,5,1.0,7,29,Semi-Urban,ML Engineer,30622,0 +95963,Male,27,High School,5,29,65,8,29,1.0,1,22,Rural,Software Engineer,129142,0 +95964,Male,34,Bachelors,14,29,4,64,6,7.0,0,72,Rural,Data Analyst,89786,0 +95965,Female,39,Bachelors,11,47,29,70,76,8.0,4,36,Urban,HR Executive,33734,0 +95966,Other,54,Diploma,11,81,20,71,80,3.0,2,33,Urban,Manager,129496,0 +95967,Male,42,Bachelors,12,95,36,16,35,3.0,1,56,Semi-Urban,ML Engineer,58329,0 +95968,Male,57,Diploma,15,25,40,36,12,4.0,3,38,Semi-Urban,Manager,130126,0 +95969,Male,33,Diploma,1,67,99,74,82,4.0,6,18,Rural,Data Analyst,122998,1 +95970,Male,53,High School,3,7,34,49,34,0.0,4,8,Rural,Data Analyst,73325,0 +95971,Female,50,Bachelors,18,2,6,6,9,3.0,2,78,Semi-Urban,Manager,77852,0 +95972,Male,26,Diploma,9,55,33,28,39,6.0,6,26,Semi-Urban,Data Analyst,70805,0 +95973,Male,27,Masters,6,1,15,84,31,2.0,1,16,Rural,Software Engineer,57400,0 +95974,Female,36,Masters,1,63,87,98,9,6.0,0,67,Semi-Urban,Data Analyst,126133,1 +95975,Male,47,Diploma,0,78,80,51,32,7.0,4,30,Urban,ML Engineer,44124,1 +95976,Male,45,High School,8,92,1,63,69,3.0,5,41,Semi-Urban,Software Engineer,105381,0 +95977,Male,31,Diploma,19,90,91,66,40,6.0,5,60,Urban,Manager,94810,1 +95978,Male,35,Bachelors,19,83,96,94,99,9.0,4,21,Rural,Software Engineer,21983,1 +95979,Male,52,Bachelors,9,48,38,69,10,1.0,1,95,Urban,Software Engineer,123393,1 +95980,Male,44,Bachelors,1,36,80,41,54,7.0,2,55,Rural,Data Analyst,100528,0 +95981,Male,54,Masters,2,71,57,81,41,8.0,1,7,Rural,HR Executive,146513,0 +95982,Male,22,Masters,13,26,38,10,78,0.0,3,69,Semi-Urban,HR Executive,96703,0 +95983,Male,49,PhD,5,83,75,62,41,6.0,1,10,Urban,Manager,68131,0 +95984,Female,46,High School,10,63,17,93,27,1.0,2,28,Urban,ML Engineer,140056,0 +95985,Female,59,Bachelors,11,21,53,40,76,2.0,6,63,Urban,Software Engineer,31378,0 +95986,Male,50,High School,0,49,37,25,20,0.0,7,5,Rural,Manager,66723,0 +95987,Female,54,Masters,1,67,77,29,24,0.0,1,58,Rural,HR Executive,98562,0 +95988,Female,33,Bachelors,12,10,86,99,10,3.0,2,23,Urban,ML Engineer,145624,0 +95989,Female,55,Bachelors,1,37,4,35,85,7.0,3,96,Rural,HR Executive,99044,0 +95990,Female,49,PhD,19,51,5,84,0,7.0,1,89,Semi-Urban,Manager,103545,0 +95991,Female,55,Masters,2,28,14,64,84,3.0,0,80,Urban,Data Analyst,143525,0 +95992,Female,26,Bachelors,1,66,94,16,82,8.0,1,48,Semi-Urban,HR Executive,106424,0 +95993,Male,22,Bachelors,2,62,99,70,61,8.0,0,48,Urban,Manager,99384,1 +95994,Female,51,High School,10,45,75,67,24,7.0,1,2,Semi-Urban,Software Engineer,44260,0 +95995,Male,50,High School,8,36,56,45,15,1.0,1,31,Urban,Data Analyst,69303,0 +95996,Female,52,Bachelors,14,92,70,38,16,6.0,4,63,Rural,Software Engineer,101718,1 +95997,Female,52,Bachelors,18,20,39,45,11,5.0,6,71,Urban,Manager,106989,0 +95998,Male,59,Bachelors,1,32,68,68,38,0.0,4,57,Urban,Data Analyst,97971,0 +95999,Male,57,High School,0,10,20,54,66,2.0,0,35,Urban,Data Analyst,77780,0 +96000,Male,56,High School,15,55,74,79,56,8.0,1,92,Urban,Software Engineer,55422,1 +96001,Male,42,Bachelors,13,23,92,29,66,4.0,6,32,Semi-Urban,Data Analyst,119313,0 +96002,Male,47,Diploma,2,65,0,32,50,6.0,5,12,Urban,Software Engineer,129084,0 +96003,Male,58,Masters,10,9,82,98,28,9.0,5,92,Semi-Urban,HR Executive,96172,1 +96004,Female,50,Masters,15,11,25,24,61,3.0,6,69,Urban,ML Engineer,53349,0 +96005,Male,45,Masters,9,88,26,12,52,3.0,0,41,Urban,Data Analyst,81750,0 +96006,Male,53,Diploma,0,59,83,42,55,4.0,4,72,Semi-Urban,HR Executive,22704,1 +96007,Male,35,Bachelors,4,25,3,79,89,2.0,2,6,Urban,Manager,61453,0 +96008,Male,35,Masters,3,77,68,65,11,1.0,2,20,Rural,Data Analyst,20142,0 +96009,Male,26,Bachelors,6,11,38,55,1,2.0,3,7,Urban,Software Engineer,131557,0 +96010,Female,33,Diploma,12,36,95,29,83,3.0,1,45,Urban,ML Engineer,129539,0 +96011,Male,59,Masters,18,63,88,82,42,9.0,1,56,Rural,ML Engineer,52685,1 +96012,Male,53,High School,6,32,28,75,31,6.0,2,27,Semi-Urban,ML Engineer,109146,0 +96013,Male,24,Bachelors,15,17,74,27,73,1.0,6,79,Rural,ML Engineer,98972,0 +96014,Male,30,Bachelors,11,37,2,8,41,5.0,1,1,Urban,ML Engineer,122142,0 +96015,Female,48,Bachelors,1,3,69,10,58,1.0,5,74,Urban,Software Engineer,119482,0 +96016,Other,32,Diploma,4,13,13,16,84,3.0,3,56,Urban,ML Engineer,143004,0 +96017,Male,57,Diploma,5,39,81,25,80,7.0,3,82,Urban,ML Engineer,22118,0 +96018,Female,21,Bachelors,18,52,45,62,8,9.0,1,44,Semi-Urban,HR Executive,38499,0 +96019,Male,59,Bachelors,13,40,76,67,82,9.0,6,31,Urban,ML Engineer,61707,0 +96020,Male,45,High School,2,78,8,84,18,6.0,7,48,Urban,HR Executive,62088,0 +96021,Male,54,Masters,17,97,75,88,16,0.0,2,76,Urban,ML Engineer,144932,1 +96022,Female,41,Diploma,14,71,84,12,37,6.0,0,29,Urban,HR Executive,53101,0 +96023,Male,45,Bachelors,0,43,14,37,12,9.0,7,93,Urban,Software Engineer,30314,0 +96024,Male,21,Bachelors,2,78,65,72,78,7.0,2,32,Rural,Manager,123934,1 +96025,Male,49,Diploma,10,54,56,24,35,2.0,6,22,Urban,Manager,64009,0 +96026,Female,32,Masters,5,17,55,95,32,8.0,7,28,Urban,HR Executive,37992,0 +96027,Female,55,Bachelors,5,57,89,51,61,9.0,6,34,Semi-Urban,HR Executive,112221,0 +96028,Male,59,Masters,0,59,8,13,36,5.0,2,80,Urban,Manager,108610,0 +96029,Female,49,Bachelors,12,43,43,12,60,7.0,3,84,Urban,HR Executive,114756,0 +96030,Male,49,Masters,15,97,27,46,81,6.0,7,31,Urban,Data Analyst,100566,0 +96031,Male,49,Bachelors,12,49,88,22,23,3.0,4,61,Semi-Urban,ML Engineer,73407,0 +96032,Female,47,Bachelors,6,38,85,60,99,3.0,5,17,Urban,Software Engineer,34002,0 +96033,Male,51,Masters,19,35,29,96,18,6.0,7,40,Urban,Manager,137532,0 +96034,Male,51,Bachelors,11,26,49,92,56,2.0,0,75,Rural,ML Engineer,70311,1 +96035,Male,26,Masters,15,29,1,84,27,9.0,7,38,Urban,HR Executive,126734,0 +96036,Female,58,Bachelors,0,95,96,79,40,0.0,2,87,Semi-Urban,Data Analyst,141620,1 +96037,Male,53,Bachelors,16,53,59,92,47,2.0,6,87,Urban,HR Executive,39508,1 +96038,Female,30,Bachelors,10,91,5,76,50,8.0,6,46,Urban,Software Engineer,148198,0 +96039,Male,41,Diploma,8,86,48,13,75,1.0,3,30,Semi-Urban,HR Executive,64769,0 +96040,Female,57,PhD,1,60,96,11,40,3.0,2,46,Urban,Software Engineer,46337,0 +96041,Female,44,Bachelors,12,94,98,87,27,5.0,3,45,Semi-Urban,ML Engineer,136757,1 +96042,Male,35,Bachelors,5,47,26,21,27,8.0,0,62,Urban,Software Engineer,82733,0 +96043,Male,22,Bachelors,11,77,10,96,29,0.0,4,52,Urban,Software Engineer,142355,1 +96044,Female,59,Bachelors,12,49,58,41,50,8.0,4,73,Semi-Urban,ML Engineer,64777,0 +96045,Male,55,High School,1,61,84,74,3,0.0,4,99,Rural,Software Engineer,78899,1 +96046,Male,21,Bachelors,18,27,53,44,49,6.0,6,25,Urban,HR Executive,123851,0 +96047,Male,31,Diploma,17,9,54,17,49,0.0,2,87,Urban,HR Executive,135157,0 +96048,Male,22,Diploma,10,86,46,6,23,5.0,1,95,Urban,Manager,80248,0 +96049,Male,51,Bachelors,18,95,19,34,96,3.0,3,38,Urban,Data Analyst,69792,0 +96050,Male,31,Diploma,9,0,61,31,83,6.0,5,38,Urban,Manager,115714,0 +96051,Female,46,High School,7,0,93,58,70,8.0,4,13,Urban,ML Engineer,118445,0 +96052,Female,25,Masters,8,50,55,21,31,7.0,3,62,Semi-Urban,Data Analyst,93979,0 +96053,Male,58,PhD,13,95,9,96,94,9.0,2,48,Semi-Urban,Data Analyst,98634,1 +96054,Male,43,Bachelors,12,88,19,73,2,6.0,2,18,Urban,Data Analyst,42984,0 +96055,Male,49,Masters,8,45,37,99,87,5.0,0,18,Urban,HR Executive,45275,0 +96056,Male,34,Diploma,0,33,28,15,64,2.0,0,22,Urban,Manager,61296,0 +96057,Male,46,Diploma,17,28,86,70,17,4.0,0,63,Semi-Urban,Manager,46238,1 +96058,Male,58,PhD,6,13,82,43,72,1.0,0,79,Semi-Urban,Manager,74296,0 +96059,Female,55,Masters,14,57,28,16,53,8.0,4,84,Urban,Software Engineer,82105,0 +96060,Male,24,Bachelors,2,20,98,12,62,5.0,2,4,Urban,HR Executive,102338,0 +96061,Male,53,Diploma,15,53,46,45,86,9.0,7,75,Urban,Software Engineer,63913,0 +96062,Female,53,High School,4,96,84,41,95,3.0,5,68,Urban,Data Analyst,127752,1 +96063,Female,46,High School,3,41,31,85,17,3.0,4,83,Urban,HR Executive,97630,0 +96064,Male,48,PhD,7,99,24,22,9,6.0,6,23,Urban,ML Engineer,146718,0 +96065,Male,45,Masters,6,24,9,24,94,2.0,2,45,Urban,ML Engineer,52418,0 +96066,Male,56,Masters,14,16,42,62,79,2.0,6,13,Urban,ML Engineer,49814,0 +96067,Male,35,Diploma,13,59,5,55,27,9.0,5,85,Semi-Urban,Manager,115877,0 +96068,Male,24,Diploma,6,63,28,77,64,2.0,0,22,Urban,Software Engineer,98940,0 +96069,Male,56,Diploma,6,63,31,4,34,9.0,5,45,Urban,Data Analyst,104919,0 +96070,Male,30,Bachelors,11,8,29,56,30,7.0,1,78,Urban,ML Engineer,101844,0 +96071,Male,26,Diploma,9,56,86,6,56,6.0,0,43,Urban,Software Engineer,38002,0 +96072,Male,22,Masters,17,32,32,42,82,2.0,6,99,Urban,Manager,34845,0 +96073,Female,35,Diploma,18,70,50,79,68,8.0,1,63,Urban,Manager,83775,1 +96074,Other,46,Masters,19,51,89,6,63,3.0,1,69,Semi-Urban,ML Engineer,130302,0 +96075,Male,57,High School,13,50,22,53,10,3.0,0,43,Urban,HR Executive,26105,0 +96076,Male,39,Bachelors,1,88,75,94,31,4.0,5,55,Urban,Software Engineer,104734,1 +96077,Male,22,Bachelors,12,91,76,39,81,4.0,7,34,Urban,HR Executive,40187,1 +96078,Female,51,High School,7,82,45,2,43,5.0,4,50,Rural,Manager,128314,0 +96079,Male,58,Diploma,5,40,55,23,77,9.0,6,19,Urban,HR Executive,122097,0 +96080,Male,34,Diploma,10,79,0,27,54,3.0,0,4,Urban,Data Analyst,38358,0 +96081,Female,56,Diploma,5,0,13,23,8,4.0,3,99,Urban,HR Executive,124758,0 +96082,Male,31,High School,10,23,56,59,69,3.0,7,9,Rural,Data Analyst,85594,0 +96083,Male,44,Bachelors,1,78,19,3,89,6.0,5,95,Semi-Urban,ML Engineer,67011,0 +96084,Other,35,Masters,0,43,8,1,7,2.0,7,14,Semi-Urban,Data Analyst,29456,0 +96085,Male,31,Diploma,12,14,4,28,49,1.0,6,92,Rural,Data Analyst,72659,0 +96086,Male,43,Masters,3,2,6,22,50,4.0,1,78,Urban,Manager,100934,0 +96087,Other,46,High School,8,78,63,72,78,0.0,0,54,Urban,HR Executive,37999,1 +96088,Female,46,Bachelors,4,3,79,47,50,1.0,6,10,Semi-Urban,Software Engineer,72523,0 +96089,Male,51,Bachelors,8,28,20,76,47,4.0,2,83,Urban,Manager,86644,0 +96090,Male,59,Bachelors,13,21,79,49,48,4.0,1,78,Rural,Data Analyst,60531,0 +96091,Other,42,Diploma,17,84,99,31,21,1.0,3,99,Semi-Urban,ML Engineer,51425,1 +96092,Male,47,Masters,10,49,97,11,60,8.0,4,69,Rural,Software Engineer,121399,0 +96093,Male,41,Diploma,12,21,55,21,23,3.0,1,88,Semi-Urban,Manager,71499,0 +96094,Female,38,High School,2,79,52,34,37,1.0,4,58,Semi-Urban,Manager,24468,0 +96095,Male,41,High School,16,70,50,85,57,7.0,2,3,Urban,HR Executive,43478,0 +96096,Male,47,Bachelors,6,29,54,95,2,1.0,4,51,Semi-Urban,Software Engineer,134399,0 +96097,Female,33,Diploma,17,81,11,17,31,1.0,0,45,Urban,Data Analyst,33177,0 +96098,Male,49,Diploma,4,11,35,85,12,6.0,0,75,Semi-Urban,Manager,63708,0 +96099,Male,41,Bachelors,14,14,34,85,13,4.0,6,39,Semi-Urban,ML Engineer,140816,0 +96100,Male,59,Bachelors,5,38,35,39,8,6.0,6,8,Semi-Urban,Data Analyst,92387,0 +96101,Female,54,PhD,4,91,46,66,52,4.0,6,74,Urban,Manager,98372,1 +96102,Male,52,Bachelors,4,61,26,25,86,3.0,6,78,Urban,Manager,52863,0 +96103,Female,36,Diploma,5,20,68,61,67,4.0,5,0,Urban,Manager,36787,0 +96104,Male,44,Diploma,18,42,79,1,68,6.0,1,66,Urban,Manager,76664,0 +96105,Female,50,Masters,0,19,91,86,45,9.0,1,93,Urban,Software Engineer,115054,1 +96106,Male,47,Diploma,15,0,51,26,46,6.0,3,28,Urban,Manager,112830,0 +96107,Male,52,Diploma,11,55,22,8,25,8.0,2,2,Semi-Urban,ML Engineer,52852,0 +96108,Male,48,Bachelors,7,25,66,32,61,8.0,3,99,Rural,HR Executive,46700,0 +96109,Male,59,Bachelors,17,55,17,75,5,4.0,5,76,Urban,HR Executive,108893,0 +96110,Male,57,Diploma,15,21,78,92,38,7.0,4,76,Semi-Urban,HR Executive,85609,1 +96111,Male,49,High School,10,46,51,45,30,6.0,4,69,Semi-Urban,Software Engineer,101292,0 +96112,Male,54,Bachelors,12,30,22,73,10,8.0,4,90,Semi-Urban,Software Engineer,74838,0 +96113,Female,47,Bachelors,9,90,31,24,39,5.0,0,83,Semi-Urban,Software Engineer,100988,0 +96114,Male,43,Bachelors,6,29,17,38,69,8.0,5,48,Urban,HR Executive,125870,0 +96115,Male,24,Diploma,6,82,18,46,21,7.0,6,63,Urban,Software Engineer,145095,0 +96116,Male,30,Masters,11,42,98,66,33,1.0,6,87,Rural,HR Executive,118283,1 +96117,Male,26,Bachelors,2,77,64,43,41,4.0,7,90,Semi-Urban,Data Analyst,61983,1 +96118,Male,34,PhD,2,64,9,94,52,7.0,4,69,Urban,Software Engineer,93899,1 +96119,Male,29,Masters,13,40,19,71,50,0.0,3,18,Urban,Data Analyst,50139,0 +96120,Male,23,Bachelors,6,97,45,30,24,7.0,6,74,Urban,Software Engineer,91135,1 +96121,Male,54,Bachelors,15,79,7,96,59,2.0,6,68,Semi-Urban,Software Engineer,118196,1 +96122,Female,50,Masters,2,66,44,16,63,6.0,2,85,Rural,Software Engineer,78666,0 +96123,Female,56,PhD,7,44,96,7,9,5.0,6,53,Urban,ML Engineer,34176,0 +96124,Female,40,Diploma,0,85,36,27,96,1.0,3,12,Urban,Manager,90249,0 +96125,Female,45,Diploma,19,93,2,53,45,2.0,2,89,Semi-Urban,Manager,84540,0 +96126,Male,55,Diploma,0,0,90,79,88,8.0,2,66,Urban,Software Engineer,143367,1 +96127,Male,34,High School,13,54,3,82,51,1.0,2,31,Urban,Software Engineer,66284,0 +96128,Male,44,Bachelors,1,62,45,33,49,3.0,1,62,Urban,ML Engineer,89910,0 +96129,Male,55,Bachelors,15,21,85,82,12,0.0,1,67,Urban,Data Analyst,35040,1 +96130,Female,40,Masters,7,83,86,11,16,5.0,3,48,Urban,Data Analyst,23788,0 +96131,Female,22,Diploma,7,84,1,99,83,5.0,7,26,Urban,Software Engineer,51241,0 +96132,Male,46,Bachelors,17,77,18,36,2,4.0,7,51,Rural,Manager,125302,0 +96133,Female,32,Diploma,18,53,86,49,9,0.0,3,57,Semi-Urban,Manager,23301,1 +96134,Female,54,Masters,7,49,2,92,70,0.0,2,94,Semi-Urban,Manager,47382,0 +96135,Male,26,Bachelors,1,23,40,41,61,1.0,4,57,Rural,Data Analyst,25382,0 +96136,Male,26,PhD,16,63,89,80,54,7.0,3,56,Urban,Data Analyst,86204,1 +96137,Male,37,Diploma,4,75,44,60,17,6.0,3,67,Urban,Data Analyst,58304,1 +96138,Male,31,Bachelors,17,38,34,0,88,4.0,1,2,Rural,ML Engineer,55031,0 +96139,Male,29,Bachelors,3,20,90,71,58,3.0,5,79,Semi-Urban,ML Engineer,41570,1 +96140,Male,37,Masters,5,87,43,26,68,9.0,3,22,Rural,ML Engineer,114815,0 +96141,Female,22,Bachelors,6,79,97,19,17,4.0,3,93,Urban,Data Analyst,65207,1 +96142,Female,29,Diploma,10,26,12,87,42,5.0,7,7,Semi-Urban,Software Engineer,87858,0 +96143,Female,32,High School,0,18,38,17,75,3.0,6,14,Urban,Software Engineer,65077,0 +96144,Female,36,Bachelors,18,92,82,20,70,4.0,6,57,Rural,Software Engineer,121010,1 +96145,Female,21,High School,13,45,82,39,72,6.0,0,7,Semi-Urban,Data Analyst,129527,0 +96146,Female,37,Bachelors,5,90,35,63,11,0.0,1,21,Semi-Urban,Software Engineer,104911,0 +96147,Female,21,Diploma,17,95,54,44,39,3.0,6,69,Urban,Data Analyst,52916,1 +96148,Male,23,Bachelors,15,74,7,79,77,0.0,2,16,Semi-Urban,ML Engineer,53988,0 +96149,Male,33,Masters,3,13,51,36,76,3.0,5,70,Semi-Urban,HR Executive,101021,0 +96150,Male,37,Bachelors,16,87,24,97,32,1.0,6,53,Rural,Data Analyst,139084,1 +96151,Female,25,Bachelors,18,98,33,23,14,9.0,5,29,Rural,Data Analyst,149147,0 +96152,Male,37,High School,11,90,13,56,40,0.0,7,45,Urban,Manager,47495,0 +96153,Male,49,High School,12,81,94,13,16,7.0,2,28,Rural,Software Engineer,25217,0 +96154,Male,30,Bachelors,14,14,62,50,61,1.0,7,99,Rural,ML Engineer,87336,0 +96155,Male,36,Bachelors,5,30,18,2,22,8.0,0,82,Urban,ML Engineer,136942,0 +96156,Female,49,Diploma,2,68,31,24,67,4.0,7,28,Rural,HR Executive,21950,0 +96157,Male,33,Bachelors,16,12,17,25,13,8.0,2,77,Urban,Manager,80546,0 +96158,Female,41,Bachelors,12,28,44,19,83,5.0,7,63,Urban,ML Engineer,112539,0 +96159,Male,40,Bachelors,12,24,94,63,54,7.0,6,30,Urban,ML Engineer,144700,0 +96160,Other,33,Bachelors,1,23,34,48,40,5.0,6,64,Rural,HR Executive,85563,0 +96161,Other,51,Bachelors,14,89,23,86,52,7.0,3,46,Semi-Urban,Data Analyst,70588,1 +96162,Male,34,Masters,2,99,6,10,10,8.0,0,16,Urban,HR Executive,61178,0 +96163,Female,31,Masters,2,28,69,2,41,5.0,0,30,Semi-Urban,HR Executive,72769,0 +96164,Female,52,Bachelors,2,33,15,4,30,5.0,0,40,Semi-Urban,ML Engineer,82591,0 +96165,Other,55,Bachelors,19,24,68,93,7,7.0,2,0,Rural,ML Engineer,87074,0 +96166,Male,40,PhD,2,40,98,53,27,7.0,1,77,Semi-Urban,Data Analyst,127451,1 +96167,Female,34,Diploma,0,0,8,26,55,4.0,1,52,Semi-Urban,HR Executive,20470,0 +96168,Male,54,Diploma,15,3,0,0,39,1.0,4,57,Urban,HR Executive,126032,0 +96169,Male,57,Diploma,16,86,48,56,44,6.0,7,64,Semi-Urban,HR Executive,122792,1 +96170,Female,29,PhD,3,85,95,51,92,2.0,6,72,Urban,ML Engineer,97181,1 +96171,Female,39,Masters,9,22,87,0,99,3.0,6,9,Semi-Urban,HR Executive,33021,0 +96172,Male,32,Diploma,7,71,87,44,29,6.0,0,86,Rural,Software Engineer,63010,1 +96173,Male,44,Masters,6,54,95,93,28,6.0,1,8,Urban,HR Executive,20128,1 +96174,Male,39,High School,18,19,7,52,60,9.0,3,30,Rural,HR Executive,74792,0 +96175,Female,53,Bachelors,12,94,75,28,98,9.0,0,4,Urban,HR Executive,74153,0 +96176,Female,28,Masters,12,32,93,93,76,1.0,0,47,Semi-Urban,Manager,50418,1 +96177,Female,51,Diploma,0,65,81,56,52,7.0,4,25,Urban,HR Executive,70822,0 +96178,Male,22,High School,13,60,58,24,92,6.0,2,54,Urban,Data Analyst,38271,0 +96179,Female,24,High School,19,61,86,0,21,8.0,2,9,Urban,Software Engineer,133888,0 +96180,Female,54,High School,17,37,36,47,69,4.0,2,78,Semi-Urban,HR Executive,114000,0 +96181,Male,55,High School,4,41,87,44,30,1.0,2,82,Rural,Software Engineer,114354,1 +96182,Male,51,Diploma,19,18,15,5,72,7.0,4,30,Urban,Manager,47385,0 +96183,Male,58,High School,0,46,88,40,55,8.0,6,98,Urban,Data Analyst,60830,1 +96184,Male,23,Bachelors,1,17,82,34,69,9.0,1,11,Semi-Urban,HR Executive,91366,0 +96185,Female,58,Masters,10,90,27,64,2,7.0,0,89,Urban,ML Engineer,136619,1 +96186,Male,40,Bachelors,5,95,16,1,28,4.0,5,9,Urban,ML Engineer,53373,0 +96187,Male,28,Bachelors,11,78,3,85,62,3.0,5,85,Urban,HR Executive,106878,1 +96188,Female,52,Bachelors,3,28,64,26,76,4.0,7,85,Urban,Manager,129338,0 +96189,Female,36,Bachelors,2,87,58,40,32,8.0,1,80,Urban,Manager,121563,1 +96190,Male,56,Bachelors,7,23,64,97,47,9.0,2,18,Semi-Urban,ML Engineer,56498,0 +96191,Female,57,Bachelors,16,8,5,0,76,9.0,2,0,Semi-Urban,HR Executive,54378,0 +96192,Female,38,Bachelors,13,62,61,72,98,8.0,4,0,Semi-Urban,Software Engineer,51116,0 +96193,Female,31,Bachelors,5,56,12,24,93,6.0,5,97,Urban,Software Engineer,110248,0 +96194,Male,33,Bachelors,10,97,57,66,10,5.0,5,81,Urban,Data Analyst,27571,1 +96195,Female,31,Bachelors,7,62,41,94,82,3.0,2,33,Urban,Software Engineer,38792,0 +96196,Male,54,Diploma,10,35,70,80,91,9.0,7,38,Rural,HR Executive,138555,0 +96197,Male,32,Bachelors,15,14,45,39,64,1.0,5,33,Urban,Software Engineer,115445,0 +96198,Male,28,Diploma,15,51,95,37,40,2.0,0,0,Urban,Software Engineer,102870,0 +96199,Male,24,Masters,8,63,75,22,73,9.0,4,53,Rural,Software Engineer,82110,0 +96200,Female,34,Masters,2,28,12,8,56,5.0,2,46,Urban,ML Engineer,133595,0 +96201,Male,58,Masters,8,75,15,70,72,3.0,4,38,Urban,Software Engineer,133510,0 +96202,Male,44,High School,17,40,55,93,59,8.0,1,81,Semi-Urban,HR Executive,119777,1 +96203,Female,42,Bachelors,10,85,3,14,23,6.0,3,20,Urban,Manager,74782,0 +96204,Male,50,Diploma,1,46,68,3,70,9.0,1,49,Rural,ML Engineer,115322,0 +96205,Male,31,Diploma,8,65,81,8,55,0.0,7,81,Rural,HR Executive,134772,1 +96206,Male,39,Bachelors,3,18,73,30,81,3.0,2,40,Rural,ML Engineer,144693,0 +96207,Male,30,Bachelors,18,23,15,64,51,3.0,7,97,Urban,Manager,27624,0 +96208,Male,41,PhD,19,45,26,0,81,0.0,4,46,Urban,HR Executive,112108,0 +96209,Male,26,Bachelors,4,78,65,90,6,0.0,7,87,Urban,Software Engineer,38778,1 +96210,Female,30,Bachelors,19,0,35,11,61,5.0,7,45,Urban,Software Engineer,82100,0 +96211,Male,31,Masters,7,11,85,69,39,1.0,4,71,Semi-Urban,Manager,75213,1 +96212,Female,54,Diploma,7,70,82,38,60,0.0,5,27,Rural,Data Analyst,61805,0 +96213,Female,25,High School,1,26,32,9,60,1.0,7,27,Urban,Data Analyst,109598,0 +96214,Male,47,Bachelors,16,2,18,63,49,7.0,5,28,Urban,Software Engineer,26115,0 +96215,Male,53,Bachelors,3,49,75,69,97,0.0,6,59,Urban,Software Engineer,40097,1 +96216,Male,56,Masters,7,67,94,15,92,6.0,1,86,Semi-Urban,Data Analyst,146466,1 +96217,Male,38,Bachelors,7,78,59,8,29,4.0,6,91,Urban,Software Engineer,94612,1 +96218,Other,49,Masters,19,67,40,13,99,9.0,6,52,Urban,Data Analyst,26137,0 +96219,Male,44,Diploma,11,58,87,37,83,4.0,4,92,Urban,HR Executive,48020,1 +96220,Male,59,Bachelors,5,94,48,6,59,4.0,1,28,Urban,HR Executive,124534,0 +96221,Female,25,Masters,17,36,24,32,75,9.0,6,73,Semi-Urban,HR Executive,91599,0 +96222,Female,42,Bachelors,7,69,90,6,48,3.0,1,74,Urban,HR Executive,81709,0 +96223,Female,43,High School,3,56,66,20,93,7.0,7,99,Rural,ML Engineer,111830,1 +96224,Male,44,Masters,5,42,27,66,52,1.0,4,10,Urban,Data Analyst,136744,0 +96225,Female,30,Bachelors,16,27,89,33,91,4.0,3,31,Urban,HR Executive,97878,0 +96226,Male,59,Masters,12,83,29,7,62,7.0,5,47,Urban,Software Engineer,141110,0 +96227,Female,21,High School,14,86,94,77,94,4.0,5,46,Urban,Software Engineer,41258,1 +96228,Female,39,Bachelors,5,20,1,19,49,1.0,5,84,Semi-Urban,ML Engineer,140565,0 +96229,Male,36,Diploma,10,17,60,34,88,9.0,0,15,Rural,HR Executive,86828,0 +96230,Male,21,PhD,13,7,55,91,29,4.0,2,19,Semi-Urban,Data Analyst,31234,0 +96231,Female,53,Diploma,0,12,97,42,48,1.0,5,33,Urban,ML Engineer,48072,0 +96232,Female,36,Bachelors,19,46,69,89,5,7.0,7,12,Urban,ML Engineer,38077,0 +96233,Male,43,PhD,0,42,59,45,69,8.0,2,64,Semi-Urban,HR Executive,71073,0 +96234,Male,32,Bachelors,8,68,12,68,29,9.0,6,9,Urban,HR Executive,29604,0 +96235,Female,32,Bachelors,1,0,87,41,37,4.0,0,39,Urban,HR Executive,123188,0 +96236,Female,46,Diploma,2,78,94,61,35,1.0,2,71,Urban,Software Engineer,144497,1 +96237,Male,26,Bachelors,19,51,52,17,79,7.0,7,4,Urban,Software Engineer,126585,0 +96238,Male,51,Bachelors,3,99,16,51,20,0.0,4,4,Urban,Software Engineer,45405,0 +96239,Male,58,Diploma,16,72,5,60,53,2.0,4,59,Urban,HR Executive,94044,0 +96240,Female,48,PhD,11,25,62,24,45,6.0,0,18,Semi-Urban,Software Engineer,31663,0 +96241,Female,32,Diploma,10,44,80,59,83,2.0,3,69,Semi-Urban,Data Analyst,53466,1 +96242,Female,38,High School,9,82,22,74,9,3.0,2,31,Rural,Data Analyst,23920,0 +96243,Male,57,Diploma,14,55,82,83,84,1.0,1,28,Rural,Software Engineer,119538,1 +96244,Male,50,Bachelors,2,88,76,63,54,5.0,5,91,Semi-Urban,Data Analyst,58256,1 +96245,Male,30,Masters,11,69,12,8,47,9.0,4,88,Rural,Manager,65484,0 +96246,Female,30,Diploma,6,77,42,84,94,1.0,5,41,Rural,Manager,21547,1 +96247,Female,46,Bachelors,13,61,20,9,78,0.0,6,30,Semi-Urban,Software Engineer,69552,0 +96248,Male,27,Masters,2,71,83,54,24,8.0,5,69,Semi-Urban,ML Engineer,98370,1 +96249,Male,22,Bachelors,3,70,40,61,15,8.0,2,53,Urban,ML Engineer,71829,0 +96250,Female,40,Masters,19,38,66,2,24,1.0,2,81,Urban,Data Analyst,132895,0 +96251,Male,41,Bachelors,15,2,36,9,99,1.0,0,30,Rural,Data Analyst,116483,0 +96252,Male,48,Diploma,10,48,45,83,39,9.0,1,77,Urban,ML Engineer,148137,1 +96253,Male,26,Bachelors,19,78,39,87,84,5.0,5,51,Urban,HR Executive,133288,1 +96254,Female,24,High School,1,24,88,79,91,3.0,0,53,Semi-Urban,ML Engineer,136699,1 +96255,Female,31,High School,3,92,87,72,1,8.0,6,91,Urban,Manager,24618,1 +96256,Male,57,Bachelors,1,66,33,20,52,5.0,0,79,Semi-Urban,Software Engineer,28349,0 +96257,Male,29,Bachelors,7,25,55,26,73,2.0,6,25,Rural,Software Engineer,64494,0 +96258,Female,25,Bachelors,19,15,43,77,48,3.0,6,10,Urban,HR Executive,40784,0 +96259,Male,41,Masters,12,9,53,7,22,4.0,2,8,Urban,ML Engineer,39675,0 +96260,Female,35,Diploma,10,59,45,87,9,1.0,2,5,Semi-Urban,Manager,95056,0 +96261,Female,34,Diploma,8,26,86,61,23,9.0,4,34,Urban,HR Executive,63418,0 +96262,Male,37,Diploma,11,19,95,82,31,8.0,5,78,Urban,Manager,129880,1 +96263,Female,35,High School,0,19,82,43,24,7.0,5,20,Urban,Software Engineer,78360,0 +96264,Male,52,Diploma,1,18,9,39,58,3.0,2,80,Urban,Manager,57366,0 +96265,Male,24,Bachelors,9,84,93,27,82,3.0,7,23,Urban,HR Executive,20437,0 +96266,Male,53,Masters,16,87,2,51,49,4.0,0,0,Rural,ML Engineer,83253,0 +96267,Male,29,Bachelors,0,84,10,31,1,4.0,5,61,Urban,HR Executive,34458,0 +96268,Female,21,Bachelors,19,58,59,36,81,9.0,1,60,Semi-Urban,Software Engineer,53458,0 +96269,Female,54,High School,16,23,93,46,57,2.0,7,56,Rural,ML Engineer,90280,0 +96270,Female,35,Masters,19,49,88,75,86,5.0,4,83,Rural,ML Engineer,96191,1 +96271,Female,33,High School,12,56,2,97,71,8.0,4,12,Urban,Manager,74609,0 +96272,Male,57,Diploma,14,62,44,12,95,2.0,4,73,Urban,Manager,26143,0 +96273,Female,43,Bachelors,12,96,94,8,12,1.0,1,21,Semi-Urban,HR Executive,49274,0 +96274,Male,52,Diploma,9,25,29,32,92,5.0,6,13,Semi-Urban,Software Engineer,128833,0 +96275,Female,34,High School,7,64,32,26,38,7.0,6,4,Urban,Software Engineer,109202,0 +96276,Male,27,Bachelors,1,17,1,88,18,9.0,0,62,Semi-Urban,Software Engineer,126252,0 +96277,Female,44,High School,4,68,63,57,73,1.0,6,44,Semi-Urban,Data Analyst,62193,0 +96278,Male,59,Diploma,13,40,15,67,80,5.0,4,78,Semi-Urban,Software Engineer,116659,0 +96279,Male,43,Diploma,10,26,21,90,39,1.0,7,69,Semi-Urban,Software Engineer,85239,0 +96280,Female,58,PhD,5,85,65,25,56,1.0,2,67,Urban,ML Engineer,30221,1 +96281,Male,55,Masters,0,99,23,71,26,9.0,3,9,Semi-Urban,HR Executive,59529,0 +96282,Male,34,Diploma,17,55,89,23,36,4.0,7,83,Semi-Urban,Manager,135194,1 +96283,Female,26,Bachelors,8,42,81,84,56,2.0,7,78,Urban,Manager,108106,1 +96284,Male,28,Bachelors,16,45,21,37,70,4.0,4,12,Urban,Manager,117064,0 +96285,Male,37,Bachelors,8,93,21,92,7,6.0,6,26,Urban,Software Engineer,143424,0 +96286,Male,27,PhD,15,64,20,81,22,2.0,6,18,Semi-Urban,ML Engineer,63752,0 +96287,Female,39,Diploma,13,71,10,33,39,6.0,0,43,Rural,HR Executive,56114,0 +96288,Other,43,High School,5,85,13,53,86,5.0,1,86,Semi-Urban,ML Engineer,136728,0 +96289,Male,50,Masters,16,55,59,53,18,2.0,0,20,Urban,Software Engineer,98579,0 +96290,Female,25,Bachelors,4,7,92,46,31,2.0,5,99,Semi-Urban,Data Analyst,129983,1 +96291,Male,54,Bachelors,10,78,49,89,92,6.0,6,55,Urban,Manager,100017,1 +96292,Female,32,Bachelors,18,6,38,41,3,3.0,4,66,Urban,ML Engineer,82402,0 +96293,Female,44,Masters,10,85,42,92,54,5.0,6,97,Urban,HR Executive,57918,1 +96294,Male,28,Bachelors,14,35,0,18,19,2.0,2,80,Rural,HR Executive,109209,0 +96295,Female,54,Diploma,9,89,17,5,79,8.0,2,14,Urban,HR Executive,99369,0 +96296,Female,49,Masters,3,73,16,17,94,7.0,1,62,Urban,Manager,96091,0 +96297,Male,40,Diploma,11,50,5,43,20,6.0,4,85,Semi-Urban,Manager,136643,0 +96298,Male,48,Bachelors,10,62,75,41,22,2.0,4,15,Urban,Software Engineer,118753,0 +96299,Female,48,Bachelors,12,98,95,28,62,3.0,0,79,Urban,HR Executive,109576,1 +96300,Male,50,Diploma,12,39,68,63,30,9.0,7,58,Urban,Manager,121291,0 +96301,Male,30,Bachelors,16,62,40,32,94,3.0,4,28,Urban,Software Engineer,61431,0 +96302,Female,54,Diploma,12,67,17,77,6,0.0,0,13,Semi-Urban,Software Engineer,82225,0 +96303,Female,32,Diploma,3,72,53,18,77,8.0,7,43,Urban,Software Engineer,141198,0 +96304,Male,34,High School,19,6,66,99,48,5.0,4,12,Semi-Urban,Manager,50562,0 +96305,Female,33,Bachelors,5,53,51,1,69,0.0,6,75,Semi-Urban,Manager,132145,0 +96306,Female,29,PhD,19,19,61,54,0,3.0,5,6,Urban,Data Analyst,114948,0 +96307,Male,47,Masters,11,96,77,99,49,4.0,6,64,Urban,Manager,35726,1 +96308,Male,46,Bachelors,7,31,68,87,6,4.0,2,61,Urban,Data Analyst,21562,1 +96309,Female,58,Diploma,18,61,40,81,24,4.0,1,0,Urban,Software Engineer,132633,0 +96310,Male,35,Bachelors,14,18,43,94,79,0.0,7,33,Urban,HR Executive,55738,0 +96311,Female,26,Bachelors,18,41,32,99,83,8.0,3,48,Urban,ML Engineer,130460,0 +96312,Male,50,Bachelors,19,86,13,23,94,7.0,1,69,Rural,Software Engineer,112325,0 +96313,Male,28,Masters,6,48,2,71,22,9.0,0,95,Rural,ML Engineer,98660,0 +96314,Male,50,Bachelors,15,75,20,83,75,0.0,5,72,Urban,Manager,134584,1 +96315,Male,29,Masters,10,88,90,14,69,1.0,0,70,Semi-Urban,Manager,73095,1 +96316,Male,31,Bachelors,14,63,48,23,12,6.0,2,41,Urban,ML Engineer,57532,0 +96317,Female,52,Bachelors,18,49,26,0,78,8.0,7,72,Semi-Urban,Data Analyst,131599,0 +96318,Male,33,Bachelors,13,11,91,21,86,0.0,6,65,Semi-Urban,HR Executive,117507,0 +96319,Male,24,High School,15,83,21,24,72,6.0,1,95,Semi-Urban,ML Engineer,63008,0 +96320,Female,48,Bachelors,11,51,55,8,53,8.0,6,81,Semi-Urban,Data Analyst,79044,0 +96321,Female,36,Bachelors,16,7,88,40,35,9.0,4,24,Rural,ML Engineer,31517,0 +96322,Female,27,Bachelors,5,11,37,46,93,2.0,5,48,Urban,Manager,120687,0 +96323,Male,21,Masters,11,41,59,8,85,6.0,4,40,Semi-Urban,ML Engineer,140114,0 +96324,Male,52,Bachelors,16,69,87,8,90,1.0,2,21,Semi-Urban,ML Engineer,41708,0 +96325,Male,49,High School,11,86,34,3,32,5.0,5,0,Rural,ML Engineer,85817,0 +96326,Female,49,Diploma,18,1,35,70,16,7.0,3,20,Semi-Urban,ML Engineer,83627,0 +96327,Male,35,Bachelors,0,52,73,63,23,7.0,3,50,Semi-Urban,HR Executive,113980,1 +96328,Male,50,High School,6,97,62,59,14,3.0,3,42,Semi-Urban,Data Analyst,64075,1 +96329,Male,29,High School,18,32,20,83,2,4.0,5,98,Urban,Software Engineer,37156,0 +96330,Male,54,Bachelors,1,12,62,18,18,9.0,0,70,Urban,HR Executive,90965,0 +96331,Female,59,Masters,19,91,32,52,70,7.0,4,72,Urban,HR Executive,120849,1 +96332,Male,47,PhD,16,5,28,38,61,5.0,2,68,Rural,ML Engineer,102988,0 +96333,Male,59,Bachelors,4,94,77,92,62,9.0,1,42,Semi-Urban,HR Executive,110497,1 +96334,Female,22,Masters,1,1,94,57,47,9.0,2,5,Urban,ML Engineer,80919,0 +96335,Male,46,Diploma,16,21,92,98,88,3.0,0,94,Urban,ML Engineer,23354,1 +96336,Male,32,High School,2,23,42,3,6,4.0,2,58,Semi-Urban,Manager,100791,0 +96337,Male,49,Bachelors,8,88,10,78,17,9.0,6,84,Rural,HR Executive,104323,1 +96338,Other,25,Bachelors,7,74,7,34,77,3.0,7,45,Rural,ML Engineer,26536,0 +96339,Female,27,Bachelors,0,28,22,48,44,0.0,1,47,Rural,HR Executive,36959,0 +96340,Male,53,Bachelors,13,42,96,78,86,6.0,6,96,Urban,HR Executive,114186,1 +96341,Female,30,Bachelors,14,88,13,26,47,7.0,2,76,Urban,ML Engineer,93903,0 +96342,Male,51,PhD,3,78,27,16,72,1.0,7,97,Urban,Manager,43656,0 +96343,Male,59,Masters,13,46,79,75,74,6.0,6,32,Urban,Software Engineer,27326,0 +96344,Male,25,Bachelors,10,6,93,5,60,9.0,6,38,Semi-Urban,Data Analyst,97095,0 +96345,Male,36,Diploma,0,43,72,69,10,8.0,7,25,Semi-Urban,Data Analyst,90292,0 +96346,Female,32,Diploma,18,16,69,37,25,5.0,7,83,Urban,Software Engineer,131655,0 +96347,Female,26,Bachelors,7,86,49,64,32,9.0,5,10,Urban,ML Engineer,32518,0 +96348,Male,48,Masters,18,31,70,17,65,5.0,1,66,Urban,Manager,22234,0 +96349,Female,35,Bachelors,0,81,51,20,18,5.0,2,48,Semi-Urban,Data Analyst,87248,0 +96350,Female,34,Diploma,14,70,71,73,91,0.0,0,85,Rural,ML Engineer,144090,1 +96351,Female,26,Diploma,1,31,68,39,0,0.0,6,63,Semi-Urban,ML Engineer,110733,0 +96352,Female,47,Bachelors,13,88,16,74,13,0.0,0,9,Urban,Software Engineer,103133,0 +96353,Female,58,Bachelors,5,34,41,22,30,9.0,6,70,Semi-Urban,Data Analyst,35441,0 +96354,Male,36,Bachelors,10,88,26,99,25,2.0,6,67,Urban,Manager,115294,1 +96355,Female,55,Masters,9,81,77,25,9,6.0,1,74,Urban,Software Engineer,80331,1 +96356,Female,51,Diploma,11,93,77,80,30,9.0,4,49,Urban,Software Engineer,123959,1 +96357,Female,36,High School,16,51,17,74,16,0.0,3,42,Urban,HR Executive,118605,0 +96358,Female,41,Bachelors,10,90,96,52,56,8.0,3,59,Urban,HR Executive,143498,1 +96359,Female,33,Diploma,19,23,75,31,9,9.0,2,57,Rural,ML Engineer,54409,0 +96360,Male,55,Bachelors,15,43,22,28,83,4.0,4,10,Urban,Software Engineer,33646,0 +96361,Male,52,PhD,3,42,5,73,77,3.0,5,89,Urban,Manager,88150,0 +96362,Male,52,Diploma,18,71,5,68,30,1.0,7,61,Urban,ML Engineer,76742,0 +96363,Male,42,High School,19,54,63,33,55,8.0,5,11,Urban,Software Engineer,145355,0 +96364,Male,37,High School,0,46,40,8,54,9.0,6,92,Semi-Urban,HR Executive,51231,0 +96365,Female,57,Masters,6,49,43,87,11,5.0,7,96,Semi-Urban,Software Engineer,21935,1 +96366,Other,37,Bachelors,17,84,47,85,23,2.0,1,9,Urban,Data Analyst,31841,0 +96367,Female,56,Bachelors,6,91,53,34,14,4.0,6,49,Urban,Data Analyst,106069,0 +96368,Male,30,Bachelors,0,17,72,22,16,0.0,3,75,Urban,ML Engineer,139509,0 +96369,Male,48,Diploma,17,82,31,60,87,1.0,1,21,Rural,Manager,54948,0 +96370,Female,36,Diploma,9,92,46,25,11,1.0,1,70,Rural,Manager,74905,0 +96371,Female,30,Bachelors,2,53,68,7,85,5.0,4,93,Rural,Software Engineer,96552,0 +96372,Male,39,Diploma,3,37,73,26,70,9.0,7,44,Semi-Urban,HR Executive,24879,0 +96373,Male,41,Bachelors,6,12,42,86,88,5.0,2,61,Urban,HR Executive,60460,0 +96374,Female,39,Masters,6,18,81,29,14,3.0,0,52,Rural,HR Executive,66036,0 +96375,Female,33,PhD,8,90,88,86,94,0.0,1,53,Semi-Urban,HR Executive,56724,1 +96376,Female,59,Bachelors,17,53,20,66,81,4.0,0,37,Urban,ML Engineer,63590,0 +96377,Male,33,Masters,18,19,69,26,97,1.0,6,62,Urban,Data Analyst,89862,0 +96378,Female,33,Bachelors,16,86,63,0,72,1.0,0,59,Urban,Manager,57591,0 +96379,Female,26,PhD,14,81,88,52,2,2.0,0,30,Rural,Data Analyst,43464,1 +96380,Male,36,Bachelors,18,37,29,14,31,1.0,2,78,Rural,Software Engineer,112617,0 +96381,Male,26,Bachelors,1,82,4,79,31,6.0,7,90,Urban,ML Engineer,132600,1 +96382,Male,21,Diploma,18,47,16,66,3,3.0,6,74,Rural,Software Engineer,104882,0 +96383,Male,27,Bachelors,10,79,73,66,18,1.0,4,10,Urban,Manager,140831,0 +96384,Female,37,Bachelors,9,17,51,46,7,1.0,6,73,Semi-Urban,Manager,108973,0 +96385,Female,45,Bachelors,6,60,84,12,54,5.0,7,8,Rural,Data Analyst,92419,0 +96386,Male,27,High School,10,32,15,46,47,1.0,2,6,Urban,Software Engineer,125198,0 +96387,Female,44,PhD,13,88,10,76,93,2.0,7,28,Urban,Manager,127185,0 +96388,Male,44,Bachelors,4,89,75,8,29,4.0,5,21,Urban,Data Analyst,21243,0 +96389,Male,30,Diploma,1,93,36,37,52,7.0,2,25,Semi-Urban,Data Analyst,45518,0 +96390,Male,52,Bachelors,17,16,83,89,17,7.0,0,99,Semi-Urban,Software Engineer,39664,1 +96391,Male,24,Bachelors,6,12,49,81,85,4.0,6,65,Urban,HR Executive,130487,0 +96392,Male,46,Bachelors,11,95,42,22,53,4.0,7,70,Rural,HR Executive,54304,0 +96393,Female,23,Masters,19,71,58,6,71,9.0,0,45,Urban,Software Engineer,85175,0 +96394,Male,38,High School,13,94,99,71,50,4.0,6,77,Urban,ML Engineer,65393,1 +96395,Male,25,Diploma,16,92,68,11,39,8.0,0,46,Urban,HR Executive,69755,0 +96396,Female,29,High School,3,27,71,67,75,0.0,0,14,Semi-Urban,Data Analyst,87251,0 +96397,Female,52,Diploma,9,15,10,12,97,5.0,7,78,Urban,ML Engineer,147540,0 +96398,Male,30,Bachelors,10,39,48,34,34,4.0,2,96,Urban,HR Executive,136331,0 +96399,Female,59,Masters,10,13,56,62,44,6.0,4,45,Semi-Urban,HR Executive,75811,0 +96400,Other,55,Bachelors,14,24,72,69,31,3.0,3,40,Semi-Urban,Software Engineer,30511,0 +96401,Female,35,High School,16,83,87,73,1,9.0,7,84,Urban,HR Executive,100428,1 +96402,Male,50,Masters,12,43,44,67,49,7.0,1,41,Urban,HR Executive,77922,0 +96403,Female,55,Masters,14,18,67,23,64,9.0,1,94,Urban,ML Engineer,149570,0 +96404,Female,28,Bachelors,6,82,13,17,10,4.0,7,79,Urban,Data Analyst,85939,0 +96405,Female,31,Bachelors,11,4,19,65,65,0.0,6,52,Semi-Urban,Data Analyst,108503,0 +96406,Male,51,Diploma,18,90,27,23,44,9.0,3,53,Rural,ML Engineer,72761,0 +96407,Female,50,Bachelors,17,0,18,4,59,2.0,3,12,Rural,Data Analyst,57180,0 +96408,Male,38,Bachelors,2,67,52,97,82,0.0,3,53,Semi-Urban,Software Engineer,24883,1 +96409,Male,51,PhD,11,15,89,0,33,4.0,5,98,Urban,HR Executive,99268,0 +96410,Male,34,Bachelors,11,33,27,31,95,3.0,5,3,Rural,HR Executive,88157,0 +96411,Female,38,Bachelors,11,22,79,29,72,5.0,3,13,Urban,HR Executive,63613,0 +96412,Female,57,Diploma,6,40,63,94,8,7.0,0,8,Rural,HR Executive,128394,0 +96413,Female,21,Masters,2,42,24,60,94,4.0,2,33,Rural,Data Analyst,43325,0 +96414,Male,52,High School,18,45,54,3,77,3.0,3,80,Urban,Software Engineer,101931,0 +96415,Female,23,Bachelors,14,45,58,73,56,7.0,5,35,Urban,Manager,27262,0 +96416,Female,26,Diploma,16,35,17,48,34,6.0,0,79,Urban,Software Engineer,84103,0 +96417,Female,26,Diploma,16,74,74,86,74,0.0,7,49,Urban,Data Analyst,135893,1 +96418,Female,44,High School,17,79,6,89,12,2.0,6,33,Urban,ML Engineer,112639,0 +96419,Male,47,Masters,4,61,8,91,98,8.0,5,8,Urban,Data Analyst,145007,0 +96420,Female,39,Bachelors,8,33,68,13,17,9.0,5,6,Rural,Software Engineer,124479,0 +96421,Other,49,Diploma,13,12,3,56,82,2.0,4,15,Urban,Manager,84963,0 +96422,Male,25,High School,6,24,83,45,13,7.0,7,66,Urban,Software Engineer,96511,0 +96423,Female,25,Bachelors,5,20,81,50,12,2.0,2,77,Urban,HR Executive,93835,0 +96424,Male,23,Bachelors,17,67,59,60,43,5.0,3,89,Rural,HR Executive,84711,1 +96425,Male,26,Diploma,19,52,10,11,55,5.0,5,9,Urban,HR Executive,25295,0 +96426,Female,52,Bachelors,9,89,84,78,5,5.0,0,2,Urban,Data Analyst,90824,1 +96427,Other,51,Diploma,14,80,26,25,74,1.0,1,15,Semi-Urban,Manager,108869,0 +96428,Male,45,Bachelors,17,84,64,40,23,4.0,7,84,Urban,Software Engineer,110152,1 +96429,Female,56,High School,3,9,99,28,86,3.0,1,49,Rural,Software Engineer,61713,0 +96430,Female,52,Diploma,15,94,65,68,35,1.0,3,51,Urban,Manager,63760,1 +96431,Female,57,Masters,17,77,15,89,48,0.0,1,0,Urban,HR Executive,92319,0 +96432,Male,51,Masters,12,24,26,8,87,5.0,2,94,Urban,Software Engineer,27437,0 +96433,Male,40,High School,11,45,78,5,33,4.0,7,76,Urban,HR Executive,28991,0 +96434,Male,45,Bachelors,2,99,60,66,98,0.0,0,82,Urban,ML Engineer,82720,1 +96435,Male,54,Masters,9,27,45,34,34,0.0,6,59,Urban,Software Engineer,24885,0 +96436,Female,38,Masters,1,91,62,14,44,9.0,7,17,Rural,Software Engineer,93621,0 +96437,Female,39,PhD,0,71,95,40,70,6.0,4,97,Urban,HR Executive,45380,1 +96438,Male,48,High School,19,45,38,61,20,2.0,6,6,Urban,Software Engineer,35978,0 +96439,Female,47,Bachelors,11,95,23,58,95,4.0,2,16,Rural,Manager,31880,0 +96440,Female,38,Masters,18,27,77,44,98,2.0,3,91,Urban,ML Engineer,49602,0 +96441,Female,29,High School,3,26,81,29,8,9.0,0,74,Rural,ML Engineer,99067,0 +96442,Male,23,PhD,1,47,92,82,94,7.0,0,51,Urban,Data Analyst,119115,1 +96443,Female,49,Diploma,7,63,62,43,26,4.0,4,53,Urban,Manager,61567,0 +96444,Male,36,Bachelors,5,77,54,49,53,1.0,1,62,Urban,Software Engineer,78625,1 +96445,Male,51,Bachelors,1,28,16,8,20,4.0,7,95,Urban,Manager,22992,0 +96446,Female,59,Diploma,5,6,2,22,70,8.0,6,5,Semi-Urban,Manager,65231,0 +96447,Female,34,Bachelors,16,86,24,18,57,6.0,7,26,Rural,HR Executive,83743,0 +96448,Male,42,Diploma,3,4,58,71,87,8.0,4,92,Rural,ML Engineer,26923,0 +96449,Male,31,Diploma,16,78,69,99,17,8.0,4,60,Urban,Data Analyst,72861,1 +96450,Female,38,Masters,0,1,51,90,94,2.0,5,5,Rural,ML Engineer,141015,0 +96451,Male,33,PhD,3,83,53,42,53,8.0,5,43,Urban,HR Executive,41741,0 +96452,Female,48,Masters,13,39,83,58,97,6.0,3,49,Semi-Urban,Software Engineer,149553,0 +96453,Male,46,Diploma,9,64,71,86,86,6.0,0,75,Rural,Manager,25025,1 +96454,Male,27,Bachelors,16,58,80,8,90,6.0,0,12,Urban,Software Engineer,33268,0 +96455,Female,41,Bachelors,11,83,69,15,59,4.0,5,21,Rural,ML Engineer,23867,0 +96456,Male,50,PhD,3,63,50,26,13,8.0,7,53,Semi-Urban,Software Engineer,67027,0 +96457,Male,24,Bachelors,16,20,77,74,71,2.0,7,43,Semi-Urban,Software Engineer,109843,0 +96458,Male,37,Diploma,13,22,90,35,93,3.0,4,70,Rural,HR Executive,132790,0 +96459,Female,55,Bachelors,0,90,75,31,61,4.0,2,40,Urban,Data Analyst,41458,0 +96460,Male,22,PhD,6,97,8,30,74,3.0,1,60,Semi-Urban,Software Engineer,117665,0 +96461,Male,30,Bachelors,7,8,91,24,85,6.0,6,88,Semi-Urban,ML Engineer,61562,0 +96462,Male,40,Diploma,8,35,72,24,56,4.0,3,37,Rural,Manager,112582,0 +96463,Male,36,Diploma,17,25,40,19,37,4.0,4,22,Urban,Data Analyst,107090,0 +96464,Male,49,Bachelors,12,56,11,91,85,6.0,2,17,Semi-Urban,Manager,61979,0 +96465,Female,32,Diploma,10,38,46,83,30,6.0,2,3,Urban,HR Executive,141098,0 +96466,Male,57,Diploma,11,66,54,14,1,8.0,3,43,Urban,ML Engineer,83912,0 +96467,Female,34,Bachelors,7,39,81,66,44,4.0,7,65,Urban,Software Engineer,65295,1 +96468,Male,34,Bachelors,9,66,1,27,86,0.0,7,30,Semi-Urban,HR Executive,66029,0 +96469,Female,21,Bachelors,4,38,99,93,71,9.0,5,21,Rural,Manager,77023,1 +96470,Male,59,Diploma,1,70,63,84,31,3.0,5,62,Rural,HR Executive,147182,1 +96471,Male,45,PhD,6,9,99,84,77,1.0,4,3,Urban,ML Engineer,99820,0 +96472,Male,51,Diploma,7,29,57,84,45,6.0,0,60,Urban,HR Executive,122048,0 +96473,Male,50,Masters,8,64,93,89,8,0.0,6,0,Urban,Manager,115091,1 +96474,Male,26,Bachelors,13,76,92,80,78,9.0,6,32,Semi-Urban,Manager,86460,1 +96475,Male,24,Diploma,7,71,38,25,31,8.0,2,69,Semi-Urban,Manager,85758,0 +96476,Male,32,Bachelors,8,99,6,83,70,5.0,2,93,Semi-Urban,Data Analyst,60672,1 +96477,Male,25,High School,17,26,41,71,60,3.0,4,39,Semi-Urban,Software Engineer,147820,0 +96478,Male,54,PhD,0,83,95,98,91,0.0,2,10,Semi-Urban,Data Analyst,20914,1 +96479,Male,41,High School,0,79,98,75,4,9.0,3,82,Urban,Manager,112163,1 +96480,Female,57,Bachelors,19,86,40,92,84,3.0,6,62,Urban,Data Analyst,67339,1 +96481,Female,41,Masters,8,87,71,51,3,3.0,6,83,Semi-Urban,ML Engineer,40841,1 +96482,Male,51,Bachelors,10,94,89,31,8,3.0,1,56,Rural,HR Executive,102954,1 +96483,Male,40,Bachelors,4,84,2,90,90,3.0,3,62,Urban,Manager,108178,1 +96484,Male,51,Masters,4,48,96,25,79,0.0,3,94,Semi-Urban,HR Executive,147022,1 +96485,Other,43,Bachelors,1,29,79,36,82,7.0,5,39,Urban,Manager,50593,0 +96486,Male,58,High School,12,64,40,35,25,5.0,7,81,Urban,HR Executive,68608,0 +96487,Female,36,Bachelors,2,51,34,34,33,7.0,0,86,Urban,HR Executive,25776,0 +96488,Female,33,High School,2,39,34,64,18,0.0,3,69,Semi-Urban,Manager,73817,0 +96489,Female,22,Masters,2,38,30,92,23,3.0,4,78,Urban,HR Executive,105754,0 +96490,Male,32,Diploma,6,62,25,76,90,2.0,2,5,Urban,HR Executive,36641,0 +96491,Female,43,Bachelors,4,32,52,8,2,7.0,1,57,Semi-Urban,Data Analyst,89104,0 +96492,Male,39,Masters,8,44,21,62,1,2.0,5,25,Urban,Data Analyst,81782,0 +96493,Other,24,High School,7,92,34,68,32,3.0,1,3,Urban,Manager,137121,0 +96494,Male,42,Bachelors,13,23,21,20,9,1.0,4,33,Urban,ML Engineer,105895,0 +96495,Female,41,Diploma,2,84,23,15,96,6.0,4,84,Urban,Data Analyst,148795,0 +96496,Female,52,Bachelors,12,65,38,2,23,6.0,4,77,Rural,Data Analyst,105638,0 +96497,Male,31,High School,6,67,37,94,10,5.0,1,31,Urban,Software Engineer,97308,0 +96498,Male,56,Bachelors,11,15,33,66,88,3.0,4,86,Rural,Data Analyst,80444,0 +96499,Male,57,Diploma,17,32,38,90,34,1.0,3,79,Semi-Urban,Software Engineer,44279,1 +96500,Male,32,Bachelors,3,2,67,12,58,2.0,7,40,Urban,HR Executive,96014,0 +96501,Male,52,PhD,8,8,31,41,49,7.0,6,72,Semi-Urban,Manager,142145,0 +96502,Female,28,Masters,15,12,74,2,16,8.0,5,79,Rural,HR Executive,55596,0 +96503,Male,29,High School,10,70,72,99,50,5.0,1,45,Rural,Software Engineer,27715,1 +96504,Female,39,Bachelors,3,33,80,95,49,7.0,2,25,Semi-Urban,Data Analyst,60448,0 +96505,Male,50,PhD,18,37,3,31,97,8.0,6,93,Rural,Data Analyst,109541,0 +96506,Male,35,Bachelors,12,40,79,83,79,6.0,5,15,Urban,Manager,101543,0 +96507,Male,29,Diploma,14,32,82,3,93,9.0,6,61,Rural,Data Analyst,32390,0 +96508,Female,56,High School,6,78,66,63,32,9.0,5,60,Urban,Manager,48901,1 +96509,Male,41,PhD,11,74,37,44,42,9.0,4,97,Semi-Urban,Manager,106937,1 +96510,Male,35,Bachelors,7,66,65,25,14,3.0,0,56,Urban,HR Executive,32616,0 +96511,Female,27,High School,16,1,2,74,2,7.0,2,30,Urban,Manager,59355,0 +96512,Male,50,Masters,5,31,50,94,2,5.0,2,5,Semi-Urban,Manager,72967,0 +96513,Female,39,PhD,6,2,95,24,39,8.0,5,42,Urban,Software Engineer,46248,0 +96514,Male,40,PhD,4,96,27,39,17,3.0,0,88,Rural,HR Executive,93613,1 +96515,Female,51,Bachelors,13,32,88,47,54,0.0,2,94,Urban,HR Executive,43293,1 +96516,Other,31,High School,14,84,49,14,43,0.0,1,44,Rural,HR Executive,131056,0 +96517,Other,29,Diploma,11,48,76,98,36,7.0,2,40,Semi-Urban,Software Engineer,108086,1 +96518,Male,55,Diploma,6,72,21,94,15,8.0,7,75,Urban,Data Analyst,122022,1 +96519,Male,35,Bachelors,9,49,37,69,38,5.0,5,44,Rural,HR Executive,135407,0 +96520,Male,29,PhD,13,47,34,81,17,9.0,6,51,Urban,ML Engineer,137795,0 +96521,Male,24,Bachelors,9,79,90,24,1,1.0,2,18,Urban,Software Engineer,142834,0 +96522,Female,39,Masters,13,31,89,24,97,8.0,6,81,Urban,Data Analyst,27944,0 +96523,Other,45,High School,8,89,10,30,95,6.0,1,42,Semi-Urban,ML Engineer,31366,0 +96524,Male,53,PhD,7,57,5,77,21,0.0,3,7,Rural,Data Analyst,63443,0 +96525,Male,43,Diploma,9,63,7,91,75,3.0,5,46,Rural,Data Analyst,109686,0 +96526,Female,42,Diploma,14,82,85,92,86,9.0,2,79,Urban,HR Executive,46042,1 +96527,Male,37,High School,10,85,28,84,19,9.0,7,27,Urban,Manager,122049,0 +96528,Male,55,Diploma,0,97,64,91,31,9.0,1,27,Urban,ML Engineer,124049,1 +96529,Female,38,Diploma,5,41,57,15,18,5.0,4,24,Rural,Data Analyst,46314,0 +96530,Male,30,PhD,1,9,36,89,63,9.0,5,21,Urban,HR Executive,145509,0 +96531,Male,21,High School,16,11,99,60,38,8.0,4,42,Rural,Data Analyst,34668,0 +96532,Male,21,Diploma,14,31,98,46,68,0.0,6,71,Urban,Software Engineer,78992,1 +96533,Male,52,High School,9,91,39,62,30,4.0,1,77,Urban,Software Engineer,94669,1 +96534,Male,53,High School,15,96,63,71,19,1.0,0,89,Urban,HR Executive,102623,1 +96535,Female,21,Diploma,8,67,95,47,46,3.0,5,50,Urban,Data Analyst,42048,1 +96536,Male,35,Bachelors,7,20,58,20,10,4.0,2,77,Urban,Manager,32352,0 +96537,Female,21,High School,14,72,92,57,94,8.0,0,93,Rural,Manager,118951,1 +96538,Male,36,Bachelors,7,76,72,70,94,1.0,5,78,Rural,Software Engineer,107810,1 +96539,Female,23,Bachelors,3,22,35,0,9,5.0,0,48,Semi-Urban,Manager,129654,0 +96540,Female,40,Masters,3,49,59,72,19,1.0,6,36,Rural,Manager,43874,0 +96541,Male,46,Masters,13,44,45,27,46,7.0,1,24,Rural,HR Executive,112338,0 +96542,Female,52,Diploma,16,67,77,28,73,1.0,7,45,Semi-Urban,Software Engineer,26602,0 +96543,Female,39,Masters,15,80,27,63,47,0.0,0,66,Semi-Urban,Software Engineer,30108,0 +96544,Female,46,Diploma,7,38,87,74,70,4.0,1,61,Rural,Data Analyst,144860,1 +96545,Male,27,PhD,15,60,36,15,41,3.0,6,56,Urban,Manager,41896,0 +96546,Other,23,Bachelors,13,85,16,16,70,5.0,7,15,Urban,ML Engineer,56135,0 +96547,Male,49,Masters,6,1,49,28,41,8.0,2,79,Rural,Manager,113482,0 +96548,Male,57,Diploma,1,65,32,97,13,4.0,7,96,Rural,Data Analyst,138279,1 +96549,Female,37,Masters,6,17,12,16,8,7.0,2,40,Rural,Manager,23509,0 +96550,Male,27,Bachelors,0,43,99,62,62,1.0,5,50,Semi-Urban,Manager,105323,1 +96551,Male,55,Bachelors,16,20,9,40,32,3.0,2,15,Urban,ML Engineer,140867,0 +96552,Male,58,Bachelors,15,34,35,49,79,1.0,5,21,Urban,Manager,73048,0 +96553,Female,34,Diploma,10,22,46,7,15,2.0,6,63,Urban,ML Engineer,42429,0 +96554,Female,27,High School,5,46,35,69,35,5.0,5,24,Urban,ML Engineer,128842,0 +96555,Other,32,High School,18,75,76,27,73,6.0,7,13,Urban,Data Analyst,106745,0 +96556,Male,41,Bachelors,18,74,32,14,37,5.0,1,99,Urban,HR Executive,38814,0 +96557,Male,52,Diploma,14,42,83,95,6,5.0,7,51,Rural,HR Executive,69067,1 +96558,Male,28,Bachelors,0,22,74,46,91,5.0,7,71,Urban,ML Engineer,62959,0 +96559,Male,56,Bachelors,5,39,85,19,49,4.0,0,77,Rural,Data Analyst,117118,0 +96560,Female,23,Bachelors,6,9,34,3,41,6.0,5,91,Urban,ML Engineer,84984,0 +96561,Female,47,High School,17,5,3,84,6,0.0,5,53,Urban,Software Engineer,145032,0 +96562,Male,43,Diploma,8,63,81,62,86,3.0,3,56,Semi-Urban,Manager,79439,1 +96563,Male,59,Bachelors,5,18,27,75,32,9.0,2,31,Rural,Manager,80257,0 +96564,Other,31,Bachelors,12,64,83,39,49,5.0,5,85,Urban,Software Engineer,140699,1 +96565,Male,35,Masters,6,97,45,52,84,6.0,7,14,Rural,Manager,23805,0 +96566,Male,48,Diploma,3,80,85,80,1,8.0,5,72,Urban,Data Analyst,113843,1 +96567,Male,21,High School,15,54,73,6,97,6.0,3,31,Semi-Urban,Data Analyst,85893,0 +96568,Female,21,High School,7,45,52,92,56,3.0,7,74,Semi-Urban,Software Engineer,22319,1 +96569,Female,37,High School,11,44,66,92,65,9.0,4,93,Urban,Software Engineer,60166,1 +96570,Male,56,Masters,14,96,96,41,76,8.0,0,97,Urban,Manager,131154,1 +96571,Female,40,Diploma,4,52,63,76,27,7.0,4,99,Rural,Manager,58220,1 +96572,Male,31,Bachelors,9,34,73,45,59,5.0,7,53,Rural,HR Executive,24090,0 +96573,Female,43,Bachelors,12,66,8,68,46,4.0,2,54,Urban,Data Analyst,49412,0 +96574,Other,56,High School,16,6,20,50,4,9.0,7,53,Urban,Software Engineer,104256,0 +96575,Other,32,Bachelors,0,7,97,11,53,2.0,4,17,Urban,HR Executive,92534,0 +96576,Female,53,Bachelors,19,76,16,24,56,5.0,4,39,Urban,Manager,100982,0 +96577,Male,48,Diploma,8,38,62,96,69,8.0,7,20,Urban,Manager,76304,0 +96578,Male,48,Bachelors,11,81,79,60,9,5.0,0,47,Urban,Software Engineer,97541,1 +96579,Male,39,Bachelors,4,59,82,76,46,2.0,5,74,Urban,ML Engineer,21156,1 +96580,Female,47,Bachelors,0,98,22,77,51,5.0,5,12,Urban,Data Analyst,93396,0 +96581,Female,30,Diploma,2,85,4,89,36,0.0,5,71,Urban,HR Executive,112891,1 +96582,Male,46,High School,16,54,59,11,77,2.0,1,61,Urban,Data Analyst,141827,0 +96583,Female,55,Bachelors,14,27,94,52,91,7.0,5,87,Rural,HR Executive,58379,1 +96584,Male,24,Bachelors,4,59,98,31,22,0.0,2,29,Semi-Urban,HR Executive,147529,0 +96585,Female,28,Diploma,8,50,41,60,82,3.0,6,38,Urban,ML Engineer,119999,0 +96586,Male,50,Bachelors,16,9,86,89,65,0.0,0,12,Urban,Data Analyst,101368,0 +96587,Male,55,Bachelors,10,38,45,86,26,8.0,0,79,Urban,Data Analyst,52290,1 +96588,Male,27,High School,14,89,80,74,57,1.0,6,2,Rural,ML Engineer,144372,1 +96589,Female,23,Diploma,4,64,39,9,5,1.0,1,50,Urban,Software Engineer,104964,0 +96590,Other,54,Bachelors,1,91,2,81,20,5.0,7,35,Urban,Software Engineer,87231,0 +96591,Male,51,Diploma,1,42,99,57,66,1.0,1,51,Urban,Software Engineer,36815,1 +96592,Male,38,Bachelors,11,63,50,49,94,3.0,4,92,Urban,Software Engineer,57889,1 +96593,Male,29,Bachelors,10,90,2,42,66,4.0,5,78,Urban,Software Engineer,103551,0 +96594,Male,41,High School,17,28,30,23,81,4.0,6,18,Urban,HR Executive,115034,0 +96595,Female,23,Bachelors,5,96,86,10,53,1.0,6,17,Rural,Manager,44133,0 +96596,Male,57,Bachelors,9,89,67,62,37,1.0,7,33,Urban,Software Engineer,117175,1 +96597,Female,44,High School,12,76,21,73,87,9.0,0,27,Semi-Urban,Software Engineer,59593,0 +96598,Male,34,PhD,9,51,30,41,68,8.0,0,97,Semi-Urban,Software Engineer,142886,0 +96599,Female,31,Bachelors,13,54,19,89,92,2.0,7,83,Urban,Software Engineer,27205,1 +96600,Female,46,Masters,19,0,79,52,1,4.0,4,87,Urban,Manager,117414,0 +96601,Male,40,Bachelors,10,39,25,74,52,5.0,3,80,Urban,Software Engineer,27166,0 +96602,Female,49,Bachelors,3,8,27,43,2,8.0,6,4,Urban,ML Engineer,116141,0 +96603,Female,45,Masters,8,4,50,66,4,1.0,3,22,Urban,Software Engineer,25909,0 +96604,Male,35,Masters,8,42,54,15,98,7.0,2,59,Rural,HR Executive,94333,0 +96605,Other,34,Masters,8,92,90,11,17,1.0,4,9,Semi-Urban,HR Executive,34593,0 +96606,Male,46,Masters,9,49,75,78,98,2.0,5,51,Urban,Manager,54906,1 +96607,Male,22,Masters,8,60,76,9,19,2.0,3,26,Urban,HR Executive,135337,0 +96608,Other,45,Bachelors,9,0,8,6,16,3.0,4,82,Urban,Manager,37607,0 +96609,Female,27,Bachelors,16,47,28,68,70,2.0,5,11,Rural,Software Engineer,115954,0 +96610,Female,25,High School,0,71,63,19,74,5.0,4,37,Rural,Software Engineer,31455,0 +96611,Female,51,High School,16,94,49,31,8,2.0,0,21,Urban,HR Executive,82645,0 +96612,Male,36,Bachelors,9,11,36,53,52,2.0,0,49,Urban,Software Engineer,49593,0 +96613,Male,25,Bachelors,19,76,86,84,64,3.0,7,6,Rural,ML Engineer,42160,1 +96614,Male,45,Masters,10,78,33,4,68,1.0,3,73,Urban,Manager,131128,0 +96615,Female,33,Masters,19,1,29,99,48,1.0,1,62,Urban,Data Analyst,137207,0 +96616,Male,24,Bachelors,8,98,16,11,92,4.0,3,21,Urban,Software Engineer,33311,0 +96617,Male,58,Bachelors,2,16,30,21,19,7.0,1,60,Urban,Data Analyst,50856,0 +96618,Male,47,High School,8,10,23,92,39,4.0,1,20,Semi-Urban,Software Engineer,37174,0 +96619,Female,44,Bachelors,6,44,36,23,46,5.0,3,96,Urban,ML Engineer,121507,0 +96620,Female,24,Diploma,2,81,80,52,87,9.0,5,80,Semi-Urban,HR Executive,61091,1 +96621,Male,45,Bachelors,17,40,85,80,17,5.0,2,26,Urban,Software Engineer,23840,0 +96622,Male,43,Masters,10,84,72,90,12,1.0,1,98,Rural,Manager,98156,1 +96623,Male,59,Bachelors,13,14,6,0,38,7.0,0,21,Urban,ML Engineer,33560,0 +96624,Male,29,High School,5,97,28,36,42,8.0,1,69,Semi-Urban,HR Executive,84100,0 +96625,Female,23,Masters,7,24,34,37,44,4.0,6,24,Urban,Manager,106816,0 +96626,Male,31,Diploma,15,88,93,7,61,3.0,4,13,Semi-Urban,Manager,130291,0 +96627,Male,35,Bachelors,4,23,5,7,51,0.0,3,33,Urban,Data Analyst,130660,0 +96628,Male,34,Masters,15,58,12,37,55,8.0,2,91,Urban,HR Executive,61719,0 +96629,Other,57,Bachelors,14,58,42,63,20,4.0,3,16,Urban,Manager,148548,0 +96630,Male,31,Diploma,4,45,16,28,33,7.0,5,86,Urban,Data Analyst,113818,0 +96631,Male,37,Bachelors,3,73,15,32,97,8.0,4,61,Rural,Software Engineer,137520,0 +96632,Female,57,Diploma,13,45,57,31,40,9.0,6,94,Rural,Manager,76945,0 +96633,Other,42,Masters,16,97,23,8,38,2.0,6,42,Urban,Software Engineer,47904,0 +96634,Male,30,Diploma,15,46,44,85,11,2.0,6,13,Urban,Data Analyst,52522,0 +96635,Male,25,Bachelors,17,73,16,17,33,6.0,5,99,Semi-Urban,Software Engineer,135956,0 +96636,Male,57,Diploma,3,53,22,92,83,9.0,6,21,Urban,Data Analyst,66790,0 +96637,Male,22,Bachelors,8,78,22,59,45,3.0,5,14,Urban,HR Executive,23274,0 +96638,Male,59,High School,9,40,13,81,24,1.0,0,87,Semi-Urban,HR Executive,106241,0 +96639,Male,26,Diploma,4,95,35,94,80,3.0,3,83,Rural,Software Engineer,53857,1 +96640,Male,29,Masters,9,45,65,68,67,1.0,1,83,Urban,HR Executive,94476,1 +96641,Male,22,Bachelors,10,34,63,34,14,4.0,6,61,Urban,Software Engineer,94398,0 +96642,Female,24,High School,7,50,46,88,38,1.0,3,68,Urban,Data Analyst,131355,1 +96643,Male,24,High School,6,51,10,66,42,3.0,5,44,Rural,HR Executive,106692,0 +96644,Female,50,Diploma,2,7,84,57,92,2.0,4,22,Rural,Software Engineer,89961,0 +96645,Female,41,Bachelors,8,59,69,90,90,0.0,5,81,Rural,Manager,45749,1 +96646,Female,40,High School,18,99,90,36,73,1.0,1,99,Semi-Urban,Data Analyst,101495,1 +96647,Other,54,High School,16,84,68,83,98,7.0,0,53,Rural,Manager,36728,1 +96648,Male,54,Bachelors,1,63,12,78,42,1.0,1,66,Urban,HR Executive,26937,0 +96649,Other,22,Diploma,16,43,63,61,79,0.0,6,19,Urban,Manager,43921,0 +96650,Male,39,High School,2,29,83,79,34,9.0,0,54,Urban,ML Engineer,48618,1 +96651,Female,29,PhD,8,22,59,72,2,1.0,1,88,Urban,Manager,38932,1 +96652,Female,33,Masters,16,10,36,61,75,1.0,2,45,Urban,Software Engineer,86828,0 +96653,Female,54,High School,14,92,65,46,72,1.0,4,53,Urban,Data Analyst,85792,1 +96654,Female,37,Diploma,17,27,61,31,55,9.0,5,92,Rural,Software Engineer,134473,0 +96655,Female,29,Bachelors,16,81,79,15,26,6.0,4,21,Urban,HR Executive,31430,0 +96656,Male,30,Bachelors,19,75,84,9,80,4.0,7,6,Semi-Urban,HR Executive,143168,0 +96657,Male,40,Bachelors,9,66,15,75,31,0.0,6,90,Rural,HR Executive,142564,1 +96658,Male,44,Bachelors,3,14,64,92,49,9.0,5,7,Rural,HR Executive,90842,0 +96659,Male,28,Bachelors,10,56,75,32,86,7.0,5,84,Urban,ML Engineer,80090,1 +96660,Male,24,Masters,4,74,48,66,45,4.0,4,37,Rural,Manager,99834,0 +96661,Male,50,PhD,3,70,67,56,51,3.0,3,29,Semi-Urban,ML Engineer,135547,0 +96662,Female,45,Diploma,5,2,14,54,27,3.0,1,86,Urban,Software Engineer,24808,0 +96663,Male,29,Bachelors,13,6,92,85,37,6.0,5,93,Urban,Manager,65850,1 +96664,Other,50,Bachelors,0,14,50,50,45,0.0,0,69,Urban,Software Engineer,100336,0 +96665,Male,42,Bachelors,18,43,7,37,10,8.0,6,53,Urban,Data Analyst,144359,0 +96666,Male,27,Diploma,19,13,15,66,36,6.0,2,30,Urban,Software Engineer,120074,0 +96667,Male,22,Bachelors,10,32,66,94,60,9.0,7,14,Semi-Urban,ML Engineer,120966,0 +96668,Male,54,Masters,14,57,48,87,94,0.0,5,40,Rural,Software Engineer,114903,0 +96669,Female,28,Bachelors,0,33,18,75,53,1.0,6,60,Urban,Manager,72566,0 +96670,Male,27,Bachelors,17,52,31,40,20,3.0,1,11,Rural,Data Analyst,92454,0 +96671,Male,41,Bachelors,12,9,37,76,31,7.0,1,81,Urban,Software Engineer,93993,0 +96672,Female,22,High School,14,2,26,50,37,3.0,0,55,Urban,Software Engineer,142947,0 +96673,Male,30,Bachelors,11,23,85,87,99,4.0,2,67,Urban,HR Executive,76786,1 +96674,Male,23,Diploma,19,3,72,77,79,5.0,0,26,Semi-Urban,Manager,21451,0 +96675,Male,58,Masters,7,30,71,7,64,0.0,0,25,Urban,HR Executive,89276,0 +96676,Female,23,Diploma,2,29,3,15,1,5.0,1,84,Semi-Urban,HR Executive,144969,0 +96677,Male,23,Diploma,17,76,48,24,89,4.0,7,1,Urban,Software Engineer,20209,0 +96678,Other,38,Bachelors,2,36,19,4,41,9.0,4,12,Urban,Software Engineer,99223,0 +96679,Male,33,Diploma,14,61,54,72,29,2.0,5,45,Rural,HR Executive,142939,0 +96680,Male,36,Bachelors,1,6,12,92,74,0.0,7,93,Urban,ML Engineer,79121,0 +96681,Male,36,Bachelors,1,41,35,44,86,1.0,0,7,Rural,ML Engineer,108419,0 +96682,Male,35,Diploma,15,83,34,16,20,9.0,7,48,Urban,HR Executive,59310,0 +96683,Male,37,Bachelors,19,44,59,77,70,9.0,5,54,Rural,ML Engineer,62714,0 +96684,Male,44,Bachelors,7,21,18,97,86,8.0,4,49,Rural,Software Engineer,113831,0 +96685,Male,30,Bachelors,9,7,77,6,60,2.0,5,33,Urban,Software Engineer,129460,0 +96686,Other,56,Masters,10,95,89,27,56,0.0,6,94,Semi-Urban,Data Analyst,44668,1 +96687,Male,57,Masters,6,77,90,1,60,8.0,1,75,Urban,Data Analyst,119185,1 +96688,Male,39,Bachelors,10,62,86,99,97,5.0,0,80,Semi-Urban,Software Engineer,91494,1 +96689,Male,37,Masters,8,37,19,93,89,6.0,6,70,Urban,ML Engineer,36847,0 +96690,Male,42,High School,17,26,1,89,25,0.0,7,38,Semi-Urban,Manager,99335,0 +96691,Female,21,Bachelors,4,12,54,65,43,7.0,5,36,Urban,Manager,20380,0 +96692,Male,21,Bachelors,1,80,47,72,66,0.0,5,81,Urban,ML Engineer,39984,1 +96693,Male,27,High School,18,91,95,36,61,7.0,0,90,Semi-Urban,Software Engineer,135691,1 +96694,Other,54,Masters,13,42,5,34,19,9.0,4,20,Semi-Urban,HR Executive,67723,0 +96695,Male,39,Bachelors,15,47,4,95,40,1.0,7,39,Semi-Urban,Data Analyst,83736,0 +96696,Female,22,Masters,1,11,87,97,35,8.0,5,34,Rural,HR Executive,130037,0 +96697,Male,39,Masters,8,50,67,58,81,9.0,7,20,Urban,HR Executive,129332,0 +96698,Male,22,Bachelors,3,69,85,28,56,5.0,6,59,Urban,Manager,110699,1 +96699,Other,30,Diploma,17,61,64,60,23,5.0,2,60,Urban,ML Engineer,80255,1 +96700,Female,33,Bachelors,7,81,17,92,38,9.0,2,14,Rural,ML Engineer,36609,0 +96701,Male,47,Diploma,12,86,86,27,80,6.0,5,65,Semi-Urban,HR Executive,108107,1 +96702,Male,52,Diploma,1,1,21,4,88,4.0,4,10,Urban,Data Analyst,124796,0 +96703,Male,23,Diploma,5,50,5,72,25,3.0,7,84,Rural,Data Analyst,134665,0 +96704,Male,25,High School,10,80,63,33,70,8.0,3,79,Urban,ML Engineer,43507,1 +96705,Male,40,High School,7,39,86,15,35,8.0,1,22,Urban,Software Engineer,52215,0 +96706,Female,42,PhD,18,58,26,63,93,2.0,0,45,Semi-Urban,HR Executive,142895,0 +96707,Female,21,Bachelors,9,15,36,82,30,2.0,0,20,Rural,HR Executive,78214,0 +96708,Other,28,Masters,9,93,23,9,9,4.0,4,53,Semi-Urban,HR Executive,33499,0 +96709,Female,39,Bachelors,6,62,5,10,91,1.0,1,81,Urban,ML Engineer,59211,0 +96710,Female,31,Bachelors,11,77,91,41,36,6.0,4,26,Semi-Urban,HR Executive,140003,0 +96711,Male,54,High School,4,44,15,84,4,6.0,2,64,Semi-Urban,Manager,41402,0 +96712,Female,38,Diploma,11,5,31,74,70,6.0,5,23,Urban,Software Engineer,79389,0 +96713,Male,36,Masters,1,44,10,6,74,2.0,1,67,Urban,HR Executive,56834,0 +96714,Female,50,Bachelors,17,6,46,97,58,1.0,6,2,Urban,ML Engineer,49262,0 +96715,Female,56,Bachelors,3,77,7,45,4,6.0,7,44,Urban,Manager,141549,0 +96716,Male,53,High School,14,50,1,28,63,1.0,6,20,Urban,Manager,23799,0 +96717,Male,58,Bachelors,9,23,97,7,47,5.0,5,32,Urban,Data Analyst,28848,0 +96718,Male,38,Diploma,2,22,32,39,92,1.0,3,33,Rural,Manager,94297,0 +96719,Female,23,Diploma,1,71,93,88,68,4.0,5,2,Semi-Urban,Software Engineer,130196,1 +96720,Male,23,Diploma,12,23,11,98,14,1.0,6,92,Semi-Urban,Manager,114484,0 +96721,Male,55,High School,18,36,39,12,48,6.0,4,76,Semi-Urban,Data Analyst,90034,0 +96722,Male,24,Bachelors,17,61,29,85,79,9.0,1,85,Rural,Data Analyst,128141,1 +96723,Male,21,Masters,13,74,64,9,43,1.0,4,76,Urban,Manager,55136,0 +96724,Female,41,PhD,5,90,32,60,12,0.0,2,53,Rural,HR Executive,88352,0 +96725,Male,35,Bachelors,4,18,83,0,91,4.0,7,74,Urban,Software Engineer,65612,0 +96726,Male,46,Masters,11,90,33,97,20,8.0,6,3,Semi-Urban,Software Engineer,84050,0 +96727,Other,39,Bachelors,18,68,1,78,81,1.0,0,28,Semi-Urban,HR Executive,67567,0 +96728,Male,43,PhD,0,58,65,57,46,2.0,2,97,Urban,ML Engineer,24484,1 +96729,Male,47,Bachelors,3,85,70,22,98,0.0,0,84,Semi-Urban,Software Engineer,128218,1 +96730,Male,44,Bachelors,15,24,0,92,28,8.0,2,80,Urban,ML Engineer,85869,0 +96731,Female,49,Diploma,12,20,49,11,66,8.0,4,63,Urban,Software Engineer,115699,0 +96732,Male,58,Masters,19,70,42,63,83,5.0,0,50,Urban,HR Executive,31326,0 +96733,Male,27,Bachelors,13,31,41,51,0,7.0,2,75,Urban,ML Engineer,42707,0 +96734,Male,46,Bachelors,3,80,58,7,86,7.0,3,41,Semi-Urban,Manager,46403,0 +96735,Female,59,Bachelors,4,34,99,61,5,9.0,7,89,Semi-Urban,Data Analyst,54882,1 +96736,Male,24,Bachelors,6,71,13,61,88,5.0,5,1,Rural,Manager,120950,0 +96737,Female,40,Bachelors,5,27,47,73,0,9.0,1,30,Urban,HR Executive,51001,0 +96738,Male,24,Masters,19,11,93,28,66,7.0,4,92,Semi-Urban,Data Analyst,31196,0 +96739,Other,48,Bachelors,18,32,26,7,69,6.0,3,94,Urban,HR Executive,34576,0 +96740,Male,36,PhD,15,51,46,39,93,4.0,2,55,Rural,Manager,122404,0 +96741,Other,22,Diploma,7,35,13,28,47,5.0,7,91,Rural,ML Engineer,97406,0 +96742,Other,26,Bachelors,5,73,7,49,95,8.0,4,96,Rural,Data Analyst,128823,0 +96743,Male,52,PhD,12,8,99,54,88,2.0,0,10,Rural,Manager,59411,0 +96744,Male,54,Masters,0,95,18,2,94,4.0,6,9,Urban,Software Engineer,32507,0 +96745,Male,48,Diploma,19,31,29,8,75,5.0,6,39,Urban,ML Engineer,118948,0 +96746,Male,26,Diploma,11,90,96,89,29,7.0,2,36,Urban,Manager,141915,1 +96747,Female,50,Bachelors,8,63,45,82,59,5.0,0,50,Urban,Software Engineer,109432,0 +96748,Male,43,Masters,5,47,88,45,67,1.0,0,18,Semi-Urban,HR Executive,85761,0 +96749,Female,56,High School,14,19,85,42,81,0.0,2,25,Urban,Data Analyst,75927,0 +96750,Male,27,Masters,17,17,36,65,65,2.0,6,86,Rural,ML Engineer,89158,0 +96751,Male,27,Bachelors,13,14,61,74,81,0.0,6,20,Rural,Manager,103076,0 +96752,Female,46,Diploma,1,64,27,88,29,2.0,1,97,Urban,Manager,56970,1 +96753,Male,57,Masters,8,94,46,44,19,8.0,3,38,Rural,ML Engineer,122084,0 +96754,Female,21,Bachelors,3,96,75,44,71,6.0,7,63,Urban,ML Engineer,140103,1 +96755,Male,53,High School,1,87,27,16,0,1.0,3,3,Rural,ML Engineer,106612,0 +96756,Female,39,Masters,14,33,13,23,64,5.0,7,10,Semi-Urban,Data Analyst,68533,0 +96757,Female,32,Bachelors,9,25,88,69,26,4.0,5,77,Urban,Data Analyst,72109,1 +96758,Male,25,Masters,2,1,46,65,82,7.0,0,36,Urban,Manager,103634,0 +96759,Male,27,Masters,14,77,73,38,57,3.0,4,1,Urban,ML Engineer,100070,0 +96760,Male,59,Diploma,11,3,12,3,66,0.0,2,84,Semi-Urban,Data Analyst,136517,0 +96761,Female,54,Bachelors,10,86,69,78,3,6.0,7,52,Urban,Data Analyst,146196,1 +96762,Male,45,High School,1,0,21,97,92,4.0,0,31,Rural,Data Analyst,102444,0 +96763,Other,26,Bachelors,5,99,80,96,64,0.0,0,6,Rural,Manager,79008,1 +96764,Female,47,Bachelors,0,82,73,4,37,7.0,3,6,Urban,HR Executive,26985,0 +96765,Female,35,Bachelors,11,53,71,74,31,3.0,0,51,Semi-Urban,Data Analyst,89669,1 +96766,Other,57,Diploma,16,5,82,57,11,9.0,7,91,Rural,HR Executive,145258,0 +96767,Female,50,Bachelors,15,14,38,69,68,7.0,0,62,Semi-Urban,HR Executive,58869,0 +96768,Male,58,Masters,4,60,31,81,8,9.0,2,28,Rural,ML Engineer,102896,0 +96769,Male,55,Bachelors,1,38,54,82,55,2.0,3,16,Urban,Manager,72625,0 +96770,Male,21,Bachelors,9,93,40,9,76,7.0,3,48,Urban,HR Executive,39351,0 +96771,Male,23,Bachelors,1,33,88,23,62,5.0,6,14,Urban,Data Analyst,62045,0 +96772,Male,35,High School,15,86,57,44,35,7.0,1,8,Urban,ML Engineer,33638,0 +96773,Male,27,Diploma,10,48,0,17,38,0.0,0,8,Rural,ML Engineer,28158,0 +96774,Female,21,Masters,12,27,82,83,94,1.0,3,20,Urban,Data Analyst,75884,0 +96775,Female,48,Bachelors,16,18,58,64,81,2.0,7,20,Urban,HR Executive,50918,0 +96776,Female,38,Diploma,5,25,64,58,70,6.0,1,64,Semi-Urban,ML Engineer,143931,0 +96777,Other,33,Diploma,16,52,15,36,40,8.0,1,99,Urban,HR Executive,138159,0 +96778,Female,28,Masters,19,28,38,99,84,5.0,0,55,Semi-Urban,Data Analyst,106159,0 +96779,Male,25,Diploma,12,18,55,48,27,6.0,1,0,Semi-Urban,HR Executive,54295,0 +96780,Male,33,Diploma,4,65,94,12,31,9.0,7,64,Urban,Software Engineer,110960,1 +96781,Male,36,High School,3,84,26,18,72,8.0,1,57,Urban,Data Analyst,86854,0 +96782,Female,29,Bachelors,7,73,12,57,30,7.0,6,22,Urban,Data Analyst,84155,0 +96783,Female,32,Masters,2,69,16,49,58,7.0,5,65,Rural,ML Engineer,21843,0 +96784,Female,30,Bachelors,4,41,78,41,7,3.0,1,68,Rural,HR Executive,100368,0 +96785,Female,59,Diploma,11,67,74,0,72,1.0,6,14,Rural,Software Engineer,86527,0 +96786,Female,51,Bachelors,9,10,39,94,45,7.0,5,78,Urban,Software Engineer,110955,0 +96787,Female,44,Bachelors,1,5,19,39,98,0.0,3,59,Urban,Software Engineer,115150,0 +96788,Female,46,Diploma,11,34,68,89,43,7.0,0,80,Rural,Manager,120243,1 +96789,Female,53,Masters,16,42,97,40,1,3.0,1,6,Rural,Data Analyst,130599,0 +96790,Female,34,Masters,4,58,21,27,13,2.0,7,88,Semi-Urban,Manager,94778,0 +96791,Male,33,Masters,3,93,79,63,12,1.0,6,58,Urban,Data Analyst,96751,1 +96792,Male,39,Diploma,8,6,10,76,59,1.0,5,51,Rural,ML Engineer,36531,0 +96793,Male,57,Diploma,5,72,16,16,68,7.0,6,46,Urban,ML Engineer,65132,0 +96794,Female,47,Diploma,4,6,95,19,50,4.0,1,31,Rural,HR Executive,141329,0 +96795,Male,22,Bachelors,11,76,71,37,33,9.0,5,10,Urban,Software Engineer,99950,0 +96796,Male,22,Masters,7,88,50,29,15,0.0,3,77,Semi-Urban,HR Executive,128008,1 +96797,Male,34,Bachelors,2,36,35,75,13,1.0,1,74,Semi-Urban,Manager,39321,0 +96798,Other,48,PhD,0,64,59,81,33,5.0,4,73,Urban,Manager,130825,1 +96799,Male,54,Masters,2,62,58,15,76,4.0,1,39,Urban,Data Analyst,62462,0 +96800,Male,30,Bachelors,6,10,50,5,61,7.0,0,16,Urban,HR Executive,115266,0 +96801,Female,44,PhD,19,99,75,59,65,6.0,1,64,Urban,Software Engineer,145448,1 +96802,Female,21,Masters,15,46,13,79,82,6.0,3,88,Rural,Manager,106608,0 +96803,Female,32,High School,8,88,57,10,15,1.0,5,79,Urban,Data Analyst,129895,0 +96804,Female,40,Masters,18,66,23,70,1,7.0,1,79,Urban,ML Engineer,53992,0 +96805,Male,35,Masters,4,24,77,0,13,0.0,0,90,Urban,Software Engineer,133626,0 +96806,Male,21,Diploma,17,8,70,79,39,0.0,4,58,Semi-Urban,ML Engineer,83271,0 +96807,Female,58,Masters,17,18,27,2,56,5.0,4,96,Rural,Data Analyst,102164,0 +96808,Female,55,Diploma,9,71,8,42,26,4.0,4,52,Semi-Urban,Software Engineer,28948,0 +96809,Male,30,Bachelors,6,57,84,90,92,5.0,1,26,Urban,Manager,29486,1 +96810,Other,31,Masters,6,93,48,5,4,9.0,5,44,Urban,Manager,49599,0 +96811,Female,41,Bachelors,17,2,98,0,2,6.0,3,34,Semi-Urban,Software Engineer,74099,0 +96812,Female,32,High School,19,49,61,30,22,2.0,4,2,Urban,ML Engineer,94150,0 +96813,Male,39,Bachelors,10,8,56,24,7,9.0,3,41,Urban,ML Engineer,139294,0 +96814,Male,49,Bachelors,1,79,89,76,96,0.0,4,71,Urban,Manager,81064,1 +96815,Male,33,Diploma,9,51,76,90,33,6.0,2,36,Urban,HR Executive,44806,1 +96816,Male,47,Bachelors,12,32,2,60,93,2.0,7,48,Rural,ML Engineer,29143,0 +96817,Female,51,Diploma,10,65,4,43,36,6.0,2,23,Rural,HR Executive,33409,0 +96818,Male,38,Bachelors,16,3,9,1,36,6.0,4,51,Urban,Manager,61256,0 +96819,Male,54,Bachelors,10,82,2,86,97,9.0,1,98,Semi-Urban,Data Analyst,57917,1 +96820,Male,56,Bachelors,7,52,60,22,1,4.0,6,74,Rural,ML Engineer,142007,0 +96821,Male,39,Masters,18,54,63,27,20,8.0,0,78,Semi-Urban,Software Engineer,45374,0 +96822,Male,56,Masters,15,87,1,22,41,5.0,7,91,Urban,HR Executive,28633,0 +96823,Other,27,Masters,5,20,49,80,3,5.0,2,78,Semi-Urban,Data Analyst,61100,0 +96824,Other,36,Diploma,14,38,43,16,0,6.0,1,97,Urban,Software Engineer,107593,0 +96825,Female,28,Bachelors,12,43,31,9,82,3.0,7,70,Semi-Urban,Manager,83555,0 +96826,Male,33,Bachelors,3,56,8,70,46,8.0,7,77,Urban,ML Engineer,84325,0 +96827,Female,34,Bachelors,10,89,48,19,37,2.0,5,10,Semi-Urban,Manager,134351,0 +96828,Other,33,High School,13,54,15,16,57,7.0,5,66,Urban,Software Engineer,92372,0 +96829,Other,21,Bachelors,18,37,25,56,89,4.0,6,87,Rural,HR Executive,32126,0 +96830,Female,46,High School,11,40,38,38,75,0.0,4,26,Rural,Data Analyst,123009,0 +96831,Male,54,Bachelors,0,64,8,6,76,8.0,3,6,Semi-Urban,ML Engineer,113950,0 +96832,Female,51,High School,18,67,28,21,94,0.0,3,56,Rural,ML Engineer,51309,0 +96833,Female,39,Diploma,14,46,44,75,40,3.0,4,1,Urban,Data Analyst,74068,0 +96834,Male,48,Diploma,7,40,70,68,62,9.0,5,34,Urban,HR Executive,143990,0 +96835,Male,28,Masters,10,6,57,74,33,4.0,4,91,Rural,Software Engineer,60110,0 +96836,Male,30,High School,4,13,15,45,49,7.0,3,99,Rural,Manager,72296,0 +96837,Male,29,Bachelors,18,13,85,40,60,3.0,1,50,Urban,Software Engineer,119407,0 +96838,Male,21,Masters,12,28,9,81,84,7.0,6,58,Semi-Urban,ML Engineer,34832,0 +96839,Male,45,Diploma,8,7,20,51,19,3.0,5,80,Rural,HR Executive,149234,0 +96840,Female,23,High School,16,30,74,31,68,8.0,2,80,Semi-Urban,ML Engineer,67986,0 +96841,Other,21,Bachelors,10,66,46,64,65,4.0,7,93,Urban,ML Engineer,51399,1 +96842,Male,35,Diploma,19,42,14,90,9,8.0,4,42,Urban,HR Executive,46782,0 +96843,Female,26,Bachelors,14,70,83,45,62,8.0,2,74,Semi-Urban,ML Engineer,141569,1 +96844,Male,47,Bachelors,19,21,2,93,52,5.0,0,62,Semi-Urban,HR Executive,143164,0 +96845,Female,28,Bachelors,15,58,82,52,37,9.0,6,27,Urban,ML Engineer,127571,0 +96846,Female,52,High School,12,98,11,15,51,8.0,3,84,Urban,Data Analyst,136047,0 +96847,Male,40,Bachelors,1,76,41,84,96,2.0,2,91,Urban,Software Engineer,31597,1 +96848,Male,30,Bachelors,1,62,8,85,39,1.0,3,54,Urban,ML Engineer,67094,0 +96849,Female,57,Diploma,13,17,33,78,43,7.0,0,49,Urban,ML Engineer,69170,0 +96850,Male,44,Diploma,5,69,65,69,92,0.0,1,82,Urban,Manager,53202,1 +96851,Other,24,Masters,18,27,45,93,76,5.0,4,82,Urban,HR Executive,28216,1 +96852,Other,24,Bachelors,6,56,20,76,44,0.0,1,41,Urban,Data Analyst,84184,0 +96853,Male,30,Bachelors,1,18,93,86,82,8.0,0,16,Urban,Data Analyst,74943,0 +96854,Female,57,Diploma,18,50,95,52,78,8.0,3,61,Urban,Data Analyst,45519,1 +96855,Female,22,Bachelors,17,27,6,29,33,7.0,2,81,Semi-Urban,Manager,106122,0 +96856,Female,27,Masters,11,72,55,22,57,1.0,7,17,Urban,ML Engineer,77679,0 +96857,Female,46,Masters,9,51,9,96,24,1.0,2,0,Urban,Software Engineer,56172,0 +96858,Male,26,Bachelors,3,66,41,93,61,7.0,0,90,Semi-Urban,Data Analyst,131771,1 +96859,Male,52,Bachelors,12,98,72,73,40,5.0,2,4,Urban,Data Analyst,43007,1 +96860,Female,34,Bachelors,4,91,63,95,24,1.0,2,10,Urban,Data Analyst,135814,1 +96861,Male,52,Bachelors,0,36,83,93,34,6.0,5,64,Urban,Manager,31553,1 +96862,Male,56,Bachelors,10,22,5,65,3,5.0,4,59,Urban,Data Analyst,101977,0 +96863,Female,22,Diploma,4,8,45,54,83,0.0,3,65,Urban,Manager,24954,0 +96864,Male,56,Bachelors,19,72,95,51,32,5.0,6,47,Semi-Urban,Manager,67924,1 +96865,Female,30,Bachelors,12,90,28,28,7,4.0,7,76,Urban,Software Engineer,44215,0 +96866,Female,23,PhD,14,8,57,63,62,0.0,4,3,Urban,HR Executive,120400,0 +96867,Other,49,Bachelors,4,68,14,99,24,0.0,5,27,Urban,ML Engineer,147583,0 +96868,Male,57,High School,5,47,80,73,13,4.0,0,52,Urban,Manager,142927,1 +96869,Male,29,Bachelors,16,99,0,37,33,4.0,5,79,Urban,Data Analyst,140117,0 +96870,Female,30,Diploma,4,34,41,79,17,8.0,7,24,Urban,ML Engineer,35624,0 +96871,Male,54,Masters,4,96,73,90,38,2.0,5,97,Semi-Urban,HR Executive,22645,1 +96872,Male,51,Bachelors,12,4,10,41,12,4.0,0,94,Urban,HR Executive,139701,0 +96873,Male,58,Bachelors,8,43,76,86,86,7.0,0,31,Rural,Data Analyst,113566,1 +96874,Female,21,High School,2,58,48,38,82,1.0,3,42,Urban,Software Engineer,108902,0 +96875,Male,55,Masters,18,72,29,67,6,9.0,4,28,Rural,Manager,58507,0 +96876,Female,25,PhD,19,58,69,2,16,0.0,6,25,Urban,ML Engineer,128243,0 +96877,Female,52,Bachelors,6,52,25,53,32,9.0,2,30,Semi-Urban,Manager,138018,0 +96878,Female,54,Diploma,15,80,10,44,18,1.0,4,55,Urban,ML Engineer,20955,0 +96879,Female,36,Bachelors,7,86,10,74,17,3.0,4,61,Urban,Manager,128193,0 +96880,Male,49,Diploma,16,49,82,61,75,9.0,2,2,Urban,ML Engineer,31274,0 +96881,Male,49,Bachelors,16,46,80,68,89,5.0,4,70,Urban,Manager,25222,1 +96882,Male,53,High School,7,4,17,63,78,7.0,3,41,Semi-Urban,HR Executive,105167,0 +96883,Male,45,Bachelors,4,88,99,21,85,3.0,4,13,Rural,ML Engineer,136436,0 +96884,Female,40,Bachelors,18,59,26,26,65,1.0,7,32,Rural,Data Analyst,106553,0 +96885,Male,46,Bachelors,13,8,9,50,58,5.0,7,61,Rural,Manager,48473,0 +96886,Male,50,Bachelors,14,66,30,48,61,9.0,2,86,Semi-Urban,Data Analyst,45703,0 +96887,Male,38,Bachelors,19,35,72,81,1,0.0,6,84,Urban,HR Executive,43582,1 +96888,Male,25,Bachelors,15,47,57,90,54,4.0,0,46,Semi-Urban,HR Executive,143146,1 +96889,Male,23,High School,7,10,13,86,63,3.0,5,11,Semi-Urban,Software Engineer,129709,0 +96890,Male,41,Masters,14,23,58,67,90,1.0,5,56,Rural,ML Engineer,87544,0 +96891,Female,39,High School,3,62,81,38,77,8.0,4,83,Rural,Data Analyst,25543,1 +96892,Female,59,Bachelors,14,65,51,27,22,5.0,0,18,Urban,HR Executive,143967,0 +96893,Male,28,Bachelors,1,50,28,35,34,3.0,1,13,Urban,Manager,57047,0 +96894,Female,30,Diploma,4,2,39,38,64,5.0,3,41,Urban,Data Analyst,78453,0 +96895,Male,55,Bachelors,1,55,55,35,78,7.0,3,52,Rural,Data Analyst,22193,0 +96896,Male,43,Diploma,5,75,96,21,96,7.0,3,11,Semi-Urban,ML Engineer,95993,0 +96897,Female,41,Masters,11,92,14,76,12,2.0,6,46,Urban,ML Engineer,101336,0 +96898,Other,49,PhD,13,40,24,71,47,3.0,7,7,Urban,Data Analyst,137782,0 +96899,Male,53,Diploma,15,5,13,76,19,3.0,5,49,Urban,Data Analyst,110458,0 +96900,Female,44,PhD,2,90,50,10,24,7.0,4,52,Semi-Urban,ML Engineer,41151,0 +96901,Female,24,Bachelors,7,28,69,75,52,9.0,6,87,Urban,HR Executive,109484,1 +96902,Female,49,Masters,4,70,94,52,13,7.0,6,61,Semi-Urban,Software Engineer,54684,1 +96903,Male,45,Diploma,10,45,14,8,89,3.0,1,24,Rural,HR Executive,45835,0 +96904,Male,42,Diploma,11,30,72,83,77,2.0,0,17,Urban,Data Analyst,138146,0 +96905,Male,29,Bachelors,1,8,45,24,90,1.0,5,37,Urban,Manager,65427,0 +96906,Male,26,Bachelors,15,11,79,67,27,5.0,5,47,Semi-Urban,ML Engineer,112418,0 +96907,Male,30,Diploma,5,90,14,25,12,3.0,2,15,Urban,Manager,143908,0 +96908,Male,32,Masters,4,67,15,30,97,5.0,0,33,Urban,Software Engineer,91506,0 +96909,Male,41,Masters,19,61,32,91,63,9.0,4,81,Semi-Urban,ML Engineer,61783,1 +96910,Male,29,Diploma,10,28,42,92,91,4.0,6,68,Semi-Urban,ML Engineer,105377,0 +96911,Male,54,High School,13,57,35,69,17,4.0,4,62,Semi-Urban,ML Engineer,73689,0 +96912,Male,54,Bachelors,9,25,59,92,8,8.0,4,44,Urban,ML Engineer,35448,0 +96913,Male,58,Bachelors,5,1,8,81,48,2.0,4,86,Urban,ML Engineer,73566,0 +96914,Other,47,Masters,15,61,1,10,79,1.0,6,46,Urban,Data Analyst,134527,0 +96915,Male,45,Bachelors,2,8,70,23,56,8.0,7,64,Urban,Manager,25454,0 +96916,Female,27,Diploma,16,7,27,70,9,5.0,3,98,Rural,Manager,106554,0 +96917,Male,32,Bachelors,0,87,37,78,83,0.0,5,33,Rural,Data Analyst,128463,1 +96918,Male,42,High School,1,19,71,66,2,5.0,5,48,Rural,Data Analyst,45484,0 +96919,Female,53,Bachelors,1,78,8,81,80,1.0,0,65,Urban,ML Engineer,85962,0 +96920,Male,33,High School,11,98,91,22,40,8.0,5,82,Rural,Data Analyst,29897,1 +96921,Male,33,High School,17,21,47,77,86,5.0,3,17,Semi-Urban,Data Analyst,70687,0 +96922,Male,38,PhD,6,42,48,61,56,7.0,5,56,Urban,Data Analyst,138450,0 +96923,Male,41,Bachelors,1,71,97,59,95,4.0,1,19,Urban,HR Executive,49605,1 +96924,Male,50,Bachelors,4,95,71,64,22,6.0,0,60,Semi-Urban,Manager,33270,1 +96925,Male,46,Bachelors,7,98,61,47,2,1.0,1,59,Urban,Manager,123793,1 +96926,Male,38,Bachelors,12,31,48,88,55,5.0,2,94,Semi-Urban,Data Analyst,131898,1 +96927,Other,25,Bachelors,14,84,46,45,71,8.0,1,88,Rural,Manager,54454,1 +96928,Female,24,Bachelors,12,71,96,58,4,6.0,0,50,Urban,Software Engineer,20720,1 +96929,Male,47,Masters,2,72,75,71,32,4.0,5,30,Rural,Manager,25649,1 +96930,Male,38,Bachelors,14,13,48,76,45,0.0,2,80,Semi-Urban,HR Executive,103723,0 +96931,Female,57,Bachelors,17,73,80,1,88,2.0,1,90,Urban,Software Engineer,84795,1 +96932,Male,54,Bachelors,12,6,78,10,84,7.0,4,5,Urban,ML Engineer,25637,0 +96933,Male,45,Bachelors,7,55,32,83,53,8.0,5,89,Urban,Data Analyst,141525,1 +96934,Male,32,Bachelors,3,76,7,56,47,5.0,3,85,Rural,HR Executive,68296,0 +96935,Male,52,Bachelors,8,7,74,14,91,1.0,2,81,Urban,HR Executive,137856,0 +96936,Female,33,High School,8,18,69,90,61,8.0,3,90,Semi-Urban,Manager,89372,1 +96937,Female,53,Bachelors,19,6,6,90,62,8.0,2,56,Urban,Data Analyst,87508,0 +96938,Female,55,Bachelors,16,85,42,30,27,2.0,2,65,Urban,HR Executive,127222,0 +96939,Female,49,Bachelors,14,60,66,73,91,1.0,3,82,Urban,Data Analyst,101708,1 +96940,Female,28,Masters,4,74,34,65,87,8.0,7,16,Urban,Data Analyst,24618,0 +96941,Female,33,Diploma,5,13,73,69,4,5.0,4,44,Urban,HR Executive,39802,0 +96942,Female,45,Bachelors,8,22,94,55,86,1.0,3,77,Rural,ML Engineer,126661,1 +96943,Male,49,Bachelors,16,72,11,61,63,7.0,3,57,Rural,ML Engineer,63396,0 +96944,Male,33,Masters,14,8,11,30,69,9.0,5,60,Urban,ML Engineer,118581,0 +96945,Male,48,Masters,0,89,76,6,61,5.0,6,17,Rural,HR Executive,26204,0 +96946,Other,31,High School,0,45,33,58,54,6.0,7,19,Semi-Urban,Manager,120306,0 +96947,Male,35,Masters,7,9,43,32,49,3.0,7,20,Urban,Software Engineer,42165,0 +96948,Female,24,Bachelors,15,20,6,40,8,2.0,7,37,Urban,HR Executive,46943,0 +96949,Female,50,Masters,11,58,15,97,43,6.0,3,56,Urban,Data Analyst,100630,0 +96950,Male,47,Bachelors,9,53,74,95,8,9.0,1,33,Urban,Manager,31361,1 +96951,Male,26,PhD,7,35,92,78,51,7.0,7,31,Urban,HR Executive,89605,1 +96952,Male,41,PhD,6,73,20,7,70,4.0,6,34,Urban,HR Executive,45068,0 +96953,Female,39,Bachelors,4,48,54,87,93,4.0,7,22,Semi-Urban,Software Engineer,35353,0 +96954,Male,41,Bachelors,0,94,13,48,53,5.0,0,63,Semi-Urban,Data Analyst,26529,0 +96955,Female,44,Diploma,19,33,72,8,0,5.0,2,30,Urban,Software Engineer,89229,0 +96956,Female,31,Diploma,13,82,49,91,43,8.0,4,84,Urban,Data Analyst,91851,1 +96957,Male,27,High School,8,48,3,25,60,8.0,7,0,Urban,Data Analyst,40814,0 +96958,Male,25,Masters,13,40,12,5,3,5.0,0,86,Urban,Data Analyst,146304,0 +96959,Female,38,Masters,16,9,13,25,50,1.0,3,86,Semi-Urban,Software Engineer,73210,0 +96960,Male,34,Masters,9,57,65,30,14,0.0,2,82,Semi-Urban,HR Executive,82397,0 +96961,Male,45,Masters,7,53,51,10,53,5.0,6,12,Urban,Software Engineer,93769,0 +96962,Male,25,High School,2,59,59,42,74,3.0,5,44,Semi-Urban,Data Analyst,107788,0 +96963,Male,57,Bachelors,19,90,6,35,90,2.0,1,46,Urban,HR Executive,52989,0 +96964,Female,22,Bachelors,2,80,47,17,42,1.0,3,2,Rural,Software Engineer,61270,0 +96965,Male,47,PhD,18,13,97,4,98,4.0,2,37,Urban,ML Engineer,73843,0 +96966,Female,31,High School,11,94,83,83,91,7.0,1,30,Urban,HR Executive,33674,1 +96967,Male,24,Bachelors,11,65,36,39,80,1.0,4,29,Semi-Urban,Manager,47947,0 +96968,Male,26,Diploma,11,54,71,5,18,6.0,3,16,Urban,Software Engineer,35148,0 +96969,Male,45,Bachelors,7,63,70,96,77,0.0,2,16,Urban,Software Engineer,73057,1 +96970,Male,37,Bachelors,13,30,79,46,43,9.0,6,33,Urban,Data Analyst,125975,0 +96971,Other,50,Masters,7,13,98,3,78,7.0,4,7,Urban,Software Engineer,47214,0 +96972,Male,55,Bachelors,10,15,76,17,15,4.0,2,20,Urban,ML Engineer,51035,0 +96973,Female,57,Bachelors,10,97,83,86,92,3.0,6,70,Semi-Urban,ML Engineer,117972,1 +96974,Female,47,Bachelors,4,16,76,4,76,7.0,0,35,Semi-Urban,Manager,32454,0 +96975,Female,58,High School,17,26,75,72,95,2.0,0,52,Urban,Data Analyst,58111,0 +96976,Male,23,Bachelors,18,18,42,88,91,0.0,3,38,Urban,HR Executive,44527,0 +96977,Female,39,PhD,16,18,15,1,65,3.0,2,0,Urban,Data Analyst,36528,0 +96978,Female,42,High School,2,41,4,89,51,1.0,0,58,Semi-Urban,HR Executive,70541,0 +96979,Other,25,Bachelors,19,62,80,58,62,4.0,6,92,Rural,Manager,117791,1 +96980,Other,41,Diploma,15,16,89,94,53,5.0,1,20,Semi-Urban,Data Analyst,47328,0 +96981,Male,54,Masters,2,54,4,9,88,9.0,6,90,Urban,HR Executive,69843,0 +96982,Female,22,Bachelors,11,28,38,75,99,9.0,6,59,Urban,HR Executive,61525,0 +96983,Female,45,Masters,4,70,1,60,19,0.0,5,64,Urban,Manager,126451,0 +96984,Other,33,Bachelors,6,6,39,55,33,7.0,4,41,Urban,Software Engineer,87768,0 +96985,Male,24,PhD,15,31,62,87,73,5.0,0,26,Rural,Manager,47079,0 +96986,Female,39,Bachelors,12,10,20,10,80,0.0,4,1,Rural,Manager,59843,0 +96987,Male,43,Masters,12,5,33,67,69,3.0,1,21,Semi-Urban,Manager,36835,0 +96988,Male,36,High School,19,60,5,31,3,2.0,7,85,Semi-Urban,Manager,142063,0 +96989,Female,54,Diploma,2,62,87,70,40,3.0,5,70,Rural,Software Engineer,49736,1 +96990,Female,51,Masters,18,92,3,63,39,4.0,0,51,Urban,Software Engineer,31215,0 +96991,Female,36,Masters,18,87,87,76,27,9.0,0,88,Semi-Urban,ML Engineer,53757,1 +96992,Female,40,Diploma,0,2,4,61,98,0.0,4,37,Urban,Software Engineer,34960,0 +96993,Female,43,Diploma,12,78,92,90,45,0.0,4,28,Urban,HR Executive,20463,1 +96994,Male,49,Bachelors,0,55,27,73,16,9.0,1,6,Urban,Data Analyst,138601,0 +96995,Male,58,Diploma,4,78,7,24,23,1.0,6,58,Rural,Software Engineer,88191,0 +96996,Male,23,PhD,3,55,56,25,36,9.0,1,24,Urban,HR Executive,51511,0 +96997,Male,52,Bachelors,9,39,87,44,75,6.0,2,69,Rural,ML Engineer,52190,1 +96998,Female,32,PhD,1,96,38,53,70,8.0,2,44,Urban,Data Analyst,96492,0 +96999,Male,55,Bachelors,0,1,21,0,79,0.0,6,86,Semi-Urban,HR Executive,46599,0 +97000,Other,28,Diploma,1,53,74,95,15,0.0,6,84,Urban,Software Engineer,118767,1 +97001,Female,50,Diploma,18,13,60,97,67,0.0,2,13,Urban,Data Analyst,98104,0 +97002,Other,55,Diploma,10,19,85,94,86,6.0,5,46,Urban,HR Executive,48108,1 +97003,Female,26,Masters,17,92,1,17,10,1.0,4,57,Urban,Software Engineer,48462,0 +97004,Male,29,High School,1,56,26,99,35,4.0,7,65,Urban,Data Analyst,54739,1 +97005,Male,39,Masters,9,24,77,9,24,1.0,7,81,Rural,ML Engineer,66515,0 +97006,Male,33,PhD,2,16,67,16,54,6.0,5,27,Urban,HR Executive,49584,0 +97007,Male,54,Bachelors,1,87,75,27,37,1.0,4,51,Semi-Urban,HR Executive,61986,1 +97008,Male,23,Diploma,19,36,43,89,84,6.0,2,74,Semi-Urban,Data Analyst,148719,1 +97009,Female,41,PhD,1,95,36,70,0,6.0,7,1,Semi-Urban,Software Engineer,126469,0 +97010,Male,48,Bachelors,0,10,91,78,66,5.0,2,28,Rural,Manager,86324,0 +97011,Male,34,Diploma,11,6,10,90,61,6.0,4,1,Urban,ML Engineer,32813,0 +97012,Female,22,Bachelors,7,77,42,9,76,7.0,0,61,Semi-Urban,ML Engineer,45969,0 +97013,Female,46,Diploma,2,71,0,40,63,2.0,3,36,Semi-Urban,HR Executive,84396,0 +97014,Male,38,Diploma,17,72,68,82,19,7.0,3,63,Rural,Software Engineer,39145,1 +97015,Male,29,Bachelors,5,29,11,19,27,7.0,3,94,Urban,HR Executive,58837,0 +97016,Male,37,Bachelors,3,11,59,44,8,9.0,7,80,Urban,HR Executive,58265,0 +97017,Male,45,Diploma,5,61,98,86,99,3.0,4,9,Urban,ML Engineer,120639,1 +97018,Female,48,Masters,18,42,31,45,34,8.0,4,10,Urban,Data Analyst,109985,0 +97019,Female,33,Bachelors,12,33,82,8,27,7.0,5,79,Urban,Data Analyst,125251,0 +97020,Female,44,Masters,1,46,33,87,67,2.0,0,35,Urban,Manager,103064,0 +97021,Male,24,Masters,13,75,82,7,48,8.0,1,82,Urban,Data Analyst,58305,1 +97022,Female,30,Bachelors,4,3,29,88,45,0.0,6,90,Urban,ML Engineer,127993,0 +97023,Male,23,Masters,8,53,58,70,6,7.0,6,15,Urban,Data Analyst,67901,0 +97024,Female,37,Bachelors,2,94,32,46,46,4.0,2,36,Rural,ML Engineer,107588,0 +97025,Male,51,Masters,5,89,84,61,50,2.0,5,96,Urban,Software Engineer,38733,1 +97026,Male,21,Diploma,16,72,79,76,26,6.0,6,47,Rural,Data Analyst,114212,1 +97027,Male,30,High School,13,87,4,3,95,0.0,4,0,Rural,ML Engineer,86466,0 +97028,Male,50,Diploma,2,75,9,91,73,3.0,0,2,Rural,Software Engineer,57488,0 +97029,Female,59,Bachelors,0,55,78,66,82,4.0,3,21,Urban,Software Engineer,119262,0 +97030,Female,51,Diploma,8,97,49,70,11,1.0,1,65,Urban,Data Analyst,71790,1 +97031,Female,37,Diploma,4,16,58,42,94,3.0,7,34,Urban,HR Executive,118694,0 +97032,Other,59,High School,4,95,69,61,69,6.0,1,45,Urban,HR Executive,44083,1 +97033,Male,30,High School,5,51,66,18,33,6.0,2,5,Urban,Software Engineer,51972,0 +97034,Male,56,Bachelors,9,41,77,67,74,1.0,1,77,Semi-Urban,ML Engineer,137081,1 +97035,Male,26,Diploma,4,68,84,92,40,1.0,2,22,Urban,Software Engineer,66001,1 +97036,Female,36,Bachelors,14,21,83,28,83,4.0,1,91,Rural,Data Analyst,60010,0 +97037,Male,34,Bachelors,8,26,95,34,41,8.0,6,2,Urban,HR Executive,45167,0 +97038,Male,38,Diploma,13,22,33,18,13,5.0,5,20,Urban,Data Analyst,136248,0 +97039,Male,51,Bachelors,14,43,45,51,9,0.0,4,42,Rural,Data Analyst,90998,0 +97040,Male,49,Bachelors,13,78,92,66,4,9.0,1,64,Rural,ML Engineer,119998,1 +97041,Other,42,Masters,8,95,48,36,70,1.0,4,60,Urban,HR Executive,40258,0 +97042,Male,34,Bachelors,14,10,89,60,4,5.0,6,79,Semi-Urban,ML Engineer,47833,1 +97043,Male,47,Masters,7,30,5,2,55,3.0,0,51,Urban,ML Engineer,83156,0 +97044,Male,22,Diploma,12,18,66,21,55,7.0,3,37,Urban,HR Executive,106465,0 +97045,Male,41,Diploma,3,99,37,84,61,9.0,4,11,Urban,Manager,42387,0 +97046,Male,41,Diploma,9,8,29,57,31,0.0,0,83,Urban,Software Engineer,69320,0 +97047,Male,45,Bachelors,16,75,63,39,87,2.0,1,49,Rural,Data Analyst,62872,0 +97048,Female,41,Bachelors,5,38,13,63,97,5.0,1,81,Urban,ML Engineer,56170,0 +97049,Female,59,Bachelors,2,25,81,12,82,8.0,5,1,Semi-Urban,Manager,76654,0 +97050,Female,53,Masters,13,6,63,45,39,4.0,4,72,Urban,ML Engineer,26296,0 +97051,Male,55,Bachelors,15,59,52,70,70,6.0,0,69,Urban,ML Engineer,116304,1 +97052,Male,53,Diploma,9,5,84,69,33,9.0,2,5,Urban,ML Engineer,42498,0 +97053,Male,43,Bachelors,10,47,52,18,35,6.0,5,64,Rural,Manager,111025,0 +97054,Female,48,Bachelors,13,55,35,31,58,0.0,5,47,Urban,Manager,66036,0 +97055,Male,56,High School,7,74,82,81,35,3.0,3,54,Urban,Manager,46047,1 +97056,Male,55,Bachelors,7,0,38,37,85,3.0,2,25,Rural,Software Engineer,41851,0 +97057,Male,30,Bachelors,5,31,79,86,5,5.0,2,19,Semi-Urban,Data Analyst,126322,0 +97058,Male,32,Diploma,19,67,50,55,93,1.0,7,32,Urban,Data Analyst,86469,0 +97059,Female,35,Masters,7,82,78,22,58,1.0,7,34,Urban,ML Engineer,50953,0 +97060,Female,27,Bachelors,15,93,5,3,92,2.0,2,58,Urban,HR Executive,36992,0 +97061,Female,59,Bachelors,13,62,76,34,34,5.0,0,7,Urban,ML Engineer,104403,0 +97062,Male,36,Bachelors,13,68,30,12,58,8.0,1,45,Urban,Data Analyst,72956,0 +97063,Male,31,Masters,2,24,65,63,84,0.0,6,14,Semi-Urban,Data Analyst,43915,0 +97064,Male,24,Masters,9,91,36,30,4,0.0,3,26,Urban,Software Engineer,142053,0 +97065,Other,33,High School,4,22,26,46,49,7.0,7,37,Urban,Manager,134715,0 +97066,Male,27,Diploma,6,59,55,1,69,4.0,1,15,Rural,Data Analyst,143098,0 +97067,Female,41,Bachelors,13,29,83,83,72,1.0,6,44,Semi-Urban,Software Engineer,26649,0 +97068,Male,39,Bachelors,8,48,74,61,14,4.0,0,75,Semi-Urban,HR Executive,132291,1 +97069,Male,45,Masters,3,92,15,24,82,5.0,3,5,Rural,ML Engineer,95781,0 +97070,Female,46,Bachelors,17,23,41,65,23,9.0,7,6,Urban,Manager,71156,0 +97071,Female,49,High School,12,66,19,55,10,5.0,2,47,Rural,Data Analyst,102671,0 +97072,Male,51,High School,11,54,75,52,64,0.0,6,97,Urban,ML Engineer,138348,1 +97073,Male,31,Bachelors,16,35,74,94,62,4.0,5,58,Rural,Software Engineer,138179,1 +97074,Female,58,PhD,9,16,52,69,34,6.0,4,20,Urban,ML Engineer,145196,0 +97075,Female,41,Masters,10,5,7,84,71,0.0,7,5,Urban,HR Executive,101481,0 +97076,Male,38,Masters,16,62,88,48,99,6.0,5,53,Rural,Software Engineer,23777,1 +97077,Male,35,Bachelors,14,62,44,42,41,9.0,1,79,Urban,ML Engineer,79979,0 +97078,Male,39,Bachelors,6,47,80,70,5,5.0,6,5,Urban,Manager,25831,0 +97079,Other,57,Bachelors,7,40,68,95,18,8.0,2,35,Urban,Manager,59513,0 +97080,Other,47,Bachelors,17,97,51,54,62,7.0,5,58,Rural,ML Engineer,124952,1 +97081,Female,32,Masters,9,28,44,70,37,7.0,6,36,Rural,Data Analyst,149033,0 +97082,Male,47,Diploma,0,25,68,76,78,8.0,1,97,Urban,Software Engineer,138927,1 +97083,Other,48,Bachelors,9,77,66,50,73,2.0,1,55,Urban,Manager,41658,1 +97084,Male,38,Diploma,10,37,84,39,90,7.0,6,81,Rural,Manager,138344,1 +97085,Male,33,Bachelors,19,27,38,26,87,7.0,0,1,Semi-Urban,HR Executive,98293,0 +97086,Male,51,Bachelors,16,41,62,34,74,0.0,1,70,Urban,Software Engineer,132353,0 +97087,Male,31,Bachelors,1,79,18,53,8,5.0,3,50,Semi-Urban,Manager,125817,0 +97088,Male,28,Masters,14,47,22,84,83,6.0,6,46,Semi-Urban,ML Engineer,124685,0 +97089,Male,38,High School,13,89,42,2,45,4.0,4,79,Urban,Data Analyst,83425,0 +97090,Male,30,Bachelors,10,24,63,57,48,3.0,3,75,Rural,Software Engineer,38519,0 +97091,Male,46,Bachelors,1,23,44,18,94,3.0,0,57,Rural,Software Engineer,80505,0 +97092,Female,50,High School,13,40,60,68,78,7.0,3,16,Semi-Urban,ML Engineer,115627,0 +97093,Male,34,Masters,19,81,85,4,31,3.0,4,45,Urban,ML Engineer,125692,0 +97094,Female,21,Bachelors,10,46,98,65,26,6.0,3,13,Semi-Urban,Manager,68519,0 +97095,Female,35,Diploma,5,71,81,2,4,7.0,2,43,Semi-Urban,Data Analyst,43255,0 +97096,Male,54,Bachelors,18,33,19,12,64,2.0,3,29,Urban,ML Engineer,38043,0 +97097,Male,43,Diploma,14,55,53,50,13,2.0,6,25,Rural,HR Executive,124393,0 +97098,Male,35,Masters,18,68,77,14,48,4.0,0,29,Semi-Urban,Manager,46710,0 +97099,Male,56,PhD,13,15,91,81,80,0.0,4,83,Urban,HR Executive,142440,1 +97100,Female,49,Bachelors,15,0,31,21,97,6.0,3,57,Semi-Urban,Manager,125604,0 +97101,Female,43,Bachelors,18,58,27,95,73,1.0,2,67,Urban,Data Analyst,91976,1 +97102,Male,50,Masters,7,69,95,32,32,0.0,6,64,Semi-Urban,Software Engineer,79549,1 +97103,Male,32,Diploma,17,83,37,59,39,8.0,0,29,Urban,HR Executive,75592,0 +97104,Male,36,Bachelors,3,66,48,60,60,0.0,0,47,Urban,Software Engineer,101293,0 +97105,Female,32,Masters,19,39,1,5,72,0.0,4,65,Rural,ML Engineer,111311,0 +97106,Male,29,PhD,5,20,87,29,90,2.0,5,14,Urban,HR Executive,108891,0 +97107,Male,37,Bachelors,8,45,6,46,29,7.0,6,46,Urban,ML Engineer,87932,0 +97108,Female,46,Bachelors,13,10,82,51,45,6.0,6,84,Urban,Software Engineer,54294,0 +97109,Male,57,Masters,4,59,68,1,58,6.0,0,24,Urban,Manager,39293,0 +97110,Male,36,High School,13,77,5,61,92,2.0,3,64,Urban,Software Engineer,87470,0 +97111,Female,33,PhD,0,91,57,99,81,7.0,0,4,Semi-Urban,Manager,131241,1 +97112,Male,31,Diploma,6,15,69,45,39,9.0,6,57,Semi-Urban,Software Engineer,20631,0 +97113,Male,33,Bachelors,13,54,28,39,15,4.0,1,46,Urban,Manager,100877,0 +97114,Female,32,Bachelors,12,18,31,63,85,3.0,5,45,Semi-Urban,Software Engineer,45938,0 +97115,Male,39,Masters,2,16,40,77,80,8.0,1,55,Semi-Urban,Manager,95300,0 +97116,Female,55,High School,5,32,38,81,71,9.0,0,22,Urban,Manager,118118,0 +97117,Male,45,Masters,19,68,84,53,5,4.0,3,87,Rural,Software Engineer,37608,1 +97118,Male,29,Bachelors,6,46,46,99,61,0.0,6,18,Rural,Manager,70465,0 +97119,Male,28,Masters,5,92,49,32,80,4.0,3,94,Urban,Data Analyst,41995,1 +97120,Male,47,Masters,18,82,76,70,92,4.0,2,10,Urban,Data Analyst,77806,1 +97121,Female,38,High School,18,32,62,14,42,0.0,5,94,Semi-Urban,ML Engineer,146209,0 +97122,Male,21,High School,8,76,47,57,1,5.0,2,85,Semi-Urban,Software Engineer,36097,1 +97123,Male,43,Bachelors,0,73,72,68,61,2.0,5,5,Urban,HR Executive,138906,0 +97124,Female,43,High School,3,51,10,64,12,8.0,4,57,Semi-Urban,ML Engineer,99444,0 +97125,Male,56,Masters,11,75,71,59,9,1.0,7,77,Rural,ML Engineer,129556,1 +97126,Male,44,Masters,0,28,81,67,18,3.0,1,47,Semi-Urban,Manager,110299,0 +97127,Other,55,Bachelors,13,5,0,19,12,6.0,7,48,Urban,Software Engineer,70185,0 +97128,Male,44,High School,14,70,55,69,59,4.0,4,42,Urban,Manager,50980,1 +97129,Female,48,Diploma,4,41,66,50,16,9.0,3,20,Rural,HR Executive,91531,0 +97130,Male,55,Masters,11,90,8,13,92,2.0,3,50,Semi-Urban,Manager,46522,0 +97131,Female,30,Diploma,4,30,72,41,81,6.0,2,80,Rural,ML Engineer,78551,0 +97132,Male,37,Masters,2,29,77,22,86,7.0,5,47,Urban,Data Analyst,29245,0 +97133,Male,47,Diploma,10,42,58,29,51,5.0,7,94,Rural,Manager,96825,0 +97134,Male,48,Masters,10,21,63,72,13,3.0,1,69,Urban,Software Engineer,54257,0 +97135,Female,51,High School,18,26,69,80,15,9.0,3,47,Urban,Manager,28650,0 +97136,Female,55,Diploma,2,98,26,95,46,7.0,3,58,Urban,ML Engineer,79673,1 +97137,Male,54,Bachelors,4,24,59,9,20,4.0,2,37,Rural,Data Analyst,106017,0 +97138,Male,34,PhD,19,92,21,85,39,9.0,2,92,Rural,Data Analyst,40851,1 +97139,Male,21,High School,16,91,84,73,97,9.0,7,89,Urban,Software Engineer,73902,1 +97140,Female,33,Bachelors,12,41,27,41,15,9.0,7,99,Urban,Data Analyst,65163,0 +97141,Male,46,Bachelors,0,89,32,77,46,5.0,5,63,Semi-Urban,ML Engineer,122171,1 +97142,Male,38,Masters,2,31,28,35,20,6.0,3,81,Semi-Urban,Software Engineer,133538,0 +97143,Male,33,Masters,8,7,40,69,70,1.0,4,81,Semi-Urban,Software Engineer,30713,0 +97144,Male,37,PhD,14,13,13,70,93,7.0,3,14,Urban,Manager,140492,0 +97145,Male,45,Bachelors,12,78,89,22,82,0.0,1,53,Urban,Software Engineer,38136,1 +97146,Female,50,Diploma,14,41,54,30,39,9.0,0,42,Rural,HR Executive,138040,0 +97147,Male,29,Bachelors,18,63,73,72,1,7.0,0,20,Urban,Data Analyst,92751,0 +97148,Male,26,Bachelors,1,22,97,35,66,1.0,4,44,Urban,HR Executive,57792,0 +97149,Male,52,Masters,0,95,98,82,96,2.0,3,72,Urban,HR Executive,24170,1 +97150,Female,57,Bachelors,4,10,51,92,22,7.0,1,84,Urban,Manager,64208,0 +97151,Male,29,Bachelors,19,34,10,95,59,1.0,6,87,Semi-Urban,Manager,88323,0 +97152,Male,59,Bachelors,19,11,66,89,87,6.0,1,63,Urban,Manager,43010,0 +97153,Female,51,Diploma,4,1,97,76,19,6.0,4,40,Urban,Data Analyst,118042,0 +97154,Male,35,Bachelors,4,97,73,65,3,3.0,7,27,Urban,Software Engineer,148689,1 +97155,Female,56,Bachelors,14,40,74,64,74,7.0,1,83,Rural,Manager,133161,1 +97156,Male,50,Bachelors,11,11,92,11,89,1.0,0,22,Urban,HR Executive,78860,0 +97157,Male,33,Bachelors,13,35,84,12,15,2.0,1,9,Semi-Urban,Software Engineer,121778,0 +97158,Male,24,Masters,14,63,53,59,99,3.0,6,92,Semi-Urban,ML Engineer,37160,1 +97159,Male,41,Bachelors,5,73,20,85,27,5.0,7,83,Urban,Software Engineer,118204,1 +97160,Female,55,High School,11,23,93,41,2,9.0,7,84,Urban,Manager,118892,1 +97161,Male,23,Bachelors,0,69,9,64,84,8.0,1,81,Urban,Software Engineer,149735,0 +97162,Male,43,Bachelors,18,50,41,63,61,3.0,5,22,Urban,Data Analyst,68654,0 +97163,Male,38,High School,16,47,88,77,85,8.0,2,30,Urban,Software Engineer,106790,1 +97164,Male,22,High School,4,52,34,53,74,5.0,2,36,Urban,HR Executive,90843,0 +97165,Male,21,Diploma,13,18,93,14,76,5.0,2,4,Urban,Data Analyst,88824,0 +97166,Female,53,Diploma,0,99,2,58,11,1.0,4,24,Urban,Manager,87988,0 +97167,Female,54,PhD,4,41,83,37,45,6.0,2,12,Urban,HR Executive,144608,0 +97168,Male,21,Diploma,10,83,86,26,68,9.0,5,16,Rural,ML Engineer,134364,0 +97169,Male,52,High School,1,52,0,14,10,6.0,2,64,Urban,Software Engineer,41204,0 +97170,Male,30,High School,14,52,65,87,75,3.0,1,7,Semi-Urban,Software Engineer,132185,0 +97171,Male,32,Bachelors,3,90,19,79,98,0.0,2,91,Urban,HR Executive,71469,1 +97172,Male,35,Diploma,0,78,68,36,39,7.0,6,10,Urban,Manager,87774,0 +97173,Male,54,Masters,4,51,37,18,94,7.0,2,90,Urban,HR Executive,37645,0 +97174,Male,25,Bachelors,4,2,29,10,92,9.0,6,49,Rural,HR Executive,137932,0 +97175,Male,43,PhD,10,5,79,86,24,0.0,0,63,Urban,ML Engineer,135416,0 +97176,Male,33,Masters,0,68,2,41,1,9.0,2,50,Urban,Software Engineer,118828,0 +97177,Male,25,Bachelors,9,50,46,35,56,2.0,1,23,Urban,Data Analyst,47211,0 +97178,Female,54,Diploma,7,84,55,47,80,4.0,5,70,Urban,Software Engineer,89640,1 +97179,Male,22,Diploma,1,15,93,18,55,3.0,3,96,Urban,HR Executive,69142,0 +97180,Male,28,High School,2,2,48,74,93,6.0,5,92,Urban,ML Engineer,85299,0 +97181,Male,56,PhD,4,20,45,81,67,7.0,5,25,Rural,Software Engineer,120452,0 +97182,Female,48,High School,1,62,61,72,92,5.0,2,61,Semi-Urban,Manager,22651,1 +97183,Male,54,Masters,9,34,10,19,76,9.0,2,71,Urban,HR Executive,55339,0 +97184,Male,29,Masters,3,67,51,14,16,3.0,2,66,Urban,Data Analyst,115483,0 +97185,Male,45,High School,16,56,85,5,45,7.0,4,31,Urban,Manager,117766,0 +97186,Male,21,High School,9,61,95,59,44,0.0,4,97,Urban,Software Engineer,111889,1 +97187,Other,32,Diploma,3,57,93,60,46,9.0,6,74,Urban,Manager,109400,1 +97188,Male,37,Masters,5,64,36,10,5,1.0,5,4,Rural,Data Analyst,61681,0 +97189,Female,26,Bachelors,9,29,69,42,40,3.0,1,53,Semi-Urban,HR Executive,46168,0 +97190,Male,30,High School,19,98,92,18,93,1.0,0,82,Rural,Software Engineer,85183,1 +97191,Male,54,Bachelors,15,90,17,5,52,8.0,4,23,Semi-Urban,ML Engineer,64021,0 +97192,Female,31,Diploma,9,96,82,78,54,2.0,7,50,Urban,Manager,49861,1 +97193,Female,43,Diploma,7,93,10,58,78,8.0,6,95,Rural,Manager,140102,1 +97194,Female,27,Bachelors,18,42,25,60,8,6.0,1,10,Rural,Data Analyst,118211,0 +97195,Male,57,Masters,14,40,65,62,15,5.0,1,57,Urban,ML Engineer,36876,0 +97196,Female,50,High School,11,56,84,40,47,1.0,2,45,Semi-Urban,Manager,29386,0 +97197,Female,43,High School,5,3,32,98,19,8.0,7,44,Urban,ML Engineer,117156,0 +97198,Male,24,Diploma,13,69,89,13,23,1.0,6,19,Semi-Urban,Manager,57870,0 +97199,Male,32,Bachelors,14,95,11,68,60,5.0,4,72,Urban,HR Executive,120371,1 +97200,Male,30,Bachelors,19,1,67,57,94,5.0,3,89,Rural,Software Engineer,64197,0 +97201,Male,28,Diploma,16,36,92,41,91,2.0,7,69,Urban,ML Engineer,97236,1 +97202,Male,28,Diploma,3,8,35,5,17,0.0,5,17,Urban,ML Engineer,60611,0 +97203,Female,30,Bachelors,18,23,32,79,62,9.0,2,21,Urban,Software Engineer,75971,0 +97204,Male,44,Masters,6,10,75,40,39,8.0,1,87,Rural,Data Analyst,103765,0 +97205,Male,58,Diploma,2,3,71,37,92,0.0,6,68,Semi-Urban,HR Executive,39106,0 +97206,Male,51,Masters,8,97,96,44,89,5.0,5,65,Rural,Data Analyst,108891,1 +97207,Female,40,Bachelors,19,58,14,4,45,9.0,4,78,Urban,Data Analyst,97196,0 +97208,Female,29,Bachelors,2,30,49,41,83,7.0,3,88,Semi-Urban,Software Engineer,135441,0 +97209,Male,39,Diploma,12,92,64,2,2,3.0,4,37,Urban,ML Engineer,82730,0 +97210,Female,31,Bachelors,0,80,64,16,1,0.0,6,68,Urban,ML Engineer,36102,0 +97211,Male,33,Diploma,11,56,83,16,65,0.0,5,27,Urban,Manager,37385,0 +97212,Male,45,Bachelors,0,77,28,68,39,2.0,5,54,Semi-Urban,ML Engineer,92467,0 +97213,Female,26,Bachelors,3,25,70,17,55,2.0,4,54,Urban,ML Engineer,58930,0 +97214,Female,28,Diploma,0,81,37,24,61,1.0,1,70,Urban,ML Engineer,49839,0 +97215,Female,52,PhD,6,3,36,74,3,2.0,6,97,Urban,Manager,61039,0 +97216,Female,25,Masters,4,20,98,26,50,6.0,2,65,Urban,ML Engineer,76496,0 +97217,Male,24,Bachelors,3,42,31,60,80,6.0,3,43,Semi-Urban,HR Executive,100548,0 +97218,Male,52,High School,16,90,73,24,84,0.0,1,90,Semi-Urban,Software Engineer,86797,1 +97219,Female,47,High School,18,32,54,79,24,7.0,1,66,Urban,HR Executive,128251,0 +97220,Male,24,Diploma,3,49,99,36,33,7.0,1,69,Urban,Manager,37428,1 +97221,Female,24,Masters,17,23,7,85,40,6.0,3,2,Semi-Urban,Data Analyst,123853,0 +97222,Male,45,PhD,5,84,0,45,66,2.0,5,71,Semi-Urban,Manager,51452,0 +97223,Male,21,Masters,8,20,58,74,53,0.0,4,70,Rural,Software Engineer,61428,0 +97224,Female,48,Diploma,17,81,47,48,12,3.0,4,41,Urban,Data Analyst,33990,0 +97225,Male,48,PhD,0,63,13,62,96,5.0,6,88,Urban,Manager,92063,0 +97226,Male,22,Masters,15,79,30,68,34,3.0,2,8,Rural,ML Engineer,143997,0 +97227,Male,54,PhD,0,47,92,64,69,3.0,5,51,Urban,Software Engineer,132979,1 +97228,Female,30,Bachelors,11,34,54,38,48,7.0,5,10,Urban,ML Engineer,88130,0 +97229,Male,35,Bachelors,19,7,64,63,42,8.0,1,71,Semi-Urban,Software Engineer,112060,0 +97230,Male,28,Diploma,9,89,25,27,95,0.0,5,69,Semi-Urban,Manager,51457,0 +97231,Female,50,Bachelors,6,32,96,96,81,1.0,3,31,Urban,Data Analyst,95592,1 +97232,Male,37,Diploma,4,62,5,5,62,9.0,7,66,Urban,ML Engineer,131953,0 +97233,Male,23,Diploma,0,33,72,94,58,9.0,6,33,Urban,HR Executive,39575,0 +97234,Female,40,Masters,0,91,98,47,42,4.0,7,6,Rural,ML Engineer,99255,1 +97235,Female,49,Diploma,18,93,93,56,9,1.0,5,60,Urban,HR Executive,143658,1 +97236,Male,46,Bachelors,3,8,59,55,56,8.0,6,62,Rural,ML Engineer,92176,0 +97237,Female,35,Diploma,11,95,66,95,90,9.0,1,10,Urban,Software Engineer,88005,1 +97238,Male,40,Bachelors,15,27,17,62,46,9.0,5,58,Rural,Software Engineer,58984,0 +97239,Male,36,Bachelors,18,53,9,57,82,9.0,5,2,Urban,Data Analyst,31123,0 +97240,Male,31,High School,0,82,16,46,51,5.0,0,51,Urban,Software Engineer,82706,0 +97241,Male,38,High School,19,39,41,51,79,7.0,2,47,Urban,ML Engineer,57769,0 +97242,Female,34,Bachelors,0,47,22,39,79,4.0,6,80,Rural,Data Analyst,84110,0 +97243,Female,52,Bachelors,11,18,44,54,4,4.0,2,54,Rural,ML Engineer,133469,0 +97244,Male,42,Diploma,5,23,61,85,29,9.0,5,84,Urban,Manager,103585,1 +97245,Male,35,Diploma,11,71,64,84,82,5.0,0,3,Urban,Software Engineer,148791,0 +97246,Male,49,Bachelors,15,35,79,14,86,0.0,5,91,Rural,Manager,121342,0 +97247,Male,49,Diploma,9,66,35,18,39,8.0,4,81,Semi-Urban,ML Engineer,84431,0 +97248,Male,51,Diploma,7,48,8,54,71,3.0,0,27,Semi-Urban,Data Analyst,20137,0 +97249,Male,51,Diploma,2,91,6,79,68,6.0,3,52,Semi-Urban,HR Executive,110864,0 +97250,Male,39,PhD,11,78,14,51,85,6.0,0,92,Urban,Software Engineer,50744,1 +97251,Male,52,Masters,19,94,62,63,33,6.0,7,57,Urban,Manager,131188,1 +97252,Male,56,PhD,4,69,81,19,13,2.0,5,28,Semi-Urban,ML Engineer,113117,0 +97253,Male,36,High School,6,32,69,20,14,5.0,0,25,Rural,HR Executive,106063,0 +97254,Male,36,Bachelors,3,22,14,44,7,9.0,2,93,Urban,Data Analyst,104996,0 +97255,Female,49,Masters,5,73,38,85,20,2.0,0,73,Urban,Data Analyst,104468,1 +97256,Male,40,High School,12,0,99,47,14,9.0,5,55,Rural,ML Engineer,25462,0 +97257,Male,49,Diploma,19,60,34,95,46,6.0,7,76,Rural,ML Engineer,48528,1 +97258,Female,54,Bachelors,3,72,49,43,74,4.0,5,90,Urban,HR Executive,34273,1 +97259,Male,39,High School,8,59,49,67,12,4.0,3,2,Urban,HR Executive,22421,0 +97260,Female,47,Bachelors,7,6,53,95,42,9.0,6,13,Urban,ML Engineer,23074,0 +97261,Male,45,Diploma,9,49,55,34,24,6.0,2,3,Semi-Urban,Manager,45271,0 +97262,Female,36,PhD,15,45,97,38,95,0.0,2,29,Urban,Data Analyst,66196,0 +97263,Female,39,PhD,9,32,71,40,90,3.0,5,69,Urban,Software Engineer,140216,0 +97264,Female,45,Bachelors,8,55,1,95,81,1.0,6,40,Semi-Urban,ML Engineer,65395,0 +97265,Male,44,Diploma,2,90,94,22,65,5.0,4,8,Urban,Data Analyst,48647,0 +97266,Male,42,Bachelors,16,94,11,69,55,1.0,6,36,Semi-Urban,ML Engineer,37283,0 +97267,Female,24,Diploma,1,63,46,14,9,9.0,4,4,Urban,Manager,66874,0 +97268,Other,27,Diploma,4,73,74,41,64,8.0,6,69,Semi-Urban,ML Engineer,73920,1 +97269,Female,58,Diploma,13,2,9,92,45,5.0,0,1,Urban,ML Engineer,81654,0 +97270,Female,52,Masters,17,98,40,38,37,6.0,0,63,Urban,ML Engineer,44677,0 +97271,Female,42,Bachelors,9,15,89,90,75,8.0,1,29,Urban,ML Engineer,68148,0 +97272,Male,52,Bachelors,13,47,25,10,64,0.0,2,57,Urban,Data Analyst,61804,0 +97273,Female,46,High School,9,34,80,36,85,4.0,2,88,Urban,Data Analyst,133971,0 +97274,Male,50,Bachelors,3,82,5,40,41,2.0,4,32,Rural,Manager,111486,0 +97275,Male,24,High School,3,31,72,27,29,6.0,5,80,Urban,ML Engineer,56273,0 +97276,Female,38,Bachelors,9,75,63,93,73,7.0,3,41,Urban,Software Engineer,59263,1 +97277,Female,29,Bachelors,9,51,22,71,52,2.0,6,26,Urban,ML Engineer,110183,0 +97278,Female,54,Bachelors,15,44,41,76,58,2.0,0,43,Semi-Urban,HR Executive,105691,0 +97279,Male,57,Bachelors,18,22,27,39,27,7.0,5,73,Semi-Urban,Manager,106369,0 +97280,Male,47,High School,2,62,41,22,19,5.0,5,94,Urban,ML Engineer,117641,0 +97281,Female,35,Masters,19,30,21,61,53,3.0,7,95,Semi-Urban,Manager,57934,0 +97282,Male,43,Bachelors,19,48,46,76,19,0.0,7,34,Rural,ML Engineer,91576,0 +97283,Female,23,Bachelors,19,62,60,75,26,2.0,3,68,Urban,ML Engineer,44605,1 +97284,Other,38,Diploma,18,0,85,38,13,2.0,7,74,Urban,ML Engineer,46164,0 +97285,Other,22,Bachelors,16,90,70,21,7,3.0,6,12,Urban,Software Engineer,65170,0 +97286,Male,48,Bachelors,1,85,0,31,53,5.0,2,48,Rural,ML Engineer,101747,0 +97287,Male,41,Bachelors,4,30,85,11,45,5.0,0,55,Rural,Data Analyst,59689,0 +97288,Male,34,PhD,14,49,45,2,57,5.0,5,58,Urban,HR Executive,135097,0 +97289,Male,56,Bachelors,2,15,6,79,1,5.0,1,25,Urban,HR Executive,97942,0 +97290,Female,44,PhD,2,46,91,0,4,0.0,3,74,Urban,Software Engineer,117658,0 +97291,Male,35,Bachelors,12,30,9,87,77,9.0,6,79,Urban,Software Engineer,52029,0 +97292,Male,53,Bachelors,0,54,3,99,71,1.0,0,12,Rural,ML Engineer,101546,0 +97293,Male,36,High School,13,82,81,45,56,4.0,0,30,Semi-Urban,ML Engineer,142222,1 +97294,Male,43,Bachelors,9,89,31,39,9,5.0,5,31,Rural,HR Executive,34169,0 +97295,Female,35,Masters,0,87,39,78,1,1.0,5,74,Urban,Data Analyst,50799,1 +97296,Male,22,Bachelors,15,51,84,13,38,5.0,2,1,Urban,Software Engineer,127492,0 +97297,Male,30,Diploma,3,50,10,39,60,3.0,6,49,Urban,Data Analyst,36759,0 +97298,Male,42,Diploma,12,39,40,19,31,3.0,0,14,Urban,Software Engineer,69970,0 +97299,Male,27,High School,12,78,23,77,76,2.0,7,46,Rural,HR Executive,136284,0 +97300,Female,22,PhD,6,33,50,66,77,2.0,5,66,Urban,ML Engineer,135558,0 +97301,Female,21,Bachelors,7,51,90,94,34,4.0,6,55,Rural,Manager,79320,1 +97302,Male,59,Diploma,5,80,50,28,56,6.0,0,21,Urban,ML Engineer,106420,0 +97303,Other,32,Bachelors,7,29,44,13,19,9.0,2,13,Urban,Data Analyst,24583,0 +97304,Male,34,Diploma,15,84,67,8,19,7.0,3,31,Semi-Urban,Data Analyst,37713,0 +97305,Female,43,Bachelors,7,46,29,4,81,7.0,2,22,Urban,ML Engineer,78490,0 +97306,Female,39,Bachelors,2,59,79,42,40,5.0,3,63,Urban,Software Engineer,81800,1 +97307,Other,26,Bachelors,19,29,89,62,50,2.0,6,18,Rural,Data Analyst,54723,0 +97308,Female,58,Masters,2,16,64,43,49,0.0,7,32,Rural,Manager,69332,0 +97309,Male,56,PhD,3,90,8,39,54,7.0,5,1,Semi-Urban,Software Engineer,47889,0 +97310,Male,45,Masters,2,67,41,81,86,3.0,4,29,Urban,ML Engineer,131201,0 +97311,Female,33,Diploma,13,97,33,12,62,1.0,5,48,Urban,Software Engineer,112411,0 +97312,Female,31,Diploma,11,71,6,32,55,4.0,1,5,Semi-Urban,Manager,143011,0 +97313,Female,28,Bachelors,4,17,9,80,28,5.0,3,27,Urban,Manager,82906,0 +97314,Other,33,Bachelors,16,30,15,92,96,0.0,1,8,Urban,Manager,20302,0 +97315,Male,37,Diploma,2,24,88,73,4,9.0,7,15,Semi-Urban,ML Engineer,79458,0 +97316,Male,47,High School,4,27,16,64,72,1.0,4,82,Rural,Software Engineer,78441,0 +97317,Male,48,Bachelors,15,56,41,64,59,5.0,2,39,Urban,Manager,149469,0 +97318,Male,25,Masters,2,94,1,83,43,8.0,5,21,Semi-Urban,Data Analyst,80712,0 +97319,Male,54,Diploma,4,68,1,5,58,5.0,2,63,Urban,Data Analyst,144667,0 +97320,Female,58,Bachelors,6,83,52,82,31,1.0,1,21,Urban,Software Engineer,51880,0 +97321,Female,53,Masters,3,43,18,7,59,3.0,6,49,Rural,Software Engineer,34113,0 +97322,Male,33,Masters,10,91,91,30,8,3.0,0,27,Rural,Manager,146832,1 +97323,Female,53,Diploma,7,69,79,67,40,4.0,3,29,Urban,ML Engineer,126694,1 +97324,Female,33,Bachelors,13,58,23,52,99,0.0,3,75,Urban,Software Engineer,82030,0 +97325,Male,52,High School,12,75,35,79,51,4.0,7,79,Urban,Manager,32935,1 +97326,Female,37,Bachelors,16,87,81,53,33,2.0,0,19,Urban,Software Engineer,72744,0 +97327,Male,44,Bachelors,10,25,66,54,89,9.0,2,24,Urban,ML Engineer,22477,0 +97328,Male,22,Diploma,8,98,42,68,18,7.0,4,36,Urban,ML Engineer,54535,1 +97329,Female,56,Bachelors,8,66,58,24,17,4.0,7,91,Urban,ML Engineer,39105,0 +97330,Male,28,High School,1,55,20,53,6,1.0,4,36,Semi-Urban,HR Executive,28646,0 +97331,Male,41,Bachelors,5,0,20,75,88,4.0,4,94,Semi-Urban,HR Executive,105783,0 +97332,Male,55,Bachelors,7,38,74,66,47,1.0,7,65,Urban,Software Engineer,34188,1 +97333,Female,53,Bachelors,11,45,51,4,77,0.0,2,10,Urban,Software Engineer,99596,0 +97334,Male,29,PhD,8,44,60,41,65,6.0,3,53,Rural,Manager,104720,0 +97335,Male,27,Bachelors,6,89,95,59,31,3.0,3,82,Urban,Software Engineer,99357,1 +97336,Female,36,High School,11,87,98,55,6,3.0,6,65,Urban,Software Engineer,125208,1 +97337,Female,59,High School,3,39,52,70,90,1.0,7,95,Rural,Software Engineer,29945,1 +97338,Male,46,Bachelors,14,63,53,91,61,0.0,6,35,Urban,HR Executive,65977,1 +97339,Male,55,High School,11,71,21,45,98,5.0,0,5,Urban,Software Engineer,126952,0 +97340,Male,56,Bachelors,0,48,28,62,61,8.0,3,86,Semi-Urban,Software Engineer,38788,0 +97341,Female,33,Masters,7,70,17,26,34,3.0,1,58,Urban,Manager,146894,0 +97342,Female,21,Diploma,8,97,20,84,68,5.0,7,45,Urban,Data Analyst,139256,1 +97343,Male,45,Bachelors,13,60,46,41,9,2.0,1,92,Urban,ML Engineer,117413,1 +97344,Male,29,Bachelors,11,12,96,18,6,7.0,1,17,Urban,Data Analyst,105595,0 +97345,Female,28,Bachelors,8,52,69,39,78,0.0,0,49,Semi-Urban,ML Engineer,69980,0 +97346,Female,49,Masters,18,79,45,2,6,5.0,1,7,Urban,ML Engineer,92965,0 +97347,Male,30,Bachelors,8,29,71,90,74,4.0,0,87,Urban,Manager,101227,1 +97348,Male,38,Masters,13,81,40,70,90,9.0,3,40,Urban,Software Engineer,140980,0 +97349,Male,49,High School,8,32,48,32,13,6.0,4,50,Urban,HR Executive,66618,0 +97350,Female,48,Masters,2,84,37,87,94,3.0,3,24,Urban,Manager,145138,0 +97351,Male,42,Bachelors,19,53,76,64,74,9.0,2,51,Urban,Data Analyst,68941,1 +97352,Male,47,Diploma,16,40,11,33,11,8.0,1,59,Semi-Urban,Software Engineer,56208,0 +97353,Male,32,Bachelors,5,36,17,58,13,8.0,6,38,Urban,Software Engineer,119818,0 +97354,Other,26,Bachelors,11,25,27,53,71,7.0,1,63,Urban,HR Executive,76916,0 +97355,Male,26,Masters,8,92,57,65,33,4.0,6,52,Semi-Urban,HR Executive,41924,1 +97356,Male,26,High School,0,69,7,48,30,5.0,1,28,Semi-Urban,Data Analyst,113645,0 +97357,Male,54,Bachelors,17,71,94,57,27,6.0,2,73,Urban,Manager,91942,1 +97358,Male,59,PhD,3,28,45,8,8,8.0,7,91,Urban,Data Analyst,51016,0 +97359,Male,23,Bachelors,6,61,85,89,99,8.0,6,17,Urban,ML Engineer,35869,1 +97360,Male,28,Bachelors,3,78,15,38,98,5.0,4,85,Semi-Urban,Data Analyst,109496,0 +97361,Male,42,Bachelors,9,5,52,51,87,1.0,6,8,Urban,HR Executive,82883,0 +97362,Female,29,PhD,9,33,6,21,85,0.0,1,14,Rural,ML Engineer,86031,0 +97363,Female,27,Masters,6,7,73,96,93,7.0,3,96,Urban,HR Executive,30098,1 +97364,Female,26,High School,8,93,62,9,57,4.0,2,53,Urban,ML Engineer,43840,0 +97365,Female,30,Diploma,16,83,80,68,34,6.0,5,17,Semi-Urban,Data Analyst,50343,1 +97366,Male,51,Masters,4,60,88,58,77,2.0,7,59,Urban,Manager,91973,1 +97367,Other,31,Bachelors,14,49,92,26,65,0.0,3,24,Rural,Data Analyst,128306,0 +97368,Male,25,Masters,1,87,19,86,50,6.0,1,34,Urban,Software Engineer,123557,0 +97369,Male,46,Masters,14,28,49,49,81,7.0,5,56,Rural,Software Engineer,78389,0 +97370,Female,57,Bachelors,15,26,48,42,11,5.0,4,15,Urban,Data Analyst,72727,0 +97371,Male,34,Bachelors,10,90,8,18,6,8.0,5,95,Rural,Software Engineer,39304,0 +97372,Male,54,High School,5,57,53,88,22,7.0,0,54,Urban,HR Executive,65564,1 +97373,Male,28,Bachelors,14,84,81,20,84,2.0,1,77,Semi-Urban,Manager,130257,1 +97374,Female,59,Diploma,5,48,85,27,22,5.0,0,78,Semi-Urban,Manager,78887,0 +97375,Male,59,Diploma,5,95,31,25,77,8.0,0,72,Rural,ML Engineer,139882,0 +97376,Female,54,Masters,8,69,91,62,44,2.0,0,95,Rural,Manager,86282,1 +97377,Male,36,Bachelors,10,91,42,32,95,7.0,0,31,Urban,Software Engineer,77746,0 +97378,Male,52,Masters,1,98,41,21,87,3.0,0,91,Urban,HR Executive,69497,1 +97379,Male,51,Diploma,16,15,73,90,36,8.0,2,48,Urban,ML Engineer,68709,0 +97380,Male,32,Masters,13,36,30,90,52,4.0,1,29,Urban,ML Engineer,83173,0 +97381,Male,48,Diploma,3,64,69,18,68,0.0,0,30,Urban,Manager,77894,0 +97382,Female,53,Bachelors,7,61,40,44,60,8.0,0,72,Urban,ML Engineer,23488,0 +97383,Male,26,Masters,15,25,39,92,37,7.0,0,84,Rural,ML Engineer,135571,1 +97384,Male,23,Bachelors,2,58,71,55,80,8.0,2,72,Urban,Manager,102331,1 +97385,Female,36,Bachelors,2,75,99,48,50,4.0,0,29,Urban,Data Analyst,54884,1 +97386,Female,54,PhD,5,69,62,3,53,4.0,0,80,Urban,HR Executive,78114,0 +97387,Female,56,Bachelors,15,11,79,38,68,4.0,5,7,Urban,ML Engineer,141177,0 +97388,Female,50,Bachelors,19,31,57,62,62,8.0,1,82,Rural,Data Analyst,87969,0 +97389,Male,25,Bachelors,3,30,80,3,81,6.0,5,90,Semi-Urban,Data Analyst,143381,0 +97390,Male,53,Masters,9,72,41,23,33,1.0,6,82,Semi-Urban,Manager,59635,0 +97391,Male,42,High School,13,89,96,12,5,8.0,2,34,Rural,ML Engineer,112302,0 +97392,Male,48,Masters,14,76,93,65,72,2.0,3,29,Rural,ML Engineer,36222,1 +97393,Male,39,High School,8,55,47,57,71,9.0,5,89,Urban,Software Engineer,111762,1 +97394,Male,45,Bachelors,2,84,50,15,48,0.0,4,88,Semi-Urban,Software Engineer,101658,1 +97395,Female,54,Bachelors,8,65,93,26,55,6.0,7,98,Rural,Software Engineer,110096,1 +97396,Other,45,High School,16,77,31,47,71,5.0,2,62,Semi-Urban,Manager,66049,0 +97397,Female,35,Bachelors,9,45,83,45,77,5.0,1,71,Urban,Software Engineer,109635,1 +97398,Male,55,Bachelors,14,71,15,74,6,4.0,4,29,Urban,Software Engineer,72639,0 +97399,Female,53,Masters,13,48,22,69,9,3.0,5,94,Semi-Urban,Manager,131564,0 +97400,Other,54,Bachelors,13,85,52,79,15,0.0,3,19,Urban,HR Executive,38723,0 +97401,Male,45,Bachelors,11,93,74,56,69,7.0,2,96,Semi-Urban,ML Engineer,51064,1 +97402,Male,40,Bachelors,2,48,92,4,57,9.0,5,14,Urban,Manager,146330,0 +97403,Male,59,Bachelors,3,44,96,86,86,0.0,1,58,Urban,Manager,94055,1 +97404,Female,31,High School,17,95,39,43,36,6.0,3,97,Urban,HR Executive,42195,1 +97405,Male,32,Masters,0,36,16,74,47,0.0,4,96,Rural,Software Engineer,38182,0 +97406,Male,49,Bachelors,15,29,76,53,18,2.0,4,15,Rural,Data Analyst,90988,0 +97407,Male,57,Masters,7,37,71,7,62,9.0,5,39,Rural,ML Engineer,20937,0 +97408,Male,34,Masters,7,95,7,22,7,9.0,2,4,Urban,Data Analyst,104862,0 +97409,Male,45,Masters,0,72,41,85,95,4.0,0,64,Semi-Urban,Software Engineer,63388,1 +97410,Male,35,High School,8,7,92,29,67,3.0,6,56,Urban,Data Analyst,30715,0 +97411,Female,44,High School,18,50,67,29,2,1.0,0,65,Urban,ML Engineer,79704,0 +97412,Female,39,Masters,14,69,63,4,26,3.0,2,45,Urban,Software Engineer,52130,0 +97413,Female,46,Diploma,16,4,44,65,59,4.0,2,17,Semi-Urban,HR Executive,122704,0 +97414,Male,45,Bachelors,14,85,5,99,0,9.0,0,76,Semi-Urban,ML Engineer,49090,1 +97415,Male,21,Masters,11,0,18,70,80,1.0,4,96,Urban,ML Engineer,52272,0 +97416,Female,38,Bachelors,0,37,97,71,95,1.0,7,23,Urban,Manager,39113,0 +97417,Female,56,Masters,4,31,71,39,52,4.0,6,59,Urban,Software Engineer,74703,0 +97418,Female,29,Diploma,14,44,21,53,29,9.0,1,82,Urban,ML Engineer,48112,0 +97419,Female,57,Bachelors,12,62,79,47,36,1.0,1,11,Urban,Software Engineer,77490,0 +97420,Other,57,Masters,17,67,65,19,34,6.0,0,95,Urban,ML Engineer,70621,1 +97421,Other,39,High School,3,41,7,85,34,5.0,7,6,Rural,Software Engineer,129403,0 +97422,Male,40,High School,8,13,91,76,61,4.0,1,22,Rural,Software Engineer,49092,0 +97423,Female,52,High School,3,99,19,92,79,6.0,5,16,Urban,ML Engineer,108059,0 +97424,Other,56,Bachelors,15,29,82,15,35,3.0,1,21,Urban,ML Engineer,115679,0 +97425,Female,42,High School,18,40,28,42,91,4.0,5,47,Urban,Manager,69454,0 +97426,Female,53,High School,1,81,78,4,68,2.0,6,40,Semi-Urban,Manager,61282,0 +97427,Female,34,Diploma,6,41,3,15,82,7.0,1,5,Urban,HR Executive,85100,0 +97428,Male,41,Bachelors,9,75,48,81,6,3.0,1,83,Semi-Urban,Data Analyst,121218,1 +97429,Male,27,Diploma,9,2,1,31,19,7.0,5,80,Urban,Software Engineer,132286,0 +97430,Male,25,Bachelors,6,13,63,26,88,4.0,6,31,Urban,Manager,36529,0 +97431,Female,22,Bachelors,9,70,99,12,38,1.0,5,75,Rural,Data Analyst,131861,1 +97432,Male,37,Bachelors,19,93,17,31,38,0.0,6,75,Urban,Data Analyst,25303,0 +97433,Male,47,Bachelors,10,37,10,54,94,4.0,6,89,Urban,Software Engineer,149824,0 +97434,Female,21,Bachelors,14,98,15,76,37,2.0,1,18,Urban,ML Engineer,126895,0 +97435,Female,51,PhD,2,62,62,46,21,2.0,6,27,Semi-Urban,HR Executive,38426,0 +97436,Female,25,Bachelors,6,62,61,27,85,8.0,0,47,Urban,Data Analyst,77062,0 +97437,Male,36,Bachelors,9,54,93,6,35,4.0,0,49,Rural,ML Engineer,140838,0 +97438,Male,22,Bachelors,15,75,40,45,77,2.0,7,69,Urban,Manager,78819,0 +97439,Female,21,Diploma,10,87,89,51,44,2.0,0,41,Urban,Data Analyst,88703,1 +97440,Female,41,Bachelors,8,73,25,86,7,1.0,3,6,Urban,HR Executive,113774,0 +97441,Male,21,Diploma,19,63,47,17,36,7.0,4,70,Urban,HR Executive,140307,0 +97442,Male,23,Bachelors,18,18,8,41,36,9.0,3,16,Urban,Manager,83700,0 +97443,Male,44,Bachelors,7,47,85,94,63,7.0,4,31,Urban,Software Engineer,142220,1 +97444,Male,21,High School,9,24,44,53,35,9.0,3,90,Rural,HR Executive,135089,0 +97445,Female,22,Bachelors,16,96,29,12,62,3.0,7,33,Semi-Urban,HR Executive,42551,0 +97446,Female,49,Bachelors,9,18,30,63,94,5.0,3,17,Urban,ML Engineer,119925,0 +97447,Male,32,Bachelors,12,53,57,43,18,0.0,7,85,Urban,ML Engineer,38247,1 +97448,Male,47,Bachelors,12,99,23,80,67,2.0,5,85,Urban,HR Executive,143256,1 +97449,Male,55,Bachelors,6,96,15,98,43,9.0,3,54,Rural,HR Executive,123143,1 +97450,Female,37,Masters,4,85,31,16,22,6.0,1,38,Urban,Software Engineer,69364,0 +97451,Female,48,Bachelors,13,41,30,13,57,7.0,2,77,Urban,ML Engineer,57272,0 +97452,Male,45,Bachelors,13,12,56,97,54,1.0,7,50,Urban,Software Engineer,56041,0 +97453,Male,39,Bachelors,16,74,67,22,34,7.0,3,65,Semi-Urban,HR Executive,145880,0 +97454,Female,27,Bachelors,13,16,70,81,49,2.0,1,94,Urban,Data Analyst,145825,1 +97455,Male,27,Masters,17,37,26,11,0,3.0,4,12,Semi-Urban,Manager,62756,0 +97456,Male,52,Diploma,18,31,61,51,82,1.0,3,64,Semi-Urban,ML Engineer,84038,0 +97457,Male,43,Diploma,16,39,9,72,91,6.0,7,0,Urban,ML Engineer,29550,0 +97458,Male,31,Masters,6,20,58,40,23,7.0,1,3,Rural,ML Engineer,135692,0 +97459,Female,28,Bachelors,14,6,59,28,41,6.0,6,99,Urban,Software Engineer,99941,0 +97460,Other,29,Diploma,1,85,5,85,89,6.0,1,21,Urban,HR Executive,131159,0 +97461,Male,43,Diploma,10,17,53,78,63,2.0,2,42,Semi-Urban,HR Executive,134185,0 +97462,Female,31,High School,11,90,23,97,90,3.0,3,20,Semi-Urban,Manager,117116,0 +97463,Other,55,Bachelors,17,58,59,82,6,6.0,4,59,Urban,ML Engineer,72966,1 +97464,Male,42,Bachelors,7,94,79,50,5,1.0,1,80,Urban,Data Analyst,22878,1 +97465,Female,50,Bachelors,9,48,13,91,96,1.0,7,93,Rural,ML Engineer,147344,1 +97466,Male,51,Bachelors,9,19,26,96,69,1.0,1,72,Urban,ML Engineer,90885,0 +97467,Male,22,Masters,13,19,4,66,83,3.0,5,66,Urban,HR Executive,78221,0 +97468,Male,39,Bachelors,0,59,5,26,9,3.0,2,83,Urban,Data Analyst,121647,0 +97469,Female,43,Masters,7,5,21,85,36,0.0,7,22,Rural,Manager,101924,0 +97470,Female,47,Bachelors,16,33,16,85,85,5.0,6,1,Urban,HR Executive,105840,0 +97471,Male,44,Bachelors,19,27,41,22,93,7.0,0,50,Semi-Urban,Software Engineer,90866,0 +97472,Female,51,Masters,2,55,2,99,88,1.0,5,33,Urban,ML Engineer,88706,0 +97473,Male,26,High School,10,97,62,83,91,4.0,2,69,Urban,Software Engineer,65099,1 +97474,Male,40,Bachelors,9,35,81,99,11,5.0,4,90,Rural,HR Executive,30837,1 +97475,Male,29,Diploma,15,52,26,18,78,4.0,2,2,Urban,HR Executive,110414,0 +97476,Female,23,Masters,10,26,54,78,62,9.0,2,64,Semi-Urban,Data Analyst,65800,0 +97477,Male,26,Masters,18,64,17,44,18,0.0,6,59,Semi-Urban,Data Analyst,61812,0 +97478,Male,38,PhD,11,88,3,16,35,3.0,3,64,Urban,ML Engineer,61801,0 +97479,Male,48,PhD,1,98,71,62,8,4.0,5,32,Rural,Software Engineer,96860,1 +97480,Female,51,High School,0,96,17,20,55,4.0,7,11,Rural,Software Engineer,30213,0 +97481,Male,45,PhD,1,4,4,96,21,8.0,1,39,Rural,HR Executive,37311,0 +97482,Male,21,Masters,2,95,95,79,72,8.0,1,73,Urban,HR Executive,27551,1 +97483,Male,31,High School,8,70,85,4,30,3.0,1,84,Semi-Urban,ML Engineer,125708,1 +97484,Male,37,Bachelors,2,32,6,19,48,3.0,5,17,Urban,Manager,25593,0 +97485,Male,44,Diploma,15,74,6,99,24,3.0,3,78,Urban,Manager,67405,1 +97486,Male,36,Diploma,0,94,96,98,33,5.0,2,4,Semi-Urban,Manager,66265,1 +97487,Other,48,High School,6,35,44,67,34,8.0,4,2,Rural,Software Engineer,136709,0 +97488,Female,39,Bachelors,15,44,68,57,5,9.0,6,97,Urban,Manager,25985,1 +97489,Male,47,High School,10,20,37,1,55,8.0,2,6,Urban,HR Executive,129576,0 +97490,Male,32,Masters,6,2,69,30,57,4.0,3,50,Semi-Urban,Manager,28040,0 +97491,Male,37,Bachelors,0,91,90,9,0,3.0,1,67,Urban,HR Executive,131846,1 +97492,Male,58,Masters,10,87,44,13,60,2.0,0,58,Semi-Urban,ML Engineer,132764,0 +97493,Male,45,Masters,6,59,64,14,14,4.0,1,38,Urban,ML Engineer,60602,0 +97494,Female,23,Bachelors,8,3,73,58,28,7.0,7,85,Urban,Manager,100520,0 +97495,Male,54,Diploma,12,96,52,17,83,8.0,0,80,Urban,Software Engineer,117910,1 +97496,Other,42,Diploma,11,80,78,63,12,8.0,4,91,Semi-Urban,Data Analyst,102825,1 +97497,Male,40,Bachelors,18,0,7,11,52,0.0,0,10,Urban,Software Engineer,102901,0 +97498,Male,37,Masters,19,24,84,61,95,1.0,6,91,Urban,HR Executive,121901,1 +97499,Female,48,Bachelors,7,92,27,76,30,7.0,5,23,Semi-Urban,ML Engineer,23834,0 +97500,Other,53,Diploma,19,62,34,59,31,2.0,4,17,Urban,Data Analyst,95250,0 +97501,Female,29,PhD,6,25,95,44,76,9.0,5,17,Urban,Manager,23936,0 +97502,Male,55,Bachelors,5,45,16,72,97,8.0,4,0,Urban,Software Engineer,90368,0 +97503,Male,34,Masters,2,47,30,61,33,1.0,7,63,Urban,Software Engineer,103519,0 +97504,Male,23,High School,9,95,77,52,38,5.0,4,85,Urban,HR Executive,60808,1 +97505,Female,45,High School,0,83,86,19,87,0.0,0,60,Semi-Urban,ML Engineer,31467,1 +97506,Male,29,Masters,0,40,34,93,63,1.0,3,7,Rural,Data Analyst,85134,0 +97507,Male,30,Masters,10,78,47,88,11,3.0,6,89,Semi-Urban,ML Engineer,105476,1 +97508,Male,51,High School,7,71,60,95,47,2.0,0,62,Urban,Data Analyst,76512,1 +97509,Male,46,High School,3,43,13,73,0,5.0,6,29,Urban,Software Engineer,128744,0 +97510,Male,41,Bachelors,9,67,81,62,71,4.0,4,87,Semi-Urban,HR Executive,146851,1 +97511,Female,32,High School,1,46,63,54,91,4.0,1,1,Semi-Urban,Software Engineer,59164,0 +97512,Female,21,Diploma,12,19,75,95,37,4.0,4,81,Semi-Urban,Manager,55520,1 +97513,Female,47,Bachelors,0,29,45,73,59,6.0,0,27,Urban,ML Engineer,25613,0 +97514,Female,49,Bachelors,15,32,78,8,32,6.0,3,10,Urban,Manager,69072,0 +97515,Female,45,Masters,10,64,8,33,33,1.0,2,41,Rural,HR Executive,84867,0 +97516,Male,46,Bachelors,18,64,99,44,66,8.0,4,22,Rural,HR Executive,88019,0 +97517,Female,58,PhD,10,47,49,88,9,9.0,0,9,Urban,ML Engineer,128102,0 +97518,Female,24,High School,9,57,27,48,21,7.0,6,27,Semi-Urban,Data Analyst,63285,0 +97519,Male,29,Diploma,4,32,31,78,92,4.0,2,17,Urban,Data Analyst,128441,0 +97520,Male,52,Masters,2,4,26,67,59,2.0,4,77,Urban,Data Analyst,97940,0 +97521,Female,58,Diploma,13,55,98,24,7,2.0,0,2,Urban,Manager,105685,0 +97522,Male,42,Diploma,4,25,43,44,89,3.0,7,33,Rural,Manager,130267,0 +97523,Female,33,High School,1,80,50,40,39,1.0,2,58,Rural,Manager,117239,0 +97524,Male,26,Bachelors,11,72,35,89,21,5.0,6,4,Rural,Manager,97187,0 +97525,Male,51,Bachelors,1,26,36,27,73,0.0,2,9,Rural,HR Executive,144004,0 +97526,Male,23,Diploma,1,40,10,32,45,0.0,0,85,Rural,Data Analyst,141272,0 +97527,Male,43,Bachelors,9,81,58,36,40,1.0,7,57,Rural,Software Engineer,117932,0 +97528,Female,43,Bachelors,9,3,19,44,37,7.0,2,73,Rural,Software Engineer,22261,0 +97529,Male,24,Bachelors,0,91,92,32,46,2.0,3,48,Semi-Urban,HR Executive,44758,1 +97530,Male,51,Masters,7,47,7,18,58,5.0,2,77,Rural,Data Analyst,143744,0 +97531,Male,58,Diploma,3,15,35,26,78,1.0,7,2,Semi-Urban,Data Analyst,78160,0 +97532,Male,56,PhD,2,94,76,65,9,1.0,7,52,Urban,ML Engineer,73599,1 +97533,Male,44,Masters,13,28,8,15,93,4.0,5,14,Urban,Software Engineer,107145,0 +97534,Male,32,Diploma,11,9,19,8,83,3.0,3,76,Semi-Urban,HR Executive,138688,0 +97535,Female,38,Bachelors,18,53,50,78,59,9.0,0,57,Semi-Urban,Software Engineer,80718,0 +97536,Male,27,High School,16,49,20,4,7,0.0,5,81,Rural,Software Engineer,59724,0 +97537,Male,45,PhD,8,37,16,66,62,3.0,4,81,Urban,Manager,140817,0 +97538,Male,49,High School,11,42,89,89,26,8.0,7,3,Rural,Manager,57665,0 +97539,Male,42,Masters,8,28,62,41,15,6.0,6,83,Urban,ML Engineer,35392,0 +97540,Male,31,Bachelors,10,23,82,7,84,4.0,0,24,Urban,ML Engineer,102379,0 +97541,Female,35,High School,19,73,0,52,4,6.0,5,82,Semi-Urban,Manager,145423,0 +97542,Male,28,Masters,15,18,52,67,6,8.0,0,51,Semi-Urban,Manager,132109,0 +97543,Female,30,Bachelors,11,95,42,70,61,6.0,7,23,Semi-Urban,ML Engineer,56880,0 +97544,Male,31,High School,7,79,43,8,94,0.0,1,48,Urban,Software Engineer,72094,0 +97545,Male,38,Diploma,1,53,24,95,44,7.0,6,86,Rural,ML Engineer,121465,1 +97546,Female,52,Bachelors,13,17,42,77,93,7.0,2,5,Urban,Data Analyst,138969,0 +97547,Female,36,Bachelors,5,13,8,53,23,5.0,0,34,Urban,Manager,60115,0 +97548,Other,40,Bachelors,13,45,43,85,92,0.0,4,88,Urban,Manager,103237,1 +97549,Female,44,Bachelors,19,75,48,6,41,1.0,4,57,Urban,Data Analyst,34138,0 +97550,Male,40,Masters,5,88,60,75,62,7.0,7,55,Semi-Urban,Data Analyst,126151,1 +97551,Male,22,Masters,12,91,81,33,44,9.0,4,50,Urban,Data Analyst,126507,1 +97552,Male,55,Bachelors,3,69,19,67,66,3.0,6,16,Urban,ML Engineer,30024,0 +97553,Male,30,Bachelors,5,80,5,58,83,0.0,3,75,Semi-Urban,Data Analyst,82131,0 +97554,Male,58,PhD,5,50,86,18,90,9.0,4,51,Urban,ML Engineer,129708,0 +97555,Male,55,High School,11,72,82,51,90,9.0,4,5,Urban,ML Engineer,90567,0 +97556,Female,24,Diploma,16,80,71,25,48,2.0,0,43,Urban,Data Analyst,30004,0 +97557,Female,56,High School,11,72,86,20,76,2.0,2,13,Urban,Software Engineer,106707,0 +97558,Male,57,Bachelors,10,46,45,23,19,3.0,2,26,Semi-Urban,Manager,33443,0 +97559,Male,29,Bachelors,19,51,76,74,83,3.0,7,29,Rural,HR Executive,82408,0 +97560,Male,46,Masters,18,59,0,75,54,3.0,6,75,Urban,HR Executive,23487,0 +97561,Female,41,High School,14,24,95,76,80,9.0,7,16,Urban,Software Engineer,50935,0 +97562,Male,46,Masters,3,0,36,62,77,7.0,2,44,Urban,ML Engineer,137582,0 +97563,Female,26,Bachelors,1,21,31,31,47,7.0,1,13,Rural,HR Executive,119224,0 +97564,Male,32,Diploma,16,81,59,63,96,5.0,5,76,Semi-Urban,HR Executive,54712,1 +97565,Male,23,High School,10,50,16,21,31,5.0,5,92,Urban,Manager,48507,0 +97566,Other,38,Diploma,19,11,48,16,31,0.0,5,0,Urban,ML Engineer,111170,0 +97567,Male,29,High School,14,21,24,31,43,8.0,5,48,Rural,ML Engineer,40059,0 +97568,Male,59,Bachelors,11,58,13,81,84,5.0,2,31,Urban,Data Analyst,147989,0 +97569,Male,52,Bachelors,3,15,23,61,82,9.0,1,29,Rural,Manager,140296,0 +97570,Male,22,Bachelors,1,8,26,12,16,4.0,7,32,Semi-Urban,Manager,77574,0 +97571,Male,30,Bachelors,16,30,50,84,34,7.0,0,14,Urban,Software Engineer,126121,0 +97572,Female,39,Bachelors,13,61,40,99,84,6.0,3,38,Semi-Urban,HR Executive,108824,0 +97573,Female,27,Masters,8,58,33,18,19,2.0,4,70,Urban,Manager,71278,0 +97574,Female,46,Masters,6,74,11,41,79,2.0,7,87,Rural,HR Executive,116206,0 +97575,Male,22,Diploma,15,33,49,87,10,1.0,2,37,Urban,HR Executive,80247,0 +97576,Female,49,Diploma,2,18,51,10,79,1.0,3,20,Urban,Manager,51382,0 +97577,Female,22,Bachelors,3,28,25,90,82,8.0,5,56,Semi-Urban,Software Engineer,49034,0 +97578,Male,55,Bachelors,11,26,39,72,20,3.0,1,24,Urban,ML Engineer,145198,0 +97579,Male,46,PhD,3,52,30,48,32,5.0,5,69,Urban,Manager,27786,0 +97580,Male,42,Masters,18,57,71,61,6,4.0,3,79,Semi-Urban,Data Analyst,138403,1 +97581,Male,25,Diploma,12,87,83,28,34,3.0,7,99,Urban,HR Executive,90682,1 +97582,Male,44,Diploma,15,2,76,2,76,0.0,6,43,Rural,ML Engineer,62691,0 +97583,Male,54,Diploma,16,6,84,10,8,2.0,0,70,Rural,Software Engineer,61475,0 +97584,Male,24,PhD,9,18,55,59,90,2.0,3,95,Semi-Urban,HR Executive,36736,0 +97585,Male,21,Bachelors,8,43,5,66,30,7.0,7,47,Urban,Manager,80844,0 +97586,Male,45,Diploma,13,89,43,12,95,1.0,5,13,Rural,Software Engineer,115583,0 +97587,Male,25,Diploma,17,77,2,57,89,2.0,1,43,Rural,Manager,70419,0 +97588,Male,54,Bachelors,10,35,99,90,46,1.0,7,38,Semi-Urban,Data Analyst,105574,1 +97589,Male,38,PhD,9,0,8,87,98,8.0,1,10,Urban,Data Analyst,124814,0 +97590,Male,57,High School,9,61,89,44,4,6.0,4,0,Urban,Manager,27642,0 +97591,Male,32,High School,5,65,9,57,43,3.0,2,53,Urban,Manager,140571,0 +97592,Male,34,Bachelors,12,3,64,88,91,9.0,6,71,Rural,Software Engineer,75039,0 +97593,Male,59,Bachelors,19,20,46,34,83,4.0,3,84,Urban,Manager,64521,0 +97594,Male,34,Bachelors,8,46,7,96,70,1.0,0,79,Semi-Urban,Data Analyst,68226,0 +97595,Female,29,Bachelors,10,43,20,79,25,3.0,4,44,Rural,ML Engineer,99618,0 +97596,Male,24,PhD,0,89,74,11,53,7.0,1,96,Urban,Manager,99309,1 +97597,Male,39,Bachelors,6,11,21,67,29,3.0,4,39,Rural,ML Engineer,96838,0 +97598,Female,43,Diploma,12,85,93,9,10,4.0,3,39,Semi-Urban,ML Engineer,53328,0 +97599,Male,49,Diploma,16,17,93,95,63,9.0,7,77,Urban,Manager,115749,1 +97600,Male,29,Masters,12,95,34,64,32,4.0,3,80,Semi-Urban,Data Analyst,54247,1 +97601,Male,45,Bachelors,10,95,49,84,43,9.0,2,12,Semi-Urban,Data Analyst,22963,1 +97602,Male,37,Masters,7,66,41,83,9,9.0,0,48,Rural,Manager,55726,1 +97603,Male,26,Bachelors,0,87,58,38,74,4.0,2,87,Urban,Software Engineer,63917,1 +97604,Female,56,High School,19,52,59,1,19,8.0,7,90,Urban,Data Analyst,103846,0 +97605,Male,32,High School,17,5,35,83,12,0.0,4,46,Rural,Data Analyst,36755,0 +97606,Male,44,Diploma,10,20,68,39,84,5.0,1,90,Urban,Data Analyst,90375,0 +97607,Female,47,Diploma,13,17,7,72,94,5.0,3,25,Semi-Urban,Software Engineer,103315,0 +97608,Male,35,High School,8,82,57,73,79,9.0,5,12,Rural,Manager,114858,0 +97609,Female,22,High School,3,68,45,15,31,3.0,7,79,Urban,HR Executive,109592,0 +97610,Male,53,Bachelors,0,8,59,43,3,3.0,1,97,Urban,Software Engineer,121797,0 +97611,Male,23,Masters,3,87,78,55,82,6.0,6,29,Urban,ML Engineer,107213,1 +97612,Male,33,Diploma,0,7,48,3,73,4.0,1,13,Urban,Data Analyst,133613,0 +97613,Male,21,Bachelors,7,67,89,98,60,5.0,6,83,Rural,HR Executive,75052,1 +97614,Female,49,Bachelors,6,48,44,6,67,9.0,5,64,Urban,HR Executive,88229,0 +97615,Male,38,High School,0,37,79,45,70,2.0,1,93,Rural,ML Engineer,92862,1 +97616,Male,32,Bachelors,13,25,13,15,24,0.0,2,30,Semi-Urban,Software Engineer,106002,0 +97617,Male,41,High School,4,42,61,62,40,2.0,0,8,Urban,Software Engineer,131255,0 +97618,Female,39,Diploma,4,50,44,0,83,2.0,3,88,Urban,ML Engineer,79016,0 +97619,Male,53,Masters,8,98,54,97,2,9.0,6,29,Urban,Data Analyst,121835,1 +97620,Female,42,Masters,14,37,51,91,28,1.0,7,87,Urban,Manager,139960,1 +97621,Male,50,Diploma,18,36,87,3,39,5.0,1,34,Rural,ML Engineer,50230,0 +97622,Male,59,High School,10,49,9,64,31,2.0,6,36,Urban,ML Engineer,99634,0 +97623,Female,53,High School,17,97,97,37,2,3.0,4,86,Urban,Manager,103511,1 +97624,Male,25,Diploma,8,51,57,12,16,8.0,7,46,Urban,HR Executive,75551,0 +97625,Other,58,Masters,7,42,98,72,42,0.0,4,61,Rural,Software Engineer,145593,1 +97626,Male,37,Bachelors,0,71,13,60,68,3.0,1,49,Urban,Manager,84292,0 +97627,Female,30,Bachelors,6,86,91,31,63,2.0,6,1,Urban,Manager,73958,0 +97628,Male,44,PhD,18,98,69,94,92,6.0,7,39,Urban,Data Analyst,73612,1 +97629,Female,39,Bachelors,0,99,34,20,37,2.0,3,70,Semi-Urban,Data Analyst,58322,0 +97630,Female,57,Bachelors,12,67,61,80,57,0.0,6,21,Urban,Data Analyst,83422,0 +97631,Female,51,PhD,3,86,38,43,10,6.0,2,61,Rural,ML Engineer,72300,0 +97632,Female,21,Bachelors,16,52,53,26,78,5.0,7,87,Urban,ML Engineer,105788,0 +97633,Male,57,Diploma,7,59,47,17,9,3.0,0,52,Semi-Urban,Manager,146027,0 +97634,Female,31,Bachelors,9,76,28,10,47,8.0,7,34,Rural,ML Engineer,124443,0 +97635,Female,27,Bachelors,13,65,97,51,76,3.0,2,93,Semi-Urban,Software Engineer,103774,1 +97636,Female,47,Diploma,13,9,20,40,6,9.0,1,68,Urban,Data Analyst,64315,0 +97637,Male,56,Diploma,15,57,56,89,47,3.0,3,84,Urban,ML Engineer,124086,1 +97638,Female,42,Masters,2,57,5,15,22,8.0,5,67,Semi-Urban,ML Engineer,21956,0 +97639,Female,29,Bachelors,14,40,54,28,21,2.0,5,28,Urban,Software Engineer,50412,0 +97640,Male,39,Masters,16,80,60,77,88,8.0,2,54,Urban,Manager,72252,1 +97641,Male,30,Bachelors,12,40,50,49,6,7.0,1,31,Urban,Data Analyst,136569,0 +97642,Female,54,High School,6,63,35,56,58,8.0,7,20,Semi-Urban,ML Engineer,109394,0 +97643,Female,23,Diploma,3,40,31,27,74,7.0,2,56,Rural,HR Executive,119186,0 +97644,Female,38,Diploma,4,3,54,36,34,4.0,6,15,Urban,HR Executive,85311,0 +97645,Female,59,Bachelors,4,28,29,93,82,3.0,2,56,Urban,Software Engineer,125640,0 +97646,Male,25,PhD,11,36,82,24,41,5.0,6,85,Rural,Data Analyst,23591,0 +97647,Male,49,Masters,1,7,94,14,89,1.0,1,28,Semi-Urban,ML Engineer,83962,0 +97648,Female,27,Diploma,16,76,64,36,96,8.0,4,12,Urban,Data Analyst,24794,0 +97649,Male,44,Diploma,6,68,22,82,6,8.0,2,59,Rural,Data Analyst,56288,0 +97650,Male,22,High School,17,30,18,67,62,8.0,6,30,Semi-Urban,Software Engineer,121449,0 +97651,Male,21,Diploma,3,74,6,35,52,5.0,2,88,Urban,HR Executive,67057,0 +97652,Female,58,High School,10,82,70,35,45,2.0,5,3,Rural,ML Engineer,22655,0 +97653,Other,39,Bachelors,1,1,45,18,40,4.0,6,87,Urban,Software Engineer,147201,0 +97654,Male,55,Masters,9,86,44,49,63,6.0,4,1,Semi-Urban,Manager,95211,0 +97655,Male,22,Diploma,10,37,75,48,8,2.0,7,4,Semi-Urban,HR Executive,132318,0 +97656,Male,55,High School,5,88,77,7,25,2.0,5,24,Urban,Manager,102895,0 +97657,Female,37,Bachelors,10,47,53,89,62,4.0,6,14,Urban,Data Analyst,100465,0 +97658,Male,59,PhD,13,22,92,40,60,3.0,7,88,Semi-Urban,Data Analyst,80519,1 +97659,Male,59,Bachelors,11,7,78,3,14,2.0,2,94,Urban,Data Analyst,35611,0 +97660,Male,54,Bachelors,14,83,46,88,2,5.0,7,25,Urban,Manager,103326,1 +97661,Male,53,Bachelors,3,24,92,62,32,3.0,3,60,Urban,Manager,75517,1 +97662,Male,23,Bachelors,12,52,22,52,10,2.0,3,88,Urban,Manager,70915,0 +97663,Male,25,High School,0,14,96,94,26,6.0,6,10,Semi-Urban,Software Engineer,95992,0 +97664,Male,45,Bachelors,11,26,94,93,72,5.0,1,67,Urban,ML Engineer,86023,1 +97665,Male,45,Bachelors,8,17,35,8,82,3.0,3,52,Urban,Manager,141798,0 +97666,Male,41,Bachelors,10,69,62,43,79,4.0,6,50,Semi-Urban,Software Engineer,119048,0 +97667,Male,27,Bachelors,18,58,45,59,75,5.0,3,8,Urban,Data Analyst,93979,0 +97668,Male,43,Bachelors,10,38,2,28,29,4.0,1,30,Urban,ML Engineer,147490,0 +97669,Male,53,Masters,14,0,29,96,29,1.0,2,80,Urban,Data Analyst,45205,0 +97670,Female,36,Masters,8,7,57,78,2,9.0,2,55,Semi-Urban,ML Engineer,52248,0 +97671,Other,31,Masters,7,45,78,33,10,1.0,5,36,Urban,ML Engineer,45391,0 +97672,Male,54,Masters,12,23,93,12,99,8.0,7,1,Rural,Software Engineer,72285,0 +97673,Male,41,PhD,6,13,80,57,75,1.0,3,46,Urban,Software Engineer,50566,0 +97674,Other,59,Bachelors,3,93,87,70,20,7.0,4,57,Semi-Urban,Data Analyst,112456,1 +97675,Male,40,Masters,8,4,41,86,92,0.0,1,60,Urban,Software Engineer,65371,0 +97676,Male,49,Bachelors,9,56,1,28,7,6.0,3,87,Urban,HR Executive,55562,0 +97677,Female,55,Diploma,18,55,8,11,51,9.0,3,64,Semi-Urban,HR Executive,81005,0 +97678,Female,48,Diploma,6,21,94,61,98,3.0,5,25,Urban,Manager,31802,0 +97679,Female,27,High School,19,83,27,55,67,2.0,5,50,Semi-Urban,Data Analyst,148594,0 +97680,Male,27,PhD,10,75,36,11,96,7.0,7,5,Rural,ML Engineer,97260,0 +97681,Male,29,Bachelors,19,55,1,78,10,2.0,4,35,Urban,HR Executive,61222,0 +97682,Female,37,Diploma,2,64,25,72,39,0.0,4,82,Rural,Data Analyst,43013,1 +97683,Female,25,Bachelors,3,17,48,78,79,2.0,7,55,Semi-Urban,Software Engineer,56756,0 +97684,Female,21,Bachelors,6,20,60,77,42,7.0,6,15,Urban,ML Engineer,115305,0 +97685,Male,41,Bachelors,5,63,95,50,45,0.0,0,62,Urban,Manager,100776,1 +97686,Female,57,Diploma,14,5,41,58,34,9.0,6,29,Urban,Data Analyst,43473,0 +97687,Female,44,Bachelors,5,25,90,63,85,0.0,2,87,Semi-Urban,ML Engineer,127436,1 +97688,Female,49,Diploma,13,91,98,72,27,8.0,3,50,Urban,Data Analyst,103907,1 +97689,Female,54,Masters,16,49,17,39,41,3.0,2,85,Urban,Manager,145677,0 +97690,Male,46,Bachelors,0,99,83,53,47,1.0,0,71,Urban,Data Analyst,61456,1 +97691,Female,26,Masters,7,41,79,80,81,4.0,0,52,Rural,Manager,95509,1 +97692,Male,43,Bachelors,19,96,36,39,4,0.0,2,47,Urban,Software Engineer,107379,0 +97693,Male,53,Bachelors,19,73,90,19,58,0.0,5,26,Urban,ML Engineer,110597,0 +97694,Female,56,Bachelors,3,5,92,87,23,7.0,3,58,Semi-Urban,HR Executive,73099,1 +97695,Female,58,Bachelors,4,47,14,85,49,5.0,0,72,Rural,Manager,87702,0 +97696,Female,48,Bachelors,0,96,77,40,68,2.0,3,15,Urban,Data Analyst,100321,0 +97697,Male,27,Masters,18,7,8,22,49,7.0,4,79,Semi-Urban,Software Engineer,74094,0 +97698,Male,42,Diploma,15,7,96,46,19,1.0,3,69,Urban,Data Analyst,146041,0 +97699,Male,59,Bachelors,13,96,13,10,86,1.0,0,75,Urban,ML Engineer,76286,0 +97700,Male,57,Bachelors,17,73,67,14,59,8.0,3,12,Urban,HR Executive,125886,0 +97701,Male,52,Diploma,6,10,35,71,58,7.0,3,59,Semi-Urban,Data Analyst,90360,0 +97702,Female,35,High School,9,18,1,70,38,8.0,7,36,Rural,Software Engineer,85679,0 +97703,Male,35,Bachelors,5,89,96,88,9,3.0,4,82,Rural,ML Engineer,92583,1 +97704,Male,51,Masters,17,42,56,91,17,3.0,7,0,Rural,HR Executive,64438,0 +97705,Female,33,Bachelors,2,73,64,62,33,7.0,4,65,Rural,Software Engineer,50614,1 +97706,Male,35,Diploma,5,17,61,40,24,6.0,6,22,Semi-Urban,Data Analyst,56190,0 +97707,Female,57,Diploma,6,87,91,62,91,8.0,2,12,Urban,Manager,117552,1 +97708,Female,52,High School,16,22,79,41,71,3.0,5,20,Rural,HR Executive,67665,0 +97709,Female,42,Diploma,15,65,15,91,81,8.0,2,96,Urban,Manager,132130,1 +97710,Male,51,Masters,13,77,8,98,41,5.0,2,68,Rural,Manager,95038,1 +97711,Male,23,Diploma,7,53,28,43,53,6.0,2,31,Semi-Urban,Manager,38190,0 +97712,Male,31,Bachelors,13,60,69,50,57,8.0,5,87,Rural,Software Engineer,23325,1 +97713,Male,56,Diploma,11,15,55,26,79,4.0,6,95,Urban,ML Engineer,20933,0 +97714,Female,23,Bachelors,18,66,92,99,56,1.0,5,54,Urban,HR Executive,140909,1 +97715,Male,42,High School,16,1,4,32,46,6.0,3,65,Urban,Manager,77603,0 +97716,Male,40,PhD,9,73,35,91,78,9.0,5,5,Urban,HR Executive,40849,0 +97717,Male,53,Masters,10,83,96,42,49,3.0,1,92,Urban,Manager,57510,1 +97718,Female,53,Bachelors,16,90,8,90,96,8.0,7,56,Urban,Manager,29817,1 +97719,Male,23,PhD,9,9,53,68,82,3.0,2,78,Urban,Data Analyst,99489,0 +97720,Male,44,Bachelors,14,21,55,88,68,3.0,2,25,Urban,ML Engineer,120790,0 +97721,Male,41,Bachelors,15,71,88,71,76,5.0,3,38,Urban,ML Engineer,40912,1 +97722,Male,28,Diploma,12,59,15,40,72,5.0,2,45,Urban,ML Engineer,144747,0 +97723,Male,51,Diploma,16,79,21,42,31,2.0,7,25,Semi-Urban,ML Engineer,97363,0 +97724,Female,33,High School,10,16,97,42,53,3.0,7,83,Semi-Urban,Software Engineer,83987,0 +97725,Female,30,Bachelors,3,39,59,46,57,3.0,6,66,Semi-Urban,HR Executive,112781,0 +97726,Male,34,Bachelors,0,60,54,45,25,8.0,5,86,Urban,Software Engineer,126441,1 +97727,Male,45,Diploma,10,95,86,94,13,5.0,0,51,Urban,Software Engineer,142601,1 +97728,Male,34,High School,9,47,64,67,87,8.0,3,91,Urban,HR Executive,35162,1 +97729,Female,35,Bachelors,6,42,49,39,63,0.0,4,67,Semi-Urban,Data Analyst,125536,0 +97730,Male,45,Masters,2,6,94,13,25,4.0,1,82,Urban,ML Engineer,72582,0 +97731,Male,22,Masters,1,9,53,25,14,1.0,1,41,Urban,Software Engineer,20306,0 +97732,Male,49,Bachelors,11,47,38,43,32,4.0,4,77,Rural,Software Engineer,103512,0 +97733,Male,50,Bachelors,8,75,54,15,14,1.0,1,9,Urban,Manager,128331,0 +97734,Female,54,Diploma,2,94,32,59,0,4.0,0,15,Urban,Manager,60518,0 +97735,Female,43,Bachelors,18,38,75,87,24,0.0,2,94,Urban,Data Analyst,125438,1 +97736,Male,41,Bachelors,4,70,60,65,49,6.0,7,23,Urban,Manager,42731,0 +97737,Male,25,High School,14,34,67,69,27,3.0,1,3,Urban,Manager,113414,0 +97738,Male,47,High School,6,86,84,90,20,0.0,5,83,Rural,HR Executive,121381,1 +97739,Male,36,Diploma,15,68,17,56,26,3.0,5,22,Urban,HR Executive,37553,0 +97740,Male,33,Masters,14,66,24,15,59,6.0,5,56,Semi-Urban,Manager,133792,0 +97741,Female,50,PhD,10,66,99,55,17,8.0,1,77,Urban,Software Engineer,61285,1 +97742,Male,59,Diploma,17,38,46,23,2,6.0,1,78,Rural,Software Engineer,123320,0 +97743,Male,26,Diploma,9,8,10,68,65,9.0,4,80,Urban,Software Engineer,81547,0 +97744,Other,52,Diploma,18,87,84,8,54,3.0,1,88,Urban,HR Executive,64085,1 +97745,Male,42,Diploma,11,75,46,60,32,9.0,4,6,Urban,Software Engineer,28027,0 +97746,Male,36,Masters,17,65,67,81,24,6.0,6,95,Semi-Urban,Manager,126802,1 +97747,Male,42,High School,19,76,68,13,57,0.0,2,33,Urban,Software Engineer,134131,0 +97748,Female,54,Masters,16,16,90,54,38,1.0,7,88,Urban,Manager,22986,1 +97749,Male,24,Diploma,7,72,24,74,14,7.0,7,9,Urban,Data Analyst,138689,0 +97750,Male,35,Masters,1,86,76,17,16,4.0,4,87,Urban,Data Analyst,51923,1 +97751,Male,33,Bachelors,4,36,84,4,72,7.0,5,11,Semi-Urban,Manager,89062,0 +97752,Male,29,Diploma,8,15,98,96,95,9.0,3,74,Semi-Urban,Data Analyst,67364,1 +97753,Male,30,Bachelors,11,60,87,97,55,3.0,3,2,Urban,Manager,135592,1 +97754,Male,54,Bachelors,12,14,90,19,98,4.0,7,89,Urban,ML Engineer,29041,0 +97755,Female,38,High School,1,17,91,98,17,5.0,5,19,Semi-Urban,Software Engineer,119555,0 +97756,Female,33,Diploma,18,91,48,81,61,9.0,2,89,Rural,Data Analyst,77690,1 +97757,Female,49,Bachelors,17,4,10,62,39,1.0,2,38,Urban,HR Executive,81463,0 +97758,Male,47,Diploma,14,16,9,43,86,1.0,3,47,Urban,Data Analyst,22744,0 +97759,Male,24,Masters,18,31,41,3,50,0.0,0,88,Urban,ML Engineer,29137,0 +97760,Male,24,Diploma,4,40,44,97,70,1.0,3,8,Urban,ML Engineer,130946,0 +97761,Other,27,Diploma,15,58,76,2,30,1.0,2,16,Rural,ML Engineer,35589,0 +97762,Female,55,High School,14,55,30,24,60,7.0,2,22,Urban,ML Engineer,47828,0 +97763,Male,56,Masters,9,34,75,83,24,9.0,2,5,Semi-Urban,Data Analyst,42128,0 +97764,Other,23,Diploma,17,28,98,91,1,4.0,0,80,Urban,Software Engineer,26289,1 +97765,Male,55,Bachelors,13,30,64,9,36,9.0,0,94,Semi-Urban,HR Executive,104593,0 +97766,Male,47,Masters,0,46,31,86,4,0.0,7,19,Urban,ML Engineer,132845,0 +97767,Male,50,High School,17,80,93,59,88,4.0,6,51,Urban,Data Analyst,34591,1 +97768,Male,26,Bachelors,15,64,94,0,11,4.0,6,55,Semi-Urban,ML Engineer,73924,0 +97769,Male,23,Masters,4,33,96,9,12,4.0,0,69,Rural,Software Engineer,120400,0 +97770,Male,26,Diploma,3,53,46,74,9,6.0,6,81,Urban,ML Engineer,97286,1 +97771,Male,39,Diploma,13,71,67,59,59,1.0,0,65,Semi-Urban,Software Engineer,53605,1 +97772,Female,27,Diploma,16,34,54,31,10,2.0,1,28,Semi-Urban,Software Engineer,63196,0 +97773,Male,36,PhD,10,16,8,67,91,5.0,1,32,Rural,Data Analyst,142099,0 +97774,Male,43,Bachelors,10,18,99,42,73,7.0,5,76,Urban,Data Analyst,81683,1 +97775,Other,21,Bachelors,10,15,74,76,51,4.0,0,96,Urban,Data Analyst,120354,1 +97776,Male,53,Masters,7,56,0,79,0,7.0,2,23,Rural,Software Engineer,75006,0 +97777,Male,30,Bachelors,13,11,70,29,24,6.0,5,21,Urban,Data Analyst,30986,0 +97778,Male,49,Bachelors,19,6,72,71,44,3.0,4,43,Rural,Software Engineer,81610,0 +97779,Male,39,Bachelors,10,1,93,92,54,7.0,3,71,Semi-Urban,Software Engineer,122686,1 +97780,Male,32,Bachelors,12,72,31,28,13,9.0,3,68,Semi-Urban,Software Engineer,145785,0 +97781,Male,36,Bachelors,7,0,52,3,73,7.0,2,10,Urban,Software Engineer,115237,0 +97782,Male,23,Bachelors,4,14,87,63,44,3.0,3,90,Rural,ML Engineer,142347,1 +97783,Female,37,Diploma,14,70,13,36,28,9.0,6,51,Rural,Manager,39563,0 +97784,Female,37,Bachelors,5,46,40,45,74,1.0,2,64,Urban,ML Engineer,123500,0 +97785,Male,29,Bachelors,2,27,97,16,87,8.0,4,39,Semi-Urban,ML Engineer,66057,0 +97786,Male,34,Masters,18,8,29,59,42,9.0,2,56,Semi-Urban,Manager,101046,0 +97787,Female,36,PhD,17,95,13,68,82,4.0,6,23,Urban,Data Analyst,125404,0 +97788,Male,43,Bachelors,3,84,67,67,27,1.0,1,9,Semi-Urban,Manager,133068,0 +97789,Female,57,Bachelors,15,97,11,59,68,9.0,6,57,Urban,Data Analyst,51984,0 +97790,Male,43,Masters,1,72,17,68,27,6.0,7,62,Urban,Manager,85136,0 +97791,Female,54,High School,4,78,88,39,46,9.0,7,78,Urban,Data Analyst,30651,1 +97792,Male,35,Diploma,7,54,39,64,9,8.0,1,39,Rural,Data Analyst,50705,0 +97793,Female,49,PhD,18,2,34,90,81,6.0,2,32,Semi-Urban,ML Engineer,69172,0 +97794,Male,47,Bachelors,3,37,12,29,83,1.0,0,28,Semi-Urban,Software Engineer,106111,0 +97795,Male,22,Diploma,3,48,9,75,34,7.0,5,30,Urban,HR Executive,82216,0 +97796,Male,58,Bachelors,8,14,53,42,70,4.0,4,21,Semi-Urban,Manager,127707,0 +97797,Male,42,High School,18,22,44,30,9,0.0,3,74,Rural,HR Executive,131372,0 +97798,Female,41,Masters,9,94,97,63,9,4.0,2,60,Urban,Data Analyst,31162,1 +97799,Male,25,Masters,3,77,49,95,48,2.0,1,30,Semi-Urban,Software Engineer,104373,1 +97800,Male,30,High School,11,54,66,39,2,4.0,3,12,Urban,Manager,31066,0 +97801,Male,47,Masters,12,9,31,93,43,2.0,1,72,Urban,Manager,89800,0 +97802,Female,49,Masters,13,80,31,23,23,7.0,3,85,Semi-Urban,Software Engineer,148271,0 +97803,Female,56,Masters,7,24,17,78,37,5.0,6,63,Urban,HR Executive,30677,0 +97804,Male,52,Bachelors,10,4,83,43,43,1.0,4,97,Semi-Urban,HR Executive,53456,0 +97805,Male,45,Bachelors,8,33,15,0,94,6.0,6,97,Urban,Manager,37531,0 +97806,Male,30,Diploma,15,83,85,44,25,5.0,7,11,Urban,HR Executive,84446,0 +97807,Female,39,Bachelors,17,46,61,27,63,0.0,2,47,Rural,Software Engineer,83050,0 +97808,Male,31,Bachelors,1,67,40,82,66,8.0,7,35,Semi-Urban,Data Analyst,56512,0 +97809,Male,49,PhD,15,35,41,21,48,3.0,2,32,Rural,Software Engineer,57938,0 +97810,Male,24,Diploma,0,89,89,27,30,9.0,4,50,Urban,Manager,37943,1 +97811,Male,38,PhD,16,93,72,59,55,7.0,2,87,Urban,Manager,131927,1 +97812,Female,43,Diploma,5,88,2,90,82,8.0,7,16,Urban,Software Engineer,63847,0 +97813,Male,59,Masters,10,84,18,1,20,7.0,6,46,Semi-Urban,Data Analyst,129686,0 +97814,Male,48,Bachelors,14,98,4,34,19,1.0,3,2,Urban,Data Analyst,102305,0 +97815,Female,44,Bachelors,13,53,0,28,92,8.0,6,32,Urban,ML Engineer,144702,0 +97816,Female,47,Bachelors,4,21,46,60,78,6.0,5,24,Rural,Data Analyst,122383,0 +97817,Male,51,Bachelors,13,52,87,62,56,8.0,2,63,Urban,ML Engineer,66800,1 +97818,Female,53,Bachelors,16,77,67,92,67,6.0,0,75,Urban,ML Engineer,96123,1 +97819,Male,53,Diploma,5,29,14,43,94,6.0,3,16,Urban,Software Engineer,125575,0 +97820,Male,44,High School,2,91,43,88,28,1.0,1,99,Semi-Urban,Manager,133523,1 +97821,Female,33,High School,16,72,94,58,85,5.0,3,26,Urban,Software Engineer,83367,1 +97822,Male,47,Bachelors,0,77,2,88,92,3.0,4,34,Urban,Software Engineer,131826,0 +97823,Male,40,Diploma,7,37,58,58,8,4.0,5,91,Semi-Urban,Data Analyst,71412,1 +97824,Male,22,Masters,12,62,87,55,22,8.0,0,50,Rural,Software Engineer,109623,1 +97825,Male,30,Masters,7,98,51,13,21,7.0,3,87,Semi-Urban,Software Engineer,138988,1 +97826,Male,23,High School,0,73,19,44,92,2.0,2,11,Rural,Manager,127910,0 +97827,Male,24,High School,1,45,92,16,31,1.0,5,28,Semi-Urban,Manager,26950,0 +97828,Male,47,Masters,15,96,40,8,11,9.0,7,91,Urban,Software Engineer,126691,1 +97829,Male,22,Bachelors,8,3,49,75,23,4.0,5,65,Urban,Software Engineer,109132,0 +97830,Male,49,Bachelors,7,71,11,0,80,7.0,0,12,Urban,Software Engineer,135183,0 +97831,Female,26,Diploma,17,25,21,64,38,3.0,7,15,Urban,ML Engineer,97531,0 +97832,Male,28,Bachelors,8,29,54,80,98,2.0,2,79,Urban,Manager,22511,1 +97833,Female,27,Bachelors,17,76,50,27,38,7.0,7,61,Rural,Manager,23307,0 +97834,Male,35,High School,14,78,59,68,52,8.0,3,34,Urban,Data Analyst,143424,1 +97835,Male,50,Bachelors,16,66,33,85,32,6.0,1,16,Semi-Urban,HR Executive,63530,0 +97836,Male,51,Diploma,4,92,96,18,5,3.0,1,97,Rural,Software Engineer,47404,1 +97837,Male,30,Masters,4,18,51,74,4,4.0,7,53,Urban,Data Analyst,122077,0 +97838,Female,43,Bachelors,3,21,21,22,3,3.0,6,30,Rural,ML Engineer,64206,0 +97839,Male,42,Bachelors,11,7,7,40,30,6.0,0,26,Semi-Urban,ML Engineer,141474,0 +97840,Male,38,Bachelors,5,59,20,32,56,7.0,0,57,Urban,Data Analyst,98078,0 +97841,Male,26,Diploma,0,8,25,45,92,3.0,4,37,Urban,Software Engineer,80945,0 +97842,Male,24,Bachelors,19,27,22,9,33,0.0,5,47,Urban,Data Analyst,41852,0 +97843,Female,53,Bachelors,8,79,96,75,54,7.0,5,37,Urban,HR Executive,51448,1 +97844,Male,40,High School,14,85,82,11,22,9.0,5,0,Semi-Urban,ML Engineer,126595,0 +97845,Male,47,Masters,16,13,63,30,62,5.0,1,34,Urban,Manager,84545,0 +97846,Female,27,Bachelors,17,71,68,67,92,3.0,7,28,Urban,ML Engineer,62860,0 +97847,Male,45,Diploma,7,0,98,14,79,0.0,2,88,Urban,ML Engineer,76144,0 +97848,Male,53,Bachelors,6,5,85,5,91,3.0,5,22,Rural,Software Engineer,37838,0 +97849,Male,29,Bachelors,16,28,56,23,64,2.0,6,87,Urban,Software Engineer,25567,0 +97850,Male,21,Diploma,13,18,61,84,57,5.0,4,64,Urban,Data Analyst,93370,0 +97851,Male,43,Bachelors,17,98,29,11,33,9.0,4,75,Urban,ML Engineer,39446,0 +97852,Male,46,Bachelors,19,6,50,88,19,9.0,3,98,Urban,Data Analyst,40858,1 +97853,Female,49,Bachelors,1,27,89,30,44,0.0,7,58,Urban,Manager,133685,0 +97854,Female,24,Bachelors,14,5,48,17,96,9.0,2,2,Urban,HR Executive,141274,0 +97855,Male,41,Masters,6,35,84,30,71,3.0,1,70,Urban,ML Engineer,106151,0 +97856,Male,35,Bachelors,9,13,40,31,90,7.0,4,25,Urban,ML Engineer,105835,0 +97857,Other,48,High School,4,49,18,44,46,4.0,6,35,Rural,Manager,25063,0 +97858,Female,53,Bachelors,12,69,67,45,85,0.0,4,0,Semi-Urban,HR Executive,126247,0 +97859,Male,30,Masters,14,47,29,66,67,0.0,0,45,Rural,Data Analyst,29668,0 +97860,Male,28,Masters,4,28,11,48,72,4.0,1,7,Semi-Urban,Manager,26102,0 +97861,Male,21,Bachelors,16,83,89,52,7,1.0,2,82,Semi-Urban,HR Executive,29117,1 +97862,Male,54,High School,2,58,0,92,94,6.0,6,84,Rural,Data Analyst,114217,0 +97863,Female,56,Bachelors,13,29,13,69,63,4.0,5,70,Urban,Data Analyst,101201,0 +97864,Female,42,Masters,18,24,46,51,48,2.0,6,86,Urban,Software Engineer,142614,0 +97865,Other,33,Masters,1,41,90,88,25,6.0,3,59,Urban,HR Executive,121317,1 +97866,Male,40,Bachelors,14,27,55,37,30,5.0,3,59,Semi-Urban,Software Engineer,79652,0 +97867,Male,41,High School,2,73,69,81,43,7.0,4,11,Urban,HR Executive,81693,0 +97868,Male,31,Bachelors,4,91,39,72,17,0.0,7,31,Urban,HR Executive,141226,0 +97869,Male,24,Diploma,5,69,44,53,3,2.0,2,0,Urban,Software Engineer,57773,0 +97870,Female,39,Bachelors,14,66,21,50,64,5.0,0,11,Urban,HR Executive,49777,0 +97871,Male,47,Diploma,18,66,49,86,18,1.0,0,72,Urban,Software Engineer,50548,1 +97872,Female,45,Bachelors,9,31,40,5,76,3.0,1,87,Semi-Urban,Manager,135221,0 +97873,Female,47,PhD,18,11,57,79,95,8.0,4,22,Semi-Urban,HR Executive,100034,0 +97874,Male,59,Diploma,17,75,29,77,80,3.0,5,82,Semi-Urban,HR Executive,34356,1 +97875,Female,56,High School,2,85,80,80,43,0.0,1,10,Rural,Data Analyst,113168,1 +97876,Male,34,Masters,2,10,65,84,10,4.0,7,3,Rural,ML Engineer,122654,0 +97877,Male,24,Bachelors,14,74,68,9,86,3.0,7,53,Urban,HR Executive,97948,0 +97878,Other,53,Masters,17,2,21,94,8,9.0,2,25,Semi-Urban,ML Engineer,84440,0 +97879,Male,33,Masters,17,22,41,21,51,2.0,1,4,Semi-Urban,HR Executive,132865,0 +97880,Male,47,Masters,0,98,47,41,40,2.0,5,70,Rural,ML Engineer,141573,1 +97881,Male,39,PhD,2,53,87,6,39,8.0,7,17,Urban,Software Engineer,104399,0 +97882,Female,58,Bachelors,16,14,81,3,64,8.0,7,30,Semi-Urban,HR Executive,103117,0 +97883,Other,23,Bachelors,0,99,22,76,44,1.0,5,44,Semi-Urban,Data Analyst,81483,1 +97884,Female,57,Diploma,17,64,74,72,84,9.0,6,52,Urban,HR Executive,135590,1 +97885,Male,42,Diploma,13,14,19,34,29,5.0,1,59,Urban,HR Executive,145346,0 +97886,Female,25,Bachelors,15,13,31,21,99,6.0,2,93,Urban,Software Engineer,81102,0 +97887,Male,57,Masters,8,17,82,27,28,2.0,0,54,Urban,Software Engineer,136709,0 +97888,Male,45,Diploma,18,55,80,71,34,6.0,1,45,Semi-Urban,HR Executive,72639,1 +97889,Male,31,Diploma,3,51,71,42,13,2.0,6,26,Urban,ML Engineer,53605,0 +97890,Male,27,Bachelors,16,0,60,0,86,4.0,0,8,Urban,HR Executive,78472,0 +97891,Female,57,PhD,17,31,49,48,93,8.0,7,8,Semi-Urban,ML Engineer,131764,0 +97892,Other,36,Diploma,12,41,24,59,16,5.0,5,10,Rural,Data Analyst,139165,0 +97893,Male,59,Bachelors,17,27,9,39,93,9.0,5,78,Semi-Urban,HR Executive,139320,0 +97894,Male,51,Masters,4,50,36,1,20,3.0,0,23,Semi-Urban,ML Engineer,42366,0 +97895,Other,34,Bachelors,12,34,43,42,96,6.0,6,88,Rural,Manager,96389,0 +97896,Female,37,Masters,13,87,36,52,44,7.0,3,0,Urban,HR Executive,38886,0 +97897,Male,53,Bachelors,0,41,35,99,99,5.0,7,5,Rural,Data Analyst,76418,0 +97898,Male,57,Diploma,11,44,72,11,83,8.0,0,24,Urban,HR Executive,51796,0 +97899,Female,51,High School,13,42,64,24,75,7.0,4,90,Urban,Data Analyst,104137,0 +97900,Male,40,Bachelors,19,14,64,71,92,6.0,2,20,Semi-Urban,Software Engineer,91322,0 +97901,Female,34,Bachelors,3,17,25,57,69,7.0,6,72,Rural,ML Engineer,109910,0 +97902,Male,28,Bachelors,19,1,43,69,95,0.0,0,60,Rural,HR Executive,26568,0 +97903,Female,54,Bachelors,3,32,91,77,0,3.0,5,87,Urban,Data Analyst,147170,1 +97904,Male,53,Diploma,1,99,43,32,7,6.0,7,89,Urban,Manager,20049,1 +97905,Other,22,High School,4,18,63,0,14,6.0,7,95,Rural,HR Executive,118565,0 +97906,Male,54,High School,0,13,71,35,0,7.0,4,31,Urban,Manager,91864,0 +97907,Other,34,Masters,3,44,12,26,85,7.0,5,33,Rural,Software Engineer,82177,0 +97908,Male,26,Diploma,3,98,84,78,66,8.0,7,63,Urban,ML Engineer,144152,1 +97909,Male,47,Masters,2,71,32,76,4,9.0,4,49,Urban,Software Engineer,92733,0 +97910,Other,35,Diploma,1,26,32,73,19,5.0,2,10,Rural,Software Engineer,47192,0 +97911,Female,59,High School,0,46,20,12,96,9.0,5,93,Urban,Manager,74541,0 +97912,Female,35,Masters,16,64,76,5,15,9.0,1,96,Semi-Urban,Software Engineer,89003,1 +97913,Male,37,Diploma,7,61,34,96,40,2.0,7,56,Urban,HR Executive,90391,1 +97914,Male,34,Diploma,0,35,75,87,17,4.0,5,31,Urban,Manager,64295,0 +97915,Male,32,High School,15,4,31,61,58,0.0,5,39,Urban,ML Engineer,29213,0 +97916,Female,47,Bachelors,4,52,51,20,60,9.0,0,77,Urban,HR Executive,106628,0 +97917,Male,44,Bachelors,15,37,31,65,10,0.0,5,38,Urban,Data Analyst,26891,0 +97918,Female,48,Masters,10,24,85,40,89,6.0,6,62,Urban,ML Engineer,129074,0 +97919,Female,38,Bachelors,0,72,50,42,83,2.0,2,93,Urban,Manager,52844,1 +97920,Male,56,Bachelors,12,36,98,90,6,6.0,0,23,Rural,ML Engineer,127418,1 +97921,Female,22,Bachelors,2,94,45,75,76,6.0,6,28,Semi-Urban,ML Engineer,77673,1 +97922,Female,42,Bachelors,11,40,60,47,71,8.0,3,29,Urban,Manager,147125,0 +97923,Female,38,Bachelors,16,96,92,50,51,3.0,3,9,Rural,Software Engineer,90627,1 +97924,Female,48,Masters,7,97,26,31,37,1.0,5,37,Urban,Manager,140560,0 +97925,Male,50,High School,0,72,82,34,30,3.0,5,44,Urban,HR Executive,84279,0 +97926,Male,45,Bachelors,1,94,33,85,21,4.0,5,99,Semi-Urban,Software Engineer,38683,1 +97927,Female,39,High School,6,27,27,58,28,6.0,6,64,Rural,HR Executive,43699,0 +97928,Female,48,PhD,12,57,70,21,75,4.0,4,65,Semi-Urban,Software Engineer,88299,0 +97929,Male,55,Diploma,2,25,83,48,45,0.0,3,70,Semi-Urban,HR Executive,51573,0 +97930,Other,34,High School,2,89,98,87,61,1.0,3,64,Semi-Urban,ML Engineer,91714,1 +97931,Female,55,Diploma,17,18,98,73,75,8.0,4,16,Semi-Urban,ML Engineer,64583,0 +97932,Female,38,Bachelors,3,37,99,7,46,9.0,6,94,Urban,Data Analyst,91848,0 +97933,Male,51,Masters,17,83,13,0,55,7.0,7,7,Urban,Manager,34806,0 +97934,Male,23,Bachelors,18,76,33,8,5,8.0,1,10,Semi-Urban,Manager,98578,0 +97935,Male,40,Diploma,15,82,5,97,84,3.0,6,6,Urban,Data Analyst,133886,0 +97936,Male,48,High School,14,60,75,87,32,0.0,1,75,Semi-Urban,HR Executive,123373,1 +97937,Female,31,Bachelors,6,13,16,87,95,5.0,3,59,Urban,Manager,142607,0 +97938,Male,24,High School,18,8,31,65,48,7.0,3,59,Urban,Data Analyst,96710,0 +97939,Female,32,Bachelors,13,96,47,94,0,0.0,2,86,Urban,HR Executive,92799,1 +97940,Female,40,Bachelors,2,72,64,86,65,7.0,4,79,Urban,Manager,145221,1 +97941,Male,59,Masters,7,28,48,79,92,3.0,0,23,Urban,ML Engineer,22457,0 +97942,Male,56,PhD,19,37,22,33,81,2.0,3,37,Semi-Urban,Data Analyst,53269,0 +97943,Male,27,High School,15,36,88,43,14,1.0,3,17,Urban,Data Analyst,110244,0 +97944,Female,49,Bachelors,3,86,58,56,27,3.0,6,94,Semi-Urban,HR Executive,25381,1 +97945,Male,43,Bachelors,3,93,33,99,40,9.0,4,10,Semi-Urban,ML Engineer,56464,1 +97946,Female,52,Bachelors,11,69,81,51,95,1.0,6,3,Urban,Software Engineer,30197,0 +97947,Male,30,Bachelors,12,59,57,92,98,1.0,7,68,Rural,Data Analyst,145571,1 +97948,Male,37,Diploma,10,68,2,42,34,5.0,0,67,Urban,Software Engineer,44196,0 +97949,Male,43,Masters,0,25,39,38,26,9.0,0,57,Urban,Data Analyst,28770,0 +97950,Male,33,Bachelors,1,0,36,53,41,5.0,7,54,Urban,ML Engineer,72897,0 +97951,Male,49,Diploma,0,93,92,54,55,0.0,7,98,Urban,ML Engineer,65831,1 +97952,Male,42,Bachelors,14,18,57,57,96,8.0,3,59,Rural,HR Executive,80943,0 +97953,Male,41,Bachelors,18,67,52,74,34,3.0,0,80,Semi-Urban,HR Executive,21294,1 +97954,Male,28,Masters,2,57,92,36,86,1.0,7,26,Urban,Data Analyst,123992,0 +97955,Male,32,PhD,14,30,89,71,84,1.0,2,75,Urban,HR Executive,53863,1 +97956,Male,44,Bachelors,10,97,5,68,97,8.0,0,17,Rural,Manager,110253,0 +97957,Male,38,Diploma,18,18,95,63,98,5.0,0,71,Urban,HR Executive,56762,1 +97958,Male,43,Bachelors,13,95,39,75,48,9.0,4,8,Semi-Urban,Data Analyst,123579,0 +97959,Male,49,Masters,10,60,19,3,27,0.0,1,54,Urban,ML Engineer,125068,0 +97960,Other,48,Diploma,18,24,39,70,85,8.0,1,51,Rural,Data Analyst,71339,0 +97961,Male,52,Masters,3,49,19,4,29,7.0,4,20,Rural,Software Engineer,45949,0 +97962,Female,54,Bachelors,0,76,64,21,41,3.0,0,39,Rural,Manager,133375,0 +97963,Male,45,High School,8,60,96,65,67,0.0,1,67,Rural,ML Engineer,144894,1 +97964,Male,58,Diploma,13,70,34,84,33,9.0,0,91,Urban,Manager,68661,1 +97965,Female,52,Bachelors,17,24,4,57,57,5.0,0,34,Rural,Manager,77277,0 +97966,Male,23,Masters,14,5,28,51,91,1.0,5,40,Urban,Manager,145148,0 +97967,Male,59,Diploma,0,38,29,55,74,5.0,4,5,Urban,Software Engineer,94103,0 +97968,Male,45,High School,7,41,14,61,41,6.0,7,27,Semi-Urban,HR Executive,48326,0 +97969,Male,26,High School,17,13,67,33,56,5.0,3,76,Semi-Urban,ML Engineer,42332,0 +97970,Female,56,Bachelors,14,87,21,37,2,1.0,1,64,Urban,Manager,94272,0 +97971,Female,30,Masters,10,45,21,45,60,5.0,3,14,Semi-Urban,ML Engineer,144184,0 +97972,Female,33,Masters,18,37,75,62,65,0.0,1,11,Urban,ML Engineer,46458,0 +97973,Male,42,Bachelors,16,48,20,34,97,3.0,5,85,Urban,Data Analyst,66716,0 +97974,Female,39,Diploma,14,23,74,25,97,2.0,6,94,Urban,Manager,74866,0 +97975,Female,27,Diploma,1,82,86,15,48,9.0,0,62,Urban,Manager,33279,1 +97976,Female,45,Bachelors,19,45,33,87,28,0.0,7,83,Semi-Urban,Manager,102938,1 +97977,Male,52,Bachelors,19,40,60,5,61,9.0,6,0,Semi-Urban,Manager,78743,0 +97978,Female,35,Diploma,11,63,0,81,56,5.0,4,11,Urban,Manager,125449,0 +97979,Female,30,Bachelors,2,92,59,87,82,4.0,2,72,Semi-Urban,Manager,85628,1 +97980,Male,55,High School,0,4,63,95,2,7.0,7,21,Rural,Data Analyst,56739,0 +97981,Female,59,Masters,13,72,12,42,38,4.0,3,40,Urban,HR Executive,29664,0 +97982,Female,47,Bachelors,12,62,79,88,10,7.0,4,47,Semi-Urban,Data Analyst,61696,1 +97983,Male,47,Masters,17,82,30,66,18,5.0,0,99,Urban,HR Executive,73325,1 +97984,Male,55,Bachelors,10,38,64,0,11,6.0,4,57,Semi-Urban,Manager,70528,0 +97985,Female,59,High School,14,56,27,52,61,2.0,0,3,Semi-Urban,Data Analyst,131723,0 +97986,Male,40,Diploma,0,58,44,82,55,6.0,1,80,Urban,ML Engineer,100868,1 +97987,Male,55,Bachelors,2,93,58,47,35,7.0,7,17,Urban,ML Engineer,105274,0 +97988,Female,31,Masters,11,20,77,91,93,3.0,3,0,Rural,Data Analyst,60703,0 +97989,Male,55,Bachelors,18,39,50,60,48,0.0,7,43,Urban,ML Engineer,130492,0 +97990,Male,43,High School,13,12,32,68,84,5.0,0,14,Rural,Software Engineer,143649,0 +97991,Female,47,Masters,16,71,30,78,67,1.0,5,11,Urban,Data Analyst,74561,0 +97992,Male,38,Masters,0,41,33,36,70,6.0,4,23,Urban,HR Executive,35394,0 +97993,Male,39,Diploma,1,55,25,2,47,6.0,3,55,Rural,HR Executive,29743,0 +97994,Female,59,Diploma,6,36,82,6,45,0.0,3,21,Urban,Data Analyst,49670,0 +97995,Male,23,Bachelors,11,66,71,80,87,0.0,6,14,Urban,Software Engineer,114593,0 +97996,Male,44,Bachelors,15,30,27,60,12,4.0,7,18,Urban,Manager,147008,0 +97997,Male,48,High School,5,92,1,11,44,1.0,1,84,Urban,Manager,54135,0 +97998,Male,32,Bachelors,9,48,60,77,44,2.0,6,5,Urban,ML Engineer,121891,0 +97999,Male,35,Bachelors,1,67,21,25,61,0.0,7,13,Semi-Urban,Manager,36691,0 +98000,Female,44,Masters,17,50,60,89,44,3.0,1,81,Semi-Urban,ML Engineer,69245,1 +98001,Male,49,High School,16,13,4,37,40,4.0,3,81,Urban,ML Engineer,41959,0 +98002,Male,21,PhD,12,41,83,70,21,9.0,0,40,Semi-Urban,Software Engineer,129411,0 +98003,Male,37,Bachelors,16,32,10,58,88,5.0,7,77,Urban,Software Engineer,68843,0 +98004,Female,37,Masters,0,83,54,48,86,0.0,3,64,Urban,HR Executive,131890,1 +98005,Male,22,Bachelors,3,24,23,65,17,8.0,6,54,Urban,ML Engineer,44358,0 +98006,Male,58,Bachelors,11,11,4,48,30,4.0,7,63,Urban,Software Engineer,107149,0 +98007,Male,58,Bachelors,17,76,85,7,74,7.0,2,32,Semi-Urban,Manager,127482,0 +98008,Male,27,Bachelors,14,10,86,40,78,8.0,0,92,Urban,ML Engineer,21554,0 +98009,Male,34,Diploma,10,80,70,64,39,9.0,3,42,Rural,Data Analyst,36510,1 +98010,Male,29,Bachelors,6,67,81,44,39,7.0,0,18,Urban,Data Analyst,130160,0 +98011,Other,53,Bachelors,11,22,58,81,82,7.0,2,36,Semi-Urban,Manager,57581,0 +98012,Male,29,Bachelors,1,94,94,70,63,9.0,1,12,Urban,Data Analyst,65807,1 +98013,Male,38,Bachelors,19,20,1,53,46,3.0,2,86,Semi-Urban,ML Engineer,47851,0 +98014,Male,35,PhD,1,75,14,8,74,0.0,7,48,Rural,Manager,149591,0 +98015,Male,24,Bachelors,13,32,41,75,59,5.0,7,27,Urban,ML Engineer,46316,0 +98016,Male,24,Bachelors,5,95,81,0,46,2.0,0,49,Semi-Urban,Manager,88220,0 +98017,Male,29,Bachelors,9,11,86,85,37,0.0,1,18,Rural,Manager,115922,0 +98018,Male,57,Diploma,9,19,46,43,3,6.0,0,79,Urban,HR Executive,26439,0 +98019,Male,44,Bachelors,7,26,68,57,72,7.0,5,90,Semi-Urban,Software Engineer,128729,1 +98020,Male,37,High School,14,24,25,30,15,7.0,1,47,Urban,Data Analyst,52602,0 +98021,Female,46,Diploma,4,84,91,84,85,8.0,3,96,Semi-Urban,HR Executive,146745,1 +98022,Male,58,Masters,18,52,73,6,48,0.0,0,77,Urban,ML Engineer,47786,0 +98023,Male,35,Diploma,18,11,96,69,51,7.0,7,84,Urban,Data Analyst,25895,1 +98024,Male,24,Bachelors,12,48,74,10,6,0.0,3,19,Rural,HR Executive,54611,0 +98025,Female,54,Bachelors,16,92,39,14,67,2.0,1,94,Urban,Data Analyst,90021,0 +98026,Female,42,Masters,16,48,70,10,96,6.0,1,5,Semi-Urban,Manager,122216,0 +98027,Female,52,Bachelors,6,73,64,29,76,1.0,1,18,Semi-Urban,ML Engineer,79253,0 +98028,Male,52,Bachelors,10,99,2,44,80,2.0,6,78,Rural,Software Engineer,45477,0 +98029,Female,57,High School,19,49,59,78,5,3.0,4,33,Semi-Urban,ML Engineer,74973,0 +98030,Female,56,Bachelors,0,48,4,11,84,8.0,4,45,Urban,Manager,114684,0 +98031,Female,41,Diploma,9,0,30,3,71,1.0,3,48,Urban,Software Engineer,137775,0 +98032,Female,56,Bachelors,5,56,45,67,43,3.0,0,38,Semi-Urban,Manager,93174,0 +98033,Male,48,Bachelors,5,28,1,26,54,6.0,6,23,Urban,HR Executive,124545,0 +98034,Male,47,High School,6,34,64,57,58,6.0,3,67,Urban,HR Executive,65809,0 +98035,Female,59,Masters,13,60,34,88,70,5.0,2,71,Semi-Urban,HR Executive,91323,1 +98036,Male,31,Bachelors,0,10,31,3,63,3.0,1,90,Urban,Manager,31213,0 +98037,Female,56,Masters,5,92,46,59,11,2.0,1,69,Urban,ML Engineer,40406,1 +98038,Other,54,Masters,13,25,47,27,22,6.0,7,35,Urban,ML Engineer,88926,0 +98039,Male,21,Masters,10,35,72,92,41,6.0,6,5,Rural,ML Engineer,51007,0 +98040,Female,56,Bachelors,19,59,89,14,64,5.0,4,71,Urban,ML Engineer,110963,0 +98041,Other,43,Masters,14,31,77,39,35,1.0,5,69,Semi-Urban,Manager,140146,0 +98042,Male,46,Bachelors,12,96,10,48,43,0.0,4,51,Urban,Manager,67554,0 +98043,Male,46,Diploma,8,91,65,76,47,1.0,1,95,Rural,Manager,60870,1 +98044,Male,57,Bachelors,6,52,3,92,60,9.0,5,51,Urban,Manager,36295,0 +98045,Male,32,High School,16,93,97,92,21,9.0,5,26,Urban,Software Engineer,111136,1 +98046,Female,50,Bachelors,12,57,25,65,53,7.0,7,79,Semi-Urban,Manager,61885,0 +98047,Female,42,High School,15,57,19,73,22,0.0,1,53,Urban,HR Executive,30813,0 +98048,Other,58,Bachelors,2,2,61,41,63,3.0,3,61,Urban,Software Engineer,129169,0 +98049,Male,49,Bachelors,19,30,98,28,8,8.0,4,10,Urban,ML Engineer,103491,0 +98050,Female,56,Masters,16,6,34,0,82,2.0,6,73,Urban,Manager,121495,0 +98051,Female,23,Diploma,7,68,51,53,53,0.0,0,21,Semi-Urban,Data Analyst,68779,0 +98052,Male,30,Diploma,0,90,99,94,23,5.0,5,29,Urban,Data Analyst,49081,1 +98053,Male,33,Bachelors,15,8,12,28,27,1.0,6,84,Semi-Urban,Data Analyst,144385,0 +98054,Female,46,Masters,13,19,48,91,44,3.0,4,8,Semi-Urban,Manager,63373,0 +98055,Male,51,Diploma,0,6,15,50,31,7.0,7,77,Urban,Data Analyst,140931,0 +98056,Female,57,Bachelors,8,31,49,11,59,3.0,6,18,Rural,Data Analyst,72982,0 +98057,Male,53,Diploma,3,0,54,29,13,9.0,4,9,Urban,HR Executive,106394,0 +98058,Male,22,Diploma,14,71,44,19,39,8.0,7,28,Urban,Manager,133302,0 +98059,Female,58,Masters,3,62,88,15,73,6.0,7,41,Urban,Software Engineer,83290,0 +98060,Male,59,Bachelors,17,96,98,72,32,4.0,5,25,Urban,ML Engineer,94324,1 +98061,Male,47,Bachelors,11,69,49,29,70,9.0,0,47,Urban,Manager,72746,0 +98062,Male,27,Masters,8,31,19,42,45,2.0,2,91,Urban,Manager,141962,0 +98063,Male,33,Bachelors,9,17,44,89,25,3.0,7,59,Urban,Data Analyst,43312,0 +98064,Other,51,High School,17,6,79,75,93,8.0,6,87,Rural,Software Engineer,138000,1 +98065,Male,25,Masters,10,64,55,54,93,5.0,5,48,Rural,HR Executive,43685,0 +98066,Male,58,Bachelors,6,75,67,68,60,0.0,3,56,Urban,ML Engineer,67754,1 +98067,Female,56,Masters,16,64,38,6,20,1.0,5,83,Semi-Urban,Data Analyst,37621,0 +98068,Male,24,Bachelors,14,76,73,51,99,5.0,5,12,Semi-Urban,ML Engineer,105003,0 +98069,Male,37,Masters,17,73,69,71,30,3.0,4,10,Urban,Data Analyst,89903,0 +98070,Male,32,Masters,13,87,96,16,56,4.0,6,33,Urban,Data Analyst,143278,0 +98071,Male,35,Bachelors,13,10,26,44,95,5.0,3,60,Urban,ML Engineer,62280,0 +98072,Male,41,High School,1,91,58,17,63,5.0,1,1,Semi-Urban,ML Engineer,79044,0 +98073,Female,48,Bachelors,19,14,98,40,77,2.0,6,28,Rural,Software Engineer,104868,0 +98074,Male,57,Bachelors,16,53,74,63,70,6.0,2,16,Rural,HR Executive,76161,0 +98075,Male,27,Diploma,1,90,13,45,71,9.0,1,38,Urban,Manager,148386,0 +98076,Female,27,Diploma,1,3,2,21,95,6.0,4,53,Urban,Software Engineer,69181,0 +98077,Male,25,Diploma,0,97,22,52,52,6.0,7,21,Urban,Manager,56982,0 +98078,Male,51,Bachelors,11,61,70,75,85,0.0,1,28,Semi-Urban,ML Engineer,40180,0 +98079,Male,37,Bachelors,12,42,20,61,82,6.0,2,9,Urban,Software Engineer,97683,0 +98080,Female,52,High School,1,91,88,55,29,2.0,6,14,Urban,ML Engineer,126489,1 +98081,Male,42,Bachelors,15,94,0,61,60,5.0,3,83,Urban,HR Executive,146854,1 +98082,Male,54,High School,7,27,87,96,14,9.0,4,14,Urban,ML Engineer,99690,0 +98083,Male,30,High School,10,86,32,19,11,2.0,4,54,Semi-Urban,HR Executive,130980,0 +98084,Male,45,Bachelors,4,59,73,22,47,3.0,5,46,Urban,Software Engineer,109447,0 +98085,Male,29,Bachelors,12,33,15,88,33,6.0,3,11,Urban,Data Analyst,116005,0 +98086,Male,31,Bachelors,3,87,8,45,61,9.0,2,41,Urban,Manager,77061,0 +98087,Female,53,Diploma,12,50,3,79,42,4.0,6,56,Urban,Software Engineer,75387,0 +98088,Female,23,High School,13,62,52,25,46,6.0,1,38,Semi-Urban,Software Engineer,41462,0 +98089,Female,26,Bachelors,9,55,69,6,49,8.0,5,39,Semi-Urban,Software Engineer,25119,0 +98090,Male,34,High School,14,31,0,56,72,7.0,2,72,Semi-Urban,Software Engineer,80143,0 +98091,Female,33,Bachelors,18,97,38,58,88,1.0,4,19,Urban,Software Engineer,72498,0 +98092,Male,32,High School,19,20,10,14,69,3.0,6,1,Rural,Manager,135401,0 +98093,Other,44,Diploma,4,96,94,63,11,7.0,2,85,Urban,HR Executive,102132,1 +98094,Male,27,Bachelors,1,93,97,1,47,1.0,4,41,Urban,HR Executive,102135,0 +98095,Male,54,Bachelors,10,2,3,96,28,3.0,4,42,Urban,Software Engineer,139090,0 +98096,Female,28,High School,8,57,24,54,67,2.0,6,15,Urban,ML Engineer,76163,0 +98097,Male,52,Bachelors,6,44,38,93,56,1.0,7,18,Urban,Manager,81686,0 +98098,Female,28,High School,3,91,94,72,87,1.0,2,42,Urban,Data Analyst,46739,1 +98099,Male,30,Diploma,19,24,72,61,40,0.0,5,36,Rural,ML Engineer,103896,0 +98100,Female,29,Bachelors,5,17,42,44,53,1.0,4,75,Urban,Manager,142653,0 +98101,Male,48,Bachelors,12,91,7,70,58,4.0,7,24,Urban,Manager,119925,0 +98102,Male,21,Bachelors,8,10,11,7,42,2.0,3,43,Rural,Manager,99838,0 +98103,Male,51,Masters,12,45,89,12,99,6.0,6,29,Urban,Manager,30924,0 +98104,Female,30,Masters,4,33,6,53,97,6.0,7,30,Urban,Data Analyst,21193,0 +98105,Female,33,Masters,10,13,3,96,34,2.0,3,28,Rural,HR Executive,135944,0 +98106,Female,51,Masters,10,9,82,37,91,6.0,4,9,Urban,HR Executive,93756,0 +98107,Female,28,PhD,1,38,16,61,25,9.0,6,67,Urban,Data Analyst,108956,0 +98108,Male,31,Diploma,7,42,91,16,29,0.0,5,44,Semi-Urban,ML Engineer,89921,0 +98109,Male,57,High School,19,10,97,34,96,9.0,0,0,Rural,HR Executive,131303,0 +98110,Female,56,Bachelors,2,23,95,8,25,5.0,0,39,Urban,Manager,22468,0 +98111,Female,50,Diploma,4,12,20,73,67,1.0,3,41,Urban,Manager,138516,0 +98112,Male,55,Masters,16,38,95,41,44,7.0,7,92,Semi-Urban,Manager,72727,1 +98113,Female,24,Diploma,15,3,24,69,26,9.0,0,64,Urban,HR Executive,113685,0 +98114,Male,53,Diploma,16,62,84,90,19,7.0,0,46,Urban,ML Engineer,34325,1 +98115,Female,22,High School,8,38,40,53,47,2.0,7,83,Semi-Urban,Data Analyst,37323,0 +98116,Male,52,High School,16,43,29,68,70,1.0,5,19,Urban,Data Analyst,62984,0 +98117,Male,33,Bachelors,9,6,1,22,46,4.0,2,44,Urban,Manager,128909,0 +98118,Female,28,Bachelors,11,71,18,11,74,4.0,7,61,Urban,ML Engineer,145496,0 +98119,Male,37,Masters,13,67,22,29,68,3.0,2,54,Urban,Data Analyst,73013,0 +98120,Other,24,Bachelors,5,23,95,71,50,7.0,4,92,Semi-Urban,Manager,104572,1 +98121,Male,57,High School,17,61,86,25,89,1.0,0,83,Rural,ML Engineer,132462,1 +98122,Female,56,Masters,14,57,49,77,67,5.0,7,11,Semi-Urban,Software Engineer,43407,0 +98123,Male,38,Masters,12,72,48,89,24,7.0,0,73,Semi-Urban,Manager,101329,1 +98124,Male,55,Masters,0,17,29,12,78,9.0,7,80,Urban,HR Executive,61344,0 +98125,Female,28,Bachelors,14,3,26,41,77,1.0,2,54,Semi-Urban,Software Engineer,99537,0 +98126,Male,50,Bachelors,8,30,43,55,78,5.0,2,22,Rural,Data Analyst,54934,0 +98127,Male,46,High School,18,8,75,3,42,6.0,3,36,Urban,Manager,54238,0 +98128,Female,58,Bachelors,12,4,46,78,59,7.0,4,33,Urban,ML Engineer,88375,0 +98129,Male,26,Masters,0,90,74,87,68,7.0,4,88,Urban,Data Analyst,22228,1 +98130,Male,34,PhD,12,56,23,28,42,5.0,5,95,Urban,ML Engineer,63167,0 +98131,Other,52,Bachelors,12,45,52,75,66,4.0,7,24,Urban,Software Engineer,102347,0 +98132,Other,27,Masters,6,15,40,93,36,0.0,4,98,Rural,HR Executive,116431,1 +98133,Male,59,Bachelors,8,52,28,26,31,6.0,5,90,Urban,Software Engineer,73018,0 +98134,Female,41,Bachelors,1,0,63,44,34,6.0,3,11,Semi-Urban,Software Engineer,127711,0 +98135,Female,36,Bachelors,6,15,12,82,50,2.0,7,42,Urban,HR Executive,140830,0 +98136,Male,52,PhD,13,78,94,82,54,8.0,2,49,Urban,Manager,37723,1 +98137,Female,35,Masters,10,51,11,64,94,0.0,6,26,Urban,ML Engineer,106881,0 +98138,Female,48,Diploma,14,94,22,83,83,6.0,2,43,Semi-Urban,Manager,38799,1 +98139,Male,54,Bachelors,11,38,86,10,55,0.0,4,65,Semi-Urban,Software Engineer,134288,0 +98140,Female,56,Bachelors,3,79,48,5,78,6.0,4,35,Urban,HR Executive,101023,0 +98141,Male,54,Bachelors,8,52,97,95,95,2.0,1,33,Urban,Software Engineer,87305,1 +98142,Female,32,Masters,6,29,29,21,55,2.0,6,90,Urban,Manager,99801,0 +98143,Female,25,High School,1,66,34,15,44,5.0,5,78,Rural,Manager,98121,0 +98144,Female,32,PhD,15,58,96,19,93,9.0,1,85,Semi-Urban,ML Engineer,54592,1 +98145,Female,59,Bachelors,9,30,9,31,50,7.0,1,70,Urban,Data Analyst,98856,0 +98146,Female,45,Masters,19,60,28,98,33,5.0,6,23,Urban,HR Executive,99117,0 +98147,Female,53,Diploma,9,50,22,69,93,7.0,1,3,Rural,Data Analyst,135283,0 +98148,Female,23,High School,10,56,29,76,95,7.0,2,2,Urban,HR Executive,88637,0 +98149,Male,28,High School,4,22,48,80,33,3.0,7,66,Semi-Urban,ML Engineer,110485,0 +98150,Male,43,Bachelors,7,85,58,98,55,5.0,1,35,Semi-Urban,Software Engineer,142795,1 +98151,Male,39,Bachelors,18,1,44,83,72,8.0,6,36,Semi-Urban,HR Executive,97849,0 +98152,Female,58,Bachelors,11,14,32,34,60,0.0,7,58,Semi-Urban,Software Engineer,29106,0 +98153,Male,50,Bachelors,12,96,12,64,16,3.0,0,14,Urban,Manager,54202,0 +98154,Male,29,Diploma,15,38,40,42,25,1.0,5,60,Urban,HR Executive,148362,0 +98155,Male,36,Bachelors,14,65,77,55,57,4.0,1,5,Semi-Urban,HR Executive,73177,0 +98156,Male,21,PhD,10,17,77,4,26,9.0,3,63,Urban,Data Analyst,77663,0 +98157,Female,22,Bachelors,13,86,59,71,12,8.0,2,47,Urban,Data Analyst,67298,1 +98158,Male,33,Diploma,2,49,26,33,19,8.0,7,69,Urban,HR Executive,106519,0 +98159,Male,21,Bachelors,16,23,54,37,66,0.0,7,83,Urban,Data Analyst,44095,0 +98160,Male,41,Diploma,4,60,62,8,21,8.0,2,93,Urban,HR Executive,33003,0 +98161,Male,34,High School,18,80,77,68,21,2.0,5,99,Rural,HR Executive,117552,1 +98162,Other,42,Bachelors,7,9,56,29,63,0.0,7,5,Rural,ML Engineer,104654,0 +98163,Male,47,Masters,10,78,76,85,81,6.0,7,51,Urban,ML Engineer,38963,1 +98164,Male,58,Masters,5,90,42,56,5,5.0,6,49,Urban,ML Engineer,104393,1 +98165,Male,42,Bachelors,4,12,84,10,61,5.0,5,36,Urban,ML Engineer,49904,0 +98166,Female,35,Bachelors,19,99,2,89,8,1.0,7,34,Rural,ML Engineer,28636,0 +98167,Male,25,Diploma,11,37,14,1,23,5.0,6,63,Rural,Data Analyst,117204,0 +98168,Male,33,High School,6,31,34,48,4,5.0,3,5,Urban,ML Engineer,130115,0 +98169,Other,50,Bachelors,12,55,6,79,27,8.0,4,86,Urban,Manager,25267,0 +98170,Male,45,Bachelors,15,2,77,3,28,1.0,4,50,Rural,Manager,108743,0 +98171,Female,52,Bachelors,8,29,92,33,61,5.0,1,42,Semi-Urban,Software Engineer,33713,0 +98172,Male,31,Bachelors,2,28,39,15,68,5.0,0,38,Semi-Urban,Manager,115926,0 +98173,Male,24,Diploma,2,75,30,36,66,0.0,6,47,Urban,Manager,146585,0 +98174,Female,45,High School,8,45,90,40,39,3.0,3,40,Urban,Manager,146943,0 +98175,Male,42,PhD,0,52,55,1,31,9.0,7,75,Rural,Data Analyst,146396,0 +98176,Male,21,Bachelors,13,44,38,97,53,7.0,6,80,Rural,Software Engineer,72586,1 +98177,Female,21,Diploma,11,97,77,70,55,6.0,1,5,Urban,Software Engineer,124465,1 +98178,Male,37,PhD,18,26,49,6,66,5.0,1,50,Rural,ML Engineer,138267,0 +98179,Female,29,Bachelors,13,4,78,98,62,9.0,4,53,Semi-Urban,Manager,100559,0 +98180,Male,23,Diploma,10,16,47,97,37,2.0,1,68,Rural,Software Engineer,85968,0 +98181,Female,23,High School,12,27,75,47,36,7.0,2,12,Urban,Manager,32749,0 +98182,Male,45,Masters,19,1,73,64,70,4.0,3,20,Semi-Urban,ML Engineer,80890,0 +98183,Male,44,Masters,16,27,29,90,61,8.0,3,19,Urban,Software Engineer,34876,0 +98184,Other,49,Bachelors,16,8,79,92,71,2.0,1,81,Urban,Data Analyst,79840,1 +98185,Male,45,Masters,14,79,71,38,73,7.0,1,30,Urban,ML Engineer,78648,0 +98186,Female,28,Diploma,9,22,6,51,49,7.0,4,58,Urban,ML Engineer,146909,0 +98187,Male,56,Diploma,13,21,5,24,11,6.0,5,44,Urban,Manager,36377,0 +98188,Male,43,Bachelors,19,5,97,72,24,7.0,3,6,Urban,Data Analyst,26823,0 +98189,Male,41,Diploma,12,99,19,99,16,6.0,3,56,Urban,Data Analyst,109471,1 +98190,Female,40,Bachelors,15,0,68,42,91,4.0,0,81,Semi-Urban,Data Analyst,119858,0 +98191,Male,27,Bachelors,1,29,77,88,71,3.0,4,57,Urban,Manager,59216,1 +98192,Male,42,Masters,9,23,25,94,7,0.0,3,41,Rural,Software Engineer,74345,0 +98193,Male,34,Bachelors,16,10,56,94,49,4.0,1,84,Rural,Software Engineer,21347,1 +98194,Male,40,Masters,1,96,17,1,85,8.0,4,37,Semi-Urban,ML Engineer,118308,0 +98195,Male,26,High School,17,51,72,77,43,2.0,0,58,Rural,Manager,98970,1 +98196,Male,45,Bachelors,14,72,34,88,60,0.0,7,69,Urban,ML Engineer,132096,1 +98197,Male,39,Bachelors,10,92,39,37,36,4.0,2,65,Urban,HR Executive,112763,0 +98198,Male,33,High School,10,56,62,69,50,5.0,1,93,Urban,Data Analyst,99204,1 +98199,Male,29,Diploma,18,62,7,77,85,7.0,1,68,Urban,Data Analyst,126641,0 +98200,Female,30,PhD,10,42,46,31,27,5.0,1,54,Urban,Manager,21365,0 +98201,Male,50,Bachelors,18,14,82,60,86,2.0,3,53,Semi-Urban,ML Engineer,139056,0 +98202,Male,32,Diploma,2,13,46,37,4,5.0,0,65,Urban,Software Engineer,79178,0 +98203,Male,34,Masters,9,70,58,22,54,4.0,4,22,Semi-Urban,ML Engineer,101069,0 +98204,Male,49,Masters,1,35,51,30,62,9.0,7,81,Urban,HR Executive,46564,0 +98205,Male,52,Diploma,5,93,18,6,35,2.0,1,34,Urban,Software Engineer,74396,0 +98206,Male,45,Masters,15,61,81,65,58,9.0,7,5,Urban,Software Engineer,88419,0 +98207,Male,44,Bachelors,11,76,69,99,38,7.0,7,65,Semi-Urban,ML Engineer,125107,1 +98208,Male,56,High School,2,70,65,36,64,0.0,5,8,Urban,HR Executive,116940,0 +98209,Male,26,Diploma,9,66,33,79,99,6.0,2,49,Urban,Software Engineer,145237,0 +98210,Female,24,Bachelors,14,93,24,44,21,4.0,3,41,Urban,ML Engineer,105984,0 +98211,Male,48,Diploma,8,48,82,47,33,1.0,6,44,Urban,ML Engineer,89221,0 +98212,Male,53,High School,7,16,78,15,46,9.0,0,2,Urban,Data Analyst,121231,0 +98213,Male,31,Diploma,19,59,59,26,32,1.0,2,5,Rural,Software Engineer,86041,0 +98214,Male,34,Masters,5,3,40,26,90,2.0,5,37,Urban,ML Engineer,79727,0 +98215,Female,21,Masters,8,69,76,97,44,6.0,7,55,Urban,ML Engineer,53138,1 +98216,Male,32,Diploma,18,72,16,40,50,5.0,7,20,Urban,Manager,91552,0 +98217,Male,32,Diploma,19,81,96,72,14,8.0,5,64,Rural,ML Engineer,97263,1 +98218,Male,41,Diploma,12,3,90,66,64,0.0,1,98,Rural,Manager,52465,1 +98219,Male,49,Diploma,5,19,16,1,27,7.0,6,71,Urban,Software Engineer,144426,0 +98220,Female,29,High School,1,89,31,84,53,7.0,2,99,Urban,Data Analyst,61268,1 +98221,Female,31,Masters,18,49,98,37,70,8.0,3,30,Rural,Manager,97695,0 +98222,Female,48,Masters,3,6,38,34,81,8.0,2,41,Semi-Urban,Software Engineer,50084,0 +98223,Male,58,High School,11,77,20,32,3,0.0,7,11,Urban,ML Engineer,53405,0 +98224,Female,48,Bachelors,12,66,20,71,18,6.0,6,92,Rural,HR Executive,119161,1 +98225,Male,30,Diploma,19,74,3,49,90,4.0,6,22,Semi-Urban,Manager,100417,0 +98226,Male,28,Diploma,6,58,52,58,39,2.0,7,91,Semi-Urban,ML Engineer,57350,1 +98227,Female,48,Masters,2,54,3,87,70,6.0,2,63,Urban,Data Analyst,118825,0 +98228,Male,47,PhD,2,66,63,1,43,8.0,6,49,Rural,HR Executive,47681,0 +98229,Male,55,Bachelors,14,47,64,81,66,7.0,5,73,Rural,Manager,38590,1 +98230,Female,41,Masters,11,70,26,46,79,5.0,0,88,Semi-Urban,Data Analyst,72604,0 +98231,Male,45,Bachelors,4,99,65,27,64,3.0,6,75,Urban,Manager,58417,1 +98232,Male,31,Diploma,6,77,32,27,22,3.0,1,83,Rural,HR Executive,85344,0 +98233,Female,34,Diploma,16,3,79,69,50,1.0,0,99,Urban,HR Executive,82584,1 +98234,Male,42,Diploma,8,58,41,1,70,0.0,6,63,Urban,Manager,60158,0 +98235,Male,24,Diploma,13,46,74,33,16,1.0,6,31,Rural,HR Executive,44669,0 +98236,Male,49,Masters,14,89,77,13,72,3.0,0,17,Rural,Manager,133336,0 +98237,Female,41,Bachelors,0,92,57,28,51,7.0,0,58,Semi-Urban,Data Analyst,95107,0 +98238,Male,35,Diploma,11,40,8,10,96,8.0,4,71,Urban,Data Analyst,143421,0 +98239,Male,28,High School,2,71,34,16,53,3.0,2,73,Semi-Urban,ML Engineer,110480,0 +98240,Female,26,Bachelors,3,52,93,43,27,7.0,3,64,Rural,Data Analyst,145336,1 +98241,Male,22,Masters,15,20,87,92,91,8.0,2,9,Semi-Urban,Software Engineer,55868,0 +98242,Female,51,High School,6,39,93,85,39,2.0,7,65,Urban,Data Analyst,43787,1 +98243,Male,53,Bachelors,16,41,52,68,98,7.0,6,71,Semi-Urban,Software Engineer,92293,0 +98244,Male,55,Bachelors,19,70,10,84,88,8.0,7,64,Rural,Software Engineer,73929,0 +98245,Male,28,Masters,4,81,25,95,37,0.0,4,82,Urban,Software Engineer,72066,1 +98246,Male,41,High School,3,62,48,44,93,4.0,5,30,Rural,ML Engineer,28867,0 +98247,Male,57,Bachelors,9,15,25,16,32,5.0,3,69,Urban,Data Analyst,83106,0 +98248,Male,57,Bachelors,17,94,64,25,32,6.0,5,17,Urban,Data Analyst,138052,0 +98249,Male,58,Bachelors,19,54,97,86,60,2.0,7,48,Urban,ML Engineer,97090,1 +98250,Male,45,Diploma,11,70,44,6,39,0.0,4,89,Rural,Manager,81952,0 +98251,Female,33,Diploma,7,63,17,69,51,1.0,7,25,Rural,Data Analyst,134861,0 +98252,Male,59,Bachelors,6,50,17,29,64,6.0,0,45,Semi-Urban,HR Executive,109074,0 +98253,Male,26,Diploma,17,9,92,1,30,9.0,1,58,Urban,Manager,51384,0 +98254,Male,40,Bachelors,8,77,93,7,5,0.0,3,85,Semi-Urban,Data Analyst,126211,1 +98255,Male,35,Diploma,17,5,52,74,8,3.0,7,14,Rural,Manager,90190,0 +98256,Male,37,PhD,2,22,79,66,1,3.0,4,6,Urban,HR Executive,139870,0 +98257,Female,37,Masters,1,16,54,4,2,1.0,5,98,Semi-Urban,Data Analyst,20587,0 +98258,Female,47,Masters,2,86,10,17,74,2.0,2,87,Rural,Data Analyst,92901,0 +98259,Male,51,PhD,8,76,51,19,22,8.0,3,25,Urban,Data Analyst,111287,0 +98260,Male,46,Bachelors,12,89,99,25,0,2.0,1,77,Urban,Manager,64354,1 +98261,Male,37,High School,15,8,59,57,20,4.0,5,79,Urban,HR Executive,94156,0 +98262,Female,33,Bachelors,3,29,69,31,96,3.0,6,91,Semi-Urban,Manager,46785,0 +98263,Male,53,Masters,11,43,25,74,96,7.0,0,82,Urban,Manager,58259,0 +98264,Female,39,Masters,0,9,75,63,51,6.0,3,91,Urban,HR Executive,120810,0 +98265,Female,45,Masters,9,97,49,65,40,3.0,5,16,Rural,Data Analyst,35497,0 +98266,Female,27,Bachelors,13,19,71,40,47,1.0,5,41,Semi-Urban,Manager,65007,0 +98267,Male,21,Diploma,15,28,89,66,27,1.0,3,47,Urban,Manager,71086,0 +98268,Female,26,Bachelors,7,94,26,85,64,0.0,5,11,Semi-Urban,ML Engineer,59902,0 +98269,Male,43,Masters,19,75,43,49,82,9.0,5,69,Semi-Urban,Data Analyst,132324,1 +98270,Other,51,Masters,13,92,92,53,17,0.0,2,68,Semi-Urban,ML Engineer,53141,1 +98271,Male,30,Bachelors,3,10,72,6,80,9.0,0,96,Urban,ML Engineer,29389,0 +98272,Female,59,Bachelors,8,87,48,64,35,8.0,4,39,Urban,Manager,30152,0 +98273,Male,44,High School,0,79,99,58,75,1.0,2,86,Semi-Urban,Software Engineer,55422,1 +98274,Male,25,Masters,18,25,69,93,54,7.0,3,17,Urban,ML Engineer,89783,0 +98275,Male,21,Bachelors,19,20,75,68,59,4.0,5,62,Urban,HR Executive,81726,0 +98276,Male,25,Masters,16,91,38,63,85,1.0,6,63,Urban,Data Analyst,79767,1 +98277,Male,33,Bachelors,19,89,64,17,55,5.0,4,91,Urban,Software Engineer,69319,1 +98278,Male,52,Masters,7,45,44,39,22,5.0,0,93,Urban,ML Engineer,140935,0 +98279,Other,52,Diploma,8,81,99,13,32,9.0,6,71,Rural,Data Analyst,139873,1 +98280,Female,56,Bachelors,5,99,66,56,67,1.0,6,6,Urban,HR Executive,71781,0 +98281,Female,33,Diploma,11,24,25,86,70,7.0,4,81,Urban,Software Engineer,149258,0 +98282,Female,40,Diploma,18,0,36,63,38,8.0,0,59,Semi-Urban,Software Engineer,132718,0 +98283,Male,38,Bachelors,4,0,77,25,12,2.0,7,14,Urban,Manager,130087,0 +98284,Female,52,High School,13,72,33,60,59,0.0,6,43,Urban,Manager,47794,0 +98285,Male,51,PhD,6,89,33,77,7,5.0,5,47,Urban,ML Engineer,103015,1 +98286,Male,53,High School,8,15,23,99,90,4.0,6,98,Urban,ML Engineer,139817,1 +98287,Male,40,Bachelors,18,83,48,73,4,4.0,1,76,Urban,Data Analyst,55028,1 +98288,Male,52,Bachelors,4,28,98,9,19,9.0,7,90,Semi-Urban,ML Engineer,51722,0 +98289,Male,30,High School,12,54,21,94,63,6.0,3,46,Rural,Manager,46612,0 +98290,Female,30,Masters,17,23,9,22,36,4.0,6,33,Rural,Manager,87472,0 +98291,Male,24,Masters,19,72,4,47,2,1.0,6,25,Urban,HR Executive,27109,0 +98292,Female,24,Masters,6,66,93,98,55,6.0,4,34,Semi-Urban,Manager,31094,1 +98293,Male,25,Bachelors,18,44,97,51,75,9.0,4,33,Urban,ML Engineer,37656,0 +98294,Male,34,Masters,8,89,84,39,88,3.0,4,85,Urban,Software Engineer,134650,1 +98295,Male,31,High School,2,9,14,56,1,3.0,7,17,Rural,ML Engineer,74040,0 +98296,Male,48,PhD,5,76,38,43,80,0.0,5,10,Rural,Data Analyst,142699,0 +98297,Female,26,Masters,18,74,47,26,85,9.0,1,5,Urban,ML Engineer,125875,0 +98298,Male,27,High School,2,64,92,59,66,9.0,1,10,Urban,HR Executive,137535,0 +98299,Female,40,Masters,19,64,75,44,77,8.0,0,23,Urban,Manager,114588,0 +98300,Male,27,Masters,3,26,39,26,47,1.0,1,67,Urban,ML Engineer,79251,0 +98301,Female,46,Diploma,9,37,40,28,99,4.0,4,43,Urban,ML Engineer,58525,0 +98302,Male,53,Masters,3,21,32,86,18,2.0,6,22,Urban,Manager,25994,0 +98303,Male,35,Diploma,4,63,44,92,4,0.0,6,28,Rural,Manager,21081,0 +98304,Male,34,Diploma,0,92,47,3,88,6.0,2,69,Semi-Urban,ML Engineer,149094,0 +98305,Male,56,Masters,10,62,94,88,25,1.0,1,32,Rural,HR Executive,45927,1 +98306,Male,42,Bachelors,9,42,32,20,48,0.0,2,45,Semi-Urban,ML Engineer,49455,0 +98307,Female,23,High School,2,22,58,50,71,5.0,7,3,Urban,Manager,98581,0 +98308,Male,24,Bachelors,13,66,49,58,66,8.0,3,12,Rural,ML Engineer,135403,0 +98309,Male,47,Bachelors,6,77,22,18,34,5.0,5,29,Urban,Software Engineer,72925,0 +98310,Male,58,Diploma,17,25,47,2,36,3.0,3,52,Urban,HR Executive,20975,0 +98311,Other,47,Masters,6,34,41,58,8,0.0,6,26,Urban,HR Executive,30968,0 +98312,Male,48,PhD,2,39,70,66,78,6.0,0,87,Rural,ML Engineer,108479,1 +98313,Male,28,Masters,8,93,90,31,18,6.0,3,80,Urban,Software Engineer,24719,1 +98314,Female,40,High School,16,27,86,65,7,7.0,2,56,Urban,HR Executive,118542,0 +98315,Male,52,High School,11,50,17,1,74,5.0,7,28,Rural,Software Engineer,118962,0 +98316,Female,56,Masters,6,47,84,67,68,8.0,1,26,Urban,HR Executive,54127,0 +98317,Male,57,Masters,13,36,28,38,83,4.0,0,40,Semi-Urban,Software Engineer,148454,0 +98318,Male,40,Masters,10,19,15,99,77,3.0,3,48,Rural,HR Executive,115090,0 +98319,Male,52,High School,11,89,69,52,23,0.0,7,7,Rural,ML Engineer,67498,0 +98320,Female,47,Bachelors,19,77,83,2,94,3.0,4,38,Urban,Manager,68706,0 +98321,Male,44,Masters,5,33,52,44,33,2.0,6,49,Urban,Data Analyst,102610,0 +98322,Female,53,Diploma,14,0,57,42,99,3.0,7,70,Rural,Manager,36518,0 +98323,Male,34,Bachelors,13,80,5,75,41,7.0,4,40,Urban,ML Engineer,109183,0 +98324,Female,53,Masters,14,40,85,49,80,0.0,3,83,Urban,Software Engineer,52993,1 +98325,Male,33,PhD,10,71,49,22,56,3.0,0,13,Urban,HR Executive,26918,0 +98326,Male,41,High School,6,8,92,10,11,0.0,0,22,Urban,HR Executive,78815,0 +98327,Male,42,Masters,11,93,26,58,27,9.0,2,52,Rural,Data Analyst,36414,0 +98328,Female,52,Bachelors,19,87,20,67,42,0.0,4,0,Semi-Urban,ML Engineer,31450,0 +98329,Male,24,Bachelors,15,90,44,43,85,6.0,0,17,Urban,Software Engineer,74138,0 +98330,Female,24,Masters,4,37,68,7,25,7.0,4,97,Urban,ML Engineer,105677,0 +98331,Male,25,Diploma,5,3,94,73,33,3.0,2,26,Urban,HR Executive,77474,0 +98332,Male,46,Diploma,13,49,26,71,20,2.0,2,20,Rural,HR Executive,46222,0 +98333,Male,53,Bachelors,17,4,0,56,70,0.0,2,78,Rural,Manager,43056,0 +98334,Female,42,PhD,6,57,40,35,98,5.0,5,26,Urban,Data Analyst,107475,0 +98335,Male,24,Bachelors,10,53,30,23,89,6.0,4,38,Urban,Manager,131901,0 +98336,Female,29,Bachelors,3,97,44,58,53,6.0,0,22,Urban,Data Analyst,45121,0 +98337,Male,23,Bachelors,3,89,32,75,14,9.0,5,30,Urban,Data Analyst,24343,0 +98338,Female,54,Masters,11,76,29,70,41,1.0,5,73,Semi-Urban,Software Engineer,133983,1 +98339,Male,44,Diploma,4,67,52,34,4,9.0,4,92,Urban,ML Engineer,29156,1 +98340,Female,52,Bachelors,0,86,7,81,40,6.0,7,95,Urban,Software Engineer,109282,1 +98341,Female,47,Masters,7,42,31,39,4,9.0,7,31,Rural,Software Engineer,93115,0 +98342,Male,49,Diploma,6,78,30,97,47,1.0,6,42,Urban,HR Executive,144372,1 +98343,Female,52,Bachelors,7,30,90,52,53,0.0,5,92,Urban,Manager,30460,1 +98344,Female,51,Bachelors,19,46,76,35,83,0.0,1,95,Urban,Software Engineer,44856,1 +98345,Male,37,Bachelors,18,67,91,61,55,2.0,7,50,Urban,Software Engineer,61307,1 +98346,Male,24,Bachelors,18,78,18,68,50,2.0,1,46,Rural,Data Analyst,113642,0 +98347,Male,30,Bachelors,18,47,54,76,22,6.0,7,46,Semi-Urban,HR Executive,86862,0 +98348,Other,40,Bachelors,2,50,83,43,60,0.0,0,82,Urban,Software Engineer,127686,1 +98349,Male,24,Diploma,16,23,73,29,58,7.0,2,31,Urban,Manager,79097,0 +98350,Female,31,PhD,10,43,94,90,68,2.0,4,31,Urban,Manager,96245,1 +98351,Male,56,PhD,19,15,68,71,79,2.0,0,50,Urban,Software Engineer,95905,0 +98352,Male,49,High School,17,36,88,4,74,3.0,0,61,Rural,Data Analyst,118940,0 +98353,Female,58,Diploma,6,31,44,28,77,2.0,5,7,Urban,HR Executive,145025,0 +98354,Other,31,Bachelors,18,75,36,35,82,9.0,7,67,Semi-Urban,HR Executive,38496,0 +98355,Female,30,Bachelors,6,21,47,87,73,8.0,0,21,Semi-Urban,Manager,40803,0 +98356,Male,38,Bachelors,11,83,9,36,6,6.0,0,16,Urban,Data Analyst,50718,0 +98357,Female,54,PhD,2,25,55,19,24,6.0,2,83,Semi-Urban,ML Engineer,100739,0 +98358,Female,23,Bachelors,16,15,17,14,45,9.0,5,9,Rural,Software Engineer,87459,0 +98359,Male,34,Bachelors,3,89,51,19,10,4.0,3,57,Rural,Manager,115722,0 +98360,Female,41,Bachelors,5,23,5,94,82,7.0,5,52,Semi-Urban,Data Analyst,70884,0 +98361,Female,38,PhD,15,85,6,83,95,9.0,3,60,Rural,Manager,31529,0 +98362,Male,22,Bachelors,2,50,26,53,13,5.0,1,20,Semi-Urban,ML Engineer,148840,0 +98363,Other,28,Diploma,12,53,58,48,23,6.0,2,66,Urban,ML Engineer,149478,0 +98364,Male,55,Bachelors,17,68,51,21,62,4.0,2,20,Urban,ML Engineer,147350,0 +98365,Female,50,Masters,12,37,23,84,51,4.0,0,89,Urban,HR Executive,23293,0 +98366,Male,27,Bachelors,17,72,70,93,15,2.0,7,79,Urban,HR Executive,128448,1 +98367,Female,21,Masters,17,92,66,22,45,7.0,0,6,Urban,Software Engineer,54949,0 +98368,Male,27,Diploma,14,63,4,52,83,1.0,5,14,Urban,Data Analyst,63433,0 +98369,Male,44,Bachelors,4,86,85,43,89,2.0,3,51,Urban,Software Engineer,122621,1 +98370,Male,53,Bachelors,6,49,83,10,20,8.0,2,95,Semi-Urban,Software Engineer,66937,1 +98371,Male,26,Masters,13,71,48,81,20,1.0,1,3,Urban,Manager,71228,0 +98372,Male,29,Diploma,4,25,48,27,75,1.0,6,45,Urban,ML Engineer,81562,0 +98373,Male,41,Masters,16,99,47,92,47,7.0,5,64,Urban,HR Executive,71968,1 +98374,Female,30,Diploma,12,87,78,87,99,7.0,6,26,Semi-Urban,Data Analyst,126554,1 +98375,Male,51,Bachelors,18,71,95,95,36,0.0,0,93,Rural,Manager,73969,1 +98376,Female,24,Bachelors,17,26,28,69,61,7.0,6,51,Semi-Urban,ML Engineer,46178,0 +98377,Male,34,Masters,18,21,23,59,47,3.0,0,36,Urban,Data Analyst,111395,0 +98378,Male,47,High School,1,55,99,69,27,8.0,0,41,Urban,Data Analyst,32031,1 +98379,Male,26,Bachelors,15,77,96,45,47,4.0,2,38,Urban,HR Executive,112584,1 +98380,Male,35,Diploma,14,24,88,48,35,8.0,0,54,Urban,HR Executive,149625,0 +98381,Male,50,Bachelors,9,46,66,98,80,2.0,4,95,Urban,HR Executive,80893,1 +98382,Female,36,Masters,14,38,22,42,57,7.0,3,13,Urban,Manager,100615,0 +98383,Male,52,Bachelors,17,66,68,35,66,6.0,2,8,Urban,HR Executive,106176,0 +98384,Male,25,Bachelors,15,87,71,34,55,0.0,3,62,Semi-Urban,Software Engineer,127102,1 +98385,Female,57,Bachelors,6,27,92,75,91,4.0,5,15,Urban,HR Executive,101681,0 +98386,Female,29,Bachelors,14,75,6,25,46,6.0,5,36,Urban,Software Engineer,125279,0 +98387,Female,44,Bachelors,1,60,18,27,21,4.0,5,95,Urban,Software Engineer,22869,0 +98388,Male,49,Masters,11,48,25,65,21,4.0,5,94,Urban,Software Engineer,61977,0 +98389,Female,38,High School,16,80,77,4,68,8.0,5,39,Rural,HR Executive,111878,0 +98390,Female,23,Diploma,10,93,21,88,96,8.0,1,84,Urban,ML Engineer,68699,1 +98391,Male,42,Diploma,16,57,65,47,99,9.0,5,62,Urban,Software Engineer,115802,0 +98392,Male,34,Masters,11,26,13,48,68,5.0,6,84,Urban,Data Analyst,102504,0 +98393,Female,40,Bachelors,11,87,51,58,26,8.0,7,91,Urban,Data Analyst,137901,1 +98394,Other,40,Masters,17,32,92,75,28,0.0,2,33,Semi-Urban,Manager,60004,0 +98395,Male,58,Bachelors,14,63,98,37,29,1.0,3,4,Urban,HR Executive,142960,0 +98396,Female,59,Bachelors,6,67,26,57,85,5.0,3,53,Urban,HR Executive,30434,0 +98397,Female,57,High School,19,37,34,36,96,4.0,4,54,Urban,HR Executive,32205,0 +98398,Female,24,Bachelors,10,25,60,58,54,9.0,0,78,Semi-Urban,Data Analyst,123884,0 +98399,Male,28,Bachelors,1,45,14,9,85,4.0,2,91,Urban,ML Engineer,138272,0 +98400,Male,51,Masters,11,73,42,72,4,1.0,7,69,Urban,Manager,46544,1 +98401,Male,22,Masters,19,47,66,92,62,4.0,3,55,Urban,ML Engineer,146334,1 +98402,Male,29,PhD,16,30,36,10,53,0.0,1,64,Urban,Manager,47595,0 +98403,Female,21,Diploma,1,6,72,79,26,4.0,0,11,Urban,Software Engineer,61410,0 +98404,Male,35,Masters,9,41,88,62,65,0.0,2,70,Urban,Software Engineer,98799,1 +98405,Male,53,Masters,12,49,96,48,18,2.0,3,35,Semi-Urban,HR Executive,57666,0 +98406,Male,46,Bachelors,13,37,65,80,45,8.0,5,38,Urban,Software Engineer,126263,0 +98407,Female,51,PhD,7,54,37,10,91,8.0,5,70,Urban,Software Engineer,79994,0 +98408,Female,31,Diploma,6,25,86,87,49,0.0,3,97,Urban,Data Analyst,142014,1 +98409,Female,54,Masters,17,24,66,83,52,0.0,4,14,Urban,ML Engineer,104869,0 +98410,Female,37,Bachelors,2,50,21,87,82,5.0,2,60,Semi-Urban,Data Analyst,51670,0 +98411,Female,38,Bachelors,2,31,13,74,88,6.0,1,37,Urban,ML Engineer,138620,0 +98412,Male,30,Diploma,11,50,54,58,71,7.0,4,8,Urban,Manager,126606,0 +98413,Male,58,Bachelors,4,41,89,42,37,6.0,5,79,Rural,Manager,71249,1 +98414,Female,24,Bachelors,10,49,70,45,54,7.0,5,51,Urban,Data Analyst,110190,0 +98415,Female,47,Bachelors,17,70,81,68,99,6.0,7,0,Semi-Urban,Data Analyst,137974,0 +98416,Female,22,Masters,7,72,13,58,13,6.0,7,25,Rural,Data Analyst,26263,0 +98417,Male,53,Bachelors,2,62,62,39,53,8.0,5,30,Urban,Software Engineer,139027,0 +98418,Male,43,Masters,13,79,58,15,97,3.0,2,29,Rural,Data Analyst,72131,0 +98419,Female,40,High School,3,86,61,8,40,7.0,3,90,Semi-Urban,HR Executive,124232,1 +98420,Male,48,Bachelors,15,3,58,65,56,5.0,6,75,Urban,Software Engineer,116550,0 +98421,Male,42,Bachelors,1,29,8,99,32,3.0,4,35,Urban,Manager,78275,0 +98422,Female,42,Diploma,8,76,33,93,69,4.0,4,49,Urban,Software Engineer,47969,1 +98423,Male,43,Masters,9,53,25,28,83,3.0,0,89,Rural,Data Analyst,24743,0 +98424,Other,40,High School,1,79,61,72,2,3.0,2,68,Urban,Manager,55119,1 +98425,Male,31,Bachelors,16,5,73,71,34,6.0,3,79,Urban,HR Executive,144484,0 +98426,Male,42,Diploma,13,71,49,52,53,9.0,6,56,Semi-Urban,Data Analyst,139037,0 +98427,Male,57,Diploma,12,85,12,19,16,3.0,0,44,Semi-Urban,Manager,107097,0 +98428,Male,32,Bachelors,16,54,41,87,22,9.0,6,66,Rural,ML Engineer,61208,1 +98429,Male,38,Bachelors,14,28,86,68,75,4.0,7,72,Semi-Urban,HR Executive,93372,1 +98430,Female,25,Diploma,0,48,19,50,7,5.0,2,93,Urban,Software Engineer,94443,0 +98431,Female,55,Bachelors,6,68,54,79,50,0.0,3,39,Rural,ML Engineer,110628,0 +98432,Female,52,Masters,15,64,65,21,33,2.0,7,67,Urban,Data Analyst,42402,0 +98433,Male,35,High School,14,11,36,15,89,8.0,3,23,Semi-Urban,ML Engineer,29684,0 +98434,Male,43,Diploma,6,6,22,40,19,6.0,4,59,Urban,HR Executive,75986,0 +98435,Male,31,Bachelors,6,82,3,43,28,1.0,5,33,Rural,Software Engineer,38383,0 +98436,Female,56,Masters,12,86,62,79,93,5.0,5,51,Urban,Manager,71364,1 +98437,Male,34,Masters,0,10,3,69,31,7.0,6,70,Urban,Manager,37416,0 +98438,Female,45,Bachelors,9,8,24,50,23,6.0,0,70,Rural,Software Engineer,20664,0 +98439,Male,21,Masters,6,17,53,92,76,2.0,0,29,Urban,ML Engineer,148482,0 +98440,Male,46,High School,2,30,20,59,10,3.0,2,30,Urban,ML Engineer,112708,0 +98441,Female,56,Bachelors,14,6,95,54,58,0.0,7,54,Urban,HR Executive,35265,0 +98442,Male,42,Diploma,10,44,65,76,75,4.0,4,89,Urban,Data Analyst,31768,1 +98443,Male,51,Diploma,14,45,78,96,78,2.0,0,56,Semi-Urban,ML Engineer,42429,1 +98444,Male,57,Masters,17,68,72,33,88,3.0,6,74,Urban,Software Engineer,85965,1 +98445,Female,52,Bachelors,18,55,63,69,89,3.0,4,78,Urban,ML Engineer,42580,1 +98446,Male,37,Bachelors,11,36,53,74,27,1.0,3,29,Semi-Urban,Software Engineer,128338,0 +98447,Male,40,Bachelors,7,33,65,97,48,7.0,5,37,Urban,ML Engineer,111332,0 +98448,Male,40,Masters,18,52,5,56,52,2.0,3,71,Urban,Data Analyst,90271,0 +98449,Male,45,Diploma,9,45,46,7,50,3.0,2,34,Urban,ML Engineer,90854,0 +98450,Male,40,Bachelors,2,97,15,20,51,9.0,0,50,Urban,HR Executive,125325,0 +98451,Male,47,Diploma,17,30,37,17,24,3.0,2,23,Semi-Urban,Manager,72830,0 +98452,Female,42,Bachelors,0,32,65,60,23,6.0,6,44,Rural,Software Engineer,125254,0 +98453,Female,36,Bachelors,1,33,89,77,47,8.0,4,51,Rural,ML Engineer,20367,1 +98454,Male,29,Bachelors,4,19,83,23,96,6.0,4,17,Semi-Urban,Data Analyst,80427,0 +98455,Male,36,Bachelors,5,76,49,37,58,1.0,0,98,Urban,Manager,96197,1 +98456,Male,52,Diploma,14,88,9,42,28,7.0,7,43,Urban,HR Executive,107307,0 +98457,Female,46,Masters,17,62,30,1,2,9.0,1,27,Rural,Manager,41702,0 +98458,Male,40,PhD,13,84,21,45,45,6.0,7,22,Semi-Urban,Data Analyst,59194,0 +98459,Female,28,Diploma,5,43,0,0,72,7.0,4,94,Semi-Urban,ML Engineer,75380,0 +98460,Male,36,Bachelors,3,25,32,47,20,1.0,3,4,Semi-Urban,HR Executive,49357,0 +98461,Female,42,Bachelors,1,29,57,53,79,0.0,1,44,Urban,ML Engineer,118823,0 +98462,Male,28,Masters,16,84,72,25,48,1.0,4,31,Urban,Software Engineer,29994,0 +98463,Female,43,High School,9,53,59,59,84,2.0,6,91,Urban,HR Executive,88601,1 +98464,Male,54,Masters,0,24,9,59,23,8.0,2,48,Semi-Urban,Data Analyst,43929,0 +98465,Male,45,Bachelors,7,47,25,9,60,2.0,0,41,Urban,Software Engineer,31996,0 +98466,Female,29,Masters,2,99,24,82,79,4.0,7,53,Urban,Data Analyst,97512,1 +98467,Female,41,Diploma,7,27,43,86,27,8.0,5,30,Rural,Software Engineer,32118,0 +98468,Female,56,Masters,17,20,38,10,80,0.0,3,76,Semi-Urban,ML Engineer,40592,0 +98469,Female,45,Bachelors,1,31,22,24,94,6.0,3,35,Urban,Manager,61635,0 +98470,Male,23,High School,16,89,16,75,94,6.0,6,18,Rural,ML Engineer,31732,0 +98471,Female,49,Diploma,12,63,38,89,21,8.0,2,51,Semi-Urban,ML Engineer,118956,1 +98472,Male,21,High School,2,92,53,88,99,8.0,7,90,Rural,HR Executive,78862,1 +98473,Male,46,Diploma,5,66,72,23,90,8.0,0,92,Urban,HR Executive,123781,1 +98474,Male,51,High School,17,16,27,31,60,0.0,1,4,Semi-Urban,Manager,71844,0 +98475,Female,29,Bachelors,1,13,20,71,76,4.0,4,34,Urban,ML Engineer,82635,0 +98476,Male,27,Bachelors,15,87,32,18,86,1.0,3,6,Urban,HR Executive,52961,0 +98477,Male,42,Bachelors,10,31,39,61,73,7.0,1,27,Urban,ML Engineer,56444,0 +98478,Female,43,Masters,8,50,47,87,6,0.0,1,20,Urban,Software Engineer,123775,0 +98479,Male,27,PhD,0,85,1,97,26,8.0,5,99,Semi-Urban,HR Executive,124322,1 +98480,Male,49,Bachelors,15,95,42,68,74,2.0,0,83,Urban,Data Analyst,121096,1 +98481,Male,52,Bachelors,2,36,39,40,24,0.0,5,8,Rural,Data Analyst,123352,0 +98482,Female,44,PhD,7,15,6,47,65,3.0,5,48,Urban,HR Executive,115314,0 +98483,Female,58,Bachelors,9,13,73,68,28,7.0,0,56,Urban,Manager,118018,0 +98484,Male,52,Masters,4,90,24,62,53,5.0,4,82,Rural,Data Analyst,100730,1 +98485,Male,47,Masters,9,24,11,71,79,2.0,5,90,Semi-Urban,HR Executive,116428,0 +98486,Male,59,Diploma,10,30,35,55,52,4.0,0,88,Urban,HR Executive,33665,0 +98487,Male,29,Masters,2,15,61,54,4,2.0,7,60,Urban,HR Executive,32727,0 +98488,Male,22,Bachelors,0,81,65,97,3,0.0,3,54,Urban,Data Analyst,79483,1 +98489,Female,28,PhD,11,28,70,75,90,3.0,0,68,Rural,Software Engineer,57739,1 +98490,Male,54,Diploma,9,8,48,36,51,6.0,4,39,Rural,HR Executive,103073,0 +98491,Male,58,Diploma,3,90,46,51,23,8.0,4,7,Semi-Urban,Data Analyst,86201,0 +98492,Male,34,Masters,8,91,54,11,40,0.0,7,58,Semi-Urban,Manager,32977,0 +98493,Male,39,Bachelors,6,87,19,17,14,4.0,7,79,Urban,ML Engineer,40072,0 +98494,Male,39,Bachelors,5,12,3,6,16,9.0,7,68,Rural,Manager,41865,0 +98495,Male,42,Bachelors,9,71,6,22,83,7.0,4,12,Rural,Data Analyst,76256,0 +98496,Male,46,Diploma,8,70,85,35,40,8.0,7,55,Urban,Data Analyst,53663,1 +98497,Male,28,PhD,11,17,5,75,53,8.0,7,41,Urban,HR Executive,54084,0 +98498,Male,22,Bachelors,5,91,85,3,68,6.0,7,3,Semi-Urban,Software Engineer,93935,0 +98499,Female,33,Masters,6,19,80,66,26,8.0,3,3,Urban,HR Executive,87040,0 +98500,Male,47,Bachelors,14,54,64,59,75,1.0,3,83,Urban,Manager,100572,1 +98501,Male,37,PhD,14,68,97,46,73,1.0,0,73,Rural,ML Engineer,73693,1 +98502,Male,44,Bachelors,10,57,51,45,70,6.0,0,57,Urban,Manager,81351,0 +98503,Other,58,Bachelors,10,41,44,81,58,5.0,2,18,Semi-Urban,Software Engineer,86255,0 +98504,Female,35,Diploma,3,40,68,7,13,5.0,7,15,Rural,ML Engineer,149347,0 +98505,Female,54,Diploma,7,14,69,94,84,0.0,0,73,Urban,HR Executive,130142,1 +98506,Female,57,Bachelors,11,90,32,78,24,4.0,5,80,Urban,ML Engineer,69557,1 +98507,Male,22,Bachelors,5,45,10,19,74,3.0,2,73,Urban,HR Executive,50936,0 +98508,Male,34,Bachelors,9,70,37,48,63,4.0,6,48,Urban,Data Analyst,25221,0 +98509,Female,50,Diploma,3,49,52,34,64,7.0,3,79,Urban,Manager,147541,0 +98510,Female,21,Bachelors,6,52,52,74,52,5.0,3,95,Rural,Software Engineer,50332,1 +98511,Female,22,Bachelors,16,13,68,21,77,9.0,3,20,Rural,ML Engineer,73194,0 +98512,Female,39,High School,14,27,27,53,1,0.0,0,53,Semi-Urban,HR Executive,51083,0 +98513,Female,53,Bachelors,19,43,79,76,48,4.0,7,30,Semi-Urban,HR Executive,54292,0 +98514,Male,27,Masters,15,23,69,55,61,0.0,1,23,Urban,Software Engineer,106659,0 +98515,Male,31,High School,17,56,3,65,19,1.0,6,66,Rural,Software Engineer,21658,0 +98516,Female,55,Bachelors,1,76,42,52,2,0.0,4,67,Semi-Urban,HR Executive,120629,0 +98517,Female,27,High School,9,95,65,95,30,0.0,3,0,Rural,Data Analyst,107551,1 +98518,Other,29,High School,0,51,51,1,25,9.0,5,47,Urban,ML Engineer,82792,0 +98519,Male,33,Bachelors,0,44,11,68,17,8.0,6,44,Rural,Manager,123745,0 +98520,Female,47,Bachelors,4,19,44,54,55,6.0,2,70,Semi-Urban,Manager,138211,0 +98521,Female,40,Masters,17,9,99,92,80,9.0,4,34,Urban,ML Engineer,102588,0 +98522,Male,24,Diploma,4,17,42,65,67,6.0,6,34,Urban,Software Engineer,59928,0 +98523,Male,42,High School,10,41,90,90,92,1.0,4,43,Rural,Software Engineer,73177,1 +98524,Male,55,Masters,5,40,27,58,26,4.0,0,48,Semi-Urban,Software Engineer,114814,0 +98525,Female,44,Bachelors,0,16,82,43,57,2.0,4,48,Semi-Urban,HR Executive,94947,0 +98526,Male,57,PhD,10,89,55,66,54,2.0,3,34,Urban,Software Engineer,85975,1 +98527,Male,57,Bachelors,8,99,70,98,60,2.0,4,21,Urban,HR Executive,44905,1 +98528,Female,44,High School,13,42,66,72,76,3.0,4,27,Urban,Software Engineer,40535,0 +98529,Male,42,Diploma,10,27,63,75,29,4.0,3,98,Rural,Manager,119901,1 +98530,Male,48,Bachelors,10,51,11,75,17,7.0,3,44,Semi-Urban,Data Analyst,69413,0 +98531,Female,56,Bachelors,1,3,97,40,4,4.0,6,5,Urban,ML Engineer,25017,0 +98532,Male,45,PhD,18,32,51,61,21,8.0,6,19,Rural,Data Analyst,143092,0 +98533,Other,33,Bachelors,19,86,70,23,49,7.0,1,87,Urban,Software Engineer,70676,1 +98534,Male,23,High School,10,87,95,75,12,1.0,6,34,Semi-Urban,ML Engineer,104734,1 +98535,Male,38,Diploma,1,73,93,48,42,7.0,6,80,Rural,ML Engineer,133527,1 +98536,Male,58,Bachelors,17,19,70,3,4,4.0,5,45,Urban,Data Analyst,65799,0 +98537,Male,57,Masters,0,71,72,62,46,8.0,3,47,Urban,Manager,35505,1 +98538,Male,45,High School,16,55,27,52,42,4.0,4,65,Rural,ML Engineer,48092,0 +98539,Female,40,Bachelors,7,70,92,15,80,8.0,2,18,Rural,Software Engineer,81028,0 +98540,Male,48,High School,19,12,77,97,30,3.0,4,34,Urban,Software Engineer,71378,0 +98541,Female,34,Bachelors,15,61,59,5,10,2.0,4,10,Semi-Urban,Manager,21588,0 +98542,Male,28,Bachelors,14,17,78,87,18,4.0,0,60,Rural,Software Engineer,67330,1 +98543,Male,45,Bachelors,13,72,91,80,0,6.0,0,24,Urban,ML Engineer,127076,1 +98544,Male,32,Bachelors,14,56,82,44,42,0.0,2,27,Urban,HR Executive,84686,0 +98545,Male,39,Masters,10,17,54,69,70,2.0,4,2,Urban,Software Engineer,117636,0 +98546,Female,41,Masters,2,92,66,55,7,3.0,4,42,Semi-Urban,ML Engineer,121977,1 +98547,Female,53,Bachelors,15,56,64,72,5,7.0,4,17,Urban,Software Engineer,108822,0 +98548,Male,21,Bachelors,8,74,16,24,69,0.0,3,85,Rural,ML Engineer,26091,0 +98549,Male,28,Masters,1,96,77,86,72,0.0,4,20,Urban,HR Executive,35758,1 +98550,Female,29,High School,5,62,71,3,56,0.0,2,66,Semi-Urban,ML Engineer,66155,0 +98551,Female,34,Bachelors,4,58,98,88,48,0.0,4,42,Semi-Urban,Data Analyst,43805,1 +98552,Male,58,High School,6,51,18,21,84,9.0,7,91,Semi-Urban,ML Engineer,110793,0 +98553,Male,40,Bachelors,0,0,94,71,95,5.0,7,97,Semi-Urban,Data Analyst,48628,1 +98554,Male,57,Diploma,9,2,29,18,54,9.0,4,49,Urban,ML Engineer,139238,0 +98555,Female,26,Diploma,0,63,43,38,75,7.0,4,18,Urban,Data Analyst,130124,0 +98556,Male,53,Diploma,3,68,8,82,61,7.0,6,96,Urban,ML Engineer,60408,1 +98557,Male,53,Bachelors,1,23,58,55,5,4.0,5,78,Semi-Urban,ML Engineer,46827,0 +98558,Female,24,High School,12,58,59,1,75,2.0,2,12,Urban,Manager,146789,0 +98559,Female,53,Bachelors,17,89,24,95,95,2.0,0,26,Urban,Manager,135421,0 +98560,Female,56,Bachelors,4,65,69,46,85,7.0,0,37,Rural,ML Engineer,72574,0 +98561,Female,29,Bachelors,13,43,52,15,41,3.0,0,73,Semi-Urban,ML Engineer,33210,0 +98562,Male,34,PhD,3,81,60,62,32,7.0,5,46,Semi-Urban,Software Engineer,149888,1 +98563,Male,51,Bachelors,4,94,49,52,31,3.0,6,56,Urban,Data Analyst,107731,1 +98564,Male,21,Bachelors,10,49,86,66,60,9.0,4,51,Semi-Urban,HR Executive,133570,1 +98565,Female,22,Bachelors,17,16,7,37,47,8.0,0,79,Urban,HR Executive,132133,0 +98566,Male,57,Masters,17,12,83,4,93,1.0,1,61,Semi-Urban,ML Engineer,109957,0 +98567,Female,23,Bachelors,1,0,56,19,80,0.0,1,60,Urban,ML Engineer,144357,0 +98568,Male,22,High School,3,51,37,30,80,3.0,7,78,Urban,Data Analyst,96972,0 +98569,Other,45,High School,9,69,82,75,40,3.0,1,40,Urban,Software Engineer,130659,1 +98570,Male,50,Bachelors,8,12,44,54,4,9.0,0,66,Urban,Data Analyst,118627,0 +98571,Male,29,Masters,18,96,6,59,54,3.0,5,73,Rural,ML Engineer,131158,0 +98572,Female,38,Bachelors,14,62,6,53,7,2.0,5,98,Rural,Data Analyst,78034,0 +98573,Female,52,Masters,9,42,16,11,56,8.0,1,15,Urban,HR Executive,100623,0 +98574,Male,39,Masters,7,74,97,94,54,3.0,2,25,Urban,ML Engineer,56277,1 +98575,Female,44,Bachelors,19,55,86,49,74,6.0,3,11,Urban,Data Analyst,90946,0 +98576,Other,47,Bachelors,7,97,97,57,14,2.0,2,44,Semi-Urban,HR Executive,121110,1 +98577,Male,35,High School,4,88,98,47,93,7.0,3,11,Urban,Manager,72257,1 +98578,Male,24,Bachelors,17,96,33,23,22,1.0,4,17,Urban,Manager,106468,0 +98579,Male,44,PhD,6,16,19,99,91,8.0,5,14,Urban,Data Analyst,70490,0 +98580,Male,27,PhD,16,31,70,25,14,0.0,6,25,Semi-Urban,HR Executive,132961,0 +98581,Male,45,Bachelors,19,67,18,66,78,8.0,5,6,Urban,HR Executive,53632,0 +98582,Male,55,Diploma,14,39,14,86,57,9.0,5,24,Urban,HR Executive,53061,0 +98583,Female,43,Masters,0,34,39,78,32,4.0,6,82,Semi-Urban,Manager,52403,0 +98584,Male,27,Bachelors,12,29,93,58,38,8.0,0,84,Urban,ML Engineer,84849,1 +98585,Male,49,Diploma,1,77,35,66,63,4.0,5,63,Semi-Urban,HR Executive,145528,1 +98586,Male,25,Masters,12,44,47,67,73,4.0,0,43,Urban,Data Analyst,24491,0 +98587,Female,42,Bachelors,6,56,36,25,54,4.0,0,16,Semi-Urban,Data Analyst,88435,0 +98588,Female,40,Bachelors,1,55,29,42,18,6.0,2,30,Semi-Urban,Manager,46428,0 +98589,Male,36,Diploma,8,17,13,99,43,3.0,7,86,Urban,Data Analyst,136655,0 +98590,Other,49,Bachelors,11,48,59,36,93,2.0,5,94,Semi-Urban,Software Engineer,100129,0 +98591,Female,45,Masters,1,12,65,18,44,7.0,6,90,Urban,Data Analyst,89928,0 +98592,Male,21,Diploma,10,53,82,99,85,7.0,5,42,Urban,HR Executive,113697,1 +98593,Female,59,Masters,10,30,91,4,3,5.0,4,94,Urban,HR Executive,71224,0 +98594,Female,23,Bachelors,17,54,72,94,45,1.0,4,66,Urban,Software Engineer,84616,1 +98595,Male,24,Bachelors,17,34,62,42,90,3.0,1,98,Urban,ML Engineer,127556,1 +98596,Female,22,Masters,16,4,97,48,88,8.0,2,79,Urban,Software Engineer,42322,0 +98597,Male,57,Bachelors,4,98,43,29,95,6.0,5,12,Semi-Urban,Data Analyst,136894,0 +98598,Male,46,Diploma,6,16,90,74,56,9.0,0,54,Urban,ML Engineer,53451,0 +98599,Female,55,Bachelors,1,43,7,93,43,6.0,7,36,Rural,HR Executive,69902,0 +98600,Male,41,Diploma,14,56,66,27,42,4.0,3,69,Urban,Data Analyst,130881,0 +98601,Male,50,Masters,8,3,56,85,45,8.0,4,11,Semi-Urban,Software Engineer,53251,0 +98602,Male,23,Diploma,16,97,91,26,27,3.0,2,60,Urban,HR Executive,114812,1 +98603,Male,23,Bachelors,13,64,44,49,66,5.0,7,41,Urban,Manager,119843,0 +98604,Male,59,Diploma,12,16,10,97,24,8.0,3,89,Urban,HR Executive,47093,0 +98605,Male,49,Bachelors,17,94,29,16,93,7.0,7,4,Urban,HR Executive,74505,0 +98606,Male,58,Diploma,9,53,65,11,15,3.0,7,13,Semi-Urban,HR Executive,96064,0 +98607,Male,59,Bachelors,16,8,56,50,77,4.0,2,66,Semi-Urban,Manager,60655,0 +98608,Female,48,PhD,1,57,80,26,83,9.0,4,62,Semi-Urban,ML Engineer,55410,0 +98609,Male,39,High School,9,53,17,38,23,0.0,0,35,Urban,Manager,48648,0 +98610,Female,56,Bachelors,14,24,70,29,66,6.0,0,16,Rural,ML Engineer,105667,0 +98611,Male,27,Bachelors,7,36,35,51,90,8.0,4,77,Urban,HR Executive,31047,0 +98612,Male,28,PhD,3,60,42,62,49,5.0,1,23,Urban,Data Analyst,101262,0 +98613,Female,40,High School,9,69,4,87,72,9.0,0,3,Urban,HR Executive,103475,0 +98614,Male,47,Bachelors,13,19,49,35,82,7.0,4,81,Urban,ML Engineer,82948,0 +98615,Male,25,Diploma,4,92,71,54,87,5.0,4,27,Semi-Urban,Software Engineer,84711,1 +98616,Male,55,Bachelors,14,5,69,46,87,1.0,2,47,Semi-Urban,Software Engineer,24792,0 +98617,Female,37,Masters,10,57,29,24,21,5.0,4,50,Semi-Urban,ML Engineer,40405,0 +98618,Female,42,Bachelors,8,90,97,5,91,8.0,7,88,Rural,Data Analyst,46871,1 +98619,Female,22,Bachelors,0,16,79,40,5,6.0,7,4,Semi-Urban,HR Executive,126454,0 +98620,Female,45,Diploma,19,12,76,72,78,4.0,0,64,Semi-Urban,Software Engineer,51021,0 +98621,Female,55,Bachelors,12,52,38,51,89,2.0,1,32,Urban,ML Engineer,89270,0 +98622,Male,32,Diploma,0,26,85,46,2,0.0,1,98,Rural,HR Executive,79895,1 +98623,Male,50,Diploma,19,51,68,70,99,0.0,7,5,Semi-Urban,Manager,27119,0 +98624,Male,57,Bachelors,3,36,87,15,9,4.0,4,7,Rural,HR Executive,137623,0 +98625,Male,59,Masters,18,42,4,71,57,3.0,5,50,Urban,Data Analyst,134792,0 +98626,Female,54,Bachelors,15,68,0,36,18,6.0,4,71,Semi-Urban,Data Analyst,87625,0 +98627,Other,59,Bachelors,10,5,32,70,18,4.0,2,62,Semi-Urban,ML Engineer,107954,0 +98628,Female,30,Diploma,6,24,71,24,76,6.0,2,96,Urban,Software Engineer,21746,0 +98629,Female,50,High School,13,73,12,32,65,5.0,1,59,Urban,HR Executive,142248,0 +98630,Female,31,Diploma,3,8,23,70,53,2.0,5,72,Urban,HR Executive,48124,0 +98631,Female,54,Diploma,15,6,76,99,2,9.0,4,92,Semi-Urban,Manager,22423,1 +98632,Male,22,Bachelors,11,2,64,55,69,0.0,3,47,Urban,Software Engineer,124381,0 +98633,Male,36,Diploma,8,85,42,78,36,8.0,6,4,Urban,HR Executive,120190,0 +98634,Female,28,Bachelors,1,39,59,45,94,8.0,1,83,Urban,HR Executive,133281,0 +98635,Male,41,Diploma,10,72,28,39,3,8.0,1,72,Rural,Software Engineer,88577,0 +98636,Female,21,PhD,0,97,37,90,77,3.0,6,50,Urban,Data Analyst,78212,1 +98637,Male,27,Masters,11,67,10,98,10,2.0,7,88,Semi-Urban,Software Engineer,81338,1 +98638,Male,34,Bachelors,0,83,76,82,14,1.0,6,67,Urban,Software Engineer,117630,1 +98639,Male,25,High School,1,36,84,72,20,0.0,1,8,Semi-Urban,HR Executive,36137,0 +98640,Female,44,Masters,9,2,85,86,7,6.0,6,41,Semi-Urban,Data Analyst,125466,0 +98641,Male,42,Bachelors,14,51,81,79,76,6.0,1,41,Urban,Manager,83640,1 +98642,Male,28,Bachelors,3,59,69,48,56,9.0,6,52,Urban,HR Executive,93514,0 +98643,Male,33,Masters,6,48,58,93,92,2.0,3,24,Urban,Data Analyst,124088,0 +98644,Female,44,PhD,7,53,79,22,70,6.0,3,50,Urban,ML Engineer,76288,0 +98645,Male,23,Bachelors,14,52,78,34,74,9.0,0,30,Rural,Manager,72011,0 +98646,Female,59,Bachelors,4,66,5,41,47,9.0,6,31,Urban,Software Engineer,65446,0 +98647,Male,23,PhD,11,75,54,40,96,4.0,7,95,Urban,Manager,78512,1 +98648,Female,57,Masters,19,60,33,2,18,5.0,5,64,Urban,HR Executive,119855,0 +98649,Female,35,High School,13,65,81,6,76,6.0,0,0,Rural,Manager,82975,0 +98650,Male,59,Bachelors,7,98,72,70,30,7.0,4,4,Urban,Software Engineer,24721,1 +98651,Male,40,Bachelors,5,39,72,28,18,7.0,2,41,Urban,ML Engineer,35615,0 +98652,Male,31,Masters,3,89,61,62,48,6.0,7,32,Urban,Data Analyst,44721,1 +98653,Female,54,High School,13,50,48,18,40,3.0,4,42,Urban,ML Engineer,21246,0 +98654,Male,41,High School,9,5,64,24,80,3.0,1,4,Urban,Data Analyst,88785,0 +98655,Female,41,Masters,16,37,26,58,91,5.0,1,23,Urban,Software Engineer,128460,0 +98656,Female,33,Bachelors,14,8,90,50,96,1.0,4,15,Rural,HR Executive,26416,0 +98657,Female,22,Diploma,16,22,19,79,54,7.0,3,68,Rural,Data Analyst,32541,0 +98658,Female,22,Diploma,6,96,67,74,58,0.0,5,38,Urban,Manager,111425,1 +98659,Male,43,Bachelors,5,23,81,76,88,2.0,2,16,Urban,ML Engineer,43600,0 +98660,Male,47,High School,16,18,55,72,3,4.0,6,39,Rural,ML Engineer,89541,0 +98661,Male,38,Diploma,16,99,96,51,45,7.0,4,72,Rural,ML Engineer,147663,1 +98662,Male,44,Masters,7,56,19,80,43,1.0,1,9,Urban,Data Analyst,50030,0 +98663,Female,26,Bachelors,8,56,21,85,85,5.0,2,98,Semi-Urban,HR Executive,139356,1 +98664,Male,43,Bachelors,13,62,66,19,0,1.0,6,60,Semi-Urban,Manager,135424,0 +98665,Male,44,Diploma,10,58,17,53,34,9.0,3,64,Urban,ML Engineer,109170,0 +98666,Male,51,Bachelors,19,57,4,60,85,9.0,6,5,Urban,ML Engineer,83379,0 +98667,Male,39,Diploma,19,13,36,48,14,6.0,5,37,Semi-Urban,ML Engineer,23655,0 +98668,Male,28,Bachelors,19,25,45,59,65,5.0,2,81,Urban,Software Engineer,141648,0 +98669,Male,50,PhD,14,11,35,1,10,3.0,3,49,Urban,Software Engineer,54665,0 +98670,Male,43,Masters,15,5,11,89,22,5.0,2,69,Rural,HR Executive,132106,0 +98671,Female,35,Diploma,3,23,56,2,7,0.0,0,78,Urban,ML Engineer,35309,0 +98672,Male,21,Bachelors,7,22,40,94,88,0.0,0,71,Urban,HR Executive,119873,0 +98673,Other,54,Bachelors,0,85,36,8,68,3.0,2,63,Urban,Software Engineer,100323,0 +98674,Male,47,Bachelors,16,98,54,6,93,0.0,4,17,Urban,Manager,83774,0 +98675,Female,56,Bachelors,2,63,94,5,96,9.0,6,78,Rural,Software Engineer,94399,0 +98676,Female,34,Diploma,4,18,2,62,64,1.0,3,98,Urban,ML Engineer,32403,0 +98677,Female,47,Bachelors,4,86,73,79,32,0.0,5,25,Urban,ML Engineer,90909,1 +98678,Female,57,Masters,7,28,13,18,54,2.0,3,74,Semi-Urban,Data Analyst,91380,0 +98679,Female,40,Diploma,16,80,57,11,0,2.0,6,46,Rural,HR Executive,103224,0 +98680,Male,36,Bachelors,3,28,18,69,61,5.0,3,79,Rural,Software Engineer,36619,0 +98681,Female,46,Masters,12,77,18,19,0,1.0,4,45,Urban,ML Engineer,48452,0 +98682,Female,25,Bachelors,10,36,27,26,35,4.0,6,87,Urban,HR Executive,126576,0 +98683,Male,40,Bachelors,7,58,32,89,25,1.0,1,94,Urban,Data Analyst,61201,1 +98684,Male,46,Bachelors,19,19,15,94,30,7.0,3,45,Rural,HR Executive,61515,0 +98685,Female,41,Bachelors,11,60,34,72,88,5.0,0,3,Urban,Data Analyst,122675,0 +98686,Male,24,Bachelors,15,99,91,61,6,4.0,0,9,Urban,Data Analyst,88902,1 +98687,Male,56,Bachelors,14,35,90,75,82,8.0,7,12,Urban,ML Engineer,103078,0 +98688,Other,58,Bachelors,5,62,14,83,43,5.0,7,1,Urban,Data Analyst,149218,0 +98689,Male,27,Bachelors,0,62,63,60,87,7.0,2,33,Rural,Manager,127892,0 +98690,Male,42,Bachelors,12,73,46,52,48,0.0,1,51,Rural,HR Executive,46567,0 +98691,Male,35,Bachelors,17,88,35,9,99,9.0,3,8,Rural,Software Engineer,54750,0 +98692,Male,34,Diploma,3,7,71,86,51,1.0,6,66,Rural,Manager,30037,0 +98693,Male,33,Bachelors,7,76,18,32,82,2.0,5,64,Semi-Urban,Manager,94026,0 +98694,Male,21,High School,4,50,61,87,21,9.0,2,31,Urban,HR Executive,143682,0 +98695,Female,23,Bachelors,1,62,99,37,37,1.0,7,95,Rural,ML Engineer,112566,1 +98696,Male,50,Diploma,13,84,1,55,83,0.0,1,27,Urban,HR Executive,115058,0 +98697,Female,35,Masters,12,90,8,20,50,7.0,0,7,Urban,ML Engineer,122372,0 +98698,Female,58,Masters,6,71,11,87,71,4.0,7,41,Rural,Data Analyst,40410,0 +98699,Male,38,Bachelors,5,98,88,42,24,2.0,3,19,Rural,Data Analyst,120488,1 +98700,Female,45,Diploma,0,61,62,85,64,3.0,2,77,Rural,Manager,121248,1 +98701,Male,42,Bachelors,4,55,30,7,17,0.0,7,75,Rural,Software Engineer,94515,0 +98702,Male,36,High School,3,3,71,87,50,3.0,7,92,Urban,ML Engineer,72209,1 +98703,Male,52,Bachelors,18,43,10,12,86,9.0,6,75,Urban,HR Executive,148675,0 +98704,Male,34,Diploma,9,35,22,59,57,7.0,3,37,Rural,Manager,82276,0 +98705,Female,59,Bachelors,9,2,45,78,78,7.0,1,18,Semi-Urban,Manager,113053,0 +98706,Female,46,Diploma,18,18,16,90,90,7.0,4,80,Semi-Urban,Software Engineer,113158,0 +98707,Male,36,Diploma,0,7,23,79,76,7.0,7,12,Urban,Software Engineer,124579,0 +98708,Female,33,Bachelors,4,60,12,59,90,1.0,1,35,Semi-Urban,Manager,142224,0 +98709,Male,48,Bachelors,16,6,0,49,94,9.0,7,41,Urban,ML Engineer,88911,0 +98710,Other,21,High School,7,17,48,83,72,2.0,3,43,Rural,Manager,33130,0 +98711,Male,39,PhD,5,12,30,8,26,7.0,4,92,Urban,Manager,110130,0 +98712,Female,42,Bachelors,17,24,75,85,16,3.0,2,52,Rural,Data Analyst,65199,0 +98713,Male,38,Bachelors,14,23,45,39,63,5.0,2,67,Urban,Software Engineer,91288,0 +98714,Female,21,Bachelors,6,15,16,43,93,6.0,2,14,Rural,Software Engineer,64262,0 +98715,Male,22,Bachelors,14,13,17,56,37,2.0,7,45,Semi-Urban,Data Analyst,148100,0 +98716,Male,49,High School,6,15,99,60,2,5.0,4,23,Semi-Urban,Data Analyst,130768,0 +98717,Male,28,High School,14,53,67,77,50,0.0,5,49,Semi-Urban,ML Engineer,138007,1 +98718,Male,56,Bachelors,15,58,66,1,24,7.0,4,40,Semi-Urban,Manager,69702,0 +98719,Male,57,Bachelors,11,4,20,19,36,5.0,2,55,Semi-Urban,Software Engineer,111125,0 +98720,Female,27,High School,1,4,49,27,61,4.0,0,6,Urban,Data Analyst,83255,0 +98721,Male,42,Bachelors,6,76,45,35,63,8.0,6,16,Urban,Data Analyst,91683,0 +98722,Female,55,Bachelors,14,13,13,47,77,2.0,0,93,Urban,HR Executive,50101,0 +98723,Male,35,Masters,10,45,55,60,29,0.0,7,21,Urban,Manager,120896,0 +98724,Male,55,Diploma,2,43,62,51,88,4.0,3,83,Urban,Manager,140255,1 +98725,Male,42,High School,0,91,5,37,3,3.0,2,22,Urban,Manager,104621,0 +98726,Male,44,Masters,6,3,33,11,43,5.0,1,3,Semi-Urban,HR Executive,47249,0 +98727,Female,22,High School,3,4,85,34,95,5.0,0,47,Rural,Data Analyst,57071,0 +98728,Male,59,Bachelors,13,36,51,25,56,0.0,1,50,Rural,Data Analyst,126046,0 +98729,Female,58,Bachelors,2,64,91,96,40,2.0,3,99,Semi-Urban,ML Engineer,93650,1 +98730,Female,38,Masters,4,3,32,85,46,6.0,0,64,Urban,HR Executive,32826,0 +98731,Male,47,Bachelors,0,86,4,73,69,6.0,3,39,Semi-Urban,ML Engineer,136467,0 +98732,Male,23,Bachelors,15,96,70,88,29,3.0,6,70,Semi-Urban,Manager,90280,1 +98733,Male,45,Masters,14,67,33,55,1,4.0,5,29,Semi-Urban,HR Executive,111340,0 +98734,Female,50,Bachelors,10,57,14,93,67,5.0,7,10,Urban,Data Analyst,71887,0 +98735,Male,22,Bachelors,14,36,77,24,75,8.0,2,66,Urban,ML Engineer,30473,0 +98736,Male,47,Bachelors,1,17,33,65,70,4.0,6,28,Rural,Data Analyst,76040,0 +98737,Female,21,Bachelors,14,63,73,26,41,4.0,0,68,Rural,ML Engineer,20383,0 +98738,Other,37,Diploma,3,37,25,42,39,1.0,0,50,Rural,HR Executive,69900,0 +98739,Female,34,Masters,19,0,34,74,10,0.0,5,62,Urban,HR Executive,73229,0 +98740,Male,31,Bachelors,8,21,43,83,80,4.0,7,24,Urban,HR Executive,53143,0 +98741,Female,46,Bachelors,10,78,96,51,64,1.0,2,46,Urban,HR Executive,134978,1 +98742,Male,48,Diploma,3,40,12,39,61,1.0,6,31,Rural,Software Engineer,127959,0 +98743,Male,37,Diploma,18,15,28,76,23,6.0,2,0,Semi-Urban,Software Engineer,57950,0 +98744,Female,50,Diploma,11,57,3,28,55,7.0,6,87,Rural,ML Engineer,101451,0 +98745,Female,34,Masters,5,91,28,45,86,8.0,1,92,Rural,ML Engineer,42094,1 +98746,Male,25,Bachelors,5,70,47,3,88,2.0,7,98,Urban,Data Analyst,77824,0 +98747,Male,29,Diploma,17,57,92,59,5,1.0,3,85,Rural,Data Analyst,36882,1 +98748,Male,33,Bachelors,1,88,42,61,23,9.0,1,85,Urban,ML Engineer,54708,1 +98749,Female,23,Diploma,3,82,33,6,86,8.0,3,91,Urban,Data Analyst,68758,0 +98750,Female,34,Masters,1,95,12,43,96,1.0,1,90,Rural,HR Executive,36299,0 +98751,Male,35,High School,18,40,98,88,40,4.0,5,32,Urban,HR Executive,89725,1 +98752,Female,56,Bachelors,1,70,18,62,53,4.0,2,41,Urban,Data Analyst,24155,0 +98753,Male,48,Diploma,17,1,90,55,90,4.0,1,76,Rural,HR Executive,97461,0 +98754,Male,37,Diploma,5,87,95,45,54,4.0,3,43,Urban,Data Analyst,139071,1 +98755,Female,22,Bachelors,19,74,96,24,98,5.0,5,0,Rural,ML Engineer,51525,0 +98756,Male,43,Bachelors,17,93,39,67,60,8.0,6,37,Urban,Software Engineer,85603,1 +98757,Female,34,Diploma,7,11,49,82,58,8.0,7,28,Urban,Data Analyst,71031,0 +98758,Male,22,PhD,14,0,14,27,11,2.0,0,25,Urban,Manager,96266,0 +98759,Female,58,High School,5,17,40,30,34,2.0,3,43,Urban,HR Executive,90063,0 +98760,Female,29,Bachelors,14,24,3,8,92,7.0,2,87,Urban,HR Executive,133961,0 +98761,Male,23,Bachelors,5,20,52,57,23,1.0,1,82,Urban,HR Executive,102895,0 +98762,Female,41,Bachelors,10,59,84,21,49,2.0,7,23,Semi-Urban,Software Engineer,76450,0 +98763,Male,40,Bachelors,1,46,77,34,16,0.0,4,4,Rural,ML Engineer,137710,0 +98764,Male,35,Bachelors,11,38,28,28,11,1.0,4,96,Semi-Urban,Data Analyst,43095,0 +98765,Female,40,Masters,13,96,74,15,95,9.0,4,44,Semi-Urban,HR Executive,80922,0 +98766,Male,47,Masters,8,18,17,87,34,3.0,5,96,Rural,Data Analyst,46578,0 +98767,Other,45,High School,11,16,67,56,71,9.0,1,8,Urban,Software Engineer,106582,0 +98768,Female,35,Diploma,18,89,26,53,67,9.0,1,99,Urban,HR Executive,31406,1 +98769,Male,41,Bachelors,12,48,84,83,57,8.0,1,12,Rural,ML Engineer,106171,0 +98770,Other,28,High School,4,21,42,31,17,1.0,3,19,Urban,ML Engineer,136589,0 +98771,Male,54,Masters,3,97,28,33,27,9.0,2,33,Urban,Data Analyst,110862,0 +98772,Male,31,Masters,5,85,39,7,42,1.0,2,27,Semi-Urban,Manager,22241,0 +98773,Male,59,High School,12,72,86,68,24,4.0,3,76,Urban,Data Analyst,130933,1 +98774,Male,44,Bachelors,9,86,39,89,69,5.0,5,18,Urban,Manager,87903,0 +98775,Male,54,Bachelors,17,88,10,80,46,0.0,7,78,Urban,Software Engineer,103843,1 +98776,Male,41,Masters,14,8,91,73,11,9.0,2,32,Urban,Data Analyst,69622,0 +98777,Male,34,Bachelors,0,45,65,59,24,1.0,5,11,Semi-Urban,Manager,148904,0 +98778,Male,36,Diploma,2,69,41,4,52,5.0,6,74,Semi-Urban,HR Executive,113693,0 +98779,Female,37,Bachelors,7,94,87,34,5,6.0,6,18,Rural,Software Engineer,101347,0 +98780,Male,48,Bachelors,9,99,23,72,27,2.0,1,17,Semi-Urban,Manager,138680,0 +98781,Male,59,Bachelors,17,28,97,17,64,8.0,2,96,Urban,Manager,59893,1 +98782,Male,27,Bachelors,12,4,6,55,55,6.0,5,31,Semi-Urban,Data Analyst,49494,0 +98783,Male,23,Bachelors,7,14,78,34,63,1.0,7,86,Urban,Software Engineer,110014,0 +98784,Male,51,Bachelors,0,84,13,82,57,4.0,5,43,Urban,Manager,97600,0 +98785,Male,48,Masters,7,80,37,99,33,1.0,5,41,Semi-Urban,ML Engineer,96817,1 +98786,Male,38,Masters,13,27,12,53,34,1.0,1,96,Rural,Data Analyst,113161,0 +98787,Male,43,Bachelors,16,88,56,44,86,8.0,1,83,Urban,Manager,59028,1 +98788,Male,41,Diploma,17,1,61,45,11,8.0,0,54,Rural,Software Engineer,116774,0 +98789,Male,55,Bachelors,8,62,58,95,42,3.0,1,22,Urban,Data Analyst,102422,1 +98790,Male,48,Bachelors,10,18,55,94,83,0.0,1,47,Urban,Manager,103346,0 +98791,Female,36,Masters,16,37,51,82,56,7.0,5,48,Urban,Software Engineer,55229,0 +98792,Male,35,Masters,13,93,99,42,93,7.0,4,23,Rural,ML Engineer,107917,1 +98793,Other,31,Diploma,18,63,35,6,90,8.0,4,36,Semi-Urban,Manager,31003,0 +98794,Male,59,Diploma,18,43,91,64,21,6.0,0,27,Rural,HR Executive,138208,0 +98795,Male,49,Diploma,11,29,99,34,4,1.0,6,44,Semi-Urban,ML Engineer,127290,0 +98796,Female,37,Diploma,12,36,94,18,89,0.0,5,91,Urban,Manager,50272,0 +98797,Male,28,Masters,0,32,11,42,80,0.0,0,98,Rural,ML Engineer,122909,0 +98798,Male,38,Bachelors,18,96,88,27,44,3.0,5,85,Urban,ML Engineer,63791,1 +98799,Female,43,Diploma,3,51,93,71,45,8.0,1,16,Urban,HR Executive,135348,0 +98800,Male,26,Diploma,18,11,16,5,64,4.0,1,65,Semi-Urban,Data Analyst,55318,0 +98801,Female,31,Bachelors,2,42,67,54,89,6.0,4,35,Rural,ML Engineer,125790,0 +98802,Female,43,Diploma,0,72,2,94,73,3.0,3,59,Semi-Urban,ML Engineer,41591,0 +98803,Male,39,Masters,15,51,82,23,51,8.0,1,64,Semi-Urban,Manager,132373,0 +98804,Male,41,Masters,17,83,99,52,26,6.0,6,68,Rural,Software Engineer,88804,1 +98805,Female,55,Bachelors,13,88,85,73,42,5.0,3,0,Urban,HR Executive,104907,1 +98806,Male,30,Bachelors,9,84,47,69,69,1.0,3,13,Urban,ML Engineer,116988,0 +98807,Male,30,High School,11,57,26,56,37,2.0,1,72,Semi-Urban,Software Engineer,91652,0 +98808,Female,42,Masters,1,57,64,16,81,5.0,6,93,Semi-Urban,Data Analyst,142293,0 +98809,Male,48,Diploma,7,93,66,96,39,6.0,2,95,Rural,ML Engineer,93905,1 +98810,Female,34,PhD,4,30,81,64,28,9.0,1,69,Rural,Software Engineer,47674,1 +98811,Male,21,Bachelors,4,69,97,66,98,8.0,4,73,Rural,HR Executive,51472,1 +98812,Male,27,Diploma,13,80,98,68,77,8.0,5,85,Rural,Data Analyst,36982,1 +98813,Male,49,Bachelors,11,36,81,21,22,4.0,6,96,Semi-Urban,Data Analyst,47358,0 +98814,Male,40,Bachelors,7,81,22,19,41,6.0,0,71,Urban,ML Engineer,41950,0 +98815,Male,43,Bachelors,5,86,24,49,78,4.0,4,11,Urban,Data Analyst,104854,0 +98816,Male,24,Bachelors,6,85,70,21,86,4.0,6,99,Urban,Software Engineer,57097,1 +98817,Female,35,Bachelors,3,67,46,69,59,6.0,2,12,Urban,Manager,98416,0 +98818,Male,36,High School,3,77,80,68,96,4.0,4,61,Urban,Software Engineer,101549,1 +98819,Male,21,Bachelors,15,59,78,64,4,6.0,4,84,Urban,HR Executive,46880,1 +98820,Male,45,Diploma,7,8,76,84,44,7.0,3,41,Urban,Manager,118700,0 +98821,Male,24,High School,18,46,78,28,50,8.0,1,73,Urban,HR Executive,81160,0 +98822,Male,33,Bachelors,12,38,98,45,40,0.0,1,6,Semi-Urban,ML Engineer,62235,0 +98823,Male,21,Masters,6,46,43,57,8,2.0,6,89,Urban,Manager,22457,1 +98824,Male,45,Masters,15,68,89,96,39,1.0,0,17,Urban,Manager,106898,1 +98825,Other,54,Bachelors,4,91,51,59,21,1.0,7,67,Semi-Urban,Software Engineer,65636,1 +98826,Male,56,Bachelors,1,8,80,38,15,0.0,5,65,Semi-Urban,Software Engineer,22071,0 +98827,Female,21,PhD,3,5,76,20,70,3.0,6,67,Rural,Manager,74182,0 +98828,Male,34,Masters,13,99,78,70,6,5.0,7,74,Semi-Urban,HR Executive,26822,1 +98829,Male,42,Bachelors,13,37,74,21,2,8.0,5,65,Semi-Urban,HR Executive,74757,0 +98830,Male,53,Masters,14,66,21,25,77,7.0,4,60,Urban,Manager,139596,0 +98831,Male,30,Bachelors,3,1,83,86,93,1.0,1,85,Urban,Software Engineer,20190,1 +98832,Male,24,Bachelors,2,60,93,66,69,1.0,2,58,Urban,HR Executive,76654,1 +98833,Female,47,Masters,3,67,36,38,73,1.0,5,29,Semi-Urban,ML Engineer,50215,0 +98834,Male,23,PhD,6,21,1,66,80,7.0,5,14,Urban,Software Engineer,31946,0 +98835,Female,57,Masters,6,57,61,81,28,5.0,4,1,Urban,HR Executive,57987,0 +98836,Male,23,Bachelors,16,69,73,43,26,3.0,7,54,Semi-Urban,Manager,48464,1 +98837,Female,55,Bachelors,2,43,82,91,39,5.0,1,93,Urban,Data Analyst,83503,1 +98838,Male,29,Masters,19,23,25,1,88,6.0,2,91,Semi-Urban,HR Executive,30679,0 +98839,Female,32,Bachelors,17,99,58,61,8,2.0,1,24,Urban,Data Analyst,117289,1 +98840,Male,21,Masters,12,93,34,88,5,1.0,4,16,Rural,Manager,42533,0 +98841,Male,24,Bachelors,12,82,84,65,40,1.0,0,73,Urban,ML Engineer,44021,1 +98842,Male,28,Diploma,10,84,53,38,36,6.0,2,53,Semi-Urban,ML Engineer,127697,0 +98843,Male,48,Bachelors,0,76,23,82,47,0.0,3,95,Urban,Data Analyst,116756,1 +98844,Male,41,High School,11,51,64,17,72,5.0,1,83,Rural,HR Executive,94923,0 +98845,Female,33,Masters,0,30,43,84,67,6.0,1,46,Semi-Urban,Software Engineer,107838,0 +98846,Male,40,High School,12,24,55,87,52,1.0,3,15,Rural,HR Executive,58371,0 +98847,Female,47,PhD,8,64,35,92,98,6.0,2,64,Urban,ML Engineer,63731,1 +98848,Female,57,Bachelors,1,45,3,98,58,8.0,4,79,Semi-Urban,HR Executive,74788,0 +98849,Male,27,Bachelors,5,23,58,7,44,2.0,0,4,Semi-Urban,Manager,66991,0 +98850,Female,39,Masters,18,54,47,52,14,1.0,4,15,Urban,HR Executive,30345,0 +98851,Female,34,Bachelors,12,24,80,72,72,2.0,4,7,Rural,HR Executive,114082,0 +98852,Male,48,High School,6,22,31,2,63,2.0,3,73,Semi-Urban,Manager,51598,0 +98853,Male,37,Masters,11,28,52,0,56,2.0,1,69,Urban,Manager,90294,0 +98854,Male,44,Masters,1,9,98,93,71,6.0,6,65,Urban,Software Engineer,144004,1 +98855,Male,52,PhD,4,98,78,69,48,2.0,3,74,Rural,Manager,129477,1 +98856,Male,39,Masters,7,74,55,69,96,6.0,4,21,Semi-Urban,Data Analyst,110087,0 +98857,Male,39,Bachelors,9,91,11,82,9,0.0,1,24,Urban,ML Engineer,41668,0 +98858,Male,41,Bachelors,14,91,83,1,31,2.0,0,2,Rural,Data Analyst,51747,0 +98859,Female,27,High School,14,20,73,8,78,7.0,2,91,Semi-Urban,Data Analyst,22576,0 +98860,Male,47,Bachelors,9,27,98,14,65,4.0,7,79,Rural,Data Analyst,28358,0 +98861,Male,49,Bachelors,7,23,96,99,42,8.0,0,25,Rural,Software Engineer,48007,1 +98862,Male,31,Bachelors,8,20,26,5,37,1.0,1,95,Semi-Urban,ML Engineer,40567,0 +98863,Male,26,Masters,15,46,90,98,71,6.0,5,86,Urban,Data Analyst,34522,1 +98864,Male,35,High School,18,89,70,70,3,4.0,7,75,Rural,Manager,46565,1 +98865,Male,30,Masters,18,44,17,12,60,8.0,5,22,Urban,Manager,92386,0 +98866,Female,55,Diploma,15,28,46,64,28,7.0,3,67,Urban,HR Executive,55678,0 +98867,Male,46,High School,19,24,77,72,80,2.0,3,61,Rural,HR Executive,80100,0 +98868,Female,27,Bachelors,13,71,63,93,27,0.0,7,27,Urban,Data Analyst,104209,1 +98869,Male,36,Bachelors,4,24,90,17,57,5.0,4,81,Urban,Data Analyst,128485,0 +98870,Female,43,Bachelors,13,93,15,27,80,9.0,0,63,Urban,Software Engineer,145526,0 +98871,Female,37,High School,10,54,75,77,65,2.0,2,40,Semi-Urban,Software Engineer,41926,1 +98872,Male,47,Diploma,2,63,8,43,62,8.0,7,79,Semi-Urban,Data Analyst,84708,0 +98873,Male,38,Masters,6,28,89,46,66,5.0,0,44,Semi-Urban,Manager,69089,0 +98874,Male,54,Bachelors,10,1,53,56,14,0.0,1,7,Urban,Software Engineer,114846,0 +98875,Male,59,Bachelors,3,3,21,66,57,9.0,5,58,Urban,Software Engineer,20236,0 +98876,Female,43,Diploma,2,93,84,75,76,6.0,5,54,Rural,Data Analyst,26565,1 +98877,Male,38,Diploma,6,26,67,23,46,5.0,4,13,Urban,ML Engineer,130853,0 +98878,Male,52,PhD,11,90,38,22,69,3.0,5,48,Urban,Manager,123367,0 +98879,Female,21,High School,12,97,49,95,0,2.0,7,59,Semi-Urban,Data Analyst,126022,1 +98880,Female,56,Bachelors,19,51,4,45,30,1.0,2,52,Urban,Software Engineer,50654,0 +98881,Female,33,Diploma,7,83,53,51,28,8.0,6,27,Urban,HR Executive,21623,0 +98882,Male,46,High School,18,39,96,40,29,5.0,4,43,Rural,Software Engineer,122401,0 +98883,Female,25,High School,18,35,10,75,80,6.0,4,6,Rural,HR Executive,52645,0 +98884,Male,34,High School,19,42,72,55,53,0.0,7,14,Urban,Manager,28830,0 +98885,Male,59,Masters,14,65,9,2,96,8.0,3,10,Semi-Urban,Software Engineer,144293,0 +98886,Male,35,Bachelors,8,31,84,81,66,3.0,4,8,Urban,ML Engineer,138420,0 +98887,Male,54,High School,3,31,75,40,65,7.0,5,88,Rural,ML Engineer,149117,0 +98888,Male,42,Masters,2,35,11,66,25,8.0,6,35,Rural,Software Engineer,89744,0 +98889,Male,31,Bachelors,11,82,62,28,96,5.0,7,1,Semi-Urban,ML Engineer,67454,0 +98890,Female,47,Masters,1,99,85,68,6,8.0,0,95,Semi-Urban,ML Engineer,82019,1 +98891,Male,36,PhD,19,41,82,94,88,2.0,5,38,Urban,ML Engineer,113043,1 +98892,Male,44,Bachelors,11,57,18,52,30,5.0,6,71,Urban,Data Analyst,26816,0 +98893,Male,53,High School,6,5,42,93,95,0.0,5,80,Urban,Manager,50343,0 +98894,Male,31,Diploma,1,97,71,24,10,6.0,1,88,Urban,Data Analyst,25829,1 +98895,Male,43,Bachelors,17,37,97,25,73,4.0,2,55,Semi-Urban,Manager,148929,0 +98896,Male,51,Bachelors,16,73,6,15,3,1.0,1,73,Semi-Urban,Data Analyst,106923,0 +98897,Male,58,Bachelors,9,19,59,39,25,6.0,7,13,Urban,HR Executive,58039,0 +98898,Male,52,High School,9,39,54,60,68,4.0,5,35,Urban,Software Engineer,31422,0 +98899,Female,28,Bachelors,6,54,14,65,96,0.0,6,99,Urban,Data Analyst,141416,0 +98900,Male,34,Bachelors,2,20,9,92,52,8.0,2,60,Urban,Software Engineer,136362,0 +98901,Male,27,Masters,0,33,69,37,61,0.0,3,17,Rural,ML Engineer,44348,0 +98902,Male,30,PhD,10,94,96,58,74,8.0,4,32,Urban,Data Analyst,33342,1 +98903,Male,45,High School,9,70,54,70,76,0.0,7,99,Rural,Manager,50193,1 +98904,Male,56,Masters,6,56,37,9,43,9.0,4,33,Rural,HR Executive,46522,0 +98905,Male,37,Masters,16,87,56,99,78,4.0,2,3,Semi-Urban,ML Engineer,94957,1 +98906,Female,21,Bachelors,18,20,12,70,43,4.0,0,39,Semi-Urban,HR Executive,46087,0 +98907,Female,41,Bachelors,15,29,39,17,1,2.0,6,41,Urban,Software Engineer,70228,0 +98908,Female,32,Diploma,4,3,98,83,28,9.0,7,42,Rural,Software Engineer,76543,0 +98909,Male,27,High School,3,90,59,60,61,4.0,0,17,Urban,Data Analyst,33447,0 +98910,Male,25,Masters,4,78,30,37,6,0.0,2,88,Semi-Urban,Data Analyst,48197,0 +98911,Male,35,Bachelors,13,51,17,90,61,5.0,4,26,Urban,HR Executive,147802,0 +98912,Male,54,High School,10,58,77,42,33,4.0,1,23,Urban,HR Executive,89436,0 +98913,Male,42,Bachelors,16,38,1,66,44,2.0,6,39,Urban,Manager,110516,0 +98914,Other,39,Bachelors,15,18,84,17,5,2.0,1,63,Urban,ML Engineer,30694,0 +98915,Male,45,Bachelors,18,38,34,24,17,7.0,0,89,Urban,Manager,40375,0 +98916,Other,37,Diploma,6,98,3,16,19,5.0,6,94,Semi-Urban,HR Executive,107926,0 +98917,Male,52,Diploma,2,3,17,77,84,4.0,3,51,Rural,Data Analyst,133297,0 +98918,Male,43,Bachelors,5,43,29,84,1,7.0,3,7,Urban,Manager,119000,0 +98919,Male,26,Bachelors,12,16,2,37,26,0.0,3,62,Semi-Urban,Software Engineer,67445,0 +98920,Male,24,High School,7,6,97,56,91,1.0,3,21,Semi-Urban,Manager,53158,0 +98921,Male,21,Bachelors,12,36,30,71,72,8.0,4,89,Urban,Data Analyst,56161,0 +98922,Male,54,Masters,6,8,90,94,79,7.0,3,74,Urban,HR Executive,107728,1 +98923,Female,49,Bachelors,12,78,42,58,9,9.0,5,98,Urban,Manager,51728,1 +98924,Male,24,Diploma,11,81,87,46,10,8.0,6,55,Rural,Data Analyst,101738,1 +98925,Female,57,High School,19,99,92,89,85,3.0,7,89,Urban,Software Engineer,68579,1 +98926,Male,47,Bachelors,18,85,35,82,36,4.0,2,33,Semi-Urban,Software Engineer,142911,1 +98927,Female,33,Bachelors,2,44,61,24,65,1.0,1,30,Semi-Urban,Software Engineer,32585,0 +98928,Female,23,Bachelors,16,42,64,75,67,7.0,3,75,Rural,Software Engineer,45903,1 +98929,Female,57,Diploma,17,17,50,71,57,3.0,1,26,Urban,HR Executive,48304,0 +98930,Female,26,High School,5,75,47,3,69,8.0,4,55,Rural,ML Engineer,78914,0 +98931,Male,30,Masters,10,17,17,38,63,9.0,2,28,Urban,Data Analyst,25124,0 +98932,Male,43,Bachelors,18,15,62,64,0,5.0,2,23,Rural,Data Analyst,129509,0 +98933,Female,51,Diploma,11,35,17,4,45,0.0,0,2,Semi-Urban,HR Executive,143926,0 +98934,Female,35,PhD,1,81,41,31,16,4.0,7,60,Urban,Data Analyst,79169,0 +98935,Male,37,Masters,16,52,74,44,15,7.0,5,55,Urban,HR Executive,115514,0 +98936,Male,49,Masters,16,58,85,47,81,3.0,7,69,Semi-Urban,Software Engineer,81926,1 +98937,Male,59,High School,3,91,42,7,10,8.0,7,56,Rural,Manager,138025,0 +98938,Male,53,Diploma,11,90,49,66,76,3.0,0,66,Urban,Data Analyst,85485,1 +98939,Male,47,Bachelors,2,99,23,80,87,2.0,0,62,Semi-Urban,Manager,136403,1 +98940,Other,22,Diploma,18,12,31,20,25,3.0,0,58,Semi-Urban,ML Engineer,112152,0 +98941,Female,48,Masters,3,13,83,96,42,1.0,7,8,Urban,Software Engineer,114518,0 +98942,Male,24,Diploma,8,88,38,78,45,7.0,0,75,Rural,Software Engineer,149877,1 +98943,Male,59,PhD,14,76,58,63,6,5.0,2,99,Rural,Data Analyst,68936,1 +98944,Male,33,High School,1,29,12,8,49,6.0,2,28,Semi-Urban,Software Engineer,133879,0 +98945,Female,26,Diploma,8,18,1,20,86,6.0,0,87,Urban,HR Executive,125630,0 +98946,Male,36,Bachelors,13,52,44,54,87,5.0,0,21,Urban,Manager,146972,0 +98947,Male,24,Bachelors,5,16,96,78,31,1.0,6,81,Urban,HR Executive,44090,1 +98948,Female,42,Bachelors,14,71,90,27,68,9.0,6,40,Semi-Urban,ML Engineer,105437,0 +98949,Female,45,Bachelors,16,29,59,77,34,0.0,4,76,Urban,Software Engineer,86387,1 +98950,Male,53,Masters,17,67,23,65,78,5.0,6,82,Rural,Data Analyst,98248,1 +98951,Female,50,Bachelors,17,83,8,19,7,8.0,2,5,Urban,Manager,74739,0 +98952,Female,51,Bachelors,3,18,63,2,20,2.0,6,75,Semi-Urban,Software Engineer,80817,0 +98953,Male,41,Diploma,16,57,24,48,88,6.0,6,7,Urban,HR Executive,96896,0 +98954,Female,29,Diploma,14,47,53,50,80,8.0,6,27,Rural,Software Engineer,77701,0 +98955,Male,58,Diploma,19,13,88,67,12,6.0,6,11,Urban,HR Executive,134837,0 +98956,Other,48,Masters,13,50,52,17,33,1.0,6,56,Urban,ML Engineer,144750,0 +98957,Female,58,Bachelors,14,91,69,48,36,0.0,4,2,Semi-Urban,ML Engineer,35985,0 +98958,Male,52,Bachelors,11,16,32,59,53,9.0,5,97,Urban,Data Analyst,112488,0 +98959,Female,43,Bachelors,10,92,46,53,79,2.0,5,0,Urban,ML Engineer,141887,0 +98960,Other,43,High School,6,18,67,92,20,3.0,1,67,Urban,HR Executive,78348,1 +98961,Male,24,Bachelors,1,98,75,19,13,0.0,1,47,Urban,Data Analyst,28898,1 +98962,Female,26,Bachelors,15,67,40,55,89,1.0,6,17,Semi-Urban,Software Engineer,26692,0 +98963,Female,44,Masters,19,13,7,84,30,8.0,1,45,Urban,Manager,39330,0 +98964,Male,39,Bachelors,13,35,7,93,23,0.0,4,46,Urban,Software Engineer,105841,0 +98965,Male,56,Bachelors,8,26,30,12,40,6.0,7,95,Urban,Manager,137327,0 +98966,Male,57,Bachelors,1,33,49,28,4,6.0,3,67,Urban,Software Engineer,59065,0 +98967,Male,25,Bachelors,16,0,41,60,91,7.0,5,96,Rural,Data Analyst,34900,0 +98968,Male,57,PhD,19,85,33,50,41,4.0,4,67,Urban,Software Engineer,106120,1 +98969,Male,41,Diploma,14,45,33,30,66,8.0,7,72,Urban,Manager,147315,0 +98970,Male,35,Bachelors,18,52,89,32,27,4.0,4,35,Rural,Data Analyst,141597,0 +98971,Male,53,Masters,4,0,85,10,24,6.0,3,69,Urban,Software Engineer,41138,0 +98972,Male,53,Bachelors,17,84,72,94,16,3.0,2,62,Urban,ML Engineer,73718,1 +98973,Female,52,Diploma,4,28,57,68,72,3.0,2,65,Semi-Urban,HR Executive,51584,0 +98974,Male,41,Bachelors,15,95,95,83,12,1.0,3,44,Urban,ML Engineer,32965,1 +98975,Female,52,High School,12,54,30,48,26,1.0,6,97,Urban,Data Analyst,77582,0 +98976,Other,35,Bachelors,7,84,9,63,83,2.0,6,93,Urban,Software Engineer,54173,1 +98977,Male,38,Bachelors,15,70,8,85,98,5.0,2,52,Urban,ML Engineer,93704,0 +98978,Female,49,Bachelors,19,13,3,67,1,6.0,7,38,Urban,ML Engineer,52791,0 +98979,Male,59,Diploma,18,13,36,89,74,0.0,3,70,Urban,Manager,29418,0 +98980,Male,38,Bachelors,17,33,70,32,23,9.0,2,41,Rural,HR Executive,28676,0 +98981,Male,47,Bachelors,4,72,68,40,37,3.0,2,33,Urban,Data Analyst,42914,0 +98982,Other,40,High School,15,3,21,74,22,3.0,7,1,Rural,Manager,119594,0 +98983,Male,47,Bachelors,6,7,14,35,21,1.0,5,4,Urban,HR Executive,62910,0 +98984,Female,21,Diploma,0,19,96,36,67,9.0,6,60,Urban,Data Analyst,130440,0 +98985,Male,34,Diploma,13,35,52,44,93,5.0,0,16,Urban,Manager,137257,0 +98986,Male,29,Bachelors,7,79,43,39,47,5.0,3,77,Urban,ML Engineer,90134,1 +98987,Female,48,Bachelors,7,65,8,98,37,5.0,6,49,Urban,ML Engineer,127345,0 +98988,Female,47,Diploma,2,49,74,8,33,4.0,5,47,Rural,Data Analyst,30963,0 +98989,Female,37,Bachelors,1,22,2,38,24,7.0,1,15,Semi-Urban,HR Executive,89765,0 +98990,Female,35,Diploma,10,74,2,83,74,8.0,3,68,Urban,Data Analyst,129086,0 +98991,Female,59,Bachelors,13,59,68,76,6,4.0,4,89,Rural,Software Engineer,145149,1 +98992,Female,43,Bachelors,3,32,71,91,44,7.0,0,34,Rural,HR Executive,114723,0 +98993,Male,24,PhD,7,89,47,15,41,6.0,5,33,Rural,Manager,110002,0 +98994,Male,52,Diploma,17,36,93,12,38,5.0,0,75,Semi-Urban,Data Analyst,101568,0 +98995,Female,36,Diploma,16,25,75,26,43,6.0,4,64,Rural,ML Engineer,25297,0 +98996,Female,40,Masters,13,65,16,6,74,5.0,4,68,Urban,Data Analyst,68615,0 +98997,Male,47,Bachelors,5,4,38,69,72,6.0,2,54,Rural,HR Executive,32311,0 +98998,Male,23,High School,6,93,45,56,2,8.0,5,25,Urban,Manager,87021,0 +98999,Female,52,Masters,18,18,6,66,94,7.0,5,37,Urban,HR Executive,62403,0 +99000,Male,29,Bachelors,2,65,31,42,88,9.0,1,85,Urban,Data Analyst,54639,0 +99001,Male,36,Bachelors,1,76,89,53,35,7.0,3,99,Rural,Data Analyst,149578,1 +99002,Male,50,High School,0,34,86,45,73,8.0,7,53,Rural,HR Executive,80327,0 +99003,Male,35,High School,0,28,91,76,14,9.0,6,43,Urban,Manager,114641,1 +99004,Male,40,Masters,17,8,80,84,99,0.0,7,92,Rural,HR Executive,83906,1 +99005,Male,37,Bachelors,18,71,84,40,35,8.0,3,91,Urban,Software Engineer,98751,1 +99006,Male,28,Bachelors,13,19,80,65,20,0.0,5,74,Urban,ML Engineer,83642,1 +99007,Female,29,Bachelors,14,26,92,9,37,6.0,1,36,Semi-Urban,HR Executive,45799,0 +99008,Male,50,Bachelors,19,30,76,67,96,9.0,4,4,Urban,ML Engineer,115509,0 +99009,Male,25,Masters,9,5,70,27,59,6.0,2,37,Urban,Data Analyst,50765,0 +99010,Male,36,Bachelors,11,73,35,36,74,3.0,7,8,Urban,ML Engineer,50809,0 +99011,Male,27,Bachelors,1,38,83,69,19,0.0,2,32,Semi-Urban,HR Executive,115303,0 +99012,Male,27,High School,11,32,32,62,35,9.0,4,46,Semi-Urban,Software Engineer,93461,0 +99013,Male,32,Bachelors,1,81,37,69,65,6.0,3,23,Semi-Urban,Manager,24897,0 +99014,Male,36,Masters,4,42,82,16,68,4.0,1,9,Urban,Manager,59288,0 +99015,Female,29,PhD,14,73,61,0,73,5.0,4,12,Semi-Urban,Manager,117403,0 +99016,Male,23,Bachelors,15,40,54,61,82,4.0,7,70,Rural,Manager,106287,0 +99017,Male,56,Bachelors,1,85,66,58,90,2.0,5,56,Rural,Software Engineer,94409,1 +99018,Male,36,Bachelors,14,3,27,92,83,0.0,1,63,Semi-Urban,Software Engineer,144281,0 +99019,Other,32,Diploma,7,20,0,15,78,0.0,1,85,Rural,ML Engineer,122489,0 +99020,Male,34,Masters,18,45,14,39,69,4.0,2,3,Semi-Urban,Data Analyst,59998,0 +99021,Female,43,PhD,4,84,96,83,75,7.0,3,43,Urban,ML Engineer,125030,1 +99022,Male,53,Bachelors,2,90,4,36,12,6.0,1,1,Rural,HR Executive,30010,0 +99023,Female,21,Masters,10,21,46,41,37,1.0,2,48,Rural,Data Analyst,88335,0 +99024,Female,58,Diploma,1,50,0,30,23,9.0,0,1,Rural,Data Analyst,122022,0 +99025,Male,38,Bachelors,10,30,94,41,44,2.0,2,14,Semi-Urban,Software Engineer,138336,0 +99026,Female,54,Bachelors,15,88,28,4,62,0.0,7,10,Semi-Urban,Software Engineer,124289,0 +99027,Male,21,Diploma,5,25,61,42,81,8.0,7,83,Urban,Software Engineer,80753,0 +99028,Male,32,Bachelors,18,52,75,22,5,5.0,4,98,Urban,Software Engineer,109101,1 +99029,Male,46,PhD,16,7,55,27,30,3.0,5,2,Urban,HR Executive,100688,0 +99030,Female,40,Bachelors,10,12,51,99,76,1.0,5,18,Rural,HR Executive,135557,0 +99031,Male,23,Bachelors,2,86,34,78,72,8.0,7,90,Semi-Urban,ML Engineer,97586,1 +99032,Other,28,Diploma,11,63,84,41,15,7.0,4,69,Urban,HR Executive,38128,1 +99033,Female,50,High School,8,38,66,66,12,7.0,1,28,Urban,ML Engineer,25155,0 +99034,Male,59,Diploma,16,76,47,93,60,4.0,6,61,Urban,HR Executive,83694,1 +99035,Other,43,Masters,13,90,7,51,24,9.0,2,60,Urban,Software Engineer,133846,0 +99036,Male,51,Masters,6,89,51,40,61,0.0,0,5,Urban,ML Engineer,63701,0 +99037,Female,35,High School,4,23,40,12,8,1.0,2,68,Urban,HR Executive,53411,0 +99038,Female,42,Bachelors,14,99,92,64,15,4.0,3,41,Rural,HR Executive,129100,1 +99039,Male,38,Bachelors,6,38,23,78,73,5.0,2,10,Urban,Manager,23246,0 +99040,Male,21,Masters,1,79,55,57,73,6.0,3,36,Semi-Urban,ML Engineer,76923,0 +99041,Male,59,Bachelors,9,23,42,28,46,8.0,3,29,Rural,Manager,25816,0 +99042,Female,28,High School,19,98,71,84,90,1.0,5,93,Urban,Manager,35775,1 +99043,Female,30,Diploma,19,85,5,32,51,9.0,3,90,Urban,Manager,87065,0 +99044,Female,26,Masters,17,1,53,7,40,4.0,2,0,Urban,ML Engineer,60529,0 +99045,Male,37,Bachelors,10,8,0,97,78,1.0,6,74,Semi-Urban,Data Analyst,70873,0 +99046,Male,37,Bachelors,19,92,1,16,7,8.0,1,73,Semi-Urban,Manager,34672,0 +99047,Other,39,PhD,19,86,79,49,35,8.0,5,95,Urban,Software Engineer,50494,1 +99048,Male,42,High School,16,81,9,70,38,1.0,1,58,Urban,Data Analyst,115436,0 +99049,Male,29,Masters,13,76,78,65,2,6.0,4,80,Urban,HR Executive,125022,1 +99050,Male,30,Masters,14,68,44,47,10,3.0,4,50,Urban,ML Engineer,138258,0 +99051,Female,40,PhD,10,23,69,0,15,2.0,2,61,Rural,Data Analyst,130167,0 +99052,Other,46,Masters,18,67,19,60,4,3.0,4,39,Semi-Urban,HR Executive,36287,0 +99053,Male,57,Masters,11,24,85,28,49,1.0,4,34,Rural,HR Executive,100408,0 +99054,Male,36,Diploma,17,64,65,21,46,1.0,3,94,Urban,Software Engineer,80068,1 +99055,Female,37,Bachelors,14,70,72,99,41,0.0,4,2,Urban,Data Analyst,104705,1 +99056,Male,46,Diploma,19,84,8,27,74,8.0,3,60,Urban,ML Engineer,101970,0 +99057,Male,50,Masters,3,83,6,63,37,1.0,7,52,Rural,Software Engineer,87361,0 +99058,Male,50,Diploma,6,71,60,26,92,8.0,5,37,Semi-Urban,HR Executive,64831,0 +99059,Male,41,Masters,7,75,87,63,10,4.0,4,15,Urban,HR Executive,39135,1 +99060,Male,39,Masters,0,62,4,41,97,5.0,0,18,Urban,Data Analyst,126552,0 +99061,Male,22,Diploma,8,27,66,92,77,3.0,6,41,Semi-Urban,Data Analyst,21734,0 +99062,Male,26,Bachelors,16,71,85,83,3,4.0,7,46,Rural,Manager,57040,1 +99063,Female,48,High School,2,24,56,18,33,5.0,4,69,Semi-Urban,HR Executive,146982,0 +99064,Male,48,PhD,6,63,32,51,86,4.0,7,14,Urban,Data Analyst,29044,0 +99065,Female,24,High School,11,82,90,4,95,1.0,6,3,Urban,ML Engineer,100542,0 +99066,Other,54,Bachelors,4,82,98,17,24,7.0,0,8,Urban,Data Analyst,143294,0 +99067,Female,32,Bachelors,15,43,11,33,22,5.0,6,17,Rural,Data Analyst,85551,0 +99068,Male,46,Diploma,7,30,82,41,89,2.0,6,20,Urban,HR Executive,124299,0 +99069,Male,58,Bachelors,0,68,10,14,71,8.0,5,15,Urban,HR Executive,80621,0 +99070,Male,42,High School,18,79,18,61,58,1.0,0,1,Urban,Software Engineer,118503,0 +99071,Female,50,Masters,6,15,76,6,4,2.0,3,63,Semi-Urban,HR Executive,140055,0 +99072,Other,30,Diploma,5,41,59,51,95,2.0,3,17,Semi-Urban,Software Engineer,117930,0 +99073,Male,28,Bachelors,15,4,14,96,56,2.0,6,29,Semi-Urban,Manager,50588,0 +99074,Female,29,Bachelors,6,34,83,67,87,3.0,6,30,Urban,Software Engineer,48512,0 +99075,Male,33,Masters,5,94,20,51,82,8.0,1,88,Urban,Data Analyst,147591,1 +99076,Female,24,Bachelors,6,1,23,92,18,4.0,5,13,Semi-Urban,HR Executive,54465,0 +99077,Female,53,Diploma,11,15,34,60,74,5.0,3,43,Semi-Urban,Software Engineer,136673,0 +99078,Male,47,Diploma,17,95,82,94,0,2.0,0,76,Urban,HR Executive,20573,1 +99079,Female,30,Diploma,15,22,3,13,13,5.0,3,61,Semi-Urban,Data Analyst,104983,0 +99080,Female,22,Bachelors,12,77,66,71,46,8.0,5,91,Semi-Urban,HR Executive,43323,1 +99081,Male,44,Diploma,16,47,10,48,94,9.0,6,96,Rural,Data Analyst,86629,0 +99082,Male,56,High School,12,86,52,81,11,5.0,0,17,Semi-Urban,Manager,24120,1 +99083,Other,50,Masters,19,30,29,18,92,6.0,4,82,Rural,Manager,96113,0 +99084,Male,42,Diploma,5,94,5,4,11,5.0,1,87,Urban,ML Engineer,133266,0 +99085,Male,22,Diploma,2,58,71,37,75,2.0,2,42,Urban,HR Executive,114007,0 +99086,Other,33,Bachelors,1,24,48,67,68,6.0,6,60,Urban,Software Engineer,28273,0 +99087,Male,38,Diploma,10,82,23,33,58,1.0,0,70,Rural,Software Engineer,149096,0 +99088,Female,55,Bachelors,2,9,98,6,91,9.0,1,70,Urban,Data Analyst,63142,0 +99089,Female,25,Bachelors,5,29,23,2,5,9.0,1,72,Semi-Urban,Manager,112183,0 +99090,Female,59,Diploma,7,91,25,40,33,0.0,2,29,Rural,HR Executive,78260,0 +99091,Female,23,Bachelors,4,42,90,0,67,2.0,1,55,Semi-Urban,ML Engineer,57087,0 +99092,Male,26,High School,13,29,25,66,22,9.0,0,64,Semi-Urban,HR Executive,76703,0 +99093,Female,26,Bachelors,17,66,13,59,70,8.0,7,87,Urban,ML Engineer,57764,0 +99094,Male,51,Masters,1,62,92,43,49,8.0,3,24,Urban,Software Engineer,119408,0 +99095,Male,54,Diploma,7,71,86,78,15,7.0,5,6,Semi-Urban,ML Engineer,145006,1 +99096,Female,28,Bachelors,14,49,78,39,53,5.0,2,80,Semi-Urban,Data Analyst,144822,1 +99097,Male,30,Bachelors,11,52,2,99,15,0.0,3,13,Urban,Software Engineer,87559,0 +99098,Female,44,Bachelors,2,2,90,89,85,2.0,1,38,Urban,HR Executive,61212,0 +99099,Male,41,Bachelors,1,16,94,63,67,3.0,2,2,Urban,Manager,147691,0 +99100,Female,25,Bachelors,16,82,52,70,47,5.0,3,99,Rural,ML Engineer,111016,1 +99101,Male,58,Bachelors,9,25,48,65,0,2.0,2,93,Urban,Data Analyst,43483,0 +99102,Male,52,Bachelors,16,88,96,17,40,1.0,5,63,Urban,Software Engineer,28616,1 +99103,Female,48,Diploma,13,80,63,7,37,4.0,4,62,Semi-Urban,Manager,105080,0 +99104,Female,55,Bachelors,0,66,44,0,71,9.0,2,65,Urban,Data Analyst,142087,0 +99105,Male,30,Bachelors,2,12,54,75,90,1.0,7,22,Rural,Data Analyst,41623,0 +99106,Male,28,Diploma,8,29,23,82,49,1.0,2,96,Urban,Data Analyst,44004,0 +99107,Male,48,Bachelors,6,17,56,54,72,4.0,4,42,Semi-Urban,HR Executive,109550,0 +99108,Female,21,Masters,14,81,81,85,18,4.0,3,12,Urban,Manager,50625,1 +99109,Male,40,Diploma,0,93,4,18,38,5.0,4,75,Rural,ML Engineer,76157,0 +99110,Other,37,PhD,4,41,35,99,26,0.0,6,89,Urban,ML Engineer,42635,1 +99111,Female,38,Diploma,3,43,82,1,44,4.0,5,83,Urban,Data Analyst,100566,0 +99112,Female,22,Bachelors,10,54,0,71,84,9.0,2,78,Urban,Data Analyst,93449,0 +99113,Male,21,Bachelors,10,93,89,49,10,4.0,5,51,Urban,Software Engineer,43384,1 +99114,Other,44,Diploma,7,16,15,12,26,5.0,1,14,Urban,Manager,115481,0 +99115,Male,26,Diploma,14,75,16,62,56,7.0,2,15,Semi-Urban,HR Executive,101287,0 +99116,Male,48,Bachelors,16,96,10,21,82,6.0,1,70,Urban,ML Engineer,45703,0 +99117,Male,24,Bachelors,9,52,1,1,84,8.0,2,13,Semi-Urban,Manager,95081,0 +99118,Female,49,Bachelors,9,95,3,21,28,9.0,5,79,Urban,ML Engineer,40544,0 +99119,Male,37,High School,14,1,54,50,16,0.0,4,78,Urban,Manager,137907,0 +99120,Male,55,Diploma,7,37,44,78,19,7.0,2,70,Urban,Data Analyst,61013,0 +99121,Male,41,Diploma,4,61,31,11,50,4.0,1,90,Urban,Data Analyst,20205,0 +99122,Male,38,Masters,7,59,75,18,97,9.0,4,39,Urban,Manager,49084,0 +99123,Male,28,Bachelors,0,99,21,34,62,9.0,7,90,Urban,Data Analyst,69353,1 +99124,Male,45,Diploma,11,73,98,92,78,3.0,3,90,Rural,Software Engineer,110042,1 +99125,Male,35,Diploma,17,93,44,12,76,7.0,1,93,Rural,Data Analyst,73757,1 +99126,Female,32,Bachelors,10,75,26,44,80,6.0,5,83,Urban,Data Analyst,82855,0 +99127,Female,56,Bachelors,16,25,30,44,98,5.0,3,48,Urban,HR Executive,47290,0 +99128,Female,43,Masters,19,10,41,65,7,5.0,6,82,Semi-Urban,Data Analyst,146238,0 +99129,Male,28,Masters,13,40,40,46,88,2.0,3,99,Urban,Manager,81357,0 +99130,Male,56,Diploma,4,94,43,23,21,0.0,1,8,Urban,HR Executive,122697,0 +99131,Female,39,High School,19,66,64,23,78,1.0,4,83,Rural,Software Engineer,53970,0 +99132,Male,34,Bachelors,9,61,53,22,90,7.0,3,97,Urban,Data Analyst,145487,0 +99133,Male,55,Bachelors,13,4,51,89,14,5.0,4,94,Urban,Manager,21152,1 +99134,Male,55,High School,3,36,56,85,86,9.0,5,10,Semi-Urban,Data Analyst,28794,0 +99135,Male,40,Bachelors,5,85,16,13,75,6.0,7,37,Urban,Software Engineer,97870,0 +99136,Male,43,Bachelors,16,58,0,80,85,8.0,0,76,Semi-Urban,Manager,111079,0 +99137,Female,54,High School,18,88,96,73,9,9.0,5,20,Urban,Software Engineer,95743,1 +99138,Female,35,Diploma,14,73,44,79,27,4.0,3,94,Urban,Software Engineer,149624,1 +99139,Male,25,Bachelors,14,44,44,60,0,2.0,6,42,Urban,Data Analyst,52597,0 +99140,Male,46,Masters,11,50,57,43,77,0.0,7,25,Urban,ML Engineer,81118,0 +99141,Male,56,Bachelors,4,67,27,39,30,1.0,3,7,Rural,ML Engineer,27239,0 +99142,Female,52,Diploma,15,49,4,99,25,4.0,4,98,Urban,Software Engineer,129376,1 +99143,Female,49,Diploma,2,78,60,2,94,1.0,5,57,Rural,Data Analyst,81779,0 +99144,Male,38,High School,14,13,9,79,67,8.0,2,40,Rural,HR Executive,113994,0 +99145,Female,28,Diploma,0,54,6,41,42,5.0,2,22,Urban,HR Executive,85258,0 +99146,Female,50,Bachelors,13,68,47,31,27,0.0,5,66,Urban,Manager,99320,0 +99147,Male,40,Masters,3,59,99,32,23,3.0,7,53,Urban,Manager,25489,1 +99148,Female,57,Diploma,3,38,71,54,18,0.0,1,61,Urban,Software Engineer,62133,0 +99149,Male,30,Bachelors,13,54,39,87,39,3.0,0,23,Urban,Manager,47475,0 +99150,Female,41,Masters,1,89,83,42,8,2.0,4,53,Semi-Urban,ML Engineer,119844,1 +99151,Male,52,Bachelors,0,25,51,39,30,6.0,0,85,Rural,Software Engineer,59560,0 +99152,Female,40,Diploma,7,75,61,59,95,8.0,3,81,Semi-Urban,Software Engineer,22304,1 +99153,Male,41,Bachelors,1,34,76,26,52,8.0,7,30,Urban,ML Engineer,58547,0 +99154,Female,53,Bachelors,2,95,98,56,11,2.0,5,86,Urban,ML Engineer,103317,1 +99155,Male,27,Bachelors,9,38,84,55,47,8.0,2,84,Urban,Software Engineer,108451,1 +99156,Female,47,PhD,9,34,52,19,83,6.0,4,69,Semi-Urban,ML Engineer,133245,0 +99157,Male,51,PhD,16,6,85,33,3,5.0,1,23,Semi-Urban,HR Executive,109771,0 +99158,Male,25,Bachelors,0,11,82,19,78,0.0,7,18,Rural,Data Analyst,69144,0 +99159,Male,32,Bachelors,0,78,83,23,45,9.0,5,26,Rural,ML Engineer,82604,0 +99160,Male,57,Diploma,4,4,17,95,99,0.0,7,36,Urban,Manager,138236,0 +99161,Male,42,PhD,4,81,6,52,69,6.0,6,6,Semi-Urban,ML Engineer,40488,0 +99162,Male,56,Bachelors,13,2,10,79,67,4.0,1,48,Rural,Manager,106351,0 +99163,Male,35,Diploma,1,76,26,4,53,0.0,4,78,Urban,Manager,33842,0 +99164,Other,24,High School,7,47,82,52,76,7.0,5,65,Semi-Urban,Software Engineer,103142,1 +99165,Female,49,Bachelors,15,62,64,94,74,9.0,3,78,Rural,Data Analyst,108989,1 +99166,Male,49,Diploma,13,95,83,53,90,0.0,4,25,Urban,Software Engineer,30407,1 +99167,Male,55,High School,14,50,57,84,76,1.0,3,76,Urban,Data Analyst,142075,1 +99168,Female,29,High School,8,37,72,62,84,8.0,6,93,Semi-Urban,Data Analyst,96805,1 +99169,Male,51,Bachelors,2,64,8,78,3,2.0,0,96,Rural,ML Engineer,137071,1 +99170,Male,55,Masters,0,3,27,27,92,2.0,7,87,Rural,ML Engineer,105206,0 +99171,Male,39,Bachelors,11,58,12,10,89,5.0,5,83,Urban,Software Engineer,129653,0 +99172,Male,41,Bachelors,4,72,3,83,68,9.0,5,6,Urban,Software Engineer,26192,0 +99173,Female,51,Bachelors,16,67,77,89,37,7.0,7,38,Urban,Software Engineer,122723,1 +99174,Male,44,Diploma,18,1,19,87,22,4.0,6,1,Urban,Data Analyst,95989,0 +99175,Male,59,Bachelors,5,37,68,9,76,2.0,3,10,Rural,ML Engineer,39820,0 +99176,Male,23,Diploma,19,69,12,34,45,0.0,6,0,Semi-Urban,Software Engineer,111074,0 +99177,Male,24,Masters,18,73,49,42,91,7.0,6,35,Rural,Software Engineer,84905,0 +99178,Female,33,High School,16,65,81,56,64,4.0,2,98,Semi-Urban,ML Engineer,97803,1 +99179,Female,43,Bachelors,6,18,43,6,6,6.0,5,5,Rural,HR Executive,61884,0 +99180,Male,27,Diploma,14,12,16,18,37,0.0,3,79,Urban,HR Executive,50922,0 +99181,Female,24,Masters,6,87,57,52,99,3.0,6,6,Urban,Data Analyst,88832,0 +99182,Male,54,Diploma,3,27,92,49,75,9.0,0,82,Urban,HR Executive,108970,1 +99183,Male,49,Bachelors,17,22,10,99,99,6.0,7,46,Semi-Urban,Software Engineer,94400,0 +99184,Male,59,Bachelors,18,2,79,1,15,7.0,3,34,Semi-Urban,ML Engineer,84720,0 +99185,Other,51,Bachelors,7,46,54,81,56,7.0,7,12,Rural,Data Analyst,91999,0 +99186,Other,42,Diploma,13,5,12,37,88,3.0,5,87,Urban,Software Engineer,126933,0 +99187,Male,50,Bachelors,18,40,22,8,36,8.0,2,74,Urban,ML Engineer,102708,0 +99188,Female,46,Bachelors,3,45,90,1,76,2.0,2,5,Urban,Data Analyst,41145,0 +99189,Male,57,Bachelors,2,13,45,40,69,6.0,6,91,Rural,HR Executive,133455,0 +99190,Female,34,Diploma,6,34,32,25,81,6.0,7,38,Rural,Data Analyst,122504,0 +99191,Female,21,Masters,11,24,18,62,12,9.0,1,68,Urban,Software Engineer,128375,0 +99192,Female,54,Diploma,3,99,84,68,8,2.0,3,71,Rural,Software Engineer,48279,1 +99193,Male,42,Bachelors,11,5,38,79,71,3.0,0,90,Urban,ML Engineer,112524,0 +99194,Female,29,Diploma,7,69,54,46,71,5.0,2,88,Semi-Urban,HR Executive,56857,1 +99195,Male,42,Diploma,19,63,10,9,84,7.0,6,70,Urban,Data Analyst,111506,0 +99196,Female,37,High School,12,40,60,35,2,7.0,6,44,Urban,Manager,65757,0 +99197,Female,35,Masters,14,28,31,55,47,7.0,1,24,Urban,Software Engineer,106640,0 +99198,Female,21,Bachelors,6,29,9,21,34,6.0,7,1,Semi-Urban,Software Engineer,122728,0 +99199,Male,59,Bachelors,14,64,83,7,32,7.0,3,71,Urban,HR Executive,42323,0 +99200,Male,22,Bachelors,16,68,27,8,91,7.0,5,19,Urban,HR Executive,27820,0 +99201,Female,31,High School,1,91,42,29,8,2.0,3,54,Rural,Software Engineer,121645,0 +99202,Male,41,High School,4,62,4,10,23,1.0,0,84,Urban,Software Engineer,118646,0 +99203,Female,31,Diploma,0,47,8,2,87,6.0,4,35,Semi-Urban,Manager,148185,0 +99204,Male,29,High School,10,99,68,96,5,9.0,1,82,Semi-Urban,HR Executive,22015,1 +99205,Male,55,Masters,5,44,94,12,99,9.0,2,88,Rural,HR Executive,29645,1 +99206,Female,35,Masters,16,6,25,42,95,8.0,4,84,Urban,Software Engineer,63587,0 +99207,Male,38,Bachelors,1,97,96,19,66,5.0,6,76,Urban,ML Engineer,96661,1 +99208,Male,36,PhD,16,28,43,43,16,1.0,3,3,Urban,ML Engineer,98183,0 +99209,Male,55,Diploma,9,39,20,33,83,8.0,4,15,Urban,HR Executive,43693,0 +99210,Female,43,High School,3,31,17,65,56,2.0,1,95,Urban,Manager,72150,0 +99211,Male,45,Masters,14,74,98,46,41,6.0,0,17,Semi-Urban,Manager,112226,1 +99212,Female,42,Diploma,6,23,88,33,57,6.0,2,27,Rural,ML Engineer,138525,0 +99213,Male,42,High School,10,29,59,50,40,1.0,2,86,Semi-Urban,ML Engineer,23037,0 +99214,Female,40,Bachelors,16,20,29,60,44,6.0,7,50,Semi-Urban,HR Executive,97711,0 +99215,Female,57,Bachelors,2,97,97,30,11,9.0,4,52,Semi-Urban,HR Executive,147525,1 +99216,Male,25,PhD,10,66,98,21,96,2.0,5,92,Urban,Data Analyst,113247,1 +99217,Female,38,Diploma,10,57,70,33,49,1.0,6,28,Semi-Urban,Software Engineer,89704,0 +99218,Male,57,Diploma,16,64,72,68,74,0.0,7,52,Urban,Manager,141880,1 +99219,Male,25,Bachelors,0,60,76,96,36,5.0,7,37,Urban,Data Analyst,148394,1 +99220,Male,44,Diploma,16,69,32,57,2,6.0,2,39,Urban,Data Analyst,122986,0 +99221,Male,51,Diploma,19,63,14,37,74,3.0,0,55,Rural,ML Engineer,75435,0 +99222,Male,46,Masters,11,7,36,36,69,0.0,6,98,Urban,HR Executive,134097,0 +99223,Female,43,Diploma,13,7,46,28,80,8.0,1,2,Rural,Manager,36137,0 +99224,Male,40,Diploma,14,82,63,65,15,6.0,7,3,Rural,HR Executive,84443,0 +99225,Male,34,Bachelors,7,44,19,72,43,6.0,0,23,Semi-Urban,ML Engineer,68254,0 +99226,Male,51,Bachelors,10,83,47,40,72,2.0,2,3,Urban,ML Engineer,125135,0 +99227,Male,51,Bachelors,12,83,63,85,37,0.0,4,22,Urban,Data Analyst,95216,1 +99228,Male,33,Masters,16,2,30,83,78,9.0,5,91,Urban,HR Executive,139454,0 +99229,Female,59,Bachelors,0,17,35,57,74,9.0,6,91,Rural,Software Engineer,148164,0 +99230,Female,34,Bachelors,2,91,89,1,12,8.0,6,62,Rural,Data Analyst,148512,1 +99231,Female,39,Masters,6,94,14,2,8,6.0,7,79,Urban,Manager,31935,0 +99232,Male,21,Bachelors,1,42,36,32,14,1.0,4,67,Semi-Urban,Software Engineer,147044,0 +99233,Male,52,Diploma,12,52,1,71,96,8.0,6,5,Semi-Urban,Data Analyst,51889,0 +99234,Female,41,Diploma,12,58,82,70,17,3.0,6,39,Urban,ML Engineer,42948,1 +99235,Female,54,Masters,18,58,53,18,37,4.0,3,94,Semi-Urban,Data Analyst,69910,0 +99236,Male,44,Bachelors,1,5,71,8,73,9.0,2,23,Rural,ML Engineer,42877,0 +99237,Female,38,Diploma,12,22,5,70,68,5.0,3,64,Semi-Urban,Software Engineer,149779,0 +99238,Male,30,High School,6,88,50,0,58,0.0,0,50,Semi-Urban,HR Executive,143843,0 +99239,Female,25,Masters,7,51,17,42,46,2.0,3,11,Semi-Urban,HR Executive,83581,0 +99240,Male,34,Diploma,5,50,83,11,65,6.0,6,93,Rural,ML Engineer,83978,1 +99241,Female,24,PhD,2,33,0,23,2,9.0,7,13,Semi-Urban,ML Engineer,25675,0 +99242,Female,34,Diploma,2,55,34,47,84,1.0,0,58,Semi-Urban,Manager,98675,0 +99243,Male,56,Masters,7,39,53,18,69,2.0,5,77,Urban,ML Engineer,141766,0 +99244,Female,30,Bachelors,5,25,32,69,78,8.0,7,79,Urban,ML Engineer,147201,0 +99245,Male,24,Diploma,0,3,55,68,14,0.0,0,58,Urban,Manager,92685,0 +99246,Female,54,Diploma,5,82,21,71,44,2.0,1,63,Rural,Manager,73018,0 +99247,Other,52,PhD,19,50,43,51,57,7.0,4,22,Semi-Urban,Manager,89610,0 +99248,Male,40,Bachelors,3,46,45,54,66,3.0,4,69,Urban,HR Executive,62908,0 +99249,Female,43,Masters,15,79,70,80,12,0.0,3,71,Rural,Data Analyst,135195,1 +99250,Male,38,Bachelors,13,62,2,10,68,8.0,1,50,Semi-Urban,ML Engineer,88206,0 +99251,Male,40,Diploma,11,15,39,54,36,3.0,5,7,Rural,Manager,36104,0 +99252,Male,25,Bachelors,19,12,21,58,31,5.0,7,86,Rural,Software Engineer,53337,0 +99253,Male,26,Bachelors,11,51,21,11,52,7.0,5,69,Semi-Urban,HR Executive,79243,0 +99254,Female,52,Bachelors,10,11,18,29,62,1.0,4,42,Urban,Manager,38849,0 +99255,Female,38,Bachelors,0,66,40,29,39,9.0,7,48,Urban,Manager,106971,0 +99256,Female,38,Bachelors,1,15,37,66,40,6.0,2,87,Urban,Software Engineer,118653,0 +99257,Male,46,Masters,12,12,2,39,30,2.0,1,35,Urban,ML Engineer,148355,0 +99258,Female,44,Masters,0,33,37,20,54,3.0,3,8,Urban,Software Engineer,56145,0 +99259,Male,28,Bachelors,12,65,39,57,90,1.0,6,44,Semi-Urban,ML Engineer,124408,0 +99260,Male,37,Masters,19,87,35,72,2,6.0,6,10,Urban,Software Engineer,78556,0 +99261,Male,55,High School,18,65,75,5,91,2.0,1,0,Urban,Manager,128899,0 +99262,Female,21,Masters,15,85,61,49,80,8.0,1,18,Semi-Urban,Data Analyst,61270,0 +99263,Male,54,High School,6,97,67,78,31,9.0,3,5,Urban,HR Executive,79762,1 +99264,Male,22,Bachelors,0,92,19,56,20,7.0,6,46,Urban,HR Executive,87598,0 +99265,Male,25,PhD,6,12,94,12,42,5.0,5,31,Rural,Software Engineer,69031,0 +99266,Male,31,Bachelors,2,94,75,79,97,7.0,3,70,Urban,ML Engineer,55039,1 +99267,Male,27,Diploma,8,32,75,25,66,7.0,7,68,Urban,HR Executive,34678,0 +99268,Male,47,High School,13,82,0,70,80,4.0,7,35,Semi-Urban,HR Executive,63822,0 +99269,Female,38,High School,14,65,18,89,89,4.0,4,73,Rural,ML Engineer,32448,1 +99270,Male,24,Bachelors,18,61,59,89,84,6.0,2,38,Rural,Data Analyst,36264,1 +99271,Female,56,High School,14,26,4,2,42,2.0,6,97,Urban,Data Analyst,36667,0 +99272,Female,53,Diploma,16,71,48,60,39,4.0,0,68,Urban,Manager,118774,1 +99273,Female,42,Diploma,17,97,0,0,94,6.0,3,9,Urban,Data Analyst,45630,0 +99274,Female,57,Bachelors,2,28,80,80,66,4.0,0,52,Semi-Urban,ML Engineer,22119,0 +99275,Other,35,Masters,15,23,95,39,46,2.0,4,91,Rural,ML Engineer,85753,1 +99276,Male,47,Diploma,5,5,87,35,31,8.0,2,75,Urban,ML Engineer,54970,0 +99277,Female,43,Diploma,1,50,57,64,78,5.0,4,95,Semi-Urban,ML Engineer,74803,1 +99278,Female,49,PhD,4,5,70,10,6,1.0,2,17,Urban,ML Engineer,23084,0 +99279,Male,52,Diploma,3,28,3,49,75,3.0,0,2,Urban,Manager,149232,0 +99280,Female,36,High School,10,67,18,62,92,6.0,0,55,Urban,Manager,136970,0 +99281,Female,46,Bachelors,5,76,63,96,70,5.0,7,8,Urban,Software Engineer,108238,1 +99282,Male,38,Diploma,14,37,78,52,46,7.0,1,53,Semi-Urban,HR Executive,100994,0 +99283,Male,33,High School,18,43,18,85,95,5.0,2,63,Rural,ML Engineer,69596,0 +99284,Other,42,Masters,4,23,30,51,2,8.0,4,63,Urban,ML Engineer,93856,0 +99285,Male,47,Bachelors,14,14,22,45,13,0.0,3,10,Rural,HR Executive,20025,0 +99286,Male,47,Diploma,15,61,89,4,45,1.0,7,55,Rural,Software Engineer,30718,0 +99287,Other,31,Masters,15,45,92,92,60,4.0,0,48,Urban,ML Engineer,42808,1 +99288,Female,39,High School,14,90,25,50,8,4.0,5,88,Urban,ML Engineer,50977,1 +99289,Female,58,Bachelors,13,16,55,2,3,3.0,1,74,Urban,HR Executive,135556,0 +99290,Female,36,Diploma,14,23,65,62,92,2.0,1,38,Urban,ML Engineer,46421,0 +99291,Male,55,Bachelors,18,54,5,28,72,8.0,4,79,Urban,HR Executive,72148,0 +99292,Female,47,Masters,14,71,52,99,86,2.0,4,57,Urban,Data Analyst,65243,1 +99293,Male,37,Bachelors,14,17,88,56,99,2.0,2,86,Urban,ML Engineer,33469,1 +99294,Male,44,Masters,14,94,17,29,74,8.0,7,61,Rural,HR Executive,78740,0 +99295,Male,46,Bachelors,15,13,26,26,5,9.0,4,88,Semi-Urban,ML Engineer,51418,0 +99296,Male,57,Bachelors,3,22,72,72,37,5.0,6,15,Urban,Manager,29711,0 +99297,Male,46,Bachelors,19,44,38,21,23,7.0,4,79,Urban,HR Executive,85582,0 +99298,Male,38,High School,11,29,80,25,83,3.0,7,17,Urban,ML Engineer,118232,0 +99299,Female,32,High School,16,5,98,62,88,0.0,1,29,Semi-Urban,HR Executive,40198,0 +99300,Male,25,Bachelors,5,0,24,82,55,4.0,7,47,Semi-Urban,HR Executive,25958,0 +99301,Female,29,Bachelors,19,51,46,53,59,0.0,0,38,Semi-Urban,HR Executive,134287,0 +99302,Male,46,High School,0,37,8,17,23,9.0,0,10,Semi-Urban,HR Executive,124630,0 +99303,Male,37,Bachelors,4,31,27,88,2,7.0,6,4,Semi-Urban,Software Engineer,56442,0 +99304,Female,24,Bachelors,17,42,8,42,43,8.0,2,47,Urban,Software Engineer,66924,0 +99305,Male,22,Bachelors,10,69,93,93,70,9.0,3,17,Urban,ML Engineer,36091,1 +99306,Female,40,Bachelors,10,40,36,36,14,3.0,5,16,Rural,Manager,38144,0 +99307,Female,53,High School,2,15,44,36,63,5.0,4,64,Semi-Urban,Software Engineer,43622,0 +99308,Other,46,Masters,15,26,78,58,24,7.0,2,44,Urban,ML Engineer,123394,0 +99309,Male,24,Bachelors,5,48,84,4,50,8.0,1,9,Urban,Software Engineer,114367,0 +99310,Male,28,Diploma,1,47,88,72,47,7.0,7,89,Urban,HR Executive,102563,1 +99311,Male,43,Bachelors,1,10,81,72,31,0.0,6,41,Urban,Manager,43449,0 +99312,Male,59,High School,13,91,99,83,15,9.0,0,33,Urban,Software Engineer,60295,1 +99313,Male,50,Bachelors,11,84,11,56,64,5.0,6,52,Urban,ML Engineer,139363,0 +99314,Female,36,Bachelors,16,5,49,56,74,9.0,4,91,Rural,HR Executive,134505,0 +99315,Male,21,Bachelors,17,80,51,85,34,8.0,5,11,Urban,Manager,36145,0 +99316,Male,25,Diploma,10,40,6,31,72,5.0,0,21,Rural,HR Executive,85722,0 +99317,Male,27,Bachelors,12,7,16,58,59,4.0,3,6,Rural,HR Executive,65073,0 +99318,Female,49,Bachelors,17,77,5,21,34,9.0,1,95,Urban,Software Engineer,81034,0 +99319,Female,27,Bachelors,19,62,27,30,73,3.0,4,50,Urban,Manager,97036,0 +99320,Male,22,High School,17,62,85,89,3,1.0,2,52,Urban,Software Engineer,20055,1 +99321,Female,45,Bachelors,3,71,69,65,54,5.0,4,86,Semi-Urban,Data Analyst,106411,1 +99322,Female,39,Bachelors,15,65,81,92,84,0.0,2,79,Urban,Software Engineer,129772,1 +99323,Male,37,High School,4,24,93,23,23,7.0,3,50,Rural,Manager,64471,0 +99324,Female,59,Diploma,6,75,14,50,86,0.0,2,92,Urban,Manager,115104,0 +99325,Male,39,Diploma,3,31,39,98,93,6.0,2,24,Semi-Urban,Software Engineer,90313,0 +99326,Male,59,Diploma,8,75,33,28,72,6.0,0,52,Urban,HR Executive,30229,0 +99327,Male,45,Diploma,16,75,84,77,90,3.0,0,57,Urban,Software Engineer,138558,1 +99328,Male,37,Masters,6,0,43,60,54,8.0,1,90,Urban,ML Engineer,23702,0 +99329,Female,39,Diploma,16,42,75,72,31,7.0,7,95,Semi-Urban,Manager,113313,1 +99330,Male,27,Diploma,3,72,76,51,94,2.0,6,32,Rural,Software Engineer,118985,0 +99331,Male,52,Diploma,15,5,76,95,42,0.0,3,90,Urban,HR Executive,139427,1 +99332,Female,47,Bachelors,15,17,88,60,23,9.0,0,3,Urban,Manager,133292,0 +99333,Female,32,High School,18,56,65,41,76,4.0,2,99,Urban,HR Executive,149330,1 +99334,Male,39,Masters,4,11,20,5,20,4.0,2,42,Semi-Urban,Data Analyst,122610,0 +99335,Male,55,High School,17,90,28,38,61,4.0,7,57,Rural,Manager,49278,0 +99336,Female,42,Bachelors,12,17,94,22,76,5.0,6,91,Urban,Software Engineer,25983,0 +99337,Female,27,Bachelors,1,73,75,41,84,7.0,4,14,Urban,Software Engineer,71410,0 +99338,Female,50,Bachelors,6,43,96,20,30,3.0,6,88,Urban,Manager,103774,1 +99339,Male,39,Masters,8,89,6,14,74,8.0,0,28,Semi-Urban,HR Executive,47478,0 +99340,Male,56,PhD,19,84,2,65,65,4.0,2,21,Urban,Software Engineer,46277,0 +99341,Female,26,Masters,8,9,78,90,53,8.0,2,19,Rural,Software Engineer,110745,0 +99342,Male,28,PhD,12,61,1,6,14,6.0,4,42,Semi-Urban,ML Engineer,126652,0 +99343,Female,43,Bachelors,1,81,26,30,16,6.0,7,5,Urban,ML Engineer,35768,0 +99344,Male,38,Diploma,2,58,73,0,8,2.0,2,96,Urban,Manager,57992,0 +99345,Female,26,Diploma,3,71,37,30,43,7.0,7,9,Urban,Data Analyst,111854,0 +99346,Female,45,Bachelors,13,27,81,82,25,0.0,7,65,Rural,Manager,122805,1 +99347,Male,29,Bachelors,12,65,14,77,66,2.0,0,35,Urban,ML Engineer,62241,0 +99348,Female,53,Bachelors,0,29,63,10,5,9.0,6,98,Rural,ML Engineer,114477,0 +99349,Male,35,Masters,13,38,22,62,9,0.0,4,74,Urban,Data Analyst,97302,0 +99350,Male,59,Diploma,14,79,73,79,39,2.0,6,35,Semi-Urban,Manager,52771,1 +99351,Female,35,Diploma,2,72,20,91,13,8.0,2,6,Rural,Manager,91771,0 +99352,Other,41,High School,14,5,52,39,22,8.0,2,76,Urban,HR Executive,53149,0 +99353,Female,23,Diploma,9,31,98,31,88,6.0,5,67,Urban,ML Engineer,75617,0 +99354,Male,35,Bachelors,8,41,39,27,79,3.0,3,51,Semi-Urban,Data Analyst,52557,0 +99355,Female,40,Masters,12,3,21,19,62,5.0,1,82,Semi-Urban,Software Engineer,105513,0 +99356,Male,52,High School,12,53,12,66,99,7.0,0,9,Rural,Software Engineer,46322,0 +99357,Male,21,Bachelors,9,85,92,22,25,3.0,4,76,Semi-Urban,HR Executive,74900,1 +99358,Male,36,Masters,0,91,63,10,98,3.0,7,12,Urban,Software Engineer,38036,0 +99359,Female,48,Bachelors,17,18,51,4,99,0.0,0,34,Rural,Manager,31039,0 +99360,Female,49,Bachelors,2,70,95,28,97,6.0,4,24,Semi-Urban,Software Engineer,106013,0 +99361,Female,50,Masters,9,52,14,62,53,7.0,5,66,Urban,Software Engineer,149863,0 +99362,Male,48,Masters,13,26,9,94,3,6.0,0,86,Urban,ML Engineer,35349,0 +99363,Male,37,Diploma,3,3,96,47,2,1.0,4,6,Semi-Urban,Software Engineer,108277,0 +99364,Female,23,Diploma,12,71,67,94,1,8.0,1,20,Urban,Data Analyst,45178,1 +99365,Female,53,Masters,10,50,1,35,73,2.0,0,2,Semi-Urban,Manager,67548,0 +99366,Male,26,Bachelors,5,24,22,11,63,7.0,3,79,Urban,Data Analyst,66609,0 +99367,Female,39,Bachelors,4,42,28,21,38,6.0,1,66,Urban,ML Engineer,64014,0 +99368,Male,29,PhD,11,88,87,73,67,2.0,0,16,Rural,Data Analyst,109330,1 +99369,Male,26,Bachelors,14,84,15,0,63,9.0,7,4,Semi-Urban,HR Executive,137146,0 +99370,Male,34,Bachelors,14,95,43,68,95,8.0,2,17,Urban,HR Executive,95324,0 +99371,Other,39,Bachelors,2,47,58,88,16,6.0,4,93,Semi-Urban,HR Executive,90192,1 +99372,Male,31,Diploma,2,17,80,18,85,2.0,5,36,Urban,Manager,48748,0 +99373,Male,22,Bachelors,8,60,12,70,18,6.0,4,20,Urban,Software Engineer,41952,0 +99374,Male,33,Diploma,2,9,33,77,28,1.0,7,8,Semi-Urban,Data Analyst,122993,0 +99375,Male,32,Diploma,8,59,62,13,57,9.0,4,43,Urban,Data Analyst,60383,0 +99376,Male,56,High School,16,41,38,32,81,9.0,0,76,Urban,Software Engineer,53256,0 +99377,Male,30,Bachelors,2,10,28,96,52,7.0,7,4,Semi-Urban,Software Engineer,107198,0 +99378,Male,36,Bachelors,4,27,9,7,56,5.0,4,5,Rural,ML Engineer,36765,0 +99379,Female,30,High School,17,25,79,28,50,5.0,1,27,Semi-Urban,HR Executive,126317,0 +99380,Male,40,Diploma,11,99,37,65,21,0.0,5,69,Urban,HR Executive,137356,1 +99381,Male,40,Bachelors,19,36,32,72,37,9.0,4,65,Urban,Manager,34315,0 +99382,Female,57,High School,10,63,3,20,96,2.0,0,14,Rural,Software Engineer,112661,0 +99383,Female,21,Bachelors,8,67,33,6,68,0.0,3,46,Rural,ML Engineer,135340,0 +99384,Female,31,Bachelors,4,64,11,56,69,8.0,6,34,Urban,Manager,55440,0 +99385,Male,27,PhD,13,34,28,60,99,0.0,0,45,Urban,Software Engineer,65736,0 +99386,Male,45,Bachelors,1,97,14,94,13,3.0,2,51,Urban,HR Executive,135040,1 +99387,Female,53,Diploma,12,67,7,31,34,3.0,4,19,Urban,Data Analyst,82615,0 +99388,Male,59,Bachelors,1,66,16,46,29,0.0,6,76,Semi-Urban,Software Engineer,63825,0 +99389,Male,54,Masters,19,5,86,44,95,3.0,2,12,Urban,HR Executive,34140,0 +99390,Male,39,PhD,7,75,47,83,64,4.0,5,58,Urban,ML Engineer,149346,1 +99391,Male,53,High School,7,22,7,71,86,6.0,4,60,Semi-Urban,Software Engineer,79914,0 +99392,Male,34,Masters,6,79,38,75,33,8.0,6,81,Semi-Urban,Manager,95697,1 +99393,Male,55,Bachelors,3,17,0,8,27,8.0,4,45,Semi-Urban,Data Analyst,25595,0 +99394,Male,36,Masters,6,38,78,72,86,2.0,6,20,Rural,HR Executive,63111,0 +99395,Male,35,Masters,18,44,57,92,14,1.0,3,0,Semi-Urban,Software Engineer,56798,0 +99396,Male,43,Bachelors,17,8,79,44,87,8.0,0,40,Urban,Software Engineer,119343,0 +99397,Female,21,Masters,11,99,96,38,69,0.0,5,78,Urban,Manager,75388,1 +99398,Female,37,PhD,6,95,76,88,9,6.0,6,13,Urban,Manager,114502,1 +99399,Female,30,Bachelors,1,83,63,16,16,7.0,6,91,Urban,Manager,135144,1 +99400,Female,56,Bachelors,0,50,2,64,86,2.0,6,54,Urban,ML Engineer,146715,0 +99401,Male,27,Diploma,2,82,64,69,35,0.0,0,88,Semi-Urban,Software Engineer,60028,1 +99402,Male,45,Bachelors,9,19,30,93,18,0.0,6,87,Urban,Manager,108585,0 +99403,Female,33,Bachelors,5,80,39,32,15,7.0,5,77,Semi-Urban,ML Engineer,45901,0 +99404,Male,21,Masters,10,81,79,91,29,5.0,0,81,Urban,Data Analyst,41035,1 +99405,Female,57,Diploma,5,11,61,61,4,6.0,3,76,Urban,Manager,77557,0 +99406,Other,40,Diploma,7,8,12,22,60,6.0,6,20,Semi-Urban,ML Engineer,35645,0 +99407,Male,37,Bachelors,16,36,51,89,79,8.0,6,19,Urban,Manager,35123,0 +99408,Other,21,Diploma,5,2,63,57,80,6.0,1,80,Urban,ML Engineer,135058,0 +99409,Male,59,Bachelors,1,92,86,87,59,7.0,1,6,Urban,HR Executive,85769,1 +99410,Female,49,Diploma,2,34,40,41,35,8.0,2,24,Urban,Data Analyst,103371,0 +99411,Male,38,Bachelors,15,54,46,95,51,8.0,0,77,Urban,HR Executive,105582,1 +99412,Female,36,Bachelors,18,29,32,33,95,7.0,1,5,Rural,Manager,145373,0 +99413,Female,33,Diploma,9,84,34,38,60,8.0,1,60,Urban,Manager,63284,0 +99414,Female,45,Bachelors,1,20,59,61,70,2.0,3,89,Rural,Software Engineer,22743,0 +99415,Male,45,High School,6,46,4,60,26,8.0,0,47,Urban,Data Analyst,54374,0 +99416,Male,50,Masters,19,97,99,0,1,3.0,3,21,Urban,Manager,108977,0 +99417,Female,36,Bachelors,17,75,72,10,56,3.0,5,58,Urban,Manager,74404,0 +99418,Female,35,Bachelors,12,83,93,48,84,6.0,7,43,Urban,Manager,77144,1 +99419,Male,28,Bachelors,3,37,25,1,17,4.0,0,6,Urban,Manager,116017,0 +99420,Male,49,Masters,5,16,10,6,4,6.0,0,89,Urban,Software Engineer,49542,0 +99421,Male,34,Bachelors,8,87,30,45,5,7.0,1,12,Rural,HR Executive,106741,0 +99422,Female,57,High School,10,0,87,1,94,2.0,6,30,Rural,Data Analyst,77729,0 +99423,Female,46,High School,2,4,56,98,5,9.0,5,99,Semi-Urban,ML Engineer,50508,1 +99424,Female,43,Diploma,14,99,89,74,6,2.0,6,51,Rural,Data Analyst,139447,1 +99425,Male,22,High School,3,14,35,67,18,6.0,0,87,Semi-Urban,Manager,70522,0 +99426,Female,44,Diploma,14,86,93,49,32,3.0,5,11,Semi-Urban,Software Engineer,64098,0 +99427,Male,23,Masters,15,44,44,35,80,3.0,2,21,Rural,Manager,93694,0 +99428,Female,53,Bachelors,18,47,52,71,68,0.0,5,15,Urban,Manager,142257,0 +99429,Female,31,Bachelors,13,83,40,36,40,9.0,5,37,Urban,Software Engineer,92206,0 +99430,Female,39,Bachelors,16,45,14,55,38,0.0,0,20,Urban,Manager,35341,0 +99431,Female,40,Bachelors,3,86,38,91,47,4.0,1,33,Urban,ML Engineer,70068,1 +99432,Male,26,Bachelors,16,31,26,80,8,5.0,1,23,Urban,Software Engineer,92534,0 +99433,Female,33,High School,6,63,13,91,80,5.0,5,31,Urban,HR Executive,43270,0 +99434,Male,50,Diploma,18,55,81,41,99,1.0,3,46,Semi-Urban,HR Executive,104495,0 +99435,Female,59,Masters,4,27,53,23,86,9.0,6,42,Urban,Software Engineer,107937,0 +99436,Male,42,Bachelors,2,57,63,10,19,9.0,2,31,Rural,ML Engineer,79670,0 +99437,Female,24,Bachelors,9,66,42,3,25,5.0,1,45,Rural,Manager,111119,0 +99438,Female,40,Bachelors,6,20,46,28,33,4.0,7,62,Urban,Manager,108658,0 +99439,Female,38,Bachelors,6,7,34,68,60,7.0,0,43,Urban,Data Analyst,60428,0 +99440,Male,24,Bachelors,10,75,50,92,44,2.0,6,81,Urban,Data Analyst,70919,1 +99441,Male,24,Masters,8,28,98,95,93,1.0,0,20,Urban,HR Executive,143060,1 +99442,Female,58,Diploma,14,74,71,70,52,3.0,6,71,Rural,HR Executive,119926,1 +99443,Male,23,Bachelors,2,13,34,93,98,4.0,7,24,Urban,Manager,96567,0 +99444,Female,57,Bachelors,14,41,80,4,17,9.0,1,30,Urban,Data Analyst,119290,0 +99445,Female,35,High School,18,70,93,99,87,2.0,0,19,Urban,Manager,116232,1 +99446,Male,58,Diploma,15,8,33,52,22,3.0,3,75,Urban,ML Engineer,61442,0 +99447,Other,53,Masters,10,90,9,15,51,2.0,7,45,Urban,Software Engineer,54810,0 +99448,Female,38,Masters,3,86,74,9,0,4.0,3,4,Urban,Data Analyst,26576,0 +99449,Male,58,Bachelors,3,84,90,69,8,4.0,7,51,Urban,ML Engineer,57978,1 +99450,Other,51,High School,8,23,72,7,90,1.0,7,77,Urban,HR Executive,114674,0 +99451,Other,49,Bachelors,16,43,72,27,62,5.0,0,5,Urban,Manager,129137,0 +99452,Male,49,Bachelors,9,11,48,24,6,5.0,6,62,Semi-Urban,HR Executive,101451,0 +99453,Other,28,Bachelors,11,13,22,13,40,9.0,1,90,Rural,HR Executive,54330,0 +99454,Female,43,High School,1,81,50,25,58,1.0,0,24,Rural,HR Executive,133529,0 +99455,Male,47,Diploma,5,36,96,6,84,1.0,4,21,Urban,ML Engineer,59628,0 +99456,Other,44,High School,5,28,31,87,31,3.0,3,50,Rural,ML Engineer,79571,0 +99457,Male,46,Masters,7,17,52,49,58,8.0,6,18,Urban,ML Engineer,88901,0 +99458,Female,56,Bachelors,8,23,89,38,31,8.0,7,61,Rural,HR Executive,141441,0 +99459,Female,31,High School,9,37,96,79,54,4.0,6,32,Semi-Urban,Software Engineer,90108,1 +99460,Female,32,Bachelors,3,47,74,87,13,1.0,4,99,Rural,Data Analyst,68479,1 +99461,Male,43,Masters,17,8,69,18,24,9.0,2,7,Urban,ML Engineer,64836,0 +99462,Male,46,Bachelors,18,2,37,62,15,2.0,2,33,Urban,ML Engineer,21258,0 +99463,Male,35,Bachelors,14,44,41,63,38,9.0,3,87,Urban,HR Executive,55181,1 +99464,Male,58,Bachelors,15,88,43,80,95,8.0,0,36,Urban,HR Executive,100283,1 +99465,Female,53,Bachelors,18,64,52,67,71,1.0,4,9,Rural,Software Engineer,32223,0 +99466,Female,56,High School,12,20,97,72,53,7.0,5,94,Semi-Urban,ML Engineer,66946,1 +99467,Female,45,Bachelors,9,75,92,2,98,1.0,3,70,Urban,Software Engineer,148854,0 +99468,Female,55,High School,2,77,7,47,48,7.0,7,21,Rural,Software Engineer,75114,0 +99469,Male,46,Masters,15,57,33,69,12,1.0,1,30,Urban,HR Executive,54542,0 +99470,Female,28,Bachelors,19,64,10,54,18,3.0,1,13,Urban,Data Analyst,129307,0 +99471,Female,55,PhD,1,8,69,97,42,7.0,5,39,Rural,Data Analyst,131344,0 +99472,Female,57,Diploma,14,18,28,87,75,1.0,6,63,Urban,ML Engineer,95416,0 +99473,Male,52,Bachelors,4,83,28,35,11,8.0,4,35,Urban,Manager,48887,0 +99474,Male,52,Masters,14,64,23,99,36,4.0,6,18,Urban,Software Engineer,103634,0 +99475,Male,43,Masters,9,5,68,18,67,7.0,2,84,Urban,HR Executive,143418,0 +99476,Male,22,Bachelors,0,99,31,14,64,5.0,5,34,Urban,Data Analyst,77651,0 +99477,Male,47,Masters,14,8,50,26,99,8.0,3,71,Rural,Software Engineer,50731,0 +99478,Male,49,Diploma,1,23,29,47,49,9.0,1,44,Urban,ML Engineer,117446,0 +99479,Female,28,Bachelors,7,35,19,0,57,9.0,5,27,Rural,Manager,38498,0 +99480,Male,50,High School,10,51,84,48,24,8.0,2,65,Urban,ML Engineer,124677,1 +99481,Male,23,Masters,1,81,61,71,96,5.0,3,65,Rural,Manager,31266,1 +99482,Female,48,Bachelors,14,10,21,64,25,6.0,2,0,Semi-Urban,Data Analyst,137861,0 +99483,Male,21,Bachelors,7,12,86,64,84,0.0,7,32,Urban,Manager,83715,0 +99484,Male,22,Masters,15,84,15,77,48,6.0,5,93,Semi-Urban,Software Engineer,32014,1 +99485,Male,51,Bachelors,1,65,80,22,11,5.0,6,32,Semi-Urban,HR Executive,45414,0 +99486,Male,37,Bachelors,1,12,27,46,83,2.0,6,56,Urban,HR Executive,22789,0 +99487,Male,56,Masters,9,71,73,16,7,8.0,5,4,Urban,Manager,50634,0 +99488,Female,34,Diploma,5,50,12,3,44,2.0,4,95,Rural,Software Engineer,101363,0 +99489,Male,57,High School,5,24,73,74,51,8.0,2,50,Rural,ML Engineer,122849,0 +99490,Male,25,Bachelors,11,94,98,68,59,1.0,0,41,Semi-Urban,HR Executive,149326,1 +99491,Male,40,Bachelors,13,22,1,65,8,9.0,3,66,Rural,Software Engineer,81963,0 +99492,Female,50,Bachelors,4,92,34,32,92,7.0,3,44,Urban,ML Engineer,99576,0 +99493,Male,28,High School,7,84,88,65,56,8.0,0,16,Urban,Software Engineer,102290,1 +99494,Male,27,Diploma,6,84,99,0,1,0.0,7,63,Rural,Manager,135693,1 +99495,Male,41,Bachelors,2,82,93,48,3,1.0,7,42,Urban,HR Executive,59014,1 +99496,Female,37,Bachelors,1,44,45,15,24,4.0,4,14,Urban,Manager,110626,0 +99497,Male,34,Diploma,11,1,87,80,37,6.0,3,40,Rural,Manager,63182,0 +99498,Female,23,Bachelors,13,5,47,47,75,4.0,0,58,Semi-Urban,Data Analyst,98391,0 +99499,Male,41,Bachelors,5,87,73,14,55,5.0,1,24,Rural,Manager,122570,0 +99500,Male,55,Masters,4,43,50,15,4,1.0,3,99,Urban,Manager,49864,0 +99501,Male,29,Bachelors,14,77,72,41,48,9.0,6,72,Semi-Urban,Manager,145307,1 +99502,Male,54,Bachelors,11,68,19,19,11,3.0,3,3,Urban,Manager,102393,0 +99503,Female,23,Bachelors,4,24,58,39,34,9.0,3,21,Urban,Software Engineer,143833,0 +99504,Female,28,Diploma,16,97,3,85,86,8.0,6,33,Urban,ML Engineer,84706,0 +99505,Male,50,Diploma,16,54,20,61,78,4.0,6,82,Urban,Data Analyst,93111,0 +99506,Other,21,Masters,15,73,20,9,42,7.0,2,20,Urban,ML Engineer,105106,0 +99507,Male,33,Masters,14,46,62,80,15,8.0,4,97,Urban,ML Engineer,59609,1 +99508,Male,52,Diploma,17,16,11,25,41,2.0,2,25,Semi-Urban,Software Engineer,130290,0 +99509,Female,39,Masters,15,19,41,36,93,4.0,0,76,Semi-Urban,Data Analyst,100505,0 +99510,Female,22,Diploma,4,12,70,53,81,6.0,5,8,Semi-Urban,Manager,144228,0 +99511,Female,41,Bachelors,2,96,0,1,88,7.0,1,35,Urban,Data Analyst,66248,0 +99512,Female,59,High School,7,58,62,75,89,9.0,6,56,Rural,HR Executive,27772,1 +99513,Other,35,Bachelors,3,42,13,23,47,2.0,6,38,Semi-Urban,HR Executive,100436,0 +99514,Male,32,Masters,19,51,6,87,52,9.0,6,36,Urban,Software Engineer,36397,0 +99515,Male,23,Bachelors,15,66,33,59,67,0.0,4,33,Semi-Urban,ML Engineer,138186,0 +99516,Female,58,Masters,9,13,98,92,40,4.0,7,27,Rural,Manager,55811,0 +99517,Male,21,Masters,13,63,63,25,19,7.0,2,61,Rural,Data Analyst,91879,0 +99518,Male,47,Bachelors,8,91,41,16,24,5.0,3,62,Rural,Software Engineer,108161,0 +99519,Male,51,Masters,15,56,63,2,69,5.0,6,40,Semi-Urban,HR Executive,94048,0 +99520,Male,41,Bachelors,4,54,70,42,59,1.0,0,60,Urban,Manager,90982,0 +99521,Female,30,Bachelors,12,36,1,34,48,1.0,0,9,Urban,HR Executive,72449,0 +99522,Male,42,Bachelors,10,54,47,8,86,6.0,1,16,Semi-Urban,Software Engineer,30427,0 +99523,Female,42,High School,7,62,43,8,70,0.0,2,88,Semi-Urban,Software Engineer,116910,0 +99524,Male,25,High School,6,15,29,98,18,0.0,5,35,Urban,Data Analyst,78432,0 +99525,Other,25,Bachelors,7,13,56,85,11,7.0,5,28,Urban,ML Engineer,148845,0 +99526,Male,28,Diploma,10,52,26,70,60,5.0,5,79,Urban,Data Analyst,65644,0 +99527,Female,36,Bachelors,9,71,63,86,78,5.0,6,18,Semi-Urban,Software Engineer,70825,0 +99528,Male,28,Diploma,18,31,81,84,29,8.0,6,65,Urban,ML Engineer,129419,1 +99529,Male,22,High School,3,92,8,98,57,2.0,4,85,Urban,Software Engineer,119483,1 +99530,Female,41,PhD,13,79,94,89,69,9.0,6,98,Semi-Urban,Manager,98458,1 +99531,Female,59,Bachelors,18,40,86,15,62,9.0,5,49,Rural,HR Executive,73110,0 +99532,Female,21,Diploma,6,39,96,11,43,2.0,0,12,Rural,Data Analyst,75757,0 +99533,Female,48,Diploma,15,1,13,6,49,7.0,2,51,Semi-Urban,Data Analyst,114378,0 +99534,Male,58,Bachelors,12,65,30,29,29,4.0,0,67,Rural,ML Engineer,109866,0 +99535,Male,26,Diploma,12,14,19,2,49,8.0,6,73,Urban,ML Engineer,25049,0 +99536,Female,55,Diploma,11,69,12,50,32,1.0,4,53,Urban,Software Engineer,31299,0 +99537,Female,36,Diploma,1,33,50,48,94,9.0,5,86,Semi-Urban,Software Engineer,119319,0 +99538,Other,32,Bachelors,0,91,89,18,37,6.0,7,37,Semi-Urban,ML Engineer,49824,0 +99539,Female,29,Masters,16,6,9,16,63,4.0,1,13,Rural,Manager,78468,0 +99540,Male,50,High School,12,75,98,29,68,8.0,7,63,Rural,HR Executive,75739,1 +99541,Other,22,Diploma,13,25,51,99,95,7.0,6,13,Urban,Manager,140043,0 +99542,Male,51,Bachelors,5,47,47,20,52,8.0,7,5,Rural,HR Executive,84179,0 +99543,Other,52,Bachelors,4,53,11,96,18,6.0,6,89,Semi-Urban,Software Engineer,120373,1 +99544,Male,44,Diploma,19,88,83,13,92,5.0,3,32,Urban,HR Executive,87205,0 +99545,Male,44,Bachelors,15,7,70,31,56,9.0,7,81,Semi-Urban,ML Engineer,120402,0 +99546,Male,58,Masters,17,21,3,87,76,4.0,2,3,Rural,ML Engineer,50924,0 +99547,Male,38,Bachelors,14,40,92,76,72,8.0,3,80,Urban,Data Analyst,65918,1 +99548,Male,55,Diploma,16,70,60,13,70,9.0,4,16,Urban,ML Engineer,54789,0 +99549,Male,31,Bachelors,11,6,11,37,41,4.0,0,23,Urban,Data Analyst,77765,0 +99550,Male,21,Diploma,11,27,8,8,69,3.0,3,31,Urban,Software Engineer,83280,0 +99551,Female,58,Masters,9,43,68,16,68,8.0,1,75,Urban,Software Engineer,149289,0 +99552,Female,55,Bachelors,6,58,56,94,43,3.0,3,35,Urban,Software Engineer,148678,1 +99553,Male,35,High School,19,36,94,46,21,2.0,0,89,Rural,Manager,88198,1 +99554,Female,24,Masters,8,19,70,71,23,1.0,0,41,Urban,Software Engineer,135584,0 +99555,Male,22,Masters,0,22,26,59,22,3.0,3,98,Urban,Manager,28620,0 +99556,Female,23,Diploma,1,90,64,41,56,5.0,3,71,Urban,ML Engineer,85070,1 +99557,Male,39,High School,18,68,32,97,45,2.0,1,31,Rural,HR Executive,139407,0 +99558,Female,27,PhD,1,59,86,87,97,7.0,1,81,Urban,HR Executive,121240,1 +99559,Male,34,Masters,16,14,61,43,48,2.0,5,60,Urban,Software Engineer,33096,0 +99560,Male,55,Masters,12,18,11,98,89,2.0,6,89,Urban,ML Engineer,24411,0 +99561,Male,37,Diploma,7,77,25,34,16,4.0,4,46,Semi-Urban,Software Engineer,75037,0 +99562,Male,38,Masters,6,6,21,82,58,5.0,4,64,Urban,HR Executive,104779,0 +99563,Female,33,Masters,16,27,99,56,54,8.0,6,58,Semi-Urban,Software Engineer,63951,0 +99564,Male,36,Bachelors,7,67,42,72,19,0.0,6,36,Urban,Data Analyst,69864,0 +99565,Male,37,Diploma,5,60,94,54,96,3.0,7,87,Urban,Software Engineer,57248,1 +99566,Male,44,Masters,1,97,5,81,98,3.0,5,69,Urban,HR Executive,26482,1 +99567,Female,24,Bachelors,5,29,64,13,68,5.0,0,90,Urban,Software Engineer,98286,0 +99568,Male,26,PhD,17,22,2,61,62,9.0,4,56,Rural,HR Executive,50914,0 +99569,Male,26,High School,1,42,2,45,4,8.0,6,29,Rural,Data Analyst,94637,0 +99570,Female,33,Masters,14,15,93,12,34,9.0,6,65,Urban,Data Analyst,58999,0 +99571,Female,24,Masters,8,79,27,22,89,2.0,5,44,Urban,HR Executive,123933,0 +99572,Male,32,Diploma,4,46,61,68,7,6.0,2,67,Semi-Urban,Manager,41005,1 +99573,Male,31,Bachelors,16,55,97,30,83,9.0,0,77,Semi-Urban,Manager,96703,1 +99574,Male,45,PhD,2,70,38,11,15,4.0,4,31,Rural,Data Analyst,49771,0 +99575,Female,32,PhD,11,89,23,29,78,4.0,1,30,Semi-Urban,Software Engineer,32325,0 +99576,Male,49,High School,14,7,67,7,65,7.0,3,52,Urban,Data Analyst,21295,0 +99577,Male,36,Bachelors,11,72,40,48,42,7.0,2,11,Rural,ML Engineer,74964,0 +99578,Female,55,Bachelors,7,38,95,50,93,2.0,2,3,Urban,ML Engineer,119621,0 +99579,Female,46,Bachelors,11,3,74,99,81,0.0,0,26,Rural,Software Engineer,82739,0 +99580,Male,30,Diploma,4,89,30,60,42,0.0,5,7,Urban,HR Executive,106779,0 +99581,Male,46,PhD,1,11,60,69,36,3.0,3,36,Rural,ML Engineer,94503,0 +99582,Male,46,Bachelors,11,62,87,84,66,5.0,7,85,Semi-Urban,HR Executive,52502,1 +99583,Male,27,Masters,17,84,39,54,36,3.0,5,76,Semi-Urban,Data Analyst,121268,1 +99584,Male,23,Diploma,0,88,44,65,41,3.0,4,69,Urban,Manager,145472,1 +99585,Male,27,Bachelors,12,43,87,23,81,2.0,3,52,Semi-Urban,ML Engineer,117507,0 +99586,Male,39,Bachelors,15,26,80,63,90,4.0,0,28,Urban,Manager,22296,0 +99587,Other,36,Bachelors,2,71,56,57,63,3.0,0,41,Urban,HR Executive,104047,0 +99588,Male,28,Diploma,14,20,82,4,43,8.0,4,42,Urban,Manager,31412,0 +99589,Male,58,Masters,17,90,13,15,49,7.0,7,57,Urban,ML Engineer,84830,0 +99590,Female,34,High School,17,48,41,45,62,5.0,3,98,Semi-Urban,Software Engineer,125150,0 +99591,Male,44,Bachelors,8,88,10,45,8,5.0,3,92,Urban,ML Engineer,22561,1 +99592,Male,33,Masters,13,28,56,80,55,9.0,4,28,Urban,Software Engineer,101224,0 +99593,Male,34,Bachelors,15,77,16,13,36,9.0,6,30,Semi-Urban,ML Engineer,72929,0 +99594,Male,23,Masters,2,93,58,63,53,4.0,6,68,Semi-Urban,Data Analyst,145463,1 +99595,Male,41,Bachelors,11,44,26,86,41,2.0,6,20,Semi-Urban,Data Analyst,70001,0 +99596,Female,55,High School,4,29,28,53,11,1.0,4,75,Urban,Manager,149291,0 +99597,Male,48,Masters,16,5,63,30,9,7.0,4,55,Rural,Manager,112831,0 +99598,Male,34,Diploma,5,26,56,60,38,9.0,0,1,Urban,Manager,140538,0 +99599,Male,55,Bachelors,10,70,8,30,50,2.0,3,87,Semi-Urban,ML Engineer,96281,0 +99600,Female,29,Bachelors,7,72,59,19,78,3.0,7,22,Urban,Manager,47181,0 +99601,Male,24,High School,4,89,19,23,67,6.0,7,8,Urban,ML Engineer,25087,0 +99602,Male,26,Diploma,3,61,4,55,34,4.0,0,54,Rural,HR Executive,67366,0 +99603,Male,39,Masters,6,5,98,77,68,8.0,0,97,Semi-Urban,Data Analyst,88095,1 +99604,Male,51,Masters,12,99,50,77,26,8.0,3,55,Rural,ML Engineer,70461,1 +99605,Male,46,Bachelors,15,21,17,4,15,4.0,7,18,Semi-Urban,Manager,122938,0 +99606,Male,58,Diploma,5,52,72,81,8,7.0,4,51,Urban,Software Engineer,86748,1 +99607,Male,52,Bachelors,9,20,82,34,55,6.0,5,24,Semi-Urban,ML Engineer,124445,0 +99608,Male,40,PhD,7,2,24,75,12,3.0,2,63,Urban,Software Engineer,126575,0 +99609,Male,40,High School,10,90,5,69,19,3.0,7,29,Urban,Software Engineer,85054,0 +99610,Female,51,Masters,1,96,72,9,49,9.0,1,30,Urban,HR Executive,98626,0 +99611,Female,52,Bachelors,7,42,61,78,15,0.0,1,65,Urban,ML Engineer,119279,1 +99612,Male,42,High School,2,51,47,83,54,7.0,6,92,Rural,Manager,35700,1 +99613,Male,38,Bachelors,1,86,38,96,7,9.0,4,78,Urban,ML Engineer,102572,1 +99614,Male,36,Bachelors,13,55,30,93,56,2.0,0,8,Semi-Urban,Data Analyst,46666,0 +99615,Other,22,Bachelors,6,97,19,11,34,6.0,1,37,Semi-Urban,Manager,65164,0 +99616,Female,46,Bachelors,16,89,68,85,78,6.0,5,75,Urban,Software Engineer,93456,1 +99617,Male,47,Diploma,17,26,60,33,79,5.0,6,37,Urban,Software Engineer,142528,0 +99618,Female,58,Bachelors,1,34,71,60,5,6.0,5,49,Urban,HR Executive,73293,0 +99619,Male,55,PhD,13,7,49,24,26,6.0,6,80,Rural,Data Analyst,122738,0 +99620,Male,53,High School,0,91,76,7,63,8.0,0,67,Urban,HR Executive,49264,1 +99621,Male,40,High School,6,88,65,55,88,7.0,6,80,Urban,Manager,144751,1 +99622,Male,24,Masters,0,6,11,21,39,8.0,4,14,Urban,HR Executive,29578,0 +99623,Male,25,PhD,4,35,95,47,17,4.0,4,42,Rural,Data Analyst,149180,0 +99624,Female,29,Masters,3,29,49,49,13,5.0,7,63,Semi-Urban,ML Engineer,63317,0 +99625,Female,38,PhD,4,32,57,23,9,1.0,6,72,Urban,Software Engineer,50384,0 +99626,Female,30,Masters,19,89,89,84,95,0.0,3,2,Rural,ML Engineer,144577,1 +99627,Female,49,Bachelors,9,65,16,96,59,6.0,0,63,Urban,Data Analyst,116127,0 +99628,Female,27,Diploma,11,62,13,96,1,0.0,3,14,Urban,HR Executive,94111,0 +99629,Male,22,Diploma,15,4,76,59,2,1.0,3,40,Semi-Urban,Software Engineer,132719,0 +99630,Male,53,High School,1,2,78,33,45,8.0,5,52,Urban,Data Analyst,82748,0 +99631,Male,52,Bachelors,5,83,4,30,32,8.0,5,39,Urban,Manager,22060,0 +99632,Male,22,High School,3,34,88,17,82,1.0,0,54,Rural,Data Analyst,26772,0 +99633,Female,26,Bachelors,10,84,30,44,47,5.0,4,43,Rural,Data Analyst,48280,0 +99634,Male,31,Masters,0,11,60,16,40,3.0,7,50,Urban,Data Analyst,59619,0 +99635,Female,36,Diploma,12,45,40,39,58,8.0,1,92,Urban,Manager,38040,0 +99636,Male,34,PhD,6,41,92,16,33,2.0,2,73,Urban,HR Executive,83851,0 +99637,Male,44,Diploma,18,24,40,61,39,4.0,6,70,Rural,Software Engineer,53681,0 +99638,Female,39,Masters,13,63,65,41,46,9.0,3,42,Urban,Manager,55792,0 +99639,Female,56,High School,10,63,40,67,1,3.0,6,24,Urban,Software Engineer,113200,0 +99640,Male,31,Bachelors,17,45,91,2,3,7.0,6,91,Semi-Urban,Data Analyst,139503,0 +99641,Male,39,Bachelors,19,33,61,46,95,3.0,6,75,Urban,Manager,132415,0 +99642,Male,26,Bachelors,12,56,81,46,93,2.0,6,30,Urban,Manager,21484,0 +99643,Male,57,Bachelors,8,8,9,61,7,2.0,0,41,Semi-Urban,Manager,143019,0 +99644,Female,47,Bachelors,14,49,21,1,32,7.0,2,94,Semi-Urban,Data Analyst,47787,0 +99645,Male,24,Masters,10,48,75,67,97,3.0,5,21,Urban,ML Engineer,70665,0 +99646,Male,34,Masters,17,83,40,11,12,2.0,1,8,Urban,Data Analyst,50604,0 +99647,Female,22,High School,17,41,81,89,32,6.0,6,84,Urban,ML Engineer,131108,1 +99648,Female,48,Bachelors,15,81,23,65,56,9.0,3,15,Urban,Manager,21850,0 +99649,Female,40,Masters,4,14,25,52,5,7.0,6,33,Semi-Urban,HR Executive,82677,0 +99650,Female,33,High School,8,70,25,60,12,4.0,3,3,Rural,ML Engineer,72499,0 +99651,Female,44,Diploma,8,93,5,48,91,7.0,2,28,Urban,Manager,104221,0 +99652,Male,52,Masters,14,40,32,60,60,4.0,4,66,Rural,Software Engineer,118775,0 +99653,Male,33,High School,13,88,60,76,72,1.0,6,42,Semi-Urban,Software Engineer,68818,1 +99654,Male,51,Bachelors,9,38,97,9,1,2.0,1,75,Semi-Urban,Software Engineer,131076,0 +99655,Male,46,Diploma,17,92,59,40,40,3.0,4,7,Semi-Urban,Manager,70642,0 +99656,Male,31,Bachelors,16,2,62,2,1,1.0,6,98,Semi-Urban,Software Engineer,113669,0 +99657,Male,59,Diploma,19,61,47,63,16,1.0,7,40,Semi-Urban,ML Engineer,45704,0 +99658,Male,42,High School,12,30,15,46,84,7.0,1,78,Rural,HR Executive,75696,0 +99659,Male,43,High School,1,50,66,1,85,4.0,3,79,Urban,Manager,86283,0 +99660,Male,46,Bachelors,0,86,22,53,41,4.0,7,9,Urban,Software Engineer,109454,0 +99661,Female,34,Diploma,4,79,73,6,4,2.0,6,51,Semi-Urban,Data Analyst,93250,0 +99662,Other,43,Bachelors,8,83,76,81,25,8.0,7,37,Urban,HR Executive,63147,1 +99663,Male,49,High School,14,1,86,92,26,8.0,4,36,Semi-Urban,Manager,39642,0 +99664,Male,45,Bachelors,7,48,71,35,70,5.0,3,63,Semi-Urban,Manager,25132,0 +99665,Male,22,High School,0,11,83,79,83,7.0,3,4,Urban,HR Executive,136351,0 +99666,Male,43,Bachelors,3,56,75,36,72,9.0,3,22,Rural,Data Analyst,120480,0 +99667,Male,33,Bachelors,19,51,5,3,9,9.0,1,71,Rural,ML Engineer,139637,0 +99668,Female,30,PhD,18,2,14,16,63,5.0,1,87,Rural,Software Engineer,95541,0 +99669,Male,46,Bachelors,6,2,27,64,63,6.0,3,17,Semi-Urban,ML Engineer,34385,0 +99670,Male,41,Bachelors,17,35,7,83,39,1.0,6,81,Semi-Urban,Data Analyst,30568,0 +99671,Female,28,Bachelors,3,27,82,30,85,3.0,7,65,Semi-Urban,Manager,45931,0 +99672,Male,58,PhD,10,11,48,58,26,7.0,1,24,Semi-Urban,Software Engineer,24211,0 +99673,Male,35,Bachelors,11,70,90,9,84,6.0,2,34,Urban,ML Engineer,92242,0 +99674,Female,51,Masters,16,43,60,56,97,8.0,2,40,Urban,Software Engineer,102579,0 +99675,Male,31,Masters,11,18,1,74,67,0.0,5,8,Semi-Urban,ML Engineer,77464,0 +99676,Female,21,Bachelors,3,7,39,79,13,1.0,4,87,Semi-Urban,ML Engineer,116957,0 +99677,Male,40,Diploma,15,65,57,22,35,9.0,7,81,Semi-Urban,ML Engineer,80384,0 +99678,Male,51,Masters,18,61,37,7,81,3.0,0,11,Urban,HR Executive,52230,0 +99679,Male,59,Bachelors,16,98,61,50,65,1.0,6,90,Rural,Data Analyst,39263,1 +99680,Female,57,PhD,18,59,24,27,5,8.0,3,80,Urban,Software Engineer,74832,0 +99681,Female,57,Bachelors,4,64,89,76,77,2.0,7,23,Rural,Data Analyst,109963,1 +99682,Male,58,High School,19,6,39,20,78,4.0,3,10,Urban,Software Engineer,92540,0 +99683,Male,50,Bachelors,15,14,40,70,16,8.0,2,36,Urban,Manager,96877,0 +99684,Female,22,Bachelors,8,25,40,77,52,1.0,3,11,Semi-Urban,HR Executive,148983,0 +99685,Male,55,Bachelors,17,75,51,3,7,2.0,4,85,Urban,Data Analyst,61861,0 +99686,Male,51,Bachelors,14,82,44,99,76,1.0,7,10,Urban,Software Engineer,100556,1 +99687,Male,22,Bachelors,0,39,83,48,68,9.0,3,29,Urban,ML Engineer,48370,0 +99688,Male,43,PhD,2,62,23,37,97,8.0,1,98,Rural,Data Analyst,54154,0 +99689,Female,50,Diploma,17,91,90,64,23,3.0,4,52,Urban,HR Executive,28198,1 +99690,Male,50,High School,1,91,15,76,55,2.0,7,24,Rural,Manager,22045,0 +99691,Male,46,Bachelors,5,14,62,19,32,0.0,7,51,Semi-Urban,ML Engineer,39980,0 +99692,Female,40,Diploma,0,25,17,35,44,8.0,2,33,Rural,Manager,26633,0 +99693,Male,42,Bachelors,10,55,79,60,18,0.0,4,35,Urban,Manager,103686,0 +99694,Male,58,Masters,16,40,40,64,17,1.0,5,0,Urban,ML Engineer,32078,0 +99695,Male,48,Bachelors,10,77,64,35,38,2.0,6,69,Rural,Manager,59344,1 +99696,Female,49,High School,19,93,21,25,93,7.0,6,39,Urban,Manager,49826,0 +99697,Male,38,Diploma,13,37,81,96,52,0.0,7,95,Semi-Urban,Manager,116689,1 +99698,Male,54,Diploma,18,26,41,8,2,0.0,7,23,Semi-Urban,ML Engineer,147205,0 +99699,Female,42,Diploma,4,94,74,88,35,6.0,1,70,Urban,Data Analyst,111513,1 +99700,Male,28,Bachelors,13,8,41,85,45,6.0,7,96,Semi-Urban,Software Engineer,58311,0 +99701,Female,29,Masters,14,37,58,20,86,1.0,3,51,Rural,Manager,131779,0 +99702,Female,49,Bachelors,6,83,94,92,95,0.0,2,5,Rural,HR Executive,70158,1 +99703,Male,55,Bachelors,10,97,69,60,80,0.0,5,78,Rural,Software Engineer,74557,1 +99704,Male,37,Bachelors,3,31,20,43,61,9.0,3,14,Rural,ML Engineer,102477,0 +99705,Male,43,Diploma,8,27,39,60,84,9.0,1,80,Urban,Manager,30870,0 +99706,Female,22,Bachelors,11,40,13,34,7,6.0,1,37,Rural,Software Engineer,105130,0 +99707,Female,21,Bachelors,0,26,9,42,20,0.0,7,63,Urban,Software Engineer,66624,0 +99708,Male,32,Bachelors,13,43,94,79,47,8.0,7,23,Urban,HR Executive,102118,1 +99709,Male,26,PhD,1,18,77,2,11,2.0,0,43,Urban,Software Engineer,95981,0 +99710,Male,51,Diploma,8,51,1,9,44,1.0,5,73,Urban,ML Engineer,96577,0 +99711,Male,55,Masters,3,81,66,42,92,7.0,1,87,Urban,ML Engineer,69669,1 +99712,Male,27,PhD,10,87,10,46,11,6.0,3,33,Rural,ML Engineer,86050,0 +99713,Female,31,Bachelors,1,98,13,84,93,6.0,4,13,Urban,Manager,59473,0 +99714,Male,26,Diploma,10,40,14,72,53,4.0,7,44,Urban,Manager,69567,0 +99715,Male,28,Bachelors,11,84,3,2,36,7.0,4,99,Urban,HR Executive,89609,0 +99716,Female,35,Masters,3,78,3,92,40,2.0,6,87,Rural,Software Engineer,137147,1 +99717,Male,34,Masters,3,9,83,48,22,2.0,3,39,Semi-Urban,Data Analyst,23306,0 +99718,Male,46,Diploma,17,84,68,95,47,9.0,3,10,Urban,ML Engineer,116456,1 +99719,Male,46,Bachelors,19,79,64,84,41,6.0,1,68,Rural,HR Executive,120788,1 +99720,Female,52,High School,3,68,99,75,96,9.0,0,66,Urban,HR Executive,70055,1 +99721,Male,51,Bachelors,14,68,99,60,97,6.0,5,65,Urban,Data Analyst,76625,1 +99722,Male,28,Bachelors,5,56,72,44,80,5.0,1,76,Urban,Software Engineer,48235,1 +99723,Male,43,High School,10,97,3,99,82,1.0,4,23,Urban,ML Engineer,27041,0 +99724,Female,42,Bachelors,11,31,15,32,86,4.0,7,93,Semi-Urban,Data Analyst,112978,0 +99725,Other,26,High School,3,16,42,74,49,9.0,1,37,Urban,Software Engineer,77745,0 +99726,Other,52,Masters,18,26,22,0,70,4.0,3,97,Urban,Manager,124071,0 +99727,Male,56,High School,10,14,47,61,5,3.0,4,17,Urban,Data Analyst,53062,0 +99728,Other,36,Diploma,17,73,78,22,16,6.0,3,43,Rural,Manager,140830,0 +99729,Male,47,Masters,6,86,9,2,35,2.0,2,16,Urban,HR Executive,145585,0 +99730,Male,57,Diploma,5,21,38,16,94,2.0,7,14,Urban,ML Engineer,60824,0 +99731,Female,30,Bachelors,6,68,93,35,90,9.0,4,19,Semi-Urban,Software Engineer,79155,0 +99732,Female,30,Diploma,11,96,82,9,13,9.0,6,79,Rural,Manager,67329,1 +99733,Male,30,Bachelors,10,73,69,51,5,1.0,6,58,Urban,HR Executive,123183,1 +99734,Male,48,Diploma,7,80,64,83,79,5.0,2,9,Semi-Urban,HR Executive,26387,1 +99735,Other,27,High School,2,40,19,34,88,8.0,1,3,Urban,HR Executive,140541,0 +99736,Male,29,High School,15,65,53,88,82,9.0,1,70,Rural,Manager,120539,1 +99737,Female,38,Diploma,10,8,18,91,68,9.0,5,85,Urban,Manager,122768,0 +99738,Female,44,Bachelors,10,18,10,90,64,1.0,4,88,Rural,Software Engineer,95701,0 +99739,Male,32,High School,13,70,38,89,0,7.0,6,99,Rural,HR Executive,120024,1 +99740,Male,48,Masters,19,30,43,41,86,4.0,6,61,Rural,Software Engineer,40739,0 +99741,Male,31,Bachelors,2,5,30,21,16,1.0,6,19,Urban,Software Engineer,109888,0 +99742,Male,42,Bachelors,13,68,31,20,49,5.0,3,40,Rural,HR Executive,136176,0 +99743,Female,45,Bachelors,12,96,19,26,56,6.0,6,97,Semi-Urban,ML Engineer,74107,0 +99744,Male,38,Masters,8,80,86,57,41,7.0,3,87,Semi-Urban,Software Engineer,69861,1 +99745,Male,29,Masters,12,79,75,29,74,2.0,4,1,Urban,Data Analyst,52092,0 +99746,Male,47,Bachelors,9,28,22,16,83,7.0,7,15,Semi-Urban,Software Engineer,102257,0 +99747,Male,53,Bachelors,4,93,62,19,86,8.0,7,70,Urban,Manager,38484,1 +99748,Male,45,Diploma,18,36,48,55,20,2.0,0,43,Rural,HR Executive,62282,0 +99749,Male,55,Diploma,10,61,90,10,13,0.0,6,7,Semi-Urban,Data Analyst,132092,0 +99750,Male,33,Masters,4,4,75,49,35,0.0,0,13,Urban,HR Executive,21119,0 +99751,Male,37,Bachelors,4,36,32,58,80,6.0,6,20,Semi-Urban,ML Engineer,44663,0 +99752,Female,47,Bachelors,12,59,57,39,93,3.0,3,14,Semi-Urban,HR Executive,48459,0 +99753,Other,54,Bachelors,9,54,1,69,50,9.0,7,18,Urban,ML Engineer,76123,0 +99754,Male,29,Diploma,0,48,11,75,59,8.0,3,1,Urban,ML Engineer,71142,0 +99755,Male,38,Bachelors,17,76,23,72,76,4.0,7,55,Rural,Data Analyst,91250,0 +99756,Male,46,Bachelors,17,58,20,32,80,9.0,3,66,Urban,Manager,44099,0 +99757,Male,40,Diploma,12,75,73,80,15,2.0,1,72,Urban,Data Analyst,123040,1 +99758,Female,28,Masters,14,91,37,59,3,2.0,7,79,Urban,Software Engineer,149897,1 +99759,Female,25,Bachelors,10,12,19,41,24,2.0,1,25,Urban,Software Engineer,79804,0 +99760,Male,51,High School,15,49,95,75,78,3.0,7,25,Semi-Urban,Data Analyst,142926,1 +99761,Female,35,Bachelors,9,60,49,46,22,1.0,3,6,Urban,Data Analyst,32602,0 +99762,Other,40,Bachelors,17,82,31,28,29,6.0,3,85,Urban,HR Executive,146722,0 +99763,Male,59,Bachelors,14,9,48,62,60,0.0,7,49,Urban,ML Engineer,29224,0 +99764,Other,43,Bachelors,3,83,68,49,80,1.0,7,35,Semi-Urban,ML Engineer,117497,0 +99765,Female,50,Diploma,4,28,28,27,95,2.0,3,71,Urban,HR Executive,107769,0 +99766,Male,22,Bachelors,2,44,5,50,67,3.0,4,34,Urban,Software Engineer,41925,0 +99767,Female,28,Masters,17,14,24,19,38,8.0,0,76,Urban,ML Engineer,70341,0 +99768,Male,39,Masters,5,9,26,64,50,0.0,5,71,Rural,ML Engineer,114491,0 +99769,Male,56,Bachelors,5,36,84,29,26,8.0,1,16,Urban,ML Engineer,45834,0 +99770,Female,42,Masters,12,93,67,17,50,5.0,6,71,Urban,Data Analyst,78382,1 +99771,Female,35,High School,0,14,49,13,34,7.0,1,98,Semi-Urban,HR Executive,117857,0 +99772,Male,44,Bachelors,3,37,30,34,31,4.0,6,30,Semi-Urban,Manager,140847,0 +99773,Male,29,PhD,14,68,99,71,49,2.0,7,56,Rural,Data Analyst,56575,1 +99774,Male,48,Diploma,9,43,2,96,6,3.0,0,38,Semi-Urban,Manager,126071,0 +99775,Male,34,Diploma,19,69,5,58,9,7.0,5,75,Urban,Manager,35834,0 +99776,Male,51,Bachelors,16,41,66,47,87,7.0,5,91,Urban,HR Executive,55981,1 +99777,Male,26,Bachelors,18,78,18,15,89,5.0,6,18,Urban,Manager,149088,0 +99778,Female,32,Bachelors,19,69,4,55,33,3.0,5,45,Urban,HR Executive,20602,0 +99779,Male,23,Bachelors,0,12,98,38,2,5.0,5,17,Urban,Data Analyst,126693,0 +99780,Male,56,Diploma,12,49,18,9,52,2.0,5,50,Urban,Manager,40718,0 +99781,Female,48,Masters,4,2,9,80,57,6.0,1,98,Urban,Manager,138719,0 +99782,Male,24,Masters,18,57,22,13,29,8.0,3,19,Semi-Urban,ML Engineer,110668,0 +99783,Male,26,High School,2,69,64,51,5,6.0,7,71,Urban,Software Engineer,24260,1 +99784,Female,38,High School,19,52,74,99,35,8.0,5,1,Urban,Data Analyst,103859,0 +99785,Male,31,Bachelors,0,68,57,11,28,2.0,0,21,Urban,Manager,69252,0 +99786,Male,29,Masters,18,10,14,99,56,3.0,5,54,Urban,ML Engineer,134595,0 +99787,Male,52,Bachelors,13,5,26,83,39,1.0,4,64,Urban,HR Executive,89497,0 +99788,Male,25,Bachelors,14,96,4,87,76,2.0,3,88,Semi-Urban,Data Analyst,39704,1 +99789,Male,41,Bachelors,8,46,82,7,67,1.0,3,71,Rural,HR Executive,35644,0 +99790,Female,55,Bachelors,13,20,22,33,22,0.0,0,70,Urban,HR Executive,32683,0 +99791,Other,45,Bachelors,0,70,18,12,57,4.0,1,54,Semi-Urban,Manager,104584,0 +99792,Male,56,Masters,12,77,7,54,58,0.0,2,35,Semi-Urban,ML Engineer,98357,0 +99793,Female,32,Diploma,1,77,33,98,26,2.0,0,95,Urban,HR Executive,102072,1 +99794,Male,47,Diploma,3,20,8,77,29,0.0,1,74,Rural,ML Engineer,101252,0 +99795,Male,30,Bachelors,2,92,1,88,18,6.0,0,88,Rural,Data Analyst,87570,1 +99796,Male,35,Bachelors,7,75,89,5,43,8.0,5,69,Rural,Data Analyst,108092,1 +99797,Female,35,Bachelors,4,29,36,53,37,4.0,6,98,Rural,Data Analyst,119694,0 +99798,Male,30,PhD,2,44,8,82,45,3.0,0,77,Urban,Software Engineer,56307,0 +99799,Female,35,Diploma,13,32,24,63,42,5.0,3,62,Urban,Software Engineer,105291,0 +99800,Female,47,High School,12,73,35,40,85,8.0,7,30,Rural,HR Executive,60911,0 +99801,Other,27,Diploma,19,1,40,7,68,1.0,5,17,Rural,Data Analyst,40104,0 +99802,Female,37,Masters,7,93,19,52,84,9.0,2,38,Semi-Urban,Software Engineer,39757,0 +99803,Other,27,High School,0,10,71,55,6,8.0,3,92,Semi-Urban,ML Engineer,61717,0 +99804,Male,59,Diploma,7,63,80,9,34,9.0,2,78,Semi-Urban,Software Engineer,66910,0 +99805,Male,58,High School,17,14,86,43,27,1.0,4,45,Urban,HR Executive,129632,0 +99806,Male,33,Masters,1,44,32,80,31,3.0,4,67,Semi-Urban,Manager,116743,0 +99807,Male,51,Masters,17,96,32,21,98,9.0,1,11,Urban,ML Engineer,99427,0 +99808,Male,29,Diploma,19,42,97,51,69,5.0,6,23,Rural,ML Engineer,128896,0 +99809,Male,30,Masters,5,43,76,15,17,9.0,7,69,Urban,ML Engineer,102871,0 +99810,Female,59,High School,0,53,67,13,74,1.0,7,51,Rural,Data Analyst,29418,0 +99811,Female,51,PhD,9,26,69,0,26,6.0,6,15,Urban,ML Engineer,124608,0 +99812,Female,25,Bachelors,8,54,44,47,29,5.0,0,82,Urban,Data Analyst,95302,0 +99813,Female,28,Bachelors,14,6,41,17,11,0.0,2,0,Urban,Manager,72238,0 +99814,Male,46,Bachelors,1,23,80,68,34,2.0,2,32,Rural,Manager,84186,0 +99815,Male,38,Bachelors,4,74,86,66,93,7.0,7,40,Urban,Data Analyst,110915,1 +99816,Male,57,Diploma,12,24,93,31,60,8.0,3,4,Semi-Urban,HR Executive,75061,0 +99817,Male,52,Bachelors,2,69,15,11,55,4.0,7,41,Rural,ML Engineer,98011,0 +99818,Male,53,Masters,3,11,7,81,71,8.0,6,84,Rural,Software Engineer,121781,0 +99819,Female,40,Bachelors,10,85,37,78,70,4.0,3,94,Urban,ML Engineer,89439,1 +99820,Male,56,Diploma,0,2,95,1,88,9.0,6,87,Semi-Urban,Data Analyst,69580,0 +99821,Male,40,Diploma,5,75,40,17,10,2.0,6,68,Urban,Software Engineer,131246,0 +99822,Male,56,Diploma,13,30,58,16,70,4.0,2,51,Urban,Software Engineer,44987,0 +99823,Female,23,PhD,12,72,97,89,32,0.0,4,66,Urban,Data Analyst,134979,1 +99824,Female,30,High School,9,16,77,82,18,0.0,6,71,Urban,Manager,86180,1 +99825,Female,46,Bachelors,10,83,41,63,29,0.0,4,35,Urban,ML Engineer,53916,0 +99826,Female,50,Masters,16,85,46,52,95,6.0,5,26,Urban,ML Engineer,127677,0 +99827,Male,58,Diploma,11,93,80,43,5,2.0,4,52,Rural,Data Analyst,109330,1 +99828,Male,42,High School,6,48,37,31,87,5.0,0,56,Urban,Data Analyst,64440,0 +99829,Male,21,High School,13,65,22,33,4,1.0,1,10,Urban,HR Executive,84027,0 +99830,Male,36,Bachelors,1,98,9,20,33,0.0,3,99,Urban,Manager,42888,0 +99831,Male,44,Masters,17,87,23,89,4,5.0,1,61,Semi-Urban,ML Engineer,72570,1 +99832,Male,22,Diploma,6,61,8,66,57,9.0,1,2,Urban,Manager,99681,0 +99833,Male,32,Bachelors,19,8,82,58,81,0.0,4,70,Rural,Data Analyst,112084,0 +99834,Female,29,Diploma,9,75,49,87,54,5.0,0,78,Semi-Urban,Software Engineer,54684,1 +99835,Male,57,Bachelors,7,85,13,37,35,8.0,3,79,Urban,Manager,127175,0 +99836,Male,57,Bachelors,5,58,41,28,92,6.0,7,1,Rural,Data Analyst,31002,0 +99837,Female,46,Bachelors,2,27,93,95,62,2.0,5,26,Urban,Manager,102978,1 +99838,Male,55,Masters,4,16,6,64,7,7.0,5,29,Rural,Software Engineer,112935,0 +99839,Female,25,Bachelors,0,27,0,90,83,1.0,2,21,Urban,Manager,122853,0 +99840,Male,51,Bachelors,9,54,61,24,49,8.0,2,30,Rural,ML Engineer,90718,0 +99841,Female,36,High School,4,76,17,17,34,2.0,7,36,Urban,Manager,116432,0 +99842,Female,45,PhD,3,36,14,29,8,1.0,0,27,Urban,Software Engineer,138774,0 +99843,Female,39,Masters,9,81,34,47,79,5.0,6,79,Urban,HR Executive,44829,1 +99844,Male,21,Masters,5,30,97,91,43,1.0,0,62,Semi-Urban,ML Engineer,94652,1 +99845,Female,34,Diploma,10,38,57,56,56,4.0,0,77,Semi-Urban,Manager,80301,0 +99846,Male,21,Diploma,14,8,69,28,78,4.0,4,34,Urban,ML Engineer,107434,0 +99847,Male,52,High School,16,29,66,94,33,6.0,1,78,Semi-Urban,HR Executive,98279,1 +99848,Female,36,Bachelors,8,25,53,67,37,1.0,6,30,Urban,Software Engineer,102091,0 +99849,Female,34,Diploma,15,25,69,97,52,0.0,3,24,Semi-Urban,ML Engineer,37293,0 +99850,Female,38,Diploma,18,59,6,56,50,4.0,4,62,Urban,Software Engineer,85236,0 +99851,Male,51,High School,17,76,60,46,83,7.0,2,80,Semi-Urban,Manager,39138,1 +99852,Male,38,High School,14,93,0,70,87,7.0,7,56,Rural,Data Analyst,24687,0 +99853,Male,51,Bachelors,6,33,27,29,96,5.0,4,34,Urban,Software Engineer,35717,0 +99854,Male,33,Diploma,8,89,72,10,9,5.0,5,87,Rural,ML Engineer,123916,1 +99855,Male,54,Masters,10,23,61,71,18,1.0,6,30,Urban,Software Engineer,139033,0 +99856,Male,32,Bachelors,5,23,90,62,52,5.0,7,31,Semi-Urban,Manager,81224,0 +99857,Female,35,Bachelors,10,44,34,83,92,5.0,5,76,Urban,ML Engineer,123143,0 +99858,Female,51,Masters,15,97,29,40,83,5.0,1,81,Urban,Software Engineer,148001,1 +99859,Male,25,Masters,6,46,20,90,28,4.0,6,2,Urban,ML Engineer,115313,0 +99860,Male,42,Bachelors,11,50,50,35,33,9.0,1,13,Urban,ML Engineer,99260,0 +99861,Male,51,High School,14,6,39,46,16,1.0,5,37,Urban,Data Analyst,42941,0 +99862,Male,24,Masters,7,58,15,40,22,8.0,3,95,Rural,Data Analyst,97419,0 +99863,Male,33,Bachelors,4,13,52,69,26,3.0,7,97,Urban,Data Analyst,95352,0 +99864,Female,47,Masters,14,1,10,62,38,9.0,3,83,Urban,ML Engineer,129508,0 +99865,Female,51,Diploma,12,96,61,96,88,8.0,3,56,Rural,Data Analyst,91496,1 +99866,Female,37,High School,9,56,15,97,0,8.0,1,53,Rural,Data Analyst,95434,0 +99867,Female,54,Bachelors,4,28,79,35,14,7.0,0,67,Urban,Software Engineer,32754,0 +99868,Male,25,PhD,6,40,55,32,0,4.0,4,82,Rural,HR Executive,98910,0 +99869,Male,32,Bachelors,1,18,20,3,74,4.0,7,56,Urban,ML Engineer,66942,0 +99870,Male,43,High School,11,36,43,38,84,1.0,3,18,Urban,Manager,127398,0 +99871,Female,48,Masters,3,58,41,46,70,7.0,3,15,Urban,ML Engineer,21797,0 +99872,Female,34,Masters,13,19,7,43,17,7.0,0,52,Urban,Manager,52019,0 +99873,Male,39,Masters,7,81,58,12,78,5.0,2,40,Urban,Software Engineer,127650,0 +99874,Male,55,Masters,9,25,67,55,75,0.0,2,29,Semi-Urban,HR Executive,20055,0 +99875,Male,25,Bachelors,12,83,18,11,3,9.0,7,87,Rural,ML Engineer,52745,0 +99876,Male,34,Masters,17,63,46,74,80,4.0,7,58,Rural,ML Engineer,70885,1 +99877,Male,24,Diploma,13,99,63,38,81,7.0,4,88,Rural,Manager,59443,1 +99878,Male,44,Bachelors,19,20,68,79,39,1.0,0,89,Urban,HR Executive,58118,1 +99879,Female,56,High School,3,57,17,38,52,3.0,7,36,Urban,Data Analyst,119953,0 +99880,Male,47,Diploma,10,93,27,14,84,3.0,0,11,Semi-Urban,Software Engineer,122232,0 +99881,Male,49,High School,19,65,75,28,51,9.0,1,72,Urban,Manager,137151,1 +99882,Male,57,Bachelors,9,23,8,58,45,0.0,4,49,Urban,ML Engineer,41171,0 +99883,Male,21,Bachelors,0,50,71,95,46,4.0,0,48,Urban,Software Engineer,30908,1 +99884,Male,45,Masters,4,4,51,75,61,7.0,0,21,Urban,Software Engineer,20592,0 +99885,Male,41,Masters,19,99,72,5,85,3.0,2,57,Rural,HR Executive,131185,0 +99886,Male,35,Masters,17,7,52,99,81,3.0,2,83,Rural,ML Engineer,32174,1 +99887,Female,57,Bachelors,17,76,75,42,22,7.0,7,34,Urban,ML Engineer,76096,0 +99888,Male,54,Bachelors,3,33,2,53,89,7.0,0,95,Urban,ML Engineer,88187,0 +99889,Male,38,Masters,5,93,32,14,74,4.0,6,17,Rural,Manager,104551,0 +99890,Male,56,Diploma,19,8,6,60,56,7.0,3,94,Urban,HR Executive,91432,0 +99891,Male,38,Diploma,18,3,91,82,43,6.0,0,83,Urban,Manager,50993,1 +99892,Male,52,High School,8,25,49,8,94,4.0,3,31,Urban,ML Engineer,134856,0 +99893,Other,56,Bachelors,16,25,58,34,8,6.0,1,79,Urban,HR Executive,39751,0 +99894,Male,21,High School,19,75,22,54,37,2.0,4,4,Urban,Software Engineer,50266,0 +99895,Female,31,Diploma,7,50,52,4,94,2.0,1,23,Rural,HR Executive,26379,0 +99896,Male,34,Bachelors,0,36,67,42,42,5.0,7,0,Urban,ML Engineer,53273,0 +99897,Female,46,Bachelors,10,38,54,80,35,4.0,6,7,Urban,Software Engineer,98368,0 +99898,Male,32,Bachelors,7,51,69,45,49,4.0,3,53,Urban,Data Analyst,66710,0 +99899,Female,53,Masters,11,2,69,24,39,0.0,3,93,Urban,Manager,79792,0 +99900,Male,36,High School,11,11,74,38,77,5.0,6,95,Urban,Manager,107261,0 +99901,Male,28,Masters,8,93,92,32,85,3.0,6,95,Urban,HR Executive,112161,1 +99902,Male,43,Diploma,9,59,87,43,98,7.0,2,72,Rural,Software Engineer,122762,1 +99903,Female,35,Diploma,16,70,78,29,70,5.0,3,3,Urban,Manager,55319,0 +99904,Male,21,PhD,15,86,18,25,55,8.0,5,72,Urban,Software Engineer,113221,0 +99905,Male,38,Bachelors,18,94,36,39,10,6.0,5,4,Rural,Data Analyst,134907,0 +99906,Female,21,Diploma,12,16,89,43,65,1.0,4,18,Urban,Data Analyst,61308,0 +99907,Male,36,Diploma,7,95,83,15,50,6.0,5,34,Urban,Manager,149632,0 +99908,Male,58,Bachelors,9,3,64,18,56,5.0,1,7,Urban,HR Executive,57872,0 +99909,Male,30,Bachelors,8,22,47,13,57,4.0,3,98,Urban,Software Engineer,111704,0 +99910,Male,47,Bachelors,0,23,43,14,0,2.0,4,77,Urban,Software Engineer,34096,0 +99911,Male,49,Bachelors,8,46,32,11,1,9.0,6,37,Semi-Urban,HR Executive,118568,0 +99912,Male,33,Masters,9,70,77,77,29,7.0,5,67,Urban,HR Executive,45838,1 +99913,Male,50,High School,3,31,95,91,31,7.0,2,69,Urban,Data Analyst,44932,1 +99914,Female,47,Diploma,13,51,44,40,43,9.0,7,76,Semi-Urban,ML Engineer,83735,0 +99915,Male,38,Masters,3,44,87,34,82,1.0,1,85,Semi-Urban,Data Analyst,64215,1 +99916,Female,50,High School,18,96,84,29,88,4.0,4,18,Rural,Software Engineer,40769,0 +99917,Male,58,PhD,1,86,43,77,50,9.0,6,22,Rural,Data Analyst,96630,0 +99918,Male,44,Masters,18,46,75,30,58,3.0,1,56,Semi-Urban,Software Engineer,66486,0 +99919,Male,39,High School,15,44,65,5,58,0.0,7,62,Semi-Urban,HR Executive,116721,0 +99920,Female,48,Masters,1,95,10,65,14,4.0,4,90,Urban,Manager,91514,1 +99921,Male,50,High School,13,63,3,36,49,3.0,3,24,Semi-Urban,ML Engineer,76623,0 +99922,Male,52,Bachelors,17,28,35,35,20,8.0,0,72,Urban,Software Engineer,77026,0 +99923,Female,52,Masters,6,78,30,43,63,4.0,7,72,Semi-Urban,HR Executive,75163,0 +99924,Female,44,Bachelors,8,88,77,92,24,2.0,3,45,Urban,Software Engineer,82370,1 +99925,Male,53,Masters,17,99,23,19,54,7.0,2,32,Urban,Software Engineer,93523,0 +99926,Male,25,Bachelors,2,33,51,95,26,0.0,2,49,Urban,HR Executive,144815,0 +99927,Female,26,High School,1,7,63,22,47,1.0,6,69,Semi-Urban,Data Analyst,49528,0 +99928,Male,55,Bachelors,8,1,20,40,66,1.0,3,28,Urban,Software Engineer,105180,0 +99929,Male,30,High School,14,53,89,95,39,2.0,3,16,Urban,HR Executive,90541,1 +99930,Male,49,Masters,11,14,73,77,68,8.0,0,39,Urban,Data Analyst,143095,0 +99931,Male,30,Bachelors,9,62,59,67,29,0.0,1,24,Rural,Software Engineer,26369,0 +99932,Female,37,Diploma,11,32,81,40,93,2.0,7,99,Urban,Data Analyst,30835,1 +99933,Female,23,Bachelors,1,78,19,67,97,3.0,3,11,Semi-Urban,Data Analyst,79547,0 +99934,Female,21,Bachelors,13,74,96,45,29,5.0,2,66,Rural,Data Analyst,87440,1 +99935,Male,58,High School,14,78,78,20,19,1.0,1,52,Rural,HR Executive,41870,0 +99936,Other,57,Diploma,19,92,58,59,66,9.0,5,32,Urban,ML Engineer,56184,1 +99937,Male,49,Diploma,17,0,43,45,19,8.0,0,26,Rural,ML Engineer,141659,0 +99938,Male,50,Bachelors,15,27,34,95,93,9.0,1,9,Urban,Data Analyst,79080,0 +99939,Female,38,PhD,5,28,87,53,15,6.0,7,35,Urban,Manager,126537,0 +99940,Male,53,Masters,8,88,60,90,8,3.0,0,37,Urban,Manager,138988,1 +99941,Male,28,Bachelors,6,83,5,95,48,7.0,3,43,Rural,Software Engineer,73672,0 +99942,Male,59,Diploma,6,48,99,31,9,7.0,2,22,Semi-Urban,Manager,41595,0 +99943,Other,52,Bachelors,4,99,2,31,74,0.0,5,74,Urban,Software Engineer,48321,0 +99944,Female,26,Bachelors,15,29,58,32,96,6.0,5,91,Semi-Urban,Manager,127614,0 +99945,Male,59,High School,18,13,13,68,12,1.0,4,15,Urban,HR Executive,134948,0 +99946,Male,40,Masters,18,98,94,99,2,1.0,1,49,Semi-Urban,ML Engineer,66691,1 +99947,Male,59,Bachelors,2,40,31,34,86,6.0,4,22,Semi-Urban,ML Engineer,48478,0 +99948,Female,41,Bachelors,11,31,27,43,95,1.0,7,82,Rural,ML Engineer,76594,0 +99949,Male,43,Masters,15,65,88,67,52,4.0,0,65,Semi-Urban,HR Executive,73729,1 +99950,Other,32,Diploma,17,58,33,63,45,2.0,7,24,Urban,Software Engineer,131706,0 +99951,Male,23,Diploma,14,59,74,82,57,1.0,4,48,Urban,HR Executive,55850,1 +99952,Male,31,Diploma,13,89,42,2,42,1.0,6,34,Rural,ML Engineer,108039,0 +99953,Male,28,Bachelors,5,82,83,29,9,7.0,2,17,Urban,ML Engineer,73497,0 +99954,Female,30,Bachelors,10,58,9,90,45,0.0,4,26,Rural,Data Analyst,48657,0 +99955,Female,48,Masters,13,47,76,9,72,4.0,6,73,Urban,HR Executive,29287,0 +99956,Male,36,Bachelors,12,73,69,40,8,5.0,0,10,Urban,Data Analyst,94567,0 +99957,Male,32,Masters,7,71,0,10,23,0.0,3,70,Urban,Software Engineer,67629,0 +99958,Male,39,Diploma,17,45,70,39,54,4.0,2,81,Semi-Urban,ML Engineer,44659,1 +99959,Male,58,High School,14,9,72,12,38,1.0,1,81,Urban,Software Engineer,78567,0 +99960,Male,57,High School,4,67,7,25,85,4.0,7,26,Urban,Data Analyst,149356,0 +99961,Female,33,Masters,11,23,33,76,55,6.0,3,10,Urban,HR Executive,30869,0 +99962,Female,22,Bachelors,17,79,25,77,73,9.0,5,75,Semi-Urban,ML Engineer,105835,1 +99963,Male,34,High School,17,88,31,12,46,8.0,4,42,Urban,HR Executive,106189,0 +99964,Male,35,Bachelors,10,75,60,70,83,6.0,3,83,Urban,Software Engineer,94624,1 +99965,Other,45,Masters,15,66,68,72,0,7.0,2,60,Rural,Software Engineer,103564,1 +99966,Male,58,Masters,3,97,92,35,46,3.0,7,48,Semi-Urban,Manager,130301,1 +99967,Male,44,Diploma,14,45,47,30,23,1.0,3,59,Rural,HR Executive,107393,0 +99968,Male,57,Masters,17,3,90,32,73,0.0,5,59,Urban,Manager,63645,0 +99969,Male,47,Diploma,11,53,58,7,93,1.0,1,0,Urban,Data Analyst,132285,0 +99970,Male,49,High School,1,45,95,78,55,5.0,6,50,Urban,Software Engineer,88753,1 +99971,Male,36,Masters,15,7,11,35,18,3.0,3,49,Rural,HR Executive,26310,0 +99972,Male,58,Bachelors,4,84,20,29,90,8.0,1,97,Rural,HR Executive,149360,0 +99973,Female,26,High School,15,53,46,81,36,2.0,6,93,Urban,Data Analyst,39966,1 +99974,Other,31,Masters,5,21,16,38,89,9.0,7,64,Semi-Urban,ML Engineer,126297,0 +99975,Male,51,Masters,19,23,79,52,52,7.0,4,0,Urban,Data Analyst,145111,0 +99976,Female,34,Bachelors,14,22,28,97,74,7.0,6,79,Urban,HR Executive,92445,0 +99977,Female,28,High School,19,34,15,59,85,5.0,5,68,Urban,Data Analyst,86052,0 +99978,Male,50,High School,0,23,69,73,34,3.0,5,27,Urban,Data Analyst,110170,0 +99979,Male,40,High School,19,90,91,85,68,4.0,3,75,Urban,Manager,77097,1 +99980,Female,55,Bachelors,5,2,44,84,6,2.0,5,44,Semi-Urban,Data Analyst,128452,0 +99981,Female,23,Masters,9,99,1,54,75,9.0,0,94,Semi-Urban,ML Engineer,68649,1 +99982,Female,56,Bachelors,13,95,44,26,43,5.0,0,11,Semi-Urban,Manager,81608,0 +99983,Male,54,Bachelors,18,66,82,45,17,2.0,2,83,Semi-Urban,Data Analyst,136654,1 +99984,Male,46,Masters,5,20,31,90,63,4.0,3,10,Urban,Data Analyst,88174,0 +99985,Female,53,Bachelors,5,72,80,66,91,9.0,6,34,Urban,Manager,74726,1 +99986,Male,40,High School,15,26,66,57,17,4.0,4,6,Semi-Urban,Software Engineer,66181,0 +99987,Female,33,Bachelors,7,81,67,12,28,4.0,2,81,Rural,HR Executive,26757,1 +99988,Male,56,High School,9,43,69,50,50,1.0,7,99,Urban,HR Executive,49274,1 +99989,Male,25,Diploma,3,37,70,49,10,2.0,0,22,Urban,Data Analyst,40487,0 +99990,Male,49,Diploma,18,16,83,56,71,5.0,7,33,Semi-Urban,HR Executive,91203,0 +99991,Female,45,Bachelors,14,21,20,93,61,4.0,4,0,Urban,Manager,50769,0 +99992,Male,29,Bachelors,4,71,43,18,7,8.0,2,96,Urban,Software Engineer,73827,0 +99993,Female,48,Bachelors,2,77,43,70,50,2.0,5,12,Semi-Urban,Manager,112936,0 +99994,Male,29,Bachelors,14,31,91,3,55,9.0,0,92,Urban,Data Analyst,136770,0 +99995,Female,47,High School,8,74,21,84,3,0.0,3,8,Rural,Software Engineer,31611,0 +99996,Female,35,Bachelors,13,75,77,31,10,1.0,6,81,Urban,ML Engineer,133888,1 +99997,Female,50,Diploma,3,79,91,95,12,5.0,2,78,Semi-Urban,ML Engineer,73180,1 +99998,Female,30,PhD,18,74,28,24,72,7.0,4,76,Urban,Software Engineer,67637,0 +99999,Male,50,Bachelors,13,63,93,7,94,6.0,5,0,Rural,HR Executive,83155,0 +100000,Male,54,Diploma,16,51,96,64,57,0.0,4,12,Urban,Data Analyst,49410,0 +100001,Male,26,Bachelors,13,53,66,77,74,4.0,6,66,Rural,Manager,69710,1 +100002,Male,51,Bachelors,14,28,0,10,10,0.0,5,90,Urban,Software Engineer,24723,0 +100003,Male,46,Bachelors,9,67,86,56,38,1.0,7,91,Semi-Urban,Manager,115817,1 +100004,Male,34,Diploma,10,76,29,19,75,6.0,0,29,Urban,Software Engineer,99425,0 +100005,Male,39,High School,11,46,84,78,86,5.0,7,20,Urban,Manager,39583,0 +100006,Female,59,Diploma,7,72,1,24,58,6.0,6,45,Rural,Software Engineer,24501,0 +100007,Female,39,Bachelors,1,60,62,94,97,4.0,2,78,Urban,Manager,26714,1 +100008,Female,40,Bachelors,5,58,98,1,18,5.0,6,69,Urban,Software Engineer,70408,0 +100009,Male,36,Bachelors,17,75,88,87,83,5.0,7,75,Urban,Software Engineer,117375,1 +100010,Male,25,Diploma,2,16,35,78,41,5.0,7,78,Urban,Manager,55424,0 +100011,Male,45,Diploma,5,53,12,81,72,6.0,7,76,Urban,ML Engineer,117106,0 +100012,Female,57,Diploma,9,39,66,52,12,0.0,5,79,Urban,ML Engineer,65735,0 +100013,Male,35,High School,5,72,30,35,36,0.0,7,39,Urban,Data Analyst,21934,0 +100014,Male,21,Masters,9,79,72,64,94,3.0,5,79,Urban,HR Executive,21464,1 +100015,Male,31,Bachelors,6,31,21,94,15,6.0,0,61,Semi-Urban,HR Executive,69358,0 +100016,Female,47,Bachelors,10,12,25,17,42,7.0,4,55,Urban,Software Engineer,138508,0 +100017,Male,28,Masters,10,75,45,87,7,5.0,1,86,Urban,ML Engineer,137911,1 +100018,Male,38,Masters,14,13,18,75,50,5.0,4,35,Semi-Urban,Data Analyst,76434,0 +100019,Male,25,PhD,5,90,5,65,2,7.0,1,32,Urban,Manager,141657,0 +100020,Male,27,Bachelors,15,49,66,20,78,8.0,4,64,Urban,Data Analyst,69937,0 +100021,Female,43,Diploma,10,83,30,46,63,1.0,4,34,Rural,ML Engineer,71686,0 +100022,Male,50,Bachelors,7,41,75,9,42,2.0,1,57,Urban,Software Engineer,108612,0 +100023,Female,45,Bachelors,8,33,27,20,44,6.0,3,22,Urban,Software Engineer,118842,0 +100024,Female,37,Bachelors,8,80,65,37,81,7.0,4,85,Urban,Data Analyst,25429,1 +100025,Male,44,High School,12,69,17,96,54,8.0,4,47,Urban,ML Engineer,36360,0 +100026,Male,49,Diploma,7,52,12,30,62,4.0,4,57,Urban,HR Executive,143452,0 +100027,Male,59,Bachelors,13,4,23,2,34,6.0,6,41,Urban,ML Engineer,59493,0 +100028,Female,45,Masters,9,61,70,89,26,5.0,0,98,Semi-Urban,HR Executive,132527,1 +100029,Male,31,Bachelors,1,5,14,68,89,0.0,2,63,Urban,HR Executive,129668,0 +100030,Male,24,Bachelors,8,11,16,76,92,2.0,1,17,Urban,Manager,129202,0 +100031,Female,34,Bachelors,13,61,90,50,5,3.0,5,14,Urban,Manager,140253,0 +100032,Male,59,High School,16,88,88,0,59,6.0,0,42,Urban,Data Analyst,34837,0 +100033,Female,27,Masters,13,4,66,16,70,6.0,5,13,Urban,HR Executive,34652,0 +100034,Female,26,Masters,12,53,30,14,8,3.0,0,17,Rural,HR Executive,124228,0 +100035,Other,50,PhD,17,63,14,24,61,6.0,3,52,Urban,Data Analyst,50227,0 +100036,Male,26,Bachelors,11,17,2,46,34,6.0,7,73,Rural,ML Engineer,86835,0 +100037,Male,43,Masters,4,95,24,12,22,1.0,3,42,Urban,Software Engineer,148970,0 +100038,Female,37,Bachelors,9,85,3,41,5,6.0,2,66,Rural,Software Engineer,91515,0 +100039,Other,32,Diploma,9,81,3,12,65,7.0,4,35,Urban,Software Engineer,126675,0 +100040,Male,27,High School,9,94,67,71,64,3.0,7,50,Urban,Software Engineer,25796,1 +100041,Male,39,High School,10,86,97,6,26,9.0,1,10,Rural,HR Executive,82109,0 +100042,Male,25,Masters,2,54,87,75,63,5.0,2,34,Urban,Software Engineer,69614,1 +100043,Female,58,Bachelors,6,14,72,52,82,3.0,7,42,Urban,Manager,90862,0 +100044,Female,40,High School,2,47,97,4,15,6.0,3,76,Urban,Manager,134919,0 +100045,Male,29,High School,8,54,84,20,55,3.0,0,53,Urban,ML Engineer,139438,0 +100046,Male,28,Diploma,6,74,47,49,93,4.0,7,85,Rural,Manager,32768,1 +100047,Male,46,Bachelors,10,2,79,7,63,8.0,3,3,Urban,ML Engineer,115884,0 +100048,Male,44,Bachelors,10,80,12,38,95,7.0,1,9,Urban,ML Engineer,40552,0 +100049,Male,36,Diploma,0,86,68,97,87,2.0,5,67,Urban,Manager,147158,1 +100050,Male,22,Diploma,7,56,24,73,50,1.0,5,61,Urban,Software Engineer,34553,0 +100051,Male,45,High School,8,85,54,84,0,3.0,1,31,Rural,HR Executive,91623,1 +100052,Male,44,High School,2,15,12,90,66,5.0,3,32,Semi-Urban,Manager,75209,0 +100053,Male,48,Bachelors,2,5,87,91,84,5.0,5,70,Urban,Manager,83697,1 +100054,Female,49,Masters,3,30,36,73,7,9.0,1,72,Urban,Software Engineer,110740,0 +100055,Female,56,Masters,13,73,21,74,21,0.0,3,50,Semi-Urban,HR Executive,25059,0 +100056,Female,45,Masters,14,87,87,22,10,6.0,7,34,Urban,Software Engineer,62561,0 +100057,Female,23,Masters,10,45,64,70,89,7.0,6,6,Urban,Manager,89572,0 +100058,Female,24,Bachelors,11,15,11,91,45,6.0,7,60,Urban,ML Engineer,34332,0 +100059,Male,54,Diploma,9,40,28,69,33,5.0,4,61,Urban,Software Engineer,43619,0 +100060,Male,49,Diploma,4,24,11,49,84,2.0,2,85,Urban,ML Engineer,106171,0 +100061,Other,22,Masters,6,61,51,55,50,0.0,4,43,Urban,Data Analyst,134310,0 +100062,Male,55,Diploma,12,16,23,4,43,2.0,7,17,Urban,Software Engineer,72070,0 +100063,Male,55,PhD,1,29,38,67,85,8.0,5,90,Urban,Data Analyst,86335,0 +100064,Male,32,Bachelors,15,82,82,83,3,9.0,0,2,Semi-Urban,ML Engineer,91243,1 +100065,Female,35,Bachelors,19,17,14,4,2,9.0,4,79,Semi-Urban,Data Analyst,93807,0 +100066,Male,54,Bachelors,13,9,85,6,44,0.0,4,9,Rural,ML Engineer,149073,0 +100067,Male,34,Bachelors,10,74,52,46,25,3.0,4,31,Semi-Urban,Manager,56089,0 +100068,Female,34,Bachelors,4,65,38,1,26,7.0,2,55,Urban,Software Engineer,83524,0 +100069,Other,35,High School,10,91,50,5,3,5.0,0,60,Urban,Software Engineer,52536,0 +100070,Male,35,Diploma,13,85,75,14,92,1.0,2,20,Semi-Urban,Software Engineer,100440,0 +100071,Male,40,Bachelors,18,46,36,76,72,5.0,4,12,Urban,Data Analyst,125916,0 +100072,Other,33,Masters,15,0,36,16,17,1.0,1,58,Rural,Data Analyst,130177,0 +100073,Male,30,Bachelors,12,7,69,73,13,0.0,0,42,Urban,Data Analyst,31478,0 +100074,Male,48,Bachelors,19,76,49,93,94,4.0,3,53,Urban,HR Executive,142647,1 +100075,Male,57,Diploma,3,92,81,96,17,7.0,1,25,Semi-Urban,Data Analyst,136739,1 +100076,Male,29,Bachelors,18,29,88,41,7,8.0,5,72,Urban,HR Executive,28491,0 +100077,Male,55,Masters,19,78,51,69,72,6.0,6,30,Rural,Data Analyst,104080,0 +100078,Female,37,Masters,15,19,12,89,67,1.0,3,52,Urban,Manager,133784,0 +100079,Male,32,Masters,0,15,36,26,77,8.0,1,13,Urban,Data Analyst,114803,0 +100080,Male,35,Masters,0,58,93,92,71,4.0,6,45,Urban,HR Executive,107200,1 +100081,Male,25,Diploma,12,65,39,38,75,8.0,4,42,Urban,Manager,96197,0 +100082,Other,21,Diploma,17,30,37,62,70,1.0,5,13,Urban,Data Analyst,45484,0 +100083,Male,38,Diploma,5,23,21,8,22,6.0,3,86,Semi-Urban,Data Analyst,146763,0 +100084,Male,36,Masters,9,93,65,26,82,9.0,2,66,Urban,ML Engineer,112370,1 +100085,Male,49,Diploma,16,36,81,52,81,7.0,2,8,Rural,Data Analyst,47804,0 +100086,Female,51,Masters,5,47,49,19,41,5.0,0,2,Urban,Data Analyst,20925,0 +100087,Female,54,Bachelors,7,44,20,9,29,6.0,2,70,Urban,Software Engineer,54401,0 +100088,Female,30,Bachelors,14,4,42,60,77,1.0,0,98,Urban,Software Engineer,61516,0 +100089,Female,23,PhD,15,69,11,48,76,6.0,7,52,Semi-Urban,HR Executive,92669,0 +100090,Male,45,Bachelors,5,29,25,9,87,8.0,4,81,Urban,Software Engineer,148951,0 +100091,Male,26,Bachelors,0,20,89,25,35,4.0,6,52,Urban,Software Engineer,86240,0 +100092,Other,29,Bachelors,7,95,4,23,33,8.0,6,94,Urban,Data Analyst,36683,0 +100093,Male,33,Diploma,11,84,22,14,6,5.0,7,78,Semi-Urban,Software Engineer,100041,0 +100094,Male,44,Masters,13,35,6,6,8,7.0,1,98,Urban,ML Engineer,36173,0 +100095,Male,44,Diploma,13,23,15,85,84,4.0,6,71,Urban,HR Executive,45120,0 +100096,Male,36,Bachelors,18,92,29,69,81,3.0,2,79,Semi-Urban,Data Analyst,75956,1 +100097,Male,45,Bachelors,5,61,70,84,62,1.0,4,19,Urban,HR Executive,87313,0 +100098,Other,23,Diploma,12,3,79,89,88,4.0,6,83,Semi-Urban,HR Executive,54448,1 +100099,Male,42,Masters,17,82,22,49,86,1.0,5,69,Semi-Urban,Data Analyst,62145,0 +100100,Male,52,Bachelors,12,49,5,41,31,0.0,0,20,Rural,HR Executive,33425,0 +100101,Female,35,Masters,5,20,93,89,8,9.0,4,45,Urban,ML Engineer,87200,1 +100102,Male,32,Masters,5,67,75,20,33,4.0,6,43,Rural,Software Engineer,98384,0 +100103,Female,45,Bachelors,6,45,45,3,53,3.0,5,47,Urban,HR Executive,148818,0 +100104,Male,57,Bachelors,19,70,38,79,41,3.0,6,58,Urban,Software Engineer,43666,1 +100105,Female,36,Bachelors,8,58,83,38,44,5.0,6,38,Semi-Urban,HR Executive,38856,0 +100106,Female,22,Bachelors,13,21,52,40,29,5.0,6,14,Semi-Urban,Software Engineer,50638,0 +100107,Male,56,Bachelors,15,32,92,84,55,0.0,3,64,Semi-Urban,Manager,87725,1 +100108,Male,38,Bachelors,8,27,32,48,52,5.0,7,63,Urban,Software Engineer,53116,0 +100109,Female,44,Bachelors,15,72,60,59,7,5.0,4,51,Urban,Data Analyst,70499,1 +100110,Female,51,Bachelors,8,87,1,40,55,4.0,0,34,Semi-Urban,ML Engineer,63876,0 +100111,Male,54,High School,2,56,78,40,65,2.0,4,72,Urban,HR Executive,70319,1 +100112,Male,56,Bachelors,19,51,1,39,93,0.0,7,49,Urban,ML Engineer,72608,0 +100113,Male,32,Bachelors,2,35,13,35,14,6.0,0,71,Urban,Data Analyst,92021,0 +100114,Female,23,Bachelors,15,39,82,14,41,8.0,2,44,Urban,Data Analyst,132496,0 +100115,Male,37,PhD,4,50,68,31,93,1.0,3,60,Urban,Software Engineer,57192,0 +100116,Female,33,Masters,14,67,35,96,52,8.0,7,27,Rural,Data Analyst,38001,0 +100117,Male,55,Bachelors,15,55,7,57,99,8.0,4,38,Rural,Manager,109876,0 +100118,Male,52,Bachelors,2,34,56,7,50,2.0,4,40,Rural,Data Analyst,111972,0 +100119,Female,40,Masters,18,83,24,11,54,0.0,4,53,Rural,ML Engineer,127528,0 +100120,Male,40,High School,2,55,41,64,49,0.0,5,72,Urban,ML Engineer,49216,0 +100121,Male,35,Masters,16,95,72,64,40,7.0,7,87,Urban,ML Engineer,68328,1 +100122,Female,37,Masters,18,0,87,23,2,5.0,2,48,Rural,Manager,109494,0 +100123,Male,52,Bachelors,13,13,46,2,77,4.0,6,97,Rural,ML Engineer,26252,0 +100124,Female,22,PhD,11,11,67,83,59,2.0,1,20,Rural,HR Executive,56057,0 +100125,Female,36,Bachelors,7,68,82,12,16,5.0,3,48,Urban,Manager,99894,0 +100126,Male,38,Bachelors,7,31,24,39,27,5.0,2,21,Semi-Urban,Data Analyst,88771,0 +100127,Male,46,Bachelors,9,68,4,67,47,7.0,0,14,Urban,Manager,72411,0 +100128,Male,36,Bachelors,16,59,57,80,92,0.0,5,2,Urban,HR Executive,98690,0 +100129,Female,53,Masters,10,68,28,78,19,1.0,2,8,Semi-Urban,Software Engineer,29719,0 +100130,Female,49,Bachelors,4,30,26,19,39,3.0,1,6,Urban,Manager,25908,0 +100131,Female,25,High School,11,90,47,37,60,2.0,0,85,Urban,Data Analyst,141919,1 +100132,Female,22,High School,13,50,93,16,88,3.0,6,25,Rural,Data Analyst,93356,0 +100133,Male,23,Diploma,13,53,48,97,48,1.0,3,58,Urban,Software Engineer,138228,1 +100134,Male,28,High School,13,96,33,16,53,3.0,6,15,Urban,ML Engineer,87333,0 +100135,Female,32,Bachelors,8,84,4,31,98,4.0,3,17,Urban,Software Engineer,46962,0 +100136,Female,38,Masters,13,45,30,39,85,7.0,7,41,Rural,ML Engineer,82526,0 +100137,Male,52,High School,17,81,77,89,85,3.0,7,44,Semi-Urban,Software Engineer,141235,1 +100138,Other,24,Diploma,12,83,17,0,90,0.0,7,13,Urban,Data Analyst,27416,0 +100139,Female,31,Masters,12,45,79,97,58,6.0,6,33,Rural,HR Executive,29766,1 +100140,Female,28,High School,11,91,57,73,35,5.0,0,24,Urban,Data Analyst,30103,1 +100141,Male,48,Masters,15,98,2,41,62,9.0,2,65,Urban,Manager,72909,0 +100142,Male,31,Diploma,15,12,92,46,34,2.0,1,53,Rural,Software Engineer,136727,0 +100143,Female,47,High School,7,71,64,99,72,0.0,1,44,Urban,Manager,106559,1 +100144,Male,31,Bachelors,13,50,92,95,27,8.0,3,13,Urban,Data Analyst,87899,1 +100145,Female,43,Masters,15,87,84,26,55,2.0,0,20,Urban,Data Analyst,95319,0 +100146,Female,37,Bachelors,8,1,95,3,96,5.0,7,81,Urban,HR Executive,141362,0 +100147,Male,48,Diploma,5,99,99,29,67,8.0,0,30,Urban,HR Executive,123769,1 +100148,Female,59,Diploma,15,13,20,44,27,8.0,2,52,Semi-Urban,ML Engineer,40348,0 +100149,Male,49,Masters,17,36,76,61,43,4.0,3,60,Urban,Data Analyst,127503,0 +100150,Female,23,Diploma,0,14,42,73,37,2.0,2,95,Urban,Data Analyst,39038,0 +100151,Male,58,Bachelors,8,99,94,96,1,7.0,4,67,Rural,ML Engineer,118468,1 +100152,Female,56,Bachelors,9,48,94,64,71,7.0,7,2,Semi-Urban,HR Executive,85608,0 +100153,Male,36,High School,18,29,12,0,60,4.0,1,47,Urban,ML Engineer,127778,0 +100154,Male,25,Bachelors,7,45,35,96,51,6.0,0,52,Rural,Software Engineer,109689,0 +100155,Male,33,Bachelors,11,98,9,79,3,4.0,6,31,Rural,HR Executive,52192,0 +100156,Male,44,Bachelors,19,20,43,75,15,8.0,1,88,Urban,Data Analyst,64567,0 +100157,Female,29,Diploma,17,83,65,46,71,4.0,4,40,Urban,HR Executive,141182,0 +100158,Female,50,High School,15,79,83,95,16,3.0,6,55,Urban,HR Executive,127381,1 +100159,Female,58,Diploma,17,78,84,88,80,9.0,2,56,Urban,ML Engineer,50504,1 +100160,Female,31,Bachelors,7,21,76,33,22,2.0,4,76,Urban,Software Engineer,136280,0 +100161,Female,52,High School,17,37,18,34,66,2.0,5,89,Rural,Manager,137163,0 +100162,Male,29,Masters,5,43,7,8,21,3.0,6,51,Urban,Manager,146716,0 +100163,Male,38,Masters,5,70,13,85,91,9.0,3,32,Urban,Manager,149069,0 +100164,Male,27,PhD,17,10,85,50,99,2.0,7,51,Rural,HR Executive,47844,0 +100165,Male,42,Diploma,14,30,57,91,63,7.0,2,48,Urban,HR Executive,20943,0 +100166,Male,33,Diploma,13,49,88,40,60,7.0,3,61,Urban,Software Engineer,122676,1 +100167,Male,49,Diploma,11,73,98,77,24,1.0,3,79,Rural,Data Analyst,119464,1 +100168,Male,22,Diploma,1,71,8,97,15,9.0,0,42,Rural,ML Engineer,98140,0 +100169,Female,46,Bachelors,12,3,98,72,15,6.0,3,83,Semi-Urban,HR Executive,76348,1 +100170,Female,37,Masters,15,99,58,67,73,7.0,1,93,Urban,HR Executive,71528,1 +100171,Male,32,Bachelors,15,17,25,14,79,6.0,4,26,Urban,Software Engineer,37320,0 +100172,Female,35,Diploma,5,2,38,20,67,3.0,5,90,Urban,HR Executive,89646,0 +100173,Male,22,High School,2,17,23,65,99,4.0,6,14,Rural,ML Engineer,111453,0 +100174,Female,42,Bachelors,13,95,90,12,91,0.0,7,48,Semi-Urban,ML Engineer,41168,1 +100175,Male,38,Diploma,3,74,65,70,21,1.0,6,68,Rural,HR Executive,87290,1 +100176,Male,39,Masters,6,12,29,1,17,5.0,2,87,Urban,ML Engineer,108268,0 +100177,Male,28,Masters,13,67,70,24,37,2.0,0,13,Urban,Manager,116863,0 +100178,Male,27,Masters,14,19,91,63,21,8.0,2,84,Urban,Manager,120342,1 +100179,Male,47,Masters,17,70,39,81,17,4.0,1,43,Semi-Urban,Software Engineer,85299,0 +100180,Female,42,Bachelors,7,17,45,83,13,5.0,5,61,Urban,ML Engineer,83259,0 +100181,Male,36,Bachelors,15,5,22,12,27,5.0,1,18,Semi-Urban,Manager,25285,0 +100182,Female,44,Bachelors,10,17,66,10,20,5.0,7,78,Rural,HR Executive,46432,0 +100183,Female,39,Bachelors,7,1,52,24,49,6.0,6,81,Semi-Urban,ML Engineer,52173,0 +100184,Male,43,Diploma,10,62,30,41,98,6.0,6,3,Urban,Software Engineer,102918,0 +100185,Female,53,Masters,4,18,20,84,47,7.0,0,79,Rural,Software Engineer,20403,0 +100186,Female,23,Masters,0,62,62,61,10,6.0,0,97,Urban,Data Analyst,127288,1 +100187,Male,29,Masters,1,87,84,86,0,3.0,5,39,Urban,Data Analyst,34195,1 +100188,Female,58,Bachelors,5,1,22,60,77,4.0,3,49,Semi-Urban,Software Engineer,148376,0 +100189,Female,57,PhD,2,38,30,8,70,6.0,7,97,Rural,Manager,126793,0 +100190,Female,25,PhD,12,40,8,30,5,6.0,6,70,Rural,Manager,65485,0 +100191,Female,31,High School,19,4,21,44,35,4.0,0,3,Semi-Urban,ML Engineer,114085,0 +100192,Female,22,Bachelors,11,56,9,12,91,7.0,1,84,Urban,HR Executive,45487,0 +100193,Female,36,Masters,3,66,34,41,61,2.0,3,90,Rural,Data Analyst,124163,0 +100194,Male,27,Masters,13,68,67,23,28,6.0,6,12,Semi-Urban,Data Analyst,102942,0 +100195,Male,27,Masters,3,51,80,95,96,7.0,4,35,Urban,HR Executive,73159,1 +100196,Female,54,Masters,4,7,50,13,37,1.0,1,17,Rural,HR Executive,65439,0 +100197,Female,46,Bachelors,19,84,20,65,27,9.0,0,17,Urban,Manager,132931,0 +100198,Male,24,Diploma,16,47,7,90,73,5.0,6,24,Urban,Data Analyst,99874,0 +100199,Female,51,Diploma,4,12,28,28,29,5.0,2,21,Urban,ML Engineer,64352,0 +100200,Female,59,Bachelors,0,35,57,99,15,4.0,0,95,Urban,Data Analyst,123538,1 +100201,Male,46,Bachelors,18,61,0,50,62,6.0,0,23,Urban,Software Engineer,114439,0 +100202,Female,44,Bachelors,1,4,64,63,30,5.0,0,91,Urban,Manager,139606,0 +100203,Other,35,Masters,6,19,72,66,99,9.0,1,83,Semi-Urban,Manager,133256,0 +100204,Female,40,High School,18,58,98,71,87,5.0,5,50,Urban,ML Engineer,64888,1 +100205,Male,26,Diploma,10,95,73,63,71,3.0,1,9,Urban,Data Analyst,79419,1 +100206,Female,26,Diploma,3,3,74,0,19,3.0,5,79,Semi-Urban,Software Engineer,140336,0 +100207,Male,55,Masters,17,30,35,92,60,9.0,7,14,Rural,HR Executive,31598,0 +100208,Male,26,Bachelors,18,33,82,78,85,7.0,0,52,Urban,Data Analyst,129878,1 +100209,Male,39,Masters,13,52,47,56,68,0.0,6,70,Urban,Manager,67589,0 +100210,Male,29,Diploma,13,15,44,58,35,1.0,5,41,Urban,HR Executive,126707,0 +100211,Female,39,Diploma,11,2,27,87,2,2.0,5,74,Urban,Manager,75672,0 +100212,Male,47,Diploma,7,85,32,37,84,7.0,6,92,Urban,Software Engineer,134575,1 +100213,Male,31,Masters,15,13,51,1,74,6.0,7,48,Urban,Data Analyst,132233,0 +100214,Male,23,Masters,13,65,66,12,51,1.0,1,77,Urban,HR Executive,53674,0 +100215,Male,39,Bachelors,14,91,18,35,19,7.0,4,67,Urban,ML Engineer,107430,0 +100216,Female,46,High School,5,43,20,87,41,5.0,6,4,Semi-Urban,Software Engineer,96394,0 +100217,Female,54,PhD,15,36,52,47,63,9.0,5,90,Urban,Data Analyst,101486,0 +100218,Female,57,Bachelors,7,0,98,91,30,1.0,5,30,Semi-Urban,Data Analyst,46473,0 +100219,Male,45,Masters,6,69,68,1,68,1.0,7,70,Semi-Urban,ML Engineer,48246,0 +100220,Male,34,Bachelors,6,19,89,89,89,3.0,5,16,Semi-Urban,HR Executive,123466,0 +100221,Female,44,Diploma,18,24,85,64,12,0.0,3,33,Urban,HR Executive,57646,0 +100222,Female,22,Masters,2,65,39,36,70,1.0,3,5,Urban,HR Executive,80712,0 +100223,Male,48,Bachelors,4,5,14,0,58,2.0,3,50,Urban,ML Engineer,147931,0 +100224,Male,29,Masters,7,54,9,42,83,6.0,2,73,Semi-Urban,ML Engineer,120134,0 +100225,Male,46,Diploma,9,97,43,93,78,2.0,2,61,Semi-Urban,Data Analyst,133205,1 +100226,Female,37,Bachelors,11,17,27,27,52,2.0,6,77,Rural,Data Analyst,63695,0 +100227,Male,47,Diploma,10,43,8,47,49,5.0,1,88,Urban,Manager,26179,0 +100228,Female,39,Masters,3,98,38,95,5,1.0,5,94,Semi-Urban,HR Executive,97777,1 +100229,Male,45,Masters,0,38,91,3,70,9.0,5,6,Urban,Data Analyst,95715,0 +100230,Female,34,High School,1,5,70,95,75,5.0,4,51,Urban,HR Executive,64045,0 +100231,Male,31,Bachelors,9,28,60,2,73,0.0,3,53,Urban,ML Engineer,61697,0 +100232,Male,35,Bachelors,11,37,11,9,77,0.0,7,60,Semi-Urban,Manager,77697,0 +100233,Male,24,Bachelors,10,32,34,49,45,4.0,0,95,Semi-Urban,ML Engineer,37298,0 +100234,Male,33,Diploma,8,37,32,16,86,4.0,4,18,Semi-Urban,Software Engineer,81320,0 +100235,Female,58,High School,17,71,24,8,58,4.0,7,93,Urban,Software Engineer,61768,0 +100236,Male,38,High School,6,27,59,68,87,0.0,2,22,Rural,HR Executive,69376,0 +100237,Female,59,Diploma,14,94,97,97,78,0.0,1,74,Semi-Urban,Data Analyst,82760,1 +100238,Female,40,Bachelors,15,98,83,76,90,9.0,0,49,Urban,HR Executive,44240,1 +100239,Female,44,Masters,17,85,97,49,82,6.0,4,99,Semi-Urban,HR Executive,121147,1 +100240,Other,43,Diploma,11,5,94,58,94,7.0,1,33,Semi-Urban,Software Engineer,59498,0 +100241,Female,45,Masters,6,94,35,4,96,4.0,0,37,Semi-Urban,ML Engineer,112521,0 +100242,Male,45,Diploma,10,2,93,85,19,6.0,1,68,Rural,Manager,144354,1 +100243,Female,46,Bachelors,7,69,34,50,22,0.0,1,81,Urban,Manager,33463,0 +100244,Male,53,High School,9,6,35,49,4,2.0,3,38,Urban,Data Analyst,55602,0 +100245,Female,30,High School,10,85,98,15,77,1.0,4,47,Urban,Manager,135122,1 +100246,Male,48,Bachelors,5,98,55,26,57,5.0,2,64,Urban,Software Engineer,81987,1 +100247,Female,49,Bachelors,1,53,63,88,31,5.0,4,36,Semi-Urban,Manager,120848,0 +100248,Female,43,Bachelors,11,35,66,75,0,2.0,4,90,Urban,ML Engineer,113398,1 +100249,Male,28,Masters,5,96,44,40,41,5.0,3,54,Rural,Software Engineer,147587,0 +100250,Female,51,Bachelors,4,74,15,27,60,5.0,1,99,Urban,ML Engineer,149187,0 +100251,Female,54,Bachelors,16,81,35,9,91,5.0,4,51,Rural,Manager,59571,0 +100252,Male,35,Bachelors,10,13,33,73,28,2.0,7,88,Urban,Software Engineer,112934,0 +100253,Male,43,Diploma,8,34,81,42,32,4.0,4,88,Rural,Data Analyst,44095,1 +100254,Male,33,High School,5,36,7,48,2,5.0,7,73,Semi-Urban,ML Engineer,113961,0 +100255,Female,29,High School,11,80,58,68,97,0.0,7,28,Urban,Manager,27074,0 +100256,Male,21,Bachelors,3,44,12,1,68,2.0,1,96,Semi-Urban,Manager,47162,0 +100257,Male,37,Bachelors,7,65,16,0,91,2.0,1,42,Rural,HR Executive,57173,0 +100258,Male,36,Diploma,11,85,3,81,75,7.0,5,22,Urban,Data Analyst,129206,0 +100259,Female,36,Bachelors,19,69,65,68,43,1.0,7,61,Urban,Manager,97831,1 +100260,Female,38,High School,16,11,16,42,90,8.0,0,56,Rural,HR Executive,57228,0 +100261,Female,40,Bachelors,12,7,94,18,79,7.0,5,67,Urban,HR Executive,45135,0 +100262,Female,27,Masters,4,11,1,70,25,8.0,4,72,Urban,HR Executive,138467,0 +100263,Female,49,Bachelors,6,15,75,35,80,3.0,2,41,Rural,ML Engineer,81689,0 +100264,Male,29,High School,19,83,62,26,43,0.0,5,42,Semi-Urban,Data Analyst,126096,0 +100265,Male,34,High School,19,10,15,34,20,7.0,2,99,Urban,HR Executive,132498,0 +100266,Male,54,Bachelors,17,73,96,3,55,6.0,1,13,Semi-Urban,HR Executive,50329,0 +100267,Male,29,Bachelors,14,40,34,95,4,9.0,2,0,Semi-Urban,Software Engineer,129029,0 +100268,Male,58,Bachelors,12,27,72,21,4,4.0,3,64,Urban,HR Executive,31341,0 +100269,Female,42,Bachelors,5,81,3,78,8,5.0,2,50,Urban,HR Executive,26259,0 +100270,Female,24,Diploma,8,68,55,6,98,3.0,1,35,Semi-Urban,Data Analyst,38447,0 +100271,Male,40,High School,1,8,77,70,73,9.0,1,44,Urban,HR Executive,91283,0 +100272,Male,29,Bachelors,7,51,52,68,57,5.0,3,14,Semi-Urban,ML Engineer,132700,0 +100273,Male,55,Diploma,6,96,61,9,64,8.0,6,71,Semi-Urban,HR Executive,50297,1 +100274,Male,41,Diploma,7,68,38,56,30,1.0,4,76,Semi-Urban,Manager,81156,1 +100275,Male,47,Diploma,7,40,98,91,22,1.0,3,52,Urban,ML Engineer,137956,1 +100276,Male,53,Bachelors,11,47,3,33,74,5.0,5,50,Urban,Manager,130886,0 +100277,Male,32,PhD,2,16,69,63,77,7.0,2,82,Rural,ML Engineer,131225,0 +100278,Male,30,Diploma,10,42,59,34,77,9.0,7,37,Semi-Urban,Software Engineer,59754,0 +100279,Female,22,High School,17,22,85,72,57,9.0,6,52,Urban,HR Executive,63573,0 +100280,Male,43,Bachelors,7,1,42,69,66,2.0,7,96,Urban,Software Engineer,99662,0 +100281,Male,43,PhD,14,89,26,14,78,0.0,6,57,Urban,Software Engineer,63466,0 +100282,Male,42,Diploma,10,53,12,68,8,9.0,3,95,Rural,Software Engineer,89876,0 +100283,Male,27,High School,17,15,99,65,47,3.0,1,10,Urban,HR Executive,129409,0 +100284,Female,49,Bachelors,9,99,41,16,57,0.0,6,36,Rural,Manager,42074,0 +100285,Male,26,Masters,19,77,68,42,10,2.0,5,99,Urban,Data Analyst,145066,1 +100286,Male,27,Bachelors,11,23,93,71,40,4.0,6,31,Urban,Manager,79099,0 +100287,Female,35,Diploma,0,91,19,9,44,7.0,2,82,Semi-Urban,Manager,89001,0 +100288,Male,59,Bachelors,13,40,50,85,55,6.0,4,77,Urban,Data Analyst,53605,1 +100289,Male,30,Bachelors,19,54,71,21,53,3.0,7,34,Urban,HR Executive,90250,0 +100290,Female,55,Diploma,0,30,51,22,59,8.0,1,24,Urban,Manager,115398,0 +100291,Other,51,High School,9,97,76,68,18,4.0,1,2,Rural,Manager,94066,1 +100292,Male,33,High School,10,90,88,6,64,3.0,0,17,Urban,HR Executive,137764,0 +100293,Male,58,High School,10,62,48,72,59,8.0,3,96,Semi-Urban,Software Engineer,31062,1 +100294,Male,27,Bachelors,5,65,73,56,93,0.0,2,90,Urban,HR Executive,80981,1 +100295,Male,43,Bachelors,5,13,65,70,56,5.0,3,14,Semi-Urban,Manager,117698,0 +100296,Male,22,High School,19,84,13,86,58,2.0,1,86,Rural,Manager,132927,1 +100297,Female,26,Bachelors,9,0,27,98,94,3.0,1,84,Semi-Urban,HR Executive,75770,0 +100298,Male,59,Masters,11,19,46,63,5,5.0,6,93,Semi-Urban,Software Engineer,147764,0 +100299,Male,51,Bachelors,19,72,22,90,77,3.0,0,32,Semi-Urban,HR Executive,75436,0 +100300,Female,52,Masters,6,42,48,43,0,7.0,6,37,Rural,HR Executive,58727,0 +100301,Male,31,Diploma,6,4,44,62,10,6.0,0,47,Urban,HR Executive,121091,0 +100302,Female,57,High School,1,73,64,47,9,3.0,6,18,Urban,Software Engineer,93684,0 +100303,Female,27,Diploma,19,64,59,47,44,2.0,3,54,Urban,ML Engineer,113498,0 +100304,Male,32,Bachelors,8,84,51,0,49,1.0,3,58,Urban,Software Engineer,31278,0 +100305,Female,28,Bachelors,17,17,45,82,27,2.0,1,1,Rural,ML Engineer,142429,0 +100306,Female,51,Diploma,2,79,64,10,45,1.0,6,38,Semi-Urban,Data Analyst,68834,0 +100307,Female,56,High School,5,59,51,77,69,2.0,4,32,Urban,Data Analyst,103564,0 +100308,Male,31,Bachelors,2,90,11,31,10,5.0,2,23,Urban,HR Executive,40902,0 +100309,Female,33,Masters,9,76,59,48,82,7.0,4,69,Urban,Data Analyst,54842,1 +100310,Female,41,Masters,7,52,21,8,83,0.0,6,24,Urban,Manager,20696,0 +100311,Male,44,Bachelors,4,63,38,65,65,2.0,7,9,Rural,Manager,72458,0 +100312,Female,57,Masters,0,91,21,43,37,6.0,1,60,Rural,ML Engineer,97636,0 +100313,Female,49,Bachelors,18,55,50,73,99,0.0,1,88,Semi-Urban,ML Engineer,136425,1 +100314,Female,41,Bachelors,9,13,36,76,68,5.0,0,14,Semi-Urban,HR Executive,69660,0 +100315,Female,45,High School,10,5,47,60,38,9.0,4,23,Rural,Software Engineer,111425,0 +100316,Female,59,Bachelors,9,92,11,94,69,1.0,0,78,Urban,Data Analyst,26587,1 +100317,Male,49,Masters,3,85,65,30,59,1.0,4,88,Rural,HR Executive,105500,1 +100318,Male,25,Diploma,10,24,95,97,8,4.0,1,46,Urban,Data Analyst,82842,1 +100319,Male,59,Diploma,0,88,68,82,47,4.0,0,36,Urban,Manager,95428,1 +100320,Female,27,Masters,7,17,2,65,90,5.0,3,41,Urban,Data Analyst,124417,0 +100321,Female,32,PhD,0,74,42,20,60,1.0,3,32,Urban,Data Analyst,42355,0 +100322,Male,50,PhD,5,92,73,99,45,5.0,3,28,Urban,Software Engineer,100773,1 +100323,Male,40,Bachelors,4,34,28,50,57,6.0,0,82,Rural,Data Analyst,23433,0 +100324,Female,26,PhD,18,34,50,54,65,2.0,3,55,Urban,Software Engineer,148565,0 +100325,Male,55,Bachelors,16,3,70,6,52,2.0,1,48,Urban,HR Executive,73111,0 +100326,Female,43,PhD,16,25,86,81,28,6.0,3,64,Urban,Software Engineer,96510,1 +100327,Male,31,Diploma,17,32,81,80,59,4.0,4,31,Urban,Manager,91444,0 +100328,Female,44,Diploma,6,86,2,2,75,8.0,7,35,Rural,ML Engineer,105093,0 +100329,Male,40,Masters,18,73,52,17,33,3.0,3,96,Urban,Manager,57900,1 +100330,Male,46,High School,17,29,42,15,92,3.0,6,81,Urban,Manager,149467,0 +100331,Male,50,Bachelors,15,37,66,44,87,4.0,4,91,Semi-Urban,Manager,89623,1 +100332,Female,38,Bachelors,12,25,24,46,65,2.0,0,6,Rural,Software Engineer,112583,0 +100333,Male,44,Bachelors,6,83,0,8,23,3.0,5,10,Urban,HR Executive,26176,0 +100334,Male,38,Bachelors,16,5,80,73,44,5.0,2,18,Rural,ML Engineer,44611,0 +100335,Male,47,Masters,8,44,85,84,82,5.0,3,3,Semi-Urban,HR Executive,38551,0 +100336,Female,22,Diploma,15,35,99,1,71,7.0,3,57,Urban,Data Analyst,133273,0 +100337,Male,36,Diploma,17,7,12,23,79,2.0,7,74,Semi-Urban,Software Engineer,93945,0 +100338,Male,40,Bachelors,7,20,36,76,58,5.0,0,24,Rural,Data Analyst,66485,0 +100339,Male,59,Bachelors,5,7,64,17,33,5.0,1,57,Semi-Urban,Manager,22301,0 +100340,Female,45,Bachelors,15,65,27,62,30,1.0,0,81,Urban,Software Engineer,106628,0 +100341,Other,24,Masters,8,13,3,81,7,2.0,6,26,Rural,ML Engineer,106957,0 +100342,Female,29,Masters,15,11,39,77,91,5.0,7,3,Urban,HR Executive,137784,0 +100343,Female,26,High School,18,90,26,59,42,8.0,6,26,Urban,Software Engineer,149614,0 +100344,Female,36,Bachelors,8,64,13,70,80,7.0,3,25,Semi-Urban,HR Executive,128265,0 +100345,Male,59,Bachelors,11,17,3,29,59,8.0,6,40,Urban,Data Analyst,94524,0 +100346,Female,54,Bachelors,16,72,31,46,18,9.0,2,6,Rural,HR Executive,149329,0 +100347,Male,29,Masters,13,17,40,15,62,6.0,3,40,Semi-Urban,Data Analyst,85434,0 +100348,Male,55,High School,0,10,9,30,56,0.0,0,7,Semi-Urban,Software Engineer,35536,0 +100349,Male,21,Masters,18,42,73,97,2,7.0,1,63,Urban,ML Engineer,92766,1 +100350,Female,49,Diploma,15,7,4,51,22,3.0,5,60,Semi-Urban,Data Analyst,93259,0 +100351,Female,26,High School,5,91,11,89,14,5.0,6,54,Urban,ML Engineer,110208,1 +100352,Male,34,Bachelors,11,79,88,11,27,2.0,4,20,Urban,Manager,41209,0 +100353,Female,36,Masters,2,72,28,12,2,2.0,3,66,Rural,Software Engineer,126376,0 +100354,Male,45,Bachelors,16,98,38,66,35,5.0,5,6,Urban,Data Analyst,75455,0 +100355,Other,23,Bachelors,2,54,39,69,56,9.0,0,83,Urban,Data Analyst,107635,1 +100356,Other,37,Bachelors,12,3,11,12,51,0.0,4,44,Semi-Urban,HR Executive,37320,0 +100357,Female,45,PhD,5,44,65,27,86,4.0,4,8,Semi-Urban,Manager,139444,0 +100358,Female,44,Diploma,15,89,84,74,63,1.0,2,35,Urban,HR Executive,86304,1 +100359,Other,45,Bachelors,13,97,55,67,47,5.0,5,10,Rural,ML Engineer,96326,0 +100360,Male,27,High School,15,67,19,83,94,4.0,1,40,Urban,Manager,21650,0 +100361,Female,39,Bachelors,3,11,22,99,26,0.0,1,6,Rural,ML Engineer,73317,0 +100362,Male,52,Diploma,9,22,16,51,84,9.0,3,60,Urban,Software Engineer,26512,0 +100363,Male,52,High School,10,70,78,54,60,3.0,0,9,Urban,Data Analyst,133155,0 +100364,Male,35,PhD,12,89,53,27,56,3.0,7,42,Urban,ML Engineer,64194,0 +100365,Female,49,Bachelors,4,48,43,12,24,8.0,1,66,Urban,ML Engineer,139507,0 +100366,Male,56,PhD,0,51,93,68,56,2.0,0,9,Semi-Urban,HR Executive,108499,0 +100367,Male,33,Masters,16,44,65,94,12,3.0,7,34,Urban,HR Executive,111503,1 +100368,Male,37,Masters,11,73,82,57,43,6.0,0,24,Urban,Data Analyst,102143,1 +100369,Male,21,Bachelors,9,46,42,54,39,2.0,2,99,Semi-Urban,HR Executive,26150,1 +100370,Female,29,Bachelors,8,37,55,82,46,5.0,4,65,Semi-Urban,ML Engineer,113265,0 +100371,Male,54,Bachelors,12,22,93,5,79,7.0,1,91,Urban,Data Analyst,33137,0 +100372,Female,34,Bachelors,3,26,52,63,93,1.0,3,14,Semi-Urban,HR Executive,124130,0 +100373,Male,52,Diploma,16,29,62,40,86,6.0,4,33,Urban,Data Analyst,91845,0 +100374,Male,47,Masters,17,23,8,89,47,9.0,0,69,Semi-Urban,HR Executive,118633,0 +100375,Female,48,Bachelors,12,87,21,50,12,4.0,3,80,Urban,Data Analyst,90972,0 +100376,Male,52,High School,0,48,84,79,4,7.0,3,3,Semi-Urban,Manager,33579,0 +100377,Female,23,Masters,15,61,45,18,64,0.0,1,11,Urban,Software Engineer,96061,0 +100378,Male,49,Bachelors,13,85,37,97,20,3.0,4,98,Urban,ML Engineer,33641,1 +100379,Female,51,Diploma,2,46,55,76,5,7.0,0,61,Semi-Urban,Software Engineer,30123,0 +100380,Male,47,PhD,0,24,24,87,80,8.0,7,14,Urban,Manager,42429,0 +100381,Male,21,Bachelors,7,26,77,43,56,0.0,2,61,Urban,HR Executive,96241,0 +100382,Other,21,Bachelors,1,10,69,4,69,5.0,4,81,Urban,Software Engineer,70200,0 +100383,Male,53,Bachelors,14,16,73,14,80,3.0,3,3,Semi-Urban,Manager,41569,0 +100384,Male,54,Diploma,7,79,36,49,19,3.0,5,69,Semi-Urban,Software Engineer,80094,0 +100385,Male,52,Bachelors,9,13,79,55,70,1.0,7,35,Semi-Urban,Manager,66413,0 +100386,Male,44,Bachelors,4,49,86,16,21,9.0,3,44,Urban,ML Engineer,128759,0 +100387,Male,44,Bachelors,5,38,45,90,24,1.0,4,68,Rural,Manager,81417,1 +100388,Female,44,High School,8,92,40,3,91,5.0,4,46,Semi-Urban,Software Engineer,141457,0 +100389,Male,47,Masters,9,8,56,76,66,5.0,3,46,Urban,ML Engineer,34812,0 +100390,Male,33,Bachelors,9,58,16,70,57,9.0,3,27,Urban,ML Engineer,67699,0 +100391,Male,29,High School,18,94,18,98,95,2.0,4,74,Rural,Data Analyst,84884,1 +100392,Male,58,Bachelors,1,69,37,54,47,8.0,2,37,Semi-Urban,Software Engineer,50031,0 +100393,Male,24,Diploma,7,45,18,0,27,8.0,1,98,Urban,Software Engineer,36180,0 +100394,Male,24,Masters,3,21,66,3,78,7.0,7,97,Urban,Software Engineer,123415,0 +100395,Male,47,Diploma,1,38,53,65,47,4.0,1,80,Semi-Urban,HR Executive,143754,1 +100396,Female,55,Masters,9,5,41,12,3,2.0,2,72,Urban,Manager,105955,0 +100397,Male,34,Bachelors,12,31,48,12,82,1.0,1,94,Urban,Manager,31403,0 +100398,Male,37,Masters,17,66,98,32,70,6.0,3,68,Rural,Data Analyst,119985,1 +100399,Male,46,Bachelors,6,60,60,27,17,1.0,5,31,Semi-Urban,ML Engineer,24614,0 +100400,Male,53,Bachelors,18,9,1,14,56,7.0,6,8,Urban,Software Engineer,112807,0 +100401,Male,55,Diploma,10,86,56,5,95,5.0,6,84,Rural,Data Analyst,36964,0 +100402,Female,49,Bachelors,11,52,63,60,12,1.0,0,8,Urban,Data Analyst,91141,0 +100403,Female,58,Bachelors,3,78,24,43,93,6.0,1,50,Semi-Urban,ML Engineer,50461,0 +100404,Female,43,Bachelors,13,92,16,55,46,1.0,1,10,Rural,ML Engineer,83305,0 +100405,Male,49,Bachelors,1,62,90,69,3,1.0,1,7,Semi-Urban,HR Executive,47743,0 +100406,Male,40,Diploma,1,44,87,84,47,4.0,4,28,Urban,Manager,121439,1 +100407,Female,51,Masters,9,97,51,46,65,2.0,2,95,Urban,HR Executive,66005,1 +100408,Female,35,Diploma,1,71,64,92,40,5.0,0,65,Semi-Urban,Software Engineer,96968,1 +100409,Female,32,Masters,18,42,76,16,16,2.0,1,76,Semi-Urban,Software Engineer,22215,0 +100410,Male,37,Bachelors,16,32,91,35,25,0.0,4,71,Urban,HR Executive,96856,0 +100411,Female,51,Masters,14,59,64,53,24,8.0,7,24,Urban,Manager,23164,0 +100412,Male,49,Diploma,17,11,70,56,34,0.0,4,4,Urban,Data Analyst,139284,0 +100413,Female,35,Bachelors,6,23,92,61,31,3.0,4,96,Semi-Urban,Manager,122238,1 +100414,Male,50,Bachelors,16,37,63,54,83,1.0,7,52,Semi-Urban,Data Analyst,83246,0 +100415,Male,53,High School,8,92,38,49,16,9.0,5,68,Urban,Software Engineer,124267,1 +100416,Female,32,Bachelors,8,70,35,27,80,4.0,1,69,Urban,Data Analyst,104236,0 +100417,Male,57,Bachelors,10,2,93,1,67,7.0,7,46,Urban,Data Analyst,56660,0 +100418,Female,43,Bachelors,18,67,11,10,87,3.0,1,11,Semi-Urban,Data Analyst,124709,0 +100419,Male,43,Masters,18,39,54,22,6,1.0,0,98,Rural,HR Executive,113252,0 +100420,Male,50,Masters,10,89,96,4,6,3.0,3,17,Urban,HR Executive,111377,0 +100421,Male,32,Bachelors,2,73,57,36,89,7.0,7,4,Urban,Software Engineer,68063,0 +100422,Male,43,Masters,17,99,18,12,34,3.0,3,89,Urban,Data Analyst,108877,0 +100423,Female,58,Diploma,6,54,47,8,80,9.0,5,48,Urban,HR Executive,115068,0 +100424,Male,39,Bachelors,6,23,12,22,6,6.0,4,39,Semi-Urban,ML Engineer,100800,0 +100425,Male,21,Diploma,15,43,57,90,72,2.0,4,63,Urban,HR Executive,114135,1 +100426,Female,49,Masters,2,18,70,30,95,1.0,1,96,Urban,Software Engineer,49285,0 +100427,Male,56,Masters,0,96,20,5,29,7.0,1,23,Rural,Data Analyst,91686,0 +100428,Male,31,Masters,18,51,87,33,20,4.0,2,68,Urban,ML Engineer,52289,1 +100429,Female,32,PhD,1,86,93,97,9,3.0,6,30,Urban,Data Analyst,131453,1 +100430,Male,42,Diploma,7,56,48,4,17,5.0,6,55,Urban,HR Executive,31443,0 +100431,Female,52,PhD,7,56,71,60,81,8.0,0,10,Semi-Urban,ML Engineer,38612,0 +100432,Male,41,Bachelors,17,11,92,27,57,5.0,4,33,Semi-Urban,Data Analyst,143927,0 +100433,Other,41,High School,14,90,39,81,18,5.0,7,17,Semi-Urban,ML Engineer,118328,0 +100434,Female,32,Bachelors,16,18,17,92,76,6.0,1,35,Rural,Software Engineer,78860,0 +100435,Female,52,Bachelors,17,7,67,67,93,1.0,3,33,Urban,Data Analyst,139570,0 +100436,Male,36,Masters,8,36,73,96,10,7.0,0,82,Semi-Urban,Manager,138671,1 +100437,Female,40,Bachelors,14,66,73,76,33,4.0,1,71,Urban,Software Engineer,130983,1 +100438,Female,24,Bachelors,12,82,49,1,99,0.0,0,63,Semi-Urban,HR Executive,137240,0 +100439,Male,53,Bachelors,10,39,26,37,90,8.0,3,79,Urban,ML Engineer,144789,0 +100440,Male,27,Bachelors,10,55,1,44,98,0.0,5,78,Urban,HR Executive,32673,0 +100441,Male,59,Bachelors,0,95,29,7,52,8.0,1,84,Semi-Urban,HR Executive,79969,0 +100442,Male,52,Bachelors,5,69,54,34,17,4.0,2,21,Rural,Software Engineer,22087,0 +100443,Male,43,Bachelors,0,2,68,47,48,4.0,5,53,Urban,Software Engineer,75198,0 +100444,Female,57,Bachelors,13,42,40,4,45,2.0,0,8,Urban,Data Analyst,119960,0 +100445,Male,34,Bachelors,16,39,62,89,78,9.0,6,88,Urban,Data Analyst,64181,1 +100446,Male,51,Bachelors,3,40,14,72,46,2.0,1,2,Urban,HR Executive,126874,0 +100447,Female,36,Diploma,2,74,52,57,30,3.0,1,12,Rural,Software Engineer,49499,0 +100448,Male,57,Masters,10,56,3,79,99,0.0,4,79,Semi-Urban,ML Engineer,86316,0 +100449,Female,44,Masters,5,23,38,29,35,5.0,1,67,Urban,Software Engineer,50558,0 +100450,Other,34,Diploma,2,36,60,35,31,5.0,1,81,Semi-Urban,ML Engineer,30802,0 +100451,Female,58,Diploma,10,36,91,81,54,1.0,5,73,Urban,HR Executive,47164,1 +100452,Male,34,Masters,0,54,83,96,45,3.0,7,79,Urban,ML Engineer,77279,1 +100453,Female,47,Masters,1,9,92,72,32,7.0,2,19,Semi-Urban,Software Engineer,41654,0 +100454,Male,55,Masters,13,37,12,2,88,0.0,2,90,Urban,Data Analyst,44658,0 +100455,Male,37,Masters,3,6,43,71,62,9.0,0,71,Urban,Manager,84630,0 +100456,Male,31,Bachelors,15,38,74,1,74,2.0,0,75,Urban,Data Analyst,27539,0 +100457,Male,59,Masters,0,86,92,32,70,0.0,4,30,Semi-Urban,Software Engineer,81498,1 +100458,Male,26,High School,11,20,77,70,59,4.0,0,62,Semi-Urban,ML Engineer,84663,0 +100459,Female,30,Bachelors,8,63,1,57,22,2.0,3,31,Urban,Data Analyst,129222,0 +100460,Male,45,PhD,1,62,1,7,42,8.0,7,4,Rural,ML Engineer,44325,0 +100461,Male,24,Diploma,16,14,89,48,4,8.0,2,2,Urban,Data Analyst,93117,0 +100462,Female,37,Bachelors,11,32,30,50,81,3.0,5,71,Semi-Urban,Manager,59127,0 +100463,Male,44,Bachelors,4,5,28,97,47,8.0,1,86,Semi-Urban,ML Engineer,50103,0 +100464,Female,39,Bachelors,1,32,61,71,23,3.0,6,91,Urban,Software Engineer,70061,1 +100465,Female,53,Bachelors,16,73,90,50,13,2.0,1,63,Urban,Software Engineer,20589,1 +100466,Male,26,Bachelors,8,56,46,46,0,0.0,2,87,Semi-Urban,ML Engineer,52290,1 +100467,Male,27,Masters,9,53,5,6,98,0.0,2,72,Rural,Software Engineer,75991,0 +100468,Male,34,High School,16,86,40,68,79,8.0,6,51,Urban,Manager,78527,1 +100469,Male,27,Bachelors,6,46,46,36,91,3.0,6,81,Urban,Manager,50701,0 +100470,Male,59,Bachelors,7,97,91,97,26,3.0,3,57,Semi-Urban,ML Engineer,86765,1 +100471,Male,56,PhD,19,87,39,48,66,7.0,6,71,Urban,Data Analyst,119882,1 +100472,Female,42,Diploma,3,94,42,14,20,9.0,4,85,Urban,Manager,86228,0 +100473,Male,41,Bachelors,16,87,10,15,23,5.0,3,73,Semi-Urban,Data Analyst,104577,0 +100474,Male,49,Bachelors,6,66,64,12,94,7.0,3,63,Semi-Urban,Data Analyst,120175,0 +100475,Female,54,Bachelors,3,77,82,87,25,7.0,6,95,Urban,Software Engineer,101690,1 +100476,Male,37,PhD,16,31,49,84,91,9.0,2,17,Urban,Manager,48293,0 +100477,Male,39,Masters,18,47,9,52,42,3.0,2,89,Urban,ML Engineer,139339,0 +100478,Male,27,Masters,12,26,9,82,80,4.0,1,7,Rural,HR Executive,30973,0 +100479,Male,46,Bachelors,0,10,99,45,33,3.0,5,58,Rural,Manager,45184,0 +100480,Female,23,Bachelors,8,63,48,66,40,3.0,2,8,Rural,HR Executive,35954,0 +100481,Male,52,Bachelors,19,35,24,24,40,6.0,7,53,Urban,HR Executive,64489,0 +100482,Male,44,Masters,5,53,95,8,79,9.0,2,35,Rural,Software Engineer,85806,0 +100483,Female,30,Diploma,19,52,81,32,88,8.0,1,19,Urban,Data Analyst,47376,0 +100484,Male,26,Diploma,4,48,0,12,10,0.0,4,24,Semi-Urban,HR Executive,146152,0 +100485,Other,29,Diploma,8,60,76,44,79,6.0,3,82,Urban,Data Analyst,83154,1 +100486,Female,52,High School,17,83,61,24,40,6.0,3,87,Semi-Urban,HR Executive,98206,1 +100487,Female,28,Diploma,18,91,53,21,4,5.0,1,97,Urban,Manager,90100,1 +100488,Female,59,High School,3,4,12,43,82,3.0,2,22,Semi-Urban,Data Analyst,46400,0 +100489,Other,57,Bachelors,6,4,65,56,92,0.0,7,76,Urban,ML Engineer,125495,0 +100490,Male,26,High School,18,73,66,58,12,3.0,2,47,Semi-Urban,Data Analyst,117271,1 +100491,Female,32,Masters,12,4,68,46,20,1.0,7,9,Urban,Data Analyst,132829,0 +100492,Male,54,Bachelors,6,57,46,7,90,0.0,1,85,Urban,ML Engineer,108227,0 +100493,Female,26,Bachelors,19,45,98,25,89,1.0,5,50,Urban,ML Engineer,116199,0 +100494,Male,37,Diploma,3,53,68,87,4,9.0,4,86,Urban,Software Engineer,97152,1 +100495,Female,24,High School,19,79,76,49,82,5.0,4,17,Urban,Manager,81979,0 +100496,Male,25,PhD,3,18,53,60,37,7.0,6,25,Semi-Urban,ML Engineer,45659,0 +100497,Female,36,Bachelors,19,16,4,69,70,2.0,7,66,Urban,Software Engineer,105478,0 +100498,Male,55,Bachelors,17,6,94,61,94,4.0,3,52,Urban,Data Analyst,149396,0 +100499,Female,37,Diploma,2,13,47,16,30,4.0,0,21,Urban,ML Engineer,86024,0 +100500,Female,55,Bachelors,15,16,66,39,12,2.0,5,52,Semi-Urban,ML Engineer,85460,0 +100501,Other,41,High School,2,27,62,30,34,8.0,7,92,Urban,HR Executive,69308,0 +100502,Male,29,Masters,13,77,41,65,22,3.0,7,36,Urban,Data Analyst,115373,0 +100503,Male,54,Bachelors,7,42,27,32,72,4.0,2,15,Semi-Urban,Manager,106120,0 +100504,Male,29,Bachelors,7,69,47,71,71,9.0,0,34,Urban,Manager,133550,0 +100505,Male,43,Bachelors,16,49,41,83,94,2.0,7,40,Urban,Data Analyst,56021,0 +100506,Male,28,Bachelors,19,27,32,62,41,6.0,2,84,Urban,Software Engineer,104105,0 +100507,Male,54,Bachelors,0,9,16,55,72,7.0,5,56,Urban,Data Analyst,109911,0 +100508,Female,34,PhD,0,15,91,41,70,6.0,3,14,Semi-Urban,HR Executive,71023,0 +100509,Male,42,High School,1,46,79,50,24,5.0,5,10,Rural,HR Executive,79956,0 +100510,Male,55,Bachelors,18,21,15,56,19,7.0,1,83,Urban,Software Engineer,102762,0 +100511,Female,24,Bachelors,9,89,62,46,75,8.0,4,92,Semi-Urban,Software Engineer,51248,1 +100512,Male,31,Bachelors,6,85,18,34,67,9.0,1,69,Rural,HR Executive,33456,0 +100513,Male,21,Bachelors,15,9,22,63,24,1.0,7,6,Semi-Urban,ML Engineer,34833,0 +100514,Male,41,Bachelors,13,96,26,50,25,4.0,0,78,Urban,ML Engineer,108769,1 +100515,Female,35,Bachelors,7,41,85,75,1,9.0,5,88,Rural,Manager,129367,1 +100516,Female,40,Bachelors,11,28,91,88,4,9.0,1,87,Urban,ML Engineer,104828,1 +100517,Female,50,Diploma,3,28,46,68,19,2.0,4,47,Rural,ML Engineer,121246,0 +100518,Female,45,Bachelors,17,67,0,23,53,0.0,2,15,Urban,HR Executive,62629,0 +100519,Male,41,Bachelors,9,44,3,48,13,6.0,7,87,Semi-Urban,Manager,83161,0 +100520,Male,22,Bachelors,12,81,92,50,22,3.0,1,44,Semi-Urban,ML Engineer,139279,1 +100521,Female,41,Bachelors,6,92,64,39,37,7.0,2,15,Urban,Data Analyst,68568,0 +100522,Female,30,Masters,3,69,90,73,26,1.0,1,10,Rural,Manager,33880,1 +100523,Female,58,Diploma,0,61,93,18,92,4.0,0,25,Rural,Manager,39219,0 +100524,Male,27,Masters,11,42,27,77,49,3.0,5,8,Urban,Data Analyst,121431,0 +100525,Male,47,PhD,14,94,52,61,66,1.0,5,26,Rural,HR Executive,82897,0 +100526,Male,24,High School,13,6,37,79,25,8.0,6,9,Urban,HR Executive,52515,0 +100527,Male,34,Diploma,2,58,55,24,18,1.0,2,29,Urban,Software Engineer,83868,0 +100528,Male,51,Diploma,0,39,97,53,74,5.0,1,70,Rural,HR Executive,40291,1 +100529,Male,53,Masters,17,26,56,71,46,1.0,5,67,Urban,ML Engineer,62895,0 +100530,Female,53,Masters,11,29,19,37,20,4.0,7,97,Rural,ML Engineer,62271,0 +100531,Female,43,Masters,14,94,4,95,52,7.0,0,65,Urban,Manager,144890,1 +100532,Female,57,Masters,4,56,10,71,82,2.0,5,44,Rural,HR Executive,67642,0 +100533,Male,29,Diploma,11,63,46,42,1,1.0,2,4,Semi-Urban,Data Analyst,143511,0 +100534,Male,33,High School,0,26,10,3,23,0.0,5,52,Rural,Data Analyst,126722,0 +100535,Female,27,Diploma,11,47,33,30,39,4.0,2,38,Rural,HR Executive,51207,0 +100536,Male,31,PhD,2,16,61,68,89,6.0,6,60,Semi-Urban,Manager,84460,0 +100537,Male,29,PhD,19,83,13,66,68,7.0,6,23,Semi-Urban,HR Executive,57480,0 +100538,Male,55,Bachelors,10,91,14,55,85,5.0,2,65,Urban,HR Executive,99476,0 +100539,Female,39,High School,4,79,39,89,3,0.0,0,57,Semi-Urban,Software Engineer,50281,1 +100540,Female,26,Bachelors,0,97,15,57,2,1.0,5,20,Semi-Urban,Software Engineer,76246,0 +100541,Female,43,Diploma,18,7,17,60,96,4.0,1,23,Urban,Data Analyst,95183,0 +100542,Male,24,Masters,14,95,77,59,58,7.0,2,10,Urban,Data Analyst,75780,1 +100543,Male,30,Diploma,4,90,95,34,25,8.0,6,47,Urban,Data Analyst,40983,1 +100544,Female,29,Diploma,16,13,50,80,87,1.0,7,22,Semi-Urban,HR Executive,138134,0 +100545,Female,30,Bachelors,14,26,35,42,18,9.0,3,6,Semi-Urban,Manager,91474,0 +100546,Female,36,High School,14,27,84,88,99,1.0,1,41,Rural,ML Engineer,120776,0 +100547,Female,22,Masters,19,29,71,85,27,0.0,6,88,Urban,Manager,103585,1 +100548,Female,42,Bachelors,15,97,40,64,61,3.0,2,16,Urban,Manager,87705,0 +100549,Male,47,Diploma,13,84,3,27,46,2.0,5,41,Semi-Urban,HR Executive,32652,0 +100550,Male,21,Diploma,9,8,47,55,21,5.0,7,83,Urban,HR Executive,104927,0 +100551,Male,49,High School,16,10,55,98,40,2.0,3,52,Semi-Urban,Data Analyst,39369,0 +100552,Female,52,Bachelors,19,15,2,99,40,7.0,4,82,Semi-Urban,Manager,35792,0 +100553,Male,49,Masters,8,20,1,35,16,8.0,2,7,Urban,Manager,95120,0 +100554,Male,54,Diploma,17,86,23,74,51,0.0,5,20,Urban,Data Analyst,140429,0 +100555,Female,56,Masters,14,37,64,24,35,0.0,4,64,Semi-Urban,ML Engineer,61171,0 +100556,Other,51,Bachelors,13,52,88,74,26,3.0,6,80,Urban,Manager,80178,1 +100557,Male,36,Masters,17,93,78,53,13,4.0,4,84,Urban,ML Engineer,48923,1 +100558,Female,54,Bachelors,18,65,83,14,53,7.0,6,30,Semi-Urban,HR Executive,72340,0 +100559,Other,48,Bachelors,7,12,4,41,99,6.0,0,38,Urban,HR Executive,104102,0 +100560,Male,32,Diploma,9,86,97,26,19,6.0,2,15,Semi-Urban,ML Engineer,60300,0 +100561,Male,34,Diploma,5,84,87,71,39,0.0,5,98,Urban,Software Engineer,103908,1 +100562,Male,55,Diploma,10,58,68,32,52,0.0,1,18,Urban,Data Analyst,57286,0 +100563,Female,45,Bachelors,7,50,19,85,8,7.0,1,22,Rural,Data Analyst,25117,0 +100564,Male,21,Bachelors,12,83,26,2,1,3.0,0,89,Semi-Urban,HR Executive,81112,0 +100565,Female,23,Diploma,1,18,2,95,38,5.0,4,30,Urban,Software Engineer,128571,0 +100566,Male,34,Diploma,14,96,43,92,69,1.0,2,4,Semi-Urban,HR Executive,70330,1 +100567,Female,39,High School,15,32,28,30,53,3.0,3,68,Semi-Urban,Data Analyst,53767,0 +100568,Female,24,Masters,15,37,76,41,84,1.0,2,45,Rural,HR Executive,35630,0 +100569,Female,45,High School,15,25,6,25,41,0.0,4,31,Rural,ML Engineer,119834,0 +100570,Male,44,High School,7,84,37,82,38,1.0,0,23,Semi-Urban,HR Executive,113861,0 +100571,Female,51,High School,11,25,85,63,97,9.0,5,73,Urban,ML Engineer,96925,1 +100572,Male,45,Bachelors,17,3,26,44,80,3.0,2,48,Urban,Manager,46576,0 +100573,Female,46,Bachelors,0,3,95,55,30,8.0,0,90,Urban,ML Engineer,61261,1 +100574,Male,30,Bachelors,2,68,29,82,32,1.0,0,10,Urban,Manager,98311,0 +100575,Female,37,Bachelors,4,78,98,36,33,2.0,6,13,Rural,ML Engineer,31009,0 +100576,Male,26,Bachelors,19,87,87,86,5,8.0,0,46,Rural,HR Executive,71425,1 +100577,Male,22,Masters,3,24,39,59,80,7.0,5,97,Semi-Urban,ML Engineer,93467,0 +100578,Male,47,High School,13,94,4,98,90,4.0,5,71,Semi-Urban,Software Engineer,63985,1 +100579,Male,33,Bachelors,5,65,25,26,96,1.0,1,32,Urban,ML Engineer,81362,0 +100580,Male,30,Masters,10,35,95,20,78,8.0,2,94,Semi-Urban,Software Engineer,117123,1 +100581,Female,23,Diploma,5,29,40,99,12,0.0,3,48,Urban,ML Engineer,131009,0 +100582,Male,52,Masters,8,81,15,4,98,1.0,7,64,Urban,Manager,24627,0 +100583,Male,47,High School,12,44,30,81,16,2.0,4,95,Urban,Software Engineer,142852,1 +100584,Male,32,Bachelors,12,59,44,30,54,6.0,4,69,Urban,Software Engineer,106162,0 +100585,Male,45,Masters,2,87,85,17,50,3.0,2,40,Rural,Data Analyst,138749,0 +100586,Female,52,Bachelors,15,84,46,43,6,6.0,2,11,Semi-Urban,Software Engineer,101153,0 +100587,Male,33,PhD,1,60,79,30,33,0.0,6,72,Urban,Data Analyst,75002,1 +100588,Male,50,Bachelors,18,28,34,85,60,8.0,4,19,Urban,Data Analyst,124931,0 +100589,Male,23,High School,4,34,60,7,35,4.0,4,67,Rural,Manager,26689,0 +100590,Male,34,Bachelors,1,16,69,13,13,5.0,5,94,Urban,HR Executive,89609,0 +100591,Male,32,Diploma,18,39,95,86,75,9.0,1,22,Urban,HR Executive,86369,1 +100592,Male,35,Diploma,16,51,2,74,51,3.0,3,77,Semi-Urban,ML Engineer,125554,0 +100593,Male,52,Bachelors,10,71,32,29,98,0.0,4,37,Rural,Software Engineer,111966,0 +100594,Male,43,Bachelors,12,12,54,56,19,0.0,5,91,Urban,Manager,34610,0 +100595,Female,55,Bachelors,18,35,3,25,6,1.0,5,66,Urban,ML Engineer,78998,0 +100596,Female,42,Bachelors,5,15,97,12,76,9.0,6,39,Semi-Urban,Data Analyst,22534,0 +100597,Female,31,Bachelors,1,58,97,91,38,5.0,5,51,Urban,Software Engineer,99972,1 +100598,Female,21,Bachelors,12,14,90,95,19,7.0,6,49,Urban,Software Engineer,47344,1 +100599,Male,52,Masters,14,66,30,88,25,0.0,2,89,Rural,Software Engineer,110842,1 +100600,Male,50,Bachelors,1,38,64,90,20,6.0,1,84,Urban,Manager,111610,1 +100601,Male,54,Masters,8,67,85,3,59,0.0,4,8,Urban,ML Engineer,77784,0 +100602,Male,57,Masters,0,92,66,96,92,6.0,2,12,Urban,ML Engineer,24097,1 +100603,Male,24,Diploma,18,69,35,39,63,7.0,2,43,Semi-Urban,Manager,131235,0 +100604,Other,24,Diploma,16,18,54,75,35,5.0,2,37,Urban,Manager,54510,0 +100605,Female,46,Masters,9,58,10,21,94,3.0,4,85,Rural,HR Executive,106045,0 +100606,Male,29,Masters,6,41,83,3,89,1.0,3,64,Urban,Manager,87543,0 +100607,Male,24,Masters,16,11,49,37,59,5.0,2,57,Urban,Manager,28080,0 +100608,Male,44,Bachelors,3,15,75,36,19,8.0,3,80,Urban,Data Analyst,129509,0 +100609,Male,51,Masters,12,74,60,8,84,0.0,7,27,Urban,Software Engineer,89757,0 +100610,Male,32,Bachelors,5,65,89,47,99,9.0,5,74,Urban,Data Analyst,85515,1 +100611,Female,28,Diploma,6,53,1,73,8,3.0,1,17,Urban,Software Engineer,119813,0 +100612,Male,45,Bachelors,15,93,52,49,21,7.0,6,98,Urban,Software Engineer,65562,1 +100613,Male,23,Bachelors,12,18,89,82,46,2.0,5,78,Urban,ML Engineer,24786,1 +100614,Male,26,Bachelors,9,21,87,32,48,6.0,6,86,Urban,ML Engineer,61730,0 +100615,Male,55,Masters,9,41,60,17,69,0.0,0,17,Rural,Software Engineer,107381,0 +100616,Male,42,Masters,13,73,10,7,71,4.0,2,32,Urban,Data Analyst,111345,0 +100617,Male,27,High School,1,39,66,37,9,9.0,1,90,Semi-Urban,Data Analyst,141243,0 +100618,Male,56,Masters,18,17,13,19,83,3.0,2,37,Urban,Software Engineer,116714,0 +100619,Male,53,Bachelors,4,27,69,16,84,3.0,5,59,Urban,ML Engineer,146078,0 +100620,Male,51,Masters,16,31,31,26,56,9.0,7,60,Urban,Manager,90312,0 +100621,Male,56,Bachelors,1,57,65,68,22,8.0,6,32,Urban,HR Executive,87711,0 +100622,Male,46,Bachelors,4,16,87,40,38,7.0,6,86,Urban,HR Executive,89053,0 +100623,Male,57,Bachelors,12,64,81,89,61,7.0,5,51,Urban,ML Engineer,79274,1 +100624,Male,38,Diploma,8,82,22,67,25,5.0,2,75,Urban,Manager,111531,1 +100625,Female,52,Diploma,8,8,26,61,96,7.0,3,45,Semi-Urban,Data Analyst,115874,0 +100626,Male,31,High School,0,52,75,92,71,5.0,3,62,Semi-Urban,Software Engineer,81207,1 +100627,Male,47,Bachelors,18,58,79,79,84,8.0,4,45,Urban,Manager,54831,1 +100628,Male,35,High School,11,94,81,96,78,9.0,7,86,Urban,Data Analyst,114195,1 +100629,Male,56,Bachelors,9,5,97,39,19,9.0,2,36,Semi-Urban,Software Engineer,83134,0 +100630,Female,54,High School,17,37,49,26,66,4.0,7,66,Urban,Software Engineer,46695,0 +100631,Female,59,Bachelors,7,94,83,0,6,8.0,4,79,Semi-Urban,ML Engineer,45969,1 +100632,Male,49,Diploma,12,92,12,90,1,8.0,0,69,Rural,Software Engineer,27591,1 +100633,Female,44,High School,9,47,84,78,17,6.0,3,37,Semi-Urban,ML Engineer,74578,1 +100634,Female,24,Bachelors,0,98,64,44,13,6.0,2,26,Urban,Data Analyst,142554,0 +100635,Female,48,Diploma,14,96,66,78,22,5.0,7,22,Rural,Manager,40155,1 +100636,Male,46,Masters,10,30,57,27,66,1.0,6,60,Urban,Data Analyst,113229,0 +100637,Female,39,Bachelors,5,47,27,85,30,4.0,6,59,Rural,HR Executive,78773,0 +100638,Male,46,Diploma,10,5,23,51,72,2.0,5,84,Urban,Software Engineer,107385,0 +100639,Other,26,Bachelors,4,72,68,25,34,2.0,2,45,Urban,Data Analyst,26971,0 +100640,Female,55,High School,14,3,31,7,30,7.0,7,65,Urban,Software Engineer,124883,0 +100641,Male,38,Bachelors,1,87,25,80,43,8.0,0,98,Semi-Urban,HR Executive,25870,1 +100642,Female,37,Bachelors,19,44,88,71,23,8.0,6,96,Urban,ML Engineer,113975,1 +100643,Other,46,Masters,0,42,27,61,90,8.0,1,66,Semi-Urban,Software Engineer,57157,0 +100644,Male,51,High School,13,63,58,13,93,5.0,0,2,Semi-Urban,Software Engineer,42245,0 +100645,Male,45,Diploma,16,42,84,51,89,8.0,6,29,Semi-Urban,Manager,67340,0 +100646,Other,26,Bachelors,5,8,33,87,9,3.0,3,61,Urban,ML Engineer,72331,0 +100647,Male,27,High School,17,53,75,87,62,7.0,0,98,Semi-Urban,HR Executive,25631,1 +100648,Female,32,Masters,19,34,70,67,42,1.0,4,21,Semi-Urban,Software Engineer,85382,0 +100649,Male,32,Masters,7,5,83,63,13,7.0,1,55,Semi-Urban,Software Engineer,49624,0 +100650,Male,47,Diploma,3,18,16,11,58,9.0,2,35,Urban,Software Engineer,65447,0 +100651,Male,28,High School,18,98,54,14,79,2.0,4,99,Urban,Manager,141185,1 +100652,Female,52,Bachelors,11,26,22,0,84,5.0,1,78,Urban,Manager,30703,0 +100653,Male,31,Masters,3,79,95,86,74,3.0,3,91,Urban,Manager,26596,1 +100654,Male,41,Diploma,4,27,63,73,62,4.0,0,6,Urban,ML Engineer,61268,0 +100655,Female,51,Bachelors,19,99,12,51,21,8.0,0,98,Urban,Manager,70065,1 +100656,Male,38,PhD,19,88,41,71,99,7.0,6,89,Urban,Manager,24994,1 +100657,Other,58,High School,16,1,55,72,24,5.0,3,29,Urban,Data Analyst,75417,0 +100658,Male,36,Bachelors,18,93,52,42,80,8.0,0,22,Urban,Software Engineer,55640,0 +100659,Female,56,Diploma,3,93,73,76,95,7.0,7,34,Semi-Urban,ML Engineer,42981,1 +100660,Male,55,Diploma,3,71,84,42,92,4.0,3,57,Urban,ML Engineer,55675,1 +100661,Male,47,High School,16,36,28,79,24,1.0,6,52,Semi-Urban,Software Engineer,79184,0 +100662,Female,52,Masters,15,5,81,10,24,7.0,5,86,Semi-Urban,ML Engineer,36717,0 +100663,Male,52,High School,17,87,92,88,64,9.0,7,85,Urban,Manager,119273,1 +100664,Male,42,Diploma,8,2,65,69,62,4.0,0,0,Rural,Data Analyst,58698,0 +100665,Male,46,Masters,2,42,4,72,19,3.0,5,88,Semi-Urban,Manager,43084,0 +100666,Male,47,Masters,9,43,46,96,36,7.0,3,0,Rural,Data Analyst,52874,0 +100667,Male,30,Diploma,2,25,22,90,26,3.0,5,18,Urban,Data Analyst,87570,0 +100668,Other,25,Bachelors,5,54,42,63,51,7.0,6,84,Urban,Software Engineer,26024,1 +100669,Male,51,High School,8,32,4,14,42,4.0,2,69,Urban,HR Executive,149853,0 +100670,Female,26,Masters,2,66,18,8,70,4.0,7,4,Urban,Software Engineer,125055,0 +100671,Male,25,Bachelors,8,81,30,65,11,3.0,4,90,Urban,Software Engineer,149995,1 +100672,Other,59,Bachelors,7,89,96,19,81,0.0,6,83,Urban,Software Engineer,81134,1 +100673,Male,48,Diploma,15,14,84,30,96,5.0,6,31,Rural,Software Engineer,131177,0 +100674,Male,44,Diploma,17,32,77,84,22,9.0,0,43,Rural,Data Analyst,36287,1 +100675,Male,42,Bachelors,0,52,1,20,17,6.0,4,62,Urban,HR Executive,149991,0 +100676,Female,53,Diploma,18,22,77,1,26,4.0,4,22,Rural,ML Engineer,45143,0 +100677,Male,49,Diploma,1,90,49,43,88,6.0,7,82,Semi-Urban,ML Engineer,60789,1 +100678,Female,23,Bachelors,3,74,94,46,35,6.0,1,74,Urban,Software Engineer,95078,1 +100679,Female,47,Bachelors,5,27,5,10,25,3.0,2,10,Urban,Manager,128932,0 +100680,Male,37,Bachelors,16,73,81,75,63,1.0,4,16,Urban,HR Executive,53627,1 +100681,Female,44,Masters,15,82,39,13,47,5.0,4,40,Urban,Data Analyst,58005,0 +100682,Male,23,Diploma,9,12,75,57,7,1.0,6,88,Urban,ML Engineer,125541,0 +100683,Male,31,Bachelors,17,54,21,75,89,8.0,0,10,Urban,ML Engineer,103867,0 +100684,Male,40,Bachelors,18,39,90,9,9,9.0,6,37,Urban,Manager,112301,0 +100685,Female,28,High School,13,21,59,56,60,2.0,5,60,Urban,Manager,88860,0 +100686,Male,31,Diploma,3,48,18,51,49,6.0,3,56,Urban,Software Engineer,132650,0 +100687,Male,31,Bachelors,8,42,34,18,69,6.0,6,28,Urban,HR Executive,149228,0 +100688,Female,57,PhD,12,88,81,86,78,9.0,3,44,Semi-Urban,HR Executive,54298,1 +100689,Female,57,Masters,4,32,86,7,89,1.0,2,66,Rural,Software Engineer,76231,0 +100690,Male,49,Bachelors,5,1,3,59,94,7.0,4,8,Urban,Manager,23249,0 +100691,Male,53,Bachelors,11,23,6,24,22,3.0,5,67,Urban,Manager,30892,0 +100692,Male,41,Masters,11,61,59,20,99,9.0,5,96,Urban,ML Engineer,125274,1 +100693,Male,27,Bachelors,15,90,58,56,43,4.0,6,0,Urban,Software Engineer,26316,0 +100694,Male,21,Masters,11,30,75,78,27,4.0,1,79,Rural,HR Executive,115897,1 +100695,Male,43,High School,13,65,62,70,1,4.0,3,75,Urban,Software Engineer,94351,1 +100696,Male,54,Masters,0,98,33,52,70,9.0,7,72,Rural,HR Executive,135321,1 +100697,Male,36,Masters,18,57,98,33,91,4.0,4,19,Urban,Software Engineer,49718,0 +100698,Female,53,Diploma,16,51,71,23,25,4.0,3,23,Semi-Urban,HR Executive,117349,0 +100699,Female,35,PhD,14,32,20,45,3,1.0,3,28,Urban,HR Executive,96445,0 +100700,Male,26,Bachelors,10,21,16,11,18,8.0,2,17,Rural,Software Engineer,88508,0 +100701,Male,55,Bachelors,11,67,94,73,50,4.0,7,96,Urban,Software Engineer,136907,1 +100702,Male,55,Diploma,1,78,61,50,59,5.0,4,40,Urban,Software Engineer,112519,0 +100703,Other,25,Masters,19,51,38,67,73,1.0,3,82,Urban,Manager,109732,0 +100704,Female,55,PhD,5,85,89,4,45,4.0,4,48,Rural,Manager,127335,0 +100705,Male,47,Bachelors,9,27,25,58,69,2.0,7,39,Urban,HR Executive,35903,0 +100706,Male,29,Bachelors,10,7,7,29,92,0.0,0,3,Urban,Data Analyst,123668,0 +100707,Male,33,Bachelors,14,87,25,51,94,9.0,2,14,Semi-Urban,Software Engineer,49991,0 +100708,Female,36,High School,14,39,57,94,6,4.0,7,65,Semi-Urban,Data Analyst,87346,1 +100709,Male,42,Masters,3,81,93,56,51,0.0,3,56,Urban,HR Executive,27718,1 +100710,Female,38,Diploma,19,51,10,29,48,6.0,2,85,Rural,Manager,132546,0 +100711,Male,49,Bachelors,18,87,58,63,7,9.0,4,78,Rural,Software Engineer,68444,1 +100712,Male,51,High School,10,80,16,79,84,2.0,3,76,Semi-Urban,Manager,96464,1 +100713,Male,41,High School,0,28,67,44,81,2.0,4,18,Rural,Data Analyst,123755,0 +100714,Female,39,Masters,8,87,12,12,35,6.0,5,60,Urban,Data Analyst,59316,0 +100715,Male,56,High School,10,82,47,58,51,9.0,6,41,Rural,HR Executive,119053,0 +100716,Female,53,PhD,13,77,80,8,25,1.0,1,42,Urban,Manager,92556,0 +100717,Male,57,PhD,2,6,30,17,80,7.0,1,9,Urban,Manager,90865,0 +100718,Female,31,Diploma,8,92,47,7,28,6.0,0,59,Semi-Urban,HR Executive,136357,0 +100719,Male,35,Bachelors,7,62,62,32,61,6.0,6,4,Rural,HR Executive,92479,0 +100720,Male,40,Diploma,7,23,23,15,33,1.0,5,44,Urban,Manager,133565,0 +100721,Female,49,Diploma,13,14,52,25,72,2.0,1,95,Semi-Urban,Manager,126028,0 +100722,Male,49,Bachelors,4,50,26,91,12,9.0,1,22,Urban,Manager,21650,0 +100723,Male,28,Diploma,19,71,25,41,55,1.0,3,45,Rural,ML Engineer,69483,0 +100724,Female,48,Masters,15,2,23,82,48,7.0,4,33,Urban,Manager,128596,0 +100725,Male,39,Bachelors,7,40,36,86,29,3.0,6,27,Urban,Software Engineer,125767,0 +100726,Male,52,High School,4,35,96,51,55,4.0,6,52,Semi-Urban,ML Engineer,82392,0 +100727,Female,39,Masters,4,61,77,78,33,2.0,2,36,Urban,Software Engineer,52577,1 +100728,Female,21,High School,7,75,44,15,58,3.0,5,82,Semi-Urban,HR Executive,37003,0 +100729,Male,42,Masters,8,68,76,13,71,1.0,6,21,Rural,Data Analyst,127113,0 +100730,Other,36,PhD,3,64,68,28,53,6.0,2,30,Urban,Manager,130254,0 +100731,Female,39,Diploma,0,12,25,82,17,2.0,0,21,Urban,Software Engineer,139745,0 +100732,Male,49,Masters,12,38,0,39,11,1.0,4,92,Rural,Manager,83427,0 +100733,Male,39,Masters,17,13,62,67,25,2.0,6,75,Rural,ML Engineer,31774,0 +100734,Male,55,PhD,3,51,17,16,50,9.0,2,30,Urban,Software Engineer,60998,0 +100735,Male,43,Diploma,1,28,93,97,56,9.0,5,55,Rural,Data Analyst,29573,1 +100736,Female,24,Masters,3,79,9,42,35,7.0,4,55,Urban,Data Analyst,68204,0 +100737,Male,31,Masters,12,50,86,21,39,9.0,5,59,Urban,HR Executive,112863,0 +100738,Female,43,Diploma,7,11,54,78,38,7.0,0,61,Urban,Data Analyst,52513,0 +100739,Female,27,Diploma,9,98,59,49,60,8.0,0,56,Urban,Data Analyst,39308,1 +100740,Female,43,Masters,8,13,44,26,4,0.0,1,34,Urban,HR Executive,90946,0 +100741,Male,47,High School,5,74,58,89,58,2.0,2,44,Urban,Manager,127088,1 +100742,Female,23,Bachelors,7,34,82,49,56,3.0,7,14,Urban,Manager,87032,0 +100743,Other,25,Bachelors,11,40,85,52,29,3.0,5,67,Rural,Data Analyst,100552,1 +100744,Male,59,Masters,7,31,14,46,3,3.0,1,81,Rural,Data Analyst,59083,0 +100745,Male,22,Masters,17,91,2,84,49,1.0,5,8,Urban,HR Executive,55099,0 +100746,Male,52,Bachelors,14,82,88,30,58,0.0,5,26,Semi-Urban,ML Engineer,57148,0 +100747,Male,52,Bachelors,17,81,71,15,23,8.0,0,61,Urban,Data Analyst,131597,0 +100748,Male,30,Bachelors,13,31,60,98,94,4.0,7,62,Urban,HR Executive,35592,1 +100749,Female,38,Masters,10,25,80,63,46,7.0,7,20,Urban,Data Analyst,64142,0 +100750,Female,57,Bachelors,8,3,32,68,80,0.0,5,97,Urban,Software Engineer,140267,0 +100751,Male,24,Masters,16,96,65,74,50,2.0,4,78,Rural,ML Engineer,78025,1 +100752,Male,55,High School,0,89,98,24,5,9.0,4,97,Urban,Manager,35198,1 +100753,Female,31,Bachelors,13,79,24,52,44,0.0,5,14,Semi-Urban,Manager,138167,0 +100754,Male,42,Masters,8,32,81,50,94,3.0,1,78,Semi-Urban,Data Analyst,93093,1 +100755,Male,39,Diploma,14,77,54,15,91,9.0,3,57,Urban,Data Analyst,30830,0 +100756,Other,48,High School,3,14,85,58,46,2.0,1,4,Urban,ML Engineer,54427,0 +100757,Male,21,Bachelors,18,21,62,23,4,9.0,5,40,Semi-Urban,Data Analyst,27342,0 +100758,Male,38,Masters,19,61,75,3,87,4.0,2,29,Urban,Software Engineer,95652,0 +100759,Male,45,Bachelors,9,2,1,42,1,1.0,2,92,Urban,ML Engineer,67913,0 +100760,Male,51,Bachelors,13,36,72,55,53,0.0,6,0,Rural,Manager,59573,0 +100761,Female,54,High School,19,60,96,67,74,2.0,4,42,Rural,HR Executive,76169,1 +100762,Male,47,Masters,18,22,21,0,27,1.0,0,3,Urban,Data Analyst,75288,0 +100763,Male,42,High School,16,9,63,86,66,4.0,0,6,Urban,HR Executive,131241,0 +100764,Male,33,Masters,9,9,30,19,88,4.0,7,61,Semi-Urban,HR Executive,61488,0 +100765,Male,39,High School,5,36,3,59,23,8.0,0,0,Urban,Software Engineer,93038,0 +100766,Female,45,Bachelors,19,12,67,19,86,9.0,3,7,Urban,HR Executive,80371,0 +100767,Male,55,Bachelors,12,95,53,41,98,4.0,1,76,Rural,Software Engineer,124703,1 +100768,Female,41,High School,10,22,0,81,89,3.0,5,81,Urban,ML Engineer,30767,0 +100769,Male,22,High School,8,20,15,10,89,3.0,6,7,Rural,Data Analyst,26924,0 +100770,Male,36,Bachelors,12,79,42,92,32,8.0,4,24,Urban,Software Engineer,65939,1 +100771,Male,41,Masters,2,36,9,10,41,3.0,7,87,Rural,Data Analyst,117006,0 +100772,Other,39,Masters,19,96,43,72,39,5.0,7,32,Rural,HR Executive,140477,1 +100773,Male,42,Masters,9,34,85,5,30,4.0,2,80,Urban,ML Engineer,74302,0 +100774,Male,22,Bachelors,13,62,23,16,2,2.0,0,62,Urban,Software Engineer,84955,0 +100775,Male,43,Bachelors,15,87,11,77,7,5.0,7,78,Urban,HR Executive,31058,1 +100776,Male,40,Diploma,12,85,31,40,66,2.0,6,70,Urban,Manager,73695,0 +100777,Female,44,Masters,5,35,15,48,98,6.0,5,54,Semi-Urban,ML Engineer,33907,0 +100778,Male,47,Bachelors,10,24,48,54,62,9.0,6,13,Urban,Software Engineer,101479,0 +100779,Male,30,Masters,1,48,48,73,6,5.0,3,65,Urban,Software Engineer,140427,0 +100780,Male,37,Diploma,2,98,35,63,77,3.0,0,95,Rural,Data Analyst,117100,1 +100781,Female,22,Diploma,3,24,5,80,69,5.0,3,72,Urban,HR Executive,65109,0 +100782,Male,58,Bachelors,3,70,58,15,61,6.0,3,74,Urban,Data Analyst,53597,0 +100783,Male,51,Diploma,5,29,25,51,9,7.0,1,78,Rural,Software Engineer,104708,0 +100784,Male,57,High School,12,91,20,45,76,8.0,5,82,Semi-Urban,Software Engineer,131984,1 +100785,Male,50,Diploma,2,74,47,63,63,8.0,7,0,Rural,Data Analyst,50868,0 +100786,Male,37,Diploma,19,67,66,65,6,8.0,7,62,Semi-Urban,HR Executive,68486,1 +100787,Female,57,Bachelors,6,23,11,2,85,3.0,7,21,Rural,Software Engineer,72436,0 +100788,Male,41,Diploma,12,51,83,71,64,9.0,7,77,Urban,ML Engineer,135435,1 +100789,Female,39,Bachelors,2,35,88,96,79,2.0,4,16,Rural,HR Executive,129988,0 +100790,Female,44,Bachelors,9,25,49,5,81,4.0,6,62,Rural,ML Engineer,108060,0 +100791,Male,38,Bachelors,19,36,61,17,89,1.0,7,8,Urban,Software Engineer,134982,0 +100792,Male,30,Masters,19,85,98,44,70,3.0,3,49,Rural,Data Analyst,33149,1 +100793,Male,23,PhD,16,0,93,63,65,7.0,2,46,Semi-Urban,Manager,41812,0 +100794,Other,40,Bachelors,17,63,47,66,79,6.0,3,66,Urban,ML Engineer,134261,1 +100795,Male,37,Bachelors,4,66,70,85,24,3.0,4,51,Urban,ML Engineer,66143,1 +100796,Male,37,High School,13,13,51,62,98,4.0,5,48,Rural,Manager,81991,0 +100797,Male,25,Bachelors,13,70,1,36,13,4.0,2,46,Semi-Urban,ML Engineer,108590,0 +100798,Other,36,Bachelors,17,12,6,56,50,1.0,7,53,Urban,HR Executive,20340,0 +100799,Male,21,Bachelors,12,60,6,18,36,7.0,3,14,Rural,ML Engineer,76902,0 +100800,Male,40,Masters,0,37,24,5,24,2.0,1,64,Semi-Urban,Data Analyst,36401,0 +100801,Male,22,Bachelors,8,64,94,62,99,9.0,0,31,Semi-Urban,Data Analyst,61243,1 +100802,Male,24,Bachelors,2,81,51,57,98,7.0,7,50,Urban,HR Executive,39403,1 +100803,Female,56,Bachelors,4,91,65,51,58,9.0,6,26,Semi-Urban,HR Executive,105497,0 +100804,Male,51,Diploma,9,81,3,18,81,6.0,7,6,Semi-Urban,HR Executive,37963,0 +100805,Other,57,Masters,15,38,75,68,26,0.0,6,87,Urban,HR Executive,88539,1 +100806,Male,30,Bachelors,17,42,41,95,78,2.0,1,51,Urban,Manager,20570,0 +100807,Other,43,Diploma,9,94,68,76,10,4.0,5,26,Rural,Data Analyst,101020,1 +100808,Male,34,High School,7,21,31,91,81,1.0,2,39,Rural,Software Engineer,49612,0 +100809,Male,25,High School,8,26,68,44,12,9.0,7,37,Urban,HR Executive,52124,0 +100810,Male,46,High School,1,2,10,9,97,2.0,2,19,Urban,ML Engineer,146770,0 +100811,Male,46,Bachelors,6,17,55,25,7,1.0,4,44,Urban,ML Engineer,39584,0 +100812,Female,44,Masters,7,41,55,14,58,3.0,3,39,Semi-Urban,Data Analyst,115431,0 +100813,Male,29,Bachelors,8,16,46,40,10,2.0,2,71,Urban,Data Analyst,112283,0 +100814,Female,53,Bachelors,11,35,47,51,77,9.0,6,45,Rural,HR Executive,56903,0 +100815,Male,53,Diploma,13,97,58,20,73,9.0,7,33,Urban,ML Engineer,76493,0 +100816,Male,41,Masters,9,83,23,92,78,1.0,2,47,Urban,Manager,58051,1 +100817,Female,32,Masters,19,14,58,79,21,8.0,4,22,Rural,HR Executive,44365,0 +100818,Male,39,High School,1,29,27,0,99,1.0,7,15,Semi-Urban,HR Executive,136534,0 +100819,Male,44,Diploma,19,46,41,43,7,6.0,3,67,Semi-Urban,Software Engineer,45235,0 +100820,Female,35,Bachelors,4,51,17,32,93,8.0,0,91,Semi-Urban,Software Engineer,128365,0 +100821,Female,51,PhD,2,24,6,80,28,0.0,2,51,Rural,Software Engineer,130439,0 +100822,Female,28,High School,1,54,44,56,41,9.0,3,92,Urban,Software Engineer,28406,1 +100823,Male,27,Masters,12,35,77,73,53,8.0,1,28,Semi-Urban,Data Analyst,134399,0 +100824,Male,59,High School,8,4,73,84,69,2.0,0,49,Urban,Software Engineer,33969,0 +100825,Male,26,Diploma,11,3,22,44,94,3.0,3,46,Semi-Urban,Data Analyst,145622,0 +100826,Female,46,Bachelors,11,25,6,49,0,0.0,5,87,Urban,Manager,105494,0 +100827,Female,21,High School,4,40,29,27,67,6.0,2,75,Urban,HR Executive,83537,0 +100828,Male,30,Masters,11,42,16,89,63,4.0,4,44,Urban,Manager,130952,0 +100829,Other,35,Diploma,14,61,55,17,98,3.0,1,72,Rural,Manager,22640,0 +100830,Female,21,Bachelors,10,37,94,99,14,4.0,1,99,Urban,Manager,46830,1 +100831,Female,54,Diploma,16,66,28,33,23,3.0,4,11,Semi-Urban,Manager,91130,0 +100832,Male,47,Masters,12,85,38,86,36,3.0,2,48,Semi-Urban,HR Executive,146666,1 +100833,Male,57,Bachelors,9,41,14,39,86,9.0,1,85,Urban,Data Analyst,105540,0 +100834,Female,47,High School,13,13,95,37,61,7.0,0,57,Rural,HR Executive,95958,0 +100835,Male,45,Bachelors,7,96,67,3,84,2.0,4,66,Urban,Data Analyst,30521,0 +100836,Female,41,Bachelors,1,19,4,67,80,3.0,2,61,Urban,Data Analyst,62724,0 +100837,Male,23,Diploma,5,8,48,28,64,9.0,3,9,Urban,Software Engineer,73319,0 +100838,Male,39,Bachelors,8,64,67,62,78,9.0,7,20,Semi-Urban,Software Engineer,28212,0 +100839,Male,51,Masters,17,84,33,47,34,0.0,7,62,Urban,Software Engineer,138768,0 +100840,Other,55,Masters,8,45,63,15,83,5.0,0,70,Urban,HR Executive,125153,0 +100841,Male,25,Bachelors,19,21,5,39,94,7.0,1,28,Semi-Urban,HR Executive,75697,0 +100842,Female,25,Diploma,0,14,30,1,14,8.0,2,99,Urban,Software Engineer,84661,0 +100843,Male,41,Bachelors,13,90,4,62,47,3.0,6,53,Semi-Urban,ML Engineer,30717,0 +100844,Female,37,Masters,8,74,68,9,96,9.0,5,14,Semi-Urban,Software Engineer,82773,0 +100845,Male,47,High School,14,1,89,40,82,7.0,1,60,Semi-Urban,ML Engineer,44709,0 +100846,Other,55,Diploma,5,92,88,17,40,1.0,7,6,Semi-Urban,Data Analyst,124098,0 +100847,Female,47,High School,4,0,71,59,83,9.0,6,30,Urban,ML Engineer,133226,0 +100848,Female,33,Bachelors,2,5,97,4,74,6.0,6,43,Urban,Data Analyst,36576,0 +100849,Female,43,Bachelors,12,47,96,63,59,2.0,7,9,Urban,HR Executive,47807,0 +100850,Male,25,Bachelors,17,62,60,56,30,2.0,7,72,Urban,Software Engineer,131706,1 +100851,Male,30,High School,18,81,48,96,3,8.0,3,65,Rural,Data Analyst,56952,1 +100852,Female,31,Masters,7,7,60,16,36,6.0,7,91,Urban,HR Executive,27088,0 +100853,Male,22,Bachelors,6,18,25,2,25,9.0,1,97,Semi-Urban,HR Executive,134959,0 +100854,Female,42,PhD,15,88,76,11,73,0.0,5,11,Semi-Urban,Manager,107143,0 +100855,Male,58,High School,0,78,16,18,39,6.0,3,31,Urban,Software Engineer,119029,0 +100856,Female,42,High School,4,59,1,71,13,2.0,3,36,Urban,HR Executive,131725,0 +100857,Other,49,Bachelors,13,85,44,4,57,8.0,1,46,Urban,Data Analyst,117229,0 +100858,Other,30,Bachelors,17,10,58,9,95,2.0,2,72,Semi-Urban,Data Analyst,54525,0 +100859,Male,51,Masters,12,38,84,85,75,4.0,0,54,Rural,Data Analyst,53442,1 +100860,Male,41,Diploma,12,46,30,47,50,2.0,1,91,Urban,HR Executive,51297,0 +100861,Female,54,Bachelors,10,16,60,50,38,4.0,4,28,Rural,Data Analyst,51572,0 +100862,Female,54,Masters,3,81,4,53,22,6.0,2,75,Semi-Urban,Software Engineer,21689,0 +100863,Male,53,Bachelors,2,87,72,7,50,9.0,6,2,Urban,Software Engineer,61999,0 +100864,Male,59,Masters,7,50,74,61,33,9.0,5,11,Urban,Software Engineer,123576,0 +100865,Male,24,Diploma,9,11,63,56,37,6.0,6,16,Urban,Manager,135339,0 +100866,Female,37,Diploma,2,63,35,60,20,0.0,2,27,Urban,ML Engineer,77576,0 +100867,Male,31,Bachelors,7,7,77,16,40,9.0,2,26,Urban,Manager,97460,0 +100868,Male,31,PhD,18,4,43,18,16,8.0,2,81,Urban,Manager,88182,0 +100869,Female,49,Bachelors,6,38,53,82,65,5.0,2,18,Urban,Software Engineer,98924,0 +100870,Male,48,Diploma,18,69,58,25,88,2.0,4,74,Urban,Manager,80754,0 +100871,Male,37,Diploma,6,88,78,96,93,0.0,4,36,Urban,Data Analyst,36082,1 +100872,Male,52,Masters,13,7,33,11,35,5.0,5,97,Urban,ML Engineer,68577,0 +100873,Male,30,Bachelors,6,84,32,83,58,9.0,1,47,Rural,HR Executive,35762,1 +100874,Other,47,Diploma,3,9,35,28,83,4.0,6,99,Rural,Data Analyst,33515,0 +100875,Male,26,PhD,0,7,29,20,44,6.0,0,59,Urban,ML Engineer,143513,0 +100876,Male,27,Diploma,17,23,74,86,2,0.0,0,6,Semi-Urban,ML Engineer,100425,0 +100877,Other,30,Bachelors,8,64,33,15,93,4.0,2,55,Urban,ML Engineer,56642,0 +100878,Male,54,PhD,10,81,42,3,78,7.0,2,28,Semi-Urban,Manager,69275,0 +100879,Male,35,Bachelors,6,65,46,59,12,4.0,4,88,Urban,Software Engineer,20992,1 +100880,Female,56,Bachelors,14,76,3,11,4,2.0,1,33,Semi-Urban,Manager,81233,0 +100881,Female,40,Bachelors,14,46,73,5,53,9.0,6,0,Urban,Software Engineer,94637,0 +100882,Female,48,Bachelors,16,3,67,21,6,2.0,7,6,Rural,Manager,70420,0 +100883,Male,37,Bachelors,17,43,32,65,22,2.0,2,50,Semi-Urban,Manager,40520,0 +100884,Male,40,Masters,2,1,47,7,78,0.0,2,76,Semi-Urban,Software Engineer,42814,0 +100885,Female,23,Bachelors,13,79,96,61,21,7.0,5,34,Urban,Data Analyst,91481,1 +100886,Male,41,Diploma,18,50,27,30,36,5.0,1,83,Semi-Urban,Software Engineer,80847,0 +100887,Female,37,Diploma,17,65,8,21,14,5.0,1,61,Semi-Urban,Data Analyst,27685,0 +100888,Male,23,Bachelors,9,92,61,34,33,8.0,3,29,Urban,ML Engineer,22807,0 +100889,Male,21,Diploma,11,37,48,89,81,1.0,6,82,Urban,Software Engineer,124079,1 +100890,Other,36,Diploma,11,52,11,16,47,4.0,2,3,Rural,ML Engineer,79137,0 +100891,Female,50,Masters,4,58,76,55,16,5.0,5,16,Urban,Data Analyst,119735,0 +100892,Male,52,Bachelors,10,67,35,4,13,8.0,0,25,Rural,Manager,135862,0 +100893,Female,29,Diploma,6,68,96,49,42,0.0,1,34,Rural,Manager,36480,1 +100894,Male,39,High School,15,86,71,64,41,1.0,1,0,Semi-Urban,Data Analyst,124258,0 +100895,Female,37,Diploma,19,61,94,52,72,6.0,5,1,Urban,HR Executive,24112,0 +100896,Male,34,Diploma,6,38,88,77,71,8.0,0,93,Rural,Manager,83894,1 +100897,Male,37,Masters,8,39,40,21,0,7.0,5,3,Urban,Software Engineer,99234,0 +100898,Female,37,Diploma,18,78,43,42,49,3.0,2,29,Urban,Data Analyst,108960,0 +100899,Female,21,Bachelors,15,60,83,94,95,7.0,0,37,Urban,Manager,106389,1 +100900,Male,39,Bachelors,5,86,5,27,10,5.0,6,75,Urban,Software Engineer,22020,0 +100901,Male,39,Masters,7,86,71,69,2,3.0,2,84,Semi-Urban,HR Executive,118325,1 +100902,Male,47,Bachelors,3,58,7,51,34,3.0,1,22,Urban,Software Engineer,52691,0 +100903,Male,49,Masters,7,38,46,97,57,6.0,7,82,Urban,Manager,104639,1 +100904,Male,48,Diploma,2,24,6,99,32,3.0,2,58,Urban,Manager,149839,0 +100905,Female,28,Bachelors,7,54,55,21,10,4.0,4,99,Semi-Urban,Data Analyst,71767,0 +100906,Male,48,High School,15,46,49,69,50,4.0,1,97,Urban,Manager,62090,1 +100907,Male,41,High School,8,72,93,11,60,6.0,7,60,Urban,Data Analyst,30238,1 +100908,Female,21,Diploma,8,66,8,7,65,0.0,2,62,Semi-Urban,Manager,108515,0 +100909,Male,49,Bachelors,11,30,54,62,61,2.0,5,72,Urban,HR Executive,95795,0 +100910,Male,38,Bachelors,15,69,99,90,46,4.0,7,52,Urban,ML Engineer,119419,1 +100911,Female,23,Diploma,16,28,12,8,77,3.0,6,87,Rural,ML Engineer,110617,0 +100912,Male,45,High School,0,99,92,5,55,7.0,0,22,Rural,Manager,86750,0 +100913,Female,33,Bachelors,15,13,8,58,63,7.0,0,12,Semi-Urban,Manager,149320,0 +100914,Male,37,High School,11,27,13,44,52,6.0,4,49,Urban,Manager,73093,0 +100915,Male,34,Bachelors,2,78,59,59,30,0.0,7,8,Urban,HR Executive,35154,0 +100916,Male,46,Bachelors,6,75,96,96,74,8.0,3,21,Urban,ML Engineer,33745,1 +100917,Female,54,Bachelors,0,83,89,85,63,0.0,6,19,Urban,Software Engineer,80077,1 +100918,Female,36,High School,1,78,11,84,88,5.0,3,49,Semi-Urban,HR Executive,54886,0 +100919,Male,45,Bachelors,5,66,17,7,38,2.0,1,46,Urban,Data Analyst,128835,0 +100920,Female,38,Masters,11,65,72,0,38,7.0,2,99,Urban,Software Engineer,134790,0 +100921,Female,27,PhD,3,86,85,73,80,5.0,6,14,Semi-Urban,Manager,81203,1 +100922,Female,52,Bachelors,15,47,40,72,9,1.0,2,59,Semi-Urban,Data Analyst,86626,0 +100923,Female,31,Bachelors,6,91,22,47,79,5.0,0,5,Rural,ML Engineer,107093,0 +100924,Male,28,Bachelors,1,40,77,9,94,1.0,7,71,Semi-Urban,Data Analyst,49272,0 +100925,Male,22,Bachelors,17,67,93,72,7,0.0,5,70,Urban,Data Analyst,85308,1 +100926,Male,25,Bachelors,5,83,85,51,16,0.0,4,59,Rural,Data Analyst,39817,1 +100927,Male,21,Masters,19,34,46,76,40,2.0,7,66,Urban,Software Engineer,20232,0 +100928,Female,52,Masters,4,68,51,15,72,6.0,6,14,Rural,Data Analyst,93984,0 +100929,Female,41,High School,15,72,45,65,50,0.0,1,67,Rural,Manager,123619,1 +100930,Male,48,Bachelors,9,38,56,74,4,5.0,3,60,Rural,Software Engineer,79340,0 +100931,Male,34,Bachelors,4,49,63,66,62,4.0,4,61,Urban,ML Engineer,98253,1 +100932,Male,45,Diploma,16,3,92,3,99,8.0,4,64,Rural,Software Engineer,143574,0 +100933,Other,24,Masters,2,25,80,35,68,4.0,4,8,Urban,Data Analyst,135733,0 +100934,Female,48,High School,3,21,64,52,11,4.0,7,62,Urban,Data Analyst,117227,0 +100935,Male,31,Bachelors,1,60,43,80,17,4.0,6,80,Semi-Urban,Software Engineer,134217,1 +100936,Male,24,Bachelors,11,54,31,93,30,4.0,3,13,Rural,Data Analyst,40654,0 +100937,Male,37,Diploma,7,55,91,88,57,4.0,6,1,Rural,HR Executive,138569,1 +100938,Male,29,Bachelors,16,19,83,88,63,0.0,2,77,Urban,HR Executive,82441,1 +100939,Female,44,Diploma,8,9,4,32,5,1.0,7,17,Urban,Manager,51556,0 +100940,Male,52,Diploma,14,66,68,88,50,1.0,0,93,Rural,ML Engineer,68496,1 +100941,Male,29,Bachelors,11,91,98,86,39,3.0,1,28,Urban,ML Engineer,105787,1 +100942,Male,39,Bachelors,12,11,97,4,59,2.0,6,60,Urban,HR Executive,42112,0 +100943,Male,28,Masters,16,79,62,47,72,7.0,7,81,Urban,Software Engineer,26131,1 +100944,Female,54,Bachelors,5,45,73,11,32,6.0,3,82,Urban,Software Engineer,126948,0 +100945,Male,49,Diploma,14,51,49,4,19,1.0,5,29,Semi-Urban,Data Analyst,56743,0 +100946,Female,59,Diploma,19,41,72,43,1,9.0,3,72,Urban,Data Analyst,44541,0 +100947,Female,35,Bachelors,18,94,36,70,69,3.0,3,59,Urban,HR Executive,20640,1 +100948,Male,51,Bachelors,4,41,49,20,45,2.0,1,29,Urban,HR Executive,21110,0 +100949,Female,42,Masters,3,19,21,12,2,6.0,0,6,Semi-Urban,ML Engineer,60270,0 +100950,Female,53,Masters,17,6,18,11,61,0.0,3,74,Urban,Software Engineer,135574,0 +100951,Female,58,High School,7,49,51,84,8,9.0,6,57,Rural,Manager,147409,1 +100952,Male,58,PhD,4,96,68,11,24,6.0,1,66,Rural,Data Analyst,34080,1 +100953,Male,51,Masters,4,84,39,60,47,1.0,4,7,Rural,Manager,25854,0 +100954,Male,23,Diploma,13,17,62,73,63,9.0,6,43,Rural,Manager,139764,0 +100955,Male,50,Bachelors,15,22,16,25,42,2.0,1,34,Rural,Data Analyst,137387,0 +100956,Female,54,Masters,14,35,61,66,12,7.0,6,7,Rural,Manager,29592,0 +100957,Male,24,Diploma,6,35,32,63,53,3.0,5,97,Semi-Urban,Software Engineer,74597,0 +100958,Male,23,Diploma,7,60,91,16,46,3.0,0,8,Urban,ML Engineer,39497,0 +100959,Female,31,Bachelors,18,23,97,75,29,8.0,0,29,Urban,Manager,30425,0 +100960,Female,28,Bachelors,0,88,19,77,60,4.0,1,18,Urban,Software Engineer,39942,0 +100961,Female,46,PhD,11,58,45,14,46,5.0,2,54,Urban,Manager,141715,0 +100962,Male,58,Masters,12,83,24,37,27,7.0,1,67,Urban,ML Engineer,118120,0 +100963,Male,56,Bachelors,2,15,74,13,37,1.0,0,18,Urban,ML Engineer,128330,0 +100964,Male,32,Bachelors,6,56,10,23,81,3.0,0,18,Urban,HR Executive,46982,0 +100965,Male,43,Masters,2,65,67,26,10,2.0,5,13,Urban,HR Executive,48425,0 +100966,Male,26,High School,9,42,62,22,29,1.0,4,56,Urban,ML Engineer,145328,0 +100967,Female,40,High School,13,7,21,14,82,7.0,2,3,Urban,Data Analyst,74913,0 +100968,Male,26,Bachelors,8,47,79,69,77,2.0,2,54,Urban,Software Engineer,53803,1 +100969,Other,27,Masters,19,66,76,2,81,9.0,0,51,Urban,Data Analyst,108362,0 +100970,Male,56,PhD,9,84,58,41,37,8.0,6,56,Semi-Urban,HR Executive,140713,1 +100971,Male,32,Masters,8,6,27,54,1,0.0,3,60,Rural,ML Engineer,124085,0 +100972,Male,46,Diploma,17,30,82,16,44,5.0,5,2,Urban,Software Engineer,81694,0 +100973,Male,56,Bachelors,13,35,34,3,99,6.0,1,36,Urban,ML Engineer,89094,0 +100974,Male,41,Bachelors,2,84,69,5,20,5.0,7,93,Urban,Manager,135319,1 +100975,Male,46,Bachelors,1,86,95,11,0,9.0,7,32,Semi-Urban,HR Executive,23434,0 +100976,Other,47,Bachelors,8,29,36,72,41,9.0,4,41,Rural,Manager,102922,0 +100977,Female,21,High School,15,5,77,39,59,1.0,3,89,Urban,Software Engineer,100544,0 +100978,Male,45,High School,7,44,28,6,31,6.0,7,35,Urban,HR Executive,24942,0 +100979,Female,58,Masters,2,59,22,73,4,2.0,5,62,Semi-Urban,HR Executive,37183,0 +100980,Female,39,Diploma,1,24,91,59,32,6.0,6,70,Urban,Software Engineer,77768,1 +100981,Female,48,High School,11,61,23,13,40,0.0,5,88,Urban,HR Executive,119390,0 +100982,Male,32,Diploma,6,70,85,41,46,3.0,5,95,Semi-Urban,Manager,62038,1 +100983,Male,39,Masters,14,44,31,91,19,4.0,6,27,Urban,HR Executive,135366,0 +100984,Male,37,Masters,8,69,50,34,50,1.0,2,33,Urban,HR Executive,104732,0 +100985,Male,23,Masters,10,35,17,29,86,3.0,6,81,Rural,Manager,137033,0 +100986,Female,45,Masters,3,93,15,93,95,7.0,0,58,Urban,ML Engineer,132119,1 +100987,Male,43,Diploma,8,85,14,48,29,4.0,7,51,Urban,ML Engineer,90392,0 +100988,Male,45,Diploma,14,85,4,0,17,3.0,0,32,Semi-Urban,ML Engineer,35959,0 +100989,Male,28,Masters,4,13,58,24,82,3.0,1,38,Semi-Urban,Data Analyst,30481,0 +100990,Female,31,Bachelors,0,58,69,27,87,6.0,0,22,Urban,Software Engineer,64537,0 +100991,Male,27,Diploma,3,55,65,19,27,7.0,4,54,Urban,Software Engineer,104176,0 +100992,Other,44,Diploma,1,8,83,6,62,6.0,4,78,Urban,ML Engineer,20304,0 +100993,Female,45,High School,7,47,44,21,42,9.0,3,93,Rural,Software Engineer,138893,0 +100994,Female,45,Bachelors,13,82,46,26,76,9.0,6,4,Urban,Manager,23824,0 +100995,Male,36,PhD,1,9,88,26,21,2.0,5,81,Urban,Data Analyst,132706,0 +100996,Male,26,Diploma,16,74,96,23,18,5.0,6,4,Semi-Urban,Manager,85535,0 +100997,Female,22,PhD,2,86,62,63,33,0.0,0,5,Semi-Urban,ML Engineer,129843,0 +100998,Male,58,Diploma,2,95,44,31,78,1.0,1,34,Semi-Urban,ML Engineer,131089,0 +100999,Female,36,Bachelors,19,29,57,40,44,9.0,6,6,Rural,Data Analyst,98809,0 +101000,Female,51,Bachelors,13,1,45,23,34,2.0,4,58,Semi-Urban,ML Engineer,148387,0 +101001,Male,53,Masters,7,87,77,52,83,5.0,1,18,Semi-Urban,Manager,36911,0 +101002,Female,49,Bachelors,2,41,54,40,78,6.0,0,60,Semi-Urban,HR Executive,45518,0 +101003,Female,56,Diploma,14,43,42,5,38,4.0,0,10,Urban,HR Executive,69641,0 +101004,Female,43,Bachelors,0,17,10,97,80,9.0,1,57,Urban,Data Analyst,108146,0 +101005,Male,49,High School,7,18,5,99,19,9.0,2,14,Urban,Manager,114114,0 +101006,Male,42,Diploma,0,42,69,59,25,6.0,5,62,Urban,HR Executive,106679,0 +101007,Female,55,Bachelors,18,56,4,79,84,5.0,3,99,Urban,Software Engineer,99651,0 +101008,Female,38,Masters,10,85,91,45,75,0.0,6,82,Semi-Urban,Software Engineer,74006,1 +101009,Female,55,PhD,12,30,4,93,25,4.0,4,48,Urban,HR Executive,99011,0 +101010,Male,43,Bachelors,17,91,38,12,58,9.0,2,25,Semi-Urban,Data Analyst,125656,0 +101011,Female,39,PhD,4,38,7,45,40,3.0,2,12,Urban,ML Engineer,24673,0 +101012,Female,35,Bachelors,14,28,49,56,17,8.0,2,73,Rural,Software Engineer,148810,0 +101013,Male,22,Masters,10,37,91,58,42,3.0,1,27,Rural,Manager,99312,0 +101014,Female,53,Bachelors,5,23,67,22,96,1.0,1,5,Rural,Data Analyst,25680,0 +101015,Female,42,Diploma,13,76,65,86,66,0.0,2,55,Rural,ML Engineer,84153,1 +101016,Male,41,High School,2,88,22,1,80,8.0,1,92,Urban,ML Engineer,46460,0 +101017,Other,52,Masters,3,29,86,61,40,3.0,1,24,Urban,ML Engineer,143436,0 +101018,Female,57,Bachelors,11,26,74,94,28,9.0,2,64,Semi-Urban,Manager,139448,1 +101019,Female,28,High School,6,97,1,67,81,7.0,4,56,Rural,Data Analyst,123809,0 +101020,Male,49,High School,14,53,25,35,81,7.0,0,67,Urban,Manager,148986,0 +101021,Female,36,Bachelors,16,99,98,17,52,3.0,3,35,Urban,HR Executive,103057,1 +101022,Male,22,Diploma,10,72,31,85,20,8.0,2,90,Semi-Urban,Software Engineer,139478,1 +101023,Male,43,Bachelors,10,58,52,0,84,0.0,1,81,Semi-Urban,Software Engineer,30449,0 +101024,Male,39,High School,1,93,82,41,52,6.0,6,47,Semi-Urban,ML Engineer,57028,1 +101025,Male,46,High School,5,62,40,79,6,1.0,2,54,Urban,ML Engineer,92842,1 +101026,Male,58,High School,7,99,50,53,89,1.0,4,91,Rural,Data Analyst,20847,1 +101027,Male,48,Bachelors,4,48,7,59,0,7.0,3,5,Urban,ML Engineer,57802,0 +101028,Male,31,Bachelors,2,35,8,49,74,7.0,5,71,Urban,ML Engineer,107839,0 +101029,Female,31,Diploma,10,59,36,1,52,4.0,7,0,Urban,Data Analyst,45560,0 +101030,Male,50,Diploma,14,13,56,8,71,7.0,3,6,Semi-Urban,Software Engineer,133540,0 +101031,Male,45,Diploma,18,81,30,42,22,0.0,4,38,Semi-Urban,HR Executive,102877,0 +101032,Male,40,Bachelors,7,1,38,48,60,7.0,6,81,Semi-Urban,Software Engineer,68554,0 +101033,Female,57,Diploma,0,99,34,35,49,6.0,7,38,Semi-Urban,HR Executive,112130,0 +101034,Male,47,Bachelors,2,4,30,92,48,2.0,4,95,Rural,Manager,116873,0 +101035,Female,59,Masters,1,15,60,1,32,1.0,4,9,Urban,Manager,77590,0 +101036,Male,41,Diploma,0,31,70,1,18,6.0,4,2,Rural,Data Analyst,146237,0 +101037,Male,32,Masters,14,1,11,30,88,1.0,7,28,Rural,ML Engineer,128775,0 +101038,Male,46,Masters,6,70,92,4,19,3.0,4,81,Rural,Software Engineer,61075,1 +101039,Female,44,Masters,2,76,59,74,75,9.0,3,82,Rural,ML Engineer,109807,1 +101040,Male,53,High School,7,90,44,54,22,7.0,7,34,Urban,Software Engineer,39308,0 +101041,Female,24,Masters,13,90,85,51,37,9.0,7,96,Urban,Data Analyst,55221,1 +101042,Male,46,PhD,12,41,97,14,59,6.0,7,37,Urban,HR Executive,36906,0 +101043,Male,58,Diploma,3,88,1,5,23,4.0,0,97,Urban,Data Analyst,62296,0 +101044,Male,39,Bachelors,3,51,2,0,66,9.0,6,66,Semi-Urban,Data Analyst,143661,0 +101045,Male,36,Masters,7,53,70,58,87,7.0,6,67,Urban,HR Executive,44136,1 +101046,Male,39,Bachelors,3,45,42,23,11,9.0,1,11,Semi-Urban,Software Engineer,39144,0 +101047,Male,34,Bachelors,2,16,94,90,67,8.0,1,20,Urban,Data Analyst,57628,0 +101048,Male,35,Bachelors,17,34,47,16,55,5.0,3,93,Rural,Software Engineer,148981,0 +101049,Male,37,Masters,2,56,88,97,40,3.0,6,22,Urban,HR Executive,89537,1 +101050,Female,49,Bachelors,8,17,55,53,10,0.0,0,16,Rural,Software Engineer,88025,0 +101051,Male,22,Diploma,1,6,90,21,58,0.0,7,60,Urban,Data Analyst,37310,0 +101052,Female,45,Bachelors,13,90,72,40,1,8.0,5,77,Urban,HR Executive,136480,1 +101053,Male,58,Bachelors,15,90,73,92,78,8.0,6,47,Semi-Urban,Data Analyst,94303,1 +101054,Male,52,Bachelors,1,60,49,19,32,0.0,6,64,Urban,Data Analyst,80683,0 +101055,Male,39,Masters,16,83,77,88,11,7.0,3,14,Urban,Data Analyst,90023,1 +101056,Male,37,Diploma,18,85,99,85,12,2.0,0,31,Urban,Data Analyst,87930,1 +101057,Female,40,High School,2,5,15,62,39,5.0,7,23,Urban,Software Engineer,69065,0 +101058,Other,37,Diploma,19,61,18,62,36,3.0,6,97,Rural,HR Executive,57120,0 +101059,Other,33,Masters,14,87,66,38,28,6.0,0,56,Urban,Software Engineer,99324,1 +101060,Female,53,Masters,4,74,17,82,67,7.0,4,97,Semi-Urban,Data Analyst,120280,1 +101061,Male,21,Bachelors,9,9,76,63,12,9.0,5,21,Urban,Data Analyst,25240,0 +101062,Male,52,Masters,12,16,99,40,15,0.0,5,76,Urban,HR Executive,45941,0 +101063,Male,37,Bachelors,13,5,84,75,8,2.0,0,17,Semi-Urban,HR Executive,93262,0 +101064,Male,25,Bachelors,15,70,67,83,77,3.0,3,10,Semi-Urban,Software Engineer,145806,0 +101065,Female,36,Diploma,3,74,20,22,52,1.0,7,90,Urban,Manager,133913,0 +101066,Male,36,Diploma,6,34,16,34,7,4.0,6,78,Urban,Data Analyst,100138,0 +101067,Female,32,Masters,3,31,35,7,75,2.0,0,57,Urban,Manager,114727,0 +101068,Male,55,Bachelors,10,49,50,70,68,0.0,1,6,Urban,HR Executive,139200,0 +101069,Male,45,Masters,0,67,1,98,16,3.0,7,80,Semi-Urban,HR Executive,50733,1 +101070,Male,33,Masters,19,69,44,96,23,8.0,6,15,Urban,ML Engineer,115932,0 +101071,Female,57,Bachelors,19,37,86,73,81,6.0,0,59,Urban,Software Engineer,107157,1 +101072,Female,38,Bachelors,5,77,16,93,12,1.0,0,47,Urban,Data Analyst,35395,0 +101073,Male,27,PhD,6,31,27,1,81,9.0,4,3,Urban,ML Engineer,44943,0 +101074,Male,55,High School,6,31,94,8,97,2.0,0,88,Urban,Data Analyst,127471,0 +101075,Other,33,Masters,11,61,57,17,41,0.0,3,11,Rural,Data Analyst,22184,0 +101076,Other,50,Masters,10,27,60,48,44,1.0,3,97,Rural,HR Executive,137789,0 +101077,Female,42,Masters,9,41,35,31,85,2.0,7,56,Rural,Software Engineer,118391,0 +101078,Male,38,High School,8,86,4,11,74,2.0,3,25,Urban,HR Executive,35532,0 +101079,Female,38,Diploma,8,54,72,16,22,4.0,7,93,Semi-Urban,Data Analyst,21753,0 +101080,Male,52,High School,15,17,31,94,78,3.0,0,35,Urban,Software Engineer,106189,0 +101081,Female,27,Diploma,0,9,38,68,98,4.0,2,69,Urban,Data Analyst,123364,0 +101082,Male,55,Bachelors,1,73,84,71,82,6.0,3,56,Semi-Urban,HR Executive,118375,1 +101083,Male,21,Bachelors,3,6,13,92,99,8.0,4,52,Urban,ML Engineer,43215,0 +101084,Male,52,Masters,3,58,25,85,16,6.0,3,7,Rural,Software Engineer,83977,0 +101085,Female,56,Masters,10,16,4,63,54,5.0,3,11,Rural,Software Engineer,74619,0 +101086,Male,34,High School,0,25,39,62,48,9.0,4,10,Urban,Data Analyst,100101,0 +101087,Female,23,Bachelors,13,93,61,75,13,7.0,1,22,Urban,HR Executive,137399,1 +101088,Male,43,Masters,3,42,49,51,45,7.0,1,73,Rural,HR Executive,28030,0 +101089,Male,48,Bachelors,1,82,30,1,83,4.0,4,21,Rural,Manager,147555,0 +101090,Female,39,Masters,5,34,89,76,74,0.0,5,30,Semi-Urban,HR Executive,53704,0 +101091,Male,43,High School,11,13,10,42,83,1.0,6,51,Rural,Software Engineer,44436,0 +101092,Female,54,Masters,2,47,51,52,10,6.0,7,34,Semi-Urban,Manager,131696,0 +101093,Male,33,Bachelors,9,32,56,12,58,8.0,7,52,Urban,Data Analyst,130146,0 +101094,Male,54,Diploma,16,26,20,62,55,3.0,5,66,Urban,ML Engineer,136295,0 +101095,Female,26,Diploma,9,16,33,9,80,4.0,6,22,Urban,Manager,31844,0 +101096,Other,30,Bachelors,9,66,48,21,14,1.0,6,30,Semi-Urban,Manager,106955,0 +101097,Female,24,Diploma,9,71,25,68,52,4.0,4,8,Semi-Urban,Data Analyst,100426,0 +101098,Male,55,Bachelors,13,21,26,46,84,9.0,7,63,Semi-Urban,HR Executive,90184,0 +101099,Male,44,Masters,11,70,36,95,50,6.0,2,86,Semi-Urban,Manager,27066,1 +101100,Male,47,Bachelors,1,32,49,28,83,9.0,6,82,Urban,Software Engineer,59746,0 +101101,Female,57,Bachelors,17,13,71,29,60,5.0,1,16,Urban,HR Executive,44494,0 +101102,Male,32,Bachelors,1,99,95,62,24,1.0,0,62,Urban,Data Analyst,40344,1 +101103,Male,49,Bachelors,9,91,24,58,45,0.0,0,95,Urban,Manager,89052,1 +101104,Female,22,Bachelors,5,46,81,19,13,9.0,1,10,Rural,Data Analyst,66825,0 +101105,Female,27,Bachelors,19,19,40,37,53,7.0,6,88,Urban,Manager,79828,0 +101106,Female,24,Diploma,12,51,54,26,57,4.0,2,19,Semi-Urban,Manager,22218,0 +101107,Male,23,Bachelors,19,86,41,34,65,3.0,2,82,Urban,Software Engineer,119172,1 +101108,Male,54,Bachelors,11,19,94,24,82,0.0,5,31,Urban,Data Analyst,55988,0 +101109,Male,30,Bachelors,4,76,34,75,52,4.0,5,58,Urban,HR Executive,132058,1 +101110,Male,34,Bachelors,0,13,7,47,44,8.0,7,57,Urban,ML Engineer,56188,0 +101111,Male,42,Masters,13,71,68,97,82,1.0,6,31,Rural,Software Engineer,104251,1 +101112,Male,43,Masters,16,87,68,13,95,0.0,6,85,Urban,Data Analyst,54895,1 +101113,Male,53,Bachelors,5,49,81,21,53,0.0,4,87,Semi-Urban,Software Engineer,37844,1 +101114,Male,40,Diploma,3,98,26,49,93,0.0,2,40,Semi-Urban,ML Engineer,55708,0 +101115,Male,42,Bachelors,14,7,98,38,37,5.0,0,37,Urban,Data Analyst,30049,0 +101116,Male,41,Masters,17,41,43,30,3,3.0,7,59,Semi-Urban,ML Engineer,39776,0 +101117,Male,27,Masters,2,53,16,35,70,3.0,6,47,Rural,ML Engineer,118149,0 +101118,Male,21,Bachelors,9,3,69,18,20,0.0,3,27,Urban,ML Engineer,25812,0 +101119,Male,59,Masters,10,85,37,77,53,7.0,4,31,Semi-Urban,HR Executive,74185,0 +101120,Male,36,Masters,1,29,28,13,24,6.0,5,41,Urban,ML Engineer,68753,0 +101121,Female,51,High School,16,43,32,71,30,3.0,0,98,Urban,ML Engineer,29372,1 +101122,Male,51,Masters,8,46,99,61,6,0.0,0,23,Urban,Data Analyst,94883,0 +101123,Female,46,Masters,8,38,98,34,76,9.0,1,55,Semi-Urban,ML Engineer,138964,0 +101124,Female,49,High School,18,54,84,48,10,9.0,0,73,Urban,Manager,133609,1 +101125,Female,25,Diploma,13,89,39,83,25,4.0,5,35,Urban,HR Executive,136448,1 +101126,Male,43,Diploma,5,56,98,13,92,4.0,4,83,Rural,Data Analyst,81441,1 +101127,Male,39,Bachelors,15,41,72,24,0,7.0,0,2,Semi-Urban,Manager,123040,0 +101128,Male,22,Bachelors,10,15,50,50,57,0.0,7,54,Urban,Data Analyst,49398,0 +101129,Female,31,Bachelors,17,36,39,30,24,6.0,2,59,Urban,Software Engineer,45118,0 +101130,Female,59,High School,17,10,80,36,5,2.0,6,23,Semi-Urban,HR Executive,20889,0 +101131,Male,37,Diploma,17,53,49,59,47,0.0,7,33,Urban,Data Analyst,60769,0 +101132,Female,38,High School,4,80,48,57,98,0.0,4,68,Semi-Urban,ML Engineer,52110,1 +101133,Female,51,PhD,11,91,34,15,75,3.0,0,11,Rural,Software Engineer,66823,0 +101134,Female,54,PhD,17,75,22,47,51,2.0,7,20,Semi-Urban,ML Engineer,81476,0 +101135,Female,48,Bachelors,4,44,10,25,88,9.0,1,41,Semi-Urban,Software Engineer,30536,0 +101136,Male,37,Bachelors,18,2,76,20,7,2.0,3,19,Urban,ML Engineer,104044,0 +101137,Female,52,Masters,5,36,21,4,71,7.0,1,65,Urban,Data Analyst,75421,0 +101138,Male,58,High School,14,36,79,60,18,3.0,0,75,Urban,Software Engineer,111655,1 +101139,Female,43,High School,1,58,51,15,9,9.0,7,84,Rural,HR Executive,53898,0 +101140,Male,49,Diploma,12,4,53,26,78,7.0,0,26,Urban,Data Analyst,128357,0 +101141,Male,58,Diploma,9,11,12,84,52,1.0,3,73,Urban,Manager,57832,0 +101142,Male,42,Diploma,17,23,75,9,50,4.0,0,38,Rural,Data Analyst,110692,0 +101143,Male,24,High School,5,88,0,49,13,1.0,2,36,Urban,HR Executive,114534,0 +101144,Male,49,Bachelors,11,87,5,76,20,1.0,0,90,Urban,ML Engineer,85735,1 +101145,Male,22,Masters,6,26,57,71,96,0.0,3,73,Rural,ML Engineer,79847,0 +101146,Male,40,Bachelors,17,60,87,38,2,2.0,2,22,Urban,Software Engineer,139176,0 +101147,Male,31,PhD,0,83,30,47,76,5.0,0,82,Urban,Data Analyst,142703,1 +101148,Female,46,High School,12,30,72,52,28,0.0,6,77,Semi-Urban,Data Analyst,106615,0 +101149,Male,32,Diploma,12,65,43,1,79,0.0,4,26,Urban,Data Analyst,128872,0 +101150,Female,46,Bachelors,15,55,35,94,51,2.0,7,33,Urban,Software Engineer,108049,0 +101151,Male,30,Diploma,7,31,47,1,3,6.0,0,39,Urban,ML Engineer,94327,0 +101152,Male,23,Bachelors,7,71,94,87,11,9.0,1,75,Urban,Software Engineer,53065,1 +101153,Male,36,Diploma,2,66,31,77,28,2.0,6,90,Urban,ML Engineer,27280,1 +101154,Male,39,Bachelors,16,17,65,64,60,1.0,1,47,Urban,ML Engineer,129154,0 +101155,Male,33,High School,17,83,66,86,49,3.0,6,9,Rural,ML Engineer,30810,1 +101156,Male,29,Masters,0,81,86,3,80,4.0,5,34,Urban,Data Analyst,136909,0 +101157,Male,25,Bachelors,18,29,78,82,39,7.0,4,38,Rural,Software Engineer,20993,0 +101158,Male,52,Masters,14,31,27,37,27,4.0,7,31,Urban,Data Analyst,129921,0 +101159,Female,27,Bachelors,3,14,7,97,26,0.0,7,53,Semi-Urban,HR Executive,128848,0 +101160,Female,30,Bachelors,1,7,45,75,97,5.0,0,51,Urban,HR Executive,114439,0 +101161,Male,28,Bachelors,14,32,89,61,87,3.0,2,90,Semi-Urban,Data Analyst,83736,1 +101162,Male,37,Diploma,7,8,59,69,14,5.0,5,23,Urban,Data Analyst,146238,0 +101163,Female,44,Bachelors,13,15,28,50,61,7.0,6,82,Rural,ML Engineer,102067,0 +101164,Male,48,Bachelors,13,76,6,74,11,9.0,7,96,Semi-Urban,ML Engineer,117776,1 +101165,Male,53,Bachelors,10,26,49,67,49,9.0,7,47,Urban,Data Analyst,25723,0 +101166,Male,55,High School,2,37,78,25,35,6.0,1,45,Urban,HR Executive,109215,0 +101167,Male,28,Diploma,17,88,38,45,13,6.0,2,50,Urban,ML Engineer,104368,0 +101168,Female,32,Bachelors,15,79,71,46,13,4.0,0,32,Rural,HR Executive,109226,0 +101169,Male,53,Bachelors,11,75,12,30,48,4.0,3,65,Urban,ML Engineer,101238,0 +101170,Female,40,Bachelors,8,42,58,67,70,7.0,4,18,Rural,Manager,128654,0 +101171,Male,32,Bachelors,13,3,89,16,69,1.0,5,94,Urban,ML Engineer,99765,0 +101172,Female,33,High School,13,71,99,93,55,5.0,1,25,Semi-Urban,HR Executive,118692,1 +101173,Female,42,Diploma,2,75,9,34,63,9.0,1,79,Semi-Urban,Software Engineer,119887,0 +101174,Female,50,Diploma,19,76,10,30,85,1.0,3,38,Semi-Urban,Software Engineer,54117,0 +101175,Male,54,Diploma,15,21,41,20,42,9.0,4,56,Urban,ML Engineer,63690,0 +101176,Male,52,Masters,18,29,8,53,46,7.0,4,7,Rural,HR Executive,148518,0 +101177,Male,35,Bachelors,5,82,21,22,92,6.0,6,37,Urban,Software Engineer,31580,0 +101178,Male,59,Diploma,18,24,7,28,14,5.0,1,44,Rural,ML Engineer,73510,0 +101179,Female,55,Masters,5,12,85,58,77,9.0,3,67,Urban,Manager,106643,0 +101180,Female,56,Bachelors,3,12,80,18,88,6.0,0,49,Urban,Data Analyst,94388,0 +101181,Female,22,Masters,7,40,38,7,47,8.0,1,93,Urban,Software Engineer,99464,0 +101182,Male,34,Bachelors,11,27,31,15,83,1.0,4,4,Urban,Software Engineer,62494,0 +101183,Male,53,Masters,1,94,79,6,30,8.0,0,16,Rural,Software Engineer,72986,0 +101184,Female,39,Bachelors,14,51,24,39,67,8.0,5,46,Rural,ML Engineer,23724,0 +101185,Male,58,Masters,5,47,19,54,58,0.0,1,79,Urban,Software Engineer,64164,0 +101186,Female,41,Diploma,4,97,79,57,44,2.0,5,44,Urban,ML Engineer,70152,1 +101187,Male,24,Diploma,5,56,55,31,85,7.0,0,43,Rural,ML Engineer,49115,0 +101188,Male,21,Bachelors,5,64,16,73,97,8.0,5,28,Semi-Urban,ML Engineer,31299,0 +101189,Male,59,High School,5,53,30,98,14,6.0,2,1,Urban,Software Engineer,83096,0 +101190,Female,41,Masters,17,96,9,61,13,1.0,0,77,Urban,HR Executive,140618,1 +101191,Male,34,Masters,14,40,22,65,82,9.0,6,63,Rural,Software Engineer,72473,0 +101192,Male,50,Bachelors,10,47,4,34,45,2.0,2,25,Semi-Urban,Software Engineer,80234,0 +101193,Female,22,Diploma,5,10,57,98,81,2.0,0,9,Urban,Manager,33527,0 +101194,Male,50,Bachelors,5,9,9,56,70,6.0,4,73,Urban,Manager,62051,0 +101195,Male,31,High School,13,21,29,58,76,1.0,1,60,Rural,HR Executive,122630,0 +101196,Female,23,Bachelors,4,92,8,1,21,4.0,5,0,Semi-Urban,HR Executive,112910,0 +101197,Female,42,Diploma,18,25,47,69,29,2.0,0,98,Urban,HR Executive,79384,0 +101198,Male,39,Bachelors,17,43,29,96,56,7.0,7,65,Rural,Data Analyst,124695,0 +101199,Female,48,Diploma,5,35,6,18,9,8.0,1,44,Urban,ML Engineer,144748,0 +101200,Female,48,Masters,16,38,29,96,94,8.0,6,73,Urban,HR Executive,145063,0 +101201,Male,23,High School,6,30,83,42,61,4.0,6,22,Semi-Urban,Manager,133719,0 +101202,Male,53,Bachelors,16,91,84,88,18,5.0,7,50,Rural,Manager,43096,1 +101203,Male,58,Bachelors,14,23,87,54,4,0.0,3,15,Urban,ML Engineer,27154,0 +101204,Female,58,Bachelors,16,7,64,46,54,0.0,4,26,Urban,HR Executive,97602,0 +101205,Female,56,Bachelors,11,52,95,87,32,3.0,5,30,Urban,Software Engineer,130963,1 +101206,Other,54,Bachelors,15,97,39,86,19,2.0,2,26,Semi-Urban,Manager,113555,1 +101207,Female,31,Bachelors,16,81,86,95,87,1.0,2,9,Urban,ML Engineer,40663,1 +101208,Male,21,Masters,12,19,28,64,65,8.0,6,18,Urban,HR Executive,67386,0 +101209,Female,51,Bachelors,15,84,62,77,64,0.0,5,74,Urban,Manager,117610,1 +101210,Male,29,Bachelors,5,98,18,47,37,8.0,1,55,Urban,Data Analyst,25881,0 +101211,Female,48,Bachelors,8,32,73,52,90,7.0,4,9,Urban,Manager,37581,0 +101212,Male,35,Masters,1,55,52,0,8,3.0,1,49,Urban,HR Executive,55413,0 +101213,Female,36,Bachelors,11,73,2,84,48,1.0,3,17,Semi-Urban,HR Executive,125625,0 +101214,Female,50,High School,12,95,95,16,46,4.0,5,51,Urban,Data Analyst,134135,1 +101215,Male,25,Bachelors,9,26,5,14,68,8.0,6,3,Semi-Urban,Data Analyst,66629,0 +101216,Female,49,PhD,1,29,56,42,6,9.0,3,17,Urban,Software Engineer,139425,0 +101217,Female,43,High School,1,73,38,56,35,5.0,4,23,Urban,Manager,105801,0 +101218,Male,33,Bachelors,11,70,56,6,8,3.0,7,81,Semi-Urban,Data Analyst,141889,0 +101219,Male,22,Diploma,9,53,77,69,44,5.0,1,61,Urban,Manager,61641,1 +101220,Male,56,Bachelors,15,60,19,98,11,5.0,3,26,Rural,HR Executive,39776,0 +101221,Female,55,Bachelors,1,94,58,81,36,7.0,5,51,Rural,Manager,114572,1 +101222,Other,39,Masters,0,13,43,79,68,9.0,3,0,Rural,HR Executive,47662,0 +101223,Male,29,Masters,15,33,82,67,19,8.0,4,3,Semi-Urban,ML Engineer,55517,0 +101224,Male,28,Masters,7,22,97,94,66,9.0,6,4,Urban,Software Engineer,104240,0 +101225,Male,55,Bachelors,9,63,86,11,65,9.0,5,15,Rural,Software Engineer,120793,0 +101226,Female,47,Bachelors,18,82,73,46,74,3.0,2,93,Urban,Software Engineer,109085,1 +101227,Female,31,Bachelors,12,73,34,13,45,2.0,0,0,Semi-Urban,HR Executive,140099,0 +101228,Male,41,Bachelors,18,29,15,78,29,3.0,7,22,Semi-Urban,ML Engineer,51287,0 +101229,Male,43,Diploma,19,14,15,52,94,5.0,5,12,Rural,ML Engineer,145871,0 +101230,Male,52,Masters,4,31,43,97,35,2.0,6,74,Rural,ML Engineer,64254,1 +101231,Male,32,Bachelors,13,52,53,15,0,6.0,4,63,Urban,Data Analyst,68283,0 +101232,Female,40,PhD,17,7,85,88,69,3.0,1,34,Urban,ML Engineer,57126,0 +101233,Male,47,Bachelors,2,94,5,12,97,6.0,3,47,Semi-Urban,Software Engineer,54171,0 +101234,Male,29,Diploma,8,17,62,14,94,0.0,6,25,Urban,Data Analyst,63184,0 +101235,Female,53,High School,5,63,66,9,47,4.0,2,5,Rural,Software Engineer,57083,0 +101236,Male,27,Bachelors,10,36,7,7,8,6.0,7,27,Urban,HR Executive,65231,0 +101237,Male,51,Diploma,12,66,20,30,84,4.0,2,6,Urban,ML Engineer,119701,0 +101238,Male,41,PhD,1,4,67,84,82,4.0,2,44,Urban,Manager,132675,0 +101239,Female,35,Diploma,17,18,21,10,51,6.0,2,82,Semi-Urban,Manager,147223,0 +101240,Female,40,Bachelors,17,43,14,43,98,3.0,5,81,Urban,Software Engineer,125343,0 +101241,Male,37,Diploma,19,31,62,55,15,4.0,1,13,Semi-Urban,Software Engineer,140470,0 +101242,Male,52,Masters,9,20,1,95,85,7.0,1,74,Urban,Data Analyst,119004,0 +101243,Female,42,Diploma,17,54,82,49,96,4.0,2,45,Rural,ML Engineer,33194,0 +101244,Male,30,Masters,8,93,1,35,31,7.0,4,62,Rural,Software Engineer,63035,0 +101245,Male,29,Masters,17,70,41,97,26,4.0,7,82,Urban,Manager,94373,1 +101246,Male,33,Bachelors,19,45,44,12,80,7.0,1,29,Rural,ML Engineer,68476,0 +101247,Male,23,Bachelors,6,91,96,7,34,6.0,7,85,Urban,Data Analyst,84585,1 +101248,Male,45,Bachelors,18,94,57,89,41,7.0,3,33,Urban,Data Analyst,62860,1 +101249,Female,35,Bachelors,12,63,33,33,11,7.0,3,13,Rural,Data Analyst,37641,0 +101250,Male,29,Bachelors,9,68,96,73,68,6.0,6,67,Urban,Manager,85522,1 +101251,Female,34,Bachelors,7,77,30,82,56,0.0,6,58,Semi-Urban,Software Engineer,134360,1 +101252,Male,50,Bachelors,10,41,7,69,54,2.0,6,85,Urban,ML Engineer,119939,0 +101253,Male,51,Diploma,18,22,3,94,31,3.0,4,55,Semi-Urban,ML Engineer,101585,0 +101254,Male,31,High School,8,34,33,35,61,5.0,5,73,Rural,HR Executive,138204,0 +101255,Other,38,High School,11,55,72,27,24,7.0,4,84,Urban,HR Executive,132559,0 +101256,Male,23,Bachelors,14,26,4,55,49,7.0,0,19,Semi-Urban,Software Engineer,55704,0 +101257,Male,37,Masters,12,10,38,78,63,1.0,2,83,Urban,HR Executive,71898,0 +101258,Female,21,Masters,4,95,71,17,60,8.0,5,52,Urban,Data Analyst,70974,0 +101259,Male,43,Bachelors,9,43,6,64,94,1.0,1,96,Rural,HR Executive,100407,0 +101260,Male,27,Bachelors,5,44,61,11,28,4.0,2,27,Urban,Software Engineer,138001,0 +101261,Female,42,High School,15,52,93,32,4,8.0,0,44,Urban,ML Engineer,22501,0 +101262,Male,57,Bachelors,18,37,59,99,32,8.0,3,23,Urban,Data Analyst,22191,0 +101263,Male,24,Diploma,11,66,22,88,0,0.0,1,50,Semi-Urban,HR Executive,119943,0 +101264,Male,43,High School,6,20,51,43,45,8.0,2,35,Urban,Data Analyst,118990,0 +101265,Male,35,Diploma,14,54,9,6,77,1.0,3,92,Rural,Software Engineer,78916,0 +101266,Male,28,High School,4,61,15,85,43,3.0,5,88,Urban,Manager,92920,1 +101267,Male,47,PhD,14,21,81,93,60,5.0,6,87,Urban,Software Engineer,86519,1 +101268,Male,27,High School,4,10,70,5,99,7.0,7,99,Urban,Software Engineer,45905,0 +101269,Male,52,Bachelors,5,90,96,15,28,1.0,3,81,Urban,Manager,32648,1 +101270,Female,39,Diploma,6,85,19,18,72,9.0,4,50,Urban,ML Engineer,147746,0 +101271,Female,41,Bachelors,6,42,64,1,48,1.0,7,28,Urban,Manager,114592,0 +101272,Male,26,Bachelors,13,91,17,46,71,9.0,1,38,Urban,Manager,86294,0 +101273,Male,31,Bachelors,17,67,8,71,80,1.0,2,56,Semi-Urban,Software Engineer,39467,0 +101274,Male,33,Bachelors,13,56,12,41,19,3.0,1,2,Urban,Software Engineer,77804,0 +101275,Male,35,Bachelors,16,54,38,3,77,0.0,5,98,Urban,Manager,115697,0 +101276,Female,21,High School,15,60,96,52,36,3.0,6,26,Urban,Software Engineer,57571,0 +101277,Male,25,Masters,6,67,30,69,5,2.0,6,43,Urban,HR Executive,122779,0 +101278,Female,32,Masters,3,67,85,47,40,5.0,1,66,Urban,HR Executive,128870,1 +101279,Male,23,Bachelors,4,62,78,72,28,9.0,5,24,Urban,HR Executive,94710,1 +101280,Female,32,Bachelors,17,67,94,78,96,6.0,3,87,Urban,Data Analyst,96485,1 +101281,Female,45,Bachelors,12,37,92,80,47,6.0,2,77,Rural,Data Analyst,35313,1 +101282,Female,37,High School,8,84,2,17,11,1.0,3,99,Semi-Urban,Manager,120994,0 +101283,Male,31,PhD,14,97,54,70,73,7.0,6,30,Urban,HR Executive,55658,1 +101284,Male,47,Bachelors,4,38,89,49,96,9.0,7,46,Semi-Urban,HR Executive,119790,0 +101285,Male,35,High School,14,63,9,95,62,6.0,6,71,Semi-Urban,Data Analyst,49500,1 +101286,Female,42,Diploma,17,92,83,46,52,3.0,2,72,Urban,Software Engineer,57050,1 +101287,Male,30,Bachelors,10,35,76,27,34,9.0,0,36,Urban,Data Analyst,143414,0 +101288,Male,40,High School,5,1,60,42,56,5.0,7,18,Rural,Manager,57398,0 +101289,Male,44,Diploma,10,21,12,56,4,0.0,3,29,Urban,ML Engineer,25835,0 +101290,Female,35,Masters,7,76,87,75,7,0.0,2,9,Urban,HR Executive,86715,1 +101291,Female,50,Bachelors,13,44,62,33,10,9.0,5,86,Rural,Manager,64191,0 +101292,Female,41,Masters,9,90,73,41,80,6.0,3,73,Semi-Urban,Manager,114522,1 +101293,Male,32,Diploma,3,29,39,58,58,8.0,1,97,Urban,HR Executive,33103,0 +101294,Male,28,Bachelors,18,81,38,66,8,7.0,3,53,Semi-Urban,ML Engineer,27448,1 +101295,Male,34,Bachelors,5,90,88,98,62,7.0,7,32,Urban,Manager,61549,1 +101296,Male,21,Bachelors,14,55,4,69,98,6.0,7,77,Urban,Manager,55816,0 +101297,Female,43,Masters,18,40,68,79,44,3.0,4,75,Semi-Urban,ML Engineer,66404,1 +101298,Male,29,Diploma,13,16,47,87,11,3.0,4,26,Urban,HR Executive,22739,0 +101299,Female,51,Bachelors,12,10,72,34,46,1.0,0,9,Semi-Urban,HR Executive,52614,0 +101300,Female,25,Masters,4,46,5,66,12,3.0,0,83,Urban,Data Analyst,143117,0 +101301,Female,40,Bachelors,5,70,22,44,72,4.0,6,69,Rural,ML Engineer,144347,0 +101302,Male,22,Masters,9,14,55,27,20,5.0,7,32,Urban,ML Engineer,71139,0 +101303,Female,27,Bachelors,6,10,65,37,58,4.0,1,77,Urban,Data Analyst,28535,0 +101304,Male,52,Diploma,9,94,89,37,6,7.0,4,20,Semi-Urban,Manager,143912,1 +101305,Other,22,Bachelors,10,61,58,70,22,6.0,4,69,Semi-Urban,Software Engineer,119592,1 +101306,Female,31,Masters,13,41,58,54,70,2.0,3,22,Semi-Urban,HR Executive,91391,0 +101307,Male,59,Diploma,2,6,45,65,45,5.0,0,16,Urban,HR Executive,65436,0 +101308,Female,33,Diploma,6,82,20,21,22,7.0,5,83,Urban,Manager,116425,0 +101309,Female,54,High School,18,53,14,60,9,7.0,4,79,Urban,Manager,95927,0 +101310,Female,52,Bachelors,12,51,55,33,22,5.0,0,13,Urban,ML Engineer,70166,0 +101311,Male,59,Bachelors,15,43,17,5,32,9.0,3,27,Urban,HR Executive,129695,0 +101312,Male,40,High School,14,54,39,70,24,3.0,3,55,Rural,Software Engineer,42295,0 +101313,Female,50,Bachelors,0,45,47,99,31,2.0,3,5,Urban,Software Engineer,129048,0 +101314,Female,24,Bachelors,17,52,80,4,94,9.0,4,52,Urban,HR Executive,103997,0 +101315,Male,59,Masters,12,40,10,39,66,3.0,3,6,Urban,ML Engineer,119098,0 +101316,Male,29,High School,2,98,48,30,74,5.0,4,84,Semi-Urban,Manager,29822,1 +101317,Male,38,Masters,17,99,71,16,77,5.0,2,54,Semi-Urban,Data Analyst,116693,1 +101318,Male,51,Bachelors,12,85,99,5,75,8.0,5,80,Rural,Data Analyst,118587,1 +101319,Male,55,Bachelors,15,61,36,16,35,7.0,4,11,Semi-Urban,Software Engineer,125087,0 +101320,Male,24,Bachelors,10,61,99,52,66,3.0,1,39,Urban,Software Engineer,129402,1 +101321,Female,31,Bachelors,11,7,22,78,94,8.0,6,98,Urban,Data Analyst,124628,0 +101322,Male,27,High School,2,63,23,99,35,3.0,5,22,Semi-Urban,Data Analyst,45823,0 +101323,Male,48,Bachelors,17,89,65,67,51,4.0,0,6,Urban,ML Engineer,142460,0 +101324,Other,47,Bachelors,6,61,20,63,5,1.0,7,5,Urban,Data Analyst,120148,0 +101325,Female,24,Bachelors,5,25,93,22,77,0.0,1,37,Urban,ML Engineer,27653,0 +101326,Male,49,Diploma,1,13,28,18,6,9.0,0,49,Urban,Data Analyst,148186,0 +101327,Male,51,Bachelors,17,88,86,54,47,4.0,1,1,Semi-Urban,Manager,63755,0 +101328,Male,44,Masters,13,83,5,41,40,4.0,1,8,Semi-Urban,Data Analyst,28377,0 +101329,Female,33,Bachelors,7,36,22,11,78,1.0,6,32,Rural,Software Engineer,49809,0 +101330,Female,49,PhD,3,4,63,90,16,6.0,7,50,Semi-Urban,Software Engineer,35178,0 +101331,Male,25,Diploma,15,69,60,93,69,8.0,6,7,Rural,Manager,87788,0 +101332,Male,44,Masters,12,62,57,28,29,3.0,1,29,Semi-Urban,HR Executive,65563,0 +101333,Male,23,Masters,13,9,62,58,57,8.0,3,48,Rural,ML Engineer,108156,0 +101334,Male,42,Masters,17,88,54,72,61,2.0,0,34,Urban,Data Analyst,30562,1 +101335,Female,43,High School,14,50,38,13,88,3.0,0,95,Rural,Data Analyst,29139,0 +101336,Female,47,Masters,11,1,59,79,86,5.0,4,57,Urban,HR Executive,128745,0 +101337,Male,35,Bachelors,18,63,35,64,58,9.0,3,28,Semi-Urban,Data Analyst,121520,0 +101338,Female,33,Bachelors,5,78,35,52,87,7.0,2,86,Rural,Manager,55703,1 +101339,Male,28,Bachelors,5,48,20,98,61,8.0,3,69,Urban,HR Executive,122759,1 +101340,Female,22,Bachelors,18,7,41,38,65,1.0,6,64,Urban,ML Engineer,52422,0 +101341,Male,56,Masters,10,24,22,80,50,2.0,6,32,Semi-Urban,Manager,59986,0 +101342,Male,53,High School,3,89,30,38,33,4.0,4,0,Rural,Data Analyst,134903,0 +101343,Male,50,Masters,9,36,79,67,86,0.0,6,32,Urban,Software Engineer,149185,0 +101344,Female,21,Diploma,6,8,94,51,62,4.0,2,46,Urban,HR Executive,68455,0 +101345,Male,39,Diploma,10,25,59,94,60,3.0,4,26,Rural,ML Engineer,30234,0 +101346,Female,29,Masters,14,25,78,75,55,1.0,1,69,Rural,Data Analyst,21897,1 +101347,Male,57,Diploma,3,80,38,44,3,3.0,4,10,Semi-Urban,HR Executive,44792,0 +101348,Male,50,Bachelors,8,64,72,19,2,3.0,0,85,Rural,ML Engineer,128024,1 +101349,Female,59,Diploma,15,72,68,96,75,6.0,7,86,Urban,Manager,108255,1 +101350,Male,37,Bachelors,13,35,40,60,47,3.0,2,21,Urban,ML Engineer,129012,0 +101351,Female,43,Bachelors,14,34,63,54,77,6.0,6,8,Urban,Manager,44647,0 +101352,Female,55,Bachelors,2,85,74,36,45,7.0,2,58,Urban,HR Executive,69508,1 +101353,Male,45,Bachelors,15,2,98,54,90,7.0,3,79,Semi-Urban,Data Analyst,72842,0 +101354,Male,27,Masters,5,73,20,51,71,9.0,7,15,Rural,Manager,75893,0 +101355,Male,58,Masters,11,92,20,31,6,5.0,6,79,Urban,Manager,125250,0 +101356,Male,38,Masters,0,41,24,26,80,6.0,3,41,Urban,Manager,89499,0 +101357,Female,53,Bachelors,8,94,9,6,59,7.0,3,93,Rural,Manager,63723,0 +101358,Male,57,Diploma,0,54,95,87,41,7.0,5,57,Urban,ML Engineer,108736,1 +101359,Male,30,High School,15,48,8,19,93,8.0,4,35,Urban,HR Executive,39460,0 +101360,Male,48,Bachelors,13,48,44,3,97,1.0,4,48,Semi-Urban,HR Executive,88307,0 +101361,Female,56,High School,14,88,87,13,68,8.0,5,91,Urban,Data Analyst,131653,1 +101362,Other,45,PhD,17,41,57,75,24,9.0,6,5,Urban,ML Engineer,64687,0 +101363,Male,25,Diploma,4,76,89,54,50,6.0,3,82,Urban,Data Analyst,119484,1 +101364,Male,28,Bachelors,0,43,14,51,1,2.0,5,97,Urban,Data Analyst,36881,0 +101365,Male,56,Bachelors,15,6,76,77,59,2.0,5,95,Urban,HR Executive,33799,1 +101366,Female,46,Bachelors,4,60,19,7,77,3.0,7,58,Rural,Software Engineer,146500,0 +101367,Female,56,Bachelors,5,24,82,49,95,2.0,1,20,Semi-Urban,Data Analyst,149841,0 +101368,Male,22,Diploma,4,42,62,83,43,7.0,4,57,Semi-Urban,Software Engineer,124456,1 +101369,Male,53,Bachelors,0,98,99,17,5,3.0,6,58,Urban,ML Engineer,45025,1 +101370,Female,39,High School,1,97,43,11,16,6.0,5,51,Semi-Urban,HR Executive,45930,0 +101371,Female,51,Bachelors,7,21,70,67,27,2.0,7,58,Semi-Urban,Data Analyst,20323,0 +101372,Male,37,Bachelors,18,60,20,60,48,3.0,4,60,Urban,ML Engineer,144378,0 +101373,Female,25,Bachelors,8,11,73,84,14,0.0,2,70,Semi-Urban,Manager,55390,0 +101374,Female,39,Bachelors,8,90,85,30,71,2.0,0,73,Urban,ML Engineer,30875,1 +101375,Male,25,High School,8,29,40,92,81,3.0,5,56,Urban,ML Engineer,118204,0 +101376,Female,44,Bachelors,3,6,18,67,24,5.0,0,46,Urban,ML Engineer,124625,0 +101377,Female,46,Masters,4,66,33,81,33,3.0,2,19,Urban,HR Executive,58511,0 +101378,Female,46,High School,0,84,42,29,55,1.0,4,11,Urban,Manager,94982,0 +101379,Male,57,Bachelors,3,50,62,69,93,0.0,7,80,Rural,Manager,149121,1 +101380,Male,36,Bachelors,12,66,17,59,70,2.0,3,76,Urban,Data Analyst,55021,0 +101381,Female,42,Bachelors,15,1,65,60,6,7.0,6,69,Rural,ML Engineer,69481,0 +101382,Male,54,High School,19,24,24,16,4,6.0,1,38,Urban,ML Engineer,20130,0 +101383,Male,42,Masters,15,32,87,90,43,5.0,1,87,Urban,HR Executive,140761,1 +101384,Male,48,High School,16,11,84,86,3,4.0,0,1,Urban,HR Executive,23109,0 +101385,Male,38,Bachelors,9,7,87,60,69,8.0,5,52,Urban,ML Engineer,92154,0 +101386,Female,54,Diploma,0,81,55,23,55,9.0,1,71,Semi-Urban,Manager,145396,0 +101387,Male,25,Diploma,1,3,64,93,11,9.0,6,61,Rural,Manager,118889,0 +101388,Male,49,Diploma,19,85,63,88,65,7.0,1,9,Rural,HR Executive,45272,1 +101389,Male,39,Masters,17,88,5,53,71,1.0,2,36,Semi-Urban,HR Executive,114852,0 +101390,Male,58,Bachelors,1,75,48,70,55,3.0,1,14,Urban,Software Engineer,93587,0 +101391,Female,22,Masters,12,73,53,99,38,6.0,5,4,Rural,ML Engineer,86297,0 +101392,Other,48,Bachelors,11,91,72,40,88,3.0,7,5,Urban,Software Engineer,128875,0 +101393,Female,55,Bachelors,15,79,30,91,89,8.0,5,18,Urban,Software Engineer,46305,0 +101394,Male,38,Bachelors,15,85,59,14,93,9.0,6,15,Semi-Urban,HR Executive,70072,0 +101395,Male,29,High School,7,23,49,61,25,6.0,2,60,Semi-Urban,Manager,148038,0 +101396,Male,30,High School,8,50,45,87,56,9.0,0,57,Urban,Manager,139189,1 +101397,Male,44,High School,0,78,31,58,83,6.0,5,33,Rural,HR Executive,141633,0 +101398,Male,39,Diploma,12,89,91,4,88,7.0,3,14,Urban,ML Engineer,60083,0 +101399,Male,45,Diploma,10,75,74,74,75,1.0,1,60,Urban,Manager,137105,1 +101400,Female,41,Bachelors,2,43,48,99,61,5.0,2,45,Urban,HR Executive,35622,0 +101401,Male,45,High School,17,89,36,19,24,4.0,0,14,Urban,Manager,45776,0 +101402,Male,33,Masters,2,85,35,36,85,6.0,7,71,Urban,HR Executive,48793,0 +101403,Female,54,Bachelors,13,3,3,89,40,5.0,2,47,Semi-Urban,Data Analyst,110680,0 +101404,Other,56,Bachelors,9,25,32,67,87,3.0,2,57,Urban,HR Executive,37455,0 +101405,Male,22,Masters,7,43,11,65,6,2.0,2,30,Semi-Urban,ML Engineer,38918,0 +101406,Female,31,Bachelors,15,94,23,54,75,4.0,3,67,Urban,HR Executive,135757,0 +101407,Female,43,Bachelors,14,47,65,35,47,8.0,1,61,Semi-Urban,ML Engineer,91181,0 +101408,Male,28,Masters,1,42,88,93,85,2.0,4,78,Urban,Data Analyst,31308,1 +101409,Female,54,Bachelors,3,74,24,51,87,2.0,5,78,Urban,ML Engineer,146259,0 +101410,Male,34,Bachelors,10,45,79,59,19,0.0,2,54,Semi-Urban,Data Analyst,143918,1 +101411,Female,29,Bachelors,11,3,29,87,38,4.0,2,30,Urban,Manager,31390,0 +101412,Male,51,Bachelors,2,16,59,78,1,6.0,7,43,Semi-Urban,HR Executive,105195,0 +101413,Male,43,Diploma,6,73,28,74,99,1.0,0,36,Semi-Urban,HR Executive,78902,0 +101414,Female,41,Bachelors,10,27,46,6,79,2.0,2,44,Semi-Urban,Manager,87649,0 +101415,Female,26,Bachelors,15,45,35,79,97,8.0,7,72,Rural,Data Analyst,112986,0 +101416,Female,41,Bachelors,18,68,33,25,26,8.0,2,41,Urban,HR Executive,24496,0 +101417,Female,59,Masters,11,82,70,70,28,9.0,1,4,Semi-Urban,Data Analyst,66497,0 +101418,Male,35,High School,8,28,44,81,87,0.0,4,31,Rural,ML Engineer,47692,0 +101419,Male,35,Diploma,17,26,53,26,45,8.0,1,19,Urban,ML Engineer,93652,0 +101420,Other,46,Bachelors,7,42,13,71,31,5.0,7,99,Rural,Software Engineer,50142,0 +101421,Female,54,Bachelors,10,92,76,93,93,5.0,2,31,Rural,Manager,81463,1 +101422,Male,28,High School,0,87,54,37,47,8.0,4,92,Semi-Urban,ML Engineer,74060,1 +101423,Male,25,Bachelors,13,52,39,30,28,1.0,3,3,Urban,ML Engineer,81122,0 +101424,Female,48,Masters,9,97,48,72,97,7.0,2,56,Rural,Manager,54965,1 +101425,Male,22,Bachelors,2,34,61,92,67,0.0,0,68,Urban,Manager,67087,1 +101426,Female,49,Masters,15,48,44,2,32,2.0,5,97,Semi-Urban,Software Engineer,67078,0 +101427,Male,46,Diploma,9,76,8,29,28,6.0,1,0,Urban,ML Engineer,106261,0 +101428,Male,52,Masters,4,33,19,75,45,1.0,0,45,Rural,ML Engineer,26996,0 +101429,Female,44,Diploma,16,34,19,53,23,0.0,1,87,Urban,Software Engineer,116004,0 +101430,Female,41,Diploma,15,25,22,51,94,2.0,1,1,Urban,HR Executive,148393,0 +101431,Male,34,Diploma,19,64,44,64,54,9.0,0,73,Rural,Data Analyst,138930,1 +101432,Male,31,Masters,5,18,87,21,49,0.0,1,26,Urban,Manager,46247,0 +101433,Female,25,High School,19,53,11,80,69,5.0,4,65,Urban,ML Engineer,128504,0 +101434,Other,37,Bachelors,10,57,5,70,14,0.0,1,21,Urban,Software Engineer,88756,0 +101435,Male,53,Diploma,13,23,77,65,36,9.0,4,18,Semi-Urban,Software Engineer,77444,0 +101436,Male,30,Diploma,18,6,35,97,89,2.0,6,22,Semi-Urban,Software Engineer,36678,0 +101437,Male,25,Bachelors,18,50,55,39,54,0.0,2,92,Urban,Software Engineer,22611,1 +101438,Male,25,Masters,8,6,88,5,18,6.0,5,28,Semi-Urban,Manager,78757,0 +101439,Male,28,Bachelors,3,99,82,35,22,5.0,0,35,Semi-Urban,Data Analyst,106243,1 +101440,Female,46,Masters,13,33,62,85,80,5.0,7,88,Semi-Urban,Manager,69422,1 +101441,Male,58,Bachelors,13,42,46,32,82,1.0,4,55,Urban,ML Engineer,138706,0 +101442,Male,48,High School,6,89,74,55,17,0.0,1,73,Semi-Urban,HR Executive,149040,1 +101443,Female,22,Masters,11,99,43,61,76,9.0,2,87,Rural,ML Engineer,31998,1 +101444,Male,58,Bachelors,9,34,35,20,52,7.0,6,70,Semi-Urban,Manager,20490,0 +101445,Male,22,High School,0,33,67,93,57,2.0,5,89,Rural,Manager,143006,1 +101446,Male,39,Masters,17,9,74,11,7,6.0,0,76,Urban,HR Executive,100041,0 +101447,Female,25,High School,6,97,58,42,90,2.0,0,18,Semi-Urban,Manager,49538,0 +101448,Female,22,Bachelors,10,94,52,27,34,7.0,4,55,Semi-Urban,Data Analyst,105125,0 +101449,Female,52,High School,13,94,74,68,92,3.0,4,17,Urban,Software Engineer,140197,1 +101450,Male,42,High School,10,0,35,48,3,5.0,7,51,Urban,Software Engineer,106534,0 +101451,Male,52,High School,10,50,74,79,63,1.0,1,0,Urban,Manager,89453,0 +101452,Male,49,Bachelors,13,28,63,38,71,9.0,5,44,Semi-Urban,Software Engineer,66889,0 +101453,Male,31,Diploma,11,78,74,20,72,8.0,2,25,Urban,Software Engineer,54642,0 +101454,Female,41,Bachelors,15,12,74,57,14,8.0,1,38,Urban,Manager,126148,0 +101455,Male,25,Diploma,5,31,27,59,18,4.0,5,81,Rural,HR Executive,98289,0 +101456,Male,26,High School,14,33,58,40,72,9.0,5,62,Semi-Urban,ML Engineer,83198,0 +101457,Male,42,Masters,10,97,51,35,61,1.0,4,48,Semi-Urban,Manager,98618,0 +101458,Female,29,Bachelors,14,71,50,58,0,2.0,1,26,Semi-Urban,ML Engineer,125424,0 +101459,Other,37,Bachelors,14,31,47,20,22,7.0,7,99,Rural,Manager,20419,0 +101460,Female,58,Bachelors,0,23,4,86,13,4.0,5,24,Semi-Urban,Software Engineer,142542,0 +101461,Male,48,Bachelors,14,38,17,42,67,6.0,7,54,Urban,Software Engineer,68280,0 +101462,Male,53,Bachelors,17,17,88,41,90,4.0,2,84,Rural,HR Executive,149266,0 +101463,Male,31,Diploma,9,30,79,45,77,7.0,5,67,Urban,Manager,26984,0 +101464,Female,30,Bachelors,7,47,48,31,52,7.0,3,16,Semi-Urban,ML Engineer,136694,0 +101465,Male,32,Bachelors,8,74,4,68,92,5.0,3,63,Urban,Manager,23102,0 +101466,Female,59,Bachelors,12,6,44,91,68,8.0,5,24,Urban,Software Engineer,96601,0 +101467,Male,36,Masters,13,7,15,62,13,4.0,4,52,Urban,HR Executive,47018,0 +101468,Female,45,Bachelors,19,74,39,14,17,3.0,2,37,Urban,ML Engineer,115269,0 +101469,Male,46,Masters,15,17,66,44,25,9.0,6,75,Rural,Manager,28434,0 +101470,Female,42,PhD,19,20,63,23,1,8.0,3,99,Semi-Urban,Data Analyst,145732,0 +101471,Male,23,High School,1,44,64,61,5,4.0,0,86,Urban,ML Engineer,81301,1 +101472,Female,45,Diploma,3,21,12,1,87,8.0,0,74,Urban,Data Analyst,51284,0 +101473,Male,42,Masters,17,63,82,32,94,6.0,0,47,Semi-Urban,Manager,116456,0 +101474,Female,21,Bachelors,10,0,80,10,6,9.0,4,32,Urban,Manager,40413,0 +101475,Female,59,Diploma,11,90,59,8,77,7.0,6,78,Urban,Manager,146835,0 +101476,Male,57,Diploma,11,72,26,15,88,6.0,2,64,Rural,Data Analyst,31122,0 +101477,Female,29,Masters,11,59,59,33,86,1.0,7,25,Urban,Software Engineer,83731,0 +101478,Female,28,Masters,13,70,34,17,4,9.0,1,67,Urban,ML Engineer,66935,0 +101479,Female,58,Diploma,1,85,59,1,22,7.0,3,69,Semi-Urban,Manager,122772,0 +101480,Other,43,High School,1,10,48,7,56,7.0,6,72,Semi-Urban,Manager,75858,0 +101481,Female,41,Masters,19,77,86,92,58,3.0,5,40,Rural,HR Executive,104368,1 +101482,Female,33,Bachelors,13,65,75,80,31,7.0,6,83,Semi-Urban,Manager,22425,1 +101483,Male,30,High School,9,37,43,81,37,1.0,2,87,Urban,HR Executive,76878,1 +101484,Male,49,High School,19,33,78,6,21,2.0,2,66,Rural,Manager,137976,0 +101485,Male,51,Masters,8,28,78,36,10,8.0,7,21,Rural,Data Analyst,144231,0 +101486,Male,38,High School,11,30,10,39,45,1.0,2,14,Semi-Urban,Software Engineer,73095,0 +101487,Female,22,Diploma,13,6,50,41,54,3.0,7,68,Semi-Urban,HR Executive,92348,0 +101488,Female,40,High School,1,36,64,15,11,0.0,4,53,Semi-Urban,Software Engineer,133868,0 +101489,Female,31,Bachelors,3,89,53,79,99,5.0,6,39,Urban,Software Engineer,123692,1 +101490,Male,31,Diploma,10,18,51,90,35,7.0,5,14,Semi-Urban,ML Engineer,72193,0 +101491,Male,38,Bachelors,11,92,3,35,74,3.0,1,6,Urban,Data Analyst,140176,0 +101492,Female,43,Bachelors,2,59,96,57,35,9.0,2,99,Rural,Data Analyst,48715,1 +101493,Male,37,Masters,19,84,27,91,97,4.0,6,97,Urban,Software Engineer,68783,1 +101494,Female,56,Masters,6,98,82,62,92,5.0,6,74,Semi-Urban,ML Engineer,61407,1 +101495,Male,37,Bachelors,15,36,26,43,1,5.0,0,54,Urban,HR Executive,147317,0 +101496,Male,31,Bachelors,12,86,88,47,7,6.0,4,0,Urban,Manager,115676,0 +101497,Female,26,Masters,9,93,0,38,15,5.0,6,21,Semi-Urban,Manager,95487,0 +101498,Other,39,Bachelors,6,45,19,1,28,9.0,0,92,Semi-Urban,HR Executive,35693,0 +101499,Male,38,Bachelors,11,93,27,75,28,9.0,0,46,Urban,ML Engineer,135933,1 +101500,Male,57,Diploma,2,18,14,33,68,1.0,5,54,Urban,ML Engineer,99384,0 +101501,Male,25,High School,14,26,54,14,28,5.0,3,34,Rural,ML Engineer,136367,0 +101502,Female,53,Diploma,16,68,43,99,48,4.0,3,88,Rural,HR Executive,47070,1 +101503,Female,44,Bachelors,4,76,23,20,11,8.0,7,61,Urban,ML Engineer,101092,0 +101504,Male,58,Diploma,1,58,78,32,59,5.0,7,65,Rural,ML Engineer,85004,0 +101505,Male,58,High School,14,51,93,44,13,3.0,1,0,Semi-Urban,Software Engineer,80263,0 +101506,Male,32,Bachelors,14,21,98,79,15,2.0,7,54,Urban,ML Engineer,53552,1 +101507,Female,55,PhD,19,70,29,66,68,3.0,1,5,Urban,Data Analyst,27898,0 +101508,Female,24,High School,17,18,8,85,60,2.0,5,70,Semi-Urban,HR Executive,105340,0 +101509,Male,47,Diploma,15,27,57,54,90,4.0,0,23,Urban,HR Executive,25113,0 +101510,Male,47,Masters,8,12,61,72,41,0.0,1,92,Urban,Data Analyst,136962,1 +101511,Female,29,Bachelors,11,86,4,0,10,1.0,7,21,Urban,HR Executive,26429,0 +101512,Female,57,Bachelors,16,81,74,99,35,5.0,2,58,Urban,Manager,98784,1 +101513,Female,41,Diploma,17,8,39,93,49,6.0,1,36,Urban,Data Analyst,127577,0 +101514,Male,24,Bachelors,0,25,10,29,70,3.0,5,31,Urban,Data Analyst,77027,0 +101515,Female,42,Bachelors,3,18,1,83,5,2.0,4,54,Urban,Data Analyst,31286,0 +101516,Female,43,Bachelors,16,80,35,52,1,5.0,3,88,Urban,ML Engineer,50540,1 +101517,Female,59,High School,5,90,58,37,87,5.0,7,1,Urban,HR Executive,113864,0 +101518,Male,49,Masters,0,74,38,77,26,8.0,0,15,Semi-Urban,Data Analyst,139089,0 +101519,Female,57,Diploma,4,39,22,5,72,8.0,6,30,Semi-Urban,ML Engineer,121972,0 +101520,Male,48,High School,6,26,8,68,54,0.0,6,20,Semi-Urban,Data Analyst,144644,0 +101521,Female,51,Masters,19,26,33,59,55,9.0,3,45,Semi-Urban,ML Engineer,31046,0 +101522,Male,47,Diploma,10,41,12,84,7,4.0,1,2,Semi-Urban,Manager,130174,0 +101523,Male,42,Diploma,0,75,49,77,34,5.0,2,12,Rural,HR Executive,84415,0 +101524,Male,53,Bachelors,5,82,24,63,31,5.0,1,74,Urban,Software Engineer,124761,1 +101525,Male,43,Bachelors,0,44,46,33,8,3.0,1,74,Semi-Urban,Software Engineer,119855,0 +101526,Male,58,Bachelors,1,14,15,44,20,1.0,3,33,Urban,HR Executive,64779,0 +101527,Male,59,Bachelors,19,78,87,40,46,6.0,5,48,Urban,Data Analyst,122216,1 +101528,Female,30,Masters,4,45,96,17,79,0.0,4,52,Urban,Manager,56258,0 +101529,Female,39,PhD,13,91,21,82,51,9.0,2,34,Rural,ML Engineer,33490,0 +101530,Male,53,High School,5,11,87,84,98,2.0,3,47,Urban,Manager,100361,0 +101531,Male,43,Bachelors,15,45,48,75,13,9.0,7,50,Urban,ML Engineer,111479,0 +101532,Female,24,Bachelors,5,58,25,91,77,2.0,7,70,Rural,HR Executive,134808,1 +101533,Female,47,Bachelors,7,62,17,19,87,4.0,2,0,Rural,ML Engineer,61046,0 +101534,Other,28,Bachelors,0,46,81,16,4,7.0,5,16,Urban,ML Engineer,22918,0 +101535,Female,43,Bachelors,8,50,98,89,52,8.0,0,3,Rural,Software Engineer,83855,0 +101536,Female,46,Diploma,5,59,23,5,60,5.0,2,75,Urban,HR Executive,51378,0 +101537,Male,28,High School,17,29,94,58,56,8.0,0,83,Semi-Urban,ML Engineer,39477,1 +101538,Male,57,Bachelors,11,27,43,37,30,0.0,5,97,Urban,Data Analyst,75406,0 +101539,Male,57,Diploma,10,91,4,72,87,7.0,0,89,Rural,Software Engineer,59812,1 +101540,Female,53,Bachelors,7,36,16,52,52,2.0,4,15,Rural,Software Engineer,94597,0 +101541,Male,58,PhD,14,42,66,36,93,8.0,5,47,Urban,ML Engineer,114129,0 +101542,Female,43,Diploma,0,16,15,14,1,6.0,5,1,Semi-Urban,HR Executive,113518,0 +101543,Female,40,Bachelors,7,85,19,4,86,2.0,5,94,Rural,Manager,59204,0 +101544,Male,34,Bachelors,9,8,32,73,0,2.0,7,21,Urban,Software Engineer,132753,0 +101545,Female,44,Bachelors,4,60,18,21,68,9.0,0,24,Semi-Urban,HR Executive,131038,0 +101546,Female,33,Bachelors,15,28,19,72,64,9.0,1,34,Urban,Data Analyst,39409,0 +101547,Male,53,Bachelors,0,55,56,69,36,2.0,1,50,Urban,Manager,117820,0 +101548,Other,47,Bachelors,0,7,11,26,11,9.0,3,99,Urban,Data Analyst,58759,0 +101549,Male,55,High School,17,90,17,21,48,3.0,3,29,Urban,Data Analyst,145456,0 +101550,Male,32,Diploma,13,13,59,57,80,9.0,6,25,Urban,Manager,22699,0 +101551,Female,33,Bachelors,9,81,44,82,97,7.0,0,71,Semi-Urban,Data Analyst,45159,1 +101552,Male,39,Bachelors,2,97,6,9,75,7.0,7,59,Urban,HR Executive,136906,0 +101553,Female,49,Masters,10,36,44,65,9,7.0,3,38,Urban,HR Executive,72972,0 +101554,Female,42,Bachelors,8,2,73,97,60,9.0,4,45,Urban,ML Engineer,92847,0 +101555,Male,37,Diploma,5,55,2,14,50,4.0,6,67,Urban,Data Analyst,62309,0 +101556,Male,42,Masters,3,1,46,3,40,8.0,3,82,Urban,HR Executive,110877,0 +101557,Female,23,Bachelors,14,78,12,94,7,5.0,2,64,Urban,Manager,95383,1 +101558,Male,58,Diploma,1,94,31,50,53,5.0,7,36,Urban,Manager,133485,0 +101559,Female,53,Diploma,19,38,30,9,66,6.0,3,49,Semi-Urban,Software Engineer,132312,0 +101560,Female,22,PhD,13,42,33,27,36,1.0,2,52,Urban,Manager,125727,0 +101561,Female,25,Masters,8,61,36,65,48,4.0,7,89,Urban,Data Analyst,72572,1 +101562,Male,58,Bachelors,18,90,14,90,18,7.0,7,88,Urban,Manager,131342,1 +101563,Male,29,High School,17,43,0,51,81,0.0,3,50,Urban,HR Executive,111962,0 +101564,Male,28,High School,16,19,75,5,9,8.0,4,79,Semi-Urban,HR Executive,137079,0 +101565,Male,33,Bachelors,10,94,36,97,57,8.0,0,13,Semi-Urban,ML Engineer,33856,1 +101566,Male,45,Bachelors,2,55,71,49,79,8.0,1,51,Urban,ML Engineer,115746,0 +101567,Male,39,Bachelors,16,86,90,12,21,7.0,7,96,Rural,Manager,56037,1 +101568,Female,59,Masters,7,27,31,81,65,5.0,2,63,Urban,Data Analyst,128297,0 +101569,Female,50,Bachelors,9,30,29,90,85,0.0,4,75,Urban,ML Engineer,137226,0 +101570,Male,37,Bachelors,1,15,59,19,8,4.0,0,41,Urban,Software Engineer,139553,0 +101571,Male,35,Bachelors,5,33,18,49,41,2.0,1,89,Rural,Data Analyst,109740,0 +101572,Male,42,Diploma,0,45,6,7,3,4.0,7,85,Semi-Urban,ML Engineer,65624,0 +101573,Male,44,Bachelors,3,29,14,69,24,8.0,1,22,Semi-Urban,Data Analyst,68737,0 +101574,Male,47,Bachelors,4,36,24,58,58,4.0,5,11,Semi-Urban,ML Engineer,46370,0 +101575,Other,43,Masters,11,16,25,17,76,5.0,4,49,Urban,Manager,87367,0 +101576,Female,55,Bachelors,19,77,89,55,29,0.0,6,80,Rural,ML Engineer,104959,1 +101577,Male,45,Bachelors,15,3,55,91,46,7.0,7,65,Urban,Software Engineer,55593,0 +101578,Female,41,Bachelors,16,24,55,99,48,9.0,1,29,Rural,Manager,32471,0 +101579,Male,36,Bachelors,11,2,8,9,72,3.0,2,65,Rural,HR Executive,80909,0 +101580,Male,26,Bachelors,9,98,16,94,7,2.0,3,29,Semi-Urban,Manager,35732,1 +101581,Female,40,Bachelors,9,3,31,90,4,2.0,7,13,Urban,Software Engineer,108452,0 +101582,Male,43,Masters,16,91,7,54,9,3.0,3,75,Rural,ML Engineer,78237,0 +101583,Male,22,Masters,0,9,11,5,64,5.0,6,61,Urban,Software Engineer,52844,0 +101584,Female,42,Bachelors,1,53,46,38,85,5.0,5,47,Urban,Software Engineer,53436,0 +101585,Female,47,High School,16,62,41,47,34,1.0,6,9,Rural,Data Analyst,101475,0 +101586,Male,47,High School,1,3,65,49,76,7.0,3,2,Urban,HR Executive,103612,0 +101587,Male,31,Masters,15,31,75,88,3,8.0,3,26,Rural,HR Executive,65937,0 +101588,Male,31,Bachelors,3,61,55,0,93,4.0,1,76,Urban,Manager,125325,0 +101589,Male,33,Diploma,0,33,89,93,70,4.0,0,22,Urban,ML Engineer,114391,1 +101590,Male,55,High School,14,99,42,37,36,7.0,7,33,Urban,Data Analyst,89256,0 +101591,Female,28,Diploma,17,0,46,60,54,1.0,1,11,Urban,Manager,27541,0 +101592,Female,32,Bachelors,15,21,52,28,51,3.0,6,18,Urban,ML Engineer,109448,0 +101593,Female,33,Masters,11,95,75,89,36,0.0,5,88,Urban,Manager,20849,1 +101594,Female,51,Bachelors,17,82,13,43,2,9.0,1,19,Urban,Software Engineer,129539,0 +101595,Male,29,Masters,13,29,20,68,91,5.0,0,85,Rural,Manager,94923,0 +101596,Female,52,Bachelors,16,17,19,89,5,6.0,0,20,Semi-Urban,Software Engineer,76672,0 +101597,Male,43,High School,4,56,35,32,27,1.0,6,6,Semi-Urban,ML Engineer,27752,0 +101598,Male,52,Bachelors,1,54,84,41,6,0.0,1,37,Semi-Urban,Data Analyst,73615,0 +101599,Male,30,Bachelors,13,32,8,93,68,8.0,5,72,Urban,Manager,108577,0 +101600,Male,28,Masters,5,10,80,28,81,3.0,7,59,Urban,Data Analyst,129168,0 +101601,Male,26,Diploma,18,17,62,81,57,9.0,1,94,Rural,Data Analyst,129999,1 +101602,Male,44,Bachelors,15,66,52,3,55,4.0,2,22,Urban,HR Executive,40484,0 +101603,Male,26,Masters,0,67,60,65,27,5.0,4,68,Semi-Urban,Software Engineer,80951,1 +101604,Female,39,Bachelors,16,58,87,43,72,2.0,5,67,Urban,Data Analyst,117021,1 +101605,Male,41,Bachelors,8,98,0,34,2,8.0,1,81,Urban,Software Engineer,23249,0 +101606,Other,24,High School,16,1,7,20,59,8.0,4,62,Semi-Urban,Data Analyst,72346,0 +101607,Male,53,High School,16,21,94,17,36,4.0,6,79,Urban,ML Engineer,84433,0 +101608,Female,30,Masters,14,94,82,2,73,7.0,4,40,Semi-Urban,Manager,102254,0 +101609,Female,55,Masters,3,94,73,53,11,2.0,6,13,Rural,Manager,98697,0 +101610,Male,53,PhD,1,56,35,82,98,4.0,3,90,Semi-Urban,Software Engineer,137097,1 +101611,Male,57,Masters,13,3,90,67,95,9.0,7,46,Semi-Urban,HR Executive,118819,0 +101612,Female,59,Bachelors,6,11,87,95,34,7.0,2,82,Semi-Urban,Data Analyst,35902,1 +101613,Female,48,Diploma,3,39,76,16,97,6.0,3,79,Urban,Software Engineer,108925,0 +101614,Female,37,High School,16,88,81,1,46,2.0,1,56,Rural,HR Executive,33499,0 +101615,Female,21,Diploma,4,33,92,44,44,5.0,0,81,Urban,Software Engineer,53200,1 +101616,Female,33,Diploma,14,28,42,76,73,5.0,7,52,Urban,Software Engineer,91797,0 +101617,Male,48,Masters,16,5,98,17,67,6.0,1,52,Rural,HR Executive,42952,0 +101618,Male,31,Bachelors,19,71,51,31,35,1.0,6,20,Urban,Manager,44873,0 +101619,Female,32,Masters,0,33,99,96,61,6.0,1,15,Urban,Software Engineer,28672,1 +101620,Female,33,High School,3,72,71,30,54,0.0,2,60,Rural,Software Engineer,137041,0 +101621,Male,46,Diploma,13,34,18,4,61,6.0,6,98,Semi-Urban,Software Engineer,42812,0 +101622,Male,49,Diploma,10,69,2,19,74,1.0,7,35,Urban,Manager,112494,0 +101623,Female,56,Masters,12,65,47,10,73,5.0,3,96,Rural,Data Analyst,90230,0 +101624,Male,30,Diploma,10,97,27,12,49,1.0,7,20,Urban,HR Executive,65398,0 +101625,Male,42,Bachelors,4,70,76,81,49,2.0,2,14,Urban,Data Analyst,145042,1 +101626,Female,32,Bachelors,0,97,85,67,47,7.0,7,44,Semi-Urban,Manager,69163,1 +101627,Male,40,Diploma,19,28,76,10,21,9.0,4,55,Urban,Software Engineer,66364,0 +101628,Male,28,High School,14,69,32,67,31,3.0,4,91,Urban,Manager,32646,1 +101629,Female,22,Bachelors,16,67,97,84,56,5.0,1,62,Urban,Software Engineer,124778,1 +101630,Male,25,Bachelors,7,91,35,51,26,8.0,3,30,Urban,HR Executive,119275,0 +101631,Male,46,Bachelors,0,85,11,13,54,5.0,1,66,Semi-Urban,HR Executive,28537,0 +101632,Male,35,High School,11,74,71,68,86,2.0,0,28,Rural,Software Engineer,63498,1 +101633,Female,34,PhD,3,36,14,84,67,5.0,6,24,Semi-Urban,ML Engineer,44800,0 +101634,Male,56,Masters,0,64,23,72,43,0.0,4,30,Urban,Manager,57996,0 +101635,Female,29,Bachelors,5,15,10,6,48,7.0,4,89,Semi-Urban,ML Engineer,65055,0 +101636,Male,53,High School,5,71,96,4,51,1.0,4,28,Semi-Urban,ML Engineer,22981,0 +101637,Male,57,Bachelors,16,23,67,18,39,4.0,2,70,Semi-Urban,HR Executive,56335,0 +101638,Female,29,Diploma,8,15,92,50,59,0.0,7,86,Rural,Manager,116093,1 +101639,Female,26,Bachelors,2,16,99,66,89,7.0,0,17,Urban,Data Analyst,44277,0 +101640,Other,30,Bachelors,12,33,1,39,2,2.0,2,77,Urban,Manager,138006,0 +101641,Male,27,Bachelors,11,6,79,69,87,6.0,6,10,Urban,Software Engineer,144518,0 +101642,Male,41,Diploma,17,11,62,81,61,0.0,2,70,Semi-Urban,Data Analyst,45162,0 +101643,Female,33,Diploma,4,23,96,4,31,7.0,0,11,Urban,Manager,103936,0 +101644,Male,25,High School,1,7,12,48,10,1.0,2,44,Rural,Software Engineer,41158,0 +101645,Male,51,Diploma,1,70,18,38,31,6.0,0,41,Rural,Software Engineer,102795,0 +101646,Male,54,Bachelors,19,31,70,34,26,9.0,7,76,Rural,HR Executive,129220,0 +101647,Female,37,Bachelors,17,95,28,96,47,2.0,2,82,Rural,Data Analyst,29891,1 +101648,Male,26,Bachelors,0,54,23,26,9,8.0,3,3,Urban,HR Executive,43359,0 +101649,Male,46,Masters,1,66,34,9,79,6.0,1,90,Rural,Manager,28103,0 +101650,Male,22,Diploma,13,39,59,83,77,6.0,7,5,Semi-Urban,Software Engineer,28284,0 +101651,Male,47,Diploma,6,39,10,41,40,3.0,5,14,Urban,Manager,42428,0 +101652,Female,56,High School,19,54,33,68,97,7.0,3,2,Rural,Software Engineer,60590,0 +101653,Female,24,High School,8,49,93,20,75,2.0,0,90,Urban,Data Analyst,34354,1 +101654,Male,21,Masters,3,4,84,16,9,1.0,2,59,Rural,Data Analyst,20607,0 +101655,Female,45,Diploma,5,79,91,68,11,2.0,6,88,Urban,ML Engineer,122261,1 +101656,Male,56,Masters,12,1,80,91,64,0.0,2,97,Semi-Urban,Manager,86304,1 +101657,Male,29,Diploma,19,80,26,99,30,4.0,2,48,Rural,Data Analyst,71226,1 +101658,Male,40,Masters,18,37,74,37,99,5.0,7,35,Urban,Data Analyst,142798,0 +101659,Female,57,Masters,13,35,2,8,18,8.0,4,40,Urban,Software Engineer,103078,0 +101660,Female,27,High School,5,77,73,46,53,3.0,1,32,Urban,Software Engineer,122618,0 +101661,Female,40,Bachelors,11,95,39,30,64,5.0,4,65,Rural,ML Engineer,121168,0 +101662,Male,23,Bachelors,10,4,74,34,68,5.0,2,42,Urban,Software Engineer,138491,0 +101663,Female,24,Diploma,11,27,49,4,73,7.0,6,6,Urban,Data Analyst,93402,0 +101664,Male,42,High School,19,42,89,88,96,3.0,4,26,Urban,ML Engineer,78645,1 +101665,Male,48,Masters,4,24,95,0,69,0.0,4,20,Rural,Data Analyst,130361,0 +101666,Male,36,Bachelors,4,54,24,76,37,2.0,3,95,Urban,Software Engineer,102540,1 +101667,Male,55,Masters,15,57,18,23,37,1.0,7,9,Semi-Urban,Manager,65372,0 +101668,Male,45,Diploma,0,48,6,63,47,1.0,0,69,Semi-Urban,Software Engineer,70085,0 +101669,Male,23,Bachelors,17,56,78,12,44,3.0,4,73,Semi-Urban,Manager,57522,0 +101670,Female,41,Bachelors,8,68,57,14,84,5.0,7,63,Rural,HR Executive,29188,0 +101671,Male,51,PhD,7,17,8,73,54,2.0,3,64,Urban,Software Engineer,72585,0 +101672,Male,52,Diploma,17,9,62,52,59,1.0,6,67,Urban,Manager,95181,0 +101673,Male,29,Bachelors,11,30,10,47,2,2.0,7,3,Rural,HR Executive,94313,0 +101674,Female,21,Diploma,18,77,17,2,97,7.0,0,53,Rural,Manager,62418,0 +101675,Female,28,Diploma,7,48,82,13,39,8.0,7,40,Semi-Urban,HR Executive,26971,0 +101676,Female,26,Diploma,11,88,99,70,78,4.0,7,46,Rural,Software Engineer,108492,1 +101677,Female,26,PhD,3,44,69,91,17,8.0,1,4,Rural,ML Engineer,95447,0 +101678,Female,44,High School,17,6,62,65,89,7.0,1,87,Semi-Urban,Manager,67178,0 +101679,Female,56,Masters,18,51,13,19,24,7.0,3,93,Rural,Manager,117713,0 +101680,Male,36,High School,12,34,38,29,16,7.0,7,48,Semi-Urban,Software Engineer,61852,0 +101681,Female,49,Diploma,1,12,9,40,54,6.0,7,43,Rural,Data Analyst,99316,0 +101682,Female,32,Diploma,0,42,14,4,39,4.0,3,10,Urban,Manager,46169,0 +101683,Male,48,Bachelors,12,12,29,82,13,2.0,4,94,Urban,Software Engineer,20264,0 +101684,Male,34,PhD,19,0,21,84,97,3.0,6,88,Urban,ML Engineer,23135,0 +101685,Male,28,Masters,14,57,83,90,96,3.0,7,55,Urban,Software Engineer,70246,1 +101686,Male,39,Diploma,0,56,40,41,85,6.0,5,48,Urban,Software Engineer,107265,0 +101687,Male,42,Bachelors,9,51,64,60,28,0.0,2,46,Semi-Urban,Software Engineer,75842,0 +101688,Female,51,Bachelors,5,93,29,47,11,0.0,5,23,Semi-Urban,Software Engineer,128079,0 +101689,Male,28,Diploma,15,35,1,12,69,8.0,5,15,Urban,Software Engineer,42212,0 +101690,Male,53,Masters,12,98,3,73,4,3.0,6,85,Semi-Urban,Data Analyst,58999,1 +101691,Female,44,PhD,14,1,55,35,91,5.0,1,78,Urban,Manager,83923,0 +101692,Other,40,Masters,4,65,73,84,2,2.0,7,75,Urban,ML Engineer,149116,1 +101693,Female,48,Bachelors,17,51,21,26,51,8.0,2,57,Urban,ML Engineer,85722,0 +101694,Female,29,Bachelors,6,34,67,27,9,3.0,7,15,Urban,HR Executive,33010,0 +101695,Male,34,Bachelors,14,68,11,41,97,1.0,6,52,Urban,HR Executive,120131,0 +101696,Female,39,High School,19,40,58,46,72,9.0,0,74,Urban,ML Engineer,41545,0 +101697,Male,39,Diploma,5,43,88,98,81,1.0,3,27,Semi-Urban,Data Analyst,132873,1 +101698,Female,27,Diploma,11,29,95,1,29,6.0,2,97,Semi-Urban,ML Engineer,84873,0 +101699,Male,52,Masters,12,81,3,61,95,5.0,3,45,Rural,HR Executive,109432,0 +101700,Male,35,Diploma,13,72,45,56,1,7.0,1,82,Urban,Manager,28194,1 +101701,Male,24,Diploma,2,32,4,57,47,7.0,7,45,Semi-Urban,HR Executive,43150,0 +101702,Male,58,Diploma,18,1,48,12,96,4.0,6,83,Urban,Manager,28810,0 +101703,Male,31,Bachelors,12,40,11,17,44,0.0,4,4,Urban,Software Engineer,110326,0 +101704,Male,57,Masters,17,70,45,12,70,9.0,7,37,Rural,ML Engineer,102997,0 +101705,Male,22,Bachelors,2,57,72,53,79,9.0,2,24,Urban,ML Engineer,85792,0 +101706,Male,28,Bachelors,16,96,6,73,58,7.0,4,28,Urban,Manager,47878,0 +101707,Male,52,Diploma,7,8,70,74,28,1.0,4,27,Urban,Data Analyst,110663,0 +101708,Female,37,Bachelors,18,4,34,95,3,9.0,7,79,Rural,HR Executive,56187,0 +101709,Male,28,Masters,9,26,16,48,89,5.0,7,4,Semi-Urban,ML Engineer,103824,0 +101710,Female,49,Diploma,2,25,90,38,6,9.0,1,26,Rural,Software Engineer,26382,0 +101711,Male,41,Bachelors,13,25,13,53,52,7.0,2,6,Rural,ML Engineer,51040,0 +101712,Male,30,Bachelors,10,33,7,59,90,4.0,7,23,Urban,HR Executive,73943,0 +101713,Male,23,High School,15,87,7,72,46,8.0,2,94,Urban,Software Engineer,127662,1 +101714,Male,33,High School,8,14,74,74,69,9.0,7,97,Urban,Data Analyst,94989,1 +101715,Female,29,Masters,14,90,43,75,71,0.0,1,8,Urban,Manager,125723,0 +101716,Male,21,Diploma,14,76,9,85,45,1.0,1,82,Rural,Data Analyst,69827,1 +101717,Male,32,PhD,11,91,61,47,18,4.0,0,56,Urban,ML Engineer,122912,1 +101718,Female,37,High School,16,47,45,58,17,0.0,5,47,Semi-Urban,HR Executive,59935,0 +101719,Female,27,Masters,6,14,20,59,0,9.0,7,66,Urban,Manager,57619,0 +101720,Male,53,PhD,14,78,8,11,22,3.0,5,53,Rural,Data Analyst,100671,0 +101721,Female,23,Bachelors,11,97,82,3,85,5.0,0,82,Urban,ML Engineer,87672,1 +101722,Male,45,Diploma,15,32,97,40,49,5.0,2,52,Urban,Data Analyst,124615,0 +101723,Male,52,Masters,9,65,19,45,31,0.0,1,74,Urban,Software Engineer,89159,0 +101724,Male,30,High School,19,53,80,2,32,2.0,1,23,Semi-Urban,Data Analyst,59816,0 +101725,Male,51,Bachelors,2,99,73,90,46,6.0,7,80,Urban,Manager,110814,1 +101726,Other,53,High School,1,44,99,60,9,6.0,5,79,Urban,ML Engineer,74477,1 +101727,Male,54,Bachelors,0,97,82,41,32,1.0,3,74,Urban,Software Engineer,27311,1 +101728,Male,32,Diploma,17,39,12,79,83,3.0,3,21,Urban,HR Executive,29176,0 +101729,Male,56,Bachelors,11,59,61,19,36,2.0,2,20,Urban,Data Analyst,145987,0 +101730,Male,32,High School,8,79,75,78,33,6.0,6,3,Urban,Data Analyst,69969,1 +101731,Male,53,Diploma,0,44,49,75,11,3.0,0,46,Semi-Urban,HR Executive,101788,0 +101732,Male,35,Bachelors,16,52,10,1,6,6.0,4,68,Semi-Urban,HR Executive,148549,0 +101733,Female,53,Masters,9,93,60,11,38,0.0,5,22,Urban,HR Executive,117581,0 +101734,Male,29,Bachelors,15,67,81,59,74,1.0,4,81,Urban,Data Analyst,73129,1 +101735,Other,58,Bachelors,6,77,85,55,43,6.0,5,65,Semi-Urban,Software Engineer,86882,1 +101736,Male,26,Bachelors,2,42,78,54,87,6.0,7,73,Semi-Urban,ML Engineer,74997,1 +101737,Male,47,Diploma,12,96,79,12,68,7.0,7,15,Urban,ML Engineer,77340,0 +101738,Male,28,Diploma,18,69,77,7,81,2.0,1,67,Rural,HR Executive,124348,0 +101739,Male,59,Masters,4,83,20,46,85,4.0,7,32,Rural,Manager,104704,0 +101740,Female,58,High School,15,91,88,74,32,6.0,7,66,Urban,Manager,124657,1 +101741,Male,36,Bachelors,14,97,89,48,32,2.0,2,24,Urban,ML Engineer,81339,1 +101742,Female,52,Bachelors,8,72,43,45,82,9.0,2,61,Semi-Urban,Manager,99602,0 +101743,Male,52,Diploma,18,23,89,66,80,7.0,5,9,Semi-Urban,ML Engineer,138327,0 +101744,Male,26,Bachelors,15,6,96,41,37,8.0,6,40,Semi-Urban,ML Engineer,127774,0 +101745,Male,47,Diploma,13,45,84,63,10,3.0,2,27,Urban,HR Executive,98681,0 +101746,Male,42,Masters,6,88,77,44,63,7.0,4,19,Urban,ML Engineer,126514,0 +101747,Female,40,High School,15,2,1,82,49,5.0,1,17,Semi-Urban,HR Executive,49250,0 +101748,Male,25,Bachelors,5,16,56,56,5,3.0,6,38,Rural,Manager,129751,0 +101749,Female,49,Bachelors,7,94,78,88,27,2.0,0,85,Semi-Urban,Software Engineer,139858,1 +101750,Male,21,Diploma,4,40,78,55,29,4.0,4,59,Urban,Data Analyst,51860,0 +101751,Female,43,Bachelors,4,54,5,73,66,2.0,0,34,Urban,Software Engineer,90341,0 +101752,Male,58,High School,16,30,37,52,12,1.0,0,3,Rural,Manager,32038,0 +101753,Male,24,Bachelors,11,72,72,21,93,4.0,7,72,Urban,Software Engineer,144402,1 +101754,Male,33,Masters,13,92,3,55,79,0.0,2,94,Urban,Data Analyst,26119,1 +101755,Male,52,Masters,12,31,71,87,84,2.0,7,95,Rural,Data Analyst,141937,1 +101756,Female,37,Bachelors,12,5,87,5,55,7.0,3,7,Urban,Data Analyst,132630,0 +101757,Female,54,Bachelors,3,99,10,39,35,4.0,7,93,Urban,Software Engineer,148647,1 +101758,Male,21,Masters,7,58,14,4,71,1.0,4,36,Rural,HR Executive,33820,0 +101759,Female,52,Diploma,6,93,7,42,76,4.0,1,28,Urban,Manager,144034,0 +101760,Male,52,High School,16,12,62,14,79,6.0,0,0,Urban,ML Engineer,20525,0 +101761,Male,43,Masters,13,54,96,98,67,6.0,4,0,Urban,ML Engineer,81077,1 +101762,Male,59,Masters,4,97,69,65,4,7.0,1,63,Semi-Urban,ML Engineer,72032,1 +101763,Male,49,Bachelors,5,14,24,2,85,5.0,4,3,Urban,Manager,42369,0 +101764,Male,24,Diploma,9,77,12,76,38,0.0,2,64,Rural,HR Executive,132038,0 +101765,Male,49,Masters,12,62,12,12,98,7.0,1,34,Urban,Data Analyst,40272,0 +101766,Male,45,Bachelors,9,93,17,96,52,9.0,7,6,Semi-Urban,Data Analyst,52421,0 +101767,Male,44,PhD,15,7,43,34,60,3.0,3,99,Rural,ML Engineer,29667,0 +101768,Female,30,Bachelors,11,31,12,11,81,0.0,2,54,Semi-Urban,HR Executive,31291,0 +101769,Male,45,Masters,3,48,47,79,21,5.0,5,88,Semi-Urban,ML Engineer,109958,1 +101770,Male,48,High School,7,66,66,11,42,5.0,6,68,Urban,Manager,98218,0 +101771,Male,43,Diploma,18,53,25,12,97,3.0,6,29,Semi-Urban,ML Engineer,68202,0 +101772,Male,39,Bachelors,2,98,66,98,24,3.0,3,78,Urban,Manager,84574,1 +101773,Female,46,High School,17,78,49,83,52,6.0,6,33,Urban,Software Engineer,88158,1 +101774,Female,33,Bachelors,11,15,48,33,33,8.0,4,17,Rural,HR Executive,148637,0 +101775,Female,42,Bachelors,15,5,23,53,88,1.0,2,14,Urban,Data Analyst,28360,0 +101776,Male,35,Diploma,14,38,31,42,95,3.0,7,74,Rural,ML Engineer,71568,0 +101777,Male,53,Diploma,19,18,6,10,96,7.0,0,69,Rural,Manager,24052,0 +101778,Male,41,Bachelors,1,81,36,70,55,0.0,4,55,Urban,Software Engineer,105653,1 +101779,Male,40,Bachelors,15,24,60,71,32,8.0,6,79,Rural,Data Analyst,133021,0 +101780,Other,37,Bachelors,8,42,31,89,72,7.0,7,24,Urban,Software Engineer,123075,0 +101781,Male,21,Masters,15,15,19,19,9,9.0,5,82,Semi-Urban,HR Executive,132246,0 +101782,Male,46,Bachelors,15,43,16,1,86,2.0,4,85,Rural,Software Engineer,68062,0 +101783,Male,41,Masters,11,21,93,92,35,2.0,6,75,Semi-Urban,Manager,44540,1 +101784,Female,35,Masters,8,8,84,76,36,5.0,5,65,Rural,Software Engineer,40316,0 +101785,Male,26,High School,18,88,41,69,30,6.0,7,62,Urban,Manager,77093,1 +101786,Male,23,Diploma,5,61,2,21,17,9.0,5,4,Urban,Manager,108912,0 +101787,Female,23,Bachelors,3,36,12,0,76,5.0,4,40,Semi-Urban,HR Executive,55965,0 +101788,Female,27,Masters,6,78,39,90,26,2.0,6,93,Rural,ML Engineer,83963,1 +101789,Female,42,Masters,10,76,63,40,63,7.0,3,98,Urban,Manager,43813,1 +101790,Female,53,Diploma,16,44,39,36,36,4.0,3,61,Urban,ML Engineer,41570,0 +101791,Female,44,Diploma,17,17,41,79,39,2.0,1,53,Urban,Manager,135836,0 +101792,Female,27,Diploma,6,1,79,60,67,5.0,7,46,Semi-Urban,ML Engineer,121806,0 +101793,Female,24,Diploma,9,65,49,69,11,3.0,3,96,Urban,Manager,23032,1 +101794,Male,25,Diploma,3,67,87,9,74,5.0,2,32,Rural,Data Analyst,125119,0 +101795,Male,25,Bachelors,2,43,1,80,33,9.0,0,57,Urban,Software Engineer,65512,0 +101796,Male,28,Masters,16,81,77,92,10,1.0,7,72,Urban,Manager,52846,1 +101797,Male,30,Bachelors,15,62,77,32,33,9.0,5,11,Urban,ML Engineer,64091,0 +101798,Male,38,Diploma,3,96,89,31,96,0.0,5,56,Urban,Data Analyst,135048,1 +101799,Male,59,Bachelors,14,66,5,29,23,8.0,1,73,Urban,HR Executive,105435,0 +101800,Male,42,Bachelors,9,34,0,73,12,3.0,5,20,Urban,ML Engineer,88665,0 +101801,Male,36,Masters,3,2,40,50,85,4.0,3,90,Urban,ML Engineer,48387,0 +101802,Female,44,PhD,5,31,93,99,35,1.0,0,97,Urban,Manager,84693,1 +101803,Male,28,High School,16,57,41,54,57,7.0,2,67,Urban,ML Engineer,146543,0 +101804,Female,31,PhD,9,52,85,21,32,8.0,7,1,Rural,Manager,148433,0 +101805,Other,40,Masters,18,42,90,49,81,5.0,5,55,Urban,Software Engineer,94718,0 +101806,Male,43,High School,19,36,90,98,92,9.0,6,1,Urban,HR Executive,57971,0 +101807,Male,27,Masters,15,85,76,4,54,0.0,0,2,Semi-Urban,Software Engineer,127072,0 +101808,Male,33,Diploma,15,96,87,14,27,4.0,7,31,Urban,Data Analyst,50053,0 +101809,Female,36,High School,2,41,79,62,29,3.0,7,28,Rural,HR Executive,35822,0 +101810,Female,27,Diploma,9,98,54,13,70,8.0,6,48,Urban,ML Engineer,70773,0 +101811,Male,23,Bachelors,11,68,79,34,92,8.0,5,42,Rural,HR Executive,58838,0 +101812,Other,37,Bachelors,2,67,23,73,15,6.0,7,93,Urban,Data Analyst,88668,1 +101813,Male,28,Diploma,1,56,70,57,78,3.0,3,92,Rural,Manager,65217,1 +101814,Male,34,High School,11,64,39,20,4,0.0,6,99,Urban,Software Engineer,124971,0 +101815,Female,58,High School,0,78,45,22,40,8.0,4,15,Semi-Urban,Manager,96390,0 +101816,Male,33,High School,3,92,18,78,40,3.0,2,43,Urban,Software Engineer,84455,0 +101817,Male,38,Masters,17,47,44,86,98,7.0,2,76,Urban,Data Analyst,126321,1 +101818,Female,59,Diploma,11,52,41,11,9,8.0,2,36,Urban,HR Executive,92448,0 +101819,Female,23,Bachelors,2,70,5,4,20,6.0,5,14,Semi-Urban,Data Analyst,108660,0 +101820,Female,34,Masters,14,79,37,99,79,6.0,7,18,Semi-Urban,ML Engineer,105858,0 +101821,Male,49,Bachelors,19,59,8,70,38,0.0,4,97,Urban,Manager,139197,0 +101822,Female,59,Diploma,18,25,6,98,3,1.0,7,79,Urban,Software Engineer,103003,0 +101823,Female,46,Masters,14,42,61,30,54,0.0,0,68,Urban,ML Engineer,29332,0 +101824,Other,57,Diploma,16,25,25,98,3,9.0,2,27,Urban,HR Executive,127439,0 +101825,Male,32,Masters,5,17,41,58,95,7.0,6,73,Rural,HR Executive,83749,0 +101826,Male,37,High School,3,83,72,1,72,2.0,1,38,Urban,Manager,103362,0 +101827,Female,43,Diploma,13,74,59,84,94,2.0,7,75,Urban,Manager,106755,1 +101828,Male,36,Bachelors,6,55,15,33,12,6.0,2,69,Semi-Urban,ML Engineer,42203,0 +101829,Male,32,PhD,18,66,50,65,32,2.0,5,65,Rural,Data Analyst,40048,1 +101830,Male,34,Bachelors,1,69,37,75,87,7.0,6,19,Urban,Software Engineer,102325,0 +101831,Female,33,High School,13,65,44,16,84,8.0,1,84,Urban,Data Analyst,57295,0 +101832,Male,32,Bachelors,14,64,71,95,5,8.0,7,20,Urban,Manager,27088,1 +101833,Other,44,Bachelors,11,73,34,46,75,0.0,2,5,Urban,ML Engineer,51413,0 +101834,Male,24,PhD,18,15,12,84,66,7.0,2,26,Urban,Data Analyst,30779,0 +101835,Female,47,Bachelors,9,95,53,56,23,0.0,7,4,Urban,Software Engineer,129722,0 +101836,Male,26,Bachelors,14,92,20,62,42,7.0,3,36,Semi-Urban,Software Engineer,30762,0 +101837,Female,23,Diploma,8,71,78,12,52,1.0,4,50,Urban,Data Analyst,22317,0 +101838,Other,27,Bachelors,18,49,72,8,24,8.0,4,81,Urban,HR Executive,47377,0 +101839,Male,52,Masters,13,69,28,24,15,3.0,7,51,Semi-Urban,Data Analyst,104283,0 +101840,Male,29,Bachelors,11,53,92,9,17,9.0,5,77,Urban,HR Executive,100547,0 +101841,Male,49,Masters,3,5,9,89,23,2.0,4,0,Urban,Data Analyst,27851,0 +101842,Male,34,Masters,15,98,35,19,18,7.0,0,78,Urban,Data Analyst,84139,0 +101843,Male,54,Diploma,11,59,29,69,19,5.0,4,83,Rural,ML Engineer,66718,1 +101844,Male,21,High School,18,63,73,0,61,5.0,3,15,Semi-Urban,HR Executive,132499,0 +101845,Female,59,PhD,8,38,33,52,24,3.0,7,0,Semi-Urban,Manager,78197,0 +101846,Female,54,Bachelors,19,72,20,9,65,2.0,0,3,Urban,Manager,65364,0 +101847,Male,30,Bachelors,10,71,54,92,40,8.0,7,94,Urban,Software Engineer,105928,1 +101848,Male,25,Bachelors,8,5,23,77,79,4.0,7,47,Rural,Manager,111781,0 +101849,Male,44,Bachelors,19,29,35,18,0,0.0,0,17,Rural,Manager,72251,0 +101850,Male,58,Masters,0,50,72,24,54,8.0,3,69,Urban,ML Engineer,38401,0 +101851,Male,59,Diploma,16,9,37,55,44,5.0,3,58,Urban,Software Engineer,71465,0 +101852,Male,38,Masters,6,57,60,40,94,6.0,5,85,Semi-Urban,HR Executive,29025,1 +101853,Male,51,Bachelors,17,21,38,90,34,3.0,2,86,Urban,ML Engineer,43455,1 +101854,Female,46,High School,3,46,69,24,44,6.0,0,48,Urban,ML Engineer,56123,0 +101855,Female,25,Diploma,2,34,61,7,22,4.0,3,21,Urban,ML Engineer,106953,0 +101856,Male,45,High School,2,33,7,2,54,6.0,4,73,Rural,ML Engineer,77277,0 +101857,Male,33,Bachelors,14,72,63,77,19,3.0,3,75,Urban,Data Analyst,88315,1 +101858,Male,23,Diploma,13,66,90,82,55,0.0,0,51,Urban,HR Executive,55483,1 +101859,Male,33,High School,11,83,75,11,69,8.0,1,62,Rural,HR Executive,30156,0 +101860,Female,25,Bachelors,11,73,92,88,23,9.0,5,91,Semi-Urban,ML Engineer,145006,1 +101861,Male,39,High School,2,32,52,50,55,3.0,2,36,Rural,Software Engineer,31909,0 +101862,Male,50,PhD,15,49,82,75,78,8.0,1,28,Rural,Manager,111262,0 +101863,Male,36,High School,19,96,44,73,44,7.0,2,83,Urban,HR Executive,106150,1 +101864,Male,59,Diploma,1,44,46,92,85,6.0,0,25,Semi-Urban,HR Executive,58131,0 +101865,Female,35,Diploma,4,30,29,82,54,7.0,3,15,Urban,ML Engineer,148540,0 +101866,Male,59,Masters,13,34,77,34,35,6.0,1,78,Rural,Software Engineer,44077,0 +101867,Female,46,Diploma,14,45,73,33,23,8.0,7,4,Rural,HR Executive,60423,0 +101868,Male,48,PhD,0,76,87,95,11,7.0,3,34,Rural,Data Analyst,145335,1 +101869,Female,48,High School,16,86,4,62,57,1.0,6,36,Semi-Urban,HR Executive,112612,0 +101870,Male,33,Diploma,19,28,71,50,53,7.0,5,36,Urban,Software Engineer,75680,0 +101871,Female,50,Bachelors,4,93,3,70,60,8.0,5,39,Rural,Software Engineer,93300,0 +101872,Male,48,Bachelors,3,84,90,40,20,3.0,7,43,Rural,ML Engineer,142782,1 +101873,Male,30,Masters,7,43,84,20,56,3.0,1,40,Semi-Urban,ML Engineer,116179,0 +101874,Female,43,High School,7,56,67,46,39,2.0,2,87,Rural,Manager,25732,1 +101875,Male,45,Bachelors,15,56,33,46,73,3.0,6,89,Rural,Data Analyst,139656,0 +101876,Male,42,Bachelors,10,11,48,56,4,9.0,3,38,Rural,ML Engineer,111563,0 +101877,Male,49,PhD,6,61,98,44,66,8.0,2,51,Rural,Data Analyst,146527,1 +101878,Male,54,Diploma,11,88,77,65,84,1.0,4,31,Urban,Software Engineer,60290,1 +101879,Male,27,Diploma,4,30,41,83,93,9.0,7,23,Semi-Urban,Manager,138144,0 +101880,Male,27,Diploma,11,5,72,51,14,0.0,7,31,Urban,HR Executive,36905,0 +101881,Male,56,Masters,5,28,66,65,28,9.0,7,62,Semi-Urban,Software Engineer,71739,0 +101882,Female,46,Masters,4,81,3,71,67,0.0,1,16,Urban,Manager,124728,0 +101883,Male,38,High School,16,33,80,22,44,5.0,0,38,Urban,Manager,131851,0 +101884,Female,43,High School,12,93,14,72,67,4.0,1,70,Semi-Urban,Manager,73001,1 +101885,Female,50,Diploma,14,91,7,1,64,0.0,4,74,Urban,Manager,65019,0 +101886,Male,36,Bachelors,11,64,78,94,41,9.0,7,21,Urban,Data Analyst,83579,1 +101887,Male,30,Masters,6,94,31,26,43,5.0,5,47,Semi-Urban,ML Engineer,105812,0 +101888,Male,33,Bachelors,15,5,55,56,50,6.0,4,69,Urban,Data Analyst,109314,0 +101889,Female,34,Bachelors,5,42,10,30,91,7.0,2,93,Urban,Software Engineer,142001,0 +101890,Male,51,Bachelors,7,68,60,38,73,5.0,2,29,Urban,Software Engineer,98038,0 +101891,Female,52,Bachelors,2,24,47,13,10,6.0,5,96,Urban,ML Engineer,99141,0 +101892,Female,55,Diploma,15,38,34,80,84,4.0,3,26,Semi-Urban,Data Analyst,25192,0 +101893,Female,29,Bachelors,16,76,97,53,63,1.0,5,55,Urban,Manager,54681,1 +101894,Female,31,Bachelors,16,46,34,59,99,0.0,3,20,Rural,ML Engineer,77486,0 +101895,Male,59,Diploma,17,17,34,28,72,2.0,4,71,Urban,ML Engineer,58103,0 +101896,Female,49,Bachelors,4,17,64,96,77,8.0,6,72,Urban,HR Executive,94546,1 +101897,Female,54,Bachelors,12,97,65,96,70,5.0,7,92,Urban,ML Engineer,74149,1 +101898,Male,39,Masters,9,82,21,2,65,7.0,3,86,Urban,Manager,132475,0 +101899,Female,58,High School,10,58,15,17,34,8.0,7,99,Urban,ML Engineer,54004,0 +101900,Male,59,Masters,17,32,26,96,83,1.0,1,24,Rural,ML Engineer,26619,0 +101901,Male,28,Diploma,4,67,67,80,28,0.0,6,45,Semi-Urban,Manager,68441,1 +101902,Male,22,Masters,2,51,9,57,7,1.0,2,73,Semi-Urban,Manager,96412,0 +101903,Female,39,Diploma,4,11,15,49,66,1.0,6,52,Urban,Data Analyst,142018,0 +101904,Female,52,High School,5,8,52,34,36,8.0,5,22,Urban,Software Engineer,149808,0 +101905,Male,31,High School,3,32,49,36,21,0.0,4,46,Urban,HR Executive,119541,0 +101906,Male,49,Masters,5,86,31,23,2,7.0,3,81,Semi-Urban,HR Executive,30750,0 +101907,Male,27,Masters,3,19,93,96,76,8.0,6,85,Urban,Manager,76444,1 +101908,Female,43,Diploma,6,8,70,27,61,6.0,7,14,Rural,Data Analyst,42469,0 +101909,Female,21,High School,8,5,48,63,13,0.0,2,87,Urban,ML Engineer,49748,0 +101910,Female,24,Bachelors,0,4,98,91,91,6.0,1,25,Rural,ML Engineer,95876,0 +101911,Male,56,Masters,9,42,1,71,57,9.0,5,1,Rural,HR Executive,50918,0 +101912,Female,34,Masters,19,57,64,70,95,7.0,7,86,Rural,HR Executive,120537,1 +101913,Male,55,High School,16,80,46,40,36,3.0,7,93,Semi-Urban,HR Executive,42743,1 +101914,Male,51,Masters,2,34,15,79,28,3.0,7,39,Semi-Urban,Software Engineer,115810,0 +101915,Male,25,Masters,4,45,54,32,70,6.0,2,64,Rural,ML Engineer,39743,0 +101916,Male,36,Diploma,11,63,8,66,62,6.0,6,59,Urban,ML Engineer,21069,0 +101917,Male,46,Diploma,6,68,13,6,52,1.0,2,97,Urban,ML Engineer,110173,0 +101918,Female,29,Masters,12,81,92,6,96,3.0,4,67,Urban,Software Engineer,47432,1 +101919,Female,49,Bachelors,8,76,48,74,15,3.0,7,65,Urban,ML Engineer,33455,1 +101920,Male,21,Bachelors,19,78,40,31,22,6.0,6,52,Urban,ML Engineer,105391,0 +101921,Female,45,High School,7,54,67,31,51,5.0,0,63,Rural,Data Analyst,89020,0 +101922,Male,22,Masters,10,24,78,29,56,6.0,3,66,Urban,Data Analyst,104712,0 +101923,Female,41,High School,11,22,63,59,60,1.0,1,16,Urban,Manager,55847,0 +101924,Female,38,Bachelors,4,80,72,63,82,0.0,6,85,Urban,Software Engineer,37850,1 +101925,Female,29,High School,2,96,71,33,92,8.0,2,36,Semi-Urban,Manager,82926,0 +101926,Male,43,High School,13,95,87,61,53,3.0,6,7,Urban,Manager,46254,1 +101927,Male,35,Bachelors,2,74,52,67,35,8.0,0,37,Semi-Urban,HR Executive,27822,0 +101928,Male,52,Bachelors,2,25,87,75,98,1.0,5,99,Urban,Manager,36355,1 +101929,Female,29,High School,12,98,97,4,49,5.0,2,46,Semi-Urban,Software Engineer,125065,1 +101930,Female,59,Masters,19,6,96,73,82,6.0,0,66,Urban,Data Analyst,37436,1 +101931,Male,33,Bachelors,11,91,17,77,77,8.0,3,30,Urban,Data Analyst,52450,0 +101932,Male,56,High School,13,52,0,22,31,6.0,1,27,Urban,HR Executive,147500,0 +101933,Male,27,Masters,6,6,33,72,83,3.0,1,86,Rural,Data Analyst,144994,0 +101934,Female,21,Bachelors,10,60,60,22,18,2.0,1,10,Urban,ML Engineer,45096,0 +101935,Male,39,Bachelors,1,9,39,85,57,5.0,0,75,Urban,Software Engineer,27495,0 +101936,Male,56,Bachelors,4,74,50,75,7,3.0,1,79,Urban,Manager,54757,1 +101937,Male,59,Masters,12,3,6,60,73,1.0,4,27,Rural,HR Executive,128709,0 +101938,Male,58,Diploma,10,3,20,2,48,8.0,6,56,Urban,ML Engineer,21079,0 +101939,Male,50,Diploma,7,59,37,91,55,0.0,1,61,Urban,Manager,112641,1 +101940,Female,49,Bachelors,5,0,80,20,51,6.0,1,88,Rural,Software Engineer,100752,0 +101941,Male,52,Bachelors,18,29,41,57,27,5.0,2,19,Urban,Data Analyst,42778,0 +101942,Female,45,Diploma,0,67,23,90,62,4.0,1,43,Urban,HR Executive,23828,0 +101943,Female,52,Diploma,18,87,27,70,6,9.0,0,57,Rural,ML Engineer,124594,1 +101944,Other,27,Bachelors,17,88,20,95,90,1.0,1,96,Urban,Software Engineer,45351,1 +101945,Male,53,Masters,19,92,11,24,17,9.0,1,41,Urban,Data Analyst,110052,0 +101946,Female,30,Bachelors,12,99,68,81,83,2.0,5,13,Semi-Urban,HR Executive,90154,1 +101947,Female,36,Bachelors,3,97,84,87,22,4.0,4,62,Semi-Urban,Data Analyst,96250,1 +101948,Female,34,Diploma,9,29,39,49,71,2.0,1,27,Semi-Urban,HR Executive,75280,0 +101949,Male,56,Bachelors,11,87,72,91,45,6.0,7,69,Rural,HR Executive,105755,1 +101950,Male,56,Masters,13,47,66,89,83,0.0,5,77,Rural,Manager,46842,1 +101951,Male,58,Bachelors,19,56,48,63,54,1.0,5,4,Urban,Manager,84557,0 +101952,Male,23,Masters,8,22,53,50,53,9.0,3,0,Urban,Software Engineer,60439,0 +101953,Female,32,Diploma,5,58,7,35,77,8.0,1,53,Semi-Urban,HR Executive,22850,0 +101954,Male,44,Diploma,4,95,64,66,82,9.0,2,22,Urban,Data Analyst,30929,1 +101955,Female,49,Diploma,3,60,83,74,58,5.0,1,8,Urban,Software Engineer,86516,0 +101956,Male,41,Bachelors,11,86,38,92,67,1.0,3,37,Rural,Manager,79607,1 +101957,Male,52,Bachelors,12,69,58,33,24,7.0,3,37,Rural,HR Executive,27735,0 +101958,Female,40,Diploma,12,24,77,5,87,6.0,3,82,Urban,Data Analyst,89117,0 +101959,Male,39,Diploma,9,5,22,31,0,0.0,1,5,Rural,HR Executive,45408,0 +101960,Male,32,Bachelors,6,21,85,92,68,8.0,4,23,Urban,Software Engineer,61868,0 +101961,Female,42,Bachelors,1,98,30,28,9,6.0,4,15,Urban,Software Engineer,45726,0 +101962,Male,30,Diploma,0,32,13,94,37,8.0,5,62,Semi-Urban,Manager,84420,0 +101963,Female,22,Masters,14,46,10,26,6,4.0,3,53,Urban,Manager,59753,0 +101964,Female,26,Diploma,7,4,44,41,77,0.0,4,20,Urban,ML Engineer,77321,0 +101965,Male,44,Bachelors,13,14,88,14,93,1.0,6,65,Semi-Urban,Data Analyst,133504,0 +101966,Male,40,Bachelors,15,82,34,29,4,8.0,7,36,Semi-Urban,Software Engineer,95330,0 +101967,Male,34,High School,6,33,21,62,60,5.0,4,37,Urban,HR Executive,78742,0 +101968,Male,59,High School,12,44,87,38,21,1.0,2,57,Rural,Software Engineer,41461,0 +101969,Male,47,Diploma,8,38,25,83,13,5.0,2,69,Urban,Data Analyst,31286,0 +101970,Male,30,High School,4,73,9,8,90,4.0,0,25,Urban,ML Engineer,104718,0 +101971,Male,53,Masters,19,51,32,81,7,5.0,3,15,Rural,Software Engineer,21885,0 +101972,Male,29,Masters,4,65,23,39,49,3.0,3,97,Urban,Data Analyst,31138,0 +101973,Male,29,Masters,1,29,91,58,7,3.0,4,45,Rural,ML Engineer,89678,0 +101974,Female,33,Bachelors,14,76,62,25,59,5.0,6,7,Rural,Manager,86339,0 +101975,Female,26,Bachelors,5,87,99,44,23,7.0,0,2,Urban,HR Executive,124048,0 +101976,Male,50,High School,7,68,82,42,30,0.0,4,49,Semi-Urban,Software Engineer,101499,1 +101977,Male,31,Diploma,2,60,2,18,93,0.0,4,0,Urban,Manager,43708,0 +101978,Female,29,Bachelors,1,45,71,30,9,2.0,5,33,Semi-Urban,HR Executive,36506,0 +101979,Male,38,Bachelors,3,83,28,13,28,8.0,5,28,Semi-Urban,HR Executive,60975,0 +101980,Male,40,High School,13,6,15,63,10,3.0,3,34,Urban,Data Analyst,127153,0 +101981,Male,23,Diploma,15,98,60,52,46,4.0,4,8,Urban,ML Engineer,88263,0 +101982,Female,46,Masters,4,98,8,75,76,0.0,7,44,Urban,Data Analyst,110223,0 +101983,Female,25,PhD,14,9,42,87,28,0.0,2,68,Urban,Manager,149245,0 +101984,Male,36,PhD,8,8,56,87,28,3.0,2,7,Urban,HR Executive,134679,0 +101985,Male,35,Masters,5,24,45,76,78,2.0,5,97,Urban,ML Engineer,103320,1 +101986,Male,30,Masters,1,78,2,40,41,5.0,7,86,Rural,HR Executive,106275,0 +101987,Female,45,Bachelors,8,88,91,39,61,1.0,5,21,Urban,HR Executive,78701,0 +101988,Male,51,Masters,2,20,26,57,80,6.0,0,83,Semi-Urban,Data Analyst,111896,0 +101989,Male,58,Diploma,18,37,79,58,98,1.0,0,7,Urban,Software Engineer,28841,0 +101990,Female,23,Diploma,12,11,60,76,73,4.0,2,49,Rural,ML Engineer,50211,0 +101991,Male,36,Diploma,12,78,77,44,64,9.0,5,47,Rural,Software Engineer,78150,1 +101992,Male,58,Masters,14,13,86,89,13,0.0,6,10,Semi-Urban,Data Analyst,93857,0 +101993,Female,46,High School,3,86,79,5,73,7.0,0,89,Urban,Software Engineer,56276,1 +101994,Female,43,Diploma,16,66,59,81,63,6.0,0,13,Rural,Manager,130234,0 +101995,Other,57,Masters,8,22,55,5,37,4.0,0,35,Urban,Software Engineer,66453,0 +101996,Female,52,PhD,6,43,53,93,18,6.0,3,29,Urban,Data Analyst,45961,0 +101997,Male,21,Bachelors,19,26,28,70,50,3.0,2,82,Urban,Data Analyst,24728,0 +101998,Male,49,Bachelors,16,40,50,66,43,8.0,3,68,Rural,HR Executive,147568,0 +101999,Male,48,Diploma,0,32,78,55,68,1.0,3,24,Rural,ML Engineer,27253,0 +102000,Female,36,Bachelors,10,87,8,45,84,8.0,0,4,Urban,Data Analyst,125088,0 +102001,Female,43,Bachelors,1,15,56,47,8,5.0,3,96,Semi-Urban,ML Engineer,124712,0 +102002,Male,44,Bachelors,3,59,99,98,55,1.0,1,72,Rural,ML Engineer,100481,1 +102003,Other,32,Masters,1,10,79,81,61,2.0,7,15,Semi-Urban,Data Analyst,68157,0 +102004,Female,49,Masters,17,54,10,4,1,8.0,4,38,Urban,Software Engineer,123013,0 +102005,Female,57,Bachelors,0,82,42,15,31,2.0,0,86,Urban,Software Engineer,34496,0 +102006,Male,40,PhD,3,2,52,5,27,0.0,4,45,Rural,Manager,50727,0 +102007,Male,39,Diploma,18,16,6,51,25,1.0,4,78,Urban,Data Analyst,112386,0 +102008,Other,21,Diploma,13,91,32,68,97,8.0,1,25,Rural,ML Engineer,62183,0 +102009,Male,28,High School,14,8,73,15,64,0.0,1,23,Urban,Data Analyst,128565,0 +102010,Male,58,Bachelors,0,19,3,34,10,2.0,7,92,Urban,HR Executive,46131,0 +102011,Male,28,PhD,0,1,61,2,84,3.0,7,84,Urban,ML Engineer,116908,0 +102012,Male,40,High School,5,84,49,82,63,1.0,4,83,Urban,Software Engineer,107675,1 +102013,Male,38,Masters,8,9,93,56,18,4.0,3,21,Rural,Manager,134814,0 +102014,Male,41,Bachelors,17,42,75,1,36,8.0,0,2,Semi-Urban,ML Engineer,84687,0 +102015,Male,41,Bachelors,3,23,61,13,75,3.0,5,33,Urban,Data Analyst,60543,0 +102016,Male,41,Bachelors,5,30,2,82,63,0.0,2,48,Urban,Data Analyst,117543,0 +102017,Male,29,Bachelors,10,48,15,84,22,0.0,6,66,Semi-Urban,ML Engineer,62312,0 +102018,Male,34,PhD,13,50,52,2,6,4.0,6,42,Semi-Urban,Data Analyst,36743,0 +102019,Male,58,Bachelors,3,38,68,55,43,9.0,0,30,Rural,ML Engineer,91454,0 +102020,Female,50,Bachelors,12,48,98,34,31,9.0,2,62,Semi-Urban,ML Engineer,31927,1 +102021,Male,42,Diploma,17,61,68,75,54,8.0,4,43,Urban,Manager,35787,1 +102022,Other,54,PhD,6,85,75,83,65,0.0,4,15,Urban,HR Executive,34893,1 +102023,Male,53,Bachelors,4,55,56,81,11,2.0,2,0,Rural,Software Engineer,22892,0 +102024,Male,26,Diploma,12,19,72,2,14,7.0,5,74,Semi-Urban,ML Engineer,30198,0 +102025,Male,28,Bachelors,11,62,70,64,49,1.0,6,38,Urban,Software Engineer,99591,0 +102026,Male,32,Masters,11,82,47,54,19,5.0,5,1,Rural,ML Engineer,55318,0 +102027,Female,32,Bachelors,11,95,88,99,46,7.0,0,38,Urban,Software Engineer,130442,1 +102028,Male,43,Bachelors,11,57,55,22,21,7.0,3,42,Rural,Software Engineer,120647,0 +102029,Female,35,Diploma,0,49,33,29,51,4.0,0,47,Rural,Manager,136149,0 +102030,Female,51,Bachelors,1,8,67,90,38,8.0,7,55,Urban,Data Analyst,135854,0 +102031,Female,34,High School,15,74,69,32,32,8.0,2,89,Urban,ML Engineer,48920,1 +102032,Female,46,High School,19,20,73,25,0,4.0,3,85,Rural,ML Engineer,128939,0 +102033,Female,41,Bachelors,15,56,84,50,4,5.0,4,13,Rural,Software Engineer,84139,0 +102034,Male,50,Masters,18,18,63,39,37,3.0,6,26,Urban,HR Executive,89109,0 +102035,Male,24,Bachelors,15,21,64,13,31,3.0,4,92,Rural,Data Analyst,34846,0 +102036,Male,48,Diploma,19,27,69,80,43,3.0,2,26,Rural,Data Analyst,85089,0 +102037,Female,56,Diploma,3,98,44,37,91,8.0,1,50,Semi-Urban,Data Analyst,128877,0 +102038,Female,55,Bachelors,4,42,3,37,66,4.0,2,61,Semi-Urban,HR Executive,134833,0 +102039,Female,53,Bachelors,3,70,25,31,84,0.0,0,89,Urban,Data Analyst,75410,0 +102040,Female,48,High School,0,99,52,92,4,5.0,0,65,Semi-Urban,Data Analyst,101400,1 +102041,Male,22,Bachelors,1,66,97,18,31,8.0,0,89,Rural,HR Executive,126948,1 +102042,Male,26,High School,5,77,79,47,60,0.0,4,44,Urban,ML Engineer,67286,1 +102043,Male,49,Bachelors,16,24,8,85,75,8.0,5,92,Urban,HR Executive,112745,0 +102044,Male,50,PhD,5,79,12,97,26,1.0,6,23,Semi-Urban,Data Analyst,29601,0 +102045,Female,56,Diploma,2,18,99,7,81,0.0,0,35,Urban,HR Executive,33563,0 +102046,Male,26,Bachelors,2,25,66,92,46,9.0,3,43,Urban,Manager,112502,0 +102047,Male,22,Bachelors,6,81,27,13,71,4.0,7,30,Urban,ML Engineer,141856,0 +102048,Male,28,Bachelors,7,94,87,6,66,3.0,2,31,Rural,HR Executive,59393,0 +102049,Female,52,PhD,4,51,63,15,63,0.0,6,7,Semi-Urban,Software Engineer,32185,0 +102050,Female,53,Bachelors,17,33,70,65,62,0.0,7,45,Semi-Urban,HR Executive,79522,0 +102051,Female,45,Diploma,14,98,62,94,28,7.0,0,97,Rural,Data Analyst,55093,1 +102052,Male,46,Masters,17,67,9,95,40,9.0,6,72,Urban,Software Engineer,77698,1 +102053,Female,57,Bachelors,3,7,0,0,3,7.0,2,76,Rural,Software Engineer,116370,0 +102054,Male,21,Masters,18,13,58,86,40,0.0,7,35,Urban,Manager,26097,0 +102055,Male,27,Masters,10,35,51,56,11,0.0,6,57,Rural,Data Analyst,58385,0 +102056,Male,29,Bachelors,14,8,68,69,65,9.0,2,91,Semi-Urban,Data Analyst,86310,1 +102057,Male,43,Masters,17,65,75,36,42,7.0,6,96,Urban,Software Engineer,33058,1 +102058,Male,21,High School,8,87,76,83,27,9.0,7,11,Semi-Urban,Data Analyst,114172,1 +102059,Male,31,Bachelors,10,58,40,71,21,2.0,4,89,Urban,Data Analyst,133018,1 +102060,Male,37,Masters,6,22,80,7,27,5.0,7,93,Rural,Manager,56735,0 +102061,Male,28,High School,4,10,52,16,25,2.0,3,57,Urban,Manager,145879,0 +102062,Male,44,High School,11,79,58,87,95,7.0,6,2,Urban,ML Engineer,133713,0 +102063,Male,49,Diploma,16,2,91,46,91,7.0,3,60,Rural,Data Analyst,145683,0 +102064,Female,50,Diploma,16,1,72,24,72,6.0,3,61,Semi-Urban,Data Analyst,92328,0 +102065,Male,26,Bachelors,7,49,31,80,74,5.0,1,44,Urban,ML Engineer,143424,0 +102066,Male,28,Bachelors,7,14,71,56,86,9.0,4,67,Rural,ML Engineer,52230,0 +102067,Male,40,Bachelors,2,15,62,42,21,4.0,4,20,Rural,Software Engineer,147284,0 +102068,Female,35,Diploma,17,53,77,71,1,5.0,6,33,Urban,ML Engineer,101399,0 +102069,Female,40,Bachelors,11,98,88,16,60,4.0,7,19,Rural,Data Analyst,83987,0 +102070,Male,41,Bachelors,10,31,27,39,3,3.0,0,95,Rural,Software Engineer,87589,0 +102071,Male,27,Masters,19,45,26,44,59,4.0,1,99,Rural,Software Engineer,85585,0 +102072,Female,41,Masters,4,77,98,57,41,0.0,3,84,Semi-Urban,Manager,95678,1 +102073,Male,56,Bachelors,15,19,28,3,15,1.0,0,2,Rural,Data Analyst,147523,0 +102074,Male,30,PhD,11,3,90,61,45,0.0,6,61,Semi-Urban,HR Executive,26615,0 +102075,Male,27,Bachelors,10,44,92,66,42,8.0,4,15,Rural,Data Analyst,115165,0 +102076,Male,45,Diploma,19,79,76,77,59,8.0,7,9,Rural,HR Executive,87487,1 +102077,Male,54,High School,13,55,51,58,47,5.0,3,53,Semi-Urban,Software Engineer,82843,0 +102078,Female,29,Bachelors,4,15,84,40,54,5.0,6,81,Urban,HR Executive,38448,0 +102079,Male,38,Diploma,0,22,93,57,59,6.0,4,64,Urban,Manager,57554,1 +102080,Male,22,High School,8,45,62,41,16,8.0,3,1,Semi-Urban,Manager,67783,0 +102081,Female,32,Diploma,5,81,72,14,4,7.0,1,8,Semi-Urban,Manager,23906,0 +102082,Female,22,Diploma,15,0,97,23,73,5.0,2,6,Rural,Manager,99355,0 +102083,Other,57,Masters,4,79,87,96,30,1.0,7,63,Semi-Urban,Manager,145518,1 +102084,Male,49,High School,7,84,35,0,2,5.0,4,59,Urban,Data Analyst,106000,0 +102085,Male,54,Bachelors,14,48,72,6,22,7.0,0,58,Urban,ML Engineer,62084,0 +102086,Other,29,Bachelors,17,4,30,64,23,0.0,5,44,Semi-Urban,ML Engineer,40576,0 +102087,Male,29,Diploma,2,66,82,37,92,3.0,7,3,Rural,Software Engineer,27539,0 +102088,Male,52,High School,11,94,6,35,42,2.0,7,66,Semi-Urban,HR Executive,52366,0 +102089,Female,59,Masters,12,59,14,24,38,2.0,4,80,Urban,HR Executive,70127,0 +102090,Male,53,Bachelors,0,29,95,25,55,6.0,2,56,Urban,Software Engineer,98364,0 +102091,Male,49,Diploma,6,17,94,42,51,3.0,5,80,Urban,Data Analyst,24297,0 +102092,Male,56,Bachelors,13,85,14,5,93,5.0,3,97,Urban,Manager,96271,0 +102093,Male,53,PhD,11,70,35,62,90,5.0,0,57,Urban,ML Engineer,147768,0 +102094,Male,21,Bachelors,13,28,52,0,3,3.0,5,0,Rural,ML Engineer,78858,0 +102095,Female,22,Bachelors,7,94,54,84,37,1.0,1,45,Urban,Data Analyst,98059,1 +102096,Male,27,Bachelors,1,49,66,34,88,0.0,5,58,Urban,ML Engineer,67695,0 +102097,Male,24,Bachelors,13,59,55,77,81,1.0,7,55,Semi-Urban,Software Engineer,111674,1 +102098,Male,50,Diploma,12,20,69,72,80,1.0,1,57,Urban,Data Analyst,108170,0 +102099,Male,27,Diploma,15,6,27,49,47,7.0,4,24,Urban,HR Executive,77138,0 +102100,Male,54,Diploma,11,46,69,30,19,2.0,2,32,Semi-Urban,HR Executive,132824,0 +102101,Male,28,Bachelors,18,96,69,37,59,2.0,1,55,Urban,Manager,55253,1 +102102,Male,42,Diploma,14,57,36,52,3,0.0,5,50,Urban,Data Analyst,34489,0 +102103,Female,55,Diploma,7,66,65,39,75,0.0,4,93,Urban,Data Analyst,141607,1 +102104,Female,39,Diploma,13,39,17,3,45,4.0,1,57,Urban,Software Engineer,64233,0 +102105,Male,37,Bachelors,3,19,69,44,88,3.0,3,99,Urban,ML Engineer,137299,0 +102106,Male,49,High School,17,56,63,16,92,6.0,4,81,Semi-Urban,Manager,135248,0 +102107,Male,29,Bachelors,18,89,9,88,89,6.0,3,24,Rural,HR Executive,61617,0 +102108,Female,45,High School,11,42,54,6,76,7.0,5,40,Urban,Data Analyst,119332,0 +102109,Male,33,Bachelors,10,83,87,83,52,4.0,3,96,Rural,HR Executive,149438,1 +102110,Male,30,Diploma,5,17,37,21,59,6.0,5,58,Rural,Data Analyst,124890,0 +102111,Male,24,Bachelors,18,96,54,53,99,0.0,0,16,Urban,Data Analyst,24324,0 +102112,Male,30,Diploma,18,68,12,95,89,5.0,7,30,Rural,ML Engineer,41250,0 +102113,Female,30,Masters,14,47,50,87,34,3.0,0,67,Urban,HR Executive,21643,1 +102114,Male,36,Diploma,14,26,50,34,99,0.0,2,24,Urban,HR Executive,48152,0 +102115,Male,56,Bachelors,10,21,36,71,97,0.0,7,55,Urban,Manager,148566,0 +102116,Other,36,Masters,6,41,19,73,61,8.0,1,33,Urban,ML Engineer,117478,0 +102117,Female,25,Diploma,17,64,35,16,75,9.0,1,43,Semi-Urban,ML Engineer,144144,0 +102118,Female,52,Masters,13,90,60,66,13,2.0,7,56,Semi-Urban,Manager,67845,1 +102119,Female,35,Diploma,17,13,94,44,85,5.0,5,83,Rural,Software Engineer,82722,0 +102120,Male,44,Diploma,19,5,94,96,6,8.0,6,79,Urban,Manager,102488,1 +102121,Male,34,Diploma,5,21,82,22,72,0.0,3,23,Urban,Manager,107419,0 +102122,Male,34,Bachelors,16,83,75,46,33,8.0,7,17,Urban,ML Engineer,147849,0 +102123,Male,25,Diploma,12,96,26,90,23,8.0,0,97,Rural,HR Executive,79249,1 +102124,Male,54,Diploma,0,48,36,63,47,6.0,7,26,Urban,Data Analyst,51930,0 +102125,Female,58,Diploma,19,29,68,79,53,5.0,6,16,Rural,ML Engineer,109590,0 +102126,Male,53,High School,9,5,9,40,3,0.0,1,2,Rural,ML Engineer,41596,0 +102127,Male,47,Bachelors,2,53,15,18,25,3.0,2,52,Urban,Data Analyst,60391,0 +102128,Male,42,Diploma,15,97,59,27,51,5.0,3,65,Semi-Urban,Software Engineer,71888,1 +102129,Female,34,Bachelors,18,36,32,43,89,2.0,1,45,Semi-Urban,Manager,128164,0 +102130,Male,37,Bachelors,7,26,81,91,97,9.0,1,61,Rural,Software Engineer,44963,1 +102131,Male,54,Masters,5,46,55,46,86,9.0,1,67,Rural,Manager,148845,0 +102132,Female,32,Masters,2,73,1,38,14,2.0,2,28,Urban,Data Analyst,100543,0 +102133,Male,46,Bachelors,15,28,39,57,35,4.0,6,68,Urban,Data Analyst,74711,0 +102134,Female,42,High School,14,1,66,98,80,8.0,3,38,Semi-Urban,Data Analyst,109742,0 +102135,Male,29,Masters,12,50,32,9,3,6.0,6,10,Urban,Software Engineer,45960,0 +102136,Male,43,High School,7,44,7,51,23,5.0,7,51,Urban,Software Engineer,46198,0 +102137,Male,27,Diploma,1,45,79,15,29,6.0,1,77,Urban,Data Analyst,147333,0 +102138,Female,58,Bachelors,2,70,69,89,90,8.0,5,86,Semi-Urban,ML Engineer,140333,1 +102139,Male,50,Diploma,8,76,53,72,84,0.0,7,43,Urban,ML Engineer,79572,1 +102140,Female,58,Masters,14,82,35,33,81,3.0,3,77,Semi-Urban,Software Engineer,124193,0 +102141,Female,53,Masters,15,8,73,14,76,7.0,5,12,Urban,HR Executive,43668,0 +102142,Male,51,Masters,3,12,85,77,60,0.0,5,99,Semi-Urban,ML Engineer,123382,1 +102143,Female,37,Masters,4,97,39,7,59,4.0,4,53,Rural,ML Engineer,136070,0 +102144,Male,30,Bachelors,13,39,10,15,60,7.0,4,53,Rural,HR Executive,95981,0 +102145,Male,33,Diploma,10,30,64,62,18,7.0,5,48,Urban,Data Analyst,26996,0 +102146,Male,43,Diploma,15,69,5,63,65,1.0,2,63,Semi-Urban,ML Engineer,143446,0 +102147,Male,48,Bachelors,14,64,79,80,2,2.0,6,61,Urban,Data Analyst,81608,1 +102148,Female,51,Diploma,18,17,44,99,81,9.0,7,86,Urban,Software Engineer,79874,1 +102149,Male,31,Masters,9,90,3,9,48,4.0,2,40,Urban,Manager,79610,0 +102150,Female,36,Bachelors,4,14,51,74,23,5.0,5,98,Urban,Manager,56358,0 +102151,Male,39,Bachelors,5,79,3,90,62,2.0,1,91,Rural,Software Engineer,41473,1 +102152,Male,55,High School,10,81,68,38,54,8.0,1,23,Urban,Manager,142188,0 +102153,Female,42,Masters,12,85,64,73,89,5.0,4,42,Semi-Urban,ML Engineer,62811,1 +102154,Male,36,Bachelors,16,42,45,79,82,5.0,6,73,Urban,ML Engineer,96626,1 +102155,Male,47,Bachelors,12,94,70,35,74,7.0,0,39,Semi-Urban,ML Engineer,98034,1 +102156,Female,35,High School,5,35,62,16,80,4.0,0,74,Urban,Data Analyst,117594,0 +102157,Male,37,Diploma,1,22,55,55,68,6.0,4,63,Semi-Urban,Manager,52458,0 +102158,Female,50,Masters,5,34,96,60,79,6.0,5,64,Urban,HR Executive,140847,1 +102159,Male,24,Bachelors,13,75,49,25,80,7.0,7,22,Semi-Urban,ML Engineer,129544,0 +102160,Male,27,Masters,15,17,22,23,29,9.0,1,73,Rural,Data Analyst,38818,0 +102161,Female,23,Bachelors,14,75,64,71,66,7.0,7,92,Urban,HR Executive,131337,1 +102162,Male,43,High School,10,40,23,27,23,5.0,0,49,Rural,Software Engineer,25962,0 +102163,Female,22,High School,3,22,94,77,5,5.0,0,50,Urban,Data Analyst,52138,1 +102164,Male,57,Bachelors,12,77,32,71,35,1.0,3,78,Urban,Software Engineer,88347,1 +102165,Male,45,Bachelors,15,54,2,15,56,3.0,6,77,Semi-Urban,Manager,59613,0 +102166,Female,34,Bachelors,12,37,25,79,72,4.0,5,3,Urban,HR Executive,77193,0 +102167,Female,45,Masters,5,3,12,76,53,6.0,6,65,Urban,HR Executive,118904,0 +102168,Female,54,Masters,0,11,98,1,19,1.0,5,4,Semi-Urban,Data Analyst,96524,0 +102169,Male,40,Diploma,15,56,82,62,42,5.0,3,56,Rural,ML Engineer,48692,1 +102170,Male,29,High School,5,92,96,51,70,7.0,3,16,Urban,Manager,27048,1 +102171,Female,25,PhD,5,21,38,79,82,4.0,6,95,Urban,Data Analyst,31829,0 +102172,Male,24,Bachelors,10,2,40,47,86,8.0,5,42,Urban,Manager,72258,0 +102173,Male,23,Diploma,1,84,71,70,82,4.0,5,58,Urban,ML Engineer,69699,1 +102174,Female,27,High School,17,31,39,13,26,5.0,7,59,Urban,Software Engineer,67732,0 +102175,Male,37,High School,6,90,56,90,42,4.0,6,99,Semi-Urban,HR Executive,116435,1 +102176,Male,28,Diploma,18,14,81,5,56,8.0,3,64,Urban,ML Engineer,22999,0 +102177,Male,26,Masters,13,4,65,4,16,5.0,0,24,Urban,Data Analyst,81870,0 +102178,Male,35,Bachelors,16,59,72,31,28,4.0,0,14,Semi-Urban,Data Analyst,95025,0 +102179,Female,41,Bachelors,4,78,27,79,38,5.0,0,78,Rural,ML Engineer,141143,1 +102180,Female,54,Bachelors,0,17,82,56,52,5.0,5,77,Urban,Manager,115011,0 +102181,Female,23,High School,4,99,11,86,53,8.0,7,68,Urban,Manager,113975,1 +102182,Female,51,Bachelors,9,52,76,78,25,4.0,2,97,Semi-Urban,Software Engineer,125961,1 +102183,Male,58,Masters,6,59,70,61,99,7.0,2,85,Semi-Urban,Manager,126750,1 +102184,Female,21,High School,3,43,96,45,65,3.0,1,60,Rural,Software Engineer,100822,1 +102185,Male,39,Masters,10,36,0,82,19,9.0,2,61,Urban,HR Executive,132496,0 +102186,Male,44,Diploma,17,96,36,60,39,5.0,4,43,Semi-Urban,ML Engineer,120763,1 +102187,Male,22,Masters,4,81,51,95,0,9.0,7,51,Urban,ML Engineer,127510,1 +102188,Male,36,Bachelors,11,92,88,83,22,8.0,3,12,Urban,HR Executive,49826,1 +102189,Female,53,Bachelors,5,46,69,4,98,5.0,6,72,Rural,ML Engineer,51494,0 +102190,Male,40,Diploma,10,73,80,33,20,6.0,5,34,Urban,HR Executive,129199,0 +102191,Other,56,Masters,13,96,96,99,47,8.0,4,92,Urban,HR Executive,37370,1 +102192,Female,25,Diploma,11,79,38,62,66,4.0,1,82,Urban,HR Executive,115786,1 +102193,Female,38,Bachelors,17,74,17,42,34,4.0,0,91,Semi-Urban,Data Analyst,135821,0 +102194,Male,26,High School,10,62,72,1,27,5.0,2,45,Urban,Data Analyst,44386,0 +102195,Female,45,Diploma,13,99,35,59,22,7.0,2,62,Urban,ML Engineer,75986,1 +102196,Male,23,Bachelors,17,37,33,83,44,0.0,4,74,Rural,ML Engineer,146782,0 +102197,Female,29,Bachelors,12,81,28,11,73,1.0,1,19,Urban,Software Engineer,100427,0 +102198,Female,25,Bachelors,0,49,25,27,95,4.0,1,75,Urban,Software Engineer,53405,0 +102199,Male,28,Bachelors,7,42,53,42,11,9.0,6,60,Urban,Manager,41153,0 +102200,Female,31,Bachelors,7,69,51,41,98,8.0,0,32,Semi-Urban,HR Executive,119946,0 +102201,Male,26,Masters,13,47,63,13,26,5.0,5,35,Semi-Urban,Data Analyst,56106,0 +102202,Female,58,Masters,2,97,91,30,94,6.0,6,63,Urban,ML Engineer,34390,1 +102203,Male,39,Bachelors,5,93,30,20,7,2.0,7,75,Urban,HR Executive,127785,0 +102204,Female,56,Diploma,18,10,50,33,42,1.0,5,75,Urban,Software Engineer,83681,0 +102205,Male,51,Diploma,18,52,7,56,16,3.0,4,94,Urban,Data Analyst,129909,0 +102206,Female,22,PhD,18,48,45,1,31,6.0,6,54,Semi-Urban,Data Analyst,100821,0 +102207,Male,49,High School,18,31,44,76,90,9.0,6,32,Semi-Urban,HR Executive,122850,0 +102208,Male,57,Bachelors,7,13,52,21,8,3.0,6,1,Rural,ML Engineer,59123,0 +102209,Male,23,Bachelors,16,85,6,40,59,1.0,0,98,Semi-Urban,Software Engineer,139588,0 +102210,Other,55,Bachelors,0,49,46,92,31,3.0,0,79,Urban,Data Analyst,55243,1 +102211,Male,33,Bachelors,16,43,12,42,31,1.0,7,18,Urban,ML Engineer,64478,0 +102212,Male,53,Diploma,6,63,9,32,58,4.0,0,31,Rural,HR Executive,90939,0 +102213,Male,40,High School,15,36,46,37,62,5.0,1,46,Urban,Data Analyst,82055,0 +102214,Other,54,Masters,11,81,57,84,50,8.0,6,28,Semi-Urban,HR Executive,51126,1 +102215,Female,26,Diploma,7,38,51,37,12,1.0,1,23,Urban,HR Executive,115444,0 +102216,Male,58,Bachelors,14,17,37,69,81,4.0,0,83,Semi-Urban,HR Executive,75979,0 +102217,Female,38,Bachelors,7,6,65,35,39,9.0,1,31,Urban,HR Executive,117361,0 +102218,Female,45,Bachelors,5,56,53,30,41,4.0,0,55,Rural,HR Executive,122818,0 +102219,Female,25,Masters,17,14,65,37,69,9.0,0,69,Semi-Urban,Data Analyst,67916,0 +102220,Male,54,Diploma,4,74,51,5,26,4.0,1,4,Urban,Software Engineer,83796,0 +102221,Male,37,Bachelors,2,11,28,97,32,6.0,2,63,Urban,Software Engineer,77798,0 +102222,Female,42,Bachelors,10,94,38,57,86,5.0,4,47,Semi-Urban,Data Analyst,26093,0 +102223,Male,30,High School,18,52,88,95,4,6.0,1,50,Semi-Urban,Data Analyst,97449,1 +102224,Male,41,Bachelors,8,96,15,71,65,4.0,2,43,Urban,Software Engineer,25736,0 +102225,Other,21,Masters,4,24,25,37,71,4.0,3,2,Urban,Manager,135124,0 +102226,Female,44,Masters,13,50,98,53,99,4.0,7,60,Urban,Data Analyst,109334,1 +102227,Male,42,Masters,7,32,52,4,9,1.0,0,36,Urban,Manager,26519,0 +102228,Male,40,Diploma,3,86,96,43,26,0.0,0,74,Urban,Software Engineer,100217,1 +102229,Male,43,Diploma,3,79,21,37,33,2.0,0,60,Urban,Software Engineer,75061,0 +102230,Male,37,Masters,10,76,73,50,10,4.0,7,95,Urban,Data Analyst,86849,1 +102231,Female,38,Diploma,18,86,35,26,26,9.0,1,50,Urban,Software Engineer,116593,0 +102232,Other,40,Masters,6,92,81,50,73,7.0,0,85,Rural,Data Analyst,90523,1 +102233,Male,27,Masters,10,60,89,48,80,6.0,1,65,Rural,Manager,139608,1 +102234,Male,51,PhD,10,7,81,74,10,7.0,4,45,Urban,HR Executive,54170,0 +102235,Male,47,Masters,17,99,19,93,57,7.0,5,6,Urban,Software Engineer,88080,0 +102236,Female,35,Masters,0,83,85,96,36,5.0,0,58,Urban,Manager,131976,1 +102237,Male,54,Bachelors,7,0,2,79,8,6.0,6,94,Urban,HR Executive,113865,0 +102238,Female,44,Masters,4,15,67,98,48,1.0,4,42,Urban,Data Analyst,24803,0 +102239,Male,44,Diploma,2,36,84,41,30,7.0,7,29,Urban,ML Engineer,55274,0 +102240,Male,42,High School,6,61,32,40,64,1.0,3,96,Semi-Urban,Software Engineer,51543,0 +102241,Other,31,Diploma,0,88,11,43,18,6.0,2,36,Rural,Data Analyst,131087,0 +102242,Male,48,Bachelors,0,39,17,99,29,6.0,5,33,Urban,Software Engineer,106810,0 +102243,Male,37,Bachelors,0,41,56,40,66,0.0,2,74,Urban,Software Engineer,134273,0 +102244,Male,34,Diploma,18,42,94,12,73,0.0,6,61,Semi-Urban,Data Analyst,146445,0 +102245,Male,34,Diploma,13,67,22,20,42,6.0,0,64,Urban,Data Analyst,67152,0 +102246,Male,57,Masters,2,49,25,6,54,0.0,6,86,Urban,Manager,23745,0 +102247,Other,42,Bachelors,2,46,72,8,53,5.0,5,75,Rural,Software Engineer,120106,0 +102248,Male,31,Bachelors,16,4,54,22,78,7.0,0,32,Urban,ML Engineer,44374,0 +102249,Male,53,Diploma,19,63,68,0,19,2.0,5,45,Semi-Urban,Software Engineer,89834,0 +102250,Male,29,Bachelors,6,68,50,42,78,1.0,5,69,Rural,Data Analyst,38593,0 +102251,Male,31,Bachelors,19,59,67,66,98,5.0,7,95,Urban,Data Analyst,53754,1 +102252,Male,40,Bachelors,0,13,77,7,64,1.0,7,97,Rural,Manager,68302,0 +102253,Male,36,Bachelors,12,8,29,41,52,2.0,4,97,Urban,ML Engineer,133195,0 +102254,Male,46,High School,17,63,71,41,39,5.0,7,21,Semi-Urban,Manager,67497,0 +102255,Female,42,Bachelors,14,94,84,70,92,2.0,4,8,Urban,Manager,61813,1 +102256,Female,27,Masters,16,0,41,29,45,0.0,7,2,Urban,Software Engineer,69766,0 +102257,Male,50,Bachelors,8,99,36,61,68,6.0,2,16,Semi-Urban,Data Analyst,28935,0 +102258,Male,34,High School,14,93,57,53,35,6.0,3,95,Rural,Software Engineer,107269,1 +102259,Other,57,Bachelors,8,89,78,46,21,3.0,4,51,Urban,Manager,35833,1 +102260,Male,30,High School,4,95,26,89,85,2.0,3,34,Urban,Data Analyst,50975,1 +102261,Male,36,Bachelors,0,76,96,8,45,1.0,4,4,Urban,Software Engineer,128472,0 +102262,Male,56,Bachelors,16,22,46,26,99,2.0,4,66,Semi-Urban,Manager,88263,0 +102263,Female,39,High School,1,7,21,33,38,2.0,0,90,Semi-Urban,Manager,31851,0 +102264,Male,58,Diploma,13,66,21,62,60,1.0,5,65,Urban,Data Analyst,73537,0 +102265,Male,31,PhD,5,87,87,58,11,6.0,4,46,Urban,ML Engineer,125540,1 +102266,Male,28,Masters,15,39,42,18,31,9.0,4,80,Urban,ML Engineer,121898,0 +102267,Male,41,Diploma,18,15,70,33,34,2.0,6,13,Urban,ML Engineer,73028,0 +102268,Female,50,Bachelors,5,5,30,60,90,2.0,2,24,Urban,Data Analyst,63542,0 +102269,Male,50,PhD,17,13,33,13,89,8.0,3,65,Urban,HR Executive,109278,0 +102270,Male,29,Masters,19,72,6,96,76,5.0,0,64,Urban,Data Analyst,149818,1 +102271,Male,47,Masters,1,52,8,60,97,1.0,7,30,Urban,Software Engineer,109110,0 +102272,Male,41,Bachelors,7,20,29,6,39,7.0,6,96,Urban,HR Executive,112934,0 +102273,Other,54,Masters,11,11,35,40,98,9.0,3,9,Rural,ML Engineer,40328,0 +102274,Female,55,Bachelors,15,64,83,35,30,3.0,6,97,Semi-Urban,HR Executive,128743,1 +102275,Male,52,PhD,14,6,26,44,81,1.0,1,69,Urban,Manager,87039,0 +102276,Female,35,Bachelors,2,65,37,26,5,1.0,7,74,Rural,Software Engineer,104122,0 +102277,Male,49,Bachelors,4,93,70,98,84,9.0,0,13,Urban,Manager,146858,1 +102278,Male,41,Masters,3,62,49,8,12,4.0,2,7,Urban,Software Engineer,139101,0 +102279,Male,33,Bachelors,12,52,88,26,70,5.0,2,83,Semi-Urban,HR Executive,76549,1 +102280,Male,39,Bachelors,11,79,49,96,41,2.0,2,65,Rural,HR Executive,147752,1 +102281,Female,55,Bachelors,16,72,52,93,54,7.0,7,98,Urban,Data Analyst,41143,1 +102282,Male,29,High School,11,29,21,15,63,5.0,2,58,Urban,Software Engineer,82658,0 +102283,Male,24,Diploma,10,78,88,6,34,1.0,3,67,Urban,ML Engineer,148253,1 +102284,Female,55,Masters,9,6,45,74,67,3.0,5,98,Urban,HR Executive,53161,0 +102285,Male,29,Masters,3,5,52,35,94,1.0,7,74,Urban,Manager,138631,0 +102286,Male,30,Bachelors,12,47,70,27,81,6.0,0,19,Semi-Urban,HR Executive,98379,0 +102287,Male,22,Diploma,14,47,61,21,41,5.0,2,54,Semi-Urban,Data Analyst,82051,0 +102288,Male,31,High School,17,40,88,52,19,1.0,1,28,Rural,Data Analyst,26511,0 +102289,Male,59,Diploma,8,94,20,34,29,8.0,0,84,Urban,Manager,134401,0 +102290,Male,45,Bachelors,15,10,14,7,10,8.0,1,82,Urban,HR Executive,96055,0 +102291,Male,33,Masters,4,28,46,81,29,7.0,1,23,Semi-Urban,Data Analyst,142070,0 +102292,Male,48,Masters,8,55,28,50,35,2.0,7,23,Rural,Software Engineer,70587,0 +102293,Male,35,Bachelors,17,84,26,29,98,5.0,6,39,Urban,HR Executive,22869,0 +102294,Male,41,Masters,3,28,50,12,61,5.0,0,89,Urban,ML Engineer,70594,0 +102295,Male,31,Diploma,18,63,87,5,3,6.0,0,94,Urban,ML Engineer,22477,1 +102296,Male,38,Bachelors,7,68,36,84,67,7.0,3,37,Urban,Manager,120577,0 +102297,Female,43,Bachelors,2,64,59,37,21,1.0,5,67,Urban,ML Engineer,34438,0 +102298,Female,58,PhD,4,31,93,12,45,0.0,1,26,Semi-Urban,Manager,20529,0 +102299,Other,43,Masters,18,10,95,7,75,2.0,0,53,Urban,Software Engineer,112508,0 +102300,Male,59,Bachelors,14,93,97,84,56,4.0,1,12,Rural,ML Engineer,127988,1 +102301,Male,56,Diploma,8,10,57,73,0,8.0,7,76,Semi-Urban,Manager,93803,0 +102302,Female,47,Diploma,4,41,45,59,53,3.0,7,54,Semi-Urban,Software Engineer,62585,0 +102303,Female,32,High School,8,73,17,97,46,4.0,0,61,Urban,Data Analyst,61825,1 +102304,Male,25,Bachelors,17,29,67,30,15,4.0,6,99,Urban,HR Executive,51144,0 +102305,Male,52,Bachelors,11,42,4,16,40,9.0,7,72,Urban,HR Executive,144554,0 +102306,Female,46,Diploma,19,18,23,53,24,2.0,7,14,Semi-Urban,Software Engineer,84440,0 +102307,Male,21,High School,1,41,80,19,70,2.0,6,50,Rural,Software Engineer,144210,0 +102308,Male,57,Bachelors,6,89,74,48,8,4.0,7,73,Semi-Urban,Software Engineer,45167,1 +102309,Male,55,Masters,11,35,96,71,16,2.0,2,52,Urban,Data Analyst,108747,1 +102310,Male,51,PhD,0,2,71,11,60,8.0,5,73,Rural,Data Analyst,53701,0 +102311,Female,50,Masters,17,74,10,83,33,6.0,4,42,Rural,Manager,53969,0 +102312,Male,41,Bachelors,9,50,71,93,85,2.0,1,50,Urban,ML Engineer,44044,1 +102313,Male,42,High School,7,22,98,73,79,5.0,1,52,Urban,Software Engineer,80869,1 +102314,Female,21,Bachelors,19,8,90,59,41,5.0,6,66,Semi-Urban,ML Engineer,120746,0 +102315,Female,45,Bachelors,3,23,1,37,8,0.0,1,84,Rural,Data Analyst,111272,0 +102316,Male,36,Bachelors,7,20,84,60,41,1.0,1,27,Urban,ML Engineer,101984,0 +102317,Male,55,Bachelors,10,15,95,54,84,8.0,1,65,Urban,HR Executive,63145,0 +102318,Female,36,Masters,10,31,20,97,59,6.0,1,34,Semi-Urban,Data Analyst,74414,0 +102319,Female,24,Masters,18,59,68,0,15,0.0,4,44,Urban,HR Executive,78570,0 +102320,Male,49,High School,11,38,61,72,84,2.0,7,35,Urban,Manager,71409,0 +102321,Other,55,Diploma,2,22,55,72,14,2.0,4,85,Semi-Urban,Manager,44126,0 +102322,Male,23,Bachelors,10,10,62,1,93,9.0,1,16,Semi-Urban,Data Analyst,116882,0 +102323,Male,35,Diploma,13,45,90,77,57,4.0,4,22,Semi-Urban,Software Engineer,96126,0 +102324,Male,52,Masters,11,90,90,36,85,3.0,2,51,Urban,Data Analyst,44149,1 +102325,Female,56,PhD,0,92,64,85,58,4.0,7,31,Urban,HR Executive,93583,1 +102326,Male,46,Masters,15,99,58,7,39,8.0,3,35,Urban,Software Engineer,60444,0 +102327,Male,34,High School,11,26,64,43,48,7.0,0,97,Semi-Urban,Software Engineer,114907,0 +102328,Female,41,High School,8,85,99,51,29,5.0,5,77,Urban,Software Engineer,111330,1 +102329,Female,45,Bachelors,6,66,82,9,93,6.0,0,47,Rural,Data Analyst,146087,0 +102330,Female,55,Masters,13,11,9,85,78,3.0,1,44,Urban,Data Analyst,85101,0 +102331,Female,54,Diploma,5,46,35,41,62,7.0,4,95,Semi-Urban,ML Engineer,143398,0 +102332,Male,33,Bachelors,11,57,47,60,63,1.0,2,6,Urban,Software Engineer,93029,0 +102333,Male,39,Diploma,10,19,17,77,97,4.0,7,22,Rural,Data Analyst,100308,0 +102334,Male,22,Bachelors,14,21,46,42,41,3.0,2,85,Rural,Manager,44534,0 +102335,Female,33,Bachelors,10,85,75,95,32,8.0,4,76,Urban,Manager,112171,1 +102336,Female,35,High School,13,72,43,35,87,0.0,0,4,Rural,Data Analyst,60259,0 +102337,Male,55,Diploma,0,27,99,9,3,1.0,7,13,Urban,Data Analyst,55402,0 +102338,Female,58,Masters,1,88,91,71,93,5.0,5,95,Urban,Manager,109423,1 +102339,Male,56,Diploma,18,31,85,81,16,8.0,4,2,Semi-Urban,Manager,49812,0 +102340,Male,55,Masters,19,86,55,72,51,8.0,5,37,Semi-Urban,Data Analyst,61580,1 +102341,Male,52,Diploma,1,5,60,95,9,1.0,1,96,Semi-Urban,Software Engineer,45939,1 +102342,Male,59,Diploma,8,98,72,49,14,2.0,7,15,Rural,Data Analyst,142106,0 +102343,Male,40,High School,13,47,48,53,60,3.0,6,37,Urban,Data Analyst,93786,0 +102344,Male,54,Masters,3,26,89,22,13,2.0,6,34,Urban,Software Engineer,104709,0 +102345,Female,51,Masters,1,79,7,33,97,9.0,3,82,Urban,ML Engineer,84098,0 +102346,Female,35,Bachelors,2,41,63,34,79,0.0,3,93,Urban,HR Executive,102724,0 +102347,Female,28,Masters,9,57,91,57,84,0.0,3,57,Urban,ML Engineer,88739,1 +102348,Female,58,Masters,10,49,90,93,64,0.0,5,21,Semi-Urban,Software Engineer,27484,1 +102349,Female,22,Bachelors,16,5,53,12,50,7.0,7,59,Urban,Data Analyst,143341,0 +102350,Male,33,Masters,14,21,8,1,20,0.0,3,28,Rural,Data Analyst,127978,0 +102351,Male,42,Bachelors,0,75,43,11,85,0.0,1,5,Rural,Software Engineer,145114,0 +102352,Male,27,Diploma,8,42,34,59,19,9.0,3,98,Urban,Data Analyst,33888,0 +102353,Male,33,Masters,1,85,20,70,65,5.0,0,86,Rural,Software Engineer,70327,1 +102354,Female,55,Bachelors,5,79,49,84,39,5.0,0,42,Semi-Urban,HR Executive,107004,1 +102355,Male,57,Bachelors,17,82,89,1,71,6.0,7,69,Semi-Urban,Software Engineer,125678,1 +102356,Female,36,Diploma,11,88,25,17,75,0.0,4,88,Urban,HR Executive,38840,0 +102357,Female,25,Masters,0,32,24,97,14,2.0,0,35,Urban,HR Executive,37994,0 +102358,Female,31,Masters,10,79,33,60,17,5.0,4,71,Urban,Data Analyst,36233,1 +102359,Male,23,High School,9,40,49,77,70,8.0,7,18,Semi-Urban,HR Executive,83987,0 +102360,Male,43,Bachelors,19,19,24,53,15,3.0,4,3,Urban,Manager,148700,0 +102361,Female,48,Bachelors,16,97,89,47,86,2.0,4,7,Rural,Software Engineer,61768,0 +102362,Male,37,Bachelors,4,42,77,67,0,4.0,7,36,Urban,Manager,116802,0 +102363,Male,49,Bachelors,11,75,96,86,69,9.0,4,76,Semi-Urban,Software Engineer,112571,1 +102364,Other,30,Bachelors,7,64,13,36,0,1.0,2,62,Urban,Manager,26920,0 +102365,Male,45,Bachelors,3,78,20,84,40,1.0,6,30,Urban,Manager,51672,0 +102366,Male,53,High School,2,76,47,47,79,4.0,6,71,Rural,Manager,95616,1 +102367,Male,58,Bachelors,10,70,96,10,74,6.0,4,57,Semi-Urban,Data Analyst,124536,0 +102368,Male,47,Bachelors,16,92,52,44,58,5.0,0,69,Urban,HR Executive,81389,1 +102369,Male,39,Bachelors,6,45,31,91,37,2.0,0,40,Rural,Manager,136989,0 +102370,Male,25,Diploma,16,64,75,49,8,7.0,2,7,Rural,Software Engineer,139595,0 +102371,Other,34,Masters,13,26,21,52,4,3.0,5,39,Urban,Data Analyst,135406,0 +102372,Male,42,Bachelors,11,83,18,18,25,3.0,5,35,Semi-Urban,Manager,137992,0 +102373,Male,45,Bachelors,4,3,38,15,66,1.0,2,24,Semi-Urban,Software Engineer,77319,0 +102374,Female,38,Masters,2,0,16,21,89,0.0,2,9,Urban,Software Engineer,97401,0 +102375,Other,55,High School,0,79,57,5,41,2.0,7,27,Urban,Software Engineer,105711,0 +102376,Male,30,High School,19,88,53,94,61,5.0,6,71,Semi-Urban,Manager,44441,1 +102377,Male,28,Bachelors,8,24,40,41,40,6.0,2,32,Rural,Data Analyst,102887,0 +102378,Male,55,Bachelors,10,70,23,71,83,0.0,6,3,Urban,Data Analyst,50098,0 +102379,Female,30,Diploma,7,59,47,12,43,1.0,3,11,Rural,ML Engineer,76589,0 +102380,Male,41,Diploma,4,69,12,14,10,2.0,4,13,Rural,Data Analyst,108626,0 +102381,Male,42,High School,18,96,15,30,75,8.0,4,87,Urban,Manager,60815,0 +102382,Male,41,Bachelors,16,38,21,53,39,1.0,3,65,Semi-Urban,ML Engineer,127855,0 +102383,Male,55,Masters,19,85,64,72,49,3.0,1,58,Urban,ML Engineer,68936,1 +102384,Female,24,Diploma,1,32,23,77,94,0.0,7,18,Urban,HR Executive,142293,0 +102385,Male,44,High School,7,58,75,61,3,7.0,3,12,Urban,ML Engineer,75169,0 +102386,Male,56,Bachelors,15,8,42,59,40,2.0,6,2,Urban,ML Engineer,54407,0 +102387,Male,30,High School,7,94,11,11,23,7.0,1,86,Semi-Urban,HR Executive,45754,0 +102388,Male,54,Bachelors,9,28,59,91,22,8.0,1,10,Semi-Urban,HR Executive,34952,0 +102389,Male,40,High School,11,22,9,79,24,4.0,7,72,Urban,HR Executive,142672,0 +102390,Male,44,Bachelors,12,39,60,23,53,4.0,7,45,Rural,HR Executive,69287,0 +102391,Male,35,Diploma,16,80,95,36,38,1.0,3,57,Semi-Urban,Software Engineer,95897,1 +102392,Male,46,PhD,17,94,56,93,30,8.0,6,88,Rural,Manager,139696,1 +102393,Female,53,Bachelors,12,51,76,93,93,6.0,2,14,Semi-Urban,ML Engineer,49911,0 +102394,Female,58,Masters,18,94,46,12,91,5.0,2,17,Urban,HR Executive,134335,0 +102395,Male,44,Bachelors,5,35,11,15,74,3.0,1,87,Urban,Data Analyst,46004,0 +102396,Male,57,Diploma,17,72,90,89,41,0.0,4,72,Urban,Data Analyst,135102,1 +102397,Female,30,Bachelors,12,68,19,84,6,2.0,7,81,Rural,Manager,35860,1 +102398,Female,39,Bachelors,14,5,40,41,42,4.0,0,31,Urban,HR Executive,98400,0 +102399,Female,52,Bachelors,16,42,11,91,92,9.0,7,43,Urban,ML Engineer,96002,0 +102400,Other,43,Bachelors,10,40,56,78,24,5.0,2,60,Urban,HR Executive,72817,0 +102401,Male,35,Bachelors,8,88,85,44,34,9.0,1,55,Urban,HR Executive,74663,1 +102402,Male,57,Masters,1,1,20,21,6,3.0,3,87,Urban,Data Analyst,103247,0 +102403,Male,31,Masters,11,85,10,43,36,4.0,6,79,Semi-Urban,ML Engineer,116156,0 +102404,Male,57,Diploma,13,94,6,61,91,9.0,2,22,Urban,Data Analyst,22814,0 +102405,Male,48,Diploma,14,97,79,53,37,9.0,6,41,Urban,HR Executive,95550,1 +102406,Male,44,Bachelors,16,72,67,3,32,9.0,6,75,Rural,HR Executive,131790,0 +102407,Female,46,Bachelors,16,70,65,63,18,1.0,4,65,Semi-Urban,ML Engineer,52081,1 +102408,Male,38,Bachelors,6,61,25,63,3,0.0,3,66,Urban,Software Engineer,83562,0 +102409,Female,27,Bachelors,16,64,18,48,77,2.0,2,68,Semi-Urban,Manager,30834,0 +102410,Male,48,High School,12,96,65,8,96,2.0,6,38,Urban,HR Executive,52465,0 +102411,Male,44,Bachelors,13,18,11,19,49,9.0,7,51,Urban,Data Analyst,126595,0 +102412,Female,59,Masters,1,39,28,27,71,7.0,1,14,Rural,HR Executive,121045,0 +102413,Female,59,Bachelors,7,62,46,72,11,1.0,7,42,Semi-Urban,Software Engineer,27416,0 +102414,Male,34,Diploma,7,5,20,46,5,8.0,1,49,Urban,Software Engineer,67790,0 +102415,Male,34,Diploma,10,53,62,23,29,2.0,6,31,Urban,HR Executive,28573,0 +102416,Male,38,Diploma,15,52,73,54,23,7.0,0,35,Urban,ML Engineer,44798,0 +102417,Male,32,Masters,11,18,63,3,40,7.0,3,78,Urban,Manager,131538,0 +102418,Female,28,High School,15,29,64,72,26,7.0,2,26,Urban,ML Engineer,110794,0 +102419,Male,42,PhD,2,14,64,64,45,2.0,3,65,Urban,Data Analyst,52845,0 +102420,Male,37,Bachelors,6,32,27,20,48,1.0,7,46,Urban,Data Analyst,79590,0 +102421,Male,56,Masters,14,66,36,64,75,9.0,6,72,Semi-Urban,Software Engineer,24408,1 +102422,Male,34,Bachelors,15,70,81,47,62,5.0,6,76,Urban,HR Executive,95752,1 +102423,Male,36,High School,3,22,34,18,8,6.0,5,9,Urban,Manager,76377,0 +102424,Male,56,High School,0,34,15,29,98,9.0,4,54,Urban,ML Engineer,60945,0 +102425,Male,49,Diploma,19,74,35,66,64,0.0,2,18,Rural,Software Engineer,93833,0 +102426,Male,57,Masters,17,89,84,88,59,5.0,6,48,Rural,Data Analyst,81525,1 +102427,Other,46,Bachelors,12,1,90,71,78,2.0,5,78,Semi-Urban,Data Analyst,134694,0 +102428,Male,33,Diploma,9,42,95,83,21,3.0,3,35,Urban,Software Engineer,30627,1 +102429,Male,30,Diploma,13,12,49,87,40,7.0,7,89,Urban,ML Engineer,20441,1 +102430,Female,28,Diploma,10,40,8,73,60,8.0,1,71,Urban,Manager,54431,0 +102431,Female,24,Diploma,2,32,75,65,28,0.0,4,6,Urban,Manager,142545,0 +102432,Male,32,PhD,16,38,67,81,36,4.0,3,81,Urban,ML Engineer,113025,1 +102433,Female,26,Masters,12,2,58,99,28,0.0,6,13,Semi-Urban,Manager,48449,0 +102434,Female,24,Bachelors,12,38,32,90,57,5.0,1,73,Semi-Urban,Software Engineer,46585,0 +102435,Female,52,Bachelors,2,2,97,3,88,3.0,7,37,Rural,Manager,47890,0 +102436,Female,31,Masters,0,69,98,14,61,1.0,5,69,Urban,Manager,143067,1 +102437,Male,22,High School,16,51,82,75,75,7.0,0,21,Urban,HR Executive,97792,0 +102438,Male,58,High School,11,80,48,91,44,9.0,6,43,Urban,ML Engineer,147682,1 +102439,Female,27,Diploma,11,95,35,73,9,1.0,4,35,Urban,Data Analyst,108007,0 +102440,Male,48,Masters,18,49,87,93,97,6.0,1,92,Rural,ML Engineer,21820,1 +102441,Male,54,Bachelors,0,72,52,4,79,3.0,2,82,Rural,Manager,94527,0 +102442,Other,51,Bachelors,14,37,87,90,17,9.0,7,66,Urban,Manager,87299,1 +102443,Other,40,Bachelors,6,61,94,44,86,9.0,1,40,Semi-Urban,Software Engineer,124354,0 +102444,Female,33,Bachelors,0,6,83,79,73,8.0,3,88,Semi-Urban,Software Engineer,55010,1 +102445,Male,50,Diploma,18,63,56,84,86,6.0,4,14,Semi-Urban,HR Executive,149130,0 +102446,Male,44,Diploma,8,76,6,27,0,5.0,2,50,Urban,HR Executive,24240,0 +102447,Male,35,High School,4,4,37,63,82,7.0,0,60,Rural,HR Executive,61521,0 +102448,Female,28,Bachelors,16,22,36,50,66,0.0,5,84,Urban,Data Analyst,34237,0 +102449,Male,30,Bachelors,7,51,72,60,42,5.0,5,64,Rural,Data Analyst,93260,1 +102450,Male,36,Diploma,2,32,97,11,13,3.0,3,77,Rural,Manager,38722,0 +102451,Male,36,Diploma,6,52,39,68,55,3.0,2,19,Semi-Urban,HR Executive,69152,0 +102452,Female,38,Bachelors,11,72,41,79,48,1.0,6,19,Urban,ML Engineer,101563,0 +102453,Female,53,Bachelors,7,74,55,49,20,8.0,5,78,Urban,ML Engineer,56444,1 +102454,Male,39,Masters,10,13,58,22,88,0.0,0,3,Rural,Software Engineer,80601,0 +102455,Female,22,Diploma,12,95,41,64,64,9.0,4,64,Semi-Urban,Software Engineer,140564,1 +102456,Female,46,Bachelors,12,16,28,73,88,3.0,7,75,Rural,Manager,45356,0 +102457,Female,56,Bachelors,3,24,80,30,55,8.0,4,47,Urban,ML Engineer,59625,0 +102458,Male,26,Diploma,7,39,66,40,53,0.0,7,24,Urban,HR Executive,50457,0 +102459,Male,38,Bachelors,13,41,92,56,63,8.0,6,57,Urban,ML Engineer,52895,1 +102460,Female,40,Bachelors,4,5,12,10,92,4.0,6,31,Urban,HR Executive,68611,0 +102461,Male,30,Bachelors,6,72,33,44,8,7.0,5,24,Urban,Manager,48025,0 +102462,Male,23,Bachelors,18,59,0,22,16,9.0,0,59,Urban,Manager,138834,0 +102463,Other,57,Bachelors,7,55,55,30,31,3.0,4,6,Rural,Manager,103546,0 +102464,Female,50,Bachelors,11,17,30,52,42,4.0,7,85,Urban,ML Engineer,25598,0 +102465,Other,36,High School,4,4,20,99,95,2.0,4,56,Urban,Data Analyst,148240,0 +102466,Male,53,Bachelors,3,68,90,83,65,4.0,0,55,Semi-Urban,ML Engineer,126867,1 +102467,Male,51,Bachelors,5,62,51,19,62,4.0,6,72,Rural,ML Engineer,28033,0 +102468,Male,48,Masters,5,87,62,0,12,5.0,6,61,Rural,Software Engineer,93469,0 +102469,Male,28,Masters,16,28,9,49,31,1.0,5,35,Semi-Urban,Manager,103480,0 +102470,Male,29,Masters,4,92,31,96,71,7.0,0,39,Rural,Manager,104428,1 +102471,Male,23,High School,14,72,25,84,68,5.0,5,27,Urban,Data Analyst,104419,0 +102472,Male,59,PhD,5,19,84,6,42,2.0,4,76,Urban,HR Executive,127967,0 +102473,Male,56,Bachelors,15,69,60,22,61,4.0,0,32,Rural,Data Analyst,107488,0 +102474,Female,43,PhD,3,17,91,85,82,5.0,3,6,Urban,Software Engineer,82840,0 +102475,Female,48,Bachelors,8,54,98,71,15,2.0,5,55,Urban,ML Engineer,135848,1 +102476,Male,55,High School,17,30,67,91,54,2.0,4,30,Rural,ML Engineer,102512,0 +102477,Male,22,Diploma,10,37,21,87,67,7.0,6,68,Urban,Manager,93096,0 +102478,Male,40,Masters,10,95,26,80,20,1.0,5,7,Rural,HR Executive,39142,0 +102479,Male,54,Bachelors,15,98,58,47,29,2.0,5,5,Urban,Manager,78732,0 +102480,Other,44,Bachelors,10,33,44,22,39,9.0,4,99,Rural,Software Engineer,99988,0 +102481,Female,50,Masters,7,26,99,75,90,7.0,0,25,Semi-Urban,Software Engineer,40959,0 +102482,Female,50,Diploma,11,41,59,49,99,7.0,0,95,Semi-Urban,HR Executive,92430,1 +102483,Female,48,High School,5,84,46,40,71,8.0,6,15,Rural,Data Analyst,75456,0 +102484,Male,35,Masters,12,98,39,78,35,4.0,5,16,Semi-Urban,Data Analyst,93743,0 +102485,Female,40,Masters,8,57,35,46,76,0.0,7,31,Semi-Urban,HR Executive,129712,0 +102486,Male,53,PhD,12,84,51,53,49,9.0,5,93,Semi-Urban,HR Executive,69326,1 +102487,Male,22,High School,18,7,72,53,24,8.0,7,91,Urban,HR Executive,111889,0 +102488,Male,21,Bachelors,14,18,30,7,89,0.0,5,97,Rural,HR Executive,50342,0 +102489,Other,59,PhD,9,29,98,4,0,0.0,3,50,Urban,Manager,28553,0 +102490,Male,37,Masters,8,81,94,95,82,3.0,2,22,Urban,Manager,76763,1 +102491,Male,31,Bachelors,11,59,76,8,72,8.0,5,46,Urban,Software Engineer,46401,0 +102492,Other,44,Bachelors,1,72,91,52,61,4.0,1,57,Urban,Data Analyst,63704,1 +102493,Female,36,Bachelors,19,19,70,74,72,2.0,3,78,Urban,HR Executive,149809,1 +102494,Female,55,Bachelors,15,41,55,26,40,1.0,5,58,Urban,HR Executive,78755,0 +102495,Female,26,PhD,8,14,55,89,83,4.0,1,39,Semi-Urban,HR Executive,124247,0 +102496,Female,48,Bachelors,8,67,61,47,87,8.0,5,44,Semi-Urban,ML Engineer,40753,0 +102497,Female,22,Bachelors,0,39,52,36,77,7.0,1,10,Urban,Manager,51111,0 +102498,Female,42,Diploma,10,89,62,69,81,0.0,3,49,Urban,ML Engineer,127141,1 +102499,Female,59,High School,16,82,46,98,62,7.0,7,94,Rural,Data Analyst,109389,1 +102500,Male,38,Diploma,7,20,4,99,88,1.0,7,3,Urban,ML Engineer,55697,0 +102501,Female,27,Diploma,18,69,12,50,93,1.0,4,88,Urban,Data Analyst,112503,0 +102502,Male,45,Bachelors,5,46,55,30,52,5.0,7,43,Rural,Software Engineer,56121,0 +102503,Female,27,PhD,7,70,29,29,91,0.0,5,24,Urban,Data Analyst,56730,0 +102504,Other,26,Bachelors,18,51,94,1,95,4.0,7,25,Semi-Urban,Software Engineer,109389,0 +102505,Male,52,High School,15,47,27,78,46,5.0,6,51,Semi-Urban,ML Engineer,138971,0 +102506,Female,37,PhD,1,18,30,79,47,7.0,0,64,Urban,HR Executive,71655,0 +102507,Male,38,High School,13,36,23,36,8,4.0,0,23,Semi-Urban,ML Engineer,97187,0 +102508,Male,44,High School,6,90,51,46,94,5.0,5,80,Semi-Urban,ML Engineer,116813,1 +102509,Female,44,High School,19,72,1,45,74,7.0,6,64,Semi-Urban,Manager,42676,0 +102510,Male,31,Masters,19,19,67,94,25,7.0,3,67,Urban,Data Analyst,134342,1 +102511,Female,45,Diploma,2,72,83,85,19,5.0,3,77,Semi-Urban,Manager,28889,1 +102512,Female,59,High School,10,97,57,44,87,5.0,5,51,Semi-Urban,Data Analyst,95500,1 +102513,Female,50,Bachelors,4,80,36,97,42,2.0,2,56,Urban,Manager,27949,1 +102514,Male,40,Bachelors,18,85,38,85,87,1.0,1,4,Urban,ML Engineer,118402,0 +102515,Female,22,High School,1,34,24,86,83,2.0,5,13,Urban,Data Analyst,69580,0 +102516,Female,45,Diploma,9,5,77,62,36,0.0,3,21,Rural,HR Executive,79488,0 +102517,Other,38,Masters,16,78,8,27,15,4.0,0,95,Urban,ML Engineer,149865,0 +102518,Male,29,High School,19,95,8,24,17,8.0,0,1,Urban,Manager,60115,0 +102519,Male,25,Diploma,9,0,17,2,80,0.0,2,2,Semi-Urban,Manager,78901,0 +102520,Female,37,Diploma,18,21,48,20,32,6.0,1,46,Semi-Urban,ML Engineer,116215,0 +102521,Female,51,Masters,9,59,75,57,93,4.0,5,20,Urban,Software Engineer,69229,0 +102522,Female,38,Diploma,1,26,62,97,58,6.0,3,71,Urban,HR Executive,104633,1 +102523,Female,33,Bachelors,19,27,47,86,20,0.0,4,82,Rural,Software Engineer,115408,1 +102524,Male,48,Bachelors,18,65,32,46,3,3.0,1,42,Semi-Urban,Data Analyst,136550,0 +102525,Female,44,PhD,15,65,58,97,96,2.0,2,45,Urban,Data Analyst,94274,1 +102526,Female,54,Masters,14,64,75,29,37,1.0,4,42,Urban,HR Executive,40027,0 +102527,Male,21,Bachelors,12,5,59,75,7,3.0,4,23,Urban,Software Engineer,79504,0 +102528,Female,24,PhD,19,22,3,74,25,2.0,1,60,Urban,Data Analyst,69951,0 +102529,Male,37,Bachelors,11,85,54,86,49,9.0,6,16,Semi-Urban,Data Analyst,112375,1 +102530,Female,42,Masters,7,36,15,8,23,3.0,6,14,Semi-Urban,HR Executive,50858,0 +102531,Male,37,Masters,16,94,17,88,83,0.0,4,85,Urban,Data Analyst,50198,1 +102532,Male,22,Bachelors,4,5,94,28,9,3.0,6,13,Urban,Manager,90054,0 +102533,Female,51,Bachelors,12,9,77,21,76,9.0,5,72,Urban,HR Executive,37855,0 +102534,Female,54,High School,17,65,30,35,26,3.0,5,74,Semi-Urban,ML Engineer,75599,0 +102535,Female,58,High School,16,54,66,25,45,0.0,4,77,Rural,HR Executive,57716,0 +102536,Female,27,Masters,1,66,78,74,77,2.0,2,56,Semi-Urban,HR Executive,59408,1 +102537,Male,22,Bachelors,9,31,42,9,55,6.0,2,17,Rural,Software Engineer,61511,0 +102538,Female,48,High School,17,18,3,73,18,0.0,1,7,Urban,Data Analyst,104385,0 +102539,Male,56,Masters,3,61,45,29,61,5.0,6,76,Urban,ML Engineer,55468,0 +102540,Male,35,Bachelors,5,32,83,60,68,1.0,3,17,Urban,Data Analyst,81101,0 +102541,Female,48,Bachelors,1,91,35,54,28,1.0,0,6,Semi-Urban,Software Engineer,147163,0 +102542,Female,54,Bachelors,4,20,22,82,47,9.0,1,40,Semi-Urban,ML Engineer,139880,0 +102543,Other,27,Bachelors,1,73,61,73,74,5.0,7,38,Rural,HR Executive,30997,1 +102544,Female,40,Bachelors,13,31,36,76,54,9.0,0,80,Urban,HR Executive,76986,0 +102545,Male,25,Bachelors,18,43,67,40,16,0.0,7,8,Semi-Urban,Data Analyst,97918,0 +102546,Male,30,Masters,9,72,82,5,57,9.0,0,70,Urban,HR Executive,52061,0 +102547,Female,31,Bachelors,16,49,97,49,12,8.0,4,43,Urban,HR Executive,61007,0 +102548,Male,28,High School,16,62,26,47,49,8.0,3,80,Urban,Software Engineer,123008,0 +102549,Other,50,Bachelors,5,38,3,32,94,6.0,2,11,Urban,HR Executive,93440,0 +102550,Male,29,Masters,1,68,18,89,99,3.0,2,16,Semi-Urban,HR Executive,144899,0 +102551,Female,53,Masters,10,60,25,51,74,6.0,0,77,Rural,Software Engineer,96424,0 +102552,Male,26,Bachelors,11,83,28,48,30,2.0,6,16,Urban,Software Engineer,53983,0 +102553,Male,27,Diploma,16,22,15,10,31,0.0,6,80,Rural,HR Executive,132606,0 +102554,Male,35,Bachelors,1,43,6,90,13,0.0,0,79,Urban,Data Analyst,35191,0 +102555,Male,55,PhD,0,94,32,21,75,6.0,4,52,Semi-Urban,Data Analyst,144256,0 +102556,Female,47,Bachelors,19,66,84,50,38,7.0,7,94,Semi-Urban,Manager,58380,1 +102557,Other,39,Masters,16,59,33,35,22,2.0,2,85,Urban,Software Engineer,26548,0 +102558,Male,27,Bachelors,7,11,28,20,44,4.0,1,72,Urban,Manager,87913,0 +102559,Female,24,Diploma,2,31,75,82,98,3.0,2,91,Urban,HR Executive,61432,1 +102560,Male,55,Diploma,19,43,33,65,15,8.0,4,27,Rural,Software Engineer,127308,0 +102561,Female,50,Bachelors,9,4,47,36,57,0.0,3,16,Urban,Data Analyst,132345,0 +102562,Male,41,Diploma,3,98,27,33,21,7.0,6,14,Semi-Urban,Software Engineer,109817,0 +102563,Male,41,Masters,15,84,57,53,88,0.0,6,25,Rural,Software Engineer,114653,0 +102564,Male,38,High School,4,37,26,19,94,8.0,3,30,Semi-Urban,Software Engineer,61249,0 +102565,Female,31,Diploma,14,26,55,68,37,4.0,6,19,Urban,Data Analyst,117431,0 +102566,Male,28,Bachelors,8,35,42,97,61,1.0,5,86,Urban,Software Engineer,135547,1 +102567,Male,42,Bachelors,12,50,93,84,26,4.0,5,20,Semi-Urban,ML Engineer,77950,1 +102568,Other,46,Masters,5,55,84,29,0,4.0,6,95,Semi-Urban,Manager,61699,1 +102569,Female,22,Bachelors,3,93,15,35,24,5.0,0,83,Urban,HR Executive,128652,0 +102570,Male,23,High School,1,24,23,23,24,5.0,3,17,Urban,ML Engineer,113728,0 +102571,Female,50,Diploma,3,12,39,63,67,3.0,5,4,Urban,ML Engineer,138623,0 +102572,Male,38,Bachelors,14,88,0,90,60,8.0,4,56,Rural,ML Engineer,88659,0 +102573,Male,46,Bachelors,2,40,85,73,8,6.0,5,73,Urban,HR Executive,144522,1 +102574,Female,26,Diploma,2,91,69,2,61,5.0,3,25,Semi-Urban,Software Engineer,127590,0 +102575,Male,41,Bachelors,2,13,39,94,1,9.0,7,8,Semi-Urban,Manager,64830,0 +102576,Other,49,Diploma,12,28,61,87,62,6.0,2,33,Urban,Manager,32001,0 +102577,Male,58,Masters,12,27,1,11,81,3.0,5,11,Urban,HR Executive,126244,0 +102578,Male,33,Bachelors,6,82,21,7,97,3.0,4,27,Semi-Urban,Manager,57198,0 +102579,Female,59,Masters,8,9,67,32,30,1.0,7,89,Urban,Manager,125648,0 +102580,Male,34,Diploma,4,90,94,40,13,6.0,1,45,Urban,Data Analyst,147170,1 +102581,Male,48,Bachelors,0,42,7,28,47,3.0,0,96,Semi-Urban,Software Engineer,135763,0 +102582,Male,41,PhD,0,36,92,6,2,0.0,0,39,Urban,Manager,23930,0 +102583,Female,56,Bachelors,11,68,47,51,12,4.0,3,54,Urban,HR Executive,115921,0 +102584,Male,45,Bachelors,9,50,77,75,77,8.0,2,18,Semi-Urban,Data Analyst,66377,0 +102585,Male,52,Masters,5,12,20,39,53,7.0,1,72,Urban,ML Engineer,66664,0 +102586,Male,37,High School,15,43,69,5,74,0.0,0,53,Semi-Urban,HR Executive,34680,0 +102587,Male,58,Masters,0,34,66,58,96,4.0,1,35,Semi-Urban,Manager,132921,0 +102588,Female,55,Masters,3,75,70,42,31,2.0,3,39,Urban,Data Analyst,63068,0 +102589,Male,25,Bachelors,5,57,88,51,55,6.0,0,96,Rural,HR Executive,61766,1 +102590,Male,51,High School,3,65,44,42,15,6.0,2,56,Urban,Software Engineer,35238,0 +102591,Male,52,Masters,8,99,60,46,80,4.0,3,33,Urban,Software Engineer,65675,1 +102592,Male,31,Bachelors,15,46,57,85,20,7.0,3,39,Semi-Urban,ML Engineer,105956,0 +102593,Other,34,High School,19,21,84,44,64,7.0,7,79,Rural,Data Analyst,22613,0 +102594,Male,34,Masters,3,53,52,79,93,0.0,5,81,Rural,ML Engineer,54313,1 +102595,Female,41,Masters,6,86,83,68,92,4.0,4,31,Semi-Urban,Data Analyst,66711,1 +102596,Female,47,Bachelors,13,48,64,82,34,9.0,0,76,Urban,Data Analyst,111290,1 +102597,Other,37,Bachelors,8,2,21,64,20,2.0,0,39,Urban,HR Executive,110309,0 +102598,Female,37,High School,12,39,93,46,31,7.0,7,80,Urban,Manager,140228,1 +102599,Male,39,Bachelors,1,72,76,55,61,5.0,5,69,Urban,Manager,45392,1 +102600,Male,39,Bachelors,16,99,77,49,65,6.0,2,31,Urban,ML Engineer,134525,1 +102601,Male,25,High School,16,26,53,42,68,4.0,6,94,Rural,Data Analyst,99910,0 +102602,Male,58,Bachelors,4,72,68,80,4,5.0,4,52,Urban,Manager,56875,1 +102603,Female,53,High School,3,32,70,97,99,7.0,4,55,Urban,Software Engineer,149560,1 +102604,Male,21,PhD,8,0,65,76,66,1.0,3,97,Semi-Urban,Manager,78963,1 +102605,Female,40,Bachelors,19,78,62,43,90,3.0,3,61,Rural,HR Executive,87778,1 +102606,Male,32,Bachelors,12,44,12,28,6,9.0,2,98,Urban,ML Engineer,32571,0 +102607,Male,34,Bachelors,19,39,30,32,33,4.0,7,40,Urban,Software Engineer,125448,0 +102608,Male,35,Masters,15,71,54,26,96,1.0,0,38,Rural,ML Engineer,109037,0 +102609,Male,50,Bachelors,16,52,45,71,7,0.0,1,5,Urban,Software Engineer,29729,0 +102610,Male,29,High School,15,58,39,60,48,5.0,4,71,Semi-Urban,Software Engineer,135216,0 +102611,Male,40,Bachelors,17,14,88,5,86,0.0,0,14,Urban,Data Analyst,54794,0 +102612,Male,35,Masters,7,28,18,94,36,8.0,2,82,Rural,Data Analyst,125353,0 +102613,Male,48,Masters,14,45,95,79,33,0.0,3,24,Urban,ML Engineer,122981,1 +102614,Male,29,Diploma,0,57,14,68,68,9.0,4,58,Rural,Manager,119117,0 +102615,Female,36,Bachelors,7,15,27,62,30,2.0,3,32,Urban,ML Engineer,23738,0 +102616,Male,32,Diploma,10,93,64,98,55,0.0,1,94,Urban,HR Executive,47576,1 +102617,Female,59,Masters,2,92,68,8,83,2.0,1,20,Semi-Urban,Software Engineer,118779,0 +102618,Female,37,Masters,9,75,60,64,62,1.0,5,2,Urban,Manager,89787,0 +102619,Male,37,Masters,16,89,30,34,56,3.0,1,91,Urban,Software Engineer,84191,1 +102620,Other,28,Masters,14,96,67,12,45,6.0,3,50,Urban,ML Engineer,54374,0 +102621,Female,56,Bachelors,2,84,61,41,67,8.0,5,0,Urban,Data Analyst,52408,0 +102622,Male,33,Masters,10,95,57,83,54,0.0,2,40,Urban,Manager,125559,1 +102623,Female,33,High School,2,7,79,23,89,8.0,5,95,Urban,ML Engineer,95304,0 +102624,Male,46,Diploma,11,99,48,75,84,6.0,7,11,Semi-Urban,Manager,123679,0 +102625,Female,31,PhD,8,67,46,55,35,1.0,3,20,Urban,Manager,125214,0 +102626,Female,50,Diploma,8,37,13,1,95,3.0,2,53,Urban,Software Engineer,78491,0 +102627,Male,52,Bachelors,13,4,75,16,57,6.0,6,99,Urban,Software Engineer,87437,0 +102628,Male,59,High School,7,34,61,60,63,7.0,3,44,Urban,Manager,103636,0 +102629,Male,22,Bachelors,11,84,9,22,67,7.0,6,76,Urban,Data Analyst,80145,0 +102630,Other,42,Bachelors,3,90,5,48,56,6.0,3,71,Urban,HR Executive,101763,0 +102631,Male,31,Masters,10,38,95,79,82,2.0,6,94,Urban,ML Engineer,43394,1 +102632,Female,25,Masters,19,27,55,55,52,8.0,1,15,Semi-Urban,ML Engineer,125629,0 +102633,Other,23,Bachelors,13,69,39,21,80,5.0,3,91,Urban,ML Engineer,67590,0 +102634,Male,45,Bachelors,12,0,51,79,24,7.0,2,60,Semi-Urban,Software Engineer,140194,0 +102635,Male,56,Diploma,3,44,76,88,56,9.0,7,86,Urban,HR Executive,136271,1 +102636,Male,26,Masters,8,84,18,21,14,7.0,0,75,Rural,Manager,38640,0 +102637,Male,45,PhD,13,97,61,10,99,2.0,6,37,Urban,ML Engineer,96007,0 +102638,Female,43,PhD,10,24,71,85,88,9.0,5,1,Semi-Urban,HR Executive,55064,0 +102639,Male,50,Bachelors,14,5,15,15,54,6.0,3,13,Semi-Urban,Manager,91780,0 +102640,Male,57,Bachelors,12,11,8,89,69,6.0,1,2,Urban,HR Executive,35180,0 +102641,Female,46,High School,1,49,56,66,70,9.0,6,73,Rural,Manager,78925,1 +102642,Male,26,Diploma,17,43,81,38,7,5.0,2,21,Urban,ML Engineer,49510,0 +102643,Male,46,Diploma,4,63,32,43,90,3.0,5,46,Rural,HR Executive,86761,0 +102644,Male,53,Bachelors,4,67,26,52,96,4.0,2,32,Semi-Urban,Data Analyst,26273,0 +102645,Male,25,Bachelors,3,57,95,6,52,9.0,5,34,Urban,HR Executive,81083,0 +102646,Male,32,Diploma,8,92,82,61,51,0.0,6,55,Semi-Urban,Data Analyst,140554,1 +102647,Male,35,PhD,10,44,30,43,28,8.0,0,50,Rural,Software Engineer,96915,0 +102648,Other,35,Diploma,0,94,72,74,72,5.0,1,48,Semi-Urban,Manager,119244,1 +102649,Male,21,Diploma,3,17,99,93,86,9.0,6,81,Urban,Manager,126029,1 +102650,Male,57,PhD,11,69,87,78,4,5.0,4,96,Urban,Data Analyst,29470,1 +102651,Male,22,High School,1,97,50,87,22,6.0,7,2,Semi-Urban,ML Engineer,131992,1 +102652,Female,24,Bachelors,15,28,28,51,90,7.0,7,71,Urban,HR Executive,41546,0 +102653,Male,35,Bachelors,19,64,72,93,89,8.0,2,74,Urban,HR Executive,59724,1 +102654,Male,54,Diploma,12,69,10,5,4,0.0,1,54,Rural,Software Engineer,135067,0 +102655,Other,35,High School,9,67,78,92,49,4.0,7,84,Rural,Software Engineer,127069,1 +102656,Male,57,Masters,15,86,68,33,71,2.0,3,50,Semi-Urban,Software Engineer,124478,1 +102657,Male,22,Masters,19,83,7,72,34,8.0,4,13,Urban,HR Executive,85410,0 +102658,Male,37,PhD,12,81,94,50,95,1.0,4,42,Urban,Manager,140760,1 +102659,Male,38,Diploma,4,61,30,87,76,8.0,2,62,Urban,Data Analyst,139440,1 +102660,Female,31,Bachelors,12,7,88,36,61,0.0,7,48,Semi-Urban,Manager,67870,0 +102661,Male,38,Masters,11,72,20,74,93,4.0,4,47,Urban,ML Engineer,21856,0 +102662,Male,38,High School,15,77,25,70,65,9.0,0,72,Semi-Urban,ML Engineer,130178,1 +102663,Male,52,Diploma,0,53,92,24,41,1.0,0,65,Urban,Software Engineer,76464,0 +102664,Male,45,High School,18,87,84,99,96,6.0,0,65,Urban,Manager,134997,1 +102665,Female,29,Bachelors,7,1,39,37,24,4.0,7,38,Semi-Urban,ML Engineer,85595,0 +102666,Female,42,Diploma,8,19,68,57,7,5.0,4,99,Urban,ML Engineer,110840,1 +102667,Male,31,Bachelors,6,96,89,94,86,7.0,0,82,Urban,Manager,81910,1 +102668,Male,21,Masters,17,25,80,91,45,7.0,4,20,Rural,Manager,46337,0 +102669,Female,48,Bachelors,4,91,82,50,89,8.0,4,90,Semi-Urban,Software Engineer,27494,1 +102670,Female,42,Bachelors,10,45,58,93,41,4.0,0,96,Urban,HR Executive,135535,1 +102671,Female,28,Diploma,3,8,43,82,50,9.0,6,83,Rural,ML Engineer,44720,0 +102672,Male,59,Bachelors,7,42,35,21,99,8.0,5,82,Urban,Data Analyst,82202,0 +102673,Female,27,Diploma,19,83,83,72,37,9.0,3,96,Urban,HR Executive,79232,1 +102674,Male,39,Bachelors,9,17,89,49,89,6.0,0,93,Urban,Software Engineer,25390,1 +102675,Male,26,Masters,12,42,78,55,22,9.0,2,43,Urban,ML Engineer,96109,0 +102676,Male,59,Diploma,18,4,87,94,15,4.0,6,91,Rural,HR Executive,36430,1 +102677,Male,48,Masters,13,17,60,45,73,6.0,7,84,Urban,Manager,129457,0 +102678,Female,41,Bachelors,7,61,1,50,72,4.0,2,2,Rural,HR Executive,65002,0 +102679,Male,24,PhD,16,48,39,39,44,2.0,7,73,Rural,HR Executive,92811,0 +102680,Male,33,Bachelors,19,79,19,45,83,1.0,6,1,Semi-Urban,Manager,146623,0 +102681,Male,26,High School,8,37,29,40,53,3.0,7,20,Urban,Software Engineer,131100,0 +102682,Male,37,Diploma,4,80,56,98,57,6.0,2,12,Rural,Manager,118812,1 +102683,Male,26,Bachelors,15,85,91,84,34,8.0,7,94,Urban,Manager,83013,1 +102684,Female,49,Bachelors,0,40,0,38,93,5.0,6,31,Semi-Urban,Software Engineer,25949,0 +102685,Male,27,PhD,14,77,71,95,41,1.0,7,11,Urban,ML Engineer,38974,1 +102686,Male,36,Diploma,1,24,23,33,44,7.0,5,14,Urban,Data Analyst,141908,0 +102687,Male,51,Masters,8,63,67,40,71,8.0,1,86,Urban,HR Executive,44847,1 +102688,Female,32,Masters,3,46,88,89,80,0.0,7,31,Semi-Urban,Manager,46309,1 +102689,Male,45,Bachelors,10,67,29,10,33,8.0,1,67,Urban,HR Executive,98849,0 +102690,Male,37,Diploma,10,67,71,95,26,8.0,5,19,Semi-Urban,Software Engineer,125245,1 +102691,Male,35,Diploma,7,60,10,9,54,1.0,1,7,Urban,Software Engineer,116112,0 +102692,Female,28,Bachelors,13,89,50,53,27,3.0,1,1,Urban,Data Analyst,75980,0 +102693,Male,27,Masters,5,73,43,24,54,4.0,5,44,Urban,Manager,86653,0 +102694,Male,31,Diploma,10,43,41,52,15,1.0,0,71,Urban,Data Analyst,141827,0 +102695,Male,44,Bachelors,12,57,71,35,41,0.0,2,72,Urban,Manager,46996,1 +102696,Female,47,Masters,14,43,58,12,9,0.0,3,30,Rural,Data Analyst,22935,0 +102697,Male,38,Masters,5,37,60,94,2,5.0,0,77,Rural,Software Engineer,69522,1 +102698,Female,52,Bachelors,8,33,6,77,98,8.0,0,19,Semi-Urban,Manager,125423,0 +102699,Male,40,High School,3,58,16,54,37,9.0,0,82,Semi-Urban,Data Analyst,22668,0 +102700,Female,33,Masters,4,92,13,85,97,1.0,2,88,Urban,Data Analyst,87291,1 +102701,Male,43,Bachelors,18,17,75,80,92,7.0,7,77,Urban,Manager,71842,1 +102702,Female,55,Diploma,11,35,39,96,88,2.0,6,45,Urban,Data Analyst,97663,0 +102703,Female,52,Masters,12,73,82,90,64,3.0,3,57,Urban,Manager,32004,1 +102704,Male,49,High School,3,38,63,51,98,2.0,2,78,Semi-Urban,Data Analyst,63338,0 +102705,Male,22,Masters,6,64,8,4,72,7.0,6,58,Urban,HR Executive,118417,0 +102706,Male,53,Masters,3,47,98,79,38,0.0,3,85,Semi-Urban,HR Executive,126795,1 +102707,Female,56,High School,13,98,88,78,16,3.0,3,29,Rural,HR Executive,36958,1 +102708,Female,39,Diploma,19,66,7,8,31,3.0,3,58,Semi-Urban,Software Engineer,22303,0 +102709,Male,39,Masters,19,68,95,19,40,6.0,0,50,Urban,HR Executive,60423,0 +102710,Male,59,Masters,4,19,35,23,76,3.0,6,65,Urban,ML Engineer,27291,0 +102711,Female,58,Bachelors,3,80,81,16,31,6.0,0,61,Rural,HR Executive,91732,0 +102712,Female,23,Masters,16,10,38,61,6,5.0,7,34,Rural,ML Engineer,31014,0 +102713,Male,35,Bachelors,8,90,88,10,15,3.0,1,13,Urban,Data Analyst,85212,0 +102714,Male,31,Bachelors,3,40,12,76,68,9.0,3,39,Urban,HR Executive,124636,0 +102715,Female,35,Diploma,14,86,67,68,37,2.0,0,95,Urban,HR Executive,85087,1 +102716,Female,25,Masters,1,57,69,4,0,6.0,3,88,Urban,Software Engineer,35228,0 +102717,Male,57,Bachelors,17,94,29,84,88,2.0,2,63,Rural,HR Executive,148920,1 +102718,Female,59,Bachelors,18,70,79,86,61,2.0,2,59,Rural,Data Analyst,141971,1 +102719,Male,32,Masters,2,44,52,63,20,0.0,4,81,Semi-Urban,ML Engineer,33307,1 +102720,Male,41,Bachelors,18,74,28,89,44,7.0,4,90,Rural,ML Engineer,59164,1 +102721,Male,53,Diploma,10,33,12,94,38,3.0,7,83,Semi-Urban,Software Engineer,98349,0 +102722,Female,49,Diploma,19,39,12,18,59,8.0,2,60,Semi-Urban,ML Engineer,147401,0 +102723,Male,37,Bachelors,0,35,30,41,2,3.0,2,51,Semi-Urban,HR Executive,31588,0 +102724,Male,27,High School,14,24,9,24,64,8.0,5,25,Urban,Manager,110704,0 +102725,Male,22,Diploma,19,6,6,96,47,1.0,0,42,Urban,Software Engineer,90875,0 +102726,Male,33,Bachelors,14,44,58,96,58,9.0,3,96,Rural,ML Engineer,124316,1 +102727,Male,33,PhD,6,78,92,35,96,7.0,5,82,Rural,ML Engineer,53618,1 +102728,Male,53,Bachelors,17,8,79,84,93,8.0,7,35,Rural,Data Analyst,37413,0 +102729,Female,47,Masters,16,5,2,63,93,4.0,1,38,Urban,Software Engineer,40910,0 +102730,Male,22,Bachelors,18,65,92,59,86,8.0,2,13,Urban,ML Engineer,21276,0 +102731,Female,32,High School,6,49,72,94,2,2.0,0,91,Rural,Data Analyst,42944,1 +102732,Male,32,Masters,0,29,77,87,37,1.0,6,32,Semi-Urban,Software Engineer,44400,0 +102733,Male,57,Bachelors,4,45,47,21,84,3.0,5,15,Urban,Software Engineer,61942,0 +102734,Male,22,Bachelors,9,22,87,87,44,4.0,6,10,Semi-Urban,ML Engineer,120419,0 +102735,Female,47,Bachelors,2,52,53,18,7,3.0,1,78,Semi-Urban,Manager,118145,0 +102736,Male,53,Masters,8,56,56,46,2,5.0,6,93,Rural,HR Executive,136241,1 +102737,Male,48,Diploma,18,18,53,60,56,6.0,4,46,Urban,ML Engineer,95099,0 +102738,Female,22,High School,1,56,31,48,23,5.0,5,14,Rural,HR Executive,111628,0 +102739,Male,47,Bachelors,7,18,90,48,13,2.0,3,61,Urban,ML Engineer,113207,0 +102740,Female,28,Diploma,2,81,43,70,21,7.0,3,41,Rural,HR Executive,86484,0 +102741,Male,50,High School,3,0,1,41,21,7.0,1,27,Rural,HR Executive,111258,0 +102742,Female,24,Masters,6,51,83,85,86,6.0,6,55,Urban,HR Executive,116449,1 +102743,Male,36,Bachelors,1,85,82,75,46,0.0,5,40,Rural,Software Engineer,138647,1 +102744,Female,23,Bachelors,4,49,64,39,33,0.0,4,52,Semi-Urban,HR Executive,130625,0 +102745,Male,47,Bachelors,3,23,78,84,77,0.0,7,95,Urban,HR Executive,35405,1 +102746,Male,43,Bachelors,11,77,40,27,12,1.0,1,27,Urban,Software Engineer,55037,0 +102747,Male,59,Diploma,10,85,30,7,20,2.0,1,2,Semi-Urban,Data Analyst,57609,0 +102748,Female,23,Masters,4,47,95,12,63,4.0,0,94,Semi-Urban,ML Engineer,140855,1 +102749,Male,27,Bachelors,2,28,82,84,0,2.0,1,36,Urban,Software Engineer,85851,0 +102750,Female,58,High School,14,58,70,41,51,3.0,5,73,Urban,Manager,119883,1 +102751,Male,38,Bachelors,3,12,34,46,2,8.0,6,7,Rural,ML Engineer,124353,0 +102752,Male,43,Masters,5,3,67,39,48,3.0,0,96,Semi-Urban,Manager,54510,0 +102753,Male,57,Bachelors,4,77,65,28,29,6.0,1,47,Semi-Urban,Manager,66175,0 +102754,Male,22,Diploma,17,96,72,23,59,6.0,4,78,Rural,ML Engineer,50306,1 +102755,Female,36,Masters,19,42,80,51,79,0.0,5,37,Urban,HR Executive,60630,0 +102756,Male,29,Diploma,5,93,46,35,75,0.0,7,88,Semi-Urban,ML Engineer,29594,1 +102757,Female,31,Bachelors,9,10,96,0,36,9.0,5,68,Urban,HR Executive,84279,0 +102758,Female,51,Bachelors,17,40,39,1,93,0.0,0,38,Semi-Urban,Data Analyst,92490,0 +102759,Other,31,High School,9,86,57,77,0,7.0,3,77,Semi-Urban,Data Analyst,117310,1 +102760,Male,28,Diploma,13,55,72,41,21,0.0,6,3,Semi-Urban,Software Engineer,102399,0 +102761,Male,22,Bachelors,5,0,76,57,82,1.0,0,11,Semi-Urban,Manager,75378,0 +102762,Male,56,High School,14,93,98,36,19,9.0,3,91,Rural,Manager,133036,1 +102763,Male,30,Bachelors,7,56,88,31,13,3.0,5,75,Urban,HR Executive,127971,1 +102764,Male,24,Bachelors,7,87,34,62,57,3.0,1,20,Urban,Software Engineer,113181,0 +102765,Female,47,Bachelors,15,63,27,50,72,1.0,1,87,Urban,Data Analyst,23227,0 +102766,Male,33,Bachelors,0,3,25,44,19,0.0,3,68,Semi-Urban,Data Analyst,44631,0 +102767,Male,24,Diploma,5,47,77,83,72,7.0,5,79,Urban,ML Engineer,60694,1 +102768,Male,50,Masters,19,63,43,43,58,2.0,6,40,Semi-Urban,Data Analyst,44956,0 +102769,Female,38,Bachelors,13,23,76,7,33,0.0,0,79,Rural,Data Analyst,62815,0 +102770,Female,35,Bachelors,7,12,86,80,40,9.0,5,98,Rural,Data Analyst,103736,1 +102771,Female,38,High School,7,48,44,17,5,5.0,3,38,Urban,Software Engineer,61323,0 +102772,Male,49,High School,15,54,80,13,26,4.0,1,56,Rural,ML Engineer,144714,0 +102773,Female,43,Bachelors,14,85,83,31,87,3.0,1,6,Urban,Software Engineer,31414,0 +102774,Male,58,Diploma,1,12,83,90,70,6.0,3,17,Rural,ML Engineer,98839,0 +102775,Female,56,Bachelors,17,22,75,2,12,5.0,1,52,Rural,Software Engineer,107296,0 +102776,Male,22,Bachelors,0,92,70,68,10,8.0,5,71,Urban,ML Engineer,138731,1 +102777,Male,39,Bachelors,2,71,53,48,53,0.0,7,77,Urban,Data Analyst,91523,1 +102778,Female,33,High School,13,36,42,55,19,7.0,6,29,Urban,HR Executive,29452,0 +102779,Male,44,Masters,0,41,98,15,80,8.0,4,3,Urban,Data Analyst,114173,0 +102780,Female,40,Bachelors,14,52,94,31,69,0.0,1,52,Rural,Software Engineer,26946,0 +102781,Female,32,Masters,5,86,32,27,56,6.0,4,69,Rural,ML Engineer,92042,0 +102782,Male,42,High School,2,40,2,41,4,1.0,5,3,Urban,Software Engineer,33711,0 +102783,Other,56,Bachelors,12,87,63,67,63,0.0,4,76,Rural,Manager,136817,1 +102784,Male,55,Diploma,6,40,79,6,82,9.0,4,18,Urban,Software Engineer,24838,0 +102785,Other,56,Masters,12,68,68,84,43,1.0,4,23,Urban,HR Executive,47276,1 +102786,Male,23,Bachelors,2,97,26,75,5,6.0,5,34,Semi-Urban,Data Analyst,50519,0 +102787,Male,24,Bachelors,8,72,50,93,18,6.0,3,16,Rural,Manager,137688,0 +102788,Female,50,Diploma,2,57,41,74,24,8.0,1,49,Urban,Software Engineer,54134,0 +102789,Male,54,Masters,4,60,12,98,63,5.0,2,95,Rural,HR Executive,40025,1 +102790,Male,32,Bachelors,3,65,31,0,16,5.0,5,3,Urban,Manager,63513,0 +102791,Other,56,Bachelors,17,2,52,38,17,5.0,0,75,Urban,Data Analyst,142461,0 +102792,Male,59,Diploma,6,59,65,18,1,6.0,2,69,Urban,Manager,138069,0 +102793,Male,21,Masters,6,52,88,13,71,7.0,6,9,Semi-Urban,Software Engineer,127754,0 +102794,Male,36,Diploma,19,44,97,72,13,8.0,5,61,Urban,Manager,33312,1 +102795,Male,26,Diploma,6,41,98,43,37,5.0,4,23,Semi-Urban,Data Analyst,111045,0 +102796,Female,33,PhD,4,6,18,90,83,4.0,0,83,Semi-Urban,Manager,67397,0 +102797,Female,56,Masters,8,53,88,66,13,7.0,7,24,Rural,Manager,100366,0 +102798,Male,42,Bachelors,19,33,96,82,94,4.0,4,69,Semi-Urban,ML Engineer,50820,1 +102799,Female,52,Bachelors,16,58,89,4,33,7.0,2,70,Urban,Manager,89162,0 +102800,Male,32,Diploma,15,45,47,60,57,1.0,3,77,Rural,HR Executive,59268,0 +102801,Male,54,Bachelors,12,33,51,94,75,4.0,6,0,Semi-Urban,Manager,93181,0 +102802,Male,48,Bachelors,18,72,37,55,93,4.0,0,30,Urban,ML Engineer,61350,0 +102803,Male,29,Diploma,7,68,98,93,46,3.0,4,35,Urban,Data Analyst,142099,1 +102804,Male,49,Bachelors,10,86,86,79,64,7.0,3,26,Urban,Data Analyst,25342,1 +102805,Male,45,Diploma,14,76,83,79,80,6.0,0,61,Semi-Urban,Data Analyst,104892,1 +102806,Female,45,Diploma,9,25,79,61,99,9.0,1,20,Urban,HR Executive,136803,0 +102807,Other,57,Bachelors,4,48,36,86,32,6.0,3,7,Urban,ML Engineer,23144,0 +102808,Male,40,Masters,18,4,95,38,89,2.0,1,30,Urban,Software Engineer,135679,0 +102809,Male,23,High School,0,6,14,23,86,9.0,1,18,Semi-Urban,HR Executive,75931,0 +102810,Female,28,Masters,5,87,32,73,59,5.0,3,43,Urban,HR Executive,99487,0 +102811,Male,27,PhD,4,38,5,53,15,0.0,6,31,Rural,Software Engineer,102269,0 +102812,Female,34,High School,14,27,62,58,95,5.0,5,47,Urban,Data Analyst,20378,0 +102813,Male,27,Diploma,4,88,21,10,58,1.0,5,41,Urban,ML Engineer,145587,0 +102814,Male,29,Diploma,16,52,85,61,9,4.0,7,9,Urban,ML Engineer,98659,0 +102815,Male,55,Masters,6,73,71,73,25,5.0,4,53,Urban,Manager,67668,1 +102816,Male,57,Bachelors,19,18,39,69,90,0.0,3,31,Urban,Data Analyst,119183,0 +102817,Female,59,Diploma,3,92,39,54,85,3.0,6,77,Urban,Data Analyst,32864,1 +102818,Female,35,Masters,16,10,64,9,20,4.0,4,5,Urban,Software Engineer,45986,0 +102819,Male,32,Diploma,12,12,75,21,12,8.0,1,59,Semi-Urban,Software Engineer,103723,0 +102820,Male,32,PhD,6,35,90,54,77,9.0,3,30,Urban,Manager,131256,0 +102821,Male,47,Masters,0,84,50,4,74,6.0,3,58,Semi-Urban,Manager,103317,0 +102822,Male,24,Bachelors,16,15,0,3,44,2.0,2,25,Semi-Urban,Manager,27608,0 +102823,Female,24,Bachelors,6,94,27,5,46,7.0,2,10,Urban,Manager,141534,0 +102824,Male,58,Bachelors,13,2,36,8,38,4.0,0,24,Urban,Software Engineer,76554,0 +102825,Other,47,Diploma,2,99,89,44,39,4.0,0,19,Urban,Software Engineer,123745,1 +102826,Female,38,Bachelors,6,99,65,67,39,4.0,0,74,Semi-Urban,HR Executive,23900,1 +102827,Female,29,Bachelors,7,46,66,28,36,1.0,6,9,Semi-Urban,ML Engineer,85282,0 +102828,Male,48,Bachelors,16,72,47,20,59,2.0,2,23,Urban,ML Engineer,65124,0 +102829,Male,45,High School,6,64,92,6,49,2.0,5,62,Rural,ML Engineer,39718,0 +102830,Male,39,High School,8,50,30,94,31,3.0,2,65,Urban,HR Executive,42461,1 +102831,Other,34,PhD,19,57,58,25,7,9.0,6,26,Urban,Manager,120729,0 +102832,Male,35,PhD,11,73,79,99,92,2.0,1,44,Urban,Manager,92654,1 +102833,Male,25,Diploma,14,68,64,9,58,6.0,1,98,Semi-Urban,Software Engineer,135572,1 +102834,Male,36,Masters,12,80,84,81,10,5.0,4,68,Urban,Software Engineer,125662,1 +102835,Male,43,Diploma,6,94,21,5,76,0.0,0,48,Urban,ML Engineer,49729,0 +102836,Male,57,Bachelors,12,19,46,49,10,5.0,1,32,Semi-Urban,Manager,136688,0 +102837,Male,53,Bachelors,10,65,12,11,5,8.0,0,29,Urban,Manager,68391,0 +102838,Male,25,Masters,13,45,97,22,68,2.0,3,40,Urban,ML Engineer,104246,0 +102839,Female,27,Bachelors,3,58,53,3,9,5.0,0,57,Urban,ML Engineer,128309,0 +102840,Male,29,Diploma,19,99,71,25,31,7.0,2,75,Urban,ML Engineer,118077,1 +102841,Female,50,Bachelors,8,12,87,81,48,8.0,3,29,Semi-Urban,Data Analyst,119421,0 +102842,Male,25,Masters,19,70,32,86,98,7.0,7,7,Semi-Urban,Software Engineer,27015,0 +102843,Male,24,Masters,7,35,51,15,10,9.0,0,0,Urban,ML Engineer,147032,0 +102844,Male,23,High School,9,94,62,56,8,1.0,5,86,Rural,HR Executive,85421,1 +102845,Male,45,Bachelors,17,39,63,51,61,7.0,3,22,Rural,HR Executive,35209,0 +102846,Male,57,Bachelors,1,77,93,49,85,5.0,3,31,Rural,Manager,58812,1 +102847,Male,29,High School,11,79,68,76,72,8.0,6,22,Rural,Data Analyst,149699,1 +102848,Female,44,Diploma,18,88,98,43,85,7.0,5,75,Urban,Manager,52794,1 +102849,Female,22,PhD,7,47,49,78,82,9.0,4,36,Urban,ML Engineer,76136,0 +102850,Female,28,Diploma,15,8,80,0,48,3.0,2,68,Rural,HR Executive,102857,0 +102851,Female,50,Masters,12,68,61,72,32,2.0,0,97,Urban,Data Analyst,106594,1 +102852,Male,49,Bachelors,18,35,87,31,93,4.0,3,12,Urban,Software Engineer,30030,0 +102853,Male,44,High School,17,51,12,16,77,9.0,0,48,Urban,ML Engineer,144577,0 +102854,Female,22,High School,15,16,68,69,62,4.0,7,96,Urban,Data Analyst,137709,1 +102855,Female,30,Bachelors,13,72,59,18,37,0.0,7,51,Semi-Urban,HR Executive,24814,0 +102856,Female,55,Bachelors,5,63,67,77,87,8.0,0,96,Urban,Data Analyst,32173,1 +102857,Male,35,High School,8,80,52,0,91,2.0,1,24,Semi-Urban,Software Engineer,133005,0 +102858,Male,22,Masters,14,58,57,29,35,0.0,3,5,Urban,HR Executive,103447,0 +102859,Male,49,Bachelors,19,35,99,3,4,7.0,5,6,Urban,ML Engineer,82408,0 +102860,Male,36,Diploma,15,67,67,65,2,1.0,0,89,Urban,HR Executive,143149,1 +102861,Male,39,Masters,18,27,31,16,66,2.0,6,51,Semi-Urban,Software Engineer,65800,0 +102862,Male,54,Bachelors,0,64,80,46,94,6.0,6,70,Urban,ML Engineer,107267,1 +102863,Male,47,Bachelors,10,8,2,76,62,5.0,4,65,Urban,Data Analyst,124593,0 +102864,Female,39,Diploma,4,96,13,15,33,5.0,5,45,Rural,HR Executive,24152,0 +102865,Male,27,Bachelors,7,29,11,90,96,1.0,7,39,Urban,Data Analyst,52896,0 +102866,Female,54,Bachelors,9,64,13,40,70,3.0,3,56,Urban,Software Engineer,87959,0 +102867,Male,45,Masters,18,40,37,13,27,8.0,1,3,Semi-Urban,Data Analyst,133100,0 +102868,Male,36,PhD,17,77,61,34,4,7.0,2,66,Rural,HR Executive,73385,1 +102869,Male,55,Bachelors,17,54,20,50,66,3.0,5,46,Urban,ML Engineer,143776,0 +102870,Male,46,Bachelors,1,46,99,14,73,3.0,0,55,Urban,Manager,72565,0 +102871,Male,49,Masters,19,74,13,33,55,8.0,5,45,Semi-Urban,ML Engineer,77663,0 +102872,Male,22,Diploma,16,74,15,17,29,3.0,4,82,Semi-Urban,HR Executive,128872,0 +102873,Male,48,Diploma,10,93,28,1,43,4.0,4,40,Semi-Urban,Software Engineer,63486,0 +102874,Female,49,Bachelors,15,35,28,8,50,1.0,3,76,Urban,HR Executive,112502,0 +102875,Male,49,Masters,1,62,51,19,66,7.0,5,67,Urban,Manager,52095,0 +102876,Male,42,Bachelors,3,60,15,79,25,9.0,0,9,Semi-Urban,HR Executive,64531,0 +102877,Male,35,High School,14,83,44,91,84,4.0,5,17,Rural,Manager,146755,1 +102878,Female,38,Bachelors,3,76,82,35,63,4.0,1,72,Semi-Urban,Software Engineer,72165,1 +102879,Male,59,High School,11,94,33,34,35,7.0,6,89,Urban,Data Analyst,137452,1 +102880,Female,21,Bachelors,6,65,32,49,57,6.0,7,11,Urban,Software Engineer,126116,0 +102881,Female,41,High School,17,82,81,40,23,6.0,7,14,Urban,Manager,134726,0 +102882,Male,22,PhD,13,91,54,40,80,2.0,1,10,Semi-Urban,Software Engineer,42077,0 +102883,Male,34,Bachelors,13,78,92,7,16,8.0,5,62,Urban,Manager,121701,1 +102884,Male,41,Masters,7,71,89,31,0,9.0,7,37,Semi-Urban,ML Engineer,117715,0 +102885,Female,22,Bachelors,5,23,24,90,5,7.0,4,35,Urban,ML Engineer,50205,0 +102886,Male,27,Bachelors,12,93,42,6,87,8.0,4,48,Semi-Urban,Software Engineer,54490,0 +102887,Male,30,Diploma,12,42,84,56,8,2.0,0,56,Semi-Urban,ML Engineer,86114,1 +102888,Female,29,Bachelors,16,33,25,10,26,3.0,6,5,Urban,Manager,73042,0 +102889,Female,53,Diploma,4,93,65,58,58,4.0,7,98,Urban,ML Engineer,24509,1 +102890,Male,38,Bachelors,11,82,77,37,54,5.0,3,39,Urban,HR Executive,140755,1 +102891,Other,25,Bachelors,6,40,61,71,94,2.0,6,78,Semi-Urban,Software Engineer,125600,1 +102892,Male,31,High School,9,59,80,44,76,4.0,1,65,Urban,ML Engineer,140477,1 +102893,Female,46,Masters,0,23,17,57,79,9.0,7,10,Urban,HR Executive,29727,0 +102894,Female,29,High School,11,62,3,35,60,1.0,6,64,Urban,HR Executive,99825,0 +102895,Female,31,Bachelors,4,85,86,10,3,0.0,1,14,Urban,ML Engineer,94426,0 +102896,Male,36,Diploma,5,69,22,20,90,3.0,6,74,Rural,Software Engineer,110145,0 +102897,Male,27,Bachelors,8,94,12,84,2,4.0,6,99,Urban,Data Analyst,40589,1 +102898,Male,44,Diploma,10,24,3,83,55,7.0,7,81,Rural,Software Engineer,75572,0 +102899,Male,36,High School,3,31,60,51,84,8.0,5,76,Rural,HR Executive,80550,0 +102900,Female,46,Masters,13,50,66,23,58,9.0,4,75,Urban,Manager,24214,0 +102901,Female,38,Diploma,8,46,59,61,15,8.0,2,97,Semi-Urban,Data Analyst,114634,1 +102902,Female,37,Bachelors,1,18,18,52,76,4.0,7,29,Urban,Manager,127859,0 +102903,Female,21,Bachelors,15,78,46,14,3,8.0,2,59,Rural,Data Analyst,65266,0 +102904,Male,23,Bachelors,6,88,32,21,24,9.0,4,4,Rural,Software Engineer,144428,0 +102905,Male,49,High School,13,58,91,9,38,9.0,7,87,Rural,Data Analyst,109553,1 +102906,Female,51,Bachelors,9,47,43,84,11,0.0,5,84,Urban,ML Engineer,96695,1 +102907,Male,53,Diploma,9,5,82,83,19,9.0,5,36,Semi-Urban,HR Executive,91948,0 +102908,Male,22,High School,6,71,4,77,55,6.0,5,69,Semi-Urban,ML Engineer,70052,0 +102909,Male,29,Bachelors,11,64,57,42,53,2.0,1,6,Urban,ML Engineer,139158,0 +102910,Male,27,Masters,11,12,9,84,45,3.0,6,43,Semi-Urban,Software Engineer,78917,0 +102911,Male,25,Bachelors,3,97,74,84,68,8.0,0,73,Urban,HR Executive,27574,1 +102912,Male,58,Bachelors,0,70,40,58,59,4.0,5,19,Semi-Urban,Data Analyst,115108,0 +102913,Female,26,PhD,8,52,40,64,64,3.0,1,38,Semi-Urban,Software Engineer,122268,0 +102914,Female,52,Bachelors,16,65,22,93,71,5.0,6,9,Rural,Data Analyst,72361,0 +102915,Male,41,Diploma,0,14,84,83,83,9.0,7,40,Rural,Data Analyst,95391,0 +102916,Male,57,High School,11,88,41,21,3,9.0,6,55,Semi-Urban,Software Engineer,92632,0 +102917,Other,50,High School,11,35,35,25,11,5.0,1,34,Urban,Software Engineer,49684,0 +102918,Male,28,Bachelors,2,36,99,53,38,8.0,1,61,Semi-Urban,Software Engineer,23130,1 +102919,Male,43,Bachelors,8,66,43,37,58,9.0,2,77,Semi-Urban,Software Engineer,62560,0 +102920,Male,40,Masters,14,60,95,39,36,0.0,5,30,Urban,Software Engineer,25190,0 +102921,Male,58,High School,1,85,49,24,67,1.0,7,10,Rural,ML Engineer,137477,0 +102922,Male,30,High School,15,22,76,65,29,6.0,6,95,Urban,HR Executive,67645,1 +102923,Male,46,Diploma,1,51,68,23,86,3.0,0,50,Semi-Urban,Software Engineer,127518,0 +102924,Male,32,Bachelors,2,59,59,7,18,6.0,5,64,Urban,Manager,51543,0 +102925,Female,32,Bachelors,11,34,23,66,37,1.0,5,39,Urban,Manager,149890,0 +102926,Male,41,Masters,17,24,21,87,90,7.0,3,91,Urban,Software Engineer,108912,0 +102927,Male,36,Diploma,1,55,43,35,27,4.0,4,5,Semi-Urban,HR Executive,127592,0 +102928,Male,45,Bachelors,1,5,97,21,32,6.0,7,23,Urban,HR Executive,148561,0 +102929,Female,53,Diploma,2,63,65,68,86,0.0,5,74,Semi-Urban,ML Engineer,140072,1 +102930,Female,43,Bachelors,16,70,50,6,58,8.0,1,23,Semi-Urban,Software Engineer,39467,0 +102931,Female,36,Bachelors,10,95,33,36,72,5.0,4,64,Semi-Urban,ML Engineer,86129,0 +102932,Male,46,Diploma,19,34,7,17,99,5.0,0,61,Urban,ML Engineer,49944,0 +102933,Female,34,Bachelors,15,15,81,56,56,3.0,2,31,Urban,Software Engineer,86423,0 +102934,Female,23,Bachelors,16,0,35,32,13,1.0,2,20,Urban,ML Engineer,122083,0 +102935,Male,44,Bachelors,10,60,82,11,78,1.0,4,74,Semi-Urban,Software Engineer,112787,0 +102936,Other,35,Masters,7,75,29,83,43,5.0,0,52,Urban,Data Analyst,70951,0 +102937,Male,22,Bachelors,5,8,13,54,90,5.0,3,83,Rural,HR Executive,22805,0 +102938,Female,54,Bachelors,15,67,53,92,27,1.0,5,14,Rural,Manager,46212,0 +102939,Male,35,Diploma,9,36,96,65,15,3.0,5,13,Rural,Software Engineer,131631,0 +102940,Male,50,Bachelors,1,4,20,96,78,4.0,2,5,Urban,Data Analyst,118118,0 +102941,Female,47,Masters,12,33,83,65,92,5.0,7,92,Rural,Data Analyst,107166,1 +102942,Female,22,Masters,11,58,57,41,70,2.0,1,24,Urban,HR Executive,141651,0 +102943,Other,51,Masters,16,83,41,32,31,8.0,5,6,Semi-Urban,HR Executive,137402,0 +102944,Other,50,Masters,3,6,25,24,48,6.0,2,50,Rural,ML Engineer,70970,0 +102945,Male,34,Diploma,18,28,71,50,38,5.0,4,23,Urban,Data Analyst,80593,0 +102946,Male,31,PhD,17,4,50,11,37,3.0,0,18,Semi-Urban,Manager,122581,0 +102947,Male,26,High School,10,6,7,64,15,8.0,4,29,Urban,Manager,38838,0 +102948,Male,42,Masters,17,67,63,12,40,5.0,0,77,Urban,Manager,64830,0 +102949,Female,54,Masters,11,17,9,67,41,6.0,2,19,Urban,HR Executive,88303,0 +102950,Male,34,Masters,10,91,6,48,53,5.0,5,50,Rural,HR Executive,26350,0 +102951,Male,49,Bachelors,16,87,52,97,20,9.0,0,28,Semi-Urban,ML Engineer,50129,1 +102952,Female,45,Masters,0,8,42,24,20,9.0,2,29,Urban,ML Engineer,26620,0 +102953,Female,26,Bachelors,11,55,7,66,57,6.0,2,90,Urban,Manager,92762,0 +102954,Female,39,Diploma,11,60,77,21,52,2.0,4,10,Urban,Data Analyst,125246,0 +102955,Male,45,Bachelors,15,92,75,60,29,2.0,0,84,Semi-Urban,ML Engineer,141197,1 +102956,Male,21,Masters,7,13,81,18,66,8.0,6,35,Rural,HR Executive,92641,0 +102957,Female,53,High School,12,28,69,31,8,2.0,4,28,Urban,HR Executive,148400,0 +102958,Female,36,High School,4,17,19,17,99,0.0,0,79,Urban,Software Engineer,76483,0 +102959,Male,54,Masters,1,44,12,24,38,3.0,4,93,Urban,Data Analyst,122019,0 +102960,Male,32,Diploma,10,8,27,76,23,8.0,2,73,Urban,HR Executive,69727,0 +102961,Male,40,Diploma,0,79,83,11,1,4.0,4,22,Rural,Software Engineer,70778,0 +102962,Female,26,Masters,19,27,31,99,6,4.0,7,13,Rural,HR Executive,125235,0 +102963,Female,59,Diploma,2,58,12,24,77,2.0,6,5,Rural,Software Engineer,100534,0 +102964,Female,31,Masters,19,92,34,14,72,3.0,5,1,Urban,HR Executive,27739,0 +102965,Female,21,High School,10,9,84,51,32,3.0,6,35,Urban,Data Analyst,75438,0 +102966,Female,42,Diploma,19,83,98,89,20,2.0,3,74,Urban,Software Engineer,131061,1 +102967,Male,24,Diploma,0,97,5,3,5,0.0,1,92,Urban,Data Analyst,127104,0 +102968,Female,35,Masters,9,11,89,23,81,8.0,1,62,Rural,Manager,136444,0 +102969,Male,35,Masters,18,53,3,79,1,2.0,6,3,Rural,ML Engineer,142166,0 +102970,Other,51,Bachelors,2,12,63,50,38,9.0,2,21,Urban,HR Executive,134209,0 +102971,Female,47,Diploma,4,11,47,93,61,4.0,0,19,Rural,Manager,138486,0 +102972,Male,55,Masters,4,81,29,83,63,4.0,4,45,Rural,Data Analyst,55900,1 +102973,Female,58,Diploma,15,53,90,6,20,7.0,0,50,Semi-Urban,Manager,135436,0 +102974,Male,40,PhD,6,48,63,18,97,4.0,3,7,Rural,Software Engineer,123631,0 +102975,Male,21,Bachelors,7,4,7,59,21,2.0,1,17,Urban,ML Engineer,149815,0 +102976,Male,29,Masters,17,19,24,12,5,2.0,1,70,Semi-Urban,Software Engineer,29207,0 +102977,Female,58,Bachelors,7,23,15,70,27,2.0,0,90,Urban,Manager,95643,0 +102978,Male,54,Masters,12,30,80,64,40,5.0,3,39,Urban,HR Executive,117823,0 +102979,Male,50,Diploma,11,76,67,7,98,7.0,2,28,Rural,Data Analyst,124677,0 +102980,Male,40,Diploma,0,55,97,11,24,1.0,1,71,Semi-Urban,Software Engineer,146761,0 +102981,Male,59,Bachelors,5,8,43,38,87,5.0,6,2,Rural,HR Executive,81223,0 +102982,Male,23,Diploma,6,10,62,42,38,4.0,7,61,Urban,Data Analyst,31597,0 +102983,Male,35,Diploma,6,90,59,82,60,7.0,6,45,Urban,Software Engineer,105512,1 +102984,Male,39,Bachelors,18,2,4,86,92,0.0,3,65,Semi-Urban,ML Engineer,58597,0 +102985,Female,36,Masters,4,31,98,57,75,4.0,3,43,Urban,ML Engineer,52075,0 +102986,Female,33,High School,18,57,6,50,9,9.0,4,31,Semi-Urban,Data Analyst,22366,0 +102987,Male,43,Bachelors,2,19,98,61,34,3.0,5,57,Semi-Urban,Manager,39046,1 +102988,Other,41,Bachelors,10,31,82,26,16,9.0,6,20,Urban,Data Analyst,58308,0 +102989,Male,21,Bachelors,1,79,28,9,1,4.0,7,33,Rural,Software Engineer,118354,0 +102990,Female,37,PhD,13,23,42,64,55,1.0,1,14,Urban,Manager,27720,0 +102991,Male,39,Masters,8,68,72,65,0,0.0,5,31,Semi-Urban,HR Executive,91929,1 +102992,Female,28,PhD,4,63,56,3,90,1.0,7,79,Semi-Urban,Software Engineer,42746,0 +102993,Female,56,Bachelors,2,85,73,51,88,4.0,6,0,Urban,ML Engineer,55357,0 +102994,Male,24,Masters,17,64,79,45,83,9.0,6,54,Semi-Urban,Manager,94055,1 +102995,Female,46,Masters,4,94,94,2,30,8.0,3,63,Urban,Data Analyst,33343,1 +102996,Female,52,Bachelors,6,94,61,78,62,8.0,0,75,Urban,Software Engineer,116757,1 +102997,Male,33,High School,3,38,75,34,21,8.0,2,99,Urban,ML Engineer,87291,1 +102998,Male,58,High School,0,31,33,78,14,1.0,0,48,Urban,Manager,114826,0 +102999,Female,40,Bachelors,13,40,35,90,33,1.0,3,12,Rural,HR Executive,66459,0 +103000,Female,25,Diploma,12,26,2,3,12,2.0,6,4,Urban,Data Analyst,94819,0 +103001,Male,22,Masters,8,36,59,39,26,7.0,0,12,Semi-Urban,HR Executive,149616,0 +103002,Female,39,High School,3,19,64,30,56,8.0,7,7,Rural,HR Executive,93843,0 +103003,Female,37,Masters,18,15,29,78,93,6.0,2,42,Urban,Manager,23165,0 +103004,Other,57,High School,1,8,15,97,35,7.0,2,62,Rural,Software Engineer,98078,0 +103005,Male,55,Masters,13,45,9,23,89,1.0,5,35,Urban,ML Engineer,91609,0 +103006,Male,44,Masters,10,77,67,86,25,5.0,6,47,Urban,Data Analyst,59314,1 +103007,Female,46,Masters,5,31,24,83,8,8.0,1,72,Urban,Data Analyst,50100,0 +103008,Female,28,Masters,0,22,36,91,65,1.0,2,59,Semi-Urban,Software Engineer,24114,0 +103009,Male,59,Masters,0,31,99,19,0,6.0,4,55,Urban,HR Executive,67141,0 +103010,Male,57,Bachelors,18,11,78,0,82,1.0,2,61,Rural,Software Engineer,133680,0 +103011,Male,24,Diploma,6,11,66,55,38,4.0,1,37,Urban,HR Executive,57446,0 +103012,Male,46,Bachelors,6,10,88,52,13,6.0,3,51,Semi-Urban,HR Executive,56348,0 +103013,Female,29,Bachelors,0,40,19,15,17,9.0,5,70,Semi-Urban,ML Engineer,53287,0 +103014,Female,44,Bachelors,7,95,63,13,22,4.0,6,85,Urban,Software Engineer,45715,1 +103015,Female,42,Bachelors,3,25,8,24,89,0.0,5,45,Urban,Data Analyst,143905,0 +103016,Male,24,Bachelors,9,27,28,61,7,1.0,3,42,Rural,HR Executive,149728,0 +103017,Female,46,Masters,15,75,79,65,12,6.0,2,47,Semi-Urban,Software Engineer,49228,1 +103018,Male,33,High School,13,65,26,99,86,7.0,2,68,Semi-Urban,Manager,24785,1 +103019,Male,59,High School,8,42,72,9,39,3.0,3,23,Urban,Data Analyst,72120,0 +103020,Male,33,Bachelors,13,78,13,77,32,8.0,0,2,Semi-Urban,HR Executive,109649,0 +103021,Male,23,Bachelors,12,21,72,89,90,2.0,3,74,Rural,Software Engineer,137331,1 +103022,Female,29,Diploma,16,73,30,92,25,0.0,7,67,Urban,Data Analyst,92398,1 +103023,Female,55,Masters,14,3,40,46,61,6.0,3,32,Rural,Software Engineer,93866,0 +103024,Male,34,Diploma,18,75,70,98,66,9.0,6,69,Urban,Data Analyst,54568,1 +103025,Male,42,Bachelors,15,58,77,46,83,0.0,7,82,Urban,Data Analyst,126311,1 +103026,Female,40,Masters,15,47,32,17,36,9.0,2,44,Rural,Data Analyst,41186,0 +103027,Male,32,Diploma,18,88,68,8,4,9.0,1,30,Semi-Urban,Manager,78326,0 +103028,Female,41,Masters,16,83,9,87,62,6.0,2,78,Semi-Urban,HR Executive,37435,1 +103029,Female,28,Diploma,0,25,73,90,44,5.0,0,22,Urban,ML Engineer,33776,0 +103030,Female,54,Diploma,15,5,88,63,53,1.0,4,77,Semi-Urban,Data Analyst,69851,0 +103031,Male,45,Diploma,4,73,15,35,90,0.0,5,9,Urban,Manager,35858,0 +103032,Female,28,Diploma,18,29,48,67,97,2.0,0,52,Semi-Urban,ML Engineer,113305,0 +103033,Male,56,Diploma,4,30,27,70,91,0.0,4,20,Urban,HR Executive,27894,0 +103034,Male,45,Bachelors,17,90,1,23,93,0.0,7,58,Semi-Urban,Data Analyst,100239,0 +103035,Male,43,Diploma,10,80,4,38,44,3.0,1,10,Semi-Urban,Manager,45964,0 +103036,Female,29,Bachelors,0,97,28,49,75,3.0,7,82,Urban,ML Engineer,97224,1 +103037,Female,51,Bachelors,14,32,83,88,76,0.0,1,62,Rural,ML Engineer,20645,1 +103038,Male,59,Masters,12,41,9,74,6,2.0,6,5,Urban,HR Executive,27914,0 +103039,Female,42,Diploma,3,29,89,67,68,4.0,3,56,Semi-Urban,Software Engineer,68575,1 +103040,Male,21,Bachelors,17,82,51,41,26,8.0,5,99,Urban,Software Engineer,110504,1 +103041,Female,56,Bachelors,15,91,98,42,30,5.0,3,32,Urban,Software Engineer,56672,1 +103042,Female,55,Bachelors,11,17,77,95,2,0.0,2,40,Rural,Software Engineer,65806,0 +103043,Male,22,Bachelors,10,39,40,55,19,5.0,3,45,Semi-Urban,HR Executive,44355,0 +103044,Female,58,High School,15,51,62,30,89,6.0,0,64,Urban,HR Executive,62379,0 +103045,Female,46,Bachelors,19,56,39,7,24,7.0,0,83,Urban,Manager,73100,0 +103046,Male,55,Bachelors,17,11,90,98,75,3.0,4,90,Urban,HR Executive,67542,1 +103047,Male,34,Diploma,9,54,33,71,26,9.0,6,42,Rural,Software Engineer,22621,0 +103048,Male,32,Bachelors,18,42,19,43,25,1.0,2,90,Urban,HR Executive,46480,0 +103049,Male,40,Bachelors,10,81,23,97,40,8.0,5,77,Urban,Data Analyst,79013,1 +103050,Male,49,Bachelors,19,92,38,90,4,5.0,7,45,Urban,ML Engineer,148449,1 +103051,Female,52,Bachelors,7,33,72,49,73,3.0,4,90,Rural,Data Analyst,77722,1 +103052,Male,23,Diploma,10,28,43,28,84,9.0,4,57,Rural,Data Analyst,136430,0 +103053,Male,49,PhD,11,12,4,79,71,8.0,3,25,Semi-Urban,Software Engineer,86470,0 +103054,Male,55,Masters,15,98,50,93,91,4.0,2,50,Urban,Software Engineer,123895,1 +103055,Male,24,Bachelors,3,9,32,74,57,0.0,0,18,Urban,Manager,111222,0 +103056,Male,30,Masters,8,50,12,59,94,0.0,0,4,Semi-Urban,HR Executive,133009,0 +103057,Female,54,Diploma,14,40,89,72,3,4.0,7,69,Urban,Manager,46363,1 +103058,Male,51,Bachelors,10,53,32,46,52,8.0,4,65,Rural,HR Executive,77395,0 +103059,Female,57,Masters,4,82,66,9,24,7.0,2,7,Urban,ML Engineer,118218,0 +103060,Male,33,High School,19,85,98,38,83,3.0,4,35,Semi-Urban,ML Engineer,107054,1 +103061,Male,21,High School,17,98,57,78,30,8.0,3,62,Semi-Urban,Data Analyst,98159,1 +103062,Male,49,High School,1,57,44,81,97,5.0,4,13,Semi-Urban,ML Engineer,38834,0 +103063,Male,41,High School,12,92,72,23,69,2.0,7,39,Urban,Software Engineer,130829,0 +103064,Female,40,Masters,6,62,83,76,91,0.0,0,52,Urban,ML Engineer,49727,1 +103065,Male,54,Bachelors,7,85,67,96,26,1.0,4,51,Rural,Manager,89153,1 +103066,Male,22,Diploma,6,85,3,33,57,1.0,5,62,Urban,HR Executive,139518,0 +103067,Male,42,Masters,14,40,5,60,62,9.0,6,31,Rural,Data Analyst,96852,0 +103068,Female,46,Bachelors,14,29,7,98,86,0.0,5,17,Urban,HR Executive,29387,0 +103069,Female,33,PhD,9,87,13,53,26,2.0,6,55,Urban,HR Executive,30275,0 +103070,Female,33,Masters,12,99,85,99,15,9.0,3,73,Urban,Manager,139250,1 +103071,Male,44,Diploma,5,85,5,31,96,6.0,6,25,Rural,ML Engineer,58668,0 +103072,Male,22,Diploma,15,36,34,4,22,7.0,1,45,Urban,Software Engineer,30820,0 +103073,Female,24,Masters,6,12,3,46,87,7.0,4,52,Urban,ML Engineer,39866,0 +103074,Female,27,Bachelors,16,7,84,67,33,7.0,4,63,Semi-Urban,Manager,45876,0 +103075,Male,55,PhD,8,5,82,40,55,4.0,4,95,Urban,Data Analyst,90702,0 +103076,Female,51,Diploma,15,51,1,38,28,2.0,2,70,Rural,Manager,126082,0 +103077,Female,42,Masters,17,31,96,12,68,8.0,2,41,Urban,HR Executive,20714,0 +103078,Male,28,High School,15,58,20,5,54,4.0,0,46,Urban,HR Executive,105613,0 +103079,Male,27,Diploma,1,85,15,41,93,4.0,0,14,Urban,ML Engineer,106115,0 +103080,Male,45,Masters,3,30,83,48,38,6.0,6,25,Semi-Urban,Data Analyst,95271,0 +103081,Female,57,PhD,4,68,53,46,91,2.0,4,75,Urban,Software Engineer,100269,1 +103082,Female,34,Masters,18,96,69,32,84,7.0,3,1,Urban,Software Engineer,22593,0 +103083,Male,23,Diploma,19,62,33,32,84,4.0,0,63,Urban,ML Engineer,34213,0 +103084,Female,22,Bachelors,13,8,56,52,37,9.0,0,42,Rural,Software Engineer,31164,0 +103085,Male,58,Masters,17,38,62,69,88,1.0,0,65,Urban,HR Executive,54934,0 +103086,Male,43,Diploma,16,25,48,33,40,5.0,7,21,Urban,ML Engineer,111341,0 +103087,Female,34,Diploma,6,24,62,29,90,4.0,5,65,Urban,Data Analyst,84918,0 +103088,Male,30,PhD,10,92,54,22,35,5.0,1,84,Semi-Urban,ML Engineer,100497,1 +103089,Female,44,High School,13,87,61,57,67,8.0,0,32,Urban,HR Executive,93732,0 +103090,Female,43,High School,14,47,21,17,46,0.0,7,46,Semi-Urban,Software Engineer,28331,0 +103091,Male,43,Bachelors,7,58,3,62,63,5.0,0,59,Urban,Manager,125757,0 +103092,Female,42,Bachelors,3,65,45,50,51,5.0,4,47,Semi-Urban,HR Executive,122878,0 +103093,Female,44,Masters,7,47,59,57,23,9.0,2,43,Urban,Data Analyst,26330,0 +103094,Male,28,Bachelors,15,15,7,2,26,3.0,5,44,Urban,Software Engineer,60177,0 +103095,Male,31,High School,0,25,26,8,4,7.0,1,62,Urban,HR Executive,115053,0 +103096,Female,31,Bachelors,14,86,53,47,20,5.0,4,44,Urban,ML Engineer,79902,0 +103097,Female,55,Bachelors,7,54,7,90,31,0.0,0,1,Urban,ML Engineer,108097,0 +103098,Male,35,High School,16,46,15,31,40,0.0,0,55,Semi-Urban,Manager,120383,0 +103099,Female,28,Bachelors,5,80,51,30,71,5.0,3,44,Urban,Manager,58331,0 +103100,Female,42,Diploma,5,29,40,87,92,6.0,4,18,Urban,HR Executive,114044,0 +103101,Male,54,High School,9,28,45,12,73,6.0,2,89,Urban,Manager,33379,0 +103102,Male,50,Bachelors,4,82,49,16,32,9.0,4,86,Urban,Software Engineer,90606,0 +103103,Male,21,Bachelors,18,66,78,96,55,2.0,4,44,Semi-Urban,Data Analyst,139701,1 +103104,Male,27,Bachelors,11,90,8,17,81,0.0,1,44,Urban,Data Analyst,28859,0 +103105,Male,59,Bachelors,12,59,49,97,73,1.0,2,56,Rural,Data Analyst,82832,1 +103106,Male,23,Bachelors,6,11,45,0,85,6.0,7,63,Rural,Software Engineer,26171,0 +103107,Female,27,Diploma,18,9,12,59,59,6.0,0,34,Rural,Software Engineer,23796,0 +103108,Male,43,Bachelors,16,57,47,32,1,2.0,4,89,Semi-Urban,ML Engineer,28219,0 +103109,Male,46,Masters,13,17,47,26,12,1.0,7,3,Semi-Urban,Software Engineer,22953,0 +103110,Male,32,Bachelors,16,77,23,76,40,6.0,2,49,Rural,Software Engineer,72891,0 +103111,Male,55,High School,4,60,59,5,22,2.0,4,15,Semi-Urban,Software Engineer,142819,0 +103112,Male,50,Diploma,0,65,80,0,32,8.0,6,58,Rural,Software Engineer,66873,0 +103113,Male,53,Bachelors,7,9,47,29,36,4.0,0,18,Semi-Urban,HR Executive,62195,0 +103114,Female,50,Masters,3,93,71,23,22,5.0,1,72,Urban,Manager,127565,1 +103115,Female,29,Masters,11,69,69,64,9,4.0,1,22,Urban,Software Engineer,26510,0 +103116,Female,56,Masters,8,41,76,14,51,6.0,5,65,Urban,Software Engineer,149129,0 +103117,Male,31,High School,17,13,87,73,50,7.0,5,22,Urban,HR Executive,93784,0 +103118,Male,22,Bachelors,15,60,50,37,39,3.0,5,40,Urban,Data Analyst,82016,0 +103119,Male,33,High School,8,42,75,99,29,5.0,5,96,Urban,HR Executive,130318,1 +103120,Female,28,Bachelors,9,99,23,98,30,3.0,0,30,Urban,Manager,31163,1 +103121,Male,59,Masters,1,73,87,69,71,1.0,0,24,Rural,ML Engineer,82295,1 +103122,Female,36,Masters,19,76,61,84,20,2.0,2,68,Semi-Urban,ML Engineer,84372,1 +103123,Male,56,High School,17,10,50,26,21,7.0,2,63,Semi-Urban,Software Engineer,125052,0 +103124,Male,33,Diploma,13,40,73,93,97,8.0,5,90,Urban,Software Engineer,135357,1 +103125,Female,22,Bachelors,0,92,50,48,33,6.0,2,29,Urban,Data Analyst,50784,0 +103126,Male,59,Bachelors,16,1,48,42,30,4.0,3,95,Urban,ML Engineer,28103,0 +103127,Male,23,High School,11,36,30,52,46,1.0,5,37,Semi-Urban,Data Analyst,36731,0 +103128,Female,26,Diploma,17,61,37,49,87,2.0,1,78,Rural,Data Analyst,101810,0 +103129,Male,32,Masters,9,5,75,40,54,8.0,1,90,Rural,Data Analyst,80388,0 +103130,Male,32,PhD,8,79,3,84,9,2.0,3,63,Urban,Manager,35885,0 +103131,Female,44,Bachelors,2,93,5,91,4,1.0,6,71,Rural,ML Engineer,101849,1 +103132,Male,27,Masters,7,70,98,24,99,4.0,3,99,Urban,Data Analyst,53830,1 +103133,Female,44,Bachelors,6,93,68,81,77,0.0,0,3,Rural,ML Engineer,113020,1 +103134,Female,32,Diploma,4,80,86,85,64,1.0,1,79,Urban,Software Engineer,146918,1 +103135,Male,57,Bachelors,16,53,1,16,5,8.0,1,44,Semi-Urban,Data Analyst,43548,0 +103136,Male,50,Masters,17,46,6,66,22,8.0,3,18,Semi-Urban,ML Engineer,32281,0 +103137,Male,23,High School,0,90,75,87,47,1.0,6,47,Urban,Data Analyst,77337,1 +103138,Male,23,Bachelors,0,41,43,0,65,3.0,0,6,Semi-Urban,ML Engineer,81807,0 +103139,Female,55,Bachelors,18,88,61,11,38,4.0,0,93,Semi-Urban,ML Engineer,91330,1 +103140,Male,26,Bachelors,1,76,79,86,94,9.0,6,38,Urban,Software Engineer,32342,1 +103141,Male,40,Diploma,10,25,93,61,56,2.0,3,3,Semi-Urban,Software Engineer,116886,0 +103142,Female,39,Diploma,1,55,22,94,54,0.0,2,27,Urban,HR Executive,67292,0 +103143,Male,40,PhD,11,42,40,74,42,4.0,1,69,Urban,ML Engineer,86677,0 +103144,Male,39,Bachelors,14,67,15,6,40,2.0,4,43,Urban,ML Engineer,50090,0 +103145,Female,21,High School,1,60,21,48,5,6.0,6,60,Semi-Urban,Data Analyst,141524,0 +103146,Female,35,Masters,16,34,25,10,72,4.0,4,10,Rural,Manager,68540,0 +103147,Female,27,High School,10,90,40,19,81,8.0,1,86,Urban,Manager,56321,0 +103148,Male,28,Diploma,13,81,8,79,37,0.0,1,77,Rural,HR Executive,106881,1 +103149,Male,56,Bachelors,19,38,43,28,80,7.0,3,97,Urban,ML Engineer,113526,0 +103150,Male,56,Bachelors,5,36,10,38,0,5.0,1,30,Rural,ML Engineer,47086,0 +103151,Female,59,Diploma,10,83,63,72,25,7.0,0,73,Urban,Manager,111466,1 +103152,Female,59,Bachelors,15,16,91,94,34,5.0,5,15,Rural,HR Executive,80000,0 +103153,Female,56,Masters,3,72,80,74,36,2.0,4,85,Urban,Manager,92243,1 +103154,Male,43,Diploma,6,43,98,48,10,7.0,7,4,Urban,Software Engineer,52508,0 +103155,Female,43,Diploma,8,76,21,1,23,1.0,5,80,Semi-Urban,Manager,132715,0 +103156,Male,21,Masters,1,90,54,57,48,7.0,1,49,Semi-Urban,Software Engineer,112033,1 +103157,Female,44,Masters,6,76,96,15,53,4.0,4,22,Semi-Urban,Data Analyst,54019,0 +103158,Female,45,High School,16,76,0,42,22,6.0,6,49,Urban,ML Engineer,101554,0 +103159,Female,21,High School,16,22,90,76,13,1.0,2,64,Semi-Urban,Software Engineer,69299,1 +103160,Female,25,Bachelors,12,42,56,2,79,2.0,1,17,Urban,ML Engineer,114267,0 +103161,Female,28,Bachelors,14,16,85,3,81,6.0,3,80,Urban,Manager,56334,0 +103162,Female,42,Bachelors,18,30,51,89,61,7.0,4,66,Semi-Urban,Manager,81338,0 +103163,Male,35,PhD,0,78,43,63,95,7.0,7,68,Urban,Data Analyst,24845,1 +103164,Female,31,Diploma,10,5,8,50,54,1.0,6,63,Urban,Data Analyst,21104,0 +103165,Male,42,Masters,11,63,37,76,44,3.0,5,47,Rural,HR Executive,55920,0 +103166,Male,39,Masters,13,92,27,24,60,8.0,1,96,Urban,Manager,122647,1 +103167,Male,29,Bachelors,3,4,72,77,88,5.0,3,80,Urban,HR Executive,44520,0 +103168,Male,24,Bachelors,18,22,12,93,87,8.0,7,2,Semi-Urban,Software Engineer,103864,0 +103169,Male,54,Bachelors,19,1,52,68,14,0.0,2,55,Semi-Urban,Software Engineer,23581,0 +103170,Male,45,Bachelors,6,97,36,58,91,7.0,2,89,Urban,HR Executive,83852,1 +103171,Female,23,High School,11,61,28,21,55,7.0,0,82,Semi-Urban,Software Engineer,46009,0 +103172,Male,31,Bachelors,13,37,48,5,80,3.0,6,78,Semi-Urban,Data Analyst,62385,0 +103173,Male,46,Bachelors,5,91,88,24,32,2.0,3,51,Rural,HR Executive,138681,1 +103174,Female,22,Bachelors,13,69,91,12,29,1.0,3,81,Urban,HR Executive,111914,1 +103175,Male,32,Bachelors,18,26,1,67,50,9.0,7,40,Urban,Data Analyst,69756,0 +103176,Female,57,Masters,0,80,46,22,84,0.0,4,60,Urban,ML Engineer,77650,0 +103177,Female,59,Bachelors,17,75,21,43,96,1.0,0,7,Urban,Data Analyst,70359,0 +103178,Male,40,Bachelors,1,75,25,93,62,1.0,0,96,Urban,Manager,95978,1 +103179,Male,30,Masters,12,73,34,9,7,6.0,2,80,Urban,HR Executive,57251,0 +103180,Female,51,Diploma,10,64,67,45,97,0.0,0,36,Urban,Software Engineer,95285,0 +103181,Other,24,PhD,17,71,61,19,74,1.0,7,7,Semi-Urban,Software Engineer,66757,0 +103182,Male,45,Bachelors,3,94,97,68,21,4.0,0,28,Urban,HR Executive,64200,1 +103183,Female,54,Bachelors,10,55,29,3,21,6.0,0,34,Semi-Urban,Software Engineer,124897,0 +103184,Male,50,Bachelors,15,55,40,46,20,6.0,0,80,Urban,Data Analyst,87690,0 +103185,Male,51,Masters,11,81,25,29,20,1.0,3,66,Semi-Urban,HR Executive,90973,0 +103186,Male,47,Diploma,16,64,74,60,52,8.0,4,75,Urban,ML Engineer,69874,1 +103187,Male,54,High School,1,93,47,96,27,5.0,5,51,Semi-Urban,Data Analyst,91173,1 +103188,Female,53,Masters,6,80,63,27,52,7.0,1,0,Urban,Data Analyst,30630,0 +103189,Male,44,Diploma,19,48,21,81,93,8.0,6,5,Rural,ML Engineer,86159,0 +103190,Male,47,Bachelors,8,4,61,51,56,5.0,5,79,Urban,Software Engineer,41428,0 +103191,Male,43,Bachelors,5,94,19,53,51,9.0,6,45,Urban,ML Engineer,45531,0 +103192,Male,34,High School,16,11,62,47,73,3.0,0,25,Semi-Urban,Manager,110673,0 +103193,Male,24,Bachelors,13,52,64,83,15,1.0,1,47,Urban,Data Analyst,61590,1 +103194,Female,52,Masters,15,24,27,50,82,0.0,1,20,Semi-Urban,HR Executive,106166,0 +103195,Male,32,Masters,16,7,45,38,81,7.0,6,30,Urban,HR Executive,39074,0 +103196,Male,28,Bachelors,5,78,93,7,46,9.0,3,59,Urban,HR Executive,40779,1 +103197,Male,55,Diploma,0,31,64,97,64,4.0,0,77,Semi-Urban,HR Executive,135698,1 +103198,Male,45,Bachelors,10,44,31,4,68,6.0,1,54,Rural,Software Engineer,68824,0 +103199,Female,42,Masters,13,3,39,12,68,1.0,4,86,Rural,Software Engineer,50916,0 +103200,Male,47,Bachelors,9,68,22,53,48,8.0,6,5,Rural,Software Engineer,40097,0 +103201,Male,26,Bachelors,3,13,32,49,45,5.0,2,82,Rural,Software Engineer,21058,0 +103202,Female,44,High School,5,59,33,98,88,2.0,4,31,Urban,HR Executive,68031,0 +103203,Male,33,Diploma,6,87,1,10,22,4.0,1,36,Urban,Software Engineer,123249,0 +103204,Female,55,Bachelors,11,67,75,71,80,5.0,0,14,Semi-Urban,Manager,145525,0 +103205,Male,34,High School,12,1,24,71,21,4.0,7,60,Urban,Software Engineer,114034,0 +103206,Female,29,Bachelors,1,53,84,15,3,7.0,4,39,Urban,Data Analyst,90476,0 +103207,Male,24,Bachelors,11,28,60,54,16,2.0,0,79,Urban,ML Engineer,82899,0 +103208,Female,31,Masters,14,57,89,64,54,0.0,5,80,Semi-Urban,Software Engineer,108616,1 +103209,Male,56,Diploma,7,37,30,21,29,2.0,4,29,Urban,Data Analyst,110136,0 +103210,Male,28,Diploma,3,43,68,69,44,5.0,6,90,Urban,Data Analyst,71192,1 +103211,Female,47,Diploma,5,71,17,77,80,0.0,0,76,Urban,HR Executive,68814,1 +103212,Female,36,Bachelors,10,23,94,75,28,6.0,6,43,Semi-Urban,Software Engineer,126284,0 +103213,Male,52,Bachelors,18,93,63,15,8,2.0,2,88,Rural,HR Executive,101391,1 +103214,Female,39,High School,9,66,46,27,29,9.0,3,96,Urban,HR Executive,48881,0 +103215,Male,27,Bachelors,17,43,56,21,42,4.0,7,53,Semi-Urban,Software Engineer,20547,0 +103216,Male,22,Masters,19,82,80,95,0,7.0,3,84,Urban,Software Engineer,126353,1 +103217,Female,51,Masters,11,42,34,87,18,5.0,5,53,Urban,Data Analyst,124184,0 +103218,Male,30,Masters,13,67,38,23,83,3.0,5,40,Urban,Data Analyst,100423,0 +103219,Female,55,Bachelors,15,6,71,76,86,0.0,5,67,Urban,HR Executive,131184,0 +103220,Female,21,Diploma,8,58,12,19,84,5.0,6,21,Urban,Software Engineer,86757,0 +103221,Female,55,Masters,17,1,74,42,8,0.0,1,18,Urban,Data Analyst,110358,0 +103222,Male,28,High School,1,51,5,26,68,1.0,6,69,Rural,Software Engineer,122145,0 +103223,Female,52,Bachelors,0,65,5,86,77,3.0,3,38,Semi-Urban,Data Analyst,56194,0 +103224,Male,32,Bachelors,3,34,19,11,50,5.0,7,50,Urban,Data Analyst,144579,0 +103225,Female,55,High School,5,19,22,42,62,8.0,5,54,Urban,ML Engineer,22546,0 +103226,Male,22,Bachelors,8,6,9,41,16,1.0,1,74,Urban,ML Engineer,88875,0 +103227,Female,23,Diploma,18,29,28,8,8,3.0,1,22,Urban,Software Engineer,42606,0 +103228,Female,45,High School,7,7,44,0,93,8.0,3,59,Urban,HR Executive,69405,0 +103229,Male,56,PhD,14,51,24,14,89,1.0,3,87,Rural,HR Executive,78320,0 +103230,Female,41,Bachelors,6,70,19,81,97,5.0,2,80,Urban,Data Analyst,80260,1 +103231,Female,25,High School,18,83,22,93,61,5.0,6,35,Urban,Data Analyst,25463,0 +103232,Male,30,Diploma,3,43,53,76,33,1.0,1,3,Urban,HR Executive,30169,0 +103233,Male,46,High School,17,39,90,37,41,2.0,4,75,Urban,Data Analyst,83399,1 +103234,Female,25,High School,14,30,59,40,19,5.0,5,60,Semi-Urban,HR Executive,27187,0 +103235,Male,21,Bachelors,15,55,54,70,73,9.0,4,28,Semi-Urban,ML Engineer,144291,0 +103236,Male,37,Diploma,1,67,7,28,88,5.0,3,43,Rural,Data Analyst,77819,0 +103237,Male,34,Bachelors,2,7,48,5,16,5.0,1,7,Urban,Software Engineer,143895,0 +103238,Male,42,Bachelors,5,63,68,16,34,0.0,4,91,Urban,Manager,103886,1 +103239,Male,31,Masters,15,28,77,55,42,2.0,5,40,Urban,HR Executive,96040,0 +103240,Male,52,Bachelors,1,74,99,83,94,7.0,5,42,Urban,HR Executive,35466,1 +103241,Male,56,Masters,7,35,54,98,54,3.0,5,68,Urban,ML Engineer,21196,1 +103242,Male,32,Bachelors,1,43,95,35,24,0.0,2,8,Rural,Manager,90055,0 +103243,Male,36,High School,11,88,14,51,93,6.0,0,4,Rural,Manager,81455,0 +103244,Female,21,Bachelors,10,35,68,55,59,6.0,2,18,Urban,Software Engineer,94143,0 +103245,Female,56,PhD,7,14,2,63,39,1.0,5,63,Urban,Manager,140159,0 +103246,Male,25,Diploma,2,6,13,61,81,9.0,5,34,Semi-Urban,Software Engineer,140102,0 +103247,Male,23,Bachelors,11,20,55,29,18,1.0,2,29,Semi-Urban,Data Analyst,117644,0 +103248,Other,52,Bachelors,0,96,41,85,71,5.0,2,69,Rural,Data Analyst,142056,1 +103249,Female,36,Masters,11,45,25,59,14,3.0,3,59,Urban,HR Executive,34987,0 +103250,Female,53,Bachelors,12,73,26,44,20,9.0,3,21,Semi-Urban,Data Analyst,42593,0 +103251,Male,40,Bachelors,10,52,81,50,90,5.0,1,12,Semi-Urban,Manager,70670,0 +103252,Male,48,PhD,7,44,54,80,19,8.0,6,77,Urban,HR Executive,79984,1 +103253,Male,42,Bachelors,2,53,16,44,35,9.0,7,5,Urban,HR Executive,136445,0 +103254,Male,24,Bachelors,6,59,8,72,77,8.0,6,45,Semi-Urban,Manager,67109,0 +103255,Female,53,Diploma,14,93,27,33,66,7.0,6,39,Urban,Software Engineer,71951,0 +103256,Male,27,Diploma,18,82,3,32,38,1.0,4,52,Rural,HR Executive,112249,0 +103257,Female,26,Bachelors,5,91,58,46,68,1.0,3,50,Urban,Data Analyst,47223,1 +103258,Male,45,Masters,4,35,74,68,5,8.0,5,57,Rural,Data Analyst,63693,0 +103259,Female,25,Diploma,18,94,63,27,93,4.0,3,28,Urban,Data Analyst,44344,0 +103260,Female,46,Bachelors,2,77,29,40,11,2.0,6,45,Semi-Urban,Data Analyst,73391,0 +103261,Male,30,Bachelors,16,13,85,44,47,0.0,1,13,Urban,HR Executive,79641,0 +103262,Male,25,Bachelors,16,55,65,8,92,5.0,5,64,Semi-Urban,HR Executive,59829,0 +103263,Male,48,PhD,4,81,27,2,18,3.0,7,67,Urban,Software Engineer,37904,0 +103264,Male,30,Bachelors,19,51,16,77,37,7.0,7,58,Urban,Data Analyst,124790,0 +103265,Female,56,Masters,17,73,55,55,14,7.0,3,81,Urban,ML Engineer,99448,1 +103266,Male,37,Diploma,14,29,38,67,64,3.0,7,42,Urban,Manager,137234,0 +103267,Female,44,Masters,9,80,27,0,53,1.0,3,35,Semi-Urban,Manager,52431,0 +103268,Female,31,Bachelors,7,37,72,97,29,9.0,6,99,Urban,ML Engineer,78800,1 +103269,Male,23,High School,12,11,16,35,1,8.0,7,56,Urban,ML Engineer,42237,0 +103270,Male,59,PhD,7,54,66,79,39,9.0,7,44,Semi-Urban,Manager,128033,1 +103271,Male,27,Bachelors,16,48,68,70,49,6.0,5,71,Semi-Urban,ML Engineer,75557,1 +103272,Female,43,Bachelors,9,89,72,84,80,3.0,2,22,Semi-Urban,Software Engineer,137743,1 +103273,Male,30,Diploma,19,67,16,33,9,6.0,4,7,Semi-Urban,Software Engineer,104700,0 +103274,Female,47,Masters,14,8,54,24,66,3.0,1,17,Urban,ML Engineer,145598,0 +103275,Female,57,Diploma,13,39,35,35,47,0.0,2,32,Rural,HR Executive,68294,0 +103276,Male,31,Diploma,7,54,15,73,29,3.0,6,71,Urban,Software Engineer,54060,0 +103277,Other,50,High School,12,35,49,91,59,1.0,6,20,Semi-Urban,Manager,132428,0 +103278,Female,21,Masters,5,88,25,38,71,9.0,1,43,Urban,HR Executive,26325,0 +103279,Male,44,Bachelors,9,95,10,9,71,1.0,3,4,Urban,HR Executive,138616,0 +103280,Male,29,Bachelors,8,16,9,27,95,4.0,4,91,Urban,HR Executive,94674,0 +103281,Male,37,Masters,3,59,95,14,16,7.0,5,57,Rural,Software Engineer,21282,0 +103282,Male,30,Masters,19,32,27,8,2,4.0,4,18,Urban,HR Executive,23561,0 +103283,Female,36,Diploma,13,69,57,75,90,3.0,0,85,Urban,Software Engineer,93244,1 +103284,Male,44,Diploma,17,17,84,1,13,9.0,4,95,Urban,Manager,37603,0 +103285,Male,51,Bachelors,11,29,10,63,71,5.0,3,19,Rural,Manager,23587,0 +103286,Male,51,Bachelors,7,68,76,51,20,0.0,6,87,Urban,ML Engineer,60515,1 +103287,Male,32,Bachelors,9,99,13,35,56,2.0,5,32,Urban,HR Executive,103186,0 +103288,Male,48,Bachelors,15,37,90,97,52,1.0,2,28,Urban,HR Executive,126066,1 +103289,Female,42,Bachelors,9,14,88,89,70,6.0,2,77,Rural,ML Engineer,126159,1 +103290,Female,30,Diploma,12,77,69,97,87,6.0,4,44,Urban,Manager,130994,1 +103291,Male,25,Bachelors,19,19,12,61,61,0.0,0,82,Rural,Data Analyst,99277,0 +103292,Male,51,High School,2,68,83,12,89,8.0,2,33,Urban,Software Engineer,82479,0 +103293,Male,23,Bachelors,14,99,54,19,93,5.0,5,19,Urban,ML Engineer,80899,0 +103294,Male,25,Masters,2,43,21,70,59,8.0,7,84,Urban,Software Engineer,29637,0 +103295,Male,55,Masters,17,52,89,27,90,2.0,1,18,Rural,Manager,118854,0 +103296,Female,23,High School,5,93,11,71,43,0.0,6,75,Urban,ML Engineer,91011,1 +103297,Male,50,High School,4,30,82,20,79,3.0,5,28,Urban,HR Executive,85387,0 +103298,Female,48,Diploma,14,89,29,93,30,3.0,5,77,Urban,Manager,71846,1 +103299,Male,39,Masters,16,52,87,95,71,8.0,7,20,Rural,Software Engineer,144118,1 +103300,Female,59,Masters,4,77,65,16,6,6.0,7,42,Urban,Software Engineer,60195,0 +103301,Female,29,Bachelors,1,99,13,81,83,4.0,6,46,Rural,HR Executive,80097,0 +103302,Other,30,Masters,16,36,69,49,62,4.0,6,74,Urban,Data Analyst,27157,0 +103303,Female,34,High School,12,80,39,41,24,8.0,3,79,Semi-Urban,Manager,62821,0 +103304,Female,47,High School,7,27,97,78,92,0.0,4,60,Urban,Manager,43845,1 +103305,Female,38,High School,10,49,59,58,97,6.0,0,96,Urban,HR Executive,104771,1 +103306,Female,37,High School,4,72,21,4,44,9.0,2,32,Semi-Urban,Manager,87489,0 +103307,Male,38,Masters,11,10,91,17,97,8.0,7,99,Semi-Urban,Software Engineer,54403,0 +103308,Other,59,Bachelors,10,11,67,74,60,3.0,5,73,Urban,HR Executive,30262,0 +103309,Female,53,Bachelors,15,25,1,63,67,9.0,4,4,Rural,Software Engineer,26681,0 +103310,Male,33,Bachelors,8,98,50,65,78,3.0,4,21,Urban,Software Engineer,109761,0 +103311,Male,51,Diploma,2,2,38,50,12,1.0,0,91,Urban,HR Executive,120224,0 +103312,Male,55,Bachelors,12,42,35,23,11,1.0,3,16,Rural,Software Engineer,49363,0 +103313,Male,32,Bachelors,0,4,7,46,40,0.0,0,98,Semi-Urban,Data Analyst,129714,0 +103314,Female,45,Masters,6,80,23,45,38,7.0,7,3,Rural,Manager,41217,0 +103315,Male,39,Masters,4,72,82,61,14,6.0,0,71,Urban,HR Executive,139677,1 +103316,Female,45,Bachelors,6,41,92,17,4,9.0,0,30,Urban,ML Engineer,30812,0 +103317,Male,56,High School,5,18,93,49,5,2.0,7,37,Urban,Software Engineer,122853,0 +103318,Female,51,Bachelors,18,10,49,14,63,5.0,6,65,Semi-Urban,Software Engineer,132809,0 +103319,Male,35,High School,9,39,60,16,95,4.0,6,31,Urban,ML Engineer,46809,0 +103320,Female,38,Bachelors,16,39,79,71,13,5.0,0,32,Urban,Manager,60726,0 +103321,Male,47,Diploma,13,60,86,73,48,1.0,5,13,Rural,HR Executive,123236,0 +103322,Male,47,Diploma,9,28,77,78,34,6.0,3,8,Urban,Data Analyst,63958,0 +103323,Female,36,Bachelors,14,97,91,30,5,5.0,1,99,Semi-Urban,Software Engineer,134223,1 +103324,Male,57,Bachelors,13,15,59,15,94,3.0,6,14,Urban,ML Engineer,115597,0 +103325,Other,38,Diploma,7,8,3,8,38,7.0,4,2,Urban,Software Engineer,135728,0 +103326,Female,28,Bachelors,17,52,14,14,34,3.0,5,85,Semi-Urban,HR Executive,83536,0 +103327,Male,36,Diploma,1,43,35,21,10,6.0,1,47,Urban,HR Executive,73783,0 +103328,Male,47,Diploma,2,51,91,33,64,8.0,1,20,Urban,ML Engineer,115276,0 +103329,Male,57,High School,13,83,4,17,86,6.0,0,23,Urban,ML Engineer,144931,0 +103330,Male,52,Diploma,5,1,71,26,30,7.0,0,50,Rural,Software Engineer,93797,0 +103331,Other,26,High School,2,3,67,71,59,4.0,2,54,Urban,Manager,86152,0 +103332,Female,51,High School,2,6,66,42,67,7.0,1,65,Semi-Urban,Manager,58463,0 +103333,Male,22,PhD,7,90,86,42,32,8.0,5,92,Semi-Urban,HR Executive,78901,1 +103334,Male,29,Bachelors,6,46,70,54,84,0.0,2,15,Urban,Manager,53738,0 +103335,Male,42,Bachelors,9,85,16,64,39,9.0,2,42,Urban,Data Analyst,108771,0 +103336,Male,54,Bachelors,1,18,75,31,69,1.0,0,34,Rural,Software Engineer,136579,0 +103337,Female,57,Masters,18,54,80,34,91,6.0,0,98,Rural,Manager,40758,1 +103338,Male,25,Diploma,2,41,80,90,96,9.0,2,43,Urban,HR Executive,41978,1 +103339,Male,36,Masters,1,82,53,48,9,3.0,2,66,Urban,Manager,64057,1 +103340,Other,42,Masters,14,64,3,65,13,3.0,3,14,Rural,ML Engineer,60307,0 +103341,Female,21,Diploma,14,78,62,66,53,6.0,1,17,Urban,Manager,93388,0 +103342,Female,26,Bachelors,0,37,33,62,91,4.0,6,50,Rural,Data Analyst,114561,0 +103343,Female,32,Masters,19,52,65,54,14,9.0,6,91,Urban,Software Engineer,90493,1 +103344,Female,45,Bachelors,16,18,54,49,70,4.0,2,31,Rural,ML Engineer,144458,0 +103345,Female,47,Bachelors,0,39,27,44,80,6.0,1,54,Urban,HR Executive,88102,0 +103346,Male,30,Bachelors,10,83,93,79,80,6.0,1,22,Urban,Software Engineer,123155,1 +103347,Male,26,Bachelors,16,37,86,14,76,0.0,2,13,Urban,Manager,147070,0 +103348,Female,26,Masters,17,94,56,47,88,3.0,1,35,Urban,Data Analyst,53599,0 +103349,Male,36,Bachelors,9,7,30,0,64,9.0,4,93,Semi-Urban,HR Executive,143263,0 +103350,Male,57,Diploma,15,28,15,84,80,2.0,6,19,Semi-Urban,ML Engineer,28930,0 +103351,Male,38,High School,6,88,94,6,28,1.0,5,34,Rural,ML Engineer,144118,0 +103352,Female,28,High School,3,66,92,32,9,2.0,2,17,Rural,HR Executive,145674,0 +103353,Male,56,Masters,5,92,24,86,13,5.0,3,54,Urban,Data Analyst,64401,1 +103354,Male,56,Bachelors,0,21,42,20,42,7.0,3,43,Rural,Software Engineer,77916,0 +103355,Male,27,Bachelors,13,89,67,81,53,5.0,1,87,Urban,Software Engineer,43694,1 +103356,Male,57,High School,11,84,60,72,74,0.0,3,69,Rural,Software Engineer,74206,1 +103357,Male,43,High School,9,9,54,5,1,9.0,4,3,Urban,Software Engineer,72857,0 +103358,Female,28,Bachelors,2,56,32,66,12,0.0,6,46,Semi-Urban,Data Analyst,115337,0 +103359,Male,43,Bachelors,18,11,52,19,85,7.0,2,5,Urban,HR Executive,141137,0 +103360,Female,26,Bachelors,15,5,92,96,40,0.0,3,20,Rural,ML Engineer,33774,0 +103361,Female,40,Masters,0,42,57,72,64,8.0,4,66,Urban,Manager,38286,0 +103362,Male,47,Bachelors,1,80,11,62,20,6.0,5,44,Semi-Urban,Software Engineer,35947,0 +103363,Male,22,Diploma,4,83,10,50,73,3.0,2,22,Rural,Manager,43029,0 +103364,Female,51,Masters,17,1,27,36,67,5.0,4,54,Rural,ML Engineer,70718,0 +103365,Female,28,Bachelors,4,24,31,2,68,7.0,4,7,Urban,ML Engineer,72360,0 +103366,Female,49,Diploma,11,61,16,69,77,2.0,7,0,Rural,Manager,21444,0 +103367,Female,26,Diploma,7,26,97,39,63,8.0,4,49,Urban,ML Engineer,83320,0 +103368,Female,46,Bachelors,7,14,96,75,25,6.0,7,26,Urban,HR Executive,132468,0 +103369,Male,41,High School,5,6,28,20,51,4.0,0,10,Urban,ML Engineer,52245,0 +103370,Female,49,High School,17,30,5,56,26,0.0,6,57,Semi-Urban,HR Executive,123560,0 +103371,Male,48,Masters,16,78,69,27,70,7.0,6,88,Urban,ML Engineer,81900,1 +103372,Female,46,Bachelors,12,29,69,39,26,1.0,0,40,Rural,ML Engineer,114373,0 +103373,Female,37,PhD,14,27,61,21,19,8.0,5,14,Semi-Urban,Software Engineer,49348,0 +103374,Female,56,High School,14,86,85,28,63,4.0,6,45,Urban,HR Executive,138944,1 +103375,Male,27,Diploma,15,53,23,37,44,5.0,4,69,Semi-Urban,ML Engineer,76800,0 +103376,Female,50,Bachelors,15,76,66,23,73,7.0,7,83,Urban,Manager,126285,1 +103377,Male,38,Bachelors,2,67,63,69,5,0.0,7,84,Rural,Software Engineer,37319,1 +103378,Female,51,Bachelors,7,89,14,22,83,2.0,7,36,Rural,HR Executive,50527,0 +103379,Male,54,Bachelors,1,62,15,76,24,3.0,2,93,Semi-Urban,ML Engineer,72452,1 +103380,Female,41,Masters,8,94,61,36,10,1.0,3,84,Semi-Urban,HR Executive,35661,1 +103381,Male,53,High School,6,85,51,91,78,1.0,4,83,Urban,ML Engineer,82607,1 +103382,Male,42,Masters,7,38,12,12,8,5.0,0,30,Urban,Software Engineer,134447,0 +103383,Male,25,Bachelors,3,80,77,0,88,4.0,3,72,Urban,ML Engineer,73622,0 +103384,Female,56,PhD,7,86,64,63,2,9.0,2,67,Urban,Manager,21685,1 +103385,Male,39,Masters,13,47,62,9,77,8.0,5,81,Semi-Urban,Data Analyst,140275,0 +103386,Female,26,Bachelors,12,83,29,50,33,9.0,7,44,Urban,HR Executive,43977,0 +103387,Male,24,High School,18,63,79,1,75,8.0,0,50,Urban,Software Engineer,34441,0 +103388,Female,32,Bachelors,17,79,97,90,64,0.0,6,35,Urban,HR Executive,65836,1 +103389,Female,22,Masters,1,55,24,81,19,5.0,0,34,Urban,HR Executive,86638,0 +103390,Other,51,Bachelors,2,19,31,52,96,2.0,5,82,Urban,ML Engineer,28100,0 +103391,Male,46,High School,13,4,7,41,25,4.0,4,3,Rural,Manager,101467,0 +103392,Female,24,PhD,12,69,27,8,70,6.0,2,21,Semi-Urban,HR Executive,89201,0 +103393,Male,53,High School,7,24,45,21,73,9.0,3,40,Semi-Urban,Manager,55150,0 +103394,Male,45,Diploma,18,12,73,80,92,1.0,6,1,Urban,ML Engineer,144843,0 +103395,Female,30,Masters,11,93,36,97,71,0.0,3,54,Urban,Software Engineer,148211,1 +103396,Male,58,High School,5,82,80,85,39,0.0,2,16,Urban,Manager,38157,1 +103397,Male,32,Bachelors,13,4,63,77,22,2.0,0,12,Rural,ML Engineer,125350,0 +103398,Male,32,PhD,13,54,20,12,70,6.0,1,92,Rural,Manager,117759,0 +103399,Female,39,Masters,12,45,95,68,49,4.0,7,9,Urban,Manager,42569,0 +103400,Other,22,Bachelors,5,45,2,40,16,9.0,4,49,Semi-Urban,Manager,83281,0 +103401,Male,55,Masters,10,96,37,64,9,2.0,6,15,Urban,HR Executive,68737,0 +103402,Male,59,Bachelors,4,90,49,85,41,9.0,4,6,Urban,Software Engineer,96183,0 +103403,Female,49,High School,12,51,33,91,9,8.0,0,31,Rural,HR Executive,54140,0 +103404,Male,41,Bachelors,14,48,21,74,71,2.0,7,46,Semi-Urban,Data Analyst,138049,0 +103405,Male,52,Diploma,15,94,67,35,54,7.0,3,63,Urban,Manager,42193,1 +103406,Male,28,Masters,12,33,92,47,7,5.0,6,9,Rural,Data Analyst,91193,0 +103407,Male,44,High School,11,34,60,5,31,1.0,0,53,Rural,Software Engineer,141220,0 +103408,Female,46,Bachelors,15,39,43,17,78,5.0,4,71,Urban,HR Executive,86627,0 +103409,Female,25,Bachelors,8,39,76,78,77,7.0,1,42,Urban,HR Executive,98540,0 +103410,Female,55,Bachelors,0,84,33,69,39,7.0,3,12,Semi-Urban,Data Analyst,28635,0 +103411,Female,24,Diploma,6,17,81,32,94,6.0,0,75,Semi-Urban,Data Analyst,92251,0 +103412,Female,41,Diploma,12,96,15,97,51,4.0,5,36,Semi-Urban,HR Executive,24146,1 +103413,Female,37,Masters,6,91,81,0,22,6.0,1,0,Semi-Urban,Data Analyst,33539,0 +103414,Male,22,Bachelors,9,14,46,19,19,7.0,3,66,Rural,Software Engineer,37259,0 +103415,Male,57,Bachelors,1,72,48,71,60,0.0,5,50,Urban,Software Engineer,129619,1 +103416,Male,35,Diploma,1,97,77,98,92,2.0,0,99,Urban,Software Engineer,46083,1 +103417,Female,28,Bachelors,17,9,80,39,85,9.0,6,76,Urban,HR Executive,130746,0 +103418,Male,23,Masters,14,61,12,0,12,0.0,6,56,Urban,HR Executive,145415,0 +103419,Male,31,Bachelors,6,81,10,7,23,3.0,1,67,Urban,ML Engineer,97131,0 +103420,Male,56,Diploma,14,21,45,76,26,7.0,4,14,Semi-Urban,ML Engineer,67729,0 +103421,Male,34,Bachelors,3,0,17,94,30,1.0,2,7,Semi-Urban,HR Executive,56114,0 +103422,Other,57,Diploma,13,61,49,61,33,2.0,1,8,Rural,Data Analyst,133884,0 +103423,Male,37,Bachelors,10,76,87,85,93,9.0,0,60,Urban,ML Engineer,71067,1 +103424,Other,57,Bachelors,6,21,16,3,60,2.0,3,90,Urban,Data Analyst,140314,0 +103425,Female,49,Diploma,7,46,36,89,80,6.0,2,2,Urban,Manager,63950,0 +103426,Female,28,High School,10,43,27,67,36,4.0,4,9,Semi-Urban,Data Analyst,124474,0 +103427,Male,26,Masters,19,81,2,48,34,8.0,4,20,Urban,HR Executive,111966,0 +103428,Male,40,Diploma,14,67,33,72,84,7.0,2,83,Urban,Data Analyst,80041,1 +103429,Other,24,Bachelors,1,55,6,96,52,3.0,7,39,Urban,Software Engineer,94860,0 +103430,Female,41,Bachelors,13,29,59,58,39,7.0,2,88,Semi-Urban,ML Engineer,46209,0 +103431,Male,45,Bachelors,3,30,36,22,74,6.0,6,24,Urban,Manager,59407,0 +103432,Female,53,Bachelors,2,56,13,22,92,7.0,0,16,Urban,Software Engineer,116094,0 +103433,Male,29,Diploma,5,83,86,56,30,5.0,7,74,Urban,ML Engineer,107714,1 +103434,Female,32,High School,1,80,48,62,57,8.0,1,6,Semi-Urban,ML Engineer,135388,0 +103435,Male,37,Bachelors,12,26,35,3,71,4.0,7,80,Urban,Manager,102872,0 +103436,Male,54,High School,2,34,42,18,37,7.0,2,26,Urban,Manager,50104,0 +103437,Male,34,Diploma,0,77,7,65,24,9.0,4,5,Urban,Data Analyst,86819,0 +103438,Male,45,Diploma,13,64,61,54,39,0.0,1,93,Urban,Manager,64158,1 +103439,Male,35,High School,12,40,61,37,80,0.0,7,35,Semi-Urban,Data Analyst,96056,0 +103440,Male,43,Bachelors,10,3,74,93,39,5.0,1,31,Rural,Manager,149552,0 +103441,Female,28,Bachelors,14,44,5,50,61,6.0,5,4,Semi-Urban,Data Analyst,37659,0 +103442,Male,23,Bachelors,0,87,30,33,33,9.0,7,91,Urban,ML Engineer,134532,1 +103443,Male,56,Bachelors,4,52,76,93,8,1.0,7,42,Rural,Software Engineer,44789,1 +103444,Female,59,Bachelors,15,81,46,51,52,1.0,0,40,Urban,Manager,108801,0 +103445,Male,34,Bachelors,10,56,48,91,79,7.0,4,7,Rural,ML Engineer,77155,0 +103446,Male,28,Bachelors,17,2,26,23,35,8.0,6,3,Semi-Urban,ML Engineer,144434,0 +103447,Male,32,Masters,1,66,92,12,45,2.0,1,5,Rural,HR Executive,126917,0 +103448,Female,47,High School,16,52,63,27,13,6.0,0,56,Urban,Software Engineer,56552,0 +103449,Male,32,Masters,0,55,24,85,49,4.0,3,70,Urban,ML Engineer,33730,0 +103450,Female,29,Bachelors,11,9,25,56,76,9.0,2,25,Rural,Data Analyst,60457,0 +103451,Male,57,Bachelors,19,94,5,36,49,5.0,4,28,Urban,HR Executive,20432,0 +103452,Male,25,Bachelors,18,29,75,2,98,3.0,7,9,Rural,ML Engineer,26265,0 +103453,Other,26,High School,14,50,77,85,70,3.0,6,72,Urban,Data Analyst,121883,1 +103454,Female,54,Diploma,17,25,3,86,47,0.0,2,42,Rural,Manager,71523,0 +103455,Male,23,Bachelors,5,35,76,84,85,7.0,7,48,Urban,HR Executive,61041,1 +103456,Other,35,PhD,13,78,88,71,15,4.0,1,22,Rural,HR Executive,75675,1 +103457,Female,48,Bachelors,6,92,85,15,48,2.0,0,20,Urban,ML Engineer,120133,0 +103458,Male,35,Bachelors,19,42,51,1,18,9.0,5,94,Urban,Data Analyst,144000,0 +103459,Male,47,Bachelors,17,24,93,34,54,7.0,6,29,Urban,Data Analyst,70979,0 +103460,Male,41,Bachelors,10,10,26,87,1,1.0,7,96,Rural,Manager,124871,0 +103461,Female,39,Bachelors,6,67,31,34,27,9.0,2,96,Urban,Software Engineer,120236,0 +103462,Male,21,Diploma,15,1,34,77,58,0.0,3,16,Rural,Software Engineer,114084,0 +103463,Female,27,Bachelors,1,3,36,34,58,2.0,3,15,Urban,Software Engineer,76661,0 +103464,Male,38,Diploma,17,91,74,1,4,9.0,3,61,Urban,Data Analyst,146389,0 +103465,Male,26,Masters,2,6,3,25,39,8.0,0,48,Semi-Urban,Manager,29537,0 +103466,Male,44,Diploma,12,79,92,79,29,2.0,0,91,Urban,Data Analyst,35773,1 +103467,Male,51,High School,1,40,7,1,47,2.0,6,82,Urban,ML Engineer,105827,0 +103468,Female,47,Bachelors,12,58,54,79,62,2.0,1,3,Urban,Manager,95062,0 +103469,Male,33,High School,4,61,39,34,33,9.0,5,92,Urban,HR Executive,103896,0 +103470,Male,36,Masters,13,41,83,7,59,8.0,4,97,Urban,ML Engineer,38623,0 +103471,Male,31,Diploma,7,70,15,25,82,7.0,0,61,Urban,Data Analyst,135936,0 +103472,Female,39,Bachelors,10,82,83,72,48,8.0,3,30,Urban,Data Analyst,29411,1 +103473,Female,29,Bachelors,9,99,83,29,82,4.0,1,87,Urban,Software Engineer,95876,1 +103474,Male,37,Bachelors,13,44,27,33,29,1.0,3,15,Urban,Software Engineer,32976,0 +103475,Male,56,PhD,8,14,59,5,97,4.0,0,55,Urban,ML Engineer,130669,0 +103476,Female,22,Bachelors,13,57,51,19,39,9.0,7,25,Rural,ML Engineer,50117,0 +103477,Female,47,Masters,11,83,75,41,4,2.0,2,51,Rural,Software Engineer,92776,1 +103478,Male,55,Masters,4,55,95,99,42,9.0,3,93,Semi-Urban,Manager,49091,1 +103479,Male,46,High School,11,88,77,13,17,6.0,4,72,Rural,HR Executive,149275,1 +103480,Male,42,Bachelors,7,53,37,16,44,6.0,2,72,Rural,HR Executive,102169,0 +103481,Male,30,High School,4,27,9,82,58,7.0,2,15,Urban,ML Engineer,51924,0 +103482,Male,34,Bachelors,16,50,19,60,0,3.0,5,53,Rural,Manager,114634,0 +103483,Male,30,PhD,1,11,23,90,37,7.0,5,32,Semi-Urban,HR Executive,85334,0 +103484,Female,41,Masters,12,51,91,9,18,9.0,6,56,Urban,Data Analyst,112544,0 +103485,Other,41,Diploma,10,99,23,15,83,5.0,2,89,Urban,Data Analyst,122235,0 +103486,Male,28,Masters,12,51,4,0,22,6.0,5,73,Semi-Urban,ML Engineer,49076,0 +103487,Female,49,Diploma,2,53,16,81,39,9.0,0,65,Urban,ML Engineer,117780,0 +103488,Female,45,Diploma,17,61,15,26,82,2.0,4,0,Urban,Data Analyst,75042,0 +103489,Male,35,Bachelors,13,12,90,8,88,8.0,4,35,Urban,ML Engineer,121651,0 +103490,Female,29,Bachelors,12,19,9,53,63,1.0,2,36,Rural,Software Engineer,94993,0 +103491,Male,43,Bachelors,19,67,31,86,84,3.0,5,25,Rural,Software Engineer,21578,0 +103492,Male,31,Bachelors,9,32,47,70,68,5.0,7,71,Semi-Urban,HR Executive,148077,0 +103493,Male,35,Bachelors,0,94,58,55,27,3.0,0,33,Urban,Data Analyst,115619,1 +103494,Male,26,Bachelors,19,11,61,38,20,1.0,6,33,Rural,HR Executive,69130,0 +103495,Female,31,Diploma,8,95,8,14,33,1.0,3,34,Rural,ML Engineer,119117,0 +103496,Other,54,Bachelors,4,73,87,39,39,8.0,0,70,Semi-Urban,Manager,115696,1 +103497,Male,56,Masters,6,46,32,70,68,5.0,1,80,Rural,Software Engineer,147705,0 +103498,Female,31,PhD,6,26,96,29,13,3.0,4,82,Semi-Urban,HR Executive,104442,0 +103499,Male,21,High School,9,72,70,37,95,5.0,3,98,Urban,Data Analyst,63512,1 +103500,Male,39,Diploma,18,49,60,85,92,3.0,2,84,Semi-Urban,HR Executive,60887,1 +103501,Female,45,Bachelors,18,45,8,40,80,2.0,2,39,Urban,Data Analyst,66754,0 +103502,Female,57,High School,2,15,44,62,50,5.0,4,77,Rural,ML Engineer,143303,0 +103503,Male,55,High School,17,61,71,86,1,1.0,3,23,Urban,HR Executive,47822,1 +103504,Female,59,Masters,14,76,13,37,53,5.0,0,0,Urban,HR Executive,137641,0 +103505,Male,22,Bachelors,8,18,70,52,72,6.0,5,69,Urban,Manager,82341,0 +103506,Male,56,Masters,8,54,11,32,31,0.0,6,18,Semi-Urban,HR Executive,80251,0 +103507,Male,53,Bachelors,6,54,5,2,92,5.0,7,92,Urban,HR Executive,98092,0 +103508,Female,21,High School,10,93,87,1,85,5.0,6,71,Semi-Urban,HR Executive,86085,1 +103509,Male,34,Diploma,8,63,91,27,10,2.0,3,63,Urban,Software Engineer,71458,1 +103510,Female,44,High School,16,3,32,43,94,9.0,2,15,Semi-Urban,ML Engineer,50400,0 +103511,Female,46,Diploma,8,47,20,33,90,1.0,4,80,Urban,Manager,128238,0 +103512,Female,35,Bachelors,8,3,48,37,71,4.0,6,27,Rural,Manager,77405,0 +103513,Female,48,Bachelors,6,12,1,26,24,5.0,2,63,Rural,Manager,72635,0 +103514,Male,56,Masters,19,92,10,89,85,5.0,2,90,Urban,Data Analyst,116014,1 +103515,Male,48,Bachelors,17,23,85,13,47,3.0,6,75,Urban,Data Analyst,133841,0 +103516,Female,38,Masters,1,61,94,71,86,2.0,3,19,Urban,Manager,59242,1 +103517,Male,36,High School,6,60,54,28,1,2.0,3,30,Urban,Software Engineer,146711,0 +103518,Male,29,High School,8,49,84,49,21,6.0,3,83,Rural,Manager,77967,1 +103519,Male,38,Masters,0,61,75,94,81,5.0,5,69,Urban,HR Executive,57959,1 +103520,Male,21,Diploma,15,98,89,7,34,4.0,7,14,Urban,ML Engineer,138855,0 +103521,Female,49,Bachelors,1,50,21,24,32,0.0,2,29,Semi-Urban,HR Executive,58956,0 +103522,Male,46,Masters,18,87,83,0,40,5.0,7,5,Urban,Data Analyst,93447,0 +103523,Male,58,Masters,3,11,22,77,75,3.0,6,21,Urban,HR Executive,144798,0 +103524,Male,31,High School,4,11,54,28,12,6.0,4,79,Urban,ML Engineer,108251,0 +103525,Male,30,Masters,3,85,46,1,58,7.0,3,46,Urban,HR Executive,29140,0 +103526,Female,29,Bachelors,4,82,71,78,15,1.0,0,16,Semi-Urban,HR Executive,35163,1 +103527,Male,24,Masters,12,5,68,22,2,1.0,7,1,Rural,HR Executive,58011,0 +103528,Male,45,Diploma,3,63,22,35,60,2.0,7,7,Urban,Software Engineer,31300,0 +103529,Female,41,Bachelors,9,73,40,28,43,4.0,4,61,Rural,HR Executive,22599,0 +103530,Female,45,Masters,11,56,85,64,97,2.0,2,10,Urban,Manager,62417,0 +103531,Female,49,Diploma,6,54,90,58,44,5.0,4,30,Urban,Manager,124279,0 +103532,Male,46,Masters,1,88,87,23,77,2.0,2,77,Rural,Software Engineer,24484,1 +103533,Male,33,Masters,13,66,77,68,2,8.0,5,58,Rural,Data Analyst,65806,1 +103534,Female,21,Bachelors,2,17,75,35,97,5.0,3,80,Rural,Data Analyst,132831,0 +103535,Other,57,Masters,15,93,74,7,79,9.0,7,20,Urban,Manager,57665,0 +103536,Male,50,Bachelors,11,73,55,62,84,5.0,1,75,Urban,Manager,38364,1 +103537,Male,25,Masters,9,43,17,85,21,3.0,6,3,Urban,Data Analyst,36884,0 +103538,Male,50,Bachelors,4,45,62,82,0,6.0,3,21,Semi-Urban,ML Engineer,35154,0 +103539,Male,41,Bachelors,2,89,50,56,43,9.0,5,87,Urban,ML Engineer,47529,1 +103540,Male,40,Masters,9,16,93,2,78,9.0,5,16,Urban,HR Executive,55946,0 +103541,Male,21,Diploma,2,47,8,28,50,4.0,4,28,Rural,Manager,32890,0 +103542,Female,23,Diploma,5,3,32,24,78,9.0,3,82,Urban,Software Engineer,139148,0 +103543,Female,30,Bachelors,18,38,16,84,89,8.0,6,96,Semi-Urban,Data Analyst,108525,0 +103544,Male,34,Bachelors,4,15,43,22,63,4.0,5,49,Rural,Data Analyst,103035,0 +103545,Male,36,Diploma,14,71,10,65,4,6.0,5,94,Urban,Software Engineer,51289,1 +103546,Other,55,Diploma,13,95,58,51,19,0.0,1,27,Semi-Urban,Data Analyst,120574,0 +103547,Female,48,Diploma,0,70,93,99,67,6.0,5,61,Rural,ML Engineer,137923,1 +103548,Female,46,Bachelors,17,59,47,64,81,6.0,2,99,Urban,Software Engineer,43135,1 +103549,Male,48,High School,4,66,93,52,70,9.0,1,54,Semi-Urban,Data Analyst,73515,1 +103550,Female,34,Bachelors,17,42,71,25,65,3.0,6,13,Urban,Software Engineer,81149,0 +103551,Male,50,Diploma,9,58,94,31,38,0.0,7,66,Rural,Data Analyst,118891,1 +103552,Female,46,Diploma,8,32,16,13,18,4.0,6,65,Semi-Urban,Data Analyst,127719,0 +103553,Female,35,Bachelors,3,11,73,29,94,6.0,1,35,Urban,Manager,45122,0 +103554,Male,25,Masters,15,55,47,28,37,0.0,6,85,Semi-Urban,ML Engineer,65649,0 +103555,Other,24,Masters,4,43,65,22,91,2.0,4,62,Urban,Software Engineer,41914,0 +103556,Male,39,High School,15,62,48,89,67,8.0,3,49,Urban,Manager,69150,1 +103557,Male,36,Masters,8,74,96,56,96,6.0,6,43,Urban,Data Analyst,134511,1 +103558,Male,43,High School,3,54,42,84,92,8.0,6,7,Semi-Urban,Data Analyst,123293,0 +103559,Male,50,Bachelors,2,91,8,13,75,4.0,7,79,Urban,ML Engineer,25217,0 +103560,Male,37,Diploma,4,22,6,94,22,2.0,3,8,Rural,HR Executive,40395,0 +103561,Male,47,Diploma,10,21,81,30,40,3.0,3,75,Semi-Urban,Manager,147140,0 +103562,Male,56,High School,8,89,73,33,35,6.0,4,31,Urban,Manager,111695,0 +103563,Male,31,Masters,3,37,30,15,94,7.0,2,52,Semi-Urban,HR Executive,47947,0 +103564,Female,32,Diploma,13,70,0,87,63,2.0,0,66,Urban,Data Analyst,25496,0 +103565,Male,59,Bachelors,16,21,78,99,43,8.0,3,57,Rural,HR Executive,67427,1 +103566,Male,37,High School,9,89,83,66,13,0.0,5,57,Urban,HR Executive,23108,1 +103567,Female,33,Bachelors,0,59,19,14,93,6.0,3,97,Rural,Software Engineer,114630,0 +103568,Male,39,Masters,4,23,11,62,20,2.0,0,62,Semi-Urban,Data Analyst,107086,0 +103569,Male,33,High School,7,48,36,72,40,7.0,2,32,Urban,Software Engineer,123932,0 +103570,Male,25,Bachelors,15,0,59,14,90,0.0,1,10,Urban,Data Analyst,41879,0 +103571,Female,53,Bachelors,10,99,28,7,67,6.0,1,94,Urban,ML Engineer,40298,0 +103572,Male,55,Masters,12,26,28,22,96,9.0,0,20,Urban,Software Engineer,72073,0 +103573,Male,42,Bachelors,3,66,12,72,89,6.0,4,79,Urban,Manager,103090,0 +103574,Female,37,High School,13,38,31,41,99,3.0,3,57,Urban,HR Executive,128426,0 +103575,Male,58,High School,5,50,73,97,62,7.0,6,51,Rural,HR Executive,87846,1 +103576,Female,37,Bachelors,2,58,1,57,72,2.0,7,65,Semi-Urban,Software Engineer,72382,0 +103577,Male,51,Masters,2,50,77,32,50,3.0,6,21,Urban,Data Analyst,147864,0 +103578,Male,49,Masters,15,9,97,96,35,9.0,1,7,Urban,Software Engineer,75040,0 +103579,Female,53,PhD,4,84,99,37,35,9.0,7,82,Urban,ML Engineer,104456,1 +103580,Male,21,High School,2,62,43,36,95,6.0,5,36,Urban,HR Executive,40537,0 +103581,Male,35,Masters,18,68,99,54,89,8.0,4,80,Urban,Software Engineer,149510,1 +103582,Male,57,Masters,4,0,81,72,65,9.0,0,42,Urban,HR Executive,113357,0 +103583,Female,43,Masters,1,14,76,23,96,3.0,3,67,Rural,Data Analyst,89752,0 +103584,Male,44,Bachelors,14,71,9,63,18,5.0,6,44,Urban,HR Executive,23812,0 +103585,Other,43,Masters,1,22,29,63,61,8.0,2,50,Urban,HR Executive,101655,0 +103586,Female,59,High School,3,43,63,68,55,6.0,1,64,Rural,HR Executive,118180,0 +103587,Male,33,Masters,15,88,20,64,33,0.0,3,66,Semi-Urban,ML Engineer,119153,1 +103588,Male,41,Masters,1,44,72,76,58,6.0,3,16,Semi-Urban,Manager,73107,0 +103589,Male,49,High School,5,9,63,3,56,4.0,4,96,Urban,ML Engineer,73897,0 +103590,Male,46,Masters,2,71,29,74,56,7.0,7,3,Urban,Manager,109293,0 +103591,Female,52,Bachelors,18,32,3,51,6,2.0,0,81,Urban,Data Analyst,45598,0 +103592,Male,53,Bachelors,1,57,98,6,77,9.0,3,16,Urban,Manager,113771,0 +103593,Other,49,Bachelors,0,22,44,22,59,0.0,5,57,Urban,Software Engineer,100746,0 +103594,Male,49,Bachelors,13,61,26,61,37,2.0,2,70,Rural,Data Analyst,72305,0 +103595,Female,54,Bachelors,1,31,40,53,29,6.0,7,5,Urban,Software Engineer,129984,0 +103596,Male,41,Masters,9,92,39,15,12,0.0,3,40,Semi-Urban,Software Engineer,116151,0 +103597,Male,34,Bachelors,19,95,5,40,92,5.0,4,68,Semi-Urban,ML Engineer,61629,0 +103598,Female,37,Bachelors,11,12,88,48,93,2.0,3,12,Urban,Data Analyst,20071,0 +103599,Female,39,Bachelors,2,48,34,38,22,9.0,5,57,Semi-Urban,HR Executive,82326,0 +103600,Female,28,High School,10,87,59,87,36,3.0,3,74,Urban,Manager,146708,1 +103601,Other,37,High School,5,5,17,42,97,1.0,5,81,Semi-Urban,Software Engineer,98777,0 +103602,Female,32,Masters,3,87,33,70,79,2.0,4,32,Rural,HR Executive,128398,0 +103603,Male,23,Diploma,4,53,28,90,60,3.0,0,93,Semi-Urban,Data Analyst,121640,1 +103604,Male,32,Masters,12,78,93,21,36,1.0,6,46,Rural,HR Executive,95062,1 +103605,Male,59,Bachelors,10,99,24,38,67,4.0,1,9,Urban,HR Executive,35942,0 +103606,Male,30,Bachelors,12,45,4,28,68,9.0,3,47,Urban,ML Engineer,56319,0 +103607,Female,34,High School,3,29,57,96,46,8.0,5,72,Rural,Data Analyst,147970,1 +103608,Female,31,Masters,13,83,19,41,63,5.0,0,98,Semi-Urban,Software Engineer,112453,1 +103609,Female,22,PhD,11,20,97,46,56,8.0,2,88,Urban,ML Engineer,48936,1 +103610,Female,24,Diploma,3,87,50,83,49,7.0,7,88,Urban,ML Engineer,77949,1 +103611,Female,45,Masters,18,26,29,98,15,4.0,0,92,Urban,HR Executive,107292,1 +103612,Male,46,High School,14,42,12,62,55,7.0,1,33,Semi-Urban,ML Engineer,53473,0 +103613,Female,49,Masters,18,52,95,72,3,5.0,3,82,Rural,HR Executive,85272,1 +103614,Female,41,Bachelors,19,65,76,50,98,9.0,1,4,Urban,Software Engineer,39482,0 +103615,Female,57,Diploma,8,33,53,17,65,1.0,3,44,Rural,ML Engineer,139906,0 +103616,Female,49,Bachelors,3,76,23,27,8,3.0,3,67,Urban,Software Engineer,36120,0 +103617,Male,59,Masters,9,26,45,32,86,1.0,7,52,Semi-Urban,ML Engineer,50056,0 +103618,Female,43,High School,19,75,40,95,21,7.0,3,26,Rural,ML Engineer,88697,0 +103619,Female,51,Bachelors,19,63,88,96,17,6.0,4,38,Urban,Software Engineer,96750,1 +103620,Male,48,Masters,13,7,44,42,83,3.0,3,30,Urban,Data Analyst,125768,0 +103621,Male,29,Bachelors,12,21,59,57,81,1.0,1,59,Urban,Data Analyst,49212,0 +103622,Male,27,High School,11,86,6,53,48,7.0,3,19,Rural,ML Engineer,66600,0 +103623,Male,50,Bachelors,13,71,8,62,28,8.0,7,54,Semi-Urban,Software Engineer,77795,0 +103624,Female,22,High School,13,75,50,38,64,3.0,4,43,Semi-Urban,Software Engineer,61762,0 +103625,Male,44,High School,12,9,48,31,27,0.0,2,80,Urban,Manager,75338,0 +103626,Male,41,Diploma,14,16,82,58,18,6.0,4,92,Urban,Data Analyst,67381,1 +103627,Male,38,Masters,12,46,34,96,93,9.0,1,85,Semi-Urban,HR Executive,49480,1 +103628,Male,30,Bachelors,14,39,99,81,60,9.0,3,9,Urban,HR Executive,27246,0 +103629,Male,23,High School,12,35,20,54,47,4.0,7,42,Rural,ML Engineer,58625,0 +103630,Other,35,Masters,14,18,64,54,83,9.0,1,45,Urban,ML Engineer,133658,0 +103631,Other,58,Bachelors,1,67,14,46,53,2.0,1,87,Rural,Manager,46037,0 +103632,Female,36,Masters,1,66,18,29,85,0.0,6,23,Semi-Urban,Manager,100670,0 +103633,Male,46,Bachelors,17,0,19,32,25,3.0,5,74,Urban,Manager,128889,0 +103634,Female,54,Diploma,18,98,25,82,50,6.0,6,2,Urban,HR Executive,143079,0 +103635,Female,21,Masters,13,74,76,69,2,2.0,0,50,Urban,ML Engineer,134279,1 +103636,Female,39,High School,15,32,27,50,32,8.0,6,38,Semi-Urban,HR Executive,24997,0 +103637,Male,32,Bachelors,2,4,70,10,15,6.0,2,49,Urban,HR Executive,46934,0 +103638,Male,59,Bachelors,14,55,86,28,28,4.0,0,17,Urban,ML Engineer,71880,0 +103639,Male,30,Masters,11,52,90,99,71,6.0,7,95,Rural,Software Engineer,54676,1 +103640,Male,44,Bachelors,1,21,55,62,62,7.0,0,16,Urban,Software Engineer,118580,0 +103641,Male,32,Bachelors,9,60,43,74,36,7.0,4,97,Rural,ML Engineer,69014,1 +103642,Male,44,PhD,4,58,10,28,11,2.0,2,75,Semi-Urban,Manager,135422,0 +103643,Female,50,Masters,15,90,0,65,98,2.0,3,12,Rural,Software Engineer,101041,0 +103644,Female,26,Diploma,17,81,88,76,6,8.0,7,77,Rural,HR Executive,90458,1 +103645,Female,49,Bachelors,16,44,62,43,36,3.0,2,63,Urban,Manager,96147,0 +103646,Female,23,Bachelors,15,11,56,2,53,9.0,4,30,Urban,HR Executive,120108,0 +103647,Male,57,Masters,5,3,42,1,65,4.0,5,22,Rural,Manager,114935,0 +103648,Male,49,Diploma,8,8,91,62,92,1.0,0,10,Rural,Data Analyst,60488,0 +103649,Other,26,High School,9,75,20,37,57,3.0,6,60,Semi-Urban,Manager,100742,0 +103650,Other,52,Masters,10,39,91,61,6,2.0,0,11,Urban,Data Analyst,42137,0 +103651,Female,49,High School,19,30,48,87,40,6.0,2,81,Urban,Data Analyst,137374,1 +103652,Male,24,Diploma,11,20,82,81,74,5.0,2,38,Urban,Software Engineer,124529,0 +103653,Male,44,Bachelors,4,71,36,47,29,2.0,4,74,Urban,ML Engineer,41828,0 +103654,Female,49,Bachelors,15,14,71,86,65,6.0,7,10,Urban,Data Analyst,36635,0 +103655,Male,34,Masters,18,56,23,28,72,2.0,7,22,Urban,HR Executive,97472,0 +103656,Other,30,Bachelors,5,23,35,62,14,2.0,1,42,Urban,Manager,27767,0 +103657,Female,31,Diploma,3,54,61,9,8,1.0,3,95,Urban,HR Executive,143324,0 +103658,Male,55,Diploma,11,88,53,93,97,7.0,1,16,Rural,Software Engineer,140780,1 +103659,Male,23,Masters,19,86,20,14,72,8.0,5,51,Urban,Data Analyst,21795,0 +103660,Male,32,Bachelors,2,92,16,75,44,5.0,3,95,Semi-Urban,Data Analyst,129662,1 +103661,Male,35,Bachelors,13,90,40,51,78,3.0,2,38,Rural,Manager,100518,0 +103662,Female,55,Diploma,7,14,6,41,66,3.0,3,41,Rural,Manager,71036,0 +103663,Male,46,Bachelors,18,27,40,44,99,0.0,5,28,Semi-Urban,HR Executive,111914,0 +103664,Male,47,Bachelors,1,5,70,54,56,7.0,4,96,Rural,Data Analyst,20027,0 +103665,Female,32,Bachelors,7,48,21,49,4,2.0,2,52,Semi-Urban,ML Engineer,81168,0 +103666,Male,46,High School,17,97,6,39,7,0.0,6,31,Urban,ML Engineer,79974,0 +103667,Female,39,Masters,17,62,35,20,38,2.0,6,83,Urban,Manager,124215,0 +103668,Male,51,Bachelors,13,1,77,62,78,1.0,3,38,Semi-Urban,Manager,29351,0 +103669,Female,29,Bachelors,1,4,68,2,93,0.0,7,37,Urban,Data Analyst,59427,0 +103670,Female,29,Bachelors,6,54,61,43,14,4.0,3,15,Semi-Urban,Manager,110803,0 +103671,Male,40,Diploma,7,31,22,7,76,4.0,1,95,Urban,HR Executive,99574,0 +103672,Male,44,High School,12,54,65,97,66,3.0,7,34,Urban,ML Engineer,35007,1 +103673,Male,21,Bachelors,1,12,65,70,6,3.0,1,6,Urban,Software Engineer,98577,0 +103674,Male,33,Bachelors,2,76,8,42,67,7.0,3,43,Urban,Data Analyst,61647,0 +103675,Female,38,Bachelors,11,5,77,19,4,8.0,2,5,Urban,Manager,94334,0 +103676,Male,45,Diploma,4,34,74,51,64,1.0,3,23,Rural,Software Engineer,116480,0 +103677,Male,28,Diploma,17,42,41,71,66,3.0,4,85,Semi-Urban,Data Analyst,98548,1 +103678,Female,23,Bachelors,18,78,24,46,70,5.0,3,35,Urban,Data Analyst,128811,0 +103679,Male,47,Diploma,19,76,80,54,12,0.0,5,93,Rural,HR Executive,131312,1 +103680,Male,39,Bachelors,16,23,86,19,80,8.0,5,79,Semi-Urban,HR Executive,126481,0 +103681,Male,30,Bachelors,5,65,47,96,7,3.0,5,2,Urban,Software Engineer,46852,0 +103682,Male,28,Bachelors,3,80,67,20,88,9.0,0,22,Urban,ML Engineer,54232,0 +103683,Male,57,Masters,3,93,93,94,81,2.0,1,22,Urban,Data Analyst,145336,1 +103684,Male,32,Bachelors,0,11,56,39,31,6.0,4,35,Rural,ML Engineer,136177,0 +103685,Male,58,Masters,17,75,77,56,35,5.0,1,45,Urban,Data Analyst,76221,1 +103686,Male,34,Bachelors,4,75,22,67,37,1.0,2,50,Rural,ML Engineer,72571,0 +103687,Male,57,High School,2,9,76,89,49,9.0,5,85,Urban,Software Engineer,137762,1 +103688,Male,29,Bachelors,18,77,92,36,37,8.0,4,22,Urban,ML Engineer,33267,0 +103689,Male,43,Bachelors,12,11,17,90,60,1.0,4,98,Urban,Software Engineer,40790,0 +103690,Other,55,Masters,13,74,36,4,63,6.0,4,63,Urban,Software Engineer,74270,0 +103691,Male,49,High School,17,82,69,88,27,8.0,3,95,Rural,Software Engineer,27033,1 +103692,Male,48,Masters,2,54,7,47,19,0.0,3,40,Urban,HR Executive,57466,0 +103693,Female,31,Bachelors,13,58,83,23,94,2.0,2,72,Semi-Urban,Manager,101420,0 +103694,Male,35,Diploma,5,30,5,30,26,5.0,0,99,Urban,Data Analyst,104897,0 +103695,Female,35,Masters,17,33,16,77,42,6.0,4,92,Urban,Software Engineer,67041,0 +103696,Female,45,Bachelors,19,50,22,46,51,9.0,1,20,Urban,ML Engineer,93462,0 +103697,Male,22,Masters,7,69,40,57,50,4.0,4,38,Semi-Urban,Software Engineer,46695,0 +103698,Female,35,Bachelors,0,44,9,39,62,5.0,7,41,Rural,Software Engineer,75042,0 +103699,Female,37,High School,6,18,9,38,57,7.0,5,1,Semi-Urban,Software Engineer,69409,0 +103700,Female,42,Bachelors,1,80,94,11,31,8.0,0,50,Semi-Urban,Manager,27519,0 +103701,Male,54,Bachelors,12,41,75,28,30,3.0,7,73,Urban,ML Engineer,76612,0 +103702,Male,27,Bachelors,2,11,56,21,20,9.0,4,80,Urban,ML Engineer,102599,0 +103703,Male,55,High School,18,35,32,86,69,7.0,2,29,Semi-Urban,Manager,41911,0 +103704,Other,46,High School,1,67,24,27,54,8.0,5,95,Semi-Urban,HR Executive,135989,0 +103705,Female,22,Masters,2,36,63,17,86,5.0,7,70,Urban,Software Engineer,114141,0 +103706,Male,21,Bachelors,0,64,7,96,33,8.0,1,12,Urban,ML Engineer,94303,0 +103707,Male,30,Masters,9,84,30,6,54,6.0,5,1,Urban,ML Engineer,56220,0 +103708,Male,37,Masters,7,92,54,9,6,1.0,0,65,Rural,HR Executive,55090,0 +103709,Male,23,Bachelors,5,30,53,94,47,1.0,5,15,Urban,ML Engineer,73834,0 +103710,Male,38,Bachelors,17,32,24,73,99,5.0,0,80,Rural,ML Engineer,46554,0 +103711,Female,50,Bachelors,17,8,43,60,15,8.0,2,21,Rural,Software Engineer,135482,0 +103712,Female,41,Bachelors,7,62,81,48,5,1.0,4,49,Rural,Data Analyst,132845,0 +103713,Male,39,Masters,11,95,33,7,61,1.0,7,43,Urban,Data Analyst,132744,0 +103714,Female,53,PhD,0,81,11,3,16,6.0,2,61,Semi-Urban,HR Executive,146829,0 +103715,Male,35,Bachelors,6,26,37,81,26,9.0,4,57,Rural,Software Engineer,129608,0 +103716,Male,22,Diploma,1,75,33,22,88,0.0,4,33,Rural,HR Executive,69531,0 +103717,Female,34,Bachelors,1,94,84,28,18,5.0,0,83,Urban,ML Engineer,23949,1 +103718,Male,56,Masters,19,46,22,36,61,8.0,5,4,Semi-Urban,ML Engineer,40881,0 +103719,Female,42,Masters,17,14,78,12,29,7.0,3,92,Urban,Software Engineer,109437,0 +103720,Male,51,Masters,7,54,16,67,19,0.0,3,58,Semi-Urban,HR Executive,77440,0 +103721,Male,31,Diploma,9,96,68,62,57,5.0,4,54,Urban,HR Executive,95691,1 +103722,Male,58,Bachelors,6,72,71,65,96,7.0,0,13,Urban,Data Analyst,88583,0 +103723,Male,45,Bachelors,0,1,69,30,68,4.0,0,59,Rural,Manager,78486,0 +103724,Male,23,Bachelors,2,69,89,39,84,3.0,7,19,Semi-Urban,ML Engineer,140554,0 +103725,Male,49,Bachelors,15,38,30,70,80,6.0,3,39,Urban,HR Executive,140920,0 +103726,Male,34,Diploma,8,90,36,76,94,0.0,3,74,Rural,ML Engineer,21081,1 +103727,Male,54,High School,1,7,61,30,20,6.0,2,63,Urban,ML Engineer,122748,0 +103728,Female,37,Bachelors,19,32,43,58,3,0.0,6,88,Semi-Urban,HR Executive,139425,0 +103729,Other,48,High School,14,65,83,58,53,5.0,3,3,Urban,Software Engineer,132512,0 +103730,Male,35,High School,17,68,27,67,21,8.0,5,25,Urban,HR Executive,110245,0 +103731,Female,45,Masters,13,16,11,94,20,3.0,2,34,Urban,ML Engineer,147877,0 +103732,Female,30,Bachelors,14,39,88,91,94,7.0,7,95,Urban,ML Engineer,73568,1 +103733,Male,21,Diploma,10,27,74,39,64,3.0,2,11,Rural,Data Analyst,75586,0 +103734,Male,59,Bachelors,19,35,32,33,65,2.0,4,34,Urban,HR Executive,101369,0 +103735,Male,33,Bachelors,4,99,15,47,55,0.0,4,57,Semi-Urban,Data Analyst,24940,0 +103736,Female,53,Masters,2,56,62,85,14,2.0,0,48,Urban,Manager,90530,1 +103737,Male,37,Diploma,15,66,61,75,59,3.0,3,75,Semi-Urban,ML Engineer,41154,1 +103738,Male,51,Masters,6,83,87,19,15,1.0,6,71,Rural,Software Engineer,52235,1 +103739,Other,39,Diploma,8,37,72,72,57,5.0,0,85,Rural,HR Executive,75123,1 +103740,Female,28,Diploma,9,94,20,88,98,9.0,3,35,Urban,Data Analyst,98011,0 +103741,Male,37,Diploma,3,56,39,4,8,6.0,4,32,Urban,Data Analyst,31636,0 +103742,Male,43,Bachelors,11,42,30,96,47,9.0,4,51,Urban,Manager,101496,0 +103743,Other,22,Diploma,5,45,15,40,29,8.0,2,65,Urban,ML Engineer,45713,0 +103744,Male,46,Masters,16,19,7,72,51,9.0,5,99,Urban,ML Engineer,106809,0 +103745,Male,26,Bachelors,16,11,67,68,93,4.0,7,50,Semi-Urban,Data Analyst,48171,0 +103746,Male,41,Bachelors,19,41,58,9,49,4.0,0,50,Semi-Urban,ML Engineer,105644,0 +103747,Female,32,Masters,9,79,84,5,80,0.0,0,1,Semi-Urban,Data Analyst,70660,0 +103748,Female,27,PhD,0,66,37,72,29,2.0,5,81,Semi-Urban,HR Executive,136656,1 +103749,Male,58,High School,4,27,78,83,54,6.0,5,50,Semi-Urban,HR Executive,125318,1 +103750,Male,47,High School,4,72,32,32,46,2.0,3,65,Urban,HR Executive,72133,0 +103751,Male,56,Masters,13,81,11,95,89,6.0,3,49,Urban,Data Analyst,109276,1 +103752,Male,44,High School,2,91,43,36,87,9.0,4,24,Urban,Software Engineer,117389,0 +103753,Male,56,Diploma,9,43,60,11,18,9.0,2,91,Urban,ML Engineer,104027,0 +103754,Male,24,Masters,14,66,60,44,57,1.0,5,81,Semi-Urban,ML Engineer,63180,1 +103755,Male,50,PhD,13,85,14,48,51,1.0,0,92,Urban,ML Engineer,83431,1 +103756,Female,47,Bachelors,11,93,33,67,21,9.0,4,60,Semi-Urban,HR Executive,65575,1 +103757,Female,59,Bachelors,2,59,66,33,39,7.0,7,81,Urban,ML Engineer,109826,0 +103758,Male,47,Bachelors,8,38,2,99,21,3.0,7,29,Rural,Manager,90797,0 +103759,Female,42,Bachelors,18,44,12,89,78,8.0,1,78,Rural,Data Analyst,21197,0 +103760,Male,38,High School,2,34,49,83,41,2.0,3,69,Urban,Software Engineer,52636,1 +103761,Other,33,Masters,12,61,81,92,79,2.0,2,92,Semi-Urban,Manager,89964,1 +103762,Male,57,Bachelors,7,14,65,30,15,9.0,1,19,Urban,Software Engineer,139403,0 +103763,Female,36,High School,18,19,44,53,33,1.0,7,42,Rural,Data Analyst,98310,0 +103764,Male,36,High School,17,77,33,62,33,0.0,6,10,Semi-Urban,ML Engineer,86622,0 +103765,Male,50,Bachelors,7,48,44,97,97,8.0,2,12,Urban,HR Executive,51872,0 +103766,Female,57,High School,13,80,66,16,65,9.0,1,0,Urban,Software Engineer,41530,0 +103767,Female,30,Masters,7,66,50,75,48,6.0,1,86,Urban,Manager,87507,1 +103768,Female,23,Bachelors,0,52,75,33,71,7.0,2,79,Urban,Manager,116536,0 +103769,Male,51,Bachelors,5,98,35,36,49,6.0,0,39,Semi-Urban,Manager,45970,0 +103770,Female,42,Masters,14,37,90,53,63,3.0,0,95,Urban,Data Analyst,113022,1 +103771,Female,50,High School,14,20,28,96,17,4.0,4,26,Urban,ML Engineer,22935,0 +103772,Male,58,High School,12,43,15,44,80,7.0,7,39,Urban,ML Engineer,36208,0 +103773,Male,35,Bachelors,7,7,50,19,92,6.0,6,1,Urban,Data Analyst,78892,0 +103774,Male,40,Bachelors,6,43,59,26,45,8.0,6,38,Urban,Manager,94892,0 +103775,Other,33,Masters,3,31,80,78,88,2.0,3,3,Urban,Data Analyst,112995,0 +103776,Female,26,High School,0,4,79,27,90,9.0,1,92,Urban,HR Executive,26244,0 +103777,Female,35,Bachelors,0,47,21,94,92,7.0,7,56,Urban,Manager,55392,0 +103778,Male,32,Bachelors,3,24,5,53,20,3.0,4,6,Urban,Data Analyst,130563,0 +103779,Female,38,Bachelors,7,76,85,8,61,7.0,7,12,Urban,Manager,68763,0 +103780,Male,40,Bachelors,17,8,41,54,31,3.0,4,77,Urban,ML Engineer,65113,0 +103781,Male,29,Masters,11,84,2,91,86,1.0,0,28,Semi-Urban,Manager,143008,0 +103782,Male,46,Bachelors,3,22,82,47,69,3.0,0,25,Rural,Software Engineer,135469,0 +103783,Female,40,Masters,1,62,2,48,14,8.0,2,95,Semi-Urban,Data Analyst,137953,0 +103784,Male,51,Masters,10,68,50,24,82,4.0,3,5,Urban,ML Engineer,111033,0 +103785,Male,48,Bachelors,14,91,69,57,38,4.0,6,14,Urban,Software Engineer,57941,0 +103786,Female,52,High School,7,10,86,62,38,2.0,1,40,Urban,Manager,124443,0 +103787,Male,52,Bachelors,14,42,18,36,30,0.0,0,52,Rural,Data Analyst,61774,0 +103788,Male,23,High School,18,56,53,1,14,7.0,2,82,Semi-Urban,Software Engineer,33549,0 +103789,Male,43,PhD,6,62,18,28,80,6.0,3,96,Urban,Data Analyst,88836,0 +103790,Male,38,Bachelors,15,30,45,14,93,3.0,2,81,Urban,Software Engineer,70014,0 +103791,Male,57,Bachelors,8,29,57,33,97,0.0,5,70,Semi-Urban,ML Engineer,42188,0 +103792,Female,30,High School,16,30,71,83,35,5.0,5,80,Semi-Urban,HR Executive,136013,1 +103793,Male,30,Bachelors,13,10,43,35,16,6.0,5,86,Urban,HR Executive,122729,0 +103794,Female,51,Bachelors,3,98,65,67,58,1.0,6,2,Urban,HR Executive,80262,0 +103795,Male,51,Diploma,19,62,51,84,73,8.0,6,22,Rural,ML Engineer,100428,0 +103796,Male,41,Masters,1,81,31,55,93,9.0,1,37,Semi-Urban,Data Analyst,41868,0 +103797,Female,51,Bachelors,5,42,97,12,24,2.0,3,4,Urban,Manager,29644,0 +103798,Male,31,Bachelors,5,63,19,89,57,2.0,0,64,Urban,HR Executive,53282,1 +103799,Female,44,High School,6,27,4,48,3,0.0,4,77,Urban,Software Engineer,149615,0 +103800,Female,21,Diploma,3,52,81,45,40,4.0,5,18,Rural,Software Engineer,128576,0 +103801,Male,35,PhD,8,66,47,68,45,7.0,3,29,Urban,HR Executive,30011,0 +103802,Male,32,Bachelors,15,85,59,84,74,3.0,1,96,Rural,Software Engineer,127940,1 +103803,Male,24,PhD,3,50,93,98,79,7.0,6,97,Urban,HR Executive,114927,1 +103804,Male,40,Masters,14,27,31,98,57,9.0,7,1,Urban,Software Engineer,68587,0 +103805,Male,38,Bachelors,13,9,78,50,14,7.0,1,62,Urban,Software Engineer,26142,0 +103806,Male,53,Diploma,0,82,92,2,73,0.0,4,62,Semi-Urban,HR Executive,50925,1 +103807,Female,49,Masters,15,77,38,28,71,8.0,0,32,Urban,Data Analyst,72049,0 +103808,Female,59,High School,8,30,38,62,41,9.0,3,26,Semi-Urban,Data Analyst,100921,0 +103809,Female,43,Bachelors,10,35,56,86,39,7.0,1,55,Semi-Urban,Software Engineer,136151,0 +103810,Female,26,Bachelors,18,80,28,99,36,9.0,3,82,Urban,HR Executive,44264,1 +103811,Female,24,Bachelors,10,90,14,59,84,6.0,2,10,Rural,HR Executive,70647,0 +103812,Female,45,Bachelors,5,14,59,87,67,6.0,2,81,Urban,ML Engineer,120205,1 +103813,Male,28,Diploma,16,46,10,83,58,8.0,2,28,Rural,ML Engineer,36601,0 +103814,Male,54,High School,2,47,60,93,19,0.0,6,57,Urban,Manager,61001,1 +103815,Male,29,Bachelors,7,3,33,73,45,1.0,1,95,Rural,ML Engineer,39948,0 +103816,Male,22,Diploma,11,9,11,74,51,3.0,4,39,Rural,Manager,47107,0 +103817,Male,27,High School,3,42,37,85,35,7.0,4,56,Urban,HR Executive,31363,0 +103818,Male,40,Diploma,14,94,55,4,92,9.0,6,72,Semi-Urban,ML Engineer,25938,0 +103819,Female,53,Bachelors,8,91,72,90,35,7.0,5,57,Semi-Urban,HR Executive,58838,1 +103820,Male,35,Bachelors,13,35,76,95,33,9.0,2,67,Urban,HR Executive,131634,1 +103821,Female,29,Diploma,19,89,73,49,63,4.0,2,40,Semi-Urban,Manager,69587,1 +103822,Male,40,Masters,4,32,41,52,62,9.0,7,84,Urban,Data Analyst,80123,0 +103823,Male,37,Bachelors,13,81,41,66,83,0.0,7,26,Rural,Data Analyst,90086,0 +103824,Male,56,Diploma,3,17,86,12,9,5.0,5,44,Semi-Urban,Data Analyst,32920,0 +103825,Female,46,Bachelors,7,67,55,25,81,8.0,7,77,Urban,HR Executive,131392,0 +103826,Male,51,Diploma,19,16,97,97,68,3.0,3,11,Semi-Urban,Software Engineer,58688,0 +103827,Other,23,Bachelors,6,29,79,99,45,2.0,1,40,Semi-Urban,Software Engineer,100798,1 +103828,Female,41,Bachelors,6,24,29,8,75,9.0,0,99,Semi-Urban,HR Executive,120083,0 +103829,Male,50,Bachelors,18,36,3,76,97,1.0,4,64,Urban,Manager,59059,0 +103830,Female,44,Diploma,17,36,50,45,91,5.0,0,17,Rural,Data Analyst,102701,0 +103831,Female,53,Masters,6,56,67,31,73,4.0,6,64,Urban,Manager,90881,0 +103832,Male,26,High School,0,59,78,5,77,7.0,3,20,Urban,HR Executive,28184,0 +103833,Male,47,Bachelors,15,40,78,80,94,6.0,2,99,Urban,ML Engineer,41545,1 +103834,Male,58,Masters,3,88,54,12,30,4.0,1,73,Semi-Urban,Manager,43472,0 +103835,Female,59,Diploma,10,94,0,0,37,1.0,7,79,Urban,HR Executive,103662,0 +103836,Female,26,Bachelors,0,53,20,92,86,2.0,4,3,Urban,Software Engineer,50003,0 +103837,Male,22,Bachelors,2,27,5,36,21,0.0,2,67,Semi-Urban,Data Analyst,49598,0 +103838,Male,46,Masters,6,40,47,3,66,5.0,2,68,Semi-Urban,ML Engineer,130836,0 +103839,Female,24,Bachelors,3,18,8,70,28,0.0,0,86,Urban,HR Executive,75742,0 +103840,Male,50,Bachelors,2,98,24,22,33,5.0,5,17,Rural,Manager,23065,0 +103841,Male,50,Bachelors,7,98,97,44,68,2.0,1,27,Urban,Software Engineer,146373,1 +103842,Female,48,Bachelors,11,21,14,58,88,1.0,2,88,Urban,Manager,100316,0 +103843,Male,37,Bachelors,3,77,60,86,53,4.0,2,55,Semi-Urban,ML Engineer,32223,1 +103844,Male,26,Masters,10,15,83,13,16,5.0,0,94,Urban,ML Engineer,58496,0 +103845,Female,38,Diploma,13,60,93,37,76,8.0,1,54,Rural,Data Analyst,91115,1 +103846,Male,43,Bachelors,14,13,83,67,40,1.0,6,65,Semi-Urban,Manager,86331,0 +103847,Male,37,Masters,2,57,18,40,10,1.0,4,20,Urban,HR Executive,73393,0 +103848,Male,38,Bachelors,2,37,94,86,79,1.0,7,96,Semi-Urban,Software Engineer,46582,1 +103849,Male,34,Bachelors,16,36,31,39,47,6.0,3,94,Semi-Urban,Manager,53298,0 +103850,Male,28,High School,13,99,92,63,65,4.0,3,68,Semi-Urban,Data Analyst,48448,1 +103851,Male,56,High School,2,15,7,4,24,6.0,6,36,Urban,HR Executive,44145,0 +103852,Male,39,Masters,4,82,3,24,26,6.0,0,82,Urban,ML Engineer,30268,0 +103853,Female,41,Masters,17,70,1,72,55,4.0,4,33,Urban,Data Analyst,68499,0 +103854,Male,23,Masters,2,26,31,14,58,9.0,7,91,Urban,Software Engineer,140575,0 +103855,Female,23,High School,18,75,16,99,98,2.0,5,3,Semi-Urban,Manager,100495,0 +103856,Female,30,Diploma,10,92,73,35,67,0.0,4,68,Urban,Software Engineer,144475,1 +103857,Female,23,Bachelors,2,10,76,74,39,7.0,6,6,Rural,Software Engineer,27092,0 +103858,Male,51,Bachelors,7,17,90,98,59,5.0,4,14,Urban,ML Engineer,51204,0 +103859,Male,51,Masters,10,55,22,60,76,9.0,7,81,Rural,Data Analyst,135538,0 +103860,Female,41,Diploma,11,13,61,28,18,5.0,1,58,Urban,HR Executive,145619,0 +103861,Male,25,High School,17,8,15,70,94,8.0,7,6,Semi-Urban,HR Executive,49429,0 +103862,Female,26,Masters,3,75,36,30,83,4.0,7,77,Urban,Data Analyst,46831,0 +103863,Female,34,Masters,8,43,95,0,94,7.0,3,55,Urban,Software Engineer,50804,0 +103864,Male,32,Diploma,9,36,43,72,17,1.0,6,93,Urban,HR Executive,95138,1 +103865,Other,46,Bachelors,15,94,64,10,78,7.0,3,32,Semi-Urban,HR Executive,84645,0 +103866,Male,56,High School,8,2,3,45,49,5.0,7,79,Urban,Manager,26823,0 +103867,Female,26,Masters,7,24,17,2,82,8.0,5,83,Urban,Software Engineer,95664,0 +103868,Male,38,Bachelors,9,15,14,48,3,0.0,0,86,Urban,Data Analyst,79758,0 +103869,Female,50,Bachelors,13,4,56,33,38,8.0,4,29,Urban,Manager,123904,0 +103870,Male,24,Bachelors,13,69,78,24,78,2.0,2,31,Urban,Manager,36508,0 +103871,Male,38,High School,9,91,29,48,3,4.0,2,60,Semi-Urban,Data Analyst,87619,0 +103872,Male,57,Bachelors,17,36,67,19,32,3.0,7,60,Semi-Urban,Software Engineer,45956,0 +103873,Male,27,Bachelors,3,24,18,58,66,5.0,0,93,Rural,Data Analyst,65474,0 +103874,Male,27,PhD,2,27,92,66,11,7.0,7,38,Semi-Urban,HR Executive,92935,0 +103875,Male,35,Bachelors,13,72,46,22,22,8.0,4,71,Rural,HR Executive,58697,0 +103876,Male,24,Diploma,1,64,7,90,93,4.0,4,64,Urban,Software Engineer,115074,0 +103877,Other,50,Diploma,1,26,24,93,23,5.0,3,57,Semi-Urban,HR Executive,81636,0 +103878,Female,35,Bachelors,11,74,43,55,68,7.0,2,47,Rural,Software Engineer,133456,0 +103879,Female,50,Bachelors,5,80,72,51,25,8.0,0,91,Urban,ML Engineer,46385,1 +103880,Male,25,Masters,10,60,56,83,12,1.0,2,0,Semi-Urban,ML Engineer,144737,0 +103881,Male,43,Bachelors,5,31,88,94,15,4.0,0,92,Rural,HR Executive,134818,1 +103882,Female,46,Masters,10,6,37,1,91,5.0,5,77,Semi-Urban,Manager,78671,0 +103883,Male,30,Bachelors,12,11,41,30,27,9.0,2,38,Urban,Software Engineer,115168,0 +103884,Other,50,Diploma,8,64,9,99,61,4.0,2,63,Rural,ML Engineer,47868,0 +103885,Male,25,High School,3,7,30,31,78,9.0,2,69,Urban,Software Engineer,52100,0 +103886,Female,40,Bachelors,18,60,81,94,44,7.0,5,13,Rural,ML Engineer,127844,1 +103887,Male,29,Bachelors,3,56,37,30,86,0.0,6,26,Urban,Software Engineer,83295,0 +103888,Male,29,Bachelors,3,14,22,56,83,5.0,6,40,Semi-Urban,Data Analyst,130184,0 +103889,Male,47,High School,5,8,97,97,50,6.0,6,23,Urban,ML Engineer,25926,0 +103890,Female,59,Diploma,2,58,92,2,98,6.0,4,61,Urban,HR Executive,137849,0 +103891,Female,58,High School,16,47,90,95,77,4.0,1,43,Semi-Urban,Data Analyst,65845,1 +103892,Male,39,High School,10,94,64,96,71,8.0,1,62,Semi-Urban,HR Executive,25749,1 +103893,Female,54,Masters,12,78,12,92,39,0.0,2,82,Semi-Urban,Software Engineer,50599,1 +103894,Male,44,Bachelors,8,35,23,89,54,1.0,0,67,Semi-Urban,Software Engineer,25860,0 +103895,Female,41,Bachelors,16,29,4,72,15,8.0,0,39,Urban,ML Engineer,112334,0 +103896,Female,49,Diploma,17,24,27,38,68,1.0,7,23,Urban,Manager,85529,0 +103897,Female,32,Masters,12,94,99,13,32,7.0,7,33,Urban,Data Analyst,112496,0 +103898,Male,50,Bachelors,1,2,6,53,20,9.0,5,85,Urban,Software Engineer,74206,0 +103899,Female,23,High School,10,76,87,43,13,4.0,0,55,Urban,Manager,88848,1 +103900,Other,36,Bachelors,2,40,29,31,17,2.0,5,21,Semi-Urban,Manager,54152,0 +103901,Male,58,Masters,16,62,88,23,46,9.0,3,82,Semi-Urban,HR Executive,110413,1 +103902,Female,55,Diploma,3,27,6,80,13,4.0,1,79,Urban,ML Engineer,36464,0 +103903,Female,40,Bachelors,7,35,20,31,28,2.0,2,51,Urban,Manager,67037,0 +103904,Female,37,PhD,2,6,65,30,23,0.0,6,96,Semi-Urban,Manager,78835,0 +103905,Male,48,Masters,19,88,64,70,14,2.0,3,87,Semi-Urban,Data Analyst,141724,1 +103906,Male,35,Masters,14,76,86,4,76,7.0,4,83,Rural,Software Engineer,140773,1 +103907,Female,35,Bachelors,7,10,81,59,84,7.0,3,39,Urban,Manager,140817,0 +103908,Male,59,Bachelors,5,94,94,70,6,1.0,2,9,Rural,ML Engineer,123268,1 +103909,Female,53,Bachelors,8,12,23,31,70,7.0,0,44,Rural,Data Analyst,76518,0 +103910,Male,37,Bachelors,6,85,20,34,41,7.0,6,48,Semi-Urban,Manager,149285,0 +103911,Male,22,Diploma,11,17,60,43,75,8.0,6,5,Rural,Manager,68520,0 +103912,Male,27,Masters,14,76,20,4,74,2.0,0,0,Semi-Urban,ML Engineer,102844,0 +103913,Male,52,Masters,19,40,44,26,68,6.0,5,13,Rural,ML Engineer,91294,0 +103914,Male,50,Masters,17,84,3,2,39,2.0,2,30,Semi-Urban,Manager,64229,0 +103915,Male,40,Masters,5,74,91,13,16,1.0,5,91,Rural,ML Engineer,100507,1 +103916,Male,23,Masters,19,15,68,22,75,2.0,4,60,Semi-Urban,Manager,115545,0 +103917,Male,28,Masters,3,77,32,32,2,4.0,7,25,Semi-Urban,HR Executive,106557,0 +103918,Female,24,High School,4,32,32,63,53,5.0,5,18,Semi-Urban,HR Executive,99398,0 +103919,Male,42,Bachelors,3,8,49,3,90,4.0,4,8,Semi-Urban,HR Executive,137863,0 +103920,Male,41,Bachelors,15,75,5,86,57,4.0,5,0,Semi-Urban,Manager,144269,0 +103921,Male,37,Masters,0,34,20,83,26,3.0,1,60,Semi-Urban,Software Engineer,78364,0 +103922,Male,36,Masters,8,46,89,17,52,0.0,7,53,Rural,HR Executive,123640,0 +103923,Male,34,Diploma,6,29,43,57,86,4.0,1,51,Urban,Manager,58407,0 +103924,Other,44,Bachelors,9,92,54,61,19,3.0,4,64,Urban,Data Analyst,50137,1 +103925,Female,27,Diploma,2,19,50,61,9,8.0,6,36,Rural,Software Engineer,57093,0 +103926,Male,35,PhD,18,82,37,40,30,3.0,4,99,Rural,ML Engineer,102793,1 +103927,Male,48,Bachelors,3,99,34,45,45,7.0,5,23,Urban,ML Engineer,86042,0 +103928,Female,53,Diploma,6,75,78,87,71,5.0,6,79,Semi-Urban,Manager,43523,1 +103929,Male,55,Diploma,12,59,71,23,83,9.0,2,86,Urban,Manager,51760,1 +103930,Male,35,High School,9,65,73,44,37,3.0,5,16,Urban,ML Engineer,143592,0 +103931,Male,52,Diploma,18,45,80,4,69,5.0,1,53,Rural,ML Engineer,145480,0 +103932,Female,37,High School,2,44,88,59,5,7.0,1,5,Semi-Urban,Software Engineer,78647,0 +103933,Male,34,Masters,8,17,16,87,4,6.0,2,36,Rural,Software Engineer,129226,0 +103934,Male,56,Masters,12,27,68,8,52,6.0,2,37,Rural,Data Analyst,64728,0 +103935,Female,25,Masters,9,10,30,43,72,4.0,2,77,Semi-Urban,Data Analyst,72504,0 +103936,Female,26,Bachelors,15,32,40,40,33,2.0,2,3,Urban,Manager,78420,0 +103937,Male,38,Diploma,0,69,36,61,23,1.0,0,15,Semi-Urban,Data Analyst,77228,0 +103938,Female,46,Diploma,3,9,73,4,18,6.0,5,84,Semi-Urban,ML Engineer,55471,0 +103939,Male,35,Masters,16,42,26,73,5,7.0,1,6,Urban,Data Analyst,109347,0 +103940,Male,38,Diploma,15,81,59,2,87,2.0,6,93,Urban,ML Engineer,144237,1 +103941,Male,21,PhD,5,97,45,86,32,0.0,5,78,Urban,HR Executive,106305,1 +103942,Female,29,Bachelors,2,19,75,52,23,3.0,5,71,Urban,Software Engineer,71424,0 +103943,Male,56,Bachelors,4,94,86,62,55,2.0,0,69,Semi-Urban,HR Executive,27961,1 +103944,Female,35,Diploma,5,16,49,47,96,5.0,2,9,Urban,ML Engineer,103318,0 +103945,Female,38,Masters,18,90,41,88,89,1.0,0,66,Urban,ML Engineer,85537,1 +103946,Male,57,Masters,10,28,58,49,67,1.0,0,87,Urban,HR Executive,98080,0 +103947,Male,38,Bachelors,6,82,21,26,76,2.0,7,20,Urban,HR Executive,82737,0 +103948,Female,59,Masters,4,82,27,68,34,8.0,6,29,Semi-Urban,ML Engineer,51266,0 +103949,Other,41,Bachelors,8,64,62,24,87,7.0,7,31,Urban,Manager,119240,0 +103950,Female,21,Diploma,12,22,38,35,46,4.0,2,4,Semi-Urban,ML Engineer,144713,0 +103951,Male,40,Bachelors,17,85,82,44,33,1.0,5,81,Urban,ML Engineer,120076,1 +103952,Male,50,Bachelors,16,0,45,33,26,0.0,5,51,Urban,Manager,96256,0 +103953,Male,42,Masters,11,70,85,83,84,3.0,7,11,Semi-Urban,Data Analyst,147434,1 +103954,Male,33,Bachelors,4,73,77,99,57,6.0,6,9,Urban,ML Engineer,113555,1 +103955,Male,35,Diploma,9,44,20,95,1,9.0,7,79,Rural,Manager,131631,1 +103956,Other,33,Bachelors,7,81,99,24,87,5.0,1,40,Rural,HR Executive,22070,1 +103957,Male,42,Bachelors,5,58,64,84,43,2.0,2,32,Urban,HR Executive,132165,1 +103958,Female,57,Diploma,19,14,0,48,68,7.0,0,22,Urban,Data Analyst,128755,0 +103959,Male,44,Bachelors,10,15,77,21,21,5.0,7,49,Rural,ML Engineer,95609,0 +103960,Male,23,Masters,5,15,7,32,85,3.0,3,57,Urban,ML Engineer,108970,0 +103961,Female,44,Masters,19,78,56,41,28,7.0,2,34,Semi-Urban,Software Engineer,82737,0 +103962,Male,56,Bachelors,16,25,35,58,23,9.0,7,26,Urban,Manager,143463,0 +103963,Other,44,Masters,11,29,87,37,0,0.0,1,11,Urban,HR Executive,113797,0 +103964,Female,37,High School,2,58,30,60,8,0.0,3,50,Urban,ML Engineer,53644,0 +103965,Male,35,High School,19,53,38,30,44,0.0,2,29,Semi-Urban,Data Analyst,62154,0 +103966,Female,21,Diploma,17,89,20,56,78,7.0,7,58,Semi-Urban,HR Executive,127969,0 +103967,Male,55,Bachelors,10,76,76,35,54,0.0,7,10,Semi-Urban,Software Engineer,70392,0 +103968,Male,42,Bachelors,19,49,83,46,13,1.0,5,78,Urban,Data Analyst,38448,1 +103969,Male,58,Bachelors,10,14,26,34,41,2.0,4,17,Urban,Software Engineer,116969,0 +103970,Male,40,Masters,11,82,80,56,32,0.0,5,71,Urban,Manager,52645,1 +103971,Male,52,Masters,17,22,68,55,4,3.0,2,15,Urban,ML Engineer,86792,0 +103972,Male,28,Bachelors,12,19,89,81,56,4.0,5,54,Rural,ML Engineer,33561,1 +103973,Female,43,Masters,5,44,29,82,70,2.0,6,24,Urban,ML Engineer,89796,0 +103974,Male,52,High School,17,9,46,24,39,3.0,3,57,Urban,Software Engineer,55287,0 +103975,Female,53,Diploma,14,1,53,58,80,2.0,7,39,Urban,ML Engineer,74395,0 +103976,Male,31,Bachelors,8,53,80,21,38,9.0,1,47,Urban,Software Engineer,36906,0 +103977,Male,48,High School,1,74,23,95,80,3.0,4,26,Rural,HR Executive,98669,0 +103978,Female,53,PhD,18,38,39,23,4,2.0,7,73,Urban,Manager,128471,0 +103979,Female,34,High School,4,28,35,6,87,7.0,5,75,Semi-Urban,Manager,90832,0 +103980,Other,25,Bachelors,16,89,70,58,22,4.0,0,49,Urban,HR Executive,44436,1 +103981,Male,27,High School,13,78,54,55,12,1.0,0,53,Semi-Urban,ML Engineer,100714,1 +103982,Other,38,High School,18,44,16,11,11,0.0,4,13,Semi-Urban,Software Engineer,103638,0 +103983,Male,54,Diploma,14,91,13,10,6,7.0,2,71,Semi-Urban,HR Executive,43148,0 +103984,Male,23,Bachelors,11,65,63,77,91,4.0,7,73,Rural,ML Engineer,70134,1 +103985,Female,39,PhD,18,26,24,57,54,9.0,2,20,Urban,HR Executive,105679,0 +103986,Male,24,Bachelors,10,10,96,89,11,8.0,4,68,Urban,Data Analyst,24998,1 +103987,Male,53,High School,1,27,59,90,65,7.0,7,14,Urban,Manager,104123,0 +103988,Male,49,Bachelors,0,83,94,22,2,3.0,2,26,Urban,ML Engineer,52093,0 +103989,Female,52,Bachelors,7,66,12,24,66,8.0,0,53,Semi-Urban,Manager,53134,0 +103990,Male,59,Diploma,8,8,34,48,41,6.0,2,5,Urban,Manager,56743,0 +103991,Other,59,Bachelors,13,2,41,61,41,2.0,4,2,Urban,ML Engineer,103268,0 +103992,Male,24,Masters,16,16,38,83,49,7.0,2,64,Urban,HR Executive,139836,0 +103993,Female,44,Masters,7,88,80,33,1,8.0,7,57,Urban,Software Engineer,37026,1 +103994,Female,31,High School,4,69,88,20,95,1.0,4,26,Semi-Urban,Manager,123716,0 +103995,Female,25,Bachelors,10,13,56,35,87,3.0,4,61,Urban,HR Executive,95439,0 +103996,Male,24,Bachelors,13,40,75,2,14,0.0,2,9,Rural,HR Executive,92178,0 +103997,Male,55,Bachelors,2,34,69,15,55,9.0,1,43,Urban,HR Executive,136833,0 +103998,Male,35,Bachelors,15,30,65,80,34,7.0,7,12,Rural,Manager,26150,0 +103999,Male,43,Diploma,9,38,8,56,94,1.0,1,97,Urban,Data Analyst,107742,0 +104000,Male,52,High School,16,86,91,59,80,2.0,4,23,Urban,Software Engineer,105593,1 +104001,Female,21,High School,16,27,36,40,59,9.0,5,87,Urban,HR Executive,29301,0 +104002,Male,55,PhD,8,50,88,7,50,0.0,3,92,Urban,HR Executive,97229,1 +104003,Male,56,Bachelors,1,66,60,24,63,2.0,6,21,Semi-Urban,HR Executive,133300,0 +104004,Male,42,Masters,3,60,43,6,48,7.0,5,3,Rural,ML Engineer,131204,0 +104005,Male,35,Masters,3,43,0,36,92,5.0,2,67,Rural,ML Engineer,30099,0 +104006,Female,34,High School,2,89,90,14,74,1.0,0,51,Semi-Urban,ML Engineer,114745,1 +104007,Male,50,Bachelors,11,54,18,34,61,5.0,7,3,Urban,Software Engineer,113416,0 +104008,Female,31,Bachelors,11,99,30,3,23,6.0,0,91,Urban,Manager,142524,0 +104009,Male,38,Bachelors,17,7,57,39,9,8.0,0,90,Urban,Software Engineer,69264,0 +104010,Female,28,High School,11,42,40,98,71,0.0,2,90,Urban,ML Engineer,116844,1 +104011,Male,48,Diploma,12,44,69,70,64,6.0,0,25,Rural,Data Analyst,119796,0 +104012,Female,35,High School,17,38,43,72,83,5.0,7,47,Urban,Manager,29233,0 +104013,Female,51,High School,19,17,43,17,64,3.0,5,59,Rural,HR Executive,75022,0 +104014,Male,38,High School,7,26,40,32,6,6.0,0,9,Urban,Software Engineer,60171,0 +104015,Male,53,Diploma,4,17,14,55,34,0.0,2,99,Semi-Urban,ML Engineer,26375,0 +104016,Male,36,Bachelors,12,42,2,25,72,7.0,7,37,Urban,HR Executive,37132,0 +104017,Female,22,PhD,18,56,91,17,25,4.0,1,81,Rural,Software Engineer,87424,1 +104018,Female,35,Masters,18,81,21,57,89,6.0,5,88,Semi-Urban,ML Engineer,37648,1 +104019,Male,44,Diploma,12,27,64,25,90,2.0,1,76,Urban,HR Executive,64210,0 +104020,Female,21,Bachelors,6,50,54,83,31,7.0,1,11,Rural,Software Engineer,21330,0 +104021,Male,29,Masters,5,89,23,9,60,9.0,3,8,Urban,ML Engineer,66761,0 +104022,Male,35,Masters,6,6,57,74,3,1.0,0,34,Urban,Manager,39202,0 +104023,Female,30,Diploma,18,83,67,13,34,9.0,5,32,Urban,Manager,86049,0 +104024,Male,44,Masters,14,42,8,36,86,3.0,2,62,Semi-Urban,ML Engineer,142746,0 +104025,Male,28,Diploma,2,85,46,63,7,9.0,3,22,Semi-Urban,HR Executive,130191,0 +104026,Male,29,Bachelors,17,66,33,79,88,7.0,7,4,Urban,HR Executive,135966,0 +104027,Female,24,Diploma,0,16,28,42,40,2.0,2,25,Urban,Manager,33377,0 +104028,Male,47,Bachelors,18,70,51,9,45,9.0,4,90,Rural,Software Engineer,21121,0 +104029,Male,58,Bachelors,8,8,3,26,34,4.0,0,41,Urban,Software Engineer,34748,0 +104030,Male,44,Masters,19,61,91,50,34,2.0,2,43,Semi-Urban,Manager,43919,1 +104031,Male,59,Masters,4,9,4,67,20,2.0,4,34,Semi-Urban,ML Engineer,72178,0 +104032,Male,42,High School,14,33,17,86,47,5.0,4,67,Rural,HR Executive,99196,0 +104033,Female,27,Bachelors,0,25,57,75,63,6.0,2,6,Semi-Urban,Data Analyst,76424,0 +104034,Male,39,Masters,19,1,36,96,56,3.0,1,78,Urban,Data Analyst,44177,0 +104035,Female,28,Diploma,2,79,40,95,38,0.0,4,0,Urban,ML Engineer,143640,0 +104036,Female,51,Diploma,5,63,66,88,18,2.0,4,5,Urban,HR Executive,145608,0 +104037,Male,31,High School,10,2,59,23,83,1.0,6,27,Urban,HR Executive,103312,0 +104038,Male,26,Bachelors,3,9,37,83,8,7.0,1,67,Urban,HR Executive,59525,0 +104039,Male,59,Bachelors,17,17,41,13,41,8.0,3,78,Urban,ML Engineer,45962,0 +104040,Female,57,Bachelors,2,39,23,47,68,1.0,6,1,Rural,Data Analyst,101552,0 +104041,Male,47,Bachelors,0,21,97,33,17,1.0,0,8,Urban,Data Analyst,86080,0 +104042,Male,52,High School,14,62,89,7,75,9.0,7,71,Rural,HR Executive,72976,0 +104043,Male,27,Diploma,7,70,92,8,33,2.0,7,84,Semi-Urban,ML Engineer,126349,1 +104044,Male,50,Diploma,8,98,94,94,29,0.0,3,55,Rural,Data Analyst,90458,1 +104045,Female,49,High School,5,85,63,72,21,7.0,1,74,Urban,Data Analyst,24454,1 +104046,Male,32,Bachelors,11,79,73,85,59,8.0,1,53,Urban,Data Analyst,103693,1 +104047,Male,39,High School,10,59,80,69,48,8.0,2,47,Urban,Manager,118711,1 +104048,Female,38,Masters,12,31,0,86,43,2.0,1,3,Urban,Data Analyst,135722,0 +104049,Female,58,Diploma,12,60,35,34,82,8.0,5,46,Urban,Data Analyst,57840,0 +104050,Male,59,Masters,7,67,63,75,84,2.0,2,43,Urban,Software Engineer,24686,1 +104051,Male,21,Masters,4,84,31,5,59,0.0,0,78,Urban,ML Engineer,56609,0 +104052,Male,29,High School,4,78,50,53,52,3.0,3,77,Rural,ML Engineer,93987,1 +104053,Male,54,High School,6,62,35,4,99,0.0,1,82,Urban,ML Engineer,120684,0 +104054,Female,22,Masters,3,89,94,36,2,4.0,1,45,Semi-Urban,Software Engineer,138813,1 +104055,Male,43,Masters,17,26,45,40,67,5.0,6,45,Semi-Urban,Manager,94576,0 +104056,Female,36,Bachelors,15,1,62,84,44,3.0,6,22,Urban,Data Analyst,127490,0 +104057,Female,40,Masters,11,39,27,74,96,9.0,4,68,Urban,Data Analyst,100957,0 +104058,Male,51,Bachelors,4,64,58,45,8,2.0,1,86,Urban,Data Analyst,123591,1 +104059,Male,48,High School,11,55,97,71,57,7.0,0,65,Urban,ML Engineer,103845,1 +104060,Male,39,High School,4,13,23,17,0,0.0,6,61,Urban,Software Engineer,145637,0 +104061,Male,43,Bachelors,7,37,38,12,54,6.0,5,0,Rural,Manager,109720,0 +104062,Female,35,Bachelors,14,97,83,91,46,6.0,7,60,Rural,Manager,66950,1 +104063,Male,57,High School,4,78,28,22,65,4.0,1,58,Semi-Urban,HR Executive,78465,0 +104064,Female,42,Diploma,15,30,0,19,93,1.0,5,91,Rural,ML Engineer,75048,0 +104065,Male,32,Diploma,0,1,42,85,68,6.0,3,76,Urban,Manager,122934,0 +104066,Male,29,PhD,10,59,56,94,24,2.0,3,7,Urban,Software Engineer,84047,0 +104067,Female,32,Bachelors,14,21,88,6,48,5.0,6,38,Rural,ML Engineer,81494,0 +104068,Female,44,High School,8,25,3,90,5,8.0,5,22,Urban,Data Analyst,32418,0 +104069,Male,57,Diploma,9,23,94,90,4,9.0,7,36,Rural,Manager,66390,1 +104070,Female,26,Masters,13,58,96,41,20,3.0,5,93,Urban,Software Engineer,57380,1 +104071,Male,52,Bachelors,12,1,29,95,65,7.0,4,39,Rural,Software Engineer,147375,0 +104072,Male,26,High School,8,80,32,46,63,4.0,1,81,Rural,HR Executive,107067,1 +104073,Male,45,Masters,4,98,14,6,72,9.0,4,32,Rural,HR Executive,30207,0 +104074,Female,45,Masters,6,46,10,94,45,1.0,0,34,Urban,HR Executive,47494,0 +104075,Male,47,Bachelors,9,12,29,0,91,9.0,2,25,Semi-Urban,Software Engineer,135253,0 +104076,Male,44,Bachelors,16,87,9,54,15,4.0,6,12,Urban,Software Engineer,76820,0 +104077,Male,26,Masters,1,61,39,59,1,1.0,2,33,Urban,ML Engineer,143620,0 +104078,Male,55,Bachelors,8,1,88,69,68,1.0,1,78,Semi-Urban,HR Executive,93008,1 +104079,Male,50,Bachelors,7,66,76,28,34,6.0,2,10,Urban,HR Executive,148414,0 +104080,Male,41,Bachelors,9,21,92,68,39,5.0,3,74,Urban,Software Engineer,144401,1 +104081,Female,43,Masters,6,65,74,29,60,9.0,5,59,Urban,HR Executive,67818,0 +104082,Male,59,Bachelors,15,18,80,53,77,1.0,4,53,Semi-Urban,HR Executive,137577,0 +104083,Male,24,Masters,2,25,20,51,93,4.0,7,73,Urban,Manager,49867,0 +104084,Male,28,Masters,7,34,65,60,89,8.0,1,34,Urban,Data Analyst,124343,0 +104085,Male,59,Bachelors,19,30,9,31,7,2.0,4,30,Rural,Data Analyst,79565,0 +104086,Female,48,Bachelors,10,83,4,85,50,7.0,1,98,Semi-Urban,HR Executive,146558,1 +104087,Female,39,Bachelors,16,49,69,37,73,7.0,4,29,Rural,Data Analyst,114006,0 +104088,Male,27,Masters,16,64,31,65,79,8.0,7,45,Urban,Data Analyst,146148,0 +104089,Male,34,Masters,5,10,12,44,49,5.0,7,46,Urban,HR Executive,91336,0 +104090,Male,46,Bachelors,4,70,93,8,80,6.0,7,46,Semi-Urban,ML Engineer,143279,0 +104091,Male,23,Bachelors,13,9,48,96,17,4.0,0,95,Urban,ML Engineer,31456,1 +104092,Male,42,Bachelors,3,90,40,3,71,0.0,7,21,Urban,Software Engineer,128955,0 +104093,Female,58,Bachelors,2,21,84,15,52,0.0,3,98,Semi-Urban,ML Engineer,71365,0 +104094,Male,54,Bachelors,9,55,68,57,72,5.0,5,59,Urban,ML Engineer,83510,1 +104095,Female,51,Diploma,2,51,36,15,87,3.0,0,63,Urban,Software Engineer,148825,0 +104096,Female,36,Masters,1,12,61,3,41,2.0,0,85,Rural,Data Analyst,149865,0 +104097,Other,23,Diploma,16,27,76,83,28,5.0,4,2,Semi-Urban,ML Engineer,60361,0 +104098,Male,21,Bachelors,18,21,4,34,71,6.0,7,18,Urban,Manager,82751,0 +104099,Male,39,Diploma,2,29,90,23,64,0.0,4,13,Urban,Manager,88510,0 +104100,Other,52,Masters,14,67,25,59,41,9.0,0,52,Rural,Manager,106134,0 +104101,Other,21,Masters,12,15,74,78,46,9.0,5,39,Urban,Manager,53072,0 +104102,Male,58,PhD,16,77,25,79,42,2.0,5,70,Rural,ML Engineer,28646,1 +104103,Male,43,Masters,1,4,43,17,11,7.0,2,33,Urban,Manager,119716,0 +104104,Male,28,Bachelors,3,94,13,83,99,2.0,7,37,Rural,Manager,64034,0 +104105,Female,38,High School,10,94,19,82,10,4.0,7,7,Urban,Data Analyst,21014,0 +104106,Male,42,Diploma,8,8,71,59,15,3.0,3,38,Urban,HR Executive,62770,0 +104107,Female,51,High School,15,10,16,6,84,2.0,0,0,Rural,ML Engineer,91241,0 +104108,Male,45,Bachelors,17,20,41,81,74,2.0,2,55,Rural,HR Executive,58352,0 +104109,Male,34,Bachelors,6,8,69,18,46,2.0,5,93,Rural,Software Engineer,29879,0 +104110,Male,54,High School,4,48,77,61,78,2.0,7,69,Urban,HR Executive,91030,1 +104111,Male,47,High School,15,5,53,63,28,2.0,2,99,Semi-Urban,Data Analyst,87386,0 +104112,Male,22,Bachelors,13,9,80,18,58,5.0,2,24,Urban,Software Engineer,26302,0 +104113,Female,30,Diploma,0,46,28,71,47,5.0,2,27,Semi-Urban,Software Engineer,34762,0 +104114,Male,29,Masters,11,78,80,82,78,1.0,0,69,Urban,Manager,112167,1 +104115,Female,44,High School,11,92,53,71,43,5.0,1,77,Urban,HR Executive,127516,1 +104116,Male,30,Diploma,19,16,39,65,45,3.0,6,24,Urban,Data Analyst,95697,0 +104117,Male,49,Diploma,19,18,5,65,90,6.0,4,19,Urban,HR Executive,142872,0 +104118,Female,45,Diploma,15,79,15,28,86,7.0,7,19,Semi-Urban,Software Engineer,93794,0 +104119,Male,39,High School,15,94,54,12,58,4.0,0,68,Rural,Software Engineer,30109,0 +104120,Female,56,High School,16,78,14,52,49,4.0,6,46,Urban,Manager,97045,0 +104121,Female,44,Masters,8,14,55,81,15,3.0,5,36,Urban,ML Engineer,105781,0 +104122,Male,43,Diploma,5,72,88,58,27,6.0,6,98,Rural,HR Executive,81870,1 +104123,Female,59,High School,5,66,92,67,88,4.0,2,86,Rural,Data Analyst,77761,1 +104124,Other,58,Bachelors,19,9,78,1,23,1.0,2,19,Urban,HR Executive,54163,0 +104125,Male,37,Masters,2,53,79,24,25,4.0,1,93,Urban,ML Engineer,117028,1 +104126,Male,49,High School,11,9,1,88,86,2.0,7,0,Semi-Urban,ML Engineer,116884,0 +104127,Male,55,High School,5,65,66,57,5,7.0,6,64,Urban,Manager,142317,1 +104128,Female,44,Bachelors,16,64,13,27,15,0.0,2,20,Semi-Urban,HR Executive,21685,0 +104129,Male,27,Diploma,12,19,94,41,89,6.0,6,57,Semi-Urban,Software Engineer,132595,0 +104130,Male,41,Bachelors,18,47,8,86,24,0.0,4,61,Urban,Software Engineer,144280,0 +104131,Male,44,Masters,7,42,18,69,98,9.0,6,83,Urban,Data Analyst,32484,0 +104132,Male,25,Bachelors,4,34,10,73,35,9.0,4,95,Semi-Urban,Manager,116909,0 +104133,Male,27,Bachelors,12,77,11,26,74,3.0,5,23,Urban,HR Executive,65053,0 +104134,Male,29,Bachelors,17,47,39,8,58,1.0,6,77,Rural,Data Analyst,96725,0 +104135,Male,31,Masters,10,78,89,84,48,8.0,7,91,Urban,Data Analyst,130059,1 +104136,Male,36,Masters,19,59,70,63,42,0.0,4,70,Urban,Data Analyst,116641,1 +104137,Female,56,Bachelors,11,80,91,66,81,9.0,0,93,Urban,HR Executive,105247,1 +104138,Male,25,Bachelors,16,42,86,35,42,3.0,2,37,Urban,ML Engineer,33819,0 +104139,Other,47,Masters,16,52,24,83,74,7.0,4,10,Urban,Manager,142688,0 +104140,Male,28,Masters,12,9,25,70,93,7.0,1,80,Rural,HR Executive,131762,0 +104141,Female,33,Masters,0,83,38,92,31,5.0,7,72,Semi-Urban,Software Engineer,48304,1 +104142,Male,25,Bachelors,2,35,24,5,42,4.0,3,56,Rural,Manager,119503,0 +104143,Other,25,Bachelors,0,92,48,54,62,1.0,1,97,Urban,Manager,31705,1 +104144,Female,32,High School,16,28,96,31,85,5.0,2,53,Rural,ML Engineer,128945,0 +104145,Female,51,Masters,13,34,35,70,53,6.0,5,75,Semi-Urban,Data Analyst,105998,0 +104146,Female,51,Bachelors,15,72,93,86,42,4.0,7,79,Semi-Urban,Manager,55664,1 +104147,Female,55,Bachelors,2,18,74,78,33,3.0,4,31,Urban,HR Executive,64388,0 +104148,Other,58,Masters,0,27,60,2,18,7.0,6,3,Rural,Software Engineer,32327,0 +104149,Male,53,Bachelors,17,2,89,15,0,5.0,4,50,Semi-Urban,Software Engineer,80561,0 +104150,Male,30,Bachelors,17,99,75,66,19,2.0,2,40,Urban,ML Engineer,149195,1 +104151,Male,55,PhD,16,6,56,2,41,4.0,0,69,Semi-Urban,Manager,117882,0 +104152,Male,21,Masters,3,65,4,39,43,8.0,6,67,Rural,Manager,101594,0 +104153,Female,51,Masters,0,53,68,60,84,4.0,0,25,Urban,ML Engineer,81340,0 +104154,Male,37,Diploma,11,78,57,94,64,1.0,7,45,Semi-Urban,HR Executive,95958,1 +104155,Female,40,High School,3,9,25,5,51,9.0,3,95,Urban,Data Analyst,87456,0 +104156,Male,43,Masters,9,74,71,38,62,4.0,0,30,Urban,HR Executive,114530,0 +104157,Male,36,Diploma,2,85,73,45,50,9.0,6,71,Urban,Data Analyst,50722,1 +104158,Other,33,Bachelors,5,33,45,19,1,4.0,6,62,Urban,Software Engineer,87343,0 +104159,Male,28,High School,13,59,54,83,92,4.0,2,37,Semi-Urban,HR Executive,89815,0 +104160,Male,55,Bachelors,13,60,51,55,24,5.0,1,14,Rural,Software Engineer,57854,0 +104161,Male,36,Bachelors,3,90,84,95,3,8.0,4,57,Urban,ML Engineer,33270,1 +104162,Male,57,High School,4,92,20,10,24,8.0,7,45,Urban,Manager,60955,0 +104163,Male,21,Bachelors,14,99,55,0,25,7.0,6,68,Rural,Data Analyst,39853,0 +104164,Male,48,Masters,16,17,17,34,37,0.0,5,69,Semi-Urban,ML Engineer,106341,0 +104165,Female,52,Masters,9,69,70,52,93,5.0,3,97,Urban,Manager,142650,1 +104166,Male,29,Masters,16,50,49,85,52,8.0,6,95,Semi-Urban,Software Engineer,68419,1 +104167,Male,48,Masters,4,66,92,54,89,1.0,0,64,Urban,ML Engineer,110037,1 +104168,Female,57,Bachelors,3,11,75,75,14,9.0,6,22,Semi-Urban,Software Engineer,36648,0 +104169,Male,44,Bachelors,9,85,24,64,49,1.0,5,95,Rural,Manager,86675,1 +104170,Male,58,High School,3,56,60,73,52,2.0,7,83,Urban,ML Engineer,53613,1 +104171,Female,28,Diploma,18,12,6,8,63,0.0,5,70,Semi-Urban,ML Engineer,42386,0 +104172,Female,49,High School,13,79,0,24,12,1.0,3,72,Semi-Urban,HR Executive,23812,0 +104173,Male,47,Diploma,12,18,27,77,77,7.0,0,34,Semi-Urban,HR Executive,110070,0 +104174,Male,52,Bachelors,1,7,38,25,24,1.0,3,74,Urban,ML Engineer,42254,0 +104175,Male,37,Bachelors,12,82,51,20,1,4.0,4,76,Urban,Manager,83029,0 +104176,Female,46,High School,10,42,12,81,45,3.0,5,74,Urban,Manager,127314,0 +104177,Female,23,PhD,16,58,22,4,77,1.0,2,73,Urban,HR Executive,57325,0 +104178,Male,44,Diploma,11,30,96,77,80,6.0,1,29,Semi-Urban,Manager,88417,0 +104179,Male,23,Masters,3,37,82,6,13,7.0,1,69,Urban,HR Executive,53017,0 +104180,Female,25,Bachelors,3,29,28,76,35,9.0,2,20,Semi-Urban,Software Engineer,68414,0 +104181,Female,59,High School,1,93,63,28,51,0.0,3,2,Urban,Data Analyst,65388,0 +104182,Female,51,Bachelors,0,30,3,32,15,9.0,1,52,Urban,Manager,120781,0 +104183,Male,25,Bachelors,7,91,35,99,68,0.0,5,51,Urban,HR Executive,76490,1 +104184,Other,33,Bachelors,14,61,58,58,25,5.0,7,99,Urban,HR Executive,66033,1 +104185,Female,54,Masters,5,62,1,75,42,5.0,3,80,Rural,Software Engineer,124867,0 +104186,Male,45,Bachelors,6,90,44,90,35,0.0,4,18,Semi-Urban,Manager,114789,1 +104187,Male,39,High School,4,99,80,94,81,6.0,6,67,Semi-Urban,Data Analyst,48356,1 +104188,Female,29,High School,17,27,50,84,25,1.0,7,67,Semi-Urban,Data Analyst,66768,0 +104189,Female,47,Diploma,17,27,74,52,97,1.0,2,85,Urban,Manager,79738,0 +104190,Male,22,Bachelors,19,27,20,75,59,3.0,6,36,Semi-Urban,Software Engineer,74391,0 +104191,Male,26,Masters,15,65,71,68,60,0.0,3,33,Semi-Urban,Manager,21721,1 +104192,Male,45,Bachelors,13,45,71,13,40,3.0,3,83,Semi-Urban,ML Engineer,34229,0 +104193,Male,43,Diploma,9,97,47,89,71,8.0,4,3,Semi-Urban,HR Executive,37662,1 +104194,Male,41,Bachelors,3,4,37,87,18,1.0,4,45,Rural,ML Engineer,116659,0 +104195,Male,32,Diploma,15,1,62,34,14,4.0,1,26,Semi-Urban,Data Analyst,93808,0 +104196,Female,25,Bachelors,4,43,88,61,74,7.0,0,35,Rural,Data Analyst,117711,0 +104197,Male,44,Bachelors,15,4,30,2,39,4.0,4,63,Rural,Manager,68051,0 +104198,Female,32,Bachelors,13,50,9,49,39,5.0,1,88,Rural,Data Analyst,20504,0 +104199,Female,48,Masters,16,68,31,25,16,1.0,5,42,Urban,Manager,109237,0 +104200,Male,37,Bachelors,18,14,52,73,39,6.0,2,29,Semi-Urban,ML Engineer,34738,0 +104201,Male,39,Masters,14,52,92,70,98,3.0,7,26,Rural,Data Analyst,34421,1 +104202,Male,24,Bachelors,13,84,77,26,89,5.0,3,86,Rural,HR Executive,96599,1 +104203,Male,37,Masters,10,34,95,69,95,4.0,1,58,Urban,ML Engineer,113742,1 +104204,Female,38,Bachelors,10,15,38,21,89,6.0,0,98,Semi-Urban,Data Analyst,122509,0 +104205,Male,33,Masters,13,93,5,7,67,5.0,6,70,Urban,Manager,43198,0 +104206,Male,52,Bachelors,8,76,59,80,98,2.0,3,57,Urban,ML Engineer,93936,1 +104207,Male,44,Masters,8,91,73,16,96,7.0,2,18,Rural,Data Analyst,77023,0 +104208,Male,46,Diploma,5,56,52,59,3,2.0,2,64,Urban,ML Engineer,133797,0 +104209,Female,48,High School,0,24,72,82,11,1.0,3,19,Urban,ML Engineer,38849,0 +104210,Male,47,Bachelors,7,53,21,65,4,5.0,3,74,Semi-Urban,Manager,113456,0 +104211,Female,59,High School,8,12,47,79,46,9.0,6,40,Rural,ML Engineer,64722,0 +104212,Female,50,Masters,7,2,0,76,12,9.0,7,99,Urban,Data Analyst,129587,0 +104213,Other,53,Diploma,13,8,72,87,35,3.0,0,15,Rural,ML Engineer,91693,0 +104214,Female,21,Bachelors,13,95,77,8,36,7.0,3,93,Rural,Data Analyst,64831,1 +104215,Female,24,Bachelors,2,69,1,38,46,2.0,7,7,Semi-Urban,Manager,141122,0 +104216,Male,46,PhD,1,83,91,36,76,7.0,7,61,Semi-Urban,Manager,82149,1 +104217,Female,45,Masters,1,84,95,33,61,1.0,3,18,Urban,HR Executive,39577,0 +104218,Male,49,PhD,5,54,78,37,38,6.0,4,10,Urban,Data Analyst,126490,0 +104219,Male,53,Diploma,6,23,98,67,67,7.0,6,52,Urban,HR Executive,21117,1 +104220,Male,21,PhD,9,71,84,10,16,1.0,1,52,Urban,Manager,47496,0 +104221,Female,56,High School,14,93,94,44,62,8.0,2,8,Urban,Software Engineer,71930,0 +104222,Male,32,Bachelors,9,77,92,55,76,8.0,2,79,Rural,Software Engineer,136414,1 +104223,Female,56,Bachelors,7,40,89,35,5,2.0,1,71,Rural,Software Engineer,142001,0 +104224,Male,31,High School,12,17,67,63,29,3.0,7,33,Rural,Data Analyst,93349,0 +104225,Male,29,Bachelors,10,73,79,73,89,8.0,3,77,Semi-Urban,ML Engineer,25093,1 +104226,Female,52,High School,14,95,99,72,61,9.0,6,57,Semi-Urban,Software Engineer,38875,1 +104227,Female,28,Bachelors,16,36,85,54,37,2.0,2,67,Urban,HR Executive,62763,1 +104228,Female,30,Diploma,13,49,0,83,5,1.0,3,87,Semi-Urban,HR Executive,33445,0 +104229,Male,27,Diploma,13,82,24,19,38,6.0,3,30,Semi-Urban,Software Engineer,20048,0 +104230,Male,54,Bachelors,13,79,0,4,73,8.0,6,96,Urban,Manager,122369,0 +104231,Male,37,High School,14,95,46,16,30,0.0,4,86,Urban,Manager,55802,1 +104232,Male,38,Bachelors,8,70,3,38,39,2.0,5,54,Urban,Software Engineer,102657,0 +104233,Male,22,Diploma,1,64,40,94,88,7.0,5,27,Rural,Software Engineer,104371,0 +104234,Male,50,Diploma,6,53,76,48,4,1.0,0,19,Rural,Data Analyst,72865,0 +104235,Other,37,High School,13,87,92,7,0,8.0,6,62,Urban,ML Engineer,93260,1 +104236,Male,24,Masters,1,86,79,41,90,2.0,6,3,Semi-Urban,HR Executive,96920,0 +104237,Male,56,Bachelors,12,82,3,79,37,8.0,4,45,Rural,Software Engineer,111104,0 +104238,Female,38,Bachelors,14,31,21,57,62,1.0,0,8,Urban,HR Executive,115479,0 +104239,Male,36,Masters,19,65,12,46,73,3.0,3,44,Urban,Software Engineer,101426,0 +104240,Male,25,Bachelors,3,58,79,60,27,9.0,4,2,Rural,Software Engineer,59938,0 +104241,Male,36,Bachelors,14,25,97,10,36,3.0,5,22,Urban,Data Analyst,139518,0 +104242,Female,34,Bachelors,10,19,58,52,8,3.0,0,39,Rural,Data Analyst,25884,0 +104243,Male,30,High School,7,90,29,84,39,6.0,3,67,Urban,Manager,139019,1 +104244,Male,50,Diploma,13,94,1,89,76,8.0,6,27,Urban,ML Engineer,87384,0 +104245,Male,55,Bachelors,10,90,0,45,5,0.0,6,11,Rural,HR Executive,62373,0 +104246,Female,41,High School,15,37,98,37,19,5.0,1,30,Semi-Urban,Data Analyst,103617,0 +104247,Male,42,Diploma,13,48,71,98,57,3.0,7,72,Urban,Software Engineer,93834,1 +104248,Male,23,Bachelors,12,63,85,32,70,9.0,3,17,Rural,Manager,56523,0 +104249,Female,34,Masters,2,52,55,55,61,1.0,5,2,Rural,HR Executive,132019,0 +104250,Other,44,Bachelors,17,37,55,73,96,7.0,0,92,Rural,Data Analyst,81737,1 +104251,Male,56,High School,6,85,7,88,8,8.0,7,67,Rural,Manager,118479,1 +104252,Female,27,Masters,10,98,54,81,21,9.0,0,28,Rural,Manager,83068,1 +104253,Female,43,Masters,2,71,21,93,57,4.0,4,81,Urban,Software Engineer,23507,1 +104254,Male,22,Bachelors,15,5,14,7,89,5.0,0,2,Rural,HR Executive,44037,0 +104255,Female,21,Bachelors,16,83,39,35,86,8.0,6,12,Semi-Urban,Software Engineer,67851,0 +104256,Female,53,Masters,0,44,65,71,39,4.0,2,84,Rural,ML Engineer,91974,1 +104257,Female,43,Bachelors,18,76,8,6,55,1.0,5,59,Urban,Data Analyst,114841,0 +104258,Male,26,High School,17,8,64,93,21,2.0,4,74,Urban,Data Analyst,101298,1 +104259,Male,40,Masters,2,32,29,85,13,0.0,4,11,Urban,Software Engineer,74744,0 +104260,Female,50,Diploma,9,32,19,51,96,7.0,6,23,Urban,Manager,60838,0 +104261,Female,54,Diploma,8,88,88,88,38,3.0,3,66,Urban,HR Executive,83334,1 +104262,Female,51,Bachelors,10,14,89,52,72,8.0,3,54,Urban,HR Executive,82213,0 +104263,Male,21,Bachelors,13,26,33,93,50,1.0,7,94,Rural,Data Analyst,82567,1 +104264,Other,50,Bachelors,18,99,37,22,79,7.0,4,62,Urban,ML Engineer,116114,0 +104265,Female,26,High School,0,13,48,74,3,1.0,3,90,Semi-Urban,Manager,102485,0 +104266,Male,23,Bachelors,6,39,92,91,22,2.0,2,32,Semi-Urban,HR Executive,111821,1 +104267,Male,41,Bachelors,16,93,21,25,33,3.0,6,14,Urban,HR Executive,142340,0 +104268,Female,28,High School,8,4,40,65,29,8.0,6,42,Urban,Software Engineer,131866,0 +104269,Female,42,Masters,4,13,21,52,86,3.0,0,47,Urban,Manager,112938,0 +104270,Female,22,High School,17,75,94,69,86,7.0,0,11,Urban,Software Engineer,94634,1 +104271,Female,25,Diploma,9,97,71,68,59,4.0,7,93,Rural,ML Engineer,98290,1 +104272,Male,56,Masters,11,2,51,98,68,7.0,1,97,Urban,HR Executive,126413,1 +104273,Male,29,Bachelors,8,40,30,23,76,7.0,7,33,Semi-Urban,Data Analyst,94020,0 +104274,Male,57,Masters,13,27,96,97,18,9.0,7,76,Semi-Urban,ML Engineer,80609,1 +104275,Male,50,Bachelors,9,21,5,81,87,9.0,3,74,Rural,Software Engineer,88553,0 +104276,Male,41,Masters,1,67,70,63,23,6.0,4,21,Semi-Urban,Manager,20503,0 +104277,Female,58,PhD,11,69,16,30,50,6.0,1,43,Urban,Manager,29394,0 +104278,Female,30,PhD,18,27,43,27,35,1.0,4,33,Urban,Data Analyst,109030,0 +104279,Female,58,Diploma,2,14,57,4,0,8.0,7,71,Urban,HR Executive,147278,0 +104280,Male,24,PhD,5,89,17,61,73,6.0,0,50,Urban,Software Engineer,56781,0 +104281,Female,41,Bachelors,19,10,18,56,28,3.0,7,32,Rural,ML Engineer,146339,0 +104282,Male,54,High School,15,98,89,91,2,5.0,0,23,Urban,Software Engineer,72022,1 +104283,Female,35,Bachelors,18,27,8,90,75,6.0,0,11,Urban,HR Executive,98114,0 +104284,Male,33,Bachelors,15,94,39,74,71,7.0,1,0,Rural,Software Engineer,59012,0 +104285,Female,56,Bachelors,16,93,48,0,58,3.0,2,87,Urban,Manager,59389,0 +104286,Male,30,Diploma,19,19,47,35,70,7.0,3,16,Rural,Manager,20178,0 +104287,Female,29,Bachelors,15,57,46,2,58,1.0,5,9,Rural,Software Engineer,93322,0 +104288,Female,44,Bachelors,14,7,37,8,37,9.0,4,69,Rural,HR Executive,41677,0 +104289,Male,21,PhD,15,16,63,95,74,7.0,2,48,Semi-Urban,HR Executive,123418,0 +104290,Male,25,Bachelors,11,63,78,28,58,2.0,0,39,Urban,Data Analyst,142825,0 +104291,Female,31,Bachelors,7,64,72,19,29,3.0,7,47,Rural,Data Analyst,27896,0 +104292,Female,26,Bachelors,11,87,51,58,15,9.0,3,13,Rural,Software Engineer,27863,0 +104293,Female,26,High School,16,75,44,76,43,2.0,4,7,Semi-Urban,Manager,56076,0 +104294,Male,32,Diploma,13,58,55,33,75,1.0,3,32,Semi-Urban,HR Executive,120320,0 +104295,Male,36,Diploma,12,83,87,69,50,7.0,5,94,Rural,Data Analyst,48643,1 +104296,Male,21,Bachelors,1,72,37,78,97,4.0,0,6,Urban,ML Engineer,101677,0 +104297,Female,39,Bachelors,15,45,88,84,65,0.0,4,70,Urban,Software Engineer,49480,1 +104298,Female,53,Bachelors,0,37,19,83,80,4.0,7,85,Semi-Urban,ML Engineer,63454,0 +104299,Male,55,Bachelors,6,67,18,48,33,1.0,1,8,Semi-Urban,HR Executive,137071,0 +104300,Female,56,Bachelors,3,34,84,73,72,5.0,1,55,Rural,Manager,115222,1 +104301,Male,30,Masters,9,11,67,95,77,6.0,5,38,Urban,Manager,81075,0 +104302,Male,26,Masters,1,4,28,3,50,8.0,1,56,Semi-Urban,Manager,23726,0 +104303,Male,47,PhD,12,10,57,72,94,7.0,5,81,Rural,HR Executive,59882,0 +104304,Female,48,Masters,0,50,71,83,20,1.0,1,35,Urban,HR Executive,90842,0 +104305,Female,57,Diploma,5,79,79,59,63,3.0,5,18,Urban,Software Engineer,138194,0 +104306,Male,58,Bachelors,6,94,79,37,19,7.0,0,97,Urban,Software Engineer,85454,1 +104307,Male,47,Masters,18,32,18,89,50,2.0,0,66,Semi-Urban,Data Analyst,40674,0 +104308,Male,53,High School,4,65,33,85,79,9.0,0,69,Rural,Data Analyst,124900,1 +104309,Male,30,Bachelors,18,15,24,69,50,8.0,0,14,Urban,Data Analyst,34243,0 +104310,Male,47,Bachelors,0,59,72,55,68,2.0,2,27,Urban,Data Analyst,113891,0 +104311,Female,54,Diploma,8,32,40,68,12,3.0,2,5,Urban,ML Engineer,90824,0 +104312,Male,32,PhD,7,34,58,82,49,4.0,5,73,Semi-Urban,Manager,114905,1 +104313,Male,56,Diploma,16,58,69,50,16,5.0,6,32,Rural,Manager,69030,0 +104314,Male,29,Bachelors,19,3,13,82,6,0.0,1,95,Urban,Software Engineer,80529,0 +104315,Female,53,Bachelors,2,27,15,1,84,8.0,3,56,Semi-Urban,Software Engineer,63854,0 +104316,Female,41,Masters,18,71,65,13,77,1.0,6,17,Urban,HR Executive,72005,0 +104317,Female,55,High School,14,52,27,21,30,3.0,7,60,Urban,ML Engineer,55523,0 +104318,Male,40,Diploma,8,19,90,12,35,4.0,1,59,Rural,Software Engineer,41029,0 +104319,Male,49,High School,12,73,35,94,88,6.0,1,30,Rural,ML Engineer,98298,0 +104320,Male,37,Bachelors,6,48,36,47,61,1.0,4,83,Semi-Urban,Manager,134149,0 +104321,Male,57,Masters,0,90,16,40,42,0.0,0,93,Semi-Urban,Manager,147559,1 +104322,Female,31,PhD,5,49,26,92,86,7.0,2,29,Rural,ML Engineer,112679,0 +104323,Male,52,Masters,0,97,2,44,29,9.0,3,5,Urban,HR Executive,78822,0 +104324,Male,26,Diploma,1,64,85,36,98,6.0,0,79,Urban,Data Analyst,90536,1 +104325,Male,35,Diploma,0,82,85,79,27,7.0,0,27,Semi-Urban,Manager,145484,1 +104326,Female,55,Masters,17,73,6,47,2,8.0,5,72,Urban,Data Analyst,102219,0 +104327,Male,27,Masters,5,17,4,93,52,7.0,1,59,Urban,HR Executive,79384,0 +104328,Male,49,Bachelors,17,81,37,12,11,6.0,2,45,Urban,Software Engineer,93063,0 +104329,Male,32,PhD,13,33,24,42,70,8.0,4,85,Rural,Data Analyst,34616,0 +104330,Female,44,Bachelors,4,87,59,46,52,4.0,5,25,Urban,Data Analyst,88586,0 +104331,Female,23,Masters,16,58,18,74,66,0.0,4,78,Rural,Data Analyst,142215,0 +104332,Female,49,High School,5,81,2,53,34,7.0,2,43,Urban,HR Executive,124062,0 +104333,Male,33,PhD,7,29,83,71,74,8.0,5,91,Semi-Urban,Software Engineer,27024,1 +104334,Female,51,Diploma,7,77,71,5,94,0.0,1,42,Urban,HR Executive,44223,0 +104335,Male,50,Bachelors,1,32,64,25,62,5.0,3,37,Rural,ML Engineer,25274,0 +104336,Male,57,Bachelors,4,47,93,75,99,3.0,6,47,Urban,Software Engineer,71765,1 +104337,Female,57,Masters,1,55,36,98,66,5.0,5,89,Urban,Software Engineer,72488,1 +104338,Male,26,Bachelors,8,13,91,9,10,0.0,7,68,Semi-Urban,Software Engineer,78366,0 +104339,Male,48,Bachelors,12,88,92,3,78,5.0,1,27,Urban,Data Analyst,35608,0 +104340,Male,46,Diploma,6,89,14,84,66,2.0,3,32,Rural,HR Executive,96757,0 +104341,Male,31,Diploma,2,54,33,51,14,0.0,0,78,Urban,Data Analyst,138660,0 +104342,Female,29,Bachelors,16,73,95,37,78,7.0,4,82,Semi-Urban,HR Executive,82921,1 +104343,Female,33,PhD,10,2,7,4,6,6.0,0,94,Semi-Urban,Software Engineer,43190,0 +104344,Male,49,Bachelors,19,97,90,79,70,1.0,5,77,Urban,Manager,46441,1 +104345,Male,26,Masters,10,67,92,92,9,4.0,0,58,Urban,HR Executive,20806,1 +104346,Male,29,Bachelors,9,65,68,4,2,3.0,5,71,Rural,ML Engineer,143381,0 +104347,Male,42,Diploma,2,22,25,11,6,9.0,0,96,Urban,ML Engineer,122018,0 +104348,Male,50,Bachelors,3,79,1,53,43,6.0,4,65,Urban,Data Analyst,145483,0 +104349,Male,55,High School,17,29,36,15,86,5.0,0,32,Urban,ML Engineer,143737,0 +104350,Female,37,Bachelors,10,40,21,82,76,7.0,0,33,Urban,HR Executive,142899,0 +104351,Male,30,Diploma,11,74,62,24,54,1.0,0,91,Urban,Manager,57262,1 +104352,Female,24,Bachelors,8,19,9,84,15,1.0,1,91,Semi-Urban,ML Engineer,45680,0 +104353,Male,26,Masters,9,77,25,72,57,1.0,7,9,Urban,ML Engineer,101356,0 +104354,Other,53,Diploma,0,54,57,23,56,4.0,2,41,Rural,Manager,138538,0 +104355,Male,46,PhD,18,26,82,40,11,7.0,1,76,Urban,Data Analyst,107346,0 +104356,Male,38,Bachelors,7,66,74,45,11,6.0,3,15,Urban,HR Executive,21965,0 +104357,Male,43,Diploma,4,70,35,83,3,7.0,7,57,Urban,ML Engineer,30980,1 +104358,Male,43,Bachelors,16,1,14,37,85,4.0,5,91,Urban,ML Engineer,105263,0 +104359,Male,27,Bachelors,2,38,29,84,89,7.0,7,1,Rural,ML Engineer,32024,0 +104360,Male,54,Bachelors,16,50,9,10,4,0.0,6,42,Semi-Urban,Data Analyst,78998,0 +104361,Female,40,Masters,3,32,48,41,43,8.0,5,13,Urban,Data Analyst,25024,0 +104362,Female,46,Diploma,6,29,59,74,53,8.0,2,78,Semi-Urban,Manager,30722,0 +104363,Male,52,Bachelors,8,81,77,72,62,8.0,1,24,Rural,Data Analyst,96730,1 +104364,Male,50,Bachelors,1,20,1,24,3,2.0,4,47,Semi-Urban,Software Engineer,83867,0 +104365,Male,50,Masters,10,60,51,72,77,3.0,7,14,Urban,ML Engineer,106254,0 +104366,Female,40,Diploma,0,83,49,1,10,7.0,0,27,Urban,ML Engineer,123953,0 +104367,Male,50,High School,16,76,49,29,87,7.0,6,91,Urban,Manager,138988,1 +104368,Male,36,Bachelors,11,62,52,90,65,1.0,1,40,Rural,Software Engineer,42291,1 +104369,Male,22,Bachelors,8,70,63,21,32,7.0,5,31,Urban,Data Analyst,113117,0 +104370,Female,54,Bachelors,1,79,4,90,14,9.0,3,41,Urban,Software Engineer,130267,0 +104371,Other,26,High School,19,60,5,68,97,3.0,4,60,Semi-Urban,Software Engineer,84983,0 +104372,Female,44,Bachelors,12,21,72,24,84,7.0,7,85,Semi-Urban,HR Executive,112230,0 +104373,Male,52,High School,3,87,14,95,2,2.0,4,72,Semi-Urban,ML Engineer,46951,1 +104374,Female,34,High School,15,36,17,46,4,8.0,6,1,Urban,Software Engineer,89122,0 +104375,Male,22,Bachelors,10,30,63,96,26,7.0,2,65,Semi-Urban,Software Engineer,98509,1 +104376,Male,58,Bachelors,19,74,51,50,20,3.0,5,30,Urban,ML Engineer,123057,0 +104377,Male,35,High School,2,70,52,0,59,5.0,0,68,Urban,HR Executive,42333,0 +104378,Female,33,Bachelors,15,64,54,13,61,1.0,2,8,Urban,ML Engineer,122855,0 +104379,Male,38,Masters,1,25,34,1,59,1.0,7,18,Urban,HR Executive,121756,0 +104380,Male,44,High School,5,58,8,90,64,6.0,6,2,Rural,HR Executive,65788,0 +104381,Male,24,High School,14,14,39,96,63,1.0,5,47,Rural,Data Analyst,75083,0 +104382,Male,29,Masters,15,75,95,56,48,1.0,7,87,Rural,ML Engineer,79339,1 +104383,Female,49,Masters,5,25,8,68,77,1.0,2,14,Rural,Manager,25061,0 +104384,Female,55,Bachelors,15,49,0,53,47,9.0,6,40,Urban,ML Engineer,36325,0 +104385,Male,33,Bachelors,2,35,1,31,58,1.0,5,25,Urban,Software Engineer,40910,0 +104386,Female,36,Diploma,2,29,57,5,92,1.0,0,95,Urban,Software Engineer,140837,0 +104387,Female,31,Bachelors,17,14,30,74,35,2.0,1,34,Urban,ML Engineer,54988,0 +104388,Male,29,High School,13,2,15,22,58,9.0,4,69,Urban,Data Analyst,108302,0 +104389,Female,23,Masters,1,84,75,5,82,3.0,6,83,Rural,Data Analyst,115233,1 +104390,Male,31,Diploma,9,45,72,96,28,0.0,2,35,Rural,ML Engineer,34720,1 +104391,Female,50,Masters,5,55,67,5,29,4.0,3,86,Semi-Urban,HR Executive,96706,0 +104392,Female,39,Diploma,12,69,47,50,83,2.0,4,68,Semi-Urban,Software Engineer,90179,0 +104393,Female,50,Bachelors,17,1,11,38,74,3.0,7,54,Urban,Data Analyst,98516,0 +104394,Female,26,PhD,2,8,90,94,17,2.0,0,37,Urban,Data Analyst,28230,0 +104395,Male,48,Diploma,10,47,84,38,10,3.0,1,93,Urban,Manager,115720,1 +104396,Male,48,Bachelors,16,56,48,96,92,2.0,2,41,Semi-Urban,HR Executive,62801,1 +104397,Male,32,Diploma,13,48,13,3,27,5.0,6,42,Rural,ML Engineer,31828,0 +104398,Male,54,Masters,3,63,71,53,64,5.0,0,54,Rural,Data Analyst,80773,1 +104399,Male,39,Masters,1,12,53,88,0,7.0,7,80,Urban,HR Executive,58478,0 +104400,Male,44,Bachelors,1,61,1,26,36,2.0,7,86,Urban,HR Executive,138011,0 +104401,Female,32,Masters,11,36,25,10,75,2.0,0,68,Semi-Urban,Manager,74125,0 +104402,Male,54,Diploma,17,40,30,84,9,7.0,7,13,Semi-Urban,Data Analyst,120346,0 +104403,Male,31,High School,6,78,14,19,78,5.0,2,14,Urban,ML Engineer,88033,0 +104404,Female,53,Diploma,19,12,50,83,53,4.0,7,71,Semi-Urban,Manager,49447,0 +104405,Male,36,Diploma,19,98,11,32,99,2.0,4,6,Rural,ML Engineer,40567,0 +104406,Female,53,Masters,7,81,84,65,88,4.0,7,70,Urban,ML Engineer,42248,1 +104407,Male,28,Diploma,17,89,95,10,50,2.0,6,5,Semi-Urban,HR Executive,100901,0 +104408,Male,25,Bachelors,4,41,2,95,9,5.0,2,17,Rural,HR Executive,139803,0 +104409,Male,29,Masters,6,82,41,14,94,1.0,5,10,Urban,Software Engineer,104770,0 +104410,Male,34,High School,3,93,64,48,82,8.0,0,58,Urban,Manager,132924,1 +104411,Female,39,Bachelors,4,21,42,6,54,5.0,3,61,Urban,Data Analyst,122940,0 +104412,Male,47,PhD,11,54,21,83,17,1.0,2,30,Urban,Software Engineer,52201,0 +104413,Other,34,High School,9,34,36,67,47,7.0,4,85,Urban,Software Engineer,58377,0 +104414,Female,32,Masters,16,37,12,12,77,1.0,2,88,Urban,HR Executive,62663,0 +104415,Male,50,Bachelors,8,48,77,54,17,2.0,3,75,Urban,Manager,111808,1 +104416,Male,24,Masters,16,82,96,27,41,7.0,5,63,Urban,Data Analyst,88944,1 +104417,Other,49,Masters,19,11,70,86,27,7.0,5,40,Urban,HR Executive,36825,0 +104418,Female,48,Bachelors,1,19,7,82,72,2.0,7,37,Rural,Software Engineer,129545,0 +104419,Female,26,Diploma,19,91,95,49,79,1.0,3,0,Semi-Urban,ML Engineer,46029,0 +104420,Male,57,High School,5,68,80,53,54,1.0,5,22,Urban,ML Engineer,68073,0 +104421,Male,32,Bachelors,12,26,20,99,60,8.0,5,66,Semi-Urban,HR Executive,22207,0 +104422,Other,38,Masters,3,20,68,3,42,1.0,1,85,Rural,HR Executive,61795,0 +104423,Female,56,Bachelors,15,96,5,46,48,2.0,6,45,Semi-Urban,ML Engineer,94109,0 +104424,Male,41,PhD,11,25,54,53,87,2.0,0,7,Rural,ML Engineer,84936,0 +104425,Female,35,Bachelors,1,24,47,76,81,1.0,4,22,Urban,Manager,128423,0 +104426,Male,39,Diploma,17,86,64,41,57,0.0,0,28,Rural,ML Engineer,20170,0 +104427,Male,55,Masters,16,46,50,47,43,0.0,0,15,Urban,Software Engineer,22466,0 +104428,Female,24,Diploma,11,59,3,94,9,1.0,3,27,Semi-Urban,Software Engineer,113094,0 +104429,Male,40,Masters,17,19,6,59,66,4.0,2,31,Urban,Manager,46066,0 +104430,Male,58,High School,5,70,98,77,61,6.0,3,24,Semi-Urban,HR Executive,122773,1 +104431,Female,29,Bachelors,7,79,36,80,75,2.0,6,15,Urban,Software Engineer,140984,0 +104432,Male,39,Bachelors,5,45,45,54,81,2.0,6,94,Rural,Software Engineer,88370,1 +104433,Male,56,PhD,14,56,10,55,72,3.0,0,55,Urban,HR Executive,90516,0 +104434,Female,44,Bachelors,15,35,52,38,15,7.0,1,23,Urban,Manager,65871,0 +104435,Male,27,Bachelors,13,8,44,2,10,4.0,0,43,Urban,ML Engineer,117883,0 +104436,Female,41,Masters,19,86,40,18,24,2.0,6,27,Urban,Software Engineer,91491,0 +104437,Male,34,High School,11,38,49,47,40,7.0,7,38,Rural,Manager,128689,0 +104438,Male,45,Masters,3,66,20,31,25,5.0,4,9,Semi-Urban,Data Analyst,55674,0 +104439,Male,55,Diploma,7,12,10,17,90,3.0,5,83,Semi-Urban,Manager,117390,0 +104440,Male,31,Bachelors,12,33,34,89,90,2.0,6,54,Semi-Urban,Data Analyst,46028,0 +104441,Male,29,Bachelors,6,74,30,69,88,7.0,4,61,Urban,Manager,67783,0 +104442,Male,29,Bachelors,16,47,23,89,68,3.0,1,95,Urban,HR Executive,143614,1 +104443,Male,35,Masters,3,40,28,51,23,3.0,7,73,Urban,Manager,58341,0 +104444,Female,29,High School,14,53,24,93,67,7.0,7,10,Semi-Urban,Manager,29354,0 +104445,Male,24,Bachelors,9,11,73,8,28,3.0,3,42,Urban,Data Analyst,97111,0 +104446,Female,42,Masters,9,25,85,83,71,8.0,7,49,Rural,Software Engineer,58644,1 +104447,Female,43,Bachelors,12,50,59,68,15,4.0,3,17,Rural,HR Executive,50560,0 +104448,Female,30,PhD,9,77,97,52,55,6.0,6,70,Urban,ML Engineer,66444,1 +104449,Male,46,Masters,2,94,80,41,3,0.0,4,73,Rural,Manager,61352,1 +104450,Male,27,Diploma,13,73,38,74,95,1.0,6,69,Urban,ML Engineer,69491,1 +104451,Female,26,Masters,3,10,38,48,99,3.0,6,27,Semi-Urban,Data Analyst,94427,0 +104452,Male,48,Bachelors,1,76,79,63,57,9.0,7,66,Rural,Data Analyst,108845,1 +104453,Female,35,Bachelors,19,68,44,49,36,6.0,2,32,Semi-Urban,ML Engineer,144803,0 +104454,Male,24,Bachelors,7,20,22,89,70,7.0,3,33,Semi-Urban,Data Analyst,84719,0 +104455,Female,31,Masters,5,54,55,48,69,1.0,4,34,Semi-Urban,Software Engineer,35528,0 +104456,Male,44,Bachelors,16,65,95,10,21,0.0,5,5,Rural,Software Engineer,51582,0 +104457,Female,40,Bachelors,13,92,58,45,19,9.0,2,84,Semi-Urban,Data Analyst,96153,1 +104458,Male,53,Bachelors,5,43,2,48,27,8.0,2,2,Urban,Manager,23837,0 +104459,Other,23,High School,3,54,30,38,22,4.0,2,61,Semi-Urban,Manager,115357,0 +104460,Female,53,Masters,14,79,39,15,99,1.0,5,44,Semi-Urban,Manager,21138,0 +104461,Male,26,Masters,10,78,68,37,52,2.0,5,17,Urban,HR Executive,118760,0 +104462,Female,49,Bachelors,17,94,31,63,69,9.0,7,61,Rural,Software Engineer,45306,1 +104463,Male,40,High School,3,38,89,25,89,6.0,4,87,Semi-Urban,Manager,136823,1 +104464,Male,30,Masters,10,24,44,85,24,3.0,0,80,Urban,Data Analyst,108539,0 +104465,Male,42,Diploma,19,7,71,75,18,0.0,6,87,Semi-Urban,ML Engineer,144887,1 +104466,Male,41,PhD,8,43,86,1,86,4.0,6,79,Rural,Software Engineer,110271,0 +104467,Female,45,Masters,19,77,41,95,63,5.0,2,47,Rural,Manager,96416,1 +104468,Male,30,Masters,9,34,55,81,94,1.0,0,29,Rural,Manager,20964,0 +104469,Female,50,High School,14,13,51,50,32,5.0,7,87,Urban,ML Engineer,48677,0 +104470,Male,39,High School,12,23,94,79,71,2.0,5,51,Urban,Software Engineer,28162,1 +104471,Male,47,Bachelors,17,1,12,14,35,1.0,2,52,Urban,Data Analyst,43623,0 +104472,Female,35,Bachelors,9,43,23,55,17,8.0,5,68,Urban,Manager,116583,0 +104473,Other,55,Bachelors,18,73,43,41,58,7.0,4,50,Semi-Urban,Manager,141276,0 +104474,Female,29,Masters,3,9,17,1,39,7.0,6,15,Urban,Data Analyst,48946,0 +104475,Male,50,High School,9,6,72,64,27,5.0,1,85,Urban,Software Engineer,32696,0 +104476,Male,29,Bachelors,10,99,81,43,99,2.0,1,34,Semi-Urban,HR Executive,63389,1 +104477,Other,50,Bachelors,6,49,60,84,32,6.0,7,67,Semi-Urban,Software Engineer,69838,1 +104478,Male,31,Bachelors,17,28,44,70,21,3.0,3,2,Semi-Urban,Data Analyst,94585,0 +104479,Male,29,Bachelors,5,28,55,76,29,1.0,2,71,Urban,HR Executive,29639,0 +104480,Female,52,Bachelors,7,49,65,35,88,7.0,1,29,Urban,HR Executive,79783,0 +104481,Male,45,Masters,0,46,2,23,30,8.0,3,84,Urban,Software Engineer,36862,0 +104482,Male,45,Bachelors,6,67,58,61,33,8.0,7,26,Urban,HR Executive,128055,0 +104483,Female,38,High School,6,19,65,52,44,9.0,3,14,Urban,Manager,66098,0 +104484,Male,36,Diploma,1,36,6,55,52,0.0,5,89,Rural,Data Analyst,59955,0 +104485,Female,43,Bachelors,10,68,1,55,56,6.0,6,18,Semi-Urban,ML Engineer,96772,0 +104486,Female,43,Diploma,6,51,67,69,32,1.0,5,35,Urban,Data Analyst,101047,0 +104487,Female,33,Diploma,18,5,63,82,75,2.0,6,63,Urban,ML Engineer,145010,0 +104488,Male,44,Bachelors,12,14,58,39,35,7.0,1,13,Semi-Urban,ML Engineer,115994,0 +104489,Male,34,Diploma,13,3,19,74,89,9.0,4,96,Rural,Software Engineer,64246,0 +104490,Male,30,Diploma,2,53,1,15,62,3.0,3,97,Urban,Data Analyst,59526,0 +104491,Male,47,Masters,12,0,23,85,42,2.0,5,15,Semi-Urban,ML Engineer,77191,0 +104492,Female,24,Bachelors,1,40,39,38,3,1.0,6,11,Urban,HR Executive,23858,0 +104493,Male,31,Masters,3,60,55,41,16,7.0,3,92,Urban,Software Engineer,65187,1 +104494,Female,42,High School,17,52,65,8,73,7.0,4,85,Semi-Urban,Data Analyst,58299,0 +104495,Female,49,Bachelors,12,22,86,4,9,2.0,0,15,Urban,HR Executive,93562,0 +104496,Male,28,Bachelors,15,16,8,3,57,7.0,4,46,Urban,ML Engineer,144158,0 +104497,Female,54,PhD,8,52,31,9,69,5.0,6,86,Urban,Software Engineer,121621,0 +104498,Other,31,Diploma,1,34,3,10,29,7.0,2,95,Urban,Manager,78378,0 +104499,Male,58,Bachelors,9,54,6,45,69,0.0,1,37,Urban,ML Engineer,120197,0 +104500,Female,58,Diploma,4,26,91,91,41,2.0,4,4,Urban,HR Executive,52817,0 +104501,Male,23,Bachelors,15,24,46,43,50,2.0,2,51,Rural,Data Analyst,43509,0 +104502,Other,35,High School,18,61,52,5,61,7.0,4,80,Semi-Urban,Software Engineer,43535,0 +104503,Female,27,Diploma,0,58,31,51,62,7.0,3,83,Semi-Urban,Software Engineer,124150,0 +104504,Male,36,High School,10,42,84,54,42,9.0,3,56,Urban,Manager,45078,1 +104505,Male,30,Masters,5,9,40,27,20,3.0,3,81,Urban,Manager,93908,0 +104506,Female,21,Diploma,13,0,60,71,20,6.0,7,13,Rural,Data Analyst,134226,0 +104507,Male,24,Bachelors,8,56,19,89,28,7.0,6,61,Urban,ML Engineer,47453,0 +104508,Male,28,Diploma,4,96,46,11,84,0.0,2,5,Urban,Manager,144223,0 +104509,Male,25,PhD,5,59,81,47,53,1.0,2,31,Urban,ML Engineer,32652,0 +104510,Female,47,Masters,6,18,39,13,73,9.0,7,57,Semi-Urban,Data Analyst,123802,0 +104511,Male,25,PhD,14,3,10,9,28,5.0,4,38,Urban,Manager,101196,0 +104512,Male,57,PhD,16,73,23,57,14,5.0,0,29,Urban,ML Engineer,76521,0 +104513,Male,49,Diploma,12,58,4,64,7,1.0,3,79,Urban,Data Analyst,22875,0 +104514,Male,35,Bachelors,14,29,61,55,77,6.0,6,65,Urban,Software Engineer,127695,0 +104515,Male,34,Bachelors,10,0,35,79,60,7.0,0,27,Urban,HR Executive,101060,0 +104516,Male,37,Bachelors,4,87,94,36,58,4.0,4,57,Urban,HR Executive,88194,1 +104517,Male,41,Bachelors,8,80,37,96,81,7.0,3,0,Urban,ML Engineer,34079,0 +104518,Male,37,Bachelors,2,65,54,49,64,7.0,0,75,Semi-Urban,HR Executive,121547,1 +104519,Male,43,PhD,11,55,46,9,2,0.0,2,4,Urban,Data Analyst,68858,0 +104520,Male,21,Bachelors,17,6,69,43,46,1.0,7,28,Urban,Software Engineer,130497,0 +104521,Male,26,High School,0,78,61,55,24,5.0,2,90,Semi-Urban,Software Engineer,37871,1 +104522,Male,25,High School,2,6,32,62,41,0.0,5,27,Urban,Manager,53538,0 +104523,Male,28,Diploma,10,86,4,59,55,4.0,4,84,Rural,HR Executive,143623,0 +104524,Female,35,Diploma,5,60,71,83,96,1.0,6,34,Rural,Data Analyst,78064,1 +104525,Male,22,Bachelors,2,82,36,78,46,0.0,6,3,Semi-Urban,ML Engineer,101240,0 +104526,Male,54,Masters,12,17,76,0,44,3.0,2,82,Urban,Manager,93138,0 +104527,Female,37,Bachelors,10,19,20,19,71,4.0,7,74,Urban,Software Engineer,88649,0 +104528,Male,48,High School,12,96,74,22,53,8.0,3,1,Urban,HR Executive,122970,0 +104529,Male,58,Bachelors,12,67,3,11,60,3.0,4,4,Urban,Manager,86860,0 +104530,Female,48,High School,15,7,50,90,86,3.0,3,40,Rural,HR Executive,58552,0 +104531,Female,50,Masters,16,20,49,5,66,7.0,3,70,Urban,Manager,119533,0 +104532,Female,55,Bachelors,2,83,58,78,32,8.0,2,53,Rural,ML Engineer,46414,1 +104533,Female,48,Bachelors,9,47,83,21,23,0.0,5,90,Rural,Data Analyst,81685,1 +104534,Female,59,Bachelors,4,3,1,99,9,5.0,0,42,Urban,ML Engineer,98232,0 +104535,Female,38,Masters,0,88,52,23,68,5.0,4,6,Rural,Data Analyst,76077,0 +104536,Male,27,Masters,18,45,61,29,83,3.0,0,7,Semi-Urban,Software Engineer,40121,0 +104537,Female,51,Bachelors,16,18,87,78,16,0.0,0,28,Urban,HR Executive,149290,0 +104538,Female,34,Masters,2,92,0,4,64,8.0,2,90,Semi-Urban,HR Executive,76140,0 +104539,Male,24,Bachelors,6,3,72,23,87,8.0,4,60,Semi-Urban,Software Engineer,20263,0 +104540,Other,50,Diploma,8,79,21,75,82,4.0,5,39,Urban,Software Engineer,39937,0 +104541,Female,47,High School,15,94,59,31,37,1.0,7,66,Rural,Software Engineer,125224,1 +104542,Female,52,Bachelors,14,68,40,11,96,2.0,6,9,Rural,Data Analyst,119295,0 +104543,Male,22,Diploma,6,58,99,78,11,9.0,5,27,Urban,Software Engineer,145545,1 +104544,Male,31,Bachelors,11,18,0,37,89,6.0,1,35,Urban,Manager,61369,0 +104545,Male,57,Bachelors,0,62,89,24,97,7.0,1,78,Urban,Manager,43255,1 +104546,Female,48,Masters,17,20,21,20,70,3.0,1,34,Urban,Software Engineer,141589,0 +104547,Male,25,Masters,11,58,77,81,32,0.0,4,23,Rural,Software Engineer,77229,1 +104548,Male,28,Bachelors,9,14,85,57,35,6.0,1,30,Semi-Urban,Software Engineer,90387,0 +104549,Female,41,Masters,8,67,60,30,95,6.0,7,18,Urban,ML Engineer,138392,0 +104550,Female,25,Bachelors,5,30,95,63,0,5.0,5,73,Semi-Urban,Software Engineer,105141,1 +104551,Female,48,Diploma,17,59,60,53,91,7.0,5,52,Rural,ML Engineer,135431,0 +104552,Female,42,Bachelors,0,57,55,11,19,7.0,0,53,Semi-Urban,Manager,137762,0 +104553,Male,23,Masters,11,60,29,63,66,0.0,2,11,Urban,Manager,58571,0 +104554,Male,55,Bachelors,5,21,39,85,67,4.0,7,30,Semi-Urban,Data Analyst,149691,0 +104555,Female,47,High School,4,81,7,18,16,0.0,5,95,Semi-Urban,ML Engineer,74671,0 +104556,Female,53,Bachelors,13,64,50,25,87,7.0,1,13,Rural,ML Engineer,36343,0 +104557,Male,54,Bachelors,8,87,60,13,64,4.0,5,31,Urban,Data Analyst,122971,0 +104558,Male,23,PhD,16,57,21,79,77,9.0,3,23,Urban,Data Analyst,79406,0 +104559,Female,48,Bachelors,8,70,1,20,74,1.0,4,79,Urban,Data Analyst,134522,0 +104560,Other,30,Bachelors,3,9,8,13,57,8.0,5,52,Urban,Manager,130949,0 +104561,Female,35,Masters,10,4,71,29,29,6.0,2,79,Urban,ML Engineer,67509,0 +104562,Male,45,High School,16,5,26,69,12,8.0,5,63,Urban,HR Executive,118221,0 +104563,Male,21,Bachelors,7,24,49,14,97,3.0,1,19,Urban,HR Executive,149005,0 +104564,Female,59,Diploma,0,17,78,38,54,6.0,1,41,Semi-Urban,Manager,120541,0 +104565,Male,50,Bachelors,12,19,82,58,60,8.0,5,52,Urban,ML Engineer,139480,0 +104566,Female,39,Bachelors,6,97,0,15,21,0.0,3,57,Semi-Urban,Manager,124941,0 +104567,Male,21,Diploma,14,67,59,69,83,1.0,4,3,Urban,Data Analyst,131497,0 +104568,Male,23,Masters,7,7,42,33,90,9.0,7,83,Semi-Urban,Software Engineer,101338,0 +104569,Female,21,Bachelors,15,62,26,25,99,5.0,6,57,Urban,HR Executive,100759,0 +104570,Male,53,Bachelors,17,24,30,84,4,2.0,2,71,Semi-Urban,HR Executive,34733,0 +104571,Other,29,Diploma,2,15,83,99,70,8.0,0,46,Semi-Urban,Manager,141449,1 +104572,Male,29,High School,9,62,12,91,48,7.0,5,18,Semi-Urban,Data Analyst,134879,0 +104573,Male,42,PhD,14,55,28,83,24,6.0,6,48,Urban,Manager,149973,0 +104574,Male,42,High School,3,30,85,54,49,4.0,7,16,Urban,Manager,124311,0 +104575,Male,37,Masters,4,27,7,26,91,4.0,7,28,Semi-Urban,ML Engineer,31454,0 +104576,Male,35,Bachelors,8,1,41,85,46,8.0,1,85,Rural,HR Executive,93409,0 +104577,Male,21,Masters,19,6,48,28,23,1.0,6,32,Rural,HR Executive,100599,0 +104578,Female,37,High School,4,55,1,12,51,7.0,7,10,Rural,HR Executive,49042,0 +104579,Female,35,Masters,17,28,37,15,65,8.0,6,96,Urban,ML Engineer,95640,0 +104580,Male,33,High School,10,21,54,11,92,6.0,4,5,Urban,ML Engineer,50882,0 +104581,Female,58,High School,7,41,73,19,90,4.0,4,5,Urban,Manager,134222,0 +104582,Male,52,High School,11,6,37,22,53,9.0,1,87,Urban,Data Analyst,107023,0 +104583,Male,40,Bachelors,17,59,75,8,18,9.0,6,18,Urban,HR Executive,64598,0 +104584,Male,39,Diploma,17,6,79,9,98,1.0,1,16,Rural,HR Executive,77514,0 +104585,Male,28,Bachelors,12,13,8,53,38,9.0,7,41,Urban,Manager,60887,0 +104586,Male,50,High School,14,52,70,5,51,7.0,2,55,Urban,ML Engineer,80214,0 +104587,Male,29,Masters,18,24,75,13,2,6.0,0,86,Rural,Manager,86607,0 +104588,Female,43,Bachelors,18,9,74,11,6,6.0,6,68,Urban,Software Engineer,21454,0 +104589,Male,33,High School,13,31,36,82,35,5.0,6,72,Semi-Urban,Data Analyst,130714,0 +104590,Female,52,Bachelors,7,45,12,89,34,5.0,1,67,Urban,ML Engineer,78142,0 +104591,Male,51,PhD,6,2,0,98,21,5.0,1,47,Rural,Data Analyst,125729,0 +104592,Female,38,PhD,3,94,35,81,2,0.0,4,97,Semi-Urban,Software Engineer,41057,1 +104593,Female,57,Masters,15,17,44,17,62,1.0,3,78,Semi-Urban,Data Analyst,36978,0 +104594,Male,29,High School,3,66,91,28,90,1.0,3,46,Semi-Urban,HR Executive,33126,0 +104595,Female,54,Masters,5,14,7,16,87,2.0,7,54,Semi-Urban,Software Engineer,139619,0 +104596,Male,37,High School,9,27,4,92,36,8.0,5,20,Rural,Software Engineer,46306,0 +104597,Female,56,Bachelors,4,18,58,74,31,4.0,3,3,Rural,Data Analyst,64659,0 +104598,Female,52,Masters,17,87,13,65,37,3.0,7,50,Urban,HR Executive,45318,0 +104599,Male,22,Masters,12,65,51,18,90,0.0,5,38,Semi-Urban,Software Engineer,103763,0 +104600,Female,28,PhD,3,25,29,84,41,0.0,6,29,Urban,Manager,81119,0 +104601,Female,38,Bachelors,3,1,43,62,93,3.0,0,41,Urban,Software Engineer,21733,0 +104602,Female,55,Diploma,0,48,23,18,70,6.0,0,58,Semi-Urban,ML Engineer,77065,0 +104603,Male,51,Bachelors,6,7,72,81,41,7.0,0,25,Urban,Software Engineer,107171,0 +104604,Female,51,High School,1,57,54,45,87,3.0,6,30,Rural,Data Analyst,68455,0 +104605,Female,44,PhD,16,39,23,46,63,5.0,3,31,Semi-Urban,Data Analyst,20935,0 +104606,Male,35,High School,9,50,45,21,33,6.0,4,11,Semi-Urban,Software Engineer,133874,0 +104607,Male,29,High School,15,99,0,44,48,8.0,2,48,Urban,Manager,32133,0 +104608,Male,53,Bachelors,5,6,12,95,59,3.0,1,85,Urban,Software Engineer,121309,0 +104609,Male,41,Bachelors,16,1,92,28,58,7.0,7,66,Urban,ML Engineer,73389,0 +104610,Female,36,Bachelors,16,60,97,46,30,7.0,6,10,Urban,Manager,115273,0 +104611,Female,27,Masters,0,99,22,0,48,5.0,2,66,Urban,HR Executive,70112,0 +104612,Male,59,High School,11,28,76,71,36,5.0,7,75,Urban,Manager,96010,1 +104613,Female,43,Bachelors,1,26,97,28,83,7.0,7,47,Urban,Software Engineer,29002,0 +104614,Female,56,Bachelors,7,66,45,77,58,5.0,6,72,Urban,Data Analyst,126614,1 +104615,Male,59,Bachelors,6,72,68,39,49,1.0,7,48,Urban,Data Analyst,107264,0 +104616,Male,54,PhD,19,3,46,67,86,8.0,1,48,Semi-Urban,Manager,66229,0 +104617,Female,45,Bachelors,1,69,74,4,0,9.0,3,24,Urban,Manager,83229,0 +104618,Other,23,High School,5,77,93,62,74,7.0,7,64,Urban,ML Engineer,23835,1 +104619,Male,58,PhD,13,83,85,1,54,5.0,4,61,Urban,Manager,68273,0 +104620,Female,28,PhD,10,59,90,51,50,6.0,3,29,Semi-Urban,Software Engineer,41213,0 +104621,Male,56,High School,19,98,2,61,69,5.0,1,97,Urban,Data Analyst,116262,1 +104622,Male,44,High School,19,19,39,96,9,6.0,6,67,Urban,Manager,51240,0 +104623,Male,43,Bachelors,10,66,41,20,87,0.0,5,86,Semi-Urban,Data Analyst,72438,0 +104624,Female,50,Bachelors,3,0,45,70,25,5.0,4,81,Urban,ML Engineer,49351,0 +104625,Male,23,Bachelors,19,43,46,89,62,5.0,4,19,Urban,HR Executive,25216,0 +104626,Female,56,Diploma,9,15,12,28,16,6.0,1,1,Rural,HR Executive,30504,0 +104627,Male,41,Bachelors,6,26,83,21,91,1.0,7,28,Semi-Urban,Data Analyst,56591,0 +104628,Male,24,Bachelors,15,70,47,76,76,8.0,5,60,Urban,Software Engineer,36231,1 +104629,Female,31,Bachelors,7,94,72,44,76,5.0,7,91,Urban,Software Engineer,147165,1 +104630,Male,53,Diploma,10,74,62,7,16,8.0,6,62,Urban,ML Engineer,38646,0 +104631,Male,22,Bachelors,19,98,39,18,6,2.0,0,4,Urban,Software Engineer,133338,0 +104632,Female,57,Bachelors,17,80,4,79,15,5.0,7,95,Semi-Urban,Software Engineer,146474,1 +104633,Female,24,Diploma,18,45,52,70,68,5.0,1,64,Rural,ML Engineer,57167,0 +104634,Female,47,Diploma,5,21,13,32,57,6.0,4,73,Urban,ML Engineer,103959,0 +104635,Male,46,High School,6,17,20,6,18,4.0,5,97,Semi-Urban,Software Engineer,141394,0 +104636,Female,26,Masters,15,80,51,72,46,6.0,2,1,Urban,ML Engineer,79383,0 +104637,Female,43,Bachelors,8,34,78,69,12,2.0,7,72,Semi-Urban,Software Engineer,109944,1 +104638,Male,38,High School,10,0,30,15,32,4.0,7,68,Semi-Urban,Software Engineer,98027,0 +104639,Male,34,Bachelors,8,79,79,82,17,1.0,2,64,Urban,HR Executive,146264,1 +104640,Female,26,Masters,14,87,96,46,78,1.0,7,96,Semi-Urban,Data Analyst,64853,1 +104641,Female,38,Bachelors,12,33,62,44,26,9.0,7,35,Urban,ML Engineer,45775,0 +104642,Male,36,Masters,4,24,18,27,84,7.0,6,96,Semi-Urban,Data Analyst,108956,0 +104643,Female,42,High School,1,25,69,64,16,6.0,2,2,Urban,ML Engineer,42493,0 +104644,Male,34,Bachelors,17,56,28,48,98,4.0,7,81,Rural,Software Engineer,122672,0 +104645,Female,24,Bachelors,18,31,27,35,55,5.0,1,90,Urban,Data Analyst,49303,0 +104646,Female,23,Masters,6,25,98,71,35,3.0,3,28,Urban,ML Engineer,72121,0 +104647,Female,53,High School,12,77,78,21,31,4.0,2,57,Rural,ML Engineer,101885,0 +104648,Other,34,Bachelors,6,57,55,2,81,3.0,0,32,Semi-Urban,Manager,61749,0 +104649,Female,54,Bachelors,13,95,15,76,83,3.0,0,6,Rural,HR Executive,38345,0 +104650,Male,53,Diploma,6,75,24,15,92,9.0,7,16,Urban,HR Executive,77078,0 +104651,Male,39,Bachelors,7,97,4,32,66,5.0,5,15,Rural,Data Analyst,139139,0 +104652,Male,22,Bachelors,11,26,67,53,81,1.0,7,46,Urban,Software Engineer,148703,0 +104653,Male,39,High School,15,73,41,36,26,2.0,3,44,Urban,HR Executive,46263,0 +104654,Male,47,High School,7,51,73,19,55,6.0,1,66,Urban,HR Executive,79496,0 +104655,Female,21,Bachelors,7,58,9,43,26,1.0,2,81,Semi-Urban,Data Analyst,55239,0 +104656,Female,35,High School,8,47,85,52,38,3.0,0,67,Rural,Data Analyst,59204,1 +104657,Female,52,Masters,17,89,76,72,58,6.0,6,39,Semi-Urban,ML Engineer,27604,1 +104658,Male,52,Bachelors,2,60,95,14,76,9.0,7,79,Urban,Software Engineer,135936,1 +104659,Male,31,Bachelors,16,42,14,18,64,5.0,3,31,Urban,Software Engineer,132205,0 +104660,Male,35,High School,0,1,10,18,77,5.0,4,88,Rural,ML Engineer,142122,0 +104661,Male,22,Bachelors,1,43,97,56,45,1.0,7,80,Urban,ML Engineer,136493,1 +104662,Male,23,Diploma,3,98,20,49,78,2.0,3,77,Urban,HR Executive,22787,1 +104663,Male,35,Diploma,11,63,73,97,31,3.0,7,29,Urban,HR Executive,84543,1 +104664,Female,35,Masters,11,92,79,91,17,5.0,0,30,Urban,HR Executive,39850,1 +104665,Male,34,Bachelors,2,35,25,76,91,0.0,4,7,Rural,Data Analyst,32595,0 +104666,Female,32,PhD,18,69,87,51,7,7.0,5,55,Urban,Manager,127189,1 +104667,Male,48,Masters,2,34,65,41,29,0.0,0,37,Semi-Urban,ML Engineer,60181,0 +104668,Female,34,Bachelors,3,95,79,13,67,1.0,2,17,Urban,HR Executive,58613,0 +104669,Male,50,Bachelors,12,86,7,68,19,2.0,7,67,Urban,ML Engineer,123258,0 +104670,Female,30,Masters,19,1,98,41,27,5.0,7,37,Urban,Manager,83097,0 +104671,Female,45,Bachelors,1,22,75,66,98,8.0,4,58,Urban,HR Executive,27372,0 +104672,Female,34,Bachelors,9,44,93,40,48,7.0,2,93,Urban,Software Engineer,25158,1 +104673,Male,48,Diploma,6,77,12,94,51,4.0,5,28,Semi-Urban,ML Engineer,56987,0 +104674,Male,51,High School,2,78,57,78,43,5.0,5,42,Semi-Urban,ML Engineer,75301,1 +104675,Male,42,Masters,16,82,98,51,6,5.0,0,91,Urban,HR Executive,135133,1 +104676,Female,28,High School,16,90,31,70,89,8.0,4,46,Urban,Data Analyst,136223,0 +104677,Male,50,Bachelors,0,99,86,90,28,4.0,3,73,Urban,ML Engineer,20764,1 +104678,Male,22,Masters,12,35,14,68,91,0.0,3,46,Semi-Urban,HR Executive,69331,0 +104679,Male,27,High School,18,60,23,97,53,6.0,2,68,Rural,HR Executive,139361,1 +104680,Male,29,Masters,10,93,42,53,2,0.0,6,45,Urban,Manager,124288,0 +104681,Male,41,Bachelors,8,68,25,70,32,5.0,2,36,Urban,HR Executive,129000,0 +104682,Male,38,Bachelors,16,50,90,95,86,1.0,0,81,Urban,HR Executive,64095,1 +104683,Male,46,PhD,4,33,56,91,30,4.0,0,64,Semi-Urban,Software Engineer,54650,1 +104684,Male,43,PhD,12,92,70,43,28,6.0,1,32,Rural,HR Executive,35605,1 +104685,Female,30,Masters,15,90,59,96,78,6.0,0,57,Urban,Software Engineer,135289,1 +104686,Male,36,Bachelors,9,12,61,55,94,6.0,0,98,Urban,ML Engineer,94853,0 +104687,Male,26,High School,8,31,45,82,4,2.0,6,88,Semi-Urban,ML Engineer,133078,1 +104688,Female,51,Masters,17,23,66,95,66,9.0,3,3,Urban,ML Engineer,78518,0 +104689,Male,23,Masters,15,80,32,31,15,6.0,5,52,Urban,ML Engineer,141016,0 +104690,Male,52,Bachelors,13,13,2,99,97,9.0,4,72,Semi-Urban,ML Engineer,96979,0 +104691,Male,54,Masters,12,97,55,26,75,8.0,2,75,Rural,Manager,145228,1 +104692,Male,32,Bachelors,14,87,97,93,49,9.0,2,57,Urban,HR Executive,91504,1 +104693,Female,22,Bachelors,14,0,88,60,90,7.0,5,10,Semi-Urban,Manager,115584,0 +104694,Male,49,High School,1,91,95,78,61,5.0,0,60,Urban,Data Analyst,111297,1 +104695,Male,49,Diploma,8,49,0,96,82,9.0,3,7,Urban,Data Analyst,55358,0 +104696,Male,43,Bachelors,0,17,17,85,11,9.0,6,94,Urban,Manager,113355,0 +104697,Male,24,Diploma,8,4,99,5,36,4.0,1,88,Urban,Data Analyst,98958,0 +104698,Male,40,High School,4,11,27,84,73,8.0,6,89,Rural,HR Executive,96742,0 +104699,Male,27,Bachelors,4,99,77,6,70,9.0,2,78,Urban,Software Engineer,136846,1 +104700,Female,26,Bachelors,1,93,33,59,3,5.0,3,11,Semi-Urban,Manager,88891,0 +104701,Male,50,High School,19,9,26,66,18,8.0,3,37,Urban,Data Analyst,106251,0 +104702,Female,58,Bachelors,15,39,82,66,47,6.0,6,78,Urban,ML Engineer,149667,1 +104703,Female,26,Bachelors,12,94,20,63,76,1.0,3,26,Urban,Software Engineer,134254,0 +104704,Male,45,Bachelors,9,86,37,9,21,7.0,3,83,Urban,Manager,27338,0 +104705,Male,28,Diploma,17,89,29,56,93,0.0,0,35,Semi-Urban,ML Engineer,99177,0 +104706,Female,34,Bachelors,16,57,55,38,73,2.0,5,63,Rural,Software Engineer,115729,0 +104707,Male,55,Masters,10,10,46,81,47,0.0,0,23,Rural,Manager,105181,0 +104708,Female,26,Masters,19,12,30,62,44,0.0,2,45,Semi-Urban,Data Analyst,65284,0 +104709,Male,34,Bachelors,19,81,56,35,61,4.0,2,14,Urban,HR Executive,96217,0 +104710,Male,57,Diploma,10,2,63,8,35,8.0,5,84,Rural,Software Engineer,103782,0 +104711,Female,45,Diploma,8,82,8,90,55,7.0,7,48,Rural,Manager,125691,0 +104712,Female,44,PhD,7,0,44,33,68,7.0,7,98,Rural,Data Analyst,38357,0 +104713,Female,54,High School,17,85,16,42,2,3.0,3,41,Rural,Manager,133529,0 +104714,Male,26,Masters,18,36,17,62,26,1.0,5,67,Rural,Manager,52621,0 +104715,Female,45,Diploma,0,93,21,40,38,0.0,3,99,Urban,Manager,129278,1 +104716,Female,36,Diploma,6,74,93,70,63,6.0,0,49,Urban,HR Executive,142690,1 +104717,Male,52,High School,16,91,40,17,50,9.0,6,96,Urban,HR Executive,25745,1 +104718,Male,22,Diploma,17,1,37,11,6,8.0,4,94,Urban,ML Engineer,130118,0 +104719,Male,25,Masters,6,64,14,85,2,1.0,7,31,Semi-Urban,ML Engineer,65138,0 +104720,Male,39,High School,5,5,10,99,33,9.0,2,82,Urban,Data Analyst,48424,0 +104721,Male,53,Diploma,16,10,84,37,37,6.0,0,28,Urban,ML Engineer,135929,0 +104722,Male,53,Diploma,18,51,28,31,67,9.0,3,13,Urban,ML Engineer,84806,0 +104723,Male,45,PhD,5,4,5,86,29,6.0,4,94,Urban,Data Analyst,118566,0 +104724,Male,53,Diploma,1,2,10,69,37,6.0,7,63,Urban,Data Analyst,23321,0 +104725,Female,49,High School,1,75,25,55,5,9.0,2,67,Rural,Data Analyst,132954,0 +104726,Male,39,Diploma,3,15,82,58,54,2.0,4,61,Rural,Data Analyst,28523,0 +104727,Female,51,Bachelors,14,29,53,77,0,2.0,5,89,Semi-Urban,ML Engineer,61498,1 +104728,Male,57,Diploma,15,90,61,67,25,0.0,3,70,Rural,Manager,90702,1 +104729,Male,29,Diploma,12,95,98,46,38,0.0,4,34,Urban,Manager,97420,1 +104730,Male,37,Bachelors,6,23,89,98,43,7.0,1,12,Urban,ML Engineer,109591,0 +104731,Male,53,Bachelors,4,24,93,6,64,9.0,1,45,Rural,ML Engineer,146603,0 +104732,Male,42,Masters,13,48,55,43,79,4.0,4,30,Rural,Software Engineer,119625,0 +104733,Female,59,Diploma,15,2,0,42,83,9.0,4,94,Rural,Manager,43373,0 +104734,Female,50,Diploma,5,77,48,6,7,5.0,1,93,Semi-Urban,Software Engineer,26954,0 +104735,Male,27,High School,9,89,42,81,74,3.0,5,17,Semi-Urban,Software Engineer,103851,0 +104736,Male,45,Bachelors,12,40,92,28,8,3.0,7,68,Urban,Manager,86366,0 +104737,Female,34,Bachelors,17,64,10,95,10,0.0,1,88,Rural,Manager,149070,1 +104738,Female,36,Bachelors,6,41,37,27,47,5.0,6,2,Urban,Software Engineer,144695,0 +104739,Female,31,Bachelors,1,48,34,4,52,3.0,1,62,Semi-Urban,ML Engineer,27150,0 +104740,Male,59,Bachelors,19,45,33,13,3,8.0,3,4,Urban,ML Engineer,133278,0 +104741,Male,35,Bachelors,5,27,99,74,92,8.0,0,71,Urban,ML Engineer,89378,1 +104742,Male,30,High School,7,38,53,24,67,4.0,2,57,Semi-Urban,Software Engineer,43389,0 +104743,Male,49,Bachelors,1,96,26,28,42,5.0,2,51,Rural,ML Engineer,38447,0 +104744,Female,46,Masters,18,0,92,18,86,8.0,2,56,Urban,Data Analyst,48519,0 +104745,Male,51,Bachelors,0,10,14,39,53,1.0,0,15,Semi-Urban,Data Analyst,58788,0 +104746,Female,38,High School,6,73,88,24,67,4.0,4,97,Urban,HR Executive,109476,1 +104747,Male,28,Diploma,14,10,75,29,5,4.0,0,30,Semi-Urban,ML Engineer,26802,0 +104748,Male,42,PhD,6,84,97,17,87,4.0,1,6,Urban,Manager,140083,0 +104749,Male,55,Diploma,6,74,35,46,38,4.0,6,5,Urban,Manager,28966,0 +104750,Male,29,Bachelors,3,5,2,40,64,0.0,0,71,Rural,HR Executive,127136,0 +104751,Male,35,Diploma,19,41,6,62,2,2.0,7,87,Rural,Data Analyst,31306,0 +104752,Female,52,Diploma,11,40,74,29,19,9.0,0,79,Urban,HR Executive,77789,0 +104753,Female,23,High School,11,59,23,63,88,2.0,5,75,Urban,Software Engineer,97622,0 +104754,Male,37,Diploma,14,24,51,50,38,8.0,5,24,Urban,HR Executive,148281,0 +104755,Male,58,Diploma,10,35,83,7,38,4.0,2,22,Semi-Urban,Data Analyst,140871,0 +104756,Male,48,Diploma,4,58,94,52,2,5.0,2,62,Urban,ML Engineer,39372,1 +104757,Male,44,High School,4,13,18,34,9,6.0,7,13,Semi-Urban,Software Engineer,119850,0 +104758,Male,42,Bachelors,5,94,18,73,23,1.0,4,77,Semi-Urban,ML Engineer,35654,1 +104759,Male,59,Bachelors,14,9,48,49,46,0.0,7,37,Urban,Manager,51930,0 +104760,Female,36,Masters,3,88,51,83,59,6.0,0,91,Urban,Data Analyst,130238,1 +104761,Female,59,Diploma,8,92,39,71,59,2.0,2,75,Urban,Data Analyst,42209,1 +104762,Male,31,Bachelors,7,69,63,23,92,9.0,1,82,Urban,ML Engineer,128446,1 +104763,Male,43,Masters,13,43,59,97,74,8.0,4,40,Rural,HR Executive,131642,1 +104764,Male,40,Bachelors,8,33,17,65,90,4.0,6,2,Urban,Data Analyst,94993,0 +104765,Male,32,Bachelors,5,5,44,98,80,8.0,3,9,Semi-Urban,Manager,81024,0 +104766,Female,46,Masters,9,56,83,55,32,5.0,4,26,Urban,Data Analyst,114209,0 +104767,Male,49,Diploma,9,31,92,21,35,4.0,6,25,Urban,Software Engineer,72602,0 +104768,Female,55,Bachelors,16,58,98,67,69,3.0,7,63,Urban,Data Analyst,57089,1 +104769,Female,37,Bachelors,8,73,26,0,65,6.0,5,43,Urban,Software Engineer,21930,0 +104770,Female,49,Diploma,14,58,21,78,44,3.0,1,82,Urban,Data Analyst,126599,0 +104771,Male,59,Diploma,14,34,36,18,84,4.0,3,2,Urban,Manager,78833,0 +104772,Male,37,Diploma,0,60,67,46,84,9.0,3,62,Semi-Urban,ML Engineer,75018,1 +104773,Male,35,Bachelors,17,47,93,27,42,9.0,6,48,Urban,Software Engineer,113957,0 +104774,Female,30,Bachelors,3,63,30,24,97,4.0,3,59,Semi-Urban,Manager,122639,0 +104775,Male,58,PhD,3,15,83,36,88,9.0,4,60,Urban,Data Analyst,34318,0 +104776,Male,38,Masters,12,63,54,50,14,6.0,6,10,Urban,ML Engineer,32956,0 +104777,Female,21,Masters,3,45,38,61,44,3.0,2,58,Semi-Urban,Manager,112656,0 +104778,Male,54,Diploma,16,33,19,83,77,9.0,0,28,Semi-Urban,HR Executive,68515,0 +104779,Male,52,Bachelors,12,13,34,81,76,8.0,7,29,Urban,Data Analyst,40198,0 +104780,Male,23,Bachelors,11,83,86,35,59,5.0,2,65,Urban,ML Engineer,57623,1 +104781,Male,44,Diploma,11,88,22,33,50,0.0,1,2,Urban,Manager,83302,0 +104782,Male,54,Masters,15,65,7,3,70,8.0,0,90,Rural,ML Engineer,26379,0 +104783,Other,42,Bachelors,19,35,22,72,92,8.0,5,73,Urban,Data Analyst,130770,0 +104784,Male,37,Bachelors,17,7,19,70,93,5.0,1,97,Urban,Software Engineer,79377,0 +104785,Female,22,High School,19,86,21,89,19,7.0,4,94,Semi-Urban,Manager,26772,1 +104786,Male,48,Masters,9,77,49,43,21,3.0,4,51,Rural,Software Engineer,25935,0 +104787,Male,48,Diploma,5,71,93,38,39,5.0,3,51,Semi-Urban,HR Executive,68771,1 +104788,Male,58,Bachelors,8,98,47,76,74,5.0,3,61,Semi-Urban,ML Engineer,122795,1 +104789,Female,51,High School,12,82,4,92,53,0.0,4,66,Semi-Urban,Manager,104459,1 +104790,Female,33,Bachelors,1,33,55,12,60,3.0,7,90,Urban,ML Engineer,121826,0 +104791,Male,52,Bachelors,17,87,23,85,12,1.0,0,52,Urban,Manager,22700,1 +104792,Male,38,Masters,15,70,48,76,1,4.0,2,52,Rural,Manager,149732,1 +104793,Female,51,Diploma,0,16,79,4,44,9.0,4,76,Urban,ML Engineer,55046,0 +104794,Male,36,Bachelors,12,12,67,52,53,9.0,2,41,Rural,ML Engineer,38281,0 +104795,Female,50,High School,8,22,85,46,90,4.0,4,98,Rural,Data Analyst,83495,1 +104796,Female,35,Bachelors,3,27,66,86,85,4.0,0,65,Urban,ML Engineer,125647,1 +104797,Male,32,High School,15,64,99,22,69,3.0,6,99,Rural,HR Executive,58410,1 +104798,Male,46,Bachelors,17,89,53,18,22,6.0,2,38,Urban,Data Analyst,108721,0 +104799,Male,21,Bachelors,1,22,77,9,3,1.0,2,72,Semi-Urban,Data Analyst,134567,0 +104800,Male,27,High School,7,28,26,17,68,1.0,2,31,Semi-Urban,Manager,57285,0 +104801,Male,50,High School,11,88,29,40,59,5.0,6,25,Semi-Urban,Manager,25842,0 +104802,Male,46,Diploma,19,10,56,66,49,8.0,6,31,Urban,Manager,116530,0 +104803,Male,41,Masters,4,12,15,90,32,5.0,4,7,Urban,ML Engineer,55282,0 +104804,Male,28,Masters,6,74,21,73,62,6.0,1,66,Semi-Urban,Manager,122815,0 +104805,Female,49,Bachelors,18,36,13,20,33,7.0,7,64,Rural,HR Executive,67976,0 +104806,Female,52,Diploma,9,52,7,58,78,3.0,6,53,Urban,Data Analyst,37087,0 +104807,Female,35,Bachelors,10,75,54,83,82,8.0,0,51,Urban,ML Engineer,80408,1 +104808,Male,56,Diploma,8,75,78,19,57,1.0,5,46,Urban,ML Engineer,42750,0 +104809,Female,47,Masters,14,27,58,80,20,0.0,4,89,Urban,Manager,113343,1 +104810,Female,39,High School,16,62,6,6,37,7.0,2,63,Semi-Urban,Data Analyst,37170,0 +104811,Male,51,Bachelors,17,21,92,90,18,6.0,2,36,Urban,HR Executive,124186,1 +104812,Male,31,Bachelors,3,81,61,54,25,7.0,4,14,Urban,Manager,77220,0 +104813,Male,29,High School,10,73,96,17,24,4.0,6,89,Urban,Data Analyst,108072,1 +104814,Male,46,PhD,8,72,69,74,77,3.0,6,98,Urban,Software Engineer,103997,1 +104815,Female,34,PhD,7,16,51,16,48,0.0,2,67,Semi-Urban,Software Engineer,145357,0 +104816,Male,21,Bachelors,18,20,2,36,19,0.0,4,14,Rural,ML Engineer,140657,0 +104817,Female,23,Bachelors,2,53,95,34,53,1.0,7,60,Semi-Urban,ML Engineer,117973,1 +104818,Female,34,Bachelors,5,18,97,85,5,1.0,6,78,Urban,HR Executive,112782,1 +104819,Male,54,Bachelors,13,64,98,64,50,2.0,3,68,Semi-Urban,Manager,69825,1 +104820,Male,55,Bachelors,6,16,71,89,85,5.0,7,53,Urban,Manager,43459,0 +104821,Female,54,PhD,18,22,63,30,6,6.0,3,99,Semi-Urban,HR Executive,105450,0 +104822,Male,24,Masters,1,10,5,6,18,1.0,6,26,Urban,Manager,31798,0 +104823,Male,51,High School,16,27,75,30,78,4.0,1,14,Semi-Urban,Software Engineer,59642,0 +104824,Female,46,Bachelors,15,59,85,14,53,9.0,0,94,Semi-Urban,Manager,38260,1 +104825,Male,23,Masters,17,15,9,38,50,1.0,3,35,Urban,HR Executive,82457,0 +104826,Female,32,Masters,10,18,20,94,11,8.0,0,72,Urban,Manager,95781,0 +104827,Male,44,High School,8,54,49,66,42,0.0,3,81,Semi-Urban,Manager,35783,1 +104828,Male,26,Diploma,4,82,63,22,51,5.0,6,58,Semi-Urban,Data Analyst,45344,0 +104829,Male,46,Masters,1,47,62,5,42,3.0,6,71,Rural,HR Executive,119191,0 +104830,Male,25,Diploma,2,13,68,85,7,8.0,2,89,Rural,Data Analyst,122252,1 +104831,Male,34,Bachelors,11,7,84,97,99,1.0,2,25,Semi-Urban,HR Executive,54118,0 +104832,Male,53,Bachelors,10,83,94,20,11,7.0,0,9,Urban,ML Engineer,142609,0 +104833,Male,52,High School,6,39,99,95,90,6.0,3,24,Semi-Urban,Data Analyst,123394,1 +104834,Male,22,PhD,10,90,79,52,56,2.0,6,1,Urban,Data Analyst,29109,0 +104835,Female,27,High School,14,95,21,70,37,4.0,3,95,Urban,Software Engineer,39787,1 +104836,Other,50,Bachelors,9,71,0,72,98,2.0,3,21,Semi-Urban,Manager,139227,0 +104837,Male,24,High School,1,15,26,85,54,6.0,1,98,Urban,Software Engineer,142432,0 +104838,Male,28,PhD,5,78,85,46,74,5.0,2,15,Urban,Manager,116160,0 +104839,Other,43,Bachelors,18,79,9,71,34,7.0,5,81,Urban,HR Executive,80055,0 +104840,Male,42,Masters,0,59,24,73,94,1.0,7,14,Urban,HR Executive,21210,0 +104841,Female,27,Bachelors,12,16,55,54,57,8.0,0,10,Urban,Software Engineer,20771,0 +104842,Female,25,Bachelors,14,91,26,4,59,2.0,1,8,Semi-Urban,Manager,89115,0 +104843,Male,27,Bachelors,16,93,40,67,39,8.0,6,5,Urban,Data Analyst,64156,0 +104844,Female,41,Bachelors,9,39,62,34,49,5.0,5,44,Urban,Manager,38806,0 +104845,Male,47,Diploma,18,50,29,67,20,7.0,3,58,Rural,ML Engineer,43059,0 +104846,Female,57,Diploma,0,56,97,74,88,0.0,0,52,Rural,HR Executive,71614,1 +104847,Male,54,Diploma,11,68,72,69,62,7.0,1,26,Urban,Manager,78244,1 +104848,Female,58,Diploma,3,47,76,53,30,4.0,7,54,Urban,ML Engineer,21171,0 +104849,Female,26,Bachelors,12,62,64,43,90,9.0,2,3,Urban,HR Executive,91830,0 +104850,Male,42,Bachelors,14,29,69,94,35,7.0,0,98,Urban,Software Engineer,76244,1 +104851,Male,42,High School,10,6,46,15,43,6.0,1,50,Rural,HR Executive,63516,0 +104852,Male,36,High School,9,42,24,4,4,6.0,3,64,Urban,Manager,65580,0 +104853,Female,40,Bachelors,1,78,78,81,1,6.0,3,89,Semi-Urban,Manager,32587,1 +104854,Male,29,Bachelors,11,81,97,38,40,3.0,2,61,Urban,Manager,93226,1 +104855,Male,55,Bachelors,8,91,81,79,88,7.0,3,46,Rural,Manager,45628,1 +104856,Male,27,Bachelors,16,47,18,21,96,7.0,0,22,Semi-Urban,ML Engineer,55625,0 +104857,Male,32,Masters,0,11,18,67,37,4.0,6,41,Urban,Manager,109904,0 +104858,Other,42,Diploma,15,11,41,78,22,1.0,3,87,Urban,Data Analyst,140229,0 +104859,Female,26,Bachelors,12,12,84,49,62,4.0,6,46,Urban,Software Engineer,57634,0 +104860,Male,22,Diploma,2,9,55,37,17,3.0,6,37,Urban,Software Engineer,64275,0 +104861,Female,51,Bachelors,14,87,68,59,17,9.0,3,7,Rural,HR Executive,58518,0 +104862,Other,46,Diploma,16,9,0,66,51,6.0,5,26,Semi-Urban,Manager,90024,0 +104863,Female,44,Bachelors,16,54,92,83,90,0.0,5,56,Rural,ML Engineer,22052,1 +104864,Male,57,Masters,19,15,7,40,67,9.0,4,90,Urban,ML Engineer,97891,0 +104865,Male,22,Bachelors,5,56,9,77,65,8.0,6,65,Urban,Manager,30089,0 +104866,Female,23,Bachelors,18,28,45,27,17,3.0,7,75,Semi-Urban,Software Engineer,28623,0 +104867,Male,41,High School,16,90,2,73,96,7.0,7,52,Urban,Software Engineer,69922,0 +104868,Male,24,Bachelors,5,10,81,14,31,1.0,7,82,Urban,HR Executive,121797,0 +104869,Male,30,Bachelors,3,51,41,38,1,6.0,5,20,Urban,ML Engineer,22287,0 +104870,Male,55,Bachelors,2,98,93,55,56,4.0,7,99,Rural,Manager,73062,1 +104871,Male,51,Masters,2,90,38,77,73,2.0,4,19,Urban,Data Analyst,21833,0 +104872,Male,51,Bachelors,9,80,5,18,3,8.0,7,92,Rural,Software Engineer,23568,0 +104873,Female,43,Bachelors,2,22,10,27,16,7.0,7,45,Urban,HR Executive,49485,0 +104874,Female,22,Bachelors,7,36,42,91,80,3.0,6,5,Urban,Software Engineer,143817,0 +104875,Female,25,Bachelors,11,31,7,22,59,2.0,4,22,Rural,Data Analyst,79753,0 +104876,Male,42,Bachelors,4,28,0,29,22,2.0,4,39,Rural,Manager,133838,0 +104877,Female,25,Bachelors,18,49,26,52,38,4.0,3,23,Rural,Data Analyst,130950,0 +104878,Male,42,High School,9,48,69,98,75,3.0,1,30,Urban,HR Executive,48713,1 +104879,Female,35,Bachelors,8,30,74,15,34,9.0,0,35,Semi-Urban,Manager,140337,0 +104880,Other,43,Bachelors,0,84,96,30,86,7.0,2,23,Urban,Data Analyst,38958,0 +104881,Female,27,Masters,12,66,35,25,28,1.0,7,37,Urban,HR Executive,21281,0 +104882,Female,36,Bachelors,15,36,74,77,37,5.0,6,18,Rural,ML Engineer,121817,0 +104883,Male,42,Diploma,18,29,35,49,77,8.0,4,69,Semi-Urban,Data Analyst,102882,0 +104884,Other,37,Bachelors,13,69,65,91,27,9.0,1,61,Urban,Software Engineer,142965,1 +104885,Female,35,Masters,3,47,48,94,98,8.0,7,77,Urban,Manager,55207,1 +104886,Female,36,Bachelors,6,89,54,23,5,0.0,6,52,Semi-Urban,Manager,53473,0 +104887,Male,52,Diploma,14,63,57,47,50,4.0,0,67,Urban,HR Executive,129904,0 +104888,Female,35,Bachelors,19,13,9,54,84,2.0,7,50,Urban,HR Executive,121461,0 +104889,Male,24,Bachelors,12,72,14,4,73,9.0,0,72,Urban,Data Analyst,44621,0 +104890,Female,42,High School,9,30,52,27,84,7.0,5,63,Rural,Data Analyst,90996,0 +104891,Male,45,Masters,11,89,90,92,29,2.0,1,90,Semi-Urban,Software Engineer,45447,1 +104892,Male,43,Bachelors,12,70,71,88,56,9.0,1,92,Semi-Urban,Data Analyst,86788,1 +104893,Male,22,High School,13,14,21,78,69,9.0,1,45,Urban,Software Engineer,79006,0 +104894,Other,42,High School,10,50,47,17,45,2.0,5,39,Urban,ML Engineer,141419,0 +104895,Female,25,High School,2,9,8,80,22,3.0,0,16,Rural,Manager,118006,0 +104896,Female,28,Diploma,7,80,60,8,57,6.0,4,25,Rural,Software Engineer,35768,0 +104897,Male,39,High School,11,50,93,48,59,0.0,3,6,Urban,Software Engineer,42549,0 +104898,Male,33,Bachelors,9,46,9,50,69,9.0,5,2,Rural,Manager,68479,0 +104899,Male,24,Bachelors,1,51,61,25,94,4.0,1,89,Semi-Urban,Manager,99504,0 +104900,Male,47,Diploma,14,68,19,16,93,6.0,3,61,Urban,Manager,102984,0 +104901,Female,23,Diploma,11,2,71,53,8,3.0,6,38,Semi-Urban,Data Analyst,27324,0 +104902,Other,58,High School,12,54,34,14,98,0.0,0,68,Urban,ML Engineer,28078,0 +104903,Female,44,Bachelors,17,86,75,44,22,1.0,3,5,Rural,Manager,26684,0 +104904,Female,33,PhD,4,93,81,27,50,8.0,1,50,Rural,Data Analyst,83604,1 +104905,Male,58,Bachelors,15,53,87,83,81,3.0,2,0,Urban,HR Executive,79063,0 +104906,Female,38,Bachelors,17,78,28,83,82,6.0,0,10,Semi-Urban,Software Engineer,59339,0 +104907,Female,39,Bachelors,18,32,23,12,99,8.0,2,15,Semi-Urban,Software Engineer,94174,0 +104908,Male,34,Bachelors,19,28,23,9,76,9.0,0,32,Urban,HR Executive,111569,0 +104909,Female,49,Masters,9,17,55,59,17,4.0,6,77,Semi-Urban,Software Engineer,69113,0 +104910,Female,55,Bachelors,11,40,27,89,10,1.0,2,36,Urban,Data Analyst,97003,0 +104911,Female,45,Diploma,16,36,47,39,63,0.0,3,86,Semi-Urban,Data Analyst,50483,0 +104912,Female,54,Bachelors,7,75,46,87,8,5.0,1,97,Urban,Software Engineer,117597,1 +104913,Male,51,High School,2,64,32,4,75,1.0,5,62,Semi-Urban,HR Executive,45191,0 +104914,Female,49,Diploma,15,67,67,52,27,2.0,2,27,Urban,ML Engineer,105830,0 +104915,Female,45,Diploma,5,35,9,25,32,1.0,4,1,Rural,Data Analyst,70145,0 +104916,Male,53,Bachelors,12,82,24,42,1,6.0,2,19,Urban,HR Executive,67812,0 +104917,Male,32,Bachelors,11,87,99,5,79,8.0,5,84,Urban,ML Engineer,58285,1 +104918,Male,54,Masters,5,12,88,19,49,5.0,5,94,Urban,Software Engineer,137555,0 +104919,Female,44,Diploma,19,21,30,94,2,6.0,4,43,Urban,HR Executive,53399,0 +104920,Female,42,Diploma,8,73,19,42,28,7.0,4,36,Urban,ML Engineer,136604,0 +104921,Male,25,Diploma,18,69,99,63,97,7.0,5,76,Urban,Data Analyst,98857,1 +104922,Male,27,Bachelors,15,20,50,14,78,8.0,0,73,Urban,Software Engineer,143266,0 +104923,Male,41,Bachelors,13,87,62,1,16,7.0,2,17,Rural,Data Analyst,30663,0 +104924,Female,55,Masters,10,74,59,32,69,0.0,4,44,Rural,Data Analyst,98916,0 +104925,Female,33,Bachelors,7,40,8,57,82,1.0,3,42,Rural,Manager,63660,0 +104926,Female,42,Diploma,10,70,37,42,31,8.0,5,17,Urban,Data Analyst,83823,0 +104927,Male,28,High School,0,75,87,5,52,8.0,7,13,Rural,Software Engineer,35938,0 +104928,Male,21,Diploma,2,68,62,28,42,5.0,0,85,Urban,Data Analyst,149763,1 +104929,Male,47,High School,14,75,4,77,94,2.0,2,21,Rural,HR Executive,54264,0 +104930,Female,51,High School,3,21,20,90,84,5.0,0,94,Urban,Software Engineer,88028,0 +104931,Male,28,Bachelors,16,56,4,71,13,3.0,2,74,Semi-Urban,Data Analyst,22112,0 +104932,Male,32,Bachelors,0,26,99,96,41,7.0,4,10,Urban,HR Executive,127070,0 +104933,Female,23,High School,8,90,28,53,27,4.0,5,85,Urban,ML Engineer,138703,1 +104934,Female,29,Bachelors,8,3,32,55,54,9.0,4,33,Urban,HR Executive,68694,0 +104935,Male,33,Bachelors,19,29,92,72,68,0.0,3,68,Urban,Data Analyst,142490,1 +104936,Male,40,Bachelors,2,95,75,42,27,0.0,6,86,Semi-Urban,HR Executive,61037,1 +104937,Female,25,Diploma,19,81,37,21,91,5.0,3,51,Urban,ML Engineer,62825,0 +104938,Female,21,Masters,2,70,54,65,57,9.0,2,64,Urban,Software Engineer,43603,1 +104939,Male,54,Diploma,10,56,41,92,90,4.0,7,69,Semi-Urban,Data Analyst,141175,1 +104940,Male,39,Bachelors,16,89,97,8,72,5.0,4,70,Rural,Manager,42922,1 +104941,Female,32,Masters,12,54,68,5,89,3.0,3,16,Semi-Urban,Manager,77824,0 +104942,Male,21,Diploma,15,90,24,85,43,7.0,1,69,Urban,HR Executive,88094,1 +104943,Female,37,High School,10,66,42,2,73,1.0,1,8,Urban,ML Engineer,24283,0 +104944,Female,44,Bachelors,18,83,27,57,36,4.0,4,29,Semi-Urban,Software Engineer,49091,0 +104945,Female,47,Diploma,8,53,8,72,83,1.0,1,2,Rural,Data Analyst,105203,0 +104946,Female,54,Bachelors,1,9,31,99,93,8.0,4,62,Urban,Manager,52031,0 +104947,Male,23,Bachelors,4,87,78,45,83,5.0,7,98,Urban,Software Engineer,129517,1 +104948,Female,26,Diploma,5,36,75,59,63,0.0,5,92,Semi-Urban,Software Engineer,89214,1 +104949,Male,25,Diploma,6,44,5,51,52,1.0,6,8,Semi-Urban,Manager,64995,0 +104950,Male,38,Bachelors,0,21,52,15,72,5.0,2,56,Rural,Manager,83401,0 +104951,Male,37,PhD,14,66,47,12,9,5.0,5,93,Urban,ML Engineer,63687,0 +104952,Female,26,Masters,12,81,62,48,8,3.0,7,40,Rural,Software Engineer,30753,0 +104953,Female,30,High School,7,91,58,94,1,6.0,1,54,Semi-Urban,HR Executive,117142,1 +104954,Female,38,Bachelors,18,27,17,64,74,3.0,7,74,Semi-Urban,Software Engineer,43408,0 +104955,Male,37,Bachelors,15,54,89,16,91,4.0,4,53,Urban,Software Engineer,78631,0 +104956,Female,58,Bachelors,7,6,30,82,27,9.0,5,54,Urban,Data Analyst,82448,0 +104957,Male,27,Bachelors,1,93,90,43,81,9.0,7,44,Urban,Manager,66226,1 +104958,Other,36,Bachelors,15,5,35,5,24,4.0,0,36,Urban,Data Analyst,149507,0 +104959,Male,43,Diploma,10,22,47,7,62,5.0,6,24,Urban,Manager,53419,0 +104960,Male,55,Diploma,1,88,6,85,78,6.0,4,94,Rural,Software Engineer,87303,1 +104961,Male,33,Masters,3,99,74,81,34,1.0,0,34,Urban,ML Engineer,77094,1 +104962,Female,36,High School,15,34,12,85,79,6.0,1,15,Urban,ML Engineer,87443,0 +104963,Male,48,High School,13,23,22,5,90,1.0,5,21,Semi-Urban,Software Engineer,49247,0 +104964,Female,32,High School,17,32,85,82,87,5.0,2,63,Urban,Data Analyst,91804,1 +104965,Male,56,High School,18,23,48,52,17,1.0,5,41,Semi-Urban,ML Engineer,93627,0 +104966,Female,25,High School,10,7,91,95,56,8.0,5,67,Urban,Manager,26938,1 +104967,Male,29,Bachelors,16,32,73,79,74,3.0,3,28,Urban,Data Analyst,83392,0 +104968,Female,45,Bachelors,11,20,97,41,64,7.0,2,56,Urban,HR Executive,93275,0 +104969,Male,21,PhD,18,33,80,65,90,4.0,1,61,Rural,Manager,145859,1 +104970,Male,33,Masters,10,54,83,50,22,3.0,4,43,Urban,Manager,83376,0 +104971,Female,56,Bachelors,2,16,54,17,30,9.0,3,92,Urban,HR Executive,35455,0 +104972,Male,38,Diploma,4,30,52,85,80,4.0,5,63,Semi-Urban,ML Engineer,138180,0 +104973,Male,43,Diploma,10,84,26,21,43,5.0,7,71,Semi-Urban,Manager,30448,0 +104974,Male,57,Bachelors,5,78,20,30,7,1.0,0,24,Urban,Manager,94961,0 +104975,Female,49,Masters,7,45,95,2,64,5.0,1,2,Rural,Software Engineer,78018,0 +104976,Male,45,Masters,12,99,43,46,72,5.0,6,58,Urban,Data Analyst,136378,1 +104977,Female,39,PhD,9,14,31,25,18,3.0,1,33,Urban,ML Engineer,112691,0 +104978,Male,35,Diploma,4,80,35,90,61,7.0,1,25,Rural,Software Engineer,132207,0 +104979,Female,54,Bachelors,7,86,86,55,61,1.0,4,14,Urban,Software Engineer,118533,1 +104980,Female,46,Bachelors,19,38,74,24,95,8.0,1,39,Semi-Urban,Manager,148305,0 +104981,Female,41,Masters,19,76,83,84,78,2.0,0,40,Urban,HR Executive,146735,1 +104982,Male,50,PhD,10,88,11,92,26,1.0,4,13,Rural,HR Executive,58659,0 +104983,Male,54,Masters,1,35,17,97,76,8.0,6,43,Urban,Software Engineer,107886,0 +104984,Male,59,Bachelors,9,16,21,9,60,5.0,6,87,Rural,ML Engineer,70813,0 +104985,Female,45,High School,1,97,24,68,79,5.0,1,56,Urban,HR Executive,87605,1 +104986,Female,34,High School,11,52,81,53,82,7.0,1,21,Urban,HR Executive,122340,0 +104987,Male,25,Bachelors,5,7,15,9,83,0.0,1,91,Urban,ML Engineer,23484,0 +104988,Male,39,Masters,10,51,48,46,89,5.0,6,45,Rural,ML Engineer,92490,0 +104989,Female,54,High School,6,73,2,28,7,0.0,5,97,Urban,ML Engineer,50454,0 +104990,Male,43,Masters,17,54,19,46,4,4.0,7,22,Semi-Urban,Manager,144187,0 +104991,Male,43,Bachelors,17,87,4,48,13,8.0,2,23,Urban,Software Engineer,133360,0 +104992,Male,22,Diploma,5,99,4,94,12,5.0,7,91,Semi-Urban,Data Analyst,63429,1 +104993,Female,30,Masters,13,75,51,62,63,7.0,1,89,Urban,HR Executive,136143,1 +104994,Male,30,Diploma,0,4,14,52,82,4.0,6,17,Rural,Data Analyst,74054,0 +104995,Female,46,Bachelors,15,27,34,33,19,2.0,7,12,Rural,Software Engineer,26173,0 +104996,Male,59,PhD,6,78,59,86,57,0.0,3,60,Semi-Urban,Software Engineer,90471,1 +104997,Male,42,Bachelors,11,6,76,54,38,8.0,2,40,Urban,Data Analyst,52615,0 +104998,Male,29,Bachelors,1,67,28,6,31,6.0,6,77,Semi-Urban,ML Engineer,97658,0 +104999,Male,35,Bachelors,17,19,13,9,15,4.0,2,9,Urban,Manager,32051,0 +105000,Male,42,Masters,7,98,18,61,64,9.0,5,31,Rural,ML Engineer,135969,0 +105001,Female,53,Bachelors,18,82,67,61,50,7.0,5,18,Semi-Urban,Manager,64120,0 +105002,Female,37,Masters,18,73,2,55,36,8.0,6,52,Semi-Urban,Data Analyst,61259,0 +105003,Male,23,Masters,16,65,8,51,95,7.0,6,59,Urban,ML Engineer,42841,0 +105004,Male,21,Bachelors,4,31,59,81,92,4.0,6,93,Urban,Manager,29358,1 +105005,Male,29,Diploma,14,85,49,54,19,0.0,2,76,Urban,Manager,118600,1 +105006,Male,58,High School,2,12,46,49,46,3.0,2,40,Semi-Urban,Manager,55713,0 +105007,Male,34,High School,1,4,64,65,77,3.0,7,85,Urban,Manager,66490,0 +105008,Male,36,Diploma,1,75,82,91,52,6.0,4,94,Rural,Data Analyst,54975,1 +105009,Female,35,PhD,0,31,37,28,60,3.0,6,92,Urban,Data Analyst,66715,0 +105010,Female,34,Bachelors,11,99,84,31,38,4.0,4,19,Urban,ML Engineer,50178,0 +105011,Other,27,Bachelors,18,97,78,36,23,6.0,6,0,Urban,ML Engineer,134098,0 +105012,Male,43,Masters,3,19,56,8,71,7.0,5,71,Rural,ML Engineer,51909,0 +105013,Female,37,High School,5,25,44,69,93,5.0,3,69,Urban,Software Engineer,56762,0 +105014,Female,53,Bachelors,10,89,78,92,61,3.0,1,2,Urban,HR Executive,20519,1 +105015,Male,56,Bachelors,0,82,15,44,57,9.0,7,62,Urban,HR Executive,132259,0 +105016,Male,43,Bachelors,7,54,60,46,80,8.0,1,28,Semi-Urban,Manager,115663,0 +105017,Other,49,Diploma,3,91,36,10,49,6.0,5,71,Rural,Data Analyst,56278,0 +105018,Male,32,High School,16,19,35,22,89,8.0,3,90,Semi-Urban,ML Engineer,45313,0 +105019,Male,57,Bachelors,19,31,32,32,95,6.0,1,52,Urban,Software Engineer,62330,0 +105020,Male,50,Bachelors,10,37,85,67,67,5.0,4,85,Urban,Manager,89999,1 +105021,Male,36,Bachelors,11,19,83,57,87,1.0,5,34,Urban,HR Executive,52608,0 +105022,Female,31,High School,19,10,8,24,15,1.0,3,37,Rural,ML Engineer,92632,0 +105023,Male,34,Bachelors,3,17,20,13,87,8.0,6,42,Urban,Data Analyst,73344,0 +105024,Male,33,Bachelors,10,26,4,92,71,7.0,7,90,Semi-Urban,HR Executive,43997,0 +105025,Male,53,Diploma,19,75,84,15,75,6.0,5,42,Urban,Software Engineer,68605,0 +105026,Male,57,Bachelors,16,17,56,80,62,3.0,4,19,Rural,Software Engineer,45112,0 +105027,Female,42,High School,16,7,45,92,69,1.0,1,70,Rural,Data Analyst,137405,0 +105028,Male,58,Bachelors,14,92,69,84,51,5.0,0,74,Urban,Manager,147780,1 +105029,Female,59,Diploma,19,61,78,42,66,9.0,5,28,Rural,Manager,33885,0 +105030,Female,43,Diploma,16,74,74,55,77,3.0,2,48,Rural,ML Engineer,87919,1 +105031,Male,38,Masters,17,44,7,10,73,9.0,4,47,Semi-Urban,HR Executive,146876,0 +105032,Male,30,Bachelors,6,52,61,89,17,5.0,3,20,Urban,Data Analyst,34886,0 +105033,Female,48,Bachelors,1,97,54,55,18,2.0,7,99,Urban,HR Executive,69089,1 +105034,Female,36,Bachelors,11,1,12,57,22,2.0,2,26,Rural,Manager,147865,0 +105035,Male,42,Bachelors,19,36,33,73,36,4.0,6,92,Urban,Data Analyst,103830,0 +105036,Male,33,Masters,0,55,33,42,39,9.0,6,19,Urban,HR Executive,98833,0 +105037,Male,48,High School,6,71,46,62,93,2.0,6,88,Semi-Urban,Software Engineer,26051,1 +105038,Female,28,Masters,1,67,6,30,92,1.0,3,34,Urban,ML Engineer,93772,0 +105039,Male,56,High School,3,34,8,59,31,3.0,1,23,Urban,Software Engineer,69602,0 +105040,Female,41,Bachelors,19,44,48,23,52,5.0,0,71,Semi-Urban,HR Executive,92272,0 +105041,Male,40,Bachelors,11,74,23,71,4,1.0,4,24,Urban,Manager,147740,0 +105042,Male,46,Masters,0,93,79,24,14,4.0,1,88,Semi-Urban,Software Engineer,127979,1 +105043,Male,56,Diploma,11,11,23,43,9,6.0,6,95,Semi-Urban,HR Executive,61886,0 +105044,Male,52,Masters,17,73,69,19,61,5.0,6,51,Urban,Data Analyst,37391,0 +105045,Male,52,Bachelors,16,7,75,62,31,2.0,0,69,Urban,Software Engineer,134910,0 +105046,Male,47,Masters,15,84,65,34,65,8.0,6,27,Semi-Urban,ML Engineer,37895,0 +105047,Male,44,Masters,2,9,15,96,2,3.0,0,58,Urban,Manager,60186,0 +105048,Male,48,Bachelors,1,57,24,85,82,3.0,2,74,Rural,Data Analyst,113867,1 +105049,Female,55,Masters,1,58,14,89,89,7.0,0,3,Urban,Manager,89576,0 +105050,Male,44,Bachelors,11,34,99,43,26,0.0,4,24,Urban,Data Analyst,117899,0 +105051,Female,30,Bachelors,8,45,7,33,34,8.0,1,96,Urban,Data Analyst,26860,0 +105052,Other,32,Bachelors,4,77,14,53,21,1.0,2,87,Urban,ML Engineer,86585,0 +105053,Female,29,Bachelors,5,86,71,96,28,1.0,4,32,Urban,Manager,98892,1 +105054,Male,58,Bachelors,15,32,50,75,68,5.0,0,23,Rural,Data Analyst,133705,0 +105055,Male,33,Bachelors,6,6,46,28,35,1.0,3,6,Urban,ML Engineer,75047,0 +105056,Other,34,Diploma,19,36,83,51,13,6.0,1,64,Semi-Urban,Data Analyst,99119,0 +105057,Male,28,Diploma,2,21,40,51,35,1.0,2,16,Semi-Urban,Software Engineer,31570,0 +105058,Male,54,PhD,14,60,59,19,85,1.0,1,61,Urban,Data Analyst,149087,0 +105059,Male,31,Masters,18,99,96,17,84,5.0,3,36,Urban,ML Engineer,46969,1 +105060,Male,47,Bachelors,19,9,57,94,94,3.0,3,63,Urban,Software Engineer,84924,0 +105061,Female,43,Masters,6,78,37,2,77,2.0,3,4,Rural,ML Engineer,52288,0 +105062,Male,22,High School,17,25,98,50,21,8.0,3,1,Semi-Urban,Software Engineer,101381,0 +105063,Male,25,Bachelors,17,0,1,67,21,0.0,6,34,Urban,HR Executive,82133,0 +105064,Male,52,Bachelors,8,85,10,44,63,1.0,0,44,Rural,HR Executive,117523,0 +105065,Female,22,Bachelors,1,64,86,60,79,7.0,5,71,Urban,Data Analyst,26904,1 +105066,Male,33,Diploma,10,30,46,57,72,6.0,3,89,Semi-Urban,HR Executive,61021,0 +105067,Female,25,High School,18,24,71,48,51,5.0,2,4,Urban,HR Executive,91674,0 +105068,Female,25,Bachelors,4,8,76,41,17,2.0,2,84,Semi-Urban,ML Engineer,80462,0 +105069,Female,54,Diploma,18,54,79,91,44,5.0,0,46,Semi-Urban,HR Executive,115570,1 +105070,Female,47,Bachelors,0,39,19,66,59,2.0,5,98,Semi-Urban,ML Engineer,104699,0 +105071,Male,38,High School,15,93,6,99,89,3.0,6,97,Rural,Data Analyst,72104,1 +105072,Male,48,Diploma,13,14,85,92,2,0.0,1,68,Urban,HR Executive,111420,1 +105073,Female,44,PhD,4,56,56,14,1,5.0,4,80,Urban,HR Executive,26024,0 +105074,Male,42,Diploma,3,63,13,92,19,0.0,5,50,Semi-Urban,Software Engineer,39508,0 +105075,Female,25,Bachelors,4,87,6,75,50,0.0,0,43,Semi-Urban,HR Executive,83353,0 +105076,Female,27,Masters,7,97,16,16,29,5.0,4,15,Urban,HR Executive,144375,0 +105077,Male,37,Diploma,1,22,92,18,8,2.0,0,30,Urban,Manager,96821,0 +105078,Male,34,Bachelors,8,2,35,99,17,0.0,0,47,Urban,Software Engineer,132352,0 +105079,Male,55,Masters,15,47,47,76,28,1.0,3,8,Semi-Urban,HR Executive,104760,0 +105080,Female,52,Masters,15,37,21,38,67,5.0,4,25,Semi-Urban,Data Analyst,105054,0 +105081,Male,40,Masters,14,19,38,47,57,9.0,0,68,Urban,Data Analyst,140483,0 +105082,Female,22,Bachelors,0,81,79,25,93,0.0,5,53,Urban,Software Engineer,51387,0 +105083,Male,28,Masters,17,72,28,86,11,8.0,7,55,Semi-Urban,Software Engineer,40648,1 +105084,Male,21,Masters,11,41,89,29,31,4.0,7,60,Rural,ML Engineer,146549,0 +105085,Female,36,Masters,5,23,2,85,49,0.0,0,17,Rural,ML Engineer,128384,0 +105086,Male,56,High School,7,67,54,54,93,6.0,1,19,Semi-Urban,Software Engineer,84375,0 +105087,Male,26,Masters,2,46,11,16,65,5.0,4,66,Rural,Software Engineer,119106,0 +105088,Female,53,Bachelors,19,80,38,53,70,5.0,6,75,Rural,Data Analyst,108554,1 +105089,Other,33,Bachelors,5,32,88,23,44,9.0,7,42,Semi-Urban,Data Analyst,104342,0 +105090,Female,29,Diploma,3,77,3,16,51,3.0,0,20,Urban,Data Analyst,142562,0 +105091,Male,42,Bachelors,13,36,73,9,16,0.0,5,69,Rural,Data Analyst,74735,0 +105092,Female,27,Bachelors,13,98,66,65,35,3.0,3,97,Urban,HR Executive,95313,1 +105093,Male,45,High School,7,79,56,71,74,3.0,4,16,Urban,ML Engineer,77326,0 +105094,Male,25,High School,18,99,33,20,99,3.0,5,96,Semi-Urban,HR Executive,145834,1 +105095,Male,29,Bachelors,17,65,1,87,66,3.0,4,82,Urban,Manager,103311,1 +105096,Male,57,Masters,17,28,29,62,62,6.0,4,5,Semi-Urban,Data Analyst,65979,0 +105097,Male,56,Diploma,13,58,64,54,60,9.0,2,5,Rural,ML Engineer,133709,0 +105098,Male,31,Bachelors,13,84,49,49,67,7.0,1,33,Urban,Software Engineer,42700,0 +105099,Female,37,Masters,6,52,15,65,61,9.0,5,47,Urban,Manager,97156,0 +105100,Male,21,Masters,16,92,84,88,57,7.0,2,60,Semi-Urban,Software Engineer,126758,1 +105101,Female,32,High School,3,29,28,54,6,2.0,7,25,Urban,Software Engineer,58920,0 +105102,Male,43,Diploma,7,26,66,32,85,4.0,7,12,Semi-Urban,Manager,116493,0 +105103,Male,30,Diploma,11,50,98,92,46,9.0,3,44,Rural,HR Executive,115141,1 +105104,Female,56,Bachelors,15,38,68,91,40,7.0,5,95,Semi-Urban,ML Engineer,140489,1 +105105,Female,48,Bachelors,14,81,36,59,29,3.0,5,56,Rural,ML Engineer,29750,0 +105106,Female,55,Masters,3,65,56,95,84,3.0,7,50,Semi-Urban,Data Analyst,136526,1 +105107,Male,41,Bachelors,9,96,11,80,24,9.0,3,95,Urban,HR Executive,114464,1 +105108,Female,26,PhD,15,26,9,7,49,7.0,4,65,Semi-Urban,HR Executive,31314,0 +105109,Female,34,Bachelors,16,30,15,71,93,3.0,0,44,Semi-Urban,Manager,142401,0 +105110,Female,59,PhD,4,41,44,42,47,5.0,6,55,Urban,Software Engineer,78047,0 +105111,Female,57,High School,11,18,49,86,63,2.0,0,75,Urban,HR Executive,31240,0 +105112,Male,25,High School,10,45,46,71,11,6.0,7,24,Urban,Data Analyst,92313,0 +105113,Male,32,Masters,2,24,60,88,84,0.0,1,2,Semi-Urban,Manager,113669,0 +105114,Female,31,Diploma,11,70,49,28,62,1.0,6,75,Semi-Urban,ML Engineer,29948,0 +105115,Other,35,Bachelors,6,32,37,72,9,5.0,5,54,Urban,ML Engineer,42698,0 +105116,Female,53,Bachelors,7,89,0,74,35,8.0,3,73,Urban,HR Executive,104366,0 +105117,Male,52,Masters,3,30,19,28,57,6.0,1,65,Urban,Manager,147878,0 +105118,Male,25,Bachelors,13,44,87,61,40,1.0,3,40,Semi-Urban,ML Engineer,75290,0 +105119,Female,56,Masters,17,52,73,64,93,2.0,5,98,Urban,ML Engineer,104750,1 +105120,Male,58,Diploma,6,76,26,45,30,3.0,4,37,Semi-Urban,ML Engineer,120117,0 +105121,Female,42,Bachelors,10,26,78,38,2,2.0,4,61,Rural,HR Executive,58327,0 +105122,Female,34,Bachelors,1,78,96,33,10,2.0,0,59,Urban,ML Engineer,130469,1 +105123,Male,38,Masters,3,73,41,56,78,6.0,1,90,Urban,Manager,68129,1 +105124,Female,39,PhD,7,36,90,11,66,0.0,5,3,Semi-Urban,Software Engineer,48305,0 +105125,Male,54,Bachelors,10,5,34,72,84,6.0,4,38,Urban,Data Analyst,116449,0 +105126,Female,21,Bachelors,3,56,37,77,88,5.0,3,80,Urban,Software Engineer,130769,1 +105127,Female,37,High School,5,85,92,50,10,9.0,0,43,Semi-Urban,Software Engineer,95105,1 +105128,Male,23,Bachelors,14,10,94,7,47,3.0,7,54,Rural,Data Analyst,144382,0 +105129,Other,49,High School,19,20,8,99,20,4.0,4,59,Urban,ML Engineer,47725,0 +105130,Male,28,Bachelors,5,36,91,87,63,5.0,4,17,Urban,Data Analyst,30066,0 +105131,Male,29,Masters,12,79,47,77,12,1.0,6,47,Urban,HR Executive,90540,1 +105132,Female,42,Diploma,2,76,58,7,29,2.0,3,85,Rural,HR Executive,55170,0 +105133,Male,34,High School,7,5,71,39,75,4.0,6,56,Semi-Urban,ML Engineer,30684,0 +105134,Male,50,Masters,16,16,5,1,19,5.0,5,21,Urban,Software Engineer,141266,0 +105135,Male,21,High School,3,56,90,87,87,7.0,1,13,Rural,Manager,116661,1 +105136,Male,22,Bachelors,5,38,65,7,93,8.0,4,78,Urban,HR Executive,70121,0 +105137,Female,41,PhD,2,60,57,36,55,3.0,4,13,Semi-Urban,Data Analyst,98640,0 +105138,Male,33,Bachelors,6,48,98,18,69,1.0,4,73,Urban,HR Executive,141866,1 +105139,Female,45,Bachelors,12,22,44,56,39,1.0,0,34,Semi-Urban,ML Engineer,98937,0 +105140,Male,33,Bachelors,3,73,73,40,67,6.0,3,23,Semi-Urban,ML Engineer,65694,0 +105141,Male,32,Diploma,16,71,43,65,85,6.0,3,51,Urban,Software Engineer,53752,0 +105142,Male,26,High School,5,9,83,97,3,0.0,1,19,Rural,HR Executive,44230,0 +105143,Male,49,High School,13,11,98,80,68,5.0,4,11,Urban,Manager,128222,0 +105144,Female,54,Masters,5,57,59,55,11,9.0,1,50,Urban,Software Engineer,71573,0 +105145,Male,50,High School,7,95,81,57,92,8.0,2,81,Semi-Urban,ML Engineer,87152,1 +105146,Male,40,Bachelors,15,33,40,53,79,1.0,7,68,Rural,Manager,50687,0 +105147,Female,37,High School,19,22,36,7,59,8.0,1,58,Semi-Urban,Software Engineer,38221,0 +105148,Male,28,High School,4,26,54,75,72,4.0,7,81,Urban,ML Engineer,123662,1 +105149,Male,22,High School,9,19,40,69,31,1.0,7,53,Urban,Software Engineer,55933,0 +105150,Other,22,Diploma,4,9,57,2,28,1.0,7,12,Urban,Software Engineer,129168,0 +105151,Male,59,Bachelors,19,24,6,20,11,8.0,4,57,Urban,HR Executive,44122,0 +105152,Female,34,Masters,16,0,3,97,69,4.0,6,37,Rural,Manager,114610,0 +105153,Female,25,High School,16,5,72,52,55,0.0,0,5,Rural,Software Engineer,141692,0 +105154,Male,52,High School,3,92,68,76,56,3.0,7,77,Urban,Manager,129804,1 +105155,Male,54,High School,10,16,83,15,53,7.0,3,4,Urban,Software Engineer,124608,0 +105156,Male,45,Diploma,0,79,26,35,7,4.0,6,81,Semi-Urban,Data Analyst,33638,0 +105157,Male,44,Bachelors,1,47,55,47,44,8.0,3,84,Urban,Data Analyst,97847,0 +105158,Other,34,High School,19,10,10,10,34,2.0,3,63,Semi-Urban,Data Analyst,50905,0 +105159,Male,29,Masters,5,22,52,87,40,3.0,3,31,Urban,Manager,49342,0 +105160,Male,42,High School,19,98,58,82,42,9.0,4,68,Semi-Urban,Manager,71862,1 +105161,Male,32,Diploma,18,63,18,16,48,3.0,2,43,Rural,HR Executive,143986,0 +105162,Female,40,Masters,12,7,40,54,30,9.0,4,30,Urban,Manager,87098,0 +105163,Female,58,Masters,3,68,20,57,48,4.0,4,58,Urban,ML Engineer,64236,0 +105164,Female,30,Diploma,9,93,29,46,6,6.0,1,72,Rural,Data Analyst,146045,0 +105165,Male,40,Bachelors,17,28,11,9,94,6.0,1,20,Rural,Software Engineer,130636,0 +105166,Female,26,High School,17,48,8,77,61,5.0,6,66,Semi-Urban,Software Engineer,60615,0 +105167,Female,35,Masters,14,84,0,64,27,6.0,5,50,Semi-Urban,ML Engineer,31119,0 +105168,Other,39,Bachelors,9,87,89,67,89,8.0,7,15,Semi-Urban,ML Engineer,102103,1 +105169,Male,41,Bachelors,2,18,25,97,53,4.0,1,60,Semi-Urban,ML Engineer,100139,0 +105170,Male,49,Diploma,2,31,10,3,60,5.0,1,99,Urban,Manager,115904,0 +105171,Male,40,Bachelors,13,52,19,72,66,4.0,4,37,Semi-Urban,ML Engineer,130170,0 +105172,Female,31,Diploma,3,35,9,53,17,0.0,7,41,Semi-Urban,Manager,61694,0 +105173,Female,37,Diploma,4,85,86,7,67,6.0,3,60,Urban,Software Engineer,32928,0 +105174,Female,48,Bachelors,0,1,82,80,79,8.0,4,44,Urban,HR Executive,20552,0 +105175,Female,45,Bachelors,19,2,52,56,49,3.0,2,23,Semi-Urban,HR Executive,54832,0 +105176,Male,28,Bachelors,3,66,0,67,70,0.0,0,5,Semi-Urban,Manager,95289,0 +105177,Male,23,Bachelors,16,78,25,95,25,8.0,6,90,Rural,Manager,110894,1 +105178,Male,48,Diploma,6,22,15,88,81,9.0,4,97,Urban,Manager,84344,0 +105179,Male,48,Bachelors,5,75,97,26,85,2.0,5,13,Urban,HR Executive,56352,0 +105180,Female,40,High School,16,7,4,62,8,2.0,1,94,Urban,Data Analyst,23793,0 +105181,Female,52,Diploma,11,25,46,10,31,8.0,7,15,Rural,Manager,69885,0 +105182,Male,39,Bachelors,4,46,84,36,61,4.0,6,36,Rural,HR Executive,139155,0 +105183,Male,59,Diploma,17,40,87,81,17,3.0,3,49,Semi-Urban,Data Analyst,21677,1 +105184,Male,44,Bachelors,5,98,12,35,45,2.0,6,14,Urban,ML Engineer,126951,0 +105185,Female,57,Masters,3,80,39,96,24,0.0,2,38,Urban,ML Engineer,135946,1 +105186,Other,35,Diploma,16,51,84,48,77,6.0,2,14,Urban,Manager,130306,0 +105187,Male,51,Diploma,13,38,39,13,39,8.0,5,87,Urban,Data Analyst,41336,0 +105188,Male,39,High School,7,33,91,66,29,2.0,2,41,Urban,ML Engineer,87102,0 +105189,Female,58,Bachelors,14,49,28,76,40,5.0,2,94,Rural,ML Engineer,21413,1 +105190,Male,22,Diploma,15,14,72,64,52,5.0,1,66,Semi-Urban,Data Analyst,61318,0 +105191,Female,50,High School,14,38,0,48,74,2.0,0,40,Urban,Manager,112826,0 +105192,Female,33,Bachelors,2,30,50,34,82,2.0,6,52,Semi-Urban,ML Engineer,109359,0 +105193,Male,37,Bachelors,2,30,32,35,98,3.0,5,1,Semi-Urban,HR Executive,46144,0 +105194,Male,30,Bachelors,15,26,9,22,87,8.0,0,31,Urban,Manager,63750,0 +105195,Male,34,Bachelors,17,86,58,73,69,8.0,6,73,Urban,Software Engineer,144534,1 +105196,Female,56,Bachelors,10,25,92,38,66,1.0,6,6,Urban,Data Analyst,36653,0 +105197,Other,37,Bachelors,12,84,56,31,32,8.0,1,80,Urban,Data Analyst,54639,1 +105198,Male,48,Diploma,7,59,7,64,15,3.0,3,59,Rural,Data Analyst,123815,0 +105199,Male,25,Bachelors,8,44,24,29,23,5.0,5,76,Urban,HR Executive,82153,0 +105200,Female,34,PhD,13,35,76,67,21,7.0,5,96,Urban,Software Engineer,69330,1 +105201,Female,29,Bachelors,0,88,36,71,69,0.0,0,9,Semi-Urban,Manager,85497,0 +105202,Male,21,High School,2,50,63,54,44,7.0,2,29,Semi-Urban,Manager,61964,0 +105203,Male,47,Bachelors,4,9,67,93,47,1.0,1,71,Rural,ML Engineer,100319,1 +105204,Male,41,Bachelors,6,32,68,54,16,5.0,4,74,Urban,HR Executive,138549,0 +105205,Male,22,Bachelors,9,59,65,63,24,1.0,7,78,Rural,ML Engineer,31476,1 +105206,Female,43,Bachelors,5,81,43,64,39,0.0,0,51,Urban,HR Executive,118373,0 +105207,Male,59,Bachelors,6,28,44,15,68,9.0,1,89,Urban,ML Engineer,33963,0 +105208,Female,53,Bachelors,15,22,37,21,96,5.0,7,17,Urban,Manager,113159,0 +105209,Female,51,Masters,9,70,60,73,51,6.0,2,7,Semi-Urban,ML Engineer,111470,0 +105210,Male,57,Bachelors,1,15,27,54,51,2.0,7,39,Urban,Software Engineer,55651,0 +105211,Male,54,Bachelors,10,67,89,3,38,9.0,6,98,Urban,ML Engineer,97266,1 +105212,Male,28,Diploma,5,89,2,37,58,9.0,5,18,Urban,Software Engineer,148208,0 +105213,Male,29,Masters,14,2,40,53,59,5.0,6,94,Urban,Data Analyst,120126,0 +105214,Female,27,Diploma,6,23,33,90,42,2.0,7,6,Rural,Manager,126242,0 +105215,Male,46,High School,14,35,94,98,28,4.0,1,90,Rural,Data Analyst,94221,1 +105216,Male,38,Diploma,15,58,70,97,34,1.0,5,60,Urban,HR Executive,146466,1 +105217,Male,52,Diploma,5,25,92,40,27,0.0,4,14,Urban,Manager,119531,0 +105218,Male,41,High School,19,52,14,12,20,8.0,1,70,Urban,Software Engineer,63306,0 +105219,Other,52,High School,12,70,67,49,6,9.0,1,97,Semi-Urban,ML Engineer,71460,1 +105220,Male,39,Diploma,11,83,62,45,63,8.0,4,48,Urban,Software Engineer,31356,1 +105221,Female,48,Bachelors,6,22,79,89,65,9.0,5,32,Urban,HR Executive,38606,0 +105222,Male,44,Masters,2,88,82,95,31,9.0,6,1,Urban,Data Analyst,96116,1 +105223,Other,56,Bachelors,15,63,24,89,53,8.0,1,74,Rural,Data Analyst,105815,1 +105224,Male,51,Masters,12,73,64,13,47,1.0,0,77,Rural,ML Engineer,114315,0 +105225,Male,44,Bachelors,11,7,25,78,97,8.0,1,16,Urban,Data Analyst,39900,0 +105226,Male,48,Diploma,4,50,11,82,66,8.0,0,79,Urban,Manager,117363,0 +105227,Male,58,Masters,18,88,34,98,95,1.0,4,67,Urban,HR Executive,62025,1 +105228,Other,35,Masters,3,15,72,84,53,5.0,4,35,Urban,Manager,120343,0 +105229,Male,51,Bachelors,10,77,36,87,15,7.0,4,74,Semi-Urban,Software Engineer,89994,1 +105230,Female,47,Bachelors,0,71,5,95,15,0.0,2,3,Urban,Software Engineer,41431,0 +105231,Male,42,Masters,4,69,79,19,53,9.0,5,6,Urban,Manager,90830,0 +105232,Male,39,PhD,2,18,70,40,89,0.0,6,44,Urban,Manager,139269,0 +105233,Male,38,Masters,9,82,68,89,88,5.0,0,27,Urban,ML Engineer,97864,1 +105234,Other,40,Bachelors,7,72,52,21,42,5.0,1,25,Semi-Urban,Data Analyst,147591,0 +105235,Male,32,Diploma,19,51,92,65,27,9.0,2,82,Urban,HR Executive,83369,1 +105236,Male,40,Bachelors,0,33,60,83,46,3.0,7,38,Urban,ML Engineer,46951,0 +105237,Male,22,High School,11,7,80,31,41,3.0,6,85,Urban,Software Engineer,114565,0 +105238,Male,22,Masters,16,54,22,21,62,7.0,3,78,Urban,Data Analyst,143167,0 +105239,Female,56,Bachelors,19,86,14,24,59,2.0,2,57,Urban,HR Executive,102693,0 +105240,Male,49,High School,18,87,8,79,86,4.0,5,17,Urban,Software Engineer,103257,0 +105241,Female,45,Diploma,11,26,84,80,83,8.0,2,2,Rural,Software Engineer,91106,0 +105242,Male,54,Masters,4,13,43,48,66,5.0,6,8,Urban,Software Engineer,119483,0 +105243,Female,52,Bachelors,3,56,2,66,24,1.0,7,19,Rural,Data Analyst,72530,0 +105244,Female,54,Masters,3,67,72,68,6,6.0,5,21,Semi-Urban,Manager,110702,0 +105245,Female,45,Diploma,18,55,65,14,23,7.0,2,42,Urban,Manager,79959,0 +105246,Male,39,Masters,17,57,59,84,68,7.0,1,28,Urban,HR Executive,140801,0 +105247,Female,26,Masters,13,89,40,97,24,0.0,5,75,Urban,ML Engineer,113930,1 +105248,Male,26,Bachelors,10,48,16,73,75,0.0,0,74,Rural,Data Analyst,66913,0 +105249,Female,48,High School,3,64,71,66,93,6.0,1,93,Rural,Data Analyst,21646,1 +105250,Male,56,Bachelors,17,71,53,33,20,9.0,4,98,Semi-Urban,HR Executive,65534,1 +105251,Male,56,Bachelors,10,64,14,2,39,3.0,7,23,Urban,ML Engineer,55976,0 +105252,Male,55,Bachelors,6,72,93,61,4,6.0,0,74,Urban,HR Executive,128778,1 +105253,Female,36,Bachelors,2,6,76,27,81,4.0,4,25,Semi-Urban,HR Executive,139881,0 +105254,Male,32,Diploma,0,78,87,56,60,8.0,5,6,Urban,ML Engineer,45636,0 +105255,Female,31,High School,1,36,23,76,78,5.0,2,67,Rural,Manager,138178,0 +105256,Male,47,Diploma,2,36,45,50,10,2.0,7,76,Urban,Manager,66122,0 +105257,Male,40,Bachelors,8,42,4,51,87,9.0,0,41,Rural,HR Executive,91548,0 +105258,Female,37,Diploma,0,43,88,49,29,1.0,1,63,Rural,Data Analyst,135522,1 +105259,Female,25,High School,7,15,46,57,82,7.0,0,18,Urban,Manager,134671,0 +105260,Female,24,Diploma,12,81,76,30,66,9.0,2,69,Semi-Urban,ML Engineer,26635,1 +105261,Male,52,Diploma,7,66,15,26,30,3.0,7,13,Rural,Data Analyst,23184,0 +105262,Male,29,Bachelors,13,94,66,15,57,7.0,5,68,Urban,ML Engineer,77426,1 +105263,Female,34,High School,13,1,81,85,89,8.0,7,30,Urban,ML Engineer,146816,0 +105264,Female,49,Diploma,8,46,27,88,56,7.0,4,71,Semi-Urban,HR Executive,100607,0 +105265,Male,21,Masters,18,50,75,64,81,5.0,7,31,Urban,Data Analyst,20647,0 +105266,Female,27,High School,5,69,97,74,96,2.0,2,43,Urban,ML Engineer,43037,1 +105267,Male,21,Bachelors,18,8,97,27,89,0.0,0,87,Urban,ML Engineer,43952,0 +105268,Male,54,Bachelors,3,88,87,5,57,5.0,0,89,Rural,ML Engineer,129500,1 +105269,Male,36,High School,17,64,80,43,24,2.0,2,81,Urban,Software Engineer,126947,1 +105270,Male,48,Bachelors,16,89,40,79,65,0.0,2,98,Urban,HR Executive,101599,1 +105271,Female,48,Masters,14,68,67,30,75,7.0,2,9,Urban,Data Analyst,44514,0 +105272,Female,58,Bachelors,5,93,38,20,6,8.0,4,49,Urban,HR Executive,55522,0 +105273,Male,54,Masters,10,17,76,12,18,0.0,7,48,Urban,Manager,76081,0 +105274,Female,42,PhD,3,96,54,40,29,3.0,4,65,Urban,Data Analyst,36606,1 +105275,Male,48,High School,0,34,92,34,52,9.0,3,80,Urban,ML Engineer,42055,1 +105276,Female,51,Masters,15,37,47,64,31,3.0,1,74,Semi-Urban,HR Executive,107011,0 +105277,Male,38,Bachelors,10,66,25,50,80,0.0,1,76,Semi-Urban,Data Analyst,146541,0 +105278,Male,37,Diploma,2,76,97,22,31,6.0,7,74,Urban,ML Engineer,122025,1 +105279,Female,59,Bachelors,11,17,21,4,39,0.0,0,46,Urban,Data Analyst,77746,0 +105280,Male,42,Bachelors,14,3,33,7,76,4.0,5,53,Urban,HR Executive,128589,0 +105281,Female,39,Masters,19,94,93,27,81,6.0,7,10,Semi-Urban,Software Engineer,135306,0 +105282,Male,43,High School,18,77,31,6,68,3.0,6,5,Rural,ML Engineer,68631,0 +105283,Male,39,Diploma,12,21,3,0,62,4.0,6,79,Semi-Urban,Manager,83245,0 +105284,Male,28,Diploma,13,66,11,44,72,6.0,4,60,Urban,HR Executive,127002,0 +105285,Female,26,Diploma,9,85,43,10,92,7.0,0,96,Urban,Data Analyst,102836,0 +105286,Other,43,High School,2,73,11,80,42,8.0,7,28,Urban,HR Executive,20088,0 +105287,Male,49,PhD,15,34,38,99,12,4.0,3,97,Semi-Urban,HR Executive,50304,1 +105288,Female,25,Bachelors,5,71,65,88,31,2.0,3,96,Urban,HR Executive,143865,1 +105289,Female,55,High School,18,24,88,3,87,4.0,7,11,Semi-Urban,ML Engineer,61203,0 +105290,Male,46,Bachelors,19,5,71,88,96,1.0,7,96,Semi-Urban,ML Engineer,135451,1 +105291,Male,34,Diploma,2,35,73,17,37,9.0,3,87,Urban,Data Analyst,107466,0 +105292,Male,26,Bachelors,19,19,69,37,44,7.0,6,6,Semi-Urban,ML Engineer,91428,0 +105293,Female,36,Bachelors,18,72,45,2,26,9.0,1,59,Rural,Software Engineer,108032,0 +105294,Male,33,High School,14,36,36,2,65,5.0,4,23,Rural,Data Analyst,99332,0 +105295,Male,39,Bachelors,13,37,91,4,65,3.0,6,93,Semi-Urban,Data Analyst,146444,0 +105296,Other,29,Bachelors,16,24,93,28,80,1.0,7,19,Rural,Manager,104192,0 +105297,Female,46,High School,6,95,83,76,85,0.0,1,34,Rural,ML Engineer,80835,1 +105298,Female,59,Diploma,10,91,29,76,33,6.0,5,4,Rural,Software Engineer,26266,0 +105299,Female,28,Bachelors,14,82,94,35,56,5.0,0,74,Urban,ML Engineer,112947,1 +105300,Female,23,Diploma,9,60,66,96,26,4.0,5,16,Rural,Data Analyst,123278,0 +105301,Male,28,Bachelors,14,50,49,99,25,2.0,4,56,Rural,HR Executive,100210,1 +105302,Male,35,Bachelors,12,79,70,14,19,0.0,0,9,Rural,Data Analyst,85000,0 +105303,Female,41,Masters,9,58,62,83,52,3.0,2,40,Rural,HR Executive,92533,1 +105304,Other,56,PhD,7,21,97,25,50,2.0,4,46,Rural,Data Analyst,49450,0 +105305,Female,48,Bachelors,6,40,51,5,91,3.0,4,70,Urban,Data Analyst,43956,0 +105306,Other,38,High School,3,13,26,54,49,6.0,5,81,Urban,Manager,42564,0 +105307,Male,54,Bachelors,3,89,86,30,38,0.0,5,99,Urban,Manager,44660,1 +105308,Male,30,High School,15,6,66,60,88,3.0,5,41,Urban,Manager,87645,0 +105309,Female,32,Bachelors,17,93,90,14,92,1.0,5,39,Urban,HR Executive,105050,0 +105310,Male,26,Masters,13,24,91,39,99,4.0,5,43,Semi-Urban,Manager,111162,0 +105311,Female,31,Bachelors,16,30,36,5,72,4.0,4,61,Semi-Urban,ML Engineer,137941,0 +105312,Female,57,Bachelors,13,29,60,37,16,5.0,1,19,Rural,Data Analyst,62636,0 +105313,Male,39,Bachelors,16,84,65,23,64,8.0,4,60,Rural,ML Engineer,42079,0 +105314,Female,22,Diploma,2,13,42,43,79,3.0,1,28,Semi-Urban,Software Engineer,107870,0 +105315,Female,28,Bachelors,16,57,25,33,48,2.0,1,45,Semi-Urban,HR Executive,69391,0 +105316,Male,35,Bachelors,19,67,41,80,28,8.0,5,73,Urban,Manager,143259,1 +105317,Female,21,Masters,10,9,62,76,24,6.0,0,96,Semi-Urban,Manager,88947,1 +105318,Male,55,Bachelors,19,59,99,21,78,5.0,7,84,Rural,Manager,20922,1 +105319,Male,42,Bachelors,15,43,24,75,7,1.0,0,5,Urban,Software Engineer,107034,0 +105320,Other,27,Bachelors,2,79,95,90,28,5.0,6,85,Urban,Manager,21712,1 +105321,Female,43,Bachelors,13,95,87,99,16,0.0,7,17,Semi-Urban,Data Analyst,84794,1 +105322,Male,35,High School,6,42,61,68,53,5.0,2,50,Urban,Software Engineer,129724,0 +105323,Female,48,Bachelors,14,81,52,0,8,8.0,5,89,Urban,Manager,141346,0 +105324,Female,54,High School,7,46,51,60,52,3.0,6,78,Urban,Software Engineer,31549,0 +105325,Male,34,High School,15,30,42,4,37,5.0,3,75,Rural,Software Engineer,108293,0 +105326,Male,54,Diploma,3,82,95,79,60,8.0,3,6,Rural,Data Analyst,23649,1 +105327,Male,21,Masters,1,18,92,63,22,8.0,5,13,Urban,ML Engineer,50447,0 +105328,Female,25,Bachelors,4,69,39,45,66,1.0,7,44,Semi-Urban,ML Engineer,112372,0 +105329,Female,32,Diploma,14,6,49,87,97,8.0,5,93,Rural,Manager,61378,0 +105330,Female,31,Bachelors,5,33,22,51,8,0.0,0,20,Urban,Data Analyst,143403,0 +105331,Female,36,Masters,10,53,21,55,20,9.0,4,16,Urban,Data Analyst,60088,0 +105332,Male,33,Bachelors,18,42,43,59,65,9.0,5,30,Urban,Software Engineer,33963,0 +105333,Male,34,Diploma,19,73,70,63,60,9.0,3,5,Urban,ML Engineer,139581,0 +105334,Female,36,Bachelors,13,51,38,10,80,4.0,6,31,Urban,ML Engineer,64603,0 +105335,Female,24,Masters,13,36,0,25,72,4.0,1,57,Semi-Urban,Data Analyst,123482,0 +105336,Male,49,Diploma,18,45,85,22,37,5.0,2,90,Rural,ML Engineer,118963,1 +105337,Female,26,Masters,11,99,7,15,83,2.0,4,65,Rural,ML Engineer,118100,0 +105338,Female,41,High School,9,41,72,69,50,1.0,5,3,Rural,Manager,72787,0 +105339,Female,49,High School,9,48,47,81,66,2.0,7,72,Urban,Data Analyst,148469,1 +105340,Female,23,Masters,2,81,64,73,27,9.0,0,0,Rural,Software Engineer,26804,0 +105341,Male,55,Bachelors,6,51,91,5,97,7.0,6,51,Urban,Data Analyst,69355,0 +105342,Male,30,High School,9,51,81,54,30,3.0,5,66,Semi-Urban,ML Engineer,37823,1 +105343,Female,32,Bachelors,7,60,40,65,46,7.0,3,7,Urban,Software Engineer,85180,0 +105344,Male,52,Masters,4,50,72,21,60,2.0,5,30,Urban,Manager,41918,0 +105345,Male,54,Diploma,18,70,39,27,57,2.0,7,86,Urban,Data Analyst,145419,0 +105346,Male,57,Diploma,19,66,60,93,24,7.0,7,10,Rural,Software Engineer,50493,0 +105347,Male,58,Bachelors,16,27,52,69,58,5.0,7,0,Rural,Data Analyst,145873,0 +105348,Female,46,Bachelors,18,84,64,71,74,3.0,2,83,Urban,Data Analyst,124325,1 +105349,Male,35,Diploma,0,71,74,4,93,3.0,4,91,Urban,ML Engineer,91517,1 +105350,Female,42,Bachelors,5,34,16,16,64,4.0,6,10,Urban,Data Analyst,123838,0 +105351,Male,25,Bachelors,9,65,52,43,54,4.0,4,37,Urban,Software Engineer,96459,0 +105352,Female,24,Bachelors,18,47,32,73,44,1.0,5,43,Urban,Manager,61216,0 +105353,Male,49,Diploma,0,49,90,3,48,3.0,4,40,Urban,Data Analyst,64915,0 +105354,Male,31,Diploma,4,48,44,6,97,1.0,7,24,Urban,Data Analyst,115210,0 +105355,Male,23,Diploma,18,80,49,8,40,1.0,2,75,Rural,Software Engineer,108280,0 +105356,Male,39,Diploma,18,30,49,93,88,6.0,7,3,Urban,Manager,51617,0 +105357,Other,22,Bachelors,13,68,88,1,82,8.0,4,38,Urban,HR Executive,51251,0 +105358,Male,31,Bachelors,15,14,54,38,69,2.0,3,35,Urban,Data Analyst,87677,0 +105359,Male,33,Bachelors,13,27,67,66,34,5.0,5,11,Urban,Software Engineer,68267,0 +105360,Female,28,Bachelors,7,86,82,99,19,1.0,0,37,Urban,ML Engineer,87345,1 +105361,Male,54,Bachelors,11,95,51,25,92,2.0,2,62,Rural,Manager,111150,0 +105362,Female,54,High School,4,96,12,15,43,7.0,0,98,Urban,Data Analyst,82068,0 +105363,Female,27,Bachelors,16,20,86,39,64,5.0,6,0,Rural,Software Engineer,102201,0 +105364,Male,57,Diploma,18,0,77,32,20,0.0,4,41,Semi-Urban,Manager,103066,0 +105365,Male,36,Bachelors,2,15,37,37,2,8.0,0,81,Urban,Data Analyst,137476,0 +105366,Female,21,Bachelors,12,36,3,31,54,8.0,6,6,Rural,Manager,35090,0 +105367,Female,44,High School,5,79,6,31,16,2.0,1,62,Rural,Data Analyst,124989,0 +105368,Male,54,Bachelors,13,91,3,90,10,8.0,1,93,Urban,Manager,120651,1 +105369,Female,25,Bachelors,12,15,47,79,6,5.0,2,95,Rural,Manager,79632,0 +105370,Male,34,Bachelors,16,7,43,4,41,5.0,2,44,Rural,HR Executive,22649,0 +105371,Female,28,Bachelors,14,30,71,48,39,7.0,5,98,Rural,HR Executive,90053,1 +105372,Male,26,High School,13,57,19,35,85,9.0,4,26,Rural,Data Analyst,101292,0 +105373,Male,36,High School,2,55,26,63,49,4.0,4,15,Urban,Manager,56102,0 +105374,Male,46,Bachelors,12,43,48,94,1,5.0,7,12,Urban,Software Engineer,144079,0 +105375,Male,59,Bachelors,7,95,10,9,49,2.0,7,76,Semi-Urban,HR Executive,25544,0 +105376,Male,44,Diploma,10,6,17,98,26,9.0,3,71,Urban,ML Engineer,107685,0 +105377,Male,58,High School,8,65,41,68,64,2.0,1,56,Rural,HR Executive,111312,0 +105378,Male,43,Bachelors,0,10,57,97,24,1.0,1,82,Semi-Urban,Manager,48956,1 +105379,Female,38,Diploma,2,54,39,60,51,0.0,3,92,Urban,ML Engineer,149950,1 +105380,Female,47,High School,10,17,29,81,66,3.0,4,2,Rural,HR Executive,109188,0 +105381,Male,27,High School,19,68,78,39,79,1.0,7,23,Urban,HR Executive,122927,0 +105382,Female,41,High School,8,89,8,53,18,0.0,5,59,Semi-Urban,ML Engineer,129941,0 +105383,Male,34,Bachelors,12,52,72,73,74,0.0,7,10,Semi-Urban,Data Analyst,67423,0 +105384,Male,23,Bachelors,11,14,65,2,38,7.0,5,97,Urban,ML Engineer,115855,0 +105385,Male,56,Diploma,19,21,57,97,90,4.0,5,38,Urban,ML Engineer,128448,0 +105386,Male,51,Bachelors,9,56,6,94,83,8.0,7,47,Rural,Software Engineer,76616,0 +105387,Male,22,Diploma,8,7,76,91,54,6.0,0,28,Rural,Manager,37239,0 +105388,Female,33,Masters,3,97,64,32,40,1.0,1,93,Urban,HR Executive,121893,1 +105389,Male,24,Bachelors,6,17,37,13,4,6.0,0,77,Semi-Urban,Software Engineer,79607,0 +105390,Female,40,Masters,9,84,9,14,52,7.0,0,9,Urban,Data Analyst,79157,0 +105391,Female,47,Bachelors,3,29,53,81,35,9.0,3,0,Urban,Software Engineer,108631,0 +105392,Male,33,Bachelors,16,76,89,72,88,7.0,6,61,Urban,Manager,72675,1 +105393,Female,26,Diploma,8,50,38,2,48,6.0,1,80,Urban,Data Analyst,77861,0 +105394,Female,24,Masters,0,47,32,96,70,5.0,4,54,Semi-Urban,ML Engineer,77151,0 +105395,Female,50,High School,14,28,26,21,75,9.0,5,23,Urban,ML Engineer,89140,0 +105396,Male,29,Bachelors,19,45,53,89,96,8.0,6,27,Urban,Data Analyst,142847,0 +105397,Female,56,,2,75,79,61,47,6.0,0,33,Urban,Manager,54116,1 +105398,Female,27,High School,1,26,85,98,74,5.0,2,80,Urban,Data Analyst,41774,1 +105399,Male,28,Bachelors,17,41,97,27,43,8.0,2,61,Urban,Data Analyst,136568,0 +105400,Female,50,Diploma,0,33,66,73,18,8.0,3,89,Urban,Data Analyst,90377,1 +105401,Other,46,Diploma,1,3,32,65,17,4.0,5,6,Urban,HR Executive,23347,0 +105402,Female,32,High School,11,55,62,48,48,8.0,1,68,Urban,Manager,129997,0 +105403,Male,38,Bachelors,8,27,94,61,23,8.0,0,50,Urban,ML Engineer,27135,0 +105404,Male,33,Masters,2,45,52,78,81,8.0,5,84,Urban,Data Analyst,43784,1 +105405,Male,58,High School,1,96,59,3,96,5.0,1,22,Urban,HR Executive,44408,0 +105406,Male,44,High School,13,56,41,14,92,1.0,4,22,Urban,Software Engineer,89911,0 +105407,Male,33,Diploma,18,19,12,12,57,5.0,0,50,Urban,Manager,69156,0 +105408,Male,39,Bachelors,6,68,41,17,98,8.0,6,0,Rural,HR Executive,82774,0 +105409,Male,36,Bachelors,12,23,9,69,68,4.0,4,26,Rural,ML Engineer,20657,0 +105410,Male,37,Bachelors,2,75,78,56,96,8.0,4,30,Rural,Data Analyst,35527,1 +105411,Female,24,Bachelors,4,53,8,70,58,5.0,1,49,Urban,ML Engineer,41398,0 +105412,Male,35,High School,15,57,18,83,81,4.0,4,54,Semi-Urban,Data Analyst,138340,0 +105413,Male,47,Bachelors,7,45,40,31,22,5.0,7,62,Urban,Data Analyst,144084,0 +105414,Female,31,Bachelors,2,11,55,7,4,0.0,2,73,Semi-Urban,Software Engineer,108760,0 +105415,Female,26,Masters,18,70,70,73,29,5.0,1,80,Urban,Data Analyst,81362,1 +105416,Male,28,Bachelors,6,26,92,85,6,0.0,5,6,Urban,HR Executive,20273,0 +105417,Female,58,Masters,18,5,27,3,10,6.0,7,48,Urban,Data Analyst,119842,0 +105418,Male,26,Masters,1,76,97,93,14,7.0,3,61,Semi-Urban,Data Analyst,49310,1 +105419,Male,23,Bachelors,13,16,26,15,74,8.0,7,73,Urban,Software Engineer,32538,0 +105420,Male,28,Bachelors,17,34,64,1,11,0.0,7,7,Urban,Software Engineer,40315,0 +105421,Female,21,High School,8,48,79,55,82,6.0,4,73,Urban,HR Executive,62144,1 +105422,Male,49,Diploma,18,83,1,74,11,5.0,2,0,Rural,HR Executive,92823,0 +105423,Female,34,Bachelors,15,0,67,28,50,7.0,3,0,Urban,Data Analyst,82697,0 +105424,Female,44,High School,7,60,40,6,94,7.0,3,0,Urban,Data Analyst,90707,0 +105425,Female,42,Bachelors,16,56,33,43,27,6.0,3,83,Urban,ML Engineer,30778,0 +105426,Male,23,Masters,6,65,92,74,29,9.0,1,75,Urban,HR Executive,103111,1 +105427,Male,30,Masters,19,62,30,73,26,5.0,5,99,Rural,HR Executive,56641,1 +105428,Female,27,Masters,0,51,34,9,90,0.0,6,56,Rural,ML Engineer,136632,0 +105429,Female,47,Masters,18,41,79,79,86,4.0,5,70,Urban,Data Analyst,29666,1 +105430,Male,26,Bachelors,8,65,25,77,38,7.0,1,66,Urban,ML Engineer,88897,0 +105431,Male,29,Masters,0,20,9,18,99,1.0,3,1,Urban,Software Engineer,52526,0 +105432,Female,44,PhD,19,83,96,34,55,3.0,5,47,Urban,Data Analyst,127195,1 +105433,Male,35,Diploma,5,22,24,30,5,8.0,6,58,Semi-Urban,Manager,127244,0 +105434,Female,29,Diploma,14,17,19,22,28,5.0,7,13,Semi-Urban,ML Engineer,120449,0 +105435,Female,21,Bachelors,13,27,50,53,14,4.0,5,55,Urban,HR Executive,101841,0 +105436,Male,49,Bachelors,4,70,84,32,50,4.0,7,51,Semi-Urban,Software Engineer,139904,1 +105437,Female,39,Bachelors,14,17,54,1,57,3.0,5,62,Urban,HR Executive,31071,0 +105438,Male,45,High School,16,26,48,11,18,1.0,7,1,Urban,ML Engineer,110690,0 +105439,Male,46,High School,12,24,83,33,41,2.0,6,56,Urban,Data Analyst,54389,0 +105440,Female,37,Bachelors,16,52,20,30,11,8.0,2,86,Urban,Manager,61552,0 +105441,Male,47,Masters,12,2,43,7,3,2.0,0,2,Urban,HR Executive,84959,0 +105442,Male,46,Bachelors,14,57,35,2,88,3.0,4,25,Rural,Data Analyst,51310,0 +105443,Male,23,Masters,10,78,67,43,35,7.0,0,97,Semi-Urban,ML Engineer,140429,1 +105444,Female,32,Masters,1,22,20,97,97,9.0,6,97,Rural,ML Engineer,70419,0 +105445,Male,43,Diploma,16,31,38,27,85,2.0,2,48,Rural,Software Engineer,68999,0 +105446,Male,21,Bachelors,5,84,84,65,20,1.0,3,18,Semi-Urban,Software Engineer,64939,1 +105447,Male,36,Bachelors,19,48,27,4,35,9.0,0,13,Urban,ML Engineer,56413,0 +105448,Female,24,Bachelors,9,98,30,45,82,1.0,0,56,Urban,ML Engineer,52981,0 +105449,Female,47,High School,13,89,2,81,12,0.0,6,99,Semi-Urban,HR Executive,122370,1 +105450,Male,53,Masters,1,64,88,18,81,8.0,3,18,Urban,Software Engineer,39198,0 +105451,Male,50,Diploma,16,87,99,56,10,6.0,6,24,Urban,Data Analyst,91810,1 +105452,Male,41,Bachelors,3,90,48,69,2,4.0,4,42,Urban,Data Analyst,139254,1 +105453,Male,37,Masters,8,97,19,98,10,4.0,6,40,Rural,Software Engineer,145508,1 +105454,Male,28,High School,15,56,65,0,14,9.0,4,11,Urban,Data Analyst,32766,0 +105455,Male,54,High School,11,29,44,87,94,7.0,4,53,Rural,Data Analyst,94744,0 +105456,Other,25,Masters,0,0,88,54,70,1.0,3,88,Urban,Manager,132735,0 +105457,Female,43,Masters,4,45,10,62,56,1.0,1,39,Urban,Manager,145982,0 +105458,Male,37,High School,12,64,50,78,64,3.0,4,35,Urban,Manager,44808,0 +105459,Female,33,Bachelors,9,6,0,12,17,8.0,5,27,Semi-Urban,ML Engineer,141283,0 +105460,Female,35,Diploma,1,76,9,97,50,2.0,3,73,Semi-Urban,HR Executive,106925,1 +105461,Male,59,Masters,6,73,30,11,73,6.0,7,59,Urban,Manager,31894,0 +105462,Male,36,Bachelors,19,64,47,96,83,0.0,0,88,Urban,HR Executive,86132,1 +105463,Female,38,High School,19,29,85,63,3,0.0,7,89,Semi-Urban,HR Executive,43804,1 +105464,Male,32,Bachelors,9,87,32,73,50,1.0,6,36,Rural,Data Analyst,128988,0 +105465,Other,42,Masters,14,76,71,60,11,3.0,2,60,Urban,Data Analyst,26189,1 +105466,Male,45,Masters,14,52,37,78,55,4.0,5,91,Rural,ML Engineer,70788,1 +105467,Male,29,Diploma,19,37,48,9,10,1.0,1,34,Rural,HR Executive,44696,0 +105468,Female,48,Bachelors,4,75,61,36,55,3.0,0,83,Rural,ML Engineer,144360,1 +105469,Male,40,Diploma,17,89,76,88,16,3.0,0,22,Urban,ML Engineer,118114,1 +105470,Male,45,PhD,3,71,53,44,75,8.0,5,95,Rural,Manager,73925,1 +105471,Male,37,Diploma,14,45,85,95,92,7.0,2,59,Rural,Manager,107803,1 +105472,Male,49,High School,12,58,26,46,55,1.0,4,15,Urban,ML Engineer,56389,0 +105473,Male,58,Bachelors,8,55,7,96,42,1.0,5,0,Semi-Urban,Data Analyst,28125,0 +105474,Female,51,Bachelors,4,93,51,17,92,8.0,1,66,Semi-Urban,Data Analyst,62338,0 +105475,Female,21,High School,15,81,2,7,32,0.0,2,19,Urban,HR Executive,131247,0 +105476,Male,37,Bachelors,18,6,8,85,45,2.0,2,40,Urban,Software Engineer,41067,0 +105477,Female,46,High School,15,32,60,51,51,1.0,0,91,Rural,ML Engineer,131300,0 +105478,Other,38,High School,13,62,28,49,5,7.0,2,97,Rural,ML Engineer,32355,0 +105479,Male,51,Bachelors,17,80,10,44,99,7.0,7,9,Urban,Manager,93776,0 +105480,Female,43,Bachelors,13,36,6,60,20,8.0,0,25,Urban,HR Executive,88920,0 +105481,Male,52,Bachelors,13,56,26,58,97,1.0,1,4,Urban,Manager,68807,0 +105482,Male,57,Diploma,14,46,95,51,68,1.0,4,85,Urban,Data Analyst,117591,1 +105483,Male,52,Masters,9,28,97,75,40,7.0,7,58,Urban,Data Analyst,36882,1 +105484,Male,21,High School,14,76,30,79,94,3.0,0,56,Semi-Urban,HR Executive,58471,1 +105485,Female,48,Bachelors,11,27,9,75,71,4.0,7,75,Rural,Manager,69297,0 +105486,Male,52,Diploma,4,31,24,56,85,6.0,0,90,Semi-Urban,Manager,136348,0 +105487,Male,39,Masters,7,89,23,47,58,7.0,2,59,Urban,Manager,49251,0 +105488,Male,39,Masters,15,78,11,40,43,2.0,3,84,Urban,Manager,35624,0 +105489,Male,24,Bachelors,19,93,13,67,39,9.0,3,17,Semi-Urban,Software Engineer,121905,0 +105490,Male,37,High School,1,8,79,9,38,7.0,1,0,Urban,Data Analyst,147705,0 +105491,Male,22,Bachelors,6,35,19,55,2,8.0,6,43,Urban,HR Executive,121490,0 +105492,Male,30,Diploma,18,55,39,82,55,1.0,6,78,Urban,Software Engineer,126934,1 +105493,Male,26,Bachelors,5,24,51,6,77,6.0,6,91,Urban,Software Engineer,81204,0 +105494,Male,26,Bachelors,15,71,12,3,23,8.0,2,8,Urban,HR Executive,131546,0 +105495,Male,43,PhD,17,20,20,92,25,8.0,4,43,Urban,Data Analyst,34554,0 +105496,Male,23,Bachelors,5,72,30,83,62,1.0,7,62,Urban,ML Engineer,62616,1 +105497,Male,48,Bachelors,7,95,36,42,58,2.0,3,78,Urban,Software Engineer,112086,1 +105498,Male,49,Bachelors,4,10,99,93,81,9.0,3,94,Urban,Manager,58987,1 +105499,Female,23,Bachelors,5,72,9,16,34,1.0,7,18,Semi-Urban,ML Engineer,55570,0 +105500,Male,35,Bachelors,15,99,46,28,78,7.0,1,34,Rural,Manager,20025,0 +105501,Male,48,High School,7,19,1,26,93,9.0,1,11,Urban,Data Analyst,44901,0 +105502,Female,52,Masters,1,30,56,87,75,3.0,4,94,Urban,ML Engineer,94362,1 +105503,Female,26,Diploma,10,78,42,90,19,7.0,4,40,Rural,ML Engineer,33766,1 +105504,Male,25,Diploma,13,49,96,53,62,3.0,6,38,Urban,Data Analyst,24989,1 +105505,Male,28,High School,15,94,90,60,0,7.0,3,49,Rural,Manager,129146,1 +105506,Male,36,High School,7,8,63,23,77,9.0,1,69,Urban,Software Engineer,142497,0 +105507,Male,57,PhD,5,35,58,29,72,5.0,2,91,Rural,Software Engineer,102367,0 +105508,Male,34,Diploma,9,62,76,13,40,3.0,1,56,Urban,Software Engineer,35619,0 +105509,Male,22,Masters,18,7,10,85,83,9.0,1,4,Rural,Software Engineer,126565,0 +105510,Male,38,Bachelors,14,49,1,46,82,3.0,6,53,Semi-Urban,HR Executive,70630,0 +105511,Female,31,Bachelors,3,56,18,9,17,3.0,1,99,Urban,Data Analyst,95790,0 +105512,Male,43,Diploma,5,1,66,77,15,3.0,7,23,Rural,ML Engineer,27944,0 +105513,Male,31,Bachelors,19,90,97,98,39,1.0,1,84,Urban,Software Engineer,113634,1 +105514,Female,23,Bachelors,14,0,50,51,28,1.0,6,61,Urban,Manager,86082,0 +105515,Male,40,Masters,14,83,28,44,1,5.0,5,95,Urban,ML Engineer,69987,1 +105516,Female,30,Bachelors,0,73,71,98,95,9.0,3,38,Urban,Manager,57189,1 +105517,Male,37,Bachelors,7,40,2,72,85,5.0,7,99,Rural,Data Analyst,97406,0 +105518,Male,42,High School,3,70,50,74,18,9.0,3,95,Urban,HR Executive,55557,1 +105519,Male,45,Bachelors,19,72,94,94,75,5.0,5,30,Urban,ML Engineer,62106,1 +105520,Male,28,Diploma,5,96,41,61,54,6.0,1,10,Urban,Software Engineer,119846,0 +105521,Female,47,Bachelors,17,35,77,76,54,8.0,7,87,Urban,ML Engineer,45569,1 +105522,Female,36,Masters,5,17,5,73,76,2.0,0,84,Urban,ML Engineer,148485,0 +105523,Male,49,Diploma,15,68,17,30,54,7.0,5,46,Semi-Urban,Data Analyst,103994,0 +105524,Female,52,Masters,8,56,83,50,71,7.0,0,32,Semi-Urban,Manager,38756,0 +105525,Female,30,High School,10,48,72,64,21,7.0,7,83,Semi-Urban,Software Engineer,45438,1 +105526,Male,27,Masters,0,54,25,29,35,9.0,3,3,Semi-Urban,ML Engineer,133101,0 +105527,Male,46,Masters,15,94,2,10,50,1.0,6,20,Rural,Manager,90902,0 +105528,Female,51,PhD,13,88,18,65,62,7.0,2,20,Urban,Manager,29015,0 +105529,Male,47,Diploma,12,35,80,23,19,9.0,0,20,Urban,Data Analyst,126930,0 +105530,Male,24,Bachelors,9,82,98,78,34,0.0,3,4,Urban,HR Executive,54324,1 +105531,Male,41,Masters,17,95,43,8,27,8.0,4,11,Rural,Manager,93487,0 +105532,Male,30,Masters,15,22,43,34,44,0.0,3,80,Rural,Software Engineer,79187,0 +105533,Male,54,Diploma,6,59,25,36,73,4.0,1,26,Urban,Manager,56978,0 +105534,Female,52,Masters,19,14,6,19,88,3.0,6,38,Urban,HR Executive,57027,0 +105535,Male,28,High School,16,60,88,5,3,7.0,4,52,Urban,Data Analyst,36971,0 +105536,Male,32,Masters,7,99,30,20,13,1.0,6,10,Rural,Manager,25106,0 +105537,Male,45,Bachelors,18,74,8,35,70,3.0,3,49,Rural,Data Analyst,82193,0 +105538,Male,28,High School,13,71,55,76,1,7.0,2,28,Urban,Manager,92765,0 +105539,Male,43,Masters,1,40,97,24,28,6.0,5,44,Rural,Data Analyst,77727,0 +105540,Female,53,High School,16,23,90,13,33,3.0,4,96,Urban,ML Engineer,49260,0 +105541,Female,48,Masters,8,80,75,60,26,8.0,3,10,Urban,Software Engineer,120059,0 +105542,Female,28,Bachelors,0,56,75,2,49,7.0,0,62,Urban,Manager,38749,0 +105543,Female,45,Masters,11,14,89,68,45,9.0,6,63,Semi-Urban,ML Engineer,77310,0 +105544,Female,41,Bachelors,17,45,76,41,48,9.0,1,64,Urban,Data Analyst,46689,0 +105545,Male,23,High School,14,18,39,80,33,2.0,6,66,Rural,HR Executive,140377,0 +105546,Male,30,Bachelors,1,52,84,25,70,8.0,6,15,Rural,Manager,94924,0 +105547,Male,40,Masters,5,55,57,29,78,2.0,6,15,Urban,Data Analyst,34116,0 +105548,Female,57,Bachelors,17,44,29,41,1,3.0,2,75,Rural,ML Engineer,32136,0 +105549,Female,52,Diploma,9,65,26,55,91,4.0,1,84,Urban,HR Executive,59746,0 +105550,Male,30,Masters,2,61,98,62,92,0.0,4,92,Rural,Data Analyst,25171,1 +105551,Male,42,Masters,4,78,5,10,3,3.0,4,22,Semi-Urban,Manager,81028,0 +105552,Female,47,PhD,18,10,48,77,34,0.0,6,70,Semi-Urban,Software Engineer,115197,0 +105553,Male,54,Masters,13,47,57,98,48,1.0,6,79,Urban,HR Executive,98295,1 +105554,Female,46,PhD,1,72,68,50,93,8.0,7,32,Rural,HR Executive,113307,0 +105555,Female,24,High School,3,90,86,27,13,1.0,4,56,Rural,Data Analyst,32705,1 +105556,Male,22,Masters,14,47,69,55,47,2.0,4,67,Semi-Urban,HR Executive,127853,1 +105557,Male,27,Diploma,0,7,53,24,17,9.0,0,64,Semi-Urban,HR Executive,110605,0 +105558,Male,44,Masters,6,64,33,72,59,5.0,7,17,Rural,Manager,74837,0 +105559,Male,38,High School,4,90,35,2,81,1.0,6,25,Urban,HR Executive,94546,0 +105560,Male,27,Bachelors,4,87,83,63,12,5.0,6,11,Urban,Manager,64298,1 +105561,Male,25,Bachelors,9,54,66,56,90,6.0,1,31,Urban,ML Engineer,144396,0 +105562,Male,41,PhD,15,35,80,86,12,4.0,3,10,Rural,ML Engineer,140948,0 +105563,Male,57,PhD,9,12,38,8,48,9.0,1,82,Urban,HR Executive,78978,0 +105564,Male,44,Bachelors,16,37,93,94,88,7.0,7,58,Rural,ML Engineer,77444,1 +105565,Male,51,Bachelors,10,67,15,99,26,3.0,4,97,Semi-Urban,HR Executive,24146,1 +105566,Male,56,Bachelors,1,65,62,67,91,0.0,0,50,Urban,Data Analyst,126775,1 +105567,Female,46,Bachelors,17,20,33,47,54,6.0,2,80,Semi-Urban,ML Engineer,133481,0 +105568,Male,48,Bachelors,2,44,93,39,21,5.0,3,5,Rural,HR Executive,120196,0 +105569,Male,59,Masters,10,64,8,79,20,7.0,7,94,Semi-Urban,Manager,120850,1 +105570,Female,52,Masters,11,40,26,97,11,5.0,4,33,Urban,Manager,142726,0 +105571,Male,36,Diploma,13,12,79,92,96,2.0,4,29,Urban,Manager,48149,0 +105572,Male,58,High School,3,33,30,90,25,7.0,4,77,Urban,ML Engineer,119418,0 +105573,Male,56,Bachelors,0,1,12,17,95,4.0,3,58,Rural,Manager,52067,0 +105574,Female,24,Diploma,14,84,24,37,18,8.0,3,97,Semi-Urban,Software Engineer,144851,1 +105575,Female,39,Diploma,3,46,59,10,14,1.0,5,85,Rural,Manager,115595,0 +105576,Female,37,Masters,14,27,17,80,55,5.0,1,24,Urban,Software Engineer,24807,0 +105577,Male,54,Diploma,12,52,85,13,56,9.0,4,59,Urban,Data Analyst,35146,0 +105578,Female,49,Bachelors,2,59,97,82,20,7.0,1,85,Urban,Manager,59479,1 +105579,Female,23,Masters,9,4,76,55,56,4.0,4,81,Semi-Urban,ML Engineer,54663,0 +105580,Female,46,Masters,1,8,15,85,65,4.0,4,8,Rural,Data Analyst,30550,0 +105581,Female,42,PhD,10,80,56,57,35,0.0,5,64,Rural,ML Engineer,82684,1 +105582,Female,35,Bachelors,9,39,82,1,2,1.0,1,82,Semi-Urban,Manager,72028,0 +105583,Female,52,Bachelors,4,57,84,75,33,9.0,4,33,Urban,HR Executive,149603,1 +105584,Other,31,Bachelors,16,50,64,74,27,4.0,3,57,Urban,Software Engineer,99033,1 +105585,Female,37,Diploma,15,64,34,73,45,1.0,4,81,Urban,Data Analyst,149315,1 +105586,Male,44,Bachelors,11,8,9,31,95,5.0,6,97,Urban,Manager,136941,0 +105587,Male,21,Diploma,13,60,12,47,41,5.0,0,8,Rural,Software Engineer,46940,0 +105588,Male,44,Bachelors,17,67,66,70,67,9.0,5,85,Rural,Software Engineer,96157,1 +105589,Female,41,Bachelors,4,7,29,27,37,1.0,4,2,Urban,Data Analyst,117147,0 +105590,Male,51,Bachelors,3,54,48,11,5,6.0,7,25,Urban,Data Analyst,85948,0 +105591,Male,26,Bachelors,15,1,61,62,72,5.0,3,56,Urban,Manager,79101,0 +105592,Male,39,PhD,9,79,22,54,49,5.0,4,79,Rural,HR Executive,119152,0 +105593,Male,40,Bachelors,5,74,40,47,93,3.0,0,52,Urban,Data Analyst,122492,0 +105594,Male,28,Masters,19,82,32,52,30,3.0,4,10,Rural,Software Engineer,137259,0 +105595,Male,44,Diploma,10,34,87,19,64,9.0,6,71,Semi-Urban,Software Engineer,109448,0 +105596,Male,50,Bachelors,19,23,35,40,21,3.0,5,9,Urban,Data Analyst,140641,0 +105597,Male,58,Diploma,11,57,15,70,86,9.0,4,60,Urban,Data Analyst,27743,0 +105598,Male,35,Bachelors,1,32,79,38,57,1.0,3,28,Semi-Urban,Software Engineer,145920,0 +105599,Male,40,Masters,12,65,53,3,23,4.0,2,6,Urban,Software Engineer,147622,0 +105600,Male,21,Diploma,0,66,53,63,1,2.0,2,41,Rural,ML Engineer,50276,0 +105601,Female,55,Bachelors,17,17,45,2,92,4.0,6,18,Urban,Data Analyst,127900,0 +105602,Male,22,Bachelors,0,23,71,13,2,0.0,0,51,Rural,Data Analyst,29129,0 +105603,Male,32,Diploma,11,15,85,77,21,2.0,3,34,Urban,Manager,41842,0 +105604,Female,45,High School,19,13,81,87,62,0.0,6,72,Urban,Manager,44447,1 +105605,Male,32,Masters,15,49,53,88,39,5.0,7,54,Urban,HR Executive,88550,1 +105606,Other,49,Bachelors,4,60,44,57,39,9.0,2,96,Urban,HR Executive,135060,1 +105607,Male,47,Bachelors,17,7,7,4,74,9.0,5,43,Urban,Manager,99016,0 +105608,Male,40,Bachelors,11,12,63,86,89,8.0,0,56,Urban,ML Engineer,74940,0 +105609,Male,38,Bachelors,6,17,51,58,27,6.0,7,97,Rural,Data Analyst,97078,0 +105610,Female,23,Bachelors,4,57,51,16,68,6.0,4,18,Urban,Manager,57031,0 +105611,Female,39,Masters,3,74,68,90,13,7.0,0,83,Rural,ML Engineer,108735,1 +105612,Male,56,Bachelors,7,67,45,29,12,2.0,4,85,Urban,Manager,107703,0 +105613,Male,47,Masters,17,76,51,96,9,7.0,0,83,Urban,Manager,126590,1 +105614,Female,44,Diploma,14,99,55,10,77,7.0,6,20,Urban,HR Executive,64593,0 +105615,Female,30,Diploma,0,46,29,39,23,5.0,6,50,Rural,Data Analyst,42343,0 +105616,Male,52,Bachelors,9,68,13,25,79,8.0,5,99,Rural,Manager,21164,0 +105617,Female,56,Bachelors,12,60,46,26,87,6.0,5,62,Urban,Manager,143902,0 +105618,Male,29,High School,13,38,49,90,36,7.0,3,43,Urban,Manager,49460,0 +105619,Male,36,High School,11,35,29,65,62,1.0,7,99,Semi-Urban,Software Engineer,82411,0 +105620,Female,30,High School,19,25,34,94,28,6.0,3,50,Urban,ML Engineer,143761,0 +105621,Male,33,Diploma,0,91,75,91,94,0.0,7,41,Semi-Urban,Manager,100327,1 +105622,Male,57,Bachelors,19,66,50,92,51,9.0,1,65,Semi-Urban,Software Engineer,113757,1 +105623,Male,55,Masters,11,58,4,41,97,6.0,6,62,Urban,Manager,142068,0 +105624,Male,34,Bachelors,18,42,84,84,50,9.0,6,95,Urban,HR Executive,77377,1 +105625,Other,25,Masters,5,43,5,35,21,5.0,3,81,Urban,Software Engineer,42845,0 +105626,Male,37,Bachelors,9,24,14,67,97,6.0,1,18,Rural,HR Executive,49267,0 +105627,Other,30,Masters,10,18,7,29,56,8.0,4,9,Rural,Software Engineer,145360,0 +105628,Female,53,Masters,4,67,67,35,54,3.0,1,14,Urban,Software Engineer,103695,0 +105629,Other,35,Bachelors,7,85,92,91,41,6.0,0,87,Urban,ML Engineer,40605,1 +105630,Female,43,Diploma,2,45,46,79,60,8.0,4,42,Semi-Urban,ML Engineer,40417,0 +105631,Female,23,Diploma,17,82,97,10,78,9.0,7,97,Rural,Software Engineer,115963,1 +105632,Female,33,Masters,18,21,53,15,45,1.0,7,88,Rural,ML Engineer,47278,0 +105633,Female,33,High School,11,31,65,55,1,2.0,4,47,Urban,Software Engineer,43251,0 +105634,Female,48,PhD,4,16,21,78,21,4.0,2,32,Urban,Software Engineer,132765,0 +105635,Other,33,Bachelors,15,21,26,75,30,2.0,1,5,Semi-Urban,ML Engineer,96869,0 +105636,Female,46,Masters,5,85,76,35,94,2.0,2,66,Urban,Software Engineer,64963,1 +105637,Male,28,Masters,19,43,23,79,79,1.0,2,74,Semi-Urban,ML Engineer,88141,0 +105638,Female,23,PhD,13,66,97,91,81,9.0,3,49,Rural,Software Engineer,127790,1 +105639,Male,22,High School,9,73,62,76,63,0.0,5,72,Urban,ML Engineer,135660,1 +105640,Male,35,Bachelors,14,19,54,35,12,3.0,3,96,Urban,Data Analyst,102160,0 +105641,Female,35,Masters,8,19,29,2,19,1.0,4,56,Rural,HR Executive,89958,0 +105642,Female,35,Bachelors,0,54,55,27,70,4.0,6,62,Semi-Urban,Data Analyst,138418,0 +105643,Female,50,Bachelors,6,31,60,2,99,3.0,3,78,Urban,Manager,117176,0 +105644,Female,30,High School,2,96,64,16,42,6.0,5,42,Urban,HR Executive,147011,0 +105645,Male,43,Diploma,16,11,49,96,23,7.0,2,90,Semi-Urban,Software Engineer,33260,1 +105646,Male,49,Bachelors,10,20,28,55,8,2.0,5,61,Urban,Manager,53892,0 +105647,Male,27,Bachelors,0,39,82,22,37,8.0,0,92,Urban,Data Analyst,45221,1 +105648,Male,21,Masters,5,6,56,54,44,9.0,3,86,Semi-Urban,ML Engineer,133962,0 +105649,Other,26,High School,16,71,19,74,7,4.0,0,45,Urban,Manager,59072,0 +105650,Female,39,High School,14,33,65,93,71,7.0,2,74,Urban,Data Analyst,110415,1 +105651,Male,40,Diploma,5,61,45,19,40,7.0,7,76,Urban,ML Engineer,45922,0 +105652,Female,58,Diploma,12,48,6,97,57,8.0,6,16,Urban,Manager,99270,0 +105653,Male,24,High School,4,43,72,30,96,2.0,6,72,Urban,HR Executive,93363,0 +105654,Male,36,High School,19,37,46,89,28,3.0,5,9,Semi-Urban,HR Executive,72817,0 +105655,Male,57,High School,15,22,26,25,11,1.0,1,59,Semi-Urban,Data Analyst,106650,0 +105656,Male,23,High School,19,13,22,25,49,3.0,4,86,Urban,Software Engineer,84574,0 +105657,Male,24,Masters,2,92,85,69,91,5.0,6,50,Urban,Manager,149226,1 +105658,Male,28,Diploma,0,60,8,32,7,6.0,4,15,Urban,Software Engineer,86945,0 +105659,Male,32,Diploma,13,55,33,20,72,1.0,4,95,Urban,Manager,70217,0 +105660,Female,36,Masters,0,5,20,38,20,6.0,0,1,Rural,ML Engineer,98933,0 +105661,Female,48,PhD,16,46,37,44,6,2.0,0,48,Rural,Data Analyst,68007,0 +105662,Female,49,Bachelors,18,18,2,95,76,8.0,6,86,Rural,Software Engineer,123497,0 +105663,Female,37,Diploma,11,92,84,24,72,7.0,3,14,Urban,Manager,139508,0 +105664,Male,50,High School,1,62,55,84,11,3.0,4,31,Rural,ML Engineer,81353,0 +105665,Female,30,High School,7,78,80,43,90,5.0,5,87,Urban,Manager,84594,1 +105666,Other,35,High School,2,99,91,65,60,4.0,2,94,Rural,Data Analyst,118525,1 +105667,Female,53,PhD,6,11,78,50,74,3.0,7,74,Semi-Urban,Software Engineer,141841,0 +105668,Male,54,Diploma,3,16,68,64,42,8.0,0,86,Semi-Urban,ML Engineer,62929,0 +105669,Female,45,Diploma,14,82,71,5,72,5.0,3,88,Urban,ML Engineer,60262,1 +105670,Male,31,High School,0,66,39,36,76,9.0,6,55,Semi-Urban,Data Analyst,49674,0 +105671,Male,22,Bachelors,15,71,90,48,71,2.0,5,69,Urban,Software Engineer,100244,1 +105672,Male,40,High School,12,13,12,49,72,5.0,4,49,Urban,Data Analyst,133308,0 +105673,Male,23,Diploma,10,87,8,78,69,5.0,4,45,Urban,ML Engineer,128160,0 +105674,Female,24,Bachelors,13,85,59,83,42,5.0,1,40,Urban,HR Executive,28714,1 +105675,Other,34,Bachelors,15,44,67,91,80,5.0,3,32,Urban,ML Engineer,81510,0 +105676,Male,23,Bachelors,7,32,58,75,50,4.0,6,16,Rural,HR Executive,67815,0 +105677,Male,52,Diploma,12,34,56,97,93,1.0,1,92,Rural,ML Engineer,105113,1 +105678,Male,42,High School,19,95,92,67,68,9.0,7,73,Urban,Manager,145745,1 +105679,Male,37,Bachelors,1,27,88,94,41,9.0,4,71,Urban,Software Engineer,90674,1 +105680,Male,36,High School,5,15,70,95,9,0.0,7,58,Urban,Data Analyst,72386,1 +105681,Male,58,Diploma,15,30,32,68,89,4.0,2,97,Urban,Manager,70756,0 +105682,Female,52,Bachelors,8,16,41,49,21,8.0,0,16,Rural,ML Engineer,119094,0 +105683,Male,57,Diploma,16,26,57,38,92,5.0,0,73,Rural,Manager,103537,0 +105684,Female,45,Bachelors,13,16,19,76,37,1.0,7,49,Semi-Urban,Manager,30919,0 +105685,Female,48,High School,13,53,17,61,6,9.0,3,31,Urban,Software Engineer,69676,0 +105686,Male,33,Masters,6,2,79,11,93,1.0,3,85,Urban,ML Engineer,116075,0 +105687,Male,49,High School,12,26,39,74,50,3.0,5,29,Urban,Software Engineer,22986,0 +105688,Male,53,Masters,14,29,19,48,23,8.0,0,74,Urban,ML Engineer,52355,0 +105689,Female,25,High School,4,27,17,66,14,5.0,2,33,Semi-Urban,Manager,75221,0 +105690,Female,26,Masters,5,82,83,12,80,4.0,2,48,Urban,HR Executive,80784,0 +105691,Male,53,Diploma,13,87,33,47,69,8.0,6,24,Urban,HR Executive,101762,0 +105692,Male,36,Diploma,19,85,45,92,12,9.0,6,88,Urban,HR Executive,21017,1 +105693,Male,43,High School,7,99,67,24,66,9.0,5,58,Urban,HR Executive,36796,1 +105694,Male,55,Bachelors,17,44,1,11,27,4.0,5,9,Rural,ML Engineer,55520,0 +105695,Female,34,Masters,15,61,69,70,70,5.0,2,84,Urban,ML Engineer,69776,1 +105696,Female,42,Diploma,11,93,56,99,27,0.0,4,41,Urban,Data Analyst,74196,1 +105697,Other,59,High School,16,24,51,37,74,3.0,6,66,Rural,HR Executive,35407,0 +105698,Male,32,Diploma,9,59,68,44,3,4.0,6,22,Urban,Software Engineer,127637,0 +105699,Male,43,Bachelors,13,97,27,6,7,5.0,6,2,Urban,Data Analyst,130823,0 +105700,Female,58,Diploma,12,54,76,99,64,6.0,2,29,Urban,Manager,26860,1 +105701,Male,48,Bachelors,11,72,33,76,44,6.0,4,79,Rural,ML Engineer,50869,1 +105702,Male,48,Masters,7,91,9,49,33,6.0,7,47,Urban,HR Executive,141779,0 +105703,Male,36,Bachelors,2,28,77,93,45,5.0,7,24,Urban,ML Engineer,52002,0 +105704,Male,38,High School,16,31,73,25,14,8.0,5,27,Urban,ML Engineer,87290,0 +105705,Male,58,Bachelors,13,36,78,24,61,2.0,7,21,Urban,HR Executive,90922,0 +105706,Female,42,High School,13,1,50,11,37,3.0,3,15,Semi-Urban,Software Engineer,77943,0 +105707,Male,29,High School,0,12,26,0,66,6.0,6,60,Semi-Urban,ML Engineer,66687,0 +105708,Male,51,Bachelors,3,25,29,7,62,6.0,7,43,Rural,Manager,113745,0 +105709,Female,25,Diploma,10,99,90,71,75,4.0,5,76,Urban,HR Executive,82192,1 +105710,Male,31,High School,6,49,6,34,32,1.0,4,54,Urban,Software Engineer,95559,0 +105711,Female,24,Bachelors,18,92,98,71,32,8.0,3,94,Urban,ML Engineer,26697,1 +105712,Male,49,Bachelors,0,81,82,89,56,5.0,3,11,Urban,Software Engineer,102025,1 +105713,Female,45,Bachelors,17,76,84,20,70,4.0,3,35,Urban,Software Engineer,86040,0 +105714,Male,57,Masters,16,30,83,75,26,3.0,5,87,Urban,Software Engineer,37043,1 +105715,Other,41,Diploma,11,58,86,54,42,1.0,3,85,Rural,Manager,103359,1 +105716,Male,48,Bachelors,1,90,41,44,64,8.0,2,48,Semi-Urban,Manager,74957,0 +105717,Male,52,Diploma,6,51,25,47,29,1.0,4,10,Urban,Data Analyst,37627,0 +105718,Male,27,Masters,11,51,51,46,22,0.0,7,66,Rural,Manager,59939,0 +105719,Male,48,Bachelors,6,41,66,75,42,5.0,7,37,Urban,HR Executive,89681,0 +105720,Female,58,Masters,4,69,66,11,70,3.0,7,56,Semi-Urban,Software Engineer,113490,0 +105721,Male,32,Bachelors,14,30,24,95,61,4.0,4,9,Semi-Urban,Data Analyst,20153,0 +105722,Male,40,Diploma,16,91,12,19,86,5.0,3,6,Rural,ML Engineer,47790,0 +105723,Male,25,Bachelors,3,45,55,80,68,6.0,3,83,Rural,Data Analyst,149662,1 +105724,Male,28,Bachelors,17,18,24,4,3,5.0,7,57,Semi-Urban,Software Engineer,91035,0 +105725,Female,57,High School,15,58,35,83,60,6.0,1,5,Urban,Software Engineer,98313,0 +105726,Male,24,Bachelors,19,78,69,0,70,4.0,2,90,Urban,ML Engineer,117382,1 +105727,Male,26,Masters,5,86,53,95,68,2.0,3,25,Urban,Software Engineer,126677,1 +105728,Male,43,Bachelors,7,61,2,31,43,9.0,2,4,Rural,Data Analyst,73966,0 +105729,Male,56,Masters,19,24,85,77,89,9.0,6,67,Urban,HR Executive,125487,1 +105730,Male,25,Masters,14,21,22,76,47,6.0,3,77,Urban,Data Analyst,120261,0 +105731,Other,42,Masters,16,56,25,54,35,0.0,7,9,Urban,HR Executive,85898,0 +105732,Male,29,Bachelors,12,10,34,5,38,4.0,7,27,Semi-Urban,Data Analyst,45321,0 +105733,Female,40,Diploma,2,39,72,19,38,9.0,4,69,Semi-Urban,Software Engineer,59306,0 +105734,Male,28,High School,17,45,93,47,80,2.0,1,58,Urban,HR Executive,24286,1 +105735,Male,49,High School,11,28,77,65,77,2.0,5,7,Urban,HR Executive,66551,0 +105736,Male,27,PhD,3,59,61,31,23,8.0,1,34,Semi-Urban,HR Executive,88566,0 +105737,Female,30,Bachelors,13,56,30,66,9,0.0,5,69,Rural,Software Engineer,70941,0 +105738,Female,53,Bachelors,18,36,44,97,11,1.0,4,25,Semi-Urban,Manager,56654,0 +105739,Female,25,Bachelors,1,51,37,14,26,7.0,4,75,Urban,ML Engineer,89269,0 +105740,Female,28,High School,3,72,64,73,65,2.0,7,86,Urban,ML Engineer,36183,1 +105741,Female,23,Bachelors,14,61,5,15,33,0.0,0,58,Urban,Manager,42848,0 +105742,Male,51,Bachelors,7,85,88,50,99,0.0,6,91,Urban,HR Executive,130522,1 +105743,Male,35,Bachelors,10,42,54,80,19,8.0,6,95,Rural,Software Engineer,138235,1 +105744,Female,32,Masters,3,58,79,36,26,0.0,4,87,Rural,Software Engineer,68189,1 +105745,Male,42,Bachelors,19,47,90,3,9,0.0,0,36,Semi-Urban,ML Engineer,22457,0 +105746,Male,25,Masters,9,8,69,98,31,3.0,7,45,Rural,ML Engineer,130623,0 +105747,Female,34,Bachelors,13,70,55,88,70,8.0,5,47,Urban,Software Engineer,74318,1 +105748,Other,41,Diploma,4,89,93,92,16,8.0,6,65,Semi-Urban,Data Analyst,45350,1 +105749,Female,42,Masters,3,94,63,62,55,8.0,6,3,Urban,Data Analyst,135354,0 +105750,Male,59,Bachelors,4,38,23,95,52,7.0,3,54,Semi-Urban,Software Engineer,32685,0 +105751,Male,56,Bachelors,6,67,88,39,95,4.0,3,5,Urban,HR Executive,76395,0 +105752,Other,29,Masters,15,63,18,36,87,9.0,6,12,Urban,Manager,58394,0 +105753,Male,58,Bachelors,4,89,88,49,74,6.0,6,20,Rural,Data Analyst,84943,1 +105754,Male,25,PhD,19,24,50,73,19,1.0,2,21,Urban,HR Executive,47718,0 +105755,Male,37,Diploma,4,64,23,70,2,3.0,4,60,Urban,Data Analyst,105376,0 +105756,Male,38,Masters,16,49,25,1,5,5.0,5,98,Semi-Urban,Data Analyst,89984,0 +105757,Male,45,Bachelors,13,44,30,26,15,9.0,2,55,Rural,ML Engineer,37776,0 +105758,Male,45,High School,10,24,8,80,45,1.0,2,71,Urban,Data Analyst,99371,0 +105759,Male,39,Diploma,4,31,48,94,47,8.0,3,64,Rural,Manager,45852,1 +105760,Female,36,Masters,10,89,19,21,85,3.0,3,84,Semi-Urban,Software Engineer,138446,0 +105761,Male,27,Masters,6,92,16,77,86,7.0,6,19,Semi-Urban,Data Analyst,123076,0 +105762,Female,49,Bachelors,15,78,28,87,37,3.0,1,80,Urban,HR Executive,144032,1 +105763,Male,27,High School,3,49,4,65,71,1.0,3,10,Urban,Software Engineer,53030,0 +105764,Male,49,Bachelors,3,41,43,97,44,0.0,2,19,Rural,Software Engineer,94418,0 +105765,Other,23,Bachelors,2,36,72,71,98,5.0,5,89,Semi-Urban,Software Engineer,75528,1 +105766,Male,29,Bachelors,14,8,61,23,19,3.0,3,1,Semi-Urban,HR Executive,54198,0 +105767,Male,54,Diploma,12,45,22,1,29,9.0,6,72,Rural,Software Engineer,111264,0 +105768,Female,42,Masters,15,16,61,74,24,7.0,6,53,Urban,ML Engineer,46239,0 +105769,Female,23,Masters,10,43,31,77,69,9.0,2,62,Rural,ML Engineer,23912,0 +105770,Female,50,Bachelors,5,82,71,22,36,8.0,1,76,Rural,HR Executive,117678,1 +105771,Male,33,Masters,14,52,91,3,35,5.0,4,59,Semi-Urban,Software Engineer,69121,0 +105772,Male,24,Masters,0,22,89,11,37,6.0,4,20,Urban,HR Executive,26271,0 +105773,Male,54,High School,2,81,1,83,98,9.0,0,89,Urban,Data Analyst,30799,1 +105774,Female,36,Diploma,14,29,43,37,71,3.0,6,31,Urban,ML Engineer,89580,0 +105775,Female,34,Bachelors,7,56,74,94,7,2.0,7,71,Semi-Urban,Data Analyst,132143,1 +105776,Male,28,High School,18,34,5,96,31,7.0,2,39,Urban,Data Analyst,119565,0 +105777,Male,35,Bachelors,4,20,88,43,97,7.0,1,58,Semi-Urban,ML Engineer,21894,0 +105778,Male,46,PhD,12,47,28,46,55,9.0,0,67,Urban,Manager,113351,0 +105779,Female,33,Bachelors,7,45,78,42,84,3.0,2,38,Rural,Software Engineer,112731,0 +105780,Male,29,Diploma,5,0,8,32,32,2.0,4,74,Urban,Software Engineer,78415,0 +105781,Female,46,Masters,10,37,57,19,14,9.0,3,94,Urban,Software Engineer,34391,0 +105782,Female,54,Bachelors,4,37,44,24,85,0.0,4,81,Urban,Manager,111115,0 +105783,Female,52,Bachelors,5,47,57,79,55,8.0,1,21,Rural,Software Engineer,96176,0 +105784,Other,31,Masters,8,50,33,36,69,4.0,6,51,Urban,Data Analyst,131876,0 +105785,Other,56,Bachelors,14,98,98,69,87,8.0,0,35,Urban,HR Executive,77985,1 +105786,Male,24,Bachelors,8,98,71,57,87,4.0,1,46,Semi-Urban,ML Engineer,92023,1 +105787,Male,23,Masters,15,27,71,56,82,9.0,7,40,Urban,Manager,119784,0 +105788,Female,42,High School,2,70,57,30,88,3.0,3,3,Urban,Data Analyst,27611,0 +105789,Female,33,Masters,8,14,92,66,27,4.0,2,15,Rural,Data Analyst,131380,0 +105790,Female,54,Diploma,9,95,90,81,84,1.0,7,59,Semi-Urban,Software Engineer,126916,1 +105791,Male,31,High School,2,81,98,39,62,5.0,1,38,Rural,HR Executive,27372,1 +105792,Male,59,Diploma,19,94,17,20,95,1.0,6,19,Semi-Urban,HR Executive,82239,0 +105793,Male,34,Diploma,2,22,33,50,91,9.0,7,24,Semi-Urban,ML Engineer,25450,0 +105794,Male,50,Bachelors,3,67,11,0,25,4.0,0,13,Urban,Manager,66620,0 +105795,Male,26,Masters,2,38,35,85,10,2.0,7,81,Urban,Software Engineer,125415,1 +105796,Female,31,Bachelors,8,3,52,61,8,8.0,3,24,Urban,ML Engineer,148110,0 +105797,Male,58,Diploma,19,29,79,26,91,4.0,3,87,Semi-Urban,ML Engineer,140694,0 +105798,Male,24,High School,15,48,17,92,28,3.0,4,31,Urban,ML Engineer,125076,0 +105799,Female,56,High School,3,57,59,77,67,9.0,6,69,Urban,Software Engineer,99393,1 +105800,Female,42,Bachelors,5,0,71,4,45,6.0,5,34,Semi-Urban,Manager,108807,0 +105801,Female,30,Diploma,11,90,40,1,79,9.0,1,81,Urban,Data Analyst,143654,0 +105802,Male,39,High School,13,56,16,60,74,4.0,2,97,Semi-Urban,Manager,148538,0 +105803,Male,23,Bachelors,11,22,67,73,20,5.0,6,50,Semi-Urban,Software Engineer,127910,0 +105804,Female,38,Diploma,14,14,40,81,99,5.0,5,8,Urban,Software Engineer,40758,0 +105805,Female,27,Diploma,3,58,71,73,15,2.0,0,75,Rural,HR Executive,73328,1 +105806,Male,54,Masters,4,97,45,52,17,2.0,1,24,Urban,ML Engineer,126679,0 +105807,Male,47,Masters,0,35,86,34,67,2.0,2,59,Urban,Software Engineer,109077,0 +105808,Male,37,Bachelors,5,63,32,60,86,5.0,2,66,Urban,Data Analyst,145144,0 +105809,Female,40,High School,1,6,43,57,57,9.0,2,75,Urban,Manager,148453,0 +105810,Male,29,Masters,11,71,30,47,59,8.0,3,37,Semi-Urban,ML Engineer,20254,0 +105811,Female,35,Masters,2,44,34,97,44,8.0,6,42,Urban,Manager,28471,0 +105812,Male,30,Diploma,6,68,87,62,9,0.0,1,97,Urban,HR Executive,52725,1 +105813,Male,59,Bachelors,2,48,88,24,46,0.0,4,87,Urban,HR Executive,69112,1 +105814,Male,22,Bachelors,16,24,86,8,84,4.0,6,25,Urban,Data Analyst,41951,0 +105815,Male,23,High School,7,2,99,10,14,9.0,2,46,Semi-Urban,Data Analyst,21512,0 +105816,Male,30,Diploma,6,64,45,68,83,8.0,6,0,Urban,Manager,54695,0 +105817,Female,26,Bachelors,14,11,68,81,44,1.0,3,19,Urban,ML Engineer,93477,0 +105818,Male,49,Masters,2,56,46,28,38,4.0,4,73,Semi-Urban,HR Executive,34572,0 +105819,Female,52,Bachelors,13,27,4,44,21,0.0,1,8,Urban,Data Analyst,77624,0 +105820,Male,40,Bachelors,19,33,82,35,51,8.0,3,30,Rural,Manager,88967,0 +105821,Male,37,Masters,7,40,36,90,65,0.0,5,36,Rural,HR Executive,32591,0 +105822,Female,38,Masters,10,13,22,46,4,4.0,6,98,Rural,HR Executive,91810,0 +105823,Female,50,Masters,2,60,75,87,87,9.0,5,77,Rural,HR Executive,100163,1 +105824,Male,23,Diploma,13,54,52,42,43,1.0,3,98,Urban,ML Engineer,85136,1 +105825,Female,50,Diploma,7,83,21,54,91,2.0,2,88,Rural,ML Engineer,119848,1 +105826,Female,52,High School,16,31,13,64,99,8.0,7,8,Semi-Urban,Manager,27250,0 +105827,Male,53,Bachelors,13,69,33,79,46,1.0,5,3,Rural,Data Analyst,31855,0 +105828,Female,54,Bachelors,10,92,28,81,17,1.0,7,14,Rural,Software Engineer,65445,0 +105829,Male,52,High School,10,11,50,40,35,0.0,1,77,Urban,HR Executive,21744,0 +105830,Male,35,Bachelors,1,73,72,11,26,2.0,1,9,Urban,Manager,111625,0 +105831,Male,55,Masters,11,66,5,16,8,5.0,6,26,Semi-Urban,Data Analyst,36607,0 +105832,Male,55,Diploma,11,49,90,47,38,6.0,4,1,Urban,ML Engineer,106187,0 +105833,Male,37,High School,8,44,15,34,21,8.0,0,44,Semi-Urban,Manager,102413,0 +105834,Male,31,Bachelors,12,16,86,6,77,3.0,7,14,Urban,ML Engineer,92340,0 +105835,Male,45,Masters,14,59,76,69,96,3.0,6,5,Semi-Urban,HR Executive,136542,0 +105836,Female,39,High School,8,54,9,36,83,8.0,0,95,Rural,Manager,96584,0 +105837,Female,42,Masters,15,50,41,86,6,8.0,0,22,Urban,Software Engineer,134440,0 +105838,Female,39,Masters,9,45,28,84,17,9.0,7,57,Semi-Urban,ML Engineer,93311,0 +105839,Female,51,Bachelors,3,29,45,60,59,6.0,3,93,Semi-Urban,Software Engineer,143966,0 +105840,Male,41,Bachelors,0,6,86,84,58,4.0,1,36,Urban,Software Engineer,107608,0 +105841,Male,43,Masters,9,55,42,52,79,1.0,1,12,Semi-Urban,ML Engineer,25287,0 +105842,Female,36,Bachelors,16,93,58,63,39,7.0,4,66,Semi-Urban,ML Engineer,120239,1 +105843,Male,27,High School,1,94,51,19,94,1.0,5,21,Semi-Urban,Software Engineer,35027,0 +105844,Female,59,High School,2,45,67,80,23,9.0,2,76,Semi-Urban,HR Executive,93183,1 +105845,Male,44,Bachelors,18,17,11,76,80,3.0,6,23,Urban,ML Engineer,24284,0 +105846,Male,45,Bachelors,1,71,99,98,54,0.0,5,50,Urban,Software Engineer,43899,1 +105847,Female,31,Bachelors,12,70,61,21,82,9.0,3,85,Urban,Manager,31464,0 +105848,Male,39,Bachelors,8,28,4,16,70,5.0,5,57,Urban,HR Executive,36354,0 +105849,Male,42,Masters,0,66,61,74,53,3.0,1,90,Urban,HR Executive,72861,1 +105850,Male,38,Bachelors,6,17,63,10,94,6.0,5,14,Urban,Manager,46045,0 +105851,Male,36,High School,11,11,33,50,52,6.0,6,70,Rural,Software Engineer,137038,0 +105852,Female,25,High School,4,38,26,83,35,5.0,5,29,Urban,Data Analyst,100765,0 +105853,Male,22,Bachelors,6,83,88,19,65,7.0,7,68,Semi-Urban,ML Engineer,41821,1 +105854,Female,59,Masters,13,14,8,80,58,1.0,0,73,Semi-Urban,Manager,121133,0 +105855,Male,43,Masters,0,55,39,48,66,1.0,5,6,Rural,Software Engineer,123615,0 +105856,Male,55,Masters,16,67,11,73,97,4.0,1,35,Urban,Data Analyst,104669,0 +105857,Male,49,Bachelors,2,70,4,54,55,6.0,7,72,Urban,HR Executive,116734,0 +105858,Female,38,Diploma,2,97,85,91,83,0.0,0,29,Urban,Software Engineer,67070,1 +105859,Female,30,Bachelors,11,25,99,33,80,4.0,2,34,Urban,Software Engineer,41897,0 +105860,Male,55,High School,4,63,91,9,69,5.0,2,22,Rural,ML Engineer,94284,0 +105861,Female,46,Bachelors,3,82,98,93,16,8.0,5,78,Urban,HR Executive,54601,1 +105862,Female,35,High School,4,44,98,36,94,8.0,6,96,Rural,Manager,97572,1 +105863,Male,55,Bachelors,10,69,96,92,7,5.0,5,22,Urban,Manager,133855,1 +105864,Female,54,Bachelors,8,67,12,52,68,9.0,5,5,Urban,Manager,143567,0 +105865,Male,27,Masters,8,64,44,30,88,6.0,1,72,Urban,ML Engineer,104909,0 +105866,Male,34,Bachelors,4,46,77,4,27,3.0,7,70,Urban,Software Engineer,126695,0 +105867,Male,59,Diploma,6,93,56,30,92,0.0,3,91,Urban,ML Engineer,42506,1 +105868,Male,59,Diploma,3,53,87,0,4,0.0,2,78,Urban,Manager,46987,0 +105869,Female,38,Bachelors,7,89,74,57,42,1.0,2,12,Urban,Manager,144094,0 +105870,Male,42,Diploma,4,61,52,41,38,3.0,3,96,Urban,Software Engineer,46174,1 +105871,Male,45,Masters,7,24,68,43,55,7.0,7,48,Semi-Urban,ML Engineer,99555,0 +105872,Male,58,High School,5,76,55,7,61,9.0,0,85,Urban,Software Engineer,118564,0 +105873,Male,59,High School,12,80,4,25,68,9.0,0,24,Rural,HR Executive,49732,0 +105874,Male,47,High School,7,53,79,64,71,2.0,2,85,Semi-Urban,Software Engineer,114899,1 +105875,Female,44,Bachelors,14,43,68,53,84,7.0,4,67,Rural,Manager,121611,0 +105876,Female,58,Bachelors,7,0,12,84,96,0.0,1,62,Rural,HR Executive,32576,0 +105877,Female,40,Diploma,4,26,62,18,36,3.0,6,74,Rural,ML Engineer,62368,0 +105878,Male,30,Bachelors,19,71,61,45,66,4.0,0,9,Rural,HR Executive,102801,0 +105879,Male,45,Bachelors,2,49,46,44,59,6.0,2,9,Urban,HR Executive,129616,0 +105880,Female,50,Bachelors,12,44,58,93,27,1.0,7,32,Rural,Data Analyst,80682,0 +105881,Male,36,Diploma,9,41,87,17,61,0.0,7,57,Rural,Manager,57502,0 +105882,Male,51,High School,16,59,39,79,30,2.0,4,59,Urban,HR Executive,60717,1 +105883,Female,58,Bachelors,4,10,2,80,18,3.0,6,13,Semi-Urban,HR Executive,64515,0 +105884,Female,27,Bachelors,5,98,61,28,19,5.0,3,92,Semi-Urban,Data Analyst,37049,1 +105885,Male,29,Diploma,17,18,6,47,1,5.0,1,60,Rural,Software Engineer,36427,0 +105886,Male,25,Masters,1,84,57,5,70,7.0,0,90,Rural,Software Engineer,112904,1 +105887,Other,47,Bachelors,17,66,82,18,51,6.0,6,17,Urban,ML Engineer,119821,0 +105888,Female,47,Masters,11,93,13,68,35,8.0,3,30,Rural,ML Engineer,34817,0 +105889,Male,57,PhD,8,7,5,31,27,0.0,7,37,Urban,HR Executive,130458,0 +105890,Male,48,High School,19,10,78,96,22,9.0,2,8,Urban,Manager,43215,0 +105891,Female,58,Diploma,12,66,91,20,68,3.0,7,34,Rural,Data Analyst,74046,0 +105892,Female,39,Bachelors,11,23,65,96,84,1.0,6,50,Rural,HR Executive,133744,0 +105893,Female,53,Diploma,16,96,13,93,0,3.0,7,65,Semi-Urban,Software Engineer,112228,1 +105894,Female,32,Bachelors,17,21,31,43,64,5.0,2,58,Urban,ML Engineer,81209,0 +105895,Female,48,Diploma,19,40,66,52,13,8.0,4,5,Urban,ML Engineer,33715,0 +105896,Female,37,Bachelors,6,44,5,4,88,2.0,3,90,Semi-Urban,Manager,141718,0 +105897,Female,39,Diploma,17,55,55,14,24,6.0,2,49,Semi-Urban,Manager,90518,0 +105898,Male,24,Masters,13,3,8,38,15,9.0,5,94,Urban,Manager,131739,0 +105899,Male,22,Bachelors,10,58,3,92,82,0.0,7,31,Rural,Software Engineer,61725,0 +105900,Female,59,Masters,7,13,23,86,83,6.0,0,3,Urban,Data Analyst,104194,0 +105901,Male,49,Bachelors,13,94,35,23,7,5.0,2,74,Semi-Urban,ML Engineer,63944,0 +105902,Female,47,Bachelors,9,59,9,41,77,0.0,2,34,Urban,HR Executive,83294,0 +105903,Male,39,Masters,12,34,72,50,95,9.0,4,13,Urban,Software Engineer,111896,0 +105904,Male,34,PhD,18,51,6,76,36,6.0,0,39,Semi-Urban,Data Analyst,64568,0 +105905,Male,21,Diploma,3,37,85,19,22,5.0,4,86,Rural,Data Analyst,55255,0 +105906,Male,31,Bachelors,17,72,22,6,20,8.0,4,42,Urban,Manager,45030,0 +105907,Male,21,Bachelors,10,1,45,14,34,5.0,0,28,Rural,Software Engineer,56712,0 +105908,Male,54,Masters,12,66,11,61,23,1.0,2,75,Rural,Software Engineer,148257,0 +105909,Male,36,Masters,10,99,60,17,47,8.0,5,82,Semi-Urban,ML Engineer,20604,1 +105910,Female,32,Bachelors,2,53,39,5,97,5.0,5,69,Rural,Data Analyst,94070,0 +105911,Female,42,Diploma,12,36,40,93,70,3.0,5,76,Semi-Urban,Manager,97057,1 +105912,Female,50,Bachelors,2,14,35,65,12,3.0,2,70,Urban,HR Executive,64299,0 +105913,Male,26,PhD,18,87,14,90,23,1.0,4,32,Semi-Urban,ML Engineer,30421,0 +105914,Female,30,Masters,10,52,9,43,3,3.0,3,39,Rural,HR Executive,131071,0 +105915,Female,38,Bachelors,0,19,29,6,68,5.0,7,58,Semi-Urban,Software Engineer,96126,0 +105916,Male,43,Bachelors,13,19,91,46,75,1.0,3,93,Urban,Software Engineer,80031,1 +105917,Female,57,High School,18,97,69,76,19,9.0,5,33,Semi-Urban,Software Engineer,27928,1 +105918,Female,29,Masters,8,93,59,91,48,8.0,1,23,Urban,Manager,110864,1 +105919,Female,38,Bachelors,8,68,84,23,58,9.0,5,29,Urban,ML Engineer,59776,0 +105920,Other,47,PhD,14,43,1,17,27,2.0,0,45,Rural,ML Engineer,89475,0 +105921,Male,35,High School,18,47,47,16,88,1.0,5,53,Semi-Urban,ML Engineer,149818,0 +105922,Male,51,High School,8,5,0,79,51,6.0,5,79,Urban,HR Executive,47771,0 +105923,Female,40,Bachelors,7,2,72,97,54,2.0,6,49,Semi-Urban,Software Engineer,25827,0 +105924,Male,46,Bachelors,13,21,96,12,19,8.0,5,60,Urban,Data Analyst,137495,0 +105925,Male,43,Diploma,10,0,84,12,76,5.0,6,96,Urban,Manager,81272,0 +105926,Male,36,Masters,11,96,68,56,3,0.0,5,1,Rural,ML Engineer,91348,0 +105927,Male,54,Bachelors,8,77,30,21,52,6.0,2,13,Urban,Software Engineer,55967,0 +105928,Male,52,PhD,2,19,10,89,12,9.0,5,11,Urban,Software Engineer,128584,0 +105929,Male,59,Diploma,19,63,79,95,89,5.0,0,40,Rural,HR Executive,102567,1 +105930,Male,39,Bachelors,1,98,18,40,9,5.0,3,79,Urban,Software Engineer,77884,1 +105931,Male,29,Diploma,16,38,13,92,94,1.0,7,23,Urban,Data Analyst,127527,0 +105932,Male,52,Bachelors,0,59,18,47,57,7.0,4,0,Urban,ML Engineer,75464,0 +105933,Female,50,Diploma,7,63,46,61,51,1.0,5,3,Rural,ML Engineer,67084,0 +105934,Female,33,Bachelors,5,47,95,90,92,7.0,1,64,Rural,Software Engineer,132836,1 +105935,Female,58,Bachelors,4,96,96,16,37,4.0,2,82,Urban,HR Executive,104295,1 +105936,Male,59,Bachelors,8,7,11,62,43,3.0,1,87,Urban,Software Engineer,88296,0 +105937,Male,34,High School,7,25,22,53,81,4.0,5,30,Rural,Software Engineer,79749,0 +105938,Male,25,High School,12,3,27,17,16,4.0,0,30,Rural,Software Engineer,97459,0 +105939,Male,34,High School,2,8,99,58,89,4.0,6,61,Semi-Urban,ML Engineer,74959,0 +105940,Male,45,Bachelors,11,24,24,62,41,4.0,0,84,Semi-Urban,Manager,68951,0 +105941,Female,33,Bachelors,6,31,12,41,94,5.0,4,8,Rural,Data Analyst,65865,0 +105942,Male,55,Diploma,11,33,56,89,62,4.0,3,19,Urban,Data Analyst,60189,0 +105943,Male,33,Bachelors,15,79,81,51,64,7.0,6,92,Semi-Urban,Software Engineer,30761,1 +105944,Male,54,High School,7,47,52,15,37,6.0,2,98,Urban,ML Engineer,30628,0 +105945,Male,31,High School,19,55,77,81,26,6.0,0,28,Semi-Urban,Data Analyst,141609,1 +105946,Female,36,Bachelors,9,58,73,9,24,8.0,2,43,Semi-Urban,Software Engineer,52036,0 +105947,Female,53,Masters,9,20,64,58,7,1.0,4,3,Urban,ML Engineer,125109,0 +105948,Female,55,Diploma,13,41,96,17,74,7.0,7,10,Urban,Data Analyst,130479,0 +105949,Male,35,Bachelors,14,93,74,36,30,9.0,1,95,Urban,HR Executive,126376,1 +105950,Other,25,Masters,5,61,58,37,24,3.0,1,4,Urban,ML Engineer,129801,0 +105951,Male,56,Bachelors,16,17,98,27,41,8.0,5,76,Urban,Data Analyst,107338,0 +105952,Male,26,High School,2,98,20,87,81,1.0,6,49,Semi-Urban,Software Engineer,136215,1 +105953,Male,50,Masters,16,73,43,82,56,4.0,3,53,Urban,ML Engineer,48895,1 +105954,Male,54,Bachelors,10,76,20,84,62,8.0,1,98,Urban,ML Engineer,78453,1 +105955,Female,45,Masters,12,25,69,96,48,6.0,5,74,Semi-Urban,Software Engineer,139858,1 +105956,Male,43,Masters,17,50,26,5,61,3.0,1,89,Urban,Software Engineer,78804,0 +105957,Male,33,High School,10,90,1,44,59,6.0,4,37,Urban,ML Engineer,97707,0 +105958,Female,43,Bachelors,0,78,80,2,7,6.0,7,59,Rural,Manager,86035,0 +105959,Other,36,PhD,17,19,45,27,73,5.0,4,6,Urban,ML Engineer,75379,0 +105960,Male,30,Diploma,5,42,57,70,17,5.0,2,77,Urban,HR Executive,98528,1 +105961,Male,21,Bachelors,8,78,59,22,96,1.0,6,6,Urban,Manager,123649,0 +105962,Male,47,Bachelors,15,9,93,58,1,2.0,3,68,Urban,ML Engineer,142095,0 +105963,Female,40,Bachelors,6,36,84,15,71,7.0,6,52,Urban,HR Executive,35980,0 +105964,Male,21,High School,19,52,43,92,32,3.0,5,27,Urban,Manager,31885,0 +105965,Male,41,Bachelors,3,61,30,2,51,2.0,7,37,Urban,Data Analyst,115002,0 +105966,Female,21,Diploma,7,40,87,85,83,0.0,0,48,Urban,ML Engineer,54001,1 +105967,Male,54,High School,15,30,31,5,56,9.0,7,57,Rural,Data Analyst,126264,0 +105968,Female,40,Bachelors,12,88,1,46,90,0.0,0,24,Semi-Urban,ML Engineer,59715,0 +105969,Female,45,Diploma,4,17,71,17,1,7.0,4,67,Urban,Data Analyst,33655,0 +105970,Male,49,Bachelors,17,78,51,32,90,5.0,6,54,Semi-Urban,Software Engineer,58585,0 +105971,Female,53,Masters,12,88,70,10,7,3.0,5,98,Rural,Data Analyst,99956,1 +105972,Male,48,High School,19,68,33,9,68,4.0,0,32,Rural,Manager,106493,0 +105973,Male,31,Bachelors,11,85,41,85,95,2.0,7,95,Rural,ML Engineer,114382,1 +105974,Male,38,Masters,13,27,96,56,73,9.0,1,23,Urban,Manager,51598,0 +105975,Male,41,Masters,12,93,82,61,92,6.0,6,13,Semi-Urban,HR Executive,50437,1 +105976,Male,43,Masters,8,70,7,48,83,2.0,6,22,Semi-Urban,Data Analyst,146825,0 +105977,Male,54,Bachelors,9,26,76,89,75,0.0,5,81,Semi-Urban,Manager,133467,1 +105978,Female,28,Masters,15,16,69,77,45,4.0,1,25,Urban,Manager,113222,0 +105979,Male,43,High School,15,28,94,47,94,5.0,7,26,Urban,ML Engineer,59243,0 +105980,Female,37,Bachelors,9,74,50,27,80,2.0,3,93,Urban,Data Analyst,121015,1 +105981,Male,51,Bachelors,16,93,3,99,63,2.0,5,35,Urban,ML Engineer,147632,0 +105982,Male,53,Diploma,17,90,95,61,61,5.0,1,21,Semi-Urban,Data Analyst,132969,1 +105983,Male,32,Bachelors,0,85,36,87,6,6.0,4,95,Rural,Data Analyst,42766,1 +105984,Male,45,Bachelors,3,96,93,86,12,0.0,2,45,Rural,Data Analyst,70212,1 +105985,Male,40,Bachelors,9,48,51,70,91,4.0,3,40,Urban,HR Executive,54824,0 +105986,Male,24,Masters,16,80,62,4,7,0.0,6,14,Rural,Data Analyst,136837,0 +105987,Female,57,Masters,2,4,14,97,3,8.0,5,25,Urban,Data Analyst,46142,0 +105988,Male,57,Diploma,2,67,13,67,88,3.0,6,48,Rural,HR Executive,34698,0 +105989,Male,30,Masters,18,40,78,85,58,2.0,0,28,Rural,Manager,121536,0 +105990,Female,33,Diploma,4,84,26,79,99,2.0,3,11,Urban,Data Analyst,41784,0 +105991,Male,52,Masters,6,72,9,58,46,9.0,4,18,Rural,Software Engineer,121479,0 +105992,Male,24,Bachelors,18,57,16,44,34,6.0,0,32,Semi-Urban,ML Engineer,135000,0 +105993,Female,35,PhD,19,46,92,39,64,9.0,5,53,Rural,ML Engineer,108337,0 +105994,Male,29,Masters,6,35,12,59,21,1.0,7,38,Urban,HR Executive,104095,0 +105995,Female,33,Bachelors,5,92,75,73,80,0.0,2,47,Semi-Urban,HR Executive,54382,1 +105996,Female,27,Bachelors,8,55,13,70,45,0.0,6,43,Urban,ML Engineer,35105,0 +105997,Male,28,Bachelors,0,84,57,65,25,5.0,4,42,Urban,Software Engineer,72374,1 +105998,Female,43,Bachelors,8,96,88,44,3,7.0,6,36,Urban,Software Engineer,68340,1 +105999,Male,22,PhD,2,91,57,35,86,0.0,7,26,Urban,Manager,42650,0 +106000,Female,47,Diploma,19,13,80,5,4,3.0,2,69,Semi-Urban,Data Analyst,142874,0 +106001,Male,38,Masters,11,94,29,89,64,0.0,5,55,Urban,ML Engineer,42323,1 +106002,Female,30,Bachelors,7,29,52,19,7,8.0,0,7,Urban,Software Engineer,74418,0 +106003,Male,28,PhD,8,93,21,75,52,2.0,6,74,Semi-Urban,ML Engineer,102112,1 +106004,Male,42,Bachelors,14,4,80,69,59,8.0,5,84,Urban,ML Engineer,22968,1 +106005,Male,58,High School,12,94,49,89,34,2.0,3,23,Urban,Software Engineer,137273,1 +106006,Female,51,Bachelors,2,60,55,78,45,7.0,0,6,Rural,ML Engineer,78500,0 +106007,Female,53,Bachelors,4,10,15,25,86,5.0,5,74,Semi-Urban,Software Engineer,101411,0 +106008,Other,51,Diploma,15,45,59,57,6,8.0,1,67,Urban,Data Analyst,77368,0 +106009,Male,37,Masters,10,98,15,90,56,3.0,3,40,Urban,Manager,107086,1 +106010,Male,59,High School,17,87,31,14,19,8.0,5,99,Urban,Manager,78111,0 +106011,Male,42,Diploma,5,29,12,83,66,1.0,6,8,Rural,HR Executive,60971,0 +106012,Male,31,Bachelors,12,0,8,22,26,5.0,3,43,Urban,Data Analyst,121848,0 +106013,Male,45,Bachelors,0,4,61,81,74,5.0,6,12,Urban,Manager,26044,0 +106014,Male,25,Bachelors,2,98,14,62,77,7.0,2,4,Rural,Software Engineer,94222,0 +106015,Other,34,Bachelors,9,82,21,0,85,0.0,0,56,Urban,HR Executive,102861,0 +106016,Male,54,High School,12,24,74,37,23,4.0,5,58,Semi-Urban,Manager,114554,0 +106017,Female,50,Masters,6,90,63,66,15,9.0,7,44,Semi-Urban,Software Engineer,41640,1 +106018,Male,58,Bachelors,17,78,80,27,72,0.0,3,89,Urban,HR Executive,24656,1 +106019,Male,52,Masters,15,59,80,66,17,6.0,2,61,Rural,ML Engineer,72260,1 +106020,Male,51,High School,14,73,93,30,73,2.0,3,38,Semi-Urban,ML Engineer,125622,0 +106021,Female,52,Masters,13,90,11,58,36,9.0,3,44,Semi-Urban,Manager,53670,0 +106022,Male,50,High School,18,21,68,61,26,0.0,0,34,Rural,HR Executive,34385,0 +106023,Female,41,High School,2,18,60,58,9,8.0,4,95,Rural,ML Engineer,58100,0 +106024,Male,58,Bachelors,19,20,48,52,52,1.0,3,84,Urban,HR Executive,115227,0 +106025,Male,35,Bachelors,2,74,95,1,28,8.0,3,79,Urban,ML Engineer,59670,1 +106026,Female,57,Diploma,19,86,23,75,72,2.0,1,57,Urban,Manager,30087,1 +106027,Male,38,Bachelors,18,97,26,16,66,9.0,3,40,Urban,Software Engineer,82231,0 +106028,Other,36,Bachelors,6,74,7,66,46,3.0,6,54,Rural,Software Engineer,41957,0 +106029,Male,39,Masters,5,99,75,13,98,6.0,4,50,Urban,Data Analyst,22176,1 +106030,Female,38,High School,15,79,93,30,3,9.0,5,50,Urban,HR Executive,60217,1 +106031,Male,58,Diploma,16,39,53,74,5,7.0,3,58,Urban,Manager,23925,0 +106032,Female,28,Bachelors,3,46,43,10,53,8.0,3,71,Urban,Data Analyst,114917,0 +106033,Male,43,Diploma,5,20,88,22,38,6.0,6,13,Urban,Manager,123517,0 +106034,Male,24,Diploma,11,20,72,71,23,3.0,4,13,Semi-Urban,Software Engineer,146042,0 +106035,Male,56,Diploma,2,87,75,84,27,7.0,0,76,Urban,Manager,46716,1 +106036,Male,25,Masters,18,89,68,97,9,7.0,1,16,Rural,Manager,139348,1 +106037,Male,56,Diploma,6,30,13,34,3,0.0,2,60,Semi-Urban,Data Analyst,107988,0 +106038,Female,34,Bachelors,17,74,34,14,2,3.0,5,87,Semi-Urban,Manager,41900,0 +106039,Female,42,High School,17,49,25,75,9,7.0,1,32,Urban,Data Analyst,149676,0 +106040,Male,51,PhD,12,82,79,17,23,0.0,0,83,Urban,Data Analyst,37499,1 +106041,Male,46,High School,1,37,64,7,22,4.0,7,31,Urban,Software Engineer,133612,0 +106042,Female,21,High School,8,22,0,95,5,5.0,2,24,Urban,Software Engineer,26013,0 +106043,Female,56,Bachelors,9,50,32,23,25,9.0,0,33,Urban,Data Analyst,52002,0 +106044,Male,22,Bachelors,14,65,40,43,43,3.0,3,39,Rural,ML Engineer,128019,0 +106045,Female,54,Diploma,17,46,43,1,33,6.0,4,14,Urban,Software Engineer,148294,0 +106046,Male,45,Diploma,13,12,37,75,23,5.0,0,71,Rural,HR Executive,38040,0 +106047,Other,44,High School,14,77,12,67,60,5.0,3,77,Urban,Software Engineer,140389,0 +106048,Female,27,Diploma,6,93,91,79,6,7.0,0,93,Rural,HR Executive,21511,1 +106049,Female,21,Masters,2,57,89,1,0,0.0,1,43,Semi-Urban,ML Engineer,62968,0 +106050,Female,25,Bachelors,9,45,52,36,84,9.0,4,33,Urban,Software Engineer,32748,0 +106051,Male,36,Bachelors,19,0,1,33,71,9.0,6,70,Semi-Urban,HR Executive,24037,0 +106052,Male,37,Bachelors,13,85,53,40,8,9.0,3,34,Urban,Manager,100023,0 +106053,Male,57,Bachelors,12,13,1,77,86,6.0,0,94,Semi-Urban,HR Executive,56492,0 +106054,Male,36,Masters,6,82,73,88,48,2.0,6,5,Rural,Manager,80162,1 +106055,Male,54,High School,18,62,77,84,28,2.0,3,99,Semi-Urban,Manager,136341,1 +106056,Female,50,High School,6,96,2,33,97,1.0,0,64,Urban,Data Analyst,131482,0 +106057,Male,38,PhD,0,80,76,26,67,6.0,2,44,Urban,ML Engineer,98555,0 +106058,Male,35,Diploma,13,95,99,10,82,2.0,1,35,Semi-Urban,Software Engineer,78096,1 +106059,Male,53,Bachelors,12,16,74,17,88,1.0,2,41,Urban,Manager,91831,0 +106060,Male,37,Bachelors,11,33,39,34,47,9.0,7,69,Urban,Manager,54839,0 +106061,Male,44,Bachelors,17,67,89,7,95,0.0,0,20,Semi-Urban,HR Executive,63576,0 +106062,Female,39,High School,14,89,70,11,11,2.0,1,55,Rural,Software Engineer,113843,0 +106063,Male,24,High School,19,73,61,95,87,0.0,4,14,Rural,Data Analyst,74758,1 +106064,Female,26,PhD,7,95,31,19,51,9.0,1,55,Semi-Urban,Data Analyst,61801,0 +106065,Male,43,Masters,18,26,17,67,67,7.0,6,37,Rural,HR Executive,74420,0 +106066,Male,22,Masters,12,89,44,78,24,8.0,1,86,Urban,Software Engineer,22737,1 +106067,Male,39,Diploma,2,81,16,2,12,2.0,5,73,Rural,ML Engineer,81334,0 +106068,Male,41,PhD,11,85,42,1,73,5.0,0,31,Urban,HR Executive,40612,0 +106069,Male,44,Bachelors,4,91,76,88,1,0.0,3,23,Urban,Data Analyst,131985,1 +106070,Female,42,PhD,1,92,74,0,78,0.0,6,31,Urban,Data Analyst,24689,0 +106071,Other,36,Bachelors,17,69,29,29,30,6.0,3,53,Urban,Data Analyst,89288,0 +106072,Male,57,Bachelors,13,71,20,77,81,9.0,7,39,Semi-Urban,ML Engineer,105515,0 +106073,Male,46,Masters,19,18,51,80,38,4.0,5,19,Urban,Manager,53892,0 +106074,Female,50,Bachelors,15,89,75,15,70,6.0,3,81,Rural,Manager,145473,1 +106075,Male,40,Masters,1,74,79,20,22,6.0,3,74,Urban,ML Engineer,139408,1 +106076,Male,41,Bachelors,4,1,90,27,88,7.0,7,96,Rural,ML Engineer,58309,0 +106077,Male,57,Bachelors,8,42,13,90,15,4.0,6,17,Urban,Data Analyst,60825,0 +106078,Male,53,High School,19,84,34,72,8,6.0,6,12,Urban,HR Executive,63710,0 +106079,Male,56,Masters,10,52,57,82,60,1.0,4,14,Urban,HR Executive,36697,0 +106080,Female,49,High School,6,39,6,66,17,4.0,6,69,Rural,Data Analyst,28126,0 +106081,Male,23,Bachelors,16,55,38,94,33,4.0,6,9,Semi-Urban,Software Engineer,81759,0 +106082,Male,36,Diploma,3,46,48,55,91,0.0,7,72,Urban,Manager,80394,0 +106083,Male,35,Masters,17,14,69,50,97,1.0,4,60,Urban,ML Engineer,24867,0 +106084,Male,56,Masters,5,54,95,50,89,1.0,2,96,Urban,Software Engineer,49508,1 +106085,Female,23,High School,6,25,4,59,27,0.0,2,23,Rural,ML Engineer,88437,0 +106086,Male,28,Masters,14,53,99,52,43,8.0,7,20,Rural,HR Executive,123821,0 +106087,Male,31,Masters,4,51,1,41,99,1.0,5,11,Rural,Data Analyst,34359,0 +106088,Male,55,High School,2,65,85,32,22,3.0,7,31,Urban,Data Analyst,22685,0 +106089,Female,46,Masters,18,71,93,84,6,0.0,7,11,Urban,Manager,81283,1 +106090,Female,30,Bachelors,2,78,21,91,31,4.0,2,95,Rural,Manager,146843,1 +106091,Male,24,Bachelors,7,79,0,26,27,8.0,2,11,Semi-Urban,ML Engineer,50144,0 +106092,Male,22,Diploma,18,29,77,31,62,6.0,1,3,Semi-Urban,ML Engineer,48944,0 +106093,Female,55,High School,19,41,74,18,29,5.0,3,17,Urban,ML Engineer,109336,0 +106094,Male,43,Diploma,18,34,92,42,65,3.0,1,10,Urban,Software Engineer,99750,0 +106095,Male,41,Masters,9,47,89,22,48,1.0,7,48,Rural,HR Executive,144471,0 +106096,Male,42,Masters,14,66,92,80,11,8.0,6,39,Urban,ML Engineer,80119,1 +106097,Other,59,Diploma,2,93,29,80,14,3.0,2,80,Semi-Urban,HR Executive,29190,1 +106098,Male,45,High School,12,94,69,65,46,8.0,7,34,Urban,Manager,122112,1 +106099,Male,53,Masters,19,8,4,22,31,9.0,7,66,Urban,Manager,81717,0 +106100,Male,43,High School,14,75,78,3,32,0.0,1,86,Semi-Urban,ML Engineer,72941,1 +106101,Female,30,Diploma,18,52,42,81,42,8.0,5,25,Urban,Data Analyst,73503,0 +106102,Male,21,Bachelors,10,41,50,20,64,0.0,4,21,Urban,ML Engineer,81339,0 +106103,Female,41,Diploma,17,10,98,17,18,5.0,1,40,Rural,Data Analyst,139952,0 +106104,Male,37,Masters,1,8,14,63,40,2.0,6,45,Rural,Manager,72298,0 +106105,Female,58,Bachelors,10,51,55,21,35,4.0,1,93,Urban,HR Executive,66998,0 +106106,Male,54,Bachelors,10,0,92,71,18,8.0,7,58,Urban,Software Engineer,24105,0 +106107,Female,49,Bachelors,11,80,40,75,78,8.0,2,89,Urban,Manager,107357,1 +106108,Male,23,Bachelors,1,34,34,94,17,,2,13,Urban,Manager,128156,0 +106109,Female,25,PhD,14,85,2,27,17,0.0,0,23,Urban,ML Engineer,58544,0 +106110,Male,31,Diploma,3,26,78,75,73,4.0,5,23,Urban,HR Executive,120897,0 +106111,Male,43,Masters,19,82,7,33,27,4.0,4,90,Urban,Software Engineer,134264,0 +106112,Male,34,Masters,11,70,11,9,95,9.0,3,39,Urban,HR Executive,116061,0 +106113,Male,35,High School,5,21,73,14,31,3.0,2,78,Urban,HR Executive,31808,0 +106114,Female,28,Diploma,16,49,4,27,48,6.0,2,78,Rural,Manager,86167,0 +106115,Female,42,PhD,15,29,7,74,50,8.0,0,24,Rural,Software Engineer,26355,0 +106116,Female,38,Bachelors,5,31,84,56,74,0.0,6,83,Urban,ML Engineer,113169,1 +106117,Male,29,Bachelors,1,34,60,98,64,2.0,4,62,Urban,Software Engineer,37141,1 +106118,Male,27,Bachelors,18,42,72,6,25,1.0,5,58,Rural,HR Executive,115009,0 +106119,Female,45,Bachelors,13,64,32,35,22,6.0,1,66,Urban,Software Engineer,67140,0 +106120,Female,28,Diploma,15,95,39,17,24,3.0,0,6,Semi-Urban,ML Engineer,144259,0 +106121,Male,29,Masters,2,74,62,52,83,4.0,6,45,Semi-Urban,Manager,97614,0 +106122,Female,28,Diploma,4,80,13,86,17,4.0,1,69,Semi-Urban,Manager,52969,1 +106123,Male,42,Masters,17,36,26,85,19,2.0,2,70,Urban,Manager,139288,0 +106124,Male,55,Bachelors,1,20,81,18,57,6.0,5,55,Rural,HR Executive,135932,0 +106125,Female,40,Diploma,12,42,77,50,13,8.0,3,95,Urban,Data Analyst,94284,1 +106126,Female,46,High School,7,50,24,98,39,1.0,7,42,Urban,HR Executive,126602,0 +106127,Male,25,Diploma,4,56,13,92,91,2.0,5,47,Urban,ML Engineer,95884,0 +106128,Female,33,Bachelors,9,77,40,29,98,2.0,2,10,Rural,HR Executive,49589,0 +106129,Female,46,Masters,16,47,71,34,32,0.0,4,40,Urban,Software Engineer,122437,0 +106130,Female,58,High School,3,61,37,3,0,0.0,6,9,Semi-Urban,Manager,30663,0 +106131,Male,30,High School,11,97,56,48,87,6.0,2,82,Urban,HR Executive,104962,1 +106132,Female,55,Masters,2,65,29,55,2,5.0,1,82,Urban,HR Executive,148925,0 +106133,Male,31,Bachelors,13,96,75,59,62,4.0,7,42,Urban,ML Engineer,42481,1 +106134,Male,23,High School,6,92,74,11,73,5.0,0,57,Rural,Data Analyst,81078,0 +106135,Female,23,Bachelors,16,35,49,29,70,8.0,5,62,Urban,Data Analyst,92368,0 +106136,Female,28,Diploma,4,9,6,22,1,9.0,2,37,Semi-Urban,ML Engineer,68845,0 +106137,Male,28,Diploma,12,46,99,17,51,0.0,6,65,Urban,Software Engineer,44151,0 +106138,Male,24,Bachelors,14,32,65,75,61,5.0,1,61,Urban,HR Executive,24127,0 +106139,Male,51,High School,2,78,88,18,14,7.0,0,78,Urban,Manager,25165,1 +106140,Male,52,Masters,6,53,46,87,82,2.0,7,49,Rural,HR Executive,143971,1 +106141,Female,31,Masters,17,35,9,46,96,5.0,7,67,Rural,Software Engineer,67096,0 +106142,Female,54,PhD,7,5,55,39,97,0.0,0,11,Urban,Data Analyst,148250,0 +106143,Female,39,PhD,16,24,4,92,68,6.0,1,25,Rural,Software Engineer,93640,0 +106144,Male,42,High School,11,61,56,61,53,5.0,3,67,Urban,Data Analyst,118017,1 +106145,Male,38,Bachelors,2,94,81,8,6,6.0,2,99,Urban,ML Engineer,26261,1 +106146,Male,24,Masters,3,59,53,99,98,7.0,6,93,Urban,HR Executive,145732,1 +106147,Female,47,Diploma,16,70,98,55,2,8.0,5,40,Urban,HR Executive,20012,1 +106148,Male,46,Bachelors,16,16,17,91,54,3.0,2,70,Rural,Software Engineer,22056,0 +106149,Male,59,Bachelors,17,71,46,40,59,6.0,4,47,Urban,Manager,82577,0 +106150,Male,55,Bachelors,0,40,14,42,75,6.0,2,50,Urban,ML Engineer,100871,0 +106151,Female,59,High School,9,25,92,81,68,8.0,3,73,Rural,Manager,134227,1 +106152,Other,32,Diploma,12,66,85,59,94,1.0,1,4,Rural,Data Analyst,88814,0 +106153,Male,48,Bachelors,14,22,80,26,31,5.0,3,7,Urban,Software Engineer,88909,0 +106154,Male,52,Diploma,11,10,77,39,46,3.0,1,50,Semi-Urban,HR Executive,116136,0 +106155,Female,42,Diploma,1,61,96,13,40,4.0,7,95,Rural,Data Analyst,39334,1 +106156,Male,51,Bachelors,15,45,78,6,29,5.0,4,88,Urban,Manager,149473,0 +106157,Female,43,Bachelors,3,29,89,76,52,0.0,1,95,Urban,ML Engineer,133981,1 +106158,Male,50,Diploma,5,9,99,0,3,7.0,4,18,Urban,Manager,52981,0 +106159,Male,39,PhD,4,86,29,19,7,1.0,2,51,Urban,Data Analyst,123646,0 +106160,Male,44,Bachelors,9,31,88,80,39,9.0,7,85,Urban,Data Analyst,117764,1 +106161,Female,43,Bachelors,17,91,77,85,52,3.0,5,94,Urban,Manager,98704,1 +106162,Other,26,PhD,13,33,1,31,39,4.0,5,21,Rural,ML Engineer,130336,0 +106163,Male,24,Bachelors,0,22,64,87,46,6.0,2,25,Urban,ML Engineer,80094,0 +106164,Male,26,Masters,5,33,30,63,96,0.0,2,15,Urban,Software Engineer,128960,0 +106165,Female,35,High School,16,26,97,26,9,0.0,3,84,Urban,Data Analyst,33506,0 +106166,Male,41,Masters,3,29,35,93,22,3.0,4,48,Rural,Manager,58402,0 +106167,Female,52,Bachelors,19,43,8,13,69,3.0,3,2,Semi-Urban,Manager,102905,0 +106168,Male,51,Bachelors,16,45,30,12,88,8.0,6,23,Urban,Software Engineer,63662,0 +106169,Male,58,Bachelors,13,63,56,55,20,6.0,6,43,Semi-Urban,ML Engineer,51981,0 +106170,Male,49,Bachelors,17,27,74,69,70,2.0,6,50,Urban,HR Executive,145666,0 +106171,Male,49,Diploma,17,92,61,71,70,6.0,1,81,Urban,Data Analyst,47317,1 +106172,Male,59,Diploma,12,59,91,50,42,6.0,7,55,Semi-Urban,ML Engineer,124866,1 +106173,Female,47,Bachelors,16,97,96,2,49,5.0,4,14,Urban,HR Executive,71682,0 +106174,Female,55,Bachelors,19,45,23,16,96,0.0,7,58,Urban,Software Engineer,21204,0 +106175,Male,59,High School,4,46,87,87,46,4.0,0,63,Urban,HR Executive,25116,1 +106176,Male,24,PhD,1,65,93,44,32,2.0,6,0,Rural,ML Engineer,56346,0 +106177,Male,48,Masters,1,36,5,46,28,5.0,2,9,Semi-Urban,HR Executive,32853,0 +106178,Male,25,Bachelors,7,51,76,8,22,3.0,5,73,Urban,Manager,54485,0 +106179,Male,57,Bachelors,13,57,45,63,79,4.0,1,66,Urban,ML Engineer,68933,0 +106180,Male,46,Diploma,15,42,68,44,68,0.0,6,20,Semi-Urban,HR Executive,34239,0 +106181,Female,44,High School,10,44,90,37,42,5.0,6,61,Urban,Manager,106227,0 +106182,Female,52,Masters,4,97,50,35,53,3.0,5,52,Urban,ML Engineer,74559,0 +106183,Female,58,Masters,10,58,64,75,37,3.0,4,19,Urban,Data Analyst,147387,0 +106184,Male,55,Bachelors,13,99,47,46,80,7.0,3,22,Rural,ML Engineer,123672,0 +106185,Female,50,Bachelors,7,97,97,87,77,9.0,1,14,Urban,ML Engineer,24825,1 +106186,Male,21,PhD,13,52,56,63,63,8.0,4,97,Semi-Urban,HR Executive,109637,1 +106187,Male,47,Masters,7,79,4,9,71,7.0,0,93,Urban,ML Engineer,29470,0 +106188,Other,22,Bachelors,4,38,93,45,68,6.0,0,68,Rural,HR Executive,123202,1 +106189,Female,47,Bachelors,0,87,49,22,63,9.0,1,70,Urban,ML Engineer,94416,0 +106190,Male,50,Bachelors,4,29,4,96,93,3.0,1,29,Urban,ML Engineer,28548,0 +106191,Male,22,Diploma,11,85,78,6,84,3.0,7,58,Semi-Urban,ML Engineer,52925,0 +106192,Female,51,Diploma,7,94,74,38,58,6.0,5,48,Rural,Software Engineer,90859,1 +106193,Male,37,Diploma,6,23,22,91,47,3.0,2,25,Urban,ML Engineer,92997,0 +106194,Male,26,Bachelors,4,9,8,7,42,2.0,0,65,Urban,HR Executive,30139,0 +106195,Female,57,Bachelors,14,54,55,35,87,9.0,1,80,Urban,ML Engineer,140934,0 +106196,Female,46,High School,1,89,80,47,89,2.0,5,28,Urban,Manager,21938,1 +106197,Male,26,Diploma,1,26,52,60,27,4.0,5,84,Urban,Manager,102585,0 +106198,Male,29,Masters,19,77,94,56,54,9.0,1,44,Semi-Urban,ML Engineer,59896,1 +106199,Female,36,Masters,3,15,16,17,84,9.0,6,28,Urban,Software Engineer,137997,0 +106200,Female,54,Masters,8,7,6,27,68,5.0,6,59,Rural,Software Engineer,53183,0 +106201,Female,42,Masters,6,58,0,6,65,7.0,0,93,Semi-Urban,Software Engineer,34001,0 +106202,Male,43,Bachelors,2,13,44,21,64,4.0,1,71,Urban,ML Engineer,66181,0 +106203,Female,58,High School,7,35,66,69,67,5.0,0,43,Urban,HR Executive,52513,0 +106204,Female,50,Bachelors,12,35,0,81,68,7.0,3,26,Urban,HR Executive,46312,0 +106205,Female,29,High School,10,65,65,91,99,5.0,1,44,Urban,Manager,23266,1 +106206,Female,53,Diploma,3,94,15,77,72,7.0,7,1,Urban,Software Engineer,128718,0 +106207,Male,35,Masters,1,74,87,91,84,8.0,1,58,Semi-Urban,HR Executive,129190,1 +106208,Male,49,Diploma,17,72,62,12,48,0.0,5,71,Semi-Urban,Manager,134413,0 +106209,Male,48,Diploma,12,6,73,73,0,4.0,4,26,Urban,Manager,105565,0 +106210,Female,33,High School,7,82,19,48,8,1.0,6,94,Rural,Software Engineer,107887,1 +106211,Female,42,Masters,16,80,36,16,32,6.0,0,46,Rural,Data Analyst,35506,0 +106212,Male,47,Bachelors,4,74,1,84,16,2.0,0,86,Urban,Software Engineer,146457,1 +106213,Male,45,Masters,1,25,21,87,5,8.0,6,93,Urban,Software Engineer,117519,0 +106214,Female,41,Diploma,17,95,48,32,43,9.0,3,53,Urban,Data Analyst,50500,0 +106215,Other,42,High School,8,48,31,53,68,3.0,0,28,Rural,Data Analyst,110944,0 +106216,Female,38,Masters,19,41,61,42,65,3.0,2,62,Urban,Manager,59981,0 +106217,Female,44,Masters,15,81,40,94,48,2.0,3,44,Urban,Manager,147152,1 +106218,Other,35,Diploma,19,74,36,3,14,4.0,1,91,Rural,Manager,124178,0 +106219,Female,42,Masters,11,19,60,78,47,5.0,7,35,Semi-Urban,Data Analyst,74468,0 +106220,Female,21,Bachelors,19,6,76,70,15,4.0,0,43,Rural,Data Analyst,103968,0 +106221,Male,47,Bachelors,15,49,16,8,36,2.0,7,5,Urban,HR Executive,54185,0 +106222,Male,33,Masters,15,91,19,89,49,6.0,3,0,Urban,Software Engineer,139070,0 +106223,Male,26,High School,1,88,37,91,83,9.0,3,77,Semi-Urban,Data Analyst,125740,1 +106224,Female,37,High School,15,11,39,79,70,1.0,0,17,Semi-Urban,ML Engineer,124393,0 +106225,Male,30,High School,16,45,83,93,19,1.0,7,47,Rural,HR Executive,74781,1 +106226,Female,36,Bachelors,5,91,15,5,48,1.0,0,65,Rural,ML Engineer,135169,0 +106227,Female,39,Masters,15,35,97,25,12,7.0,1,98,Urban,Manager,25932,1 +106228,Female,32,Masters,15,93,78,63,18,3.0,6,55,Urban,ML Engineer,115425,1 +106229,Male,25,Masters,6,47,62,30,59,2.0,6,90,Rural,ML Engineer,61342,0 +106230,Male,42,High School,5,99,19,62,8,9.0,5,26,Rural,ML Engineer,102400,0 +106231,Female,33,Diploma,0,58,45,31,87,1.0,0,89,Rural,HR Executive,119268,0 +106232,Female,31,PhD,11,94,73,68,27,7.0,7,57,Semi-Urban,Software Engineer,91104,1 +106233,Male,56,High School,0,10,30,96,32,8.0,3,33,Urban,HR Executive,134850,0 +106234,Male,31,Masters,5,71,67,59,74,4.0,6,76,Semi-Urban,Data Analyst,50229,1 +106235,Female,47,Bachelors,15,85,31,99,52,1.0,7,76,Semi-Urban,HR Executive,49026,1 +106236,Male,29,Bachelors,6,4,62,25,27,0.0,7,35,Urban,ML Engineer,57762,0 +106237,Male,33,Diploma,10,86,96,42,53,3.0,5,21,Urban,Data Analyst,115312,1 +106238,Male,57,Bachelors,10,84,48,39,35,4.0,4,76,Urban,ML Engineer,23345,1 +106239,Male,45,Bachelors,10,60,7,96,57,9.0,6,93,Urban,HR Executive,78904,1 +106240,Female,22,Masters,10,65,24,51,22,4.0,6,26,Urban,Data Analyst,23750,0 +106241,Male,31,Bachelors,19,56,62,39,68,6.0,2,83,Rural,ML Engineer,59997,1 +106242,Male,33,Diploma,14,14,52,54,47,1.0,1,12,Rural,HR Executive,26102,0 +106243,Male,48,Diploma,19,49,98,27,50,6.0,6,61,Urban,HR Executive,131973,1 +106244,Male,30,PhD,17,44,66,66,84,7.0,3,51,Urban,HR Executive,118540,0 +106245,Male,56,Diploma,12,94,34,64,82,0.0,2,97,Urban,Software Engineer,70862,1 +106246,Female,55,Bachelors,1,46,52,67,28,1.0,5,7,Semi-Urban,Manager,119484,0 +106247,Male,25,Masters,3,46,4,88,16,6.0,3,92,Urban,ML Engineer,33191,0 +106248,Female,51,Diploma,17,38,20,8,26,3.0,2,56,Semi-Urban,Manager,39692,0 +106249,Male,27,Bachelors,17,59,31,32,71,5.0,1,16,Urban,Data Analyst,143685,0 +106250,Male,44,High School,17,25,34,69,49,7.0,0,55,Urban,Manager,133925,0 +106251,Male,47,High School,16,23,59,92,74,9.0,0,17,Urban,Manager,98996,0 +106252,Male,49,High School,17,67,36,64,75,1.0,1,6,Semi-Urban,Software Engineer,141397,0 +106253,Other,42,Diploma,8,20,98,45,62,9.0,6,54,Rural,HR Executive,63815,0 +106254,Female,31,Diploma,10,25,23,30,10,8.0,0,62,Urban,HR Executive,36234,0 +106255,Female,38,Bachelors,0,7,46,26,4,6.0,5,24,Rural,Manager,51303,0 +106256,Male,49,Bachelors,6,10,45,62,59,8.0,3,85,Urban,Manager,116145,0 +106257,Male,25,High School,9,73,28,71,77,0.0,1,48,Urban,ML Engineer,121785,0 +106258,Female,52,Diploma,17,40,77,89,95,9.0,3,24,Urban,Manager,46432,0 +106259,Male,45,Bachelors,1,54,60,25,83,5.0,1,5,Urban,ML Engineer,61676,0 +106260,Male,50,Bachelors,0,81,64,98,19,0.0,6,97,Urban,HR Executive,60406,1 +106261,Male,26,Diploma,19,87,60,66,27,8.0,6,37,Urban,Software Engineer,76113,1 +106262,Male,41,Bachelors,3,87,41,78,17,9.0,2,73,Rural,Data Analyst,107096,1 +106263,Female,39,Masters,12,14,77,99,35,9.0,2,97,Urban,HR Executive,119871,1 +106264,Male,26,Bachelors,7,96,91,43,50,9.0,6,62,Rural,HR Executive,103575,1 +106265,Female,43,Bachelors,1,8,7,4,43,5.0,6,61,Urban,HR Executive,110627,0 +106266,Male,51,Bachelors,1,90,78,94,94,8.0,2,72,Semi-Urban,Data Analyst,87263,1 +106267,Male,45,Masters,1,85,75,4,33,8.0,7,89,Semi-Urban,Manager,65050,1 +106268,Male,34,Bachelors,16,25,92,8,80,1.0,5,14,Rural,Software Engineer,100048,0 +106269,Male,22,High School,3,59,31,87,33,6.0,5,7,Urban,HR Executive,76688,0 +106270,Other,34,Bachelors,12,88,17,70,31,0.0,0,34,Urban,Manager,115927,0 +106271,Male,36,Bachelors,14,70,9,5,11,0.0,6,81,Urban,Software Engineer,84946,0 +106272,Male,57,High School,13,0,31,52,15,3.0,5,71,Semi-Urban,HR Executive,96143,0 +106273,Male,53,Diploma,1,1,93,98,82,2.0,5,6,Urban,Manager,21445,0 +106274,Male,57,Diploma,10,36,4,36,69,8.0,7,61,Rural,Manager,122872,0 +106275,Male,35,Bachelors,5,52,0,27,97,1.0,2,39,Urban,Software Engineer,138606,0 +106276,Male,47,Masters,14,87,81,67,31,0.0,0,55,Urban,Software Engineer,145853,1 +106277,Female,50,Bachelors,4,87,44,17,84,0.0,1,97,Rural,Software Engineer,31897,1 +106278,Male,32,Bachelors,7,21,63,79,31,0.0,1,36,Urban,ML Engineer,86688,0 +106279,Male,56,Diploma,16,18,21,28,5,4.0,4,70,Urban,Manager,90257,0 +106280,Male,47,Diploma,8,35,66,60,33,0.0,3,93,Semi-Urban,HR Executive,98783,1 +106281,Female,49,Bachelors,2,47,50,32,92,4.0,4,27,Rural,Software Engineer,30003,0 +106282,Other,38,Diploma,15,89,60,78,21,4.0,6,22,Urban,Manager,55767,1 +106283,Male,59,Bachelors,3,9,29,58,13,8.0,0,7,Rural,Software Engineer,63761,0 +106284,Female,27,Masters,8,34,78,26,22,4.0,2,16,Urban,Data Analyst,46937,0 +106285,Male,31,Bachelors,14,42,96,22,32,8.0,5,35,Urban,Software Engineer,66104,0 +106286,Female,44,Bachelors,8,39,93,83,39,0.0,2,94,Urban,Data Analyst,109922,1 +106287,Male,22,Diploma,4,37,60,45,15,5.0,1,16,Rural,Software Engineer,127412,0 +106288,Male,55,Diploma,4,57,97,22,60,6.0,4,72,Semi-Urban,Data Analyst,20300,1 +106289,Male,33,High School,14,18,57,37,5,1.0,2,57,Urban,ML Engineer,146038,0 +106290,Female,30,Bachelors,14,62,18,9,2,4.0,2,7,Urban,Data Analyst,53402,0 +106291,Male,22,Diploma,13,35,45,66,45,6.0,3,60,Urban,Data Analyst,99770,0 +106292,Other,30,Bachelors,1,79,41,60,13,4.0,5,18,Urban,ML Engineer,107658,0 +106293,Male,40,PhD,6,85,52,83,60,7.0,0,59,Semi-Urban,Software Engineer,54332,1 +106294,Female,46,Masters,13,3,60,76,36,7.0,3,36,Rural,ML Engineer,38647,0 +106295,Male,23,Bachelors,10,12,60,13,16,7.0,7,60,Urban,Data Analyst,58060,0 +106296,Female,33,Masters,7,25,92,89,0,1.0,2,92,Semi-Urban,HR Executive,37117,1 +106297,Male,53,Bachelors,14,18,81,87,22,2.0,7,69,Urban,Data Analyst,27723,1 +106298,Male,58,Diploma,14,76,2,61,28,8.0,1,48,Urban,ML Engineer,51040,0 +106299,Male,56,Diploma,3,48,64,86,8,1.0,7,31,Urban,Manager,26524,0 +106300,Female,45,Masters,8,67,10,16,62,0.0,6,79,Urban,Data Analyst,107929,0 +106301,Male,44,High School,14,71,12,19,53,2.0,6,94,Semi-Urban,HR Executive,134550,0 +106302,Male,41,Masters,9,79,92,2,7,2.0,6,56,Urban,Software Engineer,121432,0 +106303,Female,59,Bachelors,14,41,71,12,47,4.0,7,37,Rural,Data Analyst,90200,0 +106304,Male,37,Bachelors,10,56,77,38,34,3.0,4,65,Rural,Software Engineer,121073,1 +106305,Male,30,Bachelors,8,57,7,52,36,8.0,0,82,Semi-Urban,Software Engineer,102167,0 +106306,Male,33,PhD,0,11,17,61,18,5.0,4,65,Urban,ML Engineer,124427,0 +106307,Female,33,Bachelors,17,87,88,52,77,4.0,6,55,Rural,Manager,22995,1 +106308,Male,45,Bachelors,6,66,43,67,4,2.0,3,95,Semi-Urban,ML Engineer,52301,1 +106309,Male,31,Bachelors,8,53,87,15,98,6.0,1,60,Urban,HR Executive,33304,0 +106310,Male,39,Bachelors,18,72,24,57,45,8.0,4,8,Urban,HR Executive,138198,0 +106311,Female,29,Bachelors,14,54,19,72,35,0.0,5,1,Urban,ML Engineer,50023,0 +106312,Female,42,Bachelors,10,52,48,88,22,2.0,7,59,Urban,Data Analyst,46479,1 +106313,Female,22,Masters,12,67,3,78,52,0.0,0,17,Rural,Data Analyst,94272,0 +106314,Male,27,High School,10,5,46,77,74,6.0,1,57,Rural,Data Analyst,74914,0 +106315,Male,22,Diploma,4,59,53,36,66,5.0,0,38,Urban,Software Engineer,79504,0 +106316,Male,46,Bachelors,1,64,58,84,55,1.0,7,62,Urban,Data Analyst,65915,1 +106317,Female,32,Masters,14,97,22,70,98,0.0,4,9,Urban,Data Analyst,32058,0 +106318,Male,36,High School,13,41,35,1,39,8.0,2,55,Urban,ML Engineer,46934,0 +106319,Male,36,Masters,15,80,14,5,12,6.0,2,28,Semi-Urban,ML Engineer,72588,0 +106320,Female,25,Bachelors,8,37,17,87,51,9.0,7,9,Urban,Software Engineer,55764,0 +106321,Other,45,Bachelors,17,10,7,81,69,4.0,7,85,Rural,Data Analyst,109979,0 +106322,Male,37,Bachelors,8,78,91,16,70,9.0,1,44,Urban,ML Engineer,57953,0 +106323,Other,29,Bachelors,4,89,60,3,13,3.0,2,70,Rural,Manager,51098,0 +106324,Male,26,Diploma,2,2,73,21,91,2.0,0,62,Semi-Urban,Manager,81155,0 +106325,Female,31,Masters,15,34,53,93,90,2.0,6,33,Urban,Data Analyst,43830,0 +106326,Other,24,PhD,3,80,0,76,29,9.0,3,77,Urban,Software Engineer,27379,0 +106327,Female,50,Bachelors,2,86,82,93,31,7.0,1,97,Urban,Software Engineer,90518,1 +106328,Male,45,Bachelors,14,94,7,53,51,7.0,2,32,Urban,HR Executive,123633,0 +106329,Male,29,Diploma,13,98,65,60,63,6.0,6,42,Urban,HR Executive,62295,1 +106330,Female,39,High School,15,24,34,56,40,4.0,0,35,Urban,Manager,132127,0 +106331,Female,50,Bachelors,5,86,19,90,43,0.0,1,80,Urban,ML Engineer,106588,1 +106332,Male,26,High School,9,41,25,10,92,5.0,6,20,Urban,Data Analyst,149994,0 +106333,Female,24,Bachelors,0,9,37,67,69,2.0,4,31,Urban,HR Executive,131576,0 +106334,Female,24,Masters,4,88,80,86,76,2.0,4,37,Rural,HR Executive,60679,1 +106335,Male,52,Bachelors,2,97,9,64,89,9.0,7,38,Urban,Software Engineer,102708,0 +106336,Other,55,High School,9,83,52,75,25,1.0,0,6,Urban,Software Engineer,49237,0 +106337,Other,35,Bachelors,5,60,78,23,9,1.0,6,25,Semi-Urban,HR Executive,70998,0 +106338,Male,38,Masters,2,8,67,97,94,4.0,0,35,Urban,Data Analyst,75051,0 +106339,Female,53,Diploma,15,80,80,80,64,4.0,3,73,Rural,Data Analyst,81512,1 +106340,Male,51,Bachelors,9,78,49,16,31,9.0,6,36,Urban,HR Executive,22313,0 +106341,Male,57,Bachelors,18,95,45,50,41,5.0,6,62,Urban,Manager,124724,1 +106342,Female,43,Masters,7,0,36,32,2,0.0,6,68,Semi-Urban,Data Analyst,115686,0 +106343,Male,47,Bachelors,7,66,77,63,73,4.0,1,54,Semi-Urban,Manager,44253,1 +106344,Male,29,Masters,18,75,1,96,12,6.0,6,28,Rural,HR Executive,20383,0 +106345,Female,44,Masters,4,60,2,50,91,0.0,4,45,Urban,Software Engineer,96836,0 +106346,Male,55,High School,11,42,96,88,80,0.0,5,36,Rural,HR Executive,134936,1 +106347,Male,57,High School,17,80,22,41,31,6.0,0,11,Urban,HR Executive,107046,0 +106348,Male,23,PhD,0,21,39,46,48,9.0,3,60,Urban,Software Engineer,42830,0 +106349,Male,53,Diploma,15,74,77,10,76,7.0,7,79,Urban,HR Executive,23442,1 +106350,Female,42,Diploma,15,92,74,83,3,1.0,7,93,Urban,Software Engineer,106137,1 +106351,Male,32,Bachelors,2,49,52,65,35,6.0,0,68,Rural,ML Engineer,137268,0 +106352,Female,43,Masters,11,89,18,71,92,5.0,0,71,Urban,Manager,135222,1 +106353,Male,47,Bachelors,14,58,74,91,22,6.0,4,18,Urban,Software Engineer,135321,1 +106354,Male,39,Bachelors,18,57,25,67,39,1.0,5,15,Urban,Data Analyst,58253,0 +106355,Male,33,Masters,2,93,58,44,9,1.0,7,1,Urban,HR Executive,125728,0 +106356,Male,54,Diploma,17,22,24,7,61,3.0,2,17,Semi-Urban,ML Engineer,21282,0 +106357,Female,24,Masters,12,12,34,47,42,9.0,0,55,Semi-Urban,Software Engineer,40039,0 +106358,Male,28,Masters,9,76,89,66,62,8.0,3,70,Rural,ML Engineer,42459,1 +106359,Male,24,Masters,0,66,53,68,14,5.0,1,96,Urban,Data Analyst,68998,1 +106360,Male,43,Diploma,8,68,9,63,86,9.0,4,54,Semi-Urban,Software Engineer,33025,0 +106361,Male,51,Diploma,8,8,47,55,38,1.0,1,94,Semi-Urban,ML Engineer,121002,0 +106362,Female,55,High School,10,83,82,8,93,8.0,1,83,Rural,HR Executive,106601,1 +106363,Male,48,Bachelors,19,94,91,76,27,4.0,0,27,Urban,Data Analyst,98458,1 +106364,Female,47,PhD,6,3,62,7,82,7.0,7,86,Semi-Urban,Software Engineer,62078,0 +106365,Female,28,Masters,10,16,70,65,86,3.0,4,35,Semi-Urban,Manager,112795,0 +106366,Male,28,Masters,14,55,34,51,75,3.0,4,6,Urban,Manager,40098,0 +106367,Female,24,PhD,14,33,79,66,35,5.0,0,39,Urban,HR Executive,56739,0 +106368,Male,40,Bachelors,14,58,60,39,45,0.0,6,38,Urban,HR Executive,111619,0 +106369,Female,33,Diploma,10,77,3,85,36,7.0,7,19,Urban,Software Engineer,61419,0 +106370,Female,36,Bachelors,14,23,57,95,49,6.0,5,10,Rural,ML Engineer,80864,0 +106371,Female,36,Bachelors,1,28,60,9,73,3.0,1,39,Rural,HR Executive,104454,0 +106372,Male,28,High School,4,32,30,31,89,7.0,5,83,Rural,Software Engineer,78772,0 +106373,Male,44,Bachelors,1,46,52,29,80,5.0,6,33,Urban,Data Analyst,21379,0 +106374,Male,21,Bachelors,3,94,61,52,15,7.0,3,29,Urban,Software Engineer,20504,1 +106375,Male,54,Masters,0,59,52,20,33,0.0,3,55,Urban,ML Engineer,70235,0 +106376,Male,57,Diploma,14,83,12,24,85,8.0,3,17,Urban,HR Executive,70760,0 +106377,Female,25,Bachelors,11,51,23,44,46,1.0,1,90,Urban,Software Engineer,45963,0 +106378,Male,29,Diploma,2,67,62,31,35,3.0,0,79,Rural,HR Executive,28153,1 +106379,Male,33,Masters,3,77,97,53,72,0.0,5,16,Urban,Data Analyst,54719,1 +106380,Female,35,Masters,12,49,73,13,27,0.0,5,42,Urban,HR Executive,92787,0 +106381,Female,40,Diploma,4,56,29,89,92,5.0,4,4,Semi-Urban,ML Engineer,140288,0 +106382,Male,47,Diploma,0,34,22,93,63,8.0,0,69,Rural,Software Engineer,145416,0 +106383,Female,46,Bachelors,0,12,71,80,68,5.0,4,62,Urban,HR Executive,109135,0 +106384,Other,21,Bachelors,12,10,32,44,4,9.0,1,75,Rural,Software Engineer,29827,0 +106385,Female,48,Masters,17,95,16,79,80,3.0,7,14,Semi-Urban,HR Executive,44947,0 +106386,Male,49,Diploma,12,42,6,18,93,3.0,5,95,Urban,Software Engineer,66828,0 +106387,Male,27,Diploma,17,26,32,24,15,1.0,0,17,Urban,ML Engineer,33553,0 +106388,Male,24,Bachelors,17,77,62,2,36,2.0,4,83,Urban,HR Executive,112194,0 +106389,Male,45,Bachelors,15,51,49,57,61,7.0,3,52,Semi-Urban,Manager,69567,0 +106390,Female,56,High School,5,99,94,76,19,6.0,6,7,Semi-Urban,Data Analyst,131339,1 +106391,Male,43,PhD,18,21,35,92,65,4.0,3,33,Rural,Manager,42706,0 +106392,Male,31,Bachelors,13,72,49,51,83,3.0,4,4,Urban,Software Engineer,43384,0 +106393,Female,45,Bachelors,8,26,15,22,66,7.0,6,34,Urban,Software Engineer,98674,0 +106394,Male,53,Masters,8,57,9,42,63,2.0,7,58,Urban,ML Engineer,148497,0 +106395,Female,22,Diploma,4,5,55,46,11,5.0,0,15,Rural,HR Executive,113230,0 +106396,Male,23,High School,17,19,23,66,20,2.0,2,24,Urban,Software Engineer,104297,0 +106397,Female,59,Bachelors,9,50,95,66,22,1.0,4,83,Rural,Data Analyst,96928,1 +106398,Other,37,Diploma,6,56,11,67,10,2.0,1,76,Urban,Software Engineer,89745,0 +106399,Male,51,Bachelors,13,65,13,23,79,6.0,0,61,Urban,Manager,139734,0 +106400,Male,53,Diploma,2,1,83,89,30,7.0,1,15,Urban,Manager,130442,0 +106401,Other,27,High School,4,91,7,21,5,0.0,2,3,Semi-Urban,Software Engineer,35877,0 +106402,Male,51,High School,12,54,34,72,27,6.0,5,33,Urban,Data Analyst,69886,0 +106403,Male,52,Diploma,7,87,40,64,94,4.0,3,29,Urban,Data Analyst,23112,0 +106404,Male,39,Bachelors,1,63,1,62,13,4.0,1,34,Rural,ML Engineer,149947,0 +106405,Male,29,High School,6,63,16,35,63,1.0,2,88,Urban,Software Engineer,61047,0 +106406,Male,46,Bachelors,18,21,20,16,77,9.0,4,79,Semi-Urban,ML Engineer,83040,0 +106407,Male,55,Diploma,19,94,85,92,1,5.0,1,2,Urban,HR Executive,106670,1 +106408,Other,47,Bachelors,5,57,73,3,85,2.0,2,25,Urban,Manager,20236,0 +106409,Female,54,Bachelors,1,52,10,37,33,4.0,7,42,Urban,Manager,113989,0 +106410,Male,55,High School,7,53,3,25,86,2.0,1,48,Urban,Software Engineer,65472,0 +106411,Male,59,Bachelors,3,43,81,25,27,8.0,4,85,Rural,HR Executive,83739,0 +106412,Male,42,High School,6,90,48,61,86,1.0,5,84,Urban,Manager,31246,1 +106413,Male,30,PhD,5,31,56,45,97,4.0,5,50,Urban,Data Analyst,137247,0 +106414,Female,32,Masters,4,20,71,71,2,6.0,7,61,Urban,HR Executive,20447,0 +106415,Other,36,High School,11,83,25,11,11,8.0,1,22,Urban,Software Engineer,113684,0 +106416,Female,37,Masters,13,21,10,1,68,1.0,2,56,Rural,Data Analyst,58508,0 +106417,Male,55,Bachelors,4,57,59,26,32,8.0,1,98,Semi-Urban,Software Engineer,136073,1 +106418,Male,28,High School,3,63,23,89,58,3.0,4,48,Semi-Urban,Data Analyst,101277,0 +106419,Male,50,High School,18,34,44,37,41,8.0,0,84,Urban,Data Analyst,139125,0 +106420,Male,41,Masters,9,67,2,12,26,3.0,6,61,Rural,HR Executive,90441,0 +106421,Male,29,Bachelors,8,13,5,55,9,6.0,4,19,Urban,Manager,59308,0 +106422,Male,28,Diploma,3,67,34,3,15,9.0,1,35,Urban,HR Executive,128461,0 +106423,Male,41,PhD,2,98,50,3,43,2.0,3,13,Rural,HR Executive,67581,0 +106424,Male,59,Bachelors,14,93,38,85,40,7.0,7,31,Semi-Urban,Manager,58547,1 +106425,Male,21,High School,14,54,93,52,95,0.0,3,24,Urban,Software Engineer,137438,0 +106426,Male,28,Bachelors,4,25,71,67,35,8.0,2,43,Urban,Software Engineer,149564,0 +106427,Male,23,Diploma,8,74,20,60,30,2.0,1,79,Urban,Software Engineer,114706,0 +106428,Male,33,Diploma,16,7,21,88,31,4.0,2,0,Urban,HR Executive,29386,0 +106429,Female,52,Bachelors,2,58,87,76,99,6.0,6,9,Urban,Data Analyst,142554,0 +106430,Male,34,Bachelors,1,12,75,92,69,0.0,2,26,Urban,Data Analyst,74677,0 +106431,Female,42,Masters,9,55,65,73,17,4.0,5,5,Rural,Software Engineer,72157,0 +106432,Female,39,Bachelors,1,29,53,46,63,8.0,1,63,Semi-Urban,Data Analyst,62085,0 +106433,Female,28,Masters,4,49,15,88,78,0.0,7,12,Semi-Urban,Software Engineer,40867,0 +106434,Male,45,Masters,16,8,99,40,46,1.0,1,2,Semi-Urban,Software Engineer,90456,0 +106435,Female,57,Bachelors,4,29,89,54,96,3.0,4,35,Rural,Data Analyst,125027,0 +106436,Male,38,PhD,4,67,1,4,7,1.0,0,95,Rural,ML Engineer,51734,0 +106437,Male,41,Masters,3,41,82,3,12,3.0,3,64,Semi-Urban,HR Executive,22298,0 +106438,Male,43,Bachelors,6,24,21,53,46,9.0,4,30,Semi-Urban,Data Analyst,45310,0 +106439,Male,26,Masters,2,47,50,81,45,8.0,1,45,Semi-Urban,Manager,147052,0 +106440,Female,31,Diploma,17,63,80,20,63,9.0,4,10,Semi-Urban,ML Engineer,140093,0 +106441,Female,44,Bachelors,8,56,86,64,41,0.0,6,62,Semi-Urban,HR Executive,69050,1 +106442,Male,31,Bachelors,16,75,57,2,58,8.0,4,2,Urban,Software Engineer,78731,0 +106443,Male,50,Bachelors,12,29,54,26,2,8.0,2,37,Semi-Urban,HR Executive,90211,0 +106444,Male,51,Bachelors,10,60,99,68,28,9.0,5,56,Semi-Urban,Manager,96504,1 +106445,Female,48,High School,18,56,45,59,82,6.0,6,89,Urban,HR Executive,55171,1 +106446,Male,37,Bachelors,17,83,58,49,14,9.0,5,79,Urban,Software Engineer,47722,1 +106447,Male,35,Bachelors,2,26,41,75,86,1.0,7,9,Rural,Data Analyst,54346,0 +106448,Male,22,Diploma,10,76,57,66,0,8.0,7,35,Semi-Urban,Software Engineer,49991,0 +106449,Male,39,Bachelors,7,46,25,99,77,3.0,2,92,Urban,Software Engineer,65558,1 +106450,Male,50,High School,15,9,92,40,82,5.0,7,51,Urban,Software Engineer,121817,0 +106451,Other,30,Diploma,6,8,77,86,67,6.0,5,76,Urban,HR Executive,141782,1 +106452,Male,56,Bachelors,17,39,83,94,73,8.0,3,93,Rural,Manager,87455,1 +106453,Male,24,High School,5,66,51,69,87,3.0,3,32,Urban,Data Analyst,45852,0 +106454,Male,25,Bachelors,9,36,7,13,25,2.0,1,51,Urban,Manager,37329,0 +106455,Female,36,Masters,11,67,71,29,47,6.0,7,27,Rural,Data Analyst,69615,0 +106456,Female,40,Bachelors,12,53,17,66,18,4.0,5,58,Urban,HR Executive,104259,0 +106457,Male,37,Masters,9,79,17,31,26,2.0,7,1,Urban,ML Engineer,82563,0 +106458,Female,28,Bachelors,0,71,77,18,14,2.0,1,58,Rural,ML Engineer,94043,0 +106459,Male,21,Diploma,6,27,27,30,18,0.0,6,35,Rural,ML Engineer,120592,0 +106460,Female,29,Bachelors,16,25,28,11,95,8.0,0,94,Rural,Manager,69627,0 +106461,Male,27,High School,0,12,46,7,62,6.0,0,93,Urban,ML Engineer,123449,0 +106462,Male,41,Bachelors,4,6,10,55,92,3.0,5,70,Rural,Manager,98338,0 +106463,Female,45,Bachelors,12,19,31,82,85,9.0,2,53,Urban,HR Executive,85944,0 +106464,Female,36,High School,14,80,56,74,40,1.0,4,82,Urban,Data Analyst,147998,1 +106465,Male,26,Masters,12,25,84,0,12,4.0,6,61,Rural,Manager,53905,0 +106466,Male,55,PhD,4,42,2,35,73,9.0,4,49,Urban,Software Engineer,134609,0 +106467,Female,59,Bachelors,18,65,6,86,45,4.0,0,14,Urban,HR Executive,73126,0 +106468,Male,58,Bachelors,6,15,6,65,92,1.0,2,10,Semi-Urban,Data Analyst,82455,0 +106469,Male,46,Masters,17,94,35,49,67,8.0,2,17,Semi-Urban,Manager,26394,0 +106470,Male,36,Diploma,7,18,65,5,69,7.0,7,39,Rural,Data Analyst,70971,0 +106471,Female,22,High School,16,17,37,24,49,0.0,0,78,Rural,Software Engineer,22319,0 +106472,Male,52,Bachelors,12,17,86,33,90,4.0,2,46,Semi-Urban,Software Engineer,57232,0 +106473,Male,24,Bachelors,0,28,52,13,95,6.0,5,96,Semi-Urban,Software Engineer,36705,0 +106474,Other,24,PhD,7,67,80,42,75,1.0,1,13,Urban,HR Executive,89461,0 +106475,Male,48,Diploma,5,58,21,66,28,8.0,0,2,Urban,ML Engineer,106906,0 +106476,Male,36,Masters,14,3,2,46,64,7.0,1,4,Urban,HR Executive,50013,0 +106477,Male,31,Bachelors,17,30,93,70,6,1.0,2,42,Urban,HR Executive,87040,1 +106478,Female,53,Bachelors,18,39,64,83,0,0.0,7,58,Urban,HR Executive,25369,1 +106479,Male,27,Diploma,19,7,91,85,89,6.0,6,77,Rural,HR Executive,21731,1 +106480,Male,46,Masters,2,67,34,30,61,3.0,1,1,Semi-Urban,HR Executive,25436,0 +106481,Male,44,Bachelors,6,44,82,78,72,4.0,2,93,Urban,Manager,108332,1 +106482,Male,31,PhD,11,49,55,45,47,2.0,1,17,Urban,ML Engineer,55716,0 +106483,Male,46,Bachelors,3,45,72,35,61,9.0,0,46,Urban,Manager,42991,0 +106484,Male,52,Bachelors,0,4,59,70,40,0.0,6,10,Urban,Manager,129862,0 +106485,Male,46,Bachelors,5,63,80,4,71,9.0,1,45,Urban,ML Engineer,31735,0 +106486,Female,32,Bachelors,6,33,61,75,1,4.0,0,2,Rural,Software Engineer,137122,0 +106487,Female,26,Bachelors,5,56,21,39,4,4.0,1,11,Urban,Manager,107000,0 +106488,Male,46,Diploma,13,98,51,54,18,4.0,4,21,Semi-Urban,Manager,142400,0 +106489,Male,54,High School,9,89,96,7,45,2.0,0,57,Rural,Data Analyst,48951,1 +106490,Female,51,Bachelors,10,34,30,89,56,1.0,0,98,Urban,Data Analyst,103544,1 +106491,Male,39,Masters,11,49,14,99,57,9.0,7,41,Rural,Manager,48422,0 +106492,Male,59,Bachelors,1,18,85,74,73,7.0,0,71,Rural,Manager,36877,1 +106493,Female,26,High School,0,1,72,96,20,8.0,1,69,Urban,Data Analyst,98420,0 +106494,Female,59,High School,9,38,26,37,33,7.0,5,88,Semi-Urban,Software Engineer,65418,0 +106495,Male,43,High School,0,60,17,67,29,1.0,1,56,Urban,HR Executive,82894,0 +106496,Male,33,Masters,3,80,73,95,28,0.0,2,83,Urban,HR Executive,122872,1 +106497,Other,59,Bachelors,18,66,33,28,80,2.0,0,13,Semi-Urban,Data Analyst,97621,0 +106498,Male,49,Bachelors,7,94,65,72,34,1.0,7,16,Rural,Software Engineer,65426,1 +106499,Male,50,Bachelors,16,41,81,87,74,8.0,0,84,Semi-Urban,Data Analyst,50859,1 +106500,Male,36,Bachelors,7,13,48,62,49,4.0,4,89,Rural,Software Engineer,124944,0 +106501,Male,48,Diploma,6,30,22,38,13,0.0,1,83,Urban,Manager,83427,0 +106502,Male,48,PhD,7,81,93,87,4,8.0,5,72,Semi-Urban,Software Engineer,38288,1 +106503,Female,59,Diploma,4,35,48,48,13,1.0,7,73,Urban,Data Analyst,115790,0 +106504,Male,46,Diploma,4,41,36,13,76,4.0,4,60,Rural,Data Analyst,59482,0 +106505,Male,26,Bachelors,11,72,24,51,4,3.0,0,62,Rural,Manager,60890,0 +106506,Male,52,Bachelors,8,15,32,61,6,0.0,6,40,Urban,HR Executive,35321,0 +106507,Female,44,Diploma,9,66,49,96,43,2.0,3,44,Urban,Manager,96962,1 +106508,Male,27,Masters,5,47,66,6,29,9.0,7,72,Urban,Manager,59471,0 +106509,Male,25,Bachelors,18,64,9,32,18,4.0,0,77,Semi-Urban,HR Executive,72092,0 +106510,Male,37,Bachelors,14,21,98,59,66,6.0,4,66,Urban,Data Analyst,44395,1 +106511,Male,39,Diploma,3,64,76,69,20,0.0,4,80,Urban,HR Executive,119519,1 +106512,Male,31,High School,18,87,6,3,97,3.0,6,71,Urban,Software Engineer,147858,0 +106513,Female,51,PhD,10,83,20,54,1,2.0,6,73,Semi-Urban,Data Analyst,22980,0 +106514,Male,23,High School,0,83,72,20,53,6.0,4,16,Urban,Software Engineer,124707,0 +106515,Male,48,High School,16,90,24,7,98,2.0,7,51,Urban,Manager,68350,0 +106516,Female,52,Diploma,1,75,34,19,30,2.0,6,73,Semi-Urban,Data Analyst,148075,0 +106517,Female,55,Bachelors,19,35,41,48,2,4.0,3,16,Urban,ML Engineer,130893,0 +106518,Male,44,Masters,3,42,5,10,51,1.0,5,24,Rural,ML Engineer,132972,0 +106519,Male,59,Diploma,11,32,5,88,17,6.0,6,44,Semi-Urban,Software Engineer,79463,0 +106520,Female,54,Diploma,15,67,24,58,75,8.0,2,34,Urban,ML Engineer,147999,0 +106521,Male,57,Masters,3,69,36,39,10,5.0,4,96,Semi-Urban,Data Analyst,54410,1 +106522,Male,56,Masters,5,6,48,64,49,5.0,5,93,Semi-Urban,HR Executive,101723,0 +106523,Male,57,Masters,1,40,72,26,81,9.0,5,25,Rural,Manager,29660,0 +106524,Male,27,Bachelors,11,91,60,47,93,8.0,4,79,Urban,Manager,54811,1 +106525,Male,42,Bachelors,14,2,35,21,27,5.0,4,82,Urban,ML Engineer,118422,0 +106526,Male,36,Bachelors,16,9,86,91,96,9.0,3,97,Urban,ML Engineer,85701,1 +106527,Male,27,Masters,18,36,27,16,97,4.0,6,74,Urban,ML Engineer,61460,0 +106528,Other,36,Bachelors,8,9,14,31,28,8.0,6,24,Semi-Urban,Software Engineer,78525,0 +106529,Male,39,Masters,16,36,7,39,4,0.0,7,24,Urban,Software Engineer,54573,0 +106530,Female,23,Masters,16,20,97,77,1,9.0,2,86,Rural,Software Engineer,84268,1 +106531,Male,54,Bachelors,17,60,2,36,22,5.0,4,90,Semi-Urban,ML Engineer,73631,0 +106532,Male,29,Diploma,14,79,34,18,9,6.0,2,10,Urban,ML Engineer,45745,0 +106533,Male,56,Diploma,4,34,24,3,79,2.0,0,86,Semi-Urban,ML Engineer,99282,0 +106534,Male,23,Bachelors,17,86,59,2,34,8.0,2,17,Urban,Software Engineer,120983,0 +106535,Female,46,Bachelors,11,9,82,93,59,4.0,2,80,Urban,Software Engineer,144536,1 +106536,Male,28,Masters,19,96,67,34,97,9.0,6,54,Semi-Urban,HR Executive,94985,1 +106537,Male,46,Bachelors,14,90,43,81,72,7.0,1,25,Rural,HR Executive,149059,1 +106538,Female,36,Bachelors,12,85,86,90,18,5.0,4,50,Semi-Urban,ML Engineer,60661,1 +106539,Male,42,High School,1,91,99,11,22,8.0,1,12,Urban,Manager,117293,0 +106540,Male,47,Diploma,9,12,66,11,12,3.0,5,98,Urban,Data Analyst,54975,0 +106541,Male,38,Masters,1,99,45,26,41,0.0,6,16,Rural,Manager,69328,0 +106542,Male,52,Masters,2,25,19,38,36,1.0,3,83,Urban,ML Engineer,34048,0 +106543,Male,43,Masters,5,10,4,15,8,4.0,7,23,Urban,Data Analyst,54170,0 +106544,Female,59,Bachelors,4,11,46,90,42,1.0,0,82,Urban,Data Analyst,82567,0 +106545,Male,52,Bachelors,5,27,9,23,1,1.0,3,99,Urban,ML Engineer,137466,0 +106546,Male,53,Masters,3,77,82,71,65,3.0,3,63,Urban,ML Engineer,20636,1 +106547,Male,40,Masters,19,50,67,55,41,5.0,2,32,Rural,HR Executive,65356,0 +106548,Male,44,Masters,8,93,16,99,77,7.0,5,28,Urban,Data Analyst,101564,1 +106549,Male,38,High School,0,15,38,66,96,5.0,4,72,Urban,HR Executive,109230,0 +106550,Male,27,Bachelors,1,19,51,76,73,7.0,3,9,Urban,Manager,49386,0 +106551,Other,39,Bachelors,8,4,2,32,7,1.0,7,20,Semi-Urban,ML Engineer,94146,0 +106552,Female,29,High School,15,77,33,76,90,3.0,4,67,Urban,HR Executive,50884,1 +106553,Female,38,Bachelors,8,98,86,85,60,3.0,6,96,Urban,Software Engineer,32529,1 +106554,Female,54,Masters,7,41,79,14,68,9.0,3,70,Rural,ML Engineer,144361,0 +106555,Male,54,Masters,3,69,83,27,10,6.0,2,71,Urban,HR Executive,114419,1 +106556,Male,25,High School,14,33,24,85,56,9.0,3,60,Urban,HR Executive,102765,0 +106557,Male,41,Diploma,2,79,0,82,10,0.0,7,51,Semi-Urban,HR Executive,75477,0 +106558,Female,46,Bachelors,1,60,89,18,74,4.0,5,68,Rural,Software Engineer,26933,0 +106559,Female,41,Bachelors,12,57,5,29,82,4.0,4,96,Semi-Urban,ML Engineer,94238,0 +106560,Male,51,Diploma,1,5,40,1,44,1.0,5,68,Urban,Software Engineer,33595,0 +106561,Other,33,PhD,0,94,7,21,3,1.0,6,93,Urban,Data Analyst,44197,0 +106562,Male,53,Bachelors,4,50,38,31,92,1.0,0,65,Semi-Urban,HR Executive,25234,0 +106563,Female,31,Masters,13,56,28,58,26,0.0,0,84,Urban,Data Analyst,93778,0 +106564,Male,36,Bachelors,6,57,51,63,88,9.0,2,98,Urban,ML Engineer,24671,1 +106565,Other,45,Diploma,5,68,83,30,29,3.0,2,83,Rural,Software Engineer,57232,1 +106566,Male,49,Bachelors,17,74,65,24,12,0.0,0,20,Semi-Urban,Data Analyst,79513,0 +106567,Male,57,High School,13,14,0,1,37,6.0,6,36,Rural,ML Engineer,44254,0 +106568,Male,56,Masters,2,35,21,62,23,1.0,7,14,Rural,Manager,37880,0 +106569,Male,59,Diploma,6,48,45,98,58,9.0,4,28,Semi-Urban,Software Engineer,84965,0 +106570,Male,51,Bachelors,17,70,54,17,50,8.0,7,81,Urban,ML Engineer,31159,0 +106571,Male,36,Masters,1,63,49,26,48,0.0,4,28,Rural,Manager,117173,0 +106572,Female,56,Bachelors,4,86,26,12,18,1.0,4,28,Urban,Manager,24030,0 +106573,Female,30,Masters,16,68,56,47,68,7.0,1,84,Semi-Urban,Manager,87179,1 +106574,Male,24,Bachelors,7,4,87,27,52,7.0,5,36,Urban,Manager,25429,0 +106575,Male,34,Masters,10,99,37,84,21,8.0,3,3,Rural,ML Engineer,32179,0 +106576,Male,32,Bachelors,6,47,19,53,12,6.0,1,95,Urban,Data Analyst,64126,0 +106577,Female,46,Diploma,15,76,20,24,81,4.0,2,70,Semi-Urban,ML Engineer,124905,0 +106578,Female,38,Bachelors,6,19,70,33,60,1.0,2,26,Urban,Manager,72661,0 +106579,Male,22,PhD,13,7,31,66,85,8.0,4,82,Urban,ML Engineer,141156,0 +106580,Female,58,Bachelors,12,79,78,84,56,9.0,2,0,Semi-Urban,Manager,129724,1 +106581,Female,32,PhD,12,15,42,15,18,2.0,0,60,Semi-Urban,Software Engineer,26804,0 +106582,Female,23,Diploma,1,88,98,73,5,5.0,4,42,Rural,Manager,51204,1 +106583,Male,29,High School,8,59,71,94,89,6.0,6,7,Rural,Data Analyst,35313,0 +106584,Male,33,Bachelors,8,94,46,51,60,8.0,4,38,Urban,Software Engineer,23103,0 +106585,Male,48,Bachelors,14,59,90,67,23,9.0,7,92,Semi-Urban,Manager,96912,1 +106586,Male,22,High School,8,47,34,42,50,9.0,7,16,Urban,ML Engineer,53252,0 +106587,Female,43,Bachelors,15,16,69,30,43,1.0,4,98,Semi-Urban,Manager,121032,0 +106588,Female,45,Masters,5,59,74,27,95,6.0,1,79,Semi-Urban,ML Engineer,134446,0 +106589,Male,47,High School,10,90,65,9,73,3.0,1,96,Rural,HR Executive,110176,1 +106590,Female,54,Bachelors,0,23,82,4,70,3.0,5,79,Semi-Urban,Software Engineer,88331,0 +106591,Male,44,Bachelors,2,39,78,30,45,5.0,4,0,Rural,ML Engineer,128187,0 +106592,Male,50,Masters,8,45,18,0,71,2.0,7,71,Urban,Manager,140461,0 +106593,Male,54,Diploma,5,99,37,13,81,1.0,0,92,Rural,HR Executive,108471,1 +106594,Male,25,Diploma,14,24,27,47,16,8.0,1,83,Rural,HR Executive,95484,0 +106595,Other,57,Bachelors,15,43,52,5,95,8.0,3,6,Urban,HR Executive,63838,0 +106596,Female,25,High School,16,63,59,89,49,9.0,0,6,Rural,Data Analyst,112428,0 +106597,Male,34,High School,8,1,54,21,34,8.0,1,40,Semi-Urban,HR Executive,73231,0 +106598,Female,28,Masters,1,89,17,5,13,2.0,6,30,Urban,HR Executive,63086,0 +106599,Other,54,Diploma,16,8,25,7,20,7.0,4,76,Semi-Urban,Software Engineer,142305,0 +106600,Female,29,Bachelors,19,7,44,60,20,8.0,1,88,Urban,HR Executive,143741,0 +106601,Male,50,Bachelors,14,65,64,46,2,9.0,4,63,Urban,HR Executive,72630,1 +106602,Female,24,PhD,6,35,16,68,48,2.0,3,9,Rural,Data Analyst,50374,0 +106603,Male,45,High School,5,62,44,20,41,7.0,3,37,Urban,Manager,145916,0 +106604,Male,29,Diploma,3,88,72,76,72,9.0,2,43,Urban,Manager,124341,1 +106605,Other,29,PhD,9,75,29,31,95,7.0,5,32,Urban,ML Engineer,67122,0 +106606,Male,57,Diploma,14,4,68,18,94,1.0,4,34,Rural,Data Analyst,101721,0 +106607,Male,34,Masters,10,33,24,67,94,4.0,4,26,Urban,HR Executive,30007,0 +106608,Female,38,Bachelors,12,78,19,9,15,0.0,4,79,Rural,Manager,53573,0 +106609,Male,30,Masters,17,19,66,88,60,9.0,3,86,Rural,Software Engineer,46938,1 +106610,Male,32,High School,3,17,77,2,72,1.0,6,54,Urban,Manager,67763,0 +106611,Male,39,Bachelors,19,49,30,6,81,3.0,2,38,Semi-Urban,Data Analyst,116607,0 +106612,Male,31,Bachelors,18,8,29,37,87,4.0,6,28,Urban,ML Engineer,105135,0 +106613,Male,27,Bachelors,19,24,67,8,64,9.0,5,4,Semi-Urban,Data Analyst,72709,0 +106614,Male,48,Bachelors,13,16,98,27,36,3.0,2,33,Rural,ML Engineer,72879,0 +106615,Female,28,Masters,18,93,68,68,91,8.0,2,70,Rural,Software Engineer,94409,1 +106616,Female,22,Bachelors,15,94,5,97,40,4.0,0,48,Semi-Urban,Data Analyst,101110,1 +106617,Male,33,Bachelors,17,83,44,22,19,6.0,0,49,Rural,Software Engineer,51738,0 +106618,Female,40,High School,0,83,79,36,63,4.0,4,98,Urban,HR Executive,118768,1 +106619,Male,40,Masters,17,97,18,33,71,1.0,6,89,Urban,Manager,147391,1 +106620,Male,33,Diploma,8,89,2,51,29,9.0,0,56,Urban,Data Analyst,54432,0 +106621,Male,41,Bachelors,12,43,20,44,77,4.0,1,96,Semi-Urban,Software Engineer,143858,0 +106622,Female,53,Masters,18,26,39,27,95,2.0,4,9,Rural,Data Analyst,79684,0 +106623,Male,26,Diploma,10,17,89,39,59,9.0,4,33,Semi-Urban,ML Engineer,36101,0 +106624,Female,47,Bachelors,8,95,20,42,69,3.0,3,85,Semi-Urban,Manager,20364,1 +106625,Female,23,Diploma,4,64,9,49,61,3.0,5,0,Rural,HR Executive,100331,0 +106626,Female,26,Bachelors,10,37,0,19,63,9.0,4,84,Urban,Software Engineer,66475,0 +106627,Male,45,Bachelors,3,16,74,21,50,8.0,2,72,Semi-Urban,Data Analyst,23125,0 +106628,Male,35,Bachelors,17,17,34,52,19,7.0,1,27,Semi-Urban,HR Executive,21228,0 +106629,Male,49,Masters,19,23,27,73,21,7.0,1,16,Urban,Software Engineer,107480,0 +106630,Female,35,Bachelors,1,99,75,58,16,5.0,3,56,Semi-Urban,ML Engineer,99483,1 +106631,Male,25,Masters,1,25,66,41,92,5.0,6,21,Urban,Data Analyst,57626,0 +106632,Female,54,Bachelors,19,0,98,41,60,2.0,0,8,Rural,Manager,59980,0 +106633,Male,49,Bachelors,2,40,81,43,9,7.0,6,92,Urban,Software Engineer,136504,1 +106634,Female,38,Bachelors,0,25,96,98,10,7.0,3,42,Semi-Urban,Manager,73190,1 +106635,Male,23,Masters,3,66,62,92,3,1.0,0,49,Semi-Urban,Software Engineer,73362,1 +106636,Male,51,Bachelors,3,31,96,88,21,8.0,4,52,Urban,ML Engineer,98143,1 +106637,Female,55,Bachelors,3,83,2,91,8,9.0,4,41,Semi-Urban,Data Analyst,114350,0 +106638,Male,43,Bachelors,18,64,9,64,28,2.0,5,68,Semi-Urban,Software Engineer,37295,0 +106639,Male,48,Bachelors,12,52,47,51,68,1.0,5,65,Rural,ML Engineer,137961,0 +106640,Male,58,High School,19,52,92,26,71,9.0,3,83,Urban,HR Executive,65935,1 +106641,Male,36,Bachelors,17,86,9,75,66,3.0,6,93,Rural,HR Executive,94987,1 +106642,Female,41,High School,11,2,91,4,2,8.0,3,41,Rural,Manager,53481,0 +106643,Male,47,High School,5,21,69,59,97,4.0,2,72,Urban,Manager,149981,0 +106644,Male,48,High School,18,84,61,20,49,1.0,5,76,Rural,Software Engineer,102151,1 +106645,Male,25,PhD,19,22,62,73,72,9.0,7,5,Semi-Urban,ML Engineer,120389,0 +106646,Female,27,Bachelors,12,38,41,48,88,6.0,7,69,Semi-Urban,Data Analyst,108927,0 +106647,Male,26,Masters,13,82,10,79,38,4.0,1,29,Semi-Urban,Software Engineer,117137,0 +106648,Male,43,Bachelors,4,4,17,72,71,9.0,1,89,Rural,Manager,137922,0 +106649,Male,22,Diploma,7,4,34,33,2,6.0,6,11,Urban,ML Engineer,69129,0 +106650,Female,24,Masters,15,6,40,94,45,6.0,1,26,Urban,Manager,22419,0 +106651,Male,26,Bachelors,10,70,44,9,73,2.0,2,50,Urban,HR Executive,42119,0 +106652,Male,33,Diploma,13,50,20,54,33,3.0,4,29,Semi-Urban,HR Executive,98707,0 +106653,Male,35,Bachelors,18,24,15,59,64,6.0,0,51,Rural,Manager,33030,0 +106654,Female,52,Masters,1,93,5,77,17,1.0,6,81,Urban,ML Engineer,47330,1 +106655,Female,32,Masters,19,77,94,30,6,7.0,6,7,Rural,HR Executive,135280,0 +106656,Female,58,PhD,16,49,5,34,21,8.0,1,62,Urban,Software Engineer,87882,0 +106657,Male,41,Masters,5,83,21,86,75,9.0,6,77,Semi-Urban,Data Analyst,34046,1 +106658,Female,21,Masters,14,80,35,11,34,2.0,2,33,Urban,Data Analyst,59670,0 +106659,Female,57,PhD,13,22,2,21,74,6.0,0,97,Semi-Urban,HR Executive,133955,0 +106660,Female,59,Bachelors,10,60,28,0,60,3.0,0,57,Urban,ML Engineer,92081,0 +106661,Female,21,Bachelors,6,16,19,82,49,7.0,5,79,Urban,Data Analyst,49569,0 +106662,Male,53,Masters,17,27,16,78,72,0.0,7,86,Urban,Data Analyst,83912,0 +106663,Male,42,High School,19,51,56,2,11,3.0,6,84,Semi-Urban,Software Engineer,145966,0 +106664,Male,54,Diploma,0,93,98,63,16,0.0,6,47,Semi-Urban,Software Engineer,72070,1 +106665,Male,38,Masters,3,58,15,47,91,2.0,6,48,Semi-Urban,Manager,105111,0 +106666,Male,56,High School,19,49,11,68,53,5.0,3,53,Urban,Manager,112407,0 +106667,Male,52,Bachelors,14,73,6,2,76,1.0,7,75,Rural,Manager,118044,0 +106668,Female,55,Bachelors,19,56,63,0,77,9.0,4,95,Rural,HR Executive,88791,0 +106669,Male,32,Masters,0,26,56,19,11,5.0,0,79,Urban,Data Analyst,140107,0 +106670,Male,48,High School,7,90,13,92,32,4.0,0,63,Urban,HR Executive,81103,1 +106671,Male,30,Bachelors,16,93,13,4,83,0.0,1,45,Semi-Urban,HR Executive,21514,0 +106672,Female,48,Bachelors,5,91,24,33,94,7.0,7,60,Urban,Manager,149740,0 +106673,Other,49,Diploma,18,9,80,35,5,8.0,3,38,Urban,ML Engineer,51609,0 +106674,Male,57,Bachelors,10,23,38,34,8,3.0,5,19,Rural,Software Engineer,140577,0 +106675,Male,45,Diploma,2,80,44,12,64,1.0,0,84,Urban,HR Executive,89336,0 +106676,Male,54,Masters,17,66,53,80,94,8.0,4,77,Urban,Software Engineer,74590,1 +106677,Female,52,Diploma,6,65,7,74,15,4.0,5,22,Urban,Data Analyst,82269,0 +106678,Male,41,High School,12,78,12,47,78,8.0,3,75,Urban,Manager,47015,0 +106679,Male,43,Bachelors,10,77,0,83,46,0.0,3,73,Urban,Data Analyst,75355,0 +106680,Male,38,Bachelors,17,63,91,25,7,4.0,7,52,Urban,ML Engineer,121603,0 +106681,Female,38,Masters,10,97,45,40,1,6.0,1,18,Urban,Manager,86619,0 +106682,Female,50,Bachelors,1,55,82,41,3,2.0,7,23,Semi-Urban,Data Analyst,108733,0 +106683,Female,44,Diploma,13,20,73,72,96,2.0,5,10,Rural,Software Engineer,50012,0 +106684,Male,51,Bachelors,10,87,39,41,57,6.0,0,15,Urban,Data Analyst,145694,0 +106685,Male,30,Bachelors,6,1,28,88,93,8.0,1,9,Rural,HR Executive,69827,0 +106686,Female,21,Diploma,1,85,59,61,70,0.0,7,58,Urban,Data Analyst,119931,1 +106687,Male,28,Bachelors,15,42,81,88,79,4.0,5,41,Rural,Software Engineer,130465,1 +106688,Male,41,Bachelors,13,16,18,41,56,0.0,4,35,Urban,Data Analyst,108187,0 +106689,Female,38,High School,15,83,12,71,2,6.0,2,25,Urban,Data Analyst,71940,0 +106690,Female,59,High School,3,54,30,55,53,0.0,6,9,Rural,Data Analyst,100678,0 +106691,Male,55,High School,2,0,87,75,58,5.0,2,1,Urban,HR Executive,120214,0 +106692,Male,48,Bachelors,9,22,10,62,96,9.0,3,36,Semi-Urban,HR Executive,102525,0 +106693,Male,49,Masters,1,46,94,87,94,1.0,5,54,Rural,Data Analyst,133632,1 +106694,Female,56,Bachelors,19,55,25,80,74,2.0,2,40,Urban,Manager,22062,0 +106695,Male,32,Diploma,17,14,52,66,12,1.0,2,98,Semi-Urban,Software Engineer,103246,0 +106696,Female,49,Masters,15,91,11,84,39,2.0,1,85,Semi-Urban,Software Engineer,122179,1 +106697,Male,36,Masters,16,27,2,9,6,8.0,1,64,Rural,Manager,125672,0 +106698,Female,44,Bachelors,0,83,86,23,74,3.0,5,14,Urban,ML Engineer,78507,0 +106699,Male,43,Bachelors,3,47,58,87,8,9.0,3,86,Urban,Manager,123928,1 +106700,Male,55,Masters,3,12,74,72,88,9.0,7,41,Rural,Manager,126481,0 +106701,Male,24,Bachelors,11,57,11,4,39,9.0,6,82,Semi-Urban,HR Executive,132992,0 +106702,Female,30,High School,14,47,60,3,9,3.0,7,27,Semi-Urban,Manager,96572,0 +106703,Male,48,Bachelors,2,17,40,66,60,3.0,4,14,Rural,HR Executive,120388,0 +106704,Female,28,PhD,8,96,25,1,83,9.0,1,13,Semi-Urban,ML Engineer,22446,0 +106705,Male,59,Masters,14,29,98,18,24,5.0,6,87,Urban,Data Analyst,36128,0 +106706,Male,37,Bachelors,7,62,55,94,15,3.0,5,61,Urban,Data Analyst,23917,1 +106707,Male,35,Diploma,9,90,86,21,48,6.0,5,42,Urban,Manager,131877,1 +106708,Female,39,Bachelors,10,94,89,85,41,4.0,5,25,Urban,ML Engineer,64027,1 +106709,Male,44,Diploma,0,27,6,44,34,7.0,1,28,Urban,Software Engineer,144386,0 +106710,Male,30,Bachelors,9,84,48,57,77,2.0,0,21,Semi-Urban,Data Analyst,38269,0 +106711,Female,45,Diploma,2,2,49,97,39,2.0,1,19,Urban,Data Analyst,118732,0 +106712,Female,26,High School,17,37,99,74,94,0.0,4,22,Rural,Data Analyst,120068,0 +106713,Male,58,Bachelors,4,16,15,49,43,4.0,2,36,Urban,Software Engineer,20624,0 +106714,Female,58,High School,12,17,75,68,78,4.0,6,0,Semi-Urban,Manager,78018,0 +106715,Female,56,Bachelors,4,31,89,57,13,0.0,7,25,Rural,Software Engineer,136636,0 +106716,Male,22,High School,6,64,39,9,86,9.0,0,30,Urban,Data Analyst,101779,0 +106717,Female,47,High School,15,32,49,39,17,9.0,2,37,Urban,ML Engineer,33350,0 +106718,Male,50,Diploma,18,5,47,95,56,1.0,4,60,Urban,HR Executive,45191,0 +106719,Male,37,Diploma,13,77,60,20,26,7.0,2,91,Semi-Urban,HR Executive,107884,1 +106720,Female,59,High School,18,62,53,15,42,1.0,1,98,Semi-Urban,Software Engineer,92836,0 +106721,Female,30,Diploma,9,41,48,45,45,0.0,2,76,Semi-Urban,HR Executive,143048,0 +106722,Male,23,Bachelors,7,95,31,51,84,0.0,3,82,Semi-Urban,Manager,57853,1 +106723,Female,45,Bachelors,9,67,62,27,75,7.0,2,68,Semi-Urban,HR Executive,135024,0 +106724,Male,42,Masters,2,48,53,7,50,1.0,4,46,Urban,Data Analyst,67737,0 +106725,Male,23,Diploma,12,74,74,14,92,1.0,7,9,Urban,ML Engineer,125698,0 +106726,Male,30,Bachelors,2,75,37,39,0,4.0,3,50,Urban,Manager,54521,0 +106727,Male,49,Bachelors,13,97,9,39,38,8.0,5,47,Urban,Software Engineer,50133,0 +106728,Male,51,Masters,9,66,50,83,90,8.0,0,9,Rural,ML Engineer,144917,0 +106729,Female,26,Masters,7,86,83,65,35,1.0,4,42,Semi-Urban,Software Engineer,41836,1 +106730,Male,31,Bachelors,2,82,81,55,41,4.0,1,76,Rural,Software Engineer,72668,1 +106731,Other,44,High School,13,37,72,46,18,5.0,3,12,Urban,ML Engineer,51337,0 +106732,Other,32,High School,18,1,30,92,29,6.0,1,75,Urban,ML Engineer,149601,0 +106733,Male,57,Bachelors,18,95,92,33,98,4.0,3,97,Urban,HR Executive,22161,1 +106734,Female,43,Masters,19,9,36,8,77,4.0,2,39,Urban,Manager,110078,0 +106735,Male,39,Bachelors,17,64,59,47,75,9.0,0,40,Rural,ML Engineer,66173,0 +106736,Male,57,Bachelors,19,82,81,97,76,5.0,6,63,Urban,HR Executive,24317,1 +106737,Male,34,Bachelors,15,23,46,56,6,2.0,4,79,Urban,HR Executive,22924,0 +106738,Male,48,High School,18,3,63,90,86,2.0,6,14,Semi-Urban,Manager,120156,0 +106739,Male,40,Bachelors,10,34,17,63,57,3.0,0,95,Urban,Manager,35653,0 +106740,Female,56,Masters,5,43,78,90,76,7.0,3,5,Urban,HR Executive,114282,0 +106741,Male,40,Bachelors,4,20,8,18,5,3.0,7,94,Semi-Urban,HR Executive,76276,0 +106742,Male,50,Diploma,16,29,11,45,87,7.0,3,35,Urban,ML Engineer,46142,0 +106743,Female,29,Bachelors,0,20,88,40,49,7.0,4,66,Semi-Urban,Manager,47442,0 +106744,Female,58,Bachelors,15,11,76,86,43,6.0,7,14,Urban,Software Engineer,118467,0 +106745,Female,43,High School,3,77,26,34,2,2.0,4,20,Semi-Urban,Software Engineer,86059,0 +106746,Female,23,Bachelors,14,28,50,79,81,9.0,3,0,Urban,Software Engineer,129737,0 +106747,Male,30,Masters,16,13,28,15,22,0.0,1,53,Urban,Data Analyst,44803,0 +106748,Male,51,Diploma,19,79,2,82,99,9.0,7,13,Urban,Software Engineer,130406,0 +106749,Male,47,High School,7,19,53,44,9,5.0,2,11,Semi-Urban,HR Executive,51699,0 +106750,Male,42,Bachelors,4,62,59,28,39,2.0,4,92,Rural,HR Executive,91854,1 +106751,Male,48,Bachelors,18,33,73,3,75,4.0,6,95,Semi-Urban,Manager,66577,0 +106752,Male,22,Bachelors,7,51,31,70,50,5.0,4,40,Urban,ML Engineer,87622,0 +106753,Male,28,Diploma,11,41,46,97,83,4.0,4,87,Urban,Manager,55202,1 +106754,Other,46,Masters,13,90,64,8,22,5.0,7,41,Urban,HR Executive,137781,0 +106755,Female,33,Bachelors,5,55,80,10,29,2.0,4,68,Urban,Data Analyst,99073,0 +106756,Male,57,Bachelors,1,18,77,97,93,7.0,1,2,Urban,HR Executive,30492,0 +106757,Male,52,Masters,3,30,81,37,0,7.0,2,43,Urban,Data Analyst,80931,0 +106758,Male,24,High School,11,83,81,88,65,5.0,7,4,Urban,ML Engineer,36887,1 +106759,Female,21,Bachelors,13,90,2,70,8,9.0,4,30,Semi-Urban,HR Executive,88977,0 +106760,Male,25,Bachelors,12,57,1,64,62,9.0,5,67,Urban,ML Engineer,35672,0 +106761,Male,42,Bachelors,11,63,62,55,70,4.0,0,78,Rural,ML Engineer,60146,1 +106762,Other,23,Bachelors,2,47,80,45,56,1.0,3,75,Semi-Urban,Data Analyst,21161,1 +106763,Male,42,PhD,0,61,48,1,80,3.0,1,44,Semi-Urban,Manager,116851,0 +106764,Female,52,Bachelors,18,1,8,73,26,0.0,3,82,Rural,Manager,92007,0 +106765,Male,39,Diploma,18,94,19,29,58,7.0,0,77,Urban,HR Executive,83262,0 +106766,Male,38,Masters,19,16,11,75,42,0.0,7,42,Semi-Urban,Software Engineer,85716,0 +106767,Male,55,High School,10,18,91,20,71,1.0,7,5,Rural,Manager,106434,0 +106768,Male,37,High School,19,8,87,3,20,4.0,6,62,Semi-Urban,HR Executive,128263,0 +106769,Male,33,Diploma,14,82,4,51,48,1.0,5,77,Urban,Manager,48068,0 +106770,Male,47,PhD,15,92,52,57,30,1.0,6,40,Urban,ML Engineer,85854,1 +106771,Female,52,Diploma,5,46,65,93,96,7.0,4,35,Semi-Urban,ML Engineer,143632,0 +106772,Male,58,Diploma,19,66,60,42,74,3.0,0,5,Urban,Manager,74356,0 +106773,Male,36,High School,9,51,37,65,96,6.0,0,20,Urban,Data Analyst,46083,0 +106774,Male,51,High School,1,82,8,96,68,8.0,3,44,Urban,Software Engineer,102596,0 +106775,Male,34,High School,4,33,45,97,57,8.0,7,18,Rural,ML Engineer,146146,0 +106776,Other,52,Diploma,0,20,76,5,31,1.0,6,75,Urban,Data Analyst,78271,0 +106777,Male,56,PhD,10,59,87,39,89,0.0,3,12,Urban,HR Executive,79913,0 +106778,Male,44,Bachelors,8,47,13,30,38,7.0,6,37,Semi-Urban,HR Executive,119855,0 +106779,Female,24,Bachelors,18,16,61,40,4,8.0,2,97,Urban,Data Analyst,132717,0 +106780,Male,21,Diploma,1,81,16,3,44,2.0,3,10,Urban,Data Analyst,43401,0 +106781,Male,26,High School,0,87,23,87,72,4.0,7,71,Urban,Data Analyst,25031,1 +106782,Male,57,Masters,18,75,10,29,47,3.0,4,18,Semi-Urban,Software Engineer,88152,0 +106783,Female,21,Diploma,4,44,14,12,0,7.0,0,75,Urban,HR Executive,104789,0 +106784,Female,34,Diploma,7,25,95,84,59,7.0,1,51,Urban,HR Executive,149194,1 +106785,Female,25,Masters,0,96,93,56,13,6.0,7,30,Urban,Manager,78609,1 +106786,Male,59,Bachelors,11,32,4,78,21,4.0,2,4,Rural,HR Executive,24079,0 +106787,Male,32,High School,9,38,50,73,40,5.0,1,78,Urban,HR Executive,130842,1 +106788,Male,59,High School,8,40,71,53,3,9.0,1,84,Urban,Software Engineer,139950,1 +106789,Male,23,Bachelors,12,97,47,54,37,4.0,4,85,Semi-Urban,HR Executive,29345,1 +106790,Female,55,Masters,14,27,67,59,51,9.0,0,87,Semi-Urban,ML Engineer,111012,0 +106791,Male,30,Bachelors,3,0,73,6,1,9.0,4,28,Urban,Manager,143931,0 +106792,Male,56,Bachelors,15,45,90,70,1,0.0,5,63,Rural,Software Engineer,54242,1 +106793,Male,57,Bachelors,18,26,57,11,5,1.0,6,88,Urban,HR Executive,28815,0 +106794,Male,37,Masters,14,30,64,7,76,9.0,4,11,Urban,Manager,126941,0 +106795,Male,42,Bachelors,8,31,97,34,23,3.0,0,38,Semi-Urban,ML Engineer,31647,0 +106796,Male,40,Bachelors,12,29,99,76,25,0.0,6,0,Semi-Urban,Manager,66759,0 +106797,Male,54,Bachelors,16,78,96,61,50,5.0,5,89,Semi-Urban,Data Analyst,29092,1 +106798,Male,22,Bachelors,18,75,8,51,34,4.0,3,60,Rural,Software Engineer,70745,0 +106799,Male,50,Bachelors,4,18,59,55,29,5.0,7,0,Rural,Manager,126700,0 +106800,Female,26,Diploma,15,97,51,42,84,7.0,3,72,Rural,ML Engineer,24672,1 +106801,Male,31,High School,5,23,41,22,16,3.0,5,89,Rural,Software Engineer,66824,0 +106802,Male,46,Masters,18,38,81,24,96,7.0,4,17,Rural,Software Engineer,127976,0 +106803,Male,39,Diploma,4,4,66,52,45,4.0,1,80,Semi-Urban,Data Analyst,57176,0 +106804,Male,31,Bachelors,4,23,62,80,0,7.0,7,37,Urban,Software Engineer,95755,0 +106805,Female,34,Bachelors,0,98,5,78,53,7.0,7,62,Semi-Urban,Data Analyst,23114,1 +106806,Female,59,Bachelors,7,64,2,32,37,8.0,6,88,Urban,HR Executive,99968,0 +106807,Female,32,PhD,18,15,66,44,21,7.0,6,91,Urban,HR Executive,40006,0 +106808,Male,34,Bachelors,10,26,2,16,69,4.0,6,10,Urban,HR Executive,137780,0 +106809,Female,41,High School,4,18,20,41,76,3.0,2,25,Semi-Urban,Software Engineer,77568,0 +106810,Female,50,Masters,5,48,41,43,46,8.0,3,86,Urban,Manager,28849,0 +106811,Male,42,Diploma,3,49,57,26,31,3.0,2,86,Rural,Software Engineer,27938,0 +106812,Female,53,Masters,10,75,42,55,60,8.0,3,64,Urban,Manager,84172,0 +106813,Female,51,Bachelors,1,38,71,8,6,6.0,2,53,Rural,HR Executive,86900,0 +106814,Male,21,High School,13,20,50,38,29,7.0,1,5,Rural,Manager,119878,0 +106815,Female,38,High School,9,58,1,45,16,3.0,7,85,Semi-Urban,Software Engineer,102963,0 +106816,Male,32,PhD,17,3,78,92,79,3.0,7,10,Urban,ML Engineer,146615,0 +106817,Male,34,Diploma,14,70,59,44,54,3.0,6,85,Urban,Data Analyst,67493,1 +106818,Female,42,Bachelors,12,58,67,38,24,6.0,5,22,Urban,Manager,129963,0 +106819,Female,37,High School,4,73,45,8,56,4.0,5,53,Rural,Manager,32638,0 +106820,Female,33,Bachelors,14,57,26,88,21,5.0,7,64,Urban,Manager,126126,0 +106821,Female,21,PhD,14,91,25,96,26,8.0,1,15,Urban,Software Engineer,60944,0 +106822,Male,41,High School,2,80,56,22,81,7.0,7,56,Semi-Urban,ML Engineer,80302,0 +106823,Male,56,Masters,2,59,0,91,65,1.0,6,86,Urban,Software Engineer,62038,1 +106824,Male,43,Diploma,10,69,39,49,32,1.0,1,50,Urban,ML Engineer,52802,0 +106825,Female,29,Bachelors,18,80,22,14,63,9.0,2,99,Rural,ML Engineer,32409,0 +106826,Male,51,Diploma,11,0,51,25,52,9.0,7,53,Urban,HR Executive,102223,0 +106827,Male,31,Bachelors,14,58,40,35,56,0.0,4,28,Rural,ML Engineer,62762,0 +106828,Female,43,Diploma,2,43,51,60,48,7.0,5,34,Urban,ML Engineer,69974,0 +106829,Female,37,Bachelors,7,81,32,31,37,3.0,6,22,Rural,HR Executive,94893,0 +106830,Male,47,Masters,12,30,45,83,80,9.0,7,96,Semi-Urban,Manager,138217,1 +106831,Male,32,Masters,5,64,28,36,13,3.0,1,37,Urban,Data Analyst,24058,0 +106832,Male,27,Masters,3,15,1,40,67,4.0,3,80,Semi-Urban,Data Analyst,71404,0 +106833,Female,49,Bachelors,11,67,35,32,21,0.0,0,79,Urban,Manager,41820,0 +106834,Female,54,Bachelors,6,36,84,47,66,5.0,2,30,Urban,Data Analyst,137761,0 +106835,Female,46,Bachelors,19,89,25,24,34,4.0,1,82,Semi-Urban,Data Analyst,44217,0 +106836,Female,49,Diploma,8,5,70,17,9,2.0,1,61,Rural,Data Analyst,100264,0 +106837,Male,54,Bachelors,11,57,10,77,0,2.0,0,2,Urban,Data Analyst,96949,0 +106838,Male,44,High School,13,8,88,97,39,9.0,3,54,Rural,Data Analyst,72805,1 +106839,Female,40,Masters,18,62,71,50,34,4.0,7,72,Urban,Manager,38899,1 +106840,Male,23,Diploma,18,42,29,46,27,2.0,1,0,Semi-Urban,HR Executive,52872,0 +106841,Male,38,Masters,12,72,93,46,87,9.0,2,18,Semi-Urban,ML Engineer,37012,0 +106842,Female,21,Diploma,13,95,12,64,92,2.0,2,33,Urban,Software Engineer,148581,0 +106843,Female,24,Bachelors,16,32,29,93,37,5.0,6,18,Rural,Software Engineer,32174,0 +106844,Male,24,Bachelors,1,62,25,90,24,3.0,4,65,Urban,Manager,70387,1 +106845,Other,54,Bachelors,11,49,10,64,18,2.0,1,69,Semi-Urban,Manager,111840,0 +106846,Male,45,Bachelors,17,61,49,30,81,2.0,2,69,Urban,Manager,81266,0 +106847,Male,54,Diploma,16,80,68,2,40,3.0,1,60,Urban,HR Executive,44147,0 +106848,Female,47,Diploma,12,54,71,76,52,7.0,6,49,Rural,Manager,75144,1 +106849,Male,49,High School,14,9,59,79,75,0.0,3,33,Urban,Data Analyst,85599,0 +106850,Male,42,Bachelors,8,48,55,27,1,5.0,2,35,Rural,Software Engineer,111417,0 +106851,Female,43,Bachelors,17,68,38,99,62,1.0,1,12,Urban,Manager,94931,0 +106852,Male,44,Masters,16,65,94,13,96,0.0,2,10,Semi-Urban,Software Engineer,28858,0 +106853,Male,52,Masters,10,24,49,10,97,4.0,2,85,Urban,Manager,99424,0 +106854,Male,48,Bachelors,11,87,16,88,45,1.0,7,48,Urban,ML Engineer,81739,1 +106855,Female,31,High School,7,42,46,40,3,8.0,1,8,Semi-Urban,Software Engineer,28148,0 +106856,Female,40,Diploma,4,11,23,92,60,6.0,7,74,Urban,Manager,123998,0 +106857,Female,22,Diploma,14,82,74,17,36,1.0,7,48,Semi-Urban,Data Analyst,139361,0 +106858,Female,42,Masters,10,23,73,0,89,7.0,6,57,Urban,Software Engineer,68364,0 +106859,Male,43,High School,3,59,54,8,35,9.0,2,20,Urban,HR Executive,77975,0 +106860,Female,29,Bachelors,8,59,99,23,21,4.0,5,76,Rural,Data Analyst,52585,1 +106861,Male,42,Bachelors,19,48,89,97,57,4.0,7,97,Rural,Data Analyst,99374,1 +106862,Female,23,PhD,11,21,57,82,20,5.0,3,45,Rural,ML Engineer,80157,0 +106863,Male,43,Bachelors,5,9,64,75,55,5.0,3,77,Rural,Data Analyst,80766,0 +106864,Female,25,Bachelors,7,94,64,30,30,0.0,0,35,Urban,Software Engineer,147908,0 +106865,Female,43,Bachelors,5,76,76,2,98,8.0,3,51,Rural,ML Engineer,93919,0 +106866,Female,42,PhD,5,8,85,31,85,3.0,3,49,Rural,Manager,114550,0 +106867,Male,38,Bachelors,1,28,89,3,39,6.0,4,70,Urban,HR Executive,70225,0 +106868,Other,48,Diploma,14,29,51,63,8,7.0,0,45,Semi-Urban,Manager,43803,0 +106869,Male,53,Masters,16,33,5,59,78,0.0,6,75,Urban,ML Engineer,36105,0 +106870,Male,30,Masters,11,3,56,76,56,0.0,0,76,Urban,Manager,104107,0 +106871,Male,57,High School,18,73,12,62,69,6.0,6,10,Urban,ML Engineer,56436,0 +106872,Male,49,Bachelors,16,39,38,20,48,6.0,2,60,Urban,Manager,80898,0 +106873,Male,38,Masters,1,27,73,13,41,9.0,0,81,Urban,Software Engineer,35675,0 +106874,Male,27,Bachelors,0,87,85,8,25,7.0,3,86,Rural,Software Engineer,143942,1 +106875,Male,27,Bachelors,17,80,52,85,86,2.0,4,89,Urban,ML Engineer,104883,1 +106876,Male,58,Bachelors,18,3,97,71,1,5.0,2,50,Urban,ML Engineer,125322,0 +106877,Female,21,Diploma,1,76,96,83,44,5.0,0,97,Urban,Data Analyst,142074,1 +106878,Male,22,PhD,17,22,29,57,6,4.0,3,14,Urban,Manager,64075,0 +106879,Male,37,High School,5,27,49,4,45,2.0,3,25,Urban,ML Engineer,124426,0 +106880,Male,44,Diploma,4,66,8,12,14,4.0,2,86,Urban,Data Analyst,132216,0 +106881,Other,57,Masters,3,48,84,15,43,2.0,4,48,Semi-Urban,Manager,69144,0 +106882,Female,21,Diploma,0,68,43,94,89,9.0,2,91,Semi-Urban,Manager,93911,1 +106883,Male,49,PhD,15,73,74,95,90,4.0,5,79,Urban,Manager,46944,1 +106884,Male,28,PhD,13,31,23,88,72,0.0,5,51,Urban,ML Engineer,51005,0 +106885,Male,32,Bachelors,12,42,44,59,16,5.0,6,68,Urban,ML Engineer,38027,0 +106886,Female,39,High School,0,69,40,56,24,3.0,5,34,Rural,Manager,136872,0 +106887,Female,34,Diploma,16,40,83,53,22,4.0,6,0,Urban,HR Executive,80161,0 +106888,Male,48,Bachelors,3,74,21,78,74,0.0,1,85,Urban,ML Engineer,147082,1 +106889,Male,40,Bachelors,0,79,29,14,99,3.0,1,28,Urban,Manager,24621,0 +106890,Male,46,Bachelors,19,13,7,83,93,7.0,2,27,Urban,Manager,98496,0 +106891,Other,28,Bachelors,13,12,50,53,87,0.0,5,13,Urban,Manager,55219,0 +106892,Male,40,Bachelors,16,57,67,39,13,0.0,0,44,Urban,Manager,117668,0 +106893,Female,50,Bachelors,9,64,68,37,74,0.0,0,31,Urban,Manager,44509,0 +106894,Male,27,High School,2,23,98,66,56,5.0,2,10,Urban,HR Executive,141918,0 +106895,Female,56,Bachelors,7,71,64,16,14,6.0,2,79,Semi-Urban,ML Engineer,64569,0 +106896,Male,29,Masters,0,44,54,51,78,1.0,7,96,Semi-Urban,HR Executive,102696,1 +106897,Male,57,High School,3,60,81,61,57,0.0,7,6,Urban,Manager,86501,0 +106898,Male,23,Masters,0,67,2,55,85,8.0,5,22,Rural,Manager,34495,0 +106899,Male,34,Masters,5,69,39,85,27,0.0,6,73,Semi-Urban,HR Executive,25897,1 +106900,Male,22,High School,19,11,42,40,3,7.0,5,50,Urban,Software Engineer,142826,0 +106901,Female,25,Bachelors,10,49,3,54,14,5.0,3,25,Rural,HR Executive,101265,0 +106902,Male,53,High School,6,74,90,66,66,8.0,0,49,Semi-Urban,Manager,119423,1 +106903,Female,43,Masters,3,78,42,75,67,3.0,5,95,Semi-Urban,Data Analyst,147322,1 +106904,Female,32,Bachelors,1,14,50,49,71,7.0,3,22,Urban,Software Engineer,78631,0 +106905,Male,46,Bachelors,13,93,22,62,16,2.0,2,15,Urban,HR Executive,127783,0 +106906,Female,21,Masters,6,18,23,39,71,6.0,5,22,Urban,Data Analyst,88073,0 +106907,Male,28,Diploma,12,1,93,85,69,5.0,3,58,Urban,HR Executive,90472,1 +106908,Male,48,Bachelors,5,15,67,46,45,1.0,2,1,Urban,Software Engineer,90169,0 +106909,Male,35,Masters,11,34,32,74,79,0.0,0,91,Urban,Software Engineer,67689,0 +106910,Male,21,Diploma,7,38,15,94,1,5.0,7,15,Urban,Data Analyst,138243,0 +106911,Female,22,Bachelors,16,21,4,19,39,2.0,4,75,Urban,Software Engineer,49040,0 +106912,Female,33,High School,6,39,34,74,6,3.0,7,12,Semi-Urban,Manager,63839,0 +106913,Male,48,Bachelors,15,99,22,30,6,5.0,1,5,Rural,ML Engineer,149468,0 +106914,Male,38,Masters,16,91,54,22,15,8.0,3,9,Semi-Urban,Data Analyst,91327,0 +106915,Male,58,Bachelors,8,16,7,92,75,0.0,2,7,Urban,HR Executive,30144,0 +106916,Male,27,Diploma,17,87,35,17,45,5.0,3,6,Urban,Data Analyst,149395,0 +106917,Other,37,High School,12,78,92,2,72,5.0,4,49,Urban,Data Analyst,80032,0 +106918,Male,57,Bachelors,5,48,23,21,65,7.0,0,60,Rural,HR Executive,97845,0 +106919,Male,22,High School,17,89,64,79,50,6.0,4,46,Rural,Manager,121643,1 +106920,Other,38,Bachelors,5,3,94,67,53,8.0,4,65,Semi-Urban,ML Engineer,98130,0 +106921,Female,30,Bachelors,11,24,17,46,25,1.0,2,33,Urban,Manager,28278,0 +106922,Male,47,Bachelors,9,43,56,46,83,9.0,5,57,Urban,HR Executive,43782,0 +106923,Female,46,Bachelors,6,57,75,51,86,7.0,2,93,Urban,Software Engineer,112136,1 +106924,Male,45,Diploma,5,29,96,68,40,9.0,1,21,Semi-Urban,Software Engineer,129734,0 +106925,Other,53,Diploma,6,21,8,85,62,6.0,7,21,Urban,HR Executive,123407,0 +106926,Female,25,PhD,1,30,26,78,43,5.0,2,30,Urban,Data Analyst,114426,0 +106927,Other,52,Diploma,2,57,53,92,12,5.0,7,77,Rural,Data Analyst,40833,1 +106928,Female,59,Bachelors,16,36,25,63,91,2.0,4,45,Urban,Data Analyst,38231,0 +106929,Male,56,Bachelors,3,20,26,77,85,2.0,4,64,Semi-Urban,Data Analyst,121498,0 +106930,Female,30,Diploma,19,94,47,34,37,4.0,3,95,Semi-Urban,Data Analyst,60058,1 +106931,Male,43,Diploma,6,30,22,10,19,8.0,1,58,Urban,ML Engineer,122455,0 +106932,Male,41,High School,16,94,74,84,42,4.0,2,57,Urban,Data Analyst,99078,1 +106933,Male,27,Bachelors,9,71,29,3,65,7.0,6,37,Rural,Software Engineer,24794,0 +106934,Male,50,Diploma,4,13,37,13,30,7.0,4,78,Urban,Manager,102867,0 +106935,Female,40,Bachelors,10,95,70,95,86,2.0,6,80,Urban,ML Engineer,141537,1 +106936,Male,31,High School,8,25,28,20,91,1.0,2,80,Urban,Software Engineer,61542,0 +106937,Female,38,Bachelors,12,34,52,46,2,9.0,6,23,Semi-Urban,Manager,129836,0 +106938,Female,39,Diploma,9,48,33,47,62,9.0,2,98,Urban,Software Engineer,70497,0 +106939,Female,42,Masters,13,37,98,67,9,1.0,6,63,Urban,ML Engineer,148082,1 +106940,Male,28,Diploma,9,85,10,34,81,6.0,6,67,Urban,Data Analyst,136790,0 +106941,Female,41,Bachelors,19,44,44,14,26,9.0,5,8,Semi-Urban,HR Executive,114121,0 +106942,Female,40,Masters,16,12,41,55,17,6.0,3,96,Urban,ML Engineer,136566,0 +106943,Male,32,Bachelors,15,24,2,86,73,1.0,7,70,Semi-Urban,HR Executive,81709,0 +106944,Female,27,Bachelors,9,28,72,41,54,3.0,4,77,Urban,Data Analyst,111638,0 +106945,Male,50,Bachelors,3,96,49,50,50,1.0,6,94,Urban,Data Analyst,113813,1 +106946,Female,45,Diploma,19,88,36,42,34,8.0,6,77,Urban,Manager,122077,1 +106947,Male,52,Masters,10,61,66,80,44,1.0,0,7,Urban,Software Engineer,149845,0 +106948,Female,49,PhD,5,76,71,98,81,9.0,4,13,Urban,Data Analyst,63137,1 +106949,Male,38,Bachelors,11,84,47,99,21,1.0,0,56,Urban,Manager,69733,1 +106950,Female,44,Bachelors,10,78,15,46,19,7.0,6,73,Rural,Software Engineer,79432,0 +106951,Male,42,Masters,4,77,14,52,78,3.0,6,74,Semi-Urban,Manager,135928,0 +106952,Male,42,High School,19,75,10,40,2,7.0,6,6,Urban,HR Executive,137396,0 +106953,Male,47,High School,7,27,74,26,17,1.0,5,27,Rural,Manager,43935,0 +106954,Female,42,Bachelors,16,25,73,17,45,0.0,3,4,Urban,Manager,97532,0 +106955,Male,37,Bachelors,5,79,42,16,12,0.0,1,30,Urban,Manager,93703,0 +106956,Male,32,Bachelors,15,64,72,72,31,2.0,1,18,Urban,HR Executive,67498,0 +106957,Male,47,PhD,12,31,61,49,14,0.0,7,11,Urban,Manager,43021,0 +106958,Male,38,Bachelors,1,14,69,39,14,4.0,7,37,Semi-Urban,Manager,143320,0 +106959,Male,21,Diploma,19,8,19,24,56,7.0,7,75,Semi-Urban,ML Engineer,35566,0 +106960,Other,42,High School,18,59,18,19,11,7.0,6,21,Urban,HR Executive,104981,0 +106961,Male,44,Masters,2,61,70,26,8,4.0,6,82,Urban,Manager,83044,1 +106962,Female,49,High School,6,50,17,93,42,4.0,3,12,Semi-Urban,ML Engineer,136203,0 +106963,Male,33,Masters,6,25,65,86,11,2.0,0,45,Rural,Software Engineer,43845,0 +106964,Male,58,Bachelors,15,40,35,14,66,8.0,6,47,Semi-Urban,ML Engineer,29606,0 +106965,Female,39,Bachelors,19,58,97,73,83,4.0,2,24,Semi-Urban,ML Engineer,141061,1 +106966,Male,27,Diploma,13,19,61,35,83,4.0,1,69,Urban,Manager,134535,0 +106967,Male,29,High School,9,58,75,84,41,7.0,0,27,Urban,Manager,128924,1 +106968,Male,28,Masters,6,38,32,22,85,6.0,5,73,Urban,Manager,38529,0 +106969,Male,29,Diploma,16,80,18,71,72,0.0,3,52,Semi-Urban,Manager,127856,0 +106970,Male,30,Masters,18,40,42,51,57,8.0,3,27,Rural,ML Engineer,95264,0 +106971,Male,47,High School,15,83,74,54,19,8.0,5,73,Urban,Software Engineer,79894,1 +106972,Male,52,Bachelors,5,56,90,80,15,9.0,6,75,Urban,ML Engineer,51782,1 +106973,Female,49,Bachelors,8,75,12,93,76,6.0,0,47,Urban,HR Executive,41065,0 +106974,Female,35,Bachelors,1,1,85,84,64,9.0,5,52,Semi-Urban,Data Analyst,42342,0 +106975,Male,25,Masters,6,96,1,25,47,9.0,0,8,Urban,Data Analyst,132357,0 +106976,Female,29,Bachelors,4,65,54,63,93,8.0,6,1,Rural,Data Analyst,27626,0 +106977,Male,34,Bachelors,7,94,59,29,75,7.0,0,68,Rural,Manager,40883,1 +106978,Male,39,Masters,0,58,6,26,79,9.0,5,37,Semi-Urban,Software Engineer,113709,0 +106979,Female,25,Masters,14,22,48,1,72,4.0,2,64,Semi-Urban,ML Engineer,83560,0 +106980,Female,22,Bachelors,0,35,11,5,52,8.0,5,84,Rural,Manager,30440,0 +106981,Male,38,Bachelors,10,14,40,27,21,8.0,2,46,Urban,HR Executive,92894,0 +106982,Male,53,Diploma,3,50,96,44,21,4.0,2,83,Urban,HR Executive,93726,1 +106983,Female,32,High School,4,29,3,91,96,7.0,1,44,Rural,HR Executive,94475,0 +106984,Male,38,Bachelors,1,62,41,54,29,7.0,5,97,Semi-Urban,HR Executive,47088,1 +106985,Male,36,Bachelors,3,45,79,67,56,3.0,5,6,Rural,Software Engineer,99314,0 +106986,Male,33,Bachelors,3,49,39,84,92,1.0,6,83,Rural,ML Engineer,26741,1 +106987,Other,46,Diploma,2,10,23,71,4,4.0,7,37,Urban,ML Engineer,43800,0 +106988,Female,28,High School,15,88,7,0,20,1.0,4,54,Semi-Urban,HR Executive,96050,0 +106989,Female,38,Masters,1,97,42,24,63,8.0,2,52,Semi-Urban,Software Engineer,20536,0 +106990,Male,38,Bachelors,13,97,90,21,73,7.0,4,39,Urban,HR Executive,61198,1 +106991,Male,52,High School,18,56,53,82,88,1.0,6,17,Urban,Manager,25734,0 +106992,Male,45,Bachelors,18,2,55,71,41,5.0,3,39,Urban,Software Engineer,146563,0 +106993,Female,21,Masters,15,82,82,86,99,2.0,6,66,Urban,Manager,137290,1 +106994,Male,39,Diploma,12,32,78,32,35,4.0,3,20,Rural,Manager,111607,0 +106995,Male,48,Bachelors,18,0,46,13,38,6.0,6,44,Semi-Urban,ML Engineer,47183,0 +106996,Male,31,PhD,16,78,81,13,7,9.0,5,81,Urban,HR Executive,123660,1 +106997,Male,36,Diploma,3,98,47,49,17,1.0,2,3,Rural,HR Executive,51309,0 +106998,Male,22,Diploma,2,35,57,59,38,0.0,2,8,Rural,Data Analyst,74722,0 +106999,Male,52,Bachelors,13,17,66,73,88,3.0,2,35,Urban,Manager,32275,0 +107000,Male,45,Masters,17,64,8,64,32,3.0,6,69,Urban,Data Analyst,71656,0 +107001,Male,45,Bachelors,2,20,11,42,29,4.0,6,38,Semi-Urban,ML Engineer,80099,0 +107002,Male,32,Bachelors,5,84,37,52,96,0.0,6,9,Rural,Data Analyst,24919,0 +107003,Male,44,Masters,13,95,2,77,85,9.0,3,88,Semi-Urban,HR Executive,111774,1 +107004,Male,28,Diploma,18,11,15,75,96,0.0,7,12,Urban,HR Executive,85558,0 +107005,Male,26,Bachelors,4,48,18,23,83,7.0,2,94,Urban,Manager,57083,0 +107006,Female,28,Bachelors,19,68,3,67,56,7.0,3,70,Semi-Urban,Manager,20399,0 +107007,Male,35,Bachelors,18,61,89,81,64,5.0,3,42,Urban,HR Executive,130123,1 +107008,Male,48,Bachelors,6,49,40,98,6,2.0,5,76,Rural,Data Analyst,48641,1 +107009,Male,40,Diploma,2,28,80,76,99,7.0,4,88,Semi-Urban,Data Analyst,24529,1 +107010,Female,46,Masters,1,96,57,53,18,9.0,3,90,Urban,Software Engineer,57547,1 +107011,Female,27,Bachelors,6,15,85,45,39,9.0,1,51,Urban,Software Engineer,116174,0 +107012,Female,58,Diploma,10,31,96,22,44,5.0,6,64,Rural,HR Executive,92128,0 +107013,Male,22,High School,1,1,61,11,33,5.0,2,81,Urban,Software Engineer,106497,0 +107014,Female,41,High School,4,21,94,33,4,0.0,2,99,Urban,Manager,67839,1 +107015,Male,37,Bachelors,12,59,31,33,81,9.0,5,27,Urban,HR Executive,146744,0 +107016,Male,31,Bachelors,19,49,77,70,86,1.0,3,42,Urban,Data Analyst,104133,1 +107017,Female,30,High School,10,73,54,16,75,1.0,0,95,Semi-Urban,Manager,31608,0 +107018,Male,48,Diploma,19,70,75,82,56,0.0,4,34,Urban,Manager,118283,1 +107019,Male,26,Bachelors,6,24,6,33,77,6.0,1,69,Urban,Data Analyst,22266,0 +107020,Female,45,Bachelors,4,70,80,98,88,8.0,7,82,Urban,HR Executive,131360,1 +107021,Female,46,Bachelors,5,32,88,88,35,6.0,6,48,Rural,ML Engineer,98632,1 +107022,Male,31,Bachelors,14,3,46,57,27,0.0,3,55,Semi-Urban,ML Engineer,69338,0 +107023,Male,35,Bachelors,14,86,40,55,56,2.0,5,74,Semi-Urban,Data Analyst,40427,1 +107024,Male,35,High School,7,19,99,70,63,3.0,7,23,Urban,ML Engineer,122101,0 +107025,Female,50,Masters,5,15,95,88,19,2.0,5,55,Semi-Urban,Data Analyst,32230,1 +107026,Female,50,High School,3,74,94,41,67,5.0,3,93,Rural,Data Analyst,108142,1 +107027,Female,29,High School,14,51,83,71,99,3.0,4,1,Urban,ML Engineer,74670,0 +107028,Female,32,Bachelors,13,43,29,45,63,2.0,2,38,Urban,Data Analyst,45525,0 +107029,Female,35,High School,15,55,56,18,93,8.0,0,36,Semi-Urban,HR Executive,95461,0 +107030,Female,58,High School,19,29,26,7,62,8.0,6,21,Urban,ML Engineer,20172,0 +107031,Female,38,High School,15,33,34,3,92,2.0,3,5,Urban,Manager,112253,0 +107032,Female,54,Bachelors,0,21,99,50,56,2.0,7,21,Urban,HR Executive,47239,0 +107033,Male,47,Diploma,5,47,98,30,5,9.0,4,87,Urban,ML Engineer,45348,1 +107034,Male,26,Bachelors,15,89,82,61,74,2.0,3,52,Urban,ML Engineer,140079,1 +107035,Male,28,High School,1,96,24,76,90,2.0,4,59,Urban,ML Engineer,93915,1 +107036,Male,24,High School,9,12,42,43,25,1.0,2,96,Urban,Software Engineer,81232,0 +107037,Male,44,Diploma,14,29,49,2,44,1.0,7,90,Urban,Manager,110923,0 +107038,Female,37,Bachelors,14,66,77,35,58,8.0,1,21,Urban,Manager,94409,0 +107039,Other,55,Masters,11,25,82,11,73,5.0,4,85,Semi-Urban,HR Executive,36112,0 +107040,Male,31,Bachelors,9,88,85,58,11,1.0,2,72,Rural,Software Engineer,117546,1 +107041,Female,37,Bachelors,1,54,57,44,27,7.0,1,52,Urban,HR Executive,55209,0 +107042,Other,50,Diploma,0,36,32,60,53,2.0,0,70,Urban,Data Analyst,74160,0 +107043,Male,53,Diploma,14,73,30,11,2,6.0,5,93,Semi-Urban,Data Analyst,118484,0 +107044,Female,45,Diploma,1,57,56,45,42,5.0,4,34,Urban,ML Engineer,81743,0 +107045,Male,25,Diploma,5,15,48,65,39,5.0,4,94,Rural,HR Executive,107830,0 +107046,Male,27,Diploma,0,0,39,17,53,6.0,5,27,Rural,Software Engineer,117594,0 +107047,Female,29,Masters,16,40,7,8,36,1.0,0,84,Urban,ML Engineer,33704,0 +107048,Male,28,Bachelors,19,7,0,48,83,8.0,4,41,Rural,ML Engineer,89451,0 +107049,Male,46,Bachelors,15,30,62,68,10,9.0,0,40,Rural,Data Analyst,23049,0 +107050,Male,42,Bachelors,3,27,38,31,96,3.0,4,25,Urban,Data Analyst,44602,0 +107051,Female,53,High School,16,32,4,88,68,6.0,2,49,Semi-Urban,Software Engineer,95240,0 +107052,Male,44,Bachelors,7,15,16,99,89,7.0,3,27,Urban,Software Engineer,85905,0 +107053,Female,41,Masters,9,59,74,98,45,5.0,3,98,Urban,HR Executive,113155,1 +107054,Male,37,Bachelors,12,17,51,30,10,8.0,6,88,Semi-Urban,ML Engineer,20396,0 +107055,Male,38,Diploma,17,45,9,49,2,5.0,2,19,Urban,ML Engineer,91687,0 +107056,Male,59,High School,13,47,96,23,66,9.0,1,36,Rural,HR Executive,146017,0 +107057,Other,34,Bachelors,11,32,59,23,97,0.0,6,34,Semi-Urban,Manager,54854,0 +107058,Male,29,Bachelors,8,73,6,53,94,4.0,4,60,Urban,Manager,44972,0 +107059,Female,30,Diploma,4,66,27,17,83,2.0,7,44,Rural,Software Engineer,114620,0 +107060,Male,48,Masters,16,64,25,91,20,7.0,6,96,Rural,Software Engineer,101776,1 +107061,Male,44,Bachelors,11,66,4,78,51,9.0,2,56,Urban,HR Executive,32511,0 +107062,Male,55,Diploma,12,82,28,79,83,6.0,0,55,Urban,Software Engineer,58079,1 +107063,Male,29,Masters,19,46,10,33,53,7.0,2,41,Urban,Manager,60232,0 +107064,Other,51,Masters,4,17,1,33,23,5.0,4,65,Urban,Software Engineer,113275,0 +107065,Female,46,Bachelors,19,98,24,26,69,8.0,2,54,Urban,Software Engineer,49742,0 +107066,Male,32,Bachelors,7,20,48,62,50,5.0,0,0,Semi-Urban,HR Executive,35370,0 +107067,Male,33,Bachelors,13,48,64,77,6,0.0,0,49,Semi-Urban,Software Engineer,37178,1 +107068,Female,34,High School,16,21,46,66,63,0.0,6,79,Rural,ML Engineer,100286,0 +107069,Male,48,Masters,18,68,26,13,32,4.0,4,36,Rural,Software Engineer,44291,0 +107070,Female,45,PhD,1,9,72,68,72,4.0,6,71,Urban,Manager,139969,0 +107071,Male,45,Diploma,9,81,16,30,68,1.0,3,77,Semi-Urban,Manager,102368,0 +107072,Male,28,Masters,12,84,81,41,47,7.0,2,26,Semi-Urban,Data Analyst,113261,0 +107073,Female,53,Bachelors,2,51,49,43,26,3.0,5,11,Semi-Urban,Software Engineer,124857,0 +107074,Female,51,High School,5,59,93,95,77,8.0,7,6,Semi-Urban,HR Executive,89712,1 +107075,Female,35,Diploma,16,90,90,82,80,3.0,7,21,Urban,Software Engineer,147641,1 +107076,Male,53,Bachelors,11,7,4,45,19,6.0,5,87,Urban,Software Engineer,95908,0 +107077,Male,49,Masters,12,13,90,58,92,5.0,5,89,Rural,Manager,107893,1 +107078,Female,26,Bachelors,14,11,86,23,85,9.0,7,18,Urban,ML Engineer,105483,0 +107079,Male,28,PhD,8,6,4,73,86,1.0,1,8,Rural,ML Engineer,76445,0 +107080,Female,27,Bachelors,0,84,41,26,51,1.0,7,55,Urban,Data Analyst,92605,0 +107081,Male,45,Bachelors,12,79,63,45,71,6.0,0,81,Urban,Software Engineer,64318,1 +107082,Female,41,Masters,2,26,53,99,73,9.0,5,84,Urban,Manager,36421,1 +107083,Other,27,PhD,10,9,90,38,65,7.0,0,86,Urban,ML Engineer,38300,0 +107084,Other,38,Bachelors,12,44,27,93,33,7.0,0,98,Rural,HR Executive,67289,1 +107085,Male,28,Bachelors,2,54,83,0,87,8.0,2,11,Urban,ML Engineer,126786,0 +107086,Male,24,Bachelors,17,62,77,76,65,1.0,2,27,Urban,ML Engineer,59907,1 +107087,Male,28,High School,0,5,58,78,10,5.0,1,26,Semi-Urban,ML Engineer,83921,0 +107088,Male,43,Bachelors,6,57,91,19,81,4.0,7,23,Rural,ML Engineer,28991,0 +107089,Female,25,Diploma,0,81,20,81,69,3.0,4,86,Rural,Data Analyst,117658,1 +107090,Male,30,Diploma,15,54,78,28,41,1.0,3,33,Urban,Software Engineer,91574,0 +107091,Male,33,Bachelors,4,81,85,74,17,3.0,4,80,Semi-Urban,ML Engineer,49918,1 +107092,Male,54,Diploma,13,44,75,88,48,9.0,6,6,Urban,HR Executive,146509,0 +107093,Female,58,High School,12,63,94,41,46,7.0,3,30,Rural,Manager,98554,0 +107094,Female,38,Diploma,2,41,9,64,25,7.0,4,12,Semi-Urban,Manager,90114,0 +107095,Male,33,High School,10,26,68,45,40,0.0,0,17,Urban,HR Executive,141693,0 +107096,Female,34,Diploma,2,37,47,52,13,1.0,7,36,Urban,Manager,92456,0 +107097,Male,56,High School,0,77,66,79,67,9.0,2,0,Rural,HR Executive,55820,0 +107098,Male,23,High School,15,87,44,84,48,5.0,3,20,Semi-Urban,Manager,127776,1 +107099,Other,37,Masters,0,22,21,35,75,1.0,0,33,Urban,HR Executive,77864,0 +107100,Male,24,Diploma,18,29,92,89,17,0.0,4,81,Urban,ML Engineer,127250,1 +107101,Male,34,Bachelors,17,93,0,26,1,8.0,6,92,Urban,Manager,119767,0 +107102,Female,23,Bachelors,14,66,20,25,67,7.0,6,58,Urban,Manager,40682,0 +107103,Male,58,High School,13,84,19,68,88,9.0,7,97,Urban,Software Engineer,132227,1 +107104,Female,23,High School,17,15,30,14,53,8.0,1,36,Urban,ML Engineer,69913,0 +107105,Male,53,Diploma,2,67,54,4,58,0.0,3,85,Rural,Data Analyst,84048,0 +107106,Male,30,Bachelors,8,68,29,75,69,6.0,7,59,Urban,Manager,45637,0 +107107,Male,29,Diploma,17,17,76,33,38,6.0,3,10,Urban,Software Engineer,58177,0 +107108,Male,58,Bachelors,5,27,64,36,15,7.0,5,81,Semi-Urban,Manager,23104,0 +107109,Male,59,Diploma,7,21,12,45,98,0.0,3,77,Rural,ML Engineer,38809,0 +107110,Male,25,Bachelors,13,4,97,4,87,6.0,3,81,Urban,Manager,76061,0 +107111,Female,21,Masters,2,11,70,88,20,6.0,0,91,Rural,ML Engineer,120057,1 +107112,Female,27,High School,6,35,6,23,72,2.0,4,55,Semi-Urban,ML Engineer,31567,0 +107113,Male,25,Diploma,4,31,48,1,63,8.0,0,4,Semi-Urban,Software Engineer,82404,0 +107114,Male,50,Bachelors,0,4,34,94,57,6.0,6,5,Semi-Urban,HR Executive,33178,0 +107115,Male,21,Bachelors,10,59,84,9,42,7.0,6,40,Urban,ML Engineer,124943,0 +107116,Male,53,Masters,3,65,41,47,84,9.0,1,3,Urban,ML Engineer,82682,0 +107117,Male,43,Diploma,16,44,29,30,5,0.0,6,75,Urban,Data Analyst,118757,0 +107118,Male,46,Masters,4,32,91,59,22,7.0,4,67,Rural,Software Engineer,117197,1 +107119,Male,43,Bachelors,1,81,9,74,74,9.0,3,48,Rural,ML Engineer,94176,0 +107120,Male,35,Masters,18,88,85,72,45,1.0,2,2,Urban,ML Engineer,144636,1 +107121,Female,26,High School,15,88,7,38,3,0.0,3,50,Rural,ML Engineer,105601,0 +107122,Male,29,Masters,4,13,43,7,93,0.0,6,59,Urban,Manager,123174,0 +107123,Female,44,Diploma,17,77,73,53,32,2.0,6,31,Rural,HR Executive,54582,0 +107124,Male,33,Bachelors,11,62,5,1,68,1.0,1,41,Rural,Manager,51208,0 +107125,Female,28,Diploma,10,47,52,8,11,8.0,7,74,Urban,HR Executive,62147,0 +107126,Male,40,Masters,11,35,85,21,81,1.0,1,61,Rural,ML Engineer,52321,0 +107127,Male,53,Bachelors,6,12,76,21,64,5.0,4,1,Rural,Manager,144941,0 +107128,Female,52,Masters,7,76,13,87,56,9.0,1,73,Urban,HR Executive,68796,1 +107129,Male,46,Bachelors,2,41,84,31,17,8.0,2,46,Semi-Urban,HR Executive,148343,0 +107130,Male,22,Diploma,2,82,60,95,16,3.0,6,85,Semi-Urban,HR Executive,27571,1 +107131,Female,26,Diploma,17,57,51,25,97,6.0,6,96,Urban,Manager,32326,0 +107132,Male,58,Bachelors,3,72,74,98,11,1.0,7,9,Rural,Manager,72029,1 +107133,Male,37,Masters,0,78,15,25,33,9.0,1,58,Semi-Urban,Software Engineer,31130,0 +107134,Female,42,Masters,17,76,71,72,17,6.0,4,82,Urban,Software Engineer,138840,1 +107135,Other,48,High School,11,11,0,26,58,0.0,1,59,Urban,Software Engineer,131462,0 +107136,Male,22,Masters,7,36,35,62,79,7.0,5,53,Urban,Software Engineer,36403,0 +107137,Female,36,Masters,6,33,83,68,89,0.0,6,42,Urban,Software Engineer,58060,0 +107138,Male,44,Masters,19,69,56,70,84,6.0,0,15,Semi-Urban,Software Engineer,87238,0 +107139,Male,45,Bachelors,14,94,10,86,64,3.0,5,97,Urban,Data Analyst,41980,1 +107140,Male,56,Diploma,11,45,96,56,32,6.0,7,18,Urban,Manager,20928,0 +107141,Male,46,High School,9,75,3,91,30,2.0,6,84,Urban,Software Engineer,63155,1 +107142,Male,24,High School,18,84,16,93,85,5.0,1,43,Urban,HR Executive,127686,1 +107143,Male,33,PhD,19,31,99,98,29,7.0,1,1,Semi-Urban,ML Engineer,70025,0 +107144,Male,26,Bachelors,13,90,74,77,19,0.0,2,15,Semi-Urban,HR Executive,102146,1 +107145,Female,58,Bachelors,5,70,61,81,88,4.0,5,22,Urban,ML Engineer,29905,0 +107146,Male,55,Bachelors,8,4,74,46,69,1.0,0,34,Urban,ML Engineer,46411,0 +107147,Female,50,Bachelors,12,0,58,71,35,6.0,7,60,Rural,HR Executive,144054,0 +107148,Male,35,Bachelors,10,6,28,71,99,3.0,5,3,Urban,Manager,115350,0 +107149,Male,39,Bachelors,9,99,1,81,65,0.0,7,84,Urban,ML Engineer,125027,1 +107150,Male,41,Masters,10,4,96,8,54,7.0,3,93,Urban,Data Analyst,143039,0 +107151,Female,54,PhD,13,44,61,90,78,5.0,4,21,Urban,Manager,110182,0 +107152,Male,32,Bachelors,6,15,39,91,73,4.0,6,54,Rural,ML Engineer,144698,0 +107153,Male,49,Masters,14,99,8,63,96,0.0,5,60,Urban,ML Engineer,129295,0 +107154,Female,23,Masters,4,20,24,75,24,2.0,5,5,Urban,Data Analyst,52489,0 +107155,Male,39,Bachelors,13,38,11,11,71,1.0,4,44,Rural,Data Analyst,31705,0 +107156,Male,50,Bachelors,10,84,82,94,63,8.0,0,82,Rural,HR Executive,56206,1 +107157,Female,33,Bachelors,7,46,17,45,14,4.0,6,56,Urban,Data Analyst,95202,0 +107158,Male,43,Masters,12,6,7,27,80,1.0,5,24,Urban,HR Executive,141837,0 +107159,Male,36,Diploma,12,20,24,70,2,5.0,5,62,Semi-Urban,Data Analyst,78111,0 +107160,Female,43,Bachelors,2,86,82,28,63,4.0,5,41,Semi-Urban,Data Analyst,56301,0 +107161,Male,29,Diploma,12,98,59,34,61,8.0,6,93,Urban,HR Executive,114296,1 +107162,Female,44,Bachelors,1,3,70,99,81,8.0,3,64,Semi-Urban,Data Analyst,66662,0 +107163,Male,46,Bachelors,7,17,94,41,97,8.0,2,40,Urban,ML Engineer,27142,0 +107164,Male,48,Masters,15,58,99,31,98,5.0,5,60,Semi-Urban,Data Analyst,58354,1 +107165,Female,23,Bachelors,11,45,15,32,68,8.0,2,29,Urban,Data Analyst,137203,0 +107166,Male,49,Masters,1,33,34,65,5,1.0,2,18,Urban,Software Engineer,143173,0 +107167,Female,24,PhD,8,16,8,64,44,1.0,6,80,Semi-Urban,Manager,74580,0 +107168,Female,53,Diploma,5,88,34,37,36,6.0,5,9,Semi-Urban,Software Engineer,85693,0 +107169,Female,56,High School,18,6,64,1,25,7.0,1,85,Semi-Urban,Manager,62291,0 +107170,Male,30,Bachelors,18,28,80,40,77,1.0,2,68,Urban,Data Analyst,102662,0 +107171,Male,26,Masters,5,92,57,14,11,6.0,1,40,Semi-Urban,HR Executive,75258,0 +107172,Male,50,Bachelors,12,42,68,58,11,1.0,2,37,Urban,Software Engineer,79000,0 +107173,Male,23,Masters,10,49,22,79,85,8.0,6,71,Semi-Urban,HR Executive,78154,0 +107174,Female,38,Bachelors,9,29,28,57,0,9.0,0,27,Rural,HR Executive,120964,0 +107175,Male,43,Masters,18,0,36,98,78,7.0,1,31,Urban,Software Engineer,94690,0 +107176,Male,33,High School,3,48,11,41,2,3.0,5,59,Semi-Urban,Data Analyst,76358,0 +107177,Female,52,Diploma,18,50,21,79,29,1.0,7,22,Semi-Urban,Manager,121327,0 +107178,Male,27,Bachelors,1,55,26,21,53,0.0,4,78,Rural,ML Engineer,86556,0 +107179,Male,27,Bachelors,4,25,41,5,80,0.0,6,78,Urban,Manager,58289,0 +107180,Female,26,Masters,13,44,66,65,93,4.0,6,20,Semi-Urban,Data Analyst,102925,0 +107181,Male,22,Bachelors,12,73,23,61,41,1.0,6,77,Urban,ML Engineer,108545,0 +107182,Female,47,Bachelors,0,64,17,71,3,2.0,6,61,Urban,Software Engineer,99390,0 +107183,Male,55,Bachelors,16,71,15,42,57,8.0,7,80,Urban,HR Executive,45489,0 +107184,Other,21,High School,0,90,6,4,58,3.0,3,35,Semi-Urban,ML Engineer,77145,0 +107185,Male,49,Bachelors,3,81,30,30,40,5.0,0,44,Semi-Urban,Data Analyst,53233,0 +107186,Female,37,Diploma,2,21,89,91,11,4.0,1,91,Urban,Software Engineer,89099,1 +107187,Male,57,Masters,13,84,71,5,26,0.0,1,91,Semi-Urban,HR Executive,146438,1 +107188,Female,45,Masters,9,98,71,78,8,6.0,6,83,Semi-Urban,Data Analyst,28821,1 +107189,Male,39,High School,12,74,56,56,44,6.0,0,83,Semi-Urban,ML Engineer,49757,1 +107190,Male,58,Bachelors,15,38,63,13,42,4.0,6,27,Urban,Software Engineer,114450,0 +107191,Male,59,Masters,9,29,1,38,34,8.0,0,22,Urban,Software Engineer,113392,0 +107192,Female,28,Bachelors,13,1,3,45,13,3.0,5,36,Rural,Software Engineer,133137,0 +107193,Male,51,Bachelors,19,35,16,49,40,1.0,7,7,Semi-Urban,ML Engineer,113848,0 +107194,Female,42,High School,1,79,77,72,10,2.0,2,99,Urban,Data Analyst,145077,1 +107195,Female,24,Bachelors,16,87,7,94,69,2.0,5,47,Rural,HR Executive,97334,0 +107196,Male,33,Diploma,0,12,89,6,45,1.0,0,65,Urban,ML Engineer,115512,0 +107197,Male,42,Diploma,9,92,41,47,59,2.0,6,21,Urban,Data Analyst,149133,0 +107198,Female,47,Diploma,6,50,9,82,66,8.0,4,35,Urban,Manager,99830,0 +107199,Female,53,Bachelors,19,20,34,0,11,5.0,5,48,Urban,Software Engineer,126940,0 +107200,Female,40,Bachelors,7,79,82,34,58,1.0,5,1,Semi-Urban,HR Executive,104654,0 +107201,Male,26,Bachelors,8,76,34,74,61,5.0,6,78,Urban,Manager,25423,1 +107202,Female,28,High School,5,60,90,58,3,9.0,1,35,Rural,Manager,89268,1 +107203,Male,28,High School,15,50,94,83,5,8.0,2,85,Rural,Software Engineer,94733,1 +107204,Female,41,Bachelors,14,36,13,8,59,7.0,0,10,Semi-Urban,Manager,117979,0 +107205,Female,36,Masters,5,98,48,17,99,7.0,3,76,Rural,HR Executive,80041,0 +107206,Male,32,Bachelors,11,93,23,74,19,4.0,6,69,Urban,HR Executive,112633,1 +107207,Male,40,Bachelors,7,63,58,97,97,9.0,2,73,Urban,ML Engineer,43831,1 +107208,Male,56,Diploma,14,63,69,54,87,6.0,5,95,Rural,ML Engineer,90111,1 +107209,Male,50,Masters,12,91,12,90,8,4.0,0,32,Urban,Manager,48917,0 +107210,Male,37,Bachelors,9,8,30,38,20,0.0,3,2,Urban,Data Analyst,112651,0 +107211,Male,23,Bachelors,3,7,44,67,40,3.0,3,2,Urban,ML Engineer,76585,0 +107212,Female,51,Bachelors,19,93,42,51,91,1.0,4,40,Semi-Urban,Data Analyst,132395,0 +107213,Male,51,Masters,11,38,94,39,80,5.0,7,97,Semi-Urban,Software Engineer,67048,1 +107214,Male,59,Bachelors,13,57,12,93,21,6.0,4,93,Urban,Manager,48793,1 +107215,Male,35,Bachelors,11,10,72,62,82,2.0,2,88,Urban,HR Executive,132330,0 +107216,Male,30,Masters,14,31,59,46,48,0.0,3,96,Urban,Manager,31884,0 +107217,Male,59,Masters,10,31,61,6,45,9.0,2,76,Urban,Manager,65309,0 +107218,Male,32,Masters,9,90,50,35,95,7.0,6,21,Rural,Manager,52411,0 +107219,Male,44,Bachelors,14,18,65,42,42,2.0,1,69,Urban,Data Analyst,38581,0 +107220,Male,25,Masters,18,10,26,20,17,1.0,5,10,Semi-Urban,Manager,101549,0 +107221,Male,55,Bachelors,9,31,52,34,86,3.0,7,99,Rural,HR Executive,34656,0 +107222,Male,26,Masters,9,59,51,45,10,7.0,6,35,Semi-Urban,ML Engineer,68335,0 +107223,Male,25,Masters,16,85,85,95,16,1.0,6,65,Urban,ML Engineer,141851,1 +107224,Female,25,PhD,11,57,33,82,2,5.0,4,25,Urban,Data Analyst,92030,0 +107225,Male,38,High School,10,93,44,83,44,2.0,4,96,Urban,Data Analyst,64583,1 +107226,Female,22,Bachelors,15,8,43,74,7,5.0,1,9,Urban,HR Executive,88060,0 +107227,Male,44,PhD,2,51,23,55,50,7.0,7,69,Urban,ML Engineer,106394,0 +107228,Male,23,Masters,13,82,22,39,17,0.0,0,42,Urban,HR Executive,101598,0 +107229,Male,28,Masters,17,93,79,69,96,8.0,7,92,Urban,Manager,89532,1 +107230,Male,31,High School,13,14,52,54,1,3.0,7,89,Rural,Data Analyst,132769,0 +107231,Female,42,High School,13,33,86,29,32,7.0,7,58,Urban,Data Analyst,46495,0 +107232,Male,22,High School,14,32,93,11,6,9.0,3,17,Urban,HR Executive,27257,0 +107233,Male,37,Masters,4,18,57,45,2,6.0,5,68,Urban,Data Analyst,62547,0 +107234,Male,55,Bachelors,9,79,82,76,42,5.0,0,13,Urban,HR Executive,26861,1 +107235,Male,57,Masters,15,92,17,95,83,3.0,5,41,Urban,ML Engineer,62359,1 +107236,Male,24,Bachelors,7,70,41,24,85,4.0,4,62,Semi-Urban,HR Executive,20292,0 +107237,Female,57,Masters,13,83,79,34,88,8.0,4,20,Urban,ML Engineer,110074,0 +107238,Female,22,Masters,15,78,58,51,27,6.0,3,52,Rural,Manager,144090,0 +107239,Male,23,High School,7,88,79,48,88,3.0,0,9,Urban,ML Engineer,104616,0 +107240,Female,33,High School,13,99,13,68,99,9.0,5,50,Rural,ML Engineer,25418,0 +107241,Other,56,Bachelors,9,34,27,49,47,8.0,0,96,Urban,Data Analyst,119949,0 +107242,Male,37,PhD,14,38,97,93,42,8.0,1,5,Urban,ML Engineer,38856,0 +107243,Male,57,Diploma,13,7,96,38,48,9.0,3,48,Urban,ML Engineer,47031,0 +107244,Female,22,Bachelors,0,54,75,66,31,2.0,4,27,Urban,Data Analyst,100186,0 +107245,Male,55,High School,5,51,55,96,16,3.0,2,96,Urban,Software Engineer,88975,1 +107246,Male,44,Bachelors,8,51,25,75,18,9.0,0,41,Semi-Urban,Data Analyst,111042,0 +107247,Male,35,Masters,2,66,90,63,29,9.0,2,8,Urban,Manager,24353,0 +107248,Female,38,Bachelors,18,56,24,12,39,4.0,2,14,Urban,ML Engineer,126508,0 +107249,Male,39,Diploma,11,61,95,52,93,4.0,7,84,Rural,Software Engineer,43005,1 +107250,Male,53,Bachelors,11,18,58,12,76,0.0,0,39,Urban,HR Executive,48393,0 +107251,Female,59,High School,1,3,48,84,98,0.0,5,36,Urban,HR Executive,47359,0 +107252,Male,57,Bachelors,15,36,62,55,66,7.0,3,87,Urban,Data Analyst,31204,1 +107253,Other,58,PhD,11,12,44,65,26,3.0,5,15,Urban,Data Analyst,121029,0 +107254,Female,38,Masters,1,47,54,72,52,7.0,6,96,Rural,ML Engineer,64633,1 +107255,Female,23,High School,12,58,57,22,67,3.0,4,84,Rural,ML Engineer,21192,0 +107256,Male,21,Bachelors,15,51,5,24,7,0.0,3,7,Rural,Data Analyst,112798,0 +107257,Other,31,Diploma,18,85,65,96,77,3.0,1,85,Urban,Software Engineer,125865,1 +107258,Male,47,Diploma,19,26,94,48,97,7.0,4,14,Urban,ML Engineer,91388,0 +107259,Male,43,Bachelors,9,51,16,3,77,5.0,1,32,Rural,ML Engineer,95496,0 +107260,Female,21,PhD,12,38,39,37,82,4.0,5,62,Urban,HR Executive,37361,0 +107261,Male,34,Masters,10,38,86,58,26,5.0,7,24,Rural,Manager,131399,0 +107262,Male,52,Bachelors,12,16,65,61,98,2.0,5,16,Semi-Urban,HR Executive,122577,0 +107263,Male,58,Diploma,10,30,57,29,85,0.0,1,0,Urban,Software Engineer,23018,0 +107264,Female,21,PhD,13,60,14,76,66,6.0,4,50,Urban,ML Engineer,50900,0 +107265,Male,35,Bachelors,0,94,64,36,3,0.0,2,72,Urban,Data Analyst,79086,1 +107266,Female,38,PhD,11,82,6,63,94,4.0,5,97,Urban,HR Executive,99718,1 +107267,Male,39,Masters,17,40,46,11,20,9.0,7,30,Urban,Manager,77275,0 +107268,Male,47,High School,8,59,94,81,23,7.0,7,65,Rural,Manager,37639,1 +107269,Male,50,High School,1,14,81,95,46,4.0,4,40,Rural,Software Engineer,146717,0 +107270,Male,50,Bachelors,13,96,63,49,82,0.0,3,9,Urban,Data Analyst,21577,0 +107271,Male,57,Bachelors,6,91,38,71,11,6.0,4,72,Rural,HR Executive,49514,1 +107272,Male,36,PhD,9,5,95,45,63,7.0,7,11,Urban,Data Analyst,127085,0 +107273,Male,53,Bachelors,13,48,56,1,53,7.0,0,4,Urban,Software Engineer,84463,0 +107274,Female,32,Bachelors,18,69,96,72,22,4.0,7,73,Urban,Manager,127702,1 +107275,Female,52,Masters,12,41,76,75,3,2.0,3,68,Urban,Software Engineer,42500,1 +107276,Male,27,Masters,5,73,58,43,27,3.0,5,83,Semi-Urban,Manager,90055,1 +107277,Female,55,Masters,13,13,93,86,42,4.0,4,96,Urban,Data Analyst,139465,1 +107278,Male,52,Bachelors,7,97,25,30,55,8.0,6,17,Semi-Urban,HR Executive,126724,0 +107279,Female,32,Bachelors,2,69,63,17,93,6.0,2,4,Rural,HR Executive,73366,0 +107280,Male,48,Diploma,1,87,28,16,54,6.0,6,93,Semi-Urban,Manager,115366,0 +107281,Male,50,High School,11,56,22,96,77,1.0,1,64,Semi-Urban,Data Analyst,91044,1 +107282,Other,32,Bachelors,5,50,76,44,19,6.0,0,6,Urban,Software Engineer,78778,0 +107283,Male,41,Bachelors,9,72,27,72,54,6.0,5,8,Urban,Manager,38470,0 +107284,Female,41,Bachelors,9,67,46,39,86,6.0,2,33,Urban,ML Engineer,100549,0 +107285,Female,44,Bachelors,12,48,79,35,30,7.0,5,48,Rural,Software Engineer,65643,0 +107286,Male,30,Bachelors,3,56,79,25,60,8.0,2,56,Urban,Software Engineer,46058,0 +107287,Male,32,Bachelors,14,81,88,93,75,3.0,4,14,Urban,ML Engineer,46973,1 +107288,Male,48,PhD,5,36,37,58,36,0.0,7,7,Urban,Software Engineer,62773,0 +107289,Male,38,Bachelors,7,45,14,85,41,3.0,5,92,Semi-Urban,ML Engineer,101814,1 +107290,Male,39,Diploma,17,3,6,73,10,0.0,0,16,Urban,Manager,102579,0 +107291,Female,37,High School,12,23,43,26,64,0.0,4,65,Semi-Urban,Software Engineer,118350,0 +107292,Male,55,Diploma,12,80,76,70,14,8.0,3,83,Urban,ML Engineer,119203,1 +107293,Other,54,Diploma,12,53,75,18,82,8.0,2,26,Urban,ML Engineer,136656,0 +107294,Male,43,Bachelors,8,33,31,81,90,4.0,3,94,Urban,HR Executive,57780,1 +107295,Male,49,Masters,14,3,25,9,78,4.0,5,0,Semi-Urban,Data Analyst,129703,0 +107296,Other,31,Bachelors,10,35,74,32,72,8.0,2,81,Rural,Manager,134579,0 +107297,Female,26,High School,8,24,75,72,23,1.0,2,70,Urban,HR Executive,112308,1 +107298,Male,22,High School,13,91,86,64,39,1.0,4,88,Urban,Manager,81665,1 +107299,Male,54,Bachelors,19,90,31,22,39,9.0,0,24,Urban,Software Engineer,113735,0 +107300,Male,46,Bachelors,6,82,70,42,33,4.0,5,65,Urban,HR Executive,106985,1 +107301,Male,39,Bachelors,15,46,40,40,66,8.0,1,84,Urban,Software Engineer,141744,0 +107302,Male,57,High School,1,66,19,66,0,9.0,1,12,Urban,ML Engineer,125893,0 +107303,Male,41,High School,4,5,7,19,64,8.0,3,72,Urban,Data Analyst,74041,0 +107304,Female,45,Bachelors,8,54,85,10,77,2.0,3,77,Urban,Data Analyst,86396,0 +107305,Male,31,Bachelors,7,71,17,88,34,1.0,6,66,Semi-Urban,HR Executive,112681,1 +107306,Female,25,Bachelors,16,79,65,18,93,6.0,5,31,Semi-Urban,ML Engineer,62006,0 +107307,Male,58,Masters,11,1,26,56,61,4.0,2,62,Semi-Urban,ML Engineer,129868,0 +107308,Female,49,Diploma,14,56,71,3,52,1.0,5,99,Urban,ML Engineer,112460,0 +107309,Female,26,Masters,8,43,47,47,47,8.0,0,97,Urban,Manager,33062,0 +107310,Female,25,PhD,3,27,83,78,16,9.0,2,97,Rural,Data Analyst,129720,1 +107311,Other,47,High School,8,37,13,67,8,9.0,6,57,Semi-Urban,ML Engineer,33130,0 +107312,Female,37,PhD,18,17,69,85,91,6.0,7,58,Semi-Urban,HR Executive,100112,0 +107313,Female,41,Bachelors,2,74,4,77,90,6.0,0,50,Urban,Manager,74079,0 +107314,Female,46,Bachelors,1,89,96,56,0,0.0,3,50,Urban,Manager,135308,1 +107315,Female,41,Bachelors,17,42,65,90,41,0.0,5,23,Urban,Manager,80741,0 +107316,Male,24,Diploma,15,93,68,26,80,3.0,6,75,Urban,HR Executive,125014,1 +107317,Female,59,Diploma,6,48,30,43,85,8.0,4,12,Urban,Manager,55091,0 +107318,Male,56,PhD,8,61,30,42,18,0.0,3,41,Semi-Urban,HR Executive,125802,0 +107319,Female,44,Bachelors,14,13,33,56,23,5.0,6,28,Urban,Manager,52498,0 +107320,Female,43,Bachelors,16,2,70,48,28,4.0,2,4,Rural,HR Executive,80716,0 +107321,Male,46,Diploma,17,88,22,15,68,0.0,2,55,Semi-Urban,Manager,36138,0 +107322,Male,51,Masters,15,22,72,62,10,2.0,7,67,Urban,Manager,101336,0 +107323,Female,41,Bachelors,19,91,69,2,29,0.0,4,1,Urban,ML Engineer,36925,0 +107324,Male,56,Diploma,16,83,89,7,75,0.0,3,1,Urban,HR Executive,121583,0 +107325,Male,23,Masters,10,69,81,44,10,3.0,3,25,Urban,ML Engineer,145827,0 +107326,Female,28,Masters,15,60,98,11,75,1.0,2,39,Urban,Data Analyst,86492,0 +107327,Male,47,Bachelors,10,51,75,71,35,9.0,3,12,Urban,Manager,54615,0 +107328,Female,50,PhD,3,12,79,40,86,9.0,3,89,Urban,Data Analyst,113978,0 +107329,Male,33,Diploma,12,16,55,81,65,8.0,4,88,Urban,Manager,33163,1 +107330,Male,43,Bachelors,7,48,23,91,80,5.0,4,6,Urban,HR Executive,89103,0 +107331,Female,43,Bachelors,2,78,0,63,13,1.0,5,15,Urban,Data Analyst,26494,0 +107332,Female,36,Bachelors,2,1,91,55,16,1.0,6,90,Urban,ML Engineer,80698,0 +107333,Male,32,PhD,15,0,58,69,67,8.0,6,46,Urban,Manager,106848,0 +107334,Male,47,Bachelors,17,91,95,4,29,0.0,0,95,Urban,ML Engineer,81946,1 +107335,Male,31,Bachelors,7,23,84,43,8,9.0,3,6,Urban,Software Engineer,112717,0 +107336,Male,46,Bachelors,11,16,28,24,50,3.0,4,61,Urban,Data Analyst,95611,0 +107337,Female,24,Diploma,0,56,32,15,49,5.0,5,95,Urban,Manager,85072,0 +107338,Male,48,High School,0,15,32,14,1,8.0,5,2,Urban,ML Engineer,102958,0 +107339,Male,35,Bachelors,5,67,44,16,97,3.0,2,65,Urban,Data Analyst,144333,0 +107340,Female,26,High School,15,61,43,73,52,9.0,3,31,Urban,Manager,131953,0 +107341,Male,52,Bachelors,5,50,21,17,62,6.0,3,80,Urban,Data Analyst,78411,0 +107342,Male,41,Bachelors,16,13,65,3,97,1.0,7,13,Urban,Data Analyst,37366,0 +107343,Male,25,Bachelors,3,20,89,82,88,9.0,4,47,Semi-Urban,HR Executive,33697,1 +107344,Female,48,Masters,7,11,74,2,25,4.0,0,9,Urban,Software Engineer,52718,0 +107345,Female,55,Masters,0,45,45,66,9,5.0,6,75,Semi-Urban,HR Executive,127668,0 +107346,Male,21,Bachelors,5,16,95,41,18,3.0,5,73,Semi-Urban,Data Analyst,109632,0 +107347,Male,58,Diploma,17,12,10,40,95,8.0,0,22,Urban,ML Engineer,144166,0 +107348,Male,21,Diploma,1,84,86,86,19,4.0,6,16,Semi-Urban,Software Engineer,27887,1 +107349,Male,28,Bachelors,2,3,78,32,15,3.0,0,24,Urban,Data Analyst,21902,0 +107350,Male,58,Bachelors,2,91,90,71,26,9.0,3,8,Rural,HR Executive,130747,1 +107351,Male,53,High School,18,66,24,39,73,6.0,4,12,Urban,ML Engineer,39829,0 +107352,Female,38,Bachelors,0,94,86,35,35,7.0,5,77,Urban,Software Engineer,143571,1 +107353,Male,40,Masters,12,73,10,38,99,2.0,4,1,Urban,ML Engineer,148674,0 +107354,Female,42,PhD,17,46,16,54,44,9.0,1,97,Semi-Urban,Data Analyst,111333,0 +107355,Female,43,Masters,18,42,7,68,96,7.0,7,84,Rural,Software Engineer,49627,0 +107356,Female,27,Masters,8,93,13,83,96,0.0,7,24,Urban,ML Engineer,143685,0 +107357,Other,40,Diploma,19,36,55,40,1,6.0,3,59,Rural,HR Executive,85915,0 +107358,Male,25,Bachelors,14,40,94,57,13,3.0,2,20,Rural,HR Executive,57403,0 +107359,Male,52,Bachelors,10,32,27,99,39,0.0,5,75,Urban,Software Engineer,78365,0 +107360,Male,51,High School,11,90,79,6,29,9.0,7,7,Rural,ML Engineer,20282,0 +107361,Other,38,Masters,16,21,30,69,82,1.0,3,42,Rural,Data Analyst,23861,0 +107362,Male,40,Bachelors,17,68,93,97,82,5.0,6,66,Urban,Software Engineer,129453,1 +107363,Male,21,PhD,6,86,68,13,56,5.0,6,4,Urban,Software Engineer,79900,0 +107364,Male,50,Bachelors,2,23,56,58,8,3.0,0,27,Semi-Urban,Data Analyst,74268,0 +107365,Female,31,Bachelors,10,20,87,35,61,5.0,0,13,Urban,Manager,44808,0 +107366,Male,26,Masters,2,96,46,59,24,4.0,2,93,Semi-Urban,Software Engineer,125931,1 +107367,Other,39,Bachelors,8,13,46,54,74,7.0,3,80,Urban,Manager,56189,0 +107368,Female,30,Bachelors,18,90,63,32,8,4.0,0,76,Semi-Urban,Data Analyst,98307,1 +107369,Female,27,Masters,9,40,80,68,77,4.0,2,93,Semi-Urban,Data Analyst,78558,1 +107370,Male,58,Masters,7,2,83,33,1,0.0,5,84,Semi-Urban,ML Engineer,100471,0 +107371,Female,42,Bachelors,8,36,2,69,79,6.0,2,49,Urban,Data Analyst,100411,0 +107372,Male,54,Bachelors,17,97,20,55,92,8.0,1,8,Rural,Data Analyst,37949,0 +107373,Female,36,Bachelors,9,37,78,41,42,8.0,3,64,Rural,Data Analyst,45080,0 +107374,Female,37,Bachelors,16,94,51,70,26,7.0,5,10,Urban,HR Executive,106551,0 +107375,Female,52,High School,13,67,55,26,31,3.0,2,86,Urban,Software Engineer,135760,0 +107376,Male,21,Bachelors,5,15,38,14,36,0.0,1,40,Semi-Urban,HR Executive,97380,0 +107377,Male,21,Masters,8,47,55,17,45,8.0,7,83,Urban,HR Executive,41159,0 +107378,Female,49,Bachelors,0,44,2,75,36,8.0,4,43,Urban,Manager,40332,0 +107379,Female,51,Masters,6,51,51,97,2,3.0,7,17,Urban,HR Executive,119379,0 +107380,Female,48,Masters,8,99,49,1,28,2.0,5,13,Urban,ML Engineer,113949,0 +107381,Male,40,Diploma,1,40,37,70,51,8.0,6,22,Urban,HR Executive,134868,0 +107382,Female,57,Masters,13,34,84,58,63,9.0,7,43,Rural,ML Engineer,33633,0 +107383,Male,43,Bachelors,15,0,7,87,73,3.0,6,20,Semi-Urban,HR Executive,41938,0 +107384,Female,55,Bachelors,6,51,37,77,55,2.0,6,64,Rural,Manager,90075,0 +107385,Male,21,Bachelors,11,62,1,82,29,0.0,0,69,Urban,Software Engineer,83695,0 +107386,Female,58,High School,9,82,99,17,82,7.0,3,96,Urban,Software Engineer,50745,1 +107387,Male,45,High School,3,32,81,19,98,3.0,5,85,Rural,HR Executive,133914,0 +107388,Male,41,Bachelors,16,66,15,24,6,7.0,2,96,Urban,ML Engineer,26957,0 +107389,Male,33,Diploma,3,84,55,72,2,3.0,5,37,Urban,Data Analyst,61744,1 +107390,Male,56,Bachelors,14,69,40,75,45,9.0,5,4,Urban,Data Analyst,62706,0 +107391,Male,29,High School,1,95,27,55,92,4.0,0,71,Urban,Software Engineer,88566,1 +107392,Male,32,Masters,4,50,2,89,74,7.0,7,70,Urban,ML Engineer,27985,0 +107393,Female,33,Bachelors,15,20,18,68,1,4.0,7,36,Rural,Data Analyst,87894,0 +107394,Male,55,Bachelors,7,49,43,84,75,0.0,3,38,Urban,HR Executive,80102,0 +107395,Female,29,Bachelors,14,30,77,26,33,3.0,3,36,Urban,ML Engineer,55476,0 +107396,Male,54,Diploma,10,69,84,81,46,4.0,2,52,Semi-Urban,ML Engineer,123904,1 +107397,Male,23,Bachelors,16,20,64,45,8,9.0,2,73,Urban,ML Engineer,79768,0 +107398,Female,57,Diploma,11,69,83,17,59,2.0,7,47,Urban,HR Executive,83464,0 +107399,Female,58,High School,19,59,73,33,26,6.0,5,23,Semi-Urban,Manager,32238,0 +107400,Male,45,Diploma,1,26,71,12,35,1.0,5,65,Urban,ML Engineer,27681,0 +107401,Male,45,Bachelors,2,26,16,97,90,2.0,7,10,Rural,HR Executive,144648,0 +107402,Male,37,Masters,0,2,70,16,87,7.0,0,32,Rural,HR Executive,96736,0 +107403,Male,21,Bachelors,6,44,89,81,22,0.0,2,64,Urban,Software Engineer,70031,1 +107404,Male,23,Bachelors,10,38,25,48,16,7.0,5,30,Urban,ML Engineer,126048,0 +107405,Male,23,Diploma,9,88,46,32,9,3.0,4,58,Urban,Manager,96826,0 +107406,Male,36,High School,10,54,21,1,18,9.0,5,20,Urban,HR Executive,43088,0 +107407,Female,46,Diploma,4,28,46,67,94,0.0,6,91,Semi-Urban,Software Engineer,58514,0 +107408,Female,34,High School,3,82,99,36,69,6.0,2,40,Semi-Urban,Data Analyst,134548,1 +107409,Female,26,Bachelors,18,12,39,32,28,2.0,1,62,Urban,Manager,61415,0 +107410,Female,44,High School,8,44,89,38,91,0.0,5,2,Rural,ML Engineer,133165,0 +107411,Female,48,High School,18,64,8,78,50,9.0,4,2,Urban,Data Analyst,98539,0 +107412,Female,38,Diploma,18,56,10,13,39,0.0,2,25,Urban,Software Engineer,126619,0 +107413,Female,59,Masters,0,94,1,22,69,7.0,3,98,Semi-Urban,Data Analyst,50519,0 +107414,Female,57,Masters,1,45,41,10,61,4.0,2,15,Semi-Urban,ML Engineer,99899,0 +107415,Female,35,Bachelors,6,8,41,5,26,4.0,4,99,Rural,ML Engineer,97263,0 +107416,Male,49,High School,9,51,58,30,92,1.0,0,94,Urban,HR Executive,139705,0 +107417,Male,26,Masters,19,78,62,69,43,9.0,0,99,Rural,Manager,72573,1 +107418,Male,44,Masters,18,52,66,15,60,3.0,4,87,Semi-Urban,Data Analyst,55268,0 +107419,Female,28,Bachelors,3,98,66,6,87,4.0,6,49,Urban,Software Engineer,49660,0 +107420,Male,34,Bachelors,8,92,89,65,83,3.0,6,53,Urban,Software Engineer,116426,1 +107421,Male,42,High School,16,44,73,53,12,4.0,7,43,Urban,Manager,24132,0 +107422,Male,22,Masters,6,84,7,79,26,1.0,0,1,Urban,Data Analyst,77034,0 +107423,Female,35,High School,0,92,59,91,40,3.0,6,72,Urban,ML Engineer,61237,1 +107424,Female,46,Masters,16,82,78,34,75,2.0,3,33,Rural,Data Analyst,148783,0 +107425,Male,58,Bachelors,14,5,71,45,63,6.0,5,94,Urban,Data Analyst,116076,0 +107426,Male,25,High School,16,39,51,79,46,5.0,0,94,Urban,Manager,124222,1 +107427,Male,24,Bachelors,16,36,73,62,92,1.0,2,95,Rural,Data Analyst,85447,1 +107428,Male,46,Diploma,10,4,88,5,76,6.0,6,2,Urban,Software Engineer,89866,0 +107429,Male,30,PhD,6,38,42,8,85,1.0,2,58,Semi-Urban,Data Analyst,96742,0 +107430,Male,39,High School,11,56,57,76,60,7.0,6,77,Urban,Software Engineer,53250,1 +107431,Other,52,Bachelors,16,44,75,19,76,7.0,3,48,Urban,ML Engineer,74841,0 +107432,Male,42,Diploma,10,38,84,44,36,2.0,3,13,Urban,Software Engineer,124692,0 +107433,Male,36,Diploma,6,7,24,64,1,9.0,6,0,Semi-Urban,Manager,96014,0 +107434,Female,54,Diploma,9,13,9,85,89,2.0,1,32,Semi-Urban,Data Analyst,115147,0 +107435,Male,28,High School,2,84,41,19,16,8.0,4,4,Urban,ML Engineer,123021,0 +107436,Female,21,Bachelors,8,27,58,22,22,8.0,4,60,Urban,Data Analyst,92877,0 +107437,Male,49,Masters,16,34,40,47,76,3.0,7,15,Semi-Urban,ML Engineer,40606,0 +107438,Female,51,Masters,12,93,57,39,82,2.0,5,74,Urban,Manager,111578,1 +107439,Male,57,Diploma,12,86,8,35,95,7.0,5,33,Urban,HR Executive,49888,0 +107440,Female,55,Masters,17,3,0,99,86,2.0,4,69,Semi-Urban,HR Executive,67147,0 +107441,Male,43,Bachelors,1,47,20,53,72,1.0,2,5,Urban,Data Analyst,40581,0 +107442,Male,22,High School,10,97,93,16,12,8.0,5,39,Urban,Manager,146981,1 +107443,Male,30,Bachelors,4,60,50,57,68,1.0,0,54,Urban,HR Executive,144465,0 +107444,Male,21,High School,17,83,0,1,29,5.0,0,66,Urban,ML Engineer,28464,0 +107445,Male,59,Bachelors,17,18,97,65,56,3.0,2,38,Semi-Urban,Software Engineer,92334,0 +107446,Male,58,Masters,1,66,76,43,7,7.0,4,5,Urban,Manager,129989,0 +107447,Male,31,Diploma,18,44,43,75,3,6.0,7,8,Urban,Manager,69248,0 +107448,Male,54,High School,3,12,58,39,4,6.0,4,70,Urban,ML Engineer,135521,0 +107449,Male,46,Bachelors,2,25,80,31,61,5.0,1,47,Urban,Manager,88527,0 +107450,Male,51,Diploma,16,44,6,84,34,1.0,7,83,Semi-Urban,Software Engineer,72338,0 +107451,Male,26,High School,10,7,23,31,56,9.0,4,16,Urban,Software Engineer,42863,0 +107452,Female,56,Masters,2,72,58,67,41,8.0,1,94,Urban,Software Engineer,125191,1 +107453,Female,24,Bachelors,13,62,10,91,83,6.0,1,78,Urban,ML Engineer,101010,1 +107454,Female,49,Masters,2,45,84,17,29,4.0,0,59,Urban,HR Executive,70076,0 +107455,Female,59,Diploma,15,10,84,69,53,0.0,3,25,Urban,Software Engineer,76739,0 +107456,Male,50,Masters,18,43,63,63,43,7.0,7,89,Urban,Software Engineer,112480,1 +107457,Male,44,High School,6,91,79,11,39,3.0,4,40,Rural,Data Analyst,113707,0 +107458,Male,34,High School,5,89,28,8,67,2.0,4,38,Rural,HR Executive,56697,0 +107459,Female,33,Bachelors,16,15,37,67,27,5.0,1,68,Urban,Software Engineer,117037,0 +107460,Female,48,Diploma,16,57,65,23,36,1.0,1,94,Semi-Urban,Manager,143711,0 +107461,Female,49,PhD,1,94,84,13,38,3.0,5,9,Urban,ML Engineer,43067,0 +107462,Male,35,Bachelors,1,12,54,48,39,9.0,6,35,Urban,Manager,45999,0 +107463,Female,26,Bachelors,2,90,2,47,1,5.0,5,75,Urban,Data Analyst,131987,0 +107464,Female,26,Bachelors,9,1,83,14,72,4.0,0,94,Rural,HR Executive,33998,0 +107465,Female,22,Diploma,15,58,12,0,17,3.0,0,29,Urban,HR Executive,113863,0 +107466,Female,43,Bachelors,16,29,16,48,0,4.0,2,56,Urban,HR Executive,116614,0 +107467,Female,48,Bachelors,12,89,55,67,71,4.0,3,7,Urban,Data Analyst,70881,0 +107468,Male,48,Diploma,7,42,22,52,5,6.0,1,53,Urban,HR Executive,58995,0 +107469,Male,22,Bachelors,18,25,37,52,12,4.0,3,5,Urban,Manager,137104,0 +107470,Male,57,Bachelors,14,47,62,2,70,9.0,5,29,Semi-Urban,Software Engineer,29877,0 +107471,Female,23,High School,4,86,98,88,20,2.0,4,78,Rural,HR Executive,82702,1 +107472,Male,25,Bachelors,1,78,69,74,21,6.0,5,18,Semi-Urban,ML Engineer,49916,1 +107473,Male,58,Masters,4,95,85,38,60,1.0,1,61,Rural,HR Executive,88510,1 +107474,Male,32,Bachelors,5,65,43,24,33,8.0,7,78,Semi-Urban,HR Executive,65228,0 +107475,Male,52,Diploma,2,58,72,49,60,7.0,0,21,Urban,ML Engineer,142210,0 +107476,Male,55,High School,5,93,5,64,28,0.0,6,98,Urban,HR Executive,92776,1 +107477,Male,25,Bachelors,11,54,19,15,62,9.0,0,0,Semi-Urban,ML Engineer,67606,0 +107478,Male,29,Bachelors,2,99,11,86,47,1.0,2,77,Urban,ML Engineer,129681,1 +107479,Male,59,Masters,12,4,34,12,18,9.0,3,56,Urban,Manager,111336,0 +107480,Female,49,Masters,15,54,17,94,88,8.0,0,44,Rural,HR Executive,125479,0 +107481,Female,45,Masters,8,52,70,15,44,4.0,5,15,Rural,ML Engineer,69362,0 +107482,Male,57,Bachelors,15,67,61,33,79,4.0,4,31,Semi-Urban,Manager,135975,0 +107483,Male,35,Bachelors,17,35,94,59,50,1.0,4,16,Semi-Urban,Manager,133792,0 +107484,Other,39,High School,7,11,90,43,42,2.0,4,49,Urban,Data Analyst,47929,0 +107485,Male,22,Bachelors,6,22,63,48,7,0.0,0,96,Urban,HR Executive,147835,0 +107486,Female,37,Masters,17,32,52,31,8,2.0,4,56,Rural,Manager,121762,0 +107487,Male,27,Bachelors,15,37,28,33,75,3.0,7,38,Semi-Urban,ML Engineer,49940,0 +107488,Female,50,Diploma,14,41,91,53,81,5.0,4,65,Semi-Urban,Manager,54858,1 +107489,Male,49,Masters,1,96,27,31,35,0.0,0,68,Urban,Data Analyst,141135,0 +107490,Male,39,Bachelors,6,81,20,56,48,2.0,6,88,Semi-Urban,ML Engineer,111434,1 +107491,Female,21,Bachelors,5,91,33,20,20,4.0,6,47,Urban,ML Engineer,132597,0 +107492,Male,54,Bachelors,14,8,42,35,11,1.0,5,99,Rural,Data Analyst,118233,0 +107493,Male,46,PhD,12,42,81,41,1,1.0,1,47,Semi-Urban,Data Analyst,88954,0 +107494,Male,49,Masters,11,22,54,18,17,9.0,7,36,Urban,Data Analyst,30291,0 +107495,Male,51,Bachelors,11,72,66,47,74,7.0,0,72,Urban,Software Engineer,33448,1 +107496,Male,28,High School,3,77,66,6,78,7.0,3,84,Urban,ML Engineer,69320,0 +107497,Female,40,Masters,12,12,94,88,21,7.0,4,66,Urban,Software Engineer,29476,1 +107498,Male,26,Bachelors,10,86,64,18,19,1.0,4,44,Urban,Software Engineer,121324,0 +107499,Male,21,High School,14,98,48,52,1,5.0,5,96,Urban,Data Analyst,141835,1 +107500,Male,34,Bachelors,4,29,68,92,11,1.0,3,37,Urban,Software Engineer,61419,0 +107501,Female,49,Diploma,5,91,57,30,40,3.0,6,24,Rural,Manager,91323,0 +107502,Male,45,Diploma,19,28,3,40,85,6.0,4,60,Urban,Software Engineer,128682,0 +107503,Female,40,Bachelors,16,43,69,81,19,2.0,2,74,Rural,Data Analyst,51992,1 +107504,Male,36,High School,12,83,53,28,41,5.0,6,92,Urban,Data Analyst,22627,1 +107505,Other,39,Bachelors,16,52,1,19,46,7.0,7,48,Semi-Urban,Manager,34857,0 +107506,Male,57,Masters,19,98,49,35,81,8.0,5,5,Semi-Urban,Data Analyst,34660,0 +107507,Male,22,High School,9,55,26,9,20,9.0,3,37,Urban,HR Executive,149802,0 +107508,Female,47,Diploma,7,91,64,33,54,3.0,2,65,Rural,Data Analyst,124498,1 +107509,Female,36,Masters,1,37,93,98,9,5.0,2,17,Semi-Urban,HR Executive,49581,1 +107510,Female,35,Bachelors,6,48,98,57,58,4.0,0,72,Urban,Software Engineer,54278,1 +107511,Other,22,Bachelors,14,66,51,90,50,8.0,5,55,Semi-Urban,Manager,40405,1 +107512,Female,44,Masters,10,79,19,10,86,4.0,4,27,Semi-Urban,Software Engineer,106097,0 +107513,Female,36,High School,6,82,43,11,50,4.0,1,99,Rural,ML Engineer,85208,0 +107514,Male,26,Masters,3,51,51,60,0,8.0,5,47,Rural,HR Executive,143273,0 +107515,Male,32,High School,0,21,22,5,31,9.0,3,69,Semi-Urban,HR Executive,133854,0 +107516,Male,50,Diploma,10,66,57,48,16,3.0,2,4,Urban,Data Analyst,31376,0 +107517,Male,32,Masters,7,93,2,76,54,5.0,2,76,Semi-Urban,Software Engineer,39878,1 +107518,Male,48,Bachelors,19,47,45,87,77,3.0,6,57,Urban,Software Engineer,126996,1 +107519,Female,57,Bachelors,14,21,86,26,83,9.0,2,74,Urban,HR Executive,139941,0 +107520,Male,25,Bachelors,13,57,84,83,47,8.0,7,98,Urban,HR Executive,109210,1 +107521,Male,47,Bachelors,18,76,89,62,52,0.0,1,23,Urban,ML Engineer,57044,1 +107522,Male,31,High School,19,55,77,87,87,7.0,5,21,Semi-Urban,Data Analyst,123957,1 +107523,Male,40,Bachelors,15,57,95,78,27,3.0,1,28,Urban,Software Engineer,143425,1 +107524,Male,53,High School,0,55,62,92,68,6.0,4,5,Urban,ML Engineer,102171,0 +107525,Male,22,Masters,7,96,25,52,6,1.0,2,75,Semi-Urban,Data Analyst,38223,1 +107526,Female,31,High School,8,63,12,7,47,7.0,2,61,Urban,HR Executive,111723,0 +107527,Male,22,High School,3,70,34,15,96,9.0,0,45,Urban,ML Engineer,132665,0 +107528,Male,48,High School,12,51,53,69,45,6.0,6,57,Semi-Urban,Manager,125908,0 +107529,Male,27,Bachelors,1,2,34,26,38,5.0,3,57,Semi-Urban,Software Engineer,82153,0 +107530,Female,38,Bachelors,12,91,90,54,62,2.0,6,52,Urban,ML Engineer,55493,1 +107531,Male,31,Bachelors,9,57,69,64,54,5.0,2,78,Urban,Data Analyst,85026,1 +107532,Female,58,Diploma,17,99,10,4,22,0.0,6,15,Semi-Urban,ML Engineer,106688,0 +107533,Male,48,Bachelors,7,73,33,45,2,8.0,6,36,Urban,Data Analyst,94916,0 +107534,Male,31,Bachelors,15,63,10,81,1,9.0,1,70,Urban,Data Analyst,134420,0 +107535,Male,53,Bachelors,13,15,64,21,25,3.0,6,94,Rural,ML Engineer,83047,0 +107536,Male,27,Masters,17,42,31,34,86,7.0,3,50,Rural,Software Engineer,50153,0 +107537,Female,40,Bachelors,7,42,78,64,83,8.0,3,97,Urban,Data Analyst,136869,1 +107538,Male,29,Diploma,0,88,22,39,77,1.0,5,86,Rural,Manager,57745,1 +107539,Female,48,Bachelors,18,68,53,38,36,5.0,2,37,Urban,Software Engineer,71124,0 +107540,Male,51,Masters,2,40,34,83,93,3.0,1,94,Urban,HR Executive,132337,1 +107541,Male,21,Bachelors,17,30,80,49,24,5.0,4,13,Urban,Software Engineer,104732,0 +107542,Female,32,High School,18,67,72,77,3,2.0,0,51,Rural,ML Engineer,29213,1 +107543,Female,34,Bachelors,1,61,87,48,50,4.0,1,77,Urban,Software Engineer,81063,1 +107544,Female,33,Bachelors,14,10,32,99,88,4.0,4,46,Rural,Data Analyst,144376,0 +107545,Male,25,Diploma,6,59,68,10,77,8.0,1,57,Urban,ML Engineer,23104,0 +107546,Other,41,Bachelors,5,19,14,0,26,3.0,0,13,Rural,Software Engineer,31876,0 +107547,Other,28,Bachelors,18,4,49,24,23,8.0,6,43,Urban,HR Executive,38326,0 +107548,Female,44,PhD,7,69,65,93,3,6.0,2,58,Rural,Manager,59113,1 +107549,Male,55,Bachelors,18,11,0,16,33,5.0,2,11,Urban,ML Engineer,146730,0 +107550,Male,28,Masters,18,97,0,38,70,1.0,3,53,Urban,Data Analyst,65633,0 +107551,Male,23,High School,13,72,79,47,77,4.0,1,64,Semi-Urban,ML Engineer,74027,1 +107552,Male,29,Bachelors,2,74,77,45,5,0.0,3,24,Urban,Manager,60308,0 +107553,Female,57,Bachelors,6,18,0,45,79,3.0,6,57,Rural,Data Analyst,43270,0 +107554,Male,26,Bachelors,1,25,56,60,98,8.0,0,81,Semi-Urban,Data Analyst,25313,0 +107555,Male,52,Bachelors,15,73,1,61,61,7.0,3,42,Urban,Software Engineer,80476,0 +107556,Male,25,Bachelors,19,87,23,22,6,1.0,4,49,Urban,HR Executive,99355,0 +107557,Female,45,Masters,9,49,21,6,45,6.0,5,58,Urban,Software Engineer,40420,0 +107558,Male,21,High School,19,14,17,5,63,4.0,5,0,Semi-Urban,ML Engineer,138664,0 +107559,Female,59,Bachelors,10,58,73,56,81,1.0,7,48,Urban,Data Analyst,134957,0 +107560,Female,39,High School,10,48,19,11,41,7.0,1,79,Semi-Urban,Software Engineer,79946,0 +107561,Female,37,Bachelors,1,81,61,71,20,5.0,5,53,Rural,Data Analyst,127030,1 +107562,Female,37,Bachelors,9,8,31,51,44,2.0,5,51,Semi-Urban,ML Engineer,107209,0 +107563,Male,31,Masters,16,63,33,62,15,3.0,7,13,Semi-Urban,Manager,46365,0 +107564,Male,49,Masters,6,31,94,14,56,2.0,4,64,Urban,Data Analyst,39264,0 +107565,Male,25,Bachelors,13,77,91,76,28,7.0,5,88,Urban,Data Analyst,90851,1 +107566,Female,25,Bachelors,6,2,77,29,20,7.0,7,49,Semi-Urban,Manager,142126,0 +107567,Male,30,Masters,3,46,21,99,27,6.0,6,5,Semi-Urban,Software Engineer,29012,0 +107568,Male,44,Bachelors,3,73,6,43,62,2.0,6,22,Rural,Software Engineer,44732,0 +107569,Female,52,Masters,5,87,24,9,60,9.0,1,22,Rural,ML Engineer,113383,0 +107570,Male,38,Bachelors,18,72,62,45,93,8.0,2,36,Rural,Data Analyst,91705,0 +107571,Male,46,Diploma,14,1,84,0,52,1.0,7,41,Urban,Manager,133061,0 +107572,Male,48,Diploma,13,2,33,31,98,6.0,1,78,Urban,HR Executive,35902,0 +107573,Female,58,Bachelors,18,34,49,72,54,8.0,0,56,Rural,HR Executive,123181,0 +107574,Male,35,Bachelors,0,59,1,66,92,9.0,0,8,Urban,Data Analyst,65662,0 +107575,Male,53,Diploma,13,34,74,69,98,5.0,3,71,Urban,Data Analyst,119927,1 +107576,Male,27,Bachelors,10,7,51,53,38,6.0,2,46,Semi-Urban,Manager,44215,0 +107577,Male,51,Masters,17,68,29,13,31,1.0,1,17,Semi-Urban,Manager,85619,0 +107578,Male,52,Bachelors,0,67,18,54,22,4.0,2,59,Urban,HR Executive,120708,0 +107579,Male,35,Diploma,13,75,11,16,37,6.0,0,63,Urban,Data Analyst,102163,0 +107580,Other,48,Bachelors,15,67,77,52,5,9.0,3,19,Urban,HR Executive,45563,0 +107581,Other,43,High School,17,23,30,89,22,6.0,3,44,Semi-Urban,Data Analyst,147611,0 +107582,Female,48,High School,17,24,53,66,2,8.0,5,35,Urban,Data Analyst,20808,0 +107583,Female,48,High School,17,20,72,29,72,8.0,2,89,Urban,HR Executive,47102,0 +107584,Male,49,Diploma,19,39,99,65,56,9.0,4,5,Semi-Urban,Data Analyst,104117,0 +107585,Male,28,Diploma,9,64,98,55,84,9.0,0,93,Semi-Urban,Manager,131901,1 +107586,Male,21,High School,8,93,44,80,17,9.0,2,63,Urban,Data Analyst,105482,1 +107587,Male,25,Bachelors,7,12,94,10,11,6.0,4,87,Urban,Data Analyst,55980,0 +107588,Male,22,Bachelors,18,6,49,44,5,7.0,2,63,Urban,Manager,40330,0 +107589,Male,27,High School,4,69,4,60,80,6.0,3,98,Rural,HR Executive,117558,0 +107590,Female,59,Diploma,1,66,28,2,51,1.0,2,87,Urban,Data Analyst,21585,0 +107591,Female,42,Bachelors,17,57,70,11,79,9.0,7,89,Urban,Software Engineer,111002,0 +107592,Female,31,Bachelors,2,82,70,29,17,9.0,7,91,Urban,Data Analyst,76928,1 +107593,Male,37,Bachelors,10,90,55,84,58,3.0,0,0,Rural,HR Executive,130244,0 +107594,Male,43,Masters,8,32,87,46,56,6.0,4,55,Semi-Urban,ML Engineer,56774,0 +107595,Male,49,Bachelors,0,59,18,82,67,8.0,1,94,Urban,HR Executive,35041,1 +107596,Other,54,High School,15,30,74,24,74,1.0,1,28,Urban,Data Analyst,134504,0 +107597,Female,52,High School,6,3,98,89,69,9.0,6,99,Urban,Software Engineer,117962,1 +107598,Male,38,Bachelors,19,2,64,73,3,1.0,5,72,Rural,HR Executive,56169,0 +107599,Female,45,Bachelors,4,91,37,6,68,4.0,5,11,Rural,Data Analyst,84790,0 +107600,Female,53,High School,14,31,87,74,18,7.0,7,33,Urban,ML Engineer,36204,0 +107601,Male,27,Masters,8,20,91,18,43,0.0,4,31,Urban,ML Engineer,28199,0 +107602,Male,41,Masters,15,35,45,51,92,9.0,6,44,Rural,ML Engineer,69437,0 +107603,Male,23,Bachelors,8,89,38,99,87,2.0,2,5,Rural,HR Executive,54402,0 +107604,Male,46,High School,6,74,17,29,61,0.0,2,63,Urban,Manager,140848,0 +107605,Male,32,Masters,6,37,3,46,99,1.0,3,86,Semi-Urban,ML Engineer,107584,0 +107606,Male,56,Masters,3,2,56,33,17,7.0,5,63,Rural,Software Engineer,89262,0 +107607,Female,28,Masters,8,32,13,85,78,4.0,1,38,Urban,Software Engineer,54348,0 +107608,Male,37,High School,8,8,53,99,79,5.0,1,7,Semi-Urban,Software Engineer,45895,0 +107609,Male,44,Diploma,19,93,64,88,17,1.0,4,62,Rural,Software Engineer,75930,1 +107610,Male,29,Masters,13,83,0,18,38,3.0,3,90,Urban,ML Engineer,30444,0 +107611,Male,24,Masters,0,43,14,5,18,5.0,3,12,Rural,Data Analyst,25661,0 +107612,Male,36,High School,11,34,38,78,52,2.0,1,24,Semi-Urban,Manager,148827,0 +107613,Male,40,High School,14,18,36,11,29,8.0,1,85,Urban,Manager,126706,0 +107614,Male,26,Bachelors,18,37,32,5,82,2.0,3,21,Semi-Urban,Data Analyst,125013,0 +107615,Male,57,Bachelors,9,36,3,83,57,4.0,0,1,Urban,HR Executive,62264,0 +107616,Male,46,Masters,2,70,63,24,81,3.0,3,78,Rural,Manager,42593,1 +107617,Female,41,High School,18,63,22,99,82,6.0,2,61,Semi-Urban,Manager,62978,1 +107618,Male,49,PhD,2,37,18,3,46,1.0,0,0,Urban,ML Engineer,104945,0 +107619,Male,22,High School,13,0,17,63,22,1.0,5,99,Rural,Data Analyst,51224,0 +107620,Male,54,Bachelors,5,83,28,0,94,2.0,1,19,Semi-Urban,Data Analyst,67658,0 +107621,Female,44,High School,4,60,45,38,82,2.0,3,57,Urban,Manager,102319,0 +107622,Male,40,Diploma,1,12,69,11,35,8.0,6,86,Rural,Manager,148768,0 +107623,Male,37,Masters,5,67,16,6,50,3.0,5,5,Semi-Urban,ML Engineer,69478,0 +107624,Female,37,High School,18,77,76,52,73,2.0,4,3,Urban,Software Engineer,89671,0 +107625,Female,24,High School,14,42,83,89,78,7.0,7,94,Urban,ML Engineer,90102,1 +107626,Male,58,Bachelors,14,45,91,46,24,9.0,5,96,Urban,Data Analyst,133436,1 +107627,Male,49,Bachelors,6,95,95,62,41,1.0,0,68,Urban,Manager,104572,1 +107628,Male,47,Diploma,3,39,50,62,2,9.0,1,8,Urban,ML Engineer,124986,0 +107629,Male,39,Bachelors,3,75,48,37,40,1.0,3,68,Rural,Data Analyst,86803,0 +107630,Male,41,Diploma,4,83,81,10,29,2.0,4,89,Urban,Manager,35011,1 +107631,Male,54,High School,9,4,58,22,11,3.0,4,28,Semi-Urban,HR Executive,115786,0 +107632,Female,33,High School,18,32,94,25,87,7.0,0,74,Semi-Urban,ML Engineer,66047,0 +107633,Male,25,Diploma,17,31,96,48,7,5.0,2,93,Urban,HR Executive,23385,1 +107634,Male,26,Diploma,7,9,63,5,15,3.0,6,28,Urban,ML Engineer,54101,0 +107635,Female,52,High School,16,42,35,31,73,5.0,5,92,Urban,HR Executive,26095,0 +107636,Female,49,Masters,14,56,67,33,33,0.0,0,17,Urban,HR Executive,116761,0 +107637,Male,31,Diploma,13,24,4,17,0,5.0,7,92,Urban,ML Engineer,47992,0 +107638,Male,53,High School,14,35,19,45,52,3.0,7,70,Urban,Data Analyst,139477,0 +107639,Male,47,Diploma,16,13,40,69,91,1.0,0,39,Semi-Urban,Software Engineer,41133,0 +107640,Female,27,Bachelors,11,47,83,45,54,4.0,5,18,Urban,Manager,64833,0 +107641,Female,43,Diploma,9,67,50,87,35,9.0,5,59,Semi-Urban,ML Engineer,105228,1 +107642,Female,45,Diploma,2,22,16,99,19,7.0,3,59,Rural,HR Executive,99866,0 +107643,Female,27,Masters,12,59,67,7,1,4.0,4,34,Rural,Manager,98737,0 +107644,Male,48,Diploma,6,53,28,0,21,4.0,2,3,Rural,HR Executive,61614,0 +107645,Male,42,Bachelors,6,86,18,70,49,3.0,5,83,Rural,Manager,59197,1 +107646,Male,37,Diploma,9,10,36,3,48,9.0,5,57,Rural,ML Engineer,21252,0 +107647,Female,54,Diploma,5,36,96,91,70,0.0,1,68,Semi-Urban,Data Analyst,81199,1 +107648,Male,42,Bachelors,4,6,27,76,94,7.0,3,29,Urban,Data Analyst,29343,0 +107649,Male,30,Diploma,14,39,27,46,45,3.0,4,80,Semi-Urban,Software Engineer,81195,0 +107650,Male,22,Bachelors,0,70,42,4,10,7.0,1,43,Urban,Software Engineer,138273,0 +107651,Female,32,Masters,17,4,13,22,70,1.0,0,8,Urban,ML Engineer,71014,0 +107652,Female,26,Bachelors,14,57,3,47,76,3.0,6,11,Rural,Software Engineer,94988,0 +107653,Female,38,Masters,16,19,12,18,8,8.0,2,77,Semi-Urban,HR Executive,85596,0 +107654,Male,24,Masters,3,98,74,38,54,7.0,6,46,Rural,ML Engineer,148593,1 +107655,Male,58,Bachelors,8,59,10,57,17,5.0,6,99,Semi-Urban,ML Engineer,54717,0 +107656,Male,43,Diploma,3,43,69,4,16,6.0,2,4,Rural,HR Executive,120758,0 +107657,Male,38,Diploma,1,67,24,26,20,8.0,6,32,Urban,HR Executive,141790,0 +107658,Female,54,Diploma,6,80,83,14,55,8.0,6,19,Urban,ML Engineer,106227,0 +107659,Female,34,High School,12,67,30,80,4,8.0,3,84,Rural,HR Executive,28977,1 +107660,Male,39,Masters,3,89,66,11,58,4.0,2,22,Urban,ML Engineer,90755,0 +107661,Female,25,PhD,9,73,15,61,93,5.0,2,0,Urban,Software Engineer,143038,0 +107662,Male,24,High School,16,95,77,7,83,4.0,5,63,Urban,Manager,57023,1 +107663,Male,35,High School,6,14,10,63,20,4.0,2,67,Semi-Urban,Manager,62636,0 +107664,Male,44,Masters,4,33,26,27,58,7.0,7,64,Urban,Manager,49574,0 +107665,Male,34,Bachelors,11,69,94,48,19,2.0,6,27,Urban,HR Executive,40594,1 +107666,Male,54,Diploma,13,59,58,94,66,1.0,4,93,Rural,Software Engineer,143437,1 +107667,Male,57,High School,4,20,78,83,9,4.0,0,55,Rural,ML Engineer,42645,1 +107668,Other,50,Bachelors,4,45,31,27,33,8.0,2,90,Semi-Urban,Manager,94180,0 +107669,Male,22,Bachelors,19,33,19,97,4,6.0,0,81,Urban,HR Executive,39733,0 +107670,Female,31,Diploma,10,38,96,35,2,0.0,7,99,Semi-Urban,Data Analyst,70552,1 +107671,Male,32,Masters,2,57,59,59,92,1.0,3,48,Rural,Manager,40409,0 +107672,Female,54,Bachelors,7,26,67,5,61,5.0,4,27,Urban,Software Engineer,43571,0 +107673,Female,27,Diploma,10,46,87,77,2,6.0,2,18,Urban,Software Engineer,52977,0 +107674,Male,23,Bachelors,10,88,78,35,88,3.0,6,8,Urban,Data Analyst,53461,0 +107675,Female,24,Bachelors,18,24,45,83,5,8.0,4,5,Rural,Software Engineer,102750,0 +107676,Female,40,Bachelors,9,33,28,77,41,6.0,1,7,Urban,ML Engineer,144870,0 +107677,Female,57,Bachelors,18,67,84,76,35,6.0,1,22,Urban,ML Engineer,58741,1 +107678,Male,37,High School,6,26,51,18,31,2.0,1,4,Urban,Data Analyst,147811,0 +107679,Female,54,Bachelors,5,54,81,2,23,2.0,5,57,Urban,HR Executive,39085,0 +107680,Male,47,Bachelors,4,60,25,48,22,9.0,6,22,Rural,HR Executive,27182,0 +107681,Male,21,Bachelors,3,42,25,9,10,9.0,5,76,Urban,ML Engineer,27507,0 +107682,Male,32,Diploma,8,42,19,33,29,2.0,5,58,Urban,Software Engineer,117659,0 +107683,Female,47,Masters,0,94,68,24,80,2.0,3,84,Urban,HR Executive,57491,1 +107684,Female,53,Masters,0,96,40,96,34,0.0,1,88,Rural,HR Executive,108166,1 +107685,Male,45,Bachelors,3,92,34,91,6,6.0,1,1,Semi-Urban,ML Engineer,145518,0 +107686,Female,52,PhD,7,41,15,41,11,0.0,7,62,Urban,Software Engineer,43731,0 +107687,Male,58,Bachelors,1,66,1,36,38,3.0,4,53,Urban,Manager,76192,0 +107688,Female,54,High School,0,65,88,48,71,8.0,5,79,Urban,HR Executive,65565,1 +107689,Female,28,Diploma,6,8,46,99,53,9.0,4,74,Urban,Software Engineer,21879,0 +107690,Male,51,Diploma,13,79,42,27,46,2.0,2,47,Urban,HR Executive,61930,0 +107691,Male,51,Diploma,9,44,34,55,66,5.0,1,41,Semi-Urban,HR Executive,22787,0 +107692,Male,48,Bachelors,16,68,26,17,79,0.0,7,69,Urban,ML Engineer,138122,0 +107693,Female,45,Diploma,10,31,26,97,69,2.0,7,79,Urban,Data Analyst,122496,0 +107694,Female,46,Masters,3,82,20,64,68,0.0,2,15,Semi-Urban,Manager,137211,0 +107695,Male,47,Bachelors,6,59,1,56,4,2.0,6,78,Rural,HR Executive,142169,0 +107696,Other,46,Bachelors,13,39,46,4,11,4.0,1,54,Urban,ML Engineer,104700,0 +107697,Male,41,Bachelors,11,60,0,6,10,6.0,3,51,Semi-Urban,Software Engineer,132876,0 +107698,Female,36,High School,3,38,50,1,80,7.0,3,51,Urban,Data Analyst,128657,0 +107699,Female,40,Diploma,19,78,25,14,5,2.0,4,14,Urban,HR Executive,136040,0 +107700,Male,49,Bachelors,7,64,34,24,18,0.0,4,91,Urban,Manager,146295,0 +107701,Female,59,Masters,18,59,41,12,19,7.0,5,94,Urban,ML Engineer,92682,0 +107702,Male,46,Bachelors,4,43,90,9,45,3.0,1,73,Rural,Manager,94411,0 +107703,Male,51,Bachelors,9,7,8,71,85,3.0,0,82,Urban,Manager,128544,0 +107704,Male,37,Diploma,12,70,28,60,45,7.0,1,96,Urban,Data Analyst,100226,1 +107705,Male,46,Bachelors,16,51,70,69,53,1.0,1,73,Rural,Software Engineer,81426,1 +107706,Female,52,Bachelors,1,44,66,1,12,9.0,4,73,Semi-Urban,Manager,108764,0 +107707,Male,40,Masters,10,93,71,96,79,3.0,1,90,Semi-Urban,Data Analyst,72504,1 +107708,Male,58,Bachelors,1,97,34,50,4,0.0,7,3,Semi-Urban,Manager,56047,0 +107709,Male,35,Bachelors,3,73,56,85,57,0.0,4,64,Urban,Manager,57344,1 +107710,Female,32,Bachelors,9,71,89,61,44,5.0,6,57,Urban,HR Executive,58286,1 +107711,Female,52,High School,16,69,17,11,4,9.0,7,76,Urban,ML Engineer,103546,0 +107712,Male,54,Bachelors,15,54,3,52,18,7.0,2,82,Semi-Urban,Manager,119583,0 +107713,Male,44,Diploma,4,49,55,18,90,2.0,1,8,Rural,Data Analyst,77421,0 +107714,Female,36,Diploma,5,31,80,97,2,0.0,5,19,Rural,Manager,105401,0 +107715,Male,45,Masters,8,0,71,86,37,2.0,6,77,Rural,HR Executive,135496,0 +107716,Female,59,Bachelors,13,36,10,37,6,6.0,6,38,Urban,Data Analyst,58642,0 +107717,Female,47,Bachelors,18,92,87,67,74,9.0,7,68,Urban,ML Engineer,37077,1 +107718,Male,42,Bachelors,17,94,83,98,79,7.0,5,28,Semi-Urban,Software Engineer,123874,1 +107719,Male,33,Masters,0,14,71,78,13,4.0,3,77,Semi-Urban,ML Engineer,40807,1 +107720,Male,42,High School,0,21,82,67,61,5.0,6,77,Urban,Data Analyst,90372,1 +107721,Male,59,High School,2,61,18,93,51,6.0,5,3,Urban,Data Analyst,87097,0 +107722,Female,52,Masters,9,10,73,98,95,0.0,3,67,Urban,Manager,36359,1 +107723,Female,52,Bachelors,0,46,39,31,65,7.0,3,47,Semi-Urban,Data Analyst,36924,0 +107724,Female,56,High School,10,71,4,21,50,7.0,6,25,Urban,HR Executive,80235,0 +107725,Female,30,Bachelors,4,9,35,94,67,9.0,0,33,Urban,ML Engineer,62906,0 +107726,Male,26,Masters,4,50,55,89,70,9.0,1,7,Semi-Urban,Data Analyst,63651,0 +107727,Male,49,PhD,6,54,35,60,27,3.0,4,40,Semi-Urban,HR Executive,51797,0 +107728,Female,34,Bachelors,16,33,91,65,90,4.0,3,33,Semi-Urban,Data Analyst,22447,0 +107729,Female,40,Bachelors,12,53,4,48,15,7.0,0,55,Rural,ML Engineer,107135,0 +107730,Male,59,Masters,9,51,57,87,31,8.0,5,57,Rural,Manager,24234,1 +107731,Other,59,Diploma,2,69,69,8,46,0.0,1,33,Semi-Urban,Software Engineer,65382,0 +107732,Male,34,High School,19,0,40,90,14,4.0,2,53,Semi-Urban,Software Engineer,123775,0 +107733,Male,44,Masters,16,57,58,73,26,6.0,2,18,Rural,HR Executive,48619,0 +107734,Male,58,Bachelors,6,62,78,34,90,9.0,4,44,Rural,Data Analyst,138175,0 +107735,Male,50,Bachelors,7,38,7,86,60,4.0,1,25,Urban,ML Engineer,57514,0 +107736,Male,25,Diploma,3,3,56,42,92,0.0,3,49,Urban,Software Engineer,68497,0 +107737,Male,30,Diploma,6,26,40,36,40,9.0,1,32,Urban,ML Engineer,71148,0 +107738,Female,31,Bachelors,10,71,82,43,68,5.0,2,71,Urban,Manager,105518,1 +107739,Male,41,Masters,19,69,59,54,91,0.0,3,91,Urban,ML Engineer,66129,1 +107740,Female,30,High School,3,67,57,45,53,2.0,4,94,Semi-Urban,HR Executive,103998,1 +107741,Female,38,High School,12,90,49,86,47,7.0,7,4,Semi-Urban,Software Engineer,134374,0 +107742,Male,23,Diploma,5,38,14,98,81,9.0,6,79,Urban,Data Analyst,137165,0 +107743,Male,52,Bachelors,6,80,3,34,21,9.0,0,54,Urban,ML Engineer,128916,0 +107744,Female,27,PhD,2,4,89,24,6,7.0,4,32,Urban,Manager,74688,0 +107745,Female,59,Bachelors,12,53,1,23,3,8.0,5,97,Rural,Data Analyst,73353,0 +107746,Female,44,Bachelors,13,88,85,60,79,7.0,5,88,Semi-Urban,Data Analyst,38933,1 +107747,Male,41,Masters,14,8,30,25,24,9.0,4,85,Semi-Urban,ML Engineer,23416,0 +107748,Male,47,High School,14,28,10,11,80,2.0,0,7,Semi-Urban,Manager,133333,0 +107749,Female,36,High School,11,69,93,33,0,2.0,4,9,Urban,Data Analyst,142050,0 +107750,Male,38,Diploma,4,31,62,29,58,7.0,1,92,Semi-Urban,Software Engineer,44631,0 +107751,Male,55,Bachelors,7,38,55,76,61,7.0,6,10,Urban,Data Analyst,127389,0 +107752,Female,58,Bachelors,5,31,33,85,8,6.0,2,76,Urban,ML Engineer,49838,0 +107753,Female,34,Bachelors,2,42,34,26,5,8.0,6,43,Urban,HR Executive,72878,0 +107754,Male,30,Diploma,15,69,20,98,32,9.0,6,25,Semi-Urban,Software Engineer,71298,0 +107755,Female,36,Bachelors,11,42,10,64,95,1.0,0,45,Urban,ML Engineer,117231,0 +107756,Male,59,Bachelors,16,34,34,2,67,8.0,5,30,Semi-Urban,Manager,144210,0 +107757,Female,48,PhD,5,91,61,62,4,4.0,6,79,Rural,HR Executive,70311,1 +107758,Female,32,Bachelors,11,63,69,9,20,9.0,0,69,Semi-Urban,Manager,143572,0 +107759,Male,45,PhD,11,96,43,45,19,8.0,0,19,Rural,ML Engineer,53431,0 +107760,Female,22,Masters,8,44,16,84,32,3.0,4,82,Rural,ML Engineer,87007,0 +107761,Female,46,Bachelors,11,14,20,26,14,7.0,1,1,Urban,ML Engineer,39398,0 +107762,Male,55,Bachelors,12,13,44,54,83,2.0,0,14,Urban,Software Engineer,47709,0 +107763,Male,52,Diploma,17,79,55,87,56,6.0,3,31,Semi-Urban,ML Engineer,59215,1 +107764,Other,22,Bachelors,14,96,96,70,40,8.0,7,46,Urban,Manager,60700,1 +107765,Male,49,Diploma,15,56,48,15,89,4.0,6,77,Rural,ML Engineer,48167,0 +107766,Other,42,High School,7,99,7,0,57,8.0,7,12,Urban,HR Executive,93795,0 +107767,Male,31,Diploma,13,43,69,32,83,8.0,1,41,Rural,Data Analyst,81527,0 +107768,Male,55,Diploma,15,18,1,86,31,0.0,0,61,Semi-Urban,Data Analyst,39189,0 +107769,Male,53,High School,12,19,97,78,53,9.0,4,86,Semi-Urban,Manager,111797,1 +107770,Male,51,High School,17,71,43,44,43,0.0,2,2,Semi-Urban,Data Analyst,79876,0 +107771,Male,30,High School,17,61,91,37,34,1.0,7,57,Urban,Manager,64929,1 +107772,Male,23,Diploma,4,63,6,4,43,6.0,2,56,Urban,HR Executive,69502,0 +107773,Male,59,Bachelors,16,75,55,94,54,8.0,7,98,Semi-Urban,Data Analyst,46933,1 +107774,Male,37,Diploma,3,52,9,58,97,9.0,6,2,Rural,Manager,88406,0 +107775,Other,22,Bachelors,4,17,21,50,21,5.0,2,5,Urban,Software Engineer,69468,0 +107776,Male,55,Masters,13,26,22,62,48,5.0,3,66,Urban,Data Analyst,82038,0 +107777,Other,46,Bachelors,17,28,61,30,32,2.0,5,6,Urban,HR Executive,82542,0 +107778,Male,30,Masters,2,67,23,68,40,0.0,4,92,Urban,HR Executive,44901,1 +107779,Male,31,High School,6,66,44,23,11,8.0,2,83,Urban,Software Engineer,87373,0 +107780,Male,41,PhD,13,16,2,84,55,0.0,0,12,Rural,ML Engineer,71953,0 +107781,Male,54,High School,4,40,15,69,79,0.0,6,34,Urban,HR Executive,105254,0 +107782,Male,48,Bachelors,3,48,80,99,59,8.0,4,76,Rural,HR Executive,123775,1 +107783,Male,30,Masters,15,65,11,31,64,5.0,6,32,Urban,Data Analyst,23275,0 +107784,Male,34,Bachelors,8,53,37,29,39,1.0,1,87,Semi-Urban,Data Analyst,75852,0 +107785,Male,50,Diploma,6,55,20,55,96,9.0,7,15,Rural,Software Engineer,53954,0 +107786,Male,49,Bachelors,2,75,69,64,71,1.0,1,32,Urban,Data Analyst,73666,1 +107787,Male,55,Bachelors,0,38,60,41,42,4.0,2,14,Urban,Manager,149219,0 +107788,Female,32,Bachelors,12,1,45,33,56,1.0,4,46,Rural,ML Engineer,54732,0 +107789,Male,43,Diploma,6,11,29,48,70,3.0,1,49,Rural,Data Analyst,57124,0 +107790,Male,23,Bachelors,13,81,36,21,90,9.0,4,77,Rural,ML Engineer,79471,0 +107791,Female,28,Bachelors,10,17,18,79,18,5.0,7,57,Urban,ML Engineer,56207,0 +107792,Male,41,Masters,5,43,16,63,52,2.0,5,36,Urban,HR Executive,74667,0 +107793,Female,46,Masters,16,65,47,67,94,6.0,3,29,Urban,Data Analyst,56224,0 +107794,Female,28,Bachelors,16,94,10,18,22,6.0,4,87,Rural,Data Analyst,134050,0 +107795,Female,50,Masters,1,75,50,26,56,6.0,0,31,Semi-Urban,HR Executive,102887,0 +107796,Male,55,PhD,7,88,0,84,65,2.0,1,7,Urban,ML Engineer,39204,0 +107797,Female,42,Diploma,17,91,67,31,83,4.0,2,66,Urban,HR Executive,44109,1 +107798,Male,57,Bachelors,8,16,43,35,53,4.0,0,51,Semi-Urban,HR Executive,119201,0 +107799,Other,38,Masters,6,21,31,37,60,8.0,5,79,Semi-Urban,Software Engineer,29847,0 +107800,Female,29,High School,0,6,12,15,77,1.0,2,87,Urban,Manager,112768,0 +107801,Female,29,Bachelors,0,9,54,30,2,2.0,0,68,Semi-Urban,Software Engineer,124530,0 +107802,Male,45,Bachelors,13,63,61,75,4,0.0,6,90,Semi-Urban,ML Engineer,108834,1 +107803,Male,28,Bachelors,8,17,55,28,63,8.0,3,39,Urban,Manager,125186,0 +107804,Male,36,High School,9,81,5,46,11,5.0,4,78,Urban,HR Executive,147292,0 +107805,Male,50,Diploma,11,14,94,32,62,8.0,4,27,Urban,Data Analyst,54280,0 +107806,Male,29,Masters,6,34,64,8,21,6.0,4,70,Rural,HR Executive,65543,0 +107807,Male,45,Diploma,2,79,70,36,54,8.0,5,85,Urban,Data Analyst,124386,1 +107808,Female,46,Bachelors,0,94,73,77,9,6.0,0,61,Urban,ML Engineer,139633,1 +107809,Male,27,PhD,6,80,77,2,81,0.0,6,77,Semi-Urban,Software Engineer,44759,1 +107810,Male,25,Bachelors,1,54,39,18,90,1.0,6,60,Urban,Software Engineer,95774,0 +107811,Male,58,Masters,4,54,25,18,39,4.0,0,98,Rural,ML Engineer,117139,0 +107812,Female,39,Masters,18,21,92,90,7,5.0,0,34,Urban,ML Engineer,55138,0 +107813,Female,55,Diploma,9,38,33,53,81,2.0,5,18,Urban,Manager,37254,0 +107814,Female,26,Bachelors,2,31,91,53,90,3.0,7,12,Urban,HR Executive,146277,0 +107815,Male,52,Bachelors,2,15,11,60,35,2.0,4,97,Semi-Urban,Software Engineer,79811,0 +107816,Male,48,Diploma,5,67,32,14,89,1.0,0,55,Semi-Urban,ML Engineer,28510,0 +107817,Male,35,Bachelors,16,96,71,35,29,7.0,7,5,Urban,ML Engineer,117428,0 +107818,Female,58,Bachelors,14,62,42,45,18,2.0,4,23,Urban,Software Engineer,99553,0 +107819,Male,32,Masters,7,17,17,27,11,4.0,2,84,Urban,Manager,31236,0 +107820,Female,56,Diploma,12,84,90,26,26,9.0,3,29,Rural,Manager,95823,0 +107821,Male,42,Diploma,12,97,51,92,66,6.0,3,66,Semi-Urban,ML Engineer,87016,1 +107822,Male,50,Bachelors,10,96,67,1,50,8.0,3,95,Urban,Manager,78847,1 +107823,Male,51,High School,14,13,2,46,87,3.0,1,11,Urban,ML Engineer,41873,0 +107824,Male,28,Bachelors,0,15,62,24,19,3.0,3,66,Urban,ML Engineer,98384,0 +107825,Female,21,Masters,15,63,71,50,10,4.0,5,89,Urban,Manager,66472,1 +107826,Male,48,Diploma,4,30,35,62,5,4.0,3,79,Urban,ML Engineer,36338,0 +107827,Female,29,Diploma,16,47,88,3,38,7.0,4,54,Urban,ML Engineer,59941,0 +107828,Female,58,Masters,16,69,18,0,54,8.0,6,75,Urban,HR Executive,92702,0 +107829,Male,44,PhD,12,90,5,87,0,1.0,4,17,Urban,ML Engineer,85370,0 +107830,Other,32,Masters,12,10,91,98,92,9.0,6,69,Urban,ML Engineer,113157,1 +107831,Male,48,Bachelors,11,8,4,81,89,4.0,5,81,Urban,Manager,54874,0 +107832,Male,23,Bachelors,10,5,78,12,88,3.0,3,30,Urban,Software Engineer,137037,0 +107833,Other,58,High School,15,75,39,89,8,4.0,6,24,Semi-Urban,HR Executive,140150,0 +107834,Male,45,Bachelors,18,47,58,67,11,7.0,4,2,Semi-Urban,ML Engineer,50095,0 +107835,Female,35,PhD,1,35,69,73,31,1.0,0,14,Urban,ML Engineer,121064,0 +107836,Female,46,Bachelors,4,72,39,50,13,5.0,1,44,Semi-Urban,ML Engineer,44106,0 +107837,Female,37,Bachelors,5,45,47,61,59,8.0,4,70,Semi-Urban,ML Engineer,143073,0 +107838,Male,49,Bachelors,15,61,31,71,43,0.0,5,56,Rural,HR Executive,25713,0 +107839,Male,53,High School,11,82,21,48,82,9.0,5,18,Urban,ML Engineer,118513,0 +107840,Male,28,Diploma,2,65,25,71,8,8.0,5,66,Urban,Data Analyst,56794,0 +107841,Male,41,High School,0,30,93,96,83,6.0,4,80,Urban,Software Engineer,51980,1 +107842,Male,34,Diploma,15,20,37,3,49,5.0,3,76,Rural,HR Executive,127311,0 +107843,Male,45,Bachelors,16,36,45,77,1,4.0,5,55,Urban,ML Engineer,136327,0 +107844,Female,51,PhD,3,77,78,60,23,3.0,4,94,Urban,Data Analyst,92391,1 +107845,Other,43,Masters,16,63,10,84,49,4.0,4,96,Urban,ML Engineer,123285,1 +107846,Female,52,Bachelors,3,38,84,54,35,6.0,7,96,Urban,ML Engineer,109272,1 +107847,Male,45,High School,3,8,88,11,30,8.0,6,54,Semi-Urban,Manager,30798,0 +107848,Male,35,High School,1,83,94,22,30,5.0,4,72,Urban,Manager,45614,1 +107849,Other,26,Diploma,8,80,41,83,67,2.0,1,93,Urban,Software Engineer,87932,1 +107850,Male,31,High School,11,1,57,92,90,7.0,1,23,Rural,Software Engineer,80459,0 +107851,Male,26,Bachelors,18,27,81,44,20,1.0,6,24,Urban,Data Analyst,133635,0 +107852,Male,37,Masters,10,75,22,3,98,9.0,1,28,Semi-Urban,Manager,89931,0 +107853,Male,36,High School,11,14,87,26,71,1.0,4,39,Rural,Manager,81964,0 +107854,Male,58,Bachelors,2,37,22,61,33,1.0,4,71,Urban,Software Engineer,144585,0 +107855,Female,47,Diploma,2,78,67,19,56,1.0,6,63,Urban,ML Engineer,130512,0 +107856,Female,54,Bachelors,12,6,41,2,64,1.0,0,8,Urban,ML Engineer,120393,0 +107857,Female,45,High School,15,44,99,20,59,6.0,6,60,Urban,Manager,69039,0 +107858,Female,59,Bachelors,12,38,66,61,45,2.0,2,45,Rural,ML Engineer,115985,0 +107859,Male,36,Diploma,13,52,51,15,74,5.0,2,55,Urban,HR Executive,140651,0 +107860,Male,45,Masters,11,88,55,1,95,5.0,3,45,Urban,Data Analyst,54454,0 +107861,Male,25,Bachelors,7,51,55,80,81,2.0,2,71,Semi-Urban,ML Engineer,77998,1 +107862,Female,28,Bachelors,1,49,60,93,22,7.0,1,69,Rural,ML Engineer,22035,1 +107863,Male,46,Masters,19,57,41,20,15,4.0,7,34,Rural,ML Engineer,146341,0 +107864,Male,44,Diploma,15,72,64,44,41,3.0,3,93,Urban,ML Engineer,23952,1 +107865,Male,39,Diploma,12,88,0,44,72,1.0,0,90,Urban,Manager,124627,0 +107866,Male,21,Masters,4,81,86,37,72,9.0,6,22,Urban,ML Engineer,73105,0 +107867,Male,22,High School,8,49,48,67,56,1.0,6,0,Urban,Data Analyst,41169,0 +107868,Male,39,Bachelors,12,95,76,12,76,8.0,5,93,Semi-Urban,HR Executive,53005,1 +107869,Male,44,Masters,5,18,31,94,58,0.0,1,53,Urban,Data Analyst,75391,0 +107870,Male,26,Bachelors,2,28,19,87,61,6.0,4,6,Semi-Urban,ML Engineer,63358,0 +107871,Male,33,Bachelors,8,33,44,85,41,5.0,2,80,Rural,Manager,80042,1 +107872,Male,50,High School,17,3,78,53,84,8.0,0,78,Urban,Manager,110176,0 +107873,Male,30,Masters,9,6,31,90,18,6.0,3,20,Urban,Software Engineer,121761,0 +107874,Male,35,Masters,15,54,44,31,14,2.0,6,28,Urban,ML Engineer,60421,0 +107875,Male,35,Bachelors,2,69,32,42,41,5.0,5,10,Semi-Urban,ML Engineer,45304,0 +107876,Male,25,Bachelors,19,5,71,8,15,2.0,6,5,Urban,HR Executive,95851,0 +107877,Female,55,Diploma,0,32,75,17,24,2.0,6,88,Urban,Data Analyst,33084,0 +107878,Male,45,Diploma,5,31,51,2,35,2.0,1,96,Rural,Manager,76922,0 +107879,Male,57,Bachelors,7,52,63,40,20,9.0,3,14,Rural,Software Engineer,114871,0 +107880,Male,34,Diploma,10,69,4,9,37,5.0,7,67,Semi-Urban,ML Engineer,22154,0 +107881,Male,40,High School,2,2,29,18,95,4.0,6,96,Urban,Data Analyst,22766,0 +107882,Male,32,Bachelors,3,42,51,85,78,3.0,2,84,Urban,ML Engineer,65952,1 +107883,Female,33,Bachelors,7,29,1,63,91,2.0,7,42,Rural,Software Engineer,54933,0 +107884,Female,57,Bachelors,6,42,15,60,21,3.0,2,58,Urban,Manager,117822,0 +107885,Male,26,Masters,14,53,4,98,76,1.0,6,57,Urban,HR Executive,69094,0 +107886,Male,21,Bachelors,19,16,18,41,18,3.0,0,98,Semi-Urban,ML Engineer,91746,0 +107887,Female,25,Masters,15,13,61,16,49,1.0,2,33,Urban,Data Analyst,51400,0 +107888,Male,21,Bachelors,18,10,30,99,50,7.0,0,89,Urban,Software Engineer,45453,0 +107889,Other,53,Masters,7,11,88,77,39,2.0,0,62,Urban,Data Analyst,57460,0 +107890,Other,55,Bachelors,13,32,90,58,4,8.0,0,26,Semi-Urban,HR Executive,104179,0 +107891,Female,32,High School,17,64,21,95,53,6.0,0,9,Rural,Manager,100812,0 +107892,Male,57,Diploma,15,28,93,87,40,7.0,2,46,Urban,Software Engineer,96192,1 +107893,Female,25,Diploma,17,80,38,63,35,1.0,4,78,Urban,Manager,132174,1 +107894,Male,44,High School,12,28,87,51,83,7.0,5,70,Urban,HR Executive,72010,1 +107895,Female,27,PhD,7,44,50,80,36,2.0,5,9,Urban,ML Engineer,140374,0 +107896,Female,38,Diploma,0,2,64,49,51,5.0,4,48,Urban,Data Analyst,41380,0 +107897,Male,28,Masters,6,77,91,87,60,0.0,2,86,Urban,Manager,21271,1 +107898,Male,28,PhD,18,68,90,59,92,4.0,7,34,Urban,Manager,141314,1 +107899,Male,39,Bachelors,13,16,52,15,34,2.0,5,10,Urban,ML Engineer,53157,0 +107900,Female,33,Masters,9,15,94,70,71,4.0,3,94,Rural,Manager,41796,1 +107901,Female,22,Diploma,11,43,7,13,53,9.0,4,4,Urban,Manager,88385,0 +107902,Male,52,High School,1,61,41,46,7,8.0,6,9,Rural,Software Engineer,131547,0 +107903,Male,55,Bachelors,2,87,19,72,18,1.0,5,39,Urban,Software Engineer,84656,0 +107904,Other,59,High School,7,21,30,19,52,3.0,2,54,Urban,ML Engineer,58875,0 +107905,Male,23,High School,5,91,70,2,11,4.0,7,64,Urban,ML Engineer,38072,0 +107906,Male,54,PhD,1,30,35,82,43,5.0,1,99,Semi-Urban,Data Analyst,118758,1 +107907,Male,30,Masters,19,58,78,32,11,7.0,4,85,Semi-Urban,Data Analyst,130280,1 +107908,Other,56,Bachelors,15,89,77,10,13,5.0,3,4,Semi-Urban,Manager,46891,0 +107909,Male,36,Bachelors,15,82,82,82,89,5.0,1,25,Rural,ML Engineer,39715,1 +107910,Female,37,Bachelors,8,92,7,89,18,7.0,4,66,Urban,Software Engineer,48855,1 +107911,Male,33,Bachelors,1,94,47,8,36,8.0,5,23,Urban,ML Engineer,65994,0 +107912,Female,36,Masters,19,41,6,60,3,1.0,2,46,Rural,HR Executive,90201,0 +107913,Male,54,Diploma,0,86,29,99,22,6.0,5,15,Urban,ML Engineer,138940,0 +107914,Male,41,Diploma,10,10,86,79,63,7.0,1,64,Urban,Manager,53200,1 +107915,Female,41,Masters,12,74,62,16,53,9.0,6,7,Urban,ML Engineer,95920,0 +107916,Male,29,Diploma,0,32,46,21,59,7.0,1,21,Rural,Software Engineer,92705,0 +107917,Female,33,Bachelors,8,51,98,30,97,4.0,2,94,Urban,Data Analyst,89185,1 +107918,Male,31,Diploma,17,88,81,9,87,2.0,5,66,Semi-Urban,HR Executive,27408,1 +107919,Male,46,Bachelors,19,67,94,50,71,6.0,0,95,Semi-Urban,Software Engineer,60533,1 +107920,Female,56,Bachelors,3,7,2,2,20,9.0,1,60,Rural,Software Engineer,40191,0 +107921,Male,40,Bachelors,16,71,71,75,73,7.0,6,63,Urban,ML Engineer,84082,1 +107922,Male,38,Bachelors,7,41,89,56,38,4.0,2,99,Rural,HR Executive,37238,1 +107923,Male,46,Bachelors,19,56,9,47,88,1.0,4,69,Urban,ML Engineer,119311,0 +107924,Female,27,Masters,6,9,16,80,40,4.0,3,66,Semi-Urban,ML Engineer,21293,0 +107925,Male,33,Bachelors,16,27,79,67,6,7.0,0,67,Rural,Manager,78030,1 +107926,Female,50,Masters,19,42,74,16,33,7.0,7,17,Urban,Manager,33570,0 +107927,Female,38,Bachelors,15,24,45,82,79,5.0,5,28,Urban,Data Analyst,70819,0 +107928,Male,33,Bachelors,1,35,69,33,11,7.0,1,92,Urban,Software Engineer,149356,0 +107929,Male,50,Bachelors,15,38,9,83,77,3.0,3,84,Rural,Manager,65331,0 +107930,Female,35,PhD,5,14,47,2,64,5.0,7,15,Urban,ML Engineer,101412,0 +107931,Female,40,High School,6,44,96,82,28,3.0,5,99,Urban,Manager,55161,1 +107932,Female,21,Masters,3,23,3,55,23,6.0,2,83,Urban,Software Engineer,121966,0 +107933,Male,51,Bachelors,5,56,96,32,0,5.0,7,89,Urban,Software Engineer,41749,1 +107934,Male,28,High School,17,10,74,81,32,1.0,5,70,Urban,Data Analyst,97643,1 +107935,Male,52,Bachelors,12,27,65,67,59,3.0,1,93,Semi-Urban,Data Analyst,55608,1 +107936,Female,34,Masters,18,79,43,61,24,0.0,1,84,Rural,Manager,43647,1 +107937,Male,24,High School,6,73,87,70,2,9.0,2,59,Urban,HR Executive,82692,1 +107938,Male,37,Bachelors,19,47,79,51,83,4.0,6,71,Rural,ML Engineer,36529,1 +107939,Female,34,High School,2,63,63,69,95,4.0,7,71,Rural,Software Engineer,34204,1 +107940,Male,25,Diploma,9,60,94,91,65,6.0,7,98,Semi-Urban,Manager,148968,1 +107941,Male,57,High School,2,1,47,94,24,9.0,4,0,Rural,Software Engineer,133207,0 +107942,Female,43,Diploma,19,91,80,3,44,5.0,6,48,Urban,Software Engineer,141675,0 +107943,Male,36,Bachelors,1,9,65,68,78,5.0,5,71,Urban,Manager,60221,0 +107944,Male,51,Bachelors,8,41,19,88,66,5.0,5,81,Urban,Manager,145426,0 +107945,Male,39,High School,2,89,6,2,20,0.0,6,5,Semi-Urban,HR Executive,138908,0 +107946,Female,25,Diploma,13,14,42,57,36,9.0,2,69,Rural,Data Analyst,39954,0 +107947,Male,23,High School,18,1,41,57,90,6.0,4,10,Semi-Urban,Manager,78671,0 +107948,Male,34,Diploma,19,90,79,91,30,1.0,3,42,Rural,Software Engineer,149480,1 +107949,Male,35,PhD,0,79,45,60,57,8.0,5,35,Semi-Urban,HR Executive,72192,0 +107950,Male,52,High School,12,80,56,80,31,3.0,6,97,Rural,Data Analyst,72820,1 +107951,Female,29,Bachelors,18,58,21,13,51,1.0,1,88,Urban,HR Executive,74234,0 +107952,Other,32,Bachelors,11,84,90,18,66,7.0,2,20,Urban,Data Analyst,142807,0 +107953,Male,41,High School,16,95,54,24,81,9.0,3,99,Urban,Manager,130757,1 +107954,Male,24,Bachelors,18,28,29,67,90,9.0,3,30,Semi-Urban,HR Executive,69378,0 +107955,Female,59,High School,19,25,1,81,14,9.0,0,26,Urban,HR Executive,142617,0 +107956,Female,58,High School,4,14,76,57,59,8.0,6,53,Semi-Urban,Software Engineer,134449,0 +107957,Male,29,Bachelors,12,98,25,75,55,8.0,3,57,Semi-Urban,HR Executive,31075,1 +107958,Female,39,Bachelors,15,88,23,80,29,0.0,3,28,Urban,Manager,94667,0 +107959,Male,46,Masters,10,86,50,79,36,5.0,6,18,Semi-Urban,Data Analyst,146393,0 +107960,Other,51,PhD,12,26,35,10,1,3.0,1,24,Rural,Manager,143814,0 +107961,Male,49,Masters,3,98,23,16,56,0.0,4,98,Rural,Data Analyst,55051,1 +107962,Female,47,Diploma,14,25,62,96,10,3.0,6,24,Semi-Urban,ML Engineer,33275,0 +107963,Male,56,High School,6,22,89,32,93,2.0,7,33,Urban,Manager,40466,0 +107964,Female,31,Masters,15,64,28,78,1,7.0,7,87,Urban,Manager,90846,1 +107965,Female,29,Bachelors,4,12,63,56,22,4.0,7,0,Rural,HR Executive,137451,0 +107966,Male,40,Bachelors,11,74,83,23,71,8.0,7,73,Semi-Urban,Data Analyst,136938,1 +107967,Male,21,Masters,15,12,60,74,58,7.0,1,1,Urban,Data Analyst,141286,0 +107968,Male,31,Bachelors,12,4,22,62,40,1.0,2,92,Urban,HR Executive,99089,0 +107969,Male,22,Bachelors,18,8,2,4,47,4.0,2,44,Rural,ML Engineer,149781,0 +107970,Male,45,High School,19,19,66,58,13,3.0,7,66,Urban,ML Engineer,68885,0 +107971,Male,52,High School,5,12,60,18,9,7.0,4,52,Rural,Data Analyst,35769,0 +107972,Female,29,High School,10,46,65,23,72,7.0,2,74,Semi-Urban,ML Engineer,149957,0 +107973,Female,57,Diploma,19,83,45,69,43,2.0,6,98,Urban,Software Engineer,89757,1 +107974,Male,31,Bachelors,10,80,17,99,34,7.0,0,43,Semi-Urban,ML Engineer,119599,1 +107975,Female,41,Bachelors,3,99,75,68,52,8.0,3,77,Urban,HR Executive,25852,1 +107976,Male,35,Masters,9,48,67,69,58,5.0,6,5,Urban,Software Engineer,55235,0 +107977,Male,56,High School,13,51,51,40,5,0.0,0,20,Rural,HR Executive,130479,0 +107978,Male,58,Bachelors,16,32,25,28,61,2.0,6,53,Urban,HR Executive,125010,0 +107979,Male,41,Masters,10,93,84,26,93,3.0,7,37,Urban,Manager,146069,1 +107980,Male,48,Bachelors,8,26,19,73,57,7.0,7,57,Rural,Data Analyst,78670,0 +107981,Male,24,Masters,16,37,9,14,17,7.0,5,10,Urban,Software Engineer,123296,0 +107982,Male,30,High School,4,39,81,10,95,5.0,3,30,Semi-Urban,Manager,68767,0 +107983,Female,28,Bachelors,0,84,36,29,93,9.0,6,37,Urban,ML Engineer,136123,0 +107984,Male,22,Bachelors,19,77,74,58,63,4.0,7,15,Urban,HR Executive,113612,0 +107985,Male,44,Bachelors,14,79,55,72,61,3.0,2,32,Urban,ML Engineer,107005,1 +107986,Male,31,Diploma,10,50,91,33,84,6.0,2,66,Rural,Manager,149552,1 +107987,Male,41,High School,6,53,91,81,91,1.0,5,26,Urban,Manager,144665,1 +107988,Male,39,Bachelors,10,54,0,63,51,9.0,5,4,Urban,Manager,105183,0 +107989,Male,28,Diploma,13,21,15,66,53,9.0,4,76,Semi-Urban,Manager,43146,0 +107990,Male,33,Diploma,14,42,50,21,32,1.0,5,36,Semi-Urban,Manager,110364,0 +107991,Male,54,Bachelors,1,40,22,99,62,5.0,6,81,Urban,HR Executive,32085,1 +107992,Female,45,Bachelors,10,93,65,40,39,5.0,6,95,Urban,Data Analyst,64899,1 +107993,Male,47,Bachelors,4,76,77,1,74,1.0,2,32,Semi-Urban,HR Executive,134549,0 +107994,Male,44,Bachelors,10,80,31,78,3,9.0,5,84,Rural,ML Engineer,29910,1 +107995,Male,58,Bachelors,18,15,69,34,75,0.0,2,9,Urban,ML Engineer,146923,0 +107996,Female,57,Masters,7,85,29,66,15,7.0,4,6,Urban,Manager,27247,0 +107997,Female,58,Diploma,7,46,29,23,61,5.0,5,36,Rural,ML Engineer,69677,0 +107998,Female,44,Bachelors,7,87,11,82,9,9.0,5,29,Semi-Urban,ML Engineer,85058,0 +107999,Female,30,Diploma,9,70,0,35,40,5.0,3,12,Urban,Data Analyst,100465,0 +108000,Female,29,Masters,10,77,46,68,57,1.0,1,38,Urban,HR Executive,41581,0 +108001,Male,51,Diploma,7,55,86,50,46,3.0,2,33,Urban,Manager,80055,0 +108002,Male,42,Diploma,2,41,16,52,31,3.0,6,96,Urban,Manager,71299,0 +108003,Female,25,Bachelors,15,87,84,43,57,3.0,2,35,Urban,HR Executive,76988,1 +108004,Female,33,Bachelors,18,7,41,57,78,1.0,2,11,Semi-Urban,Data Analyst,85232,0 +108005,Female,26,Bachelors,12,44,67,7,92,4.0,5,75,Urban,ML Engineer,82941,0 +108006,Female,55,Masters,5,6,17,59,92,3.0,7,73,Semi-Urban,Software Engineer,142122,0 +108007,Male,38,Masters,18,59,75,2,10,0.0,2,90,Urban,Data Analyst,32055,0 +108008,Male,40,High School,1,82,58,79,50,4.0,1,3,Rural,ML Engineer,80381,0 +108009,Male,23,Masters,14,42,82,15,13,7.0,4,89,Urban,Manager,62067,0 +108010,Male,42,Masters,9,75,27,26,50,4.0,0,86,Rural,Data Analyst,149717,0 +108011,Male,45,Diploma,15,86,20,24,69,8.0,7,5,Semi-Urban,Manager,108920,0 +108012,Female,23,Bachelors,19,62,1,41,61,4.0,0,15,Rural,Manager,88528,0 +108013,Female,47,High School,7,13,62,23,32,8.0,1,75,Semi-Urban,Data Analyst,117200,0 +108014,Male,23,Bachelors,6,68,38,84,73,2.0,1,52,Semi-Urban,Manager,143062,1 +108015,Male,45,Bachelors,11,89,14,19,85,9.0,1,95,Urban,Data Analyst,110679,0 +108016,Male,30,Masters,1,95,59,43,63,8.0,2,0,Semi-Urban,HR Executive,137884,0 +108017,Male,51,Masters,12,72,74,82,65,7.0,0,66,Semi-Urban,Software Engineer,105039,1 +108018,Female,25,Diploma,7,32,98,94,17,9.0,1,81,Semi-Urban,ML Engineer,85781,1 +108019,Male,57,Bachelors,5,8,45,27,65,7.0,6,98,Urban,Manager,133527,0 +108020,Male,31,Diploma,19,78,71,30,76,6.0,3,93,Semi-Urban,Software Engineer,66553,1 +108021,Male,30,Bachelors,8,46,73,40,25,2.0,1,29,Urban,HR Executive,86976,0 +108022,Male,34,Bachelors,15,84,8,1,39,8.0,1,92,Urban,ML Engineer,133639,0 +108023,Male,37,Diploma,3,79,81,43,29,3.0,1,20,Urban,ML Engineer,124815,0 +108024,Female,30,Diploma,8,55,44,62,19,9.0,0,3,Urban,ML Engineer,91208,0 +108025,Male,38,Bachelors,8,43,0,3,46,0.0,2,78,Semi-Urban,ML Engineer,143245,0 +108026,Female,36,High School,3,15,83,88,39,0.0,1,72,Urban,HR Executive,50213,1 +108027,Female,26,Bachelors,3,4,44,84,9,5.0,5,78,Semi-Urban,HR Executive,97773,0 +108028,Female,37,Bachelors,15,89,62,1,52,6.0,7,21,Semi-Urban,ML Engineer,148448,0 +108029,Male,37,Diploma,2,56,54,72,30,3.0,2,53,Semi-Urban,ML Engineer,34425,1 +108030,Male,26,High School,14,38,65,80,79,1.0,4,68,Semi-Urban,Software Engineer,85008,1 +108031,Male,58,Diploma,0,41,41,83,16,6.0,4,85,Urban,Software Engineer,44544,1 +108032,Female,28,Diploma,17,84,48,41,34,8.0,2,58,Urban,Manager,129116,0 +108033,Female,28,Bachelors,4,44,78,94,78,5.0,3,14,Urban,HR Executive,25143,0 +108034,Male,32,Bachelors,5,31,28,80,31,3.0,1,64,Urban,Data Analyst,51760,0 +108035,Male,37,High School,0,65,31,6,46,2.0,4,16,Urban,ML Engineer,144506,0 +108036,Male,36,High School,13,91,31,61,46,0.0,7,6,Urban,ML Engineer,60359,0 +108037,Male,27,Masters,1,60,93,27,16,3.0,4,89,Urban,Data Analyst,103287,1 +108038,Female,42,High School,16,38,83,12,29,8.0,5,60,Rural,Data Analyst,32796,0 +108039,Male,48,Bachelors,0,82,35,24,45,8.0,5,16,Semi-Urban,Data Analyst,109703,0 +108040,Female,33,Bachelors,9,56,48,39,75,4.0,6,57,Urban,Data Analyst,108587,0 +108041,Other,38,High School,12,25,12,59,21,8.0,0,35,Urban,Software Engineer,77524,0 +108042,Male,49,Diploma,3,35,38,7,9,0.0,7,68,Urban,Manager,53632,0 +108043,Male,42,Bachelors,16,14,59,9,8,7.0,2,98,Rural,HR Executive,148659,0 +108044,Female,51,Diploma,13,66,67,56,23,3.0,6,89,Rural,Software Engineer,57388,1 +108045,Female,29,Bachelors,17,25,28,24,25,9.0,2,71,Urban,Software Engineer,57788,0 +108046,Male,29,Masters,8,30,45,76,79,3.0,2,15,Urban,HR Executive,48457,0 +108047,Other,38,PhD,7,83,20,25,14,0.0,7,21,Urban,Data Analyst,48005,0 +108048,Female,57,Bachelors,17,40,95,80,29,4.0,4,13,Urban,Manager,141108,0 +108049,Male,46,Bachelors,19,42,13,1,33,8.0,3,68,Urban,HR Executive,63374,0 +108050,Male,35,Bachelors,16,76,0,60,34,7.0,1,33,Rural,ML Engineer,24815,0 +108051,Male,37,Diploma,12,29,82,53,75,8.0,6,74,Urban,HR Executive,140287,1 +108052,Female,33,Bachelors,11,15,85,93,77,2.0,5,74,Semi-Urban,HR Executive,42401,1 +108053,Male,50,Masters,19,17,7,81,53,9.0,5,48,Urban,Software Engineer,72258,0 +108054,Male,56,Diploma,14,15,18,93,50,7.0,3,73,Urban,Manager,60594,0 +108055,Male,47,Masters,8,78,2,7,94,1.0,0,77,Urban,HR Executive,81555,0 +108056,Female,24,Bachelors,16,38,86,16,15,4.0,2,23,Rural,Software Engineer,85373,0 +108057,Female,36,Bachelors,0,6,71,19,42,2.0,5,23,Rural,ML Engineer,59357,0 +108058,Female,26,Bachelors,0,52,90,62,98,2.0,7,2,Rural,Software Engineer,109969,0 +108059,Female,45,Bachelors,12,94,20,5,67,1.0,2,77,Urban,Data Analyst,34883,0 +108060,Other,56,PhD,8,98,14,40,4,6.0,4,14,Urban,Data Analyst,90201,0 +108061,Male,58,Diploma,15,43,63,96,60,9.0,3,99,Semi-Urban,HR Executive,106179,1 +108062,Female,54,High School,18,66,70,61,69,4.0,7,44,Semi-Urban,Manager,138189,1 +108063,Female,55,High School,5,87,60,23,4,2.0,6,21,Semi-Urban,Data Analyst,51419,0 +108064,Female,36,Bachelors,14,80,8,70,52,7.0,5,22,Rural,ML Engineer,130649,0 +108065,Male,29,Bachelors,7,49,16,77,95,6.0,6,52,Rural,Software Engineer,92376,0 +108066,Female,48,Bachelors,8,9,92,42,66,2.0,4,61,Urban,HR Executive,138383,0 +108067,Male,21,Diploma,10,92,96,8,75,0.0,1,77,Urban,Data Analyst,109044,1 +108068,Male,26,Bachelors,4,20,66,57,36,9.0,1,82,Semi-Urban,ML Engineer,64683,0 +108069,Other,25,Diploma,0,9,97,97,14,4.0,3,13,Urban,Software Engineer,22999,0 +108070,Female,31,Bachelors,15,13,0,86,7,3.0,7,13,Urban,ML Engineer,47293,0 +108071,Female,35,Masters,12,56,22,89,85,5.0,6,28,Urban,Data Analyst,71696,0 +108072,Male,51,Diploma,16,66,66,19,97,4.0,6,82,Urban,Manager,125960,0 +108073,Female,53,Bachelors,6,64,94,42,1,3.0,3,88,Semi-Urban,Data Analyst,35360,1 +108074,Female,37,Bachelors,3,58,14,18,55,3.0,7,55,Semi-Urban,Data Analyst,53470,0 +108075,Male,32,Diploma,11,86,63,25,98,3.0,7,98,Semi-Urban,Software Engineer,24274,1 +108076,Male,43,Bachelors,14,5,36,57,74,2.0,5,20,Urban,Software Engineer,131295,0 +108077,Female,43,Bachelors,2,71,95,89,65,7.0,1,52,Semi-Urban,Manager,103097,1 +108078,Female,39,Masters,17,48,36,9,36,6.0,3,40,Rural,ML Engineer,21767,0 +108079,Male,21,Diploma,9,24,66,97,64,0.0,7,67,Urban,Software Engineer,29911,1 +108080,Male,58,Masters,2,70,49,55,27,4.0,2,19,Rural,HR Executive,44757,0 +108081,Male,25,High School,14,34,1,68,4,6.0,0,87,Rural,Software Engineer,134449,0 +108082,Male,48,Bachelors,17,71,89,48,16,0.0,7,53,Urban,Software Engineer,107952,1 +108083,Male,53,Masters,2,68,94,94,60,1.0,3,53,Rural,HR Executive,121138,1 +108084,Other,32,Diploma,7,32,32,14,10,2.0,7,52,Semi-Urban,Data Analyst,144951,0 +108085,Male,38,Masters,9,2,90,76,91,8.0,2,42,Urban,ML Engineer,45775,0 +108086,Male,51,Diploma,12,60,13,4,56,4.0,0,32,Urban,Data Analyst,119123,0 +108087,Other,55,Diploma,15,89,34,13,22,7.0,0,69,Urban,Data Analyst,60336,0 +108088,Male,27,Bachelors,9,38,79,74,31,6.0,0,23,Rural,HR Executive,27037,0 +108089,Female,43,PhD,8,58,14,63,77,9.0,1,62,Urban,ML Engineer,67177,0 +108090,Other,52,Bachelors,10,13,32,79,6,8.0,3,80,Urban,ML Engineer,122127,0 +108091,Female,26,Diploma,11,19,20,74,88,9.0,2,90,Rural,Data Analyst,71052,0 +108092,Female,53,Bachelors,13,4,25,11,92,4.0,7,11,Semi-Urban,Manager,144414,0 +108093,Male,26,Masters,0,93,87,71,32,5.0,5,97,Rural,HR Executive,141065,1 +108094,Male,50,High School,8,10,12,49,99,4.0,0,50,Urban,HR Executive,100616,0 +108095,Other,33,Diploma,3,46,12,11,60,5.0,2,62,Urban,Data Analyst,128498,0 +108096,Male,37,Bachelors,2,58,79,97,11,7.0,0,50,Semi-Urban,HR Executive,65357,1 +108097,Female,29,High School,9,74,21,62,24,5.0,1,33,Semi-Urban,Data Analyst,58021,0 +108098,Male,42,Bachelors,15,73,66,35,72,6.0,1,88,Urban,ML Engineer,137317,1 +108099,Female,35,Bachelors,13,0,36,19,87,9.0,4,49,Urban,ML Engineer,100486,0 +108100,Male,51,Bachelors,1,33,32,61,48,4.0,7,58,Urban,Data Analyst,105393,0 +108101,Male,34,Masters,3,46,79,9,13,3.0,5,24,Urban,Manager,111860,0 +108102,Female,36,Diploma,0,59,26,26,62,8.0,0,75,Urban,Data Analyst,110214,0 +108103,Male,25,Bachelors,13,52,62,91,45,8.0,0,60,Semi-Urban,HR Executive,84608,1 +108104,Male,26,Masters,18,50,20,11,47,6.0,0,8,Urban,ML Engineer,80872,0 +108105,Female,22,Bachelors,9,11,55,91,41,8.0,6,88,Rural,ML Engineer,55331,1 +108106,Other,58,Bachelors,3,7,15,32,54,5.0,5,65,Urban,HR Executive,86605,0 +108107,Female,46,Masters,4,58,65,30,6,7.0,0,37,Urban,HR Executive,81136,0 +108108,Male,34,PhD,9,70,20,85,35,1.0,1,82,Urban,HR Executive,121271,1 +108109,Female,27,Bachelors,19,10,79,31,12,3.0,7,35,Rural,ML Engineer,42701,0 +108110,Male,36,Bachelors,7,45,35,66,43,9.0,7,75,Semi-Urban,Data Analyst,44886,0 +108111,Female,54,Masters,10,54,98,44,29,9.0,7,73,Urban,Data Analyst,86228,1 +108112,Female,42,Diploma,3,74,45,36,49,8.0,4,62,Urban,ML Engineer,27173,0 +108113,Female,43,Diploma,11,77,14,8,18,1.0,6,49,Urban,HR Executive,38954,0 +108114,Female,51,PhD,1,53,68,33,75,0.0,4,92,Urban,ML Engineer,24467,1 +108115,Female,25,PhD,10,11,46,68,78,7.0,2,97,Urban,HR Executive,128580,0 +108116,Male,51,Bachelors,9,67,42,43,53,6.0,4,97,Rural,Manager,72437,1 +108117,Male,47,Diploma,14,66,58,83,49,7.0,0,16,Semi-Urban,Data Analyst,115001,0 +108118,Male,38,Bachelors,9,13,86,14,75,5.0,1,78,Semi-Urban,Software Engineer,81682,0 +108119,Male,36,Masters,0,35,17,40,97,0.0,0,29,Urban,HR Executive,80145,0 +108120,Female,37,High School,3,20,61,79,9,4.0,1,42,Rural,Manager,80100,0 +108121,Female,37,Bachelors,19,33,33,48,28,9.0,2,38,Urban,Software Engineer,31749,0 +108122,Male,26,Diploma,3,57,42,56,85,9.0,1,32,Rural,Software Engineer,56137,0 +108123,Male,43,Bachelors,18,6,67,34,80,7.0,4,24,Urban,HR Executive,122811,0 +108124,Male,55,Bachelors,5,22,1,13,44,0.0,1,40,Urban,HR Executive,44821,0 +108125,Male,22,Diploma,2,72,34,54,36,1.0,2,54,Urban,Data Analyst,63053,0 +108126,Male,21,Bachelors,11,54,4,57,0,1.0,7,91,Urban,Manager,140097,0 +108127,Male,27,Bachelors,8,91,73,42,45,8.0,4,81,Urban,Data Analyst,84309,1 +108128,Male,31,Bachelors,4,47,80,95,95,3.0,0,99,Rural,HR Executive,110716,1 +108129,Female,58,PhD,4,57,10,34,34,1.0,1,56,Urban,Software Engineer,105532,0 +108130,Male,41,High School,0,9,34,98,33,0.0,2,74,Rural,ML Engineer,80711,0 +108131,Female,54,Masters,7,61,50,39,98,7.0,4,51,Urban,Data Analyst,27004,0 +108132,Male,57,PhD,15,35,94,4,90,5.0,3,36,Urban,HR Executive,128209,0 +108133,Male,49,Diploma,12,24,61,9,7,9.0,1,50,Urban,Data Analyst,53353,0 +108134,Female,29,Bachelors,6,43,79,44,98,4.0,7,68,Urban,Manager,23057,0 +108135,Male,28,Bachelors,1,60,34,70,86,5.0,7,61,Semi-Urban,Manager,51627,0 +108136,Female,36,High School,0,86,96,44,44,0.0,4,76,Rural,Data Analyst,98739,1 +108137,Male,43,Bachelors,12,38,95,61,13,3.0,5,18,Urban,Manager,105395,0 +108138,Other,36,High School,5,70,28,57,44,4.0,5,38,Semi-Urban,HR Executive,24410,0 +108139,Female,38,Masters,6,81,47,44,74,6.0,4,0,Rural,HR Executive,31699,0 +108140,Female,47,Bachelors,13,14,58,1,86,8.0,4,4,Rural,Data Analyst,130883,0 +108141,Female,34,Masters,2,14,47,63,0,5.0,5,57,Urban,Data Analyst,66688,0 +108142,Male,29,Bachelors,18,86,0,86,50,3.0,7,13,Urban,HR Executive,142728,0 +108143,Male,28,Bachelors,5,30,51,77,12,5.0,3,82,Semi-Urban,Data Analyst,59985,1 +108144,Male,52,Bachelors,14,89,62,24,0,2.0,2,45,Urban,Manager,118265,0 +108145,Male,50,High School,15,44,33,89,26,5.0,2,36,Semi-Urban,Manager,25139,0 +108146,Male,21,Diploma,7,45,10,76,98,3.0,7,22,Urban,ML Engineer,30264,0 +108147,Female,29,Bachelors,8,67,35,73,6,6.0,1,62,Urban,ML Engineer,62890,0 +108148,Male,36,Bachelors,17,20,73,72,97,7.0,3,78,Semi-Urban,Data Analyst,118369,1 +108149,Male,26,Bachelors,10,38,8,80,25,3.0,2,28,Urban,Software Engineer,30739,0 +108150,Male,33,High School,6,32,38,9,6,5.0,1,11,Urban,Manager,124476,0 +108151,Male,23,Bachelors,3,41,83,58,29,1.0,2,91,Urban,ML Engineer,34335,1 +108152,Male,41,Diploma,2,54,53,85,56,8.0,2,23,Urban,Manager,130435,0 +108153,Female,40,Diploma,10,25,89,74,70,5.0,5,67,Semi-Urban,Data Analyst,63683,1 +108154,Male,52,Bachelors,2,28,9,11,7,9.0,6,65,Rural,Data Analyst,81280,0 +108155,Male,22,Masters,7,85,64,30,95,8.0,2,24,Urban,Software Engineer,139346,0 +108156,Female,59,Bachelors,9,96,66,38,42,3.0,2,15,Semi-Urban,Software Engineer,131507,0 +108157,Female,53,High School,13,4,76,33,50,2.0,0,59,Rural,Data Analyst,62428,0 +108158,Male,56,Bachelors,2,57,92,35,40,9.0,6,63,Rural,Data Analyst,117657,1 +108159,Female,35,Bachelors,6,55,74,21,42,6.0,6,98,Semi-Urban,HR Executive,89161,1 +108160,Other,41,Diploma,9,81,65,46,37,5.0,5,29,Semi-Urban,Manager,117025,0 +108161,Male,51,Masters,11,28,9,42,80,1.0,1,32,Semi-Urban,Data Analyst,70878,0 +108162,Female,37,Bachelors,4,93,50,99,47,6.0,6,85,Urban,Software Engineer,75136,1 +108163,Male,58,Bachelors,5,77,77,44,78,0.0,0,97,Rural,HR Executive,134819,1 +108164,Female,38,Masters,7,4,67,79,81,8.0,6,52,Rural,Software Engineer,138569,0 +108165,Female,48,Diploma,0,44,52,78,40,7.0,5,67,Urban,Software Engineer,60355,1 +108166,Female,55,Bachelors,17,80,33,36,48,3.0,5,43,Semi-Urban,Data Analyst,148084,0 +108167,Female,34,Bachelors,4,53,43,76,80,9.0,5,15,Urban,Manager,52199,0 +108168,Female,27,Diploma,11,35,93,51,26,4.0,3,44,Semi-Urban,Software Engineer,64206,0 +108169,Male,25,Bachelors,14,50,60,79,4,9.0,0,76,Urban,ML Engineer,93649,1 +108170,Female,41,Bachelors,6,16,48,53,45,2.0,1,2,Urban,Manager,133330,0 +108171,Male,26,PhD,16,44,70,1,6,5.0,1,53,Urban,ML Engineer,72318,0 +108172,Other,52,Bachelors,3,45,37,44,39,8.0,0,31,Semi-Urban,ML Engineer,64499,0 +108173,Male,58,High School,18,23,77,38,95,7.0,2,36,Urban,Manager,149763,0 +108174,Male,47,Masters,2,62,1,73,33,0.0,3,71,Semi-Urban,ML Engineer,42764,0 +108175,Male,28,Diploma,8,41,63,89,74,0.0,5,47,Urban,Data Analyst,73314,1 +108176,Female,40,Bachelors,19,13,30,92,5,7.0,5,61,Urban,Software Engineer,141593,0 +108177,Female,37,Masters,19,20,85,56,89,5.0,0,18,Rural,Data Analyst,74794,0 +108178,Male,33,PhD,10,38,3,22,77,0.0,6,60,Rural,Software Engineer,137582,0 +108179,Male,43,Diploma,14,61,45,54,36,2.0,0,62,Rural,Manager,45723,0 +108180,Male,52,PhD,12,38,78,72,51,4.0,3,22,Urban,Software Engineer,138545,0 +108181,Female,39,Bachelors,11,6,94,34,29,7.0,3,7,Semi-Urban,Manager,58768,0 +108182,Male,34,Masters,16,58,44,1,49,5.0,4,2,Semi-Urban,Manager,27648,0 +108183,Male,37,Bachelors,4,95,23,39,83,1.0,5,78,Semi-Urban,Manager,144305,1 +108184,Male,58,Bachelors,6,82,31,27,53,0.0,1,95,Rural,HR Executive,145179,1 +108185,Male,59,Diploma,17,39,44,64,62,6.0,2,70,Urban,ML Engineer,31066,0 +108186,Female,27,Diploma,7,29,35,66,85,7.0,6,89,Urban,HR Executive,76092,0 +108187,Other,21,Masters,10,24,36,80,46,9.0,6,61,Urban,Manager,37937,0 +108188,Male,36,High School,8,52,95,65,19,3.0,4,45,Rural,Data Analyst,21583,1 +108189,Male,24,High School,3,51,98,35,58,7.0,0,8,Urban,Software Engineer,27250,0 +108190,Male,39,Bachelors,9,65,5,70,50,0.0,0,42,Urban,Data Analyst,69197,0 +108191,Male,34,PhD,13,72,44,64,63,3.0,6,86,Rural,Manager,97445,1 +108192,Female,28,High School,16,7,39,58,50,0.0,3,94,Semi-Urban,Software Engineer,113577,0 +108193,Male,54,Bachelors,0,49,12,8,70,2.0,3,47,Urban,Manager,91750,0 +108194,Male,43,Diploma,17,84,95,33,30,9.0,6,96,Semi-Urban,Software Engineer,97151,1 +108195,Male,43,Diploma,5,12,93,65,97,7.0,7,90,Rural,ML Engineer,41299,1 +108196,Male,45,Diploma,13,85,53,72,69,0.0,7,16,Semi-Urban,Data Analyst,128782,0 +108197,Male,50,PhD,15,40,96,63,8,4.0,5,90,Urban,HR Executive,49576,1 +108198,Male,23,Masters,17,88,90,6,95,8.0,6,53,Rural,Software Engineer,65185,1 +108199,Other,46,Diploma,4,75,46,53,79,1.0,2,62,Urban,ML Engineer,125018,0 +108200,Male,36,Diploma,13,39,17,24,0,6.0,3,42,Urban,Data Analyst,27145,0 +108201,Male,57,Masters,0,36,33,90,24,4.0,1,58,Urban,ML Engineer,73588,0 +108202,Male,41,Diploma,6,44,52,31,10,2.0,3,6,Urban,Manager,63715,0 +108203,Male,57,Bachelors,3,55,99,23,66,1.0,2,4,Urban,Data Analyst,47975,0 +108204,Female,46,High School,18,24,37,66,82,4.0,3,72,Rural,Software Engineer,20454,0 +108205,Female,29,Masters,19,31,42,96,68,0.0,6,54,Rural,Data Analyst,131724,0 +108206,Female,48,Diploma,5,39,74,5,79,7.0,6,45,Urban,Software Engineer,128740,0 +108207,Male,53,Masters,10,64,68,39,4,6.0,0,77,Urban,Data Analyst,84197,1 +108208,Female,44,Diploma,18,30,93,71,81,7.0,4,59,Urban,ML Engineer,146287,1 +108209,Male,46,Bachelors,6,96,96,34,20,5.0,7,95,Urban,Manager,106057,1 +108210,Female,52,PhD,19,65,13,96,36,1.0,3,31,Semi-Urban,HR Executive,22885,0 +108211,Other,29,Bachelors,2,88,20,69,37,2.0,6,21,Urban,ML Engineer,37428,0 +108212,Male,58,High School,3,86,73,53,30,3.0,3,65,Semi-Urban,Manager,127662,1 +108213,Male,40,Bachelors,0,20,79,44,16,6.0,7,39,Rural,HR Executive,128034,0 +108214,Male,58,High School,2,86,96,27,44,1.0,1,33,Semi-Urban,ML Engineer,81965,1 +108215,Male,34,Masters,8,51,11,33,65,8.0,1,1,Semi-Urban,Software Engineer,109890,0 +108216,Female,47,Bachelors,6,11,36,47,86,3.0,4,47,Semi-Urban,Manager,146051,0 +108217,Female,32,Bachelors,7,17,96,69,67,6.0,7,96,Rural,HR Executive,77517,1 +108218,Male,21,Bachelors,0,12,22,27,45,7.0,7,25,Semi-Urban,Software Engineer,108261,0 +108219,Female,52,Bachelors,4,93,24,24,82,3.0,5,33,Urban,HR Executive,48461,0 +108220,Male,32,Diploma,14,43,77,59,59,0.0,6,16,Urban,ML Engineer,140771,0 +108221,Male,56,Masters,10,30,48,62,87,9.0,2,55,Urban,Data Analyst,67121,0 +108222,Male,53,Bachelors,4,42,67,3,32,3.0,6,87,Urban,ML Engineer,79677,0 +108223,Male,43,Bachelors,11,6,53,38,47,4.0,5,68,Semi-Urban,ML Engineer,118124,0 +108224,Male,28,High School,15,36,69,52,54,4.0,5,29,Urban,HR Executive,122027,0 +108225,Female,33,Bachelors,12,32,15,4,55,2.0,1,51,Rural,Data Analyst,23081,0 +108226,Female,58,Masters,19,80,17,11,74,5.0,2,86,Urban,Data Analyst,61854,0 +108227,Female,40,Bachelors,2,27,78,45,67,5.0,2,97,Urban,Manager,23664,1 +108228,Female,42,High School,2,4,60,9,76,7.0,4,83,Urban,Data Analyst,53006,0 +108229,Male,23,High School,7,34,91,42,73,9.0,4,88,Semi-Urban,Software Engineer,132789,1 +108230,Male,54,Diploma,2,7,26,99,41,0.0,3,33,Semi-Urban,ML Engineer,64226,0 +108231,Male,54,High School,9,88,67,38,62,8.0,0,37,Semi-Urban,ML Engineer,64279,0 +108232,Male,37,High School,14,5,22,14,95,7.0,0,48,Semi-Urban,Manager,52003,0 +108233,Other,46,Bachelors,15,45,1,0,32,3.0,7,46,Semi-Urban,ML Engineer,38803,0 +108234,Female,46,Diploma,8,65,3,29,78,4.0,4,98,Rural,Data Analyst,77684,0 +108235,Male,31,Diploma,19,62,82,62,33,0.0,3,96,Semi-Urban,Software Engineer,135041,1 +108236,Male,26,Bachelors,16,96,80,90,9,4.0,0,47,Urban,ML Engineer,118177,1 +108237,Female,49,Diploma,14,55,16,46,96,6.0,6,74,Semi-Urban,Data Analyst,33984,0 +108238,Male,25,Bachelors,1,77,57,84,57,2.0,4,42,Urban,HR Executive,116944,1 +108239,Male,35,Bachelors,4,12,86,19,86,2.0,4,12,Semi-Urban,Manager,42128,0 +108240,Female,50,Masters,3,45,92,69,91,8.0,0,6,Urban,ML Engineer,83926,0 +108241,Female,27,Masters,11,90,29,40,89,0.0,2,20,Urban,HR Executive,29325,0 +108242,Female,58,Diploma,10,75,27,66,85,2.0,5,75,Urban,Software Engineer,88651,1 +108243,Female,23,Bachelors,13,56,6,8,1,6.0,7,87,Urban,Data Analyst,53113,0 +108244,Male,45,Masters,2,79,15,78,31,0.0,3,17,Semi-Urban,ML Engineer,97753,0 +108245,Male,26,Bachelors,6,50,60,72,41,0.0,4,28,Urban,HR Executive,146834,0 +108246,Male,37,Diploma,13,89,40,90,46,1.0,4,85,Urban,Data Analyst,127046,1 +108247,Male,38,Diploma,3,74,19,42,26,5.0,3,93,Rural,Software Engineer,129524,0 +108248,Female,24,Masters,12,70,12,86,3,1.0,0,88,Urban,HR Executive,110097,1 +108249,Other,56,Diploma,1,62,18,2,89,0.0,3,0,Urban,HR Executive,66954,0 +108250,Male,41,Bachelors,4,80,73,74,67,0.0,5,39,Semi-Urban,ML Engineer,118962,1 +108251,Female,23,Bachelors,2,10,8,97,80,6.0,4,86,Urban,Manager,136328,0 +108252,Other,24,Bachelors,11,53,70,50,17,0.0,2,93,Urban,ML Engineer,77238,1 +108253,Male,36,Diploma,7,10,40,1,51,5.0,5,32,Urban,Software Engineer,68996,0 +108254,Male,44,Bachelors,3,24,71,12,58,5.0,1,11,Urban,HR Executive,130567,0 +108255,Male,26,Diploma,15,54,90,3,95,1.0,4,86,Urban,Data Analyst,52844,0 +108256,Male,52,Bachelors,19,16,59,9,31,2.0,7,37,Urban,HR Executive,96791,0 +108257,Other,35,Diploma,16,38,18,38,4,6.0,7,45,Rural,Manager,31471,0 +108258,Male,48,Bachelors,7,39,22,69,30,1.0,6,53,Rural,Manager,77161,0 +108259,Male,27,Masters,14,11,72,59,28,2.0,5,55,Semi-Urban,ML Engineer,75796,0 +108260,Female,58,Diploma,18,46,47,48,89,8.0,2,78,Rural,HR Executive,80264,0 +108261,Female,43,Masters,3,29,67,21,19,3.0,5,23,Urban,Manager,147352,0 +108262,Male,45,Diploma,16,83,19,34,50,4.0,1,20,Semi-Urban,HR Executive,144406,0 +108263,Male,47,Diploma,7,25,43,15,72,6.0,1,45,Urban,Data Analyst,99189,0 +108264,Male,29,Diploma,19,10,74,56,57,9.0,4,87,Urban,Manager,130522,0 +108265,Male,54,Diploma,2,11,42,6,38,1.0,6,20,Urban,Software Engineer,64710,0 +108266,Male,39,Diploma,13,36,51,49,45,7.0,6,30,Urban,Data Analyst,52108,0 +108267,Female,38,Masters,10,31,52,25,59,1.0,5,77,Urban,Software Engineer,107859,0 +108268,Female,54,Masters,2,1,3,93,42,5.0,6,90,Rural,HR Executive,42399,0 +108269,Male,29,Bachelors,14,65,23,97,8,2.0,0,68,Semi-Urban,Data Analyst,102375,1 +108270,Male,31,Bachelors,16,95,41,42,39,9.0,3,61,Semi-Urban,Manager,109452,1 +108271,Male,33,High School,19,68,36,94,35,1.0,3,87,Urban,Data Analyst,131793,1 +108272,Female,27,Bachelors,15,93,21,73,76,2.0,3,87,Urban,HR Executive,104157,1 +108273,Male,22,Bachelors,12,47,86,59,42,3.0,3,48,Rural,ML Engineer,23116,1 +108274,Male,34,High School,4,1,77,84,99,3.0,2,36,Urban,Data Analyst,126017,0 +108275,Female,43,Bachelors,6,69,77,15,48,9.0,3,20,Rural,Data Analyst,104344,0 +108276,Female,52,Masters,11,55,52,57,81,6.0,4,29,Urban,ML Engineer,106400,0 +108277,Male,58,Diploma,18,80,63,87,75,5.0,5,70,Semi-Urban,Software Engineer,66868,1 +108278,Female,53,High School,0,49,33,40,32,8.0,4,56,Urban,ML Engineer,37854,0 +108279,Female,55,Bachelors,2,44,15,83,22,9.0,1,99,Rural,Data Analyst,39090,1 +108280,Male,24,High School,16,4,49,75,80,2.0,2,47,Urban,Software Engineer,82808,0 +108281,Male,35,Bachelors,11,42,90,36,35,6.0,4,0,Urban,Data Analyst,111256,0 +108282,Male,43,Bachelors,19,18,83,38,95,4.0,6,62,Urban,HR Executive,103858,0 +108283,Male,50,Bachelors,10,62,41,45,34,8.0,3,45,Urban,Manager,87002,0 +108284,Male,59,PhD,15,91,17,89,63,6.0,4,77,Rural,Data Analyst,27099,1 +108285,Male,52,Masters,12,21,16,86,68,6.0,6,79,Urban,Manager,83603,0 +108286,Female,28,Diploma,3,77,71,1,70,0.0,6,9,Urban,ML Engineer,115675,0 +108287,Male,41,Bachelors,1,89,16,23,31,5.0,0,56,Urban,Data Analyst,94000,0 +108288,Male,53,Bachelors,1,84,65,29,66,4.0,4,51,Urban,Data Analyst,135424,0 +108289,Male,49,Bachelors,16,27,73,43,20,4.0,4,30,Urban,Software Engineer,112665,0 +108290,Female,36,Diploma,16,35,5,13,47,9.0,2,89,Rural,HR Executive,75900,0 +108291,Male,45,Masters,13,83,30,31,60,4.0,1,12,Rural,Software Engineer,35559,0 +108292,Male,48,Bachelors,17,80,18,26,4,5.0,5,15,Urban,HR Executive,96927,0 +108293,Female,49,Bachelors,13,89,51,19,68,2.0,5,11,Semi-Urban,Data Analyst,48884,0 +108294,Male,52,Bachelors,16,47,58,21,81,3.0,3,66,Urban,ML Engineer,52253,0 +108295,Female,46,Bachelors,9,45,92,61,82,5.0,1,47,Urban,Manager,124762,1 +108296,Female,55,Diploma,3,69,85,5,14,7.0,2,2,Urban,Software Engineer,136661,0 +108297,Male,28,Diploma,11,3,70,34,56,6.0,0,73,Urban,Manager,84161,0 +108298,Male,45,Diploma,13,52,64,19,89,2.0,5,97,Rural,ML Engineer,54330,0 +108299,Male,21,High School,13,54,4,23,43,2.0,6,22,Urban,Data Analyst,32209,0 +108300,Female,31,Bachelors,9,14,39,0,60,9.0,2,55,Urban,ML Engineer,132266,0 +108301,Other,32,PhD,5,23,52,67,79,7.0,7,26,Semi-Urban,HR Executive,50501,0 +108302,Male,26,Masters,2,10,76,75,95,6.0,4,65,Semi-Urban,ML Engineer,137564,0 +108303,Male,27,Bachelors,17,97,39,58,53,8.0,6,3,Semi-Urban,Manager,117888,0 +108304,Male,55,Diploma,10,69,44,84,2,3.0,0,37,Urban,HR Executive,45884,0 +108305,Other,37,Diploma,17,67,3,22,85,0.0,1,13,Urban,HR Executive,43984,0 +108306,Female,54,Bachelors,7,44,32,22,89,4.0,5,28,Urban,Manager,102324,0 +108307,Female,44,Bachelors,18,37,17,94,15,4.0,7,19,Semi-Urban,Manager,130461,0 +108308,Male,25,Bachelors,15,48,23,64,29,4.0,4,8,Urban,Manager,54149,0 +108309,Male,58,Masters,7,19,10,1,86,9.0,6,83,Rural,Data Analyst,63652,0 +108310,Other,44,Bachelors,9,77,81,58,13,9.0,4,71,Semi-Urban,Software Engineer,65302,1 +108311,Male,36,Masters,15,12,56,98,11,9.0,4,24,Urban,Data Analyst,97518,0 +108312,Female,59,Diploma,19,12,40,68,54,0.0,0,17,Urban,Manager,105126,0 +108313,Male,43,PhD,13,68,31,38,48,5.0,7,97,Urban,Manager,69611,0 +108314,Male,22,Diploma,11,51,86,91,3,8.0,5,20,Urban,ML Engineer,105563,1 +108315,Female,55,Diploma,4,83,1,77,56,2.0,3,36,Urban,HR Executive,142358,0 +108316,Female,53,High School,16,92,37,18,92,6.0,3,8,Urban,Data Analyst,119957,0 +108317,Male,56,Masters,14,68,7,66,48,1.0,3,33,Urban,ML Engineer,70973,0 +108318,Female,54,Bachelors,9,67,37,7,80,0.0,5,15,Urban,ML Engineer,65299,0 +108319,Male,32,High School,7,0,88,88,17,1.0,2,41,Rural,Software Engineer,74138,0 +108320,Male,51,Bachelors,9,90,63,58,44,5.0,1,10,Rural,HR Executive,52838,0 +108321,Male,29,Bachelors,4,25,79,58,98,2.0,1,13,Urban,Manager,124529,0 +108322,Male,32,High School,17,50,98,65,67,0.0,2,72,Rural,ML Engineer,145376,1 +108323,Male,51,Diploma,5,7,82,36,33,0.0,7,3,Urban,ML Engineer,135917,0 +108324,Female,59,Masters,0,2,90,21,8,1.0,3,78,Semi-Urban,Software Engineer,143855,0 +108325,Female,51,Masters,13,70,74,18,15,2.0,5,21,Semi-Urban,Software Engineer,132432,0 +108326,Other,39,Bachelors,17,68,94,96,20,2.0,2,62,Rural,ML Engineer,101704,1 +108327,Male,24,High School,14,65,67,25,8,3.0,5,36,Urban,Data Analyst,143814,0 +108328,Male,41,High School,19,87,7,5,97,3.0,1,72,Semi-Urban,HR Executive,120066,0 +108329,Male,23,Bachelors,0,39,81,2,15,2.0,4,25,Urban,HR Executive,122422,0 +108330,Female,34,Diploma,12,33,47,43,76,7.0,3,86,Semi-Urban,Manager,149208,0 +108331,Male,30,Masters,7,14,98,4,60,6.0,7,84,Urban,HR Executive,142709,0 +108332,Female,46,High School,3,57,26,8,98,7.0,6,17,Urban,ML Engineer,140002,0 +108333,Male,36,High School,2,41,33,28,76,9.0,0,13,Rural,ML Engineer,119345,0 +108334,Female,56,Bachelors,11,50,47,19,50,3.0,2,95,Urban,Software Engineer,58474,0 +108335,Male,56,Diploma,0,13,12,12,2,5.0,1,86,Semi-Urban,HR Executive,25032,0 +108336,Male,47,Masters,19,42,76,4,80,5.0,5,70,Rural,ML Engineer,45032,0 +108337,Female,42,Diploma,7,71,71,28,60,5.0,3,40,Rural,Software Engineer,42839,0 +108338,Male,35,Bachelors,10,5,88,94,65,5.0,1,66,Urban,Manager,39116,1 +108339,Male,28,Masters,4,51,73,81,4,3.0,0,70,Urban,Data Analyst,56679,1 +108340,Female,41,Bachelors,3,14,48,8,46,9.0,6,68,Urban,HR Executive,90639,0 +108341,Male,47,Bachelors,6,13,81,34,25,5.0,3,60,Urban,Data Analyst,66259,0 +108342,Male,42,Bachelors,19,16,6,69,79,2.0,3,18,Urban,Manager,139629,0 +108343,Male,26,Bachelors,10,86,42,18,37,0.0,6,7,Urban,HR Executive,90610,0 +108344,Male,49,Masters,2,20,59,91,74,9.0,2,99,Rural,Software Engineer,41099,1 +108345,Female,42,Bachelors,0,99,36,15,24,6.0,4,99,Semi-Urban,ML Engineer,28783,1 +108346,Female,56,Bachelors,7,92,57,4,17,4.0,6,30,Urban,Software Engineer,131068,0 +108347,Male,49,Diploma,7,77,33,92,2,1.0,7,63,Urban,Software Engineer,74911,1 +108348,Female,23,Bachelors,5,79,72,5,76,8.0,0,27,Semi-Urban,HR Executive,72753,0 +108349,Male,58,Masters,8,67,68,32,90,4.0,0,99,Semi-Urban,Software Engineer,120854,1 +108350,Male,44,Bachelors,17,14,59,15,23,0.0,6,5,Rural,Data Analyst,90454,0 +108351,Male,55,Diploma,13,24,22,32,40,4.0,2,19,Rural,Manager,47459,0 +108352,Male,50,Bachelors,4,6,53,24,46,7.0,4,0,Rural,Data Analyst,144239,0 +108353,Male,35,High School,10,18,86,96,85,1.0,3,49,Urban,ML Engineer,91466,1 +108354,Female,52,Masters,19,68,92,66,31,3.0,0,8,Urban,Data Analyst,111785,0 +108355,Female,29,Masters,6,30,7,23,14,2.0,6,12,Urban,ML Engineer,139471,0 +108356,Male,43,Bachelors,3,19,14,74,10,4.0,6,41,Semi-Urban,Manager,109787,0 +108357,Female,43,Bachelors,14,2,11,33,24,3.0,7,40,Semi-Urban,Software Engineer,141413,0 +108358,Female,24,Bachelors,16,0,85,17,26,3.0,4,98,Rural,ML Engineer,148861,0 +108359,Female,41,Masters,19,67,78,10,77,1.0,5,42,Urban,Manager,113584,0 +108360,Male,42,Masters,2,5,68,22,61,5.0,0,74,Urban,HR Executive,87220,0 +108361,Female,49,Masters,3,82,74,22,98,1.0,2,23,Urban,Manager,21046,0 +108362,Male,54,Masters,11,82,71,22,78,8.0,4,33,Urban,Software Engineer,135853,0 +108363,Male,54,High School,12,96,7,12,84,4.0,6,66,Semi-Urban,ML Engineer,60895,0 +108364,Male,35,Diploma,12,85,44,39,94,3.0,2,39,Urban,Software Engineer,39872,0 +108365,Male,33,Bachelors,3,29,62,24,82,6.0,0,91,Semi-Urban,Data Analyst,114295,0 +108366,Female,54,Diploma,19,51,56,13,46,6.0,0,48,Urban,Data Analyst,102747,0 +108367,Female,54,High School,14,82,76,37,57,5.0,4,21,Semi-Urban,Data Analyst,84968,0 +108368,Male,23,Diploma,6,78,10,60,62,7.0,7,84,Urban,Manager,116441,0 +108369,Female,51,Diploma,17,80,41,14,15,8.0,0,78,Rural,Manager,129052,0 +108370,Female,43,Bachelors,6,57,34,34,30,4.0,7,2,Semi-Urban,Software Engineer,130904,0 +108371,Male,22,Masters,0,16,30,50,48,2.0,2,11,Urban,Software Engineer,135080,0 +108372,Male,43,High School,0,53,47,11,52,4.0,0,65,Semi-Urban,ML Engineer,87070,0 +108373,Male,45,Bachelors,6,79,86,94,94,3.0,3,90,Semi-Urban,Software Engineer,49121,1 +108374,Male,39,Bachelors,3,0,55,52,74,5.0,2,63,Urban,ML Engineer,118372,0 +108375,Female,25,Masters,18,42,78,9,63,0.0,4,87,Urban,Manager,95145,0 +108376,Male,34,PhD,14,31,64,5,91,4.0,0,84,Rural,Manager,69844,0 +108377,Female,57,Bachelors,10,92,98,5,35,6.0,3,55,Urban,HR Executive,25019,1 +108378,Male,42,High School,3,69,74,99,6,6.0,2,0,Urban,Manager,53370,1 +108379,Female,35,Bachelors,8,96,3,57,21,2.0,4,57,Semi-Urban,Data Analyst,74159,0 +108380,Male,55,Masters,3,47,58,45,35,9.0,2,1,Semi-Urban,HR Executive,133571,0 +108381,Female,58,Masters,12,48,90,55,30,6.0,1,48,Rural,Data Analyst,75103,1 +108382,Male,37,Masters,8,77,4,52,18,0.0,5,99,Urban,ML Engineer,144296,0 +108383,Male,58,Masters,8,51,16,14,64,1.0,0,45,Urban,ML Engineer,46028,0 +108384,Male,34,Masters,1,11,51,42,60,1.0,2,2,Urban,Manager,130363,0 +108385,Male,24,Diploma,0,4,54,7,92,3.0,5,68,Urban,ML Engineer,101416,0 +108386,Male,33,Bachelors,11,46,60,37,52,4.0,6,46,Rural,Manager,129806,0 +108387,Male,45,Diploma,2,2,68,78,44,1.0,5,38,Rural,Manager,52298,0 +108388,Female,44,Masters,4,73,82,82,52,5.0,4,63,Urban,Data Analyst,145802,1 +108389,Male,36,Bachelors,10,40,61,8,11,2.0,4,96,Urban,ML Engineer,147685,0 +108390,Male,50,Masters,4,49,35,31,81,6.0,5,71,Rural,ML Engineer,97071,0 +108391,Female,26,Bachelors,18,7,53,73,20,9.0,6,35,Urban,Software Engineer,87825,0 +108392,Female,40,Masters,9,21,14,95,61,4.0,2,5,Rural,Data Analyst,55572,0 +108393,Female,56,High School,5,77,23,80,87,4.0,6,96,Urban,Data Analyst,148541,1 +108394,Male,42,Bachelors,13,55,42,49,97,6.0,0,66,Rural,Software Engineer,79494,0 +108395,Female,32,High School,18,28,68,32,15,4.0,2,46,Rural,Data Analyst,114959,0 +108396,Male,37,Masters,3,68,53,61,7,5.0,6,80,Urban,Data Analyst,82022,1 +108397,Male,54,Bachelors,19,10,11,53,5,9.0,0,49,Semi-Urban,Manager,96791,0 +108398,Other,58,High School,14,60,44,63,2,5.0,3,9,Rural,Data Analyst,140471,0 +108399,Male,22,Masters,4,34,2,49,27,0.0,1,21,Urban,Manager,41752,0 +108400,Female,48,Diploma,5,37,72,30,49,8.0,1,87,Urban,HR Executive,94698,0 +108401,Male,54,Bachelors,12,35,44,13,97,4.0,6,25,Rural,Software Engineer,112588,0 +108402,Female,48,Diploma,5,9,70,90,59,4.0,0,65,Urban,ML Engineer,80869,0 +108403,Male,41,High School,6,46,80,39,70,2.0,1,40,Semi-Urban,HR Executive,35275,0 +108404,Female,48,Masters,15,58,71,74,53,3.0,5,28,Semi-Urban,Software Engineer,56531,0 +108405,Male,51,High School,12,48,8,35,2,6.0,7,54,Rural,Manager,81887,0 +108406,Male,41,High School,13,87,21,8,15,1.0,3,33,Urban,Software Engineer,90140,0 +108407,Other,57,Masters,16,45,62,61,95,9.0,3,85,Semi-Urban,Manager,82511,1 +108408,Male,40,Bachelors,12,26,53,21,91,7.0,3,34,Semi-Urban,Software Engineer,30466,0 +108409,Female,58,Masters,12,12,54,80,71,0.0,1,30,Urban,ML Engineer,140257,0 +108410,Female,27,Masters,19,25,65,11,6,2.0,7,12,Urban,Manager,74467,0 +108411,Male,47,Diploma,15,0,9,18,83,2.0,0,30,Rural,ML Engineer,125105,0 +108412,Male,59,Bachelors,11,65,64,49,8,3.0,7,25,Semi-Urban,HR Executive,128784,0 +108413,Male,27,Bachelors,15,75,39,52,48,2.0,5,4,Semi-Urban,Manager,120299,0 +108414,Male,54,Diploma,4,79,32,52,58,2.0,1,71,Semi-Urban,Manager,59484,0 +108415,Male,54,Masters,3,73,97,97,79,4.0,2,44,Urban,Data Analyst,101856,1 +108416,Male,21,Masters,16,70,43,41,96,1.0,2,92,Urban,Data Analyst,134988,1 +108417,Female,30,Masters,12,26,14,12,96,6.0,7,85,Semi-Urban,HR Executive,57896,0 +108418,Male,31,High School,19,7,64,3,81,6.0,3,98,Semi-Urban,Data Analyst,145652,0 +108419,Female,28,Masters,3,71,81,65,5,2.0,6,98,Urban,Software Engineer,41289,1 +108420,Other,25,Bachelors,6,6,84,84,22,0.0,1,99,Urban,Data Analyst,20588,1 +108421,Other,29,Bachelors,11,85,2,91,8,5.0,1,86,Urban,Manager,55590,1 +108422,Female,35,Bachelors,12,53,69,70,47,6.0,5,90,Rural,Manager,93397,1 +108423,Female,53,High School,19,84,45,72,34,0.0,2,79,Urban,Manager,94926,1 +108424,Female,46,Masters,1,89,58,47,32,7.0,4,39,Urban,Data Analyst,30977,0 +108425,Female,57,High School,3,94,88,26,80,3.0,2,88,Rural,Software Engineer,88927,1 +108426,Male,42,PhD,13,74,38,42,43,6.0,5,43,Urban,Data Analyst,132388,0 +108427,Male,38,Bachelors,7,36,82,16,68,2.0,3,19,Semi-Urban,Manager,106930,0 +108428,Male,47,High School,8,0,53,27,80,8.0,1,32,Semi-Urban,HR Executive,69865,0 +108429,Female,36,Masters,2,91,4,38,76,6.0,4,54,Urban,Software Engineer,102901,0 +108430,Male,34,Bachelors,18,53,65,75,98,5.0,3,41,Urban,Data Analyst,63661,0 +108431,Female,48,Masters,16,23,13,9,26,2.0,4,18,Semi-Urban,Data Analyst,53400,0 +108432,Male,22,High School,5,10,88,19,57,8.0,2,87,Semi-Urban,Data Analyst,52935,0 +108433,Male,55,Bachelors,17,26,57,77,66,9.0,0,42,Urban,Software Engineer,41592,0 +108434,Female,35,High School,18,62,10,17,81,7.0,0,79,Urban,Manager,35731,0 +108435,Male,22,Diploma,17,50,20,96,12,1.0,7,47,Semi-Urban,ML Engineer,120648,0 +108436,Male,46,Bachelors,5,34,51,57,24,2.0,6,34,Urban,ML Engineer,63222,0 +108437,Male,27,Bachelors,0,39,37,25,88,3.0,2,34,Semi-Urban,Data Analyst,115244,0 +108438,Male,43,Bachelors,9,45,31,70,16,6.0,7,79,Rural,HR Executive,77308,0 +108439,Male,37,Bachelors,15,58,3,19,88,7.0,0,56,Semi-Urban,Data Analyst,133314,0 +108440,Male,34,Bachelors,9,98,13,71,35,5.0,3,88,Rural,HR Executive,23976,1 +108441,Female,28,Bachelors,3,70,96,49,28,9.0,0,63,Urban,ML Engineer,32743,1 +108442,Male,28,Bachelors,15,80,38,82,45,6.0,4,9,Urban,Data Analyst,89569,0 +108443,Male,30,Diploma,15,86,69,53,55,1.0,1,32,Urban,Data Analyst,126232,1 +108444,Male,55,Bachelors,4,34,87,6,1,8.0,6,54,Urban,Manager,143572,0 +108445,Male,52,Masters,3,40,85,26,17,9.0,4,5,Rural,Data Analyst,23948,0 +108446,Male,37,Masters,4,62,7,29,99,0.0,2,75,Urban,Manager,146113,0 +108447,Male,36,Diploma,10,28,68,78,64,4.0,3,63,Urban,Software Engineer,114043,1 +108448,Male,31,Masters,15,94,26,97,42,5.0,4,58,Rural,Data Analyst,37667,1 +108449,Male,58,Bachelors,6,66,21,60,39,0.0,7,64,Semi-Urban,Manager,112658,0 +108450,Male,34,Bachelors,0,55,54,40,51,5.0,3,61,Urban,HR Executive,58363,0 +108451,Male,26,High School,14,5,66,80,1,3.0,6,22,Semi-Urban,Software Engineer,85517,0 +108452,Female,36,Bachelors,6,19,7,47,83,3.0,0,31,Semi-Urban,HR Executive,79779,0 +108453,Female,46,Masters,0,3,42,50,65,9.0,1,77,Urban,Manager,107358,0 +108454,Female,34,High School,18,44,82,23,32,5.0,3,44,Semi-Urban,Software Engineer,38433,0 +108455,Male,28,PhD,10,19,31,31,71,6.0,0,86,Semi-Urban,ML Engineer,42561,0 +108456,Female,30,Bachelors,16,8,20,67,6,1.0,7,40,Urban,Manager,77962,0 +108457,Male,38,Diploma,16,8,43,70,74,3.0,3,95,Rural,HR Executive,29202,0 +108458,Male,52,Bachelors,15,29,31,57,95,2.0,4,53,Urban,Software Engineer,22317,0 +108459,Male,51,Bachelors,17,60,94,3,7,6.0,2,43,Urban,ML Engineer,147086,0 +108460,Female,22,Bachelors,0,95,61,77,61,6.0,1,81,Urban,ML Engineer,23701,1 +108461,Male,46,Bachelors,16,56,52,85,12,9.0,5,62,Urban,Software Engineer,23129,1 +108462,Female,42,Diploma,8,24,7,25,63,6.0,5,13,Urban,ML Engineer,33601,0 +108463,Male,46,High School,3,54,9,31,79,9.0,3,75,Rural,Data Analyst,27085,0 +108464,Male,52,Diploma,18,60,83,12,10,0.0,5,33,Rural,Data Analyst,86331,0 +108465,Female,29,Masters,5,48,51,50,86,6.0,5,39,Urban,Data Analyst,48951,0 +108466,Male,28,PhD,18,36,89,68,44,9.0,6,31,Urban,Software Engineer,104759,0 +108467,Female,32,PhD,0,24,37,57,27,5.0,2,32,Urban,Manager,34062,0 +108468,Female,48,PhD,13,26,71,24,5,2.0,0,3,Urban,Software Engineer,94191,0 +108469,Male,34,Bachelors,14,50,19,27,37,9.0,5,35,Rural,HR Executive,92686,0 +108470,Male,38,Masters,14,30,61,32,94,2.0,7,80,Urban,HR Executive,135901,0 +108471,Female,44,Diploma,17,30,86,75,99,3.0,7,34,Urban,ML Engineer,121117,0 +108472,Male,33,Masters,17,13,29,81,29,5.0,5,0,Urban,HR Executive,47867,0 +108473,Male,35,Bachelors,12,70,14,64,16,2.0,6,34,Urban,Data Analyst,29725,0 +108474,Male,25,Bachelors,19,6,71,93,74,3.0,2,21,Urban,ML Engineer,149118,0 +108475,Female,52,Masters,7,86,47,41,1,5.0,2,97,Rural,ML Engineer,31176,1 +108476,Male,27,Bachelors,18,24,62,85,54,2.0,3,36,Rural,Software Engineer,56542,0 +108477,Male,46,Diploma,13,37,56,80,2,2.0,7,68,Rural,Software Engineer,117139,1 +108478,Male,43,Masters,19,90,66,92,64,0.0,2,68,Urban,Data Analyst,101043,1 +108479,Female,47,Diploma,1,83,63,6,46,2.0,1,7,Urban,Manager,41706,0 +108480,Female,24,High School,10,37,52,63,73,2.0,7,3,Rural,HR Executive,76855,0 +108481,Male,30,Bachelors,13,53,28,65,76,1.0,2,32,Semi-Urban,Software Engineer,68388,0 +108482,Female,49,High School,4,52,1,61,71,9.0,5,60,Semi-Urban,HR Executive,115234,0 +108483,Male,23,Bachelors,4,1,17,80,45,8.0,3,79,Urban,ML Engineer,40179,0 +108484,Male,33,Diploma,1,9,38,48,16,3.0,5,36,Urban,HR Executive,113599,0 +108485,Male,35,Bachelors,6,29,90,18,89,2.0,4,72,Urban,Software Engineer,75773,0 +108486,Male,27,Bachelors,4,59,76,54,57,6.0,2,44,Semi-Urban,ML Engineer,74017,0 +108487,Female,24,Diploma,15,90,45,84,46,0.0,7,17,Semi-Urban,ML Engineer,31102,0 +108488,Female,22,High School,13,88,24,82,97,0.0,1,16,Urban,Data Analyst,77234,0 +108489,Female,57,PhD,2,94,63,25,58,5.0,6,6,Rural,Manager,127101,0 +108490,Male,40,Diploma,11,46,7,57,10,0.0,5,37,Semi-Urban,Data Analyst,26781,0 +108491,Female,40,PhD,7,57,74,8,93,8.0,5,89,Urban,Data Analyst,21393,0 +108492,Male,24,Bachelors,11,33,73,44,36,4.0,4,58,Urban,HR Executive,146986,0 +108493,Female,33,Bachelors,16,42,49,88,86,2.0,2,97,Semi-Urban,Software Engineer,25128,1 +108494,Male,28,Diploma,5,72,3,64,2,1.0,7,19,Urban,Manager,140416,0 +108495,Female,37,Bachelors,13,63,72,65,49,0.0,5,78,Urban,Data Analyst,69807,1 +108496,Female,29,Masters,9,3,19,85,13,4.0,0,20,Urban,Software Engineer,81927,0 +108497,Male,40,Diploma,18,26,87,88,85,9.0,3,66,Urban,HR Executive,102310,1 +108498,Male,57,Bachelors,10,68,3,0,17,6.0,7,14,Semi-Urban,Data Analyst,118573,0 +108499,Male,28,High School,7,86,49,98,92,8.0,7,70,Urban,Data Analyst,128109,1 +108500,Female,43,PhD,3,49,99,39,11,3.0,1,6,Semi-Urban,Software Engineer,93699,0 +108501,Female,26,Bachelors,10,8,50,25,84,4.0,5,15,Rural,ML Engineer,93121,0 +108502,Female,29,Masters,5,94,91,0,50,2.0,3,54,Urban,Manager,66542,0 +108503,Female,45,Diploma,7,0,32,65,27,5.0,3,42,Urban,HR Executive,92513,0 +108504,Male,21,Diploma,0,84,80,58,55,9.0,3,64,Urban,Data Analyst,116109,1 +108505,Male,59,Diploma,4,65,83,26,70,3.0,7,60,Semi-Urban,Software Engineer,142021,0 +108506,Male,36,Bachelors,15,61,22,62,80,1.0,7,10,Urban,Manager,28963,0 +108507,Male,31,High School,2,3,83,50,7,5.0,5,68,Semi-Urban,Manager,135364,0 +108508,Male,50,Masters,7,11,41,50,15,4.0,7,86,Semi-Urban,Manager,32726,0 +108509,Female,37,Bachelors,4,11,15,13,26,7.0,5,33,Urban,Manager,107931,0 +108510,Male,55,Bachelors,9,80,23,94,62,6.0,6,61,Rural,HR Executive,65972,1 +108511,Male,25,Bachelors,6,22,34,94,4,3.0,2,3,Rural,ML Engineer,90222,0 +108512,Male,23,Diploma,11,4,86,6,57,2.0,0,29,Rural,Data Analyst,76937,0 +108513,Female,50,Bachelors,0,99,37,48,15,3.0,5,5,Rural,Data Analyst,72956,0 +108514,Male,52,Bachelors,0,13,42,43,54,1.0,0,9,Semi-Urban,Software Engineer,103391,0 +108515,Female,29,High School,3,54,12,60,93,5.0,0,26,Semi-Urban,Data Analyst,96960,0 +108516,Male,55,Diploma,15,93,50,5,8,3.0,4,21,Urban,Software Engineer,126423,0 +108517,Other,22,High School,12,15,68,90,28,8.0,4,27,Urban,HR Executive,36800,0 +108518,Female,23,Bachelors,5,59,29,8,54,7.0,4,17,Semi-Urban,Software Engineer,68907,0 +108519,Male,43,Masters,15,43,23,50,0,6.0,5,2,Semi-Urban,Manager,108467,0 +108520,Female,53,PhD,13,85,54,38,55,2.0,3,27,Semi-Urban,Software Engineer,121777,0 +108521,Male,48,Diploma,9,15,25,25,77,8.0,7,51,Urban,Manager,48860,0 +108522,Male,50,High School,9,62,76,70,73,7.0,3,57,Urban,Data Analyst,107508,1 +108523,Female,33,Masters,7,65,80,10,14,4.0,7,86,Semi-Urban,HR Executive,95549,1 +108524,Female,48,High School,9,72,18,39,15,0.0,2,69,Urban,HR Executive,108377,0 +108525,Male,34,High School,6,95,22,6,44,2.0,1,73,Urban,HR Executive,107643,0 +108526,Male,25,Diploma,8,13,37,56,22,5.0,2,65,Rural,Manager,41696,0 +108527,Male,48,Diploma,1,21,58,29,63,3.0,5,24,Urban,Data Analyst,38968,0 +108528,Female,39,Bachelors,18,80,43,36,44,8.0,3,67,Urban,Software Engineer,99282,0 +108529,Male,33,Diploma,13,75,29,74,10,4.0,3,45,Rural,Data Analyst,116014,0 +108530,Male,58,Bachelors,17,32,17,9,54,6.0,1,72,Urban,Data Analyst,125743,0 +108531,Male,34,Masters,14,78,78,25,72,3.0,0,33,Urban,HR Executive,108043,0 +108532,Female,40,High School,6,90,94,75,34,2.0,7,88,Semi-Urban,Data Analyst,61334,1 +108533,Female,57,Bachelors,7,1,20,2,75,1.0,2,4,Urban,Software Engineer,105895,0 +108534,Other,35,Bachelors,2,41,85,14,31,7.0,3,15,Semi-Urban,Data Analyst,143305,0 +108535,Female,39,Masters,14,4,66,49,13,3.0,0,90,Urban,Software Engineer,149686,0 +108536,Female,33,Bachelors,1,10,31,7,81,8.0,7,92,Rural,HR Executive,114137,0 +108537,Male,38,Bachelors,8,93,62,36,4,4.0,2,85,Urban,HR Executive,26659,1 +108538,Female,52,High School,1,8,74,75,93,8.0,0,18,Rural,Software Engineer,61620,0 +108539,Female,27,High School,6,48,9,74,70,1.0,7,94,Urban,ML Engineer,47512,0 +108540,Female,54,High School,15,24,12,26,5,3.0,4,3,Urban,Data Analyst,124153,0 +108541,Male,33,Diploma,4,92,43,51,5,8.0,4,2,Urban,Data Analyst,78816,0 +108542,Female,42,Diploma,19,43,62,30,60,1.0,4,70,Urban,Manager,132861,0 +108543,Female,54,Diploma,17,24,68,98,10,1.0,4,33,Urban,HR Executive,103922,0 +108544,Female,57,Bachelors,7,70,25,24,78,6.0,2,24,Rural,ML Engineer,146303,0 +108545,Male,42,Bachelors,6,65,46,8,28,8.0,0,95,Urban,Manager,80335,0 +108546,Male,48,Bachelors,9,24,36,82,98,4.0,7,85,Semi-Urban,ML Engineer,63558,0 +108547,Female,39,Bachelors,12,29,25,70,61,8.0,5,59,Urban,Software Engineer,119256,0 +108548,Other,59,Bachelors,11,56,48,25,34,3.0,5,85,Rural,HR Executive,40879,0 +108549,Other,59,Bachelors,11,54,27,65,6,8.0,7,99,Urban,ML Engineer,104123,1 +108550,Other,41,High School,1,24,54,89,28,7.0,0,89,Semi-Urban,ML Engineer,128868,1 +108551,Male,58,Bachelors,19,99,75,20,30,6.0,1,71,Semi-Urban,Manager,23767,1 +108552,Female,29,High School,18,9,91,0,78,9.0,6,87,Rural,HR Executive,34503,0 +108553,Female,47,Masters,7,75,40,2,98,8.0,1,1,Rural,HR Executive,54744,0 +108554,Male,45,Bachelors,0,33,46,86,90,9.0,5,28,Urban,HR Executive,38976,0 +108555,Male,34,PhD,17,89,9,30,37,5.0,6,90,Rural,Manager,22491,0 +108556,Male,43,Diploma,2,54,73,49,75,4.0,3,65,Semi-Urban,Software Engineer,55749,1 +108557,Male,42,Bachelors,18,53,20,80,31,2.0,2,91,Rural,ML Engineer,144384,1 +108558,Male,50,High School,15,40,86,77,25,4.0,4,59,Urban,ML Engineer,34719,1 +108559,Male,35,Masters,18,92,52,76,81,2.0,3,33,Urban,HR Executive,72909,1 +108560,Male,57,Diploma,3,49,14,87,59,2.0,1,80,Urban,HR Executive,89477,0 +108561,Female,58,Masters,8,12,82,41,8,2.0,3,21,Urban,HR Executive,75924,0 +108562,Male,41,Bachelors,4,69,38,16,14,1.0,5,55,Semi-Urban,Manager,66004,0 +108563,Female,22,High School,8,92,63,40,20,3.0,5,89,Urban,ML Engineer,101428,1 +108564,Other,56,PhD,1,29,24,29,7,0.0,4,30,Urban,ML Engineer,58152,0 +108565,Female,32,Masters,0,4,2,31,80,9.0,2,82,Urban,HR Executive,140151,0 +108566,Male,54,Masters,6,43,56,49,13,0.0,1,42,Urban,Software Engineer,90945,0 +108567,Male,29,PhD,12,99,91,10,75,0.0,7,57,Urban,Data Analyst,88903,1 +108568,Female,43,Bachelors,13,64,97,49,95,4.0,4,83,Urban,Software Engineer,81703,1 +108569,Male,43,Diploma,8,69,37,44,24,8.0,7,37,Urban,Manager,147465,0 +108570,Male,39,Bachelors,2,81,61,1,21,0.0,1,97,Urban,ML Engineer,103922,1 +108571,Female,24,Diploma,19,30,94,9,26,9.0,6,2,Semi-Urban,HR Executive,28904,0 +108572,Female,30,Masters,11,87,92,32,83,8.0,6,16,Semi-Urban,Software Engineer,27929,0 +108573,Female,37,Bachelors,18,10,43,72,87,3.0,6,4,Urban,Manager,120233,0 +108574,Female,44,High School,5,7,7,75,29,0.0,3,47,Urban,HR Executive,121817,0 +108575,Female,51,Diploma,1,94,59,38,62,9.0,6,49,Semi-Urban,Manager,28336,0 +108576,Female,33,Diploma,4,26,90,69,48,9.0,1,8,Urban,ML Engineer,55173,0 +108577,Female,59,Masters,7,51,16,82,3,1.0,3,83,Urban,ML Engineer,50431,0 +108578,Male,22,High School,17,92,20,50,72,0.0,0,84,Rural,Software Engineer,120228,1 +108579,Male,37,Bachelors,12,34,60,52,40,9.0,2,0,Urban,HR Executive,103448,0 +108580,Male,36,High School,0,34,6,95,97,1.0,0,15,Urban,Software Engineer,111560,0 +108581,Female,22,Bachelors,0,71,61,70,83,8.0,2,22,Urban,Manager,31692,0 +108582,Male,32,Diploma,0,48,67,81,46,6.0,7,56,Semi-Urban,Software Engineer,68777,1 +108583,Other,26,Diploma,5,58,62,89,29,6.0,6,29,Urban,HR Executive,22729,0 +108584,Female,21,Bachelors,3,53,47,8,2,5.0,3,58,Urban,Software Engineer,29990,0 +108585,Male,33,Masters,8,50,42,99,90,7.0,0,46,Rural,Software Engineer,20477,1 +108586,Female,24,Diploma,4,62,93,0,19,5.0,3,0,Urban,Data Analyst,107030,0 +108587,Other,31,Bachelors,18,49,6,52,8,3.0,1,58,Semi-Urban,HR Executive,127950,0 +108588,Female,49,Bachelors,16,21,10,83,19,2.0,7,32,Semi-Urban,ML Engineer,59409,0 +108589,Female,36,High School,16,52,53,36,50,9.0,6,32,Semi-Urban,Manager,56004,0 +108590,Male,25,High School,5,32,94,46,98,2.0,6,85,Rural,Data Analyst,49952,1 +108591,Male,52,Bachelors,4,53,48,51,51,3.0,5,81,Urban,Manager,86366,0 +108592,Female,59,Bachelors,0,68,0,79,41,5.0,3,28,Urban,HR Executive,146046,0 +108593,Female,24,Bachelors,17,0,2,42,45,1.0,0,1,Urban,ML Engineer,121981,0 +108594,Male,58,Bachelors,4,37,51,53,52,4.0,2,2,Urban,ML Engineer,149298,0 +108595,Male,48,Masters,16,59,62,16,70,6.0,2,1,Rural,Manager,130202,0 +108596,Female,22,Diploma,10,77,88,84,74,3.0,7,52,Urban,ML Engineer,83423,1 +108597,Female,56,Diploma,3,25,81,6,97,6.0,3,56,Semi-Urban,Software Engineer,123555,0 +108598,Female,43,Bachelors,14,47,78,87,21,9.0,5,61,Urban,ML Engineer,57464,1 +108599,Male,56,High School,1,15,27,68,37,2.0,5,76,Urban,Software Engineer,82126,0 +108600,Male,47,Masters,15,31,7,19,67,6.0,3,76,Semi-Urban,ML Engineer,113825,0 +108601,Male,32,Diploma,5,81,5,49,3,3.0,1,79,Urban,Software Engineer,132803,0 +108602,Male,33,Diploma,9,73,66,99,48,7.0,7,61,Urban,Manager,21039,1 +108603,Female,53,Bachelors,7,79,65,30,5,2.0,1,71,Urban,Software Engineer,120679,1 +108604,Female,29,Bachelors,7,73,84,57,12,7.0,7,3,Urban,HR Executive,140150,0 +108605,Other,54,Bachelors,12,83,95,84,51,6.0,7,40,Semi-Urban,Data Analyst,73100,1 +108606,Male,50,High School,13,12,13,41,7,2.0,6,9,Semi-Urban,Software Engineer,24092,0 +108607,Female,35,High School,19,57,70,73,86,0.0,3,96,Urban,Software Engineer,109511,1 +108608,Male,52,Masters,10,45,98,98,56,0.0,0,31,Urban,ML Engineer,118115,1 +108609,Male,24,Bachelors,13,83,12,28,65,6.0,3,84,Semi-Urban,Software Engineer,124550,0 +108610,Female,41,High School,5,83,24,11,40,1.0,5,34,Semi-Urban,HR Executive,135185,0 +108611,Male,41,Masters,8,38,69,73,20,5.0,6,69,Rural,Software Engineer,117494,1 +108612,Male,36,High School,9,15,49,42,38,1.0,5,9,Urban,Software Engineer,35553,0 +108613,Male,47,Masters,2,83,80,59,96,3.0,7,17,Urban,Manager,39393,1 +108614,Other,50,High School,5,19,71,88,71,8.0,4,32,Urban,Manager,132994,0 +108615,Male,55,Diploma,18,80,30,42,31,4.0,0,92,Urban,Manager,25329,1 +108616,Male,44,Masters,10,9,63,87,45,8.0,4,96,Urban,Software Engineer,69329,1 +108617,Male,59,Masters,5,51,62,60,10,9.0,0,95,Semi-Urban,Data Analyst,104211,1 +108618,Male,56,Masters,9,31,23,97,41,8.0,3,13,Urban,Software Engineer,134273,0 +108619,Female,52,Bachelors,7,32,12,73,58,8.0,0,53,Rural,ML Engineer,51591,0 +108620,Male,30,Bachelors,15,27,36,83,40,3.0,7,85,Urban,ML Engineer,42488,0 +108621,Female,51,Bachelors,10,22,83,80,99,5.0,3,30,Urban,Data Analyst,119397,0 +108622,Male,23,Bachelors,13,63,34,86,12,0.0,5,64,Rural,HR Executive,97326,1 +108623,Male,41,Bachelors,0,51,67,13,96,9.0,1,44,Semi-Urban,Software Engineer,63641,0 +108624,Male,21,Diploma,8,86,77,25,9,3.0,2,30,Rural,ML Engineer,120836,0 +108625,Male,23,Diploma,5,96,28,22,65,0.0,4,2,Rural,Data Analyst,111942,0 +108626,Male,52,Bachelors,11,96,29,90,39,1.0,7,55,Rural,HR Executive,84453,1 +108627,Male,25,Bachelors,10,84,23,46,44,4.0,1,84,Rural,Software Engineer,88765,1 +108628,Male,55,Bachelors,0,71,75,88,11,9.0,0,19,Rural,Data Analyst,140900,1 +108629,Male,49,High School,19,27,1,54,14,6.0,5,34,Urban,Software Engineer,86757,0 +108630,Female,35,Bachelors,2,99,78,82,77,8.0,1,9,Urban,Software Engineer,59029,1 +108631,Male,37,Bachelors,2,32,57,42,57,7.0,5,53,Rural,Manager,144539,0 +108632,Male,43,Bachelors,8,37,10,77,6,8.0,5,23,Urban,HR Executive,61044,0 +108633,Male,49,Bachelors,10,77,2,14,18,0.0,2,9,Urban,Software Engineer,105426,0 +108634,Male,25,Bachelors,11,92,83,41,28,5.0,1,50,Semi-Urban,Data Analyst,107363,1 +108635,Male,40,Bachelors,1,81,75,21,97,7.0,5,44,Semi-Urban,Data Analyst,138572,0 +108636,Female,46,Diploma,6,49,88,96,32,8.0,7,89,Semi-Urban,Data Analyst,148414,1 +108637,Other,25,Bachelors,3,32,98,37,79,8.0,0,46,Rural,Data Analyst,124319,0 +108638,Female,49,PhD,2,88,33,91,42,7.0,0,82,Semi-Urban,Manager,46605,1 +108639,Male,32,Diploma,10,10,56,50,28,8.0,2,99,Semi-Urban,HR Executive,110993,0 +108640,Male,25,Masters,10,92,63,86,53,0.0,2,5,Urban,Software Engineer,127336,1 +108641,Male,59,High School,9,17,38,35,13,3.0,5,99,Urban,ML Engineer,140587,0 +108642,Male,45,High School,10,72,34,76,93,6.0,7,31,Semi-Urban,ML Engineer,108561,0 +108643,Male,50,High School,4,81,4,65,58,6.0,2,59,Semi-Urban,HR Executive,108280,0 +108644,Male,25,Bachelors,4,21,7,53,68,8.0,2,57,Rural,Software Engineer,36613,0 +108645,Female,37,Bachelors,16,12,49,80,95,8.0,0,73,Urban,Manager,55619,0 +108646,Male,22,Bachelors,16,39,41,38,6,6.0,2,6,Semi-Urban,Manager,118075,0 +108647,Male,56,Bachelors,10,44,11,47,80,0.0,2,14,Semi-Urban,HR Executive,36659,0 +108648,Male,55,High School,17,63,55,88,99,8.0,0,61,Urban,Data Analyst,74420,1 +108649,Male,43,Bachelors,4,12,72,58,32,9.0,2,46,Semi-Urban,Manager,41117,0 +108650,Female,26,Bachelors,3,0,24,52,65,6.0,4,93,Semi-Urban,ML Engineer,106062,0 +108651,Female,58,Diploma,13,40,78,78,92,6.0,1,98,Urban,Data Analyst,69884,1 +108652,Female,21,High School,8,26,15,0,41,0.0,2,47,Urban,Software Engineer,32074,0 +108653,Male,55,PhD,14,34,10,65,53,6.0,1,11,Urban,Manager,76745,0 +108654,Male,23,Bachelors,9,57,42,58,41,1.0,3,79,Urban,Software Engineer,103112,1 +108655,Other,26,Diploma,7,39,16,30,76,9.0,5,12,Rural,ML Engineer,112292,0 +108656,Female,57,Bachelors,1,85,73,5,30,4.0,5,65,Rural,Software Engineer,68839,0 +108657,Male,42,Masters,12,58,58,84,80,2.0,6,51,Urban,ML Engineer,22702,1 +108658,Male,52,Masters,9,70,21,52,67,2.0,1,18,Urban,HR Executive,22760,0 +108659,Male,32,Bachelors,3,94,29,13,0,9.0,5,61,Urban,Data Analyst,107638,0 +108660,Male,58,Diploma,19,37,24,14,72,1.0,3,12,Semi-Urban,Data Analyst,127015,0 +108661,Female,53,High School,0,58,57,22,51,2.0,3,6,Semi-Urban,Manager,93708,0 +108662,Male,51,High School,13,96,70,43,1,9.0,6,78,Urban,Data Analyst,89398,1 +108663,Male,22,Masters,5,85,92,94,15,0.0,4,19,Rural,HR Executive,74933,1 +108664,Female,24,High School,1,83,83,49,16,5.0,6,33,Urban,Software Engineer,79630,1 +108665,Female,54,Bachelors,6,16,90,70,79,4.0,0,43,Urban,Data Analyst,142714,0 +108666,Female,25,Diploma,7,51,7,17,22,2.0,4,24,Urban,ML Engineer,132008,0 +108667,Female,54,Masters,5,60,20,28,64,1.0,7,75,Rural,HR Executive,75220,0 +108668,Male,21,Bachelors,11,36,87,98,77,4.0,6,24,Rural,Software Engineer,35252,1 +108669,Female,33,Masters,8,23,48,25,86,6.0,6,4,Rural,Manager,55256,0 +108670,Male,22,Masters,0,39,55,83,32,9.0,7,38,Rural,ML Engineer,42056,0 +108671,Female,44,High School,1,98,31,17,21,0.0,5,25,Urban,HR Executive,72158,0 +108672,Female,55,Bachelors,17,87,19,9,6,0.0,3,49,Urban,ML Engineer,115390,0 +108673,Female,30,Bachelors,17,90,13,25,55,3.0,1,68,Rural,Data Analyst,122258,0 +108674,Female,26,Diploma,14,50,98,67,77,1.0,1,38,Rural,Manager,39874,1 +108675,Male,46,Diploma,13,6,15,92,67,7.0,0,34,Urban,Manager,29505,0 +108676,Male,41,Bachelors,7,31,68,41,88,7.0,4,89,Urban,ML Engineer,103847,0 +108677,Male,41,Bachelors,6,29,22,6,43,2.0,4,79,Urban,HR Executive,82203,0 +108678,Male,24,High School,12,1,78,66,48,6.0,1,32,Rural,Manager,77656,0 +108679,Male,49,High School,19,60,6,7,33,0.0,2,77,Urban,Software Engineer,129506,0 +108680,Female,42,Diploma,15,63,68,17,90,7.0,6,79,Rural,HR Executive,98752,0 +108681,Male,23,PhD,11,64,61,21,44,6.0,3,61,Semi-Urban,Data Analyst,85862,0 +108682,Male,51,Bachelors,7,0,29,8,96,8.0,6,61,Urban,Data Analyst,95739,0 +108683,Male,24,Bachelors,14,96,63,86,65,7.0,0,34,Rural,HR Executive,104981,1 +108684,Female,41,Masters,14,85,37,76,14,5.0,7,95,Semi-Urban,Manager,117917,1 +108685,Male,29,Diploma,15,77,4,43,8,5.0,2,66,Urban,Software Engineer,104028,0 +108686,Male,51,PhD,6,21,44,27,87,4.0,1,56,Urban,Manager,32828,0 +108687,Male,57,Bachelors,6,66,17,39,34,5.0,7,43,Urban,HR Executive,115920,0 +108688,Female,58,Bachelors,11,9,39,33,58,7.0,2,21,Semi-Urban,HR Executive,39417,0 +108689,Female,47,Diploma,14,59,32,88,22,6.0,3,51,Urban,Manager,107844,0 +108690,Female,32,Bachelors,9,59,47,5,9,1.0,0,79,Rural,Data Analyst,43207,0 +108691,Male,53,Bachelors,5,49,2,70,88,2.0,6,5,Urban,Manager,33157,0 +108692,Male,42,Diploma,16,8,29,89,79,5.0,4,77,Semi-Urban,Manager,103844,0 +108693,Other,29,Bachelors,17,14,74,11,87,1.0,6,23,Urban,ML Engineer,137490,0 +108694,Male,41,Bachelors,11,67,30,83,95,5.0,4,83,Urban,Data Analyst,67967,1 +108695,Female,31,Diploma,13,41,41,68,64,0.0,6,63,Rural,ML Engineer,43847,0 +108696,Female,44,Diploma,17,34,66,70,49,1.0,7,66,Urban,Software Engineer,72252,0 +108697,Male,26,Masters,2,10,85,11,83,6.0,0,2,Urban,Data Analyst,132754,0 +108698,Male,58,Masters,6,8,38,54,28,2.0,1,89,Urban,Data Analyst,90969,0 +108699,Male,26,Diploma,10,90,5,29,27,5.0,4,9,Urban,Data Analyst,112861,0 +108700,Female,37,Bachelors,12,8,60,55,91,7.0,7,9,Semi-Urban,Data Analyst,100411,0 +108701,Female,27,Diploma,0,59,74,63,7,6.0,1,91,Urban,Software Engineer,117311,1 +108702,Male,35,Bachelors,3,93,28,30,0,6.0,0,3,Urban,HR Executive,22976,0 +108703,Female,39,Masters,11,98,48,37,14,3.0,6,16,Rural,HR Executive,122139,0 +108704,Male,39,Diploma,5,33,97,18,94,4.0,5,48,Rural,HR Executive,66070,0 +108705,Male,52,Diploma,10,45,99,16,34,4.0,2,5,Semi-Urban,Data Analyst,144571,0 +108706,Male,26,Diploma,15,20,48,95,96,5.0,6,64,Rural,Software Engineer,140406,0 +108707,Female,35,Bachelors,3,11,77,59,40,9.0,7,55,Semi-Urban,Manager,31987,0 +108708,Female,23,Diploma,15,91,60,1,62,4.0,3,1,Urban,Manager,148096,0 +108709,Male,25,Diploma,7,66,63,33,44,4.0,3,45,Semi-Urban,HR Executive,148160,0 +108710,Male,33,High School,9,18,85,33,71,1.0,3,56,Urban,Data Analyst,26794,0 +108711,Male,37,Bachelors,0,73,10,88,10,5.0,6,3,Urban,Software Engineer,32430,0 +108712,Female,22,Diploma,7,89,90,5,51,7.0,3,36,Rural,HR Executive,62663,0 +108713,Female,40,Bachelors,18,95,64,92,30,4.0,0,36,Urban,Software Engineer,22463,1 +108714,Male,55,Bachelors,6,15,76,1,98,5.0,6,64,Semi-Urban,ML Engineer,108986,0 +108715,Male,39,Bachelors,6,31,33,6,59,1.0,5,17,Rural,ML Engineer,23299,0 +108716,Female,51,Bachelors,2,24,3,20,13,6.0,5,64,Urban,Data Analyst,36910,0 +108717,Male,41,Masters,15,39,41,95,83,7.0,0,91,Semi-Urban,ML Engineer,78182,1 +108718,Female,46,Bachelors,16,20,3,38,92,2.0,2,23,Urban,Software Engineer,140829,0 +108719,Male,56,Masters,12,77,8,33,18,9.0,5,35,Rural,HR Executive,143057,0 +108720,Male,49,Bachelors,10,83,74,35,21,9.0,2,97,Urban,ML Engineer,131450,1 +108721,Male,43,Masters,2,87,14,46,85,1.0,5,85,Rural,HR Executive,33238,0 +108722,Male,33,Masters,3,43,71,47,39,3.0,6,5,Urban,Data Analyst,149153,0 +108723,Male,58,Bachelors,15,56,63,95,15,8.0,5,62,Urban,HR Executive,144131,1 +108724,Male,53,Bachelors,19,45,34,77,96,9.0,1,63,Urban,ML Engineer,140307,0 +108725,Male,57,Masters,10,0,90,5,88,4.0,2,8,Semi-Urban,Software Engineer,127976,0 +108726,Female,45,Bachelors,1,47,29,21,32,1.0,7,76,Urban,Software Engineer,60023,0 +108727,Other,27,High School,19,14,6,41,45,6.0,3,39,Semi-Urban,ML Engineer,141208,0 +108728,Female,21,Masters,0,90,24,93,71,4.0,6,63,Urban,ML Engineer,33019,1 +108729,Female,25,Diploma,18,84,56,52,40,5.0,5,31,Urban,Software Engineer,111355,0 +108730,Male,22,Bachelors,15,46,43,83,97,3.0,2,13,Semi-Urban,Data Analyst,35858,0 +108731,Male,53,Masters,12,51,3,35,69,6.0,0,66,Urban,Manager,83276,0 +108732,Female,35,High School,6,56,69,21,21,4.0,7,35,Urban,Software Engineer,120327,0 +108733,Male,36,High School,3,81,10,13,35,7.0,0,11,Urban,Manager,37106,0 +108734,Male,33,Diploma,7,36,95,32,58,8.0,7,97,Rural,Data Analyst,116934,1 +108735,Male,59,Masters,0,99,68,98,39,5.0,7,89,Urban,ML Engineer,108936,1 +108736,Female,44,Bachelors,12,27,78,80,18,6.0,4,95,Urban,HR Executive,125340,1 +108737,Other,28,Masters,10,87,83,18,58,6.0,2,93,Rural,ML Engineer,85817,1 +108738,Female,44,Diploma,18,34,26,1,97,4.0,1,16,Rural,Manager,53276,0 +108739,Other,44,Masters,4,84,50,40,3,5.0,0,25,Semi-Urban,ML Engineer,104355,0 +108740,Male,22,Bachelors,17,65,22,99,31,3.0,6,82,Semi-Urban,Manager,50446,1 +108741,Male,24,Bachelors,11,16,25,51,78,0.0,7,25,Semi-Urban,ML Engineer,42611,0 +108742,Male,34,Masters,12,87,20,36,41,0.0,3,15,Urban,HR Executive,119882,0 +108743,Female,46,PhD,18,68,26,72,64,0.0,7,88,Rural,ML Engineer,96814,1 +108744,Male,37,Bachelors,15,90,13,16,45,9.0,2,28,Rural,ML Engineer,145313,0 +108745,Female,22,PhD,3,45,51,16,54,4.0,0,97,Urban,Manager,138572,0 +108746,Female,50,Bachelors,12,43,37,26,35,5.0,2,1,Urban,ML Engineer,59860,0 +108747,Female,42,Masters,0,37,69,36,98,0.0,3,58,Rural,ML Engineer,60876,0 +108748,Female,33,Bachelors,19,19,33,44,21,4.0,3,77,Urban,Manager,65186,0 +108749,Female,47,Bachelors,5,38,12,28,45,0.0,7,13,Urban,ML Engineer,68951,0 +108750,Female,44,Diploma,2,26,84,43,46,8.0,1,50,Rural,Data Analyst,138703,0 +108751,Female,39,Bachelors,3,43,18,74,6,4.0,5,39,Urban,HR Executive,98101,0 +108752,Male,22,Masters,2,46,22,0,49,0.0,1,83,Urban,Data Analyst,114706,0 +108753,Male,44,Masters,11,93,85,78,58,0.0,0,0,Urban,Manager,64260,1 +108754,Female,57,Bachelors,7,31,94,41,7,4.0,1,82,Rural,Software Engineer,104707,1 +108755,Male,57,High School,6,53,47,0,17,8.0,0,49,Semi-Urban,Software Engineer,84259,0 +108756,Male,32,Masters,11,57,31,47,26,1.0,2,96,Urban,Manager,81244,0 +108757,Female,24,PhD,10,77,35,74,32,9.0,5,64,Urban,ML Engineer,29582,1 +108758,Female,29,High School,1,32,70,4,67,1.0,2,67,Rural,Manager,72014,0 +108759,Male,27,Bachelors,16,69,85,52,28,3.0,4,19,Urban,Data Analyst,27402,0 +108760,Female,54,Bachelors,7,51,77,50,95,2.0,5,19,Urban,HR Executive,118178,0 +108761,Male,48,High School,18,97,83,12,14,1.0,5,47,Semi-Urban,Data Analyst,37968,1 +108762,Female,56,Masters,8,48,5,10,96,1.0,7,79,Urban,Software Engineer,140399,0 +108763,Female,34,Bachelors,8,12,95,18,39,3.0,4,14,Urban,Software Engineer,129115,0 +108764,Female,34,Diploma,11,24,66,42,62,5.0,5,86,Urban,Data Analyst,29037,0 +108765,Female,53,Bachelors,18,56,99,17,66,0.0,7,25,Semi-Urban,Data Analyst,125836,0 +108766,Male,55,Diploma,19,98,60,28,30,1.0,5,0,Urban,Data Analyst,82365,0 +108767,Male,23,Bachelors,17,35,17,41,52,1.0,5,55,Semi-Urban,Manager,80124,0 +108768,Male,53,Masters,0,92,38,58,55,1.0,3,66,Urban,ML Engineer,63551,1 +108769,Female,28,Masters,14,41,33,93,83,8.0,2,75,Urban,Software Engineer,56589,1 +108770,Female,30,Bachelors,10,95,53,46,21,8.0,1,37,Rural,ML Engineer,133133,0 +108771,Male,42,Bachelors,18,29,47,42,95,6.0,2,18,Urban,Data Analyst,120059,0 +108772,Female,24,Diploma,12,55,44,53,9,0.0,1,99,Urban,Data Analyst,111747,1 +108773,Other,57,Bachelors,0,65,90,79,98,0.0,6,28,Urban,Manager,131092,1 +108774,Male,29,Masters,12,42,6,56,69,6.0,4,89,Rural,Manager,51338,0 +108775,Male,36,High School,3,7,91,82,39,6.0,5,57,Semi-Urban,HR Executive,77111,1 +108776,Female,25,Diploma,17,16,99,66,20,9.0,2,61,Semi-Urban,ML Engineer,41160,1 +108777,Male,24,Bachelors,12,46,19,1,58,9.0,3,76,Urban,Manager,110074,0 +108778,Male,52,Diploma,12,66,66,26,45,8.0,0,11,Semi-Urban,Software Engineer,114931,0 +108779,Female,52,PhD,18,4,74,80,3,0.0,4,91,Urban,Manager,119840,1 +108780,Male,31,Bachelors,5,96,95,89,1,5.0,4,21,Urban,Software Engineer,84643,1 +108781,Male,48,Bachelors,16,65,25,37,5,5.0,5,48,Semi-Urban,Manager,99709,0 +108782,Male,51,Bachelors,5,64,13,28,30,4.0,5,43,Urban,ML Engineer,134156,0 +108783,Female,47,Bachelors,9,89,90,15,72,1.0,0,82,Urban,Data Analyst,20484,1 +108784,Male,32,High School,8,96,55,20,21,0.0,7,83,Semi-Urban,Software Engineer,48024,1 +108785,Male,34,Bachelors,10,7,74,54,63,0.0,0,50,Rural,ML Engineer,86743,0 +108786,Male,29,High School,2,31,39,81,90,8.0,5,24,Urban,Data Analyst,78944,0 +108787,Female,51,High School,15,36,54,10,28,7.0,1,8,Urban,Manager,55474,0 +108788,Male,30,Bachelors,1,19,79,11,80,4.0,0,60,Urban,ML Engineer,103669,0 +108789,Male,32,Bachelors,16,5,54,72,48,5.0,1,68,Rural,Software Engineer,41767,0 +108790,Female,49,Bachelors,17,55,0,2,36,1.0,3,0,Semi-Urban,ML Engineer,141802,0 +108791,Male,22,High School,6,41,76,2,86,5.0,5,1,Rural,Data Analyst,24506,0 +108792,Male,48,Bachelors,0,35,74,83,94,1.0,3,82,Urban,Software Engineer,34620,1 +108793,Male,21,Masters,17,48,28,77,37,6.0,0,19,Urban,Manager,109126,0 +108794,Male,26,Masters,17,55,41,40,88,9.0,5,33,Urban,Data Analyst,103443,0 +108795,Female,45,Bachelors,10,65,88,86,68,7.0,4,37,Semi-Urban,Manager,93474,1 +108796,Male,40,Diploma,8,90,98,11,19,3.0,4,69,Urban,ML Engineer,75851,1 +108797,Male,48,Bachelors,9,36,76,74,83,2.0,6,1,Urban,HR Executive,73584,0 +108798,Male,44,Bachelors,16,2,37,46,11,8.0,0,31,Urban,Manager,59252,0 +108799,Female,40,Masters,14,49,93,35,25,1.0,1,53,Rural,Software Engineer,68516,0 +108800,Other,37,Bachelors,6,55,96,90,46,7.0,2,27,Urban,Manager,115671,1 +108801,Female,43,Diploma,4,79,54,58,1,6.0,5,20,Rural,ML Engineer,97165,0 +108802,Female,32,Diploma,3,48,98,67,7,2.0,2,93,Urban,Manager,120825,1 +108803,Female,56,Bachelors,18,79,72,81,94,8.0,5,61,Urban,ML Engineer,144492,1 +108804,Female,24,Masters,2,56,66,86,29,5.0,5,50,Urban,ML Engineer,145397,1 +108805,Male,57,Masters,19,10,49,42,14,8.0,3,59,Rural,HR Executive,68791,0 +108806,Male,41,Bachelors,9,99,82,54,42,4.0,6,42,Semi-Urban,Manager,109602,1 +108807,Male,54,Masters,5,67,77,86,15,7.0,5,75,Semi-Urban,Software Engineer,59944,1 +108808,Female,53,Masters,16,31,57,29,22,5.0,7,12,Urban,Manager,51217,0 +108809,Male,39,High School,10,75,47,36,52,2.0,2,0,Rural,Data Analyst,77272,0 +108810,Male,34,Bachelors,8,91,1,45,86,5.0,3,44,Rural,Data Analyst,21068,0 +108811,Other,50,Masters,18,44,71,56,46,1.0,6,4,Rural,Software Engineer,122791,0 +108812,Male,40,Bachelors,4,26,94,68,77,2.0,0,83,Urban,HR Executive,59743,1 +108813,Male,45,Bachelors,3,62,17,61,73,1.0,1,51,Rural,HR Executive,144418,0 +108814,Female,45,Masters,11,27,73,34,91,0.0,5,20,Urban,Data Analyst,69639,0 +108815,Female,26,Bachelors,0,99,5,33,58,4.0,3,37,Urban,Software Engineer,98927,0 +108816,Male,22,Bachelors,15,20,90,66,38,3.0,4,38,Urban,Software Engineer,100644,0 +108817,Male,25,Diploma,5,73,99,21,88,6.0,6,88,Rural,Data Analyst,142534,1 +108818,Male,27,Bachelors,0,30,95,28,44,9.0,1,99,Urban,Software Engineer,119859,1 +108819,Male,21,Diploma,17,79,84,83,13,1.0,7,8,Semi-Urban,HR Executive,147774,1 +108820,Female,24,PhD,11,31,47,17,25,0.0,0,66,Rural,HR Executive,101501,0 +108821,Male,49,High School,18,81,30,64,19,2.0,1,55,Urban,HR Executive,32453,0 +108822,Female,49,Bachelors,10,41,1,33,0,1.0,7,92,Semi-Urban,Software Engineer,89425,0 +108823,Other,46,High School,1,51,37,29,75,9.0,2,44,Urban,ML Engineer,66196,0 +108824,Female,48,PhD,17,67,10,84,60,0.0,0,37,Urban,Data Analyst,50175,0 +108825,Male,27,Bachelors,10,45,74,16,47,1.0,5,78,Urban,HR Executive,33614,0 +108826,Male,54,Diploma,10,2,55,27,45,7.0,7,94,Urban,Software Engineer,125463,0 +108827,Male,49,Bachelors,0,64,80,21,13,3.0,6,41,Urban,Data Analyst,41726,0 +108828,Male,56,High School,4,47,50,92,5,2.0,0,69,Semi-Urban,Manager,126885,1 +108829,Female,26,Masters,2,74,54,94,25,4.0,7,67,Semi-Urban,HR Executive,95411,1 +108830,Male,23,Masters,11,31,35,62,64,9.0,7,14,Urban,Data Analyst,79567,0 +108831,Female,45,Bachelors,4,29,37,92,99,3.0,7,51,Rural,Data Analyst,143595,0 +108832,Male,54,Diploma,5,61,53,60,51,8.0,1,43,Urban,ML Engineer,38808,0 +108833,Female,29,Bachelors,17,54,28,33,54,5.0,5,45,Urban,Data Analyst,24000,0 +108834,Female,53,Masters,0,69,27,14,20,4.0,2,33,Urban,Manager,145335,0 +108835,Female,30,Diploma,17,30,30,95,39,1.0,5,88,Urban,HR Executive,117908,1 +108836,Male,23,Bachelors,11,80,60,98,4,5.0,1,96,Urban,ML Engineer,112193,1 +108837,Male,39,PhD,9,79,84,74,74,6.0,3,45,Urban,Data Analyst,41471,1 +108838,Male,21,Masters,16,77,26,97,33,3.0,4,40,Rural,HR Executive,21378,1 +108839,Female,48,Masters,18,70,6,67,80,9.0,5,54,Semi-Urban,Data Analyst,81842,0 +108840,Male,41,Masters,3,39,79,11,12,7.0,0,62,Urban,Software Engineer,81952,0 +108841,Male,56,Bachelors,10,19,7,88,79,7.0,2,4,Semi-Urban,HR Executive,50623,0 +108842,Other,49,Bachelors,7,95,27,23,39,7.0,5,90,Urban,Software Engineer,31954,0 +108843,Male,56,Bachelors,6,19,15,79,80,1.0,0,94,Rural,Manager,31684,0 +108844,Male,35,Bachelors,6,90,20,48,37,4.0,2,39,Urban,HR Executive,116036,0 +108845,Male,51,Bachelors,14,37,20,91,44,2.0,6,2,Urban,Manager,96648,0 +108846,Male,53,Masters,9,68,45,38,53,4.0,3,30,Semi-Urban,ML Engineer,97699,0 +108847,Male,57,Bachelors,14,41,60,39,77,6.0,4,64,Urban,Software Engineer,73280,0 +108848,Male,53,Masters,17,3,42,91,98,2.0,1,52,Urban,Software Engineer,107125,0 +108849,Female,35,Masters,1,62,80,42,52,6.0,6,34,Rural,HR Executive,108335,0 +108850,Male,45,High School,12,20,32,86,65,2.0,1,41,Rural,ML Engineer,148065,0 +108851,Female,41,High School,8,53,67,42,12,2.0,1,7,Urban,Manager,21941,0 +108852,Female,29,Bachelors,13,90,10,87,9,8.0,1,74,Urban,HR Executive,144621,1 +108853,Female,45,Masters,8,98,7,17,56,2.0,0,23,Urban,HR Executive,148000,0 +108854,Male,49,Bachelors,3,5,95,93,55,9.0,4,30,Urban,Manager,96094,0 +108855,Male,37,PhD,19,9,34,40,43,4.0,1,58,Urban,ML Engineer,62639,0 +108856,Male,30,Masters,17,29,10,26,64,1.0,5,18,Urban,HR Executive,108404,0 +108857,Female,48,Masters,9,29,56,45,82,5.0,6,99,Urban,HR Executive,124585,0 +108858,Male,37,Bachelors,19,97,16,10,50,5.0,4,83,Urban,Software Engineer,98686,0 +108859,Male,42,Bachelors,7,72,14,98,90,5.0,3,78,Rural,Manager,29560,1 +108860,Male,52,Diploma,19,47,71,18,78,5.0,4,59,Semi-Urban,Software Engineer,114992,0 +108861,Male,49,Masters,5,32,40,79,54,4.0,4,90,Semi-Urban,Software Engineer,37982,1 +108862,Male,40,Bachelors,4,57,68,69,24,1.0,1,62,Rural,HR Executive,147876,1 +108863,Male,54,High School,10,74,7,96,47,4.0,5,98,Urban,Manager,139558,1 +108864,Male,47,Diploma,17,51,15,0,90,7.0,7,82,Semi-Urban,Data Analyst,138536,0 +108865,Male,40,Bachelors,9,54,72,27,80,4.0,4,74,Semi-Urban,Data Analyst,138385,0 +108866,Female,30,Bachelors,2,64,22,39,47,5.0,3,22,Urban,Data Analyst,130746,0 +108867,Male,36,Bachelors,17,3,76,45,31,2.0,0,51,Urban,Manager,133725,0 +108868,Male,29,Masters,2,77,17,20,33,6.0,7,95,Semi-Urban,ML Engineer,120219,0 +108869,Female,23,Bachelors,8,27,34,35,52,2.0,3,11,Urban,Data Analyst,91564,0 +108870,Male,27,Diploma,3,89,79,58,95,5.0,4,21,Semi-Urban,Data Analyst,122917,1 +108871,Male,25,High School,4,17,9,23,44,6.0,5,4,Rural,Data Analyst,77262,0 +108872,Male,40,High School,9,29,47,49,58,6.0,2,83,Urban,Manager,113925,0 +108873,Male,36,Masters,18,96,50,45,11,1.0,4,9,Urban,ML Engineer,93285,0 +108874,Male,45,Bachelors,12,68,11,57,58,0.0,0,68,Rural,ML Engineer,123326,0 +108875,Male,42,Masters,4,33,48,75,53,1.0,7,55,Urban,Software Engineer,90226,0 +108876,Male,43,High School,19,63,63,81,42,1.0,6,9,Urban,Software Engineer,38849,0 +108877,Female,49,Diploma,9,5,67,12,40,9.0,6,73,Urban,Manager,140956,0 +108878,Male,39,Bachelors,19,63,6,56,35,9.0,2,26,Urban,Software Engineer,89234,0 +108879,Female,55,Diploma,12,82,39,79,78,1.0,0,84,Urban,Data Analyst,38993,1 +108880,Other,33,High School,2,4,31,36,54,1.0,0,91,Semi-Urban,HR Executive,59556,0 +108881,Male,26,Diploma,2,25,92,83,17,2.0,0,95,Urban,Manager,78176,1 +108882,Male,25,High School,18,76,97,59,78,2.0,6,76,Semi-Urban,HR Executive,89961,1 +108883,Male,40,Bachelors,7,50,15,65,41,5.0,5,74,Urban,Software Engineer,25871,0 +108884,Female,49,Bachelors,10,69,23,62,43,1.0,4,88,Semi-Urban,ML Engineer,83929,1 +108885,Male,52,Bachelors,6,12,62,86,69,3.0,4,25,Urban,Data Analyst,67342,0 +108886,Female,46,Masters,2,72,32,26,41,3.0,2,80,Urban,Data Analyst,73179,0 +108887,Male,50,PhD,5,22,93,81,48,5.0,0,17,Rural,Software Engineer,50993,0 +108888,Male,58,Bachelors,19,37,41,95,82,8.0,3,72,Semi-Urban,Software Engineer,37273,1 +108889,Male,24,Diploma,19,62,72,96,87,8.0,5,82,Rural,Software Engineer,127929,1 +108890,Male,54,Masters,14,39,91,94,65,9.0,0,36,Urban,ML Engineer,107913,1 +108891,Female,21,Bachelors,11,50,20,57,15,0.0,7,42,Rural,Data Analyst,117722,0 +108892,Female,36,Bachelors,14,17,28,13,16,0.0,0,3,Urban,ML Engineer,75146,0 +108893,Other,56,Bachelors,0,59,73,44,19,5.0,4,73,Urban,HR Executive,81510,1 +108894,Male,22,Diploma,2,36,32,57,5,7.0,7,38,Urban,ML Engineer,100456,0 +108895,Male,36,High School,2,11,9,88,91,2.0,4,28,Urban,Software Engineer,75941,0 +108896,Other,36,Diploma,19,51,48,18,20,0.0,0,74,Urban,Data Analyst,140525,0 +108897,Male,21,Diploma,6,48,47,55,92,2.0,6,97,Urban,Manager,142259,1 +108898,Male,44,Bachelors,12,67,6,69,54,6.0,5,90,Rural,HR Executive,134784,0 +108899,Female,42,PhD,11,44,53,64,22,0.0,0,33,Urban,Manager,104472,0 +108900,Male,59,High School,18,23,80,97,92,1.0,7,73,Urban,Manager,90649,1 +108901,Female,26,High School,2,2,67,1,96,2.0,3,22,Urban,Data Analyst,46405,0 +108902,Female,46,Bachelors,9,81,99,53,74,2.0,6,94,Semi-Urban,ML Engineer,104120,1 +108903,Male,47,Masters,7,72,86,95,62,6.0,0,16,Semi-Urban,Manager,26530,1 +108904,Female,56,Bachelors,16,65,88,20,70,8.0,3,89,Urban,Software Engineer,85945,1 +108905,Male,45,Bachelors,17,95,9,92,34,6.0,3,39,Urban,Manager,147612,1 +108906,Female,58,Masters,19,21,25,94,28,0.0,0,70,Rural,ML Engineer,104860,0 +108907,Male,22,Diploma,5,91,32,91,43,6.0,5,5,Semi-Urban,Data Analyst,37284,0 +108908,Male,28,Diploma,13,28,36,29,91,2.0,7,97,Urban,Data Analyst,70763,0 +108909,Male,52,Diploma,8,85,16,11,77,6.0,3,79,Semi-Urban,ML Engineer,82259,0 +108910,Male,50,Bachelors,4,65,43,42,30,6.0,7,52,Urban,Software Engineer,114651,0 +108911,Female,24,Bachelors,14,20,41,37,26,8.0,1,51,Rural,Software Engineer,98518,0 +108912,Male,43,Diploma,11,5,26,75,12,1.0,4,47,Urban,ML Engineer,29739,0 +108913,Female,59,Diploma,11,40,43,29,49,4.0,3,18,Urban,ML Engineer,45356,0 +108914,Male,55,High School,6,99,14,67,76,7.0,6,39,Urban,Data Analyst,49040,0 +108915,Female,54,Bachelors,12,55,98,56,61,8.0,6,37,Urban,Software Engineer,21718,1 +108916,Male,41,Bachelors,2,96,40,4,74,6.0,4,13,Urban,Manager,92707,0 +108917,Male,31,Diploma,13,41,71,38,8,3.0,6,12,Semi-Urban,ML Engineer,32003,0 +108918,Male,32,Masters,12,54,55,12,60,5.0,2,23,Semi-Urban,Software Engineer,80562,0 +108919,Male,36,High School,19,68,11,73,74,6.0,1,89,Urban,HR Executive,98198,1 +108920,Male,41,Bachelors,1,2,44,12,93,9.0,7,24,Rural,Manager,116287,0 +108921,Male,53,High School,4,20,75,27,83,9.0,5,95,Semi-Urban,HR Executive,55312,0 +108922,Female,52,Bachelors,2,41,52,59,73,6.0,5,50,Semi-Urban,Manager,24416,0 +108923,Female,23,High School,10,43,46,35,30,9.0,7,9,Urban,Software Engineer,146685,0 +108924,Male,50,Bachelors,14,7,4,39,90,7.0,0,37,Urban,ML Engineer,140255,0 +108925,Female,24,Diploma,13,68,51,93,10,6.0,6,88,Urban,Data Analyst,119256,1 +108926,Male,34,Bachelors,6,85,33,28,92,3.0,4,15,Urban,Software Engineer,42308,0 +108927,Male,55,Masters,1,40,28,25,14,9.0,7,84,Rural,Software Engineer,53290,0 +108928,Other,29,Bachelors,9,64,48,83,20,7.0,7,50,Urban,Software Engineer,30717,1 +108929,Male,47,Bachelors,16,61,17,37,59,3.0,4,45,Rural,Data Analyst,142740,0 +108930,Male,23,Masters,4,39,37,62,35,2.0,2,83,Urban,Data Analyst,70346,0 +108931,Male,51,Bachelors,17,20,90,83,56,4.0,2,93,Urban,HR Executive,81822,1 +108932,Female,43,Diploma,17,55,33,69,75,0.0,5,49,Urban,Software Engineer,66561,0 +108933,Female,43,Bachelors,18,91,2,10,25,2.0,0,71,Urban,Manager,54448,0 +108934,Male,25,Bachelors,4,39,25,61,61,6.0,6,33,Urban,Manager,105517,0 +108935,Female,42,Bachelors,16,59,56,90,60,7.0,7,28,Urban,Data Analyst,110035,0 +108936,Male,55,Diploma,18,90,37,34,46,5.0,5,53,Rural,ML Engineer,113717,0 +108937,Male,57,High School,3,8,38,9,16,1.0,0,12,Rural,ML Engineer,143136,0 +108938,Female,44,Masters,19,65,23,83,89,9.0,7,0,Urban,Manager,66165,0 +108939,Male,53,Bachelors,7,31,29,24,37,7.0,5,90,Urban,Data Analyst,46850,0 +108940,Male,54,Diploma,6,2,38,9,35,4.0,3,38,Rural,ML Engineer,121360,0 +108941,Female,42,High School,10,15,87,8,4,9.0,4,54,Urban,Manager,76599,0 +108942,Male,40,High School,8,96,38,84,5,4.0,7,6,Urban,ML Engineer,34187,0 +108943,Female,30,Bachelors,10,35,30,35,32,8.0,6,68,Urban,Manager,84226,0 +108944,Female,21,Bachelors,1,9,65,71,30,4.0,5,59,Semi-Urban,Data Analyst,84743,0 +108945,Female,25,Masters,10,55,13,83,74,1.0,6,71,Urban,Data Analyst,98563,0 +108946,Female,30,PhD,0,35,90,99,22,0.0,2,9,Urban,HR Executive,132514,0 +108947,Male,59,Bachelors,17,64,25,60,79,7.0,2,87,Semi-Urban,HR Executive,24092,1 +108948,Female,29,Bachelors,3,50,87,79,50,2.0,1,34,Rural,Manager,33515,1 +108949,Female,33,Diploma,9,42,15,32,65,2.0,4,36,Urban,HR Executive,119000,0 +108950,Male,47,Bachelors,5,68,94,97,82,7.0,7,61,Rural,Data Analyst,133069,1 +108951,Male,53,Bachelors,5,9,1,42,39,0.0,5,72,Urban,Data Analyst,58680,0 +108952,Female,50,Bachelors,11,86,29,55,62,5.0,4,4,Urban,Software Engineer,93890,0 +108953,Female,58,Bachelors,1,93,31,87,77,7.0,3,1,Urban,Software Engineer,85165,0 +108954,Male,44,Bachelors,0,29,26,6,72,4.0,3,14,Urban,Manager,69520,0 +108955,Other,35,Masters,5,20,23,20,5,4.0,0,75,Urban,Data Analyst,113019,0 +108956,Male,35,High School,19,12,53,79,25,7.0,2,3,Urban,Data Analyst,114003,0 +108957,Male,30,Masters,15,88,83,6,43,9.0,1,98,Semi-Urban,Manager,28757,1 +108958,Male,42,Bachelors,7,37,25,86,82,8.0,5,4,Semi-Urban,HR Executive,75154,0 +108959,Male,37,Bachelors,16,56,43,46,54,7.0,5,30,Semi-Urban,Software Engineer,41599,0 +108960,Male,51,Diploma,16,49,73,33,42,8.0,2,18,Semi-Urban,HR Executive,36381,0 +108961,Male,22,Bachelors,15,54,74,33,76,5.0,5,64,Urban,Data Analyst,111996,0 +108962,Male,37,Diploma,6,30,82,80,42,5.0,4,28,Urban,Manager,133127,0 +108963,Male,42,PhD,19,9,9,39,16,4.0,4,61,Rural,Software Engineer,95260,0 +108964,Male,42,Bachelors,8,35,19,80,38,5.0,4,81,Semi-Urban,Manager,75522,0 +108965,Female,23,Masters,5,78,25,54,72,4.0,6,13,Urban,HR Executive,21343,0 +108966,Male,37,Bachelors,1,65,33,33,98,8.0,3,69,Urban,HR Executive,94580,0 +108967,Female,38,Bachelors,8,70,42,68,25,3.0,2,94,Semi-Urban,Manager,21138,1 +108968,Other,29,Diploma,9,3,44,53,8,4.0,2,43,Rural,HR Executive,147879,0 +108969,Female,36,Bachelors,12,28,36,49,28,5.0,6,51,Rural,ML Engineer,47913,0 +108970,Female,42,Masters,3,89,7,74,33,2.0,3,29,Semi-Urban,Manager,148007,0 +108971,Male,39,Diploma,1,71,73,47,6,2.0,5,11,Urban,Software Engineer,45085,0 +108972,Female,55,Masters,11,23,11,87,55,5.0,6,28,Semi-Urban,ML Engineer,31136,0 +108973,Male,27,Masters,19,23,99,76,75,0.0,5,53,Urban,ML Engineer,103928,1 +108974,Male,29,Masters,19,83,40,63,4,9.0,2,5,Urban,Manager,24193,0 +108975,Female,21,Diploma,1,1,1,65,11,0.0,4,5,Rural,Manager,86747,0 +108976,Male,55,Diploma,7,96,16,23,7,2.0,3,60,Rural,Data Analyst,23143,0 +108977,Female,36,Diploma,6,83,66,79,37,4.0,0,31,Rural,ML Engineer,104469,1 +108978,Male,27,Bachelors,12,45,20,21,79,3.0,5,4,Rural,Data Analyst,69683,0 +108979,Male,43,Masters,16,4,14,55,13,8.0,1,15,Urban,Data Analyst,49147,0 +108980,Male,38,High School,14,49,48,92,75,4.0,2,52,Semi-Urban,Data Analyst,41742,1 +108981,Male,53,Bachelors,15,13,44,61,29,6.0,3,1,Semi-Urban,Data Analyst,69953,0 +108982,Female,58,Bachelors,8,4,27,84,98,8.0,1,15,Semi-Urban,Data Analyst,89121,0 +108983,Male,42,Bachelors,2,92,35,46,93,8.0,5,1,Urban,Data Analyst,72818,0 +108984,Male,59,Masters,1,72,36,35,52,3.0,5,84,Urban,HR Executive,39848,0 +108985,Male,30,Masters,8,6,97,30,8,6.0,0,80,Rural,Software Engineer,59856,0 +108986,Male,23,Masters,6,56,26,41,13,0.0,3,62,Urban,Data Analyst,143319,0 +108987,Female,34,Masters,13,28,63,12,96,1.0,7,49,Urban,ML Engineer,126526,0 +108988,Male,34,High School,11,6,2,62,26,5.0,3,1,Urban,HR Executive,78478,0 +108989,Male,28,High School,4,12,95,60,55,6.0,1,22,Urban,Software Engineer,46679,0 +108990,Male,51,PhD,17,52,8,74,52,9.0,1,40,Urban,HR Executive,126350,0 +108991,Male,41,Bachelors,13,18,68,45,93,9.0,2,31,Urban,ML Engineer,54573,0 +108992,Male,41,Masters,4,19,18,67,47,6.0,0,60,Rural,HR Executive,92350,0 +108993,Male,41,Bachelors,19,14,77,78,74,8.0,5,60,Rural,Manager,84556,0 +108994,Female,43,Masters,11,68,51,40,54,0.0,4,63,Urban,Manager,74348,0 +108995,Male,21,Bachelors,3,3,53,38,82,4.0,2,52,Rural,Software Engineer,78130,0 +108996,Female,38,Bachelors,10,60,62,29,53,7.0,6,21,Semi-Urban,Manager,40464,0 +108997,Male,22,Masters,15,19,34,66,61,8.0,7,62,Semi-Urban,Manager,112023,0 +108998,Female,55,Bachelors,11,88,86,36,83,8.0,2,91,Urban,ML Engineer,146435,1 +108999,Male,55,Bachelors,5,3,25,41,78,7.0,7,94,Rural,ML Engineer,56590,0 +109000,Male,24,Masters,8,90,54,90,1,9.0,7,61,Urban,Manager,104813,1 +109001,Male,31,Bachelors,9,83,31,88,39,1.0,3,19,Semi-Urban,Data Analyst,24332,0 +109002,Female,23,Diploma,15,90,32,56,84,9.0,3,57,Rural,Software Engineer,24331,0 +109003,Male,40,Diploma,11,10,41,8,36,3.0,3,13,Rural,HR Executive,143174,0 +109004,Male,25,Masters,14,40,80,24,85,1.0,1,37,Semi-Urban,Manager,149554,0 +109005,Female,35,Bachelors,18,66,74,59,34,5.0,2,80,Urban,HR Executive,65705,1 +109006,Male,51,Masters,9,50,80,71,5,2.0,5,99,Urban,Software Engineer,63296,1 +109007,Male,41,Diploma,19,19,83,15,95,2.0,2,29,Urban,ML Engineer,58011,0 +109008,Male,40,Bachelors,1,21,41,86,91,8.0,5,10,Rural,ML Engineer,142165,0 +109009,Male,25,Bachelors,16,25,38,21,71,9.0,6,58,Rural,Software Engineer,95076,0 +109010,Female,21,Masters,17,56,76,33,9,7.0,6,92,Urban,HR Executive,26217,1 +109011,Male,28,Diploma,3,81,93,26,20,4.0,3,71,Urban,Software Engineer,22838,1 +109012,Male,21,Bachelors,3,11,63,11,25,0.0,0,68,Semi-Urban,Data Analyst,117479,0 +109013,Male,48,Bachelors,15,43,2,84,83,5.0,3,72,Semi-Urban,ML Engineer,86703,0 +109014,Female,48,High School,2,35,94,7,33,0.0,3,16,Semi-Urban,Software Engineer,142821,0 +109015,Male,30,Bachelors,14,64,20,42,62,7.0,3,14,Semi-Urban,Software Engineer,79882,0 +109016,Male,40,Bachelors,1,67,29,30,4,3.0,1,40,Urban,Data Analyst,45857,0 +109017,Male,37,Diploma,3,44,12,68,71,7.0,0,80,Urban,Software Engineer,113146,0 +109018,Male,51,Bachelors,8,47,89,75,52,8.0,4,57,Semi-Urban,Manager,29584,1 +109019,Male,57,Bachelors,10,91,90,17,67,0.0,2,83,Rural,Software Engineer,94129,1 +109020,Male,31,Diploma,16,97,54,49,96,8.0,2,58,Urban,ML Engineer,59438,1 +109021,Other,46,Bachelors,10,38,29,42,3,6.0,6,72,Urban,Data Analyst,58540,0 +109022,Female,39,High School,4,92,21,30,6,6.0,1,88,Urban,HR Executive,57388,0 +109023,Male,26,Bachelors,13,29,43,60,80,6.0,0,14,Rural,HR Executive,23464,0 +109024,Female,59,Diploma,1,49,18,34,5,0.0,6,61,Urban,Data Analyst,123329,0 +109025,Male,50,Masters,9,74,52,35,18,8.0,0,80,Urban,ML Engineer,66110,1 +109026,Female,53,High School,3,12,78,88,8,2.0,7,78,Urban,Data Analyst,73613,1 +109027,Male,41,Diploma,8,21,79,43,40,8.0,0,75,Rural,HR Executive,147831,0 +109028,Male,45,Masters,4,5,66,67,36,9.0,4,71,Urban,ML Engineer,66567,0 +109029,Female,23,High School,7,60,32,36,78,2.0,2,81,Urban,Data Analyst,88513,0 +109030,Male,23,Masters,19,59,19,92,93,9.0,7,11,Urban,Software Engineer,71091,0 +109031,Male,43,Masters,6,73,97,54,39,7.0,4,41,Semi-Urban,Manager,54019,1 +109032,Male,51,Diploma,1,77,15,86,48,6.0,2,3,Urban,Data Analyst,62544,0 +109033,Female,56,Diploma,8,61,74,95,73,2.0,4,45,Semi-Urban,Software Engineer,148535,1 +109034,Male,25,Bachelors,18,13,48,41,44,9.0,2,60,Urban,ML Engineer,136579,0 +109035,Female,21,High School,0,50,1,78,65,9.0,1,23,Urban,Manager,72165,0 +109036,Female,28,Diploma,17,87,61,45,31,7.0,3,77,Urban,Data Analyst,116850,1 +109037,Male,46,High School,10,16,31,8,7,5.0,5,7,Rural,ML Engineer,110532,0 +109038,Male,34,High School,10,46,50,21,67,0.0,1,35,Rural,Data Analyst,64121,0 +109039,Other,35,Bachelors,15,48,68,33,76,6.0,5,90,Urban,HR Executive,143352,0 +109040,Male,40,Masters,15,35,55,55,46,3.0,5,59,Urban,Manager,109848,0 +109041,Male,44,Masters,18,40,69,5,5,7.0,2,86,Urban,ML Engineer,111999,0 +109042,Male,21,High School,16,27,28,85,30,2.0,5,14,Semi-Urban,HR Executive,104406,0 +109043,Male,38,Bachelors,7,7,97,79,63,5.0,3,34,Urban,ML Engineer,114901,0 +109044,Female,32,Masters,11,76,41,80,45,6.0,5,76,Urban,Manager,58237,1 +109045,Female,31,Bachelors,4,72,89,7,83,8.0,2,13,Semi-Urban,Data Analyst,74632,0 +109046,Female,29,Diploma,13,27,98,71,14,4.0,7,29,Urban,Data Analyst,103080,0 +109047,Male,29,Bachelors,14,19,93,62,92,2.0,6,63,Urban,Software Engineer,56279,1 +109048,Female,50,Bachelors,10,70,34,17,4,0.0,3,24,Rural,Manager,97414,0 +109049,Male,25,Diploma,2,43,75,52,45,5.0,6,15,Rural,ML Engineer,32626,0 +109050,Male,31,Bachelors,7,83,89,41,66,3.0,4,2,Urban,Manager,33435,0 +109051,Female,43,High School,7,57,0,87,98,7.0,3,56,Urban,Manager,125717,0 +109052,Male,32,Bachelors,13,39,17,22,7,1.0,3,94,Urban,ML Engineer,149707,0 +109053,Male,41,Bachelors,11,43,16,29,71,0.0,7,13,Urban,Software Engineer,47910,0 +109054,Female,48,Bachelors,11,11,60,35,30,1.0,7,88,Urban,Data Analyst,93421,0 +109055,Female,51,Bachelors,5,7,37,92,70,9.0,5,29,Urban,Data Analyst,65470,0 +109056,Male,50,High School,1,15,45,44,55,9.0,4,86,Rural,Software Engineer,114297,0 +109057,Male,39,High School,15,69,90,85,69,6.0,1,46,Rural,HR Executive,146516,1 +109058,Male,25,Bachelors,10,35,19,94,28,3.0,7,38,Semi-Urban,ML Engineer,75952,0 +109059,Female,22,High School,6,33,11,11,46,1.0,1,89,Rural,Manager,34480,0 +109060,Male,54,Bachelors,1,2,22,25,97,3.0,7,24,Urban,HR Executive,99802,0 +109061,Male,42,Bachelors,3,88,76,91,63,2.0,4,81,Urban,HR Executive,45983,1 +109062,Female,47,Diploma,15,23,5,1,45,4.0,3,26,Semi-Urban,Manager,82398,0 +109063,Male,47,Masters,5,14,63,45,67,3.0,7,84,Rural,ML Engineer,43007,0 +109064,Male,49,Diploma,8,22,68,12,74,8.0,4,64,Rural,Data Analyst,31675,0 +109065,Male,58,Masters,15,18,52,91,40,2.0,7,80,Urban,ML Engineer,98225,1 +109066,Male,22,Bachelors,9,52,1,45,94,8.0,3,22,Urban,HR Executive,137925,0 +109067,Female,25,Bachelors,17,66,80,28,0,8.0,4,52,Semi-Urban,HR Executive,30850,0 +109068,Male,45,Diploma,7,80,47,1,60,0.0,0,5,Urban,Data Analyst,126621,0 +109069,Male,55,Bachelors,16,4,94,45,47,8.0,3,28,Rural,ML Engineer,80105,0 +109070,Female,57,Bachelors,14,30,21,10,91,0.0,7,52,Urban,Manager,58275,0 +109071,Male,37,Bachelors,16,36,28,5,26,6.0,6,65,Urban,Manager,61913,0 +109072,Female,49,PhD,1,90,59,55,10,7.0,1,37,Rural,Data Analyst,84395,1 +109073,Female,38,Masters,9,62,8,24,83,7.0,2,14,Urban,Data Analyst,125002,0 +109074,Male,38,Masters,10,8,77,94,13,4.0,3,77,Semi-Urban,ML Engineer,120484,1 +109075,Female,22,Masters,16,11,25,55,40,4.0,1,58,Semi-Urban,Software Engineer,33617,0 +109076,Male,22,Bachelors,3,57,6,77,67,6.0,1,46,Semi-Urban,ML Engineer,101770,0 +109077,Male,36,PhD,15,66,13,11,31,5.0,5,90,Semi-Urban,Software Engineer,77943,0 +109078,Male,39,Bachelors,10,38,93,28,10,5.0,0,12,Rural,ML Engineer,65105,0 +109079,Male,35,Masters,0,72,1,65,85,6.0,2,11,Semi-Urban,Software Engineer,70394,0 +109080,Male,42,Masters,0,30,64,86,87,5.0,7,95,Urban,HR Executive,128486,1 +109081,Male,49,Bachelors,5,30,80,85,22,0.0,7,7,Semi-Urban,Software Engineer,59148,0 +109082,Female,30,High School,10,44,32,46,87,6.0,3,92,Urban,ML Engineer,27444,0 +109083,Male,22,Diploma,15,70,56,43,24,0.0,7,64,Semi-Urban,Software Engineer,37434,0 +109084,Male,58,Bachelors,8,70,42,55,96,8.0,7,8,Urban,Data Analyst,113059,0 +109085,Male,41,Masters,16,55,52,91,1,2.0,2,84,Semi-Urban,ML Engineer,139602,1 +109086,Male,39,Diploma,17,92,38,85,34,6.0,7,11,Urban,Software Engineer,142886,0 +109087,Male,55,Bachelors,6,59,87,6,31,8.0,0,54,Semi-Urban,Manager,57106,0 +109088,Female,49,Masters,19,76,19,90,7,1.0,1,10,Urban,Software Engineer,139559,0 +109089,Male,36,Bachelors,9,72,74,62,6,6.0,1,88,Urban,Manager,59867,1 +109090,Female,59,Masters,3,2,57,72,82,5.0,5,90,Semi-Urban,ML Engineer,123073,0 +109091,Male,28,Bachelors,19,11,70,57,23,9.0,3,5,Semi-Urban,Software Engineer,69558,0 +109092,Other,33,Bachelors,2,66,91,20,99,6.0,5,23,Urban,HR Executive,107238,0 +109093,Female,54,Diploma,14,70,86,10,12,7.0,2,55,Urban,Software Engineer,25112,0 +109094,Male,24,Bachelors,7,53,59,9,6,1.0,7,54,Urban,Manager,29381,0 +109095,Male,32,Masters,0,80,96,80,59,9.0,4,97,Rural,Software Engineer,90162,1 +109096,Male,46,Masters,17,40,38,23,96,5.0,1,22,Urban,Software Engineer,148935,0 +109097,Male,43,Diploma,2,59,51,5,43,2.0,2,77,Rural,Data Analyst,71049,0 +109098,Male,26,Bachelors,8,30,47,72,74,8.0,5,75,Urban,Manager,66471,0 +109099,Female,35,High School,16,93,59,39,13,8.0,6,77,Semi-Urban,HR Executive,77863,1 +109100,Female,24,Diploma,16,95,93,58,78,1.0,1,14,Urban,Manager,104792,1 +109101,Male,38,High School,1,42,1,48,85,6.0,0,31,Rural,Data Analyst,35794,0 +109102,Female,22,Bachelors,0,64,39,39,62,2.0,0,57,Semi-Urban,HR Executive,24770,0 +109103,Female,56,Bachelors,0,98,28,78,58,8.0,4,69,Rural,HR Executive,57415,1 +109104,Male,23,Bachelors,7,94,93,80,76,9.0,5,68,Urban,Software Engineer,116495,1 +109105,Male,29,Diploma,1,13,91,97,22,6.0,4,7,Rural,Manager,113127,0 +109106,Male,53,Bachelors,5,16,16,56,72,3.0,3,99,Urban,Software Engineer,39574,0 +109107,Male,48,Bachelors,5,47,2,2,62,9.0,3,50,Urban,ML Engineer,71436,0 +109108,Female,54,Bachelors,1,77,72,15,65,9.0,7,63,Semi-Urban,Data Analyst,121026,0 +109109,Female,25,Bachelors,19,94,83,89,1,9.0,4,41,Urban,Data Analyst,71823,1 +109110,Male,43,Masters,2,63,84,93,45,1.0,0,78,Urban,Software Engineer,70973,1 +109111,Male,33,Bachelors,13,56,22,84,26,4.0,7,23,Rural,Data Analyst,44814,0 +109112,Female,34,Bachelors,15,18,33,14,58,7.0,1,72,Semi-Urban,HR Executive,140360,0 +109113,Male,45,High School,7,82,21,68,83,5.0,0,7,Urban,HR Executive,60026,0 +109114,Male,24,Bachelors,2,75,16,82,12,8.0,6,37,Urban,Software Engineer,87482,0 +109115,Female,52,Bachelors,2,73,44,68,7,8.0,6,20,Urban,ML Engineer,119701,0 +109116,Male,23,Bachelors,14,99,77,50,15,7.0,2,17,Urban,HR Executive,141502,1 +109117,Female,52,Masters,17,46,58,46,68,8.0,2,30,Urban,HR Executive,36071,0 +109118,Male,28,Masters,9,79,81,16,31,0.0,7,88,Rural,Data Analyst,118662,1 +109119,Female,28,Masters,16,59,23,53,68,9.0,7,59,Urban,Manager,20633,0 +109120,Female,54,Masters,7,89,38,39,9,9.0,1,59,Semi-Urban,HR Executive,119031,0 +109121,Female,32,Bachelors,15,71,80,99,86,0.0,5,16,Rural,ML Engineer,120286,1 +109122,Male,36,Bachelors,9,99,29,59,70,1.0,4,86,Urban,Data Analyst,118469,1 +109123,Male,32,Masters,18,20,22,62,38,2.0,7,61,Semi-Urban,Software Engineer,147091,0 +109124,Male,52,Masters,8,66,53,25,2,1.0,7,55,Urban,Software Engineer,141364,0 +109125,Female,21,Bachelors,14,65,92,45,8,2.0,1,93,Rural,ML Engineer,79386,1 +109126,Female,59,Bachelors,1,66,76,89,10,6.0,3,58,Rural,Software Engineer,27957,1 +109127,Male,26,Masters,0,33,29,64,80,1.0,6,82,Urban,Data Analyst,32189,0 +109128,Male,53,Masters,3,52,89,34,30,3.0,4,38,Semi-Urban,Manager,124052,0 +109129,Male,52,Masters,3,85,45,71,0,1.0,3,62,Semi-Urban,Manager,47004,1 +109130,Male,35,Bachelors,10,78,1,82,15,4.0,6,71,Urban,Manager,100040,0 +109131,Male,21,Bachelors,11,1,71,54,12,0.0,0,44,Urban,Manager,122066,0 +109132,Male,36,Bachelors,14,82,24,57,20,8.0,7,40,Urban,Manager,41053,0 +109133,Male,55,PhD,2,75,38,42,61,8.0,0,15,Semi-Urban,ML Engineer,40709,0 +109134,Female,45,Bachelors,16,65,65,46,13,3.0,4,70,Urban,Manager,128189,1 +109135,Female,29,Masters,8,18,24,14,70,8.0,2,93,Semi-Urban,Manager,95850,0 +109136,Male,45,High School,19,65,79,29,30,8.0,3,54,Urban,Manager,92848,0 +109137,Male,29,Diploma,19,85,51,5,21,6.0,0,36,Rural,HR Executive,119318,0 +109138,Male,44,Diploma,7,81,60,84,96,0.0,7,39,Rural,ML Engineer,56585,1 +109139,Female,56,Bachelors,12,81,59,61,79,0.0,3,83,Urban,Software Engineer,76395,1 +109140,Female,46,Bachelors,9,24,39,66,57,0.0,2,87,Semi-Urban,ML Engineer,75189,0 +109141,Female,58,Masters,4,0,7,69,7,6.0,6,61,Urban,Software Engineer,138706,0 +109142,Male,22,High School,17,85,40,46,51,1.0,6,14,Semi-Urban,Software Engineer,89689,0 +109143,Male,47,Masters,10,2,9,87,38,7.0,7,25,Urban,Data Analyst,129976,0 +109144,Male,39,Diploma,2,7,3,72,35,3.0,1,51,Semi-Urban,Manager,53648,0 +109145,Female,30,Masters,7,20,24,77,70,1.0,0,35,Urban,Software Engineer,60761,0 +109146,Female,48,Bachelors,8,54,66,68,74,9.0,0,30,Semi-Urban,ML Engineer,83771,0 +109147,Female,38,Masters,1,34,9,73,13,9.0,6,19,Urban,Manager,120571,0 +109148,Male,50,Bachelors,0,36,22,58,59,3.0,5,69,Rural,ML Engineer,58454,0 +109149,Female,25,Bachelors,15,19,51,23,37,3.0,3,88,Urban,ML Engineer,69877,0 +109150,Male,56,High School,11,65,56,61,54,5.0,2,0,Urban,Manager,123143,0 +109151,Female,33,Diploma,16,20,97,76,10,8.0,5,51,Urban,ML Engineer,111397,1 +109152,Male,57,Bachelors,11,1,12,90,80,4.0,5,14,Urban,ML Engineer,22060,0 +109153,Male,53,Bachelors,9,11,29,41,59,6.0,2,76,Semi-Urban,Data Analyst,41030,0 +109154,Male,27,Bachelors,14,73,94,74,83,9.0,5,11,Urban,ML Engineer,126499,1 +109155,Female,50,Bachelors,2,67,86,1,45,7.0,7,78,Urban,Manager,47892,0 +109156,Female,45,Bachelors,5,85,38,40,23,4.0,2,25,Semi-Urban,Software Engineer,41341,0 +109157,Male,33,Bachelors,6,45,36,0,75,0.0,6,1,Urban,Manager,133616,0 +109158,Male,31,Bachelors,7,22,94,35,40,0.0,4,74,Urban,Manager,118260,0 +109159,Male,31,PhD,16,34,64,56,13,6.0,2,9,Urban,Data Analyst,55198,0 +109160,Male,44,Bachelors,16,67,15,44,82,1.0,2,52,Semi-Urban,HR Executive,70459,0 +109161,Male,23,Diploma,2,34,94,12,78,5.0,4,26,Semi-Urban,Software Engineer,55207,0 +109162,Male,59,Diploma,6,7,58,59,64,1.0,5,62,Rural,Software Engineer,138055,0 +109163,Male,41,Bachelors,4,63,96,65,23,4.0,6,54,Semi-Urban,ML Engineer,59257,1 +109164,Male,48,Bachelors,19,18,69,65,93,7.0,1,75,Urban,Manager,79264,0 +109165,Male,41,Diploma,13,5,56,71,15,4.0,6,49,Urban,HR Executive,44630,0 +109166,Female,32,PhD,14,2,11,2,62,4.0,3,41,Semi-Urban,HR Executive,36532,0 +109167,Female,52,High School,4,13,40,32,20,3.0,6,64,Urban,HR Executive,130889,0 +109168,Male,30,Bachelors,11,70,13,79,53,8.0,7,38,Urban,Manager,76663,0 +109169,Male,41,Masters,13,67,71,54,85,1.0,6,99,Semi-Urban,Manager,78274,1 +109170,Male,45,Bachelors,8,65,76,54,53,6.0,3,22,Urban,Manager,64937,0 +109171,Male,40,Diploma,2,7,78,90,60,2.0,7,68,Rural,ML Engineer,68605,1 +109172,Female,27,PhD,9,73,80,0,60,8.0,6,30,Rural,HR Executive,146683,0 +109173,Female,22,Bachelors,19,33,14,16,14,7.0,1,83,Urban,HR Executive,50672,0 +109174,Male,49,Masters,2,5,12,47,86,2.0,7,46,Rural,Manager,107977,0 +109175,Male,56,Bachelors,11,31,52,43,53,2.0,4,67,Urban,Data Analyst,140540,0 +109176,Male,46,Diploma,3,20,78,32,64,6.0,3,52,Urban,Manager,36183,0 +109177,Male,56,Diploma,3,42,95,11,59,6.0,7,27,Rural,Manager,131981,0 +109178,Male,22,Bachelors,1,17,39,14,70,6.0,0,6,Urban,ML Engineer,106098,0 +109179,Female,59,Bachelors,18,60,9,63,76,4.0,2,9,Semi-Urban,ML Engineer,90599,0 +109180,Female,50,Masters,4,10,49,72,4,9.0,4,53,Semi-Urban,Manager,66779,0 +109181,Male,31,High School,12,87,26,60,60,0.0,6,61,Urban,ML Engineer,28848,0 +109182,Male,47,Diploma,12,3,61,91,77,2.0,7,36,Urban,ML Engineer,141918,0 +109183,Female,26,Bachelors,18,98,6,68,97,6.0,6,60,Urban,HR Executive,74253,0 +109184,Female,37,Bachelors,14,58,73,68,22,2.0,7,81,Urban,Software Engineer,41824,1 +109185,Male,25,High School,19,39,21,91,49,3.0,7,23,Urban,Software Engineer,87447,0 +109186,Female,55,Masters,15,32,64,3,11,9.0,4,28,Urban,Software Engineer,51035,0 +109187,Male,34,Bachelors,15,85,0,34,8,8.0,5,68,Rural,Software Engineer,75510,0 +109188,Male,47,Masters,0,94,28,37,4,1.0,0,43,Urban,ML Engineer,66643,0 +109189,Male,34,Masters,6,43,46,65,10,4.0,0,43,Urban,HR Executive,104834,0 +109190,Female,31,Bachelors,11,51,16,54,79,2.0,4,33,Urban,Manager,73081,0 +109191,Male,45,Diploma,1,96,37,77,39,9.0,1,94,Rural,HR Executive,97985,1 +109192,Male,22,Bachelors,7,39,62,94,49,1.0,6,43,Urban,ML Engineer,92121,1 +109193,Male,58,Bachelors,13,30,15,61,84,6.0,7,30,Urban,Manager,29134,0 +109194,Female,45,Diploma,18,71,45,18,99,4.0,4,6,Urban,Software Engineer,83061,0 +109195,Male,38,Bachelors,1,85,75,82,41,6.0,0,20,Semi-Urban,Manager,81679,1 +109196,Female,54,Bachelors,10,85,81,69,22,2.0,1,8,Semi-Urban,HR Executive,38044,1 +109197,Male,45,High School,3,19,26,20,68,7.0,7,63,Urban,Data Analyst,34994,0 +109198,Male,25,High School,6,53,72,77,57,2.0,3,50,Urban,Data Analyst,127375,1 +109199,Male,52,Diploma,9,76,17,38,2,6.0,5,19,Urban,HR Executive,52863,0 +109200,Male,47,Bachelors,0,55,0,72,41,3.0,0,32,Urban,Manager,35400,0 +109201,Male,56,High School,3,76,30,78,53,5.0,2,73,Urban,Manager,51182,1 +109202,Female,27,Masters,11,51,15,45,1,5.0,2,70,Urban,Software Engineer,66572,0 +109203,Female,41,Diploma,14,87,28,32,1,1.0,6,29,Rural,Data Analyst,107156,0 +109204,Male,33,Bachelors,10,75,29,12,47,1.0,6,97,Urban,ML Engineer,29167,0 +109205,Male,59,Bachelors,6,57,24,52,25,5.0,7,91,Semi-Urban,Data Analyst,25703,0 +109206,Male,32,Masters,4,3,45,27,50,3.0,5,73,Urban,Data Analyst,147672,0 +109207,Male,27,Bachelors,12,40,11,83,38,7.0,4,49,Rural,HR Executive,60570,0 +109208,Male,36,Diploma,2,61,2,77,87,2.0,5,89,Urban,Manager,116522,0 +109209,Female,37,Diploma,1,37,50,78,65,5.0,6,22,Semi-Urban,ML Engineer,79912,0 +109210,Male,46,Bachelors,0,38,64,32,59,9.0,5,7,Rural,Data Analyst,83083,0 +109211,Male,42,PhD,3,74,13,53,20,5.0,6,89,Urban,ML Engineer,74802,0 +109212,Female,31,High School,3,53,68,31,45,2.0,6,80,Semi-Urban,Data Analyst,134616,0 +109213,Female,21,Diploma,15,51,11,91,80,7.0,1,37,Urban,ML Engineer,89413,0 +109214,Female,41,High School,7,16,25,40,9,8.0,5,4,Rural,ML Engineer,74651,0 +109215,Female,43,Masters,3,6,25,49,45,4.0,1,11,Rural,Manager,144965,0 +109216,Male,32,Bachelors,12,27,73,22,55,5.0,7,64,Urban,HR Executive,36890,0 +109217,Male,28,Bachelors,16,71,98,32,47,1.0,2,21,Semi-Urban,HR Executive,80526,0 +109218,Male,29,High School,8,56,82,45,30,0.0,3,98,Urban,HR Executive,130340,1 +109219,Female,52,Masters,8,25,28,91,63,2.0,6,43,Semi-Urban,ML Engineer,27664,0 +109220,Female,32,Diploma,14,43,80,38,99,1.0,5,29,Urban,ML Engineer,43583,0 +109221,Female,58,Bachelors,16,84,72,25,89,0.0,2,0,Urban,HR Executive,138892,0 +109222,Female,24,Masters,16,78,65,25,38,5.0,1,80,Rural,HR Executive,139765,1 +109223,Female,53,Diploma,12,36,32,30,26,2.0,7,81,Urban,Data Analyst,113153,0 +109224,Female,27,Diploma,6,98,12,66,70,0.0,5,32,Semi-Urban,ML Engineer,22893,0 +109225,Female,21,Bachelors,1,38,7,58,48,5.0,3,12,Semi-Urban,Manager,36407,0 +109226,Male,41,Bachelors,5,8,6,42,58,4.0,0,46,Semi-Urban,ML Engineer,94530,0 +109227,Female,32,Masters,18,46,3,27,6,1.0,6,51,Urban,Manager,31562,0 +109228,Male,44,Masters,8,3,59,67,14,3.0,3,16,Urban,Data Analyst,74850,0 +109229,Male,59,Diploma,1,27,13,74,42,8.0,0,87,Urban,Manager,76966,0 +109230,Male,28,Bachelors,4,26,37,15,45,0.0,5,39,Urban,ML Engineer,114806,0 +109231,Female,22,High School,9,5,99,27,67,9.0,0,90,Urban,Software Engineer,28479,0 +109232,Male,41,High School,12,5,23,65,73,9.0,3,88,Semi-Urban,Software Engineer,135906,0 +109233,Male,33,PhD,15,86,62,79,46,1.0,0,68,Urban,Software Engineer,120252,1 +109234,Female,56,Masters,14,65,63,87,56,8.0,7,96,Rural,Software Engineer,147604,1 +109235,Male,36,Bachelors,5,82,73,62,95,6.0,2,50,Rural,ML Engineer,58734,1 +109236,Male,55,Masters,14,41,65,23,0,5.0,4,48,Semi-Urban,ML Engineer,29472,0 +109237,Male,27,Diploma,2,18,58,82,34,5.0,3,70,Rural,Data Analyst,120819,0 +109238,Female,41,Diploma,6,10,25,52,19,8.0,3,1,Urban,HR Executive,92531,0 +109239,Male,45,Bachelors,0,52,77,8,19,8.0,0,42,Rural,ML Engineer,41472,0 +109240,Male,48,Masters,18,30,50,71,17,1.0,4,6,Urban,HR Executive,46612,0 +109241,Male,53,Bachelors,12,96,54,23,46,8.0,1,50,Urban,ML Engineer,20774,0 +109242,Female,36,Bachelors,4,11,79,13,90,4.0,6,85,Urban,Software Engineer,107412,0 +109243,Female,25,High School,17,32,47,38,32,7.0,3,24,Semi-Urban,Software Engineer,147317,0 +109244,Female,41,Masters,15,11,23,30,94,0.0,5,99,Rural,ML Engineer,31918,0 +109245,Female,50,Diploma,9,97,15,75,17,6.0,6,73,Semi-Urban,HR Executive,142973,1 +109246,Male,37,Bachelors,17,17,66,27,66,2.0,0,90,Rural,Data Analyst,129398,0 +109247,Female,54,Diploma,16,67,34,65,70,3.0,0,54,Rural,Manager,102808,0 +109248,Female,22,Masters,19,14,77,72,75,0.0,6,41,Urban,Software Engineer,55544,0 +109249,Female,52,Bachelors,1,39,23,4,67,9.0,6,22,Urban,HR Executive,74651,0 +109250,Female,36,Bachelors,15,39,42,81,93,5.0,4,82,Urban,Data Analyst,24781,1 +109251,Female,58,High School,5,18,48,0,38,2.0,1,54,Semi-Urban,Data Analyst,88518,0 +109252,Male,23,Bachelors,8,76,60,89,74,4.0,4,72,Semi-Urban,Data Analyst,47338,1 +109253,Other,24,Bachelors,17,19,16,27,33,8.0,3,52,Urban,ML Engineer,51362,0 +109254,Male,24,PhD,2,36,34,96,86,5.0,1,54,Urban,Data Analyst,41232,0 +109255,Female,44,High School,19,19,47,7,48,7.0,0,74,Urban,Data Analyst,128798,0 +109256,Male,34,Masters,1,41,37,10,86,4.0,6,92,Urban,Manager,116716,0 +109257,Male,44,Diploma,4,94,44,51,94,4.0,2,74,Urban,Data Analyst,137592,1 +109258,Male,27,Bachelors,10,74,71,83,11,8.0,2,68,Semi-Urban,HR Executive,94126,1 +109259,Female,51,Bachelors,0,83,17,23,37,0.0,0,80,Rural,Software Engineer,121666,0 +109260,Male,52,Masters,19,85,66,65,54,8.0,3,5,Rural,HR Executive,136320,0 +109261,Male,34,Bachelors,16,49,32,38,9,5.0,2,74,Urban,HR Executive,89213,0 +109262,Male,27,Bachelors,16,85,24,41,4,3.0,6,1,Rural,Data Analyst,111620,0 +109263,Male,53,Diploma,18,33,36,71,87,1.0,1,65,Urban,HR Executive,85403,0 +109264,Male,51,Bachelors,17,90,32,3,38,8.0,7,50,Semi-Urban,HR Executive,58227,0 +109265,Male,47,Bachelors,11,73,80,33,48,0.0,1,36,Semi-Urban,ML Engineer,68110,0 +109266,Male,26,Diploma,11,49,62,56,61,1.0,5,18,Urban,HR Executive,54125,0 +109267,Female,27,Bachelors,13,19,54,73,47,0.0,5,64,Semi-Urban,ML Engineer,119966,0 +109268,Male,38,Diploma,5,29,42,2,40,7.0,1,38,Urban,HR Executive,70197,0 +109269,Female,46,Diploma,11,55,96,79,66,6.0,4,97,Semi-Urban,Manager,107651,1 +109270,Female,34,PhD,3,38,11,75,55,4.0,5,6,Semi-Urban,ML Engineer,76213,0 +109271,Female,21,Bachelors,6,3,35,16,79,8.0,3,41,Urban,ML Engineer,100477,0 +109272,Male,45,High School,12,97,9,84,13,8.0,4,19,Urban,Manager,97378,0 +109273,Male,24,Bachelors,17,73,41,2,27,0.0,2,33,Urban,HR Executive,80686,0 +109274,Male,58,High School,2,95,64,58,27,8.0,4,3,Urban,HR Executive,142590,0 +109275,Male,39,Bachelors,10,96,77,57,43,5.0,5,21,Semi-Urban,ML Engineer,73365,1 +109276,Male,41,High School,17,89,49,42,68,5.0,7,19,Rural,Manager,43377,0 +109277,Male,45,Diploma,18,63,78,0,30,3.0,4,25,Urban,HR Executive,92348,0 +109278,Female,27,Bachelors,2,39,8,34,59,6.0,2,79,Rural,HR Executive,119773,0 +109279,Male,21,Diploma,16,44,43,15,12,1.0,3,55,Semi-Urban,ML Engineer,145826,0 +109280,Female,29,Diploma,0,76,19,34,97,3.0,3,69,Rural,ML Engineer,117454,0 +109281,Male,48,Diploma,19,33,89,36,40,5.0,5,6,Urban,Data Analyst,29708,0 +109282,Female,46,Bachelors,19,0,15,35,52,9.0,4,94,Semi-Urban,Software Engineer,96394,0 +109283,Female,22,Bachelors,14,14,67,85,20,3.0,7,86,Rural,HR Executive,83982,1 +109284,Male,35,High School,4,20,32,89,85,0.0,6,48,Rural,Manager,148514,0 +109285,Male,57,Bachelors,19,73,57,26,40,2.0,4,18,Semi-Urban,Manager,75371,0 +109286,Female,59,Bachelors,16,20,93,54,56,7.0,0,16,Rural,Manager,144791,0 +109287,Male,22,Bachelors,10,50,77,74,65,1.0,2,57,Urban,HR Executive,93069,1 +109288,Female,42,Masters,17,14,45,42,11,9.0,1,64,Semi-Urban,ML Engineer,41936,0 +109289,Male,42,Bachelors,2,41,64,48,49,2.0,6,28,Semi-Urban,Manager,132285,0 +109290,Female,21,Diploma,13,18,83,30,48,0.0,0,21,Rural,HR Executive,131771,0 +109291,Male,30,Masters,5,52,55,17,58,9.0,4,25,Rural,Data Analyst,64173,0 +109292,Male,42,Bachelors,6,94,34,8,29,8.0,6,14,Semi-Urban,Data Analyst,45333,0 +109293,Female,48,Masters,9,47,8,70,79,8.0,3,27,Semi-Urban,Data Analyst,47939,0 +109294,Female,41,High School,7,21,14,9,37,6.0,1,92,Urban,Software Engineer,112916,0 +109295,Male,52,PhD,5,1,15,73,46,4.0,5,8,Semi-Urban,Manager,46090,0 +109296,Male,27,Bachelors,4,85,35,18,60,3.0,4,15,Urban,Software Engineer,106068,0 +109297,Male,34,Diploma,3,34,34,25,51,3.0,1,74,Rural,Data Analyst,60902,0 +109298,Male,21,Masters,18,20,15,4,22,5.0,6,75,Urban,Software Engineer,100833,0 +109299,Male,52,Masters,7,69,38,73,71,9.0,0,77,Semi-Urban,Data Analyst,84502,1 +109300,Male,47,PhD,8,50,88,11,0,3.0,5,36,Urban,HR Executive,112692,0 +109301,Male,24,High School,4,98,2,59,84,2.0,7,66,Rural,Software Engineer,44819,0 +109302,Female,51,Bachelors,10,71,28,61,26,3.0,1,12,Urban,Software Engineer,132414,0 +109303,Male,23,Diploma,7,70,50,88,96,1.0,5,32,Urban,Manager,37708,1 +109304,Female,23,Bachelors,17,11,56,49,34,3.0,5,4,Urban,Data Analyst,41839,0 +109305,Male,32,Bachelors,4,89,71,90,90,5.0,5,95,Urban,ML Engineer,139387,1 +109306,Male,26,Diploma,9,91,50,83,30,9.0,5,5,Semi-Urban,Data Analyst,40529,0 +109307,Male,45,Bachelors,10,37,16,38,79,8.0,5,16,Urban,Manager,68468,0 +109308,Female,28,PhD,18,42,15,12,93,2.0,3,41,Urban,Data Analyst,34325,0 +109309,Female,34,Bachelors,18,39,89,77,24,9.0,5,30,Urban,Manager,149470,0 +109310,Male,57,Bachelors,10,7,95,12,87,3.0,4,11,Semi-Urban,HR Executive,143755,0 +109311,Female,22,PhD,16,50,67,74,37,9.0,4,33,Rural,Manager,78131,0 +109312,Male,34,Diploma,8,64,37,54,25,9.0,6,27,Rural,HR Executive,147458,0 +109313,Male,52,Masters,0,78,52,62,69,8.0,7,6,Urban,ML Engineer,123413,0 +109314,Male,30,Bachelors,13,15,23,37,25,4.0,2,96,Urban,HR Executive,148942,0 +109315,Male,39,Diploma,5,4,11,41,94,8.0,2,15,Semi-Urban,Software Engineer,111094,0 +109316,Male,43,Bachelors,8,38,65,64,36,7.0,6,61,Urban,ML Engineer,35896,0 +109317,Female,55,Masters,18,74,78,97,53,6.0,6,10,Semi-Urban,Manager,48456,1 +109318,Female,47,Masters,2,94,38,23,21,6.0,0,86,Semi-Urban,ML Engineer,38111,1 +109319,Male,38,Bachelors,6,1,16,18,75,6.0,5,29,Rural,HR Executive,20422,0 +109320,Male,33,Bachelors,11,61,86,49,49,9.0,4,24,Semi-Urban,HR Executive,71651,0 +109321,Female,51,Masters,3,49,79,39,27,6.0,5,62,Urban,Data Analyst,66315,0 +109322,Male,37,High School,13,45,44,35,67,1.0,0,1,Urban,Data Analyst,55076,0 +109323,Female,30,Bachelors,19,43,38,38,23,4.0,7,63,Urban,Manager,91481,0 +109324,Male,28,Masters,9,96,5,51,64,6.0,4,96,Urban,Manager,129173,1 +109325,Male,40,Bachelors,17,14,75,37,48,9.0,4,81,Rural,ML Engineer,20710,0 +109326,Male,47,Bachelors,14,13,79,49,51,6.0,4,65,Urban,Data Analyst,139562,0 +109327,Male,37,High School,9,80,6,4,11,0.0,6,36,Semi-Urban,ML Engineer,89666,0 +109328,Male,37,High School,17,64,27,31,79,8.0,7,58,Urban,ML Engineer,79397,0 +109329,Male,25,Bachelors,4,70,97,21,18,9.0,1,71,Urban,Data Analyst,98830,1 +109330,Male,35,Diploma,16,16,6,63,53,9.0,4,33,Urban,Data Analyst,131620,0 +109331,Male,47,Masters,8,68,98,55,73,9.0,7,37,Urban,Manager,25018,1 +109332,Female,52,High School,6,43,30,99,77,7.0,5,86,Urban,Software Engineer,79701,1 +109333,Male,55,Diploma,3,40,86,84,34,8.0,1,3,Urban,HR Executive,84380,0 +109334,Female,50,Bachelors,7,89,42,82,47,9.0,6,37,Rural,Manager,90057,1 +109335,Male,45,Diploma,18,78,99,69,25,3.0,2,95,Urban,Manager,57550,1 +109336,Female,25,Bachelors,11,52,57,60,14,5.0,4,81,Urban,Software Engineer,88175,1 +109337,Male,58,Bachelors,11,93,48,33,35,5.0,6,55,Rural,HR Executive,42872,0 +109338,Male,28,Diploma,10,58,46,96,6,7.0,0,22,Urban,HR Executive,41495,0 +109339,Male,31,Bachelors,0,57,89,37,44,6.0,0,14,Urban,ML Engineer,140560,0 +109340,Male,25,Masters,14,7,82,58,32,9.0,2,91,Urban,ML Engineer,90078,1 +109341,Female,58,Bachelors,13,49,0,21,99,5.0,2,82,Urban,ML Engineer,22385,0 +109342,Female,30,Diploma,7,43,11,13,22,4.0,4,31,Urban,Manager,130697,0 +109343,Male,35,Masters,5,72,98,47,31,4.0,0,79,Rural,ML Engineer,90201,1 +109344,Female,30,Masters,14,11,56,61,77,2.0,7,63,Semi-Urban,Software Engineer,23083,0 +109345,Male,37,Diploma,18,32,87,85,41,9.0,6,47,Urban,Software Engineer,33290,1 +109346,Male,47,High School,19,61,95,50,23,3.0,5,83,Semi-Urban,Software Engineer,79843,1 +109347,Female,54,Masters,10,89,50,50,25,9.0,5,64,Rural,Manager,74508,1 +109348,Male,39,Bachelors,2,56,53,29,25,6.0,3,59,Urban,Manager,125630,0 +109349,Male,43,Bachelors,3,97,48,45,4,3.0,7,57,Urban,Data Analyst,45954,1 +109350,Female,27,Masters,4,45,33,20,83,5.0,5,60,Urban,Data Analyst,108243,0 +109351,Male,35,Masters,1,31,94,13,67,8.0,4,16,Urban,HR Executive,109287,0 +109352,Male,54,Masters,11,37,97,45,92,8.0,2,57,Semi-Urban,Software Engineer,134652,1 +109353,Female,25,Bachelors,8,15,21,9,12,5.0,4,42,Rural,Data Analyst,128569,0 +109354,Other,30,High School,2,61,92,80,58,7.0,0,58,Urban,HR Executive,146681,1 +109355,Male,38,High School,10,52,73,28,2,7.0,4,11,Urban,Software Engineer,24590,0 +109356,Male,38,Bachelors,10,47,29,66,39,0.0,7,40,Semi-Urban,Software Engineer,98875,0 +109357,Male,44,PhD,8,48,6,75,7,0.0,4,10,Rural,ML Engineer,89596,0 +109358,Female,47,Diploma,2,55,73,8,97,7.0,0,20,Rural,ML Engineer,23126,0 +109359,Male,39,Bachelors,2,16,17,14,94,0.0,1,9,Urban,Software Engineer,143022,0 +109360,Male,38,Diploma,14,25,63,83,61,1.0,1,18,Semi-Urban,HR Executive,126513,0 +109361,Female,21,Bachelors,10,94,6,25,61,3.0,7,45,Semi-Urban,Data Analyst,109586,0 +109362,Female,52,Diploma,0,41,32,14,43,6.0,3,10,Rural,Software Engineer,33178,0 +109363,Male,32,High School,2,84,30,48,57,8.0,7,47,Urban,ML Engineer,130010,0 +109364,Male,50,Diploma,17,82,8,7,33,7.0,7,40,Urban,Software Engineer,26414,0 +109365,Female,26,Bachelors,0,11,62,71,17,2.0,4,65,Urban,Manager,46653,0 +109366,Female,28,Masters,1,47,44,67,63,8.0,7,23,Urban,HR Executive,50888,0 +109367,Female,37,Bachelors,12,42,65,80,81,5.0,0,65,Semi-Urban,Software Engineer,119750,1 +109368,Male,42,High School,15,85,2,84,36,0.0,4,65,Rural,HR Executive,119545,1 +109369,Male,41,Bachelors,2,55,30,40,78,4.0,0,59,Urban,Manager,96636,0 +109370,Male,24,Diploma,6,14,62,7,29,6.0,2,20,Urban,Data Analyst,112146,0 +109371,Female,44,Diploma,18,12,81,99,30,5.0,5,74,Urban,ML Engineer,56583,1 +109372,Male,37,Bachelors,17,91,51,43,84,9.0,7,27,Urban,Software Engineer,64570,0 +109373,Male,52,Bachelors,2,82,3,38,11,6.0,3,81,Urban,HR Executive,138469,0 +109374,Female,48,Bachelors,0,54,70,7,48,4.0,4,16,Urban,ML Engineer,74351,0 +109375,Female,54,Bachelors,17,84,1,90,13,8.0,2,17,Urban,Manager,140682,0 +109376,Female,32,High School,0,60,85,81,87,6.0,4,26,Rural,Data Analyst,91716,1 +109377,Male,26,Bachelors,13,52,80,31,14,8.0,1,58,Semi-Urban,Manager,80941,0 +109378,Female,42,Diploma,16,26,74,75,60,5.0,0,75,Urban,Software Engineer,67998,1 +109379,Other,33,Bachelors,14,15,34,40,93,6.0,4,84,Semi-Urban,HR Executive,86665,0 +109380,Male,59,Masters,12,23,93,29,29,2.0,6,32,Semi-Urban,Data Analyst,32083,0 +109381,Female,29,Bachelors,16,41,96,1,73,2.0,6,92,Urban,HR Executive,53242,0 +109382,Other,24,Bachelors,3,0,65,78,98,4.0,5,79,Semi-Urban,Data Analyst,51999,0 +109383,Male,58,High School,10,94,56,31,78,4.0,2,29,Urban,ML Engineer,107868,0 +109384,Male,43,Diploma,13,41,96,9,38,6.0,4,68,Urban,HR Executive,136028,0 +109385,Male,29,Bachelors,11,19,19,80,19,8.0,2,87,Urban,Software Engineer,104422,0 +109386,Female,53,PhD,11,82,53,59,74,7.0,0,41,Urban,HR Executive,107150,0 +109387,Male,50,Diploma,0,45,20,31,13,5.0,1,69,Urban,ML Engineer,42314,0 +109388,Male,34,Masters,9,89,90,53,27,1.0,0,42,Semi-Urban,Manager,75713,1 +109389,Male,24,High School,18,45,53,77,95,6.0,0,90,Urban,Manager,105898,1 +109390,Female,21,High School,13,66,61,58,7,5.0,7,50,Rural,Manager,132446,0 +109391,Male,27,Bachelors,7,57,88,3,60,0.0,5,99,Semi-Urban,ML Engineer,30353,1 +109392,Male,36,Diploma,2,54,15,37,32,2.0,7,78,Semi-Urban,Data Analyst,74964,0 +109393,Male,42,High School,4,31,12,72,16,4.0,2,64,Urban,Data Analyst,80334,0 +109394,Male,46,High School,9,83,86,56,17,7.0,1,78,Semi-Urban,Software Engineer,39947,1 +109395,Male,43,Diploma,8,39,72,17,45,7.0,5,31,Semi-Urban,Manager,58409,0 +109396,Female,56,Masters,13,18,50,58,76,7.0,3,85,Urban,Software Engineer,90547,0 +109397,Female,42,High School,7,6,45,67,99,5.0,7,6,Semi-Urban,ML Engineer,107946,0 +109398,Female,24,Bachelors,18,27,70,11,19,2.0,2,41,Rural,Software Engineer,40715,0 +109399,Male,42,Bachelors,0,69,48,76,2,1.0,1,37,Urban,ML Engineer,95456,0 +109400,Male,51,PhD,2,20,33,26,21,5.0,2,90,Urban,Data Analyst,43887,0 +109401,Other,33,Diploma,16,56,97,8,81,4.0,7,30,Urban,Data Analyst,57997,0 +109402,Female,28,Bachelors,13,88,76,13,82,0.0,1,9,Rural,Manager,56164,0 +109403,Male,56,Bachelors,7,22,44,31,59,7.0,1,81,Semi-Urban,ML Engineer,84574,0 +109404,Male,23,Bachelors,7,70,19,59,35,3.0,7,19,Urban,HR Executive,138488,0 +109405,Male,57,Bachelors,1,61,16,20,28,7.0,6,69,Rural,Data Analyst,44636,0 +109406,Male,50,Masters,11,50,41,98,87,9.0,5,17,Urban,HR Executive,111885,0 +109407,Female,34,High School,9,43,50,3,69,5.0,3,85,Urban,ML Engineer,146137,0 +109408,Other,41,Bachelors,8,77,25,43,45,1.0,2,11,Urban,ML Engineer,83271,0 +109409,Male,22,Bachelors,1,22,72,56,55,2.0,7,69,Urban,ML Engineer,117886,0 +109410,Female,21,Diploma,6,21,30,41,61,3.0,0,13,Urban,ML Engineer,45824,0 +109411,Male,23,Diploma,14,42,5,27,53,3.0,0,1,Rural,Software Engineer,102451,0 +109412,Female,45,Masters,0,82,98,1,90,8.0,0,40,Semi-Urban,Data Analyst,66438,0 +109413,Male,48,Bachelors,12,85,49,67,92,3.0,2,27,Rural,Software Engineer,98591,0 +109414,Male,48,Diploma,2,72,77,30,62,1.0,0,51,Urban,Manager,121053,0 +109415,Male,35,High School,13,95,37,49,59,8.0,0,25,Rural,ML Engineer,127674,0 +109416,Female,57,Bachelors,14,81,92,50,0,4.0,4,75,Urban,Manager,92045,1 +109417,Female,25,Bachelors,7,51,53,4,43,1.0,6,10,Urban,Data Analyst,61624,0 +109418,Female,49,High School,14,73,11,2,23,3.0,7,58,Urban,HR Executive,44990,0 +109419,Female,33,High School,18,44,65,14,70,7.0,3,22,Urban,ML Engineer,90473,0 +109420,Male,56,Masters,7,36,28,20,65,5.0,1,95,Urban,ML Engineer,105916,0 +109421,Female,53,PhD,4,45,63,33,0,9.0,4,33,Urban,Software Engineer,57657,0 +109422,Male,28,High School,7,53,39,48,58,1.0,5,23,Semi-Urban,Manager,90725,0 +109423,Female,38,Diploma,6,22,60,62,32,1.0,0,71,Urban,ML Engineer,129429,0 +109424,Female,21,Masters,12,86,31,75,13,8.0,3,99,Semi-Urban,Data Analyst,83427,1 +109425,Male,54,Masters,2,58,53,70,72,4.0,6,70,Rural,Software Engineer,122744,1 +109426,Male,35,PhD,19,76,80,83,65,3.0,0,18,Semi-Urban,Manager,59555,1 +109427,Male,58,Bachelors,11,95,39,44,43,4.0,5,23,Urban,Data Analyst,23573,0 +109428,Male,32,Bachelors,11,82,14,99,24,4.0,1,97,Semi-Urban,Software Engineer,27112,1 +109429,Male,52,Masters,16,93,55,10,54,5.0,3,34,Rural,Data Analyst,137400,0 +109430,Male,25,Masters,2,43,53,0,30,0.0,4,98,Semi-Urban,Data Analyst,108489,0 +109431,Male,45,High School,12,64,54,84,26,4.0,6,27,Urban,Manager,137865,0 +109432,Female,43,High School,9,72,7,45,56,3.0,4,52,Urban,Software Engineer,25076,0 +109433,Male,41,Masters,0,73,50,90,14,8.0,2,5,Urban,Data Analyst,46026,0 +109434,Male,21,Bachelors,18,44,85,12,28,9.0,0,84,Semi-Urban,Data Analyst,37619,0 +109435,Male,41,High School,18,54,76,89,23,7.0,4,68,Semi-Urban,Software Engineer,45150,1 +109436,Female,26,Bachelors,18,36,22,39,52,8.0,3,23,Urban,Data Analyst,48533,0 +109437,Female,47,Masters,7,83,33,30,18,6.0,1,60,Urban,Data Analyst,107599,0 +109438,Other,34,Masters,18,63,11,6,23,1.0,0,5,Urban,HR Executive,132408,0 +109439,Male,33,Masters,9,28,63,21,68,6.0,6,55,Urban,Data Analyst,87767,0 +109440,Male,50,High School,12,34,75,24,30,3.0,2,51,Semi-Urban,Manager,70892,0 +109441,Female,57,Masters,7,85,90,43,53,2.0,5,99,Semi-Urban,Manager,40468,1 +109442,Male,42,High School,11,12,85,33,60,2.0,3,74,Urban,ML Engineer,149249,0 +109443,Female,26,Bachelors,10,13,13,25,4,0.0,1,64,Urban,Manager,118511,0 +109444,Male,46,Bachelors,6,37,89,95,95,1.0,6,68,Rural,Manager,109158,1 +109445,Female,43,Bachelors,8,27,95,70,78,1.0,2,58,Rural,Manager,34939,1 +109446,Female,44,Diploma,14,93,41,39,7,5.0,4,93,Urban,Data Analyst,81400,1 +109447,Male,38,High School,0,38,26,77,50,2.0,4,58,Urban,Manager,73943,0 +109448,Male,42,Bachelors,12,90,83,79,62,8.0,4,77,Urban,Manager,99765,1 +109449,Male,27,Masters,13,5,29,13,80,2.0,0,97,Urban,Data Analyst,46211,0 +109450,Female,50,Masters,9,65,66,36,37,2.0,2,51,Urban,Software Engineer,92213,0 +109451,Male,57,Masters,17,27,61,93,16,0.0,6,23,Urban,Software Engineer,110220,0 +109452,Female,49,Diploma,7,95,99,19,91,9.0,5,77,Rural,Software Engineer,149320,1 +109453,Male,36,Bachelors,18,73,24,49,83,1.0,3,25,Urban,Software Engineer,82067,0 +109454,Female,49,Diploma,17,47,36,43,66,4.0,2,57,Urban,HR Executive,105772,0 +109455,Female,36,Diploma,9,92,13,7,44,4.0,3,54,Urban,Data Analyst,94092,0 +109456,Male,23,Diploma,1,70,62,42,3,7.0,1,84,Urban,Data Analyst,43420,1 +109457,Male,30,High School,13,94,95,56,74,8.0,7,70,Urban,ML Engineer,80397,1 +109458,Male,56,Masters,5,90,32,88,3,5.0,5,70,Urban,HR Executive,86985,1 +109459,Male,28,Bachelors,2,24,57,16,35,3.0,0,7,Urban,ML Engineer,145442,0 +109460,Male,58,Bachelors,17,32,51,43,44,1.0,2,49,Urban,Manager,52358,0 +109461,Male,49,Bachelors,5,96,92,9,67,0.0,2,18,Urban,Manager,80976,0 +109462,Female,27,Bachelors,11,27,51,16,1,4.0,7,80,Urban,HR Executive,27310,0 +109463,Male,27,Masters,19,25,46,80,39,8.0,1,66,Rural,Manager,101391,0 +109464,Male,57,High School,14,99,19,86,40,6.0,7,43,Rural,Software Engineer,110964,1 +109465,Male,45,Diploma,7,98,75,37,95,4.0,0,88,Semi-Urban,HR Executive,73012,1 +109466,Male,54,High School,14,93,84,15,31,2.0,2,10,Rural,HR Executive,131092,0 +109467,Male,57,Bachelors,1,13,37,72,98,9.0,2,59,Rural,ML Engineer,98372,0 +109468,Male,39,High School,11,63,6,70,58,4.0,3,48,Urban,Data Analyst,69808,0 +109469,Female,52,High School,17,27,64,76,26,5.0,7,51,Urban,Data Analyst,62261,0 +109470,Female,45,Bachelors,17,4,53,37,81,0.0,3,57,Rural,HR Executive,121202,0 +109471,Female,23,Bachelors,6,8,64,55,65,7.0,0,70,Urban,Manager,31994,0 +109472,Female,46,Bachelors,8,25,15,55,22,5.0,1,75,Semi-Urban,HR Executive,130370,0 +109473,Male,56,High School,4,30,47,67,87,2.0,3,74,Urban,Software Engineer,49837,0 +109474,Male,55,Masters,8,35,57,84,80,6.0,3,58,Urban,HR Executive,85622,0 +109475,Male,49,Bachelors,3,87,1,79,46,2.0,5,84,Urban,Data Analyst,144354,1 +109476,Male,50,Diploma,0,55,96,66,36,8.0,6,39,Semi-Urban,Manager,96039,1 +109477,Male,41,Bachelors,12,59,69,17,52,7.0,7,49,Urban,Data Analyst,124190,0 +109478,Male,43,Bachelors,19,9,56,43,99,1.0,1,29,Semi-Urban,HR Executive,30995,0 +109479,Male,31,Bachelors,9,55,72,75,76,0.0,7,65,Urban,ML Engineer,50313,1 +109480,Male,23,Masters,4,5,46,41,94,6.0,5,84,Semi-Urban,Manager,33137,0 +109481,Male,58,High School,11,73,26,8,6,1.0,6,27,Urban,Data Analyst,32793,0 +109482,Other,33,Masters,9,47,76,95,95,2.0,5,37,Semi-Urban,HR Executive,90242,1 +109483,Other,48,Bachelors,5,92,27,71,2,7.0,5,65,Semi-Urban,ML Engineer,25888,1 +109484,Male,55,Bachelors,14,12,55,56,63,3.0,5,77,Urban,ML Engineer,68112,0 +109485,Male,37,Masters,5,21,0,37,71,7.0,1,85,Rural,Software Engineer,62486,0 +109486,Male,35,Masters,14,98,88,51,0,9.0,0,67,Urban,HR Executive,145695,1 +109487,Male,29,Bachelors,4,42,34,52,15,4.0,2,40,Rural,Software Engineer,94575,0 +109488,Male,51,Diploma,11,34,92,51,12,4.0,0,9,Semi-Urban,Software Engineer,61572,0 +109489,Male,24,Masters,5,12,62,68,72,8.0,2,85,Urban,Manager,127953,0 +109490,Female,47,Masters,14,45,31,43,15,1.0,5,95,Rural,ML Engineer,106996,0 +109491,Male,57,Masters,16,51,35,45,52,5.0,5,72,Semi-Urban,Manager,94526,0 +109492,Male,35,High School,2,78,30,61,33,8.0,0,35,Urban,Software Engineer,77612,0 +109493,Male,39,High School,18,33,15,18,49,6.0,5,29,Rural,Data Analyst,140552,0 +109494,Male,49,Bachelors,0,86,46,45,1,0.0,2,9,Semi-Urban,ML Engineer,139806,0 +109495,Other,23,Bachelors,16,15,55,48,85,3.0,0,60,Semi-Urban,ML Engineer,36152,0 +109496,Female,27,Diploma,9,89,88,27,92,8.0,7,60,Rural,Software Engineer,142456,1 +109497,Male,51,High School,19,20,37,1,49,5.0,6,99,Rural,ML Engineer,51305,0 +109498,Other,44,High School,9,61,43,39,97,7.0,3,29,Urban,Manager,30144,0 +109499,Male,36,High School,15,62,96,48,33,9.0,3,12,Rural,Data Analyst,97185,0 +109500,Male,50,PhD,6,16,39,1,98,5.0,3,99,Semi-Urban,Manager,121516,0 +109501,Male,25,Diploma,0,13,9,63,37,9.0,5,5,Urban,Manager,132950,0 +109502,Male,42,Bachelors,12,77,53,75,68,5.0,0,18,Semi-Urban,Manager,63059,0 +109503,Female,36,Bachelors,5,39,92,0,29,6.0,2,64,Urban,Data Analyst,75177,0 +109504,Male,35,Masters,10,63,5,55,35,7.0,4,17,Urban,HR Executive,118841,0 +109505,Male,57,Diploma,12,34,28,89,51,4.0,0,65,Urban,Manager,125141,0 +109506,Female,43,Diploma,9,45,79,79,10,2.0,3,10,Rural,HR Executive,20600,0 +109507,Male,47,Masters,10,91,92,35,87,8.0,4,31,Urban,HR Executive,58740,1 +109508,Male,31,Bachelors,18,67,49,12,82,7.0,4,57,Rural,ML Engineer,105225,0 +109509,Male,31,Masters,5,48,54,12,13,0.0,5,83,Semi-Urban,Software Engineer,24368,0 +109510,Male,39,High School,4,0,21,2,59,5.0,5,10,Urban,Manager,107672,0 +109511,Male,31,PhD,1,90,37,85,40,5.0,4,22,Urban,HR Executive,62127,0 +109512,Female,56,Masters,8,89,62,42,40,2.0,2,35,Urban,Data Analyst,27106,0 +109513,Female,48,Diploma,15,7,8,75,12,2.0,7,43,Urban,Manager,82770,0 +109514,Male,44,Diploma,14,59,63,2,4,0.0,5,71,Urban,Software Engineer,42434,0 +109515,Female,56,High School,1,51,70,70,81,3.0,5,7,Urban,ML Engineer,113758,0 +109516,Female,31,Masters,7,33,90,86,93,7.0,3,23,Urban,Software Engineer,34839,0 +109517,Female,39,High School,10,80,75,47,1,8.0,2,33,Rural,Manager,146764,0 +109518,Male,44,Bachelors,17,72,94,72,20,7.0,6,4,Rural,Manager,87074,1 +109519,Female,47,High School,17,61,60,4,80,3.0,0,80,Urban,ML Engineer,84426,0 +109520,Female,34,Bachelors,18,74,82,75,48,2.0,0,3,Urban,ML Engineer,134318,0 +109521,Male,45,Masters,14,15,28,24,94,8.0,6,46,Semi-Urban,HR Executive,131934,0 +109522,Male,38,Bachelors,13,32,58,85,70,0.0,1,27,Semi-Urban,ML Engineer,133397,0 +109523,Female,39,Bachelors,16,39,44,3,73,1.0,5,36,Semi-Urban,Data Analyst,138015,0 +109524,Female,40,Bachelors,12,0,24,41,10,8.0,7,42,Urban,Manager,70236,0 +109525,Male,25,Bachelors,14,60,61,28,14,7.0,3,23,Rural,HR Executive,114688,0 +109526,Female,42,Diploma,6,87,75,14,56,7.0,5,36,Urban,Manager,148892,0 +109527,Male,46,Diploma,16,74,44,41,45,7.0,2,62,Urban,HR Executive,121418,0 +109528,Female,40,Diploma,18,9,50,87,88,0.0,2,92,Urban,Software Engineer,100981,0 +109529,Male,41,Bachelors,8,60,0,5,18,3.0,3,98,Urban,Software Engineer,88826,0 +109530,Male,50,Masters,11,26,56,22,72,5.0,3,2,Semi-Urban,HR Executive,66659,0 +109531,Female,39,Diploma,6,85,91,8,44,9.0,4,42,Urban,HR Executive,45767,0 +109532,Male,21,High School,7,1,82,40,38,5.0,1,99,Semi-Urban,ML Engineer,40250,0 +109533,Male,57,Bachelors,11,13,40,1,9,4.0,1,13,Urban,Software Engineer,133350,0 +109534,Male,22,Diploma,2,31,56,89,21,1.0,0,37,Urban,HR Executive,51682,0 +109535,Male,49,PhD,9,59,53,3,59,0.0,6,43,Semi-Urban,HR Executive,61977,0 +109536,Female,37,Diploma,17,67,72,74,13,1.0,4,13,Rural,HR Executive,144724,0 +109537,Male,22,Masters,7,74,60,87,72,6.0,7,18,Semi-Urban,HR Executive,53245,1 +109538,Female,24,High School,19,20,31,44,73,8.0,6,10,Urban,Data Analyst,110544,0 +109539,Male,57,High School,9,84,58,89,24,2.0,7,87,Urban,Software Engineer,90779,1 +109540,Female,25,Masters,14,48,40,15,72,0.0,7,79,Urban,ML Engineer,36628,0 +109541,Male,25,Bachelors,5,77,73,28,34,9.0,7,38,Rural,ML Engineer,135767,0 +109542,Male,53,Masters,16,98,36,42,17,5.0,3,30,Semi-Urban,Data Analyst,44200,0 +109543,Female,59,Diploma,6,74,54,79,59,5.0,5,13,Urban,Software Engineer,85175,0 +109544,Male,26,Bachelors,18,52,56,16,99,2.0,1,31,Semi-Urban,Software Engineer,117245,0 +109545,Male,34,Bachelors,0,78,39,0,23,0.0,7,91,Urban,Data Analyst,49426,0 +109546,Male,53,High School,7,15,44,3,74,1.0,5,48,Rural,Software Engineer,33919,0 +109547,Male,50,Bachelors,15,54,34,97,96,0.0,6,3,Urban,HR Executive,148802,0 +109548,Male,49,PhD,4,82,7,45,17,1.0,6,47,Urban,Software Engineer,134748,0 +109549,Female,27,High School,5,69,59,68,11,5.0,6,20,Semi-Urban,HR Executive,41662,0 +109550,Female,21,PhD,18,6,56,74,10,8.0,3,12,Rural,Manager,40811,0 +109551,Female,56,Bachelors,5,7,77,0,92,5.0,0,82,Urban,Software Engineer,84495,0 +109552,Male,37,High School,17,85,30,63,19,0.0,2,13,Rural,Manager,70202,0 +109553,Female,38,Diploma,14,82,12,67,11,1.0,5,57,Urban,Software Engineer,98616,0 +109554,Other,44,Diploma,9,47,68,14,22,2.0,0,37,Urban,HR Executive,65400,0 +109555,Female,49,Diploma,3,33,74,84,68,0.0,6,76,Urban,ML Engineer,82190,1 +109556,Male,38,Diploma,18,72,59,34,26,5.0,7,66,Urban,ML Engineer,29543,0 +109557,Female,21,Masters,6,4,50,8,11,7.0,2,10,Urban,Data Analyst,35136,0 +109558,Female,28,Bachelors,5,68,41,26,74,6.0,2,31,Urban,Software Engineer,142565,0 +109559,Female,31,Bachelors,12,55,73,76,79,6.0,1,47,Urban,Software Engineer,120227,1 +109560,Male,48,Diploma,1,72,95,51,7,7.0,0,78,Urban,ML Engineer,105818,1 +109561,Female,56,Diploma,17,36,17,13,87,8.0,2,64,Semi-Urban,Data Analyst,104760,0 +109562,Male,29,Bachelors,0,99,3,65,33,7.0,5,17,Semi-Urban,Software Engineer,85916,0 +109563,Male,53,Bachelors,3,38,30,64,81,3.0,4,52,Rural,ML Engineer,84459,0 +109564,Male,52,Diploma,17,59,15,45,78,5.0,0,45,Urban,ML Engineer,37923,0 +109565,Female,40,Bachelors,17,1,82,22,35,9.0,4,45,Semi-Urban,Data Analyst,65493,0 +109566,Male,31,Diploma,14,62,85,78,8,4.0,5,31,Rural,Data Analyst,113182,1 +109567,Male,29,Bachelors,15,89,73,33,39,5.0,7,82,Urban,HR Executive,45343,1 +109568,Other,59,Diploma,11,64,47,11,57,7.0,2,67,Semi-Urban,ML Engineer,43015,0 +109569,Male,47,Bachelors,8,19,46,20,62,9.0,3,64,Urban,Data Analyst,21507,0 +109570,Female,29,Diploma,16,8,50,0,31,0.0,7,42,Urban,Manager,90316,0 +109571,Male,47,Masters,4,15,34,71,67,8.0,5,65,Rural,Manager,105338,0 +109572,Female,29,High School,4,79,74,37,67,7.0,4,27,Urban,HR Executive,125214,0 +109573,Female,52,Bachelors,12,3,38,93,69,5.0,5,28,Urban,Manager,124991,0 +109574,Male,21,Diploma,4,33,48,79,20,7.0,3,70,Rural,HR Executive,74133,0 +109575,Male,57,Masters,6,99,70,92,86,6.0,1,3,Rural,Software Engineer,46902,1 +109576,Male,37,Bachelors,2,13,28,69,6,9.0,1,44,Semi-Urban,ML Engineer,23169,0 +109577,Female,35,Diploma,5,27,98,37,69,4.0,1,17,Semi-Urban,Manager,141899,0 +109578,Female,49,Bachelors,0,67,13,47,41,2.0,6,54,Urban,ML Engineer,57476,0 +109579,Male,39,PhD,13,8,65,72,5,3.0,7,54,Rural,Software Engineer,88187,0 +109580,Male,50,Bachelors,12,2,34,81,34,8.0,5,58,Urban,HR Executive,51280,0 +109581,Male,47,Masters,7,53,25,28,39,5.0,6,90,Urban,ML Engineer,85578,0 +109582,Male,31,Bachelors,2,69,64,7,98,3.0,4,90,Urban,HR Executive,34687,0 +109583,Male,49,Diploma,15,64,58,80,61,6.0,3,97,Urban,Data Analyst,149522,1 +109584,Female,57,Diploma,17,3,95,1,0,9.0,6,36,Semi-Urban,Software Engineer,66333,0 +109585,Female,31,Bachelors,18,15,16,40,38,0.0,4,48,Semi-Urban,Manager,50840,0 +109586,Female,35,Diploma,3,90,44,92,95,7.0,3,13,Urban,Data Analyst,127408,0 +109587,Female,41,Bachelors,5,95,78,99,58,6.0,3,7,Rural,ML Engineer,127358,1 +109588,Male,27,Masters,9,74,35,86,72,6.0,7,89,Urban,HR Executive,46470,1 +109589,Male,36,PhD,18,5,99,89,52,2.0,7,80,Semi-Urban,Manager,102675,1 +109590,Male,22,Diploma,13,82,70,30,15,6.0,6,33,Semi-Urban,Manager,96125,0 +109591,Female,38,PhD,19,45,13,57,17,0.0,0,5,Semi-Urban,Manager,100704,0 +109592,Male,21,Diploma,9,62,29,93,28,5.0,7,65,Rural,Software Engineer,127925,1 +109593,Male,58,Masters,10,87,59,72,48,6.0,2,48,Urban,ML Engineer,50952,1 +109594,Other,39,High School,4,28,19,38,53,6.0,6,77,Semi-Urban,HR Executive,141697,0 +109595,Male,52,Bachelors,19,30,74,34,53,3.0,5,25,Semi-Urban,Manager,46035,0 +109596,Male,34,Diploma,0,8,47,57,95,3.0,1,84,Urban,Software Engineer,97842,0 +109597,Male,48,High School,19,65,54,26,30,3.0,1,52,Urban,HR Executive,92867,0 +109598,Male,48,Bachelors,1,50,97,5,89,6.0,7,17,Urban,Data Analyst,127119,0 +109599,Male,26,High School,2,97,91,12,47,0.0,4,50,Urban,Manager,113258,1 +109600,Female,26,Bachelors,8,47,0,65,55,5.0,2,45,Urban,HR Executive,110116,0 +109601,Female,38,Bachelors,2,82,31,5,84,5.0,4,69,Urban,HR Executive,47189,0 +109602,Female,46,Diploma,5,65,96,90,32,1.0,1,97,Semi-Urban,ML Engineer,48572,1 +109603,Female,50,Bachelors,8,32,59,56,76,9.0,6,8,Urban,ML Engineer,146040,0 +109604,Male,22,Bachelors,10,57,71,57,60,9.0,0,34,Urban,ML Engineer,123497,0 +109605,Male,43,Bachelors,4,58,53,11,16,9.0,7,11,Semi-Urban,Data Analyst,68128,0 +109606,Female,35,Bachelors,1,87,49,43,93,6.0,7,42,Rural,Manager,74119,0 +109607,Male,50,PhD,19,50,90,65,59,8.0,2,70,Urban,Manager,73148,1 +109608,Female,35,Diploma,11,77,91,14,40,5.0,2,45,Urban,Manager,106083,0 +109609,Male,54,High School,8,1,73,89,63,9.0,7,17,Urban,HR Executive,103690,0 +109610,Male,44,Diploma,14,34,9,53,74,3.0,0,95,Urban,Software Engineer,124832,0 +109611,Male,47,Diploma,15,3,94,49,42,6.0,3,57,Urban,HR Executive,139541,0 +109612,Male,51,Masters,3,15,65,1,43,8.0,1,18,Urban,Data Analyst,82130,0 +109613,Female,30,Masters,10,33,26,31,82,1.0,5,93,Urban,Data Analyst,143775,0 +109614,Female,22,Bachelors,15,42,25,94,86,2.0,1,44,Urban,Software Engineer,83646,0 +109615,Male,50,Diploma,17,87,39,52,31,0.0,6,70,Semi-Urban,Software Engineer,67962,1 +109616,Male,58,Bachelors,12,54,0,72,53,7.0,1,17,Urban,Manager,104972,0 +109617,Male,49,High School,19,9,29,75,67,1.0,5,69,Rural,HR Executive,80598,0 +109618,Male,38,Diploma,10,20,5,92,65,4.0,3,64,Semi-Urban,Data Analyst,141435,0 +109619,Male,37,Bachelors,0,12,23,29,84,8.0,5,31,Rural,Manager,118638,0 +109620,Female,46,Masters,16,96,81,33,0,8.0,7,89,Rural,Data Analyst,65998,1 +109621,Female,39,High School,9,59,98,82,32,6.0,1,27,Urban,HR Executive,148384,1 +109622,Female,44,Masters,13,78,44,41,5,7.0,5,35,Urban,ML Engineer,83661,0 +109623,Male,43,Bachelors,19,8,96,58,2,1.0,5,88,Urban,ML Engineer,141818,1 +109624,Male,29,Bachelors,1,50,85,85,28,8.0,5,18,Rural,Software Engineer,46521,1 +109625,Male,34,Bachelors,18,93,68,53,9,5.0,1,11,Urban,Data Analyst,71927,0 +109626,Female,39,Bachelors,3,19,79,47,26,2.0,2,99,Urban,ML Engineer,139864,1 +109627,Male,23,Bachelors,14,43,64,41,50,4.0,3,9,Semi-Urban,Data Analyst,49549,0 +109628,Male,33,Diploma,11,94,43,1,81,4.0,6,71,Rural,Data Analyst,123979,0 +109629,Male,35,Masters,12,90,84,10,96,5.0,4,65,Rural,Manager,91708,1 +109630,Male,25,Diploma,12,13,46,58,55,4.0,3,89,Urban,HR Executive,20357,0 +109631,Male,28,Bachelors,15,64,70,92,97,9.0,4,32,Rural,ML Engineer,31138,1 +109632,Male,38,PhD,10,35,3,36,20,4.0,0,60,Semi-Urban,Software Engineer,112252,0 +109633,Male,59,Bachelors,19,73,26,62,24,2.0,5,20,Rural,Manager,57019,0 +109634,Male,47,PhD,1,65,52,53,72,3.0,7,4,Semi-Urban,ML Engineer,132852,0 +109635,Female,45,High School,14,51,8,17,61,0.0,2,82,Urban,Manager,134581,0 +109636,Male,52,Diploma,19,48,15,72,74,1.0,5,99,Urban,Data Analyst,108716,0 +109637,Female,32,Masters,3,5,2,1,53,5.0,2,49,Rural,HR Executive,100082,0 +109638,Female,26,High School,10,45,77,24,1,8.0,3,10,Urban,Data Analyst,37939,0 +109639,Male,21,PhD,7,47,60,84,57,0.0,5,98,Urban,ML Engineer,122510,1 +109640,Male,33,High School,7,27,53,28,22,4.0,5,19,Semi-Urban,Software Engineer,135384,0 +109641,Female,24,Bachelors,17,18,71,87,36,5.0,4,42,Urban,Manager,41694,0 +109642,Female,31,Bachelors,15,49,68,65,38,1.0,1,2,Semi-Urban,HR Executive,134943,0 +109643,Male,56,PhD,0,70,69,52,46,5.0,5,41,Semi-Urban,HR Executive,115704,0 +109644,Male,33,High School,1,88,27,52,58,0.0,3,44,Urban,Data Analyst,110970,0 +109645,Female,45,Diploma,4,50,49,87,19,4.0,7,58,Urban,Software Engineer,74081,1 +109646,Male,54,High School,16,93,0,82,63,7.0,2,73,Semi-Urban,Software Engineer,103546,1 +109647,Male,24,Bachelors,2,91,87,21,11,3.0,7,71,Urban,ML Engineer,110724,1 +109648,Female,58,Masters,1,73,91,46,64,0.0,3,5,Urban,Manager,73777,0 +109649,Male,53,Masters,9,13,17,37,55,3.0,3,39,Urban,Data Analyst,28514,0 +109650,Female,36,Bachelors,13,87,25,63,12,2.0,2,6,Urban,Data Analyst,30022,0 +109651,Male,29,PhD,4,11,60,66,99,8.0,6,8,Semi-Urban,HR Executive,37833,0 +109652,Male,58,Bachelors,12,28,78,82,53,1.0,4,24,Rural,HR Executive,28684,0 +109653,Male,48,Diploma,13,51,97,89,39,0.0,4,49,Urban,HR Executive,38265,1 +109654,Female,26,Bachelors,9,21,14,11,63,5.0,6,24,Semi-Urban,Manager,149550,0 +109655,Male,42,Diploma,9,23,83,52,98,9.0,5,71,Urban,ML Engineer,118121,0 +109656,Female,53,Bachelors,6,72,33,20,91,5.0,2,10,Rural,Software Engineer,60026,0 +109657,Male,45,Masters,8,12,42,83,23,8.0,5,13,Urban,Data Analyst,112359,0 +109658,Female,39,Bachelors,10,82,92,86,29,9.0,2,56,Urban,HR Executive,101218,1 +109659,Female,48,Bachelors,1,96,95,86,36,4.0,1,38,Semi-Urban,Data Analyst,28155,1 +109660,Other,24,Diploma,1,65,13,2,25,5.0,5,58,Urban,Data Analyst,101798,0 +109661,Male,53,Masters,9,30,37,23,49,9.0,0,87,Urban,Manager,124087,0 +109662,Male,57,Diploma,4,31,65,88,43,2.0,0,50,Rural,HR Executive,40861,0 +109663,Male,21,Bachelors,3,83,33,87,77,9.0,5,1,Urban,HR Executive,26402,0 +109664,Male,47,Masters,5,14,15,89,43,9.0,5,10,Urban,HR Executive,84595,0 +109665,Male,28,High School,9,87,84,89,89,3.0,1,89,Urban,HR Executive,140451,1 +109666,Male,48,Bachelors,6,65,40,81,43,6.0,2,67,Semi-Urban,ML Engineer,111074,1 +109667,Female,44,Bachelors,2,47,88,28,51,2.0,6,85,Rural,Manager,61745,1 +109668,Male,27,Masters,5,25,45,46,97,3.0,2,99,Urban,Manager,84323,0 +109669,Female,45,Bachelors,13,15,83,34,56,4.0,2,59,Urban,Data Analyst,73086,0 +109670,Male,53,Bachelors,4,97,26,41,83,3.0,4,38,Urban,Manager,43998,0 +109671,Male,50,Bachelors,16,91,58,94,36,5.0,1,94,Semi-Urban,HR Executive,50779,1 +109672,Male,42,Masters,19,59,62,48,23,7.0,5,85,Semi-Urban,ML Engineer,28517,1 +109673,Male,41,High School,18,82,2,43,79,3.0,1,71,Semi-Urban,HR Executive,144619,0 +109674,Female,27,Diploma,15,92,93,99,2,7.0,5,37,Rural,Software Engineer,25728,1 +109675,Male,37,Bachelors,16,66,78,68,77,9.0,6,58,Urban,Software Engineer,98607,1 +109676,Male,33,Masters,11,45,81,95,64,0.0,3,66,Rural,Software Engineer,67886,1 +109677,Other,35,Bachelors,1,46,94,10,90,0.0,1,69,Rural,ML Engineer,80944,0 +109678,Female,25,Bachelors,6,7,6,41,34,5.0,1,69,Urban,Software Engineer,37070,0 +109679,Male,39,Diploma,5,77,49,61,2,2.0,3,26,Semi-Urban,HR Executive,108365,0 +109680,Male,57,Bachelors,2,74,48,7,56,0.0,7,9,Rural,Manager,82392,0 +109681,Male,32,Bachelors,11,69,72,48,17,3.0,2,8,Urban,Data Analyst,90318,0 +109682,Male,38,Bachelors,18,84,59,86,74,1.0,4,2,Urban,HR Executive,79772,0 +109683,Female,40,Diploma,11,54,69,8,95,6.0,4,34,Urban,Manager,90623,0 +109684,Male,51,Diploma,18,48,44,31,81,6.0,5,28,Rural,Manager,61256,0 +109685,Male,52,Bachelors,13,72,56,48,36,8.0,1,4,Rural,Software Engineer,130267,0 +109686,Other,24,Diploma,18,44,42,20,52,0.0,7,59,Rural,Data Analyst,83143,0 +109687,Male,54,Diploma,1,22,53,3,28,3.0,2,69,Urban,Software Engineer,93951,0 +109688,Female,50,Masters,11,40,62,86,83,6.0,4,20,Urban,Manager,118019,0 +109689,Female,27,High School,8,68,6,31,3,8.0,4,19,Rural,Software Engineer,57100,0 +109690,Male,37,Bachelors,15,8,89,58,68,0.0,3,42,Urban,ML Engineer,21138,0 +109691,Male,26,High School,11,22,76,68,16,2.0,7,4,Semi-Urban,Software Engineer,30101,0 +109692,Male,37,PhD,7,33,0,66,49,3.0,1,87,Urban,ML Engineer,28131,0 +109693,Male,22,Diploma,4,65,1,98,0,4.0,5,98,Urban,HR Executive,47601,1 +109694,Male,56,Bachelors,17,87,80,64,43,7.0,3,15,Semi-Urban,HR Executive,75700,1 +109695,Male,34,Bachelors,3,76,40,63,86,2.0,0,87,Semi-Urban,ML Engineer,94911,1 +109696,Female,31,Masters,5,93,98,14,16,5.0,4,81,Semi-Urban,ML Engineer,25448,1 +109697,Male,40,Bachelors,0,24,63,50,92,6.0,2,91,Urban,HR Executive,39146,0 +109698,Female,43,Bachelors,9,44,22,16,3,6.0,3,4,Semi-Urban,Data Analyst,126112,0 +109699,Male,28,Diploma,13,16,51,14,24,4.0,6,97,Semi-Urban,Manager,146621,0 +109700,Male,32,Diploma,4,70,36,71,30,4.0,7,40,Urban,Manager,100355,0 +109701,Male,50,High School,9,66,19,62,80,9.0,7,90,Urban,HR Executive,125987,1 +109702,Female,54,PhD,16,21,82,50,93,8.0,6,61,Urban,HR Executive,76835,0 +109703,Male,36,Diploma,11,30,96,58,32,2.0,0,98,Semi-Urban,ML Engineer,129886,1 +109704,Male,24,Bachelors,18,8,79,94,29,9.0,7,12,Urban,ML Engineer,29338,0 +109705,Other,30,High School,5,47,33,65,21,0.0,7,33,Urban,Manager,90351,0 +109706,Female,46,Bachelors,14,75,10,5,45,3.0,7,53,Urban,Manager,112920,0 +109707,Female,41,Bachelors,0,10,85,23,67,7.0,1,47,Semi-Urban,Manager,101616,0 +109708,Male,47,PhD,6,90,68,34,41,0.0,5,41,Urban,Software Engineer,63257,0 +109709,Female,48,Masters,11,33,57,92,4,4.0,3,1,Semi-Urban,ML Engineer,67034,0 +109710,Male,54,Bachelors,16,85,14,80,85,7.0,4,19,Urban,Data Analyst,95966,0 +109711,Female,54,Bachelors,15,91,16,29,63,6.0,6,37,Urban,Software Engineer,39795,0 +109712,Female,51,Bachelors,0,98,88,0,24,1.0,7,43,Urban,Data Analyst,32127,0 +109713,Other,50,Diploma,4,93,92,48,77,2.0,7,97,Rural,ML Engineer,107580,1 +109714,Male,56,Bachelors,8,48,39,86,57,0.0,4,85,Rural,Software Engineer,134174,1 +109715,Male,44,PhD,6,79,4,41,35,4.0,2,90,Urban,Manager,132553,0 +109716,Female,55,Bachelors,12,88,77,93,94,1.0,3,68,Semi-Urban,ML Engineer,64202,1 +109717,Other,51,Bachelors,0,83,94,5,24,3.0,5,25,Urban,Data Analyst,55603,0 +109718,Male,53,Masters,14,7,88,95,88,3.0,7,49,Rural,Software Engineer,117285,1 +109719,Male,41,PhD,2,20,78,18,27,7.0,7,30,Urban,Data Analyst,72617,0 +109720,Male,21,Bachelors,8,88,93,24,13,6.0,1,60,Rural,Data Analyst,51118,1 +109721,Female,42,Masters,1,0,92,89,21,1.0,2,20,Urban,HR Executive,78831,0 +109722,Male,33,Bachelors,3,42,96,64,95,9.0,6,14,Urban,Software Engineer,23536,0 +109723,Female,46,PhD,0,39,70,58,12,1.0,7,81,Semi-Urban,Software Engineer,98376,1 +109724,Female,43,PhD,9,19,16,95,31,1.0,5,75,Urban,ML Engineer,121803,0 +109725,Male,37,Bachelors,9,2,96,29,58,5.0,5,32,Urban,Software Engineer,60035,0 +109726,Male,32,Bachelors,16,59,94,22,92,9.0,1,15,Rural,HR Executive,88019,0 +109727,Female,51,High School,9,25,38,50,64,8.0,6,9,Urban,Software Engineer,108058,0 +109728,Male,47,Diploma,1,62,71,84,71,6.0,7,58,Semi-Urban,HR Executive,31383,1 +109729,Female,41,High School,18,50,6,24,29,5.0,7,39,Urban,Data Analyst,45301,0 +109730,Female,50,Masters,19,29,15,75,77,3.0,3,14,Urban,Data Analyst,99787,0 +109731,Female,49,High School,4,87,86,32,74,9.0,0,35,Urban,Manager,111205,0 +109732,Male,21,Bachelors,9,30,26,15,79,2.0,0,41,Urban,Software Engineer,114750,0 +109733,Other,45,Diploma,12,68,46,97,11,1.0,6,66,Urban,Software Engineer,129147,1 +109734,Female,33,Bachelors,18,44,16,74,76,8.0,4,12,Semi-Urban,ML Engineer,76573,0 +109735,Male,45,Bachelors,12,23,39,15,80,5.0,6,31,Urban,Software Engineer,24640,0 +109736,Male,41,High School,5,1,32,41,18,5.0,7,70,Urban,Software Engineer,65745,0 +109737,Male,22,Masters,13,21,11,9,93,4.0,4,9,Semi-Urban,Software Engineer,126464,0 +109738,Male,43,Masters,11,68,99,29,75,4.0,5,57,Urban,Data Analyst,89041,1 +109739,Male,52,Diploma,4,73,50,76,2,2.0,5,96,Urban,Data Analyst,142897,1 +109740,Male,45,Bachelors,19,7,82,2,2,3.0,5,89,Urban,ML Engineer,140339,0 +109741,Male,35,High School,9,94,15,79,58,0.0,3,65,Rural,Software Engineer,55572,1 +109742,Male,55,Bachelors,12,35,75,19,28,6.0,6,3,Semi-Urban,HR Executive,61595,0 +109743,Female,58,Bachelors,2,24,94,38,88,0.0,0,81,Semi-Urban,ML Engineer,51868,0 +109744,Female,48,Diploma,6,75,27,93,71,2.0,3,83,Rural,ML Engineer,66872,1 +109745,Other,41,Diploma,5,24,80,73,77,8.0,3,95,Rural,Manager,134593,1 +109746,Female,43,Bachelors,1,38,49,72,28,1.0,0,79,Urban,Data Analyst,71386,0 +109747,Male,27,Diploma,5,98,81,25,27,1.0,3,57,Urban,Data Analyst,78240,1 +109748,Male,24,Bachelors,0,79,88,75,39,9.0,6,63,Urban,HR Executive,137518,1 +109749,Male,52,Bachelors,14,98,93,89,17,3.0,6,36,Rural,Manager,122208,1 +109750,Female,33,Diploma,17,36,81,8,28,1.0,2,54,Semi-Urban,ML Engineer,31261,0 +109751,Female,56,Diploma,19,52,82,74,93,0.0,7,54,Urban,Software Engineer,66888,1 +109752,Male,37,Masters,19,68,54,24,72,9.0,2,12,Urban,Software Engineer,133936,0 +109753,Male,59,Bachelors,15,6,0,12,32,2.0,7,15,Urban,HR Executive,116481,0 +109754,Female,21,Masters,9,90,42,67,82,5.0,7,89,Urban,ML Engineer,41281,1 +109755,Male,33,Masters,4,19,64,85,93,3.0,5,2,Urban,Data Analyst,82628,0 +109756,Male,37,Bachelors,19,91,46,33,27,5.0,4,97,Urban,Data Analyst,87036,1 +109757,Female,27,Bachelors,10,51,81,24,79,1.0,5,71,Semi-Urban,Software Engineer,149481,0 +109758,Male,37,Bachelors,11,33,58,72,3,8.0,7,78,Urban,Data Analyst,147829,1 +109759,Male,22,High School,18,1,59,10,33,5.0,5,31,Semi-Urban,HR Executive,50787,0 +109760,Male,59,Bachelors,16,9,25,1,81,6.0,5,88,Urban,Data Analyst,67504,0 +109761,Male,47,High School,3,3,29,69,0,1.0,4,5,Urban,Software Engineer,149494,0 +109762,Male,22,Masters,19,3,11,54,2,0.0,0,81,Urban,Data Analyst,58163,0 +109763,Other,38,Diploma,12,96,59,41,16,5.0,1,92,Urban,Software Engineer,28261,1 +109764,Female,27,Masters,8,99,43,14,79,4.0,1,23,Urban,ML Engineer,87708,0 +109765,Female,49,High School,2,27,88,86,93,9.0,1,92,Rural,ML Engineer,32182,1 +109766,Female,54,High School,0,91,39,84,6,7.0,1,16,Rural,Manager,94757,0 +109767,Female,28,High School,6,88,26,78,8,5.0,1,98,Urban,Software Engineer,84513,1 +109768,Male,54,Bachelors,5,29,19,58,24,1.0,5,94,Rural,Software Engineer,65895,0 +109769,Male,37,Bachelors,5,51,24,45,73,1.0,6,49,Urban,ML Engineer,111138,0 +109770,Female,39,Diploma,18,83,72,81,36,3.0,5,0,Semi-Urban,Software Engineer,81910,0 +109771,Male,50,Diploma,7,4,80,95,57,4.0,0,30,Semi-Urban,ML Engineer,94447,0 +109772,Male,33,Masters,13,74,13,10,73,9.0,1,14,Urban,Manager,79691,0 +109773,Female,39,Bachelors,18,36,30,4,17,7.0,1,69,Urban,Software Engineer,87842,0 +109774,Male,47,Diploma,9,35,56,6,5,3.0,5,23,Semi-Urban,Manager,25296,0 +109775,Female,23,Bachelors,7,9,95,18,85,2.0,0,66,Rural,Data Analyst,75619,0 +109776,Female,52,Bachelors,10,93,11,59,85,2.0,6,1,Urban,Manager,79121,0 +109777,Male,21,Bachelors,12,99,88,87,55,4.0,0,65,Urban,Software Engineer,113147,1 +109778,Male,55,PhD,14,69,17,38,45,4.0,2,63,Rural,Data Analyst,43749,0 +109779,Female,48,High School,16,68,98,33,22,3.0,5,41,Urban,Manager,111578,0 +109780,Male,33,Diploma,5,23,78,70,34,8.0,3,90,Urban,Software Engineer,76855,1 +109781,Other,25,Bachelors,18,57,77,41,51,2.0,4,10,Rural,Data Analyst,28869,0 +109782,Female,55,Diploma,15,86,83,54,95,3.0,2,51,Urban,Data Analyst,106051,1 +109783,Male,23,Diploma,7,75,56,92,37,1.0,1,13,Rural,Data Analyst,40161,1 +109784,Other,31,Bachelors,11,19,60,43,91,6.0,1,38,Urban,Manager,109806,0 +109785,Male,36,Bachelors,18,49,47,31,89,9.0,7,10,Rural,Manager,24454,0 +109786,Female,23,Bachelors,18,87,85,91,91,1.0,6,77,Urban,Manager,149769,1 +109787,Male,31,High School,3,39,80,63,43,2.0,7,88,Urban,ML Engineer,120759,1 +109788,Female,46,Masters,8,86,93,43,64,7.0,6,73,Semi-Urban,Manager,147529,1 +109789,Male,41,PhD,13,41,73,35,64,8.0,3,58,Semi-Urban,Manager,111135,0 +109790,Male,32,Diploma,14,29,14,65,30,6.0,3,62,Urban,ML Engineer,121079,0 +109791,Male,36,Masters,1,56,79,19,14,9.0,4,2,Urban,Manager,149968,0 +109792,Male,56,Bachelors,13,73,20,98,51,0.0,1,65,Rural,Data Analyst,49843,1 +109793,Male,35,Masters,9,48,23,62,91,1.0,0,81,Urban,Data Analyst,88334,0 +109794,Male,37,High School,0,17,51,53,39,6.0,6,56,Rural,HR Executive,104140,0 +109795,Male,41,Masters,9,74,55,66,66,9.0,6,78,Semi-Urban,HR Executive,102732,1 +109796,Male,48,Diploma,18,32,28,81,23,1.0,2,36,Urban,Software Engineer,123060,0 +109797,Female,29,Bachelors,19,12,57,94,15,0.0,0,70,Semi-Urban,ML Engineer,52459,0 +109798,Male,42,Masters,18,68,5,19,39,2.0,6,32,Urban,HR Executive,28395,0 +109799,Male,36,High School,3,88,62,79,12,5.0,0,9,Urban,Manager,88277,1 +109800,Female,32,Bachelors,12,82,62,48,76,9.0,0,94,Rural,HR Executive,57455,1 +109801,Male,30,Bachelors,16,42,24,89,41,9.0,3,17,Urban,Software Engineer,26211,0 +109802,Female,35,PhD,13,17,34,73,84,7.0,5,52,Semi-Urban,Data Analyst,21348,0 +109803,Male,26,Bachelors,16,72,35,36,42,0.0,1,28,Semi-Urban,Software Engineer,74398,0 +109804,Male,56,High School,18,82,57,31,62,5.0,0,92,Urban,Manager,44114,1 +109805,Male,25,High School,5,38,76,91,69,8.0,6,96,Urban,Software Engineer,100350,1 +109806,Female,56,Masters,8,75,58,17,40,8.0,0,49,Rural,Software Engineer,142160,0 +109807,Male,59,Bachelors,12,70,44,7,14,8.0,1,53,Urban,ML Engineer,65333,0 +109808,Female,26,Bachelors,3,49,32,43,37,7.0,2,93,Urban,Data Analyst,112049,0 +109809,Female,43,Bachelors,17,56,31,21,17,9.0,6,93,Urban,Data Analyst,136544,0 +109810,Male,29,Diploma,10,41,15,21,37,4.0,2,74,Urban,ML Engineer,97259,0 +109811,Male,37,High School,3,87,60,62,94,0.0,1,60,Rural,Manager,144803,1 +109812,Male,40,High School,18,12,93,13,33,0.0,4,78,Urban,Data Analyst,21087,0 +109813,Female,56,Bachelors,15,70,97,3,96,4.0,4,58,Semi-Urban,ML Engineer,94676,0 +109814,Female,46,Masters,14,48,1,52,65,2.0,4,86,Rural,ML Engineer,98892,0 +109815,Male,57,High School,2,28,37,99,92,3.0,4,52,Semi-Urban,HR Executive,47417,0 +109816,Female,25,Bachelors,19,53,33,32,4,7.0,3,39,Urban,Manager,49158,0 +109817,Male,33,Bachelors,14,55,92,9,24,8.0,7,18,Urban,Manager,123392,0 +109818,Male,29,PhD,5,22,36,99,20,3.0,0,59,Urban,Manager,124351,0 +109819,Male,23,Diploma,10,70,44,76,41,0.0,6,58,Urban,Manager,58008,1 +109820,Male,43,Diploma,5,72,58,21,46,9.0,4,50,Rural,ML Engineer,50135,0 +109821,Female,52,Bachelors,2,57,94,69,26,6.0,2,11,Urban,Manager,127039,0 +109822,Female,31,Bachelors,9,88,88,86,82,1.0,7,33,Urban,Data Analyst,29691,1 +109823,Female,59,Bachelors,14,30,20,96,24,0.0,3,44,Semi-Urban,ML Engineer,135810,0 +109824,Male,54,Bachelors,19,7,34,25,92,3.0,0,79,Semi-Urban,HR Executive,117249,0 +109825,Female,23,Bachelors,5,41,39,23,33,3.0,3,15,Semi-Urban,Data Analyst,115807,0 +109826,Female,38,Masters,9,59,39,36,9,6.0,2,81,Urban,Manager,67432,0 +109827,Male,33,Masters,2,68,64,84,13,8.0,2,85,Semi-Urban,ML Engineer,39710,1 +109828,Male,26,Bachelors,14,27,65,27,36,6.0,0,3,Rural,Software Engineer,147366,0 +109829,Female,49,Bachelors,12,76,35,17,91,0.0,6,31,Semi-Urban,HR Executive,137642,0 +109830,Male,29,Bachelors,17,44,99,96,76,4.0,0,77,Urban,Manager,99739,1 +109831,Female,27,Bachelors,14,53,14,41,9,3.0,1,62,Urban,HR Executive,92498,0 +109832,Female,50,Bachelors,6,11,24,33,21,2.0,5,58,Semi-Urban,HR Executive,86632,0 +109833,Other,23,Bachelors,5,81,30,87,31,2.0,4,88,Urban,Manager,22874,1 +109834,Male,46,Bachelors,7,8,38,34,55,2.0,4,43,Semi-Urban,HR Executive,109230,0 +109835,Other,41,Bachelors,0,56,54,32,90,4.0,3,23,Urban,ML Engineer,129634,0 +109836,Male,55,Bachelors,17,81,35,19,46,3.0,5,18,Urban,Data Analyst,84532,0 +109837,Male,33,High School,6,50,64,98,47,7.0,7,81,Urban,Data Analyst,120124,1 +109838,Male,45,Bachelors,7,3,97,34,18,9.0,4,97,Urban,ML Engineer,123384,0 +109839,Female,44,Masters,14,91,12,50,60,4.0,2,88,Rural,ML Engineer,27009,1 +109840,Male,25,Diploma,0,76,76,32,78,2.0,4,79,Semi-Urban,Manager,26035,1 +109841,Male,59,PhD,3,37,47,83,4,5.0,5,30,Urban,HR Executive,119656,0 +109842,Male,44,High School,7,93,29,0,17,4.0,5,7,Urban,Data Analyst,121260,0 +109843,Male,48,High School,10,44,55,72,56,7.0,5,2,Urban,HR Executive,139563,0 +109844,Male,24,Bachelors,5,1,73,20,35,6.0,4,82,Rural,HR Executive,106668,0 +109845,Female,29,Diploma,9,13,45,9,86,2.0,6,28,Rural,Software Engineer,106223,0 +109846,Female,29,Bachelors,6,80,9,24,12,2.0,2,16,Urban,Software Engineer,60296,0 +109847,Male,44,Bachelors,4,62,51,3,65,2.0,3,11,Semi-Urban,Manager,111728,0 +109848,Male,44,Diploma,7,70,43,14,37,6.0,7,92,Urban,ML Engineer,105456,0 +109849,Male,49,Bachelors,2,98,88,9,98,7.0,1,54,Urban,Software Engineer,85150,1 +109850,Male,39,Masters,11,92,22,83,15,5.0,4,96,Urban,Data Analyst,115836,1 +109851,Male,57,Bachelors,12,81,83,55,71,2.0,6,74,Semi-Urban,HR Executive,130598,1 +109852,Male,35,Diploma,4,32,40,28,40,2.0,7,21,Urban,Software Engineer,93790,0 +109853,Male,25,Diploma,18,96,58,67,13,1.0,3,51,Semi-Urban,Data Analyst,121595,1 +109854,Female,25,Bachelors,16,9,87,68,0,6.0,5,40,Semi-Urban,Software Engineer,128553,0 +109855,Other,25,Bachelors,16,85,57,58,93,7.0,4,81,Urban,HR Executive,121769,1 +109856,Male,35,Masters,7,26,86,77,14,4.0,1,88,Urban,HR Executive,97743,1 +109857,Male,34,Masters,11,11,99,20,28,6.0,1,32,Semi-Urban,ML Engineer,26270,0 +109858,Male,40,PhD,13,40,33,58,56,7.0,6,73,Urban,ML Engineer,37502,0 +109859,Female,49,Diploma,13,54,66,83,58,5.0,7,10,Rural,Data Analyst,63245,0 +109860,Male,39,High School,3,41,43,15,64,7.0,4,92,Urban,HR Executive,124460,0 +109861,Male,27,Diploma,0,29,33,9,14,4.0,6,6,Urban,Manager,118604,0 +109862,Male,46,Bachelors,4,20,5,1,32,7.0,0,0,Rural,ML Engineer,95344,0 +109863,Female,24,Bachelors,19,99,29,53,70,6.0,7,99,Urban,Manager,89573,1 +109864,Male,42,Diploma,11,88,25,98,80,1.0,5,85,Urban,HR Executive,20406,1 +109865,Female,54,Bachelors,17,67,90,72,56,0.0,4,3,Urban,Manager,20226,0 +109866,Male,54,Diploma,15,2,39,9,55,9.0,7,6,Urban,Manager,50161,0 +109867,Male,29,Bachelors,17,9,63,65,26,0.0,3,83,Semi-Urban,Software Engineer,109296,0 +109868,Female,41,Bachelors,6,90,13,83,17,9.0,1,66,Urban,Software Engineer,136505,1 +109869,Female,26,Masters,3,93,0,48,56,4.0,2,75,Urban,Software Engineer,44073,0 +109870,Male,53,High School,14,35,92,83,98,7.0,0,3,Semi-Urban,Manager,66644,0 +109871,Female,56,High School,3,35,2,72,61,0.0,4,92,Urban,ML Engineer,74891,0 +109872,Male,35,Masters,10,62,0,30,67,3.0,5,23,Semi-Urban,Manager,71102,0 +109873,Female,39,Bachelors,1,80,8,91,35,0.0,5,64,Urban,HR Executive,89101,1 +109874,Male,28,Bachelors,9,20,57,55,42,8.0,1,30,Semi-Urban,Data Analyst,26369,0 +109875,Male,38,High School,3,20,25,72,42,1.0,2,66,Urban,ML Engineer,69926,0 +109876,Male,28,Diploma,4,82,29,62,24,6.0,2,55,Semi-Urban,Manager,105428,0 +109877,Other,26,Bachelors,0,73,44,69,75,2.0,1,95,Urban,HR Executive,49331,1 +109878,Female,59,Bachelors,13,40,42,98,47,2.0,3,89,Urban,Manager,148093,1 +109879,Male,35,Bachelors,12,33,48,86,47,2.0,3,38,Urban,Manager,84503,0 +109880,Female,53,Diploma,9,96,58,9,29,3.0,2,13,Urban,Data Analyst,98318,0 +109881,Male,26,Diploma,15,24,47,65,62,5.0,7,51,Urban,Data Analyst,57411,0 +109882,Male,37,Diploma,9,27,62,83,57,6.0,5,51,Semi-Urban,ML Engineer,125104,0 +109883,Female,59,Masters,7,52,22,8,87,1.0,0,42,Semi-Urban,Data Analyst,99489,0 +109884,Female,30,Masters,10,96,95,40,83,8.0,4,86,Semi-Urban,Manager,93592,1 +109885,Male,29,Bachelors,16,0,71,47,98,3.0,5,33,Urban,ML Engineer,123400,0 +109886,Male,54,Bachelors,16,34,83,42,45,6.0,4,31,Rural,Manager,72004,0 +109887,Male,23,Diploma,6,49,72,59,52,5.0,4,13,Urban,Data Analyst,90650,0 +109888,Male,43,Masters,3,64,2,43,44,0.0,0,76,Urban,ML Engineer,61760,0 +109889,Male,48,Bachelors,4,54,39,86,32,4.0,6,44,Urban,ML Engineer,146363,0 +109890,Female,41,Bachelors,16,60,26,47,49,5.0,6,61,Urban,Data Analyst,96519,0 +109891,Other,21,Masters,4,75,63,41,9,3.0,4,44,Semi-Urban,HR Executive,149115,0 +109892,Male,25,Masters,17,47,89,1,42,7.0,6,94,Semi-Urban,Software Engineer,140919,0 +109893,Female,51,Masters,13,54,20,73,6,1.0,6,85,Urban,Manager,122354,0 +109894,Female,44,Bachelors,19,56,83,68,8,3.0,3,73,Urban,Manager,27557,1 +109895,Male,58,PhD,18,95,30,64,47,1.0,6,57,Semi-Urban,Data Analyst,75187,1 +109896,Male,54,Bachelors,10,61,87,43,30,8.0,6,56,Rural,Manager,130158,1 +109897,Female,30,Bachelors,12,98,49,55,62,0.0,3,28,Urban,ML Engineer,116579,0 +109898,Male,34,Masters,0,99,24,19,73,0.0,1,80,Urban,Data Analyst,44087,0 +109899,Male,38,Diploma,16,22,61,58,62,4.0,5,93,Urban,Data Analyst,23965,0 +109900,Other,56,Bachelors,8,88,2,77,60,9.0,1,88,Rural,ML Engineer,141281,1 +109901,Female,55,Masters,0,94,76,42,33,0.0,0,8,Urban,Manager,100606,0 +109902,Female,27,Bachelors,13,11,40,92,41,4.0,1,1,Urban,HR Executive,86712,0 +109903,Male,46,Bachelors,3,47,14,2,92,5.0,5,62,Urban,HR Executive,76319,0 +109904,Male,48,Masters,6,8,88,73,71,3.0,2,28,Urban,Data Analyst,143800,0 +109905,Female,40,Masters,11,5,84,54,66,0.0,4,80,Urban,Software Engineer,27707,0 +109906,Male,26,Masters,4,73,7,28,53,2.0,1,81,Urban,HR Executive,85283,0 +109907,Male,29,Bachelors,6,68,45,46,66,7.0,1,0,Semi-Urban,ML Engineer,89605,0 +109908,Male,44,Masters,1,59,37,19,60,9.0,4,28,Semi-Urban,Software Engineer,104487,0 +109909,Male,35,Bachelors,18,3,96,19,31,6.0,5,80,Urban,Software Engineer,138673,0 +109910,Female,53,Masters,12,50,75,8,2,9.0,2,74,Urban,HR Executive,129908,0 +109911,Other,29,Diploma,6,3,60,81,73,7.0,7,82,Urban,Software Engineer,67485,0 +109912,Female,36,Bachelors,19,51,95,92,87,5.0,2,58,Urban,HR Executive,23069,1 +109913,Male,40,Bachelors,5,8,87,32,85,6.0,2,14,Urban,Software Engineer,22066,0 +109914,Female,44,Masters,13,7,28,3,6,2.0,3,84,Semi-Urban,ML Engineer,44786,0 +109915,Female,33,Bachelors,13,87,3,6,69,5.0,6,90,Urban,Manager,42824,0 +109916,Female,38,High School,12,37,31,46,13,4.0,3,36,Urban,Software Engineer,55748,0 +109917,Male,36,Diploma,3,58,75,32,47,8.0,3,89,Urban,Data Analyst,91877,1 +109918,Male,39,Bachelors,4,82,34,28,68,5.0,5,3,Urban,Manager,65606,0 +109919,Female,50,Masters,12,0,73,53,13,8.0,5,28,Semi-Urban,Software Engineer,57766,0 +109920,Female,53,Masters,6,93,20,27,56,3.0,5,73,Rural,Data Analyst,105167,0 +109921,Female,27,Masters,19,82,17,66,57,7.0,7,85,Rural,Software Engineer,69166,1 +109922,Male,46,Diploma,2,24,35,23,26,0.0,0,84,Urban,ML Engineer,132474,0 +109923,Other,26,Masters,2,44,85,6,47,0.0,0,83,Urban,Manager,49513,0 +109924,Male,41,Diploma,8,37,81,57,28,6.0,6,12,Urban,Data Analyst,92711,0 +109925,Male,42,Bachelors,17,9,4,72,0,6.0,4,62,Urban,Manager,81475,0 +109926,Female,47,High School,17,11,92,73,82,4.0,1,21,Urban,ML Engineer,139325,0 +109927,Male,37,Masters,10,43,22,25,60,1.0,6,19,Urban,Manager,21459,0 +109928,Male,24,Diploma,0,63,22,90,50,2.0,6,51,Rural,ML Engineer,52579,0 +109929,Male,54,Bachelors,5,46,15,81,81,6.0,1,13,Urban,Software Engineer,140645,0 +109930,Male,51,Masters,16,17,73,32,97,3.0,7,18,Urban,HR Executive,40406,0 +109931,Male,29,Bachelors,7,66,32,22,88,3.0,6,97,Urban,Manager,109774,0 +109932,Male,56,High School,9,45,30,48,14,2.0,4,8,Urban,Manager,21951,0 +109933,Female,22,Bachelors,16,85,18,74,75,2.0,2,16,Urban,ML Engineer,98094,0 +109934,Male,24,Masters,15,55,63,6,93,5.0,2,23,Semi-Urban,Data Analyst,134165,0 +109935,Female,29,Bachelors,9,77,87,86,16,1.0,6,21,Urban,Manager,142359,1 +109936,Female,25,PhD,7,66,8,35,0,6.0,5,1,Urban,Data Analyst,113210,0 +109937,Male,23,Bachelors,2,75,74,62,66,1.0,6,40,Urban,HR Executive,112601,1 +109938,Female,46,Bachelors,1,91,29,30,53,4.0,5,50,Urban,Manager,75108,0 +109939,Male,41,Masters,11,83,33,0,50,0.0,7,42,Semi-Urban,Manager,57772,0 +109940,Male,30,High School,5,78,78,19,26,0.0,7,63,Semi-Urban,Manager,69828,1 +109941,Other,57,Masters,2,8,64,26,66,0.0,2,70,Urban,Manager,43498,0 +109942,Female,59,Bachelors,15,5,75,95,84,6.0,3,84,Urban,Data Analyst,84516,1 +109943,Male,27,Diploma,15,93,84,76,56,2.0,3,27,Rural,Manager,31534,1 +109944,Male,22,Bachelors,17,60,82,55,93,3.0,2,13,Rural,Data Analyst,55173,0 +109945,Male,26,Bachelors,19,24,54,18,93,0.0,7,30,Urban,Software Engineer,89940,0 +109946,Male,31,Diploma,4,82,31,72,65,6.0,3,84,Rural,HR Executive,140132,1 +109947,Other,50,Bachelors,4,18,6,94,27,0.0,1,64,Semi-Urban,Manager,126566,0 +109948,Male,49,Diploma,10,76,16,60,53,4.0,5,81,Urban,Manager,112998,0 +109949,Male,37,Bachelors,6,16,98,13,26,3.0,1,44,Urban,Data Analyst,110933,0 +109950,Male,48,Bachelors,14,2,29,30,48,0.0,7,24,Urban,Software Engineer,44885,0 +109951,Female,34,Bachelors,13,92,24,42,11,0.0,0,79,Urban,ML Engineer,58739,0 +109952,Female,26,Bachelors,10,53,87,62,66,8.0,7,43,Semi-Urban,ML Engineer,72528,1 +109953,Male,23,Masters,0,20,30,60,49,9.0,2,29,Rural,ML Engineer,132698,0 +109954,Male,51,PhD,7,91,97,52,14,7.0,4,45,Semi-Urban,Manager,128692,1 +109955,Male,21,Bachelors,9,55,48,91,63,6.0,1,85,Urban,Data Analyst,28002,1 +109956,Female,33,Masters,3,79,73,42,86,0.0,5,92,Urban,Software Engineer,54056,1 +109957,Male,31,Bachelors,6,14,82,14,8,9.0,1,18,Rural,ML Engineer,74574,0 +109958,Male,37,Diploma,18,91,33,6,42,3.0,7,95,Urban,HR Executive,137963,0 +109959,Male,27,Masters,5,24,5,70,49,2.0,0,30,Semi-Urban,HR Executive,142252,0 +109960,Male,35,Diploma,17,88,32,67,41,2.0,0,5,Rural,HR Executive,104243,0 +109961,Female,53,Masters,0,19,57,61,16,6.0,4,90,Urban,Manager,64748,0 +109962,Male,30,Bachelors,19,87,42,76,67,8.0,7,98,Urban,HR Executive,87617,1 +109963,Male,56,Bachelors,13,69,76,73,98,1.0,1,8,Urban,Data Analyst,112277,0 +109964,Male,38,High School,4,43,94,52,7,1.0,6,82,Rural,ML Engineer,91642,1 +109965,Female,45,Masters,13,90,34,31,35,9.0,2,8,Semi-Urban,Data Analyst,116627,0 +109966,Female,22,Bachelors,14,35,10,20,93,5.0,4,70,Urban,ML Engineer,72031,0 +109967,Male,52,Bachelors,11,27,31,53,94,8.0,6,55,Rural,HR Executive,94706,0 +109968,Male,52,High School,1,93,93,95,27,6.0,7,43,Urban,HR Executive,103239,1 +109969,Female,24,Diploma,8,31,68,60,31,7.0,3,33,Urban,HR Executive,111694,0 +109970,Female,33,Bachelors,7,49,59,2,77,0.0,4,5,Urban,Manager,131574,0 +109971,Female,47,Bachelors,11,17,65,82,25,7.0,5,52,Rural,ML Engineer,56143,0 +109972,Male,38,Bachelors,10,43,7,46,14,1.0,1,16,Urban,Data Analyst,121988,0 +109973,Female,34,Bachelors,8,65,82,7,69,6.0,7,49,Urban,HR Executive,141012,0 +109974,Other,46,Bachelors,19,44,49,27,16,8.0,4,0,Semi-Urban,ML Engineer,54499,0 +109975,Female,32,Diploma,3,73,10,33,7,6.0,3,80,Rural,Software Engineer,38457,0 +109976,Male,50,Bachelors,9,42,80,58,97,8.0,6,13,Semi-Urban,Manager,81399,0 +109977,Male,36,Bachelors,16,82,87,63,49,1.0,4,21,Urban,HR Executive,58500,1 +109978,Male,31,Bachelors,18,39,70,45,42,5.0,7,98,Semi-Urban,HR Executive,119285,1 +109979,Female,53,Diploma,3,49,2,33,4,1.0,5,64,Urban,Data Analyst,116081,0 +109980,Female,36,Bachelors,13,91,6,39,0,2.0,7,1,Urban,Software Engineer,62295,0 +109981,Female,45,Diploma,2,18,0,32,11,7.0,3,64,Rural,Software Engineer,51812,0 +109982,Male,25,Diploma,7,6,40,20,21,1.0,3,35,Urban,HR Executive,146931,0 +109983,Male,40,Bachelors,4,95,2,72,9,1.0,0,30,Semi-Urban,Manager,43786,0 +109984,Male,39,High School,12,68,38,42,80,2.0,2,18,Semi-Urban,ML Engineer,136042,0 +109985,Other,56,High School,7,45,87,43,72,6.0,5,90,Semi-Urban,Manager,102156,1 +109986,Male,49,Masters,14,6,17,74,85,3.0,5,62,Urban,Software Engineer,127563,0 +109987,Male,44,Masters,11,11,85,21,62,5.0,2,94,Urban,HR Executive,88325,0 +109988,Female,36,High School,3,24,54,2,5,0.0,7,32,Semi-Urban,Data Analyst,31385,0 +109989,Male,55,PhD,15,85,7,82,20,9.0,3,8,Urban,Data Analyst,80728,0 +109990,Female,47,Masters,17,79,86,56,11,3.0,7,44,Urban,Manager,101682,1 +109991,Other,50,Bachelors,0,7,31,92,48,5.0,7,27,Urban,Data Analyst,81118,0 +109992,Female,39,Diploma,11,57,58,51,60,6.0,7,50,Semi-Urban,HR Executive,89638,0 +109993,Male,27,High School,6,52,60,73,96,7.0,3,84,Semi-Urban,HR Executive,48565,1 +109994,Female,47,Masters,18,97,38,4,66,8.0,3,47,Urban,HR Executive,143360,0 +109995,Female,35,Bachelors,8,41,9,17,27,7.0,0,66,Urban,Data Analyst,79976,0 +109996,Female,36,Bachelors,16,81,47,58,92,0.0,0,58,Urban,HR Executive,80226,1 +109997,Male,23,Bachelors,19,34,16,62,19,0.0,5,12,Urban,Manager,32859,0 +109998,Female,47,Bachelors,1,47,85,64,38,5.0,0,86,Semi-Urban,Data Analyst,21641,1 +109999,Male,24,Masters,9,97,36,23,62,7.0,3,87,Urban,HR Executive,68742,1 +110000,Male,44,Bachelors,10,68,68,10,56,3.0,7,10,Semi-Urban,Software Engineer,63613,0 +110001,Male,49,Bachelors,17,9,86,25,61,4.0,3,3,Urban,Data Analyst,102188,0 +110002,Male,40,PhD,16,53,75,73,96,0.0,1,96,Semi-Urban,Data Analyst,149716,1 +110003,Male,46,Bachelors,19,42,74,76,43,2.0,2,56,Urban,Data Analyst,38418,1 +110004,Female,28,Diploma,18,47,74,1,52,9.0,7,34,Semi-Urban,Data Analyst,100266,0 +110005,Male,42,Bachelors,16,39,34,24,56,9.0,6,14,Urban,Manager,89575,0 +110006,Female,21,Masters,4,78,53,19,58,1.0,1,20,Rural,Manager,74464,0 +110007,Male,23,Bachelors,1,33,52,98,82,4.0,2,67,Semi-Urban,HR Executive,28447,1 +110008,Male,49,Bachelors,4,84,50,28,73,8.0,5,50,Rural,HR Executive,49090,0 +110009,Male,32,Diploma,4,21,30,6,64,0.0,4,29,Urban,ML Engineer,81247,0 +110010,Male,33,Diploma,17,41,53,84,98,3.0,7,27,Urban,Data Analyst,127653,0 +110011,Female,33,Bachelors,15,18,21,66,56,2.0,7,9,Urban,Manager,76638,0 +110012,Male,27,Masters,16,37,67,42,32,9.0,0,91,Urban,Manager,147111,1 +110013,Male,41,High School,0,76,20,59,94,5.0,3,53,Semi-Urban,ML Engineer,95712,0 +110014,Male,28,Masters,10,97,69,90,59,3.0,0,97,Semi-Urban,ML Engineer,77118,1 +110015,Male,55,Diploma,15,59,93,72,71,1.0,7,5,Rural,HR Executive,75784,0 +110016,Female,40,High School,5,49,18,12,29,8.0,1,10,Semi-Urban,HR Executive,140401,0 +110017,Female,33,Masters,16,55,84,66,60,2.0,1,32,Urban,Manager,29845,0 +110018,Male,29,High School,2,89,91,20,44,0.0,0,83,Urban,Software Engineer,68578,1 +110019,Female,27,Masters,9,37,94,5,68,0.0,5,93,Semi-Urban,HR Executive,137243,0 +110020,Male,35,High School,6,48,18,74,16,5.0,6,38,Urban,ML Engineer,52803,0 +110021,Male,51,High School,2,35,40,47,28,0.0,4,70,Urban,HR Executive,109677,0 +110022,Female,42,PhD,4,94,30,70,81,5.0,4,29,Rural,Manager,149230,0 +110023,Male,36,PhD,11,98,53,15,10,9.0,0,46,Semi-Urban,Manager,64289,0 +110024,Male,38,Bachelors,19,78,74,90,7,2.0,2,4,Urban,Software Engineer,49218,1 +110025,Female,51,Bachelors,4,95,5,88,81,6.0,3,61,Urban,Data Analyst,149670,1 +110026,Female,31,Bachelors,18,79,53,33,66,4.0,4,21,Semi-Urban,Data Analyst,132614,0 +110027,Male,38,PhD,3,75,96,53,31,1.0,5,80,Urban,Software Engineer,32974,1 +110028,Male,23,High School,6,14,30,84,28,7.0,2,56,Urban,Manager,148733,0 +110029,Female,49,High School,8,29,58,95,45,1.0,3,15,Urban,ML Engineer,21218,0 +110030,Male,54,Masters,2,28,66,62,52,8.0,0,2,Urban,Manager,24610,0 +110031,Male,42,Diploma,17,58,3,65,29,2.0,1,35,Semi-Urban,ML Engineer,128820,0 +110032,Male,28,Masters,6,33,48,20,93,1.0,2,45,Urban,Manager,49018,0 +110033,Female,37,Bachelors,7,11,48,16,10,4.0,1,10,Semi-Urban,Software Engineer,97991,0 +110034,Female,30,Bachelors,3,18,30,81,21,8.0,7,11,Urban,ML Engineer,92063,0 +110035,Male,57,Bachelors,2,79,30,55,2,9.0,7,14,Urban,Software Engineer,75971,0 +110036,Male,56,Diploma,11,10,35,71,64,1.0,4,20,Semi-Urban,Data Analyst,29433,0 +110037,Male,49,Diploma,4,5,68,81,35,6.0,7,30,Urban,Software Engineer,57695,0 +110038,Male,54,Masters,7,7,92,62,25,5.0,3,97,Urban,Manager,39145,1 +110039,Male,31,Diploma,5,65,88,60,98,2.0,0,10,Urban,HR Executive,27418,0 +110040,Other,47,Diploma,19,45,65,32,20,6.0,7,82,Semi-Urban,Manager,76712,0 +110041,Female,25,Bachelors,10,27,48,84,19,3.0,2,24,Urban,Data Analyst,24903,0 +110042,Male,51,Diploma,5,10,2,93,81,7.0,3,71,Urban,HR Executive,69512,0 +110043,Female,31,Masters,19,61,34,57,61,1.0,3,4,Rural,HR Executive,26769,0 +110044,Male,22,High School,18,54,57,22,11,5.0,4,58,Rural,Software Engineer,93932,0 +110045,Female,25,Diploma,11,19,42,23,7,6.0,1,11,Urban,Manager,93470,0 +110046,Male,24,Masters,7,69,30,70,49,9.0,2,54,Semi-Urban,Data Analyst,142739,0 +110047,Male,57,Bachelors,16,88,35,78,81,8.0,4,66,Urban,Data Analyst,139836,1 +110048,Female,32,Bachelors,8,94,38,46,93,1.0,0,52,Urban,Software Engineer,108699,0 +110049,Female,54,Bachelors,9,98,7,68,52,7.0,2,12,Semi-Urban,Software Engineer,43106,0 +110050,Female,30,Masters,10,64,19,6,7,9.0,4,21,Urban,Manager,97591,0 +110051,Female,53,Diploma,16,85,36,65,85,3.0,4,77,Urban,Manager,43153,1 +110052,Female,27,Diploma,16,80,35,62,86,3.0,7,32,Rural,Software Engineer,114018,0 +110053,Female,46,Masters,11,4,78,70,80,6.0,3,87,Urban,Data Analyst,64959,0 +110054,Male,44,Bachelors,13,41,61,47,86,5.0,1,26,Urban,Software Engineer,129172,0 +110055,Male,43,Masters,8,1,68,37,15,7.0,3,66,Urban,Manager,24990,0 +110056,Male,28,Bachelors,8,6,10,22,70,1.0,0,23,Semi-Urban,ML Engineer,81805,0 +110057,Male,53,Masters,2,81,37,82,30,2.0,3,15,Urban,Manager,74163,0 +110058,Female,28,Masters,19,99,47,31,95,7.0,1,15,Urban,Manager,116948,0 +110059,Male,41,Diploma,11,73,67,86,38,5.0,5,34,Urban,Manager,69162,1 +110060,Male,41,Masters,6,66,42,87,54,4.0,2,28,Urban,Data Analyst,127518,0 +110061,Male,23,Diploma,12,24,1,42,20,6.0,6,89,Urban,Data Analyst,53719,0 +110062,Female,44,Masters,0,32,82,6,93,9.0,2,5,Rural,Data Analyst,114915,0 +110063,Female,27,Diploma,9,45,95,32,62,1.0,6,40,Rural,Data Analyst,29726,0 +110064,Female,30,Masters,7,62,53,8,50,3.0,2,7,Semi-Urban,ML Engineer,113192,0 +110065,Male,52,Bachelors,18,99,4,47,20,3.0,1,87,Rural,Data Analyst,56594,1 +110066,Male,55,Diploma,10,75,9,42,44,7.0,0,83,Semi-Urban,ML Engineer,139719,0 +110067,Male,32,Masters,18,56,81,76,86,6.0,0,69,Urban,Manager,128650,1 +110068,Female,50,High School,9,34,92,60,33,3.0,3,91,Urban,HR Executive,20182,1 +110069,Female,49,Masters,7,23,1,10,3,3.0,3,93,Urban,ML Engineer,81775,0 +110070,Male,26,High School,18,77,77,72,94,4.0,0,77,Semi-Urban,Manager,67315,1 +110071,Female,35,Bachelors,19,25,52,22,60,3.0,1,38,Rural,ML Engineer,129024,0 +110072,Female,40,Masters,7,68,79,48,69,3.0,1,84,Urban,HR Executive,45145,1 +110073,Female,29,Bachelors,12,91,70,27,36,3.0,5,5,Rural,ML Engineer,27751,0 +110074,Female,48,Diploma,13,39,86,13,17,3.0,0,53,Rural,Data Analyst,20489,0 +110075,Female,59,Masters,0,33,89,30,35,3.0,4,71,Rural,Software Engineer,97305,0 +110076,Male,58,Masters,5,30,3,62,54,4.0,7,92,Semi-Urban,HR Executive,44163,0 +110077,Female,55,Bachelors,19,53,62,93,34,0.0,3,78,Rural,Data Analyst,80832,1 +110078,Male,48,Bachelors,12,31,80,38,92,3.0,1,72,Urban,ML Engineer,125079,0 +110079,Female,36,Diploma,11,16,10,51,61,5.0,5,33,Urban,Software Engineer,51972,0 +110080,Male,23,Masters,14,17,84,63,47,3.0,3,7,Urban,Software Engineer,136352,0 +110081,Female,59,Masters,8,16,18,42,99,2.0,6,84,Urban,Manager,114185,0 +110082,Female,45,Bachelors,1,21,13,1,9,8.0,0,0,Rural,Manager,45166,0 +110083,Female,24,Masters,4,12,84,56,2,7.0,1,24,Rural,Data Analyst,141468,0 +110084,Female,42,Bachelors,15,34,51,66,68,2.0,0,64,Urban,HR Executive,111901,0 +110085,Female,34,High School,4,78,85,41,14,8.0,4,24,Rural,HR Executive,63557,0 +110086,Male,39,Bachelors,8,60,72,61,44,5.0,0,42,Urban,Manager,138376,1 +110087,Male,29,Masters,14,48,89,93,47,6.0,2,17,Semi-Urban,ML Engineer,49525,1 +110088,Female,33,Bachelors,8,24,72,93,85,2.0,0,13,Urban,ML Engineer,132859,0 +110089,Male,44,Bachelors,15,4,56,25,91,9.0,7,78,Semi-Urban,Manager,34957,0 +110090,Male,30,Bachelors,14,47,59,35,78,8.0,1,38,Urban,Data Analyst,122272,0 +110091,Male,56,Bachelors,13,48,52,34,56,3.0,5,28,Semi-Urban,Data Analyst,135053,0 +110092,Male,31,PhD,15,71,99,18,92,1.0,6,72,Urban,Software Engineer,40011,1 +110093,Other,29,Bachelors,16,19,44,85,48,7.0,3,30,Semi-Urban,ML Engineer,61157,0 +110094,Male,43,Diploma,6,38,87,74,68,0.0,5,2,Rural,Data Analyst,35904,0 +110095,Female,39,Bachelors,16,86,95,40,76,7.0,4,66,Urban,Manager,51885,1 +110096,Male,37,Bachelors,1,68,97,98,50,6.0,5,62,Rural,Manager,61056,1 +110097,Male,43,High School,5,24,1,14,40,7.0,4,86,Semi-Urban,Software Engineer,126423,0 +110098,Female,26,Bachelors,19,64,76,81,41,5.0,0,11,Urban,HR Executive,62021,0 +110099,Male,31,Diploma,2,96,20,11,49,0.0,4,29,Urban,HR Executive,119886,0 +110100,Female,27,PhD,4,33,82,43,99,7.0,2,30,Semi-Urban,HR Executive,112402,0 +110101,Other,53,PhD,0,96,20,57,62,7.0,6,65,Urban,Manager,76110,0 +110102,Female,59,Bachelors,12,71,40,35,56,2.0,0,74,Urban,HR Executive,59030,0 +110103,Female,55,Bachelors,16,94,92,51,15,7.0,3,78,Urban,HR Executive,97382,1 +110104,Male,34,Bachelors,13,8,87,21,24,9.0,0,87,Urban,Software Engineer,22562,0 +110105,Male,37,Masters,10,28,22,25,92,2.0,0,65,Semi-Urban,HR Executive,107017,0 +110106,Female,53,Bachelors,7,37,83,56,27,1.0,0,41,Urban,Manager,148118,0 +110107,Female,41,Masters,6,72,15,60,59,7.0,6,91,Semi-Urban,Data Analyst,63619,0 +110108,Male,49,Bachelors,9,54,56,19,73,3.0,0,98,Urban,Data Analyst,52216,0 +110109,Male,30,Diploma,3,32,18,15,42,9.0,0,53,Urban,Software Engineer,108777,0 +110110,Female,30,High School,4,45,56,31,8,5.0,1,52,Urban,Manager,81201,0 +110111,Male,55,Bachelors,18,98,67,57,22,4.0,0,49,Semi-Urban,ML Engineer,53996,1 +110112,Male,51,PhD,17,42,43,50,68,7.0,4,17,Urban,Data Analyst,99470,0 +110113,Male,27,Bachelors,1,28,26,28,43,5.0,0,78,Urban,Manager,104799,0 +110114,Male,39,High School,14,91,50,89,49,6.0,6,34,Semi-Urban,HR Executive,72505,1 +110115,Other,58,Diploma,7,45,36,88,87,6.0,5,95,Urban,HR Executive,120849,1 +110116,Male,31,High School,5,76,86,5,48,6.0,4,43,Rural,Data Analyst,109129,0 +110117,Female,32,High School,17,82,10,93,86,0.0,6,1,Rural,ML Engineer,134207,0 +110118,Male,21,High School,3,78,75,80,32,2.0,3,75,Urban,Data Analyst,122521,1 +110119,Female,27,Bachelors,0,93,85,39,19,5.0,3,46,Urban,Manager,131192,1 +110120,Female,43,Bachelors,0,57,6,55,95,6.0,2,30,Urban,HR Executive,25366,0 +110121,Female,26,Masters,11,40,94,96,21,1.0,6,94,Urban,Software Engineer,49032,1 +110122,Female,47,Bachelors,4,61,94,65,38,0.0,3,61,Urban,Software Engineer,38218,1 +110123,Female,54,Masters,5,56,10,44,65,3.0,2,43,Rural,Data Analyst,21507,0 +110124,Male,50,Bachelors,7,36,94,85,8,9.0,0,40,Urban,Data Analyst,125778,1 +110125,Male,43,Masters,7,35,21,37,49,6.0,0,88,Semi-Urban,Software Engineer,58801,0 +110126,Female,29,Bachelors,17,41,76,46,82,6.0,5,80,Rural,Software Engineer,50087,1 +110127,Male,27,Masters,2,5,43,5,20,5.0,6,41,Semi-Urban,Manager,44812,0 +110128,Female,56,Diploma,13,99,54,38,30,5.0,3,26,Rural,Data Analyst,94340,0 +110129,Male,58,Bachelors,4,21,83,0,90,0.0,1,10,Urban,Manager,64343,0 +110130,Male,33,Diploma,11,65,22,1,28,7.0,2,74,Urban,Manager,116255,0 +110131,Female,26,Masters,5,61,22,76,79,6.0,0,71,Urban,Software Engineer,24750,0 +110132,Female,57,Diploma,5,60,79,40,39,0.0,1,11,Rural,ML Engineer,62643,0 +110133,Female,41,Bachelors,10,72,1,0,53,1.0,4,62,Urban,HR Executive,142507,0 +110134,Male,42,Masters,3,73,88,87,29,6.0,2,54,Semi-Urban,ML Engineer,28067,1 +110135,Male,55,Diploma,10,74,35,78,15,3.0,7,35,Urban,Software Engineer,34138,0 +110136,Male,34,PhD,12,99,66,21,52,5.0,7,43,Urban,Data Analyst,137942,0 +110137,Male,51,Bachelors,18,49,95,1,90,8.0,6,31,Urban,Data Analyst,130232,0 +110138,Female,26,PhD,7,52,38,47,55,8.0,3,6,Rural,ML Engineer,141243,0 +110139,Female,45,PhD,9,91,72,92,16,8.0,7,95,Urban,HR Executive,52255,1 +110140,Male,44,Bachelors,4,93,8,82,77,8.0,0,61,Urban,ML Engineer,131619,1 +110141,Male,39,Bachelors,14,24,17,22,39,4.0,6,91,Semi-Urban,Software Engineer,53497,0 +110142,Male,35,Masters,4,47,41,70,63,0.0,6,75,Urban,Data Analyst,73183,0 +110143,Male,56,Bachelors,5,56,84,58,13,1.0,0,16,Urban,HR Executive,91467,0 +110144,Other,42,Diploma,13,9,7,36,99,6.0,0,58,Urban,Data Analyst,58230,0 +110145,Male,22,Masters,15,70,40,81,14,6.0,5,51,Semi-Urban,Software Engineer,25320,1 +110146,Female,37,High School,16,58,23,17,30,1.0,3,57,Urban,ML Engineer,71028,0 +110147,Male,59,Bachelors,13,50,63,87,24,5.0,0,5,Semi-Urban,HR Executive,58303,0 +110148,Female,56,Bachelors,6,94,70,84,77,3.0,1,81,Urban,ML Engineer,145683,1 +110149,Male,49,PhD,7,45,98,4,2,3.0,0,59,Urban,ML Engineer,132819,0 +110150,Male,40,Masters,17,33,32,76,27,4.0,3,47,Urban,ML Engineer,103322,0 +110151,Male,59,Masters,5,48,72,8,44,6.0,5,72,Urban,HR Executive,146981,0 +110152,Female,55,Bachelors,19,72,1,69,88,7.0,2,26,Semi-Urban,Data Analyst,131932,0 +110153,Other,55,PhD,13,34,13,41,88,3.0,4,92,Rural,Software Engineer,101890,0 +110154,Female,33,Bachelors,16,26,66,1,95,7.0,3,79,Semi-Urban,Manager,82923,0 +110155,Male,51,High School,1,65,13,37,91,1.0,7,14,Urban,HR Executive,48483,0 +110156,Female,46,Masters,5,84,62,19,66,7.0,2,98,Urban,Manager,58210,1 +110157,Male,56,Bachelors,19,26,9,55,43,7.0,6,6,Rural,HR Executive,36156,0 +110158,Male,43,Diploma,2,40,75,55,86,6.0,6,2,Urban,Manager,33571,0 +110159,Female,21,High School,5,50,55,90,81,1.0,1,2,Urban,Software Engineer,91396,0 +110160,Male,54,High School,18,67,15,14,16,8.0,2,59,Semi-Urban,Software Engineer,90955,0 +110161,Male,58,Bachelors,11,48,5,97,75,6.0,5,97,Urban,Software Engineer,35753,1 +110162,Male,55,High School,8,19,56,71,78,5.0,6,93,Urban,Data Analyst,67841,1 +110163,Male,58,High School,1,34,32,40,28,2.0,0,47,Urban,ML Engineer,138050,0 +110164,Male,22,Bachelors,12,73,89,83,49,9.0,6,18,Urban,HR Executive,24214,1 +110165,Male,58,Masters,18,42,42,43,64,6.0,0,74,Urban,ML Engineer,69262,0 +110166,Male,25,Bachelors,6,99,44,0,84,6.0,5,81,Rural,Software Engineer,36538,0 +110167,Male,30,Bachelors,19,87,90,97,64,0.0,2,58,Semi-Urban,ML Engineer,37101,1 +110168,Female,31,Diploma,16,1,62,31,16,7.0,6,60,Rural,Manager,146653,0 +110169,Male,30,Bachelors,13,36,47,57,73,9.0,3,81,Rural,Data Analyst,69690,0 +110170,Female,34,Masters,16,32,36,37,86,8.0,1,42,Urban,HR Executive,135813,0 +110171,Male,22,Masters,16,79,57,36,63,9.0,4,93,Rural,Data Analyst,127316,1 +110172,Male,21,Diploma,10,38,40,58,17,3.0,4,64,Rural,HR Executive,51694,0 +110173,Male,57,Bachelors,12,74,14,20,5,9.0,3,98,Urban,HR Executive,33233,0 +110174,Male,26,Masters,12,77,15,37,80,2.0,7,62,Semi-Urban,Manager,74646,0 +110175,Female,40,Masters,12,58,95,51,5,9.0,2,80,Rural,ML Engineer,128350,1 +110176,Female,24,High School,18,13,45,93,93,0.0,6,68,Rural,ML Engineer,115032,0 +110177,Female,59,Diploma,16,29,6,53,23,4.0,4,82,Semi-Urban,HR Executive,119570,0 +110178,Male,23,Masters,9,77,46,23,67,5.0,5,90,Semi-Urban,Manager,116865,1 +110179,Male,31,Bachelors,9,4,65,48,89,6.0,6,92,Semi-Urban,ML Engineer,133340,0 +110180,Male,29,Masters,3,97,83,22,83,7.0,1,10,Urban,ML Engineer,124272,0 +110181,Other,21,High School,0,41,13,4,2,9.0,3,94,Rural,Software Engineer,133767,0 +110182,Other,28,High School,5,28,65,36,70,8.0,3,29,Semi-Urban,Data Analyst,102017,0 +110183,Female,26,PhD,2,61,58,3,45,1.0,3,30,Semi-Urban,ML Engineer,85337,0 +110184,Male,22,High School,3,57,56,89,56,6.0,4,19,Semi-Urban,HR Executive,107342,0 +110185,Female,56,Bachelors,6,26,11,18,27,7.0,0,20,Urban,ML Engineer,28232,0 +110186,Female,51,Bachelors,18,69,11,11,56,7.0,4,8,Rural,ML Engineer,93006,0 +110187,Male,59,Masters,2,78,13,75,54,6.0,7,81,Rural,Software Engineer,26853,1 +110188,Male,28,Bachelors,1,74,38,6,80,5.0,0,31,Urban,ML Engineer,114221,0 +110189,Male,57,Bachelors,18,86,92,32,7,6.0,5,4,Urban,ML Engineer,148779,0 +110190,Male,35,Diploma,1,87,15,33,60,4.0,2,74,Urban,ML Engineer,53669,0 +110191,Male,37,Diploma,14,71,0,8,87,0.0,5,77,Urban,Software Engineer,59362,0 +110192,Female,21,Bachelors,1,73,82,2,31,5.0,5,42,Semi-Urban,Manager,147220,0 +110193,Male,28,Bachelors,18,61,23,7,95,4.0,5,60,Rural,HR Executive,133923,0 +110194,Male,31,Masters,5,62,91,71,52,4.0,4,24,Rural,ML Engineer,43867,1 +110195,Male,27,Bachelors,4,14,28,33,87,6.0,1,10,Urban,Software Engineer,55764,0 +110196,Male,58,Bachelors,1,62,74,55,56,2.0,5,58,Rural,ML Engineer,128508,1 +110197,Male,32,Diploma,12,36,74,63,65,1.0,5,25,Urban,HR Executive,125601,0 +110198,Male,28,High School,14,8,98,31,50,0.0,2,43,Rural,ML Engineer,37625,0 +110199,Male,35,Bachelors,0,85,42,23,50,1.0,5,27,Semi-Urban,ML Engineer,48423,0 +110200,Female,52,Bachelors,18,4,40,51,43,1.0,3,19,Urban,Data Analyst,85536,0 +110201,Other,36,Bachelors,17,71,39,14,64,6.0,4,5,Urban,ML Engineer,54831,0 +110202,Male,21,Bachelors,14,50,82,29,42,3.0,4,52,Semi-Urban,Software Engineer,44713,0 +110203,Male,47,Bachelors,15,3,78,41,40,6.0,7,17,Semi-Urban,HR Executive,102848,0 +110204,Male,47,High School,18,7,17,79,50,1.0,2,11,Urban,HR Executive,120676,0 +110205,Male,53,Masters,8,52,14,48,80,2.0,5,83,Rural,Manager,109584,0 +110206,Male,29,Diploma,18,46,47,33,75,3.0,6,89,Semi-Urban,Manager,71741,0 +110207,Female,43,High School,11,4,93,85,94,2.0,3,30,Urban,HR Executive,42556,0 +110208,Male,28,Masters,7,27,98,51,26,7.0,4,25,Urban,Manager,102217,0 +110209,Male,43,PhD,19,46,92,91,20,3.0,1,55,Rural,Software Engineer,66526,1 +110210,Male,55,Masters,12,93,43,55,4,7.0,2,41,Urban,HR Executive,144416,0 +110211,Female,41,Bachelors,6,48,65,30,23,0.0,2,51,Semi-Urban,HR Executive,83997,0 +110212,Male,22,Bachelors,6,58,12,22,49,7.0,0,19,Urban,Manager,78042,0 +110213,Male,50,High School,13,23,60,74,20,3.0,0,9,Urban,HR Executive,44285,0 +110214,Male,54,High School,10,1,23,6,13,1.0,2,64,Rural,HR Executive,50891,0 +110215,Male,46,Diploma,6,74,74,53,0,9.0,6,14,Urban,Data Analyst,75406,0 +110216,Female,50,Diploma,8,37,27,95,72,4.0,1,38,Urban,ML Engineer,28353,0 +110217,Male,59,Diploma,18,19,54,9,61,5.0,2,91,Semi-Urban,ML Engineer,137446,0 +110218,Male,39,Diploma,18,89,9,95,11,8.0,2,64,Urban,Manager,108537,1 +110219,Male,59,Bachelors,1,5,78,95,93,7.0,5,8,Urban,Data Analyst,121663,0 +110220,Female,50,Bachelors,1,95,90,52,93,3.0,4,96,Semi-Urban,ML Engineer,49377,1 +110221,Male,29,Diploma,8,46,49,17,51,6.0,4,5,Semi-Urban,ML Engineer,129607,0 +110222,Other,23,Bachelors,2,55,15,5,9,5.0,5,70,Rural,Manager,51425,0 +110223,Female,50,High School,4,94,89,17,7,8.0,3,62,Urban,Data Analyst,99419,1 +110224,Female,36,Masters,8,75,87,8,16,5.0,2,57,Semi-Urban,Software Engineer,85163,0 +110225,Female,21,High School,11,15,18,98,73,2.0,3,60,Urban,Software Engineer,101585,0 +110226,Male,31,Bachelors,2,7,58,94,13,1.0,2,85,Semi-Urban,Data Analyst,66642,1 +110227,Female,33,Diploma,11,2,0,69,10,8.0,5,92,Semi-Urban,HR Executive,92069,0 +110228,Female,27,Bachelors,10,95,39,60,97,3.0,3,18,Rural,ML Engineer,119038,0 +110229,Male,40,Bachelors,7,92,86,62,86,1.0,7,6,Urban,Manager,106134,1 +110230,Male,59,High School,10,30,57,78,74,5.0,7,61,Urban,Data Analyst,68974,0 +110231,Male,44,High School,17,93,93,26,30,0.0,4,24,Urban,Software Engineer,128009,1 +110232,Male,59,Masters,7,33,64,67,79,0.0,3,47,Rural,Manager,119468,0 +110233,Male,56,Masters,19,0,53,44,63,1.0,4,95,Urban,Software Engineer,69499,0 +110234,Female,33,High School,3,74,59,11,6,3.0,5,0,Rural,HR Executive,127581,0 +110235,Male,24,Masters,19,28,65,44,29,2.0,7,80,Urban,Manager,116782,0 +110236,Female,26,Diploma,16,87,93,62,35,6.0,3,12,Urban,ML Engineer,144974,1 +110237,Male,28,Bachelors,13,66,81,67,2,4.0,6,87,Semi-Urban,Software Engineer,46194,1 +110238,Female,45,Bachelors,19,27,38,72,41,3.0,0,27,Semi-Urban,ML Engineer,86868,0 +110239,Female,24,Bachelors,5,34,86,75,74,1.0,1,2,Urban,HR Executive,116459,0 +110240,Male,31,High School,19,84,92,43,81,8.0,0,36,Urban,ML Engineer,148652,1 +110241,Male,31,Masters,19,84,18,97,67,9.0,4,98,Semi-Urban,Software Engineer,149427,1 +110242,Male,37,Diploma,0,74,84,30,58,3.0,2,89,Urban,ML Engineer,97502,1 +110243,Male,44,High School,17,64,10,64,17,3.0,4,35,Semi-Urban,Data Analyst,85370,0 +110244,Male,34,Bachelors,16,72,39,52,57,8.0,5,49,Rural,Software Engineer,106439,0 +110245,Other,36,Masters,16,52,88,2,17,8.0,4,46,Rural,Data Analyst,134975,0 +110246,Male,45,Bachelors,17,83,28,95,53,2.0,5,70,Semi-Urban,HR Executive,35965,1 +110247,Female,24,Bachelors,5,54,0,61,48,8.0,3,95,Urban,Data Analyst,142449,0 +110248,Male,34,Bachelors,10,93,91,52,5,4.0,3,49,Urban,Manager,84878,1 +110249,Female,43,Masters,9,72,69,28,30,3.0,5,33,Semi-Urban,Manager,101224,0 +110250,Male,55,Diploma,19,38,89,95,25,8.0,0,98,Urban,Data Analyst,56515,1 +110251,Male,40,Bachelors,17,50,98,19,14,2.0,2,94,Urban,HR Executive,89132,1 +110252,Female,52,Diploma,13,68,30,86,18,8.0,6,56,Semi-Urban,HR Executive,123046,0 +110253,Male,45,Bachelors,12,46,96,27,15,7.0,0,35,Semi-Urban,HR Executive,147909,0 +110254,Male,34,Diploma,16,85,2,74,63,1.0,1,2,Urban,ML Engineer,21567,0 +110255,Female,36,Bachelors,9,26,31,22,38,0.0,4,2,Urban,Data Analyst,22835,0 +110256,Male,42,Diploma,9,35,61,85,9,6.0,2,72,Urban,Manager,144768,1 +110257,Male,24,Masters,9,47,16,93,44,6.0,3,23,Semi-Urban,HR Executive,129020,0 +110258,Male,29,Masters,2,10,3,2,43,6.0,6,14,Urban,ML Engineer,83590,0 +110259,Male,23,Bachelors,3,1,69,55,24,6.0,3,38,Urban,HR Executive,64053,0 +110260,Male,43,PhD,17,59,74,54,16,6.0,1,80,Semi-Urban,Manager,103458,1 +110261,Female,54,Bachelors,5,72,44,53,22,6.0,4,27,Urban,ML Engineer,130187,0 +110262,Male,41,PhD,16,35,44,50,92,5.0,7,40,Urban,Data Analyst,62579,0 +110263,Female,58,Diploma,5,63,3,71,81,9.0,5,28,Semi-Urban,HR Executive,72953,0 +110264,Male,56,High School,13,93,50,97,4,3.0,3,44,Rural,HR Executive,24405,1 +110265,Female,26,Bachelors,16,82,47,21,57,6.0,1,55,Urban,Software Engineer,126420,0 +110266,Male,34,Bachelors,17,91,28,79,88,9.0,1,23,Urban,ML Engineer,23656,0 +110267,Female,58,Diploma,11,74,71,20,47,2.0,5,64,Urban,Software Engineer,52063,0 +110268,Male,24,Diploma,11,89,76,71,9,7.0,2,83,Semi-Urban,Software Engineer,132564,1 +110269,Female,22,Bachelors,12,72,97,31,99,0.0,3,16,Semi-Urban,HR Executive,21233,0 +110270,Female,51,Bachelors,12,9,31,51,64,7.0,3,80,Urban,HR Executive,24472,0 +110271,Male,50,Bachelors,0,62,13,3,3,5.0,6,31,Rural,ML Engineer,129701,0 +110272,Female,46,Bachelors,2,71,71,51,99,5.0,1,0,Rural,ML Engineer,137336,0 +110273,Male,45,Bachelors,12,96,77,52,97,6.0,3,80,Urban,HR Executive,133940,1 +110274,Male,56,High School,2,48,81,50,42,5.0,1,45,Semi-Urban,Data Analyst,88592,0 +110275,Male,46,High School,10,75,46,63,2,7.0,3,66,Urban,Software Engineer,84349,1 +110276,Male,57,High School,13,48,60,20,80,5.0,1,50,Semi-Urban,Software Engineer,148269,0 +110277,Female,23,Masters,10,47,3,90,55,4.0,2,58,Rural,Software Engineer,22623,0 +110278,Female,22,PhD,17,81,22,43,8,0.0,3,46,Semi-Urban,Data Analyst,58309,0 +110279,Male,25,High School,0,87,43,85,18,3.0,0,98,Urban,Software Engineer,36258,1 +110280,Male,57,Masters,17,1,87,43,95,1.0,4,43,Urban,ML Engineer,106752,0 +110281,Male,41,Diploma,4,97,31,89,23,0.0,6,63,Semi-Urban,ML Engineer,75920,1 +110282,Female,54,Diploma,9,4,69,9,64,7.0,2,17,Semi-Urban,Data Analyst,116656,0 +110283,Male,56,Masters,14,16,89,82,29,0.0,2,93,Urban,ML Engineer,84211,1 +110284,Male,23,Bachelors,18,88,5,63,45,4.0,6,94,Semi-Urban,Data Analyst,20022,1 +110285,Male,36,Masters,18,89,64,35,94,0.0,3,94,Urban,HR Executive,88319,1 +110286,Other,58,Masters,3,60,43,87,62,6.0,4,1,Rural,HR Executive,77898,0 +110287,Male,35,Diploma,0,65,72,47,23,1.0,6,51,Urban,Data Analyst,49394,1 +110288,Female,59,Masters,7,96,32,62,84,9.0,6,4,Rural,Data Analyst,68848,0 +110289,Male,56,High School,3,13,2,93,72,3.0,6,45,Urban,ML Engineer,63228,0 +110290,Female,50,High School,17,24,99,22,91,0.0,4,71,Urban,Software Engineer,111821,0 +110291,Male,37,Diploma,7,85,65,64,32,7.0,7,11,Urban,ML Engineer,26064,0 +110292,Male,32,Diploma,7,40,8,11,18,0.0,4,53,Urban,ML Engineer,126211,0 +110293,Male,33,Diploma,17,12,24,98,61,1.0,6,61,Rural,Software Engineer,45640,0 +110294,Male,40,Masters,17,94,44,24,73,4.0,1,74,Urban,ML Engineer,147596,1 +110295,Male,45,Diploma,0,91,80,87,58,1.0,2,61,Urban,HR Executive,134514,1 +110296,Male,47,High School,10,5,29,9,77,2.0,2,77,Urban,ML Engineer,103188,0 +110297,Male,55,Bachelors,8,1,57,16,37,3.0,4,33,Semi-Urban,ML Engineer,135002,0 +110298,Female,37,Bachelors,4,84,66,61,55,3.0,2,66,Urban,HR Executive,25414,1 +110299,Male,51,Bachelors,16,61,36,8,15,0.0,1,60,Urban,Software Engineer,101071,0 +110300,Male,57,Diploma,16,34,36,67,64,0.0,3,30,Urban,ML Engineer,48780,0 +110301,Female,21,Bachelors,4,81,87,52,33,3.0,2,65,Rural,ML Engineer,65739,1 +110302,Other,58,Bachelors,6,80,89,31,82,7.0,2,73,Urban,Data Analyst,41555,1 +110303,Female,27,High School,7,66,39,6,53,5.0,5,36,Rural,Software Engineer,31824,0 +110304,Male,22,Masters,0,1,30,9,1,7.0,2,60,Urban,ML Engineer,119189,0 +110305,Female,46,Masters,14,97,73,8,37,7.0,6,68,Rural,Manager,141103,1 +110306,Female,46,Bachelors,11,97,78,42,26,7.0,4,24,Rural,HR Executive,20551,1 +110307,Male,23,Bachelors,7,95,27,25,47,5.0,1,64,Semi-Urban,Data Analyst,70357,0 +110308,Male,34,High School,9,47,53,56,33,3.0,7,85,Rural,Data Analyst,41999,1 +110309,Male,56,Bachelors,0,32,98,17,50,4.0,1,86,Urban,ML Engineer,95976,0 +110310,Female,38,High School,6,14,77,9,88,8.0,0,24,Urban,Data Analyst,129073,0 +110311,Female,43,Diploma,13,15,99,54,10,0.0,2,2,Semi-Urban,HR Executive,115491,0 +110312,Male,25,Bachelors,14,15,80,18,27,4.0,1,38,Rural,HR Executive,147139,0 +110313,Male,50,Masters,1,18,66,5,5,1.0,2,95,Urban,HR Executive,73597,0 +110314,Female,34,Bachelors,19,46,97,72,43,3.0,7,86,Urban,Manager,55864,1 +110315,Male,58,Bachelors,14,14,34,21,69,5.0,1,16,Semi-Urban,Data Analyst,126195,0 +110316,Female,26,High School,3,85,72,88,56,7.0,0,60,Semi-Urban,HR Executive,92743,1 +110317,Female,45,High School,2,74,7,4,70,9.0,3,85,Urban,Data Analyst,82944,0 +110318,Female,59,Diploma,4,25,15,98,22,7.0,4,14,Urban,Software Engineer,29100,0 +110319,Female,49,Bachelors,1,28,53,69,78,1.0,4,39,Urban,Data Analyst,100087,0 +110320,Male,35,Diploma,1,56,69,35,76,8.0,5,96,Rural,Data Analyst,143069,1 +110321,Female,27,Masters,0,6,84,36,19,2.0,1,91,Semi-Urban,HR Executive,81950,0 +110322,Female,42,Bachelors,0,31,94,86,34,1.0,5,29,Rural,ML Engineer,61525,0 +110323,Male,35,Diploma,1,39,82,41,83,9.0,2,35,Urban,Software Engineer,119106,0 +110324,Male,48,Diploma,8,47,44,54,51,9.0,0,82,Urban,Data Analyst,81960,0 +110325,Male,25,High School,1,27,87,37,49,6.0,2,45,Rural,Manager,104463,0 +110326,Female,29,Diploma,2,30,72,8,61,9.0,0,22,Urban,Software Engineer,138665,0 +110327,Male,58,Bachelors,8,43,93,62,92,5.0,4,46,Rural,ML Engineer,81542,1 +110328,Female,21,Masters,16,75,76,50,58,6.0,5,18,Urban,Software Engineer,35399,0 +110329,Male,42,Diploma,3,44,31,11,53,1.0,6,1,Rural,Software Engineer,85323,0 +110330,Female,26,Masters,14,86,61,78,65,1.0,1,31,Rural,ML Engineer,134807,1 +110331,Male,54,Masters,1,83,91,38,71,8.0,7,62,Rural,Manager,130886,1 +110332,Male,52,Masters,9,31,34,8,55,3.0,3,41,Urban,ML Engineer,68025,0 +110333,Female,29,High School,15,89,29,29,84,8.0,6,93,Rural,Data Analyst,83039,0 +110334,Female,29,Bachelors,13,48,14,75,13,5.0,5,65,Semi-Urban,HR Executive,114176,0 +110335,Female,29,High School,11,1,38,17,78,9.0,0,39,Urban,HR Executive,45345,0 +110336,Female,27,Masters,11,45,93,57,48,8.0,4,68,Semi-Urban,Data Analyst,100742,1 +110337,Female,26,Masters,4,4,84,20,86,2.0,2,96,Urban,ML Engineer,77847,0 +110338,Female,54,Masters,18,36,57,97,90,3.0,0,17,Urban,Manager,48568,0 +110339,Male,54,Masters,18,27,9,14,17,6.0,7,88,Urban,Data Analyst,31871,0 +110340,Other,46,High School,15,31,15,98,9,7.0,6,75,Urban,Software Engineer,53871,0 +110341,Male,24,Bachelors,14,84,53,98,16,8.0,0,52,Rural,HR Executive,131855,1 +110342,Male,36,Masters,13,10,9,18,54,7.0,6,48,Semi-Urban,Software Engineer,38191,0 +110343,Male,52,PhD,3,97,58,21,40,5.0,1,76,Semi-Urban,Manager,39345,1 +110344,Male,30,Diploma,8,54,41,80,70,9.0,4,62,Rural,HR Executive,61547,1 +110345,Male,32,Bachelors,7,29,16,24,95,8.0,5,20,Rural,Manager,146151,0 +110346,Male,44,PhD,5,59,38,82,1,2.0,6,69,Urban,Data Analyst,72906,1 +110347,Female,27,Masters,6,36,30,72,55,2.0,3,16,Rural,Data Analyst,124347,0 +110348,Female,47,Masters,1,85,14,7,49,1.0,2,50,Semi-Urban,HR Executive,121650,0 +110349,Male,51,Bachelors,11,50,6,62,4,0.0,1,14,Semi-Urban,HR Executive,96380,0 +110350,Female,47,PhD,16,52,26,45,95,3.0,3,68,Urban,ML Engineer,85747,0 +110351,Male,52,Masters,4,18,94,72,15,5.0,5,36,Urban,HR Executive,20184,0 +110352,Male,41,Masters,14,18,28,28,87,8.0,4,5,Urban,ML Engineer,68573,0 +110353,Male,51,Bachelors,0,55,54,97,62,7.0,1,26,Rural,ML Engineer,149650,0 +110354,Male,45,Bachelors,12,84,34,81,68,6.0,1,70,Urban,ML Engineer,97435,1 +110355,Female,35,Bachelors,1,34,81,47,17,1.0,7,38,Semi-Urban,Software Engineer,145103,0 +110356,Other,29,Diploma,9,65,79,7,41,6.0,2,20,Urban,Data Analyst,131538,0 +110357,Female,56,Masters,6,77,13,7,21,6.0,7,31,Semi-Urban,ML Engineer,20521,0 +110358,Male,24,Bachelors,18,34,94,2,72,0.0,2,52,Rural,HR Executive,114802,0 +110359,Female,55,Diploma,2,71,28,19,55,1.0,5,1,Urban,Manager,93246,0 +110360,Female,29,High School,2,18,78,23,29,0.0,2,87,Semi-Urban,Data Analyst,26601,0 +110361,Male,56,Bachelors,3,2,72,4,33,8.0,7,1,Urban,ML Engineer,105964,0 +110362,Male,39,PhD,14,37,94,1,25,5.0,2,29,Rural,Data Analyst,84320,0 +110363,Male,54,Bachelors,3,36,30,70,33,3.0,1,82,Urban,Software Engineer,116012,0 +110364,Female,57,Diploma,16,27,76,19,90,6.0,4,94,Rural,Manager,44364,0 +110365,Male,42,High School,10,29,41,11,31,3.0,5,52,Semi-Urban,Data Analyst,57284,0 +110366,Male,38,High School,10,73,80,51,47,0.0,7,30,Urban,HR Executive,137326,0 +110367,Female,21,PhD,8,37,84,79,95,1.0,6,19,Semi-Urban,Data Analyst,98588,0 +110368,Female,59,Diploma,10,4,82,31,3,0.0,6,71,Urban,HR Executive,119237,0 +110369,Female,30,Masters,5,99,58,42,75,4.0,6,31,Urban,Software Engineer,81906,0 +110370,Male,32,Bachelors,6,32,71,31,14,2.0,2,98,Urban,HR Executive,70463,0 +110371,Male,51,Diploma,18,27,44,94,13,5.0,1,34,Urban,HR Executive,57060,0 +110372,Male,46,High School,19,59,21,91,65,4.0,3,51,Urban,Software Engineer,134310,0 +110373,Male,21,Diploma,10,73,99,74,9,8.0,5,6,Urban,ML Engineer,54836,1 +110374,Male,35,Bachelors,1,67,49,87,14,2.0,3,22,Urban,Software Engineer,31621,0 +110375,Female,43,Diploma,16,17,76,95,88,3.0,1,83,Semi-Urban,Software Engineer,94266,1 +110376,Female,33,Bachelors,8,94,12,48,65,2.0,7,23,Urban,HR Executive,139821,0 +110377,Female,44,High School,0,56,21,93,42,4.0,7,47,Urban,ML Engineer,117428,0 +110378,Male,31,Bachelors,6,39,78,97,49,2.0,4,47,Rural,Manager,59305,1 +110379,Male,32,High School,19,14,96,55,9,5.0,5,95,Urban,Manager,45767,1 +110380,Female,30,Masters,16,23,9,70,12,4.0,3,8,Rural,Manager,145020,0 +110381,Male,56,High School,1,57,42,16,47,8.0,3,69,Semi-Urban,Software Engineer,131559,0 +110382,Female,57,PhD,3,54,2,98,80,5.0,2,24,Semi-Urban,Software Engineer,80421,0 +110383,Male,42,Diploma,0,52,76,47,27,5.0,1,52,Urban,Data Analyst,134513,0 +110384,Male,41,Bachelors,3,2,21,88,53,0.0,5,16,Semi-Urban,HR Executive,109664,0 +110385,Female,23,High School,14,95,54,27,99,0.0,3,19,Urban,HR Executive,82027,0 +110386,Male,30,High School,11,23,47,79,4,8.0,2,22,Urban,HR Executive,21895,0 +110387,Male,31,High School,18,1,76,33,15,4.0,3,3,Urban,Manager,56912,0 +110388,Male,22,Masters,8,29,93,36,99,2.0,7,44,Rural,HR Executive,123871,0 +110389,Male,32,Bachelors,12,16,63,89,83,0.0,3,82,Urban,ML Engineer,146293,1 +110390,Male,33,Bachelors,5,54,3,37,60,3.0,7,51,Semi-Urban,ML Engineer,49018,0 +110391,Female,23,Masters,19,38,67,51,83,4.0,3,64,Rural,Software Engineer,24986,0 +110392,Female,35,Diploma,7,19,37,3,38,4.0,1,74,Semi-Urban,Software Engineer,77176,0 +110393,Female,40,Diploma,17,93,55,33,28,0.0,5,98,Urban,Software Engineer,29308,1 +110394,Male,55,Bachelors,15,36,46,11,18,0.0,0,82,Semi-Urban,ML Engineer,95212,0 +110395,Female,44,High School,7,32,15,53,24,0.0,0,98,Urban,Software Engineer,54353,0 +110396,Male,33,Masters,7,24,33,6,27,7.0,4,92,Rural,Manager,142250,0 +110397,Female,46,Bachelors,13,77,9,32,33,7.0,2,68,Rural,Software Engineer,109642,0 +110398,Male,37,Diploma,6,41,30,14,5,2.0,7,71,Urban,Manager,35994,0 +110399,Male,27,Diploma,17,97,59,71,52,0.0,6,27,Urban,HR Executive,137959,1 +110400,Male,51,Bachelors,18,60,18,64,71,3.0,4,17,Urban,Data Analyst,27569,0 +110401,Male,23,High School,16,56,26,10,68,8.0,4,8,Urban,Software Engineer,60273,0 +110402,Female,44,High School,2,92,22,71,70,9.0,7,91,Urban,Manager,134219,1 +110403,Female,38,Masters,14,12,55,89,26,1.0,5,81,Semi-Urban,HR Executive,125931,0 +110404,Female,55,Masters,7,10,26,79,6,2.0,7,52,Semi-Urban,HR Executive,99942,0 +110405,Female,23,Bachelors,12,78,72,89,48,1.0,0,69,Urban,Manager,147140,1 +110406,Male,57,High School,9,8,32,68,58,1.0,2,44,Urban,ML Engineer,48633,0 +110407,Female,36,Masters,16,75,82,3,41,3.0,1,20,Urban,Data Analyst,110358,0 +110408,Female,23,Bachelors,2,63,65,40,44,1.0,7,20,Urban,Data Analyst,108181,0 +110409,Male,59,PhD,1,2,90,30,71,2.0,7,19,Urban,Manager,123462,0 +110410,Male,52,High School,17,98,48,7,82,9.0,6,95,Rural,Software Engineer,135551,1 +110411,Male,41,Diploma,10,18,26,67,82,6.0,3,49,Urban,Manager,80615,0 +110412,Male,31,Diploma,1,75,58,29,44,9.0,3,36,Urban,Manager,71349,0 +110413,Male,47,Bachelors,6,41,76,55,26,4.0,0,4,Semi-Urban,Data Analyst,65696,0 +110414,Female,51,Diploma,8,85,1,22,91,6.0,4,76,Rural,Data Analyst,94216,0 +110415,Female,22,PhD,8,13,97,67,21,0.0,6,62,Semi-Urban,ML Engineer,67674,0 +110416,Female,34,Diploma,18,85,40,8,3,9.0,6,65,Urban,ML Engineer,98133,0 +110417,Female,26,Bachelors,14,46,34,62,33,8.0,4,90,Urban,Data Analyst,119085,0 +110418,Female,36,Masters,15,19,89,25,21,6.0,4,16,Rural,HR Executive,128731,0 +110419,Male,55,Masters,6,80,62,45,81,3.0,1,75,Rural,Data Analyst,84731,1 +110420,Male,43,Bachelors,8,83,89,47,2,1.0,4,50,Urban,ML Engineer,25926,1 +110421,Female,46,Bachelors,6,86,50,14,69,7.0,6,27,Semi-Urban,ML Engineer,78923,0 +110422,Male,21,Bachelors,4,77,58,80,51,8.0,4,13,Urban,Data Analyst,117365,0 +110423,Female,42,Bachelors,19,20,67,55,17,5.0,3,39,Urban,Data Analyst,124242,0 +110424,Female,30,Bachelors,15,72,89,46,52,5.0,7,26,Urban,Software Engineer,131130,0 +110425,Female,33,Diploma,2,89,43,34,29,7.0,3,37,Semi-Urban,HR Executive,147727,0 +110426,Male,37,Bachelors,14,7,53,22,0,2.0,5,42,Semi-Urban,Software Engineer,71383,0 +110427,Female,21,Bachelors,6,25,27,43,35,0.0,7,46,Rural,ML Engineer,68297,0 +110428,Male,45,Diploma,10,52,70,30,16,3.0,3,82,Rural,HR Executive,88218,0 +110429,Female,34,Diploma,19,34,24,25,61,5.0,4,79,Urban,Data Analyst,124810,0 +110430,Male,46,Masters,11,2,5,28,25,4.0,3,90,Urban,Manager,55869,0 +110431,Male,45,Bachelors,17,15,30,43,95,8.0,6,79,Semi-Urban,Manager,98186,0 +110432,Female,39,High School,5,34,75,83,46,1.0,5,17,Urban,Software Engineer,121721,0 +110433,Female,52,Bachelors,1,32,30,7,36,1.0,2,70,Semi-Urban,ML Engineer,60028,0 +110434,Male,44,Bachelors,14,16,89,36,41,2.0,5,27,Urban,Software Engineer,138352,0 +110435,Male,48,Bachelors,3,60,75,87,20,5.0,1,43,Urban,HR Executive,138898,1 +110436,Female,53,High School,19,72,63,63,32,6.0,4,33,Urban,Manager,25513,0 +110437,Male,23,Bachelors,3,50,23,57,89,4.0,4,62,Urban,Manager,39282,0 +110438,Male,48,Bachelors,7,57,69,28,40,2.0,6,35,Rural,ML Engineer,99912,0 +110439,Male,35,Masters,5,77,49,16,19,4.0,2,34,Urban,Data Analyst,74498,0 +110440,Male,28,Masters,12,41,57,84,94,4.0,1,61,Urban,Data Analyst,37470,1 +110441,Female,59,Bachelors,11,77,45,52,81,6.0,3,93,Rural,Manager,80223,1 +110442,Male,30,Diploma,1,6,62,40,49,8.0,6,42,Rural,Software Engineer,95303,0 +110443,Male,48,Bachelors,10,20,70,30,51,9.0,4,16,Semi-Urban,ML Engineer,79258,0 +110444,Other,34,Bachelors,12,21,10,18,89,6.0,3,19,Urban,Data Analyst,130025,0 +110445,Male,45,Masters,13,39,6,56,85,0.0,6,80,Urban,HR Executive,42011,0 +110446,Male,21,Bachelors,4,81,30,35,8,1.0,6,37,Urban,Software Engineer,87970,0 +110447,Other,25,PhD,0,11,71,33,62,2.0,5,65,Rural,HR Executive,60139,0 +110448,Male,32,PhD,13,55,1,41,24,2.0,6,99,Urban,ML Engineer,99027,0 +110449,Male,36,Masters,13,21,39,93,19,9.0,0,24,Semi-Urban,ML Engineer,30909,0 +110450,Male,59,High School,7,72,81,53,77,1.0,1,48,Urban,ML Engineer,41328,1 +110451,Male,45,Masters,9,82,85,33,61,7.0,5,67,Urban,HR Executive,126480,1 +110452,Female,52,Masters,1,4,86,90,10,6.0,0,93,Urban,ML Engineer,88480,1 +110453,Male,46,Bachelors,13,92,2,29,26,4.0,1,53,Urban,HR Executive,102354,0 +110454,Female,43,Bachelors,0,60,93,57,10,4.0,3,16,Semi-Urban,Software Engineer,115890,0 +110455,Male,38,Bachelors,17,12,90,6,66,2.0,2,34,Urban,ML Engineer,70821,0 +110456,Female,32,Masters,4,53,47,27,15,6.0,4,69,Semi-Urban,HR Executive,104270,0 +110457,Female,41,Diploma,5,26,83,43,87,3.0,1,96,Urban,Data Analyst,81345,1 +110458,Female,41,High School,17,52,89,59,59,8.0,4,50,Urban,Data Analyst,67739,1 +110459,Male,37,Diploma,15,76,0,53,0,9.0,4,82,Urban,HR Executive,109310,0 +110460,Male,32,Diploma,13,36,71,81,6,4.0,2,7,Urban,HR Executive,61974,0 +110461,Male,33,Bachelors,6,58,5,71,35,0.0,6,94,Semi-Urban,Manager,149314,0 +110462,Female,46,Bachelors,10,26,88,41,90,2.0,7,61,Urban,ML Engineer,69806,0 +110463,Male,38,Bachelors,10,83,64,76,64,5.0,6,62,Semi-Urban,ML Engineer,39079,1 +110464,Male,24,PhD,13,65,85,79,24,1.0,5,73,Urban,HR Executive,122458,1 +110465,Female,44,Bachelors,11,18,6,95,92,4.0,3,6,Rural,ML Engineer,112297,0 +110466,Male,52,High School,19,43,13,94,27,4.0,0,87,Urban,HR Executive,76604,1 +110467,Male,26,Bachelors,17,21,45,87,6,3.0,6,41,Rural,Manager,109980,0 +110468,Male,31,High School,7,36,25,90,88,8.0,1,83,Rural,Manager,127880,0 +110469,Male,22,Bachelors,6,74,20,37,22,5.0,5,40,Rural,ML Engineer,101740,0 +110470,Female,28,Diploma,13,43,8,62,64,6.0,5,92,Urban,Software Engineer,122025,0 +110471,Female,35,PhD,9,40,63,35,5,3.0,2,6,Urban,Manager,24114,0 +110472,Male,23,Diploma,6,87,0,75,41,0.0,4,74,Urban,HR Executive,77622,1 +110473,Male,38,High School,14,82,60,33,48,2.0,7,3,Semi-Urban,Manager,74474,0 +110474,Female,38,Bachelors,17,84,33,89,73,2.0,0,9,Rural,Manager,39242,0 +110475,Male,45,Bachelors,18,36,84,8,48,6.0,5,95,Urban,Software Engineer,92203,0 +110476,Female,32,High School,6,66,32,46,64,3.0,6,43,Urban,Software Engineer,25871,0 +110477,Male,48,Bachelors,14,74,42,22,50,0.0,3,43,Rural,Software Engineer,63799,0 +110478,Male,56,Diploma,7,55,45,10,90,2.0,3,52,Semi-Urban,ML Engineer,30317,0 +110479,Other,47,High School,18,61,98,0,75,9.0,7,43,Semi-Urban,Software Engineer,99188,0 +110480,Female,52,Diploma,6,7,37,20,73,1.0,4,65,Urban,Data Analyst,22661,0 +110481,Male,59,Masters,1,76,90,87,45,8.0,4,90,Urban,ML Engineer,119643,1 +110482,Male,35,Bachelors,16,7,84,55,11,2.0,3,23,Rural,Data Analyst,73763,0 +110483,Female,50,Masters,3,36,13,38,35,1.0,3,83,Urban,Data Analyst,64203,0 +110484,Male,43,Diploma,14,76,43,7,70,9.0,5,36,Semi-Urban,ML Engineer,130011,0 +110485,Male,55,Bachelors,2,29,43,7,75,3.0,7,45,Semi-Urban,ML Engineer,108253,0 +110486,Male,55,High School,8,63,54,46,42,2.0,6,18,Urban,Data Analyst,85150,0 +110487,Male,46,Masters,10,68,25,7,84,1.0,2,9,Urban,Data Analyst,93093,0 +110488,Female,54,Bachelors,7,61,59,60,68,1.0,2,0,Semi-Urban,Data Analyst,28851,0 +110489,Male,24,Masters,0,98,41,46,93,1.0,7,71,Semi-Urban,ML Engineer,135180,1 +110490,Male,59,Masters,14,90,23,83,19,3.0,4,86,Semi-Urban,ML Engineer,63595,1 +110491,Male,25,Bachelors,8,44,60,92,41,5.0,1,51,Rural,Manager,101992,1 +110492,Male,40,Bachelors,13,92,52,50,90,8.0,4,78,Urban,Software Engineer,89479,1 +110493,Female,57,High School,9,95,91,30,42,8.0,5,83,Urban,HR Executive,84165,1 +110494,Male,51,PhD,13,59,90,29,64,0.0,0,66,Urban,Manager,39652,1 +110495,Male,57,Bachelors,15,76,33,27,56,1.0,5,49,Rural,ML Engineer,130829,0 +110496,Male,47,Diploma,3,30,80,25,6,4.0,6,72,Urban,Data Analyst,40463,0 +110497,Other,43,Masters,2,57,47,87,51,0.0,3,37,Semi-Urban,HR Executive,59109,0 +110498,Male,26,Masters,17,17,20,43,9,9.0,2,15,Urban,ML Engineer,56364,0 +110499,Male,26,Bachelors,4,5,97,38,46,3.0,5,59,Urban,ML Engineer,56807,0 +110500,Other,59,Bachelors,12,33,10,65,8,4.0,4,59,Semi-Urban,Data Analyst,78285,0 +110501,Female,44,High School,19,77,89,18,40,1.0,3,50,Semi-Urban,Manager,48336,0 +110502,Male,36,Masters,8,67,62,17,87,0.0,2,27,Rural,Manager,65198,0 +110503,Male,33,Bachelors,11,96,92,12,33,1.0,4,4,Urban,Software Engineer,43642,0 +110504,Male,27,Masters,13,64,82,82,15,9.0,1,15,Urban,Manager,136113,1 +110505,Male,27,Bachelors,5,79,21,59,24,3.0,4,62,Semi-Urban,Software Engineer,107984,0 +110506,Female,46,Masters,14,63,78,14,94,5.0,5,81,Urban,HR Executive,36598,0 +110507,Other,22,Diploma,5,70,19,61,15,5.0,3,88,Urban,Data Analyst,65111,0 +110508,Female,21,High School,10,47,45,65,84,0.0,3,22,Urban,ML Engineer,113525,0 +110509,Female,55,Bachelors,19,59,52,69,88,6.0,6,29,Semi-Urban,HR Executive,103819,0 +110510,Male,21,Bachelors,10,1,10,59,62,9.0,1,56,Urban,Manager,76089,0 +110511,Male,30,Bachelors,11,1,23,60,2,4.0,3,34,Urban,Manager,102368,0 +110512,Male,50,Diploma,7,42,74,54,24,6.0,1,14,Semi-Urban,Manager,66236,0 +110513,Male,31,Masters,12,70,85,29,76,4.0,0,40,Semi-Urban,Manager,92925,0 +110514,Female,38,Bachelors,8,49,33,21,94,0.0,2,35,Urban,ML Engineer,85532,0 +110515,Female,30,Diploma,12,18,90,59,70,3.0,5,18,Urban,Software Engineer,98082,0 +110516,Female,25,Bachelors,6,33,34,55,28,0.0,7,84,Urban,Data Analyst,127669,0 +110517,Male,59,Diploma,8,98,18,84,95,4.0,7,54,Urban,Software Engineer,149402,1 +110518,Male,28,Diploma,15,24,26,16,76,7.0,6,46,Semi-Urban,Data Analyst,127998,0 +110519,Male,51,Bachelors,17,39,15,80,7,2.0,7,58,Rural,Software Engineer,148600,0 +110520,Female,59,Bachelors,1,59,3,9,88,8.0,6,15,Urban,HR Executive,78652,0 +110521,Female,22,Bachelors,4,30,12,15,84,7.0,4,14,Semi-Urban,HR Executive,86596,0 +110522,Male,21,Bachelors,0,62,42,19,77,5.0,0,80,Urban,Software Engineer,104489,0 +110523,Male,22,Bachelors,15,46,11,38,7,1.0,2,71,Urban,Manager,123126,0 +110524,Male,44,Masters,0,90,82,11,98,7.0,0,31,Urban,Manager,27856,0 +110525,Male,24,High School,11,18,59,19,79,3.0,0,76,Urban,Manager,38636,0 +110526,Male,54,Bachelors,4,9,24,13,20,0.0,3,9,Semi-Urban,ML Engineer,85705,0 +110527,Male,55,Masters,19,66,46,25,85,1.0,3,85,Urban,ML Engineer,76910,0 +110528,Male,57,Bachelors,7,1,24,65,69,2.0,5,28,Semi-Urban,HR Executive,127215,0 +110529,Male,24,Bachelors,1,48,71,20,30,9.0,5,28,Urban,ML Engineer,149547,0 +110530,Male,48,Masters,6,30,93,16,73,2.0,7,44,Urban,Data Analyst,102168,0 +110531,Male,52,Bachelors,9,7,87,84,40,7.0,1,16,Semi-Urban,HR Executive,111771,0 +110532,Male,58,High School,6,49,55,47,94,9.0,7,4,Rural,Manager,77688,0 +110533,Male,51,PhD,15,16,95,96,46,6.0,3,2,Rural,Software Engineer,132849,0 +110534,Male,55,Diploma,12,51,82,22,37,1.0,6,4,Urban,Software Engineer,117716,0 +110535,Male,38,Masters,9,97,99,32,73,7.0,5,62,Urban,Data Analyst,106950,1 +110536,Male,38,Bachelors,10,5,65,90,11,0.0,4,73,Rural,Manager,58411,0 +110537,Male,27,Diploma,17,66,92,45,23,1.0,4,0,Urban,Manager,143539,0 +110538,Male,34,High School,15,2,14,8,86,9.0,4,95,Urban,Manager,62032,0 +110539,Female,34,Masters,4,64,63,84,66,1.0,0,85,Urban,ML Engineer,56151,1 +110540,Female,52,Diploma,12,23,2,17,56,2.0,6,53,Urban,Software Engineer,100092,0 +110541,Female,47,Bachelors,6,79,23,26,13,2.0,4,17,Urban,HR Executive,51545,0 +110542,Male,45,Bachelors,13,44,26,6,1,2.0,3,68,Urban,Manager,110018,0 +110543,Female,34,Masters,14,32,41,46,17,7.0,2,50,Urban,Data Analyst,140338,0 +110544,Other,31,Masters,12,27,20,69,8,8.0,7,43,Semi-Urban,Manager,107983,0 +110545,Other,52,Bachelors,14,49,59,13,58,6.0,6,91,Semi-Urban,HR Executive,104868,0 +110546,Male,29,Bachelors,19,33,88,33,27,4.0,4,85,Urban,Manager,52291,1 +110547,Female,51,Masters,18,99,46,20,38,5.0,6,53,Semi-Urban,Manager,74175,0 +110548,Male,50,Bachelors,18,37,93,74,82,7.0,4,55,Rural,ML Engineer,136259,1 +110549,Male,31,Masters,5,12,46,46,72,7.0,0,68,Urban,Manager,42206,0 +110550,Female,24,Masters,12,98,35,49,36,5.0,5,48,Urban,ML Engineer,97534,0 +110551,Female,49,Bachelors,3,91,49,47,17,9.0,3,63,Rural,Manager,45658,1 +110552,Female,44,Bachelors,1,70,94,27,34,4.0,5,2,Rural,HR Executive,99850,0 +110553,Other,38,High School,8,23,91,24,70,7.0,7,26,Urban,Software Engineer,146955,0 +110554,Female,40,Masters,10,71,29,77,45,9.0,5,3,Urban,ML Engineer,109130,0 +110555,Male,34,Masters,4,63,33,37,64,3.0,6,70,Rural,Software Engineer,92409,0 +110556,Male,36,Bachelors,18,28,4,21,80,4.0,3,45,Urban,Manager,73129,0 +110557,Male,36,Bachelors,0,64,7,91,10,5.0,6,87,Semi-Urban,HR Executive,91808,1 +110558,Female,59,Bachelors,0,27,72,13,40,5.0,4,58,Urban,Manager,118786,0 +110559,Male,36,PhD,4,57,6,0,99,8.0,6,30,Urban,Software Engineer,32167,0 +110560,Female,34,PhD,16,39,6,4,56,6.0,0,22,Semi-Urban,Software Engineer,57818,0 +110561,Other,30,Diploma,0,56,0,90,33,1.0,0,66,Urban,Data Analyst,118054,0 +110562,Male,47,Bachelors,19,97,59,41,67,4.0,0,62,Semi-Urban,Software Engineer,113772,1 +110563,Male,35,Diploma,0,24,48,88,89,6.0,4,62,Semi-Urban,ML Engineer,26530,0 +110564,Male,45,Bachelors,13,68,9,21,75,2.0,4,87,Semi-Urban,Data Analyst,129420,0 +110565,Female,32,Diploma,7,26,67,59,69,6.0,4,26,Semi-Urban,Manager,91587,0 +110566,Female,28,Masters,16,47,84,33,52,2.0,1,57,Rural,ML Engineer,122959,0 +110567,Female,47,Bachelors,11,70,67,30,57,2.0,7,30,Urban,HR Executive,131953,0 +110568,Female,48,Bachelors,1,48,46,95,29,7.0,6,75,Semi-Urban,Manager,25328,1 +110569,Female,30,Bachelors,6,50,16,4,67,0.0,7,23,Semi-Urban,Data Analyst,30846,0 +110570,Male,55,Masters,14,6,70,28,74,5.0,3,66,Semi-Urban,ML Engineer,115223,0 +110571,Male,26,Masters,9,47,12,62,18,3.0,0,9,Urban,Manager,85324,0 +110572,Male,57,Masters,15,7,61,24,3,1.0,3,51,Urban,Manager,141023,0 +110573,Female,25,Bachelors,19,50,10,53,45,9.0,5,52,Urban,Manager,46274,0 +110574,Female,59,Diploma,18,62,96,81,73,6.0,1,50,Urban,Data Analyst,91148,1 +110575,Male,57,Bachelors,9,5,74,28,28,0.0,3,73,Urban,HR Executive,49102,0 +110576,Male,32,Bachelors,11,54,64,72,13,2.0,7,20,Semi-Urban,Software Engineer,37098,0 +110577,Female,43,Bachelors,14,20,86,47,81,7.0,7,33,Urban,ML Engineer,88169,0 +110578,Male,28,PhD,17,98,51,64,89,9.0,2,35,Semi-Urban,Data Analyst,61890,1 +110579,Female,50,Bachelors,5,33,97,40,2,3.0,6,66,Urban,Software Engineer,57947,0 +110580,Male,50,Masters,15,32,7,17,66,9.0,4,72,Urban,HR Executive,85006,0 +110581,Male,22,Bachelors,17,82,72,0,91,0.0,1,0,Urban,Data Analyst,135371,0 +110582,Female,51,Masters,3,49,66,2,70,4.0,5,52,Semi-Urban,ML Engineer,114900,0 +110583,Female,54,PhD,0,81,50,55,87,0.0,3,93,Urban,Data Analyst,129121,1 +110584,Male,31,Bachelors,14,11,72,84,11,1.0,0,99,Semi-Urban,ML Engineer,112998,1 +110585,Male,34,High School,3,85,99,26,12,6.0,3,52,Semi-Urban,Software Engineer,72824,1 +110586,Female,45,Bachelors,3,96,27,10,71,4.0,4,69,Urban,ML Engineer,108663,0 +110587,Male,28,Diploma,6,10,40,29,40,6.0,4,2,Urban,HR Executive,97285,0 +110588,Male,40,PhD,11,89,79,17,22,8.0,2,42,Urban,ML Engineer,113055,0 +110589,Male,42,Masters,3,90,33,53,17,2.0,1,29,Rural,HR Executive,41999,0 +110590,Male,35,Diploma,8,23,17,17,24,2.0,6,81,Semi-Urban,Software Engineer,111804,0 +110591,Other,30,Bachelors,0,82,73,37,65,1.0,4,25,Semi-Urban,Manager,92131,0 +110592,Female,25,High School,11,15,58,67,22,9.0,4,50,Urban,Software Engineer,47949,0 +110593,Male,46,Diploma,12,69,47,71,78,5.0,2,74,Urban,Software Engineer,113727,1 +110594,Female,48,Bachelors,5,68,87,14,64,5.0,6,43,Urban,Manager,122886,0 +110595,Female,57,High School,11,48,79,74,58,5.0,1,38,Urban,Software Engineer,86561,0 +110596,Other,23,Bachelors,4,47,18,79,49,9.0,5,26,Urban,Data Analyst,76912,0 +110597,Male,23,Bachelors,13,27,58,85,13,8.0,0,11,Semi-Urban,ML Engineer,97660,0 +110598,Male,29,Diploma,4,27,19,4,20,6.0,3,43,Urban,ML Engineer,96867,0 +110599,Female,30,Bachelors,16,13,75,10,49,1.0,1,44,Rural,Manager,32493,0 +110600,Female,42,Masters,11,10,86,84,27,7.0,1,53,Urban,ML Engineer,67935,0 +110601,Female,21,Bachelors,15,86,7,36,47,6.0,2,72,Urban,Manager,60908,0 +110602,Male,29,High School,18,14,88,87,79,1.0,2,6,Semi-Urban,Manager,82955,0 +110603,Female,37,Diploma,9,3,14,42,34,0.0,4,25,Urban,ML Engineer,47510,0 +110604,Female,28,Masters,10,56,85,77,56,5.0,2,29,Semi-Urban,Data Analyst,140893,1 +110605,Male,53,Diploma,7,47,79,11,97,9.0,4,79,Rural,Manager,133871,0 +110606,Male,33,Bachelors,9,0,3,12,85,7.0,3,49,Urban,Manager,97296,0 +110607,Male,32,Bachelors,14,74,26,56,19,1.0,1,78,Urban,Data Analyst,31749,0 +110608,Male,23,Bachelors,0,45,94,24,99,0.0,4,56,Urban,Software Engineer,30396,0 +110609,Female,25,Diploma,18,9,8,61,96,4.0,3,41,Urban,ML Engineer,66713,0 +110610,Male,33,High School,7,28,67,89,53,5.0,3,50,Rural,ML Engineer,133946,0 +110611,Male,36,Diploma,7,68,26,3,4,1.0,3,81,Urban,Data Analyst,137369,0 +110612,Female,49,High School,10,71,73,15,17,4.0,0,19,Urban,Data Analyst,103069,0 +110613,Female,53,Masters,2,44,43,63,43,6.0,3,3,Rural,Software Engineer,75101,0 +110614,Male,23,Diploma,1,65,92,59,12,9.0,6,45,Urban,HR Executive,105646,1 +110615,Female,45,Bachelors,10,25,7,83,76,9.0,4,34,Urban,Software Engineer,78084,0 +110616,Male,26,Diploma,4,9,31,67,92,3.0,5,28,Semi-Urban,Manager,67381,0 +110617,Other,21,Diploma,8,95,53,59,19,1.0,6,64,Urban,ML Engineer,44938,1 +110618,Male,48,Masters,7,7,17,13,89,6.0,2,66,Urban,HR Executive,90733,0 +110619,Female,50,Bachelors,19,12,79,6,33,8.0,7,79,Semi-Urban,ML Engineer,58683,0 +110620,Other,31,Diploma,0,53,14,89,84,1.0,7,56,Urban,Software Engineer,140736,0 +110621,Male,27,Diploma,9,76,84,91,25,0.0,2,65,Semi-Urban,ML Engineer,147835,1 +110622,Female,46,Bachelors,12,85,32,74,53,6.0,0,62,Rural,Data Analyst,23956,1 +110623,Female,45,Diploma,9,22,33,36,55,7.0,7,46,Semi-Urban,Data Analyst,55058,0 +110624,Other,36,High School,12,33,31,59,90,7.0,1,31,Rural,Manager,111332,0 +110625,Female,45,Diploma,15,39,71,81,72,1.0,5,75,Semi-Urban,Data Analyst,145287,1 +110626,Female,26,Bachelors,7,61,83,8,88,6.0,2,39,Urban,Software Engineer,147351,0 +110627,Male,44,Bachelors,15,67,67,84,49,1.0,1,64,Semi-Urban,Data Analyst,79297,1 +110628,Male,37,High School,17,49,62,24,41,9.0,1,38,Rural,Manager,142358,0 +110629,Male,55,PhD,13,83,73,35,35,5.0,3,4,Semi-Urban,ML Engineer,66037,0 +110630,Male,35,Diploma,4,96,7,19,59,4.0,6,79,Rural,HR Executive,57467,0 +110631,Male,33,Bachelors,16,87,75,33,57,6.0,7,85,Urban,Data Analyst,48809,1 +110632,Female,49,Diploma,6,15,69,59,37,9.0,1,12,Urban,Software Engineer,143800,0 +110633,Male,56,Bachelors,4,50,28,38,45,9.0,6,81,Rural,ML Engineer,85123,0 +110634,Male,47,Bachelors,14,91,78,55,38,4.0,5,39,Urban,Manager,108179,1 +110635,Female,30,Bachelors,8,87,67,28,1,4.0,2,27,Semi-Urban,Data Analyst,118369,0 +110636,Female,28,Bachelors,11,31,42,59,83,9.0,1,43,Urban,Manager,33085,0 +110637,Male,52,Bachelors,3,77,92,84,46,6.0,6,90,Rural,Software Engineer,31214,1 +110638,Female,59,Masters,14,52,89,61,47,0.0,1,47,Urban,Manager,138123,1 +110639,Female,28,Diploma,17,99,35,3,51,2.0,0,58,Urban,ML Engineer,119589,0 +110640,Female,59,High School,3,40,67,18,14,6.0,2,78,Urban,Software Engineer,69498,0 +110641,Male,30,Masters,10,16,59,50,76,2.0,3,15,Rural,Manager,82171,0 +110642,Female,52,Bachelors,2,71,3,0,1,2.0,7,83,Urban,Data Analyst,67913,0 +110643,Male,26,Bachelors,5,58,48,87,74,8.0,2,30,Rural,ML Engineer,64652,0 +110644,Female,42,High School,1,72,0,80,95,0.0,3,40,Urban,Software Engineer,120264,0 +110645,Female,21,Bachelors,19,67,75,41,94,3.0,6,83,Semi-Urban,ML Engineer,76943,1 +110646,Female,37,Bachelors,16,40,24,73,27,0.0,1,93,Urban,ML Engineer,55791,0 +110647,Female,44,Masters,10,63,81,34,74,7.0,7,27,Semi-Urban,Software Engineer,88809,0 +110648,Male,52,Diploma,18,81,36,48,40,4.0,0,76,Urban,HR Executive,146377,1 +110649,Male,38,Bachelors,4,98,31,12,52,9.0,1,49,Semi-Urban,ML Engineer,102969,0 +110650,Male,27,High School,14,58,71,42,71,5.0,3,48,Semi-Urban,HR Executive,141362,0 +110651,Female,21,Bachelors,8,16,67,67,39,1.0,5,70,Rural,HR Executive,148824,0 +110652,Female,33,Bachelors,10,17,57,84,44,2.0,1,4,Semi-Urban,Data Analyst,87322,0 +110653,Female,42,High School,18,43,74,44,52,7.0,3,27,Semi-Urban,Manager,27558,0 +110654,Male,33,Masters,11,64,75,88,20,2.0,2,4,Urban,HR Executive,109532,0 +110655,Male,57,Bachelors,18,26,71,23,50,5.0,7,70,Urban,Software Engineer,53551,0 +110656,Male,23,High School,2,75,49,27,82,2.0,1,1,Urban,Software Engineer,130545,0 +110657,Male,34,Bachelors,16,8,97,62,42,7.0,1,14,Rural,Manager,40559,0 +110658,Female,32,Masters,9,79,68,0,5,6.0,7,54,Urban,Data Analyst,52518,0 +110659,Female,48,High School,4,22,99,57,55,2.0,1,73,Rural,Data Analyst,44776,1 +110660,Female,46,Diploma,12,17,17,5,77,8.0,2,85,Urban,Software Engineer,28768,0 +110661,Male,39,Masters,15,20,44,3,89,0.0,4,58,Urban,Manager,99910,0 +110662,Male,34,Bachelors,11,15,35,56,65,7.0,5,42,Rural,Data Analyst,105450,0 +110663,Male,43,Diploma,16,86,86,22,85,9.0,1,84,Semi-Urban,HR Executive,112962,1 +110664,Male,36,High School,13,95,84,65,82,3.0,4,19,Urban,Software Engineer,114685,1 +110665,Male,22,Bachelors,1,77,19,24,77,5.0,0,32,Urban,HR Executive,48444,0 +110666,Female,24,High School,17,59,91,28,16,3.0,6,59,Urban,Software Engineer,58197,0 +110667,Male,29,High School,15,66,14,44,57,6.0,3,69,Rural,HR Executive,111728,0 +110668,Male,40,Bachelors,9,4,43,49,77,2.0,6,15,Urban,HR Executive,36297,0 +110669,Other,47,High School,14,58,32,90,79,0.0,1,81,Semi-Urban,Software Engineer,46596,1 +110670,Other,46,Bachelors,17,19,2,54,68,4.0,0,20,Urban,Data Analyst,96999,0 +110671,Female,21,Diploma,11,91,33,21,34,5.0,2,57,Urban,Manager,96752,0 +110672,Male,40,Bachelors,10,20,22,35,9,2.0,5,79,Rural,ML Engineer,142090,0 +110673,Male,32,Bachelors,18,48,43,51,50,4.0,4,55,Urban,HR Executive,114540,0 +110674,Male,59,PhD,3,38,84,10,50,1.0,7,54,Urban,Data Analyst,87544,0 +110675,Male,57,PhD,10,93,92,50,35,8.0,2,44,Semi-Urban,Manager,22933,1 +110676,Male,57,Bachelors,17,23,39,66,70,0.0,0,58,Rural,HR Executive,128049,0 +110677,Male,50,Diploma,7,12,32,66,30,7.0,5,77,Urban,Software Engineer,124787,0 +110678,Female,46,High School,18,26,36,50,68,4.0,0,6,Urban,Data Analyst,61401,0 +110679,Female,52,Diploma,3,45,15,19,49,3.0,6,44,Semi-Urban,ML Engineer,109249,0 +110680,Male,49,Bachelors,1,44,68,86,9,6.0,6,7,Rural,Data Analyst,124560,0 +110681,Female,48,Bachelors,6,15,99,42,0,4.0,1,46,Urban,ML Engineer,108619,0 +110682,Male,30,Masters,16,47,86,8,85,6.0,5,40,Semi-Urban,ML Engineer,27351,0 +110683,Female,27,Bachelors,19,80,84,48,8,6.0,6,57,Urban,HR Executive,90092,1 +110684,Male,33,Bachelors,16,44,72,72,2,2.0,3,42,Urban,Data Analyst,105934,0 +110685,Female,22,Bachelors,11,1,72,43,66,4.0,3,85,Urban,Data Analyst,31351,0 +110686,Male,42,Diploma,1,13,76,86,76,0.0,4,28,Rural,ML Engineer,82892,0 +110687,Male,42,PhD,0,81,72,35,62,1.0,7,4,Urban,Software Engineer,20858,0 +110688,Female,47,Bachelors,16,60,55,15,43,1.0,3,54,Urban,Software Engineer,140297,0 +110689,Male,50,Bachelors,6,52,1,1,63,3.0,4,18,Urban,Software Engineer,116303,0 +110690,Male,46,Bachelors,18,0,58,13,73,5.0,3,13,Urban,ML Engineer,117718,0 +110691,Male,50,Bachelors,11,32,32,75,1,0.0,5,41,Urban,Software Engineer,32244,0 +110692,Female,28,High School,16,26,99,68,66,6.0,5,41,Semi-Urban,Software Engineer,82040,0 +110693,Female,45,Bachelors,15,62,41,27,81,6.0,1,62,Urban,Data Analyst,30233,0 +110694,Female,35,Bachelors,9,38,39,82,85,2.0,0,5,Rural,ML Engineer,48401,0 +110695,Female,35,Diploma,14,24,7,84,74,7.0,6,27,Rural,ML Engineer,97297,0 +110696,Other,54,Masters,5,57,51,14,24,7.0,6,38,Semi-Urban,Data Analyst,78507,0 +110697,Other,21,Masters,7,90,48,72,22,2.0,4,67,Urban,Software Engineer,94990,1 +110698,Male,21,Bachelors,3,29,90,70,55,8.0,5,79,Urban,Data Analyst,123602,1 +110699,Female,38,Bachelors,6,46,63,19,67,9.0,4,32,Semi-Urban,ML Engineer,42308,0 +110700,Female,57,High School,6,68,49,73,90,5.0,3,97,Urban,Data Analyst,123094,1 +110701,Male,27,Bachelors,4,30,9,10,78,1.0,7,47,Urban,Manager,130327,0 +110702,Female,55,Masters,3,86,44,98,42,2.0,5,77,Urban,ML Engineer,102908,1 +110703,Female,23,High School,16,80,45,23,70,4.0,6,34,Urban,Software Engineer,66419,0 +110704,Male,23,Bachelors,8,45,30,57,71,7.0,3,58,Rural,Manager,139987,0 +110705,Male,49,Masters,17,26,54,45,54,0.0,5,73,Semi-Urban,Manager,36020,0 +110706,Male,53,Diploma,10,47,28,35,16,7.0,5,25,Urban,Manager,123390,0 +110707,Female,40,Bachelors,11,61,48,52,23,5.0,7,78,Rural,ML Engineer,109243,0 +110708,Male,37,Diploma,18,27,76,47,97,2.0,2,30,Urban,Software Engineer,128463,0 +110709,Female,26,Masters,13,6,17,5,20,3.0,3,22,Urban,Data Analyst,73865,0 +110710,Female,25,Bachelors,14,65,9,99,19,3.0,2,68,Semi-Urban,Manager,73614,1 +110711,Male,46,Bachelors,6,82,76,19,88,3.0,3,30,Rural,HR Executive,148987,0 +110712,Female,47,High School,9,89,99,51,10,2.0,7,13,Urban,ML Engineer,76015,1 +110713,Male,41,Bachelors,17,41,95,14,8,3.0,7,62,Semi-Urban,Software Engineer,66986,0 +110714,Female,55,Bachelors,12,11,0,65,13,6.0,7,1,Semi-Urban,Data Analyst,21661,0 +110715,Male,48,Bachelors,8,36,28,31,22,1.0,3,20,Urban,HR Executive,27396,0 +110716,Male,36,Diploma,5,94,80,83,30,4.0,4,36,Semi-Urban,ML Engineer,121704,1 +110717,Male,44,Diploma,16,13,99,4,94,0.0,6,88,Rural,Data Analyst,62720,0 +110718,Female,49,Masters,5,64,91,85,14,6.0,4,54,Urban,HR Executive,33138,1 +110719,Female,54,Bachelors,19,46,37,5,25,7.0,2,96,Semi-Urban,ML Engineer,128062,0 +110720,Male,23,Masters,1,17,81,6,71,9.0,7,48,Urban,HR Executive,31008,0 +110721,Male,30,Masters,0,37,62,85,86,0.0,5,55,Urban,ML Engineer,96332,1 +110722,Female,40,Masters,7,81,14,55,93,4.0,5,12,Urban,Software Engineer,112536,0 +110723,Male,58,Bachelors,0,83,6,97,77,0.0,1,90,Urban,Data Analyst,53290,1 +110724,Male,34,Bachelors,1,70,90,3,63,5.0,2,89,Rural,ML Engineer,73816,1 +110725,Other,55,Masters,4,86,93,84,55,4.0,2,9,Urban,Software Engineer,103787,1 +110726,Female,36,Bachelors,11,97,55,90,0,5.0,5,47,Urban,Software Engineer,34576,1 +110727,Male,25,Diploma,19,4,80,34,19,3.0,1,0,Rural,Software Engineer,94586,0 +110728,Male,27,High School,4,87,46,32,48,2.0,2,3,Urban,Software Engineer,44148,0 +110729,Male,41,Masters,18,12,95,56,55,5.0,2,3,Rural,Manager,85727,0 +110730,Male,34,Diploma,7,71,38,16,3,6.0,3,70,Urban,HR Executive,73597,0 +110731,Male,39,Masters,13,61,3,92,72,9.0,2,92,Urban,HR Executive,83632,1 +110732,Male,49,High School,13,73,32,33,62,7.0,2,19,Urban,Manager,40610,0 +110733,Other,31,Bachelors,0,68,37,14,86,1.0,7,61,Urban,Software Engineer,64801,0 +110734,Male,45,Diploma,17,10,61,80,35,2.0,7,80,Semi-Urban,Data Analyst,20012,0 +110735,Female,54,Bachelors,7,45,25,48,76,3.0,2,50,Semi-Urban,HR Executive,44364,0 +110736,Female,23,Bachelors,15,89,19,27,71,5.0,5,50,Rural,HR Executive,53846,0 +110737,Female,21,High School,9,39,75,78,26,0.0,6,14,Urban,Data Analyst,83632,0 +110738,Male,23,Bachelors,16,16,84,84,89,1.0,1,81,Urban,Software Engineer,64733,1 +110739,Male,25,Diploma,12,73,72,94,47,5.0,2,81,Urban,Manager,95451,1 +110740,Female,26,Diploma,7,16,41,8,74,8.0,2,80,Urban,ML Engineer,57038,0 +110741,Female,52,Bachelors,6,97,93,22,37,1.0,2,18,Urban,ML Engineer,97093,0 +110742,Female,48,Bachelors,10,6,17,34,54,5.0,4,97,Urban,HR Executive,131062,0 +110743,Male,23,Masters,5,77,87,32,28,6.0,2,64,Urban,HR Executive,50932,1 +110744,Female,49,Diploma,14,45,2,94,89,8.0,0,83,Rural,HR Executive,24164,0 +110745,Male,36,Bachelors,18,36,73,62,82,6.0,6,22,Semi-Urban,HR Executive,64981,0 +110746,Male,50,Bachelors,9,52,86,70,77,6.0,0,94,Rural,Manager,33444,1 +110747,Male,39,Bachelors,8,11,33,64,7,5.0,1,12,Urban,HR Executive,99156,0 +110748,Female,40,Bachelors,5,80,59,20,73,8.0,7,88,Semi-Urban,HR Executive,85083,1 +110749,Male,56,Bachelors,12,65,68,23,80,1.0,0,89,Rural,Software Engineer,24183,1 +110750,Female,50,Bachelors,7,38,58,71,33,7.0,2,13,Urban,Software Engineer,128678,0 +110751,Female,52,High School,2,72,75,19,45,2.0,4,17,Urban,Data Analyst,21419,0 +110752,Female,36,Bachelors,7,25,77,94,12,1.0,2,17,Urban,ML Engineer,90174,0 +110753,Male,43,Bachelors,0,69,78,87,92,5.0,1,6,Rural,Software Engineer,74341,1 +110754,Female,32,Masters,7,96,11,46,14,9.0,7,33,Urban,ML Engineer,100553,0 +110755,Female,36,Bachelors,6,9,9,14,59,5.0,2,75,Rural,Manager,99650,0 +110756,Male,41,High School,2,20,93,95,81,6.0,1,11,Rural,ML Engineer,113387,0 +110757,Female,56,Bachelors,0,8,27,70,15,6.0,4,92,Semi-Urban,Manager,103337,0 +110758,Male,32,High School,3,68,79,14,99,9.0,4,15,Rural,Software Engineer,89760,0 +110759,Female,57,Bachelors,13,96,51,51,40,9.0,4,34,Semi-Urban,Manager,22046,0 +110760,Female,30,Masters,9,21,53,88,55,4.0,7,20,Semi-Urban,ML Engineer,46469,0 +110761,Male,40,Bachelors,10,35,51,65,28,0.0,2,83,Semi-Urban,Software Engineer,128653,0 +110762,Male,49,Diploma,5,55,36,99,11,5.0,3,4,Urban,ML Engineer,146574,0 +110763,Female,38,Bachelors,4,38,84,31,73,4.0,2,26,Urban,Data Analyst,133320,0 +110764,Female,53,Bachelors,8,66,23,43,70,0.0,4,57,Urban,ML Engineer,31473,0 +110765,Male,27,Bachelors,10,5,29,72,59,0.0,7,49,Urban,Data Analyst,21779,0 +110766,Male,30,Bachelors,8,17,9,87,35,1.0,6,36,Semi-Urban,Software Engineer,97292,0 +110767,Male,38,High School,0,91,66,57,99,7.0,7,89,Urban,Data Analyst,139314,1 +110768,Male,56,Bachelors,11,34,45,81,5,9.0,6,48,Urban,Data Analyst,80606,0 +110769,Female,57,Bachelors,16,37,65,58,68,7.0,3,43,Urban,Software Engineer,30263,0 +110770,Male,44,Bachelors,0,0,43,1,78,4.0,3,65,Urban,Software Engineer,22481,0 +110771,Female,28,High School,0,11,34,69,82,1.0,2,46,Urban,Data Analyst,110907,0 +110772,Female,48,Diploma,14,62,88,86,23,3.0,4,61,Rural,HR Executive,113137,1 +110773,Male,40,PhD,0,55,78,20,28,3.0,3,44,Urban,HR Executive,98428,0 +110774,Female,41,Masters,17,70,27,89,64,5.0,1,17,Rural,ML Engineer,124440,0 +110775,Male,53,High School,11,86,29,65,58,7.0,5,35,Rural,ML Engineer,37379,0 +110776,Male,40,Bachelors,8,96,72,18,36,3.0,3,72,Rural,ML Engineer,57014,1 +110777,Male,51,Bachelors,0,34,11,21,15,6.0,4,26,Rural,Software Engineer,80621,0 +110778,Male,23,Bachelors,10,31,4,89,30,5.0,2,53,Urban,Data Analyst,111079,0 +110779,Female,37,High School,13,3,46,17,6,3.0,6,92,Urban,ML Engineer,74592,0 +110780,Female,52,High School,16,44,23,28,40,8.0,0,48,Urban,Manager,72748,0 +110781,Female,44,Bachelors,11,94,19,28,60,8.0,0,92,Semi-Urban,HR Executive,55744,0 +110782,Female,56,Bachelors,12,9,52,19,7,5.0,0,98,Rural,Data Analyst,134289,0 +110783,Male,59,Diploma,10,65,43,16,61,5.0,3,52,Urban,Manager,138973,0 +110784,Male,35,Bachelors,3,7,71,53,97,9.0,2,20,Urban,ML Engineer,141447,0 +110785,Male,32,Bachelors,3,12,83,78,54,7.0,4,86,Rural,Software Engineer,133788,1 +110786,Female,29,Bachelors,10,92,79,52,78,5.0,7,18,Semi-Urban,HR Executive,33431,1 +110787,Male,51,Bachelors,5,90,34,21,15,2.0,3,86,Urban,Data Analyst,100801,0 +110788,Male,23,Diploma,16,69,30,88,31,7.0,3,6,Urban,HR Executive,95028,0 +110789,Female,33,Masters,18,86,0,63,83,5.0,0,56,Semi-Urban,Software Engineer,89189,0 +110790,Male,41,Bachelors,10,48,77,16,25,6.0,6,3,Urban,Manager,36756,0 +110791,Male,52,Diploma,2,71,70,93,3,5.0,0,58,Urban,HR Executive,118525,1 +110792,Female,40,Bachelors,3,73,1,52,88,4.0,7,52,Urban,Software Engineer,56395,0 +110793,Male,26,Bachelors,19,23,79,81,2,9.0,5,24,Semi-Urban,Data Analyst,74085,0 +110794,Male,51,Bachelors,14,45,21,58,35,3.0,5,93,Semi-Urban,ML Engineer,52490,0 +110795,Female,49,Bachelors,15,2,35,76,31,4.0,5,68,Urban,Manager,119411,0 +110796,Female,49,Masters,19,30,75,96,39,9.0,6,18,Urban,Software Engineer,146783,0 +110797,Male,51,Masters,11,83,3,36,31,3.0,4,84,Urban,Software Engineer,120251,0 +110798,Male,21,Masters,15,72,2,2,5,3.0,7,69,Urban,HR Executive,20111,0 +110799,Male,25,High School,5,49,81,47,94,2.0,6,3,Semi-Urban,HR Executive,102137,0 +110800,Female,40,Diploma,14,75,61,52,64,2.0,0,81,Urban,HR Executive,52620,1 +110801,Male,23,Diploma,6,54,43,95,62,5.0,1,90,Semi-Urban,HR Executive,24317,1 +110802,Female,27,Bachelors,12,16,23,68,84,5.0,1,68,Urban,Software Engineer,110034,0 +110803,Female,27,Bachelors,16,34,71,94,82,8.0,7,96,Urban,Manager,57479,1 +110804,Male,44,Bachelors,7,57,39,55,44,9.0,1,82,Urban,ML Engineer,112436,0 +110805,Female,25,Bachelors,5,17,14,1,58,7.0,6,7,Urban,Manager,24776,0 +110806,Male,29,Masters,3,22,79,71,23,9.0,6,36,Urban,ML Engineer,99203,0 +110807,Male,59,High School,18,68,81,56,51,2.0,7,58,Urban,Software Engineer,75862,1 +110808,Male,52,Bachelors,18,71,88,7,65,3.0,6,93,Urban,Software Engineer,108395,1 +110809,Female,41,Masters,12,37,76,68,77,7.0,6,58,Urban,Software Engineer,114507,0 +110810,Female,35,Diploma,10,72,80,79,82,1.0,4,80,Urban,ML Engineer,20263,1 +110811,Female,47,Diploma,8,51,89,46,75,0.0,2,21,Urban,Software Engineer,68042,0 +110812,Female,42,High School,17,14,8,12,15,3.0,5,67,Rural,Manager,95301,0 +110813,Male,56,Diploma,6,16,30,50,21,4.0,3,29,Rural,Manager,112022,0 +110814,Female,57,Bachelors,4,68,92,57,11,1.0,2,63,Rural,ML Engineer,46458,1 +110815,Male,40,Bachelors,0,48,99,80,48,0.0,1,83,Urban,Data Analyst,88255,1 +110816,Female,48,Bachelors,5,60,86,79,7,2.0,5,59,Semi-Urban,Data Analyst,43873,1 +110817,Male,50,Masters,3,70,57,87,29,7.0,4,49,Urban,Manager,148641,1 +110818,Male,56,Bachelors,16,44,88,79,98,4.0,6,11,Rural,Software Engineer,108843,0 +110819,Male,22,PhD,3,41,35,74,74,1.0,6,55,Urban,HR Executive,23408,0 +110820,Male,34,Diploma,7,48,18,63,41,8.0,3,24,Semi-Urban,Software Engineer,55836,0 +110821,Female,23,Bachelors,8,72,90,40,65,5.0,6,28,Semi-Urban,Software Engineer,32249,0 +110822,Female,32,Masters,10,32,81,60,16,5.0,2,95,Urban,HR Executive,118916,1 +110823,Female,43,Masters,13,74,40,35,9,7.0,7,51,Semi-Urban,Manager,22561,0 +110824,Female,49,Diploma,18,52,18,46,64,5.0,6,48,Urban,Manager,79930,0 +110825,Male,45,PhD,2,26,20,8,52,3.0,2,29,Semi-Urban,ML Engineer,25948,0 +110826,Male,25,Diploma,0,61,54,77,23,2.0,5,12,Urban,Software Engineer,46712,0 +110827,Male,50,Masters,2,67,33,66,84,0.0,1,50,Urban,Data Analyst,37647,0 +110828,Male,54,PhD,10,58,71,38,82,8.0,3,15,Urban,Manager,39604,0 +110829,Male,44,Bachelors,14,85,41,88,8,9.0,1,13,Urban,Manager,56380,0 +110830,Female,38,Masters,15,48,83,9,91,2.0,0,12,Rural,Manager,115160,0 +110831,Male,54,Bachelors,6,90,70,63,69,5.0,7,87,Urban,Data Analyst,117522,1 +110832,Female,37,Masters,4,52,88,33,77,4.0,6,50,Rural,Software Engineer,114410,0 +110833,Male,59,Bachelors,17,82,77,54,67,8.0,1,25,Urban,Data Analyst,79742,1 +110834,Female,21,High School,7,73,0,84,63,9.0,6,55,Urban,HR Executive,61953,0 +110835,Female,48,Bachelors,2,6,50,92,93,6.0,4,46,Urban,HR Executive,123096,0 +110836,Female,35,Bachelors,2,2,81,53,28,7.0,3,4,Urban,Software Engineer,65035,0 +110837,Male,49,Bachelors,0,15,38,26,69,3.0,1,83,Urban,Data Analyst,138775,0 +110838,Female,40,Diploma,19,93,42,81,91,7.0,1,52,Rural,Manager,109634,1 +110839,Male,34,Diploma,4,69,30,99,57,6.0,4,74,Urban,HR Executive,68292,1 +110840,Male,52,Bachelors,3,47,81,89,63,5.0,3,23,Rural,Software Engineer,133839,1 +110841,Female,29,Masters,8,9,59,77,24,4.0,4,12,Semi-Urban,Data Analyst,116305,0 +110842,Female,56,Diploma,9,88,81,50,48,3.0,7,90,Urban,HR Executive,28717,1 +110843,Male,22,Diploma,17,1,34,65,59,7.0,3,90,Urban,Manager,86233,0 +110844,Male,45,Masters,14,4,25,83,19,8.0,4,68,Rural,Manager,113555,0 +110845,Female,57,Bachelors,11,51,98,97,55,6.0,7,66,Urban,Manager,134732,1 +110846,Female,34,Bachelors,4,48,45,46,91,6.0,6,30,Rural,Manager,87056,0 +110847,Male,54,Bachelors,4,1,18,98,56,6.0,6,16,Rural,Data Analyst,61960,0 +110848,Other,58,Bachelors,5,84,96,71,29,8.0,7,56,Urban,Data Analyst,28602,1 +110849,Female,24,Diploma,10,90,27,89,40,4.0,7,60,Urban,Manager,122030,1 +110850,Male,46,Masters,17,90,16,64,87,8.0,7,56,Urban,HR Executive,140651,0 +110851,Male,45,Bachelors,13,30,83,54,21,8.0,4,47,Urban,Manager,58999,0 +110852,Male,25,Bachelors,12,78,66,80,96,2.0,1,69,Urban,Data Analyst,58225,1 +110853,Female,58,Diploma,5,88,39,58,35,4.0,2,98,Urban,HR Executive,65171,1 +110854,Female,42,High School,16,27,38,47,2,8.0,6,10,Urban,Manager,90078,0 +110855,Female,40,Bachelors,18,91,30,67,71,1.0,5,16,Urban,HR Executive,45480,0 +110856,Male,28,Bachelors,3,51,92,27,87,4.0,4,6,Urban,HR Executive,145402,0 +110857,Male,27,Diploma,9,20,8,29,63,5.0,4,50,Semi-Urban,ML Engineer,79263,0 +110858,Female,27,Bachelors,3,11,93,64,42,9.0,0,48,Urban,ML Engineer,73000,0 +110859,Male,48,Bachelors,11,24,28,87,71,8.0,7,79,Semi-Urban,HR Executive,119167,0 +110860,Female,48,Diploma,4,11,55,17,57,3.0,0,79,Urban,ML Engineer,72552,0 +110861,Male,49,Bachelors,5,83,5,31,84,8.0,1,18,Urban,ML Engineer,75169,0 +110862,Male,44,Bachelors,15,45,9,53,77,0.0,6,2,Rural,Manager,99728,0 +110863,Male,27,Masters,18,53,38,60,63,6.0,4,13,Urban,Manager,26678,0 +110864,Male,38,Bachelors,19,11,44,82,27,4.0,7,82,Rural,Manager,43167,0 +110865,Male,34,Diploma,12,75,3,67,26,3.0,4,21,Urban,Software Engineer,133115,0 +110866,Male,45,Masters,10,79,35,40,68,7.0,5,23,Semi-Urban,Software Engineer,30975,0 +110867,Male,57,Bachelors,2,66,57,79,72,6.0,5,31,Urban,Software Engineer,61661,0 +110868,Male,55,High School,2,41,19,84,36,4.0,5,83,Urban,ML Engineer,95314,0 +110869,Other,31,Masters,7,10,80,59,35,2.0,1,9,Semi-Urban,Manager,126821,0 +110870,Male,23,Diploma,9,24,94,70,55,3.0,2,81,Rural,ML Engineer,56031,1 +110871,Male,55,Diploma,12,80,34,74,39,7.0,2,83,Semi-Urban,Data Analyst,82618,1 +110872,Female,45,High School,9,70,39,3,44,7.0,4,15,Semi-Urban,Manager,58450,0 +110873,Male,24,Bachelors,19,13,75,42,78,5.0,3,33,Semi-Urban,Data Analyst,134481,0 +110874,Female,21,Diploma,0,88,97,60,14,5.0,4,84,Urban,HR Executive,109110,1 +110875,Male,59,Diploma,13,3,18,66,48,0.0,0,45,Urban,Software Engineer,140468,0 +110876,Male,32,Diploma,2,93,15,78,25,7.0,5,60,Semi-Urban,HR Executive,148261,1 +110877,Male,49,Masters,4,98,27,19,79,0.0,1,76,Rural,HR Executive,134294,0 +110878,Female,25,Bachelors,5,5,75,43,48,9.0,3,21,Urban,ML Engineer,48387,0 +110879,Male,53,Diploma,13,57,75,4,45,9.0,1,22,Urban,Software Engineer,110766,0 +110880,Male,38,Bachelors,2,41,97,31,52,2.0,6,52,Rural,Manager,96108,0 +110881,Male,29,Bachelors,10,27,43,57,53,8.0,3,17,Semi-Urban,Data Analyst,68118,0 +110882,Female,34,Bachelors,5,89,94,10,49,2.0,3,6,Rural,ML Engineer,72182,0 +110883,Male,47,Diploma,7,80,10,87,20,5.0,4,50,Urban,Software Engineer,96656,0 +110884,Other,38,Bachelors,12,63,2,21,50,4.0,6,95,Urban,Data Analyst,102512,0 +110885,Male,43,High School,7,87,61,21,84,2.0,1,8,Urban,ML Engineer,82381,0 +110886,Male,58,Diploma,5,83,7,54,98,5.0,2,37,Urban,Manager,128699,0 +110887,Male,44,Diploma,19,76,44,17,54,9.0,2,93,Urban,ML Engineer,135355,0 +110888,Male,43,PhD,17,25,7,46,93,4.0,2,6,Rural,Manager,113881,0 +110889,Male,45,Bachelors,5,78,17,8,44,4.0,5,80,Urban,ML Engineer,129589,0 +110890,Other,51,High School,14,34,77,46,60,7.0,2,7,Urban,HR Executive,86585,0 +110891,Female,25,PhD,0,70,26,54,55,4.0,4,25,Urban,HR Executive,94472,0 +110892,Male,42,Masters,11,21,46,60,27,2.0,2,38,Semi-Urban,ML Engineer,20811,0 +110893,Male,56,Masters,12,13,62,6,79,9.0,1,39,Urban,ML Engineer,65298,0 +110894,Male,31,Bachelors,7,33,52,31,78,0.0,2,44,Urban,HR Executive,52731,0 +110895,Male,27,Masters,16,22,86,43,59,9.0,2,72,Urban,ML Engineer,124808,0 +110896,Female,37,Masters,7,63,27,19,73,7.0,6,36,Rural,Software Engineer,47196,0 +110897,Female,22,High School,13,73,84,43,83,4.0,6,95,Semi-Urban,Manager,125893,1 +110898,Male,40,Diploma,19,3,36,67,25,8.0,7,6,Urban,Data Analyst,142044,0 +110899,Female,26,High School,1,76,10,3,72,7.0,7,70,Urban,HR Executive,148203,0 +110900,Male,43,Bachelors,13,60,92,71,68,6.0,3,11,Urban,Software Engineer,140028,0 +110901,Female,51,Bachelors,18,59,46,35,77,4.0,7,93,Semi-Urban,Manager,70317,0 +110902,Male,39,Bachelors,5,74,23,0,64,5.0,4,15,Urban,ML Engineer,60976,0 +110903,Male,30,Diploma,4,49,44,36,35,6.0,3,96,Urban,Data Analyst,63247,0 +110904,Male,23,Masters,14,5,54,54,36,1.0,1,91,Urban,ML Engineer,60796,0 +110905,Female,33,Diploma,12,32,35,63,39,8.0,3,18,Rural,HR Executive,101752,0 +110906,Other,25,High School,7,67,18,91,8,5.0,3,86,Urban,HR Executive,77907,1 +110907,Female,22,Masters,6,55,53,86,8,6.0,6,99,Urban,Software Engineer,35115,1 +110908,Female,40,High School,19,67,83,10,42,3.0,6,61,Urban,HR Executive,107141,0 +110909,Male,36,Masters,7,23,74,77,18,0.0,2,4,Urban,ML Engineer,84410,0 +110910,Male,56,Bachelors,5,31,17,95,16,2.0,3,7,Semi-Urban,Data Analyst,28390,0 +110911,Male,31,Masters,16,62,69,59,55,9.0,6,28,Urban,Data Analyst,109390,0 +110912,Male,57,Bachelors,19,94,6,19,24,1.0,2,0,Semi-Urban,Manager,126954,0 +110913,Female,22,Diploma,11,54,27,40,85,2.0,6,2,Urban,Software Engineer,53561,0 +110914,Male,47,Bachelors,14,25,22,75,80,6.0,7,61,Urban,ML Engineer,26053,0 +110915,Male,42,Masters,9,1,39,50,15,1.0,4,7,Semi-Urban,HR Executive,68434,0 +110916,Male,53,Bachelors,13,71,10,48,76,1.0,7,1,Urban,HR Executive,67475,0 +110917,Female,21,Diploma,10,94,81,97,46,8.0,7,59,Urban,Manager,131066,1 +110918,Male,43,High School,0,10,59,77,47,9.0,7,49,Semi-Urban,ML Engineer,54216,0 +110919,Female,46,Bachelors,9,62,85,61,92,1.0,7,45,Urban,Manager,70580,1 +110920,Male,58,PhD,4,91,72,57,65,5.0,7,69,Urban,Manager,94563,1 +110921,Other,40,High School,4,42,1,75,14,9.0,4,92,Rural,Data Analyst,46556,0 +110922,Female,55,Bachelors,17,21,63,47,31,3.0,6,60,Urban,Manager,65163,0 +110923,Male,36,Masters,0,38,60,69,48,4.0,6,69,Urban,Software Engineer,44205,1 +110924,Female,40,Masters,2,3,65,54,94,6.0,3,19,Semi-Urban,Data Analyst,148397,0 +110925,Male,34,Bachelors,5,86,15,16,49,1.0,6,3,Urban,HR Executive,77541,0 +110926,Male,28,Diploma,15,38,77,54,23,7.0,6,98,Semi-Urban,ML Engineer,76509,1 +110927,Male,59,Diploma,13,40,28,86,21,5.0,6,15,Urban,Software Engineer,34240,0 +110928,Female,27,Bachelors,10,19,5,20,10,1.0,0,43,Semi-Urban,Manager,64219,0 +110929,Male,33,Diploma,7,23,66,55,69,9.0,6,73,Semi-Urban,ML Engineer,118684,0 +110930,Male,26,Diploma,7,83,13,96,94,6.0,5,22,Urban,HR Executive,110983,0 +110931,Male,37,Bachelors,15,57,28,59,52,0.0,2,83,Semi-Urban,Software Engineer,91863,0 +110932,Male,40,Masters,7,90,54,12,94,4.0,2,94,Urban,HR Executive,139987,1 +110933,Female,35,Masters,6,24,71,26,89,6.0,6,63,Urban,HR Executive,108755,0 +110934,Male,57,Diploma,8,68,13,55,84,7.0,4,32,Rural,Software Engineer,116026,0 +110935,Male,51,Bachelors,10,42,90,43,99,9.0,3,25,Urban,HR Executive,82109,0 +110936,Male,23,Bachelors,3,60,30,15,39,9.0,3,76,Semi-Urban,Manager,103222,0 +110937,Male,46,Masters,14,38,90,97,35,4.0,5,34,Urban,Manager,47542,1 +110938,Male,55,Bachelors,9,79,98,80,6,7.0,1,91,Urban,Manager,80328,1 +110939,Male,55,Diploma,1,60,22,77,13,8.0,7,77,Rural,HR Executive,85926,1 +110940,Female,40,Masters,11,53,55,35,56,3.0,6,81,Urban,Data Analyst,73499,0 +110941,Other,40,Bachelors,13,13,88,26,7,1.0,1,60,Urban,ML Engineer,88823,0 +110942,Male,47,Masters,7,15,69,33,55,6.0,1,99,Urban,Manager,148070,0 +110943,Female,44,Masters,19,88,38,44,59,3.0,6,2,Semi-Urban,Software Engineer,79325,0 +110944,Male,47,Bachelors,18,70,69,13,52,0.0,4,25,Urban,Manager,68632,0 +110945,Female,55,Bachelors,2,0,47,65,48,0.0,7,46,Urban,Data Analyst,83531,0 +110946,Female,41,Masters,1,18,16,41,7,5.0,6,43,Rural,ML Engineer,107455,0 +110947,Female,54,High School,6,31,26,80,15,1.0,0,78,Urban,Manager,134578,0 +110948,Female,58,PhD,5,88,5,18,57,4.0,1,85,Urban,Manager,84466,0 +110949,Male,41,Masters,6,35,42,65,11,1.0,1,53,Urban,HR Executive,83126,0 +110950,Male,53,Diploma,12,28,86,53,18,1.0,1,18,Urban,Software Engineer,70945,0 +110951,Male,21,Masters,12,98,64,37,71,6.0,6,20,Urban,Data Analyst,108419,0 +110952,Male,54,Diploma,19,63,83,8,75,9.0,1,79,Urban,HR Executive,20629,0 +110953,Male,57,Bachelors,2,15,96,68,66,3.0,3,47,Urban,Data Analyst,107768,0 +110954,Other,28,High School,16,34,16,30,35,6.0,4,41,Urban,Software Engineer,31001,0 +110955,Male,37,Diploma,12,91,78,8,50,4.0,4,94,Urban,Manager,145626,1 +110956,Male,54,Diploma,0,8,12,46,83,0.0,3,32,Semi-Urban,ML Engineer,40420,0 +110957,Female,29,Diploma,14,61,26,1,82,1.0,2,10,Urban,Data Analyst,91555,0 +110958,Male,52,PhD,17,30,54,9,36,3.0,3,41,Urban,HR Executive,73315,0 +110959,Male,33,High School,10,90,0,57,55,5.0,4,28,Rural,HR Executive,112734,0 +110960,Female,21,High School,7,6,87,12,28,9.0,2,85,Urban,Data Analyst,29249,0 +110961,Female,57,Bachelors,10,86,1,8,57,5.0,6,69,Urban,Manager,44803,0 +110962,Female,32,High School,4,7,20,83,23,1.0,5,42,Semi-Urban,Software Engineer,127680,0 +110963,Male,29,Diploma,17,40,36,33,57,1.0,0,46,Rural,Data Analyst,66747,0 +110964,Female,52,Bachelors,3,0,4,80,46,8.0,5,87,Rural,HR Executive,73116,0 +110965,Male,40,Bachelors,16,97,1,61,45,5.0,3,86,Urban,HR Executive,98274,1 +110966,Male,25,Masters,1,7,95,11,14,4.0,3,42,Urban,ML Engineer,61438,0 +110967,Female,51,Diploma,8,63,61,59,57,8.0,4,38,Rural,HR Executive,75574,0 +110968,Other,24,Bachelors,15,23,69,31,8,2.0,5,62,Urban,Software Engineer,45713,0 +110969,Female,49,Bachelors,14,65,32,16,81,5.0,3,74,Urban,Software Engineer,131608,0 +110970,Female,30,High School,4,84,33,9,59,5.0,6,17,Semi-Urban,HR Executive,89069,0 +110971,Male,29,Bachelors,18,34,34,10,14,2.0,7,62,Rural,Data Analyst,132675,0 +110972,Female,46,PhD,19,39,90,5,1,1.0,1,28,Urban,Manager,39651,0 +110973,Male,22,High School,0,12,28,55,75,3.0,3,58,Urban,Manager,38601,0 +110974,Male,23,Bachelors,2,12,15,51,45,4.0,4,71,Urban,Manager,40328,0 +110975,Female,23,Bachelors,1,77,30,56,57,0.0,5,26,Urban,Data Analyst,26830,0 +110976,Male,41,Masters,11,83,76,85,55,0.0,1,36,Semi-Urban,Data Analyst,121892,1 +110977,Male,52,High School,2,71,67,74,16,7.0,6,75,Rural,Manager,51812,1 +110978,Male,29,Masters,1,99,95,64,72,9.0,7,84,Urban,Manager,61233,1 +110979,,30,PhD,18,26,78,57,21,2.0,5,98,Urban,Software Engineer,36640,1 +110980,Male,42,Masters,6,93,39,37,89,7.0,2,11,Urban,Data Analyst,87750,0 +110981,Female,45,Bachelors,5,34,81,21,26,3.0,6,0,Urban,ML Engineer,48202,0 +110982,Male,23,Bachelors,3,90,97,5,1,1.0,0,51,Semi-Urban,HR Executive,79886,1 +110983,Male,45,High School,7,90,55,81,98,0.0,5,94,Semi-Urban,ML Engineer,145664,1 +110984,Male,43,Bachelors,7,60,44,56,23,0.0,5,29,Urban,Manager,122940,0 +110985,Other,49,Bachelors,7,71,80,37,79,8.0,0,22,Urban,Data Analyst,74253,0 +110986,Male,38,Bachelors,4,97,42,46,63,7.0,5,85,Urban,Data Analyst,107710,1 +110987,Male,50,PhD,17,0,8,9,90,9.0,2,24,Urban,HR Executive,70956,0 +110988,Male,46,Bachelors,8,75,15,75,14,0.0,7,92,Rural,Data Analyst,51056,1 +110989,Other,27,Masters,11,23,77,32,71,9.0,2,85,Rural,Manager,50490,0 +110990,Female,50,Bachelors,15,10,57,89,89,9.0,2,70,Urban,HR Executive,47887,0 +110991,Female,30,Bachelors,14,41,70,48,73,7.0,5,49,Urban,Manager,32752,0 +110992,Female,57,High School,5,97,5,68,15,4.0,6,60,Urban,Manager,76073,0 +110993,Male,59,Bachelors,4,82,65,15,37,3.0,6,86,Semi-Urban,Software Engineer,78157,1 +110994,Male,55,Bachelors,9,67,31,56,88,5.0,4,9,Urban,Data Analyst,20552,0 +110995,Male,23,High School,9,46,23,87,48,3.0,0,61,Urban,HR Executive,112824,0 +110996,Male,24,High School,2,83,36,16,62,3.0,1,77,Urban,Data Analyst,62952,0 +110997,Male,57,Diploma,5,24,38,49,23,9.0,4,67,Urban,Manager,75054,0 +110998,Male,41,Bachelors,12,63,62,33,61,7.0,3,38,Urban,Manager,61408,0 +110999,Female,31,Masters,9,74,39,3,84,7.0,5,40,Rural,ML Engineer,65000,0 +111000,Male,56,PhD,17,69,31,28,33,0.0,1,46,Semi-Urban,Manager,147377,0 +111001,Female,55,High School,2,94,3,50,13,0.0,4,3,Urban,Data Analyst,102295,0 +111002,Male,39,Masters,7,39,99,1,25,3.0,1,94,Urban,Software Engineer,31961,0 +111003,Male,23,High School,19,23,51,38,31,3.0,3,71,Semi-Urban,Manager,125386,0 +111004,Male,39,Masters,13,76,89,67,82,8.0,0,23,Semi-Urban,HR Executive,122778,1 +111005,Female,40,Masters,10,93,93,12,18,8.0,3,60,Urban,Manager,36596,1 +111006,Female,32,Bachelors,11,18,54,3,58,7.0,5,32,Urban,ML Engineer,96024,0 +111007,Female,41,PhD,16,41,92,87,35,2.0,4,66,Urban,Software Engineer,96722,1 +111008,Male,24,Masters,14,49,40,44,68,6.0,6,21,Semi-Urban,ML Engineer,76521,0 +111009,Other,34,Bachelors,3,74,65,79,12,4.0,2,15,Rural,Manager,57222,0 +111010,Male,26,Bachelors,1,97,17,28,55,7.0,3,23,Urban,HR Executive,37280,0 +111011,Male,23,Bachelors,1,4,95,28,6,0.0,6,20,Semi-Urban,ML Engineer,94650,0 +111012,Male,26,Diploma,15,87,40,85,48,4.0,7,88,Rural,ML Engineer,106519,1 +111013,Male,39,Masters,19,42,7,36,90,9.0,1,54,Urban,Data Analyst,76451,0 +111014,Male,59,PhD,9,52,48,78,73,1.0,4,72,Urban,Manager,105744,1 +111015,Male,49,Bachelors,15,35,44,0,10,6.0,2,43,Rural,Manager,109463,0 +111016,Male,51,Diploma,17,63,93,56,16,8.0,0,33,Urban,HR Executive,115249,1 +111017,Male,23,Diploma,5,27,11,41,77,1.0,1,20,Rural,Manager,121871,0 +111018,Female,34,High School,17,20,54,78,7,2.0,3,23,Semi-Urban,Software Engineer,88965,0 +111019,Male,21,Masters,5,18,43,96,50,2.0,0,28,Urban,Data Analyst,22773,0 +111020,Female,28,Bachelors,4,3,20,22,1,8.0,7,84,Urban,Software Engineer,38645,0 +111021,Female,42,PhD,3,80,78,40,99,1.0,6,93,Urban,HR Executive,45451,1 +111022,Female,58,High School,8,5,91,40,32,6.0,4,5,Rural,ML Engineer,58736,0 +111023,Female,22,Bachelors,12,23,16,94,46,5.0,5,81,Urban,Manager,64254,0 +111024,Male,50,Diploma,3,27,13,13,66,3.0,6,32,Semi-Urban,Manager,112656,0 +111025,Male,54,High School,15,43,41,65,0,5.0,4,40,Urban,Data Analyst,131573,0 +111026,Male,37,Masters,18,29,93,12,36,1.0,6,33,Urban,ML Engineer,76661,0 +111027,Female,24,Bachelors,19,41,84,26,6,3.0,1,72,Semi-Urban,HR Executive,48670,0 +111028,Male,28,PhD,7,96,67,31,32,1.0,6,21,Urban,Software Engineer,85148,0 +111029,Female,37,Bachelors,5,78,68,0,82,3.0,0,83,Urban,Software Engineer,149576,0 +111030,Female,47,Bachelors,0,76,76,28,33,6.0,5,60,Urban,Software Engineer,40731,0 +111031,Female,46,High School,19,54,78,90,91,7.0,0,48,Semi-Urban,Manager,122212,1 +111032,Female,36,Diploma,4,87,54,50,74,4.0,0,55,Semi-Urban,ML Engineer,20423,1 +111033,Male,46,Diploma,17,51,12,54,5,3.0,4,59,Urban,Data Analyst,102956,0 +111034,Male,54,High School,2,97,48,40,74,2.0,0,59,Urban,Manager,31735,1 +111035,Male,58,Diploma,18,35,65,18,91,0.0,1,99,Urban,Software Engineer,25246,0 +111036,Male,44,Masters,3,14,53,88,34,6.0,5,7,Urban,HR Executive,67406,0 +111037,Male,44,Diploma,8,18,81,29,97,3.0,1,22,Urban,HR Executive,32244,0 +111038,Female,33,High School,2,75,16,56,29,3.0,2,71,Urban,Data Analyst,47106,0 +111039,Male,49,Bachelors,7,74,14,22,56,5.0,0,57,Semi-Urban,Software Engineer,85336,0 +111040,Male,31,Masters,19,25,86,66,56,9.0,6,74,Semi-Urban,ML Engineer,118683,1 +111041,Female,24,High School,19,3,36,49,84,1.0,6,40,Semi-Urban,Data Analyst,78935,0 +111042,Female,40,PhD,11,63,20,3,42,6.0,7,23,Rural,HR Executive,88025,0 +111043,Female,32,Bachelors,16,0,56,14,19,5.0,3,47,Urban,ML Engineer,62116,0 +111044,Male,39,Diploma,5,8,62,81,95,6.0,0,15,Semi-Urban,Software Engineer,146085,0 +111045,Male,22,High School,1,22,94,77,71,0.0,7,40,Urban,Manager,122734,0 +111046,Female,34,Diploma,2,80,17,94,26,5.0,5,11,Urban,Manager,86017,0 +111047,Male,25,Diploma,16,82,52,83,79,9.0,5,42,Rural,ML Engineer,106867,1 +111048,Male,54,Bachelors,5,17,87,7,33,3.0,5,8,Urban,Data Analyst,47864,0 +111049,Male,34,Bachelors,2,13,89,3,4,7.0,1,55,Rural,Data Analyst,143006,0 +111050,Female,24,Diploma,16,60,77,54,32,5.0,2,42,Urban,Data Analyst,74543,0 +111051,Male,51,Bachelors,18,89,84,63,51,4.0,1,30,Urban,Software Engineer,131476,1 +111052,Male,50,High School,4,9,18,53,76,8.0,6,55,Rural,HR Executive,122238,0 +111053,Male,37,High School,1,5,61,81,56,9.0,0,69,Semi-Urban,ML Engineer,121292,0 +111054,Female,30,Masters,10,95,89,98,54,7.0,4,55,Urban,Software Engineer,139986,1 +111055,Male,25,Bachelors,6,41,14,79,40,1.0,1,12,Rural,HR Executive,74002,0 +111056,Male,25,High School,2,5,90,82,7,0.0,3,70,Rural,HR Executive,81048,1 +111057,Female,48,Bachelors,18,89,73,75,98,1.0,6,31,Urban,Manager,129270,1 +111058,Male,48,Masters,17,58,55,74,26,7.0,1,81,Rural,ML Engineer,29715,1 +111059,Male,30,Masters,8,22,71,7,61,6.0,7,31,Urban,Manager,149810,0 +111060,Male,33,Masters,3,73,76,32,46,5.0,0,5,Rural,ML Engineer,52778,0 +111061,Female,21,Bachelors,11,6,91,15,61,8.0,2,78,Semi-Urban,Manager,55338,0 +111062,Male,27,High School,18,85,78,96,77,7.0,2,64,Semi-Urban,Manager,80870,1 +111063,Female,28,Masters,6,54,25,91,16,2.0,1,45,Urban,Software Engineer,85777,0 +111064,Male,26,Bachelors,13,84,54,15,39,4.0,5,57,Rural,HR Executive,23862,0 +111065,Male,41,Bachelors,11,0,38,12,19,9.0,7,55,Semi-Urban,HR Executive,39130,0 +111066,Female,31,Bachelors,11,19,66,80,78,5.0,7,34,Urban,Manager,27624,0 +111067,Male,26,Bachelors,19,64,31,7,64,6.0,6,66,Urban,Manager,75400,0 +111068,Male,50,High School,8,15,6,21,33,4.0,2,16,Semi-Urban,Data Analyst,84049,0 +111069,Female,23,Masters,15,48,93,84,17,4.0,0,88,Rural,Software Engineer,32030,1 +111070,Female,37,Bachelors,5,56,13,16,75,1.0,5,43,Urban,ML Engineer,101339,0 +111071,Male,34,Bachelors,3,10,32,7,4,9.0,6,41,Urban,Manager,33781,0 +111072,Male,59,Bachelors,10,66,63,45,36,1.0,7,93,Semi-Urban,ML Engineer,64388,1 +111073,Female,30,Diploma,5,39,62,72,21,9.0,1,32,Urban,Manager,80494,0 +111074,Male,29,Bachelors,9,1,99,96,40,1.0,4,32,Urban,ML Engineer,28693,0 +111075,Male,21,Bachelors,13,92,87,11,94,9.0,7,8,Urban,Data Analyst,72690,0 +111076,Male,43,Diploma,18,99,63,48,5,7.0,1,78,Rural,Data Analyst,110227,1 +111077,Male,33,Bachelors,19,31,62,5,47,3.0,1,45,Rural,Manager,119807,0 +111078,Male,44,Masters,5,1,74,81,61,1.0,2,21,Rural,HR Executive,97199,0 +111079,Male,38,Masters,1,67,51,21,59,4.0,6,57,Urban,ML Engineer,114639,0 +111080,Male,41,Masters,2,94,99,46,49,1.0,3,57,Semi-Urban,Manager,40970,1 +111081,Female,35,High School,17,98,1,96,3,4.0,2,85,Urban,ML Engineer,130994,1 +111082,Female,56,Bachelors,11,6,79,27,86,6.0,2,13,Urban,Data Analyst,118656,0 +111083,Male,39,Diploma,8,39,3,31,93,7.0,6,55,Urban,Manager,40440,0 +111084,Male,32,High School,6,14,77,4,63,9.0,6,66,Urban,Software Engineer,126368,0 +111085,Female,52,High School,12,30,17,19,61,0.0,0,76,Urban,Software Engineer,61848,0 +111086,Female,25,Diploma,18,62,18,2,66,1.0,5,83,Urban,Software Engineer,38038,0 +111087,Male,26,Bachelors,1,98,93,25,19,0.0,6,45,Urban,Software Engineer,20890,1 +111088,Male,28,Bachelors,4,50,12,84,34,5.0,4,97,Urban,Manager,31374,1 +111089,Female,52,Diploma,10,40,26,47,87,7.0,0,56,Urban,Manager,95812,0 +111090,Female,22,Bachelors,15,63,90,60,45,6.0,0,88,Semi-Urban,Software Engineer,90068,1 +111091,Female,55,Masters,12,57,77,85,19,4.0,6,38,Rural,HR Executive,138963,1 +111092,Female,40,Bachelors,1,17,10,4,69,3.0,3,37,Rural,Manager,34334,0 +111093,Female,25,High School,14,2,40,88,99,9.0,3,86,Semi-Urban,Manager,39872,0 +111094,Male,56,High School,16,45,83,7,30,5.0,7,60,Urban,Manager,24480,0 +111095,Male,27,High School,8,40,47,47,75,0.0,7,29,Urban,Data Analyst,131492,0 +111096,Male,46,PhD,0,34,18,62,87,8.0,6,3,Urban,Software Engineer,93061,0 +111097,Male,41,PhD,15,8,0,90,21,3.0,0,93,Urban,HR Executive,104835,0 +111098,Male,57,Bachelors,2,9,59,42,9,7.0,2,72,Rural,ML Engineer,41738,0 +111099,Male,38,Diploma,8,72,66,11,31,3.0,1,20,Urban,ML Engineer,36055,0 +111100,Male,32,Bachelors,6,22,81,37,81,3.0,5,2,Semi-Urban,HR Executive,115949,0 +111101,Female,39,Bachelors,5,39,35,2,56,0.0,3,7,Urban,Data Analyst,46783,0 +111102,Male,59,Bachelors,17,46,29,54,46,4.0,1,60,Semi-Urban,Software Engineer,116294,0 +111103,Male,41,Bachelors,7,59,77,21,39,0.0,2,75,Urban,Software Engineer,40068,0 +111104,Female,45,Masters,0,71,82,63,84,5.0,6,76,Urban,Software Engineer,102095,1 +111105,Female,59,Bachelors,19,7,7,98,16,2.0,1,16,Semi-Urban,ML Engineer,66407,0 +111106,Male,49,High School,8,77,87,87,21,6.0,0,56,Rural,Software Engineer,71064,1 +111107,Male,25,Diploma,5,98,45,97,15,4.0,0,2,Urban,HR Executive,123775,1 +111108,Male,55,Masters,5,11,25,65,95,2.0,6,31,Urban,Software Engineer,109369,0 +111109,Female,50,Bachelors,7,89,88,7,14,5.0,0,46,Rural,ML Engineer,109190,0 +111110,Female,50,Diploma,16,35,29,19,10,4.0,5,76,Urban,Software Engineer,28008,0 +111111,Male,37,Diploma,18,5,95,69,73,4.0,2,73,Urban,ML Engineer,129404,1 +111112,Male,58,Masters,10,49,94,21,83,3.0,4,28,Urban,Manager,74687,0 +111113,Female,42,Bachelors,3,28,39,43,94,8.0,4,91,Urban,ML Engineer,88582,0 +111114,Female,56,Bachelors,12,46,96,64,11,9.0,4,72,Urban,Manager,30531,1 +111115,Male,27,Masters,6,7,34,58,14,8.0,7,97,Semi-Urban,ML Engineer,62819,0 +111116,Male,29,Diploma,17,79,42,92,77,7.0,1,12,Urban,Manager,124809,0 +111117,Male,21,Bachelors,8,8,73,29,62,2.0,4,1,Semi-Urban,Manager,42594,0 +111118,Male,34,High School,12,90,48,45,91,1.0,1,88,Semi-Urban,Manager,103733,1 +111119,Male,27,Diploma,13,51,98,46,2,9.0,0,60,Urban,Manager,30556,1 +111120,Male,47,Bachelors,10,96,85,22,18,9.0,3,64,Semi-Urban,HR Executive,106408,1 +111121,Female,42,Bachelors,13,32,78,63,62,5.0,4,73,Urban,ML Engineer,27521,1 +111122,Male,31,Masters,16,80,28,36,74,0.0,5,40,Urban,Data Analyst,50441,0 +111123,Male,37,Bachelors,7,58,60,49,81,6.0,4,31,Semi-Urban,Manager,24258,0 +111124,Female,23,Masters,5,99,62,16,10,5.0,3,11,Urban,HR Executive,128909,0 +111125,Male,48,Diploma,13,12,64,95,59,4.0,0,62,Rural,Software Engineer,90629,0 +111126,Female,49,Bachelors,13,52,60,67,84,4.0,2,79,Urban,HR Executive,49511,1 +111127,Female,55,Bachelors,1,4,75,90,77,3.0,1,48,Urban,Manager,88482,0 +111128,Male,58,Bachelors,19,21,89,63,19,8.0,0,40,Urban,ML Engineer,99719,0 +111129,Male,44,Bachelors,0,90,45,46,46,8.0,1,15,Urban,HR Executive,46364,0 +111130,Female,35,Bachelors,17,43,37,23,58,6.0,4,98,Rural,Manager,79009,0 +111131,Male,26,Diploma,5,73,52,74,76,6.0,2,79,Urban,Software Engineer,71710,1 +111132,Male,26,Bachelors,10,26,64,39,25,5.0,3,93,Rural,Data Analyst,62754,0 +111133,Female,52,Bachelors,3,48,92,72,2,3.0,1,57,Rural,Software Engineer,60336,1 +111134,Male,31,Diploma,2,24,7,57,10,2.0,2,12,Urban,Data Analyst,117307,0 +111135,Male,39,Masters,1,6,71,42,15,8.0,7,51,Urban,HR Executive,90042,0 +111136,Male,45,Bachelors,5,0,81,44,8,0.0,0,83,Urban,Data Analyst,81497,0 +111137,Female,49,Masters,1,41,22,95,85,1.0,2,33,Urban,Manager,67304,0 +111138,Male,40,High School,16,53,36,6,78,8.0,5,27,Urban,HR Executive,51355,0 +111139,Male,45,Bachelors,10,56,44,58,7,6.0,6,49,Urban,Data Analyst,141001,0 +111140,Male,56,Bachelors,17,62,48,98,98,7.0,3,67,Semi-Urban,ML Engineer,27081,1 +111141,Male,38,Masters,12,97,4,75,87,3.0,5,97,Urban,Software Engineer,99256,1 +111142,Male,30,Bachelors,13,2,28,98,72,4.0,7,98,Urban,Data Analyst,112625,0 +111143,Female,25,PhD,14,80,6,68,87,1.0,1,12,Urban,ML Engineer,73343,0 +111144,Male,40,High School,12,49,7,64,15,2.0,2,48,Urban,ML Engineer,63323,0 +111145,Male,54,Bachelors,5,25,83,29,21,5.0,2,92,Semi-Urban,Software Engineer,136340,0 +111146,Male,36,Masters,3,30,52,28,38,0.0,2,67,Urban,Software Engineer,105443,0 +111147,Female,49,Masters,2,78,98,22,16,8.0,0,83,Urban,Manager,47584,1 +111148,Male,55,Bachelors,15,43,26,36,44,7.0,3,46,Semi-Urban,Data Analyst,120457,0 +111149,Other,50,Bachelors,18,64,63,19,92,2.0,6,66,Urban,Manager,77254,0 +111150,Male,36,Bachelors,2,67,70,1,55,1.0,2,38,Semi-Urban,Manager,132084,0 +111151,Female,35,Diploma,11,55,21,59,93,6.0,2,0,Urban,HR Executive,137791,0 +111152,Male,51,Bachelors,9,11,24,67,52,4.0,3,22,Semi-Urban,HR Executive,23530,0 +111153,Female,51,PhD,2,62,97,7,47,4.0,5,43,Semi-Urban,HR Executive,66563,0 +111154,Female,52,Bachelors,2,60,12,70,18,4.0,0,53,Semi-Urban,HR Executive,111699,0 +111155,Male,52,Bachelors,11,3,95,16,20,0.0,3,87,Rural,HR Executive,21066,0 +111156,Male,54,Masters,19,65,80,82,8,0.0,7,62,Semi-Urban,HR Executive,84421,1 +111157,Female,31,PhD,16,51,79,2,5,3.0,5,36,Urban,Software Engineer,99091,0 +111158,Female,56,PhD,8,8,46,19,82,1.0,6,79,Semi-Urban,ML Engineer,36598,0 +111159,Male,46,Diploma,19,91,83,47,27,7.0,0,68,Urban,ML Engineer,32289,1 +111160,Male,50,High School,11,16,64,67,70,3.0,5,70,Rural,Software Engineer,108759,0 +111161,Female,44,Masters,11,53,22,70,72,1.0,0,0,Rural,Software Engineer,35844,0 +111162,Male,40,Diploma,7,37,92,69,83,5.0,7,99,Semi-Urban,ML Engineer,51566,1 +111163,Male,22,Masters,17,62,94,38,22,6.0,3,68,Urban,ML Engineer,97271,1 +111164,Female,51,Diploma,16,56,92,10,94,4.0,4,57,Semi-Urban,Data Analyst,91489,0 +111165,Female,55,High School,13,32,68,17,47,7.0,5,49,Urban,ML Engineer,91517,0 +111166,Female,52,Masters,18,53,16,24,78,3.0,7,22,Rural,HR Executive,38367,0 +111167,Male,50,Bachelors,2,43,63,23,5,8.0,5,86,Urban,Data Analyst,59287,0 +111168,Female,29,PhD,5,7,37,26,77,7.0,6,39,Urban,ML Engineer,46283,0 +111169,Male,43,Diploma,17,3,70,70,3,6.0,0,25,Urban,ML Engineer,143017,0 +111170,Female,25,High School,17,12,32,1,54,0.0,1,61,Rural,ML Engineer,45509,0 +111171,Other,56,Bachelors,17,16,80,94,10,6.0,6,62,Semi-Urban,Software Engineer,87163,1 +111172,Male,46,Bachelors,9,2,14,33,69,8.0,1,57,Semi-Urban,Data Analyst,112613,0 +111173,Male,35,PhD,4,67,80,48,17,8.0,4,32,Semi-Urban,ML Engineer,92819,0 +111174,Female,55,Masters,4,55,50,8,62,6.0,0,52,Rural,HR Executive,33609,0 +111175,Male,54,Diploma,2,55,84,93,53,1.0,4,45,Urban,Software Engineer,140259,1 +111176,Male,35,PhD,15,72,17,6,71,0.0,7,41,Urban,HR Executive,140756,0 +111177,Female,27,Bachelors,3,58,69,14,31,8.0,0,37,Urban,HR Executive,78015,0 +111178,Female,58,Bachelors,2,80,92,14,96,0.0,5,71,Semi-Urban,HR Executive,120677,1 +111179,Other,56,High School,7,93,51,42,39,5.0,7,34,Urban,Data Analyst,52772,0 +111180,Male,40,Masters,10,37,99,66,24,2.0,4,90,Semi-Urban,HR Executive,20668,1 +111181,Male,40,Bachelors,0,45,50,37,44,2.0,6,61,Urban,HR Executive,69672,0 +111182,Female,23,Bachelors,4,16,77,75,1,3.0,3,54,Semi-Urban,Software Engineer,134479,0 +111183,Male,31,Masters,14,39,58,36,39,5.0,3,26,Urban,ML Engineer,133279,0 +111184,Male,31,Bachelors,8,84,64,63,19,5.0,1,21,Semi-Urban,Software Engineer,97837,0 +111185,Female,52,Masters,15,49,89,75,78,2.0,7,80,Semi-Urban,Software Engineer,73280,1 +111186,Female,49,Bachelors,0,74,67,14,50,5.0,0,58,Semi-Urban,ML Engineer,119138,0 +111187,Male,45,Masters,8,33,7,44,64,9.0,1,87,Semi-Urban,Software Engineer,113361,0 +111188,Male,25,High School,5,72,51,46,18,6.0,4,43,Urban,Manager,111011,0 +111189,Female,55,Bachelors,5,45,85,72,85,8.0,2,44,Rural,HR Executive,28185,1 +111190,Male,46,Bachelors,14,93,80,6,29,8.0,4,41,Urban,Software Engineer,92392,0 +111191,Male,41,Diploma,11,60,74,66,16,6.0,2,49,Urban,HR Executive,122201,1 +111192,Male,21,High School,10,76,60,88,44,9.0,4,75,Semi-Urban,ML Engineer,121816,1 +111193,Male,37,Bachelors,12,18,26,44,59,7.0,6,44,Urban,Manager,45769,0 +111194,Male,23,Masters,18,20,82,4,36,7.0,3,5,Urban,HR Executive,98898,0 +111195,Male,47,Diploma,16,78,2,30,2,0.0,4,62,Urban,HR Executive,126431,0 +111196,Male,46,High School,0,23,43,65,59,5.0,2,45,Semi-Urban,ML Engineer,34757,0 +111197,Male,36,Bachelors,1,28,39,97,68,6.0,2,72,Rural,Software Engineer,96628,1 +111198,Male,49,Masters,14,84,60,99,9,9.0,1,64,Urban,Software Engineer,103035,1 +111199,Male,41,High School,10,69,50,0,30,4.0,4,69,Urban,ML Engineer,51600,0 +111200,Male,24,Bachelors,5,35,9,76,41,7.0,1,86,Urban,Software Engineer,80357,0 +111201,Female,41,Bachelors,10,83,90,31,92,0.0,0,4,Rural,Software Engineer,117022,0 +111202,Male,58,Bachelors,1,84,30,24,47,6.0,6,40,Semi-Urban,ML Engineer,44794,0 +111203,Male,49,High School,6,60,39,78,86,2.0,0,62,Urban,Manager,123391,1 +111204,Male,55,Bachelors,14,8,5,50,50,6.0,2,95,Urban,ML Engineer,100544,0 +111205,Female,35,PhD,13,16,7,72,32,2.0,5,74,Urban,Data Analyst,104696,0 +111206,Male,24,Diploma,16,88,41,98,19,6.0,0,37,Rural,Data Analyst,79998,1 +111207,Male,45,High School,3,12,79,37,6,3.0,5,75,Urban,Software Engineer,94772,0 +111208,Male,40,High School,13,60,10,63,68,2.0,4,26,Semi-Urban,Software Engineer,142667,0 +111209,Male,35,Masters,14,63,92,60,67,2.0,6,6,Rural,Manager,61314,0 +111210,Female,44,Diploma,16,36,82,89,49,6.0,7,70,Urban,HR Executive,75775,1 +111211,Female,33,High School,15,39,81,40,50,0.0,3,8,Semi-Urban,Software Engineer,43790,0 +111212,Male,30,Bachelors,16,19,25,12,60,8.0,6,64,Urban,HR Executive,43096,0 +111213,Female,31,Bachelors,11,70,13,3,3,4.0,2,43,Semi-Urban,ML Engineer,77324,0 +111214,Male,48,Bachelors,16,14,88,23,35,4.0,3,75,Semi-Urban,Manager,80291,0 +111215,Male,35,PhD,5,8,0,58,55,4.0,0,36,Semi-Urban,ML Engineer,88476,0 +111216,Male,40,Diploma,11,19,82,77,2,5.0,2,93,Urban,ML Engineer,88423,1 +111217,Female,54,Bachelors,6,2,77,54,89,5.0,2,51,Urban,Data Analyst,43270,0 +111218,Male,33,Diploma,15,22,8,67,85,8.0,1,54,Semi-Urban,HR Executive,46784,0 +111219,Male,59,Bachelors,7,98,72,78,68,5.0,2,2,Urban,ML Engineer,144084,1 +111220,Male,34,PhD,7,7,35,77,3,4.0,7,37,Semi-Urban,ML Engineer,74397,0 +111221,Male,21,Diploma,8,22,57,7,37,9.0,1,67,Semi-Urban,Manager,38244,0 +111222,Female,32,Diploma,1,81,39,56,0,3.0,3,44,Urban,Software Engineer,80587,0 +111223,Female,42,Masters,12,86,85,25,56,8.0,4,14,Urban,Software Engineer,81055,0 +111224,Female,34,Diploma,5,75,59,96,19,5.0,5,34,Urban,HR Executive,92529,1 +111225,Male,51,Bachelors,15,22,54,90,52,1.0,7,89,Urban,Data Analyst,41341,1 +111226,Female,57,Bachelors,5,4,40,89,39,0.0,3,35,Semi-Urban,ML Engineer,40397,0 +111227,Male,52,Diploma,14,15,55,19,65,4.0,4,45,Semi-Urban,Software Engineer,59269,0 +111228,Female,57,Bachelors,19,31,20,81,41,9.0,7,12,Semi-Urban,HR Executive,126429,0 +111229,Female,47,Diploma,8,36,98,77,33,8.0,1,91,Semi-Urban,Data Analyst,37324,1 +111230,Male,24,Diploma,16,6,92,98,81,7.0,2,31,Urban,Data Analyst,81580,0 +111231,Male,29,Bachelors,16,58,57,2,13,0.0,7,21,Urban,ML Engineer,62658,0 +111232,Male,27,Masters,18,47,22,97,5,5.0,0,48,Semi-Urban,HR Executive,46609,0 +111233,Other,40,High School,6,92,94,70,78,1.0,5,34,Semi-Urban,Manager,55982,1 +111234,Male,33,Masters,2,3,72,30,59,5.0,3,82,Urban,ML Engineer,85390,0 +111235,Female,37,Diploma,0,15,89,54,62,8.0,5,45,Urban,Manager,25970,0 +111236,Male,58,Diploma,6,2,64,10,40,5.0,0,53,Urban,Data Analyst,33272,0 +111237,Male,47,Masters,14,80,99,31,13,7.0,5,96,Rural,ML Engineer,96759,1 +111238,Female,42,Masters,12,24,58,6,51,3.0,6,14,Urban,Software Engineer,130740,0 +111239,Female,36,Bachelors,1,26,95,7,80,7.0,2,99,Urban,ML Engineer,51920,0 +111240,Female,57,Bachelors,11,37,67,18,19,2.0,4,62,Urban,Data Analyst,48912,0 +111241,Male,32,Bachelors,13,89,46,86,79,2.0,3,20,Rural,Software Engineer,144487,1 +111242,Male,35,Diploma,6,93,73,23,68,6.0,7,1,Urban,Software Engineer,61124,0 +111243,Female,55,Diploma,15,59,36,21,73,3.0,2,78,Urban,HR Executive,59538,0 +111244,Other,24,Diploma,4,80,54,87,24,2.0,3,41,Rural,Software Engineer,74990,1 +111245,Male,39,Bachelors,14,34,20,7,70,6.0,2,41,Semi-Urban,Manager,44058,0 +111246,Male,28,Masters,10,52,24,28,72,1.0,7,37,Rural,ML Engineer,48825,0 +111247,Male,29,PhD,14,66,25,96,60,0.0,1,84,Urban,Data Analyst,98250,1 +111248,Female,50,Bachelors,14,34,18,29,69,6.0,1,47,Rural,HR Executive,79656,0 +111249,Male,46,Masters,9,70,37,28,30,1.0,7,19,Urban,Manager,53067,0 +111250,Female,41,Masters,14,16,11,73,30,9.0,4,53,Urban,Data Analyst,32299,0 +111251,Female,24,High School,11,14,57,61,59,0.0,5,31,Urban,Software Engineer,97388,0 +111252,Female,43,Diploma,1,17,62,0,98,5.0,2,59,Semi-Urban,ML Engineer,128914,0 +111253,Male,55,Bachelors,1,61,21,82,3,0.0,5,62,Urban,ML Engineer,26983,0 +111254,Female,26,Bachelors,6,76,64,16,2,9.0,5,54,Rural,ML Engineer,26594,0 +111255,Female,36,Masters,16,20,98,20,21,1.0,6,41,Urban,Software Engineer,109250,0 +111256,Female,33,Bachelors,12,29,62,3,7,4.0,1,60,Urban,Data Analyst,130462,0 +111257,Female,40,PhD,9,32,97,20,90,3.0,6,14,Rural,HR Executive,72819,0 +111258,Male,26,High School,6,31,76,53,21,4.0,2,45,Rural,ML Engineer,73659,0 +111259,Female,30,Masters,7,82,92,93,87,7.0,3,65,Urban,ML Engineer,65033,1 +111260,Male,55,Diploma,15,41,11,51,44,7.0,7,79,Urban,Manager,117093,0 +111261,Male,37,Masters,12,20,96,15,76,7.0,1,4,Rural,Software Engineer,124829,0 +111262,Male,24,Diploma,3,45,38,49,37,0.0,2,92,Urban,Software Engineer,78017,0 +111263,Female,22,Masters,16,30,37,30,60,6.0,5,25,Rural,Data Analyst,38786,0 +111264,Male,50,Bachelors,4,92,69,18,81,5.0,2,46,Rural,Data Analyst,109179,0 +111265,Female,36,Diploma,7,4,60,29,50,2.0,7,8,Semi-Urban,Data Analyst,28885,0 +111266,Other,31,Bachelors,6,31,29,39,38,7.0,6,33,Urban,Data Analyst,36643,0 +111267,Male,36,Bachelors,8,55,30,25,47,5.0,3,73,Urban,Manager,20877,0 +111268,Other,55,High School,3,96,68,62,95,5.0,5,90,Urban,HR Executive,37172,1 +111269,Male,55,Diploma,18,20,69,13,79,1.0,7,49,Urban,Data Analyst,56838,0 +111270,Female,48,PhD,17,60,42,73,80,7.0,6,59,Urban,Data Analyst,40954,0 +111271,Female,23,Masters,0,35,95,24,20,0.0,3,27,Semi-Urban,Manager,38858,0 +111272,Male,32,Diploma,7,91,13,20,80,0.0,5,90,Semi-Urban,Manager,47423,0 +111273,Other,55,High School,13,25,64,88,32,7.0,7,50,Urban,Software Engineer,109648,0 +111274,Female,39,Bachelors,3,62,31,98,32,5.0,5,0,Urban,HR Executive,76084,0 +111275,Female,44,Bachelors,9,92,29,20,12,5.0,2,0,Rural,Manager,48668,0 +111276,Male,54,Diploma,1,25,81,95,15,6.0,5,75,Urban,ML Engineer,36610,1 +111277,Male,30,Diploma,9,46,47,0,88,6.0,4,36,Urban,Data Analyst,77069,0 +111278,Male,43,Masters,3,36,91,78,7,3.0,3,31,Urban,Software Engineer,100685,1 +111279,Male,48,Masters,16,24,92,60,43,5.0,6,42,Semi-Urban,Data Analyst,89496,0 +111280,Male,50,Bachelors,10,32,45,52,31,6.0,3,78,Urban,ML Engineer,79895,0 +111281,Female,49,Bachelors,1,26,65,52,28,8.0,3,8,Urban,HR Executive,50590,0 +111282,Male,38,Diploma,19,75,5,34,88,5.0,6,68,Urban,Manager,21242,0 +111283,Male,46,Bachelors,13,33,55,69,98,4.0,6,22,Urban,ML Engineer,97602,0 +111284,Male,29,Bachelors,2,76,8,5,29,9.0,5,76,Rural,HR Executive,132303,0 +111285,Female,30,Masters,1,45,43,28,45,8.0,7,69,Urban,HR Executive,37687,0 +111286,Male,23,Diploma,10,63,39,80,35,5.0,7,4,Semi-Urban,Manager,105758,0 +111287,Female,45,Bachelors,8,55,87,33,74,1.0,4,19,Semi-Urban,ML Engineer,29765,0 +111288,Female,33,Masters,14,11,57,5,75,8.0,6,21,Urban,HR Executive,46936,0 +111289,Female,42,High School,5,75,4,95,0,5.0,7,43,Urban,Data Analyst,74840,0 +111290,Male,34,Bachelors,8,75,44,3,19,2.0,6,93,Rural,Manager,136822,0 +111291,Male,24,Diploma,9,51,34,19,44,4.0,2,68,Urban,Software Engineer,84871,0 +111292,Female,21,Bachelors,17,14,10,18,71,7.0,3,88,Rural,Software Engineer,94499,0 +111293,Male,33,Masters,15,37,98,54,36,3.0,1,44,Urban,Software Engineer,71009,0 +111294,Female,52,Diploma,9,76,87,73,40,7.0,1,91,Urban,ML Engineer,30408,1 +111295,Female,44,High School,9,53,31,40,40,5.0,5,55,Urban,Software Engineer,125131,0 +111296,Male,52,Diploma,18,27,15,61,29,2.0,4,57,Urban,ML Engineer,53113,0 +111297,Male,42,Masters,3,23,78,12,97,5.0,3,35,Urban,HR Executive,32971,0 +111298,Male,57,Bachelors,3,44,50,91,91,2.0,5,90,Urban,HR Executive,45642,1 +111299,Male,40,Diploma,11,34,79,20,28,2.0,4,81,Urban,ML Engineer,123158,0 +111300,Female,32,Masters,16,95,29,21,52,5.0,2,94,Rural,Software Engineer,133217,0 +111301,Male,39,Bachelors,6,83,50,83,91,1.0,7,8,Semi-Urban,Data Analyst,27750,0 +111302,Female,49,Bachelors,14,56,36,23,68,5.0,0,59,Urban,Manager,20740,0 +111303,Male,34,Bachelors,2,95,42,15,10,2.0,4,3,Urban,Data Analyst,52755,0 +111304,Male,23,Masters,8,64,99,0,58,1.0,5,33,Urban,Software Engineer,141390,0 +111305,Female,35,Diploma,10,52,77,27,6,4.0,3,36,Urban,Software Engineer,75509,0 +111306,Female,25,Bachelors,16,27,2,33,38,0.0,6,94,Semi-Urban,Software Engineer,73894,0 +111307,Male,39,Bachelors,4,64,20,56,89,4.0,5,37,Urban,Data Analyst,60086,0 +111308,Male,23,Bachelors,0,96,64,23,45,9.0,0,46,Semi-Urban,Software Engineer,87629,0 +111309,Male,36,Bachelors,11,41,66,63,16,6.0,6,80,Rural,Software Engineer,109006,1 +111310,Male,34,High School,10,36,68,52,62,9.0,3,67,Rural,HR Executive,119319,0 +111311,Female,34,Bachelors,0,87,0,12,55,3.0,6,72,Urban,Data Analyst,58491,0 +111312,Male,43,High School,8,40,20,98,46,2.0,3,14,Urban,Software Engineer,53683,0 +111313,Male,26,Masters,0,26,22,68,54,9.0,0,87,Rural,Manager,127374,0 +111314,Female,31,PhD,4,24,98,87,36,0.0,5,7,Urban,Software Engineer,64195,0 +111315,Female,36,Bachelors,13,44,83,19,40,1.0,4,94,Urban,Manager,133680,0 +111316,Male,27,Bachelors,13,37,12,79,86,3.0,5,27,Semi-Urban,Manager,43804,0 +111317,Female,30,Bachelors,2,88,3,32,67,8.0,1,96,Semi-Urban,Data Analyst,59384,0 +111318,Female,37,High School,9,11,42,22,85,2.0,1,11,Urban,Manager,145449,0 +111319,Male,21,Bachelors,4,56,97,12,66,4.0,1,23,Semi-Urban,Software Engineer,69352,0 +111320,Female,47,High School,12,48,84,53,90,5.0,1,4,Rural,Manager,21998,0 +111321,Male,37,High School,15,34,49,53,48,0.0,0,25,Urban,Data Analyst,125577,0 +111322,Male,55,Masters,11,28,17,79,98,3.0,5,81,Urban,HR Executive,111174,0 +111323,Other,32,Bachelors,5,34,42,99,55,8.0,6,46,Urban,Manager,110698,0 +111324,Male,36,Masters,8,20,38,28,23,0.0,0,87,Urban,Data Analyst,75625,0 +111325,Male,41,Diploma,2,91,19,18,20,4.0,7,27,Semi-Urban,Data Analyst,146644,0 +111326,Male,52,Bachelors,9,99,53,23,43,1.0,4,32,Semi-Urban,Data Analyst,129054,0 +111327,Male,48,Diploma,14,41,66,24,44,2.0,0,16,Semi-Urban,HR Executive,126019,0 +111328,Male,52,Masters,8,30,98,2,16,0.0,6,27,Semi-Urban,ML Engineer,121453,0 +111329,Male,46,Diploma,3,56,19,70,18,4.0,2,10,Urban,Manager,50863,0 +111330,Female,21,Masters,4,43,97,1,40,4.0,5,70,Urban,Manager,67155,0 +111331,Female,34,Bachelors,9,88,21,5,22,2.0,3,73,Urban,Manager,113419,0 +111332,Female,38,Masters,8,47,32,28,74,2.0,0,33,Urban,ML Engineer,92486,0 +111333,Male,21,Bachelors,8,86,22,43,35,8.0,7,60,Rural,Software Engineer,123797,0 +111334,Male,38,Masters,16,85,85,12,83,4.0,7,6,Rural,Data Analyst,35578,0 +111335,Female,56,Bachelors,10,51,47,92,41,1.0,0,98,Urban,Data Analyst,83449,1 +111336,Male,23,High School,19,69,35,91,2,7.0,3,24,Semi-Urban,Software Engineer,23004,0 +111337,Male,37,Diploma,19,13,18,17,95,7.0,3,8,Rural,Software Engineer,42830,0 +111338,Male,44,Bachelors,12,92,32,29,70,0.0,2,46,Urban,Software Engineer,65340,0 +111339,Female,55,Diploma,8,53,82,26,54,6.0,5,53,Urban,HR Executive,119832,0 +111340,Female,46,Bachelors,8,92,27,97,45,7.0,0,1,Semi-Urban,HR Executive,74401,0 +111341,Male,26,Bachelors,6,56,93,10,76,0.0,1,2,Rural,ML Engineer,137207,0 +111342,Female,26,Diploma,14,94,48,63,25,3.0,0,96,Rural,HR Executive,61993,1 +111343,Female,28,Diploma,6,22,29,42,10,2.0,3,57,Urban,Manager,92818,0 +111344,Male,47,Masters,6,16,13,8,32,8.0,2,92,Semi-Urban,ML Engineer,84617,0 +111345,Male,44,High School,8,38,85,59,38,0.0,7,7,Semi-Urban,HR Executive,71010,0 +111346,Female,44,Masters,8,34,17,75,88,3.0,3,58,Urban,HR Executive,134436,0 +111347,Female,59,Masters,17,65,70,39,64,7.0,6,91,Rural,Data Analyst,64144,1 +111348,Male,29,Bachelors,6,62,95,73,61,6.0,6,31,Urban,Data Analyst,81071,1 +111349,Male,55,Bachelors,11,69,87,72,44,1.0,7,88,Urban,Data Analyst,67935,1 +111350,Female,36,Diploma,3,25,21,75,63,6.0,1,95,Urban,HR Executive,35263,0 +111351,Female,52,Bachelors,8,12,26,93,35,0.0,2,36,Semi-Urban,ML Engineer,146205,0 +111352,Other,39,Diploma,7,43,9,11,20,2.0,4,16,Semi-Urban,ML Engineer,106854,0 +111353,Male,36,Bachelors,4,62,84,53,53,7.0,1,73,Semi-Urban,ML Engineer,70943,1 +111354,Female,25,High School,7,69,28,47,72,1.0,3,65,Semi-Urban,Manager,114336,0 +111355,Male,44,Bachelors,18,30,29,87,48,8.0,2,6,Semi-Urban,HR Executive,68397,0 +111356,Female,26,Diploma,7,0,83,29,79,8.0,3,84,Urban,HR Executive,60201,0 +111357,Male,36,Diploma,14,96,4,88,59,4.0,2,45,Urban,HR Executive,103455,0 +111358,Male,25,High School,10,85,28,86,51,2.0,1,56,Urban,Software Engineer,24066,1 +111359,Female,50,High School,11,65,91,96,74,3.0,4,2,Urban,Manager,39177,1 +111360,Male,52,Masters,16,59,70,10,36,4.0,7,99,Urban,Manager,80166,1 +111361,Female,24,Bachelors,6,6,94,88,75,4.0,3,3,Semi-Urban,Manager,125210,0 +111362,Female,38,Bachelors,17,29,62,80,72,6.0,4,0,Urban,Data Analyst,125306,0 +111363,Male,30,High School,17,57,31,98,49,9.0,5,86,Semi-Urban,HR Executive,68939,1 +111364,Male,39,Diploma,19,1,91,57,45,4.0,0,16,Urban,Manager,80980,0 +111365,Female,58,Bachelors,10,68,32,56,14,9.0,5,80,Urban,Manager,28878,0 +111366,Other,33,High School,16,77,51,67,66,8.0,6,15,Rural,ML Engineer,32634,0 +111367,Male,39,Masters,9,68,10,4,65,3.0,2,74,Urban,HR Executive,108879,0 +111368,Male,23,Diploma,16,33,48,78,45,2.0,7,88,Urban,Manager,42706,1 +111369,Female,38,Masters,8,18,64,69,46,7.0,0,26,Rural,Manager,84588,0 +111370,Other,54,Bachelors,13,23,69,84,36,7.0,2,84,Semi-Urban,Manager,101720,1 +111371,Male,34,Diploma,16,25,78,64,71,6.0,1,25,Urban,Software Engineer,78059,0 +111372,Male,44,Diploma,0,21,54,76,7,1.0,2,73,Rural,Manager,64432,0 +111373,Female,22,Diploma,1,33,73,48,20,9.0,2,84,Rural,Manager,141213,0 +111374,Female,26,High School,3,13,82,96,73,3.0,5,13,Urban,HR Executive,32557,0 +111375,Male,35,Masters,12,33,62,19,98,6.0,5,62,Urban,ML Engineer,134681,0 +111376,Other,54,Masters,0,81,86,27,14,2.0,0,10,Urban,HR Executive,94553,0 +111377,Male,27,Bachelors,9,84,26,31,0,9.0,7,56,Urban,HR Executive,134491,0 +111378,Male,46,Diploma,6,46,28,83,6,3.0,1,39,Semi-Urban,ML Engineer,104485,0 +111379,Female,56,Masters,8,91,64,86,67,3.0,3,9,Rural,Data Analyst,115422,1 +111380,Male,39,Diploma,13,32,80,30,26,7.0,1,50,Semi-Urban,ML Engineer,137881,0 +111381,Female,56,Bachelors,12,37,70,43,25,0.0,3,36,Rural,HR Executive,89094,0 +111382,Female,37,Bachelors,12,18,43,24,15,4.0,0,97,Urban,ML Engineer,145487,0 +111383,Male,54,Bachelors,1,46,71,26,80,6.0,1,33,Rural,Data Analyst,86328,0 +111384,Male,27,High School,18,36,24,20,69,0.0,1,85,Urban,ML Engineer,82676,0 +111385,Male,54,Bachelors,0,61,72,84,50,9.0,0,59,Semi-Urban,Software Engineer,88936,1 +111386,Female,55,Bachelors,19,61,13,26,48,8.0,7,64,Semi-Urban,ML Engineer,42315,0 +111387,Male,23,Bachelors,18,17,73,92,20,1.0,0,25,Urban,Manager,40108,0 +111388,Male,27,Masters,10,87,57,26,96,8.0,0,55,Urban,Software Engineer,139910,0 +111389,Female,55,Bachelors,6,98,29,63,58,6.0,6,85,Urban,ML Engineer,92336,1 +111390,Male,43,Diploma,15,33,1,64,35,9.0,6,64,Semi-Urban,HR Executive,115009,0 +111391,Male,47,Diploma,16,82,49,90,54,1.0,3,11,Rural,ML Engineer,35182,0 +111392,Male,39,Masters,11,18,26,34,18,2.0,5,67,Semi-Urban,HR Executive,92645,0 +111393,Female,53,Diploma,1,67,37,45,27,9.0,2,23,Rural,HR Executive,34434,0 +111394,Male,25,High School,9,1,96,32,17,7.0,3,57,Semi-Urban,Data Analyst,65301,0 +111395,Male,56,Bachelors,0,17,54,42,16,1.0,4,7,Urban,Manager,136865,0 +111396,Female,29,PhD,11,58,3,19,12,4.0,3,90,Urban,Software Engineer,47778,0 +111397,Other,24,Bachelors,9,9,43,99,26,0.0,2,44,Rural,Software Engineer,79725,0 +111398,Male,57,Diploma,2,48,17,91,23,4.0,7,58,Urban,ML Engineer,39921,0 +111399,Female,30,Bachelors,5,48,78,58,21,1.0,5,59,Urban,ML Engineer,111972,1 +111400,Male,49,Masters,5,42,6,94,94,3.0,2,31,Semi-Urban,Software Engineer,60294,0 +111401,Male,54,Bachelors,5,44,84,34,49,5.0,1,35,Urban,ML Engineer,57025,0 +111402,Male,49,High School,9,6,20,51,10,1.0,7,18,Urban,Software Engineer,129837,0 +111403,Female,53,Bachelors,11,96,14,33,38,7.0,5,46,Rural,ML Engineer,73590,0 +111404,Male,39,High School,4,54,53,35,99,2.0,7,24,Urban,Data Analyst,146839,0 +111405,Male,43,Masters,17,66,45,78,96,9.0,6,13,Urban,ML Engineer,120143,0 +111406,Male,59,Diploma,0,83,38,69,99,4.0,6,97,Urban,ML Engineer,103929,1 +111407,Male,23,Masters,7,65,50,60,59,7.0,5,55,Urban,Software Engineer,34743,0 +111408,Female,55,Bachelors,6,37,76,87,28,2.0,1,85,Semi-Urban,Manager,102598,1 +111409,Male,57,High School,12,94,80,6,45,2.0,2,53,Rural,ML Engineer,48818,0 +111410,Female,34,Bachelors,6,5,81,51,58,0.0,1,7,Urban,HR Executive,132666,0 +111411,Other,48,Bachelors,4,57,11,36,63,5.0,0,52,Semi-Urban,ML Engineer,135168,0 +111412,Male,58,Diploma,8,53,61,84,18,8.0,6,1,Urban,Manager,71750,0 +111413,Female,39,Diploma,6,11,88,84,35,7.0,7,0,Rural,Manager,124577,0 +111414,Male,36,High School,15,92,2,57,20,5.0,0,48,Semi-Urban,ML Engineer,37416,0 +111415,Male,51,High School,7,61,47,74,93,3.0,1,73,Rural,Data Analyst,130745,1 +111416,Male,25,Masters,9,54,71,31,97,8.0,4,2,Semi-Urban,Data Analyst,94012,0 +111417,Male,57,Diploma,4,40,19,24,29,3.0,6,93,Urban,HR Executive,66569,0 +111418,Male,40,High School,10,2,53,32,62,6.0,0,96,Semi-Urban,HR Executive,105491,0 +111419,Male,30,Bachelors,9,69,79,10,61,9.0,3,88,Rural,Data Analyst,59865,1 +111420,Other,31,Masters,13,4,24,25,51,8.0,6,32,Urban,Software Engineer,145348,0 +111421,Female,54,Diploma,18,24,31,84,49,4.0,2,91,Semi-Urban,Software Engineer,94109,0 +111422,Male,54,Bachelors,12,13,88,62,92,7.0,1,33,Urban,Software Engineer,149477,0 +111423,Female,34,Diploma,8,25,13,66,60,1.0,3,83,Rural,HR Executive,95916,0 +111424,Male,21,Bachelors,4,44,28,27,22,2.0,6,13,Urban,Manager,133805,0 +111425,Female,57,Bachelors,12,62,73,35,37,2.0,7,89,Urban,Data Analyst,39497,1 +111426,Male,31,Diploma,3,1,72,69,2,9.0,7,10,Semi-Urban,HR Executive,58959,0 +111427,Male,35,Bachelors,6,3,62,69,3,3.0,5,71,Urban,ML Engineer,82931,0 +111428,Male,43,Diploma,15,74,41,55,29,7.0,5,97,Urban,ML Engineer,97562,1 +111429,Female,55,Bachelors,3,74,19,51,89,7.0,1,11,Rural,Data Analyst,103007,0 +111430,Male,35,High School,17,63,75,39,78,2.0,6,60,Urban,HR Executive,100054,1 +111431,Female,47,Masters,10,73,0,24,29,8.0,6,73,Semi-Urban,Data Analyst,59126,0 +111432,Female,33,Masters,11,69,58,21,59,4.0,2,95,Urban,ML Engineer,75052,1 +111433,Male,46,Bachelors,6,92,5,71,54,3.0,6,90,Rural,ML Engineer,30425,1 +111434,Male,54,Diploma,0,70,68,3,29,0.0,6,89,Urban,Software Engineer,36567,0 +111435,Male,37,Bachelors,11,32,1,63,15,4.0,0,8,Semi-Urban,Software Engineer,136527,0 +111436,Female,43,Diploma,7,88,35,76,99,0.0,1,58,Rural,Data Analyst,55288,1 +111437,Other,42,Bachelors,17,80,25,80,60,0.0,6,79,Rural,HR Executive,86424,1 +111438,Male,29,Bachelors,7,23,20,8,13,3.0,3,99,Semi-Urban,Software Engineer,51284,0 +111439,Male,45,Bachelors,16,53,18,15,82,3.0,0,50,Semi-Urban,Software Engineer,98673,0 +111440,Male,22,Bachelors,9,2,35,22,84,3.0,0,14,Rural,Data Analyst,114281,0 +111441,Male,40,High School,14,45,7,3,57,7.0,7,36,Urban,HR Executive,84121,0 +111442,Female,49,Bachelors,13,12,0,40,41,8.0,2,6,Urban,Manager,144115,0 +111443,Female,23,Bachelors,16,58,2,81,35,6.0,4,98,Rural,ML Engineer,96284,0 +111444,Male,42,Diploma,16,44,29,2,59,7.0,0,92,Semi-Urban,HR Executive,86561,0 +111445,Male,43,Bachelors,19,1,47,21,52,2.0,0,56,Urban,Software Engineer,133004,0 +111446,Male,31,Bachelors,9,69,40,96,75,0.0,1,28,Urban,Software Engineer,78797,0 +111447,Male,40,Diploma,4,67,13,55,40,8.0,0,17,Rural,ML Engineer,132466,0 +111448,Male,50,Masters,13,10,82,29,81,2.0,3,10,Urban,Manager,123790,0 +111449,Female,50,Diploma,5,59,29,5,1,1.0,4,23,Semi-Urban,ML Engineer,80879,0 +111450,Female,33,Bachelors,14,3,40,29,15,1.0,7,58,Rural,Software Engineer,145806,0 +111451,Female,48,Bachelors,11,86,1,82,36,2.0,1,38,Rural,Software Engineer,105917,0 +111452,Female,58,Diploma,18,93,74,34,38,1.0,0,77,Urban,HR Executive,139659,1 +111453,Male,45,Masters,7,41,95,55,69,9.0,4,65,Urban,Data Analyst,54629,1 +111454,Female,26,Bachelors,4,27,96,97,48,9.0,5,67,Urban,Software Engineer,72842,1 +111455,Female,46,Diploma,19,87,10,40,16,0.0,1,29,Rural,HR Executive,146791,0 +111456,Other,56,Diploma,10,51,93,13,35,5.0,3,3,Semi-Urban,Software Engineer,48568,0 +111457,Male,29,Bachelors,9,67,0,61,24,1.0,4,2,Urban,Data Analyst,51832,0 +111458,Male,24,High School,2,75,59,50,35,3.0,5,94,Urban,Data Analyst,64651,1 +111459,Male,24,Bachelors,16,49,24,64,64,8.0,6,39,Urban,Software Engineer,104005,0 +111460,Male,24,Bachelors,12,53,42,43,9,6.0,1,8,Semi-Urban,ML Engineer,54220,0 +111461,Male,50,High School,10,45,24,46,95,7.0,2,73,Rural,Data Analyst,77996,0 +111462,Female,50,Bachelors,17,23,14,20,63,5.0,4,6,Urban,Software Engineer,114203,0 +111463,Female,49,Masters,5,74,88,93,20,3.0,1,83,Urban,Manager,115530,1 +111464,Male,53,Bachelors,2,7,37,63,59,5.0,4,75,Urban,ML Engineer,128359,0 +111465,Male,39,Bachelors,10,89,72,56,23,9.0,0,61,Semi-Urban,Software Engineer,128455,1 +111466,Other,44,Bachelors,3,28,90,24,57,9.0,0,61,Semi-Urban,Manager,137398,0 +111467,Male,25,Diploma,6,94,82,59,26,8.0,4,60,Urban,ML Engineer,104095,1 +111468,Male,55,Diploma,5,24,19,94,65,4.0,3,62,Rural,Software Engineer,84191,0 +111469,Female,49,Bachelors,6,58,8,82,98,8.0,5,14,Urban,Data Analyst,127350,0 +111470,Female,37,High School,9,16,70,39,23,0.0,5,60,Urban,Software Engineer,26325,0 +111471,Other,53,Bachelors,9,77,27,46,51,0.0,5,73,Urban,Manager,116119,0 +111472,Other,54,Bachelors,10,44,53,1,66,0.0,3,49,Urban,Data Analyst,74128,0 +111473,Female,26,Bachelors,7,58,1,76,12,0.0,0,85,Urban,Data Analyst,126241,0 +111474,Male,32,Diploma,14,14,34,79,81,4.0,1,59,Urban,Manager,66989,0 +111475,Female,29,Diploma,8,13,36,93,22,1.0,7,34,Rural,HR Executive,76714,0 +111476,Female,34,Diploma,11,34,97,66,93,1.0,1,90,Semi-Urban,HR Executive,31624,1 +111477,Male,23,Masters,10,88,70,3,10,6.0,0,31,Urban,Software Engineer,109031,0 +111478,Male,22,Diploma,4,86,82,77,84,5.0,1,92,Semi-Urban,Data Analyst,113055,1 +111479,Female,39,Bachelors,11,68,65,9,20,5.0,5,13,Urban,Software Engineer,123539,0 +111480,Male,28,Diploma,16,66,45,46,31,7.0,1,51,Rural,Software Engineer,93498,0 +111481,Female,52,Bachelors,2,12,57,50,7,0.0,4,17,Rural,Data Analyst,58362,0 +111482,Male,48,Bachelors,4,49,16,85,77,7.0,6,13,Semi-Urban,ML Engineer,135078,0 +111483,Male,34,Diploma,17,0,84,87,52,6.0,6,38,Semi-Urban,Data Analyst,95859,0 +111484,Male,47,Bachelors,13,83,16,97,80,3.0,2,63,Semi-Urban,Data Analyst,42163,1 +111485,Female,46,High School,5,2,30,39,2,7.0,6,10,Urban,Manager,137762,0 +111486,Male,26,High School,3,23,16,42,95,7.0,4,24,Rural,ML Engineer,45461,0 +111487,Female,25,Masters,8,38,18,47,69,2.0,7,12,Semi-Urban,Software Engineer,29666,0 +111488,Female,25,Bachelors,11,18,98,47,55,5.0,1,88,Urban,Manager,65654,1 +111489,Male,40,High School,2,34,39,18,38,2.0,5,60,Semi-Urban,Software Engineer,27915,0 +111490,Female,49,Diploma,0,93,94,69,21,8.0,0,42,Urban,HR Executive,146786,1 +111491,Male,24,Diploma,16,64,85,22,17,4.0,1,33,Semi-Urban,Data Analyst,132119,0 +111492,Female,56,Masters,11,69,90,19,46,6.0,6,47,Urban,Software Engineer,57597,0 +111493,Female,42,Diploma,14,31,29,23,64,9.0,7,29,Urban,Software Engineer,142703,0 +111494,Female,59,High School,10,28,74,69,47,2.0,7,54,Urban,Software Engineer,68122,0 +111495,Female,31,Diploma,15,18,10,84,90,1.0,2,48,Semi-Urban,Software Engineer,53821,0 +111496,Male,47,High School,4,83,32,47,44,6.0,0,87,Urban,ML Engineer,71536,1 +111497,Male,38,Bachelors,17,69,42,48,29,6.0,0,61,Urban,Software Engineer,51024,0 +111498,Male,37,Diploma,8,29,17,19,47,1.0,5,2,Urban,Software Engineer,60197,0 +111499,Male,46,Diploma,8,8,85,98,69,9.0,1,55,Semi-Urban,ML Engineer,38384,1 +111500,Male,51,Bachelors,10,25,11,39,81,4.0,6,69,Urban,HR Executive,144777,0 +111501,Female,31,Diploma,13,47,11,28,77,1.0,0,82,Rural,Software Engineer,139965,0 +111502,Male,53,Diploma,19,97,66,54,78,0.0,2,64,Urban,Data Analyst,143535,1 +111503,Male,52,Bachelors,1,61,70,70,65,9.0,2,89,Rural,Manager,21940,1 +111504,Other,56,Bachelors,8,1,24,76,79,1.0,1,87,Rural,Software Engineer,24776,0 +111505,Male,28,Bachelors,12,5,32,24,55,4.0,0,40,Rural,HR Executive,112936,0 +111506,Male,35,Bachelors,7,40,2,0,22,7.0,7,72,Semi-Urban,ML Engineer,26040,0 +111507,Female,46,Bachelors,14,15,27,86,34,6.0,1,73,Rural,Data Analyst,30676,0 +111508,Female,43,Bachelors,2,95,46,14,74,3.0,7,19,Rural,Manager,140361,0 +111509,Male,47,Masters,7,88,40,87,13,7.0,7,87,Urban,Software Engineer,93382,1 +111510,Female,31,High School,7,12,5,72,21,3.0,4,66,Rural,Data Analyst,48282,0 +111511,Female,26,High School,18,97,38,78,83,0.0,2,43,Urban,Manager,135857,1 +111512,Male,22,Bachelors,0,51,39,94,33,1.0,6,94,Semi-Urban,HR Executive,56340,1 +111513,Male,39,High School,2,52,22,65,43,3.0,6,47,Urban,ML Engineer,37030,0 +111514,Female,38,Bachelors,13,72,67,51,5,2.0,6,98,Urban,Software Engineer,82430,1 +111515,Male,25,Bachelors,17,40,63,58,35,9.0,2,21,Urban,Data Analyst,49777,0 +111516,Female,45,High School,5,90,57,91,88,0.0,5,77,Rural,ML Engineer,135927,1 +111517,Female,37,Masters,6,3,13,51,57,5.0,4,35,Urban,ML Engineer,38829,0 +111518,Male,26,Bachelors,13,40,80,70,3,1.0,7,49,Urban,Data Analyst,134409,1 +111519,Female,39,Diploma,9,67,37,13,18,5.0,7,76,Semi-Urban,Software Engineer,143352,0 +111520,Female,25,High School,5,25,26,82,12,8.0,1,0,Rural,HR Executive,148973,0 +111521,Male,36,High School,6,85,93,63,48,0.0,6,15,Semi-Urban,ML Engineer,108325,1 +111522,Male,48,Diploma,14,50,68,32,30,4.0,5,11,Semi-Urban,Manager,24502,0 +111523,Other,56,Bachelors,13,30,95,32,29,4.0,5,17,Rural,ML Engineer,52997,0 +111524,Male,58,Diploma,4,38,14,85,46,0.0,4,56,Urban,Software Engineer,52210,0 +111525,Female,22,Bachelors,3,79,98,58,84,1.0,2,55,Semi-Urban,HR Executive,22134,1 +111526,Male,23,Masters,19,80,75,33,25,4.0,7,65,Rural,HR Executive,33954,1 +111527,Female,23,Bachelors,16,38,45,28,25,9.0,5,15,Urban,HR Executive,24857,0 +111528,Male,39,Bachelors,16,3,73,43,39,2.0,0,56,Urban,Data Analyst,107786,0 +111529,Male,59,Diploma,1,94,70,91,5,0.0,3,35,Urban,ML Engineer,37788,1 +111530,Female,23,Diploma,14,10,54,62,4,8.0,2,81,Urban,HR Executive,74772,0 +111531,Male,33,Diploma,19,14,55,66,54,7.0,6,76,Urban,Data Analyst,89904,0 +111532,Male,48,Masters,5,16,22,30,34,1.0,5,75,Semi-Urban,ML Engineer,101726,0 +111533,Male,24,Masters,5,27,34,80,50,0.0,6,93,Urban,HR Executive,118386,0 +111534,Male,35,Masters,0,7,38,9,65,9.0,1,93,Urban,Data Analyst,135457,0 +111535,Male,31,Bachelors,2,77,59,9,39,7.0,6,16,Urban,ML Engineer,104539,0 +111536,Female,57,Bachelors,5,29,20,14,40,1.0,7,37,Semi-Urban,Data Analyst,23092,0 +111537,Male,28,High School,13,94,14,8,62,3.0,1,35,Rural,ML Engineer,26268,0 +111538,Male,53,High School,12,79,53,51,62,5.0,7,45,Urban,HR Executive,118147,0 +111539,Male,22,Diploma,16,61,96,63,18,6.0,5,55,Rural,Data Analyst,98467,1 +111540,Male,57,Bachelors,0,71,54,49,53,9.0,6,52,Semi-Urban,Software Engineer,114187,0 +111541,Male,23,Bachelors,16,41,36,21,85,7.0,6,45,Urban,ML Engineer,87823,0 +111542,Female,55,Diploma,12,49,31,93,42,0.0,5,49,Rural,Data Analyst,79537,0 +111543,Male,39,Masters,4,24,65,56,34,3.0,7,1,Rural,Software Engineer,122512,0 +111544,Male,49,Bachelors,10,88,95,19,27,8.0,5,49,Urban,Software Engineer,44553,1 +111545,Female,45,High School,18,60,76,94,93,3.0,3,56,Rural,HR Executive,37904,1 +111546,Female,55,Bachelors,15,95,18,74,35,2.0,2,91,Rural,Data Analyst,121215,1 +111547,Male,42,High School,5,25,33,32,26,4.0,2,54,Urban,Software Engineer,41507,0 +111548,Male,33,Bachelors,7,65,29,23,82,2.0,5,0,Semi-Urban,ML Engineer,81506,0 +111549,Male,38,Masters,2,23,93,23,36,9.0,6,88,Urban,ML Engineer,64845,0 +111550,Male,32,Diploma,6,57,97,49,78,7.0,6,45,Urban,Manager,145377,1 +111551,Male,55,Bachelors,4,81,89,0,82,6.0,5,83,Rural,ML Engineer,59968,1 +111552,Female,35,Bachelors,3,29,26,84,78,1.0,1,82,Urban,ML Engineer,63320,0 +111553,Male,55,Bachelors,4,62,8,98,29,1.0,4,44,Urban,ML Engineer,29911,0 +111554,Female,34,Bachelors,11,15,34,89,1,9.0,7,42,Urban,ML Engineer,145072,0 +111555,Male,58,Bachelors,7,26,35,10,12,9.0,1,28,Urban,Manager,24888,0 +111556,Male,24,Masters,6,5,52,56,37,0.0,5,32,Urban,Software Engineer,81814,0 +111557,Female,25,Bachelors,1,5,93,55,35,7.0,6,47,Urban,Software Engineer,127457,0 +111558,Other,38,High School,13,4,99,79,57,4.0,7,47,Rural,Data Analyst,101067,0 +111559,Male,50,Bachelors,10,83,45,41,15,6.0,5,9,Urban,Software Engineer,77337,0 +111560,Male,28,Diploma,5,37,36,67,72,8.0,3,80,Rural,ML Engineer,89524,0 +111561,Male,22,Bachelors,7,59,42,9,68,8.0,3,97,Rural,Software Engineer,113582,0 +111562,Male,35,Bachelors,7,62,24,62,61,0.0,3,63,Semi-Urban,Software Engineer,95650,0 +111563,Female,25,Bachelors,1,32,62,38,83,7.0,5,58,Semi-Urban,Software Engineer,105482,0 +111564,Male,30,Bachelors,17,85,43,4,98,2.0,1,32,Urban,Data Analyst,94381,0 +111565,Male,57,Diploma,4,77,78,17,14,4.0,6,57,Urban,Software Engineer,124113,0 +111566,Female,42,Masters,3,19,58,89,58,2.0,0,81,Urban,Manager,75029,1 +111567,Male,31,Diploma,17,56,97,26,48,7.0,3,53,Urban,HR Executive,109997,0 +111568,Female,28,High School,1,22,73,83,8,7.0,1,29,Urban,Manager,77059,0 +111569,Male,38,Masters,15,84,97,41,9,2.0,4,70,Rural,ML Engineer,112561,1 +111570,Female,26,Bachelors,14,94,48,62,87,5.0,6,52,Semi-Urban,Manager,22718,1 +111571,Female,44,Bachelors,11,61,8,99,52,2.0,6,97,Rural,Manager,108361,1 +111572,Female,39,Masters,10,3,22,7,66,5.0,0,92,Urban,HR Executive,127284,0 +111573,Male,47,Bachelors,17,34,55,11,34,9.0,0,46,Urban,Data Analyst,89416,0 +111574,Male,40,Diploma,14,32,27,22,32,9.0,6,56,Rural,Manager,20850,0 +111575,Male,30,Masters,6,18,16,99,66,1.0,5,53,Urban,ML Engineer,60707,0 +111576,Female,45,Bachelors,1,3,5,29,21,8.0,4,1,Urban,HR Executive,107562,0 +111577,Female,28,Masters,15,81,54,70,19,7.0,6,85,Urban,HR Executive,60779,1 +111578,Male,45,Bachelors,2,33,99,80,15,0.0,6,72,Rural,HR Executive,100514,1 +111579,Female,51,PhD,2,29,2,83,59,5.0,2,68,Semi-Urban,Manager,135512,0 +111580,Male,47,Bachelors,14,30,97,10,92,3.0,0,9,Urban,HR Executive,76480,0 +111581,Female,41,Diploma,6,40,13,31,42,5.0,1,39,Urban,Manager,135548,0 +111582,Female,59,High School,19,72,12,25,94,4.0,4,74,Urban,Software Engineer,45188,0 +111583,Female,40,Masters,9,21,22,46,53,8.0,1,45,Urban,Software Engineer,47291,0 +111584,Female,48,Bachelors,5,78,91,64,82,2.0,0,5,Semi-Urban,Software Engineer,77943,0 +111585,Female,46,Diploma,15,59,69,11,64,8.0,2,96,Urban,Data Analyst,41548,0 +111586,Male,27,High School,4,32,74,6,75,5.0,0,77,Rural,ML Engineer,83915,0 +111587,Male,59,Bachelors,18,42,22,23,5,2.0,6,23,Semi-Urban,HR Executive,36647,0 +111588,Female,47,Bachelors,18,80,74,84,68,1.0,0,65,Urban,Data Analyst,65143,1 +111589,Male,46,Masters,3,64,15,80,40,9.0,5,66,Semi-Urban,HR Executive,149363,0 +111590,Other,46,Masters,4,86,63,16,89,0.0,4,46,Semi-Urban,Data Analyst,47403,0 +111591,Male,44,Masters,15,76,55,31,35,3.0,0,18,Semi-Urban,ML Engineer,89593,0 +111592,Female,25,Bachelors,10,74,38,22,95,1.0,0,17,Rural,HR Executive,62887,0 +111593,Male,45,Diploma,7,46,16,28,77,0.0,1,29,Semi-Urban,Manager,48895,0 +111594,Other,59,High School,0,87,30,10,71,9.0,1,78,Semi-Urban,Software Engineer,104029,0 +111595,Male,38,Masters,19,17,41,33,46,7.0,0,63,Semi-Urban,Manager,136926,0 +111596,Male,44,Masters,19,11,6,68,73,8.0,0,10,Urban,Data Analyst,108539,0 +111597,Female,46,Diploma,19,36,43,17,89,1.0,3,6,Urban,HR Executive,119477,0 +111598,Male,49,High School,15,61,66,68,27,7.0,5,43,Semi-Urban,Manager,139796,1 +111599,Female,28,Masters,19,71,22,6,93,6.0,0,74,Urban,Data Analyst,67779,0 +111600,Male,57,Masters,10,80,68,82,93,6.0,2,69,Semi-Urban,Manager,142585,1 +111601,Female,42,High School,7,85,92,39,55,0.0,5,43,Urban,Software Engineer,137379,1 +111602,Male,52,Diploma,11,85,1,60,61,3.0,7,24,Urban,Manager,79722,0 +111603,Other,25,Bachelors,3,94,51,58,49,2.0,6,17,Semi-Urban,Software Engineer,97604,0 +111604,Male,39,Bachelors,18,12,37,85,32,4.0,6,46,Semi-Urban,Data Analyst,127243,0 +111605,Male,38,PhD,7,20,72,22,15,6.0,4,9,Semi-Urban,Software Engineer,110500,0 +111606,Male,52,High School,19,56,81,60,47,9.0,6,30,Urban,HR Executive,71522,0 +111607,Male,27,High School,11,10,50,11,66,7.0,4,74,Rural,ML Engineer,84229,0 +111608,Male,56,High School,12,58,19,44,6,1.0,5,53,Semi-Urban,Manager,146177,0 +111609,Female,31,Bachelors,0,24,36,20,0,8.0,1,41,Urban,ML Engineer,26277,0 +111610,Female,32,Bachelors,16,80,52,10,48,6.0,7,46,Urban,Software Engineer,24041,0 +111611,Female,40,PhD,11,80,78,21,54,6.0,5,16,Rural,Manager,149069,0 +111612,Female,56,Bachelors,18,41,83,17,10,9.0,5,43,Semi-Urban,ML Engineer,137832,0 +111613,Female,37,High School,4,65,69,59,98,9.0,4,40,Semi-Urban,HR Executive,118440,0 +111614,Female,29,Bachelors,9,16,6,25,55,2.0,0,32,Urban,ML Engineer,131579,0 +111615,Female,28,Masters,4,38,55,59,79,0.0,1,84,Urban,ML Engineer,26363,0 +111616,Male,57,Bachelors,5,16,14,20,14,9.0,2,62,Urban,Software Engineer,136585,0 +111617,Male,57,Diploma,3,96,92,29,70,9.0,0,89,Urban,Software Engineer,45549,1 +111618,Female,42,Bachelors,8,25,24,36,12,0.0,0,42,Urban,Data Analyst,38422,0 +111619,Male,49,Bachelors,9,98,5,66,2,4.0,2,30,Rural,Data Analyst,96354,0 +111620,Male,58,Bachelors,19,79,15,17,71,5.0,2,79,Semi-Urban,Data Analyst,22455,0 +111621,Female,40,Bachelors,9,21,92,4,41,7.0,5,89,Semi-Urban,Data Analyst,146890,0 +111622,Other,53,Bachelors,8,43,73,74,86,0.0,0,80,Rural,Data Analyst,52235,1 +111623,Female,33,Diploma,7,43,47,12,50,4.0,5,30,Semi-Urban,HR Executive,94999,0 +111624,Female,32,High School,14,94,23,84,20,5.0,2,71,Semi-Urban,Data Analyst,59893,1 +111625,Male,37,High School,0,37,93,73,83,2.0,2,10,Urban,Manager,138596,0 +111626,Female,26,Masters,13,49,38,43,12,0.0,7,2,Semi-Urban,Manager,82999,0 +111627,Male,49,Bachelors,4,3,85,3,30,7.0,2,82,Semi-Urban,ML Engineer,22124,0 +111628,Female,40,PhD,6,15,97,82,82,2.0,3,85,Semi-Urban,ML Engineer,95549,1 +111629,Male,42,Bachelors,7,72,14,61,42,6.0,7,16,Rural,Software Engineer,106150,0 +111630,Male,57,Bachelors,17,39,98,21,5,1.0,6,65,Urban,Manager,91366,0 +111631,Male,23,High School,3,40,83,43,39,2.0,7,49,Rural,Software Engineer,38410,0 +111632,Female,46,Diploma,19,35,79,61,57,8.0,6,15,Rural,Manager,85329,0 +111633,Female,25,Bachelors,10,63,6,71,65,2.0,6,26,Urban,Manager,135040,0 +111634,Male,36,High School,12,73,40,66,13,5.0,4,19,Urban,HR Executive,86156,0 +111635,Female,59,Masters,9,60,0,66,46,2.0,2,9,Semi-Urban,Manager,143731,0 +111636,Female,46,Diploma,2,59,89,81,2,3.0,6,38,Urban,Software Engineer,24336,1 +111637,Male,41,Bachelors,2,60,67,16,21,2.0,5,56,Urban,Software Engineer,95829,0 +111638,Male,53,Bachelors,4,96,98,40,59,5.0,3,33,Urban,ML Engineer,103106,1 +111639,Male,59,High School,19,93,6,19,76,2.0,6,96,Rural,Software Engineer,118168,0 +111640,Male,23,Masters,18,42,42,53,82,1.0,7,95,Urban,Manager,107192,0 +111641,Male,32,Diploma,19,60,72,27,89,8.0,1,59,Urban,ML Engineer,129610,0 +111642,Female,36,Bachelors,11,36,31,84,1,7.0,1,63,Urban,Manager,25967,0 +111643,Female,33,Diploma,9,43,5,49,2,6.0,5,33,Semi-Urban,ML Engineer,101203,0 +111644,Female,35,Bachelors,0,40,14,47,47,1.0,6,70,Urban,ML Engineer,48011,0 +111645,Male,22,High School,2,44,69,7,27,3.0,5,86,Urban,Software Engineer,24436,0 +111646,Female,48,Bachelors,15,93,70,94,92,1.0,3,99,Urban,Data Analyst,115108,1 +111647,Male,41,Masters,9,40,78,37,39,7.0,6,24,Urban,Data Analyst,122599,0 +111648,Male,37,Bachelors,15,87,34,23,4,6.0,1,40,Rural,HR Executive,73502,0 +111649,Male,33,Diploma,6,34,92,70,59,1.0,2,47,Rural,Manager,66782,1 +111650,Male,40,PhD,10,98,5,62,68,7.0,6,5,Rural,HR Executive,41948,0 +111651,Male,49,Diploma,4,79,58,86,32,8.0,6,77,Urban,HR Executive,31940,1 +111652,Male,43,Masters,1,7,33,23,22,6.0,5,34,Urban,ML Engineer,46075,0 +111653,Male,44,Bachelors,11,92,35,78,53,0.0,2,36,Rural,ML Engineer,86548,1 +111654,Male,51,Bachelors,0,27,81,25,78,6.0,7,63,Rural,Data Analyst,40813,0 +111655,Female,59,Diploma,5,37,36,71,46,5.0,1,34,Urban,Manager,130763,0 +111656,Female,23,High School,18,6,38,70,59,6.0,0,38,Urban,ML Engineer,118764,0 +111657,Male,38,Bachelors,4,6,34,10,52,7.0,5,33,Rural,Manager,129278,0 +111658,Female,51,PhD,0,35,14,19,70,4.0,1,59,Semi-Urban,Software Engineer,104601,0 +111659,Male,55,Masters,0,17,62,43,30,7.0,4,38,Urban,HR Executive,53545,0 +111660,Other,34,Diploma,2,99,26,84,4,0.0,3,86,Rural,Data Analyst,48695,1 +111661,Male,44,High School,11,40,59,96,97,4.0,7,60,Semi-Urban,HR Executive,69033,1 +111662,Female,39,High School,18,70,61,28,52,2.0,6,98,Urban,ML Engineer,125986,1 +111663,Male,48,Masters,13,84,11,87,83,2.0,1,54,Rural,Software Engineer,113343,1 +111664,Female,40,Bachelors,1,14,74,12,15,9.0,1,46,Urban,Software Engineer,51457,0 +111665,Male,26,Bachelors,2,69,88,82,2,1.0,3,50,Urban,ML Engineer,138769,1 +111666,Other,22,Masters,13,21,84,29,91,3.0,1,25,Urban,Software Engineer,65854,0 +111667,Male,21,Bachelors,2,68,73,73,74,1.0,2,41,Urban,Data Analyst,115485,1 +111668,Male,49,High School,11,3,86,98,10,0.0,6,89,Urban,Software Engineer,29739,1 +111669,Male,45,High School,13,63,83,28,14,5.0,2,64,Semi-Urban,ML Engineer,68564,1 +111670,Female,49,Bachelors,2,5,22,71,13,6.0,1,41,Urban,Manager,45808,0 +111671,Male,32,Masters,7,11,79,1,54,4.0,1,40,Urban,HR Executive,126777,0 +111672,Female,57,Masters,6,29,44,89,48,9.0,0,55,Urban,Data Analyst,27547,0 +111673,Male,37,Masters,3,88,1,42,18,8.0,1,54,Urban,ML Engineer,85450,0 +111674,Male,31,Bachelors,18,85,70,84,78,0.0,6,82,Rural,Manager,31111,1 +111675,Other,39,High School,18,32,97,50,34,2.0,0,5,Semi-Urban,ML Engineer,135089,0 +111676,Female,53,Diploma,19,11,85,83,50,4.0,7,75,Semi-Urban,Manager,69520,1 +111677,Male,38,Diploma,14,26,25,71,43,8.0,3,50,Urban,ML Engineer,144729,0 +111678,Male,51,Bachelors,2,42,14,16,40,9.0,5,7,Semi-Urban,Manager,111592,0 +111679,Male,30,Masters,5,8,4,85,63,9.0,7,88,Rural,Data Analyst,33851,0 +111680,Female,41,Bachelors,15,7,64,81,71,0.0,2,32,Urban,Manager,73326,0 +111681,Female,44,Masters,12,71,43,21,77,8.0,3,28,Urban,HR Executive,41928,0 +111682,Female,21,Diploma,10,41,96,74,70,3.0,3,99,Urban,Software Engineer,71048,1 +111683,Male,37,High School,18,51,54,4,30,2.0,0,45,Urban,HR Executive,126029,0 +111684,Female,56,Bachelors,12,9,25,22,60,0.0,3,25,Urban,Data Analyst,49823,0 +111685,Male,52,Bachelors,5,39,23,30,90,6.0,0,51,Urban,Manager,24528,0 +111686,Male,37,Bachelors,6,56,44,49,82,5.0,6,99,Urban,ML Engineer,66518,1 +111687,Male,56,Diploma,9,19,95,88,66,4.0,2,96,Semi-Urban,Software Engineer,62857,1 +111688,Female,25,High School,12,25,80,82,34,0.0,5,15,Rural,ML Engineer,48196,0 +111689,Male,43,Bachelors,11,79,16,16,88,9.0,0,72,Urban,Manager,23652,0 +111690,Male,39,Bachelors,16,25,62,37,39,1.0,5,10,Semi-Urban,Data Analyst,69480,0 +111691,Other,28,High School,1,75,38,78,98,9.0,3,66,Semi-Urban,HR Executive,54499,1 +111692,Male,39,PhD,18,98,8,11,16,1.0,1,38,Urban,Manager,33570,0 +111693,Male,45,High School,18,88,8,9,71,6.0,1,86,Semi-Urban,HR Executive,40881,0 +111694,Female,28,PhD,4,24,44,42,29,5.0,1,78,Semi-Urban,ML Engineer,22721,0 +111695,Male,33,Bachelors,0,91,79,22,75,7.0,1,61,Urban,Manager,73982,1 +111696,Male,52,Masters,14,94,20,81,52,7.0,7,14,Rural,ML Engineer,76647,0 +111697,Male,21,High School,14,14,29,59,3,6.0,2,4,Urban,Manager,136331,0 +111698,Female,44,Bachelors,13,4,62,74,82,1.0,4,90,Rural,Software Engineer,100538,0 +111699,Other,55,Diploma,6,36,45,13,94,5.0,2,98,Rural,Manager,22471,0 +111700,Female,44,Bachelors,6,37,75,7,89,2.0,1,17,Rural,ML Engineer,86444,0 +111701,Male,58,High School,9,78,25,43,68,2.0,1,15,Rural,HR Executive,58132,0 +111702,Female,34,PhD,10,96,10,9,69,8.0,6,11,Urban,HR Executive,103581,0 +111703,Female,34,Masters,4,86,57,82,37,4.0,4,49,Urban,ML Engineer,70436,1 +111704,Female,33,Diploma,16,60,8,37,72,0.0,7,3,Rural,Software Engineer,61270,0 +111705,Male,30,Diploma,1,32,45,24,77,9.0,6,31,Urban,ML Engineer,92741,0 +111706,Male,22,Diploma,13,68,28,67,91,3.0,6,2,Urban,Manager,82072,0 +111707,Male,48,Bachelors,19,87,87,6,92,9.0,0,71,Rural,ML Engineer,91828,1 +111708,Male,23,Bachelors,6,85,59,76,28,4.0,1,84,Urban,Software Engineer,55276,1 +111709,Male,26,Bachelors,11,59,50,31,87,8.0,0,51,Semi-Urban,Data Analyst,21315,0 +111710,Male,27,Bachelors,15,90,68,16,60,2.0,3,45,Semi-Urban,Software Engineer,96004,0 +111711,Female,44,Bachelors,13,57,24,95,2,5.0,6,69,Urban,Manager,98494,1 +111712,Female,53,High School,3,84,15,36,53,2.0,0,44,Rural,ML Engineer,149627,0 +111713,Female,56,High School,17,8,76,69,38,7.0,1,41,Urban,HR Executive,120224,0 +111714,Male,58,Diploma,18,78,88,59,72,5.0,0,48,Semi-Urban,Data Analyst,20954,1 +111715,Male,30,Bachelors,18,73,42,60,2,6.0,4,90,Urban,Software Engineer,140994,1 +111716,Male,41,Diploma,5,90,19,11,50,2.0,6,83,Rural,Software Engineer,107930,0 +111717,Male,58,Diploma,19,12,93,57,62,3.0,1,52,Rural,Software Engineer,50412,0 +111718,Male,58,Bachelors,12,19,49,67,52,6.0,6,55,Urban,ML Engineer,39904,0 +111719,Male,54,Bachelors,13,25,19,54,59,7.0,0,2,Rural,ML Engineer,134593,0 +111720,Male,59,PhD,12,7,84,6,0,7.0,5,66,Urban,Data Analyst,52586,0 +111721,Male,23,Diploma,13,44,83,17,21,4.0,6,32,Urban,Data Analyst,139433,0 +111722,Male,41,High School,12,94,11,2,19,3.0,5,87,Semi-Urban,Data Analyst,113153,0 +111723,Male,27,High School,8,95,98,54,24,8.0,5,26,Urban,Software Engineer,76554,1 +111724,Male,46,Bachelors,17,21,13,42,43,5.0,2,79,Rural,Data Analyst,53300,0 +111725,Female,28,Diploma,1,21,80,39,29,3.0,1,44,Rural,ML Engineer,49969,0 +111726,Female,25,Masters,13,90,59,63,12,3.0,6,62,Urban,Manager,88289,1 +111727,Female,46,Bachelors,18,3,98,43,78,3.0,0,57,Rural,ML Engineer,92161,0 +111728,Female,37,Diploma,19,32,65,1,22,5.0,6,1,Urban,Manager,88243,0 +111729,Male,49,Bachelors,6,67,35,6,27,8.0,2,27,Urban,ML Engineer,25885,0 +111730,Male,42,Bachelors,1,36,18,87,6,0.0,4,27,Semi-Urban,Software Engineer,40047,0 +111731,Male,29,Masters,0,86,44,78,24,9.0,1,76,Urban,Data Analyst,57470,1 +111732,Male,21,Bachelors,19,50,7,52,15,7.0,0,0,Urban,HR Executive,24881,0 +111733,Female,46,Bachelors,17,17,47,42,97,2.0,1,49,Rural,HR Executive,42712,0 +111734,Male,37,Bachelors,11,2,88,85,67,1.0,5,6,Semi-Urban,Software Engineer,79281,0 +111735,Female,45,PhD,19,42,58,71,18,2.0,5,26,Urban,Software Engineer,96615,0 +111736,Male,35,Masters,2,99,50,38,46,1.0,0,99,Semi-Urban,Manager,43001,1 +111737,Male,39,PhD,15,97,73,48,87,8.0,2,84,Semi-Urban,Manager,134193,1 +111738,Male,29,Masters,18,77,79,3,52,5.0,5,71,Urban,Software Engineer,126420,0 +111739,Female,22,Bachelors,8,81,23,61,83,0.0,2,88,Urban,Data Analyst,79263,1 +111740,Male,42,Bachelors,5,88,60,40,88,0.0,0,55,Semi-Urban,Software Engineer,33936,1 +111741,Male,38,Masters,13,87,14,34,99,6.0,4,82,Rural,Software Engineer,121888,0 +111742,Female,52,High School,9,3,38,63,71,6.0,2,62,Urban,Data Analyst,42717,0 +111743,Female,41,Bachelors,13,6,89,31,90,2.0,4,70,Urban,Software Engineer,132735,0 +111744,Male,23,Bachelors,0,68,16,44,99,9.0,6,11,Urban,Data Analyst,56659,0 +111745,Male,31,Masters,1,56,85,18,42,0.0,3,26,Semi-Urban,Data Analyst,117701,0 +111746,Male,55,Bachelors,5,10,97,8,67,9.0,7,20,Urban,Data Analyst,145882,0 +111747,Female,33,Bachelors,16,28,6,34,49,2.0,2,64,Urban,Data Analyst,55760,0 +111748,Male,23,Diploma,9,36,71,89,83,4.0,3,30,Semi-Urban,Software Engineer,33070,0 +111749,Female,26,Masters,6,90,14,80,63,9.0,1,20,Semi-Urban,Software Engineer,144085,0 +111750,Female,38,PhD,8,8,5,25,6,3.0,1,31,Urban,Software Engineer,94930,0 +111751,Male,49,High School,3,3,94,90,10,0.0,4,89,Urban,Data Analyst,73846,1 +111752,Male,39,High School,15,71,17,73,83,5.0,7,12,Rural,HR Executive,29007,0 +111753,Male,53,Bachelors,19,55,71,37,43,3.0,0,16,Urban,HR Executive,38223,0 +111754,Male,29,PhD,19,65,23,31,49,8.0,0,61,Urban,Software Engineer,145471,0 +111755,Female,25,Masters,18,56,42,8,75,5.0,1,42,Urban,Data Analyst,30899,0 +111756,Female,38,Diploma,14,31,44,57,73,4.0,1,27,Urban,ML Engineer,24686,0 +111757,Female,50,Masters,9,69,24,43,39,5.0,0,31,Urban,HR Executive,93339,0 +111758,Female,37,Masters,2,20,54,71,21,6.0,0,92,Semi-Urban,HR Executive,52671,0 +111759,Male,23,High School,14,49,58,92,3,8.0,0,3,Urban,Manager,27884,0 +111760,Male,29,High School,2,98,78,29,42,2.0,7,79,Semi-Urban,Software Engineer,135666,1 +111761,Male,45,Bachelors,1,61,55,0,61,6.0,6,68,Urban,HR Executive,141588,0 +111762,Female,36,Bachelors,9,1,90,35,37,6.0,1,45,Semi-Urban,ML Engineer,55424,0 +111763,Male,39,Masters,1,87,67,61,72,2.0,5,63,Urban,ML Engineer,129614,1 +111764,Male,21,Bachelors,3,77,36,1,86,3.0,7,54,Urban,Data Analyst,117039,0 +111765,Female,38,Bachelors,4,35,93,49,21,4.0,3,40,Rural,Data Analyst,128480,0 +111766,Male,56,High School,19,70,62,61,7,0.0,3,90,Rural,Data Analyst,108738,1 +111767,Female,29,Diploma,16,95,16,10,90,7.0,2,25,Urban,Manager,71352,0 +111768,Male,54,Bachelors,0,0,29,11,58,4.0,6,56,Rural,Manager,141078,0 +111769,Female,53,Bachelors,0,49,83,93,66,9.0,6,90,Semi-Urban,Manager,30493,1 +111770,Male,30,Diploma,13,5,8,4,29,9.0,4,34,Rural,Data Analyst,126574,0 +111771,Female,34,Masters,10,24,86,44,68,3.0,1,0,Urban,Data Analyst,99122,0 +111772,Male,50,High School,1,70,58,61,70,1.0,3,52,Rural,HR Executive,86315,1 +111773,Male,21,Masters,18,26,13,14,9,9.0,7,10,Urban,ML Engineer,45629,0 +111774,Female,34,Masters,0,52,48,70,49,3.0,1,34,Urban,Manager,127111,0 +111775,Male,31,Bachelors,0,66,25,47,9,9.0,2,76,Rural,ML Engineer,140997,0 +111776,Male,34,Masters,2,0,37,51,40,8.0,7,47,Rural,Manager,139057,0 +111777,Male,34,Masters,4,1,4,0,8,0.0,0,36,Urban,ML Engineer,143336,0 +111778,Other,45,Masters,19,12,27,75,29,4.0,0,1,Urban,ML Engineer,48753,0 +111779,Female,36,Bachelors,8,48,75,99,25,2.0,3,20,Urban,Data Analyst,122885,1 +111780,Male,28,Bachelors,4,19,54,43,27,9.0,5,44,Urban,Manager,58104,0 +111781,Male,27,High School,7,46,89,30,12,6.0,3,70,Urban,Data Analyst,120312,1 +111782,Female,38,Masters,1,95,21,61,16,8.0,4,80,Urban,Software Engineer,68149,1 +111783,Female,47,High School,14,70,23,75,58,7.0,2,5,Semi-Urban,Manager,112164,0 +111784,Male,47,Bachelors,10,66,55,34,80,8.0,1,20,Semi-Urban,Software Engineer,132471,0 +111785,Male,31,Masters,14,5,54,98,64,3.0,7,64,Semi-Urban,Software Engineer,73056,0 +111786,Male,37,PhD,3,34,18,72,88,9.0,6,52,Semi-Urban,ML Engineer,45282,0 +111787,Male,34,Diploma,19,40,27,99,29,1.0,4,85,Semi-Urban,ML Engineer,131537,1 +111788,Other,23,Diploma,0,96,25,96,94,2.0,5,80,Rural,Manager,21746,1 +111789,Female,23,Bachelors,2,25,59,54,10,4.0,1,68,Urban,Data Analyst,149230,0 +111790,Male,32,Masters,17,33,15,17,39,8.0,5,47,Urban,ML Engineer,64630,0 +111791,Male,29,Bachelors,12,34,63,60,64,4.0,3,3,Urban,HR Executive,21079,0 +111792,Female,32,PhD,14,51,58,69,76,3.0,3,96,Urban,HR Executive,82410,1 +111793,Female,52,Bachelors,17,69,85,12,82,5.0,7,49,Rural,Software Engineer,67475,0 +111794,Male,21,PhD,5,92,64,61,67,6.0,2,9,Semi-Urban,ML Engineer,53128,0 +111795,Male,35,Bachelors,15,21,9,75,25,4.0,7,37,Urban,ML Engineer,117036,0 +111796,Male,58,High School,18,68,74,9,31,2.0,7,54,Urban,Data Analyst,69326,0 +111797,Male,49,Bachelors,12,40,68,91,98,0.0,5,55,Semi-Urban,HR Executive,145151,1 +111798,Male,32,Bachelors,3,13,3,83,71,8.0,7,24,Urban,Software Engineer,106683,0 +111799,Male,59,Bachelors,14,76,74,84,85,7.0,0,6,Rural,Manager,38908,1 +111800,Male,44,Masters,18,26,0,34,69,1.0,3,33,Urban,Data Analyst,37685,0 +111801,Male,27,Bachelors,9,26,74,91,26,9.0,0,96,Semi-Urban,ML Engineer,87928,1 +111802,Male,31,Diploma,7,15,68,87,36,5.0,6,95,Urban,ML Engineer,50367,1 +111803,Male,34,Masters,13,25,94,81,25,6.0,4,0,Urban,HR Executive,107564,0 +111804,Male,33,Bachelors,13,9,37,57,85,0.0,0,99,Urban,Manager,114797,0 +111805,Male,46,Bachelors,7,4,85,93,22,7.0,5,42,Semi-Urban,ML Engineer,22972,0 +111806,Male,21,Masters,14,6,48,49,18,6.0,4,60,Urban,Software Engineer,94905,0 +111807,Male,59,High School,10,91,73,40,23,1.0,6,90,Urban,Data Analyst,99099,1 +111808,Female,50,Bachelors,11,29,44,41,0,7.0,5,87,Urban,HR Executive,144841,0 +111809,Male,44,PhD,2,46,67,9,85,5.0,4,59,Rural,Software Engineer,42471,0 +111810,Female,32,High School,14,67,39,0,63,4.0,6,81,Urban,ML Engineer,105723,0 +111811,Male,26,Bachelors,7,48,4,57,71,1.0,1,55,Urban,ML Engineer,33998,0 +111812,Female,47,Bachelors,15,36,70,62,93,7.0,3,51,Urban,Software Engineer,147771,0 +111813,Female,41,Bachelors,10,59,62,56,35,5.0,1,74,Urban,HR Executive,52854,1 +111814,Male,27,Bachelors,14,60,46,72,9,4.0,1,58,Urban,HR Executive,23144,1 +111815,Female,37,High School,9,75,63,17,8,6.0,7,55,Urban,ML Engineer,60331,0 +111816,Male,38,Diploma,15,10,84,55,66,1.0,0,13,Rural,Software Engineer,53713,0 +111817,Female,40,High School,17,9,10,33,20,2.0,1,4,Urban,ML Engineer,28345,0 +111818,Female,40,High School,18,65,87,77,66,7.0,4,28,Urban,Data Analyst,146648,1 +111819,Male,45,Bachelors,16,96,91,97,51,8.0,5,29,Semi-Urban,Manager,44158,1 +111820,Male,49,Bachelors,19,5,97,69,47,6.0,1,89,Urban,HR Executive,121698,1 +111821,Female,28,Diploma,7,21,20,32,50,7.0,3,26,Urban,ML Engineer,147634,0 +111822,Male,23,High School,10,0,70,99,89,5.0,2,93,Semi-Urban,HR Executive,67999,1 +111823,Male,26,Bachelors,12,36,69,99,82,0.0,4,24,Urban,Data Analyst,34222,0 +111824,Female,36,High School,13,59,79,37,2,9.0,4,16,Urban,Software Engineer,30998,0 +111825,Male,25,Bachelors,11,1,21,55,13,9.0,5,33,Urban,Manager,69136,0 +111826,Male,55,Bachelors,18,19,36,51,32,3.0,4,92,Urban,Manager,78596,0 +111827,Male,23,Bachelors,18,52,40,64,38,0.0,5,74,Rural,Manager,139015,0 +111828,Male,41,Bachelors,11,70,48,82,65,7.0,4,92,Rural,Software Engineer,102838,1 +111829,Other,40,Diploma,3,89,73,14,97,0.0,6,71,Semi-Urban,Manager,54157,1 +111830,Female,31,Masters,17,73,73,87,30,4.0,5,48,Urban,Manager,121397,1 +111831,Male,22,PhD,19,18,84,68,80,6.0,7,73,Rural,Manager,100040,1 +111832,Male,43,Bachelors,6,82,93,57,79,5.0,2,63,Rural,HR Executive,63805,1 +111833,Female,50,Masters,1,61,94,39,22,4.0,7,60,Rural,HR Executive,67999,1 +111834,Male,53,Masters,16,40,40,46,96,9.0,1,14,Rural,Data Analyst,127863,0 +111835,Male,45,Bachelors,8,89,92,96,48,8.0,1,33,Rural,Software Engineer,116382,1 +111836,Male,49,Diploma,5,78,83,3,48,9.0,3,80,Semi-Urban,Software Engineer,89264,1 +111837,Male,54,Diploma,2,53,3,70,0,5.0,6,49,Urban,Manager,105917,0 +111838,Female,25,Bachelors,6,47,22,25,51,1.0,1,44,Rural,HR Executive,86909,0 +111839,Female,28,Bachelors,13,56,90,79,78,7.0,3,95,Semi-Urban,ML Engineer,127196,1 +111840,Male,25,High School,17,68,63,0,24,0.0,0,2,Rural,Software Engineer,58989,0 +111841,Other,59,Bachelors,2,20,73,85,48,9.0,2,6,Urban,Data Analyst,114380,0 +111842,Male,32,Diploma,14,10,96,13,83,3.0,1,75,Semi-Urban,ML Engineer,81494,0 +111843,Male,49,Bachelors,19,64,12,5,93,7.0,1,52,Semi-Urban,ML Engineer,98872,0 +111844,Male,55,Masters,10,90,60,42,82,1.0,0,36,Rural,Manager,122612,0 +111845,Male,44,Bachelors,6,43,78,71,21,2.0,5,3,Semi-Urban,Manager,65990,0 +111846,Male,56,High School,8,26,23,27,37,9.0,2,44,Rural,HR Executive,121180,0 +111847,Male,27,Diploma,17,71,58,57,9,2.0,0,84,Urban,ML Engineer,100570,1 +111848,Female,56,Bachelors,3,36,57,22,54,5.0,4,8,Semi-Urban,ML Engineer,134736,0 +111849,Female,50,Masters,6,5,43,12,88,0.0,4,63,Semi-Urban,Data Analyst,106524,0 +111850,Male,44,High School,3,18,35,10,90,5.0,4,92,Semi-Urban,Software Engineer,76083,0 +111851,Male,51,High School,10,23,4,49,60,6.0,5,78,Urban,Software Engineer,148601,0 +111852,Male,57,Diploma,2,98,65,85,10,2.0,5,92,Urban,ML Engineer,137178,1 +111853,Male,53,Masters,5,1,11,66,63,9.0,7,20,Rural,ML Engineer,134882,0 +111854,Male,58,Diploma,1,28,89,13,10,4.0,6,91,Urban,ML Engineer,142065,0 +111855,Male,30,Masters,16,53,66,11,45,2.0,1,9,Urban,Manager,111421,0 +111856,Male,41,Diploma,3,3,96,12,85,3.0,0,40,Urban,Manager,98744,0 +111857,Male,39,High School,18,99,38,89,48,2.0,6,3,Semi-Urban,HR Executive,117897,0 +111858,Female,52,Masters,15,49,22,40,27,2.0,2,32,Semi-Urban,Software Engineer,62537,0 +111859,Male,26,Masters,4,78,97,72,15,7.0,2,52,Rural,HR Executive,146989,1 +111860,Male,56,Bachelors,14,56,29,25,44,0.0,5,66,Urban,HR Executive,62639,0 +111861,Male,50,Diploma,19,31,82,15,83,4.0,0,67,Rural,Data Analyst,50012,0 +111862,Male,28,PhD,4,12,21,64,12,1.0,4,84,Rural,ML Engineer,43955,0 +111863,Male,36,Bachelors,11,84,6,78,71,8.0,3,24,Urban,Manager,69515,0 +111864,Female,56,Bachelors,12,91,94,59,55,6.0,5,46,Semi-Urban,HR Executive,79456,1 +111865,Male,58,Diploma,1,69,58,80,13,3.0,6,22,Semi-Urban,HR Executive,138518,0 +111866,Male,46,High School,12,75,10,27,21,9.0,6,91,Urban,Manager,116028,0 +111867,Female,29,Masters,8,65,69,30,9,2.0,1,60,Semi-Urban,HR Executive,59039,0 +111868,Female,58,Bachelors,9,36,42,5,52,4.0,5,64,Rural,ML Engineer,30612,0 +111869,Female,45,Bachelors,1,38,62,57,74,3.0,6,1,Rural,HR Executive,47898,0 +111870,Male,32,Bachelors,3,10,72,21,68,2.0,1,7,Urban,Manager,107862,0 +111871,Male,21,Diploma,11,91,49,35,44,3.0,0,85,Urban,Data Analyst,118281,1 +111872,Other,53,Diploma,8,83,75,23,89,8.0,5,50,Urban,HR Executive,61207,0 +111873,Male,55,Masters,1,44,85,86,15,9.0,2,62,Urban,HR Executive,96862,1 +111874,Male,35,Diploma,15,22,72,19,15,3.0,0,39,Urban,HR Executive,119640,0 +111875,Male,56,Bachelors,9,1,6,34,7,3.0,6,51,Urban,Software Engineer,22791,0 +111876,Male,27,Diploma,5,82,8,67,98,2.0,0,73,Urban,Data Analyst,62124,0 +111877,Male,34,PhD,4,94,40,43,16,1.0,3,0,Urban,Data Analyst,131646,0 +111878,Female,26,Diploma,7,1,75,33,24,5.0,0,80,Urban,Data Analyst,79809,0 +111879,Female,21,High School,9,70,42,86,49,0.0,3,35,Urban,Software Engineer,60969,0 +111880,Male,45,Bachelors,14,19,5,4,71,5.0,1,15,Semi-Urban,Software Engineer,35021,0 +111881,Female,23,PhD,17,57,54,98,68,5.0,3,45,Urban,Manager,95344,1 +111882,Male,50,Diploma,2,88,31,27,11,1.0,4,85,Urban,Manager,92147,0 +111883,Male,38,High School,8,79,54,28,85,4.0,4,21,Rural,HR Executive,115995,0 +111884,Male,52,Diploma,3,92,92,85,33,8.0,3,90,Urban,ML Engineer,147594,1 +111885,Other,56,Masters,8,8,80,55,84,4.0,1,65,Urban,Data Analyst,45433,0 +111886,Male,54,High School,4,60,58,50,5,7.0,2,89,Semi-Urban,HR Executive,93956,1 +111887,Male,28,High School,16,38,13,72,27,8.0,3,31,Rural,Manager,69188,0 +111888,Male,57,Bachelors,12,5,83,88,76,1.0,5,33,Urban,Manager,115370,0 +111889,Male,54,High School,17,30,6,70,24,0.0,3,84,Urban,HR Executive,131779,0 +111890,Female,27,Masters,5,94,19,61,87,4.0,0,17,Semi-Urban,HR Executive,93124,0 +111891,Female,29,Masters,7,65,55,8,59,5.0,3,39,Urban,ML Engineer,120549,0 +111892,Female,29,High School,12,59,22,54,14,6.0,7,19,Rural,Data Analyst,54424,0 +111893,Male,34,Bachelors,11,41,45,27,4,0.0,3,57,Urban,HR Executive,39463,0 +111894,Male,38,Masters,13,17,20,62,31,3.0,0,31,Urban,Manager,82490,0 +111895,Male,50,Bachelors,8,78,19,53,67,1.0,5,26,Urban,HR Executive,108556,0 +111896,Other,50,High School,6,43,26,16,40,4.0,3,34,Urban,HR Executive,51805,0 +111897,Male,35,High School,14,40,80,6,47,3.0,5,74,Urban,ML Engineer,121101,0 +111898,Male,37,Diploma,9,33,16,20,14,9.0,5,80,Semi-Urban,Software Engineer,121590,0 +111899,Male,29,Bachelors,15,82,24,52,56,4.0,1,46,Rural,Software Engineer,56744,0 +111900,Female,52,Bachelors,0,94,16,58,22,3.0,2,2,Urban,Software Engineer,145069,0 +111901,Female,54,Bachelors,4,9,52,66,67,3.0,4,10,Urban,Software Engineer,30277,0 +111902,Other,41,Masters,12,35,82,98,35,4.0,1,57,Urban,HR Executive,108495,1 +111903,Male,29,Bachelors,9,61,70,10,31,8.0,1,33,Rural,ML Engineer,115844,0 +111904,Male,25,Masters,4,50,35,62,94,1.0,7,99,Rural,Data Analyst,91962,1 +111905,Male,28,Diploma,16,89,94,77,65,8.0,5,39,Urban,Data Analyst,62878,1 +111906,Male,45,Bachelors,9,20,37,77,34,9.0,7,91,Semi-Urban,Software Engineer,30354,0 +111907,Male,51,Bachelors,17,34,19,78,75,1.0,6,34,Semi-Urban,ML Engineer,56969,0 +111908,Female,31,PhD,14,20,4,34,41,7.0,4,28,Urban,Manager,98930,0 +111909,Male,56,Masters,0,37,40,33,14,0.0,6,25,Urban,Software Engineer,23498,0 +111910,Male,49,Bachelors,15,21,14,66,73,9.0,6,11,Urban,Data Analyst,91328,0 +111911,Male,21,Bachelors,12,36,60,85,87,4.0,4,65,Rural,Data Analyst,39185,1 +111912,Female,23,Masters,12,33,53,92,0,8.0,5,6,Semi-Urban,Software Engineer,20814,0 +111913,Male,42,Masters,17,88,59,20,39,7.0,0,27,Urban,HR Executive,30971,0 +111914,Male,35,Diploma,16,13,68,40,38,9.0,7,85,Semi-Urban,Software Engineer,98073,0 +111915,Male,21,Diploma,1,65,77,46,23,0.0,4,3,Urban,Data Analyst,96541,0 +111916,Male,41,Bachelors,12,66,70,96,98,4.0,2,34,Urban,HR Executive,30994,1 +111917,Female,59,Diploma,5,15,71,90,32,1.0,1,78,Semi-Urban,Software Engineer,74049,1 +111918,Female,39,Diploma,8,19,40,83,15,9.0,6,0,Urban,Data Analyst,141350,0 +111919,Male,51,Diploma,16,72,74,1,67,2.0,0,47,Urban,Software Engineer,54169,0 +111920,Male,43,Masters,11,31,69,7,67,4.0,2,40,Semi-Urban,Software Engineer,126499,0 +111921,Male,44,Bachelors,16,54,95,12,17,0.0,5,46,Urban,Manager,82610,0 +111922,Female,39,Bachelors,9,17,65,77,93,9.0,3,14,Semi-Urban,Manager,54317,0 +111923,Male,54,Bachelors,4,24,4,62,89,6.0,5,74,Semi-Urban,ML Engineer,90947,0 +111924,Male,29,High School,0,74,15,6,17,6.0,4,44,Semi-Urban,Data Analyst,85318,0 +111925,Male,55,Bachelors,13,14,40,33,67,1.0,4,5,Urban,ML Engineer,43059,0 +111926,Male,22,Bachelors,17,93,98,61,46,2.0,2,2,Rural,Data Analyst,46480,1 +111927,Male,52,Diploma,15,43,27,57,17,7.0,5,93,Urban,ML Engineer,72890,0 +111928,Female,45,Bachelors,11,14,21,51,52,6.0,6,38,Semi-Urban,ML Engineer,76741,0 +111929,Female,27,Diploma,1,31,12,46,64,3.0,0,49,Urban,ML Engineer,132614,0 +111930,Male,28,Bachelors,4,20,96,69,11,8.0,3,19,Urban,Manager,21933,0 +111931,Female,51,Bachelors,3,46,65,64,28,6.0,2,7,Urban,HR Executive,113372,0 +111932,Male,49,Masters,3,32,44,31,3,5.0,5,57,Semi-Urban,HR Executive,75857,0 +111933,Female,26,Bachelors,12,42,6,9,7,2.0,1,50,Urban,HR Executive,23974,0 +111934,Female,56,Masters,10,44,26,20,32,1.0,2,82,Rural,ML Engineer,37849,0 +111935,Male,22,Diploma,9,4,99,92,93,5.0,6,43,Urban,Data Analyst,99251,1 +111936,Female,26,Bachelors,10,53,88,25,26,9.0,4,52,Urban,Data Analyst,20505,0 +111937,Male,23,Bachelors,11,74,41,38,39,5.0,3,75,Urban,Software Engineer,146083,0 +111938,Male,50,High School,4,23,54,63,73,8.0,1,18,Semi-Urban,ML Engineer,27760,0 +111939,Male,48,Diploma,1,76,69,64,76,4.0,7,83,Urban,Data Analyst,134442,1 +111940,Female,25,Bachelors,4,66,51,94,40,2.0,2,67,Semi-Urban,Data Analyst,146957,1 +111941,Female,55,PhD,6,25,93,11,82,6.0,6,53,Semi-Urban,ML Engineer,74112,0 +111942,Male,51,Bachelors,10,71,36,29,51,1.0,6,35,Rural,Manager,94087,0 +111943,Male,55,Masters,6,72,79,81,6,2.0,7,52,Urban,ML Engineer,111663,1 +111944,Male,34,Diploma,15,0,24,42,10,7.0,3,9,Rural,HR Executive,55350,0 +111945,Male,42,Bachelors,10,10,2,94,17,5.0,4,42,Urban,HR Executive,105815,0 +111946,Male,35,High School,11,98,77,26,72,4.0,3,92,Semi-Urban,Manager,77580,1 +111947,Male,28,Bachelors,0,49,1,49,16,2.0,0,23,Semi-Urban,HR Executive,79915,0 +111948,Female,38,Bachelors,4,59,14,7,83,9.0,4,81,Urban,Data Analyst,110821,0 +111949,Female,36,Masters,7,30,94,91,98,9.0,7,15,Semi-Urban,Data Analyst,83828,0 +111950,Male,24,Masters,12,48,59,52,47,5.0,6,94,Urban,Data Analyst,62011,1 +111951,Male,21,Bachelors,13,96,64,60,13,9.0,6,38,Urban,ML Engineer,44926,1 +111952,Male,34,Bachelors,19,56,14,74,39,8.0,4,8,Urban,ML Engineer,131067,0 +111953,Male,21,Diploma,16,29,53,60,16,4.0,5,88,Semi-Urban,ML Engineer,72397,0 +111954,Female,35,Bachelors,11,71,55,13,21,2.0,1,17,Semi-Urban,Data Analyst,82726,0 +111955,Female,58,Bachelors,13,16,18,52,23,5.0,7,80,Urban,Manager,28713,0 +111956,Female,21,Bachelors,14,86,89,71,70,6.0,5,0,Semi-Urban,HR Executive,93661,1 +111957,Male,55,Bachelors,3,44,24,17,90,0.0,6,76,Semi-Urban,ML Engineer,107342,0 +111958,Male,37,Masters,2,10,2,31,55,1.0,2,80,Urban,Software Engineer,109766,0 +111959,Male,54,High School,11,28,52,35,68,9.0,0,73,Urban,HR Executive,31133,0 +111960,Female,43,Diploma,7,76,85,92,71,6.0,6,52,Semi-Urban,Data Analyst,95893,1 +111961,Male,58,High School,11,3,55,74,62,2.0,2,37,Rural,Manager,122457,0 +111962,Female,29,Bachelors,14,82,57,87,82,3.0,2,71,Rural,HR Executive,133054,1 +111963,Female,28,Bachelors,7,29,84,8,69,1.0,1,31,Rural,Manager,60249,0 +111964,Male,22,Bachelors,18,3,97,93,9,1.0,4,0,Urban,HR Executive,54218,0 +111965,Female,57,Bachelors,13,34,40,3,52,1.0,2,48,Urban,Data Analyst,106913,0 +111966,Female,36,Bachelors,3,62,53,67,20,9.0,1,43,Urban,HR Executive,133642,0 +111967,Male,43,Bachelors,12,15,39,23,81,1.0,3,28,Urban,Software Engineer,77612,0 +111968,Male,33,High School,8,6,15,90,24,6.0,6,71,Urban,ML Engineer,122356,0 +111969,Male,29,Diploma,13,17,47,25,37,0.0,7,90,Rural,Software Engineer,127022,0 +111970,Other,44,High School,7,90,58,28,45,5.0,1,92,Urban,Manager,101381,1 +111971,Female,54,Masters,16,54,74,90,70,2.0,6,28,Urban,ML Engineer,85364,1 +111972,Female,57,Masters,4,74,98,99,59,2.0,4,14,Urban,ML Engineer,24155,1 +111973,Male,46,PhD,12,22,92,29,4,9.0,4,48,Urban,ML Engineer,41938,0 +111974,Female,49,Masters,12,92,16,85,27,7.0,6,31,Urban,Manager,130936,0 +111975,Female,39,Masters,11,66,93,72,38,7.0,7,5,Semi-Urban,HR Executive,144276,0 +111976,Male,22,High School,11,89,30,34,79,5.0,2,96,Urban,Software Engineer,32017,1 +111977,Female,39,Bachelors,10,68,21,60,51,3.0,4,3,Rural,Software Engineer,82496,0 +111978,Male,32,Masters,17,44,42,90,16,9.0,1,30,Urban,Software Engineer,35257,0 +111979,Female,37,Masters,15,52,36,51,57,8.0,1,19,Urban,Software Engineer,87966,0 +111980,Male,44,Masters,4,2,92,36,73,7.0,4,3,Rural,Software Engineer,126570,0 +111981,Female,37,Bachelors,8,93,65,3,4,4.0,5,12,Urban,Manager,37345,0 +111982,Male,21,PhD,13,85,47,83,43,3.0,7,32,Urban,Data Analyst,39468,1 +111983,Male,26,Masters,18,61,99,41,45,6.0,1,86,Urban,HR Executive,127243,1 +111984,Female,25,Diploma,5,95,5,20,28,3.0,4,51,Urban,ML Engineer,64185,0 +111985,Male,23,Masters,12,77,3,5,98,3.0,2,36,Urban,HR Executive,136868,0 +111986,Other,45,Bachelors,6,10,71,45,45,9.0,7,23,Urban,HR Executive,84544,0 +111987,Female,45,Diploma,7,48,31,54,51,6.0,0,15,Urban,HR Executive,125155,0 +111988,Male,37,High School,19,88,83,96,28,2.0,7,94,Urban,Manager,71511,1 +111989,Female,51,Masters,9,43,6,6,44,2.0,1,15,Rural,Software Engineer,126646,0 +111990,Male,57,High School,0,84,62,41,56,7.0,1,9,Urban,HR Executive,20117,0 +111991,Male,52,Masters,14,19,63,41,65,5.0,3,73,Rural,Manager,110354,0 +111992,Male,34,Bachelors,17,60,94,53,23,6.0,3,22,Urban,Data Analyst,84954,0 +111993,Male,49,High School,15,8,88,59,3,3.0,5,64,Rural,Software Engineer,36657,0 +111994,Female,44,High School,1,96,38,53,47,8.0,7,34,Urban,Manager,92454,0 +111995,Male,35,Masters,16,33,20,17,18,1.0,4,63,Semi-Urban,Manager,147264,0 +111996,Female,32,High School,6,10,92,96,22,1.0,5,75,Urban,ML Engineer,35632,1 +111997,Female,37,Masters,15,95,74,84,38,2.0,1,63,Urban,ML Engineer,67111,1 +111998,Male,48,PhD,13,53,28,13,88,0.0,4,96,Rural,ML Engineer,55370,0 +111999,Other,47,Bachelors,4,23,65,78,8,5.0,3,71,Urban,Data Analyst,59810,0 +112000,Female,57,Masters,1,75,71,90,3,3.0,4,38,Urban,Data Analyst,65816,1 +112001,Male,27,PhD,12,12,45,96,87,0.0,5,18,Rural,HR Executive,33830,0 +112002,Male,33,Diploma,6,24,69,94,37,9.0,2,8,Urban,ML Engineer,112768,0 +112003,Female,50,High School,18,51,38,8,91,8.0,7,60,Semi-Urban,ML Engineer,119839,0 +112004,Female,27,High School,0,18,24,47,25,6.0,1,28,Semi-Urban,HR Executive,100766,0 +112005,Female,30,Diploma,17,77,33,32,31,3.0,7,39,Urban,Software Engineer,117189,0 +112006,Other,52,PhD,14,70,41,58,30,0.0,1,29,Rural,Manager,144012,0 +112007,Male,56,High School,0,45,57,3,65,4.0,7,14,Urban,Manager,116946,0 +112008,Male,45,PhD,18,21,27,81,58,0.0,5,76,Urban,ML Engineer,98982,0 +112009,Male,36,Diploma,17,17,31,8,81,9.0,4,98,Rural,HR Executive,24074,0 +112010,Male,57,Bachelors,17,47,34,62,26,9.0,6,95,Urban,Manager,109648,1 +112011,Female,42,Masters,12,93,15,75,25,9.0,7,49,Urban,Manager,57869,0 +112012,Male,23,Bachelors,7,17,52,98,22,4.0,0,72,Urban,Manager,39996,1 +112013,Male,27,Bachelors,3,80,58,20,64,9.0,5,84,Urban,Manager,94832,1 +112014,Other,27,Masters,2,69,86,96,77,9.0,5,19,Rural,Data Analyst,99065,1 +112015,Female,49,High School,2,44,35,96,15,0.0,3,24,Urban,Data Analyst,43429,0 +112016,Male,21,Bachelors,19,0,31,19,89,0.0,7,78,Rural,Manager,147581,0 +112017,Female,51,Bachelors,10,13,47,23,59,2.0,5,21,Urban,HR Executive,57900,0 +112018,Male,39,Bachelors,16,92,57,42,5,1.0,5,53,Urban,Software Engineer,122363,1 +112019,Female,31,Bachelors,3,20,56,59,37,0.0,0,4,Urban,Data Analyst,97936,0 +112020,Male,47,Bachelors,4,73,15,24,38,2.0,2,91,Semi-Urban,ML Engineer,69247,0 +112021,Male,27,Bachelors,11,91,36,19,97,6.0,0,57,Rural,Manager,43553,0 +112022,Female,50,Bachelors,11,83,48,7,72,8.0,7,69,Rural,Manager,42836,0 +112023,Female,53,High School,2,48,45,4,82,6.0,7,18,Rural,HR Executive,141564,0 +112024,Female,33,Bachelors,6,75,33,30,51,1.0,7,74,Urban,Software Engineer,38202,0 +112025,Female,36,Diploma,1,23,63,0,10,1.0,0,88,Urban,Manager,80959,0 +112026,Male,54,Diploma,18,62,19,50,10,6.0,5,62,Urban,Data Analyst,103114,0 +112027,Female,23,High School,8,74,66,13,84,6.0,0,28,Urban,HR Executive,111212,0 +112028,Male,24,Bachelors,17,34,74,87,34,1.0,1,29,Urban,Software Engineer,89285,0 +112029,Female,22,High School,6,22,3,0,68,5.0,7,98,Urban,Software Engineer,64397,0 +112030,Male,28,High School,14,78,98,62,62,2.0,5,23,Urban,Software Engineer,22193,1 +112031,Male,23,Bachelors,1,37,89,84,42,2.0,1,80,Urban,ML Engineer,91131,1 +112032,Female,32,Diploma,9,55,30,5,60,2.0,7,57,Rural,Software Engineer,57759,0 +112033,Male,54,Bachelors,11,22,16,34,65,1.0,4,18,Semi-Urban,Software Engineer,124046,0 +112034,Female,25,Bachelors,14,91,14,94,47,5.0,7,11,Urban,ML Engineer,80659,0 +112035,Male,51,Diploma,4,25,34,62,91,9.0,4,14,Urban,Manager,88243,0 +112036,Female,30,Bachelors,18,18,61,88,91,7.0,5,19,Urban,Manager,60167,0 +112037,Male,35,Masters,11,25,6,13,19,0.0,7,65,Urban,HR Executive,66625,0 +112038,Female,21,Bachelors,3,39,60,85,20,4.0,5,51,Urban,Software Engineer,23002,0 +112039,Female,22,Diploma,19,11,62,71,71,4.0,4,15,Urban,ML Engineer,141155,0 +112040,Female,49,Masters,10,73,71,32,92,1.0,1,75,Rural,Data Analyst,23227,1 +112041,Male,59,Bachelors,5,7,29,37,46,4.0,5,17,Semi-Urban,Manager,31838,0 +112042,Female,21,High School,19,64,57,12,18,6.0,0,84,Urban,Software Engineer,56158,0 +112043,Female,55,Bachelors,4,77,85,6,24,3.0,3,55,Urban,Software Engineer,149795,0 +112044,Female,34,Bachelors,4,54,72,62,46,0.0,4,44,Semi-Urban,Manager,28016,0 +112045,Male,21,PhD,13,35,34,66,9,8.0,6,6,Urban,ML Engineer,131610,0 +112046,Other,52,Bachelors,8,69,16,27,9,6.0,1,2,Semi-Urban,Software Engineer,110833,0 +112047,Female,57,High School,11,90,4,11,34,0.0,2,71,Urban,ML Engineer,84117,0 +112048,Male,36,Masters,6,77,72,40,68,6.0,1,56,Rural,HR Executive,83445,1 +112049,Male,51,PhD,17,69,96,78,39,5.0,1,90,Urban,HR Executive,108215,1 +112050,Female,54,Masters,2,24,76,87,14,2.0,2,41,Urban,Software Engineer,72776,0 +112051,Male,26,Masters,19,52,74,21,29,2.0,6,25,Urban,Data Analyst,61091,0 +112052,Male,23,Bachelors,10,14,44,39,60,4.0,2,97,Semi-Urban,Software Engineer,147793,0 +112053,Female,26,High School,7,40,12,51,79,8.0,4,52,Urban,ML Engineer,47292,0 +112054,Male,43,Diploma,14,20,6,41,16,9.0,1,82,Urban,Manager,50165,0 +112055,Male,31,Masters,4,47,78,12,51,5.0,6,31,Semi-Urban,ML Engineer,93379,0 +112056,Male,45,Bachelors,16,34,29,89,10,1.0,5,95,Rural,Data Analyst,94699,1 +112057,Male,39,Bachelors,0,50,26,92,52,6.0,3,62,Urban,HR Executive,117824,0 +112058,Male,58,Masters,18,56,95,92,12,9.0,4,92,Urban,ML Engineer,113248,1 +112059,Female,25,PhD,10,32,80,35,25,3.0,4,52,Urban,HR Executive,123058,0 +112060,Male,25,Bachelors,11,97,97,62,0,3.0,6,0,Rural,Data Analyst,143613,1 +112061,Male,56,Masters,10,97,83,84,89,1.0,0,21,Urban,ML Engineer,54579,1 +112062,Female,34,Bachelors,18,50,76,37,35,1.0,6,18,Semi-Urban,Data Analyst,46659,0 +112063,Male,26,Masters,17,15,69,43,5,8.0,4,49,Urban,HR Executive,120713,0 +112064,Male,46,High School,1,17,78,19,73,3.0,4,73,Urban,Software Engineer,71641,0 +112065,Male,35,Bachelors,19,0,71,63,99,2.0,1,5,Urban,Manager,149759,0 +112066,Other,28,Diploma,19,53,25,97,96,0.0,6,93,Urban,ML Engineer,87426,1 +112067,Male,48,Bachelors,17,92,78,38,72,3.0,5,80,Urban,Software Engineer,50969,1 +112068,Male,48,PhD,10,60,70,51,45,9.0,6,84,Rural,HR Executive,132034,1 +112069,Female,54,Bachelors,10,53,17,37,60,4.0,2,3,Semi-Urban,Software Engineer,25938,0 +112070,Female,37,Masters,14,97,38,94,78,1.0,4,85,Rural,Manager,126036,1 +112071,Other,56,Masters,12,14,3,25,14,7.0,0,87,Semi-Urban,HR Executive,61229,0 +112072,Female,37,Diploma,15,33,40,57,43,2.0,5,74,Semi-Urban,HR Executive,28088,0 +112073,Male,59,Bachelors,10,41,24,51,96,6.0,1,93,Urban,Software Engineer,32180,0 +112074,Male,42,High School,16,20,14,79,97,2.0,0,62,Semi-Urban,ML Engineer,99794,0 +112075,Other,23,Masters,13,36,26,85,91,6.0,3,63,Urban,Data Analyst,124837,0 +112076,Female,42,Masters,17,4,53,74,31,0.0,0,84,Semi-Urban,ML Engineer,97341,0 +112077,Female,54,Bachelors,15,16,49,83,76,8.0,1,35,Urban,ML Engineer,134812,0 +112078,Male,50,High School,11,8,35,71,77,9.0,4,19,Semi-Urban,HR Executive,83880,0 +112079,Male,41,Masters,0,8,77,74,74,2.0,7,62,Semi-Urban,HR Executive,118622,0 +112080,Male,50,High School,11,18,14,53,81,1.0,4,41,Urban,Data Analyst,32326,0 +112081,Male,25,High School,14,76,98,27,58,6.0,3,18,Rural,Data Analyst,54674,0 +112082,Male,37,Bachelors,16,10,78,15,76,2.0,0,61,Rural,Data Analyst,49451,0 +112083,Male,28,Masters,16,56,29,58,15,9.0,4,96,Semi-Urban,Software Engineer,89151,1 +112084,Male,55,Masters,18,57,79,60,96,4.0,6,4,Rural,Manager,102890,0 +112085,Female,23,High School,3,38,58,15,96,4.0,7,0,Rural,ML Engineer,44010,0 +112086,Male,23,Bachelors,12,46,74,52,62,6.0,4,98,Urban,ML Engineer,142118,1 +112087,Female,27,Bachelors,10,3,85,81,56,5.0,2,62,Urban,ML Engineer,144388,0 +112088,Male,41,Masters,2,0,18,85,56,6.0,3,98,Rural,ML Engineer,69979,0 +112089,Male,26,Bachelors,13,40,58,60,71,0.0,3,11,Urban,HR Executive,91586,0 +112090,Other,54,Bachelors,16,22,8,90,56,4.0,6,3,Rural,Manager,69296,0 +112091,Male,35,High School,15,17,15,43,88,5.0,6,92,Urban,Software Engineer,102129,0 +112092,Male,46,Bachelors,5,18,10,43,13,8.0,5,34,Semi-Urban,Manager,28408,0 +112093,Male,33,Bachelors,19,76,53,76,6,8.0,0,7,Urban,ML Engineer,137383,0 +112094,Female,58,Diploma,15,14,15,44,46,5.0,4,92,Urban,Manager,35151,0 +112095,Male,48,PhD,19,36,93,15,78,3.0,1,10,Semi-Urban,HR Executive,23121,0 +112096,Female,47,Diploma,17,34,6,37,47,3.0,4,63,Urban,Manager,90567,0 +112097,Male,33,Bachelors,2,68,72,25,40,6.0,5,85,Urban,Manager,40765,1 +112098,Other,24,Diploma,4,79,53,92,34,5.0,2,99,Rural,Data Analyst,52966,1 +112099,Female,29,Diploma,19,3,20,62,32,4.0,4,13,Urban,ML Engineer,22643,0 +112100,Male,42,Diploma,6,62,96,50,56,7.0,4,19,Urban,HR Executive,73983,0 +112101,Male,31,Bachelors,1,17,69,28,96,5.0,6,60,Rural,Software Engineer,34139,0 +112102,Male,58,High School,1,85,36,78,27,1.0,2,93,Urban,Data Analyst,32564,1 +112103,Male,54,High School,17,6,25,42,21,2.0,2,94,Urban,ML Engineer,147035,0 +112104,Female,59,High School,7,93,99,95,76,5.0,7,31,Semi-Urban,Manager,64140,1 +112105,Male,22,High School,4,96,95,40,54,1.0,3,98,Rural,Software Engineer,27327,1 +112106,Male,33,Bachelors,15,51,31,36,56,1.0,7,28,Urban,Data Analyst,104703,0 +112107,Male,29,Bachelors,3,24,36,92,73,6.0,3,85,Semi-Urban,ML Engineer,107760,1 +112108,Male,35,Diploma,11,82,85,75,69,3.0,5,57,Urban,ML Engineer,100654,1 +112109,Male,57,Bachelors,9,46,89,69,94,4.0,2,31,Urban,Software Engineer,93855,1 +112110,Male,55,Bachelors,17,87,39,1,34,9.0,7,64,Urban,Software Engineer,56246,0 +112111,Female,40,High School,13,76,99,16,45,1.0,7,37,Semi-Urban,ML Engineer,70092,0 +112112,Male,36,Bachelors,14,48,87,35,15,2.0,2,48,Urban,HR Executive,50011,0 +112113,Male,55,Bachelors,2,83,24,96,14,1.0,5,95,Urban,Manager,108557,1 +112114,Male,53,Diploma,0,65,51,75,43,7.0,4,74,Urban,HR Executive,32799,1 +112115,Male,54,Bachelors,17,77,21,31,86,5.0,3,1,Urban,Software Engineer,111104,0 +112116,Female,31,Diploma,8,76,4,49,29,3.0,6,43,Rural,Manager,128077,0 +112117,Male,31,Diploma,4,42,98,4,95,0.0,1,28,Rural,Manager,76040,0 +112118,Male,25,Masters,18,46,70,40,64,9.0,3,56,Urban,Software Engineer,124311,0 +112119,Other,22,Masters,13,39,71,57,39,6.0,3,18,Semi-Urban,ML Engineer,60374,0 +112120,Female,58,PhD,14,15,33,91,18,0.0,7,84,Semi-Urban,HR Executive,135758,0 +112121,Male,26,Bachelors,4,63,68,30,60,4.0,7,7,Rural,HR Executive,76719,0 +112122,Male,44,Bachelors,3,28,68,99,16,5.0,7,34,Rural,Data Analyst,141595,0 +112123,Male,58,High School,8,68,61,44,45,2.0,1,39,Semi-Urban,Manager,139826,0 +112124,Female,42,Diploma,11,99,52,17,80,0.0,1,51,Urban,Data Analyst,97650,0 +112125,Male,32,Bachelors,7,96,35,3,42,8.0,5,31,Urban,HR Executive,89446,0 +112126,Male,44,High School,15,57,39,24,9,4.0,2,45,Rural,ML Engineer,147170,0 +112127,Female,24,Bachelors,0,22,95,42,54,9.0,4,57,Rural,Data Analyst,124050,0 +112128,Male,46,High School,11,0,88,56,40,5.0,2,93,Rural,HR Executive,26207,1 +112129,Male,32,Bachelors,17,27,61,63,78,1.0,1,78,Urban,Software Engineer,20891,0 +112130,Female,58,Bachelors,18,74,56,92,15,0.0,1,3,Semi-Urban,ML Engineer,46075,0 +112131,Female,42,Bachelors,8,24,52,69,3,0.0,3,7,Rural,Manager,34364,0 +112132,Female,45,Bachelors,12,54,64,75,80,0.0,4,69,Urban,HR Executive,147705,1 +112133,Other,45,High School,6,42,50,90,39,3.0,1,43,Urban,Manager,51160,0 +112134,Female,51,Bachelors,10,85,79,95,44,2.0,7,74,Urban,HR Executive,147469,1 +112135,Male,27,Diploma,3,73,1,90,68,4.0,6,21,Semi-Urban,Data Analyst,47236,0 +112136,Male,58,Bachelors,4,33,38,98,60,1.0,2,52,Urban,HR Executive,127689,0 +112137,Male,58,Bachelors,13,67,71,9,2,3.0,5,90,Rural,ML Engineer,92746,1 +112138,Male,56,High School,9,63,73,58,55,5.0,7,70,Semi-Urban,Software Engineer,146861,1 +112139,Female,30,Bachelors,14,72,55,68,42,4.0,4,0,Urban,Data Analyst,23120,0 +112140,Male,52,PhD,9,20,55,18,76,3.0,0,97,Urban,Software Engineer,73832,0 +112141,Female,21,Bachelors,3,19,90,91,7,3.0,2,3,Urban,HR Executive,83605,0 +112142,Male,59,Masters,1,98,39,56,6,5.0,1,0,Semi-Urban,Manager,51459,0 +112143,Male,53,Diploma,2,46,92,40,92,3.0,2,25,Urban,HR Executive,116806,0 +112144,Male,58,Bachelors,18,80,30,71,85,1.0,7,17,Urban,ML Engineer,47310,0 +112145,Female,36,High School,17,63,78,71,27,5.0,4,57,Urban,Software Engineer,116506,1 +112146,Male,34,Bachelors,18,20,41,41,48,2.0,5,2,Rural,ML Engineer,144375,0 +112147,Female,51,Bachelors,13,90,55,41,60,4.0,4,34,Urban,ML Engineer,70234,0 +112148,Male,59,Bachelors,17,66,79,87,24,8.0,4,78,Urban,Software Engineer,90928,1 +112149,Female,29,Bachelors,14,24,17,97,78,8.0,7,49,Urban,ML Engineer,82842,0 +112150,Male,22,Masters,6,21,19,33,82,8.0,6,56,Rural,Data Analyst,55074,0 +112151,Male,25,Bachelors,12,7,55,32,25,7.0,1,34,Urban,Manager,133964,0 +112152,Male,53,Diploma,18,31,14,25,85,3.0,2,34,Urban,ML Engineer,79888,0 +112153,Female,41,Bachelors,1,36,51,15,70,1.0,5,84,Urban,HR Executive,93532,0 +112154,Male,59,Bachelors,18,39,80,49,78,2.0,0,13,Semi-Urban,Software Engineer,111126,0 +112155,Female,23,High School,3,6,76,21,82,3.0,5,53,Urban,ML Engineer,84909,0 +112156,Male,52,High School,18,50,82,16,98,9.0,1,45,Urban,HR Executive,139011,0 +112157,Male,31,High School,16,97,83,92,29,3.0,3,91,Urban,Manager,21715,1 +112158,Male,42,PhD,14,59,28,76,24,2.0,5,37,Urban,Software Engineer,100118,0 +112159,Female,37,Bachelors,18,40,17,23,97,1.0,6,12,Urban,ML Engineer,130483,0 +112160,Male,44,High School,0,10,32,41,74,8.0,2,50,Urban,ML Engineer,62185,0 +112161,Male,28,High School,4,5,80,53,21,2.0,3,37,Urban,Software Engineer,26028,0 +112162,Male,54,Masters,8,88,58,61,91,1.0,3,59,Urban,ML Engineer,94844,1 +112163,Female,27,Bachelors,8,51,15,90,40,0.0,3,55,Urban,Data Analyst,139162,0 +112164,Male,22,Diploma,4,64,64,94,95,2.0,7,72,Urban,ML Engineer,47228,1 +112165,Male,39,Bachelors,0,40,78,31,22,3.0,3,64,Rural,Manager,90932,0 +112166,Female,46,Diploma,13,78,96,32,82,2.0,7,50,Urban,Manager,20844,1 +112167,Male,29,Diploma,11,74,89,25,78,2.0,4,48,Semi-Urban,Manager,119483,1 +112168,Female,34,Bachelors,14,64,3,23,13,3.0,5,12,Urban,HR Executive,95006,0 +112169,Male,45,Masters,15,58,78,1,12,0.0,4,90,Urban,ML Engineer,90583,0 +112170,Male,41,Masters,4,48,30,41,23,2.0,0,1,Urban,Manager,116196,0 +112171,Male,41,Bachelors,13,15,20,95,69,6.0,0,71,Urban,ML Engineer,22526,0 +112172,Male,50,Bachelors,0,39,81,17,50,0.0,6,15,Urban,Software Engineer,58850,0 +112173,Male,55,Bachelors,1,40,90,20,33,6.0,0,20,Semi-Urban,ML Engineer,93783,0 +112174,Male,40,High School,7,76,72,12,94,0.0,7,23,Urban,Software Engineer,90925,0 +112175,Male,54,Bachelors,5,18,44,24,3,2.0,1,85,Urban,Software Engineer,83043,0 +112176,Male,50,Diploma,4,5,33,75,42,8.0,7,69,Urban,Data Analyst,22426,0 +112177,Male,41,Diploma,14,18,57,14,7,2.0,7,65,Urban,ML Engineer,71342,0 +112178,Female,25,High School,17,85,1,75,29,1.0,0,55,Semi-Urban,Manager,143205,0 +112179,Male,54,PhD,4,71,68,37,58,0.0,3,80,Rural,Software Engineer,49491,1 +112180,Male,40,Diploma,5,81,52,23,47,8.0,7,83,Semi-Urban,Software Engineer,126945,1 +112181,Male,37,Masters,8,31,45,70,45,2.0,3,85,Urban,Data Analyst,84749,0 +112182,Male,42,Diploma,1,80,5,79,4,9.0,4,49,Semi-Urban,Manager,106501,0 +112183,Male,49,Bachelors,18,13,16,19,63,6.0,1,44,Urban,Software Engineer,99555,0 +112184,Female,55,Bachelors,17,68,44,11,94,7.0,0,10,Urban,HR Executive,65196,0 +112185,Male,51,Bachelors,10,87,86,39,7,1.0,7,23,Urban,Data Analyst,110515,1 +112186,Male,26,Bachelors,3,71,52,99,25,8.0,2,92,Semi-Urban,Software Engineer,58685,1 +112187,Male,41,High School,1,90,91,65,63,0.0,3,75,Rural,Data Analyst,120868,1 +112188,Male,34,Bachelors,6,16,26,88,76,6.0,4,88,Semi-Urban,Data Analyst,35514,0 +112189,Male,31,Diploma,4,40,13,63,51,6.0,1,89,Rural,ML Engineer,118022,0 +112190,Male,28,Bachelors,15,70,4,75,33,2.0,2,62,Rural,HR Executive,69894,0 +112191,Male,26,Masters,17,0,52,36,15,2.0,7,39,Urban,ML Engineer,81835,0 +112192,Female,41,Masters,2,85,15,53,47,1.0,2,83,Semi-Urban,ML Engineer,69243,0 +112193,Male,49,Masters,13,66,94,59,54,9.0,2,46,Urban,ML Engineer,26125,1 +112194,Female,34,Bachelors,5,63,45,58,19,7.0,5,8,Semi-Urban,ML Engineer,137560,0 +112195,Female,34,Diploma,15,44,66,59,34,3.0,6,89,Semi-Urban,ML Engineer,31270,1 +112196,Male,35,Bachelors,9,97,68,16,21,6.0,4,60,Urban,Software Engineer,110113,1 +112197,Male,42,Diploma,2,53,46,51,98,8.0,6,10,Urban,Software Engineer,94456,0 +112198,Female,36,Diploma,10,95,45,84,71,6.0,6,45,Rural,ML Engineer,91370,1 +112199,Male,32,Masters,15,39,25,20,98,2.0,1,62,Urban,ML Engineer,28233,0 +112200,Male,48,Masters,15,3,56,85,70,3.0,4,15,Urban,Manager,136515,0 +112201,Male,41,Diploma,6,53,70,4,33,3.0,2,79,Urban,Software Engineer,120774,0 +112202,Male,30,High School,4,7,76,54,67,8.0,1,98,Urban,ML Engineer,76270,1 +112203,Female,55,Bachelors,9,53,15,94,69,6.0,3,64,Rural,ML Engineer,50193,0 +112204,Male,22,Diploma,19,73,15,70,59,1.0,0,63,Urban,Manager,25912,0 +112205,Male,24,Masters,1,26,54,77,51,1.0,1,55,Urban,Data Analyst,118054,0 +112206,Female,54,Masters,10,73,72,52,48,8.0,7,52,Semi-Urban,ML Engineer,30596,1 +112207,Male,55,Masters,4,34,17,80,89,1.0,3,45,Rural,HR Executive,20421,0 +112208,Male,36,PhD,6,31,89,33,63,8.0,5,96,Semi-Urban,HR Executive,117747,1 +112209,Female,34,Diploma,14,93,96,30,85,0.0,1,90,Semi-Urban,ML Engineer,86854,1 +112210,Male,28,Bachelors,17,19,82,86,15,6.0,1,49,Urban,Software Engineer,69675,1 +112211,Male,34,Masters,10,35,17,11,85,5.0,5,67,Urban,Software Engineer,90556,0 +112212,Other,21,Diploma,3,98,23,80,90,8.0,5,31,Urban,ML Engineer,84548,0 +112213,Male,22,Bachelors,3,92,88,28,1,7.0,1,82,Rural,Software Engineer,98017,1 +112214,Male,50,Masters,14,44,12,45,17,9.0,0,68,Semi-Urban,Software Engineer,115649,0 +112215,Female,25,High School,4,7,70,91,13,4.0,5,56,Urban,Software Engineer,134810,0 +112216,Male,45,PhD,11,6,40,93,99,8.0,0,58,Urban,Software Engineer,64784,0 +112217,Female,58,Diploma,0,37,24,83,37,2.0,2,98,Semi-Urban,Software Engineer,110902,1 +112218,Female,39,PhD,8,6,81,68,84,2.0,4,60,Urban,Data Analyst,107570,0 +112219,Male,40,Bachelors,17,17,93,15,19,4.0,4,5,Urban,ML Engineer,143892,0 +112220,Male,34,Bachelors,5,38,98,21,22,2.0,6,89,Semi-Urban,ML Engineer,88487,1 +112221,Female,58,Diploma,10,28,92,8,40,4.0,2,60,Urban,HR Executive,45097,0 +112222,Other,23,Bachelors,10,83,97,80,44,2.0,7,8,Semi-Urban,ML Engineer,144813,1 +112223,Male,45,Masters,15,66,78,64,21,2.0,1,46,Semi-Urban,ML Engineer,68277,1 +112224,Other,57,Diploma,16,32,24,18,45,2.0,5,92,Urban,HR Executive,37860,0 +112225,Male,28,Bachelors,11,31,6,48,14,9.0,2,85,Urban,HR Executive,93821,0 +112226,Female,54,Masters,3,86,88,35,69,4.0,6,33,Urban,Software Engineer,34035,1 +112227,Male,59,Bachelors,4,76,56,61,60,2.0,6,66,Semi-Urban,Software Engineer,68551,1 +112228,Male,33,Bachelors,15,38,6,62,66,8.0,6,17,Semi-Urban,HR Executive,121746,0 +112229,Male,21,Diploma,14,54,0,10,26,2.0,3,87,Semi-Urban,Data Analyst,93601,0 +112230,Other,51,Bachelors,15,46,35,78,13,1.0,4,36,Semi-Urban,HR Executive,59284,0 +112231,Female,45,Diploma,17,5,17,37,79,5.0,4,16,Urban,Data Analyst,22161,0 +112232,Male,53,Masters,4,77,2,70,26,6.0,4,71,Semi-Urban,Software Engineer,114983,0 +112233,Female,36,Diploma,17,93,53,80,40,3.0,0,5,Semi-Urban,Manager,132076,0 +112234,Male,38,PhD,18,90,72,22,95,9.0,1,78,Urban,Software Engineer,128941,1 +112235,Male,59,Diploma,16,15,36,42,18,9.0,1,45,Rural,Software Engineer,113395,0 +112236,Male,31,Bachelors,3,97,78,88,87,0.0,0,58,Urban,HR Executive,65507,1 +112237,Female,30,High School,18,28,55,66,14,3.0,7,50,Semi-Urban,ML Engineer,113543,0 +112238,Male,44,Diploma,6,95,49,56,25,0.0,1,99,Urban,Data Analyst,53627,1 +112239,Female,45,Bachelors,12,49,28,1,42,2.0,0,44,Rural,HR Executive,102961,0 +112240,Male,43,Masters,15,92,64,95,8,7.0,7,30,Urban,Data Analyst,108717,1 +112241,Other,56,Diploma,5,84,13,54,58,9.0,7,66,Semi-Urban,Software Engineer,139385,0 +112242,Male,23,High School,2,24,40,13,83,7.0,4,9,Urban,HR Executive,138759,0 +112243,Male,37,Bachelors,5,63,52,51,59,8.0,1,54,Semi-Urban,Software Engineer,45295,0 +112244,Male,37,Bachelors,16,2,92,33,79,8.0,4,15,Urban,Data Analyst,119213,0 +112245,Female,31,Bachelors,5,44,42,39,56,9.0,4,13,Rural,Data Analyst,74604,0 +112246,Female,26,Bachelors,19,21,72,87,50,7.0,1,98,Rural,Software Engineer,142242,1 +112247,Male,35,PhD,14,78,21,50,5,3.0,6,68,Semi-Urban,Manager,113062,0 +112248,Female,29,High School,17,59,91,23,31,6.0,5,19,Urban,Manager,78163,0 +112249,Male,50,Diploma,15,44,97,11,93,7.0,2,71,Semi-Urban,ML Engineer,39163,0 +112250,Male,56,Bachelors,17,86,55,45,23,0.0,0,76,Urban,ML Engineer,54318,1 +112251,Male,30,Bachelors,5,13,39,54,38,3.0,1,31,Urban,Data Analyst,89730,0 +112252,Female,44,Masters,3,17,4,4,33,6.0,3,84,Urban,Manager,149750,0 +112253,Male,32,Masters,5,44,39,3,88,2.0,1,76,Semi-Urban,Manager,21417,0 +112254,Male,28,Diploma,3,82,19,13,20,5.0,1,58,Semi-Urban,Data Analyst,67108,0 +112255,Female,46,Masters,4,15,42,28,35,7.0,0,56,Urban,ML Engineer,95521,0 +112256,Male,31,High School,10,26,50,39,64,5.0,3,74,Rural,Manager,95440,0 +112257,Other,42,High School,3,80,15,36,76,4.0,6,28,Urban,HR Executive,147294,0 +112258,Male,34,Masters,6,37,8,0,63,2.0,7,72,Urban,HR Executive,66735,0 +112259,Female,21,Bachelors,11,78,73,54,71,5.0,2,25,Semi-Urban,Software Engineer,55414,0 +112260,Male,21,Bachelors,1,48,9,19,28,7.0,1,9,Semi-Urban,Software Engineer,112354,0 +112261,Male,57,Masters,4,85,49,5,6,1.0,6,29,Urban,ML Engineer,66593,0 +112262,Female,46,Masters,7,57,74,8,0,4.0,1,21,Urban,Data Analyst,74276,0 +112263,Female,22,Bachelors,9,80,23,13,93,5.0,3,13,Urban,Data Analyst,92659,0 +112264,Female,59,Masters,9,97,86,6,29,1.0,1,82,Urban,ML Engineer,70086,1 +112265,Female,28,Bachelors,12,9,28,49,26,9.0,7,31,Rural,HR Executive,93398,0 +112266,Male,34,Masters,3,84,90,32,15,9.0,4,14,Urban,Data Analyst,37178,0 +112267,Male,28,Bachelors,14,50,39,84,32,3.0,0,83,Urban,Data Analyst,127108,1 +112268,Male,37,Bachelors,13,79,24,23,2,0.0,1,21,Urban,HR Executive,118731,0 +112269,Male,26,Masters,17,67,89,56,70,7.0,5,26,Urban,ML Engineer,54551,1 +112270,Male,34,Bachelors,16,65,62,55,13,4.0,1,53,Urban,Manager,134084,1 +112271,Other,42,High School,0,32,33,67,34,9.0,0,99,Urban,HR Executive,45563,0 +112272,Male,22,Masters,15,30,18,79,63,2.0,1,14,Urban,Software Engineer,74672,0 +112273,Male,32,Bachelors,11,85,44,22,77,0.0,6,73,Urban,Software Engineer,49406,0 +112274,Female,44,Bachelors,0,11,76,81,96,7.0,6,55,Urban,Software Engineer,57365,0 +112275,Male,44,Diploma,17,73,14,99,12,6.0,2,27,Urban,Data Analyst,86347,0 +112276,Female,59,Bachelors,8,21,73,79,0,4.0,7,41,Urban,HR Executive,49235,0 +112277,Female,51,Bachelors,1,36,3,8,62,8.0,7,69,Urban,HR Executive,32929,0 +112278,Male,29,Diploma,13,82,17,18,24,9.0,6,11,Urban,Manager,35258,0 +112279,Female,53,PhD,15,31,65,20,73,1.0,7,36,Urban,ML Engineer,26576,0 +112280,Male,31,Masters,13,46,80,74,78,8.0,1,25,Urban,Software Engineer,75836,0 +112281,Male,44,Diploma,5,95,22,12,32,6.0,7,14,Urban,Software Engineer,127784,0 +112282,Female,31,Bachelors,17,35,60,62,83,0.0,5,60,Semi-Urban,Manager,95372,0 +112283,Male,35,PhD,6,22,68,33,96,8.0,1,18,Urban,Data Analyst,87477,0 +112284,Male,54,Bachelors,15,62,98,58,92,1.0,4,85,Urban,HR Executive,119644,1 +112285,Female,43,Bachelors,6,44,42,25,48,7.0,5,96,Urban,HR Executive,99262,0 +112286,Male,47,Masters,3,47,24,39,43,5.0,4,82,Urban,ML Engineer,33541,0 +112287,Male,49,High School,1,91,90,56,38,7.0,3,53,Rural,Data Analyst,109101,1 +112288,Female,48,PhD,10,11,73,21,37,1.0,4,65,Semi-Urban,HR Executive,34113,0 +112289,Male,57,Bachelors,16,24,61,4,68,3.0,5,35,Semi-Urban,HR Executive,94850,0 +112290,Male,32,Bachelors,12,21,1,73,36,5.0,6,3,Semi-Urban,HR Executive,142315,0 +112291,Male,37,Bachelors,2,6,17,49,0,2.0,3,78,Urban,ML Engineer,85377,0 +112292,Male,28,Bachelors,13,4,12,78,22,0.0,7,87,Urban,Manager,148815,0 +112293,Male,40,Bachelors,5,98,24,87,96,4.0,6,33,Urban,Manager,75394,1 +112294,Male,55,Masters,8,57,81,39,6,8.0,4,81,Urban,ML Engineer,86753,1 +112295,Male,59,PhD,1,86,81,37,95,6.0,4,72,Urban,ML Engineer,35803,1 +112296,Male,54,Bachelors,7,9,39,54,13,8.0,7,24,Urban,ML Engineer,35236,0 +112297,Female,21,Masters,19,21,6,78,9,6.0,1,38,Urban,Software Engineer,23367,0 +112298,Male,35,Diploma,5,4,30,36,28,9.0,6,26,Rural,Manager,64104,0 +112299,Male,57,Bachelors,16,80,97,93,50,4.0,0,35,Rural,Manager,111611,1 +112300,Male,27,Bachelors,1,75,78,80,68,5.0,0,89,Urban,Software Engineer,86164,1 +112301,Female,46,High School,12,28,69,69,9,1.0,0,23,Urban,Software Engineer,112163,0 +112302,Female,29,Bachelors,2,95,84,24,32,8.0,3,17,Urban,Data Analyst,117347,0 +112303,Female,49,Masters,2,76,65,72,57,6.0,0,15,Urban,Data Analyst,108617,0 +112304,Male,52,Bachelors,0,48,5,55,24,3.0,6,26,Urban,Software Engineer,102611,0 +112305,Female,29,Masters,4,84,63,76,35,6.0,3,0,Urban,Software Engineer,54522,0 +112306,Female,51,PhD,18,66,44,98,73,3.0,3,32,Urban,Data Analyst,80514,0 +112307,Female,57,Bachelors,10,65,22,51,61,2.0,2,50,Urban,Manager,147707,0 +112308,Male,25,Bachelors,13,12,43,61,0,6.0,7,84,Urban,ML Engineer,85024,0 +112309,Male,41,Masters,5,58,36,10,99,4.0,5,83,Urban,Manager,127808,0 +112310,Male,59,Masters,11,96,35,16,27,2.0,7,69,Rural,Manager,101713,0 +112311,Male,43,Diploma,13,83,73,36,87,1.0,7,39,Urban,Data Analyst,40271,0 +112312,Male,44,Bachelors,12,61,65,56,70,3.0,6,68,Urban,ML Engineer,141591,1 +112313,Female,37,Diploma,10,66,86,37,12,6.0,7,26,Urban,Data Analyst,32335,0 +112314,Male,29,Bachelors,6,93,16,77,17,4.0,3,10,Semi-Urban,Manager,88328,0 +112315,Female,58,High School,13,48,43,41,41,2.0,3,61,Semi-Urban,Manager,120672,0 +112316,Female,43,Bachelors,19,55,73,75,26,1.0,5,9,Urban,Software Engineer,60957,0 +112317,Male,25,High School,5,33,9,96,51,4.0,2,74,Urban,HR Executive,56741,0 +112318,Male,23,Bachelors,11,83,45,56,28,8.0,5,64,Urban,Data Analyst,41188,1 +112319,Male,57,Diploma,14,61,75,70,24,0.0,4,23,Rural,Data Analyst,136105,0 +112320,Female,28,Bachelors,18,36,99,13,3,4.0,1,85,Urban,HR Executive,114216,0 +112321,Male,29,Bachelors,3,12,60,25,45,6.0,7,17,Urban,HR Executive,124029,0 +112322,Female,40,Bachelors,16,15,31,1,87,1.0,1,35,Rural,Software Engineer,96043,0 +112323,Other,44,High School,6,83,95,69,37,0.0,2,2,Rural,Data Analyst,47814,1 +112324,Male,32,High School,10,20,25,47,91,8.0,1,49,Semi-Urban,Software Engineer,41912,0 +112325,Female,46,Masters,18,42,98,26,91,5.0,1,38,Semi-Urban,ML Engineer,82643,0 +112326,Male,45,Bachelors,7,1,23,31,75,9.0,0,74,Semi-Urban,Manager,115610,0 +112327,Male,28,PhD,11,13,34,24,61,1.0,2,2,Urban,HR Executive,97599,0 +112328,Male,43,Masters,12,30,71,25,65,4.0,7,18,Semi-Urban,Software Engineer,90863,0 +112329,Male,46,Bachelors,12,34,37,20,41,5.0,4,70,Urban,ML Engineer,110539,0 +112330,Other,42,Masters,14,48,10,6,10,6.0,1,67,Urban,Manager,99830,0 +112331,Male,41,Bachelors,10,8,59,49,95,2.0,2,90,Urban,Software Engineer,40342,0 +112332,Female,48,PhD,2,95,64,81,50,5.0,0,17,Urban,Data Analyst,70873,1 +112333,Female,39,Masters,0,37,62,86,35,2.0,3,49,Urban,Software Engineer,141526,0 +112334,Female,53,Masters,6,64,73,98,84,1.0,2,75,Semi-Urban,HR Executive,141429,1 +112335,Female,32,Masters,8,63,75,58,22,7.0,1,71,Urban,Software Engineer,143679,1 +112336,Male,29,Masters,11,86,5,56,78,1.0,3,58,Semi-Urban,ML Engineer,33494,0 +112337,Male,53,Masters,18,83,83,5,16,6.0,0,21,Rural,ML Engineer,69595,0 +112338,Male,58,Diploma,7,59,38,95,83,1.0,0,47,Urban,Software Engineer,28466,1 +112339,Male,39,High School,19,77,2,69,13,3.0,3,87,Urban,Software Engineer,30199,1 +112340,Female,36,Bachelors,13,11,45,22,6,9.0,1,1,Semi-Urban,Data Analyst,93912,0 +112341,Male,28,Diploma,7,57,35,90,8,2.0,3,95,Urban,Data Analyst,141856,1 +112342,Male,55,Bachelors,5,82,93,73,76,6.0,0,8,Urban,ML Engineer,147779,1 +112343,Male,47,Bachelors,17,99,28,17,20,5.0,5,7,Semi-Urban,HR Executive,78210,0 +112344,Male,40,Bachelors,13,17,3,70,25,7.0,1,98,Semi-Urban,HR Executive,118212,0 +112345,Male,40,Bachelors,5,76,4,92,0,5.0,2,71,Urban,Software Engineer,43019,1 +112346,Female,38,Diploma,18,30,47,0,72,0.0,6,26,Semi-Urban,Software Engineer,114654,0 +112347,Female,25,High School,9,16,35,35,48,8.0,6,40,Rural,Manager,52795,0 +112348,Male,36,Bachelors,3,12,99,50,35,7.0,0,9,Semi-Urban,Data Analyst,83677,0 +112349,Male,35,PhD,13,9,31,33,45,8.0,3,58,Rural,ML Engineer,108317,0 +112350,Male,27,Masters,10,12,2,63,70,0.0,5,37,Semi-Urban,Software Engineer,63112,0 +112351,Male,45,Bachelors,12,60,98,39,78,2.0,2,22,Urban,Software Engineer,123977,0 +112352,Female,57,Bachelors,0,49,7,6,62,7.0,0,12,Semi-Urban,Data Analyst,82674,0 +112353,Female,25,Masters,2,40,2,17,6,9.0,4,91,Semi-Urban,HR Executive,42954,0 +112354,Male,25,Masters,11,57,58,8,71,0.0,2,28,Urban,Data Analyst,122838,0 +112355,Female,57,Bachelors,19,99,31,30,87,7.0,1,66,Urban,HR Executive,50666,0 +112356,Female,55,Masters,12,96,93,22,93,5.0,4,63,Urban,ML Engineer,145452,1 +112357,Female,52,Bachelors,19,14,9,66,13,9.0,6,83,Urban,HR Executive,49053,0 +112358,Female,23,Bachelors,12,1,97,87,14,6.0,5,5,Rural,Data Analyst,68767,0 +112359,Male,56,Diploma,2,34,14,95,19,3.0,7,67,Urban,ML Engineer,91680,0 +112360,Female,38,Masters,15,79,28,11,41,9.0,4,86,Urban,HR Executive,86377,0 +112361,Male,37,Bachelors,11,78,14,18,32,5.0,3,43,Rural,ML Engineer,129832,0 +112362,Female,37,High School,9,48,18,90,48,2.0,7,84,Urban,HR Executive,120820,0 +112363,Male,22,High School,12,99,8,10,84,1.0,3,51,Urban,ML Engineer,65121,0 +112364,Female,57,Bachelors,2,4,45,5,66,6.0,7,51,Semi-Urban,ML Engineer,79238,0 +112365,Female,35,PhD,4,14,71,2,8,3.0,6,13,Urban,Data Analyst,26994,0 +112366,Female,55,Bachelors,4,75,71,52,9,1.0,1,49,Urban,HR Executive,75696,1 +112367,Male,31,High School,10,49,91,17,84,3.0,6,90,Semi-Urban,Software Engineer,119841,1 +112368,Female,35,Bachelors,19,49,11,62,72,2.0,0,24,Urban,HR Executive,71623,0 +112369,Female,38,Bachelors,14,94,12,86,27,2.0,7,99,Rural,Software Engineer,66934,1 +112370,Male,42,Bachelors,17,46,12,92,23,1.0,3,62,Semi-Urban,ML Engineer,124597,0 +112371,Female,52,Diploma,12,22,70,58,5,7.0,3,93,Urban,HR Executive,115062,1 +112372,Male,34,Bachelors,1,21,50,35,93,0.0,1,72,Rural,HR Executive,27982,0 +112373,Male,43,High School,4,89,27,95,45,9.0,6,70,Urban,Manager,131555,1 +112374,Male,22,High School,4,60,66,26,13,2.0,4,38,Urban,HR Executive,59148,0 +112375,Male,28,High School,9,43,70,64,5,1.0,3,72,Urban,Data Analyst,104236,1 +112376,Male,33,Bachelors,9,49,87,31,30,5.0,5,48,Rural,ML Engineer,56842,0 +112377,Female,23,Bachelors,13,13,99,19,52,4.0,3,28,Semi-Urban,Data Analyst,92494,0 +112378,Male,39,High School,1,8,59,48,49,2.0,6,82,Urban,Data Analyst,20635,0 +112379,Male,38,High School,6,40,37,37,60,0.0,2,23,Urban,ML Engineer,100557,0 +112380,Female,32,Bachelors,2,67,56,57,40,7.0,4,77,Urban,Software Engineer,55813,1 +112381,Female,24,Bachelors,1,62,8,78,35,3.0,5,70,Urban,Data Analyst,50277,0 +112382,Female,35,Bachelors,19,95,98,83,12,2.0,1,53,Urban,HR Executive,117238,1 +112383,Male,43,Bachelors,2,94,24,19,5,0.0,3,49,Urban,Manager,34089,0 +112384,Male,53,Bachelors,4,95,66,3,87,5.0,3,90,Semi-Urban,Software Engineer,26927,1 +112385,Male,31,Diploma,1,91,20,73,76,6.0,3,50,Rural,HR Executive,115752,0 +112386,Male,22,Diploma,11,91,25,76,36,1.0,2,79,Urban,ML Engineer,111414,1 +112387,Female,39,Bachelors,9,15,65,78,46,9.0,2,55,Semi-Urban,HR Executive,48776,0 +112388,Male,30,Masters,19,16,88,25,93,0.0,5,26,Urban,Data Analyst,45031,0 +112389,Male,25,High School,9,34,55,35,88,5.0,5,55,Semi-Urban,Data Analyst,108784,0 +112390,Male,31,Masters,15,68,13,11,81,7.0,0,37,Rural,Software Engineer,103358,0 +112391,Male,33,Masters,14,96,44,64,87,3.0,7,71,Urban,Data Analyst,48355,1 +112392,Female,30,Diploma,9,76,62,55,90,3.0,6,58,Urban,Manager,98116,1 +112393,Male,39,High School,6,60,11,96,91,8.0,3,13,Semi-Urban,Data Analyst,102298,0 +112394,Female,52,Diploma,11,95,14,98,87,1.0,6,52,Urban,HR Executive,134672,1 +112395,Male,32,Bachelors,7,13,39,61,51,7.0,7,95,Urban,Data Analyst,139277,0 +112396,Male,47,Bachelors,5,12,0,0,34,8.0,6,20,Semi-Urban,ML Engineer,126827,0 +112397,Male,27,Bachelors,16,46,72,83,37,2.0,7,32,Urban,Manager,87431,0 +112398,Female,45,Bachelors,9,17,17,21,77,8.0,1,29,Rural,Manager,142002,0 +112399,Male,53,Diploma,14,62,75,12,19,9.0,7,58,Semi-Urban,ML Engineer,128418,0 +112400,Male,36,Diploma,3,60,86,84,11,2.0,5,89,Semi-Urban,HR Executive,94486,1 +112401,Female,28,Diploma,7,8,91,30,82,0.0,3,69,Urban,ML Engineer,147306,0 +112402,Male,24,High School,6,66,2,98,32,7.0,5,19,Rural,Data Analyst,85510,0 +112403,Male,36,High School,12,82,79,61,2,9.0,2,3,Urban,ML Engineer,127464,0 +112404,Female,54,Diploma,5,4,35,40,10,9.0,3,20,Urban,Manager,108722,0 +112405,Female,54,Masters,12,39,57,40,55,8.0,7,18,Semi-Urban,Manager,125759,0 +112406,Male,54,Masters,15,50,2,60,80,2.0,2,90,Urban,Manager,43599,0 +112407,Male,25,Bachelors,9,79,94,52,14,0.0,1,5,Urban,Data Analyst,109022,0 +112408,Male,54,High School,18,84,70,14,18,7.0,6,68,Semi-Urban,Data Analyst,67304,1 +112409,Other,22,Bachelors,11,71,2,79,45,6.0,2,95,Semi-Urban,Manager,91580,1 +112410,Female,45,High School,5,30,28,27,73,6.0,7,87,Semi-Urban,ML Engineer,97363,0 +112411,Male,52,PhD,16,33,86,39,73,5.0,3,52,Urban,Manager,20106,0 +112412,Male,37,Bachelors,18,46,93,24,15,8.0,4,67,Urban,ML Engineer,53169,0 +112413,Male,21,Masters,7,80,36,11,10,0.0,7,32,Urban,ML Engineer,71999,0 +112414,Other,43,High School,6,44,63,49,72,2.0,7,61,Semi-Urban,ML Engineer,116361,0 +112415,Male,21,Diploma,17,28,54,95,31,6.0,6,60,Urban,ML Engineer,138705,1 +112416,Female,48,High School,18,84,56,96,27,6.0,4,97,Urban,ML Engineer,130340,1 +112417,Male,26,Bachelors,8,74,63,53,33,7.0,3,48,Rural,ML Engineer,120714,1 +112418,Female,56,Diploma,9,37,92,44,61,6.0,1,58,Rural,HR Executive,95379,0 +112419,Male,38,Bachelors,13,87,62,81,22,7.0,5,25,Semi-Urban,HR Executive,148783,1 +112420,Female,56,Bachelors,2,87,34,22,11,3.0,0,62,Semi-Urban,ML Engineer,74857,0 +112421,Female,36,PhD,11,56,6,49,61,0.0,7,19,Semi-Urban,Software Engineer,71299,0 +112422,Male,30,Masters,18,32,37,65,56,5.0,6,31,Urban,ML Engineer,77839,0 +112423,Female,40,Bachelors,11,30,75,93,45,3.0,7,7,Semi-Urban,Data Analyst,61756,0 +112424,Male,45,Diploma,14,41,32,22,34,5.0,6,51,Rural,Data Analyst,93757,0 +112425,Female,42,Bachelors,17,8,82,59,33,7.0,5,41,Semi-Urban,Data Analyst,83737,0 +112426,Male,57,Bachelors,10,5,38,76,97,3.0,1,96,Urban,HR Executive,25600,0 +112427,Male,32,Masters,18,37,26,30,61,5.0,7,35,Urban,ML Engineer,32833,0 +112428,Female,31,High School,19,21,16,42,87,3.0,0,23,Urban,Data Analyst,50273,0 +112429,Male,52,High School,9,75,10,21,10,3.0,1,62,Semi-Urban,HR Executive,28333,0 +112430,Male,58,Bachelors,10,14,62,27,4,0.0,3,49,Urban,Data Analyst,115477,0 +112431,Female,40,Masters,5,96,11,95,19,9.0,7,29,Semi-Urban,ML Engineer,138364,0 +112432,Male,41,Bachelors,8,42,30,85,91,5.0,6,26,Urban,Data Analyst,51154,0 +112433,Female,56,Bachelors,5,76,32,97,84,1.0,1,7,Semi-Urban,ML Engineer,76857,0 +112434,Male,43,High School,7,5,9,71,52,7.0,3,86,Rural,Software Engineer,125264,0 +112435,Male,22,Diploma,4,93,64,87,26,5.0,3,22,Urban,Software Engineer,111266,1 +112436,Male,56,Bachelors,19,19,94,91,49,9.0,7,57,Urban,HR Executive,53812,1 +112437,Male,30,Bachelors,2,32,52,83,15,1.0,1,57,Urban,HR Executive,23011,0 +112438,Female,37,Diploma,14,87,41,12,75,5.0,4,0,Urban,Data Analyst,92845,0 +112439,Female,25,Diploma,14,31,93,77,94,3.0,2,72,Urban,ML Engineer,53300,1 +112440,Male,44,Diploma,1,95,87,94,54,0.0,7,23,Urban,Software Engineer,58693,1 +112441,Female,25,Bachelors,17,86,1,86,95,6.0,1,13,Urban,HR Executive,127606,0 +112442,Male,49,Masters,10,64,99,91,76,8.0,2,99,Semi-Urban,HR Executive,109449,1 +112443,Female,56,Bachelors,19,18,77,33,99,0.0,0,25,Rural,Data Analyst,144255,0 +112444,Female,46,Bachelors,0,75,14,81,46,9.0,3,78,Urban,ML Engineer,126889,1 +112445,Male,42,Bachelors,16,63,97,94,25,6.0,4,50,Urban,HR Executive,66641,1 +112446,Female,37,Masters,4,6,0,0,68,3.0,3,33,Urban,Manager,88202,0 +112447,Other,31,Masters,8,24,83,22,4,4.0,1,34,Urban,HR Executive,45517,0 +112448,Female,42,Masters,9,34,69,8,22,7.0,6,5,Urban,Data Analyst,113157,0 +112449,Male,35,Bachelors,8,62,25,69,64,8.0,5,81,Semi-Urban,Data Analyst,41262,1 +112450,Male,26,Diploma,7,39,2,9,64,5.0,6,7,Urban,ML Engineer,23552,0 +112451,Female,23,Masters,19,26,30,81,30,3.0,6,83,Rural,Data Analyst,75027,0 +112452,Female,56,Bachelors,18,89,71,64,55,8.0,6,7,Urban,HR Executive,75800,0 +112453,Male,22,Diploma,7,64,72,79,15,8.0,5,85,Urban,Software Engineer,79350,1 +112454,Male,36,Masters,3,4,63,39,63,9.0,1,27,Urban,Software Engineer,28180,0 +112455,Male,40,Bachelors,3,47,28,3,52,4.0,2,16,Urban,Data Analyst,73974,0 +112456,Female,34,High School,16,85,62,54,41,1.0,7,13,Rural,Data Analyst,66018,0 +112457,Male,41,Bachelors,9,58,1,43,60,9.0,5,15,Semi-Urban,Data Analyst,61072,0 +112458,Male,48,Masters,13,61,33,3,60,5.0,2,58,Urban,Software Engineer,58453,0 +112459,Female,44,Diploma,10,56,21,32,49,8.0,4,68,Urban,Software Engineer,131268,0 +112460,Male,44,Diploma,8,82,46,57,2,9.0,2,80,Rural,Software Engineer,90837,1 +112461,Male,37,Masters,10,98,53,5,82,7.0,1,16,Semi-Urban,Software Engineer,104817,0 +112462,Female,52,Diploma,2,53,75,13,43,2.0,2,47,Urban,ML Engineer,22245,0 +112463,Male,51,High School,11,71,12,38,30,6.0,5,69,Semi-Urban,HR Executive,30866,0 +112464,Male,44,Diploma,9,93,24,5,2,9.0,6,84,Urban,Manager,149467,0 +112465,Female,51,Masters,6,33,38,33,88,9.0,1,98,Semi-Urban,HR Executive,34352,0 +112466,Male,58,Diploma,15,62,94,94,47,9.0,5,12,Semi-Urban,Data Analyst,119643,1 +112467,Male,55,Bachelors,2,32,65,49,13,3.0,7,36,Semi-Urban,ML Engineer,95425,0 +112468,Male,33,Diploma,5,32,29,12,15,4.0,2,1,Urban,Software Engineer,32086,0 +112469,Female,34,High School,2,3,99,64,20,5.0,5,82,Urban,Software Engineer,122273,1 +112470,Male,25,Diploma,17,11,56,72,79,8.0,2,3,Urban,Software Engineer,44709,0 +112471,Female,26,Diploma,19,87,69,91,31,4.0,0,54,Urban,ML Engineer,149557,1 +112472,Male,45,Diploma,0,15,52,46,94,6.0,6,75,Rural,Data Analyst,148506,0 +112473,Female,32,Masters,11,49,69,87,42,9.0,1,93,Semi-Urban,Manager,31085,1 +112474,Male,34,Bachelors,17,89,92,92,82,4.0,5,73,Urban,Software Engineer,97374,1 +112475,Female,55,Masters,15,39,33,17,32,3.0,0,32,Semi-Urban,HR Executive,108740,0 +112476,Female,23,High School,7,11,32,55,79,0.0,7,98,Urban,ML Engineer,48153,0 +112477,Male,38,Bachelors,16,11,95,31,62,4.0,1,8,Urban,HR Executive,106061,0 +112478,Male,29,Bachelors,14,6,54,95,72,8.0,2,61,Rural,ML Engineer,31775,0 +112479,Male,29,Masters,4,88,39,91,18,3.0,3,31,Urban,ML Engineer,122048,1 +112480,Male,24,Bachelors,12,82,56,30,27,8.0,1,44,Urban,HR Executive,106389,0 +112481,Male,23,Diploma,7,27,90,52,71,9.0,0,30,Semi-Urban,ML Engineer,100064,0 +112482,Male,45,Masters,15,43,60,92,62,1.0,1,39,Urban,HR Executive,84712,0 +112483,Male,51,Diploma,19,42,31,42,91,7.0,3,66,Semi-Urban,Manager,77838,0 +112484,Male,21,Bachelors,10,4,2,91,33,5.0,7,46,Urban,Data Analyst,55647,0 +112485,Male,51,Bachelors,11,75,88,85,36,3.0,0,28,Urban,Manager,72866,1 +112486,Male,32,Diploma,3,14,19,3,95,7.0,4,69,Urban,ML Engineer,65241,0 +112487,Male,44,Bachelors,11,98,28,72,79,4.0,1,41,Urban,Software Engineer,79443,1 +112488,Other,53,Bachelors,1,19,0,87,36,9.0,7,92,Urban,Software Engineer,64153,0 +112489,Male,30,High School,14,11,27,13,83,3.0,0,65,Semi-Urban,ML Engineer,115718,0 +112490,Female,30,Diploma,10,94,53,78,15,5.0,4,77,Urban,ML Engineer,142449,1 +112491,Male,54,Bachelors,8,86,85,93,34,0.0,4,56,Rural,ML Engineer,39249,1 +112492,Female,29,High School,2,93,5,54,28,6.0,4,26,Urban,Data Analyst,47316,0 +112493,Other,43,Masters,6,19,55,71,83,9.0,6,49,Urban,Manager,57224,0 +112494,Female,55,Masters,6,83,1,73,6,5.0,2,16,Urban,Data Analyst,23936,0 +112495,Male,59,High School,0,50,7,49,3,4.0,1,31,Urban,Manager,130404,0 +112496,Female,53,Masters,9,55,88,17,63,2.0,6,17,Urban,Software Engineer,115594,0 +112497,Male,31,High School,10,46,7,26,23,8.0,5,95,Urban,Software Engineer,129081,0 +112498,Male,47,Diploma,16,33,17,95,16,5.0,5,51,Semi-Urban,Data Analyst,96162,0 +112499,Male,45,PhD,11,36,20,0,17,7.0,0,49,Semi-Urban,Data Analyst,91034,0 +112500,Male,50,Masters,18,35,81,32,25,2.0,6,98,Urban,ML Engineer,72459,1 +112501,Male,26,Masters,4,8,90,26,1,0.0,0,59,Urban,Software Engineer,24371,0 +112502,Male,28,Bachelors,7,18,24,22,43,8.0,6,3,Urban,Manager,88264,0 +112503,Female,49,Bachelors,16,75,39,41,75,9.0,0,67,Urban,HR Executive,116488,0 +112504,Female,33,Bachelors,17,99,81,45,97,2.0,7,33,Urban,HR Executive,90601,1 +112505,Male,33,Bachelors,6,79,90,21,78,7.0,0,23,Urban,ML Engineer,95810,0 +112506,Male,52,Diploma,18,46,14,13,13,7.0,1,25,Rural,Software Engineer,146633,0 +112507,Male,33,Diploma,5,73,62,35,1,2.0,7,40,Urban,Software Engineer,138067,0 +112508,Male,42,Bachelors,5,79,91,21,65,6.0,7,22,Urban,Manager,57632,0 +112509,Female,28,Diploma,12,0,36,35,29,8.0,6,71,Urban,Software Engineer,74281,0 +112510,Male,48,Diploma,13,2,13,79,73,8.0,1,92,Urban,Manager,107779,0 +112511,Male,59,Diploma,0,19,32,24,88,2.0,0,92,Urban,Manager,23112,0 +112512,Female,34,Diploma,12,31,3,18,97,6.0,4,38,Urban,Manager,94792,0 +112513,Male,21,Bachelors,18,27,75,99,97,2.0,7,2,Urban,Manager,67509,0 +112514,Female,27,Bachelors,13,43,99,48,42,3.0,4,52,Rural,HR Executive,89481,1 +112515,Female,36,Masters,16,24,20,29,47,8.0,6,64,Urban,ML Engineer,44781,0 +112516,Male,57,Masters,10,1,63,64,31,2.0,4,90,Rural,Software Engineer,137301,0 +112517,Female,48,Bachelors,18,87,12,38,39,2.0,1,69,Urban,HR Executive,73339,0 +112518,Other,25,Masters,3,64,83,62,44,7.0,0,64,Semi-Urban,Data Analyst,28232,1 +112519,Female,44,Masters,9,5,85,39,96,1.0,6,76,Semi-Urban,ML Engineer,134495,0 +112520,Male,45,Bachelors,3,64,11,32,97,6.0,4,69,Urban,HR Executive,62590,0 +112521,Male,29,Masters,8,8,65,31,42,8.0,7,51,Urban,Manager,72114,0 +112522,Male,40,Diploma,15,68,97,16,44,6.0,0,88,Semi-Urban,ML Engineer,134268,1 +112523,Male,42,Diploma,14,81,17,31,96,8.0,2,38,Urban,Data Analyst,26603,0 +112524,Male,34,Bachelors,0,28,61,72,13,9.0,2,21,Urban,ML Engineer,136010,0 +112525,Male,41,Bachelors,3,91,64,35,54,2.0,4,75,Urban,HR Executive,48291,1 +112526,Male,48,High School,11,54,98,79,5,4.0,7,94,Semi-Urban,Manager,149984,1 +112527,Male,28,Diploma,14,75,11,15,59,1.0,3,97,Semi-Urban,Data Analyst,92920,0 +112528,Female,24,Masters,4,12,55,39,26,5.0,0,84,Rural,Manager,144226,0 +112529,Male,53,Diploma,18,60,85,61,41,0.0,3,10,Rural,ML Engineer,118583,0 +112530,Male,57,Bachelors,16,18,40,72,57,0.0,3,26,Urban,Data Analyst,84553,0 +112531,Female,31,Bachelors,0,29,89,56,15,5.0,2,42,Urban,HR Executive,21496,0 +112532,Female,27,Bachelors,7,0,65,49,31,8.0,5,38,Rural,Manager,40049,0 +112533,Female,45,Bachelors,2,74,25,94,46,0.0,2,55,Urban,Software Engineer,135107,1 +112534,Female,31,Masters,15,30,5,35,10,6.0,1,43,Semi-Urban,Software Engineer,96368,0 +112535,Male,56,Diploma,17,76,97,23,79,0.0,4,52,Urban,Manager,45591,1 +112536,Male,49,Masters,17,80,21,31,94,1.0,1,62,Urban,Software Engineer,25305,0 +112537,Female,31,Bachelors,19,5,55,45,48,6.0,1,85,Urban,ML Engineer,23783,0 +112538,Male,47,Diploma,2,42,13,72,18,1.0,7,31,Rural,HR Executive,82935,0 +112539,Female,22,Masters,9,96,25,49,65,4.0,5,70,Urban,Data Analyst,59346,0 +112540,Female,31,High School,3,36,40,46,99,4.0,3,4,Urban,Manager,55681,0 +112541,Male,30,Bachelors,7,49,59,69,21,9.0,2,70,Urban,ML Engineer,44267,1 +112542,Other,35,Diploma,4,28,93,42,68,2.0,5,84,Urban,Data Analyst,72927,1 +112543,Male,52,Bachelors,7,43,90,72,86,6.0,3,79,Urban,ML Engineer,120962,1 +112544,Female,42,High School,0,90,64,65,41,4.0,2,40,Urban,HR Executive,77145,1 +112545,Male,52,Diploma,14,36,40,99,93,9.0,1,26,Urban,Software Engineer,63356,0 +112546,Other,24,PhD,0,50,61,50,46,4.0,6,51,Rural,Manager,20790,0 +112547,Male,45,Masters,3,97,76,77,61,7.0,2,65,Urban,Data Analyst,22484,1 +112548,Male,49,Diploma,1,76,72,45,6,2.0,4,3,Semi-Urban,Manager,124644,0 +112549,Male,31,Masters,11,87,63,51,79,0.0,3,63,Urban,ML Engineer,20005,1 +112550,Female,39,Diploma,16,97,59,51,39,9.0,6,98,Rural,HR Executive,149303,1 +112551,Male,42,Diploma,3,81,63,20,64,1.0,3,98,Urban,ML Engineer,70878,1 +112552,Female,54,PhD,4,50,0,87,34,8.0,7,91,Rural,ML Engineer,106764,0 +112553,Male,38,Bachelors,16,98,66,24,88,8.0,1,81,Urban,HR Executive,137205,1 +112554,Female,50,High School,16,66,24,57,63,2.0,2,16,Rural,HR Executive,58758,0 +112555,Male,40,Masters,1,22,65,73,93,3.0,2,47,Urban,ML Engineer,91837,0 +112556,Male,39,Masters,14,27,26,18,89,7.0,5,40,Urban,Manager,71845,0 +112557,Male,26,Bachelors,0,0,86,18,36,2.0,1,17,Rural,ML Engineer,80159,0 +112558,Male,47,Masters,18,42,76,79,45,5.0,2,78,Urban,Manager,97843,1 +112559,Male,39,High School,3,59,89,22,12,7.0,4,21,Rural,ML Engineer,46560,0 +112560,Male,27,High School,1,61,56,24,38,9.0,3,61,Urban,Data Analyst,48511,0 +112561,Male,44,Bachelors,19,20,54,27,32,7.0,4,39,Semi-Urban,Data Analyst,79027,0 +112562,Male,30,Masters,16,97,21,71,36,0.0,6,45,Urban,HR Executive,21438,0 +112563,Male,37,High School,16,72,24,45,84,2.0,5,93,Semi-Urban,Manager,30046,0 +112564,Male,49,Masters,6,63,78,20,49,3.0,1,56,Rural,Software Engineer,38642,0 +112565,Female,40,Bachelors,10,89,28,63,84,9.0,5,86,Semi-Urban,Data Analyst,81553,1 +112566,Male,47,Masters,8,85,53,98,77,7.0,1,56,Urban,HR Executive,80176,1 +112567,Male,21,Masters,13,76,35,99,38,9.0,4,25,Urban,Software Engineer,110732,1 +112568,Male,30,PhD,8,36,7,30,82,3.0,2,17,Urban,ML Engineer,63230,0 +112569,Male,54,Bachelors,15,14,91,5,12,8.0,3,96,Semi-Urban,ML Engineer,135908,0 +112570,Female,40,High School,11,87,85,63,41,2.0,3,34,Semi-Urban,Manager,141580,1 +112571,Female,31,Diploma,4,21,27,53,13,5.0,5,23,Rural,Software Engineer,117081,0 +112572,Male,24,Bachelors,15,21,31,37,23,2.0,1,84,Urban,ML Engineer,120547,0 +112573,Female,40,High School,14,36,19,83,96,4.0,1,58,Semi-Urban,Manager,138263,0 +112574,Male,26,PhD,13,98,62,60,15,6.0,3,91,Semi-Urban,HR Executive,134299,1 +112575,Female,49,Diploma,7,89,10,67,23,7.0,2,81,Urban,HR Executive,65289,1 +112576,Female,30,Diploma,8,94,84,61,65,3.0,5,64,Urban,ML Engineer,134302,1 +112577,Female,47,High School,7,8,47,59,9,9.0,2,27,Urban,HR Executive,64734,0 +112578,Male,29,Diploma,6,28,32,73,53,8.0,3,56,Semi-Urban,ML Engineer,58898,0 +112579,Other,47,High School,8,86,36,44,3,5.0,5,32,Urban,ML Engineer,61797,0 +112580,Female,52,Diploma,14,93,19,7,39,4.0,0,6,Urban,HR Executive,54007,0 +112581,Male,27,PhD,9,41,53,89,68,6.0,2,38,Rural,Software Engineer,147781,0 +112582,Male,29,Bachelors,6,99,73,75,92,1.0,6,18,Rural,HR Executive,121034,1 +112583,Male,27,Diploma,8,13,64,13,11,1.0,7,88,Semi-Urban,ML Engineer,126039,0 +112584,Female,30,Bachelors,2,97,98,25,47,6.0,3,70,Semi-Urban,ML Engineer,61515,1 +112585,Male,56,Bachelors,18,83,27,2,49,6.0,3,48,Semi-Urban,HR Executive,101159,0 +112586,Male,22,Masters,15,17,56,42,67,3.0,2,8,Urban,HR Executive,52830,0 +112587,Female,52,Bachelors,10,5,71,36,14,7.0,2,44,Urban,HR Executive,46051,0 +112588,Male,31,Bachelors,12,19,92,81,11,3.0,7,0,Semi-Urban,Software Engineer,32012,0 +112589,Female,59,Bachelors,13,71,18,86,67,5.0,5,0,Rural,HR Executive,64824,0 +112590,Male,52,Bachelors,17,65,61,32,29,9.0,2,90,Semi-Urban,HR Executive,126077,1 +112591,Female,59,Bachelors,14,68,30,35,49,1.0,4,4,Urban,ML Engineer,21282,0 +112592,Male,58,Masters,6,34,70,49,6,9.0,1,63,Semi-Urban,Software Engineer,50841,0 +112593,Male,39,Bachelors,3,27,95,8,89,7.0,0,84,Rural,HR Executive,80144,0 +112594,Female,23,Masters,18,59,0,91,43,4.0,7,70,Rural,HR Executive,111787,0 +112595,Male,30,Diploma,2,10,1,64,71,9.0,3,72,Rural,HR Executive,50168,0 +112596,Male,56,PhD,8,35,37,2,50,2.0,0,22,Semi-Urban,Manager,46531,0 +112597,Female,39,Bachelors,15,85,84,61,53,1.0,5,80,Semi-Urban,Software Engineer,55361,1 +112598,Female,28,Bachelors,1,45,93,89,19,1.0,7,56,Rural,Manager,142213,1 +112599,Male,51,Bachelors,14,23,5,18,29,3.0,6,91,Urban,ML Engineer,129417,0 +112600,Female,32,Diploma,11,10,93,46,38,9.0,4,17,Urban,HR Executive,102206,0 +112601,Male,54,Bachelors,12,51,60,16,83,0.0,7,21,Urban,ML Engineer,145495,0 +112602,Female,29,PhD,1,48,23,1,45,4.0,7,46,Rural,Manager,99997,0 +112603,Male,56,Diploma,1,96,78,67,83,5.0,4,1,Semi-Urban,HR Executive,141683,1 +112604,Male,24,Diploma,10,73,52,79,91,2.0,2,26,Urban,Manager,74255,0 +112605,Male,53,Masters,9,79,3,76,12,0.0,3,80,Urban,Manager,81469,1 +112606,Male,30,High School,10,89,62,47,94,4.0,6,6,Rural,HR Executive,149811,0 +112607,Female,50,Masters,0,26,49,33,9,1.0,5,11,Rural,ML Engineer,114071,0 +112608,Male,28,Bachelors,10,12,78,83,68,0.0,4,48,Urban,Manager,142195,0 +112609,Male,44,Diploma,10,70,56,0,31,3.0,2,69,Semi-Urban,Software Engineer,63019,0 +112610,Male,32,Bachelors,16,49,53,37,65,5.0,2,96,Urban,HR Executive,118335,1 +112611,Female,42,Diploma,11,42,53,74,4,3.0,3,39,Rural,ML Engineer,138252,0 +112612,Male,53,Masters,4,45,68,83,18,2.0,1,42,Urban,Manager,25633,1 +112613,Male,31,Bachelors,10,15,22,91,58,1.0,7,51,Urban,HR Executive,131798,0 +112614,Male,48,Bachelors,13,36,38,62,35,2.0,5,64,Urban,ML Engineer,49225,0 +112615,Other,57,Bachelors,19,80,88,30,23,4.0,4,76,Urban,Software Engineer,93608,1 +112616,Female,58,High School,7,77,47,54,55,0.0,3,24,Semi-Urban,Software Engineer,122210,0 +112617,Male,37,Bachelors,10,70,68,34,89,1.0,7,25,Urban,Manager,31989,0 +112618,Male,35,High School,2,83,53,78,83,6.0,7,90,Urban,ML Engineer,109478,1 +112619,Male,42,High School,3,58,27,51,5,1.0,6,4,Urban,HR Executive,57329,0 +112620,Male,42,Masters,3,72,49,83,13,1.0,3,63,Urban,HR Executive,52853,1 +112621,Female,25,Bachelors,17,63,91,42,65,5.0,0,38,Semi-Urban,HR Executive,76265,0 +112622,Male,52,Masters,10,16,52,38,22,3.0,7,43,Semi-Urban,Manager,94954,0 +112623,Female,46,Diploma,11,83,87,59,52,5.0,1,60,Semi-Urban,HR Executive,66101,1 +112624,Female,35,Bachelors,3,30,48,4,13,7.0,5,16,Semi-Urban,HR Executive,22733,0 +112625,Male,41,Diploma,16,57,43,10,52,3.0,6,49,Urban,ML Engineer,37368,0 +112626,Male,29,Bachelors,3,17,8,24,16,8.0,1,1,Rural,Data Analyst,103648,0 +112627,Male,30,Diploma,0,81,16,14,98,6.0,6,22,Semi-Urban,Software Engineer,92994,0 +112628,Male,45,Diploma,1,66,32,26,83,9.0,0,26,Urban,ML Engineer,143328,0 +112629,Male,28,Diploma,6,43,71,53,24,6.0,0,45,Urban,ML Engineer,35952,0 +112630,Male,45,Diploma,5,46,38,96,20,2.0,7,19,Urban,Manager,128128,0 +112631,Male,39,High School,14,57,43,94,32,2.0,5,9,Urban,Software Engineer,30243,0 +112632,Female,22,PhD,10,72,94,71,95,8.0,0,7,Urban,Data Analyst,120205,1 +112633,Male,33,Bachelors,0,72,18,71,88,8.0,1,29,Urban,HR Executive,112298,0 +112634,Male,36,Bachelors,19,79,71,95,71,4.0,6,59,Urban,Software Engineer,51275,1 +112635,Male,32,PhD,10,29,84,8,63,9.0,2,57,Urban,Manager,70188,0 +112636,Female,37,High School,8,35,85,74,58,2.0,1,86,Urban,Data Analyst,32515,1 +112637,Male,42,High School,7,48,40,37,53,2.0,5,88,Rural,ML Engineer,73471,0 +112638,Female,28,High School,5,36,84,37,0,4.0,5,6,Semi-Urban,ML Engineer,37262,0 +112639,Male,24,Diploma,18,17,52,2,40,8.0,7,80,Urban,HR Executive,96483,0 +112640,Female,59,Masters,0,50,93,54,76,9.0,3,40,Urban,HR Executive,118012,0 +112641,Female,58,Masters,2,51,40,30,27,3.0,5,34,Semi-Urban,Software Engineer,20552,0 +112642,Male,30,Bachelors,16,27,54,52,78,5.0,6,3,Urban,HR Executive,104684,0 +112643,Female,44,High School,9,13,89,91,33,6.0,5,89,Rural,Data Analyst,36396,1 +112644,Female,28,Bachelors,15,63,44,4,75,2.0,6,80,Semi-Urban,Manager,26376,0 +112645,Female,27,Bachelors,10,76,8,98,69,7.0,5,60,Semi-Urban,Data Analyst,145283,1 +112646,Male,23,Diploma,13,18,16,1,37,3.0,6,96,Urban,HR Executive,104107,0 +112647,Female,43,Diploma,14,35,36,84,78,1.0,0,13,Semi-Urban,ML Engineer,104764,0 +112648,Male,39,PhD,9,93,34,27,80,2.0,5,61,Semi-Urban,Software Engineer,76569,0 +112649,Male,44,Bachelors,3,58,76,91,22,3.0,0,22,Semi-Urban,Manager,89908,1 +112650,Female,24,High School,14,51,9,49,89,2.0,6,36,Rural,Manager,52780,0 +112651,Female,31,Diploma,6,57,68,3,70,0.0,7,39,Urban,Data Analyst,89516,0 +112652,Female,21,High School,18,75,74,97,36,8.0,3,58,Urban,ML Engineer,135577,1 +112653,Male,30,Bachelors,0,13,43,0,57,9.0,2,85,Semi-Urban,Manager,71265,0 +112654,Female,42,High School,2,61,79,68,81,2.0,7,16,Rural,Software Engineer,73614,0 +112655,Other,37,High School,16,83,38,69,73,7.0,5,41,Semi-Urban,HR Executive,76745,0 +112656,Female,30,PhD,6,9,92,71,59,4.0,0,45,Semi-Urban,Data Analyst,35290,0 +112657,Female,48,High School,4,72,81,10,68,4.0,2,76,Urban,HR Executive,92002,0 +112658,Female,35,Masters,19,21,68,60,66,0.0,4,10,Semi-Urban,Software Engineer,106153,0 +112659,Female,58,Bachelors,5,25,77,91,24,6.0,7,3,Urban,Manager,117163,0 +112660,Male,45,Masters,2,96,60,49,80,1.0,2,96,Semi-Urban,Software Engineer,35399,1 +112661,Male,23,Diploma,2,30,31,47,61,2.0,2,18,Urban,Data Analyst,133321,0 +112662,Other,26,High School,15,51,57,62,28,6.0,2,71,Urban,HR Executive,45866,1 +112663,Female,51,Diploma,12,97,1,3,2,3.0,3,48,Urban,ML Engineer,62375,0 +112664,Male,22,Bachelors,2,34,40,88,1,9.0,6,43,Urban,ML Engineer,101647,0 +112665,Female,43,PhD,2,98,6,67,16,5.0,2,76,Urban,Manager,36712,1 +112666,Male,39,Bachelors,6,83,10,44,67,9.0,3,41,Semi-Urban,ML Engineer,70552,0 +112667,Male,22,Bachelors,4,23,74,44,83,2.0,5,69,Rural,HR Executive,38450,0 +112668,Male,23,High School,1,97,46,49,62,4.0,1,7,Semi-Urban,Data Analyst,91476,0 +112669,Male,36,Masters,11,92,19,80,50,9.0,6,39,Urban,ML Engineer,101868,0 +112670,Other,42,PhD,9,16,24,76,17,2.0,5,68,Urban,HR Executive,123744,0 +112671,Female,52,Masters,8,3,88,62,50,3.0,4,60,Rural,Software Engineer,98250,0 +112672,Female,21,Masters,0,10,78,39,27,4.0,7,26,Rural,ML Engineer,147063,0 +112673,Male,42,Bachelors,9,23,55,75,21,2.0,1,49,Rural,Manager,144295,0 +112674,Male,52,Masters,4,36,79,50,75,1.0,0,7,Urban,HR Executive,149178,0 +112675,Female,41,Diploma,15,96,6,12,0,1.0,6,52,Urban,ML Engineer,91813,0 +112676,Female,46,High School,19,16,45,81,28,8.0,1,9,Rural,Data Analyst,40290,0 +112677,Male,29,Diploma,14,15,41,16,8,4.0,7,31,Urban,Manager,65271,0 +112678,Male,52,Bachelors,1,3,73,23,28,6.0,4,58,Urban,Data Analyst,35570,0 +112679,Female,34,Bachelors,15,41,23,53,31,0.0,1,34,Rural,HR Executive,36317,0 +112680,Male,54,Bachelors,0,24,98,56,67,1.0,0,40,Urban,ML Engineer,132937,0 +112681,Male,24,Diploma,13,24,51,86,96,8.0,0,56,Urban,Software Engineer,103287,0 +112682,Female,27,Bachelors,14,28,14,31,51,4.0,0,60,Semi-Urban,Manager,87396,0 +112683,Male,49,Masters,4,57,24,31,6,6.0,4,55,Semi-Urban,HR Executive,89331,0 +112684,Male,49,High School,7,46,52,9,34,9.0,1,13,Rural,Data Analyst,101810,0 +112685,Male,47,High School,11,58,43,94,73,2.0,0,79,Urban,Software Engineer,28994,1 +112686,Male,59,Masters,19,70,99,18,23,5.0,2,25,Semi-Urban,Data Analyst,109033,0 +112687,Male,21,High School,19,55,82,49,91,0.0,1,68,Semi-Urban,Manager,107683,1 +112688,Female,56,Diploma,17,7,58,20,59,8.0,2,35,Rural,ML Engineer,60744,0 +112689,Female,44,Masters,7,16,43,27,50,3.0,4,8,Urban,HR Executive,83810,0 +112690,Male,48,Diploma,15,69,23,68,31,7.0,7,56,Urban,HR Executive,112976,0 +112691,Female,40,Bachelors,5,8,24,38,70,5.0,2,0,Urban,ML Engineer,28438,0 +112692,Male,44,Masters,13,35,4,84,81,0.0,2,87,Urban,Data Analyst,50355,0 +112693,Female,27,Masters,4,79,35,63,36,7.0,0,64,Urban,Data Analyst,83307,1 +112694,Female,58,PhD,12,49,21,45,55,8.0,2,28,Semi-Urban,Manager,73328,0 +112695,Male,22,Diploma,5,24,36,84,0,5.0,7,86,Urban,Data Analyst,22745,0 +112696,Male,42,Bachelors,15,12,80,51,53,2.0,7,69,Urban,Software Engineer,41323,0 +112697,Male,38,Bachelors,0,69,86,68,80,7.0,0,68,Rural,Data Analyst,60466,1 +112698,Female,50,Diploma,3,91,95,69,35,8.0,2,85,Urban,Data Analyst,127159,1 +112699,Male,37,Masters,8,22,84,12,59,3.0,6,16,Urban,Software Engineer,107689,0 +112700,Female,57,Bachelors,2,19,19,34,74,6.0,4,7,Urban,HR Executive,84964,0 +112701,Male,55,Masters,8,42,65,23,48,5.0,4,79,Urban,Manager,134280,0 +112702,Male,58,Diploma,17,94,98,4,35,0.0,1,15,Urban,Manager,133783,0 +112703,Male,49,Bachelors,18,34,43,4,93,6.0,6,26,Urban,Data Analyst,119030,0 +112704,Female,36,Diploma,15,5,67,31,99,6.0,7,10,Urban,ML Engineer,147148,0 +112705,Female,41,Bachelors,8,84,67,16,76,8.0,3,2,Urban,Data Analyst,142078,0 +112706,Female,30,Masters,9,13,22,56,42,1.0,3,90,Urban,HR Executive,119598,0 +112707,Female,25,High School,1,40,35,3,73,1.0,7,92,Rural,HR Executive,67015,0 +112708,Female,23,Diploma,3,68,26,4,97,0.0,4,10,Urban,ML Engineer,144755,0 +112709,Male,51,High School,2,26,38,76,81,0.0,2,75,Urban,Manager,65885,0 +112710,Male,33,Bachelors,7,46,26,23,74,3.0,2,89,Rural,Software Engineer,43891,0 +112711,Female,36,Bachelors,6,75,79,22,41,9.0,4,10,Rural,Data Analyst,149613,0 +112712,Male,40,Diploma,15,64,94,4,32,6.0,7,30,Urban,HR Executive,65544,0 +112713,Male,52,Masters,3,86,49,27,67,0.0,0,89,Semi-Urban,Data Analyst,78090,1 +112714,Male,27,High School,19,1,79,96,93,6.0,2,51,Urban,Data Analyst,115639,0 +112715,Male,24,High School,14,25,83,26,77,7.0,4,6,Urban,Manager,29102,0 +112716,Male,35,Bachelors,8,2,67,45,3,4.0,7,26,Semi-Urban,Data Analyst,58343,0 +112717,Male,26,Masters,7,85,19,80,20,5.0,3,72,Semi-Urban,Data Analyst,59051,1 +112718,Female,46,Bachelors,8,93,79,63,81,6.0,2,29,Rural,Data Analyst,104847,1 +112719,Male,40,Bachelors,19,95,91,43,98,3.0,6,62,Rural,HR Executive,148601,1 +112720,Male,52,Diploma,17,28,35,99,12,1.0,6,86,Semi-Urban,Software Engineer,137500,1 +112721,Male,41,High School,0,95,64,36,79,0.0,2,87,Urban,HR Executive,135170,1 +112722,Male,44,Bachelors,17,98,0,94,42,7.0,1,73,Semi-Urban,ML Engineer,129913,1 +112723,Male,25,Bachelors,0,82,29,25,6,7.0,4,56,Urban,Data Analyst,89132,0 +112724,Female,44,Masters,17,43,33,31,92,2.0,0,68,Urban,Data Analyst,138853,0 +112725,Male,51,Bachelors,0,38,10,98,47,0.0,5,89,Semi-Urban,ML Engineer,120436,1 +112726,Female,30,Bachelors,15,20,33,9,75,8.0,5,20,Urban,Manager,67440,0 +112727,Male,42,Masters,11,18,96,57,64,2.0,7,5,Urban,HR Executive,102683,0 +112728,Male,27,Diploma,11,70,80,51,77,2.0,0,20,Urban,Manager,74578,0 +112729,Male,37,Masters,4,45,94,69,79,9.0,7,85,Urban,Software Engineer,52085,1 +112730,Male,47,Bachelors,8,8,80,98,35,2.0,5,66,Urban,Software Engineer,148780,1 +112731,Male,59,High School,5,23,82,88,73,3.0,7,96,Urban,Data Analyst,26183,1 +112732,Male,45,Diploma,10,10,5,21,18,7.0,0,78,Urban,Data Analyst,52224,0 +112733,Male,43,Bachelors,10,87,77,65,72,5.0,0,5,Urban,HR Executive,70962,0 +112734,Male,59,Bachelors,3,87,66,28,44,5.0,2,15,Urban,ML Engineer,124916,0 +112735,Male,56,Bachelors,19,65,79,84,77,6.0,7,95,Urban,Software Engineer,78312,1 +112736,Male,56,Bachelors,0,86,60,39,3,1.0,1,85,Urban,Software Engineer,73178,1 +112737,Male,49,Bachelors,11,49,66,52,71,4.0,3,89,Urban,HR Executive,72261,1 +112738,Male,44,Bachelors,4,20,72,83,20,5.0,3,50,Semi-Urban,Manager,148293,0 +112739,Male,25,PhD,18,11,75,58,34,3.0,2,47,Semi-Urban,Software Engineer,148016,0 +112740,Male,47,PhD,2,43,90,56,91,1.0,3,84,Rural,Software Engineer,117570,1 +112741,Female,48,Diploma,3,46,53,21,12,0.0,4,38,Urban,Manager,109679,0 +112742,Female,54,PhD,7,83,49,31,52,4.0,1,88,Semi-Urban,ML Engineer,77298,1 +112743,Male,27,PhD,8,97,78,1,43,6.0,1,97,Urban,HR Executive,88948,1 +112744,Male,29,Bachelors,19,10,34,74,14,3.0,5,41,Urban,Manager,99163,0 +112745,Female,28,High School,0,5,93,15,39,7.0,7,21,Rural,Manager,124267,0 +112746,Male,24,Bachelors,17,68,7,35,96,4.0,5,36,Urban,Data Analyst,111390,0 +112747,Male,32,Diploma,4,72,73,21,2,8.0,0,74,Urban,ML Engineer,45159,1 +112748,Female,53,PhD,8,72,75,22,10,9.0,0,3,Rural,HR Executive,105758,0 +112749,Female,28,PhD,9,34,31,60,53,6.0,2,65,Urban,Software Engineer,102605,0 +112750,Male,24,Masters,16,37,70,85,59,4.0,4,6,Urban,Manager,123034,0 +112751,Female,54,Bachelors,6,38,28,45,58,6.0,3,76,Urban,ML Engineer,125956,0 +112752,Female,54,Masters,15,62,69,87,73,3.0,3,75,Rural,Manager,110816,1 +112753,Female,37,Diploma,15,29,52,28,3,6.0,2,97,Semi-Urban,Data Analyst,129837,0 +112754,Female,46,Masters,18,72,42,12,41,7.0,7,70,Urban,ML Engineer,142057,0 +112755,Male,47,Bachelors,17,42,58,98,59,6.0,5,54,Rural,Manager,53767,1 +112756,Male,59,Bachelors,18,99,7,74,40,1.0,4,58,Semi-Urban,Software Engineer,20747,1 +112757,Male,37,Bachelors,14,35,1,59,11,8.0,3,31,Semi-Urban,ML Engineer,76643,0 +112758,Female,21,Bachelors,8,37,31,85,73,0.0,6,96,Urban,HR Executive,146466,1 +112759,Male,55,High School,3,37,95,19,79,7.0,4,57,Urban,Data Analyst,111269,0 +112760,Male,44,Bachelors,15,97,26,31,27,9.0,4,22,Urban,ML Engineer,81980,0 +112761,Female,24,Bachelors,4,20,52,14,43,8.0,2,35,Rural,Manager,36110,0 +112762,Female,45,Masters,2,56,49,38,18,8.0,3,73,Urban,Manager,148841,0 +112763,Male,28,High School,4,12,6,6,7,7.0,4,87,Urban,HR Executive,69857,0 +112764,Male,51,Bachelors,10,96,75,63,84,8.0,3,30,Urban,Software Engineer,133533,1 +112765,Male,23,Bachelors,2,32,97,52,91,7.0,0,63,Rural,HR Executive,113786,1 +112766,Male,38,Bachelors,6,78,86,40,95,9.0,0,86,Urban,ML Engineer,29251,1 +112767,Female,42,Masters,2,60,48,6,38,4.0,0,74,Rural,Manager,145469,0 +112768,Male,25,Bachelors,8,80,33,96,56,1.0,1,55,Urban,Data Analyst,145832,1 +112769,Male,35,Bachelors,5,46,38,25,92,7.0,5,81,Urban,HR Executive,32024,0 +112770,Male,43,Bachelors,17,92,71,53,98,8.0,7,99,Semi-Urban,Software Engineer,138815,1 +112771,Male,30,Bachelors,6,40,33,80,63,1.0,2,47,Rural,ML Engineer,74256,0 +112772,Female,43,Diploma,18,9,28,50,73,6.0,4,58,Semi-Urban,HR Executive,137576,0 +112773,Male,59,Masters,3,65,92,16,61,7.0,5,15,Rural,Data Analyst,62849,0 +112774,Male,54,Bachelors,5,23,25,43,85,1.0,6,12,Urban,HR Executive,116163,0 +112775,Male,33,Bachelors,10,93,26,41,98,8.0,1,6,Semi-Urban,HR Executive,20641,0 +112776,Male,25,High School,18,59,30,88,73,4.0,3,17,Urban,Manager,134987,0 +112777,Other,32,Diploma,14,81,42,66,9,9.0,2,49,Urban,HR Executive,104573,0 +112778,Male,41,Masters,2,72,23,54,97,6.0,7,88,Urban,HR Executive,85018,1 +112779,Male,55,Bachelors,15,97,64,62,86,1.0,1,47,Rural,Data Analyst,96149,1 +112780,Female,33,Bachelors,10,37,37,26,40,0.0,1,82,Urban,Data Analyst,114862,0 +112781,Other,36,Masters,10,64,77,96,91,8.0,6,20,Urban,Manager,25590,1 +112782,Other,58,Masters,19,66,26,44,93,4.0,0,26,Urban,Software Engineer,75309,0 +112783,Male,52,Masters,18,22,48,36,48,1.0,0,1,Urban,Software Engineer,79019,0 +112784,Male,48,High School,10,57,54,26,10,8.0,7,16,Semi-Urban,Manager,62625,0 +112785,Other,25,Bachelors,0,18,10,73,54,0.0,1,42,Urban,Data Analyst,44469,0 +112786,Other,35,Bachelors,1,4,56,77,9,9.0,3,37,Urban,Manager,120190,0 +112787,Male,35,High School,1,8,21,40,33,1.0,1,93,Urban,HR Executive,39298,0 +112788,Male,57,Bachelors,7,68,55,59,2,3.0,2,1,Urban,HR Executive,66185,0 +112789,Female,40,Bachelors,17,47,4,1,55,3.0,5,50,Semi-Urban,Data Analyst,50720,0 +112790,Male,34,Bachelors,13,53,40,24,55,7.0,3,45,Semi-Urban,ML Engineer,56485,0 +112791,Male,47,Diploma,17,15,20,57,8,0.0,6,96,Urban,ML Engineer,38721,0 +112792,Male,54,Bachelors,12,0,94,35,78,4.0,1,21,Rural,Software Engineer,87002,0 +112793,Female,36,Masters,9,80,73,3,42,9.0,1,92,Urban,HR Executive,125409,1 +112794,Male,26,Masters,16,44,55,58,93,4.0,6,16,Rural,ML Engineer,38016,0 +112795,Male,55,Masters,2,14,17,39,14,7.0,5,86,Urban,Manager,38330,0 +112796,Female,59,High School,3,51,39,93,50,7.0,3,42,Semi-Urban,Software Engineer,145327,0 +112797,Female,55,Masters,3,55,72,71,85,3.0,4,53,Semi-Urban,Software Engineer,140323,1 +112798,Other,23,Diploma,17,35,3,20,55,6.0,0,91,Urban,Software Engineer,146263,0 +112799,Male,53,Masters,0,90,76,20,78,4.0,5,33,Semi-Urban,ML Engineer,118076,0 +112800,Male,44,Masters,11,87,40,36,14,9.0,7,93,Semi-Urban,Data Analyst,40963,1 +112801,Male,21,Masters,15,97,34,65,20,5.0,3,14,Urban,HR Executive,131829,0 +112802,Male,39,Bachelors,16,54,18,84,46,7.0,2,19,Urban,Data Analyst,81565,0 +112803,Male,44,Masters,3,67,34,5,80,4.0,2,12,Urban,Manager,28291,0 +112804,Male,31,High School,7,34,3,48,56,2.0,1,89,Urban,Data Analyst,23022,0 +112805,Male,37,Bachelors,0,52,27,97,8,8.0,6,46,Urban,Manager,128055,0 +112806,Male,52,Bachelors,0,9,18,16,39,5.0,4,76,Urban,HR Executive,64355,0 +112807,Male,46,Masters,9,24,26,85,40,9.0,3,17,Semi-Urban,ML Engineer,117966,0 +112808,Female,46,Bachelors,3,10,53,64,65,2.0,0,63,Urban,HR Executive,32629,0 +112809,Female,51,Masters,1,63,60,90,2,0.0,7,78,Semi-Urban,Data Analyst,143768,1 +112810,Male,57,High School,11,58,79,90,3,6.0,6,77,Urban,Data Analyst,87505,1 +112811,Male,28,Bachelors,17,66,71,16,50,0.0,4,36,Urban,Software Engineer,40478,0 +112812,Male,29,Bachelors,16,89,76,75,52,1.0,1,57,Semi-Urban,HR Executive,105017,1 +112813,Male,38,Masters,8,45,18,11,82,4.0,4,51,Urban,Manager,26150,0 +112814,Other,47,Diploma,13,42,63,80,88,5.0,2,48,Rural,ML Engineer,100373,0 +112815,Male,25,High School,14,87,2,95,72,9.0,0,64,Rural,ML Engineer,132564,1 +112816,Male,30,High School,18,40,71,49,4,5.0,6,23,Rural,HR Executive,93059,0 +112817,Male,37,Bachelors,5,8,66,64,81,0.0,5,27,Rural,ML Engineer,148182,0 +112818,Female,26,Bachelors,11,18,70,63,36,2.0,0,80,Rural,Manager,138516,0 +112819,Female,26,PhD,15,62,13,52,14,7.0,1,6,Urban,HR Executive,33363,0 +112820,Female,25,High School,8,75,14,86,35,3.0,3,21,Urban,ML Engineer,64248,0 +112821,Male,23,Bachelors,17,21,82,23,6,2.0,7,87,Urban,Manager,39761,0 +112822,Other,57,Masters,18,76,45,19,60,3.0,0,92,Semi-Urban,Data Analyst,56954,0 +112823,Male,51,Masters,13,88,80,86,55,9.0,1,70,Urban,Software Engineer,139572,1 +112824,Female,39,Bachelors,3,66,12,52,28,8.0,2,29,Rural,Manager,59144,0 +112825,Female,56,High School,7,47,77,92,57,1.0,3,53,Urban,Software Engineer,72694,1 +112826,Other,36,Diploma,10,78,98,4,46,1.0,7,66,Urban,HR Executive,137117,1 +112827,Male,50,Bachelors,3,4,18,36,85,0.0,0,25,Semi-Urban,HR Executive,23367,0 +112828,Male,50,Bachelors,3,77,70,4,99,2.0,0,22,Semi-Urban,Data Analyst,21434,0 +112829,Female,57,Masters,9,83,60,37,90,3.0,2,9,Rural,Data Analyst,91409,0 +112830,Male,36,Bachelors,7,39,80,98,90,8.0,6,52,Urban,HR Executive,103600,1 +112831,Female,56,Bachelors,17,74,26,14,29,2.0,7,70,Urban,ML Engineer,72809,0 +112832,Female,58,Bachelors,15,6,31,25,23,7.0,0,73,Semi-Urban,ML Engineer,92596,0 +112833,Male,44,Masters,8,61,80,97,41,0.0,3,87,Semi-Urban,Data Analyst,124477,1 +112834,Male,28,High School,15,86,49,76,16,0.0,0,36,Rural,HR Executive,56337,1 +112835,Female,21,Bachelors,10,65,94,87,38,8.0,4,52,Rural,Data Analyst,55037,1 +112836,Male,23,Bachelors,15,49,66,90,23,6.0,2,26,Urban,Manager,54663,0 +112837,Male,32,High School,19,91,18,54,67,3.0,5,28,Semi-Urban,ML Engineer,95668,0 +112838,Male,29,Bachelors,9,56,73,24,41,8.0,0,23,Semi-Urban,Software Engineer,90317,0 +112839,Male,49,Bachelors,10,48,47,60,18,6.0,7,27,Semi-Urban,Software Engineer,95071,0 +112840,Male,48,Masters,15,98,15,63,27,5.0,7,80,Urban,Software Engineer,56256,1 +112841,Male,24,Masters,1,43,71,3,29,1.0,6,6,Urban,Data Analyst,95559,0 +112842,Female,27,Diploma,19,77,43,74,15,1.0,6,9,Urban,Software Engineer,75464,0 +112843,Female,29,Diploma,18,89,81,23,40,7.0,3,22,Semi-Urban,Data Analyst,73004,0 +112844,Male,46,Bachelors,9,72,67,41,33,6.0,3,51,Rural,HR Executive,79815,0 +112845,Male,22,Bachelors,3,42,73,93,73,4.0,1,64,Urban,Software Engineer,69012,1 +112846,Other,45,Diploma,1,74,57,97,16,2.0,0,48,Urban,HR Executive,119294,1 +112847,Male,22,Diploma,7,52,85,14,19,8.0,7,52,Urban,HR Executive,107257,0 +112848,Male,23,Masters,18,72,39,88,47,0.0,5,17,Semi-Urban,HR Executive,29892,0 +112849,Male,35,Bachelors,2,93,62,21,50,8.0,4,77,Semi-Urban,Software Engineer,106762,1 +112850,Male,44,Bachelors,3,51,6,56,60,8.0,3,87,Urban,HR Executive,22238,0 +112851,Female,36,High School,12,27,24,5,94,3.0,2,39,Rural,HR Executive,110336,0 +112852,Female,25,Bachelors,18,48,68,98,29,3.0,1,49,Urban,Manager,80737,1 +112853,Female,58,Bachelors,4,45,31,73,58,2.0,7,60,Urban,HR Executive,112359,0 +112854,Other,21,Diploma,8,86,13,52,61,1.0,5,10,Semi-Urban,ML Engineer,45429,0 +112855,Male,57,Bachelors,3,40,53,28,54,5.0,0,13,Semi-Urban,Data Analyst,76762,0 +112856,Male,36,Masters,16,84,35,35,32,1.0,5,16,Rural,Software Engineer,44609,0 +112857,Female,38,Bachelors,17,42,77,65,97,2.0,1,90,Semi-Urban,ML Engineer,120891,1 +112858,Female,27,Bachelors,12,10,80,35,28,6.0,1,4,Rural,Data Analyst,137845,0 +112859,Male,41,PhD,19,24,13,45,34,9.0,4,70,Semi-Urban,ML Engineer,39671,0 +112860,Male,50,Bachelors,15,99,40,32,74,0.0,4,4,Semi-Urban,Data Analyst,102970,0 +112861,Female,39,Masters,12,94,96,57,57,2.0,3,21,Urban,ML Engineer,34339,1 +112862,Male,43,Diploma,15,98,59,65,46,9.0,1,14,Semi-Urban,ML Engineer,65885,1 +112863,Male,25,Masters,16,16,97,5,48,9.0,7,25,Urban,ML Engineer,115021,0 +112864,Male,57,Diploma,6,37,48,85,92,2.0,6,28,Urban,Manager,42453,0 +112865,Male,41,High School,13,89,43,38,75,4.0,0,99,Urban,ML Engineer,97201,1 +112866,Male,52,Masters,13,92,52,48,41,5.0,0,46,Rural,Manager,88134,1 +112867,Male,39,Masters,9,1,24,96,71,1.0,3,21,Urban,HR Executive,80658,0 +112868,Male,55,Diploma,17,86,69,54,70,1.0,4,10,Rural,HR Executive,59016,0 +112869,Male,40,Bachelors,7,4,19,8,41,9.0,6,94,Semi-Urban,Software Engineer,58191,0 +112870,Male,31,PhD,1,22,43,15,8,3.0,0,93,Semi-Urban,Manager,79811,0 +112871,Female,27,Bachelors,18,96,2,83,68,1.0,3,32,Urban,Software Engineer,102073,0 +112872,Female,47,Bachelors,15,76,35,73,48,3.0,6,20,Urban,Data Analyst,79898,0 +112873,Female,40,Diploma,1,96,46,51,10,5.0,4,50,Urban,Software Engineer,66465,1 +112874,Male,35,Masters,16,89,61,27,69,7.0,5,87,Urban,Software Engineer,87888,1 +112875,Male,33,Diploma,8,52,41,7,28,8.0,6,67,Urban,Data Analyst,134366,0 +112876,Male,22,Diploma,14,78,5,67,4,8.0,2,4,Urban,ML Engineer,50301,0 +112877,Male,38,Masters,7,59,91,52,41,5.0,7,76,Urban,Data Analyst,121265,1 +112878,Female,28,Bachelors,14,52,7,81,92,1.0,2,21,Urban,Data Analyst,113799,0 +112879,Male,30,Bachelors,2,53,7,45,16,4.0,3,61,Rural,Manager,126807,0 +112880,Male,57,Bachelors,14,74,79,20,39,4.0,4,52,Urban,Software Engineer,23864,0 +112881,Male,57,Bachelors,7,1,76,52,15,3.0,0,12,Rural,Data Analyst,66657,0 +112882,Male,30,Bachelors,0,2,77,25,80,5.0,6,27,Urban,HR Executive,86191,0 +112883,Male,37,Bachelors,0,49,10,53,37,1.0,0,16,Urban,Software Engineer,23998,0 +112884,Male,59,High School,9,23,90,7,99,1.0,7,41,Urban,Software Engineer,118826,0 +112885,Male,59,Diploma,9,45,53,80,45,8.0,0,66,Urban,Manager,89835,1 +112886,Female,34,PhD,15,17,72,57,5,7.0,6,31,Urban,Data Analyst,120648,0 +112887,Male,42,High School,3,90,8,29,5,1.0,7,61,Urban,Data Analyst,139576,0 +112888,Male,29,Bachelors,10,83,74,20,6,6.0,4,11,Semi-Urban,ML Engineer,66697,0 +112889,Male,41,Bachelors,5,21,83,56,48,4.0,0,30,Rural,Manager,142673,0 +112890,Male,22,Bachelors,6,25,82,55,71,8.0,6,12,Urban,ML Engineer,55751,0 +112891,Female,27,Masters,9,70,92,83,84,9.0,2,61,Urban,ML Engineer,86615,1 +112892,Female,52,Diploma,7,63,83,34,92,2.0,6,11,Semi-Urban,HR Executive,59274,0 +112893,Female,34,Masters,10,0,66,68,59,0.0,6,84,Semi-Urban,HR Executive,139468,0 +112894,Male,42,Bachelors,6,51,13,37,71,9.0,7,7,Urban,Manager,149085,0 +112895,Male,54,Bachelors,3,50,94,23,74,7.0,1,33,Semi-Urban,ML Engineer,93400,0 +112896,Male,24,Bachelors,10,18,75,53,10,0.0,4,44,Rural,Software Engineer,123930,0 +112897,Male,36,PhD,19,18,89,6,5,1.0,3,21,Rural,Manager,78667,0 +112898,Female,32,Bachelors,15,39,41,21,15,8.0,5,79,Rural,ML Engineer,54076,0 +112899,Male,48,Diploma,6,6,6,12,36,5.0,4,20,Rural,Software Engineer,40371,0 +112900,Male,34,Masters,13,62,86,58,45,3.0,6,83,Rural,Software Engineer,149248,1 +112901,Female,51,High School,6,54,12,87,59,3.0,1,98,Urban,HR Executive,20315,1 +112902,Male,38,Bachelors,6,77,27,44,31,9.0,2,42,Urban,ML Engineer,29850,0 +112903,Female,37,Bachelors,0,93,94,71,77,4.0,2,80,Rural,Manager,64532,1 +112904,Male,53,Bachelors,16,48,77,57,63,1.0,2,25,Urban,Manager,42953,0 +112905,Female,36,Bachelors,7,24,85,2,28,3.0,4,43,Semi-Urban,HR Executive,122180,0 +112906,Female,36,High School,7,95,15,72,51,9.0,0,54,Semi-Urban,Data Analyst,48282,0 +112907,Female,23,Diploma,5,22,72,16,29,3.0,7,89,Rural,Data Analyst,125207,0 +112908,Female,43,Bachelors,11,70,2,73,4,8.0,6,74,Semi-Urban,Software Engineer,134410,0 +112909,Male,41,High School,17,19,72,21,71,0.0,7,15,Urban,Software Engineer,140421,0 +112910,Female,45,Bachelors,4,65,17,50,26,8.0,5,94,Semi-Urban,HR Executive,143821,0 +112911,Female,36,Masters,17,25,64,8,68,1.0,6,73,Urban,Manager,85120,0 +112912,Female,44,Bachelors,10,23,64,55,10,2.0,5,87,Urban,Data Analyst,45748,0 +112913,Other,37,Masters,6,82,30,25,13,6.0,1,57,Urban,Manager,58513,0 +112914,Male,29,Masters,14,42,31,79,63,1.0,4,31,Urban,Manager,99323,0 +112915,Female,37,High School,2,66,7,8,61,8.0,3,63,Rural,Software Engineer,49891,0 +112916,Male,35,Bachelors,10,91,78,42,84,2.0,3,8,Urban,Manager,20150,0 +112917,Male,44,Diploma,13,48,32,4,26,4.0,2,4,Urban,Software Engineer,114873,0 +112918,Female,42,Masters,15,97,28,46,70,4.0,5,28,Urban,ML Engineer,147677,0 +112919,Male,23,Masters,9,78,12,96,21,2.0,3,98,Urban,Manager,68737,1 +112920,Female,56,Bachelors,10,28,5,38,82,5.0,4,95,Urban,HR Executive,60448,0 +112921,Female,52,Diploma,16,35,87,21,65,4.0,1,69,Rural,Manager,103998,0 +112922,Male,58,Bachelors,13,78,16,7,19,6.0,7,97,Urban,ML Engineer,90304,0 +112923,Female,24,Diploma,11,37,69,51,76,9.0,0,81,Urban,HR Executive,63860,0 +112924,Female,42,Bachelors,11,22,89,18,27,8.0,4,88,Semi-Urban,Manager,112095,0 +112925,Female,55,Diploma,6,45,91,21,91,4.0,4,45,Urban,HR Executive,21559,0 +112926,Female,34,High School,3,97,92,72,1,3.0,5,15,Semi-Urban,ML Engineer,92374,1 +112927,Male,55,Diploma,3,86,75,3,74,4.0,1,49,Rural,ML Engineer,107575,0 +112928,Female,54,Bachelors,4,38,80,84,82,8.0,1,70,Urban,Manager,99673,1 +112929,Female,34,Bachelors,19,83,94,39,94,5.0,4,26,Urban,Software Engineer,45874,1 +112930,Male,58,Diploma,17,45,27,12,29,3.0,7,70,Urban,Manager,79631,0 +112931,Male,57,Bachelors,14,34,33,43,99,7.0,0,89,Rural,Data Analyst,145795,0 +112932,Female,45,Masters,17,51,11,60,61,9.0,7,22,Semi-Urban,Data Analyst,32534,0 +112933,Male,56,Bachelors,1,87,0,87,73,6.0,1,60,Urban,Data Analyst,60724,0 +112934,Other,23,Diploma,19,25,73,36,75,5.0,4,95,Urban,Software Engineer,125746,0 +112935,Male,45,PhD,11,40,97,50,67,3.0,4,57,Urban,ML Engineer,23526,1 +112936,Male,28,Masters,8,99,63,38,7,7.0,2,53,Urban,HR Executive,38704,1 +112937,Female,23,Diploma,14,56,1,37,90,7.0,5,50,Urban,ML Engineer,94114,0 +112938,Male,39,High School,8,28,12,37,77,1.0,3,88,Semi-Urban,ML Engineer,65529,0 +112939,Other,43,Diploma,12,99,38,32,50,2.0,0,53,Urban,Manager,53404,0 +112940,Male,36,Bachelors,17,90,1,24,88,1.0,5,69,Urban,ML Engineer,109313,0 +112941,Male,34,Bachelors,18,70,73,32,33,6.0,3,61,Urban,HR Executive,25738,1 +112942,Female,43,Masters,16,50,20,32,59,1.0,4,33,Urban,Manager,93241,0 +112943,Female,26,Bachelors,13,98,64,87,6,6.0,0,11,Urban,Data Analyst,25580,1 +112944,Male,43,Bachelors,14,14,5,93,94,0.0,5,16,Urban,Data Analyst,35952,0 +112945,Male,55,Masters,14,14,30,75,64,7.0,4,22,Urban,ML Engineer,61213,0 +112946,Female,44,Masters,1,19,51,95,58,8.0,5,13,Urban,ML Engineer,43041,0 +112947,Female,56,Masters,14,64,39,75,40,2.0,6,2,Semi-Urban,ML Engineer,22343,0 +112948,Other,29,Bachelors,10,79,57,20,89,9.0,5,27,Semi-Urban,Manager,69666,0 +112949,Male,48,PhD,2,52,64,98,51,0.0,1,72,Urban,Software Engineer,139017,1 +112950,Male,45,Bachelors,19,51,54,29,98,5.0,4,63,Semi-Urban,Manager,77164,0 +112951,Other,24,Bachelors,9,7,33,57,50,3.0,1,17,Urban,HR Executive,36368,0 +112952,Male,21,Bachelors,2,15,34,36,53,0.0,7,43,Urban,Software Engineer,123911,0 +112953,Female,43,Masters,6,16,57,19,34,5.0,1,84,Urban,Data Analyst,54073,0 +112954,Female,26,Masters,17,8,39,59,13,8.0,4,82,Rural,ML Engineer,64887,0 +112955,Male,52,Bachelors,4,96,14,80,47,3.0,2,75,Urban,Manager,108285,1 +112956,Female,40,High School,5,95,69,95,16,5.0,1,81,Semi-Urban,Data Analyst,56668,1 +112957,Female,22,Bachelors,4,24,56,90,33,0.0,7,37,Urban,Data Analyst,46356,0 +112958,Male,41,High School,10,35,83,60,74,1.0,4,34,Urban,Data Analyst,54590,0 +112959,Other,24,Bachelors,1,30,51,3,26,1.0,2,0,Urban,Manager,37193,0 +112960,Female,34,Masters,13,53,29,60,15,2.0,4,58,Urban,HR Executive,63063,0 +112961,Other,43,Masters,3,34,77,24,78,9.0,6,86,Urban,Data Analyst,73617,0 +112962,Male,21,PhD,18,90,40,59,11,8.0,3,76,Urban,Manager,96079,1 +112963,Male,30,Bachelors,11,98,78,20,77,5.0,3,29,Urban,HR Executive,63513,0 +112964,Male,32,High School,2,5,80,98,96,5.0,1,11,Urban,Data Analyst,97525,0 +112965,Female,41,Bachelors,19,51,66,84,1,2.0,3,41,Urban,HR Executive,127040,1 +112966,Male,21,Bachelors,17,92,62,55,25,8.0,0,51,Semi-Urban,Data Analyst,131147,1 +112967,Male,43,Bachelors,18,78,40,85,60,2.0,7,11,Semi-Urban,HR Executive,91696,0 +112968,Female,59,Diploma,7,70,75,44,25,5.0,2,47,Rural,ML Engineer,116807,0 +112969,Male,38,Bachelors,4,2,29,1,9,1.0,2,26,Urban,Manager,116557,0 +112970,Male,32,Bachelors,6,43,74,77,64,4.0,0,60,Urban,Data Analyst,139290,1 +112971,Male,49,High School,10,39,66,20,19,5.0,5,68,Urban,Manager,58930,0 +112972,Male,31,Bachelors,14,99,42,70,59,6.0,4,98,Rural,Data Analyst,144111,1 +112973,Male,23,Bachelors,9,66,86,59,34,0.0,0,11,Urban,Software Engineer,62454,0 +112974,Male,36,PhD,17,25,62,9,28,9.0,3,44,Urban,HR Executive,68826,0 +112975,Male,39,Masters,2,2,0,83,15,0.0,3,64,Semi-Urban,Manager,22524,0 +112976,Male,55,Diploma,13,57,48,92,78,1.0,3,18,Rural,Manager,34203,0 +112977,Male,51,Bachelors,15,26,8,3,63,6.0,2,19,Rural,HR Executive,104079,0 +112978,Other,27,Bachelors,18,72,74,50,36,9.0,2,95,Urban,Software Engineer,120106,1 +112979,Other,32,Diploma,6,34,85,72,56,2.0,7,70,Urban,Manager,23080,1 +112980,Male,59,Diploma,1,55,84,65,60,5.0,5,9,Urban,Software Engineer,69404,0 +112981,Female,29,Diploma,2,33,57,42,44,6.0,5,22,Semi-Urban,Data Analyst,36144,0 +112982,Male,59,Diploma,18,0,97,74,82,8.0,6,39,Urban,Software Engineer,147775,0 +112983,Male,34,Bachelors,17,55,1,77,38,0.0,7,61,Semi-Urban,Software Engineer,102538,0 +112984,Male,54,Bachelors,19,94,20,87,22,2.0,5,10,Rural,Manager,46630,0 +112985,Female,58,Bachelors,19,13,79,43,93,1.0,7,20,Urban,Manager,81576,0 +112986,Male,59,Diploma,9,84,52,96,62,1.0,5,81,Rural,HR Executive,140249,1 +112987,Male,54,Masters,5,37,88,2,12,0.0,1,66,Urban,Manager,144347,0 +112988,Female,31,Bachelors,2,49,74,68,67,7.0,5,84,Urban,Software Engineer,148287,1 +112989,Other,52,Masters,8,59,13,42,9,5.0,5,31,Urban,HR Executive,129586,0 +112990,Male,40,Diploma,14,4,28,58,91,5.0,6,37,Urban,Software Engineer,46025,0 +112991,Male,32,Bachelors,3,90,59,49,83,8.0,3,21,Urban,Software Engineer,82190,0 +112992,Male,53,Masters,7,73,44,93,32,2.0,2,58,Rural,Software Engineer,41648,1 +112993,Male,59,Bachelors,8,19,29,77,65,9.0,6,32,Rural,HR Executive,46196,0 +112994,Male,27,Bachelors,11,79,14,6,50,2.0,3,89,Rural,ML Engineer,31770,0 +112995,Female,36,Masters,11,46,27,6,54,1.0,0,30,Urban,Software Engineer,78318,0 +112996,Male,55,Masters,13,27,92,1,73,2.0,6,58,Semi-Urban,Data Analyst,67742,0 +112997,Male,39,Bachelors,17,79,82,23,3,0.0,3,57,Rural,Manager,117023,1 +112998,Female,38,Masters,14,69,70,93,77,4.0,5,98,Urban,Data Analyst,71076,1 +112999,Female,45,High School,10,35,42,40,42,6.0,3,86,Rural,ML Engineer,82515,0 +113000,Female,31,High School,10,60,79,41,1,1.0,6,75,Urban,HR Executive,61257,1 +113001,Male,56,Masters,5,68,23,16,37,6.0,4,36,Urban,ML Engineer,56992,0 +113002,Female,27,Masters,3,41,36,62,78,0.0,0,24,Urban,Manager,23373,0 +113003,Female,40,Masters,16,64,17,68,73,8.0,0,89,Semi-Urban,HR Executive,92566,0 +113004,Female,49,Diploma,8,76,18,2,53,6.0,1,41,Rural,Software Engineer,98175,0 +113005,Female,26,High School,9,81,14,62,60,3.0,0,48,Semi-Urban,Manager,82317,0 +113006,Female,39,Diploma,17,65,50,98,89,1.0,6,90,Semi-Urban,Data Analyst,48189,1 +113007,Female,38,Masters,1,51,88,84,62,0.0,4,68,Urban,Data Analyst,36300,1 +113008,Female,21,Bachelors,11,23,40,40,31,1.0,6,55,Rural,HR Executive,102283,0 +113009,Male,51,Bachelors,16,63,61,35,0,4.0,4,44,Urban,Manager,41417,0 +113010,Male,30,Diploma,1,65,49,88,99,7.0,5,49,Rural,Data Analyst,86808,1 +113011,Male,49,Bachelors,12,26,68,36,11,7.0,6,72,Urban,HR Executive,136922,0 +113012,Male,33,Bachelors,13,96,80,4,89,1.0,3,82,Rural,Manager,142617,1 +113013,Female,45,High School,9,42,79,15,61,8.0,1,20,Urban,HR Executive,73167,0 +113014,Other,52,Bachelors,4,59,33,27,46,9.0,6,13,Rural,ML Engineer,98422,0 +113015,Male,43,Bachelors,16,66,60,30,10,7.0,0,92,Rural,HR Executive,79063,1 +113016,Male,50,Diploma,9,65,88,64,71,4.0,3,51,Urban,Software Engineer,71642,1 +113017,Male,29,Diploma,3,53,50,54,65,6.0,5,35,Rural,Software Engineer,60807,0 +113018,Male,30,Diploma,16,4,88,89,41,3.0,2,4,Rural,Manager,134613,0 +113019,Male,54,Bachelors,13,63,24,71,56,5.0,3,34,Semi-Urban,ML Engineer,70855,0 +113020,Female,52,Bachelors,18,22,15,71,33,6.0,4,74,Rural,Software Engineer,145494,0 +113021,Male,21,Masters,19,64,84,70,90,1.0,4,20,Urban,Data Analyst,29153,1 +113022,Male,47,Diploma,4,56,52,8,92,2.0,5,81,Rural,Data Analyst,72590,0 +113023,Male,33,PhD,13,64,96,66,34,9.0,7,31,Semi-Urban,Manager,61665,1 +113024,Male,24,Bachelors,0,38,92,20,8,5.0,3,27,Urban,Software Engineer,50223,0 +113025,Female,53,Bachelors,10,66,60,90,5,0.0,3,52,Urban,Data Analyst,90280,1 +113026,Male,34,Bachelors,10,65,86,53,48,6.0,2,19,Semi-Urban,Manager,93132,0 +113027,Male,30,Masters,13,81,71,75,59,4.0,0,26,Urban,Data Analyst,43194,1 +113028,Male,37,Masters,17,42,19,29,0,1.0,2,41,Semi-Urban,HR Executive,25839,0 +113029,Male,38,Diploma,19,61,3,90,19,1.0,0,99,Rural,HR Executive,109813,1 +113030,Male,41,Bachelors,2,38,1,93,65,8.0,2,91,Semi-Urban,Manager,77019,0 +113031,Female,39,Bachelors,14,2,53,42,20,6.0,2,31,Semi-Urban,Data Analyst,69396,0 +113032,Male,24,Diploma,3,98,99,46,88,0.0,3,69,Urban,Manager,116793,1 +113033,Male,28,Diploma,4,16,7,10,46,1.0,5,80,Semi-Urban,Manager,82266,0 +113034,Female,27,Masters,18,73,39,79,0,4.0,5,74,Urban,Data Analyst,77939,1 +113035,Female,50,Bachelors,4,26,63,38,11,2.0,2,71,Semi-Urban,ML Engineer,90891,0 +113036,Female,50,Masters,17,60,92,9,41,4.0,3,65,Urban,Software Engineer,65841,0 +113037,Male,41,Bachelors,5,17,65,70,57,1.0,4,96,Urban,Software Engineer,36939,1 +113038,Female,31,Bachelors,6,48,63,71,16,8.0,7,59,Semi-Urban,Data Analyst,57275,1 +113039,Female,43,Bachelors,16,10,65,59,79,7.0,3,10,Urban,Manager,75968,0 +113040,Female,36,Masters,15,95,55,45,65,5.0,1,82,Semi-Urban,Software Engineer,52671,1 +113041,Male,52,PhD,7,14,18,1,44,6.0,7,13,Rural,Manager,41248,0 +113042,Female,32,Bachelors,1,4,42,96,86,1.0,0,29,Urban,Data Analyst,55089,0 +113043,Male,35,High School,8,94,64,24,20,0.0,2,4,Rural,HR Executive,30367,0 +113044,Male,39,Masters,10,57,38,18,67,6.0,7,67,Urban,Software Engineer,104971,0 +113045,Male,46,PhD,0,30,70,14,89,8.0,2,16,Urban,ML Engineer,88960,0 +113046,Male,53,Masters,6,52,36,73,66,5.0,7,26,Urban,Software Engineer,129016,0 +113047,Female,58,Diploma,13,70,57,80,2,4.0,7,61,Semi-Urban,Manager,93877,1 +113048,Female,30,Bachelors,2,56,4,39,34,7.0,2,85,Urban,Software Engineer,77719,0 +113049,Male,46,High School,11,31,9,65,27,5.0,2,25,Rural,ML Engineer,58150,0 +113050,Female,48,High School,16,28,36,41,26,2.0,0,19,Urban,Manager,22354,0 +113051,Male,37,Diploma,8,58,82,15,11,7.0,1,96,Urban,Software Engineer,37636,1 +113052,Male,43,Masters,17,9,53,34,90,5.0,3,90,Urban,Manager,100817,0 +113053,Male,35,Diploma,4,64,90,38,45,8.0,4,43,Semi-Urban,HR Executive,26276,1 +113054,Male,40,Bachelors,17,67,94,10,53,3.0,4,68,Urban,Software Engineer,95388,1 +113055,Male,41,Masters,13,54,68,3,56,4.0,0,91,Rural,Data Analyst,114054,0 +113056,Male,55,PhD,14,39,86,5,77,9.0,3,34,Urban,Software Engineer,70701,0 +113057,Male,59,High School,15,46,38,84,60,2.0,3,10,Rural,HR Executive,79558,0 +113058,Male,44,Masters,2,25,46,89,79,7.0,7,72,Semi-Urban,Manager,52589,0 +113059,Male,23,Diploma,11,68,56,69,27,6.0,7,91,Urban,Manager,25101,1 +113060,Male,32,High School,13,35,83,87,85,8.0,7,94,Semi-Urban,HR Executive,128381,1 +113061,Male,25,High School,12,82,70,53,55,5.0,5,62,Rural,Data Analyst,107728,1 +113062,Other,25,High School,7,62,85,10,36,1.0,3,29,Urban,HR Executive,131973,0 +113063,Female,31,Bachelors,10,2,54,20,91,5.0,6,39,Urban,HR Executive,97512,0 +113064,Male,55,Bachelors,9,79,79,58,97,6.0,3,7,Urban,Data Analyst,46323,0 +113065,Female,29,PhD,2,90,54,85,96,9.0,3,67,Rural,Manager,59160,1 +113066,Male,57,PhD,16,57,49,81,79,4.0,0,63,Urban,ML Engineer,125900,1 +113067,Male,21,Bachelors,1,9,83,65,66,9.0,7,18,Urban,Data Analyst,37707,0 +113068,Male,35,Bachelors,10,87,46,21,97,6.0,3,8,Urban,Manager,133999,0 +113069,Male,42,Masters,18,40,96,36,59,2.0,1,76,Urban,Software Engineer,78256,1 +113070,Female,26,Bachelors,12,64,77,81,52,8.0,3,96,Rural,Software Engineer,102017,1 +113071,Female,21,Masters,18,23,88,93,77,8.0,6,91,Urban,ML Engineer,72398,1 +113072,Other,56,Diploma,11,84,93,76,36,5.0,6,68,Semi-Urban,ML Engineer,137398,1 +113073,Female,35,Diploma,19,28,43,87,87,3.0,6,90,Urban,Software Engineer,106498,1 +113074,Male,47,Masters,11,39,46,91,71,0.0,4,81,Semi-Urban,Data Analyst,96943,1 +113075,Male,48,Bachelors,6,76,18,74,10,0.0,7,59,Urban,ML Engineer,56329,0 +113076,Male,52,Bachelors,6,23,2,80,78,1.0,2,96,Urban,Software Engineer,29576,0 +113077,Male,55,Bachelors,15,63,0,33,90,2.0,7,18,Urban,Software Engineer,123545,0 +113078,Male,24,High School,10,79,26,72,24,8.0,2,32,Rural,Data Analyst,81844,0 +113079,Female,57,Masters,17,41,73,21,9,2.0,4,71,Rural,Software Engineer,60818,0 +113080,Male,26,Bachelors,8,81,38,26,33,5.0,6,96,Urban,HR Executive,140670,1 +113081,Female,45,Bachelors,8,51,13,61,48,8.0,2,12,Semi-Urban,Manager,128163,0 +113082,Female,55,Bachelors,7,86,78,56,1,7.0,6,9,Urban,Software Engineer,115097,0 +113083,Male,21,Bachelors,2,3,42,90,88,3.0,6,94,Urban,Data Analyst,26826,0 +113084,Male,56,Bachelors,9,77,11,55,19,1.0,7,10,Rural,Manager,56109,0 +113085,Male,49,PhD,15,90,19,53,83,4.0,2,75,Urban,Data Analyst,107125,1 +113086,Female,53,Masters,18,93,38,71,43,8.0,1,20,Urban,Data Analyst,77211,0 +113087,Female,29,Bachelors,7,43,23,63,99,5.0,0,18,Urban,Manager,90783,0 +113088,Female,24,Diploma,11,72,50,50,44,0.0,4,23,Urban,Software Engineer,126139,0 +113089,Male,41,Masters,12,26,85,38,24,9.0,3,77,Semi-Urban,Data Analyst,86863,0 +113090,Male,38,PhD,10,33,3,54,76,3.0,7,90,Rural,ML Engineer,86204,0 +113091,Male,50,High School,18,19,47,56,97,8.0,3,37,Urban,Manager,120336,0 +113092,Male,48,Diploma,15,62,85,60,26,4.0,7,98,Urban,HR Executive,20585,1 +113093,Male,54,Masters,4,64,30,30,36,1.0,5,23,Semi-Urban,ML Engineer,76424,0 +113094,Female,47,Bachelors,11,45,99,67,70,2.0,4,55,Urban,ML Engineer,30394,1 +113095,Female,58,Diploma,9,38,15,60,22,9.0,0,96,Urban,Manager,76320,0 +113096,Female,30,PhD,10,50,47,40,73,9.0,4,85,Semi-Urban,Software Engineer,50629,0 +113097,Male,31,Diploma,7,23,90,69,28,4.0,6,47,Semi-Urban,Software Engineer,23996,0 +113098,Male,48,High School,10,56,70,59,40,3.0,3,98,Urban,Software Engineer,60405,1 +113099,Male,22,PhD,3,20,88,68,34,0.0,2,9,Rural,Manager,40977,0 +113100,Female,45,PhD,6,19,88,9,94,1.0,2,32,Semi-Urban,Software Engineer,95712,0 +113101,Male,24,Bachelors,2,5,63,30,57,8.0,0,52,Rural,Data Analyst,72219,0 +113102,Male,42,Diploma,4,86,46,92,76,1.0,5,88,Urban,HR Executive,141848,1 +113103,Other,26,Masters,17,84,10,49,67,4.0,3,13,Rural,Manager,76941,0 +113104,Male,42,Diploma,19,2,93,36,41,8.0,4,20,Urban,Software Engineer,130843,0 +113105,Male,35,PhD,5,65,83,82,18,5.0,6,59,Semi-Urban,HR Executive,49676,1 +113106,Male,54,Bachelors,15,36,80,78,92,4.0,6,8,Urban,Manager,143455,0 +113107,Male,33,Bachelors,5,34,82,72,1,5.0,2,64,Semi-Urban,HR Executive,57455,1 +113108,Male,51,Diploma,17,31,77,41,81,4.0,0,65,Urban,Manager,33144,0 +113109,Female,41,Bachelors,17,27,15,53,91,2.0,0,10,Rural,Software Engineer,144141,0 +113110,Male,25,Bachelors,17,9,51,28,43,6.0,2,47,Semi-Urban,HR Executive,144909,0 +113111,Male,39,Bachelors,15,59,62,99,49,3.0,0,29,Semi-Urban,Software Engineer,138165,1 +113112,Female,23,High School,2,83,58,88,48,2.0,1,32,Urban,Data Analyst,45399,1 +113113,Male,57,Bachelors,16,50,84,13,89,5.0,6,72,Urban,Manager,58743,0 +113114,Male,24,Bachelors,1,48,42,0,56,0.0,2,51,Rural,Data Analyst,120370,0 +113115,Female,52,High School,3,57,43,12,66,3.0,3,66,Semi-Urban,Manager,66285,0 +113116,Female,48,High School,14,41,23,59,55,3.0,7,15,Semi-Urban,Data Analyst,28585,0 +113117,Male,54,High School,10,61,70,58,84,1.0,3,86,Urban,Data Analyst,142310,1 +113118,Female,59,Diploma,3,61,57,24,80,2.0,2,82,Urban,Manager,25432,0 +113119,Male,25,Bachelors,11,56,15,60,33,7.0,7,69,Urban,HR Executive,106081,0 +113120,Other,45,Masters,2,19,28,2,82,2.0,7,74,Urban,ML Engineer,25192,0 +113121,Female,43,Bachelors,1,45,52,60,94,3.0,1,7,Urban,Manager,63504,0 +113122,Male,31,Bachelors,6,18,37,98,87,9.0,3,83,Semi-Urban,Software Engineer,143506,1 +113123,Female,55,Masters,10,81,28,89,52,0.0,3,81,Rural,ML Engineer,139425,1 +113124,Male,35,Diploma,17,2,29,76,14,0.0,6,28,Urban,ML Engineer,39206,0 +113125,Female,38,Masters,15,40,70,26,8,1.0,0,42,Urban,Data Analyst,32657,0 +113126,Female,55,High School,3,34,62,11,7,9.0,3,55,Urban,Data Analyst,62740,0 +113127,Female,35,Bachelors,12,94,76,72,15,5.0,2,45,Semi-Urban,Software Engineer,95627,1 +113128,Male,34,Bachelors,11,73,4,10,61,7.0,6,96,Rural,Software Engineer,37146,0 +113129,Male,43,Bachelors,9,52,91,38,13,7.0,1,87,Rural,ML Engineer,67678,1 +113130,Female,40,Bachelors,13,94,80,3,92,6.0,2,67,Urban,ML Engineer,46480,1 +113131,Female,28,High School,17,70,41,80,29,3.0,6,43,Urban,Data Analyst,36674,0 +113132,Male,23,Bachelors,13,27,17,35,43,3.0,7,21,Urban,Manager,65769,0 +113133,Female,28,Diploma,19,78,34,18,4,9.0,5,51,Semi-Urban,HR Executive,58420,0 +113134,Male,54,Diploma,12,70,52,25,59,9.0,0,53,Urban,HR Executive,149598,0 +113135,Male,57,Diploma,16,7,35,22,36,6.0,1,43,Semi-Urban,Software Engineer,69871,0 +113136,Other,40,Bachelors,9,64,71,9,33,8.0,6,33,Urban,ML Engineer,94752,0 +113137,Female,30,Masters,19,42,43,32,59,7.0,0,83,Urban,Data Analyst,68102,0 +113138,Female,49,Masters,2,93,80,70,13,1.0,3,46,Rural,Data Analyst,82240,1 +113139,Male,40,Diploma,17,83,87,60,94,8.0,0,93,Semi-Urban,HR Executive,73768,1 +113140,Male,56,Masters,13,59,48,54,34,3.0,0,86,Semi-Urban,Software Engineer,85323,1 +113141,Male,31,Diploma,4,70,68,82,56,0.0,2,82,Rural,ML Engineer,137333,1 +113142,Male,27,Bachelors,10,29,67,45,19,0.0,1,72,Semi-Urban,ML Engineer,112388,0 +113143,Male,47,Masters,18,85,56,67,62,9.0,4,85,Rural,Data Analyst,92624,1 +113144,Male,47,Masters,17,15,16,73,62,9.0,0,26,Semi-Urban,Software Engineer,76380,0 +113145,Male,25,Bachelors,9,44,99,44,39,1.0,7,7,Semi-Urban,Data Analyst,42451,0 +113146,Female,36,High School,0,64,35,92,52,2.0,2,78,Urban,ML Engineer,22490,1 +113147,Female,36,Masters,17,42,57,19,99,9.0,2,58,Semi-Urban,ML Engineer,86265,0 +113148,Female,25,Masters,10,24,16,1,95,9.0,7,64,Rural,Manager,65119,0 +113149,Male,25,Masters,9,60,53,51,51,4.0,6,88,Semi-Urban,ML Engineer,101924,1 +113150,Female,58,Diploma,14,36,12,49,56,7.0,6,36,Urban,Manager,81397,0 +113151,Male,23,Bachelors,18,51,50,1,68,5.0,5,28,Urban,ML Engineer,105417,0 +113152,Male,23,High School,3,0,4,97,21,3.0,2,69,Urban,Data Analyst,93814,0 +113153,Other,27,Masters,12,32,86,78,64,5.0,7,95,Semi-Urban,HR Executive,112043,1 +113154,Female,57,Masters,6,36,7,9,15,7.0,4,98,Urban,ML Engineer,56182,0 +113155,Female,44,Bachelors,12,81,15,53,95,8.0,0,48,Semi-Urban,Data Analyst,133344,0 +113156,Male,29,PhD,3,37,47,67,84,8.0,5,84,Urban,HR Executive,86354,1 +113157,Female,53,Bachelors,2,14,21,80,15,8.0,0,73,Urban,ML Engineer,138144,0 +113158,Female,32,Bachelors,7,91,88,84,46,5.0,2,89,Urban,Manager,62332,1 +113159,Female,28,High School,16,48,76,26,11,3.0,0,87,Urban,ML Engineer,59022,0 +113160,Female,31,Bachelors,8,12,20,13,27,5.0,4,42,Urban,Manager,55713,0 +113161,Female,45,Bachelors,15,33,8,63,13,2.0,6,0,Semi-Urban,ML Engineer,95277,0 +113162,Male,40,High School,11,8,9,58,19,8.0,4,0,Urban,Manager,100496,0 +113163,Male,54,Bachelors,8,89,2,66,73,0.0,2,8,Urban,HR Executive,76213,0 +113164,Male,27,Bachelors,9,16,38,33,87,1.0,7,93,Urban,Software Engineer,56403,0 +113165,Male,59,Diploma,12,59,45,70,94,5.0,2,77,Rural,Data Analyst,20417,1 +113166,Male,59,Bachelors,10,50,52,29,92,7.0,1,49,Urban,HR Executive,69432,0 +113167,Other,29,Bachelors,19,76,15,87,30,5.0,1,97,Semi-Urban,HR Executive,66833,1 +113168,Female,39,High School,1,58,99,56,73,6.0,2,54,Rural,Data Analyst,74888,1 +113169,Male,44,Bachelors,11,9,38,64,56,1.0,0,97,Urban,HR Executive,59358,0 +113170,Female,23,High School,17,55,21,3,37,8.0,2,85,Urban,Manager,44586,0 +113171,Male,42,Bachelors,11,25,38,76,99,3.0,3,10,Rural,Data Analyst,112560,0 +113172,Male,41,Bachelors,18,33,6,65,57,7.0,1,19,Rural,HR Executive,49201,0 +113173,Male,36,Bachelors,5,35,33,93,22,9.0,1,21,Rural,ML Engineer,30557,0 +113174,Male,34,High School,10,6,53,20,23,9.0,0,92,Semi-Urban,Manager,109031,0 +113175,Male,40,Bachelors,4,5,54,32,97,3.0,5,36,Urban,HR Executive,122038,0 +113176,Male,36,Masters,19,78,71,61,72,4.0,6,54,Urban,Manager,102485,1 +113177,Male,55,Masters,10,78,39,96,21,4.0,0,63,Urban,Software Engineer,25888,1 +113178,Male,49,Bachelors,2,52,62,4,10,6.0,1,42,Urban,Data Analyst,23709,0 +113179,Female,28,Bachelors,3,57,19,45,86,7.0,1,34,Rural,Data Analyst,49372,0 +113180,Male,31,Bachelors,18,40,56,36,16,5.0,3,79,Urban,Software Engineer,81636,0 +113181,Male,32,Bachelors,4,1,56,61,66,9.0,0,74,Rural,HR Executive,93379,0 +113182,Male,57,Masters,3,1,20,54,74,1.0,7,77,Rural,HR Executive,20625,0 +113183,Female,46,Masters,3,16,52,17,59,2.0,6,25,Urban,Manager,25667,0 +113184,Male,55,Diploma,12,51,13,1,84,6.0,4,20,Urban,HR Executive,85768,0 +113185,Male,31,Diploma,2,69,8,20,6,8.0,3,36,Urban,Manager,84678,0 +113186,Male,23,Bachelors,5,10,12,42,48,2.0,5,20,Urban,Manager,144983,0 +113187,Male,24,Bachelors,4,63,21,8,8,5.0,3,51,Urban,Manager,129137,0 +113188,Male,46,Bachelors,13,7,66,13,43,6.0,4,98,Urban,HR Executive,79609,0 +113189,Female,23,Bachelors,1,65,20,98,81,5.0,6,79,Urban,Software Engineer,106025,1 +113190,Male,50,Diploma,17,87,15,25,73,4.0,7,93,Semi-Urban,Data Analyst,112200,0 +113191,Female,55,High School,7,76,32,94,62,4.0,5,49,Semi-Urban,Manager,48911,1 +113192,Female,28,Bachelors,12,4,94,28,57,9.0,0,24,Urban,Data Analyst,80051,0 +113193,Female,38,PhD,6,5,59,28,62,8.0,2,87,Rural,Software Engineer,125463,0 +113194,Male,30,Bachelors,12,72,16,60,20,6.0,7,66,Urban,Software Engineer,89743,0 +113195,Female,32,Masters,17,43,11,36,51,0.0,2,70,Urban,Software Engineer,86696,0 +113196,Male,27,Bachelors,13,40,57,92,3,1.0,1,95,Semi-Urban,HR Executive,132211,1 +113197,Other,34,High School,15,3,71,16,54,4.0,0,51,Semi-Urban,Software Engineer,92416,0 +113198,Female,23,Diploma,17,72,25,41,0,3.0,4,16,Urban,Manager,81582,0 +113199,Male,29,Diploma,2,30,83,11,30,7.0,3,85,Urban,ML Engineer,54936,0 +113200,Other,41,High School,14,15,6,55,28,2.0,6,93,Semi-Urban,Manager,72082,0 +113201,Male,45,Bachelors,7,88,47,60,61,1.0,4,17,Rural,Software Engineer,87019,0 +113202,Female,30,Bachelors,15,80,92,15,73,3.0,7,60,Semi-Urban,Data Analyst,120390,1 +113203,Female,22,Diploma,4,2,35,96,59,2.0,4,35,Urban,Data Analyst,24686,0 +113204,Male,22,PhD,15,0,43,18,78,1.0,2,47,Urban,Data Analyst,38792,0 +113205,Female,44,Masters,6,19,35,29,33,8.0,0,45,Semi-Urban,Data Analyst,78299,0 +113206,Female,52,Bachelors,7,32,87,92,49,0.0,4,28,Urban,Data Analyst,53630,0 +113207,Male,56,Bachelors,4,28,87,29,57,6.0,5,29,Semi-Urban,Data Analyst,59195,0 +113208,Male,52,Bachelors,3,93,6,25,93,8.0,4,32,Rural,Data Analyst,52634,0 +113209,Male,49,Bachelors,10,84,17,82,42,2.0,3,35,Urban,ML Engineer,89748,0 +113210,Male,27,Bachelors,15,84,99,61,44,1.0,1,97,Rural,Manager,65384,1 +113211,Male,29,High School,5,91,10,8,28,4.0,6,70,Semi-Urban,ML Engineer,132821,0 +113212,Male,54,High School,13,48,28,54,3,5.0,2,79,Semi-Urban,Software Engineer,112122,0 +113213,Male,40,Masters,7,77,9,25,2,6.0,3,24,Semi-Urban,HR Executive,29346,0 +113214,Male,54,Bachelors,9,7,76,86,39,0.0,5,86,Urban,HR Executive,44031,1 +113215,Male,42,High School,3,98,39,78,46,8.0,2,83,Rural,Manager,90686,1 +113216,Male,40,Bachelors,13,43,87,42,62,1.0,4,78,Semi-Urban,Manager,79156,1 +113217,Female,28,Bachelors,5,79,84,45,56,5.0,3,71,Urban,Software Engineer,123583,1 +113218,Female,51,Diploma,14,47,74,62,2,4.0,4,3,Urban,Manager,97738,0 +113219,Male,40,Bachelors,11,3,36,19,19,5.0,2,24,Semi-Urban,HR Executive,117204,0 +113220,Female,52,PhD,5,54,31,36,51,4.0,3,92,Rural,Data Analyst,83850,0 +113221,Male,53,High School,4,57,8,59,55,6.0,4,68,Urban,Manager,63041,0 +113222,Male,32,Diploma,7,24,48,9,9,9.0,0,18,Urban,HR Executive,24094,0 +113223,Female,25,Bachelors,3,29,80,9,32,5.0,3,10,Urban,Software Engineer,45803,0 +113224,Female,31,Bachelors,11,72,22,21,70,6.0,7,77,Urban,ML Engineer,98394,0 +113225,Female,39,Bachelors,4,83,40,89,17,9.0,7,68,Rural,Software Engineer,143031,1 +113226,Female,48,Diploma,6,55,75,62,24,7.0,7,75,Urban,Software Engineer,94293,1 +113227,Female,51,Diploma,2,59,17,48,28,0.0,6,82,Urban,Manager,97958,0 +113228,Female,28,Bachelors,18,49,66,7,75,3.0,4,12,Rural,HR Executive,78777,0 +113229,Male,26,Diploma,1,26,34,40,16,9.0,2,27,Rural,Data Analyst,107530,0 +113230,Male,39,High School,17,32,9,66,81,6.0,0,52,Urban,ML Engineer,70044,0 +113231,Male,40,High School,19,33,33,53,5,7.0,6,13,Urban,HR Executive,140830,0 +113232,Female,24,PhD,1,92,55,33,29,3.0,0,43,Semi-Urban,ML Engineer,134412,0 +113233,Male,57,Bachelors,0,54,48,77,7,6.0,0,12,Urban,HR Executive,123904,0 +113234,Female,53,Masters,13,49,6,76,1,8.0,3,31,Rural,ML Engineer,40971,0 +113235,Female,29,High School,11,2,7,72,65,4.0,2,29,Urban,Manager,141542,0 +113236,Female,29,Masters,17,12,89,3,43,6.0,2,94,Semi-Urban,HR Executive,44771,0 +113237,Male,56,Masters,18,43,96,83,47,6.0,5,6,Urban,Manager,56001,0 +113238,Female,37,PhD,16,50,67,89,10,4.0,7,95,Urban,ML Engineer,78633,1 +113239,Male,28,Masters,7,95,64,0,94,9.0,6,49,Urban,Manager,48369,0 +113240,Male,56,High School,1,1,2,29,49,5.0,1,35,Semi-Urban,Software Engineer,63833,0 +113241,Female,55,Diploma,16,28,35,3,4,0.0,2,78,Urban,Manager,128866,0 +113242,Male,58,Bachelors,4,93,35,61,34,0.0,6,56,Urban,Data Analyst,53223,1 +113243,Male,31,Masters,8,56,40,44,13,9.0,1,15,Urban,ML Engineer,21516,0 +113244,Female,32,Bachelors,10,71,62,46,87,1.0,3,84,Rural,ML Engineer,134840,1 +113245,Male,35,Bachelors,14,54,19,79,43,7.0,2,56,Semi-Urban,HR Executive,37221,0 +113246,Female,39,Bachelors,13,57,92,53,43,3.0,6,23,Semi-Urban,ML Engineer,99950,0 +113247,Female,45,Bachelors,19,25,28,86,39,2.0,5,52,Urban,ML Engineer,121642,0 +113248,Male,56,High School,19,94,7,4,33,1.0,4,41,Urban,HR Executive,119573,0 +113249,Male,25,Bachelors,11,31,62,24,38,4.0,7,97,Semi-Urban,HR Executive,120894,0 +113250,Female,34,Bachelors,12,80,37,69,56,5.0,0,82,Urban,Software Engineer,61198,1 +113251,Female,23,Diploma,6,98,55,7,37,9.0,1,98,Urban,Manager,85639,1 +113252,Male,40,Masters,18,71,63,81,58,2.0,2,6,Semi-Urban,HR Executive,33290,0 +113253,Male,38,High School,10,28,44,98,65,3.0,7,73,Rural,Manager,50379,1 +113254,Female,21,High School,4,89,6,90,51,8.0,3,13,Urban,ML Engineer,28116,0 +113255,Male,51,High School,11,6,33,55,19,2.0,2,28,Urban,ML Engineer,64836,0 +113256,Female,43,Diploma,7,14,11,73,63,0.0,7,29,Urban,ML Engineer,38525,0 +113257,Female,49,Bachelors,8,54,72,47,83,5.0,0,28,Urban,Software Engineer,31716,0 +113258,Male,41,Bachelors,12,75,79,2,9,3.0,0,7,Urban,ML Engineer,50213,0 +113259,Male,43,High School,13,38,66,22,21,6.0,1,42,Semi-Urban,Software Engineer,147907,0 +113260,Male,35,Bachelors,19,44,80,26,81,4.0,1,85,Urban,ML Engineer,36372,1 +113261,Male,30,Diploma,6,17,28,0,44,3.0,4,39,Rural,Data Analyst,97742,0 +113262,Male,59,PhD,7,68,44,89,14,1.0,2,29,Urban,Data Analyst,41428,0 +113263,Male,38,Masters,16,10,90,11,18,0.0,7,75,Urban,HR Executive,84946,0 +113264,Female,40,Masters,0,43,1,79,18,4.0,1,20,Semi-Urban,HR Executive,31512,0 +113265,Female,37,Diploma,12,41,30,18,34,2.0,7,20,Urban,Data Analyst,122026,0 +113266,Female,50,Bachelors,5,83,52,74,39,0.0,4,49,Semi-Urban,Data Analyst,27314,1 +113267,Male,48,High School,9,13,54,63,58,5.0,0,27,Rural,Manager,29898,0 +113268,Male,39,Bachelors,14,52,93,91,84,2.0,5,62,Rural,ML Engineer,125794,1 +113269,Male,46,Diploma,17,46,7,99,31,8.0,2,84,Urban,Software Engineer,46685,1 +113270,Male,47,Bachelors,10,89,20,34,79,8.0,6,70,Urban,Manager,148865,0 +113271,Male,50,Bachelors,13,32,93,85,16,8.0,0,47,Rural,Data Analyst,124200,1 +113272,Female,24,Bachelors,8,21,63,55,20,8.0,3,83,Urban,Software Engineer,145548,0 +113273,Male,46,Bachelors,16,11,94,79,87,0.0,5,6,Urban,Data Analyst,54853,0 +113274,Male,47,High School,3,37,1,7,46,8.0,5,25,Urban,Manager,24270,0 +113275,Female,49,Bachelors,14,55,63,22,23,7.0,4,3,Urban,Manager,68571,0 +113276,Female,53,Bachelors,2,98,2,59,83,3.0,6,12,Urban,Software Engineer,53447,0 +113277,Other,50,Masters,0,36,89,40,49,3.0,1,25,Semi-Urban,Data Analyst,38126,0 +113278,Female,24,Diploma,12,50,31,72,25,1.0,7,40,Urban,HR Executive,65109,0 +113279,Female,39,Bachelors,7,74,78,15,5,4.0,3,96,Semi-Urban,Software Engineer,33794,1 +113280,Female,45,Masters,17,38,52,4,30,4.0,4,86,Urban,Manager,130233,0 +113281,Male,23,Diploma,3,97,1,8,87,5.0,5,18,Semi-Urban,HR Executive,50248,0 +113282,Male,28,Bachelors,3,82,85,33,17,0.0,7,64,Urban,Data Analyst,27011,1 +113283,Female,43,Diploma,12,28,41,73,50,6.0,3,66,Urban,Software Engineer,56377,0 +113284,Male,38,Bachelors,8,64,2,77,25,5.0,1,54,Rural,ML Engineer,109222,0 +113285,Male,53,Masters,14,5,3,9,13,5.0,3,69,Urban,ML Engineer,100171,0 +113286,Male,33,Diploma,1,69,61,16,33,9.0,0,2,Semi-Urban,Software Engineer,83921,0 +113287,Female,46,Bachelors,0,84,2,99,89,3.0,5,42,Urban,Manager,144274,0 +113288,Female,48,Masters,15,24,66,30,81,0.0,1,53,Urban,Software Engineer,104118,0 +113289,Other,54,Masters,18,15,95,60,88,5.0,7,88,Semi-Urban,HR Executive,118120,1 +113290,Female,33,High School,15,68,7,74,89,0.0,7,44,Urban,ML Engineer,123639,0 +113291,Male,30,PhD,2,51,40,79,19,6.0,4,21,Rural,HR Executive,106719,0 +113292,Male,27,Masters,9,98,8,99,57,2.0,4,28,Urban,Manager,126001,0 +113293,Male,55,Bachelors,14,91,99,15,91,5.0,6,83,Semi-Urban,Software Engineer,78468,1 +113294,Male,36,High School,13,6,97,67,62,9.0,1,41,Urban,Data Analyst,83670,0 +113295,Male,58,High School,5,34,51,30,33,3.0,5,77,Urban,Manager,53350,0 +113296,Female,29,Diploma,2,71,13,4,84,7.0,0,94,Urban,ML Engineer,135738,0 +113297,Female,30,Bachelors,5,84,59,89,72,1.0,7,95,Semi-Urban,ML Engineer,110896,1 +113298,Male,58,PhD,11,15,53,76,74,8.0,4,1,Semi-Urban,ML Engineer,145818,0 +113299,Male,33,Bachelors,19,74,65,45,89,5.0,5,98,Urban,HR Executive,60153,1 +113300,Male,51,Bachelors,15,28,61,62,81,2.0,4,21,Urban,Manager,80464,0 +113301,Female,47,Diploma,15,81,25,66,17,4.0,6,18,Urban,HR Executive,101772,0 +113302,Male,37,Masters,3,22,70,87,17,2.0,5,79,Urban,Data Analyst,85910,1 +113303,Male,36,Diploma,8,19,10,22,50,2.0,0,51,Urban,Manager,143237,0 +113304,Male,55,Bachelors,0,98,55,65,6,7.0,6,4,Semi-Urban,Data Analyst,101995,0 +113305,Female,22,Masters,18,90,82,65,0,4.0,2,28,Urban,ML Engineer,26795,1 +113306,Male,49,Masters,12,4,41,69,32,6.0,3,79,Urban,HR Executive,28536,0 +113307,Male,43,Masters,2,8,19,15,38,5.0,2,60,Rural,HR Executive,149740,0 +113308,Male,22,High School,17,21,11,53,33,7.0,7,90,Rural,Software Engineer,116369,0 +113309,Male,27,Masters,7,86,54,25,21,9.0,4,74,Urban,Software Engineer,109913,1 +113310,Male,44,Masters,14,27,32,41,80,8.0,7,65,Urban,HR Executive,48483,0 +113311,Male,52,Diploma,0,85,81,58,46,2.0,0,5,Urban,Software Engineer,98435,0 +113312,Female,47,Bachelors,0,79,80,96,97,6.0,6,71,Semi-Urban,Data Analyst,138993,1 +113313,Male,28,Masters,16,88,58,3,62,5.0,2,75,Urban,Manager,86465,0 +113314,Male,38,Diploma,8,5,79,58,94,3.0,5,47,Rural,Data Analyst,132389,0 +113315,Female,46,Masters,7,81,4,72,14,5.0,5,27,Urban,HR Executive,48228,0 +113316,Male,42,Diploma,11,7,58,49,81,9.0,2,94,Urban,Software Engineer,30228,0 +113317,Male,37,Bachelors,8,13,2,62,55,5.0,7,14,Rural,ML Engineer,132406,0 +113318,Other,37,Diploma,10,74,55,30,33,8.0,2,31,Semi-Urban,HR Executive,106953,0 +113319,Female,54,Bachelors,6,67,46,51,66,1.0,2,75,Semi-Urban,Software Engineer,41823,0 +113320,Female,45,Masters,9,53,21,24,46,3.0,6,94,Semi-Urban,Data Analyst,46644,0 +113321,Male,56,Bachelors,13,27,91,93,54,0.0,1,91,Rural,Software Engineer,93031,1 +113322,Female,39,Diploma,7,74,14,91,91,4.0,5,86,Rural,HR Executive,137639,1 +113323,Male,29,Bachelors,2,88,78,30,51,1.0,3,95,Urban,HR Executive,102700,1 +113324,Female,39,Bachelors,4,75,58,99,90,2.0,7,55,Semi-Urban,Manager,139891,1 +113325,Male,33,Masters,9,53,67,16,48,6.0,1,0,Urban,ML Engineer,90954,0 +113326,Female,36,Bachelors,13,51,32,24,22,8.0,0,14,Urban,Software Engineer,98120,0 +113327,Male,42,Masters,14,72,75,15,5,1.0,6,1,Rural,HR Executive,62737,0 +113328,Male,56,Masters,3,89,55,14,60,6.0,2,83,Semi-Urban,Manager,119203,1 +113329,Female,48,High School,14,8,49,9,6,5.0,1,52,Urban,Data Analyst,95775,0 +113330,Female,36,Bachelors,7,45,26,82,98,3.0,5,54,Semi-Urban,HR Executive,110315,0 +113331,Female,37,Bachelors,12,34,32,18,15,2.0,3,22,Rural,HR Executive,22157,0 +113332,Male,47,Bachelors,15,33,69,10,82,0.0,3,65,Urban,Manager,87478,0 +113333,Other,57,High School,9,83,38,31,31,1.0,3,37,Semi-Urban,Data Analyst,127437,0 +113334,Female,29,High School,1,41,31,43,74,4.0,6,20,Semi-Urban,Software Engineer,58549,0 +113335,Female,39,Bachelors,10,85,67,44,33,8.0,5,33,Semi-Urban,Software Engineer,58320,0 +113336,Male,49,Masters,19,19,53,66,50,6.0,0,25,Semi-Urban,Software Engineer,90541,0 +113337,Male,40,Diploma,19,45,83,8,23,8.0,1,57,Semi-Urban,ML Engineer,127497,0 +113338,Male,54,Masters,12,21,1,6,75,7.0,3,89,Urban,ML Engineer,101159,0 +113339,Female,34,Diploma,12,31,29,59,65,3.0,4,4,Urban,HR Executive,60612,0 +113340,Male,38,Diploma,0,65,77,14,28,4.0,3,30,Urban,Data Analyst,52103,0 +113341,Male,49,Diploma,4,78,69,65,81,9.0,0,67,Semi-Urban,Software Engineer,60548,1 +113342,Male,38,High School,11,84,56,19,89,1.0,1,59,Rural,HR Executive,130963,0 +113343,Male,52,Diploma,17,72,53,68,49,8.0,7,87,Semi-Urban,Software Engineer,126749,1 +113344,Male,29,Bachelors,19,80,65,67,46,2.0,0,71,Semi-Urban,ML Engineer,98013,1 +113345,Female,34,Masters,5,43,44,78,91,9.0,0,77,Semi-Urban,Data Analyst,74657,1 +113346,Female,32,PhD,0,37,13,14,33,6.0,6,77,Urban,Software Engineer,125471,0 +113347,Male,50,Bachelors,13,21,47,49,13,6.0,7,80,Urban,Software Engineer,99868,0 +113348,Female,25,Diploma,7,68,95,3,8,8.0,7,3,Semi-Urban,Manager,72345,0 +113349,Female,24,High School,15,70,30,26,50,7.0,3,46,Semi-Urban,Data Analyst,125863,0 +113350,Male,22,Bachelors,9,23,80,94,11,1.0,0,64,Urban,Software Engineer,49737,1 +113351,Male,58,Diploma,1,6,69,63,71,6.0,2,29,Urban,ML Engineer,97724,0 +113352,Male,53,High School,3,96,49,49,3,2.0,4,98,Urban,Manager,85253,1 +113353,Male,50,Bachelors,17,20,4,4,7,5.0,5,90,Rural,HR Executive,38765,0 +113354,Other,58,Bachelors,7,83,11,26,80,2.0,7,51,Urban,ML Engineer,129257,0 +113355,Female,27,Diploma,15,96,48,43,6,5.0,6,86,Semi-Urban,Software Engineer,139708,1 +113356,Female,37,Masters,8,56,56,7,60,6.0,3,55,Semi-Urban,Manager,24701,0 +113357,Male,30,Diploma,16,54,97,57,0,1.0,1,42,Semi-Urban,Manager,119461,1 +113358,Female,26,High School,3,93,84,6,27,8.0,7,40,Semi-Urban,Data Analyst,106618,0 +113359,Male,39,Bachelors,8,24,74,12,94,0.0,2,42,Urban,Data Analyst,28144,0 +113360,Female,21,Diploma,10,7,6,71,45,4.0,7,89,Urban,HR Executive,148872,0 +113361,Male,34,Bachelors,17,8,59,78,23,4.0,2,11,Rural,HR Executive,121945,0 +113362,Male,58,Masters,18,95,57,25,98,6.0,5,33,Semi-Urban,Manager,45901,0 +113363,Female,57,Bachelors,6,47,71,61,69,7.0,1,18,Semi-Urban,Software Engineer,134598,0 +113364,Female,58,Bachelors,6,77,30,1,99,2.0,5,39,Semi-Urban,HR Executive,58191,0 +113365,Male,26,Bachelors,1,86,27,16,70,4.0,2,32,Urban,Software Engineer,90752,0 +113366,Female,59,High School,10,86,5,46,67,2.0,6,3,Urban,Software Engineer,127394,0 +113367,Female,34,Bachelors,0,17,37,94,26,1.0,1,95,Rural,Software Engineer,98753,1 +113368,Female,56,Bachelors,7,71,53,53,24,2.0,6,69,Urban,Software Engineer,32298,1 +113369,Male,28,Bachelors,1,72,65,62,2,1.0,6,84,Semi-Urban,Manager,59662,1 +113370,Male,44,High School,13,82,50,49,66,9.0,7,46,Urban,Manager,138783,0 +113371,Male,59,High School,19,74,2,16,3,3.0,7,94,Urban,Software Engineer,46336,0 +113372,Male,59,Bachelors,12,73,48,94,2,6.0,5,87,Urban,Manager,115737,1 +113373,Male,34,Bachelors,17,22,52,48,80,3.0,1,92,Urban,Data Analyst,114617,0 +113374,Male,25,Diploma,5,54,64,2,61,8.0,0,12,Urban,HR Executive,30711,0 +113375,Female,27,High School,0,4,49,35,69,7.0,7,47,Urban,ML Engineer,103502,0 +113376,Male,27,High School,6,60,95,75,31,1.0,0,81,Urban,Software Engineer,94206,1 +113377,Male,49,Bachelors,18,96,85,82,51,8.0,0,1,Urban,ML Engineer,141739,1 +113378,Male,47,Diploma,8,18,99,71,64,5.0,7,51,Urban,ML Engineer,44073,1 +113379,Male,27,Diploma,4,0,39,68,3,0.0,1,13,Semi-Urban,ML Engineer,71188,0 +113380,Male,39,Bachelors,2,52,9,75,12,6.0,4,50,Urban,HR Executive,66699,0 +113381,Male,25,Masters,8,75,37,79,27,5.0,0,84,Rural,ML Engineer,38637,1 +113382,Male,30,Masters,1,44,94,8,3,3.0,4,61,Rural,Manager,111907,0 +113383,Female,33,Diploma,6,85,55,79,51,3.0,1,99,Urban,ML Engineer,148683,1 +113384,Male,26,High School,3,11,16,37,50,4.0,1,80,Urban,Software Engineer,144572,0 +113385,Female,49,High School,4,79,57,53,34,9.0,4,44,Semi-Urban,Data Analyst,102303,0 +113386,Female,55,Bachelors,2,45,34,74,0,4.0,5,20,Urban,Manager,77482,0 +113387,Other,59,Diploma,7,89,39,69,16,8.0,5,39,Urban,ML Engineer,67255,0 +113388,Female,47,Bachelors,7,43,1,23,26,9.0,6,61,Semi-Urban,Data Analyst,137933,0 +113389,Male,34,Bachelors,11,1,78,15,19,7.0,0,56,Urban,HR Executive,36052,0 +113390,Female,43,High School,16,26,19,81,23,4.0,6,45,Rural,Software Engineer,73050,0 +113391,Male,25,Diploma,1,83,81,84,23,3.0,2,11,Urban,ML Engineer,127134,1 +113392,Male,34,Bachelors,5,18,15,84,34,5.0,7,46,Semi-Urban,ML Engineer,125548,0 +113393,Male,54,Masters,9,42,58,52,75,1.0,1,41,Urban,Manager,39691,0 +113394,Male,37,Bachelors,16,37,60,40,47,6.0,2,67,Semi-Urban,Manager,59241,0 +113395,Male,32,Bachelors,12,35,90,27,73,8.0,0,66,Urban,Software Engineer,72930,0 +113396,Female,26,Bachelors,13,13,14,68,14,8.0,2,74,Urban,Data Analyst,120152,0 +113397,Male,32,Bachelors,14,53,89,90,55,6.0,4,60,Urban,ML Engineer,40629,1 +113398,Male,49,PhD,12,80,99,82,36,8.0,5,21,Urban,Manager,52159,1 +113399,Male,29,Bachelors,18,20,66,94,1,7.0,2,88,Urban,ML Engineer,136746,1 +113400,Male,22,Diploma,4,79,56,5,20,4.0,0,84,Urban,Data Analyst,136462,0 +113401,Male,39,Bachelors,19,63,48,73,41,9.0,1,93,Semi-Urban,HR Executive,115619,1 +113402,Male,37,Diploma,7,44,14,89,35,2.0,1,90,Urban,HR Executive,118588,1 +113403,Male,33,Bachelors,19,10,35,61,13,9.0,1,3,Urban,HR Executive,29264,0 +113404,Female,40,Bachelors,9,35,38,72,19,9.0,0,96,Urban,Manager,113831,1 +113405,Male,59,High School,15,24,83,1,37,5.0,2,35,Rural,Data Analyst,73258,0 +113406,Male,40,Masters,5,22,78,91,36,9.0,2,23,Urban,HR Executive,122468,0 +113407,Male,56,Masters,5,34,61,5,50,1.0,7,11,Rural,Software Engineer,81025,0 +113408,Male,36,Masters,1,26,62,55,75,3.0,5,98,Urban,HR Executive,112555,1 +113409,Male,39,High School,7,45,6,52,65,1.0,7,29,Semi-Urban,HR Executive,73013,0 +113410,Female,53,Bachelors,9,94,50,42,64,1.0,3,5,Semi-Urban,ML Engineer,100505,0 +113411,Male,53,High School,14,21,57,96,77,7.0,6,99,Urban,Manager,119380,1 +113412,Male,34,Diploma,8,98,89,20,15,5.0,6,47,Semi-Urban,ML Engineer,44909,1 +113413,Male,41,Masters,4,55,36,24,98,0.0,5,33,Urban,Data Analyst,25401,0 +113414,Female,48,Diploma,15,37,27,86,42,6.0,6,73,Semi-Urban,Software Engineer,138162,0 +113415,Male,55,Bachelors,9,33,71,8,51,9.0,0,98,Semi-Urban,HR Executive,44915,0 +113416,Male,39,Bachelors,7,77,18,67,40,1.0,5,17,Semi-Urban,Data Analyst,52280,0 +113417,Female,37,Bachelors,15,70,66,1,58,2.0,0,74,Urban,Data Analyst,92414,0 +113418,Male,31,Bachelors,4,58,36,16,57,1.0,2,52,Urban,ML Engineer,138841,0 +113419,Other,32,Masters,17,11,93,9,19,1.0,6,11,Rural,Manager,114030,0 +113420,Male,58,Masters,9,45,62,66,68,2.0,5,52,Rural,Data Analyst,88123,0 +113421,Female,24,Masters,12,90,98,52,49,7.0,0,95,Urban,Data Analyst,58430,1 +113422,Male,48,Bachelors,19,33,40,33,78,0.0,1,70,Urban,Data Analyst,89779,0 +113423,Male,22,Bachelors,14,57,53,62,14,2.0,3,15,Urban,HR Executive,52065,0 +113424,Male,43,Bachelors,14,39,71,41,24,1.0,6,23,Urban,ML Engineer,45493,0 +113425,Male,25,Masters,16,44,53,5,90,7.0,5,48,Urban,ML Engineer,137310,0 +113426,Male,36,Diploma,10,32,4,55,66,1.0,7,1,Semi-Urban,HR Executive,148078,0 +113427,Female,38,Masters,8,74,34,4,67,4.0,5,84,Semi-Urban,Manager,141031,0 +113428,Male,49,Bachelors,18,22,66,27,97,5.0,1,2,Rural,Manager,58474,0 +113429,Male,54,Bachelors,0,32,96,95,98,1.0,6,0,Semi-Urban,ML Engineer,95165,0 +113430,Male,30,High School,5,86,23,18,24,0.0,7,37,Rural,Software Engineer,76099,0 +113431,Other,25,Bachelors,16,78,76,25,43,7.0,1,81,Urban,HR Executive,134276,1 +113432,Male,37,PhD,12,4,66,90,71,6.0,0,43,Semi-Urban,Manager,89917,0 +113433,Male,53,Masters,1,83,51,72,35,3.0,3,41,Semi-Urban,ML Engineer,116371,1 +113434,Male,57,Diploma,1,80,85,29,65,7.0,5,99,Urban,Data Analyst,82392,1 +113435,Female,28,Diploma,16,0,57,80,70,8.0,6,43,Urban,ML Engineer,79519,0 +113436,Female,47,Bachelors,12,69,85,28,33,0.0,7,3,Urban,Data Analyst,90865,0 +113437,Female,52,Bachelors,18,50,68,70,98,5.0,5,67,Urban,Software Engineer,48676,1 +113438,Male,30,Diploma,19,86,29,67,46,2.0,6,31,Rural,Data Analyst,34874,0 +113439,Female,39,Bachelors,12,51,9,21,63,5.0,2,18,Urban,HR Executive,75374,0 +113440,Male,29,High School,6,97,75,39,89,3.0,2,11,Urban,Manager,26719,0 +113441,Male,37,Masters,2,69,38,98,93,0.0,1,22,Semi-Urban,ML Engineer,89060,0 +113442,Female,44,Bachelors,12,4,48,98,65,1.0,2,11,Semi-Urban,Software Engineer,118677,0 +113443,Male,32,High School,3,51,84,92,65,8.0,3,0,Semi-Urban,Data Analyst,39044,0 +113444,Female,45,High School,17,9,77,53,82,4.0,3,92,Semi-Urban,HR Executive,143736,0 +113445,Male,44,High School,18,44,64,35,61,1.0,3,37,Urban,ML Engineer,42271,0 +113446,Male,30,Bachelors,5,25,11,95,62,3.0,3,69,Urban,Manager,74362,0 +113447,Male,23,Diploma,11,35,29,41,52,7.0,6,24,Urban,Software Engineer,62789,0 +113448,Male,48,High School,5,30,41,39,73,6.0,0,77,Urban,Software Engineer,48587,0 +113449,Other,54,Bachelors,3,94,28,5,77,0.0,1,84,Rural,Software Engineer,56615,0 +113450,Male,43,Masters,12,34,78,33,40,6.0,6,62,Semi-Urban,Manager,21639,0 +113451,Male,47,High School,16,96,66,44,99,9.0,3,7,Semi-Urban,Software Engineer,49808,0 +113452,Male,48,Diploma,12,70,85,10,26,9.0,7,35,Urban,Software Engineer,55515,0 +113453,Female,32,Bachelors,17,47,89,15,23,1.0,5,34,Semi-Urban,ML Engineer,37184,0 +113454,Male,37,Bachelors,18,31,26,30,91,0.0,4,8,Urban,Data Analyst,57773,0 +113455,Female,47,Diploma,1,4,46,34,58,5.0,0,35,Rural,ML Engineer,90449,0 +113456,Male,43,Diploma,1,89,82,1,32,5.0,5,94,Urban,Software Engineer,130299,1 +113457,Female,22,Diploma,12,88,26,6,67,5.0,0,61,Urban,ML Engineer,73940,0 +113458,Female,32,Bachelors,15,59,27,20,18,5.0,1,67,Semi-Urban,Data Analyst,25693,0 +113459,Other,58,Bachelors,8,39,51,98,65,4.0,3,32,Urban,HR Executive,147601,0 +113460,Male,43,Diploma,6,77,35,56,43,3.0,1,72,Semi-Urban,Manager,20922,1 +113461,Male,49,Bachelors,12,8,1,46,49,4.0,2,62,Urban,Software Engineer,42317,0 +113462,Female,26,Diploma,12,64,87,41,35,3.0,0,15,Urban,ML Engineer,138034,0 +113463,Male,50,Bachelors,11,25,48,43,13,3.0,4,27,Urban,HR Executive,135446,0 +113464,Female,34,Bachelors,14,46,76,2,40,2.0,7,81,Urban,Data Analyst,60819,0 +113465,Female,44,Diploma,7,33,33,14,31,8.0,4,78,Rural,ML Engineer,120836,0 +113466,Female,42,Diploma,9,21,94,39,20,2.0,7,85,Semi-Urban,HR Executive,67017,0 +113467,Female,33,PhD,13,40,56,85,97,3.0,4,1,Semi-Urban,ML Engineer,54676,0 +113468,Male,27,Diploma,17,36,20,17,96,2.0,3,49,Urban,Software Engineer,77892,0 +113469,Male,47,Bachelors,1,93,72,2,92,7.0,3,85,Urban,Data Analyst,139066,1 +113470,Male,43,High School,8,51,22,56,15,8.0,7,12,Semi-Urban,ML Engineer,66928,0 +113471,Female,34,Bachelors,7,2,30,3,80,6.0,1,68,Rural,Software Engineer,126185,0 +113472,Female,55,Diploma,0,49,27,18,93,8.0,7,37,Urban,Software Engineer,109766,0 +113473,Male,30,Bachelors,11,56,76,85,65,2.0,7,57,Urban,Manager,33339,1 +113474,Other,48,Bachelors,7,62,41,4,84,3.0,1,93,Urban,Data Analyst,105454,0 +113475,Male,59,Bachelors,14,15,83,91,76,3.0,0,94,Urban,ML Engineer,53728,1 +113476,Female,43,High School,0,92,64,22,67,1.0,3,95,Rural,Data Analyst,103238,1 +113477,Male,39,Diploma,2,68,27,56,2,7.0,6,24,Semi-Urban,Manager,52761,0 +113478,Other,25,Bachelors,17,73,29,43,81,3.0,1,26,Rural,Manager,98389,0 +113479,Male,38,High School,19,36,74,18,58,8.0,5,9,Semi-Urban,Manager,60827,0 +113480,Female,57,Masters,19,74,44,50,9,6.0,7,4,Semi-Urban,Manager,42923,0 +113481,Male,22,PhD,12,34,16,4,99,4.0,7,20,Urban,ML Engineer,84493,0 +113482,Male,52,High School,14,73,41,75,3,3.0,5,11,Semi-Urban,ML Engineer,46574,0 +113483,Other,25,Masters,14,34,18,3,64,3.0,6,34,Rural,HR Executive,22887,0 +113484,Male,24,Bachelors,9,87,47,27,93,2.0,0,56,Semi-Urban,Software Engineer,56222,0 +113485,Female,46,Diploma,3,43,90,21,14,2.0,2,85,Urban,HR Executive,82182,0 +113486,Male,25,Bachelors,5,69,62,41,85,9.0,0,96,Urban,Data Analyst,69073,1 +113487,Female,56,Bachelors,7,75,51,3,85,9.0,6,58,Rural,Manager,65057,0 +113488,Male,39,Bachelors,4,35,85,45,79,7.0,4,45,Semi-Urban,ML Engineer,70989,0 +113489,Male,48,Masters,14,37,43,71,55,1.0,1,96,Rural,Software Engineer,132233,1 +113490,Male,41,Diploma,0,23,23,91,30,8.0,7,64,Rural,Manager,42013,0 +113491,Male,48,Masters,9,86,2,72,64,3.0,0,10,Semi-Urban,HR Executive,83990,0 +113492,Male,33,Diploma,12,83,58,86,12,9.0,4,50,Urban,HR Executive,62179,1 +113493,Female,49,Bachelors,15,29,59,77,0,8.0,3,70,Rural,ML Engineer,74131,0 +113494,Female,37,Bachelors,9,75,89,97,24,5.0,1,60,Rural,Manager,74651,1 +113495,Female,34,Bachelors,0,88,25,25,51,5.0,0,43,Urban,Data Analyst,72133,0 +113496,Female,56,Diploma,2,17,46,16,64,8.0,5,85,Rural,Software Engineer,94325,0 +113497,Male,25,Bachelors,4,81,25,66,58,2.0,7,97,Urban,Data Analyst,51080,1 +113498,Female,59,Diploma,13,71,81,0,35,7.0,5,11,Urban,Manager,73667,0 +113499,Male,54,High School,10,12,60,44,54,1.0,1,17,Urban,ML Engineer,35101,0 +113500,Male,54,PhD,19,1,29,28,13,0.0,2,95,Urban,ML Engineer,139230,0 +113501,Male,37,Bachelors,3,41,22,77,82,1.0,3,75,Urban,HR Executive,97694,0 +113502,Male,24,High School,9,3,27,40,60,3.0,0,12,Urban,Data Analyst,149788,0 +113503,Male,24,Masters,19,91,98,57,44,8.0,7,36,Rural,Manager,61904,1 +113504,Male,57,Bachelors,9,86,79,67,20,9.0,1,36,Semi-Urban,Data Analyst,137312,1 +113505,Other,25,Bachelors,12,22,9,36,56,2.0,2,37,Urban,Data Analyst,148738,0 +113506,Male,36,Diploma,6,19,72,0,34,7.0,2,30,Semi-Urban,Manager,115451,0 +113507,Male,36,Bachelors,6,52,97,92,86,5.0,7,46,Urban,Software Engineer,94035,1 +113508,Female,31,Bachelors,13,19,95,19,65,8.0,5,81,Rural,ML Engineer,82462,0 +113509,Male,47,Masters,12,77,53,84,43,2.0,3,17,Urban,Manager,61597,0 +113510,Male,22,Bachelors,0,17,32,13,68,9.0,2,31,Semi-Urban,HR Executive,46395,0 +113511,Female,48,Diploma,19,91,19,69,47,9.0,5,42,Urban,ML Engineer,101734,0 +113512,Male,22,Bachelors,15,44,33,88,71,0.0,3,70,Urban,HR Executive,117656,1 +113513,Other,54,Masters,0,14,66,57,21,4.0,1,36,Rural,Data Analyst,137733,0 +113514,Female,29,Bachelors,11,30,49,89,39,3.0,1,48,Urban,Software Engineer,30804,0 +113515,Male,52,Bachelors,18,74,88,3,36,7.0,0,83,Semi-Urban,Data Analyst,96256,1 +113516,Other,52,High School,10,61,83,17,6,1.0,6,46,Rural,ML Engineer,130744,0 +113517,Female,53,High School,1,68,9,35,83,9.0,3,21,Rural,ML Engineer,51561,0 +113518,Male,23,Bachelors,1,94,7,17,62,4.0,5,68,Semi-Urban,Software Engineer,133443,0 +113519,Male,37,Bachelors,13,24,40,67,38,5.0,7,22,Rural,Data Analyst,110802,0 +113520,Male,45,Bachelors,15,88,6,44,99,5.0,5,45,Rural,HR Executive,63065,0 +113521,Male,43,High School,7,36,46,53,28,5.0,4,69,Urban,ML Engineer,101012,0 +113522,Male,42,Bachelors,15,54,8,18,1,5.0,4,62,Semi-Urban,Data Analyst,82385,0 +113523,Male,45,PhD,18,13,87,2,43,0.0,6,13,Rural,Data Analyst,91285,0 +113524,Male,46,Bachelors,18,33,73,84,32,7.0,0,39,Urban,Software Engineer,142330,0 +113525,Male,53,High School,17,16,77,71,66,1.0,0,4,Urban,Manager,136279,0 +113526,Female,42,High School,15,16,58,43,36,0.0,5,38,Urban,Manager,135035,0 +113527,Other,44,Diploma,14,48,18,37,96,5.0,1,60,Urban,Data Analyst,95511,0 +113528,Male,26,Diploma,11,93,28,59,33,0.0,3,2,Semi-Urban,HR Executive,79892,0 +113529,Male,56,High School,15,90,51,97,43,9.0,2,30,Semi-Urban,HR Executive,30441,1 +113530,Male,31,PhD,19,22,16,13,60,8.0,0,80,Urban,Data Analyst,38485,0 +113531,Male,57,Masters,13,72,34,89,15,2.0,0,16,Semi-Urban,Software Engineer,107786,0 +113532,Male,36,Bachelors,9,23,39,91,28,8.0,2,2,Urban,ML Engineer,39431,0 +113533,Male,25,Bachelors,4,17,4,52,34,2.0,4,64,Urban,Manager,34288,0 +113534,Female,42,Bachelors,14,15,10,90,77,4.0,3,63,Urban,Manager,48921,0 +113535,Other,22,Bachelors,2,51,17,34,97,2.0,3,86,Urban,ML Engineer,117797,0 +113536,Female,48,Masters,13,42,3,7,34,6.0,3,52,Rural,Software Engineer,133547,0 +113537,Male,47,Bachelors,1,76,87,91,70,0.0,3,20,Semi-Urban,Software Engineer,42083,1 +113538,Female,50,Bachelors,15,3,86,38,44,3.0,5,13,Urban,Software Engineer,64074,0 +113539,Female,31,Diploma,19,83,27,11,5,2.0,1,73,Urban,Software Engineer,101219,0 +113540,Male,49,Bachelors,9,68,72,27,39,6.0,6,1,Semi-Urban,HR Executive,20598,0 +113541,Male,21,High School,19,5,78,59,52,5.0,7,72,Urban,HR Executive,66189,0 +113542,Male,40,Bachelors,14,51,57,73,85,0.0,7,14,Urban,Data Analyst,120622,0 +113543,Male,28,Bachelors,19,27,29,7,34,7.0,6,60,Urban,ML Engineer,117128,0 +113544,Male,26,High School,16,97,79,19,69,7.0,7,5,Urban,Software Engineer,50919,0 +113545,Other,48,Masters,19,55,33,16,14,2.0,5,89,Urban,Software Engineer,87509,0 +113546,Female,52,Diploma,3,30,60,9,54,7.0,6,37,Urban,Manager,46173,0 +113547,Male,21,Bachelors,11,53,35,29,70,9.0,7,35,Semi-Urban,ML Engineer,143514,0 +113548,Female,42,Masters,15,77,65,22,3,8.0,1,45,Urban,Manager,26978,0 +113549,Male,45,Bachelors,8,7,25,7,23,1.0,4,79,Urban,HR Executive,79362,0 +113550,Female,24,Bachelors,0,23,0,58,37,6.0,2,35,Urban,Data Analyst,101259,0 +113551,Female,55,High School,4,97,36,45,24,4.0,3,74,Urban,Manager,62147,1 +113552,Male,22,Masters,4,39,98,36,20,3.0,5,42,Urban,Data Analyst,132907,0 +113553,Male,40,Diploma,9,35,56,98,28,2.0,4,28,Urban,Software Engineer,33767,0 +113554,Male,24,Bachelors,8,48,90,20,21,2.0,4,74,Urban,Manager,119625,0 +113555,Male,45,High School,11,94,63,61,65,9.0,1,7,Rural,Software Engineer,77646,0 +113556,Female,47,High School,6,98,74,60,94,9.0,6,35,Urban,ML Engineer,88272,1 +113557,Male,25,Diploma,6,42,94,3,1,9.0,5,46,Urban,Data Analyst,122665,0 +113558,Female,59,Diploma,3,74,94,29,59,8.0,4,41,Urban,HR Executive,61517,0 +113559,Male,36,Bachelors,7,71,46,72,67,9.0,6,68,Semi-Urban,Software Engineer,43884,1 +113560,Male,39,Bachelors,0,13,46,16,71,2.0,2,54,Urban,ML Engineer,128661,0 +113561,Female,23,Bachelors,16,42,53,18,72,7.0,4,70,Urban,Software Engineer,87648,0 +113562,Female,41,Bachelors,19,0,91,60,29,7.0,1,98,Urban,ML Engineer,28420,1 +113563,Male,34,Diploma,1,90,12,62,5,4.0,1,28,Urban,Manager,80444,0 +113564,Female,31,Diploma,1,25,6,26,83,9.0,2,28,Urban,Software Engineer,102459,0 +113565,Female,27,High School,3,92,52,51,27,7.0,6,13,Rural,Data Analyst,141753,0 +113566,Male,28,High School,19,1,50,70,41,7.0,6,4,Urban,Manager,82531,0 +113567,Female,35,Bachelors,4,59,22,18,28,6.0,2,33,Rural,Software Engineer,143354,0 +113568,Male,48,High School,8,66,8,41,29,8.0,1,38,Rural,HR Executive,95863,0 +113569,Male,49,Masters,14,22,48,14,27,2.0,7,31,Semi-Urban,HR Executive,132418,0 +113570,Male,25,Bachelors,13,2,9,23,34,9.0,0,0,Urban,HR Executive,129490,0 +113571,Female,56,Masters,8,43,85,98,55,8.0,2,41,Semi-Urban,ML Engineer,101984,1 +113572,Male,22,Bachelors,18,56,37,14,66,4.0,6,93,Urban,HR Executive,145647,0 +113573,Male,46,Bachelors,3,72,26,38,40,4.0,2,13,Semi-Urban,HR Executive,86270,0 +113574,Male,31,High School,18,86,90,30,57,7.0,7,81,Semi-Urban,Manager,75369,1 +113575,Male,28,Masters,1,1,36,1,28,4.0,4,73,Urban,ML Engineer,49540,0 +113576,Male,56,Diploma,17,51,9,53,4,1.0,7,74,Semi-Urban,Software Engineer,84534,0 +113577,Female,39,Diploma,8,15,14,92,21,3.0,4,69,Urban,ML Engineer,31654,0 +113578,Female,51,Diploma,0,56,23,26,45,3.0,5,0,Urban,HR Executive,104141,0 +113579,Male,56,Bachelors,10,71,46,23,54,5.0,0,72,Urban,HR Executive,112184,0 +113580,Female,37,High School,16,79,79,52,74,1.0,6,16,Rural,ML Engineer,54652,0 +113581,Female,25,Bachelors,1,9,94,6,67,1.0,7,5,Urban,Software Engineer,21614,0 +113582,Male,26,Diploma,11,98,51,60,42,4.0,2,95,Urban,Data Analyst,61274,1 +113583,Female,49,Bachelors,2,2,0,22,70,5.0,4,39,Urban,Data Analyst,47614,0 +113584,Male,46,Masters,2,65,82,82,77,3.0,6,36,Rural,Software Engineer,38709,1 +113585,Male,42,High School,17,27,7,27,21,5.0,6,90,Urban,HR Executive,93775,0 +113586,Male,41,Masters,9,18,83,57,9,3.0,2,35,Urban,Manager,38522,0 +113587,Female,29,Bachelors,0,97,51,50,79,9.0,6,82,Rural,HR Executive,125679,1 +113588,Other,30,Diploma,2,82,7,86,38,1.0,6,97,Urban,Software Engineer,104192,1 +113589,Female,34,Masters,18,54,0,83,62,7.0,6,22,Rural,Software Engineer,98866,0 +113590,Male,38,Diploma,1,76,71,79,61,3.0,5,64,Rural,HR Executive,62286,1 +113591,Male,52,Bachelors,3,85,97,46,24,3.0,6,53,Rural,Data Analyst,110685,1 +113592,Male,42,High School,7,84,71,84,84,9.0,3,50,Urban,ML Engineer,39901,1 +113593,Male,25,Masters,17,19,75,43,65,2.0,4,14,Urban,Manager,33736,0 +113594,Female,24,High School,7,26,66,2,65,1.0,6,80,Urban,ML Engineer,80837,0 +113595,Male,24,Bachelors,2,99,96,23,14,2.0,0,7,Semi-Urban,ML Engineer,95513,0 +113596,Male,21,Masters,16,41,37,86,50,6.0,6,71,Urban,Manager,149565,1 +113597,Female,28,Masters,2,92,54,88,37,9.0,2,18,Semi-Urban,ML Engineer,76170,1 +113598,Male,37,Masters,12,19,98,18,42,4.0,2,3,Urban,ML Engineer,65911,0 +113599,Female,47,Masters,5,51,35,23,61,0.0,2,91,Urban,ML Engineer,55382,0 +113600,Male,27,Diploma,11,43,16,8,8,0.0,4,67,Rural,HR Executive,75895,0 +113601,Female,47,High School,19,86,62,17,10,9.0,7,6,Urban,Manager,110156,0 +113602,Female,55,PhD,6,34,99,73,59,9.0,5,77,Urban,Manager,72601,1 +113603,Female,58,High School,16,79,62,46,61,6.0,2,44,Urban,Data Analyst,103059,0 +113604,Male,34,Bachelors,10,74,47,37,78,5.0,1,3,Rural,Software Engineer,38626,0 +113605,Other,40,Masters,18,80,34,67,41,0.0,6,84,Urban,Software Engineer,98228,1 +113606,Male,56,Masters,10,5,4,83,18,6.0,1,25,Urban,Manager,81112,0 +113607,Female,29,Bachelors,19,4,60,41,22,6.0,0,30,Rural,HR Executive,74999,0 +113608,Male,41,High School,15,38,71,38,3,0.0,3,67,Semi-Urban,ML Engineer,52878,0 +113609,Other,46,Diploma,17,11,69,95,18,8.0,1,84,Rural,Manager,108368,1 +113610,Male,44,Bachelors,9,21,62,47,52,3.0,5,45,Urban,HR Executive,51570,0 +113611,Female,47,Bachelors,17,3,89,12,84,1.0,6,90,Urban,Manager,72971,0 +113612,Other,54,Bachelors,4,9,60,90,38,1.0,3,63,Urban,ML Engineer,125680,0 +113613,Female,32,High School,8,37,14,73,45,8.0,4,40,Urban,ML Engineer,130271,0 +113614,Female,40,Bachelors,6,36,64,73,29,5.0,2,46,Semi-Urban,Data Analyst,146178,0 +113615,Female,30,Diploma,19,18,14,19,17,9.0,4,79,Semi-Urban,ML Engineer,92869,0 +113616,Other,49,Masters,12,61,2,36,9,5.0,2,76,Urban,ML Engineer,71826,0 +113617,Female,43,Diploma,4,84,9,56,50,1.0,4,41,Urban,ML Engineer,137134,0 +113618,Male,23,Diploma,6,56,82,69,67,5.0,3,92,Semi-Urban,Data Analyst,67775,1 +113619,Male,33,Bachelors,18,19,31,69,11,1.0,3,38,Semi-Urban,Manager,62857,0 +113620,Female,25,Bachelors,13,99,29,61,2,1.0,5,81,Urban,Manager,121723,1 +113621,Male,34,High School,19,77,84,37,22,2.0,4,25,Urban,Manager,50406,0 +113622,Male,54,Bachelors,7,89,49,97,66,8.0,5,76,Urban,HR Executive,34258,1 +113623,Female,40,High School,16,26,9,66,71,1.0,0,64,Semi-Urban,Data Analyst,96703,0 +113624,Male,44,High School,6,13,47,19,27,3.0,1,54,Semi-Urban,Software Engineer,130073,0 +113625,Male,32,High School,12,69,63,97,34,3.0,2,23,Urban,ML Engineer,95112,1 +113626,Female,47,Masters,9,5,72,67,16,8.0,7,57,Rural,Data Analyst,100022,0 +113627,Female,51,Bachelors,1,30,13,96,88,7.0,7,11,Urban,HR Executive,125797,0 +113628,Male,35,High School,12,58,44,39,25,5.0,3,84,Rural,ML Engineer,76558,0 +113629,Male,22,Masters,18,6,15,81,47,7.0,3,78,Rural,Software Engineer,25201,0 +113630,Male,50,High School,11,16,20,32,62,2.0,3,1,Semi-Urban,Manager,49789,0 +113631,Female,49,Bachelors,5,50,93,89,5,5.0,6,33,Rural,Manager,114842,1 +113632,Male,46,Diploma,5,73,65,65,28,4.0,6,89,Urban,Manager,120714,1 +113633,Male,59,PhD,0,11,82,98,43,6.0,7,72,Urban,Software Engineer,44998,1 +113634,Female,28,High School,18,57,31,63,35,6.0,0,44,Urban,Data Analyst,24559,0 +113635,Male,40,Masters,6,97,99,19,91,7.0,7,19,Rural,ML Engineer,140344,0 +113636,Female,46,Diploma,15,22,33,1,18,2.0,1,12,Urban,ML Engineer,39312,0 +113637,Male,47,Bachelors,1,67,95,60,18,6.0,6,14,Rural,HR Executive,114240,1 +113638,Male,32,Diploma,8,62,75,69,95,9.0,1,87,Urban,HR Executive,98452,1 +113639,Male,46,Diploma,4,9,33,26,62,4.0,1,96,Urban,HR Executive,64118,0 +113640,Female,38,Bachelors,4,46,14,36,32,1.0,7,25,Rural,Data Analyst,56834,0 +113641,Male,58,Bachelors,1,58,24,80,86,9.0,1,96,Urban,Software Engineer,133596,1 +113642,Male,44,Masters,5,32,21,53,59,1.0,0,75,Urban,Data Analyst,36433,0 +113643,Other,44,Bachelors,17,74,61,44,88,3.0,5,75,Semi-Urban,ML Engineer,144981,1 +113644,Male,43,Bachelors,1,23,67,81,84,8.0,7,50,Urban,Manager,76341,0 +113645,Female,22,Bachelors,9,9,5,18,12,4.0,7,98,Semi-Urban,Software Engineer,80374,0 +113646,Female,41,Bachelors,5,11,53,8,12,8.0,3,81,Urban,Data Analyst,24716,0 +113647,Male,24,High School,5,57,35,5,6,7.0,2,76,Semi-Urban,ML Engineer,93698,0 +113648,Male,24,Masters,13,31,5,17,31,3.0,7,44,Rural,Data Analyst,136234,0 +113649,Male,32,High School,13,68,28,33,82,0.0,1,86,Rural,ML Engineer,51820,0 +113650,Male,41,Bachelors,1,29,89,22,59,1.0,1,81,Urban,Software Engineer,116631,0 +113651,Male,39,Bachelors,11,68,96,36,11,5.0,7,51,Urban,Software Engineer,87965,1 +113652,Female,59,PhD,18,51,35,6,69,2.0,6,63,Semi-Urban,Data Analyst,37316,0 +113653,Other,44,Diploma,16,83,82,68,97,2.0,0,59,Urban,Data Analyst,20102,1 +113654,Male,43,High School,3,51,31,84,56,3.0,4,49,Urban,Manager,137073,0 +113655,Female,53,Bachelors,19,91,54,75,98,2.0,6,55,Urban,Software Engineer,31703,1 +113656,Female,28,Bachelors,8,88,14,15,9,7.0,1,53,Urban,HR Executive,39954,0 +113657,Male,48,Masters,9,10,87,21,86,1.0,1,80,Urban,HR Executive,120893,0 +113658,Male,58,Bachelors,14,88,88,77,37,7.0,6,46,Urban,ML Engineer,35634,1 +113659,Male,54,High School,11,64,36,59,58,7.0,6,77,Urban,Manager,132450,1 +113660,Male,50,PhD,11,85,16,24,2,6.0,4,9,Urban,Manager,137820,0 +113661,Male,30,Diploma,11,20,27,44,40,3.0,5,25,Semi-Urban,Manager,114675,0 +113662,Female,42,Bachelors,8,86,31,38,75,8.0,2,34,Urban,HR Executive,101570,0 +113663,Female,44,PhD,18,2,65,18,92,4.0,7,22,Urban,Data Analyst,59175,0 +113664,Male,24,Masters,3,14,55,59,54,8.0,1,28,Rural,Software Engineer,50624,0 +113665,Male,36,Diploma,8,97,56,81,3,9.0,7,59,Rural,Manager,130622,1 +113666,Male,55,Masters,9,68,12,12,7,8.0,7,72,Urban,Software Engineer,80647,0 +113667,Male,33,Bachelors,13,23,29,63,37,6.0,7,54,Semi-Urban,Software Engineer,143756,0 +113668,Female,49,Bachelors,4,30,65,91,27,4.0,5,13,Urban,Software Engineer,28390,0 +113669,Male,50,Bachelors,5,13,81,71,99,3.0,7,53,Urban,Software Engineer,25936,0 +113670,Male,45,High School,13,71,74,17,34,4.0,5,42,Urban,Manager,41353,0 +113671,Male,29,Bachelors,13,13,29,35,11,8.0,3,11,Rural,Software Engineer,64989,0 +113672,Male,23,PhD,19,33,20,11,38,5.0,4,51,Semi-Urban,HR Executive,79731,0 +113673,Female,33,Bachelors,16,87,35,68,37,7.0,2,52,Urban,Manager,114479,1 +113674,Female,28,Bachelors,6,89,31,40,80,3.0,5,65,Urban,HR Executive,53050,0 +113675,Female,39,High School,4,2,27,23,57,0.0,3,75,Urban,Manager,126803,0 +113676,Female,51,Bachelors,19,40,94,44,25,4.0,5,18,Rural,ML Engineer,46211,0 +113677,Male,41,Bachelors,16,70,35,32,84,4.0,5,12,Semi-Urban,HR Executive,82517,0 +113678,Female,31,Masters,14,55,4,71,3,6.0,0,76,Urban,Software Engineer,117415,0 +113679,Male,49,Diploma,8,82,0,98,78,4.0,2,33,Semi-Urban,ML Engineer,55425,0 +113680,Male,57,Bachelors,4,74,88,47,57,8.0,5,74,Rural,ML Engineer,89581,1 +113681,Male,31,Masters,7,97,95,0,3,5.0,6,13,Urban,Manager,96788,0 +113682,Female,33,Masters,8,36,70,69,61,7.0,6,91,Urban,Software Engineer,68855,1 +113683,Male,37,Diploma,18,12,32,24,59,5.0,6,69,Rural,ML Engineer,101798,0 +113684,Female,27,Bachelors,0,93,5,38,47,6.0,3,31,Semi-Urban,HR Executive,89042,0 +113685,Male,21,Bachelors,3,91,57,33,2,5.0,5,86,Urban,ML Engineer,100386,1 +113686,Male,26,Bachelors,5,23,32,48,71,3.0,0,14,Urban,HR Executive,44833,0 +113687,Female,45,Masters,12,14,61,48,23,8.0,0,31,Semi-Urban,HR Executive,146730,0 +113688,Male,32,Diploma,7,24,1,85,18,1.0,7,43,Urban,Manager,132977,0 +113689,Female,30,High School,9,95,93,58,14,5.0,7,64,Urban,HR Executive,119678,1 +113690,Male,30,High School,10,43,9,65,54,5.0,2,72,Semi-Urban,Data Analyst,57288,0 +113691,Male,30,Diploma,3,98,36,72,37,9.0,2,59,Semi-Urban,HR Executive,122655,1 +113692,Female,31,Bachelors,1,13,73,8,80,5.0,5,59,Semi-Urban,Software Engineer,103732,0 +113693,Male,24,High School,6,74,37,91,59,7.0,2,62,Semi-Urban,Software Engineer,65306,1 +113694,Male,43,Bachelors,8,89,93,45,0,0.0,2,99,Urban,ML Engineer,31614,1 +113695,Other,45,Masters,11,59,60,92,67,1.0,3,50,Urban,Manager,60312,1 +113696,Male,24,Bachelors,9,97,43,69,34,9.0,7,93,Semi-Urban,Data Analyst,33058,1 +113697,Female,36,Bachelors,8,70,69,28,52,9.0,7,72,Semi-Urban,ML Engineer,121524,0 +113698,Female,54,Bachelors,0,91,87,20,79,7.0,0,32,Urban,Software Engineer,107702,0 +113699,Male,54,Bachelors,14,23,47,57,24,4.0,0,86,Urban,Manager,20073,0 +113700,Male,31,Bachelors,8,57,10,67,32,0.0,6,1,Urban,HR Executive,137146,0 +113701,Female,57,Bachelors,13,36,1,59,57,4.0,3,9,Rural,HR Executive,103931,0 +113702,Male,40,PhD,2,68,98,3,77,2.0,2,80,Urban,HR Executive,62676,1 +113703,Female,27,High School,12,27,80,33,83,8.0,7,76,Semi-Urban,ML Engineer,124887,0 +113704,Female,40,Bachelors,17,4,32,11,92,4.0,3,2,Semi-Urban,HR Executive,47140,0 +113705,Male,51,Diploma,1,93,62,41,24,2.0,1,42,Rural,ML Engineer,103207,1 +113706,Male,40,Bachelors,19,56,22,50,29,3.0,4,29,Urban,Manager,89981,0 +113707,Male,37,Masters,1,64,68,12,5,1.0,3,72,Semi-Urban,Software Engineer,40438,0 +113708,Other,56,Masters,6,98,93,36,22,8.0,6,14,Semi-Urban,HR Executive,144948,1 +113709,Male,57,PhD,18,99,15,55,51,7.0,5,84,Semi-Urban,Software Engineer,21090,1 +113710,Male,43,PhD,15,58,6,77,55,9.0,5,84,Urban,Manager,129156,0 +113711,Male,55,High School,2,79,55,1,69,9.0,2,59,Semi-Urban,Manager,111486,0 +113712,Male,21,Bachelors,9,31,38,34,45,9.0,5,26,Rural,ML Engineer,37233,0 +113713,Male,21,Bachelors,8,46,96,57,40,5.0,1,93,Urban,HR Executive,115736,1 +113714,Male,24,Bachelors,14,16,9,0,2,9.0,4,85,Urban,Software Engineer,126234,0 +113715,Female,50,Diploma,16,33,28,87,35,9.0,5,10,Urban,HR Executive,60945,0 +113716,Female,29,Bachelors,9,90,26,20,86,4.0,5,98,Semi-Urban,Data Analyst,64598,0 +113717,Male,28,Bachelors,8,59,10,53,29,4.0,0,81,Rural,HR Executive,43005,0 +113718,Male,27,Bachelors,3,31,39,77,15,7.0,4,65,Urban,Software Engineer,59135,0 +113719,Male,49,Bachelors,4,64,84,87,16,8.0,6,3,Rural,Data Analyst,25970,1 +113720,Male,45,Bachelors,0,1,25,4,99,5.0,6,88,Urban,HR Executive,37591,0 +113721,Male,24,Masters,16,14,58,22,10,0.0,5,99,Urban,ML Engineer,57460,0 +113722,Male,48,High School,18,91,33,33,41,3.0,4,88,Urban,Manager,130065,1 +113723,Male,43,PhD,11,87,11,6,80,1.0,3,87,Rural,Software Engineer,123191,0 +113724,Male,46,Masters,19,17,21,61,74,0.0,6,12,Urban,Manager,63617,0 +113725,Male,41,Masters,3,81,54,98,64,2.0,7,88,Semi-Urban,Data Analyst,96940,1 +113726,Male,44,Bachelors,11,65,2,66,96,8.0,2,75,Urban,Data Analyst,28837,0 +113727,Male,47,High School,17,42,18,41,85,8.0,5,86,Urban,Manager,135047,0 +113728,Male,35,High School,6,28,41,68,56,7.0,1,20,Urban,ML Engineer,105205,0 +113729,Female,41,Diploma,1,27,3,25,57,4.0,1,37,Urban,Data Analyst,37567,0 +113730,Male,54,Bachelors,19,70,57,16,65,5.0,1,63,Urban,Manager,31227,0 +113731,Male,37,High School,7,32,67,9,34,5.0,4,70,Semi-Urban,Manager,117383,0 +113732,Female,23,Bachelors,3,23,9,50,76,2.0,5,71,Urban,HR Executive,49306,0 +113733,Male,44,Bachelors,8,84,42,45,70,7.0,2,91,Urban,ML Engineer,53596,1 +113734,Male,25,Masters,2,30,77,88,0,5.0,0,80,Urban,ML Engineer,46085,1 +113735,Male,39,Bachelors,7,28,60,5,54,1.0,1,44,Urban,HR Executive,38149,0 +113736,Female,33,Diploma,3,70,80,25,22,5.0,4,48,Urban,Manager,90462,0 +113737,Male,45,Bachelors,3,1,0,81,81,5.0,6,54,Urban,ML Engineer,38805,0 +113738,Female,57,Masters,4,3,65,46,6,7.0,2,14,Urban,ML Engineer,84775,0 +113739,Female,54,Masters,6,81,84,96,56,3.0,5,15,Urban,Data Analyst,20443,1 +113740,Female,48,High School,7,11,37,89,91,5.0,3,70,Urban,Manager,63053,0 +113741,Female,21,High School,7,31,6,31,8,3.0,0,46,Urban,ML Engineer,103403,0 +113742,Male,56,PhD,1,44,80,37,90,1.0,4,16,Semi-Urban,Software Engineer,148279,0 +113743,Female,47,High School,0,75,93,65,5,9.0,3,21,Semi-Urban,Software Engineer,110750,1 +113744,Male,33,Bachelors,14,40,62,43,88,6.0,4,73,Semi-Urban,Software Engineer,103087,0 +113745,Male,37,Masters,9,67,49,65,52,4.0,4,25,Urban,HR Executive,134525,0 +113746,Female,25,Bachelors,2,24,78,68,19,5.0,7,30,Urban,ML Engineer,44490,0 +113747,Male,24,Masters,4,49,29,4,79,7.0,6,44,Rural,ML Engineer,78877,0 +113748,Male,42,High School,13,79,43,3,12,9.0,0,49,Urban,ML Engineer,95098,0 +113749,Other,28,Bachelors,2,87,46,46,92,1.0,1,43,Urban,ML Engineer,105675,0 +113750,Female,24,Diploma,11,81,18,12,20,3.0,4,42,Urban,HR Executive,24707,0 +113751,Male,55,PhD,12,12,45,45,16,8.0,6,13,Urban,HR Executive,92147,0 +113752,Other,46,Diploma,8,31,31,1,51,1.0,7,98,Urban,Data Analyst,36208,0 +113753,Male,57,Diploma,3,9,41,29,50,2.0,2,39,Semi-Urban,ML Engineer,66290,0 +113754,Male,38,Masters,6,26,19,44,81,1.0,4,46,Urban,Data Analyst,57374,0 +113755,Male,40,Bachelors,1,76,7,8,14,4.0,2,83,Rural,HR Executive,84983,0 +113756,Female,52,Masters,10,33,67,93,23,2.0,5,76,Urban,ML Engineer,59958,1 +113757,Female,57,Diploma,16,15,41,66,87,2.0,6,96,Semi-Urban,ML Engineer,30752,0 +113758,Female,42,Masters,0,85,20,74,88,6.0,1,34,Urban,HR Executive,90472,0 +113759,Female,55,Bachelors,3,75,14,98,76,3.0,0,82,Rural,Software Engineer,50434,1 +113760,Other,24,Bachelors,17,80,40,53,41,6.0,4,76,Semi-Urban,HR Executive,47654,1 +113761,Male,48,Bachelors,13,4,14,20,29,6.0,4,67,Rural,Manager,72939,0 +113762,Male,33,Bachelors,4,62,61,66,67,6.0,6,57,Urban,Manager,132916,1 +113763,Female,55,Masters,16,7,43,88,50,5.0,4,46,Urban,Manager,72682,0 +113764,Female,41,Diploma,7,68,79,52,93,3.0,2,80,Urban,ML Engineer,149692,1 +113765,Female,36,Diploma,8,29,85,12,35,8.0,2,94,Semi-Urban,Manager,88250,0 +113766,Male,29,High School,12,88,34,51,74,2.0,1,80,Rural,ML Engineer,77557,1 +113767,Male,49,High School,3,22,83,22,65,9.0,6,64,Rural,HR Executive,63195,0 +113768,Male,59,PhD,2,66,48,50,54,7.0,3,34,Urban,ML Engineer,106808,0 +113769,Female,34,PhD,18,68,31,34,55,6.0,2,97,Urban,Data Analyst,31967,0 +113770,Other,37,Masters,10,6,73,12,27,4.0,4,78,Urban,Manager,116285,0 +113771,Male,30,Bachelors,11,69,75,22,88,1.0,5,91,Urban,Data Analyst,68350,1 +113772,Female,38,Bachelors,11,2,47,70,23,7.0,7,51,Urban,ML Engineer,98993,0 +113773,Male,56,Masters,9,22,82,79,52,2.0,6,52,Rural,Manager,106824,1 +113774,Female,57,Diploma,8,63,14,44,30,8.0,6,88,Rural,HR Executive,108969,0 +113775,Male,33,High School,1,34,40,8,5,0.0,0,5,Rural,HR Executive,83599,0 +113776,Other,54,Masters,14,74,71,32,97,2.0,1,58,Urban,ML Engineer,133937,0 +113777,Male,29,Diploma,9,3,98,24,91,6.0,0,21,Semi-Urban,Software Engineer,66271,0 +113778,Female,52,Bachelors,6,84,91,12,97,6.0,4,23,Semi-Urban,ML Engineer,56303,0 +113779,Male,51,Bachelors,8,6,50,14,3,8.0,0,12,Semi-Urban,Software Engineer,42798,0 +113780,Female,45,High School,13,18,49,86,74,1.0,2,66,Rural,ML Engineer,127502,0 +113781,Female,48,Diploma,6,7,94,64,95,1.0,6,91,Semi-Urban,HR Executive,45494,1 +113782,Male,46,Diploma,2,98,71,96,61,2.0,5,97,Urban,Software Engineer,104720,1 +113783,Male,40,Diploma,14,32,9,51,72,3.0,1,46,Urban,ML Engineer,133695,0 +113784,Female,39,Masters,3,23,4,38,93,8.0,7,17,Urban,Software Engineer,93812,0 +113785,Male,21,High School,0,46,82,76,99,7.0,5,94,Urban,ML Engineer,91600,1 +113786,Female,27,Diploma,10,37,76,86,81,5.0,4,6,Urban,Software Engineer,123629,0 +113787,Female,53,Bachelors,6,54,31,9,59,2.0,7,76,Rural,ML Engineer,68208,0 +113788,Male,45,Bachelors,0,45,99,98,44,4.0,3,20,Rural,Manager,109580,1 +113789,Female,28,Masters,13,10,78,57,11,1.0,3,5,Rural,Software Engineer,140130,0 +113790,Male,26,Bachelors,6,53,17,21,64,7.0,6,22,Urban,Data Analyst,47192,0 +113791,Female,54,High School,19,60,4,87,77,3.0,2,60,Semi-Urban,Manager,40658,0 +113792,Male,53,Bachelors,4,84,7,60,71,4.0,7,21,Semi-Urban,ML Engineer,63894,0 +113793,Female,21,Diploma,6,74,13,8,17,1.0,4,46,Urban,HR Executive,106264,0 +113794,Female,54,PhD,3,63,16,56,43,8.0,1,56,Rural,Software Engineer,39526,0 +113795,Female,49,Diploma,16,55,28,7,64,6.0,5,50,Urban,Manager,26558,0 +113796,Male,40,High School,6,67,70,26,24,1.0,2,55,Rural,ML Engineer,71343,0 +113797,Male,55,Masters,0,64,70,28,91,4.0,0,4,Urban,Manager,146076,0 +113798,Female,49,Diploma,18,23,25,70,57,9.0,0,63,Urban,ML Engineer,53433,0 +113799,Other,31,Bachelors,1,92,93,21,28,3.0,5,37,Urban,Data Analyst,93752,1 +113800,Male,23,Bachelors,5,46,94,18,59,1.0,0,79,Semi-Urban,Data Analyst,99961,1 +113801,Male,54,High School,9,61,64,33,35,7.0,4,83,Urban,ML Engineer,64780,1 +113802,Male,48,High School,7,67,21,55,46,4.0,1,99,Urban,HR Executive,94519,1 +113803,Male,50,Diploma,18,91,78,52,35,6.0,7,58,Rural,Manager,139652,1 +113804,Male,24,Bachelors,19,15,6,24,86,0.0,1,21,Semi-Urban,Data Analyst,62712,0 +113805,Male,41,Diploma,10,40,24,51,59,7.0,2,50,Rural,Software Engineer,29749,0 +113806,Female,36,Bachelors,14,48,32,29,54,1.0,2,69,Semi-Urban,Data Analyst,33480,0 +113807,Male,57,Bachelors,3,38,23,63,15,0.0,0,88,Rural,ML Engineer,115986,0 +113808,Female,51,Diploma,9,18,84,34,95,1.0,1,95,Semi-Urban,ML Engineer,58925,0 +113809,Male,45,Bachelors,6,21,43,22,91,2.0,0,41,Rural,HR Executive,77898,0 +113810,Female,51,Masters,16,80,82,46,36,9.0,4,84,Urban,Data Analyst,104943,1 +113811,Male,27,Masters,16,90,86,64,82,4.0,5,97,Urban,Manager,28362,1 +113812,Female,53,Masters,13,94,3,35,37,3.0,2,40,Urban,Manager,56907,0 +113813,Female,25,Diploma,3,62,50,83,97,7.0,4,14,Semi-Urban,HR Executive,69519,0 +113814,Male,31,Masters,0,20,72,4,47,1.0,7,53,Urban,Software Engineer,82491,0 +113815,Female,58,PhD,5,85,96,18,43,2.0,3,21,Urban,Data Analyst,141130,0 +113816,Male,53,Bachelors,1,31,0,52,24,4.0,4,69,Urban,HR Executive,149401,0 +113817,Male,37,Bachelors,9,78,13,20,48,6.0,5,64,Urban,Data Analyst,145704,0 +113818,Male,27,PhD,0,81,45,52,28,2.0,2,44,Urban,Manager,22354,0 +113819,Female,52,Bachelors,12,31,81,61,66,3.0,1,88,Urban,Software Engineer,48444,1 +113820,Male,26,Masters,11,72,26,53,44,3.0,1,68,Urban,ML Engineer,139337,0 +113821,Male,56,Bachelors,8,0,7,82,99,1.0,5,81,Rural,Software Engineer,135627,0 +113822,Male,55,PhD,18,24,64,94,86,9.0,7,21,Rural,Manager,34114,0 +113823,Female,34,Masters,2,3,51,99,23,2.0,5,56,Urban,HR Executive,71600,0 +113824,Female,22,Diploma,16,72,67,43,72,7.0,2,30,Rural,ML Engineer,42124,0 +113825,Male,58,Bachelors,3,47,6,61,60,2.0,0,64,Urban,Manager,143376,0 +113826,Female,45,High School,4,63,21,29,16,9.0,6,22,Semi-Urban,Software Engineer,147812,0 +113827,Female,33,Bachelors,11,0,63,95,16,2.0,2,29,Urban,HR Executive,105026,0 +113828,Female,35,Diploma,4,77,72,52,80,8.0,2,32,Urban,Software Engineer,143418,0 +113829,Male,36,Masters,16,23,93,17,28,3.0,1,93,Urban,Manager,130864,0 +113830,Female,37,Masters,3,3,40,63,10,1.0,2,0,Urban,HR Executive,81743,0 +113831,Female,40,Masters,2,91,73,18,35,4.0,6,21,Semi-Urban,Data Analyst,70703,0 +113832,Female,55,High School,13,40,82,36,25,4.0,4,48,Urban,HR Executive,60310,0 +113833,Male,38,Diploma,4,63,88,50,66,9.0,7,40,Urban,HR Executive,123724,1 +113834,Male,39,Diploma,5,13,79,5,41,7.0,7,17,Semi-Urban,Manager,140336,0 +113835,Male,43,Masters,9,66,90,53,25,3.0,1,54,Semi-Urban,ML Engineer,36724,1 +113836,Male,36,Bachelors,5,5,23,94,7,9.0,4,67,Semi-Urban,Data Analyst,78252,0 +113837,Female,40,Masters,12,61,98,3,15,8.0,2,82,Rural,HR Executive,46617,1 +113838,Female,31,High School,0,70,24,12,78,5.0,5,22,Rural,Software Engineer,28224,0 +113839,Female,37,Masters,6,47,87,3,86,2.0,0,75,Rural,Software Engineer,52816,0 +113840,Male,35,Bachelors,14,72,64,25,38,0.0,6,65,Semi-Urban,ML Engineer,31498,0 +113841,Male,47,Bachelors,1,8,62,17,79,6.0,0,94,Urban,Data Analyst,78980,0 +113842,Female,35,High School,4,80,75,98,6,7.0,2,35,Urban,Manager,27721,1 +113843,Male,55,High School,9,4,58,64,37,8.0,7,71,Urban,HR Executive,61054,0 +113844,Female,56,Bachelors,12,19,23,26,55,7.0,6,87,Urban,Data Analyst,126207,0 +113845,Female,29,Bachelors,3,57,95,83,49,0.0,5,74,Urban,Data Analyst,67726,1 +113846,Male,30,Bachelors,18,40,3,58,42,9.0,1,78,Urban,HR Executive,112262,0 +113847,Male,44,Masters,6,72,32,86,70,1.0,7,45,Semi-Urban,Data Analyst,137577,1 +113848,Male,57,Masters,19,30,51,73,29,2.0,7,51,Urban,Manager,96826,0 +113849,Male,46,Bachelors,1,18,43,6,30,9.0,4,69,Urban,Software Engineer,139006,0 +113850,Male,54,Bachelors,14,85,70,87,42,7.0,4,74,Urban,ML Engineer,71536,1 +113851,Male,54,Bachelors,10,1,30,54,58,3.0,3,48,Rural,Manager,140943,0 +113852,Male,26,Bachelors,9,24,12,58,74,0.0,0,87,Urban,ML Engineer,33801,0 +113853,Other,30,Bachelors,11,78,50,25,2,6.0,2,97,Semi-Urban,Data Analyst,27004,1 +113854,Male,24,Diploma,14,91,4,95,37,7.0,7,13,Urban,Software Engineer,143343,0 +113855,Female,22,Diploma,8,56,29,24,53,9.0,4,4,Rural,HR Executive,25876,0 +113856,Female,38,Bachelors,11,85,93,25,78,5.0,4,23,Urban,Data Analyst,74904,0 +113857,Male,42,High School,6,77,61,34,24,1.0,0,70,Rural,Data Analyst,45098,1 +113858,Female,29,Diploma,4,89,62,61,57,9.0,0,37,Urban,HR Executive,146636,1 +113859,Male,27,Diploma,6,45,67,7,14,4.0,3,47,Urban,ML Engineer,129687,0 +113860,Male,46,PhD,7,98,71,96,36,4.0,2,49,Semi-Urban,ML Engineer,76975,1 +113861,Male,31,Bachelors,11,36,91,37,14,0.0,4,58,Rural,Software Engineer,58463,0 +113862,Male,25,Bachelors,7,33,56,9,98,1.0,1,83,Semi-Urban,HR Executive,106240,0 +113863,Male,59,High School,4,51,4,3,74,3.0,5,55,Urban,Software Engineer,138606,0 +113864,Female,31,Bachelors,19,36,13,33,64,8.0,0,23,Semi-Urban,Data Analyst,51243,0 +113865,Male,51,Masters,15,71,95,23,51,5.0,6,45,Rural,Data Analyst,88684,0 +113866,Male,48,Diploma,7,60,49,77,22,0.0,6,95,Rural,Data Analyst,107585,1 +113867,Male,41,Bachelors,10,80,34,57,93,0.0,7,41,Urban,ML Engineer,91477,0 +113868,Female,41,Bachelors,9,71,18,56,77,1.0,1,80,Semi-Urban,Software Engineer,148150,0 +113869,Male,22,High School,7,66,2,14,60,9.0,3,94,Urban,ML Engineer,24688,0 +113870,Male,56,Bachelors,8,4,63,19,70,4.0,6,81,Semi-Urban,Data Analyst,108672,0 +113871,Male,28,Diploma,10,28,70,72,91,3.0,1,65,Urban,Software Engineer,103742,1 +113872,Male,24,High School,8,5,42,91,55,4.0,7,41,Urban,ML Engineer,80437,0 +113873,Female,50,Masters,19,61,73,68,37,5.0,6,74,Rural,HR Executive,92628,1 +113874,Male,25,PhD,4,53,82,33,58,1.0,6,6,Urban,ML Engineer,55865,0 +113875,Female,56,Bachelors,5,86,83,2,18,7.0,5,75,Urban,Manager,84358,1 +113876,Male,23,Masters,3,30,32,93,17,3.0,6,21,Urban,ML Engineer,25219,0 +113877,Male,42,Bachelors,17,85,48,43,7,0.0,5,86,Semi-Urban,Manager,37487,1 +113878,Male,55,Diploma,8,94,84,72,84,5.0,2,0,Urban,Software Engineer,30925,1 +113879,Female,58,Diploma,15,36,42,68,42,4.0,6,74,Urban,Manager,27031,0 +113880,Male,22,Bachelors,4,28,63,92,5,0.0,5,66,Semi-Urban,Data Analyst,22800,1 +113881,Male,40,Bachelors,19,43,66,68,90,2.0,0,38,Rural,HR Executive,74387,0 +113882,Male,37,High School,2,11,19,86,9,4.0,6,68,Urban,Software Engineer,123099,0 +113883,Female,40,Masters,3,51,9,57,9,8.0,5,76,Urban,Software Engineer,119256,0 +113884,Male,42,Bachelors,12,3,53,20,86,9.0,3,71,Rural,Data Analyst,43500,0 +113885,Female,31,High School,2,31,51,70,54,6.0,0,78,Semi-Urban,Software Engineer,149754,0 +113886,Male,23,Diploma,18,0,9,72,10,4.0,2,22,Urban,HR Executive,123399,0 +113887,Male,27,Masters,6,51,32,12,20,4.0,0,44,Urban,Software Engineer,148480,0 +113888,Male,37,Masters,17,57,18,25,70,3.0,6,2,Rural,ML Engineer,98556,0 +113889,Male,50,Bachelors,16,86,31,95,85,9.0,1,45,Urban,Software Engineer,115155,1 +113890,Male,41,Masters,12,20,86,56,46,2.0,2,37,Semi-Urban,HR Executive,78435,0 +113891,Male,58,Masters,18,65,18,59,44,9.0,1,83,Rural,Manager,109495,0 +113892,Female,51,High School,8,13,94,21,28,6.0,3,70,Urban,HR Executive,79503,0 +113893,Male,52,Masters,9,56,97,89,42,0.0,4,25,Urban,ML Engineer,93308,1 +113894,Female,35,Diploma,12,25,86,54,70,7.0,2,10,Rural,Software Engineer,132458,0 +113895,Female,57,Bachelors,19,73,98,56,39,4.0,0,37,Urban,Software Engineer,111174,1 +113896,Female,42,Diploma,2,95,71,63,93,0.0,7,24,Rural,Software Engineer,38681,1 +113897,Female,32,Masters,2,78,21,85,70,9.0,7,33,Urban,Manager,64768,0 +113898,Female,47,High School,18,57,76,65,50,5.0,5,82,Rural,ML Engineer,132840,1 +113899,Male,58,Masters,8,33,71,4,77,3.0,0,15,Urban,ML Engineer,44639,0 +113900,Female,51,Masters,0,81,92,30,27,5.0,2,40,Urban,Software Engineer,45794,1 +113901,Male,50,Bachelors,6,26,11,33,90,7.0,0,69,Urban,Manager,129128,0 +113902,Male,23,Bachelors,2,19,63,82,11,0.0,3,81,Rural,HR Executive,136945,1 +113903,Female,40,PhD,12,8,23,59,14,2.0,2,79,Urban,ML Engineer,79932,0 +113904,Female,56,Masters,10,24,93,24,86,9.0,2,40,Urban,Software Engineer,96010,0 +113905,Male,42,Bachelors,5,46,70,15,84,3.0,6,2,Rural,Data Analyst,108809,0 +113906,Female,45,Diploma,5,55,17,34,71,0.0,5,32,Rural,ML Engineer,148550,0 +113907,Male,37,Diploma,16,45,60,29,68,1.0,2,17,Urban,Data Analyst,58477,0 +113908,Male,35,Bachelors,4,87,79,95,19,4.0,3,36,Rural,Software Engineer,28279,1 +113909,Male,30,Diploma,10,99,96,23,74,9.0,0,29,Urban,ML Engineer,133830,1 +113910,Other,34,Bachelors,17,67,44,83,10,2.0,6,28,Urban,ML Engineer,95104,0 +113911,Male,27,Bachelors,13,92,34,42,34,5.0,1,58,Semi-Urban,ML Engineer,42217,0 +113912,Male,55,Masters,7,22,18,37,53,9.0,3,16,Urban,Data Analyst,39163,0 +113913,Male,22,Bachelors,11,33,88,91,2,3.0,2,21,Semi-Urban,Manager,76576,0 +113914,Male,27,High School,10,0,51,56,91,7.0,1,63,Semi-Urban,Manager,120915,0 +113915,Male,44,High School,2,14,96,9,96,2.0,0,20,Semi-Urban,Data Analyst,127886,0 +113916,Male,34,Diploma,17,58,53,24,43,1.0,7,45,Urban,Software Engineer,50341,0 +113917,Female,41,Masters,12,18,93,4,32,4.0,6,12,Urban,Data Analyst,81661,0 +113918,Male,53,Diploma,14,62,32,13,48,8.0,2,9,Urban,ML Engineer,121666,0 +113919,Female,34,Diploma,2,40,32,12,80,7.0,6,79,Rural,Data Analyst,108181,0 +113920,Male,46,Diploma,0,41,99,82,63,5.0,3,23,Urban,Software Engineer,67067,1 +113921,Male,35,Bachelors,15,26,52,7,29,8.0,0,77,Semi-Urban,Software Engineer,106622,0 +113922,Male,40,Bachelors,6,2,12,79,11,0.0,4,72,Urban,Manager,62132,0 +113923,Male,25,Bachelors,7,17,23,24,10,1.0,1,41,Semi-Urban,ML Engineer,115108,0 +113924,Male,42,Diploma,3,7,12,71,91,8.0,6,65,Semi-Urban,ML Engineer,106912,0 +113925,Male,57,PhD,6,49,98,88,22,3.0,0,48,Rural,Software Engineer,45608,1 +113926,Male,42,Diploma,11,47,89,37,42,7.0,3,14,Semi-Urban,ML Engineer,138719,0 +113927,Male,53,PhD,6,30,18,37,22,1.0,5,94,Urban,HR Executive,77469,0 +113928,Male,47,High School,8,32,33,62,4,4.0,5,58,Rural,ML Engineer,45261,0 +113929,Female,27,Bachelors,16,21,51,76,23,9.0,5,14,Urban,Manager,54476,0 +113930,Female,55,High School,18,52,64,53,50,7.0,4,78,Urban,Manager,20833,1 +113931,Female,21,High School,6,95,76,69,95,8.0,0,7,Rural,HR Executive,44129,1 +113932,Male,24,Bachelors,5,6,29,30,89,6.0,4,27,Rural,Software Engineer,48864,0 +113933,Female,59,Diploma,10,17,90,26,47,0.0,7,13,Rural,Manager,41479,0 +113934,Female,36,Bachelors,12,32,46,80,63,8.0,1,34,Urban,Manager,149179,0 +113935,Female,45,Masters,12,91,13,48,86,9.0,1,88,Urban,Data Analyst,54853,0 +113936,Other,46,Bachelors,17,21,27,46,25,6.0,0,96,Urban,ML Engineer,45104,0 +113937,Male,38,Diploma,10,36,13,75,37,3.0,7,54,Urban,HR Executive,146674,0 +113938,Female,31,High School,12,60,97,36,45,2.0,6,95,Urban,HR Executive,127989,1 +113939,Male,54,Masters,19,38,58,0,29,7.0,7,88,Urban,Software Engineer,140541,0 +113940,Male,29,Bachelors,1,74,43,77,42,0.0,2,4,Urban,HR Executive,125139,0 +113941,Female,23,Bachelors,5,88,24,13,21,9.0,2,62,Urban,Data Analyst,51541,0 +113942,Male,21,Masters,10,54,5,66,3,5.0,3,79,Semi-Urban,HR Executive,74619,0 +113943,Male,28,Masters,0,63,25,36,33,0.0,7,23,Urban,Manager,71423,0 +113944,Male,26,Diploma,12,96,56,98,15,1.0,1,27,Rural,Manager,139993,1 +113945,Male,36,High School,1,57,62,12,47,0.0,0,9,Semi-Urban,Manager,25918,0 +113946,Male,38,Bachelors,9,44,57,63,7,5.0,6,53,Urban,HR Executive,62323,0 +113947,Female,29,Bachelors,9,96,12,1,92,4.0,1,73,Urban,ML Engineer,133040,0 +113948,Male,43,Masters,15,73,20,42,12,2.0,4,69,Urban,Data Analyst,87324,0 +113949,Male,50,Diploma,12,46,37,8,36,2.0,0,57,Urban,ML Engineer,127826,0 +113950,Male,55,Bachelors,19,13,45,73,8,9.0,5,93,Urban,Software Engineer,24119,0 +113951,Male,56,High School,11,55,64,44,61,7.0,6,68,Urban,ML Engineer,87733,0 +113952,Male,45,Bachelors,18,75,67,39,7,8.0,7,13,Urban,Software Engineer,117144,0 +113953,Male,47,Bachelors,8,5,14,98,37,1.0,6,0,Urban,Manager,35579,0 +113954,Male,53,Bachelors,7,95,35,87,81,1.0,3,34,Semi-Urban,Data Analyst,92753,1 +113955,Male,23,Bachelors,8,85,33,6,55,3.0,0,17,Urban,ML Engineer,115097,0 +113956,Male,59,Masters,11,82,72,98,50,8.0,2,81,Rural,HR Executive,147832,1 +113957,Male,43,Masters,15,50,3,40,2,7.0,1,61,Urban,Software Engineer,30210,0 +113958,Female,53,High School,15,82,66,6,99,2.0,5,8,Semi-Urban,Manager,70627,0 +113959,Male,53,Diploma,5,50,39,76,97,6.0,5,76,Urban,Software Engineer,144456,1 +113960,Male,25,Masters,19,59,83,8,2,9.0,7,79,Semi-Urban,HR Executive,36004,0 +113961,Male,56,Bachelors,7,7,58,11,56,6.0,1,32,Urban,HR Executive,48081,0 +113962,Female,46,Masters,0,26,47,43,46,9.0,5,83,Urban,Manager,95831,0 +113963,Male,23,Bachelors,12,80,97,95,50,6.0,1,89,Rural,Data Analyst,137598,1 +113964,Female,49,Masters,14,94,22,33,54,5.0,2,70,Urban,ML Engineer,22769,0 +113965,Male,47,Bachelors,6,49,76,47,17,3.0,3,38,Rural,Manager,89797,0 +113966,Female,35,Bachelors,11,77,33,76,20,1.0,7,50,Semi-Urban,Data Analyst,71441,0 +113967,Female,53,Diploma,11,95,71,90,81,3.0,5,47,Semi-Urban,Software Engineer,100524,1 +113968,Male,42,Masters,14,42,75,60,64,7.0,2,40,Urban,ML Engineer,86421,0 +113969,Male,58,Diploma,9,88,28,37,81,8.0,6,71,Urban,Data Analyst,115937,0 +113970,Male,47,Masters,16,10,85,85,82,1.0,5,56,Rural,ML Engineer,116257,1 +113971,Female,49,Masters,11,94,94,52,75,6.0,3,51,Rural,Data Analyst,115582,1 +113972,Male,57,Diploma,1,2,81,6,59,7.0,4,71,Urban,Manager,75741,0 +113973,Female,23,Diploma,6,45,33,86,65,2.0,0,57,Urban,HR Executive,63275,0 +113974,Male,44,PhD,12,75,54,13,23,1.0,3,15,Semi-Urban,HR Executive,114506,0 +113975,Female,44,Bachelors,13,54,80,79,74,1.0,4,43,Rural,ML Engineer,42990,1 +113976,Female,39,Masters,4,85,98,65,77,7.0,7,0,Semi-Urban,Software Engineer,107100,1 +113977,Male,48,Diploma,1,71,20,91,40,6.0,5,70,Rural,Data Analyst,81728,1 +113978,Female,37,Bachelors,15,50,41,98,1,6.0,5,1,Urban,Data Analyst,107179,0 +113979,Male,25,Masters,9,51,50,11,94,2.0,5,70,Urban,HR Executive,111006,0 +113980,Female,22,Bachelors,14,29,87,78,89,7.0,5,14,Urban,Software Engineer,42083,0 +113981,Female,26,Diploma,10,63,82,74,93,6.0,0,21,Rural,HR Executive,54479,0 +113982,Male,59,PhD,5,55,33,25,77,5.0,7,88,Semi-Urban,HR Executive,92723,0 +113983,Male,50,Bachelors,8,40,48,48,81,3.0,5,35,Urban,Data Analyst,102532,0 +113984,Female,47,High School,0,82,10,84,14,2.0,1,96,Urban,Manager,47427,1 +113985,Male,53,Masters,1,66,98,19,6,9.0,7,13,Urban,Manager,144208,0 +113986,Female,43,Masters,9,40,30,55,16,6.0,1,38,Rural,Software Engineer,52389,0 +113987,Female,46,Diploma,18,50,59,28,25,3.0,2,60,Urban,Software Engineer,24804,0 +113988,Male,34,Masters,15,38,81,19,86,8.0,4,0,Urban,Data Analyst,99728,0 +113989,Male,28,Masters,15,75,4,70,0,5.0,4,79,Urban,ML Engineer,140356,0 +113990,Male,41,Bachelors,13,73,58,78,25,5.0,5,24,Semi-Urban,Data Analyst,142047,0 +113991,Male,53,PhD,4,67,16,38,67,6.0,2,43,Urban,Manager,77255,0 +113992,Other,54,Diploma,19,11,77,16,24,1.0,2,14,Urban,Data Analyst,42431,0 +113993,Female,22,Bachelors,13,14,2,15,49,6.0,0,51,Urban,Manager,113507,0 +113994,Male,33,Bachelors,18,60,16,47,75,0.0,3,34,Urban,Manager,148619,0 +113995,Female,53,Bachelors,5,0,46,32,50,6.0,4,23,Urban,HR Executive,90184,0 +113996,Male,43,Bachelors,0,91,24,77,48,5.0,5,49,Urban,HR Executive,102183,1 +113997,Female,49,Bachelors,8,82,46,63,61,4.0,0,1,Rural,Software Engineer,131821,0 +113998,Male,30,Masters,0,2,37,58,11,8.0,1,63,Rural,Software Engineer,111744,0 +113999,Male,58,Bachelors,8,86,19,27,6,8.0,6,21,Semi-Urban,HR Executive,106842,0 +114000,Male,55,Bachelors,16,80,67,80,98,7.0,6,40,Urban,ML Engineer,83086,1 +114001,Male,25,High School,1,70,80,36,13,6.0,0,3,Semi-Urban,ML Engineer,84159,0 +114002,Female,30,High School,7,2,0,10,43,2.0,5,88,Urban,Manager,53623,0 +114003,Female,38,Masters,8,56,66,72,6,2.0,6,19,Rural,Manager,20374,0 +114004,Male,35,Bachelors,10,79,30,49,51,6.0,3,43,Rural,Software Engineer,60660,0 +114005,Female,45,High School,1,78,83,47,55,4.0,1,24,Semi-Urban,Software Engineer,93147,0 +114006,Male,33,High School,19,67,39,20,17,0.0,3,1,Urban,Software Engineer,93679,0 +114007,Female,56,High School,6,31,30,0,76,0.0,0,6,Rural,Data Analyst,122424,0 +114008,Male,49,High School,5,1,6,89,88,7.0,1,38,Rural,Software Engineer,115445,0 +114009,Female,43,Bachelors,3,73,36,92,35,0.0,5,43,Semi-Urban,ML Engineer,129365,1 +114010,Female,39,Bachelors,8,51,1,60,92,0.0,3,14,Rural,Software Engineer,35871,0 +114011,Male,23,Masters,0,46,59,45,97,0.0,4,83,Rural,Manager,107895,0 +114012,Female,22,PhD,14,97,97,82,12,6.0,6,67,Urban,Manager,24654,1 +114013,Male,23,High School,17,51,46,36,84,0.0,4,18,Urban,Data Analyst,85703,0 +114014,Female,51,Masters,9,11,85,62,76,3.0,0,11,Semi-Urban,ML Engineer,102165,0 +114015,Male,43,Bachelors,2,99,2,19,79,5.0,6,41,Urban,Software Engineer,88400,0 +114016,Female,37,High School,16,20,62,50,46,9.0,3,92,Urban,Data Analyst,74013,0 +114017,Female,52,High School,12,10,64,13,18,0.0,4,46,Rural,Manager,41886,0 +114018,Other,35,Diploma,4,8,44,56,38,6.0,2,28,Semi-Urban,Software Engineer,120915,0 +114019,Female,32,High School,2,27,85,12,1,1.0,7,0,Urban,ML Engineer,142602,0 +114020,Male,41,High School,18,85,44,14,40,1.0,6,92,Rural,ML Engineer,131750,1 +114021,Male,45,Bachelors,16,49,75,23,3,6.0,1,22,Urban,Manager,80191,0 +114022,Male,33,Diploma,15,48,11,62,94,4.0,6,65,Rural,Manager,24491,0 +114023,Female,46,Masters,16,55,61,62,15,2.0,5,72,Rural,HR Executive,21962,1 +114024,Male,38,Masters,16,11,23,75,16,0.0,0,95,Semi-Urban,Software Engineer,123191,0 +114025,Male,30,High School,14,58,64,78,48,6.0,3,90,Urban,HR Executive,129281,1 +114026,Female,58,Diploma,2,22,54,83,15,0.0,6,96,Urban,Manager,137603,1 +114027,Female,43,Diploma,10,11,31,43,89,2.0,0,28,Rural,HR Executive,126182,0 +114028,Female,30,Bachelors,4,53,66,74,40,5.0,1,89,Semi-Urban,Software Engineer,109512,1 +114029,Male,29,Masters,11,51,93,60,45,3.0,5,24,Rural,Software Engineer,92458,0 +114030,Female,33,High School,12,99,29,93,15,3.0,1,15,Rural,Software Engineer,94390,0 +114031,Other,41,Diploma,16,49,86,75,79,6.0,0,19,Rural,HR Executive,138290,0 +114032,Male,50,Bachelors,19,49,62,50,34,8.0,6,0,Urban,Data Analyst,91615,0 +114033,Male,40,Bachelors,3,7,94,74,98,7.0,6,22,Semi-Urban,Manager,71418,0 +114034,Male,25,Bachelors,11,13,45,20,64,8.0,7,58,Urban,ML Engineer,83866,0 +114035,Male,33,High School,17,45,73,82,4,9.0,3,87,Urban,Software Engineer,25494,1 +114036,Male,39,PhD,7,65,2,64,23,6.0,3,2,Urban,ML Engineer,107293,0 +114037,Female,47,Bachelors,7,61,41,30,36,2.0,4,11,Semi-Urban,HR Executive,48215,0 +114038,Male,45,High School,6,34,17,1,88,1.0,2,90,Semi-Urban,Software Engineer,57421,0 +114039,Male,34,Bachelors,4,3,54,70,85,9.0,3,76,Urban,Data Analyst,102304,0 +114040,Male,52,High School,5,55,55,92,28,9.0,6,44,Urban,HR Executive,100584,1 +114041,Male,39,Diploma,18,51,96,89,94,0.0,5,44,Urban,HR Executive,25282,1 +114042,Male,50,Masters,8,95,40,84,16,5.0,4,66,Urban,HR Executive,64854,1 +114043,Male,30,Masters,4,32,93,31,12,4.0,6,48,Urban,HR Executive,63575,0 +114044,Male,32,Bachelors,6,92,68,67,94,0.0,1,19,Rural,Software Engineer,105003,1 +114045,Male,53,Bachelors,6,60,8,85,81,6.0,2,13,Semi-Urban,HR Executive,147267,0 +114046,Female,56,Masters,17,77,91,72,43,0.0,3,96,Urban,HR Executive,57362,1 +114047,Female,36,Bachelors,16,38,38,88,50,8.0,1,27,Semi-Urban,HR Executive,122921,0 +114048,Male,29,Masters,10,40,71,41,0,6.0,7,23,Urban,Software Engineer,49599,0 +114049,Male,34,Bachelors,15,1,78,60,88,8.0,4,3,Rural,Manager,130528,0 +114050,Female,58,Bachelors,12,77,14,92,27,1.0,2,74,Urban,Software Engineer,88290,1 +114051,Female,22,High School,5,24,40,85,31,9.0,4,0,Rural,Data Analyst,103353,0 +114052,Male,24,Bachelors,9,73,18,74,2,0.0,4,85,Urban,HR Executive,23414,1 +114053,Male,36,Bachelors,14,65,96,76,24,9.0,1,54,Urban,ML Engineer,52598,1 +114054,Male,56,Diploma,5,91,93,3,14,9.0,6,55,Urban,Data Analyst,74749,1 +114055,Female,58,Diploma,19,86,84,1,80,5.0,2,44,Rural,Data Analyst,52536,0 +114056,Female,54,Bachelors,0,61,83,57,32,9.0,0,33,Semi-Urban,HR Executive,146218,0 +114057,Male,24,Bachelors,18,20,31,51,63,8.0,4,95,Urban,HR Executive,115595,0 +114058,Male,28,High School,11,38,91,43,28,7.0,5,49,Urban,Software Engineer,90882,0 +114059,Male,32,Masters,16,61,25,46,95,8.0,5,5,Urban,Manager,67731,0 +114060,Male,37,Masters,15,42,22,23,80,1.0,0,43,Semi-Urban,ML Engineer,89052,0 +114061,Female,52,Bachelors,13,70,97,37,60,7.0,3,92,Urban,Data Analyst,26534,1 +114062,Male,37,High School,8,90,50,67,49,0.0,1,99,Rural,Data Analyst,129671,1 +114063,Male,29,Bachelors,17,19,12,74,6,7.0,1,15,Rural,HR Executive,28452,0 +114064,Male,54,Bachelors,16,67,55,85,0,5.0,2,19,Semi-Urban,Software Engineer,83273,0 +114065,Female,58,Bachelors,19,53,18,46,99,6.0,0,32,Urban,ML Engineer,55227,0 +114066,Male,40,Masters,4,68,93,19,98,8.0,0,34,Urban,HR Executive,118003,0 +114067,Male,56,Masters,10,44,96,87,7,9.0,3,55,Rural,Data Analyst,79283,1 +114068,Other,26,Bachelors,5,32,39,6,18,6.0,5,11,Semi-Urban,Manager,45119,0 +114069,Male,39,Masters,12,0,56,28,23,5.0,6,29,Rural,Software Engineer,41303,0 +114070,Male,27,Bachelors,8,15,42,71,24,5.0,6,63,Urban,Manager,78306,0 +114071,Male,29,Masters,6,27,75,86,10,5.0,2,36,Urban,Data Analyst,47442,0 +114072,Male,42,High School,10,41,43,98,6,5.0,3,61,Urban,Manager,99216,1 +114073,Female,34,Diploma,12,23,72,14,6,5.0,3,78,Urban,ML Engineer,71701,0 +114074,Male,30,Bachelors,18,57,50,44,88,8.0,7,7,Urban,Software Engineer,67935,0 +114075,Male,34,Diploma,1,30,43,29,10,7.0,7,61,Urban,ML Engineer,108266,0 +114076,Male,32,Bachelors,6,86,51,9,27,2.0,6,31,Urban,HR Executive,77853,0 +114077,Female,50,Masters,6,21,2,77,17,6.0,4,56,Urban,Software Engineer,131345,0 +114078,Male,21,Diploma,10,9,66,40,68,3.0,5,34,Urban,Software Engineer,108363,0 +114079,Male,46,High School,2,97,5,59,84,8.0,3,59,Urban,HR Executive,69988,0 +114080,Female,42,Diploma,13,76,35,33,61,4.0,1,24,Semi-Urban,ML Engineer,37498,0 +114081,Male,27,Bachelors,16,93,12,83,93,4.0,6,2,Urban,Data Analyst,119801,0 +114082,Female,36,Masters,9,7,36,39,75,8.0,7,3,Urban,ML Engineer,90687,0 +114083,Male,31,Bachelors,8,77,58,11,57,8.0,7,2,Urban,Software Engineer,91793,0 +114084,Female,37,Masters,3,65,67,52,80,6.0,1,65,Urban,ML Engineer,50568,1 +114085,Other,27,PhD,16,31,45,5,71,0.0,5,33,Rural,ML Engineer,43233,0 +114086,Male,53,Bachelors,1,54,68,48,82,5.0,6,55,Rural,Manager,20285,0 +114087,Male,35,Bachelors,0,89,5,26,83,2.0,7,75,Semi-Urban,Manager,105542,0 +114088,Female,28,High School,17,52,56,20,79,3.0,1,64,Semi-Urban,HR Executive,33709,0 +114089,Male,25,High School,15,3,5,91,40,6.0,6,94,Semi-Urban,HR Executive,57730,0 +114090,Male,45,Bachelors,11,4,82,72,61,4.0,4,27,Semi-Urban,Software Engineer,124055,0 +114091,Male,56,Diploma,9,47,10,81,39,2.0,4,23,Urban,ML Engineer,20276,0 +114092,Male,56,Bachelors,13,62,96,8,53,0.0,6,93,Urban,HR Executive,57906,1 +114093,Male,59,Masters,12,45,62,78,2,4.0,5,4,Semi-Urban,HR Executive,80602,0 +114094,Male,39,High School,17,35,10,98,80,0.0,7,80,Semi-Urban,Software Engineer,20079,0 +114095,Male,40,Masters,9,53,38,21,39,4.0,6,76,Urban,Software Engineer,79805,0 +114096,Male,59,Bachelors,12,51,36,54,23,5.0,3,46,Rural,Data Analyst,120860,0 +114097,Male,49,Bachelors,14,64,99,43,93,0.0,4,41,Urban,Manager,71071,1 +114098,Male,35,Bachelors,9,8,3,1,15,3.0,1,45,Urban,Software Engineer,76065,0 +114099,Female,55,Masters,18,85,5,4,91,1.0,4,29,Urban,Data Analyst,49324,0 +114100,Male,48,High School,18,54,35,64,94,7.0,1,66,Urban,Manager,121904,0 +114101,Male,55,Bachelors,17,50,1,90,26,8.0,1,91,Urban,ML Engineer,96689,0 +114102,Male,57,PhD,17,27,61,74,0,8.0,4,91,Semi-Urban,Data Analyst,125997,1 +114103,Male,51,Bachelors,17,8,68,43,9,9.0,3,19,Rural,Software Engineer,79975,0 +114104,Male,53,Diploma,19,66,87,1,61,9.0,7,87,Urban,ML Engineer,79120,1 +114105,Male,32,Masters,14,39,55,64,33,6.0,4,71,Urban,ML Engineer,53019,0 +114106,Other,21,Masters,15,33,31,7,37,7.0,0,28,Urban,Manager,49733,0 +114107,Female,36,Bachelors,18,40,66,71,90,6.0,6,84,Rural,Data Analyst,91904,1 +114108,Male,25,Bachelors,6,83,74,35,72,6.0,5,36,Rural,HR Executive,106148,0 +114109,Male,44,Diploma,0,77,10,88,92,2.0,6,27,Semi-Urban,HR Executive,58926,0 +114110,Male,46,Bachelors,2,93,98,61,69,5.0,6,81,Urban,Data Analyst,61511,1 +114111,Male,45,Diploma,9,11,40,16,87,9.0,6,87,Semi-Urban,HR Executive,133000,0 +114112,Female,58,Masters,2,82,3,3,21,4.0,7,84,Urban,Manager,101194,0 +114113,Female,54,Diploma,13,84,9,91,24,2.0,0,27,Urban,Software Engineer,132640,0 +114114,Male,49,Bachelors,5,65,29,34,53,4.0,0,81,Semi-Urban,Data Analyst,52167,0 +114115,Male,49,Masters,9,59,2,36,38,2.0,2,16,Urban,Software Engineer,132011,0 +114116,Female,41,Diploma,10,10,70,90,38,2.0,7,35,Semi-Urban,HR Executive,52224,0 +114117,Male,44,PhD,11,13,46,66,51,6.0,6,43,Semi-Urban,Data Analyst,37981,0 +114118,Male,24,Bachelors,14,0,47,35,22,5.0,3,93,Urban,Manager,101331,0 +114119,Female,39,Masters,2,76,19,28,72,7.0,5,45,Urban,ML Engineer,107071,0 +114120,Male,38,Bachelors,7,26,90,66,44,3.0,5,5,Urban,Data Analyst,125010,0 +114121,Male,46,Bachelors,11,91,97,41,55,1.0,2,41,Semi-Urban,Manager,88677,1 +114122,Male,31,Bachelors,7,24,69,29,0,6.0,7,49,Semi-Urban,Software Engineer,40665,0 +114123,Female,52,Bachelors,6,38,71,97,95,1.0,6,10,Urban,HR Executive,49838,0 +114124,Female,59,High School,1,33,93,84,9,3.0,2,11,Urban,Software Engineer,128257,0 +114125,Male,30,Bachelors,9,96,10,25,64,3.0,5,71,Urban,Manager,137446,0 +114126,Male,44,Diploma,2,20,63,70,40,1.0,4,81,Urban,Data Analyst,112019,0 +114127,Other,50,Diploma,1,76,27,70,26,4.0,1,37,Urban,ML Engineer,123642,0 +114128,Female,27,Masters,7,13,47,73,86,2.0,2,46,Semi-Urban,Manager,103750,0 +114129,Male,49,Bachelors,12,8,47,66,47,1.0,0,83,Urban,Data Analyst,50790,0 +114130,Female,48,Bachelors,4,36,99,60,82,9.0,3,28,Urban,Software Engineer,121790,0 +114131,Male,36,Masters,5,20,56,82,75,3.0,3,51,Urban,ML Engineer,29522,0 +114132,Male,31,Diploma,15,71,15,10,69,7.0,1,95,Semi-Urban,Software Engineer,122567,0 +114133,Male,31,PhD,15,90,14,47,17,4.0,5,91,Urban,Software Engineer,82910,1 +114134,Male,43,Bachelors,6,92,72,96,99,4.0,2,47,Urban,ML Engineer,108612,1 +114135,Female,42,Bachelors,2,82,8,30,93,9.0,1,62,Urban,Software Engineer,69731,0 +114136,Male,57,Masters,5,31,74,85,5,5.0,1,68,Urban,HR Executive,33853,1 +114137,Male,32,Bachelors,17,66,18,3,75,6.0,2,65,Urban,Software Engineer,115464,0 +114138,Female,25,High School,1,49,63,9,7,7.0,7,95,Urban,Software Engineer,57894,0 +114139,Female,55,Diploma,15,74,30,13,31,0.0,4,9,Semi-Urban,Data Analyst,62552,0 +114140,Female,31,Diploma,2,15,38,21,14,5.0,2,70,Urban,Data Analyst,89834,0 +114141,Male,39,Diploma,2,60,56,86,47,6.0,1,83,Urban,ML Engineer,63072,1 +114142,Male,26,High School,10,33,30,45,83,5.0,3,94,Rural,Software Engineer,111955,0 +114143,Male,39,Bachelors,19,72,86,56,55,7.0,1,59,Urban,HR Executive,31389,1 +114144,Male,33,Bachelors,17,61,87,18,49,3.0,4,63,Semi-Urban,Software Engineer,43873,0 +114145,Male,23,PhD,12,71,55,58,87,3.0,5,68,Semi-Urban,Software Engineer,115421,1 +114146,Male,29,Bachelors,3,95,73,68,75,7.0,2,83,Semi-Urban,Manager,148903,1 +114147,Male,56,Diploma,2,75,44,33,10,4.0,0,63,Semi-Urban,Manager,146553,0 +114148,Male,26,High School,19,85,59,80,7,6.0,6,18,Rural,ML Engineer,138573,1 +114149,Female,43,Masters,2,39,23,98,30,9.0,6,20,Urban,ML Engineer,136846,0 +114150,Male,40,Masters,1,21,90,0,39,4.0,3,92,Urban,Data Analyst,69656,0 +114151,Male,50,Diploma,6,4,22,2,51,4.0,5,92,Semi-Urban,Data Analyst,138190,0 +114152,Male,25,High School,12,51,19,3,92,0.0,7,68,Urban,Data Analyst,128700,0 +114153,Male,22,Masters,12,75,54,4,13,0.0,4,9,Rural,ML Engineer,83411,0 +114154,Male,56,High School,8,85,56,22,6,8.0,2,25,Semi-Urban,Software Engineer,26773,0 +114155,Male,57,Bachelors,17,85,88,5,74,6.0,1,56,Urban,HR Executive,67907,0 +114156,Female,47,Bachelors,10,89,38,78,37,3.0,6,33,Urban,Software Engineer,71897,0 +114157,Male,25,Diploma,3,83,44,90,71,7.0,2,74,Urban,HR Executive,26595,1 +114158,Female,24,Bachelors,11,88,81,37,82,8.0,5,13,Urban,HR Executive,115045,0 +114159,Male,40,Bachelors,3,7,95,79,62,8.0,5,90,Urban,Software Engineer,136925,1 +114160,Male,40,Diploma,2,32,48,62,24,7.0,7,39,Urban,Data Analyst,140022,0 +114161,Male,55,PhD,7,65,28,98,20,4.0,0,32,Urban,Manager,95949,0 +114162,Male,37,High School,11,81,66,91,62,2.0,0,47,Semi-Urban,HR Executive,81456,1 +114163,Male,39,Masters,13,4,85,82,44,8.0,7,26,Rural,HR Executive,109806,0 +114164,Female,42,Diploma,14,68,30,90,89,6.0,2,35,Rural,Software Engineer,91291,0 +114165,Male,25,High School,6,17,41,48,17,7.0,4,76,Rural,Manager,55889,0 +114166,Male,33,Bachelors,4,0,87,51,72,7.0,0,8,Urban,Data Analyst,114569,0 +114167,Male,30,Bachelors,9,90,18,41,50,9.0,6,31,Semi-Urban,Manager,149390,0 +114168,Female,54,High School,11,90,17,33,9,0.0,5,79,Semi-Urban,ML Engineer,122208,0 +114169,Female,28,Bachelors,6,84,78,81,76,7.0,6,7,Urban,HR Executive,30988,1 +114170,Female,23,Masters,17,60,62,17,90,2.0,6,96,Urban,Software Engineer,124723,0 +114171,Male,29,Bachelors,0,4,30,87,89,0.0,5,18,Rural,Manager,75150,0 +114172,Male,32,Bachelors,6,37,57,12,27,2.0,6,20,Rural,Software Engineer,30986,0 +114173,Female,54,Bachelors,16,73,90,27,38,9.0,6,26,Urban,Software Engineer,73963,0 +114174,Other,29,High School,18,58,37,77,90,0.0,7,30,Rural,Manager,140277,0 +114175,Female,28,High School,2,92,3,40,73,3.0,4,10,Urban,ML Engineer,43721,0 +114176,Male,41,PhD,16,13,37,87,26,0.0,7,41,Urban,ML Engineer,113324,0 +114177,Male,48,Bachelors,17,53,13,34,97,8.0,2,23,Urban,Software Engineer,92922,0 +114178,Other,50,Diploma,16,70,40,33,14,6.0,0,16,Rural,Manager,136643,0 +114179,Male,21,Bachelors,12,2,33,14,58,4.0,2,82,Urban,Data Analyst,63565,0 +114180,Male,51,High School,12,53,92,17,47,6.0,0,78,Urban,Software Engineer,124855,1 +114181,Male,46,Masters,12,18,58,64,20,6.0,5,62,Urban,Software Engineer,49010,0 +114182,Male,41,Bachelors,13,57,32,42,7,8.0,0,95,Urban,Manager,25760,0 +114183,Male,48,Diploma,13,46,28,91,39,9.0,1,76,Rural,Manager,35457,1 +114184,Male,39,Diploma,10,80,5,20,42,4.0,0,46,Semi-Urban,Manager,86889,0 +114185,Male,52,Bachelors,17,78,45,92,45,2.0,6,57,Urban,ML Engineer,104879,1 +114186,Female,40,Bachelors,17,50,1,54,24,2.0,6,38,Urban,Software Engineer,72120,0 +114187,Female,56,Diploma,5,27,75,24,69,8.0,0,88,Rural,Manager,35308,0 +114188,Female,37,Diploma,10,62,81,85,27,8.0,3,85,Semi-Urban,HR Executive,101417,1 +114189,Female,37,Masters,15,64,8,37,71,0.0,5,20,Rural,HR Executive,76991,0 +114190,Male,32,Bachelors,16,2,63,84,74,5.0,2,36,Urban,Software Engineer,70915,0 +114191,Male,53,Masters,4,92,68,30,84,1.0,0,91,Semi-Urban,Manager,102213,1 +114192,Male,34,Bachelors,3,4,46,32,78,4.0,7,93,Urban,Manager,30951,0 +114193,Female,45,Masters,6,39,25,90,69,0.0,4,33,Rural,Software Engineer,28304,0 +114194,Female,39,Bachelors,8,2,42,70,54,4.0,6,8,Semi-Urban,ML Engineer,103714,0 +114195,Male,30,Masters,11,34,4,89,38,5.0,4,6,Rural,HR Executive,66097,0 +114196,Male,52,Bachelors,5,82,81,59,52,7.0,5,7,Rural,Data Analyst,97796,0 +114197,Male,39,Bachelors,8,46,10,6,51,2.0,5,46,Semi-Urban,Software Engineer,57536,0 +114198,Female,33,Masters,13,90,42,92,21,4.0,3,33,Urban,Manager,66383,1 +114199,Female,36,Masters,3,55,88,73,79,4.0,0,39,Urban,Software Engineer,111509,1 +114200,Female,47,Diploma,15,2,22,25,16,2.0,5,60,Urban,HR Executive,146253,0 +114201,Male,49,Masters,5,46,5,99,26,0.0,6,32,Urban,Data Analyst,104919,0 +114202,Female,50,Bachelors,1,76,18,7,8,0.0,7,92,Urban,Manager,113551,0 +114203,Female,22,Diploma,0,39,88,84,72,4.0,6,85,Semi-Urban,HR Executive,104636,1 +114204,Male,53,Bachelors,14,98,20,49,90,7.0,5,64,Semi-Urban,HR Executive,30490,0 +114205,Male,25,High School,2,51,57,93,17,4.0,4,27,Urban,Manager,27794,0 +114206,Male,39,Masters,5,40,5,26,29,4.0,4,47,Semi-Urban,ML Engineer,90777,0 +114207,Female,51,Bachelors,13,51,77,74,66,5.0,0,42,Urban,Data Analyst,138840,1 +114208,Male,58,Bachelors,7,9,85,90,47,5.0,2,49,Urban,Manager,108563,0 +114209,Male,21,High School,3,63,10,46,92,2.0,5,78,Urban,Software Engineer,42829,0 +114210,Male,25,High School,17,12,39,75,88,3.0,0,83,Urban,ML Engineer,111256,0 +114211,Male,32,Masters,11,66,86,2,74,8.0,7,3,Rural,ML Engineer,28899,0 +114212,Male,42,PhD,5,9,43,78,91,8.0,2,53,Semi-Urban,Data Analyst,50273,0 +114213,Male,39,Masters,3,4,56,8,36,9.0,1,34,Semi-Urban,HR Executive,119076,0 +114214,Female,58,Bachelors,6,10,35,26,23,2.0,7,76,Semi-Urban,HR Executive,23787,0 +114215,Female,37,Bachelors,13,20,95,99,46,0.0,7,89,Rural,Data Analyst,127571,1 +114216,Male,58,Bachelors,8,74,64,10,28,7.0,7,38,Urban,ML Engineer,83640,0 +114217,Female,34,Bachelors,15,79,85,71,95,8.0,2,80,Semi-Urban,Software Engineer,30724,1 +114218,Male,26,Diploma,18,59,89,93,77,8.0,3,92,Urban,HR Executive,34581,1 +114219,Female,53,Bachelors,3,41,51,22,52,0.0,1,77,Urban,Data Analyst,137505,0 +114220,Male,35,Bachelors,3,9,37,37,39,0.0,6,98,Urban,ML Engineer,32295,0 +114221,Male,23,Diploma,1,72,81,35,18,7.0,6,75,Semi-Urban,Software Engineer,107341,1 +114222,Female,42,Bachelors,3,19,8,96,73,4.0,6,17,Urban,Software Engineer,81735,0 +114223,Male,57,Bachelors,19,11,40,6,51,5.0,5,33,Urban,Software Engineer,46932,0 +114224,Male,45,Bachelors,19,94,7,60,32,4.0,0,52,Semi-Urban,Software Engineer,116866,0 +114225,Male,57,Masters,3,88,62,6,88,0.0,0,26,Urban,Data Analyst,121711,0 +114226,Female,39,Diploma,13,1,65,56,54,9.0,3,90,Semi-Urban,Manager,51920,0 +114227,Female,29,Diploma,10,88,38,46,99,8.0,1,10,Urban,ML Engineer,61402,0 +114228,Female,41,High School,4,76,73,78,24,6.0,5,1,Rural,HR Executive,104594,0 +114229,Female,27,Masters,14,42,64,19,66,9.0,6,1,Urban,Software Engineer,64682,0 +114230,Other,45,Bachelors,3,6,14,0,99,4.0,5,14,Urban,Software Engineer,104590,0 +114231,Male,54,Masters,11,94,70,1,49,4.0,3,26,Urban,Software Engineer,25264,0 +114232,Male,40,Diploma,6,14,49,98,0,7.0,4,48,Urban,Data Analyst,109855,0 +114233,Male,21,Diploma,3,33,7,35,5,7.0,3,55,Urban,Software Engineer,82477,0 +114234,Female,51,Bachelors,13,74,63,31,74,6.0,5,16,Urban,ML Engineer,146692,0 +114235,Male,48,High School,19,68,23,93,57,6.0,0,36,Semi-Urban,ML Engineer,76529,0 +114236,Male,35,Masters,10,76,55,3,60,2.0,2,32,Urban,ML Engineer,105747,0 +114237,Male,43,High School,9,81,83,75,60,7.0,1,34,Urban,ML Engineer,122825,1 +114238,Female,28,Bachelors,0,15,11,57,37,3.0,0,31,Rural,HR Executive,147762,0 +114239,Female,47,Masters,15,58,53,95,95,4.0,4,7,Semi-Urban,Data Analyst,24717,0 +114240,Male,40,Masters,16,86,26,52,91,7.0,3,57,Urban,ML Engineer,31736,0 +114241,Female,54,Bachelors,8,77,64,54,99,2.0,4,14,Urban,Data Analyst,142893,0 +114242,Female,58,Bachelors,16,51,80,84,81,0.0,2,16,Urban,Software Engineer,69053,0 +114243,Female,48,High School,10,79,41,37,82,2.0,1,82,Rural,Software Engineer,58519,0 +114244,Male,47,Diploma,19,27,87,51,25,8.0,1,81,Urban,HR Executive,77861,1 +114245,Male,47,Masters,11,72,22,64,20,1.0,5,8,Semi-Urban,HR Executive,53526,0 +114246,Male,44,Masters,3,77,31,47,24,8.0,4,21,Semi-Urban,Data Analyst,71332,0 +114247,Male,31,Bachelors,5,28,99,33,18,1.0,0,26,Urban,Data Analyst,115939,0 +114248,Female,54,PhD,5,91,96,99,62,9.0,0,84,Semi-Urban,Manager,79460,1 +114249,Male,59,PhD,6,7,87,60,12,3.0,7,76,Semi-Urban,HR Executive,67612,0 +114250,Female,47,Diploma,14,48,77,21,36,3.0,3,33,Urban,Manager,34897,0 +114251,Female,21,High School,3,41,64,35,33,4.0,6,66,Rural,Manager,55261,0 +114252,Male,58,Diploma,16,77,80,89,10,1.0,4,15,Urban,Data Analyst,132301,1 +114253,Male,22,Masters,15,24,74,71,97,0.0,0,67,Urban,Data Analyst,43341,1 +114254,Male,31,Bachelors,18,51,97,35,71,0.0,7,67,Urban,Software Engineer,112176,1 +114255,Male,24,High School,6,71,31,95,90,5.0,3,83,Rural,Manager,108190,1 +114256,Female,40,Bachelors,17,35,4,39,6,4.0,7,71,Urban,Data Analyst,145552,0 +114257,Female,25,High School,11,33,3,27,33,7.0,0,78,Rural,Data Analyst,55357,0 +114258,Female,28,PhD,13,54,62,27,0,5.0,5,94,Urban,Data Analyst,24800,0 +114259,Female,36,Bachelors,15,42,11,65,39,2.0,6,88,Semi-Urban,ML Engineer,44197,0 +114260,Female,22,Diploma,12,84,88,38,37,2.0,0,52,Urban,Manager,67344,1 +114261,Male,38,Bachelors,10,64,42,74,56,9.0,2,52,Urban,Software Engineer,33477,0 +114262,Male,47,Bachelors,4,15,20,30,41,4.0,0,63,Rural,HR Executive,129188,0 +114263,Male,30,Diploma,19,30,75,52,60,2.0,4,44,Semi-Urban,Manager,99450,0 +114264,Female,32,Bachelors,3,28,69,18,84,3.0,6,47,Rural,ML Engineer,140773,0 +114265,Female,51,Bachelors,11,74,36,90,5,9.0,3,35,Urban,HR Executive,124623,0 +114266,Female,22,Bachelors,6,51,8,86,63,9.0,5,48,Urban,Manager,22561,0 +114267,Other,44,Diploma,4,59,60,25,80,1.0,6,73,Urban,Manager,126442,0 +114268,Other,46,Bachelors,1,33,38,18,27,0.0,0,6,Rural,Data Analyst,117750,0 +114269,Female,26,Bachelors,17,21,35,75,26,2.0,0,15,Urban,ML Engineer,35112,0 +114270,Female,41,Bachelors,11,20,4,72,52,0.0,2,95,Semi-Urban,Data Analyst,39208,0 +114271,Male,27,Diploma,18,54,38,90,95,3.0,0,86,Urban,HR Executive,83955,1 +114272,Male,22,Bachelors,3,93,65,42,2,9.0,1,8,Urban,Manager,95173,0 +114273,Female,54,Diploma,13,50,35,17,77,9.0,3,21,Urban,HR Executive,87396,0 +114274,Female,22,Masters,5,20,95,91,89,5.0,2,8,Urban,HR Executive,126848,0 +114275,Other,49,Masters,0,21,73,87,59,7.0,1,52,Urban,Software Engineer,54798,0 +114276,Male,57,Masters,15,52,70,73,81,0.0,7,58,Rural,Data Analyst,102719,1 +114277,Female,31,Masters,0,27,85,14,59,5.0,5,88,Urban,ML Engineer,138567,0 +114278,Male,28,Bachelors,14,11,93,39,14,4.0,4,76,Semi-Urban,Data Analyst,52661,0 +114279,Male,24,Bachelors,12,53,58,19,84,9.0,0,77,Semi-Urban,Manager,109284,0 +114280,Male,21,Bachelors,12,34,60,25,41,7.0,6,83,Urban,HR Executive,42449,0 +114281,Male,41,High School,15,89,53,42,98,9.0,0,3,Urban,Data Analyst,149468,0 +114282,Female,57,Bachelors,17,58,3,12,11,6.0,2,50,Rural,ML Engineer,28514,0 +114283,Male,30,Bachelors,11,87,32,79,8,2.0,2,32,Semi-Urban,HR Executive,110031,0 +114284,Other,26,Bachelors,5,77,94,90,62,5.0,6,3,Urban,Manager,81348,1 +114285,Male,22,Masters,14,31,53,11,6,4.0,6,26,Semi-Urban,HR Executive,126616,0 +114286,Male,38,Diploma,2,37,70,66,95,1.0,6,65,Urban,ML Engineer,36916,1 +114287,Female,32,PhD,14,66,49,33,81,5.0,3,76,Rural,Software Engineer,30834,0 +114288,Female,50,Masters,16,13,55,42,69,6.0,1,39,Semi-Urban,Data Analyst,114443,0 +114289,Female,23,High School,5,6,49,78,22,3.0,7,27,Urban,Data Analyst,108896,0 +114290,Male,52,Masters,16,26,85,74,4,3.0,4,71,Semi-Urban,HR Executive,120379,1 +114291,Male,42,PhD,5,41,2,23,39,4.0,6,71,Urban,Manager,93610,0 +114292,Male,30,Masters,13,87,40,47,37,6.0,3,17,Semi-Urban,Software Engineer,129633,0 +114293,Female,55,Masters,12,73,88,26,62,9.0,1,62,Urban,Manager,131149,1 +114294,Male,49,Diploma,9,82,82,79,94,9.0,0,74,Urban,Manager,21291,1 +114295,Female,24,Diploma,16,77,98,48,32,7.0,3,4,Urban,Data Analyst,62486,0 +114296,Male,29,Bachelors,13,48,91,89,69,1.0,0,89,Rural,Manager,79961,1 +114297,Female,48,Diploma,17,97,39,54,37,6.0,0,96,Urban,Software Engineer,81577,1 +114298,Male,44,Masters,9,60,62,42,76,8.0,4,58,Urban,Software Engineer,86425,0 +114299,Female,37,High School,14,58,95,3,4,0.0,6,37,Urban,HR Executive,101904,0 +114300,Male,49,Masters,18,38,64,55,21,1.0,1,80,Urban,Data Analyst,55161,1 +114301,Male,28,PhD,6,20,81,21,10,1.0,0,36,Semi-Urban,Data Analyst,39558,0 +114302,Female,47,Bachelors,6,44,8,13,82,4.0,0,76,Urban,Manager,110560,0 +114303,Male,42,Masters,0,53,27,52,82,7.0,0,70,Urban,Data Analyst,82386,0 +114304,Male,27,PhD,7,76,80,27,36,9.0,0,50,Urban,Manager,88877,0 +114305,Female,45,Diploma,1,22,99,88,21,3.0,4,30,Urban,Software Engineer,95156,0 +114306,Female,51,Diploma,18,32,94,88,54,0.0,0,76,Rural,Manager,49064,1 +114307,Male,44,Bachelors,8,7,48,57,87,0.0,6,16,Urban,Software Engineer,116524,0 +114308,Female,29,Bachelors,19,62,83,19,14,1.0,0,83,Rural,Software Engineer,39878,1 +114309,Male,27,Bachelors,17,97,31,47,45,4.0,1,28,Urban,Manager,74977,0 +114310,Female,28,Bachelors,15,33,4,35,75,4.0,2,65,Urban,Manager,86939,0 +114311,Male,26,Masters,0,68,75,1,68,2.0,3,36,Rural,HR Executive,128473,0 +114312,Male,26,High School,1,7,78,58,1,8.0,5,97,Urban,ML Engineer,120589,1 +114313,Male,24,Bachelors,6,90,31,50,8,0.0,4,19,Urban,ML Engineer,94431,0 +114314,Male,24,Diploma,6,25,7,11,46,7.0,5,87,Urban,HR Executive,24498,0 +114315,Male,44,Masters,3,10,80,27,34,3.0,4,68,Urban,Manager,106982,0 +114316,Male,57,Bachelors,18,56,83,55,10,6.0,0,63,Urban,ML Engineer,71930,1 +114317,Male,21,Bachelors,4,45,80,51,84,4.0,6,47,Urban,ML Engineer,29368,0 +114318,Female,45,Diploma,18,11,89,57,55,3.0,6,92,Urban,Manager,100672,1 +114319,Female,45,Diploma,0,93,36,86,21,3.0,2,39,Rural,Software Engineer,56299,1 +114320,Male,40,Bachelors,5,49,75,58,70,0.0,1,51,Semi-Urban,HR Executive,100374,0 +114321,Other,56,Diploma,14,2,88,16,55,2.0,6,88,Urban,Data Analyst,99249,0 +114322,Female,28,Bachelors,4,58,95,74,82,3.0,0,71,Urban,Software Engineer,70978,1 +114323,Female,39,Diploma,1,44,2,3,47,0.0,5,79,Urban,ML Engineer,103413,0 +114324,Male,58,Masters,19,52,18,29,83,2.0,0,28,Urban,HR Executive,70058,0 +114325,Female,44,Bachelors,11,86,53,91,58,2.0,1,15,Urban,Data Analyst,55312,1 +114326,Female,41,High School,3,70,5,60,27,0.0,2,12,Urban,Data Analyst,137706,0 +114327,Male,55,Bachelors,9,27,81,36,42,1.0,5,40,Urban,Data Analyst,146033,0 +114328,Female,48,Masters,0,4,87,31,0,0.0,6,92,Rural,Data Analyst,71674,0 +114329,Female,36,Bachelors,10,33,47,96,86,0.0,5,75,Urban,Data Analyst,131415,1 +114330,Female,34,Bachelors,17,48,99,37,79,4.0,7,39,Urban,Data Analyst,141200,0 +114331,Other,46,Bachelors,16,61,93,56,57,8.0,3,91,Urban,Manager,33725,1 +114332,Female,29,Diploma,12,27,17,31,8,8.0,3,90,Semi-Urban,Data Analyst,104533,0 +114333,Male,47,Diploma,4,87,25,3,18,3.0,7,48,Semi-Urban,ML Engineer,129569,0 +114334,Female,55,Bachelors,16,41,70,85,34,2.0,0,65,Rural,Manager,84962,1 +114335,Male,27,High School,4,1,67,40,26,0.0,5,56,Semi-Urban,HR Executive,31105,0 +114336,Male,40,Masters,13,90,40,76,33,0.0,3,50,Urban,Manager,103858,1 +114337,Male,40,Masters,13,35,18,58,88,3.0,4,45,Rural,Software Engineer,105641,0 +114338,Male,40,Bachelors,2,35,69,90,92,9.0,4,60,Urban,Data Analyst,82526,1 +114339,Male,22,Diploma,11,34,97,59,64,5.0,1,56,Semi-Urban,HR Executive,61978,1 +114340,Male,40,High School,4,74,71,99,11,1.0,4,98,Rural,Data Analyst,94781,1 +114341,Male,50,Masters,19,26,99,96,97,0.0,2,64,Rural,HR Executive,87542,1 +114342,Male,35,Bachelors,16,34,72,99,8,6.0,7,47,Urban,Software Engineer,85753,1 +114343,Male,22,Bachelors,1,23,91,85,72,1.0,4,74,Urban,Data Analyst,92566,1 +114344,Male,40,High School,5,82,11,19,53,8.0,1,80,Semi-Urban,ML Engineer,45716,0 +114345,Male,47,Bachelors,4,45,92,37,21,3.0,6,36,Semi-Urban,HR Executive,121636,0 +114346,Female,23,Bachelors,3,9,62,45,36,6.0,3,82,Semi-Urban,Data Analyst,86321,0 +114347,Female,56,Masters,8,8,25,83,45,4.0,3,81,Semi-Urban,Manager,70108,0 +114348,Male,28,Diploma,1,75,39,8,92,9.0,0,43,Urban,ML Engineer,101310,0 +114349,Male,35,Masters,15,84,62,9,49,2.0,6,28,Urban,Data Analyst,29957,0 +114350,Male,44,Bachelors,19,90,17,92,57,4.0,4,46,Semi-Urban,Software Engineer,72399,1 +114351,Other,26,Bachelors,17,73,20,23,83,4.0,3,75,Urban,Manager,66029,0 +114352,Female,44,Bachelors,8,18,85,61,5,7.0,7,53,Urban,Data Analyst,109178,0 +114353,Male,23,PhD,3,22,28,23,60,9.0,1,73,Urban,Manager,78172,0 +114354,Female,54,Masters,16,33,32,10,11,6.0,1,50,Semi-Urban,Data Analyst,30435,0 +114355,Male,47,High School,7,36,49,93,55,9.0,2,81,Rural,HR Executive,67220,1 +114356,Male,26,High School,6,56,53,98,31,5.0,0,36,Urban,ML Engineer,115841,1 +114357,Female,53,Bachelors,15,41,76,97,90,7.0,4,67,Urban,Manager,32433,1 +114358,Male,21,Diploma,13,74,38,34,25,3.0,3,74,Semi-Urban,Manager,37862,0 +114359,Female,35,Bachelors,11,38,45,24,27,7.0,5,70,Urban,Manager,81460,0 +114360,Male,57,Bachelors,17,1,58,68,24,6.0,0,91,Semi-Urban,Manager,128400,0 +114361,Other,56,Bachelors,10,2,83,95,3,7.0,1,29,Semi-Urban,ML Engineer,55660,0 +114362,Female,29,High School,19,92,12,24,15,7.0,5,45,Semi-Urban,HR Executive,99658,0 +114363,Male,56,Diploma,17,51,38,63,92,2.0,5,94,Urban,Data Analyst,72585,1 +114364,Female,47,Masters,19,90,39,67,23,5.0,3,41,Rural,Data Analyst,87383,0 +114365,Male,35,Bachelors,8,54,69,78,4,3.0,7,21,Urban,Manager,114953,0 +114366,Male,52,Bachelors,0,78,15,49,99,8.0,7,25,Urban,Software Engineer,28450,0 +114367,Male,56,Diploma,15,46,69,10,34,1.0,1,52,Semi-Urban,HR Executive,93100,0 +114368,Female,29,High School,19,75,6,66,13,7.0,3,47,Semi-Urban,Software Engineer,128618,0 +114369,Male,39,Masters,1,36,74,12,66,6.0,7,15,Rural,Data Analyst,32601,0 +114370,Male,44,Masters,5,9,83,76,73,3.0,5,14,Semi-Urban,Software Engineer,92188,0 +114371,Female,58,Masters,11,66,80,55,64,1.0,0,4,Urban,Software Engineer,40552,0 +114372,Female,57,Bachelors,2,26,13,1,47,3.0,1,7,Rural,Data Analyst,66501,0 +114373,Male,46,High School,11,32,4,23,82,4.0,5,56,Semi-Urban,Manager,71400,0 +114374,Female,35,PhD,6,72,28,46,86,5.0,3,31,Semi-Urban,ML Engineer,98372,0 +114375,Male,35,Masters,4,48,66,40,91,0.0,3,18,Urban,Software Engineer,64522,0 +114376,Male,24,Bachelors,0,22,12,42,48,5.0,6,0,Urban,ML Engineer,94826,0 +114377,Male,35,Masters,14,90,34,60,62,2.0,5,9,Urban,Data Analyst,116911,0 +114378,Male,37,Diploma,16,33,63,58,93,9.0,5,56,Rural,Data Analyst,117965,0 +114379,Male,36,PhD,10,4,92,95,89,5.0,0,60,Semi-Urban,Software Engineer,72044,1 +114380,Male,58,Bachelors,12,48,57,96,3,5.0,0,93,Rural,ML Engineer,136349,1 +114381,Male,54,Masters,4,78,25,31,49,6.0,2,77,Urban,Software Engineer,46756,0 +114382,Male,55,Diploma,12,27,9,60,9,8.0,0,25,Rural,HR Executive,41216,0 +114383,Male,46,High School,18,79,47,93,25,4.0,2,30,Urban,ML Engineer,144151,1 +114384,Male,37,Bachelors,4,20,63,11,69,5.0,5,58,Urban,Data Analyst,37250,0 +114385,Male,24,Bachelors,11,55,77,74,61,1.0,2,79,Semi-Urban,HR Executive,52147,1 +114386,Male,41,Masters,9,95,25,56,31,2.0,1,72,Urban,Software Engineer,43442,1 +114387,Male,42,Bachelors,0,81,88,89,27,8.0,6,51,Semi-Urban,Manager,136296,1 +114388,Female,37,Diploma,7,16,22,75,61,2.0,5,88,Semi-Urban,Manager,24385,0 +114389,Other,33,Masters,4,50,46,99,97,8.0,0,51,Urban,Software Engineer,115571,1 +114390,Female,32,High School,4,11,30,2,65,2.0,3,53,Urban,HR Executive,31638,0 +114391,Female,22,High School,3,56,0,64,25,7.0,7,1,Rural,Manager,67507,0 +114392,Male,27,Bachelors,7,9,88,67,89,4.0,0,15,Semi-Urban,HR Executive,40830,0 +114393,Male,26,Masters,8,19,82,96,24,4.0,2,8,Urban,ML Engineer,50063,0 +114394,Male,57,Masters,9,23,98,5,20,3.0,1,10,Rural,Manager,66861,0 +114395,Male,46,Masters,1,57,21,37,91,5.0,2,84,Urban,Manager,87031,0 +114396,Male,58,Bachelors,4,39,97,45,46,2.0,7,80,Urban,ML Engineer,123212,1 +114397,Female,32,Bachelors,4,60,17,84,14,7.0,2,76,Urban,Software Engineer,57728,0 +114398,Male,23,Diploma,3,41,14,2,1,2.0,4,73,Urban,Manager,64829,0 +114399,Male,39,Masters,10,38,22,27,92,5.0,4,48,Semi-Urban,Manager,76051,0 +114400,Male,30,Masters,13,4,21,89,38,3.0,2,97,Semi-Urban,ML Engineer,92947,0 +114401,Male,57,Bachelors,3,79,79,49,27,5.0,2,43,Semi-Urban,Data Analyst,51847,1 +114402,Female,39,Bachelors,5,23,71,73,79,0.0,3,53,Urban,Manager,138941,0 +114403,Other,54,PhD,4,86,35,10,92,8.0,1,37,Urban,HR Executive,114669,0 +114404,Female,45,High School,2,0,0,53,98,6.0,6,86,Rural,HR Executive,37033,0 +114405,Female,36,Masters,11,23,78,8,7,6.0,2,66,Urban,Manager,71435,0 +114406,Male,43,Diploma,18,52,46,28,28,2.0,2,88,Rural,Manager,37224,0 +114407,Male,21,Bachelors,7,47,79,31,62,8.0,0,98,Urban,Manager,62333,1 +114408,Male,27,Bachelors,18,71,43,86,86,8.0,3,98,Urban,Data Analyst,101996,1 +114409,Male,56,Masters,18,72,24,27,46,9.0,2,47,Urban,Manager,81089,0 +114410,Female,56,Masters,8,30,77,73,71,9.0,7,41,Urban,Software Engineer,105765,0 +114411,Male,35,Bachelors,4,65,76,63,65,3.0,4,24,Semi-Urban,HR Executive,40388,0 +114412,Female,39,High School,16,64,20,67,70,5.0,7,99,Rural,Manager,62452,1 +114413,Male,43,Masters,12,16,64,83,47,0.0,1,57,Rural,Data Analyst,89939,0 +114414,Other,30,Bachelors,13,26,57,13,98,5.0,0,81,Semi-Urban,ML Engineer,46224,0 +114415,Female,49,Diploma,6,55,80,28,23,9.0,0,3,Urban,Manager,100895,0 +114416,Other,35,High School,1,39,24,24,69,5.0,4,24,Urban,Software Engineer,138799,0 +114417,Male,22,Diploma,11,34,68,48,50,2.0,3,26,Urban,Manager,35856,0 +114418,Male,42,Bachelors,9,62,69,42,37,8.0,3,9,Urban,Data Analyst,73671,0 +114419,Male,24,Diploma,9,48,90,15,86,4.0,7,29,Rural,Software Engineer,48951,0 +114420,Male,22,Bachelors,15,70,87,26,57,6.0,0,89,Urban,Manager,83902,1 +114421,Male,42,Masters,11,91,14,34,50,0.0,1,9,Semi-Urban,ML Engineer,138854,0 +114422,Female,31,Bachelors,0,35,14,58,70,3.0,2,71,Semi-Urban,ML Engineer,55897,0 +114423,Female,44,Diploma,18,62,39,8,1,1.0,3,75,Urban,Data Analyst,99935,0 +114424,Male,54,Bachelors,0,66,4,42,32,2.0,3,41,Urban,HR Executive,32387,0 +114425,Male,51,Bachelors,9,55,30,79,94,4.0,5,49,Urban,HR Executive,81286,0 +114426,Male,41,PhD,6,3,48,50,71,8.0,3,88,Urban,Manager,118090,0 +114427,Male,39,Masters,14,30,53,41,78,7.0,0,59,Urban,HR Executive,79632,0 +114428,Female,35,Bachelors,19,43,68,45,58,2.0,2,82,Semi-Urban,Data Analyst,137594,0 +114429,Male,59,Bachelors,16,72,82,28,35,7.0,1,15,Semi-Urban,ML Engineer,33804,0 +114430,Other,55,High School,18,58,37,61,23,5.0,7,57,Urban,HR Executive,133274,0 +114431,Male,51,Masters,18,25,81,89,63,5.0,2,0,Rural,ML Engineer,88097,0 +114432,Male,45,Bachelors,16,30,94,78,58,7.0,7,86,Urban,ML Engineer,94914,1 +114433,Male,35,Diploma,3,80,86,4,72,6.0,4,46,Semi-Urban,Manager,74310,0 +114434,Female,38,Diploma,8,39,5,46,76,2.0,7,75,Semi-Urban,HR Executive,148168,0 +114435,Male,41,Bachelors,6,75,63,11,56,0.0,1,90,Urban,Manager,133234,1 +114436,Male,42,Diploma,2,8,16,3,68,6.0,0,55,Semi-Urban,ML Engineer,93809,0 +114437,Male,31,High School,1,4,96,26,50,3.0,5,58,Semi-Urban,Data Analyst,102511,0 +114438,Male,34,Bachelors,3,28,75,27,91,6.0,7,23,Urban,HR Executive,123970,0 +114439,Female,33,Bachelors,1,19,64,17,75,5.0,2,80,Rural,Software Engineer,147746,0 +114440,Male,33,Bachelors,6,14,49,55,48,8.0,6,47,Rural,Software Engineer,78532,0 +114441,Male,28,Bachelors,2,68,60,49,6,3.0,1,28,Rural,Manager,36441,0 +114442,Male,40,Masters,10,70,5,27,8,3.0,1,86,Urban,Software Engineer,144777,0 +114443,Male,52,Diploma,2,16,69,72,55,6.0,3,52,Urban,HR Executive,78344,0 +114444,Other,22,PhD,10,14,20,32,88,7.0,0,62,Urban,Software Engineer,47147,0 +114445,Other,41,High School,2,90,97,91,27,6.0,5,92,Urban,Manager,116321,1 +114446,Other,30,Bachelors,3,81,49,65,84,9.0,5,95,Rural,Data Analyst,126673,1 +114447,Male,53,Bachelors,3,47,66,58,76,1.0,2,17,Urban,HR Executive,120527,0 +114448,Female,54,Masters,12,84,22,45,54,1.0,6,75,Semi-Urban,ML Engineer,139844,0 +114449,Female,33,Bachelors,4,63,37,90,24,2.0,2,87,Semi-Urban,HR Executive,59634,1 +114450,Male,48,Bachelors,14,24,48,83,84,3.0,0,39,Semi-Urban,ML Engineer,66839,0 +114451,Male,49,Bachelors,8,2,87,62,45,3.0,7,23,Semi-Urban,Manager,78600,0 +114452,Female,52,Bachelors,11,96,77,87,46,7.0,1,59,Urban,Data Analyst,110305,1 +114453,Male,51,Diploma,3,62,26,11,57,9.0,5,93,Urban,Manager,104177,0 +114454,Male,41,Diploma,10,95,50,47,84,3.0,0,26,Urban,ML Engineer,30411,0 +114455,Male,42,Bachelors,12,42,12,85,27,4.0,6,41,Rural,HR Executive,47059,0 +114456,Female,43,Masters,2,1,74,10,72,7.0,5,39,Urban,HR Executive,134409,0 +114457,Female,21,Masters,12,99,63,37,55,4.0,5,78,Urban,HR Executive,33728,1 +114458,Male,32,Bachelors,0,25,32,60,96,6.0,6,58,Urban,HR Executive,89251,0 +114459,Male,44,Diploma,10,97,47,12,25,9.0,3,81,Urban,ML Engineer,109004,1 +114460,Female,46,High School,4,31,58,98,36,8.0,1,99,Urban,ML Engineer,39377,1 +114461,Male,21,Bachelors,4,56,34,91,98,8.0,5,89,Urban,ML Engineer,48316,1 +114462,Male,38,Bachelors,12,2,62,94,57,6.0,4,63,Urban,Manager,80517,0 +114463,Other,50,Bachelors,14,17,33,91,38,4.0,7,58,Urban,Manager,45384,0 +114464,Male,22,Diploma,8,20,35,46,96,5.0,4,50,Urban,ML Engineer,40073,0 +114465,Female,54,Bachelors,4,20,17,60,54,3.0,6,4,Urban,Manager,103122,0 +114466,Male,54,Bachelors,6,69,30,6,39,1.0,0,65,Urban,ML Engineer,90272,0 +114467,Male,40,Diploma,0,93,47,63,60,6.0,1,88,Urban,HR Executive,49545,1 +114468,Male,47,Masters,14,16,33,15,71,2.0,7,30,Urban,Data Analyst,93164,0 +114469,Male,42,Bachelors,19,99,48,39,5,1.0,5,16,Urban,ML Engineer,86416,0 +114470,Female,23,Masters,12,32,12,91,70,5.0,0,91,Urban,HR Executive,68601,0 +114471,Male,53,PhD,6,84,39,72,95,3.0,6,35,Urban,HR Executive,128430,0 +114472,Male,47,High School,12,41,8,56,96,0.0,2,17,Urban,Software Engineer,111136,0 +114473,Male,26,Diploma,8,23,56,28,25,6.0,0,39,Urban,ML Engineer,48673,0 +114474,Other,27,Masters,3,47,10,34,76,9.0,2,80,Rural,Manager,143248,0 +114475,Other,47,Bachelors,11,88,18,90,12,7.0,2,35,Semi-Urban,Software Engineer,25706,0 +114476,Female,37,Diploma,12,69,58,49,94,3.0,6,3,Semi-Urban,Data Analyst,62592,0 +114477,Female,53,Masters,12,53,59,42,21,2.0,6,5,Urban,ML Engineer,55326,0 +114478,Male,30,High School,1,31,41,68,23,3.0,4,63,Rural,Software Engineer,116283,0 +114479,Male,53,Diploma,10,96,18,93,70,9.0,1,96,Rural,Software Engineer,84214,1 +114480,Female,24,High School,15,68,51,28,88,1.0,6,89,Urban,Software Engineer,144593,0 +114481,Male,21,Bachelors,2,86,74,41,31,8.0,0,50,Urban,ML Engineer,21711,1 +114482,Male,40,High School,12,2,70,12,70,3.0,0,8,Semi-Urban,ML Engineer,93763,0 +114483,Male,30,Masters,5,36,25,29,59,8.0,6,64,Urban,Data Analyst,130750,0 +114484,Female,34,Bachelors,18,20,99,85,76,9.0,7,11,Urban,Manager,103653,0 +114485,Male,22,Bachelors,18,75,72,58,37,4.0,5,94,Urban,Software Engineer,79056,1 +114486,Male,25,Masters,15,57,1,6,9,8.0,1,2,Rural,ML Engineer,132101,0 +114487,Male,53,Diploma,3,91,40,93,8,7.0,6,51,Urban,Manager,145494,1 +114488,Female,55,High School,6,88,77,36,42,6.0,2,60,Urban,Data Analyst,95859,1 +114489,Female,54,Diploma,18,30,2,69,85,0.0,0,11,Rural,ML Engineer,26372,0 +114490,Male,22,High School,5,81,36,14,55,9.0,5,26,Semi-Urban,Software Engineer,103700,0 +114491,Female,42,High School,15,60,19,85,3,5.0,5,81,Urban,Software Engineer,148961,1 +114492,Male,47,Bachelors,17,94,90,63,16,9.0,2,38,Semi-Urban,ML Engineer,54312,1 +114493,Male,51,Bachelors,5,2,52,37,2,2.0,1,45,Rural,Software Engineer,52220,0 +114494,Male,23,Bachelors,0,81,24,76,2,2.0,5,93,Urban,ML Engineer,68407,1 +114495,Male,56,Bachelors,8,83,86,84,32,9.0,0,97,Semi-Urban,Data Analyst,48011,1 +114496,Male,53,PhD,11,37,42,82,19,2.0,1,26,Semi-Urban,Data Analyst,70246,0 +114497,Male,25,Diploma,13,96,5,59,67,0.0,2,78,Urban,Manager,41893,1 +114498,Female,57,Bachelors,17,0,88,41,26,5.0,3,69,Rural,Manager,55264,0 +114499,Male,56,Bachelors,0,30,47,9,71,3.0,7,65,Semi-Urban,Manager,48401,0 +114500,Female,42,Masters,0,97,37,56,0,1.0,7,10,Urban,HR Executive,48014,0 +114501,Female,58,Bachelors,9,78,20,88,5,1.0,6,20,Rural,Data Analyst,67491,0 +114502,Male,28,Diploma,11,58,27,91,49,8.0,3,39,Urban,HR Executive,124692,0 +114503,Male,37,Bachelors,7,98,46,26,44,5.0,7,20,Urban,HR Executive,39673,0 +114504,Male,34,High School,7,2,15,41,3,1.0,7,78,Semi-Urban,Data Analyst,88168,0 +114505,Female,45,PhD,1,9,69,25,98,5.0,3,88,Urban,Software Engineer,126273,0 +114506,Female,30,Diploma,8,97,1,84,50,8.0,3,35,Semi-Urban,Manager,134750,0 +114507,Male,21,Diploma,7,92,19,90,4,4.0,1,38,Urban,Data Analyst,99202,1 +114508,Male,30,Bachelors,2,29,87,3,38,5.0,4,20,Urban,ML Engineer,148809,0 +114509,Female,43,Bachelors,3,76,36,70,2,6.0,1,7,Semi-Urban,ML Engineer,144437,0 +114510,Male,30,Bachelors,9,29,63,4,41,8.0,5,91,Semi-Urban,ML Engineer,146644,0 +114511,Male,23,Diploma,5,80,42,8,70,6.0,1,34,Urban,Manager,28827,0 +114512,Male,50,Bachelors,17,37,39,41,51,4.0,5,9,Urban,HR Executive,89450,0 +114513,Male,56,Bachelors,13,40,78,62,25,8.0,5,84,Urban,Software Engineer,120736,1 +114514,Other,36,PhD,13,12,5,27,5,1.0,2,78,Semi-Urban,HR Executive,131344,0 +114515,Male,59,High School,3,66,28,10,97,7.0,0,22,Rural,Manager,34033,0 +114516,Female,44,High School,14,75,6,6,83,6.0,6,9,Urban,HR Executive,126695,0 +114517,Female,55,High School,11,57,84,92,24,0.0,1,1,Urban,ML Engineer,89985,0 +114518,Female,38,Diploma,17,13,57,61,22,1.0,0,53,Urban,ML Engineer,112846,0 +114519,Female,55,Bachelors,18,72,99,12,90,3.0,1,68,Rural,HR Executive,98374,1 +114520,Female,36,Bachelors,10,12,83,58,68,6.0,4,84,Urban,ML Engineer,29138,0 +114521,Male,54,Diploma,18,26,84,78,10,8.0,3,81,Urban,Software Engineer,106321,1 +114522,Female,25,Bachelors,3,23,11,22,51,3.0,3,70,Urban,Software Engineer,38355,0 +114523,Other,33,Diploma,17,49,5,63,21,9.0,4,84,Urban,HR Executive,129094,0 +114524,Male,47,Bachelors,10,74,16,37,93,5.0,6,55,Rural,Data Analyst,102427,0 +114525,Male,45,Bachelors,5,77,69,51,68,1.0,4,44,Semi-Urban,Manager,73418,1 +114526,Male,53,Masters,2,67,17,26,2,9.0,3,39,Urban,HR Executive,139317,0 +114527,Female,42,Diploma,6,56,85,89,67,3.0,4,81,Rural,Manager,101877,1 +114528,Male,35,Bachelors,19,16,66,89,6,6.0,7,45,Semi-Urban,ML Engineer,119751,0 +114529,Male,40,Bachelors,10,77,23,4,94,8.0,1,67,Urban,ML Engineer,71467,0 +114530,Female,27,Diploma,5,85,63,55,27,9.0,6,65,Rural,Manager,65328,1 +114531,Male,51,Diploma,6,75,94,78,38,4.0,2,97,Semi-Urban,Software Engineer,61689,1 +114532,Female,55,Masters,12,17,19,79,15,9.0,6,34,Urban,HR Executive,94448,0 +114533,Other,42,Masters,12,80,65,14,37,7.0,4,64,Semi-Urban,Manager,47664,0 +114534,Male,47,Masters,9,97,25,92,26,7.0,4,65,Urban,ML Engineer,118138,1 +114535,Female,34,PhD,19,45,38,89,88,1.0,4,42,Urban,HR Executive,92921,0 +114536,Female,40,High School,15,92,26,92,61,4.0,0,79,Semi-Urban,Data Analyst,98976,1 +114537,Male,37,Masters,14,90,6,82,0,7.0,4,79,Urban,Software Engineer,115240,1 +114538,Male,54,Masters,17,39,20,55,36,3.0,1,66,Urban,ML Engineer,70454,0 +114539,Female,55,PhD,17,63,81,70,92,3.0,6,84,Urban,HR Executive,127190,1 +114540,Male,59,Diploma,18,27,5,74,52,7.0,6,65,Urban,ML Engineer,91060,0 +114541,Male,46,Bachelors,7,83,70,23,5,0.0,3,87,Urban,Data Analyst,132926,1 +114542,Other,49,Bachelors,2,5,11,75,62,6.0,2,79,Rural,Data Analyst,77466,0 +114543,Male,37,Bachelors,11,7,9,89,84,4.0,7,76,Semi-Urban,Manager,114989,0 +114544,Male,55,Masters,19,66,27,33,58,6.0,1,5,Urban,ML Engineer,60552,0 +114545,Female,34,Bachelors,6,40,4,92,56,8.0,6,82,Semi-Urban,Manager,72547,0 +114546,Male,23,Bachelors,5,36,31,0,63,4.0,3,78,Rural,Software Engineer,95389,0 +114547,Male,49,High School,13,3,82,14,35,2.0,4,27,Urban,Software Engineer,142682,0 +114548,Male,35,Diploma,13,19,19,10,96,8.0,1,48,Rural,ML Engineer,115073,0 +114549,Male,42,Bachelors,13,8,93,94,4,1.0,5,25,Urban,Software Engineer,107097,0 +114550,Male,21,PhD,9,44,25,8,82,8.0,7,57,Rural,Data Analyst,33120,0 +114551,Female,30,Masters,12,18,47,40,36,2.0,0,71,Semi-Urban,HR Executive,143028,0 +114552,Male,33,Diploma,13,20,96,1,21,7.0,7,57,Rural,HR Executive,93436,0 +114553,Male,59,Diploma,16,26,66,98,85,7.0,2,12,Urban,ML Engineer,131459,0 +114554,Male,41,PhD,13,74,77,39,2,9.0,3,51,Urban,HR Executive,136184,1 +114555,Male,56,PhD,1,44,23,54,30,5.0,7,77,Rural,Data Analyst,99564,0 +114556,Other,34,Diploma,17,29,91,26,28,6.0,7,30,Urban,Software Engineer,128053,0 +114557,Female,51,High School,12,90,82,71,54,1.0,5,76,Urban,ML Engineer,119243,1 +114558,Male,57,Masters,16,9,1,33,22,9.0,1,39,Semi-Urban,HR Executive,53200,0 +114559,Male,40,High School,9,32,29,77,58,7.0,3,82,Semi-Urban,Data Analyst,101075,0 +114560,Male,27,Diploma,9,43,2,89,79,4.0,5,74,Urban,Manager,141056,0 +114561,Male,36,Diploma,1,68,67,97,56,4.0,2,68,Urban,ML Engineer,33446,1 +114562,Male,45,Bachelors,17,9,78,11,23,5.0,6,99,Urban,Data Analyst,90453,0 +114563,Female,31,Bachelors,2,68,6,68,53,3.0,5,24,Urban,ML Engineer,124611,0 +114564,Female,21,High School,3,29,97,31,75,0.0,2,85,Semi-Urban,HR Executive,68609,1 +114565,Female,22,Bachelors,2,53,2,49,88,7.0,2,39,Semi-Urban,HR Executive,81793,0 +114566,Male,55,Diploma,16,71,54,10,26,7.0,4,34,Semi-Urban,HR Executive,140155,0 +114567,Male,55,Bachelors,0,86,54,18,71,5.0,3,34,Urban,HR Executive,111174,0 +114568,Male,56,Bachelors,13,29,52,96,61,0.0,4,0,Urban,HR Executive,131087,0 +114569,Female,58,Bachelors,18,42,40,65,78,4.0,0,69,Urban,HR Executive,142758,0 +114570,Male,59,Diploma,2,44,29,40,19,3.0,7,66,Urban,Software Engineer,126419,0 +114571,Other,22,Bachelors,18,68,63,57,74,9.0,5,76,Urban,Manager,99300,1 +114572,Male,23,PhD,12,4,11,90,68,8.0,7,7,Semi-Urban,HR Executive,134452,0 +114573,Male,34,Masters,7,68,24,22,18,8.0,5,67,Semi-Urban,Data Analyst,22740,0 +114574,Female,26,Bachelors,1,27,7,8,70,3.0,3,87,Urban,Manager,20936,0 +114575,Male,26,High School,12,58,34,9,33,6.0,0,14,Rural,Manager,111381,0 +114576,Male,31,Bachelors,3,89,40,63,64,8.0,5,12,Urban,HR Executive,138319,0 +114577,Female,49,Diploma,11,31,74,24,74,8.0,7,50,Urban,ML Engineer,129014,0 +114578,Female,42,High School,19,8,79,61,12,2.0,7,9,Urban,Software Engineer,92599,0 +114579,Male,58,Bachelors,2,10,63,93,72,0.0,1,51,Urban,Manager,117742,0 +114580,Female,44,Bachelors,5,35,40,56,92,9.0,2,97,Rural,HR Executive,125225,0 +114581,Male,21,Masters,12,91,94,87,87,5.0,1,71,Semi-Urban,Software Engineer,82636,1 +114582,Male,42,Masters,5,39,21,66,43,6.0,2,96,Rural,Data Analyst,71677,0 +114583,Male,34,Diploma,3,83,46,8,10,3.0,4,64,Rural,Manager,73034,0 +114584,Female,36,Masters,8,18,53,30,84,6.0,1,29,Rural,HR Executive,135973,0 +114585,Female,25,Diploma,11,80,94,5,64,9.0,4,25,Urban,Software Engineer,23438,0 +114586,Male,49,Diploma,10,51,63,34,86,1.0,3,43,Urban,Software Engineer,77101,0 +114587,Male,51,Masters,19,3,91,45,6,7.0,0,65,Semi-Urban,Data Analyst,109213,0 +114588,Female,51,Diploma,13,74,19,46,7,8.0,2,60,Urban,Software Engineer,73423,0 +114589,Male,25,Masters,10,87,32,59,52,8.0,3,32,Urban,Software Engineer,22791,0 +114590,Female,43,High School,2,12,96,65,22,1.0,3,38,Semi-Urban,Manager,91797,0 +114591,Female,22,Bachelors,6,20,22,87,7,9.0,1,73,Urban,ML Engineer,102717,0 +114592,Female,51,Masters,8,18,55,96,47,1.0,6,98,Rural,Data Analyst,42416,1 +114593,Female,40,Masters,3,39,70,77,99,3.0,6,71,Rural,Manager,126221,1 +114594,Male,51,Bachelors,5,13,58,12,35,1.0,7,51,Rural,Software Engineer,85841,0 +114595,Male,21,Bachelors,17,46,54,79,98,9.0,2,44,Semi-Urban,HR Executive,30940,0 +114596,Male,37,Masters,16,82,39,4,38,6.0,0,33,Urban,HR Executive,24200,0 +114597,Female,54,Diploma,6,15,29,23,18,2.0,2,40,Semi-Urban,Software Engineer,148525,0 +114598,Male,44,Masters,9,62,7,9,49,4.0,5,68,Semi-Urban,Software Engineer,42851,0 +114599,Male,51,Masters,7,18,74,6,56,8.0,1,94,Urban,Software Engineer,90805,0 +114600,Male,54,Bachelors,4,33,85,79,27,9.0,3,42,Rural,Software Engineer,54014,1 +114601,Female,45,Masters,10,82,74,87,98,1.0,0,2,Urban,Software Engineer,66361,1 +114602,Male,49,Diploma,18,71,55,70,3,1.0,2,82,Urban,Manager,126911,1 +114603,Female,48,Bachelors,16,27,18,0,99,8.0,0,71,Semi-Urban,HR Executive,145867,0 +114604,Male,45,Bachelors,0,9,73,53,90,5.0,7,88,Urban,Software Engineer,40146,0 +114605,Male,55,Bachelors,5,94,57,0,65,3.0,6,67,Urban,Software Engineer,110643,0 +114606,Female,54,Diploma,18,28,59,1,53,6.0,0,39,Rural,Software Engineer,73253,0 +114607,Male,29,Bachelors,12,81,92,94,21,0.0,7,89,Rural,Software Engineer,89441,1 +114608,Other,33,Bachelors,16,4,69,13,6,8.0,5,59,Urban,ML Engineer,96546,0 +114609,Female,29,High School,18,78,5,45,79,9.0,6,72,Semi-Urban,Software Engineer,143382,0 +114610,Male,56,High School,17,67,63,43,83,5.0,1,28,Rural,Data Analyst,29190,0 +114611,Other,33,Diploma,14,40,35,59,5,7.0,0,48,Urban,ML Engineer,117107,0 +114612,Female,50,Bachelors,6,68,22,5,92,5.0,1,91,Semi-Urban,ML Engineer,40607,0 +114613,Female,37,Masters,14,15,79,72,9,9.0,6,51,Urban,Manager,53570,0 +114614,Female,47,Bachelors,12,20,50,57,69,3.0,7,25,Urban,ML Engineer,29623,0 +114615,Female,43,High School,17,19,88,20,95,4.0,3,6,Urban,Data Analyst,47579,0 +114616,Female,50,Masters,8,48,41,15,71,8.0,7,50,Urban,Software Engineer,38830,0 +114617,Male,56,High School,6,63,84,66,66,0.0,1,95,Semi-Urban,Manager,109171,1 +114618,Male,29,Masters,4,39,88,34,71,5.0,7,28,Urban,HR Executive,32459,0 +114619,Male,38,Bachelors,2,23,75,40,68,9.0,0,85,Urban,HR Executive,91361,0 +114620,Female,47,Masters,11,11,23,1,88,6.0,4,71,Semi-Urban,Software Engineer,143800,0 +114621,Male,29,Diploma,14,58,66,58,94,0.0,4,85,Rural,Manager,66986,1 +114622,Male,23,Bachelors,3,97,46,31,17,3.0,5,63,Semi-Urban,Data Analyst,86153,1 +114623,Male,47,Bachelors,14,7,64,81,89,3.0,4,60,Semi-Urban,Manager,102444,0 +114624,Other,22,Bachelors,15,56,57,2,93,2.0,0,82,Rural,HR Executive,30930,0 +114625,Male,58,Bachelors,8,37,6,3,93,4.0,1,23,Rural,Software Engineer,131422,0 +114626,Male,52,High School,3,19,66,55,58,4.0,3,95,Rural,HR Executive,80126,1 +114627,Male,28,Diploma,12,11,96,86,15,4.0,3,66,Urban,HR Executive,100073,1 +114628,Female,50,Masters,0,98,95,81,38,7.0,6,67,Urban,Manager,85765,1 +114629,Male,52,Masters,3,31,13,25,2,0.0,5,38,Rural,Data Analyst,97599,0 +114630,Male,37,Bachelors,11,21,64,87,35,3.0,2,43,Semi-Urban,Data Analyst,61859,0 +114631,Female,22,Bachelors,7,86,33,11,11,0.0,4,13,Urban,Software Engineer,105187,0 +114632,Male,54,Diploma,2,61,4,43,45,3.0,4,0,Rural,Software Engineer,71790,0 +114633,Male,29,Masters,17,16,88,13,60,6.0,4,38,Semi-Urban,ML Engineer,84468,0 +114634,Female,38,High School,7,59,4,98,62,0.0,7,98,Rural,Manager,46449,1 +114635,Female,59,PhD,19,94,90,75,89,6.0,7,11,Semi-Urban,ML Engineer,75907,1 +114636,Male,21,High School,8,91,73,48,56,7.0,4,89,Rural,ML Engineer,106234,1 +114637,Male,36,Masters,16,67,11,46,47,5.0,1,49,Urban,Software Engineer,70867,0 +114638,Male,51,Bachelors,12,43,4,19,72,9.0,6,71,Urban,Data Analyst,149712,0 +114639,Female,52,Bachelors,11,22,77,43,95,6.0,4,64,Semi-Urban,HR Executive,118002,0 +114640,Female,43,Masters,7,38,20,3,33,6.0,2,5,Urban,HR Executive,132244,0 +114641,Male,40,Bachelors,14,91,25,25,12,0.0,6,78,Urban,ML Engineer,101068,0 +114642,Female,42,Diploma,18,89,33,65,12,2.0,5,99,Semi-Urban,Software Engineer,97794,1 +114643,Female,51,Bachelors,16,74,91,85,57,8.0,5,91,Semi-Urban,Software Engineer,27621,1 +114644,Male,22,Bachelors,7,74,35,84,98,5.0,7,23,Urban,ML Engineer,28055,0 +114645,Male,38,Masters,8,13,29,30,62,1.0,6,7,Urban,Data Analyst,143782,0 +114646,Male,51,Diploma,18,88,87,31,49,2.0,0,34,Semi-Urban,Software Engineer,130927,1 +114647,Female,40,Diploma,15,92,56,24,26,5.0,0,22,Urban,Software Engineer,68476,0 +114648,Male,23,PhD,19,55,11,71,50,0.0,4,85,Rural,HR Executive,123270,0 +114649,Male,22,Diploma,5,97,36,17,41,6.0,6,28,Semi-Urban,HR Executive,131237,0 +114650,Male,26,Masters,8,20,53,63,93,5.0,4,44,Semi-Urban,Manager,111442,0 +114651,Female,41,Diploma,16,42,3,81,5,6.0,3,96,Urban,HR Executive,118963,0 +114652,Other,52,Diploma,5,29,68,16,18,9.0,7,62,Urban,Data Analyst,38397,0 +114653,Male,45,Diploma,0,55,6,26,24,4.0,7,72,Semi-Urban,Software Engineer,53694,0 +114654,Male,26,Diploma,3,24,40,70,0,0.0,1,26,Urban,Manager,98918,0 +114655,Female,40,Masters,18,65,71,91,44,1.0,0,93,Urban,ML Engineer,39615,1 +114656,Male,36,Bachelors,0,55,59,75,52,8.0,7,84,Rural,Data Analyst,63206,1 +114657,Male,29,Diploma,19,53,40,1,41,4.0,2,74,Urban,HR Executive,102146,0 +114658,Female,50,Diploma,18,41,66,19,14,2.0,6,37,Urban,ML Engineer,138654,0 +114659,Male,24,Masters,9,62,45,49,5,9.0,4,69,Urban,Manager,143811,0 +114660,Male,37,Masters,8,74,93,69,42,2.0,6,93,Semi-Urban,Data Analyst,31301,1 +114661,Male,55,Diploma,5,51,23,40,10,9.0,4,9,Urban,Software Engineer,121877,0 +114662,Female,45,High School,17,36,12,25,97,2.0,5,60,Rural,Manager,47273,0 +114663,Male,51,High School,15,2,98,17,76,8.0,4,13,Semi-Urban,Software Engineer,78102,0 +114664,Female,40,PhD,4,33,18,96,63,6.0,7,42,Semi-Urban,ML Engineer,20223,0 +114665,Male,36,Bachelors,16,34,6,4,53,2.0,7,23,Urban,Data Analyst,48106,0 +114666,Male,34,High School,13,72,30,40,1,5.0,2,45,Urban,Data Analyst,140748,0 +114667,Female,45,Bachelors,0,25,39,48,38,6.0,3,0,Urban,ML Engineer,106626,0 +114668,Male,55,Bachelors,10,60,16,7,4,8.0,5,57,Urban,Manager,126824,0 +114669,Female,44,Bachelors,6,82,28,22,24,4.0,1,80,Rural,ML Engineer,79346,0 +114670,Female,58,Diploma,5,99,68,48,70,6.0,6,46,Urban,ML Engineer,122899,1 +114671,Female,48,Masters,17,6,73,20,8,4.0,6,90,Rural,Data Analyst,113421,0 +114672,Male,25,Bachelors,3,43,63,7,37,2.0,7,20,Urban,Data Analyst,130846,0 +114673,Female,23,Masters,13,3,20,5,30,6.0,2,26,Rural,Manager,34504,0 +114674,Male,34,Bachelors,13,17,37,8,56,0.0,7,33,Urban,ML Engineer,21508,0 +114675,Male,21,Bachelors,5,0,6,85,16,2.0,5,3,Urban,Data Analyst,146906,0 +114676,Male,54,PhD,14,9,45,76,53,2.0,7,0,Urban,HR Executive,103932,0 +114677,Male,49,Bachelors,10,58,21,18,7,1.0,5,16,Semi-Urban,Manager,27542,0 +114678,Male,24,Bachelors,6,38,96,68,54,1.0,0,46,Semi-Urban,Data Analyst,113800,1 +114679,Male,29,Diploma,14,34,77,41,96,6.0,5,27,Semi-Urban,Software Engineer,90245,0 +114680,Male,39,Bachelors,5,70,51,73,98,7.0,1,38,Urban,Software Engineer,124481,0 +114681,Other,55,Diploma,14,6,35,87,19,8.0,7,24,Semi-Urban,HR Executive,28144,0 +114682,Female,34,High School,1,9,70,15,21,4.0,4,47,Urban,Software Engineer,96506,0 +114683,Male,47,Bachelors,14,49,32,30,46,4.0,6,81,Urban,HR Executive,119270,0 +114684,Male,56,Bachelors,17,56,29,29,82,7.0,1,45,Semi-Urban,Data Analyst,134367,0 +114685,Male,26,Bachelors,18,9,75,33,60,6.0,1,75,Rural,ML Engineer,36184,0 +114686,Female,25,Masters,3,23,77,93,94,2.0,7,90,Semi-Urban,ML Engineer,111825,1 +114687,Male,59,Diploma,17,46,55,22,20,7.0,0,49,Urban,Manager,89526,0 +114688,Other,30,Bachelors,2,79,41,13,13,7.0,2,93,Urban,Manager,91959,0 +114689,Male,59,Bachelors,17,69,24,51,96,7.0,2,47,Rural,Data Analyst,64080,0 +114690,Male,25,Bachelors,1,2,89,28,20,3.0,3,17,Rural,Software Engineer,145922,0 +114691,Other,30,Bachelors,4,70,61,48,50,7.0,4,91,Semi-Urban,Manager,31876,1 +114692,Male,28,PhD,2,82,41,69,14,8.0,1,11,Urban,HR Executive,142822,0 +114693,Male,33,Diploma,10,5,6,49,47,0.0,0,5,Urban,Software Engineer,29431,0 +114694,Male,23,Bachelors,14,24,22,75,27,5.0,3,38,Urban,Data Analyst,29032,0 +114695,Female,29,Masters,13,22,24,28,30,7.0,0,67,Semi-Urban,ML Engineer,98816,0 +114696,Female,41,Diploma,8,64,17,2,1,7.0,6,63,Urban,ML Engineer,37699,0 +114697,Male,45,Bachelors,0,46,73,29,84,7.0,4,44,Rural,Data Analyst,47909,0 +114698,Male,34,High School,6,27,48,6,45,9.0,1,15,Rural,ML Engineer,52452,0 +114699,Female,28,PhD,4,71,14,15,12,6.0,6,43,Semi-Urban,Software Engineer,137266,0 +114700,Male,59,High School,12,69,37,26,84,2.0,0,15,Rural,Manager,20966,0 +114701,Male,27,High School,6,59,3,76,1,3.0,1,97,Urban,ML Engineer,52922,1 +114702,Female,54,Diploma,7,12,26,54,77,8.0,1,35,Semi-Urban,ML Engineer,83123,0 +114703,Male,48,PhD,16,13,74,70,6,4.0,7,87,Urban,Data Analyst,118097,1 +114704,Male,36,Diploma,18,51,45,87,11,8.0,7,84,Urban,Data Analyst,27927,1 +114705,Female,23,High School,17,9,50,12,73,2.0,4,9,Rural,Software Engineer,95772,0 +114706,Female,45,High School,0,66,53,89,42,5.0,7,41,Urban,Manager,97784,1 +114707,Female,32,Bachelors,9,55,85,10,30,4.0,5,1,Semi-Urban,Manager,99912,0 +114708,Female,54,High School,12,26,6,74,77,8.0,2,0,Urban,Software Engineer,61726,0 +114709,Female,49,Bachelors,9,61,63,48,19,5.0,0,75,Semi-Urban,Data Analyst,59240,1 +114710,Female,44,Bachelors,15,28,65,87,72,4.0,0,82,Urban,Software Engineer,82986,1 +114711,Male,53,Diploma,16,19,2,7,7,5.0,2,32,Urban,Manager,92387,0 +114712,Female,27,Bachelors,14,50,46,61,24,6.0,3,93,Semi-Urban,HR Executive,29075,1 +114713,Male,32,Bachelors,14,2,97,76,24,5.0,5,68,Urban,Data Analyst,119318,1 +114714,Male,41,Diploma,15,35,5,61,36,1.0,0,25,Urban,Software Engineer,39865,0 +114715,Male,56,Bachelors,18,23,19,11,58,7.0,0,93,Urban,Software Engineer,38134,0 +114716,Female,54,High School,16,27,63,54,49,4.0,6,87,Semi-Urban,ML Engineer,85418,0 +114717,Male,24,Masters,3,39,36,5,5,6.0,4,42,Semi-Urban,ML Engineer,45197,0 +114718,Male,31,Diploma,4,5,37,22,65,8.0,7,19,Urban,Software Engineer,27174,0 +114719,Female,31,High School,10,24,13,81,98,2.0,6,74,Urban,ML Engineer,84854,0 +114720,Other,39,Diploma,10,77,1,34,99,2.0,7,70,Urban,Data Analyst,79274,0 +114721,Female,24,Bachelors,5,30,42,3,0,2.0,2,86,Urban,Manager,110371,0 +114722,Male,27,Bachelors,18,8,71,54,14,4.0,7,81,Urban,HR Executive,41635,0 +114723,Male,38,High School,11,58,33,27,56,5.0,6,91,Semi-Urban,ML Engineer,98766,0 +114724,Female,21,Bachelors,14,70,37,91,50,0.0,2,66,Semi-Urban,Software Engineer,62964,1 +114725,Female,39,Masters,0,45,76,51,56,6.0,1,2,Rural,Software Engineer,143391,0 +114726,Male,52,Diploma,11,17,75,38,33,9.0,5,76,Urban,HR Executive,66737,0 +114727,Female,41,Bachelors,6,56,49,33,56,5.0,4,12,Semi-Urban,Data Analyst,84708,0 +114728,Male,51,Masters,11,69,43,55,31,8.0,6,51,Urban,ML Engineer,61389,0 +114729,Other,54,Bachelors,5,90,52,59,54,0.0,5,18,Urban,Software Engineer,109976,0 +114730,Male,48,Bachelors,1,38,44,24,96,8.0,2,22,Semi-Urban,ML Engineer,57162,0 +114731,Male,33,Bachelors,17,43,41,51,20,9.0,0,28,Semi-Urban,Software Engineer,40524,0 +114732,Male,36,Masters,6,49,89,42,76,9.0,0,33,Rural,Software Engineer,44624,0 +114733,Male,59,Bachelors,17,46,57,13,45,3.0,3,81,Urban,ML Engineer,140228,0 +114734,Female,58,Masters,14,67,21,41,42,5.0,0,63,Urban,Software Engineer,116661,0 +114735,Male,22,Diploma,5,20,38,12,64,7.0,5,19,Urban,ML Engineer,149213,0 +114736,Female,22,Masters,19,0,39,62,63,8.0,6,20,Rural,Software Engineer,64387,0 +114737,Male,32,High School,6,15,99,46,77,8.0,2,30,Semi-Urban,ML Engineer,88316,0 +114738,Female,29,High School,8,61,45,10,55,7.0,0,24,Rural,HR Executive,23304,0 +114739,Male,48,Diploma,0,10,83,40,47,1.0,6,9,Semi-Urban,HR Executive,71053,0 +114740,Male,21,Bachelors,9,33,70,73,36,2.0,2,31,Semi-Urban,ML Engineer,27783,0 +114741,Female,22,Masters,7,21,76,94,85,2.0,2,57,Urban,Software Engineer,40166,1 +114742,Male,59,High School,12,50,95,88,65,3.0,0,49,Urban,Software Engineer,59213,1 +114743,Male,55,Bachelors,14,35,47,48,7,6.0,6,42,Rural,Data Analyst,120822,0 +114744,Female,40,Masters,8,6,90,3,63,9.0,7,73,Semi-Urban,Software Engineer,88148,0 +114745,Male,25,High School,14,53,75,34,12,3.0,1,5,Rural,Software Engineer,93736,0 +114746,Male,31,PhD,18,56,15,50,49,3.0,7,73,Urban,HR Executive,51574,0 +114747,Female,47,Diploma,5,71,65,78,74,8.0,2,47,Rural,Data Analyst,84989,1 +114748,Female,21,Masters,7,81,90,11,0,6.0,7,97,Semi-Urban,Software Engineer,54509,1 +114749,Male,43,Diploma,18,37,75,28,78,8.0,0,45,Rural,ML Engineer,52282,0 +114750,Male,22,Diploma,5,96,66,29,51,7.0,4,91,Urban,Manager,21260,1 +114751,Male,54,High School,7,50,0,94,20,7.0,3,61,Urban,HR Executive,107639,0 +114752,Female,29,Bachelors,9,7,84,30,46,0.0,6,88,Urban,ML Engineer,72456,0 +114753,Other,59,Masters,9,12,80,43,30,8.0,2,33,Semi-Urban,Data Analyst,23523,0 +114754,Male,24,Diploma,11,75,6,77,93,2.0,5,13,Rural,Manager,142589,0 +114755,Male,45,Masters,17,23,91,47,30,7.0,7,58,Urban,HR Executive,39255,0 +114756,Male,23,Masters,1,47,48,30,60,7.0,0,7,Semi-Urban,HR Executive,76813,0 +114757,Male,54,Diploma,6,20,71,80,45,4.0,1,95,Urban,Manager,137725,1 +114758,Female,42,Masters,16,3,85,67,81,5.0,3,39,Urban,HR Executive,85754,0 +114759,Male,30,Diploma,11,38,13,16,95,7.0,6,29,Rural,ML Engineer,101712,0 +114760,Male,58,Bachelors,0,1,80,12,18,7.0,7,39,Rural,Manager,50686,0 +114761,Male,57,Bachelors,18,33,15,34,56,9.0,5,42,Urban,Software Engineer,131818,0 +114762,Male,53,Diploma,11,25,15,46,46,1.0,3,83,Urban,Data Analyst,84847,0 +114763,Male,26,Bachelors,0,80,20,39,76,2.0,6,33,Rural,ML Engineer,131117,0 +114764,Male,23,Bachelors,5,45,42,4,33,1.0,6,81,Semi-Urban,ML Engineer,74010,0 +114765,Male,24,PhD,17,62,93,26,29,1.0,1,8,Urban,Manager,66365,0 +114766,Female,26,Diploma,19,11,88,8,91,9.0,2,1,Urban,Data Analyst,106495,0 +114767,Male,55,Masters,10,69,72,87,10,7.0,3,59,Urban,Software Engineer,89395,1 +114768,Male,30,Masters,10,61,76,54,66,1.0,3,0,Urban,Data Analyst,74339,0 +114769,Female,40,High School,13,64,63,42,48,0.0,7,90,Rural,Data Analyst,28576,1 +114770,Male,49,Diploma,13,96,99,52,10,9.0,3,49,Semi-Urban,Manager,70751,1 +114771,Male,31,Bachelors,16,30,60,51,42,3.0,7,57,Urban,HR Executive,121887,0 +114772,Female,30,Diploma,12,56,23,24,29,6.0,1,14,Urban,ML Engineer,82940,0 +114773,Male,32,Diploma,18,85,21,9,91,9.0,0,36,Semi-Urban,HR Executive,111362,0 +114774,Male,52,Diploma,9,99,93,60,45,4.0,6,42,Urban,Data Analyst,131906,1 +114775,Other,42,Diploma,12,60,18,44,72,0.0,5,9,Semi-Urban,Software Engineer,68505,0 +114776,Female,53,Bachelors,0,78,86,14,37,0.0,2,91,Urban,Manager,90732,1 +114777,Female,23,Bachelors,15,7,43,82,66,8.0,7,98,Urban,ML Engineer,140029,0 +114778,Male,54,Bachelors,3,43,72,57,81,3.0,6,2,Semi-Urban,Software Engineer,71151,0 +114779,Female,38,Bachelors,14,69,18,81,50,8.0,5,47,Rural,HR Executive,28159,0 +114780,Male,49,High School,13,42,39,60,20,0.0,1,74,Semi-Urban,Manager,137590,0 +114781,Other,48,Bachelors,9,63,61,45,43,8.0,5,17,Urban,Data Analyst,64868,0 +114782,Male,46,Masters,17,4,41,41,33,9.0,4,98,Urban,Software Engineer,32239,0 +114783,Female,29,Bachelors,9,38,69,54,31,2.0,6,74,Rural,HR Executive,62587,0 +114784,Male,22,Diploma,15,96,4,77,17,6.0,3,62,Urban,Software Engineer,101454,1 +114785,Male,51,Diploma,19,44,36,22,74,0.0,0,64,Urban,Manager,142562,0 +114786,Male,53,Masters,5,75,84,54,74,7.0,7,39,Rural,HR Executive,88191,1 +114787,Male,36,Bachelors,7,59,41,85,33,1.0,0,69,Urban,Software Engineer,84187,1 +114788,Female,52,Diploma,11,13,71,16,10,5.0,4,53,Semi-Urban,Manager,95279,0 +114789,Female,27,Diploma,12,26,90,86,26,4.0,1,60,Urban,Data Analyst,141210,1 +114790,Male,21,High School,2,99,75,24,75,5.0,3,17,Rural,ML Engineer,103707,0 +114791,Female,37,High School,9,37,84,12,76,3.0,5,44,Urban,ML Engineer,70737,0 +114792,Female,31,Bachelors,0,99,21,60,35,1.0,7,4,Semi-Urban,ML Engineer,35717,0 +114793,Female,36,Bachelors,11,71,4,63,37,0.0,1,15,Rural,Manager,48690,0 +114794,Male,30,Diploma,2,24,59,93,33,2.0,2,8,Urban,Manager,127515,0 +114795,Female,49,Bachelors,1,1,51,94,46,0.0,0,65,Urban,Manager,32427,0 +114796,Male,29,Diploma,6,81,94,8,65,1.0,0,56,Rural,Software Engineer,111652,1 +114797,Female,32,Bachelors,14,20,67,61,95,2.0,5,56,Urban,Data Analyst,63703,0 +114798,Male,45,Bachelors,19,43,27,34,78,6.0,5,41,Urban,Data Analyst,121317,0 +114799,Female,59,Bachelors,4,1,42,45,29,3.0,1,57,Semi-Urban,Manager,22254,0 +114800,Male,29,High School,4,37,67,60,54,9.0,2,27,Urban,Software Engineer,38284,0 +114801,Male,24,Masters,1,75,28,97,30,8.0,0,91,Urban,Software Engineer,103323,1 +114802,Female,27,Masters,6,55,91,0,83,3.0,3,64,Urban,Data Analyst,105901,0 +114803,Female,57,Diploma,6,78,0,25,39,2.0,2,10,Urban,Data Analyst,33034,0 +114804,Female,58,Bachelors,18,91,62,50,62,6.0,3,45,Rural,Manager,54158,1 +114805,Female,53,High School,11,7,39,68,97,8.0,5,83,Urban,Data Analyst,102133,0 +114806,Male,23,Bachelors,17,71,78,11,81,6.0,6,47,Urban,ML Engineer,67178,0 +114807,Female,23,Bachelors,10,99,63,86,30,6.0,2,79,Urban,HR Executive,52236,1 +114808,Male,35,Masters,11,76,7,24,15,3.0,3,37,Urban,HR Executive,109818,0 +114809,Male,45,Bachelors,0,50,72,40,1,4.0,6,65,Rural,ML Engineer,142461,0 +114810,Female,26,High School,19,68,67,51,91,4.0,3,69,Semi-Urban,Software Engineer,122143,1 +114811,Female,47,Bachelors,9,20,31,45,79,6.0,2,43,Semi-Urban,Software Engineer,35598,0 +114812,Male,28,High School,16,20,98,45,52,8.0,0,81,Rural,Data Analyst,127401,1 +114813,Male,35,Bachelors,12,82,25,32,85,3.0,2,65,Urban,HR Executive,26474,0 +114814,Female,56,Bachelors,10,33,4,18,4,6.0,2,12,Urban,Data Analyst,76642,0 +114815,Male,53,Bachelors,19,81,70,33,76,3.0,1,66,Rural,ML Engineer,66928,1 +114816,Other,52,Masters,2,4,75,1,67,8.0,4,66,Semi-Urban,Manager,145911,0 +114817,Female,30,Diploma,6,24,22,77,42,9.0,2,64,Rural,Manager,89323,0 +114818,Female,25,Bachelors,11,88,84,4,32,8.0,4,44,Rural,Data Analyst,20869,0 +114819,Male,40,Masters,4,39,50,8,72,5.0,2,1,Rural,Data Analyst,53904,0 +114820,Male,44,Masters,15,54,34,53,81,9.0,5,66,Semi-Urban,Software Engineer,71717,0 +114821,Female,21,Masters,9,96,75,43,80,6.0,0,65,Urban,Software Engineer,134894,1 +114822,Male,38,High School,19,85,55,66,96,7.0,5,63,Semi-Urban,HR Executive,59150,1 +114823,Male,45,Diploma,10,87,94,25,0,5.0,5,57,Rural,Data Analyst,110980,1 +114824,Male,37,Diploma,14,57,66,92,98,7.0,7,66,Rural,HR Executive,39414,1 +114825,Male,58,Masters,2,89,73,35,61,9.0,7,41,Urban,Software Engineer,62489,1 +114826,Male,54,Diploma,5,62,14,37,23,8.0,2,81,Rural,Data Analyst,91249,0 +114827,Male,27,Bachelors,8,98,9,53,57,9.0,1,73,Urban,HR Executive,129747,0 +114828,Male,22,Bachelors,9,94,8,25,17,9.0,4,47,Semi-Urban,Data Analyst,123797,0 +114829,Male,49,Bachelors,0,96,20,94,10,8.0,4,59,Urban,Data Analyst,74101,1 +114830,Male,40,PhD,1,55,60,89,89,3.0,3,74,Semi-Urban,Software Engineer,106088,1 +114831,Male,36,Bachelors,2,83,23,19,13,8.0,1,38,Urban,Manager,112521,0 +114832,Male,59,Diploma,11,60,4,87,72,1.0,0,64,Urban,Data Analyst,92094,0 +114833,Male,26,Bachelors,14,6,46,27,6,4.0,5,90,Semi-Urban,Software Engineer,146502,0 +114834,Female,35,Masters,1,94,41,37,97,5.0,1,10,Semi-Urban,Software Engineer,92347,0 +114835,Female,23,Bachelors,5,8,93,16,2,2.0,2,74,Urban,ML Engineer,49748,0 +114836,Male,31,Bachelors,7,17,30,27,59,9.0,6,73,Urban,HR Executive,99304,0 +114837,Male,30,Diploma,5,24,72,49,45,1.0,6,83,Semi-Urban,ML Engineer,83512,0 +114838,Male,28,Diploma,11,28,61,20,88,5.0,1,19,Rural,Software Engineer,31857,0 +114839,Female,46,Bachelors,2,97,47,5,17,3.0,0,97,Rural,HR Executive,95586,1 +114840,Male,59,Bachelors,17,82,15,50,44,3.0,2,49,Rural,Data Analyst,108118,0 +114841,Male,35,PhD,12,47,51,47,75,5.0,4,23,Urban,Manager,22397,0 +114842,Female,22,Masters,13,40,70,67,53,3.0,4,47,Urban,Software Engineer,105163,0 +114843,Female,21,Diploma,17,87,95,14,6,2.0,5,14,Urban,ML Engineer,80234,0 +114844,Female,46,PhD,15,24,83,86,80,0.0,4,18,Urban,Manager,110525,0 +114845,Male,24,Bachelors,0,7,93,22,88,2.0,3,63,Urban,ML Engineer,85881,0 +114846,Male,34,Bachelors,10,5,33,13,43,2.0,6,10,Semi-Urban,Data Analyst,38919,0 +114847,Male,57,Diploma,2,58,54,70,87,3.0,1,74,Rural,HR Executive,78666,1 +114848,Male,53,Masters,7,60,12,46,12,6.0,5,57,Urban,ML Engineer,62499,0 +114849,Other,39,PhD,7,16,56,85,32,3.0,5,48,Urban,Manager,120768,0 +114850,Male,27,Bachelors,18,41,46,38,89,9.0,3,92,Urban,Software Engineer,106942,0 +114851,Male,39,Bachelors,17,13,77,1,83,6.0,2,80,Semi-Urban,Software Engineer,60907,0 +114852,Female,53,High School,2,0,95,39,50,4.0,4,70,Rural,Data Analyst,44533,0 +114853,Other,28,Diploma,17,18,0,66,61,8.0,4,46,Urban,Software Engineer,69227,0 +114854,Male,25,Bachelors,11,90,96,32,52,7.0,2,5,Urban,Manager,93241,0 +114855,Male,37,Bachelors,14,74,34,58,20,6.0,4,98,Urban,Software Engineer,30951,1 +114856,Male,37,PhD,18,36,8,5,18,4.0,0,2,Rural,ML Engineer,43640,0 +114857,Female,24,Bachelors,17,10,31,25,79,9.0,5,64,Semi-Urban,HR Executive,71342,0 +114858,Female,35,High School,7,16,77,79,21,3.0,3,26,Urban,Data Analyst,117750,0 +114859,Female,28,Masters,13,85,75,40,42,9.0,6,31,Urban,ML Engineer,66690,0 +114860,Female,58,PhD,8,38,28,28,72,2.0,5,10,Rural,Data Analyst,128229,0 +114861,Other,42,High School,7,57,28,79,31,1.0,3,42,Semi-Urban,Data Analyst,87827,0 +114862,Male,21,High School,11,29,18,17,76,3.0,1,33,Urban,HR Executive,29310,0 +114863,Male,48,Diploma,0,68,62,0,36,5.0,7,1,Urban,Manager,128608,0 +114864,Male,57,Diploma,11,90,43,4,84,1.0,7,81,Rural,Manager,37536,0 +114865,Male,47,Bachelors,19,33,20,98,10,1.0,0,61,Urban,Software Engineer,139756,0 +114866,Male,21,Masters,11,10,57,31,66,0.0,2,30,Semi-Urban,Software Engineer,148697,0 +114867,Male,25,Diploma,6,14,4,6,1,7.0,5,66,Urban,Software Engineer,116033,0 +114868,Male,42,High School,1,11,45,86,17,8.0,3,76,Rural,HR Executive,23982,0 +114869,Male,21,High School,10,41,87,57,15,7.0,7,11,Urban,HR Executive,100546,0 +114870,Male,52,Masters,1,66,87,46,89,1.0,1,29,Semi-Urban,Software Engineer,34063,0 +114871,Male,26,Diploma,14,23,21,39,8,7.0,0,10,Urban,HR Executive,29554,0 +114872,Male,54,Masters,10,15,92,36,12,9.0,0,29,Urban,Software Engineer,20495,0 +114873,Male,30,Bachelors,1,14,59,69,3,3.0,1,10,Urban,HR Executive,146061,0 +114874,Male,53,Bachelors,12,48,59,15,7,5.0,2,31,Urban,Software Engineer,121314,0 +114875,Male,51,Diploma,6,90,20,92,88,5.0,4,29,Semi-Urban,Data Analyst,55996,0 +114876,Male,56,Bachelors,19,33,87,65,2,4.0,1,0,Urban,ML Engineer,93588,0 +114877,Female,53,PhD,16,64,47,76,15,9.0,2,8,Semi-Urban,HR Executive,46083,0 +114878,Male,29,Masters,14,57,4,72,43,4.0,1,62,Rural,ML Engineer,23324,0 +114879,Male,33,High School,16,60,2,87,82,6.0,5,12,Semi-Urban,Manager,21021,0 +114880,Male,48,Masters,5,85,77,50,39,8.0,6,57,Urban,ML Engineer,109821,1 +114881,Male,35,Bachelors,16,42,80,33,98,6.0,7,79,Urban,HR Executive,136846,0 +114882,Female,51,Diploma,6,58,46,81,20,3.0,5,95,Urban,Manager,51753,1 +114883,Male,41,Bachelors,16,76,74,77,87,9.0,7,11,Urban,Software Engineer,146184,1 +114884,Male,43,High School,9,17,71,70,99,1.0,0,60,Urban,Software Engineer,116746,0 +114885,Male,34,High School,7,96,68,45,34,3.0,6,81,Rural,Data Analyst,122602,1 +114886,Female,34,Bachelors,4,79,89,18,92,2.0,3,38,Semi-Urban,Software Engineer,87746,0 +114887,Female,57,Bachelors,12,4,27,99,95,8.0,4,46,Urban,Data Analyst,144718,0 +114888,Male,32,Diploma,9,91,50,88,16,8.0,7,61,Urban,ML Engineer,140744,1 +114889,Female,31,Masters,8,6,40,36,47,5.0,0,30,Urban,ML Engineer,122950,0 +114890,Male,58,Bachelors,4,6,2,62,76,2.0,6,0,Semi-Urban,Data Analyst,36820,0 +114891,Other,52,Diploma,16,69,61,75,10,2.0,4,90,Semi-Urban,ML Engineer,80832,1 +114892,Male,28,Diploma,5,19,96,25,71,7.0,2,52,Urban,Software Engineer,115751,0 +114893,Male,53,PhD,11,3,23,61,50,7.0,0,76,Rural,Data Analyst,44378,0 +114894,Male,44,Diploma,11,73,84,56,42,5.0,1,91,Semi-Urban,Software Engineer,88019,1 +114895,Male,44,Masters,4,25,70,19,50,7.0,4,26,Urban,Manager,100851,0 +114896,Male,42,Masters,17,40,8,50,7,8.0,1,84,Urban,HR Executive,134071,0 +114897,Male,55,Diploma,0,48,43,54,61,6.0,3,67,Semi-Urban,Software Engineer,107961,0 +114898,Female,55,Bachelors,15,97,74,44,47,5.0,1,44,Urban,ML Engineer,23169,1 +114899,Male,43,PhD,19,62,69,87,19,1.0,4,53,Rural,Manager,144559,1 +114900,Female,36,Masters,16,57,27,90,18,5.0,4,77,Urban,ML Engineer,39768,1 +114901,Male,55,Diploma,19,43,64,65,39,9.0,3,85,Semi-Urban,Manager,121552,1 +114902,Female,46,Bachelors,7,46,30,91,38,5.0,3,86,Rural,Software Engineer,56174,1 +114903,Male,52,Bachelors,7,0,85,17,12,2.0,2,13,Urban,Software Engineer,148161,0 +114904,Female,48,Masters,3,99,58,2,82,7.0,4,18,Semi-Urban,Data Analyst,76795,0 +114905,Male,59,Diploma,13,60,39,55,81,9.0,2,19,Rural,Manager,25412,0 +114906,Male,38,High School,7,25,79,15,81,1.0,3,51,Urban,HR Executive,138559,0 +114907,Male,25,Masters,4,73,64,69,30,3.0,4,11,Urban,ML Engineer,138030,0 +114908,Female,27,Masters,2,71,92,62,69,4.0,5,38,Rural,HR Executive,36881,1 +114909,Male,50,Bachelors,18,48,32,63,89,4.0,2,79,Urban,Manager,76810,0 +114910,Male,31,Masters,10,70,85,80,26,6.0,5,63,Rural,ML Engineer,145623,1 +114911,Female,34,Bachelors,19,57,52,51,12,0.0,6,48,Urban,ML Engineer,77497,0 +114912,Male,43,Masters,5,51,73,10,92,2.0,6,96,Urban,Data Analyst,63673,0 +114913,Female,37,Bachelors,12,48,95,69,89,8.0,0,64,Semi-Urban,Data Analyst,141905,1 +114914,Female,53,Diploma,4,12,54,55,96,6.0,4,60,Rural,ML Engineer,25972,0 +114915,Male,32,High School,19,38,91,26,59,0.0,3,25,Urban,HR Executive,92947,0 +114916,Male,36,Bachelors,9,30,34,80,58,1.0,0,54,Semi-Urban,Data Analyst,116689,0 +114917,Male,27,Masters,5,1,85,19,33,1.0,5,8,Urban,Software Engineer,52886,0 +114918,Male,56,Diploma,11,34,80,55,0,4.0,4,2,Urban,HR Executive,149547,0 +114919,Male,32,High School,5,80,55,38,32,7.0,4,85,Urban,Manager,107095,1 +114920,Male,33,Diploma,12,74,65,15,94,2.0,0,3,Semi-Urban,Software Engineer,134097,0 +114921,Female,43,Masters,18,61,82,0,6,7.0,4,97,Rural,Data Analyst,55899,0 +114922,Male,30,Masters,13,14,52,76,13,7.0,6,69,Urban,Manager,101430,0 +114923,Other,55,Diploma,11,7,49,66,78,4.0,5,68,Urban,ML Engineer,55418,0 +114924,Female,56,Bachelors,15,50,36,54,12,3.0,6,7,Semi-Urban,Data Analyst,27944,0 +114925,Male,59,Bachelors,14,77,45,33,79,7.0,3,73,Rural,Manager,75475,0 +114926,Male,27,High School,19,8,8,43,58,4.0,5,27,Urban,Data Analyst,95427,0 +114927,Male,47,Bachelors,13,5,9,37,47,6.0,4,96,Urban,Software Engineer,67154,0 +114928,Female,40,Masters,4,87,68,4,15,3.0,7,23,Rural,HR Executive,57345,0 +114929,Female,49,Bachelors,7,42,85,7,83,8.0,3,43,Rural,Data Analyst,52726,0 +114930,Male,36,High School,12,4,93,40,85,4.0,6,52,Urban,HR Executive,140923,0 +114931,Male,55,Bachelors,3,92,18,46,48,3.0,5,68,Urban,Software Engineer,131461,0 +114932,Male,52,Masters,5,29,4,26,52,6.0,5,10,Urban,Manager,39382,0 +114933,Male,46,Diploma,14,56,50,40,20,7.0,7,41,Rural,Manager,28898,0 +114934,Female,46,Bachelors,3,61,89,12,74,2.0,1,5,Urban,HR Executive,126521,0 +114935,Male,23,Bachelors,15,51,67,98,72,6.0,3,18,Urban,Software Engineer,78695,0 +114936,Female,22,Bachelors,4,16,89,65,76,0.0,5,12,Rural,ML Engineer,127246,0 +114937,Male,59,High School,12,24,90,72,28,3.0,7,61,Rural,Manager,86171,1 +114938,Female,58,PhD,14,68,85,97,61,9.0,6,39,Urban,ML Engineer,101514,1 +114939,Male,53,Bachelors,1,81,20,75,44,5.0,0,89,Urban,ML Engineer,89414,1 +114940,Female,45,Diploma,8,29,88,77,7,4.0,4,81,Urban,ML Engineer,129171,1 +114941,Male,29,Bachelors,7,42,35,43,68,3.0,4,33,Semi-Urban,ML Engineer,142907,0 +114942,Male,31,Masters,18,16,53,86,12,6.0,2,35,Semi-Urban,HR Executive,41687,0 +114943,Other,42,Bachelors,14,18,23,97,40,2.0,1,1,Urban,Manager,100484,0 +114944,Female,29,Diploma,16,94,71,54,26,1.0,3,25,Semi-Urban,Data Analyst,81492,1 +114945,Male,38,Masters,11,37,9,44,41,9.0,0,3,Urban,Manager,60426,0 +114946,Male,39,High School,0,38,91,80,1,4.0,5,99,Semi-Urban,HR Executive,105530,1 +114947,Male,23,Bachelors,3,97,83,57,11,2.0,4,21,Urban,ML Engineer,58566,1 +114948,Male,48,Diploma,17,99,18,26,84,8.0,1,23,Rural,Data Analyst,89978,0 +114949,Male,24,High School,10,79,73,49,87,0.0,5,17,Urban,Data Analyst,63722,0 +114950,Male,32,Masters,7,72,59,3,55,7.0,6,13,Urban,HR Executive,25954,0 +114951,Male,49,High School,13,97,48,40,33,6.0,6,86,Semi-Urban,Manager,112871,1 +114952,Female,25,Diploma,4,68,74,65,6,7.0,4,91,Semi-Urban,Manager,129538,1 +114953,Female,32,Bachelors,17,96,16,78,18,8.0,5,73,Rural,HR Executive,76973,1 +114954,Other,34,Bachelors,10,4,54,30,83,6.0,0,0,Rural,Software Engineer,58268,0 +114955,Female,43,Bachelors,18,92,30,84,1,4.0,0,69,Urban,Software Engineer,36806,1 +114956,Male,40,Bachelors,1,65,67,14,75,0.0,3,48,Rural,HR Executive,24547,0 +114957,Male,55,Diploma,10,16,19,75,72,2.0,7,66,Urban,HR Executive,113670,0 +114958,Male,25,Bachelors,8,87,73,5,14,3.0,6,35,Rural,ML Engineer,129947,0 +114959,Other,43,Diploma,11,41,1,51,22,1.0,6,72,Urban,Data Analyst,136296,0 +114960,Male,40,Diploma,3,94,9,14,55,0.0,7,35,Semi-Urban,Software Engineer,51235,0 +114961,Male,53,Bachelors,19,35,96,89,48,4.0,3,25,Rural,Software Engineer,55825,1 +114962,Female,21,Diploma,10,30,61,47,14,7.0,7,12,Semi-Urban,HR Executive,71582,0 +114963,Female,59,Bachelors,6,36,82,52,39,9.0,4,30,Urban,HR Executive,72336,0 +114964,Male,59,Masters,2,62,63,70,79,2.0,6,27,Semi-Urban,Manager,97465,0 +114965,Female,31,Bachelors,4,6,5,64,56,5.0,1,43,Urban,Data Analyst,30121,0 +114966,Male,52,Bachelors,11,94,3,79,7,1.0,5,69,Urban,HR Executive,131649,1 +114967,Male,52,Masters,3,56,37,18,59,4.0,3,99,Rural,Software Engineer,28610,0 +114968,Male,30,Bachelors,19,92,41,42,64,5.0,7,66,Urban,ML Engineer,82817,1 +114969,Male,45,Bachelors,0,43,49,84,3,5.0,2,57,Urban,HR Executive,97703,0 +114970,Male,45,Diploma,18,23,79,52,1,9.0,1,52,Urban,Software Engineer,93086,0 +114971,Male,38,Bachelors,13,95,34,16,2,4.0,2,11,Semi-Urban,HR Executive,113612,0 +114972,Male,54,Bachelors,15,68,82,92,41,7.0,1,99,Urban,Software Engineer,90378,1 +114973,Female,40,High School,6,42,8,56,84,9.0,6,6,Rural,Manager,132549,0 +114974,Male,36,Masters,1,13,57,70,19,7.0,4,41,Semi-Urban,Software Engineer,80882,0 +114975,Male,29,High School,15,76,4,73,66,3.0,4,15,Urban,Data Analyst,42600,0 +114976,Male,21,Bachelors,5,94,62,37,81,7.0,7,44,Semi-Urban,Software Engineer,98743,1 +114977,Male,57,Diploma,3,80,50,56,62,7.0,3,41,Semi-Urban,ML Engineer,30450,0 +114978,Male,50,Masters,18,59,50,0,17,1.0,6,99,Semi-Urban,Manager,94199,0 +114979,Male,38,Bachelors,2,47,62,20,53,2.0,2,88,Urban,Data Analyst,85495,0 +114980,Female,51,Masters,12,29,95,35,31,3.0,2,96,Urban,HR Executive,141994,1 +114981,Male,30,Bachelors,5,91,68,63,26,9.0,0,37,Urban,ML Engineer,37562,1 +114982,Male,24,Bachelors,13,72,46,83,29,8.0,1,92,Urban,Software Engineer,84090,1 +114983,Female,23,Diploma,5,34,99,72,41,6.0,0,33,Urban,Software Engineer,128107,0 +114984,Male,55,Bachelors,16,64,55,95,42,4.0,0,63,Rural,Software Engineer,95841,1 +114985,Female,30,Bachelors,15,58,28,50,19,2.0,3,90,Urban,Data Analyst,148080,0 +114986,Male,24,Bachelors,13,47,10,1,65,2.0,0,46,Urban,HR Executive,106628,0 +114987,Female,53,Bachelors,10,6,27,51,6,4.0,7,98,Urban,ML Engineer,149124,0 +114988,Male,26,Bachelors,13,35,39,39,68,8.0,0,12,Urban,ML Engineer,97979,0 +114989,Female,43,PhD,15,6,57,30,3,5.0,0,59,Rural,ML Engineer,131933,0 +114990,Male,48,High School,15,15,42,57,15,8.0,3,75,Rural,ML Engineer,51079,0 +114991,Female,30,Bachelors,9,91,3,45,47,3.0,3,7,Rural,Data Analyst,147151,0 +114992,Male,50,High School,5,85,57,80,86,7.0,1,23,Semi-Urban,Software Engineer,70016,1 +114993,Female,23,Masters,8,41,74,82,6,3.0,0,90,Urban,Manager,141324,1 +114994,Male,31,Masters,15,81,68,46,57,5.0,4,96,Urban,Manager,140002,1 +114995,Female,31,Masters,11,99,50,90,74,0.0,3,11,Semi-Urban,Software Engineer,134563,1 +114996,Other,29,Bachelors,13,19,8,36,37,9.0,0,65,Urban,ML Engineer,121727,0 +114997,Male,42,Diploma,10,3,73,43,62,8.0,0,20,Semi-Urban,HR Executive,78350,0 +114998,Male,51,Bachelors,3,4,51,84,93,7.0,7,11,Urban,Software Engineer,57014,0 +114999,Male,49,Bachelors,2,22,85,33,35,3.0,4,68,Urban,Data Analyst,92450,0 +115000,Female,37,Masters,19,77,68,62,19,2.0,3,43,Urban,Software Engineer,125493,1 +115001,Male,59,Masters,7,1,72,14,39,9.0,7,26,Urban,ML Engineer,113584,0 +115002,Female,36,Masters,1,9,50,35,63,5.0,1,84,Urban,Data Analyst,59577,0 +115003,Male,34,Bachelors,4,53,4,57,50,3.0,7,93,Rural,Software Engineer,88776,0 +115004,Female,41,Diploma,12,28,55,78,21,0.0,3,55,Rural,HR Executive,49128,0 +115005,Male,42,High School,13,80,77,88,47,0.0,2,32,Urban,Software Engineer,126866,1 +115006,Other,40,Masters,12,14,30,95,6,8.0,1,61,Urban,Data Analyst,94273,0 +115007,Male,45,High School,17,39,7,79,39,6.0,7,83,Urban,HR Executive,46818,0 +115008,Female,57,Bachelors,13,42,85,33,28,7.0,2,63,Semi-Urban,Manager,80735,0 +115009,Female,30,Bachelors,12,68,44,60,87,9.0,4,30,Urban,ML Engineer,138003,0 +115010,Female,53,Bachelors,13,97,10,47,55,3.0,0,63,Semi-Urban,HR Executive,125751,0 +115011,Male,50,Masters,7,24,94,94,59,9.0,1,77,Rural,HR Executive,106940,1 +115012,Male,29,Diploma,9,5,34,24,85,0.0,4,33,Urban,Software Engineer,76658,0 +115013,Male,23,Bachelors,17,78,92,60,8,5.0,5,92,Urban,Manager,87832,1 +115014,Male,36,Bachelors,7,38,85,88,22,5.0,2,95,Urban,Manager,55448,1 +115015,Female,22,Masters,6,57,65,87,16,8.0,2,97,Semi-Urban,Software Engineer,121662,1 +115016,Other,25,Masters,12,52,35,77,23,2.0,2,41,Urban,Data Analyst,143687,0 +115017,Male,49,PhD,18,45,67,45,52,9.0,7,35,Urban,Software Engineer,127860,0 +115018,Male,59,Masters,4,1,66,98,86,1.0,6,79,Urban,ML Engineer,131789,1 +115019,Male,33,Diploma,3,22,96,29,29,4.0,0,47,Urban,Data Analyst,132789,0 +115020,Male,50,Bachelors,14,15,61,80,74,4.0,6,4,Semi-Urban,HR Executive,54343,0 +115021,Female,46,High School,15,90,69,91,86,5.0,3,87,Urban,Software Engineer,115423,1 +115022,Male,47,Diploma,13,30,43,4,67,0.0,3,39,Urban,ML Engineer,119922,0 +115023,Female,36,Masters,14,80,33,22,0,6.0,2,65,Rural,HR Executive,91681,0 +115024,Male,48,Masters,1,27,75,8,5,8.0,0,75,Rural,HR Executive,91551,0 +115025,Female,56,Bachelors,16,6,59,75,22,6.0,5,79,Urban,Data Analyst,29730,0 +115026,Female,58,Bachelors,5,67,54,64,31,0.0,4,97,Urban,HR Executive,44224,1 +115027,Female,24,PhD,1,21,11,52,22,2.0,4,60,Rural,HR Executive,51016,0 +115028,Male,47,Bachelors,12,90,41,40,56,1.0,5,64,Semi-Urban,Software Engineer,110133,1 +115029,Female,34,Bachelors,14,8,48,5,98,2.0,4,10,Rural,Data Analyst,84584,0 +115030,Male,47,Diploma,13,14,60,84,44,6.0,0,56,Semi-Urban,HR Executive,86646,0 +115031,Male,59,Diploma,10,72,72,35,91,0.0,7,27,Semi-Urban,Manager,116818,0 +115032,Female,47,PhD,16,17,61,18,46,1.0,0,23,Rural,HR Executive,80148,0 +115033,Male,59,Bachelors,1,25,46,32,25,0.0,6,27,Semi-Urban,Manager,122472,0 +115034,Female,59,Diploma,18,92,50,4,32,7.0,1,37,Rural,Data Analyst,149061,0 +115035,Male,29,Bachelors,7,97,70,87,18,0.0,0,86,Urban,Data Analyst,47781,1 +115036,Male,41,Bachelors,2,45,19,9,53,4.0,7,71,Semi-Urban,ML Engineer,62909,0 +115037,Female,58,Masters,18,16,6,85,50,2.0,2,47,Semi-Urban,Software Engineer,103404,0 +115038,Male,35,Masters,15,62,5,73,92,4.0,7,78,Urban,ML Engineer,74644,0 +115039,Male,42,Bachelors,6,12,24,30,85,9.0,3,45,Rural,ML Engineer,87228,0 +115040,Male,36,Masters,1,42,34,78,25,6.0,5,94,Semi-Urban,HR Executive,145251,1 +115041,Female,29,Masters,18,68,46,5,59,4.0,7,52,Urban,Manager,134606,0 +115042,Male,40,Masters,15,96,98,19,82,6.0,2,8,Urban,ML Engineer,44873,0 +115043,Male,51,Masters,7,25,95,63,43,4.0,3,38,Urban,ML Engineer,101893,0 +115044,Male,30,Diploma,2,59,5,84,32,1.0,1,76,Semi-Urban,HR Executive,74472,0 +115045,Male,40,High School,2,96,29,18,89,2.0,1,31,Semi-Urban,ML Engineer,65177,0 +115046,Female,46,Masters,5,81,20,20,13,1.0,6,62,Semi-Urban,HR Executive,110671,0 +115047,Male,47,Masters,11,33,61,88,35,8.0,1,55,Urban,Manager,43015,1 +115048,Male,44,Masters,9,6,82,45,2,2.0,1,35,Urban,Software Engineer,66050,0 +115049,Other,33,Diploma,1,48,25,50,91,8.0,0,94,Rural,ML Engineer,119301,0 +115050,Female,46,Masters,15,51,0,77,11,6.0,3,44,Semi-Urban,HR Executive,81382,0 +115051,Female,50,High School,18,83,92,5,32,2.0,7,32,Semi-Urban,ML Engineer,74508,0 +115052,Female,30,Diploma,15,95,64,40,39,9.0,7,5,Rural,Manager,85727,0 +115053,Female,37,Diploma,15,13,39,78,29,6.0,4,51,Semi-Urban,Manager,24412,0 +115054,Female,41,Bachelors,19,56,75,4,19,8.0,5,81,Urban,Data Analyst,41113,0 +115055,Male,55,Diploma,7,78,63,47,40,4.0,3,71,Semi-Urban,Data Analyst,69354,1 +115056,Male,42,Bachelors,17,54,80,17,96,4.0,3,16,Urban,Software Engineer,122599,0 +115057,Male,21,Masters,6,90,21,16,17,1.0,0,45,Urban,Data Analyst,23952,0 +115058,Male,56,Bachelors,3,24,4,2,79,1.0,2,35,Urban,HR Executive,34756,0 +115059,Male,25,High School,18,1,70,76,35,2.0,7,64,Urban,Data Analyst,51811,0 +115060,Male,27,Bachelors,11,92,25,15,91,3.0,3,78,Semi-Urban,Data Analyst,27855,0 +115061,Female,56,High School,14,79,75,99,11,5.0,2,36,Semi-Urban,Data Analyst,25904,1 +115062,Male,45,High School,2,61,1,24,9,2.0,5,70,Urban,Software Engineer,63843,0 +115063,Male,35,Bachelors,10,93,53,13,98,6.0,6,96,Rural,HR Executive,33105,1 +115064,Male,59,Masters,18,42,27,16,61,9.0,6,15,Urban,Manager,39457,0 +115065,Male,42,Bachelors,10,81,66,49,66,9.0,7,71,Urban,Manager,60483,1 +115066,Female,24,High School,14,27,49,1,22,7.0,6,30,Rural,Data Analyst,54957,0 +115067,Female,54,Diploma,4,71,66,94,66,5.0,3,1,Semi-Urban,Data Analyst,31307,0 +115068,Female,57,Diploma,19,86,42,17,38,8.0,3,16,Urban,HR Executive,134888,0 +115069,Male,28,Masters,5,28,9,3,63,6.0,6,13,Urban,Software Engineer,121607,0 +115070,Male,52,PhD,1,54,24,60,93,6.0,7,58,Semi-Urban,Manager,95595,0 +115071,Male,34,High School,10,82,94,27,33,3.0,7,80,Semi-Urban,Manager,73574,1 +115072,Male,42,Bachelors,13,36,8,96,43,5.0,5,77,Rural,HR Executive,24411,0 +115073,Female,24,Diploma,8,76,99,75,79,0.0,2,9,Urban,HR Executive,74586,1 +115074,Female,28,Bachelors,0,26,83,68,58,6.0,5,92,Semi-Urban,Manager,78271,1 +115075,Male,52,Diploma,15,55,55,32,86,8.0,4,81,Rural,Software Engineer,69499,0 +115076,Female,40,Bachelors,10,7,47,81,3,2.0,3,91,Urban,HR Executive,108891,0 +115077,Female,29,High School,15,33,74,24,9,1.0,2,93,Urban,Data Analyst,88137,0 +115078,Male,29,Bachelors,12,92,34,6,48,2.0,0,83,Semi-Urban,HR Executive,62599,0 +115079,Female,28,High School,17,41,99,8,53,8.0,1,29,Urban,HR Executive,72642,0 +115080,Female,28,Bachelors,16,5,52,99,21,3.0,0,17,Urban,Manager,44658,0 +115081,Male,43,Masters,18,47,28,48,75,8.0,6,33,Urban,Software Engineer,60490,0 +115082,Other,54,Bachelors,14,85,50,41,9,8.0,5,48,Semi-Urban,Manager,76153,0 +115083,Female,43,Bachelors,17,48,94,27,59,6.0,1,88,Urban,Manager,56704,1 +115084,Male,33,Masters,4,79,33,39,74,5.0,1,94,Urban,Software Engineer,63466,1 +115085,Male,51,Masters,17,61,70,97,42,9.0,1,22,Semi-Urban,HR Executive,135415,1 +115086,Female,46,Bachelors,11,3,48,49,95,8.0,3,21,Rural,HR Executive,112471,0 +115087,Female,54,Bachelors,2,43,3,47,0,2.0,7,31,Semi-Urban,ML Engineer,56341,0 +115088,Female,45,Masters,19,26,91,93,11,1.0,3,34,Urban,Manager,70316,1 +115089,Other,26,High School,5,35,55,37,98,6.0,2,65,Semi-Urban,Manager,31421,0 +115090,Male,21,PhD,10,69,22,11,27,1.0,1,17,Rural,HR Executive,64943,0 +115091,Male,51,Bachelors,15,99,48,13,77,2.0,7,37,Urban,Manager,144799,0 +115092,Male,28,Diploma,5,60,83,88,46,6.0,5,1,Semi-Urban,Manager,33421,0 +115093,Female,44,High School,3,96,32,20,94,6.0,2,99,Urban,Software Engineer,120856,1 +115094,Male,25,Masters,2,77,64,0,74,1.0,2,84,Rural,Data Analyst,104125,0 +115095,Female,27,High School,7,33,68,63,77,3.0,6,24,Urban,Software Engineer,39103,0 +115096,Male,50,Diploma,16,39,72,49,25,6.0,0,95,Urban,Manager,83286,1 +115097,Female,33,Masters,0,46,68,52,47,7.0,3,56,Urban,Software Engineer,22924,0 +115098,Male,29,PhD,6,84,1,72,3,9.0,3,48,Urban,Software Engineer,80595,0 +115099,Female,46,Bachelors,14,1,75,15,78,0.0,5,49,Urban,Manager,104908,0 +115100,Male,32,Bachelors,12,21,75,26,56,1.0,2,23,Semi-Urban,ML Engineer,79733,0 +115101,Male,44,Bachelors,10,43,4,83,99,4.0,5,64,Urban,Data Analyst,81812,0 +115102,Female,39,Bachelors,8,50,28,80,51,7.0,1,41,Urban,Software Engineer,145043,0 +115103,Male,35,Diploma,14,20,62,39,54,2.0,3,61,Rural,ML Engineer,113195,0 +115104,Male,47,Bachelors,18,21,83,50,12,7.0,2,72,Semi-Urban,Software Engineer,104058,0 +115105,Male,22,Bachelors,16,15,31,92,6,3.0,4,97,Urban,Software Engineer,119593,1 +115106,Male,41,PhD,2,37,41,5,89,3.0,1,29,Urban,ML Engineer,27017,0 +115107,Male,22,Masters,8,73,76,68,43,4.0,3,66,Semi-Urban,Software Engineer,62794,1 +115108,Male,36,Bachelors,8,85,84,21,64,8.0,0,86,Urban,Software Engineer,31317,1 +115109,Male,30,Bachelors,7,84,12,21,59,1.0,0,28,Semi-Urban,HR Executive,21109,0 +115110,Male,39,Diploma,13,3,52,12,3,9.0,4,58,Semi-Urban,Data Analyst,20282,0 +115111,Female,58,Bachelors,4,88,92,37,70,8.0,3,90,Semi-Urban,Manager,76205,1 +115112,Female,58,Bachelors,11,0,88,82,30,7.0,2,14,Urban,ML Engineer,127322,0 +115113,Female,30,Diploma,7,61,17,35,36,6.0,5,43,Rural,Software Engineer,146672,0 +115114,Male,21,Bachelors,19,91,46,47,68,2.0,5,62,Rural,Software Engineer,120302,1 +115115,Male,40,Diploma,7,85,76,1,10,0.0,3,85,Urban,ML Engineer,24085,1 +115116,Female,57,Bachelors,14,99,11,21,95,9.0,5,9,Semi-Urban,ML Engineer,68871,0 +115117,Male,27,Bachelors,9,9,26,4,25,3.0,7,7,Rural,Manager,145972,0 +115118,Female,54,Diploma,19,93,60,85,67,0.0,0,49,Urban,Data Analyst,97579,1 +115119,Female,24,Masters,15,23,76,90,18,8.0,7,66,Rural,ML Engineer,83530,1 +115120,Male,43,Bachelors,5,20,27,54,85,4.0,2,6,Rural,Data Analyst,132433,0 +115121,Male,30,High School,14,29,34,8,71,1.0,1,3,Urban,Software Engineer,106319,0 +115122,Male,25,Masters,10,14,34,6,27,3.0,0,56,Urban,HR Executive,131736,0 +115123,Female,50,Masters,7,5,29,15,74,6.0,1,27,Urban,Manager,123126,0 +115124,Female,48,Diploma,12,45,86,99,88,1.0,4,19,Urban,HR Executive,140452,1 +115125,Male,25,Bachelors,17,36,34,21,14,8.0,0,87,Semi-Urban,HR Executive,123607,0 +115126,Male,38,Masters,7,40,58,16,42,8.0,4,14,Urban,Data Analyst,110292,0 +115127,Male,59,Bachelors,1,36,33,69,85,6.0,2,11,Urban,Manager,93053,0 +115128,Male,40,Masters,2,34,22,36,12,2.0,6,31,Urban,Manager,36412,0 +115129,Male,54,Bachelors,8,64,53,67,99,5.0,5,67,Rural,Manager,107578,1 +115130,Male,59,Bachelors,16,18,37,50,94,5.0,0,10,Urban,ML Engineer,137421,0 +115131,Male,46,Bachelors,4,92,53,19,63,0.0,2,32,Rural,HR Executive,56218,0 +115132,Female,49,Bachelors,19,60,46,89,48,7.0,2,0,Semi-Urban,Software Engineer,115858,0 +115133,Male,40,Diploma,11,76,10,21,47,6.0,4,68,Semi-Urban,Manager,128171,0 +115134,Female,50,High School,2,18,67,90,70,9.0,1,15,Rural,Software Engineer,124503,0 +115135,Male,48,Bachelors,0,24,22,30,20,2.0,3,10,Urban,Manager,138342,0 +115136,Female,32,Diploma,17,12,56,81,20,5.0,1,36,Urban,HR Executive,119101,0 +115137,Male,35,Diploma,15,74,93,47,8,1.0,3,68,Urban,Manager,69136,1 +115138,Female,37,Diploma,6,66,57,60,20,3.0,1,74,Urban,Data Analyst,136829,1 +115139,Female,48,Bachelors,18,77,98,65,69,6.0,4,75,Rural,HR Executive,71585,1 +115140,Male,53,Bachelors,14,27,30,77,61,4.0,6,48,Urban,Software Engineer,74597,0 +115141,Female,28,Bachelors,5,41,83,59,45,0.0,3,71,Urban,Data Analyst,104431,1 +115142,Male,59,Masters,2,44,11,33,9,4.0,1,0,Urban,Manager,107676,0 +115143,Female,40,High School,17,40,85,96,73,7.0,3,31,Urban,Data Analyst,36234,1 +115144,Male,41,Bachelors,7,36,29,87,0,1.0,7,68,Rural,Software Engineer,97145,0 +115145,Male,50,Diploma,0,94,55,85,44,2.0,4,63,Semi-Urban,Data Analyst,118416,1 +115146,Male,33,Masters,1,36,62,65,36,6.0,2,60,Urban,Manager,46577,0 +115147,Male,38,Masters,0,44,53,74,69,8.0,2,85,Urban,HR Executive,139950,1 +115148,Male,33,High School,17,4,29,84,38,5.0,1,92,Urban,HR Executive,89548,0 +115149,Male,43,Diploma,5,36,48,38,21,7.0,5,2,Rural,Manager,139377,0 +115150,Male,27,Masters,15,67,96,63,99,7.0,6,27,Urban,Manager,106317,1 +115151,Female,47,Bachelors,5,40,58,60,47,8.0,6,65,Urban,ML Engineer,103158,0 +115152,Male,51,Diploma,14,88,3,73,66,3.0,7,74,Urban,HR Executive,116137,1 +115153,Female,25,Diploma,8,8,67,59,70,9.0,7,96,Urban,Manager,78526,0 +115154,Male,36,Masters,5,54,94,38,20,8.0,0,56,Semi-Urban,Data Analyst,85904,1 +115155,Male,59,Diploma,6,23,40,91,52,7.0,6,45,Urban,Software Engineer,87817,0 +115156,Male,44,Masters,2,62,71,83,42,0.0,7,5,Urban,ML Engineer,60913,0 +115157,Other,58,High School,9,40,76,44,7,4.0,6,76,Urban,ML Engineer,50858,0 +115158,Female,34,Masters,14,63,61,66,36,4.0,4,74,Rural,HR Executive,35655,1 +115159,Male,51,Diploma,15,46,73,31,21,8.0,6,50,Rural,HR Executive,68507,0 +115160,Male,53,Diploma,5,23,28,54,85,6.0,0,79,Rural,ML Engineer,75058,0 +115161,Male,53,Bachelors,0,3,73,99,68,2.0,0,59,Urban,Software Engineer,70963,0 +115162,Female,26,Diploma,16,66,54,93,82,8.0,4,96,Urban,Manager,67613,1 +115163,Male,57,Bachelors,5,27,89,92,8,2.0,7,72,Semi-Urban,Data Analyst,62912,1 +115164,Male,31,Diploma,18,72,44,11,80,1.0,3,26,Semi-Urban,Software Engineer,109489,0 +115165,Male,41,Bachelors,17,95,66,47,58,8.0,7,51,Semi-Urban,Software Engineer,111117,1 +115166,Male,48,Bachelors,17,14,74,73,67,3.0,6,42,Semi-Urban,Software Engineer,47777,0 +115167,Male,33,Bachelors,7,1,55,47,92,3.0,5,10,Urban,HR Executive,78136,0 +115168,Female,31,Bachelors,7,71,82,21,32,6.0,2,77,Semi-Urban,HR Executive,115129,1 +115169,Male,42,Bachelors,19,69,87,86,86,6.0,4,59,Urban,HR Executive,102668,1 +115170,Male,46,Bachelors,6,68,72,0,5,3.0,6,45,Urban,ML Engineer,42956,0 +115171,Female,26,Bachelors,11,42,9,73,15,1.0,1,58,Urban,Manager,143218,0 +115172,Female,25,Bachelors,19,38,86,13,24,9.0,4,41,Urban,HR Executive,105923,0 +115173,Female,38,Diploma,10,46,86,53,25,3.0,1,77,Semi-Urban,Data Analyst,126456,1 +115174,Male,47,Bachelors,0,28,12,51,74,0.0,5,91,Urban,ML Engineer,127029,0 +115175,Female,39,Masters,19,89,13,60,1,4.0,4,43,Urban,Software Engineer,32547,0 +115176,Other,59,Masters,16,63,37,73,78,8.0,2,17,Semi-Urban,HR Executive,47585,0 +115177,Female,50,Masters,11,80,26,90,29,5.0,1,22,Urban,ML Engineer,42427,0 +115178,Male,21,Bachelors,10,97,12,7,10,4.0,1,58,Urban,Data Analyst,72035,0 +115179,Male,53,High School,0,46,56,74,61,8.0,7,32,Semi-Urban,Data Analyst,131977,0 +115180,Male,57,Bachelors,17,98,99,5,69,2.0,7,2,Urban,Manager,98391,0 +115181,Female,38,Diploma,11,63,28,60,8,6.0,4,60,Rural,Manager,138603,0 +115182,Male,35,Bachelors,2,12,37,4,57,3.0,7,24,Urban,Manager,105580,0 +115183,Male,51,Diploma,6,71,17,58,8,4.0,0,91,Urban,ML Engineer,56718,1 +115184,Male,39,Bachelors,10,82,9,35,30,7.0,6,29,Urban,Data Analyst,90667,0 +115185,Male,38,Bachelors,16,60,96,73,58,5.0,1,33,Urban,Software Engineer,46984,1 +115186,Male,57,Diploma,2,4,21,80,0,9.0,1,46,Urban,Software Engineer,32090,0 +115187,Female,42,Bachelors,7,4,45,80,91,2.0,5,36,Urban,Software Engineer,79244,0 +115188,Male,50,Diploma,10,60,41,61,88,3.0,3,62,Urban,Data Analyst,64846,0 +115189,Other,58,Masters,16,70,69,92,28,6.0,0,74,Semi-Urban,ML Engineer,54456,1 +115190,Male,34,Bachelors,4,54,26,20,86,0.0,1,26,Rural,Software Engineer,30054,0 +115191,Other,49,Diploma,19,26,93,58,46,1.0,0,11,Urban,Manager,55687,0 +115192,Male,57,PhD,16,0,47,86,46,7.0,4,82,Rural,Software Engineer,80043,0 +115193,Female,58,High School,17,3,90,10,34,7.0,1,70,Semi-Urban,Software Engineer,76354,0 +115194,Female,23,Bachelors,13,55,44,72,68,7.0,6,49,Semi-Urban,ML Engineer,111212,0 +115195,Male,34,Bachelors,18,71,43,99,29,8.0,4,46,Urban,ML Engineer,96577,1 +115196,Female,29,Masters,9,33,89,72,45,1.0,4,88,Urban,Manager,29501,1 +115197,Female,43,Bachelors,12,42,22,74,39,0.0,3,81,Urban,Software Engineer,74198,0 +115198,Female,41,Masters,0,13,64,79,67,9.0,4,4,Urban,ML Engineer,53788,0 +115199,Male,47,Bachelors,9,7,46,77,15,4.0,7,20,Urban,ML Engineer,143920,0 +115200,Male,58,High School,6,2,32,54,0,4.0,6,98,Semi-Urban,Software Engineer,86079,0 +115201,Male,39,Masters,13,11,34,93,45,0.0,6,30,Urban,HR Executive,33997,0 +115202,Male,47,Bachelors,15,30,48,58,43,3.0,2,48,Urban,Manager,62783,0 +115203,Male,24,High School,7,70,86,68,71,9.0,6,11,Urban,ML Engineer,36002,1 +115204,Other,41,High School,1,78,71,53,72,7.0,1,14,Urban,Software Engineer,114683,0 +115205,Male,28,Bachelors,9,4,47,27,93,7.0,3,59,Urban,Software Engineer,140092,0 +115206,Female,38,High School,10,45,96,55,0,6.0,6,9,Urban,Manager,71119,0 +115207,Male,49,Masters,7,8,39,74,48,3.0,5,61,Rural,Data Analyst,94025,0 +115208,Female,24,Bachelors,14,98,25,92,97,3.0,4,7,Semi-Urban,Software Engineer,142722,0 +115209,Male,48,Masters,4,23,31,67,21,4.0,4,57,Urban,Manager,132392,0 +115210,Female,58,Masters,11,9,10,61,84,9.0,6,94,Urban,ML Engineer,28520,0 +115211,Male,26,Masters,13,79,93,3,36,1.0,3,50,Rural,HR Executive,108569,0 +115212,Other,51,Bachelors,12,81,65,41,52,5.0,1,40,Urban,ML Engineer,131233,0 +115213,Male,24,Bachelors,1,57,88,17,38,4.0,3,11,Rural,Manager,101081,0 +115214,Male,34,Masters,8,13,95,31,34,0.0,1,15,Rural,HR Executive,34859,0 +115215,Male,46,PhD,4,7,94,88,39,0.0,1,30,Semi-Urban,Manager,82529,0 +115216,Male,28,High School,18,51,94,67,21,1.0,2,72,Semi-Urban,Software Engineer,43773,1 +115217,Male,21,Diploma,6,96,38,28,73,6.0,4,20,Rural,ML Engineer,80760,0 +115218,Male,56,Bachelors,2,27,45,84,19,6.0,2,69,Urban,ML Engineer,35223,0 +115219,Male,48,Diploma,16,31,3,21,59,9.0,1,71,Urban,Software Engineer,23316,0 +115220,Female,24,Bachelors,14,24,23,92,97,8.0,0,75,Rural,HR Executive,122811,0 +115221,Male,25,High School,4,3,39,64,58,7.0,1,83,Rural,Manager,58958,0 +115222,Female,59,Masters,11,10,91,39,91,1.0,2,96,Semi-Urban,ML Engineer,46687,0 +115223,Male,45,Bachelors,11,99,5,8,7,2.0,2,65,Semi-Urban,Manager,20787,0 +115224,Female,30,Masters,14,17,33,88,21,8.0,3,76,Urban,ML Engineer,111445,0 +115225,Male,37,High School,14,70,29,44,40,3.0,5,79,Semi-Urban,HR Executive,50979,0 +115226,Male,58,Bachelors,7,56,82,91,81,9.0,0,68,Semi-Urban,ML Engineer,87937,1 +115227,Male,46,Bachelors,18,5,66,94,16,1.0,1,90,Rural,ML Engineer,29104,1 +115228,Female,56,PhD,3,93,91,48,11,4.0,7,84,Semi-Urban,ML Engineer,106128,1 +115229,Female,27,Diploma,7,80,89,73,5,7.0,0,67,Urban,Data Analyst,79086,1 +115230,Female,59,Diploma,12,95,66,86,97,2.0,2,8,Rural,Manager,49654,1 +115231,Female,29,Masters,2,39,82,44,50,5.0,3,86,Urban,Data Analyst,136599,1 +115232,Female,26,High School,15,44,57,3,16,6.0,6,15,Urban,ML Engineer,132001,0 +115233,Other,55,Bachelors,6,54,51,34,13,0.0,4,95,Semi-Urban,Data Analyst,149100,0 +115234,Female,51,Diploma,2,51,91,70,55,7.0,2,3,Urban,Data Analyst,95393,0 +115235,Female,45,Bachelors,8,77,14,19,35,5.0,2,56,Rural,Software Engineer,121822,0 +115236,Male,51,Masters,0,99,16,13,48,6.0,6,2,Rural,ML Engineer,63176,0 +115237,Male,38,PhD,8,44,4,65,87,2.0,0,32,Rural,Data Analyst,72740,0 +115238,Male,47,PhD,0,8,72,51,21,4.0,6,82,Semi-Urban,Software Engineer,67049,0 +115239,Male,21,Bachelors,13,54,24,17,78,2.0,3,28,Urban,Software Engineer,123878,0 +115240,Male,50,Diploma,12,64,24,71,51,4.0,5,14,Rural,Data Analyst,87330,0 +115241,Male,25,Bachelors,17,2,17,37,16,8.0,2,38,Urban,Software Engineer,135600,0 +115242,Male,46,Diploma,15,36,90,10,73,6.0,3,55,Urban,Data Analyst,32980,0 +115243,Male,43,High School,9,84,68,0,58,2.0,7,61,Rural,HR Executive,146295,0 +115244,Male,46,Bachelors,16,41,10,23,16,5.0,3,75,Rural,Software Engineer,143388,0 +115245,Male,38,High School,12,61,55,18,32,5.0,0,31,Urban,HR Executive,46858,0 +115246,Male,49,High School,2,71,97,55,29,8.0,2,51,Rural,ML Engineer,31925,1 +115247,Other,56,Diploma,11,38,47,30,29,8.0,6,40,Rural,HR Executive,116188,0 +115248,Male,30,Bachelors,6,41,94,0,32,4.0,4,63,Urban,ML Engineer,88997,0 +115249,Male,53,Bachelors,0,71,0,87,88,3.0,3,79,Semi-Urban,HR Executive,27081,1 +115250,Female,45,Masters,19,54,14,70,86,4.0,2,22,Semi-Urban,ML Engineer,129157,0 +115251,Male,37,Bachelors,3,41,58,71,23,4.0,5,94,Urban,Manager,63800,1 +115252,Male,47,Masters,18,69,9,3,86,3.0,3,38,Semi-Urban,ML Engineer,146656,0 +115253,Female,59,High School,13,38,56,3,47,3.0,1,0,Rural,ML Engineer,138401,0 +115254,Male,53,High School,19,59,1,71,98,2.0,2,99,Urban,HR Executive,34173,0 +115255,Female,43,Masters,18,42,50,42,75,6.0,7,57,Urban,Manager,148237,0 +115256,Female,41,Bachelors,11,30,7,69,34,3.0,3,19,Rural,ML Engineer,36461,0 +115257,Female,49,Bachelors,2,18,70,95,66,1.0,7,25,Semi-Urban,Software Engineer,35243,0 +115258,Female,55,Bachelors,4,36,2,20,49,0.0,1,45,Rural,HR Executive,56190,0 +115259,Male,24,Diploma,4,54,28,54,76,4.0,1,78,Semi-Urban,Manager,38806,0 +115260,Male,39,High School,19,20,40,35,90,4.0,6,20,Urban,Software Engineer,83988,0 +115261,Female,36,Bachelors,2,46,84,17,38,7.0,2,17,Urban,Manager,70015,0 +115262,Female,45,Diploma,3,39,23,56,14,8.0,0,48,Semi-Urban,ML Engineer,81221,0 +115263,Male,44,Bachelors,12,20,25,23,75,3.0,4,11,Semi-Urban,ML Engineer,23681,0 +115264,Male,42,Bachelors,4,87,1,58,64,5.0,5,76,Rural,Manager,122228,0 +115265,Male,41,High School,3,8,16,67,66,7.0,7,59,Semi-Urban,ML Engineer,118346,0 +115266,Male,38,Bachelors,13,35,0,40,98,9.0,0,11,Semi-Urban,Data Analyst,76520,0 +115267,Male,22,High School,18,61,72,65,28,0.0,5,13,Rural,Data Analyst,21441,0 +115268,Female,47,Masters,19,11,99,18,92,8.0,3,22,Semi-Urban,Software Engineer,91126,0 +115269,Male,31,Masters,9,48,68,32,59,7.0,5,95,Urban,Software Engineer,52016,1 +115270,Female,36,High School,18,62,17,64,38,5.0,2,0,Semi-Urban,Manager,94438,0 +115271,Male,45,Diploma,13,44,63,24,12,5.0,1,64,Semi-Urban,ML Engineer,80295,0 +115272,Female,39,High School,0,82,38,45,82,8.0,4,90,Semi-Urban,Data Analyst,75791,1 +115273,Male,22,Bachelors,6,18,99,29,73,0.0,0,5,Rural,Software Engineer,138066,0 +115274,Male,40,Bachelors,0,68,20,46,85,3.0,1,57,Urban,HR Executive,56094,0 +115275,Male,46,Diploma,5,50,22,99,61,0.0,6,18,Urban,Manager,73100,0 +115276,Male,28,Diploma,6,82,96,90,41,9.0,5,78,Urban,Manager,96406,1 +115277,Male,21,Bachelors,11,96,55,15,52,7.0,1,97,Semi-Urban,Software Engineer,77374,1 +115278,Male,21,Masters,13,58,19,33,31,9.0,1,69,Urban,Manager,78434,0 +115279,Female,33,Bachelors,15,53,21,77,84,7.0,4,23,Semi-Urban,ML Engineer,51802,0 +115280,Male,39,Diploma,7,92,44,14,26,1.0,2,30,Semi-Urban,HR Executive,141121,0 +115281,Male,58,Bachelors,15,77,45,96,13,3.0,7,15,Urban,Manager,149917,0 +115282,Male,21,Diploma,5,71,19,31,33,9.0,7,73,Urban,ML Engineer,56159,0 +115283,Male,38,Bachelors,5,7,28,74,92,0.0,0,87,Urban,Data Analyst,69969,0 +115284,Female,48,Diploma,6,30,47,1,17,5.0,7,21,Urban,Manager,126477,0 +115285,Male,51,Diploma,7,41,58,22,60,2.0,6,41,Semi-Urban,Software Engineer,136457,0 +115286,Male,27,Diploma,16,44,17,77,20,0.0,7,83,Rural,Manager,134305,0 +115287,Male,39,High School,16,54,50,9,25,0.0,4,9,Semi-Urban,Data Analyst,139063,0 +115288,Male,21,Diploma,2,97,33,29,3,0.0,2,18,Semi-Urban,Manager,36428,0 +115289,Female,43,High School,0,30,54,46,99,6.0,2,42,Urban,Software Engineer,55813,0 +115290,Male,27,Diploma,5,82,23,31,99,9.0,2,47,Urban,ML Engineer,64186,0 +115291,Female,53,Bachelors,14,42,15,53,80,2.0,2,42,Semi-Urban,ML Engineer,68590,0 +115292,Male,46,Masters,1,78,74,97,63,9.0,5,75,Urban,Manager,56641,1 +115293,Female,46,Bachelors,19,83,3,22,52,1.0,5,69,Urban,HR Executive,100515,0 +115294,Male,58,Diploma,10,44,97,35,89,0.0,4,11,Rural,HR Executive,133260,0 +115295,Female,35,Bachelors,16,10,34,44,2,1.0,1,26,Urban,Manager,91570,0 +115296,Other,36,Bachelors,16,9,76,82,63,2.0,2,77,Urban,Software Engineer,48532,1 +115297,Female,59,Masters,17,98,14,80,99,7.0,4,69,Urban,Data Analyst,119362,1 +115298,Female,24,Bachelors,0,45,28,33,70,8.0,3,45,Semi-Urban,Data Analyst,59881,0 +115299,Male,22,Bachelors,0,90,31,48,59,3.0,1,89,Rural,HR Executive,23656,1 +115300,Female,39,Bachelors,16,49,35,85,81,6.0,0,97,Urban,Manager,101566,1 +115301,Male,41,Diploma,0,58,41,69,2,2.0,1,13,Urban,Manager,134597,0 +115302,Male,52,Masters,7,33,96,44,7,8.0,5,26,Rural,ML Engineer,80197,0 +115303,Male,47,High School,3,27,25,30,66,4.0,2,48,Urban,Software Engineer,27960,0 +115304,Male,26,Diploma,18,58,81,21,78,3.0,3,75,Urban,Software Engineer,37927,1 +115305,Male,41,Diploma,1,97,98,90,91,7.0,2,16,Semi-Urban,ML Engineer,109141,1 +115306,Female,40,Masters,17,54,17,90,43,8.0,3,38,Rural,Data Analyst,123700,0 +115307,Male,23,High School,18,89,75,67,76,0.0,0,60,Urban,ML Engineer,89240,1 +115308,Female,33,Masters,16,0,95,63,4,9.0,5,0,Urban,ML Engineer,140015,0 +115309,Male,21,Bachelors,10,96,88,72,6,4.0,1,85,Rural,HR Executive,115870,1 +115310,Male,29,Masters,3,30,82,9,88,0.0,7,54,Urban,Manager,147779,0 +115311,Female,56,PhD,12,52,85,25,77,2.0,0,46,Urban,Software Engineer,99294,0 +115312,Male,59,Diploma,10,83,90,57,86,5.0,3,9,Rural,Software Engineer,126235,1 +115313,Female,31,Bachelors,19,99,67,48,7,1.0,5,65,Urban,ML Engineer,99821,1 +115314,Female,33,Diploma,14,41,77,39,72,2.0,1,88,Urban,Data Analyst,124551,1 +115315,Male,34,Diploma,0,52,46,46,80,9.0,7,95,Semi-Urban,Data Analyst,73416,1 +115316,Female,54,PhD,13,40,14,75,72,8.0,7,17,Urban,Software Engineer,62500,0 +115317,Female,42,Bachelors,14,16,85,74,71,6.0,0,9,Semi-Urban,Software Engineer,98190,0 +115318,Male,47,Masters,2,34,18,21,20,9.0,1,80,Rural,Software Engineer,78162,0 +115319,Female,43,High School,10,99,7,68,44,0.0,0,27,Urban,Software Engineer,135679,0 +115320,Male,48,Diploma,16,57,29,93,33,5.0,1,45,Semi-Urban,Manager,35311,0 +115321,Female,36,Bachelors,3,43,5,83,1,2.0,6,14,Semi-Urban,Manager,123287,0 +115322,Male,59,Bachelors,2,20,5,19,76,5.0,7,94,Semi-Urban,Software Engineer,99889,0 +115323,Male,36,Bachelors,7,38,99,18,94,2.0,3,36,Urban,HR Executive,148605,0 +115324,Male,35,High School,3,0,81,28,5,0.0,0,40,Rural,Software Engineer,124288,0 +115325,Male,50,Bachelors,18,19,62,18,19,3.0,3,50,Urban,HR Executive,90055,0 +115326,Female,59,PhD,13,36,95,3,49,7.0,1,93,Semi-Urban,Data Analyst,107874,0 +115327,Male,44,Diploma,8,62,76,93,80,3.0,7,29,Semi-Urban,Software Engineer,128745,1 +115328,Male,21,Bachelors,2,10,70,25,78,7.0,3,3,Semi-Urban,HR Executive,120932,0 +115329,Male,43,Bachelors,8,22,21,33,68,5.0,1,37,Urban,ML Engineer,102108,0 +115330,Male,46,Diploma,17,21,77,73,22,4.0,3,45,Urban,Software Engineer,47978,0 +115331,Male,34,Diploma,0,67,2,44,3,7.0,3,67,Semi-Urban,HR Executive,54139,0 +115332,Female,54,Diploma,18,32,66,49,43,8.0,4,85,Urban,ML Engineer,30445,0 +115333,Male,55,Masters,10,53,15,60,34,2.0,6,48,Urban,Data Analyst,61974,0 +115334,Female,54,High School,5,31,87,90,7,8.0,3,71,Semi-Urban,Data Analyst,43866,1 +115335,Female,33,Diploma,3,90,96,52,90,9.0,1,70,Urban,Data Analyst,38248,1 +115336,Male,47,Masters,18,87,5,89,94,1.0,2,93,Semi-Urban,HR Executive,135117,1 +115337,Female,25,Bachelors,11,97,53,14,1,8.0,7,57,Rural,Data Analyst,55385,0 +115338,Female,42,Diploma,12,51,38,5,89,3.0,6,84,Urban,HR Executive,40085,0 +115339,Male,41,High School,16,68,95,18,78,9.0,7,37,Urban,ML Engineer,133599,0 +115340,Female,27,Diploma,15,88,30,3,94,5.0,1,76,Urban,Software Engineer,110902,0 +115341,Male,57,Masters,2,63,56,6,78,4.0,7,32,Urban,ML Engineer,50364,0 +115342,Male,33,Masters,11,69,68,32,14,7.0,3,29,Urban,HR Executive,135486,0 +115343,Female,50,Bachelors,3,76,42,91,45,2.0,1,80,Urban,ML Engineer,70329,1 +115344,Female,25,Masters,19,27,55,14,5,7.0,1,12,Urban,Software Engineer,28667,0 +115345,Male,57,High School,13,9,53,79,43,3.0,4,78,Rural,Manager,35844,0 +115346,Male,58,High School,5,51,2,6,12,6.0,4,10,Rural,HR Executive,112767,0 +115347,Female,32,High School,19,52,89,27,26,4.0,0,49,Semi-Urban,Manager,81638,0 +115348,Male,54,Bachelors,9,37,32,84,8,6.0,6,24,Semi-Urban,ML Engineer,73371,0 +115349,Male,46,Diploma,0,67,55,80,59,8.0,6,97,Semi-Urban,Software Engineer,111786,1 +115350,Male,29,High School,16,41,76,26,13,4.0,5,60,Urban,HR Executive,80382,0 +115351,Male,43,Bachelors,11,40,97,27,22,0.0,6,41,Urban,ML Engineer,91123,0 +115352,Other,57,Masters,10,30,70,24,21,5.0,2,68,Semi-Urban,Software Engineer,146412,0 +115353,Male,33,Bachelors,5,68,68,39,17,6.0,1,75,Semi-Urban,Data Analyst,105265,1 +115354,Male,50,Bachelors,3,9,72,92,15,8.0,7,91,Urban,Manager,74057,1 +115355,Male,34,Bachelors,8,20,49,34,91,1.0,4,11,Semi-Urban,ML Engineer,55107,0 +115356,Male,31,Bachelors,11,87,0,29,3,7.0,0,19,Semi-Urban,HR Executive,90245,0 +115357,Other,30,PhD,0,53,87,19,51,5.0,5,79,Semi-Urban,ML Engineer,94636,0 +115358,Male,47,Diploma,2,28,51,44,14,0.0,0,82,Rural,Manager,63078,0 +115359,Male,56,Bachelors,11,27,84,45,47,5.0,4,19,Semi-Urban,HR Executive,141576,0 +115360,Male,50,Diploma,12,82,78,61,94,2.0,4,59,Urban,Manager,85288,1 +115361,Female,50,Diploma,18,5,82,22,34,3.0,2,34,Rural,Manager,141266,0 +115362,Male,26,Masters,4,5,18,36,47,1.0,4,30,Rural,Manager,145511,0 +115363,Female,56,Diploma,2,41,4,26,73,3.0,7,88,Urban,Manager,118090,0 +115364,Male,23,High School,11,72,57,78,39,2.0,5,5,Semi-Urban,ML Engineer,86187,0 +115365,Male,48,High School,7,89,82,1,83,4.0,1,27,Urban,Software Engineer,55087,0 +115366,Male,26,Bachelors,9,29,49,61,8,7.0,5,87,Urban,Manager,67449,0 +115367,Male,49,Bachelors,19,11,42,34,23,4.0,1,93,Semi-Urban,Data Analyst,32362,0 +115368,Male,47,Masters,19,88,69,15,37,6.0,0,2,Semi-Urban,HR Executive,36879,0 +115369,Other,58,Bachelors,19,86,92,94,87,8.0,2,66,Urban,Software Engineer,61386,1 +115370,Male,57,Diploma,1,30,38,4,75,5.0,7,61,Semi-Urban,Software Engineer,130038,0 +115371,Male,45,High School,4,19,83,95,19,4.0,0,37,Urban,Manager,128331,0 +115372,Female,59,Masters,2,59,53,73,22,8.0,6,52,Semi-Urban,ML Engineer,116646,0 +115373,Male,47,Bachelors,4,37,3,59,91,6.0,3,26,Urban,Data Analyst,27845,0 +115374,Female,41,High School,5,62,29,92,70,3.0,0,8,Urban,ML Engineer,68600,0 +115375,Male,45,Masters,7,2,12,62,52,8.0,6,28,Urban,Software Engineer,117351,0 +115376,Female,33,PhD,9,36,64,49,18,6.0,7,20,Rural,Manager,84526,0 +115377,Male,41,Bachelors,14,54,2,86,22,2.0,1,71,Rural,ML Engineer,86325,0 +115378,Other,45,Masters,17,63,80,25,68,7.0,1,56,Urban,ML Engineer,115067,0 +115379,Male,51,Diploma,1,37,25,12,1,2.0,0,26,Urban,Software Engineer,57425,0 +115380,Female,28,Bachelors,3,90,48,89,80,0.0,1,88,Semi-Urban,Data Analyst,49080,1 +115381,Male,30,Bachelors,7,30,10,72,18,2.0,7,9,Rural,Data Analyst,57351,0 +115382,Male,30,High School,9,30,56,98,29,2.0,7,94,Urban,ML Engineer,38416,1 +115383,Other,29,High School,13,81,29,64,48,6.0,7,72,Semi-Urban,ML Engineer,61257,1 +115384,Female,54,Diploma,1,98,96,5,3,9.0,6,99,Rural,Data Analyst,128313,1 +115385,Female,24,Bachelors,14,85,36,62,59,3.0,2,74,Urban,Software Engineer,148719,1 +115386,Female,38,Bachelors,14,80,34,24,12,9.0,6,29,Rural,Software Engineer,75673,0 +115387,Female,49,Diploma,4,2,25,36,28,4.0,0,88,Semi-Urban,Software Engineer,59887,0 +115388,Male,35,Masters,19,95,81,26,79,6.0,2,46,Urban,ML Engineer,97295,1 +115389,Female,57,Bachelors,12,41,56,42,61,5.0,1,38,Rural,HR Executive,63457,0 +115390,Male,42,Bachelors,17,81,26,88,59,0.0,6,68,Urban,Software Engineer,100846,1 +115391,Female,27,Bachelors,16,9,23,25,79,7.0,7,63,Urban,Data Analyst,145748,0 +115392,Male,55,High School,15,29,81,1,68,4.0,1,26,Urban,HR Executive,34680,0 +115393,Female,22,Bachelors,13,28,2,24,64,9.0,7,7,Urban,Data Analyst,45335,0 +115394,Female,48,Diploma,2,34,86,84,37,4.0,3,98,Rural,Manager,109837,1 +115395,Female,52,Bachelors,6,37,0,68,73,3.0,2,13,Rural,ML Engineer,25934,0 +115396,Male,44,Bachelors,15,76,47,18,46,3.0,6,26,Urban,Data Analyst,93526,0 +115397,Female,50,Bachelors,0,85,81,15,5,0.0,4,54,Rural,Data Analyst,23980,0 +115398,Female,57,Bachelors,17,30,80,16,93,4.0,6,80,Semi-Urban,Software Engineer,102235,0 +115399,Female,40,Diploma,11,43,60,19,91,8.0,1,35,Urban,ML Engineer,101120,0 +115400,Male,56,Bachelors,9,51,71,97,2,2.0,4,92,Semi-Urban,Manager,115548,1 +115401,Male,26,Masters,13,43,40,91,54,7.0,0,75,Semi-Urban,Software Engineer,45391,1 +115402,Male,33,Bachelors,11,79,33,82,67,7.0,3,70,Semi-Urban,Software Engineer,63982,1 +115403,Male,43,Bachelors,6,45,73,73,0,6.0,3,58,Rural,ML Engineer,52296,1 +115404,Female,40,High School,14,51,35,27,95,4.0,2,92,Urban,ML Engineer,80952,0 +115405,Female,25,High School,0,59,26,62,39,4.0,2,70,Rural,Manager,84153,0 +115406,Female,40,Bachelors,6,94,56,56,48,8.0,6,53,Urban,Software Engineer,122565,1 +115407,Female,24,High School,17,50,49,43,19,7.0,5,28,Urban,Software Engineer,30559,0 +115408,Male,47,Diploma,7,36,22,50,49,1.0,5,18,Semi-Urban,ML Engineer,82711,0 +115409,Male,47,Diploma,17,22,44,44,36,2.0,2,80,Semi-Urban,Manager,90382,0 +115410,Female,42,High School,11,78,94,68,41,4.0,4,70,Urban,HR Executive,137587,1 +115411,Male,57,Bachelors,9,33,89,30,41,2.0,3,67,Urban,Data Analyst,66009,0 +115412,Male,46,Diploma,7,21,35,94,43,1.0,6,61,Urban,HR Executive,63498,0 +115413,Male,23,Bachelors,9,90,12,59,65,0.0,1,39,Urban,ML Engineer,108201,0 +115414,Male,58,Diploma,10,65,13,45,58,9.0,4,57,Urban,HR Executive,20618,0 +115415,Male,50,Bachelors,11,72,93,69,76,7.0,4,82,Rural,HR Executive,142863,1 +115416,Female,25,Bachelors,0,51,71,38,98,1.0,2,24,Rural,ML Engineer,34690,0 +115417,Female,57,High School,17,98,69,56,47,1.0,0,70,Rural,Software Engineer,66010,1 +115418,Male,30,Masters,6,17,87,28,0,5.0,1,60,Semi-Urban,Manager,104044,0 +115419,Male,37,High School,12,55,58,53,82,7.0,6,17,Urban,Data Analyst,114058,0 +115420,Male,47,Diploma,8,44,53,34,17,0.0,7,11,Semi-Urban,Manager,80307,0 +115421,Male,41,Diploma,6,23,31,58,50,0.0,1,51,Urban,Manager,102167,0 +115422,Male,40,Bachelors,1,82,3,60,41,2.0,7,49,Urban,HR Executive,69861,0 +115423,Female,54,Bachelors,1,55,94,72,18,3.0,3,43,Urban,HR Executive,61587,1 +115424,Male,32,Diploma,1,87,33,88,96,1.0,0,6,Urban,Software Engineer,47031,0 +115425,Female,55,Masters,3,12,56,85,30,9.0,5,55,Urban,Manager,133910,0 +115426,Female,51,Bachelors,7,28,70,56,62,2.0,2,15,Urban,Data Analyst,43577,0 +115427,Other,46,Bachelors,12,40,42,74,39,2.0,6,93,Urban,Software Engineer,142131,1 +115428,Male,32,Diploma,2,67,49,47,59,5.0,4,15,Rural,Manager,96564,0 +115429,Male,35,Masters,14,13,27,36,46,5.0,2,86,Rural,HR Executive,65390,0 +115430,Male,28,Bachelors,0,47,67,10,44,5.0,1,10,Urban,ML Engineer,96805,0 +115431,Female,51,High School,19,85,90,80,10,6.0,2,51,Urban,Software Engineer,111401,1 +115432,Male,24,High School,17,16,52,88,5,1.0,3,42,Semi-Urban,ML Engineer,100211,0 +115433,Other,47,High School,6,29,72,14,10,1.0,0,88,Urban,Data Analyst,127355,0 +115434,Male,29,Diploma,15,46,79,24,7,1.0,2,24,Semi-Urban,Data Analyst,130034,0 +115435,Male,35,Masters,4,99,15,88,78,2.0,4,84,Urban,ML Engineer,28764,1 +115436,Female,42,High School,6,28,5,80,9,5.0,4,64,Urban,ML Engineer,107840,0 +115437,Male,50,Bachelors,18,16,2,91,63,5.0,0,92,Urban,Software Engineer,25245,0 +115438,Female,49,High School,16,86,53,40,21,2.0,1,59,Urban,HR Executive,148421,0 +115439,Male,57,High School,9,6,43,58,20,4.0,4,57,Urban,Software Engineer,123168,0 +115440,Female,36,Masters,14,66,39,27,63,3.0,0,41,Semi-Urban,ML Engineer,143993,0 +115441,Male,39,Diploma,11,63,26,31,58,3.0,5,57,Rural,Data Analyst,86212,0 +115442,Male,28,Bachelors,19,64,67,35,54,6.0,5,54,Urban,ML Engineer,61984,0 +115443,Female,47,Bachelors,15,1,49,35,83,7.0,3,35,Semi-Urban,Manager,109641,0 +115444,Female,40,Bachelors,15,88,47,48,58,4.0,6,35,Semi-Urban,HR Executive,56777,0 +115445,Female,49,Bachelors,11,43,74,58,57,0.0,1,1,Urban,Manager,62247,0 +115446,Male,44,Bachelors,10,55,79,59,68,5.0,5,45,Rural,Manager,114062,1 +115447,Female,47,Masters,6,10,83,87,52,2.0,6,43,Urban,ML Engineer,132939,0 +115448,Male,30,Diploma,17,52,80,9,36,6.0,3,2,Semi-Urban,Manager,105126,0 +115449,Male,22,Masters,3,39,37,46,72,6.0,1,32,Urban,HR Executive,47562,0 +115450,Male,47,Masters,5,3,65,55,88,5.0,1,11,Urban,HR Executive,123433,0 +115451,Male,57,Masters,7,56,37,88,74,9.0,1,45,Urban,HR Executive,129278,0 +115452,Male,46,High School,0,99,24,50,5,6.0,3,66,Urban,Data Analyst,79754,1 +115453,Male,26,Bachelors,6,98,11,17,10,2.0,5,62,Semi-Urban,ML Engineer,69636,0 +115454,Male,33,Bachelors,2,1,21,46,7,6.0,6,80,Urban,Manager,137377,0 +115455,Female,25,Bachelors,7,32,6,7,1,8.0,0,16,Urban,Data Analyst,36722,0 +115456,Female,58,Diploma,16,69,74,92,22,8.0,6,23,Urban,HR Executive,119885,1 +115457,Male,37,Masters,1,39,77,87,29,4.0,1,11,Urban,HR Executive,49226,0 +115458,Male,30,Diploma,2,17,60,99,98,9.0,0,60,Urban,HR Executive,49350,1 +115459,Other,32,Bachelors,12,28,98,73,29,7.0,1,94,Urban,Software Engineer,55457,1 +115460,Male,55,Masters,11,45,89,4,97,4.0,4,96,Semi-Urban,HR Executive,61852,0 +115461,Female,37,Masters,9,50,87,9,34,7.0,0,6,Urban,Manager,38332,0 +115462,Other,50,Bachelors,1,78,13,24,38,0.0,5,25,Semi-Urban,ML Engineer,94819,0 +115463,Female,25,Diploma,0,31,12,2,98,5.0,1,81,Urban,Data Analyst,73043,0 +115464,Male,21,Diploma,3,53,4,77,89,7.0,6,94,Urban,Manager,40526,0 +115465,Male,33,Diploma,4,34,23,15,70,8.0,3,77,Urban,ML Engineer,112004,0 +115466,Male,21,Diploma,17,29,41,16,97,5.0,4,43,Semi-Urban,HR Executive,46548,0 +115467,Male,46,High School,15,74,17,24,40,2.0,6,60,Semi-Urban,Manager,95555,0 +115468,Male,44,High School,17,49,99,60,48,1.0,3,80,Semi-Urban,Data Analyst,70809,1 +115469,Male,24,Bachelors,1,86,69,3,28,0.0,2,64,Rural,HR Executive,142604,0 +115470,Female,45,Diploma,3,47,59,63,58,5.0,4,28,Urban,Manager,66240,0 +115471,Male,56,Diploma,13,26,76,63,85,2.0,4,78,Urban,Software Engineer,39018,1 +115472,Female,49,Bachelors,18,63,73,39,75,6.0,4,81,Urban,Manager,59671,1 +115473,Male,51,PhD,2,57,17,67,98,0.0,1,26,Rural,Software Engineer,79422,0 +115474,Male,33,Bachelors,13,82,26,61,81,6.0,1,43,Urban,Manager,68506,0 +115475,Female,59,Diploma,13,97,65,72,2,6.0,4,70,Semi-Urban,Data Analyst,48753,1 +115476,Male,46,Masters,17,13,11,36,64,1.0,2,10,Urban,HR Executive,33970,0 +115477,Female,52,Bachelors,12,20,66,35,33,7.0,6,13,Semi-Urban,ML Engineer,26129,0 +115478,Male,36,Bachelors,12,48,68,93,18,5.0,6,80,Rural,HR Executive,34001,1 +115479,Male,44,Diploma,11,79,25,52,36,1.0,6,99,Urban,Data Analyst,99765,1 +115480,Male,50,High School,12,86,40,99,77,8.0,5,71,Urban,Data Analyst,128984,1 +115481,Male,59,Masters,3,32,19,72,1,5.0,5,11,Urban,HR Executive,102347,0 +115482,Male,46,Diploma,10,6,79,54,67,1.0,2,68,Semi-Urban,Software Engineer,108122,0 +115483,Male,43,Masters,2,77,6,11,95,1.0,4,34,Urban,HR Executive,76578,0 +115484,Female,26,High School,9,3,75,69,58,0.0,4,95,Urban,Data Analyst,92134,1 +115485,Female,24,Bachelors,16,65,46,50,90,0.0,6,59,Semi-Urban,HR Executive,92553,0 +115486,Male,53,Masters,4,48,88,56,7,4.0,2,26,Rural,Manager,56164,0 +115487,Female,34,Bachelors,12,10,88,56,86,6.0,4,14,Urban,Data Analyst,62710,0 +115488,Female,38,Masters,18,46,69,92,14,8.0,2,64,Urban,Manager,63985,1 +115489,Male,45,PhD,18,5,47,2,33,3.0,1,74,Urban,Manager,87125,0 +115490,Female,38,Bachelors,17,39,96,13,16,6.0,6,11,Urban,Software Engineer,75221,0 +115491,Male,30,High School,6,69,63,15,47,2.0,2,25,Urban,Manager,42551,0 +115492,Male,47,High School,15,9,44,60,2,6.0,5,96,Semi-Urban,Manager,109892,0 +115493,Male,57,Bachelors,8,43,36,0,97,8.0,0,54,Urban,Data Analyst,32781,0 +115494,Male,25,Bachelors,1,66,98,9,76,8.0,2,37,Urban,HR Executive,149913,0 +115495,Female,56,Diploma,14,68,23,1,95,4.0,5,4,Semi-Urban,HR Executive,117910,0 +115496,Male,55,Bachelors,2,40,82,49,35,0.0,4,18,Semi-Urban,Data Analyst,98353,0 +115497,Male,22,PhD,7,57,53,41,30,5.0,6,72,Urban,Software Engineer,38689,0 +115498,Male,31,Bachelors,3,79,89,81,49,9.0,0,77,Urban,ML Engineer,126095,1 +115499,Male,40,Bachelors,11,9,89,84,10,2.0,3,45,Urban,Data Analyst,141582,0 +115500,Female,53,Bachelors,2,45,88,76,72,7.0,5,41,Semi-Urban,Software Engineer,62448,1 +115501,Female,52,Masters,13,82,79,78,65,7.0,3,67,Semi-Urban,Data Analyst,57332,1 +115502,Male,28,Bachelors,3,70,65,71,23,3.0,0,25,Urban,Manager,143231,0 +115503,Female,37,Diploma,1,95,6,53,82,2.0,4,72,Semi-Urban,Manager,128117,0 +115504,Male,32,Diploma,15,66,93,86,1,6.0,1,96,Rural,HR Executive,55874,1 +115505,Female,45,High School,2,95,45,99,14,8.0,6,20,Urban,HR Executive,118690,1 +115506,Female,47,Bachelors,1,58,2,73,97,4.0,6,84,Semi-Urban,Data Analyst,98254,0 +115507,Female,54,Masters,12,8,7,6,31,6.0,7,22,Urban,ML Engineer,124262,0 +115508,Female,35,Bachelors,19,4,25,16,95,9.0,3,30,Semi-Urban,Software Engineer,104579,0 +115509,Male,56,Diploma,0,54,32,9,68,7.0,0,81,Urban,Manager,95675,0 +115510,Male,42,Bachelors,18,80,22,90,27,3.0,3,86,Urban,Data Analyst,130028,1 +115511,Male,51,Bachelors,9,9,68,39,97,2.0,7,82,Urban,HR Executive,56989,0 +115512,Female,23,Diploma,18,89,76,97,62,0.0,2,83,Rural,ML Engineer,129264,1 +115513,Male,29,Masters,0,57,21,67,52,9.0,4,8,Rural,HR Executive,58105,0 +115514,Male,39,Bachelors,18,51,62,67,62,0.0,5,83,Urban,Manager,99094,1 +115515,Male,52,Masters,13,94,78,5,82,0.0,3,15,Rural,Data Analyst,37777,0 +115516,Female,26,Masters,6,23,47,95,17,5.0,6,62,Urban,Software Engineer,32246,0 +115517,Female,32,Diploma,10,71,36,49,53,7.0,2,96,Urban,HR Executive,104599,1 +115518,Female,48,Bachelors,14,30,25,76,27,2.0,1,0,Semi-Urban,Manager,136857,0 +115519,Male,58,Bachelors,16,9,26,17,38,6.0,1,44,Urban,Software Engineer,36004,0 +115520,Male,39,Bachelors,10,75,95,76,98,0.0,6,86,Urban,Software Engineer,112101,1 +115521,Male,56,Bachelors,10,92,14,59,17,4.0,7,3,Urban,HR Executive,133273,0 +115522,Male,43,Masters,9,52,49,38,9,3.0,1,1,Urban,Data Analyst,52075,0 +115523,Female,58,Diploma,5,39,99,33,76,7.0,6,24,Urban,HR Executive,54584,0 +115524,Female,48,High School,13,77,14,86,0,3.0,3,28,Urban,HR Executive,21843,0 +115525,Male,37,Bachelors,13,1,26,84,58,7.0,4,74,Rural,Data Analyst,57310,0 +115526,Female,42,Bachelors,18,94,76,26,78,0.0,6,1,Urban,Data Analyst,104208,0 +115527,Male,39,High School,11,15,74,3,97,9.0,7,58,Urban,HR Executive,132345,0 +115528,Male,59,Bachelors,19,15,90,48,18,1.0,3,81,Semi-Urban,Manager,28685,0 +115529,Female,31,Masters,3,41,87,9,72,3.0,6,65,Rural,Software Engineer,26534,0 +115530,Male,30,High School,4,37,83,9,38,9.0,3,31,Rural,HR Executive,104239,0 +115531,Female,44,Bachelors,16,6,13,35,24,5.0,1,12,Urban,Software Engineer,135939,0 +115532,Female,42,Masters,11,23,53,47,81,4.0,0,90,Urban,ML Engineer,93306,0 +115533,Female,41,Bachelors,10,30,79,28,30,0.0,1,63,Rural,HR Executive,104492,0 +115534,Male,26,Diploma,9,61,80,95,89,7.0,5,20,Urban,Software Engineer,37816,1 +115535,Male,44,Bachelors,5,16,97,35,7,5.0,6,57,Urban,Software Engineer,69159,0 +115536,Male,51,Diploma,0,97,7,57,44,2.0,1,52,Rural,Manager,101345,0 +115537,Female,30,Diploma,18,90,34,83,12,4.0,6,84,Semi-Urban,Data Analyst,106835,1 +115538,Male,39,Bachelors,11,16,93,62,52,9.0,1,10,Urban,ML Engineer,115946,0 +115539,Female,32,Diploma,4,25,46,36,17,8.0,2,87,Urban,ML Engineer,44338,0 +115540,Male,45,Masters,5,33,5,78,99,8.0,4,91,Rural,Manager,134738,0 +115541,Female,33,Masters,19,21,70,13,88,5.0,3,59,Urban,HR Executive,130549,0 +115542,Female,40,Bachelors,15,64,86,45,51,7.0,1,70,Urban,Manager,139493,1 +115543,Male,42,Bachelors,0,13,50,51,16,3.0,6,41,Semi-Urban,Data Analyst,95216,0 +115544,Male,45,Bachelors,11,60,70,82,46,2.0,5,78,Urban,HR Executive,115492,1 +115545,Male,31,PhD,18,62,70,55,60,0.0,4,52,Rural,Data Analyst,22405,1 +115546,Female,46,Masters,16,20,36,60,62,9.0,2,89,Urban,ML Engineer,97608,0 +115547,Female,52,High School,16,1,48,22,3,9.0,3,65,Urban,Manager,54534,0 +115548,Male,44,Bachelors,0,9,30,11,50,3.0,0,40,Urban,Data Analyst,149933,0 +115549,Male,32,Bachelors,11,65,87,76,70,0.0,1,94,Urban,HR Executive,94466,1 +115550,Male,32,High School,2,56,55,28,30,2.0,1,2,Urban,Manager,51637,0 +115551,Female,32,Bachelors,1,62,23,32,41,5.0,4,74,Semi-Urban,Manager,51498,0 +115552,Male,39,Bachelors,5,33,21,26,90,0.0,4,15,Semi-Urban,Manager,33738,0 +115553,Female,21,Diploma,10,75,6,8,43,1.0,2,65,Urban,HR Executive,126851,0 +115554,Male,25,Bachelors,10,18,92,56,94,6.0,4,4,Semi-Urban,ML Engineer,81102,0 +115555,Female,27,Bachelors,4,90,75,64,9,0.0,2,64,Urban,ML Engineer,79060,1 +115556,Male,58,Bachelors,6,87,36,41,68,1.0,2,51,Semi-Urban,Manager,76052,0 +115557,Male,46,Diploma,17,58,51,26,90,5.0,6,44,Semi-Urban,Data Analyst,121730,0 +115558,Male,49,Bachelors,7,18,42,10,12,1.0,2,41,Urban,Software Engineer,66022,0 +115559,Female,57,Masters,17,29,90,85,57,2.0,1,19,Urban,Manager,59241,0 +115560,Female,33,High School,7,67,94,29,59,4.0,4,98,Rural,Data Analyst,146591,1 +115561,Male,50,Bachelors,19,38,11,7,83,8.0,2,70,Urban,Manager,48341,0 +115562,Male,56,Diploma,3,0,35,79,51,9.0,6,93,Urban,ML Engineer,136880,0 +115563,Other,32,High School,5,16,87,79,92,7.0,7,22,Rural,Manager,79527,0 +115564,Female,35,Diploma,6,34,96,94,87,0.0,3,74,Rural,Data Analyst,61084,1 +115565,Female,26,Bachelors,3,10,88,20,73,2.0,6,93,Urban,ML Engineer,62336,0 +115566,Female,52,PhD,0,41,68,35,81,9.0,6,7,Urban,HR Executive,63602,0 +115567,Male,33,Bachelors,14,65,13,18,92,1.0,3,68,Semi-Urban,HR Executive,89267,0 +115568,Female,34,Masters,18,51,41,46,87,7.0,5,50,Rural,ML Engineer,144004,0 +115569,Male,28,Masters,14,3,23,34,13,2.0,0,71,Urban,HR Executive,79274,0 +115570,Male,53,High School,11,97,9,78,22,6.0,6,1,Urban,Manager,54318,0 +115571,Male,42,Diploma,17,25,84,29,61,3.0,1,2,Urban,HR Executive,119409,0 +115572,Male,52,Masters,16,2,98,3,16,5.0,2,13,Urban,HR Executive,147292,0 +115573,Male,57,Bachelors,7,74,37,0,67,4.0,2,35,Urban,Data Analyst,22617,0 +115574,Female,54,Diploma,2,30,67,80,1,0.0,3,41,Semi-Urban,Software Engineer,47565,0 +115575,Male,33,High School,2,2,34,67,17,9.0,2,82,Urban,Software Engineer,148491,0 +115576,Male,23,Bachelors,3,33,98,58,54,5.0,6,55,Urban,HR Executive,148095,1 +115577,Female,27,High School,2,4,29,98,59,3.0,4,38,Urban,ML Engineer,71245,0 +115578,Male,52,PhD,7,68,40,24,61,9.0,1,4,Semi-Urban,ML Engineer,108031,0 +115579,Female,35,High School,6,2,55,52,29,7.0,3,25,Semi-Urban,ML Engineer,45812,0 +115580,Male,39,High School,10,85,78,52,98,4.0,4,39,Rural,Manager,50576,1 +115581,Male,32,Diploma,19,95,24,8,52,5.0,0,87,Urban,ML Engineer,117547,0 +115582,Male,42,Bachelors,15,95,37,24,75,2.0,3,5,Urban,Data Analyst,26481,0 +115583,Male,53,Bachelors,12,29,84,0,94,4.0,0,24,Semi-Urban,ML Engineer,87638,0 +115584,Male,54,Diploma,17,36,71,70,89,5.0,5,50,Urban,Data Analyst,127449,0 +115585,Female,54,Bachelors,3,49,24,11,47,7.0,0,41,Urban,Software Engineer,138717,0 +115586,Male,27,Diploma,3,18,29,13,99,5.0,4,64,Semi-Urban,ML Engineer,97287,0 +115587,Other,47,Bachelors,10,79,68,63,25,5.0,1,97,Urban,Software Engineer,138507,1 +115588,Female,50,Bachelors,11,31,86,81,50,5.0,5,20,Semi-Urban,HR Executive,75743,0 +115589,Female,35,High School,0,11,37,55,75,5.0,0,56,Urban,Software Engineer,47339,0 +115590,Male,21,Diploma,3,23,84,0,93,5.0,7,84,Rural,HR Executive,120527,0 +115591,Male,39,High School,15,61,14,21,83,8.0,5,37,Urban,HR Executive,117345,0 +115592,Other,52,Masters,8,55,2,9,38,3.0,0,19,Semi-Urban,Software Engineer,123894,0 +115593,Male,55,Masters,12,14,64,48,77,2.0,2,47,Urban,Software Engineer,46369,0 +115594,Male,46,High School,2,81,58,94,98,1.0,2,97,Urban,Manager,37669,1 +115595,Male,40,High School,10,54,63,85,95,0.0,0,79,Rural,Manager,70497,1 +115596,Other,32,High School,15,44,17,55,53,7.0,5,99,Urban,Data Analyst,35723,0 +115597,Female,26,Bachelors,19,7,43,68,40,8.0,5,20,Rural,Software Engineer,90187,0 +115598,Male,40,Diploma,14,2,45,98,94,4.0,7,98,Rural,Data Analyst,37916,1 +115599,Male,51,Masters,13,50,99,2,5,4.0,0,91,Semi-Urban,HR Executive,134973,1 +115600,Female,27,Bachelors,13,81,39,64,83,3.0,6,75,Rural,Software Engineer,148989,1 +115601,Male,37,Bachelors,18,29,81,56,17,2.0,4,2,Rural,HR Executive,86634,0 +115602,Male,46,High School,9,17,50,15,84,4.0,1,54,Urban,Software Engineer,142978,0 +115603,Male,59,Bachelors,13,20,35,21,93,4.0,2,21,Semi-Urban,Manager,107033,0 +115604,Other,46,PhD,9,37,11,99,27,2.0,6,78,Semi-Urban,ML Engineer,104041,0 +115605,Male,46,Bachelors,8,12,22,10,91,9.0,1,48,Urban,HR Executive,37871,0 +115606,Female,39,Diploma,6,3,46,82,72,2.0,7,45,Urban,Data Analyst,94412,0 +115607,Male,30,Bachelors,3,94,41,12,87,0.0,3,78,Urban,HR Executive,96728,0 +115608,Male,28,Masters,4,64,0,50,30,1.0,3,20,Semi-Urban,Manager,96681,0 +115609,Female,54,Bachelors,1,28,77,93,56,5.0,5,19,Rural,HR Executive,30977,0 +115610,Male,33,Bachelors,1,26,13,7,69,4.0,2,73,Rural,Manager,60776,0 +115611,Male,49,High School,2,95,46,50,88,0.0,4,20,Urban,Data Analyst,124862,0 +115612,Female,37,Diploma,12,68,27,73,68,0.0,6,69,Rural,Software Engineer,50364,0 +115613,Female,48,High School,5,38,43,13,65,4.0,5,56,Urban,HR Executive,35611,0 +115614,Female,55,Bachelors,4,42,56,92,74,8.0,2,73,Urban,Software Engineer,42134,1 +115615,Male,32,Bachelors,1,14,12,96,57,3.0,4,55,Urban,Data Analyst,120891,0 +115616,Male,50,Masters,15,58,89,7,80,0.0,2,22,Urban,Data Analyst,38438,0 +115617,Female,22,High School,1,82,99,37,18,0.0,0,69,Urban,HR Executive,139008,1 +115618,Female,35,Masters,6,29,2,94,6,4.0,0,83,Semi-Urban,Manager,47042,0 +115619,Male,47,Diploma,17,69,43,51,89,7.0,3,28,Rural,Data Analyst,110359,0 +115620,Male,36,High School,6,81,87,11,4,6.0,0,29,Semi-Urban,ML Engineer,47487,0 +115621,Male,33,High School,3,56,36,97,47,5.0,4,40,Urban,Data Analyst,57222,0 +115622,Female,32,Masters,3,73,65,19,71,6.0,7,38,Urban,Software Engineer,80924,0 +115623,Male,50,Diploma,10,73,57,14,42,7.0,3,61,Urban,ML Engineer,105352,0 +115624,Male,58,Bachelors,11,17,8,9,6,6.0,3,98,Urban,HR Executive,36994,0 +115625,Female,48,Diploma,14,52,72,45,64,8.0,5,65,Rural,ML Engineer,79164,0 +115626,Female,45,Bachelors,13,3,36,2,94,7.0,2,14,Semi-Urban,Data Analyst,91981,0 +115627,Male,29,Bachelors,19,16,34,36,0,7.0,7,63,Urban,Software Engineer,122448,0 +115628,Female,34,Diploma,18,77,83,83,21,9.0,1,98,Rural,HR Executive,96141,1 +115629,Male,47,Bachelors,12,60,58,37,97,6.0,6,48,Urban,Manager,127841,0 +115630,Female,52,Bachelors,9,6,23,30,3,1.0,5,37,Urban,Software Engineer,104039,0 +115631,Other,36,Bachelors,16,93,90,34,39,9.0,3,98,Semi-Urban,ML Engineer,133391,1 +115632,Female,58,High School,17,68,72,96,34,9.0,3,81,Urban,ML Engineer,88681,1 +115633,Female,27,Masters,12,54,22,67,70,0.0,0,53,Urban,HR Executive,75703,0 +115634,Male,52,Bachelors,12,36,16,33,81,4.0,5,15,Rural,ML Engineer,108244,0 +115635,Female,23,Diploma,11,63,57,38,50,3.0,7,0,Urban,HR Executive,141769,0 +115636,Male,44,High School,17,81,27,4,39,2.0,4,25,Urban,Data Analyst,72835,0 +115637,Male,34,Diploma,5,57,55,98,81,4.0,7,25,Semi-Urban,Data Analyst,139593,1 +115638,Male,55,Masters,14,46,24,17,50,6.0,0,30,Urban,ML Engineer,75251,0 +115639,Female,40,Bachelors,16,62,91,9,91,6.0,4,62,Semi-Urban,Data Analyst,108481,0 +115640,Female,33,Bachelors,6,2,58,28,26,5.0,0,4,Urban,Manager,98420,0 +115641,Male,44,Masters,15,36,54,86,18,1.0,0,22,Rural,HR Executive,111249,0 +115642,Other,32,Diploma,11,81,38,49,33,7.0,1,53,Urban,Manager,69562,0 +115643,Male,38,Bachelors,17,53,18,85,74,0.0,6,64,Rural,Data Analyst,131905,0 +115644,Female,45,Bachelors,7,73,93,30,16,4.0,5,91,Rural,Manager,125765,1 +115645,Female,53,High School,0,33,46,6,31,2.0,7,80,Rural,ML Engineer,114168,0 +115646,Male,33,Masters,7,63,34,94,1,4.0,1,85,Urban,ML Engineer,100700,1 +115647,Other,24,Bachelors,9,45,27,87,30,6.0,1,77,Urban,Manager,143566,0 +115648,Male,30,Bachelors,19,58,84,22,42,4.0,2,14,Rural,ML Engineer,144348,0 +115649,Female,44,Masters,8,89,65,45,46,2.0,7,11,Urban,Software Engineer,89728,0 +115650,Male,33,Bachelors,12,22,96,58,43,8.0,7,38,Urban,Data Analyst,123965,0 +115651,Male,32,Masters,1,5,54,96,85,4.0,4,5,Urban,ML Engineer,58488,0 +115652,Male,53,Diploma,10,6,84,35,2,0.0,0,31,Semi-Urban,ML Engineer,98882,0 +115653,Other,45,High School,8,54,7,39,58,4.0,0,11,Rural,HR Executive,58896,0 +115654,Male,42,High School,4,10,13,85,25,5.0,5,5,Urban,Software Engineer,134615,0 +115655,Female,51,Bachelors,9,20,42,65,19,9.0,2,94,Urban,Software Engineer,144675,0 +115656,Female,54,Bachelors,13,8,88,42,61,6.0,6,91,Rural,Manager,36169,0 +115657,Male,21,Masters,2,9,38,20,75,8.0,7,31,Urban,ML Engineer,31121,0 +115658,Male,49,Bachelors,0,85,39,50,99,7.0,2,1,Urban,Manager,84298,0 +115659,Male,53,Masters,6,5,16,1,33,9.0,6,4,Urban,ML Engineer,66462,0 +115660,Female,49,Diploma,9,41,16,10,19,2.0,0,95,Urban,Data Analyst,106103,0 +115661,Male,22,Bachelors,9,75,83,21,88,9.0,6,77,Semi-Urban,Software Engineer,32305,1 +115662,Male,58,Bachelors,6,24,68,26,6,1.0,7,55,Rural,Manager,75976,0 +115663,Female,49,Bachelors,10,74,13,10,7,3.0,0,40,Urban,HR Executive,92691,0 +115664,Male,33,Diploma,5,79,53,22,51,6.0,5,55,Urban,Software Engineer,89565,0 +115665,Male,50,Masters,10,79,39,28,25,8.0,0,81,Urban,Manager,117140,0 +115666,Male,54,PhD,0,22,21,69,64,8.0,1,37,Semi-Urban,Data Analyst,56493,0 +115667,Male,29,Diploma,13,41,30,87,36,1.0,4,28,Urban,HR Executive,44505,0 +115668,Female,47,Bachelors,9,63,57,36,71,9.0,2,63,Urban,Software Engineer,21079,0 +115669,Female,27,Diploma,3,2,54,63,25,0.0,4,16,Semi-Urban,Manager,29512,0 +115670,Female,31,Diploma,16,24,55,59,17,2.0,7,92,Semi-Urban,Data Analyst,27756,0 +115671,Male,54,Bachelors,7,91,0,64,69,3.0,7,22,Urban,HR Executive,22065,0 +115672,Male,29,Masters,18,33,7,9,76,5.0,5,89,Semi-Urban,ML Engineer,87784,0 +115673,Female,54,High School,6,21,6,83,52,7.0,0,55,Urban,Manager,104469,0 +115674,Male,23,Diploma,11,97,86,18,11,1.0,3,69,Rural,Data Analyst,138563,1 +115675,Male,28,High School,2,49,52,37,56,1.0,7,9,Rural,Software Engineer,114985,0 +115676,Female,32,Bachelors,18,18,19,18,99,7.0,3,70,Urban,Manager,29557,0 +115677,Male,51,High School,7,94,36,88,86,6.0,4,79,Urban,HR Executive,149331,1 +115678,Male,49,Masters,13,66,13,82,53,3.0,6,0,Urban,Manager,56041,0 +115679,Male,59,Diploma,11,79,69,76,48,2.0,5,77,Urban,ML Engineer,39493,1 +115680,Male,23,Bachelors,16,15,28,87,23,0.0,7,92,Urban,Manager,132610,0 +115681,Female,58,Bachelors,1,27,56,58,26,6.0,2,23,Urban,HR Executive,65915,0 +115682,Male,51,High School,14,65,25,74,45,4.0,0,80,Rural,Manager,59734,1 +115683,Female,34,PhD,6,39,61,95,1,1.0,5,74,Urban,Software Engineer,71589,1 +115684,Male,42,Masters,1,81,79,54,23,8.0,5,49,Rural,ML Engineer,105566,1 +115685,Male,48,Bachelors,0,34,38,27,76,2.0,3,90,Semi-Urban,HR Executive,99945,0 +115686,Female,54,Bachelors,18,64,58,59,50,0.0,4,25,Urban,Manager,110359,0 +115687,Male,31,Bachelors,7,80,0,64,97,7.0,5,95,Urban,Data Analyst,58014,1 +115688,Female,39,Bachelors,15,34,67,84,86,0.0,6,28,Rural,HR Executive,123372,0 +115689,Male,37,Masters,2,69,41,8,18,2.0,4,7,Urban,Software Engineer,139474,0 +115690,Male,40,Diploma,7,31,80,30,38,9.0,4,77,Semi-Urban,Manager,63177,0 +115691,Male,57,Masters,19,23,16,47,95,0.0,4,99,Semi-Urban,ML Engineer,47826,0 +115692,Male,50,High School,0,48,85,47,29,8.0,2,65,Urban,HR Executive,79230,1 +115693,Male,56,Masters,1,58,50,39,28,1.0,2,29,Rural,Data Analyst,109399,0 +115694,Male,43,Bachelors,3,52,65,27,73,3.0,5,65,Semi-Urban,HR Executive,64317,0 +115695,Male,48,Masters,11,58,38,69,12,3.0,6,37,Urban,Software Engineer,143431,0 +115696,Male,34,Diploma,11,21,40,61,81,3.0,3,91,Urban,Manager,137751,0 +115697,Male,57,PhD,11,28,95,83,35,7.0,2,13,Semi-Urban,HR Executive,142745,0 +115698,Male,50,High School,13,15,30,79,36,0.0,0,57,Semi-Urban,HR Executive,28107,0 +115699,Male,55,Masters,19,32,64,60,38,6.0,0,23,Semi-Urban,Manager,56581,0 +115700,Male,51,Bachelors,3,38,63,85,27,1.0,0,99,Rural,ML Engineer,82531,1 +115701,Other,22,High School,2,36,65,57,18,7.0,0,80,Urban,Manager,137999,0 +115702,Male,42,Bachelors,7,8,17,79,58,7.0,0,83,Urban,Software Engineer,131174,0 +115703,Female,42,Masters,0,14,8,8,37,5.0,0,79,Rural,ML Engineer,81351,0 +115704,Male,23,Bachelors,8,17,9,75,22,5.0,6,37,Urban,HR Executive,121869,0 +115705,Female,50,Bachelors,13,18,5,49,33,5.0,6,27,Urban,Manager,105297,0 +115706,Female,23,High School,17,45,10,13,98,8.0,6,52,Semi-Urban,Software Engineer,68203,0 +115707,Male,31,Bachelors,0,14,85,18,64,1.0,2,76,Semi-Urban,Data Analyst,31252,0 +115708,Male,59,Bachelors,8,76,89,34,65,5.0,7,82,Urban,ML Engineer,38574,1 +115709,Male,37,Diploma,8,90,11,27,81,6.0,6,1,Urban,Manager,104819,0 +115710,Male,42,Bachelors,6,18,91,43,24,4.0,5,69,Rural,HR Executive,127313,0 +115711,Male,43,Bachelors,12,89,25,16,87,5.0,5,34,Urban,Manager,57618,0 +115712,Female,42,Bachelors,14,53,30,96,50,0.0,2,12,Rural,HR Executive,128708,0 +115713,Female,46,Bachelors,1,20,52,5,38,7.0,0,15,Urban,Data Analyst,35095,0 +115714,Female,25,Bachelors,15,15,15,7,69,2.0,3,40,Urban,Manager,128623,0 +115715,Male,47,Bachelors,8,71,97,91,41,3.0,4,68,Rural,Manager,98660,1 +115716,Female,32,Masters,19,87,62,5,13,1.0,2,75,Semi-Urban,ML Engineer,105454,0 +115717,Male,56,Bachelors,10,94,69,20,42,6.0,1,96,Urban,HR Executive,131374,1 +115718,Female,42,Diploma,15,90,64,40,25,5.0,4,49,Semi-Urban,HR Executive,91182,1 +115719,Female,51,PhD,2,0,38,95,73,4.0,1,39,Urban,Data Analyst,37464,0 +115720,Female,25,Diploma,0,9,71,37,82,8.0,7,21,Urban,Data Analyst,120978,0 +115721,Male,40,Masters,0,15,94,73,18,9.0,2,60,Rural,Software Engineer,133033,1 +115722,Male,54,Masters,2,0,81,63,83,2.0,5,31,Rural,ML Engineer,143225,0 +115723,Male,34,High School,13,53,67,47,87,5.0,6,72,Urban,Manager,130244,1 +115724,Female,55,Diploma,5,73,85,41,58,4.0,1,79,Urban,HR Executive,86906,1 +115725,Other,21,Masters,1,48,88,84,29,6.0,3,25,Urban,HR Executive,107857,1 +115726,Male,54,Masters,12,95,20,97,64,2.0,7,54,Urban,ML Engineer,30625,1 +115727,Female,36,Bachelors,15,19,84,86,3,4.0,1,39,Semi-Urban,Software Engineer,141066,0 +115728,Male,44,High School,18,19,19,43,91,7.0,7,2,Urban,Data Analyst,84826,0 +115729,Male,55,PhD,9,61,83,25,11,4.0,1,48,Urban,ML Engineer,93458,0 +115730,Female,36,Bachelors,3,63,34,31,56,1.0,6,27,Urban,Data Analyst,148769,0 +115731,Male,28,Masters,1,30,47,88,47,9.0,4,52,Urban,Manager,50528,0 +115732,Female,40,High School,12,10,85,74,78,7.0,7,26,Rural,Data Analyst,57262,0 +115733,Female,38,High School,8,45,61,34,86,2.0,7,25,Semi-Urban,Data Analyst,68805,0 +115734,Female,40,PhD,16,21,98,64,91,0.0,0,80,Semi-Urban,HR Executive,20180,1 +115735,Female,57,Masters,17,52,66,66,76,2.0,7,61,Urban,Software Engineer,97192,1 +115736,Female,57,High School,8,81,7,20,79,1.0,6,67,Urban,Software Engineer,69993,0 +115737,Female,39,Diploma,8,80,71,67,66,7.0,0,70,Urban,Data Analyst,116980,1 +115738,Male,54,Bachelors,8,72,63,10,4,1.0,5,87,Semi-Urban,Manager,51423,0 +115739,Female,35,Bachelors,4,13,40,45,8,5.0,5,94,Urban,Software Engineer,104043,0 +115740,Male,53,Masters,16,74,80,15,8,2.0,7,44,Semi-Urban,ML Engineer,27740,0 +115741,Male,24,High School,12,19,26,84,30,6.0,0,23,Urban,Manager,77210,0 +115742,Female,33,Diploma,13,23,27,49,43,0.0,0,24,Semi-Urban,Data Analyst,137831,0 +115743,Female,50,Bachelors,9,3,45,11,87,1.0,1,5,Semi-Urban,Software Engineer,51250,0 +115744,Male,22,High School,11,98,29,68,96,8.0,0,46,Urban,ML Engineer,99609,1 +115745,Male,25,Masters,15,47,73,28,20,3.0,6,68,Semi-Urban,ML Engineer,149636,0 +115746,Male,43,Bachelors,15,19,49,97,49,6.0,3,46,Rural,Manager,44132,0 +115747,Male,48,Diploma,9,86,39,47,6,6.0,4,34,Semi-Urban,Data Analyst,56484,0 +115748,Male,27,High School,1,39,22,34,72,8.0,6,91,Rural,ML Engineer,97585,0 +115749,Male,29,Bachelors,9,29,44,57,77,3.0,0,70,Rural,HR Executive,84310,0 +115750,Male,36,Diploma,0,22,23,32,90,4.0,1,57,Urban,Manager,111472,0 +115751,Male,46,Diploma,19,61,22,97,27,5.0,2,90,Rural,Data Analyst,69480,1 +115752,Male,34,Bachelors,14,10,68,85,73,7.0,3,87,Semi-Urban,Software Engineer,56305,1 +115753,Male,50,High School,14,71,81,78,47,0.0,6,20,Rural,ML Engineer,146106,1 +115754,Male,55,Bachelors,15,80,72,36,68,0.0,0,79,Urban,Software Engineer,58482,1 +115755,Male,28,Bachelors,15,92,52,27,90,9.0,2,12,Urban,HR Executive,126481,0 +115756,Other,36,Bachelors,11,57,22,3,94,5.0,1,70,Urban,Manager,41339,0 +115757,Female,51,High School,18,98,23,50,40,5.0,7,22,Semi-Urban,Manager,37598,0 +115758,Female,49,Bachelors,12,34,47,93,89,2.0,1,14,Urban,Data Analyst,142624,0 +115759,Male,36,High School,14,88,61,99,36,4.0,1,94,Urban,Software Engineer,129497,1 +115760,Female,48,Bachelors,2,2,13,70,82,1.0,2,88,Urban,Data Analyst,35962,0 +115761,Female,21,High School,11,7,10,23,16,3.0,3,94,Urban,Manager,35184,0 +115762,Male,57,Bachelors,19,68,61,99,1,2.0,2,92,Rural,Data Analyst,34751,1 +115763,Male,55,Masters,6,71,47,7,42,2.0,0,0,Rural,Data Analyst,86614,0 +115764,Male,51,Bachelors,15,21,62,63,73,1.0,0,48,Rural,ML Engineer,140816,0 +115765,Male,37,High School,8,10,40,44,5,3.0,0,54,Urban,Software Engineer,131490,0 +115766,Male,43,High School,19,54,56,37,70,2.0,6,83,Rural,ML Engineer,120339,0 +115767,Female,35,Diploma,14,59,76,35,47,4.0,6,90,Semi-Urban,Software Engineer,146380,1 +115768,Female,26,Bachelors,10,89,69,97,38,0.0,3,90,Rural,Software Engineer,47813,1 +115769,Male,24,Bachelors,19,67,71,75,58,4.0,0,65,Rural,Manager,115216,1 +115770,Female,57,Masters,16,21,57,0,15,8.0,7,7,Urban,Manager,128787,0 +115771,Male,44,Bachelors,7,48,8,48,99,2.0,5,14,Semi-Urban,ML Engineer,98544,0 +115772,Female,53,Bachelors,11,14,77,85,16,2.0,7,11,Urban,ML Engineer,29646,0 +115773,Female,34,Bachelors,3,21,89,87,83,7.0,0,10,Urban,Manager,49092,0 +115774,Female,50,Bachelors,6,53,71,99,17,5.0,3,51,Urban,Data Analyst,25798,1 +115775,Male,40,Bachelors,9,4,0,77,60,7.0,7,21,Rural,Software Engineer,94135,0 +115776,Male,22,Diploma,8,88,72,13,14,8.0,4,42,Semi-Urban,HR Executive,119476,0 +115777,Male,50,High School,11,26,61,62,40,2.0,5,60,Semi-Urban,ML Engineer,20158,0 +115778,Female,32,Bachelors,13,53,54,36,49,4.0,6,65,Semi-Urban,Data Analyst,141093,0 +115779,Male,43,Bachelors,19,66,22,18,94,8.0,6,15,Urban,HR Executive,110971,0 +115780,Male,56,Bachelors,17,93,13,65,20,6.0,2,66,Urban,Data Analyst,30401,1 +115781,Female,48,PhD,14,74,89,66,85,6.0,6,36,Semi-Urban,Manager,30655,1 +115782,Female,54,Diploma,4,41,0,26,67,4.0,0,56,Rural,HR Executive,100073,0 +115783,Female,31,Diploma,1,34,11,0,20,7.0,2,50,Urban,Data Analyst,79402,0 +115784,Male,59,Masters,5,39,57,27,8,1.0,6,87,Rural,Software Engineer,21659,0 +115785,Male,57,Bachelors,2,82,94,16,60,3.0,7,39,Urban,Manager,65571,0 +115786,Female,23,PhD,10,30,92,87,49,4.0,6,69,Urban,ML Engineer,141395,1 +115787,Female,46,Diploma,7,54,76,37,49,3.0,1,97,Urban,Manager,30591,1 +115788,Male,40,Masters,13,27,78,7,17,7.0,6,74,Semi-Urban,ML Engineer,71376,0 +115789,Female,24,Bachelors,10,86,13,57,96,1.0,3,85,Semi-Urban,ML Engineer,130083,1 +115790,Male,23,Bachelors,19,29,71,85,65,5.0,7,31,Rural,HR Executive,129238,0 +115791,Female,30,Bachelors,2,80,28,36,88,6.0,2,94,Urban,Data Analyst,144129,0 +115792,Male,57,Bachelors,0,49,84,9,71,7.0,5,1,Semi-Urban,Data Analyst,24403,0 +115793,Female,37,Bachelors,15,97,55,37,94,0.0,0,70,Semi-Urban,HR Executive,24631,1 +115794,Male,27,Bachelors,1,18,68,1,19,2.0,3,32,Semi-Urban,HR Executive,97073,0 +115795,Female,52,Bachelors,6,74,99,47,31,4.0,0,58,Urban,Data Analyst,90376,1 +115796,Male,22,Bachelors,18,32,18,92,88,9.0,1,8,Urban,Manager,70731,0 +115797,Female,58,Diploma,6,43,52,13,98,8.0,0,81,Rural,HR Executive,91073,0 +115798,Other,41,Bachelors,3,58,36,13,47,4.0,3,44,Urban,HR Executive,66924,0 +115799,Male,40,Masters,16,49,21,51,93,3.0,1,93,Rural,HR Executive,114962,0 +115800,Male,38,Masters,10,38,70,8,45,3.0,6,2,Urban,HR Executive,101095,0 +115801,Male,57,Diploma,7,19,97,56,37,8.0,5,84,Urban,Manager,30294,1 +115802,Other,51,Diploma,14,67,5,76,27,0.0,2,47,Urban,ML Engineer,24357,0 +115803,Female,31,Diploma,1,17,34,16,8,3.0,1,41,Rural,Data Analyst,32036,0 +115804,Other,21,Bachelors,2,96,95,37,39,7.0,1,82,Semi-Urban,HR Executive,73556,1 +115805,Female,41,Bachelors,8,38,24,21,4,4.0,6,37,Urban,Data Analyst,99516,0 +115806,Female,39,Bachelors,10,54,4,65,23,9.0,6,29,Urban,Data Analyst,128131,0 +115807,Male,37,Bachelors,7,53,78,1,16,3.0,5,78,Rural,HR Executive,97739,0 +115808,Female,59,Bachelors,9,57,33,12,73,4.0,5,77,Urban,Manager,28669,0 +115809,Female,37,Bachelors,14,11,33,9,84,0.0,0,76,Semi-Urban,ML Engineer,138582,0 +115810,Male,22,Bachelors,14,28,41,2,39,4.0,6,69,Semi-Urban,HR Executive,48874,0 +115811,Male,40,Bachelors,3,51,36,97,34,8.0,6,51,Semi-Urban,Data Analyst,141003,1 +115812,Other,43,Masters,1,42,32,88,38,0.0,3,76,Urban,HR Executive,65695,0 +115813,Male,57,Bachelors,2,86,88,65,51,1.0,2,56,Urban,Data Analyst,101661,1 +115814,Female,45,High School,7,12,26,12,53,3.0,5,93,Semi-Urban,Software Engineer,56947,0 +115815,Female,55,Bachelors,15,51,23,59,60,0.0,5,82,Urban,HR Executive,65080,0 +115816,Male,40,Diploma,17,16,44,64,18,1.0,4,75,Urban,Software Engineer,37876,0 +115817,Other,21,Masters,1,88,74,37,37,9.0,2,94,Urban,Data Analyst,22033,1 +115818,Male,40,High School,9,91,45,62,64,4.0,2,19,Urban,Data Analyst,108992,0 +115819,Female,58,Bachelors,14,98,99,18,31,4.0,4,70,Semi-Urban,Data Analyst,123749,1 +115820,Male,28,Bachelors,3,21,56,40,40,9.0,3,57,Urban,ML Engineer,52923,0 +115821,Male,56,Masters,6,98,18,39,65,4.0,2,11,Urban,Data Analyst,20858,0 +115822,Male,21,High School,17,37,35,24,80,0.0,5,87,Urban,Manager,107964,0 +115823,Female,29,Bachelors,19,87,19,0,87,5.0,2,3,Semi-Urban,Data Analyst,112358,0 +115824,Female,54,Diploma,13,19,2,84,76,8.0,3,40,Urban,Manager,72051,0 +115825,Female,43,High School,19,62,12,76,98,7.0,2,95,Urban,HR Executive,96094,1 +115826,Male,31,Bachelors,6,85,95,27,42,0.0,1,91,Urban,Manager,79458,1 +115827,Male,58,Bachelors,10,67,38,35,91,2.0,5,62,Semi-Urban,Manager,36476,0 +115828,Female,31,Masters,7,83,30,30,67,0.0,5,61,Urban,Data Analyst,78686,0 +115829,Male,41,PhD,17,35,73,44,36,6.0,3,60,Urban,Data Analyst,39751,0 +115830,Male,27,Bachelors,6,72,70,60,21,6.0,5,83,Rural,ML Engineer,27875,1 +115831,Male,48,Diploma,19,28,2,20,30,7.0,6,74,Rural,HR Executive,50370,0 +115832,Female,29,Diploma,4,81,67,54,67,6.0,0,57,Rural,Manager,52567,1 +115833,Male,54,Masters,16,49,60,65,65,8.0,7,96,Rural,HR Executive,42312,1 +115834,Male,37,Bachelors,14,18,30,23,5,4.0,0,67,Urban,ML Engineer,131230,0 +115835,Male,46,High School,16,6,10,25,37,5.0,1,43,Urban,HR Executive,136271,0 +115836,Female,59,Masters,7,5,28,26,65,5.0,6,16,Rural,HR Executive,101814,0 +115837,Male,30,Masters,10,15,39,44,0,6.0,7,50,Urban,Manager,142605,0 +115838,Male,42,Masters,13,43,67,92,89,0.0,5,15,Urban,Data Analyst,20670,0 +115839,Female,38,Diploma,2,87,65,89,56,5.0,6,18,Urban,Data Analyst,94887,1 +115840,Male,47,Masters,15,53,8,19,93,7.0,0,46,Urban,HR Executive,40376,0 +115841,Other,44,High School,10,50,48,84,13,7.0,7,36,Semi-Urban,Software Engineer,26737,0 +115842,Male,38,Bachelors,15,89,56,45,67,4.0,4,53,Semi-Urban,HR Executive,94495,1 +115843,Male,29,High School,12,5,54,93,99,6.0,5,8,Urban,ML Engineer,71980,0 +115844,Male,58,Bachelors,8,63,99,9,95,2.0,5,18,Urban,Data Analyst,99672,0 +115845,Female,23,Masters,12,46,55,66,44,4.0,2,27,Urban,ML Engineer,89095,0 +115846,Female,26,Bachelors,8,69,90,42,58,6.0,2,53,Rural,Software Engineer,113927,1 +115847,Female,38,Bachelors,5,8,74,12,60,3.0,4,9,Semi-Urban,Data Analyst,96476,0 +115848,Female,55,High School,4,18,59,15,30,1.0,0,74,Urban,HR Executive,114786,0 +115849,Male,26,PhD,17,45,77,42,81,2.0,0,5,Rural,Software Engineer,52581,0 +115850,Female,30,High School,13,86,50,15,78,5.0,6,10,Urban,Software Engineer,107564,0 +115851,Male,47,High School,6,58,36,63,53,6.0,0,46,Urban,Manager,55440,0 +115852,Male,47,Masters,19,13,80,28,74,8.0,5,44,Urban,Data Analyst,102270,0 +115853,Female,47,Bachelors,18,65,55,16,77,6.0,2,42,Urban,Manager,63295,0 +115854,Male,36,Bachelors,14,64,64,8,83,6.0,1,28,Urban,Data Analyst,61170,0 +115855,Female,51,Bachelors,2,22,23,36,19,0.0,3,38,Urban,Data Analyst,20004,0 +115856,Male,57,Bachelors,9,82,60,54,79,6.0,7,47,Urban,ML Engineer,45877,1 +115857,Male,54,Bachelors,8,74,9,2,33,4.0,3,82,Rural,Software Engineer,140239,0 +115858,Male,35,Bachelors,6,28,97,66,60,9.0,3,90,Rural,Software Engineer,73083,1 +115859,Female,52,Bachelors,0,47,77,19,12,3.0,6,58,Urban,Software Engineer,116211,0 +115860,Male,29,Masters,14,45,60,40,62,9.0,5,64,Urban,Data Analyst,59813,0 +115861,Male,43,Diploma,2,72,7,53,4,8.0,4,60,Urban,HR Executive,98049,0 +115862,Female,51,Diploma,15,54,29,94,43,4.0,1,39,Semi-Urban,HR Executive,51376,0 +115863,Female,34,High School,4,46,60,39,80,7.0,3,73,Semi-Urban,HR Executive,72606,0 +115864,Male,42,Bachelors,10,12,38,90,99,2.0,1,54,Rural,Data Analyst,104642,0 +115865,Male,33,Diploma,1,87,64,59,84,6.0,4,11,Urban,HR Executive,61270,0 +115866,Male,49,Diploma,11,42,38,4,73,0.0,0,9,Urban,Data Analyst,45288,0 +115867,Female,47,High School,17,54,79,25,11,4.0,7,78,Urban,Data Analyst,27725,0 +115868,Male,28,Bachelors,8,78,78,91,24,8.0,2,57,Urban,Software Engineer,107796,1 +115869,Male,44,Bachelors,17,29,50,22,92,0.0,3,56,Rural,Data Analyst,76569,0 +115870,Female,49,Bachelors,10,19,85,54,31,3.0,1,7,Urban,Software Engineer,123164,0 +115871,Male,31,Bachelors,12,7,89,48,54,8.0,4,75,Semi-Urban,Data Analyst,105617,0 +115872,Male,21,Diploma,12,47,10,65,77,4.0,5,28,Rural,ML Engineer,73109,0 +115873,Female,39,Diploma,4,61,14,33,44,6.0,5,74,Semi-Urban,Software Engineer,37665,0 +115874,Male,33,Bachelors,13,0,72,17,33,1.0,1,21,Semi-Urban,Manager,76841,0 +115875,Male,35,Diploma,0,16,56,18,22,9.0,0,99,Urban,Data Analyst,148583,0 +115876,Female,30,Diploma,11,76,69,94,71,7.0,6,41,Urban,Data Analyst,65980,1 +115877,Male,40,Masters,15,93,69,12,33,1.0,1,44,Urban,ML Engineer,76135,0 +115878,Male,57,High School,14,41,12,12,86,0.0,5,37,Semi-Urban,Software Engineer,60515,0 +115879,Female,58,Diploma,16,77,1,19,52,2.0,4,41,Rural,Data Analyst,31192,0 +115880,Female,30,High School,6,63,44,21,59,3.0,0,22,Urban,Software Engineer,141241,0 +115881,Male,35,High School,16,61,70,13,8,5.0,7,67,Semi-Urban,Data Analyst,68862,0 +115882,Male,34,Diploma,1,49,37,61,6,9.0,7,73,Semi-Urban,HR Executive,115004,0 +115883,Male,30,High School,3,37,13,23,47,6.0,7,45,Rural,Manager,128255,0 +115884,Female,50,Diploma,18,12,24,77,39,3.0,6,59,Semi-Urban,Data Analyst,28682,0 +115885,Female,55,Bachelors,10,21,65,81,55,3.0,0,68,Rural,ML Engineer,59893,0 +115886,Other,50,Diploma,16,26,29,47,77,6.0,0,31,Rural,Software Engineer,112162,0 +115887,Male,41,Diploma,6,79,55,14,50,8.0,5,16,Urban,Manager,95568,0 +115888,Female,50,Bachelors,4,1,27,71,61,9.0,5,71,Semi-Urban,HR Executive,121987,0 +115889,Female,46,Bachelors,13,1,82,94,63,5.0,2,78,Semi-Urban,Manager,108649,1 +115890,Female,59,Diploma,7,33,5,50,9,9.0,7,64,Semi-Urban,Software Engineer,61600,0 +115891,Female,44,Bachelors,18,68,90,17,98,2.0,7,71,Urban,Manager,125341,1 +115892,Male,43,Bachelors,12,10,34,99,27,9.0,2,81,Semi-Urban,HR Executive,142134,0 +115893,Male,35,High School,10,43,68,81,59,9.0,6,5,Urban,ML Engineer,69018,0 +115894,Male,57,Diploma,17,49,94,49,62,5.0,2,62,Semi-Urban,Data Analyst,77765,1 +115895,Male,55,Bachelors,11,59,15,94,31,8.0,5,1,Rural,ML Engineer,125921,0 +115896,Male,50,Bachelors,13,85,66,91,10,1.0,2,8,Urban,Manager,61899,1 +115897,Female,33,Masters,17,94,73,86,52,0.0,1,7,Urban,Data Analyst,83001,1 +115898,Male,35,Bachelors,18,50,31,40,67,2.0,5,24,Urban,Software Engineer,24913,0 +115899,Female,42,Bachelors,15,97,57,49,31,3.0,6,61,Semi-Urban,Manager,97823,1 +115900,Male,34,Bachelors,1,33,17,92,6,1.0,7,88,Urban,HR Executive,140077,0 +115901,Male,24,Diploma,9,75,42,39,80,6.0,7,73,Urban,Software Engineer,120514,0 +115902,Male,42,Diploma,5,44,53,75,44,7.0,6,18,Urban,Software Engineer,135076,0 +115903,Other,45,PhD,2,73,68,68,16,6.0,1,56,Rural,ML Engineer,149822,1 +115904,Other,44,Bachelors,17,24,27,66,95,2.0,6,21,Semi-Urban,ML Engineer,134765,0 +115905,Female,32,Diploma,7,63,20,2,17,3.0,1,24,Urban,ML Engineer,84943,0 +115906,Male,48,Diploma,1,1,1,15,63,6.0,2,4,Semi-Urban,Software Engineer,40987,0 +115907,Male,28,High School,16,61,72,15,17,0.0,1,35,Semi-Urban,Data Analyst,141470,0 +115908,Other,36,High School,8,50,98,65,29,1.0,7,68,Semi-Urban,ML Engineer,78069,1 +115909,Female,23,Diploma,16,35,55,29,65,2.0,6,43,Urban,Data Analyst,109012,0 +115910,Female,52,Masters,17,72,66,80,6,3.0,5,2,Rural,HR Executive,23202,0 +115911,Female,59,High School,5,29,29,93,96,6.0,4,31,Urban,Manager,127648,0 +115912,Female,29,Bachelors,15,53,62,99,36,9.0,3,82,Urban,ML Engineer,106635,1 +115913,Male,55,Diploma,0,69,88,95,74,3.0,1,83,Semi-Urban,Software Engineer,43731,1 +115914,Male,39,Diploma,5,11,41,91,47,6.0,1,14,Semi-Urban,Manager,143241,0 +115915,Male,29,Masters,19,19,23,44,85,4.0,2,12,Semi-Urban,Manager,76515,0 +115916,Male,42,Bachelors,10,79,32,67,75,7.0,4,29,Urban,Data Analyst,126062,0 +115917,Other,45,Bachelors,16,60,6,94,79,5.0,7,17,Rural,Software Engineer,43322,0 +115918,Male,34,Bachelors,17,10,28,89,73,1.0,2,36,Semi-Urban,HR Executive,140471,0 +115919,Male,24,Bachelors,5,69,66,3,20,5.0,2,11,Urban,ML Engineer,68635,0 +115920,Male,54,Diploma,18,81,20,3,49,2.0,3,48,Semi-Urban,HR Executive,91211,0 +115921,Male,54,High School,12,80,96,44,20,4.0,7,59,Urban,HR Executive,32418,1 +115922,Male,22,Diploma,17,28,48,7,7,1.0,7,65,Semi-Urban,HR Executive,54804,0 +115923,Female,41,Masters,7,11,79,35,4,0.0,7,4,Urban,Data Analyst,24827,0 +115924,Male,34,High School,4,94,11,65,3,3.0,2,44,Urban,Data Analyst,45813,0 +115925,Male,30,Masters,14,5,21,0,78,5.0,0,97,Rural,HR Executive,59943,0 +115926,Female,46,Masters,15,0,89,38,31,3.0,2,12,Rural,HR Executive,79463,0 +115927,Female,39,Diploma,12,26,58,18,23,5.0,6,32,Urban,HR Executive,100129,0 +115928,Male,41,Bachelors,15,15,81,57,94,8.0,2,63,Urban,Data Analyst,106128,0 +115929,Male,42,Masters,9,42,83,31,72,1.0,1,46,Rural,Data Analyst,135952,0 +115930,Male,23,Diploma,6,93,15,39,55,9.0,6,75,Semi-Urban,HR Executive,68944,0 +115931,Male,34,Diploma,0,90,27,73,69,9.0,4,22,Semi-Urban,Data Analyst,29384,0 +115932,Male,50,Masters,19,67,42,29,69,8.0,3,14,Urban,HR Executive,46484,0 +115933,Female,49,Masters,4,87,26,29,81,4.0,7,41,Semi-Urban,HR Executive,116950,0 +115934,Male,41,PhD,1,92,4,35,45,3.0,7,30,Urban,ML Engineer,106628,0 +115935,Male,30,Bachelors,4,49,39,35,50,0.0,7,45,Urban,Data Analyst,114403,0 +115936,Male,33,Diploma,16,22,23,49,64,5.0,3,56,Urban,Data Analyst,107015,0 +115937,Female,21,Bachelors,0,93,81,97,30,2.0,0,32,Semi-Urban,HR Executive,46327,1 +115938,Female,30,Diploma,7,51,15,21,36,1.0,4,76,Urban,Manager,116988,0 +115939,Male,25,Diploma,6,22,18,93,11,3.0,6,2,Rural,Data Analyst,82369,0 +115940,Male,21,Bachelors,9,24,89,16,12,8.0,0,72,Semi-Urban,Data Analyst,107030,0 +115941,Female,23,Masters,7,43,59,34,71,1.0,2,18,Urban,HR Executive,44394,0 +115942,Male,35,Bachelors,4,34,75,38,34,6.0,2,35,Urban,Data Analyst,60121,0 +115943,Male,42,Bachelors,11,2,89,27,60,2.0,6,71,Rural,ML Engineer,62307,0 +115944,Male,57,Diploma,3,82,40,8,78,7.0,5,30,Semi-Urban,Software Engineer,96995,0 +115945,Female,50,PhD,0,26,47,29,85,5.0,1,34,Urban,Software Engineer,146814,0 +115946,Male,37,Bachelors,18,41,78,60,62,4.0,0,27,Semi-Urban,Software Engineer,126270,0 +115947,Female,52,Diploma,10,45,39,60,46,5.0,0,77,Urban,Manager,119319,0 +115948,Male,43,Bachelors,2,15,99,82,23,1.0,2,51,Urban,Manager,128263,1 +115949,Male,37,Bachelors,13,79,25,28,4,5.0,0,70,Semi-Urban,HR Executive,63688,0 +115950,Male,45,Bachelors,6,39,41,28,39,3.0,2,10,Rural,Data Analyst,40140,0 +115951,Other,55,PhD,0,28,86,15,75,8.0,2,91,Rural,Manager,60978,0 +115952,Male,32,Bachelors,18,43,64,83,68,6.0,2,54,Urban,Data Analyst,75378,1 +115953,Male,21,High School,2,74,86,90,59,5.0,5,69,Urban,ML Engineer,100873,1 +115954,Male,41,Bachelors,5,45,13,35,62,6.0,6,31,Semi-Urban,ML Engineer,89337,0 +115955,Male,56,Bachelors,12,46,90,46,61,9.0,4,30,Urban,Data Analyst,131817,0 +115956,Female,55,Diploma,11,1,95,41,4,6.0,1,27,Urban,ML Engineer,118849,0 +115957,Male,43,Masters,0,77,43,57,10,8.0,2,13,Urban,HR Executive,126616,0 +115958,Male,57,Masters,12,33,88,62,95,6.0,2,93,Semi-Urban,Data Analyst,82634,1 +115959,Female,38,Bachelors,3,30,20,41,17,9.0,0,24,Urban,Manager,131783,0 +115960,Male,43,Masters,1,81,81,22,88,3.0,4,85,Urban,Software Engineer,106318,1 +115961,Other,44,Bachelors,2,36,67,88,35,3.0,1,21,Semi-Urban,Software Engineer,54172,0 +115962,Male,57,Bachelors,14,65,45,53,39,2.0,0,95,Urban,Manager,100865,1 +115963,Male,33,Bachelors,3,13,3,76,37,3.0,1,8,Semi-Urban,Manager,87346,0 +115964,Male,53,Masters,0,39,74,97,80,8.0,6,98,Urban,Software Engineer,135660,1 +115965,Female,42,Masters,5,17,29,0,68,5.0,4,10,Rural,Data Analyst,78682,0 +115966,Male,54,Diploma,10,60,20,57,18,6.0,6,16,Urban,ML Engineer,130572,0 +115967,Female,54,Diploma,14,55,20,14,61,8.0,4,96,Urban,Data Analyst,47353,0 +115968,Female,45,High School,4,95,10,87,61,2.0,4,64,Urban,ML Engineer,148917,1 +115969,Other,55,PhD,4,8,70,83,3,7.0,1,17,Rural,Software Engineer,49516,0 +115970,Male,56,Diploma,2,36,47,25,48,2.0,7,49,Urban,HR Executive,140200,0 +115971,Male,32,Bachelors,14,73,70,50,73,4.0,2,2,Semi-Urban,HR Executive,44166,0 +115972,Female,50,Bachelors,19,33,34,81,44,1.0,1,12,Urban,ML Engineer,146515,0 +115973,Male,25,Diploma,4,73,34,9,20,8.0,4,14,Urban,ML Engineer,119617,0 +115974,Female,33,Bachelors,8,50,38,55,24,1.0,0,32,Urban,Manager,80543,0 +115975,Male,40,Diploma,6,27,50,84,94,2.0,4,60,Rural,ML Engineer,87872,0 +115976,Male,23,Bachelors,11,25,73,56,41,7.0,7,87,Urban,Software Engineer,118831,1 +115977,Male,46,Diploma,8,30,29,79,75,4.0,7,7,Rural,HR Executive,124911,0 +115978,Male,24,Diploma,2,20,8,75,71,7.0,5,16,Rural,HR Executive,148577,0 +115979,Female,53,Masters,6,82,73,68,55,8.0,5,28,Urban,Software Engineer,61534,1 +115980,Other,58,High School,3,33,85,18,83,4.0,3,85,Rural,Software Engineer,95842,0 +115981,Female,42,Bachelors,12,22,23,34,46,4.0,1,33,Urban,ML Engineer,78303,0 +115982,Male,47,High School,8,40,82,5,64,1.0,1,79,Urban,Manager,75560,0 +115983,Male,42,Diploma,9,62,69,59,12,7.0,4,44,Urban,Software Engineer,122513,0 +115984,Male,44,Masters,7,64,10,43,85,3.0,7,66,Urban,Software Engineer,93407,0 +115985,Male,37,Bachelors,2,16,95,0,92,5.0,3,62,Urban,Manager,49791,0 +115986,Female,48,Masters,19,52,41,65,83,0.0,4,38,Rural,Data Analyst,107531,0 +115987,Male,52,Diploma,11,16,22,67,37,2.0,7,95,Rural,HR Executive,93719,0 +115988,Male,43,Masters,7,28,92,8,50,6.0,0,98,Urban,ML Engineer,44367,0 +115989,Male,51,Bachelors,18,97,83,43,92,5.0,1,3,Rural,ML Engineer,22608,0 +115990,Female,52,Masters,15,24,92,35,12,6.0,5,11,Semi-Urban,Manager,132017,0 +115991,Female,38,Masters,7,2,90,31,42,2.0,2,86,Urban,Data Analyst,58757,0 +115992,Male,44,Bachelors,1,48,76,27,92,4.0,3,35,Urban,ML Engineer,82894,0 +115993,Male,29,Masters,13,28,7,28,32,2.0,5,16,Urban,Data Analyst,58794,0 +115994,Female,39,Bachelors,8,23,58,65,15,6.0,5,0,Urban,Manager,145311,0 +115995,Male,38,High School,1,66,99,0,98,8.0,6,67,Rural,Data Analyst,34783,0 +115996,Male,52,Masters,1,3,70,79,83,0.0,4,13,Urban,Software Engineer,100625,0 +115997,Female,50,Bachelors,2,50,85,34,2,6.0,1,82,Semi-Urban,Software Engineer,53454,1 +115998,Male,41,Masters,8,4,45,51,75,6.0,7,27,Rural,Software Engineer,113160,0 +115999,Male,44,Diploma,1,63,17,73,92,9.0,4,0,Urban,HR Executive,98815,0 +116000,Male,32,Bachelors,13,73,31,7,34,0.0,6,82,Semi-Urban,HR Executive,86530,0 +116001,Female,26,Bachelors,9,72,31,44,21,4.0,3,96,Urban,HR Executive,109462,1 +116002,Male,44,Bachelors,13,80,17,58,62,9.0,3,31,Semi-Urban,Software Engineer,69304,0 +116003,Female,59,Bachelors,7,36,83,85,24,5.0,3,14,Urban,Manager,105389,0 +116004,Male,55,Masters,13,2,65,48,86,4.0,5,6,Semi-Urban,HR Executive,53415,0 +116005,Male,59,Bachelors,11,79,85,63,15,7.0,2,54,Rural,Data Analyst,63455,1 +116006,Male,31,Diploma,11,72,60,28,49,0.0,5,41,Rural,HR Executive,95096,0 +116007,Female,37,PhD,12,2,53,80,13,2.0,1,49,Urban,ML Engineer,79896,0 +116008,Female,26,High School,9,30,91,54,41,2.0,6,89,Rural,ML Engineer,31426,1 +116009,Male,59,Bachelors,19,44,53,15,50,0.0,3,21,Semi-Urban,Data Analyst,70238,0 +116010,Male,31,Bachelors,10,80,16,62,48,1.0,6,22,Semi-Urban,Software Engineer,85238,0 +116011,Female,54,PhD,3,0,79,6,49,7.0,1,94,Semi-Urban,Data Analyst,55804,0 +116012,Male,26,High School,15,80,74,18,79,4.0,0,44,Urban,ML Engineer,74206,0 +116013,Female,45,Masters,5,51,63,35,13,6.0,7,23,Semi-Urban,Manager,129512,0 +116014,Male,53,High School,1,56,15,73,76,3.0,4,87,Urban,Software Engineer,71336,0 +116015,Female,51,Bachelors,19,16,82,43,8,7.0,2,77,Semi-Urban,Manager,143239,0 +116016,Male,37,Masters,5,6,16,64,55,5.0,2,19,Rural,Data Analyst,60593,0 +116017,Female,50,Diploma,6,79,34,32,27,0.0,6,44,Urban,HR Executive,47854,0 +116018,Male,37,Diploma,11,93,18,17,81,4.0,7,33,Urban,Software Engineer,109772,0 +116019,Male,36,Diploma,19,65,17,6,7,2.0,4,87,Urban,HR Executive,71076,0 +116020,Male,52,Masters,3,93,22,90,10,2.0,7,18,Semi-Urban,Software Engineer,112789,0 +116021,Male,49,Bachelors,18,63,10,40,11,6.0,0,54,Urban,Manager,139642,0 +116022,Male,43,Bachelors,15,93,61,45,99,9.0,4,49,Semi-Urban,HR Executive,143425,1 +116023,Female,44,Diploma,17,43,55,27,47,4.0,0,36,Urban,Manager,52837,0 +116024,Male,53,Bachelors,3,80,86,84,32,0.0,1,30,Urban,ML Engineer,50413,1 +116025,Male,33,Bachelors,0,50,96,51,64,8.0,6,75,Rural,Software Engineer,66821,1 +116026,Male,53,Bachelors,1,85,72,34,99,8.0,6,98,Rural,Data Analyst,94470,1 +116027,Male,40,High School,16,21,35,97,32,4.0,4,83,Urban,Data Analyst,69056,1 +116028,Male,56,PhD,0,88,96,0,52,2.0,1,34,Rural,Manager,42105,0 +116029,Male,23,Bachelors,17,32,78,32,84,3.0,7,42,Semi-Urban,HR Executive,73365,0 +116030,Male,45,Diploma,19,74,38,51,57,8.0,0,74,Urban,Data Analyst,57092,1 +116031,Female,27,High School,18,43,22,39,3,7.0,5,31,Urban,Manager,117375,0 +116032,Male,41,Diploma,18,6,33,12,15,0.0,7,25,Semi-Urban,Software Engineer,73121,0 +116033,Male,27,High School,7,30,56,89,8,3.0,0,69,Semi-Urban,HR Executive,50293,1 +116034,Male,48,Bachelors,9,71,58,12,2,0.0,3,32,Urban,Manager,60598,0 +116035,Male,24,Masters,12,38,35,64,32,9.0,2,77,Urban,Manager,115974,0 +116036,Male,35,Bachelors,15,67,50,48,26,4.0,0,19,Urban,Software Engineer,93121,0 +116037,Male,34,PhD,18,74,72,39,41,8.0,6,58,Urban,ML Engineer,65992,1 +116038,Male,59,Bachelors,17,4,30,75,51,4.0,3,72,Urban,Software Engineer,123756,0 +116039,Female,40,Masters,18,1,18,23,92,7.0,3,39,Semi-Urban,Manager,139555,0 +116040,Male,44,Bachelors,7,46,87,31,44,8.0,7,57,Urban,Manager,140781,0 +116041,Male,21,Bachelors,7,92,21,33,33,5.0,2,70,Urban,HR Executive,28857,0 +116042,Female,38,Diploma,12,65,68,12,57,1.0,3,56,Rural,Data Analyst,119198,0 +116043,Female,25,Bachelors,19,39,12,4,71,6.0,7,85,Semi-Urban,Manager,141415,0 +116044,Other,44,Bachelors,7,81,18,67,45,3.0,2,15,Urban,Manager,105489,0 +116045,Female,56,Bachelors,19,93,79,55,23,9.0,2,82,Urban,Software Engineer,51915,1 +116046,Female,46,Bachelors,19,22,1,15,8,1.0,0,24,Semi-Urban,HR Executive,36360,0 +116047,Male,21,Bachelors,1,95,85,59,90,7.0,0,15,Urban,Data Analyst,127328,1 +116048,Female,38,Bachelors,10,20,33,80,3,2.0,5,88,Rural,Data Analyst,32021,0 +116049,Male,49,Bachelors,15,5,91,66,6,1.0,6,61,Urban,Data Analyst,135320,0 +116050,Male,59,Bachelors,7,94,30,30,30,6.0,1,15,Urban,Software Engineer,21408,0 +116051,Male,35,Diploma,13,23,31,24,23,7.0,2,30,Urban,Software Engineer,49183,0 +116052,Female,50,Bachelors,12,46,1,12,54,2.0,0,94,Semi-Urban,Manager,30037,0 +116053,Male,47,Diploma,3,55,8,40,67,2.0,0,45,Urban,Software Engineer,141340,0 +116054,Male,54,Bachelors,17,53,89,59,74,3.0,2,20,Urban,HR Executive,100733,0 +116055,Male,27,High School,5,53,2,93,2,8.0,1,64,Urban,Data Analyst,51808,0 +116056,Male,28,Masters,15,37,69,62,22,9.0,1,8,Urban,HR Executive,141570,0 +116057,Female,57,Masters,11,71,37,3,16,3.0,0,90,Urban,Data Analyst,36168,0 +116058,Female,50,Diploma,2,95,79,44,83,4.0,6,28,Urban,Software Engineer,41034,1 +116059,Male,52,Bachelors,0,4,34,8,71,6.0,2,22,Urban,HR Executive,129254,0 +116060,Male,57,Bachelors,12,59,42,64,85,2.0,1,57,Semi-Urban,ML Engineer,25510,0 +116061,Male,36,Diploma,5,8,22,30,95,9.0,0,44,Rural,HR Executive,60500,0 +116062,Female,35,Bachelors,19,89,74,70,72,9.0,6,80,Urban,ML Engineer,46555,1 +116063,Male,25,High School,15,84,19,80,71,4.0,4,39,Urban,ML Engineer,138350,0 +116064,Male,31,Bachelors,14,9,40,43,19,9.0,6,42,Rural,Software Engineer,50806,0 +116065,Female,50,High School,13,56,25,28,83,7.0,1,94,Rural,Software Engineer,24578,0 +116066,Female,37,Bachelors,0,53,90,75,33,4.0,0,62,Rural,HR Executive,72955,1 +116067,Female,22,Bachelors,10,12,97,82,31,2.0,6,26,Rural,ML Engineer,41637,0 +116068,Male,47,Diploma,18,70,74,76,31,7.0,5,98,Semi-Urban,Data Analyst,80540,1 +116069,Female,57,PhD,11,14,10,22,23,6.0,0,47,Rural,Software Engineer,73834,0 +116070,Female,39,Bachelors,10,36,80,67,46,7.0,3,43,Rural,Software Engineer,95947,0 +116071,Male,57,Bachelors,19,57,56,10,16,8.0,2,93,Urban,Manager,57448,0 +116072,Female,41,Bachelors,8,49,84,95,73,3.0,5,75,Semi-Urban,ML Engineer,117034,1 +116073,Female,36,Bachelors,10,8,66,98,55,2.0,4,63,Urban,Data Analyst,149508,0 +116074,Male,34,Bachelors,4,76,41,70,2,8.0,2,3,Rural,Software Engineer,87522,0 +116075,Male,40,Bachelors,16,15,4,77,73,9.0,6,24,Urban,ML Engineer,81246,0 +116076,Other,22,Bachelors,11,54,15,30,25,6.0,3,2,Urban,HR Executive,130777,0 +116077,Other,57,Bachelors,15,68,18,84,85,4.0,0,11,Semi-Urban,Manager,30636,0 +116078,Female,34,Bachelors,16,78,57,54,4,5.0,0,8,Urban,Manager,109637,0 +116079,Female,57,Masters,15,11,57,66,70,6.0,0,88,Urban,Software Engineer,115584,0 +116080,Male,36,Bachelors,8,25,66,31,4,8.0,0,27,Urban,Data Analyst,22198,0 +116081,Male,44,Bachelors,17,53,39,73,59,3.0,1,24,Urban,Software Engineer,81061,0 +116082,Other,33,Bachelors,13,55,55,0,55,8.0,4,96,Urban,Software Engineer,73477,0 +116083,Female,23,Bachelors,0,82,66,67,23,7.0,1,19,Urban,Software Engineer,109432,0 +116084,Male,53,High School,8,94,5,75,93,5.0,1,77,Urban,Data Analyst,93482,1 +116085,Male,21,Bachelors,12,63,74,46,24,0.0,1,62,Urban,Data Analyst,89037,1 +116086,Male,27,Bachelors,14,13,1,96,91,2.0,3,94,Urban,HR Executive,118255,0 +116087,Male,39,Diploma,9,46,95,75,64,0.0,1,77,Urban,ML Engineer,114407,1 +116088,Male,51,Bachelors,1,46,60,20,75,9.0,1,18,Urban,Software Engineer,122129,0 +116089,Male,25,Bachelors,0,29,61,77,67,0.0,6,57,Semi-Urban,Manager,58728,0 +116090,Other,57,Masters,8,64,1,72,23,2.0,1,76,Urban,ML Engineer,104432,0 +116091,Male,43,Bachelors,17,59,88,74,26,8.0,4,0,Urban,ML Engineer,87654,0 +116092,Male,38,Bachelors,5,73,33,23,96,5.0,1,65,Semi-Urban,HR Executive,108721,0 +116093,Male,50,Bachelors,14,2,4,64,85,7.0,0,12,Urban,ML Engineer,32102,0 +116094,Male,37,PhD,6,65,36,58,59,6.0,5,99,Urban,Data Analyst,106352,1 +116095,Male,28,Diploma,6,75,27,13,35,6.0,0,55,Urban,ML Engineer,38099,0 +116096,Female,55,Diploma,1,43,68,12,34,9.0,7,79,Urban,Data Analyst,149362,0 +116097,Male,28,Bachelors,18,75,69,45,70,2.0,6,65,Urban,HR Executive,54198,1 +116098,Female,50,Bachelors,4,21,27,74,38,3.0,5,40,Urban,ML Engineer,101809,0 +116099,Male,50,Bachelors,6,49,64,79,46,6.0,2,89,Semi-Urban,Manager,61427,1 +116100,Female,47,High School,13,33,49,34,20,2.0,4,20,Urban,Data Analyst,73408,0 +116101,Female,56,Masters,12,90,10,72,72,8.0,7,71,Urban,HR Executive,88058,1 +116102,Male,44,High School,9,43,71,39,15,2.0,6,4,Urban,HR Executive,125620,0 +116103,Other,22,Masters,3,47,63,12,72,7.0,6,24,Urban,HR Executive,63026,0 +116104,Female,58,Bachelors,15,32,24,90,48,9.0,7,79,Rural,ML Engineer,42497,0 +116105,Female,35,Masters,5,7,88,85,54,7.0,1,13,Urban,ML Engineer,146540,0 +116106,Male,51,Masters,16,92,5,23,80,6.0,7,15,Urban,Data Analyst,146081,0 +116107,Male,48,High School,10,2,61,89,25,7.0,0,16,Semi-Urban,Manager,109003,0 +116108,Female,42,Masters,19,51,97,34,79,0.0,6,90,Semi-Urban,Software Engineer,68350,1 +116109,Other,40,High School,17,28,72,25,12,8.0,0,3,Urban,Data Analyst,87863,0 +116110,Female,24,Diploma,18,33,94,92,27,4.0,0,73,Semi-Urban,Data Analyst,138084,1 +116111,Male,30,Masters,18,17,46,50,86,2.0,5,69,Rural,Data Analyst,77458,0 +116112,Male,27,Bachelors,8,82,59,55,72,6.0,5,22,Urban,Manager,144781,0 +116113,Male,28,Bachelors,2,0,61,46,91,0.0,1,3,Rural,Manager,27309,0 +116114,Male,59,Bachelors,6,87,42,19,59,7.0,3,18,Rural,HR Executive,145347,0 +116115,Male,27,Bachelors,6,69,28,23,85,1.0,1,29,Rural,ML Engineer,80128,0 +116116,Female,44,Bachelors,6,56,69,40,64,3.0,0,48,Urban,Software Engineer,131531,0 +116117,Male,43,Bachelors,6,80,52,50,93,2.0,1,67,Semi-Urban,HR Executive,128132,1 +116118,Female,59,PhD,4,60,54,60,73,6.0,3,45,Urban,Data Analyst,34264,0 +116119,Female,41,High School,15,98,18,69,45,2.0,6,97,Urban,Software Engineer,24317,1 +116120,Male,58,PhD,17,5,0,90,75,2.0,0,58,Semi-Urban,ML Engineer,63214,0 +116121,Female,25,Masters,15,54,50,3,99,7.0,2,16,Urban,HR Executive,47007,0 +116122,Other,59,Bachelors,11,94,37,86,62,0.0,6,16,Urban,HR Executive,49588,0 +116123,Male,58,Diploma,3,96,33,12,51,6.0,3,11,Urban,ML Engineer,79064,0 +116124,Male,58,Bachelors,6,53,68,72,2,5.0,6,64,Urban,Data Analyst,105764,1 +116125,Male,45,Bachelors,11,46,83,53,31,6.0,0,21,Rural,Manager,82661,0 +116126,Female,50,Bachelors,0,67,97,35,89,4.0,3,56,Rural,Data Analyst,124973,1 +116127,Other,43,Bachelors,16,36,33,26,23,1.0,3,4,Urban,ML Engineer,48713,0 +116128,Male,31,Masters,9,94,92,26,89,4.0,0,48,Semi-Urban,Software Engineer,106682,1 +116129,Female,28,Masters,15,47,60,43,50,1.0,6,85,Semi-Urban,Manager,31563,0 +116130,Male,45,High School,18,48,51,46,36,0.0,4,18,Rural,ML Engineer,136674,0 +116131,Female,40,Masters,12,56,55,74,69,9.0,6,54,Semi-Urban,Software Engineer,105763,0 +116132,Female,23,Bachelors,6,92,9,74,83,9.0,4,54,Urban,Manager,127149,0 +116133,Male,23,Bachelors,12,11,37,20,15,1.0,7,61,Urban,HR Executive,48195,0 +116134,Female,25,Diploma,1,13,96,46,6,5.0,5,1,Urban,Manager,39804,0 +116135,Male,27,Diploma,17,60,63,97,60,9.0,2,51,Rural,HR Executive,126273,1 +116136,Male,39,Diploma,7,89,75,22,51,0.0,0,14,Urban,Software Engineer,75513,0 +116137,Female,41,Bachelors,5,95,93,11,52,8.0,7,55,Urban,Software Engineer,104363,1 +116138,Male,32,Masters,8,43,12,38,98,8.0,5,3,Urban,Data Analyst,132405,0 +116139,Male,25,Masters,9,36,54,25,39,3.0,4,92,Urban,Software Engineer,79575,0 +116140,Female,57,Diploma,11,49,28,60,86,1.0,5,27,Rural,Software Engineer,80017,0 +116141,Male,35,Diploma,17,9,97,51,51,9.0,4,5,Urban,HR Executive,68305,0 +116142,Male,50,Masters,8,9,78,10,19,8.0,2,94,Semi-Urban,ML Engineer,141987,0 +116143,Female,48,Masters,13,18,68,58,92,3.0,5,66,Urban,HR Executive,36741,0 +116144,Male,21,Diploma,12,81,6,99,97,0.0,1,42,Semi-Urban,Manager,21447,0 +116145,Female,50,Bachelors,2,38,54,10,23,9.0,1,26,Urban,Manager,66880,0 +116146,Male,45,Bachelors,17,50,89,68,7,5.0,6,81,Semi-Urban,HR Executive,107214,1 +116147,Male,25,Bachelors,10,55,4,44,63,2.0,2,59,Urban,Data Analyst,118745,0 +116148,Male,23,Bachelors,10,8,87,44,59,2.0,1,55,Rural,Data Analyst,143021,0 +116149,Male,42,High School,2,0,6,11,93,6.0,5,67,Urban,Data Analyst,40586,0 +116150,Male,23,Bachelors,14,78,62,97,93,3.0,5,39,Urban,Manager,134913,1 +116151,Male,32,Bachelors,3,47,93,44,2,6.0,7,11,Rural,Data Analyst,146474,0 +116152,Female,24,Bachelors,7,87,9,52,61,7.0,2,84,Urban,Manager,60363,0 +116153,Female,49,Bachelors,19,19,48,21,39,6.0,7,24,Urban,Data Analyst,40364,0 +116154,Male,45,Bachelors,16,79,12,74,29,0.0,3,73,Urban,ML Engineer,99894,1 +116155,Male,55,Masters,4,55,7,86,90,3.0,6,99,Semi-Urban,HR Executive,107900,1 +116156,Male,25,Diploma,1,94,95,35,17,4.0,0,53,Urban,ML Engineer,141140,1 +116157,Male,38,Bachelors,6,52,7,15,88,7.0,4,96,Semi-Urban,Data Analyst,116248,0 +116158,Male,27,Bachelors,8,11,6,89,49,5.0,6,42,Urban,Software Engineer,46342,0 +116159,Female,37,Diploma,4,98,89,34,4,2.0,3,68,Rural,HR Executive,89509,1 +116160,Female,50,Diploma,11,53,75,21,51,3.0,3,73,Urban,Manager,108507,0 +116161,Male,56,Masters,2,91,25,40,5,4.0,4,0,Semi-Urban,Manager,95875,0 +116162,Female,49,Bachelors,13,79,40,81,66,5.0,6,32,Rural,HR Executive,101907,0 +116163,Female,53,Diploma,1,90,78,32,15,5.0,0,43,Semi-Urban,Software Engineer,69804,1 +116164,Female,21,High School,15,0,68,35,71,1.0,4,16,Semi-Urban,Manager,65836,0 +116165,Female,40,Masters,13,97,12,55,85,0.0,3,60,Urban,HR Executive,127898,0 +116166,Male,50,Masters,11,61,51,56,97,1.0,1,17,Semi-Urban,Software Engineer,89141,0 +116167,Other,21,Bachelors,13,98,6,85,48,0.0,5,14,Rural,Data Analyst,42558,0 +116168,Female,22,Bachelors,13,11,36,67,26,2.0,7,51,Rural,HR Executive,77717,0 +116169,Male,52,High School,19,75,98,44,46,6.0,1,66,Urban,HR Executive,41401,1 +116170,Male,46,Masters,19,63,71,26,32,6.0,1,55,Semi-Urban,Software Engineer,93299,0 +116171,Male,45,Diploma,18,43,66,12,87,3.0,6,59,Urban,Software Engineer,123627,0 +116172,Female,24,Masters,17,28,89,7,7,7.0,7,90,Urban,HR Executive,50003,0 +116173,Female,48,Masters,15,45,81,11,25,2.0,0,24,Semi-Urban,Data Analyst,135631,0 +116174,Male,57,Diploma,18,23,75,92,75,5.0,1,10,Rural,Software Engineer,42401,0 +116175,Female,32,Bachelors,14,62,17,87,43,9.0,7,3,Urban,HR Executive,72868,0 +116176,Male,58,Diploma,9,56,99,75,33,9.0,0,38,Urban,Data Analyst,110197,1 +116177,Male,54,Diploma,14,61,33,71,12,2.0,1,40,Urban,Data Analyst,36700,0 +116178,Female,40,Bachelors,1,76,49,22,71,1.0,5,98,Rural,Software Engineer,104243,1 +116179,Male,49,Bachelors,13,60,19,27,81,6.0,7,31,Semi-Urban,Data Analyst,42227,0 +116180,Male,31,Masters,5,11,52,31,11,9.0,1,34,Urban,Manager,117080,0 +116181,Male,49,Bachelors,0,98,81,73,57,8.0,5,81,Semi-Urban,Data Analyst,33394,1 +116182,Other,30,Diploma,10,99,30,81,39,0.0,5,49,Urban,ML Engineer,51185,1 +116183,Female,51,Bachelors,6,25,8,23,41,5.0,4,17,Semi-Urban,Manager,121562,0 +116184,Male,21,Bachelors,6,49,61,83,45,0.0,3,64,Semi-Urban,Software Engineer,112525,1 +116185,Male,40,Diploma,19,12,15,46,80,7.0,0,73,Urban,Software Engineer,114221,0 +116186,Female,35,Bachelors,15,86,76,95,84,3.0,6,34,Rural,Manager,64217,1 +116187,Male,28,High School,11,54,34,29,71,1.0,1,10,Semi-Urban,ML Engineer,133127,0 +116188,Female,56,Bachelors,19,25,98,1,61,3.0,0,39,Urban,Software Engineer,71376,0 +116189,Male,56,Bachelors,5,43,67,96,16,0.0,7,12,Semi-Urban,Manager,138823,0 +116190,Male,29,Bachelors,11,68,18,24,11,9.0,0,69,Semi-Urban,ML Engineer,108661,0 +116191,Male,55,Bachelors,15,35,42,18,70,8.0,0,45,Rural,Manager,46643,0 +116192,Male,43,Bachelors,15,85,37,7,12,3.0,2,94,Semi-Urban,ML Engineer,104803,0 +116193,Male,38,PhD,16,53,49,1,87,3.0,4,92,Rural,HR Executive,123371,0 +116194,Male,21,Bachelors,15,51,13,96,42,0.0,2,85,Rural,Manager,47109,1 +116195,Other,33,Bachelors,6,76,15,32,91,1.0,7,88,Rural,Data Analyst,49094,0 +116196,Other,45,High School,11,96,11,72,98,2.0,5,59,Urban,Manager,33661,0 +116197,Male,25,PhD,9,35,74,3,71,7.0,1,69,Rural,Manager,104153,0 +116198,Female,38,Bachelors,11,67,14,73,99,3.0,1,29,Semi-Urban,Manager,62709,0 +116199,Male,30,High School,2,86,50,96,40,4.0,5,21,Urban,Software Engineer,78860,1 +116200,Other,27,Bachelors,4,92,59,17,81,9.0,5,18,Rural,HR Executive,104318,0 +116201,Male,49,Diploma,14,57,12,59,68,8.0,0,90,Urban,Manager,43661,0 +116202,Male,31,Masters,11,22,4,73,55,2.0,4,71,Semi-Urban,Data Analyst,54449,0 +116203,Male,48,High School,18,68,35,76,3,7.0,6,48,Urban,HR Executive,37418,0 +116204,Male,58,Masters,10,13,98,64,85,7.0,3,24,Semi-Urban,HR Executive,44315,0 +116205,Male,31,Masters,16,51,41,52,48,4.0,2,63,Semi-Urban,HR Executive,75677,0 +116206,Female,53,High School,3,92,83,58,6,1.0,6,53,Urban,Manager,136191,1 +116207,Male,37,Diploma,2,3,83,36,35,2.0,7,84,Urban,ML Engineer,109152,0 +116208,Other,57,Masters,13,53,14,53,53,1.0,4,13,Urban,Data Analyst,105377,0 +116209,Male,35,Masters,8,64,32,1,27,9.0,4,66,Urban,HR Executive,107748,0 +116210,Male,27,Bachelors,18,57,71,90,99,4.0,7,59,Rural,HR Executive,110993,1 +116211,Male,54,Masters,13,35,2,90,78,6.0,7,95,Semi-Urban,Data Analyst,95577,0 +116212,Male,34,PhD,8,84,3,31,85,5.0,5,46,Semi-Urban,HR Executive,37260,0 +116213,Female,48,Masters,19,33,82,91,97,9.0,4,0,Urban,ML Engineer,90066,0 +116214,Male,44,Diploma,7,3,38,19,76,3.0,2,23,Urban,Software Engineer,143300,0 +116215,Female,45,Bachelors,8,88,35,86,27,5.0,4,76,Semi-Urban,Manager,25458,1 +116216,Male,46,Masters,11,54,4,50,34,8.0,4,40,Urban,ML Engineer,44523,0 +116217,Female,36,Diploma,1,27,66,29,62,1.0,1,97,Urban,ML Engineer,85318,0 +116218,Female,31,Bachelors,0,39,61,66,90,4.0,5,45,Urban,Manager,91367,0 +116219,Female,44,Bachelors,12,81,82,52,11,4.0,4,91,Semi-Urban,Data Analyst,119210,1 +116220,Female,59,Bachelors,6,86,37,80,30,4.0,7,48,Semi-Urban,Software Engineer,131047,1 +116221,Female,43,Masters,2,46,67,72,27,1.0,2,67,Rural,Software Engineer,100260,1 +116222,Female,25,High School,4,64,49,92,89,0.0,4,41,Urban,HR Executive,79656,1 +116223,Female,44,High School,16,6,47,81,14,0.0,7,25,Urban,Data Analyst,90385,0 +116224,Male,58,Masters,13,87,81,77,79,1.0,1,59,Urban,Software Engineer,145376,1 +116225,Female,35,High School,6,46,11,26,42,4.0,2,42,Rural,Data Analyst,32667,0 +116226,Female,53,Diploma,19,13,1,96,62,6.0,1,33,Urban,Software Engineer,35612,0 +116227,Female,55,Bachelors,17,77,16,6,79,3.0,6,92,Urban,ML Engineer,94837,0 +116228,Male,26,Bachelors,17,6,46,27,22,9.0,3,71,Urban,HR Executive,66317,0 +116229,Female,23,Bachelors,7,69,81,26,25,1.0,0,77,Rural,Software Engineer,98319,1 +116230,Male,53,Masters,15,73,75,47,67,2.0,3,48,Urban,Data Analyst,57793,1 +116231,Female,44,Diploma,17,53,45,49,90,8.0,2,26,Urban,HR Executive,55761,0 +116232,Female,35,Bachelors,6,9,70,83,98,8.0,4,42,Urban,Software Engineer,66135,0 +116233,Male,39,Bachelors,10,64,31,59,55,0.0,0,74,Urban,HR Executive,38870,0 +116234,Male,52,High School,13,54,72,19,56,8.0,3,1,Rural,Software Engineer,65294,0 +116235,Female,33,Bachelors,4,72,48,94,74,6.0,6,71,Urban,Manager,38895,1 +116236,Male,21,High School,12,93,30,93,31,8.0,4,65,Urban,HR Executive,49871,1 +116237,Male,55,Bachelors,11,81,67,0,90,6.0,2,99,Semi-Urban,Software Engineer,83302,1 +116238,Male,31,Diploma,8,44,84,0,48,3.0,2,36,Rural,ML Engineer,73608,0 +116239,Male,45,Masters,0,53,85,25,0,8.0,6,34,Urban,ML Engineer,22578,0 +116240,Male,51,Bachelors,8,92,45,55,68,8.0,2,1,Semi-Urban,ML Engineer,56445,0 +116241,Male,54,High School,17,16,31,80,39,4.0,5,32,Rural,Manager,91727,0 +116242,Male,26,PhD,19,36,92,70,89,2.0,0,74,Urban,HR Executive,34020,1 +116243,Male,41,Bachelors,10,21,87,60,80,6.0,3,12,Rural,ML Engineer,146130,0 +116244,Other,58,Diploma,15,75,30,71,97,6.0,3,36,Rural,HR Executive,29855,0 +116245,Male,55,Bachelors,1,40,74,73,19,3.0,3,89,Semi-Urban,HR Executive,20883,1 +116246,Male,21,Masters,16,37,9,88,53,5.0,3,80,Urban,Manager,134332,0 +116247,Male,28,Masters,0,33,5,70,88,4.0,7,17,Semi-Urban,Data Analyst,42696,0 +116248,Female,56,Diploma,0,13,44,36,29,2.0,2,41,Urban,Data Analyst,53776,0 +116249,Female,30,High School,11,38,86,31,82,9.0,3,85,Semi-Urban,ML Engineer,29119,0 +116250,Male,38,Diploma,9,3,93,73,39,9.0,6,51,Urban,Manager,54725,0 +116251,Female,51,Masters,3,44,71,82,11,9.0,1,18,Urban,ML Engineer,80182,0 +116252,Male,58,Bachelors,1,83,80,12,50,3.0,2,94,Urban,ML Engineer,111037,1 +116253,Female,41,Diploma,17,97,83,46,19,6.0,5,33,Rural,Data Analyst,53573,1 +116254,Female,33,Masters,4,68,21,92,37,0.0,0,95,Rural,Data Analyst,98709,1 +116255,Female,41,Diploma,2,83,66,11,10,6.0,4,3,Urban,Software Engineer,20634,0 +116256,Female,48,High School,0,73,15,47,78,7.0,7,46,Urban,Manager,76720,0 +116257,Male,50,Masters,1,58,65,97,33,5.0,1,86,Urban,HR Executive,119553,1 +116258,Female,37,Diploma,17,36,88,82,69,4.0,3,43,Semi-Urban,ML Engineer,102965,1 +116259,Female,38,Bachelors,4,12,82,67,67,4.0,3,9,Semi-Urban,Software Engineer,26714,0 +116260,Male,42,High School,7,72,17,69,70,4.0,1,1,Rural,Data Analyst,45859,0 +116261,Female,39,Diploma,17,45,99,97,17,5.0,2,85,Urban,ML Engineer,33946,1 +116262,Male,30,Masters,10,41,27,76,43,0.0,2,54,Semi-Urban,Software Engineer,47963,0 +116263,Male,55,Bachelors,5,95,15,5,23,8.0,2,76,Urban,HR Executive,65854,0 +116264,Male,38,High School,6,61,71,46,7,9.0,4,80,Urban,Manager,122024,1 +116265,Male,46,High School,16,73,99,97,54,5.0,0,50,Urban,Manager,94546,1 +116266,Female,22,Bachelors,13,96,60,13,83,2.0,0,55,Semi-Urban,Manager,132010,0 +116267,Female,37,Masters,0,66,71,64,23,9.0,1,7,Urban,Data Analyst,121433,0 +116268,Male,57,Masters,7,57,85,73,74,5.0,4,53,Urban,Data Analyst,77398,1 +116269,Male,50,Bachelors,8,14,66,16,56,5.0,7,23,Semi-Urban,HR Executive,128245,0 +116270,Female,33,Bachelors,19,30,12,11,61,0.0,6,83,Rural,Manager,128867,0 +116271,Male,58,Diploma,19,42,61,33,7,6.0,7,35,Urban,Manager,80472,0 +116272,Male,47,High School,8,77,65,94,70,4.0,5,0,Urban,HR Executive,120569,1 +116273,Female,30,Masters,17,25,4,33,57,2.0,5,82,Urban,ML Engineer,101197,0 +116274,Male,44,Diploma,19,54,1,35,68,9.0,0,51,Urban,Manager,35953,0 +116275,Other,52,Bachelors,10,97,84,47,63,8.0,2,40,Urban,Software Engineer,114645,1 +116276,Female,59,Diploma,7,94,10,61,83,4.0,4,4,Semi-Urban,Data Analyst,105881,0 +116277,Male,21,Masters,4,55,92,90,1,4.0,0,43,Semi-Urban,Manager,25274,1 +116278,Male,24,Bachelors,6,55,2,54,65,5.0,4,77,Urban,ML Engineer,112547,0 +116279,Male,55,Masters,13,95,94,57,2,8.0,4,47,Urban,Data Analyst,131444,1 +116280,Male,27,Bachelors,5,96,39,61,41,9.0,3,8,Urban,Manager,129402,0 +116281,Female,39,Bachelors,7,34,38,99,2,7.0,3,52,Urban,ML Engineer,28392,0 +116282,Male,44,Masters,17,6,28,31,53,2.0,3,32,Urban,ML Engineer,88498,0 +116283,Female,38,Bachelors,4,52,16,68,38,3.0,3,65,Semi-Urban,Manager,90827,0 +116284,Male,22,Masters,3,84,33,0,25,7.0,0,65,Urban,Manager,65680,0 +116285,Male,45,PhD,11,37,1,40,86,5.0,4,53,Urban,HR Executive,61045,0 +116286,Female,58,Masters,1,84,23,94,75,7.0,1,24,Urban,HR Executive,100790,0 +116287,Male,39,Diploma,11,98,14,26,93,3.0,1,32,Rural,Software Engineer,127537,0 +116288,Female,34,Masters,8,83,0,6,83,6.0,5,5,Urban,HR Executive,54578,0 +116289,Female,29,Bachelors,4,74,17,32,90,5.0,5,82,Semi-Urban,ML Engineer,89642,0 +116290,Male,46,Masters,5,46,71,78,51,8.0,0,79,Rural,Data Analyst,97167,1 +116291,Male,52,Bachelors,16,28,17,96,24,7.0,3,7,Semi-Urban,HR Executive,64817,0 +116292,Male,42,High School,6,54,0,25,18,7.0,3,55,Urban,Manager,37192,0 +116293,Male,24,Bachelors,11,97,2,50,2,1.0,4,13,Rural,Data Analyst,35038,0 +116294,Male,23,Diploma,17,83,1,11,39,3.0,6,51,Urban,ML Engineer,99596,0 +116295,Other,47,Bachelors,18,15,59,32,59,3.0,2,98,Urban,Data Analyst,65409,0 +116296,Male,59,PhD,7,95,6,6,36,6.0,6,81,Urban,ML Engineer,23014,0 +116297,Female,43,Masters,11,70,46,98,81,5.0,0,38,Semi-Urban,Software Engineer,56667,1 +116298,Male,22,Bachelors,13,57,66,29,88,2.0,7,83,Semi-Urban,Data Analyst,139504,1 +116299,Female,34,Bachelors,4,3,53,8,0,9.0,0,1,Urban,Data Analyst,97166,0 +116300,Female,26,Diploma,6,86,84,40,89,5.0,0,49,Urban,Data Analyst,76494,1 +116301,Female,44,High School,9,86,7,40,8,5.0,4,55,Urban,Software Engineer,30625,0 +116302,Female,48,High School,11,80,87,88,26,3.0,3,71,Urban,HR Executive,125483,1 +116303,Female,27,Masters,18,9,44,98,33,5.0,5,90,Urban,Data Analyst,86658,1 +116304,Male,51,Bachelors,16,88,11,55,59,7.0,7,17,Semi-Urban,Data Analyst,130850,0 +116305,Female,40,Masters,4,35,96,51,97,5.0,1,94,Semi-Urban,ML Engineer,78258,1 +116306,Male,21,Bachelors,3,93,91,78,18,2.0,3,1,Rural,Software Engineer,37652,1 +116307,Male,52,Masters,13,37,50,73,36,9.0,5,74,Urban,Data Analyst,80729,0 +116308,Male,41,Diploma,18,7,50,11,3,0.0,3,60,Urban,HR Executive,120830,0 +116309,Female,51,High School,14,28,80,57,64,9.0,6,95,Rural,Manager,130363,1 +116310,Male,40,High School,2,73,4,28,55,3.0,3,95,Rural,Manager,113437,0 +116311,Female,54,Bachelors,6,76,74,33,5,6.0,1,60,Urban,ML Engineer,141993,1 +116312,Female,52,Masters,12,93,0,98,35,5.0,6,20,Urban,Manager,29062,0 +116313,Male,40,High School,8,45,1,68,32,7.0,3,10,Urban,Manager,45419,0 +116314,Male,35,Diploma,15,71,48,19,15,6.0,3,88,Urban,Data Analyst,90532,0 +116315,Male,48,High School,1,31,30,98,44,6.0,1,48,Semi-Urban,HR Executive,56211,0 +116316,Female,48,Masters,19,57,96,25,88,2.0,1,58,Semi-Urban,Software Engineer,57991,0 +116317,Male,56,Bachelors,10,77,75,4,89,8.0,5,86,Urban,HR Executive,73788,1 +116318,Male,21,Bachelors,10,37,28,79,74,1.0,0,16,Semi-Urban,Data Analyst,26630,0 +116319,Male,40,Bachelors,5,32,68,49,12,2.0,4,47,Urban,HR Executive,144048,0 +116320,Male,25,High School,15,15,87,95,12,1.0,7,41,Semi-Urban,Manager,30541,1 +116321,Female,28,Diploma,15,87,88,55,66,2.0,1,11,Semi-Urban,Manager,48101,1 +116322,Male,49,High School,14,75,32,31,57,1.0,4,84,Semi-Urban,HR Executive,148307,0 +116323,Male,39,Bachelors,6,35,89,6,0,7.0,5,71,Rural,HR Executive,101292,0 +116324,Female,39,Diploma,11,11,87,9,44,6.0,1,70,Rural,HR Executive,148773,0 +116325,Male,58,Diploma,0,28,39,44,99,4.0,3,76,Rural,HR Executive,58970,0 +116326,Male,48,PhD,15,95,47,19,14,4.0,6,49,Rural,Software Engineer,66572,0 +116327,Male,32,Diploma,8,87,76,1,4,1.0,3,28,Semi-Urban,Software Engineer,72143,0 +116328,Male,51,Masters,14,12,21,24,45,2.0,2,38,Urban,HR Executive,35211,0 +116329,Male,25,Masters,15,97,89,61,37,0.0,2,56,Rural,Data Analyst,44858,1 +116330,Female,46,Diploma,19,51,81,42,42,0.0,3,34,Rural,Manager,40345,0 +116331,Female,53,PhD,7,36,90,18,49,0.0,7,87,Rural,Software Engineer,82689,0 +116332,Female,36,Masters,2,3,64,57,63,5.0,5,64,Urban,HR Executive,28502,0 +116333,Male,46,Masters,2,63,29,80,61,3.0,7,58,Semi-Urban,ML Engineer,128344,0 +116334,Female,37,High School,3,53,82,26,70,5.0,1,65,Semi-Urban,Software Engineer,113771,0 +116335,Male,40,High School,18,81,67,78,69,1.0,0,41,Semi-Urban,Manager,71344,1 +116336,Female,44,Bachelors,13,24,38,93,89,9.0,1,9,Urban,Data Analyst,78272,0 +116337,Female,34,Diploma,10,45,1,12,11,9.0,0,72,Rural,Data Analyst,82146,0 +116338,Male,49,Bachelors,13,36,51,63,34,7.0,2,33,Urban,HR Executive,70546,0 +116339,Male,44,Bachelors,17,48,64,91,0,6.0,1,26,Urban,Data Analyst,50620,0 +116340,Male,28,Masters,2,59,96,64,71,2.0,4,37,Urban,Manager,119710,1 +116341,Male,26,High School,18,19,69,58,1,5.0,0,7,Urban,Manager,51494,0 +116342,Male,59,High School,0,55,99,2,1,3.0,3,25,Urban,HR Executive,87386,0 +116343,Male,42,Bachelors,14,63,68,18,88,0.0,0,40,Urban,Manager,134824,0 +116344,Male,28,Masters,19,72,27,48,61,6.0,0,73,Rural,Data Analyst,139932,0 +116345,Male,23,Masters,16,16,31,95,54,7.0,3,72,Urban,ML Engineer,98307,0 +116346,Male,31,Bachelors,5,73,49,53,21,3.0,3,42,Rural,Manager,71451,0 +116347,Female,29,Bachelors,1,24,23,30,45,1.0,4,52,Rural,Manager,66403,0 +116348,Female,37,Bachelors,0,32,7,2,11,1.0,1,88,Urban,Data Analyst,108914,0 +116349,Male,56,Bachelors,9,36,32,14,51,4.0,5,6,Urban,Data Analyst,41991,0 +116350,Male,40,Masters,15,87,85,9,59,4.0,3,3,Urban,HR Executive,23567,0 +116351,Female,36,High School,18,32,61,17,38,1.0,2,41,Urban,ML Engineer,64444,0 +116352,Male,33,Diploma,2,62,30,10,46,5.0,7,29,Urban,ML Engineer,64544,0 +116353,Male,25,High School,18,12,60,32,43,6.0,3,34,Semi-Urban,HR Executive,86621,0 +116354,Other,25,High School,2,86,42,10,93,6.0,1,60,Rural,Software Engineer,32316,0 +116355,Female,26,Bachelors,12,48,47,66,27,7.0,7,29,Urban,Software Engineer,145353,0 +116356,Male,23,Masters,1,96,85,84,68,1.0,2,14,Rural,Software Engineer,120504,1 +116357,Male,38,Bachelors,10,48,25,23,32,1.0,2,59,Rural,Data Analyst,130312,0 +116358,Female,52,Bachelors,16,12,87,55,6,2.0,6,85,Urban,Manager,142688,0 +116359,Male,58,Masters,15,93,33,79,53,7.0,3,23,Urban,ML Engineer,50636,0 +116360,Male,32,Diploma,18,41,85,96,61,2.0,7,95,Urban,HR Executive,62614,1 +116361,Male,52,Bachelors,7,17,39,98,30,7.0,6,92,Rural,Data Analyst,114140,1 +116362,Female,36,Bachelors,15,84,7,24,65,5.0,4,22,Urban,Manager,48961,0 +116363,Male,40,Bachelors,5,2,81,98,56,7.0,7,98,Urban,ML Engineer,39574,1 +116364,Male,24,High School,11,85,46,97,6,0.0,7,73,Semi-Urban,ML Engineer,102876,1 +116365,Male,29,Masters,5,35,73,83,0,8.0,3,46,Urban,ML Engineer,54033,1 +116366,Male,23,Diploma,1,51,23,60,80,6.0,6,6,Rural,HR Executive,108428,0 +116367,Female,56,Diploma,1,70,80,36,51,3.0,7,88,Urban,HR Executive,130526,1 +116368,Female,23,PhD,3,29,98,15,68,5.0,5,89,Urban,Data Analyst,81968,0 +116369,Male,43,Bachelors,1,25,50,21,98,1.0,7,99,Rural,Manager,51586,0 +116370,Female,50,Bachelors,2,10,53,97,50,1.0,2,57,Urban,Software Engineer,40266,0 +116371,Male,27,High School,3,17,33,39,34,6.0,7,52,Rural,Manager,124995,0 +116372,Male,49,Bachelors,7,60,79,45,80,7.0,2,13,Semi-Urban,ML Engineer,136064,0 +116373,Male,27,Bachelors,3,20,0,95,68,4.0,6,27,Urban,ML Engineer,82943,0 +116374,Male,21,Bachelors,5,6,50,27,87,6.0,7,42,Urban,HR Executive,85375,0 +116375,Male,40,Bachelors,1,17,61,52,34,1.0,7,43,Urban,HR Executive,121251,0 +116376,Female,22,Bachelors,15,23,60,35,54,9.0,2,44,Semi-Urban,ML Engineer,129001,0 +116377,Male,59,PhD,9,44,79,88,91,8.0,5,75,Semi-Urban,ML Engineer,111314,1 +116378,Female,32,High School,8,80,85,55,23,0.0,3,84,Urban,Software Engineer,82441,1 +116379,Male,33,Diploma,16,49,43,44,78,2.0,5,59,Semi-Urban,Data Analyst,24871,0 +116380,Male,24,Masters,3,62,84,79,96,0.0,4,40,Urban,Manager,75971,1 +116381,Male,54,High School,2,30,77,9,82,4.0,0,79,Semi-Urban,Software Engineer,136346,0 +116382,Male,31,Bachelors,8,11,97,73,19,1.0,6,31,Rural,Manager,122676,0 +116383,Male,50,Bachelors,8,32,63,50,35,2.0,3,22,Semi-Urban,Software Engineer,111947,0 +116384,Male,55,Diploma,14,75,38,6,55,2.0,5,61,Semi-Urban,Manager,29855,0 +116385,Male,38,PhD,1,58,38,67,80,9.0,2,60,Rural,Software Engineer,77777,0 +116386,Female,53,Bachelors,4,24,35,5,69,0.0,3,59,Urban,Software Engineer,100200,0 +116387,Male,31,High School,18,92,28,81,36,9.0,6,79,Urban,Software Engineer,65462,1 +116388,Male,31,Diploma,16,55,63,74,41,6.0,3,39,Urban,Software Engineer,113418,0 +116389,Male,30,Bachelors,16,38,65,87,53,5.0,1,99,Rural,Software Engineer,106772,1 +116390,Male,23,Bachelors,15,1,97,94,26,9.0,4,19,Urban,HR Executive,143364,0 +116391,Female,56,Bachelors,3,3,33,8,66,7.0,7,83,Urban,Data Analyst,48867,0 +116392,Female,30,Bachelors,13,48,3,34,10,0.0,5,61,Urban,HR Executive,128515,0 +116393,Female,40,High School,5,92,30,35,8,0.0,2,13,Urban,Manager,140026,0 +116394,Male,55,Diploma,14,91,98,34,33,5.0,1,2,Urban,HR Executive,107421,0 +116395,Male,55,PhD,1,73,78,98,13,3.0,4,40,Rural,Software Engineer,117065,1 +116396,Male,58,Masters,7,62,18,95,4,6.0,6,15,Semi-Urban,HR Executive,145239,0 +116397,Male,33,Masters,0,3,44,99,20,1.0,7,92,Semi-Urban,ML Engineer,123298,1 +116398,Female,24,High School,0,28,19,12,45,8.0,6,2,Urban,HR Executive,100902,0 +116399,Other,42,Bachelors,11,50,84,57,28,4.0,4,18,Rural,Software Engineer,123286,0 +116400,Male,44,Bachelors,5,55,68,29,21,6.0,7,45,Rural,Data Analyst,101699,0 +116401,Male,33,Bachelors,6,46,83,84,41,4.0,6,76,Urban,HR Executive,38612,1 +116402,Female,57,Bachelors,10,8,53,85,86,3.0,2,8,Rural,Data Analyst,121520,0 +116403,Female,50,Bachelors,1,28,96,4,78,5.0,1,48,Urban,ML Engineer,104857,0 +116404,Male,39,Diploma,1,35,51,93,2,3.0,3,10,Urban,ML Engineer,133013,0 +116405,Male,58,Bachelors,16,24,74,50,58,8.0,7,62,Urban,ML Engineer,78085,0 +116406,Female,59,Bachelors,8,91,57,15,11,3.0,6,50,Semi-Urban,Manager,136219,0 +116407,Male,57,Diploma,10,2,60,59,38,8.0,5,37,Semi-Urban,HR Executive,48980,0 +116408,Female,45,Bachelors,13,14,39,9,27,5.0,0,99,Rural,HR Executive,47463,0 +116409,Female,28,Bachelors,17,17,16,79,75,3.0,0,19,Urban,Manager,146971,0 +116410,Male,23,Masters,14,50,84,75,31,3.0,0,60,Semi-Urban,ML Engineer,136942,1 +116411,Male,58,Masters,4,14,99,16,47,2.0,2,86,Urban,Manager,141685,0 +116412,Male,27,Masters,16,1,17,50,85,3.0,5,56,Rural,Software Engineer,82910,0 +116413,Male,59,Bachelors,8,80,6,65,17,7.0,5,82,Urban,Software Engineer,113826,0 +116414,Female,44,Bachelors,12,24,94,90,75,7.0,2,53,Rural,Data Analyst,56803,1 +116415,Male,54,Bachelors,2,16,89,77,62,7.0,7,99,Urban,ML Engineer,133739,1 +116416,Female,35,Bachelors,1,62,84,43,87,6.0,1,67,Urban,Manager,32240,1 +116417,Male,59,Bachelors,12,89,34,94,39,9.0,7,73,Semi-Urban,Data Analyst,126280,1 +116418,Male,53,Diploma,9,72,89,81,46,4.0,2,34,Urban,Software Engineer,76172,1 +116419,Male,48,Masters,0,18,41,27,53,7.0,3,6,Rural,HR Executive,90101,0 +116420,Other,43,Diploma,15,15,11,33,35,7.0,7,6,Rural,Data Analyst,100238,0 +116421,Female,44,High School,8,60,58,39,40,1.0,3,33,Urban,Software Engineer,62513,0 +116422,Male,22,Bachelors,13,29,44,90,55,7.0,3,44,Semi-Urban,HR Executive,25415,0 +116423,Female,50,Masters,7,92,43,84,25,2.0,1,4,Urban,Data Analyst,90933,0 +116424,Male,47,Bachelors,2,27,87,66,67,5.0,7,92,Urban,HR Executive,85738,1 +116425,Female,25,Bachelors,14,83,20,16,91,1.0,7,67,Rural,HR Executive,118839,0 +116426,Other,40,Diploma,12,10,61,33,66,4.0,6,4,Rural,Software Engineer,64019,0 +116427,Female,34,PhD,3,81,67,26,11,9.0,1,79,Urban,Software Engineer,55576,1 +116428,Male,47,Bachelors,2,6,90,86,8,3.0,6,54,Semi-Urban,Manager,122588,1 +116429,Female,43,Bachelors,3,23,42,9,94,2.0,4,9,Urban,Manager,69559,0 +116430,Male,21,Masters,0,24,35,83,85,1.0,7,55,Urban,Manager,131086,0 +116431,Female,58,Bachelors,10,44,27,48,77,6.0,3,50,Urban,Manager,109953,0 +116432,Other,25,Masters,16,7,89,18,40,8.0,7,89,Rural,Data Analyst,106442,0 +116433,Male,26,Bachelors,12,86,42,13,43,3.0,3,8,Urban,ML Engineer,65245,0 +116434,Male,59,Bachelors,14,36,46,45,39,2.0,7,52,Urban,Data Analyst,112609,0 +116435,Female,48,Masters,5,30,59,58,29,2.0,4,96,Urban,ML Engineer,125386,1 +116436,Male,36,Masters,9,12,79,65,71,6.0,5,17,Urban,ML Engineer,89665,0 +116437,Female,29,PhD,1,72,38,46,70,7.0,6,98,Urban,Data Analyst,75553,1 +116438,Male,48,Masters,10,41,36,92,90,5.0,3,26,Rural,ML Engineer,124414,0 +116439,Male,51,High School,15,24,35,77,10,1.0,4,65,Urban,HR Executive,120347,0 +116440,Female,59,Diploma,11,4,80,46,57,8.0,2,94,Urban,HR Executive,85119,0 +116441,Male,54,High School,4,74,51,36,54,5.0,5,60,Urban,Data Analyst,74380,0 +116442,Male,58,Diploma,4,70,46,46,31,4.0,0,45,Urban,Software Engineer,64365,0 +116443,Male,23,Bachelors,2,99,78,8,26,8.0,3,49,Urban,ML Engineer,100730,0 +116444,Male,37,PhD,2,26,64,93,74,3.0,6,25,Urban,Software Engineer,89855,0 +116445,Male,23,Bachelors,18,95,89,23,63,2.0,5,6,Rural,HR Executive,74115,0 +116446,Female,58,Bachelors,3,31,87,14,61,4.0,2,22,Semi-Urban,Manager,43348,0 +116447,Female,50,PhD,16,27,80,59,20,6.0,5,57,Urban,HR Executive,49849,0 +116448,Male,46,Bachelors,9,54,94,56,41,3.0,0,24,Urban,HR Executive,27107,0 +116449,Male,59,Bachelors,12,92,69,14,78,5.0,6,46,Rural,ML Engineer,99776,0 +116450,Female,31,Bachelors,13,39,65,40,14,9.0,7,79,Rural,HR Executive,141464,0 +116451,Male,46,Diploma,11,95,75,30,22,1.0,7,89,Urban,Data Analyst,64075,1 +116452,Male,48,High School,16,14,22,39,82,1.0,2,37,Urban,HR Executive,87361,0 +116453,Male,37,Bachelors,1,69,35,74,93,7.0,6,1,Urban,HR Executive,141189,0 +116454,Female,28,Bachelors,5,47,86,51,56,8.0,3,29,Urban,Data Analyst,126243,0 +116455,Male,36,Masters,19,32,86,79,48,7.0,1,15,Semi-Urban,ML Engineer,129252,0 +116456,Male,56,High School,14,1,75,96,76,5.0,1,14,Rural,ML Engineer,139602,0 +116457,Female,29,Bachelors,16,0,24,43,33,6.0,0,20,Urban,Data Analyst,59459,0 +116458,Female,40,Bachelors,16,51,64,30,10,6.0,3,90,Semi-Urban,Data Analyst,144797,0 +116459,Male,35,Bachelors,9,27,18,46,32,0.0,7,3,Semi-Urban,HR Executive,42690,0 +116460,Male,41,Bachelors,15,84,2,32,67,4.0,1,48,Urban,Manager,132726,0 +116461,Female,30,Masters,13,35,87,17,14,0.0,6,61,Semi-Urban,Manager,131792,0 +116462,Male,32,Masters,17,12,73,78,4,5.0,6,63,Urban,ML Engineer,82713,0 +116463,Female,37,High School,4,81,49,88,69,5.0,0,66,Semi-Urban,Data Analyst,147909,1 +116464,Female,21,Bachelors,13,17,77,93,41,2.0,4,76,Semi-Urban,Software Engineer,93957,1 +116465,Male,49,Bachelors,18,77,75,2,40,6.0,3,54,Urban,ML Engineer,65841,0 +116466,Male,34,PhD,11,42,67,8,3,1.0,0,79,Urban,HR Executive,71543,0 +116467,Female,42,Bachelors,15,15,27,42,36,4.0,2,20,Semi-Urban,Manager,83321,0 +116468,Male,51,High School,11,87,12,36,40,6.0,1,58,Urban,HR Executive,96541,0 +116469,Male,33,Bachelors,13,21,80,6,82,8.0,6,68,Rural,Manager,94921,0 +116470,Female,42,Bachelors,7,1,86,87,19,9.0,1,36,Semi-Urban,Manager,58597,0 +116471,Male,56,Diploma,8,95,48,40,8,5.0,3,12,Urban,HR Executive,32044,0 +116472,Female,48,PhD,15,78,74,1,64,0.0,6,36,Semi-Urban,ML Engineer,67188,0 +116473,Female,55,Bachelors,4,38,53,1,55,1.0,2,79,Rural,Data Analyst,122007,0 +116474,Female,26,Bachelors,19,65,70,89,68,7.0,7,62,Urban,HR Executive,57425,1 +116475,Male,26,Masters,19,51,85,53,87,3.0,4,8,Urban,Software Engineer,28565,0 +116476,Male,31,Masters,9,76,32,30,39,7.0,1,31,Rural,Manager,144767,0 +116477,Male,53,Bachelors,8,87,30,70,53,1.0,3,59,Rural,Software Engineer,126002,1 +116478,Male,52,Bachelors,4,51,46,61,66,8.0,2,29,Semi-Urban,Data Analyst,36019,0 +116479,Male,23,Bachelors,11,17,74,50,90,1.0,6,65,Rural,HR Executive,40751,0 +116480,Male,42,High School,15,81,46,21,85,7.0,2,46,Urban,ML Engineer,23542,0 +116481,Male,40,Masters,5,52,71,85,50,1.0,6,59,Semi-Urban,Manager,37617,1 +116482,Female,47,Diploma,11,64,11,5,22,4.0,3,88,Urban,Manager,39831,0 +116483,Male,51,Masters,8,23,72,49,42,5.0,2,54,Urban,HR Executive,57664,0 +116484,Male,34,Bachelors,1,22,53,80,89,6.0,0,7,Urban,Data Analyst,84203,0 +116485,Male,58,Bachelors,0,86,55,90,9,7.0,3,96,Urban,HR Executive,74611,1 +116486,Female,21,Diploma,9,18,25,8,87,5.0,1,24,Rural,Data Analyst,63342,0 +116487,Male,40,Bachelors,2,56,14,95,29,4.0,7,39,Urban,HR Executive,77514,0 +116488,Male,41,High School,16,6,28,93,30,9.0,3,26,Urban,Manager,53026,0 +116489,Male,40,Bachelors,17,64,66,98,4,9.0,3,36,Semi-Urban,Data Analyst,33354,1 +116490,Other,43,Diploma,18,63,12,53,76,0.0,2,0,Rural,Manager,129623,0 +116491,Male,55,Masters,19,10,69,49,21,0.0,3,17,Urban,Data Analyst,21702,0 +116492,Female,24,High School,15,75,50,54,39,3.0,4,14,Rural,HR Executive,102448,0 +116493,Female,36,Bachelors,11,37,77,64,59,9.0,6,19,Semi-Urban,HR Executive,82962,0 +116494,Male,24,High School,6,23,13,91,67,4.0,6,63,Urban,HR Executive,28853,0 +116495,Male,36,Bachelors,17,19,52,80,3,3.0,2,98,Urban,Software Engineer,56030,1 +116496,Female,50,Diploma,0,3,31,54,73,3.0,4,19,Urban,ML Engineer,122476,0 +116497,Male,52,Bachelors,15,15,73,40,88,4.0,5,37,Semi-Urban,ML Engineer,134398,0 +116498,Male,41,Diploma,5,41,78,79,80,8.0,5,31,Rural,Manager,115553,0 +116499,Female,27,High School,17,96,65,63,27,1.0,7,28,Urban,Data Analyst,111756,1 +116500,Male,45,Bachelors,1,63,0,10,87,5.0,4,90,Urban,Manager,39888,0 +116501,Other,57,Bachelors,12,22,46,61,52,5.0,1,48,Semi-Urban,ML Engineer,119782,0 +116502,Male,52,Bachelors,13,42,39,41,13,0.0,0,99,Semi-Urban,Data Analyst,74514,0 +116503,Female,37,Bachelors,6,41,9,37,47,1.0,5,46,Rural,Software Engineer,115352,0 +116504,Other,31,Bachelors,17,98,62,55,76,8.0,0,58,Urban,Manager,105115,1 +116505,Male,43,High School,8,69,46,70,92,3.0,0,10,Urban,Manager,67822,0 +116506,Male,22,High School,1,94,77,63,49,5.0,3,98,Urban,HR Executive,28489,1 +116507,Other,30,Bachelors,15,97,6,47,14,6.0,0,63,Urban,HR Executive,52495,0 +116508,Female,33,Diploma,0,6,93,17,97,7.0,6,23,Urban,Data Analyst,81751,0 +116509,Male,41,Bachelors,15,77,15,97,53,4.0,6,82,Urban,Manager,51857,1 +116510,Male,40,High School,3,86,64,56,65,7.0,6,44,Rural,ML Engineer,35042,1 +116511,Female,44,Bachelors,4,7,13,97,39,9.0,2,10,Semi-Urban,Data Analyst,35666,0 +116512,Male,48,Bachelors,14,27,93,50,15,9.0,6,43,Semi-Urban,Data Analyst,37994,0 +116513,Male,29,High School,11,4,82,4,25,9.0,7,14,Rural,HR Executive,92099,0 +116514,Male,41,High School,5,68,2,33,18,8.0,1,23,Semi-Urban,Software Engineer,45192,0 +116515,Male,40,Bachelors,2,33,79,74,0,4.0,4,49,Semi-Urban,ML Engineer,101309,1 +116516,Male,44,Bachelors,19,14,54,93,59,0.0,3,78,Rural,HR Executive,43977,1 +116517,Male,26,Diploma,11,42,1,9,65,4.0,3,66,Semi-Urban,HR Executive,68870,0 +116518,Female,59,Bachelors,8,18,50,23,40,7.0,5,30,Urban,HR Executive,112100,0 +116519,Male,22,Bachelors,6,57,27,71,18,1.0,6,49,Urban,Software Engineer,148162,0 +116520,Male,56,Masters,4,85,8,45,16,1.0,4,47,Urban,HR Executive,100413,0 +116521,Female,22,Bachelors,18,10,63,29,40,5.0,1,49,Urban,Manager,70528,0 +116522,Female,58,High School,6,59,76,69,73,7.0,1,72,Urban,Software Engineer,101902,1 +116523,Female,54,Diploma,4,77,19,35,20,7.0,0,60,Semi-Urban,Manager,29454,0 +116524,Female,37,Bachelors,6,40,93,85,43,0.0,7,83,Urban,HR Executive,27740,1 +116525,Male,55,Bachelors,5,24,78,82,41,8.0,0,77,Urban,Software Engineer,135457,1 +116526,Female,51,Bachelors,5,38,54,76,64,1.0,4,10,Urban,HR Executive,98235,0 +116527,Female,56,High School,13,40,42,89,72,1.0,2,52,Semi-Urban,HR Executive,44614,0 +116528,Female,42,High School,16,80,64,45,97,9.0,0,92,Urban,Manager,107103,1 +116529,Male,53,High School,4,47,94,85,54,1.0,6,71,Urban,Data Analyst,126343,1 +116530,Female,38,Bachelors,1,40,1,70,31,5.0,2,5,Urban,Manager,47528,0 +116531,Male,53,Diploma,18,87,0,18,40,8.0,5,64,Rural,Software Engineer,66378,0 +116532,Male,41,Bachelors,11,44,62,88,68,7.0,0,50,Urban,HR Executive,80067,1 +116533,Female,24,Bachelors,10,53,85,57,61,8.0,3,13,Semi-Urban,Manager,36378,0 +116534,Female,44,Masters,4,80,67,22,45,8.0,0,77,Rural,ML Engineer,104287,1 +116535,Male,58,High School,4,48,56,1,9,3.0,0,47,Rural,Data Analyst,30421,0 +116536,Female,38,Bachelors,12,50,14,29,66,6.0,6,4,Urban,ML Engineer,28327,0 +116537,Female,25,High School,14,67,41,24,68,3.0,3,34,Urban,Data Analyst,124151,0 +116538,Female,53,Diploma,0,90,0,87,13,6.0,7,5,Rural,Data Analyst,134985,0 +116539,Female,50,High School,4,79,37,71,35,4.0,5,52,Urban,Manager,86988,0 +116540,Female,45,Bachelors,5,42,66,26,49,8.0,0,32,Rural,Manager,45238,0 +116541,Male,39,Bachelors,12,42,5,88,47,8.0,5,6,Urban,HR Executive,71456,0 +116542,Male,43,Diploma,10,88,82,65,35,5.0,7,91,Rural,HR Executive,72137,1 +116543,Male,45,Masters,17,60,67,86,81,8.0,0,47,Urban,HR Executive,56885,1 +116544,Female,37,Bachelors,1,63,21,25,31,1.0,7,99,Urban,Manager,99402,0 +116545,Male,49,Diploma,5,81,2,33,90,3.0,1,79,Urban,Software Engineer,61749,0 +116546,Female,21,Masters,0,38,27,44,2,1.0,2,60,Urban,HR Executive,144574,0 +116547,Male,32,Masters,11,16,44,58,4,4.0,7,23,Urban,ML Engineer,115135,0 +116548,Male,31,Diploma,13,50,50,9,68,9.0,6,45,Rural,Manager,29971,0 +116549,Male,21,Diploma,15,79,8,13,86,7.0,6,20,Urban,Manager,132358,0 +116550,Female,53,Masters,4,86,35,34,32,5.0,2,29,Semi-Urban,HR Executive,144968,0 +116551,Male,57,High School,13,4,30,44,10,4.0,1,37,Urban,Data Analyst,78414,0 +116552,Other,37,PhD,16,36,43,21,98,7.0,4,63,Semi-Urban,HR Executive,125941,0 +116553,Female,47,Masters,2,89,28,17,88,3.0,6,90,Urban,ML Engineer,124036,0 +116554,Male,21,Masters,7,5,15,43,60,1.0,1,70,Urban,Data Analyst,59187,0 +116555,Female,39,Diploma,8,14,25,86,55,1.0,2,55,Urban,ML Engineer,116604,0 +116556,Female,28,Diploma,5,93,66,68,50,6.0,3,1,Semi-Urban,Data Analyst,133026,0 +116557,Female,49,PhD,7,49,73,48,97,2.0,2,40,Urban,ML Engineer,117348,0 +116558,Male,54,Diploma,5,26,10,79,82,0.0,5,84,Rural,HR Executive,20960,0 +116559,Female,26,Masters,4,10,1,75,68,9.0,3,81,Urban,Data Analyst,48921,0 +116560,Male,49,Bachelors,0,36,33,34,81,7.0,5,12,Urban,Data Analyst,23676,0 +116561,Female,52,High School,15,59,97,38,74,3.0,1,11,Semi-Urban,Manager,90554,0 +116562,Male,21,Diploma,13,13,93,9,59,7.0,3,79,Urban,HR Executive,45201,0 +116563,Male,54,Diploma,9,12,4,77,60,0.0,1,84,Urban,HR Executive,118548,0 +116564,Male,29,High School,18,8,71,65,81,5.0,5,47,Rural,HR Executive,41672,0 +116565,Female,58,Diploma,4,65,17,59,32,2.0,6,62,Semi-Urban,Software Engineer,128345,0 +116566,Male,33,Bachelors,5,47,51,20,75,8.0,7,53,Semi-Urban,Data Analyst,91222,0 +116567,Male,50,High School,12,30,49,89,15,3.0,3,85,Semi-Urban,HR Executive,117839,1 +116568,Female,59,Masters,18,48,92,48,8,8.0,7,25,Rural,ML Engineer,61772,0 +116569,Female,37,Diploma,15,75,60,47,70,0.0,5,24,Urban,Manager,138831,0 +116570,Male,36,Diploma,14,6,47,51,63,3.0,3,49,Semi-Urban,Software Engineer,35994,0 +116571,Female,59,High School,8,46,32,15,46,8.0,4,99,Urban,ML Engineer,91159,0 +116572,Male,57,Bachelors,2,26,13,61,57,6.0,3,39,Rural,ML Engineer,61614,0 +116573,Male,41,High School,7,95,7,60,15,7.0,0,65,Rural,Data Analyst,135547,0 +116574,Male,32,Diploma,15,13,75,16,14,3.0,2,7,Semi-Urban,Data Analyst,146961,0 +116575,Male,31,Diploma,14,54,99,28,34,6.0,4,26,Urban,ML Engineer,62728,0 +116576,Male,55,Diploma,8,76,38,41,80,0.0,7,56,Semi-Urban,Software Engineer,32339,0 +116577,Male,29,Masters,6,45,74,51,74,9.0,3,33,Rural,Manager,60491,0 +116578,Male,52,Diploma,11,36,70,19,30,1.0,6,80,Semi-Urban,Data Analyst,144914,0 +116579,Female,27,Bachelors,3,72,86,79,25,3.0,6,98,Urban,Manager,105355,1 +116580,Female,27,Masters,18,79,68,93,65,8.0,5,23,Rural,HR Executive,90247,1 +116581,Male,49,Masters,8,90,15,63,62,8.0,4,89,Urban,Software Engineer,91038,1 +116582,Female,30,Bachelors,18,37,25,65,87,0.0,2,98,Urban,HR Executive,149765,0 +116583,Female,52,Bachelors,1,76,7,55,39,1.0,4,77,Semi-Urban,Data Analyst,147067,0 +116584,Male,59,Bachelors,11,55,6,65,53,5.0,3,34,Urban,Manager,53598,0 +116585,Female,59,High School,19,51,10,42,14,3.0,2,50,Urban,Data Analyst,107892,0 +116586,Male,29,High School,0,69,90,56,65,5.0,0,11,Rural,HR Executive,36788,0 +116587,Female,55,Masters,12,85,65,96,33,4.0,7,65,Urban,Data Analyst,25428,1 +116588,Male,53,Diploma,9,62,69,11,51,0.0,7,99,Urban,ML Engineer,44148,1 +116589,Female,39,Diploma,6,18,46,3,75,8.0,2,79,Semi-Urban,Software Engineer,122537,0 +116590,Female,54,Bachelors,0,62,26,52,89,5.0,3,14,Semi-Urban,Data Analyst,46241,0 +116591,Male,44,Bachelors,4,38,52,39,85,2.0,0,25,Urban,Software Engineer,58848,0 +116592,Male,22,Masters,6,97,29,56,40,1.0,1,63,Rural,ML Engineer,127756,1 +116593,Male,46,High School,18,36,48,20,99,5.0,6,10,Semi-Urban,Data Analyst,23560,0 +116594,Male,26,Bachelors,18,91,22,78,97,4.0,0,27,Urban,ML Engineer,106170,0 +116595,Male,53,High School,10,19,10,60,98,8.0,5,0,Urban,Data Analyst,107113,0 +116596,Male,21,Bachelors,8,85,46,72,74,8.0,1,97,Urban,ML Engineer,106829,1 +116597,Female,36,Masters,1,60,48,7,41,6.0,4,89,Urban,Data Analyst,101741,0 +116598,Female,55,Masters,9,35,92,90,93,1.0,1,79,Semi-Urban,Data Analyst,38388,1 +116599,Male,44,Bachelors,10,52,79,2,96,4.0,7,42,Urban,ML Engineer,140883,0 +116600,Male,59,Bachelors,12,52,19,54,70,2.0,3,48,Semi-Urban,ML Engineer,26001,0 +116601,Male,57,Masters,6,69,49,53,19,6.0,5,9,Urban,Manager,112544,0 +116602,Female,42,Bachelors,18,37,62,73,29,1.0,5,42,Urban,Manager,129404,0 +116603,Male,41,Masters,11,27,76,87,72,0.0,5,63,Rural,Software Engineer,26350,1 +116604,Female,58,Bachelors,4,46,57,22,90,4.0,3,26,Semi-Urban,Data Analyst,124611,0 +116605,Male,32,Bachelors,6,90,95,59,48,0.0,5,76,Urban,Software Engineer,59630,1 +116606,Male,36,Bachelors,11,53,88,80,26,0.0,6,61,Urban,Software Engineer,87851,1 +116607,Male,50,Diploma,18,74,11,78,75,8.0,0,23,Semi-Urban,ML Engineer,124564,0 +116608,Female,57,Bachelors,3,19,82,84,3,3.0,2,99,Rural,HR Executive,51125,1 +116609,Female,25,Masters,14,73,47,69,15,8.0,5,10,Urban,ML Engineer,101180,0 +116610,Male,54,Diploma,11,85,80,91,73,2.0,4,72,Urban,Software Engineer,49262,1 +116611,Other,29,Bachelors,4,78,85,34,49,0.0,5,14,Rural,ML Engineer,102140,0 +116612,Male,24,High School,17,91,54,11,83,6.0,1,99,Semi-Urban,Software Engineer,109230,1 +116613,Male,46,Masters,19,24,35,30,3,8.0,5,70,Semi-Urban,HR Executive,98491,0 +116614,Male,53,Bachelors,15,93,22,53,25,6.0,7,10,Semi-Urban,Software Engineer,38620,0 +116615,Male,30,Diploma,6,35,71,47,58,1.0,1,93,Rural,HR Executive,125590,1 +116616,Male,28,Masters,18,93,46,26,40,5.0,1,47,Semi-Urban,Software Engineer,135566,0 +116617,Male,31,Masters,11,26,5,56,24,5.0,5,72,Urban,Manager,29265,0 +116618,Female,28,High School,16,31,35,73,10,9.0,0,16,Urban,ML Engineer,87141,0 +116619,Male,41,Masters,4,88,59,86,5,3.0,3,86,Semi-Urban,Manager,123825,1 +116620,Other,58,Bachelors,18,91,49,54,63,8.0,3,72,Semi-Urban,Data Analyst,30638,1 +116621,Female,57,Masters,9,86,19,37,78,4.0,2,58,Semi-Urban,Software Engineer,123528,0 +116622,Female,31,Masters,7,72,6,43,90,6.0,7,93,Urban,Data Analyst,74565,0 +116623,Female,38,Bachelors,10,30,58,84,12,9.0,2,62,Semi-Urban,HR Executive,34661,0 +116624,Female,39,Bachelors,7,12,66,37,19,7.0,1,56,Urban,Data Analyst,25539,0 +116625,Female,24,Bachelors,12,39,9,73,10,1.0,4,57,Semi-Urban,ML Engineer,134275,0 +116626,Female,56,Diploma,4,43,2,73,87,6.0,7,62,Urban,Software Engineer,117072,0 +116627,Female,49,Diploma,5,24,96,79,86,9.0,0,53,Urban,ML Engineer,27925,1 +116628,Female,35,Diploma,1,94,54,73,22,1.0,0,34,Urban,HR Executive,43202,1 +116629,Male,45,Diploma,11,17,0,2,72,1.0,0,74,Urban,Manager,146884,0 +116630,Male,57,Bachelors,5,2,54,62,3,6.0,2,96,Urban,HR Executive,46035,0 +116631,Female,43,High School,7,61,36,76,60,2.0,4,24,Urban,Data Analyst,78081,0 +116632,Male,36,Diploma,6,39,69,27,46,9.0,6,66,Urban,Manager,55339,0 +116633,Female,26,Masters,14,89,28,73,80,9.0,3,3,Semi-Urban,Manager,45795,0 +116634,Female,41,Diploma,4,66,71,97,62,4.0,6,64,Urban,Data Analyst,146377,1 +116635,Male,44,Diploma,18,99,46,38,7,5.0,2,60,Urban,Data Analyst,32333,1 +116636,Male,37,Bachelors,0,76,3,84,22,9.0,3,67,Urban,ML Engineer,76235,0 +116637,Female,57,PhD,14,58,2,21,9,1.0,5,82,Urban,Data Analyst,79876,0 +116638,Female,47,Diploma,5,74,50,87,30,1.0,3,64,Urban,HR Executive,109972,1 +116639,Female,46,High School,10,67,98,99,1,1.0,1,6,Urban,Data Analyst,26627,1 +116640,Male,36,High School,0,95,31,57,32,5.0,6,98,Urban,Manager,128066,1 +116641,Female,41,Bachelors,15,69,2,93,38,7.0,7,35,Urban,HR Executive,119040,0 +116642,Male,38,Diploma,18,64,79,43,72,9.0,3,83,Urban,Software Engineer,99822,1 +116643,Other,49,Masters,19,66,62,67,36,2.0,3,39,Rural,Manager,76551,0 +116644,Male,24,Bachelors,0,15,0,98,65,3.0,5,5,Urban,Software Engineer,140245,0 +116645,Male,42,PhD,10,96,62,25,62,2.0,7,4,Semi-Urban,HR Executive,124330,0 +116646,Female,27,Bachelors,4,91,20,99,25,9.0,7,50,Urban,ML Engineer,80254,1 +116647,Male,51,Diploma,13,40,81,60,39,0.0,5,69,Urban,Data Analyst,71090,1 +116648,Female,58,Masters,0,2,64,73,62,6.0,2,42,Urban,Software Engineer,107292,0 +116649,Male,27,Diploma,10,32,27,51,14,2.0,2,60,Rural,Manager,130117,0 +116650,Male,35,Bachelors,14,54,23,60,1,2.0,1,94,Semi-Urban,HR Executive,20839,0 +116651,Male,40,Masters,11,17,82,82,75,0.0,5,79,Urban,HR Executive,60912,1 +116652,Male,24,Diploma,16,93,8,47,91,0.0,2,54,Semi-Urban,HR Executive,25853,0 +116653,Female,25,Diploma,11,13,94,13,56,6.0,3,72,Rural,ML Engineer,85852,0 +116654,Other,57,Masters,15,27,75,46,50,6.0,7,10,Urban,HR Executive,32737,0 +116655,Male,55,High School,11,60,25,26,60,0.0,4,90,Semi-Urban,Manager,119810,0 +116656,Female,44,Bachelors,9,48,4,74,72,8.0,3,80,Urban,HR Executive,69258,0 +116657,Male,25,Masters,11,76,41,94,81,0.0,1,48,Urban,HR Executive,47786,1 +116658,Male,24,High School,19,69,96,6,88,4.0,1,46,Semi-Urban,ML Engineer,57660,0 +116659,Female,25,Bachelors,19,79,11,47,51,3.0,4,23,Urban,ML Engineer,124536,0 +116660,Male,45,Bachelors,7,97,28,60,64,2.0,5,4,Urban,HR Executive,141083,0 +116661,Female,51,Bachelors,4,80,3,80,83,1.0,5,27,Urban,HR Executive,70624,0 +116662,Female,23,Diploma,19,48,72,8,1,0.0,6,50,Semi-Urban,ML Engineer,67917,0 +116663,Male,55,Bachelors,9,74,69,59,25,5.0,7,80,Semi-Urban,Software Engineer,37062,1 +116664,Female,59,Diploma,3,48,84,82,73,7.0,3,35,Urban,Data Analyst,104871,1 +116665,Female,46,Bachelors,13,54,85,43,29,6.0,6,87,Rural,Manager,70160,1 +116666,Male,35,Diploma,15,59,2,68,35,2.0,5,83,Urban,Software Engineer,76248,0 +116667,Male,23,High School,19,69,16,97,80,2.0,4,48,Urban,ML Engineer,116345,0 +116668,Male,26,Bachelors,12,81,64,70,95,1.0,5,41,Rural,ML Engineer,72272,1 +116669,Female,43,Bachelors,12,38,73,10,42,5.0,5,68,Urban,ML Engineer,138827,0 +116670,Female,36,Bachelors,17,24,31,35,92,5.0,1,12,Urban,Software Engineer,20233,0 +116671,Male,59,High School,7,86,23,42,61,9.0,0,6,Urban,HR Executive,148294,0 +116672,Male,53,Diploma,2,98,96,75,71,5.0,6,66,Semi-Urban,Data Analyst,57238,1 +116673,Male,41,Bachelors,3,10,79,55,13,8.0,4,26,Urban,ML Engineer,143823,0 +116674,Male,24,Diploma,9,72,42,48,30,1.0,5,85,Rural,Software Engineer,99771,1 +116675,Male,23,High School,1,91,11,15,44,8.0,0,5,Urban,HR Executive,149450,0 +116676,Female,53,Bachelors,5,26,32,95,65,2.0,4,40,Urban,Software Engineer,30749,0 +116677,Male,50,Bachelors,13,48,55,59,53,4.0,5,11,Semi-Urban,Data Analyst,26767,0 +116678,Female,41,High School,8,79,18,35,87,0.0,3,0,Urban,HR Executive,109208,0 +116679,Male,33,Bachelors,9,79,34,32,62,9.0,2,96,Semi-Urban,ML Engineer,137876,1 +116680,Female,55,Masters,5,72,33,97,96,8.0,4,43,Urban,HR Executive,67937,1 +116681,Male,44,High School,17,10,96,74,97,4.0,1,19,Semi-Urban,Software Engineer,136721,0 +116682,Male,26,Diploma,19,97,6,0,50,3.0,0,51,Urban,Manager,121552,0 +116683,Male,26,High School,0,29,24,6,65,9.0,7,18,Urban,Manager,28553,0 +116684,Male,46,High School,18,57,55,98,69,6.0,6,36,Rural,ML Engineer,20508,1 +116685,Male,57,High School,0,60,38,20,49,7.0,5,32,Rural,ML Engineer,135865,0 +116686,Female,31,Bachelors,14,84,2,81,92,4.0,1,25,Rural,Data Analyst,74071,0 +116687,Male,53,Masters,15,69,41,6,8,5.0,5,23,Semi-Urban,Manager,57518,0 +116688,Other,52,Bachelors,0,57,5,54,16,1.0,0,57,Rural,HR Executive,29682,0 +116689,Female,58,Diploma,10,68,35,82,63,0.0,3,71,Urban,HR Executive,138983,1 +116690,Male,21,Bachelors,10,66,62,84,73,1.0,0,53,Urban,HR Executive,106463,1 +116691,Female,21,Bachelors,1,90,34,16,58,7.0,1,45,Urban,Software Engineer,65541,0 +116692,Female,36,Bachelors,0,3,60,59,29,4.0,6,25,Urban,HR Executive,143245,0 +116693,Other,46,Masters,7,89,28,8,7,1.0,7,27,Rural,ML Engineer,51289,0 +116694,Female,52,Diploma,13,48,38,60,52,2.0,7,73,Semi-Urban,Data Analyst,87734,0 +116695,Male,57,Bachelors,8,14,95,43,75,8.0,3,99,Urban,Manager,70751,1 +116696,Female,38,Bachelors,6,15,59,41,3,4.0,4,73,Urban,ML Engineer,116745,0 +116697,Female,21,High School,10,69,28,49,49,3.0,0,70,Urban,HR Executive,60417,0 +116698,Female,21,Diploma,0,40,46,20,26,2.0,2,3,Urban,ML Engineer,32459,0 +116699,Male,50,Diploma,5,76,69,97,82,2.0,5,85,Urban,HR Executive,65083,1 +116700,Male,36,Bachelors,14,86,10,98,13,1.0,6,62,Urban,Manager,138257,1 +116701,Male,40,Diploma,9,14,43,90,18,9.0,3,68,Urban,ML Engineer,146045,0 +116702,Male,42,Bachelors,16,96,33,87,93,3.0,2,75,Urban,HR Executive,111729,1 +116703,Male,59,Diploma,9,21,36,4,75,9.0,2,99,Semi-Urban,ML Engineer,103322,0 +116704,Female,45,High School,14,49,55,80,29,4.0,4,10,Semi-Urban,Software Engineer,23630,0 +116705,Male,39,Masters,10,68,78,40,51,9.0,7,62,Rural,Manager,96179,1 +116706,Male,40,Diploma,3,69,39,69,55,6.0,3,23,Semi-Urban,Software Engineer,140732,0 +116707,Male,34,Masters,16,78,56,92,63,7.0,6,54,Urban,Data Analyst,136107,1 +116708,Female,29,Diploma,7,3,61,75,92,0.0,3,50,Urban,Manager,123569,0 +116709,Male,21,Masters,9,92,97,5,85,6.0,0,31,Urban,Software Engineer,105059,0 +116710,Male,56,Bachelors,15,66,76,84,78,3.0,3,61,Rural,Data Analyst,108469,1 +116711,Male,49,Bachelors,3,65,63,29,28,5.0,0,22,Urban,ML Engineer,91270,0 +116712,Female,30,Diploma,18,27,19,35,30,7.0,0,54,Urban,Manager,147296,0 +116713,Male,24,PhD,5,43,10,39,94,6.0,1,45,Semi-Urban,Data Analyst,25388,0 +116714,Male,34,Bachelors,9,81,30,21,17,1.0,7,2,Urban,Data Analyst,145158,0 +116715,Male,24,Bachelors,10,51,98,8,47,4.0,7,59,Urban,HR Executive,147066,0 +116716,Male,37,High School,19,97,1,0,67,7.0,0,5,Urban,ML Engineer,56968,0 +116717,Female,52,Bachelors,13,69,68,39,86,4.0,1,56,Rural,Software Engineer,129951,0 +116718,Male,55,PhD,17,85,46,25,21,3.0,2,21,Urban,Software Engineer,72874,0 +116719,Female,49,Masters,13,38,42,88,25,7.0,7,28,Urban,Manager,62127,0 +116720,Male,52,Bachelors,0,69,96,75,5,1.0,5,76,Urban,Data Analyst,77450,1 +116721,Female,28,High School,11,17,37,37,41,2.0,7,49,Urban,Manager,32908,0 +116722,Male,31,Diploma,13,75,19,77,44,3.0,6,24,Rural,Data Analyst,37050,0 +116723,Other,52,Bachelors,14,43,14,83,94,1.0,2,12,Urban,HR Executive,147563,0 +116724,Female,28,Bachelors,8,49,84,65,55,3.0,0,26,Rural,HR Executive,111962,0 +116725,Male,45,Diploma,3,51,68,29,63,1.0,4,74,Urban,Manager,36719,0 +116726,Male,56,Diploma,9,48,11,10,62,0.0,6,53,Semi-Urban,ML Engineer,94667,0 +116727,Male,22,Masters,13,31,34,74,95,4.0,2,63,Urban,Software Engineer,32410,0 +116728,Male,49,Diploma,12,29,25,59,40,1.0,6,11,Urban,HR Executive,35056,0 +116729,Female,49,Bachelors,10,77,82,26,44,0.0,5,96,Urban,Manager,62969,1 +116730,Male,56,Bachelors,3,4,50,50,60,0.0,3,44,Semi-Urban,Manager,113816,0 +116731,Male,57,Diploma,13,21,19,16,23,6.0,3,21,Urban,HR Executive,49853,0 +116732,Female,54,Bachelors,16,3,37,63,77,0.0,1,72,Semi-Urban,HR Executive,30306,0 +116733,Male,47,Masters,13,6,6,89,66,1.0,1,53,Semi-Urban,ML Engineer,49630,0 +116734,Female,34,High School,14,22,78,7,86,6.0,2,64,Urban,Manager,128120,0 +116735,Female,47,Bachelors,4,47,29,94,32,8.0,4,63,Semi-Urban,Data Analyst,93164,0 +116736,Male,32,Masters,9,66,65,12,85,2.0,3,81,Urban,ML Engineer,102012,0 +116737,Male,42,Bachelors,13,45,28,33,67,6.0,7,72,Urban,ML Engineer,140607,0 +116738,Other,44,Bachelors,3,18,99,17,88,6.0,2,14,Rural,Manager,57605,0 +116739,Female,39,High School,17,8,0,55,51,6.0,6,72,Rural,Manager,91729,0 +116740,Male,46,Bachelors,17,43,2,17,55,8.0,4,11,Rural,Software Engineer,115852,0 +116741,Male,41,High School,9,94,39,58,19,4.0,5,40,Rural,Manager,125598,0 +116742,Male,36,Bachelors,12,11,42,33,16,2.0,3,2,Rural,Data Analyst,80434,0 +116743,Female,30,Masters,19,11,64,47,27,2.0,2,26,Semi-Urban,HR Executive,37448,0 +116744,Male,55,Bachelors,7,73,31,99,20,2.0,1,41,Urban,HR Executive,129663,1 +116745,Male,42,High School,9,52,71,67,82,3.0,6,17,Rural,ML Engineer,55664,0 +116746,Other,47,High School,7,34,37,71,94,4.0,2,6,Rural,ML Engineer,49551,0 +116747,Male,38,Diploma,15,14,44,18,1,2.0,0,3,Semi-Urban,Manager,110793,0 +116748,Male,32,Diploma,16,33,12,19,36,3.0,4,96,Semi-Urban,HR Executive,108297,0 +116749,Male,43,High School,14,13,67,70,95,9.0,2,30,Semi-Urban,Software Engineer,80355,0 +116750,Male,43,Bachelors,19,81,42,66,92,3.0,1,1,Semi-Urban,Manager,24896,0 +116751,Female,54,Bachelors,7,63,56,57,62,4.0,5,97,Urban,ML Engineer,45602,1 +116752,Male,26,Bachelors,19,29,2,17,27,1.0,6,59,Urban,Software Engineer,64292,0 +116753,Male,41,Bachelors,13,61,52,69,54,0.0,1,96,Urban,Data Analyst,20469,1 +116754,Male,45,High School,16,72,69,10,45,8.0,1,94,Urban,Data Analyst,71172,1 +116755,Male,57,PhD,18,85,14,14,3,5.0,5,64,Semi-Urban,Software Engineer,31850,0 +116756,Male,57,High School,11,38,22,1,19,9.0,7,40,Urban,ML Engineer,144914,0 +116757,Male,55,High School,2,83,39,90,45,8.0,7,47,Urban,ML Engineer,137214,1 +116758,Male,37,Diploma,9,81,91,85,83,1.0,1,97,Urban,Software Engineer,65773,1 +116759,Male,36,Bachelors,2,96,70,19,3,6.0,4,38,Urban,ML Engineer,20118,0 +116760,Female,59,Diploma,11,4,14,10,44,8.0,5,35,Urban,Data Analyst,66928,0 +116761,Male,22,Masters,16,54,12,42,73,9.0,3,20,Semi-Urban,HR Executive,113998,0 +116762,Male,44,Bachelors,6,48,68,23,38,9.0,7,52,Urban,ML Engineer,93686,0 +116763,Male,38,Bachelors,4,13,63,43,38,5.0,7,17,Rural,Software Engineer,99230,0 +116764,Male,29,High School,7,95,10,85,76,1.0,3,41,Urban,Data Analyst,29966,0 +116765,Female,53,Masters,19,93,17,56,80,7.0,3,32,Urban,Data Analyst,27021,0 +116766,Other,25,Bachelors,3,99,65,65,89,2.0,6,87,Rural,HR Executive,143597,1 +116767,Male,50,PhD,6,98,66,23,31,8.0,1,38,Semi-Urban,Software Engineer,113201,0 +116768,Other,43,Bachelors,9,71,13,1,78,5.0,5,24,Semi-Urban,HR Executive,129785,0 +116769,Male,57,Masters,19,67,96,32,82,8.0,0,37,Semi-Urban,ML Engineer,126937,0 +116770,Other,35,Masters,2,65,5,63,58,8.0,0,10,Urban,HR Executive,47136,0 +116771,Female,29,High School,11,5,93,63,20,2.0,2,23,Urban,Software Engineer,39703,0 +116772,Male,28,High School,5,56,92,79,53,2.0,5,85,Urban,ML Engineer,21883,1 +116773,Male,26,Diploma,10,66,11,44,20,0.0,5,52,Semi-Urban,Manager,55461,0 +116774,Other,57,Bachelors,10,22,43,65,22,0.0,2,20,Urban,Software Engineer,66810,0 +116775,Male,22,Bachelors,18,32,38,10,53,8.0,4,32,Urban,Manager,141477,0 +116776,Male,50,Bachelors,0,24,39,97,43,9.0,3,25,Urban,Data Analyst,124038,0 +116777,Male,31,Diploma,8,32,45,37,24,9.0,2,6,Semi-Urban,ML Engineer,62225,0 +116778,Male,29,Diploma,7,50,97,88,10,8.0,4,92,Urban,Software Engineer,21266,1 +116779,Male,55,Bachelors,16,75,28,10,36,2.0,7,29,Urban,HR Executive,39109,0 +116780,Female,54,Bachelors,2,43,51,76,96,7.0,0,5,Urban,Software Engineer,101107,0 +116781,Female,42,Bachelors,0,92,96,75,73,0.0,5,84,Urban,HR Executive,74745,1 +116782,Male,37,Masters,5,82,32,14,3,2.0,5,97,Urban,HR Executive,27209,0 +116783,Female,47,Bachelors,19,40,46,72,91,5.0,7,86,Urban,Software Engineer,51991,1 +116784,Female,33,Bachelors,4,64,54,54,24,2.0,4,36,Urban,Software Engineer,143462,0 +116785,Male,43,Bachelors,4,53,35,42,21,2.0,5,65,Semi-Urban,ML Engineer,50088,0 +116786,Male,44,Bachelors,0,37,66,57,40,6.0,6,3,Rural,HR Executive,124714,0 +116787,Female,24,PhD,9,6,62,56,42,5.0,2,88,Urban,ML Engineer,31978,0 +116788,Male,42,Diploma,11,45,45,92,0,5.0,4,92,Semi-Urban,Data Analyst,148012,1 +116789,Male,25,Masters,2,5,79,97,70,4.0,5,37,Urban,HR Executive,86384,0 +116790,Male,38,Bachelors,14,35,17,65,72,7.0,7,72,Rural,ML Engineer,46906,0 +116791,Male,55,High School,17,53,47,24,57,0.0,3,67,Urban,HR Executive,23747,0 +116792,Male,50,Diploma,17,60,66,29,76,1.0,3,21,Rural,Manager,117393,0 +116793,Male,52,PhD,11,9,10,22,31,8.0,5,33,Rural,HR Executive,96329,0 +116794,Male,58,High School,0,91,56,95,43,4.0,2,5,Semi-Urban,Data Analyst,101078,1 +116795,Male,33,High School,15,10,95,26,39,6.0,2,5,Urban,ML Engineer,73476,0 +116796,Male,36,Masters,1,63,60,17,36,0.0,7,28,Urban,ML Engineer,52021,0 +116797,Female,47,High School,10,9,93,21,93,8.0,1,48,Semi-Urban,Software Engineer,24004,0 +116798,Female,30,High School,14,68,45,3,83,5.0,3,93,Urban,Data Analyst,89057,0 +116799,Male,33,Bachelors,16,98,91,63,77,6.0,2,70,Semi-Urban,Software Engineer,28447,1 +116800,Other,59,Bachelors,2,95,77,78,11,8.0,5,8,Urban,Software Engineer,65584,1 +116801,Male,58,Diploma,13,6,15,7,44,6.0,0,55,Urban,Manager,133508,0 +116802,Female,56,Diploma,13,42,6,82,22,8.0,4,98,Urban,Data Analyst,60032,0 +116803,Male,27,High School,19,30,67,63,40,1.0,7,7,Urban,Data Analyst,93083,0 +116804,Male,50,Bachelors,18,59,90,70,52,6.0,3,4,Urban,HR Executive,119565,0 +116805,Male,41,Bachelors,17,26,76,3,25,7.0,4,21,Urban,HR Executive,149970,0 +116806,Male,27,Diploma,17,26,10,15,4,3.0,1,82,Urban,HR Executive,21312,0 +116807,Male,43,Masters,19,90,43,23,70,2.0,4,29,Urban,Data Analyst,127149,0 +116808,Male,28,Diploma,16,43,74,96,8,0.0,7,32,Rural,ML Engineer,78348,1 +116809,Male,47,Bachelors,0,17,56,60,88,8.0,1,61,Urban,Manager,128406,0 +116810,Female,36,PhD,17,42,57,80,48,8.0,2,93,Urban,Data Analyst,48592,1 +116811,Male,54,Masters,17,55,35,81,23,1.0,3,5,Urban,ML Engineer,74605,0 +116812,Male,36,Masters,4,27,92,41,51,9.0,4,49,Semi-Urban,HR Executive,74369,0 +116813,Male,32,Masters,15,69,19,76,54,9.0,6,23,Semi-Urban,HR Executive,87637,0 +116814,Female,56,Bachelors,7,57,24,0,30,6.0,1,60,Semi-Urban,HR Executive,143578,0 +116815,Female,36,Diploma,16,63,22,36,60,4.0,3,7,Urban,HR Executive,120965,0 +116816,Female,53,Bachelors,16,21,42,3,12,0.0,1,94,Rural,Manager,21689,0 +116817,Male,44,High School,13,81,89,84,86,4.0,7,95,Urban,ML Engineer,91450,1 +116818,Other,53,Bachelors,1,21,16,66,90,4.0,4,5,Semi-Urban,Software Engineer,61371,0 +116819,Female,33,High School,0,73,29,94,7,3.0,2,62,Urban,ML Engineer,117264,1 +116820,Male,28,Masters,0,58,35,30,57,0.0,7,25,Urban,HR Executive,62056,0 +116821,Male,32,PhD,9,7,80,16,77,0.0,6,54,Rural,Software Engineer,116135,0 +116822,Female,59,Bachelors,2,88,44,74,61,7.0,4,83,Semi-Urban,Software Engineer,38811,1 +116823,Male,42,Diploma,2,12,4,32,17,3.0,4,23,Urban,Data Analyst,22620,0 +116824,Male,53,Diploma,10,97,29,80,88,8.0,1,35,Urban,Data Analyst,35605,1 +116825,Male,55,High School,1,75,37,53,2,7.0,0,13,Urban,Data Analyst,144068,0 +116826,Male,56,Bachelors,17,87,21,68,22,4.0,3,70,Rural,HR Executive,142590,1 +116827,Female,37,Bachelors,8,36,17,95,25,0.0,6,36,Urban,Software Engineer,45934,0 +116828,Female,35,Bachelors,10,81,54,61,24,2.0,0,22,Urban,Software Engineer,44567,0 +116829,Male,29,Masters,4,91,2,1,35,2.0,6,82,Rural,Manager,53747,0 +116830,Male,54,Bachelors,2,71,39,15,36,4.0,2,72,Semi-Urban,Software Engineer,47475,0 +116831,Male,45,Bachelors,18,56,61,13,29,7.0,4,27,Rural,Data Analyst,132075,0 +116832,Male,21,Bachelors,0,93,27,68,40,0.0,3,9,Urban,Data Analyst,138904,0 +116833,Male,59,Bachelors,8,96,97,96,3,8.0,6,11,Urban,HR Executive,93641,1 +116834,Female,21,High School,19,18,69,59,20,8.0,3,45,Rural,ML Engineer,24150,0 +116835,Female,59,Diploma,11,32,80,33,13,9.0,0,0,Urban,HR Executive,81621,0 +116836,Male,35,High School,17,46,30,27,84,3.0,1,81,Rural,Software Engineer,87929,0 +116837,Female,27,High School,11,33,12,51,51,7.0,0,21,Rural,HR Executive,118737,0 +116838,Female,46,High School,8,53,78,26,1,5.0,2,35,Urban,Software Engineer,55978,0 +116839,Female,49,Bachelors,16,94,83,50,63,0.0,7,70,Semi-Urban,ML Engineer,111521,1 +116840,Male,41,Diploma,8,8,88,31,8,7.0,0,64,Urban,Data Analyst,106786,0 +116841,Male,30,High School,12,29,63,63,13,8.0,7,24,Urban,Manager,51629,0 +116842,Male,49,Bachelors,1,56,70,6,76,6.0,1,76,Semi-Urban,Software Engineer,46025,0 +116843,Male,39,Bachelors,9,57,12,15,6,1.0,7,13,Urban,Manager,126575,0 +116844,Female,31,Bachelors,5,53,18,35,90,9.0,1,22,Urban,Software Engineer,42949,0 +116845,Male,29,High School,8,48,34,86,40,7.0,2,43,Urban,HR Executive,110040,0 +116846,Male,30,High School,19,56,22,38,42,9.0,6,90,Semi-Urban,Manager,42205,0 +116847,Male,26,Bachelors,0,53,57,96,98,5.0,5,75,Semi-Urban,Data Analyst,57315,1 +116848,Female,39,PhD,7,5,74,72,78,5.0,4,49,Urban,Software Engineer,105353,0 +116849,Female,35,High School,3,7,22,68,45,2.0,4,48,Urban,ML Engineer,96783,0 +116850,Male,45,Masters,2,74,28,81,70,8.0,0,53,Urban,Manager,148121,1 +116851,Male,56,Diploma,9,35,18,56,4,9.0,2,15,Urban,HR Executive,62033,0 +116852,Female,21,High School,6,11,91,8,7,7.0,7,43,Rural,ML Engineer,72813,0 +116853,Male,33,Bachelors,9,37,86,84,10,9.0,0,51,Urban,Manager,20919,1 +116854,Other,58,High School,16,82,64,81,37,0.0,7,76,Semi-Urban,Data Analyst,111276,1 +116855,Male,39,Bachelors,19,7,53,7,33,1.0,4,77,Urban,Manager,116053,0 +116856,Male,49,PhD,19,88,45,77,93,4.0,4,15,Urban,ML Engineer,94061,0 +116857,Female,38,Diploma,10,28,2,17,59,1.0,2,46,Urban,Data Analyst,54829,0 +116858,Female,45,Diploma,16,76,74,46,6,9.0,5,7,Urban,Data Analyst,120696,0 +116859,Male,37,Bachelors,7,5,91,60,97,3.0,3,86,Rural,Software Engineer,123657,1 +116860,Female,28,High School,11,56,24,24,67,4.0,2,69,Rural,Data Analyst,137163,0 +116861,Male,55,Bachelors,14,81,73,26,64,0.0,7,10,Urban,HR Executive,144042,0 +116862,Male,43,High School,11,56,89,78,57,1.0,3,38,Semi-Urban,HR Executive,41221,1 +116863,Male,36,Bachelors,6,12,41,29,17,5.0,2,51,Urban,Data Analyst,138783,0 +116864,Female,54,Bachelors,14,28,74,40,55,8.0,1,9,Rural,Manager,131302,0 +116865,Male,50,Bachelors,0,56,96,18,89,6.0,0,66,Urban,HR Executive,42592,1 +116866,Male,53,Bachelors,4,58,28,41,30,1.0,0,38,Urban,HR Executive,79121,0 +116867,Male,43,Bachelors,16,16,49,95,63,1.0,5,36,Semi-Urban,Software Engineer,136080,0 +116868,Female,39,Bachelors,16,67,57,6,18,5.0,6,11,Semi-Urban,ML Engineer,109925,0 +116869,Other,29,Bachelors,18,11,50,21,31,1.0,4,77,Rural,HR Executive,60019,0 +116870,Male,30,Bachelors,1,55,50,70,87,9.0,1,79,Urban,Software Engineer,119051,1 +116871,Male,31,Bachelors,17,28,93,11,63,1.0,7,54,Urban,Manager,31761,0 +116872,Female,22,Bachelors,12,6,10,58,97,6.0,6,1,Semi-Urban,Manager,102195,0 +116873,Male,22,Diploma,9,28,37,81,11,9.0,3,13,Semi-Urban,ML Engineer,131188,0 +116874,Other,33,Masters,9,68,3,58,63,7.0,0,97,Semi-Urban,Manager,59168,0 +116875,Male,37,Bachelors,12,92,98,8,83,3.0,0,5,Rural,ML Engineer,25613,0 +116876,Male,49,PhD,18,97,70,51,35,6.0,1,72,Semi-Urban,Data Analyst,111796,1 +116877,Female,53,High School,5,79,7,62,72,9.0,6,79,Urban,Manager,45711,0 +116878,Female,23,Bachelors,3,89,69,21,50,5.0,3,13,Semi-Urban,ML Engineer,118195,0 +116879,Male,56,Diploma,18,75,97,52,73,6.0,4,50,Semi-Urban,Software Engineer,107412,1 +116880,Female,38,PhD,10,97,60,46,7,0.0,0,30,Urban,Software Engineer,128612,0 +116881,Male,26,High School,7,41,41,78,98,9.0,2,26,Semi-Urban,Data Analyst,63770,0 +116882,Male,44,Bachelors,2,48,64,81,64,8.0,4,56,Rural,HR Executive,130231,1 +116883,Male,35,Bachelors,17,50,75,75,10,3.0,6,89,Semi-Urban,HR Executive,119142,1 +116884,Female,31,Diploma,3,81,55,77,44,2.0,4,3,Urban,Data Analyst,74511,0 +116885,Female,26,Masters,7,2,8,60,97,8.0,6,59,Urban,HR Executive,66825,0 +116886,Male,39,Bachelors,16,40,28,22,1,7.0,3,68,Urban,HR Executive,24289,0 +116887,Male,39,Masters,13,43,68,14,78,6.0,0,74,Rural,Manager,124409,0 +116888,Female,59,Masters,6,47,25,56,46,6.0,5,6,Semi-Urban,HR Executive,37720,0 +116889,Male,58,Masters,9,73,56,84,89,7.0,7,33,Semi-Urban,Data Analyst,99353,1 +116890,Male,54,Bachelors,7,6,10,88,47,3.0,4,47,Urban,HR Executive,116416,0 +116891,Male,58,Bachelors,0,54,45,28,19,9.0,2,19,Semi-Urban,HR Executive,41226,0 +116892,Male,37,Masters,15,93,8,13,89,8.0,0,16,Urban,Manager,93336,0 +116893,Female,53,Diploma,6,95,86,87,6,9.0,5,18,Semi-Urban,Data Analyst,50207,1 +116894,Female,55,Bachelors,3,47,38,36,53,7.0,7,90,Semi-Urban,Manager,147924,0 +116895,Male,39,Masters,10,10,97,2,4,4.0,7,59,Urban,ML Engineer,50645,0 +116896,Male,35,Masters,2,36,43,13,43,6.0,2,81,Urban,Manager,139472,0 +116897,Male,28,Bachelors,13,77,24,49,38,8.0,5,89,Semi-Urban,Software Engineer,55684,1 +116898,Male,42,Bachelors,14,20,64,88,35,0.0,5,6,Rural,Software Engineer,38013,0 +116899,Other,39,High School,12,29,73,50,62,3.0,4,2,Urban,HR Executive,52663,0 +116900,Male,23,Bachelors,14,27,37,40,36,8.0,3,8,Urban,Data Analyst,107138,0 +116901,Male,42,PhD,0,80,83,30,54,4.0,6,33,Urban,ML Engineer,98735,0 +116902,Male,39,Masters,15,77,18,76,48,4.0,0,78,Urban,Data Analyst,144237,1 +116903,Male,55,Masters,13,65,46,38,91,8.0,0,96,Urban,ML Engineer,31472,1 +116904,Other,31,PhD,1,9,46,36,0,8.0,6,55,Urban,ML Engineer,65679,0 +116905,Male,56,Diploma,17,22,28,20,62,5.0,3,93,Semi-Urban,HR Executive,38040,0 +116906,Male,27,High School,19,93,77,20,54,9.0,3,51,Urban,Data Analyst,57884,1 +116907,Male,25,High School,10,98,46,78,14,9.0,5,54,Semi-Urban,Software Engineer,84723,1 +116908,Female,30,Bachelors,7,67,42,98,45,4.0,0,86,Semi-Urban,ML Engineer,40383,1 +116909,Male,56,Masters,4,86,19,86,79,5.0,4,26,Urban,Software Engineer,105906,0 +116910,Male,28,Masters,14,76,68,88,28,0.0,1,50,Urban,Software Engineer,80048,1 +116911,Female,59,Masters,9,7,37,52,8,4.0,0,82,Urban,HR Executive,130237,0 +116912,Male,23,Diploma,9,3,20,62,57,9.0,2,53,Urban,ML Engineer,116157,0 +116913,Female,54,High School,6,59,27,78,47,5.0,0,84,Urban,Software Engineer,141821,1 +116914,Male,31,Masters,5,31,27,60,82,0.0,7,48,Urban,Software Engineer,37695,0 +116915,Female,22,Bachelors,11,93,86,92,80,0.0,4,25,Semi-Urban,ML Engineer,140082,1 +116916,Male,25,Masters,0,55,38,60,17,3.0,5,6,Rural,Data Analyst,84398,0 +116917,Female,22,Masters,0,56,60,54,12,7.0,2,85,Semi-Urban,HR Executive,46756,1 +116918,Male,31,Bachelors,9,75,71,77,45,2.0,0,61,Urban,Manager,138720,1 +116919,Male,29,Bachelors,11,93,99,17,16,6.0,7,18,Urban,Data Analyst,133640,0 +116920,Male,47,Bachelors,8,65,94,49,45,3.0,7,23,Urban,ML Engineer,119812,0 +116921,Female,35,Bachelors,5,80,94,78,30,9.0,5,69,Urban,Software Engineer,128677,1 +116922,Male,44,Bachelors,13,29,29,81,46,7.0,7,88,Semi-Urban,Data Analyst,60449,0 +116923,Male,32,Bachelors,15,92,71,25,69,9.0,5,97,Rural,HR Executive,57359,1 +116924,Male,48,High School,7,94,22,16,30,0.0,1,10,Urban,Data Analyst,32305,0 +116925,Male,57,Bachelors,15,50,28,64,23,3.0,2,9,Urban,ML Engineer,133435,0 +116926,Female,21,Bachelors,18,57,94,79,44,0.0,0,66,Urban,Data Analyst,137659,1 +116927,Female,23,High School,1,92,69,49,22,0.0,1,71,Semi-Urban,ML Engineer,27588,1 +116928,Female,22,Masters,1,96,30,31,95,1.0,2,20,Semi-Urban,ML Engineer,76715,0 +116929,Male,30,Bachelors,16,63,47,23,60,6.0,7,75,Urban,ML Engineer,69920,0 +116930,Male,25,Bachelors,5,29,55,97,74,7.0,3,72,Semi-Urban,Manager,46342,1 +116931,Female,48,Masters,14,94,62,50,74,7.0,1,72,Urban,ML Engineer,124173,1 +116932,Female,24,Diploma,16,14,28,69,63,0.0,5,23,Urban,Data Analyst,25217,0 +116933,Other,51,Bachelors,9,70,24,93,94,5.0,3,35,Urban,Data Analyst,74220,0 +116934,Male,50,PhD,10,1,40,26,25,9.0,7,48,Rural,Manager,34157,0 +116935,Female,39,Bachelors,19,7,6,21,69,1.0,1,16,Urban,Manager,111499,0 +116936,Female,23,Bachelors,18,91,67,10,20,9.0,5,91,Rural,HR Executive,68159,1 +116937,Female,34,Diploma,6,86,92,57,14,8.0,3,31,Semi-Urban,Data Analyst,50368,1 +116938,Female,39,Bachelors,4,71,74,60,78,3.0,4,72,Urban,Software Engineer,60372,1 +116939,Male,31,Masters,2,30,50,95,80,1.0,5,15,Rural,Data Analyst,26783,0 +116940,Female,42,Bachelors,5,84,70,63,65,4.0,4,27,Urban,Data Analyst,110896,1 +116941,Male,33,Diploma,7,99,4,18,31,9.0,5,79,Semi-Urban,Data Analyst,33816,0 +116942,Other,40,Bachelors,12,23,87,38,49,8.0,5,71,Urban,HR Executive,83526,0 +116943,Male,49,High School,13,71,73,52,36,3.0,1,13,Semi-Urban,Data Analyst,124214,0 +116944,Male,40,High School,19,26,18,30,37,2.0,2,7,Semi-Urban,HR Executive,115455,0 +116945,Female,41,Bachelors,19,65,0,94,74,8.0,4,25,Urban,ML Engineer,104656,0 +116946,Male,31,Bachelors,13,36,31,41,24,7.0,4,62,Rural,Data Analyst,78434,0 +116947,Female,37,Masters,5,78,1,83,90,3.0,6,46,Urban,Manager,64479,0 +116948,Male,55,Bachelors,9,50,54,5,48,9.0,3,91,Semi-Urban,Data Analyst,32181,0 +116949,Other,32,Bachelors,3,37,9,44,56,9.0,4,21,Urban,HR Executive,70670,0 +116950,Female,24,Bachelors,15,97,43,82,21,4.0,6,44,Urban,Manager,115253,1 +116951,Female,36,PhD,10,33,38,34,17,6.0,2,37,Urban,HR Executive,79352,0 +116952,Female,50,Diploma,8,26,12,83,16,0.0,1,98,Urban,HR Executive,99263,0 +116953,Male,59,Bachelors,12,58,21,43,81,3.0,7,46,Urban,Software Engineer,104006,0 +116954,Male,34,Diploma,5,73,34,65,39,9.0,0,80,Urban,Data Analyst,126044,1 +116955,Male,45,Masters,7,46,56,89,83,9.0,0,7,Rural,HR Executive,22695,0 +116956,Female,51,Bachelors,13,34,46,4,94,1.0,1,51,Semi-Urban,ML Engineer,33140,0 +116957,Female,36,Bachelors,16,19,79,34,94,8.0,4,89,Urban,Data Analyst,140376,0 +116958,Female,28,Diploma,13,40,78,22,18,6.0,0,11,Urban,Software Engineer,97847,0 +116959,Female,47,Bachelors,13,40,98,91,26,1.0,3,41,Rural,Manager,56956,1 +116960,Male,46,Diploma,11,99,57,24,90,1.0,7,20,Urban,Software Engineer,144204,0 +116961,Female,24,High School,4,92,86,62,5,0.0,7,53,Urban,ML Engineer,56325,1 +116962,Female,47,Bachelors,7,55,58,99,72,8.0,4,36,Rural,HR Executive,50107,1 +116963,Male,24,Bachelors,16,90,93,26,35,4.0,2,46,Urban,Software Engineer,25637,1 +116964,Female,36,Bachelors,7,71,3,10,30,7.0,7,72,Rural,ML Engineer,120136,0 +116965,Female,45,Diploma,3,98,39,71,90,5.0,0,89,Rural,Manager,92261,1 +116966,Female,59,Bachelors,17,74,4,54,62,0.0,3,0,Rural,HR Executive,73991,0 +116967,Female,26,Bachelors,4,78,29,49,0,0.0,7,72,Urban,Data Analyst,74683,0 +116968,Male,44,Masters,14,3,47,94,89,7.0,5,3,Rural,Data Analyst,66708,0 +116969,Female,38,High School,1,38,30,92,24,9.0,5,0,Semi-Urban,Data Analyst,40899,0 +116970,Female,59,Masters,17,16,10,89,32,7.0,3,94,Urban,Data Analyst,23001,0 +116971,Female,58,Bachelors,11,26,17,99,60,5.0,5,60,Semi-Urban,Data Analyst,61267,0 +116972,Female,29,Bachelors,16,79,37,90,56,3.0,7,44,Rural,HR Executive,95847,1 +116973,Male,22,Bachelors,10,53,50,79,20,5.0,0,97,Semi-Urban,ML Engineer,80340,1 +116974,Male,52,PhD,9,87,88,67,40,3.0,3,7,Urban,Software Engineer,100535,1 +116975,Female,48,High School,10,67,93,2,69,4.0,2,15,Urban,ML Engineer,114026,0 +116976,Male,27,Bachelors,4,91,11,42,46,5.0,3,11,Rural,Software Engineer,76276,0 +116977,Male,51,Bachelors,16,55,18,29,34,3.0,0,58,Urban,HR Executive,140991,0 +116978,Female,59,Bachelors,15,41,8,38,66,7.0,7,82,Urban,ML Engineer,43279,0 +116979,Male,57,Bachelors,1,31,77,83,76,4.0,2,27,Urban,Data Analyst,99297,0 +116980,Female,27,Masters,18,80,8,5,32,4.0,2,1,Urban,ML Engineer,50592,0 +116981,Other,44,Bachelors,5,85,82,16,19,5.0,7,13,Semi-Urban,Manager,113119,0 +116982,Male,37,Masters,19,58,14,42,37,9.0,3,34,Semi-Urban,ML Engineer,38482,0 +116983,Male,23,Masters,17,26,58,43,96,5.0,5,18,Urban,HR Executive,28371,0 +116984,Male,32,Bachelors,3,84,36,40,70,0.0,7,21,Urban,ML Engineer,129913,0 +116985,Female,39,Masters,16,90,42,93,53,3.0,3,77,Urban,Data Analyst,137319,1 +116986,Other,27,High School,13,31,57,48,37,8.0,1,72,Urban,Manager,84771,0 +116987,Male,34,Bachelors,4,77,61,1,29,3.0,5,61,Urban,Software Engineer,72869,0 +116988,Male,40,PhD,7,85,0,80,38,2.0,2,5,Urban,Software Engineer,134099,0 +116989,Female,52,Bachelors,9,1,13,89,52,2.0,1,7,Urban,Manager,43134,0 +116990,Female,53,Masters,14,74,54,36,37,9.0,1,15,Urban,Data Analyst,144992,0 +116991,Female,32,Diploma,14,22,91,69,77,0.0,6,35,Semi-Urban,Manager,104006,0 +116992,Female,24,High School,12,13,16,91,86,8.0,4,27,Rural,HR Executive,98766,0 +116993,Male,45,Masters,0,92,11,20,78,9.0,3,97,Urban,ML Engineer,67234,0 +116994,Male,47,Masters,17,13,75,68,56,8.0,4,8,Semi-Urban,HR Executive,51941,0 +116995,Female,41,Masters,8,23,6,57,74,1.0,3,29,Semi-Urban,Manager,129337,0 +116996,Male,59,PhD,15,94,56,22,61,5.0,7,78,Urban,HR Executive,120018,1 +116997,Male,37,Bachelors,13,57,90,97,2,3.0,5,22,Semi-Urban,Manager,146029,1 +116998,Male,33,Bachelors,18,50,14,34,45,5.0,3,84,Urban,Data Analyst,117259,0 +116999,Male,42,Bachelors,15,50,25,8,43,3.0,0,16,Rural,Software Engineer,102885,0 +117000,Male,49,Bachelors,16,44,21,29,72,0.0,4,60,Rural,HR Executive,134251,0 +117001,Male,40,Diploma,9,41,87,46,13,8.0,0,66,Urban,Software Engineer,83431,1 +117002,Male,36,Masters,5,62,42,28,45,9.0,1,86,Semi-Urban,Manager,114970,0 +117003,Male,42,High School,9,79,65,42,75,5.0,7,12,Urban,Manager,87318,0 +117004,Male,45,Bachelors,9,2,78,39,86,4.0,2,89,Urban,ML Engineer,140632,0 +117005,Male,55,Masters,0,86,28,4,47,0.0,2,58,Urban,ML Engineer,44294,0 +117006,Male,37,High School,15,53,53,57,87,6.0,4,21,Urban,Software Engineer,28656,0 +117007,Male,29,Diploma,12,49,52,49,97,9.0,5,96,Rural,Software Engineer,60606,1 +117008,Male,46,Bachelors,6,40,90,74,92,2.0,5,82,Urban,Software Engineer,66191,1 +117009,Male,31,Masters,19,20,91,18,19,9.0,4,42,Semi-Urban,Data Analyst,115133,0 +117010,Male,57,Bachelors,13,80,62,79,87,6.0,4,72,Urban,Software Engineer,71775,1 +117011,Female,40,High School,11,57,74,52,21,4.0,7,18,Rural,HR Executive,79090,0 +117012,Male,47,High School,15,23,0,29,63,6.0,5,32,Urban,HR Executive,149547,0 +117013,Female,33,Bachelors,19,93,43,0,45,7.0,5,33,Urban,Data Analyst,112358,0 +117014,Male,52,High School,2,97,75,88,37,7.0,5,18,Urban,ML Engineer,25426,1 +117015,Male,59,Bachelors,9,39,27,66,91,4.0,7,22,Urban,Manager,96800,0 +117016,Female,59,Diploma,13,36,36,91,34,1.0,6,82,Rural,ML Engineer,144795,1 +117017,Female,45,Bachelors,1,24,69,54,38,8.0,3,95,Semi-Urban,Manager,85260,1 +117018,Female,35,Masters,14,17,58,81,50,3.0,0,56,Urban,Manager,35716,0 +117019,Male,50,Masters,16,83,75,98,7,6.0,5,43,Urban,Software Engineer,136302,1 +117020,Male,58,Diploma,12,6,94,56,63,3.0,1,23,Semi-Urban,Manager,35124,0 +117021,Male,23,Bachelors,16,71,83,72,92,1.0,3,53,Semi-Urban,Manager,148243,1 +117022,Male,29,Bachelors,8,67,23,10,33,5.0,2,77,Semi-Urban,Data Analyst,122244,0 +117023,Male,52,High School,1,12,0,71,17,3.0,3,9,Semi-Urban,Manager,132585,0 +117024,Female,51,High School,3,19,27,66,32,9.0,6,68,Rural,HR Executive,83175,0 +117025,Other,53,PhD,19,36,72,60,89,2.0,5,74,Urban,Manager,26991,1 +117026,Male,41,Bachelors,2,98,79,67,1,7.0,2,1,Semi-Urban,Software Engineer,62898,1 +117027,Female,35,Masters,6,82,1,52,73,6.0,6,74,Urban,Manager,20251,0 +117028,Female,28,Masters,15,95,36,88,30,8.0,5,55,Rural,ML Engineer,82134,1 +117029,Male,40,High School,6,69,87,49,92,1.0,4,74,Urban,Data Analyst,72796,1 +117030,Female,26,Diploma,7,78,86,59,6,9.0,6,51,Urban,HR Executive,146503,1 +117031,Male,50,Bachelors,17,50,49,72,87,9.0,6,16,Urban,Software Engineer,71896,0 +117032,Female,48,Bachelors,14,78,95,7,19,6.0,5,17,Rural,Manager,67428,0 +117033,Male,50,Diploma,1,43,92,11,79,9.0,4,65,Semi-Urban,HR Executive,52800,0 +117034,Female,55,Bachelors,13,59,11,40,87,8.0,6,43,Urban,Software Engineer,105179,0 +117035,Female,45,Bachelors,14,69,58,91,18,4.0,2,36,Rural,Data Analyst,52128,1 +117036,Female,26,Diploma,17,75,96,95,8,6.0,7,71,Rural,ML Engineer,32920,1 +117037,Female,44,Bachelors,11,4,42,48,74,5.0,3,62,Urban,ML Engineer,145458,0 +117038,Female,52,High School,2,44,99,87,79,6.0,5,44,Urban,ML Engineer,116040,1 +117039,Male,58,Bachelors,8,94,84,45,90,3.0,2,42,Rural,HR Executive,89053,1 +117040,Female,31,Masters,18,58,6,18,89,0.0,6,30,Urban,Data Analyst,92232,0 +117041,Female,23,Diploma,12,1,63,60,86,3.0,2,80,Semi-Urban,ML Engineer,64551,0 +117042,Female,58,Masters,3,59,3,80,61,0.0,1,91,Rural,Data Analyst,57028,0 +117043,Male,52,Diploma,3,78,50,13,59,6.0,4,83,Rural,Manager,27386,0 +117044,Male,56,Bachelors,10,30,25,92,14,2.0,7,39,Urban,ML Engineer,66139,0 +117045,Female,22,Masters,4,7,49,44,96,6.0,0,53,Urban,Software Engineer,43160,0 +117046,Other,24,PhD,2,42,71,52,9,5.0,7,22,Urban,ML Engineer,80794,0 +117047,Male,48,Masters,2,77,87,74,43,9.0,7,69,Semi-Urban,Manager,116858,1 +117048,Female,43,Diploma,18,99,93,75,47,5.0,3,23,Urban,ML Engineer,84045,1 +117049,Male,50,Bachelors,15,95,64,44,0,8.0,5,39,Urban,Manager,29383,1 +117050,Female,40,Bachelors,2,47,30,6,54,7.0,5,32,Rural,Manager,34719,0 +117051,Female,30,Bachelors,11,21,32,8,90,9.0,4,76,Urban,Manager,123709,0 +117052,Male,58,Diploma,13,30,19,69,37,8.0,5,68,Semi-Urban,Manager,48540,0 +117053,Female,53,Masters,0,76,34,73,80,9.0,7,71,Urban,HR Executive,129614,1 +117054,Male,32,Masters,9,37,93,95,99,1.0,1,9,Urban,Software Engineer,34386,0 +117055,Male,56,Bachelors,12,20,54,86,79,5.0,1,30,Urban,ML Engineer,146621,0 +117056,Female,36,Bachelors,4,44,93,61,22,8.0,2,43,Urban,HR Executive,79894,1 +117057,Male,49,Diploma,12,0,91,83,23,0.0,2,64,Rural,HR Executive,40024,1 +117058,Female,52,Bachelors,5,50,55,60,34,4.0,1,76,Urban,ML Engineer,30302,1 +117059,Female,22,Diploma,6,65,40,1,2,7.0,4,19,Rural,Manager,42708,0 +117060,Female,40,High School,15,8,17,68,56,3.0,1,48,Urban,Software Engineer,137573,0 +117061,Male,33,High School,4,21,32,69,14,8.0,1,48,Urban,ML Engineer,140896,0 +117062,Male,59,Diploma,5,43,71,92,17,3.0,1,8,Urban,Software Engineer,21506,0 +117063,Male,35,Masters,16,59,67,7,10,5.0,6,33,Rural,HR Executive,132723,0 +117064,Male,34,High School,1,45,83,67,29,3.0,1,14,Urban,ML Engineer,85054,0 +117065,Male,29,Diploma,14,68,90,45,99,1.0,3,17,Urban,Software Engineer,64913,0 +117066,Male,52,Masters,19,63,47,15,20,6.0,2,48,Urban,Data Analyst,118103,0 +117067,Male,31,Bachelors,15,30,44,68,77,1.0,7,64,Semi-Urban,Software Engineer,105109,0 +117068,Female,48,Bachelors,2,4,69,98,13,6.0,5,85,Urban,HR Executive,75226,1 +117069,Male,24,PhD,19,86,47,31,15,7.0,7,92,Semi-Urban,HR Executive,87888,1 +117070,Male,44,Diploma,14,64,41,76,22,6.0,5,41,Rural,Software Engineer,62474,0 +117071,Male,29,Bachelors,17,81,42,57,20,8.0,7,30,Urban,Software Engineer,29812,0 +117072,Female,25,Masters,19,34,90,70,19,7.0,1,13,Urban,HR Executive,32703,0 +117073,Other,27,Masters,7,86,20,31,41,9.0,1,52,Semi-Urban,ML Engineer,94610,0 +117074,Male,31,Masters,8,48,29,98,85,4.0,4,77,Semi-Urban,Data Analyst,101996,1 +117075,Male,52,Masters,17,21,27,51,29,9.0,3,41,Urban,Manager,69481,0 +117076,Male,48,Bachelors,15,34,61,84,93,4.0,6,71,Urban,Data Analyst,22641,1 +117077,Female,39,Bachelors,7,75,53,26,21,0.0,5,71,Semi-Urban,Software Engineer,33293,0 +117078,Male,41,Bachelors,18,19,5,66,77,4.0,7,23,Urban,HR Executive,89986,0 +117079,Male,29,Diploma,7,8,0,24,13,5.0,1,13,Urban,Software Engineer,90560,0 +117080,Male,53,Bachelors,3,12,47,31,76,4.0,4,84,Semi-Urban,Data Analyst,109328,0 +117081,Female,45,Diploma,16,67,13,73,87,6.0,1,85,Urban,ML Engineer,45059,0 +117082,Male,22,Bachelors,13,66,40,29,86,9.0,1,27,Semi-Urban,Data Analyst,75511,0 +117083,Male,45,Bachelors,3,13,78,44,98,0.0,1,10,Urban,Manager,30976,0 +117084,Male,36,Masters,0,97,62,38,34,3.0,5,21,Urban,ML Engineer,134457,0 +117085,Other,30,Masters,8,32,35,6,51,9.0,3,26,Semi-Urban,ML Engineer,135535,0 +117086,Male,23,Bachelors,7,8,98,79,72,8.0,5,67,Rural,Software Engineer,70437,1 +117087,Male,31,Masters,0,63,91,40,31,4.0,2,67,Semi-Urban,Manager,136396,1 +117088,Male,42,Masters,17,1,50,26,27,4.0,4,61,Urban,Software Engineer,28498,0 +117089,Female,54,Diploma,17,93,81,15,68,2.0,3,44,Rural,Data Analyst,55903,0 +117090,Male,21,High School,5,87,56,56,26,5.0,5,41,Urban,Software Engineer,52434,1 +117091,Male,41,Masters,18,74,32,52,60,5.0,5,35,Urban,Software Engineer,39929,0 +117092,Male,30,Diploma,10,40,67,55,86,5.0,6,75,Urban,ML Engineer,140655,1 +117093,Male,38,Masters,5,33,26,55,70,5.0,1,6,Rural,ML Engineer,136005,0 +117094,Female,24,High School,3,20,60,11,60,7.0,3,7,Urban,Manager,128496,0 +117095,Male,41,Diploma,13,6,18,24,25,1.0,0,99,Urban,ML Engineer,77460,0 +117096,Male,28,Masters,12,99,11,20,85,0.0,7,5,Urban,ML Engineer,76598,0 +117097,Male,58,Diploma,2,7,41,74,15,6.0,4,19,Urban,Manager,99254,0 +117098,Male,45,Bachelors,19,7,37,67,93,1.0,1,68,Urban,HR Executive,131954,0 +117099,Male,50,Bachelors,2,25,22,76,63,7.0,2,46,Semi-Urban,Data Analyst,149450,0 +117100,Male,39,Bachelors,15,35,36,4,41,1.0,1,18,Semi-Urban,Manager,145412,0 +117101,Female,29,High School,2,37,64,34,93,2.0,2,20,Urban,Manager,57798,0 +117102,Male,42,Diploma,17,70,27,32,70,8.0,0,1,Urban,Data Analyst,52419,0 +117103,Male,34,Bachelors,6,28,9,28,33,9.0,3,20,Urban,ML Engineer,114819,0 +117104,Male,36,Bachelors,16,64,84,31,86,6.0,2,0,Rural,ML Engineer,54929,0 +117105,Male,55,Bachelors,0,88,14,35,42,1.0,7,82,Urban,Software Engineer,136743,0 +117106,Female,21,Bachelors,6,34,63,25,57,9.0,5,93,Urban,HR Executive,95580,0 +117107,Female,26,Bachelors,16,25,97,25,47,6.0,5,41,Rural,Data Analyst,121532,0 +117108,Male,45,PhD,4,49,3,9,55,7.0,0,87,Urban,HR Executive,120640,0 +117109,Female,49,Bachelors,15,95,90,82,40,0.0,2,1,Urban,ML Engineer,122669,1 +117110,Male,31,Masters,16,38,11,10,41,8.0,5,28,Urban,HR Executive,77936,0 +117111,Male,34,Diploma,5,90,53,63,65,8.0,3,37,Semi-Urban,Data Analyst,69708,1 +117112,Female,56,Bachelors,9,56,25,51,9,7.0,7,1,Semi-Urban,Data Analyst,87676,0 +117113,Male,46,Masters,16,9,41,6,56,9.0,1,48,Semi-Urban,HR Executive,142710,0 +117114,Male,22,Bachelors,19,24,72,93,34,1.0,4,59,Semi-Urban,Manager,139453,1 +117115,Other,22,Masters,12,49,66,41,61,5.0,7,30,Urban,Software Engineer,56872,0 +117116,Female,52,Masters,15,4,36,24,46,5.0,3,42,Urban,ML Engineer,89372,0 +117117,Female,49,Masters,12,12,29,95,62,7.0,2,36,Rural,ML Engineer,70931,0 +117118,Male,22,Diploma,13,91,33,94,23,5.0,5,18,Urban,HR Executive,98448,1 +117119,Male,27,Diploma,5,21,79,30,93,5.0,0,59,Urban,Data Analyst,87282,0 +117120,Female,55,High School,17,19,13,78,4,6.0,4,33,Urban,Manager,32650,0 +117121,Male,29,Bachelors,0,12,3,18,12,3.0,1,65,Urban,ML Engineer,136457,0 +117122,Male,59,Bachelors,19,60,60,78,39,7.0,5,36,Urban,Data Analyst,97044,0 +117123,Female,37,Bachelors,16,81,11,59,24,4.0,2,80,Semi-Urban,Data Analyst,62231,0 +117124,Male,32,Diploma,16,24,78,95,66,3.0,3,32,Semi-Urban,HR Executive,122119,0 +117125,Male,47,High School,9,74,46,50,63,6.0,3,11,Urban,HR Executive,89944,0 +117126,Male,43,Bachelors,19,62,14,94,12,1.0,7,88,Urban,Software Engineer,149573,1 +117127,Male,40,Diploma,18,70,16,71,75,0.0,3,23,Rural,ML Engineer,121678,0 +117128,Female,37,Masters,18,5,97,53,85,9.0,0,24,Semi-Urban,Manager,21700,0 +117129,Male,59,Bachelors,17,8,74,31,81,9.0,2,89,Urban,ML Engineer,96742,0 +117130,Male,32,Bachelors,10,72,71,50,39,2.0,5,5,Urban,Software Engineer,129317,0 +117131,Male,23,High School,1,66,3,55,26,1.0,3,83,Urban,Data Analyst,59831,0 +117132,Male,31,Masters,5,64,43,52,20,9.0,3,36,Semi-Urban,Data Analyst,105177,0 +117133,Female,41,Bachelors,6,61,94,73,57,5.0,6,14,Semi-Urban,Manager,140287,1 +117134,Female,21,Bachelors,18,67,26,35,66,5.0,5,69,Urban,ML Engineer,121591,0 +117135,Male,48,High School,18,71,75,13,47,4.0,7,18,Urban,Software Engineer,88527,0 +117136,Male,38,Diploma,11,21,11,29,65,7.0,3,41,Urban,Software Engineer,35859,0 +117137,Female,41,High School,13,6,53,41,87,1.0,6,58,Urban,Software Engineer,138852,0 +117138,Male,21,Masters,13,63,40,57,40,2.0,6,56,Semi-Urban,Data Analyst,134090,0 +117139,Male,48,Diploma,14,89,94,13,54,4.0,0,29,Urban,ML Engineer,96295,0 +117140,Male,27,High School,14,14,55,37,79,9.0,3,66,Semi-Urban,HR Executive,137117,0 +117141,Female,48,High School,13,43,17,83,68,2.0,4,76,Urban,Software Engineer,75705,0 +117142,Male,36,Diploma,14,14,74,27,63,4.0,7,50,Urban,ML Engineer,61785,0 +117143,Female,29,Bachelors,4,62,26,17,77,4.0,0,1,Semi-Urban,ML Engineer,47343,0 +117144,Male,21,Bachelors,10,86,19,87,1,3.0,0,59,Semi-Urban,HR Executive,123854,1 +117145,Male,22,Masters,0,34,35,13,58,9.0,1,95,Urban,HR Executive,90555,0 +117146,Female,41,PhD,10,23,47,67,73,9.0,1,96,Semi-Urban,HR Executive,134801,0 +117147,Male,39,Diploma,17,63,50,98,96,0.0,5,56,Rural,HR Executive,73032,1 +117148,Male,59,Bachelors,8,54,4,23,80,3.0,7,57,Rural,HR Executive,143110,0 +117149,Male,32,Bachelors,8,71,19,8,93,1.0,3,66,Urban,Manager,106145,0 +117150,Male,39,High School,19,33,15,22,20,5.0,1,73,Urban,Software Engineer,62927,0 +117151,Female,28,High School,3,36,79,52,27,2.0,2,23,Urban,HR Executive,106042,0 +117152,Male,42,Diploma,7,13,85,22,14,7.0,2,70,Urban,ML Engineer,62536,0 +117153,Male,21,Masters,14,10,16,96,49,0.0,3,19,Urban,Software Engineer,97039,0 +117154,Female,36,Masters,17,5,74,3,74,2.0,5,33,Rural,HR Executive,77551,0 +117155,Male,24,Masters,10,95,48,15,12,9.0,2,82,Urban,Software Engineer,80717,1 +117156,Female,44,Masters,17,57,42,56,53,9.0,0,89,Semi-Urban,Software Engineer,59765,1 +117157,Male,49,High School,5,0,0,45,27,6.0,5,99,Semi-Urban,Software Engineer,26755,0 +117158,Male,57,Diploma,5,32,45,46,9,1.0,7,22,Semi-Urban,Data Analyst,23496,0 +117159,Male,32,Bachelors,17,73,54,99,17,3.0,5,78,Urban,ML Engineer,80600,1 +117160,Male,26,Masters,1,41,7,61,37,5.0,1,13,Urban,Manager,65380,0 +117161,Male,31,Bachelors,9,26,71,23,13,6.0,2,56,Rural,Data Analyst,59636,0 +117162,Male,53,Masters,18,73,51,54,30,1.0,7,97,Urban,Manager,46833,1 +117163,Male,46,Bachelors,0,77,15,6,72,1.0,5,87,Semi-Urban,Software Engineer,94905,0 +117164,Female,58,Masters,3,83,15,54,84,1.0,1,32,Semi-Urban,Data Analyst,37762,0 +117165,Female,51,Masters,18,21,19,74,38,7.0,7,57,Rural,HR Executive,87402,0 +117166,Female,37,Masters,9,69,74,65,82,1.0,2,84,Rural,HR Executive,40429,1 +117167,Male,24,High School,6,73,46,33,97,3.0,0,33,Urban,ML Engineer,123573,0 +117168,Male,38,Bachelors,1,76,12,88,71,5.0,0,4,Urban,Software Engineer,60266,0 +117169,Other,28,Bachelors,16,24,62,29,20,9.0,5,88,Urban,HR Executive,58722,0 +117170,Female,51,Bachelors,9,75,82,43,37,0.0,2,96,Urban,HR Executive,33142,1 +117171,Male,23,Diploma,0,93,25,6,65,4.0,1,86,Semi-Urban,ML Engineer,88628,0 +117172,Female,27,Diploma,15,7,76,29,14,4.0,5,35,Urban,HR Executive,21720,0 +117173,Male,38,PhD,4,17,50,18,71,6.0,4,81,Urban,ML Engineer,149300,0 +117174,Male,39,Bachelors,19,15,81,37,78,2.0,2,53,Urban,Data Analyst,141787,0 +117175,Female,31,Masters,10,89,18,59,67,8.0,2,91,Semi-Urban,ML Engineer,121953,1 +117176,Male,35,Bachelors,0,36,30,4,27,9.0,5,68,Semi-Urban,Software Engineer,84835,0 +117177,Male,27,High School,6,71,20,77,40,2.0,5,18,Urban,Manager,94271,0 +117178,Male,47,Masters,10,35,92,12,48,1.0,2,23,Rural,Data Analyst,60888,0 +117179,Male,31,Bachelors,12,60,60,61,61,6.0,2,93,Rural,Manager,111410,1 +117180,Male,22,Bachelors,0,81,38,43,95,7.0,7,22,Urban,Manager,95663,0 +117181,Female,54,Diploma,15,38,50,67,40,8.0,6,53,Rural,Data Analyst,139854,0 +117182,Male,51,High School,13,83,57,38,91,7.0,6,88,Urban,HR Executive,76864,1 +117183,Female,57,Diploma,15,55,92,81,87,7.0,3,34,Urban,ML Engineer,108871,1 +117184,Male,37,PhD,13,49,41,90,83,5.0,6,14,Urban,HR Executive,140729,0 +117185,Male,45,Diploma,0,41,3,19,95,1.0,3,47,Urban,ML Engineer,72565,0 +117186,Male,46,High School,6,34,43,69,68,3.0,1,60,Semi-Urban,Software Engineer,88235,0 +117187,Male,37,Bachelors,7,5,98,27,33,7.0,0,54,Semi-Urban,Manager,66348,0 +117188,Male,45,Masters,0,81,51,4,0,3.0,2,26,Urban,Data Analyst,60773,0 +117189,Male,49,High School,12,80,33,27,17,6.0,2,42,Urban,Manager,98514,0 +117190,Female,56,Bachelors,3,10,58,79,39,1.0,4,25,Semi-Urban,Software Engineer,129413,0 +117191,Male,42,Bachelors,3,61,97,86,13,8.0,5,28,Urban,Software Engineer,32599,1 +117192,Male,59,High School,12,92,14,72,19,7.0,3,12,Urban,ML Engineer,59345,0 +117193,Male,27,High School,18,30,35,76,67,0.0,7,52,Semi-Urban,ML Engineer,103570,0 +117194,Male,45,Masters,16,98,39,56,95,0.0,1,53,Rural,Data Analyst,59498,1 +117195,Female,25,Bachelors,19,63,16,65,23,0.0,5,23,Rural,ML Engineer,91882,0 +117196,Male,54,High School,1,0,95,29,94,0.0,1,95,Rural,Software Engineer,112976,0 +117197,Female,26,High School,17,5,56,76,60,4.0,0,81,Semi-Urban,Manager,64845,0 +117198,Male,21,Bachelors,6,71,65,26,45,4.0,3,94,Semi-Urban,Data Analyst,79695,1 +117199,Male,54,Diploma,10,94,24,11,58,4.0,0,97,Urban,ML Engineer,89656,0 +117200,Male,48,Bachelors,7,70,42,34,14,5.0,1,7,Urban,ML Engineer,33031,0 +117201,Female,37,Bachelors,3,81,55,2,30,1.0,6,73,Urban,Software Engineer,57816,0 +117202,Male,28,Masters,9,73,71,70,32,8.0,4,55,Urban,Software Engineer,52545,1 +117203,Male,39,Masters,6,0,37,77,95,1.0,5,23,Urban,HR Executive,95951,0 +117204,Female,50,Bachelors,8,40,21,11,90,7.0,1,0,Semi-Urban,Data Analyst,97938,0 +117205,Male,27,Masters,6,31,72,20,31,3.0,6,70,Urban,Manager,126820,0 +117206,Male,35,Masters,9,28,5,46,62,6.0,5,50,Urban,ML Engineer,29762,0 +117207,Other,31,Diploma,8,75,43,71,23,5.0,4,24,Rural,Software Engineer,108790,0 +117208,Male,39,Bachelors,14,64,11,76,39,1.0,7,24,Rural,HR Executive,21591,0 +117209,Male,49,Masters,4,64,81,68,74,7.0,0,64,Urban,ML Engineer,32305,1 +117210,Female,54,PhD,15,76,56,5,40,3.0,7,94,Urban,ML Engineer,125093,0 +117211,Male,54,Diploma,8,37,23,89,71,9.0,6,95,Semi-Urban,Manager,137680,1 +117212,Male,40,Masters,1,66,68,74,87,2.0,1,13,Urban,Data Analyst,57001,0 +117213,Female,59,High School,2,74,68,1,84,5.0,5,50,Urban,Manager,20401,0 +117214,Female,48,Bachelors,11,35,10,60,73,2.0,2,40,Urban,ML Engineer,113413,0 +117215,Female,28,High School,3,18,59,81,27,6.0,0,47,Semi-Urban,Data Analyst,113618,0 +117216,Male,59,Masters,11,15,30,66,65,0.0,6,71,Urban,Data Analyst,38442,0 +117217,Male,30,Bachelors,4,32,1,31,94,8.0,1,32,Urban,Software Engineer,134298,0 +117218,Male,47,Bachelors,0,53,23,6,23,4.0,5,37,Semi-Urban,HR Executive,115101,0 +117219,Male,42,Bachelors,16,14,96,32,79,2.0,1,72,Semi-Urban,ML Engineer,115140,0 +117220,Female,32,Bachelors,15,17,89,73,41,8.0,5,49,Urban,ML Engineer,77669,0 +117221,Female,35,Bachelors,19,0,6,98,83,5.0,4,67,Rural,Data Analyst,57542,0 +117222,Male,37,High School,3,99,98,13,56,2.0,7,74,Urban,ML Engineer,115305,1 +117223,Male,41,Bachelors,14,11,74,65,19,9.0,1,32,Urban,Data Analyst,29920,0 +117224,Female,41,Bachelors,9,4,88,39,53,8.0,7,75,Urban,Manager,119781,0 +117225,Female,43,Masters,2,24,29,84,1,4.0,1,3,Urban,Manager,23244,0 +117226,Female,58,Masters,7,25,89,12,48,6.0,1,87,Urban,Software Engineer,104769,0 +117227,Male,33,Bachelors,12,88,8,4,2,7.0,1,65,Urban,Manager,20765,0 +117228,Female,54,Masters,1,65,69,25,25,5.0,3,55,Urban,HR Executive,106426,0 +117229,Female,57,High School,6,48,6,40,39,9.0,7,51,Rural,HR Executive,53153,0 +117230,Male,58,Diploma,1,26,32,70,16,0.0,1,82,Semi-Urban,Data Analyst,38577,0 +117231,Female,43,Diploma,10,21,70,9,93,5.0,0,72,Rural,Manager,66786,0 +117232,Male,59,Masters,4,56,62,18,1,9.0,6,59,Semi-Urban,Data Analyst,38721,0 +117233,Male,45,High School,6,0,68,9,59,1.0,3,3,Rural,ML Engineer,37298,0 +117234,Male,30,PhD,5,79,24,11,86,6.0,6,61,Rural,Manager,132134,0 +117235,Male,30,Diploma,4,93,32,48,68,3.0,5,34,Semi-Urban,ML Engineer,141680,0 +117236,Female,39,Diploma,0,43,51,93,89,7.0,2,50,Rural,Data Analyst,139870,0 +117237,Male,33,Masters,11,20,98,63,36,9.0,5,65,Semi-Urban,HR Executive,96828,1 +117238,Other,41,Bachelors,13,23,30,72,71,5.0,7,90,Semi-Urban,Software Engineer,103830,0 +117239,Female,50,Masters,13,67,22,99,80,4.0,5,79,Urban,Manager,140115,1 +117240,Female,27,Masters,2,25,37,71,91,1.0,4,91,Rural,ML Engineer,138139,0 +117241,Male,34,Diploma,10,27,73,47,50,5.0,3,22,Semi-Urban,Manager,129166,0 +117242,Male,45,Bachelors,4,60,83,0,62,1.0,4,5,Urban,HR Executive,79133,0 +117243,Male,57,Bachelors,12,26,5,32,20,8.0,1,4,Semi-Urban,Software Engineer,146785,0 +117244,Female,42,High School,9,15,89,48,14,7.0,3,63,Semi-Urban,Software Engineer,26805,0 +117245,Female,59,High School,8,17,56,70,61,2.0,7,75,Urban,Data Analyst,141304,0 +117246,Female,51,Diploma,1,35,76,7,23,4.0,7,48,Semi-Urban,ML Engineer,75771,0 +117247,Male,53,Bachelors,13,43,40,15,77,3.0,6,64,Urban,Software Engineer,148055,0 +117248,Male,47,Masters,8,20,24,29,71,7.0,7,91,Rural,Data Analyst,60219,0 +117249,Female,21,Diploma,16,35,49,44,36,7.0,5,3,Rural,Software Engineer,75572,0 +117250,Male,33,Bachelors,0,4,36,21,26,1.0,5,3,Semi-Urban,Data Analyst,74631,0 +117251,Male,32,Bachelors,10,71,27,56,73,6.0,3,88,Urban,Manager,90496,1 +117252,Male,28,High School,17,68,91,43,14,4.0,1,56,Urban,HR Executive,82547,1 +117253,Female,39,Bachelors,7,98,69,62,74,7.0,2,64,Rural,Software Engineer,129460,1 +117254,Female,41,Bachelors,15,75,25,57,88,3.0,6,19,Urban,Software Engineer,137630,0 +117255,Male,57,Masters,5,41,86,22,25,9.0,2,50,Urban,ML Engineer,52159,0 +117256,Male,48,PhD,2,38,31,18,8,6.0,4,98,Urban,Software Engineer,92270,0 +117257,Female,29,Diploma,17,88,11,60,63,6.0,7,67,Semi-Urban,Software Engineer,30718,0 +117258,Male,43,Diploma,13,77,33,86,31,3.0,5,99,Urban,Manager,142088,1 +117259,Male,24,Diploma,7,15,83,88,24,4.0,6,15,Urban,Software Engineer,91169,0 +117260,Female,29,High School,15,68,48,75,35,0.0,0,73,Rural,Software Engineer,59827,1 +117261,Male,59,Masters,15,84,74,78,20,9.0,1,14,Urban,HR Executive,79800,1 +117262,Female,26,Bachelors,13,90,27,30,48,3.0,3,88,Urban,Data Analyst,58659,0 +117263,Male,51,Bachelors,13,50,41,58,2,5.0,7,0,Urban,HR Executive,127839,0 +117264,Female,34,Masters,3,36,80,10,80,6.0,5,88,Semi-Urban,ML Engineer,40734,0 +117265,Male,36,Bachelors,18,87,62,23,13,4.0,0,94,Urban,HR Executive,105752,1 +117266,Female,32,PhD,3,57,5,32,40,6.0,2,16,Urban,ML Engineer,139505,0 +117267,Male,31,Masters,12,11,31,34,14,7.0,5,86,Urban,Data Analyst,149137,0 +117268,Female,50,High School,14,98,73,1,63,0.0,2,41,Urban,ML Engineer,42356,0 +117269,Male,25,Bachelors,17,25,14,41,28,5.0,4,95,Semi-Urban,Software Engineer,45235,0 +117270,Female,53,Diploma,9,78,14,84,39,5.0,7,98,Rural,Manager,49421,1 +117271,Male,34,Bachelors,6,45,0,71,49,9.0,6,85,Rural,HR Executive,93101,0 +117272,Male,23,Bachelors,11,33,11,13,14,4.0,3,85,Urban,Manager,85802,0 +117273,Female,21,Masters,4,26,44,43,45,4.0,3,93,Urban,Data Analyst,37713,0 +117274,Male,23,Bachelors,18,45,16,35,23,5.0,0,56,Semi-Urban,Software Engineer,52584,0 +117275,Female,31,Bachelors,17,20,60,48,94,4.0,3,33,Urban,HR Executive,73116,0 +117276,Male,37,Diploma,2,29,37,34,78,1.0,1,14,Semi-Urban,HR Executive,46234,0 +117277,Male,34,Diploma,18,11,91,88,54,7.0,7,73,Urban,ML Engineer,62852,1 +117278,Male,27,High School,17,82,19,37,99,0.0,4,98,Urban,ML Engineer,59972,1 +117279,Male,31,Bachelors,8,8,99,66,32,1.0,0,76,Semi-Urban,Software Engineer,30698,1 +117280,Male,41,Bachelors,6,60,61,8,66,9.0,0,79,Urban,Software Engineer,92453,0 +117281,Male,55,Bachelors,11,64,55,38,67,6.0,6,82,Urban,ML Engineer,32758,1 +117282,Male,46,Bachelors,7,60,30,29,84,9.0,0,87,Semi-Urban,Software Engineer,126954,0 +117283,Male,54,Bachelors,19,70,71,79,93,4.0,6,47,Semi-Urban,Data Analyst,36045,1 +117284,Male,23,Masters,15,10,16,49,58,2.0,4,1,Urban,ML Engineer,112727,0 +117285,Female,21,Diploma,7,91,59,39,96,7.0,1,0,Semi-Urban,ML Engineer,43889,0 +117286,Female,33,Bachelors,16,90,2,66,25,9.0,7,1,Semi-Urban,Manager,79660,0 +117287,Female,37,PhD,17,39,12,95,84,3.0,6,66,Urban,Software Engineer,25932,0 +117288,Female,35,Bachelors,3,94,99,52,25,5.0,5,97,Rural,HR Executive,96383,1 +117289,Female,29,Diploma,11,23,81,57,34,5.0,5,79,Urban,Manager,114292,0 +117290,Female,36,Bachelors,16,86,40,33,78,8.0,1,91,Urban,Manager,144002,1 +117291,Female,47,PhD,2,85,84,44,70,9.0,3,20,Rural,HR Executive,61731,0 +117292,Male,34,Diploma,13,96,91,91,92,5.0,2,99,Urban,HR Executive,62080,1 +117293,Male,49,Bachelors,3,27,92,10,79,4.0,4,62,Semi-Urban,HR Executive,27687,0 +117294,Male,34,Bachelors,14,18,6,81,58,5.0,0,99,Rural,Software Engineer,50559,0 +117295,Female,40,Diploma,13,24,32,3,72,4.0,1,40,Rural,Data Analyst,89568,0 +117296,Male,49,Bachelors,11,92,82,61,59,0.0,4,22,Rural,Data Analyst,89970,1 +117297,Female,59,Diploma,14,22,95,44,15,5.0,6,0,Semi-Urban,HR Executive,60474,0 +117298,Male,39,Masters,18,52,60,41,41,4.0,6,79,Urban,Software Engineer,149623,0 +117299,Male,51,Masters,15,4,31,31,7,6.0,7,79,Semi-Urban,Data Analyst,81940,0 +117300,Female,43,Diploma,16,21,3,38,92,1.0,5,75,Semi-Urban,ML Engineer,65339,0 +117301,Female,24,Diploma,9,99,91,7,14,7.0,5,29,Semi-Urban,Manager,96134,0 +117302,Female,37,High School,14,9,8,68,78,1.0,7,82,Urban,ML Engineer,104514,0 +117303,Female,31,Bachelors,13,37,83,22,49,9.0,4,55,Urban,Software Engineer,141723,0 +117304,Male,30,Bachelors,9,86,98,65,34,0.0,7,65,Urban,Software Engineer,26146,1 +117305,Female,49,PhD,0,85,53,30,91,4.0,0,5,Semi-Urban,HR Executive,120611,0 +117306,Female,42,Bachelors,5,41,74,40,49,6.0,6,88,Urban,ML Engineer,101415,1 +117307,Female,30,Bachelors,4,98,92,12,98,0.0,2,58,Urban,Manager,117380,1 +117308,Female,51,Bachelors,8,75,2,51,60,9.0,7,28,Urban,HR Executive,113907,0 +117309,Female,31,Diploma,0,95,97,98,38,5.0,7,29,Urban,HR Executive,101639,1 +117310,Male,24,Bachelors,8,5,99,30,86,7.0,2,20,Semi-Urban,Software Engineer,39903,0 +117311,Male,58,Diploma,0,1,32,63,37,5.0,3,87,Urban,HR Executive,122001,0 +117312,Male,32,PhD,19,82,76,1,48,7.0,0,35,Rural,Software Engineer,80704,0 +117313,Male,48,Bachelors,13,90,84,79,92,1.0,2,85,Semi-Urban,Software Engineer,119468,1 +117314,Female,41,Bachelors,2,54,58,77,63,9.0,6,81,Urban,Software Engineer,81161,1 +117315,Female,36,PhD,0,44,29,59,86,7.0,7,43,Rural,Data Analyst,69539,0 +117316,Female,31,High School,0,37,63,23,30,0.0,7,19,Urban,Software Engineer,149233,0 +117317,Female,41,Masters,4,98,27,58,18,7.0,5,44,Urban,Manager,126296,0 +117318,Male,33,Diploma,6,17,23,2,27,1.0,6,50,Rural,ML Engineer,81862,0 +117319,Female,37,Bachelors,19,57,61,49,24,6.0,1,28,Urban,ML Engineer,122698,0 +117320,Male,50,Bachelors,12,41,35,47,10,7.0,4,19,Urban,Software Engineer,107720,0 +117321,Male,27,Bachelors,2,99,93,58,53,3.0,1,39,Semi-Urban,Data Analyst,119238,1 +117322,Male,56,Bachelors,14,16,20,44,77,7.0,6,93,Urban,ML Engineer,47551,0 +117323,Female,38,High School,18,88,26,89,43,6.0,6,35,Semi-Urban,Data Analyst,111414,0 +117324,Female,39,Bachelors,10,39,12,30,45,4.0,2,32,Rural,Software Engineer,139776,0 +117325,Female,22,High School,4,86,18,38,76,2.0,0,28,Semi-Urban,Data Analyst,87614,0 +117326,Female,44,Diploma,0,90,69,66,19,9.0,4,61,Semi-Urban,Software Engineer,68847,1 +117327,Female,40,Bachelors,16,15,64,56,55,5.0,6,89,Urban,Data Analyst,108209,0 +117328,Female,40,High School,5,66,14,75,59,6.0,6,71,Urban,Manager,63016,0 +117329,Male,48,High School,8,62,20,50,91,3.0,5,47,Semi-Urban,Manager,147505,0 +117330,Other,30,Bachelors,1,67,0,64,93,9.0,2,4,Urban,Software Engineer,74015,0 +117331,Male,58,PhD,2,47,11,66,76,3.0,2,53,Semi-Urban,ML Engineer,115730,0 +117332,Male,53,Masters,4,67,32,44,80,4.0,7,86,Urban,Software Engineer,149418,0 +117333,Male,24,PhD,8,22,55,57,56,0.0,5,1,Semi-Urban,Software Engineer,111832,0 +117334,Male,38,Bachelors,9,51,51,70,48,8.0,2,85,Semi-Urban,Data Analyst,84446,1 +117335,Male,25,Bachelors,8,62,38,38,67,3.0,3,95,Urban,ML Engineer,137539,0 +117336,Male,49,Masters,5,56,22,32,53,8.0,4,86,Semi-Urban,Software Engineer,31837,0 +117337,Female,59,Masters,6,78,41,97,2,6.0,6,31,Semi-Urban,Manager,49404,1 +117338,Male,36,Diploma,4,0,49,67,39,6.0,1,77,Semi-Urban,HR Executive,97914,0 +117339,Female,28,Bachelors,14,73,10,88,7,5.0,0,51,Rural,ML Engineer,106371,0 +117340,Female,58,Diploma,7,67,37,10,29,7.0,1,20,Urban,Manager,57913,0 +117341,Female,52,Bachelors,8,49,95,70,50,3.0,1,65,Semi-Urban,ML Engineer,60252,1 +117342,Other,47,Diploma,13,67,55,40,33,6.0,3,62,Urban,HR Executive,69416,0 +117343,Male,55,Masters,15,35,75,62,92,5.0,3,42,Rural,Software Engineer,120480,0 +117344,Other,21,High School,7,44,66,98,15,2.0,4,38,Rural,Software Engineer,20206,1 +117345,Male,33,Masters,15,49,48,27,81,8.0,4,85,Semi-Urban,Data Analyst,99426,0 +117346,Male,35,Diploma,8,57,17,76,4,0.0,4,14,Rural,ML Engineer,54338,0 +117347,Male,57,Bachelors,15,5,75,22,99,5.0,6,5,Semi-Urban,ML Engineer,133958,0 +117348,Female,40,PhD,17,16,63,40,29,8.0,1,11,Rural,HR Executive,135693,0 +117349,Male,29,Diploma,0,86,63,63,19,5.0,0,63,Urban,Data Analyst,104092,1 +117350,Male,55,High School,14,13,50,4,12,7.0,6,51,Semi-Urban,Software Engineer,46894,0 +117351,Male,51,Masters,7,35,30,69,97,7.0,5,23,Urban,Manager,146662,0 +117352,Male,38,High School,12,58,37,59,59,6.0,3,16,Urban,Manager,40776,0 +117353,Female,27,High School,14,75,13,98,39,5.0,4,50,Urban,Software Engineer,32183,0 +117354,Male,30,Bachelors,6,20,70,57,78,6.0,4,12,Semi-Urban,HR Executive,86647,0 +117355,Male,42,Masters,9,51,66,70,16,3.0,4,68,Urban,Software Engineer,146083,1 +117356,Male,36,Bachelors,12,52,56,30,81,7.0,1,86,Rural,HR Executive,138552,0 +117357,Male,45,Bachelors,13,37,41,57,21,4.0,1,77,Semi-Urban,Data Analyst,113108,0 +117358,Male,37,Diploma,17,37,26,88,19,1.0,2,55,Urban,ML Engineer,27641,0 +117359,Male,22,Diploma,15,22,90,87,73,2.0,4,53,Urban,Manager,25970,1 +117360,Male,45,High School,14,88,14,57,23,1.0,6,83,Urban,ML Engineer,23307,1 +117361,Female,43,Bachelors,7,28,31,90,83,0.0,2,85,Urban,Manager,135561,0 +117362,Male,50,Bachelors,14,23,87,58,59,2.0,0,5,Semi-Urban,Software Engineer,115234,0 +117363,Male,35,High School,15,9,3,11,65,0.0,0,49,Rural,Software Engineer,29679,0 +117364,Male,33,Diploma,19,28,48,49,71,4.0,7,98,Semi-Urban,Software Engineer,128873,0 +117365,Female,34,Masters,4,23,43,41,20,2.0,0,97,Urban,ML Engineer,54088,0 +117366,Male,25,High School,12,41,77,95,59,7.0,3,97,Urban,Software Engineer,23630,1 +117367,Male,34,Diploma,10,29,52,71,6,5.0,4,70,Rural,Manager,59629,0 +117368,Male,43,Bachelors,5,68,91,5,13,6.0,5,86,Urban,ML Engineer,114349,1 +117369,Male,30,Bachelors,12,35,54,99,47,8.0,2,50,Urban,Software Engineer,115831,1 +117370,Female,25,PhD,7,30,84,62,30,9.0,6,47,Urban,Software Engineer,34636,0 +117371,Male,26,Diploma,0,73,72,56,53,7.0,7,39,Semi-Urban,Data Analyst,134937,1 +117372,Female,49,Masters,10,70,47,29,60,2.0,1,55,Rural,HR Executive,102647,0 +117373,Male,59,PhD,16,8,74,51,76,0.0,1,28,Rural,Data Analyst,61598,0 +117374,Male,25,Masters,1,75,13,0,61,0.0,4,17,Urban,Manager,70850,0 +117375,Male,30,Masters,8,28,47,40,75,6.0,5,50,Urban,ML Engineer,97749,0 +117376,Female,29,Bachelors,15,28,47,58,60,8.0,7,50,Urban,Manager,78235,0 +117377,Female,45,Diploma,6,97,70,32,61,2.0,2,55,Rural,Data Analyst,21313,1 +117378,Female,50,Diploma,14,59,93,81,52,5.0,1,20,Urban,Software Engineer,140611,1 +117379,Female,32,Masters,6,46,21,47,53,4.0,6,46,Urban,Software Engineer,116368,0 +117380,Male,40,Masters,1,7,60,24,54,5.0,6,70,Urban,Software Engineer,104538,0 +117381,Female,57,Bachelors,6,80,30,21,44,8.0,5,50,Urban,Data Analyst,134785,0 +117382,Male,21,High School,16,97,57,47,54,2.0,7,26,Urban,ML Engineer,132238,0 +117383,Male,21,Masters,19,97,29,2,48,2.0,7,9,Urban,Manager,126294,0 +117384,Male,27,Bachelors,2,90,95,18,52,4.0,2,3,Rural,ML Engineer,46143,0 +117385,Male,44,High School,1,69,43,62,45,8.0,3,58,Semi-Urban,Software Engineer,140606,0 +117386,Female,45,Bachelors,9,48,68,43,78,3.0,4,76,Semi-Urban,Manager,43838,0 +117387,Female,52,Masters,1,73,0,38,13,2.0,6,79,Rural,Data Analyst,25963,0 +117388,Male,36,Diploma,15,32,84,38,94,9.0,4,68,Semi-Urban,HR Executive,78668,0 +117389,Female,45,Bachelors,7,59,97,11,53,1.0,2,16,Semi-Urban,ML Engineer,56037,0 +117390,Female,35,Bachelors,10,68,60,90,38,4.0,7,47,Urban,Manager,74861,1 +117391,Male,49,Bachelors,5,22,61,78,38,5.0,3,67,Urban,ML Engineer,134209,0 +117392,Male,39,Diploma,11,2,97,97,63,6.0,5,83,Semi-Urban,ML Engineer,35489,1 +117393,Male,55,Bachelors,5,53,10,67,12,8.0,0,46,Urban,Software Engineer,140447,0 +117394,Male,47,Bachelors,3,40,0,99,63,0.0,2,40,Semi-Urban,Data Analyst,109916,0 +117395,Other,25,Masters,18,8,53,5,82,5.0,7,81,Urban,ML Engineer,103254,0 +117396,Female,55,Bachelors,15,67,71,25,49,4.0,0,17,Urban,ML Engineer,37174,0 +117397,Male,28,Bachelors,7,58,71,49,47,9.0,4,16,Urban,Software Engineer,137880,0 +117398,Male,47,Bachelors,5,13,14,46,27,5.0,7,88,Urban,Data Analyst,112033,0 +117399,Male,44,High School,16,91,55,34,57,3.0,1,97,Urban,Data Analyst,36997,1 +117400,Male,21,Masters,10,26,75,29,42,3.0,4,30,Semi-Urban,ML Engineer,76552,0 +117401,Male,45,PhD,4,58,8,75,81,6.0,0,80,Semi-Urban,Software Engineer,74266,0 +117402,Female,45,Bachelors,19,13,12,1,36,3.0,2,78,Semi-Urban,Data Analyst,98308,0 +117403,Female,39,Diploma,6,66,59,15,35,5.0,5,4,Urban,Data Analyst,89146,0 +117404,Male,57,Masters,18,60,31,80,57,0.0,1,21,Semi-Urban,ML Engineer,129598,0 +117405,Female,55,Bachelors,15,18,55,84,33,9.0,4,61,Urban,Data Analyst,128829,0 +117406,Male,24,Bachelors,9,32,49,52,26,2.0,4,58,Semi-Urban,ML Engineer,63708,0 +117407,Male,31,Masters,9,81,44,62,49,6.0,5,57,Semi-Urban,Software Engineer,65204,1 +117408,Male,54,Diploma,15,15,67,1,58,3.0,1,92,Urban,ML Engineer,25442,0 +117409,Male,43,Diploma,11,15,12,70,31,5.0,1,37,Semi-Urban,ML Engineer,30146,0 +117410,Female,25,Bachelors,12,72,48,95,21,3.0,3,58,Rural,Software Engineer,110246,1 +117411,Male,24,Masters,4,18,98,73,12,1.0,1,7,Urban,Software Engineer,88491,0 +117412,Male,21,High School,10,92,62,74,18,7.0,7,4,Semi-Urban,Manager,35360,0 +117413,Female,52,Masters,2,44,63,71,83,4.0,5,33,Urban,HR Executive,26447,0 +117414,Female,21,Diploma,14,42,76,50,58,7.0,5,63,Urban,Data Analyst,103420,0 +117415,Female,23,High School,16,68,73,14,94,6.0,4,95,Urban,Software Engineer,113165,1 +117416,Male,50,Bachelors,10,55,83,13,2,9.0,5,6,Urban,Software Engineer,125565,0 +117417,Female,58,Diploma,3,93,20,50,18,8.0,2,54,Urban,Data Analyst,60097,0 +117418,Female,22,Diploma,19,16,95,1,2,9.0,4,34,Semi-Urban,ML Engineer,98302,0 +117419,Other,55,High School,9,33,86,15,5,7.0,6,40,Urban,Software Engineer,140773,0 +117420,Male,50,Bachelors,11,77,91,14,90,1.0,5,5,Urban,ML Engineer,127768,0 +117421,Male,38,Diploma,6,62,18,5,20,2.0,2,8,Urban,HR Executive,147229,0 +117422,Male,55,Bachelors,19,46,35,74,48,2.0,4,30,Urban,ML Engineer,146314,0 +117423,Female,27,Bachelors,4,79,34,38,69,0.0,7,91,Urban,ML Engineer,71352,1 +117424,Male,42,Masters,0,11,55,6,62,5.0,3,30,Urban,HR Executive,43620,0 +117425,Female,29,Diploma,17,69,74,93,6,0.0,6,65,Urban,Software Engineer,54129,1 +117426,Male,27,Masters,0,92,73,32,81,3.0,1,7,Urban,HR Executive,42567,0 +117427,Female,47,Diploma,14,82,90,40,19,8.0,0,54,Semi-Urban,Manager,79161,1 +117428,Male,27,Masters,9,77,25,35,6,5.0,5,78,Rural,ML Engineer,23016,0 +117429,Female,35,Bachelors,18,38,8,83,53,8.0,2,69,Urban,HR Executive,26421,0 +117430,Female,26,Masters,13,13,59,57,19,4.0,5,31,Urban,Manager,124228,0 +117431,Male,50,Diploma,7,75,2,74,59,4.0,4,99,Semi-Urban,Software Engineer,82960,1 +117432,Female,41,Diploma,13,33,47,26,93,0.0,1,28,Semi-Urban,Software Engineer,106422,0 +117433,Male,52,Bachelors,1,4,28,2,57,5.0,3,12,Urban,ML Engineer,41800,0 +117434,Female,50,Masters,5,15,49,84,54,9.0,7,76,Rural,Software Engineer,120175,0 +117435,Female,36,Diploma,0,99,51,76,51,9.0,7,30,Semi-Urban,Manager,131433,1 +117436,Female,32,Bachelors,18,4,87,0,90,1.0,4,23,Urban,Software Engineer,46963,0 +117437,Male,28,Diploma,0,44,55,37,11,1.0,7,42,Rural,Data Analyst,86904,0 +117438,Male,45,Bachelors,4,63,65,63,13,9.0,6,44,Rural,Manager,40281,1 +117439,Male,28,Bachelors,0,96,12,34,40,3.0,2,0,Urban,Data Analyst,63423,0 +117440,Male,35,Diploma,17,90,87,78,98,8.0,5,42,Rural,ML Engineer,107545,1 +117441,Male,53,Bachelors,11,3,85,88,5,1.0,0,33,Urban,ML Engineer,60404,0 +117442,Male,57,High School,13,92,21,24,12,7.0,4,68,Urban,ML Engineer,131871,0 +117443,Female,56,Diploma,2,65,8,95,59,8.0,3,60,Urban,Manager,71992,0 +117444,Male,56,High School,11,63,43,46,80,5.0,0,96,Urban,Software Engineer,146723,1 +117445,Female,51,Bachelors,0,65,64,94,30,6.0,0,97,Urban,Manager,136762,1 +117446,Female,23,Diploma,12,71,54,0,49,7.0,1,40,Urban,HR Executive,24313,0 +117447,Other,46,Bachelors,13,4,82,68,68,5.0,7,2,Urban,ML Engineer,49983,0 +117448,Female,47,Diploma,11,26,23,24,3,5.0,1,52,Urban,HR Executive,92908,0 +117449,Male,25,Bachelors,8,7,10,41,16,0.0,6,93,Urban,Manager,79624,0 +117450,Male,50,Bachelors,13,6,0,1,9,1.0,3,98,Urban,Data Analyst,124815,0 +117451,Male,51,Diploma,10,55,43,47,77,7.0,0,29,Semi-Urban,Data Analyst,86953,0 +117452,Male,40,Diploma,17,95,43,69,51,7.0,0,61,Rural,Software Engineer,140347,1 +117453,Male,52,Masters,9,19,58,4,82,5.0,7,34,Urban,HR Executive,86186,0 +117454,Male,27,Diploma,7,55,24,59,43,2.0,3,76,Urban,HR Executive,95538,0 +117455,Male,55,Bachelors,0,44,1,82,66,1.0,0,17,Urban,Manager,130714,0 +117456,Male,50,Bachelors,12,59,8,46,34,3.0,7,34,Semi-Urban,Data Analyst,137310,0 +117457,Male,38,PhD,15,42,65,42,30,6.0,7,29,Urban,ML Engineer,88373,0 +117458,Male,43,Masters,14,47,5,64,57,1.0,7,76,Semi-Urban,Data Analyst,99445,0 +117459,Male,38,Masters,11,75,33,65,99,3.0,1,74,Semi-Urban,HR Executive,129295,1 +117460,Male,35,Bachelors,9,92,2,85,44,4.0,3,28,Semi-Urban,Data Analyst,117272,0 +117461,Male,39,PhD,3,37,98,46,86,8.0,4,40,Semi-Urban,Software Engineer,133730,0 +117462,Female,54,Masters,3,46,41,89,75,4.0,0,55,Rural,Manager,74004,0 +117463,Female,28,Bachelors,8,94,83,14,53,7.0,6,99,Rural,Manager,95705,1 +117464,Female,45,Bachelors,15,12,67,30,69,3.0,1,92,Urban,ML Engineer,40247,0 +117465,Male,48,Bachelors,6,58,16,52,5,1.0,4,91,Urban,HR Executive,141493,0 +117466,Male,31,Diploma,2,39,84,22,24,4.0,6,57,Urban,ML Engineer,78762,0 +117467,Male,24,PhD,3,23,16,45,24,1.0,2,31,Urban,ML Engineer,149899,0 +117468,Male,32,Bachelors,2,4,53,79,87,1.0,2,45,Urban,Software Engineer,39988,0 +117469,Female,23,Bachelors,6,5,13,39,90,7.0,2,74,Urban,Manager,55288,0 +117470,Female,31,Masters,3,98,23,10,85,9.0,0,17,Urban,HR Executive,92662,0 +117471,Male,23,Diploma,6,76,30,1,96,5.0,4,53,Urban,HR Executive,71245,0 +117472,Female,44,Diploma,7,84,55,25,83,9.0,1,93,Urban,HR Executive,60806,1 +117473,Female,38,Bachelors,10,56,18,56,34,5.0,4,67,Semi-Urban,Data Analyst,68516,0 +117474,Female,22,Masters,5,76,25,84,4,9.0,0,61,Rural,Manager,38018,1 +117475,Female,49,Bachelors,3,62,5,99,22,1.0,7,57,Rural,HR Executive,92074,0 +117476,Female,50,Masters,15,10,30,62,66,2.0,7,6,Urban,Data Analyst,97257,0 +117477,Male,57,High School,15,5,45,35,56,7.0,1,26,Rural,Data Analyst,86384,0 +117478,Female,53,High School,7,99,82,85,88,4.0,7,25,Semi-Urban,Manager,70035,1 +117479,Other,42,Bachelors,6,95,62,10,87,2.0,6,82,Urban,Data Analyst,142772,1 +117480,Male,31,Bachelors,7,71,99,16,52,4.0,7,53,Urban,ML Engineer,24367,1 +117481,Male,34,Bachelors,2,17,0,88,30,9.0,4,49,Urban,HR Executive,62890,0 +117482,Female,51,Diploma,4,0,24,27,93,7.0,0,31,Semi-Urban,Software Engineer,21412,0 +117483,Male,48,Bachelors,9,17,99,34,73,6.0,6,92,Urban,ML Engineer,107430,1 +117484,Male,26,Diploma,2,45,15,43,1,3.0,0,54,Rural,HR Executive,43742,0 +117485,Female,41,Bachelors,5,8,83,53,80,8.0,5,98,Semi-Urban,HR Executive,20170,1 +117486,Female,47,Diploma,15,46,40,9,0,4.0,4,1,Urban,Manager,43725,0 +117487,Male,28,Diploma,18,46,78,12,56,4.0,3,45,Rural,ML Engineer,77495,0 +117488,Male,32,Diploma,9,49,68,77,64,8.0,6,46,Semi-Urban,ML Engineer,33641,1 +117489,Other,55,Bachelors,19,64,74,41,7,9.0,0,38,Urban,Data Analyst,52713,0 +117490,Female,40,Diploma,3,44,1,93,77,8.0,6,33,Semi-Urban,Software Engineer,70572,0 +117491,Other,59,Bachelors,10,77,19,27,18,6.0,7,71,Urban,ML Engineer,42308,0 +117492,Female,58,High School,14,72,24,66,71,1.0,7,11,Rural,ML Engineer,21173,0 +117493,Male,51,Masters,2,75,72,98,48,5.0,2,0,Urban,Data Analyst,55246,1 +117494,Male,49,Bachelors,19,5,14,46,92,8.0,0,47,Semi-Urban,Software Engineer,106112,0 +117495,Male,43,Bachelors,19,42,16,13,31,3.0,7,99,Urban,Data Analyst,30687,0 +117496,Male,25,Masters,11,60,88,68,5,1.0,1,34,Urban,ML Engineer,110858,1 +117497,Male,41,Bachelors,16,76,60,90,11,3.0,2,87,Semi-Urban,HR Executive,78678,1 +117498,Male,59,Diploma,11,48,85,49,34,5.0,0,55,Urban,Manager,82302,1 +117499,Male,39,High School,0,81,21,17,22,3.0,1,64,Semi-Urban,HR Executive,132080,0 +117500,Male,34,PhD,17,67,9,98,8,3.0,7,74,Semi-Urban,HR Executive,44074,1 +117501,Male,58,Masters,4,1,63,50,23,2.0,3,82,Urban,HR Executive,59567,0 +117502,Female,52,Diploma,10,16,0,20,23,9.0,3,9,Rural,Data Analyst,125191,0 +117503,Male,39,High School,3,7,46,99,51,9.0,1,31,Rural,ML Engineer,97999,0 +117504,Male,55,High School,8,88,22,68,37,7.0,1,53,Semi-Urban,ML Engineer,139212,0 +117505,Female,33,Masters,14,89,45,73,32,8.0,0,43,Rural,Software Engineer,56735,1 +117506,Female,48,Bachelors,9,58,68,34,68,8.0,6,51,Urban,ML Engineer,109762,0 +117507,Female,44,Bachelors,16,49,82,72,54,2.0,0,59,Semi-Urban,HR Executive,87026,1 +117508,Female,56,Bachelors,5,56,41,82,40,6.0,0,44,Urban,HR Executive,53397,0 +117509,Female,56,Masters,16,27,49,10,14,0.0,1,78,Semi-Urban,ML Engineer,32648,0 +117510,Male,26,Bachelors,0,53,86,23,29,9.0,6,84,Urban,HR Executive,32588,1 +117511,Male,31,PhD,13,93,39,60,89,2.0,5,63,Urban,HR Executive,67156,1 +117512,Male,37,Bachelors,13,36,72,80,73,5.0,3,71,Rural,Manager,38094,1 +117513,Male,50,High School,9,83,13,91,44,1.0,1,39,Semi-Urban,HR Executive,38059,0 +117514,Female,47,Bachelors,11,96,7,26,69,8.0,6,82,Semi-Urban,Software Engineer,116199,0 +117515,Male,35,Bachelors,8,11,40,48,63,9.0,6,73,Urban,Manager,130041,0 +117516,Male,42,High School,9,84,68,67,82,0.0,6,47,Urban,Data Analyst,88056,1 +117517,Female,58,Diploma,7,56,66,88,66,0.0,5,46,Urban,ML Engineer,28693,1 +117518,Female,59,Bachelors,13,21,66,63,80,2.0,3,28,Rural,ML Engineer,63785,0 +117519,Male,58,High School,16,41,11,94,51,6.0,1,23,Urban,Software Engineer,140138,0 +117520,Male,28,Bachelors,12,72,12,91,13,2.0,3,89,Semi-Urban,HR Executive,36949,1 +117521,Male,30,Bachelors,11,36,65,85,76,6.0,2,94,Urban,Manager,121064,1 +117522,Male,46,Masters,11,70,28,22,13,2.0,5,1,Urban,Manager,57519,0 +117523,Male,58,Bachelors,0,25,66,41,74,7.0,1,42,Rural,Software Engineer,78492,0 +117524,Female,22,PhD,5,3,26,58,65,3.0,5,32,Semi-Urban,HR Executive,40263,0 +117525,Female,36,Bachelors,15,88,35,35,94,0.0,7,84,Urban,ML Engineer,39281,1 +117526,Male,24,Bachelors,6,62,48,28,70,4.0,5,52,Urban,Software Engineer,118389,0 +117527,Male,46,Diploma,17,40,6,1,24,4.0,7,34,Urban,HR Executive,24175,0 +117528,Other,27,Masters,13,65,12,89,18,6.0,2,40,Semi-Urban,Data Analyst,125114,0 +117529,Male,54,Diploma,7,6,18,56,4,6.0,7,29,Rural,Data Analyst,145287,0 +117530,Female,23,Diploma,18,53,52,17,15,0.0,3,14,Urban,Data Analyst,115988,0 +117531,Male,21,Diploma,16,76,18,74,5,5.0,6,35,Semi-Urban,Data Analyst,57373,0 +117532,Male,27,Bachelors,1,98,0,88,99,6.0,7,54,Urban,Software Engineer,122408,1 +117533,Male,35,Bachelors,2,73,32,55,49,3.0,4,9,Semi-Urban,Manager,112910,0 +117534,Female,32,Diploma,5,34,49,47,71,4.0,1,47,Urban,ML Engineer,36627,0 +117535,Female,41,Masters,14,9,50,1,24,8.0,5,94,Rural,Data Analyst,124989,0 +117536,Male,43,Masters,13,77,36,71,69,0.0,0,97,Urban,Manager,69247,1 +117537,Male,58,Bachelors,8,31,89,47,94,1.0,0,31,Semi-Urban,ML Engineer,106206,0 +117538,Male,38,High School,11,76,7,42,90,4.0,7,67,Urban,Data Analyst,41963,0 +117539,Male,48,Bachelors,10,70,25,24,15,2.0,2,46,Urban,Manager,89092,0 +117540,Male,56,Bachelors,15,75,89,4,70,4.0,6,35,Urban,HR Executive,68433,0 +117541,Female,32,PhD,3,71,91,81,36,7.0,3,8,Urban,Software Engineer,34680,1 +117542,Male,23,PhD,9,60,13,6,15,1.0,4,13,Semi-Urban,HR Executive,69431,0 +117543,Male,47,Masters,19,6,31,72,8,8.0,4,91,Rural,Manager,135763,0 +117544,Male,54,Bachelors,14,86,39,58,24,7.0,7,6,Urban,ML Engineer,66512,0 +117545,Male,35,Bachelors,4,44,62,80,93,1.0,7,21,Urban,HR Executive,102614,0 +117546,Male,37,Bachelors,4,22,56,26,22,6.0,1,33,Rural,Data Analyst,126077,0 +117547,Male,29,Bachelors,5,34,75,93,80,9.0,4,52,Semi-Urban,Software Engineer,92513,1 +117548,Male,50,Diploma,10,18,49,85,30,0.0,6,76,Rural,Data Analyst,36214,0 +117549,Female,51,High School,8,5,86,29,84,9.0,1,46,Urban,ML Engineer,25478,0 +117550,Male,22,Bachelors,16,95,81,31,94,4.0,3,19,Urban,Software Engineer,58613,0 +117551,Female,43,Diploma,2,74,97,84,90,2.0,7,63,Urban,ML Engineer,54954,1 +117552,Male,57,Bachelors,3,26,11,37,36,4.0,7,80,Semi-Urban,Software Engineer,51578,0 +117553,Male,30,Bachelors,16,40,82,78,64,6.0,4,77,Semi-Urban,Data Analyst,112578,1 +117554,Female,45,Masters,10,29,11,79,0,6.0,7,16,Urban,Software Engineer,89503,0 +117555,Male,40,High School,17,24,44,43,41,5.0,3,42,Semi-Urban,ML Engineer,57889,0 +117556,Female,35,Bachelors,4,87,30,98,51,7.0,0,76,Semi-Urban,HR Executive,106956,1 +117557,Female,42,Bachelors,1,76,73,57,37,1.0,5,85,Semi-Urban,HR Executive,54307,1 +117558,Female,51,Diploma,15,16,4,0,98,5.0,7,9,Semi-Urban,ML Engineer,53855,0 +117559,Female,38,Bachelors,17,80,26,45,63,6.0,0,69,Urban,ML Engineer,58559,0 +117560,Male,28,Bachelors,11,52,15,96,87,5.0,2,3,Urban,ML Engineer,88126,0 +117561,Other,41,High School,11,59,80,44,20,9.0,5,50,Urban,Manager,34116,0 +117562,Male,52,Bachelors,11,94,59,48,3,6.0,2,39,Urban,ML Engineer,67186,1 +117563,Female,25,Masters,13,3,61,97,73,8.0,2,82,Semi-Urban,Data Analyst,133694,1 +117564,Male,24,Masters,8,72,75,79,23,6.0,4,48,Semi-Urban,Data Analyst,57061,1 +117565,Male,58,Masters,5,66,55,19,10,6.0,4,30,Urban,ML Engineer,61347,0 +117566,Other,43,Bachelors,10,80,35,85,72,8.0,5,44,Urban,ML Engineer,121577,1 +117567,Female,56,PhD,16,53,39,24,81,5.0,7,99,Rural,Software Engineer,131014,0 +117568,Female,45,Bachelors,3,22,95,24,31,1.0,4,92,Urban,Software Engineer,125662,0 +117569,Male,51,Masters,5,13,93,35,40,2.0,4,21,Rural,HR Executive,63475,0 +117570,Female,52,Masters,1,22,71,76,0,2.0,0,45,Urban,Software Engineer,51692,0 +117571,Male,33,Masters,5,41,23,22,95,1.0,4,7,Urban,ML Engineer,72924,0 +117572,Female,57,High School,4,28,46,85,25,4.0,4,14,Semi-Urban,Data Analyst,102641,0 +117573,Other,54,Bachelors,7,86,90,36,76,1.0,5,76,Urban,ML Engineer,44407,1 +117574,Male,43,PhD,4,38,83,51,89,8.0,1,15,Semi-Urban,Data Analyst,21136,0 +117575,Male,21,Bachelors,10,98,82,47,40,8.0,2,1,Urban,Software Engineer,56001,0 +117576,Male,34,Diploma,14,78,21,50,28,9.0,1,53,Rural,Data Analyst,22722,0 +117577,Male,25,Bachelors,10,61,25,0,70,0.0,1,0,Semi-Urban,Manager,36773,0 +117578,Other,21,Diploma,14,13,77,12,31,0.0,2,60,Urban,Software Engineer,27735,0 +117579,Male,48,High School,8,45,40,74,43,3.0,5,3,Urban,Software Engineer,105056,0 +117580,Other,21,PhD,10,21,46,11,89,3.0,6,0,Semi-Urban,Manager,110136,0 +117581,Female,21,Masters,2,53,75,85,2,0.0,2,35,Rural,ML Engineer,24099,1 +117582,Male,58,Diploma,18,79,9,90,96,0.0,6,80,Urban,HR Executive,42945,1 +117583,Female,38,Bachelors,14,55,79,71,98,6.0,7,65,Urban,HR Executive,60616,1 +117584,Male,28,Bachelors,5,37,50,61,61,5.0,0,14,Semi-Urban,Software Engineer,82363,0 +117585,Male,40,Diploma,8,84,58,42,28,2.0,1,50,Urban,ML Engineer,140510,0 +117586,Male,56,Masters,5,47,69,90,87,4.0,4,4,Urban,Manager,54359,0 +117587,Male,53,Bachelors,18,34,26,96,96,4.0,2,7,Urban,Data Analyst,146318,0 +117588,Female,45,High School,0,4,90,89,30,1.0,4,57,Urban,Data Analyst,30842,0 +117589,Male,38,Diploma,11,56,33,73,45,1.0,7,62,Urban,Data Analyst,135409,0 +117590,Female,28,Bachelors,5,55,77,40,48,1.0,3,26,Urban,HR Executive,94549,0 +117591,Male,46,Bachelors,16,74,98,42,31,1.0,4,1,Urban,Manager,106694,0 +117592,Female,33,High School,0,38,21,74,48,6.0,7,75,Urban,HR Executive,84735,0 +117593,Male,27,Masters,17,65,72,90,4,8.0,3,77,Semi-Urban,Data Analyst,43542,1 +117594,Male,28,PhD,0,21,21,47,70,5.0,1,39,Urban,Data Analyst,47292,0 +117595,Male,53,Bachelors,8,27,82,60,49,2.0,7,26,Rural,Software Engineer,37458,0 +117596,Female,58,Diploma,18,38,1,79,74,6.0,3,90,Semi-Urban,Manager,63207,0 +117597,Other,54,PhD,16,41,33,66,34,7.0,5,5,Urban,HR Executive,32181,0 +117598,Male,35,Diploma,7,92,55,47,8,7.0,5,19,Semi-Urban,Software Engineer,90024,0 +117599,Female,57,Bachelors,8,34,37,75,98,5.0,4,54,Urban,Software Engineer,26260,0 +117600,Female,37,Bachelors,18,16,70,51,23,6.0,2,45,Urban,Data Analyst,85978,0 +117601,Male,29,PhD,6,45,90,8,94,6.0,0,18,Semi-Urban,HR Executive,45194,0 +117602,Male,22,Bachelors,13,59,41,83,45,2.0,0,55,Semi-Urban,Manager,82388,1 +117603,Male,38,Masters,16,2,91,62,80,7.0,3,6,Urban,Manager,40761,0 +117604,Female,54,Masters,2,27,22,19,10,4.0,3,84,Urban,ML Engineer,114556,0 +117605,Male,32,PhD,2,23,72,67,42,2.0,4,80,Rural,Data Analyst,42075,1 +117606,Male,48,High School,2,38,31,16,8,6.0,6,55,Semi-Urban,ML Engineer,126447,0 +117607,Female,46,Bachelors,8,36,74,9,58,4.0,5,73,Semi-Urban,Manager,82541,0 +117608,Male,52,Masters,0,79,34,33,92,9.0,1,59,Urban,HR Executive,141350,0 +117609,Female,21,Masters,2,58,19,2,0,2.0,3,44,Urban,HR Executive,130360,0 +117610,Male,24,Masters,12,82,73,35,48,3.0,5,19,Rural,Data Analyst,55536,0 +117611,Female,25,High School,2,42,74,20,59,8.0,5,79,Urban,ML Engineer,34740,0 +117612,Female,28,Bachelors,16,15,83,88,10,6.0,0,56,Semi-Urban,HR Executive,143728,1 +117613,Male,33,Masters,7,89,38,68,12,7.0,0,74,Urban,ML Engineer,145814,1 +117614,Male,28,High School,18,76,4,85,75,1.0,4,38,Urban,HR Executive,23181,0 +117615,Male,35,Bachelors,16,78,51,21,83,1.0,7,59,Semi-Urban,Data Analyst,54580,0 +117616,Female,44,PhD,11,82,77,58,74,3.0,1,79,Semi-Urban,Software Engineer,29758,1 +117617,Male,42,Bachelors,16,5,49,13,82,1.0,5,95,Urban,HR Executive,105918,0 +117618,Female,25,Bachelors,15,87,50,46,80,1.0,6,20,Urban,Data Analyst,139243,0 +117619,Male,28,Bachelors,5,15,75,89,59,1.0,7,35,Urban,Data Analyst,101712,0 +117620,Male,47,Masters,11,10,34,87,72,3.0,5,50,Rural,Software Engineer,69906,0 +117621,Male,30,Diploma,8,95,11,33,55,8.0,6,25,Urban,Manager,58355,0 +117622,Male,29,High School,6,84,1,81,8,2.0,4,7,Semi-Urban,Data Analyst,138617,0 +117623,Male,25,Bachelors,8,71,12,14,28,9.0,7,87,Semi-Urban,HR Executive,38966,0 +117624,Female,22,Diploma,10,44,13,23,50,4.0,5,16,Rural,Manager,81440,0 +117625,Male,30,Bachelors,0,18,79,58,25,7.0,0,68,Urban,Software Engineer,137572,0 +117626,Male,32,Bachelors,4,99,32,1,23,3.0,6,70,Urban,HR Executive,126400,0 +117627,Male,23,Diploma,11,55,41,85,55,0.0,7,60,Rural,Manager,109828,1 +117628,Female,24,Diploma,19,45,61,17,83,1.0,3,86,Rural,Manager,148876,0 +117629,Male,37,Bachelors,19,40,1,48,47,1.0,5,23,Semi-Urban,HR Executive,107518,0 +117630,Female,45,Diploma,10,30,72,95,73,8.0,5,61,Urban,HR Executive,70203,1 +117631,Female,47,High School,18,13,89,98,81,8.0,5,96,Urban,Data Analyst,64972,1 +117632,Male,50,Masters,13,32,33,37,14,3.0,7,60,Urban,Manager,139332,0 +117633,Female,46,Bachelors,9,9,97,35,7,5.0,0,84,Urban,Manager,88535,0 +117634,Male,21,Diploma,17,69,31,85,14,9.0,3,12,Semi-Urban,Software Engineer,112162,0 +117635,Male,22,PhD,4,62,25,16,59,1.0,6,12,Urban,Manager,102128,0 +117636,Female,57,Diploma,8,63,73,12,53,9.0,6,81,Semi-Urban,Software Engineer,51918,0 +117637,Male,21,Bachelors,3,67,72,29,45,9.0,3,44,Rural,Manager,133319,0 +117638,Female,59,Bachelors,18,42,75,10,36,9.0,1,98,Urban,ML Engineer,27405,0 +117639,Male,45,Bachelors,4,88,92,2,54,9.0,0,35,Rural,ML Engineer,51418,0 +117640,Male,40,Bachelors,11,29,20,98,32,4.0,1,95,Urban,HR Executive,69211,1 +117641,Female,29,Bachelors,13,83,3,55,48,3.0,5,61,Rural,Manager,107516,0 +117642,Male,47,Masters,7,55,88,42,13,6.0,3,10,Urban,Software Engineer,59393,0 +117643,Male,42,Masters,17,94,82,28,35,8.0,1,3,Rural,Data Analyst,118406,0 +117644,Male,30,Masters,12,66,6,99,78,5.0,2,64,Urban,ML Engineer,68982,1 +117645,Male,45,Diploma,6,9,67,22,9,9.0,5,84,Urban,Data Analyst,137215,0 +117646,Male,25,Bachelors,6,73,9,63,14,5.0,7,78,Rural,Data Analyst,86586,0 +117647,Male,39,PhD,13,27,88,82,91,7.0,3,99,Urban,Software Engineer,52445,1 +117648,Female,32,PhD,9,28,98,97,57,1.0,2,67,Urban,HR Executive,88179,1 +117649,Male,43,Masters,15,35,62,41,11,3.0,4,27,Urban,ML Engineer,91107,0 +117650,Male,34,Masters,0,93,57,71,66,5.0,4,85,Semi-Urban,Software Engineer,68869,1 +117651,Female,48,Bachelors,10,64,79,43,83,8.0,1,67,Rural,Manager,147346,1 +117652,Male,49,Masters,13,74,29,1,6,0.0,3,47,Semi-Urban,ML Engineer,101959,0 +117653,Male,33,Bachelors,7,12,51,95,8,4.0,0,31,Semi-Urban,HR Executive,144693,0 +117654,Female,36,Bachelors,0,19,5,98,82,1.0,4,67,Urban,Manager,112215,0 +117655,Female,49,Diploma,18,0,59,64,93,0.0,4,24,Semi-Urban,ML Engineer,148340,0 +117656,Female,23,Bachelors,5,37,1,6,53,2.0,0,51,Semi-Urban,ML Engineer,41560,0 +117657,Other,39,Masters,13,67,40,49,96,7.0,0,45,Semi-Urban,HR Executive,122481,0 +117658,Male,21,Masters,7,4,60,3,74,5.0,6,65,Urban,HR Executive,30196,0 +117659,Male,29,Masters,13,11,79,97,44,2.0,4,11,Semi-Urban,ML Engineer,23494,0 +117660,Male,41,Bachelors,18,81,4,47,5,8.0,4,85,Urban,Manager,31729,0 +117661,Other,40,Diploma,7,63,96,23,78,4.0,0,30,Urban,Data Analyst,96229,0 +117662,Male,27,PhD,6,40,97,53,64,3.0,1,69,Urban,Manager,67798,1 +117663,Female,26,Masters,6,77,35,66,7,5.0,3,27,Urban,Manager,147458,0 +117664,Male,29,Bachelors,2,66,64,22,10,8.0,5,64,Urban,ML Engineer,141200,0 +117665,Female,35,Bachelors,9,75,85,46,77,1.0,5,66,Urban,Manager,126996,1 +117666,Other,29,Masters,10,86,78,64,95,5.0,3,12,Rural,Software Engineer,43620,0 +117667,Male,33,High School,15,61,53,89,26,1.0,7,52,Urban,ML Engineer,63416,1 +117668,Female,56,Masters,15,95,72,61,51,0.0,0,22,Semi-Urban,Manager,90466,1 +117669,Female,41,Bachelors,6,19,50,3,10,0.0,2,0,Rural,Software Engineer,69357,0 +117670,Male,45,Bachelors,18,25,26,55,14,0.0,3,54,Rural,Data Analyst,55506,0 +117671,Female,58,Masters,1,9,60,35,86,8.0,4,78,Semi-Urban,ML Engineer,130700,0 +117672,Male,41,Bachelors,5,76,45,78,58,1.0,2,15,Urban,Data Analyst,136027,0 +117673,Male,26,Bachelors,7,41,81,94,21,3.0,6,43,Urban,Software Engineer,36565,1 +117674,Male,51,Masters,19,15,31,97,73,7.0,6,82,Urban,ML Engineer,28017,0 +117675,Female,58,Masters,16,37,38,26,44,9.0,2,63,Rural,Manager,23730,0 +117676,Male,44,Bachelors,11,26,24,26,92,7.0,4,65,Urban,ML Engineer,21796,0 +117677,Male,32,Diploma,12,83,82,91,26,1.0,1,63,Urban,Manager,34146,1 +117678,Male,23,Bachelors,4,83,53,81,13,2.0,1,5,Urban,Data Analyst,138610,0 +117679,Male,59,Masters,0,63,42,54,33,8.0,0,59,Semi-Urban,Manager,61683,0 +117680,Female,55,Bachelors,15,53,22,47,40,8.0,0,22,Urban,Manager,40180,0 +117681,Male,25,Masters,12,4,3,61,68,9.0,2,78,Urban,Data Analyst,28053,0 +117682,Male,25,Bachelors,7,11,7,93,79,5.0,3,19,Urban,Manager,137771,0 +117683,Male,22,High School,19,84,7,61,8,4.0,4,67,Urban,Data Analyst,108563,0 +117684,Male,26,Bachelors,11,51,66,82,48,2.0,6,13,Urban,Software Engineer,128419,0 +117685,Male,33,Bachelors,8,9,85,44,98,3.0,0,13,Urban,Data Analyst,33490,0 +117686,Male,56,Diploma,13,12,12,63,15,6.0,3,82,Rural,Data Analyst,140635,0 +117687,Female,52,Masters,8,89,84,27,18,0.0,1,74,Semi-Urban,ML Engineer,83683,1 +117688,Male,43,High School,14,75,46,26,25,6.0,7,72,Semi-Urban,HR Executive,128376,0 +117689,Male,29,High School,2,64,34,74,13,2.0,2,1,Urban,Data Analyst,36232,0 +117690,Male,43,PhD,16,71,29,69,83,8.0,4,42,Urban,HR Executive,100181,0 +117691,Male,41,Bachelors,19,80,69,56,36,3.0,3,77,Urban,HR Executive,129932,1 +117692,Female,45,Masters,0,47,96,93,80,0.0,6,12,Urban,Manager,64479,1 +117693,Female,54,Masters,18,44,61,15,26,6.0,1,85,Semi-Urban,Data Analyst,127794,0 +117694,Male,29,Diploma,18,51,18,36,17,5.0,2,75,Urban,Data Analyst,73145,0 +117695,Male,39,Masters,19,5,83,51,40,3.0,1,57,Semi-Urban,ML Engineer,107876,0 +117696,Male,47,Masters,7,78,10,56,14,6.0,7,68,Urban,Data Analyst,77773,0 +117697,Female,58,High School,17,84,81,95,13,8.0,6,80,Semi-Urban,Data Analyst,67801,1 +117698,Female,26,Bachelors,14,38,79,66,52,6.0,4,49,Semi-Urban,Data Analyst,133031,0 +117699,Other,25,Masters,7,20,5,48,97,7.0,3,73,Semi-Urban,Software Engineer,81975,0 +117700,Male,26,Diploma,3,92,79,44,99,6.0,2,58,Urban,Data Analyst,98853,1 +117701,Male,25,High School,5,82,75,92,3,4.0,0,66,Rural,Data Analyst,77376,1 +117702,Female,58,Masters,6,5,1,47,68,1.0,5,88,Semi-Urban,ML Engineer,35311,0 +117703,Male,25,PhD,17,88,5,91,32,4.0,3,14,Urban,Data Analyst,114222,0 +117704,Female,48,Bachelors,14,71,92,7,5,7.0,2,98,Urban,Software Engineer,132200,1 +117705,Male,44,High School,16,31,0,98,1,9.0,3,69,Rural,Data Analyst,79151,0 +117706,Other,34,Diploma,19,53,35,72,80,4.0,6,26,Rural,HR Executive,116229,0 +117707,Male,30,Bachelors,17,3,34,27,43,3.0,6,23,Urban,HR Executive,30739,0 +117708,Male,56,Masters,9,3,43,52,95,0.0,3,30,Semi-Urban,Data Analyst,91561,0 +117709,Male,25,PhD,13,67,80,30,8,5.0,6,74,Urban,HR Executive,85304,1 +117710,Female,22,Diploma,16,64,82,12,13,3.0,1,72,Urban,Data Analyst,128316,0 +117711,Male,51,High School,6,16,50,51,2,6.0,4,88,Urban,Data Analyst,136412,0 +117712,Male,37,PhD,19,9,44,33,48,6.0,0,99,Urban,ML Engineer,72051,0 +117713,Female,41,Bachelors,3,3,52,4,60,7.0,2,44,Urban,ML Engineer,30365,0 +117714,Male,52,PhD,8,65,82,69,28,6.0,2,94,Semi-Urban,Data Analyst,89236,1 +117715,Other,54,Bachelors,19,45,68,29,92,9.0,1,56,Urban,HR Executive,94461,0 +117716,Male,49,Masters,8,57,76,49,82,0.0,0,67,Semi-Urban,Data Analyst,23854,1 +117717,Male,40,Bachelors,1,57,96,2,45,0.0,4,99,Urban,ML Engineer,47730,1 +117718,Male,53,Masters,18,44,61,18,67,2.0,2,55,Semi-Urban,Manager,35362,0 +117719,Male,29,High School,19,9,2,7,56,6.0,3,98,Urban,Manager,116612,0 +117720,Female,42,Bachelors,15,55,91,59,86,5.0,6,11,Urban,Software Engineer,97811,0 +117721,Female,48,Bachelors,19,58,1,64,57,9.0,1,11,Urban,HR Executive,59478,0 +117722,Male,56,Diploma,4,33,9,0,43,1.0,7,25,Rural,Software Engineer,97745,0 +117723,Male,52,Masters,0,26,2,95,67,2.0,1,1,Urban,HR Executive,102449,0 +117724,Male,58,Bachelors,0,13,16,96,43,8.0,4,60,Urban,ML Engineer,96143,0 +117725,Female,23,High School,4,54,97,85,38,9.0,4,39,Rural,Software Engineer,100815,1 +117726,Male,22,Diploma,7,66,30,74,5,4.0,2,46,Urban,ML Engineer,26224,0 +117727,Female,47,Bachelors,2,54,61,86,51,3.0,5,74,Rural,Software Engineer,118880,1 +117728,Female,44,Masters,6,46,16,62,81,9.0,7,27,Rural,Manager,46602,0 +117729,Female,44,Bachelors,18,32,54,92,40,6.0,2,44,Urban,Manager,25193,0 +117730,Male,52,Diploma,9,50,20,34,5,1.0,5,67,Semi-Urban,HR Executive,62712,0 +117731,Male,49,High School,0,6,80,18,0,1.0,2,40,Urban,Data Analyst,87739,0 +117732,Female,31,High School,8,57,36,70,45,4.0,6,30,Urban,HR Executive,122414,0 +117733,Male,42,High School,17,14,70,80,41,8.0,4,72,Urban,Data Analyst,86926,1 +117734,Female,45,Bachelors,3,37,89,80,10,3.0,1,0,Urban,Software Engineer,128904,0 +117735,Male,23,High School,11,26,39,17,28,0.0,2,39,Urban,Manager,93475,0 +117736,Female,39,Bachelors,7,97,89,73,26,6.0,2,78,Semi-Urban,Data Analyst,60153,1 +117737,Male,57,High School,3,52,51,99,22,8.0,3,3,Urban,Data Analyst,32285,0 +117738,Female,44,Bachelors,14,74,88,29,74,0.0,7,28,Urban,Data Analyst,122861,0 +117739,Male,49,Masters,17,13,68,24,89,9.0,0,35,Urban,Software Engineer,125522,0 +117740,Other,55,Diploma,9,69,17,95,53,9.0,0,12,Urban,HR Executive,106372,0 +117741,Male,25,Bachelors,10,86,4,28,87,0.0,7,27,Urban,Data Analyst,33607,0 +117742,Male,48,Bachelors,17,89,18,66,89,1.0,0,2,Urban,Manager,149332,0 +117743,Male,37,Bachelors,9,3,88,56,67,8.0,5,29,Urban,Software Engineer,25368,0 +117744,Other,37,Diploma,10,66,12,21,57,3.0,5,62,Semi-Urban,Software Engineer,126630,0 +117745,Male,34,Masters,8,0,65,10,81,3.0,2,65,Urban,Data Analyst,131307,0 +117746,Female,54,Diploma,10,97,17,96,99,4.0,7,70,Urban,HR Executive,117216,1 +117747,Male,47,High School,17,12,19,2,0,6.0,5,89,Urban,ML Engineer,38725,0 +117748,Male,55,Bachelors,11,68,99,71,31,3.0,4,3,Urban,Manager,76148,1 +117749,Male,58,Bachelors,4,65,68,40,94,5.0,5,41,Semi-Urban,HR Executive,81405,0 +117750,Male,29,Bachelors,7,3,78,1,72,3.0,1,15,Urban,HR Executive,56690,0 +117751,Male,24,Diploma,6,40,58,48,87,8.0,4,25,Urban,HR Executive,123189,0 +117752,Female,54,Diploma,5,92,78,75,27,7.0,6,76,Urban,HR Executive,90048,1 +117753,Male,59,Bachelors,8,68,11,79,0,2.0,4,16,Urban,ML Engineer,85199,0 +117754,Male,22,High School,2,70,14,45,87,3.0,3,15,Urban,ML Engineer,115834,0 +117755,Male,41,Masters,10,29,1,68,0,7.0,7,27,Rural,HR Executive,61506,0 +117756,Male,25,Bachelors,10,17,93,56,49,8.0,2,30,Urban,Data Analyst,98894,0 +117757,Female,54,Diploma,2,32,25,84,43,5.0,3,23,Urban,ML Engineer,129343,0 +117758,Male,57,Masters,14,53,35,4,70,6.0,5,27,Urban,Data Analyst,36932,0 +117759,Male,39,Bachelors,11,21,83,66,36,7.0,1,2,Urban,Data Analyst,41161,0 +117760,Male,35,Bachelors,18,72,60,92,36,1.0,2,75,Urban,HR Executive,106404,1 +117761,Male,39,Diploma,3,74,68,30,71,3.0,4,10,Urban,HR Executive,108765,0 +117762,Female,27,Bachelors,7,91,40,68,95,8.0,2,52,Urban,Data Analyst,38582,1 +117763,Male,43,Masters,13,46,71,4,53,7.0,3,48,Semi-Urban,ML Engineer,92260,0 +117764,Female,41,Bachelors,0,34,95,45,4,1.0,3,38,Urban,Software Engineer,101483,0 +117765,Male,46,High School,0,34,87,88,28,2.0,4,11,Urban,Manager,94729,0 +117766,Male,49,Diploma,9,45,46,20,46,7.0,6,15,Rural,ML Engineer,82696,0 +117767,Female,37,PhD,15,9,76,3,8,7.0,7,15,Urban,Data Analyst,122813,0 +117768,Female,31,High School,4,41,2,18,33,1.0,5,86,Urban,ML Engineer,131352,0 +117769,Male,29,Diploma,0,95,36,1,45,8.0,1,62,Urban,HR Executive,45363,0 +117770,Male,22,Bachelors,12,56,51,4,20,8.0,6,16,Urban,Data Analyst,108849,0 +117771,Male,36,High School,10,36,38,42,93,5.0,7,47,Urban,ML Engineer,113705,0 +117772,Male,25,Masters,3,96,43,61,70,2.0,7,25,Semi-Urban,Software Engineer,96580,0 +117773,Male,50,Bachelors,12,52,94,87,90,2.0,5,98,Semi-Urban,Software Engineer,35442,1 +117774,Female,35,High School,0,38,93,5,96,4.0,4,1,Urban,Data Analyst,36493,0 +117775,Male,21,Masters,19,23,39,79,50,9.0,2,35,Urban,Manager,106057,0 +117776,Female,38,Diploma,10,91,45,68,40,1.0,1,12,Rural,Software Engineer,40785,0 +117777,Male,35,Masters,2,10,58,62,44,2.0,7,91,Urban,Manager,146702,0 +117778,Male,30,Bachelors,12,53,63,87,36,7.0,2,27,Urban,Manager,50112,0 +117779,Male,36,Bachelors,14,81,6,19,5,2.0,6,28,Semi-Urban,Software Engineer,120652,0 +117780,Male,29,Diploma,18,13,20,17,31,9.0,1,95,Rural,ML Engineer,84270,0 +117781,Female,56,Bachelors,18,44,23,32,24,3.0,2,26,Semi-Urban,ML Engineer,42701,0 +117782,Male,52,Masters,8,32,4,25,33,1.0,1,27,Urban,Manager,111086,0 +117783,Female,51,Bachelors,10,69,93,51,11,8.0,3,1,Rural,ML Engineer,132353,0 +117784,Female,33,Bachelors,12,6,8,89,95,9.0,0,98,Urban,ML Engineer,135010,0 +117785,Male,30,High School,3,75,84,41,66,5.0,2,69,Urban,Manager,104254,1 +117786,Female,57,Diploma,17,49,94,29,2,0.0,0,81,Urban,ML Engineer,38375,1 +117787,Female,51,Bachelors,11,25,34,54,84,9.0,2,80,Urban,HR Executive,104812,0 +117788,Female,52,Diploma,11,72,66,57,81,9.0,5,78,Rural,Data Analyst,85647,1 +117789,Female,54,Diploma,9,67,94,76,1,7.0,4,49,Urban,Manager,112025,1 +117790,Male,26,Bachelors,3,75,51,77,53,4.0,3,59,Urban,Data Analyst,35497,1 +117791,Female,43,Bachelors,10,1,12,23,22,4.0,2,47,Semi-Urban,Manager,65930,0 +117792,Male,52,Bachelors,12,55,48,45,14,4.0,2,58,Urban,Manager,88427,0 +117793,Other,58,Bachelors,8,82,22,2,83,9.0,4,72,Urban,HR Executive,53335,0 +117794,Male,40,Masters,15,92,27,7,43,4.0,5,61,Urban,ML Engineer,79046,0 +117795,Female,22,Bachelors,5,8,98,47,5,9.0,5,11,Urban,Software Engineer,77272,0 +117796,Other,56,Bachelors,4,13,15,14,5,9.0,2,14,Urban,ML Engineer,118201,0 +117797,Male,48,Bachelors,18,26,23,34,61,1.0,7,86,Urban,Manager,82793,0 +117798,Female,25,Bachelors,10,70,88,7,3,8.0,0,57,Urban,Software Engineer,104687,0 +117799,Male,36,Bachelors,6,84,17,86,55,6.0,0,76,Urban,Software Engineer,31243,1 +117800,Male,46,Bachelors,0,20,65,42,38,8.0,3,4,Semi-Urban,HR Executive,87823,0 +117801,Female,36,Masters,2,16,63,50,79,5.0,2,56,Semi-Urban,Manager,56999,0 +117802,Male,55,Bachelors,14,54,42,16,31,2.0,3,57,Urban,HR Executive,138279,0 +117803,Male,41,Masters,0,31,9,5,84,7.0,4,75,Urban,HR Executive,116782,0 +117804,Male,55,Masters,6,69,40,35,13,9.0,4,36,Urban,Software Engineer,25250,0 +117805,Male,30,Bachelors,11,23,78,33,95,7.0,1,60,Urban,Data Analyst,78458,0 +117806,Female,58,Bachelors,18,49,51,11,17,0.0,5,33,Rural,HR Executive,74178,0 +117807,Female,35,Bachelors,13,73,3,19,4,9.0,6,5,Semi-Urban,Manager,72567,0 +117808,Male,24,Masters,4,47,28,44,42,0.0,5,60,Rural,ML Engineer,69032,0 +117809,Male,41,Bachelors,17,32,59,22,64,3.0,2,6,Rural,Software Engineer,132873,0 +117810,Other,27,Diploma,14,58,51,27,32,3.0,4,33,Urban,HR Executive,40374,0 +117811,Male,58,Bachelors,4,9,99,3,23,3.0,6,80,Urban,ML Engineer,70241,0 +117812,Male,32,Bachelors,4,32,56,65,92,9.0,5,64,Semi-Urban,Software Engineer,65223,0 +117813,Female,46,Bachelors,1,57,27,20,2,2.0,0,20,Urban,HR Executive,35600,0 +117814,Female,31,Masters,10,87,12,78,3,0.0,4,30,Rural,Software Engineer,45083,0 +117815,Other,45,Diploma,4,17,21,92,10,8.0,0,64,Rural,Data Analyst,82275,0 +117816,Female,42,Bachelors,3,74,51,53,41,3.0,3,68,Urban,Software Engineer,120281,1 +117817,Male,40,Masters,14,80,76,97,23,6.0,1,48,Urban,Data Analyst,55783,1 +117818,Female,27,Diploma,12,14,95,25,69,2.0,4,8,Urban,Data Analyst,42274,0 +117819,Male,46,High School,9,27,77,98,8,4.0,2,14,Urban,Software Engineer,63482,0 +117820,Female,39,High School,3,63,51,38,16,6.0,4,19,Semi-Urban,Manager,53543,0 +117821,Male,59,Diploma,19,82,19,93,33,3.0,6,13,Urban,HR Executive,125693,0 +117822,Male,42,Masters,8,5,90,16,6,0.0,5,56,Urban,Software Engineer,62712,0 +117823,Male,30,Masters,8,45,27,72,26,1.0,6,74,Urban,HR Executive,138011,0 +117824,Male,42,Diploma,18,61,65,22,88,7.0,0,7,Urban,Manager,29778,0 +117825,Female,58,PhD,2,3,22,14,23,1.0,3,22,Semi-Urban,HR Executive,39092,0 +117826,Male,54,Masters,13,64,75,21,67,3.0,6,3,Urban,ML Engineer,89770,0 +117827,Male,29,High School,14,86,37,83,7,2.0,1,48,Urban,Software Engineer,65179,1 +117828,Male,38,Bachelors,16,35,83,62,21,5.0,1,15,Urban,Software Engineer,140723,0 +117829,Male,56,Diploma,15,97,16,82,33,7.0,7,31,Urban,Data Analyst,43543,0 +117830,Male,26,Diploma,11,92,64,62,9,3.0,4,68,Rural,Software Engineer,121430,1 +117831,Female,25,Diploma,7,0,60,16,5,7.0,5,2,Urban,Data Analyst,134494,0 +117832,Male,51,High School,18,38,62,44,97,4.0,3,29,Urban,HR Executive,90226,0 +117833,Male,28,Masters,12,78,83,53,45,9.0,1,88,Rural,Manager,65910,1 +117834,Male,45,Diploma,4,59,97,96,96,5.0,6,48,Urban,Data Analyst,142789,1 +117835,Male,35,Masters,4,89,49,29,13,6.0,2,85,Semi-Urban,Data Analyst,77474,1 +117836,Male,38,Bachelors,19,37,13,94,68,7.0,6,97,Urban,Software Engineer,113901,1 +117837,Female,50,Masters,9,34,65,0,82,3.0,5,62,Rural,Data Analyst,145352,0 +117838,Female,54,Bachelors,12,21,44,96,33,9.0,6,55,Urban,Data Analyst,144706,0 +117839,Male,28,Masters,15,11,86,75,26,7.0,7,82,Rural,HR Executive,117998,1 +117840,Female,39,Masters,15,88,3,77,57,0.0,2,41,Urban,HR Executive,103712,0 +117841,Male,55,Diploma,14,81,82,9,20,6.0,0,61,Urban,Software Engineer,120322,0 +117842,Other,36,High School,18,36,33,32,86,9.0,5,96,Semi-Urban,Data Analyst,61389,0 +117843,Male,36,High School,5,15,6,98,48,6.0,1,2,Urban,Data Analyst,123535,0 +117844,Male,56,Masters,1,0,91,77,79,2.0,6,10,Urban,Data Analyst,82303,0 +117845,Male,42,Diploma,15,49,50,54,71,3.0,1,82,Urban,Software Engineer,112358,1 +117846,Male,38,Bachelors,2,82,3,0,42,6.0,0,36,Urban,Software Engineer,110818,0 +117847,Male,58,High School,0,14,62,66,39,4.0,3,14,Urban,Software Engineer,106055,0 +117848,Male,31,Masters,9,61,55,26,69,3.0,5,57,Urban,Software Engineer,76216,0 +117849,Male,50,Masters,3,84,61,25,23,6.0,6,46,Urban,ML Engineer,64381,0 +117850,Male,53,Bachelors,19,61,2,82,46,0.0,1,68,Semi-Urban,HR Executive,117803,0 +117851,Female,25,Masters,3,60,57,56,91,2.0,1,15,Urban,ML Engineer,33341,0 +117852,Male,45,Masters,10,1,95,83,70,2.0,2,11,Urban,HR Executive,95205,0 +117853,Female,54,Bachelors,12,96,28,24,52,4.0,6,90,Urban,Software Engineer,90166,0 +117854,Male,27,Diploma,11,57,74,77,61,0.0,0,78,Urban,Data Analyst,99405,1 +117855,Male,45,Masters,15,9,85,77,74,5.0,7,34,Semi-Urban,Software Engineer,127232,0 +117856,Male,53,Bachelors,13,72,77,30,52,9.0,1,23,Urban,HR Executive,84504,0 +117857,Male,37,Masters,7,21,8,21,75,6.0,3,11,Rural,Data Analyst,96244,0 +117858,Female,49,Bachelors,6,84,86,42,59,1.0,6,55,Rural,Software Engineer,79150,1 +117859,Male,52,Bachelors,9,99,69,66,80,8.0,0,72,Urban,Manager,26440,1 +117860,Male,28,Bachelors,6,81,94,67,99,1.0,0,55,Rural,Software Engineer,97755,1 +117861,Male,50,Bachelors,3,72,55,21,93,7.0,3,38,Urban,Manager,89642,0 +117862,Female,55,Bachelors,1,31,15,8,58,7.0,6,28,Urban,Software Engineer,141823,0 +117863,Male,29,PhD,13,42,34,55,70,5.0,2,42,Urban,Manager,52382,0 +117864,Female,51,Diploma,16,56,28,61,29,8.0,0,54,Semi-Urban,ML Engineer,108244,0 +117865,Female,48,Diploma,9,56,57,31,52,1.0,5,22,Urban,HR Executive,98626,0 +117866,Male,34,Diploma,1,92,22,3,86,1.0,1,24,Urban,ML Engineer,132474,0 +117867,Female,53,Bachelors,14,53,46,1,49,4.0,4,70,Rural,Manager,57475,0 +117868,Male,36,Bachelors,19,95,3,26,53,1.0,6,2,Semi-Urban,Software Engineer,90277,0 +117869,Other,23,Bachelors,14,41,52,4,87,7.0,2,21,Urban,Software Engineer,95724,0 +117870,Other,31,Diploma,19,60,84,90,8,1.0,1,38,Rural,Manager,79742,1 +117871,Female,21,PhD,9,10,74,51,56,8.0,0,93,Urban,ML Engineer,97386,0 +117872,Male,31,Bachelors,12,11,89,66,46,5.0,7,86,Urban,HR Executive,78425,1 +117873,Male,59,High School,16,61,15,1,73,7.0,2,8,Rural,Data Analyst,97827,0 +117874,Male,57,Diploma,13,80,28,47,60,1.0,2,79,Urban,HR Executive,89764,0 +117875,Male,53,Bachelors,13,87,5,14,95,7.0,2,51,Urban,Manager,93119,0 +117876,Male,46,Bachelors,7,84,86,25,5,8.0,7,19,Urban,HR Executive,122356,0 +117877,Male,47,Diploma,18,28,15,70,65,6.0,2,36,Urban,HR Executive,26462,0 +117878,Female,54,Bachelors,7,8,40,81,94,3.0,3,34,Semi-Urban,Data Analyst,112450,0 +117879,Female,56,Bachelors,12,41,86,85,78,8.0,7,61,Urban,Data Analyst,121168,1 +117880,Male,45,Bachelors,4,93,80,28,90,1.0,1,49,Semi-Urban,Manager,103794,1 +117881,Male,44,Masters,5,69,72,85,23,4.0,2,64,Urban,Software Engineer,135771,1 +117882,Female,47,Bachelors,5,4,60,65,91,0.0,3,41,Semi-Urban,Manager,31226,0 +117883,Female,22,Diploma,16,36,53,37,54,0.0,5,67,Semi-Urban,HR Executive,83186,0 +117884,Male,23,Diploma,16,9,51,58,95,2.0,2,3,Urban,Software Engineer,92513,0 +117885,Female,28,High School,5,71,29,4,62,3.0,2,22,Urban,ML Engineer,51075,0 +117886,Female,56,Diploma,16,86,82,97,20,4.0,3,88,Urban,ML Engineer,107532,1 +117887,Male,57,Masters,8,5,68,47,34,6.0,0,56,Semi-Urban,ML Engineer,124984,0 +117888,Male,31,Bachelors,4,77,29,96,52,6.0,6,48,Rural,Software Engineer,146386,1 +117889,Male,42,Masters,10,57,48,70,21,3.0,3,69,Urban,ML Engineer,129409,1 +117890,Female,48,Masters,5,14,79,36,19,7.0,3,91,Urban,Software Engineer,87518,0 +117891,Female,32,Diploma,8,2,79,17,8,2.0,5,45,Urban,ML Engineer,59196,0 +117892,Female,23,Bachelors,8,35,33,17,12,9.0,0,91,Rural,HR Executive,29569,0 +117893,Female,41,High School,10,42,58,46,96,2.0,3,14,Urban,Data Analyst,61963,0 +117894,Male,25,Diploma,2,85,42,54,8,3.0,2,55,Urban,Manager,28536,1 +117895,Male,32,Bachelors,2,33,32,46,48,1.0,3,89,Rural,Software Engineer,141898,0 +117896,Male,56,Bachelors,15,40,76,79,77,6.0,6,19,Semi-Urban,Manager,20277,0 +117897,Male,35,Diploma,2,65,94,74,40,7.0,3,9,Semi-Urban,Manager,44958,1 +117898,Male,50,Diploma,10,92,14,41,84,1.0,3,47,Semi-Urban,ML Engineer,76177,0 +117899,Male,59,Bachelors,14,10,45,12,5,4.0,2,21,Rural,ML Engineer,21374,0 +117900,Male,55,Bachelors,9,83,4,72,39,4.0,5,80,Urban,Data Analyst,75488,1 +117901,Male,27,Bachelors,0,92,82,18,66,9.0,0,28,Semi-Urban,Software Engineer,116949,0 +117902,Male,52,Bachelors,4,74,59,61,92,8.0,3,38,Semi-Urban,Manager,135296,0 +117903,Male,33,Masters,0,9,51,75,47,0.0,4,76,Rural,HR Executive,86197,0 +117904,Male,24,Bachelors,15,22,17,11,52,1.0,2,80,Rural,Data Analyst,84987,0 +117905,Male,53,Bachelors,9,6,49,96,54,0.0,7,51,Urban,Data Analyst,66612,0 +117906,Male,57,Diploma,2,96,89,64,59,0.0,2,43,Urban,Data Analyst,27546,1 +117907,Female,30,Diploma,14,33,11,48,19,7.0,6,95,Semi-Urban,ML Engineer,119667,0 +117908,Female,55,Bachelors,3,38,34,77,95,9.0,3,78,Urban,Manager,79246,0 +117909,Female,24,Bachelors,5,18,45,65,9,1.0,4,50,Semi-Urban,Data Analyst,85114,0 +117910,Female,35,High School,17,48,40,83,96,9.0,7,87,Urban,ML Engineer,111745,1 +117911,Female,43,Bachelors,19,46,67,55,51,2.0,4,73,Urban,HR Executive,22546,1 +117912,Male,51,Bachelors,5,87,13,86,91,6.0,2,23,Urban,HR Executive,149986,0 +117913,Female,53,Bachelors,19,6,7,31,83,8.0,4,83,Urban,Software Engineer,126265,0 +117914,Male,33,Bachelors,19,12,20,80,64,0.0,5,61,Urban,Manager,93293,0 +117915,Male,53,Bachelors,12,1,54,87,1,1.0,4,71,Semi-Urban,Manager,47294,0 +117916,Male,45,Diploma,1,81,39,87,46,0.0,7,40,Urban,Software Engineer,145203,1 +117917,Male,22,PhD,1,53,44,46,9,8.0,7,24,Urban,Data Analyst,122196,0 +117918,Female,43,Bachelors,9,64,30,40,16,5.0,6,10,Rural,ML Engineer,25028,0 +117919,Female,53,Bachelors,5,43,89,78,21,8.0,7,32,Urban,Manager,119796,1 +117920,Male,43,Masters,4,14,42,25,31,9.0,0,78,Urban,Software Engineer,39332,0 +117921,Male,25,Bachelors,3,85,66,83,87,0.0,7,57,Urban,HR Executive,70686,1 +117922,Male,33,Bachelors,8,14,35,34,45,4.0,0,91,Urban,Manager,106954,0 +117923,Male,22,Bachelors,10,45,95,98,45,6.0,1,14,Urban,Software Engineer,55995,1 +117924,Male,59,High School,3,48,66,21,53,1.0,4,55,Rural,ML Engineer,117664,0 +117925,Male,37,Masters,10,18,56,72,98,8.0,4,91,Urban,ML Engineer,99670,1 +117926,Male,45,Masters,17,57,50,11,25,4.0,5,90,Urban,ML Engineer,147418,0 +117927,Other,53,High School,13,40,73,66,19,5.0,4,45,Urban,Data Analyst,41046,0 +117928,Female,49,PhD,14,43,83,35,90,0.0,6,16,Urban,Manager,134040,0 +117929,Female,28,Bachelors,14,67,6,61,84,2.0,1,49,Urban,ML Engineer,112561,0 +117930,Male,22,Diploma,16,21,73,69,63,9.0,4,52,Urban,Software Engineer,112702,0 +117931,Male,51,High School,10,77,52,81,10,6.0,0,40,Semi-Urban,Software Engineer,38130,1 +117932,Female,46,Diploma,13,85,24,87,67,0.0,3,49,Urban,Software Engineer,119859,1 +117933,Male,35,Masters,17,25,14,22,62,2.0,7,38,Rural,HR Executive,59861,0 +117934,Male,30,PhD,2,78,98,32,79,9.0,5,44,Semi-Urban,ML Engineer,51315,1 +117935,Male,58,Bachelors,1,38,0,42,94,2.0,1,24,Rural,Data Analyst,40541,0 +117936,Male,42,Masters,12,18,51,84,67,3.0,3,52,Urban,ML Engineer,134473,0 +117937,Male,54,Masters,4,63,2,20,37,7.0,3,80,Urban,Software Engineer,147622,0 +117938,Male,33,Diploma,10,60,25,22,19,6.0,0,77,Urban,Data Analyst,27468,0 +117939,Male,51,Masters,3,5,69,92,88,8.0,1,92,Rural,Software Engineer,76164,1 +117940,Male,59,High School,9,85,69,60,71,4.0,4,60,Urban,Data Analyst,112033,1 +117941,Male,23,Masters,14,27,1,78,62,7.0,3,54,Rural,ML Engineer,148481,0 +117942,Male,42,Diploma,9,75,2,69,15,5.0,6,93,Semi-Urban,Data Analyst,101989,1 +117943,Male,36,Bachelors,5,61,98,53,29,0.0,3,52,Urban,Manager,88847,1 +117944,Male,50,Bachelors,9,75,47,84,14,4.0,6,43,Urban,Data Analyst,72607,1 +117945,Other,48,Masters,16,78,80,87,74,6.0,4,4,Urban,HR Executive,48538,1 +117946,Male,54,Masters,17,90,63,50,43,0.0,1,79,Rural,Manager,107396,1 +117947,Female,45,PhD,12,80,20,35,48,4.0,5,73,Semi-Urban,Data Analyst,81070,0 +117948,Male,54,Masters,8,52,41,7,5,1.0,4,10,Semi-Urban,Software Engineer,94988,0 +117949,Female,57,Bachelors,18,80,49,79,56,2.0,2,67,Rural,Software Engineer,47217,1 +117950,Male,22,Bachelors,2,87,13,82,9,4.0,4,11,Urban,ML Engineer,89514,0 +117951,Male,34,Diploma,15,69,10,63,72,6.0,4,14,Rural,ML Engineer,81870,0 +117952,Male,39,Bachelors,15,69,90,44,85,1.0,2,64,Urban,HR Executive,51893,1 +117953,Male,30,Diploma,13,42,2,87,15,6.0,2,93,Rural,ML Engineer,116585,0 +117954,Female,35,Bachelors,3,70,4,36,98,4.0,2,91,Urban,Data Analyst,105047,0 +117955,Male,35,Masters,11,43,23,99,65,5.0,0,6,Urban,Data Analyst,104613,0 +117956,Female,58,Bachelors,14,49,42,83,34,8.0,4,49,Urban,Manager,114957,0 +117957,Female,55,Diploma,17,20,53,90,36,6.0,6,44,Urban,HR Executive,123459,0 +117958,Female,57,Diploma,14,78,25,88,58,6.0,0,8,Urban,HR Executive,59739,0 +117959,Female,56,High School,0,75,5,33,44,5.0,4,79,Semi-Urban,Manager,113729,0 +117960,Female,32,Bachelors,4,9,81,27,12,8.0,4,67,Urban,ML Engineer,34875,0 +117961,Female,47,Bachelors,6,98,30,27,16,5.0,7,33,Semi-Urban,HR Executive,107739,0 +117962,Female,52,Bachelors,5,12,24,2,40,5.0,2,87,Semi-Urban,Manager,70549,0 +117963,Male,35,Masters,3,1,24,46,95,5.0,3,47,Semi-Urban,HR Executive,121626,0 +117964,Female,28,Bachelors,13,67,27,54,89,5.0,7,16,Rural,Software Engineer,74042,0 +117965,Female,34,Diploma,12,47,86,92,93,0.0,6,16,Urban,Data Analyst,36092,1 +117966,Male,50,Bachelors,15,80,1,50,43,0.0,3,47,Semi-Urban,Software Engineer,128821,0 +117967,Male,35,High School,10,42,72,25,82,7.0,2,40,Rural,Manager,132542,0 +117968,Female,53,Masters,17,74,34,28,21,8.0,4,48,Rural,HR Executive,62258,0 +117969,Male,57,Bachelors,7,30,74,4,96,7.0,0,43,Rural,HR Executive,142684,0 +117970,Other,21,Bachelors,11,85,63,18,43,7.0,2,59,Rural,ML Engineer,65142,0 +117971,Female,39,Masters,3,33,25,29,23,5.0,2,68,Urban,Software Engineer,90610,0 +117972,Male,45,Masters,3,96,13,41,11,7.0,1,71,Urban,ML Engineer,107269,0 +117973,Male,26,Diploma,18,27,31,91,4,9.0,3,34,Urban,Manager,61954,0 +117974,Female,26,Bachelors,1,6,22,17,22,1.0,5,66,Semi-Urban,HR Executive,60525,0 +117975,Male,25,Bachelors,18,16,48,36,79,1.0,7,79,Rural,Software Engineer,90893,0 +117976,Male,36,High School,7,29,54,4,22,4.0,2,12,Rural,Manager,102025,0 +117977,Male,58,Bachelors,11,40,2,50,42,3.0,3,40,Semi-Urban,Software Engineer,120966,0 +117978,Male,28,Bachelors,16,0,61,77,24,8.0,6,58,Semi-Urban,Data Analyst,54787,0 +117979,Male,33,PhD,5,13,53,59,64,4.0,5,40,Urban,Data Analyst,116337,0 +117980,Male,29,Diploma,4,13,51,3,6,2.0,0,34,Urban,Software Engineer,32514,0 +117981,Female,57,PhD,18,51,65,8,98,8.0,0,8,Urban,Software Engineer,92243,0 +117982,Female,39,Bachelors,7,22,46,88,33,0.0,7,23,Rural,Data Analyst,36103,0 +117983,Male,56,Bachelors,14,29,66,79,70,0.0,1,45,Urban,Software Engineer,60917,0 +117984,Female,40,Bachelors,5,60,41,91,64,5.0,3,83,Rural,Data Analyst,97910,1 +117985,Male,34,High School,0,6,84,39,90,6.0,7,98,Rural,Manager,133184,0 +117986,Male,47,Bachelors,12,94,61,58,9,2.0,5,88,Rural,Software Engineer,37403,1 +117987,Female,54,Diploma,13,66,3,25,10,9.0,6,1,Urban,HR Executive,84106,0 +117988,Male,28,Bachelors,0,14,37,4,14,9.0,6,43,Urban,ML Engineer,66581,0 +117989,Female,27,Bachelors,0,79,43,55,17,3.0,0,27,Urban,Software Engineer,26746,0 +117990,Male,21,Masters,7,43,10,38,94,5.0,2,67,Urban,Software Engineer,117675,0 +117991,Male,23,Bachelors,12,4,64,17,39,6.0,3,75,Semi-Urban,Software Engineer,46702,0 +117992,Female,29,Masters,16,11,66,91,53,0.0,0,54,Urban,Manager,55591,0 +117993,Male,55,Bachelors,9,8,85,23,74,8.0,2,50,Rural,Manager,112326,0 +117994,Male,42,High School,5,64,50,73,69,6.0,1,23,Urban,Data Analyst,77273,0 +117995,Female,44,Diploma,15,40,76,60,27,9.0,2,2,Urban,Software Engineer,40888,0 +117996,Male,35,Bachelors,10,93,52,38,96,3.0,7,4,Semi-Urban,Software Engineer,67463,0 +117997,Other,34,Masters,13,26,74,39,47,8.0,1,28,Semi-Urban,Manager,128950,0 +117998,Female,34,High School,19,35,69,63,74,2.0,1,52,Rural,Software Engineer,70755,0 +117999,Male,36,Diploma,2,67,58,86,28,1.0,3,62,Semi-Urban,Data Analyst,47361,1 +118000,Female,33,High School,18,85,43,61,43,8.0,7,39,Semi-Urban,Data Analyst,77203,0 +118001,Female,48,Masters,12,35,5,94,47,1.0,2,73,Urban,Software Engineer,74056,0 +118002,Female,41,High School,16,89,5,38,99,9.0,2,77,Semi-Urban,ML Engineer,104293,0 +118003,Female,53,Bachelors,13,31,56,46,17,1.0,3,59,Urban,HR Executive,128950,0 +118004,Male,47,Bachelors,5,20,43,1,81,4.0,5,74,Urban,ML Engineer,137686,0 +118005,Male,29,Bachelors,12,53,7,28,1,4.0,1,34,Semi-Urban,Data Analyst,135927,0 +118006,Female,21,High School,9,30,74,68,52,7.0,1,49,Urban,ML Engineer,79902,0 +118007,Female,55,Diploma,7,26,43,15,99,8.0,6,19,Rural,Software Engineer,117012,0 +118008,Female,47,Bachelors,7,66,23,1,50,2.0,5,47,Semi-Urban,Manager,37608,0 +118009,Male,49,High School,5,18,22,43,78,8.0,0,37,Rural,Manager,57590,0 +118010,Female,35,Diploma,17,82,58,20,47,3.0,3,94,Urban,HR Executive,111693,1 +118011,Male,35,Bachelors,2,81,4,91,53,2.0,1,25,Urban,HR Executive,112191,0 +118012,Female,43,Masters,18,42,83,81,53,0.0,6,43,Urban,Software Engineer,22855,1 +118013,Male,27,Masters,6,84,39,58,92,7.0,1,32,Urban,HR Executive,74429,0 +118014,Female,55,Bachelors,18,54,55,40,94,2.0,3,27,Urban,ML Engineer,58316,0 +118015,Male,59,PhD,0,62,20,47,82,5.0,6,58,Rural,HR Executive,55014,0 +118016,Other,35,PhD,12,96,18,85,71,8.0,5,78,Urban,Manager,94744,1 +118017,Male,53,PhD,2,2,85,47,29,2.0,0,42,Rural,ML Engineer,131338,0 +118018,Female,53,Bachelors,17,16,90,15,40,1.0,2,76,Rural,Software Engineer,110690,0 +118019,Male,50,Bachelors,13,61,50,81,18,3.0,0,14,Urban,Software Engineer,68254,0 +118020,Male,21,Masters,11,17,63,86,8,2.0,2,60,Urban,ML Engineer,26039,0 +118021,Male,28,Bachelors,14,46,3,79,50,0.0,2,68,Urban,ML Engineer,130636,0 +118022,Female,34,High School,0,26,20,41,86,7.0,2,79,Rural,ML Engineer,84694,0 +118023,Male,51,High School,6,80,3,98,87,0.0,2,58,Urban,ML Engineer,134433,1 +118024,Female,21,High School,12,90,76,71,11,0.0,3,46,Rural,Manager,33032,1 +118025,Male,57,Masters,9,81,59,99,96,1.0,4,95,Rural,ML Engineer,54654,1 +118026,Male,55,Diploma,3,39,11,60,98,7.0,0,7,Urban,Software Engineer,26488,0 +118027,Male,22,Bachelors,14,94,35,40,73,3.0,0,25,Urban,Manager,73231,0 +118028,Male,33,Diploma,2,99,98,29,64,3.0,6,30,Semi-Urban,Manager,96836,1 +118029,Female,39,High School,15,72,10,57,75,1.0,5,45,Rural,Data Analyst,44951,0 +118030,Female,48,Bachelors,0,61,46,5,65,5.0,2,38,Semi-Urban,Manager,27381,0 +118031,Female,59,Bachelors,8,68,2,12,27,4.0,0,96,Semi-Urban,Data Analyst,49556,0 +118032,Male,57,Bachelors,1,36,46,24,58,7.0,5,76,Urban,Software Engineer,134782,0 +118033,Other,59,Bachelors,4,65,84,54,22,4.0,2,13,Urban,Software Engineer,142821,0 +118034,Female,29,Bachelors,18,57,76,24,75,4.0,4,62,Rural,HR Executive,80837,0 +118035,Male,50,Bachelors,6,48,8,42,73,3.0,5,27,Semi-Urban,Data Analyst,23033,0 +118036,Female,34,Diploma,3,30,63,51,75,6.0,2,63,Urban,HR Executive,67859,0 +118037,Male,26,PhD,6,4,37,14,4,9.0,1,26,Urban,HR Executive,74879,0 +118038,Male,22,Bachelors,16,78,81,33,67,7.0,0,12,Urban,HR Executive,118113,0 +118039,Female,45,Masters,1,75,65,56,60,1.0,6,56,Urban,Manager,100243,1 +118040,Female,43,Diploma,15,57,86,85,59,7.0,5,35,Rural,Data Analyst,105283,1 +118041,Male,40,Bachelors,7,56,79,34,8,1.0,3,47,Semi-Urban,HR Executive,41807,0 +118042,Female,52,High School,6,52,87,86,15,9.0,0,55,Semi-Urban,ML Engineer,108019,1 +118043,Male,31,Diploma,2,5,93,47,57,0.0,5,90,Urban,Software Engineer,131657,1 +118044,Female,38,Masters,19,24,8,8,1,8.0,7,86,Rural,Manager,66837,0 +118045,Female,29,Bachelors,8,29,71,19,47,8.0,5,9,Urban,HR Executive,53915,0 +118046,Male,25,Bachelors,5,18,76,79,24,9.0,6,43,Urban,ML Engineer,139476,0 +118047,Female,44,Bachelors,2,11,9,79,55,1.0,4,68,Semi-Urban,Software Engineer,104287,0 +118048,Female,25,Bachelors,5,64,35,20,30,5.0,4,32,Urban,ML Engineer,132411,0 +118049,Female,48,Diploma,13,24,9,37,16,4.0,7,23,Urban,Software Engineer,60209,0 +118050,Female,22,Masters,3,70,6,24,79,4.0,6,88,Urban,Data Analyst,34750,0 +118051,Male,47,Diploma,15,40,20,40,33,4.0,0,33,Semi-Urban,Software Engineer,97230,0 +118052,Female,43,Diploma,8,34,89,36,51,4.0,2,58,Urban,Software Engineer,38617,0 +118053,Male,33,Masters,17,39,12,72,8,0.0,0,26,Urban,Software Engineer,102539,0 +118054,Male,22,Diploma,9,10,65,6,54,0.0,2,52,Urban,Software Engineer,146433,0 +118055,Female,51,Diploma,5,99,58,80,44,5.0,2,58,Urban,Software Engineer,117913,1 +118056,Female,33,High School,6,93,57,45,59,2.0,4,35,Semi-Urban,Data Analyst,105758,0 +118057,Female,33,Bachelors,7,42,83,95,66,0.0,4,54,Urban,ML Engineer,137415,1 +118058,Female,42,High School,8,12,54,97,81,6.0,4,91,Urban,Software Engineer,28419,1 +118059,Male,28,Masters,8,38,97,0,54,3.0,1,47,Rural,Manager,28721,0 +118060,Male,47,Diploma,14,75,15,73,40,4.0,5,96,Urban,Data Analyst,21615,1 +118061,Female,40,Diploma,10,90,31,73,12,6.0,3,84,Urban,Manager,104635,1 +118062,Female,22,Diploma,9,85,16,49,68,6.0,6,8,Semi-Urban,HR Executive,70979,0 +118063,Male,58,Diploma,9,32,37,4,41,4.0,3,49,Semi-Urban,HR Executive,126440,0 +118064,Male,45,Masters,0,24,95,53,86,2.0,6,9,Semi-Urban,Data Analyst,137841,0 +118065,Female,22,Masters,2,66,3,0,11,5.0,5,5,Urban,Data Analyst,106511,0 +118066,Male,34,Diploma,6,34,0,26,75,2.0,2,22,Urban,Data Analyst,132132,0 +118067,Female,41,Masters,10,0,80,52,49,2.0,0,80,Semi-Urban,HR Executive,106858,0 +118068,Male,36,Diploma,15,93,99,91,58,3.0,2,82,Urban,ML Engineer,94505,1 +118069,Male,41,Bachelors,19,60,25,44,71,1.0,7,49,Urban,HR Executive,143448,0 +118070,Female,36,Masters,5,75,99,93,54,2.0,6,73,Urban,Manager,90382,1 +118071,Male,47,Bachelors,10,58,82,43,34,2.0,2,19,Urban,Software Engineer,29156,0 +118072,Male,42,Diploma,1,50,34,21,16,7.0,4,84,Rural,Data Analyst,117356,0 +118073,Male,46,Diploma,11,95,95,63,29,8.0,6,88,Urban,ML Engineer,106658,1 +118074,Male,42,Diploma,15,41,55,4,64,8.0,5,11,Semi-Urban,Data Analyst,83070,0 +118075,Male,51,Diploma,16,98,29,67,3,1.0,4,31,Rural,Software Engineer,126102,0 +118076,Female,31,Masters,5,73,6,78,94,1.0,6,71,Urban,ML Engineer,54639,0 +118077,Male,39,Diploma,9,15,18,28,25,2.0,1,80,Semi-Urban,ML Engineer,128773,0 +118078,Male,24,High School,3,89,34,19,65,6.0,7,27,Urban,Software Engineer,100377,0 +118079,Male,26,Bachelors,1,87,64,10,35,4.0,0,98,Urban,Manager,38700,1 +118080,Male,59,PhD,14,85,43,13,56,3.0,3,93,Urban,HR Executive,97816,0 +118081,Male,37,Diploma,19,79,82,24,98,7.0,0,5,Urban,Manager,33559,0 +118082,Male,31,Masters,14,46,59,7,32,4.0,1,8,Urban,Manager,116544,0 +118083,Male,45,Masters,10,70,34,58,94,9.0,6,32,Rural,Data Analyst,114156,0 +118084,Female,44,Diploma,2,9,77,10,56,3.0,2,49,Semi-Urban,HR Executive,129754,0 +118085,Female,37,Masters,6,83,41,64,40,0.0,0,36,Urban,Manager,129608,0 +118086,Male,55,Bachelors,6,42,20,29,94,9.0,1,43,Rural,ML Engineer,31124,0 +118087,Male,48,Diploma,4,33,19,30,40,1.0,4,3,Semi-Urban,Manager,77143,0 +118088,Male,33,Diploma,12,66,21,58,5,7.0,3,20,Urban,ML Engineer,50652,0 +118089,Male,47,Bachelors,18,55,24,54,18,8.0,4,37,Urban,ML Engineer,73660,0 +118090,Male,43,High School,13,97,88,79,31,6.0,1,80,Urban,HR Executive,47314,1 +118091,Male,34,Bachelors,16,53,83,7,10,1.0,6,70,Semi-Urban,ML Engineer,72939,0 +118092,Male,47,Bachelors,3,93,41,23,81,4.0,5,48,Urban,Software Engineer,125360,0 +118093,Male,48,High School,14,14,70,82,89,9.0,6,49,Urban,Software Engineer,118818,0 +118094,Male,23,Bachelors,5,58,74,67,25,0.0,3,76,Rural,HR Executive,134390,1 +118095,Male,47,Masters,6,34,90,48,15,4.0,7,82,Urban,HR Executive,88533,1 +118096,Male,58,Bachelors,9,97,73,96,81,7.0,6,28,Urban,HR Executive,61919,1 +118097,Female,49,Bachelors,1,99,66,63,94,0.0,0,72,Urban,Data Analyst,113359,1 +118098,Female,33,Masters,14,44,16,89,93,1.0,5,21,Urban,Software Engineer,55832,0 +118099,Female,54,Masters,19,9,60,3,35,0.0,2,90,Urban,Data Analyst,62547,0 +118100,Female,52,Diploma,18,97,88,14,41,0.0,4,22,Urban,HR Executive,148983,0 +118101,Male,22,Masters,3,17,61,14,26,7.0,4,55,Urban,ML Engineer,62754,0 +118102,Male,41,Bachelors,3,48,46,1,24,4.0,7,78,Semi-Urban,Data Analyst,93430,0 +118103,Male,22,Bachelors,7,72,55,76,72,8.0,4,69,Semi-Urban,Manager,114965,1 +118104,Male,25,Diploma,2,52,93,26,67,2.0,6,11,Urban,Data Analyst,44101,0 +118105,Male,32,Diploma,15,36,90,11,84,1.0,5,38,Semi-Urban,HR Executive,85676,0 +118106,Male,35,Masters,0,40,26,87,31,5.0,4,3,Urban,HR Executive,136186,0 +118107,Female,38,High School,6,29,37,36,14,3.0,0,91,Urban,ML Engineer,29294,0 +118108,Male,24,High School,1,92,21,0,64,4.0,6,99,Semi-Urban,ML Engineer,109060,0 +118109,Male,35,Bachelors,11,46,83,17,98,4.0,6,66,Rural,Data Analyst,83886,0 +118110,Male,43,Masters,6,94,45,54,39,8.0,7,11,Urban,Manager,72063,0 +118111,Male,24,Bachelors,7,42,97,25,51,7.0,2,73,Urban,Manager,83485,1 +118112,Female,23,Diploma,9,87,45,51,81,2.0,2,39,Urban,Software Engineer,127244,0 +118113,Female,52,Bachelors,1,72,39,88,50,9.0,6,90,Rural,HR Executive,29816,1 +118114,Male,25,High School,0,76,50,77,53,8.0,2,30,Semi-Urban,Software Engineer,96395,0 +118115,Male,47,High School,10,16,69,71,30,6.0,3,4,Urban,Data Analyst,133891,0 +118116,Female,45,High School,2,26,10,0,75,1.0,3,87,Urban,Data Analyst,33010,0 +118117,Male,38,Bachelors,4,72,94,85,28,0.0,1,8,Urban,ML Engineer,64040,1 +118118,Male,45,Bachelors,3,98,40,13,79,9.0,6,80,Semi-Urban,ML Engineer,39305,0 +118119,Male,47,High School,1,91,46,66,97,2.0,6,89,Urban,Manager,67041,1 +118120,Male,28,PhD,6,73,12,72,2,0.0,1,55,Urban,Software Engineer,22500,0 +118121,Female,33,Diploma,9,17,5,80,35,7.0,7,54,Urban,HR Executive,35535,0 +118122,Male,33,Masters,8,33,53,22,68,4.0,7,32,Urban,Software Engineer,92874,0 +118123,Male,29,Bachelors,5,14,32,79,92,2.0,3,14,Urban,ML Engineer,25772,0 +118124,Female,55,Bachelors,11,9,45,59,51,9.0,7,4,Urban,ML Engineer,98301,0 +118125,Male,35,Masters,8,46,25,17,5,1.0,4,78,Urban,HR Executive,63011,0 +118126,Male,29,Diploma,3,9,27,90,99,5.0,3,38,Urban,HR Executive,51285,0 +118127,Male,47,Masters,18,60,30,97,83,7.0,2,3,Urban,ML Engineer,108841,0 +118128,Female,51,Masters,12,79,94,76,26,2.0,3,99,Urban,Data Analyst,105859,1 +118129,Female,53,High School,12,17,12,23,32,3.0,3,51,Urban,Data Analyst,74012,0 +118130,Male,24,Masters,16,10,67,36,23,6.0,1,61,Urban,HR Executive,62870,0 +118131,Female,49,Diploma,2,71,69,99,28,0.0,3,1,Rural,ML Engineer,118429,0 +118132,Female,48,Bachelors,18,78,36,98,96,5.0,1,35,Semi-Urban,Data Analyst,94732,1 +118133,Female,29,Bachelors,8,48,69,64,70,3.0,6,64,Urban,HR Executive,26891,1 +118134,Male,28,Masters,4,5,65,98,57,4.0,7,8,Urban,Manager,38066,0 +118135,Male,58,Masters,2,92,70,69,1,9.0,5,93,Rural,HR Executive,83311,1 +118136,Male,50,Bachelors,0,15,11,59,12,9.0,7,72,Urban,Data Analyst,121185,0 +118137,Male,47,Bachelors,1,8,52,12,49,6.0,3,59,Urban,Manager,96754,0 +118138,Male,42,High School,12,94,80,51,27,4.0,7,38,Semi-Urban,Data Analyst,87998,1 +118139,Male,38,Masters,10,11,73,67,0,4.0,0,43,Urban,ML Engineer,67335,0 +118140,Female,41,PhD,0,65,69,54,57,5.0,1,43,Rural,ML Engineer,28265,0 +118141,Female,46,Bachelors,10,69,92,10,44,5.0,7,80,Rural,HR Executive,61984,1 +118142,Male,35,Bachelors,4,84,84,3,3,3.0,0,96,Urban,HR Executive,95355,1 +118143,Male,38,High School,18,43,89,12,15,8.0,7,34,Rural,Data Analyst,136051,0 +118144,Male,42,Bachelors,9,25,93,27,41,7.0,4,49,Rural,HR Executive,31431,0 +118145,Female,29,Bachelors,7,63,70,95,93,7.0,1,56,Rural,Manager,58041,1 +118146,Female,55,Bachelors,7,98,93,83,38,2.0,7,98,Rural,Manager,130042,1 +118147,Female,26,Bachelors,0,10,84,42,26,7.0,0,51,Semi-Urban,ML Engineer,73832,0 +118148,Female,54,Masters,17,43,49,68,59,6.0,6,75,Rural,Software Engineer,41129,0 +118149,Female,27,Masters,11,32,8,78,52,2.0,5,88,Urban,ML Engineer,117993,0 +118150,Other,59,High School,19,52,31,31,26,9.0,4,78,Urban,Software Engineer,29296,0 +118151,Male,59,Masters,12,95,32,56,41,8.0,7,19,Urban,Manager,86218,0 +118152,Female,42,Bachelors,0,16,19,1,32,7.0,5,78,Semi-Urban,ML Engineer,70891,0 +118153,Female,53,Bachelors,10,76,15,33,48,5.0,4,45,Semi-Urban,HR Executive,108305,0 +118154,Male,25,Masters,15,16,4,55,23,9.0,7,5,Urban,Software Engineer,116143,0 +118155,Male,57,Masters,4,11,90,80,73,1.0,3,20,Semi-Urban,Data Analyst,138669,0 +118156,Male,46,High School,1,16,22,94,53,2.0,5,39,Rural,Data Analyst,121379,0 +118157,Male,52,Bachelors,9,12,87,32,65,7.0,3,42,Rural,Data Analyst,81189,0 +118158,Male,44,Diploma,14,11,40,26,33,2.0,0,2,Urban,HR Executive,26470,0 +118159,Female,43,Bachelors,8,54,51,59,88,0.0,2,15,Semi-Urban,ML Engineer,97929,0 +118160,Male,41,Masters,9,16,19,50,70,7.0,4,90,Rural,Manager,143564,0 +118161,Female,47,Masters,8,24,77,68,55,6.0,1,76,Urban,Manager,37511,1 +118162,Female,21,Diploma,6,23,30,56,20,3.0,1,74,Semi-Urban,Manager,121020,0 +118163,Male,21,Bachelors,19,43,64,33,82,2.0,3,34,Urban,ML Engineer,75009,0 +118164,Other,37,Masters,14,61,93,81,9,9.0,3,9,Urban,HR Executive,142069,1 +118165,Male,50,Diploma,6,4,25,67,55,6.0,6,34,Semi-Urban,HR Executive,118886,0 +118166,Female,37,Bachelors,3,46,55,65,77,9.0,1,94,Semi-Urban,Data Analyst,129881,1 +118167,Other,21,Diploma,15,99,34,72,33,9.0,2,85,Semi-Urban,ML Engineer,74290,1 +118168,Male,48,Masters,4,77,42,50,45,7.0,1,1,Urban,Manager,97016,0 +118169,Male,26,Bachelors,14,7,54,87,7,0.0,4,43,Urban,HR Executive,108405,0 +118170,Male,32,High School,18,52,3,84,51,0.0,3,37,Rural,Manager,106947,0 +118171,Male,38,Diploma,4,63,83,82,27,7.0,3,98,Urban,ML Engineer,43334,1 +118172,Female,34,Masters,17,2,89,16,74,7.0,4,19,Urban,Software Engineer,140045,0 +118173,Male,49,Bachelors,19,63,98,48,49,9.0,3,79,Rural,ML Engineer,95029,1 +118174,Female,47,High School,8,79,53,94,66,9.0,0,64,Semi-Urban,HR Executive,63124,1 +118175,Female,52,Bachelors,14,32,51,86,72,6.0,2,31,Rural,Data Analyst,85675,0 +118176,Male,21,High School,1,30,68,65,0,1.0,0,63,Semi-Urban,Software Engineer,87420,0 +118177,Female,26,Bachelors,2,84,3,32,90,0.0,2,27,Semi-Urban,Data Analyst,35440,0 +118178,Female,37,Bachelors,1,82,37,75,77,1.0,2,96,Urban,Manager,147830,1 +118179,Female,59,High School,6,41,38,89,23,9.0,2,35,Semi-Urban,ML Engineer,121831,0 +118180,Male,49,Diploma,4,89,70,65,1,7.0,2,85,Urban,HR Executive,141319,1 +118181,Male,36,Diploma,1,94,59,63,62,0.0,2,41,Urban,Manager,23352,1 +118182,Male,33,Diploma,9,38,48,77,72,7.0,3,65,Urban,ML Engineer,100104,0 +118183,Male,31,Masters,17,58,36,14,25,8.0,3,28,Urban,ML Engineer,83583,0 +118184,Other,44,Bachelors,18,47,7,77,76,6.0,0,75,Urban,HR Executive,78072,0 +118185,Female,26,Diploma,4,10,36,61,41,1.0,6,70,Rural,Data Analyst,37004,0 +118186,Male,36,Bachelors,4,67,70,98,86,1.0,4,25,Urban,Data Analyst,85553,1 +118187,Male,51,Masters,13,80,7,16,67,8.0,7,87,Rural,HR Executive,83894,0 +118188,Female,50,Masters,13,35,21,97,10,3.0,4,79,Semi-Urban,HR Executive,84120,0 +118189,Male,47,PhD,18,68,19,44,40,2.0,4,2,Urban,Software Engineer,51621,0 +118190,Male,45,Diploma,4,73,39,42,19,3.0,1,5,Semi-Urban,Data Analyst,99585,0 +118191,Female,41,Bachelors,1,44,7,77,23,4.0,5,75,Rural,ML Engineer,68737,0 +118192,Male,33,Bachelors,9,13,47,74,37,0.0,5,61,Semi-Urban,Software Engineer,80272,0 +118193,Male,54,Bachelors,17,34,12,41,68,4.0,1,9,Urban,Manager,139198,0 +118194,Male,50,Bachelors,8,61,42,99,14,8.0,1,33,Semi-Urban,Manager,97448,1 +118195,Other,48,PhD,13,80,90,30,2,3.0,5,90,Urban,Manager,26565,1 +118196,Male,36,Masters,17,81,9,2,26,0.0,3,38,Semi-Urban,ML Engineer,53268,0 +118197,Other,51,Bachelors,16,36,97,39,28,0.0,4,69,Rural,Software Engineer,130431,1 +118198,Male,40,High School,6,3,94,82,57,3.0,0,37,Urban,Data Analyst,36746,0 +118199,Male,32,Masters,15,89,42,62,80,4.0,3,98,Rural,Data Analyst,114997,1 +118200,Male,26,Diploma,10,28,53,51,16,9.0,4,4,Urban,ML Engineer,84677,0 +118201,Male,28,Bachelors,0,74,25,97,40,1.0,3,77,Rural,Data Analyst,126537,1 +118202,Other,29,Bachelors,18,46,15,94,90,5.0,0,91,Urban,Software Engineer,97180,1 +118203,Other,59,Bachelors,1,88,75,30,50,1.0,1,27,Urban,Data Analyst,22265,0 +118204,Male,30,High School,14,59,98,50,96,0.0,0,20,Urban,HR Executive,101637,0 +118205,Male,38,Masters,18,99,72,29,33,8.0,5,58,Semi-Urban,Software Engineer,37713,1 +118206,Male,42,Diploma,12,87,24,28,85,3.0,0,42,Urban,Software Engineer,80537,0 +118207,Male,28,High School,3,96,46,12,35,0.0,1,88,Urban,Data Analyst,44419,1 +118208,Female,42,Masters,10,36,97,57,44,3.0,4,62,Urban,HR Executive,108642,1 +118209,Female,52,Diploma,16,2,11,35,65,3.0,7,69,Semi-Urban,Software Engineer,38423,0 +118210,Female,55,High School,6,8,87,93,7,4.0,3,21,Semi-Urban,Data Analyst,141500,0 +118211,Male,43,High School,13,55,39,83,39,7.0,7,26,Semi-Urban,Data Analyst,100437,0 +118212,Female,23,PhD,18,9,47,40,39,6.0,6,18,Urban,HR Executive,44064,0 +118213,Female,22,Masters,8,81,66,44,72,4.0,4,74,Rural,HR Executive,44219,1 +118214,Male,53,Masters,12,41,70,99,59,9.0,4,87,Semi-Urban,Manager,90058,1 +118215,Male,43,Bachelors,12,39,26,78,58,7.0,0,72,Rural,Data Analyst,91911,0 +118216,Male,40,Diploma,5,64,9,41,97,3.0,0,57,Semi-Urban,Software Engineer,43219,0 +118217,Female,55,Masters,6,60,33,93,90,3.0,4,97,Urban,Manager,114189,1 +118218,Female,23,Bachelors,16,54,36,71,0,7.0,5,23,Urban,Data Analyst,36449,0 +118219,Female,45,Bachelors,14,54,71,76,54,4.0,1,12,Urban,Data Analyst,61813,0 +118220,Female,43,Diploma,14,19,55,94,9,8.0,6,2,Semi-Urban,Software Engineer,91808,0 +118221,Male,47,High School,5,61,54,90,44,5.0,1,93,Rural,ML Engineer,143321,1 +118222,Male,53,High School,7,82,45,69,88,5.0,0,33,Urban,Manager,147561,0 +118223,Female,50,High School,4,78,9,95,57,5.0,3,13,Rural,Data Analyst,87225,0 +118224,Female,38,Masters,12,0,56,59,89,4.0,0,67,Semi-Urban,HR Executive,145109,0 +118225,Female,48,High School,15,84,6,24,38,2.0,6,70,Urban,Software Engineer,96052,0 +118226,Female,36,Bachelors,16,15,34,60,42,1.0,5,43,Urban,HR Executive,101964,0 +118227,Other,32,Bachelors,14,37,21,69,12,6.0,2,37,Urban,ML Engineer,74041,0 +118228,Male,49,Bachelors,9,57,48,51,60,5.0,1,70,Urban,Data Analyst,27861,0 +118229,Female,49,Masters,6,91,54,98,11,0.0,7,49,Urban,Manager,37521,1 +118230,Other,44,Masters,12,18,64,10,55,6.0,3,53,Rural,Software Engineer,40540,0 +118231,Female,45,High School,10,96,14,74,31,4.0,1,97,Urban,Manager,79139,1 +118232,Male,26,Bachelors,17,12,52,59,14,1.0,2,99,Urban,Software Engineer,128740,0 +118233,Female,27,Diploma,17,34,99,95,33,5.0,1,39,Urban,HR Executive,123583,1 +118234,Female,48,Bachelors,12,32,50,20,52,8.0,6,54,Urban,Data Analyst,26941,0 +118235,Male,41,Diploma,10,62,77,4,7,2.0,3,42,Urban,ML Engineer,87819,0 +118236,Male,26,High School,19,9,36,8,51,5.0,4,93,Urban,Data Analyst,130969,0 +118237,Male,33,Bachelors,19,48,0,88,68,3.0,0,62,Rural,Software Engineer,84095,0 +118238,Male,31,Masters,17,38,47,51,53,4.0,3,17,Urban,ML Engineer,66813,0 +118239,Male,31,Bachelors,0,71,79,24,57,4.0,0,2,Urban,HR Executive,26763,0 +118240,Female,21,Diploma,8,46,36,60,64,8.0,6,11,Rural,Manager,40008,0 +118241,Male,55,PhD,13,74,48,11,43,6.0,2,17,Urban,Software Engineer,68365,0 +118242,Female,47,Masters,3,82,52,21,4,8.0,7,0,Urban,Manager,133116,0 +118243,Female,53,Bachelors,4,10,94,70,85,7.0,4,75,Rural,Data Analyst,141938,1 +118244,Female,52,Diploma,8,97,33,73,30,2.0,6,64,Urban,HR Executive,73015,1 +118245,Female,33,High School,6,39,21,91,28,6.0,2,83,Urban,HR Executive,43976,0 +118246,Male,21,Diploma,5,92,81,88,82,8.0,1,2,Rural,ML Engineer,73191,1 +118247,Female,59,Diploma,16,35,93,80,14,9.0,3,99,Urban,HR Executive,122655,1 +118248,Male,49,Bachelors,18,12,33,15,12,7.0,5,46,Semi-Urban,HR Executive,51593,0 +118249,Male,44,Masters,5,14,64,31,24,1.0,2,82,Semi-Urban,ML Engineer,75507,0 +118250,Male,33,Masters,0,27,13,4,90,7.0,5,95,Urban,HR Executive,135857,0 +118251,Male,30,Diploma,18,76,6,36,76,2.0,4,51,Urban,Software Engineer,98280,0 +118252,Other,42,Bachelors,3,32,39,26,73,6.0,4,17,Urban,ML Engineer,30276,0 +118253,Male,44,Masters,0,68,72,53,9,6.0,1,57,Semi-Urban,Data Analyst,46771,1 +118254,Male,43,High School,5,90,15,14,19,9.0,5,14,Rural,Data Analyst,85950,0 +118255,Female,38,Bachelors,4,94,67,27,68,6.0,6,53,Rural,HR Executive,117710,1 +118256,Male,31,Diploma,2,65,39,98,79,7.0,4,55,Urban,Software Engineer,76454,1 +118257,Female,42,Bachelors,3,51,83,47,4,4.0,4,46,Urban,Data Analyst,125491,0 +118258,Male,31,Diploma,16,58,4,80,45,4.0,0,30,Urban,ML Engineer,88476,0 +118259,Male,35,Diploma,19,90,19,91,14,4.0,0,26,Semi-Urban,ML Engineer,94089,0 +118260,Female,52,Diploma,3,25,36,34,48,4.0,3,53,Urban,Software Engineer,104312,0 +118261,Male,44,Bachelors,4,10,56,27,97,4.0,6,89,Urban,Software Engineer,37036,0 +118262,Female,31,Masters,11,64,59,39,97,4.0,1,88,Semi-Urban,HR Executive,83748,1 +118263,Male,47,High School,18,73,14,86,61,5.0,1,70,Rural,Software Engineer,67188,1 +118264,Male,41,High School,4,9,59,28,87,2.0,7,89,Semi-Urban,HR Executive,109615,0 +118265,Female,52,Diploma,12,65,72,29,77,0.0,0,91,Rural,ML Engineer,46790,1 +118266,Male,36,Masters,14,50,13,95,91,3.0,6,0,Semi-Urban,Data Analyst,128457,0 +118267,Female,52,Diploma,17,75,14,23,3,4.0,6,25,Semi-Urban,Manager,132348,0 +118268,Male,25,Bachelors,1,64,56,21,87,9.0,2,32,Urban,Software Engineer,129366,0 +118269,Other,29,Diploma,3,89,80,25,62,0.0,4,23,Urban,Manager,20103,0 +118270,Male,32,Masters,9,6,86,21,8,7.0,1,36,Rural,Data Analyst,73024,0 +118271,Female,43,Diploma,8,7,24,70,75,4.0,2,81,Semi-Urban,Software Engineer,79419,0 +118272,Female,36,Diploma,10,84,16,25,60,2.0,6,62,Urban,Data Analyst,117588,0 +118273,Male,27,Bachelors,10,93,8,30,87,9.0,2,98,Urban,ML Engineer,65716,0 +118274,Female,37,PhD,17,79,63,71,88,8.0,6,31,Semi-Urban,ML Engineer,111304,1 +118275,Female,54,Masters,6,11,8,69,61,0.0,7,9,Semi-Urban,Software Engineer,45522,0 +118276,Other,41,Bachelors,18,49,45,74,21,9.0,3,66,Semi-Urban,Manager,45800,0 +118277,Male,45,Bachelors,0,93,51,47,5,7.0,5,60,Rural,HR Executive,83609,1 +118278,Male,38,Bachelors,12,3,32,86,1,2.0,7,30,Urban,Data Analyst,96196,0 +118279,Female,44,Diploma,16,83,52,78,51,1.0,1,14,Urban,Manager,34308,0 +118280,Female,48,Bachelors,17,76,39,70,10,2.0,2,33,Urban,HR Executive,99393,0 +118281,Female,40,High School,10,31,55,7,53,8.0,7,85,Semi-Urban,Manager,60499,0 +118282,Male,47,High School,1,60,28,1,53,3.0,1,38,Urban,Data Analyst,127241,0 +118283,Female,53,High School,18,86,16,99,84,0.0,0,47,Rural,Data Analyst,111677,1 +118284,Male,43,Masters,5,82,13,69,27,4.0,5,41,Rural,HR Executive,142358,0 +118285,Male,51,High School,4,45,61,95,54,6.0,7,83,Urban,Data Analyst,142085,1 +118286,Female,46,Bachelors,14,76,51,8,82,4.0,5,96,Urban,Data Analyst,107873,0 +118287,Female,31,Bachelors,1,19,96,98,70,3.0,2,87,Rural,HR Executive,54726,1 +118288,Female,21,High School,15,47,40,38,12,4.0,4,10,Semi-Urban,HR Executive,92167,0 +118289,Male,31,Diploma,4,11,49,28,47,7.0,7,18,Urban,ML Engineer,59863,0 +118290,Male,55,Bachelors,2,38,34,60,2,3.0,2,99,Semi-Urban,Software Engineer,70547,0 +118291,Male,40,Masters,10,73,95,21,68,0.0,5,28,Urban,Manager,57953,0 +118292,Male,27,Masters,13,44,29,79,15,2.0,1,30,Urban,Software Engineer,81717,0 +118293,Male,51,Diploma,14,8,11,91,63,4.0,3,86,Semi-Urban,Software Engineer,98800,0 +118294,Male,29,Bachelors,0,5,4,12,81,1.0,1,65,Semi-Urban,ML Engineer,111654,0 +118295,Male,31,Bachelors,4,66,77,51,31,8.0,0,29,Semi-Urban,Data Analyst,111998,0 +118296,Female,42,Diploma,4,0,31,84,54,8.0,7,72,Semi-Urban,HR Executive,22012,0 +118297,Male,53,High School,18,86,23,18,54,5.0,7,83,Urban,HR Executive,64629,0 +118298,Male,24,Bachelors,3,44,33,58,70,1.0,3,51,Urban,Manager,29948,0 +118299,Male,21,Bachelors,10,82,41,2,20,9.0,0,21,Urban,Data Analyst,149076,0 +118300,Male,47,Diploma,19,9,1,75,70,3.0,7,18,Semi-Urban,Software Engineer,144993,0 +118301,Male,51,PhD,16,18,23,20,72,5.0,1,4,Urban,HR Executive,138725,0 +118302,Male,51,Bachelors,12,19,74,8,33,2.0,4,71,Urban,ML Engineer,147187,0 +118303,Female,53,Bachelors,5,41,68,81,53,1.0,6,18,Rural,Data Analyst,52481,0 +118304,Male,39,Bachelors,16,67,27,28,9,6.0,3,52,Urban,Manager,106157,0 +118305,Female,49,Diploma,0,76,74,95,42,6.0,0,43,Urban,Manager,124750,1 +118306,Male,32,Diploma,13,4,25,56,63,3.0,4,9,Semi-Urban,Data Analyst,66208,0 +118307,Male,38,Masters,9,30,50,98,95,6.0,7,1,Urban,ML Engineer,69463,0 +118308,Female,47,Diploma,15,26,74,1,69,2.0,3,81,Urban,Software Engineer,56909,0 +118309,Male,26,Diploma,7,33,39,95,73,7.0,1,93,Urban,Software Engineer,123029,1 +118310,Male,24,Diploma,17,38,95,53,53,4.0,4,30,Urban,Manager,122633,0 +118311,Other,56,Masters,3,78,28,40,31,2.0,4,93,Urban,Software Engineer,111486,0 +118312,Male,24,Masters,10,98,64,1,18,5.0,2,76,Urban,HR Executive,47371,1 +118313,Female,56,Diploma,7,56,18,11,40,3.0,4,12,Rural,ML Engineer,125357,0 +118314,Male,41,High School,3,73,71,82,20,4.0,5,30,Urban,Data Analyst,25385,1 +118315,Female,26,Masters,10,9,97,78,19,1.0,5,91,Rural,Data Analyst,87383,1 +118316,Female,53,Masters,18,57,73,80,3,3.0,0,32,Semi-Urban,Manager,46832,1 +118317,Female,38,Masters,3,82,85,51,58,0.0,0,94,Semi-Urban,Data Analyst,145870,1 +118318,Male,41,Bachelors,17,81,89,92,86,5.0,4,95,Semi-Urban,Software Engineer,20397,1 +118319,Other,33,Masters,9,33,39,54,47,6.0,7,82,Urban,HR Executive,38934,0 +118320,Female,33,Masters,0,43,27,69,79,3.0,3,76,Rural,Software Engineer,49157,0 +118321,Other,28,Bachelors,16,64,82,25,53,8.0,5,20,Semi-Urban,Software Engineer,35152,0 +118322,Other,55,Diploma,8,43,17,48,58,1.0,6,85,Urban,Software Engineer,68384,0 +118323,Male,33,Bachelors,8,95,64,67,59,2.0,5,67,Rural,Data Analyst,73631,1 +118324,Male,54,Masters,17,31,97,79,16,8.0,2,52,Semi-Urban,Software Engineer,27218,1 +118325,Male,24,Masters,19,38,49,13,77,8.0,1,62,Urban,HR Executive,105277,0 +118326,Male,34,Bachelors,9,36,89,39,76,9.0,7,69,Urban,Software Engineer,120029,0 +118327,Male,31,Bachelors,18,97,66,20,50,2.0,5,75,Rural,ML Engineer,122688,1 +118328,Male,22,Bachelors,13,74,85,76,12,0.0,1,44,Urban,Manager,38756,1 +118329,Male,36,Bachelors,13,27,34,17,78,8.0,6,24,Urban,Data Analyst,106663,0 +118330,Male,40,Diploma,9,93,72,7,27,8.0,5,27,Urban,HR Executive,40506,0 +118331,Female,24,Bachelors,3,70,62,7,58,9.0,4,34,Urban,Manager,148176,0 +118332,Male,52,Diploma,5,51,52,43,90,9.0,0,55,Semi-Urban,Software Engineer,77527,0 +118333,Female,32,Bachelors,15,63,45,45,3,9.0,7,93,Urban,Manager,135125,1 +118334,Male,36,Masters,8,56,56,79,34,9.0,6,22,Semi-Urban,Data Analyst,118032,0 +118335,Female,33,Masters,7,56,92,85,34,7.0,5,15,Urban,Software Engineer,92851,1 +118336,Male,41,Bachelors,16,14,29,87,52,3.0,7,76,Rural,HR Executive,23303,0 +118337,Female,27,Bachelors,11,51,0,75,24,0.0,0,85,Urban,HR Executive,116383,0 +118338,Female,36,Diploma,3,55,4,54,46,0.0,4,76,Urban,HR Executive,46981,0 +118339,Female,40,High School,2,82,73,56,70,4.0,7,80,Urban,Manager,129667,1 +118340,Female,52,Bachelors,15,82,95,62,82,1.0,3,25,Urban,HR Executive,97556,1 +118341,Female,25,Bachelors,16,74,76,41,66,3.0,2,38,Urban,Manager,71794,0 +118342,Female,58,Bachelors,1,53,82,11,55,4.0,0,34,Urban,ML Engineer,72624,0 +118343,Male,41,Diploma,8,68,49,49,48,7.0,0,8,Urban,Software Engineer,119264,0 +118344,Female,22,Bachelors,13,3,84,43,6,4.0,3,49,Urban,Software Engineer,40131,0 +118345,Male,53,High School,18,47,89,20,9,9.0,2,26,Urban,Manager,91560,0 +118346,Female,37,Diploma,7,87,82,54,15,3.0,2,59,Urban,HR Executive,85092,1 +118347,Male,38,Diploma,1,1,49,87,66,9.0,3,10,Rural,ML Engineer,87559,0 +118348,Other,37,Bachelors,7,86,47,34,94,2.0,5,39,Urban,Manager,113273,0 +118349,Male,57,High School,17,45,47,33,52,3.0,2,35,Semi-Urban,ML Engineer,91052,0 +118350,Male,21,Masters,8,49,13,32,5,5.0,5,58,Urban,ML Engineer,113403,0 +118351,Male,50,Masters,16,29,34,96,44,0.0,2,64,Rural,Software Engineer,58710,0 +118352,Male,55,Bachelors,12,17,97,7,87,1.0,7,25,Urban,HR Executive,44251,0 +118353,Male,26,Bachelors,3,50,42,54,25,0.0,0,77,Semi-Urban,Data Analyst,106074,0 +118354,Female,31,Bachelors,4,6,79,72,86,3.0,2,66,Urban,Data Analyst,95745,0 +118355,Female,39,Bachelors,3,1,60,71,24,6.0,2,60,Urban,HR Executive,92518,0 +118356,Male,35,PhD,11,65,61,67,60,1.0,2,42,Urban,Software Engineer,145155,1 +118357,Female,28,Diploma,9,23,27,45,29,9.0,0,61,Urban,Data Analyst,108136,0 +118358,Male,56,Diploma,11,16,85,41,80,8.0,0,67,Rural,HR Executive,30878,0 +118359,Male,58,Masters,8,3,74,91,11,3.0,6,76,Semi-Urban,Software Engineer,122327,1 +118360,Male,48,Bachelors,18,59,16,21,57,0.0,4,91,Urban,Manager,43318,0 +118361,Male,21,High School,0,12,84,20,69,8.0,0,59,Rural,HR Executive,65779,0 +118362,Male,32,Masters,1,21,17,84,29,3.0,4,15,Urban,Data Analyst,112517,0 +118363,Male,42,Bachelors,8,38,43,24,63,3.0,5,77,Urban,Data Analyst,104072,0 +118364,Female,47,Diploma,13,97,94,27,15,4.0,3,38,Urban,Manager,48879,1 +118365,Male,22,Diploma,16,0,77,99,27,2.0,4,25,Urban,Data Analyst,134858,0 +118366,Male,39,Bachelors,12,67,66,16,80,2.0,7,73,Rural,ML Engineer,142298,0 +118367,Female,23,Bachelors,11,56,33,11,32,5.0,2,92,Semi-Urban,ML Engineer,49271,0 +118368,Other,30,Bachelors,2,28,7,33,84,7.0,6,9,Urban,ML Engineer,37658,0 +118369,Other,45,High School,11,62,27,78,71,8.0,4,89,Semi-Urban,ML Engineer,78960,1 +118370,Other,29,Diploma,19,43,27,6,20,4.0,4,82,Urban,ML Engineer,139803,0 +118371,Male,46,Diploma,0,37,57,25,45,5.0,7,63,Urban,ML Engineer,84309,0 +118372,Male,56,Bachelors,0,43,81,21,76,3.0,1,28,Urban,Data Analyst,61784,0 +118373,Female,45,Bachelors,9,50,52,97,73,4.0,1,85,Urban,ML Engineer,115498,1 +118374,Female,33,Diploma,16,88,51,32,25,0.0,5,89,Urban,ML Engineer,66162,1 +118375,Other,37,High School,18,24,85,71,75,8.0,6,90,Rural,Data Analyst,94761,1 +118376,Male,21,Bachelors,19,56,79,6,13,2.0,6,74,Urban,Manager,107335,0 +118377,Other,27,High School,8,99,59,56,25,8.0,3,10,Urban,ML Engineer,75575,0 +118378,Male,29,Bachelors,6,33,48,25,81,3.0,3,53,Urban,Data Analyst,76708,0 +118379,Male,52,Masters,19,58,9,30,63,8.0,0,37,Urban,HR Executive,63919,0 +118380,Female,54,Masters,16,57,51,20,69,3.0,5,25,Semi-Urban,ML Engineer,100840,0 +118381,Female,56,Bachelors,17,9,21,85,58,6.0,0,19,Rural,Data Analyst,73064,0 +118382,Male,54,Masters,8,20,81,9,92,2.0,7,65,Semi-Urban,ML Engineer,67259,0 +118383,Male,49,Masters,10,36,99,39,10,1.0,1,85,Semi-Urban,Software Engineer,111412,1 +118384,Male,31,Masters,15,13,55,29,19,1.0,7,1,Urban,Data Analyst,65970,0 +118385,Other,33,Bachelors,15,51,89,47,74,3.0,2,87,Urban,Data Analyst,63831,1 +118386,Male,47,Masters,0,57,85,97,44,3.0,5,40,Semi-Urban,Software Engineer,72525,1 +118387,Female,45,High School,9,56,6,54,45,9.0,6,21,Urban,Data Analyst,60059,0 +118388,Male,36,Masters,3,1,72,65,18,6.0,5,84,Urban,Manager,23922,0 +118389,Male,45,Bachelors,18,78,32,14,64,0.0,7,60,Urban,HR Executive,138017,0 +118390,Male,58,High School,10,23,7,52,49,1.0,6,5,Urban,Software Engineer,96351,0 +118391,Female,42,Bachelors,13,4,84,23,73,9.0,1,38,Urban,HR Executive,54261,0 +118392,Female,29,Bachelors,19,83,65,9,76,1.0,2,9,Semi-Urban,HR Executive,51893,0 +118393,Male,29,Bachelors,1,75,6,98,45,4.0,1,85,Urban,Manager,24178,1 +118394,Male,42,Bachelors,8,99,49,45,56,8.0,3,87,Urban,Data Analyst,149982,1 +118395,Male,32,PhD,6,12,64,30,63,7.0,5,50,Semi-Urban,ML Engineer,102140,0 +118396,Male,28,Bachelors,1,82,28,93,9,5.0,6,77,Urban,ML Engineer,111521,1 +118397,Male,40,Diploma,0,63,46,35,67,5.0,2,85,Urban,ML Engineer,118072,0 +118398,Female,56,High School,17,67,31,31,23,1.0,0,16,Urban,ML Engineer,20594,0 +118399,Male,32,Bachelors,12,56,50,57,24,7.0,2,52,Semi-Urban,Data Analyst,124542,0 +118400,Female,39,Bachelors,8,15,37,30,32,7.0,6,68,Rural,Software Engineer,103981,0 +118401,Male,22,Diploma,16,72,74,45,44,0.0,0,31,Semi-Urban,Data Analyst,51571,0 +118402,Male,39,Bachelors,10,73,20,2,34,9.0,6,55,Semi-Urban,Data Analyst,24795,0 +118403,Female,33,Bachelors,17,94,38,40,22,2.0,4,62,Urban,Software Engineer,99698,0 +118404,Male,29,Bachelors,9,15,41,70,48,0.0,6,81,Rural,Manager,146623,0 +118405,Female,59,High School,13,41,33,12,47,2.0,0,24,Urban,Software Engineer,126360,0 +118406,Male,24,Diploma,18,86,73,63,6,5.0,6,42,Rural,HR Executive,23591,1 +118407,Male,21,Bachelors,2,22,41,53,18,0.0,4,12,Urban,ML Engineer,59568,0 +118408,Male,53,Bachelors,1,43,87,70,50,3.0,3,22,Urban,ML Engineer,134683,0 +118409,Female,42,Bachelors,5,16,78,58,97,2.0,4,49,Urban,ML Engineer,133327,0 +118410,Male,38,Masters,0,18,96,27,56,3.0,6,96,Rural,HR Executive,114251,1 +118411,Female,40,Bachelors,19,11,88,15,5,5.0,1,82,Urban,Manager,129225,0 +118412,Male,48,Diploma,18,33,75,37,35,0.0,1,37,Urban,HR Executive,113448,0 +118413,Male,27,PhD,1,71,97,10,10,9.0,3,51,Rural,Software Engineer,66748,0 +118414,Male,55,PhD,4,56,7,89,73,1.0,6,1,Semi-Urban,ML Engineer,99440,0 +118415,Male,27,Bachelors,9,11,88,24,65,9.0,3,9,Rural,Data Analyst,41147,0 +118416,Female,36,Diploma,11,26,97,26,79,3.0,0,93,Rural,ML Engineer,61561,1 +118417,Female,44,High School,1,85,65,87,96,8.0,6,69,Urban,ML Engineer,86060,1 +118418,Male,43,Masters,16,88,30,16,22,8.0,1,98,Rural,HR Executive,95204,0 +118419,Male,35,Masters,6,97,77,21,72,2.0,7,52,Rural,Manager,44373,1 +118420,Male,43,Bachelors,13,64,19,18,9,3.0,5,87,Semi-Urban,ML Engineer,93477,0 +118421,Male,21,Diploma,0,55,79,18,61,7.0,4,65,Semi-Urban,HR Executive,92364,0 +118422,Male,54,Bachelors,2,80,36,0,49,9.0,6,45,Rural,Data Analyst,93292,0 +118423,Male,40,High School,0,68,12,78,50,1.0,7,22,Urban,Manager,46798,0 +118424,Female,52,Masters,5,1,49,77,49,4.0,3,91,Urban,ML Engineer,142336,0 +118425,Female,30,Masters,19,5,41,69,71,9.0,6,21,Urban,Software Engineer,28668,0 +118426,Male,48,Bachelors,0,47,29,71,74,4.0,3,30,Urban,ML Engineer,52925,0 +118427,Male,44,Masters,4,80,83,77,75,4.0,0,16,Rural,Manager,58469,1 +118428,Male,25,High School,12,16,84,50,17,1.0,1,13,Urban,Manager,124888,0 +118429,Female,24,Diploma,6,4,35,97,13,8.0,4,35,Urban,ML Engineer,127563,0 +118430,Female,36,Bachelors,1,9,59,59,10,0.0,5,31,Urban,Manager,108577,0 +118431,Male,34,Bachelors,15,79,52,92,81,2.0,3,97,Semi-Urban,Software Engineer,110347,1 +118432,Male,44,Masters,14,93,52,17,32,3.0,1,49,Urban,Data Analyst,30267,0 +118433,Male,38,Bachelors,15,0,46,28,10,1.0,5,66,Urban,Data Analyst,141213,0 +118434,Male,40,Bachelors,2,79,3,76,82,5.0,4,23,Rural,ML Engineer,138658,0 +118435,Male,55,Diploma,10,27,3,87,29,1.0,3,10,Semi-Urban,Data Analyst,46451,0 +118436,Male,51,Diploma,7,62,71,81,27,8.0,0,92,Urban,Data Analyst,133465,1 +118437,Male,44,Masters,9,86,84,72,30,2.0,4,11,Urban,Software Engineer,139081,1 +118438,Female,41,Masters,6,33,16,12,71,1.0,2,84,Urban,Software Engineer,96067,0 +118439,Male,52,PhD,0,70,80,46,18,9.0,4,12,Rural,Software Engineer,143104,0 +118440,Female,39,Masters,14,13,58,95,21,4.0,3,21,Urban,ML Engineer,85952,0 +118441,Other,50,Bachelors,17,20,37,70,46,2.0,2,18,Rural,Software Engineer,62365,0 +118442,Male,36,Bachelors,8,31,65,20,35,0.0,4,10,Urban,Software Engineer,132501,0 +118443,Male,53,High School,2,0,14,38,92,5.0,6,40,Semi-Urban,Manager,81778,0 +118444,Male,36,High School,14,92,28,75,52,4.0,7,6,Rural,ML Engineer,63456,0 +118445,Male,43,High School,10,84,70,28,30,1.0,3,58,Urban,Data Analyst,122697,1 +118446,Male,47,High School,4,25,48,35,86,1.0,2,48,Urban,Manager,117431,0 +118447,Female,31,Bachelors,12,39,57,0,36,5.0,7,46,Semi-Urban,Data Analyst,142239,0 +118448,Male,59,High School,6,56,71,61,54,7.0,5,68,Semi-Urban,Data Analyst,119478,1 +118449,Male,22,Bachelors,2,28,58,15,42,3.0,6,17,Urban,Software Engineer,115355,0 +118450,Male,51,PhD,4,71,72,80,93,7.0,4,34,Semi-Urban,Software Engineer,77179,1 +118451,Male,43,Bachelors,6,54,92,29,43,8.0,6,69,Semi-Urban,Data Analyst,147514,1 +118452,Male,38,Bachelors,12,74,53,17,75,2.0,2,58,Semi-Urban,ML Engineer,93557,0 +118453,Male,37,Bachelors,5,16,99,13,51,3.0,6,10,Urban,Manager,140456,0 +118454,Male,58,Bachelors,14,27,12,49,76,1.0,2,36,Semi-Urban,Software Engineer,101399,0 +118455,Male,33,Masters,10,51,88,72,49,0.0,7,37,Rural,ML Engineer,63693,1 +118456,Male,56,Diploma,9,61,24,12,77,3.0,7,4,Semi-Urban,HR Executive,123612,0 +118457,Male,37,Diploma,12,55,97,2,22,6.0,1,84,Urban,Data Analyst,129634,1 +118458,Male,58,Bachelors,6,46,74,84,22,3.0,3,0,Urban,Manager,48645,0 +118459,Male,35,Masters,12,42,37,0,5,2.0,5,36,Urban,ML Engineer,130614,0 +118460,Female,58,Bachelors,8,67,96,39,87,6.0,3,25,Rural,Manager,109053,0 +118461,Male,53,Bachelors,11,77,16,87,75,1.0,5,50,Urban,Data Analyst,117405,0 +118462,Female,37,Bachelors,7,40,88,59,32,9.0,4,88,Urban,Software Engineer,100595,1 +118463,Female,40,Bachelors,11,92,54,31,19,7.0,4,13,Semi-Urban,Software Engineer,95000,0 +118464,Male,23,Bachelors,8,7,92,48,36,8.0,5,74,Urban,ML Engineer,37772,0 +118465,Female,32,High School,13,45,38,62,46,3.0,4,77,Urban,Software Engineer,97778,0 +118466,Male,25,Masters,4,88,30,44,38,9.0,2,35,Rural,Data Analyst,51197,0 +118467,Male,46,Bachelors,0,76,43,98,18,5.0,1,3,Rural,Software Engineer,119692,0 +118468,Male,58,Bachelors,5,90,32,27,41,7.0,0,1,Urban,Software Engineer,120199,0 +118469,Female,35,Bachelors,18,35,82,98,33,1.0,1,11,Urban,HR Executive,145184,0 +118470,Male,51,Masters,15,89,39,71,99,9.0,0,22,Rural,Data Analyst,113926,0 +118471,Male,27,High School,19,66,7,68,39,5.0,2,35,Urban,Software Engineer,127997,0 +118472,Male,27,High School,0,4,6,78,88,4.0,5,14,Urban,Data Analyst,56124,0 +118473,Female,32,Masters,1,78,9,21,25,8.0,3,88,Urban,HR Executive,143251,0 +118474,Male,36,Masters,8,83,41,27,12,0.0,5,22,Rural,HR Executive,83699,0 +118475,Other,26,Masters,2,73,54,98,24,6.0,1,37,Urban,HR Executive,68120,1 +118476,Male,46,PhD,3,33,21,80,80,0.0,6,81,Semi-Urban,HR Executive,70396,0 +118477,Male,48,Diploma,11,37,96,75,74,8.0,4,57,Urban,Data Analyst,23591,1 +118478,Female,50,High School,17,41,30,58,27,1.0,0,73,Rural,ML Engineer,118400,0 +118479,Male,59,Masters,10,77,72,32,64,2.0,7,98,Semi-Urban,Manager,49202,1 +118480,Male,39,Bachelors,17,17,21,4,93,2.0,7,18,Urban,HR Executive,82153,0 +118481,Male,47,High School,6,74,83,79,14,7.0,3,1,Semi-Urban,Manager,93147,1 +118482,Female,34,Masters,18,10,17,80,5,1.0,6,53,Urban,HR Executive,98196,0 +118483,Female,53,Bachelors,10,34,46,52,57,0.0,7,70,Urban,Manager,131666,0 +118484,Female,42,Bachelors,6,31,62,93,5,6.0,7,75,Semi-Urban,Data Analyst,94249,1 +118485,Male,52,Masters,12,3,29,28,95,8.0,3,5,Semi-Urban,Software Engineer,89554,0 +118486,Male,57,Diploma,15,60,53,39,76,0.0,2,4,Semi-Urban,Manager,96818,0 +118487,Female,43,Masters,7,81,45,86,52,3.0,0,81,Urban,Manager,73365,1 +118488,Male,51,Diploma,9,13,57,47,13,2.0,3,4,Semi-Urban,Software Engineer,21586,0 +118489,Male,42,Diploma,11,65,30,97,23,5.0,7,24,Urban,Manager,93213,0 +118490,Female,31,High School,10,70,78,85,63,6.0,7,3,Semi-Urban,HR Executive,148999,0 +118491,Female,48,Masters,15,88,65,30,89,2.0,0,63,Urban,ML Engineer,148251,1 +118492,Female,29,High School,8,85,3,36,95,4.0,0,59,Rural,Data Analyst,135552,0 +118493,Female,55,Bachelors,15,27,65,36,43,3.0,6,27,Rural,Software Engineer,67370,0 +118494,Male,44,High School,0,22,48,64,13,7.0,0,14,Rural,Software Engineer,41236,0 +118495,Male,47,Bachelors,3,99,93,46,10,2.0,6,39,Semi-Urban,Manager,83190,1 +118496,Male,54,Diploma,10,52,25,7,76,8.0,4,53,Semi-Urban,Software Engineer,127323,0 +118497,Male,43,High School,9,77,0,49,31,0.0,2,30,Semi-Urban,Software Engineer,149322,0 +118498,Female,41,Diploma,3,65,60,45,56,9.0,7,61,Semi-Urban,HR Executive,125908,0 +118499,Female,26,Bachelors,12,47,3,1,98,9.0,6,80,Urban,ML Engineer,99498,0 +118500,Male,41,Diploma,16,67,52,44,16,2.0,5,85,Urban,Software Engineer,104520,1 +118501,Female,31,Diploma,19,3,57,88,83,9.0,0,19,Urban,HR Executive,121721,0 +118502,Female,48,Bachelors,13,74,40,56,80,7.0,4,50,Urban,ML Engineer,138941,0 +118503,Male,24,Bachelors,18,15,53,30,16,9.0,6,20,Urban,Data Analyst,32209,0 +118504,Male,43,Bachelors,13,78,99,37,16,8.0,4,80,Semi-Urban,ML Engineer,91876,1 +118505,Male,33,Masters,4,15,34,70,90,0.0,5,67,Urban,Software Engineer,89629,0 +118506,Male,46,Masters,5,52,99,91,30,1.0,5,13,Urban,HR Executive,125929,1 +118507,Female,54,Masters,6,31,83,82,50,3.0,0,27,Urban,ML Engineer,47574,0 +118508,Female,43,Masters,9,0,60,46,41,6.0,4,3,Urban,ML Engineer,128882,0 +118509,Male,53,Bachelors,1,32,58,6,97,8.0,1,64,Urban,Software Engineer,81786,0 +118510,Male,24,High School,19,80,32,18,96,8.0,0,98,Urban,ML Engineer,69066,0 +118511,Male,52,PhD,19,77,36,32,48,7.0,2,4,Urban,ML Engineer,145102,0 +118512,Female,41,Diploma,8,67,44,32,68,1.0,7,60,Urban,Software Engineer,62240,0 +118513,Female,22,Bachelors,4,9,67,74,64,2.0,7,79,Semi-Urban,Manager,41618,0 +118514,Male,33,High School,1,70,24,14,77,3.0,5,18,Urban,ML Engineer,139105,0 +118515,Female,40,High School,8,86,17,49,27,8.0,1,44,Urban,Software Engineer,98321,0 +118516,Male,44,Bachelors,4,52,87,16,22,5.0,1,46,Semi-Urban,Software Engineer,132313,0 +118517,Male,37,Diploma,19,4,20,34,57,1.0,1,84,Urban,ML Engineer,140117,0 +118518,Male,59,High School,18,77,14,66,48,4.0,6,60,Urban,Data Analyst,33685,0 +118519,Male,40,Masters,8,71,10,57,75,3.0,1,79,Rural,HR Executive,133590,0 +118520,Female,24,Masters,4,96,19,10,15,7.0,6,21,Rural,HR Executive,59887,0 +118521,Female,43,Diploma,18,2,71,87,90,8.0,6,55,Urban,Software Engineer,29851,0 +118522,Male,36,Bachelors,1,56,75,11,97,6.0,0,65,Urban,Data Analyst,42408,0 +118523,Female,51,Bachelors,8,87,51,11,42,7.0,2,17,Rural,HR Executive,33621,0 +118524,Male,48,Diploma,18,96,51,11,54,3.0,3,51,Urban,HR Executive,48071,0 +118525,Female,26,High School,17,55,45,23,30,8.0,4,35,Urban,Software Engineer,76262,0 +118526,Male,45,Bachelors,2,90,14,15,50,4.0,2,29,Rural,Data Analyst,51202,0 +118527,Female,39,Masters,14,78,85,13,29,7.0,5,92,Semi-Urban,HR Executive,95978,1 +118528,Male,42,Bachelors,16,21,46,13,11,1.0,6,73,Urban,Manager,133598,0 +118529,Male,46,Masters,7,75,82,60,99,1.0,5,46,Rural,HR Executive,74470,1 +118530,Male,59,Bachelors,1,86,6,76,93,9.0,0,27,Urban,Manager,81011,0 +118531,Male,46,Masters,0,86,12,25,3,6.0,6,38,Semi-Urban,Data Analyst,147833,0 +118532,Male,24,Bachelors,2,45,22,63,4,4.0,7,66,Urban,HR Executive,55142,0 +118533,Female,21,Bachelors,7,15,25,84,49,5.0,7,89,Urban,ML Engineer,75944,0 +118534,Female,53,Diploma,19,22,89,49,86,5.0,0,45,Semi-Urban,HR Executive,71435,0 +118535,Male,59,Bachelors,4,8,31,46,57,0.0,1,44,Semi-Urban,Manager,102489,0 +118536,Male,44,High School,17,89,56,5,57,0.0,7,71,Urban,HR Executive,62791,0 +118537,Male,49,Masters,4,7,93,12,85,6.0,3,78,Urban,Software Engineer,83856,0 +118538,Male,53,PhD,3,98,47,55,52,8.0,0,31,Semi-Urban,Software Engineer,69967,0 +118539,Male,52,Bachelors,0,99,46,76,54,1.0,4,31,Rural,Software Engineer,49501,1 +118540,Female,37,Masters,19,45,68,29,58,2.0,3,76,Urban,Data Analyst,116510,0 +118541,Female,22,Diploma,11,28,16,82,51,6.0,6,88,Semi-Urban,Data Analyst,31917,0 +118542,Male,52,Masters,7,70,72,19,63,3.0,6,46,Rural,Data Analyst,21921,0 +118543,Male,48,Masters,14,18,27,38,14,5.0,2,3,Rural,ML Engineer,146317,0 +118544,Male,33,Diploma,18,0,69,62,75,5.0,6,21,Urban,ML Engineer,79196,0 +118545,Male,54,Bachelors,13,40,11,74,6,4.0,4,31,Semi-Urban,ML Engineer,85984,0 +118546,Other,35,Bachelors,6,6,55,31,8,8.0,2,34,Urban,HR Executive,75205,0 +118547,Male,44,Bachelors,3,14,34,4,47,4.0,0,16,Urban,ML Engineer,79431,0 +118548,Male,25,Bachelors,7,5,9,93,1,1.0,6,94,Urban,Manager,109274,0 +118549,Female,55,Bachelors,4,93,47,25,91,3.0,5,88,Urban,Manager,148757,1 +118550,Male,43,Bachelors,7,66,50,51,7,6.0,6,63,Urban,Manager,102118,0 +118551,Female,56,Masters,15,80,54,59,75,0.0,7,55,Urban,ML Engineer,146157,1 +118552,Male,21,Diploma,8,39,40,23,94,4.0,6,41,Urban,ML Engineer,129640,0 +118553,Female,21,Bachelors,17,26,36,38,72,0.0,3,2,Urban,Software Engineer,87049,0 +118554,Female,45,High School,11,97,77,76,45,9.0,0,24,Semi-Urban,ML Engineer,130654,1 +118555,Male,59,Bachelors,6,43,48,85,67,6.0,7,27,Urban,Data Analyst,128554,0 +118556,Female,38,PhD,19,79,54,76,18,0.0,5,32,Semi-Urban,ML Engineer,40621,1 +118557,Male,53,Bachelors,14,36,14,66,29,3.0,6,91,Urban,ML Engineer,62344,0 +118558,Male,28,Bachelors,0,44,60,96,2,6.0,1,8,Urban,Manager,126325,0 +118559,Male,54,Diploma,2,60,89,53,70,4.0,4,58,Urban,Software Engineer,146206,1 +118560,Female,48,Diploma,15,86,44,54,55,8.0,5,33,Semi-Urban,Manager,148330,0 +118561,Male,44,Diploma,8,27,46,3,42,5.0,4,44,Urban,Manager,103074,0 +118562,Male,50,Diploma,6,20,93,85,22,5.0,1,72,Urban,Data Analyst,140671,1 +118563,Male,42,Bachelors,13,27,72,61,50,8.0,1,49,Semi-Urban,Data Analyst,85368,0 +118564,Male,52,Bachelors,11,4,71,75,17,8.0,2,66,Urban,ML Engineer,49825,0 +118565,Male,21,PhD,16,52,22,26,96,2.0,5,53,Urban,Manager,29738,0 +118566,Male,27,Masters,18,8,63,12,35,6.0,6,73,Semi-Urban,Data Analyst,31476,0 +118567,Male,23,Diploma,2,87,38,27,12,8.0,3,1,Semi-Urban,Data Analyst,42128,0 +118568,Male,52,Diploma,7,83,55,44,71,5.0,5,39,Rural,Manager,21725,0 +118569,Male,28,Diploma,12,17,21,90,84,0.0,4,39,Semi-Urban,Software Engineer,55318,0 +118570,Male,44,Bachelors,5,60,13,92,63,8.0,3,62,Urban,HR Executive,135307,0 +118571,Male,47,Diploma,8,29,62,52,18,1.0,0,15,Urban,Software Engineer,51085,0 +118572,Male,31,Bachelors,4,82,33,13,31,7.0,6,74,Semi-Urban,ML Engineer,23546,0 +118573,Male,47,High School,18,62,58,83,7,2.0,5,92,Urban,ML Engineer,28381,1 +118574,Female,46,PhD,18,66,58,41,89,7.0,7,21,Urban,ML Engineer,35289,0 +118575,Female,30,Bachelors,17,49,92,15,74,8.0,2,81,Urban,ML Engineer,75678,0 +118576,Female,39,Masters,15,66,60,24,99,5.0,4,46,Urban,Software Engineer,85191,0 +118577,Female,53,PhD,11,69,10,84,51,6.0,4,82,Urban,Manager,74640,1 +118578,Male,41,Masters,19,57,78,31,77,7.0,1,38,Urban,Manager,143286,0 +118579,Male,49,Bachelors,18,41,32,49,16,6.0,3,49,Urban,Manager,108007,0 +118580,Male,28,PhD,14,40,48,49,54,0.0,6,59,Rural,ML Engineer,86481,0 +118581,Male,37,PhD,7,70,91,92,50,0.0,6,76,Urban,Data Analyst,71113,1 +118582,Male,58,High School,11,5,75,82,26,5.0,6,38,Urban,Data Analyst,25208,0 +118583,Male,30,Diploma,15,28,58,25,22,2.0,7,87,Urban,HR Executive,58706,0 +118584,Male,22,Bachelors,9,54,25,2,81,3.0,1,35,Urban,HR Executive,64409,0 +118585,Female,33,Masters,5,31,51,25,67,3.0,0,98,Rural,ML Engineer,137971,0 +118586,Male,49,Bachelors,4,79,80,90,37,0.0,1,76,Rural,ML Engineer,67078,1 +118587,Female,48,Bachelors,5,68,3,96,92,5.0,7,59,Urban,ML Engineer,110961,0 +118588,Male,48,Bachelors,15,52,16,83,18,3.0,3,41,Rural,Software Engineer,76958,0 +118589,Male,50,Bachelors,6,64,18,16,52,7.0,0,30,Urban,Software Engineer,22773,0 +118590,Female,52,Bachelors,16,36,20,41,3,2.0,2,64,Urban,Software Engineer,116595,0 +118591,Male,24,Bachelors,17,11,3,33,97,1.0,6,13,Rural,Software Engineer,122210,0 +118592,Male,46,Bachelors,1,91,23,24,14,6.0,2,30,Rural,ML Engineer,63796,0 +118593,Male,53,High School,14,34,25,29,45,7.0,5,31,Urban,Data Analyst,126998,0 +118594,Male,28,Diploma,7,43,55,90,64,2.0,1,39,Urban,ML Engineer,80367,0 +118595,Female,52,Masters,13,23,3,1,56,4.0,6,63,Urban,HR Executive,104561,0 +118596,Female,32,Bachelors,16,73,71,58,46,7.0,2,53,Urban,HR Executive,109272,1 +118597,Female,45,Bachelors,3,33,69,75,21,0.0,1,43,Urban,Data Analyst,123259,0 +118598,Female,32,High School,10,87,42,70,8,9.0,5,15,Urban,Software Engineer,35477,0 +118599,Male,35,Bachelors,14,67,35,79,49,1.0,7,2,Semi-Urban,ML Engineer,116460,0 +118600,Male,33,High School,13,81,82,72,15,5.0,1,51,Semi-Urban,Manager,136047,1 +118601,Female,45,Masters,0,98,44,96,1,9.0,4,96,Urban,ML Engineer,91469,1 +118602,Other,33,High School,12,82,20,89,73,3.0,6,26,Semi-Urban,Data Analyst,131260,0 +118603,Female,40,Bachelors,6,76,84,76,20,0.0,7,9,Urban,ML Engineer,134317,1 +118604,Male,41,Diploma,13,14,88,65,36,1.0,4,10,Rural,Software Engineer,91173,0 +118605,Female,27,Bachelors,14,23,62,49,84,6.0,2,78,Rural,ML Engineer,51763,0 +118606,Male,51,Bachelors,15,72,82,74,0,3.0,1,73,Urban,HR Executive,33745,1 +118607,Female,28,Diploma,11,93,17,95,90,4.0,5,76,Urban,Software Engineer,109925,1 +118608,Male,40,Diploma,14,76,11,29,18,7.0,4,4,Urban,Data Analyst,47997,0 +118609,Female,50,Bachelors,18,31,78,72,58,8.0,7,2,Urban,Manager,67850,0 +118610,Other,48,Masters,13,55,9,90,22,5.0,6,28,Urban,Software Engineer,61685,0 +118611,Male,41,Diploma,3,28,37,73,56,3.0,5,92,Semi-Urban,Software Engineer,46600,0 +118612,Male,26,Bachelors,6,16,85,62,78,8.0,6,92,Urban,Manager,83277,1 +118613,Female,53,Bachelors,5,32,45,10,78,1.0,3,65,Urban,Software Engineer,141213,0 +118614,Female,41,Bachelors,1,31,75,47,27,1.0,5,13,Semi-Urban,Data Analyst,31322,0 +118615,Female,50,PhD,17,0,86,4,48,8.0,5,18,Urban,ML Engineer,51168,0 +118616,Male,36,Diploma,14,73,8,55,33,8.0,7,24,Urban,Data Analyst,75239,0 +118617,Female,41,Diploma,17,9,76,94,13,3.0,1,52,Urban,Data Analyst,147697,0 +118618,Male,21,High School,2,28,91,40,61,8.0,3,96,Rural,Software Engineer,79889,1 +118619,Male,25,High School,1,25,2,70,85,1.0,0,70,Urban,ML Engineer,128063,0 +118620,Male,55,Diploma,0,38,16,64,71,5.0,1,13,Urban,HR Executive,59111,0 +118621,Male,34,PhD,19,6,91,13,73,6.0,7,76,Urban,Data Analyst,105932,0 +118622,Female,27,Bachelors,10,13,88,63,39,4.0,4,39,Urban,Manager,38901,0 +118623,Male,44,Bachelors,7,20,3,41,29,1.0,4,57,Urban,ML Engineer,83603,0 +118624,Female,28,Diploma,8,32,95,94,29,5.0,6,64,Semi-Urban,Manager,149560,1 +118625,Male,44,High School,13,16,6,25,87,1.0,2,47,Semi-Urban,Data Analyst,49146,0 +118626,Female,29,Bachelors,2,28,78,62,64,2.0,5,51,Rural,ML Engineer,86465,0 +118627,Female,56,Bachelors,8,66,87,68,44,7.0,3,76,Semi-Urban,Software Engineer,35497,1 +118628,Male,53,Masters,3,9,54,59,78,4.0,2,47,Urban,Data Analyst,40429,0 +118629,Male,35,Masters,4,54,39,94,46,0.0,7,9,Urban,HR Executive,96865,0 +118630,Female,36,Diploma,3,46,49,41,66,7.0,0,85,Semi-Urban,Software Engineer,86746,0 +118631,Female,43,Masters,14,15,24,17,82,0.0,0,18,Urban,Software Engineer,55762,0 +118632,Female,22,Masters,4,24,55,3,90,1.0,4,80,Rural,Manager,132445,0 +118633,Female,49,Masters,15,62,55,49,29,3.0,6,19,Urban,ML Engineer,61680,0 +118634,Female,38,High School,6,73,36,43,37,1.0,4,38,Semi-Urban,Data Analyst,71782,0 +118635,Male,57,Masters,1,60,12,21,19,5.0,0,86,Semi-Urban,HR Executive,124069,0 +118636,Female,49,Diploma,1,59,56,51,58,7.0,2,95,Semi-Urban,HR Executive,47816,1 +118637,Female,59,Bachelors,0,92,42,18,93,8.0,7,95,Urban,Software Engineer,139735,1 +118638,Male,56,Diploma,0,77,58,22,97,6.0,3,19,Semi-Urban,Software Engineer,55625,0 +118639,Male,59,PhD,16,51,54,98,75,3.0,4,66,Semi-Urban,HR Executive,63912,1 +118640,Female,37,Bachelors,19,67,30,5,82,8.0,1,61,Urban,ML Engineer,103787,0 +118641,Female,21,Bachelors,3,66,30,34,25,1.0,0,13,Rural,Software Engineer,49654,0 +118642,Other,49,Bachelors,3,82,48,71,47,7.0,2,3,Semi-Urban,Manager,77903,0 +118643,Male,55,Diploma,0,47,68,25,60,3.0,1,69,Urban,Software Engineer,35285,0 +118644,Female,59,Diploma,0,0,54,8,21,8.0,2,87,Urban,HR Executive,104642,0 +118645,Female,27,High School,12,43,2,81,8,5.0,2,51,Urban,ML Engineer,112646,0 +118646,Female,21,Bachelors,12,93,23,97,23,1.0,5,39,Semi-Urban,Software Engineer,80360,1 +118647,Male,25,Masters,8,59,76,47,43,0.0,2,78,Urban,Data Analyst,32654,1 +118648,Female,25,High School,19,81,49,68,6,8.0,0,68,Rural,Software Engineer,119059,1 +118649,Other,27,Diploma,19,11,61,82,3,1.0,5,64,Urban,Software Engineer,64518,0 +118650,Female,26,Bachelors,1,4,47,70,29,9.0,2,59,Urban,HR Executive,56526,0 +118651,Female,51,Masters,18,18,48,57,71,1.0,3,46,Urban,Manager,112589,0 +118652,Male,42,Masters,7,70,28,76,85,4.0,7,29,Urban,Software Engineer,128783,0 +118653,Female,39,Masters,10,47,35,30,58,6.0,2,32,Urban,HR Executive,112413,0 +118654,Male,29,Bachelors,10,93,35,87,66,5.0,0,98,Rural,Manager,97466,1 +118655,Female,31,Diploma,19,89,57,12,33,3.0,4,8,Semi-Urban,Data Analyst,39365,0 +118656,Male,41,Bachelors,8,89,99,63,75,7.0,6,8,Rural,Data Analyst,49890,1 +118657,Male,23,Bachelors,0,68,47,17,49,9.0,2,29,Semi-Urban,HR Executive,40042,0 +118658,Male,45,Bachelors,17,21,19,90,20,6.0,5,13,Urban,HR Executive,128507,0 +118659,Male,47,High School,3,35,26,86,72,0.0,0,33,Urban,Manager,130772,0 +118660,Male,46,Bachelors,6,42,48,23,9,9.0,0,62,Urban,Software Engineer,102021,0 +118661,Male,22,PhD,3,27,34,1,70,5.0,2,53,Urban,Manager,42172,0 +118662,Male,59,Diploma,18,52,19,71,43,6.0,1,75,Rural,Manager,23422,0 +118663,Male,29,High School,0,67,38,81,82,8.0,4,24,Semi-Urban,Data Analyst,46369,0 +118664,Male,48,Bachelors,7,28,8,95,12,7.0,4,94,Urban,Manager,83013,0 +118665,Male,43,Bachelors,3,84,93,75,36,7.0,7,36,Urban,HR Executive,77002,1 +118666,Male,58,Diploma,2,65,62,0,99,8.0,6,37,Semi-Urban,HR Executive,49462,0 +118667,Female,28,Bachelors,16,49,23,19,49,4.0,6,80,Semi-Urban,Software Engineer,52806,0 +118668,Male,44,Bachelors,3,34,5,73,28,3.0,5,67,Urban,Manager,117955,0 +118669,Male,30,Bachelors,17,82,50,5,70,0.0,5,2,Urban,Software Engineer,23675,0 +118670,Male,49,Bachelors,19,5,79,11,88,1.0,7,19,Urban,HR Executive,79972,0 +118671,Male,29,Bachelors,4,15,76,56,56,9.0,7,70,Semi-Urban,ML Engineer,62231,0 +118672,Female,46,PhD,1,29,12,44,97,6.0,7,91,Semi-Urban,HR Executive,57876,0 +118673,Male,49,Diploma,8,80,91,72,61,3.0,1,91,Urban,HR Executive,42650,1 +118674,Male,48,Bachelors,13,71,35,54,20,4.0,7,20,Semi-Urban,Data Analyst,57735,0 +118675,Male,41,Diploma,2,43,62,33,22,3.0,5,13,Rural,ML Engineer,58066,0 +118676,Female,52,Bachelors,3,69,67,63,59,9.0,5,65,Urban,Software Engineer,39545,1 +118677,Male,47,Bachelors,16,74,27,75,12,8.0,4,6,Semi-Urban,Data Analyst,55243,0 +118678,Female,42,Bachelors,9,29,49,4,97,6.0,4,78,Urban,Data Analyst,55671,0 +118679,Male,53,Diploma,5,20,13,13,52,0.0,4,81,Urban,Software Engineer,69395,0 +118680,Female,29,High School,18,82,14,50,62,0.0,5,98,Semi-Urban,Manager,74872,1 +118681,Male,32,Bachelors,9,2,96,65,63,7.0,4,47,Semi-Urban,Manager,140299,0 +118682,Male,30,Masters,13,82,68,67,84,9.0,7,89,Urban,Manager,68645,1 +118683,Female,53,Diploma,6,31,43,39,38,2.0,4,48,Urban,Manager,26570,0 +118684,Male,53,High School,18,13,58,28,89,7.0,6,95,Rural,Data Analyst,65652,0 +118685,Male,55,Diploma,4,13,74,55,23,2.0,5,87,Urban,Data Analyst,105752,0 +118686,Male,42,Masters,0,54,47,17,67,2.0,2,71,Urban,Software Engineer,52065,0 +118687,Female,49,Bachelors,15,38,64,31,21,3.0,1,22,Semi-Urban,ML Engineer,82613,0 +118688,Female,41,High School,9,8,0,86,87,7.0,4,9,Urban,Manager,59200,0 +118689,Female,40,Diploma,14,2,43,98,80,4.0,3,23,Rural,Data Analyst,137992,0 +118690,Female,42,High School,8,56,29,52,70,7.0,2,66,Urban,ML Engineer,20541,0 +118691,Male,24,Bachelors,15,40,41,5,4,3.0,1,57,Urban,HR Executive,20943,0 +118692,Male,31,Bachelors,4,97,80,12,12,6.0,7,49,Urban,HR Executive,28680,1 +118693,Male,50,Bachelors,0,74,4,99,46,0.0,4,93,Urban,ML Engineer,122407,1 +118694,Male,51,Masters,9,42,60,87,66,2.0,6,89,Semi-Urban,HR Executive,55294,1 +118695,Male,21,High School,19,30,29,55,72,2.0,4,27,Urban,Data Analyst,85988,0 +118696,Male,44,Bachelors,5,30,66,58,72,1.0,0,77,Semi-Urban,ML Engineer,37624,0 +118697,Male,57,Masters,10,76,17,23,89,8.0,3,12,Rural,ML Engineer,70213,0 +118698,Male,35,Bachelors,17,50,61,10,66,2.0,1,92,Rural,Software Engineer,105086,0 +118699,Female,42,Masters,2,54,3,27,50,8.0,0,33,Urban,Software Engineer,103914,0 +118700,Female,35,Diploma,1,86,27,13,15,1.0,5,6,Urban,ML Engineer,120957,0 +118701,Female,49,PhD,19,17,20,73,23,9.0,2,44,Semi-Urban,Software Engineer,117049,0 +118702,Male,34,Bachelors,15,82,34,58,82,4.0,1,12,Rural,ML Engineer,144828,0 +118703,Female,30,Bachelors,16,60,18,11,90,7.0,6,31,Urban,ML Engineer,89521,0 +118704,Male,38,Bachelors,14,46,34,82,55,9.0,3,12,Rural,Data Analyst,38071,0 +118705,Female,59,Diploma,7,49,56,63,63,5.0,4,36,Urban,Data Analyst,103635,0 +118706,Female,29,Bachelors,6,7,22,6,44,6.0,3,95,Semi-Urban,HR Executive,143666,0 +118707,Male,26,Masters,8,31,57,46,25,8.0,7,65,Urban,Manager,82142,0 +118708,Male,57,Bachelors,19,14,99,59,43,3.0,3,74,Semi-Urban,ML Engineer,87817,1 +118709,Male,58,Diploma,15,78,83,49,77,5.0,2,28,Urban,HR Executive,76726,1 +118710,Male,36,Diploma,15,64,90,25,51,6.0,0,18,Urban,Manager,84154,0 +118711,Male,58,Bachelors,18,11,71,46,68,6.0,4,34,Urban,ML Engineer,135717,0 +118712,Male,40,Diploma,3,12,39,27,69,6.0,4,27,Semi-Urban,ML Engineer,64057,0 +118713,Female,59,Diploma,11,78,28,88,43,9.0,4,43,Semi-Urban,Data Analyst,34992,0 +118714,Female,27,Masters,9,3,79,26,48,8.0,5,74,Rural,Data Analyst,46882,0 +118715,Male,48,Diploma,9,67,63,19,50,0.0,5,98,Urban,HR Executive,82952,1 +118716,Male,21,High School,14,76,61,92,76,0.0,1,16,Urban,Manager,40105,1 +118717,Male,26,High School,13,23,98,20,16,9.0,5,21,Urban,ML Engineer,49642,0 +118718,Female,29,Bachelors,9,38,30,72,55,4.0,1,40,Urban,ML Engineer,128646,0 +118719,Female,42,Bachelors,6,13,11,87,92,7.0,5,42,Urban,Manager,79494,0 +118720,Male,54,Bachelors,5,88,6,38,21,2.0,3,99,Semi-Urban,Manager,120855,0 +118721,Male,41,Bachelors,13,95,35,54,6,9.0,3,1,Semi-Urban,ML Engineer,110160,0 +118722,Female,35,Diploma,15,5,71,12,94,7.0,3,27,Rural,ML Engineer,87156,0 +118723,Male,29,Bachelors,2,71,4,32,96,4.0,3,87,Urban,Manager,74379,0 +118724,Male,50,High School,1,82,82,19,57,9.0,4,91,Semi-Urban,Manager,102687,1 +118725,Male,39,Masters,7,10,6,5,63,3.0,2,96,Urban,Data Analyst,92611,0 +118726,Other,29,Diploma,15,42,11,4,66,6.0,3,4,Rural,Manager,41973,0 +118727,Male,28,High School,0,94,89,67,91,7.0,1,78,Urban,ML Engineer,121844,1 +118728,Male,53,Bachelors,9,88,33,56,37,3.0,1,18,Semi-Urban,Software Engineer,105068,0 +118729,Female,22,Bachelors,19,7,13,78,74,4.0,4,49,Urban,HR Executive,69838,0 +118730,Female,30,Diploma,4,19,49,71,17,9.0,2,94,Urban,ML Engineer,46932,0 +118731,Female,27,High School,12,35,36,36,60,7.0,7,18,Urban,HR Executive,37389,0 +118732,Male,31,Diploma,18,23,95,13,59,0.0,1,12,Rural,ML Engineer,82306,0 +118733,Female,29,Diploma,9,77,27,14,68,2.0,5,80,Semi-Urban,HR Executive,107135,0 +118734,Male,47,Bachelors,13,41,63,11,56,3.0,7,46,Semi-Urban,ML Engineer,61141,0 +118735,Male,35,Bachelors,19,65,57,22,80,8.0,2,96,Urban,Manager,29458,1 +118736,Female,40,Diploma,6,2,51,11,67,2.0,6,39,Rural,Software Engineer,29741,0 +118737,Female,28,Bachelors,9,83,15,3,59,1.0,4,20,Urban,ML Engineer,33847,0 +118738,Male,34,Masters,13,31,56,66,8,6.0,0,97,Urban,Manager,133191,1 +118739,Male,43,Bachelors,5,86,18,1,40,0.0,6,71,Urban,Manager,63766,0 +118740,Female,55,Diploma,6,8,1,99,18,1.0,0,41,Urban,HR Executive,61972,0 +118741,Female,26,Bachelors,5,27,45,93,62,6.0,6,1,Rural,Manager,141085,0 +118742,Other,35,Bachelors,9,32,50,19,46,3.0,3,8,Rural,Manager,90436,0 +118743,Male,49,Diploma,11,78,37,42,0,7.0,2,6,Rural,Data Analyst,120650,0 +118744,Female,41,Bachelors,2,71,3,50,12,4.0,0,75,Urban,Data Analyst,33684,0 +118745,Male,28,Bachelors,6,18,5,2,93,9.0,6,88,Urban,Manager,53095,0 +118746,Female,38,Bachelors,15,88,99,88,73,2.0,1,71,Urban,HR Executive,20366,1 +118747,Male,43,High School,12,24,89,65,61,3.0,3,26,Urban,Data Analyst,120073,0 +118748,Male,55,High School,13,21,59,30,73,0.0,2,82,Urban,Manager,100665,0 +118749,Male,45,Masters,8,21,93,28,67,3.0,1,38,Rural,HR Executive,139756,0 +118750,Female,50,Bachelors,7,25,25,49,62,9.0,7,41,Rural,Software Engineer,139122,0 +118751,Male,43,Diploma,11,64,86,81,35,6.0,2,76,Rural,Software Engineer,92857,1 +118752,Female,57,Bachelors,14,31,17,91,16,2.0,4,32,Semi-Urban,Software Engineer,97728,0 +118753,Female,30,High School,12,7,4,53,67,3.0,1,24,Semi-Urban,Manager,50648,0 +118754,Male,43,Masters,8,92,29,19,29,5.0,0,29,Urban,Manager,89815,0 +118755,Male,34,Diploma,9,86,34,8,85,3.0,3,74,Semi-Urban,Manager,76504,0 +118756,Male,34,Bachelors,6,40,23,46,24,0.0,1,60,Semi-Urban,Manager,114701,0 +118757,Male,49,Bachelors,1,26,79,53,68,8.0,5,73,Semi-Urban,Software Engineer,30656,0 +118758,Male,37,Diploma,8,28,62,64,40,2.0,6,51,Urban,Data Analyst,22955,0 +118759,Male,29,Diploma,17,94,92,18,25,9.0,0,84,Urban,Software Engineer,57605,1 +118760,Male,52,Masters,15,66,92,24,88,3.0,1,75,Urban,ML Engineer,128860,1 +118761,Male,44,Bachelors,18,33,32,31,9,4.0,1,3,Semi-Urban,ML Engineer,66226,0 +118762,Male,25,Bachelors,11,15,31,55,16,5.0,4,57,Semi-Urban,Manager,139130,0 +118763,Male,38,Diploma,3,21,50,8,81,7.0,6,21,Rural,Manager,73350,0 +118764,Female,21,High School,0,61,54,78,66,1.0,6,71,Urban,Software Engineer,143574,1 +118765,Other,25,Masters,18,22,41,54,49,3.0,7,46,Urban,Manager,42967,0 +118766,Male,39,Diploma,14,38,70,76,53,8.0,5,76,Semi-Urban,Manager,74153,1 +118767,Female,41,High School,1,17,13,87,4,2.0,0,97,Urban,HR Executive,93749,0 +118768,Male,25,Bachelors,15,27,36,73,73,6.0,0,15,Urban,ML Engineer,92981,0 +118769,Female,53,Diploma,13,93,89,73,33,3.0,6,57,Rural,Data Analyst,69812,1 +118770,Male,37,Bachelors,2,1,77,73,20,0.0,6,10,Urban,HR Executive,57189,0 +118771,Male,34,Bachelors,15,53,9,56,4,5.0,7,12,Semi-Urban,ML Engineer,65861,0 +118772,Male,47,Diploma,15,87,81,23,89,9.0,1,20,Rural,Manager,118330,0 +118773,Other,35,Diploma,15,21,67,30,32,2.0,0,55,Urban,ML Engineer,26461,0 +118774,Male,31,Diploma,9,77,37,94,61,4.0,6,88,Rural,Software Engineer,28329,1 +118775,Male,46,High School,17,72,70,65,36,2.0,4,22,Urban,Software Engineer,53075,0 +118776,Female,46,Bachelors,11,41,22,68,53,6.0,6,71,Urban,Data Analyst,27775,0 +118777,Female,42,High School,11,90,87,40,71,1.0,2,82,Semi-Urban,Manager,144284,1 +118778,Female,44,Bachelors,11,44,13,25,40,2.0,1,70,Urban,Software Engineer,28503,0 +118779,Female,28,Bachelors,0,14,60,35,31,5.0,4,63,Urban,HR Executive,40109,0 +118780,Male,52,Bachelors,3,1,30,90,49,7.0,2,65,Semi-Urban,Manager,122693,0 +118781,Male,27,Masters,16,39,26,64,34,0.0,4,15,Rural,ML Engineer,129415,0 +118782,Female,36,Masters,2,39,23,78,74,0.0,0,91,Urban,HR Executive,107072,0 +118783,Male,53,Diploma,4,75,70,29,26,6.0,6,54,Urban,Data Analyst,108682,0 +118784,Male,30,Bachelors,3,84,34,96,30,7.0,5,66,Urban,Data Analyst,77632,1 +118785,Male,52,Masters,14,18,66,70,28,2.0,3,81,Urban,Software Engineer,147937,1 +118786,Male,24,Bachelors,15,91,28,30,72,7.0,1,56,Semi-Urban,ML Engineer,117850,0 +118787,Female,42,Masters,7,57,27,46,87,5.0,1,16,Urban,Data Analyst,98468,0 +118788,Female,35,Bachelors,17,28,38,99,1,3.0,4,71,Semi-Urban,Manager,106106,0 +118789,Male,25,High School,8,85,55,69,10,6.0,4,56,Rural,ML Engineer,116947,1 +118790,Male,30,Diploma,15,83,21,7,64,8.0,7,83,Semi-Urban,Data Analyst,93666,0 +118791,Male,33,Masters,12,69,62,11,76,4.0,7,31,Semi-Urban,HR Executive,122336,0 +118792,Male,41,Diploma,14,15,22,88,72,9.0,3,89,Semi-Urban,ML Engineer,28865,0 +118793,Other,28,Bachelors,16,5,61,41,99,6.0,7,42,Urban,Software Engineer,122434,0 +118794,Male,38,High School,19,76,30,19,99,9.0,5,50,Urban,Software Engineer,31413,0 +118795,Female,24,Diploma,17,50,77,64,19,4.0,2,4,Urban,ML Engineer,142847,0 +118796,Male,49,High School,11,89,28,4,17,6.0,3,43,Urban,ML Engineer,138776,0 +118797,Male,23,Bachelors,19,75,83,15,60,2.0,4,27,Urban,Data Analyst,83792,0 +118798,Male,55,Bachelors,17,16,64,49,46,9.0,2,11,Urban,HR Executive,24569,0 +118799,Female,45,High School,19,1,65,92,45,1.0,1,47,Urban,ML Engineer,37839,0 +118800,Other,46,Bachelors,3,64,65,50,38,7.0,4,67,Rural,ML Engineer,111557,1 +118801,Female,32,Diploma,1,20,28,88,83,9.0,0,2,Urban,Manager,41412,0 +118802,Female,51,High School,15,97,59,69,15,1.0,0,77,Urban,Data Analyst,31603,1 +118803,Male,25,Diploma,3,21,78,46,81,3.0,5,21,Rural,Data Analyst,129118,0 +118804,Female,43,Diploma,13,47,83,28,95,1.0,2,55,Urban,Software Engineer,49875,0 +118805,Female,28,Bachelors,10,72,52,90,46,9.0,2,71,Urban,ML Engineer,132871,1 +118806,Male,52,Bachelors,0,79,6,53,74,6.0,4,31,Rural,HR Executive,141046,0 +118807,Male,27,Diploma,11,4,79,2,67,9.0,2,62,Urban,HR Executive,93527,0 +118808,Male,37,Bachelors,6,6,48,65,80,1.0,6,8,Semi-Urban,Data Analyst,97714,0 +118809,Female,21,Diploma,12,14,41,92,84,1.0,5,48,Rural,HR Executive,117782,0 +118810,Male,31,Diploma,10,61,73,62,87,3.0,0,89,Urban,HR Executive,112969,1 +118811,Female,40,Bachelors,18,67,49,50,8,1.0,0,9,Semi-Urban,Software Engineer,148127,0 +118812,Female,53,Bachelors,12,22,15,43,98,9.0,7,45,Rural,Software Engineer,130678,0 +118813,Male,49,Diploma,6,15,6,2,57,5.0,6,83,Urban,ML Engineer,46656,0 +118814,Male,22,Diploma,16,85,23,29,69,2.0,3,18,Semi-Urban,ML Engineer,73915,0 +118815,Male,45,Bachelors,0,19,76,62,23,8.0,6,80,Urban,ML Engineer,81085,1 +118816,Female,39,Bachelors,16,63,76,61,79,3.0,5,99,Urban,HR Executive,59355,1 +118817,Male,44,Bachelors,11,24,11,38,24,0.0,0,86,Semi-Urban,Data Analyst,33936,0 +118818,Female,29,PhD,5,40,36,68,53,6.0,2,80,Semi-Urban,Manager,26105,0 +118819,Male,43,Diploma,13,98,48,79,90,1.0,0,77,Semi-Urban,Data Analyst,74265,1 +118820,Male,56,Diploma,9,37,72,70,1,1.0,7,58,Urban,Software Engineer,143980,1 +118821,Male,33,High School,2,30,8,89,44,6.0,4,25,Semi-Urban,Manager,110006,0 +118822,Male,25,Bachelors,4,4,55,7,32,1.0,2,46,Urban,HR Executive,53646,0 +118823,Male,36,Masters,12,60,30,76,70,7.0,6,81,Urban,HR Executive,99801,1 +118824,Male,42,Bachelors,9,41,4,70,44,3.0,0,24,Semi-Urban,Data Analyst,146405,0 +118825,Female,45,High School,3,44,5,73,78,6.0,2,8,Semi-Urban,Manager,22687,0 +118826,Male,26,Diploma,18,14,1,83,23,0.0,3,18,Urban,ML Engineer,97288,0 +118827,Male,48,Diploma,4,0,20,10,38,1.0,6,58,Semi-Urban,ML Engineer,84029,0 +118828,Female,28,Bachelors,15,97,98,61,9,0.0,6,76,Urban,HR Executive,35304,1 +118829,Male,33,Diploma,17,29,84,47,39,8.0,5,36,Urban,ML Engineer,41136,0 +118830,Male,24,Masters,17,28,67,26,52,4.0,4,19,Semi-Urban,ML Engineer,140855,0 +118831,Male,39,Diploma,2,28,55,21,29,6.0,6,56,Urban,Data Analyst,51989,0 +118832,Male,52,PhD,8,73,54,12,74,4.0,0,64,Rural,ML Engineer,98452,0 +118833,Female,24,High School,5,70,95,17,14,9.0,4,73,Rural,ML Engineer,32114,1 +118834,Male,33,Masters,18,44,46,25,21,1.0,0,24,Semi-Urban,Manager,67270,0 +118835,Female,52,Masters,4,43,64,9,66,1.0,3,15,Urban,Software Engineer,108845,0 +118836,Female,58,Bachelors,17,96,52,5,23,4.0,1,60,Rural,HR Executive,30520,0 +118837,Male,57,Bachelors,0,54,38,56,75,7.0,0,21,Urban,HR Executive,143710,0 +118838,Male,49,Bachelors,13,70,28,95,27,1.0,3,30,Semi-Urban,ML Engineer,102686,0 +118839,Female,50,Diploma,3,86,82,78,23,6.0,5,53,Urban,HR Executive,43882,1 +118840,Male,32,Bachelors,0,22,59,48,16,7.0,5,28,Urban,Data Analyst,124782,0 +118841,Male,49,Diploma,9,26,13,73,77,7.0,7,20,Urban,HR Executive,91193,0 +118842,Female,57,Diploma,11,66,52,78,36,3.0,1,79,Urban,Manager,84305,1 +118843,Female,49,Masters,8,24,62,56,63,3.0,3,8,Semi-Urban,Manager,119826,0 +118844,Female,23,Diploma,14,88,91,26,6,0.0,2,46,Urban,Manager,76025,1 +118845,Male,27,Masters,1,25,86,40,92,3.0,6,60,Rural,ML Engineer,76401,0 +118846,Other,37,Bachelors,8,5,13,87,85,6.0,5,75,Urban,ML Engineer,43200,0 +118847,Male,21,Bachelors,15,35,44,64,80,9.0,5,45,Urban,Manager,122421,0 +118848,Male,41,Diploma,7,77,89,29,81,7.0,6,20,Urban,Manager,23590,0 +118849,Male,46,Diploma,15,8,64,17,86,5.0,5,77,Urban,HR Executive,114130,0 +118850,Male,48,Bachelors,11,39,44,55,39,3.0,7,42,Semi-Urban,Manager,106136,0 +118851,Male,59,Masters,0,81,81,32,49,6.0,7,7,Urban,HR Executive,112802,0 +118852,Male,52,Masters,2,48,82,93,65,6.0,1,61,Urban,Data Analyst,45037,1 +118853,Male,34,Diploma,18,43,98,16,84,3.0,4,27,Urban,ML Engineer,98732,0 +118854,Male,23,Bachelors,18,48,21,6,94,1.0,7,31,Rural,ML Engineer,55256,0 +118855,Male,56,Bachelors,16,11,63,52,87,3.0,5,45,Urban,Software Engineer,149336,0 +118856,Male,53,High School,16,24,41,62,61,3.0,3,0,Urban,Data Analyst,144122,0 +118857,Female,35,High School,5,9,22,17,49,5.0,7,26,Rural,Data Analyst,114810,0 +118858,Male,23,Masters,7,36,0,59,82,0.0,5,55,Rural,HR Executive,120956,0 +118859,Male,30,High School,2,37,65,65,94,6.0,3,25,Urban,ML Engineer,143699,0 +118860,Male,58,Bachelors,0,8,47,76,66,5.0,2,54,Urban,Data Analyst,46985,0 +118861,Male,48,Diploma,18,10,19,10,26,9.0,0,73,Urban,ML Engineer,87779,0 +118862,Male,58,PhD,3,1,26,28,31,8.0,6,37,Urban,Data Analyst,30868,0 +118863,Female,28,High School,7,45,36,95,53,9.0,7,94,Urban,HR Executive,113241,1 +118864,Male,58,High School,6,51,9,46,76,2.0,3,90,Rural,Data Analyst,54686,0 +118865,Female,56,Masters,8,26,29,13,62,0.0,5,36,Rural,ML Engineer,85707,0 +118866,Female,56,Diploma,15,66,8,66,42,7.0,1,30,Rural,ML Engineer,108842,0 +118867,Male,30,Diploma,19,47,1,10,31,7.0,2,42,Urban,ML Engineer,110284,0 +118868,Male,44,Masters,7,43,7,83,50,7.0,4,37,Semi-Urban,ML Engineer,89920,0 +118869,Male,31,Diploma,15,70,40,10,97,7.0,6,3,Rural,Manager,57392,0 +118870,Male,36,PhD,11,86,58,46,51,5.0,7,14,Urban,Software Engineer,125219,0 +118871,Female,58,Bachelors,6,71,0,74,48,0.0,3,96,Urban,Manager,86292,1 +118872,Male,21,Bachelors,0,13,85,3,64,8.0,1,4,Urban,Data Analyst,112483,0 +118873,Male,44,Masters,0,76,96,69,9,7.0,1,26,Semi-Urban,HR Executive,142888,1 +118874,Female,34,High School,19,4,4,16,42,5.0,6,18,Urban,Data Analyst,72197,0 +118875,Female,34,Diploma,5,86,2,29,46,4.0,2,58,Rural,HR Executive,48412,0 +118876,Female,29,Masters,14,58,17,35,15,0.0,3,97,Semi-Urban,HR Executive,138033,0 +118877,Male,28,Diploma,0,65,41,30,49,0.0,1,13,Urban,HR Executive,52373,0 +118878,Male,28,Diploma,7,22,55,30,84,7.0,2,39,Urban,Data Analyst,96651,0 +118879,Male,53,Bachelors,13,38,67,58,73,5.0,5,1,Urban,Data Analyst,52704,0 +118880,Male,40,Bachelors,17,60,72,66,32,4.0,4,26,Rural,Data Analyst,80267,0 +118881,Female,26,Bachelors,15,65,91,80,23,5.0,2,95,Urban,ML Engineer,97949,1 +118882,Male,37,Bachelors,14,78,92,13,76,1.0,4,8,Semi-Urban,Software Engineer,74387,0 +118883,Male,26,Bachelors,2,79,45,47,19,2.0,4,48,Rural,HR Executive,76582,0 +118884,Female,53,Masters,9,27,70,47,1,2.0,3,78,Urban,Data Analyst,97853,0 +118885,Male,51,Diploma,14,3,4,86,97,9.0,3,76,Urban,Software Engineer,53350,0 +118886,Male,24,Bachelors,14,99,66,81,5,4.0,1,21,Urban,Data Analyst,45973,1 +118887,Male,28,PhD,9,69,29,97,60,6.0,0,49,Urban,Software Engineer,59998,1 +118888,Female,27,Diploma,11,47,39,11,25,8.0,0,77,Urban,HR Executive,69307,0 +118889,Female,41,Diploma,14,56,90,53,61,7.0,2,34,Rural,ML Engineer,31514,0 +118890,Male,45,Bachelors,9,34,42,68,92,1.0,3,38,Semi-Urban,Data Analyst,30976,0 +118891,Female,31,PhD,15,56,80,47,82,6.0,4,75,Urban,Data Analyst,32493,1 +118892,Other,27,High School,2,58,7,43,84,6.0,3,44,Rural,Software Engineer,46641,0 +118893,Male,35,Bachelors,13,27,2,24,41,0.0,3,94,Urban,Data Analyst,146046,0 +118894,Female,39,Masters,0,21,17,74,4,1.0,1,0,Semi-Urban,HR Executive,135519,0 +118895,Male,32,High School,8,96,61,40,89,4.0,3,21,Rural,Data Analyst,78679,0 +118896,Male,39,Bachelors,16,62,78,50,12,7.0,5,67,Semi-Urban,Software Engineer,126101,1 +118897,Male,36,Bachelors,16,80,82,28,8,3.0,4,35,Rural,Software Engineer,79698,0 +118898,Female,58,Bachelors,17,64,60,88,16,6.0,2,24,Urban,Manager,50890,0 +118899,Female,52,Masters,8,4,45,0,27,6.0,3,68,Semi-Urban,ML Engineer,113607,0 +118900,Female,35,Bachelors,16,92,41,17,30,1.0,3,29,Semi-Urban,Software Engineer,53906,0 +118901,Female,38,Bachelors,14,48,71,54,84,5.0,5,86,Urban,Manager,110335,1 +118902,Male,31,Bachelors,16,56,16,94,35,8.0,4,23,Urban,ML Engineer,127544,0 +118903,Male,48,Diploma,11,24,67,67,48,1.0,7,96,Urban,Manager,23666,1 +118904,Male,39,Bachelors,12,51,82,65,45,8.0,4,54,Urban,Data Analyst,41406,1 +118905,Male,35,Bachelors,16,38,54,21,59,4.0,1,14,Urban,Software Engineer,95983,0 +118906,Male,51,Diploma,7,14,64,90,34,3.0,1,63,Rural,ML Engineer,84879,0 +118907,Male,58,Masters,15,65,63,91,41,5.0,6,45,Urban,ML Engineer,88527,1 +118908,Other,44,Masters,2,34,97,12,93,6.0,7,94,Urban,HR Executive,102990,0 +118909,Female,32,Diploma,12,72,7,26,1,8.0,1,82,Urban,ML Engineer,102817,0 +118910,Male,52,Diploma,15,55,35,14,76,9.0,5,55,Urban,Data Analyst,113001,0 +118911,Male,56,Diploma,16,0,90,80,30,5.0,1,63,Semi-Urban,ML Engineer,23884,0 +118912,Female,41,High School,0,98,14,42,72,2.0,5,95,Urban,Software Engineer,75911,1 +118913,Male,53,Diploma,0,90,1,32,86,5.0,1,84,Semi-Urban,HR Executive,135174,0 +118914,Male,50,Bachelors,1,18,67,98,10,8.0,4,69,Rural,Manager,82924,1 +118915,Female,52,Bachelors,10,95,47,25,59,0.0,5,13,Rural,Manager,31700,0 +118916,Male,39,Masters,15,89,26,41,30,7.0,3,13,Urban,Software Engineer,54949,0 +118917,Female,45,Bachelors,4,11,6,67,78,5.0,4,21,Semi-Urban,Data Analyst,137757,0 +118918,Male,27,Bachelors,18,51,54,28,78,8.0,0,4,Urban,HR Executive,128987,0 +118919,Male,39,Bachelors,2,18,17,56,6,5.0,3,82,Urban,Software Engineer,100496,0 +118920,Other,38,High School,11,10,76,62,4,4.0,1,68,Urban,Software Engineer,71779,0 +118921,Male,35,High School,10,45,23,66,5,1.0,4,65,Semi-Urban,HR Executive,30038,0 +118922,Female,56,Diploma,11,23,30,70,47,6.0,3,13,Urban,Manager,22916,0 +118923,Female,51,Bachelors,17,31,89,91,62,2.0,4,2,Urban,Manager,145203,0 +118924,Male,47,Masters,9,89,79,8,26,6.0,6,89,Rural,HR Executive,50885,1 +118925,Female,57,Diploma,12,33,28,21,71,7.0,2,36,Urban,Data Analyst,107032,0 +118926,Male,44,Bachelors,13,29,11,13,43,6.0,5,15,Urban,Software Engineer,96283,0 +118927,Male,23,Diploma,15,37,9,53,35,2.0,2,76,Rural,Data Analyst,100796,0 +118928,Female,23,Masters,3,26,93,55,27,7.0,1,24,Urban,Software Engineer,107576,0 +118929,Male,28,Masters,12,12,66,44,70,8.0,7,77,Semi-Urban,HR Executive,102589,0 +118930,Female,41,Bachelors,18,74,57,96,82,8.0,2,37,Rural,ML Engineer,107561,1 +118931,Male,30,Masters,7,30,85,42,42,3.0,0,41,Rural,Manager,57289,0 +118932,Female,53,Bachelors,15,8,86,45,79,2.0,7,82,Semi-Urban,Manager,55632,0 +118933,Female,44,Diploma,5,79,34,22,29,4.0,6,71,Urban,Software Engineer,20404,0 +118934,Female,46,PhD,5,46,79,11,20,8.0,3,32,Urban,Software Engineer,75903,0 +118935,Other,52,Bachelors,2,93,46,66,23,8.0,5,79,Urban,Manager,50337,1 +118936,Female,39,High School,15,46,99,40,66,2.0,6,9,Semi-Urban,HR Executive,116290,0 +118937,Male,56,Masters,13,57,27,39,77,7.0,4,55,Urban,HR Executive,135642,0 +118938,Male,27,Masters,14,87,73,69,59,1.0,2,33,Urban,Software Engineer,140151,1 +118939,Female,50,Diploma,12,70,63,14,29,6.0,0,41,Urban,HR Executive,100710,0 +118940,Male,36,High School,14,69,64,49,6,5.0,2,33,Urban,HR Executive,51278,0 +118941,Male,21,PhD,0,21,62,38,56,9.0,3,29,Semi-Urban,Manager,37750,0 +118942,Male,22,High School,14,25,6,42,67,2.0,1,69,Semi-Urban,ML Engineer,63537,0 +118943,Female,54,Bachelors,11,59,31,47,95,2.0,0,2,Urban,Software Engineer,80405,0 +118944,Male,34,Masters,3,57,18,75,56,5.0,0,35,Semi-Urban,Manager,36655,0 +118945,Female,43,Diploma,15,31,91,11,0,8.0,2,37,Rural,HR Executive,88395,0 +118946,Female,49,High School,19,10,75,45,31,0.0,0,84,Urban,HR Executive,71338,0 +118947,Male,49,Bachelors,12,6,72,88,35,0.0,3,57,Urban,Manager,137749,0 +118948,Female,51,High School,10,24,48,28,20,5.0,5,51,Semi-Urban,Manager,125068,0 +118949,Male,40,Bachelors,15,76,24,46,15,5.0,1,73,Semi-Urban,Data Analyst,46083,0 +118950,Male,50,Diploma,5,70,15,82,63,9.0,3,98,Rural,Data Analyst,135171,1 +118951,Male,59,High School,13,99,9,67,27,4.0,1,88,Urban,Manager,114850,1 +118952,Male,35,Diploma,17,49,22,69,26,7.0,0,96,Rural,Manager,116714,1 +118953,Female,51,Masters,13,18,85,40,5,5.0,0,62,Rural,ML Engineer,42563,0 +118954,Male,31,PhD,7,19,4,79,3,5.0,0,10,Urban,Data Analyst,48859,0 +118955,Male,53,Diploma,3,40,90,42,99,8.0,4,10,Urban,ML Engineer,72545,0 +118956,Male,58,Bachelors,8,49,65,85,60,3.0,3,80,Semi-Urban,HR Executive,41234,1 +118957,Male,24,High School,5,33,61,5,54,1.0,7,35,Semi-Urban,Data Analyst,109437,0 +118958,Female,52,Bachelors,6,61,41,76,62,4.0,7,12,Urban,Software Engineer,57148,0 +118959,Male,55,Diploma,10,1,58,31,67,9.0,6,66,Urban,Data Analyst,115729,0 +118960,Male,49,Bachelors,16,88,35,11,75,7.0,0,71,Rural,HR Executive,32621,0 +118961,Female,39,Diploma,15,2,5,50,54,3.0,6,23,Urban,ML Engineer,59521,0 +118962,Female,47,Diploma,17,45,54,65,97,0.0,7,83,Semi-Urban,Data Analyst,55503,1 +118963,Male,25,Bachelors,3,95,4,58,54,0.0,4,25,Urban,Software Engineer,147499,0 +118964,Male,46,High School,10,41,64,12,20,4.0,3,89,Urban,HR Executive,48979,0 +118965,Female,49,Masters,16,26,46,24,6,8.0,6,18,Urban,Data Analyst,68869,0 +118966,Male,59,High School,4,64,67,12,89,1.0,7,27,Urban,ML Engineer,57184,0 +118967,Female,54,Masters,19,29,38,1,13,4.0,0,32,Urban,HR Executive,140850,0 +118968,Female,32,Bachelors,16,35,36,30,31,4.0,5,44,Semi-Urban,ML Engineer,75753,0 +118969,Female,55,Diploma,19,85,49,35,39,4.0,3,84,Urban,Manager,108650,1 +118970,Female,59,PhD,1,53,42,2,78,4.0,1,11,Rural,HR Executive,149663,0 +118971,Male,40,Masters,6,79,43,80,58,8.0,4,21,Urban,HR Executive,67297,0 +118972,Male,31,Masters,2,46,2,73,35,7.0,3,36,Urban,Data Analyst,103302,0 +118973,Male,58,Bachelors,14,80,77,31,94,0.0,4,25,Semi-Urban,Data Analyst,51488,0 +118974,Male,43,Bachelors,19,67,89,1,95,1.0,2,36,Urban,Manager,38641,0 +118975,Male,45,High School,7,36,21,83,49,5.0,5,57,Semi-Urban,Data Analyst,60468,0 +118976,Male,27,Masters,2,85,24,37,75,8.0,0,8,Urban,Data Analyst,41157,0 +118977,Female,37,Masters,3,65,98,59,64,9.0,4,83,Urban,Data Analyst,65715,1 +118978,Male,46,Bachelors,18,85,80,20,43,9.0,6,13,Urban,HR Executive,84698,0 +118979,Male,34,Masters,9,74,83,98,90,7.0,0,83,Urban,HR Executive,114095,1 +118980,Male,56,Diploma,13,62,88,57,31,7.0,4,95,Semi-Urban,Software Engineer,29216,1 +118981,Male,23,Masters,2,28,21,91,41,5.0,4,15,Semi-Urban,Software Engineer,68829,0 +118982,Male,53,Diploma,10,32,2,5,84,0.0,1,40,Urban,HR Executive,38193,0 +118983,Male,36,Bachelors,11,40,10,79,22,0.0,7,51,Urban,Data Analyst,111210,0 +118984,Female,49,Masters,6,21,41,71,86,8.0,4,34,Semi-Urban,Manager,48683,0 +118985,Female,34,Bachelors,0,77,27,8,44,3.0,4,39,Semi-Urban,ML Engineer,90454,0 +118986,Male,22,Masters,17,39,29,20,11,9.0,0,43,Rural,Manager,48454,0 +118987,Male,25,Masters,19,57,52,41,20,7.0,4,2,Urban,Data Analyst,138326,0 +118988,Female,22,Masters,16,92,38,40,15,6.0,1,90,Urban,Manager,85394,1 +118989,Male,49,Masters,5,70,17,27,34,5.0,0,49,Urban,Software Engineer,130227,0 +118990,Male,37,Bachelors,16,14,50,89,58,1.0,0,60,Rural,Data Analyst,32395,0 +118991,Female,25,Diploma,19,92,62,61,22,7.0,7,96,Rural,Data Analyst,23172,1 +118992,Male,45,Diploma,13,43,16,17,3,9.0,4,28,Urban,Data Analyst,91332,0 +118993,Male,26,Bachelors,14,53,82,32,67,4.0,7,68,Semi-Urban,HR Executive,52619,1 +118994,Male,21,Bachelors,5,88,33,9,63,1.0,4,86,Semi-Urban,Software Engineer,72737,0 +118995,Male,58,Bachelors,9,42,48,88,97,4.0,6,4,Urban,HR Executive,108220,0 +118996,Female,42,High School,15,93,3,7,20,0.0,7,89,Urban,HR Executive,122574,0 +118997,Female,44,Bachelors,9,26,42,13,30,3.0,4,41,Semi-Urban,ML Engineer,140790,0 +118998,Male,37,Bachelors,7,66,38,25,44,7.0,7,0,Urban,ML Engineer,46856,0 +118999,Other,39,Diploma,15,55,89,23,41,4.0,7,91,Urban,HR Executive,66859,1 +119000,Male,50,PhD,12,34,25,66,46,9.0,5,31,Urban,HR Executive,109083,0 +119001,Male,39,Masters,3,27,88,88,14,9.0,6,23,Urban,ML Engineer,130120,0 +119002,Other,37,PhD,6,0,32,8,8,7.0,7,88,Urban,ML Engineer,30777,0 +119003,Female,53,Diploma,16,74,22,21,77,6.0,5,62,Urban,ML Engineer,62853,0 +119004,Male,48,High School,9,35,69,97,88,6.0,1,9,Urban,Data Analyst,114937,0 +119005,Female,55,Bachelors,12,17,4,43,69,4.0,3,25,Semi-Urban,Data Analyst,117343,0 +119006,Male,42,Diploma,3,20,41,81,63,2.0,4,23,Rural,Manager,61508,0 +119007,Male,49,Masters,19,26,97,34,87,9.0,1,17,Urban,Data Analyst,118480,0 +119008,Female,58,Masters,4,6,33,18,36,6.0,7,16,Urban,ML Engineer,54805,0 +119009,Male,46,Diploma,0,59,5,57,14,5.0,7,6,Urban,Software Engineer,37166,0 +119010,Female,45,Masters,19,89,94,50,82,0.0,5,33,Semi-Urban,Software Engineer,142673,1 +119011,Male,37,Bachelors,11,68,95,63,69,7.0,4,81,Urban,Data Analyst,138844,1 +119012,Male,55,Masters,5,9,46,73,88,0.0,2,98,Urban,HR Executive,24973,0 +119013,Male,55,Masters,1,99,78,22,2,6.0,0,85,Urban,HR Executive,20693,1 +119014,Female,31,Bachelors,16,72,18,58,44,9.0,2,44,Rural,Software Engineer,144784,0 +119015,Female,27,Masters,15,93,25,83,59,3.0,1,13,Rural,Software Engineer,149039,0 +119016,Female,35,Masters,19,33,80,84,5,7.0,2,90,Urban,HR Executive,144088,1 +119017,Female,23,Bachelors,4,15,69,24,33,3.0,5,73,Urban,Manager,125071,0 +119018,Male,56,Bachelors,0,92,97,77,12,4.0,4,94,Urban,Software Engineer,83698,1 +119019,Male,22,Masters,12,97,19,65,99,7.0,4,86,Semi-Urban,Manager,77209,1 +119020,Male,32,Masters,18,26,75,56,12,3.0,2,28,Urban,Data Analyst,135957,0 +119021,Male,23,Diploma,12,61,41,87,84,2.0,0,11,Semi-Urban,Manager,128363,0 +119022,Male,58,Diploma,1,75,27,69,2,8.0,3,83,Urban,Data Analyst,67027,1 +119023,Female,31,Bachelors,6,81,38,19,44,6.0,6,2,Urban,Data Analyst,86542,0 +119024,Female,58,High School,3,58,25,40,21,7.0,7,82,Rural,Software Engineer,45160,0 +119025,Male,23,Bachelors,7,36,26,63,52,9.0,3,31,Rural,Software Engineer,27781,0 +119026,Male,32,Diploma,17,68,48,60,48,0.0,3,93,Urban,ML Engineer,44267,1 +119027,Other,36,Bachelors,6,23,0,47,2,9.0,2,51,Urban,HR Executive,129633,0 +119028,Male,45,Diploma,18,36,49,24,11,0.0,6,31,Urban,HR Executive,105096,0 +119029,Male,25,Bachelors,7,50,67,94,28,3.0,5,38,Semi-Urban,Software Engineer,33093,1 +119030,Male,23,Masters,4,66,26,23,80,4.0,0,97,Semi-Urban,Data Analyst,35800,0 +119031,Male,37,Bachelors,0,9,70,44,68,6.0,4,72,Rural,Manager,89118,0 +119032,Male,33,Bachelors,6,44,7,33,87,0.0,3,39,Semi-Urban,Data Analyst,66690,0 +119033,Female,53,Diploma,13,33,81,23,34,3.0,3,46,Semi-Urban,Manager,117743,0 +119034,Male,42,Bachelors,12,60,50,77,78,1.0,1,43,Urban,Data Analyst,53241,0 +119035,Male,56,Bachelors,10,12,65,37,56,8.0,4,53,Urban,HR Executive,36860,0 +119036,Male,36,Diploma,13,67,80,39,45,7.0,3,26,Urban,Data Analyst,20901,0 +119037,Male,30,Bachelors,0,12,76,56,13,2.0,1,89,Urban,HR Executive,125416,0 +119038,Female,41,Masters,12,18,28,53,9,6.0,0,84,Urban,HR Executive,108460,0 +119039,Male,49,Diploma,0,41,6,24,87,6.0,6,52,Urban,ML Engineer,96327,0 +119040,Male,33,Masters,13,18,91,26,97,3.0,1,46,Rural,Manager,120281,0 +119041,Male,32,Masters,3,97,92,44,65,1.0,2,73,Rural,HR Executive,55592,1 +119042,Male,53,Masters,15,51,61,24,15,3.0,6,20,Urban,HR Executive,28862,0 +119043,Male,39,Bachelors,15,87,50,68,8,0.0,7,15,Urban,Data Analyst,71759,0 +119044,Female,57,Bachelors,15,8,33,32,63,5.0,0,41,Urban,Manager,88373,0 +119045,Female,31,Bachelors,11,12,59,40,79,6.0,4,73,Urban,Data Analyst,105595,0 +119046,Female,39,Bachelors,14,64,47,76,4,7.0,2,7,Semi-Urban,Manager,75477,0 +119047,Male,29,Bachelors,9,4,15,80,2,4.0,2,59,Urban,ML Engineer,134631,0 +119048,Female,44,Bachelors,11,47,53,41,84,0.0,1,45,Urban,HR Executive,67706,0 +119049,Male,40,High School,6,75,25,65,46,8.0,2,64,Urban,HR Executive,100925,0 +119050,Male,31,High School,15,27,88,44,86,3.0,1,20,Rural,Data Analyst,135310,0 +119051,Other,31,High School,1,78,33,37,38,9.0,3,92,Urban,Software Engineer,122460,0 +119052,Other,54,Bachelors,15,93,72,2,41,3.0,3,50,Urban,Manager,81972,0 +119053,Female,44,Bachelors,4,7,93,1,97,8.0,4,33,Urban,ML Engineer,115527,0 +119054,Male,54,Diploma,11,40,40,35,81,8.0,1,76,Urban,ML Engineer,67693,0 +119055,Female,21,Diploma,4,2,76,56,51,1.0,0,42,Rural,Software Engineer,60359,0 +119056,Male,50,PhD,17,53,95,84,87,2.0,7,84,Semi-Urban,Manager,109770,1 +119057,Female,47,Bachelors,13,44,92,72,19,5.0,2,14,Urban,Software Engineer,83232,0 +119058,Male,58,Bachelors,7,93,8,81,26,3.0,5,61,Semi-Urban,Data Analyst,98598,1 +119059,Male,31,Masters,9,10,69,38,36,7.0,6,0,Urban,Data Analyst,141232,0 +119060,Male,26,Diploma,2,11,57,34,49,5.0,7,20,Rural,ML Engineer,74137,0 +119061,Male,57,High School,0,20,46,97,86,0.0,3,24,Urban,Software Engineer,123784,0 +119062,Male,45,Bachelors,14,88,30,90,57,8.0,7,49,Semi-Urban,HR Executive,59971,1 +119063,Male,46,Masters,8,87,48,43,48,4.0,6,53,Rural,Manager,38230,0 +119064,Female,31,Bachelors,6,20,17,48,14,1.0,1,66,Urban,ML Engineer,101959,0 +119065,Female,21,Bachelors,4,44,26,11,25,3.0,4,21,Urban,Manager,44128,0 +119066,Male,36,Bachelors,16,58,27,93,57,6.0,4,76,Semi-Urban,HR Executive,131258,1 +119067,Male,54,Bachelors,17,77,46,78,29,7.0,5,83,Urban,HR Executive,61430,1 +119068,Male,36,Bachelors,17,58,5,98,21,7.0,5,90,Urban,Data Analyst,67543,1 +119069,Male,47,Masters,2,55,46,32,33,2.0,3,8,Urban,HR Executive,110626,0 +119070,Female,39,Masters,16,30,64,46,46,3.0,6,15,Urban,HR Executive,120701,0 +119071,Male,50,Diploma,6,59,35,12,94,5.0,3,23,Rural,Manager,72713,0 +119072,Male,55,High School,1,57,78,67,59,6.0,5,97,Semi-Urban,Manager,56095,1 +119073,Male,42,Masters,3,81,2,63,11,1.0,3,25,Urban,Software Engineer,48646,0 +119074,Female,49,Bachelors,13,67,21,81,27,9.0,4,23,Semi-Urban,Data Analyst,140887,0 +119075,Other,51,Diploma,14,99,70,26,8,4.0,4,85,Semi-Urban,Manager,113268,1 +119076,Male,46,Masters,5,46,47,13,93,4.0,6,4,Urban,ML Engineer,98604,0 +119077,Male,45,Bachelors,1,80,20,71,57,0.0,0,54,Rural,HR Executive,129882,0 +119078,Female,40,Bachelors,14,11,56,70,59,7.0,7,68,Urban,ML Engineer,99031,0 +119079,Male,33,Bachelors,1,62,48,73,54,1.0,0,41,Urban,HR Executive,86963,0 +119080,Male,33,Diploma,18,54,11,27,67,5.0,5,30,Rural,Manager,40487,0 +119081,Male,40,High School,8,93,25,22,48,8.0,1,9,Semi-Urban,HR Executive,126791,0 +119082,Male,56,Masters,11,37,91,41,78,3.0,4,59,Rural,Manager,149589,0 +119083,Male,27,High School,2,18,39,97,57,7.0,0,29,Urban,Software Engineer,68617,0 +119084,Male,40,Masters,14,79,82,73,50,3.0,2,78,Urban,ML Engineer,28159,1 +119085,Female,26,Masters,14,79,22,49,11,4.0,2,75,Urban,HR Executive,73982,0 +119086,Female,45,High School,3,56,46,74,40,5.0,3,67,Rural,Data Analyst,70352,1 +119087,Female,58,Bachelors,0,79,81,74,56,3.0,6,35,Urban,Manager,40389,1 +119088,Female,53,Bachelors,0,44,68,50,9,0.0,2,31,Urban,Manager,83483,0 +119089,Female,22,Diploma,3,47,29,22,28,2.0,1,62,Rural,Manager,38861,0 +119090,Female,32,Bachelors,13,44,89,6,39,0.0,2,79,Rural,Data Analyst,62849,0 +119091,Female,43,Bachelors,1,48,12,59,87,0.0,3,93,Urban,HR Executive,100406,0 +119092,Male,27,Diploma,4,14,46,7,67,9.0,2,80,Urban,Data Analyst,124212,0 +119093,Female,27,Masters,12,75,50,74,78,3.0,4,41,Urban,Manager,139301,0 +119094,Female,56,Diploma,2,54,87,91,12,1.0,7,80,Urban,Manager,22998,1 +119095,Female,23,High School,17,12,66,81,41,2.0,3,3,Urban,HR Executive,89560,0 +119096,Female,35,Diploma,5,67,46,17,78,5.0,7,13,Urban,Data Analyst,38719,0 +119097,Male,46,Bachelors,17,58,3,68,23,4.0,1,83,Urban,Manager,110031,0 +119098,Male,44,Diploma,19,49,56,86,54,7.0,4,51,Urban,HR Executive,105921,1 +119099,Female,34,Bachelors,15,88,68,30,50,5.0,6,80,Rural,Manager,105654,1 +119100,Male,39,High School,19,33,34,40,14,6.0,4,2,Rural,Data Analyst,121164,0 +119101,Male,49,Diploma,0,47,47,41,13,6.0,3,75,Urban,Manager,45675,0 +119102,Other,22,PhD,4,22,93,46,57,4.0,5,94,Urban,Manager,85596,1 +119103,Female,41,Diploma,14,0,68,67,79,8.0,1,93,Urban,HR Executive,132002,0 +119104,Male,32,Diploma,8,53,87,3,10,8.0,2,68,Urban,Software Engineer,87184,0 +119105,Male,45,Masters,14,36,72,64,86,9.0,5,51,Semi-Urban,ML Engineer,62418,0 +119106,Male,59,Bachelors,0,32,66,29,88,8.0,0,58,Urban,Manager,55896,0 +119107,Other,42,Diploma,10,48,34,74,34,5.0,7,15,Urban,Software Engineer,132581,0 +119108,Other,41,Masters,19,72,57,78,46,5.0,4,55,Rural,Data Analyst,86421,1 +119109,Male,42,High School,9,1,69,68,33,7.0,2,51,Urban,ML Engineer,20879,0 +119110,Male,39,Diploma,1,42,83,6,54,0.0,3,11,Semi-Urban,Software Engineer,47854,0 +119111,Male,42,PhD,9,34,75,95,20,4.0,1,68,Urban,ML Engineer,134677,1 +119112,Female,41,Masters,15,94,86,5,96,3.0,7,9,Semi-Urban,Data Analyst,99453,0 +119113,Male,48,Bachelors,6,43,80,15,45,9.0,5,37,Urban,HR Executive,75688,0 +119114,Male,36,Diploma,11,23,35,48,65,1.0,1,21,Semi-Urban,Data Analyst,111359,0 +119115,Female,23,High School,16,77,6,5,28,1.0,2,32,Semi-Urban,ML Engineer,26446,0 +119116,Male,55,Masters,17,21,86,98,91,2.0,0,68,Urban,Data Analyst,136580,1 +119117,Male,59,Bachelors,0,46,55,24,47,5.0,1,71,Semi-Urban,Data Analyst,114957,0 +119118,Female,45,Bachelors,10,57,91,72,3,6.0,1,36,Urban,ML Engineer,22904,1 +119119,Female,38,High School,11,25,39,34,76,9.0,0,17,Urban,ML Engineer,120820,0 +119120,Female,35,PhD,5,3,0,54,68,3.0,6,11,Urban,Software Engineer,32179,0 +119121,Female,53,High School,1,22,99,59,54,1.0,3,74,Urban,Data Analyst,80356,1 +119122,Male,23,High School,14,52,17,57,52,4.0,2,88,Urban,ML Engineer,32656,0 +119123,Female,38,High School,10,37,47,96,55,1.0,3,44,Semi-Urban,HR Executive,89905,0 +119124,Male,42,Masters,19,76,0,74,35,2.0,3,52,Rural,Manager,102300,0 +119125,Male,34,PhD,5,43,90,56,35,7.0,2,24,Urban,ML Engineer,104010,0 +119126,Male,54,Bachelors,10,91,39,61,98,0.0,7,25,Urban,Software Engineer,139509,0 +119127,Male,34,Bachelors,17,53,77,21,38,9.0,6,44,Rural,HR Executive,51352,0 +119128,Male,27,Bachelors,15,42,25,30,23,1.0,5,71,Semi-Urban,HR Executive,27502,0 +119129,Male,54,Masters,13,74,88,25,0,3.0,3,0,Urban,Data Analyst,22375,0 +119130,Male,41,Bachelors,15,18,26,80,11,4.0,1,6,Semi-Urban,Data Analyst,90687,0 +119131,Female,44,Bachelors,15,16,93,10,54,1.0,3,62,Urban,Software Engineer,104288,0 +119132,Male,56,Bachelors,19,83,31,47,78,8.0,7,71,Semi-Urban,Software Engineer,100756,0 +119133,Female,37,Diploma,4,31,48,97,84,2.0,2,69,Urban,ML Engineer,136203,1 +119134,Female,40,High School,15,99,78,92,12,6.0,5,34,Rural,Software Engineer,124755,1 +119135,Female,55,High School,16,11,73,85,40,0.0,7,82,Urban,HR Executive,40634,1 +119136,Female,44,Diploma,16,96,47,1,98,1.0,6,60,Semi-Urban,Software Engineer,122674,0 +119137,Male,27,Diploma,13,90,12,64,48,4.0,4,36,Rural,ML Engineer,23440,0 +119138,Female,57,Diploma,18,29,45,96,62,8.0,1,42,Urban,ML Engineer,99674,0 +119139,Male,29,Bachelors,9,48,75,78,4,9.0,6,31,Semi-Urban,Manager,141509,0 +119140,Male,55,Diploma,12,97,45,76,49,7.0,6,72,Urban,Software Engineer,135393,1 +119141,Male,26,Bachelors,6,47,81,49,32,7.0,1,16,Urban,Data Analyst,100960,0 +119142,Male,23,Diploma,3,50,72,71,5,1.0,5,22,Urban,Software Engineer,129019,0 +119143,Male,38,Bachelors,4,39,83,57,99,2.0,1,81,Rural,HR Executive,20660,1 +119144,Other,21,Bachelors,1,73,75,65,59,0.0,5,71,Urban,ML Engineer,48344,1 +119145,Female,37,Bachelors,0,80,44,45,23,3.0,7,37,Semi-Urban,Software Engineer,129704,0 +119146,Male,53,High School,2,31,48,32,28,7.0,0,5,Urban,Manager,56572,0 +119147,Male,38,High School,10,12,74,84,92,4.0,2,31,Semi-Urban,HR Executive,102004,0 +119148,Male,48,Diploma,2,51,80,51,47,4.0,6,99,Rural,HR Executive,136500,1 +119149,Female,46,Bachelors,17,56,3,81,10,3.0,3,50,Rural,Data Analyst,97551,0 +119150,Male,30,Bachelors,7,88,30,33,28,4.0,1,99,Urban,ML Engineer,107386,1 +119151,Female,40,Bachelors,8,63,59,21,56,5.0,2,90,Urban,Software Engineer,129344,0 +119152,Male,45,Bachelors,6,95,65,35,33,2.0,1,92,Urban,Manager,137966,1 +119153,Male,23,High School,18,98,46,23,15,3.0,0,90,Urban,ML Engineer,73754,1 +119154,Male,45,Bachelors,14,28,44,45,62,9.0,4,73,Urban,Manager,58754,0 +119155,Other,54,Bachelors,1,97,37,63,31,8.0,7,10,Semi-Urban,Data Analyst,82197,0 +119156,Female,27,Masters,3,53,97,88,34,1.0,4,51,Urban,Manager,125198,1 +119157,Male,34,Bachelors,8,67,69,16,8,4.0,7,14,Urban,Data Analyst,142315,0 +119158,Male,29,High School,16,14,79,6,44,1.0,6,43,Urban,HR Executive,39317,0 +119159,Female,46,Masters,1,3,29,6,96,4.0,0,97,Semi-Urban,ML Engineer,106488,0 +119160,Female,36,High School,4,63,93,65,1,7.0,3,10,Urban,Manager,122373,0 +119161,Male,40,Bachelors,9,28,57,52,78,9.0,3,64,Rural,ML Engineer,122598,0 +119162,Male,57,Diploma,16,47,36,54,51,3.0,5,76,Semi-Urban,Software Engineer,86115,0 +119163,Male,44,Bachelors,7,92,66,41,99,8.0,5,67,Semi-Urban,ML Engineer,131216,1 +119164,Male,57,Diploma,12,25,49,50,73,4.0,3,66,Semi-Urban,ML Engineer,65114,0 +119165,Male,37,Bachelors,0,38,27,34,21,2.0,3,27,Rural,HR Executive,74914,0 +119166,Male,46,Bachelors,7,94,45,49,27,7.0,6,44,Semi-Urban,Software Engineer,45324,0 +119167,Male,59,Bachelors,18,91,94,90,65,3.0,1,51,Urban,ML Engineer,136250,1 +119168,Female,48,Diploma,17,12,80,1,57,0.0,1,85,Urban,HR Executive,148241,0 +119169,Male,30,Diploma,10,85,50,91,47,6.0,3,42,Urban,Manager,90258,1 +119170,Male,56,Bachelors,8,90,8,6,90,8.0,3,79,Urban,Software Engineer,63996,0 +119171,Other,26,Bachelors,16,94,76,11,20,3.0,2,88,Rural,HR Executive,77253,1 +119172,Male,30,Bachelors,0,93,56,40,59,4.0,0,27,Urban,ML Engineer,51261,0 +119173,Male,26,Bachelors,4,55,33,88,73,0.0,7,87,Urban,ML Engineer,95937,1 +119174,Male,27,High School,10,18,95,88,60,7.0,0,13,Semi-Urban,Data Analyst,131503,0 +119175,Male,28,Bachelors,2,48,52,11,76,1.0,7,75,Urban,HR Executive,115899,0 +119176,Male,43,Masters,17,68,56,0,37,2.0,6,86,Urban,Software Engineer,31914,0 +119177,Female,29,High School,6,48,69,82,73,7.0,4,4,Urban,HR Executive,31967,0 +119178,Male,47,Bachelors,9,76,30,87,56,2.0,7,69,Urban,Software Engineer,93564,1 +119179,Male,54,Bachelors,2,90,87,88,61,0.0,5,73,Semi-Urban,Data Analyst,70587,1 +119180,Female,56,High School,0,23,62,17,73,9.0,5,60,Rural,HR Executive,67081,0 +119181,Female,48,PhD,16,30,79,69,98,0.0,3,17,Semi-Urban,Manager,125321,0 +119182,Female,23,Masters,1,5,88,41,37,7.0,4,15,Semi-Urban,HR Executive,142829,0 +119183,Female,33,PhD,5,40,16,12,0,4.0,7,52,Urban,Manager,101597,0 +119184,Female,42,PhD,18,85,24,84,17,5.0,1,88,Urban,Software Engineer,137587,1 +119185,Male,34,High School,17,62,54,28,21,7.0,0,22,Semi-Urban,HR Executive,147539,0 +119186,Male,59,Bachelors,5,47,20,30,23,3.0,1,66,Semi-Urban,Manager,137072,0 +119187,Male,39,Masters,8,99,98,80,59,8.0,3,58,Urban,Data Analyst,88436,1 +119188,Male,40,Masters,17,97,29,28,80,0.0,6,14,Rural,Data Analyst,94666,0 +119189,Male,42,High School,4,93,64,93,96,7.0,3,51,Rural,Manager,59528,1 +119190,Male,33,Bachelors,12,89,88,90,58,1.0,4,1,Urban,Manager,147464,1 +119191,Female,52,Bachelors,14,43,45,93,76,5.0,3,0,Urban,HR Executive,74951,0 +119192,Male,51,Diploma,16,72,94,49,4,1.0,1,49,Urban,Software Engineer,101685,1 +119193,Female,32,Diploma,9,50,95,49,18,6.0,5,18,Urban,Data Analyst,75100,0 +119194,Male,40,Masters,17,58,13,51,72,6.0,1,2,Rural,Manager,96109,0 +119195,Female,46,Bachelors,8,79,87,88,88,4.0,6,52,Urban,Data Analyst,101815,1 +119196,Male,32,Diploma,13,62,64,74,19,0.0,6,85,Urban,Data Analyst,113673,1 +119197,Female,40,Diploma,16,12,30,78,84,8.0,5,17,Rural,Software Engineer,88258,0 +119198,Male,31,Masters,0,45,37,71,60,2.0,2,57,Urban,Data Analyst,83809,0 +119199,Male,33,Masters,15,96,98,86,28,3.0,5,44,Urban,HR Executive,46733,1 +119200,Female,57,Masters,5,79,58,49,70,6.0,5,79,Semi-Urban,ML Engineer,132231,1 +119201,Female,28,Bachelors,3,45,59,32,66,0.0,3,31,Semi-Urban,Software Engineer,62610,0 +119202,Male,35,Diploma,11,24,69,41,60,5.0,7,4,Urban,ML Engineer,35719,0 +119203,Male,52,Diploma,6,45,39,35,15,6.0,7,61,Semi-Urban,Software Engineer,77447,0 +119204,Male,45,Diploma,19,67,89,66,62,2.0,4,53,Urban,Data Analyst,74944,1 +119205,Female,24,Diploma,7,23,57,14,84,8.0,7,72,Urban,ML Engineer,41239,0 +119206,Male,50,Bachelors,7,6,38,8,38,8.0,4,16,Urban,Manager,58551,0 +119207,Female,42,High School,9,11,85,58,71,6.0,6,76,Rural,Data Analyst,132955,0 +119208,Male,51,Bachelors,15,28,75,69,52,6.0,5,26,Urban,Data Analyst,59894,0 +119209,Female,57,Bachelors,10,97,72,9,40,5.0,4,86,Urban,ML Engineer,35811,1 +119210,Female,34,Diploma,0,77,25,81,67,5.0,4,17,Urban,Data Analyst,26867,0 +119211,Other,59,Masters,19,51,13,3,62,6.0,1,38,Semi-Urban,Software Engineer,92139,0 +119212,Male,30,High School,8,78,99,28,90,8.0,5,3,Urban,Software Engineer,64501,0 +119213,Female,55,Masters,18,84,38,68,87,0.0,0,53,Rural,Data Analyst,116511,1 +119214,Male,54,Bachelors,18,69,61,51,69,0.0,1,75,Urban,Software Engineer,107194,1 +119215,Male,43,High School,6,5,44,37,88,2.0,2,70,Semi-Urban,HR Executive,110247,0 +119216,Male,44,Masters,12,63,31,51,92,3.0,3,78,Urban,ML Engineer,84897,0 +119217,Male,49,High School,5,8,18,97,63,4.0,1,64,Semi-Urban,HR Executive,131857,0 +119218,Male,30,Bachelors,15,36,39,82,89,5.0,0,32,Urban,ML Engineer,88075,0 +119219,Female,31,Diploma,11,11,3,15,69,7.0,5,86,Urban,Data Analyst,44218,0 +119220,Male,57,High School,8,64,22,31,78,1.0,5,85,Semi-Urban,Software Engineer,55704,0 +119221,Female,52,Diploma,19,73,75,56,84,1.0,4,7,Urban,Data Analyst,89212,0 +119222,Male,30,Diploma,1,87,32,50,3,9.0,5,0,Urban,Data Analyst,140311,0 +119223,Male,22,Bachelors,2,41,57,44,87,1.0,4,15,Rural,Data Analyst,113696,0 +119224,Male,44,Bachelors,1,19,93,99,42,9.0,3,62,Urban,Data Analyst,36793,1 +119225,Other,56,Bachelors,4,33,28,76,62,3.0,4,94,Urban,ML Engineer,143112,0 +119226,Male,23,Diploma,4,40,32,8,93,2.0,2,91,Semi-Urban,HR Executive,96019,0 +119227,Male,22,Bachelors,5,75,83,61,4,6.0,1,84,Urban,Manager,41977,1 +119228,Female,37,Bachelors,19,35,83,68,73,9.0,0,86,Semi-Urban,Manager,130072,1 +119229,Female,54,Bachelors,7,6,16,64,40,0.0,6,21,Semi-Urban,ML Engineer,81911,0 +119230,Male,54,Bachelors,9,39,31,37,6,0.0,0,1,Urban,Data Analyst,28538,0 +119231,Female,45,High School,13,95,21,38,9,4.0,5,49,Urban,Software Engineer,64812,0 +119232,Male,32,High School,0,31,54,38,61,5.0,2,92,Semi-Urban,Data Analyst,36796,0 +119233,Male,50,Bachelors,15,23,99,69,55,1.0,3,8,Urban,Software Engineer,42914,0 +119234,Male,43,Diploma,6,63,14,81,38,7.0,6,7,Rural,Data Analyst,108407,0 +119235,Male,38,Diploma,7,66,41,82,75,9.0,2,45,Urban,HR Executive,116770,0 +119236,Other,31,Bachelors,19,8,25,36,56,2.0,6,18,Urban,ML Engineer,109802,0 +119237,Male,29,Bachelors,1,60,16,43,57,2.0,5,32,Urban,Software Engineer,54450,0 +119238,Female,25,Diploma,18,23,19,1,70,3.0,7,29,Semi-Urban,Manager,100935,0 +119239,Other,27,Masters,12,16,10,61,64,7.0,0,81,Semi-Urban,HR Executive,66993,0 +119240,Female,51,Diploma,11,51,38,96,47,5.0,1,86,Urban,ML Engineer,62483,1 +119241,Male,29,Bachelors,3,94,88,75,12,6.0,6,92,Urban,Data Analyst,49546,1 +119242,Male,29,Bachelors,9,87,76,81,2,6.0,7,32,Urban,Manager,82459,1 +119243,Female,58,Bachelors,11,28,85,56,49,3.0,2,23,Urban,HR Executive,75440,0 +119244,Male,37,Masters,11,98,96,37,33,5.0,7,71,Semi-Urban,Software Engineer,39497,1 +119245,Male,51,PhD,10,19,44,65,31,3.0,7,23,Urban,ML Engineer,100742,0 +119246,Female,45,Bachelors,19,89,61,68,30,0.0,3,8,Urban,ML Engineer,33918,0 +119247,Female,48,Bachelors,6,91,0,54,5,9.0,0,82,Semi-Urban,Data Analyst,76289,0 +119248,Female,23,Diploma,3,84,91,85,49,3.0,3,84,Urban,Software Engineer,104434,1 +119249,Other,26,Diploma,18,54,89,42,22,7.0,0,13,Rural,HR Executive,86324,0 +119250,Male,23,Bachelors,8,56,3,48,62,7.0,2,94,Urban,HR Executive,85301,0 +119251,Female,24,Masters,7,46,36,38,94,6.0,3,20,Urban,Data Analyst,101672,0 +119252,Female,28,Masters,18,4,77,95,95,9.0,2,61,Rural,HR Executive,55094,0 +119253,Male,32,Diploma,6,51,95,34,91,0.0,3,13,Urban,Data Analyst,61931,0 +119254,Female,47,Bachelors,18,19,33,17,53,4.0,0,19,Urban,ML Engineer,28358,0 +119255,Male,26,Bachelors,5,21,8,15,1,0.0,6,58,Urban,Data Analyst,50632,0 +119256,Female,26,PhD,6,32,51,20,38,4.0,7,45,Semi-Urban,Software Engineer,27489,0 +119257,Female,36,Bachelors,8,37,8,11,52,0.0,1,26,Urban,Manager,114078,0 +119258,Male,58,Masters,11,13,72,47,90,4.0,1,8,Urban,Manager,92586,0 +119259,Female,32,Bachelors,1,81,70,91,95,2.0,7,51,Urban,Manager,125191,1 +119260,Female,32,Bachelors,6,28,6,48,49,2.0,3,91,Rural,Data Analyst,142546,0 +119261,Male,51,Bachelors,19,59,12,92,28,0.0,7,7,Semi-Urban,ML Engineer,135850,0 +119262,Male,35,Masters,3,2,37,70,12,5.0,6,8,Urban,Data Analyst,144339,0 +119263,Female,46,Bachelors,15,59,78,0,22,0.0,1,82,Rural,Manager,133982,0 +119264,Male,42,PhD,5,85,78,44,40,5.0,6,58,Semi-Urban,Manager,96863,1 +119265,Female,34,Bachelors,5,27,90,39,93,6.0,2,81,Semi-Urban,ML Engineer,109458,0 +119266,Male,24,High School,18,97,72,61,30,0.0,6,19,Urban,Manager,114247,1 +119267,Female,37,Bachelors,8,88,89,32,77,6.0,2,80,Urban,HR Executive,89018,1 +119268,Male,52,Bachelors,16,45,58,24,76,7.0,5,77,Rural,Manager,61637,0 +119269,Female,37,Bachelors,16,23,6,52,88,1.0,0,64,Rural,Manager,49149,0 +119270,Male,24,Bachelors,7,12,19,19,63,9.0,3,36,Semi-Urban,Manager,86632,0 +119271,Other,31,Masters,9,34,22,66,73,6.0,3,8,Rural,ML Engineer,133170,0 +119272,Male,22,Bachelors,18,56,19,99,40,5.0,1,75,Urban,Manager,147953,1 +119273,Male,54,Bachelors,10,68,28,27,14,2.0,4,17,Urban,Software Engineer,147820,0 +119274,Male,58,Masters,5,14,73,47,50,1.0,7,47,Rural,Software Engineer,113078,0 +119275,Male,51,Bachelors,15,7,0,32,41,4.0,1,17,Urban,Manager,122424,0 +119276,Female,28,Diploma,10,75,94,42,26,0.0,5,26,Urban,Software Engineer,108597,0 +119277,Male,42,High School,12,49,83,28,92,8.0,1,48,Urban,HR Executive,106688,0 +119278,Female,21,Masters,7,94,38,23,54,3.0,4,63,Urban,HR Executive,33158,0 +119279,Male,27,Diploma,0,77,81,72,20,3.0,0,92,Urban,Software Engineer,104524,1 +119280,Female,48,Diploma,17,66,99,60,82,7.0,3,10,Urban,HR Executive,75373,0 +119281,Female,55,Bachelors,18,98,89,1,2,7.0,4,56,Urban,Software Engineer,86560,1 +119282,Male,38,Masters,11,83,22,54,38,4.0,2,5,Rural,Software Engineer,53440,0 +119283,Male,23,Masters,3,57,76,87,76,2.0,7,51,Urban,Data Analyst,39735,1 +119284,Female,55,High School,14,79,69,71,49,0.0,4,62,Urban,Manager,86048,1 +119285,Male,26,Bachelors,16,29,51,59,75,7.0,0,63,Semi-Urban,HR Executive,67744,0 +119286,Male,55,Bachelors,2,1,87,22,68,4.0,7,72,Urban,Manager,114010,0 +119287,Female,29,Bachelors,11,44,69,37,10,7.0,3,72,Urban,Software Engineer,59685,0 +119288,Male,40,PhD,3,47,95,1,82,5.0,0,76,Urban,Manager,68123,0 +119289,Male,34,High School,11,43,56,83,14,7.0,1,12,Semi-Urban,Data Analyst,137657,0 +119290,Male,23,High School,14,4,83,69,57,3.0,7,18,Urban,HR Executive,115497,0 +119291,Male,27,Bachelors,12,0,13,52,52,6.0,0,7,Urban,ML Engineer,102184,0 +119292,Male,29,Bachelors,1,13,50,15,0,0.0,6,22,Semi-Urban,Manager,120012,0 +119293,Male,23,Bachelors,5,42,15,98,35,0.0,1,20,Urban,Data Analyst,78352,0 +119294,Male,40,High School,7,13,32,32,37,4.0,4,64,Urban,Manager,122176,0 +119295,Male,23,Bachelors,0,81,27,18,98,7.0,4,69,Urban,Software Engineer,26628,0 +119296,Male,59,Masters,14,50,82,44,82,1.0,1,73,Urban,ML Engineer,108974,1 +119297,Male,31,Bachelors,4,13,34,47,22,6.0,5,53,Urban,ML Engineer,103117,0 +119298,Female,26,High School,11,64,84,57,40,7.0,3,61,Urban,HR Executive,109036,1 +119299,Male,33,Masters,15,89,16,79,22,6.0,5,29,Semi-Urban,ML Engineer,121479,0 +119300,Male,32,Bachelors,6,69,92,7,17,5.0,3,35,Urban,Software Engineer,114549,0 +119301,Female,41,Masters,11,99,71,57,38,9.0,3,94,Urban,HR Executive,125716,1 +119302,Male,43,PhD,15,54,29,43,66,2.0,5,84,Rural,ML Engineer,44389,0 +119303,Male,28,Bachelors,2,13,13,4,31,4.0,1,32,Urban,ML Engineer,115569,0 +119304,Female,39,Bachelors,4,91,8,95,89,1.0,2,49,Rural,HR Executive,23413,1 +119305,Male,34,Bachelors,7,50,13,81,72,6.0,5,2,Urban,HR Executive,105325,0 +119306,Male,45,Masters,5,28,91,21,80,1.0,4,9,Rural,Data Analyst,96998,0 +119307,Male,23,High School,9,39,79,19,75,3.0,2,81,Urban,ML Engineer,93495,0 +119308,Male,57,High School,7,5,27,52,68,6.0,7,36,Rural,Software Engineer,97377,0 +119309,Female,29,Diploma,15,62,41,77,58,6.0,0,45,Urban,ML Engineer,133208,0 +119310,Male,55,Bachelors,19,48,83,15,94,3.0,7,58,Urban,Software Engineer,31158,0 +119311,Female,27,PhD,9,33,43,94,86,3.0,5,37,Urban,Software Engineer,33904,0 +119312,Male,38,Diploma,3,31,57,29,13,2.0,4,91,Urban,Data Analyst,21339,0 +119313,Female,30,High School,16,98,27,68,22,6.0,4,54,Rural,Manager,133250,1 +119314,Female,35,Masters,9,59,28,53,64,6.0,6,20,Urban,ML Engineer,55134,0 +119315,Male,33,Bachelors,17,45,43,91,51,5.0,2,11,Urban,Manager,63098,0 +119316,Male,37,Diploma,7,55,17,52,28,3.0,5,44,Urban,Manager,100090,0 +119317,Female,32,PhD,0,29,22,47,33,8.0,1,6,Semi-Urban,Manager,102814,0 +119318,Male,35,Diploma,17,65,39,41,9,8.0,2,59,Urban,ML Engineer,29548,0 +119319,Male,33,Diploma,3,21,55,63,47,4.0,0,71,Urban,HR Executive,88292,0 +119320,Other,31,Masters,11,90,20,30,13,1.0,6,62,Urban,HR Executive,71430,0 +119321,Male,26,High School,4,66,40,73,79,8.0,5,50,Urban,ML Engineer,125550,0 +119322,Female,25,Diploma,7,60,28,62,8,6.0,0,85,Rural,HR Executive,45529,0 +119323,Female,26,Diploma,3,80,6,8,42,3.0,2,22,Urban,Manager,20474,0 +119324,Female,49,Diploma,17,61,29,39,87,3.0,1,48,Urban,Manager,108269,0 +119325,Female,53,Diploma,8,90,30,96,11,5.0,5,45,Semi-Urban,ML Engineer,24811,1 +119326,Female,47,Bachelors,13,24,53,42,50,4.0,0,0,Urban,ML Engineer,80681,0 +119327,Female,26,High School,8,80,79,43,60,9.0,1,42,Urban,HR Executive,104034,1 +119328,Male,50,Bachelors,6,72,37,51,61,6.0,1,98,Urban,Software Engineer,41294,1 +119329,Male,47,Bachelors,5,76,81,87,33,9.0,5,1,Rural,Data Analyst,69636,1 +119330,Male,29,Bachelors,9,92,70,70,60,5.0,2,21,Semi-Urban,Manager,72495,1 +119331,Female,59,Diploma,15,96,46,33,82,9.0,5,15,Semi-Urban,Software Engineer,135016,0 +119332,Male,23,Bachelors,3,33,56,16,74,8.0,3,50,Urban,Software Engineer,116745,0 +119333,Male,44,Diploma,17,59,76,45,2,4.0,4,83,Rural,ML Engineer,101456,1 +119334,Male,34,Bachelors,2,62,31,45,29,1.0,2,6,Urban,Manager,73606,0 +119335,Male,46,Bachelors,16,63,44,79,28,3.0,6,13,Semi-Urban,HR Executive,73310,0 +119336,Male,55,Bachelors,5,43,58,45,63,8.0,5,16,Semi-Urban,HR Executive,72670,0 +119337,Female,46,Diploma,5,15,68,42,28,8.0,0,67,Urban,HR Executive,88984,0 +119338,Male,24,Bachelors,18,24,88,21,19,3.0,4,46,Urban,ML Engineer,55616,0 +119339,Male,41,Diploma,9,24,38,80,11,8.0,7,55,Semi-Urban,Data Analyst,121055,0 +119340,Male,32,Bachelors,19,15,35,33,25,8.0,3,90,Semi-Urban,HR Executive,34015,0 +119341,Female,56,Masters,15,48,76,19,89,0.0,1,32,Urban,HR Executive,31264,0 +119342,Female,47,Bachelors,15,63,97,64,86,5.0,6,10,Rural,HR Executive,64760,0 +119343,Female,24,Diploma,18,43,36,38,30,5.0,4,13,Urban,Software Engineer,73831,0 +119344,Female,21,Bachelors,3,38,99,6,69,5.0,1,72,Urban,Data Analyst,43109,0 +119345,Female,39,Diploma,1,55,68,4,59,4.0,4,19,Semi-Urban,Software Engineer,129242,0 +119346,Female,29,Masters,15,55,14,41,81,8.0,6,40,Urban,Data Analyst,141104,0 +119347,Male,54,High School,1,26,59,36,24,8.0,7,58,Urban,HR Executive,74906,0 +119348,Male,59,Masters,7,96,72,62,25,2.0,7,58,Urban,Manager,108201,1 +119349,Male,37,High School,7,72,46,53,36,3.0,1,29,Rural,Manager,139051,0 +119350,Female,54,PhD,3,62,91,64,93,6.0,0,41,Urban,Manager,127724,1 +119351,Male,28,Bachelors,8,55,16,39,57,5.0,1,27,Semi-Urban,Data Analyst,140598,0 +119352,Female,56,Bachelors,19,82,33,38,86,2.0,3,50,Urban,Software Engineer,31922,0 +119353,Male,54,Masters,19,47,50,75,98,0.0,5,24,Rural,Software Engineer,103300,0 +119354,Male,50,PhD,7,47,62,62,40,2.0,5,92,Urban,ML Engineer,37286,1 +119355,Male,40,Diploma,0,77,93,99,5,5.0,7,69,Urban,Software Engineer,62202,1 +119356,Male,34,PhD,18,17,66,19,3,2.0,3,68,Urban,ML Engineer,56049,0 +119357,Male,28,Bachelors,9,97,87,69,95,1.0,1,7,Urban,Data Analyst,96632,1 +119358,Female,39,Bachelors,13,86,81,45,44,4.0,5,11,Semi-Urban,Manager,118650,0 +119359,Female,39,Masters,11,81,6,2,19,4.0,2,24,Semi-Urban,ML Engineer,51996,0 +119360,Male,49,Masters,10,6,87,85,95,8.0,7,66,Semi-Urban,ML Engineer,99974,1 +119361,Female,43,Masters,2,23,76,61,55,8.0,0,96,Urban,Data Analyst,69281,1 +119362,Male,40,Bachelors,7,47,13,68,93,9.0,2,12,Urban,Software Engineer,121680,0 +119363,Male,56,Diploma,16,73,43,33,49,4.0,5,35,Urban,ML Engineer,90707,0 +119364,Male,51,Bachelors,0,67,28,39,3,0.0,4,48,Semi-Urban,Software Engineer,38645,0 +119365,Female,38,Bachelors,18,81,23,93,45,0.0,6,43,Urban,Manager,27889,0 +119366,Female,26,High School,13,37,79,47,50,0.0,0,53,Urban,Software Engineer,58984,0 +119367,Male,22,High School,4,25,65,30,65,8.0,7,91,Semi-Urban,ML Engineer,137272,0 +119368,Female,31,Masters,9,74,41,42,71,4.0,3,53,Urban,ML Engineer,21881,0 +119369,Female,33,Masters,19,31,74,39,49,9.0,3,69,Semi-Urban,Data Analyst,42525,0 +119370,Female,40,Bachelors,11,29,43,15,83,2.0,4,73,Urban,ML Engineer,65280,0 +119371,Male,48,High School,11,51,58,75,45,3.0,5,42,Semi-Urban,ML Engineer,98227,0 +119372,Male,52,Masters,7,4,22,95,33,2.0,5,62,Semi-Urban,Data Analyst,107726,0 +119373,Female,56,High School,4,43,18,40,6,9.0,0,46,Semi-Urban,Data Analyst,79593,0 +119374,Other,42,Bachelors,15,13,42,17,88,0.0,6,27,Urban,ML Engineer,87505,0 +119375,Male,43,High School,10,84,88,15,15,3.0,1,21,Semi-Urban,Manager,30744,0 +119376,Male,31,Bachelors,15,23,20,81,89,1.0,5,94,Rural,ML Engineer,114682,0 +119377,Male,24,Bachelors,9,86,86,51,86,3.0,7,90,Urban,Data Analyst,133039,1 +119378,Male,32,Masters,6,14,77,88,26,4.0,6,79,Urban,Software Engineer,110310,1 +119379,Male,23,High School,14,84,28,35,13,2.0,4,7,Urban,Software Engineer,135722,0 +119380,Male,57,Bachelors,18,99,46,1,12,4.0,1,87,Urban,Data Analyst,124474,0 +119381,Male,52,Bachelors,16,17,48,90,55,9.0,1,61,Urban,Data Analyst,146114,0 +119382,Male,58,High School,17,45,30,18,71,7.0,7,39,Urban,Manager,40868,0 +119383,Female,54,High School,5,16,9,62,50,5.0,0,81,Semi-Urban,Data Analyst,99425,0 +119384,Male,49,Bachelors,10,67,70,8,62,8.0,3,75,Semi-Urban,Manager,43004,0 +119385,Male,51,Masters,15,91,81,38,47,9.0,4,95,Semi-Urban,HR Executive,69129,1 +119386,Male,58,Bachelors,0,64,97,29,51,6.0,4,85,Urban,HR Executive,139181,1 +119387,Other,21,Bachelors,5,0,39,51,76,5.0,6,5,Urban,HR Executive,105805,0 +119388,Female,45,Bachelors,1,0,5,47,0,6.0,5,71,Urban,ML Engineer,144947,0 +119389,Male,59,Masters,18,49,55,81,90,8.0,7,6,Semi-Urban,Data Analyst,29671,0 +119390,Female,28,High School,4,21,35,14,77,1.0,3,22,Urban,HR Executive,74213,0 +119391,Female,40,Masters,18,61,65,59,74,8.0,1,36,Urban,Manager,44458,0 +119392,Female,24,Bachelors,7,10,89,44,7,2.0,7,89,Urban,Software Engineer,108752,0 +119393,Female,37,Diploma,13,78,62,30,97,9.0,2,56,Urban,Software Engineer,38248,0 +119394,Male,31,Masters,4,40,36,89,37,3.0,0,50,Semi-Urban,Software Engineer,141983,0 +119395,Male,36,Masters,11,42,73,6,57,0.0,6,5,Semi-Urban,ML Engineer,59178,0 +119396,Female,28,Diploma,16,28,93,34,14,0.0,4,39,Urban,Manager,104516,0 +119397,Male,27,Bachelors,18,9,13,5,41,0.0,5,22,Urban,ML Engineer,65534,0 +119398,Male,55,High School,1,37,34,68,66,3.0,3,89,Urban,ML Engineer,34239,0 +119399,Female,29,Bachelors,5,16,55,3,33,7.0,7,76,Urban,HR Executive,128006,0 +119400,Male,47,Masters,7,96,17,89,9,9.0,0,22,Rural,Software Engineer,132982,0 +119401,Female,21,Bachelors,16,50,99,79,65,8.0,4,28,Urban,Manager,62295,1 +119402,Female,51,High School,17,19,98,53,51,1.0,6,20,Rural,Software Engineer,107460,0 +119403,Male,24,Diploma,19,4,3,40,30,7.0,0,89,Rural,Manager,84212,0 +119404,Male,34,Diploma,3,28,52,33,86,6.0,2,7,Semi-Urban,HR Executive,102493,0 +119405,Male,45,Bachelors,18,29,31,63,77,0.0,2,93,Semi-Urban,Data Analyst,21092,0 +119406,Other,58,High School,13,78,89,51,15,1.0,7,99,Rural,ML Engineer,96006,1 +119407,Male,56,Masters,16,87,1,35,61,2.0,3,20,Urban,Data Analyst,144848,0 +119408,Female,31,Diploma,8,65,92,96,54,2.0,3,45,Urban,Manager,137843,1 +119409,Other,52,High School,9,83,63,18,8,9.0,4,52,Semi-Urban,HR Executive,89262,0 +119410,Male,31,Bachelors,17,86,16,2,25,5.0,1,1,Semi-Urban,Data Analyst,75215,0 +119411,Male,47,Bachelors,3,49,18,81,87,3.0,2,61,Semi-Urban,ML Engineer,96144,0 +119412,Female,37,Bachelors,6,80,73,26,8,4.0,4,22,Urban,Manager,138124,0 +119413,Male,45,Bachelors,8,30,95,50,53,9.0,4,84,Urban,ML Engineer,45960,1 +119414,Male,21,Bachelors,5,0,31,73,21,5.0,6,65,Urban,ML Engineer,147373,0 +119415,Male,31,High School,16,86,94,14,46,3.0,3,73,Urban,ML Engineer,124568,1 +119416,Male,37,Bachelors,2,45,35,37,49,6.0,1,23,Semi-Urban,Software Engineer,145139,0 +119417,Male,46,Bachelors,17,62,43,22,6,7.0,7,18,Rural,HR Executive,38382,0 +119418,Female,36,Masters,18,95,47,46,97,7.0,6,17,Semi-Urban,Software Engineer,136151,0 +119419,Male,56,Masters,7,76,95,97,19,2.0,1,73,Rural,ML Engineer,76675,1 +119420,Other,53,Bachelors,6,85,1,14,31,2.0,4,55,Semi-Urban,ML Engineer,101419,0 +119421,Male,51,Diploma,11,42,52,7,89,5.0,6,84,Urban,Manager,130972,0 +119422,Other,24,Bachelors,5,28,2,26,68,1.0,2,4,Semi-Urban,Data Analyst,130235,0 +119423,Female,48,Masters,19,75,0,86,62,9.0,7,85,Urban,Manager,54144,1 +119424,Female,38,Bachelors,9,66,81,60,48,4.0,7,87,Urban,Manager,74001,1 +119425,Female,22,Bachelors,3,67,90,33,55,9.0,4,96,Urban,Data Analyst,145766,1 +119426,Female,57,Bachelors,10,28,57,27,58,3.0,1,98,Urban,Software Engineer,21858,0 +119427,Male,57,Bachelors,17,33,67,6,56,9.0,3,87,Semi-Urban,HR Executive,77733,0 +119428,Female,23,Diploma,12,9,10,84,87,9.0,2,89,Semi-Urban,Software Engineer,41049,0 +119429,Male,55,Bachelors,13,61,76,50,9,8.0,1,30,Urban,HR Executive,81541,0 +119430,Male,52,Bachelors,5,28,84,31,83,0.0,1,79,Rural,Data Analyst,138652,0 +119431,Male,25,Masters,8,59,21,83,61,9.0,0,64,Urban,HR Executive,61098,0 +119432,Male,43,Bachelors,0,84,65,5,79,6.0,1,10,Semi-Urban,ML Engineer,119296,0 +119433,Male,24,PhD,4,52,18,67,60,8.0,7,18,Semi-Urban,Manager,73960,0 +119434,Male,55,Bachelors,16,50,77,64,82,1.0,4,14,Urban,Data Analyst,116187,0 +119435,Male,30,Bachelors,3,68,89,31,22,5.0,1,26,Urban,Manager,148332,0 +119436,Male,57,Masters,3,77,39,53,96,7.0,7,48,Urban,Software Engineer,99013,0 +119437,Female,30,Bachelors,18,24,33,64,82,0.0,3,43,Semi-Urban,Software Engineer,133221,0 +119438,Female,35,High School,12,17,14,96,82,4.0,5,77,Rural,Software Engineer,143910,0 +119439,Male,22,Diploma,11,7,20,2,67,2.0,6,65,Urban,HR Executive,34363,0 +119440,Female,27,High School,13,9,57,28,58,1.0,0,55,Urban,Software Engineer,93695,0 +119441,Female,41,Bachelors,2,52,34,55,34,8.0,2,66,Urban,Manager,127001,0 +119442,Female,34,Bachelors,13,47,32,44,97,7.0,1,90,Urban,Data Analyst,52436,0 +119443,Female,52,Masters,12,34,27,15,1,6.0,0,42,Urban,Manager,121000,0 +119444,Male,45,Diploma,6,62,54,44,93,9.0,4,95,Rural,Manager,126512,1 +119445,Female,27,Bachelors,12,96,65,5,35,3.0,4,18,Semi-Urban,Manager,147838,0 +119446,Male,44,High School,8,49,52,87,57,7.0,7,70,Urban,Data Analyst,61188,1 +119447,Male,37,Bachelors,13,99,76,8,11,2.0,3,37,Urban,Manager,82849,0 +119448,Female,51,Bachelors,14,54,73,20,33,0.0,3,35,Urban,Data Analyst,54103,0 +119449,Male,37,Bachelors,18,61,16,7,47,7.0,1,51,Semi-Urban,HR Executive,56030,0 +119450,Male,26,Masters,17,21,57,96,58,8.0,1,75,Urban,ML Engineer,44345,1 +119451,Male,54,Masters,8,81,67,80,30,1.0,5,33,Semi-Urban,Software Engineer,125934,1 +119452,Female,59,Bachelors,1,27,72,2,2,3.0,0,88,Urban,Data Analyst,51677,0 +119453,Female,33,Masters,18,70,3,23,69,2.0,5,62,Semi-Urban,ML Engineer,143826,0 +119454,Male,54,Diploma,0,16,25,65,27,4.0,3,71,Urban,Software Engineer,113472,0 +119455,Male,22,Bachelors,15,61,95,26,42,1.0,2,1,Semi-Urban,Manager,136221,0 +119456,Male,37,Masters,2,87,16,23,6,4.0,5,87,Semi-Urban,ML Engineer,34779,0 +119457,Male,59,Bachelors,6,39,30,48,47,5.0,1,45,Urban,Software Engineer,88434,0 +119458,Male,25,Bachelors,19,67,34,17,76,9.0,0,67,Semi-Urban,HR Executive,21966,0 +119459,Female,32,High School,10,83,46,40,57,7.0,1,80,Rural,HR Executive,97066,1 +119460,Other,43,Bachelors,12,46,63,73,89,3.0,5,75,Urban,Software Engineer,106834,1 +119461,Female,36,Bachelors,14,61,48,10,85,2.0,6,5,Urban,ML Engineer,93264,0 +119462,Male,26,Diploma,13,67,15,58,42,6.0,7,3,Semi-Urban,Manager,31859,0 +119463,Female,40,Bachelors,13,84,12,87,52,1.0,4,85,Rural,ML Engineer,117432,1 +119464,Other,51,Bachelors,7,71,33,45,9,4.0,2,8,Urban,Manager,147800,0 +119465,Male,34,Masters,5,49,44,80,84,6.0,3,29,Urban,ML Engineer,47571,0 +119466,Male,49,Bachelors,16,60,21,63,85,7.0,6,14,Urban,HR Executive,64137,0 +119467,Male,54,Bachelors,10,14,64,47,93,9.0,7,21,Urban,ML Engineer,93689,0 +119468,Female,50,Bachelors,19,8,3,45,24,3.0,5,95,Urban,Manager,90166,0 +119469,Female,57,High School,0,81,18,57,50,2.0,5,80,Urban,HR Executive,58918,0 +119470,Male,24,Bachelors,0,99,82,70,19,9.0,4,68,Urban,ML Engineer,81139,1 +119471,Male,44,Bachelors,14,4,84,72,77,3.0,7,33,Urban,Software Engineer,122038,0 +119472,Male,22,High School,2,24,23,48,4,7.0,0,4,Rural,HR Executive,46722,0 +119473,Male,31,High School,16,89,37,20,2,7.0,6,42,Semi-Urban,Manager,123881,0 +119474,Male,58,Diploma,16,18,95,26,99,6.0,6,59,Urban,ML Engineer,125852,0 +119475,Male,47,Bachelors,13,29,90,51,60,6.0,4,86,Urban,ML Engineer,91365,1 +119476,Male,28,Bachelors,19,59,98,70,54,4.0,4,28,Urban,Software Engineer,42702,1 +119477,Male,43,Bachelors,4,59,6,14,68,9.0,3,13,Urban,ML Engineer,81784,0 +119478,Female,36,High School,17,48,42,67,82,9.0,0,44,Semi-Urban,Data Analyst,133304,0 +119479,Male,53,Masters,4,80,81,27,67,6.0,6,17,Urban,ML Engineer,41312,0 +119480,Male,49,Diploma,5,42,82,13,67,0.0,0,66,Urban,Data Analyst,73440,0 +119481,Female,56,High School,0,83,81,89,71,4.0,5,95,Urban,HR Executive,43122,1 +119482,Male,28,High School,0,54,55,57,11,6.0,1,55,Urban,Data Analyst,60411,0 +119483,Male,41,Bachelors,2,90,33,25,20,2.0,6,83,Semi-Urban,Manager,60276,0 +119484,Male,45,Masters,5,35,31,12,31,8.0,5,80,Semi-Urban,ML Engineer,75399,0 +119485,Female,36,High School,19,3,12,30,23,6.0,1,63,Rural,HR Executive,121401,0 +119486,Male,34,Diploma,12,49,40,60,34,5.0,4,31,Urban,HR Executive,148079,0 +119487,Male,42,Diploma,13,64,23,71,99,0.0,6,82,Semi-Urban,ML Engineer,32438,1 +119488,Female,21,High School,10,6,13,99,56,3.0,2,66,Rural,Manager,54399,0 +119489,Female,45,Diploma,1,31,51,98,74,8.0,7,43,Semi-Urban,Software Engineer,106368,0 +119490,Male,47,High School,8,39,68,30,80,4.0,6,71,Semi-Urban,Manager,50225,0 +119491,Male,27,Bachelors,2,66,97,21,82,5.0,6,6,Urban,Manager,97165,0 +119492,Male,36,Diploma,12,61,69,32,43,2.0,5,42,Urban,Manager,77848,0 +119493,Male,38,Bachelors,13,78,26,86,16,2.0,4,23,Urban,HR Executive,70804,0 +119494,Male,24,Bachelors,7,49,67,44,52,0.0,4,23,Rural,ML Engineer,72017,0 +119495,Male,38,Bachelors,6,95,66,62,84,0.0,6,35,Semi-Urban,HR Executive,148463,1 +119496,Male,37,Masters,18,48,72,71,73,5.0,7,65,Urban,Data Analyst,32480,1 +119497,Female,56,Masters,5,63,38,63,81,1.0,4,95,Urban,ML Engineer,145434,1 +119498,Male,25,Masters,2,35,83,40,36,5.0,0,0,Semi-Urban,HR Executive,128826,0 +119499,Female,51,Masters,17,26,6,79,21,5.0,7,50,Urban,Manager,127307,0 +119500,Male,54,Bachelors,10,38,86,8,67,3.0,3,17,Rural,HR Executive,76908,0 +119501,Female,41,Bachelors,19,5,79,60,59,5.0,7,7,Urban,Data Analyst,86236,0 +119502,Female,25,Masters,8,58,63,86,7,7.0,5,68,Urban,Software Engineer,58895,1 +119503,Female,23,High School,19,46,96,53,25,8.0,3,71,Urban,Software Engineer,84925,1 +119504,Female,43,Masters,16,61,44,3,7,8.0,4,62,Urban,ML Engineer,29030,0 +119505,Male,50,Diploma,12,83,87,39,35,0.0,0,53,Urban,ML Engineer,53764,1 +119506,Male,21,High School,15,19,10,18,24,2.0,1,19,Urban,Data Analyst,85226,0 +119507,Female,56,Bachelors,1,22,91,90,39,2.0,5,53,Urban,Software Engineer,33742,1 +119508,Male,51,Bachelors,2,33,80,47,31,1.0,5,72,Urban,Software Engineer,27696,0 +119509,Male,25,PhD,13,68,75,62,8,2.0,2,7,Urban,Data Analyst,124757,0 +119510,Male,43,Bachelors,0,20,89,37,85,0.0,2,34,Urban,Data Analyst,121558,0 +119511,Female,37,Bachelors,3,10,97,54,80,8.0,2,76,Urban,HR Executive,93528,0 +119512,Female,24,Bachelors,2,45,38,60,11,6.0,4,8,Rural,ML Engineer,92519,0 +119513,Male,52,Diploma,4,3,2,6,41,7.0,5,93,Urban,HR Executive,141785,0 +119514,Other,37,Masters,9,25,60,9,12,8.0,7,87,Semi-Urban,Data Analyst,85356,0 +119515,Male,27,Bachelors,3,49,69,54,74,1.0,3,35,Urban,Manager,60547,0 +119516,Male,43,Bachelors,5,62,67,77,90,8.0,0,91,Urban,Manager,135430,1 +119517,Male,59,Bachelors,15,28,3,63,19,2.0,4,60,Urban,ML Engineer,129043,0 +119518,Female,35,Diploma,11,59,14,66,30,0.0,3,91,Urban,Manager,64896,0 +119519,Male,21,Diploma,13,69,14,69,66,1.0,3,87,Urban,ML Engineer,51530,1 +119520,Male,38,Bachelors,2,37,48,40,56,7.0,1,14,Urban,Data Analyst,43977,0 +119521,Other,26,Diploma,15,98,9,73,25,7.0,4,87,Semi-Urban,Software Engineer,63315,1 +119522,Male,39,Bachelors,10,80,54,4,56,7.0,0,75,Urban,HR Executive,34387,0 +119523,Male,29,High School,3,12,31,34,34,1.0,1,15,Semi-Urban,ML Engineer,28949,0 +119524,Male,53,Masters,9,71,23,29,52,2.0,1,9,Urban,ML Engineer,69434,0 +119525,Male,40,High School,3,79,68,94,40,8.0,6,21,Semi-Urban,ML Engineer,76807,1 +119526,Male,32,Masters,18,14,83,30,91,9.0,6,30,Urban,Software Engineer,33565,0 +119527,Female,45,High School,0,50,57,11,6,0.0,5,9,Semi-Urban,Manager,26177,0 +119528,Male,46,Bachelors,16,4,32,37,73,6.0,7,54,Semi-Urban,Manager,102582,0 +119529,Male,41,Bachelors,14,67,35,74,3,5.0,7,18,Urban,HR Executive,109611,0 +119530,Male,23,Bachelors,6,83,13,3,85,5.0,2,34,Urban,Manager,74184,0 +119531,Male,48,PhD,16,0,9,93,57,8.0,6,34,Urban,HR Executive,84861,0 +119532,Female,47,Bachelors,0,83,19,8,11,5.0,3,90,Urban,HR Executive,149218,0 +119533,Male,25,Masters,6,68,19,41,53,0.0,2,15,Semi-Urban,Data Analyst,76388,0 +119534,Female,28,Bachelors,19,70,65,43,53,3.0,2,56,Urban,HR Executive,109143,0 +119535,Female,27,Bachelors,11,76,70,93,32,0.0,4,33,Rural,HR Executive,141066,1 +119536,Female,40,Diploma,13,33,97,76,15,6.0,5,43,Urban,Software Engineer,31701,1 +119537,Female,32,High School,5,71,40,16,57,6.0,0,88,Urban,Software Engineer,89590,0 +119538,Female,33,High School,15,3,80,56,56,3.0,0,23,Urban,Manager,114317,0 +119539,Male,27,Masters,18,93,19,45,88,1.0,4,23,Semi-Urban,Manager,80447,0 +119540,Male,36,Bachelors,7,54,84,37,62,1.0,1,60,Urban,ML Engineer,83798,1 +119541,Male,27,Bachelors,1,13,15,62,40,0.0,1,19,Rural,Software Engineer,68674,0 +119542,Male,59,Bachelors,1,94,39,77,45,9.0,0,22,Urban,ML Engineer,50841,0 +119543,Female,56,Diploma,2,53,8,95,1,0.0,7,51,Urban,HR Executive,39975,0 +119544,Male,28,Masters,19,37,30,13,32,1.0,1,31,Urban,Manager,117560,0 +119545,Male,44,Bachelors,7,85,32,98,3,0.0,7,42,Urban,Data Analyst,76388,1 +119546,Male,31,Masters,12,94,63,96,8,1.0,3,54,Urban,Data Analyst,97671,1 +119547,Male,40,Masters,10,23,32,78,88,4.0,3,36,Semi-Urban,Manager,98811,0 +119548,Female,30,Bachelors,7,84,43,73,29,9.0,7,1,Semi-Urban,Data Analyst,59430,0 +119549,Female,55,Bachelors,19,68,65,17,44,8.0,7,78,Semi-Urban,Data Analyst,115321,0 +119550,Male,48,Bachelors,11,49,62,82,96,5.0,5,85,Urban,Manager,144269,1 +119551,Female,23,PhD,18,69,32,46,8,1.0,1,28,Semi-Urban,Manager,51115,0 +119552,Male,31,Diploma,7,31,57,45,15,4.0,6,7,Rural,Manager,69373,0 +119553,Male,31,Masters,15,64,2,43,66,8.0,2,29,Urban,ML Engineer,40002,0 +119554,Male,30,Diploma,18,78,64,14,72,3.0,4,49,Urban,HR Executive,35079,0 +119555,Female,28,Masters,8,17,47,59,35,6.0,6,85,Urban,Manager,104593,0 +119556,Female,52,Bachelors,14,40,38,83,5,4.0,5,19,Urban,Data Analyst,135765,0 +119557,Male,51,Bachelors,17,87,26,90,22,9.0,4,0,Rural,ML Engineer,116580,0 +119558,Male,24,Bachelors,8,22,60,24,92,2.0,4,94,Urban,Manager,82097,0 +119559,Male,53,High School,5,81,9,7,31,2.0,0,37,Semi-Urban,Software Engineer,26304,0 +119560,Female,55,Diploma,9,66,96,88,6,3.0,2,70,Semi-Urban,Software Engineer,101670,1 +119561,Male,43,Masters,5,1,30,93,33,8.0,1,45,Urban,Software Engineer,87676,0 +119562,Female,50,Bachelors,8,75,72,36,32,5.0,4,13,Urban,Software Engineer,80059,0 +119563,Male,41,Bachelors,7,13,49,3,47,9.0,3,0,Semi-Urban,ML Engineer,120827,0 +119564,Female,45,High School,9,64,19,17,65,4.0,3,90,Semi-Urban,ML Engineer,82188,0 +119565,Male,26,Bachelors,4,95,42,95,59,4.0,5,6,Rural,Manager,132437,1 +119566,Male,51,Diploma,8,33,5,89,33,5.0,1,61,Urban,Software Engineer,75447,0 +119567,Female,58,Bachelors,16,54,22,88,50,0.0,2,16,Urban,ML Engineer,111595,0 +119568,Male,40,Bachelors,14,61,27,42,28,9.0,4,96,Semi-Urban,Data Analyst,39518,0 +119569,Female,28,PhD,7,73,92,51,0,4.0,1,88,Urban,HR Executive,78620,1 +119570,Male,37,High School,6,54,24,85,84,5.0,6,47,Rural,ML Engineer,87365,0 +119571,Female,50,Bachelors,11,33,45,92,22,8.0,6,87,Rural,ML Engineer,97273,1 +119572,Male,48,Bachelors,8,73,7,16,42,6.0,4,49,Rural,Manager,37934,0 +119573,Female,51,Bachelors,11,48,84,63,75,7.0,3,18,Urban,ML Engineer,80820,0 +119574,Female,43,Masters,4,56,42,72,59,0.0,4,76,Urban,ML Engineer,105864,1 +119575,Male,53,High School,14,16,79,80,84,2.0,2,14,Semi-Urban,Software Engineer,45956,0 +119576,Female,49,High School,10,90,41,64,71,5.0,1,80,Urban,Data Analyst,56563,1 +119577,Male,55,Bachelors,15,93,92,44,53,2.0,2,94,Urban,Software Engineer,96515,1 +119578,Male,25,Bachelors,11,30,87,91,72,2.0,6,9,Rural,Manager,37716,0 +119579,Female,52,Masters,18,96,32,14,3,8.0,2,15,Semi-Urban,Data Analyst,83450,0 +119580,Male,33,High School,7,25,69,49,62,8.0,0,94,Rural,ML Engineer,83771,1 +119581,Female,36,Bachelors,0,85,40,63,63,5.0,2,32,Semi-Urban,Software Engineer,78421,0 +119582,Male,40,Bachelors,2,5,58,60,87,7.0,2,16,Rural,Data Analyst,122659,0 +119583,Female,41,High School,12,98,40,31,13,8.0,2,26,Urban,Data Analyst,106090,0 +119584,Female,28,Masters,17,35,56,28,75,2.0,6,66,Semi-Urban,ML Engineer,48860,0 +119585,Male,46,Diploma,16,98,4,36,53,9.0,0,40,Urban,Software Engineer,113224,0 +119586,Female,47,High School,14,63,63,50,65,5.0,3,12,Urban,Manager,121710,0 +119587,Male,49,Diploma,7,57,92,11,58,2.0,5,16,Semi-Urban,Manager,120196,0 +119588,Female,44,Masters,0,76,60,28,91,4.0,2,66,Urban,ML Engineer,97820,0 +119589,Male,39,Masters,9,55,48,90,78,3.0,7,66,Urban,Data Analyst,133635,1 +119590,Male,33,Bachelors,17,61,28,5,42,2.0,7,35,Rural,Data Analyst,31403,0 +119591,Male,29,Diploma,9,55,61,16,58,7.0,1,52,Semi-Urban,Manager,46179,0 +119592,Female,58,Masters,3,50,79,36,1,3.0,6,89,Urban,HR Executive,100884,1 +119593,Male,31,Masters,1,30,74,10,12,5.0,0,78,Urban,HR Executive,77757,0 +119594,Female,42,Bachelors,16,9,87,74,27,6.0,3,24,Rural,HR Executive,77186,0 +119595,Male,57,Bachelors,9,62,28,60,6,7.0,6,19,Urban,Software Engineer,102942,0 +119596,Male,31,Bachelors,16,6,51,9,69,1.0,6,76,Semi-Urban,Software Engineer,26916,0 +119597,Female,37,Masters,0,78,28,90,11,2.0,7,53,Urban,ML Engineer,105190,1 +119598,Male,36,Bachelors,15,47,75,32,2,7.0,1,23,Urban,Data Analyst,43390,0 +119599,Female,43,Masters,12,11,64,2,40,9.0,2,19,Urban,Software Engineer,144485,0 +119600,Male,54,Bachelors,11,15,59,40,40,8.0,1,83,Urban,Data Analyst,146493,0 +119601,Male,25,Diploma,3,70,43,73,22,3.0,3,70,Rural,Data Analyst,86668,1 +119602,Female,55,Bachelors,5,68,8,29,9,7.0,6,57,Urban,Software Engineer,147861,0 +119603,Male,48,Diploma,1,62,29,0,83,7.0,5,70,Semi-Urban,HR Executive,48161,0 +119604,Male,48,Bachelors,9,11,62,95,28,6.0,2,85,Urban,HR Executive,87137,1 +119605,Male,36,PhD,6,61,45,38,63,4.0,5,76,Semi-Urban,Software Engineer,37875,0 +119606,Male,41,Bachelors,0,22,11,90,20,6.0,2,93,Urban,ML Engineer,43447,0 +119607,Male,31,Bachelors,11,41,36,65,89,7.0,4,71,Semi-Urban,Software Engineer,71023,0 +119608,Female,32,High School,13,40,6,41,1,4.0,3,72,Urban,ML Engineer,51452,0 +119609,Male,36,Masters,5,45,89,37,24,7.0,4,91,Rural,Software Engineer,111635,1 +119610,Male,53,Bachelors,13,11,89,10,22,6.0,2,32,Urban,Data Analyst,59852,0 +119611,Male,22,Bachelors,11,26,85,34,22,4.0,1,53,Semi-Urban,HR Executive,136726,0 +119612,Female,41,Masters,16,78,35,94,21,8.0,3,44,Semi-Urban,ML Engineer,41475,1 +119613,Female,35,Diploma,17,43,94,46,88,0.0,4,13,Urban,Manager,114956,0 +119614,Female,37,Bachelors,1,45,99,94,94,3.0,2,77,Urban,HR Executive,121520,1 +119615,Female,57,Bachelors,19,71,33,55,50,7.0,6,29,Rural,Data Analyst,99845,0 +119616,Male,22,Diploma,18,1,61,89,92,0.0,7,91,Urban,ML Engineer,66454,1 +119617,Female,23,Bachelors,6,0,73,57,28,2.0,3,92,Rural,Manager,48106,0 +119618,Female,38,Bachelors,14,24,91,6,3,1.0,6,18,Semi-Urban,Manager,56556,0 +119619,Female,50,High School,0,95,43,51,23,7.0,6,10,Rural,Data Analyst,80001,0 +119620,Male,56,Masters,14,87,0,23,60,9.0,1,24,Semi-Urban,Manager,33072,0 +119621,Female,33,High School,5,73,22,19,36,6.0,1,26,Urban,HR Executive,47921,0 +119622,Male,35,Bachelors,11,6,46,49,48,2.0,2,18,Semi-Urban,Manager,147238,0 +119623,Male,58,High School,6,34,98,64,81,7.0,6,46,Urban,Data Analyst,35106,1 +119624,Male,43,Bachelors,2,81,52,72,38,5.0,4,1,Urban,Manager,56204,0 +119625,Female,49,Masters,1,7,58,74,27,2.0,4,64,Semi-Urban,Software Engineer,91315,0 +119626,Male,56,Bachelors,9,16,40,19,34,2.0,6,31,Urban,Manager,42828,0 +119627,Male,54,Diploma,17,23,19,77,15,2.0,7,37,Urban,HR Executive,34735,0 +119628,Male,59,Bachelors,0,65,59,77,26,7.0,3,38,Urban,Manager,82334,1 +119629,Male,56,High School,7,47,29,1,23,9.0,2,82,Semi-Urban,Data Analyst,143717,0 +119630,Male,55,Diploma,4,72,10,85,18,1.0,6,78,Rural,ML Engineer,101405,1 +119631,Female,22,Diploma,8,95,63,17,17,3.0,7,26,Urban,Manager,57813,0 +119632,Female,59,Masters,6,23,38,68,64,8.0,3,29,Urban,Manager,60022,0 +119633,Female,41,PhD,13,10,48,13,92,3.0,7,32,Semi-Urban,ML Engineer,91365,0 +119634,Female,22,Masters,3,61,85,73,67,9.0,7,58,Urban,HR Executive,125937,1 +119635,Male,41,Masters,9,78,70,73,11,8.0,7,37,Rural,ML Engineer,37114,1 +119636,Male,55,Diploma,6,54,50,75,48,8.0,1,57,Semi-Urban,ML Engineer,112368,1 +119637,Male,35,Bachelors,12,30,78,42,63,8.0,5,14,Rural,ML Engineer,129768,0 +119638,Male,30,Diploma,19,97,53,64,18,1.0,7,88,Semi-Urban,HR Executive,97192,1 +119639,Other,39,Diploma,3,75,52,85,13,8.0,5,36,Urban,Data Analyst,139396,1 +119640,Male,50,High School,5,27,59,59,2,5.0,6,40,Urban,Data Analyst,80434,0 +119641,Female,37,Masters,8,24,38,32,78,6.0,5,52,Semi-Urban,Data Analyst,137137,0 +119642,Female,50,PhD,18,12,8,46,18,8.0,7,10,Rural,Data Analyst,134845,0 +119643,Female,41,Diploma,0,83,8,2,60,9.0,4,64,Urban,Data Analyst,137651,0 +119644,Female,21,High School,18,32,8,52,3,8.0,5,93,Rural,ML Engineer,30179,0 +119645,Female,35,Diploma,9,26,93,10,71,3.0,3,98,Urban,ML Engineer,65533,0 +119646,Other,25,Bachelors,19,13,12,83,40,4.0,7,47,Urban,Data Analyst,33129,0 +119647,Male,45,Bachelors,14,50,15,81,61,5.0,6,56,Urban,Software Engineer,114114,0 +119648,Male,46,Diploma,17,24,56,60,35,6.0,0,11,Rural,Manager,106269,0 +119649,Male,35,Diploma,9,27,63,19,21,9.0,1,89,Urban,Data Analyst,63568,0 +119650,Female,54,Diploma,11,41,28,44,58,6.0,5,89,Rural,Data Analyst,126142,0 +119651,Male,26,Bachelors,8,61,84,55,38,6.0,5,13,Semi-Urban,Data Analyst,37361,0 +119652,Female,58,Masters,13,94,30,97,46,1.0,5,13,Semi-Urban,Data Analyst,119262,0 +119653,Male,35,Masters,6,32,69,51,93,7.0,6,64,Urban,HR Executive,27777,0 +119654,Male,51,Masters,6,91,20,43,51,5.0,4,50,Urban,HR Executive,145310,0 +119655,Male,40,Diploma,2,55,53,14,98,5.0,2,67,Semi-Urban,Data Analyst,129380,0 +119656,Female,32,Bachelors,13,43,28,46,36,2.0,1,22,Semi-Urban,Manager,53332,0 +119657,Male,43,PhD,17,59,62,55,51,5.0,3,85,Semi-Urban,Manager,41106,1 +119658,Female,55,PhD,19,5,15,96,98,5.0,5,76,Urban,ML Engineer,56229,0 +119659,Male,50,High School,4,13,14,29,83,0.0,6,46,Semi-Urban,Data Analyst,45137,0 +119660,Male,57,High School,15,43,21,62,91,7.0,1,76,Semi-Urban,Data Analyst,69765,0 +119661,Male,54,Diploma,10,42,81,72,26,9.0,7,47,Rural,Data Analyst,52294,1 +119662,Female,47,High School,8,44,27,70,92,4.0,5,34,Urban,Data Analyst,117009,0 +119663,Female,21,Bachelors,7,9,65,59,38,0.0,0,90,Urban,Data Analyst,70817,0 +119664,Female,35,High School,0,81,99,25,18,0.0,1,41,Rural,ML Engineer,54860,1 +119665,Female,34,Bachelors,4,68,43,59,59,6.0,3,1,Rural,HR Executive,66570,0 +119666,Male,56,Diploma,11,50,34,64,32,5.0,3,39,Semi-Urban,Data Analyst,126252,0 +119667,Male,26,Diploma,19,32,40,35,49,1.0,7,44,Urban,ML Engineer,32167,0 +119668,Female,46,Masters,18,90,29,35,93,6.0,2,92,Urban,Software Engineer,52957,1 +119669,Female,57,Masters,2,49,41,36,18,5.0,2,43,Urban,Manager,59530,0 +119670,Male,33,Bachelors,2,88,39,39,46,3.0,1,33,Urban,Software Engineer,22692,0 +119671,Male,49,Bachelors,19,88,50,77,31,5.0,4,49,Urban,Data Analyst,137946,1 +119672,Male,56,High School,16,57,29,20,33,8.0,0,67,Semi-Urban,Software Engineer,100081,0 +119673,Male,36,Bachelors,12,34,82,41,14,2.0,3,44,Urban,Data Analyst,93663,0 +119674,Female,53,Masters,19,54,62,50,96,5.0,1,76,Rural,ML Engineer,144363,1 +119675,Male,32,Bachelors,7,21,11,55,1,1.0,7,66,Semi-Urban,Data Analyst,108300,0 +119676,Other,24,Bachelors,14,37,63,67,24,3.0,3,66,Urban,Data Analyst,21266,0 +119677,Male,31,High School,3,52,24,70,70,9.0,4,24,Rural,HR Executive,44092,0 +119678,Male,44,Bachelors,4,31,49,46,20,0.0,4,0,Semi-Urban,Manager,100510,0 +119679,Other,25,Masters,18,19,60,89,13,4.0,2,18,Urban,ML Engineer,34456,0 +119680,Female,33,High School,1,17,41,56,93,3.0,1,70,Semi-Urban,Data Analyst,76749,0 +119681,Male,47,Masters,13,39,77,45,34,2.0,1,7,Semi-Urban,Software Engineer,111034,0 +119682,Male,29,Masters,3,31,13,3,21,6.0,0,60,Semi-Urban,HR Executive,29827,0 +119683,Male,38,Diploma,16,5,13,88,5,0.0,4,50,Rural,Data Analyst,71262,0 +119684,Female,53,Diploma,17,93,69,76,36,4.0,4,46,Urban,HR Executive,27835,1 +119685,Male,42,Bachelors,13,62,39,22,80,1.0,0,29,Urban,HR Executive,98709,0 +119686,Female,21,Bachelors,12,70,7,72,86,5.0,4,87,Rural,Software Engineer,114758,0 +119687,Male,26,Bachelors,9,97,25,27,9,6.0,3,89,Urban,Data Analyst,57408,1 +119688,Female,26,Diploma,5,29,55,62,67,2.0,7,78,Semi-Urban,Manager,89485,0 +119689,Female,53,Masters,15,11,14,79,39,0.0,5,29,Semi-Urban,Software Engineer,116383,0 +119690,Male,50,Bachelors,8,82,6,9,41,1.0,5,34,Semi-Urban,Software Engineer,30456,0 +119691,Male,58,Diploma,13,74,87,10,69,3.0,5,15,Urban,Software Engineer,48875,0 +119692,Female,28,Diploma,1,41,54,95,70,1.0,2,83,Urban,Data Analyst,140743,1 +119693,Female,39,High School,10,73,52,99,16,7.0,2,70,Urban,Manager,146385,1 +119694,Female,58,Bachelors,12,14,93,45,24,6.0,0,44,Semi-Urban,Manager,65114,0 +119695,Female,49,Diploma,12,86,4,15,23,1.0,6,57,Semi-Urban,Data Analyst,112184,0 +119696,Male,21,Diploma,1,4,49,47,4,0.0,7,11,Semi-Urban,Manager,70145,0 +119697,Female,36,Masters,6,3,40,33,0,7.0,2,43,Urban,ML Engineer,51258,0 +119698,Female,27,Diploma,13,16,46,72,61,2.0,0,36,Urban,Manager,52618,0 +119699,Male,35,High School,3,38,57,95,69,5.0,0,65,Urban,Manager,139755,1 +119700,Female,59,Bachelors,16,23,41,95,33,9.0,7,95,Rural,Software Engineer,86414,1 +119701,Male,31,High School,9,7,15,87,35,5.0,5,70,Semi-Urban,Manager,141440,0 +119702,Female,47,Masters,4,32,44,7,89,9.0,5,52,Urban,Software Engineer,69357,0 +119703,Male,21,PhD,4,87,1,90,9,8.0,7,3,Semi-Urban,Data Analyst,20397,0 +119704,Female,23,Diploma,0,91,64,57,11,0.0,6,17,Semi-Urban,Manager,91656,0 +119705,Male,21,PhD,2,7,49,3,83,5.0,2,51,Rural,Software Engineer,104091,0 +119706,Male,24,Masters,7,38,27,63,39,3.0,1,75,Urban,HR Executive,136454,0 +119707,Male,25,Masters,7,52,49,58,93,9.0,3,2,Semi-Urban,Software Engineer,95062,0 +119708,Male,23,Bachelors,14,78,73,82,58,9.0,3,86,Urban,ML Engineer,74581,1 +119709,Male,24,Bachelors,8,60,70,85,94,6.0,4,22,Urban,Manager,95858,1 +119710,Male,35,Diploma,0,89,95,64,10,9.0,1,17,Urban,Software Engineer,38907,1 +119711,Male,35,Bachelors,17,92,17,2,39,6.0,5,66,Urban,Software Engineer,56529,0 +119712,Male,27,Diploma,11,62,10,14,77,1.0,1,12,Urban,Data Analyst,104342,0 +119713,Female,29,Bachelors,7,20,69,4,98,7.0,0,13,Rural,HR Executive,36922,0 +119714,Male,30,High School,1,86,86,82,8,8.0,4,71,Urban,Manager,146377,1 +119715,Male,25,High School,11,4,1,59,87,0.0,2,31,Semi-Urban,HR Executive,21609,0 +119716,Female,38,Masters,12,73,86,10,98,3.0,5,94,Semi-Urban,HR Executive,128941,1 +119717,Male,34,High School,12,34,88,96,51,6.0,5,74,Rural,Data Analyst,65763,1 +119718,Male,53,High School,12,79,59,93,12,4.0,6,75,Rural,Software Engineer,98127,1 +119719,Male,28,Bachelors,11,74,57,69,49,1.0,5,90,Urban,Software Engineer,93913,1 +119720,Male,47,Bachelors,1,74,21,38,86,3.0,7,65,Rural,Data Analyst,37381,0 +119721,Female,58,High School,9,91,89,13,71,0.0,3,53,Rural,Manager,127674,1 +119722,Male,55,High School,2,13,77,35,64,0.0,0,64,Urban,Software Engineer,129980,0 +119723,Male,43,Diploma,5,91,86,99,77,0.0,1,99,Urban,Manager,46232,1 +119724,Male,59,Bachelors,6,29,47,88,39,8.0,0,15,Urban,Software Engineer,93617,0 +119725,Male,36,Masters,9,70,0,55,80,1.0,7,13,Urban,HR Executive,45146,0 +119726,Female,31,Masters,11,17,77,40,36,3.0,3,16,Urban,Software Engineer,52292,0 +119727,Female,38,Masters,3,29,26,32,2,6.0,2,74,Urban,HR Executive,106796,0 +119728,Male,39,Bachelors,13,43,73,55,27,9.0,2,68,Urban,HR Executive,25109,1 +119729,Male,27,High School,14,11,84,45,97,8.0,4,76,Urban,HR Executive,132238,0 +119730,Other,29,Masters,5,1,49,25,42,1.0,3,7,Urban,ML Engineer,35094,0 +119731,Male,22,Masters,16,3,1,92,91,1.0,6,1,Urban,HR Executive,84495,0 +119732,Male,48,Bachelors,17,35,11,52,8,5.0,1,14,Urban,Manager,124926,0 +119733,Female,54,Diploma,3,0,56,68,41,3.0,0,87,Urban,ML Engineer,48289,0 +119734,Male,22,Masters,14,20,36,43,19,2.0,5,49,Urban,ML Engineer,111764,0 +119735,Male,52,Bachelors,4,85,98,59,64,5.0,5,21,Urban,ML Engineer,37298,1 +119736,Male,54,Diploma,1,33,69,35,40,3.0,6,70,Urban,Software Engineer,125832,0 +119737,Female,29,High School,8,50,53,6,64,1.0,0,72,Urban,ML Engineer,86712,0 +119738,Female,22,PhD,11,71,57,20,41,7.0,0,22,Urban,ML Engineer,82653,0 +119739,Male,43,Bachelors,4,75,56,31,32,1.0,1,73,Urban,Software Engineer,108033,1 +119740,Male,48,High School,8,27,5,27,40,6.0,4,27,Urban,HR Executive,51463,0 +119741,Male,21,Bachelors,9,70,53,88,62,7.0,0,5,Semi-Urban,Software Engineer,47650,0 +119742,Female,49,Masters,6,24,99,30,79,9.0,7,96,Urban,Software Engineer,106602,1 +119743,Male,25,Bachelors,15,28,34,78,25,1.0,5,77,Urban,HR Executive,141894,0 +119744,Male,44,Bachelors,19,24,27,77,81,0.0,3,46,Urban,ML Engineer,55435,0 +119745,Female,37,Bachelors,18,91,95,88,46,7.0,1,32,Urban,ML Engineer,65487,1 +119746,Female,51,Bachelors,10,68,33,11,1,5.0,5,81,Urban,Data Analyst,127723,0 +119747,Male,24,Bachelors,4,56,43,16,46,7.0,1,37,Urban,ML Engineer,76779,0 +119748,Male,41,High School,1,97,36,87,88,0.0,4,9,Rural,Data Analyst,110569,0 +119749,Female,59,Bachelors,9,80,5,0,50,1.0,5,30,Urban,Data Analyst,80128,0 +119750,Male,39,Masters,2,78,3,4,22,9.0,2,3,Semi-Urban,ML Engineer,73280,0 +119751,Female,35,High School,3,58,32,14,98,8.0,2,30,Urban,ML Engineer,117334,0 +119752,Male,34,High School,5,27,73,15,16,0.0,5,17,Urban,Data Analyst,108180,0 +119753,Male,53,Diploma,3,20,49,7,60,4.0,2,43,Urban,ML Engineer,74719,0 +119754,Male,47,High School,18,94,23,75,55,3.0,4,90,Semi-Urban,Manager,111152,1 +119755,Male,45,Bachelors,13,13,5,62,3,1.0,5,50,Urban,Software Engineer,115350,0 +119756,Female,49,Bachelors,12,24,8,39,17,1.0,0,59,Urban,Manager,40317,0 +119757,Female,27,Bachelors,1,90,76,21,18,3.0,2,59,Urban,Data Analyst,54862,1 +119758,Female,39,Diploma,14,69,44,95,89,3.0,0,86,Urban,Software Engineer,96403,1 +119759,Male,48,High School,9,48,2,40,55,8.0,1,86,Semi-Urban,HR Executive,88681,0 +119760,Female,37,Diploma,6,48,66,42,67,2.0,4,24,Urban,Manager,133779,0 +119761,Male,34,Masters,7,16,28,61,33,7.0,3,87,Semi-Urban,Manager,67305,0 +119762,Male,43,Masters,18,4,80,67,3,8.0,4,87,Semi-Urban,HR Executive,105389,1 +119763,Female,48,Bachelors,17,57,17,76,50,6.0,5,31,Semi-Urban,Manager,99575,0 +119764,Male,55,Bachelors,12,13,84,32,69,6.0,3,41,Urban,HR Executive,125534,0 +119765,Male,26,Bachelors,6,81,81,17,53,7.0,6,30,Urban,HR Executive,127846,0 +119766,Female,58,Masters,11,31,28,0,93,8.0,1,14,Semi-Urban,Data Analyst,114633,0 +119767,Male,40,Bachelors,7,82,48,82,28,2.0,3,18,Rural,Data Analyst,63854,0 +119768,Male,49,Diploma,0,42,37,11,50,9.0,7,40,Semi-Urban,ML Engineer,76342,0 +119769,Other,21,Diploma,14,38,42,87,10,3.0,3,72,Semi-Urban,Software Engineer,22747,0 +119770,Male,58,High School,4,53,85,84,91,9.0,2,28,Rural,Manager,131295,1 +119771,Male,59,Bachelors,16,60,94,75,52,5.0,3,66,Rural,ML Engineer,41954,1 +119772,Female,37,Bachelors,15,88,72,59,65,9.0,2,35,Semi-Urban,Data Analyst,24527,1 +119773,Female,34,Diploma,18,71,51,41,46,6.0,6,86,Rural,ML Engineer,32361,1 +119774,Female,42,High School,6,35,15,72,66,5.0,2,73,Urban,Manager,31692,0 +119775,Female,59,Masters,17,91,51,84,99,3.0,0,94,Semi-Urban,Software Engineer,119666,1 +119776,Female,25,Diploma,8,39,48,66,21,4.0,7,26,Rural,ML Engineer,71339,0 +119777,Female,48,Masters,7,66,45,97,37,6.0,7,35,Urban,ML Engineer,145878,1 +119778,Other,28,Bachelors,16,13,39,91,71,2.0,4,82,Semi-Urban,Data Analyst,80142,0 +119779,Male,36,High School,4,41,3,23,20,6.0,7,36,Urban,Software Engineer,62827,0 +119780,Male,49,Bachelors,13,92,79,38,17,0.0,1,32,Rural,Software Engineer,29379,1 +119781,Male,42,Diploma,2,54,18,9,89,6.0,0,29,Urban,ML Engineer,86815,0 +119782,Male,49,High School,3,7,14,7,50,2.0,7,85,Rural,ML Engineer,67840,0 +119783,Female,23,Diploma,17,14,12,23,90,3.0,7,93,Semi-Urban,Data Analyst,106883,0 +119784,Male,34,Masters,0,49,15,84,26,5.0,3,92,Urban,Software Engineer,122508,1 +119785,Female,34,Diploma,19,51,55,66,84,8.0,3,8,Semi-Urban,Data Analyst,71040,0 +119786,Male,49,Bachelors,1,76,12,34,10,0.0,1,41,Urban,HR Executive,136466,0 +119787,Male,58,High School,19,99,99,10,40,2.0,0,99,Urban,HR Executive,112157,1 +119788,Male,50,Masters,12,69,57,91,20,2.0,1,2,Semi-Urban,HR Executive,96318,0 +119789,Female,53,PhD,12,57,56,63,52,8.0,5,94,Rural,HR Executive,73667,1 +119790,Male,52,Bachelors,7,46,73,88,93,4.0,7,2,Urban,Data Analyst,23720,0 +119791,Male,42,PhD,7,33,12,36,44,1.0,0,68,Urban,Data Analyst,35338,0 +119792,Female,53,High School,15,42,70,84,80,5.0,1,66,Semi-Urban,Software Engineer,68103,1 +119793,Male,46,Bachelors,12,78,22,86,15,3.0,6,62,Urban,Data Analyst,143724,1 +119794,Male,55,Bachelors,18,79,60,58,38,1.0,4,15,Semi-Urban,ML Engineer,44525,0 +119795,Male,50,High School,12,92,42,12,41,9.0,2,52,Urban,Data Analyst,105522,0 +119796,Male,47,High School,17,54,64,39,84,9.0,2,34,Urban,Manager,90436,0 +119797,Male,33,Bachelors,3,51,63,5,72,3.0,6,99,Urban,ML Engineer,52433,0 +119798,Male,26,Bachelors,3,54,84,25,63,9.0,6,51,Urban,HR Executive,109949,0 +119799,Male,21,Bachelors,11,65,18,7,88,3.0,2,1,Rural,HR Executive,91406,0 +119800,Male,48,Bachelors,13,10,94,21,58,3.0,0,56,Urban,Software Engineer,27748,0 +119801,Male,45,Masters,9,15,25,10,97,1.0,2,56,Urban,HR Executive,142050,0 +119802,Male,34,Bachelors,7,15,98,15,2,4.0,5,24,Urban,HR Executive,37158,0 +119803,Male,23,Diploma,10,57,85,39,30,3.0,4,20,Semi-Urban,ML Engineer,70179,0 +119804,Female,56,High School,11,14,49,4,81,8.0,2,6,Urban,Software Engineer,47465,0 +119805,Male,50,Bachelors,5,21,61,4,21,3.0,2,71,Rural,HR Executive,47430,0 +119806,Male,39,Masters,5,32,27,78,83,0.0,4,51,Urban,Data Analyst,83269,0 +119807,Male,28,Masters,19,64,29,91,4,5.0,2,77,Urban,HR Executive,122766,1 +119808,Female,52,PhD,0,1,66,35,47,1.0,0,39,Semi-Urban,ML Engineer,31452,0 +119809,Male,27,Bachelors,6,94,93,2,9,4.0,7,79,Urban,Manager,47830,1 +119810,Male,49,High School,14,81,93,98,83,7.0,0,48,Urban,Software Engineer,60544,1 +119811,Other,27,Bachelors,19,62,83,39,84,8.0,6,67,Urban,Data Analyst,131003,1 +119812,Male,57,Masters,0,85,2,68,59,0.0,4,59,Semi-Urban,Data Analyst,144479,0 +119813,Female,38,Bachelors,2,97,67,97,15,7.0,2,14,Urban,ML Engineer,79659,1 +119814,Female,44,Bachelors,17,15,12,9,11,3.0,2,80,Urban,Data Analyst,118879,0 +119815,Male,55,Bachelors,5,27,4,30,90,9.0,5,16,Semi-Urban,ML Engineer,44311,0 +119816,Female,29,Bachelors,19,77,73,96,48,5.0,0,98,Urban,Software Engineer,131933,1 +119817,Female,39,Bachelors,4,18,76,35,47,9.0,1,39,Urban,Software Engineer,62252,0 +119818,Male,22,Diploma,13,55,54,23,60,7.0,2,41,Urban,ML Engineer,53219,0 +119819,Male,47,Bachelors,0,71,22,6,11,0.0,2,51,Urban,Software Engineer,129112,0 +119820,Male,46,Bachelors,18,15,92,38,70,3.0,5,48,Semi-Urban,HR Executive,74238,0 +119821,Male,46,PhD,9,23,65,31,55,9.0,6,45,Semi-Urban,Manager,52116,0 +119822,Male,59,Bachelors,7,72,14,14,59,7.0,7,94,Semi-Urban,Software Engineer,123348,0 +119823,Female,23,Diploma,1,51,39,63,37,8.0,2,59,Semi-Urban,Manager,22950,0 +119824,Male,57,Bachelors,2,80,15,36,0,5.0,2,61,Urban,HR Executive,146157,0 +119825,Male,47,High School,5,91,44,2,97,7.0,7,50,Rural,Manager,56434,0 +119826,Female,45,Diploma,2,59,29,88,14,9.0,6,1,Semi-Urban,HR Executive,71403,0 +119827,Male,48,High School,3,16,3,20,75,6.0,2,55,Urban,Manager,39685,0 +119828,Other,38,Diploma,0,57,17,23,79,2.0,2,59,Semi-Urban,Data Analyst,121939,0 +119829,Female,45,Bachelors,9,58,67,26,72,4.0,3,94,Urban,Manager,23600,1 +119830,Male,54,Bachelors,5,88,50,80,54,2.0,0,68,Urban,Data Analyst,31204,1 +119831,Female,40,Bachelors,6,42,45,94,84,5.0,6,99,Rural,Software Engineer,118907,1 +119832,Other,39,Bachelors,14,3,2,2,5,5.0,4,99,Urban,ML Engineer,82966,0 +119833,Male,23,Bachelors,17,66,99,91,10,6.0,2,37,Urban,Software Engineer,33360,1 +119834,Female,29,Bachelors,16,15,61,34,2,5.0,7,17,Rural,HR Executive,40882,0 +119835,Male,23,Masters,17,19,48,43,42,3.0,3,6,Semi-Urban,ML Engineer,35181,0 +119836,Female,59,PhD,13,15,19,1,85,4.0,1,45,Urban,Data Analyst,117532,0 +119837,Male,47,Masters,9,15,83,63,73,9.0,5,60,Urban,Data Analyst,52752,0 +119838,Female,48,Masters,1,70,17,45,59,0.0,7,72,Semi-Urban,Manager,20278,0 +119839,Male,21,Masters,2,87,12,47,3,8.0,4,65,Rural,ML Engineer,75607,0 +119840,Female,45,Masters,17,58,88,80,14,0.0,0,89,Rural,Manager,29483,1 +119841,Female,45,High School,5,90,8,27,57,0.0,1,44,Semi-Urban,ML Engineer,57428,0 +119842,Female,49,Masters,11,11,17,79,22,1.0,6,33,Semi-Urban,HR Executive,40429,0 +119843,Female,52,Bachelors,15,44,41,25,96,9.0,3,87,Rural,Data Analyst,30569,0 +119844,Male,52,High School,19,69,98,42,2,9.0,3,3,Urban,Manager,135391,0 +119845,Female,36,High School,9,30,31,44,25,5.0,5,26,Urban,Data Analyst,69708,0 +119846,Male,49,Bachelors,4,73,83,37,67,2.0,7,42,Urban,Data Analyst,148714,1 +119847,Male,43,Bachelors,4,13,91,20,74,4.0,4,77,Rural,HR Executive,99685,0 +119848,Male,56,Diploma,6,68,44,90,5,6.0,3,84,Semi-Urban,HR Executive,144035,1 +119849,Male,52,High School,14,6,68,2,83,8.0,4,97,Urban,Software Engineer,60298,0 +119850,Male,55,High School,0,31,90,15,59,6.0,1,11,Urban,ML Engineer,92108,0 +119851,Male,30,High School,15,3,47,78,65,4.0,5,12,Urban,HR Executive,83504,0 +119852,Male,45,Diploma,13,82,29,35,89,9.0,7,4,Semi-Urban,Software Engineer,127313,0 +119853,Male,34,Bachelors,7,1,24,74,82,6.0,5,52,Urban,Data Analyst,75758,0 +119854,Female,30,Diploma,6,43,64,10,20,4.0,7,97,Semi-Urban,Manager,71640,0 +119855,Male,51,Diploma,8,14,44,10,45,0.0,5,56,Semi-Urban,Software Engineer,92773,0 +119856,Male,23,Diploma,5,98,60,97,67,5.0,7,65,Urban,Data Analyst,93777,1 +119857,Female,54,Bachelors,4,89,56,32,84,5.0,1,57,Rural,HR Executive,82521,0 +119858,Male,39,Diploma,0,62,20,83,39,4.0,3,7,Urban,ML Engineer,117603,0 +119859,Male,23,High School,0,74,54,23,72,2.0,1,79,Rural,HR Executive,52774,0 +119860,Female,49,Diploma,5,75,63,35,86,7.0,1,20,Urban,Manager,50255,0 +119861,Male,48,Bachelors,4,10,87,17,83,0.0,0,22,Rural,Software Engineer,121467,0 +119862,Male,53,PhD,1,62,84,48,60,7.0,1,31,Urban,Data Analyst,136346,0 +119863,Female,53,High School,17,91,59,21,85,3.0,3,60,Urban,Data Analyst,116150,0 +119864,Male,56,Diploma,17,81,41,95,42,9.0,3,57,Urban,Software Engineer,43209,1 +119865,Female,46,Diploma,4,97,56,67,48,7.0,1,93,Urban,ML Engineer,57418,1 +119866,Male,42,Diploma,15,97,93,20,54,7.0,1,61,Urban,Data Analyst,122329,1 +119867,Male,25,Bachelors,14,80,44,93,79,4.0,7,41,Urban,ML Engineer,31586,1 +119868,Male,54,Diploma,7,93,11,23,67,4.0,6,33,Rural,Data Analyst,107211,0 +119869,Female,59,Masters,3,77,0,14,75,9.0,6,62,Urban,Software Engineer,138743,0 +119870,Male,36,Diploma,17,36,82,94,5,3.0,2,70,Urban,Manager,51374,1 +119871,Male,57,Masters,10,82,22,59,97,1.0,4,67,Semi-Urban,Software Engineer,36069,0 +119872,Male,31,High School,14,65,77,5,51,6.0,3,46,Rural,Manager,127170,0 +119873,Male,23,High School,8,67,41,91,0,6.0,6,86,Urban,Manager,117173,1 +119874,Female,55,PhD,1,4,0,38,90,6.0,7,27,Rural,HR Executive,51813,0 +119875,Male,46,Bachelors,10,10,31,93,22,6.0,2,76,Urban,Manager,45330,0 +119876,Female,37,Masters,1,56,57,60,13,3.0,5,92,Urban,HR Executive,114297,1 +119877,Female,35,Bachelors,18,85,27,54,27,0.0,0,17,Urban,HR Executive,81227,0 +119878,Female,49,Bachelors,13,64,37,42,47,9.0,2,95,Semi-Urban,HR Executive,149408,0 +119879,Female,39,PhD,8,66,60,1,10,0.0,4,62,Semi-Urban,HR Executive,117443,0 +119880,Male,54,Diploma,19,4,94,10,31,4.0,0,15,Urban,HR Executive,96099,0 +119881,Female,37,Masters,3,86,93,70,67,6.0,4,58,Semi-Urban,Manager,66739,1 +119882,Female,52,Diploma,17,18,88,10,27,4.0,7,7,Rural,ML Engineer,48850,0 +119883,Male,26,Bachelors,19,43,85,16,49,9.0,0,45,Urban,Data Analyst,69429,0 +119884,Female,30,High School,1,6,94,94,19,5.0,5,56,Urban,Manager,130952,1 +119885,Male,52,Masters,1,39,12,26,90,3.0,7,58,Urban,ML Engineer,85165,0 +119886,Female,52,High School,14,25,84,68,78,8.0,2,96,Semi-Urban,HR Executive,129592,1 +119887,Female,59,Masters,11,95,97,75,62,2.0,0,38,Urban,Data Analyst,42936,1 +119888,Male,27,Diploma,16,47,64,51,32,4.0,3,47,Semi-Urban,ML Engineer,24697,0 +119889,Male,56,Bachelors,10,7,98,23,17,7.0,3,97,Rural,Software Engineer,55814,0 +119890,Female,24,Masters,7,70,0,59,56,2.0,4,47,Urban,Data Analyst,90202,0 +119891,Male,21,Diploma,6,24,57,26,38,3.0,0,52,Semi-Urban,Manager,94529,0 +119892,Male,40,Masters,13,42,66,7,48,4.0,1,10,Urban,Data Analyst,99853,0 +119893,Female,47,Bachelors,2,76,63,77,80,3.0,7,10,Semi-Urban,Software Engineer,149119,0 +119894,Female,56,High School,0,30,16,64,5,7.0,3,88,Urban,Manager,82035,0 +119895,Male,41,Masters,4,60,3,5,34,2.0,2,97,Rural,ML Engineer,88698,0 +119896,Male,41,Diploma,9,58,48,21,16,2.0,2,60,Urban,HR Executive,140992,0 +119897,Female,28,Diploma,4,33,99,85,39,8.0,5,26,Urban,Data Analyst,90743,1 +119898,Female,49,High School,11,32,55,7,30,2.0,2,59,Semi-Urban,Manager,101512,0 +119899,Female,55,Diploma,19,67,87,65,28,6.0,2,99,Urban,Software Engineer,149986,1 +119900,Male,26,High School,15,59,22,55,47,6.0,2,18,Urban,HR Executive,54100,0 +119901,Male,46,High School,19,95,12,46,33,2.0,5,81,Urban,Software Engineer,61886,0 +119902,Female,29,Masters,1,92,98,33,35,4.0,7,74,Urban,Data Analyst,48298,1 +119903,Male,42,High School,0,17,72,16,35,3.0,7,44,Urban,Data Analyst,38028,0 +119904,Male,45,Diploma,16,39,13,54,79,1.0,3,95,Semi-Urban,Manager,141211,0 +119905,Male,28,High School,19,17,92,14,10,9.0,0,9,Urban,Manager,87742,0 +119906,Female,34,Masters,5,23,25,42,33,7.0,4,26,Semi-Urban,Data Analyst,94533,0 +119907,Male,23,Bachelors,9,13,80,88,85,7.0,6,68,Semi-Urban,HR Executive,22637,1 +119908,Female,32,Bachelors,7,38,43,96,27,9.0,0,76,Urban,Manager,100490,1 +119909,Male,46,Bachelors,17,98,64,75,29,1.0,6,1,Urban,HR Executive,67295,1 +119910,Female,43,Bachelors,4,27,12,62,41,8.0,2,37,Urban,Data Analyst,79465,0 +119911,Male,47,Bachelors,2,67,53,14,0,7.0,5,69,Semi-Urban,HR Executive,37886,0 +119912,Male,49,Masters,13,39,95,59,97,9.0,7,14,Urban,Manager,86681,0 +119913,Male,35,Diploma,19,75,80,43,65,5.0,6,10,Semi-Urban,Data Analyst,77809,0 +119914,Female,49,Bachelors,0,7,6,63,57,4.0,6,42,Urban,ML Engineer,70144,0 +119915,Female,47,Diploma,11,68,44,7,45,8.0,5,47,Urban,Manager,34139,0 +119916,Female,24,Bachelors,19,90,50,58,89,5.0,5,86,Urban,Manager,104882,1 +119917,Female,49,Diploma,1,70,56,76,15,2.0,4,29,Semi-Urban,ML Engineer,117132,0 +119918,Female,33,Bachelors,2,38,56,63,15,9.0,7,40,Urban,Data Analyst,47148,0 +119919,Male,46,High School,12,36,58,88,2,9.0,1,68,Semi-Urban,Software Engineer,126232,1 +119920,Male,49,Bachelors,5,22,35,40,28,5.0,3,75,Urban,ML Engineer,106327,0 +119921,Male,35,Diploma,15,64,57,69,92,5.0,6,76,Semi-Urban,Manager,109512,1 +119922,Male,33,High School,6,18,38,80,2,7.0,5,36,Urban,Data Analyst,65399,0 +119923,Male,49,High School,12,18,63,52,13,3.0,7,57,Urban,Software Engineer,21860,0 +119924,Male,22,Bachelors,8,66,75,25,28,3.0,0,4,Urban,ML Engineer,22077,0 +119925,Male,52,Bachelors,12,19,90,9,41,0.0,1,63,Rural,ML Engineer,95767,0 +119926,Female,41,Bachelors,19,57,30,95,61,0.0,1,80,Rural,Data Analyst,27812,1 +119927,Female,39,High School,13,39,64,21,70,5.0,3,6,Urban,HR Executive,50862,0 +119928,Male,53,Diploma,4,57,90,92,49,8.0,2,35,Urban,ML Engineer,55320,1 +119929,Male,49,Masters,10,28,32,93,56,6.0,3,90,Semi-Urban,ML Engineer,134627,1 +119930,Male,31,Bachelors,15,49,45,9,27,2.0,4,75,Semi-Urban,ML Engineer,138559,0 +119931,Female,53,Masters,4,18,99,52,50,1.0,5,68,Semi-Urban,Data Analyst,71507,0 +119932,Male,30,PhD,13,1,82,37,64,8.0,3,60,Urban,Software Engineer,138273,0 +119933,Female,29,Diploma,1,61,67,0,39,7.0,7,78,Semi-Urban,ML Engineer,108450,0 +119934,Female,54,Bachelors,13,33,82,72,51,5.0,7,9,Semi-Urban,Software Engineer,23498,0 +119935,Male,26,Bachelors,3,51,96,95,33,3.0,7,76,Urban,Software Engineer,92149,1 +119936,Female,29,Bachelors,16,71,29,51,6,8.0,2,52,Urban,Data Analyst,136520,0 +119937,Female,25,Bachelors,6,3,99,24,10,2.0,4,10,Urban,Data Analyst,75285,0 +119938,Male,27,High School,17,60,88,86,89,4.0,7,96,Urban,HR Executive,40949,1 +119939,Male,24,Bachelors,18,70,98,75,37,0.0,6,70,Rural,Manager,35619,1 +119940,Female,26,High School,17,25,96,25,14,0.0,6,3,Urban,HR Executive,46657,0 +119941,Female,53,High School,4,17,87,47,44,6.0,0,49,Rural,HR Executive,146075,0 +119942,Male,50,Bachelors,2,97,65,5,30,0.0,5,38,Semi-Urban,ML Engineer,79556,0 +119943,Male,39,Bachelors,4,77,90,52,73,2.0,3,6,Urban,Software Engineer,73332,0 +119944,Female,38,High School,2,64,59,85,49,9.0,3,98,Rural,ML Engineer,98691,1 +119945,Male,44,Bachelors,11,65,45,14,10,3.0,1,37,Urban,Software Engineer,22570,0 +119946,Male,22,PhD,14,24,15,56,96,9.0,3,15,Semi-Urban,ML Engineer,109489,0 +119947,Female,58,Bachelors,1,8,74,28,57,4.0,3,10,Urban,ML Engineer,92288,0 +119948,Female,44,Diploma,18,25,72,55,30,5.0,0,78,Semi-Urban,HR Executive,48603,0 +119949,Female,25,Diploma,1,90,47,46,56,5.0,2,7,Urban,Data Analyst,67535,0 +119950,Male,53,PhD,6,39,20,99,96,7.0,5,53,Urban,Manager,76075,0 +119951,Male,52,Masters,7,53,92,75,56,6.0,4,14,Urban,ML Engineer,98531,0 +119952,Other,51,Bachelors,8,34,64,78,80,8.0,7,75,Urban,Software Engineer,46775,1 +119953,Female,49,Bachelors,3,60,0,72,57,0.0,1,62,Rural,HR Executive,130848,0 +119954,Male,22,Bachelors,1,75,23,49,86,3.0,1,99,Semi-Urban,ML Engineer,107624,1 +119955,Male,48,High School,4,83,90,34,28,5.0,1,36,Urban,Software Engineer,49645,1 +119956,Male,28,Diploma,6,75,80,94,92,8.0,4,93,Urban,Software Engineer,24825,1 +119957,Male,22,Bachelors,2,31,90,72,60,6.0,4,31,Semi-Urban,Manager,82880,0 +119958,Female,23,Diploma,7,80,45,68,28,3.0,6,61,Urban,HR Executive,145643,1 +119959,Male,46,Bachelors,15,44,80,97,91,7.0,3,3,Urban,Data Analyst,92908,0 +119960,Male,50,High School,0,12,34,93,18,0.0,1,83,Urban,Data Analyst,29399,0 +119961,Other,48,Masters,18,5,74,25,78,1.0,5,8,Semi-Urban,Manager,108671,0 +119962,Male,40,Bachelors,6,32,51,74,31,1.0,2,18,Urban,Manager,141109,0 +119963,Male,25,Masters,11,50,22,82,70,7.0,1,36,Rural,Software Engineer,139259,0 +119964,Male,38,Diploma,6,19,97,26,4,7.0,4,74,Urban,ML Engineer,44799,0 +119965,Male,33,Bachelors,10,1,86,71,15,0.0,1,24,Rural,ML Engineer,95112,0 +119966,Male,48,Diploma,16,3,64,15,13,3.0,4,67,Rural,Manager,131293,0 +119967,Male,24,Bachelors,8,15,9,7,99,2.0,0,11,Urban,Manager,60717,0 +119968,Male,24,High School,4,37,40,8,37,5.0,1,25,Urban,HR Executive,121004,0 +119969,Male,48,Masters,13,36,7,90,90,4.0,4,31,Semi-Urban,HR Executive,70283,0 +119970,Female,58,Bachelors,13,63,92,30,75,9.0,0,47,Urban,ML Engineer,31356,0 +119971,Male,30,Masters,3,45,29,19,68,0.0,6,55,Urban,ML Engineer,63334,0 +119972,Male,24,High School,5,27,88,76,8,7.0,7,61,Urban,Data Analyst,111078,1 +119973,Female,48,Bachelors,6,60,23,20,36,4.0,6,17,Semi-Urban,HR Executive,97734,0 +119974,Female,52,Bachelors,8,98,29,58,20,2.0,3,51,Semi-Urban,HR Executive,74418,0 +119975,Other,23,Masters,8,25,6,37,23,9.0,7,84,Semi-Urban,ML Engineer,64592,0 +119976,Male,30,Diploma,8,4,24,93,4,4.0,5,45,Rural,ML Engineer,128567,0 +119977,Male,52,Diploma,16,64,1,61,12,0.0,0,24,Semi-Urban,Data Analyst,54109,0 +119978,Female,23,Bachelors,1,99,24,60,33,2.0,7,6,Semi-Urban,Data Analyst,94567,0 +119979,Male,49,Bachelors,0,21,14,95,30,5.0,0,37,Urban,Data Analyst,29084,0 +119980,Male,39,High School,16,89,10,88,87,9.0,6,81,Urban,Manager,79701,1 +119981,Male,35,Bachelors,3,36,1,84,61,9.0,5,41,Urban,ML Engineer,72827,0 +119982,Female,27,Diploma,5,55,73,74,27,1.0,2,67,Urban,Software Engineer,144951,1 +119983,Male,24,Diploma,9,46,4,74,8,6.0,5,30,Urban,Software Engineer,136571,0 +119984,Female,21,Bachelors,19,93,25,89,25,2.0,6,72,Semi-Urban,Manager,106272,1 +119985,Male,53,Masters,7,71,13,48,99,5.0,1,61,Urban,Data Analyst,123800,0 +119986,Male,41,Masters,5,44,37,9,44,2.0,3,14,Semi-Urban,HR Executive,77789,0 +119987,Male,39,High School,19,3,25,41,5,7.0,4,2,Semi-Urban,Manager,93629,0 +119988,Female,34,PhD,3,12,49,34,38,8.0,0,29,Urban,Manager,42754,0 +119989,Male,40,Diploma,19,39,91,71,14,3.0,4,88,Semi-Urban,Data Analyst,123607,1 +119990,Female,44,Bachelors,1,67,34,8,52,8.0,6,61,Urban,Software Engineer,72452,0 +119991,Male,38,Bachelors,2,77,69,96,82,4.0,7,11,Semi-Urban,HR Executive,134584,1 +119992,Female,35,Masters,16,93,54,48,7,6.0,0,99,Urban,ML Engineer,30633,1 +119993,Male,23,Bachelors,7,66,55,43,37,2.0,6,72,Rural,HR Executive,88742,1 +119994,Male,23,Masters,14,40,57,32,32,1.0,1,27,Urban,ML Engineer,28824,0 +119995,Male,36,Masters,8,12,82,90,36,9.0,1,9,Urban,Software Engineer,46522,0 +119996,Male,51,Bachelors,12,36,68,55,98,2.0,6,82,Urban,Software Engineer,115884,1 +119997,Male,54,Masters,11,35,79,0,60,2.0,7,99,Urban,Software Engineer,121326,0 +119998,Male,30,Bachelors,8,18,56,60,22,6.0,0,1,Rural,Manager,63072,0 +119999,Male,30,Bachelors,6,67,99,4,46,0.0,3,66,Rural,Manager,108627,1 +120000,Male,21,Bachelors,19,99,71,63,37,8.0,2,50,Semi-Urban,Manager,137929,1 +54617,Male,27,Bachelors,14,37,12,15,34,3.0,6,41,Urban,ML Engineer,114838,0 +113444,Female,45,High School,17,9,77,53,82,4.0,3,92,Semi-Urban,HR Executive,143736,0 +56546,Male,52,Diploma,9,57,70,77,71,3.0,3,35,Urban,Data Analyst,130894,1 +106396,Male,23,High School,17,19,23,66,20,2.0,2,24,Urban,Software Engineer,104297,0 +51129,Male,49,Bachelors,19,64,29,87,24,3.0,2,92,Urban,ML Engineer,136878,1 +93505,Female,32,Masters,7,6,24,51,99,7.0,0,70,Semi-Urban,Manager,27550,0 +68111,Female,43,High School,8,13,71,45,29,7.0,0,14,Semi-Urban,Software Engineer,53840,0 +41082,Male,39,Diploma,14,18,21,31,7,1.0,6,74,Urban,ML Engineer,29713,0 +103904,Female,37,PhD,2,6,65,30,23,0.0,6,96,Semi-Urban,Manager,78835,0 +100002,Male,51,Bachelors,14,28,0,10,10,0.0,5,90,Urban,Software Engineer,24723,0 +785,Male,37,Masters,5,85,92,52,96,3.0,3,52,Rural,Software Engineer,103855,1 +87332,Female,51,Bachelors,9,87,62,81,81,8.0,7,74,Semi-Urban,HR Executive,129810,1 +50751,Male,28,Bachelors,13,78,46,1,70,2.0,4,97,Urban,Software Engineer,93030,0 +86889,Female,26,Masters,6,29,77,78,11,0.0,1,12,Semi-Urban,Software Engineer,46326,0 +19131,Male,26,Diploma,15,12,4,6,1,2.0,7,50,Semi-Urban,ML Engineer,115869,0 +104903,Female,44,Bachelors,17,86,75,44,22,1.0,3,5,Rural,Manager,26684,0 +82294,Female,24,Masters,7,1,23,92,79,9.0,7,42,Semi-Urban,Data Analyst,125139,0 +57142,Female,46,High School,4,37,52,73,40,9.0,7,28,Rural,ML Engineer,95860,0 +71237,Male,48,Diploma,5,85,3,80,58,1.0,6,2,Semi-Urban,Software Engineer,113409,0 +96197,Male,32,Bachelors,15,14,45,39,64,1.0,5,33,Urban,Software Engineer,115445,0 +105350,Female,42,Bachelors,5,34,16,16,64,4.0,6,10,Urban,Data Analyst,123838,0 +61757,Male,41,Bachelors,12,72,4,24,77,7.0,3,37,Semi-Urban,HR Executive,119593,0 +84514,Male,41,Diploma,19,38,42,85,56,6.0,5,42,Urban,Data Analyst,136338,0 +17936,Female,49,Masters,8,87,74,72,72,5.0,2,39,Urban,Software Engineer,77066,1 +37459,Female,37,PhD,1,63,20,70,83,1.0,1,37,Semi-Urban,Data Analyst,106770,0 +103427,Male,26,Masters,19,81,2,48,34,8.0,4,20,Urban,HR Executive,111966,0 +57379,Female,55,Diploma,17,35,71,27,6,1.0,0,15,Urban,Software Engineer,92995,0 +23446,Male,45,Bachelors,2,15,42,54,70,1.0,4,22,Urban,ML Engineer,100599,0 +81035,Male,23,Bachelors,15,37,38,69,14,9.0,1,57,Rural,Data Analyst,76697,0 +10040,Male,51,Masters,14,45,89,6,81,8.0,2,43,Semi-Urban,Software Engineer,57946,0 +49454,Male,57,Masters,7,70,82,33,7,4.0,1,95,Urban,ML Engineer,88061,1 +113316,Male,42,Diploma,11,7,58,49,81,9.0,2,94,Urban,Software Engineer,30228,0 +13825,Male,59,Bachelors,10,73,46,67,69,5.0,2,11,Semi-Urban,Software Engineer,114683,0 +119411,Male,47,Bachelors,3,49,18,81,87,3.0,2,61,Semi-Urban,ML Engineer,96144,0 +82809,Female,37,Bachelors,7,50,31,33,11,3.0,6,78,Urban,ML Engineer,68296,0 +54460,Male,52,High School,7,89,4,86,87,1.0,5,20,Urban,Software Engineer,24740,0 +95287,Male,58,Bachelors,7,21,24,14,88,2.0,3,56,Rural,Manager,32231,0 +32537,Male,52,Bachelors,9,60,38,93,51,1.0,5,79,Rural,Manager,26667,1 +117064,Male,34,High School,1,45,83,67,29,3.0,1,14,Urban,ML Engineer,85054,0 +48978,Male,51,Bachelors,7,88,51,33,84,1.0,5,2,Rural,Software Engineer,86679,0 +66369,Male,53,Bachelors,3,66,69,94,50,6.0,4,5,Urban,Manager,51694,0 +52405,Male,24,Bachelors,16,53,14,37,66,4.0,2,13,Urban,HR Executive,130560,0 +25977,Male,43,Bachelors,10,76,57,6,26,2.0,0,6,Urban,Manager,141569,0 +91856,Female,38,Bachelors,19,97,0,55,15,2.0,0,91,Urban,Manager,23712,1 +99796,Male,35,Bachelors,7,75,89,5,43,8.0,5,69,Rural,Data Analyst,108092,1 +79658,Female,44,Bachelors,7,98,68,13,99,6.0,2,63,Rural,ML Engineer,75524,1 +39367,Female,44,High School,19,10,54,13,27,3.0,7,43,Semi-Urban,Manager,109054,0 +103493,Male,35,Bachelors,0,94,58,55,27,3.0,0,33,Urban,Data Analyst,115619,1 +58969,Male,23,Masters,12,62,72,94,68,3.0,7,8,Urban,ML Engineer,149219,1 +66011,Male,41,Bachelors,4,97,56,21,42,2.0,2,76,Urban,ML Engineer,89058,1 +60742,Female,53,Diploma,18,12,24,60,93,3.0,7,71,Urban,Software Engineer,37768,0 +30463,Male,36,High School,10,39,66,99,3,1.0,6,1,Urban,Data Analyst,100022,0 +91123,Male,27,Bachelors,6,0,90,86,77,0.0,2,9,Rural,HR Executive,22067,0 +42772,Female,40,Bachelors,3,33,87,98,49,4.0,3,93,Semi-Urban,HR Executive,143789,1 +116079,Female,57,Masters,15,11,57,66,70,6.0,0,88,Urban,Software Engineer,115584,0 +76850,Female,26,Diploma,16,12,95,39,59,3.0,3,14,Urban,Manager,33534,0 +96654,Female,37,Diploma,17,27,61,31,55,9.0,5,92,Rural,Software Engineer,134473,0 +117719,Male,29,High School,19,9,2,7,56,6.0,3,98,Urban,Manager,116612,0 +66843,Other,44,Bachelors,14,88,17,74,76,1.0,1,53,Semi-Urban,Data Analyst,131201,0 +9131,Male,54,High School,7,58,44,15,0,4.0,7,31,Rural,Data Analyst,76938,0 +90567,Male,23,High School,5,61,88,21,83,6.0,5,60,Urban,Software Engineer,73056,0 +96771,Male,23,Bachelors,1,33,88,23,62,5.0,6,14,Urban,Data Analyst,62045,0 +14188,Other,26,Bachelors,13,32,40,76,39,2.0,6,28,Urban,Manager,56062,0 +68213,Female,25,Bachelors,4,61,92,21,88,4.0,6,58,Semi-Urban,ML Engineer,106467,0 +107000,Male,45,Masters,17,64,8,64,32,3.0,6,69,Urban,Data Analyst,71656,0 +41409,Male,48,Masters,8,66,22,79,62,7.0,6,64,Urban,ML Engineer,145314,0 +68979,Male,54,Bachelors,13,87,79,81,10,8.0,1,63,Urban,HR Executive,95424,1 +100923,Female,31,Bachelors,6,91,22,47,79,5.0,0,5,Rural,ML Engineer,107093,0 +32740,Male,57,High School,9,1,77,68,56,3.0,3,50,Rural,Manager,100808,0 +86292,Female,42,High School,10,95,5,99,33,2.0,3,82,Semi-Urban,HR Executive,54818,1 +32208,Male,30,Bachelors,16,60,70,59,44,2.0,6,90,Urban,Data Analyst,79160,1 +38315,Male,41,Bachelors,9,94,38,87,72,7.0,3,57,Semi-Urban,Software Engineer,52494,1 +11927,Male,25,Diploma,15,89,26,20,0,7.0,3,25,Urban,Data Analyst,76433,0 +75610,Male,34,Bachelors,10,16,45,37,25,8.0,0,22,Urban,Software Engineer,102578,0 +119145,Female,37,Bachelors,0,80,44,45,23,3.0,7,37,Semi-Urban,Software Engineer,129704,0 +30110,Male,41,Masters,4,52,75,56,29,0.0,3,18,Semi-Urban,Data Analyst,112456,0 +4586,Other,49,Bachelors,4,4,17,97,84,3.0,0,15,Urban,ML Engineer,54344,0 +83993,Male,49,Diploma,17,86,94,58,48,9.0,5,52,Semi-Urban,Manager,56591,1 +70787,Male,43,High School,4,95,86,28,71,4.0,3,39,Urban,Software Engineer,29898,1 +105661,Female,48,PhD,16,46,37,44,6,2.0,0,48,Rural,Data Analyst,68007,0 +40736,Female,59,Bachelors,10,44,86,70,94,4.0,4,49,Urban,Software Engineer,26466,1 +117820,Female,39,High School,3,63,51,38,16,6.0,4,19,Semi-Urban,Manager,53543,0 +2813,Female,29,Masters,1,12,48,22,29,8.0,5,85,Urban,Software Engineer,143373,0 +102256,Female,27,Masters,16,0,41,29,45,0.0,7,2,Urban,Software Engineer,69766,0 +83728,Female,30,Masters,16,73,45,36,19,5.0,4,70,Urban,Manager,123230,0 +66726,Male,27,High School,7,20,13,18,83,0.0,5,49,Urban,Data Analyst,115138,0 +84409,Other,41,High School,1,61,12,6,62,5.0,0,10,Urban,Software Engineer,85338,0 +14139,Female,57,High School,5,98,84,40,7,6.0,4,66,Semi-Urban,Manager,76936,1 +115964,Male,53,Masters,0,39,74,97,80,8.0,6,98,Urban,Software Engineer,135660,1 +85177,Male,54,Bachelors,5,21,21,58,2,1.0,5,40,Semi-Urban,HR Executive,46030,0 +40254,Female,30,Bachelors,9,75,14,21,69,0.0,7,54,Urban,Data Analyst,84266,0 +9611,Female,23,Bachelors,14,43,53,68,89,8.0,2,3,Urban,HR Executive,144511,0 +94753,Male,23,Bachelors,15,59,78,64,23,2.0,3,60,Rural,HR Executive,118393,1 +77052,Male,33,Diploma,14,49,30,2,91,9.0,2,29,Urban,Data Analyst,138501,0 +41327,Male,40,Diploma,1,8,44,55,90,7.0,0,22,Urban,Software Engineer,133637,0 +36523,Other,25,High School,8,90,17,60,58,9.0,6,51,Urban,Manager,141191,0 +64223,Other,37,Bachelors,6,14,55,72,32,9.0,3,73,Rural,Data Analyst,87277,0 +110830,Female,38,Masters,15,48,83,9,91,2.0,0,12,Rural,Manager,115160,0 +54353,Female,21,High School,9,20,57,22,90,5.0,3,1,Urban,HR Executive,81290,0 +93643,Male,38,Bachelors,7,99,51,35,26,0.0,5,76,Semi-Urban,Manager,48688,1 +19792,Male,35,Diploma,5,55,63,67,50,9.0,2,95,Rural,HR Executive,90919,1 +38130,Female,50,High School,10,25,72,24,30,7.0,5,47,Urban,Manager,87201,0 +52095,Female,57,Diploma,5,79,29,7,5,4.0,4,41,Urban,Software Engineer,88791,0 +5893,Male,52,Bachelors,6,8,23,29,58,0.0,6,85,Urban,Data Analyst,139343,0 +43771,Female,37,Bachelors,13,80,87,89,32,9.0,7,47,Rural,HR Executive,149534,1 +52344,Female,37,High School,0,43,57,50,7,7.0,3,38,Rural,Data Analyst,40520,0 +86115,Female,47,Bachelors,4,12,72,33,29,0.0,4,27,Urban,Data Analyst,138170,0 +2764,Male,29,High School,14,49,12,46,13,1.0,6,96,Semi-Urban,HR Executive,129900,0 +4566,Female,39,Bachelors,11,39,72,37,89,6.0,6,58,Urban,Manager,98237,0 +82227,Male,31,PhD,11,24,38,90,20,8.0,5,7,Semi-Urban,HR Executive,105773,0 +71441,Male,47,Masters,10,53,35,84,60,1.0,3,18,Rural,Manager,33456,0 +47933,Male,58,Bachelors,6,53,22,75,42,9.0,4,83,Urban,Software Engineer,120843,0 +21309,Female,30,Bachelors,14,85,59,41,66,5.0,0,72,Rural,Software Engineer,137155,1 +10220,Male,58,Bachelors,7,84,78,68,33,6.0,7,61,Urban,ML Engineer,44213,1 +95919,Female,24,Bachelors,12,45,44,92,59,0.0,4,62,Urban,Software Engineer,33412,1 +97119,Male,28,Masters,5,92,49,32,80,4.0,3,94,Urban,Data Analyst,41995,1 +75800,Male,36,Bachelors,17,38,60,53,2,6.0,5,47,Urban,Manager,98721,0 +23924,Female,35,Diploma,7,17,54,31,43,3.0,7,60,Urban,HR Executive,88237,0 +50445,Male,41,Masters,17,15,94,72,64,2.0,6,35,Semi-Urban,HR Executive,85107,0 +7298,Male,57,Bachelors,3,34,78,76,95,1.0,3,60,Rural,HR Executive,82263,1 +74259,Male,38,Masters,7,81,7,64,22,7.0,6,15,Semi-Urban,HR Executive,113529,0 +31862,Male,55,Masters,11,24,61,79,24,1.0,2,18,Urban,HR Executive,44117,0 +55654,Male,41,Diploma,11,76,57,64,22,9.0,1,91,Semi-Urban,Data Analyst,149281,1 +96991,Female,36,Masters,18,87,87,76,27,9.0,0,88,Semi-Urban,ML Engineer,53757,1 +37378,Male,58,Diploma,8,41,3,21,96,2.0,0,70,Semi-Urban,Software Engineer,90349,0 +4503,Male,35,High School,14,46,19,31,41,8.0,3,86,Rural,Software Engineer,102618,0 +89272,Female,35,Masters,15,27,19,44,64,0.0,4,76,Urban,HR Executive,50669,0 +96784,Female,30,Bachelors,4,41,78,41,7,3.0,1,68,Rural,HR Executive,100368,0 +85859,Female,43,Diploma,17,84,13,48,41,9.0,6,21,Semi-Urban,Data Analyst,88012,0 +4097,Male,42,Bachelors,5,15,73,61,16,5.0,5,70,Urban,Data Analyst,114647,0 +70396,Male,45,Diploma,3,13,5,32,8,8.0,3,32,Urban,Manager,95166,0 +8272,Male,56,Bachelors,18,55,63,62,90,7.0,0,48,Urban,Manager,147461,0 +101963,Female,22,Masters,14,46,10,26,6,4.0,3,53,Urban,Manager,59753,0 +11757,Female,49,Masters,2,90,65,95,25,8.0,5,33,Semi-Urban,ML Engineer,133393,1 +32745,Male,34,Bachelors,3,36,62,68,77,9.0,6,37,Urban,Manager,103593,0 +7926,Male,25,Masters,3,49,64,60,44,5.0,3,76,Urban,Data Analyst,67635,1 +91527,Male,57,Bachelors,5,7,1,30,63,2.0,7,8,Urban,ML Engineer,124192,0 +82970,Female,41,Masters,8,85,19,94,68,4.0,6,29,Urban,Data Analyst,119224,0 +73741,Male,35,Diploma,17,97,45,68,45,8.0,6,78,Semi-Urban,ML Engineer,67114,1 +61890,Female,44,Diploma,17,3,92,35,36,2.0,3,50,Urban,ML Engineer,48707,0 +176,Male,36,Bachelors,4,39,21,70,58,9.0,0,17,Urban,Software Engineer,127259,0 +17649,Male,26,Diploma,13,79,0,85,1,0.0,2,27,Semi-Urban,HR Executive,76864,0 +81070,Male,55,Diploma,7,36,11,83,88,6.0,2,59,Urban,HR Executive,95299,0 +68827,Male,40,Bachelors,18,45,69,62,11,0.0,6,7,Urban,Software Engineer,95265,0 +94201,Female,40,Masters,7,33,1,60,67,3.0,6,42,Semi-Urban,ML Engineer,121205,0 +19874,Male,57,Diploma,13,83,60,42,16,0.0,5,75,Urban,Data Analyst,109604,1 +49604,Male,40,Bachelors,0,34,10,0,77,1.0,4,58,Urban,Software Engineer,92263,0 +34828,Female,29,Bachelors,10,70,21,76,93,4.0,2,60,Urban,Manager,143499,0 +45367,Female,39,Bachelors,1,46,89,35,69,8.0,0,87,Rural,ML Engineer,29801,1 +71295,Male,44,Diploma,16,87,17,18,93,4.0,5,70,Urban,Manager,103861,0 +50868,Male,59,Diploma,15,70,99,47,5,8.0,1,94,Rural,ML Engineer,78112,1 +87227,Female,33,Diploma,16,45,27,74,76,0.0,2,80,Urban,ML Engineer,146244,0 +30664,Female,24,Bachelors,6,5,91,68,13,0.0,7,95,Urban,HR Executive,58598,1 +88449,Male,24,Diploma,11,49,28,98,17,7.0,5,30,Urban,Data Analyst,92743,0 +76142,Female,27,Bachelors,2,97,52,39,39,3.0,4,60,Urban,ML Engineer,126317,1 +109171,Male,40,Diploma,2,7,78,90,60,2.0,7,68,Rural,ML Engineer,68605,1 +15332,Female,35,Bachelors,18,26,59,10,78,7.0,4,34,Rural,HR Executive,99943,0 +33783,Male,27,Bachelors,9,47,47,69,50,8.0,5,30,Urban,ML Engineer,139821,0 +62127,Female,36,Bachelors,3,66,22,28,90,3.0,3,6,Semi-Urban,Data Analyst,99967,0 +17109,Female,51,Masters,18,38,4,59,91,0.0,6,46,Urban,Data Analyst,87241,0 +104924,Female,55,Masters,10,74,59,32,69,0.0,4,44,Rural,Data Analyst,98916,0 +39045,Female,59,Masters,11,3,83,98,54,9.0,6,91,Rural,Software Engineer,113170,1 +68033,Male,34,Bachelors,8,93,80,11,27,8.0,3,72,Urban,ML Engineer,139999,1 +68612,Male,37,High School,5,1,68,1,1,7.0,6,20,Semi-Urban,HR Executive,118822,0 +18372,Female,54,Bachelors,3,49,78,17,83,0.0,6,7,Urban,Software Engineer,23806,0 +100254,Male,33,High School,5,36,7,48,2,5.0,7,73,Semi-Urban,ML Engineer,113961,0 +7474,Male,48,Masters,11,57,66,61,79,2.0,1,70,Semi-Urban,HR Executive,129026,1 +39494,Female,32,Diploma,4,13,27,28,69,4.0,5,11,Urban,Software Engineer,28872,0 +30877,Male,57,Diploma,16,22,80,32,54,0.0,6,86,Urban,Manager,23433,0 +108963,Male,42,PhD,19,9,9,39,16,4.0,4,61,Rural,Software Engineer,95260,0 +5659,Other,48,Masters,3,99,48,40,3,2.0,0,93,Semi-Urban,Manager,100756,1 +104759,Male,59,Bachelors,14,9,48,49,46,0.0,7,37,Urban,Manager,51930,0 +103008,Female,28,Masters,0,22,36,91,65,1.0,2,59,Semi-Urban,Software Engineer,24114,0 +11637,Female,28,Bachelors,10,80,91,99,39,4.0,6,79,Rural,Manager,136530,1 +16068,Male,42,Bachelors,18,8,90,52,30,8.0,5,58,Urban,HR Executive,118308,0 +83657,Male,51,Diploma,12,13,81,5,51,0.0,0,90,Urban,ML Engineer,81172,0 +29464,Male,45,Diploma,6,1,86,10,93,6.0,1,8,Urban,Manager,112271,0 +12270,Male,43,PhD,0,26,87,77,38,1.0,4,35,Semi-Urban,HR Executive,119505,0 +98153,Male,50,Bachelors,12,96,12,64,16,3.0,0,14,Urban,Manager,54202,0 +49941,Other,48,Bachelors,15,0,13,91,86,5.0,1,0,Urban,Manager,29003,0 +64616,Female,49,Masters,7,61,6,45,41,3.0,4,46,Urban,Software Engineer,74314,0 +45232,Female,46,Bachelors,19,66,23,75,58,2.0,6,19,Urban,HR Executive,93344,0 +25020,Female,25,Diploma,16,85,28,28,18,8.0,4,55,Rural,Manager,96625,0 +16517,Male,35,Bachelors,0,16,61,39,37,4.0,5,35,Urban,ML Engineer,138771,0 +45310,Male,41,Masters,18,2,2,59,69,3.0,3,23,Urban,HR Executive,88738,0 +11543,Female,28,High School,9,46,33,58,40,6.0,7,11,Rural,Software Engineer,41939,0 +37250,Female,27,Bachelors,7,37,44,46,61,7.0,6,81,Rural,ML Engineer,73078,0 +46410,Male,46,Masters,4,88,10,77,18,6.0,3,78,Urban,Manager,111095,1 +1976,Female,40,Bachelors,9,88,74,38,48,8.0,7,75,Semi-Urban,Software Engineer,70865,1 +43756,Male,55,High School,19,33,96,2,45,9.0,6,7,Semi-Urban,Data Analyst,62980,0 +108131,Female,54,Masters,7,61,50,39,98,7.0,4,51,Urban,Data Analyst,27004,0 +5994,Male,29,Bachelors,5,86,33,93,51,9.0,5,12,Rural,ML Engineer,58011,0 +75787,Male,28,Diploma,7,54,71,59,61,8.0,1,56,Semi-Urban,Manager,138231,1 +25343,Male,30,Masters,1,3,28,62,12,2.0,0,13,Urban,Manager,23751,0 +10530,Male,22,High School,10,19,46,20,9,8.0,3,15,Urban,HR Executive,85044,0 +110468,Male,31,High School,7,36,25,90,88,8.0,1,83,Rural,Manager,127880,0 +7273,Female,21,High School,1,22,63,86,45,1.0,7,62,Semi-Urban,Software Engineer,107263,0 +7460,Male,52,Diploma,0,30,94,92,76,5.0,2,69,Urban,ML Engineer,78395,1 +4180,Male,38,High School,5,0,60,60,13,9.0,1,24,Rural,ML Engineer,82176,0 +11384,Female,44,Bachelors,5,1,6,17,93,7.0,0,60,Semi-Urban,HR Executive,111570,0 +78256,Female,56,High School,7,57,73,10,40,0.0,6,2,Semi-Urban,Manager,98565,0 +102832,Male,35,PhD,11,73,79,99,92,2.0,1,44,Urban,Manager,92654,1 +103377,Male,38,Bachelors,2,67,63,69,5,0.0,7,84,Rural,Software Engineer,37319,1 +49635,Male,32,Diploma,6,64,78,14,26,9.0,1,34,Semi-Urban,ML Engineer,97583,0 +57959,Female,22,Masters,3,35,71,67,43,0.0,2,57,Semi-Urban,HR Executive,146814,0 +93728,Female,27,Masters,11,45,14,65,56,0.0,3,64,Rural,HR Executive,113822,0 +20401,Female,32,Masters,14,45,16,82,72,5.0,5,67,Rural,HR Executive,99644,0 +44629,Male,38,Diploma,9,18,31,98,44,0.0,5,91,Urban,HR Executive,148870,1 +74984,Female,24,High School,14,60,55,37,35,6.0,2,52,Rural,Manager,46342,0 +40984,Male,36,Masters,7,31,63,90,35,9.0,0,57,Urban,Data Analyst,60232,1 +56571,Female,53,Bachelors,8,84,0,63,79,8.0,7,7,Rural,Manager,66351,0 +46629,Female,30,Diploma,13,64,52,63,6,5.0,5,11,Urban,Data Analyst,53972,0 +37096,Female,35,Masters,16,1,29,22,61,1.0,6,68,Urban,ML Engineer,70583,0 +61677,Male,23,High School,19,90,92,89,98,6.0,7,65,Semi-Urban,Software Engineer,26045,1 +23269,Male,47,Bachelors,5,14,13,41,51,0.0,3,61,Urban,Manager,53827,0 +31435,Male,59,High School,11,64,30,14,94,7.0,4,14,Urban,ML Engineer,149025,0 +24762,Male,51,Bachelors,16,67,82,83,56,8.0,5,11,Semi-Urban,ML Engineer,63965,1 +19151,Male,43,Bachelors,17,84,81,61,16,5.0,4,70,Semi-Urban,Manager,50433,1 +63925,Male,24,Bachelors,2,98,82,23,35,5.0,7,71,Urban,Software Engineer,95356,1 +13964,Male,24,Bachelors,5,80,71,30,14,7.0,5,24,Urban,Manager,64318,0 +88344,Other,37,Diploma,8,2,73,34,18,0.0,7,74,Rural,ML Engineer,109888,0 +2941,Male,23,Masters,1,90,21,77,20,6.0,6,53,Urban,HR Executive,46795,1 +93369,Male,45,Bachelors,6,79,13,84,8,3.0,1,83,Rural,Manager,79692,1 +10554,Male,26,High School,0,57,69,0,22,0.0,5,34,Urban,ML Engineer,34485,0 +109021,Other,46,Bachelors,10,38,29,42,3,6.0,6,72,Urban,Data Analyst,58540,0 +39111,Female,23,Diploma,17,30,22,31,24,4.0,3,48,Urban,Data Analyst,66100,0 +45466,Female,29,Bachelors,2,73,46,11,7,0.0,6,76,Semi-Urban,Software Engineer,51309,0 +1881,Female,46,Diploma,6,16,37,61,92,6.0,5,36,Urban,HR Executive,52591,0 +4427,Male,23,Diploma,19,30,90,70,98,9.0,6,88,Semi-Urban,ML Engineer,122070,1 +58572,Male,42,High School,1,18,80,56,3,4.0,0,13,Semi-Urban,HR Executive,50652,0 +38909,Male,47,PhD,19,10,4,53,65,0.0,3,21,Urban,Software Engineer,68989,0 +4627,Male,29,Bachelors,8,33,60,69,57,3.0,3,47,Urban,HR Executive,47364,0 +116911,Female,59,Masters,9,7,37,52,8,4.0,0,82,Urban,HR Executive,130237,0 +39448,Male,28,Bachelors,9,74,26,8,76,6.0,0,31,Semi-Urban,Data Analyst,85158,0 +18531,Male,56,Masters,8,58,72,35,11,6.0,4,9,Rural,HR Executive,120442,0 +108883,Male,40,Bachelors,7,50,15,65,41,5.0,5,74,Urban,Software Engineer,25871,0 +73272,Female,28,Bachelors,13,14,84,13,66,8.0,0,28,Semi-Urban,Software Engineer,23469,0 +118030,Female,48,Bachelors,0,61,46,5,65,5.0,2,38,Semi-Urban,Manager,27381,0 +51737,Male,38,Masters,12,48,30,34,43,2.0,6,38,Urban,Software Engineer,146345,0 +6806,Female,38,Bachelors,3,65,68,6,19,1.0,3,42,Rural,ML Engineer,32171,0 +6220,Male,46,PhD,0,67,95,16,19,6.0,4,69,Urban,Data Analyst,78884,1 +111768,Male,54,Bachelors,0,0,29,11,58,4.0,6,56,Rural,Manager,141078,0 +45567,Male,54,Diploma,10,78,25,38,83,5.0,0,70,Urban,HR Executive,91082,0 +15215,Male,48,Masters,8,93,36,6,52,9.0,1,8,Semi-Urban,Software Engineer,114909,0 +35411,Male,35,Masters,18,44,47,22,4,9.0,6,72,Rural,Software Engineer,50220,0 +106430,Male,34,Bachelors,1,12,75,92,69,0.0,2,26,Urban,Data Analyst,74677,0 +16964,Female,59,High School,17,13,79,0,21,0.0,3,11,Urban,Software Engineer,138613,0 +101370,Female,39,High School,1,97,43,11,16,6.0,5,51,Semi-Urban,HR Executive,45930,0 +109216,Male,32,Bachelors,12,27,73,22,55,5.0,7,64,Urban,HR Executive,36890,0 +71574,Male,28,Bachelors,7,83,78,76,39,0.0,2,95,Urban,Data Analyst,77774,1 +37027,Male,48,Bachelors,4,48,59,31,68,4.0,7,25,Urban,Software Engineer,147743,0 +61259,Male,31,High School,10,45,89,89,12,6.0,1,96,Semi-Urban,HR Executive,67308,1 +97800,Male,30,High School,11,54,66,39,2,4.0,3,12,Urban,Manager,31066,0 +14385,Female,45,Masters,1,45,2,15,92,9.0,4,53,Urban,ML Engineer,128466,0 +60099,Male,24,High School,9,52,21,67,90,8.0,7,14,Urban,HR Executive,123334,0 +23978,Other,59,Diploma,13,47,14,10,30,1.0,5,46,Urban,ML Engineer,145801,0 +81683,Male,31,High School,3,82,83,51,3,2.0,1,8,Urban,Data Analyst,144739,0 +31456,Female,21,Masters,9,65,50,81,39,0.0,0,82,Urban,HR Executive,104405,1 +16614,Male,58,PhD,10,85,34,11,71,4.0,1,17,Urban,Software Engineer,101324,0 +31025,Female,24,High School,8,85,22,20,41,9.0,1,26,Urban,ML Engineer,122628,0 +94672,Male,23,Bachelors,10,92,7,71,8,6.0,6,56,Semi-Urban,Manager,118866,0 +73112,Female,30,High School,16,45,50,64,31,7.0,1,67,Urban,Data Analyst,123362,0 +107024,Male,35,High School,7,19,99,70,63,3.0,7,23,Urban,ML Engineer,122101,0 +76900,Female,57,Bachelors,18,78,58,99,49,6.0,3,86,Urban,ML Engineer,93620,1 +50570,Female,39,Bachelors,16,29,11,12,84,8.0,4,89,Semi-Urban,ML Engineer,35599,0 +77308,Female,39,Diploma,12,94,50,19,34,7.0,7,0,Urban,Data Analyst,64536,0 +40435,Male,42,Bachelors,9,29,29,24,66,8.0,0,68,Urban,Manager,117744,0 +11520,Female,29,Bachelors,2,51,74,40,47,2.0,1,80,Rural,Data Analyst,85788,1 +41221,Female,59,PhD,4,78,27,81,60,0.0,2,65,Urban,ML Engineer,44424,1 +108241,Female,27,Masters,11,90,29,40,89,0.0,2,20,Urban,HR Executive,29325,0 +57428,Female,24,Bachelors,16,95,69,17,31,6.0,0,74,Urban,HR Executive,90390,1 +40499,Female,34,Diploma,6,50,23,75,55,7.0,0,39,Semi-Urban,Manager,56368,0 +60734,Male,43,Bachelors,14,25,48,65,11,4.0,2,71,Semi-Urban,ML Engineer,57910,0 +77388,Female,58,Bachelors,13,62,53,37,44,9.0,2,70,Urban,Data Analyst,96824,0 +69682,Male,23,High School,13,16,32,49,90,8.0,0,33,Urban,Data Analyst,56818,0 +32983,Female,37,Bachelors,15,40,40,21,55,3.0,3,59,Urban,HR Executive,135428,0 +78397,Male,21,Bachelors,18,22,25,19,71,7.0,1,44,Rural,Manager,138115,0 +70116,Female,42,High School,6,21,46,33,23,7.0,2,76,Urban,ML Engineer,65896,0 +54660,Female,34,Bachelors,2,22,14,82,38,1.0,4,88,Rural,Software Engineer,142624,0 +111981,Female,37,Bachelors,8,93,65,3,4,4.0,5,12,Urban,Manager,37345,0 +53176,Male,59,Diploma,18,62,53,74,11,7.0,2,71,Urban,HR Executive,88640,1 +13751,Male,54,Bachelors,0,19,60,85,72,4.0,6,54,Urban,Software Engineer,56495,0 +20983,Male,23,Diploma,3,79,77,98,34,8.0,1,97,Urban,HR Executive,128773,1 +62468,Female,27,PhD,4,76,2,82,23,4.0,5,87,Urban,ML Engineer,82220,1 +99847,Male,52,High School,16,29,66,94,33,6.0,1,78,Semi-Urban,HR Executive,98279,1 +66767,Male,47,Masters,3,64,72,66,84,9.0,3,19,Urban,Data Analyst,50679,0 +47414,Male,40,Bachelors,11,71,52,30,1,6.0,2,54,Urban,HR Executive,34867,0 +46717,Male,25,Bachelors,4,48,57,11,16,0.0,1,8,Urban,Software Engineer,125587,0 +97844,Male,40,High School,14,85,82,11,22,9.0,5,0,Semi-Urban,ML Engineer,126595,0 +32861,Female,54,Bachelors,3,49,91,48,15,8.0,2,33,Rural,ML Engineer,136855,0 +96997,Male,52,Bachelors,9,39,87,44,75,6.0,2,69,Rural,ML Engineer,52190,1 +81729,Male,25,Bachelors,4,11,71,93,61,1.0,0,46,Urban,Data Analyst,102434,0 +10037,Female,24,Bachelors,15,75,18,26,30,6.0,2,41,Urban,ML Engineer,20573,0 +69856,Female,23,Diploma,16,73,84,29,26,1.0,5,50,Semi-Urban,ML Engineer,53373,0 +67409,Male,24,High School,16,49,40,26,6,6.0,2,97,Semi-Urban,HR Executive,127808,0 +11026,Male,36,Masters,8,71,90,11,98,6.0,3,11,Semi-Urban,HR Executive,36918,0 +66635,Female,24,High School,13,53,12,94,4,8.0,5,73,Rural,Manager,77623,0 +14367,Other,25,Masters,14,41,91,8,40,1.0,7,51,Rural,Software Engineer,29990,0 +18383,Other,24,Bachelors,2,5,95,61,93,5.0,4,98,Semi-Urban,HR Executive,63413,1 +91321,Male,27,Bachelors,1,58,81,25,55,2.0,3,46,Urban,Software Engineer,72790,0 +29401,Male,40,Bachelors,12,96,41,2,51,0.0,7,54,Urban,Data Analyst,142294,0 +89461,Male,26,Bachelors,5,49,29,30,62,3.0,0,38,Urban,Software Engineer,129108,0 +30079,Male,30,PhD,16,41,97,74,58,1.0,1,98,Urban,Data Analyst,47875,1 +99451,Other,49,Bachelors,16,43,72,27,62,5.0,0,5,Urban,Manager,129137,0 +57726,Female,52,Diploma,14,74,36,59,76,7.0,3,23,Semi-Urban,HR Executive,84168,0 +92629,Female,52,Bachelors,5,73,59,31,47,6.0,0,42,Urban,Manager,105987,0 +108854,Male,49,Bachelors,3,5,95,93,55,9.0,4,30,Urban,Manager,96094,0 +112636,Female,37,High School,8,35,85,74,58,2.0,1,86,Urban,Data Analyst,32515,1 +16618,Male,48,Diploma,15,66,96,70,68,9.0,1,70,Urban,Manager,135551,1 +108748,Female,33,Bachelors,19,19,33,44,21,4.0,3,77,Urban,Manager,65186,0 +105730,Male,25,Masters,14,21,22,76,47,6.0,3,77,Urban,Data Analyst,120261,0 +72419,Female,44,Diploma,4,4,62,85,89,1.0,0,25,Rural,Software Engineer,79148,0 +11166,Male,28,Diploma,3,65,18,70,31,6.0,2,63,Semi-Urban,HR Executive,32881,0 +75293,Male,21,Diploma,18,40,86,83,14,1.0,0,72,Urban,Manager,59695,1 +116549,Male,21,Diploma,15,79,8,13,86,7.0,6,20,Urban,Manager,132358,0 +32605,Female,28,Diploma,12,29,33,23,21,0.0,4,68,Semi-Urban,HR Executive,115271,0 +63882,Female,48,Diploma,15,43,67,18,86,8.0,6,97,Urban,HR Executive,25952,0 +116052,Female,50,Bachelors,12,46,1,12,54,2.0,0,94,Semi-Urban,Manager,30037,0 +45498,Male,38,Bachelors,2,53,18,95,32,0.0,7,94,Rural,Manager,114319,1 +22956,Male,37,Bachelors,14,51,46,49,71,7.0,5,38,Semi-Urban,Manager,123051,0 +45761,Female,29,PhD,9,10,75,64,11,8.0,4,74,Urban,ML Engineer,67055,0 +113484,Male,24,Bachelors,9,87,47,27,93,2.0,0,56,Semi-Urban,Software Engineer,56222,0 +42739,Female,49,High School,13,70,94,19,3,2.0,6,14,Rural,ML Engineer,109983,0 +63647,Male,47,Bachelors,0,11,10,87,46,4.0,3,56,Urban,Manager,100321,0 +94195,Female,41,Diploma,18,56,78,81,57,7.0,2,63,Urban,Software Engineer,71278,1 +80018,Female,47,Bachelors,17,51,50,73,94,8.0,5,26,Urban,Software Engineer,36092,0 +84910,Male,47,Bachelors,3,78,43,36,71,9.0,7,89,Semi-Urban,HR Executive,38271,1 +34963,Female,59,High School,0,40,70,30,52,0.0,0,93,Rural,Data Analyst,24606,0 +29637,Male,34,Diploma,8,61,39,2,55,7.0,3,18,Urban,HR Executive,103294,0 +34823,Male,38,Diploma,9,74,43,33,62,7.0,6,52,Rural,HR Executive,27654,0 +4536,Male,55,High School,15,80,0,44,51,2.0,5,35,Semi-Urban,Data Analyst,140912,0 +58605,Male,50,Bachelors,8,47,17,40,74,4.0,6,48,Urban,Software Engineer,45899,0 +33179,Female,34,Bachelors,17,64,91,95,54,4.0,0,24,Urban,Manager,38625,1 +52869,Female,58,Masters,7,40,80,96,36,4.0,6,27,Rural,Manager,54653,1 +208,Female,42,Diploma,11,23,34,82,42,7.0,1,21,Urban,HR Executive,115642,0 +97510,Male,41,Bachelors,9,67,81,62,71,4.0,4,87,Semi-Urban,HR Executive,146851,1 +115346,Male,58,High School,5,51,2,6,12,6.0,4,10,Rural,HR Executive,112767,0 +337,Female,38,Bachelors,11,84,80,36,6,2.0,1,37,Semi-Urban,Manager,142052,0 +46807,Male,51,PhD,17,9,43,83,85,9.0,5,89,Semi-Urban,Software Engineer,84442,0 +52349,Female,42,Bachelors,15,1,55,63,15,2.0,1,92,Urban,Manager,148894,0 +91731,Male,35,Masters,17,0,14,23,70,4.0,6,3,Urban,HR Executive,99130,0 +85751,Male,36,Bachelors,1,67,84,27,88,2.0,4,31,Semi-Urban,HR Executive,135457,0 +2652,Male,48,PhD,16,83,81,88,79,7.0,0,37,Urban,Manager,124699,1 +118640,Female,37,Bachelors,19,67,30,5,82,8.0,1,61,Urban,ML Engineer,103787,0 +81412,Male,37,Bachelors,19,18,99,15,27,2.0,7,24,Rural,Manager,92325,0 +55802,Male,32,Masters,7,84,26,14,45,5.0,1,33,Urban,ML Engineer,75451,0 +25282,Male,55,Masters,5,38,39,1,76,6.0,4,40,Urban,HR Executive,142973,0 +101279,Male,23,Bachelors,4,62,78,72,28,9.0,5,24,Urban,HR Executive,94710,1 +105996,Female,27,Bachelors,8,55,13,70,45,0.0,6,43,Urban,ML Engineer,35105,0 +48967,Female,40,Masters,1,60,6,58,28,8.0,2,67,Semi-Urban,ML Engineer,48037,0 +37131,Male,44,Diploma,9,11,90,59,1,4.0,3,60,Urban,ML Engineer,24629,0 +84214,Female,59,Bachelors,11,99,58,98,57,5.0,1,87,Urban,Software Engineer,42862,1 +94212,Other,55,Diploma,5,34,60,74,59,5.0,3,16,Semi-Urban,Software Engineer,111576,0 +23785,Male,55,Masters,14,30,12,87,96,3.0,4,64,Rural,Software Engineer,67639,0 +57766,Male,45,Bachelors,7,33,72,95,22,6.0,5,47,Semi-Urban,Manager,71718,1 +29723,Male,53,Diploma,11,41,17,63,3,3.0,5,49,Semi-Urban,Data Analyst,62453,0 +110355,Female,35,Bachelors,1,34,81,47,17,1.0,7,38,Semi-Urban,Software Engineer,145103,0 +60167,Male,48,Diploma,12,47,74,45,18,0.0,1,88,Semi-Urban,Software Engineer,132086,1 +110813,Male,56,Diploma,6,16,30,50,21,4.0,3,29,Rural,Manager,112022,0 +46803,Female,44,Bachelors,9,86,10,36,34,4.0,0,23,Semi-Urban,Software Engineer,135070,0 +117317,Female,41,Masters,4,98,27,58,18,7.0,5,44,Urban,Manager,126296,0 +6913,Male,37,High School,8,93,27,6,85,6.0,5,2,Semi-Urban,Software Engineer,129904,0 +70297,Female,34,Diploma,18,20,7,90,55,0.0,5,92,Urban,ML Engineer,145949,0 +64968,Male,24,Diploma,2,98,50,2,93,1.0,5,77,Rural,Data Analyst,62392,0 +115859,Female,52,Bachelors,0,47,77,19,12,3.0,6,58,Urban,Software Engineer,116211,0 +105610,Female,23,Bachelors,4,57,51,16,68,6.0,4,18,Urban,Manager,57031,0 +97779,Male,39,Bachelors,10,1,93,92,54,7.0,3,71,Semi-Urban,Software Engineer,122686,1 +99802,Female,37,Masters,7,93,19,52,84,9.0,2,38,Semi-Urban,Software Engineer,39757,0 +96138,Male,31,Bachelors,17,38,34,0,88,4.0,1,2,Rural,ML Engineer,55031,0 +96129,Male,55,Bachelors,15,21,85,82,12,0.0,1,67,Urban,Data Analyst,35040,1 +61690,Male,39,Masters,15,11,92,52,4,9.0,7,38,Rural,ML Engineer,38963,0 +43089,Male,21,Bachelors,16,82,49,5,82,6.0,3,58,Rural,HR Executive,74580,0 +111227,Male,52,Diploma,14,15,55,19,65,4.0,4,45,Semi-Urban,Software Engineer,59269,0 +12702,Male,58,Masters,18,59,0,14,23,9.0,7,63,Urban,ML Engineer,39491,0 +74664,Male,35,Bachelors,9,15,47,43,95,2.0,7,29,Urban,Software Engineer,55530,0 +8294,Male,27,Diploma,2,28,45,76,6,9.0,1,55,Semi-Urban,Manager,149381,0 +74005,Female,35,Diploma,3,9,52,22,68,2.0,1,81,Semi-Urban,Manager,148694,0 +114984,Male,55,Bachelors,16,64,55,95,42,4.0,0,63,Rural,Software Engineer,95841,1 +3454,Male,26,High School,18,32,28,88,64,0.0,0,21,Urban,Manager,79580,0 +101584,Female,42,Bachelors,1,53,46,38,85,5.0,5,47,Urban,Software Engineer,53436,0 +57731,Male,54,Bachelors,5,87,66,73,68,5.0,4,34,Semi-Urban,Data Analyst,108018,1 +40329,Male,36,PhD,12,72,68,92,83,6.0,7,33,Semi-Urban,HR Executive,145609,1 +10856,Male,43,Bachelors,8,47,57,44,23,0.0,1,94,Urban,HR Executive,103651,1 +8742,Male,34,Bachelors,17,17,29,75,78,9.0,3,25,Rural,ML Engineer,110057,0 +44192,Male,48,Bachelors,16,28,89,46,23,6.0,2,3,Urban,ML Engineer,124615,0 +101923,Female,41,High School,11,22,63,59,60,1.0,1,16,Urban,Manager,55847,0 +663,Female,53,Diploma,8,71,62,15,62,3.0,7,31,Urban,Data Analyst,66765,0 +15942,Male,55,Diploma,17,16,21,99,55,5.0,3,60,Urban,HR Executive,108132,0 +3444,Other,55,Diploma,18,82,68,29,13,5.0,4,21,Urban,Software Engineer,107606,0 +68659,Female,47,Bachelors,9,6,12,7,71,6.0,1,44,Rural,Software Engineer,116252,0 +53464,Female,52,Masters,19,17,22,60,62,4.0,5,52,Urban,HR Executive,138320,0 +45162,Female,57,Masters,3,44,69,82,30,0.0,3,59,Rural,ML Engineer,102892,1 +114626,Male,52,High School,3,19,66,55,58,4.0,3,95,Rural,HR Executive,80126,1 +15919,Female,31,Bachelors,18,57,10,69,77,8.0,7,68,Urban,Software Engineer,63201,0 +36217,Female,37,High School,12,46,30,5,6,9.0,6,0,Urban,HR Executive,125739,0 +48564,Male,34,Masters,13,80,65,91,27,2.0,3,57,Urban,ML Engineer,52853,1 +8978,Female,43,High School,10,17,95,3,31,0.0,5,48,Semi-Urban,Software Engineer,134042,0 +40765,Male,30,Bachelors,14,9,4,64,93,6.0,7,75,Rural,HR Executive,147849,0 +56507,Male,33,Bachelors,12,35,66,14,22,7.0,7,11,Urban,Manager,69760,0 +57665,Other,48,High School,19,45,75,63,13,6.0,6,61,Urban,Data Analyst,99289,1 +41595,Female,59,High School,15,97,54,33,94,6.0,2,23,Urban,ML Engineer,145574,0 +24455,Male,24,Bachelors,7,84,45,4,86,8.0,6,81,Semi-Urban,HR Executive,21913,0 +70759,Male,32,Bachelors,2,1,11,6,98,3.0,2,49,Urban,Software Engineer,114761,0 +14534,Male,41,Bachelors,1,1,64,55,85,7.0,6,65,Urban,Data Analyst,60023,0 +17236,Female,43,Diploma,1,89,97,24,32,0.0,1,65,Semi-Urban,Software Engineer,117596,1 +64080,Male,25,High School,0,13,65,37,92,6.0,5,61,Urban,Software Engineer,140315,0 +53056,Male,21,Masters,7,86,1,75,90,5.0,4,84,Semi-Urban,Manager,118242,1 +84674,Other,34,Bachelors,2,38,8,97,25,8.0,1,9,Semi-Urban,Software Engineer,39240,0 +99165,Female,49,Bachelors,15,62,64,94,74,9.0,3,78,Rural,Data Analyst,108989,1 +70506,Male,34,Bachelors,17,99,62,8,6,5.0,5,24,Urban,Manager,95003,0 +87897,Male,47,Bachelors,2,21,32,52,64,3.0,4,49,Urban,ML Engineer,49195,0 +12397,Female,29,Diploma,15,40,84,42,65,2.0,5,45,Rural,HR Executive,136199,0 +45800,Male,34,Diploma,9,10,91,86,43,5.0,6,25,Urban,ML Engineer,36064,0 +16113,Male,38,Bachelors,3,3,17,79,56,0.0,4,55,Urban,HR Executive,142351,0 +12338,Male,41,High School,2,45,76,3,89,3.0,2,25,Rural,Software Engineer,51517,0 +52141,Male,58,Bachelors,0,10,85,13,28,3.0,1,65,Semi-Urban,Manager,94819,0 +45311,Male,41,Masters,17,55,8,10,86,7.0,2,71,Urban,Data Analyst,101973,0 +90538,Female,38,High School,16,89,36,25,15,4.0,0,97,Rural,Software Engineer,123103,1 +115427,Other,46,Bachelors,12,40,42,74,39,2.0,6,93,Urban,Software Engineer,142131,1 +53633,Male,55,Bachelors,4,63,1,66,1,4.0,3,60,Urban,ML Engineer,63699,0 +36464,Male,25,Bachelors,4,80,96,92,46,1.0,7,75,Urban,HR Executive,74267,1 +27968,Male,58,High School,14,8,55,77,25,6.0,2,30,Urban,Data Analyst,86173,0 +73142,Female,30,Bachelors,16,44,40,35,81,2.0,4,14,Urban,Data Analyst,63417,0 +29763,Female,53,Diploma,10,25,49,46,0,2.0,4,26,Urban,ML Engineer,126953,0 +99963,Male,34,High School,17,88,31,12,46,8.0,4,42,Urban,HR Executive,106189,0 +21359,Male,39,Diploma,13,72,29,89,17,2.0,6,47,Rural,Software Engineer,114340,1 +5961,Male,46,Bachelors,4,27,73,3,96,8.0,5,69,Urban,HR Executive,143353,0 +10728,Male,24,Bachelors,0,52,8,80,68,7.0,4,70,Urban,ML Engineer,66533,0 +11511,Male,55,Bachelors,14,99,55,49,46,9.0,6,14,Urban,HR Executive,75001,0 +59567,Male,56,Diploma,8,79,83,49,74,6.0,5,28,Urban,Data Analyst,47837,1 +15055,Male,35,Bachelors,9,54,20,94,78,8.0,1,7,Semi-Urban,Manager,118117,0 +7531,Male,42,Masters,9,91,61,53,47,9.0,3,31,Urban,HR Executive,120047,1 +13070,Female,36,High School,7,28,19,98,73,2.0,6,93,Semi-Urban,Manager,28848,0 +97291,Male,35,Bachelors,12,30,9,87,77,9.0,6,79,Urban,Software Engineer,52029,0 +78896,Female,48,High School,0,56,43,32,37,9.0,7,75,Semi-Urban,Data Analyst,60020,0 +32649,Female,48,Bachelors,3,46,45,37,82,1.0,1,63,Semi-Urban,HR Executive,128971,0 +97135,Female,51,High School,18,26,69,80,15,9.0,3,47,Urban,Manager,28650,0 +57036,Male,38,Masters,9,31,0,95,58,1.0,6,36,Urban,ML Engineer,132225,0 +42993,Male,48,Bachelors,6,6,31,2,11,6.0,3,65,Urban,Data Analyst,43641,0 +39242,Female,36,High School,4,81,16,70,72,2.0,1,39,Urban,HR Executive,47169,0 +3487,Male,40,Bachelors,17,60,96,43,32,6.0,3,17,Urban,ML Engineer,80212,0 +84098,Female,21,Diploma,14,85,96,99,72,6.0,1,61,Rural,Manager,91135,1 +51021,Male,45,Bachelors,5,61,53,63,68,2.0,1,0,Urban,Manager,42774,0 +92449,Male,59,Bachelors,18,75,2,18,94,4.0,5,20,Urban,Manager,109159,0 +57920,Female,54,High School,18,18,30,45,24,0.0,1,67,Semi-Urban,Data Analyst,115734,0 +62749,Male,33,Bachelors,12,94,18,56,59,2.0,2,33,Urban,Data Analyst,148733,0 +5172,Male,57,Bachelors,12,77,9,40,15,4.0,7,55,Semi-Urban,Software Engineer,74104,0 +116404,Male,39,Diploma,1,35,51,93,2,3.0,3,10,Urban,ML Engineer,133013,0 +63699,Male,52,Bachelors,1,3,71,39,4,6.0,1,34,Urban,Data Analyst,58484,0 +486,Female,42,Masters,3,57,57,36,74,3.0,6,51,Urban,Manager,140116,0 +86734,Female,58,Masters,3,84,1,20,46,8.0,1,61,Semi-Urban,Manager,38770,0 +9600,Male,37,Diploma,3,75,70,86,4,3.0,3,64,Urban,Manager,42694,1 +74769,Female,41,Diploma,17,83,86,20,3,3.0,7,84,Urban,HR Executive,41056,1 +5529,Male,51,High School,13,42,20,91,85,5.0,2,75,Urban,Data Analyst,149039,0 +28898,Female,51,High School,2,97,18,14,0,7.0,2,42,Urban,Manager,140267,0 +107463,Female,26,Bachelors,2,90,2,47,1,5.0,5,75,Urban,Data Analyst,131987,0 +6187,Female,54,Bachelors,12,52,86,44,78,4.0,2,78,Urban,Software Engineer,149288,1 +43208,Male,51,Bachelors,14,1,86,55,91,5.0,5,78,Urban,Manager,139391,0 +69445,Female,47,Masters,11,94,14,25,62,9.0,1,60,Rural,Software Engineer,87310,0 +73173,Female,43,Diploma,5,65,69,98,2,9.0,4,54,Urban,HR Executive,128018,1 +28728,Male,52,Bachelors,17,71,55,16,52,6.0,6,75,Urban,Data Analyst,90221,0 +62656,Male,50,Masters,8,51,7,33,24,0.0,1,69,Urban,Manager,123158,0 +61058,Male,36,Bachelors,1,47,94,31,6,1.0,2,18,Urban,Data Analyst,44469,0 +83371,Male,28,PhD,19,84,70,88,92,9.0,2,81,Semi-Urban,HR Executive,86812,1 +40354,Female,39,Bachelors,15,42,11,92,63,0.0,5,31,Urban,Software Engineer,148123,0 +111930,Male,28,Bachelors,4,20,96,69,11,8.0,3,19,Urban,Manager,21933,0 +42986,Male,45,Bachelors,9,59,4,92,90,3.0,3,63,Urban,HR Executive,26201,0 +75377,Male,33,Diploma,3,54,94,79,17,4.0,0,45,Rural,HR Executive,89108,1 +85463,Male,33,Bachelors,13,34,53,11,90,7.0,6,32,Rural,HR Executive,113131,0 +1287,Male,44,Bachelors,14,42,33,77,92,0.0,6,19,Urban,Data Analyst,93040,0 +57567,Male,46,Bachelors,6,1,40,21,98,6.0,1,87,Urban,Manager,116095,0 +16354,Other,55,Bachelors,9,84,13,98,36,1.0,5,54,Urban,ML Engineer,89899,1 +112053,Female,26,High School,7,40,12,51,79,8.0,4,52,Urban,ML Engineer,47292,0 +17429,Other,51,High School,17,4,64,93,90,7.0,6,31,Urban,Data Analyst,116978,0 +10630,Male,21,Bachelors,10,57,60,95,31,3.0,7,41,Urban,Data Analyst,29120,1 +91900,Female,48,Bachelors,8,34,35,60,49,2.0,2,78,Semi-Urban,ML Engineer,51013,0 +91625,Male,45,Masters,1,62,44,57,60,5.0,6,33,Semi-Urban,ML Engineer,41519,0 +119937,Female,25,Bachelors,6,3,99,24,10,2.0,4,10,Urban,Data Analyst,75285,0 +25482,Male,33,Diploma,19,16,61,22,97,2.0,2,34,Urban,Manager,143593,0 +51461,Female,44,Bachelors,8,73,63,9,39,1.0,7,62,Semi-Urban,ML Engineer,59138,0 +85510,Male,50,High School,9,49,22,53,43,6.0,0,52,Rural,Manager,139295,0 +14737,Male,31,Diploma,18,37,66,75,72,9.0,3,70,Urban,Data Analyst,86911,1 +96150,Male,37,Bachelors,16,87,24,97,32,1.0,6,53,Rural,Data Analyst,139084,1 +85585,Male,45,Bachelors,16,76,6,63,3,9.0,0,1,Rural,ML Engineer,137544,0 +97871,Male,47,Diploma,18,66,49,86,18,1.0,0,72,Urban,Software Engineer,50548,1 +57275,Female,24,High School,12,9,33,61,69,4.0,6,91,Semi-Urban,ML Engineer,32279,0 +9481,Male,40,Diploma,12,5,39,8,71,6.0,6,58,Urban,Data Analyst,73940,0 +32011,Male,34,Diploma,10,3,32,26,85,2.0,5,90,Rural,HR Executive,102199,0 +85650,Male,54,High School,4,71,96,94,19,2.0,2,78,Urban,HR Executive,73394,1 +69321,Other,47,Masters,7,7,69,34,5,6.0,4,47,Urban,Software Engineer,141860,0 +57434,Male,55,Masters,3,49,41,34,93,7.0,0,34,Urban,Data Analyst,133084,0 +45769,Female,28,High School,0,80,3,7,9,1.0,2,83,Rural,ML Engineer,45321,0 +88925,Female,44,Bachelors,2,18,30,37,84,2.0,3,67,Semi-Urban,Manager,126258,0 +43495,Female,24,Bachelors,1,79,15,42,37,9.0,3,56,Urban,Data Analyst,38304,0 +12275,Male,35,Bachelors,4,86,3,37,10,0.0,6,17,Urban,Software Engineer,116906,0 +59984,Male,44,Bachelors,15,59,64,58,81,9.0,0,32,Urban,ML Engineer,31007,0 +30866,Male,50,Bachelors,1,25,18,30,15,9.0,6,71,Urban,Data Analyst,137102,0 +101321,Female,31,Bachelors,11,7,22,78,94,8.0,6,98,Urban,Data Analyst,124628,0 +51454,Male,52,Masters,17,32,70,89,42,1.0,1,82,Urban,ML Engineer,95831,1 +62249,Male,55,Bachelors,9,0,7,41,2,1.0,0,68,Urban,Software Engineer,148049,0 +38720,Female,48,Bachelors,18,60,44,43,2,5.0,3,79,Rural,Manager,94726,0 +47147,Male,45,Diploma,1,56,4,90,62,1.0,4,40,Semi-Urban,ML Engineer,105113,0 +34091,Male,44,Masters,5,39,45,37,4,0.0,7,2,Semi-Urban,HR Executive,70275,0 +16200,Female,47,Bachelors,15,64,54,10,69,3.0,7,30,Urban,HR Executive,96611,0 +29710,Male,57,Bachelors,1,2,58,39,29,7.0,4,2,Rural,Manager,88533,0 +51293,Female,54,Masters,8,19,92,32,18,3.0,0,65,Urban,ML Engineer,61515,0 +8729,Male,56,Masters,4,94,22,45,51,3.0,4,67,Semi-Urban,HR Executive,142503,0 +61064,Female,48,Masters,3,77,56,44,25,7.0,2,92,Semi-Urban,HR Executive,65517,1 +66894,Male,38,High School,18,73,31,58,31,4.0,1,10,Rural,ML Engineer,103158,0 +54094,Female,52,Bachelors,3,76,31,4,20,1.0,1,29,Semi-Urban,ML Engineer,53869,0 +58713,Male,52,Bachelors,9,95,89,80,63,8.0,4,55,Urban,HR Executive,55420,1 +85153,Male,53,Masters,8,27,37,68,8,6.0,0,59,Urban,HR Executive,140625,0 +71107,Female,21,Bachelors,15,36,49,84,40,1.0,6,64,Urban,ML Engineer,41091,0 +64608,Female,30,Masters,0,82,59,4,15,4.0,5,41,Rural,Manager,51524,0 +19567,Male,46,High School,13,99,76,10,62,4.0,4,47,Urban,Software Engineer,102910,0 +96685,Male,30,Bachelors,9,7,77,6,60,2.0,5,33,Urban,Software Engineer,129460,0 +33840,Female,56,PhD,13,59,73,18,5,4.0,7,54,Semi-Urban,HR Executive,44833,0 +53397,Female,32,Masters,12,68,52,48,82,1.0,7,80,Rural,Data Analyst,51525,1 +50978,Female,49,Bachelors,0,90,44,95,79,5.0,1,33,Rural,HR Executive,114960,1 +105992,Male,24,Bachelors,18,57,16,44,34,6.0,0,32,Semi-Urban,ML Engineer,135000,0 +21747,Male,28,Masters,10,68,15,65,44,7.0,2,22,Urban,ML Engineer,67579,0 +106415,Other,36,High School,11,83,25,11,11,8.0,1,22,Urban,Software Engineer,113684,0 +1234,Male,28,Bachelors,15,40,23,52,62,0.0,1,35,Urban,ML Engineer,47513,0 +8356,Male,32,Bachelors,7,62,34,25,65,1.0,1,22,Urban,HR Executive,82716,0 +91966,Male,42,High School,18,3,12,79,21,4.0,6,67,Urban,ML Engineer,36556,0 +12228,Male,56,Diploma,4,79,27,66,7,3.0,4,95,Urban,Data Analyst,142547,1 +9901,Male,25,Bachelors,7,36,68,37,78,3.0,3,46,Urban,Software Engineer,39302,0 +8134,Male,50,Diploma,0,45,28,14,66,8.0,7,95,Urban,HR Executive,105499,0 +97579,Male,46,PhD,3,52,30,48,32,5.0,5,69,Urban,Manager,27786,0 +50388,Female,28,Bachelors,16,76,25,56,59,7.0,5,73,Rural,Software Engineer,37210,0 +55586,Female,26,Masters,0,26,86,42,36,2.0,5,82,Semi-Urban,Data Analyst,40450,0 +1917,Female,33,Masters,1,15,98,16,62,4.0,7,51,Urban,HR Executive,122323,0 +26967,Female,25,Masters,1,2,26,30,18,3.0,4,31,Urban,ML Engineer,59551,0 +89860,Female,37,High School,6,26,8,59,26,3.0,5,14,Semi-Urban,HR Executive,75991,0 +89567,Female,49,Bachelors,0,14,20,56,26,2.0,6,95,Semi-Urban,Data Analyst,21616,0 +83248,Female,29,Bachelors,7,42,15,2,13,4.0,5,90,Rural,Software Engineer,148604,0 +22502,Male,35,Bachelors,5,32,3,41,15,1.0,3,50,Urban,ML Engineer,55496,0 +74212,Female,50,Diploma,1,0,50,76,84,4.0,2,55,Rural,ML Engineer,114352,0 +85505,Male,56,Diploma,11,86,37,54,22,8.0,1,35,Urban,Software Engineer,130624,0 +108177,Female,37,Masters,19,20,85,56,89,5.0,0,18,Rural,Data Analyst,74794,0 +41976,Female,27,High School,7,69,47,8,14,9.0,0,77,Semi-Urban,Software Engineer,39692,0 +115488,Female,38,Masters,18,46,69,92,14,8.0,2,64,Urban,Manager,63985,1 +5710,Female,37,Diploma,11,87,74,70,27,3.0,6,94,Urban,Manager,135854,1 +40849,Female,54,Bachelors,12,97,74,10,91,8.0,0,93,Urban,Manager,119794,1 +88037,Female,31,Masters,11,84,98,54,16,1.0,4,82,Semi-Urban,Data Analyst,125556,1 +44630,Male,49,Bachelors,11,15,36,32,10,3.0,6,88,Urban,Manager,78437,0 +82927,Male,23,High School,19,88,78,79,1,9.0,1,89,Rural,Data Analyst,92065,1 +4848,Male,37,High School,9,35,29,33,82,9.0,0,2,Semi-Urban,ML Engineer,50508,0 +67781,Male,45,PhD,0,37,41,10,59,8.0,3,76,Urban,Manager,87790,0 +106009,Male,37,Masters,10,98,15,90,56,3.0,3,40,Urban,Manager,107086,1 +60145,Male,45,Bachelors,2,55,11,7,87,9.0,0,63,Urban,Software Engineer,113399,0 +22528,Female,39,Bachelors,19,11,60,67,95,6.0,6,41,Urban,Software Engineer,118101,0 +74070,Male,37,Bachelors,7,44,41,33,19,6.0,3,72,Semi-Urban,ML Engineer,78650,0 +56645,Female,49,Masters,9,83,2,99,45,8.0,7,29,Urban,Manager,54798,0 +31588,Female,27,PhD,18,90,74,73,73,3.0,1,21,Semi-Urban,Data Analyst,28773,1 +65492,Male,24,Masters,2,1,81,67,47,7.0,1,19,Urban,HR Executive,38942,0 +39227,Male,35,Bachelors,4,11,3,73,93,7.0,1,46,Rural,Software Engineer,58548,0 +8003,Male,33,High School,8,10,43,6,12,3.0,3,39,Rural,HR Executive,134856,0 +48916,Female,38,Bachelors,14,82,73,69,76,5.0,7,84,Rural,Data Analyst,72283,1 +62538,Other,27,High School,4,85,50,32,7,6.0,4,67,Urban,Data Analyst,149172,0 +64969,Male,33,Diploma,1,35,8,2,53,7.0,6,70,Rural,Manager,99405,0 +66810,Female,32,Bachelors,12,0,77,18,80,2.0,3,75,Urban,Software Engineer,98734,0 +95119,Male,23,Masters,5,21,20,68,39,9.0,7,11,Rural,Manager,145555,0 +50924,Male,43,Masters,2,54,81,49,19,2.0,7,54,Semi-Urban,Software Engineer,149613,1 +74969,Male,51,Diploma,5,68,50,91,61,6.0,5,36,Urban,ML Engineer,67364,1 +86556,Male,22,Diploma,17,72,14,77,38,4.0,3,10,Rural,Data Analyst,98734,0 +22567,Male,41,Diploma,7,58,53,1,63,1.0,7,90,Urban,Manager,82996,0 +43126,Female,29,Bachelors,9,85,60,64,95,8.0,2,87,Urban,Manager,25214,1 +20235,Male,44,Bachelors,3,48,14,16,52,7.0,0,14,Urban,ML Engineer,72091,0 +33554,Male,51,PhD,0,27,88,73,9,1.0,1,2,Urban,HR Executive,45245,0 +80123,Female,21,Masters,16,14,7,68,27,7.0,3,58,Rural,HR Executive,89524,0 +55331,Female,49,Bachelors,18,85,32,73,30,4.0,7,16,Semi-Urban,Software Engineer,93737,0 +43482,Female,28,Masters,14,94,74,50,75,8.0,7,18,Rural,HR Executive,68018,0 +12546,Male,39,High School,15,91,96,37,31,9.0,4,54,Urban,Manager,27354,1 +69533,Female,46,Bachelors,2,16,35,38,24,4.0,6,64,Urban,Software Engineer,98916,0 +59284,Male,38,Bachelors,14,84,97,49,66,9.0,5,65,Rural,HR Executive,39885,1 +65940,Male,40,Bachelors,16,31,81,30,39,5.0,5,93,Urban,ML Engineer,69135,1 +38709,Female,52,Bachelors,9,67,23,90,97,7.0,4,65,Semi-Urban,HR Executive,112510,1 +35719,Other,52,Masters,3,66,48,5,20,1.0,5,73,Urban,Manager,134795,0 +67328,Female,41,High School,11,89,71,95,89,8.0,3,50,Semi-Urban,Manager,46135,1 +30157,Male,38,High School,15,96,84,1,81,7.0,1,63,Urban,HR Executive,60204,1 +64523,Female,31,Bachelors,2,41,73,98,86,0.0,5,41,Rural,Software Engineer,107518,1 +50660,Male,50,Diploma,0,66,86,85,27,1.0,6,31,Semi-Urban,Software Engineer,24085,1 +104512,Male,57,PhD,16,73,23,57,14,5.0,0,29,Urban,ML Engineer,76521,0 +39149,Male,26,Masters,6,8,70,15,12,9.0,6,67,Rural,Manager,43452,0 +51026,Male,46,Masters,12,79,95,83,83,2.0,5,96,Urban,Data Analyst,46723,1 +82565,Female,34,Diploma,1,5,10,74,83,0.0,4,93,Semi-Urban,Manager,142607,0 +83493,Male,37,High School,10,2,69,99,76,9.0,0,25,Urban,Manager,35854,0 +75237,Female,30,Bachelors,15,13,49,48,9,2.0,1,54,Semi-Urban,Software Engineer,120884,0 +42292,Male,57,Bachelors,8,91,74,14,69,6.0,5,56,Urban,Manager,91532,1 +3828,Male,38,Masters,6,88,55,74,17,1.0,7,32,Semi-Urban,Manager,34684,1 +106778,Male,44,Bachelors,8,47,13,30,38,7.0,6,37,Semi-Urban,HR Executive,119855,0 +94637,Male,23,High School,1,25,63,71,28,9.0,0,30,Urban,ML Engineer,149336,0 +101100,Male,47,Bachelors,1,32,49,28,83,9.0,6,82,Urban,Software Engineer,59746,0 +105669,Female,45,Diploma,14,82,71,5,72,5.0,3,88,Urban,ML Engineer,60262,1 +58004,Male,28,High School,2,60,61,19,78,6.0,2,51,Urban,HR Executive,76295,0 +83073,Male,52,Bachelors,5,78,21,12,8,6.0,6,99,Urban,Data Analyst,50698,0 +100575,Female,37,Bachelors,4,78,98,36,33,2.0,6,13,Rural,ML Engineer,31009,0 +114589,Male,25,Masters,10,87,32,59,52,8.0,3,32,Urban,Software Engineer,22791,0 +77688,Other,49,Bachelors,16,15,63,25,63,4.0,7,68,Urban,Software Engineer,25302,0 +56283,Male,43,Masters,11,20,91,37,46,8.0,2,14,Urban,Data Analyst,44331,0 +107717,Female,47,Bachelors,18,92,87,67,74,9.0,7,68,Urban,ML Engineer,37077,1 +62754,Male,56,Masters,12,37,96,64,22,1.0,0,44,Urban,Data Analyst,93137,1 +77523,Female,50,Masters,5,0,12,53,25,6.0,6,77,Semi-Urban,Manager,32437,0 +75216,Male,22,Bachelors,0,15,19,40,70,0.0,5,58,Semi-Urban,Software Engineer,92713,0 +17283,Male,29,Diploma,12,55,75,39,97,1.0,6,15,Semi-Urban,ML Engineer,46512,0 +32447,Male,32,Bachelors,12,48,3,49,75,0.0,2,89,Urban,Data Analyst,117774,0 +114176,Male,41,PhD,16,13,37,87,26,0.0,7,41,Urban,ML Engineer,113324,0 +52912,Male,43,High School,1,6,90,85,35,0.0,3,55,Urban,Software Engineer,57398,1 +91605,Male,24,High School,19,20,10,49,22,0.0,3,93,Semi-Urban,ML Engineer,26707,0 +99929,Male,30,High School,14,53,89,95,39,2.0,3,16,Urban,HR Executive,90541,1 +68894,Female,27,Masters,5,58,75,14,14,8.0,7,98,Semi-Urban,HR Executive,126058,1 +74239,Male,34,Masters,4,59,91,6,86,0.0,0,4,Semi-Urban,Software Engineer,138977,0 +71846,Other,36,PhD,10,86,46,83,36,1.0,5,41,Rural,HR Executive,39586,1 +98218,Male,41,Diploma,12,3,90,66,64,0.0,1,98,Rural,Manager,52465,1 +968,Male,50,High School,6,66,67,41,66,8.0,4,0,Semi-Urban,Manager,38693,0 +2801,Female,46,Masters,0,16,36,76,19,2.0,2,54,Urban,ML Engineer,57201,0 +110560,Female,34,PhD,16,39,6,4,56,6.0,0,22,Semi-Urban,Software Engineer,57818,0 +37113,Male,55,Masters,3,17,46,41,79,6.0,7,90,Semi-Urban,Software Engineer,68922,0 +30196,Female,29,High School,5,77,37,92,75,7.0,4,59,Urban,HR Executive,61140,1 +116192,Male,43,Bachelors,15,85,37,7,12,3.0,2,94,Semi-Urban,ML Engineer,104803,0 +56206,Male,44,High School,8,7,44,77,16,1.0,1,40,Urban,Manager,78925,0 +112986,Male,59,Diploma,9,84,52,96,62,1.0,5,81,Rural,HR Executive,140249,1 +14966,Female,49,Bachelors,16,22,64,11,51,4.0,1,47,Urban,ML Engineer,120720,0 +53694,Male,34,Diploma,11,63,70,72,85,3.0,1,13,Semi-Urban,Data Analyst,62716,0 +82507,Female,24,Bachelors,18,10,81,31,43,4.0,3,15,Rural,Software Engineer,70288,0 +112634,Male,36,Bachelors,19,79,71,95,71,4.0,6,59,Urban,Software Engineer,51275,1 +74371,Male,26,Diploma,4,38,93,59,86,7.0,1,76,Semi-Urban,HR Executive,144400,1 +52804,Female,39,Diploma,17,85,46,81,89,7.0,4,84,Semi-Urban,Data Analyst,93720,1 +27619,Male,51,Diploma,14,6,36,41,32,4.0,3,68,Urban,Software Engineer,92234,0 +68594,Female,53,PhD,15,89,74,25,33,1.0,4,96,Semi-Urban,Software Engineer,22616,1 +90659,Male,59,Bachelors,13,11,17,70,28,4.0,4,59,Urban,ML Engineer,109817,0 +96195,Female,31,Bachelors,7,62,41,94,82,3.0,2,33,Urban,Software Engineer,38792,0 +56849,Male,46,Bachelors,6,1,48,70,5,2.0,6,49,Urban,Software Engineer,39299,0 +26691,Male,44,Diploma,13,20,42,22,23,5.0,7,50,Urban,Manager,24036,0 +99269,Female,38,High School,14,65,18,89,89,4.0,4,73,Rural,ML Engineer,32448,1 +84407,Female,26,Masters,11,49,48,98,66,7.0,6,26,Urban,HR Executive,44747,0 +8068,Male,58,PhD,3,17,0,51,98,6.0,5,44,Rural,Data Analyst,97267,0 +109862,Male,46,Bachelors,4,20,5,1,32,7.0,0,0,Rural,ML Engineer,95344,0 +74067,Male,23,High School,15,31,79,6,74,7.0,5,85,Rural,Manager,72222,0 +115622,Female,32,Masters,3,73,65,19,71,6.0,7,38,Urban,Software Engineer,80924,0 +87031,Female,24,Bachelors,3,95,84,5,44,9.0,7,70,Urban,HR Executive,138038,1 +88160,Male,54,Diploma,7,31,7,80,39,1.0,6,96,Urban,ML Engineer,148898,0 +98963,Female,44,Masters,19,13,7,84,30,8.0,1,45,Urban,Manager,39330,0 +78079,Other,54,Masters,16,17,95,73,40,4.0,0,8,Urban,ML Engineer,24703,0 +19484,Other,43,Bachelors,17,53,28,5,33,1.0,6,69,Urban,Software Engineer,43731,0 +11508,Male,41,Masters,10,4,75,87,6,5.0,0,97,Urban,Software Engineer,106513,1 +119974,Female,52,Bachelors,8,98,29,58,20,2.0,3,51,Semi-Urban,HR Executive,74418,0 +32945,Male,23,Masters,16,68,84,87,62,9.0,2,98,Urban,HR Executive,51277,1 +114698,Male,34,High School,6,27,48,6,45,9.0,1,15,Rural,ML Engineer,52452,0 +7218,Female,57,High School,11,62,69,4,58,1.0,4,43,Urban,HR Executive,43269,0 +37990,Male,42,Diploma,15,73,19,81,68,9.0,0,92,Urban,ML Engineer,118525,1 +112760,Male,44,Bachelors,15,97,26,31,27,9.0,4,22,Urban,ML Engineer,81980,0 +1003,Female,42,Masters,9,88,53,7,43,1.0,6,35,Urban,Software Engineer,80558,0 +17436,Male,38,Bachelors,16,20,92,38,41,4.0,4,94,Urban,ML Engineer,25513,1 +51758,Other,30,Diploma,6,45,30,40,81,0.0,0,6,Urban,Manager,66070,0 +59876,Male,45,Bachelors,18,35,32,43,28,8.0,1,61,Urban,Data Analyst,62538,0 +19390,Male,50,Bachelors,6,42,70,48,91,2.0,2,37,Semi-Urban,ML Engineer,76023,0 +69336,Female,52,Masters,8,44,50,75,4,2.0,2,84,Urban,HR Executive,95316,1 +70970,Male,25,Masters,17,12,79,70,15,8.0,1,46,Rural,ML Engineer,69456,0 +65919,Female,40,Bachelors,1,88,64,93,77,9.0,4,64,Semi-Urban,ML Engineer,87068,1 +107332,Female,36,Bachelors,2,1,91,55,16,1.0,6,90,Urban,ML Engineer,80698,0 +72174,Female,31,Bachelors,2,84,88,62,6,3.0,1,99,Semi-Urban,Software Engineer,59403,1 +49504,Female,28,Masters,19,92,17,25,33,9.0,6,74,Urban,HR Executive,83473,0 +57742,Male,22,Masters,9,16,81,99,97,7.0,2,58,Semi-Urban,Data Analyst,75704,1 +67708,Male,42,High School,16,8,56,96,49,4.0,4,56,Semi-Urban,HR Executive,60315,0 +98982,Other,40,High School,15,3,21,74,22,3.0,7,1,Rural,Manager,119594,0 +70676,Female,58,Masters,19,86,1,27,32,4.0,1,49,Rural,Manager,77159,0 +97841,Male,26,Diploma,0,8,25,45,92,3.0,4,37,Urban,Software Engineer,80945,0 +41937,Female,23,Bachelors,2,82,18,55,1,6.0,3,93,Urban,HR Executive,45325,1 +113551,Female,55,High School,4,97,36,45,24,4.0,3,74,Urban,Manager,62147,1 +4917,Male,21,Masters,0,81,44,16,67,3.0,1,7,Urban,Software Engineer,22619,0 +101730,Male,32,High School,8,79,75,78,33,6.0,6,3,Urban,Data Analyst,69969,1 +13917,Female,29,Bachelors,15,40,24,12,62,0.0,7,35,Rural,ML Engineer,28246,0 +43828,Female,42,Bachelors,13,66,94,48,14,3.0,7,92,Rural,Data Analyst,22993,1 +102474,Female,43,PhD,3,17,91,85,82,5.0,3,6,Urban,Software Engineer,82840,0 +116706,Male,40,Diploma,3,69,39,69,55,6.0,3,23,Semi-Urban,Software Engineer,140732,0 +8988,Female,47,Diploma,11,73,4,60,80,0.0,6,60,Urban,Data Analyst,84941,0 +111315,Female,36,Bachelors,13,44,83,19,40,1.0,4,94,Urban,Manager,133680,0 +74757,Male,52,Bachelors,14,68,29,65,60,5.0,3,47,Rural,Software Engineer,74274,0 +29828,Male,22,Diploma,4,86,76,69,41,9.0,7,76,Rural,Data Analyst,27431,1 +55763,Male,55,Bachelors,15,15,52,30,46,2.0,0,57,Urban,Manager,80768,0 +86407,Female,56,Bachelors,1,78,99,66,80,6.0,4,99,Rural,Data Analyst,37591,1 +29841,Female,45,Bachelors,4,4,52,5,31,3.0,2,96,Urban,HR Executive,129152,0 +61120,Female,21,PhD,0,84,50,80,60,5.0,7,90,Urban,Manager,131848,1 +117446,Female,23,Diploma,12,71,54,0,49,7.0,1,40,Urban,HR Executive,24313,0 +3560,Male,39,Bachelors,16,13,63,98,2,8.0,7,23,Urban,HR Executive,131591,0 +10913,Male,33,PhD,11,74,80,41,97,0.0,3,57,Urban,ML Engineer,74622,1 +70754,Female,54,Diploma,0,65,20,35,73,8.0,0,74,Urban,Software Engineer,101268,0 +2563,Male,41,Bachelors,0,41,4,65,22,1.0,6,5,Urban,HR Executive,128695,0 +33478,Male,28,Bachelors,3,42,40,59,96,0.0,4,80,Semi-Urban,Software Engineer,97965,0 +25992,Male,58,Masters,12,96,12,74,74,0.0,5,54,Urban,Data Analyst,41974,1 +76126,Female,54,Bachelors,10,92,98,17,50,2.0,3,59,Rural,ML Engineer,124712,1 +38331,Other,31,Masters,4,5,29,99,66,9.0,6,10,Urban,Data Analyst,62636,0 +74021,Female,50,Bachelors,15,31,79,77,29,9.0,4,74,Rural,Manager,79880,1 +47276,Female,35,Bachelors,6,98,37,40,73,6.0,2,55,Urban,Data Analyst,93708,0 +117950,Male,22,Bachelors,2,87,13,82,9,4.0,4,11,Urban,ML Engineer,89514,0 +71373,Female,30,Bachelors,3,82,31,56,18,0.0,6,31,Urban,Manager,61634,0 +102325,Female,56,PhD,0,92,64,85,58,4.0,7,31,Urban,HR Executive,93583,1 +82051,Female,57,Diploma,16,53,31,36,81,4.0,2,2,Urban,Manager,133690,0 +73078,Male,35,High School,3,97,64,9,62,4.0,7,84,Urban,HR Executive,80064,1 +20738,Male,33,Bachelors,6,19,75,92,39,8.0,1,59,Semi-Urban,Data Analyst,30857,1 +34581,Female,52,Bachelors,9,38,90,31,48,1.0,0,6,Urban,Manager,47902,0 +92640,Male,42,Diploma,19,30,44,45,52,5.0,3,40,Semi-Urban,Manager,95911,0 +52421,Other,46,Bachelors,15,54,84,16,84,2.0,7,33,Urban,HR Executive,47938,0 +83340,Male,54,Diploma,4,44,52,6,87,7.0,2,77,Urban,HR Executive,88928,0 +41304,Female,32,Bachelors,14,60,38,79,93,7.0,6,96,Rural,Software Engineer,111675,1 +14343,Male,23,Masters,17,99,8,73,69,6.0,6,39,Semi-Urban,HR Executive,25539,0 +34117,Female,23,Bachelors,13,37,91,87,34,6.0,0,60,Urban,ML Engineer,112740,1 +112594,,23,Masters,18,59,0,91,43,4.0,7,70,Rural,HR Executive,111787,0 +66303,Female,51,Diploma,17,99,68,41,16,1.0,1,77,Urban,ML Engineer,58127,1 +48871,Female,26,Bachelors,9,36,70,95,72,5.0,1,44,Semi-Urban,HR Executive,26183,1 +81039,Male,48,Bachelors,16,75,15,36,33,6.0,1,57,Urban,Data Analyst,37701,0 +89095,Male,57,Diploma,15,86,3,33,40,0.0,7,46,Urban,Manager,145645,0 +51193,Female,29,Diploma,19,32,65,86,61,0.0,3,25,Urban,HR Executive,70373,0 +15102,Male,55,Masters,10,34,18,88,90,0.0,7,42,Semi-Urban,HR Executive,115527,0 +44844,Male,37,High School,18,15,32,32,28,2.0,2,51,Rural,Data Analyst,52523,0 +99178,Female,33,High School,16,65,81,56,64,4.0,2,98,Semi-Urban,ML Engineer,97803,1 +28231,Male,29,Diploma,14,96,57,17,43,5.0,5,94,Semi-Urban,Software Engineer,78666,1 +32727,Male,56,PhD,1,38,66,36,56,0.0,4,96,Urban,Manager,114221,1 +57312,Female,34,Masters,7,70,30,5,37,3.0,4,94,Urban,HR Executive,109700,0 +17708,Male,35,Masters,18,95,18,96,1,7.0,2,79,Semi-Urban,Data Analyst,40671,1 +22955,Male,39,Masters,9,17,22,61,42,9.0,2,37,Urban,Software Engineer,49400,0 +24992,Male,41,Diploma,19,86,79,12,55,4.0,2,3,Semi-Urban,Software Engineer,86568,0 +9025,Male,35,PhD,18,68,95,47,48,1.0,0,65,Rural,ML Engineer,107093,1 +49949,Male,45,Bachelors,3,31,2,89,5,9.0,1,95,Urban,Data Analyst,81282,0 +112544,Female,42,High School,0,90,64,65,41,4.0,2,40,Urban,HR Executive,77145,1 +108068,Male,26,Bachelors,4,20,66,57,36,9.0,1,82,Semi-Urban,ML Engineer,64683,0 +59751,Female,45,Bachelors,7,7,59,57,64,3.0,1,98,Rural,Software Engineer,103283,0 +112997,Male,39,Bachelors,17,79,82,23,3,0.0,3,57,Rural,Manager,117023,1 +24588,Male,56,Masters,19,44,15,86,43,0.0,4,41,Urban,Manager,80857,0 +61181,Female,55,Bachelors,5,83,23,60,27,2.0,5,16,Semi-Urban,Software Engineer,97071,0 +10648,Female,30,Diploma,19,10,32,59,50,9.0,3,80,Urban,Software Engineer,50204,0 +13045,Male,23,Bachelors,1,74,17,96,15,2.0,0,21,Urban,HR Executive,110245,0 +93050,Male,31,Bachelors,3,10,10,37,65,4.0,3,31,Rural,Software Engineer,64623,0 +24528,Male,23,Masters,14,19,80,41,10,8.0,5,51,Urban,HR Executive,88743,0 +109594,Other,39,High School,4,28,19,38,53,6.0,6,77,Semi-Urban,HR Executive,141697,0 +82694,Male,40,High School,1,98,30,61,56,3.0,4,62,Urban,ML Engineer,136080,1 +45786,Female,21,High School,11,2,82,20,57,9.0,0,36,Semi-Urban,Software Engineer,38631,0 +86723,Male,27,Bachelors,4,44,42,71,42,4.0,7,10,Urban,ML Engineer,142200,0 +101027,Male,48,Bachelors,4,48,7,59,0,7.0,3,5,Urban,ML Engineer,57802,0 +48417,Male,51,Masters,7,63,98,63,72,3.0,1,5,Rural,ML Engineer,90841,0 +61008,Male,55,High School,7,84,19,89,93,3.0,6,88,Urban,Data Analyst,93828,1 +111009,Other,34,Bachelors,3,74,65,79,12,4.0,2,15,Rural,Manager,57222,0 +118258,Male,31,Diploma,16,58,4,80,45,4.0,0,30,Urban,ML Engineer,88476,0 +10044,Male,21,High School,18,97,68,98,22,1.0,6,67,Semi-Urban,Data Analyst,33868,1 +85311,Female,51,Bachelors,18,80,68,71,94,1.0,1,13,Rural,Data Analyst,141080,0 +73119,Male,24,Bachelors,16,26,67,50,17,6.0,3,31,Semi-Urban,Software Engineer,121209,0 +41230,Female,37,Masters,19,95,97,90,42,9.0,5,37,Urban,ML Engineer,130853,1 +27172,Male,42,PhD,5,94,9,6,54,4.0,4,99,Urban,HR Executive,100274,0 +118670,Male,49,Bachelors,19,5,79,11,88,1.0,7,19,Urban,HR Executive,79972,0 +38189,Female,53,Bachelors,16,59,95,96,73,1.0,7,46,Urban,Data Analyst,99339,1 +47244,Male,28,Diploma,2,27,21,95,20,3.0,3,11,Urban,Software Engineer,27949,0 +104373,Male,52,High School,3,87,14,95,2,2.0,4,72,Semi-Urban,ML Engineer,46951,1 +56256,Female,41,Diploma,5,83,22,50,59,8.0,4,94,Urban,HR Executive,54872,1 +106348,Male,23,PhD,0,21,39,46,48,9.0,3,60,Urban,Software Engineer,42830,0 +11259,Female,31,Masters,4,1,50,70,0,0.0,2,42,Urban,HR Executive,117364,0 +93642,Female,59,Bachelors,1,59,43,76,77,0.0,3,8,Urban,HR Executive,89247,0 +56622,Female,36,High School,11,80,43,62,5,6.0,6,18,Rural,Data Analyst,38379,0 +70594,Male,59,PhD,10,28,14,63,72,1.0,5,95,Urban,ML Engineer,26803,0 +86566,Female,44,Bachelors,14,14,95,70,39,1.0,7,30,Urban,HR Executive,117323,0 +62508,Female,51,Bachelors,15,24,78,17,10,7.0,4,43,Urban,Data Analyst,109969,0 +38499,Female,24,Diploma,14,63,87,82,89,1.0,7,19,Semi-Urban,Manager,55923,1 +100711,Male,49,Bachelors,18,87,58,63,7,9.0,4,78,Rural,Software Engineer,68444,1 +115569,Male,28,Masters,14,3,23,34,13,2.0,0,71,Urban,HR Executive,79274,0 +64073,Female,21,Masters,19,36,0,37,17,8.0,3,7,Urban,ML Engineer,85493,0 +34168,Male,31,Masters,16,68,39,56,56,2.0,1,61,Urban,Data Analyst,70596,0 +84771,Male,31,PhD,9,65,74,24,91,4.0,4,26,Urban,Software Engineer,98876,0 +64597,Male,22,Bachelors,9,67,34,37,34,4.0,7,29,Urban,Data Analyst,142886,0 +107570,Male,38,Bachelors,18,72,62,45,93,8.0,2,36,Rural,Data Analyst,91705,0 +97166,Female,53,Diploma,0,99,2,58,11,1.0,4,24,Urban,Manager,87988,0 +90605,Male,25,Bachelors,13,67,55,48,68,1.0,6,14,Semi-Urban,HR Executive,77412,0 +59786,Male,41,Bachelors,13,31,32,85,17,5.0,6,42,Urban,ML Engineer,31274,0 +8252,Other,54,Bachelors,15,87,3,80,67,0.0,1,18,Semi-Urban,ML Engineer,25903,0 +30462,Male,27,Masters,10,77,46,27,65,2.0,7,3,Semi-Urban,HR Executive,112930,0 +57647,Male,47,Bachelors,11,23,84,74,8,3.0,7,87,Urban,Software Engineer,127755,1 +57600,Female,26,Diploma,12,71,50,55,29,5.0,7,10,Urban,Data Analyst,134289,0 +24767,Male,29,Diploma,15,72,97,67,47,2.0,3,24,Semi-Urban,Data Analyst,117799,1 +1940,Male,29,Bachelors,2,29,70,85,45,4.0,0,49,Urban,Data Analyst,54238,0 +82911,Female,56,High School,0,38,46,75,70,6.0,3,26,Semi-Urban,Manager,85018,0 +78867,Male,51,Bachelors,1,61,65,14,7,0.0,6,40,Semi-Urban,ML Engineer,94537,0 +88810,Male,50,Bachelors,9,78,20,82,19,1.0,7,97,Semi-Urban,Software Engineer,80005,1 +25393,Male,41,PhD,11,48,33,78,19,1.0,5,62,Urban,Data Analyst,148126,0 +88672,Male,39,Masters,7,98,5,44,35,8.0,2,37,Urban,HR Executive,131720,0 +65031,Male,46,Masters,12,16,61,90,20,5.0,1,8,Semi-Urban,HR Executive,48279,0 +12903,Male,32,Bachelors,16,73,21,33,97,3.0,2,43,Rural,ML Engineer,23011,0 +85612,Male,55,Bachelors,3,60,11,65,11,1.0,4,52,Semi-Urban,Manager,109977,0 +39406,Male,41,Bachelors,11,24,63,42,63,5.0,6,66,Rural,ML Engineer,148917,0 +76415,Female,48,Bachelors,11,93,83,43,52,4.0,5,59,Rural,Data Analyst,57749,1 +77409,Female,24,Diploma,4,96,9,20,46,9.0,0,34,Urban,Manager,142197,0 +113768,Male,59,PhD,2,66,48,50,54,7.0,3,34,Urban,ML Engineer,106808,0 +12802,Male,36,Bachelors,4,81,47,56,30,7.0,5,77,Semi-Urban,Data Analyst,90147,1 +63033,Male,43,Masters,9,23,80,82,14,9.0,1,20,Urban,HR Executive,69077,0 +59660,Female,25,PhD,15,69,82,75,21,5.0,3,21,Urban,Manager,77446,1 +32977,Male,41,Bachelors,9,5,89,70,53,4.0,0,55,Semi-Urban,Data Analyst,59263,0 +8803,Male,21,Bachelors,15,33,38,8,66,1.0,0,23,Urban,HR Executive,142560,0 +81959,Male,32,Bachelors,12,8,67,1,81,7.0,1,97,Rural,ML Engineer,116527,0 +77640,Male,46,Bachelors,19,3,42,88,44,2.0,2,67,Semi-Urban,HR Executive,102642,0 +115292,Male,46,Masters,1,78,74,97,63,9.0,5,75,Urban,Manager,56641,1 +56213,Male,53,Bachelors,19,15,2,37,34,1.0,5,78,Rural,Data Analyst,38808,0 +77383,Female,57,Bachelors,17,97,94,48,27,9.0,6,5,Urban,Software Engineer,73823,1 +74250,Male,47,Bachelors,14,40,90,96,64,4.0,2,58,Rural,Software Engineer,32485,1 +28926,Female,48,High School,18,75,62,53,65,5.0,5,67,Rural,Software Engineer,82885,1 +41210,Male,40,Bachelors,0,7,1,90,38,4.0,3,14,Urban,ML Engineer,45103,0 +67402,Male,55,Bachelors,3,91,90,80,77,9.0,6,27,Urban,HR Executive,88672,1 +92652,Male,55,Bachelors,10,75,30,94,4,6.0,4,25,Urban,Software Engineer,149973,0 +42501,Male,46,Bachelors,5,12,26,25,43,5.0,3,17,Urban,Manager,138036,0 +115499,Male,40,Bachelors,11,9,89,84,10,2.0,3,45,Urban,Data Analyst,141582,0 +28544,Male,36,PhD,14,10,26,88,58,7.0,5,3,Urban,Software Engineer,134905,0 +26550,Male,54,Bachelors,4,70,48,78,0,2.0,6,31,Semi-Urban,HR Executive,118004,0 +512,Male,40,PhD,3,79,80,57,67,0.0,4,42,Semi-Urban,Data Analyst,131676,1 +27725,Female,48,Diploma,7,86,91,59,40,2.0,7,2,Urban,HR Executive,59348,0 +71417,Male,23,Masters,19,98,52,59,95,7.0,0,49,Semi-Urban,Data Analyst,32685,1 +31708,Male,58,PhD,3,95,84,17,0,1.0,1,80,Urban,HR Executive,98646,1 +44657,Male,49,High School,17,10,28,88,83,7.0,3,18,Urban,ML Engineer,121198,0 +80970,Male,42,Masters,18,41,58,67,40,6.0,2,88,Urban,HR Executive,72320,1 +73976,Female,21,Bachelors,2,52,89,55,28,3.0,0,86,Urban,Data Analyst,140319,1 +97396,Other,45,High School,16,77,31,47,71,5.0,2,62,Semi-Urban,Manager,66049,0 +19904,Male,29,Bachelors,6,77,12,23,35,4.0,2,69,Urban,HR Executive,119389,0 +64420,Male,53,PhD,14,45,67,89,91,5.0,4,85,Urban,HR Executive,135212,1 +106405,Male,29,High School,6,63,16,35,63,1.0,2,88,Urban,Software Engineer,61047,0 +102753,Male,57,Bachelors,4,77,65,28,29,6.0,1,47,Semi-Urban,Manager,66175,0 +76938,Male,33,Diploma,0,14,99,34,82,3.0,3,96,Rural,HR Executive,134204,1 +59875,Male,38,Masters,14,84,26,11,32,4.0,5,22,Urban,Software Engineer,110188,0 +110908,Female,40,High School,19,67,83,10,42,3.0,6,61,Urban,HR Executive,107141,0 +41710,Male,54,Diploma,7,90,9,1,84,0.0,5,23,Urban,ML Engineer,115748,0 +100216,Female,46,High School,5,43,20,87,41,5.0,6,4,Semi-Urban,Software Engineer,96394,0 +106621,Male,41,Bachelors,12,43,20,44,77,4.0,1,96,Semi-Urban,Software Engineer,143858,0 +1284,Male,31,Bachelors,0,9,36,75,62,6.0,4,46,Semi-Urban,ML Engineer,48828,0 +92096,Female,30,Diploma,7,34,55,86,98,6.0,6,95,Semi-Urban,HR Executive,109655,1 +48677,Male,46,Bachelors,11,65,19,55,47,8.0,1,14,Semi-Urban,Software Engineer,36752,0 +57864,Male,51,Bachelors,1,57,49,15,38,5.0,3,21,Urban,Software Engineer,124495,0 +51819,Male,37,Diploma,18,43,48,82,29,5.0,4,24,Semi-Urban,Software Engineer,50302,0 +70309,Other,38,High School,5,41,10,13,19,4.0,0,93,Rural,Software Engineer,45224,0 +51585,Female,47,Bachelors,4,99,81,91,33,7.0,0,86,Urban,Software Engineer,56710,1 +90813,Female,36,Diploma,3,28,92,40,64,9.0,7,96,Rural,Software Engineer,23324,1 +104623,Male,43,Bachelors,10,66,41,20,87,0.0,5,86,Semi-Urban,Data Analyst,72438,0 +116856,Male,49,PhD,19,88,45,77,93,4.0,4,15,Urban,ML Engineer,94061,0 +71974,Female,51,High School,0,86,7,77,56,5.0,7,7,Urban,Manager,128942,0 +43725,Male,56,PhD,13,54,85,16,58,4.0,6,84,Semi-Urban,Manager,141735,1 +76821,Male,46,Bachelors,7,52,61,80,19,3.0,5,76,Rural,Manager,114879,1 +34194,Male,30,Bachelors,16,48,35,39,90,5.0,7,47,Urban,Software Engineer,146960,0 +16743,Female,47,Bachelors,0,83,47,34,20,5.0,0,92,Urban,Software Engineer,142794,1 +42201,Other,55,Diploma,4,14,53,71,97,9.0,1,3,Semi-Urban,ML Engineer,129576,0 +20785,Female,50,Masters,8,27,61,49,81,8.0,3,85,Urban,HR Executive,136066,0 +74952,Male,24,Masters,10,24,64,30,66,4.0,4,72,Urban,HR Executive,51009,0 +69139,Male,26,Bachelors,14,54,5,80,62,5.0,7,63,Rural,Data Analyst,52725,0 +45953,Female,41,High School,5,74,50,36,39,0.0,4,58,Urban,Data Analyst,120215,0 +87360,Female,57,Bachelors,13,54,2,8,35,0.0,4,36,Semi-Urban,Software Engineer,144822,0 +957,Male,38,Bachelors,6,88,34,68,41,6.0,7,98,Urban,Manager,75009,1 +34571,Female,22,Bachelors,10,80,26,48,99,7.0,7,31,Urban,Data Analyst,147707,0 +117443,Female,56,Diploma,2,65,8,95,59,8.0,3,60,Urban,Manager,71992,0 +117431,Male,50,Diploma,7,75,2,74,59,4.0,4,99,Semi-Urban,Software Engineer,82960,1 +20361,Other,24,Bachelors,11,48,19,28,40,6.0,4,15,Urban,ML Engineer,94612,0 +71481,Female,46,Bachelors,11,99,84,53,56,9.0,7,35,Urban,HR Executive,109047,1 +107275,Female,52,Masters,12,41,76,75,3,2.0,3,68,Urban,Software Engineer,42500,1 +34078,Male,53,Diploma,9,47,13,31,77,1.0,2,13,Semi-Urban,Software Engineer,57401,0 +12269,Female,41,Masters,1,48,54,90,80,8.0,3,65,Urban,HR Executive,106861,1 +24840,Female,51,Masters,19,83,88,18,96,4.0,4,42,Rural,HR Executive,89231,0 +29769,Female,41,Bachelors,15,68,99,54,47,6.0,2,91,Semi-Urban,ML Engineer,143248,1 +87508,Female,59,Bachelors,7,41,88,16,58,3.0,6,75,Rural,Software Engineer,46778,0 +23633,Male,34,Bachelors,17,64,44,0,64,6.0,0,80,Urban,ML Engineer,71666,0 +55169,Male,51,Bachelors,15,32,30,85,82,2.0,4,91,Urban,Manager,25130,1 +80329,Female,59,Bachelors,12,73,46,56,18,2.0,3,66,Urban,HR Executive,144854,1 +2591,Female,36,Bachelors,3,30,35,45,42,0.0,7,98,Urban,Data Analyst,114972,0 +14776,Female,30,Bachelors,18,29,15,89,70,6.0,6,10,Urban,HR Executive,75094,0 +30246,Female,28,PhD,10,85,33,0,41,0.0,4,9,Urban,ML Engineer,117383,0 +90186,Female,33,Bachelors,4,15,29,18,15,5.0,7,38,Urban,Manager,32972,0 +96064,Male,48,PhD,7,99,24,22,9,6.0,6,23,Urban,ML Engineer,146718,0 +36863,Female,36,Diploma,18,44,20,88,63,7.0,0,89,Urban,HR Executive,47011,1 +113691,Male,30,Diploma,3,98,36,72,37,9.0,2,59,Semi-Urban,HR Executive,122655,1 +6471,Female,49,PhD,1,44,27,21,66,0.0,1,26,Urban,Software Engineer,40141,0 +14944,Male,35,Bachelors,16,20,28,54,43,8.0,4,32,Semi-Urban,Manager,137400,0 +104305,Female,57,Diploma,5,79,79,59,63,3.0,5,18,Urban,Software Engineer,138194,0 +40079,Male,31,Bachelors,15,3,3,26,41,1.0,3,4,Semi-Urban,ML Engineer,102299,0 +106647,Male,26,Masters,13,82,10,79,38,4.0,1,29,Semi-Urban,Software Engineer,117137,0 +75164,Male,49,Diploma,0,8,94,80,20,6.0,6,68,Urban,HR Executive,115826,1 +109433,Male,41,Masters,0,73,50,90,14,8.0,2,5,Urban,Data Analyst,46026,0 +106907,Male,28,Diploma,12,1,93,85,69,5.0,3,58,Urban,HR Executive,90472,1 +2289,Male,23,Diploma,8,76,34,85,33,8.0,6,53,Urban,Software Engineer,146463,1 +13047,Male,39,High School,11,78,73,3,38,4.0,2,58,Rural,ML Engineer,81637,0 +11268,Male,39,Bachelors,4,28,23,73,5,0.0,0,79,Urban,ML Engineer,140893,0 +26209,Male,48,Bachelors,15,53,2,43,4,7.0,4,52,Urban,HR Executive,133717,0 +74820,Male,33,High School,12,2,48,17,84,1.0,7,3,Urban,Manager,84125,0 +72512,Female,34,Bachelors,9,75,3,90,79,6.0,2,62,Urban,Software Engineer,98319,0 +10882,Male,36,Bachelors,17,17,74,12,92,1.0,4,16,Semi-Urban,HR Executive,54359,0 +38653,Male,42,Masters,4,34,6,36,96,1.0,5,91,Semi-Urban,Software Engineer,35870,0 +109161,Male,23,Diploma,2,34,94,12,78,5.0,4,26,Semi-Urban,Software Engineer,55207,0 +97211,Male,33,Diploma,11,56,83,16,65,0.0,5,27,Urban,Manager,37385,0 +211,Male,37,Bachelors,1,17,85,72,69,1.0,6,68,Rural,Data Analyst,58605,1 +28839,Male,31,High School,15,44,61,71,37,1.0,7,52,Urban,Software Engineer,44125,0 +12983,Male,30,High School,2,68,67,6,12,9.0,6,48,Rural,Data Analyst,59765,0 +79512,Male,50,Masters,15,29,66,21,77,0.0,6,44,Semi-Urban,HR Executive,116175,0 +118340,Female,52,Bachelors,15,82,95,62,82,1.0,3,25,Urban,HR Executive,97556,1 +95082,Male,43,Bachelors,10,99,31,52,53,0.0,5,80,Semi-Urban,Software Engineer,143914,1 +71952,Female,54,Bachelors,0,45,48,27,44,2.0,4,66,Semi-Urban,ML Engineer,145013,0 +111097,Male,41,PhD,15,8,0,90,21,3.0,0,93,Urban,HR Executive,104835,0 +73370,Other,36,Bachelors,3,76,84,2,12,2.0,1,2,Urban,Software Engineer,22779,0 +14895,Male,32,Bachelors,0,61,52,21,48,2.0,3,91,Rural,Data Analyst,98952,0 +75101,Male,41,Diploma,15,81,60,24,46,9.0,1,56,Semi-Urban,Data Analyst,57005,0 +24540,Female,51,Masters,7,90,4,59,40,8.0,5,57,Semi-Urban,HR Executive,128764,0 +26825,Female,26,Bachelors,0,9,45,28,13,6.0,2,3,Urban,Software Engineer,139240,0 +36219,Male,42,Bachelors,1,19,18,89,23,1.0,3,56,Urban,HR Executive,110423,0 +117098,Male,45,Bachelors,19,7,37,67,93,1.0,1,68,Urban,HR Executive,131954,0 +22697,Male,26,Bachelors,3,27,7,3,96,5.0,0,54,Rural,HR Executive,40949,0 +13043,Other,23,Masters,10,12,78,60,93,4.0,3,58,Urban,HR Executive,147599,0 +102506,Female,37,PhD,1,18,30,79,47,7.0,0,64,Urban,HR Executive,71655,0 +47292,Other,55,Diploma,13,21,65,15,46,8.0,6,27,Semi-Urban,HR Executive,57888,0 +44710,Male,34,High School,3,25,98,41,82,2.0,2,1,Rural,Software Engineer,105894,0 +42610,Male,58,Diploma,11,8,60,67,76,5.0,5,93,Semi-Urban,ML Engineer,32018,0 +52631,Male,39,Masters,15,97,14,11,87,5.0,6,47,Urban,Software Engineer,119393,0 +13235,Female,29,Diploma,4,49,58,43,68,7.0,4,68,Urban,Software Engineer,23986,0 +92453,Female,33,High School,16,29,3,87,63,5.0,4,78,Urban,Data Analyst,127003,0 +63244,Male,43,Bachelors,7,95,45,2,55,0.0,1,97,Rural,Software Engineer,44927,1 +15669,Female,42,Bachelors,6,25,8,37,30,5.0,7,95,Urban,Data Analyst,94249,0 +85685,Male,41,High School,8,63,41,95,93,9.0,2,28,Urban,Manager,90571,0 +66865,Male,55,Bachelors,16,48,34,71,27,0.0,6,2,Semi-Urban,Manager,48804,0 +117996,Male,35,Bachelors,10,93,52,38,96,3.0,7,4,Semi-Urban,Software Engineer,67463,0 +22647,Other,45,Bachelors,19,74,96,95,6,9.0,5,32,Rural,Manager,97645,1 +43212,Male,33,Diploma,7,15,75,95,43,3.0,2,46,Semi-Urban,Software Engineer,28563,0 +12403,Male,52,Bachelors,7,91,60,18,93,4.0,0,77,Rural,Data Analyst,117281,1 +37895,Male,43,Bachelors,1,26,91,69,6,8.0,3,1,Rural,Data Analyst,148593,0 +92717,Female,51,Diploma,18,13,12,77,57,7.0,6,68,Urban,Software Engineer,129780,0 +75951,Female,43,Masters,1,65,83,47,29,4.0,5,98,Urban,HR Executive,47461,1 +101946,Female,30,Bachelors,12,99,68,81,83,2.0,5,13,Semi-Urban,HR Executive,90154,1 +5661,Male,50,Bachelors,9,33,39,34,98,7.0,2,56,Urban,ML Engineer,56979,0 +41071,Other,34,Masters,19,26,37,94,40,6.0,6,66,Urban,HR Executive,138998,0 +77562,Male,39,Diploma,9,67,48,56,54,6.0,2,16,Urban,Manager,57373,0 +81477,Female,33,Diploma,19,74,4,38,79,5.0,5,87,Urban,HR Executive,112752,0 +11887,Male,48,Masters,16,93,76,85,97,9.0,6,91,Urban,Software Engineer,43361,1 +24939,Male,57,Bachelors,7,14,33,90,70,8.0,6,12,Urban,HR Executive,76696,0 +73399,Male,35,Bachelors,18,60,68,35,12,1.0,4,19,Rural,Software Engineer,55489,0 +88929,Female,42,Bachelors,7,80,43,13,7,9.0,4,89,Urban,Manager,97748,0 +111887,Male,28,High School,16,38,13,72,27,8.0,3,31,Rural,Manager,69188,0 +9073,Male,35,Bachelors,12,22,34,16,73,8.0,2,76,Semi-Urban,HR Executive,87912,0 +86069,Male,56,Bachelors,17,18,1,88,24,8.0,1,58,Urban,Manager,117537,0 +77352,Male,55,Masters,9,49,20,3,8,7.0,1,33,Urban,Software Engineer,136718,0 +37360,Female,32,Masters,7,56,71,51,24,2.0,4,83,Rural,Manager,29522,1 +44343,Female,27,Masters,15,70,76,88,41,6.0,1,70,Urban,ML Engineer,30035,1 +55999,Female,49,Diploma,0,8,1,87,31,2.0,4,81,Semi-Urban,Data Analyst,73832,0 +113569,Male,49,Masters,14,22,48,14,27,2.0,7,31,Semi-Urban,HR Executive,132418,0 +96259,Male,41,Masters,12,9,53,7,22,4.0,2,8,Urban,ML Engineer,39675,0 +5092,Male,40,Bachelors,8,10,16,19,49,9.0,2,45,Semi-Urban,HR Executive,99072,0 +39163,Other,43,Bachelors,8,92,23,33,62,6.0,4,44,Urban,ML Engineer,24332,0 +42677,Male,24,Bachelors,13,30,5,80,80,6.0,7,92,Urban,Software Engineer,20129,0 +88429,Male,43,Diploma,11,37,34,96,12,2.0,6,18,Urban,Software Engineer,111292,0 +44890,Male,41,Masters,1,87,52,92,62,0.0,1,73,Urban,ML Engineer,85175,1 +21533,Male,52,Bachelors,15,60,80,56,80,7.0,0,15,Rural,Manager,102183,0 +50165,Other,52,High School,16,60,91,16,41,9.0,1,12,Semi-Urban,Software Engineer,68056,0 +87736,Male,29,Bachelors,19,73,83,91,49,6.0,4,29,Urban,ML Engineer,88052,1 +86061,Female,58,Diploma,8,28,92,48,15,8.0,7,86,Semi-Urban,Software Engineer,146700,1 +79169,Female,59,Bachelors,0,2,36,37,81,0.0,1,64,Semi-Urban,ML Engineer,61467,0 +54338,Other,53,Diploma,17,40,79,57,17,2.0,4,21,Rural,HR Executive,146960,0 +58278,Female,53,High School,5,28,42,14,63,0.0,1,28,Urban,Data Analyst,108230,0 +61095,Female,41,Bachelors,12,10,69,22,34,8.0,5,87,Rural,Software Engineer,78113,0 +53258,Male,47,Diploma,14,76,48,75,11,5.0,3,99,Semi-Urban,Software Engineer,148052,1 +14144,Male,24,Masters,1,95,86,10,63,7.0,2,75,Semi-Urban,Data Analyst,116469,1 +60307,Male,21,Masters,10,63,53,82,73,8.0,6,34,Rural,Software Engineer,61309,0 +39481,Female,31,Bachelors,12,70,60,73,56,2.0,1,50,Urban,Software Engineer,41302,1 +104473,Other,55,Bachelors,18,73,43,41,58,7.0,4,50,Semi-Urban,Manager,141276,0 +19322,Other,59,Diploma,6,17,84,65,69,9.0,4,2,Urban,Software Engineer,108126,0 +101037,Male,32,Masters,14,1,11,30,88,1.0,7,28,Rural,ML Engineer,128775,0 +18722,Female,56,Bachelors,10,14,72,94,82,3.0,7,82,Urban,Software Engineer,79380,1 +111063,Female,28,Masters,6,54,25,91,16,2.0,1,45,Urban,Software Engineer,85777,0 +104930,Female,51,High School,3,21,20,90,84,5.0,0,94,Urban,Software Engineer,88028,0 +52313,Male,59,Masters,5,23,88,14,92,4.0,6,68,Rural,HR Executive,125275,0 +41353,Male,48,Bachelors,6,83,26,35,31,0.0,4,14,Semi-Urban,Software Engineer,133459,0 +116170,Male,46,Masters,19,63,71,26,32,6.0,1,55,Semi-Urban,Software Engineer,93299,0 +26219,Male,54,Bachelors,17,50,30,74,74,2.0,4,87,Urban,HR Executive,48990,1 +88251,Male,31,Bachelors,16,81,4,60,26,7.0,5,76,Urban,Software Engineer,94011,0 +16990,Other,33,Bachelors,7,57,96,78,16,7.0,2,24,Rural,Manager,68560,1 +15968,Male,43,Diploma,18,34,99,58,95,9.0,5,91,Urban,ML Engineer,111048,1 +75008,Male,22,Diploma,11,74,92,22,27,4.0,1,51,Urban,HR Executive,78057,1 +56822,Male,56,High School,11,89,62,42,10,5.0,4,58,Urban,HR Executive,47231,1 +18263,Male,42,Bachelors,10,32,24,52,97,1.0,3,6,Semi-Urban,HR Executive,119287,0 +431,Male,41,Bachelors,15,65,85,83,88,9.0,6,47,Urban,HR Executive,112116,1 +6887,Male,32,Bachelors,2,81,20,84,67,7.0,6,1,Rural,Manager,67535,0 +31792,Male,42,High School,11,23,93,93,66,4.0,3,38,Semi-Urban,Software Engineer,89720,1 +77932,Male,41,Bachelors,15,56,60,32,51,9.0,0,0,Semi-Urban,Manager,45721,0 +7072,Male,40,Masters,12,20,41,78,42,4.0,4,25,Semi-Urban,Software Engineer,118143,0 +88303,Male,57,Bachelors,0,96,60,10,0,8.0,4,16,Rural,Data Analyst,94617,0 +49180,Male,56,Bachelors,7,70,83,11,72,4.0,0,72,Semi-Urban,Manager,85903,1 +36721,Female,27,High School,9,58,74,38,24,3.0,1,30,Rural,Manager,99253,0 +110790,Male,41,Bachelors,10,48,77,16,25,6.0,6,3,Urban,Manager,36756,0 +119394,Male,31,Masters,4,40,36,89,37,3.0,0,50,Semi-Urban,Software Engineer,141983,0 +9044,Male,33,Bachelors,12,4,24,76,39,4.0,1,42,Urban,HR Executive,26422,0 +11125,Male,55,PhD,17,0,15,71,2,8.0,3,97,Urban,Manager,112892,0 +6014,Male,43,Bachelors,18,94,25,72,72,2.0,2,79,Semi-Urban,ML Engineer,36056,1 +67355,Female,29,Masters,4,84,99,47,25,2.0,7,77,Semi-Urban,Manager,96319,1 +108471,Female,44,Diploma,17,30,86,75,99,3.0,7,34,Urban,ML Engineer,121117,0 +71836,Female,39,Masters,11,19,74,1,99,0.0,4,38,Urban,HR Executive,111843,0 +89920,Male,58,Bachelors,0,65,83,18,30,3.0,2,84,Urban,Software Engineer,124805,1 +67385,Male,52,Bachelors,6,9,92,80,12,7.0,0,98,Urban,Manager,142764,1 +44245,Other,25,Diploma,10,75,54,59,50,8.0,1,56,Urban,Manager,45546,1 +110235,Male,24,Masters,19,28,65,44,29,2.0,7,80,Urban,Manager,116782,0 +41515,Male,57,Bachelors,11,59,83,90,67,1.0,7,26,Rural,ML Engineer,47882,1 +107674,Male,23,Bachelors,10,88,78,35,88,3.0,6,8,Urban,Data Analyst,53461,0 +35367,Male,52,Bachelors,15,5,34,0,34,3.0,4,33,Semi-Urban,Software Engineer,54567,0 +20226,Male,42,Bachelors,8,0,12,45,79,7.0,3,83,Urban,HR Executive,44933,0 +73857,Female,40,High School,2,26,30,62,27,9.0,3,66,Urban,ML Engineer,49457,0 +96415,Female,23,Bachelors,14,45,58,73,56,7.0,5,35,Urban,Manager,27262,0 +91554,Male,53,High School,18,88,66,17,99,7.0,5,75,Semi-Urban,HR Executive,149829,1 +74046,Male,55,Diploma,5,1,94,82,76,9.0,6,57,Urban,Manager,93587,0 +107042,Other,50,Diploma,0,36,32,60,53,2.0,0,70,Urban,Data Analyst,74160,0 +33456,Male,21,Bachelors,13,27,68,34,57,4.0,4,44,Semi-Urban,Data Analyst,113411,0 +81985,Female,29,Masters,0,75,96,66,7,9.0,4,4,Semi-Urban,Data Analyst,20176,1 +30304,Male,43,High School,13,1,82,30,72,5.0,7,47,Urban,ML Engineer,25863,0 +85321,Male,48,Diploma,12,28,39,37,46,7.0,4,69,Urban,Data Analyst,126118,0 +9686,Male,24,Bachelors,7,83,93,56,66,1.0,0,33,Urban,HR Executive,30915,1 +47606,Male,55,Masters,12,45,22,36,13,3.0,6,11,Urban,ML Engineer,117438,0 +35039,Male,50,High School,0,57,90,47,83,9.0,7,2,Urban,Manager,70190,0 +28949,Male,33,Masters,1,15,65,74,20,3.0,3,66,Urban,HR Executive,32627,0 +8182,Male,59,Masters,11,94,23,58,39,8.0,0,70,Urban,HR Executive,134479,1 +30801,Female,38,Diploma,13,71,40,46,73,2.0,4,12,Rural,HR Executive,146736,0 +97171,Male,32,Bachelors,3,90,19,79,98,0.0,2,91,Urban,HR Executive,71469,1 +69714,Female,30,Masters,12,87,61,23,26,3.0,0,58,Urban,HR Executive,108565,0 +37288,Female,22,Diploma,15,63,72,84,12,2.0,2,40,Urban,ML Engineer,143490,1 +42861,Male,46,Bachelors,17,77,37,65,31,3.0,2,14,Urban,Software Engineer,127729,0 +88907,Male,52,Bachelors,17,1,22,84,80,4.0,0,83,Urban,ML Engineer,101342,0 +105801,Female,30,Diploma,11,90,40,1,79,9.0,1,81,Urban,Data Analyst,143654,0 +117897,Male,35,Diploma,2,65,94,74,40,7.0,3,9,Semi-Urban,Manager,44958,1 +45037,Male,44,High School,11,30,45,47,55,0.0,2,6,Semi-Urban,Manager,141760,0 +64393,Female,26,Diploma,14,72,89,11,94,2.0,5,88,Semi-Urban,Manager,116623,1 +29677,Male,50,Bachelors,17,18,49,9,20,6.0,6,31,Urban,Data Analyst,53021,0 +100143,Female,47,High School,7,71,64,99,72,0.0,1,44,Urban,Manager,106559,1 +27116,Male,21,Masters,6,11,45,28,59,6.0,0,63,Semi-Urban,ML Engineer,79843,0 +118636,Female,49,Diploma,1,59,56,51,58,7.0,2,95,Semi-Urban,HR Executive,47816,1 +44773,Female,25,Diploma,2,83,92,77,94,3.0,1,62,Semi-Urban,Software Engineer,81536,1 +112358,Female,23,Bachelors,12,1,97,87,14,6.0,5,5,Rural,Data Analyst,68767,0 +119073,Male,42,Masters,3,81,2,63,11,1.0,3,25,Urban,Software Engineer,48646,0 +11540,Female,59,Diploma,6,17,13,7,26,0.0,6,91,Urban,HR Executive,30151,0 +16075,Female,34,Bachelors,5,10,55,35,9,8.0,5,69,Rural,Manager,142086,0 +117045,Female,22,Masters,4,7,49,44,96,6.0,0,53,Urban,Software Engineer,43160,0 +84690,Female,52,Bachelors,18,2,28,24,60,7.0,7,59,Urban,Software Engineer,142889,0 +61528,Male,42,Bachelors,16,50,37,84,31,5.0,4,89,Semi-Urban,Software Engineer,38180,1 +103635,Female,21,Masters,13,74,76,69,2,2.0,0,50,Urban,ML Engineer,134279,1 +49543,Female,40,High School,8,60,10,11,33,2.0,7,95,Semi-Urban,Manager,108266,0 +45101,Male,24,Masters,2,63,2,89,5,4.0,1,55,Urban,Software Engineer,37436,0 +40500,Male,42,PhD,10,5,70,84,56,1.0,5,23,Semi-Urban,Software Engineer,75739,0 +103216,Male,22,Masters,19,82,80,95,0,7.0,3,84,Urban,Software Engineer,126353,1 +105206,Female,43,Bachelors,5,81,43,64,39,0.0,0,51,Urban,HR Executive,118373,0 +64422,Male,45,High School,8,35,90,41,30,4.0,5,1,Urban,Manager,86268,0 +100616,Male,42,Masters,13,73,10,7,71,4.0,2,32,Urban,Data Analyst,111345,0 +30838,Female,24,High School,9,98,32,35,73,7.0,5,64,Urban,Data Analyst,68385,0 +51904,Male,58,Bachelors,2,56,35,65,41,0.0,1,91,Urban,Manager,24112,1 +11423,Female,22,Masters,14,83,22,99,90,1.0,6,79,Urban,Software Engineer,49805,1 +88411,Male,34,Masters,13,86,99,45,99,6.0,1,75,Semi-Urban,HR Executive,145552,1 +75681,Male,27,Bachelors,1,30,40,81,84,7.0,2,22,Semi-Urban,Data Analyst,107286,0 +83938,Male,53,Bachelors,0,62,47,57,40,1.0,1,61,Urban,Data Analyst,111795,0 +92004,Male,49,Bachelors,3,72,27,89,41,1.0,0,75,Urban,Software Engineer,80301,1 +30340,Male,34,Masters,11,19,78,62,4,9.0,0,68,Urban,Data Analyst,130028,0 +116167,Other,21,Bachelors,13,98,6,85,48,0.0,5,14,Rural,Data Analyst,42558,0 +31956,Male,41,Bachelors,1,19,70,32,4,7.0,7,90,Semi-Urban,Manager,114600,0 +96871,Male,54,Masters,4,96,73,90,38,2.0,5,97,Semi-Urban,HR Executive,22645,1 +69190,Male,53,High School,19,95,78,21,1,7.0,5,16,Rural,Software Engineer,102235,0 +23887,Male,22,Masters,8,1,22,24,32,0.0,4,37,Urban,Software Engineer,35424,0 +109508,Male,31,Bachelors,18,67,49,12,82,7.0,4,57,Rural,ML Engineer,105225,0 +32744,Male,24,Bachelors,12,86,93,17,21,9.0,1,59,Semi-Urban,Software Engineer,112088,1 +100845,Male,47,High School,14,1,89,40,82,7.0,1,60,Semi-Urban,ML Engineer,44709,0 +74915,Other,43,Diploma,0,40,16,76,1,9.0,6,58,Semi-Urban,ML Engineer,85227,0 +118055,Female,51,Diploma,5,99,58,80,44,5.0,2,58,Urban,Software Engineer,117913,1 +50048,Male,36,PhD,15,72,32,17,89,7.0,0,25,Urban,HR Executive,50576,0 +50240,Male,32,PhD,8,92,71,90,46,6.0,4,13,Urban,Software Engineer,79589,1 +89511,Male,52,Bachelors,12,37,22,78,53,5.0,5,10,Rural,HR Executive,110345,0 +39168,Male,28,Masters,6,52,14,44,9,7.0,2,8,Urban,ML Engineer,46038,0 +42013,Male,28,Masters,5,83,30,26,6,2.0,5,37,Semi-Urban,Manager,65623,0 +8877,Male,36,Bachelors,4,6,51,68,56,0.0,5,96,Urban,Software Engineer,74665,0 +5004,Male,55,Bachelors,8,64,69,88,72,9.0,7,10,Urban,Software Engineer,37420,0 +92370,Female,53,Diploma,8,89,21,48,76,0.0,2,20,Urban,Software Engineer,32019,0 +20319,Male,37,High School,1,53,83,41,95,3.0,5,2,Rural,Software Engineer,33961,0 +58489,Male,39,Bachelors,19,40,27,79,31,9.0,0,49,Rural,Data Analyst,67977,0 +73595,Male,23,Bachelors,13,37,7,97,40,2.0,6,84,Rural,Software Engineer,111703,0 +63410,Male,31,Masters,15,13,90,35,32,5.0,3,93,Urban,Data Analyst,46304,0 +80979,Female,54,Bachelors,17,15,64,62,74,6.0,5,31,Urban,Manager,127564,0 +21582,Female,36,Diploma,18,61,26,30,14,7.0,4,77,Semi-Urban,Software Engineer,92066,0 +77150,Male,54,Diploma,6,72,10,85,98,0.0,7,11,Rural,ML Engineer,61171,0 +17924,Female,58,Bachelors,18,88,27,57,86,3.0,0,98,Rural,Data Analyst,109516,1 +37713,Male,36,High School,10,46,22,11,79,4.0,0,62,Semi-Urban,Data Analyst,96911,0 +34311,Male,42,Diploma,11,40,66,77,89,2.0,5,81,Urban,HR Executive,139108,1 +95475,Female,25,High School,10,13,42,36,66,6.0,4,77,Urban,Manager,45471,0 +110399,Male,27,Diploma,17,97,59,71,52,0.0,6,27,Urban,HR Executive,137959,1 +27295,Male,25,Diploma,0,11,96,25,25,8.0,4,51,Semi-Urban,HR Executive,73865,0 +80406,Female,39,Diploma,7,75,93,43,3,2.0,1,48,Urban,Manager,41863,1 +47105,Male,53,Bachelors,8,43,28,92,89,1.0,7,36,Urban,HR Executive,130736,0 +31355,Female,38,Bachelors,11,74,36,59,16,9.0,5,14,Urban,Manager,113222,0 +89872,Male,23,Bachelors,18,41,15,70,88,4.0,3,27,Semi-Urban,Manager,85935,0 +11571,Male,34,Bachelors,16,19,92,78,27,4.0,3,5,Urban,ML Engineer,106361,0 +108818,Male,27,Bachelors,0,30,95,28,44,9.0,1,99,Urban,Software Engineer,119859,1 +32705,Male,36,Masters,15,65,89,64,66,0.0,7,83,Rural,Software Engineer,47389,1 +18397,Male,33,Masters,0,34,15,15,16,6.0,6,86,Semi-Urban,Data Analyst,119052,0 +115837,Male,30,Masters,10,15,39,44,0,6.0,7,50,Urban,Manager,142605,0 +95645,Male,24,Bachelors,19,6,96,71,89,5.0,5,45,Rural,HR Executive,132173,0 +84641,Female,26,Diploma,14,0,45,26,99,8.0,7,92,Semi-Urban,Manager,92136,0 +108303,Male,27,Bachelors,17,97,39,58,53,8.0,6,3,Semi-Urban,Manager,117888,0 +69676,Male,37,High School,4,70,76,52,79,3.0,4,12,Semi-Urban,HR Executive,21337,0 +102295,Male,31,Diploma,18,63,87,5,3,6.0,0,94,Urban,ML Engineer,22477,1 +55826,Male,42,High School,11,58,91,48,93,7.0,1,65,Urban,Manager,127926,1 +42171,Male,25,High School,14,27,62,11,13,5.0,1,42,Rural,Data Analyst,57210,0 +43810,Male,27,Bachelors,11,4,8,35,83,2.0,4,3,Semi-Urban,Manager,95085,0 +112588,Male,31,Bachelors,12,19,92,81,11,3.0,7,0,Semi-Urban,Software Engineer,32012,0 +13421,Female,37,Bachelors,8,43,91,81,22,8.0,0,19,Urban,HR Executive,127665,0 +105394,Female,24,Masters,0,47,32,96,70,5.0,4,54,Semi-Urban,ML Engineer,77151,0 +69142,Female,57,Bachelors,4,95,72,13,27,4.0,4,83,Semi-Urban,HR Executive,144006,1 +5104,Male,40,Bachelors,10,86,25,35,48,1.0,5,42,Urban,Data Analyst,121851,0 +39811,Other,34,Masters,15,19,65,14,80,8.0,2,92,Rural,Data Analyst,90245,0 +113159,Female,28,High School,16,48,76,26,11,3.0,0,87,Urban,ML Engineer,59022,0 +107311,Other,47,High School,8,37,13,67,8,9.0,6,57,Semi-Urban,ML Engineer,33130,0 +43113,Male,57,Bachelors,7,56,76,48,58,5.0,4,17,Urban,ML Engineer,143837,0 +12733,Female,24,PhD,15,14,84,29,30,7.0,0,44,Rural,HR Executive,51593,0 +75533,Female,26,Bachelors,2,14,43,67,2,7.0,0,28,Urban,ML Engineer,29485,0 +106815,Female,38,High School,9,58,1,45,16,3.0,7,85,Semi-Urban,Software Engineer,102963,0 +19895,Male,48,Bachelors,19,81,78,43,79,8.0,7,12,Urban,ML Engineer,141220,0 +15032,Female,30,PhD,16,91,77,52,65,6.0,6,98,Urban,Data Analyst,129270,1 +67715,Female,49,Diploma,4,54,10,66,48,7.0,0,3,Rural,ML Engineer,98747,0 +57172,Male,21,Diploma,1,83,62,67,10,9.0,4,40,Rural,HR Executive,102691,1 +57122,Female,56,High School,12,23,81,40,1,8.0,6,73,Urban,Software Engineer,58505,0 +69721,Female,58,PhD,4,81,92,27,68,9.0,0,65,Semi-Urban,Manager,87220,1 +96446,Female,59,Diploma,5,6,2,22,70,8.0,6,5,Semi-Urban,Manager,65231,0 +116227,Female,55,Bachelors,17,77,16,6,79,3.0,6,92,Urban,ML Engineer,94837,0 +96389,Male,30,Diploma,1,93,36,37,52,7.0,2,25,Semi-Urban,Data Analyst,45518,0 +92391,Male,30,Bachelors,10,56,51,44,90,4.0,2,5,Urban,ML Engineer,119420,0 +108872,Male,40,High School,9,29,47,49,58,6.0,2,83,Urban,Manager,113925,0 +50100,Other,58,Diploma,10,0,56,45,17,9.0,6,24,Urban,Manager,90110,0 +97223,Male,21,Masters,8,20,58,74,53,0.0,4,70,Rural,Software Engineer,61428,0 +91626,Male,34,Diploma,6,13,88,96,10,6.0,6,85,Rural,HR Executive,50686,1 +110740,Female,26,Diploma,7,16,41,8,74,8.0,2,80,Urban,ML Engineer,57038,0 +15939,Male,29,Diploma,17,54,35,14,25,9.0,0,83,Urban,ML Engineer,146455,0 +114514,Other,36,PhD,13,12,5,27,5,1.0,2,78,Semi-Urban,HR Executive,131344,0 +78992,Male,41,Masters,3,12,24,1,77,7.0,5,62,Urban,ML Engineer,54928,0 +33317,Male,36,Masters,8,58,90,63,80,2.0,7,93,Urban,Manager,62168,1 +4984,Female,37,Diploma,4,52,83,20,98,6.0,6,52,Urban,HR Executive,137560,0 +62080,Male,42,Masters,9,19,41,83,11,6.0,0,19,Semi-Urban,Manager,59320,0 +25952,Male,32,Bachelors,2,74,42,12,37,9.0,3,19,Rural,ML Engineer,71419,0 +7945,Male,21,High School,5,31,28,48,49,4.0,2,88,Rural,Manager,31509,0 +116945,Female,41,Bachelors,19,65,0,94,74,8.0,4,25,Urban,ML Engineer,104656,0 +16674,Female,38,Masters,16,35,6,83,21,8.0,1,42,Rural,Data Analyst,126616,0 +92277,Male,33,Bachelors,10,46,31,58,55,6.0,7,7,Semi-Urban,ML Engineer,27013,0 +61793,Female,39,Bachelors,10,17,37,45,86,5.0,5,75,Urban,Software Engineer,112427,0 +9990,Female,49,Diploma,14,80,98,1,88,2.0,0,11,Urban,ML Engineer,41460,0 +48586,Female,35,Masters,4,91,2,48,7,0.0,2,62,Urban,HR Executive,22362,0 +53115,Male,53,Bachelors,7,89,36,73,69,3.0,6,25,Rural,Manager,129272,0 +98919,Male,26,Bachelors,12,16,2,37,26,0.0,3,62,Semi-Urban,Software Engineer,67445,0 +119672,Male,56,High School,16,57,29,20,33,8.0,0,67,Semi-Urban,Software Engineer,100081,0 +22344,Female,40,Masters,18,48,92,7,7,1.0,1,90,Semi-Urban,Manager,116709,0 +74507,Male,47,Bachelors,14,16,55,0,98,5.0,6,49,Urban,ML Engineer,52107,0 +64042,Male,37,Bachelors,14,4,55,96,20,7.0,5,87,Semi-Urban,Manager,84319,1 +1473,Female,40,Bachelors,1,64,81,54,25,9.0,4,52,Urban,Data Analyst,70967,1 +62291,Male,32,High School,0,55,94,50,14,4.0,5,38,Urban,Manager,34512,1 +51185,Male,57,Bachelors,1,40,26,83,11,6.0,7,36,Rural,HR Executive,145560,0 +34402,Male,25,Bachelors,12,23,9,5,24,4.0,3,90,Semi-Urban,HR Executive,86021,0 +119663,Female,21,Bachelors,7,9,65,59,38,0.0,0,90,Urban,Data Analyst,70817,0 +47294,Male,52,Diploma,8,51,82,31,91,2.0,2,59,Urban,HR Executive,107477,0 +60070,Male,26,High School,17,55,56,61,70,8.0,3,37,Rural,HR Executive,72153,0 +7296,Other,25,Bachelors,17,38,79,74,24,3.0,4,40,Rural,Software Engineer,114469,0 +50737,Female,24,High School,6,54,80,25,61,5.0,2,65,Semi-Urban,ML Engineer,117219,0 +54587,Male,29,PhD,6,41,43,35,38,5.0,5,49,Semi-Urban,HR Executive,84276,0 +67532,Male,34,Bachelors,8,21,50,66,4,9.0,0,31,Rural,Data Analyst,20290,0 +103854,Male,23,Masters,2,26,31,14,58,9.0,7,91,Urban,Software Engineer,140575,0 +73564,Female,59,Masters,16,19,55,13,12,0.0,6,50,Urban,ML Engineer,30597,0 +40454,Male,32,High School,0,15,91,57,77,8.0,0,39,Rural,ML Engineer,123009,0 +88396,Female,56,High School,11,91,24,25,56,9.0,7,22,Urban,Manager,44015,0 +10729,Male,58,Bachelors,14,80,66,76,85,1.0,0,16,Rural,ML Engineer,53640,1 +3133,Female,41,Masters,8,82,10,62,66,9.0,5,16,Urban,Software Engineer,133285,0 +27445,Female,27,Diploma,18,49,80,24,69,1.0,2,4,Semi-Urban,Software Engineer,146074,0 +102954,Female,39,Diploma,11,60,77,21,52,2.0,4,10,Urban,Data Analyst,125246,0 +80756,Female,54,Bachelors,13,71,62,79,93,7.0,3,34,Rural,HR Executive,37156,1 +93911,Male,42,Diploma,4,3,80,49,52,0.0,3,2,Rural,Manager,129531,0 +78503,Male,49,High School,16,92,84,87,92,5.0,1,9,Urban,Manager,48357,1 +73803,Male,38,Bachelors,2,50,23,63,41,4.0,5,28,Urban,Manager,97011,0 +94434,Female,27,Masters,15,32,13,64,52,0.0,4,32,Urban,Software Engineer,55948,0 +102756,Male,29,Diploma,5,93,46,35,75,0.0,7,88,Semi-Urban,ML Engineer,29594,1 +26190,Male,21,Bachelors,13,52,26,66,65,5.0,5,1,Semi-Urban,Manager,60936,0 +13444,Female,56,Masters,11,26,88,54,76,8.0,6,40,Semi-Urban,ML Engineer,80161,0 +100577,Male,22,Masters,3,24,39,59,80,7.0,5,97,Semi-Urban,ML Engineer,93467,0 +88572,Male,45,Bachelors,10,49,0,6,34,2.0,0,66,Urban,ML Engineer,37922,0 +89793,Male,41,Bachelors,14,4,19,39,79,6.0,2,70,Urban,Software Engineer,37084,0 +53719,Male,59,Diploma,7,72,80,59,62,2.0,2,68,Rural,HR Executive,46203,1 +88332,Male,42,Bachelors,12,95,48,11,58,7.0,5,5,Urban,Software Engineer,92199,0 +69032,Male,46,Bachelors,19,92,62,81,97,1.0,4,65,Rural,Software Engineer,95639,1 +37927,Male,53,High School,17,68,99,64,48,2.0,0,76,Rural,Data Analyst,139792,1 +113741,Female,21,High School,7,31,6,31,8,3.0,0,46,Urban,ML Engineer,103403,0 +107485,Male,22,Bachelors,6,22,63,48,7,0.0,0,96,Urban,HR Executive,147835,0 +48864,Male,32,Bachelors,14,94,1,43,92,5.0,3,42,Semi-Urban,Data Analyst,121106,0 +92793,Male,29,Masters,7,86,21,19,62,3.0,2,37,Rural,HR Executive,41463,0 +39789,Male,48,High School,7,18,74,44,77,7.0,6,50,Semi-Urban,Manager,62867,0 +116157,Male,38,Bachelors,6,52,7,15,88,7.0,4,96,Semi-Urban,Data Analyst,116248,0 +116369,Male,43,Bachelors,1,25,50,21,98,1.0,7,99,Rural,Manager,51586,0 +20023,Male,35,Diploma,6,67,21,80,19,5.0,0,88,Urban,Software Engineer,79502,1 +45376,Male,27,Bachelors,3,87,40,6,61,2.0,3,25,Urban,Data Analyst,27075,0 +20766,Male,40,Diploma,11,38,29,58,10,0.0,0,49,Urban,ML Engineer,65467,0 +55498,Female,38,Bachelors,9,26,29,82,0,9.0,6,62,Rural,Software Engineer,108979,0 +4269,Female,44,High School,5,69,50,75,60,5.0,7,11,Semi-Urban,ML Engineer,70631,0 +84013,Male,47,Masters,9,42,63,13,3,3.0,0,71,Semi-Urban,HR Executive,89065,0 +9096,Female,23,Bachelors,14,18,96,82,81,9.0,5,57,Rural,Manager,138307,1 +29794,Male,49,Bachelors,10,83,80,59,82,7.0,4,81,Urban,Data Analyst,135671,1 +47344,Male,37,Bachelors,17,71,55,56,80,8.0,2,70,Urban,Data Analyst,44867,1 +111198,Male,49,Masters,14,84,60,99,9,9.0,1,64,Urban,Software Engineer,103035,1 +52991,Female,37,Diploma,12,49,59,64,26,8.0,5,89,Urban,Manager,99111,1 +101228,Male,41,Bachelors,18,29,15,78,29,3.0,7,22,Semi-Urban,ML Engineer,51287,0 +64796,Male,38,Bachelors,1,29,22,94,44,3.0,2,23,Urban,Software Engineer,21304,0 diff --git a/tests/fixtures/adult.csv b/tests/fixtures/adult.csv new file mode 100644 index 0000000..5cf74ed --- /dev/null +++ b/tests/fixtures/adult.csv @@ -0,0 +1,32562 @@ +"age","workclass","fnlwgt","education","education.num","marital.status","occupation","relationship","race","sex","capital.gain","capital.loss","hours.per.week","native.country","income" +90,"?",77053,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,4356,40,"United-States","<=50K" +82,"Private",132870,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,4356,18,"United-States","<=50K" +66,"?",186061,"Some-college",10,"Widowed","?","Unmarried","Black","Female",0,4356,40,"United-States","<=50K" +54,"Private",140359,"7th-8th",4,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,3900,40,"United-States","<=50K" +41,"Private",264663,"Some-college",10,"Separated","Prof-specialty","Own-child","White","Female",0,3900,40,"United-States","<=50K" +34,"Private",216864,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,3770,45,"United-States","<=50K" +38,"Private",150601,"10th",6,"Separated","Adm-clerical","Unmarried","White","Male",0,3770,40,"United-States","<=50K" +74,"State-gov",88638,"Doctorate",16,"Never-married","Prof-specialty","Other-relative","White","Female",0,3683,20,"United-States",">50K" +68,"Federal-gov",422013,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Female",0,3683,40,"United-States","<=50K" +41,"Private",70037,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,3004,60,"?",">50K" +45,"Private",172274,"Doctorate",16,"Divorced","Prof-specialty","Unmarried","Black","Female",0,3004,35,"United-States",">50K" +38,"Self-emp-not-inc",164526,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,2824,45,"United-States",">50K" +52,"Private",129177,"Bachelors",13,"Widowed","Other-service","Not-in-family","White","Female",0,2824,20,"United-States",">50K" +32,"Private",136204,"Masters",14,"Separated","Exec-managerial","Not-in-family","White","Male",0,2824,55,"United-States",">50K" +51,"?",172175,"Doctorate",16,"Never-married","?","Not-in-family","White","Male",0,2824,40,"United-States",">50K" +46,"Private",45363,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",0,2824,40,"United-States",">50K" +45,"Private",172822,"11th",7,"Divorced","Transport-moving","Not-in-family","White","Male",0,2824,76,"United-States",">50K" +57,"Private",317847,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",0,2824,50,"United-States",">50K" +22,"Private",119592,"Assoc-acdm",12,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,2824,40,"?",">50K" +34,"Private",203034,"Bachelors",13,"Separated","Sales","Not-in-family","White","Male",0,2824,50,"United-States",">50K" +37,"Private",188774,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,2824,40,"United-States",">50K" +29,"Private",77009,"11th",7,"Separated","Sales","Not-in-family","White","Female",0,2754,42,"United-States","<=50K" +61,"Private",29059,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,2754,25,"United-States","<=50K" +51,"Private",153870,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,2603,40,"United-States","<=50K" +61,"?",135285,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,2603,32,"United-States","<=50K" +21,"Private",34310,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2603,40,"United-States","<=50K" +33,"Private",228696,"1st-4th",2,"Married-civ-spouse","Craft-repair","Not-in-family","White","Male",0,2603,32,"Mexico","<=50K" +49,"Private",122066,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,2603,40,"Greece","<=50K" +37,"Self-emp-inc",107164,"10th",6,"Never-married","Transport-moving","Not-in-family","White","Male",0,2559,50,"United-States",">50K" +38,"Private",175360,"10th",6,"Never-married","Prof-specialty","Not-in-family","White","Male",0,2559,90,"United-States",">50K" +23,"Private",44064,"Some-college",10,"Separated","Other-service","Not-in-family","White","Male",0,2559,40,"United-States",">50K" +59,"Self-emp-inc",107287,"10th",6,"Widowed","Exec-managerial","Unmarried","White","Female",0,2559,50,"United-States",">50K" +52,"Private",198863,"Prof-school",15,"Divorced","Exec-managerial","Not-in-family","White","Male",0,2559,60,"United-States",">50K" +51,"Private",123011,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,2559,50,"United-States",">50K" +60,"Self-emp-not-inc",205246,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,2559,50,"United-States",">50K" +63,"Federal-gov",39181,"Doctorate",16,"Divorced","Exec-managerial","Not-in-family","White","Female",0,2559,60,"United-States",">50K" +53,"Private",149650,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,2559,48,"United-States",">50K" +51,"Private",197163,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,2559,50,"United-States",">50K" +37,"Self-emp-not-inc",137527,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,2559,60,"United-States",">50K" +54,"Private",161691,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,2559,40,"United-States",">50K" +44,"Private",326232,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Male",0,2547,50,"United-States",">50K" +43,"Private",115806,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",0,2547,40,"United-States",">50K" +51,"Private",115066,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,2547,40,"United-States",">50K" +43,"Private",289669,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,2547,40,"United-States",">50K" +71,"?",100820,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,2489,15,"United-States","<=50K" +48,"Private",121253,"Bachelors",13,"Married-spouse-absent","Sales","Unmarried","White","Female",0,2472,70,"United-States",">50K" +71,"Private",110380,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,2467,52,"United-States","<=50K" +73,"Self-emp-not-inc",233882,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Asian-Pac-Islander","Male",0,2457,40,"Vietnam","<=50K" +68,"?",192052,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,2457,40,"United-States","<=50K" +67,"?",174995,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,2457,40,"United-States","<=50K" +40,"Self-emp-not-inc",335549,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,2444,45,"United-States",">50K" +50,"Private",237729,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,2444,72,"United-States",">50K" +51,"State-gov",68898,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","White","Male",0,2444,39,"United-States",">50K" +42,"Private",107276,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,2444,40,"United-States",">50K" +39,"Private",141584,"Masters",14,"Never-married","Sales","Not-in-family","White","Male",0,2444,45,"United-States",">50K" +32,"Private",207668,"Bachelors",13,"Never-married","Exec-managerial","Other-relative","White","Male",0,2444,50,"United-States",">50K" +53,"Private",313243,"Some-college",10,"Separated","Craft-repair","Not-in-family","White","Male",0,2444,45,"United-States",">50K" +40,"Local-gov",147372,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,2444,40,"United-States",">50K" +38,"Private",237608,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,2444,45,"United-States",">50K" +33,"Private",194901,"Assoc-voc",11,"Separated","Craft-repair","Not-in-family","White","Male",0,2444,42,"United-States",">50K" +43,"Private",155106,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","White","Male",0,2444,70,"United-States",">50K" +50,"Self-emp-inc",121441,"11th",7,"Never-married","Exec-managerial","Other-relative","White","Male",0,2444,40,"United-States",">50K" +44,"Private",162028,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,2415,6,"United-States",">50K" +51,"Self-emp-not-inc",160724,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,2415,40,"China",">50K" +41,"Private",132222,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,40,"United-States",">50K" +60,"Self-emp-inc",226355,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,2415,70,"?",">50K" +37,"Private",329980,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2415,60,"United-States",">50K" +55,"Self-emp-inc",124137,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,35,"Greece",">50K" +39,"Self-emp-inc",329980,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,2415,60,"United-States",">50K" +42,"Self-emp-inc",187702,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,60,"United-States",">50K" +49,"Private",199029,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,2415,55,"United-States",">50K" +47,"Self-emp-not-inc",145290,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2415,50,"United-States",">50K" +41,"Local-gov",297248,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,45,"United-States",">50K" +55,"Self-emp-inc",227856,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2415,50,"United-States",">50K" +39,"Private",179731,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,2415,65,"United-States",">50K" +42,"Private",154374,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2415,60,"United-States",">50K" +41,"?",27187,"Assoc-voc",11,"Married-civ-spouse","?","Husband","White","Male",0,2415,12,"United-States",">50K" +46,"Private",326857,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,2415,65,"United-States",">50K" +40,"Private",160369,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2415,45,"United-States",">50K" +32,"Private",396745,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,48,"United-States",">50K" +41,"Self-emp-inc",151089,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2415,55,"United-States",">50K" +60,"Self-emp-inc",336188,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,80,"United-States",">50K" +31,"Private",279015,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2415,70,"Taiwan",">50K" +58,"Self-emp-not-inc",43221,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,2415,40,"United-States",">50K" +37,"Self-emp-inc",30529,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,2415,50,"United-States",">50K" +44,"Self-emp-not-inc",201742,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2415,50,"United-States",">50K" +39,"Self-emp-not-inc",218490,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,50,"?",">50K" +43,"Federal-gov",156996,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,2415,55,"?",">50K" +55,"Self-emp-inc",298449,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2415,50,"United-States",">50K" +44,"Self-emp-inc",191712,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,55,"United-States",">50K" +39,"Private",198654,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,2415,67,"India",">50K" +46,"Self-emp-not-inc",102308,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,2415,40,"United-States",">50K" +39,"Private",348521,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,2415,99,"United-States",">50K" +62,"Self-emp-inc",56248,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,2415,60,"United-States",">50K" +31,"Self-emp-not-inc",252752,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,2415,40,"United-States",">50K" +46,"Private",192963,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,2415,35,"Philippines",">50K" +46,"Self-emp-not-inc",198759,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,80,"United-States",">50K" +39,"Self-emp-inc",143123,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2415,40,"United-States",">50K" +39,"Private",237713,"Prof-school",15,"Married-civ-spouse","Sales","Husband","White","Male",0,2415,99,"United-States",">50K" +59,"Private",81929,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,45,"United-States",">50K" +50,"Self-emp-inc",167793,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,60,"United-States",">50K" +46,"Private",456062,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,55,"United-States",">50K" +53,"Self-emp-not-inc",105478,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2415,40,"United-States",">50K" +50,"Self-emp-not-inc",42402,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,30,"United-States",">50K" +41,"Self-emp-inc",114580,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,2415,55,"United-States",">50K" +36,"Private",346478,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,2415,45,"United-States",">50K" +38,"Private",187870,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,90,"United-States",">50K" +54,"Private",35576,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,2415,50,"United-States",">50K" +50,"Private",102346,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,2415,20,"United-States",">50K" +47,"Private",148995,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2415,60,"United-States",">50K" +47,"Self-emp-inc",102308,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2415,45,"United-States",">50K" +67,"Private",105252,"Bachelors",13,"Widowed","Exec-managerial","Not-in-family","White","Male",0,2392,40,"United-States",">50K" +67,"Self-emp-inc",106175,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2392,75,"United-States",">50K" +72,"Self-emp-not-inc",52138,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2392,25,"United-States",">50K" +72,"?",118902,"Doctorate",16,"Married-civ-spouse","?","Husband","White","Male",0,2392,6,"United-States",">50K" +46,"Self-emp-inc",191978,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2392,50,"United-States",">50K" +78,"Self-emp-inc",188044,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2392,40,"United-States",">50K" +71,"Self-emp-inc",66624,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2392,60,"United-States",">50K" +83,"Self-emp-inc",153183,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2392,55,"United-States",">50K" +68,"Private",211287,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2392,40,"United-States",">50K" +26,"Private",181655,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,2377,45,"United-States","<=50K" +68,"State-gov",235882,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2377,60,"United-States",">50K" +49,"Self-emp-inc",158685,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,2377,40,"United-States",">50K" +36,"Private",370767,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2377,60,"United-States","<=50K" +70,"Self-emp-not-inc",155141,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2377,12,"United-States",">50K" +27,"Private",156516,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,2377,20,"United-States","<=50K" +35,"Local-gov",177305,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2377,40,"United-States","<=50K" +23,"Private",162945,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,2377,40,"United-States","<=50K" +81,"Private",177408,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2377,26,"United-States",">50K" +66,"Self-emp-not-inc",427422,"Doctorate",16,"Married-civ-spouse","Sales","Husband","White","Male",0,2377,25,"United-States",">50K" +71,"Private",152307,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2377,45,"United-States",">50K" +68,"Private",218637,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,2377,55,"United-States",">50K" +68,"State-gov",202699,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2377,42,"?",">50K" +65,"?",240857,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,2377,40,"United-States",">50K" +52,"Private",222405,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,2377,40,"United-States","<=50K" +40,"Self-emp-inc",110862,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2377,50,"United-States","<=50K" +68,"?",257269,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,2377,35,"United-States",">50K" +21,"Private",377931,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2377,48,"United-States","<=50K" +35,"Private",192923,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2377,40,"United-States","<=50K" +70,"Self-emp-inc",207938,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2377,50,"United-States",">50K" +61,"Self-emp-not-inc",36671,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,2352,50,"United-States","<=50K" +65,"Self-emp-inc",81413,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,2352,65,"United-States","<=50K" +46,"Private",214955,"5th-6th",3,"Divorced","Craft-repair","Not-in-family","White","Female",0,2339,45,"United-States","<=50K" +26,"Local-gov",166295,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,2339,55,"United-States","<=50K" +59,"Local-gov",147707,"HS-grad",9,"Widowed","Farming-fishing","Unmarried","White","Male",0,2339,40,"United-States","<=50K" +61,"Private",43554,"5th-6th",3,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,2339,40,"United-States","<=50K" +60,"State-gov",358893,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,2339,40,"United-States","<=50K" +49,"Self-emp-inc",141058,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,2339,50,"United-States","<=50K" +34,"Private",25322,"Bachelors",13,"Married-spouse-absent","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Male",0,2339,40,"?","<=50K" +25,"Private",77071,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,2339,35,"United-States","<=50K" +55,"Private",158702,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,2339,45,"?","<=50K" +59,"Local-gov",171328,"HS-grad",9,"Separated","Protective-serv","Other-relative","Black","Female",0,2339,40,"United-States","<=50K" +28,"State-gov",381789,"Some-college",10,"Separated","Exec-managerial","Own-child","White","Male",0,2339,40,"United-States","<=50K" +43,"?",152569,"Assoc-voc",11,"Widowed","?","Not-in-family","White","Female",0,2339,36,"United-States","<=50K" +56,"Self-emp-not-inc",346635,"Masters",14,"Divorced","Sales","Unmarried","White","Female",0,2339,60,"United-States","<=50K" +41,"Private",162140,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,2339,40,"United-States","<=50K" +42,"Private",191765,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","Black","Female",0,2339,40,"Trinadad&Tobago","<=50K" +28,"Private",251905,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,2339,40,"Canada","<=50K" +40,"Self-emp-not-inc",33310,"Prof-school",15,"Divorced","Other-service","Not-in-family","White","Female",0,2339,35,"United-States","<=50K" +69,"Private",228921,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","White","Male",0,2282,40,"United-States",">50K" +66,"Local-gov",36364,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2267,40,"United-States","<=50K" +69,"Private",124930,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,2267,40,"United-States","<=50K" +55,"Local-gov",176046,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,2267,40,"United-States","<=50K" +57,"Federal-gov",370890,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,2258,40,"United-States","<=50K" +20,"Self-emp-not-inc",157145,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,2258,10,"United-States","<=50K" +33,"Private",288825,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,2258,84,"United-States","<=50K" +30,"Self-emp-not-inc",257295,"Some-college",10,"Never-married","Sales","Other-relative","Asian-Pac-Islander","Male",0,2258,40,"South","<=50K" +40,"Private",287983,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Asian-Pac-Islander","Female",0,2258,48,"Philippines","<=50K" +38,"Private",101978,"Some-college",10,"Separated","Machine-op-inspct","Not-in-family","White","Male",0,2258,55,"United-States",">50K" +46,"State-gov",192779,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Male",0,2258,38,"United-States",">50K" +29,"Private",135296,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,2258,45,"United-States",">50K" +57,"Federal-gov",199114,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,2258,40,"United-States","<=50K" +39,"Private",156897,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,2258,42,"United-States",">50K" +47,"Private",138107,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,2258,40,"United-States",">50K" +26,"Private",279833,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,2258,45,"United-States",">50K" +27,"Self-emp-not-inc",208577,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,2258,50,"United-States","<=50K" +23,"Private",102942,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,2258,40,"United-States",">50K" +34,"Private",36385,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,2258,50,"United-States","<=50K" +33,"Private",176185,"12th",8,"Divorced","Craft-repair","Not-in-family","White","Male",0,2258,42,"United-States","<=50K" +38,"Local-gov",162613,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,2258,60,"United-States","<=50K" +57,"Private",121362,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,2258,38,"United-States",">50K" +36,"Private",145933,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,2258,70,"United-States","<=50K" +44,"Federal-gov",29591,"Bachelors",13,"Divorced","Tech-support","Not-in-family","White","Male",0,2258,40,"United-States",">50K" +49,"State-gov",269417,"Doctorate",16,"Never-married","Exec-managerial","Not-in-family","White","Female",0,2258,50,"United-States",">50K" +44,"Self-emp-inc",178510,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,2258,60,"United-States","<=50K" +55,"Private",41108,"Some-college",10,"Widowed","Farming-fishing","Not-in-family","White","Male",0,2258,62,"United-States",">50K" +45,"Private",187901,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,2258,44,"United-States",">50K" +48,"Private",175070,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,2258,40,"United-States",">50K" +31,"Private",263561,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2246,45,"United-States",">50K" +55,"Local-gov",99131,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Other-relative","White","Female",0,2246,40,"United-States",">50K" +70,"Self-emp-not-inc",143833,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2246,40,"United-States",">50K" +70,"Self-emp-not-inc",124449,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2246,8,"United-States",">50K" +73,"Private",336007,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2246,40,"United-States",">50K" +72,"Self-emp-not-inc",285408,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2246,28,"United-States",">50K" +31,"Private",327825,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","White","Female",0,2238,40,"United-States","<=50K" +28,"Private",129460,"10th",6,"Widowed","Adm-clerical","Unmarried","White","Female",0,2238,35,"United-States","<=50K" +23,"Self-emp-not-inc",258298,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,2231,40,"United-States",">50K" +49,"Local-gov",102359,"9th",5,"Widowed","Handlers-cleaners","Unmarried","White","Male",0,2231,40,"United-States",">50K" +27,"Local-gov",92431,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,2231,40,"United-States",">50K" +90,"Private",51744,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,2206,40,"United-States","<=50K" +68,"Private",166149,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,2206,30,"United-States","<=50K" +65,"Private",149811,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,2206,59,"Canada","<=50K" +65,"?",143118,"HS-grad",9,"Widowed","?","Unmarried","White","Female",0,2206,10,"United-States","<=50K" +67,"Private",118363,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,2206,5,"United-States","<=50K" +66,"Local-gov",362165,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","Black","Female",0,2206,25,"United-States","<=50K" +24,"Private",379066,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,2205,24,"United-States","<=50K" +44,"Self-emp-not-inc",171424,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,2205,35,"United-States","<=50K" +35,"Private",108293,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,2205,40,"United-States","<=50K" +20,"Private",107801,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Female",0,2205,18,"United-States","<=50K" +38,"Private",126675,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,2205,40,"United-States","<=50K" +39,"Private",155603,"Some-college",10,"Never-married","Other-service","Own-child","Black","Female",0,2205,40,"United-States","<=50K" +32,"Private",27882,"Some-college",10,"Never-married","Machine-op-inspct","Other-relative","White","Female",0,2205,40,"Holand-Netherlands","<=50K" +42,"Private",242564,"7th-8th",4,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,2205,40,"United-States","<=50K" +63,"?",234083,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,2205,40,"United-States","<=50K" +42,"Self-emp-inc",23510,"Masters",14,"Divorced","Exec-managerial","Unmarried","Asian-Pac-Islander","Male",0,2201,60,"India",">50K" +64,"Private",181232,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2179,40,"United-States","<=50K" +28,"Private",166481,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","Other","Male",0,2179,40,"Puerto-Rico","<=50K" +41,"Self-emp-inc",139916,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","Other","Male",0,2179,84,"Mexico","<=50K" +41,"Self-emp-not-inc",144594,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2179,40,"United-States","<=50K" +58,"Self-emp-not-inc",266707,"1st-4th",2,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,2179,18,"United-States","<=50K" +59,"State-gov",303176,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2179,40,"United-States","<=50K" +34,"Self-emp-not-inc",56460,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,2179,12,"United-States","<=50K" +45,"Private",167523,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,2179,45,"United-States","<=50K" +29,"Private",119004,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,2179,40,"United-States","<=50K" +47,"Private",175925,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,2179,52,"United-States","<=50K" +40,"Private",212847,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,2179,40,"United-States","<=50K" +47,"Self-emp-not-inc",191175,"5th-6th",3,"Married-civ-spouse","Sales","Husband","White","Male",0,2179,50,"Mexico","<=50K" +63,"?",83043,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,2179,45,"United-States","<=50K" +41,"Self-emp-not-inc",170214,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,2179,40,"United-States","<=50K" +34,"Private",180714,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,2179,40,"United-States","<=50K" +66,"?",177351,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,2174,40,"United-States",">50K" +65,"Self-emp-not-inc",111483,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2174,10,"United-States",">50K" +70,"Private",282642,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,2174,40,"United-States",">50K" +75,"Self-emp-not-inc",309955,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2174,50,"United-States",">50K" +65,"State-gov",215908,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,2174,40,"United-States",">50K" +65,"Federal-gov",23494,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,2174,40,"United-States",">50K" +73,"Private",147551,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2174,50,"United-States",">50K" +60,"?",141221,"Bachelors",13,"Married-civ-spouse","?","Husband","Asian-Pac-Islander","Male",0,2163,25,"South","<=50K" +68,"Self-emp-not-inc",116903,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2149,40,"United-States","<=50K" +74,"Self-emp-not-inc",119129,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,2149,20,"United-States","<=50K" +43,"Private",143582,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Wife","Asian-Pac-Islander","Female",0,2129,72,"?","<=50K" +19,"Self-emp-not-inc",342384,"11th",7,"Married-civ-spouse","Craft-repair","Own-child","White","Male",0,2129,55,"United-States","<=50K" +37,"Self-emp-not-inc",68899,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2129,40,"United-States","<=50K" +45,"Federal-gov",207107,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","Asian-Pac-Islander","Male",0,2080,40,"Philippines","<=50K" +64,"Private",149044,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,2057,60,"China","<=50K" +30,"Private",148524,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,2057,40,"United-States","<=50K" +51,"Self-emp-not-inc",268639,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,2057,60,"Canada","<=50K" +35,"Private",272019,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2057,40,"United-States","<=50K" +29,"Private",239753,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,2057,20,"United-States","<=50K" +34,"Private",199864,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,2057,40,"United-States","<=50K" +41,"Private",125831,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2051,60,"United-States","<=50K" +35,"Private",67728,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2051,45,"United-States","<=50K" +26,"Private",115717,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,2051,40,"United-States","<=50K" +54,"Private",172281,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,2051,50,"United-States","<=50K" +52,"Local-gov",305053,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2051,40,"United-States","<=50K" +50,"Self-emp-not-inc",105010,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,2051,20,"United-States","<=50K" +31,"Private",291052,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,2051,40,"United-States","<=50K" +38,"Federal-gov",248919,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,2051,40,"United-States","<=50K" +30,"Private",84119,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2051,40,"United-States","<=50K" +34,"Local-gov",105540,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2051,40,"United-States","<=50K" +31,"Private",161765,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,2051,57,"United-States","<=50K" +52,"Private",195635,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,2051,38,"United-States","<=50K" +54,"Private",816750,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2051,40,"United-States","<=50K" +38,"Private",160192,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2051,44,"United-States","<=50K" +39,"Private",136081,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,2051,40,"United-States","<=50K" +29,"Private",244473,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,2051,40,"United-States","<=50K" +45,"Private",187033,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2051,40,"United-States","<=50K" +34,"Private",265807,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,2051,55,"United-States","<=50K" +38,"Private",154410,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2051,40,"Poland","<=50K" +39,"Private",314007,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2051,40,"United-States","<=50K" +61,"Private",179743,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2051,20,"United-States","<=50K" +43,"Private",117037,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,2042,40,"United-States","<=50K" +35,"Private",40135,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,2042,40,"United-States","<=50K" +46,"Private",315423,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,2042,50,"United-States","<=50K" +38,"Private",35429,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,2042,40,"United-States","<=50K" +42,"Self-emp-not-inc",120837,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2042,48,"United-States","<=50K" +34,"Private",90614,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,2042,10,"United-States","<=50K" +29,"Private",202878,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,2042,40,"United-States","<=50K" +32,"Private",260954,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2042,30,"United-States","<=50K" +60,"Private",127084,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,2042,34,"United-States","<=50K" +49,"Local-gov",107231,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2002,40,"United-States","<=50K" +53,"Local-gov",135102,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,2002,45,"United-States","<=50K" +56,"Private",201822,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,2002,40,"United-States","<=50K" +48,"Private",413363,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,2002,40,"United-States","<=50K" +32,"Federal-gov",148138,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,2002,40,"Iran","<=50K" +42,"Self-emp-not-inc",170721,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2002,40,"United-States","<=50K" +32,"Private",102858,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2002,42,"United-States","<=50K" +28,"Local-gov",175262,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,2002,40,"England","<=50K" +26,"Private",36936,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2002,40,"United-States","<=50K" +59,"Private",169982,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2002,50,"United-States","<=50K" +47,"Self-emp-not-inc",208407,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2002,30,"United-States","<=50K" +26,"?",131777,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,2002,40,"United-States","<=50K" +41,"Private",41090,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,2002,60,"United-States","<=50K" +36,"Private",183739,"HS-grad",9,"Married-civ-spouse","Craft-repair","Own-child","White","Female",0,2002,40,"United-States","<=50K" +45,"Private",357540,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,2002,55,"United-States","<=50K" +30,"Private",48520,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,2002,40,"United-States","<=50K" +36,"Private",107916,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,2002,40,"United-States","<=50K" +34,"Self-emp-inc",198613,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,2002,40,"United-States","<=50K" +53,"Private",283743,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,2002,40,"United-States","<=50K" +51,"Private",210940,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,2002,45,"United-States","<=50K" +47,"Self-emp-not-inc",355978,"Doctorate",16,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,2002,45,"United-States","<=50K" +19,"?",241616,"HS-grad",9,"Never-married","?","Unmarried","White","Male",0,2001,40,"United-States","<=50K" +30,"Private",57651,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Male",0,2001,42,"United-States","<=50K" +20,"Private",315877,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Male",0,2001,40,"United-States","<=50K" +42,"Federal-gov",74680,"Masters",14,"Divorced","Adm-clerical","Not-in-family","White","Male",0,2001,60,"United-States","<=50K" +31,"Private",454508,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,2001,40,"United-States","<=50K" +33,"Private",202046,"Bachelors",13,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,2001,40,"United-States","<=50K" +25,"Private",121102,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Female",0,2001,30,"United-States","<=50K" +20,"Private",146879,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,2001,40,"United-States","<=50K" +23,"Private",213955,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Male",0,2001,40,"United-States","<=50K" +55,"?",123382,"HS-grad",9,"Separated","?","Not-in-family","Black","Female",0,2001,40,"United-States","<=50K" +41,"Self-emp-not-inc",277783,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,2001,50,"United-States","<=50K" +54,"Self-emp-not-inc",199741,"HS-grad",9,"Widowed","Craft-repair","Not-in-family","White","Male",0,2001,35,"United-States","<=50K" +25,"Private",378322,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,2001,50,"United-States","<=50K" +19,"Private",264390,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,2001,40,"United-States","<=50K" +24,"Private",210029,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,2001,37,"United-States","<=50K" +56,"Federal-gov",61885,"Bachelors",13,"Never-married","Transport-moving","Not-in-family","Black","Male",0,2001,65,"United-States","<=50K" +21,"Local-gov",102942,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,2001,40,"United-States","<=50K" +34,"Private",209297,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,2001,40,"United-States","<=50K" +19,"Private",198459,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,2001,40,"United-States","<=50K" +21,"?",40052,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,2001,45,"United-States","<=50K" +48,"Private",93476,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Female",0,2001,40,"United-States","<=50K" +34,"Private",174789,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,2001,40,"United-States","<=50K" +31,"Private",189759,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,2001,40,"United-States","<=50K" +36,"Private",297847,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,2001,40,"United-States","<=50K" +27,"Private",124953,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,1980,40,"United-States","<=50K" +27,"Private",116358,"Some-college",10,"Never-married","Craft-repair","Own-child","Asian-Pac-Islander","Male",0,1980,40,"Philippines","<=50K" +35,"Private",187119,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,1980,65,"United-States","<=50K" +31,"Self-emp-not-inc",161745,"Bachelors",13,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Male",0,1980,60,"United-States","<=50K" +27,"Federal-gov",469705,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",0,1980,40,"United-States","<=50K" +28,"Local-gov",304960,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,1980,40,"United-States","<=50K" +42,"Private",175935,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,1980,46,"United-States","<=50K" +44,"Private",355728,"Some-college",10,"Separated","Exec-managerial","Not-in-family","White","Male",0,1980,45,"England","<=50K" +41,"Private",53956,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,1980,56,"United-States","<=50K" +28,"Private",184723,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,1980,35,"United-States","<=50K" +41,"Federal-gov",185616,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,1980,40,"United-States","<=50K" +35,"Private",54595,"10th",6,"Widowed","Other-service","Not-in-family","Black","Female",0,1980,40,"United-States","<=50K" +58,"Private",126104,"Masters",14,"Divorced","Adm-clerical","Not-in-family","White","Female",0,1980,45,"United-States","<=50K" +40,"Private",139193,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,1980,48,"United-States","<=50K" +31,"Private",184306,"Assoc-voc",11,"Never-married","Transport-moving","Own-child","White","Male",0,1980,60,"United-States","<=50K" +30,"Private",207301,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,1980,40,"United-States","<=50K" +32,"Private",199529,"Some-college",10,"Separated","Tech-support","Not-in-family","Amer-Indian-Eskimo","Male",0,1980,40,"United-States","<=50K" +25,"Private",111058,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,1980,40,"United-States","<=50K" +34,"Private",198103,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,1980,40,"United-States","<=50K" +56,"Private",34626,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,1980,40,"United-States","<=50K" +45,"Private",100651,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,1980,40,"United-States","<=50K" +50,"Private",104501,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,1980,40,"United-States","<=50K" +27,"Private",132805,"10th",6,"Never-married","Sales","Other-relative","White","Male",0,1980,40,"United-States","<=50K" +51,"Private",96062,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,40,"United-States",">50K" +40,"Private",207578,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1977,60,"United-States",">50K" +41,"Private",445382,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,65,"United-States",">50K" +49,"Private",192776,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,45,"United-States",">50K" +37,"Private",22463,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1977,40,"United-States",">50K" +36,"Self-emp-inc",108293,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1977,45,"United-States",">50K" +35,"Private",199352,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,80,"United-States",">50K" +29,"Self-emp-inc",260729,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,1977,25,"United-States",">50K" +50,"Private",133963,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1977,40,"United-States",">50K" +46,"Private",129007,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,40,"United-States",">50K" +44,"Self-emp-not-inc",179557,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,45,"United-States",">50K" +42,"Local-gov",111252,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,40,"United-States",">50K" +38,"Federal-gov",338320,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +45,"Private",192835,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,55,"United-States",">50K" +43,"Local-gov",147328,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,60,"United-States",">50K" +47,"Self-emp-inc",139268,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,60,"United-States",">50K" +58,"Self-emp-inc",349910,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +48,"Private",331482,"Prof-school",15,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1977,40,"United-States",">50K" +42,"Local-gov",245307,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,48,"United-States",">50K" +55,"Private",153484,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +51,"Private",252903,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,40,"United-States",">50K" +32,"Private",295589,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,1977,40,"United-States",">50K" +45,"Local-gov",160472,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +56,"Private",192869,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1977,44,"United-States",">50K" +38,"Private",234901,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,60,"United-States",">50K" +45,"Private",33300,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,50,"United-States",">50K" +49,"Private",101825,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1977,40,"United-States",">50K" +36,"Private",183612,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,40,"United-States",">50K" +49,"Private",185041,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,40,"United-States",">50K" +30,"Private",315640,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,1977,40,"China",">50K" +42,"Self-emp-inc",123838,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +55,"Private",31905,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,40,"United-States",">50K" +34,"Private",181091,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,45,"United-States",">50K" +54,"Private",88278,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +42,"Self-emp-not-inc",323790,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,70,"United-States",">50K" +25,"Local-gov",90730,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,40,"United-States",">50K" +55,"Self-emp-inc",138594,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,45,"United-States",">50K" +58,"State-gov",194068,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +62,"Private",218009,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1977,60,"United-States",">50K" +43,"Self-emp-inc",221172,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,40,"United-States",">50K" +57,"Local-gov",174132,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,1977,40,"United-States",">50K" +42,"Self-emp-inc",277256,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,60,"United-States",">50K" +63,"Self-emp-not-inc",35021,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,1977,32,"China",">50K" +47,"Self-emp-not-inc",213668,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +37,"Private",99146,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +40,"Private",209547,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,60,"United-States",">50K" +43,"Private",118308,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +43,"State-gov",33331,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,70,"United-States",">50K" +41,"Self-emp-not-inc",200574,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,60,"United-States",">50K" +32,"Private",204374,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,60,"United-States",">50K" +47,"Private",189680,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,40,"United-States",">50K" +39,"Federal-gov",175232,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,1977,60,"United-States",">50K" +53,"Private",193720,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,40,"United-States",">50K" +34,"Private",189759,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,45,"United-States",">50K" +36,"Private",32776,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,40,"United-States",">50K" +47,"Local-gov",285060,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,41,"United-States",">50K" +52,"Private",23780,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,45,"United-States",">50K" +40,"Self-emp-not-inc",284706,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",0,1977,60,"United-States",">50K" +42,"Self-emp-inc",130126,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,40,"United-States",">50K" +51,"Private",102615,"Masters",14,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1977,40,"United-States",">50K" +55,"Private",208311,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1977,20,"United-States",">50K" +38,"Private",111499,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,99,"United-States",">50K" +52,"Private",139671,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +60,"Federal-gov",165630,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1977,40,"United-States",">50K" +55,"Private",124808,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"Germany",">50K" +47,"Local-gov",29819,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,1977,50,"United-States",">50K" +46,"Private",102771,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1977,40,"United-States",">50K" +35,"Private",86648,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,45,"United-States",">50K" +59,"Self-emp-inc",223215,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +57,"Private",437727,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,45,"United-States",">50K" +46,"Private",167515,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +46,"Federal-gov",213140,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,40,"United-States",">50K" +52,"Private",168553,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1977,40,"United-States",">50K" +45,"Private",363677,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1977,30,"United-States",">50K" +37,"Private",241998,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1977,40,"United-States",">50K" +46,"Private",337050,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,45,"United-States",">50K" +44,"Private",157249,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,1977,50,"United-States",">50K" +45,"Private",84298,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +43,"Private",55213,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1977,52,"United-States",">50K" +54,"Local-gov",185846,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,40,"United-States",">50K" +50,"Private",150999,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,40,"United-States",">50K" +51,"Private",199688,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,60,"?",">50K" +45,"Private",225456,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,40,"United-States",">50K" +36,"Private",192939,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,60,"United-States",">50K" +27,"Private",183627,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +36,"Private",189404,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,35,"United-States",">50K" +53,"Private",152810,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,55,"United-States",">50K" +51,"Local-gov",123011,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,35,"United-States",">50K" +28,"Private",114158,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1977,24,"United-States",">50K" +47,"Self-emp-not-inc",228660,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1977,40,"United-States",">50K" +45,"Private",233511,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,60,"United-States",">50K" +45,"Local-gov",159816,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1977,35,"United-States",">50K" +39,"Self-emp-not-inc",202027,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +39,"Private",218490,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,40,"United-States",">50K" +55,"Self-emp-not-inc",248841,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,40,"United-States",">50K" +62,"Private",71751,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,98,"United-States",">50K" +49,"Private",137192,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,1977,50,"South",">50K" +53,"Self-emp-not-inc",100109,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,40,"United-States",">50K" +31,"Private",183043,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,48,"United-States",">50K" +42,"Self-emp-inc",188738,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,60,"Italy",">50K" +39,"Private",201410,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1977,45,"Philippines",">50K" +60,"Self-emp-not-inc",282066,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,45,"United-States",">50K" +26,"Private",291968,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,40,"United-States",">50K" +37,"Private",126569,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,40,"United-States",">50K" +45,"State-gov",103406,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,60,"United-States",">50K" +37,"Private",109133,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,45,"United-States",">50K" +32,"Private",195602,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,45,"United-States",">50K" +39,"Self-emp-inc",135500,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,40,"United-States",">50K" +58,"Self-emp-not-inc",147653,"10th",6,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,1977,35,"?",">50K" +45,"Private",145636,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,43,"United-States",">50K" +41,"Private",137126,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,45,"United-States",">50K" +36,"Self-emp-not-inc",36270,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1977,65,"United-States",">50K" +51,"State-gov",285747,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,60,"United-States",">50K" +39,"Private",80324,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,62,"United-States",">50K" +56,"Self-emp-not-inc",94156,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +53,"Federal-gov",271544,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,1977,40,"United-States",">50K" +40,"Self-emp-not-inc",175943,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1977,15,"United-States",">50K" +57,"Private",141570,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,1977,40,"United-States",">50K" +50,"Local-gov",124963,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1977,35,"United-States",">50K" +34,"Private",112115,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,55,"United-States",">50K" +35,"Private",99357,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1977,30,"United-States",">50K" +30,"Self-emp-not-inc",404062,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,15,"United-States",">50K" +53,"Local-gov",200190,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,55,"United-States",">50K" +31,"State-gov",207505,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,70,"United-States",">50K" +37,"Private",135436,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,60,"United-States",">50K" +34,"Private",345705,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,50,"United-States",">50K" +36,"Private",126675,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +40,"Private",107433,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +51,"Private",230858,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1977,60,"United-States",">50K" +33,"Private",133503,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,45,"United-States",">50K" +40,"Private",46990,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1977,20,"United-States",">50K" +50,"Self-emp-inc",201689,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1977,63,"?",">50K" +46,"Self-emp-inc",216414,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,60,"United-States",">50K" +54,"Private",182314,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +39,"Private",134367,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1977,24,"United-States",">50K" +54,"Self-emp-inc",206964,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,40,"United-States",">50K" +31,"Private",147284,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,99,"United-States",">50K" +51,"Private",172046,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +55,"Private",175942,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,55,"?",">50K" +36,"Private",145576,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1977,40,"Japan",">50K" +41,"Self-emp-inc",93227,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,1977,60,"Taiwan",">50K" +56,"Self-emp-not-inc",48102,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1977,50,"United-States",">50K" +38,"Private",172538,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1977,40,"United-States",">50K" +47,"Private",239865,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1977,45,"United-States",">50K" +39,"Local-gov",180686,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,45,"United-States",">50K" +59,"Private",170104,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +54,"Private",511668,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,43,"United-States",">50K" +54,"Self-emp-not-inc",109418,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1977,35,"United-States",">50K" +31,"Private",110643,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,55,"United-States",">50K" +59,"Self-emp-inc",122390,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,48,"United-States",">50K" +46,"Private",261059,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +57,"Private",140426,"Doctorate",16,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1977,40,"Germany",">50K" +36,"Private",386726,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1977,44,"United-States",">50K" +44,"Private",340885,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1977,40,"United-States",">50K" +33,"Private",149184,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +54,"Private",308087,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1977,18,"United-States",">50K" +55,"Private",368797,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,60,"United-States",">50K" +36,"Private",218689,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,1977,50,"United-States",">50K" +49,"Local-gov",298445,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1977,60,"United-States",">50K" +41,"Private",347653,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,50,"United-States",">50K" +40,"Private",320451,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,1977,45,"Hong",">50K" +43,"Private",170730,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +39,"Local-gov",344855,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1977,20,"United-States",">50K" +26,"?",370727,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,1977,40,"United-States",">50K" +48,"Private",109814,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,45,"United-States",">50K" +43,"Private",409922,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,50,"United-States",">50K" +42,"Self-emp-inc",191196,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1977,60,"?",">50K" +36,"Private",237943,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1977,45,"United-States",">50K" +39,"Private",49020,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1974,40,"United-States","<=50K" +21,"Private",109414,"Some-college",10,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Male",0,1974,40,"United-States","<=50K" +23,"Private",275818,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,1974,40,"United-States","<=50K" +47,"Private",133758,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,1974,40,"United-States","<=50K" +30,"Private",43953,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,1974,40,"United-States","<=50K" +35,"Private",147258,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,1974,40,"United-States","<=50K" +26,"Private",58098,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,1974,40,"United-States","<=50K" +26,"Private",215384,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1974,55,"United-States","<=50K" +41,"Local-gov",33068,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,1974,40,"United-States","<=50K" +30,"Local-gov",145692,"Some-college",10,"Never-married","Protective-serv","Not-in-family","Black","Male",0,1974,40,"United-States","<=50K" +28,"Private",111696,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,1974,40,"United-States","<=50K" +56,"Private",105281,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,1974,40,"United-States","<=50K" +35,"Private",200445,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,1974,40,"United-States","<=50K" +34,"Private",258666,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Female",0,1974,40,"United-States","<=50K" +29,"Private",214702,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,1974,35,"United-States","<=50K" +23,"Private",188545,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Female",0,1974,20,"United-States","<=50K" +24,"Federal-gov",210736,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,1974,40,"United-States","<=50K" +62,"Private",81116,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,1974,40,"United-States","<=50K" +77,"Self-emp-not-inc",71676,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,1944,1,"United-States","<=50K" +47,"Private",51835,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1902,60,"Honduras",">50K" +48,"Self-emp-not-inc",191277,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,60,"United-States",">50K" +42,"Self-emp-not-inc",214242,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,50,"United-States",">50K" +31,"Private",118710,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1902,40,"United-States",">50K" +43,"Private",274363,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,40,"England",">50K" +50,"Private",168212,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,65,"United-States",">50K" +36,"Private",156667,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,50,"United-States",">50K" +49,"Local-gov",193960,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +38,"Private",132879,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"United-States",">50K" +48,"State-gov",55863,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1902,46,"United-States",">50K" +46,"Private",265266,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +56,"Self-emp-not-inc",145574,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,1902,60,"United-States",">50K" +37,"Private",188540,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,45,"United-States",">50K" +51,"Private",415287,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,1902,40,"United-States",">50K" +43,"Private",201723,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,40,"United-States",">50K" +46,"Local-gov",36228,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"United-States","<=50K" +42,"Local-gov",121718,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,60,"United-States",">50K" +45,"Private",26522,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,1902,35,"United-States",">50K" +23,"Private",196827,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1902,40,"United-States","<=50K" +45,"Private",246891,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,40,"United-States",">50K" +30,"State-gov",199539,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1902,40,"United-States","<=50K" +49,"State-gov",133917,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,1902,60,"?",">50K" +49,"Private",101320,"Assoc-acdm",12,"Married-civ-spouse","Sales","Wife","White","Female",0,1902,40,"United-States",">50K" +57,"Private",98350,"Prof-school",15,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,1902,40,"Philippines",">50K" +42,"Self-emp-not-inc",157562,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1902,80,"United-States",">50K" +43,"Local-gov",105862,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,1902,40,"United-States",">50K" +43,"Private",336513,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,40,"United-States",">50K" +42,"Private",378384,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,60,"United-States",">50K" +53,"Private",104501,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,55,"United-States",">50K" +40,"Local-gov",244522,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,48,"United-States",">50K" +46,"Private",324655,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1902,40,"?",">50K" +41,"Private",84610,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,60,"United-States",">50K" +49,"Private",329603,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"United-States",">50K" +31,"Self-emp-not-inc",348038,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,50,"Puerto-Rico",">50K" +34,"Private",299635,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,50,"United-States",">50K" +40,"Federal-gov",298635,"Masters",14,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,1902,40,"Philippines",">50K" +50,"Private",184424,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,1902,38,"United-States",">50K" +54,"Private",86837,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,1902,40,"United-States",">50K" +49,"Private",142287,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1902,50,"United-States",">50K" +44,"Self-emp-not-inc",402397,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1902,60,"United-States",">50K" +57,"Local-gov",118481,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +28,"Local-gov",250135,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1902,55,"United-States","<=50K" +57,"Private",20953,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,40,"United-States",">50K" +59,"Private",348430,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,43,"United-States",">50K" +38,"Private",169926,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1902,40,"United-States",">50K" +36,"Self-emp-not-inc",283122,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1902,60,"United-States",">50K" +55,"Private",323706,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,40,"United-States",">50K" +34,"Self-emp-not-inc",77209,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,60,"United-States",">50K" +51,"Private",337195,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,50,"United-States",">50K" +46,"Private",377401,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1902,70,"Canada",">50K" +33,"Private",111567,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,45,"Germany",">50K" +31,"State-gov",181824,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1902,35,"United-States",">50K" +31,"Private",37546,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1902,35,"United-States",">50K" +59,"Self-emp-not-inc",325732,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,52,"United-States",">50K" +48,"Private",194772,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,40,"United-States",">50K" +33,"Private",112115,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,45,"United-States",">50K" +46,"Private",459189,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,50,"United-States",">50K" +53,"Private",608184,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,1902,40,"United-States",">50K" +39,"Private",165215,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1902,18,"United-States",">50K" +44,"Self-emp-not-inc",124692,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +45,"Private",360393,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,50,"United-States",">50K" +42,"Local-gov",188291,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1902,40,"United-States",">50K" +24,"Self-emp-not-inc",322931,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1902,40,"United-States",">50K" +57,"Private",173832,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,40,"United-States",">50K" +51,"Local-gov",176751,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +50,"Private",320510,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,40,"United-States",">50K" +50,"Private",162327,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1902,50,"?",">50K" +52,"Private",108435,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,50,"Greece",">50K" +46,"Self-emp-inc",328216,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,42,"?",">50K" +44,"Private",68729,"Some-college",10,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,1902,40,"United-States",">50K" +47,"Self-emp-inc",192894,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,45,"United-States",">50K" +36,"Private",206951,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,45,"United-States",">50K" +34,"Private",164190,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,38,"United-States",">50K" +49,"Private",148549,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,50,"United-States",">50K" +45,"Private",198223,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,45,"United-States",">50K" +46,"Private",172581,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,50,"United-States",">50K" +53,"Self-emp-inc",96062,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,48,"United-States",">50K" +63,"State-gov",194682,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,50,"United-States",">50K" +52,"Private",143953,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +44,"Private",286750,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,1902,40,"United-States",">50K" +37,"Private",200374,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,40,"United-States",">50K" +44,"State-gov",136546,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +53,"Private",139671,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +32,"Private",175856,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1902,40,"United-States",">50K" +50,"State-gov",289207,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,45,"United-States",">50K" +42,"Federal-gov",108183,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,1902,40,"South",">50K" +50,"Private",138179,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"United-States",">50K" +33,"Private",236396,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,55,"United-States",">50K" +50,"Local-gov",168672,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1902,40,"United-States",">50K" +32,"Private",127610,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1902,32,"United-States",">50K" +41,"Private",287306,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +54,"Private",167770,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,55,"United-States",">50K" +34,"Private",277314,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","Black","Male",0,1902,50,"United-States",">50K" +41,"Self-emp-inc",140365,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,55,"United-States",">50K" +39,"Self-emp-inc",239755,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,50,"United-States",">50K" +42,"Federal-gov",52781,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +31,"Private",201122,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,45,"United-States",">50K" +45,"Private",341995,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,42,"United-States",">50K" +41,"Private",106900,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1902,42,"United-States",">50K" +48,"Private",140782,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1902,38,"United-States",">50K" +32,"Self-emp-inc",161153,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1902,55,"United-States",">50K" +41,"Private",267252,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,1902,40,"United-States",">50K" +31,"Self-emp-not-inc",325355,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1902,40,"United-States",">50K" +30,"Self-emp-inc",173858,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,1902,40,"South",">50K" +41,"Private",352812,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1902,40,"United-States",">50K" +48,"Private",109832,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +60,"State-gov",234854,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +38,"Self-emp-not-inc",93206,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,1902,65,"United-States",">50K" +46,"Private",147640,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,1902,40,"United-States","<=50K" +28,"Private",147560,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,55,"United-States",">50K" +64,"Self-emp-inc",59145,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,60,"United-States",">50K" +31,"?",85077,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,1902,20,"United-States",">50K" +42,"Private",145711,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,50,"United-States",">50K" +43,"Private",112181,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Wife","White","Female",0,1902,32,"United-States",">50K" +61,"Self-emp-inc",139391,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,35,"United-States",">50K" +48,"Private",143098,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,1902,40,"China",">50K" +46,"Local-gov",114160,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,45,"United-States",">50K" +44,"Private",325461,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,50,"United-States",">50K" +39,"Federal-gov",30916,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,50,"United-States",">50K" +46,"Self-emp-not-inc",131091,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,40,"United-States",">50K" +48,"Private",276664,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,50,"United-States",">50K" +27,"Private",160786,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"United-States",">50K" +22,"Federal-gov",32950,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,37,"United-States","<=50K" +51,"Federal-gov",163671,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,40,"United-States","<=50K" +48,"State-gov",31141,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1902,40,"United-States",">50K" +52,"Private",144361,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"United-States",">50K" +31,"Self-emp-not-inc",182177,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"United-States",">50K" +53,"Private",95469,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1902,40,"United-States",">50K" +51,"Private",22211,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,60,"United-States",">50K" +46,"Local-gov",398986,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1902,52,"United-States",">50K" +25,"Private",253267,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,1902,36,"United-States",">50K" +46,"Private",403911,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,1902,40,"United-States",">50K" +57,"Self-emp-inc",199768,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,30,"United-States",">50K" +44,"Private",151089,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,50,"United-States",">50K" +42,"Private",344624,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1902,50,"United-States",">50K" +42,"Private",172297,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1902,40,"United-States",">50K" +30,"Private",159187,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,55,"United-States",">50K" +54,"State-gov",103179,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,50,"United-States",">50K" +46,"Self-emp-not-inc",168195,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,45,"United-States",">50K" +33,"Private",154981,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1902,50,"United-States",">50K" +38,"Private",159179,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,50,"United-States",">50K" +50,"Private",168212,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,45,"United-States",">50K" +46,"Private",155659,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"United-States",">50K" +41,"Self-emp-not-inc",186909,"Masters",14,"Married-civ-spouse","Sales","Wife","White","Female",0,1902,35,"United-States",">50K" +56,"Private",193453,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,65,"United-States",">50K" +39,"Private",284166,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,50,"United-States",">50K" +46,"Self-emp-not-inc",353012,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,50,"United-States",">50K" +48,"Local-gov",273402,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1902,40,"United-States","<=50K" +35,"Private",161637,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,1902,40,"Taiwan",">50K" +56,"Private",189975,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,60,"United-States",">50K" +49,"Self-emp-inc",213140,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,60,"United-States",">50K" +61,"State-gov",186451,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +43,"Private",113324,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"United-States",">50K" +37,"Private",193855,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,50,"United-States","<=50K" +43,"Private",196545,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1902,40,"United-States",">50K" +41,"Private",37869,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,40,"United-States",">50K" +61,"?",202106,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,1902,40,"United-States",">50K" +30,"Private",167309,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1902,40,"United-States",">50K" +58,"Private",100313,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1902,40,"United-States",">50K" +40,"Private",146908,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +44,"State-gov",193524,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,40,"United-States",">50K" +40,"Private",153238,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,32,"United-States",">50K" +58,"Private",225394,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"United-States","<=50K" +48,"Self-emp-not-inc",353012,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"United-States",">50K" +49,"Private",165953,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1902,40,"United-States","<=50K" +50,"Private",134766,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,50,"United-States",">50K" +43,"Private",125461,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,55,"United-States",">50K" +53,"Private",48343,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1902,40,"United-States",">50K" +42,"Private",146659,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,50,"United-States",">50K" +56,"Self-emp-inc",208809,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,40,"United-States",">50K" +44,"Private",35910,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,56,"United-States",">50K" +29,"Private",46442,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1902,50,"United-States",">50K" +35,"Private",139364,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,40,"United-States",">50K" +44,"Private",277647,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,40,"United-States",">50K" +34,"Federal-gov",190228,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1902,48,"United-States",">50K" +42,"Private",198341,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,1902,55,"India",">50K" +43,"Private",110970,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +57,"Private",64960,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,45,"United-States","<=50K" +50,"?",204577,"Bachelors",13,"Married-civ-spouse","?","Husband","Black","Male",0,1902,60,"United-States",">50K" +45,"Private",47314,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"?",">50K" +32,"Private",108116,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,60,"United-States",">50K" +33,"Private",59083,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1902,45,"United-States",">50K" +43,"Self-emp-not-inc",101534,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,15,"United-States",">50K" +32,"Private",156464,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,50,"United-States",">50K" +36,"Private",531055,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,48,"United-States",">50K" +50,"Self-emp-not-inc",371305,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,60,"United-States",">50K" +27,"Private",141545,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1902,45,"United-States","<=50K" +60,"Private",162347,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,40,"United-States",">50K" +53,"Private",110977,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,50,"United-States",">50K" +61,"State-gov",379885,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,40,"United-States",">50K" +32,"Private",194740,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,40,"United-States",">50K" +52,"Self-emp-inc",230767,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,60,"Cuba",">50K" +37,"Private",298539,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,55,"United-States",">50K" +33,"Private",51471,"HS-grad",9,"Married-civ-spouse","Tech-support","Wife","White","Female",0,1902,40,"United-States",">50K" +57,"Self-emp-not-inc",413373,"Doctorate",16,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,40,"United-States",">50K" +43,"Private",266324,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,99,"United-States",">50K" +50,"Private",102615,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1902,40,"United-States",">50K" +43,"Private",254146,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,40,"United-States",">50K" +45,"Private",265097,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,1902,40,"United-States",">50K" +37,"Self-emp-not-inc",162834,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1902,45,"United-States",">50K" +31,"Private",183801,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1902,43,"United-States",">50K" +33,"Private",191335,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1902,50,"United-States",">50K" +56,"Self-emp-not-inc",335605,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,1887,50,"Canada",">50K" +43,"Private",187728,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1887,50,"United-States",">50K" +28,"?",123147,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,1887,40,"United-States",">50K" +52,"Private",25826,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,47,"United-States",">50K" +38,"Private",189623,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +40,"Local-gov",289403,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,1887,40,"?",">50K" +57,"Private",173796,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1887,40,"United-States",">50K" +41,"Private",122381,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,50,"United-States",">50K" +37,"Private",171150,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,50,"United-States",">50K" +42,"Private",213821,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,40,"United-States",">50K" +44,"Private",146659,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,35,"United-States",">50K" +39,"Private",77146,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,50,"United-States",">50K" +53,"Federal-gov",173093,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","Asian-Pac-Islander","Female",0,1887,40,"Philippines",">50K" +51,"Private",191659,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,65,"United-States",">50K" +38,"Private",278924,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,50,"United-States",">50K" +43,"Local-gov",96102,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1887,40,"United-States",">50K" +33,"Self-emp-inc",117963,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,60,"United-States",">50K" +43,"Private",293305,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,40,"United-States",">50K" +35,"Private",152909,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,45,"United-States",">50K" +41,"Private",221947,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,50,"United-States",">50K" +45,"Private",120131,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,40,"United-States",">50K" +59,"Private",168569,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1887,40,"United-States",">50K" +30,"Local-gov",226443,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,45,"United-States",">50K" +32,"State-gov",182556,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1887,45,"United-States",">50K" +39,"Federal-gov",99146,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1887,60,"United-States",">50K" +43,"Self-emp-not-inc",396758,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1887,70,"United-States",">50K" +32,"Private",116539,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,55,"United-States",">50K" +39,"Local-gov",177907,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1887,40,"United-States",">50K" +37,"Local-gov",218184,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +34,"Private",182274,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1887,40,"United-States",">50K" +46,"Private",114032,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1887,45,"United-States",">50K" +51,"Local-gov",146325,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +29,"Private",81648,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,55,"United-States",">50K" +34,"Private",195136,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1887,40,"United-States",">50K" +50,"Private",285200,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,35,"United-States",">50K" +34,"Private",207668,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,1887,40,"United-States",">50K" +58,"Private",222247,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1887,40,"United-States",">50K" +56,"Self-emp-not-inc",162130,"5th-6th",3,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,67,"United-States",">50K" +34,"Self-emp-not-inc",234960,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,1887,48,"United-States",">50K" +36,"Local-gov",410034,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +46,"Private",54985,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1887,40,"United-States",">50K" +35,"Private",200117,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,1887,50,"?",">50K" +50,"Self-emp-not-inc",312477,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,40,"United-States",">50K" +27,"Self-emp-inc",120126,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,45,"United-States",">50K" +32,"Private",185027,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,40,"Ireland",">50K" +44,"Self-emp-inc",151089,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,70,"United-States",">50K" +39,"Private",355468,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,46,"United-States",">50K" +33,"Private",34748,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,1887,20,"United-States",">50K" +59,"Federal-gov",117299,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,40,"United-States",">50K" +59,"Private",530099,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,55,"United-States",">50K" +51,"State-gov",155594,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,40,"United-States",">50K" +37,"Private",167735,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,40,"United-States",">50K" +57,"Private",169329,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","Black","Male",0,1887,40,"Trinadad&Tobago",">50K" +25,"Private",203871,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1887,40,"United-States",">50K" +54,"Private",163671,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1887,65,"United-States",">50K" +47,"Local-gov",162187,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1887,40,"United-States",">50K" +52,"State-gov",254285,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,70,"Germany",">50K" +40,"Private",104196,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +27,"Private",31659,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1887,60,"United-States",">50K" +31,"Private",467579,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,1887,40,"United-States",">50K" +41,"Self-emp-inc",223671,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,55,"United-States",">50K" +41,"Private",174575,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1887,45,"United-States",">50K" +50,"Private",150876,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,1887,55,"United-States",">50K" +36,"Private",99146,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1887,40,"United-States",">50K" +27,"Private",169117,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,1887,40,"United-States",">50K" +46,"Private",190115,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,40,"United-States",">50K" +61,"Self-emp-not-inc",215591,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,40,"United-States",">50K" +39,"Local-gov",132879,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +47,"Private",168232,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1887,45,"United-States",">50K" +45,"Private",168262,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1887,40,"United-States",">50K" +55,"State-gov",153451,"HS-grad",9,"Married-civ-spouse","Tech-support","Wife","White","Female",0,1887,40,"United-States",">50K" +38,"Self-emp-not-inc",43712,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,45,"United-States",">50K" +57,"Private",314153,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,55,"United-States",">50K" +38,"Self-emp-not-inc",122493,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,40,"United-States",">50K" +28,"Private",51461,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1887,40,"United-States",">50K" +40,"Private",187802,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,1887,40,"United-States",">50K" +36,"Private",174938,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,50,"United-States",">50K" +36,"Private",180667,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,60,"United-States",">50K" +30,"Self-emp-not-inc",146161,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,50,"United-States",">50K" +35,"Private",401930,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,1887,42,"United-States",">50K" +32,"Self-emp-not-inc",410615,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1887,60,"United-States",">50K" +55,"Private",193130,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,1887,40,"United-States",">50K" +29,"Private",383745,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1887,30,"United-States",">50K" +37,"Self-emp-inc",183800,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,40,"United-States",">50K" +36,"Private",86459,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,50,"United-States",">50K" +42,"?",212206,"Masters",14,"Married-civ-spouse","?","Wife","White","Female",0,1887,48,"United-States",">50K" +40,"State-gov",174283,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,50,"United-States",">50K" +26,"Private",164488,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +44,"Private",151089,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,60,"United-States",">50K" +47,"Private",284871,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,40,"United-States",">50K" +35,"Private",185556,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +58,"Private",34788,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,40,"United-States",">50K" +41,"Self-emp-inc",125831,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,55,"United-States",">50K" +41,"Private",194360,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,40,"United-States",">50K" +38,"Local-gov",286405,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,50,"United-States",">50K" +47,"Self-emp-not-inc",122307,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,40,"United-States",">50K" +39,"Private",176296,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,1887,40,"United-States",">50K" +42,"Private",173704,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,50,"United-States",">50K" +42,"Private",212894,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,40,"United-States",">50K" +37,"Private",292855,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1887,35,"United-States",">50K" +41,"Private",214242,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +51,"Private",110747,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,40,"United-States",">50K" +50,"Private",128143,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,50,"United-States",">50K" +43,"Private",184321,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,1887,40,"United-States",">50K" +28,"Private",141957,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1887,70,"United-States",">50K" +35,"Self-emp-inc",111319,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,45,"United-States",">50K" +59,"Private",100313,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,40,"United-States",">50K" +28,"Private",138692,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +42,"Self-emp-not-inc",185129,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +51,"Private",162238,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,47,"United-States",">50K" +54,"Private",215990,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,44,"United-States",">50K" +45,"Private",102771,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,40,"United-States",">50K" +38,"Local-gov",172855,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,1887,40,"United-States",">50K" +46,"Federal-gov",344415,"Masters",14,"Married-civ-spouse","Armed-Forces","Husband","White","Male",0,1887,40,"United-States",">50K" +33,"Local-gov",182971,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1887,40,"United-States",">50K" +36,"Private",272944,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,40,"United-States",">50K" +36,"Local-gov",52532,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,50,"United-States",">50K" +61,"Federal-gov",229062,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1887,40,"United-States",">50K" +30,"Self-emp-inc",127651,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,48,"United-States",">50K" +50,"Private",213290,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1887,36,"United-States",">50K" +58,"Private",314092,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,48,"United-States",">50K" +43,"Private",266439,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1887,40,"United-States",">50K" +40,"Private",119101,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,68,"United-States",">50K" +55,"Federal-gov",238192,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1887,40,"United-States",">50K" +52,"Private",159755,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,40,"United-States",">50K" +44,"Self-emp-not-inc",343190,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,55,"United-States",">50K" +39,"Federal-gov",376455,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,50,"United-States",">50K" +45,"Private",126889,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,60,"United-States",">50K" +42,"Self-emp-not-inc",351161,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +29,"Private",228860,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,50,"United-States",">50K" +46,"Private",102318,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1887,40,"United-States",">50K" +55,"Private",110748,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,40,"United-States",">50K" +33,"Self-emp-not-inc",170979,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +44,"Private",186916,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1887,60,"United-States",">50K" +37,"Private",73471,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,47,"United-States",">50K" +64,"Self-emp-inc",161325,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,50,"United-States",">50K" +43,"State-gov",24763,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,45,"United-States",">50K" +36,"Private",33394,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1887,35,"United-States",">50K" +55,"Private",359972,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,40,"United-States",">50K" +34,"Private",242984,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,45,"United-States",">50K" +29,"Private",250967,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1887,48,"United-States",">50K" +37,"Private",265737,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,1887,60,"Cuba",">50K" +42,"Private",230959,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","Asian-Pac-Islander","Female",0,1887,40,"Philippines",">50K" +41,"Self-emp-not-inc",111772,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,40,"United-States",">50K" +45,"Local-gov",199590,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,40,"Mexico",">50K" +35,"Private",267866,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,1887,50,"Iran",">50K" +61,"Private",115023,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,60,"United-States",">50K" +49,"Private",34545,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,40,"United-States",">50K" +52,"Self-emp-not-inc",34973,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1887,60,"United-States",">50K" +46,"Local-gov",238162,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1887,50,"United-States",">50K" +23,"Private",143003,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,1887,50,"India",">50K" +36,"Private",334291,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1887,40,"United-States",">50K" +43,"Local-gov",34640,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Other","Male",0,1887,40,"United-States",">50K" +35,"Local-gov",116960,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,40,"United-States",">50K" +39,"Private",128392,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1887,40,"United-States",">50K" +39,"Private",30529,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1887,40,"United-States",">50K" +47,"Local-gov",324791,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1887,50,"United-States",">50K" +53,"Local-gov",186303,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1887,40,"United-States",">50K" +53,"Private",304504,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1887,45,"United-States",">50K" +26,"Private",397317,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1876,40,"United-States","<=50K" +52,"Private",186785,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,1876,50,"United-States","<=50K" +61,"Private",123273,"5th-6th",3,"Divorced","Transport-moving","Not-in-family","White","Male",0,1876,56,"United-States","<=50K" +28,"Local-gov",154863,"HS-grad",9,"Never-married","Protective-serv","Other-relative","Black","Male",0,1876,40,"United-States","<=50K" +42,"Private",44121,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,1876,40,"United-States","<=50K" +44,"Local-gov",101593,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,1876,42,"United-States","<=50K" +51,"Private",138179,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","White","Male",0,1876,40,"United-States","<=50K" +39,"Local-gov",86551,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,1876,40,"United-States","<=50K" +36,"State-gov",112497,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,1876,44,"United-States","<=50K" +45,"Private",138626,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,1876,50,"United-States","<=50K" +27,"Private",175387,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1876,40,"United-States","<=50K" +40,"Local-gov",105717,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Female",0,1876,35,"United-States","<=50K" +25,"Private",193820,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,1876,40,"United-States","<=50K" +47,"Private",151584,"HS-grad",9,"Divorced","Sales","Own-child","White","Male",0,1876,40,"United-States","<=50K" +32,"Private",244147,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,1876,50,"United-States","<=50K" +53,"Private",122109,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,1876,38,"United-States","<=50K" +32,"Private",226975,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,1876,60,"United-States","<=50K" +49,"Private",149949,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,1876,40,"United-States","<=50K" +27,"Private",34273,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1876,36,"Canada","<=50K" +26,"Private",82246,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1876,38,"United-States","<=50K" +60,"Self-emp-not-inc",73091,"HS-grad",9,"Separated","Other-service","Not-in-family","Black","Male",0,1876,50,"United-States","<=50K" +56,"Self-emp-not-inc",50791,"Masters",14,"Divorced","Sales","Not-in-family","White","Male",0,1876,60,"United-States","<=50K" +58,"Private",201393,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Male",0,1876,40,"United-States","<=50K" +39,"Private",114844,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,1876,50,"United-States","<=50K" +53,"Private",174020,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,1876,38,"United-States","<=50K" +27,"Private",292472,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,1876,45,"Cambodia","<=50K" +46,"Local-gov",175754,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,1876,60,"United-States","<=50K" +30,"Private",236861,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1876,45,"United-States","<=50K" +38,"Local-gov",329980,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,1876,40,"Canada","<=50K" +41,"Private",315834,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1876,40,"United-States","<=50K" +27,"Private",38918,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,1876,75,"United-States","<=50K" +43,"Private",81243,"Bachelors",13,"Divorced","Tech-support","Not-in-family","White","Male",0,1876,40,"United-States","<=50K" +30,"Federal-gov",164552,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,1876,40,"United-States","<=50K" +25,"Private",117833,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1876,40,"United-States","<=50K" +26,"Self-emp-not-inc",177858,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,1876,38,"United-States","<=50K" +53,"Local-gov",103995,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,1876,54,"United-States","<=50K" +39,"Private",347491,"11th",7,"Divorced","Craft-repair","Not-in-family","White","Male",0,1876,46,"United-States","<=50K" +47,"Local-gov",154033,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,1876,40,"United-States","<=50K" +44,"Private",150533,"Some-college",10,"Separated","Craft-repair","Not-in-family","White","Male",0,1876,55,"United-States","<=50K" +61,"Self-emp-not-inc",30073,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1848,60,"United-States",">50K" +44,"Private",216907,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1848,40,"United-States",">50K" +28,"Private",303954,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1848,42,"United-States",">50K" +34,"Private",223212,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1848,40,"Peru",">50K" +39,"Private",218490,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1848,40,"United-States",">50K" +41,"Private",121718,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1848,48,"United-States",">50K" +35,"Private",340110,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1848,70,"United-States",">50K" +34,"Private",155343,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1848,50,"United-States",">50K" +30,"Private",174789,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1848,50,"United-States",">50K" +30,"Private",220148,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1848,50,"United-States",">50K" +33,"Local-gov",173005,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1848,45,"United-States",">50K" +60,"?",191118,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,1848,40,"United-States",">50K" +31,"Private",339482,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1848,40,"United-States",">50K" +50,"Private",192982,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1848,40,"United-States",">50K" +27,"Private",285897,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1848,45,"United-States",">50K" +37,"Self-emp-not-inc",241463,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1848,65,"United-States",">50K" +30,"Private",206046,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1848,40,"United-States",">50K" +49,"Private",102583,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1848,44,"United-States",">50K" +52,"State-gov",125796,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,1848,40,"United-States",">50K" +39,"Local-gov",423605,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1848,40,"Nicaragua",">50K" +37,"Private",204277,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1848,48,"United-States",">50K" +39,"Private",186191,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1848,50,"United-States",">50K" +38,"Private",172571,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1848,54,"United-States",">50K" +44,"Private",192381,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1848,40,"United-States",">50K" +45,"Private",54744,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1848,40,"United-States",">50K" +54,"Private",93605,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1848,40,"United-States",">50K" +58,"Private",156040,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,1848,40,"United-States",">50K" +36,"Federal-gov",186934,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1848,55,"United-States",">50K" +45,"Private",223999,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,1848,40,"United-States",">50K" +46,"Federal-gov",349230,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1848,40,"United-States",">50K" +41,"Private",351161,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1848,45,"United-States",">50K" +41,"Federal-gov",36651,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1848,40,"United-States",">50K" +34,"Private",55717,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1848,50,"United-States",">50K" +33,"Federal-gov",331615,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1848,40,"United-States",">50K" +63,"Private",383058,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1848,40,"United-States",">50K" +56,"Private",204049,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1848,50,"United-States",">50K" +48,"Local-gov",242923,"HS-grad",9,"Married-civ-spouse","Tech-support","Wife","White","Female",0,1848,40,"United-States",">50K" +40,"Private",199900,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1848,55,"United-States",">50K" +59,"Private",231377,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1848,45,"United-States",">50K" +32,"Private",168854,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1848,50,"United-States",">50K" +29,"Local-gov",190525,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1848,60,"Germany",">50K" +41,"Private",149909,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1848,40,"United-States",">50K" +30,"Private",129707,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1848,40,"United-States",">50K" +34,"State-gov",318982,"Masters",14,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1848,40,"United-States",">50K" +41,"Private",77373,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1848,65,"United-States",">50K" +46,"Private",189498,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1848,45,"United-States",">50K" +39,"Private",91367,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1848,45,"United-States",">50K" +26,"Private",366219,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,1848,60,"United-States",">50K" +27,"Private",215504,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1848,55,"United-States",">50K" +61,"Private",181219,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1848,40,"United-States",">50K" +37,"Private",103121,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1848,40,"United-States",">50K" +67,"Private",197816,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1844,70,"United-States","<=50K" +66,"?",213149,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,1825,40,"United-States",">50K" +66,"Self-emp-inc",253741,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1825,10,"United-States",">50K" +74,"Self-emp-not-inc",292915,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1825,12,"United-States",">50K" +66,"State-gov",132055,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1825,40,"United-States",">50K" +71,"Self-emp-not-inc",494223,"Some-college",10,"Separated","Sales","Unmarried","Black","Male",0,1816,2,"United-States","<=50K" +80,"Private",87518,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,1816,60,"United-States","<=50K" +24,"Private",43323,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,1762,40,"United-States","<=50K" +20,"?",114746,"11th",7,"Married-spouse-absent","?","Own-child","Asian-Pac-Islander","Female",0,1762,40,"South","<=50K" +28,"Self-emp-not-inc",218555,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,1762,40,"United-States","<=50K" +59,"Private",226922,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,1762,30,"United-States","<=50K" +24,"Private",85088,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,1762,32,"United-States","<=50K" +24,"Private",137591,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,1762,40,"United-States","<=50K" +52,"Private",78012,"HS-grad",9,"Widowed","Sales","Unmarried","White","Female",0,1762,40,"United-States","<=50K" +39,"Self-emp-not-inc",134475,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Male",0,1762,40,"United-States","<=50K" +43,"Private",138184,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,1762,35,"United-States","<=50K" +22,"Private",156822,"10th",6,"Never-married","Sales","Not-in-family","White","Female",0,1762,25,"United-States","<=50K" +30,"Private",145231,"Assoc-acdm",12,"Divorced","Adm-clerical","Own-child","White","Female",0,1762,40,"United-States","<=50K" +21,"Private",213341,"11th",7,"Married-spouse-absent","Handlers-cleaners","Own-child","White","Male",0,1762,40,"Dominican-Republic","<=50K" +24,"Private",276851,"HS-grad",9,"Divorced","Protective-serv","Own-child","White","Female",0,1762,40,"United-States","<=50K" +21,"Private",211968,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,1762,28,"United-States","<=50K" +49,"Private",180899,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Male",0,1755,45,"United-States",">50K" +52,"Private",117496,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,1755,40,"United-States",">50K" +38,"Private",179488,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,1741,40,"United-States","<=50K" +30,"Private",204374,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,1741,48,"United-States","<=50K" +38,"Local-gov",123983,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","Asian-Pac-Islander","Male",0,1741,40,"Vietnam","<=50K" +25,"Private",302465,"12th",8,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,1741,40,"United-States","<=50K" +34,"Private",271933,"Bachelors",13,"Never-married","Exec-managerial","Other-relative","White","Female",0,1741,45,"United-States","<=50K" +24,"Federal-gov",314525,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,1741,45,"United-States","<=50K" +25,"Private",168403,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,1741,40,"United-States","<=50K" +31,"Private",255004,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1741,38,"United-States","<=50K" +39,"Federal-gov",129573,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,1741,40,"United-States","<=50K" +35,"Private",261241,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,1741,60,"United-States","<=50K" +31,"Local-gov",127651,"10th",6,"Never-married","Transport-moving","Other-relative","White","Male",0,1741,40,"United-States","<=50K" +30,"Private",104052,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,1741,42,"United-States","<=50K" +42,"Local-gov",109684,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1741,35,"United-States","<=50K" +42,"Private",202188,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,1741,50,"United-States","<=50K" +41,"Private",394669,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1741,40,"United-States","<=50K" +46,"Private",33109,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,1741,40,"United-States","<=50K" +34,"Private",176185,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1741,40,"United-States","<=50K" +33,"?",289046,"HS-grad",9,"Divorced","?","Not-in-family","Black","Male",0,1741,40,"United-States","<=50K" +36,"Private",321733,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,1741,40,"United-States","<=50K" +36,"Private",171676,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,1741,40,"United-States","<=50K" +44,"Federal-gov",139161,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,1741,40,"United-States","<=50K" +28,"Private",191088,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,1741,52,"United-States","<=50K" +52,"Private",208630,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,1741,38,"United-States","<=50K" +43,"Private",191712,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,1741,40,"United-States","<=50K" +45,"Private",428350,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,1740,40,"United-States","<=50K" +30,"Private",212237,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1740,45,"United-States","<=50K" +50,"Local-gov",177705,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1740,48,"United-States","<=50K" +41,"Local-gov",343079,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1740,20,"United-States","<=50K" +31,"Private",47296,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,1740,20,"United-States","<=50K" +27,"Self-emp-inc",64379,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1740,40,"United-States","<=50K" +63,"Private",275034,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,1740,35,"United-States","<=50K" +33,"Private",100135,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,1740,25,"United-States","<=50K" +28,"Private",183780,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1740,40,"United-States","<=50K" +34,"Local-gov",210164,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1740,40,"United-States","<=50K" +31,"Private",106753,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1740,40,"United-States","<=50K" +30,"Private",177216,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,1740,40,"Haiti","<=50K" +47,"State-gov",469907,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1740,40,"United-States","<=50K" +35,"Private",148581,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1740,40,"United-States","<=50K" +32,"Private",209808,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1740,47,"United-States","<=50K" +33,"Self-emp-not-inc",155151,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1740,50,"United-States","<=50K" +38,"Private",184655,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1740,48,"United-States","<=50K" +35,"Self-emp-inc",189404,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1740,40,"United-States","<=50K" +42,"Private",248094,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1740,43,"United-States","<=50K" +47,"Federal-gov",20956,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1740,40,"United-States","<=50K" +34,"Local-gov",134886,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,1740,35,"United-States","<=50K" +53,"Private",96062,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1740,40,"United-States","<=50K" +37,"Private",200598,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1740,45,"United-States","<=50K" +33,"Private",146440,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1740,40,"United-States","<=50K" +32,"Private",199655,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Other","Female",0,1740,40,"?","<=50K" +38,"Local-gov",210991,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1740,40,"United-States","<=50K" +52,"Private",191529,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1740,60,"United-States","<=50K" +35,"Local-gov",668319,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1740,80,"United-States","<=50K" +46,"Private",113390,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1740,60,"United-States","<=50K" +28,"Private",293926,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1740,30,"United-States","<=50K" +58,"Private",138285,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1740,40,"United-States","<=50K" +29,"Self-emp-inc",168221,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1740,70,"United-States","<=50K" +30,"Private",194827,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1740,40,"United-States","<=50K" +53,"Federal-gov",167380,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1740,50,"United-States","<=50K" +53,"Private",208321,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,1740,40,"United-States","<=50K" +31,"Private",109428,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,1740,40,"United-States","<=50K" +46,"State-gov",107231,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1740,40,"United-States","<=50K" +59,"Private",314149,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,1740,50,"United-States","<=50K" +62,"Self-emp-not-inc",197353,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1740,40,"United-States","<=50K" +46,"Private",148738,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,1740,35,"United-States","<=50K" +45,"Private",227791,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1740,50,"United-States","<=50K" +63,"State-gov",216871,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1740,40,"United-States","<=50K" +73,"Private",301210,"1st-4th",2,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1735,20,"United-States","<=50K" +75,"Self-emp-not-inc",205860,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,1735,40,"United-States","<=50K" +45,"Local-gov",132563,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","Black","Female",0,1726,40,"United-States","<=50K" +39,"Private",237943,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,1726,40,"United-States","<=50K" +32,"State-gov",213389,"Some-college",10,"Divorced","Protective-serv","Unmarried","White","Female",0,1726,38,"United-States","<=50K" +25,"Private",122489,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,1726,60,"United-States","<=50K" +24,"Private",172146,"9th",5,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,1721,40,"United-States","<=50K" +24,"Private",106085,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,1721,30,"United-States","<=50K" +31,"Private",120672,"11th",7,"Divorced","Handlers-cleaners","Other-relative","Black","Male",0,1721,40,"United-States","<=50K" +31,"Private",273324,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,1721,16,"United-States","<=50K" +20,"Private",91939,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,1721,30,"United-States","<=50K" +39,"Private",52978,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,1721,55,"United-States","<=50K" +19,"Private",184737,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,1721,40,"United-States","<=50K" +18,"Private",144711,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,1721,40,"United-States","<=50K" +18,"Private",193290,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,1721,20,"United-States","<=50K" +23,"?",381741,"Assoc-acdm",12,"Never-married","?","Own-child","White","Male",0,1721,20,"United-States","<=50K" +19,"Local-gov",210308,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,1721,30,"United-States","<=50K" +17,"Private",148522,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,1721,15,"United-States","<=50K" +17,"Private",93235,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,1721,25,"United-States","<=50K" +22,"?",236330,"Some-college",10,"Never-married","?","Own-child","Black","Male",0,1721,20,"United-States","<=50K" +19,"Private",243941,"Some-college",10,"Never-married","Sales","Own-child","Amer-Indian-Eskimo","Female",0,1721,25,"United-States","<=50K" +21,"Private",132053,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,1721,35,"United-States","<=50K" +23,"Private",129767,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,1721,40,"United-States","<=50K" +39,"Self-emp-not-inc",251710,"10th",6,"Married-spouse-absent","Other-service","Not-in-family","White","Female",0,1721,15,"United-States","<=50K" +20,"Private",111697,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,1719,28,"United-States","<=50K" +20,"State-gov",223515,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Male",0,1719,20,"United-States","<=50K" +21,"Private",32616,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,1719,16,"United-States","<=50K" +18,"Private",201901,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,1719,15,"United-States","<=50K" +30,"?",96851,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,1719,25,"United-States","<=50K" +19,"Private",387215,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,1719,16,"United-States","<=50K" +22,"Private",217961,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,1719,30,"United-States","<=50K" +26,"Private",322614,"Preschool",1,"Married-spouse-absent","Machine-op-inspct","Not-in-family","White","Male",0,1719,40,"Mexico","<=50K" +19,"Private",158118,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,1719,40,"United-States","<=50K" +22,"Private",347867,"HS-grad",9,"Married-spouse-absent","Sales","Not-in-family","White","Male",0,1719,40,"United-States","<=50K" +37,"Private",252947,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,1719,32,"United-States","<=50K" +47,"Private",27815,"9th",5,"Divorced","Other-service","Not-in-family","White","Female",0,1719,30,"United-States","<=50K" +57,"Private",299358,"HS-grad",9,"Widowed","Other-service","Other-relative","White","Female",0,1719,25,"United-States","<=50K" +21,"Private",257781,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,1719,30,"United-States","<=50K" +21,"Private",540712,"HS-grad",9,"Never-married","Other-service","Other-relative","Black","Male",0,1719,25,"United-States","<=50K" +25,"Local-gov",190107,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,1719,16,"United-States","<=50K" +23,"Private",151910,"Bachelors",13,"Never-married","Machine-op-inspct","Own-child","White","Female",0,1719,40,"United-States","<=50K" +17,"Private",184924,"9th",5,"Never-married","Handlers-cleaners","Own-child","White","Male",0,1719,15,"United-States","<=50K" +19,"?",351195,"9th",5,"Never-married","?","Other-relative","White","Male",0,1719,35,"El-Salvador","<=50K" +17,"Private",116626,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,1719,18,"United-States","<=50K" +20,"Private",39803,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,1719,36,"United-States","<=50K" +21,"Private",387335,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,1719,9,"United-States","<=50K" +32,"Private",110331,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1672,60,"United-States","<=50K" +50,"Self-emp-inc",175339,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1672,60,"United-States","<=50K" +31,"Private",59083,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,1672,50,"United-States","<=50K" +60,"Self-emp-not-inc",170114,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1672,84,"United-States","<=50K" +34,"Private",80933,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1672,40,"United-States","<=50K" +34,"Private",119422,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1672,50,"United-States","<=50K" +45,"Federal-gov",181970,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1672,40,"United-States","<=50K" +57,"Private",109638,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1672,45,"United-States","<=50K" +55,"Private",177484,"11th",7,"Married-civ-spouse","Other-service","Husband","Black","Male",0,1672,40,"United-States","<=50K" +61,"Private",213321,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1672,40,"United-States","<=50K" +51,"Self-emp-not-inc",32372,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1672,70,"United-States","<=50K" +35,"Private",54317,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1672,50,"United-States","<=50K" +29,"Private",147755,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1672,40,"United-States","<=50K" +40,"Private",187164,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1672,45,"United-States","<=50K" +46,"Self-emp-not-inc",182541,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1672,50,"United-States","<=50K" +48,"Private",185041,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1672,55,"United-States","<=50K" +36,"Local-gov",241998,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1672,50,"United-States","<=50K" +46,"Self-emp-not-inc",197836,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1672,50,"United-States","<=50K" +42,"Private",117319,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1672,40,"United-States","<=50K" +57,"Private",61761,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1672,45,"United-States","<=50K" +43,"Private",220109,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,1672,44,"United-States","<=50K" +28,"Private",346406,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1672,50,"United-States","<=50K" +49,"Private",190115,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1672,44,"United-States","<=50K" +49,"Self-emp-not-inc",208872,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1672,98,"United-States","<=50K" +33,"Private",232356,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1672,55,"United-States","<=50K" +30,"Private",460408,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1672,45,"United-States","<=50K" +54,"Private",145419,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1672,50,"United-States","<=50K" +56,"Self-emp-inc",119891,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1672,40,"United-States","<=50K" +36,"State-gov",110964,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,1672,38,"United-States","<=50K" +40,"Self-emp-not-inc",89413,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1672,40,"United-States","<=50K" +32,"Private",97723,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1672,40,"United-States","<=50K" +47,"Self-emp-not-inc",107231,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1672,65,"United-States","<=50K" +40,"Private",566537,"Preschool",1,"Married-civ-spouse","Other-service","Husband","White","Male",0,1672,40,"Mexico","<=50K" +37,"Private",186009,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1672,60,"United-States","<=50K" +28,"Private",196690,"Assoc-voc",11,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,1669,42,"United-States","<=50K" +37,"Private",35330,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,1669,55,"United-States","<=50K" +48,"Private",125933,"Some-college",10,"Widowed","Exec-managerial","Unmarried","Black","Female",0,1669,38,"United-States","<=50K" +31,"Private",207537,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,1669,50,"United-States","<=50K" +26,"Private",117833,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,1669,50,"United-States","<=50K" +23,"Private",435835,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,1669,55,"United-States","<=50K" +39,"Self-emp-not-inc",331481,"Bachelors",13,"Divorced","Craft-repair","Not-in-family","Black","Male",0,1669,60,"?","<=50K" +49,"Private",30219,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,1669,40,"United-States","<=50K" +56,"State-gov",274111,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,1669,40,"United-States","<=50K" +47,"Private",155124,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Female",0,1669,40,"United-States","<=50K" +34,"Private",185041,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1669,45,"United-States","<=50K" +32,"Private",48458,"HS-grad",9,"Never-married","Sales","Own-child","Black","Female",0,1669,45,"United-States","<=50K" +28,"Private",72443,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1669,60,"United-States","<=50K" +38,"Local-gov",30509,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1669,55,"United-States","<=50K" +34,"Private",245173,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,1669,45,"United-States","<=50K" +36,"Private",224566,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Male",0,1669,45,"United-States","<=50K" +30,"Private",33688,"HS-grad",9,"Never-married","Transport-moving","Unmarried","White","Female",0,1669,70,"United-States","<=50K" +26,"Private",104834,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1669,40,"United-States","<=50K" +40,"Private",180032,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1669,40,"United-States","<=50K" +56,"Local-gov",52953,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Female",0,1669,38,"United-States","<=50K" +44,"Local-gov",196456,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1669,40,"United-States","<=50K" +33,"Local-gov",169652,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Male",0,1669,55,"United-States","<=50K" +53,"Local-gov",137250,"Masters",14,"Widowed","Prof-specialty","Unmarried","Black","Female",0,1669,35,"United-States","<=50K" +61,"Private",190682,"HS-grad",9,"Widowed","Craft-repair","Not-in-family","Black","Female",0,1669,50,"United-States","<=50K" +65,"Self-emp-not-inc",316093,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",0,1668,40,"United-States","<=50K" +81,"Self-emp-not-inc",123959,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","White","Female",0,1668,3,"Hungary","<=50K" +68,"?",286869,"7th-8th",4,"Widowed","?","Not-in-family","White","Female",0,1668,40,"?","<=50K" +68,"Local-gov",144761,"HS-grad",9,"Widowed","Protective-serv","Not-in-family","White","Male",0,1668,20,"United-States","<=50K" +39,"Self-emp-inc",218184,"9th",5,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1651,40,"Mexico","<=50K" +61,"Private",107438,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,1651,40,"United-States","<=50K" +61,"Private",162391,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1651,40,"United-States","<=50K" +46,"Private",138370,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,1651,40,"China","<=50K" +56,"Self-emp-inc",216636,"12th",8,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1651,40,"United-States","<=50K" +30,"Private",190912,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","Asian-Pac-Islander","Male",0,1651,40,"Vietnam","<=50K" +35,"State-gov",193241,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1651,40,"United-States","<=50K" +34,"Private",261023,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1651,38,"United-States","<=50K" +27,"Private",37250,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1651,40,"United-States","<=50K" +65,"Local-gov",146454,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1648,4,"Greece","<=50K" +74,"Self-emp-not-inc",206682,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1648,35,"United-States","<=50K" +26,"Private",280093,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1628,50,"United-States","<=50K" +62,"Private",162245,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1628,70,"United-States","<=50K" +45,"Private",188386,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,1628,45,"United-States","<=50K" +28,"Private",241895,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1628,40,"United-States","<=50K" +37,"Private",295949,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1628,40,"United-States","<=50K" +28,"Private",273929,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,1628,60,"United-States","<=50K" +46,"Private",85109,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1628,40,"United-States","<=50K" +39,"Federal-gov",432555,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,1628,40,"United-States","<=50K" +34,"Private",238305,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,1628,12,"?","<=50K" +37,"Private",282872,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1628,40,"United-States","<=50K" +41,"?",211873,"Assoc-voc",11,"Married-civ-spouse","?","Wife","White","Female",0,1628,5,"?","<=50K" +39,"Private",278557,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1628,48,"United-States","<=50K" +51,"Local-gov",47415,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,1628,30,"United-States","<=50K" +42,"Private",173590,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1628,40,"United-States","<=50K" +40,"Private",87771,"HS-grad",9,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,1628,45,"United-States","<=50K" +23,"Private",107801,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,1617,25,"United-States","<=50K" +43,"Private",216042,"Some-college",10,"Divorced","Tech-support","Own-child","White","Female",0,1617,72,"United-States","<=50K" +55,"State-gov",71630,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,1617,40,"United-States","<=50K" +56,"Private",99359,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,1617,40,"United-States","<=50K" +44,"Private",344920,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,1617,20,"United-States","<=50K" +30,"Private",194141,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,1617,40,"United-States","<=50K" +36,"Private",206253,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,1617,40,"United-States","<=50K" +62,"Private",109463,"Some-college",10,"Separated","Sales","Unmarried","White","Female",0,1617,33,"United-States","<=50K" +33,"Private",190772,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,1617,40,"United-States","<=50K" +19,"Private",242941,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,1602,10,"United-States","<=50K" +26,"Private",225279,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,1602,40,"?","<=50K" +19,"Private",93604,"7th-8th",4,"Never-married","Craft-repair","Own-child","White","Male",0,1602,32,"United-States","<=50K" +19,"Private",167140,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,1602,24,"United-States","<=50K" +25,"?",122745,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,1602,40,"United-States","<=50K" +26,"Private",303973,"HS-grad",9,"Never-married","Priv-house-serv","Other-relative","White","Female",0,1602,15,"Mexico","<=50K" +22,"?",219233,"HS-grad",9,"Never-married","?","Own-child","Black","Male",0,1602,30,"United-States","<=50K" +19,"Private",240468,"Some-college",10,"Married-spouse-absent","Sales","Own-child","White","Female",0,1602,40,"United-States","<=50K" +32,"Private",105938,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,1602,20,"United-States","<=50K" +18,"?",276864,"Some-college",10,"Never-married","?","Own-child","White","Female",0,1602,20,"United-States","<=50K" +22,"Private",215395,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,1602,10,"United-States","<=50K" +21,"Private",119309,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,1602,16,"United-States","<=50K" +20,"?",144685,"Some-college",10,"Never-married","?","Own-child","Asian-Pac-Islander","Female",0,1602,40,"Taiwan","<=50K" +18,"?",255282,"11th",7,"Never-married","?","Own-child","Black","Male",0,1602,48,"United-States","<=50K" +25,"Private",282313,"10th",6,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,1602,40,"United-States","<=50K" +21,"Private",180339,"Assoc-voc",11,"Never-married","Farming-fishing","Not-in-family","White","Female",0,1602,30,"United-States","<=50K" +21,"State-gov",48121,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,1602,10,"United-States","<=50K" +17,"Private",209949,"11th",7,"Never-married","Sales","Own-child","White","Female",0,1602,12,"United-States","<=50K" +57,"Private",142791,"7th-8th",4,"Widowed","Sales","Other-relative","White","Female",0,1602,3,"United-States","<=50K" +23,"Private",53245,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,1602,12,"United-States","<=50K" +30,"Private",48829,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,1602,30,"United-States","<=50K" +18,"Private",238867,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,1602,40,"United-States","<=50K" +18,"?",214989,"Some-college",10,"Never-married","?","Own-child","White","Female",0,1602,24,"United-States","<=50K" +17,"Private",225106,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,1602,18,"United-States","<=50K" +39,"Private",194287,"7th-8th",4,"Never-married","Other-service","Own-child","White","Male",0,1602,35,"United-States","<=50K" +18,"Private",414721,"11th",7,"Never-married","Other-service","Own-child","Black","Male",0,1602,23,"United-States","<=50K" +19,"?",218471,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,1602,30,"United-States","<=50K" +18,"?",261276,"Some-college",10,"Never-married","?","Own-child","Black","Female",0,1602,40,"Cambodia","<=50K" +17,"Local-gov",170916,"10th",6,"Never-married","Protective-serv","Own-child","White","Female",0,1602,40,"United-States","<=50K" +21,"State-gov",145651,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,1602,12,"United-States","<=50K" +18,"Private",166889,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Black","Female",0,1602,35,"United-States","<=50K" +19,"Private",124486,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,1602,20,"United-States","<=50K" +18,"Private",404868,"11th",7,"Never-married","Sales","Own-child","Black","Female",0,1602,20,"United-States","<=50K" +18,"Private",77845,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,1602,15,"United-States","<=50K" +19,"?",278220,"Some-college",10,"Never-married","?","Own-child","White","Female",0,1602,40,"United-States","<=50K" +17,"Federal-gov",99893,"11th",7,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,1602,40,"United-States","<=50K" +17,"Private",218361,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,1602,12,"United-States","<=50K" +18,"?",171964,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,1602,20,"United-States","<=50K" +19,"Private",283945,"10th",6,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,1602,45,"United-States","<=50K" +20,"Private",289405,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,1602,15,"United-States","<=50K" +57,"Self-emp-not-inc",118806,"1st-4th",2,"Widowed","Craft-repair","Other-relative","White","Female",0,1602,45,"Columbia","<=50K" +17,"Private",132680,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,1602,10,"United-States","<=50K" +21,"Private",301408,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,1602,22,"United-States","<=50K" +18,"?",51574,"HS-grad",9,"Never-married","?","Own-child","Asian-Pac-Islander","Female",0,1602,38,"United-States","<=50K" +20,"?",369678,"12th",8,"Never-married","?","Not-in-family","Other","Male",0,1602,40,"United-States","<=50K" +46,"Private",155933,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,1602,8,"United-States","<=50K" +18,"Private",41381,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,1602,20,"United-States","<=50K" +23,"Private",183327,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Female",0,1594,20,"United-States","<=50K" +27,"Private",60374,"HS-grad",9,"Widowed","Craft-repair","Unmarried","White","Female",0,1594,26,"United-States","<=50K" +48,"Private",254809,"10th",6,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,1594,32,"United-States","<=50K" +46,"Private",213611,"7th-8th",4,"Married-spouse-absent","Priv-house-serv","Unmarried","White","Female",0,1594,24,"Guatemala","<=50K" +31,"Private",651396,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,1594,30,"United-States","<=50K" +25,"Private",52536,"Assoc-acdm",12,"Divorced","Tech-support","Own-child","White","Female",0,1594,25,"United-States","<=50K" +26,"Private",149734,"HS-grad",9,"Separated","Craft-repair","Unmarried","Black","Female",0,1594,40,"United-States","<=50K" +35,"Private",220943,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Female",0,1594,40,"United-States","<=50K" +27,"Private",137645,"Bachelors",13,"Never-married","Sales","Not-in-family","Black","Female",0,1590,40,"United-States","<=50K" +29,"Private",149943,"Some-college",10,"Never-married","Other-service","Not-in-family","Other","Male",0,1590,40,"?","<=50K" +39,"?",103986,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,1590,40,"United-States","<=50K" +42,"Private",191712,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,1590,40,"United-States","<=50K" +20,"Private",131230,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,1590,40,"United-States","<=50K" +32,"Private",43403,"Some-college",10,"Divorced","Farming-fishing","Not-in-family","White","Female",0,1590,54,"United-States","<=50K" +50,"Federal-gov",176969,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Male",0,1590,40,"United-States","<=50K" +55,"Private",151474,"Bachelors",13,"Never-married","Tech-support","Other-relative","White","Female",0,1590,38,"United-States","<=50K" +29,"State-gov",188986,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Female",0,1590,64,"United-States","<=50K" +41,"Private",48087,"7th-8th",4,"Divorced","Craft-repair","Not-in-family","White","Male",0,1590,40,"United-States","<=50K" +25,"Private",34402,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1590,60,"United-States","<=50K" +46,"Private",170850,"Bachelors",13,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,1590,40,"?","<=50K" +29,"Private",183009,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Other","Female",0,1590,40,"United-States","<=50K" +23,"Private",220993,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,1590,48,"United-States","<=50K" +25,"Private",177499,"Bachelors",13,"Never-married","Craft-repair","Own-child","White","Male",0,1590,35,"United-States","<=50K" +42,"Private",37869,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,1590,40,"United-States","<=50K" +41,"Self-emp-not-inc",214541,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,1590,40,"United-States","<=50K" +32,"Private",290964,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,1590,40,"United-States","<=50K" +25,"Private",123095,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,1590,40,"United-States","<=50K" +41,"State-gov",518030,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","Black","Male",0,1590,40,"Puerto-Rico","<=50K" +24,"Private",24243,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,1590,40,"United-States","<=50K" +44,"State-gov",154176,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,1590,40,"United-States","<=50K" +29,"Private",190539,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1590,50,"United-States","<=50K" +51,"Private",348099,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,1590,40,"United-States","<=50K" +39,"Private",382802,"10th",6,"Widowed","Machine-op-inspct","Not-in-family","Black","Male",0,1590,40,"United-States","<=50K" +28,"Self-emp-not-inc",54683,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,1590,40,"United-States","<=50K" +48,"Private",99096,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,1590,38,"United-States","<=50K" +34,"Private",54850,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1590,50,"United-States","<=50K" +45,"Private",293691,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,1590,40,"Japan","<=50K" +47,"Private",192053,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,1590,40,"United-States","<=50K" +50,"Private",188186,"Masters",14,"Divorced","Sales","Not-in-family","White","Female",0,1590,45,"United-States","<=50K" +32,"Private",317219,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1590,40,"United-States","<=50K" +46,"Private",160474,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,1590,43,"United-States","<=50K" +32,"Private",165949,"Bachelors",13,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,1590,42,"United-States","<=50K" +34,"Private",211948,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,1590,40,"United-States","<=50K" +32,"Self-emp-not-inc",188246,"HS-grad",9,"Divorced","Sales","Own-child","White","Male",0,1590,62,"United-States","<=50K" +35,"Private",140915,"Bachelors",13,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,1590,40,"South","<=50K" +29,"Local-gov",82393,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","Asian-Pac-Islander","Male",0,1590,45,"United-States","<=50K" +46,"Private",254367,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,1590,48,"United-States","<=50K" +30,"Private",340899,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,1590,80,"United-States","<=50K" +34,"Local-gov",62463,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1579,40,"United-States","<=50K" +35,"Private",111387,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,1579,40,"United-States","<=50K" +31,"Private",260782,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1579,45,"El-Salvador","<=50K" +21,"Private",146499,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Other-relative","White","Female",0,1579,40,"United-States","<=50K" +40,"Federal-gov",177595,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1579,40,"United-States","<=50K" +48,"Private",273435,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1579,40,"United-States","<=50K" +41,"Private",289886,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","Other","Male",0,1579,40,"Nicaragua","<=50K" +33,"Private",54782,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1579,42,"United-States","<=50K" +31,"Private",164243,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1579,40,"United-States","<=50K" +54,"Self-emp-not-inc",58898,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1579,48,"United-States","<=50K" +51,"Self-emp-not-inc",136322,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1579,40,"United-States","<=50K" +25,"Private",182227,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1579,40,"United-States","<=50K" +43,"Local-gov",301638,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1579,40,"United-States","<=50K" +26,"Self-emp-not-inc",221626,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,1579,20,"United-States","<=50K" +27,"Private",87006,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,1579,40,"United-States","<=50K" +24,"Private",216469,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1579,50,"United-States","<=50K" +50,"Private",95435,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1579,65,"Canada","<=50K" +55,"Private",135803,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Other","Male",0,1579,35,"India","<=50K" +42,"Private",119679,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1579,42,"United-States","<=50K" +59,"Self-emp-not-inc",56392,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1579,60,"United-States","<=50K" +30,"Private",117747,"HS-grad",9,"Married-civ-spouse","Sales","Wife","Asian-Pac-Islander","Female",0,1573,35,"?","<=50K" +20,"Private",115824,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,1573,40,"United-States","<=50K" +23,"Private",278107,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1573,30,"United-States","<=50K" +34,"Private",58305,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1573,40,"United-States","<=50K" +31,"Private",202450,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1573,40,"United-States","<=50K" +27,"Self-emp-not-inc",151402,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1573,70,"United-States","<=50K" +45,"Private",196584,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1564,40,"United-States",">50K" +43,"Private",174575,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,1564,45,"United-States",">50K" +40,"Self-emp-not-inc",266324,"Some-college",10,"Divorced","Exec-managerial","Other-relative","White","Male",0,1564,70,"Iran",">50K" +53,"Private",156843,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1564,54,"United-States",">50K" +51,"Federal-gov",282680,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1564,70,"United-States",">50K" +40,"Private",179717,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,1564,60,"United-States",">50K" +46,"Federal-gov",43206,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1564,50,"United-States",">50K" +51,"Private",216475,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,1564,43,"United-States",">50K" +42,"Private",143046,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1564,38,"United-States",">50K" +46,"State-gov",119904,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1564,55,"United-States",">50K" +28,"Private",181291,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,1564,50,"United-States",">50K" +34,"Private",98283,"Prof-school",15,"Never-married","Tech-support","Not-in-family","Asian-Pac-Islander","Male",0,1564,40,"India",">50K" +39,"Self-emp-not-inc",230329,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,1564,12,"United-States",">50K" +30,"Private",327112,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,1564,40,"United-States",">50K" +33,"Local-gov",281784,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Black","Male",0,1564,52,"United-States",">50K" +28,"Private",190067,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,1564,40,"United-States",">50K" +44,"Private",207685,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1564,55,"England",">50K" +34,"Private",34862,"Bachelors",13,"Divorced","Sales","Not-in-family","Amer-Indian-Eskimo","Male",0,1564,60,"United-States",">50K" +29,"Self-emp-not-inc",341672,"HS-grad",9,"Married-spouse-absent","Transport-moving","Other-relative","Asian-Pac-Islander","Male",0,1564,50,"India",">50K" +47,"Private",150768,"Bachelors",13,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,1564,51,"United-States",">50K" +39,"Private",165106,"Bachelors",13,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,1564,50,"?",">50K" +29,"Local-gov",302422,"Assoc-voc",11,"Never-married","Protective-serv","Not-in-family","White","Male",0,1564,56,"United-States",">50K" +31,"Private",240441,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1564,40,"United-States",">50K" +31,"Private",44464,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,1564,60,"United-States",">50K" +39,"Private",284166,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,1564,50,"United-States",">50K" +67,"Private",397831,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1539,40,"United-States","<=50K" +46,"Private",187370,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,1504,40,"United-States","<=50K" +44,"Private",111483,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,1504,50,"United-States","<=50K" +21,"?",161930,"HS-grad",9,"Never-married","?","Own-child","Black","Female",0,1504,30,"United-States","<=50K" +25,"Private",178505,"Some-college",10,"Never-married","Exec-managerial","Other-relative","White","Female",0,1504,45,"United-States","<=50K" +59,"Local-gov",114401,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,1504,19,"United-States","<=50K" +47,"Private",223342,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,1504,35,"United-States","<=50K" +21,"Private",118712,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,1504,40,"United-States","<=50K" +44,"Private",222978,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,1504,40,"United-States","<=50K" +31,"Private",187901,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,1504,40,"United-States","<=50K" +37,"Private",245053,"Some-college",10,"Divorced","Handlers-cleaners","Own-child","White","Male",0,1504,40,"United-States","<=50K" +44,"Private",262684,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,1504,45,"United-States","<=50K" +25,"Private",177017,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,1504,37,"United-States","<=50K" +21,"Private",52753,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,1504,40,"United-States","<=50K" +27,"Private",189462,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1504,45,"United-States","<=50K" +27,"Private",38606,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,1504,45,"United-States","<=50K" +53,"?",150393,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,1504,35,"United-States","<=50K" +34,"Self-emp-not-inc",156809,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,1504,60,"United-States","<=50K" +30,"Private",89735,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,1504,40,"United-States","<=50K" +43,"Private",50356,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1485,50,"United-States","<=50K" +32,"Private",211699,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1485,40,"United-States",">50K" +49,"Private",168211,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1485,40,"United-States",">50K" +41,"Local-gov",344624,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,1485,40,"United-States",">50K" +32,"Private",130304,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1485,48,"United-States","<=50K" +48,"Private",202467,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1485,40,"United-States",">50K" +46,"Private",175109,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1485,40,"United-States",">50K" +59,"Private",107833,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1485,40,"United-States",">50K" +36,"Private",398931,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1485,50,"United-States",">50K" +53,"Private",238481,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1485,40,"United-States","<=50K" +37,"Private",176756,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,1485,70,"United-States",">50K" +58,"Federal-gov",81973,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,1485,40,"United-States",">50K" +47,"Private",189123,"11th",7,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1485,58,"United-States","<=50K" +40,"Private",316820,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,1485,40,"United-States","<=50K" +45,"Self-emp-not-inc",192203,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1485,40,"United-States",">50K" +30,"Private",97933,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Wife","White","Female",0,1485,37,"United-States",">50K" +60,"Self-emp-not-inc",148492,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1485,50,"United-States",">50K" +29,"Private",149324,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1485,40,"United-States",">50K" +29,"Self-emp-not-inc",190636,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,1485,60,"United-States",">50K" +32,"Private",351869,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1485,45,"United-States",">50K" +50,"Private",337606,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,1485,40,"United-States","<=50K" +41,"Private",204410,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1485,44,"United-States",">50K" +60,"?",56248,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,1485,70,"United-States",">50K" +29,"Local-gov",383745,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,1485,40,"United-States",">50K" +59,"Private",174864,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1485,45,"United-States",">50K" +37,"Self-emp-inc",26698,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1485,44,"United-States",">50K" +47,"Private",209460,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1485,47,"United-States","<=50K" +34,"Self-emp-not-inc",213226,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1485,35,"?","<=50K" +27,"Private",112754,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1485,60,"United-States",">50K" +34,"Private",90705,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,1485,40,"United-States","<=50K" +41,"Private",428499,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1485,50,"United-States",">50K" +42,"Local-gov",227890,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1485,40,"United-States","<=50K" +33,"?",173998,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,1485,38,"United-States","<=50K" +50,"Private",234373,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1485,40,"United-States","<=50K" +41,"Private",193524,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1485,40,"United-States","<=50K" +45,"Self-emp-not-inc",28497,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,1485,70,"United-States",">50K" +42,"Private",268183,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1485,60,"United-States","<=50K" +46,"Private",74895,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1485,55,"United-States","<=50K" +57,"State-gov",399246,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,1485,40,"China","<=50K" +38,"Self-emp-inc",244803,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1485,60,"Cuba",">50K" +45,"Self-emp-inc",311231,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,1485,50,"United-States",">50K" +34,"Private",287737,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,1485,40,"United-States",">50K" +38,"Private",300975,"Masters",14,"Married-civ-spouse","Other-service","Husband","Black","Male",0,1485,40,"?","<=50K" +35,"State-gov",184659,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,1485,40,"United-States",">50K" +63,"?",29859,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,1485,40,"United-States",">50K" +34,"Private",112212,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,1485,40,"United-States","<=50K" +44,"Private",223194,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,1485,40,"Haiti","<=50K" +44,"Local-gov",165304,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1485,40,"United-States",">50K" +50,"Self-emp-inc",52565,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,1485,40,"United-States","<=50K" +41,"Private",117585,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1485,40,"United-States",">50K" +31,"Private",251659,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,1485,55,"?",">50K" +65,"Local-gov",103153,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1411,40,"United-States","<=50K" +45,"Private",386940,"Bachelors",13,"Divorced","Exec-managerial","Own-child","White","Male",0,1408,40,"United-States","<=50K" +36,"Federal-gov",255191,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,1408,40,"United-States","<=50K" +31,"Private",331065,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,1408,40,"United-States","<=50K" +42,"Private",83411,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,1408,40,"United-States","<=50K" +38,"Private",193026,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Male",0,1408,40,"?","<=50K" +46,"Local-gov",202560,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,1408,40,"United-States","<=50K" +28,"Private",103802,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,1408,40,"?","<=50K" +35,"Private",474136,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,1408,40,"United-States","<=50K" +54,"Private",188136,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,1408,38,"United-States","<=50K" +34,"Private",345705,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,1408,38,"United-States","<=50K" +29,"Private",193152,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,1408,40,"United-States","<=50K" +24,"Private",216129,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,1408,50,"United-States","<=50K" +44,"Private",225263,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,1408,46,"United-States","<=50K" +33,"Private",213002,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,1408,36,"United-States","<=50K" +47,"Local-gov",219632,"Assoc-acdm",12,"Separated","Exec-managerial","Not-in-family","White","Male",0,1408,40,"United-States","<=50K" +28,"Private",339372,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,1408,40,"United-States","<=50K" +38,"Private",123833,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,1408,40,"United-States","<=50K" +41,"Private",41901,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,1408,40,"United-States","<=50K" +50,"Private",178596,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,1408,50,"United-States","<=50K" +29,"Federal-gov",106179,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1408,40,"United-States","<=50K" +50,"Self-emp-not-inc",240922,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Female",0,1408,5,"United-States","<=50K" +49,"Private",141944,"Assoc-voc",11,"Married-spouse-absent","Handlers-cleaners","Unmarried","White","Male",0,1380,42,"United-States","<=50K" +31,"Private",243605,"Bachelors",13,"Widowed","Sales","Unmarried","White","Female",0,1380,40,"Cuba","<=50K" +44,"Private",199031,"Some-college",10,"Divorced","Transport-moving","Own-child","White","Male",0,1380,40,"United-States","<=50K" +48,"Local-gov",121622,"Masters",14,"Never-married","Prof-specialty","Unmarried","White","Female",0,1380,40,"United-States","<=50K" +39,"Private",115289,"Some-college",10,"Divorced","Sales","Own-child","White","Male",0,1380,70,"United-States","<=50K" +39,"Private",49436,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",0,1380,40,"United-States","<=50K" +32,"Federal-gov",90653,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","White","Female",0,1380,40,"United-States","<=50K" +42,"Local-gov",254817,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1340,40,"United-States","<=50K" +25,"Private",212495,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,1340,40,"United-States","<=50K" +42,"Federal-gov",296798,"11th",7,"Never-married","Tech-support","Not-in-family","White","Male",0,1340,40,"United-States","<=50K" +44,"Local-gov",193882,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Male",0,1340,40,"United-States","<=50K" +38,"Private",188888,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,1340,40,"United-States","<=50K" +54,"Private",172962,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,1340,40,"United-States","<=50K" +37,"Private",405284,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1340,42,"United-States","<=50K" +62,"Local-gov",159908,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,1258,38,"United-States","<=50K" +72,"Local-gov",144515,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,1258,40,"United-States","<=50K" +76,"?",224680,"Prof-school",15,"Married-civ-spouse","?","Husband","White","Male",0,1258,20,"United-States","<=50K" +66,"Private",350498,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,1258,20,"United-States","<=50K" +33,"Local-gov",262042,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,1138,40,"United-States","<=50K" +29,"Private",138190,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,1138,40,"United-States","<=50K" +25,"Private",74883,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Asian-Pac-Islander","Female",0,1092,40,"Philippines","<=50K" +39,"Private",230467,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,1092,40,"Germany","<=50K" +33,"Private",207937,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,1092,40,"United-States","<=50K" +53,"State-gov",281074,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,1092,40,"United-States","<=50K" +52,"Private",113094,"Bachelors",13,"Separated","Adm-clerical","Unmarried","White","Female",0,1092,40,"United-States","<=50K" +23,"Local-gov",442359,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,1092,40,"United-States","<=50K" +60,"Private",75726,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,1092,40,"United-States","<=50K" +27,"Private",151382,"7th-8th",4,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,974,40,"United-States","<=50K" +34,"Private",32528,"Assoc-voc",11,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",0,974,40,"United-States","<=50K" +43,"Self-emp-not-inc",336763,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,880,42,"United-States","<=50K" +33,"Private",99339,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Female",0,880,40,"United-States","<=50K" +31,"Private",323069,"Assoc-acdm",12,"Divorced","Sales","Unmarried","White","Female",0,880,45,"United-States","<=50K" +50,"Federal-gov",299831,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,880,40,"United-States","<=50K" +32,"Private",203674,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",0,880,36,"United-States","<=50K" +34,"Private",60567,"11th",7,"Divorced","Transport-moving","Unmarried","White","Male",0,880,60,"United-States","<=50K" +69,"State-gov",159191,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,810,38,"United-States","<=50K" +65,"Private",190568,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,810,36,"United-States","<=50K" +57,"Private",34269,"HS-grad",9,"Widowed","Transport-moving","Unmarried","White","Male",0,653,42,"United-States",">50K" +42,"Private",259757,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Male",0,653,50,"United-States",">50K" +49,"Private",116338,"HS-grad",9,"Separated","Prof-specialty","Unmarried","White","Female",0,653,60,"United-States","<=50K" +40,"Private",315321,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,625,52,"United-States","<=50K" +43,"Local-gov",118600,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,625,40,"United-States","<=50K" +59,"Private",230039,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","White","Female",0,625,38,"United-States","<=50K" +39,"Federal-gov",257175,"Bachelors",13,"Divorced","Tech-support","Unmarried","Black","Female",0,625,40,"United-States","<=50K" +49,"Local-gov",159641,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,625,40,"United-States","<=50K" +39,"State-gov",119421,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,625,35,"United-States","<=50K" +49,"Private",169042,"HS-grad",9,"Separated","Prof-specialty","Unmarried","White","Female",0,625,40,"Puerto-Rico","<=50K" +39,"Private",81487,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,625,40,"United-States","<=50K" +43,"Private",122473,"9th",5,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,625,40,"United-States","<=50K" +41,"Private",332703,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Other","Female",0,625,40,"United-States","<=50K" +46,"Private",157991,"Assoc-voc",11,"Divorced","Tech-support","Unmarried","Black","Female",0,625,40,"United-States","<=50K" +47,"Private",144351,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,625,40,"United-States","<=50K" +67,"?",184506,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,419,3,"United-States","<=50K" +68,"Private",32779,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,419,12,"United-States","<=50K" +27,"?",501172,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,419,20,"Mexico","<=50K" +52,"Private",122109,"HS-grad",9,"Never-married","Prof-specialty","Unmarried","White","Female",0,323,40,"United-States","<=50K" +46,"Private",198774,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",0,323,45,"United-States","<=50K" +49,"Local-gov",78859,"Masters",14,"Widowed","Prof-specialty","Unmarried","White","Female",0,323,20,"United-States","<=50K" +37,"Private",262409,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",0,213,45,"United-States","<=50K" +38,"Private",173047,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,213,40,"Philippines","<=50K" +40,"Private",65866,"Some-college",10,"Divorced","Tech-support","Unmarried","White","Female",0,213,40,"United-States","<=50K" +36,"Private",204590,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","Black","Female",0,213,40,"United-States","<=50K" +28,"Private",140845,"10th",6,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,155,40,"United-States","<=50K" +54,"Self-emp-inc",166459,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,60,"United-States",">50K" +52,"Private",152234,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",99999,0,40,"Japan",">50K" +53,"Self-emp-inc",263925,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,40,"United-States",">50K" +52,"Private",118025,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,50,"United-States",">50K" +46,"Private",370119,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,60,"United-States",">50K" +43,"Private",176270,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,60,"United-States",">50K" +49,"Private",159816,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",99999,0,20,"United-States",">50K" +50,"Private",171338,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,50,"United-States",">50K" +22,"Self-emp-not-inc",202920,"HS-grad",9,"Never-married","Prof-specialty","Unmarried","White","Female",99999,0,40,"Dominican-Republic",">50K" +43,"Self-emp-inc",172826,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,55,"United-States",">50K" +65,"Self-emp-inc",139272,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,60,"United-States",">50K" +26,"Private",256000,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,60,"United-States",">50K" +52,"Self-emp-not-inc",64045,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,45,"United-States",">50K" +46,"Private",176814,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,50,"United-States",">50K" +36,"Private",208358,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",99999,0,45,"United-States",">50K" +40,"Self-emp-not-inc",223881,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,70,"United-States",">50K" +52,"Self-emp-inc",90363,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,35,"United-States",">50K" +32,"Self-emp-inc",46807,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",99999,0,40,"United-States",">50K" +53,"Private",88842,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,40,"United-States",">50K" +47,"Private",345493,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",99999,0,55,"Taiwan",">50K" +37,"Local-gov",287306,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",99999,0,40,"?",">50K" +37,"Self-emp-not-inc",362062,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,50,"United-States",">50K" +39,"Self-emp-inc",114844,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,65,"United-States",">50K" +38,"Private",146091,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Wife","White","Female",99999,0,36,"United-States",">50K" +44,"Private",332401,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,65,"United-States",">50K" +57,"Self-emp-inc",159028,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,60,"United-States",">50K" +51,"Private",44000,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",99999,0,50,"United-States",">50K" +78,"Self-emp-not-inc",316261,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",99999,0,20,"United-States",">50K" +36,"Private",383518,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",99999,0,40,"United-States",">50K" +49,"Self-emp-inc",362795,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Male",99999,0,80,"Mexico",">50K" +54,"Self-emp-not-inc",269068,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",99999,0,50,"Philippines",">50K" +41,"Self-emp-inc",194636,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,65,"United-States",">50K" +46,"Local-gov",222115,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",99999,0,40,"United-States",">50K" +33,"Private",170769,"Doctorate",16,"Divorced","Sales","Not-in-family","White","Male",99999,0,60,"United-States",">50K" +36,"Self-emp-not-inc",241998,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,20,"United-States",">50K" +63,"Private",118798,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",99999,0,40,"United-States",">50K" +38,"Private",167140,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,70,"United-States",">50K" +33,"Private",198660,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",99999,0,56,"United-States",">50K" +47,"Private",168262,"Masters",14,"Separated","Exec-managerial","Not-in-family","White","Male",99999,0,50,"United-States",">50K" +28,"Private",37359,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,50,"United-States",">50K" +52,"Self-emp-inc",181855,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Other","Male",99999,0,65,"United-States",">50K" +30,"Private",132601,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,50,"United-States",">50K" +50,"Private",108435,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,60,"United-States",">50K" +32,"Private",134737,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,50,"United-States",">50K" +46,"Private",273771,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,40,"United-States",">50K" +49,"Self-emp-not-inc",355978,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,35,"United-States",">50K" +30,"Private",235124,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",99999,0,40,"United-States",">50K" +32,"Private",204567,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,60,"United-States",">50K" +59,"Private",122283,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",99999,0,40,"India",">50K" +46,"Self-emp-inc",198660,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,72,"United-States",">50K" +32,"Private",330715,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",99999,0,40,"United-States",">50K" +21,"Private",334618,"Some-college",10,"Never-married","Protective-serv","Not-in-family","Black","Female",99999,0,40,"United-States",">50K" +56,"Self-emp-inc",205601,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,70,"United-States",">50K" +43,"Private",208613,"Prof-school",15,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",99999,0,40,"United-States",">50K" +30,"Private",129707,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,35,"United-States",">50K" +39,"Private",77005,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,40,"United-States",">50K" +24,"?",151153,"Some-college",10,"Never-married","?","Not-in-family","Asian-Pac-Islander","Male",99999,0,50,"South",">50K" +46,"Self-emp-inc",120131,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,60,"United-States",">50K" +50,"Self-emp-not-inc",155118,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",99999,0,35,"United-States",">50K" +60,"Private",191446,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,40,"United-States",">50K" +36,"Self-emp-inc",216711,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,50,"?",">50K" +47,"Private",193047,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,50,"United-States",">50K" +56,"Self-emp-not-inc",163212,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",99999,0,40,"United-States",">50K" +53,"Private",366957,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",99999,0,50,"India",">50K" +42,"Private",187795,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,55,"United-States",">50K" +50,"Private",238959,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,60,"?",">50K" +48,"Private",25468,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",99999,0,50,"United-States",">50K" +41,"Private",320984,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,65,"United-States",">50K" +72,"Self-emp-inc",172407,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,50,"United-States",">50K" +55,"Private",197399,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,55,"United-States",">50K" +33,"Private",162572,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,40,"United-States",">50K" +62,"Self-emp-inc",245491,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",99999,0,40,"United-States",">50K" +52,"Self-emp-inc",334273,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,65,"United-States",">50K" +50,"Private",124963,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,55,"United-States",">50K" +28,"Self-emp-inc",201186,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",99999,0,40,"United-States",">50K" +42,"Local-gov",180985,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",99999,0,40,"United-States",">50K" +51,"Private",145714,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,50,"?",">50K" +42,"Private",190179,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,40,"United-States",">50K" +50,"Self-emp-inc",158294,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,80,"United-States",">50K" +41,"Self-emp-inc",495061,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,70,"United-States",">50K" +47,"Private",102308,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,50,"United-States",">50K" +38,"Federal-gov",37683,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",99999,0,57,"Canada",">50K" +61,"?",139391,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",99999,0,30,"United-States",">50K" +57,"Self-emp-not-inc",95280,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,45,"United-States",">50K" +42,"Self-emp-not-inc",201908,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,50,"United-States",">50K" +47,"Private",354148,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,48,"United-States",">50K" +51,"Self-emp-not-inc",111283,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",99999,0,35,"United-States",">50K" +42,"Local-gov",175642,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",99999,0,40,"United-States",">50K" +47,"Self-emp-inc",181130,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,50,"United-States",">50K" +74,"Private",188709,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,50,"United-States",">50K" +39,"Private",190297,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,55,"United-States",">50K" +43,"Private",462180,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,60,"United-States",">50K" +47,"Private",181307,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,60,"United-States",">50K" +52,"Self-emp-not-inc",140985,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",99999,0,30,"United-States",">50K" +69,"?",323016,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",99999,0,40,"United-States",">50K" +58,"?",266792,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",99999,0,40,"United-States",">50K" +48,"Private",108557,"Bachelors",13,"Married-civ-spouse","Tech-support","Wife","White","Female",99999,0,40,"United-States",">50K" +55,"Self-emp-inc",392325,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,60,"United-States",">50K" +50,"Private",183173,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,40,"United-States",">50K" +49,"State-gov",423222,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,80,"United-States",">50K" +30,"Self-emp-not-inc",115932,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",99999,0,50,"United-States",">50K" +52,"Private",163998,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,45,"United-States",">50K" +46,"Private",28419,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,50,"United-States",">50K" +58,"Private",136841,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",99999,0,35,"United-States",">50K" +59,"Self-emp-not-inc",165315,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,43,"United-States",">50K" +50,"Self-emp-not-inc",401118,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",99999,0,50,"United-States",">50K" +40,"Private",79586,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",99999,0,40,"?",">50K" +43,"Private",58447,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,55,"United-States",">50K" +47,"Private",246739,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,55,"United-States",">50K" +65,"Private",105491,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,40,"United-States",">50K" +33,"Private",134886,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",99999,0,30,"United-States",">50K" +53,"Private",124076,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",99999,0,37,"United-States",">50K" +42,"Self-emp-not-inc",269733,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,80,"United-States",">50K" +69,"Self-emp-not-inc",240562,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,40,"United-States",">50K" +44,"Self-emp-inc",120277,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,45,"United-States",">50K" +44,"Self-emp-not-inc",282722,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,50,"United-States",">50K" +38,"Self-emp-inc",478829,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,50,"United-States",">50K" +39,"Private",237943,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,70,"United-States",">50K" +32,"Private",553405,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,50,"United-States",">50K" +41,"Private",115932,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,50,"United-States",">50K" +31,"Private",100252,"Bachelors",13,"Divorced","Other-service","Not-in-family","Asian-Pac-Islander","Male",99999,0,70,"United-States",">50K" +50,"Self-emp-not-inc",132716,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,50,"United-States",">50K" +49,"Private",187454,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,65,"United-States",">50K" +29,"Self-emp-not-inc",69132,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",99999,0,60,"United-States",">50K" +48,"Private",107231,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,50,"United-States",">50K" +40,"Local-gov",150755,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,75,"United-States",">50K" +45,"Private",148995,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",99999,0,30,"United-States",">50K" +60,"Private",166330,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",99999,0,40,"United-States",">50K" +49,"Self-emp-inc",229737,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,37,"United-States",">50K" +56,"Self-emp-inc",98418,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,40,"United-States",">50K" +45,"Self-emp-inc",108100,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","Asian-Pac-Islander","Female",99999,0,25,"?",">50K" +71,"Self-emp-inc",38822,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,40,"United-States",">50K" +57,"Self-emp-inc",376230,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,40,"United-States",">50K" +64,"Self-emp-inc",185912,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,35,"United-States",">50K" +41,"Private",124956,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","Black","Female",99999,0,60,"United-States",">50K" +49,"Self-emp-not-inc",43348,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",99999,0,70,"United-States",">50K" +55,"Private",408537,"9th",5,"Divorced","Craft-repair","Unmarried","White","Female",99999,0,37,"United-States",">50K" +48,"Self-emp-not-inc",107231,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,50,"United-States",">50K" +40,"Self-emp-not-inc",204235,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,50,"United-States",">50K" +55,"Private",115439,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,40,"United-States",">50K" +44,"Self-emp-inc",118212,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,70,"United-States",">50K" +38,"Private",227945,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,65,"United-States",">50K" +34,"Private",49469,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",99999,0,50,"United-States",">50K" +37,"Self-emp-not-inc",353298,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,50,"United-States",">50K" +51,"Self-emp-not-inc",120781,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Other","Male",99999,0,70,"India",">50K" +65,"Self-emp-inc",210381,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,65,"United-States",">50K" +38,"Self-emp-not-inc",194534,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",99999,0,60,"United-States",">50K" +65,"Self-emp-inc",184965,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,40,"United-States",">50K" +37,"Private",171150,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",99999,0,60,"United-States",">50K" +38,"Private",100375,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,60,"United-States",">50K" +50,"Self-emp-inc",190333,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",99999,0,55,"United-States",">50K" +55,"Private",134120,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",99999,0,40,"United-States",">50K" +38,"Private",185848,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,70,"United-States",">50K" +22,"Self-emp-not-inc",214014,"Some-college",10,"Never-married","Sales","Own-child","Black","Male",99999,0,55,"United-States",">50K" +47,"Private",155664,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,55,"United-States",">50K" +43,"Self-emp-inc",62026,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,40,"United-States",">50K" +66,"Private",115498,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,55,"?",">50K" +47,"Private",294913,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",99999,0,40,"United-States",">50K" +57,"Local-gov",110417,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",99999,0,40,"United-States",">50K" +27,"Private",211032,"Preschool",1,"Married-civ-spouse","Farming-fishing","Other-relative","White","Male",41310,0,24,"Mexico","<=50K" +63,"Self-emp-not-inc",289741,"Masters",14,"Married-civ-spouse","Farming-fishing","Husband","White","Male",41310,0,50,"United-States","<=50K" +17,"?",304873,"10th",6,"Never-married","?","Own-child","White","Female",34095,0,32,"United-States","<=50K" +18,"Private",301948,"HS-grad",9,"Never-married","Protective-serv","Own-child","White","Male",34095,0,3,"United-States","<=50K" +19,"Private",188815,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",34095,0,20,"United-States","<=50K" +55,"Self-emp-not-inc",145574,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",34095,0,60,"United-States","<=50K" +20,"?",273701,"Some-college",10,"Never-married","?","Other-relative","Black","Male",34095,0,10,"United-States","<=50K" +46,"Private",133938,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",27828,0,50,"United-States",">50K" +35,"Private",202027,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",27828,0,50,"United-States",">50K" +47,"Self-emp-inc",79627,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",27828,0,50,"United-States",">50K" +55,"Self-emp-not-inc",124975,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",27828,0,55,"United-States",">50K" +34,"Private",50276,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",27828,0,40,"United-States",">50K" +25,"Private",169905,"Assoc-voc",11,"Never-married","Sales","Not-in-family","White","Male",27828,0,40,"United-States",">50K" +56,"Self-emp-inc",70720,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",27828,0,60,"United-States",">50K" +25,"Private",102476,"Bachelors",13,"Never-married","Farming-fishing","Own-child","White","Male",27828,0,50,"United-States",">50K" +41,"Private",182108,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",27828,0,35,"United-States",">50K" +42,"Private",46221,"Doctorate",16,"Married-spouse-absent","Other-service","Not-in-family","White","Male",27828,0,60,"?",">50K" +37,"Self-emp-not-inc",32239,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",27828,0,40,"United-States",">50K" +47,"Private",233511,"Masters",14,"Divorced","Sales","Not-in-family","White","Male",27828,0,60,"United-States",">50K" +36,"Private",184456,"Prof-school",15,"Never-married","Exec-managerial","Not-in-family","White","Male",27828,0,50,"United-States",">50K" +58,"Self-emp-inc",112945,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",27828,0,40,"United-States",">50K" +45,"Private",148549,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",27828,0,56,"United-States",">50K" +49,"Private",120629,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","Black","Female",27828,0,60,"United-States",">50K" +37,"Private",116358,"HS-grad",9,"Never-married","Craft-repair","Other-relative","Amer-Indian-Eskimo","Male",27828,0,48,"United-States",">50K" +56,"Self-emp-not-inc",39380,"Some-college",10,"Married-spouse-absent","Farming-fishing","Not-in-family","White","Female",27828,0,20,"United-States",">50K" +37,"Private",109133,"Masters",14,"Separated","Exec-managerial","Not-in-family","White","Male",27828,0,60,"Iran",">50K" +59,"Private",154100,"Masters",14,"Never-married","Sales","Not-in-family","White","Female",27828,0,45,"United-States",">50K" +30,"Private",116138,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",27828,0,60,"United-States",">50K" +58,"?",353244,"Bachelors",13,"Widowed","?","Unmarried","White","Female",27828,0,50,"United-States",">50K" +29,"Private",82242,"Prof-school",15,"Never-married","Prof-specialty","Unmarried","White","Male",27828,0,45,"Germany",">50K" +36,"Private",329980,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",27828,0,40,"United-States",">50K" +51,"Self-emp-inc",54342,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",27828,0,60,"United-States",">50K" +38,"Private",125933,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","White","Male",27828,0,45,"United-States",">50K" +36,"Self-emp-inc",184456,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",27828,0,55,"United-States",">50K" +41,"Private",106679,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",27828,0,50,"United-States",">50K" +47,"Private",304857,"Masters",14,"Separated","Tech-support","Not-in-family","White","Male",27828,0,40,"United-States",">50K" +64,"Private",218490,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",27828,0,55,"United-States",">50K" +64,"Private",66634,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Male",27828,0,50,"United-States",">50K" +51,"Private",673764,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",27828,0,40,"United-States",">50K" +54,"Self-emp-not-inc",28186,"Bachelors",13,"Divorced","Farming-fishing","Not-in-family","White","Male",27828,0,50,"United-States",">50K" +53,"Self-emp-not-inc",137547,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",27828,0,40,"Philippines",">50K" +46,"Private",295566,"Doctorate",16,"Divorced","Prof-specialty","Unmarried","White","Female",25236,0,65,"United-States",">50K" +51,"Self-emp-not-inc",165001,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Male",25236,0,50,"United-States",">50K" +45,"Self-emp-inc",191776,"Masters",14,"Divorced","Sales","Unmarried","White","Female",25236,0,42,"United-States",">50K" +43,"State-gov",261929,"Doctorate",16,"Married-spouse-absent","Prof-specialty","Unmarried","White","Male",25236,0,64,"United-States",">50K" +59,"State-gov",398626,"Doctorate",16,"Divorced","Prof-specialty","Unmarried","White","Male",25236,0,45,"United-States",">50K" +37,"Private",270059,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",25236,0,25,"United-States",">50K" +45,"Self-emp-inc",208802,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Male",25236,0,36,"United-States",">50K" +45,"State-gov",190406,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","Black","Male",25236,0,36,"United-States",">50K" +32,"Private",170154,"Assoc-acdm",12,"Separated","Exec-managerial","Unmarried","White","Female",25236,0,50,"United-States",">50K" +36,"Self-emp-not-inc",112497,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Male",25236,0,40,"United-States",">50K" +47,"Private",97883,"Bachelors",13,"Widowed","Priv-house-serv","Unmarried","White","Female",25236,0,35,"United-States",">50K" +75,"?",111177,"Bachelors",13,"Widowed","?","Not-in-family","White","Female",25124,0,16,"United-States",">50K" +73,"Private",183213,"Assoc-voc",11,"Widowed","Prof-specialty","Not-in-family","White","Male",25124,0,60,"United-States",">50K" +65,"?",224472,"Prof-school",15,"Never-married","?","Not-in-family","White","Male",25124,0,80,"United-States",">50K" +68,"Self-emp-inc",52052,"Assoc-voc",11,"Widowed","Sales","Not-in-family","White","Female",25124,0,50,"United-States",">50K" +61,"Self-emp-not-inc",32423,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Wife","White","Female",22040,0,40,"United-States","<=50K" +67,"Private",231559,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",20051,0,48,"United-States",">50K" +65,"Private",198766,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",20051,0,40,"United-States",">50K" +63,"Self-emp-not-inc",167501,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",20051,0,10,"United-States",">50K" +64,"Self-emp-inc",132832,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",20051,0,40,"?",">50K" +90,"Local-gov",227796,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",20051,0,60,"United-States",">50K" +79,"Private",120707,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",20051,0,35,"El-Salvador",">50K" +67,"Private",195161,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",20051,0,60,"United-States",">50K" +90,"Private",87372,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",20051,0,72,"United-States",">50K" +68,"Private",193666,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",20051,0,55,"United-States",">50K" +65,"Private",154171,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",20051,0,60,"United-States",">50K" +68,"?",146645,"Doctorate",16,"Married-civ-spouse","?","Husband","White","Male",20051,0,50,"United-States",">50K" +62,"Self-emp-inc",118725,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",20051,0,72,"United-States",">50K" +69,"Private",36956,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",20051,0,50,"United-States",">50K" +67,"Self-emp-not-inc",106143,"Doctorate",16,"Married-civ-spouse","Sales","Husband","White","Male",20051,0,40,"United-States",">50K" +66,"Private",169804,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",20051,0,40,"United-States",">50K" +67,"?",129188,"Doctorate",16,"Married-civ-spouse","?","Husband","White","Male",20051,0,5,"United-States",">50K" +70,"Self-emp-not-inc",36311,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",20051,0,35,"United-States",">50K" +68,"Self-emp-not-inc",133736,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",20051,0,40,"United-States",">50K" +68,"Local-gov",242095,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",20051,0,40,"United-States",">50K" +74,"Self-emp-inc",228075,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",20051,0,25,"United-States",">50K" +71,"Federal-gov",422149,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",20051,0,40,"United-States",">50K" +67,"Self-emp-inc",171564,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",20051,0,30,"England",">50K" +68,"Private",195868,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",20051,0,40,"United-States",">50K" +77,"Self-emp-inc",84979,"Doctorate",16,"Married-civ-spouse","Farming-fishing","Husband","White","Male",20051,0,40,"United-States",">50K" +71,"Self-emp-inc",118119,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",20051,0,50,"United-States",">50K" +76,"Private",199949,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",20051,0,50,"United-States",">50K" +83,"Self-emp-inc",240150,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",20051,0,50,"United-States",">50K" +68,"Private",117236,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",20051,0,45,"United-States",">50K" +79,"?",76641,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",20051,0,40,"Poland",">50K" +69,"Self-emp-not-inc",58213,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",20051,0,45,"United-States",">50K" +66,"Local-gov",174486,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",20051,0,35,"Jamaica",">50K" +73,"Private",148003,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",20051,0,36,"United-States",">50K" +67,"Self-emp-not-inc",431426,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",20051,0,4,"United-States",">50K" +66,"Private",113323,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",20051,0,40,"United-States",">50K" +66,"State-gov",162945,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",20051,0,55,"United-States",">50K" +67,"Self-emp-not-inc",191380,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",20051,0,25,"United-States",">50K" +67,"Self-emp-inc",182581,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",20051,0,20,"United-States",">50K" +79,"Self-emp-inc",97082,"12th",8,"Widowed","Sales","Not-in-family","White","Male",18481,0,45,"United-States",">50K" +67,"Self-emp-not-inc",148690,"Masters",14,"Widowed","Prof-specialty","Not-in-family","White","Male",18481,0,2,"United-States",">50K" +74,"Private",129879,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",15831,0,40,"United-States",">50K" +67,"Self-emp-inc",411007,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",15831,0,40,"United-States",">50K" +67,"Local-gov",103315,"Masters",14,"Never-married","Exec-managerial","Other-relative","White","Female",15831,0,72,"United-States",">50K" +67,"Private",224984,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",15831,0,16,"Germany",">50K" +69,"Private",182862,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",15831,0,40,"United-States",">50K" +74,"Self-emp-not-inc",199136,"Bachelors",13,"Widowed","Craft-repair","Not-in-family","White","Male",15831,0,8,"Germany",">50K" +44,"Private",198282,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +58,"Self-emp-inc",210563,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",15024,0,35,"United-States",">50K" +57,"Federal-gov",425161,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,40,"United-States",">50K" +46,"Private",188386,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +38,"Private",91039,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,60,"United-States",">50K" +38,"Self-emp-inc",99146,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,80,"United-States",">50K" +46,"Private",102388,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,45,"United-States",">50K" +43,"Private",154374,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,60,"United-States",">50K" +33,"Private",175697,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +39,"Private",202027,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,45,"United-States",">50K" +39,"Self-emp-inc",329980,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +54,"Self-emp-not-inc",123011,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,52,"United-States",">50K" +33,"Private",354573,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,44,"United-States",">50K" +54,"Private",99185,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,45,"United-States",">50K" +51,"Self-emp-inc",229465,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +47,"Self-emp-not-inc",370119,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"United-States",">50K" +53,"State-gov",156877,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",15024,0,35,"United-States",">50K" +64,"Self-emp-inc",179436,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,55,"United-States",">50K" +30,"Self-emp-not-inc",167990,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,65,"United-States",">50K" +55,"Private",98361,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"?",">50K" +52,"Private",147876,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",15024,0,60,"United-States",">50K" +48,"Private",126754,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +44,"Private",120277,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"Italy",">50K" +53,"State-gov",281590,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",15024,0,40,"United-States",">50K" +64,"Self-emp-not-inc",134960,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,35,"United-States",">50K" +39,"Private",79331,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",15024,0,40,"United-States",">50K" +50,"Private",147629,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,45,"United-States",">50K" +57,"Self-emp-inc",119253,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,65,"United-States",">50K" +59,"Self-emp-not-inc",174056,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,40,"United-States",">50K" +44,"Private",198282,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +37,"Private",82521,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +56,"Self-emp-inc",211804,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"United-States",">50K" +64,"Private",319371,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +32,"Private",194426,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",15024,0,40,"United-States",">50K" +39,"Self-emp-inc",122742,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,55,"United-States",">50K" +57,"Self-emp-inc",172654,"Prof-school",15,"Married-civ-spouse","Transport-moving","Husband","White","Male",15024,0,50,"United-States",">50K" +35,"Private",376455,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +51,"Self-emp-not-inc",145409,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"United-States",">50K" +44,"Private",198316,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +57,"Self-emp-not-inc",225334,"Prof-school",15,"Married-civ-spouse","Sales","Wife","White","Female",15024,0,35,"United-States",">50K" +47,"Private",151267,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","Black","Female",15024,0,40,"United-States",">50K" +51,"Private",293196,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,60,"Iran",">50K" +50,"Self-emp-not-inc",44368,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,55,"El-Salvador",">50K" +52,"Private",338816,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,45,"United-States",">50K" +47,"Self-emp-inc",214169,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",15024,0,40,"United-States",">50K" +34,"Private",30497,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +37,"Self-emp-inc",291518,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,55,"United-States",">50K" +49,"Self-emp-inc",362654,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +54,"Private",22743,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",15024,0,60,"United-States",">50K" +39,"Private",191807,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"United-States",">50K" +39,"Self-emp-not-inc",126569,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,60,"United-States",">50K" +32,"Private",312667,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +34,"Self-emp-inc",186824,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +53,"Private",114758,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,65,"United-States",">50K" +53,"Federal-gov",199720,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,60,"Germany",">50K" +52,"Self-emp-inc",100506,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"United-States",">50K" +37,"Local-gov",233825,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,50,"United-States",">50K" +53,"Private",424079,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,55,"United-States",">50K" +37,"Private",148015,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",15024,0,40,"United-States",">50K" +47,"Private",124973,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +58,"Self-emp-not-inc",93664,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +39,"Private",173175,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +46,"Private",155659,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,45,"United-States",">50K" +49,"Private",65087,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +46,"Private",117849,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,40,"United-States",">50K" +32,"Private",207668,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,45,"United-States",">50K" +50,"Self-emp-inc",127315,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +61,"Private",85548,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",15024,0,18,"United-States",">50K" +33,"Private",56701,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,75,"United-States",">50K" +31,"Local-gov",381153,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",15024,0,56,"United-States",">50K" +39,"Self-emp-not-inc",109766,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +45,"Self-emp-inc",170871,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,55,"United-States",">50K" +35,"Private",99357,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,50,"United-States",">50K" +36,"Private",261382,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,45,"United-States",">50K" +40,"Self-emp-inc",157240,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",15024,0,30,"Iran",">50K" +47,"Self-emp-not-inc",168109,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",15024,0,50,"United-States",">50K" +41,"Private",280167,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,70,"United-States",">50K" +52,"Self-emp-inc",173754,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,60,"United-States",">50K" +43,"Private",303051,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +55,"Private",116878,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,30,"United-States",">50K" +39,"Private",179668,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",15024,0,40,"United-States",">50K" +61,"Private",176839,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +46,"Private",360096,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +49,"Private",198759,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,60,"United-States",">50K" +52,"Private",145409,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",15024,0,60,"Canada",">50K" +58,"Private",306233,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,40,"United-States",">50K" +49,"Local-gov",149210,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Black","Male",15024,0,40,"United-States",">50K" +46,"Private",219021,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",15024,0,44,"United-States",">50K" +47,"Self-emp-inc",332355,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +47,"Self-emp-inc",173783,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,60,"United-States",">50K" +36,"Local-gov",61778,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +63,"Self-emp-inc",137940,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +37,"Private",108140,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,45,"United-States",">50K" +46,"Private",328216,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +39,"Private",187098,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Wife","White","Female",15024,0,47,"United-States",">50K" +53,"Private",151580,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +30,"Private",154950,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +32,"Private",193042,"Prof-school",15,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,60,"United-States",">50K" +47,"State-gov",120429,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +55,"Private",229029,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,48,"United-States",">50K" +57,"Private",200453,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,40,"United-States",">50K" +39,"Private",70995,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",15024,0,99,"United-States",">50K" +37,"Private",186934,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,60,"United-States",">50K" +32,"Private",167531,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","Asian-Pac-Islander","Female",15024,0,50,"United-States",">50K" +50,"Private",34832,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",15024,0,40,"United-States",">50K" +41,"Private",35166,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +43,"Private",352005,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,45,"United-States",">50K" +45,"Private",205100,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +40,"State-gov",199381,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,37,"United-States",">50K" +55,"Private",282023,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"United-States",">50K" +59,"Private",271571,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,50,"United-States",">50K" +63,"Private",213945,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,40,"Iran",">50K" +34,"Private",187215,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,36,"United-States",">50K" +50,"Local-gov",259377,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,40,"United-States",">50K" +51,"Self-emp-inc",167793,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +36,"Private",237943,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +54,"Private",135803,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",15024,0,60,"South",">50K" +42,"Private",340234,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",15024,0,40,"United-States",">50K" +40,"Private",226902,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +42,"Local-gov",121998,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +36,"Private",198237,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +32,"Self-emp-inc",78530,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +53,"State-gov",43952,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,38,"United-States",">50K" +46,"Self-emp-not-inc",43348,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,55,"United-States",">50K" +52,"Self-emp-inc",254211,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,60,"United-States",">50K" +30,"Self-emp-inc",321990,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"?",">50K" +33,"Private",144949,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +32,"Private",137076,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +43,"Private",194726,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,55,"United-States",">50K" +50,"Private",89041,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,50,"United-States",">50K" +38,"Private",409604,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +43,"State-gov",139734,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +53,"Private",30244,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +30,"Private",340917,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +59,"Self-emp-not-inc",201263,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,55,"United-States",">50K" +44,"Private",116825,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,80,"United-States",">50K" +41,"Private",101593,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +38,"?",70282,"Masters",14,"Married-civ-spouse","?","Wife","Black","Female",15024,0,2,"United-States",">50K" +60,"Private",103344,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,40,"United-States",">50K" +42,"Self-emp-not-inc",336513,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,60,"United-States",">50K" +42,"Self-emp-not-inc",24763,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +48,"Private",38950,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +55,"Private",199067,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,42,"United-States",">50K" +49,"State-gov",391585,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +50,"Private",205803,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,40,"United-States",">50K" +55,"Private",182460,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,35,"United-States",">50K" +44,"Private",267717,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,45,"United-States",">50K" +46,"Private",330087,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,45,"United-States",">50K" +40,"Private",88909,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +39,"Self-emp-not-inc",343476,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"Japan",">50K" +30,"Local-gov",182926,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",15024,0,40,"United-States",">50K" +44,"Private",109912,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Wife","White","Female",15024,0,32,"United-States",">50K" +60,"Self-emp-inc",376133,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",15024,0,15,"United-States",">50K" +60,"Private",142494,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +36,"Private",184112,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,45,"United-States",">50K" +36,"Self-emp-inc",77146,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,45,"United-States",">50K" +39,"Private",322143,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",15024,0,70,"United-States",">50K" +40,"Self-emp-inc",182437,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"United-States",">50K" +51,"Private",90363,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",15024,0,40,"United-States",">50K" +45,"Private",101452,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"England",">50K" +51,"Private",338620,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +47,"Private",149700,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",15024,0,40,"United-States",">50K" +59,"Private",153484,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,50,"United-States",">50K" +47,"Private",162741,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",15024,0,40,"United-States",">50K" +46,"Federal-gov",102308,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +35,"Private",81232,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"United-States",">50K" +39,"Private",33983,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",15024,0,40,"United-States",">50K" +52,"Self-emp-not-inc",194995,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,55,"United-States",">50K" +32,"Federal-gov",42900,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +40,"Private",166662,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,45,"United-States",">50K" +61,"Private",170262,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",15024,0,38,"United-States",">50K" +57,"Private",127728,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +48,"State-gov",212954,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +51,"Private",221672,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"United-States",">50K" +34,"Self-emp-not-inc",198664,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",15024,0,70,"South",">50K" +62,"Private",109190,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +42,"Private",252518,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +59,"Private",165922,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +57,"Self-emp-inc",123053,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",15024,0,50,"India",">50K" +59,"Self-emp-inc",31359,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,80,"United-States",">50K" +50,"Private",98975,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +61,"Private",119684,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,20,"United-States",">50K" +44,"Private",181762,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",15024,0,55,"United-States",">50K" +41,"Private",150755,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"Canada",">50K" +43,"Private",345789,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,50,"United-States",">50K" +46,"Private",102569,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,65,"United-States",">50K" +42,"Private",119359,"Prof-school",15,"Married-civ-spouse","Sales","Wife","Amer-Indian-Eskimo","Female",15024,0,40,"South",">50K" +37,"Private",359001,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",15024,0,50,"United-States",">50K" +46,"Private",393715,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +46,"Self-emp-not-inc",366089,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +47,"Private",61885,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +46,"Private",121124,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +59,"Self-emp-inc",169982,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +43,"State-gov",506329,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",15024,0,40,"?",">50K" +48,"Private",182541,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,45,"United-States",">50K" +47,"Private",323798,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,55,"United-States",">50K" +43,"Private",130126,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +44,"Local-gov",189956,"Bachelors",13,"Married-civ-spouse","Protective-serv","Wife","Black","Female",15024,0,40,"United-States",">50K" +45,"Private",266860,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +43,"Local-gov",188291,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,45,"United-States",">50K" +40,"Private",99604,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,24,"United-States",">50K" +50,"Private",204447,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,65,"United-States",">50K" +52,"Self-emp-inc",114758,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"United-States",">50K" +52,"?",92968,"Masters",14,"Married-civ-spouse","?","Wife","White","Female",15024,0,40,"United-States",">50K" +40,"Private",198873,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,30,"United-States",">50K" +44,"Private",148138,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",15024,0,40,"Japan",">50K" +47,"Private",355320,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +58,"Self-emp-inc",89922,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +50,"Private",138852,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +54,"Self-emp-inc",129432,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +50,"Private",145409,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +43,"Private",64631,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +52,"Private",186303,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,55,"Canada",">50K" +44,"Self-emp-not-inc",172479,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",15024,0,60,"United-States",">50K" +58,"Private",147707,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +45,"Private",148171,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,40,"United-States",">50K" +30,"Private",196385,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,35,"United-States",">50K" +40,"Self-emp-inc",191429,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +49,"Self-emp-inc",58359,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +52,"Self-emp-inc",89041,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +35,"Private",186183,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",15024,0,80,"United-States",">50K" +49,"Self-emp-inc",191277,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +50,"Private",164198,"Assoc-acdm",12,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",15024,0,45,"United-States",">50K" +31,"Private",167725,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",15024,0,48,"Philippines",">50K" +53,"Local-gov",283602,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,40,"United-States",">50K" +34,"Private",203488,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,40,"United-States",">50K" +19,"?",200790,"12th",8,"Married-civ-spouse","?","Other-relative","White","Female",15024,0,40,"United-States",">50K" +46,"Federal-gov",20956,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +44,"State-gov",141858,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,75,"United-States",">50K" +45,"Private",148995,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,40,"United-States",">50K" +50,"Private",43764,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +49,"Self-emp-not-inc",181307,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,65,"United-States",">50K" +49,"?",271346,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",15024,0,60,"United-States",">50K" +41,"Self-emp-not-inc",174395,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,55,"United-States",">50K" +58,"Private",146477,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"Greece",">50K" +44,"Self-emp-inc",357679,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",15024,0,65,"United-States",">50K" +36,"Self-emp-inc",306156,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,60,"United-States",">50K" +57,"Federal-gov",42298,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",15024,0,40,"United-States",">50K" +39,"Private",375452,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Wife","White","Female",15024,0,48,"United-States",">50K" +55,"Private",98361,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,55,"United-States",">50K" +42,"Private",98211,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,45,"United-States",">50K" +47,"Self-emp-inc",215620,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,55,"United-States",">50K" +55,"State-gov",296991,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +45,"Private",390368,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",15024,0,99,"United-States",">50K" +32,"Private",447066,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Black","Male",15024,0,50,"United-States",">50K" +58,"Federal-gov",200042,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +31,"Private",352465,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +49,"Private",309033,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,60,"United-States",">50K" +52,"Private",284329,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +28,"Private",312372,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",15024,0,40,"United-States",">50K" +55,"Federal-gov",305850,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +42,"Self-emp-inc",277488,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,65,"United-States",">50K" +46,"Private",273575,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",15024,0,40,"United-States",">50K" +40,"Self-emp-not-inc",237293,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,40,"United-States",">50K" +45,"Self-emp-not-inc",176814,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +51,"Local-gov",133336,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +42,"Private",187720,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"?",">50K" +48,"Self-emp-inc",54190,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +53,"Self-emp-inc",134793,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +46,"Local-gov",121124,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",15024,0,40,"United-States",">50K" +41,"Self-emp-inc",236021,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +42,"State-gov",190044,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +47,"Private",120781,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",15024,0,40,"?",">50K" +51,"Private",215404,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",15024,0,40,"United-States",">50K" +38,"Private",117312,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",15024,0,40,"United-States",">50K" +52,"Self-emp-inc",234286,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +50,"Self-emp-inc",283676,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,60,"United-States",">50K" +45,"Private",102308,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +45,"Self-emp-not-inc",210364,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,80,"United-States",">50K" +49,"Self-emp-not-inc",219718,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,40,"United-States",">50K" +54,"Private",104501,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,40,"United-States",">50K" +51,"Self-emp-inc",100029,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +56,"Self-emp-inc",109856,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +58,"Self-emp-not-inc",248841,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,40,"United-States",">50K" +43,"Self-emp-inc",117158,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,60,"United-States",">50K" +46,"Private",110171,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +43,"Private",212894,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +59,"Private",354037,"Prof-school",15,"Married-civ-spouse","Transport-moving","Husband","Black","Male",15024,0,50,"United-States",">50K" +47,"Local-gov",149700,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,35,"United-States",">50K" +33,"Private",182926,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +56,"Local-gov",381965,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +41,"Private",222596,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,45,"United-States",">50K" +64,"Federal-gov",388594,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,45,"?",">50K" +43,"Private",183273,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",15024,0,32,"United-States",">50K" +47,"Private",102628,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,55,"United-States",">50K" +42,"Private",227065,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,32,"United-States",">50K" +48,"State-gov",171926,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +61,"Private",96660,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",15024,0,34,"United-States",">50K" +60,"Private",93997,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,45,"United-States",">50K" +38,"Private",38312,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,65,"United-States",">50K" +28,"Private",285294,"Bachelors",13,"Married-civ-spouse","Sales","Wife","Black","Female",15024,0,45,"United-States",">50K" +54,"Private",182187,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","Black","Male",15024,0,38,"Jamaica",">50K" +48,"Private",207277,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +31,"Private",187560,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +38,"Private",114591,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,40,"United-States",">50K" +32,"Private",126132,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +42,"Private",383493,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +41,"Self-emp-not-inc",153132,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +40,"Private",287008,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,55,"Germany",">50K" +44,"Local-gov",136986,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,35,"United-States",">50K" +57,"Self-emp-inc",127728,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,60,"United-States",">50K" +34,"Private",177437,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,45,"United-States",">50K" +52,"Private",145166,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,55,"United-States",">50K" +37,"Private",19899,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,45,"United-States",">50K" +56,"Private",367984,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +38,"Private",172538,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +47,"Private",264052,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +53,"Private",73134,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,60,"United-States",">50K" +37,"Private",588003,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +31,"Private",197886,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,45,"United-States",">50K" +47,"Private",121124,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",15024,0,50,"United-States",">50K" +46,"Private",58683,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,55,"United-States",">50K" +55,"Private",175071,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",15024,0,40,"United-States",">50K" +43,"Private",180599,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,60,"United-States",">50K" +46,"Self-emp-inc",192779,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,60,"United-States",">50K" +45,"Private",30457,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +43,"Self-emp-inc",130126,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,45,"United-States",">50K" +61,"Private",86067,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,40,"United-States",">50K" +49,"Private",187370,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,50,"United-States",">50K" +39,"Private",177154,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"United-States",">50K" +54,"Private",36480,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,50,"United-States",">50K" +62,"Private",244087,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,50,"United-States",">50K" +51,"Private",392668,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,84,"United-States",">50K" +40,"Private",25005,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,99,"United-States",">50K" +46,"Self-emp-inc",320124,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","Amer-Indian-Eskimo","Female",15024,0,40,"United-States",">50K" +38,"Private",333651,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,70,"United-States",">50K" +57,"Private",199847,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +39,"Private",110426,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",15024,0,45,"United-States",">50K" +28,"Private",119287,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",15024,0,28,"United-States",">50K" +36,"State-gov",747719,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",15024,0,50,"United-States",">50K" +63,"Private",294009,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,45,"United-States",">50K" +41,"Private",359696,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",15024,0,60,"United-States",">50K" +56,"Private",122390,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",15024,0,40,"United-States",">50K" +51,"Self-emp-inc",338260,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,60,"United-States",">50K" +45,"Self-emp-inc",181307,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,43,"United-States",">50K" +43,"Local-gov",153132,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +41,"Private",287306,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,60,"United-States",">50K" +44,"Private",201723,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,45,"United-States",">50K" +30,"Private",341051,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +42,"Private",176063,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,55,"United-States",">50K" +39,"Private",174242,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,60,"United-States",">50K" +46,"State-gov",250821,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",15024,0,40,"United-States",">50K" +47,"Self-emp-not-inc",242391,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +51,"Federal-gov",223206,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",15024,0,40,"Vietnam",">50K" +41,"Private",122215,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,40,"United-States",">50K" +37,"Private",121521,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",15024,0,45,"United-States",">50K" +52,"Self-emp-inc",287927,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",15024,0,40,"United-States",">50K" +45,"Private",214627,"Doctorate",16,"Widowed","Prof-specialty","Unmarried","White","Male",15020,0,40,"Iran",">50K" +52,"Private",99736,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Male",15020,0,50,"United-States",">50K" +39,"Private",150061,"Masters",14,"Divorced","Exec-managerial","Unmarried","Black","Female",15020,0,60,"United-States",">50K" +62,"Private",195343,"Doctorate",16,"Divorced","Prof-specialty","Unmarried","White","Male",15020,0,50,"United-States",">50K" +38,"Private",139180,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","Black","Female",15020,0,45,"United-States",">50K" +44,"Private",343591,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Female",14344,0,40,"United-States",">50K" +31,"Private",220066,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",14344,0,50,"United-States",">50K" +31,"Private",340917,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",14344,0,40,"United-States",">50K" +45,"Private",543922,"Masters",14,"Divorced","Transport-moving","Not-in-family","White","Male",14344,0,48,"United-States",">50K" +37,"Private",538443,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",14344,0,40,"United-States",">50K" +53,"Local-gov",221722,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",14344,0,50,"United-States",">50K" +23,"Private",106957,"11th",7,"Never-married","Craft-repair","Own-child","Asian-Pac-Islander","Male",14344,0,40,"Vietnam",">50K" +53,"Private",171924,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",14344,0,55,"United-States",">50K" +43,"Private",170525,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",14344,0,40,"United-States",">50K" +44,"Self-emp-not-inc",274562,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",14344,0,40,"United-States",">50K" +39,"Private",174924,"HS-grad",9,"Separated","Exec-managerial","Not-in-family","White","Male",14344,0,40,"United-States",">50K" +49,"Private",149049,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",14344,0,45,"United-States",">50K" +35,"Private",252897,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",14344,0,40,"United-States",">50K" +41,"State-gov",108945,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Female",14344,0,40,"United-States",">50K" +35,"Private",127306,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",14344,0,40,"United-States",">50K" +38,"Private",217349,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Female",14344,0,40,"United-States",">50K" +29,"Private",157612,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",14344,0,40,"United-States",">50K" +22,"Private",233955,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Amer-Indian-Eskimo","Female",14344,0,40,"United-States",">50K" +54,"Private",288992,"10th",6,"Divorced","Prof-specialty","Unmarried","White","Male",14344,0,68,"United-States",">50K" +36,"Private",337039,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","Black","Male",14344,0,40,"England",">50K" +58,"Private",234213,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",14344,0,48,"United-States",">50K" +24,"Local-gov",452640,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",14344,0,50,"United-States",">50K" +52,"Private",146567,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","Black","Male",14344,0,40,"United-States",">50K" +29,"Private",152461,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Female",14344,0,50,"United-States",">50K" +29,"Private",176037,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","Black","Male",14344,0,40,"United-States",">50K" +44,"Private",147110,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Male",14344,0,40,"United-States",">50K" +31,"Private",45781,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",14084,0,50,"United-States",">50K" +40,"Federal-gov",56795,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",14084,0,55,"United-States",">50K" +42,"Private",151408,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",14084,0,50,"United-States",">50K" +44,"Private",75227,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",14084,0,40,"United-States",">50K" +55,"Private",163083,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","White","Male",14084,0,45,"United-States",">50K" +30,"Local-gov",125159,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",14084,0,45,"?",">50K" +52,"Private",218550,"Some-college",10,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Female",14084,0,16,"United-States",">50K" +36,"Private",297449,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",14084,0,40,"United-States",">50K" +42,"Federal-gov",170230,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",14084,0,60,"United-States",">50K" +31,"Private",345122,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",14084,0,50,"United-States",">50K" +51,"Private",196501,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",14084,0,50,"United-States",">50K" +58,"Private",150560,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",14084,0,40,"United-States",">50K" +28,"Private",34335,"HS-grad",9,"Divorced","Sales","Not-in-family","Amer-Indian-Eskimo","Male",14084,0,40,"United-States",">50K" +56,"Private",295067,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",14084,0,45,"United-States",">50K" +48,"Self-emp-not-inc",328606,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Male",14084,0,63,"United-States",">50K" +37,"Private",125550,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Female",14084,0,35,"United-States",">50K" +36,"Private",111499,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",14084,0,40,"United-States",">50K" +37,"Self-emp-not-inc",164526,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",14084,0,45,"United-States",">50K" +54,"Private",155233,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",14084,0,40,"United-States",">50K" +40,"Private",105794,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",14084,0,50,"United-States",">50K" +34,"Private",160261,"HS-grad",9,"Never-married","Tech-support","Own-child","Asian-Pac-Islander","Male",14084,0,35,"China",">50K" +59,"Private",140569,"Some-college",10,"Separated","Sales","Not-in-family","White","Male",14084,0,60,"United-States",">50K" +31,"Private",72630,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",14084,0,50,"United-States",">50K" +49,"Private",153536,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",14084,0,44,"United-States",">50K" +55,"Private",436861,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",14084,0,40,"United-States",">50K" +53,"Self-emp-inc",42924,"Doctorate",16,"Divorced","Exec-managerial","Not-in-family","White","Male",14084,0,50,"United-States",">50K" +33,"Private",168981,"Masters",14,"Divorced","Exec-managerial","Own-child","White","Female",14084,0,50,"United-States",">50K" +40,"Private",175935,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",14084,0,40,"United-States",">50K" +48,"?",175653,"Assoc-acdm",12,"Divorced","?","Not-in-family","White","Female",14084,0,40,"United-States",">50K" +45,"Self-emp-not-inc",319122,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",14084,0,45,"United-States",">50K" +49,"Self-emp-not-inc",107597,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",14084,0,30,"United-States",">50K" +31,"Private",178623,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Female",14084,0,60,"United-States",">50K" +37,"Private",82576,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",14084,0,36,"United-States",">50K" +39,"Private",347960,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",14084,0,35,"United-States",">50K" +47,"Private",160187,"HS-grad",9,"Separated","Prof-specialty","Other-relative","Black","Female",14084,0,38,"United-States",">50K" +62,"State-gov",202056,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",14084,0,40,"United-States",">50K" +51,"Self-emp-inc",98642,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",14084,0,40,"United-States",">50K" +63,"Self-emp-inc",38472,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",14084,0,60,"United-States",">50K" +44,"Private",110396,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",14084,0,56,"United-States",">50K" +32,"Private",167990,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",14084,0,40,"United-States",">50K" +58,"Federal-gov",72998,"11th",7,"Divorced","Craft-repair","Not-in-family","Black","Female",14084,0,40,"United-States",">50K" +40,"Private",121956,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",13550,0,40,"Cambodia",">50K" +53,"Private",283602,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",13550,0,43,"United-States",">50K" +35,"Private",188069,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",13550,0,55,"?",">50K" +24,"Self-emp-inc",493034,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",13550,0,50,"United-States",">50K" +41,"Private",116493,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",13550,0,44,"United-States",">50K" +26,"Private",164488,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",13550,0,50,"United-States",">50K" +22,"Private",100345,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",13550,0,55,"United-States",">50K" +32,"Private",252752,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",13550,0,60,"United-States",">50K" +36,"Private",201769,"11th",7,"Never-married","Protective-serv","Not-in-family","Black","Male",13550,0,40,"United-States",">50K" +31,"Private",158162,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",13550,0,50,"United-States",">50K" +36,"Private",175360,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Male",13550,0,50,"United-States",">50K" +32,"Private",95885,"11th",7,"Never-married","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",13550,0,60,"United-States",">50K" +32,"Private",133861,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",13550,0,48,"United-States",">50K" +43,"Federal-gov",105936,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",13550,0,40,"United-States",">50K" +36,"Federal-gov",192443,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Male",13550,0,40,"United-States",">50K" +30,"Private",347166,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",13550,0,45,"United-States",">50K" +45,"Private",229967,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",13550,0,50,"United-States",">50K" +39,"Private",191227,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",13550,0,50,"United-States",">50K" +27,"Private",186454,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",13550,0,40,"United-States",">50K" +25,"Self-emp-not-inc",368115,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",13550,0,35,"United-States",">50K" +39,"Private",209867,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",13550,0,45,"United-States",">50K" +29,"Private",124680,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",13550,0,35,"United-States",">50K" +32,"Private",159442,"Prof-school",15,"Never-married","Sales","Not-in-family","White","Female",13550,0,50,"United-States",">50K" +55,"?",141807,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",13550,0,40,"United-States",">50K" +35,"Private",589809,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",13550,0,60,"United-States",">50K" +27,"Private",388998,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",13550,0,46,"United-States",">50K" +44,"Federal-gov",281739,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",13550,0,50,"United-States",">50K" +65,"Private",242580,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",11678,0,50,"United-States",">50K" +71,"Private",182395,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",11678,0,45,"United-States",">50K" +71,"Self-emp-not-inc",143437,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",10605,0,40,"United-States",">50K" +65,"Private",350498,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",10605,0,20,"United-States",">50K" +63,"Self-emp-not-inc",298249,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",10605,0,40,"United-States",">50K" +80,"?",29020,"Prof-school",15,"Married-civ-spouse","?","Husband","White","Male",10605,0,10,"United-States",">50K" +67,"Private",279980,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",10605,0,10,"United-States",">50K" +66,"Self-emp-inc",197816,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",10605,0,40,"United-States",">50K" +65,"?",249043,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",10605,0,40,"United-States",">50K" +69,"?",254834,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",10605,0,10,"United-States",">50K" +65,"Self-emp-not-inc",139960,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",10605,0,60,"United-States",">50K" +59,"State-gov",349910,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",10605,0,50,"United-States",">50K" +68,"Self-emp-inc",182131,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",10605,0,20,"United-States",">50K" +67,"Self-emp-not-inc",217892,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",10605,0,35,"United-States",">50K" +62,"Self-emp-not-inc",82388,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",10566,0,40,"United-States","<=50K" +90,"Self-emp-not-inc",155981,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",10566,0,50,"United-States","<=50K" +63,"Private",108097,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",10566,0,45,"United-States","<=50K" +64,"Private",292639,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",10566,0,35,"United-States","<=50K" +70,"Self-emp-inc",379819,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",10566,0,40,"United-States","<=50K" +67,"Private",257557,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","Black","Male",10566,0,40,"United-States","<=50K" +39,"Private",128715,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",10520,0,40,"United-States",">50K" +40,"Private",163215,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",10520,0,40,"United-States",">50K" +45,"Private",67716,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",10520,0,48,"United-States",">50K" +51,"Private",159910,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","Black","Male",10520,0,40,"United-States",">50K" +45,"Private",154430,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","White","Female",10520,0,50,"United-States",">50K" +54,"Self-emp-not-inc",278230,"Some-college",10,"Divorced","Farming-fishing","Unmarried","White","Female",10520,0,30,"United-States",">50K" +36,"Self-emp-not-inc",164526,"Masters",14,"Never-married","Sales","Not-in-family","White","Male",10520,0,45,"United-States",">50K" +48,"Federal-gov",205707,"Masters",14,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Female",10520,0,50,"United-States",">50K" +33,"State-gov",208785,"Some-college",10,"Separated","Prof-specialty","Not-in-family","White","Male",10520,0,40,"United-States",">50K" +37,"Private",361888,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",10520,0,40,"United-States",">50K" +45,"Private",89028,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",10520,0,40,"United-States",">50K" +44,"Local-gov",177240,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",10520,0,40,"United-States",">50K" +38,"Private",179117,"Assoc-acdm",12,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",10520,0,50,"United-States",">50K" +38,"Private",255941,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",10520,0,50,"United-States",">50K" +47,"Self-emp-not-inc",112200,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Black","Male",10520,0,45,"United-States",">50K" +29,"Private",87905,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",10520,0,40,"United-States",">50K" +43,"Local-gov",209544,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",10520,0,50,"United-States",">50K" +44,"Private",203761,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",10520,0,40,"United-States",">50K" +62,"Private",103344,"Bachelors",13,"Widowed","Exec-managerial","Not-in-family","White","Male",10520,0,50,"United-States",">50K" +28,"Private",119793,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Male",10520,0,50,"United-States",">50K" +42,"Private",54202,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",10520,0,50,"United-States",">50K" +50,"Private",145333,"Doctorate",16,"Divorced","Prof-specialty","Other-relative","White","Male",10520,0,50,"United-States",">50K" +53,"Local-gov",216691,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Female",10520,0,40,"United-States",">50K" +32,"Private",317378,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",10520,0,40,"United-States",">50K" +28,"Private",378460,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",10520,0,60,"United-States",">50K" +26,"Private",102476,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",10520,0,64,"United-States",">50K" +27,"Private",128730,"Assoc-voc",11,"Never-married","Exec-managerial","Not-in-family","White","Male",10520,0,65,"Greece",">50K" +23,"State-gov",287988,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",10520,0,40,"United-States",">50K" +51,"Self-emp-inc",210736,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",10520,0,40,"United-States",">50K" +36,"Private",225516,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","Black","Male",10520,0,43,"United-States",">50K" +30,"Private",207937,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",10520,0,50,"United-States",">50K" +25,"Private",242700,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",10520,0,50,"United-States",">50K" +44,"Private",236746,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",10520,0,45,"United-States",">50K" +27,"Private",279580,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",10520,0,45,"United-States",">50K" +33,"Private",356823,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",10520,0,45,"United-States",">50K" +30,"Private",426431,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",10520,0,40,"United-States",">50K" +60,"Federal-gov",404023,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",10520,0,40,"United-States",">50K" +57,"Private",186386,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","White","Male",10520,0,40,"United-States",">50K" +28,"Private",167336,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",10520,0,40,"United-States",">50K" +62,"Local-gov",113443,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",10520,0,33,"United-States",">50K" +47,"Self-emp-not-inc",33300,"Assoc-acdm",12,"Never-married","Farming-fishing","Other-relative","White","Male",10520,0,45,"United-States",">50K" +57,"Private",132704,"Masters",14,"Separated","Prof-specialty","Not-in-family","White","Male",10520,0,32,"United-States",">50K" +35,"Private",207066,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",10520,0,45,"United-States",">50K" +48,"Local-gov",238959,"Masters",14,"Divorced","Exec-managerial","Unmarried","Black","Female",9562,0,40,"United-States",">50K" +43,"Local-gov",143828,"Masters",14,"Divorced","Prof-specialty","Unmarried","Black","Female",9562,0,40,"United-States",">50K" +27,"Self-emp-not-inc",420054,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",9562,0,50,"United-States",">50K" +42,"Private",126701,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Male",9562,0,45,"United-States",">50K" +65,"Self-emp-not-inc",118474,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",9386,0,59,"?",">50K" +67,"?",182378,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",9386,0,60,"United-States",">50K" +65,"Private",193216,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",9386,0,40,"United-States",">50K" +90,"Private",46786,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",9386,0,15,"United-States",">50K" +77,"?",28678,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",9386,0,6,"United-States",">50K" +72,"?",33608,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",9386,0,30,"United-States",">50K" +90,"Private",175491,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",9386,0,50,"Ecuador",">50K" +71,"?",35303,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",9386,0,30,"United-States",">50K" +67,"Private",264095,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",9386,0,24,"Cuba",">50K" +78,"Self-emp-inc",385242,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",9386,0,45,"United-States",">50K" +65,"Private",101104,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",9386,0,10,"United-States",">50K" +64,"Federal-gov",301383,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",9386,0,45,"United-States",">50K" +67,"Self-emp-inc",73559,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",9386,0,50,"United-States",">50K" +69,"Self-emp-not-inc",204645,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",9386,0,72,"United-States",">50K" +70,"Self-emp-not-inc",37203,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",9386,0,30,"United-States",">50K" +70,"Private",141742,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",9386,0,50,"United-States",">50K" +65,"?",191380,"10th",6,"Married-civ-spouse","?","Husband","White","Male",9386,0,50,"United-States",">50K" +61,"Federal-gov",221943,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",9386,0,40,"United-States",">50K" +69,"Self-emp-not-inc",185039,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",9386,0,12,"United-States",">50K" +69,"Private",197080,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",9386,0,60,"United-States",">50K" +69,"Private",128348,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",9386,0,50,"United-States",">50K" +57,"Private",334224,"Some-college",10,"Married-civ-spouse","Craft-repair","Wife","White","Female",9386,0,40,"United-States",">50K" +42,"Private",341204,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",8614,0,40,"United-States",">50K" +42,"Local-gov",339671,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Female",8614,0,45,"United-States",">50K" +26,"Private",122999,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +37,"State-gov",367237,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +39,"Private",315776,"Masters",14,"Never-married","Exec-managerial","Not-in-family","Black","Male",8614,0,52,"United-States",">50K" +37,"Private",269329,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Female",8614,0,45,"United-States",">50K" +39,"Private",185520,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",8614,0,40,"United-States",">50K" +53,"?",158352,"Masters",14,"Never-married","?","Not-in-family","White","Female",8614,0,35,"United-States",">50K" +22,"Private",195532,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",8614,0,40,"United-States",">50K" +35,"Self-emp-not-inc",225399,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",8614,0,40,"United-States",">50K" +28,"Private",78870,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +36,"Private",183892,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",8614,0,45,"United-States",">50K" +45,"Private",339863,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",8614,0,48,"United-States",">50K" +42,"State-gov",117583,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Female",8614,0,60,"United-States",">50K" +62,"Private",122246,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Female",8614,0,39,"United-States",">50K" +34,"Private",96483,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",8614,0,60,"United-States",">50K" +35,"Federal-gov",287031,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +51,"Self-emp-not-inc",174824,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +43,"Local-gov",209899,"Masters",14,"Never-married","Tech-support","Not-in-family","Black","Female",8614,0,47,"United-States",">50K" +37,"State-gov",191841,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",8614,0,40,"United-States",">50K" +35,"Private",117381,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",8614,0,45,"United-States",">50K" +53,"Self-emp-inc",251675,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",8614,0,50,"Cuba",">50K" +53,"Private",104461,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",8614,0,50,"Italy",">50K" +33,"Private",238381,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Male",8614,0,40,"United-States",">50K" +37,"Federal-gov",90881,"Some-college",10,"Separated","Exec-managerial","Not-in-family","White","Male",8614,0,55,"United-States",">50K" +64,"?",159938,"HS-grad",9,"Divorced","?","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +29,"Private",133696,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",8614,0,45,"United-States",">50K" +40,"Local-gov",197012,"Bachelors",13,"Divorced","Tech-support","Not-in-family","White","Female",8614,0,40,"England",">50K" +58,"Private",275859,"HS-grad",9,"Widowed","Craft-repair","Unmarried","White","Male",8614,0,52,"Mexico",">50K" +36,"Private",178815,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +48,"?",151584,"Some-college",10,"Never-married","?","Not-in-family","White","Male",8614,0,60,"United-States",">50K" +60,"Private",125019,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",8614,0,48,"United-States",">50K" +58,"Private",111625,"Bachelors",13,"Widowed","Exec-managerial","Unmarried","White","Male",8614,0,40,"United-States",">50K" +29,"Private",236436,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",8614,0,40,"United-States",">50K" +56,"Private",188856,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",8614,0,55,"United-States",">50K" +39,"Self-emp-not-inc",154641,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",8614,0,50,"United-States",">50K" +31,"Private",1033222,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +42,"Private",331651,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",8614,0,50,"United-States",">50K" +25,"Private",469572,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +40,"Local-gov",290660,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Male",8614,0,50,"United-States",">50K" +47,"Private",176893,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","Black","Male",8614,0,44,"United-States",">50K" +46,"Private",364548,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +48,"State-gov",120131,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",8614,0,40,"United-States",">50K" +44,"Private",247880,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +43,"Private",112763,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",8614,0,43,"United-States",">50K" +35,"Private",182898,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +43,"Private",180599,"Bachelors",13,"Separated","Exec-managerial","Unmarried","White","Male",8614,0,40,"United-States",">50K" +59,"Local-gov",296253,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",8614,0,60,"United-States",">50K" +29,"Private",122127,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",8614,0,40,"United-States",">50K" +24,"Private",243190,"Assoc-acdm",12,"Separated","Craft-repair","Unmarried","Asian-Pac-Islander","Male",8614,0,40,"United-States",">50K" +35,"Private",109351,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",8614,0,45,"United-States",">50K" +31,"Local-gov",158291,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",8614,0,40,"United-States",">50K" +30,"Private",225231,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",8614,0,50,"United-States",">50K" +64,"Private",60940,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",8614,0,50,"France",">50K" +46,"Local-gov",140219,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",8614,0,55,"United-States",">50K" +67,"Private",105252,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",7978,0,35,"United-States","<=50K" +66,"Local-gov",222810,"Some-college",10,"Divorced","Other-service","Other-relative","White","Female",7896,0,40,"?",">50K" +70,"Local-gov",88638,"Masters",14,"Never-married","Prof-specialty","Unmarried","White","Female",7896,0,50,"United-States",">50K" +67,"Local-gov",190661,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",7896,0,50,"United-States",">50K" +32,"Self-emp-inc",317660,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +48,"Private",146268,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7688,0,40,"United-States",">50K" +34,"State-gov",98101,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,45,"?",">50K" +50,"Private",196232,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +31,"Private",168387,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"Canada",">50K" +55,"Private",197422,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",7688,0,40,"United-States",">50K" +29,"State-gov",356089,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +37,"Private",183800,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,50,"United-States",">50K" +44,"Private",167005,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,60,"United-States",">50K" +48,"Self-emp-not-inc",243631,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",7688,0,40,"United-States",">50K" +32,"Self-emp-inc",199765,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,50,"United-States",">50K" +48,"Self-emp-inc",192945,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +62,"Private",134768,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"?",">50K" +44,"Private",43711,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,40,"United-States",">50K" +43,"Private",193882,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,40,"United-States",">50K" +46,"Private",243190,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7688,0,40,"United-States",">50K" +60,"Self-emp-inc",197553,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +53,"Private",149784,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +23,"Self-emp-not-inc",282604,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",7688,0,60,"United-States",">50K" +44,"Self-emp-inc",153132,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,52,"United-States",">50K" +56,"Self-emp-inc",105582,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +34,"Private",203408,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,50,"United-States",">50K" +47,"Private",213140,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +55,"State-gov",146326,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,45,"United-States",">50K" +47,"Private",155489,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",7688,0,55,"United-States",">50K" +38,"Private",236391,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +43,"Private",128170,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,40,"United-States",">50K" +37,"Self-emp-inc",186359,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,60,"United-States",">50K" +38,"Federal-gov",115433,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7688,0,33,"United-States",">50K" +28,"Private",119545,"Some-college",10,"Married-civ-spouse","Exec-managerial","Own-child","White","Male",7688,0,50,"United-States",">50K" +52,"Local-gov",317733,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +45,"Federal-gov",352094,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",7688,0,40,"Guatemala",">50K" +49,"Private",186172,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,45,"United-States",">50K" +46,"State-gov",192779,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +38,"Private",111398,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,40,"United-States",">50K" +53,"State-gov",50048,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,50,"United-States",">50K" +59,"?",154236,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",7688,0,40,"United-States",">50K" +52,"Federal-gov",617021,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","Black","Male",7688,0,40,"United-States",">50K" +44,"State-gov",174325,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",7688,0,40,"United-States",">50K" +33,"Private",274222,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",7688,0,38,"United-States",">50K" +39,"Private",183898,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,60,"Germany",">50K" +50,"Self-emp-inc",156623,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",7688,0,50,"Philippines",">50K" +27,"Self-emp-not-inc",37302,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Husband","White","Male",7688,0,70,"United-States",">50K" +33,"Local-gov",43959,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,50,"United-States",">50K" +41,"Private",95047,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7688,0,44,"United-States",">50K" +38,"Self-emp-not-inc",108947,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",7688,0,40,"United-States",">50K" +41,"Private",67339,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",7688,0,40,"United-States",">50K" +48,"Private",189462,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +36,"Self-emp-not-inc",20333,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",7688,0,40,"United-States",">50K" +41,"Self-emp-not-inc",27305,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",7688,0,40,"United-States",">50K" +45,"Federal-gov",88564,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +41,"Private",151504,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +34,"State-gov",34104,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,38,"United-States",">50K" +47,"Private",164113,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",7688,0,40,"United-States",">50K" +56,"Self-emp-not-inc",172618,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +64,"Self-emp-inc",165667,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,60,"Canada",">50K" +47,"Local-gov",56482,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",7688,0,50,"United-States",">50K" +45,"Local-gov",236586,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,55,"United-States",">50K" +39,"Private",194404,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +55,"State-gov",175127,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7688,0,38,"United-States",">50K" +63,"Private",346975,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,36,"United-States",">50K" +44,"State-gov",33658,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,50,"United-States",">50K" +38,"Local-gov",185394,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,40,"United-States",">50K" +39,"Private",85319,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,60,"United-States",">50K" +44,"Private",172479,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +37,"Private",152909,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7688,0,40,"United-States",">50K" +47,"Local-gov",123681,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,60,"United-States",">50K" +58,"Self-emp-not-inc",222311,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",7688,0,55,"United-States",">50K" +58,"Private",289364,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,45,"United-States",">50K" +34,"Private",134737,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,55,"United-States",">50K" +38,"Federal-gov",238342,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,42,"United-States",">50K" +61,"Private",230292,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7688,0,40,"United-States",">50K" +38,"Self-emp-inc",275223,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,40,"United-States",">50K" +41,"Self-emp-inc",253060,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,45,"United-States",">50K" +36,"Private",29702,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,40,"United-States",">50K" +35,"Private",186934,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +53,"Federal-gov",205288,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7688,0,35,"United-States",">50K" +56,"Private",132026,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Black","Male",7688,0,45,"United-States",">50K" +34,"Self-emp-not-inc",179673,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,60,"United-States",">50K" +33,"?",193172,"Assoc-voc",11,"Married-civ-spouse","?","Own-child","White","Female",7688,0,50,"United-States",">50K" +41,"Private",290660,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,55,"United-States",">50K" +32,"Private",173730,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +24,"Private",585203,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",7688,0,45,"United-States",">50K" +37,"Local-gov",218490,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",7688,0,35,"United-States",">50K" +52,"Private",84278,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,55,"?",">50K" +34,"Private",242460,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +49,"Private",165468,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,55,"United-States",">50K" +35,"Private",44780,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7688,0,20,"United-States",">50K" +36,"Private",607848,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,45,"United-States",">50K" +36,"Private",187847,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +30,"Private",162442,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,50,"United-States",">50K" +45,"Local-gov",215862,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,45,"United-States",">50K" +58,"Private",349910,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +37,"Federal-gov",93225,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7688,0,40,"United-States",">50K" +54,"Private",145714,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",7688,0,25,"United-States",">50K" +48,"Private",237525,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,65,"United-States",">50K" +47,"Local-gov",114459,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,45,"United-States",">50K" +36,"Private",20507,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,50,"United-States",">50K" +43,"Private",403467,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",7688,0,40,"United-States",">50K" +47,"Private",151584,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,60,"United-States",">50K" +62,"Private",208711,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,50,"United-States",">50K" +26,"Private",180246,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +61,"Self-emp-inc",61040,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,36,"United-States",">50K" +57,"Self-emp-inc",161662,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,60,"United-States",">50K" +50,"Local-gov",311551,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,50,"United-States",">50K" +33,"Local-gov",183923,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,35,"United-States",">50K" +46,"Private",184169,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,35,"United-States",">50K" +45,"Private",178319,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,50,"United-States",">50K" +37,"Local-gov",99935,"Masters",14,"Married-civ-spouse","Protective-serv","Husband","White","Male",7688,0,50,"United-States",">50K" +55,"Private",223594,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",7688,0,40,"Puerto-Rico",">50K" +41,"Self-emp-not-inc",169023,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7688,0,40,"United-States",">50K" +41,"Self-emp-not-inc",57924,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",7688,0,50,"United-States",">50K" +35,"Self-emp-not-inc",202027,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,55,"United-States",">50K" +46,"State-gov",30219,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,38,"United-States",">50K" +47,"Private",121836,"Masters",14,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7688,0,38,"United-States",">50K" +46,"State-gov",27243,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,45,"United-States",">50K" +53,"Local-gov",202733,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,70,"United-States",">50K" +38,"Private",192337,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +46,"Private",423222,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +43,"Private",191814,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,50,"United-States",">50K" +58,"Private",123436,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +31,"Private",43819,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,43,"United-States",">50K" +54,"Private",154728,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",7688,0,40,"United-States",">50K" +45,"Private",182313,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +54,"Self-emp-inc",96460,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,60,"United-States",">50K" +42,"Private",325353,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7688,0,42,"United-States",">50K" +43,"Local-gov",198096,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +51,"Private",339905,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,40,"United-States",">50K" +39,"State-gov",221059,"Masters",14,"Married-civ-spouse","Prof-specialty","Other-relative","Other","Female",7688,0,38,"United-States",">50K" +55,"Self-emp-not-inc",141409,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,50,"United-States",">50K" +44,"Private",230684,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +43,"Private",258049,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,53,"United-States",">50K" +46,"Federal-gov",207022,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +46,"Private",241935,"11th",7,"Married-civ-spouse","Other-service","Husband","Black","Male",7688,0,40,"United-States",">50K" +49,"Private",84298,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,40,"United-States",">50K" +60,"State-gov",165827,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,60,"United-States",">50K" +38,"Private",87556,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,55,"United-States",">50K" +46,"Federal-gov",341762,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,45,"United-States",">50K" +36,"Private",174717,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +39,"Self-emp-inc",116358,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",7688,0,40,"?",">50K" +37,"Private",125933,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +48,"Private",155664,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,70,"United-States",">50K" +41,"Private",352834,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,55,"United-States",">50K" +54,"Private",249322,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,50,"United-States",">50K" +42,"Private",384236,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +40,"Private",219266,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +40,"Local-gov",163725,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +25,"Private",99126,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,40,"United-States",">50K" +34,"Private",122612,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","Asian-Pac-Islander","Female",7688,0,50,"Philippines",">50K" +51,"Private",139347,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7688,0,40,"United-States",">50K" +40,"Private",195394,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +34,"?",166545,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",7688,0,6,"United-States",">50K" +29,"Private",148431,"Assoc-acdm",12,"Married-civ-spouse","Sales","Wife","Other","Female",7688,0,45,"United-States",">50K" +57,"Private",548256,"12th",8,"Married-civ-spouse","Transport-moving","Husband","Black","Male",7688,0,40,"United-States",">50K" +63,"?",222289,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",7688,0,54,"United-States",">50K" +45,"Local-gov",318280,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,50,"United-States",">50K" +45,"Private",197240,"12th",8,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,40,"United-States",">50K" +41,"Self-emp-inc",220821,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +58,"Self-emp-inc",113806,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,30,"United-States",">50K" +38,"Private",241998,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +47,"Private",155659,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,55,"United-States",">50K" +44,"Self-emp-inc",56651,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,45,"United-States",">50K" +47,"Private",98012,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,40,"United-States",">50K" +44,"Private",155930,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,55,"United-States",">50K" +38,"State-gov",110426,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,40,"?",">50K" +33,"Private",251120,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,50,"United-States",">50K" +34,"Private",181091,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +53,"Self-emp-not-inc",145419,"1st-4th",2,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,67,"Italy",">50K" +51,"Private",87205,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7688,0,20,"United-States",">50K" +50,"Self-emp-inc",302708,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",7688,0,50,"Japan",">50K" +32,"Self-emp-not-inc",37232,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,45,"United-States",">50K" +42,"Private",124792,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",7688,0,45,"United-States",">50K" +55,"?",270228,"Assoc-acdm",12,"Married-civ-spouse","?","Husband","Black","Male",7688,0,40,"United-States",">50K" +50,"Self-emp-not-inc",68898,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,55,"United-States",">50K" +28,"Private",183151,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",7688,0,40,"United-States",">50K" +46,"Private",110171,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +39,"Private",173476,"Prof-school",15,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +37,"Private",202027,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7688,0,50,"United-States",">50K" +40,"Private",177027,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","Asian-Pac-Islander","Female",7688,0,52,"Japan",">50K" +40,"Private",154374,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +54,"Private",185407,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +41,"Private",58880,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,10,"United-States",">50K" +50,"Private",48358,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +41,"Private",163287,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,43,"United-States",">50K" +44,"Private",198096,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,40,"United-States",">50K" +48,"Self-emp-inc",287647,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,55,"United-States",">50K" +55,"Private",117299,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +48,"Private",155659,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +45,"Local-gov",160173,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +39,"Private",184117,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,20,"United-States",">50K" +50,"Self-emp-not-inc",172281,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +28,"Local-gov",168524,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,35,"United-States",">50K" +57,"Private",61474,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,45,"United-States",">50K" +32,"Self-emp-inc",275094,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,55,"Mexico",">50K" +37,"Private",219141,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",7688,0,40,"United-States",">50K" +51,"Federal-gov",20795,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",7688,0,40,"United-States",">50K" +54,"Self-emp-inc",304570,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",7688,0,40,"?",">50K" +37,"Private",178948,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",7688,0,45,"United-States",">50K" +39,"Private",103925,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,32,"United-States",">50K" +30,"Private",19302,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +46,"Local-gov",303918,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",7688,0,96,"United-States",">50K" +40,"Federal-gov",75313,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,66,"United-States",">50K" +38,"State-gov",188303,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",7688,0,40,"United-States",">50K" +39,"Self-emp-not-inc",274683,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,50,"United-States",">50K" +50,"Local-gov",196307,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +60,"Self-emp-inc",210827,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +42,"Private",52781,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +50,"Self-emp-not-inc",145419,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,45,"United-States",">50K" +44,"Local-gov",171589,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +51,"Private",159755,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +51,"State-gov",231495,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,55,"United-States",">50K" +47,"Private",278322,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +53,"Self-emp-not-inc",135339,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",7688,0,20,"China",">50K" +41,"Private",149909,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,50,"United-States",">50K" +29,"Federal-gov",244473,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +46,"Private",197332,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,46,"United-States",">50K" +44,"Private",147206,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,45,"United-States",">50K" +38,"?",94559,"Bachelors",13,"Married-civ-spouse","?","Wife","Other","Female",7688,0,50,"?",">50K" +49,"Private",83610,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,66,"United-States",">50K" +51,"Private",289572,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,50,"United-States",">50K" +41,"Private",138975,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,45,"United-States",">50K" +54,"Private",176240,"Masters",14,"Married-civ-spouse","Transport-moving","Husband","White","Male",7688,0,60,"United-States",">50K" +60,"Private",325971,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",7688,0,40,"United-States",">50K" +40,"Private",284303,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",7688,0,40,"United-States",">50K" +54,"Local-gov",173050,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +42,"Private",511068,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +38,"Private",103323,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +34,"Private",24266,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +34,"Private",167497,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",7688,0,50,"United-States",">50K" +56,"Federal-gov",156229,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +38,"Private",276559,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,70,"United-States",">50K" +35,"Private",86648,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,50,"United-States",">50K" +43,"Private",75993,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,40,"United-States",">50K" +50,"Self-emp-not-inc",27539,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",7688,0,40,"United-States",">50K" +35,"Private",253006,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,38,"United-States",">50K" +61,"Private",159822,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"Poland",">50K" +45,"Self-emp-not-inc",315984,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,50,"United-States",">50K" +36,"Private",223433,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,50,"United-States",">50K" +40,"Private",121874,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,50,"United-States",">50K" +49,"Local-gov",119904,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,30,"United-States",">50K" +36,"Private",262688,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",7688,0,50,"United-States",">50K" +52,"Private",102828,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +53,"Private",126592,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",7688,0,40,"United-States",">50K" +29,"Private",191722,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",7688,0,54,"United-States",">50K" +56,"Private",109015,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",7688,0,50,"United-States",">50K" +41,"Private",100451,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,38,"United-States",">50K" +30,"Private",159589,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,50,"United-States",">50K" +58,"Private",172333,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,40,"United-States",">50K" +45,"Self-emp-inc",180239,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",7688,0,40,"?",">50K" +52,"Self-emp-not-inc",138611,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,55,"United-States",">50K" +42,"Private",154076,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,50,"United-States",">50K" +38,"Private",245372,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,45,"United-States",">50K" +30,"Self-emp-inc",77689,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,50,"United-States",">50K" +50,"Private",22211,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,50,"United-States",">50K" +54,"Private",215990,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",7688,0,40,"United-States",">50K" +48,"Federal-gov",166634,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7688,0,40,"United-States",">50K" +54,"Self-emp-inc",223752,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"?",">50K" +46,"Private",52291,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,45,"United-States",">50K" +42,"Private",261929,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,40,"United-States",">50K" +63,"Self-emp-not-inc",29859,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",7688,0,60,"United-States",">50K" +51,"Private",154342,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,45,"United-States",">50K" +39,"Federal-gov",363630,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",7688,0,52,"United-States",">50K" +29,"Local-gov",115305,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",7688,0,40,"United-States",">50K" +35,"Private",64922,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,50,"United-States",">50K" +41,"Self-emp-inc",177905,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,70,"United-States",">50K" +38,"Private",478346,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",7688,0,40,"United-States",">50K" +39,"Private",176335,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,65,"United-States",">50K" +40,"Federal-gov",330174,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +44,"Private",242521,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7688,0,50,"United-States",">50K" +38,"State-gov",125499,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",7688,0,60,"India",">50K" +47,"Private",252079,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",7688,0,44,"United-States",">50K" +37,"Private",103986,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,39,"United-States",">50K" +39,"Private",198841,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,45,"United-States",">50K" +28,"Local-gov",229223,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7688,0,36,"United-States",">50K" +33,"Private",133503,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",7688,0,48,"United-States",">50K" +42,"Private",24982,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +32,"Self-emp-not-inc",112115,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7688,0,40,"United-States",">50K" +34,"Self-emp-inc",343789,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,55,"United-States",">50K" +58,"Local-gov",311409,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",7688,0,30,"United-States",">50K" +42,"Private",402367,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",7688,0,45,"United-States",">50K" +39,"Private",358753,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",7688,0,40,"United-States",">50K" +31,"Federal-gov",130057,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,60,"United-States",">50K" +40,"Private",177905,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7688,0,44,"United-States",">50K" +35,"Private",91839,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","Amer-Indian-Eskimo","Male",7688,0,20,"United-States",">50K" +34,"Private",212064,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",7443,0,35,"United-States","<=50K" +38,"Private",22494,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",7443,0,40,"United-States","<=50K" +41,"Private",24763,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Male",7443,0,40,"United-States","<=50K" +35,"Private",316141,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",7443,0,40,"United-States","<=50K" +34,"Private",213307,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","White","Female",7443,0,35,"United-States","<=50K" +37,"Private",234807,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",7430,0,45,"United-States",">50K" +42,"Local-gov",195124,"11th",7,"Divorced","Sales","Unmarried","White","Male",7430,0,50,"Puerto-Rico",">50K" +35,"Private",275364,"Bachelors",13,"Divorced","Tech-support","Unmarried","White","Male",7430,0,40,"Germany",">50K" +41,"Local-gov",112763,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",7430,0,36,"United-States",">50K" +49,"State-gov",185800,"Masters",14,"Divorced","Prof-specialty","Unmarried","Black","Female",7430,0,40,"United-States",">50K" +41,"Private",529216,"Bachelors",13,"Divorced","Tech-support","Unmarried","Black","Male",7430,0,45,"?",">50K" +45,"Private",187370,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Male",7430,0,70,"United-States",">50K" +42,"Self-emp-not-inc",199143,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Female",7430,0,44,"United-States",">50K" +42,"Self-emp-not-inc",32546,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Male",7430,0,40,"United-States",">50K" +35,"Private",138992,"Masters",14,"Married-civ-spouse","Prof-specialty","Other-relative","White","Male",7298,0,40,"United-States",">50K" +36,"Private",128757,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","Black","Male",7298,0,36,"United-States",">50K" +44,"Private",170924,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +24,"Private",279472,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",7298,0,48,"United-States",">50K" +34,"Private",142897,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",7298,0,35,"Taiwan",">50K" +38,"Private",296478,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +36,"State-gov",119272,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",7298,0,40,"United-States",">50K" +42,"Private",162140,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,45,"United-States",">50K" +30,"Private",296453,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,40,"United-States",">50K" +42,"Private",150533,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,52,"United-States",">50K" +50,"Self-emp-inc",293196,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +35,"Private",119098,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +40,"Private",228535,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,36,"United-States",">50K" +38,"Private",31033,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,40,"United-States",">50K" +35,"Private",183898,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,50,"United-States",">50K" +41,"Private",220132,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +29,"Private",241431,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,40,"United-States",">50K" +36,"Private",183892,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,44,"United-States",">50K" +60,"Private",240521,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +50,"Private",88842,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,40,"United-States",">50K" +41,"Private",168071,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,50,"United-States",">50K" +52,"Federal-gov",30731,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +37,"Private",93717,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7298,0,45,"United-States",">50K" +39,"Private",188391,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,50,"United-States",">50K" +33,"Private",220939,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,45,"United-States",">50K" +34,"Private",340940,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,60,"United-States",">50K" +31,"Private",203488,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,50,"United-States",">50K" +59,"Private",146391,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",7298,0,40,"United-States",">50K" +41,"Private",113555,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",7298,0,50,"United-States",">50K" +39,"Private",33355,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,48,"United-States",">50K" +51,"Private",162632,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,60,"United-States",">50K" +46,"Self-emp-inc",219962,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",7298,0,40,"?",">50K" +38,"Private",111499,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,50,"United-States",">50K" +33,"Private",198003,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,50,"United-States",">50K" +25,"Private",163620,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,84,"United-States",">50K" +35,"Private",360799,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +52,"Private",99185,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,50,"United-States",">50K" +25,"Self-emp-not-inc",182809,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +49,"Local-gov",194895,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",7298,0,40,"United-States",">50K" +39,"Private",102953,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,55,"United-States",">50K" +43,"Private",111483,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,40,"United-States",">50K" +42,"Private",266084,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,45,"United-States",">50K" +53,"Private",106176,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,60,"United-States",">50K" +51,"Private",114927,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",7298,0,40,"United-States",">50K" +34,"Private",157747,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +50,"Private",95469,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,45,"United-States",">50K" +50,"Local-gov",145166,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +36,"Private",143486,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,50,"United-States",">50K" +32,"Private",131584,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,40,"United-States",">50K" +58,"Local-gov",217775,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +47,"Private",284916,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,45,"United-States",">50K" +31,"State-gov",75755,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,55,"United-States",">50K" +36,"Private",83089,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",7298,0,40,"Mexico",">50K" +36,"Private",199739,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,60,"United-States",">50K" +54,"Local-gov",31533,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,40,"United-States",">50K" +43,"Federal-gov",203637,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,40,"United-States",">50K" +37,"Local-gov",51158,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","White","Female",7298,0,36,"United-States",">50K" +35,"Private",359131,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7298,0,8,"?",">50K" +39,"Self-emp-inc",283338,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +57,"?",300104,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",7298,0,84,"United-States",">50K" +39,"Private",224531,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +24,"Private",161092,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,40,"United-States",">50K" +37,"Self-emp-not-inc",268598,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Other","Male",7298,0,50,"Puerto-Rico",">50K" +35,"State-gov",126569,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +39,"Private",43712,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +48,"Self-emp-inc",254291,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,50,"United-States",">50K" +59,"Private",159008,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,20,"United-States",">50K" +48,"Self-emp-not-inc",164582,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",7298,0,60,"United-States",">50K" +38,"Private",132879,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,50,"United-States",">50K" +47,"Self-emp-not-inc",165468,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",7298,0,40,"United-States",">50K" +60,"Local-gov",124987,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +48,"Private",102359,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,60,"United-States",">50K" +32,"Private",222221,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,42,"United-States",">50K" +54,"Private",225599,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",7298,0,40,"India",">50K" +28,"Self-emp-not-inc",209205,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +44,"Private",145441,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,48,"United-States",">50K" +45,"Private",186272,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",7298,0,40,"United-States",">50K" +51,"Private",143822,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +37,"Federal-gov",22201,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",7298,0,40,"Philippines",">50K" +38,"State-gov",134069,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,60,"United-States",">50K" +49,"Federal-gov",586657,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +47,"Private",328216,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",7298,0,40,"United-States",">50K" +51,"Private",192182,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",7298,0,40,"United-States",">50K" +46,"Private",113806,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"?",">50K" +36,"Private",169469,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +53,"Private",158294,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +45,"Private",199058,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,50,"United-States",">50K" +34,"Federal-gov",419691,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",7298,0,54,"United-States",">50K" +41,"Private",116797,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,50,"United-States",">50K" +38,"Self-emp-inc",269318,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +57,"Private",180779,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +46,"Private",332884,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,65,"United-States",">50K" +53,"Private",177916,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,40,"United-States",">50K" +37,"Private",105813,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,40,"United-States",">50K" +50,"Private",160724,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",7298,0,40,"Philippines",">50K" +40,"Private",111483,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +33,"Private",164190,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +29,"Private",39484,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",7298,0,42,"United-States",">50K" +42,"Private",184837,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",7298,0,40,"United-States",">50K" +44,"Private",196545,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +34,"Private",208043,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,45,"United-States",">50K" +38,"Private",190895,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,50,"United-States",">50K" +64,"Self-emp-not-inc",65991,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",7298,0,45,"United-States",">50K" +36,"Self-emp-not-inc",35945,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",7298,0,45,"United-States",">50K" +37,"Private",190987,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",7298,0,40,"United-States",">50K" +48,"Local-gov",493862,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",7298,0,38,"United-States",">50K" +47,"Private",274200,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +42,"Private",87284,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,35,"United-States",">50K" +51,"State-gov",454063,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +45,"State-gov",213646,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +33,"Private",222221,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,45,"United-States",">50K" +43,"Self-emp-not-inc",421837,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,50,"Mexico",">50K" +40,"Local-gov",188436,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",7298,0,40,"United-States",">50K" +51,"Private",237630,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",7298,0,50,"United-States",">50K" +38,"Private",297449,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,50,"United-States",">50K" +36,"Private",225399,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +60,"Local-gov",138502,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",7298,0,48,"United-States",">50K" +54,"Private",203635,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,60,"United-States",">50K" +41,"Private",274363,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",7298,0,42,"United-States",">50K" +42,"Private",175943,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Wife","White","Female",7298,0,35,"United-States",">50K" +50,"Private",211319,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,50,"United-States",">50K" +52,"Federal-gov",291096,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Husband","White","Male",7298,0,40,"United-States",">50K" +38,"Private",275223,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,40,"United-States",">50K" +59,"Private",159724,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,55,"United-States",">50K" +36,"Private",175759,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,50,"United-States",">50K" +55,"Private",198145,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +39,"Local-gov",203482,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +40,"Federal-gov",121012,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,48,"United-States",">50K" +41,"Private",143003,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",7298,0,60,"India",">50K" +38,"Private",257250,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,60,"United-States",">50K" +32,"Private",154120,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,40,"United-States",">50K" +60,"Self-emp-inc",105339,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,60,"United-States",">50K" +50,"Federal-gov",98980,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +62,"Private",69867,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,50,"United-States",">50K" +49,"Private",196707,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",7298,0,43,"United-States",">50K" +46,"State-gov",238648,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",7298,0,40,"United-States",">50K" +44,"Private",172032,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,51,"United-States",">50K" +30,"Private",271710,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,50,"United-States",">50K" +61,"Local-gov",144723,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,60,"United-States",">50K" +31,"Private",265706,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +53,"Private",89587,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,45,"United-States",">50K" +36,"Self-emp-not-inc",182898,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +40,"Private",360884,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7298,0,40,"United-States",">50K" +30,"Federal-gov",321990,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,48,"Cuba",">50K" +50,"Local-gov",117496,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7298,0,30,"United-States",">50K" +63,"Private",137843,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,48,"United-States",">50K" +38,"Self-emp-not-inc",280169,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,50,"United-States",">50K" +33,"Self-emp-not-inc",272359,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,80,"United-States",">50K" +45,"Private",203653,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",7298,0,40,"United-States",">50K" +41,"Federal-gov",253770,"Some-college",10,"Married-civ-spouse","Transport-moving","Wife","White","Female",7298,0,40,"United-States",">50K" +37,"Local-gov",160910,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,40,"United-States",">50K" +35,"Local-gov",300681,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","Black","Male",7298,0,35,"United-States",">50K" +33,"Private",192002,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,60,"Canada",">50K" +35,"Private",202027,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",7298,0,35,"United-States",">50K" +35,"Self-emp-not-inc",170174,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,60,"United-States",">50K" +51,"Private",279156,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +46,"Self-emp-not-inc",176319,"HS-grad",9,"Married-civ-spouse","Sales","Own-child","White","Female",7298,0,40,"United-States",">50K" +44,"Federal-gov",469454,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",7298,0,48,"United-States",">50K" +34,"Private",191856,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",7298,0,40,"United-States",">50K" +36,"Private",115834,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Wife","White","Female",7298,0,55,"United-States",">50K" +35,"Local-gov",302149,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",7298,0,40,"Philippines",">50K" +40,"Private",409922,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +38,"Private",187870,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,50,"United-States",">50K" +33,"Private",168030,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7298,0,21,"United-States",">50K" +55,"Self-emp-not-inc",157486,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +28,"Private",233796,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7298,0,32,"United-States",">50K" +43,"Federal-gov",195897,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",7298,0,40,"United-States",">50K" +40,"Private",48087,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,45,"United-States",">50K" +51,"Self-emp-not-inc",246820,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,48,"United-States",">50K" +40,"Local-gov",153031,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,35,"United-States",">50K" +49,"Private",139268,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +39,"Local-gov",267893,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","Black","Male",7298,0,40,"United-States",">50K" +27,"Private",224105,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",7298,0,40,"United-States",">50K" +45,"Private",34419,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +60,"Private",109530,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",7298,0,40,"United-States",">50K" +60,"Private",116707,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,40,"United-States",">50K" +47,"Private",185041,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +43,"Private",152958,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +31,"Private",246439,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",7298,0,50,"United-States",">50K" +62,"?",191118,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",7298,0,40,"United-States",">50K" +52,"Private",74275,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,45,"United-States",">50K" +34,"Private",199934,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",7298,0,40,"United-States",">50K" +44,"Private",54310,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +49,"Local-gov",269527,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +50,"Private",268553,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,40,"United-States",">50K" +26,"Private",94477,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,55,"United-States",">50K" +46,"Private",321327,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,45,"United-States",">50K" +45,"Local-gov",348172,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","Asian-Pac-Islander","Male",7298,0,40,"United-States",">50K" +36,"State-gov",86805,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",7298,0,39,"United-States",">50K" +41,"Self-emp-not-inc",100800,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,70,"United-States",">50K" +60,"Private",282923,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +45,"Private",174533,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,50,"United-States",">50K" +44,"Self-emp-not-inc",127482,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,50,"England",">50K" +34,"Private",252646,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,50,"United-States",">50K" +51,"Private",137815,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,40,"United-States",">50K" +35,"Federal-gov",49657,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +54,"Private",35557,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,50,"United-States",">50K" +53,"Private",386773,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,40,"United-States",">50K" +51,"Private",162745,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,50,"United-States",">50K" +40,"Self-emp-not-inc",26892,"Bachelors",13,"Married-AF-spouse","Prof-specialty","Husband","White","Male",7298,0,50,"United-States",">50K" +42,"Private",149210,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,45,"United-States",">50K" +50,"Self-emp-inc",155574,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,50,"United-States",">50K" +51,"Private",48343,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,50,"United-States",">50K" +33,"Private",188246,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,45,"United-States",">50K" +48,"Private",83444,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,40,"United-States",">50K" +40,"Private",124747,"HS-grad",9,"Married-civ-spouse","Craft-repair","Wife","White","Female",7298,0,40,"United-States",">50K" +36,"Private",169426,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",7298,0,40,"United-States",">50K" +27,"Private",190525,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,55,"United-States",">50K" +37,"Private",263094,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +54,"Self-emp-inc",357596,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,55,"United-States",">50K" +36,"Private",171393,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,55,"United-States",">50K" +46,"Private",98637,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,50,"United-States",">50K" +38,"Private",43712,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,60,"United-States",">50K" +38,"Private",122076,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,43,"United-States",">50K" +45,"Private",192776,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,55,"United-States",">50K" +48,"Private",248254,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7298,0,40,"United-States",">50K" +60,"Private",178312,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,65,"United-States",">50K" +58,"Self-emp-inc",78104,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,60,"United-States",">50K" +42,"Private",171424,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",7298,0,45,"United-States",">50K" +51,"Private",138852,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",7298,0,40,"El-Salvador",">50K" +42,"Federal-gov",34218,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,50,"United-States",">50K" +44,"Private",235786,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,45,"United-States",">50K" +32,"Private",195000,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,45,"United-States",">50K" +60,"Federal-gov",119832,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,40,"United-States",">50K" +49,"Private",195612,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,40,"United-States",">50K" +31,"State-gov",373432,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,55,"United-States",">50K" +45,"Private",25649,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",7298,0,50,"United-States",">50K" +55,"Private",227856,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,60,"United-States",">50K" +61,"Private",81132,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","Asian-Pac-Islander","Male",7298,0,40,"Philippines",">50K" +57,"Local-gov",189824,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",7298,0,40,"United-States",">50K" +47,"Private",168232,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",7298,0,40,"United-States",">50K" +40,"Private",254478,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,50,"United-States",">50K" +47,"Private",334039,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,44,"United-States",">50K" +29,"Private",112847,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",7298,0,32,"United-States",">50K" +52,"Local-gov",199995,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",7298,0,60,"United-States",">50K" +28,"Private",207513,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,42,"United-States",">50K" +30,"Private",430283,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",7298,0,40,"United-States",">50K" +35,"Private",75855,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",7298,0,40,"?",">50K" +28,"Local-gov",33662,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",7298,0,40,"United-States",">50K" +36,"State-gov",179488,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",7298,0,55,"United-States",">50K" +41,"State-gov",106900,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",7298,0,60,"United-States",">50K" +30,"Private",176410,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Own-child","White","Female",7298,0,16,"United-States",">50K" +45,"Private",170871,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,60,"United-States",">50K" +38,"Private",59660,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,40,"United-States",">50K" +42,"Private",161510,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",7298,0,40,"United-States",">50K" +48,"Self-emp-inc",185041,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",7298,0,50,"United-States",">50K" +52,"Private",200853,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",6849,0,60,"United-States","<=50K" +24,"Private",180060,"Masters",14,"Never-married","Exec-managerial","Own-child","White","Male",6849,0,90,"United-States","<=50K" +34,"Private",33945,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",6849,0,55,"United-States","<=50K" +29,"Private",190539,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",6849,0,48,"United-States","<=50K" +35,"?",296738,"11th",7,"Separated","?","Not-in-family","White","Female",6849,0,60,"United-States","<=50K" +25,"Private",262778,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",6849,0,50,"United-States","<=50K" +40,"Local-gov",24763,"Some-college",10,"Divorced","Transport-moving","Unmarried","White","Male",6849,0,40,"United-States","<=50K" +28,"State-gov",38309,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",6849,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",241297,"Some-college",10,"Widowed","Farming-fishing","Not-in-family","White","Female",6849,0,40,"United-States","<=50K" +30,"Private",189620,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",6849,0,40,"England","<=50K" +26,"Private",177147,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",6849,0,65,"United-States","<=50K" +53,"Private",223660,"HS-grad",9,"Widowed","Machine-op-inspct","Not-in-family","White","Male",6849,0,40,"United-States","<=50K" +40,"Private",207025,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",6849,0,38,"United-States","<=50K" +39,"Private",87556,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",6849,0,40,"United-States","<=50K" +25,"Private",194897,"HS-grad",9,"Never-married","Sales","Own-child","Amer-Indian-Eskimo","Male",6849,0,40,"United-States","<=50K" +28,"Private",124680,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",6849,0,60,"United-States","<=50K" +35,"Private",139770,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",6849,0,40,"United-States","<=50K" +47,"Private",266281,"11th",7,"Never-married","Machine-op-inspct","Unmarried","Black","Female",6849,0,40,"United-States","<=50K" +35,"Private",167735,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",6849,0,40,"United-States","<=50K" +33,"Private",108328,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",6849,0,50,"United-States","<=50K" +39,"Private",106183,"HS-grad",9,"Divorced","Other-service","Unmarried","Amer-Indian-Eskimo","Female",6849,0,40,"United-States","<=50K" +50,"State-gov",45961,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",6849,0,40,"United-States","<=50K" +40,"Private",34113,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","Amer-Indian-Eskimo","Male",6849,0,43,"United-States","<=50K" +38,"Private",234298,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",6849,0,60,"United-States","<=50K" +55,"State-gov",294395,"Assoc-voc",11,"Widowed","Prof-specialty","Unmarried","White","Female",6849,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",67072,"Bachelors",13,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",6849,0,60,"United-States","<=50K" +35,"Private",162256,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",6849,0,40,"United-States","<=50K" +71,"Private",105200,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",6767,0,20,"United-States","<=50K" +65,"Private",90377,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",6767,0,60,"United-States","<=50K" +90,"Local-gov",153602,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",6767,0,40,"United-States","<=50K" +66,"?",212759,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",6767,0,20,"United-States","<=50K" +74,"?",169303,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",6767,0,6,"United-States","<=50K" +72,"Private",298070,"Assoc-voc",11,"Separated","Other-service","Unmarried","White","Female",6723,0,25,"United-States","<=50K" +65,"Private",170939,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",6723,0,40,"United-States","<=50K" +67,"Private",171584,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",6514,0,7,"United-States",">50K" +65,"State-gov",209280,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",6514,0,35,"United-States",">50K" +65,"Self-emp-not-inc",223580,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",6514,0,40,"United-States",">50K" +71,"?",144872,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",6514,0,40,"United-States",">50K" +69,"Self-emp-inc",107850,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",6514,0,40,"United-States",">50K" +57,"Private",188872,"5th-6th",3,"Divorced","Transport-moving","Unmarried","White","Male",6497,0,40,"United-States","<=50K" +46,"Private",182128,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",6497,0,50,"United-States","<=50K" +45,"Local-gov",326064,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",6497,0,35,"United-States","<=50K" +36,"Federal-gov",930948,"Some-college",10,"Separated","Adm-clerical","Unmarried","Black","Female",6497,0,56,"United-States","<=50K" +35,"Private",115214,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Male",6497,0,65,"United-States","<=50K" +41,"Private",200671,"Bachelors",13,"Divorced","Transport-moving","Own-child","Black","Male",6497,0,40,"United-States","<=50K" +38,"Private",188503,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",6497,0,35,"United-States","<=50K" +49,"Self-emp-inc",26502,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Male",6497,0,45,"United-States","<=50K" +47,"Private",105273,"Bachelors",13,"Widowed","Craft-repair","Unmarried","Black","Female",6497,0,40,"United-States","<=50K" +26,"Private",214413,"11th",7,"Never-married","Machine-op-inspct","Unmarried","White","Male",6497,0,48,"United-States","<=50K" +46,"Private",117310,"Assoc-acdm",12,"Widowed","Tech-support","Unmarried","White","Female",6497,0,40,"United-States","<=50K" +67,"?",157403,"Prof-school",15,"Married-civ-spouse","?","Husband","White","Male",6418,0,10,"United-States",">50K" +69,"Self-emp-inc",169717,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",6418,0,45,"United-States",">50K" +62,"?",160155,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",6418,0,40,"United-States",">50K" +73,"Self-emp-not-inc",102510,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",6418,0,99,"United-States",">50K" +62,"Private",266624,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",6418,0,40,"United-States",">50K" +67,"Self-emp-not-inc",123393,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",6418,0,58,"United-States",">50K" +65,"Self-emp-inc",66360,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",6418,0,35,"United-States",">50K" +55,"Private",61708,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",6418,0,50,"United-States",">50K" +70,"Private",187292,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",6418,0,40,"United-States",">50K" +72,"Private",496538,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",6360,0,40,"United-States","<=50K" +68,"Private",50351,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Female",6360,0,20,"United-States","<=50K" +67,"Local-gov",191800,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","Black","Female",6360,0,35,"United-States","<=50K" +71,"Private",196610,"7th-8th",4,"Widowed","Exec-managerial","Not-in-family","White","Male",6097,0,40,"United-States",">50K" +38,"Private",168407,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",5721,0,44,"United-States","<=50K" +26,"Private",101812,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Male",5721,0,40,"United-States","<=50K" +28,"Local-gov",127491,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Female",5721,0,40,"United-States","<=50K" +66,"Private",146454,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",5556,0,40,"United-States",">50K" +66,"Private",142624,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",5556,0,40,"Yugoslavia",">50K" +66,"Self-emp-inc",249043,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",5556,0,26,"United-States",">50K" +65,"Private",344152,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5556,0,50,"United-States",">50K" +65,"?",115513,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",5556,0,48,"United-States",">50K" +45,"Private",189890,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",5455,0,38,"United-States","<=50K" +42,"Private",129684,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","Black","Female",5455,0,50,"United-States","<=50K" +39,"Private",114678,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Female",5455,0,40,"United-States","<=50K" +47,"Local-gov",247676,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",5455,0,45,"United-States","<=50K" +36,"State-gov",108320,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Male",5455,0,30,"United-States","<=50K" +39,"Federal-gov",193583,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",5455,0,60,"United-States","<=50K" +43,"Self-emp-inc",247981,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",5455,0,50,"United-States","<=50K" +45,"Private",474617,"HS-grad",9,"Divorced","Sales","Unmarried","Black","Male",5455,0,40,"United-States","<=50K" +37,"State-gov",252939,"Assoc-voc",11,"Never-married","Prof-specialty","Unmarried","Black","Female",5455,0,40,"United-States","<=50K" +40,"Local-gov",105862,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",5455,0,40,"United-States","<=50K" +60,"Local-gov",48788,"Bachelors",13,"Separated","Prof-specialty","Unmarried","White","Female",5455,0,55,"United-States","<=50K" +42,"Private",159449,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,40,"United-States",">50K" +42,"Local-gov",97688,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,40,"United-States",">50K" +36,"Private",188563,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",5178,0,50,"United-States",">50K" +32,"Private",231043,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,48,"United-States",">50K" +44,"Self-emp-inc",320984,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",5178,0,60,"United-States",">50K" +50,"Private",88926,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",5178,0,40,"United-States",">50K" +54,"Private",206369,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",5178,0,50,"United-States",">50K" +32,"Self-emp-inc",244665,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,45,"United-States",">50K" +61,"Local-gov",95450,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,50,"United-States",">50K" +51,"Private",106728,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,60,"United-States",">50K" +40,"Private",572751,"Prof-school",15,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,40,"Mexico",">50K" +32,"Private",107843,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",5178,0,50,"United-States",">50K" +34,"Private",275438,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5178,0,40,"United-States",">50K" +48,"Local-gov",31264,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",5178,0,40,"United-States",">50K" +45,"Private",186272,"9th",5,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",5178,0,40,"United-States",">50K" +35,"Private",46385,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",5178,0,90,"United-States",">50K" +41,"Federal-gov",168294,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",5178,0,40,"United-States",">50K" +31,"Private",132996,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5178,0,45,"United-States",">50K" +29,"Self-emp-not-inc",169544,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",5178,0,40,"United-States",">50K" +37,"Local-gov",312232,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",5178,0,40,"United-States",">50K" +26,"Private",247455,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",5178,0,42,"United-States",">50K" +36,"Private",175232,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,40,"United-States",">50K" +42,"Private",94600,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,40,"United-States",">50K" +47,"?",109832,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",5178,0,30,"Canada",">50K" +40,"Private",119101,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,40,"United-States",">50K" +30,"Private",164190,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5178,0,52,"United-States",">50K" +37,"Private",220237,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,40,"United-States",">50K" +36,"Private",247558,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5178,0,60,"?",">50K" +40,"Private",198692,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",5178,0,60,"United-States",">50K" +33,"Private",141841,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",5178,0,40,"United-States",">50K" +49,"Private",176814,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",5178,0,40,"United-States",">50K" +42,"Local-gov",174575,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5178,0,40,"United-States",">50K" +38,"Private",76878,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,40,"United-States",">50K" +26,"Private",97153,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",5178,0,40,"United-States",">50K" +54,"Self-emp-not-inc",172898,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5178,0,50,"United-States",">50K" +46,"Private",127089,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5178,0,38,"United-States",">50K" +32,"Private",29933,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",5178,0,40,"United-States",">50K" +25,"Private",161027,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",5178,0,40,"United-States",">50K" +44,"Private",74680,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,50,"United-States",">50K" +30,"Private",186932,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5178,0,75,"United-States",">50K" +25,"Private",120238,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",5178,0,40,"Poland",">50K" +37,"Private",287031,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,75,"United-States",">50K" +28,"Private",176683,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,50,"United-States",">50K" +31,"Private",473133,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5178,0,40,"United-States",">50K" +44,"Private",99651,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,40,"United-States",">50K" +44,"Private",175669,"11th",7,"Married-civ-spouse","Prof-specialty","Wife","White","Female",5178,0,36,"United-States",">50K" +39,"Self-emp-inc",543042,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,50,"United-States",">50K" +51,"Federal-gov",97934,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",5178,0,40,"United-States",">50K" +27,"Private",311446,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",5178,0,40,"United-States",">50K" +31,"Private",123397,"HS-grad",9,"Married-civ-spouse","Transport-moving","Wife","White","Female",5178,0,35,"United-States",">50K" +53,"Private",195813,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","Other","Male",5178,0,40,"Puerto-Rico",">50K" +37,"Local-gov",365430,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,40,"United-States",">50K" +48,"State-gov",118330,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,40,"United-States",">50K" +56,"Private",116143,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",5178,0,44,"United-States",">50K" +35,"Private",282979,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",5178,0,50,"United-States",">50K" +50,"Local-gov",153064,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,40,"United-States",">50K" +42,"Private",230684,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",5178,0,50,"United-States",">50K" +58,"Private",280309,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,60,"United-States",">50K" +35,"Private",105821,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,40,"United-States",">50K" +46,"Private",173243,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",5178,0,40,"United-States",">50K" +34,"Private",209101,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,55,"United-States",">50K" +43,"Private",214781,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5178,0,40,"United-States",">50K" +39,"State-gov",122011,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",5178,0,38,"United-States",">50K" +46,"Federal-gov",97863,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",5178,0,40,"United-States",">50K" +55,"Private",162205,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",5178,0,72,"United-States",">50K" +38,"Private",207568,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,40,"United-States",">50K" +63,"?",310396,"9th",5,"Married-civ-spouse","?","Husband","White","Male",5178,0,40,"United-States",">50K" +27,"Private",210498,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,40,"United-States",">50K" +47,"Private",187440,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,40,"United-States",">50K" +47,"Private",201699,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",5178,0,50,"United-States",">50K" +36,"Private",186035,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,40,"United-States",">50K" +43,"Private",339814,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5178,0,40,"United-States",">50K" +44,"Private",112262,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",5178,0,40,"United-States",">50K" +36,"Private",226013,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",5178,0,40,"United-States",">50K" +51,"Private",175070,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",5178,0,45,"United-States",">50K" +57,"Self-emp-inc",258883,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",5178,0,60,"Hungary",">50K" +32,"Private",106014,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",5178,0,50,"United-States",">50K" +39,"Self-emp-inc",131288,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",5178,0,48,"United-States",">50K" +35,"Self-emp-inc",186845,"Bachelors",13,"Married-civ-spouse","Sales","Own-child","White","Male",5178,0,50,"United-States",">50K" +62,"?",125493,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",5178,0,40,"Scotland",">50K" +45,"Private",261278,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","Asian-Pac-Islander","Female",5178,0,40,"Philippines",">50K" +39,"Private",248011,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",5178,0,40,"United-States",">50K" +31,"Private",151053,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",5178,0,40,"United-States",">50K" +53,"Self-emp-inc",152810,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,45,"United-States",">50K" +54,"Private",135388,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,40,"United-States",">50K" +37,"Private",187589,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",5178,0,40,"United-States",">50K" +55,"Private",184882,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",5178,0,50,"United-States",">50K" +45,"Local-gov",374450,"HS-grad",9,"Married-civ-spouse","Transport-moving","Wife","White","Female",5178,0,40,"United-States",">50K" +59,"Private",126668,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5178,0,50,"United-States",">50K" +33,"?",369386,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",5178,0,40,"United-States",">50K" +47,"Private",70943,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",5178,0,40,"United-States",">50K" +28,"Federal-gov",163862,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,40,"United-States",">50K" +47,"Local-gov",200471,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",5178,0,40,"United-States",">50K" +38,"Private",269318,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",5178,0,50,"United-States",">50K" +34,"State-gov",118551,"Bachelors",13,"Married-civ-spouse","Tech-support","Own-child","White","Female",5178,0,25,"?",">50K" +54,"Federal-gov",75235,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5178,0,40,"United-States",">50K" +58,"Private",250206,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",5178,0,40,"United-States",">50K" +24,"Private",206827,"Some-college",10,"Never-married","Sales","Own-child","White","Female",5060,0,30,"United-States","<=50K" +30,"Private",188146,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",5013,0,40,"United-States","<=50K" +43,"Self-emp-inc",188436,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5013,0,45,"United-States","<=50K" +54,"Private",398212,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",5013,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",256866,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",5013,0,40,"United-States","<=50K" +47,"Private",326857,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"United-States","<=50K" +40,"Private",105936,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",5013,0,20,"United-States","<=50K" +36,"Private",84306,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5013,0,50,"United-States","<=50K" +26,"Private",139098,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5013,0,40,"United-States","<=50K" +49,"Private",82649,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5013,0,45,"United-States","<=50K" +44,"Self-emp-inc",103643,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5013,0,60,"Greece","<=50K" +27,"Private",181667,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",5013,0,46,"Canada","<=50K" +41,"Self-emp-not-inc",29762,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",5013,0,70,"United-States","<=50K" +30,"Private",155343,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"United-States","<=50K" +29,"Private",206351,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"United-States","<=50K" +26,"Private",132661,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",5013,0,40,"United-States","<=50K" +30,"Private",137606,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",5013,0,40,"United-States","<=50K" +35,"Private",37314,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"United-States","<=50K" +30,"Local-gov",346122,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",5013,0,45,"United-States","<=50K" +29,"Private",221366,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5013,0,40,"Germany","<=50K" +46,"Private",276087,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",5013,0,50,"United-States","<=50K" +48,"Self-emp-not-inc",30840,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5013,0,45,"United-States","<=50K" +52,"Private",204322,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",5013,0,40,"United-States","<=50K" +60,"Private",160625,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5013,0,40,"United-States","<=50K" +43,"Private",242488,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",5013,0,40,"United-States","<=50K" +39,"Private",196673,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",5013,0,40,"United-States","<=50K" +31,"Private",356882,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",5013,0,40,"United-States","<=50K" +52,"Federal-gov",192386,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5013,0,40,"United-States","<=50K" +26,"Private",104746,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,60,"United-States","<=50K" +44,"State-gov",150755,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",5013,0,40,"United-States","<=50K" +35,"Private",158046,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",5013,0,70,"United-States","<=50K" +35,"Private",167140,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5013,0,40,"United-States","<=50K" +45,"Federal-gov",56904,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",5013,0,45,"United-States","<=50K" +52,"Local-gov",40641,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"United-States","<=50K" +28,"Self-emp-inc",219705,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5013,0,55,"United-States","<=50K" +54,"Private",147863,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",5013,0,40,"Vietnam","<=50K" +56,"Private",98809,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",5013,0,45,"United-States","<=50K" +48,"Private",248059,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5013,0,45,"United-States","<=50K" +59,"Private",182062,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5013,0,40,"United-States","<=50K" +46,"Private",186820,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",5013,0,40,"United-States","<=50K" +45,"Private",362883,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"United-States","<=50K" +55,"Private",147989,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,52,"United-States","<=50K" +50,"Private",99307,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,45,"United-States","<=50K" +49,"Private",261688,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,60,"United-States","<=50K" +33,"Private",197424,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",5013,0,40,"United-States","<=50K" +51,"Private",99064,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"United-States","<=50K" +42,"Private",230684,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5013,0,40,"United-States","<=50K" +47,"Private",193285,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",5013,0,40,"United-States","<=50K" +32,"Private",343789,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",5013,0,55,"United-States","<=50K" +49,"Private",87928,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",189123,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,50,"United-States","<=50K" +31,"Private",288825,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",5013,0,40,"United-States","<=50K" +52,"State-gov",135388,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"United-States","<=50K" +32,"Local-gov",186784,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",5013,0,45,"United-States","<=50K" +63,"Private",308028,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",5013,0,40,"United-States","<=50K" +39,"Private",219483,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",5013,0,32,"United-States","<=50K" +56,"Private",235826,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"United-States","<=50K" +35,"Private",112077,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",5013,0,40,"United-States","<=50K" +53,"Local-gov",124094,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,35,"United-States","<=50K" +57,"Private",372020,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",5013,0,50,"United-States","<=50K" +29,"Private",133420,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"United-States","<=50K" +47,"Private",185385,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5013,0,24,"United-States","<=50K" +52,"Private",203392,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"United-States","<=50K" +51,"Private",123053,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",5013,0,40,"India","<=50K" +24,"Private",259510,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",5013,0,30,"United-States","<=50K" +37,"Private",177895,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","White","Female",5013,0,40,"United-States","<=50K" +43,"Federal-gov",25005,"Masters",14,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",5013,0,12,"United-States","<=50K" +28,"Private",180928,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",5013,0,55,"United-States","<=50K" +36,"Private",67728,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",5013,0,40,"Italy","<=50K" +49,"Private",66385,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",5013,0,40,"United-States","<=50K" +45,"Local-gov",224474,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",4934,0,50,"United-States",">50K" +40,"Private",116103,"Some-college",10,"Separated","Craft-repair","Unmarried","White","Male",4934,0,47,"United-States",">50K" +37,"Private",118486,"Bachelors",13,"Separated","Prof-specialty","Unmarried","White","Female",4934,0,32,"United-States",">50K" +60,"Federal-gov",237317,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Male",4934,0,40,"United-States",">50K" +52,"Local-gov",187830,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Male",4934,0,36,"United-States",">50K" +43,"Private",334991,"Some-college",10,"Separated","Transport-moving","Unmarried","White","Male",4934,0,51,"United-States",">50K" +43,"Private",104660,"Masters",14,"Widowed","Exec-managerial","Unmarried","White","Male",4934,0,40,"United-States",">50K" +75,"Self-emp-not-inc",231741,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",4931,0,3,"United-States","<=50K" +45,"Federal-gov",170915,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Female",4865,0,40,"United-States","<=50K" +34,"Private",173806,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",4865,0,60,"United-States","<=50K" +34,"Private",92682,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",4865,0,40,"United-States","<=50K" +26,"Local-gov",117833,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",4865,0,35,"United-States","<=50K" +34,"State-gov",154246,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",4865,0,55,"United-States","<=50K" +27,"Federal-gov",105189,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",4865,0,50,"United-States","<=50K" +30,"Private",189759,"Bachelors",13,"Never-married","Transport-moving","Not-in-family","White","Male",4865,0,40,"United-States","<=50K" +36,"Private",116608,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",4865,0,40,"United-States","<=50K" +27,"Private",29732,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",4865,0,36,"United-States","<=50K" +61,"?",226989,"HS-grad",9,"Divorced","?","Not-in-family","White","Male",4865,0,40,"United-States","<=50K" +28,"Private",123147,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",4865,0,40,"United-States","<=50K" +52,"Local-gov",146565,"Assoc-acdm",12,"Divorced","Other-service","Not-in-family","White","Female",4865,0,30,"United-States","<=50K" +37,"Local-gov",48976,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",4865,0,45,"United-States","<=50K" +59,"Private",66356,"7th-8th",4,"Never-married","Farming-fishing","Unmarried","White","Male",4865,0,40,"United-States","<=50K" +32,"Local-gov",230912,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",4865,0,40,"United-States","<=50K" +25,"Private",80312,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",4865,0,40,"United-States","<=50K" +55,"Private",256526,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","White","Male",4865,0,45,"United-States","<=50K" +34,"Self-emp-inc",215382,"Masters",14,"Separated","Prof-specialty","Not-in-family","White","Female",4787,0,40,"United-States",">50K" +64,"State-gov",194894,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",4787,0,40,"United-States",">50K" +51,"Private",142717,"Doctorate",16,"Divorced","Craft-repair","Not-in-family","White","Female",4787,0,60,"United-States",">50K" +40,"Private",45687,"Some-college",10,"Divorced","Other-service","Not-in-family","Black","Male",4787,0,50,"United-States",">50K" +51,"Private",89652,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",4787,0,24,"United-States",">50K" +58,"Private",142076,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Male",4787,0,39,"United-States",">50K" +39,"Self-emp-not-inc",164593,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",4787,0,40,"United-States",">50K" +34,"Self-emp-inc",174215,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",4787,0,45,"France",">50K" +61,"Private",298400,"Bachelors",13,"Divorced","Sales","Not-in-family","Black","Male",4787,0,48,"United-States",">50K" +30,"Private",509500,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",4787,0,45,"United-States",">50K" +58,"Federal-gov",244830,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Male",4787,0,40,"United-States",">50K" +35,"Private",241998,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",4787,0,40,"United-States",">50K" +46,"Local-gov",230979,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",4787,0,25,"United-States",">50K" +52,"Local-gov",194788,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",4787,0,60,"United-States",">50K" +46,"Local-gov",148995,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",4787,0,45,"United-States",">50K" +39,"Private",121590,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Black","Male",4787,0,40,"United-States",">50K" +35,"?",98080,"Prof-school",15,"Never-married","?","Not-in-family","Asian-Pac-Islander","Male",4787,0,45,"Japan",">50K" +38,"Local-gov",194630,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","White","Female",4787,0,43,"United-States",">50K" +49,"Private",287647,"Masters",14,"Divorced","Sales","Not-in-family","White","Male",4787,0,45,"United-States",">50K" +30,"Private",331419,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",4787,0,50,"United-States",">50K" +53,"Private",346871,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Male",4787,0,46,"United-States",">50K" +59,"Local-gov",303455,"Masters",14,"Widowed","Prof-specialty","Unmarried","White","Female",4787,0,60,"United-States",">50K" +52,"State-gov",109600,"Masters",14,"Married-spouse-absent","Exec-managerial","Unmarried","White","Female",4787,0,44,"United-States",">50K" +45,"Private",160647,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",4687,0,35,"United-States",">50K" +42,"Private",210275,"Masters",14,"Divorced","Tech-support","Unmarried","Black","Female",4687,0,35,"United-States",">50K" +39,"Private",148903,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",4687,0,50,"United-States",">50K" +29,"Private",271328,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",4650,0,40,"United-States","<=50K" +31,"Private",231263,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",4650,0,45,"United-States","<=50K" +35,"Self-emp-not-inc",185848,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",4650,0,50,"United-States","<=50K" +36,"Private",208358,"9th",5,"Divorced","Handlers-cleaners","Not-in-family","White","Male",4650,0,56,"United-States","<=50K" +36,"Private",192704,"12th",8,"Never-married","Exec-managerial","Not-in-family","White","Male",4650,0,50,"United-States","<=50K" +42,"Private",259643,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",4650,0,40,"United-States","<=50K" +53,"State-gov",116367,"Some-college",10,"Divorced","Adm-clerical","Other-relative","White","Female",4650,0,40,"United-States","<=50K" +49,"Local-gov",192349,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",4650,0,40,"United-States","<=50K" +39,"Local-gov",116666,"HS-grad",9,"Never-married","Protective-serv","Own-child","Amer-Indian-Eskimo","Male",4650,0,48,"United-States","<=50K" +31,"Private",213002,"12th",8,"Never-married","Sales","Not-in-family","White","Male",4650,0,50,"United-States","<=50K" +30,"Self-emp-inc",124420,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",4650,0,40,"United-States","<=50K" +39,"Private",179481,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Male",4650,0,44,"United-States","<=50K" +25,"Private",231016,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",4650,0,37,"United-States","<=50K" +37,"Local-gov",117760,"Assoc-voc",11,"Never-married","Protective-serv","Not-in-family","White","Male",4650,0,40,"United-States","<=50K" +35,"Private",70447,"Some-college",10,"Never-married","Prof-specialty","Unmarried","Asian-Pac-Islander","Male",4650,0,20,"United-States","<=50K" +39,"Private",101146,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Female",4650,0,40,"United-States","<=50K" +40,"Private",242619,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",4650,0,40,"United-States","<=50K" +42,"Local-gov",125461,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",4650,0,35,"United-States","<=50K" +34,"?",286689,"Masters",14,"Never-married","?","Not-in-family","White","Male",4650,0,30,"United-States","<=50K" +41,"Federal-gov",197069,"Some-college",10,"Married-spouse-absent","Adm-clerical","Not-in-family","Black","Male",4650,0,40,"United-States","<=50K" +35,"Private",276153,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Asian-Pac-Islander","Female",4650,0,40,"United-States","<=50K" +32,"Private",216145,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",4650,0,45,"United-States","<=50K" +42,"Private",367049,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",4650,0,40,"United-States","<=50K" +47,"Private",167159,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",4650,0,40,"United-States","<=50K" +28,"Private",334368,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",4650,0,40,"United-States","<=50K" +23,"Private",151888,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",4650,0,50,"Ireland","<=50K" +55,"Private",145214,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",4650,0,20,"United-States","<=50K" +23,"Private",242912,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",4650,0,40,"United-States","<=50K" +45,"Private",111994,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",4650,0,40,"United-States","<=50K" +43,"Private",227065,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",4650,0,40,"United-States","<=50K" +38,"Private",43770,"Some-college",10,"Separated","Other-service","Not-in-family","White","Female",4650,0,72,"United-States","<=50K" +40,"Private",289748,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",4650,0,48,"United-States","<=50K" +50,"Local-gov",191025,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",4650,0,70,"United-States","<=50K" +33,"Private",319854,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Male",4650,0,35,"United-States","<=50K" +31,"Private",347166,"Some-college",10,"Divorced","Craft-repair","Own-child","White","Male",4650,0,40,"United-States","<=50K" +41,"Private",70645,"Masters",14,"Widowed","Prof-specialty","Not-in-family","White","Female",4650,0,55,"United-States","<=50K" +60,"Private",184183,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",4650,0,40,"United-States","<=50K" +62,"Private",138253,"Masters",14,"Never-married","Handlers-cleaners","Not-in-family","White","Male",4650,0,40,"United-States","<=50K" +50,"Private",138852,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",4650,0,22,"United-States","<=50K" +41,"Private",36699,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",4650,0,40,"United-States","<=50K" +32,"Federal-gov",386877,"Assoc-voc",11,"Never-married","Tech-support","Own-child","Black","Male",4650,0,40,"United-States","<=50K" +57,"Private",182677,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",4508,0,40,"South","<=50K" +32,"Private",112137,"Preschool",1,"Married-civ-spouse","Machine-op-inspct","Wife","Asian-Pac-Islander","Female",4508,0,40,"Cambodia","<=50K" +23,"Private",188409,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",4508,0,25,"United-States","<=50K" +39,"Private",291665,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",4508,0,24,"United-States","<=50K" +22,"Private",200109,"HS-grad",9,"Married-civ-spouse","Priv-house-serv","Wife","White","Female",4508,0,40,"United-States","<=50K" +56,"Private",105363,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4508,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",343061,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",4508,0,40,"Cuba","<=50K" +28,"Private",163265,"9th",5,"Married-civ-spouse","Sales","Husband","White","Male",4508,0,40,"United-States","<=50K" +21,"Self-emp-not-inc",103277,"12th",8,"Married-civ-spouse","Adm-clerical","Wife","White","Female",4508,0,30,"Portugal","<=50K" +34,"Self-emp-not-inc",254304,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",4508,0,90,"United-States","<=50K" +32,"Private",201988,"Prof-school",15,"Married-civ-spouse","Sales","Husband","White","Male",4508,0,40,"?","<=50K" +38,"Private",167440,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",4508,0,40,"United-States","<=50K" +27,"Private",406662,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",4416,0,40,"United-States","<=50K" +25,"Private",272428,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",4416,0,42,"United-States","<=50K" +25,"Private",164938,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",4416,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",114758,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",4416,0,45,"United-States","<=50K" +49,"Private",173115,"10th",6,"Separated","Exec-managerial","Not-in-family","Black","Male",4416,0,99,"United-States","<=50K" +33,"Private",153151,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",4416,0,40,"United-States","<=50K" +22,"Without-pay",302347,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",4416,0,40,"United-States","<=50K" +56,"Private",178033,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Male",4416,0,60,"United-States","<=50K" +34,"Private",154874,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",4416,0,30,"United-States","<=50K" +54,"?",155755,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",4416,0,25,"United-States","<=50K" +25,"Private",148460,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",4416,0,40,"Puerto-Rico","<=50K" +20,"Private",168187,"Some-college",10,"Never-married","Other-service","Other-relative","White","Female",4416,0,25,"United-States","<=50K" +38,"Self-emp-not-inc",120985,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",4386,0,35,"United-States","<=50K" +55,"Private",238638,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",4386,0,40,"United-States",">50K" +40,"Private",144995,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",4386,0,40,"United-States","<=50K" +53,"Private",194259,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",4386,0,40,"United-States",">50K" +55,"Private",387569,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",4386,0,40,"United-States",">50K" +50,"Private",75472,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",4386,0,40,"?","<=50K" +45,"Self-emp-inc",36228,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",4386,0,35,"United-States",">50K" +38,"Private",31069,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",4386,0,40,"United-States",">50K" +53,"Self-emp-not-inc",174102,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4386,0,50,"Greece",">50K" +46,"Private",503923,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",4386,0,40,"United-States",">50K" +42,"Private",255847,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",4386,0,48,"United-States",">50K" +51,"Private",335997,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4386,0,55,"United-States",">50K" +43,"Private",313022,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",4386,0,40,"United-States",">50K" +47,"Local-gov",265097,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",4386,0,40,"United-States",">50K" +51,"Federal-gov",306784,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",4386,0,40,"United-States",">50K" +31,"Private",182237,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",4386,0,45,"United-States",">50K" +30,"Private",110643,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",4386,0,40,"United-States",">50K" +44,"Private",98779,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",4386,0,60,"United-States","<=50K" +29,"Private",144259,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",4386,0,80,"?",">50K" +48,"Private",248164,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",4386,0,50,"United-States",">50K" +51,"Private",123703,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",4386,0,40,"United-States",">50K" +35,"Private",36214,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4386,0,47,"United-States",">50K" +48,"Private",141944,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",4386,0,40,"United-States",">50K" +41,"Private",156566,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4386,0,50,"United-States",">50K" +54,"Self-emp-not-inc",242606,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",4386,0,45,"United-States",">50K" +31,"Private",110554,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",4386,0,40,"United-States",">50K" +44,"Private",120057,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4386,0,45,"United-States",">50K" +51,"Federal-gov",73670,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",4386,0,52,"United-States",">50K" +61,"?",160625,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",4386,0,15,"United-States",">50K" +63,"Private",180911,"11th",7,"Married-civ-spouse","Protective-serv","Husband","White","Male",4386,0,37,"United-States",">50K" +51,"Private",29580,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",4386,0,30,"United-States",">50K" +35,"Private",209214,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",4386,0,35,"United-States",">50K" +52,"Private",204447,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",4386,0,40,"United-States",">50K" +24,"Private",117959,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",4386,0,40,"United-States",">50K" +33,"Private",195576,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4386,0,60,"United-States","<=50K" +44,"Local-gov",241851,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",4386,0,40,"United-States",">50K" +57,"Self-emp-not-inc",291529,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4386,0,13,"United-States",">50K" +47,"Private",329144,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",4386,0,45,"United-States",">50K" +44,"Private",184105,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",4386,0,40,"United-States",">50K" +45,"Private",120724,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4386,0,40,"United-States","<=50K" +37,"Private",219546,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",4386,0,44,"United-States",">50K" +31,"Private",240771,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",4386,0,50,"United-States",">50K" +53,"State-gov",151580,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",4386,0,40,"United-States",">50K" +34,"Private",209691,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",4386,0,50,"United-States",">50K" +29,"Private",51944,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",4386,0,40,"United-States",">50K" +53,"Local-gov",216931,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",4386,0,40,"United-States",">50K" +44,"Local-gov",193425,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",4386,0,40,"United-States",">50K" +48,"Private",449354,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",4386,0,45,"United-States",">50K" +34,"State-gov",177331,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",4386,0,40,"United-States",">50K" +44,"Private",167005,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",4386,0,55,"United-States","<=50K" +29,"Self-emp-not-inc",104423,"Some-college",10,"Married-civ-spouse","Exec-managerial","Other-relative","White","Male",4386,0,45,"United-States",">50K" +51,"Local-gov",349431,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",4386,0,40,"United-States",">50K" +37,"Private",215503,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4386,0,45,"United-States",">50K" +34,"Private",169527,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",4386,0,20,"United-States","<=50K" +40,"Private",70539,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",4386,0,50,"United-States","<=50K" +46,"Private",269652,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",4386,0,38,"United-States",">50K" +37,"Self-emp-not-inc",188563,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4386,0,50,"United-States",">50K" +36,"Self-emp-not-inc",138940,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4386,0,50,"United-States",">50K" +31,"Private",319146,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",4386,0,40,"Mexico",">50K" +53,"Private",70387,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",4386,0,40,"India",">50K" +46,"Self-emp-not-inc",51271,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",4386,0,70,"United-States","<=50K" +32,"Private",123964,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",4386,0,50,"United-States","<=50K" +38,"Private",160808,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",4386,0,48,"United-States","<=50K" +43,"Local-gov",118853,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",4386,0,99,"United-States",">50K" +53,"Private",133219,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",4386,0,30,"United-States",">50K" +45,"Private",294671,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",4386,0,38,"United-States",">50K" +41,"Private",433989,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",4386,0,60,"United-States",">50K" +63,"Private",117473,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",4386,0,40,"United-States",">50K" +42,"Self-emp-not-inc",69333,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",4386,0,80,"United-States",">50K" +40,"Private",132222,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",4386,0,50,"United-States",">50K" +24,"Private",556660,"HS-grad",9,"Never-married","Exec-managerial","Other-relative","White","Male",4101,0,50,"United-States","<=50K" +21,"Private",255957,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",4101,0,40,"United-States","<=50K" +32,"Private",115631,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",4101,0,50,"United-States","<=50K" +56,"Private",191917,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",4101,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",31095,"Some-college",10,"Separated","Farming-fishing","Not-in-family","White","Male",4101,0,60,"United-States","<=50K" +43,"Private",59107,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",4101,0,40,"United-States","<=50K" +31,"Private",369825,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",4101,0,50,"United-States","<=50K" +56,"Private",168625,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Female",4101,0,40,"United-States","<=50K" +23,"Private",211049,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",4101,0,40,"United-States","<=50K" +21,"Private",20728,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",4101,0,40,"United-States","<=50K" +25,"Private",321205,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",4101,0,35,"United-States","<=50K" +31,"Private",188108,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",4101,0,40,"United-States","<=50K" +27,"State-gov",142621,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",4101,0,40,"United-States","<=50K" +37,"Private",143582,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","Other","Female",4101,0,35,"United-States","<=50K" +19,"Private",223648,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",4101,0,48,"United-States","<=50K" +23,"Private",32950,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",4101,0,40,"United-States","<=50K" +28,"Local-gov",135567,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Black","Female",4101,0,60,"United-States","<=50K" +54,"State-gov",137815,"12th",8,"Never-married","Other-service","Own-child","White","Male",4101,0,40,"United-States","<=50K" +36,"Private",108320,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",4101,0,40,"United-States","<=50K" +25,"Private",149943,"HS-grad",9,"Never-married","Other-service","Other-relative","Asian-Pac-Islander","Male",4101,0,60,"?","<=50K" +28,"Private",377869,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",4064,0,25,"United-States","<=50K" +59,"Private",146013,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,40,"United-States","<=50K" +58,"State-gov",110517,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",4064,0,40,"India","<=50K" +43,"Private",149670,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",4064,0,15,"United-States","<=50K" +39,"Private",187046,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,38,"United-States","<=50K" +26,"Private",164018,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,50,"United-States","<=50K" +63,"Private",143098,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,40,"United-States","<=50K" +32,"Local-gov",217296,"HS-grad",9,"Married-civ-spouse","Transport-moving","Wife","White","Female",4064,0,22,"United-States","<=50K" +47,"Private",170850,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",4064,0,60,"United-States","<=50K" +35,"Private",28572,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",4064,0,35,"United-States","<=50K" +38,"Federal-gov",122493,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",4064,0,40,"United-States","<=50K" +52,"Self-emp-inc",177727,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,45,"United-States","<=50K" +32,"Self-emp-not-inc",70985,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",4064,0,40,"United-States","<=50K" +35,"Private",126569,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,40,"United-States","<=50K" +54,"Private",234938,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,55,"United-States","<=50K" +49,"Private",40000,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,44,"United-States","<=50K" +40,"Private",316820,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,40,"United-States","<=50K" +40,"Private",145439,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","Other","Male",4064,0,40,"Mexico","<=50K" +43,"Private",484861,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",4064,0,38,"United-States","<=50K" +31,"Local-gov",176185,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",4064,0,40,"?","<=50K" +50,"Local-gov",50178,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",4064,0,55,"United-States","<=50K" +46,"Private",181810,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",4064,0,40,"United-States","<=50K" +27,"Federal-gov",196386,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",4064,0,40,"El-Salvador","<=50K" +34,"Private",34848,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",4064,0,40,"United-States","<=50K" +61,"Local-gov",180079,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4064,0,40,"United-States","<=50K" +55,"Private",226875,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,40,"United-States","<=50K" +33,"Federal-gov",293550,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","White","Female",4064,0,40,"United-States","<=50K" +31,"?",182191,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",4064,0,30,"Canada","<=50K" +32,"Private",317809,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4064,0,50,"United-States","<=50K" +49,"Private",297884,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",4064,0,50,"United-States","<=50K" +36,"Private",267556,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",4064,0,40,"United-States","<=50K" +42,"Private",195096,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,40,"United-States","<=50K" +30,"Private",281030,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",344480,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",4064,0,40,"United-States","<=50K" +26,"Private",39092,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",4064,0,50,"United-States","<=50K" +47,"Private",178341,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",4064,0,60,"United-States","<=50K" +47,"Private",200471,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",4064,0,40,"United-States","<=50K" +51,"Private",86332,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",4064,0,55,"United-States","<=50K" +28,"Private",294936,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",4064,0,45,"United-States","<=50K" +34,"Local-gov",155781,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",4064,0,50,"United-States","<=50K" +46,"Private",285750,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",4064,0,55,"United-States","<=50K" +45,"Private",288437,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Other","Male",4064,0,40,"United-States","<=50K" +47,"?",174525,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",3942,0,40,"?","<=50K" +41,"Private",187881,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",3942,0,40,"United-States","<=50K" +38,"Private",450924,"12th",8,"Married-civ-spouse","Other-service","Husband","White","Male",3942,0,40,"United-States","<=50K" +29,"Private",184596,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",3942,0,50,"United-States","<=50K" +50,"Private",166220,"Assoc-acdm",12,"Married-civ-spouse","Sales","Wife","White","Female",3942,0,40,"United-States","<=50K" +45,"Private",192835,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",3942,0,40,"United-States","<=50K" +41,"Local-gov",103759,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",3942,0,40,"United-States","<=50K" +23,"Private",209034,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",3942,0,40,"United-States","<=50K" +59,"Private",340591,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",3942,0,40,"United-States","<=50K" +38,"Private",331395,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",3942,0,84,"Portugal","<=50K" +26,"Private",208326,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3942,0,45,"United-States","<=50K" +35,"Private",145704,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",3942,0,35,"United-States","<=50K" +27,"Private",243569,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",3942,0,40,"United-States","<=50K" +61,"?",229744,"1st-4th",2,"Married-civ-spouse","?","Husband","White","Male",3942,0,20,"Mexico","<=50K" +36,"?",53606,"Assoc-voc",11,"Married-civ-spouse","?","Wife","White","Female",3908,0,8,"United-States","<=50K" +45,"Federal-gov",311671,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",3908,0,40,"United-States","<=50K" +32,"Private",187560,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3908,0,40,"United-States","<=50K" +36,"Private",160035,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3908,0,55,"United-States","<=50K" +43,"Private",177905,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",3908,0,40,"United-States","<=50K" +59,"Private",191965,"11th",7,"Married-civ-spouse","Other-service","Wife","White","Female",3908,0,28,"United-States","<=50K" +27,"Private",152683,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",3908,0,35,"United-States","<=50K" +24,"Private",196816,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3908,0,40,"United-States","<=50K" +34,"Private",36069,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3908,0,46,"United-States","<=50K" +31,"Private",213643,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",3908,0,40,"United-States","<=50K" +31,"Private",66278,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",3908,0,40,"United-States","<=50K" +32,"Private",207685,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Wife","Black","Female",3908,0,40,"United-States","<=50K" +42,"Private",424855,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3908,0,40,"United-States","<=50K" +38,"Private",36989,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",3908,0,70,"United-States","<=50K" +58,"Private",244605,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3908,0,40,"United-States","<=50K" +51,"Private",101722,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","Amer-Indian-Eskimo","Male",3908,0,47,"United-States","<=50K" +51,"State-gov",105943,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",3908,0,40,"United-States","<=50K" +44,"Private",107584,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",3908,0,50,"United-States","<=50K" +23,"Private",193586,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",3908,0,40,"United-States","<=50K" +27,"Private",188941,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",3908,0,40,"United-States","<=50K" +35,"Private",143152,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",3908,0,27,"United-States","<=50K" +33,"Private",55699,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",3908,0,40,"United-States","<=50K" +28,"Local-gov",327533,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",3908,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",320744,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",3908,0,45,"United-States","<=50K" +33,"Local-gov",152351,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",3908,0,40,"United-States","<=50K" +21,"Private",163870,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",3908,0,40,"United-States","<=50K" +34,"Private",231043,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",3908,0,45,"United-States","<=50K" +31,"Self-emp-inc",256362,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",3908,0,50,"United-States","<=50K" +51,"Private",312477,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",3908,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",89508,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3908,0,60,"United-States","<=50K" +36,"Self-emp-not-inc",34378,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",3908,0,75,"United-States","<=50K" +58,"Local-gov",212864,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",3908,0,40,"United-States","<=50K" +54,"State-gov",123592,"HS-grad",9,"Separated","Adm-clerical","Unmarried","Black","Female",3887,0,35,"United-States","<=50K" +37,"Private",277022,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","White","Female",3887,0,40,"Nicaragua","<=50K" +28,"Federal-gov",526528,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",3887,0,40,"United-States","<=50K" +32,"State-gov",200469,"Some-college",10,"Never-married","Protective-serv","Unmarried","Black","Female",3887,0,40,"United-States","<=50K" +32,"Private",356689,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Male",3887,0,40,"United-States","<=50K" +32,"Private",269182,"Some-college",10,"Separated","Tech-support","Unmarried","Black","Female",3887,0,40,"United-States","<=50K" +69,"Self-emp-inc",69209,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3818,0,30,"United-States","<=50K" +67,"?",192916,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",3818,0,11,"United-States","<=50K" +65,"Private",113323,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3818,0,40,"United-States","<=50K" +65,"?",178931,"HS-grad",9,"Married-civ-spouse","?","Husband","Amer-Indian-Eskimo","Male",3818,0,40,"United-States","<=50K" +68,"Private",144056,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",3818,0,40,"United-States","<=50K" +77,"Local-gov",177550,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",3818,0,14,"United-States","<=50K" +65,"Self-emp-not-inc",115498,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",3818,0,10,"United-States","<=50K" +37,"Private",758700,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",3781,0,50,"Mexico","<=50K" +20,"Private",34568,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3781,0,35,"United-States","<=50K" +32,"Private",400535,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3781,0,40,"United-States","<=50K" +60,"Private",88055,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3781,0,16,"United-States","<=50K" +50,"Self-emp-not-inc",176867,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3781,0,40,"United-States","<=50K" +58,"Private",298601,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",3781,0,40,"United-States","<=50K" +33,"Private",163110,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",3781,0,40,"United-States","<=50K" +20,"Private",194630,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",3781,0,50,"United-States","<=50K" +21,"?",262280,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",3781,0,40,"United-States","<=50K" +22,"?",154235,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",3781,0,35,"United-States","<=50K" +52,"Private",230657,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",3781,0,40,"Columbia","<=50K" +48,"Private",373366,"1st-4th",2,"Married-civ-spouse","Farming-fishing","Husband","White","Male",3781,0,50,"Mexico","<=50K" +35,"Private",538583,"11th",7,"Separated","Transport-moving","Not-in-family","Black","Male",3674,0,40,"United-States","<=50K" +33,"Private",40681,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",3674,0,16,"United-States","<=50K" +36,"Private",130926,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",3674,0,40,"United-States","<=50K" +50,"Federal-gov",166419,"11th",7,"Never-married","Sales","Not-in-family","Black","Female",3674,0,40,"United-States","<=50K" +23,"Private",193090,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",3674,0,40,"United-States","<=50K" +64,"?",239529,"11th",7,"Widowed","?","Not-in-family","White","Female",3674,0,35,"United-States","<=50K" +21,"Private",148211,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",3674,0,50,"United-States","<=50K" +25,"Private",40512,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",3674,0,30,"United-States","<=50K" +44,"Private",408717,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",3674,0,50,"United-States","<=50K" +41,"Self-emp-not-inc",89942,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",3674,0,45,"United-States","<=50K" +29,"Local-gov",419722,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",3674,0,40,"United-States","<=50K" +46,"Private",270693,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",3674,0,30,"United-States","<=50K" +32,"Private",426467,"1st-4th",2,"Never-married","Craft-repair","Not-in-family","White","Male",3674,0,40,"Guatemala","<=50K" +24,"Private",103064,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",3674,0,40,"United-States","<=50K" +61,"Private",128848,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3471,0,40,"United-States","<=50K" +74,"?",340939,"9th",5,"Married-civ-spouse","?","Husband","White","Male",3471,0,40,"United-States","<=50K" +63,"Private",273010,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",3471,0,40,"United-States","<=50K" +64,"Local-gov",237379,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",3471,0,40,"United-States","<=50K" +73,"Private",242769,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3471,0,40,"England","<=50K" +37,"Private",259846,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",3471,0,40,"United-States","<=50K" +72,"Private",116640,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3471,0,20,"United-States","<=50K" +66,"Federal-gov",47358,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",3471,0,40,"United-States","<=50K" +39,"?",157443,"Masters",14,"Married-civ-spouse","?","Wife","Asian-Pac-Islander","Female",3464,0,40,"?","<=50K" +39,"Private",129597,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",3464,0,40,"United-States","<=50K" +38,"Private",203836,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",3464,0,40,"Columbia","<=50K" +32,"Private",209103,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3464,0,40,"United-States","<=50K" +40,"?",428584,"HS-grad",9,"Married-civ-spouse","?","Wife","Black","Female",3464,0,20,"United-States","<=50K" +41,"State-gov",227734,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",3464,0,40,"United-States","<=50K" +36,"?",216256,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",3464,0,30,"United-States","<=50K" +26,"Private",302097,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3464,0,48,"United-States","<=50K" +29,"Self-emp-not-inc",70604,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",3464,0,40,"United-States","<=50K" +38,"State-gov",364958,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",3464,0,40,"United-States","<=50K" +27,"Private",267325,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",3464,0,40,"United-States","<=50K" +39,"State-gov",42186,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Asian-Pac-Islander","Female",3464,0,20,"United-States","<=50K" +54,"Private",28683,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",3464,0,40,"United-States","<=50K" +37,"Private",212512,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3464,0,50,"United-States","<=50K" +31,"Private",149507,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",3464,0,38,"United-States","<=50K" +38,"Self-emp-not-inc",184456,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",3464,0,80,"Italy","<=50K" +31,"Local-gov",209103,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",3464,0,45,"United-States","<=50K" +46,"Private",248059,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3464,0,40,"United-States","<=50K" +37,"Private",236990,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3464,0,40,"United-States","<=50K" +30,"Private",151001,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3464,0,40,"Mexico","<=50K" +32,"Private",184440,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3464,0,40,"United-States","<=50K" +36,"Private",115360,"10th",6,"Married-civ-spouse","Machine-op-inspct","Own-child","White","Female",3464,0,40,"United-States","<=50K" +55,"Private",141727,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",3464,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",280169,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",3456,0,8,"United-States","<=50K" +75,"Self-emp-not-inc",31428,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",3456,0,40,"United-States","<=50K" +71,"?",250263,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",3432,0,30,"United-States","<=50K" +70,"Private",278139,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",3432,0,40,"United-States","<=50K" +71,"?",108390,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",3432,0,20,"United-States","<=50K" +66,"Local-gov",179285,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3432,0,20,"United-States","<=50K" +25,"?",262245,"Assoc-voc",11,"Never-married","?","Own-child","White","Female",3418,0,40,"United-States","<=50K" +33,"Private",207267,"10th",6,"Separated","Other-service","Unmarried","White","Female",3418,0,35,"United-States","<=50K" +29,"Private",286452,"Assoc-acdm",12,"Divorced","Sales","Unmarried","White","Female",3418,0,40,"United-States","<=50K" +25,"Private",195914,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",3418,0,30,"United-States","<=50K" +29,"?",339100,"11th",7,"Divorced","?","Not-in-family","White","Female",3418,0,48,"United-States","<=50K" +27,"State-gov",249362,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",3411,0,40,"United-States","<=50K" +44,"Private",193459,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",3411,0,40,"United-States","<=50K" +62,"?",225652,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",3411,0,50,"United-States","<=50K" +39,"Private",297847,"9th",5,"Married-civ-spouse","Other-service","Wife","Black","Female",3411,0,34,"United-States","<=50K" +62,"?",94931,"Assoc-voc",11,"Married-civ-spouse","?","Husband","White","Male",3411,0,40,"United-States","<=50K" +51,"Private",147954,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",3411,0,38,"United-States","<=50K" +40,"Self-emp-not-inc",55363,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3411,0,40,"United-States","<=50K" +29,"Private",233421,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",3411,0,45,"United-States","<=50K" +47,"Local-gov",138342,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",3411,0,40,"El-Salvador","<=50K" +37,"Private",219546,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Other-relative","White","Male",3411,0,47,"United-States","<=50K" +30,"Private",72887,"HS-grad",9,"Married-civ-spouse","Craft-repair","Own-child","Asian-Pac-Islander","Male",3411,0,40,"United-States","<=50K" +50,"Private",158948,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",3411,0,40,"United-States","<=50K" +44,"State-gov",96249,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3411,0,40,"United-States","<=50K" +28,"Private",190836,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3411,0,40,"United-States","<=50K" +26,"Private",255193,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3411,0,40,"United-States","<=50K" +41,"Private",439919,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",3411,0,40,"Mexico","<=50K" +61,"Private",180382,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",3411,0,45,"United-States","<=50K" +46,"Private",171228,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3411,0,35,"Guatemala","<=50K" +56,"Self-emp-not-inc",201318,"9th",5,"Married-civ-spouse","Exec-managerial","Other-relative","White","Male",3411,0,50,"Columbia","<=50K" +64,"?",146272,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",3411,0,15,"United-States","<=50K" +38,"Self-emp-not-inc",163204,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3411,0,25,"United-States","<=50K" +55,"Private",132887,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",3411,0,40,"Jamaica","<=50K" +29,"Private",413297,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3411,0,70,"Mexico","<=50K" +33,"Private",60567,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3411,0,40,"United-States","<=50K" +51,"Private",122159,"Some-college",10,"Widowed","Prof-specialty","Not-in-family","White","Female",3325,0,40,"United-States","<=50K" +25,"Private",221757,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",3325,0,45,"United-States","<=50K" +49,"Private",50282,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",3325,0,45,"United-States","<=50K" +45,"Federal-gov",273194,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","Black","Male",3325,0,40,"United-States","<=50K" +45,"Private",330535,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +34,"Private",182177,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",3325,0,35,"United-States","<=50K" +24,"Private",182812,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",3325,0,52,"Dominican-Republic","<=50K" +43,"Private",218558,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +58,"Private",140363,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",3325,0,30,"United-States","<=50K" +26,"Federal-gov",95806,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +29,"Private",159768,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",3325,0,40,"Ecuador","<=50K" +47,"Self-emp-inc",175958,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",3325,0,60,"United-States","<=50K" +47,"Private",184005,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","Amer-Indian-Eskimo","Female",3325,0,45,"United-States","<=50K" +48,"Private",348144,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",3325,0,53,"United-States","<=50K" +26,"Private",120238,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +31,"State-gov",188900,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",3325,0,35,"United-States","<=50K" +22,"Private",310152,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +38,"Private",51100,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +21,"Private",189888,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",3325,0,60,"United-States","<=50K" +60,"Private",128367,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Male",3325,0,42,"United-States","<=50K" +51,"Local-gov",209320,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +31,"Private",193231,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",3325,0,60,"United-States","<=50K" +29,"Private",157612,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",3325,0,45,"United-States","<=50K" +49,"Private",323798,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",3325,0,50,"United-States","<=50K" +35,"Private",246449,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",3325,0,50,"United-States","<=50K" +31,"Private",286406,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +28,"Private",230856,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Black","Female",3325,0,50,"United-States","<=50K" +48,"Private",247685,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +40,"Private",222011,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",3325,0,40,"United-States","<=50K" +42,"Private",397346,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +33,"Private",460408,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",3325,0,50,"United-States","<=50K" +41,"Private",152742,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","White","Female",3325,0,40,"United-States","<=50K" +40,"Private",168071,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +27,"Private",314240,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +36,"Private",32709,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",3325,0,45,"United-States","<=50K" +25,"Private",247025,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",3325,0,48,"United-States","<=50K" +25,"Private",361493,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +25,"Private",167835,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",3325,0,40,"United-States","<=50K" +27,"Local-gov",66824,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Amer-Indian-Eskimo","Female",3325,0,43,"United-States","<=50K" +27,"Private",287476,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",3325,0,40,"United-States","<=50K" +26,"Private",108019,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",3325,0,40,"United-States","<=50K" +48,"Self-emp-not-inc",108557,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",3325,0,60,"United-States","<=50K" +46,"Self-emp-inc",256909,"HS-grad",9,"Married-spouse-absent","Farming-fishing","Not-in-family","White","Male",3325,0,45,"United-States","<=50K" +44,"Self-emp-not-inc",185057,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",3325,0,40,"United-States","<=50K" +30,"Private",195576,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",3325,0,50,"United-States","<=50K" +23,"Private",91733,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Female",3325,0,40,"United-States","<=50K" +46,"Private",65353,"Some-college",10,"Divorced","Transport-moving","Own-child","White","Male",3325,0,55,"United-States","<=50K" +29,"Private",114158,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",3325,0,10,"United-States","<=50K" +42,"Local-gov",246862,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Female",3325,0,40,"United-States","<=50K" +41,"Private",320744,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",3325,0,50,"United-States","<=50K" +52,"Private",114228,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",3325,0,40,"United-States","<=50K" +46,"State-gov",327786,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","White","Female",3325,0,42,"United-States","<=50K" +59,"Private",152968,"Some-college",10,"Separated","Adm-clerical","Other-relative","White","Male",3325,0,40,"United-States","<=50K" +67,"Self-emp-not-inc",116057,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",3273,0,16,"United-States","<=50K" +66,"Federal-gov",38621,"Assoc-voc",11,"Widowed","Other-service","Unmarried","Black","Female",3273,0,40,"United-States","<=50K" +66,"Local-gov",376506,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Female",3273,0,40,"United-States","<=50K" +73,"Federal-gov",127858,"Some-college",10,"Widowed","Tech-support","Not-in-family","White","Female",3273,0,40,"United-States","<=50K" +68,"Private",191581,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",3273,0,40,"United-States","<=50K" +69,"Self-emp-not-inc",92472,"10th",6,"Married-spouse-absent","Farming-fishing","Not-in-family","White","Male",3273,0,45,"United-States","<=50K" +54,"Private",183611,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",3137,0,50,"United-States","<=50K" +31,"Private",247328,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3137,0,40,"Mexico","<=50K" +45,"Self-emp-not-inc",239093,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Amer-Indian-Eskimo","Male",3137,0,40,"United-States","<=50K" +38,"Private",170020,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3137,0,45,"United-States","<=50K" +37,"Private",195148,"HS-grad",9,"Married-civ-spouse","Craft-repair","Own-child","White","Male",3137,0,40,"United-States","<=50K" +41,"Private",282948,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","Black","Male",3137,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",73199,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",3137,0,77,"Vietnam","<=50K" +64,"Local-gov",202984,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3137,0,40,"United-States","<=50K" +47,"Local-gov",80282,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3137,0,40,"United-States","<=50K" +29,"Private",183627,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3137,0,48,"Ireland","<=50K" +57,"Self-emp-not-inc",57071,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",3137,0,40,"United-States","<=50K" +25,"Private",335005,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",3137,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",118259,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3137,0,60,"United-States","<=50K" +28,"Private",66777,"Assoc-voc",11,"Married-civ-spouse","Other-service","Other-relative","White","Female",3137,0,40,"United-States","<=50K" +45,"Private",273194,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",3137,0,35,"United-States","<=50K" +37,"Private",78928,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",3137,0,40,"United-States","<=50K" +44,"Private",889965,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Wife","White","Female",3137,0,30,"United-States","<=50K" +39,"Private",258276,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",3137,0,40,"?","<=50K" +53,"Private",150980,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3137,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",194636,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3137,0,50,"United-States","<=50K" +50,"Private",266945,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",3137,0,40,"El-Salvador","<=50K" +50,"Private",160572,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3137,0,47,"United-States","<=50K" +51,"Private",282549,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",3137,0,40,"United-States","<=50K" +60,"Private",121319,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3137,0,40,"Poland","<=50K" +35,"Private",180686,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3137,0,40,"United-States","<=50K" +40,"Local-gov",153489,"HS-grad",9,"Married-civ-spouse","Other-service","Other-relative","White","Male",3137,0,40,"United-States","<=50K" +42,"Private",125280,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3137,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",183735,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3137,0,30,"United-States","<=50K" +60,"Self-emp-not-inc",95445,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",3137,0,46,"United-States","<=50K" +31,"Self-emp-not-inc",265807,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3137,0,50,"United-States","<=50K" +52,"Local-gov",30118,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",3137,0,42,"United-States","<=50K" +36,"Self-emp-not-inc",179896,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",3137,0,40,"United-States","<=50K" +36,"Private",245090,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",3137,0,50,"El-Salvador","<=50K" +38,"Self-emp-not-inc",245372,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3137,0,50,"United-States","<=50K" +30,"Self-emp-not-inc",113838,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",3137,0,60,"Germany","<=50K" +31,"Private",109055,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",3137,0,45,"United-States","<=50K" +46,"Self-emp-not-inc",101722,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3137,0,40,"United-States","<=50K" +33,"Private",169879,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3103,0,47,"United-States",">50K" +37,"Private",186934,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3103,0,44,"United-States",">50K" +50,"Private",767403,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3103,0,40,"United-States",">50K" +41,"Private",118212,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,40,"United-States",">50K" +26,"Private",167350,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",3103,0,40,"United-States",">50K" +51,"Private",120173,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,50,"United-States",">50K" +33,"Private",155343,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,40,"United-States",">50K" +36,"Private",24106,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,40,"United-States",">50K" +39,"Private",127772,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,44,"United-States",">50K" +51,"Private",237735,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",3103,0,40,"United-States",">50K" +36,"Private",131239,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3103,0,45,"United-States",">50K" +48,"Private",235646,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,40,"United-States",">50K" +32,"Private",34104,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,55,"United-States",">50K" +50,"Private",71417,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,40,"United-States",">50K" +50,"Private",69345,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",3103,0,55,"United-States",">50K" +41,"Self-emp-not-inc",120539,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3103,0,40,"United-States",">50K" +52,"Private",99307,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,48,"United-States",">50K" +44,"Private",152629,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",3103,0,40,"United-States",">50K" +56,"Private",176118,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,40,"United-States",">50K" +37,"Self-emp-inc",39089,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,50,"United-States",">50K" +35,"Self-emp-not-inc",181705,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,40,"United-States",">50K" +34,"?",353881,"Assoc-voc",11,"Married-civ-spouse","?","Husband","White","Male",3103,0,60,"United-States",">50K" +62,"Private",121319,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3103,0,40,"United-States",">50K" +43,"Private",115323,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,40,"United-States",">50K" +28,"Private",215955,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,40,"United-States",">50K" +43,"Private",99212,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,48,"United-States",">50K" +57,"Private",298507,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3103,0,40,"United-States",">50K" +47,"Private",340982,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",3103,0,40,"Philippines",">50K" +50,"Private",158294,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",3103,0,40,"United-States",">50K" +33,"Self-emp-not-inc",58702,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",3103,0,50,"United-States",">50K" +54,"Private",139703,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,40,"Germany",">50K" +47,"Private",33710,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,60,"United-States",">50K" +33,"Private",150570,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3103,0,43,"United-States",">50K" +52,"Private",229983,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",3103,0,30,"United-States",">50K" +39,"Private",306646,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,50,"United-States",">50K" +55,"Private",105582,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",3103,0,40,"United-States",">50K" +57,"Private",211804,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3103,0,50,"United-States",">50K" +40,"Private",220977,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",3103,0,40,"India",">50K" +60,"State-gov",194252,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",3103,0,40,"United-States",">50K" +26,"Local-gov",242464,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",3103,0,40,"United-States",">50K" +36,"Private",181382,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3103,0,40,"United-States",">50K" +32,"Private",205152,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,40,"United-States",">50K" +39,"Self-emp-inc",336226,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,60,"United-States",">50K" +51,"Self-emp-not-inc",276456,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,30,"United-States",">50K" +27,"Private",221366,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3103,0,50,"United-States",">50K" +41,"State-gov",293485,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",3103,0,40,"United-States",">50K" +61,"Private",160942,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,50,"United-States","<=50K" +38,"Private",383239,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,40,"United-States",">50K" +40,"Self-emp-not-inc",167081,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,50,"United-States","<=50K" +43,"Private",358199,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,40,"United-States",">50K" +46,"Private",33842,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",3103,0,40,"United-States",">50K" +54,"Private",169719,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,40,"United-States",">50K" +36,"Private",58343,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",3103,0,42,"United-States",">50K" +49,"Private",54772,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,45,"United-States",">50K" +52,"Private",210736,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,55,"United-States",">50K" +55,"Private",101468,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,40,"United-States",">50K" +38,"Self-emp-not-inc",146042,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",3103,0,60,"United-States",">50K" +39,"Private",280570,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,50,"United-States",">50K" +59,"Private",258579,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",3103,0,35,"United-States",">50K" +34,"Private",175856,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,55,"United-States",">50K" +42,"Private",78765,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,45,"United-States",">50K" +46,"Private",423222,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,60,"United-States",">50K" +53,"Self-emp-not-inc",159876,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",3103,0,72,"United-States","<=50K" +51,"Self-emp-not-inc",156802,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",3103,0,60,"United-States",">50K" +34,"Private",198265,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",3103,0,40,"United-States",">50K" +35,"Self-emp-not-inc",37778,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",3103,0,55,"United-States","<=50K" +51,"Private",145409,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,48,"United-States",">50K" +50,"Self-emp-not-inc",156951,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3103,0,40,"United-States",">50K" +55,"Self-emp-not-inc",322691,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,55,"United-States",">50K" +37,"Private",105803,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,45,"United-States",">50K" +48,"Private",188432,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3103,0,46,"United-States",">50K" +25,"Self-emp-not-inc",259299,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,50,"United-States",">50K" +39,"Private",49020,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,48,"United-States",">50K" +45,"Private",168598,"12th",8,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",3103,0,40,"United-States",">50K" +45,"Self-emp-not-inc",118081,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",3103,0,42,"United-States","<=50K" +46,"Private",186172,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3103,0,40,"United-States",">50K" +28,"?",303674,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",3103,0,20,"United-States","<=50K" +18,"Private",184016,"HS-grad",9,"Married-civ-spouse","Priv-house-serv","Not-in-family","White","Female",3103,0,40,"United-States","<=50K" +46,"Private",31432,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",3103,0,52,"United-States",">50K" +34,"Private",99872,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",3103,0,40,"India",">50K" +30,"Private",114912,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,60,"United-States",">50K" +25,"Private",353795,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",3103,0,40,"United-States",">50K" +56,"Private",89922,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",3103,0,45,"United-States",">50K" +44,"Private",124747,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",3103,0,40,"United-States",">50K" +29,"Private",278637,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",3103,0,45,"United-States",">50K" +61,"?",71467,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",3103,0,40,"United-States",">50K" +46,"Self-emp-inc",120902,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",3103,0,37,"United-States",">50K" +30,"Private",101345,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",3103,0,55,"United-States",">50K" +46,"Federal-gov",33794,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",3103,0,40,"United-States",">50K" +44,"Private",277488,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",3103,0,40,"United-States",">50K" +60,"Self-emp-not-inc",187794,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",3103,0,60,"United-States",">50K" +45,"Private",179659,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,40,"United-States",">50K" +53,"Private",53197,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",3103,0,40,"United-States",">50K" +55,"Local-gov",143949,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",3103,0,45,"United-States",">50K" +41,"Private",167106,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",3103,0,35,"Philippines",">50K" +30,"Private",345522,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",3103,0,70,"United-States",">50K" +37,"Private",377798,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",3103,0,40,"United-States",">50K" +69,"Private",108196,"9th",5,"Never-married","Craft-repair","Other-relative","White","Male",2993,0,40,"United-States","<=50K" +70,"?",158642,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",2993,0,20,"United-States","<=50K" +40,"Local-gov",50442,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Amer-Indian-Eskimo","Female",2977,0,35,"United-States","<=50K" +40,"Private",197923,"Bachelors",13,"Never-married","Adm-clerical","Unmarried","Black","Female",2977,0,40,"United-States","<=50K" +35,"State-gov",172475,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Female",2977,0,45,"United-States","<=50K" +34,"Private",269723,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",2977,0,50,"United-States","<=50K" +36,"Private",275653,"7th-8th",4,"Married-spouse-absent","Machine-op-inspct","Unmarried","White","Female",2977,0,40,"Puerto-Rico","<=50K" +39,"Private",160728,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",2977,0,40,"United-States","<=50K" +32,"Private",116055,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",2977,0,35,"United-States","<=50K" +42,"State-gov",109462,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","Black","Female",2977,0,40,"United-States","<=50K" +78,"Private",182977,"HS-grad",9,"Widowed","Other-service","Not-in-family","Black","Female",2964,0,40,"United-States","<=50K" +71,"Private",157909,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",2964,0,60,"United-States","<=50K" +69,"Private",370888,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Female",2964,0,6,"Germany","<=50K" +69,"Private",159522,"7th-8th",4,"Divorced","Machine-op-inspct","Unmarried","Black","Female",2964,0,40,"United-States","<=50K" +79,"Private",172220,"7th-8th",4,"Widowed","Priv-house-serv","Not-in-family","White","Female",2964,0,30,"United-States","<=50K" +66,"?",186032,"Assoc-voc",11,"Widowed","?","Not-in-family","White","Female",2964,0,30,"United-States","<=50K" +70,"?",149040,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",2964,0,12,"United-States","<=50K" +90,"Self-emp-not-inc",82628,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",2964,0,12,"United-States","<=50K" +69,"?",107575,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",2964,0,35,"United-States","<=50K" +51,"Private",120914,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",2961,0,40,"United-States","<=50K" +62,"?",302142,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",2961,0,30,"United-States","<=50K" +20,"Private",279538,"11th",7,"Married-civ-spouse","Handlers-cleaners","Other-relative","White","Male",2961,0,35,"United-States","<=50K" +66,"Private",116468,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",2936,0,20,"United-States","<=50K" +81,"Self-emp-inc",247232,"10th",6,"Married-civ-spouse","Exec-managerial","Wife","White","Female",2936,0,28,"United-States","<=50K" +58,"Private",407138,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2936,0,50,"Mexico","<=50K" +59,"Private",108496,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",2907,0,40,"United-States","<=50K" +26,"Private",48718,"10th",6,"Never-married","Adm-clerical","Not-in-family","White","Female",2907,0,40,"United-States","<=50K" +23,"Private",55674,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","White","Female",2907,0,40,"United-States","<=50K" +36,"Private",544686,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",2907,0,40,"Nicaragua","<=50K" +26,"Private",116044,"11th",7,"Separated","Craft-repair","Other-relative","White","Male",2907,0,50,"United-States","<=50K" +56,"Private",266091,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",2907,0,52,"Cuba","<=50K" +31,"Private",511289,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",2907,0,99,"United-States","<=50K" +22,"Private",385077,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",2907,0,40,"United-States","<=50K" +23,"?",138768,"Bachelors",13,"Never-married","?","Own-child","White","Male",2907,0,40,"United-States","<=50K" +25,"Private",104993,"9th",5,"Never-married","Handlers-cleaners","Own-child","Black","Male",2907,0,40,"United-States","<=50K" +18,"Private",225859,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",2907,0,30,"United-States","<=50K" +59,"Private",284834,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",2885,0,30,"United-States","<=50K" +41,"Private",187821,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2885,0,40,"United-States","<=50K" +35,"Private",174856,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",2885,0,40,"United-States","<=50K" +56,"Private",286487,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",2885,0,45,"United-States","<=50K" +47,"Self-emp-inc",483596,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",2885,0,32,"United-States","<=50K" +35,"Private",306678,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2885,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",285020,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",2885,0,40,"United-States","<=50K" +56,"State-gov",54260,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",2885,0,40,"China","<=50K" +55,"?",216941,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",2885,0,40,"United-States","<=50K" +27,"Private",165365,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",2885,0,40,"Laos","<=50K" +22,"Private",31387,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Own-child","Amer-Indian-Eskimo","Female",2885,0,25,"United-States","<=50K" +48,"Private",118889,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",2885,0,15,"United-States","<=50K" +27,"Private",57052,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",2885,0,40,"United-States","<=50K" +34,"?",205256,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",2885,0,80,"United-States","<=50K" +47,"Private",133969,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",2885,0,65,"Japan","<=50K" +26,"Private",345405,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",2885,0,40,"United-States","<=50K" +61,"Local-gov",35001,"7th-8th",4,"Married-civ-spouse","Adm-clerical","Husband","White","Male",2885,0,40,"United-States","<=50K" +42,"Self-emp-inc",23813,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",2885,0,30,"United-States","<=50K" +25,"Private",120238,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",2885,0,43,"United-States","<=50K" +28,"Private",148429,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2885,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",101709,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",2885,0,40,"United-States","<=50K" +42,"Private",319016,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",2885,0,45,"United-States","<=50K" +50,"Private",108933,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",2885,0,40,"United-States","<=50K" +24,"Private",437666,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",2885,0,50,"United-States","<=50K" +27,"Private",358636,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",2829,0,70,"United-States","<=50K" +38,"Private",234962,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",2829,0,30,"Mexico","<=50K" +35,"Private",356838,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",2829,0,55,"Poland","<=50K" +26,"Private",182178,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",2829,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",31848,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",2829,0,90,"United-States","<=50K" +39,"Private",84954,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",2829,0,65,"United-States","<=50K" +36,"Private",103323,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2829,0,40,"United-States","<=50K" +40,"Private",144594,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",2829,0,40,"United-States","<=50K" +32,"Private",183811,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",2829,0,40,"United-States","<=50K" +41,"Private",150533,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",2829,0,40,"United-States","<=50K" +25,"Private",104097,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",2829,0,60,"United-States","<=50K" +29,"Private",170301,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",2829,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",77146,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",2829,0,45,"United-States","<=50K" +62,"Private",238913,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",2829,0,24,"United-States","<=50K" +39,"Private",231141,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2829,0,40,"United-States","<=50K" +30,"Private",130021,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",2829,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",108435,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",2829,0,30,"United-States","<=50K" +43,"Private",154210,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",2829,0,60,"China","<=50K" +47,"Self-emp-not-inc",237731,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",2829,0,65,"United-States","<=50K" +31,"Private",156763,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",2829,0,40,"United-States","<=50K" +34,"Private",340917,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",2829,0,50,"?","<=50K" +27,"Private",215955,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",2829,0,40,"United-States","<=50K" +40,"Private",27821,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",2829,0,40,"United-States","<=50K" +45,"Private",213140,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",2829,0,40,"United-States","<=50K" +28,"Private",416577,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",2829,0,40,"United-States","<=50K" +61,"Self-emp-inc",171831,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",2829,0,45,"United-States","<=50K" +41,"Private",104892,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",2829,0,40,"United-States","<=50K" +29,"Private",157308,"11th",7,"Married-civ-spouse","Handlers-cleaners","Wife","Asian-Pac-Islander","Female",2829,0,14,"Philippines","<=50K" +62,"Local-gov",203525,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",2829,0,40,"United-States","<=50K" +53,"Private",257940,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2829,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",31478,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",2829,0,60,"United-States","<=50K" +75,"?",248833,"HS-grad",9,"Married-AF-spouse","?","Wife","White","Female",2653,0,14,"United-States","<=50K" +70,"Private",216390,"9th",5,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",2653,0,40,"United-States","<=50K" +70,"Self-emp-not-inc",139889,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",2653,0,70,"United-States","<=50K" +75,"Private",104896,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",2653,0,20,"United-States","<=50K" +90,"Local-gov",214594,"7th-8th",4,"Married-civ-spouse","Protective-serv","Husband","White","Male",2653,0,40,"United-States","<=50K" +24,"Private",296045,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",2635,0,38,"United-States","<=50K" +29,"Local-gov",30069,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",2635,0,40,"United-States","<=50K" +39,"Private",326342,"11th",7,"Married-civ-spouse","Other-service","Husband","Black","Male",2635,0,37,"United-States","<=50K" +33,"Private",133503,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",2635,0,16,"United-States","<=50K" +37,"Self-emp-not-inc",192251,"10th",6,"Married-civ-spouse","Other-service","Wife","White","Female",2635,0,40,"United-States","<=50K" +54,"?",31588,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",2635,0,40,"United-States","<=50K" +64,"Self-emp-inc",213574,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",2635,0,10,"United-States","<=50K" +39,"Private",117166,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2635,0,40,"United-States","<=50K" +64,"Private",116084,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",2635,0,40,"United-States","<=50K" +64,"Self-emp-not-inc",159938,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",2635,0,24,"Italy","<=50K" +35,"Self-emp-not-inc",241469,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",2635,0,30,"United-States","<=50K" +22,"Private",240817,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",2597,0,40,"United-States","<=50K" +25,"Private",186925,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",2597,0,48,"United-States","<=50K" +26,"Private",262617,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",2597,0,40,"United-States","<=50K" +21,"Private",203924,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",2597,0,45,"United-States","<=50K" +19,"Private",38294,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",2597,0,40,"United-States","<=50K" +25,"Private",179953,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",2597,0,31,"United-States","<=50K" +60,"Private",163729,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",2597,0,40,"United-States","<=50K" +26,"Private",456618,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",2597,0,40,"United-States","<=50K" +25,"Private",164229,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",2597,0,40,"United-States","<=50K" +24,"Private",103277,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",2597,0,40,"United-States","<=50K" +32,"Private",168138,"Assoc-acdm",12,"Divorced","Sales","Not-in-family","White","Male",2597,0,48,"United-States","<=50K" +53,"Private",113176,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",2597,0,40,"United-States","<=50K" +26,"Private",151551,"Some-college",10,"Separated","Sales","Own-child","Amer-Indian-Eskimo","Male",2597,0,48,"United-States","<=50K" +25,"State-gov",99076,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",2597,0,50,"United-States","<=50K" +32,"Private",79870,"Some-college",10,"Married-civ-spouse","Exec-managerial","Own-child","White","Female",2597,0,40,"Japan","<=50K" +23,"Private",160951,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",2597,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",153356,"HS-grad",9,"Divorced","Sales","Not-in-family","Black","Male",2597,0,55,"United-States","<=50K" +49,"Private",83622,"Assoc-acdm",12,"Separated","Adm-clerical","Not-in-family","White","Female",2597,0,40,"United-States","<=50K" +23,"Private",239663,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",2597,0,50,"United-States","<=50K" +25,"Private",222539,"10th",6,"Never-married","Transport-moving","Not-in-family","White","Male",2597,0,50,"United-States","<=50K" +40,"Private",82465,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2580,0,40,"United-States","<=50K" +37,"Private",34378,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",2580,0,60,"United-States","<=50K" +28,"Private",212091,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2580,0,40,"United-States","<=50K" +22,"Self-emp-inc",269583,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",2580,0,40,"United-States","<=50K" +63,"Private",133144,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",2580,0,20,"United-States","<=50K" +24,"Private",141113,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",2580,0,40,"United-States","<=50K" +30,"Private",326199,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",2580,0,40,"United-States","<=50K" +27,"Private",198188,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",2580,0,45,"United-States","<=50K" +55,"Private",154580,"10th",6,"Married-civ-spouse","Other-service","Husband","Black","Male",2580,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",144071,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",2580,0,15,"El-Salvador","<=50K" +40,"Private",367533,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2580,0,40,"United-States","<=50K" +64,"Private",75577,"7th-8th",4,"Married-civ-spouse","Adm-clerical","Husband","White","Male",2580,0,50,"United-States","<=50K" +69,"Private",165017,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","White","Male",2538,0,40,"United-States","<=50K" +23,"Private",211046,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",2463,0,40,"United-States","<=50K" +26,"State-gov",203279,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",2463,0,50,"India","<=50K" +48,"Private",161187,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",2463,0,40,"United-States","<=50K" +34,"Private",394447,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",2463,0,50,"France","<=50K" +36,"Private",100681,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",2463,0,40,"United-States","<=50K" +34,"Private",112820,"HS-grad",9,"Separated","Handlers-cleaners","Not-in-family","White","Male",2463,0,40,"United-States","<=50K" +31,"Private",194293,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",2463,0,38,"United-States","<=50K" +24,"Private",229393,"11th",7,"Never-married","Farming-fishing","Unmarried","White","Male",2463,0,40,"United-States","<=50K" +28,"Private",54042,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Female",2463,0,35,"United-States","<=50K" +26,"Private",333677,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",2463,0,35,"United-States","<=50K" +30,"Private",139012,"Assoc-voc",11,"Never-married","Adm-clerical","Other-relative","Asian-Pac-Islander","Male",2463,0,40,"Vietnam","<=50K" +61,"Private",149981,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",2414,0,5,"United-States","<=50K" +67,"Self-emp-not-inc",127543,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",2414,0,80,"United-States","<=50K" +67,"?",188903,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",2414,0,40,"United-States","<=50K" +68,"Self-emp-not-inc",195881,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",2414,0,40,"United-States","<=50K" +65,"Without-pay",172949,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",2414,0,20,"United-States","<=50K" +65,"?",404601,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",2414,0,30,"United-States","<=50K" +59,"Private",328525,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",2414,0,15,"United-States","<=50K" +72,"Private",156310,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",2414,0,12,"United-States","<=50K" +30,"Private",59496,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",2407,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",30653,"Masters",14,"Married-civ-spouse","Farming-fishing","Husband","White","Male",2407,0,98,"United-States","<=50K" +35,"Private",234901,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",2407,0,40,"United-States","<=50K" +39,"Private",328466,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",2407,0,70,"Mexico","<=50K" +31,"Private",211334,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",2407,0,65,"United-States","<=50K" +26,"Private",143068,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",2407,0,50,"United-States","<=50K" +25,"Private",297154,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",2407,0,40,"United-States","<=50K" +28,"Private",38309,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",2407,0,40,"United-States","<=50K" +42,"Private",212894,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",2407,0,40,"United-States","<=50K" +45,"Private",358886,"12th",8,"Married-civ-spouse","Adm-clerical","Husband","White","Male",2407,0,50,"United-States","<=50K" +42,"Private",322385,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2407,0,40,"United-States","<=50K" +53,"Private",178356,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",2407,0,99,"United-States","<=50K" +24,"Private",41838,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",2407,0,40,"United-States","<=50K" +32,"Private",178615,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",2407,0,40,"United-States","<=50K" +22,"Private",190968,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",2407,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",224886,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",2407,0,40,"United-States","<=50K" +55,"Private",202220,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",2407,0,35,"United-States","<=50K" +49,"Private",251180,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",2407,0,50,"United-States","<=50K" +59,"?",160662,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",2407,0,60,"United-States","<=50K" +69,"Private",130060,"HS-grad",9,"Separated","Transport-moving","Unmarried","Black","Female",2387,0,40,"United-States","<=50K" +25,"Private",173212,"Assoc-acdm",12,"Never-married","Farming-fishing","Not-in-family","White","Male",2354,0,45,"United-States","<=50K" +44,"Private",83508,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Female",2354,0,99,"United-States","<=50K" +24,"Private",180060,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",2354,0,40,"United-States","<=50K" +42,"Private",30824,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",2354,0,16,"United-States","<=50K" +44,"Federal-gov",240628,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Female",2354,0,40,"United-States","<=50K" +38,"Private",203761,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Female",2354,0,40,"United-States","<=50K" +37,"Private",196529,"Some-college",10,"Widowed","Other-service","Not-in-family","White","Female",2354,0,40,"?","<=50K" +28,"Private",112403,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",2354,0,40,"United-States","<=50K" +35,"Private",183898,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",2354,0,40,"United-States","<=50K" +41,"Private",322980,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","Black","Male",2354,0,40,"United-States","<=50K" +26,"Private",195734,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",2354,0,40,"United-States","<=50K" +68,"Federal-gov",232151,"Some-college",10,"Divorced","Adm-clerical","Other-relative","Black","Female",2346,0,40,"United-States","<=50K" +75,"Self-emp-not-inc",242108,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",2346,0,15,"United-States","<=50K" +72,"Private",97304,"HS-grad",9,"Married-spouse-absent","Machine-op-inspct","Unmarried","White","Male",2346,0,40,"?","<=50K" +69,"Private",130413,"Bachelors",13,"Widowed","Exec-managerial","Not-in-family","White","Female",2346,0,15,"United-States","<=50K" +65,"Private",105116,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",2346,0,40,"United-States","<=50K" +70,"Private",237065,"5th-6th",3,"Widowed","Other-service","Other-relative","White","Female",2346,0,40,"?","<=50K" +71,"Private",269708,"Bachelors",13,"Divorced","Tech-support","Own-child","White","Female",2329,0,16,"United-States","<=50K" +67,"?",183374,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",2329,0,15,"United-States","<=50K" +70,"Self-emp-not-inc",280639,"HS-grad",9,"Widowed","Other-service","Other-relative","White","Female",2329,0,20,"United-States","<=50K" +65,"?",315728,"HS-grad",9,"Widowed","?","Unmarried","White","Female",2329,0,75,"United-States","<=50K" +72,"Private",107814,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",2329,0,60,"United-States","<=50K" +78,"Private",135566,"HS-grad",9,"Widowed","Sales","Unmarried","White","Female",2329,0,12,"United-States","<=50K" +65,"Private",192133,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",2290,0,40,"Greece","<=50K" +63,"Self-emp-not-inc",179400,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",2290,0,20,"United-States","<=50K" +66,"Self-emp-not-inc",174995,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",2290,0,30,"Hungary","<=50K" +65,"Self-emp-not-inc",78875,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",2290,0,40,"United-States","<=50K" +72,"Local-gov",259762,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",2290,0,10,"United-States","<=50K" +73,"Local-gov",232871,"7th-8th",4,"Married-civ-spouse","Protective-serv","Husband","White","Male",2228,0,10,"United-States","<=50K" +60,"Private",39952,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2228,0,37,"United-States","<=50K" +78,"?",27979,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",2228,0,32,"United-States","<=50K" +70,"?",207627,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",2228,0,24,"United-States","<=50K" +55,"Self-emp-not-inc",105582,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",2228,0,50,"United-States","<=50K" +28,"Private",89718,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",2202,0,48,"United-States","<=50K" +31,"Private",19302,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",2202,0,38,"United-States","<=50K" +29,"Self-emp-not-inc",189346,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",2202,0,50,"United-States","<=50K" +53,"Private",233780,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","Black","Female",2202,0,40,"United-States","<=50K" +58,"Self-emp-inc",21626,"Assoc-voc",11,"Divorced","Sales","Not-in-family","White","Male",2202,0,56,"United-States","<=50K" +33,"Private",221966,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",2202,0,50,"United-States","<=50K" +44,"Self-emp-inc",56236,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Male",2202,0,45,"United-States","<=50K" +55,"Private",195329,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",2202,0,35,"Italy","<=50K" +23,"Private",565313,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",2202,0,80,"United-States","<=50K" +29,"Private",163003,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",2202,0,40,"Taiwan","<=50K" +39,"Local-gov",163278,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",2202,0,44,"United-States","<=50K" +28,"Local-gov",50512,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",2202,0,50,"United-States","<=50K" +50,"Local-gov",157043,"Masters",14,"Divorced","Prof-specialty","Not-in-family","Black","Female",2202,0,30,"?","<=50K" +38,"Private",108140,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",2202,0,45,"United-States","<=50K" +24,"Private",72119,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",2202,0,30,"United-States","<=50K" +22,"Private",205939,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",2202,0,4,"United-States","<=50K" +17,"Private",175024,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",2176,0,18,"United-States","<=50K" +49,"?",261059,"10th",6,"Separated","?","Own-child","White","Male",2176,0,40,"United-States","<=50K" +20,"Private",56322,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",2176,0,25,"United-States","<=50K" +18,"Private",376647,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",2176,0,25,"United-States","<=50K" +21,"Private",201603,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",2176,0,40,"United-States","<=50K" +20,"Private",169600,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",2176,0,12,"United-States","<=50K" +21,"Private",83033,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",2176,0,20,"United-States","<=50K" +20,"Private",286391,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",2176,0,20,"United-States","<=50K" +28,"Self-emp-not-inc",315417,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",2176,0,40,"United-States","<=50K" +19,"Private",42069,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",2176,0,45,"United-States","<=50K" +36,"Private",177907,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",2176,0,20,"?","<=50K" +63,"Private",169983,"11th",7,"Widowed","Sales","Not-in-family","White","Female",2176,0,30,"United-States","<=50K" +33,"Private",190511,"7th-8th",4,"Divorced","Handlers-cleaners","Not-in-family","White","Male",2176,0,35,"United-States","<=50K" +25,"Private",176047,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",2176,0,40,"United-States","<=50K" +21,"?",175166,"Some-college",10,"Never-married","?","Own-child","White","Female",2176,0,40,"United-States","<=50K" +18,"Private",60981,"Some-college",10,"Never-married","Sales","Own-child","White","Female",2176,0,35,"United-States","<=50K" +48,"Private",189462,"Some-college",10,"Divorced","Handlers-cleaners","Own-child","White","Male",2176,0,40,"United-States","<=50K" +27,"Private",177955,"5th-6th",3,"Never-married","Priv-house-serv","Other-relative","White","Female",2176,0,40,"El-Salvador","<=50K" +39,"Private",339442,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","Black","Male",2176,0,40,"United-States","<=50K" +20,"Private",26842,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",2176,0,40,"United-States","<=50K" +18,"Private",206008,"Some-college",10,"Never-married","Sales","Unmarried","White","Male",2176,0,40,"United-States","<=50K" +18,"Private",141626,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",2176,0,20,"United-States","<=50K" +21,"Private",213015,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","Black","Male",2176,0,40,"United-States","<=50K" +39,"State-gov",77516,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",2174,0,40,"United-States","<=50K" +40,"Self-emp-not-inc",204116,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Female",2174,0,40,"United-States","<=50K" +25,"Private",200408,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",2174,0,40,"United-States","<=50K" +29,"Private",177119,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","White","Female",2174,0,45,"United-States","<=50K" +41,"Private",107306,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",2174,0,40,"United-States","<=50K" +23,"Private",107578,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",2174,0,40,"United-States","<=50K" +28,"Private",56179,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",2174,0,55,"United-States","<=50K" +36,"Private",176101,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",2174,0,60,"United-States","<=50K" +39,"Private",190466,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",2174,0,40,"United-States","<=50K" +33,"Private",164707,"Assoc-acdm",12,"Never-married","Exec-managerial","Unmarried","White","Female",2174,0,55,"?","<=50K" +28,"Private",32291,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",2174,0,40,"United-States","<=50K" +39,"Private",115418,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",2174,0,45,"United-States","<=50K" +26,"Local-gov",425092,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",2174,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",151476,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",2174,0,40,"United-States","<=50K" +32,"Federal-gov",191385,"Assoc-acdm",12,"Divorced","Protective-serv","Not-in-family","White","Male",2174,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",219611,"Bachelors",13,"Never-married","Sales","Not-in-family","Black","Female",2174,0,50,"United-States","<=50K" +34,"Private",133503,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",2174,0,40,"United-States","<=50K" +29,"Private",196116,"Prof-school",15,"Divorced","Prof-specialty","Own-child","White","Female",2174,0,72,"United-States","<=50K" +40,"Private",149102,"HS-grad",9,"Married-spouse-absent","Handlers-cleaners","Not-in-family","White","Male",2174,0,60,"Poland","<=50K" +58,"Private",106546,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",2174,0,40,"United-States","<=50K" +57,"State-gov",25045,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Male",2174,0,37,"United-States","<=50K" +24,"Private",163665,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",2174,0,40,"United-States","<=50K" +32,"Private",107793,"HS-grad",9,"Divorced","Other-service","Own-child","White","Male",2174,0,40,"United-States","<=50K" +41,"Private",204682,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",2174,0,40,"Japan","<=50K" +27,"Private",191628,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","Black","Male",2174,0,40,"United-States","<=50K" +37,"Private",177858,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",2174,0,40,"United-States","<=50K" +48,"Private",245948,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",2174,0,40,"United-States","<=50K" +57,"Private",206343,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","White","Male",2174,0,40,"Cuba","<=50K" +41,"Private",115411,"Some-college",10,"Divorced","Sales","Own-child","White","Male",2174,0,45,"United-States","<=50K" +26,"Private",258768,"Some-college",10,"Never-married","Transport-moving","Not-in-family","Black","Male",2174,0,75,"United-States","<=50K" +63,"Private",125954,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",2174,0,40,"United-States","<=50K" +45,"Private",138626,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Male",2174,0,50,"United-States","<=50K" +21,"Private",100462,"Assoc-voc",11,"Never-married","Exec-managerial","Own-child","White","Female",2174,0,60,"United-States","<=50K" +31,"Private",187560,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",2174,0,40,"United-States","<=50K" +28,"Private",46987,"Assoc-voc",11,"Never-married","Tech-support","Own-child","White","Female",2174,0,36,"United-States","<=50K" +62,"Private",194167,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",2174,0,40,"United-States","<=50K" +41,"Private",45156,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",2174,0,41,"United-States","<=50K" +29,"Federal-gov",37933,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",2174,0,40,"United-States","<=50K" +24,"Private",254293,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",2174,0,45,"United-States","<=50K" +29,"Private",189565,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",2174,0,50,"United-States","<=50K" +43,"Federal-gov",134026,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Male",2174,0,40,"United-States","<=50K" +47,"Private",223342,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",2174,0,40,"England","<=50K" +25,"Private",139012,"Bachelors",13,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",2174,0,40,"Vietnam","<=50K" +32,"Self-emp-not-inc",261056,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Female",2174,0,60,"?","<=50K" +43,"Private",187702,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",2174,0,45,"United-States","<=50K" +25,"Private",198587,"Some-college",10,"Never-married","Tech-support","Not-in-family","Black","Female",2174,0,50,"United-States","<=50K" +27,"State-gov",192257,"HS-grad",9,"Never-married","Protective-serv","Own-child","White","Male",2174,0,40,"United-States","<=50K" +27,"Local-gov",162404,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","Black","Male",2174,0,40,"United-States","<=50K" +51,"Private",246519,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",2105,0,45,"United-States","<=50K" +31,"Private",209448,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",2105,0,40,"Mexico","<=50K" +63,"Private",135339,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",2105,0,40,"Vietnam","<=50K" +23,"Private",222925,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Own-child","White","Female",2105,0,40,"United-States","<=50K" +24,"Private",254767,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",2105,0,50,"United-States","<=50K" +21,"?",357029,"Some-college",10,"Married-civ-spouse","?","Wife","Black","Female",2105,0,20,"United-States","<=50K" +52,"Private",152373,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",2105,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",154641,"Assoc-acdm",12,"Married-civ-spouse","Farming-fishing","Husband","White","Male",2105,0,50,"United-States","<=50K" +33,"Local-gov",365908,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",2105,0,40,"United-States","<=50K" +81,"Private",114670,"9th",5,"Widowed","Priv-house-serv","Not-in-family","Black","Female",2062,0,5,"United-States","<=50K" +67,"Private",172756,"1st-4th",2,"Widowed","Machine-op-inspct","Not-in-family","White","Female",2062,0,34,"Ecuador","<=50K" +66,"Private",127921,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",2050,0,55,"United-States","<=50K" +67,"?",407618,"9th",5,"Divorced","?","Not-in-family","White","Female",2050,0,40,"United-States","<=50K" +69,"Private",541737,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",2050,0,24,"United-States","<=50K" +66,"?",306178,"10th",6,"Divorced","?","Not-in-family","White","Male",2050,0,40,"United-States","<=50K" +71,"Local-gov",303860,"Masters",14,"Widowed","Exec-managerial","Not-in-family","White","Male",2050,0,20,"United-States","<=50K" +46,"Self-emp-inc",110702,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",2036,0,60,"United-States","<=50K" +34,"Private",245211,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",2036,0,30,"United-States","<=50K" +38,"State-gov",103925,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",2036,0,20,"United-States","<=50K" +19,"Private",376683,"Some-college",10,"Never-married","Other-service","Unmarried","Black","Female",2036,0,30,"United-States","<=50K" +67,"Local-gov",342175,"Masters",14,"Divorced","Adm-clerical","Not-in-family","White","Female",2009,0,40,"United-States","<=50K" +65,"Local-gov",153890,"12th",8,"Widowed","Exec-managerial","Not-in-family","White","Male",2009,0,44,"United-States","<=50K" +70,"?",163057,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",2009,0,40,"United-States","<=50K" +69,"Private",106595,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",1848,0,40,"United-States","<=50K" +69,"Private",177374,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",1848,0,12,"United-States","<=50K" +65,"Private",172510,"Some-college",10,"Widowed","Prof-specialty","Not-in-family","White","Female",1848,0,20,"Hungary","<=50K" +65,"Private",80174,"HS-grad",9,"Divorced","Exec-managerial","Other-relative","White","Female",1848,0,50,"United-States","<=50K" +69,"Self-emp-not-inc",29980,"7th-8th",4,"Never-married","Farming-fishing","Other-relative","White","Male",1848,0,10,"United-States","<=50K" +69,"?",320280,"Some-college",10,"Never-married","?","Not-in-family","White","Male",1848,0,1,"United-States","<=50K" +41,"Private",162189,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",1831,0,40,"Peru","<=50K" +33,"State-gov",73296,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",1831,0,40,"United-States","<=50K" +44,"Private",126199,"Some-college",10,"Divorced","Transport-moving","Unmarried","White","Male",1831,0,50,"United-States","<=50K" +36,"Private",353524,"HS-grad",9,"Divorced","Exec-managerial","Own-child","White","Female",1831,0,40,"United-States","<=50K" +29,"Private",326330,"Some-college",10,"Divorced","Exec-managerial","Own-child","White","Female",1831,0,40,"United-States","<=50K" +40,"Private",341204,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",1831,0,30,"United-States","<=50K" +47,"State-gov",108890,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",1831,0,38,"United-States","<=50K" +65,"?",299494,"11th",7,"Married-civ-spouse","?","Husband","White","Male",1797,0,40,"United-States","<=50K" +69,"Private",141181,"5th-6th",3,"Married-civ-spouse","Adm-clerical","Husband","White","Male",1797,0,40,"United-States","<=50K" +67,"Private",101132,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",1797,0,40,"United-States","<=50K" +65,"Self-emp-not-inc",131417,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",1797,0,21,"United-States","<=50K" +74,"?",33114,"10th",6,"Married-civ-spouse","?","Husband","Amer-Indian-Eskimo","Male",1797,0,30,"United-States","<=50K" +78,"Private",184759,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",1797,0,15,"United-States","<=50K" +67,"Self-emp-not-inc",252842,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",1797,0,20,"United-States","<=50K" +34,"Private",104509,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",1639,0,20,"United-States","<=50K" +45,"Local-gov",339681,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",1506,0,45,"United-States","<=50K" +46,"State-gov",106705,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",1506,0,50,"United-States","<=50K" +36,"Private",135293,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",1506,0,45,"?","<=50K" +44,"Private",239723,"Some-college",10,"Married-spouse-absent","Craft-repair","Unmarried","White","Female",1506,0,45,"United-States","<=50K" +39,"Private",99357,"Masters",14,"Divorced","Prof-specialty","Own-child","White","Female",1506,0,40,"United-States","<=50K" +41,"Private",283116,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",1506,0,50,"United-States","<=50K" +40,"Self-emp-inc",50644,"Assoc-acdm",12,"Divorced","Sales","Unmarried","White","Female",1506,0,40,"United-States","<=50K" +37,"Private",257042,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",1506,0,40,"United-States","<=50K" +39,"Private",58972,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","White","Male",1506,0,40,"United-States","<=50K" +49,"Private",48120,"HS-grad",9,"Never-married","Transport-moving","Unmarried","Black","Female",1506,0,40,"United-States","<=50K" +40,"State-gov",150874,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",1506,0,40,"United-States","<=50K" +43,"State-gov",241506,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",1506,0,36,"United-States","<=50K" +49,"Private",50748,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","White","Female",1506,0,35,"United-States","<=50K" +42,"Private",384508,"11th",7,"Divorced","Sales","Unmarried","White","Male",1506,0,50,"Mexico","<=50K" +41,"Federal-gov",160467,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",1506,0,40,"United-States","<=50K" +61,"Local-gov",101265,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",1471,0,35,"United-States","<=50K" +34,"Federal-gov",67083,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","Asian-Pac-Islander","Male",1471,0,40,"Cambodia","<=50K" +32,"Private",197457,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",1471,0,38,"United-States","<=50K" +33,"Private",288273,"12th",8,"Separated","Adm-clerical","Unmarried","White","Female",1471,0,40,"United-States","<=50K" +48,"Federal-gov",497486,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",1471,0,40,"United-States","<=50K" +53,"Private",95540,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",1471,0,40,"United-States","<=50K" +40,"Private",260425,"Assoc-acdm",12,"Separated","Tech-support","Unmarried","White","Female",1471,0,32,"United-States","<=50K" +72,"Private",157593,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",1455,0,6,"United-States","<=50K" +69,"Private",88566,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",1424,0,35,"United-States","<=50K" +76,"Private",93125,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",1424,0,24,"United-States","<=50K" +69,"Local-gov",61958,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",1424,0,6,"United-States","<=50K" +66,"Self-emp-not-inc",167687,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",1409,0,50,"United-States","<=50K" +66,"Self-emp-inc",150726,"9th",5,"Married-civ-spouse","Exec-managerial","Husband","White","Male",1409,0,1,"?","<=50K" +66,"Self-emp-not-inc",293114,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",1409,0,40,"United-States","<=50K" +75,"?",164849,"9th",5,"Married-civ-spouse","?","Husband","Black","Male",1409,0,5,"United-States","<=50K" +68,"?",117542,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",1409,0,15,"United-States","<=50K" +79,"?",142171,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",1409,0,35,"United-States","<=50K" +80,"Self-emp-not-inc",225892,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",1409,0,40,"United-States","<=50K" +76,"?",79445,"10th",6,"Married-civ-spouse","?","Husband","White","Male",1173,0,40,"United-States","<=50K" +73,"Private",105886,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",1173,0,75,"United-States","<=50K" +57,"?",202903,"7th-8th",4,"Married-civ-spouse","?","Wife","White","Female",1173,0,45,"Puerto-Rico","<=50K" +42,"Self-emp-inc",184018,"HS-grad",9,"Divorced","Sales","Unmarried","White","Male",1151,0,50,"United-States","<=50K" +35,"Private",342824,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Female",1151,0,40,"United-States","<=50K" +38,"Private",275338,"Bachelors",13,"Divorced","Sales","Unmarried","White","Female",1151,0,40,"United-States","<=50K" +37,"Local-gov",80680,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",1151,0,35,"United-States","<=50K" +30,"Private",149368,"HS-grad",9,"Divorced","Sales","Unmarried","White","Male",1151,0,30,"United-States","<=50K" +24,"Local-gov",187397,"Some-college",10,"Never-married","Protective-serv","Unmarried","Other","Male",1151,0,40,"United-States","<=50K" +44,"Private",155472,"Assoc-acdm",12,"Never-married","Prof-specialty","Unmarried","Black","Female",1151,0,50,"United-States","<=50K" +34,"Private",130369,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Female",1151,0,48,"Germany","<=50K" +70,"?",167358,"9th",5,"Widowed","?","Unmarried","White","Female",1111,0,15,"United-States","<=50K" +66,"?",160995,"10th",6,"Divorced","?","Not-in-family","White","Female",1086,0,20,"United-States","<=50K" +78,"?",135839,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",1086,0,20,"United-States","<=50K" +67,"?",102693,"HS-grad",9,"Widowed","?","Not-in-family","White","Male",1086,0,35,"United-States","<=50K" +65,"Self-emp-not-inc",99359,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",1086,0,60,"United-States","<=50K" +17,"Private",191260,"9th",5,"Never-married","Other-service","Own-child","White","Male",1055,0,24,"United-States","<=50K" +26,"Local-gov",208122,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",1055,0,40,"United-States","<=50K" +21,"?",149704,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",1055,0,40,"United-States","<=50K" +17,"?",333100,"10th",6,"Never-married","?","Own-child","White","Male",1055,0,30,"United-States","<=50K" +20,"?",206671,"Some-college",10,"Never-married","?","Own-child","White","Male",1055,0,50,"United-States","<=50K" +17,"Private",103851,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",1055,0,20,"United-States","<=50K" +64,"Self-emp-not-inc",177825,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",1055,0,40,"United-States","<=50K" +19,"?",37332,"HS-grad",9,"Never-married","?","Own-child","White","Female",1055,0,12,"United-States","<=50K" +17,"Private",130125,"10th",6,"Never-married","Other-service","Own-child","Amer-Indian-Eskimo","Female",1055,0,20,"United-States","<=50K" +33,"Private",170651,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",1055,0,40,"United-States","<=50K" +33,"Local-gov",161942,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",1055,0,40,"United-States","<=50K" +18,"Private",125441,"11th",7,"Never-married","Other-service","Own-child","White","Male",1055,0,20,"United-States","<=50K" +19,"Private",123416,"12th",8,"Separated","Prof-specialty","Own-child","White","Female",1055,0,40,"United-States","<=50K" +18,"Private",186909,"HS-grad",9,"Never-married","Sales","Other-relative","White","Female",1055,0,30,"United-States","<=50K" +21,"Private",223352,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",1055,0,30,"United-States","<=50K" +26,"Private",183171,"11th",7,"Never-married","Other-service","Own-child","Black","Male",1055,0,32,"United-States","<=50K" +43,"Private",88913,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Asian-Pac-Islander","Female",1055,0,40,"United-States","<=50K" +18,"Private",173255,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",1055,0,25,"United-States","<=50K" +21,"Private",253612,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",1055,0,32,"United-States","<=50K" +62,"Private",147627,"9th",5,"Never-married","Priv-house-serv","Not-in-family","Black","Female",1055,0,22,"United-States","<=50K" +19,"Private",243373,"12th",8,"Never-married","Sales","Other-relative","White","Male",1055,0,40,"United-States","<=50K" +20,"Private",148409,"Some-college",10,"Never-married","Sales","Other-relative","White","Male",1055,0,20,"United-States","<=50K" +17,"Private",56536,"11th",7,"Never-married","Sales","Own-child","White","Female",1055,0,18,"India","<=50K" +22,"Private",205940,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",1055,0,30,"United-States","<=50K" +23,"Private",142766,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",1055,0,20,"United-States","<=50K" +90,"?",256514,"Bachelors",13,"Widowed","?","Other-relative","White","Female",991,0,10,"United-States","<=50K" +72,"?",289930,"Bachelors",13,"Separated","?","Not-in-family","White","Female",991,0,7,"United-States","<=50K" +67,"Private",335979,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",991,0,18,"United-States","<=50K" +69,"Private",203313,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",991,0,18,"United-States","<=50K" +65,"Private",180807,"HS-grad",9,"Separated","Protective-serv","Not-in-family","White","Male",991,0,20,"United-States","<=50K" +54,"Private",175912,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","White","Male",914,0,40,"United-States","<=50K" +33,"Private",131776,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",914,0,40,"Germany","<=50K" +55,"Local-gov",177163,"Masters",14,"Widowed","Prof-specialty","Unmarried","White","Female",914,0,50,"United-States","<=50K" +41,"Private",116103,"HS-grad",9,"Widowed","Exec-managerial","Other-relative","White","Male",914,0,40,"United-States","<=50K" +25,"Private",114345,"9th",5,"Never-married","Craft-repair","Unmarried","White","Male",914,0,40,"United-States","<=50K" +48,"Private",210424,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",914,0,40,"United-States","<=50K" +40,"Private",88368,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",914,0,40,"United-States","<=50K" +43,"Local-gov",188280,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",914,0,40,"United-States","<=50K" +34,"Local-gov",284843,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","Black","Male",594,0,60,"United-States","<=50K" +52,"?",271749,"12th",8,"Never-married","?","Other-relative","Black","Male",594,0,40,"United-States","<=50K" +56,"Private",156052,"HS-grad",9,"Widowed","Other-service","Unmarried","Black","Female",594,0,20,"United-States","<=50K" +18,"?",169882,"Some-college",10,"Never-married","?","Own-child","White","Female",594,0,15,"United-States","<=50K" +18,"Private",675421,"9th",5,"Never-married","Handlers-cleaners","Own-child","White","Male",594,0,40,"United-States","<=50K" +57,"Private",296152,"Some-college",10,"Divorced","Exec-managerial","Other-relative","White","Female",594,0,10,"United-States","<=50K" +20,"Private",196745,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",594,0,16,"United-States","<=50K" +21,"Private",321666,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",594,0,40,"United-States","<=50K" +18,"Private",32244,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",594,0,30,"United-States","<=50K" +17,"Private",191260,"11th",7,"Never-married","Other-service","Own-child","White","Male",594,0,10,"United-States","<=50K" +19,"?",217769,"Some-college",10,"Never-married","?","Own-child","White","Female",594,0,10,"United-States","<=50K" +43,"Private",397963,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",594,0,16,"United-States","<=50K" +20,"Private",266525,"Some-college",10,"Never-married","Prof-specialty","Other-relative","Black","Female",594,0,20,"United-States","<=50K" +26,"Private",144483,"Assoc-voc",11,"Divorced","Sales","Own-child","White","Female",594,0,35,"United-States","<=50K" +43,"Local-gov",337469,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",594,0,20,"Mexico","<=50K" +49,"Local-gov",46537,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",594,0,10,"United-States","<=50K" +18,"?",256179,"Some-college",10,"Never-married","?","Own-child","White","Male",594,0,10,"United-States","<=50K" +28,"Private",183597,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",594,0,50,"Germany","<=50K" +38,"Private",82552,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",594,0,50,"United-States","<=50K" +19,"Private",208656,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",594,0,20,"United-States","<=50K" +44,"Private",67065,"Assoc-voc",11,"Never-married","Priv-house-serv","Not-in-family","White","Male",594,0,25,"United-States","<=50K" +18,"Private",198616,"12th",8,"Never-married","Craft-repair","Own-child","White","Male",594,0,20,"United-States","<=50K" +18,"Self-emp-not-inc",230373,"11th",7,"Never-married","Other-service","Own-child","White","Female",594,0,4,"United-States","<=50K" +24,"Private",270872,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",594,0,40,"?","<=50K" +17,"Private",232713,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",594,0,30,"United-States","<=50K" +20,"?",66695,"Some-college",10,"Never-married","?","Own-child","Other","Female",594,0,35,"United-States","<=50K" +19,"Private",286435,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",594,0,40,"United-States","<=50K" +20,"Private",316043,"11th",7,"Never-married","Other-service","Own-child","Black","Male",594,0,20,"United-States","<=50K" +19,"State-gov",67217,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",594,0,24,"United-States","<=50K" +22,"Local-gov",39236,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",594,0,25,"United-States","<=50K" +18,"Private",199039,"12th",8,"Never-married","Sales","Own-child","White","Male",594,0,14,"United-States","<=50K" +21,"Local-gov",309348,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",594,0,4,"United-States","<=50K" +24,"Private",128061,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",594,0,15,"United-States","<=50K" +17,"Private",106733,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",594,0,40,"United-States","<=50K" +77,"Self-emp-not-inc",145329,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",401,0,20,"United-States","<=50K" +90,"?",39824,"HS-grad",9,"Widowed","?","Not-in-family","White","Male",401,0,4,"United-States","<=50K" +38,"State-gov",354591,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",114,0,38,"United-States","<=50K" +20,"Private",59948,"9th",5,"Never-married","Adm-clerical","Unmarried","Black","Female",114,0,20,"United-States","<=50K" +39,"Private",151023,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",114,0,45,"United-States","<=50K" +33,"Private",175412,"9th",5,"Divorced","Craft-repair","Unmarried","White","Male",114,0,55,"United-States","<=50K" +38,"Private",254439,"10th",6,"Widowed","Transport-moving","Unmarried","Black","Male",114,0,40,"United-States","<=50K" +25,"Private",104193,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",114,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",83311,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,13,"United-States","<=50K" +38,"Private",215646,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",234721,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +28,"Private",338409,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,40,"Cuba","<=50K" +37,"Private",284582,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +49,"Private",160187,"9th",5,"Married-spouse-absent","Other-service","Not-in-family","Black","Female",0,0,16,"Jamaica","<=50K" +52,"Self-emp-not-inc",209642,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +37,"Private",280464,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,80,"United-States",">50K" +30,"State-gov",141297,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"India",">50K" +23,"Private",122272,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +32,"Private",205019,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +40,"Private",121772,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"?",">50K" +34,"Private",245487,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,45,"Mexico","<=50K" +25,"Self-emp-not-inc",176756,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,35,"United-States","<=50K" +32,"Private",186824,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +38,"Private",28887,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +43,"Self-emp-not-inc",292175,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States",">50K" +40,"Private",193524,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +54,"Private",302146,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +35,"Federal-gov",76845,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","Black","Male",0,0,40,"United-States","<=50K" +59,"Private",109015,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +56,"Local-gov",216851,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",168294,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"?",180211,"Some-college",10,"Married-civ-spouse","?","Husband","Asian-Pac-Islander","Male",0,0,60,"South",">50K" +39,"Private",367260,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +49,"Private",193366,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Local-gov",190709,"Assoc-acdm",12,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +20,"Private",266015,"Some-college",10,"Never-married","Sales","Own-child","Black","Male",0,0,44,"United-States","<=50K" +30,"Federal-gov",59951,"Some-college",10,"Married-civ-spouse","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"State-gov",311512,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,15,"United-States","<=50K" +48,"Private",242406,"11th",7,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"Puerto-Rico","<=50K" +21,"Private",197200,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",544091,"HS-grad",9,"Married-AF-spouse","Adm-clerical","Wife","White","Female",0,0,25,"United-States","<=50K" +31,"Private",84154,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,38,"?",">50K" +48,"Self-emp-not-inc",265477,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",507875,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,43,"United-States","<=50K" +53,"Self-emp-not-inc",88506,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",172987,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States","<=50K" +49,"Private",94638,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",289980,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +57,"Federal-gov",337895,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States",">50K" +53,"Private",144361,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,38,"United-States","<=50K" +44,"Private",128354,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"State-gov",101603,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",271466,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,43,"United-States","<=50K" +25,"Private",32275,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","Other","Female",0,0,40,"United-States","<=50K" +18,"Private",226956,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"?","<=50K" +50,"Federal-gov",251585,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States",">50K" +47,"Self-emp-inc",109832,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +43,"Private",237993,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",216666,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +35,"Private",56352,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +41,"Private",147372,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,48,"United-States","<=50K" +32,"?",293936,"7th-8th",4,"Married-spouse-absent","?","Not-in-family","White","Male",0,0,40,"?","<=50K" +48,"Private",149640,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",116632,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +29,"Private",105598,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Male",0,0,58,"United-States","<=50K" +36,"Private",155537,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",183175,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Private",169846,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +49,"Self-emp-inc",191681,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +25,"?",200681,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",101509,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,32,"United-States","<=50K" +31,"Private",309974,"Bachelors",13,"Separated","Sales","Own-child","Black","Female",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",162298,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States",">50K" +23,"Private",211678,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +79,"Private",124744,"Some-college",10,"Married-civ-spouse","Prof-specialty","Other-relative","White","Male",0,0,20,"United-States","<=50K" +27,"Private",213921,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"Mexico","<=50K" +40,"Private",32214,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +67,"?",212759,"10th",6,"Married-civ-spouse","?","Husband","White","Male",0,0,2,"United-States","<=50K" +18,"Private",309634,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,22,"United-States","<=50K" +31,"Local-gov",125927,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",446839,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +52,"Private",276515,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Cuba","<=50K" +46,"Private",51618,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +59,"Private",159937,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +53,"Private",346253,"HS-grad",9,"Divorced","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +49,"Local-gov",268234,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",202051,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",54334,"9th",5,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Federal-gov",410867,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States",">50K" +57,"Private",249977,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",286730,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",212563,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +34,"Local-gov",226296,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Local-gov",115585,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +37,"Private",202683,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States",">50K" +48,"Private",171095,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"England","<=50K" +32,"Federal-gov",249409,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +76,"Private",124191,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Self-emp-not-inc",149116,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +20,"Private",188300,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",103432,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",194901,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Local-gov",189265,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",124692,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",432376,"Bachelors",13,"Never-married","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +38,"Private",65324,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",102864,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +53,"Private",95647,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +56,"Self-emp-inc",303090,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +49,"Local-gov",197371,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +55,"Private",247552,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,56,"United-States","<=50K" +22,"Private",102632,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,41,"United-States","<=50K" +21,"Private",199915,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",118853,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +30,"Private",77143,"Bachelors",13,"Never-married","Exec-managerial","Own-child","Black","Male",0,0,40,"Germany","<=50K" +29,"State-gov",267989,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +19,"Private",301606,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,35,"United-States","<=50K" +47,"Private",287828,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +31,"Private",114937,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +35,"?",129305,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",365739,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",69621,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +37,"Private",254202,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +46,"Private",146195,"Assoc-acdm",12,"Divorced","Tech-support","Not-in-family","Black","Female",0,0,36,"United-States","<=50K" +38,"Federal-gov",125933,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Iran",">50K" +43,"Self-emp-not-inc",56920,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +27,"Private",163127,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States","<=50K" +20,"Private",34310,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +49,"Private",81973,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +61,"Self-emp-inc",66614,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",232782,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",316868,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,30,"Mexico","<=50K" +70,"Private",105376,"Some-college",10,"Never-married","Tech-support","Other-relative","White","Male",0,0,40,"United-States","<=50K" +31,"Private",185814,"HS-grad",9,"Never-married","Transport-moving","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +22,"Private",175374,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,24,"United-States","<=50K" +36,"Private",108293,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,24,"United-States","<=50K" +43,"?",174662,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Local-gov",186009,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"Mexico","<=50K" +34,"Private",198183,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",163003,"Bachelors",13,"Never-married","Exec-managerial","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +21,"Private",296158,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +52,"?",252903,"HS-grad",9,"Divorced","?","Not-in-family","White","Male",0,0,45,"United-States",">50K" +48,"Private",187715,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,46,"United-States","<=50K" +23,"Private",214542,"Bachelors",13,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",191535,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +42,"Private",228456,"Bachelors",13,"Separated","Other-service","Other-relative","Black","Male",0,0,50,"United-States","<=50K" +68,"?",38317,"1st-4th",2,"Divorced","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +25,"Private",252752,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Self-emp-inc",78374,"Masters",14,"Divorced","Exec-managerial","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +28,"Private",88419,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"England","<=50K" +45,"Self-emp-not-inc",201080,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",207157,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +39,"Federal-gov",235485,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +46,"State-gov",102628,"Masters",14,"Widowed","Protective-serv","Unmarried","White","Male",0,0,40,"United-States","<=50K" +18,"Private",25828,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,16,"United-States","<=50K" +66,"Local-gov",54826,"Assoc-voc",11,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +28,"State-gov",175325,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",428030,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +28,"State-gov",149624,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",253814,"HS-grad",9,"Married-spouse-absent","Sales","Unmarried","White","Female",0,0,25,"United-States","<=50K" +21,"Private",312956,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +34,"Private",483777,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +18,"Private",183930,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,12,"United-States","<=50K" +33,"Private",37274,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,65,"United-States","<=50K" +44,"Local-gov",181344,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,38,"United-States",">50K" +43,"Private",114580,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",633742,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,45,"United-States","<=50K" +40,"Private",286370,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico",">50K" +37,"Federal-gov",29054,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,42,"United-States",">50K" +34,"Private",304030,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",143129,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"?",135105,"Bachelors",13,"Divorced","?","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +31,"Private",99928,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States","<=50K" +58,"State-gov",109567,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,1,"United-States",">50K" +38,"Private",155222,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,28,"United-States","<=50K" +24,"Private",159567,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",523910,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +47,"Private",120939,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States","<=50K" +41,"Federal-gov",130760,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,24,"United-States","<=50K" +23,"Private",197387,"5th-6th",3,"Married-civ-spouse","Transport-moving","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +36,"Private",99374,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Self-emp-not-inc",32921,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"?",170653,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"Italy","<=50K" +51,"Private",259323,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +37,"State-gov",48211,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +18,"Private",140164,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",36270,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +17,"Private",65368,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,12,"United-States","<=50K" +44,"Local-gov",160943,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +37,"Private",208358,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",153790,"Some-college",10,"Never-married","Sales","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +60,"Private",85815,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-inc",125417,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",635913,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,60,"United-States",">50K" +50,"Private",313321,"Assoc-acdm",12,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",182609,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"Poland","<=50K" +45,"Private",109434,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +25,"Private",255004,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",197860,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"?",187656,"1st-4th",2,"Divorced","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Private",176681,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,20,"United-States","<=50K" +53,"Local-gov",140359,"Preschool",1,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +18,"Private",243313,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +60,"?",24215,"10th",6,"Divorced","?","Not-in-family","Amer-Indian-Eskimo","Female",0,0,10,"United-States","<=50K" +75,"Private",314209,"Assoc-voc",11,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,20,"Columbia","<=50K" +65,"Private",176796,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",130408,"HS-grad",9,"Divorced","Sales","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +25,"Private",159732,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +33,"Private",110978,"Some-college",10,"Divorced","Craft-repair","Other-relative","Other","Female",0,0,40,"United-States","<=50K" +28,"Private",76714,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,55,"United-States",">50K" +59,"State-gov",268700,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"State-gov",170525,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +41,"Private",180138,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"Iran",">50K" +38,"Local-gov",115076,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States",">50K" +23,"Private",115458,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",347890,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Self-emp-not-inc",196001,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,20,"United-States","<=50K" +24,"State-gov",273905,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"?",119156,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +56,"Private",203580,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"?","<=50K" +58,"Private",236596,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +32,"Private",183916,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,34,"United-States","<=50K" +45,"Private",153141,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"?","<=50K" +41,"Private",112763,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +42,"Private",390781,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +59,"Local-gov",171328,"10th",6,"Widowed","Other-service","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +19,"Local-gov",27382,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +58,"Private",259014,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +42,"Self-emp-not-inc",303044,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Asian-Pac-Islander","Male",0,0,40,"Cambodia",">50K" +20,"Private",117789,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +32,"Private",172579,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +45,"Private",187666,"Assoc-voc",11,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +50,"Private",204518,"7th-8th",4,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",150042,"Bachelors",13,"Divorced","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Private",98092,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +17,"Private",245918,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,12,"United-States","<=50K" +26,"Private",378322,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-inc",257295,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,75,"Thailand",">50K" +19,"?",218956,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,24,"Canada","<=50K" +64,"Private",21174,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",185480,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +33,"Private",222205,"HS-grad",9,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,40,"United-States",">50K" +61,"Private",69867,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Local-gov",209109,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Male",0,0,35,"United-States","<=50K" +30,"Private",70377,"HS-grad",9,"Divorced","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Private",477983,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",190174,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",193787,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",34918,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,15,"Germany","<=50K" +34,"Private",175413,"Assoc-acdm",12,"Divorced","Sales","Unmarried","Black","Female",0,0,45,"United-States","<=50K" +60,"Private",173960,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +21,"Private",205759,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",220531,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +50,"Private",176609,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +25,"Private",371987,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Private",193884,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Ecuador","<=50K" +36,"Private",200352,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +31,"Private",127595,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Local-gov",220419,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +21,"Private",231931,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,45,"United-States","<=50K" +27,"Private",248402,"Bachelors",13,"Never-married","Tech-support","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +65,"Private",111095,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,16,"United-States","<=50K" +37,"Self-emp-inc",57424,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +24,"Private",278130,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",169469,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +21,"Private",153718,"Some-college",10,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,25,"United-States","<=50K" +31,"Private",217460,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Private",303296,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Asian-Pac-Islander","Female",0,0,40,"Laos","<=50K" +43,"Private",173321,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",193945,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +46,"Private",83082,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,33,"United-States","<=50K" +35,"Private",193815,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Self-emp-inc",34987,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,54,"United-States",">50K" +26,"Private",59306,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"?",860348,"Some-college",10,"Never-married","?","Own-child","Black","Female",0,0,25,"United-States","<=50K" +36,"Self-emp-not-inc",205607,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States",">50K" +22,"Private",199698,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,15,"United-States","<=50K" +24,"Private",191954,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +77,"Self-emp-not-inc",138714,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",399087,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Other-relative","White","Female",0,0,40,"Mexico","<=50K" +29,"Private",423158,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +62,"Private",159841,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +39,"Self-emp-not-inc",174308,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",186110,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +29,"Private",200381,"11th",7,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +76,"Self-emp-not-inc",174309,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,10,"United-States","<=50K" +63,"Self-emp-not-inc",78383,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +23,"?",211601,"Assoc-voc",11,"Never-married","?","Own-child","Black","Female",0,0,15,"United-States","<=50K" +58,"Self-emp-not-inc",321171,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",206565,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,45,"United-States","<=50K" +26,"Private",224563,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",178686,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"Local-gov",98545,"10th",6,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",242606,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",270942,"5th-6th",3,"Never-married","Other-service","Other-relative","White","Male",0,0,48,"Mexico","<=50K" +30,"Private",94235,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +49,"Private",71195,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +19,"Private",104112,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Male",0,0,30,"Haiti","<=50K" +45,"Private",261192,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",94936,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",85043,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +22,"State-gov",293364,"Some-college",10,"Never-married","Protective-serv","Own-child","Black","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",241895,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +67,"?",36135,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +30,"?",151989,"Assoc-voc",11,"Divorced","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +56,"Private",101128,"Assoc-acdm",12,"Married-spouse-absent","Other-service","Not-in-family","White","Male",0,0,25,"Iran","<=50K" +31,"Private",156464,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,25,"United-States","<=50K" +33,"Private",117963,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",192262,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",111363,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Local-gov",329752,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States","<=50K" +59,"?",372020,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Federal-gov",95432,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +65,"Private",161400,"11th",7,"Widowed","Other-service","Unmarried","Other","Male",0,0,40,"United-States","<=50K" +40,"Private",96129,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",111949,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States","<=50K" +26,"Self-emp-not-inc",117125,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Portugal","<=50K" +36,"Private",348022,"10th",6,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,24,"United-States","<=50K" +62,"Private",270092,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",180609,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"Private",410439,"HS-grad",9,"Married-spouse-absent","Sales","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +28,"Private",92262,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",183081,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"Private",362589,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +57,"Private",212448,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States",">50K" +39,"Private",481060,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Federal-gov",185885,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,15,"United-States","<=50K" +17,"Private",89821,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,10,"United-States","<=50K" +40,"State-gov",184018,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,38,"United-States",">50K" +45,"Private",256649,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +44,"Private",160323,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +20,"Local-gov",350845,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +33,"Private",267404,"HS-grad",9,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,40,"United-States","<=50K" +23,"Private",35633,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-not-inc",80914,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +38,"Private",172927,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +54,"Private",174319,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",344991,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",108699,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Local-gov",117312,"Some-college",10,"Married-civ-spouse","Transport-moving","Wife","White","Female",0,0,40,"United-States","<=50K" +23,"Private",396099,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +29,"Private",134152,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",25429,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,16,"United-States","<=50K" +19,"Private",232392,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +35,"Private",220098,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States",">50K" +27,"Private",301302,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +46,"Self-emp-not-inc",277946,"Assoc-acdm",12,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",196164,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +44,"Private",115562,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",96975,"Some-college",10,"Divorced","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"?",137300,"HS-grad",9,"Never-married","?","Other-relative","White","Female",0,0,35,"United-States","<=50K" +25,"Private",86872,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +52,"Self-emp-inc",132178,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +20,"Private",416103,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",108574,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"State-gov",288353,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",227689,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","White","Female",0,0,64,"United-States","<=50K" +28,"Private",110145,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-not-inc",317253,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,25,"United-States","<=50K" +32,"Private",364657,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Local-gov",42346,"Some-college",10,"Divorced","Other-service","Not-in-family","Black","Female",0,0,24,"United-States","<=50K" +24,"Private",241951,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",118500,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"State-gov",1033222,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",92440,"12th",8,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States",">50K" +52,"Private",190762,"1st-4th",2,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +30,"Private",426017,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,19,"United-States","<=50K" +34,"Local-gov",243867,"11th",7,"Separated","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +34,"State-gov",240283,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",61777,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +32,"State-gov",92003,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +29,"Private",188401,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",228528,"10th",6,"Never-married","Craft-repair","Unmarried","White","Female",0,0,35,"United-States","<=50K" +25,"Private",133373,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +23,"Private",204653,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,72,"Dominican-Republic","<=50K" +63,"Self-emp-inc",222289,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Local-gov",287480,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +80,"?",107762,"HS-grad",9,"Widowed","?","Not-in-family","White","Male",0,0,24,"United-States","<=50K" +17,"?",202521,"11th",7,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",29662,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,25,"United-States",">50K" +33,"Private",208405,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Local-gov",117018,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",81281,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",340148,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +29,"Private",363425,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",45857,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +24,"Federal-gov",191073,"HS-grad",9,"Never-married","Armed-Forces","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Private",116632,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",405855,"9th",5,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +20,"Private",298227,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +44,"Private",290521,"HS-grad",9,"Widowed","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +51,"Private",56915,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +20,"Private",146538,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"?",258872,"11th",7,"Never-married","?","Own-child","White","Female",0,0,5,"United-States","<=50K" +19,"Private",206399,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-inc",197332,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +60,"Private",245062,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",197583,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"?",">50K" +44,"Self-emp-not-inc",234885,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +40,"Private",72887,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +30,"Private",180374,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +38,"Private",351299,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,50,"United-States","<=50K" +23,"Private",54012,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +32,"?",115745,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",116632,"Assoc-acdm",12,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"Local-gov",288825,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",132601,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +50,"Private",193374,"1st-4th",2,"Married-spouse-absent","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +24,"Private",170070,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +37,"Private",126708,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,60,"United-States","<=50K" +52,"Private",35598,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +38,"Private",33983,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",118551,"Bachelors",13,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,16,"United-States",">50K" +60,"Private",201965,"Some-college",10,"Never-married","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States",">50K" +22,"?",139883,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",285020,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",303990,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +67,"Private",49401,"Assoc-voc",11,"Divorced","Other-service","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +46,"Private",279196,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Private",211870,"9th",5,"Never-married","Other-service","Not-in-family","White","Male",0,0,6,"United-States","<=50K" +22,"Private",281432,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +27,"Private",161155,"10th",6,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",197904,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +33,"Private",111746,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"Portugal","<=50K" +43,"Self-emp-not-inc",170721,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +28,"State-gov",70100,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +41,"Private",193626,"HS-grad",9,"Married-spouse-absent","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",189775,"Some-college",10,"Married-spouse-absent","Adm-clerical","Own-child","Black","Female",0,0,20,"United-States","<=50K" +63,"?",401531,"1st-4th",2,"Married-civ-spouse","?","Husband","White","Male",0,0,35,"United-States","<=50K" +59,"Local-gov",286967,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +45,"Local-gov",164427,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",347934,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +46,"Federal-gov",371373,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",32220,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +34,"Private",187251,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,25,"United-States","<=50K" +33,"Private",178107,"Bachelors",13,"Never-married","Craft-repair","Own-child","White","Male",0,0,20,"United-States","<=50K" +41,"Private",343121,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,36,"United-States","<=50K" +20,"Private",262749,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",403107,"5th-6th",3,"Never-married","Other-service","Own-child","White","Male",0,0,40,"El-Salvador","<=50K" +26,"Private",64293,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +72,"?",303588,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +23,"Local-gov",324960,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"Poland","<=50K" +62,"Local-gov",114060,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",48925,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",180980,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,42,"France","<=50K" +25,"Private",181054,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",388093,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +19,"Private",249609,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,8,"United-States","<=50K" +43,"Private",112131,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Local-gov",543162,"HS-grad",9,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +39,"Private",91996,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +53,"?",251804,"5th-6th",3,"Widowed","?","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +32,"Private",37070,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +34,"Private",337587,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",189346,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +57,"?",222216,"Assoc-voc",11,"Widowed","?","Unmarried","White","Female",0,0,38,"United-States","<=50K" +25,"Private",267044,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Amer-Indian-Eskimo","Female",0,0,20,"United-States","<=50K" +20,"?",214635,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,24,"United-States","<=50K" +21,"?",204226,"Some-college",10,"Never-married","?","Unmarried","White","Female",0,0,35,"United-States","<=50K" +34,"Private",108116,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Local-gov",248344,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +37,"Local-gov",186035,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +44,"Private",177905,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,58,"United-States",">50K" +28,"Private",85812,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +42,"Private",221172,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +74,"Private",99183,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,9,"United-States","<=50K" +38,"Self-emp-not-inc",190387,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Self-emp-not-inc",202692,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",109339,"11th",7,"Divorced","Machine-op-inspct","Unmarried","Other","Female",0,0,46,"Puerto-Rico","<=50K" +26,"Private",108658,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",197202,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +41,"Private",101739,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +39,"Local-gov",207853,"12th",8,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"Private",190942,"1st-4th",2,"Widowed","Priv-house-serv","Not-in-family","Black","Female",0,0,30,"United-States","<=50K" +29,"Private",102345,"Assoc-voc",11,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Self-emp-inc",41493,"Bachelors",13,"Never-married","Farming-fishing","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +34,"?",190027,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +44,"Private",210525,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",133937,"Doctorate",16,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",237903,"Some-college",10,"Never-married","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",163862,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",201872,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",84179,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +58,"Private",51662,"10th",6,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,8,"United-States","<=50K" +35,"Local-gov",233327,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",259510,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,36,"United-States","<=50K" +28,"Private",184831,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-not-inc",245724,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +36,"Self-emp-not-inc",27053,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +72,"Private",205343,"11th",7,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",229328,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","Black","Female",0,0,40,"United-States","<=50K" +33,"Federal-gov",319560,"Assoc-voc",11,"Divorced","Craft-repair","Unmarried","Black","Female",0,0,40,"United-States",">50K" +69,"Private",136218,"11th",7,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",54576,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",323069,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,20,"?","<=50K" +34,"Private",148291,"HS-grad",9,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,32,"United-States","<=50K" +30,"Private",152453,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +28,"Private",114053,"Bachelors",13,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +54,"Private",212960,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States",">50K" +47,"Private",264052,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",82804,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",334273,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +20,"Private",27337,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Amer-Indian-Eskimo","Male",0,0,48,"United-States","<=50K" +45,"Private",433665,"7th-8th",4,"Separated","Other-service","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +29,"Self-emp-not-inc",110663,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +47,"Private",87490,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,42,"United-States","<=50K" +24,"Private",354351,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",95469,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",242718,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,12,"United-States","<=50K" +27,"Private",158156,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +29,"Private",350162,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Male",0,0,40,"United-States",">50K" +18,"?",165532,"12th",8,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +36,"Self-emp-not-inc",28738,"Assoc-acdm",12,"Divorced","Sales","Unmarried","White","Female",0,0,35,"United-States","<=50K" +58,"Local-gov",283635,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Self-emp-not-inc",86646,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +65,"?",195733,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States",">50K" +57,"Private",69884,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Private",199713,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",181659,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",340939,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",197747,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,24,"United-States","<=50K" +29,"Private",34292,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +18,"Private",156764,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +57,"Self-emp-inc",103948,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +42,"?",137390,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"?",105138,"HS-grad",9,"Married-civ-spouse","?","Wife","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +60,"Private",39352,"7th-8th",4,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,48,"United-States",">50K" +23,"Private",117789,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Private",267147,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"?",99399,"Some-college",10,"Never-married","?","Unmarried","Amer-Indian-Eskimo","Female",0,0,25,"United-States","<=50K" +49,"Private",136455,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +32,"Private",239824,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",217039,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,28,"United-States","<=50K" +60,"Private",51290,"7th-8th",4,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Local-gov",175674,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",194404,"Assoc-acdm",12,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",45612,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +51,"Private",410114,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",182521,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",339772,"HS-grad",9,"Separated","Exec-managerial","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +17,"Private",169658,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,21,"United-States","<=50K" +24,"Private",247564,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",249909,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",109881,"Bachelors",13,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +39,"Private",207824,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,60,"United-States","<=50K" +30,"Private",369027,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,45,"United-States","<=50K" +50,"Self-emp-not-inc",114117,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,32,"United-States","<=50K" +52,"Self-emp-inc",51048,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +23,"Private",190483,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +45,"Private",462440,"11th",7,"Widowed","Other-service","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +65,"Private",109351,"9th",5,"Widowed","Priv-house-serv","Unmarried","Black","Female",0,0,24,"United-States","<=50K" +29,"Private",34383,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +47,"Private",241832,"9th",5,"Married-spouse-absent","Handlers-cleaners","Unmarried","White","Male",0,0,40,"El-Salvador","<=50K" +30,"Private",124187,"HS-grad",9,"Never-married","Farming-fishing","Own-child","Black","Male",0,0,60,"United-States","<=50K" +34,"Private",153614,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +38,"Self-emp-not-inc",267556,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,64,"United-States","<=50K" +33,"Private",205469,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Private",268090,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,26,"United-States",">50K" +47,"Self-emp-not-inc",165039,"Some-college",10,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +49,"Local-gov",120451,"10th",6,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +30,"Private",103649,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States",">50K" +58,"Self-emp-not-inc",35723,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +19,"Private",262601,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,14,"United-States","<=50K" +21,"Private",226181,"Bachelors",13,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-inc",248145,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"Cuba","<=50K" +52,"Self-emp-not-inc",289436,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +26,"Private",75654,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +60,"Private",199378,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",160968,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",55849,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +50,"Self-emp-inc",195322,"Doctorate",16,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +31,"Local-gov",402089,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +71,"Private",78277,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,15,"United-States","<=50K" +58,"?",158611,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"State-gov",169496,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",130959,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +35,"Private",292472,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Taiwan",">50K" +38,"State-gov",143774,"Some-college",10,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +27,"Private",288341,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,32,"United-States","<=50K" +29,"State-gov",71592,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +34,"Private",106742,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +44,"Private",219288,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +43,"Private",174524,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Self-emp-not-inc",335183,"12th",8,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States",">50K" +35,"Private",261293,"Masters",14,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +27,"Private",111900,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",194360,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +20,"Private",81145,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +42,"Private",247019,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +48,"Federal-gov",110457,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"?",80077,"11th",7,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +17,"Self-emp-not-inc",368700,"11th",7,"Never-married","Farming-fishing","Own-child","White","Male",0,0,10,"United-States","<=50K" +33,"Private",182556,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Self-emp-inc",219420,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",102726,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +32,"Private",226267,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Mexico","<=50K" +31,"Private",125457,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +58,"Self-emp-not-inc",204021,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +29,"Local-gov",92262,"HS-grad",9,"Never-married","Protective-serv","Own-child","White","Male",0,0,48,"United-States","<=50K" +37,"Private",161141,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Portugal",">50K" +34,"Self-emp-not-inc",190290,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Local-gov",430828,"Some-college",10,"Separated","Exec-managerial","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +18,"State-gov",59342,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,5,"United-States","<=50K" +34,"Private",136721,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +66,"?",149422,"7th-8th",4,"Never-married","?","Not-in-family","White","Male",0,0,4,"United-States","<=50K" +45,"Local-gov",86644,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,55,"United-States","<=50K" +41,"Private",195124,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,35,"Dominican-Republic","<=50K" +26,"Private",167350,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,30,"United-States","<=50K" +54,"Local-gov",113000,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",140027,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,45,"United-States","<=50K" +42,"Private",262425,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"Private",316702,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +23,"State-gov",335453,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +25,"?",202480,"Assoc-acdm",12,"Never-married","?","Other-relative","White","Male",0,0,45,"United-States","<=50K" +35,"Private",203628,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States",">50K" +30,"Private",189620,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"Poland","<=50K" +19,"Private",475028,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +36,"Local-gov",110866,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +21,"Private",163870,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +31,"Self-emp-not-inc",80145,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",63042,"Bachelors",13,"Divorced","Exec-managerial","Own-child","White","Female",0,0,50,"United-States",">50K" +40,"Private",229148,"12th",8,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"Jamaica","<=50K" +45,"Private",242552,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +60,"Private",177665,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +18,"Private",208103,"11th",7,"Never-married","Other-service","Other-relative","White","Male",0,0,25,"United-States","<=50K" +28,"Private",296450,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",70282,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",271767,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,40,"?","<=50K" +36,"Local-gov",382635,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"Honduras","<=50K" +31,"Private",295697,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",194141,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"State-gov",378418,"HS-grad",9,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",214399,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +34,"Private",217460,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +33,"Private",182556,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",50459,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States",">50K" +43,"Private",177937,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"?",">50K" +44,"Private",111502,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +20,"Private",299047,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +31,"Private",223212,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +23,"Private",352139,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +55,"Private",173093,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +25,"Private",332702,"Assoc-voc",11,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +45,"?",51164,"Some-college",10,"Married-civ-spouse","?","Wife","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",131414,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Female",0,0,36,"United-States","<=50K" +43,"State-gov",260960,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +42,"Private",279914,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",192453,"Some-college",10,"Never-married","Other-service","Other-relative","White","Female",0,0,25,"United-States","<=50K" +55,"Self-emp-not-inc",200939,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,72,"United-States","<=50K" +26,"Private",112847,"Assoc-voc",11,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"Private",316929,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +42,"Local-gov",126319,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +32,"Private",267736,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",267034,"11th",7,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"Haiti","<=50K" +46,"State-gov",193047,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,37,"United-States","<=50K" +22,"Private",223515,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Male",0,0,20,"United-States","<=50K" +58,"Self-emp-not-inc",87510,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",145111,"HS-grad",9,"Never-married","Transport-moving","Unmarried","White","Male",0,0,50,"United-States","<=50K" +39,"Private",48093,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",31757,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,38,"United-States","<=50K" +54,"Private",285854,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Local-gov",120064,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +46,"Federal-gov",167381,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +37,"Private",103408,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",101460,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,18,"United-States","<=50K" +59,"Local-gov",420537,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,38,"United-States",">50K" +34,"Local-gov",119411,"HS-grad",9,"Divorced","Protective-serv","Unmarried","White","Male",0,0,40,"Portugal","<=50K" +53,"Self-emp-inc",128272,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States",">50K" +51,"Private",386773,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,55,"United-States",">50K" +32,"Private",283268,"10th",6,"Separated","Other-service","Unmarried","White","Female",0,0,42,"United-States","<=50K" +31,"State-gov",301526,"Some-college",10,"Married-spouse-absent","Other-service","Other-relative","White","Male",0,0,40,"United-States","<=50K" +22,"Private",151790,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,30,"Germany","<=50K" +47,"Self-emp-not-inc",106252,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +32,"Private",188557,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",171114,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +37,"Private",327323,"5th-6th",3,"Separated","Farming-fishing","Not-in-family","White","Male",0,0,32,"Guatemala","<=50K" +31,"Private",244147,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,55,"United-States","<=50K" +37,"Private",280282,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,24,"United-States",">50K" +55,"Private",116442,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +23,"Local-gov",282579,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +36,"Private",51838,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",73585,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?","<=50K" +43,"Private",226902,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +54,"Private",279129,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"State-gov",146908,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?","<=50K" +40,"Private",130760,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +41,"Self-emp-not-inc",49572,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +40,"Private",237601,"Bachelors",13,"Never-married","Sales","Not-in-family","Other","Female",0,0,55,"United-States",">50K" +42,"Private",169628,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,38,"United-States","<=50K" +18,"Private",231193,"12th",8,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,30,"United-States","<=50K" +59,"?",192130,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,16,"United-States","<=50K" +48,"Private",102102,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States",">50K" +41,"Self-emp-inc",32185,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"?",196061,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,33,"United-States","<=50K" +60,"Private",31577,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +22,"Private",162343,"Some-college",10,"Never-married","Other-service","Other-relative","Black","Male",0,0,20,"United-States","<=50K" +61,"Private",128831,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",316688,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +46,"Private",90758,"Masters",14,"Never-married","Tech-support","Not-in-family","White","Male",0,0,35,"United-States",">50K" +43,"Private",154538,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +68,"Self-emp-not-inc",315859,"11th",7,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,20,"United-States","<=50K" +31,"Private",51471,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +17,"Private",193830,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +50,"?",23780,"Masters",14,"Married-spouse-absent","?","Other-relative","White","Male",0,0,40,"United-States","<=50K" +64,"Private",270333,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",138768,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,30,"United-States","<=50K" +30,"Private",191571,"HS-grad",9,"Separated","Other-service","Own-child","White","Female",0,0,36,"United-States","<=50K" +22,"?",219941,"Some-college",10,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +43,"Private",94113,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +22,"Private",137510,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"Private",32607,"10th",6,"Never-married","Farming-fishing","Own-child","White","Male",0,0,20,"United-States","<=50K" +47,"Self-emp-not-inc",93208,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,75,"Italy","<=50K" +41,"Private",254440,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +56,"Private",186556,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +64,"Private",169871,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +47,"Private",191277,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +48,"Private",167159,"Assoc-voc",11,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +31,"Private",171871,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,46,"United-States","<=50K" +29,"Private",154411,"Assoc-voc",11,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",129227,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +62,"Private",174355,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",680390,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","White","Female",0,0,24,"United-States","<=50K" +43,"Private",233130,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +24,"Self-emp-inc",165474,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"?",257780,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,15,"United-States","<=50K" +26,"Private",280093,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +73,"Self-emp-not-inc",177387,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +72,"?",28929,"11th",7,"Widowed","?","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +55,"Private",105304,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",499233,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",180572,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States",">50K" +24,"Private",321435,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +63,"Private",86108,"HS-grad",9,"Widowed","Farming-fishing","Not-in-family","White","Male",0,0,6,"United-States","<=50K" +17,"Private",198124,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +35,"Private",135162,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +51,"Private",146813,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +62,"Local-gov",291175,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +43,"Private",102895,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Local-gov",33274,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +37,"Private",86551,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +39,"Private",138192,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",118966,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,18,"United-States","<=50K" +61,"Private",99784,"Masters",14,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +26,"Private",90980,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +46,"Self-emp-not-inc",177407,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Private",96467,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"State-gov",327886,"Doctorate",16,"Divorced","Prof-specialty","Own-child","White","Male",0,0,50,"United-States",">50K" +34,"Private",111567,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",166545,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +59,"Private",142182,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",188798,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +49,"Private",38563,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,56,"United-States",">50K" +18,"Private",216284,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +43,"Private",191547,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +48,"Private",285335,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"Self-emp-inc",142712,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +33,"Private",80945,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",309055,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +21,"Private",62339,"10th",6,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"Private",368700,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,28,"United-States","<=50K" +39,"Private",176186,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States",">50K" +29,"Self-emp-not-inc",266855,"Bachelors",13,"Separated","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Private",48087,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",121313,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,50,"United-States","<=50K" +55,"Private",282753,"5th-6th",3,"Divorced","Other-service","Unmarried","Black","Male",0,0,25,"United-States","<=50K" +41,"Private",194636,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +23,"Private",153044,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","Black","Female",0,0,7,"United-States","<=50K" +38,"Private",411797,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Private",117683,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",376540,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +49,"Private",72393,"9th",5,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",270335,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Other-relative","White","Male",0,0,40,"Philippines",">50K" +27,"Private",96226,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States","<=50K" +38,"Private",95336,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Private",258498,"Some-college",10,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,60,"United-States","<=50K" +63,"?",149698,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,15,"United-States","<=50K" +23,"Private",205865,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,28,"United-States","<=50K" +33,"Self-emp-inc",155781,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"?","<=50K" +54,"Self-emp-not-inc",406468,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States","<=50K" +48,"?",144397,"Some-college",10,"Divorced","?","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +35,"Self-emp-not-inc",372525,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",164170,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","Asian-Pac-Islander","Female",0,0,40,"India","<=50K" +42,"Self-emp-not-inc",177307,"Prof-school",15,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,65,"United-States",">50K" +40,"Private",170108,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",341995,"Some-college",10,"Divorced","Sales","Own-child","White","Male",0,0,55,"United-States","<=50K" +22,"Private",226508,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,50,"United-States","<=50K" +30,"Private",87418,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Private",109165,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Local-gov",28856,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,55,"United-States","<=50K" +51,"Self-emp-not-inc",175897,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +22,"Private",99697,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"?",90270,"Assoc-acdm",12,"Married-civ-spouse","?","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +35,"Private",152375,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +46,"Private",171550,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +37,"Private",211154,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +24,"Private",202570,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Male",0,0,15,"United-States","<=50K" +37,"Self-emp-not-inc",168496,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,10,"United-States","<=50K" +53,"Private",68898,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",93235,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +38,"Private",278924,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +53,"Self-emp-not-inc",311020,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +34,"Private",175878,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",543028,"HS-grad",9,"Never-married","Sales","Own-child","Black","Male",0,0,40,"United-States","<=50K" +43,"Private",158926,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","Asian-Pac-Islander","Female",0,0,50,"South","<=50K" +67,"Self-emp-inc",76860,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +81,"Self-emp-not-inc",136063,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"United-States","<=50K" +21,"Private",186648,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +23,"Private",257509,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +25,"Private",98155,"Some-college",10,"Never-married","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +42,"Private",274198,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,38,"Mexico","<=50K" +38,"Private",97083,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +64,"?",29825,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,5,"United-States","<=50K" +32,"Private",262153,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",214738,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",138022,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +22,"Private",91842,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +33,"Private",373662,"1st-4th",2,"Married-spouse-absent","Priv-house-serv","Not-in-family","White","Female",0,0,40,"Guatemala","<=50K" +42,"Private",162003,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +19,"?",52114,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,10,"United-States","<=50K" +51,"Local-gov",241843,"Preschool",1,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",375871,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"Mexico","<=50K" +37,"Private",176900,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,99,"United-States",">50K" +47,"Private",21906,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +33,"Private",143653,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +31,"Private",111567,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States",">50K" +31,"Private",78602,"Assoc-acdm",12,"Divorced","Other-service","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +35,"Private",465507,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-inc",196373,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",293227,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +20,"Private",241752,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Local-gov",166398,"Some-college",10,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +40,"Private",184682,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",250802,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,35,"United-States","<=50K" +44,"Self-emp-not-inc",325159,"Some-college",10,"Divorced","Farming-fishing","Unmarried","White","Male",0,0,40,"United-States","<=50K" +44,"State-gov",174675,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +43,"Private",227065,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,43,"United-States",">50K" +51,"Private",269080,"7th-8th",4,"Widowed","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",177722,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +51,"Private",133461,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",239683,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"?","<=50K" +44,"Self-emp-inc",398473,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States",">50K" +33,"Local-gov",298785,"10th",6,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",123424,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",176286,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",150062,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +32,"Private",169240,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +32,"Private",288273,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"Mexico","<=50K" +36,"Private",526968,"10th",6,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",57066,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",323573,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +35,"Self-emp-inc",368825,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +55,"Self-emp-not-inc",189721,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +48,"Private",164966,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"India",">50K" +36,"?",94954,"Assoc-voc",11,"Widowed","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +34,"Private",202046,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States",">50K" +28,"Private",161538,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +37,"Private",200153,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",32185,"HS-grad",9,"Never-married","Transport-moving","Unmarried","White","Male",0,0,70,"United-States","<=50K" +25,"Private",178326,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"State-gov",188693,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +34,"Private",159929,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"Private",123207,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +22,"Private",284317,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"?",184699,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",154474,"HS-grad",9,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,42,"United-States","<=50K" +45,"Local-gov",318280,"HS-grad",9,"Widowed","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States",">50K" +63,"Private",254907,"Assoc-voc",11,"Divorced","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +41,"Private",349221,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Female",0,0,35,"United-States","<=50K" +47,"Private",335973,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",126701,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +41,"Private",194636,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",124793,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +47,"Private",192835,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +35,"Private",290226,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +56,"Private",112840,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +45,"Private",89325,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +48,"Federal-gov",33109,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,58,"United-States",">50K" +20,"Private",148294,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"State-gov",343642,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +23,"Local-gov",115244,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,60,"United-States","<=50K" +31,"Private",162572,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +58,"Private",356067,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +66,"Private",271567,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-inc",180804,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",109186,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"Germany","<=50K" +51,"Private",220537,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",124827,"Assoc-voc",11,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Private",118494,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,44,"United-States",">50K" +38,"Private",173208,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,25,"United-States","<=50K" +48,"Private",107373,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",26973,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States",">50K" +51,"Private",191965,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,32,"United-States","<=50K" +22,"Private",122346,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"?",117201,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +41,"Private",198316,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"Japan","<=50K" +48,"Local-gov",123075,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +42,"Private",209370,"HS-grad",9,"Separated","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +34,"Private",33117,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",129042,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +56,"Private",169133,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"Yugoslavia","<=50K" +30,"Private",201624,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,45,"?","<=50K" +45,"Private",368561,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +48,"Private",207848,"10th",6,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-inc",138370,"Masters",14,"Married-spouse-absent","Sales","Not-in-family","Asian-Pac-Islander","Male",0,0,50,"India","<=50K" +31,"Private",93106,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",389713,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",206365,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +76,"?",431192,"7th-8th",4,"Widowed","?","Not-in-family","White","Male",0,0,2,"United-States","<=50K" +37,"Private",123785,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,75,"United-States","<=50K" +34,"Private",289984,"HS-grad",9,"Divorced","Priv-house-serv","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +34,"?",164309,"11th",7,"Married-civ-spouse","?","Wife","White","Female",0,0,8,"United-States","<=50K" +90,"Private",137018,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",137994,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",341204,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",34446,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +28,"Private",187160,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,55,"United-States","<=50K" +64,"?",196288,"Assoc-acdm",12,"Never-married","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +23,"Private",217961,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",74631,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +61,"Private",125155,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Self-emp-not-inc",263925,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Canada",">50K" +52,"Self-emp-not-inc",44728,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +38,"Private",193026,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"Iran","<=50K" +32,"Private",87643,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",106742,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,75,"United-States","<=50K" +41,"Private",302122,"Assoc-voc",11,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",185385,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,47,"United-States",">50K" +43,"Self-emp-not-inc",277647,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States","<=50K" +54,"Private",377701,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,32,"Mexico","<=50K" +34,"Private",157886,"Assoc-acdm",12,"Separated","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Private",175958,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,80,"United-States",">50K" +38,"Private",223004,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",29984,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",181651,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",117312,"Assoc-acdm",12,"Divorced","Tech-support","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +22,"Local-gov",34029,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"United-States","<=50K" +37,"Private",215310,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",220384,"11th",7,"Never-married","Adm-clerical","Own-child","White","Male",0,0,15,"United-States","<=50K" +19,"Self-emp-not-inc",36012,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,20,"United-States","<=50K" +22,"Private",191342,"Bachelors",13,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,50,"Taiwan","<=50K" +49,"Private",31339,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"State-gov",227910,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +43,"Private",173728,"Bachelors",13,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Local-gov",167816,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +58,"Self-emp-not-inc",81642,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +41,"Local-gov",195258,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",232475,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",241259,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",118161,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",201954,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +38,"Private",412296,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,28,"United-States","<=50K" +41,"Federal-gov",133060,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Self-emp-not-inc",120539,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +31,"Private",196025,"Doctorate",16,"Married-spouse-absent","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,60,"China","<=50K" +34,"Private",107793,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",163870,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Self-emp-not-inc",361280,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Male",0,0,20,"India","<=50K" +62,"Private",92178,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"?",80710,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Private",182254,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +68,"?",140282,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +45,"Self-emp-inc",149865,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"United-States",">50K" +41,"Private",118619,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,50,"United-States","<=50K" +34,"Self-emp-not-inc",196791,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,25,"United-States",">50K" +34,"Local-gov",167999,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,33,"United-States","<=50K" +31,"Private",51259,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,47,"United-States","<=50K" +29,"Private",131088,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +41,"Private",293791,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +35,"Self-emp-inc",289430,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"Mexico",">50K" +33,"Private",35378,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,45,"United-States",">50K" +37,"State-gov",60227,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +69,"Private",168139,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +34,"Private",290763,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",51100,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",227644,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +58,"Local-gov",205267,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +53,"Private",288020,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Japan","<=50K" +29,"Private",140863,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"State-gov",50178,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States","<=50K" +36,"Private",112497,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",95244,"Some-college",10,"Divorced","Other-service","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +20,"Private",117606,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",89508,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +63,"Federal-gov",124244,"HS-grad",9,"Widowed","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",154374,"Some-college",10,"Divorced","Other-service","Unmarried","White","Male",0,0,45,"United-States","<=50K" +28,"Private",294936,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Private",347132,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +34,"?",181934,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",316672,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +37,"Private",189382,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,38,"United-States","<=50K" +42,"?",184018,"Some-college",10,"Divorced","?","Unmarried","White","Male",0,0,40,"United-States","<=50K" +31,"Private",184307,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"Jamaica",">50K" +46,"Self-emp-not-inc",246212,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +35,"Federal-gov",250504,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,60,"United-States",">50K" +27,"Private",138705,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,53,"United-States","<=50K" +41,"Private",328447,"1st-4th",2,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"Mexico","<=50K" +19,"Private",194608,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +20,"Private",230891,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +59,"Federal-gov",212448,"HS-grad",9,"Widowed","Sales","Unmarried","White","Female",0,0,40,"Germany","<=50K" +40,"Private",214010,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +56,"Self-emp-not-inc",200235,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +30,"Self-emp-inc",205733,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +46,"Private",185041,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +61,"Self-emp-inc",84409,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +25,"Private",241626,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +40,"Private",520586,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,39,"United-States","<=50K" +24,"?",35633,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,40,"?","<=50K" +51,"Private",302847,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,54,"United-States","<=50K" +43,"State-gov",165309,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",117529,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,54,"Mexico","<=50K" +46,"Private",106092,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +28,"State-gov",445824,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +26,"Private",227332,"Bachelors",13,"Never-married","Transport-moving","Unmarried","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +20,"Private",275691,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,28,"United-States","<=50K" +51,"Private",284329,"HS-grad",9,"Widowed","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +33,"Private",114691,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +54,"Private",96062,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",178506,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +22,"?",131573,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,8,"United-States","<=50K" +88,"Self-emp-not-inc",206291,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",182302,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Private",241346,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +50,"Private",157043,"11th",7,"Divorced","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +25,"Private",404616,"Masters",14,"Married-civ-spouse","Farming-fishing","Not-in-family","White","Male",0,0,99,"United-States",">50K" +20,"Private",411862,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +47,"Private",183013,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"?",169982,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",188544,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +50,"State-gov",356619,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States",">50K" +47,"Private",45857,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Local-gov",289886,"11th",7,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,45,"United-States","<=50K" +50,"?",146015,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",216237,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States",">50K" +36,"Private",416745,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",202952,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",167725,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"?",165637,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Federal-gov",43280,"Some-college",10,"Never-married","Exec-managerial","Own-child","Black","Female",0,0,40,"United-States","<=50K" +65,"Private",118779,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +24,"State-gov",191269,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,65,"United-States","<=50K" +27,"Local-gov",247507,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,35,"United-States","<=50K" +51,"Private",239155,"Assoc-voc",11,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",182862,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",33886,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +28,"Private",444304,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",187161,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +49,"Local-gov",116892,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +51,"Local-gov",176813,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +59,"Private",151616,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +18,"Private",240747,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"Dominican-Republic","<=50K" +45,"Federal-gov",320818,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,80,"United-States",">50K" +30,"Local-gov",235271,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",166497,"Bachelors",13,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +44,"Private",344060,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States",">50K" +33,"Private",221196,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-inc",113544,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +61,"Local-gov",321117,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",79619,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,42,"United-States",">50K" +22,"?",42004,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +36,"Private",135289,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +37,"Private",203070,"Some-college",10,"Separated","Adm-clerical","Own-child","White","Male",0,0,62,"United-States","<=50K" +31,"Private",32406,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Female",0,0,20,"United-States","<=50K" +20,"Private",205839,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +63,"?",150389,"Bachelors",13,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States",">50K" +33,"?",163003,"HS-grad",9,"Divorced","?","Not-in-family","Asian-Pac-Islander","Female",0,0,41,"China","<=50K" +38,"Private",200818,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Self-emp-not-inc",247379,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",349151,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",22154,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",176317,"HS-grad",9,"Widowed","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Private",22245,"Masters",14,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,72,"?",">50K" +29,"Private",236436,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",354078,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +42,"Self-emp-not-inc",166813,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +50,"Private",358740,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"England","<=50K" +75,"Self-emp-not-inc",208426,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States","<=50K" +52,"Federal-gov",31838,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",175034,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",413297,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +31,"Private",106347,"11th",7,"Separated","Other-service","Not-in-family","Black","Female",0,0,42,"United-States","<=50K" +23,"Private",174754,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +34,"Private",441454,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +41,"Self-emp-not-inc",209344,"HS-grad",9,"Married-civ-spouse","Sales","Other-relative","White","Female",0,0,40,"Cuba","<=50K" +31,"Private",185732,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +42,"Private",65372,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",33975,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +55,"Private",326297,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +36,"State-gov",194630,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +65,"Self-emp-not-inc",167414,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,59,"United-States",">50K" +38,"Local-gov",165799,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,12,"United-States","<=50K" +62,"Private",192866,"Some-college",10,"Widowed","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +49,"Private",148995,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",190040,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +32,"Private",209432,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-not-inc",397466,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +30,"Private",283767,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"?","<=50K" +52,"Federal-gov",202452,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +29,"Private",128604,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +38,"Private",65466,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +57,"Private",141326,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Federal-gov",369468,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +37,"State-gov",136137,"Some-college",10,"Separated","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",236770,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",89534,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States",">50K" +69,"?",195779,"Assoc-voc",11,"Widowed","?","Not-in-family","White","Female",0,0,1,"United-States","<=50K" +73,"Private",29778,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +22,"Self-emp-inc",153516,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +31,"Private",163594,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +50,"Self-emp-not-inc",343748,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +37,"Private",387430,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,37,"United-States","<=50K" +44,"Local-gov",409505,"Bachelors",13,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",200734,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","Black","Female",0,0,45,"United-States","<=50K" +27,"Private",115831,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",150296,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","White","Female",0,0,80,"United-States","<=50K" +25,"Private",323545,"HS-grad",9,"Never-married","Tech-support","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +20,"Private",232577,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +51,"Local-gov",152754,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",386136,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States","<=50K" +42,"Private",342865,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Federal-gov",158926,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Philippines",">50K" +65,"?",36039,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",164019,"Some-college",10,"Never-married","Farming-fishing","Own-child","Black","Male",0,0,10,"United-States","<=50K" +46,"Private",188861,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",182062,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",37238,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +50,"Private",421132,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"?",178660,"12th",8,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Self-emp-not-inc",795830,"1st-4th",2,"Widowed","Other-service","Unmarried","White","Female",0,0,30,"El-Salvador","<=50K" +39,"Private",278403,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States","<=50K" +46,"Private",279661,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,35,"United-States","<=50K" +36,"Private",113397,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",236696,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,57,"United-States","<=50K" +41,"Private",265266,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Local-gov",34935,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +22,"Private",58222,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Federal-gov",301010,"Some-college",10,"Never-married","Armed-Forces","Not-in-family","Black","Male",0,0,60,"United-States","<=50K" +29,"Private",419721,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"Japan","<=50K" +58,"Self-emp-inc",186791,"Some-college",10,"Married-civ-spouse","Transport-moving","Wife","White","Female",0,0,40,"United-States",">50K" +36,"Self-emp-not-inc",180686,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",209103,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States","<=50K" +37,"Private",32668,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,43,"United-States",">50K" +29,"Private",256956,"Assoc-voc",11,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",202203,"5th-6th",3,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"Mexico","<=50K" +43,"Private",85995,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +49,"Private",125421,"HS-grad",9,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,40,"United-States",">50K" +45,"Federal-gov",283037,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",192932,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"?",244689,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +51,"Private",179646,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",509350,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"Canada",">50K" +24,"Private",96279,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"?",327120,"Assoc-acdm",12,"Never-married","?","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +41,"State-gov",144928,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",55237,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +20,"Private",114874,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +27,"Private",190525,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +55,"Private",121912,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,24,"United-States",">50K" +39,"Private",83893,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +17,"?",138507,"10th",6,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +47,"Private",256522,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"?","<=50K" +52,"Private",168381,"HS-grad",9,"Widowed","Other-service","Unmarried","Asian-Pac-Islander","Female",0,0,40,"India",">50K" +24,"Private",293579,"HS-grad",9,"Never-married","Sales","Own-child","Black","Female",0,0,20,"United-States","<=50K" +29,"Private",285290,"11th",7,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +25,"Private",188488,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +20,"Private",324469,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",275244,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,35,"United-States","<=50K" +57,"Private",265099,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +51,"Private",146767,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",174938,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",240124,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"State-gov",34180,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"State-gov",225904,"Prof-school",15,"Never-married","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +57,"Private",89392,"Masters",14,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",46857,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"State-gov",105363,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",195105,"HS-grad",9,"Never-married","Sales","Not-in-family","Other","Male",0,0,40,"United-States","<=50K" +35,"Private",184117,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +61,"Self-emp-inc",134768,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"Germany",">50K" +17,"?",145886,"11th",7,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +36,"Private",153078,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,60,"?",">50K" +34,"Private",467108,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +42,"Private",173938,"HS-grad",9,"Separated","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Private",191161,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",132606,"5th-6th",3,"Divorced","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +40,"Private",155190,"10th",6,"Never-married","Craft-repair","Other-relative","Black","Male",0,0,55,"United-States","<=50K" +31,"Private",42900,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +36,"Private",191161,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +23,"Private",181820,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",105974,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,41,"United-States","<=50K" +52,"Private",146378,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",103440,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +51,"Private",203435,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,40,"Italy","<=50K" +31,"Federal-gov",168312,"Assoc-voc",11,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Self-emp-inc",257764,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Private",171301,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","Black","Female",0,0,40,"United-States","<=50K" +53,"Federal-gov",225339,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +20,"Private",444554,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",403788,"Assoc-acdm",12,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +61,"?",190997,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,6,"United-States","<=50K" +43,"Private",221550,"Masters",14,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"Poland","<=50K" +46,"Self-emp-inc",98929,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,52,"United-States","<=50K" +43,"Local-gov",169203,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +41,"Private",102332,"HS-grad",9,"Divorced","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",230684,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +54,"Private",449257,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",97429,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"Canada","<=50K" +25,"Private",208999,"Some-college",10,"Separated","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",37072,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +25,"Local-gov",163101,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +19,"Private",119075,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,50,"United-States","<=50K" +37,"Self-emp-not-inc",137314,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +45,"Private",127303,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,45,"United-States","<=50K" +37,"Private",349116,"HS-grad",9,"Never-married","Sales","Not-in-family","Black","Male",0,0,44,"United-States","<=50K" +19,"?",194095,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"Private",46496,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,5,"United-States","<=50K" +27,"Private",29904,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Federal-gov",234151,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",238287,"10th",6,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +42,"Private",230624,"10th",6,"Never-married","Transport-moving","Unmarried","White","Male",0,0,40,"United-States",">50K" +54,"Self-emp-not-inc",114758,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +50,"Private",137815,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +40,"Private",260696,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Private",325007,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,25,"United-States","<=50K" +50,"Private",113176,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",66815,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +42,"?",51795,"HS-grad",9,"Divorced","?","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +24,"Private",241523,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,45,"United-States",">50K" +30,"Private",30226,"11th",7,"Divorced","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Local-gov",352628,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,50,"United-States",">50K" +37,"Private",143912,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +33,"Private",130021,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",329778,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-inc",196945,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,78,"Thailand","<=50K" +39,"Private",24342,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",34368,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +52,"Self-emp-not-inc",173839,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +28,"State-gov",73211,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,20,"United-States","<=50K" +32,"Private",86723,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +31,"Private",179186,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,90,"United-States",">50K" +31,"Private",127610,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +47,"Private",115070,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"?",172582,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,50,"United-States","<=50K" +40,"Private",256202,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +40,"Private",202872,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Female",0,0,45,"United-States","<=50K" +41,"Private",184102,"11th",7,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Federal-gov",130703,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +46,"Private",134727,"11th",7,"Divorced","Machine-op-inspct","Unmarried","Amer-Indian-Eskimo","Male",0,0,43,"Germany","<=50K" +19,"Private",213644,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",147322,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"Peru","<=50K" +59,"Private",296253,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",180871,"Assoc-voc",11,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +35,"State-gov",211115,"Some-college",10,"Never-married","Protective-serv","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-inc",183870,"10th",6,"Married-civ-spouse","Transport-moving","Wife","White","Female",0,0,40,"United-States","<=50K" +28,"Private",441620,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,43,"Mexico","<=50K" +36,"Federal-gov",218542,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +41,"Self-emp-not-inc",141327,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,35,"United-States","<=50K" +47,"Private",67716,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +61,"?",347089,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,16,"United-States","<=50K" +36,"Private",336595,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +38,"Private",27997,"Assoc-voc",11,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",30447,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +44,"Self-emp-not-inc",120837,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,66,"United-States","<=50K" +51,"Private",185283,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +44,"Self-emp-inc",229466,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Private",298225,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +60,"Private",185749,"11th",7,"Widowed","Transport-moving","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-inc",125892,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +46,"Private",563883,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,60,"United-States",">50K" +56,"Private",311249,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +22,"Private",310152,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +76,"?",211453,"HS-grad",9,"Widowed","?","Not-in-family","Black","Female",0,0,2,"United-States","<=50K" +41,"Self-emp-inc",94113,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +46,"Private",161508,"10th",6,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",177675,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States",">50K" +39,"Private",51100,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",100584,"10th",6,"Divorced","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +70,"Federal-gov",163003,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +49,"Private",101320,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,75,"United-States","<=50K" +24,"Private",42706,"Assoc-voc",11,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +61,"Private",120939,"Prof-school",15,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,5,"United-States",">50K" +25,"Private",98283,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +28,"Local-gov",216481,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +69,"State-gov",208869,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,11,"United-States","<=50K" +22,"Private",207940,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,36,"United-States","<=50K" +47,"Private",34248,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,38,"United-States","<=50K" +38,"Private",83727,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,48,"United-States","<=50K" +26,"Private",183077,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +17,"Private",197850,"11th",7,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,24,"United-States","<=50K" +33,"Self-emp-not-inc",235271,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +43,"Self-emp-not-inc",35236,"HS-grad",9,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +58,"Private",255822,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",256263,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +43,"Local-gov",293535,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States",">50K" +25,"Private",174592,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +57,"Federal-gov",278763,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",175232,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,60,"United-States",">50K" +32,"Private",402812,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +26,"Private",101150,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,41,"United-States","<=50K" +45,"Private",103538,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",23940,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-inc",210295,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +32,"Private",80058,"11th",7,"Divorced","Sales","Not-in-family","White","Male",0,0,43,"United-States",">50K" +36,"Self-emp-not-inc",105021,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +19,"Private",225775,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-inc",395831,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,80,"United-States",">50K" +20,"Private",32732,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +60,"?",290593,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",123253,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,42,"United-States","<=50K" +58,"State-gov",48433,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",245317,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"Private",431745,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,14,"United-States","<=50K" +42,"State-gov",436006,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",224943,"Some-college",10,"Married-spouse-absent","Prof-specialty","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-inc",217054,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +66,"Self-emp-not-inc",298834,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +59,"Self-emp-inc",125000,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"England",">50K" +44,"Private",123983,"Bachelors",13,"Divorced","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +46,"Private",155489,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,58,"United-States",">50K" +17,"Local-gov",32124,"9th",5,"Never-married","Other-service","Own-child","Black","Male",0,0,9,"United-States","<=50K" +47,"Local-gov",246891,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"State-gov",141483,"9th",5,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",31985,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",170800,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"Private",231286,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,15,"United-States","<=50K" +33,"Private",159322,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Male",0,0,40,"United-States","<=50K" +48,"Private",176026,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",26898,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,12,"United-States","<=50K" +47,"Private",232628,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +40,"Private",85995,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",125421,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States",">50K" +49,"Private",245305,"10th",6,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,42,"United-States",">50K" +50,"Private",73493,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",197058,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",122116,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",75742,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",214731,"10th",6,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +35,"Private",265954,"HS-grad",9,"Separated","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +26,"State-gov",197156,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +39,"Local-gov",203070,"HS-grad",9,"Separated","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"Local-gov",165695,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +69,"?",473040,"5th-6th",3,"Divorced","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",168107,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",163494,"10th",6,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +38,"Private",180342,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",148069,"10th",6,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",200973,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +17,"Private",130806,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,24,"United-States","<=50K" +56,"Private",117148,"7th-8th",4,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",213977,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",139338,"12th",8,"Divorced","Transport-moving","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",315877,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +41,"Self-emp-not-inc",195124,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"?","<=50K" +25,"Private",352057,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +21,"Private",236684,"Some-college",10,"Never-married","Other-service","Other-relative","Black","Female",0,0,8,"United-States","<=50K" +18,"Private",208447,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,6,"United-States","<=50K" +45,"Private",149640,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",154342,"7th-8th",4,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Federal-gov",141459,"HS-grad",9,"Separated","Other-service","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +47,"Private",111797,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Female",0,0,35,"Outlying-US(Guam-USVI-etc)","<=50K" +29,"Private",111900,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",78707,"11th",7,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",160574,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"?",174714,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,16,"United-States","<=50K" +19,"?",62534,"Bachelors",13,"Never-married","?","Own-child","Black","Female",0,0,40,"Jamaica","<=50K" +24,"Private",198148,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +19,"Private",124265,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Private",208137,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",257250,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +24,"State-gov",147253,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +32,"Local-gov",244268,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +72,"?",213255,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +26,"Private",266912,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Private",169104,"Bachelors",13,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +29,"Private",200511,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +48,"Self-emp-not-inc",65535,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",103395,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +51,"Private",71046,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,45,"Scotland","<=50K" +28,"Self-emp-not-inc",125442,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",169188,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,20,"United-States","<=50K" +23,"Private",121471,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +65,"Private",207281,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,16,"United-States","<=50K" +26,"Local-gov",46097,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",322143,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,10,"United-States","<=50K" +33,"Private",149184,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States",">50K" +33,"Local-gov",119829,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,60,"United-States","<=50K" +37,"Private",910398,"Bachelors",13,"Never-married","Sales","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",176570,"11th",7,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,60,"United-States","<=50K" +24,"Private",216129,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Private",27207,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +57,"State-gov",68830,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +22,"State-gov",178818,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"United-States","<=50K" +57,"Private",236944,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States",">50K" +46,"State-gov",273771,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +67,"Private",318533,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"United-States","<=50K" +35,"?",451940,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +47,"Private",102318,"HS-grad",9,"Separated","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Private",379350,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",21095,"Some-college",10,"Divorced","Other-service","Unmarried","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +58,"Self-emp-not-inc",211547,"12th",8,"Divorced","Sales","Not-in-family","White","Female",0,0,52,"United-States","<=50K" +36,"Private",85272,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,30,"United-States",">50K" +45,"Private",46406,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,36,"England",">50K" +54,"Private",53833,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",161007,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +60,"Private",53707,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",310907,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,35,"United-States","<=50K" +32,"Private",375833,"11th",7,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +38,"Local-gov",107513,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Self-emp-not-inc",58683,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States",">50K" +37,"Private",70240,"HS-grad",9,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +44,"Private",147206,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",175548,"HS-grad",9,"Never-married","Other-service","Not-in-family","Other","Female",0,0,35,"United-States","<=50K" +61,"Self-emp-not-inc",163174,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +51,"Private",126010,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"?",200904,"Assoc-acdm",12,"Married-civ-spouse","?","Wife","Black","Female",0,0,21,"Haiti","<=50K" +67,"Local-gov",258973,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +40,"State-gov",345969,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",127796,"5th-6th",3,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,35,"Mexico","<=50K" +37,"Private",405723,"1st-4th",2,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +57,"Private",175942,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",284196,"10th",6,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-inc",175761,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +52,"Private",158993,"HS-grad",9,"Divorced","Other-service","Other-relative","Black","Female",0,0,38,"United-States","<=50K" +42,"Private",285066,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +55,"Self-emp-not-inc",52888,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,10,"United-States","<=50K" +71,"Self-emp-inc",133821,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States",">50K" +33,"Private",240763,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",39054,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",119272,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +59,"Private",143372,"10th",6,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",323421,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +36,"Self-emp-not-inc",136028,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +26,"Self-emp-not-inc",163189,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",202729,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",421871,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +26,"?",211798,"HS-grad",9,"Separated","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Private",198901,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +18,"Private",214617,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,16,"United-States","<=50K" +55,"Self-emp-not-inc",179715,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,18,"United-States","<=50K" +44,"Private",110355,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",184378,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +62,"Private",273454,"7th-8th",4,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"Cuba","<=50K" +44,"Private",443040,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +39,"?",71701,"HS-grad",9,"Divorced","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +50,"Self-emp-inc",160151,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +35,"Private",107991,"11th",7,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +52,"Private",94391,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",99835,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +43,"Private",83756,"Some-college",10,"Never-married","Exec-managerial","Unmarried","White","Male",0,0,50,"United-States","<=50K" +20,"Private",180052,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +47,"Private",170846,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"Italy",">50K" +43,"Private",37937,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,50,"United-States","<=50K" +64,"?",168340,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"?",">50K" +24,"Private",38455,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Federal-gov",128059,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",420895,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",166744,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,12,"United-States","<=50K" +26,"Private",238768,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"United-States","<=50K" +50,"Private",140592,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +20,"Self-emp-not-inc",211466,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,80,"United-States","<=50K" +43,"Private",39581,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,45,"United-States","<=50K" +53,"Private",117496,"9th",5,"Divorced","Other-service","Not-in-family","White","Female",0,0,36,"Canada","<=50K" +44,"Private",145160,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",28520,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",375077,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,50,"United-States","<=50K" +44,"Private",151504,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +49,"Private",32212,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,43,"United-States","<=50K" +35,"Private",123606,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",202565,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +54,"Private",177927,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +37,"Private",256723,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +18,"Private",46247,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +24,"Private",266926,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",112031,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +22,"?",376277,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +35,"Private",168817,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"Private",187487,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +32,"?",158784,"7th-8th",4,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",67222,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Male",0,0,45,"China","<=50K" +73,"Private",267408,"HS-grad",9,"Widowed","Sales","Other-relative","White","Female",0,0,15,"United-States","<=50K" +47,"Federal-gov",168191,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?","<=50K" +49,"Private",105444,"12th",8,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,39,"United-States","<=50K" +38,"Private",156728,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",148600,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",19914,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +42,"Private",190767,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",233955,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,45,"China",">50K" +35,"Private",30381,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +38,"Private",187069,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +31,"Private",367314,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Local-gov",101119,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,70,"United-States","<=50K" +38,"Private",86551,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,48,"United-States",">50K" +40,"Local-gov",218995,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States",">50K" +21,"Private",57711,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +44,"Private",303521,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"Private",199067,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",247445,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +49,"Private",186078,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +31,"Private",77634,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,42,"United-States","<=50K" +46,"Private",56482,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",314177,"HS-grad",9,"Never-married","Sales","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",239755,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +27,"Private",377680,"Assoc-voc",11,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +26,"Private",294493,"Bachelors",13,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +45,"Private",182655,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Male",0,0,45,"?",">50K" +57,"Local-gov",52267,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,72,"United-States","<=50K" +30,"Private",117963,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",98881,"11th",7,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,32,"United-States","<=50K" +50,"Private",196963,"7th-8th",4,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +38,"Private",166988,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",193459,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +42,"Private",182342,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +32,"Private",496743,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",154781,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",219371,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +45,"Private",99179,"11th",7,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",224910,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",304651,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +37,"Private",349689,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +60,"Private",106850,"10th",6,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Self-emp-not-inc",196328,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,45,"United-States",">50K" +25,"Private",169323,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",162924,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","Asian-Pac-Islander","Male",0,0,60,"Japan","<=50K" +40,"Self-emp-not-inc",34037,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +51,"?",167651,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",197384,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,10,"United-States","<=50K" +42,"Private",251795,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +65,"?",266081,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",165309,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",215873,"10th",6,"Never-married","Machine-op-inspct","Own-child","Black","Male",0,0,45,"United-States","<=50K" +24,"Private",228424,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",195576,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",52199,"HS-grad",9,"Married-spouse-absent","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"?",158762,"10th",6,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +49,"Private",169818,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,40,"United-States",">50K" +31,"Private",288419,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",207546,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"?",228373,"10th",6,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +37,"Private",272950,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",183523,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Private",238415,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +35,"Local-gov",103260,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,35,"United-States",">50K" +40,"Private",135056,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +66,"Private",142723,"5th-6th",3,"Married-spouse-absent","Handlers-cleaners","Unmarried","White","Female",0,0,40,"Puerto-Rico","<=50K" +30,"Federal-gov",188569,"9th",5,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",57322,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",178309,"9th",5,"Never-married","Other-service","Unmarried","White","Female",0,0,50,"United-States","<=50K" +45,"Private",166107,"Masters",14,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +31,"Private",53042,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"Trinadad&Tobago","<=50K" +32,"Private",35595,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",429507,"Assoc-acdm",12,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +50,"Federal-gov",159670,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +63,"Private",151210,"7th-8th",4,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",186792,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",204640,"Some-college",10,"Widowed","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +52,"Private",87205,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +38,"Self-emp-inc",112847,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +50,"State-gov",211319,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +59,"Private",183606,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",205390,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,49,"United-States","<=50K" +52,"Self-emp-inc",101017,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,38,"United-States","<=50K" +57,"Private",114495,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +51,"Private",163921,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,56,"United-States",">50K" +22,"Private",311764,"11th",7,"Widowed","Sales","Own-child","Black","Female",0,0,35,"United-States","<=50K" +49,"Private",188330,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",267174,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +48,"Private",199739,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +52,"Private",185407,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?","<=50K" +43,"State-gov",206139,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Private",282063,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +31,"Private",332379,"7th-8th",4,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",418324,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,36,"United-States","<=50K" +19,"?",263338,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,45,"United-States","<=50K" +51,"Private",158948,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,84,"United-States",">50K" +51,"Private",221532,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States",">50K" +37,"Local-gov",118909,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +19,"Private",286469,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +45,"Private",191914,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Female",0,0,55,"United-States","<=50K" +21,"State-gov",142766,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,10,"United-States","<=50K" +52,"Private",198744,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Local-gov",272780,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,24,"United-States","<=50K" +42,"State-gov",219553,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +56,"Private",261232,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",64292,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +58,"Private",312131,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +70,"Private",30713,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +30,"Private",246439,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +45,"Private",338105,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +23,"Private",228243,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +38,"Private",31603,"Bachelors",13,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,40,"United-States","<=50K" +24,"Private",165054,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",121618,"7th-8th",4,"Never-married","Transport-moving","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +21,"?",163665,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"Private",538319,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"Puerto-Rico","<=50K" +34,"Private",238246,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",131811,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"?",231777,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States","<=50K" +23,"Private",156807,"9th",5,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,36,"United-States","<=50K" +28,"Private",236861,"Bachelors",13,"Divorced","Craft-repair","Unmarried","White","Male",0,0,50,"United-States","<=50K" +29,"Self-emp-not-inc",229842,"HS-grad",9,"Never-married","Transport-moving","Unmarried","Black","Male",0,0,45,"United-States","<=50K" +25,"Local-gov",190057,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +44,"State-gov",55076,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +18,"Private",152545,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,8,"United-States","<=50K" +26,"Private",153434,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,24,"United-States","<=50K" +47,"Local-gov",171095,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States",">50K" +23,"Private",239322,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",138999,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",176520,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +38,"Local-gov",72338,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","Asian-Pac-Islander","Male",0,0,54,"United-States",">50K" +60,"?",386261,"Bachelors",13,"Married-spouse-absent","?","Unmarried","Black","Female",0,0,15,"United-States","<=50K" +23,"Private",235722,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +36,"Federal-gov",128884,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +46,"Private",187226,"9th",5,"Divorced","Other-service","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +32,"Self-emp-not-inc",298332,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +40,"Private",173607,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",226756,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,40,"United-States","<=50K" +31,"Private",157887,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +32,"State-gov",171111,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +21,"Private",126314,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,10,"United-States","<=50K" +63,"Private",174018,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States",">50K" +44,"Private",144778,"Some-college",10,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States",">50K" +42,"Self-emp-not-inc",201522,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +23,"?",22966,"Bachelors",13,"Never-married","?","Own-child","White","Male",0,0,35,"United-States","<=50K" +30,"Private",399088,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +24,"Private",282202,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Male",0,0,40,"El-Salvador","<=50K" +42,"Private",102606,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Self-emp-not-inc",246862,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"Italy",">50K" +27,"Federal-gov",508336,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,48,"United-States","<=50K" +27,"Local-gov",263431,"Some-college",10,"Never-married","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +22,"Private",235733,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +68,"Private",107910,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",184425,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,99,"United-States",">50K" +22,"Self-emp-not-inc",143062,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"Greece","<=50K" +25,"Private",199545,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,15,"United-States","<=50K" +68,"Self-emp-not-inc",197015,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +62,"Private",149617,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +26,"Private",33610,"HS-grad",9,"Divorced","Other-service","Other-relative","White","Male",0,0,40,"United-States","<=50K" +34,"Private",192002,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +68,"Private",67791,"Some-college",10,"Widowed","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",445382,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States",">50K" +45,"Private",112283,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +26,"Private",157249,"11th",7,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",109872,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +23,"Private",119838,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,50,"United-States","<=50K" +65,"Without-pay",27012,"7th-8th",4,"Widowed","Farming-fishing","Unmarried","White","Female",0,0,50,"United-States","<=50K" +31,"Private",91666,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +26,"Private",270276,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",179271,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Private",161819,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Self-emp-not-inc",219897,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +26,"Private",91683,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States","<=50K" +36,"Private",188834,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +38,"Private",187046,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +39,"Private",191807,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,48,"United-States","<=50K" +52,"Self-emp-inc",179951,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",324420,"1st-4th",2,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"Mexico","<=50K" +41,"Self-emp-not-inc",66632,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",162034,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States","<=50K" +28,"Local-gov",218990,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,46,"United-States","<=50K" +25,"Local-gov",125863,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,35,"United-States","<=50K" +35,"Private",225330,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",120426,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",119741,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +44,"Private",32000,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,18,"United-States",">50K" +21,"?",124242,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Private",278581,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +30,"Private",230224,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States",">50K" +20,"Private",164922,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +57,"Private",195176,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +43,"Private",166740,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +50,"?",156008,"11th",7,"Married-civ-spouse","?","Own-child","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",162551,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Other-relative","Asian-Pac-Islander","Female",0,0,48,"China","<=50K" +25,"Private",211231,"HS-grad",9,"Married-civ-spouse","Tech-support","Other-relative","White","Female",0,0,48,"United-States",">50K" +25,"Private",169990,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +90,"Private",221832,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +38,"Local-gov",255454,"Bachelors",13,"Separated","Prof-specialty","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",28160,"Bachelors",13,"Married-spouse-absent","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +50,"State-gov",159219,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Canada",">50K" +26,"Local-gov",103148,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",165186,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +56,"Private",31782,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Local-gov",249101,"HS-grad",9,"Divorced","Protective-serv","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +18,"Local-gov",153405,"11th",7,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,25,"United-States","<=50K" +57,"Private",176079,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"State-gov",218542,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +29,"State-gov",303446,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,25,"Nicaragua","<=50K" +40,"Private",102606,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Self-emp-not-inc",483201,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +77,"Local-gov",144608,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,6,"United-States","<=50K" +30,"Private",226013,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",165475,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +66,"Private",263637,"10th",6,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",201495,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,35,"United-States","<=50K" +68,"Private",213720,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Private",170483,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +26,"Private",214303,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +32,"Private",190511,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",242150,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,38,"United-States","<=50K" +51,"Local-gov",159755,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Private",268022,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",188711,"Bachelors",13,"Never-married","Transport-moving","Unmarried","White","Male",0,0,20,"United-States","<=50K" +29,"Private",452205,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,36,"United-States","<=50K" +21,"Private",260847,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +28,"Private",291374,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +55,"Private",189933,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",133969,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,50,"South",">50K" +35,"Private",330664,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"?",672412,"11th",7,"Separated","?","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",111415,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,55,"Germany","<=50K" +33,"Private",217235,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"United-States","<=50K" +23,"Private",120172,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",343403,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-not-inc",104790,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States",">50K" +39,"Local-gov",473547,"10th",6,"Divorced","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +53,"Local-gov",260106,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +49,"Federal-gov",168232,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",348491,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",421065,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +54,"Self-emp-inc",138852,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +28,"?",169631,"Assoc-acdm",12,"Married-AF-spouse","?","Wife","White","Female",0,0,3,"United-States","<=50K" +34,"Private",379412,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",181992,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +19,"Private",365640,"HS-grad",9,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,45,"?","<=50K" +26,"Private",236564,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",363418,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,70,"United-States",">50K" +50,"Private",112351,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,38,"United-States","<=50K" +30,"Private",204704,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States",">50K" +44,"Private",54611,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +49,"Private",128132,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +75,"Self-emp-not-inc",30599,"Masters",14,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +37,"Private",379522,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +51,"State-gov",196504,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,38,"United-States","<=50K" +35,"Private",82552,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,35,"United-States","<=50K" +28,"Private",104024,"Some-college",10,"Never-married","Sales","Other-relative","White","Female",0,0,40,"United-States","<=50K" +72,"Private",74141,"9th",5,"Married-civ-spouse","Exec-managerial","Wife","Asian-Pac-Islander","Female",0,0,48,"United-States",">50K" +39,"Private",192337,"Bachelors",13,"Separated","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +27,"Private",262478,"HS-grad",9,"Never-married","Farming-fishing","Own-child","Black","Male",0,0,30,"United-States","<=50K" +57,"Private",185072,"Some-college",10,"Never-married","Adm-clerical","Other-relative","Black","Female",0,0,40,"Jamaica","<=50K" +28,"Private",246595,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,70,"United-States","<=50K" +23,"Private",54472,"Some-college",10,"Married-spouse-absent","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +23,"Private",161708,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +31,"Private",264936,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Local-gov",113545,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",170430,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,80,"?","<=50K" +39,"Private",505119,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Cuba",">50K" +23,"Private",193089,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Local-gov",33432,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +36,"Private",103110,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"England","<=50K" +32,"Private",160362,"Some-college",10,"Divorced","Other-service","Other-relative","White","Male",0,0,40,"Nicaragua","<=50K" +35,"Private",204621,"Assoc-acdm",12,"Divorced","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",35309,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"?",154373,"Bachelors",13,"Never-married","?","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +47,"Private",194772,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",154410,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Federal-gov",220563,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"State-gov",253354,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",229732,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",185465,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",335764,"11th",7,"Married-civ-spouse","Sales","Own-child","Black","Male",0,0,35,"United-States","<=50K" +23,"Private",460046,"HS-grad",9,"Separated","Exec-managerial","Unmarried","White","Female",0,0,42,"United-States","<=50K" +19,"?",33487,"Some-college",10,"Never-married","?","Other-relative","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +50,"Private",176924,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,38,"United-States","<=50K" +49,"State-gov",213307,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",83893,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",194102,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +61,"Private",238611,"7th-8th",4,"Widowed","Other-service","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +41,"Private",113597,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,16,"United-States","<=50K" +27,"Self-emp-not-inc",208406,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +53,"Private",274528,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +17,"Self-emp-not-inc",60116,"10th",6,"Never-married","Adm-clerical","Own-child","White","Male",0,0,10,"United-States","<=50K" +23,"?",196816,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +53,"Private",166368,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",99386,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",188569,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +53,"Private",302868,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +18,"Private",283342,"11th",7,"Never-married","Other-service","Other-relative","Black","Male",0,0,20,"United-States","<=50K" +24,"Private",233777,"Some-college",10,"Never-married","Sales","Unmarried","White","Male",0,0,50,"Mexico","<=50K" +20,"Private",170038,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Local-gov",261319,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",126838,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",354104,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +20,"Private",176321,"12th",8,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"Mexico","<=50K" +47,"Private",85129,"HS-grad",9,"Divorced","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +20,"?",376474,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,32,"United-States","<=50K" +22,"Private",62507,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +60,"Private",156889,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",549430,"HS-grad",9,"Never-married","Priv-house-serv","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +46,"Private",29696,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +66,"Private",98837,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",86150,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","Asian-Pac-Islander","Female",0,0,30,"United-States",">50K" +34,"Private",204991,"Some-college",10,"Divorced","Exec-managerial","Own-child","White","Male",0,0,44,"United-States","<=50K" +45,"Private",371886,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,46,"United-States","<=50K" +35,"Private",103605,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"?",54851,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Local-gov",133050,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +36,"Local-gov",126569,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Federal-gov",144259,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,40,"United-States","<=50K" +51,"Private",161482,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,38,"United-States","<=50K" +25,"Self-emp-not-inc",305449,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",125010,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,45,"United-States","<=50K" +47,"Private",304133,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +59,"Local-gov",120617,"HS-grad",9,"Separated","Protective-serv","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +34,"Private",157747,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",297396,"Some-college",10,"Separated","Exec-managerial","Unmarried","White","Female",0,0,60,"United-States","<=50K" +42,"Private",121287,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +28,"?",308493,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,17,"Honduras","<=50K" +37,"Private",49115,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +51,"Self-emp-inc",208302,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,38,"United-States",">50K" +25,"Private",304032,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,36,"United-States","<=50K" +31,"Federal-gov",207301,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +37,"Private",123211,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,44,"United-States",">50K" +42,"Private",33521,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +29,"?",410351,"Bachelors",13,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",410034,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +51,"Private",175339,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,47,"United-States",">50K" +22,"?",27937,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,36,"United-States","<=50K" +26,"Private",125680,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,16,"Japan","<=50K" +56,"Local-gov",160829,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,46,"United-States","<=50K" +52,"Private",266529,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +61,"Self-emp-not-inc",115023,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,4,"?","<=50K" +47,"State-gov",224149,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +52,"Private",150930,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",343699,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",163392,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +17,"?",103810,"12th",8,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",211265,"Some-college",10,"Married-spouse-absent","Craft-repair","Other-relative","Black","Female",0,0,35,"Dominican-Republic","<=50K" +58,"Local-gov",160586,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",203277,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States",">50K" +46,"Private",309895,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +57,"Private",103809,"HS-grad",9,"Never-married","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",90291,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"State-gov",181761,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,10,"United-States","<=50K" +45,"Local-gov",135776,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +61,"?",188172,"Doctorate",16,"Widowed","?","Not-in-family","White","Female",0,0,5,"United-States","<=50K" +39,"Private",179579,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Private",193626,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,53,"United-States","<=50K" +20,"Private",108887,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"Private",199070,"HS-grad",9,"Never-married","Protective-serv","Own-child","Black","Male",0,0,16,"United-States","<=50K" +25,"Private",441591,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",185254,"5th-6th",3,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,40,"El-Salvador","<=50K" +24,"Private",109307,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,45,"United-States","<=50K" +20,"?",81853,"Some-college",10,"Never-married","?","Own-child","Asian-Pac-Islander","Female",0,0,15,"United-States","<=50K" +35,"Private",23621,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +44,"Local-gov",145178,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,38,"Jamaica",">50K" +47,"State-gov",30575,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"State-gov",130620,"11th",7,"Separated","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,40,"India","<=50K" +41,"Local-gov",22155,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,60,"United-States","<=50K" +31,"Private",106437,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",79787,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +44,"Private",81853,"HS-grad",9,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +61,"Private",120933,"Some-college",10,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Federal-gov",153143,"Some-college",10,"Divorced","Adm-clerical","Other-relative","White","Female",0,0,40,"Puerto-Rico","<=50K" +46,"Private",27669,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +46,"Private",105444,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +54,"Local-gov",169785,"Masters",14,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,38,"United-States","<=50K" +49,"Private",122493,"HS-grad",9,"Widowed","Tech-support","Unmarried","White","Male",0,0,40,"United-States","<=50K" +56,"Local-gov",242670,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +52,"Private",54933,"Masters",14,"Divorced","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",209317,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +25,"Self-emp-not-inc",282631,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",98044,"11th",7,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +58,"Private",187487,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"State-gov",60186,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",75648,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +28,"Private",201175,"11th",7,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",19302,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +21,"?",300812,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +75,"Private",101887,"10th",6,"Widowed","Priv-house-serv","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +66,"?",117778,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",60726,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-inc",201763,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +47,"Self-emp-not-inc",121124,"5th-6th",3,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"Italy",">50K" +21,"Private",60639,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +17,"Private",195262,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,17,"United-States","<=50K" +61,"?",113544,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,55,"United-States","<=50K" +47,"?",331650,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,8,"United-States",">50K" +22,"Private",100587,"Some-college",10,"Never-married","Other-service","Own-child","Black","Female",0,0,15,"United-States","<=50K" +47,"Private",298130,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",242391,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Self-emp-not-inc",197867,"Assoc-voc",11,"Divorced","Sales","Unmarried","White","Male",0,0,50,"United-States","<=50K" +59,"Private",151977,"10th",6,"Separated","Priv-house-serv","Not-in-family","Black","Female",0,0,30,"United-States","<=50K" +38,"Private",277347,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +33,"Private",125249,"HS-grad",9,"Separated","Protective-serv","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Private",222142,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",270194,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",169995,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +27,"Private",359155,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +60,"Private",123992,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +64,"Local-gov",266080,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +37,"Private",201531,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Self-emp-not-inc",179704,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +36,"Private",393673,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +34,"Private",244147,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?",">50K" +41,"Self-emp-not-inc",438696,"Masters",14,"Divorced","Sales","Unmarried","White","Male",0,0,5,"United-States",">50K" +35,"Self-emp-not-inc",207568,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,75,"United-States","<=50K" +63,"Self-emp-inc",54052,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,68,"United-States",">50K" +46,"Private",187581,"HS-grad",9,"Divorced","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",77102,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",353010,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +29,"Private",54131,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +74,"Federal-gov",39890,"Some-college",10,"Widowed","Transport-moving","Not-in-family","White","Female",0,0,18,"United-States","<=50K" +50,"Private",156877,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,70,"United-States",">50K" +22,"Private",355686,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Private",300168,"12th",8,"Separated","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +30,"Private",488720,"9th",5,"Married-civ-spouse","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +32,"Private",157287,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",184659,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",214169,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",192149,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Private",137253,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +44,"Private",373050,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Federal-gov",183151,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,60,"United-States","<=50K" +55,"Private",227158,"Bachelors",13,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Local-gov",34021,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,50,"United-States","<=50K" +31,"Private",165148,"HS-grad",9,"Separated","Exec-managerial","Unmarried","White","Female",0,0,12,"United-States","<=50K" +47,"Private",211668,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","Black","Female",0,0,40,"United-States",">50K" +45,"Private",358886,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",47707,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",306982,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,60,"South","<=50K" +49,"Local-gov",52590,"HS-grad",9,"Widowed","Protective-serv","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +39,"?",179352,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +27,"Private",158156,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +42,"Private",70055,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"?",131852,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States",">50K" +33,"Private",127215,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States",">50K" +23,"Private",175183,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",142287,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Private",221324,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +53,"Private",227602,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,37,"Mexico","<=50K" +22,"Private",228452,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +57,"State-gov",39380,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +20,"?",96862,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,8,"United-States","<=50K" +23,"Private",336360,"7th-8th",4,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +31,"Private",257644,"11th",7,"Never-married","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +23,"State-gov",235853,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,22,"United-States","<=50K" +30,"Private",270577,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Local-gov",222900,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States",">50K" +42,"Private",99254,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States",">50K" +51,"Private",224763,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Cuba","<=50K" +36,"Private",127306,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Private",339506,"HS-grad",9,"Never-married","Sales","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",178322,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"Germany",">50K" +33,"Private",189843,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",160815,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +60,"Private",207665,"HS-grad",9,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States",">50K" +37,"State-gov",160402,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +35,"Private",170263,"Some-college",10,"Never-married","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",184659,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,52,"United-States","<=50K" +54,"Private",101017,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",204322,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",241350,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +63,"Federal-gov",217994,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +51,"Private",128143,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Self-emp-not-inc",164065,"Masters",14,"Divorced","Sales","Not-in-family","White","Male",0,0,18,"United-States","<=50K" +64,"Local-gov",78866,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",236769,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Federal-gov",239539,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +39,"Private",34028,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,48,"United-States","<=50K" +45,"State-gov",207847,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",175935,"Doctorate",16,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,55,"United-States",">50K" +22,"Federal-gov",218445,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +63,"Self-emp-inc",215833,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",156976,"Assoc-voc",11,"Separated","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",220647,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +20,"Private",218343,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +25,"Private",73289,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",408623,"Bachelors",13,"Married-civ-spouse","Craft-repair","Other-relative","White","Male",0,0,50,"United-States","<=50K" +46,"Private",169180,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",54929,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +24,"Private",306779,"Assoc-voc",11,"Never-married","Exec-managerial","Own-child","White","Male",0,0,35,"United-States","<=50K" +43,"Private",159549,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",482082,"12th",8,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,21,"Mexico","<=50K" +32,"Local-gov",286101,"HS-grad",9,"Never-married","Transport-moving","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +44,"Private",167955,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Poland","<=50K" +40,"Self-emp-not-inc",209040,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",105017,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +23,"Private",27776,"Assoc-voc",11,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",118853,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",119565,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",275361,"Assoc-acdm",12,"Widowed","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +42,"Private",225193,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",329783,"10th",6,"Never-married","Sales","Other-relative","White","Female",0,0,10,"United-States","<=50K" +29,"Local-gov",107411,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +21,"State-gov",258490,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +18,"?",120243,"11th",7,"Never-married","?","Own-child","White","Male",0,0,27,"United-States","<=50K" +31,"Private",219509,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico",">50K" +27,"Local-gov",29174,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",40083,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"Canada","<=50K" +23,"Private",87528,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +41,"Private",116379,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,55,"Taiwan",">50K" +46,"Local-gov",216214,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +34,"Private",268051,"Some-college",10,"Married-civ-spouse","Protective-serv","Other-relative","Black","Female",0,0,25,"Haiti","<=50K" +42,"Self-emp-not-inc",121718,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,24,"United-States","<=50K" +46,"Private",109089,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +18,"?",346382,"11th",7,"Never-married","?","Own-child","White","Male",0,0,15,"United-States","<=50K" +52,"Private",284129,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Private",143030,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +21,"Private",212619,"Assoc-voc",11,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Self-emp-not-inc",199011,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,20,"United-States","<=50K" +31,"Private",118901,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +41,"Self-emp-not-inc",129865,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,60,"United-States","<=50K" +25,"Private",157900,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",349341,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +45,"Private",158685,"HS-grad",9,"Separated","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",386585,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +90,"Private",52386,"Some-college",10,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,35,"United-States","<=50K" +30,"Private",190385,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States",">50K" +42,"Private",37869,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",217807,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +64,"State-gov",201293,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +56,"Private",128764,"7th-8th",4,"Widowed","Transport-moving","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +42,"Private",27444,"Some-college",10,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +26,"Private",62438,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +31,"Local-gov",151726,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +40,"Private",29841,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +58,"Private",131608,"Some-college",10,"Widowed","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",110562,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-inc",190541,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,47,"United-States","<=50K" +62,"State-gov",33142,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +40,"Private",234633,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Local-gov",238386,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",460835,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,55,"United-States","<=50K" +23,"?",243190,"Some-college",10,"Never-married","?","Own-child","Asian-Pac-Islander","Male",0,0,20,"China","<=50K" +63,"Federal-gov",97855,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",200863,"Some-college",10,"Widowed","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +25,"?",41107,"Bachelors",13,"Married-spouse-absent","?","Not-in-family","White","Male",0,0,40,"Canada","<=50K" +56,"Private",77415,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",236770,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +32,"Private",235124,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",199288,"11th",7,"Separated","Transport-moving","Not-in-family","White","Male",0,0,90,"United-States","<=50K" +19,"Private",43285,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +41,"Private",160837,"11th",7,"Married-spouse-absent","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"Guatemala","<=50K" +22,"Private",230574,"10th",6,"Never-married","Transport-moving","Own-child","White","Male",0,0,25,"United-States","<=50K" +23,"Private",176178,"HS-grad",9,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",116358,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Taiwan",">50K" +27,"?",253873,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +45,"Private",107787,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Canada","<=50K" +23,"Self-emp-not-inc",519627,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,25,"Mexico","<=50K" +21,"Private",191460,"11th",7,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",214858,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Self-emp-not-inc",64875,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,60,"United-States","<=50K" +62,"Self-emp-not-inc",134768,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Federal-gov",207342,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +34,"Private",64830,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +33,"Private",176711,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"England","<=50K" +22,"?",217421,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +28,"Private",111900,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +22,"?",196943,"Some-college",10,"Separated","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +47,"Private",481987,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +20,"?",121313,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",158420,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +28,"Private",42734,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",181773,"HS-grad",9,"Never-married","Transport-moving","Own-child","Black","Male",0,0,40,"United-States","<=50K" +47,"Private",184945,"Some-college",10,"Separated","Other-service","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +33,"Private",107248,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +25,"Private",122999,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"State-gov",166606,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Local-gov",192060,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,30,"?","<=50K" +57,"Private",205708,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Poland","<=50K" +55,"Private",67450,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"England","<=50K" +20,"Private",242077,"HS-grad",9,"Divorced","Sales","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",129573,"HS-grad",9,"Never-married","Sales","Not-in-family","Black","Female",0,0,44,"United-States","<=50K" +54,"Private",181132,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"England",">50K" +25,"Private",212302,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"?",148751,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +17,"Private",317681,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,10,"United-States","<=50K" +63,"Private",30602,"7th-8th",4,"Married-spouse-absent","Other-service","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +19,"Private",172893,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,30,"United-States","<=50K" +33,"Self-emp-not-inc",312055,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +37,"Private",65390,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",200500,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +36,"Local-gov",241962,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Self-emp-inc",78530,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"Canada",">50K" +22,"Private",189950,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +20,"Private",241951,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +18,"Private",343059,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"?",79728,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",55284,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +34,"Private",509364,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +32,"State-gov",117927,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +20,"Private",137651,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +70,"Private",131060,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,25,"United-States","<=50K" +57,"Private",346963,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",134737,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",36503,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",250121,"11th",7,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +27,"Private",387776,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",41474,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +36,"Local-gov",318972,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,65,"United-States","<=50K" +33,"Private",86143,"Some-college",10,"Never-married","Exec-managerial","Own-child","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +50,"Private",181139,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Local-gov",153976,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Self-emp-not-inc",59469,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,25,"United-States","<=50K" +24,"Private",127139,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",136343,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",350624,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",121523,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +24,"Self-emp-not-inc",267396,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"Private",83045,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",160449,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,44,"United-States",">50K" +20,"?",287681,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,36,"United-States","<=50K" +41,"Private",154194,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",295127,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,84,"United-States","<=50K" +61,"Self-emp-not-inc",244087,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States",">50K" +35,"Private",356250,"Prof-school",15,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,35,"China","<=50K" +42,"State-gov",293791,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",44308,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Local-gov",210527,"Some-college",10,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +31,"State-gov",151763,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +39,"State-gov",267581,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",100188,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,24,"United-States","<=50K" +32,"Self-emp-inc",111746,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",171091,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",355645,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,20,"Trinadad&Tobago","<=50K" +54,"Local-gov",137678,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",70894,"Assoc-acdm",12,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +19,"Private",171306,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,3,"United-States","<=50K" +31,"Private",100997,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +35,"Private",63921,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +29,"Private",32897,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +29,"Local-gov",251854,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +25,"Private",345121,"10th",6,"Separated","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +46,"Private",86220,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",172845,"Assoc-voc",11,"Never-married","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +20,"Private",171398,"10th",6,"Never-married","Sales","Not-in-family","Other","Male",0,0,40,"United-States","<=50K" +24,"Self-emp-not-inc",174391,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +48,"Private",207058,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,37,"United-States","<=50K" +37,"Private",291251,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",224377,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",105813,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Local-gov",180916,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +31,"Self-emp-not-inc",122749,"Assoc-voc",11,"Divorced","Craft-repair","Own-child","White","Male",0,0,20,"United-States","<=50K" +26,"Self-emp-not-inc",284343,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",174224,"Assoc-voc",11,"Divorced","Protective-serv","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +69,"?",183958,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +48,"Private",80651,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +46,"Private",62793,"HS-grad",9,"Divorced","Sales","Other-relative","White","Female",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",237532,"HS-grad",9,"Married-civ-spouse","Sales","Wife","Black","Female",0,0,54,"Dominican-Republic",">50K" +50,"Federal-gov",20179,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",311376,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",432565,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Other-relative","White","Female",0,0,40,"Canada",">50K" +29,"Self-emp-not-inc",125190,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",342946,"11th",7,"Never-married","Transport-moving","Own-child","White","Female",0,0,38,"United-States","<=50K" +21,"?",219835,"Assoc-voc",11,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",123429,"10th",6,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"Private",66356,"HS-grad",9,"Separated","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +41,"Private",195897,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +18,"Private",230875,"11th",7,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +74,"Self-emp-not-inc",92298,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,10,"United-States","<=50K" +40,"Private",185145,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",297296,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",145214,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",242341,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +54,"Private",240542,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,48,"United-States","<=50K" +36,"Private",104772,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,48,"United-States","<=50K" +76,"?",152802,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +26,"Private",181666,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +18,"Private",415520,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,20,"United-States","<=50K" +38,"Private",258761,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +19,"?",356717,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,25,"United-States","<=50K" +32,"Private",158438,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +57,"Private",206206,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",51816,"HS-grad",9,"Never-married","Protective-serv","Own-child","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",253814,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"Private",162947,"5th-6th",3,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"Puerto-Rico","<=50K" +52,"Private",163027,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,50,"United-States","<=50K" +61,"Private",146788,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",73309,"HS-grad",9,"Widowed","Craft-repair","Not-in-family","White","Male",0,0,55,"United-States",">50K" +19,"?",143867,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",104216,"Prof-school",15,"Married-civ-spouse","Sales","Husband","White","Male",0,0,25,"United-States","<=50K" +34,"Self-emp-not-inc",345705,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States",">50K" +31,"Private",133770,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,0,50,"United-States",">50K" +42,"Private",209392,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","Black","Male",0,0,35,"United-States","<=50K" +70,"Private",262345,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,6,"United-States","<=50K" +47,"Private",277545,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"?",">50K" +29,"Private",490332,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +27,"Private",211570,"11th",7,"Never-married","Handlers-cleaners","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",374918,"12th",8,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +28,"Private",173649,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"?","<=50K" +35,"Private",174597,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",233533,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +54,"?",169785,"Masters",14,"Never-married","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",133169,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",198824,"Assoc-voc",11,"Separated","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +65,"Private",174056,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",188696,"Assoc-voc",11,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",90692,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",102359,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"United-States","<=50K" +49,"Federal-gov",213668,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,56,"United-States",">50K" +21,"Private",294789,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +20,"Private",157599,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +18,"Local-gov",134935,"12th",8,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",466224,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",111985,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +38,"Private",264627,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",213427,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",279015,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +47,"Private",165937,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Federal-gov",188343,"HS-grad",9,"Separated","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +63,"Private",158609,"Assoc-voc",11,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,8,"United-States","<=50K" +34,"Private",193036,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States",">50K" +25,"Private",198632,"Some-college",10,"Married-spouse-absent","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +19,"?",192773,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +35,"Private",101387,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +24,"Private",60783,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,70,"United-States",">50K" +26,"Private",183224,"Some-college",10,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,35,"United-States","<=50K" +59,"Local-gov",100776,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",57600,"Doctorate",16,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Female",0,0,40,"?","<=50K" +20,"Private",174063,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Private",306495,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",249741,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",93021,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Other","Female",0,0,40,"United-States","<=50K" +36,"Private",49626,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",63062,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,60,"United-States","<=50K" +55,"Private",320835,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Local-gov",123727,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,21,"United-States","<=50K" +39,"Private",172425,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States",">50K" +40,"Private",216116,"9th",5,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"Haiti","<=50K" +46,"Private",174209,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +54,"Federal-gov",175083,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,20,"United-States","<=50K" +19,"Private",129059,"Some-college",10,"Never-married","Sales","Own-child","Black","Male",0,0,30,"United-States","<=50K" +24,"Private",121313,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"?",181317,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"State-gov",166851,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,13,"United-States","<=50K" +29,"Self-emp-not-inc",29616,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,65,"United-States","<=50K" +54,"?",124993,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +21,"?",148509,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +34,"Private",230246,"9th",5,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"?","<=50K" +56,"Private",117881,"11th",7,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",446219,"10th",6,"Never-married","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +32,"Self-emp-inc",110331,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States",">50K" +48,"Private",207946,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,52,"United-States","<=50K" +67,"?",45537,"Masters",14,"Married-civ-spouse","?","Husband","Black","Male",0,0,40,"United-States",">50K" +47,"Private",188330,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,25,"United-States","<=50K" +52,"Private",147629,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +40,"Private",153799,"1st-4th",2,"Married-spouse-absent","Machine-op-inspct","Unmarried","White","Female",0,0,40,"Dominican-Republic","<=50K" +28,"Private",203776,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"Private",348430,"1st-4th",2,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"Portugal","<=50K" +51,"Private",103407,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"?",152046,"11th",7,"Never-married","?","Not-in-family","White","Female",0,0,35,"Germany","<=50K" +36,"Private",153205,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,45,"?","<=50K" +33,"Private",326104,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +46,"Private",238162,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +50,"Private",221336,"HS-grad",9,"Divorced","Adm-clerical","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +33,"Private",180656,"Some-college",10,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"?","<=50K" +67,"?",150516,"HS-grad",9,"Widowed","?","Unmarried","White","Male",0,0,3,"United-States","<=50K" +35,"Private",325802,"Assoc-acdm",12,"Divorced","Handlers-cleaners","Unmarried","White","Female",0,0,24,"United-States","<=50K" +23,"Private",133985,"10th",6,"Never-married","Craft-repair","Own-child","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",183203,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +60,"Private",76127,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"United-States",">50K" +32,"Private",195891,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +56,"Federal-gov",162137,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +45,"State-gov",37672,"Assoc-voc",11,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",161708,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States",">50K" +18,"Private",80616,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,27,"United-States","<=50K" +31,"Private",209276,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Other","Male",0,0,40,"United-States","<=50K" +21,"?",34443,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,50,"United-States","<=50K" +23,"Private",203240,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"State-gov",102308,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",40829,"11th",7,"Never-married","Sales","Other-relative","Amer-Indian-Eskimo","Female",0,0,25,"United-States","<=50K" +25,"Private",60726,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,30,"United-States","<=50K" +31,"State-gov",116677,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",57067,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,45,"United-States","<=50K" +41,"Private",304906,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +74,"Private",101590,"Prof-school",15,"Widowed","Adm-clerical","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +27,"Private",258102,"5th-6th",3,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +23,"Private",241185,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",124827,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Self-emp-inc",76625,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Federal-gov",263339,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",135645,"Masters",14,"Never-married","Sales","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +42,"Private",245626,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,0,60,"United-States","<=50K" +24,"Private",210781,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",235786,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Self-emp-not-inc",160167,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States","<=50K" +34,"Private",314375,"Assoc-voc",11,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",81528,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,60,"United-States","<=50K" +54,"Private",182854,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +40,"?",70645,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"United-States","<=50K" +55,"Self-emp-inc",141807,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +66,"?",112871,"11th",7,"Never-married","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +52,"State-gov",71344,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"State-gov",341410,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +33,"Private",118941,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +52,"?",159755,"Assoc-voc",11,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",128509,"5th-6th",3,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"?","<=50K" +27,"Self-emp-not-inc",229125,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",142756,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +27,"Self-emp-inc",243871,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,45,"United-States","<=50K" +19,"Private",196857,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",138626,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",161334,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,25,"Nicaragua","<=50K" +50,"Private",273536,"7th-8th",4,"Married-civ-spouse","Sales","Husband","Other","Male",0,0,49,"Dominican-Republic","<=50K" +28,"Private",185957,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +23,"Private",334357,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",96102,"Masters",14,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +34,"Private",213226,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Iran",">50K" +19,"Private",115248,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +37,"Private",185061,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,55,"United-States","<=50K" +27,"Private",147638,"Bachelors",13,"Never-married","Adm-clerical","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Hong","<=50K" +18,"Private",280298,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,24,"United-States","<=50K" +31,"Private",163516,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Private",277434,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Federal-gov",206983,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"Columbia","<=50K" +48,"Private",108993,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +39,"Private",288551,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +41,"Private",176069,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +48,"State-gov",183486,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,56,"United-States",">50K" +70,"Private",94692,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States",">50K" +20,"Private",118462,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,43,"United-States","<=50K" +38,"Private",407068,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,75,"Mexico","<=50K" +37,"Self-emp-not-inc",243587,"Some-college",10,"Separated","Other-service","Own-child","White","Female",0,0,40,"Cuba","<=50K" +49,"Private",23074,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +43,"Private",188291,"1st-4th",2,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",284166,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +18,"?",423460,"11th",7,"Never-married","?","Own-child","White","Male",0,0,36,"United-States","<=50K" +23,"Private",287681,"7th-8th",4,"Never-married","Other-service","Not-in-family","White","Male",0,0,25,"Mexico","<=50K" +34,"Private",509364,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"?",139391,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,24,"United-States","<=50K" +33,"Private",91964,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +31,"Private",117526,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +64,"Private",91343,"Some-college",10,"Widowed","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Local-gov",336969,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,28,"El-Salvador","<=50K" +55,"Private",255364,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Local-gov",167670,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",211494,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +78,"Local-gov",136198,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,15,"United-States","<=50K" +27,"Federal-gov",409815,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +49,"Private",188823,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +42,"Private",154374,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,58,"United-States","<=50K" +22,"?",216563,"HS-grad",9,"Never-married","?","Other-relative","White","Female",0,0,40,"United-States","<=50K" +61,"Private",197286,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Self-emp-not-inc",100722,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,5,"United-States","<=50K" +46,"Local-gov",377622,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",145964,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",57413,"Some-college",10,"Divorced","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +48,"Private",320421,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +50,"Self-emp-not-inc",174752,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"State-gov",229364,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +56,"Self-emp-not-inc",157486,"10th",6,"Divorced","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +56,"Federal-gov",101338,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",132652,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +21,"Private",34616,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +40,"Private",218903,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Local-gov",204098,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Other-relative","White","Male",0,0,50,"United-States","<=50K" +46,"Private",189763,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +23,"Private",26248,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Private",92079,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +19,"Private",280071,"Some-college",10,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,50,"United-States","<=50K" +20,"Private",224059,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",265567,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +72,"Private",106890,"Assoc-voc",11,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"State-gov",39586,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,20,"United-States",">50K" +42,"Private",153132,"Bachelors",13,"Divorced","Sales","Unmarried","White","Male",0,0,45,"?","<=50K" +51,"Private",209912,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","Amer-Indian-Eskimo","Male",0,0,50,"United-States","<=50K" +39,"Private",144169,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Private",89644,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +19,"Private",275889,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"Mexico","<=50K" +26,"Private",231638,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"Private",355259,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +30,"Federal-gov",68330,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +32,"Private",185410,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",87653,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +21,"Private",286853,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +54,"Private",96710,"HS-grad",9,"Married-civ-spouse","Priv-house-serv","Other-relative","Black","Female",0,0,20,"United-States","<=50K" +62,"Private",160143,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States",">50K" +49,"Self-emp-inc",109705,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,32,"United-States","<=50K" +32,"Private",94235,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Local-gov",297449,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Private",205896,"HS-grad",9,"Divorced","Sales","Other-relative","White","Female",0,0,40,"United-States","<=50K" +41,"Private",194710,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"State-gov",189123,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",358677,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Male",0,0,35,"United-States","<=50K" +34,"Private",231238,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +46,"Private",166003,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",281437,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +20,"Private",190231,"9th",5,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,11,"Nicaragua","<=50K" +47,"Private",122026,"Assoc-voc",11,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +55,"?",205527,"HS-grad",9,"Divorced","?","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +43,"Private",125461,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States",">50K" +80,"Self-emp-not-inc",184335,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +24,"Private",211345,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"Mexico","<=50K" +22,"Private",222993,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",225978,"Some-college",10,"Separated","Exec-managerial","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +48,"Private",121124,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +56,"?",656036,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States","<=50K" +34,"?",346762,"11th",7,"Divorced","?","Own-child","White","Male",0,0,84,"United-States","<=50K" +51,"Private",234057,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Federal-gov",306515,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",116562,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",171159,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,30,"United-States","<=50K" +24,"Private",199011,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",443508,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"Canada",">50K" +24,"Private",29810,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +22,"Local-gov",238831,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Federal-gov",566117,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",255044,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +20,"Private",436253,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +31,"Private",300687,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +55,"Private",144071,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,18,"United-States",">50K" +26,"Private",188767,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",300777,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +35,"Private",26987,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",174395,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,60,"Greece","<=50K" +59,"Private",90290,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,34,"United-States","<=50K" +61,"Private",183735,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +31,"Private",123273,"HS-grad",9,"Never-married","Sales","Own-child","Black","Female",0,0,40,"United-States","<=50K" +43,"Federal-gov",186916,"Masters",14,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,60,"United-States",">50K" +54,"Private",178251,"Assoc-acdm",12,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,30,"United-States","<=50K" +30,"Private",255885,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"Private",64292,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +27,"State-gov",194773,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"Germany","<=50K" +44,"Self-emp-inc",133060,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +64,"Private",258006,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"Cuba","<=50K" +55,"Private",92215,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +61,"Private",153048,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +28,"Private",192200,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?","<=50K" +34,"Private",355571,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +26,"Private",34402,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +35,"Private",25955,"11th",7,"Never-married","Other-service","Unmarried","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +36,"Private",209609,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States","<=50K" +47,"Private",168283,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",295488,"11th",7,"Never-married","Other-service","Own-child","Black","Female",0,0,25,"United-States","<=50K" +35,"Private",190895,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +33,"Private",164190,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +25,"Private",216010,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +18,"Private",387568,"10th",6,"Never-married","Sales","Own-child","White","Male",0,0,10,"United-States","<=50K" +47,"State-gov",188386,"Masters",14,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +44,"Private",174491,"HS-grad",9,"Widowed","Other-service","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +41,"Private",31221,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +30,"Private",272451,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Self-emp-not-inc",152652,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +53,"Private",104413,"HS-grad",9,"Widowed","Other-service","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +27,"Private",214858,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Private",237735,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,37,"Mexico","<=50K" +36,"Private",158592,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Private",237321,"1st-4th",2,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico",">50K" +41,"Private",23646,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",169240,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Federal-gov",454508,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",130356,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,48,"United-States","<=50K" +22,"Private",427686,"10th",6,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Local-gov",36411,"12th",8,"Never-married","Prof-specialty","Own-child","White","Male",0,0,30,"United-States","<=50K" +39,"Private",548510,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,30,"United-States","<=50K" +38,"Private",187264,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,55,"United-States","<=50K" +35,"State-gov",140752,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",325596,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",175804,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",107302,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +63,"Local-gov",41161,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +39,"Private",401832,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States","<=50K" +57,"Self-emp-not-inc",353808,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +29,"Private",161478,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Japan","<=50K" +17,"Private",400225,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +40,"Private",367533,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +69,"Self-emp-not-inc",69306,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,15,"United-States","<=50K" +28,"Private",270366,"10th",6,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",103751,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"State-gov",79580,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +50,"Private",121685,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +48,"Private",75104,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"?",188343,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",246449,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +21,"Private",85088,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,37,"United-States","<=50K" +37,"Private",545483,"Assoc-acdm",12,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"State-gov",243986,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"United-States","<=50K" +54,"Self-emp-not-inc",32778,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,30,"United-States","<=50K" +28,"Private",369114,"HS-grad",9,"Separated","Sales","Other-relative","White","Female",0,0,40,"United-States","<=50K" +27,"Private",217200,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",149220,"Assoc-voc",11,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +46,"?",162034,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"?",157813,"11th",7,"Divorced","?","Unmarried","White","Female",0,0,58,"Canada","<=50K" +17,"?",179715,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",102308,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",367749,"1st-4th",2,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"El-Salvador","<=50K" +25,"Private",98281,"12th",8,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,43,"United-States","<=50K" +35,"Private",115792,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +29,"Private",277788,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,25,"United-States","<=50K" +30,"Private",103435,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +30,"Private",37646,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",385632,"7th-8th",4,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Self-emp-not-inc",210278,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,30,"United-States","<=50K" +28,"Private",335357,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",272165,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Local-gov",148995,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States",">50K" +46,"Self-emp-not-inc",113434,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"State-gov",132551,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,35,"United-States","<=50K" +29,"Private",227890,"HS-grad",9,"Never-married","Protective-serv","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",503012,"5th-6th",3,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +56,"Private",250873,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +31,"Private",407930,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",148187,"11th",7,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"United-States","<=50K" +31,"Private",159322,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +28,"Private",334368,"Some-college",10,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Private",196328,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States","<=50K" +45,"Private",270842,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +71,"Private",235079,"Preschool",1,"Widowed","Craft-repair","Unmarried","Black","Male",0,0,10,"United-States","<=50K" +65,"?",327154,"HS-grad",9,"Widowed","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Federal-gov",30559,"HS-grad",9,"Married-AF-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +34,"Local-gov",255098,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",248010,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +40,"Private",174515,"HS-grad",9,"Married-spouse-absent","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +90,"Private",171956,"Some-college",10,"Separated","Adm-clerical","Own-child","White","Female",0,0,40,"Puerto-Rico","<=50K" +56,"Private",193130,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,16,"United-States","<=50K" +21,"Private",108670,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Private",186172,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +45,"Private",348854,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,27,"United-States","<=50K" +46,"Private",271828,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +64,"Private",148606,"10th",6,"Separated","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +29,"Local-gov",123983,"Masters",14,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Male",0,0,40,"Taiwan","<=50K" +22,"Private",24896,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",0,0,30,"Germany","<=50K" +47,"Private",573583,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"Italy",">50K" +43,"Private",307767,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",200574,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",358056,"11th",7,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +17,"Private",206010,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,8,"United-States","<=50K" +55,"Self-emp-inc",183869,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"?",">50K" +28,"Private",159001,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +24,"Private",155818,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",96055,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +30,"Local-gov",131776,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",228613,"11th",7,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",198163,"Masters",14,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +38,"Private",37028,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,38,"United-States","<=50K" +30,"Private",177304,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",144064,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",146659,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +63,"Self-emp-not-inc",26904,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,98,"United-States","<=50K" +23,"Private",238917,"7th-8th",4,"Never-married","Craft-repair","Other-relative","White","Male",0,0,36,"United-States","<=50K" +56,"Private",170148,"HS-grad",9,"Divorced","Craft-repair","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",27821,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +40,"Private",220460,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Canada","<=50K" +35,"Private",173858,"HS-grad",9,"Married-spouse-absent","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +52,"Private",91048,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","Black","Female",0,0,35,"United-States","<=50K" +28,"Private",298696,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",207202,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,70,"United-States","<=50K" +21,"?",230397,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,5,"United-States","<=50K" +43,"Self-emp-not-inc",180599,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +32,"?",199046,"Assoc-voc",11,"Never-married","?","Unmarried","White","Female",0,0,2,"United-States","<=50K" +29,"Self-emp-not-inc",132686,"Prof-school",15,"Never-married","Prof-specialty","Own-child","White","Male",0,0,50,"Italy",">50K" +23,"Private",240063,"Bachelors",13,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,25,"United-States","<=50K" +34,"Private",511361,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +19,"Private",89397,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",239439,"11th",7,"Married-civ-spouse","Machine-op-inspct","Wife","Black","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",36989,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",76978,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +75,"Private",200068,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +24,"Private",454941,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"State-gov",107218,"Bachelors",13,"Never-married","Tech-support","Own-child","Asian-Pac-Islander","Male",0,0,20,"United-States","<=50K" +17,"Local-gov",182070,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +31,"Private",176360,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +31,"Private",452405,"Preschool",1,"Never-married","Other-service","Other-relative","White","Female",0,0,35,"Mexico","<=50K" +18,"?",297396,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,10,"United-States","<=50K" +45,"Private",84790,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +31,"Private",186787,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,42,"United-States","<=50K" +27,"Private",169662,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,42,"United-States",">50K" +22,"?",35448,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,22,"United-States","<=50K" +34,"Private",225548,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,30,"United-States","<=50K" +26,"Private",240842,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +53,"Private",103931,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Private",232618,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +49,"Local-gov",288548,"Masters",14,"Separated","Prof-specialty","Unmarried","White","Female",0,0,50,"United-States","<=50K" +40,"Private",220609,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-inc",26145,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,80,"United-States","<=50K" +23,"Private",268525,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +68,"?",133758,"7th-8th",4,"Widowed","?","Not-in-family","Black","Male",0,0,10,"United-States","<=50K" +42,"Private",121264,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Self-emp-not-inc",29814,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,85,"United-States","<=50K" +27,"Private",193701,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Female",0,0,45,"United-States","<=50K" +38,"Private",183279,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,44,"United-States",">50K" +27,"Private",163942,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"Ireland","<=50K" +75,"Private",188612,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Self-emp-inc",102771,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,52,"United-States",">50K" +27,"Private",85625,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +36,"Self-emp-not-inc",245090,"Bachelors",13,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"Mexico","<=50K" +35,"Private",182074,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +36,"Private",187046,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",90624,"11th",7,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",37933,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +61,"Private",716416,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States",">50K" +29,"Private",190562,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,56,"United-States","<=50K" +40,"State-gov",141583,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +37,"Private",98941,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +22,"Private",201729,"9th",5,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,30,"United-States","<=50K" +43,"Self-emp-inc",175485,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",149168,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +28,"Private",115971,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",161708,"Bachelors",13,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +64,"Local-gov",244903,"11th",7,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +46,"Private",155664,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",112754,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Private",178385,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,48,"India","<=50K" +20,"Private",44064,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,25,"United-States","<=50K" +62,"Self-emp-not-inc",120939,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",165134,"Assoc-voc",11,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,35,"Columbia","<=50K" +29,"Private",100405,"10th",6,"Married-civ-spouse","Farming-fishing","Wife","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",361888,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"Japan","<=50K" +39,"Local-gov",167864,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States","<=50K" +39,"Private",202950,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +37,"Private",218188,"HS-grad",9,"Divorced","Machine-op-inspct","Other-relative","White","Female",0,0,32,"United-States","<=50K" +72,"?",177226,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +31,"Private",259931,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",189528,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +38,"Private",34996,"Some-college",10,"Separated","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",112584,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +25,"Private",117589,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"?",145234,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +37,"Private",267086,"Assoc-voc",11,"Divorced","Tech-support","Unmarried","White","Female",0,0,52,"United-States","<=50K" +49,"Private",44434,"Some-college",10,"Divorced","Tech-support","Other-relative","White","Male",0,0,35,"United-States","<=50K" +26,"Private",96130,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +35,"Private",181382,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States","<=50K" +44,"Self-emp-inc",168845,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,60,"United-States","<=50K" +37,"Private",271767,"Masters",14,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States",">50K" +42,"Private",194636,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Private",132686,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +40,"State-gov",184378,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Federal-gov",270859,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",231866,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,65,"United-States","<=50K" +49,"Private",36032,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +51,"State-gov",172962,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Private",24185,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",53930,"10th",6,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"?","<=50K" +45,"Self-emp-not-inc",94962,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"England","<=50K" +28,"Private",480861,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"Private",52262,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"State-gov",52636,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Private",175273,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Private",125892,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,75,"United-States",">50K" +40,"?",78255,"HS-grad",9,"Divorced","?","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +30,"Private",398827,"HS-grad",9,"Married-AF-spouse","Adm-clerical","Husband","White","Male",0,0,60,"United-States","<=50K" +61,"Private",208919,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +71,"Local-gov",365996,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,6,"United-States","<=50K" +42,"Private",307638,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +44,"Local-gov",33068,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +46,"Self-emp-not-inc",254291,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +50,"Local-gov",125417,"Prof-school",15,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,52,"United-States",">50K" +27,"State-gov",28848,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,9,"United-States","<=50K" +40,"?",273425,"Assoc-voc",11,"Married-civ-spouse","?","Husband","White","Male",0,0,15,"United-States","<=50K" +21,"Private",194723,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"Mexico","<=50K" +25,"Private",195118,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,35,"United-States","<=50K" +54,"Private",220115,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +31,"Private",265706,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Self-emp-not-inc",279129,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +48,"Private",119199,"Bachelors",13,"Divorced","Sales","Unmarried","White","Female",0,0,44,"United-States","<=50K" +30,"Private",107793,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,56,"United-States",">50K" +35,"Private",237943,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,60,"United-States","<=50K" +42,"Self-emp-not-inc",64632,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Self-emp-not-inc",96245,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Private",361494,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +69,"Local-gov",122850,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States","<=50K" +29,"Private",173652,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",164663,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",98678,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +40,"Private",245529,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",55294,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",140583,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",79797,"HS-grad",9,"Married-spouse-absent","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Japan",">50K" +72,"?",113044,"HS-grad",9,"Widowed","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +20,"Private",283499,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,30,"United-States","<=50K" +41,"Local-gov",51111,"Bachelors",13,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",232475,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +48,"Private",176140,"11th",7,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +27,"Private",301654,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"?",192569,"HS-grad",9,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",229803,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",337639,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",130849,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +32,"Private",296282,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",266645,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +23,"State-gov",110128,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",90196,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +40,"State-gov",40024,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +35,"Private",144322,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +74,"Self-emp-inc",162340,"Some-college",10,"Widowed","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +28,"Private",169069,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",113601,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +44,"Private",111275,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,56,"United-States","<=50K" +46,"Local-gov",102076,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,25,"United-States","<=50K" +20,"?",182117,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",190122,"Some-college",10,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-inc",193188,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Local-gov",267588,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,70,"United-States","<=50K" +48,"Self-emp-inc",200471,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +22,"?",175586,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +24,"Local-gov",322658,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"State-gov",263982,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +18,"Private",266287,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +39,"Private",278187,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",221745,"Some-college",10,"Divorced","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"Private",140764,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +28,"Private",206351,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"State-gov",124971,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?",">50K" +18,"Private",179203,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +24,"Federal-gov",44075,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +45,"Private",178319,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,56,"United-States",">50K" +24,"Private",219754,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",168165,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +52,"Self-emp-inc",210736,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +19,"Private",130431,"5th-6th",3,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,36,"Mexico","<=50K" +35,"?",169809,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +54,"Private",197481,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +21,"Private",155066,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",31290,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +42,"Private",54102,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",181546,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +44,"State-gov",351228,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",131976,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,55,"United-States","<=50K" +26,"Private",200639,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Federal-gov",267546,"Assoc-acdm",12,"Separated","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +41,"Private",179875,"11th",7,"Divorced","Other-service","Unmarried","Other","Female",0,0,40,"United-States","<=50K" +25,"?",237865,"Some-college",10,"Never-married","?","Own-child","Black","Male",0,0,40,"?","<=50K" +43,"Private",300528,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Federal-gov",326048,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,44,"United-States",">50K" +60,"Private",191188,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",32172,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +37,"Federal-gov",334314,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",83704,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +44,"Private",160574,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States",">50K" +27,"Private",203776,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +47,"Local-gov",328610,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",174373,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +41,"Private",247752,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"?",199244,"10th",6,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",139992,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",95680,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +55,"Self-emp-inc",189933,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +38,"Private",498785,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"State-gov",177526,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +64,"Self-emp-not-inc",150121,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,25,"United-States",">50K" +56,"Federal-gov",130454,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",119079,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,49,"United-States",">50K" +33,"Private",94235,"Prof-school",15,"Never-married","Prof-specialty","Own-child","White","Male",0,0,42,"United-States",">50K" +21,"Private",305874,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Local-gov",62020,"HS-grad",9,"Widowed","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +58,"Private",235624,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Germany",">50K" +43,"Local-gov",247514,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +21,"Private",275726,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +45,"Private",72896,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Local-gov",110510,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +41,"Private",173938,"Prof-school",15,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"?",">50K" +27,"Private",200641,"10th",6,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"Mexico","<=50K" +53,"Private",211654,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"?",">50K" +38,"Private",242720,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +31,"Private",111567,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States",">50K" +41,"Private",179533,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States","<=50K" +22,"State-gov",334693,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",198096,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +41,"State-gov",355756,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",19395,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Wife","White","Female",0,0,35,"United-States","<=50K" +41,"Local-gov",242586,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",160647,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +20,"Private",227943,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,45,"United-States","<=50K" +58,"Self-emp-not-inc",197665,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,45,"United-States","<=50K" +35,"Self-emp-not-inc",216129,"12th",8,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"Trinadad&Tobago","<=50K" +30,"Local-gov",326104,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",57211,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",100219,"Assoc-acdm",12,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,45,"United-States","<=50K" +40,"Private",291192,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +54,"State-gov",93415,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States",">50K" +35,"Private",191502,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +35,"Private",261382,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",170230,"Bachelors",13,"Married-spouse-absent","Other-service","Not-in-family","White","Female",0,0,40,"?","<=50K" +59,"Private",374924,"HS-grad",9,"Separated","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-inc",320984,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"Private",338320,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +51,"Private",135190,"7th-8th",4,"Separated","Machine-op-inspct","Not-in-family","Black","Female",0,0,30,"United-States","<=50K" +33,"Private",637222,"12th",8,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",430084,"HS-grad",9,"Divorced","Other-service","Own-child","Black","Male",0,0,35,"United-States","<=50K" +30,"Private",125279,"HS-grad",9,"Married-spouse-absent","Sales","Unmarried","White","Male",0,0,40,"United-States","<=50K" +20,"Private",221955,"5th-6th",3,"Married-spouse-absent","Farming-fishing","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +51,"Self-emp-inc",180195,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"Private",208778,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States",">50K" +62,"Private",81534,"Some-college",10,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +37,"Private",325538,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Male",0,0,60,"?","<=50K" +28,"Private",142264,"9th",5,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,50,"Dominican-Republic","<=50K" +23,"Private",128604,"HS-grad",9,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,48,"South","<=50K" +39,"Private",277886,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,30,"United-States","<=50K" +50,"Self-emp-inc",100029,"Bachelors",13,"Widowed","Sales","Unmarried","White","Male",0,0,65,"United-States",">50K" +31,"Private",169269,"7th-8th",4,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +23,"?",123983,"Bachelors",13,"Never-married","?","Own-child","Other","Male",0,0,40,"United-States","<=50K" +47,"Private",297884,"10th",6,"Widowed","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"Private",99131,"HS-grad",9,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,18,"United-States","<=50K" +32,"Private",44392,"Assoc-acdm",12,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +82,"?",29441,"7th-8th",4,"Widowed","?","Not-in-family","White","Male",0,0,5,"United-States","<=50K" +74,"Federal-gov",181508,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Male",0,0,17,"United-States","<=50K" +22,"Private",190625,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,35,"United-States","<=50K" +32,"Private",194740,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"Greece","<=50K" +34,"Private",27380,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States",">50K" +59,"Private",160631,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +36,"Private",224531,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +59,"Private",283005,"11th",7,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Self-emp-inc",101926,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,70,"United-States",">50K" +25,"Self-emp-not-inc",113436,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,35,"United-States","<=50K" +44,"Private",248973,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","Black","Male",0,0,65,"United-States","<=50K" +58,"Local-gov",310085,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"?",53042,"HS-grad",9,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +45,"Private",204205,"7th-8th",4,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +47,"Private",169324,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,35,"United-States",">50K" +52,"?",134447,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States","<=50K" +56,"Self-emp-not-inc",236731,"1st-4th",2,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,25,"?","<=50K" +52,"Private",141301,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",235124,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +36,"Self-emp-not-inc",367020,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +41,"Private",149102,"HS-grad",9,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"Poland","<=50K" +30,"Private",423770,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"Mexico","<=50K" +44,"Private",211759,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Other","Male",0,0,40,"Puerto-Rico","<=50K" +17,"?",110998,"Some-college",10,"Never-married","?","Own-child","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +34,"Private",56883,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",223062,"Some-college",10,"Separated","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",406662,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",206600,"9th",5,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,48,"Mexico","<=50K" +42,"Local-gov",147510,"Bachelors",13,"Separated","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +26,"Private",187577,"Assoc-voc",11,"Never-married","Sales","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +46,"Self-emp-inc",278322,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +49,"State-gov",203039,"11th",7,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",145651,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,20,"United-States","<=50K" +46,"Local-gov",144531,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +30,"Private",91145,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,55,"United-States","<=50K" +49,"Self-emp-not-inc",211762,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +47,"?",111563,"Assoc-voc",11,"Divorced","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",180985,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"?",">50K" +19,"Private",417657,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,50,"United-States","<=50K" +26,"Private",108658,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",190023,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",222130,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +36,"Self-emp-inc",164866,"Assoc-acdm",12,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +31,"Private",170983,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +30,"Private",186269,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",286026,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",403433,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,50,"United-States",">50K" +21,"?",224209,"HS-grad",9,"Married-civ-spouse","?","Wife","Black","Female",0,0,30,"United-States","<=50K" +73,"Private",123160,"10th",6,"Widowed","Other-service","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +38,"Federal-gov",99527,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",123178,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +33,"Private",231043,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +58,"Private",241056,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,46,"United-States","<=50K" +34,"Local-gov",220066,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +35,"Private",180342,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Federal-gov",31840,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",183168,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",386036,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +31,"Local-gov",446358,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"Mexico",">50K" +45,"Private",28035,"Some-college",10,"Never-married","Farming-fishing","Other-relative","White","Male",0,0,50,"United-States","<=50K" +40,"Private",282155,"HS-grad",9,"Separated","Other-service","Other-relative","White","Female",0,0,25,"United-States","<=50K" +27,"Private",192384,"Prof-school",15,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",383637,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +29,"Private",457402,"5th-6th",3,"Never-married","Other-service","Not-in-family","White","Male",0,0,25,"Mexico","<=50K" +34,"Self-emp-inc",80249,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,72,"United-States","<=50K" +32,"State-gov",159537,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",240859,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Cuba","<=50K" +33,"Private",83446,"11th",7,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States",">50K" +74,"?",29866,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,2,"United-States","<=50K" +62,"Private",185503,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +39,"Self-emp-not-inc",68781,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",220589,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",51136,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +24,"Private",54560,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +76,"?",28221,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Canada",">50K" +25,"Private",201413,"Some-college",10,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",40425,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +31,"Private",189461,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,41,"United-States","<=50K" +53,"Private",200576,"11th",7,"Divorced","Craft-repair","Other-relative","White","Female",0,0,40,"United-States","<=50K" +61,"Private",92691,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,3,"United-States","<=50K" +47,"Private",664821,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +37,"Private",175130,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +50,"Self-emp-not-inc",391016,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +27,"Private",249315,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +58,"Private",111169,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",334946,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",352248,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",173804,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +56,"Private",155449,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Private",73689,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,55,"United-States","<=50K" +23,"Private",227594,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,38,"United-States","<=50K" +47,"Private",161676,"11th",7,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +68,"Private",75913,"12th",8,"Widowed","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +47,"Local-gov",242552,"Some-college",10,"Never-married","Protective-serv","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",159732,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +46,"Private",180695,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"Private",189922,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",409189,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +43,"Private",111252,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,42,"United-States","<=50K" +59,"Private",294395,"Masters",14,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",172718,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +63,"Private",111963,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,16,"United-States","<=50K" +45,"Private",247869,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +59,"Private",114032,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"?",356838,"12th",8,"Never-married","?","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +26,"Private",179633,"HS-grad",9,"Never-married","Tech-support","Other-relative","White","Male",0,0,40,"United-States","<=50K" +34,"Private",19847,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",231689,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",209942,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +53,"Private",197492,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",262439,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States",">50K" +46,"Private",283037,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +79,"?",144533,"HS-grad",9,"Widowed","?","Not-in-family","Black","Female",0,0,30,"United-States","<=50K" +31,"Private",83446,"HS-grad",9,"Widowed","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",215443,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Local-gov",268252,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,62,"United-States","<=50K" +40,"Private",181015,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,47,"United-States","<=50K" +20,"Private",195770,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,26,"United-States","<=50K" +45,"Private",125194,"11th",7,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +27,"Private",58654,"Assoc-voc",11,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",252327,"5th-6th",3,"Married-spouse-absent","Craft-repair","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +30,"Private",116508,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Germany","<=50K" +36,"Private",166988,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +25,"Private",374163,"HS-grad",9,"Married-spouse-absent","Farming-fishing","Not-in-family","Other","Male",0,0,40,"Mexico","<=50K" +31,"Private",196788,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +26,"Private",245628,"11th",7,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,20,"United-States","<=50K" +25,"Private",159732,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",129856,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Private",314322,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",102976,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +57,"Self-emp-inc",42959,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +21,"Private",256356,"11th",7,"Never-married","Priv-house-serv","Other-relative","White","Female",0,0,40,"Mexico","<=50K" +29,"Private",136277,"10th",6,"Never-married","Other-service","Own-child","Black","Female",0,0,32,"United-States","<=50K" +36,"Private",284616,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",185554,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +51,"Private",138847,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",33487,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",149653,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +38,"Private",348739,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +20,"?",235442,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,35,"United-States","<=50K" +21,"Private",34506,"HS-grad",9,"Separated","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +40,"Private",346964,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +46,"Private",192208,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +21,"Private",305874,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,54,"United-States","<=50K" +35,"Self-emp-not-inc",462890,"10th",6,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,50,"United-States","<=50K" +39,"Private",89508,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",200153,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +30,"Private",179446,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",208965,"9th",5,"Never-married","Machine-op-inspct","Unmarried","Other","Male",0,0,40,"Mexico","<=50K" +32,"Private",40142,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Self-emp-not-inc",57452,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",327573,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",265266,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"?",163998,"HS-grad",9,"Married-spouse-absent","?","Not-in-family","White","Male",0,0,20,"United-States",">50K" +46,"Self-emp-not-inc",28281,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",368852,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +44,"Private",353396,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +33,"Private",161745,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +18,"Private",97963,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +61,"Self-emp-inc",156542,"Prof-school",15,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +50,"State-gov",198103,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Federal-gov",55377,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Male",0,0,40,"United-States","<=50K" +34,"Private",173730,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +53,"Private",374588,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,60,"United-States","<=50K" +39,"Self-emp-not-inc",174330,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",78141,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +66,"?",190324,"HS-grad",9,"Married-civ-spouse","?","Husband","Black","Male",0,0,18,"United-States","<=50K" +26,"Private",31350,"11th",7,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +41,"Private",243607,"5th-6th",3,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Mexico","<=50K" +47,"Local-gov",134671,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",197023,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +52,"Private",117674,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",169815,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Private",598606,"9th",5,"Separated","Handlers-cleaners","Unmarried","Black","Female",0,0,50,"United-States","<=50K" +42,"Federal-gov",122861,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",166235,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",0,0,30,"United-States","<=50K" +52,"Self-emp-not-inc",194791,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",231323,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Local-gov",305597,"HS-grad",9,"Separated","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +19,"Private",25429,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +39,"Private",346478,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +22,"Private",341368,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"State-gov",295612,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",168936,"Assoc-voc",11,"Divorced","Other-service","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +37,"Private",336598,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,36,"Mexico","<=50K" +23,"Private",308205,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +39,"Local-gov",357173,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,59,"United-States","<=50K" +54,"Private",457237,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-inc",284799,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +20,"Private",179423,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",363405,"Bachelors",13,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,50,"United-States",">50K" +17,"Private",139183,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +36,"Private",203482,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",112554,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +53,"Private",99476,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +50,"Private",93690,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",220585,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Self-emp-not-inc",194638,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,32,"United-States","<=50K" +53,"Private",154785,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +40,"?",162108,"Bachelors",13,"Divorced","?","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +23,"Self-emp-inc",214542,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +20,"Private",161922,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,43,"United-States","<=50K" +46,"Private",207940,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +28,"Private",259351,"10th",6,"Never-married","Other-service","Other-relative","Amer-Indian-Eskimo","Male",0,0,40,"Mexico","<=50K" +59,"Private",208395,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +41,"Private",116391,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",239781,"Preschool",1,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +56,"Private",174351,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Italy","<=50K" +31,"Local-gov",188798,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +41,"Private",50122,"Assoc-voc",11,"Divorced","Sales","Own-child","White","Male",0,0,50,"United-States","<=50K" +25,"State-gov",152035,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +18,"?",139003,"HS-grad",9,"Never-married","?","Other-relative","Other","Female",0,0,12,"United-States","<=50K" +49,"Local-gov",249289,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +39,"Private",257726,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"?",113175,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +21,"Private",151158,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,25,"United-States","<=50K" +35,"Private",465326,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"?",356772,"HS-grad",9,"Never-married","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",364782,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Private",198385,"7th-8th",4,"Widowed","Other-service","Unmarried","White","Female",0,0,20,"?","<=50K" +31,"Private",329301,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +17,"Self-emp-inc",254859,"11th",7,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +25,"Local-gov",222800,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",96452,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +50,"Private",170050,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Local-gov",116580,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,20,"United-States",">50K" +50,"Private",400004,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +63,"Private",183608,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",194055,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +23,"Private",210443,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +18,"Private",43272,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +43,"Local-gov",108945,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,48,"United-States","<=50K" +34,"Private",114691,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +18,"Private",304169,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +35,"Private",340428,"Bachelors",13,"Never-married","Sales","Unmarried","White","Female",0,0,40,"United-States",">50K" +46,"State-gov",106705,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +31,"Private",235389,"7th-8th",4,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,30,"Portugal","<=50K" +27,"Private",39665,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,37,"United-States","<=50K" +41,"Private",113823,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"England","<=50K" +42,"Private",217826,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"?","<=50K" +55,"Private",349304,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +34,"?",197688,"HS-grad",9,"Never-married","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +44,"Private",54507,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",163396,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +33,"Private",323619,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",75755,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",148903,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,16,"United-States",">50K" +25,"Private",40915,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +21,"Private",182606,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"?","<=50K" +18,"Private",131033,"11th",7,"Never-married","Other-service","Other-relative","Black","Male",0,0,15,"United-States","<=50K" +35,"Self-emp-not-inc",168475,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +20,"Private",121568,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +46,"Private",357338,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",283268,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,36,"United-States","<=50K" +31,"Private",120461,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",65278,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Self-emp-not-inc",208503,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Local-gov",112835,"Masters",14,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",265038,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +18,"Private",89478,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +55,"Private",276229,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +52,"Private",366232,"9th",5,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"Cuba","<=50K" +26,"Private",152035,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"Private",205339,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States",">50K" +39,"Private",75995,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +62,"Self-emp-not-inc",192236,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +19,"?",188618,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,25,"United-States","<=50K" +47,"Private",229737,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +51,"Local-gov",199688,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Private",52953,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",221043,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +59,"Federal-gov",115389,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,36,"United-States","<=50K" +45,"Self-emp-not-inc",204205,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States","<=50K" +21,"Private",197387,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +31,"Private",42485,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,55,"United-States","<=50K" +29,"Private",367706,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,40,"United-States","<=50K" +24,"Private",102493,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",263746,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,24,"United-States","<=50K" +47,"Private",115358,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +46,"Private",189680,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +32,"?",282622,"HS-grad",9,"Divorced","?","Unmarried","White","Female",0,0,28,"United-States","<=50K" +34,"Private",127651,"10th",6,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,44,"?","<=50K" +63,"Private",230823,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Cuba","<=50K" +21,"Private",300812,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +18,"Private",174732,"HS-grad",9,"Never-married","Other-service","Other-relative","Black","Male",0,0,36,"United-States","<=50K" +49,"State-gov",183710,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +81,"Self-emp-not-inc",137018,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +36,"Self-emp-inc",213008,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",357848,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",165799,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +39,"Self-emp-not-inc",188571,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +46,"Private",97883,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +39,"Local-gov",57424,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +29,"Private",151476,"Some-college",10,"Separated","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",129583,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Female",0,0,16,"United-States","<=50K" +57,"Private",180920,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States","<=50K" +38,"Self-emp-not-inc",182416,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,42,"United-States","<=50K" +25,"Private",251915,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Local-gov",187127,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",69045,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Male",0,0,40,"Jamaica","<=50K" +39,"Private",74163,"12th",8,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",60847,"Assoc-voc",11,"Never-married","Sales","Unmarried","White","Female",0,0,60,"United-States","<=50K" +17,"?",213055,"11th",7,"Never-married","?","Not-in-family","Other","Female",0,0,20,"United-States","<=50K" +41,"Private",82393,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Male",0,0,50,"United-States","<=50K" +24,"Local-gov",134181,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,50,"United-States","<=50K" +30,"Self-emp-inc",117570,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +56,"Private",56331,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +51,"Private",35576,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +57,"Self-emp-not-inc",149168,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +34,"Private",157165,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",278130,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Private",257200,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",283122,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",580248,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",230054,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +58,"Private",519006,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States","<=50K" +19,"?",365871,"7th-8th",4,"Never-married","?","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +17,"Private",115551,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +37,"Self-emp-inc",382802,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,99,"United-States",">50K" +21,"?",180303,"Bachelors",13,"Never-married","?","Not-in-family","Asian-Pac-Islander","Male",0,0,25,"?","<=50K" +63,"Private",106023,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",332379,"Some-college",10,"Married-spouse-absent","Transport-moving","Unmarried","White","Male",0,0,50,"United-States","<=50K" +29,"Private",95465,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",36440,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,65,"United-States",">50K" +25,"Self-emp-not-inc",209384,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,32,"United-States","<=50K" +28,"Private",50814,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +54,"Private",143865,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,35,"United-States","<=50K" +74,"?",104661,"Some-college",10,"Widowed","?","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +31,"Local-gov",50442,"Some-college",10,"Never-married","Exec-managerial","Own-child","Amer-Indian-Eskimo","Female",0,0,32,"United-States","<=50K" +23,"Private",236601,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +19,"Private",100999,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,30,"United-States","<=50K" +39,"?",362685,"Preschool",1,"Widowed","?","Not-in-family","White","Female",0,0,20,"El-Salvador","<=50K" +27,"Self-emp-inc",153546,"Assoc-voc",11,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,36,"United-States",">50K" +19,"Private",182355,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,20,"United-States","<=50K" +23,"?",191444,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Local-gov",44216,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Amer-Indian-Eskimo","Female",0,0,35,"United-States","<=50K" +40,"Private",97688,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,48,"United-States",">50K" +53,"Private",209022,"11th",7,"Divorced","Other-service","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +32,"Private",96016,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +61,"Private",159046,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",138634,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +73,"Private",247355,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,16,"Canada","<=50K" +41,"Self-emp-not-inc",227065,"Some-college",10,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",244771,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,20,"Jamaica","<=50K" +23,"Private",215616,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"Canada","<=50K" +65,"Private",386672,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,15,"United-States","<=50K" +45,"Self-emp-inc",177543,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,50,"United-States","<=50K" +24,"Local-gov",117109,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,27,"United-States","<=50K" +23,"Private",373550,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",19847,"Some-college",10,"Divorced","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",189590,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",58343,"HS-grad",9,"Divorced","Farming-fishing","Unmarried","White","Male",0,0,56,"United-States","<=50K" +17,"Private",354201,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",119422,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",363405,"HS-grad",9,"Separated","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +63,"Private",181863,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,27,"United-States","<=50K" +27,"Private",194472,"HS-grad",9,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +71,"Self-emp-not-inc",130731,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +35,"Private",236910,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +44,"Private",378251,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,38,"United-States","<=50K" +36,"Private",120760,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +22,"Private",203182,"Bachelors",13,"Never-married","Exec-managerial","Other-relative","White","Female",0,0,20,"United-States","<=50K" +30,"Local-gov",352542,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +60,"?",191024,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",197728,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +76,"Private",316185,"7th-8th",4,"Widowed","Protective-serv","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +41,"Private",89226,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",292353,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",0,0,40,"United-States","<=50K" +45,"Private",304570,"12th",8,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +32,"Private",180296,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",361487,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +63,"Self-emp-not-inc",231777,"Bachelors",13,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",189832,"Assoc-acdm",12,"Never-married","Transport-moving","Unmarried","White","Female",0,0,40,"United-States","<=50K" +61,"Private",232308,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"State-gov",33308,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",333677,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +39,"Private",343403,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,36,"United-States","<=50K" +53,"Private",166386,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Wife","Asian-Pac-Islander","Female",0,0,40,"China","<=50K" +26,"Federal-gov",48099,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",143062,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,32,"United-States","<=50K" +18,"Private",104704,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,40,"United-States","<=50K" +31,"Private",286675,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +44,"Private",59474,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",245842,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,44,"Mexico","<=50K" +21,"Private",342575,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,30,"United-States","<=50K" +30,"Private",206051,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Private",234213,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +57,"Private",145189,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",233490,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +32,"Private",344129,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +62,"Self-emp-not-inc",171315,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +31,"Self-emp-not-inc",181485,"Bachelors",13,"Never-married","Sales","Not-in-family","Black","Male",0,0,40,"United-States",">50K" +51,"Private",255412,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"France",">50K" +45,"Private",199590,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,38,"Mexico","<=50K" +47,"Private",84726,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"?",226883,"HS-grad",9,"Divorced","?","Own-child","White","Male",0,0,75,"United-States","<=50K" +75,"Self-emp-not-inc",184335,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"United-States","<=50K" +43,"Private",102025,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Other","Male",0,0,50,"United-States","<=50K" +30,"Private",55291,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",150025,"5th-6th",3,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Guatemala","<=50K" +44,"Private",100584,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +53,"Local-gov",181755,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States",">50K" +40,"Private",150528,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",107277,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +33,"Private",247205,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"England","<=50K" +20,"Private",291979,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",270985,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,50,"United-States","<=50K" +48,"Private",62605,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +46,"Self-emp-not-inc",176863,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",53197,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",267776,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Female",0,0,30,"United-States","<=50K" +24,"Private",308205,"7th-8th",4,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +30,"Private",306383,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +70,"Private",35494,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"United-States","<=50K" +26,"Private",291968,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,44,"United-States","<=50K" +46,"Private",271828,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +70,"Private",121993,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,5,"United-States","<=50K" +37,"Local-gov",31023,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",36425,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,35,"United-States","<=50K" +23,"Private",407684,"9th",5,"Never-married","Machine-op-inspct","Other-relative","White","Female",0,0,40,"Mexico","<=50K" +44,"Self-emp-not-inc",158555,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +53,"Private",123429,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +23,"Private",40060,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",290286,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +21,"?",249271,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",106169,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +43,"Private",76487,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",437994,"Some-college",10,"Never-married","Other-service","Other-relative","Black","Male",0,0,20,"United-States","<=50K" +36,"Private",160120,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +42,"Self-emp-not-inc",37618,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +27,"Private",114158,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +41,"Private",115562,"HS-grad",9,"Divorced","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",353994,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Other-relative","Asian-Pac-Islander","Female",0,0,40,"China",">50K" +21,"Private",344891,"Some-college",10,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Male",0,0,20,"United-States","<=50K" +44,"Private",286750,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,50,"United-States",">50K" +29,"Private",194197,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Self-emp-not-inc",206599,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,22,"United-States","<=50K" +21,"Local-gov",596776,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"Guatemala","<=50K" +46,"Private",56841,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",112561,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +43,"Private",147110,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,48,"United-States",">50K" +54,"Self-emp-inc",175339,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +18,"?",298133,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Private",217083,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +30,"Private",97757,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,36,"United-States",">50K" +30,"Private",151868,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Local-gov",25864,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","Amer-Indian-Eskimo","Female",0,0,35,"United-States","<=50K" +26,"Private",109419,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +37,"Federal-gov",203070,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States","<=50K" +64,"State-gov",264544,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,5,"United-States",">50K" +18,"Private",148644,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,28,"United-States","<=50K" +30,"Private",125762,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,30,"United-States","<=50K" +18,"Private",193741,"11th",7,"Never-married","Other-service","Other-relative","Black","Male",0,0,30,"United-States","<=50K" +27,"Private",588905,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",115613,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"State-gov",222374,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,43,"United-States",">50K" +37,"Private",185359,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",173647,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",31166,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","Other","Female",0,0,30,"Germany","<=50K" +22,"?",517995,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"Mexico","<=50K" +25,"Self-emp-not-inc",189027,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +38,"Private",296125,"HS-grad",9,"Separated","Priv-house-serv","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +32,"?",640383,"Bachelors",13,"Divorced","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",334291,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +56,"Private",318450,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,80,"United-States",">50K" +29,"Private",174163,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",119721,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",142719,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",162593,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +46,"Self-emp-not-inc",236852,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +39,"Private",168894,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,20,"United-States","<=50K" +42,"Self-emp-not-inc",344920,"Some-college",10,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,0,50,"United-States","<=50K" +68,"?",196782,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States","<=50K" +57,"Private",170244,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",369549,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Female",0,0,30,"United-States","<=50K" +24,"Private",23438,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,30,"United-States",">50K" +19,"Private",202673,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,50,"United-States","<=50K" +55,"Private",171780,"Assoc-acdm",12,"Divorced","Sales","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +37,"Local-gov",264503,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Local-gov",244341,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",209109,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",187392,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"State-gov",119578,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,20,"United-States","<=50K" +51,"Private",195105,"HS-grad",9,"Divorced","Priv-house-serv","Own-child","White","Female",0,0,40,"United-States","<=50K" +52,"Private",101752,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,56,"United-States","<=50K" +74,"?",95825,"Some-college",10,"Widowed","?","Not-in-family","White","Female",0,0,3,"United-States","<=50K" +20,"?",29810,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Federal-gov",77332,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +63,"Private",113324,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Private",96299,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Male",0,0,45,"United-States",">50K" +51,"Private",237729,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",200973,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +66,"Self-emp-not-inc",212456,"HS-grad",9,"Widowed","Craft-repair","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +33,"Self-emp-not-inc",131568,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,66,"United-States","<=50K" +49,"Private",185859,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States","<=50K" +20,"Private",231981,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +26,"Private",78172,"Some-college",10,"Married-AF-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",164135,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Private",171216,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +47,"Private",140664,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +23,"Private",249277,"HS-grad",9,"Never-married","Exec-managerial","Own-child","Black","Male",0,0,75,"United-States","<=50K" +53,"Federal-gov",117847,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",52372,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +53,"Private",137428,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +65,"Private",169047,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +68,"Private",339168,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States","<=50K" +30,"Private",504725,"10th",6,"Never-married","Sales","Other-relative","White","Male",0,0,18,"Guatemala","<=50K" +28,"Private",132870,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +54,"Local-gov",135840,"10th",6,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Private",35644,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,10,"United-States","<=50K" +22,"Private",198148,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,50,"United-States","<=50K" +25,"Private",220098,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +19,"Private",262515,"11th",7,"Never-married","Other-service","Other-relative","White","Male",0,0,20,"United-States","<=50K" +19,"?",423863,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +32,"Federal-gov",111567,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",194096,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Local-gov",420917,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"Private",197871,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States",">50K" +46,"Local-gov",253116,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",206535,"Some-college",10,"Divorced","Tech-support","Unmarried","White","Female",0,0,50,"United-States","<=50K" +26,"State-gov",70447,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +46,"Private",201217,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",209970,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Local-gov",175262,"Masters",14,"Married-civ-spouse","Prof-specialty","Other-relative","White","Male",0,0,35,"United-States","<=50K" +51,"Self-emp-inc",304955,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +40,"Private",181265,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States","<=50K" +24,"Private",200973,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Self-emp-not-inc",37440,"Bachelors",13,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,50,"United-States","<=50K" +31,"Private",395170,"Assoc-voc",11,"Married-civ-spouse","Other-service","Wife","Amer-Indian-Eskimo","Female",0,0,24,"Mexico","<=50K" +54,"?",32385,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +34,"Private",353213,"Assoc-acdm",12,"Separated","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +19,"Private",38619,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,66,"United-States","<=50K" +21,"Private",177711,"HS-grad",9,"Never-married","Transport-moving","Own-child","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",190761,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +23,"Private",27776,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,24,"United-States","<=50K" +37,"Federal-gov",470663,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",71738,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,46,"United-States",">50K" +57,"Private",74156,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States","<=50K" +24,"Private",123983,"11th",7,"Married-civ-spouse","Transport-moving","Husband","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +43,"Private",193494,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"?",169886,"Bachelors",13,"Never-married","?","Not-in-family","White","Female",0,0,20,"?","<=50K" +40,"Private",130571,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Private",83444,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +62,"Local-gov",151369,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",56630,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",117095,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +55,"Federal-gov",189985,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +20,"?",34862,"Some-college",10,"Never-married","?","Own-child","Amer-Indian-Eskimo","Male",0,0,72,"United-States","<=50K" +37,"Self-emp-inc",126675,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"State-gov",199806,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",57596,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",103459,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +28,"Private",282398,"Some-college",10,"Separated","Tech-support","Unmarried","White","Male",0,0,40,"United-States",">50K" +38,"Private",298841,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +22,"?",306031,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",306467,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +20,"Private",189888,"12th",8,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +60,"Private",83861,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",117393,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",129934,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +51,"Private",179010,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +31,"Private",375680,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","Black","Female",0,0,40,"?","<=50K" +48,"Private",316101,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +51,"Local-gov",175750,"HS-grad",9,"Divorced","Transport-moving","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +50,"State-gov",229272,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +46,"Private",142828,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +68,"Private",76371,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States",">50K" +23,"Self-emp-not-inc",216129,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +49,"Private",107425,"Masters",14,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +24,"Private",611029,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Local-gov",363032,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States","<=50K" +34,"Private",137900,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +22,"Private",322674,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",23778,"7th-8th",4,"Separated","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"Private",147845,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,31,"United-States","<=50K" +36,"Private",175759,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-inc",166459,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",128212,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Wife","Asian-Pac-Islander","Female",0,0,40,"Vietnam",">50K" +54,"Federal-gov",127455,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,48,"United-States",">50K" +63,"Private",134699,"HS-grad",9,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +51,"Private",254230,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +63,"Self-emp-not-inc",159715,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Local-gov",116286,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +27,"Private",146719,"HS-grad",9,"Divorced","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +35,"Private",361888,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +31,"?",26553,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,25,"United-States",">50K" +46,"Self-emp-not-inc",32825,"HS-grad",9,"Separated","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +53,"Private",225768,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +26,"Federal-gov",393728,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Male",0,0,24,"United-States","<=50K" +43,"Private",160369,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"Federal-gov",33863,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +62,"?",182687,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,45,"United-States",">50K" +57,"State-gov",141459,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"?",174233,"Some-college",10,"Never-married","?","Own-child","Black","Male",0,0,24,"United-States","<=50K" +29,"Local-gov",95393,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +20,"Private",221095,"HS-grad",9,"Never-married","Craft-repair","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +18,"?",437851,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"?",131230,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",495888,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"El-Salvador","<=50K" +69,"Private",185691,"11th",7,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,20,"United-States","<=50K" +53,"Local-gov",549341,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,35,"United-States","<=50K" +28,"Private",247445,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",199566,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-inc",139057,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,84,"Taiwan",">50K" +48,"Private",185039,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +61,"Private",166124,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",109275,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",408328,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",186338,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +27,"?",130856,"Bachelors",13,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",251579,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,14,"United-States","<=50K" +47,"Private",76612,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Private",22546,"Bachelors",13,"Never-married","Transport-moving","Own-child","White","Male",0,0,60,"United-States","<=50K" +72,"Private",53684,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",183627,"11th",7,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",73203,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +57,"Private",108426,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,48,"England","<=50K" +50,"Private",116287,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,60,"Columbia","<=50K" +45,"Self-emp-inc",145697,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +52,"Private",326156,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +53,"Private",201127,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +36,"Private",250791,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,48,"United-States","<=50K" +46,"Private",328216,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",400443,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +75,"Private",95985,"5th-6th",3,"Widowed","Other-service","Unmarried","Black","Male",0,0,10,"United-States","<=50K" +32,"Local-gov",127651,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",250679,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",103950,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Private",200199,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +46,"State-gov",295791,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +39,"Private",191841,"Assoc-acdm",12,"Separated","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +38,"Private",82622,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +36,"Private",160728,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"United-States","<=50K" +63,"Local-gov",109849,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,21,"United-States","<=50K" +28,"Private",339897,"1st-4th",2,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,43,"Mexico","<=50K" +28,"?",37215,"Bachelors",13,"Never-married","?","Own-child","White","Male",0,0,45,"United-States","<=50K" +49,"Private",371299,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +43,"Private",421837,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +38,"Private",29702,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +39,"Private",117381,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Male",0,0,62,"England","<=50K" +42,"?",240027,"HS-grad",9,"Divorced","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +40,"Private",338740,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"?",28359,"HS-grad",9,"Separated","?","Unmarried","White","Female",0,0,10,"United-States","<=50K" +29,"?",315026,"HS-grad",9,"Divorced","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",173005,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Private",286750,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +40,"Private",163985,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,24,"United-States","<=50K" +30,"Private",219318,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Female",0,0,35,"Puerto-Rico","<=50K" +52,"Self-emp-not-inc",103794,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +42,"Private",310632,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +39,"Private",153976,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States",">50K" +43,"Private",174575,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,45,"United-States","<=50K" +30,"Private",207253,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"England","<=50K" +83,"?",251951,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +39,"Private",746786,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +41,"Private",308296,"HS-grad",9,"Married-civ-spouse","Transport-moving","Wife","White","Female",0,0,20,"United-States","<=50K" +25,"Private",109009,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"?",117751,"Assoc-acdm",12,"Divorced","?","Not-in-family","White","Male",0,0,8,"United-States","<=50K" +44,"State-gov",296326,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",120277,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"Ireland","<=50K" +21,"Private",193219,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,35,"Jamaica","<=50K" +41,"Private",86399,"Some-college",10,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +24,"Private",215251,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +67,"Self-emp-not-inc",124470,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +24,"Private",228649,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,38,"United-States","<=50K" +50,"Self-emp-not-inc",386397,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +48,"Private",96798,"Masters",14,"Divorced","Sales","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +55,"?",106707,"Assoc-acdm",12,"Married-civ-spouse","?","Husband","Black","Male",0,0,20,"United-States",">50K" +50,"Private",139464,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,36,"Ireland","<=50K" +64,"State-gov",550848,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Private",68505,"9th",5,"Divorced","Other-service","Not-in-family","Black","Male",0,0,37,"United-States","<=50K" +20,"Private",122215,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,52,"United-States","<=50K" +30,"Private",159442,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",80638,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,30,"China","<=50K" +52,"Private",192390,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",191324,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,25,"United-States","<=50K" +77,"?",147284,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,14,"United-States","<=50K" +19,"State-gov",73009,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,15,"United-States","<=50K" +52,"Private",177858,"HS-grad",9,"Divorced","Craft-repair","Other-relative","White","Male",0,0,55,"United-States",">50K" +42,"Private",163003,"Bachelors",13,"Married-spouse-absent","Tech-support","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +35,"Private",95551,"HS-grad",9,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +27,"Private",125298,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States","<=50K" +54,"State-gov",198186,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,38,"United-States","<=50K" +37,"Private",182668,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States","<=50K" +28,"Private",124905,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +63,"Private",171635,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",376240,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,42,"United-States","<=50K" +28,"Private",157391,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"?",114357,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",178134,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +31,"Private",207201,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",124483,"Bachelors",13,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Male",0,0,50,"?",">50K" +64,"Private",102103,"HS-grad",9,"Divorced","Priv-house-serv","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +40,"Private",92036,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Local-gov",236426,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +22,"Private",400966,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",404573,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +35,"Private",227571,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +20,"Private",145917,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +35,"Local-gov",190226,"HS-grad",9,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",356555,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States","<=50K" +28,"Private",66473,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"?",172256,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +25,"Self-emp-inc",163039,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +37,"Private",89559,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"?",35507,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,45,"United-States","<=50K" +31,"Private",163303,"Assoc-voc",11,"Divorced","Sales","Own-child","White","Female",0,0,38,"United-States","<=50K" +41,"Private",192712,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +31,"Private",381153,"10th",6,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",222434,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",34706,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,47,"United-States","<=50K" +57,"Self-emp-not-inc",47857,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Private",195216,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +29,"Local-gov",329426,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",184105,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",211385,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","Black","Male",0,0,35,"Jamaica","<=50K" +21,"Private",61777,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +34,"Self-emp-not-inc",320194,"Prof-school",15,"Separated","Prof-specialty","Unmarried","White","Male",0,0,48,"United-States",">50K" +24,"Private",199444,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,15,"United-States","<=50K" +28,"Private",312588,"10th",6,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",168675,"HS-grad",9,"Separated","Transport-moving","Own-child","White","Male",0,0,50,"United-States","<=50K" +35,"Private",87556,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"State-gov",220421,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Federal-gov",404599,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +39,"Private",99065,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Wife","White","Female",0,0,40,"Poland",">50K" +57,"Local-gov",109973,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",246652,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",57423,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +23,"Private",291248,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +50,"Private",163708,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",240358,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +28,"Private",25955,"Assoc-voc",11,"Divorced","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +44,"Private",101593,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +29,"Self-emp-not-inc",227890,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +31,"Private",225053,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +27,"Private",228472,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +34,"Private",245378,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +27,"Private",35032,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",258849,"Assoc-voc",11,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +46,"Private",190115,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",63910,"Some-college",10,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +40,"Private",510072,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +28,"Private",210867,"11th",7,"Divorced","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",263024,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Private",306785,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +58,"Self-emp-inc",104333,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +66,"Private",340734,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",288585,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Asian-Pac-Islander","Female",0,0,20,"South","<=50K" +38,"Private",241765,"11th",7,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +25,"Private",111058,"Assoc-acdm",12,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",104662,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,22,"United-States","<=50K" +90,"Private",313986,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",52037,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"?",146589,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",254221,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",211785,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Female",0,0,20,"United-States","<=50K" +59,"Private",160362,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +19,"?",208874,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",169631,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +52,"Private",202956,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",80467,"HS-grad",9,"Divorced","Other-service","Own-child","White","Female",0,0,24,"United-States","<=50K" +28,"Private",407672,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",243425,"HS-grad",9,"Divorced","Other-service","Other-relative","White","Female",0,0,50,"Peru","<=50K" +50,"?",174964,"10th",6,"Married-civ-spouse","?","Husband","White","Male",0,0,99,"United-States","<=50K" +36,"Private",347491,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Private",146161,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +23,"Private",449432,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"?",175499,"11th",7,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +27,"Local-gov",134813,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Male",0,0,52,"United-States","<=50K" +31,"Local-gov",190401,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",260617,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,36,"United-States","<=50K" +31,"Private",45604,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,54,"United-States","<=50K" +59,"Private",67841,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",430471,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",194698,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",94235,"Bachelors",13,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +57,"Private",188330,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,78,"United-States","<=50K" +51,"Local-gov",146181,"9th",5,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",177125,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +30,"Self-emp-inc",68330,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +46,"Private",95636,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +40,"Private",238329,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +52,"Private",416129,"Preschool",1,"Married-civ-spouse","Other-service","Not-in-family","White","Male",0,0,40,"El-Salvador","<=50K" +23,"Private",285004,"Bachelors",13,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Male",0,0,50,"Taiwan","<=50K" +25,"Private",186294,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +43,"Private",188786,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +38,"State-gov",31352,"Some-college",10,"Divorced","Protective-serv","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States",">50K" +22,"Private",197613,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +65,"Private",361721,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,20,"United-States","<=50K" +50,"Private",144968,"HS-grad",9,"Never-married","Tech-support","Own-child","White","Male",0,0,15,"United-States","<=50K" +25,"Private",178037,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",306985,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Private",87928,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",242619,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",154165,"9th",5,"Divorced","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",511331,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +65,"Local-gov",221026,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,20,"United-States","<=50K" +56,"Self-emp-not-inc",222182,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,45,"United-States","<=50K" +23,"Private",202344,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"Private",190423,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +24,"Private",238917,"5th-6th",3,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"El-Salvador","<=50K" +40,"Self-emp-inc",37997,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +55,"Private",147098,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +38,"Private",278253,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,48,"United-States","<=50K" +23,"Private",195411,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +44,"Private",76196,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"Self-emp-not-inc",186014,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,12,"Germany","<=50K" +29,"Private",205903,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"State-gov",125405,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",219838,"12th",8,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"State-gov",19395,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +31,"Private",223327,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",114062,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",95654,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"Iran",">50K" +38,"Private",177305,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +66,"?",299616,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Self-emp-not-inc",117681,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",237651,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +33,"State-gov",150570,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"?",174714,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +33,"Private",144064,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +66,"?",107112,"7th-8th",4,"Never-married","?","Other-relative","Black","Male",0,0,30,"United-States","<=50K" +20,"Private",54152,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"?","<=50K" +28,"Private",152951,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",190487,"HS-grad",9,"Divorced","Priv-house-serv","Unmarried","White","Female",0,0,28,"Ecuador","<=50K" +25,"Private",306666,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,45,"United-States","<=50K" +31,"Self-emp-not-inc",226624,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +49,"Private",157569,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"State-gov",22966,"Some-college",10,"Married-spouse-absent","Tech-support","Unmarried","White","Male",0,0,20,"United-States","<=50K" +52,"Private",379682,"Assoc-voc",11,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,20,"United-States",">50K" +29,"Private",446559,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States","<=50K" +18,"Private",41794,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +31,"Local-gov",90409,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States","<=50K" +23,"Private",125491,"Some-college",10,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,35,"Vietnam","<=50K" +27,"?",129661,"Assoc-voc",11,"Married-civ-spouse","?","Wife","Amer-Indian-Eskimo","Female",0,0,40,"United-States",">50K" +54,"Self-emp-not-inc",104748,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States","<=50K" +50,"Local-gov",169182,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,49,"Dominican-Republic","<=50K" +24,"Private",122272,"Bachelors",13,"Never-married","Farming-fishing","Own-child","White","Female",0,0,40,"United-States","<=50K" +17,"?",114798,"11th",7,"Never-married","?","Own-child","White","Female",0,0,18,"United-States","<=50K" +49,"Self-emp-inc",289707,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +54,"Local-gov",137691,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Private",166789,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",348728,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +23,"Private",348092,"HS-grad",9,"Never-married","Transport-moving","Own-child","Black","Male",0,0,40,"Haiti","<=50K" +63,"Private",154526,"Some-college",10,"Widowed","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +67,"Private",288371,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Canada",">50K" +23,"Private",182342,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",244366,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +66,"Private",102423,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,30,"United-States","<=50K" +25,"Private",259688,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",98733,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,20,"United-States","<=50K" +67,"Self-emp-not-inc",141797,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",327202,"12th",8,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",76996,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",0,0,38,"United-States","<=50K" +34,"Private",260560,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",370990,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",129010,"12th",8,"Never-married","Craft-repair","Own-child","White","Male",0,0,10,"United-States","<=50K" +21,"Private",452640,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +76,"Self-emp-inc",120796,"9th",5,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Federal-gov",45334,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Asian-Pac-Islander","Male",0,0,70,"?","<=50K" +26,"Private",229523,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,56,"United-States","<=50K" +18,"Private",127388,"12th",8,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +18,"?",395567,"11th",7,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +59,"Private",193895,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",155343,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,72,"United-States","<=50K" +25,"Private",73895,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,10,"United-States","<=50K" +48,"Private",107682,"HS-grad",9,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +64,"Private",321166,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,5,"United-States","<=50K" +47,"Local-gov",154940,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States",">50K" +26,"Private",103700,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",63509,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States",">50K" +21,"Private",243842,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"?",187221,"7th-8th",4,"Never-married","?","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +30,"Private",58597,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,44,"United-States","<=50K" +41,"Self-emp-not-inc",190290,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",62165,"Some-college",10,"Never-married","Sales","Other-relative","Black","Male",0,0,30,"United-States","<=50K" +20,"?",307149,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +24,"Private",280134,"10th",6,"Never-married","Sales","Not-in-family","White","Male",0,0,49,"El-Salvador","<=50K" +26,"Private",118736,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +25,"Private",171114,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +35,"Private",169638,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,36,"United-States","<=50K" +41,"Private",125461,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States",">50K" +33,"Private",145434,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",152182,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +27,"Self-emp-inc",233724,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +32,"Private",153963,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +51,"Local-gov",88120,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +38,"Private",96330,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +41,"Local-gov",66118,"Some-college",10,"Married-civ-spouse","Transport-moving","Wife","White","Female",0,0,25,"United-States","<=50K" +38,"Self-emp-not-inc",53628,"Assoc-voc",11,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,35,"United-States","<=50K" +54,"Private",174865,"9th",5,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +30,"Private",66194,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"Outlying-US(Guam-USVI-etc)","<=50K" +31,"Private",73796,"Some-college",10,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,30,"United-States","<=50K" +26,"State-gov",28366,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",237865,"Masters",14,"Never-married","Transport-moving","Own-child","Black","Male",0,0,40,"United-States","<=50K" +61,"Private",195453,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",116934,"Some-college",10,"Separated","Sales","Unmarried","White","Female",0,0,45,"United-States","<=50K" +22,"?",87867,"12th",8,"Never-married","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +34,"Private",456399,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",263608,"Some-college",10,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",263498,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",183765,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"?","<=50K" +39,"Local-gov",113253,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +20,"Private",138768,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",302146,"11th",7,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +68,"Private",253866,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +28,"Federal-gov",214858,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,48,"United-States","<=50K" +43,"Private",243476,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",169104,"Some-college",10,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",103218,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",57233,"Bachelors",13,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",228320,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +20,"Private",217421,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +46,"Private",185041,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,75,"United-States",">50K" +32,"Private",261059,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +46,"Private",59767,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +26,"Private",333541,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,24,"United-States","<=50K" +20,"Private",133352,"Some-college",10,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +36,"Private",99270,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,0,40,"United-States","<=50K" +49,"Private",204629,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",281021,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +22,"Private",275385,"Some-college",10,"Never-married","Other-service","Other-relative","White","Male",0,0,25,"United-States","<=50K" +52,"Federal-gov",129177,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",385591,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +22,"?",201179,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +72,"Private",38360,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,16,"United-States","<=50K" +30,"Local-gov",73796,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",67671,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",257621,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +22,"Private",180052,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +59,"Private",656036,"Bachelors",13,"Separated","Adm-clerical","Unmarried","White","Male",0,0,60,"United-States","<=50K" +46,"Private",215943,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",488720,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +64,"Federal-gov",199298,"7th-8th",4,"Widowed","Other-service","Unmarried","White","Female",0,0,30,"Puerto-Rico","<=50K" +31,"Private",305692,"Some-college",10,"Married-civ-spouse","Sales","Wife","Black","Female",0,0,40,"United-States","<=50K" +64,"Private",114994,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +45,"Private",88265,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +32,"Private",175413,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","Black","Female",0,0,40,"Jamaica","<=50K" +43,"Private",161226,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +23,"Private",208598,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +49,"Self-emp-not-inc",200471,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",256609,"12th",8,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +49,"Private",176684,"Assoc-voc",11,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",206512,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",212640,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,85,"United-States","<=50K" +47,"Private",148724,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States","<=50K" +41,"Private",266510,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",240252,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",358975,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +20,"?",124242,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"Private",434710,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +25,"Private",204338,"HS-grad",9,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,30,"?","<=50K" +46,"Private",241844,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",191342,"1st-4th",2,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Cambodia","<=50K" +41,"Private",221947,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,56,"United-States",">50K" +30,"Private",65278,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Private",133403,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",166416,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,99,"United-States","<=50K" +58,"?",142158,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +21,"Private",221480,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,25,"Ecuador","<=50K" +35,"Self-emp-not-inc",189878,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",278403,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,80,"United-States",">50K" +19,"Private",184710,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,20,"United-States","<=50K" +48,"Private",177775,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"?",275943,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Nicaragua","<=50K" +65,"Self-emp-not-inc",225473,"Some-college",10,"Widowed","Craft-repair","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +40,"Private",289403,"Bachelors",13,"Separated","Adm-clerical","Unmarried","Black","Male",0,0,35,"United-States","<=50K" +26,"Private",269060,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",449354,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",214413,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",80058,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Self-emp-not-inc",123440,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +37,"Private",191524,"Assoc-voc",11,"Separated","Prof-specialty","Own-child","White","Female",0,0,38,"United-States","<=50K" +25,"Private",308144,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +64,"Private",164204,"1st-4th",2,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,53,"?","<=50K" +46,"Private",205100,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +30,"Private",195750,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,27,"United-States","<=50K" +63,"Private",149756,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +51,"Local-gov",240358,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +68,"Self-emp-not-inc",241174,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,16,"United-States","<=50K" +36,"Private",356838,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"Canada","<=50K" +28,"Self-emp-inc",115705,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +41,"Local-gov",137142,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",296066,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",401335,"Some-college",10,"Never-married","Other-service","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +33,"?",182771,"Bachelors",13,"Never-married","?","Own-child","Asian-Pac-Islander","Male",0,0,80,"Philippines","<=50K" +46,"Federal-gov",162187,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",98010,"Some-college",10,"Married-spouse-absent","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",172538,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States",">50K" +18,"Private",80163,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +56,"Self-emp-not-inc",115422,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States","<=50K" +54,"Private",100933,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",270379,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +40,"Private",20109,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","Amer-Indian-Eskimo","Female",0,0,84,"United-States","<=50K" +22,"Private",100345,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +33,"Private",184901,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",87239,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +63,"Private",127363,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,12,"United-States","<=50K" +37,"Private",143058,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +50,"Federal-gov",36489,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +22,"Private",141698,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Federal-gov",26358,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",30039,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",125159,"Assoc-acdm",12,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"Jamaica","<=50K" +20,"Private",246250,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Federal-gov",77370,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",355569,"Assoc-voc",11,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States","<=50K" +32,"Private",180603,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",201785,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Private",256211,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +27,"Private",146764,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +22,"?",211968,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"Iran","<=50K" +29,"Private",200515,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,38,"United-States","<=50K" +29,"Private",52636,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",27049,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,20,"United-States","<=50K" +35,"Private",111128,"10th",6,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",93930,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +46,"Private",33794,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,10,"United-States","<=50K" +45,"Private",178215,"9th",5,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States",">50K" +17,"Local-gov",191910,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +48,"Self-emp-not-inc",133694,"Bachelors",13,"Married-spouse-absent","Exec-managerial","Not-in-family","Black","Male",0,0,40,"Jamaica",">50K" +49,"Private",148398,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +20,"Private",133515,"Some-college",10,"Never-married","Sales","Other-relative","White","Female",0,0,40,"United-States","<=50K" +64,"Private",159715,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +53,"Federal-gov",174040,"Some-college",10,"Separated","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +52,"Private",117700,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",37215,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +48,"Self-emp-not-inc",317360,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,20,"United-States",">50K" +30,"Private",425627,"Some-college",10,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +34,"Private",82623,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +19,"?",63574,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,50,"United-States","<=50K" +39,"Private",140854,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +28,"Private",185061,"11th",7,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +17,"Private",160118,"12th",8,"Never-married","Sales","Not-in-family","White","Female",0,0,10,"?","<=50K" +54,"Private",282680,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +25,"Private",198163,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",132749,"11th",7,"Divorced","Other-service","Unmarried","White","Female",0,0,12,"United-States","<=50K" +24,"Private",399449,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Private",27494,"Some-college",10,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,50,"Taiwan","<=50K" +47,"Private",368561,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",102096,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"?",">50K" +19,"Private",406078,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +52,"Private",29658,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"?",20469,"HS-grad",9,"Never-married","?","Other-relative","Asian-Pac-Islander","Female",0,0,12,"South","<=50K" +60,"Private",181953,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,28,"United-States","<=50K" +43,"Private",304175,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",170070,"Assoc-acdm",12,"Divorced","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +20,"?",193416,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Private",194908,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",357962,"9th",5,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",214716,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +40,"Self-emp-inc",207578,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +54,"Private",146409,"Some-college",10,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",341643,"Bachelors",13,"Never-married","Other-service","Other-relative","White","Male",0,0,50,"United-States","<=50K" +52,"Private",131631,"11th",7,"Separated","Machine-op-inspct","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +56,"?",128900,"Some-college",10,"Widowed","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",417136,"HS-grad",9,"Divorced","Craft-repair","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",209301,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Canada","<=50K" +29,"Private",120986,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,65,"United-States","<=50K" +27,"Private",51025,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +58,"Private",218281,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Mexico","<=50K" +64,"Private",114994,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,18,"United-States","<=50K" +53,"Private",335481,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,32,"United-States","<=50K" +21,"Private",174503,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +40,"Self-emp-not-inc",230478,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +52,"State-gov",149650,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Iran",">50K" +38,"Private",149419,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +40,"?",341539,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +39,"Private",185099,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"?",132930,"Masters",14,"Never-married","?","Not-in-family","White","Female",0,0,50,"United-States",">50K" +68,"Private",128472,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +24,"Private",124971,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +40,"Self-emp-inc",344060,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Self-emp-inc",286750,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,99,"United-States",">50K" +38,"Private",296999,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +45,"Private",123681,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",232024,"11th",7,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,55,"United-States","<=50K" +57,"Local-gov",52267,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +49,"Private",119182,"HS-grad",9,"Separated","Other-service","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +25,"Private",191230,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"Yugoslavia","<=50K" +52,"Federal-gov",23780,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"Private",184553,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +26,"Self-emp-inc",242651,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +19,"Private",246226,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Self-emp-inc",86745,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +25,"Private",106889,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,30,"United-States","<=50K" +21,"Private",460835,"HS-grad",9,"Never-married","Sales","Other-relative","White","Male",0,0,45,"United-States","<=50K" +48,"Self-emp-not-inc",213140,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Italy","<=50K" +33,"State-gov",37070,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"Canada","<=50K" +31,"State-gov",93589,"HS-grad",9,"Divorced","Protective-serv","Own-child","Other","Male",0,0,40,"United-States","<=50K" +26,"Self-emp-not-inc",213258,"HS-grad",9,"Divorced","Farming-fishing","Unmarried","White","Male",0,0,65,"United-States","<=50K" +37,"State-gov",46814,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +29,"?",168873,"Some-college",10,"Divorced","?","Unmarried","White","Female",0,0,30,"United-States","<=50K" +20,"Private",284737,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +28,"Private",309620,"Some-college",10,"Married-civ-spouse","Sales","Husband","Other","Male",0,0,60,"?","<=50K" +49,"Private",197418,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,20,"United-States","<=50K" +73,"?",132737,"10th",6,"Never-married","?","Not-in-family","White","Male",0,0,4,"United-States","<=50K" +51,"Private",159604,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +40,"Private",123557,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",275421,"Assoc-voc",11,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +18,"Private",167147,"12th",8,"Never-married","Sales","Own-child","White","Male",0,0,24,"United-States","<=50K" +41,"Private",197583,"10th",6,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States",">50K" +46,"Private",117502,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +64,"Private",180401,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Self-emp-not-inc",146603,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +53,"State-gov",143822,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,36,"United-States",">50K" +21,"Private",51985,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"State-gov",48121,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,25,"United-States","<=50K" +39,"Federal-gov",65324,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,55,"United-States",">50K" +30,"Private",302149,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +26,"Private",159897,"Some-college",10,"Never-married","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",416338,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +59,"Private",370615,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,60,"United-States","<=50K" +27,"Private",219371,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",0,0,40,"Jamaica","<=50K" +55,"Private",120970,"10th",6,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +20,"Private",22966,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,12,"Canada","<=50K" +25,"Private",34541,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,36,"Canada","<=50K" +28,"Private",191027,"Assoc-acdm",12,"Separated","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",107458,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +60,"Private",121832,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",73839,"11th",7,"Divorced","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Private",109165,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +50,"State-gov",103063,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",111979,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,47,"United-States","<=50K" +35,"Private",150125,"Assoc-voc",11,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +21,"?",301853,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",118001,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +49,"Private",149337,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",36601,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +39,"Private",279272,"Assoc-acdm",12,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,60,"United-States","<=50K" +35,"Private",181020,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,60,"United-States","<=50K" +52,"Private",165998,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",218136,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"Outlying-US(Guam-USVI-etc)","<=50K" +20,"Self-emp-inc",182200,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,30,"United-States","<=50K" +46,"Private",39363,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,10,"?","<=50K" +24,"Private",140001,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",193260,"Bachelors",13,"Married-civ-spouse","Craft-repair","Other-relative","Asian-Pac-Islander","Male",0,0,30,"India","<=50K" +21,"Private",191243,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Federal-gov",207887,"Bachelors",13,"Divorced","Exec-managerial","Other-relative","White","Female",0,0,50,"United-States","<=50K" +43,"Federal-gov",211450,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",184759,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,26,"United-States","<=50K" +47,"Private",197836,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +61,"Private",232308,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +21,"?",189888,"Assoc-acdm",12,"Never-married","?","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +35,"Private",301614,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,60,"United-States","<=50K" +60,"Private",146674,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",225291,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"Local-gov",148509,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,35,"India","<=50K" +56,"Private",136413,"1st-4th",2,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",126060,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",73064,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Wife","Black","Female",0,0,35,"United-States","<=50K" +19,"Private",39026,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +28,"Self-emp-not-inc",33035,"12th",8,"Divorced","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +43,"Private",193494,"10th",6,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Local-gov",147440,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +22,"?",153131,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",64671,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +20,"Private",174391,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +48,"Private",377757,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States","<=50K" +30,"Local-gov",364310,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"Germany","<=50K" +31,"Private",110643,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",70240,"HS-grad",9,"Never-married","Sales","Own-child","Asian-Pac-Islander","Female",0,0,24,"Philippines","<=50K" +57,"State-gov",32694,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Private",264936,"HS-grad",9,"Divorced","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +27,"Private",367329,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",56026,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +22,"Private",186452,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +50,"Private",125417,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,40,"United-States",">50K" +40,"Self-emp-not-inc",242082,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +37,"Private",31023,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,51,"United-States","<=50K" +40,"?",397346,"Assoc-acdm",12,"Divorced","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"State-gov",261979,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Private",55507,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +22,"?",291407,"12th",8,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +18,"Private",353358,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +33,"Private",235109,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",208180,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +67,"State-gov",423561,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",403671,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Local-gov",49325,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",370494,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +25,"Private",267012,"Assoc-voc",11,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +33,"Private",191856,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Private",80445,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",379798,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Local-gov",168387,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",274809,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States","<=50K" +58,"Private",233193,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,27,"United-States","<=50K" +19,"Private",236396,"11th",7,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",688355,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-inc",37019,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +43,"Private",122975,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","Black","Female",0,0,21,"Trinadad&Tobago","<=50K" +52,"State-gov",349795,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",229846,"Assoc-voc",11,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"?","<=50K" +43,"Private",108945,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,38,"United-States","<=50K" +22,"Private",237498,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",324019,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",82488,"Some-college",10,"Divorced","Sales","Unmarried","Asian-Pac-Islander","Female",0,0,38,"United-States","<=50K" +54,"Private",206964,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",37088,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",152540,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +65,"Private",143554,"Some-college",10,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +30,"Private",126242,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +22,"Private",127185,"9th",5,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",210184,"11th",7,"Separated","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"?",117528,"Assoc-voc",11,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States",">50K" +23,"Private",182117,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Male",0,0,60,"United-States","<=50K" +42,"Private",220049,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States",">50K" +39,"Self-emp-not-inc",247975,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,0,30,"United-States","<=50K" +55,"Private",50164,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +24,"State-gov",123160,"Masters",14,"Married-spouse-absent","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",0,0,10,"China","<=50K" +53,"Private",79324,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",129100,"11th",7,"Separated","Other-service","Unmarried","Black","Female",0,0,60,"United-States","<=50K" +40,"Private",210275,"HS-grad",9,"Separated","Transport-moving","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +26,"Private",171114,"Assoc-voc",11,"Separated","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +22,"Private",201799,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"?",200426,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,12,"United-States","<=50K" +20,"?",24395,"Some-college",10,"Never-married","?","Unmarried","White","Female",0,0,20,"United-States","<=50K" +43,"Private",191149,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Local-gov",34173,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,25,"United-States","<=50K" +30,"Private",350979,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Laos","<=50K" +41,"Private",147314,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Amer-Indian-Eskimo","Male",0,0,50,"United-States","<=50K" +38,"Private",136081,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +77,"?",232894,"9th",5,"Married-civ-spouse","?","Husband","Black","Male",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",373403,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"Private",120601,"HS-grad",9,"Never-married","Transport-moving","Own-child","Black","Male",0,0,40,"United-States","<=50K" +32,"Federal-gov",72338,"Assoc-voc",11,"Never-married","Prof-specialty","Other-relative","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +27,"Private",129624,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +25,"State-gov",328697,"Some-college",10,"Divorced","Protective-serv","Other-relative","White","Male",0,0,45,"United-States","<=50K" +40,"Private",191196,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"?",191117,"11th",7,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +49,"Private",110243,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +17,"Private",181580,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +29,"Private",89030,"HS-grad",9,"Never-married","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Self-emp-not-inc",277700,"Some-college",10,"Separated","Handlers-cleaners","Own-child","White","Male",0,0,45,"United-States","<=50K" +58,"?",198478,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,24,"United-States","<=50K" +29,"Private",250679,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",168837,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,24,"Canada",">50K" +30,"Private",142675,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +19,"Private",299050,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +47,"Private",121958,"7th-8th",4,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +28,"Private",176683,"Assoc-acdm",12,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"France","<=50K" +46,"Private",34377,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Self-emp-not-inc",209833,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +66,"State-gov",41506,"10th",6,"Divorced","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",147206,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,12,"United-States","<=50K" +21,"Private",315065,"7th-8th",4,"Never-married","Other-service","Other-relative","White","Male",0,0,48,"Mexico","<=50K" +59,"Private",381851,"9th",5,"Widowed","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +35,"Local-gov",185769,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",312667,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",343925,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"Jamaica","<=50K" +26,"Private",195994,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +48,"Private",398843,"Some-college",10,"Separated","Sales","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +31,"Private",73514,"HS-grad",9,"Never-married","Sales","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +36,"Private",288049,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +48,"Private",54759,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,38,"United-States","<=50K" +33,"Private",401104,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States",">50K" +19,"?",124884,"9th",5,"Never-married","?","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +53,"Private",113995,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +18,"Private",146378,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"?","<=50K" +34,"Private",34374,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +45,"Private",162187,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,52,"United-States",">50K" +33,"Local-gov",147654,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +35,"Private",182467,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,44,"United-States","<=50K" +22,"Private",183970,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",332588,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +45,"Private",26781,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",0,0,8,"United-States","<=50K" +17,"Private",48610,"11th",7,"Never-married","Farming-fishing","Own-child","White","Male",0,0,45,"United-States","<=50K" +50,"Private",162632,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +38,"Local-gov",91711,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +46,"Private",179048,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"?","<=50K" +64,"Private",102470,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Self-emp-not-inc",123170,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,10,"United-States","<=50K" +32,"Private",164243,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,60,"United-States",">50K" +17,"Private",262511,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +61,"Private",51170,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +40,"State-gov",91949,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +21,"Private",123727,"HS-grad",9,"Never-married","Exec-managerial","Other-relative","White","Female",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",120301,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +29,"Private",250967,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Federal-gov",285432,"Assoc-acdm",12,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",36235,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"?",317219,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"United-States",">50K" +51,"Local-gov",110965,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",123283,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","Black","Female",0,0,15,"United-States","<=50K" +20,"?",249087,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Private",152940,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",376680,"HS-grad",9,"Never-married","Tech-support","Own-child","Black","Male",0,0,40,"United-States","<=50K" +56,"Private",231232,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,30,"Canada","<=50K" +55,"Self-emp-not-inc",168625,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Female",0,0,12,"United-States",">50K" +26,"Private",33939,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,20,"United-States","<=50K" +32,"Local-gov",190228,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",216178,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",587310,"7th-8th",4,"Never-married","Other-service","Other-relative","White","Male",0,0,35,"Guatemala","<=50K" +23,"Private",155919,"9th",5,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +59,"Private",227386,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",138152,"12th",8,"Never-married","Craft-repair","Other-relative","Other","Male",0,0,48,"Guatemala","<=50K" +36,"Private",167482,"10th",6,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",57957,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +33,"Private",157747,"9th",5,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +60,"Self-emp-not-inc",88570,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Wife","White","Female",0,0,15,"Germany",">50K" +40,"Private",273308,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,48,"Mexico","<=50K" +48,"Private",216292,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,43,"United-States","<=50K" +27,"Self-emp-not-inc",131298,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +19,"Private",386378,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +38,"Private",179668,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",210812,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,43,"United-States","<=50K" +20,"Private",215247,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +32,"Federal-gov",125856,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +22,"Private",74631,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,13,"United-States","<=50K" +22,"Private",24008,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",308334,"1st-4th",2,"Widowed","Other-service","Unmarried","Other","Female",0,0,30,"Mexico","<=50K" +39,"Private",245361,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +79,"Self-emp-not-inc",158319,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +60,"?",204486,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States",">50K" +24,"Private",314823,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"Dominican-Republic","<=50K" +23,"Private",126550,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +29,"Private",114224,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +22,"State-gov",64292,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,43,"United-States","<=50K" +69,"?",628797,"Some-college",10,"Widowed","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +55,"Local-gov",219775,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,38,"United-States","<=50K" +43,"Private",212894,"HS-grad",9,"Divorced","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +23,"Private",260019,"7th-8th",4,"Never-married","Farming-fishing","Unmarried","Other","Male",0,0,36,"Mexico","<=50K" +29,"Private",228075,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,35,"Mexico","<=50K" +22,"Private",239806,"Assoc-voc",11,"Never-married","Other-service","Other-relative","White","Female",0,0,40,"Mexico","<=50K" +22,"Private",324637,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +29,"Private",194200,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,45,"United-States","<=50K" +25,"State-gov",129200,"Some-college",10,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +33,"Federal-gov",207172,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",135312,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +31,"Private",100734,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +55,"Private",110871,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"?",224108,"HS-grad",9,"Widowed","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Private",107762,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Private",183611,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,55,"Germany","<=50K" +62,"Local-gov",249078,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +65,"Self-emp-inc",208452,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States",">50K" +23,"Private",302195,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"?",199947,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,32,"United-States","<=50K" +47,"Private",379118,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,60,"United-States",">50K" +50,"Self-emp-inc",174855,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +70,"?",173736,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,6,"United-States","<=50K" +32,"Self-emp-not-inc",39369,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Federal-gov",196348,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +76,"Private",97077,"10th",6,"Widowed","Sales","Unmarried","Black","Female",0,0,12,"United-States","<=50K" +54,"Private",200098,"Bachelors",13,"Divorced","Sales","Not-in-family","Black","Female",0,0,60,"United-States","<=50K" +32,"Federal-gov",127651,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",315128,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,52,"United-States","<=50K" +31,"Federal-gov",206823,"Bachelors",13,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,50,"United-States",">50K" +30,"Private",112115,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"Ireland",">50K" +63,"?",203821,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",250051,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,10,"United-States","<=50K" +26,"State-gov",109193,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",130849,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,8,"United-States","<=50K" +34,"Local-gov",43959,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Self-emp-not-inc",27242,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,60,"United-States","<=50K" +30,"Private",53158,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",206520,"Bachelors",13,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",164190,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",287988,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +28,"?",200819,"7th-8th",4,"Divorced","?","Own-child","White","Male",0,0,84,"United-States","<=50K" +23,"Private",83891,"HS-grad",9,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",363418,"Bachelors",13,"Separated","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +19,"Private",278870,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,16,"United-States","<=50K" +25,"Private",228608,"Some-college",10,"Never-married","Craft-repair","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Cambodia","<=50K" +24,"Private",184400,"HS-grad",9,"Never-married","Transport-moving","Own-child","Asian-Pac-Islander","Male",0,0,30,"?","<=50K" +46,"Private",263568,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",117381,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +41,"Federal-gov",83411,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Self-emp-not-inc",49156,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,20,"United-States","<=50K" +44,"Private",421449,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",238944,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",188982,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,20,"United-States",">50K" +48,"Private",175925,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +34,"Private",164190,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",232914,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +46,"Self-emp-inc",120121,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Local-gov",180805,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +59,"Local-gov",161944,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +29,"Private",319149,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Mexico","<=50K" +50,"?",22428,"Masters",14,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",290528,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",123984,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,35,"Philippines","<=50K" +48,"Private",34186,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +49,"State-gov",55938,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",209900,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,20,"United-States","<=50K" +26,"Private",150361,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +69,"?",164102,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States",">50K" +59,"Private",252714,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,30,"Italy","<=50K" +30,"Private",205204,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Local-gov",168906,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States","<=50K" +30,"Private",112115,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",116531,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"?",202994,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,16,"United-States","<=50K" +24,"Private",341294,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",216734,"Bachelors",13,"Divorced","Sales","Unmarried","White","Female",0,0,50,"United-States","<=50K" +51,"Private",182187,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,35,"United-States","<=50K" +34,"Private",424988,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +47,"Private",379118,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Male",0,0,9,"United-States","<=50K" +47,"Private",168232,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,44,"United-States",">50K" +20,"Private",147171,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +34,"Self-emp-inc",207668,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,54,"?",">50K" +31,"Private",193650,"11th",7,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",200187,"Assoc-voc",11,"Divorced","Other-service","Unmarried","White","Female",0,0,32,"United-States","<=50K" +52,"Private",188644,"5th-6th",3,"Married-spouse-absent","Craft-repair","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +56,"Private",398067,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Private",29658,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",154966,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +81,"Private",364099,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +28,"?",291374,"10th",6,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +57,"Federal-gov",97837,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,48,"United-States",">50K" +34,"Private",117983,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"?",345497,"10th",6,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",64167,"Assoc-voc",11,"Never-married","Tech-support","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +60,"Private",225526,"HS-grad",9,"Separated","Sales","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +37,"Federal-gov",289653,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",179462,"7th-8th",4,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +36,"Federal-gov",67317,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",77764,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",253438,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +31,"Private",150309,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +47,"Self-emp-not-inc",83064,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +60,"Self-emp-not-inc",376973,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,42,"United-States",">50K" +75,"Private",311184,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,24,"United-States","<=50K" +43,"Local-gov",159449,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",168288,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",275190,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +32,"Private",189838,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +57,"Self-emp-inc",101338,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States","<=50K" +43,"Private",331894,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +18,"Self-emp-not-inc",40293,"HS-grad",9,"Never-married","Farming-fishing","Other-relative","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",88904,"Bachelors",13,"Separated","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +48,"Private",145041,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"Dominican-Republic","<=50K" +41,"State-gov",363591,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",267859,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"El-Salvador","<=50K" +58,"Private",190747,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",162869,"Some-college",10,"Never-married","Sales","Other-relative","White","Male",0,0,65,"United-States","<=50K" +33,"Private",141229,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +42,"Self-emp-not-inc",174216,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +25,"Private",366416,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Private",172538,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +35,"Private",193026,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +49,"Local-gov",337768,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Local-gov",179059,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Federal-gov",99549,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +46,"Private",72619,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +42,"State-gov",55764,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +37,"Private",30267,"11th",7,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States",">50K" +25,"Private",308144,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +26,"Private",282304,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +26,"?",176077,"Some-college",10,"Never-married","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-inc",142719,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",114973,"HS-grad",9,"Separated","Exec-managerial","Unmarried","White","Female",0,0,30,"United-States","<=50K" +33,"Federal-gov",159548,"Assoc-acdm",12,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",91209,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",196564,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +51,"Self-emp-not-inc",149220,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,75,"United-States","<=50K" +21,"Private",169699,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +23,"Private",218215,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +30,"Private",156718,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",55720,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +38,"Self-emp-inc",257250,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +20,"Private",194630,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",196266,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Local-gov",197332,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",97842,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",57324,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +43,"Private",116852,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,36,"Portugal",">50K" +37,"Private",38468,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Local-gov",188808,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",187322,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +38,"Private",168680,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",256755,"Bachelors",13,"Never-married","Handlers-cleaners","Other-relative","White","Female",0,0,40,"Cuba","<=50K" +18,"Private",188476,"11th",7,"Never-married","Exec-managerial","Own-child","White","Male",0,0,20,"United-States","<=50K" +47,"Private",30457,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",252752,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +41,"Self-emp-not-inc",443508,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +23,"Private",244408,"Some-college",10,"Never-married","Adm-clerical","Other-relative","Asian-Pac-Islander","Female",0,0,24,"Vietnam","<=50K" +41,"Private",178983,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +30,"Local-gov",247328,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",201732,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",246829,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"?",290267,"Bachelors",13,"Never-married","?","Not-in-family","White","Male",0,0,18,"United-States","<=50K" +29,"Private",119170,"Some-college",10,"Separated","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +21,"Private",207923,"Some-college",10,"Married-spouse-absent","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +48,"State-gov",170142,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +44,"Self-emp-not-inc",187164,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Male",0,0,60,"United-States","<=50K" +34,"Local-gov",303867,"9th",5,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",291429,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +32,"Private",213179,"Some-college",10,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States",">50K" +31,"State-gov",111843,"Assoc-acdm",12,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +47,"Federal-gov",68493,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States",">50K" +46,"Federal-gov",340718,"11th",7,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",194059,"12th",8,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"State-gov",286310,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Private",207202,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States",">50K" +33,"Self-emp-inc",132601,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +17,"?",139183,"10th",6,"Never-married","?","Own-child","White","Female",0,0,15,"United-States","<=50K" +41,"Private",160785,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Local-gov",225605,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,44,"United-States","<=50K" +24,"Private",190290,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +49,"Private",164799,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +60,"Federal-gov",21876,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +44,"Private",160785,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +63,"Self-emp-inc",272425,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",168538,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +45,"Self-emp-inc",204205,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Private",169926,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +65,"Local-gov",205024,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,8,"United-States","<=50K" +41,"Private",374764,"Bachelors",13,"Widowed","Exec-managerial","Unmarried","White","Male",0,0,20,"United-States","<=50K" +25,"Private",108779,"Masters",14,"Separated","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"?",293136,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +60,"Private",227332,"Assoc-voc",11,"Widowed","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"Local-gov",246308,"11th",7,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"Puerto-Rico","<=50K" +28,"Private",51331,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,16,"United-States",">50K" +31,"Private",153078,"Assoc-acdm",12,"Never-married","Craft-repair","Own-child","Other","Male",0,0,50,"United-States","<=50K" +47,"Private",169180,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +45,"Self-emp-not-inc",193451,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +51,"Private",305147,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",138892,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Male",0,0,40,"United-States","<=50K" +34,"Private",223267,"HS-grad",9,"Never-married","Exec-managerial","Other-relative","White","Male",0,0,50,"United-States","<=50K" +19,"Private",29250,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,10,"United-States","<=50K" +51,"?",203953,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +46,"State-gov",29696,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",632613,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"Mexico","<=50K" +56,"Private",282023,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +29,"Private",77760,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +46,"Self-emp-not-inc",148599,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +55,"Private",414994,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",499249,"HS-grad",9,"Married-spouse-absent","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"Guatemala","<=50K" +45,"?",144354,"9th",5,"Separated","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +41,"Private",252058,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"?",99543,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +34,"Private",117963,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",194652,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",299705,"Some-college",10,"Never-married","Handlers-cleaners","Unmarried","Black","Male",0,0,37,"United-States","<=50K" +19,"Federal-gov",27433,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +47,"Local-gov",39986,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-inc",135342,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Private",270142,"Assoc-voc",11,"Separated","Exec-managerial","Unmarried","Black","Female",0,0,60,"United-States","<=50K" +33,"Self-emp-not-inc",118267,"Assoc-acdm",12,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +29,"Private",266043,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",35633,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",74568,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",214816,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +43,"Private",222971,"5th-6th",3,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +31,"Private",259425,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Self-emp-inc",212120,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",245880,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +58,"Local-gov",54947,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +28,"Private",161674,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",62346,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +40,"Private",227236,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +19,"Private",283033,"11th",7,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",251229,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +76,"Private",199949,"9th",5,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,13,"United-States","<=50K" +23,"State-gov",305498,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",203836,"5th-6th",3,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"State-gov",79440,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,30,"Japan","<=50K" +48,"Local-gov",142719,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Private",119859,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States",">50K" +32,"Private",141410,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +44,"Local-gov",202872,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,25,"United-States","<=50K" +27,"Private",198813,"HS-grad",9,"Divorced","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +33,"Federal-gov",129707,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +22,"Private",445758,"5th-6th",3,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +18,"?",30246,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +44,"Private",173981,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",108506,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,60,"United-States","<=50K" +34,"Private",134886,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-inc",282913,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Cuba","<=50K" +59,"Local-gov",196013,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Federal-gov",348491,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,40,"United-States",">50K" +52,"Private",416164,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Other","Male",0,0,49,"Mexico","<=50K" +17,"Private",121037,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +29,"Private",103111,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,30,"Canada","<=50K" +63,"Self-emp-not-inc",147589,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States",">50K" +20,"Private",24008,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,24,"United-States","<=50K" +50,"Self-emp-not-inc",175456,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +55,"Private",84774,"HS-grad",9,"Married-civ-spouse","Priv-house-serv","Wife","White","Female",0,0,30,"United-States","<=50K" +27,"Private",194590,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,25,"United-States","<=50K" +28,"Private",134566,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +55,"Private",211678,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +44,"Federal-gov",44822,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"State-gov",144586,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",119156,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",371987,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"State-gov",144125,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-not-inc",121124,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +46,"Private",58126,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",318518,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",296509,"7th-8th",4,"Separated","Farming-fishing","Not-in-family","White","Male",0,0,45,"Mexico","<=50K" +32,"Private",473133,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",155434,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States","<=50K" +39,"Private",56648,"HS-grad",9,"Separated","Sales","Not-in-family","White","Female",0,0,47,"United-States","<=50K" +22,"State-gov",119838,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,10,"United-States","<=50K" +26,"Private",330695,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"State-gov",58039,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",313022,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +42,"Private",178134,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +40,"Private",165309,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,43,"United-States","<=50K" +22,"Private",216181,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,45,"United-States","<=50K" +62,"Private",178745,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +44,"Private",111067,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"?",163788,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",295591,"1st-4th",2,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +45,"Private",123075,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +18,"Private",78045,"11th",7,"Married-civ-spouse","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Local-gov",255004,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",254221,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States",">50K" +20,"Private",174714,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,15,"United-States","<=50K" +68,"Self-emp-not-inc",450580,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,20,"United-States","<=50K" +61,"Private",128230,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +48,"Private",192894,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",325390,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Federal-gov",128714,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,32,"United-States","<=50K" +35,"Private",170797,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",269186,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",127671,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",211840,"Some-college",10,"Separated","Sales","Unmarried","Black","Female",0,0,16,"United-States","<=50K" +37,"Private",163392,"HS-grad",9,"Never-married","Transport-moving","Other-relative","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +40,"Private",201495,"Bachelors",13,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +25,"Private",251854,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"Jamaica","<=50K" +41,"Private",279297,"HS-grad",9,"Never-married","Sales","Not-in-family","Black","Female",0,0,60,"United-States","<=50K" +52,"Self-emp-not-inc",195462,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,98,"United-States",">50K" +33,"Private",170769,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",142443,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +53,"Private",121441,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +44,"Private",275094,"1st-4th",2,"Never-married","Other-service","Own-child","White","Male",0,0,10,"United-States","<=50K" +35,"Private",170263,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",172571,"Some-college",10,"Divorced","Craft-repair","Own-child","White","Male",0,0,58,"Poland","<=50K" +34,"Private",178615,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",279524,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"State-gov",165201,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,45,"United-States","<=50K" +65,"Local-gov",323006,"HS-grad",9,"Widowed","Other-service","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +29,"Private",235168,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +46,"Local-gov",216414,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +47,"State-gov",80914,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,47,"United-States",">50K" +62,"Private",73292,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",212165,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +90,"Private",52386,"Some-college",10,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,35,"United-States","<=50K" +33,"Private",205649,"Assoc-acdm",12,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +25,"Private",200408,"Assoc-acdm",12,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-inc",187720,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Private",236180,"Bachelors",13,"Married-spouse-absent","Other-service","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +21,"Private",118693,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",363130,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Male",0,0,18,"United-States","<=50K" +39,"Private",225544,"Masters",14,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Poland","<=50K" +59,"Federal-gov",243612,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",160786,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +49,"Private",234320,"7th-8th",4,"Never-married","Prof-specialty","Other-relative","Black","Male",0,0,45,"United-States","<=50K" +34,"Private",314646,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",124971,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",209184,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Other","Male",0,0,40,"Puerto-Rico","<=50K" +39,"State-gov",121838,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +46,"Private",265275,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +34,"Private",45522,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",120283,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,24,"United-States","<=50K" +20,"Private",216972,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +20,"Private",116791,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Female",0,0,40,"United-States","<=50K" +55,"State-gov",26290,"Assoc-voc",11,"Widowed","Exec-managerial","Not-in-family","Amer-Indian-Eskimo","Female",0,0,38,"United-States","<=50K" +22,"Private",216134,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",143932,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",217120,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +47,"State-gov",223944,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,30,"United-States","<=50K" +23,"Private",185452,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,35,"Canada","<=50K" +57,"Local-gov",44273,"HS-grad",9,"Widowed","Transport-moving","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +52,"Private",178983,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",219288,"7th-8th",4,"Widowed","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +25,"Private",349190,"Assoc-acdm",12,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +41,"Federal-gov",57924,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"State-gov",270324,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,30,"United-States","<=50K" +38,"Private",33001,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +58,"Private",204021,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"Canada","<=50K" +26,"Private",192506,"Bachelors",13,"Never-married","Other-service","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +57,"Private",372967,"10th",6,"Divorced","Adm-clerical","Other-relative","White","Female",0,0,70,"Germany","<=50K" +42,"Private",195821,"HS-grad",9,"Separated","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +17,"?",127003,"9th",5,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",124090,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",199600,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",218311,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,50,"United-States","<=50K" +27,"Private",167336,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,39,"United-States","<=50K" +41,"Private",59938,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,43,"United-States","<=50K" +28,"Private",263728,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +73,"?",180603,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +49,"Private",43910,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,30,"United-States","<=50K" +47,"Private",190139,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",109001,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,49,"United-States","<=50K" +42,"Local-gov",159931,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +32,"Private",194987,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +32,"Local-gov",87310,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,41,"United-States","<=50K" +27,"Private",133937,"Masters",14,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",207064,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",36011,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +58,"Self-emp-not-inc",49884,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Private",229977,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +21,"Private",64520,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +32,"?",134886,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,2,"United-States",">50K" +37,"Private",305379,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",202284,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +42,"Self-emp-not-inc",99185,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",159662,"HS-grad",9,"Married-civ-spouse","Sales","Own-child","White","Male",0,0,26,"United-States",">50K" +67,"Private",197865,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Local-gov",175149,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","Black","Female",0,0,38,"United-States","<=50K" +49,"Local-gov",349633,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +18,"Private",242893,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +25,"Private",218667,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"State-gov",144811,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +21,"Private",206861,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,20,"?","<=50K" +65,"Self-emp-not-inc",226215,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,15,"United-States","<=50K" +66,"Private",114447,"Assoc-voc",11,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +33,"Private",124187,"11th",7,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,60,"United-States","<=50K" +17,"Private",156501,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +61,"?",161279,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +38,"Private",225707,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Cuba",">50K" +43,"Local-gov",115603,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"State-gov",506329,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Taiwan",">50K" +76,"?",172637,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States",">50K" +42,"Private",56483,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Federal-gov",144778,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +76,"Self-emp-not-inc",33213,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"?",">50K" +17,"Private",137042,"10th",6,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +30,"Self-emp-not-inc",33308,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",158420,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"Iran","<=50K" +22,"Private",41763,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +53,"?",220640,"Bachelors",13,"Divorced","?","Other-relative","Other","Female",0,0,20,"United-States","<=50K" +28,"Private",149734,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,52,"United-States","<=50K" +24,"Private",349691,"Some-college",10,"Never-married","Sales","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +47,"Private",185385,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Self-emp-not-inc",174463,"Assoc-voc",11,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +26,"Private",236068,"Some-college",10,"Never-married","Sales","Other-relative","White","Female",0,0,20,"United-States","<=50K" +63,"?",445168,"Bachelors",13,"Widowed","?","Not-in-family","Amer-Indian-Eskimo","Female",0,0,56,"United-States","<=50K" +25,"Private",91334,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,75,"United-States","<=50K" +28,"Private",33895,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +36,"Private",214816,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",229773,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-inc",166386,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","Asian-Pac-Islander","Female",0,0,35,"Taiwan","<=50K" +44,"Private",266135,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +18,"Private",300379,"12th",8,"Never-married","Adm-clerical","Own-child","White","Male",0,0,12,"United-States","<=50K" +54,"Federal-gov",392502,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +61,"Private",73809,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Private",193720,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +43,"Private",316183,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",162944,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",186888,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,40,"United-States",">50K" +27,"?",330132,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +24,"Private",192017,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,30,"United-States","<=50K" +20,"State-gov",161978,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +52,"Private",202930,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +57,"Local-gov",323309,"7th-8th",4,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-inc",197332,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +42,"Self-emp-inc",204033,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"?","<=50K" +22,"Private",271274,"11th",7,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",174242,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",209483,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +52,"Self-emp-not-inc",102346,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,35,"United-States","<=50K" +25,"Private",181666,"Assoc-acdm",12,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Private",207367,"Some-college",10,"Married-spouse-absent","Other-service","Not-in-family","White","Female",0,0,40,"Cuba","<=50K" +35,"State-gov",82622,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,80,"United-States","<=50K" +50,"Private",202296,"Assoc-voc",11,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +58,"Private",142182,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,25,"United-States","<=50K" +48,"Federal-gov",94342,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +30,"Private",41493,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"Canada","<=50K" +18,"Private",181712,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,12,"United-States","<=50K" +29,"Self-emp-not-inc",164607,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",41496,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +36,"Local-gov",196529,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +24,"Private",157332,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,42,"United-States","<=50K" +30,"Local-gov",154935,"Assoc-acdm",12,"Never-married","Protective-serv","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",223231,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",0,0,40,"Mexico","<=50K" +35,"?",253860,"HS-grad",9,"Divorced","?","Unmarried","White","Female",0,0,20,"United-States","<=50K" +21,"Private",362589,"Bachelors",13,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +28,"Private",94880,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,43,"Mexico","<=50K" +20,"Private",309580,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",130389,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,20,"Scotland","<=50K" +21,"Private",349365,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +27,"Private",376936,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",179557,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",105577,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +51,"Private",224207,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Federal-gov",47907,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Self-emp-not-inc",191283,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"State-gov",186569,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,12,"United-States","<=50K" +59,"Private",43221,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +38,"Private",161141,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",203003,"HS-grad",9,"Never-married","Transport-moving","Other-relative","White","Male",0,0,40,"United-States","<=50K" +90,"Private",141758,"9th",5,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",113322,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",343847,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,38,"United-States",">50K" +45,"Private",214068,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Private",116632,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",240160,"Assoc-acdm",12,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",516337,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +23,"Self-emp-inc",284651,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +39,"State-gov",141420,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",42750,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +54,"Private",165278,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",167265,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,43,"United-States","<=50K" +44,"Private",139907,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,50,"United-States","<=50K" +31,"Self-emp-inc",236415,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States",">50K" +25,"Private",312966,"9th",5,"Separated","Handlers-cleaners","Other-relative","White","Male",0,0,40,"El-Salvador","<=50K" +33,"Private",118941,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,32,"United-States",">50K" +32,"Private",198068,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +36,"Private",373952,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",236111,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Other","Male",0,0,55,"United-States",">50K" +80,"Private",157778,"Masters",14,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +21,"Private",143604,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,8,"United-States","<=50K" +35,"Self-emp-not-inc",319831,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +77,"?",132728,"Masters",14,"Divorced","?","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +35,"?",61343,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",268234,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Self-emp-not-inc",34973,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +41,"Private",323790,"HS-grad",9,"Divorced","Handlers-cleaners","Unmarried","White","Male",0,0,55,"United-States","<=50K" +57,"Private",319733,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Poland",">50K" +21,"?",180339,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,25,"United-States","<=50K" +19,"Private",125591,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"Private",60772,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,45,"United-States","<=50K" +29,"Self-emp-not-inc",141185,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,55,"United-States","<=50K" +38,"?",204668,"Assoc-voc",11,"Separated","?","Unmarried","White","Female",0,0,25,"United-States","<=50K" +26,"Private",273792,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +40,"Private",343068,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",177907,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +28,"Private",144063,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Self-emp-not-inc",257574,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +42,"Self-emp-not-inc",67065,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +32,"Private",183356,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",152940,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +37,"Private",227128,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Local-gov",45607,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,56,"United-States","<=50K" +49,"Private",155489,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"?",230704,"HS-grad",9,"Never-married","?","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +24,"?",267955,"9th",5,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +19,"Private",165115,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",49923,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",272240,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",255476,"7th-8th",4,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"Mexico","<=50K" +59,"Private",194290,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,48,"United-States","<=50K" +52,"Private",145548,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",175262,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Local-gov",37306,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +58,"Private",137547,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +53,"Private",276515,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"Cuba","<=50K" +23,"Private",174626,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +35,"Private",215310,"11th",7,"Divorced","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +49,"Private",332355,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",204057,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",391591,"12th",8,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",169092,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,50,"United-States",">50K" +28,"Private",230743,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",190963,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +74,"?",204840,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,56,"Mexico","<=50K" +19,"Private",169853,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,24,"United-States","<=50K" +31,"Private",202822,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +61,"?",226989,"Some-college",10,"Married-spouse-absent","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",140011,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,53,"United-States","<=50K" +20,"?",432376,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"Germany","<=50K" +35,"Private",90273,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"?",">50K" +23,"Private",224424,"Bachelors",13,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",168943,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,30,"United-States",">50K" +19,"Private",571853,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +30,"Private",156464,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +26,"Private",108542,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +34,"Local-gov",194325,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +49,"Private",114797,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",204756,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",228190,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,20,"United-States","<=50K" +33,"Private",163392,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",0,0,48,"United-States",">50K" +54,"Private",138845,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Local-gov",169853,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Never-worked",206359,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +60,"Private",224097,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",160786,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",190044,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Local-gov",145290,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",120268,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,70,"United-States","<=50K" +17,"Private",327434,"10th",6,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +41,"Self-emp-inc",218302,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +30,"Private",1184622,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,35,"United-States","<=50K" +25,"Private",206343,"HS-grad",9,"Never-married","Protective-serv","Other-relative","White","Male",0,0,40,"United-States","<=50K" +27,"Private",36851,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +29,"Private",148550,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",157079,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"?",">50K" +31,"Federal-gov",142470,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",86750,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,99,"United-States","<=50K" +63,"Private",361631,"Masters",14,"Separated","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +46,"Private",163229,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Private",179594,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",254773,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,50,"United-States",">50K" +26,"Private",58065,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +26,"Private",205428,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +20,"?",41183,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +19,"?",308064,"HS-grad",9,"Never-married","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +61,"Private",173924,"9th",5,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"Puerto-Rico",">50K" +23,"State-gov",142547,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",119704,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",207392,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,12,"United-States","<=50K" +31,"Private",147215,"12th",8,"Divorced","Other-service","Unmarried","White","Female",0,0,21,"United-States","<=50K" +31,"Private",101562,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,55,"United-States","<=50K" +63,"Private",216413,"Bachelors",13,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +43,"State-gov",52849,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",304710,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,10,"Vietnam","<=50K" +17,"Private",265657,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +35,"Private",360814,"9th",5,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +32,"Private",53260,"HS-grad",9,"Divorced","Other-service","Unmarried","Other","Female",0,0,28,"United-States","<=50K" +25,"Private",233777,"HS-grad",9,"Never-married","Transport-moving","Other-relative","White","Male",0,0,40,"?","<=50K" +26,"Local-gov",197530,"Masters",14,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",340940,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",88432,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"Private",183810,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +90,"Private",51744,"Masters",14,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,50,"United-States",">50K" +35,"Private",175614,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States",">50K" +31,"Self-emp-not-inc",235237,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,60,"United-States",">50K" +60,"Private",227266,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,33,"United-States","<=50K" +71,"Local-gov",337064,"Masters",14,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",141003,"Assoc-voc",11,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +50,"Local-gov",117791,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",172846,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +23,"Private",73514,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +74,"Private",211075,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States","<=50K" +59,"Private",43221,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States",">50K" +45,"Private",26781,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +63,"Self-emp-not-inc",271550,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,20,"United-States","<=50K" +39,"Private",250157,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,63,"United-States","<=50K" +33,"State-gov",913447,"Some-college",10,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +32,"Private",153078,"Bachelors",13,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +39,"Private",231491,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +29,"State-gov",95423,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,36,"United-States","<=50K" +22,"Private",234663,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",328669,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,42,"United-States","<=50K" +51,"Private",143741,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States",">50K" +56,"State-gov",81954,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",261375,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +52,"Private",310045,"9th",5,"Married-spouse-absent","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Female",0,0,30,"China","<=50K" +39,"Private",316211,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +37,"Private",61299,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +33,"Private",113364,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"?",476573,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,4,"United-States","<=50K" +46,"Private",267107,"5th-6th",3,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,45,"Italy","<=50K" +35,"Private",48123,"12th",8,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,50,"United-States","<=50K" +33,"Private",214635,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,50,"United-States","<=50K" +48,"Private",115585,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",194141,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,50,"United-States","<=50K" +18,"?",23233,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",89991,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,32,"United-States","<=50K" +35,"Private",101709,"HS-grad",9,"Never-married","Transport-moving","Own-child","Asian-Pac-Islander","Male",0,0,60,"United-States","<=50K" +19,"Private",237455,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,25,"United-States","<=50K" +21,"Private",206492,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"?","<=50K" +56,"Private",28729,"11th",7,"Separated","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",153475,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,16,"El-Salvador","<=50K" +45,"Private",275517,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",128002,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,45,"United-States","<=50K" +44,"Private",175485,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,12,"United-States","<=50K" +55,"Private",189664,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",209808,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",176992,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",154669,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,55,"United-States","<=50K" +25,"Private",191271,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"Private",375482,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",169182,"10th",6,"Married-spouse-absent","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"Columbia","<=50K" +49,"Self-emp-inc",30751,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +22,"Private",145477,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +31,"Private",91964,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-inc",49249,"Some-college",10,"Divorced","Other-service","Unmarried","White","Male",0,0,80,"United-States","<=50K" +19,"Private",218956,"HS-grad",9,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",241306,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +60,"?",251572,"HS-grad",9,"Widowed","?","Not-in-family","White","Male",0,0,35,"Poland","<=50K" +23,"Private",319842,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +54,"Local-gov",182388,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"United-States","<=50K" +23,"Private",205939,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,38,"United-States","<=50K" +21,"Private",203914,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,10,"United-States","<=50K" +19,"State-gov",156294,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,25,"United-States","<=50K" +51,"Private",254211,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States",">50K" +19,"Self-emp-not-inc",30800,"10th",6,"Married-spouse-absent","Adm-clerical","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +22,"Private",131230,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",61850,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Private",227800,"7th-8th",4,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,32,"United-States","<=50K" +35,"Private",133454,"10th",6,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +38,"Private",104094,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",105422,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Private",142182,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +41,"Private",336643,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,80,"United-States","<=50K" +62,"Self-emp-inc",200577,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +27,"Private",208703,"HS-grad",9,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"Japan","<=50K" +55,"?",193895,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,40,"England","<=50K" +26,"Private",288592,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",266439,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +53,"Federal-gov",276868,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",131435,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Private",175127,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,35,"United-States","<=50K" +25,"Private",277444,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +60,"Private",63296,"Masters",14,"Divorced","Prof-specialty","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +28,"Private",96337,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",221955,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"Mexico","<=50K" +29,"Private",632593,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",205970,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Female",0,0,25,"United-States","<=50K" +25,"Private",139730,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,80,"United-States",">50K" +18,"Private",201901,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,10,"United-States","<=50K" +32,"State-gov",230224,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"United-States","<=50K" +27,"Private",113464,"1st-4th",2,"Never-married","Other-service","Own-child","Other","Male",0,0,35,"Dominican-Republic","<=50K" +48,"Private",94461,"HS-grad",9,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +20,"Private",271379,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +55,"Private",231738,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"England","<=50K" +33,"Local-gov",198183,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States",">50K" +21,"State-gov",140764,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,12,"United-States","<=50K" +43,"Self-emp-not-inc",183479,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +35,"Private",165767,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Local-gov",139364,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +19,"Private",227491,"HS-grad",9,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +25,"Private",222254,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +44,"Private",193494,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,72,"United-States",">50K" +27,"Private",29261,"Assoc-acdm",12,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +39,"Private",174368,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +69,"Private",108196,"10th",6,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +34,"Private",110622,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +20,"?",201680,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,35,"United-States","<=50K" +37,"Private",130277,"5th-6th",3,"Separated","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Local-gov",98130,"Bachelors",13,"Divorced","Prof-specialty","Own-child","White","Female",0,0,39,"United-States","<=50K" +62,"?",235521,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,48,"United-States","<=50K" +34,"State-gov",595000,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,40,"United-States",">50K" +31,"Self-emp-not-inc",349148,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +26,"Private",164583,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +39,"Private",340091,"Some-college",10,"Separated","Other-service","Unmarried","White","Female",0,0,75,"United-States","<=50K" +25,"Private",49092,"Bachelors",13,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"Local-gov",186884,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,30,"United-States","<=50K" +44,"State-gov",167265,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +21,"Self-emp-inc",265116,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",128378,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,55,"?","<=50K" +33,"Private",158416,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Self-emp-inc",169878,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +44,"Private",296728,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Local-gov",342458,"Assoc-acdm",12,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +21,"Local-gov",38771,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",269300,"Bachelors",13,"Never-married","Other-service","Not-in-family","Black","Female",0,0,60,"United-States","<=50K" +57,"?",199114,"10th",6,"Separated","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +51,"Local-gov",33863,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +29,"Private",132874,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Local-gov",277024,"HS-grad",9,"Separated","Protective-serv","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",112160,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",703067,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +58,"Private",127264,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"Self-emp-inc",257200,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",57206,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +37,"Private",201319,"Some-college",10,"Separated","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",114079,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States","<=50K" +45,"Private",230979,"Some-college",10,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",292472,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Cambodia",">50K" +64,"?",286732,"7th-8th",4,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Local-gov",134444,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,72,"United-States","<=50K" +30,"Private",172403,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +46,"Private",191357,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"?",279288,"10th",6,"Never-married","?","Other-relative","White","Female",0,0,30,"United-States","<=50K" +60,"Private",389254,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",303867,"HS-grad",9,"Separated","Transport-moving","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +39,"Private",111499,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",61580,"Some-college",10,"Divorced","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +44,"Private",231348,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",164748,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",205337,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +58,"Self-emp-not-inc",54566,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +45,"Private",34419,"Bachelors",13,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +59,"Private",116442,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",290740,"Assoc-acdm",12,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +27,"Private",255582,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",112517,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,20,"United-States",">50K" +44,"Private",169397,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",172664,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States",">50K" +27,"Private",329005,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",123253,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +55,"Private",81865,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",173314,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","Other","Male",0,0,60,"United-States","<=50K" +31,"Private",34572,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Private",149184,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +78,"?",363134,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,1,"United-States","<=50K" +28,"Private",308709,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +29,"Private",168479,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +66,"Private",142501,"HS-grad",9,"Never-married","Other-service","Other-relative","Black","Female",0,0,3,"United-States","<=50K" +60,"Private",338345,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +31,"Private",177675,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",200997,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,45,"United-States","<=50K" +29,"Private",176683,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +44,"Private",376072,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +34,"Local-gov",177675,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +23,"Private",320451,"Bachelors",13,"Never-married","Exec-managerial","Own-child","Asian-Pac-Islander","Male",0,0,24,"United-States","<=50K" +23,"Private",38151,"11th",7,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"Philippines","<=50K" +55,"Local-gov",123382,"Assoc-voc",11,"Separated","Prof-specialty","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +39,"Self-emp-inc",151029,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",484475,"11th",7,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +57,"Private",329792,"7th-8th",4,"Divorced","Transport-moving","Unmarried","White","Male",0,0,75,"United-States","<=50K" +35,"Private",148903,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Local-gov",301614,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,48,"United-States",">50K" +47,"Private",176319,"HS-grad",9,"Married-civ-spouse","Sales","Own-child","White","Female",0,0,38,"United-States",">50K" +53,"State-gov",53197,"Doctorate",16,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",291407,"Some-college",10,"Never-married","Sales","Own-child","Black","Male",0,0,25,"United-States","<=50K" +35,"Private",204527,"Masters",14,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States",">50K" +44,"Private",476391,"Some-college",10,"Divorced","Farming-fishing","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",224964,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +26,"Private",306225,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Poland","<=50K" +23,"Private",292023,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +32,"Private",94041,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,25,"Ireland","<=50K" +49,"Self-emp-inc",187563,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Private",749105,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,36,"United-States","<=50K" +41,"?",230020,"5th-6th",3,"Married-civ-spouse","?","Husband","Other","Male",0,0,40,"United-States","<=50K" +21,"Private",216070,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","Amer-Indian-Eskimo","Female",0,0,46,"United-States",">50K" +54,"Self-emp-not-inc",105010,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",198203,"Some-college",10,"Married-spouse-absent","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +35,"Local-gov",215419,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",120460,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States",">50K" +46,"Private",199316,"Some-college",10,"Married-civ-spouse","Craft-repair","Other-relative","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +46,"Private",146919,"HS-grad",9,"Separated","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Private",174744,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"?",189564,"Masters",14,"Married-civ-spouse","?","Wife","White","Female",0,0,1,"United-States","<=50K" +21,"Private",249957,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",146574,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +47,"State-gov",156417,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,20,"United-States","<=50K" +42,"Private",236110,"5th-6th",3,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"Puerto-Rico","<=50K" +19,"Private",63363,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +25,"Private",190107,"Bachelors",13,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",126569,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,60,"United-States",">50K" +35,"Private",176756,"12th",8,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +40,"Private",115161,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States","<=50K" +57,"Self-emp-not-inc",138892,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,15,"United-States","<=50K" +38,"Private",256864,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States",">50K" +48,"Private",265083,"10th",6,"Divorced","Sales","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +34,"Private",249948,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,34,"United-States","<=50K" +46,"Federal-gov",31141,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",164190,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,38,"?","<=50K" +45,"State-gov",67544,"Masters",14,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +32,"Self-emp-not-inc",174789,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +35,"Private",199753,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,48,"United-States","<=50K" +56,"?",188166,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",96586,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",189590,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",140590,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Male",0,0,33,"United-States","<=50K" +35,"Private",255702,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,27,"United-States","<=50K" +33,"Private",260782,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,41,"United-States",">50K" +37,"State-gov",151322,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"Private",192869,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",86958,"9th",5,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +53,"Local-gov",228723,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","Other","Male",0,0,40,"?",">50K" +33,"Private",192644,"HS-grad",9,"Separated","Handlers-cleaners","Unmarried","White","Male",0,0,35,"Puerto-Rico","<=50K" +72,"Private",284080,"1st-4th",2,"Divorced","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +54,"Private",43269,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +30,"Private",190040,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Private",306108,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +30,"Private",381645,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +32,"Private",216361,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,16,"United-States","<=50K" +30,"Private",213722,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +35,"Private",112271,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",208277,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Female",0,0,44,"United-States",">50K" +38,"State-gov",352628,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",129620,"10th",6,"Never-married","Other-service","Other-relative","White","Female",0,0,30,"United-States","<=50K" +32,"Private",249550,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +49,"Private",178749,"Masters",14,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +76,"?",173542,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,10,"United-States","<=50K" +60,"Private",167670,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States","<=50K" +60,"Private",81578,"9th",5,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",160662,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,80,"United-States",">50K" +41,"Private",163322,"Bachelors",13,"Divorced","Tech-support","Not-in-family","White","Female",0,0,30,"?","<=50K" +24,"Private",152189,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",78410,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +32,"Private",131379,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Private",166929,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Private",380357,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",79190,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +40,"Private",342164,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,37,"United-States","<=50K" +44,"Private",182616,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +63,"Private",339473,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +51,"Private",300816,"Bachelors",13,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,20,"United-States","<=50K" +51,"Private",240988,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +23,"Private",149224,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",168216,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +39,"Private",305597,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Self-emp-not-inc",188798,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",240170,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"Germany","<=50K" +31,"Private",459465,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +44,"Local-gov",162506,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States","<=50K" +43,"Self-emp-not-inc",145441,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States",">50K" +37,"Federal-gov",129573,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,72,"?",">50K" +41,"Private",27444,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,46,"United-States",">50K" +43,"Private",195258,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +47,"State-gov",55272,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",27802,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"State-gov",165289,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",274657,"5th-6th",3,"Never-married","Other-service","Not-in-family","White","Male",0,0,50,"Guatemala","<=50K" +24,"Private",317175,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +39,"Self-emp-inc",163237,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,65,"United-States","<=50K" +37,"Private",170408,"Assoc-voc",11,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +28,"?",55950,"Bachelors",13,"Never-married","?","Own-child","Black","Female",0,0,40,"Germany","<=50K" +40,"Private",76625,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +27,"Private",366066,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",349368,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +21,"Private",286824,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,12,"United-States","<=50K" +32,"Private",373263,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +20,"Private",161978,"HS-grad",9,"Separated","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Local-gov",109089,"Prof-school",15,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",110151,"Assoc-voc",11,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +26,"Private",34110,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +47,"Self-emp-not-inc",118506,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Own-child","White","Male",0,0,60,"United-States","<=50K" +22,"Private",117789,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,10,"United-States","<=50K" +34,"Self-emp-not-inc",353881,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +49,"Private",200471,"1st-4th",2,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Portugal","<=50K" +20,"Private",258517,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +28,"Private",190367,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Private",174704,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",179413,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",329530,"9th",5,"Never-married","Priv-house-serv","Own-child","White","Male",0,0,40,"Mexico","<=50K" +31,"Private",273818,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,55,"Mexico","<=50K" +46,"Private",256522,"1st-4th",2,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"Puerto-Rico","<=50K" +42,"Private",196001,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",282660,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",72630,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +27,"Private",50295,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States","<=50K" +20,"Private",203240,"9th",5,"Never-married","Sales","Own-child","White","Female",0,0,32,"United-States","<=50K" +41,"Private",202168,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +61,"Private",176839,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",176140,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States",">50K" +33,"Private",292465,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"?",161285,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,25,"United-States","<=50K" +48,"Private",355320,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"Canada",">50K" +56,"Private",182460,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Self-emp-not-inc",102058,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",165804,"Some-college",10,"Never-married","Adm-clerical","Own-child","Other","Female",0,0,40,"United-States","<=50K" +46,"Private",318259,"Assoc-voc",11,"Divorced","Tech-support","Other-relative","White","Female",0,0,36,"United-States","<=50K" +21,"Private",117606,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",170718,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",413297,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",190457,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +62,"?",97231,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,1,"United-States","<=50K" +50,"Private",123429,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Federal-gov",420282,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +48,"Private",498325,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Private",248533,"Some-college",10,"Never-married","Sales","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +46,"Private",137354,"Masters",14,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +42,"Private",272910,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +52,"Self-emp-inc",206054,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Local-gov",92141,"Assoc-acdm",12,"Widowed","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +37,"Private",163199,"Some-college",10,"Divorced","Tech-support","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +34,"Private",195860,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",120029,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,20,"United-States","<=50K" +33,"Private",221762,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +41,"Private",342164,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +21,"Private",176356,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +23,"Private",133239,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Federal-gov",169101,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +33,"Private",159442,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +24,"Private",174461,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,45,"United-States","<=50K" +43,"Private",361280,"10th",6,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,42,"China","<=50K" +52,"State-gov",447579,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"England","<=50K" +27,"?",308995,"Some-college",10,"Divorced","?","Own-child","Black","Female",0,0,40,"United-States","<=50K" +61,"Private",248448,"7th-8th",4,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",161141,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",212465,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Local-gov",233865,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Private",163052,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",348690,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Federal-gov",34845,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"Germany",">50K" +22,"Private",206861,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-inc",349230,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +20,"Private",130840,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,20,"United-States","<=50K" +19,"Private",415354,"10th",6,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",132191,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",202466,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,45,"United-States","<=50K" +27,"?",224421,"Some-college",10,"Divorced","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Self-emp-not-inc",236804,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,35,"United-States","<=50K" +20,"Private",107658,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +47,"Private",102771,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +17,"Private",221403,"12th",8,"Never-married","Other-service","Own-child","Black","Male",0,0,18,"United-States","<=50K" +76,"?",211574,"10th",6,"Married-civ-spouse","?","Husband","White","Male",0,0,1,"United-States","<=50K" +39,"Private",52645,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",276310,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +31,"Private",134613,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,43,"United-States","<=50K" +44,"Private",215479,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","Black","Male",0,0,20,"Haiti","<=50K" +53,"Private",266529,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",265807,"Some-college",10,"Separated","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +45,"Self-emp-not-inc",67716,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +34,"Private",178951,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +35,"Private",241126,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",176544,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +45,"Private",169180,"Some-college",10,"Widowed","Other-service","Unmarried","White","Female",0,0,45,"United-States","<=50K" +37,"Self-emp-not-inc",282461,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +53,"Private",157069,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Self-emp-not-inc",414991,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,70,"?","<=50K" +65,"Self-emp-inc",338316,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",59612,"10th",6,"Divorced","Farming-fishing","Unmarried","White","Male",0,0,70,"United-States","<=50K" +24,"Private",220426,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Private",115912,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",27032,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,12,"United-States","<=50K" +19,"Private",170720,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +60,"Private",183162,"HS-grad",9,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",192360,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +78,"?",165694,"Masters",14,"Widowed","?","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +26,"Private",128553,"Some-college",10,"Never-married","Exec-managerial","Own-child","Black","Female",0,0,40,"United-States","<=50K" +58,"Private",209423,"1st-4th",2,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,38,"Cuba","<=50K" +37,"Self-emp-not-inc",121510,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,55,"United-States","<=50K" +41,"Private",93793,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +30,"Private",133602,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",391329,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +48,"Private",96359,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"Greece",">50K" +22,"Private",203894,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +50,"Private",196193,"Masters",14,"Married-spouse-absent","Prof-specialty","Other-relative","White","Male",0,0,60,"?","<=50K" +25,"Private",195994,"1st-4th",2,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,40,"Guatemala","<=50K" +18,"Private",50879,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,6,"United-States","<=50K" +21,"Private",186849,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",201127,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +33,"Private",110998,"HS-grad",9,"Never-married","Other-service","Other-relative","Amer-Indian-Eskimo","Female",0,0,36,"United-States","<=50K" +67,"Self-emp-not-inc",173935,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,8,"United-States",">50K" +18,"Private",110230,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,11,"United-States","<=50K" +36,"Private",287658,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",224954,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,25,"United-States","<=50K" +25,"?",394820,"Some-college",10,"Separated","?","Unmarried","White","Female",0,0,20,"United-States","<=50K" +40,"Private",37618,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?","<=50K" +73,"Self-emp-not-inc",29306,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",420749,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",482732,"10th",6,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",206215,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Private",101364,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +66,"Self-emp-inc",185369,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +66,"Private",216856,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +64,"Private",256019,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +24,"Private",190293,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",25932,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +25,"Private",176729,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +33,"Private",166961,"11th",7,"Separated","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +50,"Private",86373,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +51,"Private",320513,"7th-8th",4,"Married-spouse-absent","Craft-repair","Not-in-family","Black","Male",0,0,50,"Dominican-Republic","<=50K" +34,"State-gov",190290,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +41,"Local-gov",111891,"7th-8th",4,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",45796,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",323155,"1st-4th",2,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,85,"Mexico","<=50K" +28,"Private",65389,"HS-grad",9,"Never-married","Other-service","Not-in-family","Amer-Indian-Eskimo","Male",0,0,30,"United-States","<=50K" +19,"Private",414871,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",161607,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +62,"Private",224953,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",231818,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Greece","<=50K" +43,"Self-emp-inc",133060,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",35032,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"State-gov",304212,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +64,"Local-gov",50442,"9th",5,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,40,"United-States","<=50K" +39,"Private",146091,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,20,"United-States",">50K" +26,"Private",267431,"Bachelors",13,"Never-married","Sales","Own-child","Black","Female",0,0,20,"United-States","<=50K" +19,"Private",121240,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +21,"Private",192572,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,45,"United-States","<=50K" +32,"Private",211028,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",202203,"Bachelors",13,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,50,"United-States","<=50K" +20,"Private",159297,"Some-college",10,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,15,"United-States","<=50K" +19,"Private",310158,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,30,"United-States","<=50K" +33,"Federal-gov",193246,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,42,"United-States",">50K" +23,"Private",200089,"Some-college",10,"Married-civ-spouse","Craft-repair","Other-relative","White","Male",0,0,40,"El-Salvador","<=50K" +29,"Private",38353,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +42,"Private",76280,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",243665,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +63,"Private",68872,"HS-grad",9,"Married-civ-spouse","Transport-moving","Wife","Asian-Pac-Islander","Female",0,0,20,"United-States","<=50K" +34,"Private",103596,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",88055,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,24,"United-States","<=50K" +48,"Private",186203,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Private",257910,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +27,"Private",200227,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +32,"Private",227669,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +22,"Private",117210,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,25,"Greece","<=50K" +25,"Private",76144,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +18,"Private",98667,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +24,"Local-gov",155818,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,44,"United-States","<=50K" +29,"Private",283760,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +73,"?",281907,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,3,"United-States","<=50K" +39,"Private",186183,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Self-emp-inc",202153,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",365683,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States",">50K" +22,"Private",187538,"10th",6,"Separated","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"?",209432,"HS-grad",9,"Separated","?","Unmarried","White","Female",0,0,20,"United-States","<=50K" +33,"Private",126950,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +42,"Private",110028,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",104660,"Bachelors",13,"Separated","Prof-specialty","Unmarried","White","Male",0,0,45,"United-States","<=50K" +57,"Self-emp-not-inc",437281,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,38,"United-States",">50K" +21,"?",134746,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +42,"Self-emp-not-inc",120539,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +39,"Private",25803,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +41,"Private",63596,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,32,"United-States",">50K" +20,"Local-gov",325493,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +47,"Private",211239,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",206686,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",427965,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +71,"Private",163385,"Some-college",10,"Widowed","Sales","Not-in-family","White","Male",0,0,35,"United-States",">50K" +52,"Private",124993,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,55,"United-States","<=50K" +36,"Private",107410,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",152373,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,48,"United-States",">50K" +37,"Private",161226,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,30,"United-States",">50K" +26,"Private",213799,"10th",6,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",204461,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +35,"Private",377798,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +20,"Private",116375,"9th",5,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",258752,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +39,"Private",327435,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,36,"United-States",">50K" +24,"Private",301199,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,20,"United-States","<=50K" +24,"Private",186221,"11th",7,"Divorced","Sales","Unmarried","White","Female",0,0,35,"United-States","<=50K" +23,"Private",203924,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +27,"Private",192236,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +25,"Private",152035,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",201454,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",156580,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,37,"United-States",">50K" +51,"Private",115851,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Private",359292,"1st-4th",2,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +29,"Private",83003,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +18,"Private",78817,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +24,"Private",200967,"HS-grad",9,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,36,"United-States","<=50K" +38,"State-gov",107164,"Some-college",10,"Separated","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",189674,"HS-grad",9,"Never-married","Priv-house-serv","Unmarried","Black","Female",0,0,28,"?","<=50K" +34,"Self-emp-not-inc",90614,"HS-grad",9,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +45,"Self-emp-not-inc",242552,"12th",8,"Divorced","Craft-repair","Other-relative","Black","Male",0,0,35,"United-States","<=50K" +21,"Private",90935,"Assoc-voc",11,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",162604,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +45,"Private",205424,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +53,"Private",97411,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,40,"Laos","<=50K" +42,"Private",184857,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,16,"United-States","<=50K" +32,"Private",165226,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Private",115784,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Private",368476,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,24,"Mexico","<=50K" +28,"Private",53063,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +29,"?",134566,"Doctorate",16,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States",">50K" +32,"Private",153471,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +38,"Private",180303,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,50,"Japan",">50K" +44,"Local-gov",236321,"HS-grad",9,"Divorced","Transport-moving","Own-child","White","Male",0,0,25,"United-States","<=50K" +19,"Private",141868,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"?",367655,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",203518,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +58,"Private",119558,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +56,"Private",108276,"Bachelors",13,"Widowed","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",385452,"10th",6,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",162003,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",349028,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",45114,"Bachelors",13,"Never-married","Sales","Own-child","Black","Female",0,0,40,"United-States","<=50K" +44,"Private",112797,"9th",5,"Divorced","Other-service","Own-child","White","Female",0,0,50,"United-States","<=50K" +28,"Private",183639,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +35,"Private",177121,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +38,"Private",239755,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",150361,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"Private",293091,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,60,"United-States","<=50K" +24,"Private",200089,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"Mexico",">50K" +40,"Private",91836,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +23,"Private",324960,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +79,"Local-gov",84616,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,7,"United-States","<=50K" +44,"Private",252930,"10th",6,"Divorced","Adm-clerical","Unmarried","Other","Female",0,0,42,"United-States","<=50K" +30,"Private",154843,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",182567,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"?",">50K" +33,"Private",93206,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +50,"Private",100109,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,45,"United-States",">50K" +41,"Private",121287,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",189916,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,30,"United-States",">50K" +28,"Private",39232,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +31,"Self-emp-inc",133861,"Assoc-voc",11,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",505980,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",140752,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",549349,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",179008,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"Self-emp-not-inc",190554,"10th",6,"Divorced","Exec-managerial","Own-child","White","Male",0,0,60,"United-States",">50K" +47,"Private",80924,"Some-college",10,"Widowed","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +51,"Local-gov",319054,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,60,"United-States","<=50K" +34,"Private",297094,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +52,"Private",170562,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +29,"Private",240738,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",297544,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Local-gov",169905,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",149637,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",182526,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",158315,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +61,"Self-emp-inc",227232,"Bachelors",13,"Separated","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +41,"Private",286970,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Local-gov",223529,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Male",0,0,43,"United-States","<=50K" +40,"Private",170214,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Self-emp-not-inc",224361,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,75,"United-States","<=50K" +43,"Private",124919,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,60,"Japan","<=50K" +55,"?",103654,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +25,"Private",306352,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"Mexico","<=50K" +26,"Self-emp-not-inc",227858,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +43,"Self-emp-inc",150533,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,68,"United-States",">50K" +25,"Private",144478,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"Poland","<=50K" +22,"Private",254547,"Some-college",10,"Never-married","Adm-clerical","Other-relative","Black","Female",0,0,30,"Jamaica","<=50K" +52,"Self-emp-not-inc",313243,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +42,"Private",125461,"Bachelors",13,"Never-married","Sales","Unmarried","White","Male",0,0,40,"United-States","<=50K" +21,"Private",306967,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",192976,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +56,"?",131608,"HS-grad",9,"Divorced","?","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +33,"Federal-gov",339388,"Assoc-acdm",12,"Divorced","Other-service","Unmarried","White","Male",0,0,40,"United-States","<=50K" +22,"Private",203240,"10th",6,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",83827,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +45,"Self-emp-inc",160440,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +42,"Private",108502,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +37,"Private",410913,"HS-grad",9,"Married-spouse-absent","Farming-fishing","Unmarried","Other","Male",0,0,40,"Mexico","<=50K" +56,"Private",193818,"9th",5,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"?",163582,"10th",6,"Divorced","?","Unmarried","White","Female",0,0,16,"?","<=50K" +40,"Private",103789,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +31,"Private",34572,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +26,"Private",43408,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"State-gov",105787,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Self-emp-inc",90693,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +45,"Self-emp-not-inc",285575,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +22,"Private",496025,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +33,"Private",382764,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",259284,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +48,"Self-emp-not-inc",185385,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,98,"United-States","<=50K" +57,"Self-emp-not-inc",286836,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,8,"United-States","<=50K" +47,"Private",139145,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +58,"Local-gov",44246,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",169611,"11th",7,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +52,"Private",133403,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +29,"Private",187327,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",180032,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",46561,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +23,"Private",86065,"12th",8,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +46,"Self-emp-not-inc",256014,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +30,"Private",188403,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",60485,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +32,"Private",271276,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,80,"United-States",">50K" +56,"Private",229525,"9th",5,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +33,"Private",34574,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,43,"United-States","<=50K" +19,"State-gov",112432,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,10,"United-States","<=50K" +20,"Private",105312,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,18,"United-States","<=50K" +34,"Private",221396,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",304872,"9th",5,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",319733,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",176012,"9th",5,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,23,"United-States","<=50K" +31,"Private",213750,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +30,"Private",248384,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",351187,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Male",0,0,40,"United-States","<=50K" +59,"Private",50223,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",117477,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,36,"United-States","<=50K" +40,"Private",194360,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",118108,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +18,"Self-emp-inc",38307,"11th",7,"Never-married","Farming-fishing","Own-child","White","Male",0,0,30,"United-States","<=50K" +41,"Private",116391,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",210496,"10th",6,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",168475,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",174386,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,24,"United-States","<=50K" +39,"Private",166744,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,38,"United-States","<=50K" +19,"Private",375114,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",373469,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",339667,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,41,"United-States","<=50K" +39,"Private",91711,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",82049,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",236242,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +57,"Self-emp-inc",140319,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States","<=50K" +33,"Local-gov",34080,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Private",204816,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +60,"Private",187124,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",72310,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +58,"Private",175127,"12th",8,"Married-civ-spouse","Transport-moving","Other-relative","White","Male",0,0,40,"United-States","<=50K" +18,"Private",71792,"HS-grad",9,"Never-married","Sales","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +56,"Private",87584,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-inc",136878,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +38,"Private",110607,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +58,"Private",109015,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",235071,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,50,"United-States","<=50K" +63,"Private",88653,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?","<=50K" +51,"Private",332243,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +22,"?",291547,"5th-6th",3,"Married-civ-spouse","?","Wife","Other","Female",0,0,40,"Mexico","<=50K" +44,"Private",45093,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +46,"Federal-gov",161337,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +64,"State-gov",211222,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",295117,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"England",">50K" +31,"Private",206541,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",238415,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +21,"Private",29810,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +30,"Private",108023,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",114324,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +59,"Local-gov",197290,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Local-gov",191177,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,20,"United-States",">50K" +57,"Private",562558,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",79531,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +53,"Self-emp-inc",157881,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +58,"Self-emp-not-inc",204816,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +19,"Private",185695,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +39,"Self-emp-inc",167482,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Self-emp-inc",83748,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","Asian-Pac-Islander","Female",0,0,70,"South","<=50K" +27,"Private",39232,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Local-gov",236827,"9th",5,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",154410,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",135308,"Bachelors",13,"Never-married","Sales","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",204042,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +20,"Private",308239,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +55,"Private",183884,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +39,"Private",98948,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",141642,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",162623,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Self-emp-inc",186934,"Bachelors",13,"Married-spouse-absent","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",179512,"HS-grad",9,"Separated","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States","<=50K" +25,"Private",391192,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,24,"United-States","<=50K" +31,"Private",87054,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +51,"Private",30008,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +24,"Private",113466,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +70,"Private",642830,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +23,"Private",182117,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +61,"Private",162432,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",242184,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +56,"Private",435022,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +20,"Private",170800,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +30,"Private",268575,"HS-grad",9,"Never-married","Craft-repair","Unmarried","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +27,"Private",269354,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,25,"?","<=50K" +40,"Private",224232,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +60,"?",153072,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,5,"United-States","<=50K" +58,"Private",177368,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +71,"Self-emp-not-inc",163293,"Prof-school",15,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,2,"United-States","<=50K" +50,"Private",178530,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +29,"Local-gov",183523,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"Iran","<=50K" +60,"State-gov",27037,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States",">50K" +33,"Private",176711,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +43,"Private",163215,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"?",">50K" +33,"Private",394727,"10th",6,"Never-married","Handlers-cleaners","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +33,"Private",195488,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,52,"United-States","<=50K" +32,"State-gov",443546,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,45,"United-States","<=50K" +21,"Private",121023,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,9,"United-States","<=50K" +38,"Private",51838,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +38,"Private",258888,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States",">50K" +39,"State-gov",189385,"Some-college",10,"Separated","Exec-managerial","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +17,"Private",198146,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +21,"Private",337766,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",210525,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,20,"United-States",">50K" +42,"Private",185602,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +36,"Private",173804,"11th",7,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",251243,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +37,"Self-emp-not-inc",415847,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",119793,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",181705,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",182360,"HS-grad",9,"Separated","Prof-specialty","Unmarried","Other","Female",0,0,60,"Puerto-Rico","<=50K" +49,"Private",61885,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",146520,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",323790,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",146268,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Local-gov",292217,"HS-grad",9,"Divorced","Protective-serv","Unmarried","White","Male",0,0,40,"United-States","<=50K" +24,"Private",88126,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",143046,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",401623,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","Black","Male",0,0,40,"Jamaica",">50K" +84,"Self-emp-not-inc",155057,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,20,"United-States","<=50K" +23,"Private",260254,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",152292,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +30,"Self-emp-not-inc",523095,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +46,"Private",175262,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +34,"Private",316470,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",163815,"Masters",14,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +27,"Private",72208,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,40,"United-States","<=50K" +52,"Local-gov",74784,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +25,"Self-emp-not-inc",266668,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Private",347519,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +24,"Private",336088,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","Amer-Indian-Eskimo","Female",0,0,50,"United-States","<=50K" +36,"Private",190350,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",204052,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +66,"?",31362,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +47,"Private",26994,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +55,"Self-emp-not-inc",189933,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",101283,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +48,"Private",113598,"Some-college",10,"Separated","Adm-clerical","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +21,"Private",188793,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Other","Male",0,0,35,"United-States","<=50K" +33,"Private",109996,"Assoc-acdm",12,"Married-spouse-absent","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Private",195681,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,48,"?","<=50K" +47,"Private",436770,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",84253,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,24,"United-States","<=50K" +44,"Self-emp-inc",383493,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +23,"Private",216867,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,37,"Mexico","<=50K" +18,"Private",401051,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +56,"Private",83196,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Private",325596,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,35,"United-States","<=50K" +43,"Private",187322,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",193949,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,60,"United-States","<=50K" +26,"Private",133373,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,42,"United-States","<=50K" +42,"Private",113324,"HS-grad",9,"Widowed","Sales","Unmarried","White","Male",0,0,40,"United-States","<=50K" +23,"Private",178818,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Self-emp-not-inc",152810,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",436493,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +27,"Private",704108,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +24,"Local-gov",150084,"Some-college",10,"Separated","Protective-serv","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +42,"Private",341204,"HS-grad",9,"Divorced","Craft-repair","Other-relative","White","Female",0,0,40,"United-States","<=50K" +41,"Private",187336,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",204209,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,10,"United-States","<=50K" +42,"Self-emp-not-inc",206066,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,65,"United-States","<=50K" +38,"Private",63509,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +63,"Self-emp-not-inc",391121,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +31,"Private",56026,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Self-emp-not-inc",60981,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,4,"United-States","<=50K" +21,"Private",228255,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +24,"Private",86745,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +55,"Private",234327,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",137814,"Some-college",10,"Divorced","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +23,"Private",167692,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +35,"Private",245090,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +51,"Self-emp-not-inc",256963,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +19,"Private",160033,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Female",0,0,30,"United-States","<=50K" +38,"Local-gov",289430,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +70,"Self-emp-not-inc",172370,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,25,"United-States","<=50K" +53,"Private",320510,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"Private",171355,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",65027,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,43,"United-States","<=50K" +18,"Private",215190,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +41,"?",149385,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +19,"?",169324,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,10,"United-States","<=50K" +24,"Private",138938,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",557082,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +32,"Private",273287,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,40,"Jamaica","<=50K" +35,"Private",317153,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",302859,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +37,"Private",333651,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +30,"Private",177596,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,36,"United-States","<=50K" +22,"Private",184779,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Local-gov",138358,"Some-college",10,"Separated","Other-service","Unmarried","Black","Female",0,0,28,"United-States","<=50K" +70,"Private",176285,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,23,"United-States","<=50K" +43,"Private",102180,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +77,"Self-emp-not-inc",209507,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",229741,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",324546,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,39,"United-States","<=50K" +22,"Private",250647,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,12,"United-States","<=50K" +33,"Private",477106,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",104329,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",224566,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +32,"Private",169841,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +41,"Private",42563,"Bachelors",13,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,25,"United-States",">50K" +37,"Private",31368,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",132755,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,15,"United-States","<=50K" +50,"Private",279129,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States",">50K" +31,"?",86143,"HS-grad",9,"Married-civ-spouse","?","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +54,"State-gov",44172,"HS-grad",9,"Separated","Exec-managerial","Unmarried","White","Female",0,0,38,"United-States","<=50K" +23,"State-gov",93076,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +40,"Private",146653,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,20,"United-States","<=50K" +38,"Private",189404,"HS-grad",9,"Married-spouse-absent","Other-service","Not-in-family","White","Male",0,0,35,"?","<=50K" +30,"Private",172304,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +20,"Private",116666,"Some-college",10,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,8,"India","<=50K" +43,"Self-emp-not-inc",64112,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Private",55718,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,25,"United-States","<=50K" +39,"Private",126675,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +48,"Private",102112,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +41,"Self-emp-not-inc",226505,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",211527,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +20,"Private",175069,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"Yugoslavia","<=50K" +25,"Private",25249,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"Private",73411,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",207185,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,35,"Puerto-Rico",">50K" +66,"Private",127139,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",41809,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +46,"Private",141483,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +42,"Local-gov",117227,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,45,"United-States","<=50K" +34,"Local-gov",167063,"HS-grad",9,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",253759,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","Black","Female",0,0,40,"United-States","<=50K" +42,"Private",183096,"Some-college",10,"Divorced","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Private",269654,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +70,"?",293076,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States","<=50K" +32,"Private",34104,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Federal-gov",80057,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Germany",">50K" +42,"Self-emp-inc",369781,"7th-8th",4,"Divorced","Craft-repair","Unmarried","White","Male",0,0,25,"United-States","<=50K" +21,"Private",223811,"Assoc-voc",11,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",163053,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",189461,"HS-grad",9,"Never-married","Sales","Other-relative","White","Male",0,0,55,"United-States","<=50K" +37,"Private",86310,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +19,"?",263224,"11th",7,"Never-married","?","Unmarried","White","Female",0,0,30,"United-States","<=50K" +44,"Federal-gov",280362,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",301031,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",74966,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,24,"United-States","<=50K" +36,"Private",254493,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States","<=50K" +49,"Self-emp-not-inc",204241,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +29,"Private",225024,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Local-gov",148222,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +75,"State-gov",113868,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,20,"United-States",">50K" +42,"Private",132633,"HS-grad",9,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,40,"?","<=50K" +37,"Private",44780,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Private",86373,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,25,"United-States","<=50K" +61,"Local-gov",176753,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,48,"United-States","<=50K" +50,"Local-gov",370733,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +59,"Private",216851,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",137951,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,30,"United-States","<=50K" +22,"Private",185279,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,16,"United-States","<=50K" +56,"Private",159724,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",103233,"Bachelors",13,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",63509,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"Private",174353,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",159724,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",179112,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Male",0,0,40,"?","<=50K" +46,"Private",364913,"11th",7,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +48,"Self-emp-inc",155664,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +61,"Private",230568,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States",">50K" +33,"Private",86492,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,87,"United-States","<=50K" +40,"Private",71305,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-inc",189933,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +35,"Private",38948,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Self-emp-inc",139127,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States","<=50K" +37,"Private",301568,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Private",197344,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,54,"United-States","<=50K" +44,"Self-emp-not-inc",315406,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,88,"United-States","<=50K" +41,"State-gov",47170,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","Amer-Indian-Eskimo","Female",0,0,48,"United-States",">50K" +37,"Private",196338,"9th",5,"Separated","Priv-house-serv","Unmarried","White","Female",0,0,16,"Mexico","<=50K" +34,"Private",269243,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +24,"Federal-gov",215115,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"?","<=50K" +20,"Private",117767,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",176101,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",138283,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Self-emp-not-inc",132320,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,45,"United-States","<=50K" +22,"Federal-gov",471452,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Male",0,0,8,"United-States","<=50K" +55,"Private",147653,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,73,"United-States","<=50K" +20,"Private",49179,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +26,"Private",174921,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Self-emp-inc",95997,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,70,"United-States","<=50K" +40,"Private",247245,"9th",5,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",67072,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +54,"?",95329,"Some-college",10,"Divorced","?","Own-child","White","Male",0,0,50,"United-States","<=50K" +24,"Private",107882,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",241825,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,46,"United-States","<=50K" +18,"Private",79443,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,8,"United-States","<=50K" +49,"Self-emp-not-inc",233059,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +17,"Private",226980,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,17,"United-States","<=50K" +34,"Self-emp-not-inc",181087,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +37,"Private",305597,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +49,"Federal-gov",311671,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",83375,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",141657,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,35,"United-States",">50K" +44,"Private",228057,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,40,"Puerto-Rico","<=50K" +40,"Private",222848,"10th",6,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,32,"United-States","<=50K" +58,"Private",121111,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"Greece","<=50K" +44,"Private",298885,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",149909,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,25,"United-States",">50K" +39,"Private",387430,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,18,"United-States","<=50K" +19,"Private",121972,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +29,"State-gov",191355,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Federal-gov",112115,"Some-college",10,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +38,"?",104094,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,15,"United-States","<=50K" +54,"Private",199307,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Female",0,0,48,"United-States","<=50K" +40,"Private",205175,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +19,"Private",257750,"Some-college",10,"Never-married","Sales","Other-relative","White","Female",0,0,25,"United-States","<=50K" +33,"Private",342730,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,52,"United-States","<=50K" +80,"Private",249983,"7th-8th",4,"Widowed","Other-service","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +24,"Self-emp-not-inc",161508,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +28,"Private",338376,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Private",334308,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,30,"United-States",">50K" +21,"Private",133471,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",129177,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +19,"Private",178811,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +42,"Private",178537,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +60,"Self-emp-not-inc",235535,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States","<=50K" +20,"?",298155,"Some-college",10,"Never-married","?","Own-child","Black","Female",0,0,40,"United-States","<=50K" +51,"Private",145114,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",194096,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"State-gov",191779,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",159732,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +40,"Private",104719,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",163083,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",403552,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,32,"United-States","<=50K" +47,"Private",179313,"10th",6,"Divorced","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +26,"Private",51961,"12th",8,"Never-married","Sales","Other-relative","Black","Male",0,0,51,"United-States","<=50K" +59,"Private",426001,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",0,0,20,"Puerto-Rico","<=50K" +70,"Local-gov",176493,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,17,"United-States","<=50K" +26,"Private",124068,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +47,"Private",108510,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States","<=50K" +25,"Private",181528,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +46,"Private",169699,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +67,"Private",126849,"10th",6,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,20,"United-States","<=50K" +34,"Private",204470,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",117363,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +39,"Local-gov",106297,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Male",0,0,42,"United-States","<=50K" +54,"Self-emp-not-inc",108933,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +24,"Private",190143,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",246677,"HS-grad",9,"Separated","Prof-specialty","Unmarried","White","Female",0,0,38,"United-States","<=50K" +41,"Local-gov",210259,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",166304,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,33,"United-States","<=50K" +39,"Private",49308,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",192262,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,45,"United-States","<=50K" +37,"Self-emp-not-inc",48063,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +43,"Private",170214,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +54,"Federal-gov",51048,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Self-emp-inc",246562,"5th-6th",3,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Mexico",">50K" +57,"Local-gov",215175,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +28,"Private",114967,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",464536,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",451996,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",138852,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"State-gov",353012,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-inc",321822,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,75,"United-States",">50K" +50,"Self-emp-not-inc",324506,"HS-grad",9,"Widowed","Exec-managerial","Unmarried","Asian-Pac-Islander","Female",0,0,48,"South","<=50K" +36,"Private",162256,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Local-gov",356689,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",260199,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +36,"Private",103605,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",316211,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",308691,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +18,"Private",334427,"10th",6,"Never-married","Farming-fishing","Own-child","White","Male",0,0,36,"United-States","<=50K" +33,"Private",213226,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +23,"Private",33105,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +37,"Private",147638,"Bachelors",13,"Separated","Other-service","Unmarried","Asian-Pac-Islander","Female",0,0,36,"Philippines","<=50K" +25,"Private",315643,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States","<=50K" +51,"Federal-gov",106257,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",342768,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",108960,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +66,"?",168071,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States","<=50K" +32,"Private",136935,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,13,"United-States","<=50K" +37,"Self-emp-not-inc",188774,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,55,"United-States",">50K" +29,"Private",280344,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",202496,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,37,"United-States","<=50K" +61,"Self-emp-inc",134768,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",175686,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",194748,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Female",0,0,49,"United-States","<=50K" +49,"Private",61307,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",0,0,38,"United-States","<=50K" +34,"Private",325658,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"?",201844,"HS-grad",9,"Separated","?","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +20,"Private",505980,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",185336,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +26,"Private",126829,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +63,"Private",264600,"10th",6,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +36,"Private",82743,"Assoc-acdm",12,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,55,"Iran","<=50K" +63,"Self-emp-not-inc",125178,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",128487,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +40,"Private",321758,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",128220,"7th-8th",4,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +49,"Private",176814,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"Canada","<=50K" +23,"State-gov",156423,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"United-States","<=50K" +34,"?",157289,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",176972,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +33,"Private",91811,"HS-grad",9,"Separated","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"?",454614,"11th",7,"Never-married","?","Own-child","White","Female",0,0,8,"United-States","<=50K" +61,"Private",132972,"9th",5,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +53,"Private",157947,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Local-gov",177482,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,45,"United-States",">50K" +48,"Private",246891,"Some-college",10,"Widowed","Sales","Unmarried","White","Male",0,0,50,"United-States",">50K" +28,"State-gov",158834,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +30,"?",203834,"Bachelors",13,"Never-married","?","Not-in-family","Asian-Pac-Islander","Female",0,0,50,"Taiwan","<=50K" +29,"Private",110442,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"Private",240676,"Some-college",10,"Divorced","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"Private",192939,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",260696,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,55,"United-States","<=50K" +40,"Local-gov",55363,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",144949,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +31,"Local-gov",357954,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +21,"?",170038,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",190290,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Italy","<=50K" +26,"Private",167761,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Private",138845,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",144844,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,52,"United-States",">50K" +26,"Private",55743,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +40,"Self-emp-not-inc",117721,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +19,"Self-emp-not-inc",116385,"11th",7,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +58,"Private",301867,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",238913,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Self-emp-not-inc",123983,"Some-college",10,"Married-civ-spouse","Sales","Own-child","Asian-Pac-Islander","Male",0,0,63,"South","<=50K" +26,"Private",165510,"Bachelors",13,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +64,"Private",183513,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +42,"Self-emp-inc",119281,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +41,"Private",152629,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",110171,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",211440,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +41,"Local-gov",359259,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",125796,"11th",7,"Separated","Other-service","Not-in-family","Black","Female",0,0,40,"Jamaica","<=50K" +34,"Private",39609,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",120066,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,0,60,"United-States","<=50K" +41,"Private",132633,"11th",7,"Divorced","Priv-house-serv","Unmarried","White","Female",0,0,25,"Guatemala","<=50K" +39,"Private",192702,"Masters",14,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +41,"Private",166813,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +33,"Self-emp-inc",40444,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",290504,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"United-States","<=50K" +25,"Private",175370,"Some-college",10,"Divorced","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +77,"Self-emp-not-inc",72931,"7th-8th",4,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Male",0,0,20,"Italy",">50K" +33,"?",234542,"Assoc-voc",11,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +66,"Private",284021,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",277974,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +44,"Private",111275,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +28,"Private",125527,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +33,"Private",198660,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Private",216116,"HS-grad",9,"Married-spouse-absent","Other-service","Not-in-family","Black","Female",0,0,40,"Jamaica","<=50K" +62,"Private",200922,"7th-8th",4,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",153372,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +41,"Private",406603,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,6,"Iran","<=50K" +23,"Local-gov",248344,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Male",0,0,30,"United-States","<=50K" +48,"Private",240629,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Italy",">50K" +38,"Private",314310,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +37,"Private",259785,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Private",127111,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +29,"Private",178272,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +66,"Local-gov",75134,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,25,"United-States","<=50K" +19,"Private",195985,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +23,"Private",221955,"9th",5,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,39,"Mexico","<=50K" +34,"Private",177675,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",182828,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +33,"Self-emp-not-inc",270889,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +43,"Private",183096,"Some-college",10,"Separated","Sales","Unmarried","White","Female",0,0,10,"United-States","<=50K" +27,"Private",336951,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,99,"United-States","<=50K" +33,"State-gov",295589,"Some-college",10,"Separated","Adm-clerical","Own-child","Black","Male",0,0,35,"United-States","<=50K" +26,"Private",289980,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"Mexico","<=50K" +46,"Private",163352,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,36,"United-States","<=50K" +38,"Private",190776,"Assoc-acdm",12,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +90,"Private",313986,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +72,"Self-emp-inc",473748,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,25,"United-States",">50K" +20,"Private",163003,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,15,"United-States","<=50K" +29,"Private",183061,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,0,48,"United-States","<=50K" +49,"Private",123584,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,75,"United-States","<=50K" +23,"Private",120910,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +20,"Private",227554,"Some-college",10,"Married-spouse-absent","Sales","Own-child","Black","Female",0,0,18,"United-States","<=50K" +46,"Private",214955,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",209768,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",258120,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,55,"Jamaica","<=50K" +49,"Private",110015,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"Greece","<=50K" +54,"Private",152652,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States","<=50K" +31,"Self-emp-not-inc",114639,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +18,"?",128538,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,6,"United-States","<=50K" +19,"Private",131615,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Private",353824,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",178417,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +58,"Private",178644,"HS-grad",9,"Widowed","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",271665,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +37,"?",223732,"Some-college",10,"Separated","?","Unmarried","White","Male",0,0,40,"United-States","<=50K" +21,"Federal-gov",169003,"12th",8,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,25,"United-States","<=50K" +52,"State-gov",338816,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,70,"United-States",">50K" +34,"Private",506858,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,32,"United-States",">50K" +28,"Private",265628,"Assoc-voc",11,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",173495,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",177413,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",31670,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,65,"United-States","<=50K" +49,"Private",154451,"11th",7,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +35,"Private",265535,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,50,"Jamaica",">50K" +31,"Private",118941,"Some-college",10,"Divorced","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +18,"Private",214617,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +43,"Private",124692,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",434102,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"?",387641,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +58,"Private",87329,"11th",7,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,48,"United-States","<=50K" +36,"Private",263130,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",262882,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +19,"Private",27433,"11th",7,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",393945,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +26,"Private",173927,"Assoc-voc",11,"Never-married","Prof-specialty","Own-child","Other","Female",0,0,60,"Jamaica","<=50K" +38,"Private",343403,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +36,"Private",111128,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +40,"Private",193882,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +25,"Private",310864,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Black","Male",0,0,40,"?","<=50K" +41,"Private",128354,"Bachelors",13,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,25,"United-States",">50K" +33,"Private",113364,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +63,"?",198559,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,16,"United-States","<=50K" +51,"Private",136913,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",115488,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",154227,"Assoc-voc",11,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",279667,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Self-emp-not-inc",281030,"HS-grad",9,"Never-married","Sales","Unmarried","White","Male",0,0,66,"United-States","<=50K" +19,"Private",283945,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,25,"United-States","<=50K" +47,"Private",454989,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +26,"Private",391349,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"State-gov",166704,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,14,"United-States","<=50K" +36,"Private",151835,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,60,"United-States",">50K" +60,"Private",199085,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",61487,"HS-grad",9,"Never-married","Prof-specialty","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +19,"Private",120251,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,14,"United-States","<=50K" +42,"Private",273230,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,90,"United-States","<=50K" +36,"Private",358373,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","Black","Female",0,0,36,"United-States","<=50K" +35,"Private",267891,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,38,"United-States","<=50K" +22,"Private",234880,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +54,"Private",48358,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",96452,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +55,"Private",204751,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States","<=50K" +57,"Private",375868,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Private",413373,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,36,"United-States","<=50K" +24,"Private",537222,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Local-gov",33975,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Self-emp-inc",162327,"11th",7,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",182691,"HS-grad",9,"Divorced","Exec-managerial","Own-child","White","Male",0,0,44,"United-States","<=50K" +36,"Private",300829,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,42,"United-States","<=50K" +51,"Local-gov",114508,"9th",5,"Separated","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +46,"Self-emp-inc",214627,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +25,"State-gov",120041,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",361138,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,50,"United-States","<=50K" +37,"Private",76893,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",205424,"Bachelors",13,"Divorced","Sales","Unmarried","White","Male",0,0,40,"United-States",">50K" +40,"Private",229148,"12th",8,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"Jamaica","<=50K" +58,"Self-emp-inc",154537,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,20,"United-States",">50K" +52,"Private",181901,"HS-grad",9,"Married-spouse-absent","Farming-fishing","Other-relative","White","Male",0,0,20,"Mexico","<=50K" +18,"Private",152004,"11th",7,"Never-married","Other-service","Own-child","Black","Male",0,0,20,"United-States","<=50K" +27,"Private",205188,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Private",66634,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,16,"United-States","<=50K" +38,"Self-emp-not-inc",180220,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +40,"Self-emp-not-inc",99651,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +41,"Private",327723,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",127384,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +30,"Private",363296,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","Black","Male",0,0,72,"United-States","<=50K" +28,"Private",30070,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +31,"Private",595000,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","Black","Female",0,0,35,"United-States","<=50K" +21,"?",152328,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +33,"?",177824,"HS-grad",9,"Separated","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"State-gov",111483,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",199555,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,25,"United-States","<=50K" +42,"Private",50018,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"?","<=50K" +36,"Private",218490,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +31,"Private",159187,"HS-grad",9,"Divorced","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",83033,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"Germany","<=50K" +34,"Self-emp-not-inc",24961,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,80,"United-States","<=50K" +21,"Private",182117,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +75,"Self-emp-not-inc",146576,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","White","Male",0,0,48,"United-States",">50K" +21,"Private",176690,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,24,"United-States","<=50K" +81,"Private",122651,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,15,"United-States","<=50K" +54,"Self-emp-inc",149650,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"Canada","<=50K" +34,"Private",454508,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,65,"Iran","<=50K" +41,"Private",266530,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Amer-Indian-Eskimo","Male",0,0,45,"United-States","<=50K" +61,"?",198542,"Bachelors",13,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",217961,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",221661,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"Mexico","<=50K" +44,"Local-gov",60735,"Bachelors",13,"Divorced","Prof-specialty","Own-child","White","Female",0,0,60,"United-States","<=50K" +47,"Self-emp-not-inc",121124,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",48588,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Self-emp-not-inc",240138,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +44,"Private",104196,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +37,"Private",230035,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,46,"United-States",">50K" +28,"Private",38918,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"Germany",">50K" +71,"?",205011,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,10,"United-States","<=50K" +57,"Private",176079,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",180052,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,10,"United-States","<=50K" +30,"Private",378723,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Female",0,0,55,"United-States","<=50K" +20,"Private",233624,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",192591,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +54,"Private",249860,"11th",7,"Divorced","Priv-house-serv","Unmarried","Black","Female",0,0,10,"United-States","<=50K" +20,"Private",247564,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +34,"Private",238912,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",190227,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"State-gov",293287,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +51,"Private",180807,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Private",250217,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,70,"United-States","<=50K" +19,"Private",217418,"Some-college",10,"Never-married","Adm-clerical","Other-relative","Black","Female",0,0,38,"United-States","<=50K" +22,"Local-gov",137510,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +59,"State-gov",163047,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +18,"Private",577521,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,13,"United-States","<=50K" +22,"Private",221533,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +42,"Local-gov",255675,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",114079,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",155781,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",243762,"11th",7,"Separated","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",113062,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,7,"United-States","<=50K" +67,"Private",217028,"Masters",14,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Private",110723,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +47,"Federal-gov",191858,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",179423,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,5,"United-States","<=50K" +20,"Private",339588,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"Peru","<=50K" +22,"Private",206815,"HS-grad",9,"Never-married","Sales","Unmarried","White","Female",0,0,40,"Peru","<=50K" +47,"State-gov",103743,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",235683,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +64,"?",207321,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +35,"State-gov",197495,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +52,"Federal-gov",424012,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",178469,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +73,"Self-emp-inc",92886,"10th",6,"Widowed","Sales","Unmarried","White","Female",0,0,40,"Canada","<=50K" +38,"Self-emp-not-inc",214008,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +18,"Private",118376,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +24,"Private",51799,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +33,"Local-gov",115488,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",190621,"Some-college",10,"Divorced","Exec-managerial","Other-relative","Black","Female",0,0,55,"United-States","<=50K" +55,"Private",193568,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",192878,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",264663,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,60,"United-States","<=50K" +22,"Private",234731,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Private",308373,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +45,"Private",205644,"HS-grad",9,"Separated","Tech-support","Not-in-family","White","Female",0,0,26,"United-States","<=50K" +47,"Local-gov",321851,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States",">50K" +56,"Private",206399,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",124563,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +32,"State-gov",198211,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +17,"Private",130795,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +44,"Private",71269,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +32,"Self-emp-not-inc",319280,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +35,"Private",125933,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +27,"Private",107236,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",32732,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +68,"Private",284763,"11th",7,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +20,"Private",112668,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +33,"Private",376483,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +24,"Private",402778,"9th",5,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,12,"United-States","<=50K" +48,"Private",36177,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +45,"Private",125489,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,50,"United-States","<=50K" +48,"Private",304791,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",209205,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +60,"?",112821,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,35,"United-States",">50K" +39,"Local-gov",178100,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",70261,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +23,"State-gov",186634,"12th",8,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",32958,"Some-college",10,"Separated","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +25,"Private",254746,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +52,"Private",158746,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",140854,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",51506,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",189564,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,42,"United-States",">50K" +37,"Federal-gov",325538,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?",">50K" +58,"Private",213975,"Assoc-voc",11,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +67,"Self-emp-not-inc",431426,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,2,"United-States","<=50K" +48,"Private",199763,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,8,"United-States","<=50K" +63,"Private",161563,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +24,"Local-gov",252024,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,72,"United-States",">50K" +43,"Private",43945,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",178487,"HS-grad",9,"Divorced","Transport-moving","Own-child","White","Male",0,0,60,"United-States","<=50K" +32,"Private",604506,"HS-grad",9,"Married-civ-spouse","Transport-moving","Own-child","White","Male",0,0,72,"Mexico","<=50K" +36,"Private",228157,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Laos","<=50K" +43,"Private",199191,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +27,"Private",189775,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +17,"Private",171080,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,12,"United-States","<=50K" +45,"Private",117310,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,46,"United-States","<=50K" +41,"Self-emp-inc",82049,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",126094,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States","<=50K" +18,"?",202516,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +48,"Local-gov",246392,"Assoc-acdm",12,"Separated","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +51,"?",69328,"Assoc-voc",11,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",292803,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,24,"United-States","<=50K" +54,"Private",286989,"Preschool",1,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +22,"Private",190483,"Some-college",10,"Divorced","Sales","Own-child","White","Female",0,0,48,"Iran","<=50K" +19,"Private",235849,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,35,"United-States","<=50K" +47,"Private",359766,"7th-8th",4,"Divorced","Handlers-cleaners","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",128016,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +30,"Private",170154,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States",">50K" +35,"Private",337286,"Masters",14,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +73,"Self-emp-not-inc",143833,"12th",8,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,18,"United-States","<=50K" +17,"Private",365613,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,10,"Canada","<=50K" +32,"Private",100135,"Bachelors",13,"Separated","Prof-specialty","Unmarried","White","Female",0,0,32,"United-States","<=50K" +43,"Local-gov",180096,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +19,"?",371827,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"Portugal","<=50K" +26,"Private",61270,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Other","Female",0,0,40,"Columbia","<=50K" +41,"Federal-gov",564135,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +52,"State-gov",303462,"Some-college",10,"Separated","Protective-serv","Unmarried","White","Male",0,0,40,"United-States","<=50K" +35,"Private",193106,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,32,"United-States","<=50K" +57,"Private",250201,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,52,"United-States","<=50K" +35,"Private",200426,"Assoc-voc",11,"Married-spouse-absent","Prof-specialty","Unmarried","White","Female",0,0,44,"United-States","<=50K" +33,"Private",222654,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"Private",53366,"7th-8th",4,"Divorced","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +42,"Private",132222,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,60,"United-States","<=50K" +17,"Private",100828,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +49,"Private",31264,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +39,"Private",202027,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +34,"Self-emp-not-inc",168906,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States","<=50K" +37,"Self-emp-not-inc",255454,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +22,"Private",245524,"12th",8,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +27,"Private",386040,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +21,"Private",35424,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +59,"?",93655,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Self-emp-not-inc",151159,"10th",6,"Married-spouse-absent","Transport-moving","Not-in-family","White","Male",0,0,99,"United-States","<=50K" +26,"Private",410240,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",138970,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +39,"Private",269722,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +34,"Private",223678,"HS-grad",9,"Never-married","Other-service","Unmarried","Amer-Indian-Eskimo","Female",0,0,32,"United-States","<=50K" +54,"State-gov",197184,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States","<=50K" +50,"Private",140516,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Local-gov",85341,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +40,"Self-emp-not-inc",192507,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +30,"Private",186932,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +31,"Private",236861,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +46,"Local-gov",327886,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Self-emp-inc",197060,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +38,"Private",229180,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,40,"Cuba","<=50K" +24,"Private",284317,"Bachelors",13,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +24,"Private",73514,"Some-college",10,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Female",0,0,50,"Philippines","<=50K" +27,"Private",47907,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +43,"State-gov",134782,"Assoc-acdm",12,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +48,"Private",118831,"HS-grad",9,"Divorced","Handlers-cleaners","Unmarried","Asian-Pac-Islander","Female",0,0,40,"South","<=50K" +41,"Private",299505,"HS-grad",9,"Separated","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",267161,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","Black","Female",0,0,45,"United-States","<=50K" +38,"Private",119177,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",327886,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +45,"Private",187730,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Private",109015,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +46,"Self-emp-not-inc",110015,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,75,"Greece","<=50K" +24,"Private",104146,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +31,"Local-gov",50442,"Some-college",10,"Never-married","Adm-clerical","Own-child","Amer-Indian-Eskimo","Female",0,0,25,"United-States","<=50K" +35,"Private",57640,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +37,"Local-gov",333664,"Some-college",10,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",224858,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +56,"Private",290641,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Private",245378,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",179136,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",116788,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",129699,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Federal-gov",39606,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"England",">50K" +44,"Self-emp-inc",95150,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +63,"Private",102479,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",199191,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,30,"United-States","<=50K" +31,"Private",229636,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"Mexico","<=50K" +26,"Private",53833,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States","<=50K" +37,"Self-emp-inc",27997,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +60,"?",124487,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States",">50K" +33,"Private",111363,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +38,"Private",107630,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",134287,"Assoc-voc",11,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +46,"Self-emp-inc",283004,"Assoc-voc",11,"Divorced","Exec-managerial","Unmarried","Asian-Pac-Islander","Female",0,0,63,"Thailand","<=50K" +24,"Private",33616,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +47,"Local-gov",121124,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +27,"Private",188189,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +46,"Private",106255,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Federal-gov",282830,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States",">50K" +47,"Private",243904,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Male",0,0,40,"Honduras","<=50K" +51,"Private",427781,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",334291,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Local-gov",173224,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +29,"Private",87507,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,60,"India","<=50K" +27,"Private",204497,"10th",6,"Divorced","Transport-moving","Not-in-family","Amer-Indian-Eskimo","Male",0,0,75,"United-States","<=50K" +60,"Private",230545,"7th-8th",4,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"Cuba","<=50K" +31,"Private",118161,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",150499,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Local-gov",96554,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Private",288551,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,52,"United-States",">50K" +69,"Self-emp-not-inc",104003,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +54,"Self-emp-inc",124963,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Private",198388,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Federal-gov",126204,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",91709,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +34,"Self-emp-not-inc",152109,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +24,"Self-emp-not-inc",191954,"7th-8th",4,"Never-married","Farming-fishing","Own-child","White","Male",0,0,50,"United-States","<=50K" +29,"Local-gov",289991,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +64,"Private",92115,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",320277,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",33610,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,60,"United-States","<=50K" +36,"Private",168276,"10th",6,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",254973,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Wife","White","Female",0,0,40,"United-States",">50K" +37,"Private",95336,"10th",6,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +33,"Private",227282,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +19,"Private",138153,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +20,"?",111252,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +20,"?",168863,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +25,"Private",394503,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",141657,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",172230,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",282944,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Local-gov",55377,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States","<=50K" +35,"State-gov",49352,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,38,"United-States","<=50K" +32,"Private",213887,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,45,"United-States","<=50K" +61,"Self-emp-not-inc",24046,"HS-grad",9,"Widowed","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +26,"State-gov",208122,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +22,"Private",227994,"Some-college",10,"Married-spouse-absent","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,39,"United-States","<=50K" +49,"Private",215389,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,48,"United-States","<=50K" +40,"Private",99434,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,12,"United-States","<=50K" +37,"Private",190964,"HS-grad",9,"Separated","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"?",113700,"Bachelors",13,"Never-married","?","Own-child","White","Male",0,0,50,"United-States","<=50K" +28,"Private",259840,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +27,"Private",168827,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-inc",28984,"Assoc-voc",11,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Private",182211,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States","<=50K" +41,"Private",82393,"Some-college",10,"Never-married","Craft-repair","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +28,"Private",183639,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,21,"United-States","<=50K" +38,"Private",342448,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +28,"Local-gov",211920,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Federal-gov",34178,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",400630,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,36,"United-States",">50K" +73,"Self-emp-not-inc",161251,"HS-grad",9,"Widowed","Craft-repair","Not-in-family","White","Male",0,0,24,"United-States","<=50K" +21,"Private",255685,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"Outlying-US(Guam-USVI-etc)","<=50K" +38,"Private",199256,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +64,"?",143716,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,2,"United-States","<=50K" +47,"Private",221666,"Some-college",10,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",39615,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +44,"Private",104440,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +61,"Self-emp-not-inc",503675,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,60,"United-States",">50K" +49,"Private",50748,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,55,"England","<=50K" +23,"Private",107190,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,20,"United-States","<=50K" +19,"Private",206874,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +21,"Private",83141,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,53,"United-States","<=50K" +56,"Private",444089,"11th",7,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",141896,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Federal-gov",33487,"Some-college",10,"Divorced","Tech-support","Unmarried","Amer-Indian-Eskimo","Female",0,0,20,"United-States","<=50K" +41,"Private",65372,"Doctorate",16,"Divorced","Sales","Unmarried","White","Female",0,0,50,"United-States",">50K" +30,"Private",341346,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",343403,"Doctorate",16,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,20,"?","<=50K" +47,"Private",287480,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",199067,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,32,"United-States","<=50K" +22,"?",182771,"Assoc-voc",11,"Never-married","?","Own-child","Asian-Pac-Islander","Male",0,0,20,"United-States","<=50K" +31,"Private",159737,"10th",6,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +24,"Private",117583,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,48,"United-States","<=50K" +49,"Self-emp-not-inc",43479,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",203003,"7th-8th",4,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,25,"Germany","<=50K" +50,"Private",133963,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +38,"Private",227794,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +20,"Self-emp-not-inc",112137,"Some-college",10,"Never-married","Prof-specialty","Other-relative","Asian-Pac-Islander","Female",0,0,20,"South","<=50K" +49,"Self-emp-not-inc",110457,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Private",281565,"HS-grad",9,"Widowed","Other-service","Other-relative","Asian-Pac-Islander","Female",0,0,50,"South","<=50K" +46,"Federal-gov",297906,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,50,"United-States",">50K" +19,"Private",151506,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +31,"Federal-gov",139455,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"Cuba","<=50K" +38,"Private",26987,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",233312,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",161092,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +58,"Local-gov",98361,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"Private",188928,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",164922,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",185673,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",193598,"Preschool",1,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +56,"Private",274111,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +32,"Private",245482,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +56,"Private",160932,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,44,"United-States",">50K" +50,"Private",44368,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"?",291374,"HS-grad",9,"Separated","?","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +30,"Private",280927,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",222993,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Federal-gov",25240,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",204052,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",74054,"11th",7,"Never-married","Sales","Own-child","Other","Female",0,0,20,"?","<=50K" +46,"Private",169042,"10th",6,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"Ecuador","<=50K" +31,"Private",104509,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,65,"United-States",">50K" +44,"Local-gov",254146,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",183041,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +45,"Private",107682,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +50,"Self-emp-inc",287598,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States","<=50K" +53,"Private",182186,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Dominican-Republic","<=50K" +45,"Private",112305,"Some-college",10,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +21,"Private",212661,"10th",6,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,39,"United-States","<=50K" +37,"Private",32709,"Bachelors",13,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States",">50K" +42,"Federal-gov",46366,"HS-grad",9,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",24106,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,30,"United-States","<=50K" +45,"Self-emp-not-inc",40666,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +32,"Private",182975,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +30,"Private",345122,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"?",208311,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,80,"United-States",">50K" +37,"Private",120045,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,56,"United-States","<=50K" +18,"?",201299,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +32,"Private",152940,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",243580,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +36,"?",176458,"HS-grad",9,"Divorced","?","Unmarried","White","Female",0,0,28,"United-States","<=50K" +33,"Private",101562,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Private",108699,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",175878,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Female",0,0,40,"United-States","<=50K" +34,"Local-gov",177675,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,50,"United-States",">50K" +33,"Private",213887,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",357619,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,60,"Germany","<=50K" +39,"Private",165799,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",71469,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +19,"Private",229745,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,20,"United-States","<=50K" +46,"Private",28419,"Assoc-voc",11,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +47,"Private",26950,"Masters",14,"Divorced","Sales","Not-in-family","White","Female",0,0,6,"United-States","<=50K" +47,"Self-emp-not-inc",107231,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +52,"Local-gov",512103,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",245090,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +58,"Private",314153,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",243988,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +54,"Self-emp-not-inc",82551,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Other-relative","White","Female",0,0,10,"United-States","<=50K" +20,"Private",42706,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +25,"Private",235795,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +25,"Self-emp-not-inc",108001,"9th",5,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +69,"Self-emp-not-inc",128206,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,30,"United-States","<=50K" +28,"Private",224634,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +20,"Private",362999,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +21,"Private",346693,"7th-8th",4,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,40,"United-States","<=50K" +37,"Private",175759,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",99199,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,32,"United-States","<=50K" +25,"?",219987,"Assoc-acdm",12,"Married-civ-spouse","?","Husband","White","Male",0,0,13,"United-States","<=50K" +39,"Private",143445,"HS-grad",9,"Married-civ-spouse","Other-service","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +34,"Private",118710,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Local-gov",224185,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",118972,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +29,"Private",165360,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Private",38950,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,89,"United-States","<=50K" +29,"Private",247151,"11th",7,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",213722,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",209955,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +41,"Private",174395,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +22,"?",179973,"Assoc-voc",11,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",200207,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,44,"United-States","<=50K" +19,"Private",156587,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,38,"United-States","<=50K" +24,"Private",33016,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",197496,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,30,"?","<=50K" +32,"Private",153588,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",284166,"HS-grad",9,"Never-married","Sales","Unmarried","White","Male",0,0,60,"United-States",">50K" +18,"Private",716066,"10th",6,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,30,"United-States","<=50K" +27,"Private",188519,"HS-grad",9,"Divorced","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",109080,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +52,"Private",174421,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,32,"United-States","<=50K" +24,"Private",259351,"Some-college",10,"Never-married","Craft-repair","Unmarried","Amer-Indian-Eskimo","Male",0,0,40,"Mexico","<=50K" +42,"Federal-gov",284403,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +20,"?",201766,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +20,"State-gov",340475,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +39,"Private",487486,"HS-grad",9,"Widowed","Handlers-cleaners","Unmarried","White","Male",0,0,40,"?","<=50K" +68,"?",484298,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States","<=50K" +35,"Private",170617,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,48,"United-States","<=50K" +54,"Private",94055,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",117779,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",209770,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +20,"Private",317443,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,15,"United-States","<=50K" +64,"?",140237,"Preschool",1,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",107411,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +36,"Self-emp-not-inc",122493,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,47,"United-States","<=50K" +44,"Self-emp-inc",195124,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"?","<=50K" +22,"Private",335453,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +56,"Private",318329,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",100321,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +24,"Self-emp-not-inc",81145,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,75,"United-States","<=50K" +22,"Private",62865,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",176262,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,30,"United-States","<=50K" +42,"Private",168103,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Local-gov",208174,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,55,"United-States","<=50K" +67,"Self-emp-not-inc",226092,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,44,"United-States","<=50K" +20,"Private",212668,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +32,"Private",381583,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,40,"United-States","<=50K" +46,"Private",239439,"HS-grad",9,"Separated","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +52,"Private",172493,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +44,"Private",239876,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +65,"?",221881,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Mexico","<=50K" +27,"Self-emp-not-inc",206889,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Private",110668,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","Black","Female",0,0,35,"United-States","<=50K" +30,"Private",211028,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +48,"Private",20296,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,37,"United-States",">50K" +35,"Private",194690,"7th-8th",4,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",204984,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +40,"Self-emp-not-inc",238574,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +33,"Private",345360,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",192381,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Private",479765,"7th-8th",4,"Never-married","Sales","Other-relative","White","Male",0,0,45,"Guatemala","<=50K" +45,"Self-emp-inc",34091,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States",">50K" +30,"Private",151773,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",299080,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +27,"Local-gov",52156,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States","<=50K" +31,"Private",318647,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",80145,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +39,"State-gov",343646,"Bachelors",13,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"Mexico",">50K" +42,"Self-emp-not-inc",198692,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +19,"Private",266635,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,30,"United-States","<=50K" +31,"Private",197672,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",185846,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",315110,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,20,"United-States","<=50K" +27,"Private",220754,"Doctorate",16,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",64292,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",126060,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +32,"Private",210562,"Assoc-voc",11,"Divorced","Craft-repair","Own-child","White","Male",0,0,46,"United-States","<=50K" +23,"Private",350181,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",233421,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +53,"Private",167170,"HS-grad",9,"Widowed","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",260801,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +41,"Private",173370,"Bachelors",13,"Separated","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +27,"Private",135520,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"Dominican-Republic","<=50K" +30,"Private",121308,"Some-college",10,"Divorced","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",444743,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +21,"Private",65225,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +58,"State-gov",136982,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","Black","Female",0,0,40,"Honduras","<=50K" +45,"State-gov",271962,"Bachelors",13,"Divorced","Protective-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",204046,"10th",6,"Divorced","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",225823,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Private",121038,"Assoc-voc",11,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,40,"United-States","<=50K" +26,"Private",49092,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",148709,"HS-grad",9,"Separated","Handlers-cleaners","Other-relative","White","Female",0,0,40,"United-States","<=50K" +27,"Private",209205,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",285865,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +22,"Federal-gov",216129,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,40,"United-States","<=50K" +37,"Federal-gov",40955,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"Japan","<=50K" +54,"Private",197189,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",33001,"HS-grad",9,"Divorced","Farming-fishing","Unmarried","White","Male",0,0,50,"United-States","<=50K" +44,"Private",227399,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States","<=50K" +38,"Private",164050,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States",">50K" +49,"Private",259087,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",236262,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,12,"United-States","<=50K" +26,"Private",177929,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +48,"Private",166929,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"?",">50K" +32,"Private",199963,"11th",7,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +35,"State-gov",98776,"HS-grad",9,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",135056,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +42,"State-gov",102343,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,72,"India",">50K" +30,"Private",231263,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",226913,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +36,"Private",129573,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +31,"Private",191001,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Federal-gov",69345,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +38,"Private",204556,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",192626,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Private",202812,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",405177,"10th",6,"Separated","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",227890,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,46,"United-States",">50K" +33,"Private",101352,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States",">50K" +49,"Private",82572,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +28,"Private",132686,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",245661,"HS-grad",9,"Separated","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +42,"State-gov",104663,"Doctorate",16,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"Italy",">50K" +30,"Private",347166,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +37,"Local-gov",108540,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",333305,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,35,"United-States","<=50K" +51,"Private",155408,"HS-grad",9,"Married-spouse-absent","Sales","Not-in-family","Black","Female",0,0,38,"United-States","<=50K" +27,"Federal-gov",246372,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",30290,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",347321,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-inc",205852,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +40,"Federal-gov",163215,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"?","<=50K" +54,"State-gov",93449,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"India",">50K" +47,"Self-emp-inc",116927,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States",">50K" +35,"Private",164526,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Yugoslavia",">50K" +33,"Private",31573,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Local-gov",125159,"Some-college",10,"Never-married","Adm-clerical","Other-relative","Black","Male",0,0,40,"Haiti","<=50K" +39,"State-gov",201105,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,55,"United-States",">50K" +33,"Private",150570,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",118941,"11th",7,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"Ireland","<=50K" +53,"Private",141388,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",174714,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Male",0,0,35,"United-States","<=50K" +63,"Private",133144,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +21,"Self-emp-not-inc",318865,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +59,"Private",109638,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",92969,"1st-4th",2,"Separated","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +66,"?",376028,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"United-States","<=50K" +19,"Private",144161,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,30,"United-States","<=50K" +31,"Private",183778,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +23,"Private",398904,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +45,"Private",170846,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +35,"Local-gov",204277,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",205152,"Bachelors",13,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",225395,"7th-8th",4,"Never-married","Machine-op-inspct","Other-relative","White","Female",0,0,60,"Mexico","<=50K" +38,"Private",33975,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Other-relative","White","Male",0,0,40,"United-States",">50K" +49,"Private",147032,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Asian-Pac-Islander","Female",0,0,8,"Philippines","<=50K" +64,"Private",174826,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"Local-gov",232769,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,20,"United-States","<=50K" +25,"Private",36984,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +21,"Private",292264,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +23,"Private",287988,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +67,"Self-emp-inc",330144,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States",">50K" +24,"Private",191948,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +46,"Private",324601,"1st-4th",2,"Separated","Machine-op-inspct","Own-child","White","Female",0,0,40,"Guatemala","<=50K" +38,"State-gov",200289,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Taiwan","<=50K" +20,"Private",113307,"7th-8th",4,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +28,"?",194087,"Some-college",10,"Never-married","?","Other-relative","White","Female",0,0,40,"United-States","<=50K" +26,"Private",155213,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +58,"Private",175127,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"State-gov",358461,"Some-college",10,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +37,"State-gov",354929,"Assoc-acdm",12,"Divorced","Protective-serv","Not-in-family","Black","Male",0,0,38,"United-States","<=50K" +53,"State-gov",104501,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?",">50K" +45,"Private",112929,"7th-8th",4,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +33,"Private",132832,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +33,"State-gov",357691,"Masters",14,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",114605,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +60,"Self-emp-not-inc",525878,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",68358,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +38,"Private",174571,"10th",6,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,45,"United-States","<=50K" +40,"Private",42703,"Assoc-voc",11,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",220589,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +44,"Self-emp-not-inc",197558,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,70,"United-States",">50K" +27,"Private",423250,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +34,"Self-emp-not-inc",29254,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +20,"?",308924,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +49,"Local-gov",276247,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",213841,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Private",181677,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States",">50K" +46,"Private",160061,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",285295,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"?","<=50K" +43,"Private",265266,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"State-gov",194954,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,15,"United-States","<=50K" +48,"Private",156926,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",217414,"Some-college",10,"Divorced","Protective-serv","Unmarried","White","Male",0,0,55,"United-States","<=50K" +18,"?",192399,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,60,"United-States","<=50K" +42,"Private",383493,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +60,"Private",193235,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,24,"United-States","<=50K" +37,"Self-emp-inc",99452,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States",">50K" +44,"Local-gov",254134,"Assoc-acdm",12,"Divorced","Tech-support","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",90446,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",116613,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"Portugal","<=50K" +42,"Local-gov",238188,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +17,"Private",95909,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,12,"United-States","<=50K" +41,"Private",82319,"12th",8,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,10,"United-States","<=50K" +56,"Private",179625,"10th",6,"Separated","Other-service","Unmarried","White","Female",0,0,32,"United-States","<=50K" +28,"Private",119793,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",254989,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",104830,"7th-8th",4,"Never-married","Transport-moving","Unmarried","White","Male",0,0,25,"Guatemala","<=50K" +49,"Federal-gov",110373,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Self-emp-not-inc",135416,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,50,"United-States","<=50K" +25,"Private",298225,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States","<=50K" +42,"Private",166740,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",276624,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",226789,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,58,"United-States","<=50K" +37,"Private",31023,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +42,"Private",136986,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +41,"Private",179580,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,36,"United-States",">50K" +23,"Private",103277,"Some-college",10,"Divorced","Other-service","Own-child","White","Female",0,0,24,"United-States","<=50K" +31,"Federal-gov",351141,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",191161,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,57,"United-States",">50K" +20,"Private",148709,"Some-college",10,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,25,"United-States","<=50K" +36,"Private",128382,"Some-college",10,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,45,"United-States","<=50K" +50,"Private",144361,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",172538,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Private",46028,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,60,"United-States","<=50K" +32,"Private",198452,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,0,40,"United-States","<=50K" +59,"Private",193895,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +50,"Private",378747,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +42,"Private",31251,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,37,"United-States","<=50K" +32,"Private",71540,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",36480,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +18,"Private",116528,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +60,"Private",52152,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +60,"Private",216690,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?","<=50K" +42,"Local-gov",227065,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,22,"United-States","<=50K" +49,"Private",84013,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +35,"Self-emp-inc",82051,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",176185,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"Iran","<=50K" +59,"Private",115414,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Private",354923,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",393712,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +39,"Private",98941,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",141483,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +21,"Private",226145,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +23,"Private",394612,"Bachelors",13,"Never-married","Tech-support","Own-child","Black","Male",0,0,40,"United-States","<=50K" +22,"Private",231085,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +55,"Self-emp-not-inc",183810,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +19,"Private",186159,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",162282,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +23,"Private",273206,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,23,"United-States","<=50K" +23,"Private",102729,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +42,"Private",198096,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +22,"State-gov",292933,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +18,"Private",135924,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +34,"Private",27409,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",299507,"Assoc-acdm",12,"Separated","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +62,"Self-emp-not-inc",102631,"Some-college",10,"Widowed","Farming-fishing","Unmarried","White","Female",0,0,50,"United-States","<=50K" +51,"Private",153486,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",434292,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,30,"United-States","<=50K" +28,"Self-emp-not-inc",240172,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +56,"Private",219426,"10th",6,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",295791,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +23,"Local-gov",496382,"Some-college",10,"Married-spouse-absent","Adm-clerical","Own-child","White","Female",0,0,40,"Guatemala","<=50K" +33,"Private",376483,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,30,"United-States","<=50K" +27,"Private",107218,"HS-grad",9,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +21,"Private",246207,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,20,"United-States","<=50K" +18,"?",80564,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,60,"United-States","<=50K" +37,"Local-gov",328301,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +39,"Local-gov",301614,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",121040,"Assoc-acdm",12,"Never-married","Exec-managerial","Own-child","Black","Female",0,0,40,"United-States","<=50K" +37,"Private",125550,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +34,"Private",170772,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +33,"Private",180551,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",48189,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,30,"United-States","<=50K" +20,"Private",432154,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,8,"Mexico","<=50K" +26,"Private",263200,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +47,"Private",123207,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States",">50K" +17,"Private",110798,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +31,"Private",185528,"Some-college",10,"Divorced","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +34,"Private",181311,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",528616,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +39,"Private",272950,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +22,"?",195532,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"Private",197583,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +40,"Private",48612,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +68,"?",170182,"Some-college",10,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +27,"Local-gov",230885,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,45,"United-States",">50K" +54,"Private",174102,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +23,"Private",352606,"HS-grad",9,"Divorced","Priv-house-serv","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",241153,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +54,"Private",155433,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"United-States","<=50K" +40,"Private",125461,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +19,"Private",331556,"10th",6,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"?",138575,"HS-grad",9,"Never-married","?","Other-relative","White","Male",0,0,60,"United-States","<=50K" +35,"Private",223514,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",147206,"12th",8,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",174592,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",268620,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +70,"Self-emp-not-inc",150886,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,25,"United-States","<=50K" +45,"Private",112362,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +83,"Private",195507,"HS-grad",9,"Widowed","Protective-serv","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +59,"Private",192983,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",120544,"9th",5,"Never-married","Other-service","Own-child","Black","Male",0,0,15,"United-States","<=50K" +31,"Private",59083,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",208277,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +24,"Local-gov",184678,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",278736,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +48,"Local-gov",39464,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,52,"United-States","<=50K" +27,"Private",162343,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Dominican-Republic","<=50K" +41,"Private",204046,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",255647,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,25,"Mexico","<=50K" +53,"Private",123011,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States",">50K" +66,"Self-emp-not-inc",291362,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +31,"Private",159187,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +30,"State-gov",126414,"Bachelors",13,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",227626,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +74,"Private",211075,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",331651,"Some-college",10,"Separated","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",515025,"10th",6,"Married-civ-spouse","Handlers-cleaners","Wife","White","Female",0,0,40,"United-States","<=50K" +53,"Private",394474,"Assoc-acdm",12,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",337505,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +42,"Private",211860,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",102684,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +62,"?",225657,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,24,"United-States","<=50K" +33,"Private",121966,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",396790,"HS-grad",9,"Never-married","Transport-moving","Own-child","Black","Male",0,0,20,"United-States","<=50K" +46,"Local-gov",149949,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +25,"Private",252187,"11th",7,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",209934,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +29,"Federal-gov",229300,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +50,"Private",200618,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",216984,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +40,"Private",212760,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",150309,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Amer-Indian-Eskimo","Male",0,0,45,"United-States","<=50K" +54,"Private",174655,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",109621,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",225124,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +46,"Private",172695,"11th",7,"Widowed","Other-service","Not-in-family","White","Female",0,0,27,"El-Salvador","<=50K" +71,"Self-emp-not-inc",238479,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,8,"United-States","<=50K" +27,"Private",37754,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,80,"United-States","<=50K" +56,"Private",85018,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +64,"Private",256466,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,0,60,"Philippines",">50K" +23,"Private",169188,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,25,"United-States","<=50K" +36,"Private",210945,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Local-gov",287031,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +26,"Private",224361,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Federal-gov",108464,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",75826,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",120277,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",104439,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +27,"Private",56870,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",200819,"12th",8,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",170562,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,20,"United-States","<=50K" +30,"Private",80933,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",33088,"11th",7,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",177651,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +31,"Private",261943,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",169785,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"Italy","<=50K" +20,"Private",141481,"11th",7,"Married-civ-spouse","Sales","Other-relative","White","Female",0,0,50,"United-States","<=50K" +37,"Private",433491,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Local-gov",86615,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,30,"United-States","<=50K" +39,"Private",125550,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +46,"State-gov",421223,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",26999,"Bachelors",13,"Separated","Exec-managerial","Unmarried","White","Female",0,0,42,"United-States","<=50K" +34,"?",133861,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States","<=50K" +44,"Private",115323,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Self-emp-inc",23778,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +28,"Self-emp-not-inc",190836,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +38,"Self-emp-inc",159179,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +64,"?",205479,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States",">50K" +19,"?",47713,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",163237,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,52,"United-States",">50K" +61,"Private",202202,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",168837,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",112271,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",52537,"HS-grad",9,"Never-married","Transport-moving","Unmarried","Black","Male",0,0,30,"United-States","<=50K" +27,"Private",38353,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +22,"Private",141698,"10th",6,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +26,"Private",28856,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",175652,"11th",7,"Never-married","Other-service","Other-relative","White","Female",0,0,15,"United-States","<=50K" +36,"Private",213008,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Private",92463,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"State-gov",125165,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +42,"Self-emp-not-inc",103980,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"?",180362,"Bachelors",13,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",53903,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",179735,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States","<=50K" +41,"?",277390,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,30,"United-States",">50K" +49,"Private",122177,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,80,"United-States","<=50K" +46,"Private",188161,"HS-grad",9,"Separated","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",170108,"HS-grad",9,"Separated","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +28,"Private",175262,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"Mexico","<=50K" +19,"?",204441,"HS-grad",9,"Never-married","?","Other-relative","Black","Male",0,0,20,"United-States","<=50K" +19,"Private",164395,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +18,"Private",115630,"11th",7,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,20,"United-States","<=50K" +39,"Private",178815,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +60,"Self-emp-not-inc",168223,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +38,"Private",100295,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,50,"Canada",">50K" +36,"Private",172256,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,44,"United-States",">50K" +45,"Private",51664,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",115963,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",333910,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +23,"Private",148948,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +48,"State-gov",130561,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,24,"United-States","<=50K" +46,"Private",428350,"HS-grad",9,"Married-civ-spouse","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +43,"Private",188808,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +25,"Private",112847,"HS-grad",9,"Married-civ-spouse","Transport-moving","Own-child","Other","Male",0,0,40,"United-States","<=50K" +50,"Private",110748,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-inc",156653,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +35,"Private",196491,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +65,"Local-gov",254413,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Private",91262,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Asian-Pac-Islander","Male",0,0,45,"United-States","<=50K" +43,"Self-emp-not-inc",154785,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Wife","Asian-Pac-Islander","Female",0,0,80,"Thailand","<=50K" +55,"Private",84231,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +22,"Private",226327,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",248406,"Some-college",10,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,32,"United-States","<=50K" +22,"?",32732,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,50,"United-States","<=50K" +20,"Private",95918,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Local-gov",375675,"12th",8,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"United-States",">50K" +43,"Private",244172,"HS-grad",9,"Separated","Transport-moving","Unmarried","White","Male",0,0,40,"Mexico","<=50K" +46,"Federal-gov",233555,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"?","<=50K" +34,"Private",77271,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,20,"England","<=50K" +35,"Private",33397,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +30,"Private",446358,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,41,"United-States","<=50K" +25,"Private",151810,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,28,"United-States","<=50K" +44,"Private",125461,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +35,"Private",133906,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",155106,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",232766,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Private",305319,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",121023,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +29,"Private",198997,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States","<=50K" +20,"Private",38772,"10th",6,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,50,"United-States","<=50K" +41,"Private",253759,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +27,"Private",130067,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,65,"United-States","<=50K" +37,"Private",203828,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"State-gov",221558,"Masters",14,"Separated","Prof-specialty","Unmarried","White","Female",0,0,24,"?","<=50K" +31,"Private",156464,"10th",6,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",72333,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +33,"Local-gov",83671,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,50,"United-States","<=50K" +19,"Private",91928,"Some-college",10,"Never-married","Other-service","Other-relative","White","Female",0,0,35,"United-States","<=50K" +44,"Private",99203,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Self-emp-inc",455995,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,65,"United-States",">50K" +62,"Private",192515,"HS-grad",9,"Widowed","Farming-fishing","Unmarried","White","Female",0,0,40,"United-States","<=50K" +17,"Private",221129,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Private",85413,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,44,"United-States",">50K" +31,"Private",196125,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",265638,"Some-college",10,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +53,"Private",177727,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",205822,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",112607,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +18,"Private",183315,"11th",7,"Never-married","Sales","Own-child","Black","Female",0,0,10,"United-States","<=50K" +47,"Private",116279,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,43,"United-States","<=50K" +37,"Private",215419,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,25,"United-States","<=50K" +40,"Private",310101,"Some-college",10,"Separated","Sales","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-inc",61885,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,60,"United-States",">50K" +32,"Private",227214,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Other","Male",0,0,40,"Ecuador","<=50K" +64,"Private",239450,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",118847,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +40,"Self-emp-not-inc",95226,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +17,"?",659273,"11th",7,"Never-married","?","Own-child","Black","Female",0,0,40,"Trinadad&Tobago","<=50K" +23,"Private",215395,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",170600,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",91044,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +27,"Private",318639,"10th",6,"Never-married","Other-service","Not-in-family","White","Male",0,0,60,"Mexico","<=50K" +23,"Private",160398,"Some-college",10,"Married-spouse-absent","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",216824,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Asian-Pac-Islander","Male",0,0,30,"United-States","<=50K" +35,"Private",308945,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",0,0,75,"United-States","<=50K" +47,"Private",30840,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +33,"Private",99309,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",188576,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +46,"Private",83064,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",403865,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,56,"United-States","<=50K" +40,"Private",235786,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States",">50K" +44,"Private",191893,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,24,"United-States","<=50K" +31,"Local-gov",149184,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,97,"United-States",">50K" +23,"Private",435604,"Assoc-voc",11,"Separated","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +30,"Self-emp-inc",109282,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,52,"United-States",">50K" +31,"Private",248178,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,35,"United-States","<=50K" +24,"?",112683,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +27,"Private",183639,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Local-gov",107233,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Amer-Indian-Eskimo","Male",0,0,55,"United-States","<=50K" +30,"Self-emp-not-inc",178255,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"?","<=50K" +33,"Self-emp-not-inc",38223,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,70,"United-States","<=50K" +34,"Private",228873,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +29,"Private",202182,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"Self-emp-not-inc",152587,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",204304,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +53,"Private",290640,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +29,"Private",134890,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",452924,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",0,0,40,"Mexico","<=50K" +57,"Private",245193,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +69,"State-gov",34339,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",184756,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,12,"United-States","<=50K" +56,"Private",392160,"HS-grad",9,"Widowed","Sales","Unmarried","White","Female",0,0,25,"Mexico","<=50K" +49,"Private",168337,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",309513,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +70,"Private",77219,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,37,"United-States","<=50K" +44,"Private",212888,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +58,"Local-gov",237879,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,58,"United-States","<=50K" +42,"Self-emp-not-inc",93099,"Some-college",10,"Married-civ-spouse","Prof-specialty","Own-child","White","Female",0,0,25,"United-States","<=50K" +41,"Private",225193,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",50814,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",249351,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +18,"Private",301762,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +50,"Private",195298,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +84,"Private",241065,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,66,"United-States","<=50K" +47,"Private",129513,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +19,"Private",374262,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +24,"Private",382146,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +48,"?",185291,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,6,"United-States","<=50K" +53,"Private",30447,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +58,"Private",49893,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"Private",197387,"Some-college",10,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,24,"Mexico","<=50K" +36,"Self-emp-not-inc",111957,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,52,"United-States","<=50K" +34,"Private",340458,"12th",8,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",185670,"1st-4th",2,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,21,"Mexico","<=50K" +37,"Private",210945,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,24,"United-States","<=50K" +43,"Private",350661,"Prof-school",15,"Separated","Tech-support","Not-in-family","White","Male",0,0,50,"Columbia",">50K" +42,"Private",190543,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States",">50K" +21,"Private",70261,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +49,"Self-emp-not-inc",179048,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"Greece","<=50K" +35,"Private",242094,"HS-grad",9,"Married-civ-spouse","Other-service","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",117634,"Some-college",10,"Widowed","Craft-repair","Unmarried","White","Female",0,0,30,"United-States","<=50K" +28,"Private",82531,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +51,"Private",193374,"1st-4th",2,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +30,"?",186420,"Bachelors",13,"Never-married","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",323605,"7th-8th",4,"Never-married","Other-service","Not-in-family","White","Male",0,0,60,"United-States",">50K" +56,"Private",371064,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",39927,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,8,"United-States","<=50K" +22,"Private",64292,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,37,"United-States","<=50K" +54,"?",196975,"HS-grad",9,"Divorced","?","Other-relative","White","Male",0,0,45,"United-States","<=50K" +22,"Private",210165,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +68,"Private",144137,"Some-college",10,"Divorced","Priv-house-serv","Other-relative","White","Female",0,0,30,"United-States","<=50K" +56,"Local-gov",155657,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"?",72953,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +69,"Self-emp-not-inc",107548,"9th",5,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",163258,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",221324,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",444822,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,8,"Mexico","<=50K" +17,"Private",154398,"11th",7,"Never-married","Other-service","Own-child","Black","Male",0,0,16,"Haiti","<=50K" +50,"Private",159650,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,60,"United-States",">50K" +62,"Private",290754,"10th",6,"Widowed","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",49654,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,52,"United-States","<=50K" +20,"Federal-gov",147352,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",227943,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +18,"Private",423024,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +53,"?",64322,"7th-8th",4,"Separated","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",445940,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +23,"Private",230824,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",48882,"HS-grad",9,"Divorced","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +47,"Private",168195,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +53,"Local-gov",188644,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +28,"Private",136077,"10th",6,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"State-gov",119793,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",336513,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +58,"Private",186991,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"?",218948,"7th-8th",4,"Never-married","?","Not-in-family","White","Female",0,0,32,"Mexico","<=50K" +26,"Private",211435,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",109997,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",286789,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +25,"Private",102460,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",287160,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +39,"Private",198097,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +52,"Private",119111,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",174461,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +26,"Self-emp-not-inc",281678,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,55,"United-States","<=50K" +24,"?",377725,"Bachelors",13,"Never-married","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",151053,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Local-gov",186539,"Masters",14,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +20,"?",149478,"Some-college",10,"Never-married","?","Other-relative","White","Female",0,0,25,"United-States","<=50K" +40,"Private",198452,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",176711,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",165310,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Other-relative","White","Male",0,0,20,"United-States","<=50K" +37,"Private",213008,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Japan","<=50K" +21,"State-gov",38251,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,20,"United-States","<=50K" +33,"Private",125761,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,36,"United-States","<=50K" +28,"Private",148645,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",208613,"Bachelors",13,"Separated","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",192565,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",183885,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +47,"Self-emp-not-inc",243631,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +37,"Private",191754,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",261278,"Some-college",10,"Separated","Sales","Other-relative","Black","Male",0,0,30,"United-States","<=50K" +55,"Private",127014,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,60,"United-States","<=50K" +40,"Private",197919,"Assoc-acdm",12,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",217460,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",86551,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Self-emp-inc",98051,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,54,"United-States",">50K" +38,"Private",215917,"Some-college",10,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +53,"Self-emp-not-inc",192982,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,85,"United-States","<=50K" +27,"Self-emp-not-inc",334132,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,78,"United-States","<=50K" +42,"Private",136986,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +62,"Private",116812,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",89648,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +33,"?",190027,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +59,"Private",99248,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",57600,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +25,"Private",199224,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +58,"Private",140363,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,36,"United-States","<=50K" +30,"Private",308812,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +21,"Private",275421,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Female",0,0,40,"United-States","<=50K" +61,"Private",213321,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",157747,"Assoc-acdm",12,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",182314,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +70,"Private",220589,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +55,"?",208640,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States",">50K" +46,"Private",124071,"Masters",14,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +35,"Federal-gov",20469,"Some-college",10,"Divorced","Exec-managerial","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +31,"Private",154227,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States",">50K" +37,"Private",105044,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States",">50K" +43,"Private",35910,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,43,"United-States",">50K" +23,"Private",189203,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",19700,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +45,"Private",106113,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",256263,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"?",202498,"7th-8th",4,"Separated","?","Not-in-family","White","Male",0,0,40,"Guatemala","<=50K" +38,"Private",120074,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",122922,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +42,"Local-gov",222596,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",107302,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"India","<=50K" +36,"Private",156400,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",53373,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +22,"Private",58916,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +45,"Local-gov",167159,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",283806,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"Private",140426,"1st-4th",2,"Married-spouse-absent","Other-service","Not-in-family","White","Male",0,0,35,"?","<=50K" +41,"Private",33310,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Self-emp-not-inc",202560,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,35,"United-States","<=50K" +25,"Self-emp-not-inc",60828,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Female",0,0,50,"United-States","<=50K" +53,"State-gov",153486,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"Local-gov",167536,"Assoc-acdm",12,"Widowed","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +30,"Local-gov",370990,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",198867,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Local-gov",174924,"Some-college",10,"Divorced","Protective-serv","Unmarried","White","Male",0,0,48,"Germany","<=50K" +30,"Private",175856,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States","<=50K" +41,"Private",169628,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","Black","Female",0,0,40,"?","<=50K" +29,"?",125159,"Some-college",10,"Never-married","?","Not-in-family","Black","Male",0,0,36,"?","<=50K" +31,"Private",220690,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +59,"Self-emp-not-inc",116878,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"Greece","<=50K" +33,"Self-emp-not-inc",134737,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +49,"State-gov",122177,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Federal-gov",69614,"10th",6,"Separated","Craft-repair","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +28,"Private",299422,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +81,"?",162882,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +24,"Private",112854,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +32,"Self-emp-not-inc",33417,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +47,"Federal-gov",224559,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States",">50K" +44,"?",468706,"HS-grad",9,"Married-civ-spouse","?","Husband","Black","Male",0,0,40,"United-States","<=50K" +24,"Private",357028,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",186303,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",127749,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +22,"Private",291386,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",138054,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","Other","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",174533,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",200835,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",108658,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +43,"Private",180985,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +25,"Private",34803,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,20,"United-States","<=50K" +59,"Private",75867,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +29,"Private",156819,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,35,"United-States","<=50K" +30,"Private",61272,"9th",5,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"Portugal","<=50K" +24,"Private",39827,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Wife","Other","Female",0,0,40,"Puerto-Rico","<=50K" +38,"Private",130007,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",80324,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +30,"Private",140869,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +73,"Local-gov",181902,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,10,"Poland",">50K" +30,"Private",287908,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +33,"Private",309630,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",28225,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,58,"United-States","<=50K" +18,"Private",39222,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",122272,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Self-emp-inc",198400,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,60,"United-States","<=50K" +62,"?",73091,"7th-8th",4,"Widowed","?","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +22,"Private",208946,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",348416,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",379046,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +29,"Private",183887,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",127961,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Private",211129,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +29,"Local-gov",187649,"HS-grad",9,"Separated","Protective-serv","Other-relative","White","Female",0,0,40,"United-States","<=50K" +49,"Federal-gov",94754,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",231826,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +28,"Private",142764,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +22,"Private",126822,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,60,"United-States","<=50K" +37,"Private",188069,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",284395,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +49,"Private",31267,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",161444,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Columbia","<=50K" +25,"Private",144483,"HS-grad",9,"Separated","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",133655,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"State-gov",112074,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +21,"Private",249727,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,22,"United-States","<=50K" +18,"Private",165754,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +30,"Local-gov",172822,"Assoc-voc",11,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",288433,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +40,"Private",33331,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +43,"Private",168071,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,44,"United-States","<=50K" +45,"Private",207277,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +29,"Private",130620,"Some-college",10,"Married-spouse-absent","Sales","Own-child","Asian-Pac-Islander","Female",0,0,26,"India","<=50K" +40,"Private",136244,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +43,"Private",972354,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,48,"United-States","<=50K" +20,"Private",245297,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +32,"State-gov",71151,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,20,"United-States","<=50K" +19,"Private",118352,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +21,"Private",117210,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",120068,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",48343,"11th",7,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +52,"Private",84451,"Assoc-voc",11,"Divorced","Other-service","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +51,"?",76437,"Some-college",10,"Divorced","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",281704,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +54,"Private",123011,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +50,"Private",104729,"HS-grad",9,"Divorced","Machine-op-inspct","Other-relative","White","Female",0,0,48,"United-States","<=50K" +29,"Private",110134,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"Private",186067,"10th",6,"Never-married","Tech-support","Own-child","White","Male",0,0,10,"United-States","<=50K" +47,"Private",214702,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,37,"Puerto-Rico","<=50K" +46,"Private",384795,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +30,"Private",175931,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,44,"United-States","<=50K" +58,"Private",366324,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,30,"United-States","<=50K" +48,"Private",118717,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",219835,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"Mexico","<=50K" +23,"Private",176486,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,36,"United-States","<=50K" +45,"Private",273435,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",182661,"Some-college",10,"Never-married","Sales","Own-child","Black","Male",0,0,20,"United-States","<=50K" +26,"Private",212304,"7th-8th",4,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,48,"United-States","<=50K" +50,"Local-gov",133963,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States",">50K" +49,"Private",165152,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States",">50K" +26,"Private",274724,"Some-college",10,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"Nicaragua","<=50K" +47,"Private",196707,"Prof-school",15,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"?",26620,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"Private",361481,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"?","<=50K" +28,"Self-emp-not-inc",214689,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",174907,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",348099,"10th",6,"Divorced","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +30,"?",104965,"9th",5,"Never-married","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +31,"Private",31600,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",286282,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States","<=50K" +33,"Private",238912,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +37,"Private",197429,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States",">50K" +48,"Private",47343,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",249957,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Private",175942,"HS-grad",9,"Divorced","Priv-house-serv","Not-in-family","White","Female",0,0,40,"France","<=50K" +33,"Private",142675,"Bachelors",13,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +51,"Federal-gov",190333,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",196396,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",166740,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Local-gov",174533,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",210867,"7th-8th",4,"Never-married","Farming-fishing","Own-child","White","Male",0,0,50,"?","<=50K" +40,"Private",144067,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",106964,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",178136,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +38,"Private",196554,"Prof-school",15,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States",">50K" +40,"Self-emp-not-inc",403550,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Private",498216,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",192755,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,20,"United-States",">50K" +20,"?",53738,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,60,"United-States","<=50K" +33,"Private",156192,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +45,"Private",189802,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",179171,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,38,"Germany","<=50K" +32,"Private",77634,"11th",7,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +23,"Private",189830,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,50,"United-States","<=50K" +19,"Private",127190,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +44,"?",174147,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",138107,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,35,"United-States","<=50K" +44,"Self-emp-inc",269733,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +19,"Private",318822,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +48,"Private",48885,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +45,"Private",205424,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States",">50K" +40,"Private",173858,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,42,"Cambodia","<=50K" +34,"Private",202450,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +20,"Private",154779,"Some-college",10,"Never-married","Sales","Other-relative","Other","Female",0,0,40,"United-States","<=50K" +33,"Private",180551,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",177522,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +23,"Private",277328,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,32,"Cuba","<=50K" +34,"Private",112584,"10th",6,"Divorced","Other-service","Unmarried","White","Female",0,0,38,"United-States","<=50K" +48,"State-gov",85384,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +32,"?",123971,"11th",7,"Divorced","?","Not-in-family","White","Female",0,0,49,"United-States","<=50K" +42,"Private",69019,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +22,"Private",112847,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",52900,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,42,"United-States",">50K" +42,"Private",37937,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +45,"Private",59380,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +47,"Private",114770,"HS-grad",9,"Divorced","Other-service","Own-child","White","Female",0,0,32,"United-States","<=50K" +29,"Private",216481,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +34,"Private",176469,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +34,"Private",176831,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States",">50K" +39,"Federal-gov",410034,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",93662,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,24,"United-States","<=50K" +42,"Self-emp-inc",144236,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +48,"Private",240917,"11th",7,"Separated","Other-service","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +51,"Private",243361,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +44,"Self-emp-not-inc",35166,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,90,"United-States","<=50K" +46,"Self-emp-inc",182655,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +32,"Private",272944,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",228686,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +33,"Private",236818,"Assoc-voc",11,"Never-married","Prof-specialty","Unmarried","Black","Female",0,0,26,"United-States","<=50K" +47,"Self-emp-not-inc",117865,"HS-grad",9,"Married-AF-spouse","Craft-repair","Husband","White","Male",0,0,90,"United-States","<=50K" +64,"Self-emp-not-inc",106538,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +62,"Private",153891,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Private",190909,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",191002,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"Poland","<=50K" +42,"Private",89073,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States","<=50K" +55,"Private",259532,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"?",189282,"HS-grad",9,"Married-civ-spouse","?","Not-in-family","White","Female",0,0,27,"United-States","<=50K" +42,"Private",132481,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +30,"Private",205659,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"Thailand",">50K" +32,"Private",182323,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",152246,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +47,"Private",155659,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +33,"Private",155198,"9th",5,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +48,"Self-emp-not-inc",100931,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",162945,"7th-8th",4,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +31,"Federal-gov",334346,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",181597,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-not-inc",133969,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,63,"South","<=50K" +50,"Private",210217,"Bachelors",13,"Divorced","Sales","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +49,"Private",169711,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Germany",">50K" +19,"Private",271521,"HS-grad",9,"Never-married","Other-service","Other-relative","Asian-Pac-Islander","Male",0,0,24,"United-States","<=50K" +18,"Private",51255,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,15,"United-States","<=50K" +44,"Self-emp-not-inc",26669,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,99,"United-States","<=50K" +54,"Private",194580,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"State-gov",177974,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +27,"State-gov",315640,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,20,"China","<=50K" +50,"Self-emp-inc",136913,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +43,"State-gov",230961,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",167062,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +47,"Private",120131,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",243368,"Preschool",1,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"Mexico","<=50K" +30,"Private",171876,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +19,"Private",136866,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,45,"United-States","<=50K" +55,"Private",185459,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +67,"?",81761,"HS-grad",9,"Divorced","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +31,"Private",43716,"Assoc-voc",11,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,43,"United-States","<=50K" +30,"Private",220939,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"?",148657,"Preschool",1,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"Mexico","<=50K" +51,"Federal-gov",40808,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Amer-Indian-Eskimo","Female",0,0,43,"United-States","<=50K" +34,"Private",183473,"HS-grad",9,"Divorced","Transport-moving","Own-child","White","Female",0,0,40,"United-States","<=50K" +59,"Private",108496,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +50,"Private",204838,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,38,"United-States","<=50K" +29,"Private",132686,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +17,"State-gov",117906,"10th",6,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",304386,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +52,"?",248113,"Preschool",1,"Married-spouse-absent","?","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +18,"?",215463,"12th",8,"Never-married","?","Own-child","White","Female",0,0,25,"United-States","<=50K" +32,"Private",259719,"Some-college",10,"Divorced","Handlers-cleaners","Unmarried","Black","Male",0,0,40,"Nicaragua","<=50K" +25,"?",35829,"Some-college",10,"Divorced","?","Unmarried","White","Female",0,0,50,"United-States","<=50K" +34,"Private",248795,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +37,"Local-gov",128054,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Self-emp-inc",113543,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",252153,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +45,"Federal-gov",45891,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Male",0,0,42,"United-States","<=50K" +30,"Private",112263,"11th",7,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",47791,"12th",8,"Divorced","Other-service","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +41,"Private",202980,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,4,"Peru","<=50K" +21,"Private",34918,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +48,"Private",91251,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,30,"China","<=50K" +34,"Private",306215,"Assoc-voc",11,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",203570,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",355918,"Bachelors",13,"Separated","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +35,"Self-emp-not-inc",198841,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +42,"Private",282964,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",312197,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,75,"Mexico",">50K" +32,"Private",200246,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",182771,"Some-college",10,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +23,"Private",199908,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",172104,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","Other","Male",0,0,40,"India",">50K" +53,"Self-emp-not-inc",35295,"Bachelors",13,"Never-married","Sales","Unmarried","White","Male",0,0,60,"United-States",">50K" +27,"Private",216858,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +27,"Private",332187,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,65,"United-States","<=50K" +57,"Private",255109,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +17,"Private",111332,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +59,"Local-gov",238431,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +34,"Private",131552,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +30,"Private",110239,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +31,"State-gov",255830,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,45,"United-States","<=50K" +18,"?",175648,"11th",7,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",82998,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +19,"Private",164320,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Self-emp-not-inc",263498,"Assoc-voc",11,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",162381,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Local-gov",229651,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",357348,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,50,"United-States","<=50K" +19,"Private",269657,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +38,"Local-gov",82880,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,15,"United-States","<=50K" +19,"Private",389755,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,16,"United-States","<=50K" +41,"Private",207685,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"?","<=50K" +24,"?",196388,"Assoc-acdm",12,"Never-married","?","Not-in-family","White","Male",0,0,12,"United-States","<=50K" +24,"Private",50341,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",214134,"10th",6,"Never-married","Transport-moving","Not-in-family","Amer-Indian-Eskimo","Male",0,0,84,"United-States","<=50K" +45,"Private",114032,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +45,"Private",192053,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +48,"Private",240231,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Japan",">50K" +42,"Private",44402,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +35,"Self-emp-not-inc",191503,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",163530,"HS-grad",9,"Divorced","Other-service","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +51,"Local-gov",136823,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,32,"United-States","<=50K" +59,"Private",121912,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Local-gov",58624,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Local-gov",74056,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +57,"Private",182028,"Assoc-acdm",12,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +40,"Private",209040,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",206046,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",182494,"7th-8th",4,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Private",185057,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,35,"Scotland","<=50K" +60,"Private",147473,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"?",388811,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Private",221912,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",48189,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +29,"State-gov",382272,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",48347,"Bachelors",13,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",249571,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +79,"Private",121318,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,20,"United-States","<=50K" +29,"Private",185019,"12th",8,"Never-married","Other-service","Not-in-family","Other","Male",0,0,40,"United-States","<=50K" +60,"Private",27886,"7th-8th",4,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +58,"Private",94741,"12th",8,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,24,"United-States","<=50K" +44,"Private",191256,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States",">50K" +47,"Private",256866,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States","<=50K" +59,"Private",197148,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,24,"United-States",">50K" +37,"Private",312271,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +21,"Private",118657,"HS-grad",9,"Separated","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +68,"Private",224338,"Assoc-voc",11,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"?",234970,"Some-college",10,"Never-married","?","Own-child","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",227915,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Female",0,0,33,"United-States","<=50K" +45,"Self-emp-not-inc",160962,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +22,"Private",188950,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",201328,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",218678,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,49,"United-States","<=50K" +23,"Private",184255,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +39,"Federal-gov",200968,"Some-college",10,"Married-civ-spouse","Adm-clerical","Other-relative","White","Male",0,0,45,"United-States",">50K" +26,"Private",102264,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",300584,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +22,"Private",208946,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,25,"United-States","<=50K" +36,"Private",105021,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +20,"Private",124751,"Some-college",10,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,20,"United-States","<=50K" +18,"Private",274057,"11th",7,"Never-married","Other-service","Own-child","Black","Male",0,0,8,"United-States","<=50K" +38,"Private",132879,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Self-emp-inc",260960,"Bachelors",13,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +56,"Private",208415,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","Black","Male",0,0,40,"?","<=50K" +42,"Private",356934,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",154410,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Private",35378,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +32,"Private",73621,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,42,"United-States","<=50K" +66,"Private",217198,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,10,"United-States","<=50K" +22,"Private",157332,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +51,"Private",202956,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",173495,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +39,"Private",444219,"HS-grad",9,"Married-civ-spouse","Craft-repair","Wife","Black","Female",0,0,45,"United-States","<=50K" +48,"Private",125120,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,37,"United-States","<=50K" +20,"Private",190429,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"?",190303,"Assoc-acdm",12,"Never-married","?","Other-relative","White","Male",0,0,40,"United-States","<=50K" +29,"Federal-gov",208534,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,80,"United-States","<=50K" +36,"Self-emp-not-inc",343721,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,30,"?",">50K" +35,"Self-emp-inc",196373,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +31,"Private",433788,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +48,"State-gov",122086,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",137314,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +40,"Self-emp-not-inc",33068,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"Private",210688,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,15,"United-States","<=50K" +37,"State-gov",103474,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +65,"Private",115880,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Self-emp-not-inc",233933,"10th",6,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +42,"Private",52781,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",586657,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Japan",">50K" +62,"Private",113080,"7th-8th",4,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",251905,"Assoc-voc",11,"Never-married","Exec-managerial","Own-child","White","Male",0,0,50,"United-States","<=50K" +76,"Self-emp-not-inc",225964,"Some-college",10,"Widowed","Sales","Not-in-family","White","Male",0,0,8,"United-States","<=50K" +20,"?",194096,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",263831,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",133136,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",121634,"10th",6,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"Mexico","<=50K" +22,"Self-emp-inc",40767,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Federal-gov",355789,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,50,"United-States","<=50K" +43,"Local-gov",311914,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",91189,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +44,"Federal-gov",344060,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",113823,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",76107,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States",">50K" +23,"Private",117618,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +39,"Private",238008,"HS-grad",9,"Widowed","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +32,"Private",136480,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +19,"Private",351040,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"Puerto-Rico","<=50K" +35,"Private",1226583,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,52,"United-States",">50K" +23,"Private",195767,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",187540,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",79372,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",226665,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,42,"United-States",">50K" +52,"Private",213209,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Private",211005,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,60,"United-States","<=50K" +24,"Private",96178,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Private",110713,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Self-emp-not-inc",225456,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Private",180309,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +62,"Self-emp-not-inc",39630,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",273828,"5th-6th",3,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +56,"Private",172071,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"Jamaica","<=50K" +28,"Private",218887,"HS-grad",9,"Never-married","Farming-fishing","Unmarried","White","Female",0,0,35,"United-States","<=50K" +23,"Private",664670,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +43,"Private",209149,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +26,"Private",84619,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",447346,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +55,"Local-gov",37869,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +48,"State-gov",99086,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +38,"Private",326886,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +18,"Private",181755,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +56,"Self-emp-not-inc",249368,"HS-grad",9,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +39,"Self-emp-not-inc",326400,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",504725,"5th-6th",3,"Separated","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"Mexico","<=50K" +36,"Private",88967,"11th",7,"Never-married","Transport-moving","Unmarried","Amer-Indian-Eskimo","Male",0,0,65,"United-States","<=50K" +50,"Private",148953,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",342752,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +57,"Private",220871,"7th-8th",4,"Widowed","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +73,"Private",29675,"HS-grad",9,"Widowed","Other-service","Other-relative","White","Female",0,0,12,"United-States","<=50K" +50,"Federal-gov",183611,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",115215,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,45,"United-States","<=50K" +27,"Private",152231,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +24,"?",41356,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",225142,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Self-emp-not-inc",121313,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",134821,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Private",311350,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",102106,"10th",6,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +47,"Private",427055,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"Mexico","<=50K" +40,"Private",117860,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +58,"Private",285885,"9th",5,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",212800,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",194864,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,18,"United-States","<=50K" +36,"Private",31438,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,43,"United-States","<=50K" +46,"Private",148254,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +69,"Private",113035,"1st-4th",2,"Widowed","Priv-house-serv","Not-in-family","Black","Female",0,0,4,"United-States","<=50K" +28,"Private",144521,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +20,"Private",172232,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,48,"United-States","<=50K" +25,"Private",191921,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"Private",208463,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +53,"Federal-gov",68985,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",22418,"9th",5,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +57,"Private",163047,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,38,"United-States","<=50K" +20,"?",124954,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +47,"Private",197702,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",166415,"HS-grad",9,"Never-married","Transport-moving","Unmarried","White","Male",0,0,52,"United-States","<=50K" +50,"State-gov",116211,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,52,"United-States",">50K" +20,"Private",33644,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +46,"Private",73019,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +54,"Private",169182,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,38,"Puerto-Rico","<=50K" +53,"Private",20438,"Some-college",10,"Separated","Exec-managerial","Unmarried","Amer-Indian-Eskimo","Female",0,0,15,"United-States","<=50K" +21,"Private",109869,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,30,"United-States","<=50K" +58,"Private",316849,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",208043,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +61,"Private",153790,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +56,"State-gov",153451,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +59,"Private",96840,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +72,"Private",192732,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,20,"United-States","<=50K" +33,"Private",209101,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",146919,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +46,"Local-gov",192323,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,38,"United-States",">50K" +48,"Private",217019,"HS-grad",9,"Never-married","Prof-specialty","Unmarried","Black","Female",0,0,28,"United-States","<=50K" +33,"Private",198211,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",222490,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Private",106758,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +31,"Private",561334,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",203710,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Local-gov",203322,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +46,"State-gov",312015,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +25,"Private",209428,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,25,"El-Salvador","<=50K" +17,"Private",114420,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +35,"Private",100375,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +33,"Self-emp-not-inc",42485,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +37,"Private",130620,"12th",8,"Married-civ-spouse","Sales","Wife","Asian-Pac-Islander","Female",0,0,33,"?","<=50K" +39,"Local-gov",134367,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +42,"Private",147099,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +45,"Private",119904,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Female",0,0,50,"United-States",">50K" +47,"Self-emp-inc",105779,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States",">50K" +64,"Private",165020,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +43,"?",142030,"HS-grad",9,"Divorced","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",241360,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?","<=50K" +31,"Private",162572,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",35917,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-inc",35723,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Private",194773,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",62155,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Male",0,0,35,"United-States","<=50K" +46,"Private",174370,"Some-college",10,"Separated","Sales","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +26,"Private",161007,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,80,"United-States","<=50K" +24,"Private",270517,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"Mexico","<=50K" +43,"Private",163847,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States",">50K" +40,"Private",193882,"Assoc-voc",11,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +61,"Private",160037,"7th-8th",4,"Divorced","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +34,"Federal-gov",189944,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,72,"United-States","<=50K" +85,"Private",115364,"HS-grad",9,"Widowed","Sales","Unmarried","White","Male",0,0,35,"United-States","<=50K" +41,"Private",163174,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",214399,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +60,"Private",156616,"HS-grad",9,"Widowed","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",204862,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +34,"?",55921,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",153082,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +45,"Local-gov",195418,"Masters",14,"Divorced","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +21,"Local-gov",276840,"12th",8,"Never-married","Other-service","Own-child","Black","Male",0,0,20,"United-States","<=50K" +50,"Self-emp-inc",119099,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,99,"United-States",">50K" +41,"Self-emp-not-inc",83411,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",198992,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,33,"United-States","<=50K" +45,"Private",337825,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +34,"Private",192002,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",189346,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",231962,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Male",0,0,40,"United-States","<=50K" +48,"Private",200471,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +41,"Private",184846,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",233851,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",499001,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"Mexico","<=50K" +65,"Local-gov",125768,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +28,"Private",157624,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Private",146767,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",118291,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,80,"United-States","<=50K" +43,"Private",313181,"HS-grad",9,"Divorced","Adm-clerical","Other-relative","Black","Male",0,0,38,"United-States","<=50K" +31,"Private",87891,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +31,"Private",226443,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +45,"Private",81132,"Some-college",10,"Married-civ-spouse","Craft-repair","Other-relative","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +20,"Private",216436,"Bachelors",13,"Never-married","Sales","Other-relative","Black","Female",0,0,30,"United-States","<=50K" +25,"Private",213412,"Bachelors",13,"Never-married","Tech-support","Unmarried","White","Male",0,0,40,"United-States","<=50K" +36,"Private",179358,"HS-grad",9,"Widowed","Handlers-cleaners","Unmarried","White","Female",0,0,30,"United-States","<=50K" +56,"Private",199763,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +26,"Private",239390,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,18,"United-States","<=50K" +47,"Self-emp-not-inc",173613,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,65,"United-States","<=50K" +40,"Self-emp-inc",37869,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",302845,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,48,"United-States","<=50K" +34,"State-gov",85218,"Masters",14,"Never-married","Prof-specialty","Unmarried","Black","Female",0,0,24,"United-States","<=50K" +37,"Private",48268,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +38,"Private",173968,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +19,"Private",70982,"Assoc-voc",11,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Male",0,0,16,"United-States","<=50K" +49,"Private",166857,"9th",5,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"?",256191,"HS-grad",9,"Never-married","?","Own-child","Black","Female",0,0,25,"United-States","<=50K" +26,"Private",162872,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +82,"Private",152148,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,2,"United-States","<=50K" +40,"Private",139193,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",791084,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +23,"Private",137214,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,37,"United-States","<=50K" +19,"Private",183258,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +67,"Private",154035,"HS-grad",9,"Widowed","Handlers-cleaners","Other-relative","Black","Male",0,0,32,"United-States","<=50K" +41,"Private",213055,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","Other","Female",0,0,50,"United-States","<=50K" +37,"Private",155064,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",33551,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",169995,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +40,"Private",104196,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"State-gov",114055,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",274398,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,20,"United-States","<=50K" +67,"?",244122,"Assoc-voc",11,"Widowed","?","Not-in-family","White","Female",0,0,1,"United-States","<=50K" +49,"Private",196571,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +66,"Private",101607,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +59,"Self-emp-inc",255822,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +72,"Private",195184,"HS-grad",9,"Widowed","Priv-house-serv","Unmarried","White","Female",0,0,12,"Cuba","<=50K" +35,"Federal-gov",245372,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",169583,"Bachelors",13,"Married-AF-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +36,"Private",224531,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",186151,"HS-grad",9,"Separated","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"Private",118693,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +39,"Private",297449,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Self-emp-not-inc",125206,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",393264,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",108140,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +63,"Private",264968,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",318106,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",156025,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"State-gov",149455,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +25,"Private",359985,"5th-6th",3,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,33,"Mexico","<=50K" +44,"State-gov",165108,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",115178,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +21,"Private",149224,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,30,"United-States","<=50K" +41,"Local-gov",352056,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",174717,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +75,"?",173064,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,6,"United-States","<=50K" +52,"Self-emp-not-inc",135716,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +47,"Private",44216,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +24,"Private",178255,"Some-college",10,"Married-civ-spouse","Priv-house-serv","Wife","White","Female",0,0,40,"?","<=50K" +30,"State-gov",70617,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,10,"China","<=50K" +40,"Private",356934,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +27,"Private",271714,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +26,"Private",247025,"HS-grad",9,"Never-married","Protective-serv","Unmarried","White","Male",0,0,44,"United-States","<=50K" +32,"Private",107417,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +36,"State-gov",116554,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",917220,"12th",8,"Never-married","Transport-moving","Own-child","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",430084,"Some-college",10,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",202937,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"Poland","<=50K" +27,"Private",62737,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",508548,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Self-emp-not-inc",381931,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,55,"United-States","<=50K" +29,"Private",246974,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",105431,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",146311,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",159869,"Doctorate",16,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +21,"Private",204641,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",66297,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Philippines",">50K" +38,"Private",227615,"1st-4th",2,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +66,"?",107744,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",263340,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +18,"Private",141918,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,22,"United-States","<=50K" +37,"Private",294292,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",128736,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Local-gov",511289,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,48,"United-States",">50K" +27,"Private",302406,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Local-gov",101517,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +54,"State-gov",161334,"Masters",14,"Married-spouse-absent","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"China","<=50K" +24,"Self-emp-inc",189148,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",103111,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +48,"Self-emp-not-inc",51620,"Bachelors",13,"Separated","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +23,"Private",31606,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",34292,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,38,"United-States","<=50K" +21,"Private",107882,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Female",0,0,9,"United-States","<=50K" +18,"Private",39529,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,32,"United-States","<=50K" +18,"Private",135315,"9th",5,"Never-married","Sales","Own-child","Other","Female",0,0,32,"United-States","<=50K" +29,"Private",107812,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",229729,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",111891,"HS-grad",9,"Separated","Machine-op-inspct","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +32,"Private",340917,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"Private",202952,"10th",6,"Divorced","Other-service","Not-in-family","Black","Female",0,0,24,"United-States","<=50K" +79,"Private",333230,"HS-grad",9,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",0,0,6,"United-States","<=50K" +34,"Private",114955,"Assoc-acdm",12,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",159869,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Self-emp-not-inc",57758,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +29,"Private",207064,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Private",151364,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Private",102828,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Greece","<=50K" +20,"?",210029,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",142519,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"Private",104455,"Bachelors",13,"Married-spouse-absent","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +77,"Self-emp-inc",192230,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",292592,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +27,"Private",330132,"Bachelors",13,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States",">50K" +22,"Private",51111,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Local-gov",258037,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Cuba",">50K" +35,"State-gov",349066,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +62,"?",191188,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",146497,"Some-college",10,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,55,"United-States","<=50K" +38,"Private",175120,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",416577,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,45,"United-States","<=50K" +29,"Private",253814,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +33,"Private",159247,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Self-emp-not-inc",102471,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,80,"Puerto-Rico","<=50K" +42,"Private",213464,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",211968,"Assoc-voc",11,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +43,"Federal-gov",32016,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +69,"Private",512992,"11th",7,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,45,"United-States","<=50K" +39,"Private",135020,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",109133,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Portugal","<=50K" +28,"Private",142712,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Federal-gov",76900,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",112176,"Some-college",10,"Divorced","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +43,"Federal-gov",262233,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +49,"Private",122066,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"Hungary","<=50K" +28,"Private",194690,"7th-8th",4,"Separated","Other-service","Own-child","White","Male",0,0,60,"Mexico","<=50K" +35,"Local-gov",308945,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",46699,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +45,"Private",377757,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",102147,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",113770,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +35,"Private",139012,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +45,"Private",148900,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Federal-gov",329426,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +64,"Self-emp-inc",181408,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,10,"United-States","<=50K" +44,"Local-gov",101950,"Prof-school",15,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",32537,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",209547,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",202373,"Some-college",10,"Never-married","Sales","Own-child","Black","Male",0,0,25,"United-States","<=50K" +22,"Private",138768,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"Private",143482,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +53,"Private",200190,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,80,"United-States",">50K" +23,"Private",148315,"Some-college",10,"Separated","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",270517,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"Mexico","<=50K" +40,"Private",53506,"Bachelors",13,"Divorced","Craft-repair","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",105693,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",189589,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",164574,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +37,"Private",185744,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,20,"United-States","<=50K" +40,"Local-gov",33155,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",233571,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Private",211253,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",137895,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +62,"State-gov",159699,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,38,"United-States","<=50K" +31,"Private",295922,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",175856,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +24,"Private",216129,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +62,"Local-gov",407669,"7th-8th",4,"Widowed","Other-service","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +43,"Local-gov",214242,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",285457,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,50,"United-States","<=50K" +22,"?",246386,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",142751,"10th",6,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"Local-gov",283635,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Private",76482,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"State-gov",431745,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +33,"Private",67006,"10th",6,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +23,"Private",240398,"Bachelors",13,"Never-married","Sales","Not-in-family","Black","Male",0,0,15,"United-States","<=50K" +33,"Federal-gov",182714,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,65,"United-States",">50K" +50,"Federal-gov",172046,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",185177,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,43,"United-States","<=50K" +21,"Private",115895,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +23,"Private",184589,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,21,"United-States","<=50K" +32,"Private",282611,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"Private",218649,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"State-gov",157541,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +70,"Private",145419,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,5,"United-States","<=50K" +34,"Private",122616,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,84,"United-States",">50K" +53,"Private",204584,"Masters",14,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",117210,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,45,"United-States","<=50K" +37,"Private",69481,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",29312,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,80,"United-States",">50K" +57,"Private",120302,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +65,"?",111916,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",182227,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +30,"Private",219110,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,46,"United-States","<=50K" +31,"Private",200192,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"Germany","<=50K" +19,"Private",427862,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +23,"State-gov",33551,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,38,"United-States","<=50K" +44,"Private",164043,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"?",116632,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,45,"United-States",">50K" +42,"Private",175133,"Some-college",10,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",289731,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",256362,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",282612,"Assoc-voc",11,"Never-married","Tech-support","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +21,"Private",73679,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Private",237824,"HS-grad",9,"Married-spouse-absent","Priv-house-serv","Other-relative","Black","Female",0,0,60,"Jamaica","<=50K" +36,"Local-gov",357720,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",155489,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"Poland","<=50K" +44,"Private",138077,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,32,"United-States","<=50K" +42,"Private",183479,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",103596,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,99,"United-States","<=50K" +33,"Private",172304,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",313853,"Bachelors",13,"Divorced","Other-service","Unmarried","Black","Male",0,0,45,"United-States",">50K" +17,"Private",294485,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +20,"Private",637080,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +32,"Private",385959,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +33,"Self-emp-not-inc",116539,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",129263,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,60,"United-States","<=50K" +60,"Private",141253,"10th",6,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +35,"State-gov",35626,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,15,"United-States","<=50K" +43,"Federal-gov",94937,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +46,"Private",220269,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",214604,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,42,"United-States",">50K" +27,"Private",81540,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",24013,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,84,"United-States",">50K" +22,"Private",124940,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Amer-Indian-Eskimo","Female",0,0,44,"United-States","<=50K" +33,"State-gov",313729,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +61,"Private",192237,"10th",6,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"?",168524,"Assoc-voc",11,"Married-civ-spouse","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",113324,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States",">50K" +22,"Private",215477,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",199903,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",431861,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",274679,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +28,"Private",206125,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Local-gov",221740,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,30,"United-States",">50K" +58,"Private",202652,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +39,"Private",348960,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",171876,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +59,"Private",157932,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Private",201344,"Bachelors",13,"Divorced","Craft-repair","Own-child","White","Female",0,0,20,"United-States","<=50K" +38,"Private",354739,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,36,"Philippines",">50K" +34,"Private",40067,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",326862,"Some-college",10,"Divorced","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +48,"Local-gov",189762,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +65,"?",149049,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",226246,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +23,"Private",38251,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +33,"Private",196385,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,37,"United-States",">50K" +38,"Self-emp-not-inc",217054,"Some-college",10,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",104973,"Masters",14,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +40,"State-gov",34218,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Local-gov",292962,"HS-grad",9,"Never-married","Craft-repair","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +45,"Private",235924,"Bachelors",13,"Divorced","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",98656,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +70,"Private",102610,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +32,"Local-gov",296466,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +33,"Private",323069,"Assoc-voc",11,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",184756,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Local-gov",233993,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,15,"United-States","<=50K" +22,"Private",130724,"Some-college",10,"Never-married","Sales","Own-child","Black","Male",0,0,25,"United-States","<=50K" +55,"Private",113912,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,20,"United-States","<=50K" +29,"Private",216479,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +62,"Private",135480,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,16,"United-States","<=50K" +22,"Private",204160,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +64,"State-gov",114650,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",240172,"Bachelors",13,"Never-married","Exec-managerial","Other-relative","White","Male",0,0,50,"United-States","<=50K" +28,"Private",184831,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",124590,"HS-grad",9,"Never-married","Exec-managerial","Other-relative","White","Male",0,0,40,"United-States","<=50K" +26,"Private",202033,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",156874,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,27,"United-States","<=50K" +48,"Local-gov",334409,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +36,"Private",311255,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"Haiti","<=50K" +23,"Private",214227,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +41,"Private",115849,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"State-gov",671292,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,38,"United-States",">50K" +53,"Private",31460,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",141824,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",137952,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Other","Male",0,0,40,"Puerto-Rico","<=50K" +46,"Private",174426,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",169955,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,36,"Puerto-Rico","<=50K" +43,"Self-emp-not-inc",48087,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +37,"State-gov",210452,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States","<=50K" +22,"Local-gov",134181,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,50,"United-States","<=50K" +51,"Federal-gov",45487,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,80,"United-States","<=50K" +47,"Private",183522,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,40,"United-States",">50K" +40,"Private",199303,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",83064,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"?",134997,"Some-college",10,"Separated","?","Unmarried","White","Female",0,0,20,"United-States","<=50K" +30,"Private",44419,"Some-college",10,"Never-married","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",442612,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States",">50K" +31,"Local-gov",158092,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +31,"Private",374833,"1st-4th",2,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +30,"Private",112650,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",183390,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +27,"Private",207418,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +22,"?",335453,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,16,"United-States","<=50K" +29,"Private",243660,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",54243,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +54,"Private",50385,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","Black","Female",0,0,45,"United-States",">50K" +47,"State-gov",187581,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,48,"United-States",">50K" +34,"Private",37380,"HS-grad",9,"Married-spouse-absent","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",247025,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"?",29231,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,35,"United-States","<=50K" +23,"State-gov",101094,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,60,"United-States","<=50K" +42,"Local-gov",176716,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",118429,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +52,"Federal-gov",221532,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,45,"United-States",">50K" +22,"?",120572,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Local-gov",124680,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",153160,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"State-gov",142856,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",277700,"Preschool",1,"Never-married","Other-service","Own-child","White","Male",0,0,32,"United-States","<=50K" +55,"Self-emp-inc",67433,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +47,"Private",121124,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",394447,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,33,"United-States",">50K" +36,"Private",79649,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",203763,"Doctorate",16,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,80,"United-States","<=50K" +21,"?",494638,"Assoc-acdm",12,"Never-married","?","Own-child","White","Male",0,0,15,"United-States","<=50K" +48,"Private",162816,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Private",109117,"Assoc-voc",11,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,45,"United-States","<=50K" +24,"Private",32732,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"Self-emp-not-inc",217692,"HS-grad",9,"Widowed","Craft-repair","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +20,"Private",34590,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,60,"United-States","<=50K" +36,"Private",91037,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +44,"Private",171484,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",36990,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,52,"United-States","<=50K" +33,"Private",198211,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"?",30475,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",245790,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +60,"Private",182687,"Assoc-acdm",12,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Local-gov",247807,"Assoc-voc",11,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States",">50K" +58,"Private",163113,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,35,"United-States",">50K" +50,"Private",180522,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +23,"Local-gov",203353,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,12,"United-States","<=50K" +30,"Private",87469,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"?",216563,"11th",7,"Never-married","?","Other-relative","White","Male",0,0,40,"United-States","<=50K" +49,"Local-gov",173584,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +34,"Private",319854,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"Taiwan",">50K" +37,"Federal-gov",408229,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",431307,"10th",6,"Married-civ-spouse","Protective-serv","Wife","Black","Female",0,0,50,"United-States","<=50K" +37,"Private",134088,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",246396,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Mexico","<=50K" +34,"Private",159255,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +34,"Private",106014,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",120130,"Some-college",10,"Separated","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"State-gov",203849,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,19,"United-States","<=50K" +24,"Private",207940,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,30,"United-States","<=50K" +28,"Private",302406,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +69,"?",171050,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,9,"United-States","<=50K" +32,"Private",459007,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,90,"United-States","<=50K" +58,"Private",372181,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States",">50K" +47,"Self-emp-not-inc",172034,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,75,"United-States",">50K" +35,"Self-emp-inc",338320,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",353696,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"Canada","<=50K" +46,"Self-emp-not-inc",342907,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,60,"United-States",">50K" +22,"Private",103762,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"State-gov",47570,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",119432,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Local-gov",144165,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Amer-Indian-Eskimo","Male",0,0,30,"United-States","<=50K" +35,"Private",180647,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +35,"State-gov",150488,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",200876,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,16,"United-States","<=50K" +43,"Private",188199,"9th",5,"Divorced","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +53,"State-gov",118793,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Local-gov",204325,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,52,"United-States","<=50K" +29,"Private",256671,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +46,"Private",231515,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,47,"Cuba","<=50K" +24,"Private",100669,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Asian-Pac-Islander","Male",0,0,30,"United-States","<=50K" +30,"Private",88913,"Some-college",10,"Separated","Other-service","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +23,"Private",363219,"Some-college",10,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,6,"United-States","<=50K" +27,"?",291547,"Bachelors",13,"Married-civ-spouse","?","Not-in-family","Other","Female",0,0,6,"Mexico","<=50K" +36,"Private",308945,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",100316,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +33,"Private",296453,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,15,"United-States","<=50K" +66,"Private",298834,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"Canada","<=50K" +45,"Self-emp-not-inc",188694,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +68,"?",29240,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +17,"Private",154908,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,10,"United-States","<=50K" +31,"Private",22201,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States",">50K" +46,"Private",216999,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States",">50K" +40,"Private",186916,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",116677,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Private",95763,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +42,"Private",266710,"Some-college",10,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,41,"United-States","<=50K" +46,"Private",117849,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +30,"Private",242460,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +33,"Self-emp-not-inc",202729,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",181652,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",174760,"Assoc-acdm",12,"Married-spouse-absent","Farming-fishing","Unmarried","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +34,"Private",56121,"11th",7,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +40,"Private",390369,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",149726,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",51262,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",190350,"12th",8,"Never-married","Other-service","Unmarried","Black","Female",0,0,35,"?","<=50K" +36,"Private",154835,"HS-grad",9,"Separated","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +36,"Private",194630,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +18,"Self-emp-not-inc",212207,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,11,"United-States","<=50K" +27,"Private",204788,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",158688,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",97723,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",193026,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Self-emp-not-inc",257250,"7th-8th",4,"Never-married","Farming-fishing","Own-child","White","Male",0,0,75,"United-States","<=50K" +48,"Private",355978,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",376929,"5th-6th",3,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +47,"State-gov",123219,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +41,"Private",82778,"1st-4th",2,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +61,"Self-emp-not-inc",115882,"1st-4th",2,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +64,"Private",103021,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",297767,"Some-college",10,"Separated","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +44,"Private",259479,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Male",0,0,50,"United-States","<=50K" +20,"Private",167787,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +23,"Local-gov",40021,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,70,"United-States","<=50K" +52,"Private",245275,"10th",6,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"United-States","<=50K" +43,"Private",37402,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +32,"Private",103608,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +63,"Private",137192,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +29,"Private",137618,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,41,"United-States",">50K" +42,"Self-emp-inc",96509,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,60,"Taiwan","<=50K" +65,"Private",196174,"10th",6,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +24,"Private",172612,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",141186,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",228190,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +40,"Self-emp-inc",190290,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"?",">50K" +38,"Federal-gov",307404,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",152436,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +39,"Private",282153,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +29,"?",41281,"Bachelors",13,"Married-spouse-absent","?","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +42,"Private",162003,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,36,"United-States",">50K" +36,"Private",190759,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +26,"Private",208122,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +55,"Private",129173,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",287548,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +41,"Private",216116,"HS-grad",9,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"?","<=50K" +24,"Private",146706,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +47,"Private",285200,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-inc",314375,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +44,"Private",203943,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,35,"United-States",">50K" +18,"?",274746,"HS-grad",9,"Never-married","?","Unmarried","White","Female",0,0,20,"United-States","<=50K" +27,"Private",517000,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +36,"Private",66173,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +21,"Private",182823,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +29,"Private",159479,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Other","Male",0,0,55,"United-States","<=50K" +25,"Private",135568,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +73,"Private",333676,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +45,"Private",201699,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",96020,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +43,"Private",176138,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +47,"Private",47496,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +20,"Private",187158,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +22,"Private",249727,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,20,"United-States","<=50K" +76,"Self-emp-not-inc",237624,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,10,"United-States","<=50K" +24,"Private",175254,"Some-college",10,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",42924,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",205950,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",111985,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,58,"United-States","<=50K" +30,"Private",167476,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +40,"Private",221172,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +27,"?",188711,"Some-college",10,"Divorced","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +49,"Private",199448,"Assoc-voc",11,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",313038,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",148431,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Other","Female",0,0,40,"United-States","<=50K" +19,"Private",112432,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,58,"United-States","<=50K" +46,"Private",57914,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",145166,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States","<=50K" +56,"Private",247119,"7th-8th",4,"Widowed","Machine-op-inspct","Unmarried","Other","Female",0,0,40,"Dominican-Republic","<=50K" +53,"Private",196278,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"?",366531,"Assoc-voc",11,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",216481,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",188027,"Some-college",10,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +37,"Private",66686,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",74775,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,30,"Vietnam","<=50K" +65,"?",325537,"Assoc-voc",11,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States",">50K" +30,"Self-emp-not-inc",250499,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,55,"United-States",">50K" +57,"Self-emp-not-inc",192869,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,72,"United-States","<=50K" +44,"Self-emp-inc",121352,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Self-emp-not-inc",123116,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Local-gov",339163,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +59,"Self-emp-not-inc",124771,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +22,"Private",199266,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +39,"Private",190728,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Local-gov",421446,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,50,"United-States",">50K" +61,"Private",215944,"9th",5,"Divorced","Sales","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +24,"Private",72310,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,43,"United-States","<=50K" +25,"Private",57512,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +44,"Private",89413,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Local-gov",28151,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States",">50K" +30,"Private",226943,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +44,"Private",182402,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",305352,"10th",6,"Divorced","Craft-repair","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +63,"Self-emp-inc",189253,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +60,"Private",296485,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",204375,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States",">50K" +49,"Self-emp-not-inc",249585,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States","<=50K" +47,"Private",148995,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +42,"Self-emp-inc",168071,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,43,"United-States",">50K" +53,"Private",194995,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"Italy","<=50K" +28,"?",196630,"Assoc-voc",11,"Separated","?","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +20,"Private",50397,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,35,"United-States","<=50K" +43,"Private",60001,"Bachelors",13,"Divorced","Sales","Unmarried","White","Male",0,0,44,"United-States",">50K" +31,"Private",223046,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +29,"?",44921,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States","<=50K" +24,"Private",154571,"Some-college",10,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Male",0,0,20,"United-States","<=50K" +39,"Private",67136,"Assoc-voc",11,"Separated","Adm-clerical","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +29,"Private",188675,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"Jamaica",">50K" +20,"Private",390817,"5th-6th",3,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,25,"Mexico","<=50K" +23,"?",145964,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",30424,"11th",7,"Separated","Other-service","Unmarried","White","Female",0,0,38,"United-States","<=50K" +53,"Private",548361,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",189148,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,48,"United-States","<=50K" +51,"Self-emp-not-inc",311569,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",187653,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +38,"Private",235379,"Assoc-acdm",12,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,36,"United-States","<=50K" +41,"Private",188615,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Private",322691,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",184698,"10th",6,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"Dominican-Republic","<=50K" +50,"Private",144361,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",130057,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +31,"Self-emp-inc",117963,"Doctorate",16,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",123876,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +37,"Private",248445,"HS-grad",9,"Divorced","Handlers-cleaners","Other-relative","White","Male",0,0,40,"El-Salvador","<=50K" +32,"Private",207172,"Some-college",10,"Never-married","Sales","Other-relative","White","Female",0,0,40,"United-States","<=50K" +62,"Private",134768,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Local-gov",269168,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Other","Male",0,0,40,"?","<=50K" +37,"Private",60722,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Japan",">50K" +41,"Private",648223,"1st-4th",2,"Married-spouse-absent","Farming-fishing","Unmarried","White","Male",0,0,40,"Mexico","<=50K" +56,"Private",298695,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +20,"Private",219835,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +34,"Self-emp-not-inc",313729,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +45,"Private",140644,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +30,"Private",203488,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Self-emp-not-inc",132341,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +27,"Private",161683,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,42,"United-States","<=50K" +38,"Private",312771,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",258102,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"?",24127,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +47,"Private",254367,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +77,"?",185426,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,15,"United-States","<=50K" +43,"Private",152629,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Local-gov",141058,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States","<=50K" +41,"Private",233130,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",406641,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +30,"State-gov",119422,"10th",6,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",255486,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,25,"United-States","<=50K" +22,"Private",161532,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +25,"Private",75759,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,44,"United-States",">50K" +18,"Private",163332,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,22,"United-States","<=50K" +28,"Private",37933,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,48,"United-States","<=50K" +21,"Private",165107,"Some-college",10,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"Private",126011,"Assoc-voc",11,"Divorced","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Federal-gov",56651,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",522881,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"Mexico","<=50K" +32,"Private",191777,"Assoc-voc",11,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,35,"England","<=50K" +27,"Private",132686,"12th",8,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,50,"United-States","<=50K" +55,"Private",201112,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +44,"Private",174283,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",208591,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",126399,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,32,"United-States","<=50K" +50,"Private",142073,"HS-grad",9,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +18,"Private",395567,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +74,"Private",180455,"Bachelors",13,"Widowed","Other-service","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +22,"Private",235853,"9th",5,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",160731,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"State-gov",31935,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,80,"United-States","<=50K" +23,"Private",223019,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +46,"State-gov",248895,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",200323,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +41,"Private",230020,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,40,"United-States","<=50K" +29,"Private",134890,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",162096,"9th",5,"Married-civ-spouse","Machine-op-inspct","Other-relative","Asian-Pac-Islander","Female",0,0,45,"China","<=50K" +51,"Private",103824,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"Haiti","<=50K" +34,"State-gov",61431,"12th",8,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +58,"Private",197319,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +52,"Private",183618,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",263729,"Some-college",10,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +54,"Private",39493,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,20,"United-States","<=50K" +36,"Private",185360,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +25,"Private",132661,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,60,"United-States","<=50K" +20,"Private",266400,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,48,"United-States","<=50K" +23,"Private",433669,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-inc",216473,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +20,"Self-emp-not-inc",217404,"10th",6,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",227778,"Assoc-voc",11,"Never-married","Other-service","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +73,"State-gov",96262,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +67,"Private",247566,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,24,"United-States","<=50K" +56,"Private",139616,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States",">50K" +32,"Private",73585,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",165814,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +37,"Private",108913,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",34975,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +31,"Private",157078,"10th",6,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +59,"Private",232672,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",294295,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-inc",130454,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Local-gov",461678,"10th",6,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"State-gov",252284,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",256737,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Local-gov",96480,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"Germany","<=50K" +25,"Private",234263,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",109952,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Private",262570,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",65716,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +68,"Private",201732,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +66,"Self-emp-not-inc",174788,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +38,"Private",278924,"Bachelors",13,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",101593,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +71,"?",193863,"7th-8th",4,"Widowed","?","Other-relative","White","Female",0,0,16,"Poland","<=50K" +37,"Private",342768,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"State-gov",176727,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",99179,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"State-gov",354104,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,10,"United-States","<=50K" +25,"Private",61956,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +47,"Federal-gov",137917,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States",">50K" +40,"Private",224658,"Some-college",10,"Married-civ-spouse","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +25,"Private",224361,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",362912,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Female",0,0,50,"United-States","<=50K" +23,"Private",218782,"10th",6,"Never-married","Handlers-cleaners","Other-relative","Other","Male",0,0,40,"United-States","<=50K" +28,"Private",103389,"Masters",14,"Divorced","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",308944,"HS-grad",9,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",140092,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",202210,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +52,"Private",416059,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States",">50K" +33,"Self-emp-not-inc",281030,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,94,"United-States","<=50K" +19,"Private",169758,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +41,"Private",139907,"10th",6,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,50,"United-States","<=50K" +18,"Self-emp-inc",119422,"HS-grad",9,"Never-married","Other-service","Unmarried","Asian-Pac-Islander","Female",0,0,30,"India","<=50K" +40,"Private",259307,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +51,"Self-emp-not-inc",74160,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,60,"United-States",">50K" +49,"Private",134797,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"State-gov",41103,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +38,"Local-gov",193026,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +57,"Private",303986,"5th-6th",3,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"Cuba","<=50K" +66,"Private",166461,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,26,"United-States","<=50K" +27,"?",61387,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,15,"United-States","<=50K" +25,"Private",254746,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"?",180976,"10th",6,"Never-married","?","Unmarried","White","Female",0,0,35,"United-States","<=50K" +59,"Self-emp-not-inc",136413,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,48,"United-States","<=50K" +25,"Private",131463,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",218490,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"El-Salvador",">50K" +75,"?",260543,"10th",6,"Widowed","?","Other-relative","Asian-Pac-Islander","Female",0,0,1,"China","<=50K" +21,"?",80680,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Federal-gov",117628,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +32,"State-gov",175931,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",309566,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,20,"United-States","<=50K" +53,"Private",123703,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"?",369678,"HS-grad",9,"Never-married","?","Not-in-family","Other","Male",0,0,30,"United-States","<=50K" +58,"Private",29928,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,36,"United-States","<=50K" +22,"Private",167868,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +23,"Private",235894,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +36,"Private",111545,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States","<=50K" +39,"Private",175972,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,15,"United-States","<=50K" +34,"Local-gov",254270,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Local-gov",185057,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",101345,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States",">50K" +32,"Self-emp-not-inc",97723,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",127601,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +37,"Private",227597,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"?",143995,"Some-college",10,"Never-married","?","Own-child","Black","Male",0,0,20,"United-States","<=50K" +21,"Private",250051,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,10,"United-States","<=50K" +26,"Private",284078,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",163787,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +27,"Private",119170,"11th",7,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +20,"Private",188612,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,38,"Nicaragua","<=50K" +36,"Private",114605,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +31,"?",317761,"Bachelors",13,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",164197,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +54,"Private",329266,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States",">50K" +34,"Local-gov",207383,"Masters",14,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",123598,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States",">50K" +33,"Private",259931,"11th",7,"Separated","Machine-op-inspct","Other-relative","White","Male",0,0,30,"United-States","<=50K" +42,"Private",106900,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",87054,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +37,"Private",82622,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",181659,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",231348,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",276096,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",290560,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +21,"Private",307315,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +39,"State-gov",99156,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",237928,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,39,"United-States","<=50K" +46,"Private",153501,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +47,"?",149700,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,36,"United-States",">50K" +35,"Private",374524,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,75,"United-States",">50K" +60,"Self-emp-not-inc",127805,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",150217,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,24,"Poland","<=50K" +33,"Private",295649,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,40,"China","<=50K" +21,"Private",197182,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",241998,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States",">50K" +48,"Federal-gov",156410,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,50,"United-States",">50K" +58,"Private",473836,"7th-8th",4,"Widowed","Farming-fishing","Other-relative","White","Female",0,0,45,"Guatemala","<=50K" +21,"Private",198431,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",113936,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",318915,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",175406,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,30,"United-States",">50K" +23,"Federal-gov",320294,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +58,"State-gov",400285,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States",">50K" +24,"?",283731,"Bachelors",13,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Local-gov",227154,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +49,"Private",298659,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,15,"Mexico","<=50K" +47,"Private",212120,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +21,"Private",175800,"HS-grad",9,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,55,"United-States","<=50K" +55,"Private",170169,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",344157,"11th",7,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",199441,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",225456,"HS-grad",9,"Never-married","Tech-support","Other-relative","White","Male",0,0,50,"United-States","<=50K" +36,"Private",61178,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",152568,"HS-grad",9,"Widowed","Sales","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +32,"Private",208291,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",224358,"10th",6,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",55176,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"State-gov",152711,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",68684,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",185452,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +23,"Private",173851,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",51424,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",262656,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Private",233194,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States",">50K" +22,"Private",151105,"Some-college",10,"Never-married","Sales","Other-relative","White","Female",0,0,18,"United-States","<=50K" +39,"Private",317434,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Local-gov",745768,"Some-college",10,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,45,"United-States","<=50K" +19,"Private",69927,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,16,"United-States","<=50K" +26,"Private",302603,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,45,"United-States","<=50K" +52,"Private",46788,"Bachelors",13,"Divorced","Craft-repair","Unmarried","White","Male",0,0,25,"United-States","<=50K" +45,"Private",179135,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +58,"Federal-gov",175873,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",57426,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +36,"Private",312206,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Without-pay",344858,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,20,"United-States","<=50K" +26,"State-gov",177035,"11th",7,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +60,"Private",88055,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",111095,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"Private",192251,"10th",6,"Divorced","Other-service","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +27,"Private",29807,"HS-grad",9,"Separated","Handlers-cleaners","Unmarried","White","Female",0,0,40,"Japan","<=50K" +26,"Federal-gov",211596,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"Private",268276,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,12,"United-States","<=50K" +59,"Self-emp-not-inc",181070,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"England",">50K" +53,"Local-gov",20676,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Amer-Indian-Eskimo","Male",0,0,48,"United-States","<=50K" +35,"Private",115803,"11th",7,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",124827,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",95336,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +36,"Private",257942,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",72593,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",147340,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",185325,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +59,"Self-emp-not-inc",357943,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Local-gov",30682,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Federal-gov",29591,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Other","Female",0,0,40,"United-States","<=50K" +36,"Private",215392,"Bachelors",13,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",133584,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +38,"Private",210438,"7th-8th",4,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +52,"Private",256916,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",73541,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",109952,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +54,"Private",197975,"5th-6th",3,"Married-civ-spouse","Sales","Husband","White","Male",0,0,51,"United-States","<=50K" +27,"Private",401723,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +42,"Private",179524,"Bachelors",13,"Separated","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +33,"State-gov",296282,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",145844,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +54,"Private",96792,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,32,"United-States","<=50K" +19,"?",233779,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,60,"United-States","<=50K" +45,"Private",347834,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",215373,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +35,"Self-emp-not-inc",169426,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",202856,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +33,"Private",50276,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Self-emp-not-inc",187454,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",126098,"HS-grad",9,"Separated","Craft-repair","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",250639,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,24,"United-States","<=50K" +64,"Self-emp-inc",195366,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",186845,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,8,"United-States","<=50K" +20,"Federal-gov",119156,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,20,"United-States","<=50K" +28,"Private",162343,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"Puerto-Rico","<=50K" +29,"Self-emp-not-inc",394927,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +51,"Private",172281,"Bachelors",13,"Separated","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Private",165681,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",258819,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States",">50K" +25,"Private",130793,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +36,"Private",118909,"Assoc-acdm",12,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"Jamaica","<=50K" +44,"Private",202466,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,60,"United-States","<=50K" +47,"Private",161558,"10th",6,"Married-spouse-absent","Transport-moving","Not-in-family","Black","Male",0,0,45,"United-States","<=50K" +32,"Private",188246,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",160120,"Masters",14,"Never-married","Prof-specialty","Unmarried","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +34,"Self-emp-not-inc",123429,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +35,"Self-emp-inc",340110,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",523067,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,3,"El-Salvador","<=50K" +49,"Self-emp-not-inc",113513,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +63,"?",186809,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States",">50K" +46,"Self-emp-not-inc",320421,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +31,"Local-gov",295589,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,40,"United-States","<=50K" +22,"Private",370548,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +20,"Private",120572,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +52,"Private",110977,"Doctorate",16,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +26,"Private",55860,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +34,"Private",158800,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Private",131568,"9th",5,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",173613,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +22,"Private",216867,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +38,"Private",104089,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",208106,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Ecuador","<=50K" +27,"State-gov",340269,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",236246,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",213408,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,40,"Cuba","<=50K" +40,"?",84232,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,4,"United-States","<=50K" +19,"Private",302945,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,10,"Thailand","<=50K" +69,"?",28197,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,60,"United-States",">50K" +20,"Private",262749,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +34,"Federal-gov",198265,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States","<=50K" +49,"Private",170871,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +27,"Private",177761,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","Other","Male",0,0,50,"United-States","<=50K" +59,"Private",175689,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,14,"Cuba",">50K" +21,"Private",77759,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +51,"State-gov",77905,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +64,"?",193575,"11th",7,"Never-married","?","Unmarried","White","Male",0,0,40,"United-States","<=50K" +41,"State-gov",116520,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +18,"?",85154,"12th",8,"Never-married","?","Own-child","Asian-Pac-Islander","Female",0,0,24,"Germany","<=50K" +49,"Private",180532,"Masters",14,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Private",508891,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",211345,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,20,"United-States","<=50K" +69,"Self-emp-not-inc",170877,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +18,"?",97318,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +43,"Private",184105,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +50,"Private",150941,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,44,"United-States","<=50K" +32,"Private",303942,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Local-gov",273929,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",197077,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Private",162825,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",159869,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +19,"Private",158343,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"?","<=50K" +17,"?",406920,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",227986,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",137527,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +36,"Private",180150,"12th",8,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",239539,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +58,"Private",281792,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",224799,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +66,"Private",22313,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +42,"Private",194636,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",156089,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",218667,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",358837,"Some-college",10,"Never-married","Tech-support","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +20,"Private",174685,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",168854,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,54,"United-States","<=50K" +28,"Private",133696,"Bachelors",13,"Never-married","Sales","Unmarried","White","Male",0,0,65,"United-States","<=50K" +23,"Federal-gov",350680,"Assoc-acdm",12,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"Poland","<=50K" +18,"Private",115215,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +43,"Self-emp-not-inc",152958,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +29,"Private",217200,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",235124,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,46,"Dominican-Republic","<=50K" +31,"Local-gov",144949,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +60,"Private",135470,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +42,"Private",281209,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +46,"Private",155489,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +38,"Private",290306,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",182042,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,19,"United-States","<=50K" +31,"Private",210008,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",30244,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,80,"United-States","<=50K" +50,"Local-gov",30008,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +38,"Self-emp-not-inc",201328,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,56,"United-States","<=50K" +36,"State-gov",96468,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",486332,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +19,"Private",46162,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,25,"United-States","<=50K" +60,"Local-gov",98350,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,60,"Philippines","<=50K" +45,"Local-gov",175958,"9th",5,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",204527,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +22,"?",57827,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",418176,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,32,"United-States","<=50K" +23,"Private",262744,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",177287,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,30,"United-States","<=50K" +30,"Private",255004,"Assoc-acdm",12,"Divorced","Sales","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +62,"Private",183735,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Self-emp-not-inc",318644,"Prof-school",15,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +42,"Federal-gov",132125,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,52,"United-States",">50K" +33,"Private",206051,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-inc",99185,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"?",">50K" +35,"Private",225750,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,32,"United-States","<=50K" +33,"Private",245777,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",169092,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +62,"Private",211035,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,30,"United-States",">50K" +24,"Private",285432,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",154779,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +54,"Private",37237,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Private",417419,"7th-8th",4,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-inc",33975,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",42485,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +27,"Private",170017,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",41721,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,60,"United-States","<=50K" +64,"Private",66634,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Self-emp-inc",257216,"Masters",14,"Widowed","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",167882,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +45,"Private",179428,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +26,"Private",57512,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",301614,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-inc",189092,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +47,"Private",217509,"HS-grad",9,"Widowed","Priv-house-serv","Not-in-family","Asian-Pac-Islander","Female",0,0,45,"Thailand","<=50K" +35,"Private",308691,"Masters",14,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +38,"Private",169672,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",120914,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",370156,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +28,"Private",398220,"5th-6th",3,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +44,"Self-emp-not-inc",208277,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,45,"United-States","<=50K" +40,"Private",337456,"HS-grad",9,"Divorced","Protective-serv","Unmarried","White","Female",0,0,40,"United-States","<=50K" +55,"Private",172666,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Self-emp-not-inc",32280,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +33,"Private",194901,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +19,"?",57329,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"Japan","<=50K" +45,"Local-gov",153312,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,10,"United-States",">50K" +23,"Private",274797,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +31,"Private",359249,"Assoc-voc",11,"Never-married","Protective-serv","Own-child","Black","Male",0,0,40,"United-States","<=50K" +22,"Private",152744,"Some-college",10,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +59,"Private",188041,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",97723,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +49,"State-gov",354529,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",249727,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +26,"Private",189590,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +23,"State-gov",298871,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +55,"Self-emp-not-inc",205296,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,50,"United-States","<=50K" +47,"Private",303637,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,49,"United-States",">50K" +44,"Private",242861,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",37599,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,24,"United-States","<=50K" +32,"Self-emp-not-inc",56328,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,8,"United-States",">50K" +20,"Private",256211,"Some-college",10,"Never-married","Machine-op-inspct","Other-relative","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +84,"Local-gov",163685,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,33,"United-States","<=50K" +40,"Private",266084,"Some-college",10,"Divorced","Craft-repair","Other-relative","White","Male",0,0,50,"United-States","<=50K" +37,"Private",161111,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",166634,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"Germany","<=50K" +62,"Self-emp-not-inc",204085,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,25,"United-States","<=50K" +19,"?",369527,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +47,"Private",464945,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +44,"Local-gov",174684,"HS-grad",9,"Divorced","Craft-repair","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +26,"Local-gov",166295,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,41,"United-States","<=50K" +36,"Private",220511,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",246936,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",104509,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +48,"?",266337,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",252168,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",92093,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States","<=50K" +62,"Private",88055,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",129591,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",142719,"HS-grad",9,"Married-spouse-absent","Farming-fishing","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +18,"?",264924,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +46,"Private",128796,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,44,"United-States",">50K" +38,"Private",115336,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,70,"United-States","<=50K" +52,"Private",190333,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +63,"Self-emp-not-inc",179444,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,15,"United-States","<=50K" +49,"Private",218676,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,43,"United-States","<=50K" +17,"Local-gov",148194,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,12,"United-States","<=50K" +33,"Private",184833,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +19,"Private",217769,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +27,"?",180553,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States",">50K" +61,"Private",56009,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",255334,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,25,"United-States",">50K" +29,"Private",349154,"10th",6,"Separated","Farming-fishing","Unmarried","White","Female",0,0,40,"Guatemala","<=50K" +43,"State-gov",41834,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,38,"United-States",">50K" +24,"Private",113466,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",130856,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +61,"Self-emp-not-inc",268797,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,17,"United-States","<=50K" +48,"Private",202117,"11th",7,"Divorced","Other-service","Not-in-family","White","Female",0,0,34,"United-States","<=50K" +19,"Private",280146,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +30,"Private",70377,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",236696,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +39,"Local-gov",222572,"Masters",14,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,43,"United-States","<=50K" +40,"Private",96129,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,72,"United-States",">50K" +27,"Local-gov",200492,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",193820,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +58,"Private",220789,"Bachelors",13,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +33,"Private",101345,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,42,"Canada",">50K" +40,"Private",140559,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,25,"United-States","<=50K" +40,"Self-emp-inc",64885,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States",">50K" +31,"Private",402361,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",143582,"HS-grad",9,"Separated","Other-service","Unmarried","Asian-Pac-Islander","Female",0,0,48,"China","<=50K" +49,"Private",185385,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +24,"Private",112706,"Assoc-voc",11,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Private",130364,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +58,"Local-gov",147428,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",205895,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +65,"?",273569,"HS-grad",9,"Widowed","?","Unmarried","White","Male",0,0,40,"United-States","<=50K" +43,"Private",153160,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-not-inc",167918,"Masters",14,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,50,"India","<=50K" +41,"Private",195661,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,54,"United-States","<=50K" +27,"State-gov",146243,"Some-college",10,"Separated","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +52,"?",105428,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,12,"United-States","<=50K" +26,"Private",149943,"HS-grad",9,"Never-married","Other-service","Other-relative","Asian-Pac-Islander","Male",0,0,60,"?","<=50K" +52,"Local-gov",246197,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Local-gov",192563,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +19,"Private",244115,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,30,"United-States","<=50K" +39,"Local-gov",98587,"Some-college",10,"Divorced","Prof-specialty","Own-child","White","Female",0,0,45,"United-States","<=50K" +47,"Private",145886,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",244315,"HS-grad",9,"Divorced","Craft-repair","Other-relative","Other","Male",0,0,40,"United-States","<=50K" +48,"Private",192779,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",209464,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +60,"Private",25141,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +28,"Private",405793,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +47,"Federal-gov",53498,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +69,"?",476653,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +40,"Self-emp-not-inc",162312,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,66,"South","<=50K" +41,"State-gov",109762,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",123031,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,48,"Trinadad&Tobago","<=50K" +46,"Federal-gov",119890,"Assoc-voc",11,"Separated","Tech-support","Not-in-family","Other","Female",0,0,30,"United-States","<=50K" +21,"Self-emp-not-inc",409230,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +44,"Private",223308,"Masters",14,"Separated","Sales","Unmarried","White","Female",0,0,48,"United-States","<=50K" +38,"?",129150,"10th",6,"Separated","?","Own-child","White","Male",0,0,35,"United-States","<=50K" +47,"Self-emp-not-inc",119199,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States",">50K" +42,"Local-gov",351161,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"Private",174533,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States",">50K" +32,"Private",324386,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",126568,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,33,"United-States","<=50K" +26,"Private",275703,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",200471,"11th",7,"Never-married","Other-service","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +65,"Private",155261,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +73,"State-gov",74040,"7th-8th",4,"Divorced","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +34,"Private",226296,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",211968,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +49,"Local-gov",126446,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +25,"Private",262885,"11th",7,"Never-married","Other-service","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +39,"Private",188069,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,25,"United-States","<=50K" +19,"Private",113546,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +24,"Private",227070,"10th",6,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +34,"Private",136997,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +35,"?",119006,"HS-grad",9,"Widowed","?","Own-child","White","Female",0,0,38,"United-States","<=50K" +21,"Private",212407,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +43,"Private",197810,"Masters",14,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Federal-gov",35309,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Asian-Pac-Islander","Male",0,0,28,"?","<=50K" +39,"Private",141802,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +48,"?",184513,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,80,"United-States",">50K" +33,"Self-emp-not-inc",124187,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","Black","Male",0,0,32,"United-States","<=50K" +19,"Private",201743,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,26,"United-States","<=50K" +17,"Private",156736,"10th",6,"Never-married","Sales","Unmarried","White","Female",0,0,12,"United-States","<=50K" +43,"Self-emp-not-inc",47261,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +62,"Private",150693,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +53,"Local-gov",233734,"Masters",14,"Divorced","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States",">50K" +45,"State-gov",35969,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +47,"Private",159550,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +30,"Private",190823,"Some-college",10,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +53,"Private",213378,"HS-grad",9,"Separated","Sales","Not-in-family","White","Female",0,0,33,"United-States","<=50K" +24,"Private",257500,"HS-grad",9,"Separated","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +41,"Local-gov",488706,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Local-gov",239405,"5th-6th",3,"Divorced","Other-service","Other-relative","Black","Female",0,0,40,"Haiti","<=50K" +63,"State-gov",109735,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +50,"Private",172942,"Some-college",10,"Divorced","Other-service","Own-child","White","Male",0,0,28,"United-States","<=50K" +29,"Self-emp-inc",87745,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +55,"Private",234125,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",272944,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +23,"Local-gov",129232,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",195835,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +25,"Private",251854,"11th",7,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +40,"Private",103474,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,30,"United-States","<=50K" +38,"Private",22042,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,39,"United-States","<=50K" +37,"Private",343721,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",232368,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +55,"Private",174478,"10th",6,"Never-married","Other-service","Not-in-family","White","Male",0,0,29,"United-States","<=50K" +28,"Private",274690,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +53,"Private",251675,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +32,"?",647882,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"?","<=50K" +32,"Private",37380,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +34,"Private",173730,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +49,"Private",353824,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +21,"Private",225890,"Some-college",10,"Never-married","Other-service","Other-relative","White","Female",0,0,30,"United-States","<=50K" +24,"State-gov",147147,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +29,"Private",394927,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"?","<=50K" +34,"Local-gov",188682,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +52,"?",115209,"Prof-school",15,"Married-spouse-absent","?","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +41,"Private",277192,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,0,40,"Mexico","<=50K" +21,"Private",314182,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",220776,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +31,"Local-gov",189269,"HS-grad",9,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +62,"Private",161460,"Bachelors",13,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +51,"Private",251487,"7th-8th",4,"Widowed","Machine-op-inspct","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +30,"Private",177531,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +24,"Private",53942,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",113481,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Private",361324,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",330087,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +33,"Private",276221,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",121055,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +62,"Private",118696,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Self-emp-not-inc",289741,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"United-States","<=50K" +18,"Private",238401,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +43,"Private",262038,"5th-6th",3,"Married-spouse-absent","Farming-fishing","Unmarried","White","Male",0,0,35,"Mexico","<=50K" +62,"Self-emp-not-inc",26911,"7th-8th",4,"Widowed","Other-service","Not-in-family","White","Female",0,0,66,"United-States","<=50K" +29,"Private",161155,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +43,"Private",252519,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"Haiti",">50K" +69,"?",167826,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",188900,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +25,"Private",134113,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +47,"Local-gov",165822,"Some-college",10,"Divorced","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +17,"Private",99161,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,8,"United-States","<=50K" +41,"Local-gov",74581,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,65,"United-States","<=50K" +19,"Private",304643,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +57,"Private",121821,"1st-4th",2,"Married-civ-spouse","Other-service","Husband","Other","Male",0,0,40,"Dominican-Republic","<=50K" +25,"Private",154863,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Male",0,0,35,"United-States","<=50K" +37,"Local-gov",365430,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Canada",">50K" +29,"Private",183111,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",50178,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +35,"Private",186845,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +52,"Private",159908,"12th",8,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",128509,"HS-grad",9,"Married-spouse-absent","Machine-op-inspct","Not-in-family","White","Female",0,0,38,"El-Salvador","<=50K" +23,"Private",143032,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,36,"United-States","<=50K" +31,"Private",382368,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",210013,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +19,"Private",293928,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +21,"Private",208503,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,10,"United-States","<=50K" +64,"Local-gov",202738,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States","<=50K" +37,"Local-gov",144322,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +22,"Private",160120,"10th",6,"Never-married","Transport-moving","Own-child","Asian-Pac-Islander","Male",0,0,30,"United-States","<=50K" +29,"Self-emp-inc",190450,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,40,"Germany","<=50K" +37,"Private",212900,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",115677,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",252250,"11th",7,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +27,"Private",212041,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +58,"State-gov",198145,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"United-States",">50K" +60,"Local-gov",113658,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States","<=50K" +20,"Private",32426,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +51,"Private",98791,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",203828,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States","<=50K" +22,"State-gov",186634,"12th",8,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +56,"Self-emp-not-inc",125147,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +19,"Private",97215,"Some-college",10,"Separated","Sales","Unmarried","White","Female",0,0,25,"United-States","<=50K" +37,"Private",330826,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,30,"United-States","<=50K" +27,"Private",200802,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",156266,"HS-grad",9,"Never-married","Sales","Own-child","Amer-Indian-Eskimo","Male",0,0,20,"United-States","<=50K" +52,"Self-emp-not-inc",72257,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +45,"Private",363087,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",25955,"Some-college",10,"Never-married","Craft-repair","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +20,"Private",334633,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",109162,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +44,"Private",569761,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",209900,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"State-gov",272986,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,8,"United-States","<=50K" +55,"?",52267,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,18,"United-States","<=50K" +46,"Private",82946,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Private",104651,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Local-gov",58441,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Local-gov",269733,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"?",128453,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,28,"United-States","<=50K" +36,"Private",179468,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",183081,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",102938,"Bachelors",13,"Never-married","Other-service","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +30,"?",157289,"11th",7,"Never-married","?","Unmarried","White","Male",0,0,40,"United-States","<=50K" +24,"Private",359828,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,44,"United-States",">50K" +30,"Private",155659,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,36,"United-States","<=50K" +62,"Private",173601,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",163352,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,85,"United-States",">50K" +36,"Self-emp-not-inc",153976,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +49,"State-gov",155372,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +52,"Private",329733,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Private",162576,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",176520,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,53,"United-States","<=50K" +51,"State-gov",226885,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",120781,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +30,"Private",375827,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +46,"Private",205504,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +28,"Private",198813,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Female",0,0,40,"United-States","<=50K" +62,"Private",159908,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,38,"United-States",">50K" +69,"Private",102874,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +78,"Private",180239,"Masters",14,"Widowed","Craft-repair","Unmarried","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +61,"Private",539563,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Private",261561,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",81057,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",160120,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Other","Male",0,0,45,"?","<=50K" +17,"Private",41979,"10th",6,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",275110,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,80,"United-States",">50K" +64,"Private",265661,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",193246,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"France","<=50K" +32,"Private",236543,"12th",8,"Married-civ-spouse","Craft-repair","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +19,"Private",29510,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +42,"State-gov",105804,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",194604,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +23,"Private",1038553,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,45,"United-States","<=50K" +44,"Private",307468,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,29,"United-States",">50K" +44,"Local-gov",107845,"Assoc-acdm",12,"Divorced","Protective-serv","Not-in-family","White","Female",0,0,56,"United-States",">50K" +44,"Self-emp-not-inc",567788,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +38,"Private",91857,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +36,"Private",732569,"9th",5,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",86613,"1st-4th",2,"Never-married","Other-service","Not-in-family","White","Male",0,0,20,"El-Salvador","<=50K" +46,"Private",35961,"Assoc-acdm",12,"Divorced","Sales","Not-in-family","White","Female",0,0,25,"Germany","<=50K" +47,"Private",114754,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",329426,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +43,"Private",181015,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,50,"United-States","<=50K" +44,"Self-emp-not-inc",264740,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",381153,"Some-college",10,"Never-married","Exec-managerial","Unmarried","White","Male",0,0,60,"United-States","<=50K" +36,"Private",218542,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +78,"Private",111189,"7th-8th",4,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,35,"Dominican-Republic","<=50K" +24,"Private",168997,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",168894,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",149809,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",344073,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States",">50K" +22,"Private",416165,"Some-college",10,"Never-married","Sales","Unmarried","White","Female",0,0,32,"United-States","<=50K" +36,"Private",41490,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +61,"Private",40269,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +67,"?",243256,"9th",5,"Married-civ-spouse","?","Husband","White","Male",0,0,15,"United-States","<=50K" +42,"Private",250536,"Some-college",10,"Separated","Other-service","Unmarried","Black","Female",0,0,21,"Haiti","<=50K" +49,"Federal-gov",105586,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +58,"Private",51499,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Local-gov",189878,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States","<=50K" +25,"Private",299765,"Some-college",10,"Separated","Adm-clerical","Other-relative","Black","Female",0,0,40,"Jamaica","<=50K" +45,"Self-emp-inc",155664,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?",">50K" +30,"Private",54608,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"?",174702,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +23,"Private",201145,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +51,"Private",125796,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,35,"Jamaica","<=50K" +55,"Private",249072,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +35,"Private",99156,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +45,"State-gov",94754,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"India","<=50K" +36,"Private",111128,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States",">50K" +32,"Local-gov",157887,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",74194,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +47,"Self-emp-inc",168191,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",28334,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +44,"Private",721161,"Some-college",10,"Separated","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",188069,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +40,"Private",145178,"Some-college",10,"Divorced","Craft-repair","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +17,"Private",52967,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,6,"United-States","<=50K" +18,"Private",177578,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,38,"United-States","<=50K" +30,"Self-emp-inc",185384,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,25,"United-States","<=50K" +66,"Private",66008,"HS-grad",9,"Widowed","Priv-house-serv","Not-in-family","White","Female",0,0,50,"England","<=50K" +59,"Private",329059,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Local-gov",348802,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +50,"Private",34233,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Private",509629,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +28,"Private",27956,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,99,"Philippines","<=50K" +44,"Local-gov",83286,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +25,"Private",309098,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",188950,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +20,"Private",224217,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +67,"Private",222899,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Self-emp-not-inc",123306,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +52,"Federal-gov",279337,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",347166,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +37,"Local-gov",251396,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"Canada",">50K" +17,"Self-emp-inc",143034,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,4,"United-States","<=50K" +25,"Private",57635,"Assoc-voc",11,"Married-civ-spouse","Sales","Wife","White","Female",0,0,42,"United-States",">50K" +35,"Local-gov",162651,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"Puerto-Rico","<=50K" +63,"Private",28334,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +38,"Local-gov",84570,"Some-college",10,"Never-married","Adm-clerical","Own-child","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +33,"Private",181091,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,60,"Iran",">50K" +51,"Local-gov",117496,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +64,"State-gov",216160,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"Columbia",">50K" +50,"Self-emp-inc",204447,"Some-college",10,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",374969,"10th",6,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +67,"Private",35015,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,99,"United-States","<=50K" +46,"Private",179869,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",137733,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",193125,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",103649,"Some-college",10,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",197932,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Wife","White","Female",0,0,40,"Mexico",">50K" +37,"Private",249720,"Bachelors",13,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,27,"United-States","<=50K" +55,"Private",223613,"1st-4th",2,"Divorced","Priv-house-serv","Unmarried","White","Female",0,0,30,"Cuba","<=50K" +24,"Private",259865,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +21,"Private",301694,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"Mexico","<=50K" +46,"Self-emp-inc",276934,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States",">50K" +25,"Private",395512,"12th",8,"Married-civ-spouse","Machine-op-inspct","Other-relative","Other","Male",0,0,40,"Mexico","<=50K" +40,"Private",168071,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,28,"United-States","<=50K" +23,"Private",45317,"Some-college",10,"Separated","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",311177,"Some-college",10,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,30,"United-States","<=50K" +59,"Private",221336,"10th",6,"Widowed","Other-service","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +18,"Private",120691,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,35,"?","<=50K" +28,"Private",107389,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Male",0,0,32,"United-States","<=50K" +17,"Private",293440,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +53,"Private",145409,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",213902,"5th-6th",3,"Never-married","Priv-house-serv","Other-relative","White","Female",0,0,40,"El-Salvador","<=50K" +63,"Private",100099,"HS-grad",9,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",191856,"Masters",14,"Married-civ-spouse","Sales","Wife","White","Female",0,0,45,"United-States",">50K" +40,"Local-gov",233891,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +61,"Self-emp-not-inc",96073,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"England",">50K" +43,"Self-emp-not-inc",355856,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,50,"Philippines","<=50K" +48,"Self-emp-not-inc",139212,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"State-gov",143931,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Federal-gov",160703,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",191291,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"Private",119986,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?",">50K" +37,"Private",227545,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States",">50K" +34,"Private",228881,"Some-college",10,"Separated","Machine-op-inspct","Not-in-family","Other","Male",0,0,40,"United-States","<=50K" +23,"Private",84648,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +63,"Federal-gov",101996,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +63,"?",68954,"HS-grad",9,"Widowed","?","Not-in-family","Black","Female",0,0,11,"United-States","<=50K" +55,"Self-emp-inc",209569,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,50,"United-States",">50K" +31,"Local-gov",331126,"Bachelors",13,"Never-married","Protective-serv","Own-child","Black","Male",0,0,48,"United-States","<=50K" +27,"Private",279872,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Local-gov",185647,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,48,"United-States","<=50K" +52,"Private",128871,"7th-8th",4,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,64,"United-States","<=50K" +31,"Federal-gov",386331,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,50,"United-States","<=50K" +53,"Private",117814,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +43,"Private",220609,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +43,"Local-gov",117022,"HS-grad",9,"Married-spouse-absent","Farming-fishing","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-inc",176751,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,80,"United-States",">50K" +68,"?",76371,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,35,"United-States","<=50K" +37,"Private",80410,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",127202,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",121471,"11th",7,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",219086,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +30,"Private",241583,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",374253,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +30,"Private",214993,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",199995,"Bachelors",13,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States",">50K" +29,"Private",120359,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",187513,"Assoc-voc",11,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +65,"Private",243569,"Some-college",10,"Widowed","Other-service","Unmarried","White","Female",0,0,24,"United-States","<=50K" +43,"Private",295510,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +29,"Private",29732,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,24,"United-States","<=50K" +32,"Private",211743,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +37,"Private",251396,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +64,"Private",477697,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,16,"United-States","<=50K" +49,"Private",151584,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",193882,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",411395,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,36,"United-States","<=50K" +53,"Private",191025,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +24,"Private",154571,"Assoc-voc",11,"Never-married","Sales","Unmarried","Asian-Pac-Islander","Male",0,0,50,"South","<=50K" +31,"Private",208657,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",29599,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,38,"United-States","<=50K" +36,"Private",423711,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +29,"Private",122000,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +37,"Private",148581,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +42,"Self-emp-not-inc",222978,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +30,"Private",149118,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Self-emp-inc",218407,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,70,"Cuba","<=50K" +44,"Private",85604,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States",">50K" +19,"Private",111232,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",99199,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States","<=50K" +51,"Private",199995,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +69,"Private",122850,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,16,"United-States","<=50K" +73,"?",90557,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +18,"?",271935,"11th",7,"Never-married","?","Other-relative","White","Female",0,0,20,"United-States","<=50K" +33,"Self-emp-not-inc",361497,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Local-gov",399020,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +33,"Private",345277,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,45,"United-States",">50K" +20,"Federal-gov",55233,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",200515,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",188119,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",176683,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +22,"Private",309178,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +67,"Self-emp-not-inc",40021,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +31,"Self-emp-inc",49923,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"?",36635,"Some-college",10,"Never-married","?","Unmarried","White","Female",0,0,25,"United-States","<=50K" +43,"Federal-gov",325706,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,50,"India",">50K" +33,"Private",124407,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",301568,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,35,"United-States",">50K" +27,"Private",339956,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,60,"United-States","<=50K" +36,"Private",176335,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",198452,"Assoc-acdm",12,"Divorced","Sales","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +48,"Private",171807,"Bachelors",13,"Divorced","Other-service","Unmarried","White","Female",0,0,56,"United-States",">50K" +25,"Private",362826,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,45,"United-States","<=50K" +41,"Self-emp-not-inc",344329,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,10,"United-States","<=50K" +26,"Private",137678,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",175424,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +30,"State-gov",137613,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,17,"Taiwan","<=50K" +67,"Self-emp-not-inc",354405,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +32,"Private",130057,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +48,"Self-emp-not-inc",362883,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States",">50K" +51,"Private",49017,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +39,"Private",149943,"Masters",14,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +40,"Self-emp-inc",99185,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +40,"Private",294708,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States",">50K" +19,"Private",228238,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +28,"Private",156819,"HS-grad",9,"Divorced","Handlers-cleaners","Unmarried","White","Female",0,0,36,"United-States","<=50K" +47,"Private",332727,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +20,"Private",289944,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +29,"Private",24153,"Some-college",10,"Married-civ-spouse","Other-service","Wife","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +40,"Private",273425,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +61,"Private",231183,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",313930,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +26,"Private",114483,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",162108,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Private",168807,"7th-8th",4,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +46,"Local-gov",111558,"Some-college",10,"Divorced","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",69770,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +37,"Private",291981,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",102460,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Local-gov",287320,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",115677,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",239632,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",409172,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Own-child","White","Male",0,0,55,"United-States","<=50K" +20,"Private",186849,"HS-grad",9,"Never-married","Transport-moving","Other-relative","White","Male",0,0,40,"United-States","<=50K" +28,"Private",118861,"10th",6,"Married-civ-spouse","Craft-repair","Wife","Other","Female",0,0,48,"Guatemala","<=50K" +26,"Private",142689,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"?","<=50K" +41,"State-gov",170924,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +67,"?",274451,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",153489,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Private",186489,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,46,"United-States","<=50K" +18,"Private",192409,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +55,"State-gov",337599,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",195545,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +64,"Private",61892,"HS-grad",9,"Widowed","Priv-house-serv","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +34,"Self-emp-not-inc",175697,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,75,"United-States","<=50K" +38,"Private",80303,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +25,"Private",419658,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,8,"United-States","<=50K" +21,"Private",319163,"Some-college",10,"Never-married","Transport-moving","Own-child","Black","Male",0,0,40,"United-States","<=50K" +37,"Private",126743,"1st-4th",2,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,53,"Mexico","<=50K" +39,"Private",301568,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",120461,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +23,"Private",268145,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +54,"Private",257337,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Self-emp-inc",213354,"Masters",14,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,70,"United-States",">50K" +25,"Private",303431,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +51,"Private",124963,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",158218,"HS-grad",9,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,35,"United-States","<=50K" +27,"State-gov",553473,"Bachelors",13,"Married-civ-spouse","Protective-serv","Wife","Black","Female",0,0,48,"United-States","<=50K" +53,"Private",46155,"HS-grad",9,"Married-civ-spouse","Priv-house-serv","Other-relative","White","Female",0,0,40,"United-States","<=50K" +68,"Private",138714,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +56,"Private",231781,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",496414,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"?","<=50K" +24,"Private",19410,"HS-grad",9,"Divorced","Sales","Unmarried","Amer-Indian-Eskimo","Female",0,0,48,"United-States","<=50K" +70,"?",28471,"9th",5,"Widowed","?","Unmarried","White","Female",0,0,25,"United-States","<=50K" +24,"Private",185821,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +74,"?",272667,"Assoc-acdm",12,"Widowed","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +23,"?",194031,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +41,"Local-gov",144995,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +45,"Private",162494,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,19,"United-States","<=50K" +35,"Private",171968,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",232569,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",161819,"11th",7,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +18,"Private",123343,"11th",7,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +49,"Private",105449,"Bachelors",13,"Never-married","Priv-house-serv","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +49,"Private",181717,"Assoc-voc",11,"Separated","Prof-specialty","Own-child","White","Female",0,0,36,"United-States","<=50K" +45,"Local-gov",102359,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,37,"United-States","<=50K" +27,"Private",72887,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +28,"Private",154571,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +35,"Private",255191,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +33,"Private",174789,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",110402,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +19,"Private",208513,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +33,"Private",121904,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +49,"Private",59380,"Some-college",10,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Self-emp-inc",126675,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,25,"United-States","<=50K" +22,"Private",217363,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Private",91836,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",184813,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",178142,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-inc",281832,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Cuba",">50K" +28,"Private",96226,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +42,"Private",195124,"7th-8th",4,"Married-spouse-absent","Prof-specialty","Other-relative","White","Male",0,0,35,"Puerto-Rico","<=50K" +50,"Local-gov",97449,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,48,"United-States","<=50K" +32,"Private",339773,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Federal-gov",210926,"HS-grad",9,"Separated","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",199499,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +46,"Federal-gov",190729,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-inc",191385,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,77,"United-States","<=50K" +61,"Private",193479,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,24,"United-States","<=50K" +43,"Self-emp-not-inc",225165,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +35,"Private",346766,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"State-gov",152307,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"?",79990,"11th",7,"Never-married","?","Own-child","White","Male",0,0,35,"United-States","<=50K" +42,"Self-emp-not-inc",170649,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +23,"Private",197207,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",229732,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +52,"Private",204402,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,85,"United-States",">50K" +36,"Private",181065,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",179579,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"?",">50K" +23,"?",164574,"Assoc-acdm",12,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +71,"Private",179574,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,12,"United-States",">50K" +27,"Private",191782,"HS-grad",9,"Never-married","Other-service","Other-relative","Black","Female",0,0,30,"United-States","<=50K" +56,"Private",146660,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +28,"Self-emp-not-inc",115945,"Some-college",10,"Never-married","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +45,"Private",210875,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",137898,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +28,"Local-gov",216965,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",201554,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +62,"Private",57970,"7th-8th",4,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",208378,"12th",8,"Separated","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Private",61343,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"United-States","<=50K" +24,"Private",283872,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,20,"United-States","<=50K" +58,"Private",225603,"9th",5,"Divorced","Farming-fishing","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +48,"Private",401333,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Private",278228,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Private",145377,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +25,"Private",120238,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",144063,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,72,"United-States","<=50K" +38,"Private",238721,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +21,"Private",164920,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",152493,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +50,"Private",92968,"Bachelors",13,"Never-married","Sales","Unmarried","White","Female",0,0,32,"United-States","<=50K" +50,"Private",136836,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +49,"Federal-gov",216453,"Assoc-voc",11,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,45,"United-States","<=50K" +30,"Private",349148,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +29,"State-gov",309620,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,20,"Taiwan","<=50K" +22,"State-gov",347803,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Other","Male",0,0,20,"United-States","<=50K" +42,"Private",85995,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +19,"?",167428,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",164569,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,48,"United-States","<=50K" +42,"Self-emp-not-inc",308279,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,21,"United-States","<=50K" +20,"Private",56322,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +51,"?",203015,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",211654,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Self-emp-inc",120126,"9th",5,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",239043,"11th",7,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"?",179761,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",312017,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"Germany","<=50K" +51,"Private",257485,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",49243,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",229716,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +31,"Private",341672,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,60,"India","<=50K" +24,"Private",32311,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +56,"Private",275236,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"?",400356,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",152420,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,50,"United-States","<=50K" +21,"Private",235442,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",161691,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +20,"?",173945,"11th",7,"Married-civ-spouse","?","Other-relative","White","Female",0,0,39,"United-States","<=50K" +41,"Private",355918,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States",">50K" +45,"State-gov",198660,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",122649,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +28,"Private",421967,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,60,"United-States",">50K" +47,"Private",74305,"Bachelors",13,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +80,"Self-emp-not-inc",34340,"7th-8th",4,"Widowed","Farming-fishing","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +47,"Self-emp-not-inc",182752,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"Iran","<=50K" +19,"?",48393,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,84,"United-States","<=50K" +45,"Private",34248,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +17,"Private",186677,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,12,"United-States","<=50K" +37,"Private",167851,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",146460,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Private",209650,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +18,"Self-emp-not-inc",132986,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +57,"Private",94429,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",252406,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",174592,"Masters",14,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",151322,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +51,"Private",37237,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,80,"United-States",">50K" +38,"Private",101192,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +77,"?",152900,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +51,"Private",94081,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States",">50K" +24,"Private",329408,"11th",7,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",106028,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +35,"?",164866,"10th",6,"Divorced","?","Not-in-family","White","Male",0,0,99,"United-States","<=50K" +28,"Private",138692,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",173968,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",228320,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",96585,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +42,"Private",156580,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"Puerto-Rico","<=50K" +58,"Private",210673,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +52,"Local-gov",137753,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,20,"United-States","<=50K" +29,"Private",29865,"HS-grad",9,"Divorced","Sales","Not-in-family","Amer-Indian-Eskimo","Female",0,0,50,"United-States","<=50K" +27,"Private",196044,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +28,"Private",308995,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"Jamaica","<=50K" +28,"Private",362491,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",94395,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",320047,"10th",6,"Married-spouse-absent","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Private",98535,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +65,"Private",183170,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +18,"?",331511,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +38,"Private",195686,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",178244,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",127833,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",269722,"Masters",14,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"State-gov",136819,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",205604,"5th-6th",3,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,30,"Mexico","<=50K" +28,"Private",132078,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",234880,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +68,"Self-emp-inc",140852,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",105614,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +18,"Private",83492,"7th-8th",4,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",225772,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States",">50K" +37,"Private",242713,"12th",8,"Separated","Priv-house-serv","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +60,"Private",355865,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Private",173316,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-inc",35662,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,70,"United-States",">50K" +17,"Private",297246,"11th",7,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,9,"United-States","<=50K" +43,"Private",108945,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +39,"Private",112158,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,26,"?","<=50K" +21,"Self-emp-not-inc",57298,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +42,"Self-emp-not-inc",115323,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,7,"?","<=50K" +21,"Private",177265,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +28,"Local-gov",336543,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","Asian-Pac-Islander","Male",0,0,40,"Hong",">50K" +39,"Self-emp-not-inc",52870,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Local-gov",200153,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"Private",453067,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,36,"United-States",">50K" +51,"Federal-gov",27166,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",299598,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,16,"United-States","<=50K" +23,"Private",122048,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",345277,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",113147,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States","<=50K" +43,"Private",34007,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",255014,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +34,"Private",152667,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,35,"United-States","<=50K" +21,"Private",231053,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,30,"United-States","<=50K" +34,"Private",103651,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Self-emp-inc",124137,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",198183,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",466458,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +45,"Self-emp-not-inc",114396,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +42,"Private",186376,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,72,"Philippines",">50K" +90,"Self-emp-not-inc",282095,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"State-gov",244974,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,44,"United-States",">50K" +34,"Self-emp-not-inc",114691,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",107160,"12th",8,"Separated","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +39,"Self-emp-not-inc",142573,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +29,"Private",203833,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +24,"Private",47791,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,32,"United-States","<=50K" +49,"Private",133729,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,17,"United-States","<=50K" +52,"Self-emp-not-inc",135339,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"?",">50K" +31,"Private",128591,"9th",5,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",133853,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +18,"?",137363,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +27,"Self-emp-not-inc",243569,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",119156,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",391114,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,60,"United-States","<=50K" +27,"Private",252506,"Some-college",10,"Divorced","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"State-gov",117503,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,20,"Italy","<=50K" +25,"State-gov",117833,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,19,"United-States","<=50K" +39,"Private",294183,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",394927,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Self-emp-not-inc",259323,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States","<=50K" +21,"?",207988,"HS-grad",9,"Married-civ-spouse","?","Other-relative","White","Female",0,0,35,"United-States","<=50K" +33,"Private",96635,"Some-college",10,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Male",0,0,26,"South","<=50K" +27,"Private",192283,"Assoc-voc",11,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,38,"United-States","<=50K" +29,"Private",214881,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"State-gov",167474,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",110713,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +20,"Private",201204,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",197666,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",162002,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +41,"Private",224799,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",89942,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",238685,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +54,"Private",38795,"9th",5,"Separated","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +55,"Private",90414,"Bachelors",13,"Married-spouse-absent","Craft-repair","Unmarried","White","Female",0,0,55,"Ireland","<=50K" +21,"Private",190805,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,32,"United-States","<=50K" +19,"Private",285263,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",177331,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +22,"Private",347530,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +17,"?",210547,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",204752,"12th",8,"Never-married","Sales","Own-child","White","Male",0,0,32,"United-States","<=50K" +74,"Self-emp-not-inc",104001,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",253116,"10th",6,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",169037,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Self-emp-inc",202027,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +45,"Private",170099,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",212847,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,85,"United-States","<=50K" +50,"State-gov",307392,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Private",233428,"HS-grad",9,"Divorced","Exec-managerial","Other-relative","White","Female",0,0,40,"United-States","<=50K" +52,"Private",177995,"1st-4th",2,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,56,"Mexico",">50K" +24,"Private",283613,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,43,"United-States","<=50K" +56,"Self-emp-inc",184598,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,99,"United-States","<=50K" +27,"Private",185647,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States",">50K" +38,"Private",179579,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",131679,"Assoc-voc",11,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +52,"Private",132973,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +22,"Private",154713,"HS-grad",9,"Divorced","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",121718,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Italy","<=50K" +30,"Private",255279,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,20,"United-States","<=50K" +55,"Private",202559,"Bachelors",13,"Married-civ-spouse","Other-service","Other-relative","Asian-Pac-Islander","Male",0,0,35,"Philippines","<=50K" +32,"Private",153326,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Other-relative","White","Male",0,0,40,"United-States","<=50K" +28,"Private",75695,"Some-college",10,"Separated","Other-service","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +33,"Self-emp-inc",206609,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +17,"Private",234780,"HS-grad",9,"Never-married","Farming-fishing","Own-child","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",178778,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",171355,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,20,"United-States","<=50K" +63,"Federal-gov",95680,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,18,"United-States",">50K" +67,"Self-emp-not-inc",139960,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-inc",397280,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,72,"?","<=50K" +54,"Private",421561,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +59,"Private",245196,"10th",6,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States",">50K" +18,"Private",27620,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +19,"Private",187570,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,20,"United-States","<=50K" +31,"Private",102884,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +17,"Private",228399,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,7,"United-States","<=50K" +37,"Private",176293,"Some-college",10,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +51,"Local-gov",108435,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",278391,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",157941,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"Private",182866,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",206512,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +33,"Private",357954,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,35,"India","<=50K" +28,"Private",189346,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,48,"United-States","<=50K" +45,"Private",234652,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +25,"Private",113436,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,15,"United-States","<=50K" +37,"Private",204145,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +59,"Private",157305,"Preschool",1,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"Dominican-Republic","<=50K" +26,"Private",104045,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +48,"Private",280422,"Some-college",10,"Separated","Other-service","Not-in-family","White","Female",0,0,25,"Peru","<=50K" +64,"Federal-gov",173754,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",211154,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Private",321435,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"State-gov",177083,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +46,"Private",178829,"Masters",14,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Male",0,0,70,"United-States",">50K" +35,"Federal-gov",287658,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States",">50K" +43,"Private",209894,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +31,"Private",334744,"HS-grad",9,"Separated","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",306967,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +35,"Private",52187,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +35,"Private",101978,"HS-grad",9,"Separated","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +35,"State-gov",483530,"Some-college",10,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",77357,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",149770,"Masters",14,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +70,"?",172652,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +46,"Private",188293,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",116608,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,38,"United-States","<=50K" +37,"State-gov",348960,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,36,"United-States",">50K" +24,"Private",329530,"9th",5,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"Mexico","<=50K" +47,"Local-gov",93476,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +35,"Self-emp-not-inc",195744,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +43,"Private",125833,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +18,"State-gov",191117,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +54,"Private",311020,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +62,"Private",210464,"HS-grad",9,"Never-married","Other-service","Other-relative","Black","Female",0,0,38,"United-States","<=50K" +36,"Private",135289,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +27,"Private",156266,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +23,"Private",154210,"Some-college",10,"Never-married","Adm-clerical","Other-relative","Asian-Pac-Islander","Male",0,0,14,"Puerto-Rico","<=50K" +33,"Self-emp-not-inc",249249,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",261725,"1st-4th",2,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +22,"Private",239612,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +31,"Self-emp-not-inc",226696,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +26,"Private",190330,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +44,"Private",193755,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +73,"Private",192740,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States","<=50K" +44,"Private",201924,"Bachelors",13,"Divorced","Sales","Unmarried","White","Female",0,0,35,"United-States","<=50K" +35,"Private",77146,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +33,"Private",126414,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"?","<=50K" +27,"Private",43652,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Federal-gov",227244,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,50,"United-States",">50K" +29,"Private",160731,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +33,"Private",287878,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,26,"United-States","<=50K" +50,"Private",166758,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +41,"Self-emp-not-inc",254818,"Masters",14,"Divorced","Handlers-cleaners","Unmarried","White","Male",0,0,40,"Peru","<=50K" +19,"?",220517,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +45,"Private",295046,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +42,"State-gov",211915,"Some-college",10,"Separated","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",295621,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,25,"United-States",">50K" +42,"Private",204235,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Private",186982,"Some-college",10,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States",">50K" +38,"Private",133586,"HS-grad",9,"Married-civ-spouse","Protective-serv","Own-child","White","Male",0,0,45,"United-States","<=50K" +38,"Private",165930,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +37,"Private",164898,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States","<=50K" +24,"Private",278155,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +27,"Self-emp-not-inc",115705,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +25,"Private",150553,"9th",5,"Married-spouse-absent","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +29,"Private",185127,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +46,"Private",201595,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,70,"United-States","<=50K" +44,"Self-emp-inc",165815,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,96,"United-States","<=50K" +26,"Private",102420,"Bachelors",13,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"South","<=50K" +46,"Local-gov",344172,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,49,"United-States",">50K" +38,"Private",222450,"Some-college",10,"Separated","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +38,"Private",212245,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"State-gov",190625,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States","<=50K" +33,"Private",203488,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",304260,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +31,"Local-gov",243665,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,41,"United-States",">50K" +26,"Self-emp-not-inc",189238,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,4,"Mexico","<=50K" +42,"Private",77373,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,38,"United-States","<=50K" +27,"Private",410351,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",36385,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +64,"Private",110150,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",198316,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",127772,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",199058,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +56,"Private",285730,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,66,"United-States","<=50K" +25,"Local-gov",334133,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +60,"State-gov",97030,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +52,"Private",67090,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States","<=50K" +46,"Private",182533,"Bachelors",13,"Never-married","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +19,"Private",560804,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +56,"Private",365050,"7th-8th",4,"Never-married","Farming-fishing","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +22,"Private",110200,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",150025,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"?","<=50K" +39,"Private",299828,"5th-6th",3,"Separated","Sales","Unmarried","Black","Female",0,0,30,"Puerto-Rico","<=50K" +28,"Private",109282,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",103435,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",34747,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +39,"Private",137522,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,40,"?",">50K" +39,"Private",286789,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Self-emp-not-inc",211032,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +31,"Private",219318,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,35,"Puerto-Rico","<=50K" +50,"Private",112873,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",73434,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"Germany",">50K" +51,"Private",200576,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +54,"Private",172962,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",44006,"Assoc-voc",11,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",234474,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,20,"United-States","<=50K" +37,"Private",212826,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +38,"Private",234901,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Federal-gov",200700,"Assoc-acdm",12,"Married-civ-spouse","Farming-fishing","Husband","Black","Male",0,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",41258,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +51,"Private",249644,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,48,"United-States",">50K" +60,"?",230165,"Bachelors",13,"Married-civ-spouse","?","Husband","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",351731,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",114765,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",349884,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +28,"Self-emp-inc",204247,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Private",143392,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",37913,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Italy",">50K" +22,"Self-emp-inc",150683,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,24,"United-States","<=50K" +27,"Private",207611,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,52,"United-States","<=50K" +45,"State-gov",319666,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,43,"United-States","<=50K" +39,"Private",155961,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +25,"Local-gov",117833,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +63,"?",447079,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +24,"Self-emp-inc",142404,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",155752,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +19,"?",252292,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",111450,"12th",8,"Never-married","Other-service","Unmarried","Black","Male",0,0,38,"United-States","<=50K" +20,"Private",528616,"5th-6th",3,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +17,"Self-emp-not-inc",228786,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,24,"United-States","<=50K" +63,"Self-emp-inc",80572,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Local-gov",180271,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,65,"United-States",">50K" +51,"Federal-gov",237819,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +64,"Private",379062,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,12,"United-States","<=50K" +17,"Private",191910,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +18,"Private",312353,"12th",8,"Never-married","Other-service","Own-child","Black","Male",0,0,20,"United-States","<=50K" +31,"Local-gov",213307,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-not-inc",209057,"Bachelors",13,"Married-spouse-absent","Sales","Own-child","White","Male",0,0,50,"United-States",">50K" +41,"Private",340148,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +27,"Private",94064,"Assoc-voc",11,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",119098,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",388496,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,8,"Puerto-Rico",">50K" +49,"Private",181363,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +58,"?",210031,"HS-grad",9,"Divorced","?","Unmarried","White","Male",0,0,40,"United-States","<=50K" +25,"Private",485496,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",210259,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +31,"Private",118551,"9th",5,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"State-gov",242517,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +63,"Private",298113,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",277783,"Masters",14,"Never-married","Farming-fishing","Own-child","White","Male",0,0,99,"United-States","<=50K" +48,"Private",155862,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +51,"Self-emp-not-inc",171924,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +18,"Private",243900,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +23,"Private",231160,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +38,"Private",49020,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"?",105460,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,20,"England","<=50K" +56,"Private",157749,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +31,"Private",131568,"7th-8th",4,"Divorced","Transport-moving","Unmarried","White","Male",0,0,20,"United-States","<=50K" +46,"Private",332355,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",204501,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +56,"Local-gov",305767,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +31,"Private",129761,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +53,"Private",102828,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +18,"Private",160984,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +20,"?",346341,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +31,"Private",356689,"Bachelors",13,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",394860,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",113129,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,24,"United-States","<=50K" +26,"Private",55929,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Local-gov",177018,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",161141,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",309463,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",49218,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",306850,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",187322,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Male",0,0,45,"United-States","<=50K" +26,"Private",148298,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +47,"Private",34845,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +27,"Private",200733,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,55,"United-States","<=50K" +45,"Private",191858,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +30,"Private",425528,"HS-grad",9,"Never-married","Protective-serv","Own-child","White","Male",0,0,70,"United-States","<=50K" +33,"Private",125856,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",100508,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",148294,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,20,"United-States","<=50K" +42,"Private",39324,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Federal-gov",147397,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,36,"United-States","<=50K" +46,"Private",24728,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +36,"Private",177616,"5th-6th",3,"Separated","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +54,"Private",163826,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",199947,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +26,"Local-gov",386949,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,25,"United-States","<=50K" +36,"Self-emp-inc",116133,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,57,"United-States","<=50K" +56,"Self-emp-not-inc",196307,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +37,"Private",177181,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",324854,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +23,"Private",188505,"Bachelors",13,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +23,"State-gov",502316,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"State-gov",26892,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"Private",102058,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +39,"Private",167728,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +67,"Local-gov",233681,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States","<=50K" +60,"Private",26756,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +54,"Private",101890,"HS-grad",9,"Widowed","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",192337,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"England",">50K" +49,"State-gov",102308,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,42,"United-States",">50K" +19,"Private",84747,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,24,"United-States","<=50K" +20,"Private",197752,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +66,"Private",185336,"HS-grad",9,"Widowed","Sales","Other-relative","White","Female",0,0,35,"United-States","<=50K" +22,"?",289984,"Some-college",10,"Never-married","?","Not-in-family","Black","Female",0,0,25,"United-States","<=50K" +51,"Self-emp-not-inc",125417,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States",">50K" +19,"Private",278480,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",146412,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",193042,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +78,"?",33186,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,60,"United-States","<=50K" +36,"Private",144154,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",194901,"Prof-school",15,"Divorced","Sales","Own-child","White","Male",0,0,55,"United-States","<=50K" +35,"Private",335777,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +46,"Private",139268,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +38,"Private",33887,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +24,"Private",283613,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",141245,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"Puerto-Rico","<=50K" +49,"Private",298130,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",186096,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,30,"United-States","<=50K" +77,"Private",187656,"Some-college",10,"Widowed","Priv-house-serv","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +46,"Private",102308,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,56,"United-States",">50K" +41,"Private",124639,"Some-college",10,"Separated","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +28,"Private",388112,"1st-4th",2,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,77,"Mexico","<=50K" +21,"Private",109952,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",164529,"12th",8,"Never-married","Farming-fishing","Own-child","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",247750,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,45,"United-States","<=50K" +23,"State-gov",103588,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,25,"United-States","<=50K" +29,"Self-emp-not-inc",178551,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",136137,"Some-college",10,"Married-civ-spouse","Exec-managerial","Other-relative","White","Male",0,0,50,"United-States",">50K" +47,"Federal-gov",55377,"Bachelors",13,"Never-married","Adm-clerical","Unmarried","Black","Male",0,0,40,"United-States",">50K" +39,"Local-gov",177728,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Local-gov",243580,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States","<=50K" +21,"?",188535,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",63910,"HS-grad",9,"Divorced","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +23,"Private",219535,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"State-gov",180609,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",59313,"Some-college",10,"Separated","Other-service","Not-in-family","Black","Male",0,0,40,"?","<=50K" +70,"Private",170428,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,20,"Puerto-Rico","<=50K" +66,"Private",193132,"9th",5,"Separated","Other-service","Not-in-family","Black","Female",0,0,30,"United-States","<=50K" +57,"Self-emp-inc",124137,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",136629,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Self-emp-inc",148995,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States",">50K" +24,"?",203076,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",63424,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +43,"Private",241895,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",266973,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +32,"Private",188048,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"Private",366929,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +33,"Private",214129,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",250818,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Local-gov",240979,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +35,"Private",98283,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"India",">50K" +39,"Private",103710,"HS-grad",9,"Never-married","Sales","Unmarried","White","Female",0,0,60,"United-States","<=50K" +24,"Private",159580,"Bachelors",13,"Never-married","Other-service","Own-child","Black","Female",0,0,75,"United-States","<=50K" +45,"Private",117409,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",140001,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"State-gov",31650,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Other-relative","White","Female",0,0,45,"United-States","<=50K" +35,"State-gov",80771,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",66278,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",206609,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +35,"Private",282461,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +31,"Private",188246,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"Private",279763,"11th",7,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,25,"United-States","<=50K" +44,"Private",467799,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",137674,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +50,"Private",158284,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",204219,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +28,"State-gov",210498,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Federal-gov",63526,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States",">50K" +38,"Federal-gov",216924,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",372559,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +50,"Private",168539,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Local-gov",189911,"11th",7,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Private",204450,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +53,"Private",311350,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",113750,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",359591,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",301199,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,24,"United-States","<=50K" +38,"State-gov",267540,"Some-college",10,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +52,"Private",185407,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"Poland",">50K" +48,"Self-emp-inc",191277,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +30,"Private",78980,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",216999,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +33,"Local-gov",120508,"Bachelors",13,"Divorced","Protective-serv","Unmarried","White","Female",0,0,60,"Germany","<=50K" +33,"Private",122612,"HS-grad",9,"Married-spouse-absent","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,35,"Thailand","<=50K" +20,"Private",94057,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +41,"State-gov",197558,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",121761,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,50,"?","<=50K" +36,"Federal-gov",184556,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +46,"Private",268281,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",235646,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",186909,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +62,"Private",35783,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +33,"Private",188861,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",363591,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +18,"Private",469921,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +32,"Private",51150,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",174325,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",347530,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +50,"Private",72351,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +42,"Local-gov",185129,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,43,"?",">50K" +36,"Private",188571,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",255252,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",291951,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",223046,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",37937,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,43,"United-States","<=50K" +38,"Private",295127,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",183801,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,14,"United-States","<=50K" +40,"Private",116218,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +40,"Private",143069,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",235951,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +57,"Private",112840,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Federal-gov",43705,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +48,"Private",101299,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +45,"Private",96798,"5th-6th",3,"Divorced","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +24,"Private",194654,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"State-gov",206889,"Assoc-acdm",12,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",200679,"HS-grad",9,"Never-married","Farming-fishing","Own-child","Black","Male",0,0,50,"United-States","<=50K" +71,"Private",183678,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,16,"United-States","<=50K" +17,"Private",33138,"12th",8,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",188576,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +33,"Private",169496,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",58124,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",356344,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",444134,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,15,"United-States","<=50K" +18,"?",340117,"11th",7,"Never-married","?","Unmarried","Black","Female",0,0,50,"United-States","<=50K" +34,"Private",219619,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"?",334585,"10th",6,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States","<=50K" +27,"Local-gov",331046,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +46,"?",443179,"Bachelors",13,"Divorced","?","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +24,"Private",100345,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +23,"Private",205653,"Bachelors",13,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +33,"Private",112383,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",135568,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",190532,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +53,"Federal-gov",266598,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Local-gov",116608,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States",">50K" +36,"Private",353263,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States",">50K" +25,"State-gov",157617,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Federal-gov",21698,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",77143,"12th",8,"Separated","Transport-moving","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +18,"State-gov",342852,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",176602,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",146343,"Some-college",10,"Married-civ-spouse","Sales","Wife","Black","Female",0,0,40,"United-States","<=50K" +22,"Private",215546,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +50,"State-gov",173020,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"?",247734,"Bachelors",13,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +44,"Private",252202,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",497300,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",426431,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Federal-gov",162410,"Some-college",10,"Widowed","Tech-support","Not-in-family","White","Female",0,0,45,"United-States",">50K" +77,"?",143516,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States",">50K" +25,"Private",190350,"10th",6,"Married-civ-spouse","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +20,"Private",194504,"Some-college",10,"Separated","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +46,"Federal-gov",110884,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +26,"Private",187652,"Assoc-acdm",12,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",81400,"1st-4th",2,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,25,"El-Salvador","<=50K" +70,"?",97831,"HS-grad",9,"Widowed","?","Unmarried","White","Female",0,0,4,"United-States","<=50K" +57,"Private",180920,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",189186,"Assoc-voc",11,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"?",144172,"Assoc-acdm",12,"Married-civ-spouse","?","Wife","White","Female",0,0,16,"United-States","<=50K" +32,"Private",207301,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",293073,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +36,"Private",210452,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,45,"United-States","<=50K" +19,"Private",41400,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +27,"Private",164170,"Bachelors",13,"Never-married","Tech-support","Unmarried","Asian-Pac-Islander","Female",0,0,20,"Philippines","<=50K" +48,"Private",112906,"Masters",14,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States",">50K" +49,"Self-emp-not-inc",126268,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +61,"Private",28291,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Female",0,0,82,"United-States","<=50K" +42,"Federal-gov",31621,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Local-gov",108386,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",134727,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",208391,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",112271,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Private",173350,"Assoc-voc",11,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",243190,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,20,"India",">50K" +55,"Private",185436,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States",">50K" +36,"Private",290409,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",80058,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,48,"United-States","<=50K" +56,"Local-gov",370045,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",231180,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",119793,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,60,"United-States","<=50K" +38,"Private",102178,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +76,"?",135039,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +35,"?",317780,"Some-college",10,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +48,"Private",232840,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,43,"United-States","<=50K" +35,"Private",33975,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Local-gov",256997,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Private",298301,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",310380,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +45,"Local-gov",182100,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",501172,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Mexico","<=50K" +43,"State-gov",143939,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States",">50K" +23,"Private",85088,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,37,"United-States","<=50K" +39,"Private",230054,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +63,"Private",236338,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,35,"United-States","<=50K" +37,"Private",321943,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Federal-gov",218782,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Other","Male",0,0,40,"United-States","<=50K" +33,"Private",191385,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"Canada","<=50K" +45,"Self-emp-inc",185497,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","Asian-Pac-Islander","Female",0,0,70,"?","<=50K" +28,"Private",126129,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",199268,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +34,"Private",255693,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States","<=50K" +34,"Private",203488,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",203233,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",203836,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +38,"Private",116358,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +43,"Self-emp-not-inc",89636,"Bachelors",13,"Married-civ-spouse","Sales","Wife","Asian-Pac-Islander","Female",0,0,60,"South","<=50K" +49,"Private",120629,"Some-college",10,"Widowed","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +26,"Local-gov",150226,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,35,"United-States","<=50K" +28,"Private",137898,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +54,"Self-emp-inc",146574,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",88725,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Other","Female",0,0,40,"?","<=50K" +24,"Private",142022,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,50,"United-States","<=50K" +23,"Private",284898,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,30,"United-States","<=50K" +55,"Local-gov",212448,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",203039,"9th",5,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",227489,"HS-grad",9,"Never-married","Tech-support","Other-relative","Black","Male",0,0,40,"?","<=50K" +19,"Private",105289,"10th",6,"Never-married","Other-service","Other-relative","Black","Female",0,0,20,"United-States","<=50K" +28,"?",223745,"Some-college",10,"Never-married","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Private",242994,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +30,"Private",196385,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +76,"Private",116202,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,33,"United-States","<=50K" +47,"Private",140045,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",226585,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States",">50K" +24,"Private",85041,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,25,"United-States","<=50K" +24,"Private",216563,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +43,"Local-gov",231964,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",263855,"12th",8,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +40,"Private",124915,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Federal-gov",178312,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"State-gov",39236,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +52,"Private",75839,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",176711,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"?",34307,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",331776,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",111469,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"State-gov",198965,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",288185,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +21,"Private",198050,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +37,"Private",173128,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",173704,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",323269,"Some-college",10,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,40,"United-States","<=50K" +32,"Private",133503,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",172296,"Some-college",10,"Separated","Sales","Unmarried","White","Male",0,0,60,"United-States","<=50K" +39,"?",201105,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,30,"United-States","<=50K" +23,"Private",176486,"Some-college",10,"Never-married","Other-service","Other-relative","White","Female",0,0,25,"United-States","<=50K" +25,"Self-emp-inc",182750,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States",">50K" +23,"Private",82497,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,28,"United-States","<=50K" +47,"Private",208872,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",145269,"11th",7,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +25,"Private",19214,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",149347,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +68,"?",53850,"7th-8th",4,"Married-civ-spouse","?","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +47,"Private",152073,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",189623,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Private",341368,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",270572,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +30,"Private",285295,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +17,"Private",126779,"11th",7,"Never-married","Other-service","Own-child","Black","Male",0,0,20,"United-States","<=50K" +49,"?",202874,"HS-grad",9,"Separated","?","Unmarried","White","Female",0,0,40,"Columbia","<=50K" +27,"Private",373499,"5th-6th",3,"Never-married","Other-service","Not-in-family","White","Male",0,0,60,"El-Salvador","<=50K" +22,"Private",244773,"HS-grad",9,"Never-married","Sales","Own-child","Black","Female",0,0,15,"United-States","<=50K" +22,"State-gov",96862,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Private",162632,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,2,"United-States","<=50K" +51,"Self-emp-not-inc",159755,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,38,"United-States",">50K" +27,"Private",37088,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,30,"United-States","<=50K" +27,"Private",335421,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +23,"Never-worked",188535,"7th-8th",4,"Divorced","?","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +20,"State-gov",349365,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",33002,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States","<=50K" +45,"Private",146857,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States",">50K" +35,"Private",275522,"7th-8th",4,"Widowed","Other-service","Unmarried","White","Female",0,0,80,"United-States","<=50K" +22,"Private",43646,"HS-grad",9,"Married-civ-spouse","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",154548,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +28,"Private",47907,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",238397,"Bachelors",13,"Divorced","Priv-house-serv","Unmarried","White","Female",0,0,24,"United-States","<=50K" +48,"Local-gov",195949,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,42,"United-States",">50K" +22,"?",354351,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",349169,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +25,"Private",158662,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,50,"United-States",">50K" +23,"Local-gov",23438,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",107302,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +43,"Private",174196,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +49,"Local-gov",226871,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States",">50K" +23,"Private",124971,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Private",214061,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",441700,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-inc",104892,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,58,"United-States",">50K" +34,"Private",234386,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +29,"Local-gov",188278,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",244395,"11th",7,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",30916,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +48,"Private",219565,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",377486,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,36,"United-States","<=50K" +42,"Local-gov",137232,"HS-grad",9,"Divorced","Protective-serv","Unmarried","White","Female",0,0,50,"United-States","<=50K" +53,"Private",233369,"Some-college",10,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",71067,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +59,"Private",195176,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,72,"United-States","<=50K" +31,"Private",98639,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +34,"Private",183778,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"?",147471,"HS-grad",9,"Divorced","?","Own-child","White","Female",0,0,10,"United-States","<=50K" +46,"Private",81497,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +45,"Private",189225,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",141264,"Some-college",10,"Never-married","Exec-managerial","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",97939,"Assoc-acdm",12,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +44,"Private",160829,"Bachelors",13,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,20,"United-States",">50K" +25,"Private",483822,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"El-Salvador","<=50K" +48,"State-gov",148738,"Some-college",10,"Divorced","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",289982,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",146706,"Some-college",10,"Married-civ-spouse","Sales","Other-relative","White","Female",0,0,30,"United-States","<=50K" +23,"Private",420973,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +71,"Private",124959,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"State-gov",121471,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",280758,"11th",7,"Never-married","Craft-repair","Other-relative","White","Male",0,0,60,"United-States","<=50K" +40,"Private",191544,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +30,"Private",261023,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,50,"United-States","<=50K" +30,"State-gov",231043,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",340917,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",370795,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +39,"Federal-gov",209609,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States","<=50K" +74,"Private",209454,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",88922,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +64,"Private",86972,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",134367,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,37,"United-States",">50K" +47,"Private",199058,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",183612,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",191982,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States",">50K" +22,"Private",514033,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,80,"United-States","<=50K" +56,"Private",172364,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",190105,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,55,"United-States","<=50K" +30,"Self-emp-inc",119422,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +20,"Private",236592,"12th",8,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"Italy","<=50K" +43,"Private",194636,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +23,"Private",235853,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",150528,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +30,"Private",213722,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",41432,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,46,"United-States","<=50K" +22,"Private",285775,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",470663,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +54,"Self-emp-not-inc",114520,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",113466,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",224559,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +59,"Private",186385,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"?",167094,"10th",6,"Divorced","?","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +18,"?",216508,"12th",8,"Never-married","?","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +41,"Local-gov",384236,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",181265,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States","<=50K" +58,"Private",190997,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",98287,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"Private",103456,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +25,"Private",165622,"Masters",14,"Never-married","Sales","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +29,"Private",101597,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,54,"United-States","<=50K" +53,"Private",146378,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Local-gov",152163,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"State-gov",106812,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +45,"Private",187581,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",135296,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Private",210736,"10th",6,"Married-spouse-absent","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +21,"Private",210165,"9th",5,"Married-spouse-absent","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",224584,"Some-college",10,"Divorced","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",80771,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +46,"Private",164733,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,41,"United-States","<=50K" +31,"Self-emp-not-inc",119411,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,60,"United-States",">50K" +68,"Local-gov",177596,"10th",6,"Separated","Other-service","Not-in-family","Black","Female",0,0,90,"United-States","<=50K" +43,"?",396116,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",185251,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Private",173590,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,3,"United-States","<=50K" +56,"Federal-gov",196307,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"?",293091,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,12,"United-States","<=50K" +21,"Private",51047,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +52,"Local-gov",152795,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",121548,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,25,"United-States","<=50K" +29,"Private",244566,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +36,"Private",75073,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,55,"United-States","<=50K" +29,"Private",179008,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,55,"United-States","<=50K" +21,"Private",170800,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +58,"Private",373344,"1st-4th",2,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",127961,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",99392,"Some-college",10,"Divorced","Craft-repair","Not-in-family","Black","Female",0,0,45,"United-States","<=50K" +30,"Private",392812,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"Germany","<=50K" +29,"Private",262478,"HS-grad",9,"Never-married","Farming-fishing","Own-child","Black","Male",0,0,30,"United-States","<=50K" +48,"Self-emp-not-inc",32825,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",167380,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",203204,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,25,"United-States",">50K" +35,"Federal-gov",105138,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +24,"Private",182276,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,25,"United-States","<=50K" +20,"Private",275385,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,45,"United-States","<=50K" +30,"Self-emp-not-inc",292472,"Some-college",10,"Married-civ-spouse","Sales","Husband","Amer-Indian-Eskimo","Male",0,0,55,"United-States",">50K" +19,"Self-emp-not-inc",73514,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,30,"United-States","<=50K" +26,"Private",199600,"HS-grad",9,"Never-married","Sales","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",202560,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",99309,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,50,"United-States","<=50K" +30,"Private",287986,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",119411,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",198668,"7th-8th",4,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",117583,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",234664,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"?",114357,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"State-gov",176949,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,52,"United-States","<=50K" +33,"Private",189710,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"Mexico","<=50K" +65,"Private",205309,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,24,"United-States","<=50K" +34,"Private",195576,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +20,"Private",216825,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,25,"Mexico","<=50K" +23,"?",329174,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",197036,"10th",6,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",206512,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +37,"Private",312766,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",124827,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",77820,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Private",190115,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +44,"Private",106682,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +32,"Local-gov",42596,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",143058,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"United-States",">50K" +53,"Private",102615,"11th",7,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"Canada","<=50K" +43,"Private",240124,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",132565,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +52,"Private",96359,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,57,"United-States",">50K" +20,"Private",165201,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,4,"United-States","<=50K" +45,"Private",264526,"Assoc-acdm",12,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",37359,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +61,"?",232618,"Prof-school",15,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Local-gov",115497,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",157747,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States","<=50K" +27,"Self-emp-not-inc",41099,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +38,"Private",472604,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"Mexico","<=50K" +33,"Private",348618,"5th-6th",3,"Married-spouse-absent","Transport-moving","Unmarried","Other","Male",0,0,20,"El-Salvador","<=50K" +43,"Private",135606,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +36,"Private",248445,"HS-grad",9,"Separated","Transport-moving","Other-relative","White","Male",0,0,60,"Mexico","<=50K" +38,"Private",112093,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Local-gov",197552,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",303822,"10th",6,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",288566,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"?",487411,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +39,"State-gov",239409,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,50,"United-States","<=50K" +47,"State-gov",118447,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +46,"Private",234690,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"?",141003,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,60,"United-States","<=50K" +45,"Private",190482,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +55,"Private",381965,"Bachelors",13,"Married-civ-spouse","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +68,"Private",186943,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,8,"United-States","<=50K" +39,"Private",142707,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",53447,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",127772,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",344414,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",194138,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,20,"United-States","<=50K" +49,"?",558183,"Assoc-voc",11,"Married-spouse-absent","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",150154,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",306114,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +72,"?",177121,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,3,"United-States","<=50K" +58,"Local-gov",368797,"Masters",14,"Widowed","Prof-specialty","Unmarried","White","Male",0,0,35,"United-States",">50K" +43,"Self-emp-inc",175715,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,55,"United-States","<=50K" +62,"Private",416829,"11th",7,"Separated","Other-service","Not-in-family","Black","Female",0,0,21,"United-States","<=50K" +21,"Private",350001,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,20,"United-States","<=50K" +26,"Private",339952,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +27,"Private",114967,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Local-gov",166039,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",250135,"HS-grad",9,"Never-married","Prof-specialty","Other-relative","White","Female",0,0,40,"United-States","<=50K" +29,"Private",103628,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +58,"Private",430005,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Self-emp-inc",106517,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",162236,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Private",92430,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",169388,"11th",7,"Divorced","Other-service","Unmarried","White","Female",0,0,15,"United-States","<=50K" +35,"Private",150057,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",75742,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +33,"Private",177675,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"Germany",">50K" +49,"Local-gov",193249,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",266072,"10th",6,"Never-married","Other-service","Not-in-family","White","Male",0,0,20,"El-Salvador","<=50K" +28,"?",80165,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +25,"Private",339324,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +69,"?",111238,"9th",5,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +41,"Self-emp-not-inc",284086,"Assoc-voc",11,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +31,"Private",206051,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",426263,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States",">50K" +40,"Private",277647,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",193061,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +50,"Private",121411,"12th",8,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",89202,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,50,"United-States","<=50K" +17,"Private",232900,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +30,"Local-gov",319280,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +79,"?",165209,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",193494,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +67,"Self-emp-not-inc",195066,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",99146,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +35,"Private",92028,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",174419,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",57916,"7th-8th",4,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Private",383384,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",109813,"11th",7,"Never-married","Tech-support","Other-relative","White","Male",0,0,40,"United-States","<=50K" +17,"Private",174298,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +28,"Private",263614,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",96128,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Private",220262,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",35340,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +47,"Private",280483,"HS-grad",9,"Separated","Craft-repair","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",351324,"Some-college",10,"Never-married","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",58602,"5th-6th",3,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +37,"Private",64922,"Bachelors",13,"Separated","Other-service","Not-in-family","White","Male",0,0,70,"England","<=50K" +43,"Private",185832,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States",">50K" +39,"Federal-gov",32312,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +47,"Self-emp-not-inc",109421,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +42,"Private",183205,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +48,"Local-gov",145886,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,60,"United-States","<=50K" +27,"Private",244566,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",253801,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Ecuador","<=50K" +22,"Private",181313,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +37,"State-gov",150566,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +38,"Private",237713,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +48,"Local-gov",187969,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,80,"United-States","<=50K" +46,"Self-emp-not-inc",224108,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States","<=50K" +51,"Private",174754,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,38,"United-States","<=50K" +35,"Private",167062,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",190325,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,30,"United-States","<=50K" +45,"Private",108859,"HS-grad",9,"Separated","Craft-repair","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",344351,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +73,"Private",153127,"Some-college",10,"Widowed","Priv-house-serv","Unmarried","White","Female",0,0,10,"United-States","<=50K" +52,"Private",180881,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",183066,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Federal-gov",339002,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",185480,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"?",">50K" +20,"Private",172047,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,10,"United-States","<=50K" +37,"Private",302604,"Some-college",10,"Separated","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +40,"Private",248094,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",36467,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +29,"Private",53181,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +20,"Private",181032,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",248990,"11th",7,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",117381,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,80,"United-States",">50K" +18,"?",173125,"12th",8,"Never-married","?","Own-child","White","Female",0,0,24,"United-States","<=50K" +33,"?",316663,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,50,"United-States","<=50K" +26,"Private",154966,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +24,"Private",198259,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +33,"Private",167939,"HS-grad",9,"Married-civ-spouse","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +23,"Private",131275,"HS-grad",9,"Never-married","Craft-repair","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +20,"?",236523,"10th",6,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",272950,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +37,"Private",174503,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +24,"Private",116800,"Assoc-voc",11,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,35,"United-States","<=50K" +38,"Private",110713,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +50,"Private",202044,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,45,"United-States","<=50K" +44,"Private",300528,"11th",7,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",133126,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +37,"Private",74593,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States","<=50K" +44,"Private",302424,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +21,"Private",344492,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +31,"Private",349148,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",234699,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","Black","Female",0,0,60,"United-States",">50K" +20,"Local-gov",243178,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Private",189728,"HS-grad",9,"Separated","Priv-house-serv","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +47,"Self-emp-not-inc",318593,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,25,"United-States","<=50K" +41,"Private",108681,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +40,"Private",187376,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +41,"State-gov",75409,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +49,"Private",266150,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +65,"Private",271092,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"?","<=50K" +50,"Private",135643,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Other-relative","Asian-Pac-Islander","Female",0,0,40,"China","<=50K" +59,"Private",46466,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",130652,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +45,"Private",195554,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +17,"Private",244589,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-inc",271901,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,32,"United-States",">50K" +73,"Private",139978,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",180446,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +64,"?",178724,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"United-States","<=50K" +38,"State-gov",341643,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +37,"Federal-gov",289653,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",187891,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-inc",116338,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +54,"Federal-gov",439608,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +65,"Private",330144,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",251905,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +37,"Private",218955,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",188972,"Doctorate",16,"Separated","Prof-specialty","Unmarried","White","Female",0,0,10,"Canada","<=50K" +60,"Self-emp-not-inc",25825,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States",">50K" +62,"Private",116104,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,20,"Germany","<=50K" +20,"Private",194891,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"?",285131,"Assoc-acdm",12,"Never-married","?","Unmarried","White","Male",0,0,20,"United-States","<=50K" +29,"State-gov",409201,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +74,"Private",97167,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,15,"United-States","<=50K" +37,"Local-gov",244803,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?","<=50K" +51,"Self-emp-not-inc",115851,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",118058,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +42,"Private",258589,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States",">50K" +26,"Private",158810,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +58,"Self-emp-not-inc",165695,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +30,"?",97281,"Some-college",10,"Separated","?","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +23,"Private",170482,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,45,"United-States","<=50K" +35,"Private",241001,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,44,"United-States","<=50K" +50,"Private",165001,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +17,"?",297117,"11th",7,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",340260,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,48,"United-States","<=50K" +31,"Private",96480,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +30,"Private",185177,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,49,"United-States","<=50K" +84,"Self-emp-inc",172907,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States",">50K" +35,"Self-emp-not-inc",308874,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",54098,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States",">50K" +46,"Private",288608,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",254148,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +37,"Private",111128,"11th",7,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",171116,"HS-grad",9,"Divorced","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Federal-gov",276776,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",152878,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",149211,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",58343,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States","<=50K" +38,"Private",127601,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Wife","White","Female",0,0,35,"United-States","<=50K" +29,"Private",357781,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",137367,"Some-college",10,"Never-married","Handlers-cleaners","Other-relative","Asian-Pac-Islander","Male",0,0,44,"Philippines","<=50K" +34,"Private",110978,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +31,"Private",34503,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",223515,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",372525,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,48,"United-States","<=50K" +32,"Private",116365,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States","<=50K" +36,"Private",111268,"Assoc-acdm",12,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +78,"?",83511,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Portugal","<=50K" +46,"Self-emp-not-inc",199596,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States","<=50K" +18,"Private",301867,"HS-grad",9,"Never-married","Sales","Own-child","Amer-Indian-Eskimo","Female",0,0,20,"United-States","<=50K" +57,"Private",191983,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,50,"United-States","<=50K" +37,"Private",105803,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",456236,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",116255,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +32,"Private",235109,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Federal-gov",91716,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +70,"Private",235781,"Some-college",10,"Divorced","Farming-fishing","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +40,"Private",136986,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States",">50K" +40,"Self-emp-not-inc",33658,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",53878,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +29,"Private",200928,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",173736,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +28,"Private",214385,"Assoc-voc",11,"Never-married","Exec-managerial","Own-child","Black","Female",0,0,40,"United-States","<=50K" +58,"Private",102509,"10th",6,"Divorced","Transport-moving","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +18,"Private",329054,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +40,"Private",274158,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-inc",241153,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +45,"Private",229516,"HS-grad",9,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,72,"Mexico","<=50K" +62,"?",250091,"Bachelors",13,"Divorced","?","Not-in-family","White","Male",0,0,5,"United-States","<=50K" +24,"State-gov",247075,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +22,"Private",315524,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,30,"Dominican-Republic","<=50K" +23,"Private",126945,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",29874,"Some-college",10,"Separated","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States",">50K" +28,"Private",115579,"Assoc-voc",11,"Never-married","Tech-support","Own-child","White","Female",0,0,38,"United-States","<=50K" +44,"Private",56483,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,37,"United-States","<=50K" +73,"?",89852,"1st-4th",2,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Portugal","<=50K" +24,"Private",420779,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Black","Male",0,0,35,"United-States","<=50K" +24,"Private",255474,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",241444,"1st-4th",2,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,50,"Puerto-Rico","<=50K" +43,"Private",85995,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +67,"Self-emp-inc",116986,"12th",8,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States","<=50K" +31,"Private",217962,"12th",8,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"?","<=50K" +43,"Private",184099,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",117816,"7th-8th",4,"Divorced","Handlers-cleaners","Other-relative","White","Male",0,0,70,"United-States","<=50K" +23,"Private",263899,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,20,"Haiti","<=50K" +26,"Private",45869,"Bachelors",13,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"Private",186539,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",326310,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +55,"Local-gov",84564,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,39,"United-States","<=50K" +49,"Private",247294,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +34,"Private",72793,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +29,"Private",261375,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,60,"United-States","<=50K" +50,"Private",77905,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +19,"Private",66838,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,9,"United-States","<=50K" +66,"Private",180211,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,30,"Philippines","<=50K" +65,"?",79272,"Some-college",10,"Widowed","?","Not-in-family","Asian-Pac-Islander","Female",0,0,6,"United-States","<=50K" +60,"Private",101198,"Assoc-voc",11,"Divorced","Other-service","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +60,"Private",80574,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,38,"United-States","<=50K" +19,"Private",198663,"HS-grad",9,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Self-emp-inc",160340,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +58,"State-gov",69579,"Some-college",10,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +18,"Self-emp-not-inc",379242,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +26,"Private",259505,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Federal-gov",171335,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +19,"?",541282,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Federal-gov",155970,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",99682,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,52,"Canada",">50K" +23,"Private",117789,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"Private",296158,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"Local-gov",78859,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +59,"?",188070,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,35,"United-States",">50K" +50,"Private",189811,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",360593,"HS-grad",9,"Divorced","Sales","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +40,"Private",145504,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Black","Male",0,0,40,"United-States","<=50K" +19,"Private",459248,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +30,"?",288419,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Mexico","<=50K" +42,"State-gov",126094,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Male",0,0,39,"United-States","<=50K" +23,"Private",209483,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,50,"United-States","<=50K" +21,"Private",210355,"11th",7,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +28,"Private",84547,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +50,"?",260579,"HS-grad",9,"Married-civ-spouse","?","Husband","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",105585,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,25,"United-States","<=50K" +21,"Private",132320,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +21,"Private",129172,"Some-college",10,"Never-married","Other-service","Other-relative","White","Male",0,0,16,"United-States","<=50K" +45,"Self-emp-not-inc",222374,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-inc",201498,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",114157,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"Local-gov",148121,"Bachelors",13,"Married-spouse-absent","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +73,"?",84053,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +34,"Private",96480,"Some-college",10,"Separated","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",179423,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +58,"State-gov",123329,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +41,"Private",134130,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +53,"Private",188644,"Preschool",1,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +40,"Private",226388,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +18,"Private",28648,"11th",7,"Never-married","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +37,"State-gov",34996,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",281422,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,45,"United-States","<=50K" +22,"Private",214716,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"Private",314177,"10th",6,"Never-married","Handlers-cleaners","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +51,"Private",112310,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +63,"Private",203783,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,72,"United-States","<=50K" +29,"Private",205499,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,45,"United-States","<=50K" +44,"Private",155701,"7th-8th",4,"Separated","Other-service","Unmarried","White","Female",0,0,38,"Peru","<=50K" +37,"State-gov",186934,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Federal-gov",209433,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +31,"Private",80933,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States","<=50K" +20,"Private",102607,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +24,"Self-emp-not-inc",102942,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +56,"State-gov",175057,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Federal-gov",68781,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"United-States","<=50K" +29,"Private",108594,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Private",56269,"Some-college",10,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",152503,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,45,"United-States","<=50K" +38,"Self-emp-inc",206951,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States","<=50K" +23,"Private",82393,"9th",5,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Male",0,0,20,"Philippines","<=50K" +37,"Private",167396,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Guatemala","<=50K" +30,"Self-emp-not-inc",123397,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +58,"?",147653,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,36,"United-States","<=50K" +42,"Private",118652,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",182689,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-inc",60949,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +49,"Private",129513,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",84306,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",117507,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +22,"Private",88050,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,6,"United-States","<=50K" +22,"Private",305498,"HS-grad",9,"Divorced","Sales","Own-child","White","Female",0,0,33,"United-States","<=50K" +17,"Private",295308,"11th",7,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,20,"United-States","<=50K" +47,"Private",114459,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",176017,"10th",6,"Never-married","Other-service","Other-relative","White","Male",0,0,15,"United-States","<=50K" +39,"Private",248445,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +23,"Private",214542,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +41,"Private",384508,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Federal-gov",403489,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +21,"Private",254904,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +33,"Private",98995,"10th",6,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +17,"?",237078,"11th",7,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +41,"Private",193995,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +19,"Private",205829,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +38,"Federal-gov",205852,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States",">50K" +24,"Private",37072,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"State-gov",122353,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +19,"Private",100009,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +31,"?",37030,"Assoc-acdm",12,"Never-married","?","Own-child","White","Female",0,0,25,"United-States","<=50K" +42,"Private",135056,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +36,"Private",135162,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,45,"?","<=50K" +29,"Private",280618,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",226717,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +47,"Local-gov",173938,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",291355,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +61,"Federal-gov",160155,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Self-emp-not-inc",29762,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +31,"?",82473,"9th",5,"Divorced","?","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +59,"Private",172071,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,38,"Jamaica","<=50K" +29,"Private",166210,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +26,"Private",330263,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",247043,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Federal-gov",155238,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",130557,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Private",56986,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,18,"United-States","<=50K" +29,"Private",220692,"Assoc-voc",11,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",121650,"5th-6th",3,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,30,"United-States","<=50K" +67,"Private",174603,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +29,"Private",341846,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +32,"Private",34437,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",141058,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,62,"Mexico","<=50K" +49,"Private",192323,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",117674,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"?","<=50K" +39,"Private",28572,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",120277,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",164309,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +47,"Federal-gov",102771,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",147951,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,1,"United-States","<=50K" +44,"Private",173888,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,80,"United-States",">50K" +25,"Private",247006,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +23,"Private",82889,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,16,"United-States","<=50K" +52,"Private",259363,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +62,"Federal-gov",159165,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +31,"Private",112062,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",299050,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +22,"?",186452,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,36,"United-States","<=50K" +53,"Private",548580,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Guatemala","<=50K" +25,"Private",234057,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",241350,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",278322,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",157443,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","Asian-Pac-Islander","Female",0,0,27,"Taiwan",">50K" +44,"Self-emp-not-inc",37618,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Local-gov",238582,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,41,"United-States",">50K" +37,"State-gov",28887,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",77820,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +22,"Private",110946,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Local-gov",230420,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",206521,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"?",156877,"HS-grad",9,"Divorced","?","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +28,"Local-gov",283227,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States","<=50K" +28,"Private",141957,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",58337,"10th",6,"Never-married","Sales","Unmarried","White","Female",0,0,35,"?","<=50K" +73,"Local-gov",161027,"5th-6th",3,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,20,"United-States","<=50K" +37,"Self-emp-not-inc",31670,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +24,"Private",205844,"Bachelors",13,"Never-married","Exec-managerial","Own-child","Black","Female",0,0,65,"United-States","<=50K" +30,"State-gov",46144,"HS-grad",9,"Married-AF-spouse","Adm-clerical","Own-child","White","Female",0,0,38,"United-States","<=50K" +38,"Private",168055,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",98350,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +69,"?",182668,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,45,"United-States",">50K" +42,"Private",334522,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +54,"State-gov",187686,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +27,"State-gov",365916,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,58,"United-States","<=50K" +39,"Private",190719,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +27,"Private",218184,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"Jamaica","<=50K" +30,"Private",222162,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,66,"United-States","<=50K" +37,"Private",267085,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Federal-gov",307555,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States",">50K" +36,"Private",229180,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"Cuba","<=50K" +22,"Private",279041,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,10,"United-States","<=50K" +21,"Private",312017,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +76,"Private",70697,"7th-8th",4,"Widowed","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +22,"?",263970,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +37,"Private",188774,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",302770,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +29,"Private",183639,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,97,"United-States","<=50K" +29,"Private",178551,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",175343,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +73,"Self-emp-not-inc",190078,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States","<=50K" +43,"Private",117627,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +39,"Private",108419,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +74,"Private",183701,"10th",6,"Widowed","Other-service","Not-in-family","Black","Female",0,0,6,"United-States","<=50K" +27,"State-gov",208406,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +47,"Private",148884,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +90,"Private",87285,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,24,"United-States","<=50K" +47,"Private",199058,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +42,"Private",173628,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +69,"Private",370837,"Bachelors",13,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"?",179484,"12th",8,"Never-married","?","Own-child","Other","Male",0,0,40,"United-States","<=50K" +23,"Private",342769,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +44,"Local-gov",65145,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States","<=50K" +47,"Local-gov",272182,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +33,"Private",252168,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +48,"Private",80430,"11th",7,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +39,"Private",189623,"Bachelors",13,"Divorced","Sales","Unmarried","White","Male",0,0,60,"United-States","<=50K" +18,"?",28357,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +52,"Private",226084,"HS-grad",9,"Widowed","Priv-house-serv","Other-relative","White","Female",0,0,40,"United-States","<=50K" +18,"Private",150817,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +27,"Self-emp-inc",190911,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,45,"United-States","<=50K" +45,"Local-gov",255559,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +79,"?",142370,"Prof-school",15,"Married-civ-spouse","?","Husband","White","Male",0,0,10,"United-States","<=50K" +24,"Private",173679,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +25,"Private",35854,"Some-college",10,"Married-spouse-absent","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",82161,"10th",6,"Widowed","Transport-moving","Unmarried","White","Male",0,0,35,"United-States","<=50K" +63,"Self-emp-not-inc",129845,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",226505,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,46,"United-States",">50K" +42,"Private",136419,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +42,"Private",66460,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +63,"Local-gov",379940,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Local-gov",102936,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,55,"United-States","<=50K" +65,"Private",205309,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,20,"United-States","<=50K" +30,"?",156890,"10th",6,"Divorced","?","Unmarried","White","Male",0,0,40,"United-States","<=50K" +46,"Private",137547,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +23,"Private",220168,"HS-grad",9,"Never-married","Sales","Other-relative","Black","Female",0,0,25,"Jamaica","<=50K" +47,"Local-gov",37672,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States","<=50K" +20,"Private",196643,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +21,"?",355686,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,10,"United-States","<=50K" +28,"Private",197484,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +61,"Local-gov",115023,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"State-gov",234824,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,72,"United-States","<=50K" +30,"State-gov",361497,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,72,"United-States",">50K" +29,"Private",351871,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +39,"Private",324231,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",123490,"11th",7,"Divorced","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +32,"Private",188245,"11th",7,"Never-married","Priv-house-serv","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +63,"Private",50349,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,34,"United-States","<=50K" +19,"Self-emp-not-inc",47176,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +57,"State-gov",290661,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States",">50K" +41,"Private",221172,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",188950,"Assoc-voc",11,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",356882,"Doctorate",16,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +43,"Self-emp-inc",150533,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +64,"Self-emp-not-inc",167149,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,25,"United-States","<=50K" +56,"Private",301835,"5th-6th",3,"Separated","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",313729,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",130957,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +17,"Private",197732,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,12,"United-States","<=50K" +17,"Private",250541,"10th",6,"Never-married","Other-service","Own-child","Black","Male",0,0,20,"United-States","<=50K" +29,"Private",218785,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,65,"United-States","<=50K" +23,"?",232512,"HS-grad",9,"Separated","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"Private",194630,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +39,"Private",38721,"HS-grad",9,"Divorced","Priv-house-serv","Unmarried","White","Female",0,0,22,"United-States","<=50K" +36,"Private",201519,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +50,"Private",279337,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States",">50K" +31,"Private",87560,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +56,"Private",208431,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","Black","Female",0,0,32,"United-States","<=50K" +20,"Private",163205,"Some-college",10,"Separated","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +33,"State-gov",137616,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +45,"Private",117556,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +33,"Self-emp-not-inc",24504,"HS-grad",9,"Separated","Craft-repair","Other-relative","White","Male",0,0,50,"United-States","<=50K" +27,"?",157624,"HS-grad",9,"Separated","?","Other-relative","White","Female",0,0,40,"United-States","<=50K" +36,"Private",181721,"10th",6,"Never-married","Farming-fishing","Own-child","Black","Male",0,0,60,"United-States","<=50K" +42,"Local-gov",55363,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +33,"Private",92865,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",258633,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"?","<=50K" +52,"Federal-gov",221532,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +41,"Local-gov",183224,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","Asian-Pac-Islander","Female",0,0,40,"Taiwan",">50K" +30,"Private",381153,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",300871,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",158333,"5th-6th",3,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"Columbia","<=50K" +36,"Private",288103,"11th",7,"Separated","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",108907,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +46,"Private",358533,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States",">50K" +24,"Private",126613,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,8,"United-States","<=50K" +38,"Private",199816,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Private",98228,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,45,"United-States","<=50K" +41,"Local-gov",129060,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",22245,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +36,"Private",226918,"Bachelors",13,"Never-married","Sales","Not-in-family","Black","Male",0,0,48,"United-States","<=50K" +47,"Private",398652,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +59,"Private",268840,"Some-college",10,"Married-civ-spouse","Adm-clerical","Other-relative","White","Female",0,0,16,"United-States",">50K" +35,"?",103710,"Bachelors",13,"Divorced","?","Unmarried","White","Female",0,0,16,"?","<=50K" +59,"Private",91384,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +52,"Private",174767,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +37,"Self-emp-inc",126675,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +52,"Private",82285,"Bachelors",13,"Married-spouse-absent","Other-service","Other-relative","Black","Female",0,0,40,"Haiti","<=50K" +51,"Private",177727,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +67,"Self-emp-not-inc",345236,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +58,"?",347692,"11th",7,"Divorced","?","Not-in-family","Black","Male",0,0,15,"United-States","<=50K" +68,"Private",156000,"10th",6,"Widowed","Other-service","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +71,"Private",228806,"9th",5,"Divorced","Priv-house-serv","Not-in-family","Black","Female",0,0,6,"United-States","<=50K" +49,"Local-gov",184428,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Local-gov",102938,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",161063,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",253752,"10th",6,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",274800,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +31,"Private",129804,"9th",5,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"Puerto-Rico","<=50K" +22,"Federal-gov",65547,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",107658,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +57,"Private",161097,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,26,"United-States","<=50K" +18,"Private",118376,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +32,"Private",131224,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",120985,"HS-grad",9,"Divorced","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",215392,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Private",63685,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,50,"Cambodia","<=50K" +48,"Private",131826,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",211440,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States",">50K" +35,"Private",31023,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +19,"Private",255161,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,25,"United-States","<=50K" +28,"Private",411950,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",318082,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +23,"Local-gov",287988,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Federal-gov",115932,"Bachelors",13,"Divorced","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",60358,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"Private",140117,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,12,"United-States","<=50K" +34,"Private",158040,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +29,"Private",232784,"Assoc-acdm",12,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",349368,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +46,"Federal-gov",325573,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +69,"Private",140176,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,24,"United-States","<=50K" +50,"Private",128478,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +19,"?",318264,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +59,"Private",147989,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"?","<=50K" +45,"Federal-gov",155659,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +41,"State-gov",288433,"Masters",14,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +47,"Federal-gov",329205,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +64,"Private",171373,"11th",7,"Widowed","Farming-fishing","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",228860,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"United-States","<=50K" +17,"Private",47771,"11th",7,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"United-States","<=50K" +24,"Private",201680,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,60,"United-States","<=50K" +28,"Private",337378,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",227714,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +36,"Private",177285,"Assoc-voc",11,"Never-married","Prof-specialty","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +38,"Private",71701,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"Portugal","<=50K" +42,"Private",280167,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Self-emp-inc",27408,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +25,"Private",167031,"10th",6,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"Columbia","<=50K" +41,"Private",173682,"Masters",14,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",278557,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +32,"Private",113688,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +41,"Self-emp-not-inc",252986,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",33669,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +56,"Private",100776,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,50,"United-States","<=50K" +47,"Self-emp-not-inc",177457,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +30,"State-gov",312767,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +51,"Private",43354,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Self-emp-inc",375422,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"South","<=50K" +49,"Self-emp-not-inc",263568,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +67,"?",74335,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,10,"Germany","<=50K" +35,"Private",248010,"Bachelors",13,"Married-spouse-absent","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +37,"?",87369,"9th",5,"Divorced","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",405577,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"State-gov",167065,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",102476,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",175878,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +55,"Private",213894,"11th",7,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +17,"Private",150262,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +40,"Private",75363,"Some-college",10,"Separated","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",272671,"Bachelors",13,"Divorced","Sales","Own-child","White","Male",0,0,50,"United-States","<=50K" +44,"Private",222434,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",171236,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Private",367037,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",304651,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +62,"Private",97017,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +45,"State-gov",320818,"Some-college",10,"Married-spouse-absent","Other-service","Other-relative","Black","Male",0,0,40,"Haiti","<=50K" +47,"Self-emp-not-inc",84735,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,20,"United-States",">50K" +49,"Private",184428,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",326886,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +24,"?",169624,"HS-grad",9,"Divorced","?","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +29,"Private",212102,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +23,"Private",175837,"11th",7,"Never-married","Farming-fishing","Other-relative","White","Female",0,0,40,"Puerto-Rico","<=50K" +50,"Private",177487,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",171424,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",194981,"HS-grad",9,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,36,"United-States","<=50K" +73,"Private",199362,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States","<=50K" +24,"Private",204226,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"State-gov",72506,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,40,"United-States","<=50K" +37,"Federal-gov",194630,"Masters",14,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",391867,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",94080,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",289405,"11th",7,"Never-married","Machine-op-inspct","Own-child","Other","Male",0,0,12,"United-States","<=50K" +30,"Private",170130,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",447739,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +76,"?",312500,"5th-6th",3,"Widowed","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +65,"?",293385,"Preschool",1,"Married-civ-spouse","?","Husband","Black","Male",0,0,30,"United-States","<=50K" +25,"Private",106377,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",66118,"Bachelors",13,"Divorced","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +47,"Private",274883,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Local-gov",123773,"Assoc-acdm",12,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +42,"Local-gov",70655,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +49,"Private",177426,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +19,"State-gov",159269,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,15,"United-States","<=50K" +24,"Private",235894,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,38,"United-States","<=50K" +34,"Local-gov",97723,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",167309,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",98106,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",108993,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",265954,"Bachelors",13,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-inc",100960,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +45,"Private",170092,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +54,"Private",326156,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",216932,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",214014,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",99872,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +61,"State-gov",151459,"10th",6,"Never-married","Other-service","Not-in-family","Black","Female",0,0,38,"United-States","<=50K" +56,"Private",367200,"HS-grad",9,"Divorced","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +51,"Local-gov",168539,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +50,"Private",140741,"11th",7,"Never-married","Machine-op-inspct","Other-relative","White","Female",0,0,40,"United-States","<=50K" +25,"Private",197651,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,43,"United-States","<=50K" +46,"Private",123053,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,50,"Japan",">50K" +23,"Private",330571,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +44,"Private",204235,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"State-gov",346766,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"?",257250,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",163396,"Some-college",10,"Never-married","Tech-support","Not-in-family","Other","Female",0,0,40,"United-States","<=50K" +18,"Private",36251,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +61,"?",222395,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"State-gov",29152,"12th",8,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +33,"Private",79303,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +35,"Private",272338,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +55,"State-gov",200497,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +19,"Private",148392,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +43,"State-gov",129298,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Local-gov",174981,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,47,"United-States",">50K" +48,"Local-gov",328610,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +27,"Private",77774,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,34,"United-States","<=50K" +29,"Private",153805,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","Other","Male",0,0,40,"Ecuador","<=50K" +27,"Private",168827,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,2,"United-States","<=50K" +31,"Private",373432,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States","<=50K" +26,"Private",57600,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Self-emp-not-inc",302847,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +23,"Private",227594,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +32,"Federal-gov",44777,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","Black","Male",0,0,46,"United-States","<=50K" +54,"?",133963,"HS-grad",9,"Widowed","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",279615,"Bachelors",13,"Divorced","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",276133,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +62,"Private",136314,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +43,"Private",184625,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +34,"Self-emp-inc",265917,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",158647,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",22055,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",0,0,60,"United-States","<=50K" +41,"Local-gov",176716,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +42,"Private",270721,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +24,"Private",100321,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +35,"Private",79050,"HS-grad",9,"Never-married","Transport-moving","Unmarried","Black","Male",0,0,72,"United-States","<=50K" +40,"Local-gov",42703,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +46,"Private",116952,"7th-8th",4,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States","<=50K" +45,"Private",331643,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +68,"Private",223486,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,7,"England","<=50K" +33,"Private",340332,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","Black","Female",0,0,45,"United-States","<=50K" +23,"Private",184813,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +42,"Self-emp-not-inc",32185,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +30,"Private",197886,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States",">50K" +35,"State-gov",248374,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +40,"Private",382499,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States","<=50K" +46,"Self-emp-inc",161386,"9th",5,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,50,"United-States","<=50K" +49,"Local-gov",110172,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",144032,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +26,"Private",224426,"Masters",14,"Never-married","Exec-managerial","Own-child","White","Male",0,0,38,"United-States","<=50K" +37,"Private",230408,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +50,"Local-gov",20795,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",174714,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +30,"Private",149531,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",34113,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +44,"Local-gov",323790,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",331381,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",160647,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"Ireland",">50K" +34,"Private",339142,"HS-grad",9,"Separated","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +58,"Private",164857,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,99,"United-States","<=50K" +33,"Local-gov",267859,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",167725,"Bachelors",13,"Married-spouse-absent","Transport-moving","Not-in-family","Other","Male",0,0,84,"India","<=50K" +67,"Self-emp-not-inc",105907,"1st-4th",2,"Widowed","Other-service","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +23,"Private",200677,"10th",6,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",193882,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Private",138026,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +49,"Private",122385,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",49020,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +26,"Private",283715,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",166416,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",156334,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Local-gov",45607,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States",">50K" +40,"Local-gov",112362,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",200419,"Assoc-acdm",12,"Separated","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +42,"State-gov",341638,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +25,"?",34161,"12th",8,"Separated","?","Unmarried","White","Female",0,0,30,"United-States","<=50K" +50,"Self-emp-not-inc",127151,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"Canada",">50K" +52,"Private",321959,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","Black","Male",0,0,40,"United-States",">50K" +51,"Local-gov",35211,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +19,"Private",214935,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",132130,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",222247,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",165799,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +30,"Private",257874,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +38,"Private",357173,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"State-gov",305739,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",172047,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",110677,"Some-college",10,"Separated","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"?",405684,"HS-grad",9,"Never-married","?","Other-relative","White","Male",0,0,35,"Mexico","<=50K" +60,"Private",82388,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,38,"United-States","<=50K" +45,"Private",289230,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,48,"United-States",">50K" +49,"State-gov",336509,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",383402,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +40,"Private",280362,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States","<=50K" +42,"Private",173704,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",433375,"1st-4th",2,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"Mexico","<=50K" +63,"Self-emp-not-inc",106551,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",22418,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",54816,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",358199,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +43,"Private",190044,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",97698,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +56,"Private",53366,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",236136,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +44,"Private",326232,"7th-8th",4,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +34,"Private",581071,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Male",0,0,48,"United-States",">50K" +40,"Private",220589,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Federal-gov",161463,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +44,"Private",95255,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Federal-gov",223267,"Some-college",10,"Divorced","Protective-serv","Own-child","White","Male",0,0,72,"United-States","<=50K" +22,"Private",236769,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,20,"England","<=50K" +58,"Self-emp-inc",229498,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",0,0,20,"United-States",">50K" +43,"Private",177083,"Some-college",10,"Divorced","Tech-support","Unmarried","White","Female",0,0,30,"United-States","<=50K" +23,"Private",287681,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"Columbia","<=50K" +41,"Private",49797,"Some-college",10,"Separated","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +44,"Private",174051,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +32,"Private",194901,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Local-gov",252250,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,56,"United-States",">50K" +47,"Private",191277,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",174907,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +39,"Private",167140,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",236543,"12th",8,"Divorced","Protective-serv","Own-child","White","Male",0,0,54,"Mexico","<=50K" +40,"Private",214242,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +71,"Private",200418,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Local-gov",167334,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +54,"Private",146834,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +26,"Private",78424,"Assoc-voc",11,"Never-married","Sales","Unmarried","White","Female",0,0,54,"United-States","<=50K" +37,"Private",182675,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,45,"United-States",">50K" +28,"Self-emp-not-inc",38079,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,55,"United-States","<=50K" +42,"Private",115178,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,15,"United-States","<=50K" +45,"Private",195949,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",167415,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"Private",223214,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"Private",22245,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +45,"State-gov",81853,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Asian-Pac-Islander","Female",0,0,40,"United-States",">50K" +30,"Private",147921,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,46,"United-States","<=50K" +27,"Private",29261,"HS-grad",9,"Married-AF-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",257758,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",205493,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,60,"United-States",">50K" +19,"Private",71650,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Private",150217,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +55,"Self-emp-inc",258648,"10th",6,"Widowed","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"Private",114798,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +43,"Private",186188,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Local-gov",175255,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"United-States","<=50K" +45,"Private",249935,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +44,"Private",120277,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States",">50K" +26,"Private",193165,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,52,"United-States",">50K" +21,"Private",221418,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Federal-gov",56063,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +34,"Private",153927,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"State-gov",163110,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +40,"Self-emp-inc",175696,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,51,"United-States","<=50K" +46,"Private",143189,"5th-6th",3,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"Dominican-Republic","<=50K" +20,"?",114969,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"State-gov",32778,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",150683,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-inc",78104,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +42,"Self-emp-not-inc",201520,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"Private",124111,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +60,"Private",166386,"11th",7,"Married-civ-spouse","Machine-op-inspct","Wife","Asian-Pac-Islander","Female",0,0,30,"Hong","<=50K" +43,"State-gov",117471,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",361307,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Private",142038,"HS-grad",9,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,45,"United-States","<=50K" +35,"Private",276552,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",50402,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",174090,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States",">50K" +27,"Private",277760,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",165278,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,22,"United-States","<=50K" +49,"Private",182752,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +31,"Private",173002,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +59,"Private",261232,"11th",7,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",164607,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",129573,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +51,"Federal-gov",36186,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",325744,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-inc",329793,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +46,"Private",133616,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +55,"Private",83401,"5th-6th",3,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +76,"Private",239880,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +25,"Private",201737,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",143540,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",28334,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",245873,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +42,"Local-gov",199095,"Assoc-voc",11,"Widowed","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +41,"Local-gov",575442,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"State-gov",184682,"Assoc-acdm",12,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",69251,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +31,"Private",225507,"Assoc-voc",11,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",407068,"1st-4th",2,"Married-spouse-absent","Other-service","Not-in-family","White","Male",0,0,40,"Guatemala","<=50K" +40,"Private",170019,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"?","<=50K" +46,"Local-gov",125892,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Local-gov",35824,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +35,"Private",67083,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +23,"Private",107801,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +50,"Self-emp-not-inc",95577,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,12,"?","<=50K" +43,"Private",118536,"HS-grad",9,"Divorced","Machine-op-inspct","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +61,"Private",198078,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",78261,"Prof-school",15,"Never-married","Prof-specialty","Own-child","White","Male",0,0,50,"United-States","<=50K" +21,"Private",234108,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",92717,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",257683,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +90,"Private",40388,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +24,"Private",55424,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Local-gov",319271,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +37,"Self-emp-not-inc",75050,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +31,"Private",182896,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",188274,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",211497,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Local-gov",172246,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +48,"Local-gov",219962,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"?",186815,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"?",132749,"Bachelors",13,"Never-married","?","Not-in-family","White","Female",0,0,80,"United-States","<=50K" +28,"Private",209801,"9th",5,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +20,"State-gov",178517,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Private",169364,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"Ireland","<=50K" +32,"Federal-gov",164707,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +55,"Private",144084,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",133692,"Bachelors",13,"Divorced","Protective-serv","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-inc",145290,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +65,"Local-gov",24824,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",235829,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"?",196280,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +42,"Self-emp-not-inc",54202,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",59146,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +67,"Private",64148,"Some-college",10,"Divorced","Other-service","Unmarried","Black","Female",0,0,41,"United-States","<=50K" +28,"Private",196621,"HS-grad",9,"Married-spouse-absent","Tech-support","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +56,"Private",195668,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"Cuba",">50K" +31,"State-gov",263000,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,38,"United-States","<=50K" +33,"Private",554986,"Some-college",10,"Separated","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +52,"?",108211,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",217654,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Germany",">50K" +47,"Private",102771,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Portugal","<=50K" +40,"Private",213019,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +35,"Private",228493,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,48,"United-States","<=50K" +65,"Self-emp-not-inc",22907,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",24364,"Some-college",10,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,30,"United-States","<=50K" +23,"Federal-gov",41432,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +39,"Private",235259,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",343476,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +37,"Private",326886,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",248313,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",30290,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Private",188540,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +39,"Private",237943,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States",">50K" +25,"Private",198870,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,35,"United-States","<=50K" +30,"Private",233980,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",171090,"9th",5,"Married-civ-spouse","Machine-op-inspct","Wife","Black","Female",0,0,48,"United-States","<=50K" +22,"Private",353039,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Female",0,0,36,"Mexico","<=50K" +33,"Private",130057,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +70,"State-gov",345339,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",182074,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +53,"Local-gov",176557,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,50,"United-States","<=50K" +17,"Private",159849,"11th",7,"Never-married","Protective-serv","Own-child","White","Female",0,0,30,"United-States","<=50K" +36,"Private",183425,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",125933,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,55,"United-States",">50K" +40,"Local-gov",180123,"HS-grad",9,"Married-spouse-absent","Farming-fishing","Own-child","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",592930,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,50,"United-States",">50K" +28,"Private",183802,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +49,"Private",80914,"5th-6th",3,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +63,"Self-emp-inc",165667,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",123991,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,20,"United-States","<=50K" +48,"Self-emp-inc",181307,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +55,"Private",124137,"HS-grad",9,"Married-spouse-absent","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"Poland","<=50K" +18,"?",137363,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,4,"United-States","<=50K" +20,"Private",291979,"HS-grad",9,"Married-civ-spouse","Sales","Other-relative","White","Male",0,0,20,"United-States","<=50K" +49,"Private",91251,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +27,"Federal-gov",148153,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +37,"Private",131463,"10th",6,"Divorced","Other-service","Unmarried","White","Female",0,0,33,"United-States","<=50K" +32,"State-gov",127651,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-inc",239018,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +47,"Private",276087,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,26,"United-States","<=50K" +34,"Private",386877,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +61,"Private",210464,"HS-grad",9,"Divorced","Adm-clerical","Other-relative","Black","Female",0,0,35,"United-States","<=50K" +25,"Private",632834,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",245465,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +18,"Private",198087,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +35,"Private",27408,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",242713,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"?","<=50K" +56,"Private",314727,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States",">50K" +40,"State-gov",269733,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",177287,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,38,"United-States","<=50K" +66,"Private",167711,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,40,"United-States",">50K" +42,"Private",112181,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +28,"Private",339002,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,20,"United-States","<=50K" +39,"State-gov",24721,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +65,"Self-emp-not-inc",37092,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,25,"United-States","<=50K" +20,"Private",216563,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +39,"Private",187089,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",423052,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +49,"Private",169180,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"Hong","<=50K" +21,"Private",104981,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,48,"United-States","<=50K" +35,"?",120074,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States","<=50K" +38,"Private",269323,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Private",141549,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",214858,"10th",6,"Married-civ-spouse","Craft-repair","Other-relative","White","Male",0,0,55,"United-States","<=50K" +34,"Private",173524,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +54,"Local-gov",365049,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +38,"Private",60355,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",86808,"HS-grad",9,"Divorced","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +33,"State-gov",174171,"Some-college",10,"Separated","Tech-support","Not-in-family","White","Male",0,0,12,"United-States","<=50K" +32,"Federal-gov",504951,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",294064,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"France","<=50K" +46,"Private",120131,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States",">50K" +48,"Private",199058,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",152328,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"Federal-gov",88564,"7th-8th",4,"Married-spouse-absent","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +67,"Private",95113,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,37,"United-States",">50K" +25,"Private",178421,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +27,"Local-gov",225291,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Private",205735,"1st-4th",2,"Separated","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",184362,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,25,"United-States","<=50K" +27,"Private",347513,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",138768,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",29810,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Private",126501,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",60783,"10th",6,"Never-married","Craft-repair","Own-child","White","Male",0,0,15,"United-States","<=50K" +26,"Private",179772,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +45,"Self-emp-inc",281911,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +33,"Private",70447,"HS-grad",9,"Never-married","Transport-moving","Other-relative","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +55,"?",449576,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,48,"Mexico","<=50K" +29,"Private",327964,"9th",5,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",153066,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +53,"State-gov",77651,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",119493,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"Private",256240,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +41,"Local-gov",37848,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,25,"United-States","<=50K" +45,"Private",129336,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +27,"Private",183511,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",190508,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,35,"United-States","<=50K" +31,"Private",363130,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +45,"Private",240356,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +64,"Private",133166,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,5,"United-States","<=50K" +38,"Private",32916,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +17,"Private",117477,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",459463,"12th",8,"Married-spouse-absent","Other-service","Unmarried","Black","Female",0,0,50,"United-States","<=50K" +23,"Private",95989,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +25,"Private",118088,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +31,"?",505438,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"Mexico","<=50K" +37,"Private",179731,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +28,"Local-gov",163942,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",106670,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +41,"Private",123403,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-inc",119986,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Private",66622,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +20,"?",40060,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,56,"United-States","<=50K" +35,"Private",260578,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States",">50K" +64,"Local-gov",96076,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",70604,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,38,"United-States","<=50K" +53,"Private",49715,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +28,"Private",116531,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Federal-gov",214542,"Some-college",10,"Divorced","Handlers-cleaners","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +25,"Local-gov",335005,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"Italy","<=50K" +19,"Private",258633,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +20,"Private",203240,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +27,"Private",104457,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +21,"?",479482,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +30,"Private",167790,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",106843,"10th",6,"Never-married","Craft-repair","Other-relative","White","Male",0,0,30,"United-States","<=50K" +26,"Private",174921,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",134152,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +57,"Private",99364,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +18,"Local-gov",155905,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,60,"United-States","<=50K" +30,"Private",467108,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +34,"Self-emp-not-inc",304622,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,50,"United-States","<=50K" +60,"Private",178050,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +25,"Private",162687,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",113151,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +48,"Private",158924,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +27,"Self-emp-not-inc",141795,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"United-States","<=50K" +33,"Self-emp-not-inc",33404,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,65,"United-States",">50K" +65,"Self-emp-inc",178771,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",110648,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",151053,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",142871,"Some-college",10,"Separated","Sales","Unmarried","White","Male",0,0,50,"United-States","<=50K" +18,"?",343161,"11th",7,"Never-married","?","Own-child","White","Male",0,0,16,"United-States","<=50K" +27,"Private",183523,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +57,"Self-emp-not-inc",222216,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,60,"United-States","<=50K" +44,"Private",121874,"Some-college",10,"Divorced","Sales","Unmarried","White","Male",0,0,55,"United-States",">50K" +30,"Private",467108,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,44,"United-States",">50K" +26,"Private",34393,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Federal-gov",42003,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +61,"Private",180418,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Self-emp-not-inc",199590,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"Mexico","<=50K" +50,"Private",155594,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States",">50K" +53,"Self-emp-not-inc",162576,"7th-8th",4,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,99,"United-States","<=50K" +33,"Private",232475,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",269474,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,10,"United-States","<=50K" +45,"Local-gov",140644,"Bachelors",13,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States",">50K" +26,"?",39640,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +50,"?",346014,"7th-8th",4,"Separated","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +47,"Self-emp-not-inc",159726,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Federal-gov",290856,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",217886,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +21,"?",199915,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +50,"Local-gov",220640,"Masters",14,"Divorced","Prof-specialty","Not-in-family","Amer-Indian-Eskimo","Female",0,0,50,"United-States",">50K" +33,"Federal-gov",88913,"Some-college",10,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",288486,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",227411,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +57,"Private",201112,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",123778,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +21,"Private",204596,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Female",0,0,8,"United-States","<=50K" +40,"Private",190290,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",196674,"Some-college",10,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Private",108435,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,20,"United-States","<=50K" +38,"Private",186359,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +22,"State-gov",262819,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",171655,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +42,"Private",183319,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +36,"Private",127306,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,47,"United-States","<=50K" +22,"Private",68678,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States","<=50K" +40,"State-gov",140108,"9th",5,"Separated","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",263444,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +46,"State-gov",265554,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +28,"Private",410216,"11th",7,"Married-civ-spouse","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States",">50K" +46,"State-gov",20534,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +55,"Private",188917,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +76,"Private",98695,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +27,"Private",411950,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +50,"Private",237819,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +75,"Private",187424,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +42,"Federal-gov",198316,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Local-gov",139703,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +51,"Private",152596,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",82601,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"?",229843,"Some-college",10,"Never-married","?","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +60,"Private",122276,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"Italy","<=50K" +47,"State-gov",188386,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +73,"Private",92298,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,15,"United-States","<=50K" +27,"Private",390657,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",314897,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +31,"Private",166343,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Male",0,0,50,"?","<=50K" +45,"Private",88781,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Germany",">50K" +57,"Private",41762,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"South",">50K" +34,"Private",849857,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Nicaragua","<=50K" +19,"Private",307496,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +25,"Private",324372,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",99270,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"Germany",">50K" +28,"Private",160731,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Poland",">50K" +48,"State-gov",148306,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",259019,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +53,"Private",224894,"5th-6th",3,"Married-civ-spouse","Priv-house-serv","Wife","Black","Female",0,0,10,"Haiti","<=50K" +19,"Private",258470,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",197919,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,60,"United-States","<=50K" +23,"Private",213719,"Assoc-acdm",12,"Never-married","Sales","Own-child","Black","Female",0,0,36,"United-States","<=50K" +32,"Private",226535,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",146042,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +24,"Private",99970,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",300687,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +29,"Local-gov",219906,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,25,"United-States",">50K" +24,"Private",122234,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,20,"?","<=50K" +55,"Private",158641,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",239539,"HS-grad",9,"Married-spouse-absent","Machine-op-inspct","Own-child","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +46,"Local-gov",102308,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",186934,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",234447,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",125933,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +29,"Private",142760,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +41,"State-gov",309056,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +40,"Self-emp-not-inc",48859,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,32,"United-States","<=50K" +30,"Private",110594,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +72,"Private",426562,"11th",7,"Divorced","Other-service","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +17,"Private",169037,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-inc",123075,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,70,"United-States","<=50K" +38,"Private",195744,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +36,"Private",81896,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +24,"Self-emp-not-inc",172047,"Assoc-acdm",12,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",253814,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +28,"Private",66473,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",271521,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Other","Male",0,0,40,"United-States",">50K" +48,"Private",265295,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Self-emp-not-inc",174308,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",196342,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +30,"Private",149787,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +68,"Private",124686,"7th-8th",4,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +45,"Private",50163,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +26,"Private",175789,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",218215,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",166371,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Private",145081,"7th-8th",4,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +68,"Private",214521,"Prof-school",15,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,16,"United-States","<=50K" +26,"Local-gov",287233,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,40,"United-States",">50K" +52,"Private",201310,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"?","<=50K" +17,"Private",127366,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,8,"United-States","<=50K" +29,"Private",203697,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Own-child","White","Male",0,0,75,"United-States","<=50K" +41,"Private",168730,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Private",165232,"Some-college",10,"Divorced","Tech-support","Not-in-family","Black","Female",0,0,40,"Trinadad&Tobago","<=50K" +57,"Private",175942,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +30,"Federal-gov",356689,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,30,"Japan","<=50K" +46,"Private",132912,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +45,"Private",187226,"Assoc-acdm",12,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"?",254765,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",202565,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,52,"United-States","<=50K" +22,"Private",112164,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"?","<=50K" +59,"Self-emp-not-inc",70623,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,85,"United-States","<=50K" +36,"Private",102729,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",558944,"7th-8th",4,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",256967,"10th",6,"Never-married","Sales","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +62,"?",144583,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Private",102412,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",159788,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,80,"United-States","<=50K" +27,"Private",55743,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,45,"United-States",">50K" +47,"State-gov",148171,"Doctorate",16,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,50,"France",">50K" +20,"Local-gov",271354,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"Private",98524,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +29,"Private",272913,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,30,"Mexico","<=50K" +22,"Private",324445,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",155469,"Assoc-acdm",12,"Widowed","Tech-support","Unmarried","White","Female",0,0,24,"United-States","<=50K" +36,"Private",102945,"Assoc-voc",11,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +60,"Private",291904,"10th",6,"Divorced","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +41,"Federal-gov",186601,"HS-grad",9,"Separated","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",172401,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",193285,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +34,"Private",176244,"7th-8th",4,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +32,"Private",117779,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Female",0,0,35,"United-States","<=50K" +22,"?",34616,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +52,"Private",169182,"9th",5,"Widowed","Other-service","Not-in-family","White","Female",0,0,25,"Puerto-Rico","<=50K" +27,"Private",180758,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +60,"Local-gov",141637,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Self-emp-not-inc",101266,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,62,"United-States","<=50K" +30,"Private",164190,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",142282,"Some-college",10,"Separated","Other-service","Unmarried","White","Female",0,0,25,"United-States","<=50K" +39,"Federal-gov",103984,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +64,"Private",187601,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Self-emp-not-inc",36218,"11th",7,"Never-married","Farming-fishing","Own-child","White","Male",0,0,20,"United-States","<=50K" +29,"State-gov",106334,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"?","<=50K" +37,"Local-gov",249392,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Self-emp-not-inc",110355,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Self-emp-not-inc",117944,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,25,"United-States","<=50K" +17,"Private",163836,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,12,"United-States","<=50K" +29,"Private",145592,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Guatemala","<=50K" +24,"Private",108495,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"India","<=50K" +27,"Self-emp-not-inc",212041,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +69,"Self-emp-inc",182451,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",124020,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",199116,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +17,"?",144114,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +70,"Private",405362,"7th-8th",4,"Widowed","Other-service","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +21,"?",262241,"HS-grad",9,"Never-married","?","Other-relative","White","Male",0,0,40,"United-States","<=50K" +27,"Private",86681,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",187161,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +44,"State-gov",691903,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,60,"United-States",">50K" +36,"Private",219483,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",192010,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"Poland","<=50K" +28,"Local-gov",356089,"Bachelors",13,"Never-married","Prof-specialty","Other-relative","White","Male",0,0,50,"United-States","<=50K" +34,"Private",684015,"5th-6th",3,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"El-Salvador","<=50K" +18,"Private",36882,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +39,"Private",203180,"Some-college",10,"Divorced","Farming-fishing","Unmarried","White","Female",0,0,45,"United-States","<=50K" +34,"Private",183811,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Local-gov",103966,"Masters",14,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,41,"United-States","<=50K" +24,"Private",304602,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",57233,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States","<=50K" +68,"Private",224019,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +35,"Private",267966,"11th",7,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +47,"Private",214800,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",241528,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",197365,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",296724,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,17,"United-States","<=50K" +26,"Private",136226,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Private",40623,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",264874,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"Private",112847,"HS-grad",9,"Never-married","Farming-fishing","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +18,"?",236090,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",89028,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +71,"State-gov",210673,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,28,"United-States","<=50K" +55,"Private",60193,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Private",216137,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,8,"United-States","<=50K" +36,"Private",139743,"Some-college",10,"Widowed","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"?",32276,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",298871,"Bachelors",13,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +42,"Private",318255,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +57,"Private",279636,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States",">50K" +34,"Private",405386,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,28,"United-States","<=50K" +31,"Private",297188,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +24,"Private",182342,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",229148,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,60,"Jamaica","<=50K" +17,"Private",413557,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,32,"United-States","<=50K" +26,"Self-emp-inc",246025,"HS-grad",9,"Separated","Sales","Unmarried","White","Female",0,0,20,"Honduras","<=50K" +32,"Private",390997,"1st-4th",2,"Never-married","Farming-fishing","Not-in-family","Other","Male",0,0,50,"Mexico","<=50K" +55,"Private",102058,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +19,"Private",247298,"12th",8,"Married-spouse-absent","Other-service","Own-child","Other","Female",0,0,20,"United-States","<=50K" +28,"Private",140108,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +49,"Private",81654,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +23,"Private",177526,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",64631,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",110028,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",203761,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",163870,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",50648,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +21,"Private",166517,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"?",173800,"Bachelors",13,"Married-spouse-absent","?","Not-in-family","Asian-Pac-Islander","Female",0,0,10,"Taiwan","<=50K" +44,"Self-emp-inc",181762,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +31,"Self-emp-not-inc",340880,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +54,"Private",138847,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Private",215014,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",183778,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",273629,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Self-emp-inc",113870,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +29,"Private",114982,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",205338,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +90,"?",225063,"Some-college",10,"Never-married","?","Own-child","Asian-Pac-Islander","Male",0,0,10,"South","<=50K" +20,"Private",281356,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Other","Male",0,0,40,"United-States","<=50K" +31,"Private",38223,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,45,"United-States","<=50K" +23,"Private",172232,"HS-grad",9,"Never-married","Tech-support","Own-child","White","Male",0,0,50,"United-States","<=50K" +60,"Private",140544,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",221366,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",180799,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +44,"Self-emp-not-inc",155930,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +34,"Private",201122,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +27,"Private",101709,"HS-grad",9,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +49,"Private",140121,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,50,"United-States","<=50K" +48,"Private",172709,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +47,"Private",120131,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Private",117444,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +27,"Private",256764,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",223811,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",201603,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +25,"Private",138765,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",133974,"Assoc-voc",11,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Federal-gov",137953,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +57,"Private",103403,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",461678,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States",">50K" +41,"State-gov",70884,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"State-gov",466498,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,60,"United-States",">50K" +19,"Private",148644,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +44,"Private",190739,"HS-grad",9,"Never-married","Other-service","Other-relative","Black","Male",0,0,32,"United-States","<=50K" +34,"Private",299507,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",211424,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"State-gov",106721,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",192017,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",119153,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",202450,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States",">50K" +21,"Private",50341,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +24,"Private",140001,"Some-college",10,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Italy","<=50K" +19,"?",220517,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,15,"United-States","<=50K" +82,"?",52921,"Some-college",10,"Widowed","?","Not-in-family","Amer-Indian-Eskimo","Male",0,0,3,"United-States","<=50K" +35,"Private",31964,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +32,"Private",148207,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",151627,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +30,"Private",402539,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",188278,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +28,"Self-emp-not-inc",96219,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,5,"United-States","<=50K" +29,"Private",340534,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +60,"Private",160339,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Columbia","<=50K" +28,"Private",120135,"Assoc-voc",11,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Federal-gov",303817,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",181091,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",200515,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"United-States",">50K" +42,"Private",160893,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,23,"United-States","<=50K" +40,"Local-gov",183096,"9th",5,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"Yugoslavia",">50K" +24,"Private",241367,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-inc",342084,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +36,"Private",193855,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",80410,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",554317,"9th",5,"Married-spouse-absent","Other-service","Other-relative","White","Male",0,0,35,"Mexico","<=50K" +28,"Private",108569,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,43,"United-States","<=50K" +34,"Private",120959,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Private",222011,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,43,"United-States","<=50K" +43,"Private",238530,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",48404,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",243923,"HS-grad",9,"Married-civ-spouse","Transport-moving","Other-relative","White","Male",0,0,80,"United-States","<=50K" +39,"Private",305597,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",129764,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",150993,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +63,"Self-emp-not-inc",147140,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +48,"Private",167967,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",133278,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +39,"Private",192251,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States",">50K" +43,"Private",210844,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States",">50K" +28,"Private",263015,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"State-gov",232918,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +48,"Private",143542,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",45607,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +62,"Private",29828,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",104118,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",27484,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +40,"Private",205987,"Prof-school",15,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"Cuba","<=50K" +39,"Local-gov",143385,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"?",200508,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",186995,"HS-grad",9,"Divorced","Protective-serv","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",54159,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,38,"United-States","<=50K" +39,"Private",113481,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +30,"Local-gov",235271,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",349365,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,65,"United-States","<=50K" +18,"Private",283637,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",70282,"Assoc-acdm",12,"Never-married","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +26,"Private",166051,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Private",193720,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,42,"United-States","<=50K" +35,"?",124836,"Some-college",10,"Divorced","?","Not-in-family","Amer-Indian-Eskimo","Female",0,0,36,"United-States","<=50K" +33,"Private",236379,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +46,"Private",122026,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States",">50K" +40,"Private",114537,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Private",191834,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +29,"Private",420054,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",160045,"Some-college",10,"Widowed","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +34,"Private",303187,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"?",">50K" +45,"Private",190088,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",0,0,30,"United-States","<=50K" +53,"Private",126977,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +52,"Self-emp-not-inc",63004,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +64,"Private",391121,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",211450,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States",">50K" +44,"Private",156413,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,44,"United-States",">50K" +53,"Local-gov",204447,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,43,"United-States",">50K" +25,"Private",66935,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +20,"Private",344278,"11th",7,"Separated","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",108574,"Assoc-voc",11,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,40,"United-States","<=50K" +56,"Private",244605,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Private",219762,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,35,"United-States","<=50K" +62,"Private",77884,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +28,"Self-emp-not-inc",70100,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +24,"Private",69640,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +65,"Private",170012,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,34,"United-States","<=50K" +40,"Private",329924,"HS-grad",9,"Separated","Handlers-cleaners","Not-in-family","Black","Male",0,0,30,"United-States","<=50K" +31,"Private",193285,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",296618,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +30,"Local-gov",257796,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",155320,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,45,"United-States","<=50K" +22,"Private",151888,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +56,"Private",92444,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,50,"United-States",">50K" +51,"Private",229272,"HS-grad",9,"Divorced","Other-service","Other-relative","Black","Male",0,0,32,"Haiti","<=50K" +36,"Self-emp-not-inc",207202,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +28,"Private",205337,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",343021,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +39,"Private",185053,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Private",212864,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",66473,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",285169,"11th",7,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"Private",175431,"9th",5,"Divorced","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +18,"?",152641,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Private",339346,"Masters",14,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +39,"Private",287306,"Some-college",10,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +21,"Private",88926,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,10,"United-States","<=50K" +36,"Private",91275,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +56,"Private",244554,"10th",6,"Widowed","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +49,"Private",232586,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-inc",127678,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,80,"United-States","<=50K" +44,"Private",162184,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",408229,"1st-4th",2,"Never-married","Other-service","Not-in-family","White","Male",0,0,45,"El-Salvador","<=50K" +62,"Private",197286,"12th",8,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,48,"Germany","<=50K" +25,"Private",252803,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +63,"Self-emp-inc",110890,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,70,"United-States",">50K" +51,"Private",160724,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,99,"South","<=50K" +25,"Private",89625,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +62,"?",266037,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",126730,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Federal-gov",96854,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +32,"Private",186788,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",28996,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Self-emp-not-inc",347166,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"State-gov",110311,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",310850,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Private",220694,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +61,"Private",149405,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +70,"Self-emp-inc",131699,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,55,"United-States","<=50K" +55,"Private",49996,"11th",7,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",187112,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +36,"Private",180859,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,38,"United-States","<=50K" +29,"Private",185647,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,60,"United-States","<=50K" +30,"Private",316606,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +45,"Private",274657,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?","<=50K" +18,"Private",338836,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +28,"Private",216814,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",106935,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +38,"Private",223433,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",174789,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",135603,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +25,"?",344719,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,4,"United-States","<=50K" +38,"Private",372484,"11th",7,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",181820,"Some-college",10,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,45,"United-States","<=50K" +40,"Private",235371,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +20,"Private",299399,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +41,"Private",202508,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +44,"Private",172025,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +49,"Self-emp-inc",246891,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",450920,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +26,"Private",53598,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",103757,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",76017,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,25,"United-States","<=50K" +28,"Self-emp-inc",80158,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Private",427952,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"?",230955,"12th",8,"Never-married","?","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +36,"Private",342642,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +77,"Private",253642,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",0,0,30,"United-States","<=50K" +21,"Private",219086,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +24,"Private",162593,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +30,"Private",87561,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Local-gov",142411,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States","<=50K" +22,"Private",154422,"Some-college",10,"Divorced","Sales","Own-child","Asian-Pac-Islander","Female",0,0,30,"Philippines","<=50K" +23,"Private",169104,"Some-college",10,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,25,"United-States","<=50K" +17,"Private",151141,"12th",8,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +48,"Private",267912,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,50,"Mexico",">50K" +43,"Private",137126,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",152453,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Guatemala","<=50K" +19,"Private",357059,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +42,"State-gov",202011,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",98283,"Bachelors",13,"Never-married","Exec-managerial","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-not-inc",176965,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +63,"Private",187919,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States","<=50K" +65,"Private",274916,"HS-grad",9,"Widowed","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Local-gov",193524,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",152734,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"?","<=50K" +21,"Private",263641,"HS-grad",9,"Divorced","Sales","Other-relative","White","Female",0,0,40,"United-States","<=50K" +48,"Local-gov",102076,"Bachelors",13,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +43,"Private",33331,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +22,"State-gov",156773,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,15,"?","<=50K" +56,"Self-emp-not-inc",115439,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +47,"Private",181652,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",120268,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,24,"United-States","<=50K" +39,"Private",196308,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,24,"United-States","<=50K" +45,"Self-emp-not-inc",40690,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,75,"United-States","<=50K" +49,"Private",228583,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Male",0,0,40,"Columbia","<=50K" +23,"Private",695136,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +69,"Private",209236,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,36,"United-States","<=50K" +41,"Federal-gov",214838,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +40,"Self-emp-not-inc",188436,"HS-grad",9,"Separated","Exec-managerial","Other-relative","White","Male",0,0,40,"United-States","<=50K" +25,"Private",177625,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Private",124591,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +50,"Federal-gov",221532,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",232577,"Assoc-voc",11,"Never-married","Tech-support","Own-child","White","Female",0,0,30,"United-States","<=50K" +48,"Private",168216,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",214702,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,42,"United-States",">50K" +63,"Private",237620,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +47,"State-gov",54887,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",224506,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"?","<=50K" +58,"Private",183870,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",208330,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,51,"United-States","<=50K" +67,"Self-emp-inc",168370,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Self-emp-not-inc",320376,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,48,"United-States","<=50K" +28,"Private",192384,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",167350,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-not-inc",103538,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,65,"United-States",">50K" +29,"Private",58522,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",191342,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +25,"Private",193820,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,35,"United-States","<=50K" +20,"Private",258490,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +21,"Private",56520,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",102476,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +44,"Self-emp-inc",311357,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",166497,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,38,"United-States","<=50K" +29,"Private",338270,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +18,"Private",282394,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,21,"United-States","<=50K" +32,"Private",383269,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +58,"Private",119386,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +50,"Private",196975,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",334221,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,18,"United-States","<=50K" +58,"Private",27385,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +29,"State-gov",133846,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",361888,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +21,"Private",230429,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +49,"Private",328776,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +60,"Private",243829,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +30,"Private",280069,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +55,"Private",305759,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"?","<=50K" +64,"Local-gov",164876,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Male",0,0,20,"United-States","<=50K" +29,"Self-emp-inc",138597,"Assoc-acdm",12,"Never-married","Prof-specialty","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +42,"Private",144778,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +55,"Private",171015,"HS-grad",9,"Widowed","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",112494,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +28,"Private",408473,"12th",8,"Never-married","Sales","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +46,"State-gov",27802,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,38,"United-States",">50K" +34,"Private",236318,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",315971,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",698418,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,25,"United-States","<=50K" +21,"Private",329530,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +65,"Private",194456,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"England",">50K" +20,"Private",282579,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"State-gov",26401,"Masters",14,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +22,"Private",83998,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",94364,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Other","Female",0,0,20,"United-States","<=50K" +44,"Private",174189,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +44,"Local-gov",101967,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +41,"Private",146908,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +21,"Private",31606,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"Germany","<=50K" +24,"Private",132327,"Some-college",10,"Married-spouse-absent","Sales","Unmarried","Other","Female",0,0,30,"Ecuador","<=50K" +24,"Private",112459,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +28,"Private",48894,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Private",181943,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +24,"Local-gov",195808,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",172052,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,35,"South",">50K" +68,"Private",351711,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"State-gov",190305,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +22,"Private",464103,"1st-4th",2,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Guatemala","<=50K" +18,"?",36348,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,48,"United-States","<=50K" +25,"Private",120238,"HS-grad",9,"Married-spouse-absent","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"Poland","<=50K" +28,"Private",354095,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Local-gov",308901,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +24,"State-gov",208826,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,99,"England","<=50K" +20,"Private",369677,"10th",6,"Separated","Sales","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +45,"Federal-gov",98524,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",231232,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"?",119156,"Bachelors",13,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",320451,"Some-college",10,"Never-married","Protective-serv","Own-child","Asian-Pac-Islander","Male",0,0,24,"India","<=50K" +41,"Private",38397,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Self-emp-inc",189183,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Local-gov",199281,"Bachelors",13,"Separated","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +52,"Private",286342,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +50,"Private",152810,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Self-emp-inc",176981,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,50,"United-States","<=50K" +17,"Private",117549,"10th",6,"Never-married","Sales","Other-relative","Black","Female",0,0,12,"United-States","<=50K" +64,"Private",254797,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",133336,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Self-emp-not-inc",182826,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States","<=50K" +51,"Private",136224,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Private",272778,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,32,"United-States","<=50K" +44,"Private",279183,"Some-college",10,"Married-civ-spouse","Other-service","Own-child","White","Female",0,0,40,"United-States",">50K" +47,"Private",110243,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",202071,"HS-grad",9,"Widowed","Craft-repair","Own-child","White","Female",0,0,40,"United-States","<=50K" +58,"Private",197642,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,39,"United-States","<=50K" +19,"Private",125591,"11th",7,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",197462,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",238831,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",182177,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Yugoslavia","<=50K" +40,"Local-gov",240504,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Self-emp-inc",125892,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,38,"United-States",">50K" +46,"Private",154430,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +50,"Private",222020,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",243240,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +26,"Private",158734,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +36,"Private",257691,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +19,"Private",209826,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +54,"Private",133050,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Male",0,0,41,"United-States","<=50K" +29,"Private",138332,"Some-college",10,"Married-civ-spouse","Adm-clerical","Own-child","White","Female",0,0,6,"United-States","<=50K" +81,"Private",201398,"Masters",14,"Widowed","Prof-specialty","Unmarried","White","Male",0,0,60,"?","<=50K" +37,"Private",526968,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,38,"United-States",">50K" +40,"Private",79036,"Assoc-voc",11,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States",">50K" +36,"Private",240323,"Some-college",10,"Widowed","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",270544,"12th",8,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +44,"State-gov",199551,"11th",7,"Separated","Tech-support","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",231052,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +69,"State-gov",203072,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",126771,"12th",8,"Never-married","Prof-specialty","Own-child","White","Male",0,0,7,"United-States","<=50K" +38,"Private",31848,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",328981,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +52,"Private",159670,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",450695,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +57,"Private",182028,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +19,"Private",349620,"10th",6,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Private",161066,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",0,0,50,"United-States","<=50K" +21,"Private",548303,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Own-child","White","Male",0,0,40,"Mexico",">50K" +29,"Private",150861,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"Japan","<=50K" +33,"?",335625,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",133766,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +28,"Private",200511,"HS-grad",9,"Separated","Farming-fishing","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +26,"Private",50103,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +37,"?",148266,"Prof-school",15,"Married-civ-spouse","?","Husband","White","Male",0,0,6,"Mexico","<=50K" +49,"Private",177211,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",132686,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +57,"Federal-gov",21626,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +60,"Private",52900,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"?",150084,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +38,"Private",248886,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,42,"United-States","<=50K" +60,"Private",145493,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Federal-gov",399155,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Female",0,0,40,"United-States","<=50K" +19,"Self-emp-not-inc",227310,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +59,"Private",333270,"Masters",14,"Married-civ-spouse","Craft-repair","Wife","Asian-Pac-Islander","Female",0,0,35,"Philippines","<=50K" +50,"Private",231495,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Federal-gov",133935,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Federal-gov",55237,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +18,"Private",183034,"Some-college",10,"Never-married","Sales","Own-child","Black","Male",0,0,35,"United-States","<=50K" +32,"Private",245487,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","Amer-Indian-Eskimo","Male",0,0,40,"Mexico","<=50K" +32,"Private",185480,"Assoc-voc",11,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Private",114251,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",181814,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Female",0,0,40,"United-States","<=50K" +38,"Self-emp-inc",125324,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,80,"United-States",">50K" +36,"Private",34744,"Assoc-acdm",12,"Divorced","Other-service","Unmarried","White","Female",0,0,37,"United-States","<=50K" +56,"Private",131608,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Federal-gov",226916,"Bachelors",13,"Widowed","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States",">50K" +56,"Private",124137,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,41,"United-States","<=50K" +17,"Private",96282,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,14,"United-States","<=50K" +56,"Private",229335,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +61,"State-gov",199495,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",111675,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,43,"United-States","<=50K" +27,"Private",139209,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",32372,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +33,"Self-emp-not-inc",203784,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,62,"United-States","<=50K" +38,"Private",64875,"Some-college",10,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,60,"United-States","<=50K" +51,"Private",41806,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",208725,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +49,"Local-gov",79019,"Masters",14,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,16,"United-States","<=50K" +26,"Private",136951,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +42,"Private",203554,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +38,"Private",170861,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +48,"Private",199590,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico",">50K" +30,"Private",182177,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"Ireland","<=50K" +25,"State-gov",183678,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +50,"Private",209320,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Self-emp-inc",206862,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,36,"United-States",">50K" +37,"Private",168941,"11th",7,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"Private",75333,"10th",6,"Never-married","Sales","Own-child","Black","Female",0,0,24,"United-States","<=50K" +57,"Private",139290,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +33,"Private",400416,"10th",6,"Never-married","Other-service","Own-child","Black","Male",0,0,20,"United-States","<=50K" +41,"Self-emp-not-inc",223763,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States","<=50K" +45,"Private",77927,"Bachelors",13,"Widowed","Other-service","Own-child","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +50,"Private",175804,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +18,"Private",91525,"HS-grad",9,"Never-married","Sales","Other-relative","White","Male",0,0,25,"United-States","<=50K" +19,"Private",279968,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +26,"Private",77698,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +61,"?",198686,"Assoc-acdm",12,"Married-civ-spouse","?","Husband","White","Male",0,0,2,"United-States",">50K" +67,"?",190340,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",113491,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",202878,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +27,"Private",108431,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",194490,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +37,"Private",48093,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,90,"United-States",">50K" +22,"Private",136824,"11th",7,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",143280,"10th",6,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,24,"United-States","<=50K" +26,"Private",150062,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Local-gov",298510,"HS-grad",9,"Divorced","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",115025,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",350440,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +60,"Private",83850,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",62669,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +24,"Private",229773,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Local-gov",196234,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Female",0,0,40,"Puerto-Rico","<=50K" +69,"?",163595,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +52,"Self-emp-inc",49069,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +38,"Private",122952,"HS-grad",9,"Separated","Craft-repair","Unmarried","White","Female",0,0,35,"United-States","<=50K" +18,"Private",123856,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,49,"United-States","<=50K" +24,"Private",216181,"Assoc-voc",11,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Private",180062,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +21,"Private",188535,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +64,"Self-emp-not-inc",170421,"Some-college",10,"Widowed","Craft-repair","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +25,"Private",283087,"Some-college",10,"Never-married","Exec-managerial","Own-child","Black","Male",0,0,40,"United-States","<=50K" +34,"Federal-gov",341051,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +39,"Self-emp-not-inc",34378,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Private",380674,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,52,"United-States","<=50K" +19,"Private",304469,"10th",6,"Never-married","Farming-fishing","Own-child","White","Male",0,0,25,"United-States","<=50K" +35,"Private",99146,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",205109,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",99156,"HS-grad",9,"Separated","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +45,"Private",97842,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,65,"United-States","<=50K" +18,"Private",100875,"11th",7,"Never-married","Other-service","Unmarried","White","Female",0,0,28,"United-States","<=50K" +51,"Private",200576,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,63,"United-States","<=50K" +36,"Private",355053,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,28,"United-States","<=50K" +18,"Private",118376,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,16,"?","<=50K" +37,"Private",117567,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +39,"Federal-gov",189632,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +21,"Private",170108,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",192663,"HS-grad",9,"Separated","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +23,"Private",526164,"Bachelors",13,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",146579,"HS-grad",9,"Divorced","Sales","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +28,"Private",60288,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"State-gov",241951,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Self-emp-inc",213140,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",218124,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +22,"Self-emp-not-inc",279802,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,3,"United-States","<=50K" +26,"Private",153078,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Male",0,0,80,"?",">50K" +40,"Private",167919,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +90,"Private",250832,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",193158,"HS-grad",9,"Divorced","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +44,"Private",172032,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",269015,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"Germany",">50K" +17,"?",262196,"10th",6,"Never-married","?","Own-child","White","Male",0,0,8,"United-States","<=50K" +49,"Federal-gov",125892,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",134890,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Male",0,0,50,"United-States","<=50K" +60,"Self-emp-not-inc",261119,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",119409,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","Other","Female",0,0,40,"Columbia","<=50K" +53,"Self-emp-not-inc",118793,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +19,"Private",184207,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",191027,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",207782,"Assoc-acdm",12,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +48,"Self-emp-not-inc",209146,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +19,"Private",187724,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +58,"Private",158002,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States","<=50K" +19,"Self-emp-not-inc",305834,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Female",0,0,25,"United-States","<=50K" +37,"?",122265,"HS-grad",9,"Divorced","?","Not-in-family","Asian-Pac-Islander","Female",0,0,42,"?","<=50K" +22,"Private",211798,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",123011,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Private",36302,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +62,"Private",169204,"HS-grad",9,"Widowed","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +26,"Private",38232,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +64,"State-gov",277657,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +38,"Private",32271,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",226198,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",28145,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,52,"United-States","<=50K" +39,"Private",140477,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +50,"Private",165050,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Self-emp-inc",202937,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +36,"Private",316298,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Private",203070,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,49,"United-States","<=50K" +51,"Self-emp-inc",103995,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +28,"Private",176137,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,32,"United-States","<=50K" +57,"Self-emp-not-inc",103948,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States",">50K" +40,"Local-gov",39581,"Prof-school",15,"Separated","Prof-specialty","Own-child","Black","Female",0,0,40,"United-States","<=50K" +27,"Private",506436,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,40,"Peru","<=50K" +49,"State-gov",154493,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,44,"United-States","<=50K" +34,"Self-emp-not-inc",137223,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +24,"Private",102323,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"Private",257765,"7th-8th",4,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"Guatemala","<=50K" +52,"Private",42924,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +43,"Private",167599,"11th",7,"Married-civ-spouse","Handlers-cleaners","Wife","White","Female",0,0,25,"United-States","<=50K" +84,"?",368925,"5th-6th",3,"Widowed","?","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +79,"?",100881,"Assoc-acdm",12,"Married-civ-spouse","?","Wife","White","Female",0,0,2,"United-States",">50K" +35,"Private",52738,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,46,"United-States","<=50K" +56,"Private",98418,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +30,"Private",381153,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Private",103700,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",298635,"Bachelors",13,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Male",0,0,50,"United-States","<=50K" +32,"Private",127895,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +44,"Self-emp-inc",212760,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +32,"Private",281384,"HS-grad",9,"Married-AF-spouse","Other-service","Other-relative","White","Female",0,0,10,"United-States","<=50K" +60,"Private",181200,"12th",8,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",257364,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +50,"Private",283281,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +58,"Private",214502,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States",">50K" +41,"Private",69333,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Private",190060,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",95864,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,35,"United-States","<=50K" +17,"?",275778,"9th",5,"Never-married","?","Own-child","White","Female",0,0,25,"Mexico","<=50K" +45,"Private",27332,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",24395,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,30,"United-States","<=50K" +25,"Private",330695,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Self-emp-not-inc",171615,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States",">50K" +28,"Private",116372,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +27,"Private",38599,"12th",8,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Local-gov",202184,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,15,"United-States","<=50K" +24,"Private",315303,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,25,"United-States","<=50K" +38,"Private",103456,"Bachelors",13,"Separated","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +24,"State-gov",163480,"Masters",14,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",317425,"11th",7,"Never-married","Other-service","Own-child","Black","Male",0,0,7,"United-States","<=50K" +58,"Private",216941,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",116541,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Male",0,0,44,"United-States",">50K" +43,"Private",186396,"9th",5,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +24,"Private",385540,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Mexico","<=50K" +63,"Private",201631,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","Black","Male",0,0,40,"United-States","<=50K" +40,"Private",439919,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +21,"Private",182117,"Bachelors",13,"Never-married","Other-service","Other-relative","White","Male",0,0,20,"United-States","<=50K" +20,"State-gov",334113,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"?",228372,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States",">50K" +47,"Federal-gov",211123,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Self-emp-inc",38819,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,36,"United-States","<=50K" +23,"?",302836,"Assoc-acdm",12,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +35,"State-gov",89040,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",264210,"Some-college",10,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,0,20,"United-States","<=50K" +18,"Private",87157,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +28,"Self-emp-not-inc",398918,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +62,"?",123612,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,4,"United-States","<=50K" +20,"Private",155818,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +28,"Private",243660,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",134195,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Private",238638,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",159929,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",198668,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",215504,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",158002,"Some-college",10,"Never-married","Craft-repair","Other-relative","White","Male",0,0,55,"Ecuador","<=50K" +53,"Local-gov",35305,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,57,"United-States","<=50K" +25,"Private",195994,"1st-4th",2,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,40,"Guatemala","<=50K" +44,"State-gov",321824,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,38,"United-States","<=50K" +22,"Private",180449,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,28,"United-States","<=50K" +40,"Private",201764,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",250038,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"?","<=50K" +30,"Self-emp-not-inc",226535,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +51,"Private",136121,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +17,"Private",47199,"11th",7,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,24,"United-States","<=50K" +46,"Local-gov",215895,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +50,"State-gov",24647,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",734193,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +42,"?",321086,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Federal-gov",192589,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",326283,"Bachelors",13,"Never-married","Other-service","Unmarried","Other","Male",0,0,40,"United-States","<=50K" +32,"Private",207284,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",109089,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,70,"United-States","<=50K" +50,"Private",274528,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +77,"Private",142646,"7th-8th",4,"Widowed","Priv-house-serv","Unmarried","White","Female",0,0,23,"United-States","<=50K" +33,"Private",180859,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-inc",188610,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +64,"Private",169604,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",260560,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Local-gov",188245,"HS-grad",9,"Never-married","Prof-specialty","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +37,"Local-gov",52465,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",737315,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +22,"?",195143,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,29,"United-States","<=50K" +50,"Self-emp-not-inc",219420,"Doctorate",16,"Divorced","Sales","Not-in-family","White","Male",0,0,64,"United-States","<=50K" +60,"Private",198170,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +46,"Local-gov",183168,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,43,"United-States","<=50K" +43,"Private",168412,"HS-grad",9,"Married-civ-spouse","Sales","Other-relative","White","Female",0,0,44,"Poland","<=50K" +48,"Private",174386,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"El-Salvador",">50K" +48,"Private",95661,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +37,"Private",468713,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",169112,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",74024,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +27,"Private",110622,"5th-6th",3,"Never-married","Sales","Own-child","Asian-Pac-Islander","Female",0,0,20,"Vietnam","<=50K" +43,"Local-gov",33331,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",181557,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,25,"United-States","<=50K" +35,"Private",146091,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Private",200949,"10th",6,"Never-married","Other-service","Unmarried","White","Female",0,0,38,"Peru","<=50K" +51,"Local-gov",201560,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +71,"Federal-gov",149386,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Male",0,0,9,"United-States","<=50K" +63,"Private",38352,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"State-gov",180272,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,35,"United-States","<=50K" +24,"State-gov",275421,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Local-gov",173051,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,45,"United-States","<=50K" +33,"Local-gov",167474,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",267138,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",135138,"Bachelors",13,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +49,"Private",218357,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +28,"Self-emp-not-inc",107236,"12th",8,"Married-civ-spouse","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",138416,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,56,"Mexico","<=50K" +28,"Private",154863,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,35,"United-States","<=50K" +37,"Private",194004,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,25,"United-States","<=50K" +19,"Private",339123,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Local-gov",548361,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,26,"United-States","<=50K" +25,"Private",101812,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,41,"United-States","<=50K" +49,"Self-emp-inc",127111,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +47,"Private",171807,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,45,"United-States","<=50K" +48,"Local-gov",40666,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",340682,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",175052,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"?",321629,"HS-grad",9,"Never-married","?","Unmarried","White","Female",0,0,16,"United-States","<=50K" +46,"Private",154405,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +17,"Private",108402,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +34,"Private",346275,"11th",7,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,43,"United-States","<=50K" +44,"Private",42476,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,30,"United-States","<=50K" +23,"Private",161708,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +65,"?",137354,"Some-college",10,"Married-civ-spouse","?","Husband","Asian-Pac-Islander","Male",0,0,20,"United-States","<=50K" +34,"Private",250724,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"Jamaica","<=50K" +34,"Federal-gov",149368,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",154641,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",56150,"11th",7,"Never-married","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +21,"Private",260254,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",108083,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +54,"Self-emp-not-inc",71344,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +32,"Private",174215,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"State-gov",114366,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +39,"Private",158962,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",179498,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Germany","<=50K" +29,"Private",31935,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",149909,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,42,"United-States",">50K" +20,"?",58740,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,15,"United-States","<=50K" +39,"Private",216552,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",255348,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",176050,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +71,"?",125101,"Assoc-voc",11,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +62,"?",197286,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",159737,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,58,"United-States","<=50K" +39,"Private",316211,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +45,"Local-gov",556652,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +19,"Private",265576,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,50,"United-States","<=50K" +43,"Private",347653,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States",">50K" +32,"Private",62374,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",170230,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +34,"Private",203051,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,27,"United-States","<=50K" +66,"Self-emp-inc",115880,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-inc",181413,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +23,"Private",185554,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Private",350387,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +63,"Private",225102,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"?","<=50K" +35,"Self-emp-not-inc",350247,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",150025,"9th",5,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"?",">50K" +37,"Private",107737,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +63,"?",334741,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +43,"Private",115562,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,42,"United-States",">50K" +30,"Self-emp-not-inc",131584,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,60,"United-States","<=50K" +36,"Local-gov",95855,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,60,"United-States",">50K" +54,"Private",391016,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Federal-gov",51089,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +77,"Private",117898,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",70240,"HS-grad",9,"Married-spouse-absent","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +39,"Self-emp-not-inc",187693,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,72,"United-States",">50K" +37,"Private",341672,"Bachelors",13,"Separated","Tech-support","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +22,"Local-gov",289982,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,35,"United-States","<=50K" +54,"Private",76344,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +21,"Private",200973,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +36,"Private",111377,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Self-emp-not-inc",136684,"HS-grad",9,"Widowed","Adm-clerical","Other-relative","White","Female",0,0,30,"United-States","<=50K" +40,"Private",176716,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Self-emp-not-inc",166894,"Some-college",10,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",243872,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States",">50K" +28,"Private",155621,"5th-6th",3,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Columbia","<=50K" +46,"Private",102597,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",60331,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"United-States","<=50K" +37,"Private",75024,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,25,"Canada","<=50K" +69,"Private",174474,"10th",6,"Separated","Machine-op-inspct","Not-in-family","White","Female",0,0,28,"Peru","<=50K" +43,"Private",145441,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +53,"Private",83434,"Bachelors",13,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,21,"Japan",">50K" +20,"Private",691830,"HS-grad",9,"Never-married","Sales","Own-child","Black","Female",0,0,35,"United-States","<=50K" +22,"Private",189203,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +48,"Private",115784,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +40,"Federal-gov",280167,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +68,"?",407338,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +23,"Private",315065,"10th",6,"Never-married","Other-service","Unmarried","White","Male",0,0,60,"Mexico","<=50K" +25,"Local-gov",167835,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,38,"United-States",">50K" +22,"Private",63105,"HS-grad",9,"Never-married","Prof-specialty","Own-child","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",520775,"12th",8,"Never-married","Priv-house-serv","Own-child","White","Male",0,0,30,"United-States","<=50K" +41,"Local-gov",47902,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +25,"Private",145434,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +58,"Private",56392,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",162312,"HS-grad",9,"Divorced","Sales","Not-in-family","Asian-Pac-Islander","Male",0,0,45,"Japan","<=50K" +28,"Private",204074,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States","<=50K" +19,"Private",99246,"11th",7,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +44,"Private",102085,"Some-college",10,"Divorced","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +68,"Private",168794,"Preschool",1,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +33,"State-gov",332379,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",233419,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",57233,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +31,"Private",442429,"HS-grad",9,"Separated","Craft-repair","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +29,"Private",369114,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +65,"Private",261334,"9th",5,"Widowed","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Private",160303,"HS-grad",9,"Widowed","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +49,"Private",50474,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",321577,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",29591,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +33,"Self-emp-not-inc",334744,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Self-emp-not-inc",269474,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +66,"Private",33619,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,4,"United-States","<=50K" +38,"Private",149347,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +43,"Private",96249,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,42,"United-States",">50K" +40,"Local-gov",370502,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +32,"Private",188246,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",167558,"HS-grad",9,"Never-married","Sales","Unmarried","White","Female",0,0,35,"Mexico","<=50K" +35,"Private",292185,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Local-gov",70164,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Amer-Indian-Eskimo","Male",0,0,60,"United-States","<=50K" +36,"Private",269722,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +33,"Self-emp-not-inc",175502,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +53,"Private",233165,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +27,"Private",177351,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +22,"Private",212114,"Bachelors",13,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,15,"United-States","<=50K" +26,"Private",288959,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,36,"United-States","<=50K" +64,"Private",231619,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,21,"United-States","<=50K" +48,"Private",146919,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +23,"Private",388811,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",243560,"Some-college",10,"Never-married","Sales","Unmarried","White","Female",0,0,40,"?","<=50K" +35,"Self-emp-not-inc",98360,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",369538,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +65,"Self-emp-not-inc",31740,"Some-college",10,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +18,"Private",333611,"5th-6th",3,"Never-married","Other-service","Other-relative","White","Male",0,0,54,"Mexico","<=50K" +34,"Self-emp-not-inc",108247,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +28,"Private",76129,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"Guatemala","<=50K" +37,"Private",91711,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +61,"?",166855,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,10,"United-States","<=50K" +31,"Private",43953,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,35,"United-States","<=50K" +25,"Local-gov",84224,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +81,"Private",100675,"1st-4th",2,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,15,"Poland","<=50K" +47,"Private",155509,"HS-grad",9,"Separated","Other-service","Other-relative","Black","Female",0,0,35,"United-States","<=50K" +39,"Private",29814,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",241805,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,30,"United-States","<=50K" +44,"Private",214838,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +37,"Private",240810,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +41,"Private",154076,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +27,"?",175552,"5th-6th",3,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"Mexico","<=50K" +55,"Private",170287,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Poland",">50K" +60,"Private",145995,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",433669,"Assoc-acdm",12,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,36,"?","<=50K" +23,"Private",233626,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +19,"Private",607799,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +45,"Private",88500,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,44,"United-States",">50K" +36,"Private",127809,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +46,"Private",243743,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",177211,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",231180,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",253856,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,20,"United-States","<=50K" +39,"Private",177075,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",152855,"HS-grad",9,"Never-married","Exec-managerial","Own-child","Other","Female",0,0,40,"Mexico","<=50K" +37,"Private",191137,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,25,"United-States","<=50K" +49,"Private",255559,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +27,"Private",169815,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",221215,"10th",6,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +35,"Private",270059,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +17,"Private",345403,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",194897,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +33,"Private",388741,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Other","Female",0,0,38,"United-States","<=50K" +33,"Private",355856,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,60,"United-States","<=50K" +51,"Private",122109,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States","<=50K" +49,"Private",75673,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +41,"Private",47902,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States",">50K" +64,"Private",221343,"1st-4th",2,"Divorced","Priv-house-serv","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +40,"Private",255675,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Federal-gov",203505,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",125106,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",139890,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",28035,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,86,"United-States","<=50K" +36,"Private",163237,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Local-gov",55890,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",255934,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,80,"United-States","<=50K" +61,"Private",168654,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"Canada","<=50K" +47,"Self-emp-not-inc",39986,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Private",208451,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",206681,"12th",8,"Never-married","Sales","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +33,"Private",117779,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,46,"United-States",">50K" +36,"Self-emp-not-inc",129150,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States",">50K" +38,"?",177273,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,35,"United-States","<=50K" +34,"Local-gov",226443,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Private",146326,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",187901,"Assoc-voc",11,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,23,"United-States","<=50K" +49,"Private",188694,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +71,"Private",187493,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",212468,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +20,"Private",84726,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",137907,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +51,"Private",34361,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,20,"United-States",">50K" +38,"Private",254114,"Some-college",10,"Married-spouse-absent","Prof-specialty","Own-child","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",170174,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Self-emp-not-inc",190895,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +24,"Local-gov",317443,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,40,"United-States","<=50K" +40,"Private",375603,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",203076,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +49,"Private",53893,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"?",171748,"Some-college",10,"Never-married","?","Own-child","Black","Female",0,0,24,"United-States","<=50K" +52,"Private",204584,"Bachelors",13,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +27,"Private",660870,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +20,"Private",105686,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",148607,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",255849,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Federal-gov",255921,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"England","<=50K" +33,"Private",113326,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +23,"Private",440456,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",105493,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Local-gov",89491,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",171818,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",51151,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",188957,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",97933,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Self-emp-inc",195447,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +63,"?",46907,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States",">50K" +54,"Self-emp-inc",383365,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States",">50K" +32,"Self-emp-not-inc",203408,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +29,"Local-gov",148182,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +26,"Local-gov",211497,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",48063,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +54,"Private",185407,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",225927,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Federal-gov",314525,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",208577,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +42,"Private",222884,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States",">50K" +31,"Private",209538,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Local-gov",177114,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +50,"Private",173754,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Local-gov",121370,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,30,"United-States","<=50K" +37,"Private",67125,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +26,"Private",67240,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",198346,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +24,"Private",141003,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,25,"United-States","<=50K" +24,"Self-emp-inc",60668,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",104256,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,34,"United-States","<=50K" +47,"Private",131002,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",177720,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,45,"United-States","<=50K" +20,"Private",39615,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",112264,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Private",169100,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",155659,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Germany",">50K" +29,"Private",224215,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",270502,"11th",7,"Never-married","Exec-managerial","Own-child","White","Female",0,0,20,"United-States","<=50K" +46,"Private",125487,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",51385,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +41,"Private",112763,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Private",108926,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +36,"Local-gov",109766,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +38,"Private",226106,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +75,"Self-emp-not-inc",92792,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +26,"Private",186950,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +44,"Private",230478,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",231638,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Private",120461,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +49,"Private",33673,"12th",8,"Never-married","Transport-moving","Not-in-family","Asian-Pac-Islander","Male",0,0,35,"United-States","<=50K" +34,"Private",191385,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +31,"Self-emp-not-inc",229946,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Columbia","<=50K" +47,"Self-emp-not-inc",160131,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",126021,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Female",0,0,20,"United-States","<=50K" +42,"Private",203542,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",144592,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Local-gov",223004,"Some-college",10,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,75,"United-States","<=50K" +22,"Private",183257,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,20,"United-States","<=50K" +32,"Private",172714,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",131611,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,48,"United-States","<=50K" +41,"Private",253060,"Prof-school",15,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +46,"Private",471990,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,46,"United-States",">50K" +44,"Private",138966,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,38,"United-States","<=50K" +35,"Private",385412,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"?",184101,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +36,"Local-gov",135786,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,25,"United-States","<=50K" +30,"Private",227359,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +40,"State-gov",86912,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Private",172581,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",483822,"7th-8th",4,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,40,"Guatemala","<=50K" +66,"Self-emp-inc",220543,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +48,"Private",152953,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,32,"Dominican-Republic","<=50K" +35,"Private",239755,"Some-college",10,"Never-married","Sales","Unmarried","White","Male",0,0,50,"United-States","<=50K" +41,"Private",177905,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +19,"Private",200136,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +55,"Self-emp-not-inc",111625,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",162915,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +29,"Private",116662,"Bachelors",13,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +65,"Private",225580,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +30,"Private",169104,"Assoc-acdm",12,"Never-married","Other-service","Other-relative","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +43,"Private",212894,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",93997,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Italy","<=50K" +22,"Private",189924,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +23,"Private",274424,"11th",7,"Separated","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",188246,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",284211,"HS-grad",9,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,35,"United-States","<=50K" +21,"Private",198259,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +31,"Private",368517,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +34,"Private",168768,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +33,"Federal-gov",122220,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,40,"United-States",">50K" +44,"Private",175641,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +21,"State-gov",173324,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,20,"United-States","<=50K" +75,"Local-gov",31195,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +55,"Federal-gov",88876,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,60,"United-States",">50K" +43,"Self-emp-not-inc",176069,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,16,"United-States","<=50K" +31,"Private",215297,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +41,"Private",198425,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +26,"Local-gov",180957,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +23,"Private",206129,"Assoc-voc",11,"Never-married","Craft-repair","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +42,"Federal-gov",65950,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",197618,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",185357,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +28,"Private",134890,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +64,"?",193043,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Federal-gov",153633,"Some-college",10,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +65,"Private",115890,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,20,"United-States","<=50K" +58,"Private",343957,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +63,"?",247986,"Prof-school",15,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States",">50K" +59,"Private",159048,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",89735,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",31778,"Bachelors",13,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"?",157327,"5th-6th",3,"Married-civ-spouse","?","Husband","Black","Male",0,0,8,"United-States","<=50K" +34,"Private",236543,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"State-gov",194475,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",303510,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",171242,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Self-emp-not-inc",39388,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +62,"Local-gov",197218,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,18,"United-States","<=50K" +22,"State-gov",151991,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,20,"United-States","<=50K" +38,"Private",374524,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +34,"?",267352,"11th",7,"Never-married","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +45,"Local-gov",364563,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",186035,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +21,"Private",47541,"HS-grad",9,"Divorced","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +49,"Private",151107,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +24,"Private",500509,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +20,"Federal-gov",225515,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,24,"United-States","<=50K" +27,"Private",153291,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +40,"Private",169885,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"?",112780,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +31,"Local-gov",175778,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",174330,"HS-grad",9,"Separated","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +50,"Private",35224,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",175622,"Assoc-voc",11,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",164678,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States","<=50K" +50,"?",87263,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,55,"United-States",">50K" +17,"Self-emp-not-inc",181317,"10th",6,"Never-married","Farming-fishing","Own-child","White","Male",0,0,35,"United-States","<=50K" +33,"Federal-gov",177945,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +28,"Private",47168,"10th",6,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",190023,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +33,"Private",168782,"Assoc-voc",11,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +59,"Private",175290,"7th-8th",4,"Never-married","Other-service","Other-relative","White","Male",0,0,32,"United-States","<=50K" +74,"Private",145463,"1st-4th",2,"Widowed","Priv-house-serv","Not-in-family","Black","Female",0,0,15,"United-States","<=50K" +54,"Private",159755,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",113364,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,55,"United-States","<=50K" +31,"Private",487742,"Some-college",10,"Separated","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",304710,"Some-college",10,"Never-married","Sales","Own-child","Asian-Pac-Islander","Female",0,0,20,"United-States","<=50K" +57,"Self-emp-not-inc",315460,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,36,"United-States","<=50K" +49,"Private",135643,"HS-grad",9,"Widowed","Craft-repair","Unmarried","Asian-Pac-Islander","Female",0,0,40,"South","<=50K" +19,"?",117444,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +38,"Private",202683,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",164866,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,42,"United-States",">50K" +32,"?",227160,"Some-college",10,"Divorced","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Private",158077,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +38,"Private",191103,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,99,"United-States",">50K" +25,"Private",193701,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +40,"Private",143046,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +34,"Private",206297,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +35,"Self-emp-not-inc",188563,"HS-grad",9,"Divorced","Farming-fishing","Own-child","White","Male",0,0,50,"United-States","<=50K" +53,"Private",35102,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,34,"United-States","<=50K" +21,"Private",203055,"Some-college",10,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +43,"Private",309932,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",243432,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +22,"Private",177107,"Assoc-voc",11,"Never-married","Prof-specialty","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +64,"Self-emp-not-inc",113929,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +19,"?",291509,"12th",8,"Never-married","?","Own-child","White","Male",0,0,28,"United-States","<=50K" +34,"Private",186824,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,70,"United-States","<=50K" +46,"Private",192768,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +35,"Private",234962,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +32,"Private",83253,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +26,"Private",248990,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",346159,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"Private",272656,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,55,"United-States",">50K" +22,"Private",60552,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"State-gov",33798,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +38,"Self-emp-not-inc",112158,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,99,"United-States","<=50K" +55,"Private",200992,"Some-college",10,"Widowed","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +26,"Private",98155,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-inc",79586,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Other","Male",0,0,60,"United-States","<=50K" +25,"State-gov",143062,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +18,"?",284450,"11th",7,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +58,"State-gov",159021,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",353270,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",162312,"Some-college",10,"Never-married","Exec-managerial","Own-child","Asian-Pac-Islander","Male",0,0,45,"South","<=50K" +49,"State-gov",231961,"Doctorate",16,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,50,"United-States",">50K" +38,"Private",181943,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +21,"Private",163595,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +28,"Private",130856,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",208875,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"El-Salvador",">50K" +29,"Self-emp-not-inc",58744,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Male",0,0,60,"United-States","<=50K" +48,"Private",116641,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +40,"Private",69333,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",320811,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",197886,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +57,"Self-emp-not-inc",253914,"1st-4th",2,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"Mexico","<=50K" +24,"Private",89154,"9th",5,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"El-Salvador","<=50K" +32,"Private",372317,"9th",5,"Separated","Other-service","Unmarried","White","Female",0,0,23,"Mexico","<=50K" +18,"Self-emp-not-inc",296090,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,48,"?","<=50K" +39,"Private",192614,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,56,"United-States","<=50K" +39,"Private",403489,"11th",7,"Divorced","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",169652,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,12,"United-States","<=50K" +20,"Private",217467,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"?",162104,"9th",5,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +54,"Private",175912,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Self-emp-not-inc",179533,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,75,"United-States",">50K" +27,"Private",149624,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,30,"United-States","<=50K" +27,"Private",289147,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Federal-gov",347720,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +22,"Private",406978,"Bachelors",13,"Never-married","Exec-managerial","Other-relative","White","Female",0,0,40,"United-States","<=50K" +17,"Private",193199,"11th",7,"Never-married","Sales","Unmarried","White","Female",0,0,12,"Poland","<=50K" +37,"Self-emp-inc",163998,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Private",333701,"Assoc-voc",11,"Never-married","Other-service","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +45,"Private",186256,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",104525,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +71,"Private",212806,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,36,"United-States","<=50K" +23,"Local-gov",203353,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,45,"United-States","<=50K" +41,"Private",130126,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,80,"United-States",">50K" +21,"?",270043,"10th",6,"Never-married","?","Unmarried","White","Female",0,0,30,"United-States","<=50K" +47,"Private",218435,"HS-grad",9,"Married-spouse-absent","Sales","Unmarried","White","Female",0,0,20,"Cuba","<=50K" +30,"Private",154120,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +40,"Private",193537,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"Dominican-Republic","<=50K" +44,"Private",84535,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,48,"United-States","<=50K" +31,"State-gov",157673,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +68,"Private",217424,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,24,"United-States","<=50K" +38,"Private",186191,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +78,"Self-emp-inc",212660,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,10,"United-States","<=50K" +31,"Self-emp-inc",31740,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,55,"United-States","<=50K" +39,"Private",498785,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Local-gov",162566,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,50,"Canada","<=50K" +30,"Private",118861,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,50,"United-States",">50K" +34,"Private",206609,"Some-college",10,"Never-married","Sales","Unmarried","White","Male",0,0,35,"United-States","<=50K" +30,"Federal-gov",423064,"HS-grad",9,"Separated","Adm-clerical","Other-relative","Black","Male",0,0,35,"United-States","<=50K" +47,"Private",191957,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States",">50K" +40,"Private",223934,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,17,"United-States",">50K" +62,"?",129246,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",195486,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,70,"Jamaica","<=50K" +40,"Private",114580,"HS-grad",9,"Divorced","Craft-repair","Other-relative","White","Female",0,0,40,"Vietnam","<=50K" +20,"Private",119215,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",240554,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Private",144084,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Private",358682,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Local-gov",59612,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Local-gov",101345,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,26,"United-States","<=50K" +20,"Private",117618,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",231238,"9th",5,"Separated","Farming-fishing","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",143046,"HS-grad",9,"Widowed","Transport-moving","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",203642,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +62,"Private",88579,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +21,"Private",240517,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,70,"United-States","<=50K" +58,"Local-gov",156649,"1st-4th",2,"Widowed","Handlers-cleaners","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",143392,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +37,"Private",365465,"HS-grad",9,"Separated","Craft-repair","Unmarried","White","Male",0,0,70,"Philippines","<=50K" +22,"State-gov",264710,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +64,"State-gov",223830,"9th",5,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +42,"Private",154374,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +43,"State-gov",242521,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",124569,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",209230,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,6,"United-States","<=50K" +21,"Private",162228,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Federal-gov",60267,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Self-emp-not-inc",76901,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +24,"Private",137876,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +70,"Self-emp-not-inc",347910,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States","<=50K" +27,"Local-gov",138917,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +34,"Private",532379,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",31532,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",30973,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",117295,"1st-4th",2,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +32,"Private",295282,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +42,"Private",190786,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",246207,"Bachelors",13,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +50,"Private",130780,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",186212,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +42,"Private",175526,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Federal-gov",82622,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +38,"State-gov",318886,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,52,"United-States","<=50K" +18,"Private",256005,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +63,"Self-emp-not-inc",217715,"5th-6th",3,"Never-married","Sales","Not-in-family","White","Female",0,0,3,"United-States","<=50K" +82,"Self-emp-not-inc",240491,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Cuba","<=50K" +33,"Private",154120,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,45,"United-States","<=50K" +37,"Private",69251,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +24,"Private",333505,"HS-grad",9,"Married-spouse-absent","Transport-moving","Own-child","White","Male",0,0,40,"Peru","<=50K" +31,"Private",168521,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States","<=50K" +59,"Private",193568,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +18,"Private",426895,"12th",8,"Never-married","Farming-fishing","Own-child","White","Male",0,0,55,"United-States","<=50K" +47,"Self-emp-not-inc",131826,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",79646,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",167031,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","Other","Female",0,0,33,"United-States","<=50K" +34,"Private",73199,"11th",7,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +50,"Private",114056,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,84,"United-States","<=50K" +57,"Self-emp-not-inc",110417,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,75,"United-States","<=50K" +60,"Private",33266,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",154410,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +56,"?",154537,"Some-college",10,"Divorced","?","Unmarried","White","Female",0,0,50,"United-States",">50K" +18,"Private",27780,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +26,"Private",142914,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,75,"United-States","<=50K" +20,"Private",314422,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +29,"Local-gov",273771,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +30,"Private",175083,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +21,"Private",63665,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +24,"Local-gov",193416,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Private",74275,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",122609,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Local-gov",116892,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",196971,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,72,"United-States","<=50K" +20,"Private",105312,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +46,"Private",108699,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +44,"Private",171615,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +39,"Private",388023,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +39,"Private",181553,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +45,"Private",170850,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,44,"United-States",">50K" +28,"Private",187479,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +44,"Private",277720,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States","<=50K" +27,"Private",220754,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +34,"Self-emp-not-inc",209768,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",93225,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Federal-gov",341709,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",236242,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +21,"Private",121889,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,20,"United-States","<=50K" +18,"Private",318190,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +63,"Self-emp-not-inc",111306,"7th-8th",4,"Widowed","Farming-fishing","Unmarried","White","Female",0,0,10,"United-States","<=50K" +18,"Private",198614,"11th",7,"Never-married","Sales","Own-child","Black","Female",0,0,8,"United-States","<=50K" +32,"Private",193231,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"?",104614,"11th",7,"Never-married","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",172368,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,20,"United-States","<=50K" +23,"Private",60331,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +38,"Private",154568,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +45,"Private",238567,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"England",">50K" +30,"Private",208068,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,40,"Mexico","<=50K" +24,"Federal-gov",283918,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +23,"Private",37783,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Private",263552,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +48,"Private",255439,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Self-emp-inc",344275,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +31,"Private",70568,"1st-4th",2,"Never-married","Other-service","Other-relative","White","Female",0,0,25,"El-Salvador","<=50K" +18,"Private",127827,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +36,"Private",185203,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",187052,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +72,"Private",177769,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,15,"United-States","<=50K" +61,"Private",68268,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,55,"United-States","<=50K" +37,"Federal-gov",81853,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","Asian-Pac-Islander","Female",0,0,40,"?","<=50K" +30,"Self-emp-inc",153549,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +40,"Private",271393,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",198148,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +65,"Private",469602,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,15,"United-States","<=50K" +36,"Private",163290,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",295949,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",125279,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +64,"Local-gov",182866,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +61,"Self-emp-not-inc",111563,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,20,"United-States",">50K" +38,"Private",34173,"Bachelors",13,"Never-married","Sales","Unmarried","White","Female",0,0,45,"United-States","<=50K" +24,"Private",197757,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +39,"Private",98941,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +44,"Private",205474,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",206659,"Some-college",10,"Divorced","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +73,"?",191394,"Prof-school",15,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +66,"Private",244661,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +53,"Private",47396,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +43,"State-gov",270721,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +57,"State-gov",32694,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",171256,"Assoc-acdm",12,"Divorced","Machine-op-inspct","Own-child","White","Female",0,0,45,"United-States","<=50K" +52,"Self-emp-not-inc",217210,"HS-grad",9,"Widowed","Other-service","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +46,"Private",218329,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",386643,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"Federal-gov",125933,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Self-emp-not-inc",155767,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",54929,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +59,"Private",162136,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +22,"Private",256504,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",162098,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,30,"United-States","<=50K" +39,"Self-emp-not-inc",103110,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Private",227610,"10th",6,"Divorced","Handlers-cleaners","Unmarried","White","Female",0,0,58,"United-States","<=50K" +63,"Private",176696,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Private",220019,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-inc",242984,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +38,"Private",187847,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",132636,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +20,"Private",108887,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +42,"Self-emp-not-inc",195897,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",112181,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,12,"United-States",">50K" +56,"Local-gov",391926,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",195505,"10th",6,"Never-married","Sales","Own-child","White","Male",0,0,5,"United-States","<=50K" +23,"Private",145389,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +33,"?",186824,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",101833,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",82283,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +52,"Private",99602,"HS-grad",9,"Separated","Craft-repair","Own-child","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",213276,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +59,"Private",424468,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?","<=50K" +30,"Private",176123,"10th",6,"Never-married","Machine-op-inspct","Other-relative","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +32,"Private",38797,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",101859,"7th-8th",4,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +53,"Private",87158,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",205066,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,36,"United-States","<=50K" +26,"Private",56929,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,50,"?","<=50K" +31,"Private",87950,"Assoc-voc",11,"Divorced","Sales","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +34,"Private",150154,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"State-gov",112139,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",149217,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +27,"Private",189974,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +23,"Private",109199,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +24,"Private",190290,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +33,"Federal-gov",428271,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +22,"State-gov",134192,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,10,"United-States","<=50K" +47,"Private",168211,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +44,"Federal-gov",316120,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States",">50K" +41,"Private",107276,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +45,"?",112453,"HS-grad",9,"Separated","?","Not-in-family","Asian-Pac-Islander","Male",0,0,4,"United-States","<=50K" +24,"Private",346909,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"Mexico","<=50K" +65,"?",105017,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",317360,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,50,"United-States","<=50K" +23,"Private",189017,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +54,"Private",138179,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",299813,"11th",7,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,37,"Dominican-Republic","<=50K" +45,"Private",265083,"5th-6th",3,"Divorced","Priv-house-serv","Unmarried","White","Female",0,0,35,"Mexico","<=50K" +50,"Private",185846,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",184655,"Assoc-acdm",12,"Never-married","Other-service","Other-relative","White","Male",0,0,25,"United-States","<=50K" +24,"Private",200295,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",63000,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +58,"Self-emp-not-inc",106942,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +47,"Private",52795,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,46,"United-States","<=50K" +37,"Private",51264,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,99,"France",">50K" +37,"Self-emp-not-inc",410919,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +22,"Private",105592,"Assoc-acdm",12,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +29,"Self-emp-not-inc",183151,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States","<=50K" +45,"Private",209912,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"India",">50K" +49,"Self-emp-not-inc",275845,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +72,"Private",89299,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +63,"Self-emp-not-inc",106648,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,12,"United-States","<=50K" +26,"Private",58426,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +58,"Self-emp-not-inc",121912,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,42,"United-States","<=50K" +40,"Private",170730,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +56,"Private",257555,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",51499,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,72,"United-States","<=50K" +28,"Private",195000,"Bachelors",13,"Never-married","Sales","Other-relative","White","Female",0,0,45,"United-States","<=50K" +57,"Private",108741,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +37,"Private",184964,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States",">50K" +44,"Private",156815,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",49325,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",121718,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Germany","<=50K" +18,"Private",172076,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +57,"Self-emp-not-inc",327901,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Local-gov",215990,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"United-States","<=50K" +38,"Private",210866,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,44,"United-States",">50K" +33,"Private",322873,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +42,"Private",265698,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +70,"?",26990,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,60,"United-States","<=50K" +50,"Private",177896,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +50,"Private",189107,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",306830,"Assoc-acdm",12,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Nicaragua","<=50K" +72,"Federal-gov",39110,"11th",7,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,8,"Canada","<=50K" +33,"Private",155475,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",135803,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,25,"Philippines","<=50K" +48,"Private",117849,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +64,"Self-emp-not-inc",339321,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,24,"United-States",">50K" +19,"Private",318822,"11th",7,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +48,"Private",174794,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",193920,"Masters",14,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,45,"?","<=50K" +42,"Federal-gov",91468,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",106760,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,50,"Canada",">50K" +34,"Private",375680,"Assoc-acdm",12,"Never-married","Craft-repair","Own-child","Black","Female",0,0,40,"United-States","<=50K" +55,"Self-emp-inc",222615,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +22,"Private",190968,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",76767,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +50,"Self-emp-not-inc",203098,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States","<=50K" +25,"Private",242729,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +52,"Private",253784,"11th",7,"Divorced","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +30,"Private",206051,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",181553,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +73,"Self-emp-inc",80986,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"United-States","<=50K" +50,"Private",200783,"7th-8th",4,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +34,"Private",42596,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +24,"Private",464502,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","Black","Male",0,0,40,"?","<=50K" +66,"Private",205724,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,24,"United-States",">50K" +22,"Private",446140,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,55,"United-States","<=50K" +69,"Local-gov",32287,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,25,"United-States","<=50K" +23,"Private",56774,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Private",308118,"Bachelors",13,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,40,"?","<=50K" +35,"Private",176279,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,30,"United-States","<=50K" +20,"Private",103277,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +70,"Self-emp-inc",225780,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States",">50K" +34,"Private",149943,"HS-grad",9,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Japan","<=50K" +38,"State-gov",22245,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +33,"Private",93056,"7th-8th",4,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",270522,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,26,"United-States","<=50K" +60,"Self-emp-inc",123218,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",103642,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +34,"Private",157747,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +46,"Self-emp-not-inc",154083,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +30,"State-gov",23037,"Some-college",10,"Never-married","Other-service","Own-child","Amer-Indian-Eskimo","Male",0,0,84,"United-States","<=50K" +23,"?",226891,"HS-grad",9,"Never-married","?","Other-relative","Asian-Pac-Islander","Female",0,0,20,"South","<=50K" +29,"Private",50028,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",138251,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +31,"Private",369825,"7th-8th",4,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,25,"United-States","<=50K" +36,"Federal-gov",44364,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,36,"United-States","<=50K" +23,"Private",230704,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,22,"United-States","<=50K" +35,"Private",42044,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,30,"United-States","<=50K" +28,"Local-gov",56340,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"State-gov",156015,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",163434,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",85251,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +38,"Self-emp-inc",187411,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",396633,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,56,"United-States",">50K" +38,"Private",52596,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +66,"?",260111,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +65,"Local-gov",143570,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +30,"Private",160634,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States",">50K" +54,"Private",29909,"11th",7,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,43,"United-States","<=50K" +49,"Private",94215,"12th",8,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",151990,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,15,"United-States",">50K" +48,"Federal-gov",188081,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",218445,"5th-6th",3,"Never-married","Priv-house-serv","Unmarried","White","Female",0,0,12,"Mexico","<=50K" +77,"Private",235775,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,25,"Cuba","<=50K" +19,"Private",98605,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +30,"Private",188398,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +35,"Private",202950,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"Iran",">50K" +20,"Private",218215,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +49,"Private",147002,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Female",0,0,40,"Puerto-Rico","<=50K" +52,"Private",138497,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Private",57711,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,35,"United-States",">50K" +50,"Private",169925,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,15,"United-States","<=50K" +22,"Private",72310,"11th",7,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +19,"Private",170800,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +39,"Private",215095,"11th",7,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,30,"Puerto-Rico","<=50K" +45,"Private",480717,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,38,"?","<=50K" +61,"Local-gov",34632,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +45,"Private",140664,"Assoc-acdm",12,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +36,"Local-gov",177858,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",129102,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +52,"Local-gov",278522,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +29,"Federal-gov",124953,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,42,"United-States",">50K" +33,"Private",63184,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Self-emp-not-inc",165815,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",248584,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +46,"Local-gov",226871,"Bachelors",13,"Divorced","Protective-serv","Not-in-family","Black","Male",0,0,50,"United-States",">50K" +19,"Private",60367,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,13,"United-States","<=50K" +44,"Private",134120,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +40,"Private",95639,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +20,"Private",132053,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,2,"United-States","<=50K" +24,"Private",138768,"Assoc-acdm",12,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +76,"Private",203910,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Male",0,0,17,"United-States","<=50K" +20,"Private",109952,"HS-grad",9,"Married-civ-spouse","Tech-support","Other-relative","White","Male",0,0,40,"United-States","<=50K" +33,"Private",155781,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +31,"Private",49398,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",159303,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",248339,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +30,"Private",183620,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +42,"Private",201495,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",52221,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",176027,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +42,"Local-gov",266135,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,52,"United-States",">50K" +76,"?",164835,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +21,"Private",363192,"Assoc-voc",11,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",31360,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",63503,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",157614,"HS-grad",9,"Divorced","Sales","Own-child","White","Male",0,0,38,"United-States","<=50K" +38,"Private",363395,"Some-college",10,"Never-married","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",338376,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +29,"Private",87523,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"Private",280714,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-inc",119565,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Local-gov",171482,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,56,"United-States",">50K" +40,"Self-emp-inc",49249,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",331552,"12th",8,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +45,"Private",174426,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",184105,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,28,"United-States","<=50K" +29,"Private",37933,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",376416,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",263612,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"Haiti","<=50K" +23,"Private",227471,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,24,"United-States","<=50K" +39,"Private",191103,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",35644,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Self-emp-not-inc",227298,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +25,"State-gov",187508,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",184378,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"Puerto-Rico","<=50K" +52,"Self-emp-not-inc",190333,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +48,"Private",155372,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,36,"United-States","<=50K" +37,"Private",259882,"Assoc-voc",11,"Never-married","Sales","Unmarried","Black","Female",0,0,6,"United-States","<=50K" +36,"Private",217077,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +33,"Private",103596,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",188236,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +24,"Private",353010,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +42,"Local-gov",70655,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-inc",64874,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Federal-gov",219240,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,22,"United-States","<=50K" +50,"Self-emp-inc",104849,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +40,"Private",173590,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",412316,"HS-grad",9,"Never-married","Sales","Other-relative","Black","Male",0,0,40,"?","<=50K" +57,"Self-emp-inc",195835,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Local-gov",170579,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +61,"Federal-gov",230545,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,35,"Puerto-Rico","<=50K" +71,"Private",162297,"HS-grad",9,"Widowed","Sales","Unmarried","White","Female",0,0,20,"United-States","<=50K" +47,"Private",169549,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",117528,"Bachelors",13,"Never-married","Other-service","Other-relative","White","Female",0,0,45,"United-States","<=50K" +25,"Private",273876,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +33,"Private",529104,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"State-gov",456110,"11th",7,"Divorced","Transport-moving","Unmarried","White","Female",0,0,52,"United-States","<=50K" +39,"?",180868,"11th",7,"Never-married","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",55717,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",166181,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,36,"United-States","<=50K" +24,"Private",52242,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +28,"Private",224629,"Masters",14,"Never-married","Exec-managerial","Not-in-family","Other","Male",0,0,30,"Cuba","<=50K" +20,"Private",197997,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",46144,"Some-college",10,"Divorced","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"State-gov",180871,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,55,"United-States","<=50K" +25,"Private",212311,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",232874,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",175999,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",177121,"Some-college",10,"Separated","Other-service","Not-in-family","White","Female",0,0,58,"United-States","<=50K" +20,"?",326624,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +56,"Private",129836,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,10,"United-States","<=50K" +24,"Private",225515,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"Private",145664,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +37,"Private",151764,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",183523,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Private",257869,"Some-college",10,"Separated","Other-service","Not-in-family","White","Male",0,0,28,"Columbia","<=50K" +40,"Private",73025,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,30,"China","<=50K" +18,"Private",165532,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +51,"Federal-gov",140035,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Self-emp-not-inc",325159,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States",">50K" +64,"Federal-gov",161926,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,8,"United-States","<=50K" +33,"Private",106938,"HS-grad",9,"Married-civ-spouse","Tech-support","Wife","Black","Female",0,0,38,"United-States","<=50K" +31,"Private",97453,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",248653,"1st-4th",2,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,37,"Mexico","<=50K" +39,"Private",59313,"12th",8,"Married-spouse-absent","Transport-moving","Not-in-family","Black","Male",0,0,45,"?","<=50K" +22,"Private",141297,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",227325,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +68,"Private",123653,"5th-6th",3,"Separated","Other-service","Not-in-family","White","Male",0,0,12,"Italy","<=50K" +59,"Federal-gov",176317,"10th",6,"Divorced","Other-service","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +25,"Private",169124,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",179413,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +35,"Private",180137,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,60,"United-States","<=50K" +17,"State-gov",179319,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +19,"Private",45766,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +59,"Private",214052,"5th-6th",3,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",201141,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,37,"United-States","<=50K" +74,"Self-emp-not-inc",43599,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +28,"Private",292536,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +40,"Private",82161,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",180656,"Some-college",10,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"?","<=50K" +20,"Private",181370,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +80,"Private",148623,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +51,"Private",84399,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +17,"Private",143331,"10th",6,"Never-married","Sales","Own-child","White","Male",0,0,15,"United-States","<=50K" +37,"Federal-gov",48779,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"?",175495,"HS-grad",9,"Never-married","?","Own-child","Black","Female",0,0,24,"United-States","<=50K" +58,"Private",83542,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Private",214619,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",160035,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Federal-gov",39603,"Some-college",10,"Never-married","Craft-repair","Unmarried","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +36,"Private",181589,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,32,"Columbia","<=50K" +33,"Private",261511,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",29522,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +30,"Private",36340,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,24,"United-States","<=50K" +57,"?",403625,"Some-college",10,"Married-civ-spouse","?","Husband","Asian-Pac-Islander","Male",0,0,60,"United-States",">50K" +23,"Private",122346,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +53,"Private",152883,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +31,"State-gov",123037,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",0,0,13,"United-States","<=50K" +41,"?",339682,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Mexico","<=50K" +36,"Private",182074,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,40,"United-States","<=50K" +30,"Private",248588,"12th",8,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",187584,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"Canada","<=50K" +36,"Private",46706,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Private",190290,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Self-emp-not-inc",247294,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"Peru","<=50K" +22,"Private",117779,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",121602,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",451744,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +35,"Private",339772,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",185582,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,43,"United-States","<=50K" +26,"Private",260614,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Local-gov",53220,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",213844,"HS-grad",9,"Married-AF-spouse","Craft-repair","Wife","Black","Female",0,0,42,"United-States",">50K" +33,"Private",213226,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +30,"Private",58582,"Bachelors",13,"Never-married","Craft-repair","Own-child","White","Male",0,0,10,"United-States","<=50K" +52,"Private",193116,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +38,"Local-gov",201410,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",190525,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,46,"United-States",">50K" +57,"Self-emp-not-inc",138285,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Iran","<=50K" +51,"Private",111939,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +50,"Private",109277,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +32,"Private",331539,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,50,"China",">50K" +37,"Private",126675,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +69,"Self-emp-not-inc",349022,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,33,"United-States","<=50K" +33,"?",98145,"Some-college",10,"Divorced","?","Unmarried","Amer-Indian-Eskimo","Male",0,0,30,"United-States","<=50K" +37,"Private",234901,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"Germany",">50K" +47,"Self-emp-not-inc",265097,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +63,"Private",237379,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",44793,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +17,"Private",270942,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,35,"Mexico","<=50K" +56,"Private",193622,"HS-grad",9,"Separated","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +90,"Local-gov",187749,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,20,"Philippines","<=50K" +27,"Private",160178,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +38,"Private",680390,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,20,"United-States","<=50K" +33,"Private",96245,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Private",34803,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",170091,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +42,"Private",231813,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",23789,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"State-gov",438711,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,40,"United-States","<=50K" +49,"Private",28791,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",162814,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","Black","Male",0,0,45,"United-States","<=50K" +38,"Private",58108,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +40,"Self-emp-inc",102226,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Federal-gov",209131,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +46,"Self-emp-not-inc",157117,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",172865,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +19,"Private",29798,"12th",8,"Never-married","Handlers-cleaners","Own-child","Amer-Indian-Eskimo","Male",0,0,20,"United-States","<=50K" +71,"?",229424,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +52,"Local-gov",238959,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,32,"United-States",">50K" +27,"Private",189462,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,46,"United-States","<=50K" +52,"Private",139347,"HS-grad",9,"Married-civ-spouse","Transport-moving","Wife","White","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-inc",111128,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",81540,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",257562,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +31,"Private",59496,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",29974,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",102597,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +69,"Private",41419,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +50,"Private",118565,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +54,"State-gov",312897,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,46,"England",">50K" +17,"Private",166290,"9th",5,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +32,"Self-emp-not-inc",116834,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,5,"?","<=50K" +23,"Private",203076,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +66,"Private",201197,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +61,"Private",273803,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",156797,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",283896,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",156926,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States",">50K" +21,"?",163911,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,3,"United-States","<=50K" +56,"Self-emp-inc",165881,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Private",86872,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",167523,"Bachelors",13,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +58,"Private",154950,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Federal-gov",171231,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"Puerto-Rico","<=50K" +62,"Private",244933,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +54,"Private",256908,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,25,"United-States",">50K" +34,"Self-emp-not-inc",33442,"Assoc-voc",11,"Never-married","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +18,"Private",126142,"10th",6,"Never-married","Craft-repair","Own-child","White","Male",0,0,30,"United-States","<=50K" +28,"?",268222,"11th",7,"Never-married","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +32,"Private",167106,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,40,"Hong","<=50K" +22,"Local-gov",50065,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +34,"State-gov",252529,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +53,"?",199665,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States",">50K" +47,"Private",343579,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +19,"Private",190817,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",210731,"7th-8th",4,"Divorced","Sales","Other-relative","White","Male",0,0,20,"Mexico","<=50K" +42,"Private",123816,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +42,"Private",115085,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"Self-emp-not-inc",34297,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",180985,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +62,"Local-gov",33365,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,40,"Canada","<=50K" +20,"Private",197752,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,16,"United-States","<=50K" +47,"Private",180551,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",77975,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",159297,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","Asian-Pac-Islander","Female",0,0,40,"?",">50K" +48,"Private",94342,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +39,"Self-emp-inc",34180,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +46,"Local-gov",367251,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +53,"Private",303462,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,30,"United-States","<=50K" +47,"Federal-gov",220269,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Self-emp-not-inc",45093,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,45,"Canada","<=50K" +34,"Private",101709,"HS-grad",9,"Separated","Transport-moving","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +41,"Private",219591,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",76625,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",342599,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +42,"Self-emp-inc",125846,"1st-4th",2,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"?","<=50K" +54,"Local-gov",238257,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +39,"Self-emp-inc",206253,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +37,"Private",172571,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"Private",95165,"Doctorate",16,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",267843,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,35,"United-States","<=50K" +21,"?",207782,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +68,"?",103161,"HS-grad",9,"Widowed","?","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +20,"Private",132320,"Some-college",10,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Self-emp-not-inc",201138,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +48,"Private",239058,"12th",8,"Widowed","Handlers-cleaners","Unmarried","White","Female",0,0,50,"United-States","<=50K" +21,"Private",176262,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Female",0,0,18,"United-States","<=50K" +22,"Private",264738,"HS-grad",9,"Never-married","Exec-managerial","Other-relative","White","Female",0,0,42,"Germany","<=50K" +34,"Private",182218,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",318982,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +46,"Private",216666,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Guatemala","<=50K" +65,"Private",150095,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",192978,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",68021,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +34,"Self-emp-not-inc",28568,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States",">50K" +20,"Private",115057,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",139568,"11th",7,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Self-emp-inc",138497,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +40,"State-gov",182460,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","Asian-Pac-Islander","Female",0,0,38,"China",">50K" +22,"Private",253310,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,7,"United-States","<=50K" +29,"Self-emp-inc",130856,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +31,"Self-emp-not-inc",389765,"7th-8th",4,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +38,"Private",146178,"HS-grad",9,"Never-married","Craft-repair","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +22,"Private",231053,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,70,"United-States",">50K" +21,"?",145964,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",483450,"9th",5,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Mexico","<=50K" +43,"Self-emp-inc",198316,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Private",160614,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +17,"Self-emp-inc",325171,"10th",6,"Never-married","Other-service","Own-child","Black","Male",0,0,35,"United-States","<=50K" +45,"Private",186473,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +55,"Local-gov",286967,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +51,"Self-emp-not-inc",111939,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States",">50K" +65,"Federal-gov",325089,"10th",6,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +21,"Private",143582,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Female",0,0,45,"United-States","<=50K" +40,"Private",308027,"HS-grad",9,"Widowed","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +58,"Private",105060,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,37,"United-States","<=50K" +53,"Federal-gov",39643,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,58,"United-States","<=50K" +56,"Local-gov",267763,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",124293,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Private",36271,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",143459,"9th",5,"Separated","Handlers-cleaners","Own-child","White","Male",0,0,38,"United-States","<=50K" +36,"Private",186376,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,50,"United-States",">50K" +59,"Self-emp-inc",52822,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +33,"Private",104509,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",192302,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,25,"United-States","<=50K" +25,"Private",214413,"Masters",14,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",108574,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,15,"United-States","<=50K" +41,"Private",223934,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +45,"Private",200559,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +43,"Private",137722,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",261677,"9th",5,"Never-married","Handlers-cleaners","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +33,"Private",136331,"HS-grad",9,"Married-spouse-absent","Craft-repair","Unmarried","White","Male",0,0,50,"United-States","<=50K" +34,"Private",329993,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",91819,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +48,"Private",315423,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",103277,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +47,"Private",236805,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,60,"United-States","<=50K" +27,"Private",74883,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +18,"Private",115443,"11th",7,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +43,"Private",150528,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",43701,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +37,"Federal-gov",419053,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",183594,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,20,"United-States","<=50K" +24,"Private",390348,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",247895,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +75,"Private",191446,"1st-4th",2,"Married-civ-spouse","Other-service","Other-relative","Black","Female",0,0,16,"United-States","<=50K" +43,"Self-emp-not-inc",33521,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,70,"United-States",">50K" +64,"Private",46087,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +36,"Private",356824,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Private",158746,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",153323,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,20,"United-States","<=50K" +73,"Self-emp-not-inc",130391,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +46,"Private",173613,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",182757,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",50397,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,20,"United-States","<=50K" +43,"Federal-gov",101709,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +21,"Private",202570,"12th",8,"Never-married","Adm-clerical","Other-relative","Black","Male",0,0,48,"?","<=50K" +40,"Private",145649,"HS-grad",9,"Separated","Sales","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +36,"Private",136343,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +64,"Self-emp-inc",142166,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +19,"?",242001,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +46,"Local-gov",124071,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,65,"United-States",">50K" +41,"Local-gov",190368,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +29,"?",19793,"Some-college",10,"Divorced","?","Unmarried","White","Female",0,0,8,"United-States","<=50K" +28,"Private",67661,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +23,"Private",62278,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Federal-gov",295010,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","White","Female",0,0,60,"United-States",">50K" +44,"Private",203897,"Bachelors",13,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Female",0,0,40,"Cuba","<=50K" +27,"Private",265314,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +25,"Private",159603,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,34,"United-States","<=50K" +29,"Private",134331,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",123011,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Poland",">50K" +27,"Private",274964,"Bachelors",13,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +34,"Private",66309,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +38,"Private",73471,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"?",26671,"HS-grad",9,"Never-married","?","Other-relative","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +56,"Private",357118,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +35,"Self-emp-inc",184655,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,62,"United-States","<=50K" +23,"?",55492,"Assoc-voc",11,"Never-married","?","Not-in-family","Amer-Indian-Eskimo","Female",0,0,30,"United-States","<=50K" +23,"Private",175266,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",188008,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,20,"United-States","<=50K" +48,"Self-emp-inc",56975,"HS-grad",9,"Divorced","Sales","Unmarried","Asian-Pac-Islander","Female",0,0,84,"?","<=50K" +27,"Private",150025,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"Puerto-Rico","<=50K" +22,"?",189203,"Assoc-acdm",12,"Never-married","?","Other-relative","White","Male",0,0,15,"United-States","<=50K" +49,"Self-emp-inc",330874,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States",">50K" +23,"Private",136824,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +24,"Private",201179,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",324654,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +25,"Federal-gov",366207,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",103860,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +22,"Private",106700,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Female",0,0,27,"United-States","<=50K" +54,"Local-gov",163557,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +39,"Self-emp-inc",286261,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",123083,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +75,"Self-emp-inc",125197,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,26,"United-States","<=50K" +28,"Self-emp-not-inc",278073,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","Black","Male",0,0,30,"United-States","<=50K" +50,"Private",133963,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +62,"Self-emp-not-inc",71467,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +40,"Private",76487,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Local-gov",215245,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +24,"Federal-gov",127185,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +21,"Private",179720,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Female",0,0,30,"United-States","<=50K" +48,"Private",173938,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +34,"Private",344275,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +23,"Private",150463,"HS-grad",9,"Never-married","Priv-house-serv","Unmarried","Other","Female",0,0,40,"Guatemala","<=50K" +42,"Local-gov",201723,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Self-emp-inc",77392,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +21,"?",171156,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +56,"Self-emp-not-inc",357118,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +48,"Federal-gov",167749,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +37,"Self-emp-not-inc",352882,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","Asian-Pac-Islander","Female",0,0,70,"South",">50K" +25,"Private",51201,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +40,"Private",365986,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States",">50K" +34,"Private",400416,"11th",7,"Never-married","Machine-op-inspct","Own-child","Black","Male",0,0,45,"United-States","<=50K" +52,"Private",31533,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",192337,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",301654,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",145162,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"?",">50K" +20,"Private",88126,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,9,"England","<=50K" +68,"Private",165017,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Italy",">50K" +35,"Private",238342,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",857532,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Male",0,0,40,"United-States","<=50K" +64,"Private",134378,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",260797,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,23,"United-States","<=50K" +25,"Private",138765,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +74,"?",256674,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +31,"Private",247444,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Columbia","<=50K" +67,"Private",180539,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,10,"United-States","<=50K" +29,"Private",107160,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",262024,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",131230,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,37,"United-States","<=50K" +67,"Private",274451,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,16,"United-States","<=50K" +41,"State-gov",365986,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States",">50K" +27,"Private",204515,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +51,"Private",99316,"12th",8,"Divorced","Transport-moving","Unmarried","White","Male",0,0,50,"United-States","<=50K" +21,"?",206681,"11th",7,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States","<=50K" +28,"Private",268726,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,46,"United-States","<=50K" +21,"Private",275395,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",383322,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",126822,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"United-States","<=50K" +39,"Self-emp-inc",168355,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +21,"Private",162667,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"Columbia","<=50K" +43,"Private",373403,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",249362,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +31,"Private",111567,"9th",5,"Never-married","Sales","Not-in-family","White","Male",0,0,43,"United-States",">50K" +18,"?",216508,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +27,"Private",145784,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Amer-Indian-Eskimo","Female",0,0,45,"United-States","<=50K" +34,"State-gov",209317,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",259505,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",345360,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"England","<=50K" +40,"Self-emp-inc",33126,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +21,"Private",206354,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +25,"Private",1484705,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,25,"United-States","<=50K" +21,"Private",26410,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Self-emp-not-inc",220901,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,30,"United-States","<=50K" +49,"Self-emp-inc",44671,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",38620,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +36,"Private",89040,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,47,"United-States","<=50K" +32,"Private",370160,"Some-college",10,"Separated","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",208946,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,32,"United-States","<=50K" +21,"Private",131230,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,10,"United-States","<=50K" +25,"Private",60358,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",350853,"5th-6th",3,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"?","<=50K" +24,"Private",209782,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",351952,"Some-college",10,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,20,"United-States","<=50K" +26,"Private",142081,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"Mexico","<=50K" +22,"Private",164775,"9th",5,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"Guatemala","<=50K" +41,"Local-gov",47858,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",404085,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +24,"Private",218678,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",321760,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,17,"United-States","<=50K" +45,"Local-gov",185399,"Masters",14,"Divorced","Prof-specialty","Own-child","White","Female",0,0,55,"United-States","<=50K" +38,"Local-gov",409200,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",40077,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Self-emp-not-inc",31740,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Local-gov",233722,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",192039,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +17,"Private",222618,"11th",7,"Never-married","Sales","Own-child","Black","Female",0,0,30,"United-States","<=50K" +31,"Local-gov",194141,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,48,"United-States","<=50K" +47,"State-gov",80282,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +27,"Private",166350,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +61,"Federal-gov",60641,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,30,"United-States","<=50K" +33,"Private",124827,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +67,"Private",105438,"HS-grad",9,"Separated","Machine-op-inspct","Other-relative","White","Female",0,0,40,"United-States","<=50K" +38,"Private",85244,"Bachelors",13,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",120535,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Local-gov",269604,"5th-6th",3,"Never-married","Other-service","Unmarried","Other","Female",0,0,40,"El-Salvador","<=50K" +27,"Private",247711,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +45,"Private",380922,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +24,"Private",281221,"Bachelors",13,"Never-married","Adm-clerical","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Taiwan","<=50K" +23,"Private",269687,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",181758,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +61,"Federal-gov",136787,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",107882,"HS-grad",9,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"United-States","<=50K" +34,"Private",172579,"Assoc-voc",11,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Federal-gov",38905,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +36,"Private",168826,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",424034,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +60,"Private",117509,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"?",196971,"Bachelors",13,"Never-married","?","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +64,"Private",69525,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,20,"United-States","<=50K" +22,"Private",374116,"HS-grad",9,"Never-married","Sales","Unmarried","White","Female",0,0,35,"United-States","<=50K" +27,"Private",283913,"5th-6th",3,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,65,"England","<=50K" +36,"State-gov",147258,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +27,"Private",139903,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +52,"Private",112959,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",264148,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +23,"Private",256211,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Male",0,0,24,"Vietnam","<=50K" +29,"Self-emp-not-inc",142519,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",281852,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,80,"United-States","<=50K" +38,"Private",380543,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +50,"Self-emp-not-inc",204402,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,84,"United-States",">50K" +50,"Private",192203,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",199005,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +17,"Self-emp-inc",61838,"10th",6,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",210095,"11th",7,"Married-spouse-absent","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +19,"Private",187352,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",32451,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",79443,"9th",5,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"Mexico","<=50K" +27,"Private",212622,"Masters",14,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Private",32650,"Assoc-voc",11,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +44,"Private",125461,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",219867,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,35,"United-States","<=50K" +32,"Local-gov",206609,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"Private",101299,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",29437,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +65,"Private",87164,"11th",7,"Widowed","Sales","Other-relative","White","Female",0,0,20,"United-States","<=50K" +57,"Self-emp-inc",146103,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +48,"Private",169324,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,32,"Haiti","<=50K" +27,"Private",29523,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"?",247075,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +20,"?",200967,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,12,"United-States","<=50K" +51,"?",175985,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",267661,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +65,"Private",243858,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +20,"?",43587,"HS-grad",9,"Married-spouse-absent","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +47,"Federal-gov",31339,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",73145,"9th",5,"Never-married","Craft-repair","Own-child","White","Female",0,0,16,"United-States","<=50K" +38,"Local-gov",218184,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +38,"Local-gov",223237,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Self-emp-not-inc",93319,"HS-grad",9,"Never-married","Sales","Other-relative","White","Female",0,0,4,"United-States","<=50K" +24,"?",212300,"HS-grad",9,"Separated","?","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +52,"Private",187356,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,41,"United-States","<=50K" +46,"Self-emp-not-inc",220832,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,58,"United-States",">50K" +22,"Private",211361,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +56,"Private",134195,"Masters",14,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +37,"Self-emp-not-inc",218249,"11th",7,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +59,"Private",70720,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,55,"United-States",">50K" +31,"Private",237317,"9th",5,"Never-married","Craft-repair","Not-in-family","Other","Male",0,0,45,"United-States","<=50K" +22,"Private",359759,"Some-college",10,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Male",0,0,20,"Philippines","<=50K" +48,"Self-emp-not-inc",181758,"Doctorate",16,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,60,"United-States",">50K" +63,"Self-emp-inc",267101,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +53,"Private",55139,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +38,"Private",220237,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?",">50K" +39,"Private",101073,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,24,"United-States","<=50K" +59,"Private",69884,"Prof-school",15,"Married-spouse-absent","Prof-specialty","Unmarried","White","Male",0,0,50,"United-States","<=50K" +45,"Private",201127,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",164733,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +60,"State-gov",129447,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +38,"Private",32837,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,56,"United-States","<=50K" +31,"Private",200117,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-not-inc",219183,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +66,"?",188842,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,24,"United-States","<=50K" +26,"Private",272669,"Bachelors",13,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Male",0,0,20,"South","<=50K" +68,"?",191288,"7th-8th",4,"Widowed","?","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +32,"Private",176185,"Some-college",10,"Divorced","Exec-managerial","Other-relative","White","Male",0,0,60,"United-States","<=50K" +25,"Local-gov",197728,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +43,"Local-gov",144778,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"?","<=50K" +26,"?",133373,"Bachelors",13,"Never-married","?","Own-child","White","Male",0,0,44,"United-States","<=50K" +66,"Private",86010,"10th",6,"Widowed","Transport-moving","Not-in-family","White","Female",0,0,11,"United-States","<=50K" +31,"Private",228873,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",187415,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,50,"?","<=50K" +56,"Private",98361,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?",">50K" +22,"Private",129172,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +46,"Local-gov",316205,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +33,"Private",226629,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"United-States","<=50K" +26,"State-gov",180886,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States","<=50K" +42,"Self-emp-not-inc",69333,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +45,"Private",213620,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Private",197397,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","Other","Female",0,0,6,"Puerto-Rico","<=50K" +19,"Private",223648,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,20,"?","<=50K" +27,"Private",179915,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,99,"United-States","<=50K" +42,"Private",112956,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",187999,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +44,"Private",77313,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",231948,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,64,"United-States",">50K" +37,"Private",37109,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Asian-Pac-Islander","Female",0,0,60,"Philippines","<=50K" +29,"Private",79387,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +53,"?",133963,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",177937,"Bachelors",13,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Male",0,0,45,"Poland","<=50K" +80,"Private",173488,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +61,"Private",183355,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",289944,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +23,"Private",62278,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +48,"Federal-gov",110457,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",295763,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,50,"United-States","<=50K" +71,"State-gov",100063,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +49,"Private",194962,"11th",7,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,6,"United-States","<=50K" +39,"Federal-gov",227597,"HS-grad",9,"Never-married","Armed-Forces","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +22,"Private",117606,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +67,"Federal-gov",44774,"Bachelors",13,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",177648,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +38,"?",203482,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,45,"United-States","<=50K" +50,"Private",153931,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",84774,"Assoc-acdm",12,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,0,40,"United-States","<=50K" +23,"Private",157127,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +26,"Private",170786,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",281030,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",167405,"HS-grad",9,"Married-spouse-absent","Farming-fishing","Own-child","White","Female",0,0,40,"Mexico","<=50K" +43,"Private",388849,"Assoc-acdm",12,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,60,"United-States","<=50K" +31,"State-gov",176998,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States",">50K" +57,"Private",200316,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",160300,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +22,"Private",236684,"Assoc-voc",11,"Never-married","Other-service","Own-child","Black","Female",0,0,36,"United-States","<=50K" +20,"Local-gov",247794,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +39,"Private",279490,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +27,"State-gov",280618,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",248406,"HS-grad",9,"Separated","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Local-gov",226494,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +41,"Private",220460,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"United-States","<=50K" +25,"Private",108317,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"State-gov",147256,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States",">50K" +22,"Private",110371,"HS-grad",9,"Married-civ-spouse","Other-service","Own-child","White","Male",0,0,50,"United-States","<=50K" +62,"Private",114060,"7th-8th",4,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,91,"United-States","<=50K" +29,"Federal-gov",31161,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","Other","Female",0,0,40,"United-States","<=50K" +44,"Private",105862,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,70,"United-States",">50K" +32,"Private",402089,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,2,"United-States","<=50K" +19,"?",425447,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +20,"Private",137300,"Assoc-voc",11,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +65,"State-gov",326691,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States",">50K" +24,"Private",275093,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +37,"Self-emp-not-inc",112497,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Local-gov",174491,"HS-grad",9,"Divorced","Tech-support","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",114835,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,60,"United-States",">50K" +28,"Private",137898,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +32,"Private",134886,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +38,"Private",193815,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +33,"Private",237833,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",101593,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +27,"Private",164924,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",174201,"HS-grad",9,"Divorced","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +47,"Local-gov",36169,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +55,"Private",144071,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Self-emp-not-inc",180859,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,8,"United-States","<=50K" +54,"Private",221915,"Some-college",10,"Widowed","Craft-repair","Unmarried","White","Female",0,0,50,"United-States","<=50K" +40,"Private",26892,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",351084,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",97306,"Bachelors",13,"Divorced","Craft-repair","Unmarried","White","Female",0,0,25,"United-States","<=50K" +30,"Private",185027,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",182539,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +22,"Private",215395,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +37,"Private",186434,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States",">50K" +41,"?",217921,"9th",5,"Married-civ-spouse","?","Wife","Asian-Pac-Islander","Female",0,0,40,"Hong","<=50K" +52,"Local-gov",346668,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-inc",412952,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",167009,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +58,"Private",316000,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Self-emp-not-inc",216256,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",341835,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +30,"Private",169841,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +26,"Self-emp-not-inc",200681,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Outlying-US(Guam-USVI-etc)","<=50K" +46,"Self-emp-not-inc",456956,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +26,"Federal-gov",276075,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +50,"Federal-gov",96657,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +22,"Private",374313,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Private",110998,"Masters",14,"Widowed","Tech-support","Unmarried","Asian-Pac-Islander","Female",0,0,40,"India","<=50K" +30,"Private",53285,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,52,"United-States",">50K" +58,"Private",104613,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +17,"?",303317,"11th",7,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",318822,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",375078,"7th-8th",4,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"Mexico","<=50K" +20,"?",232799,"HS-grad",9,"Never-married","?","Own-child","Black","Female",0,0,25,"United-States","<=50K" +30,"Private",210851,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",213745,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,45,"United-States","<=50K" +51,"Private",204447,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +26,"Private",318934,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",237386,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +44,"Private",182629,"Masters",14,"Divorced","Sales","Not-in-family","White","Male",0,0,24,"Iran","<=50K" +43,"Private",144778,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +35,"Private",117166,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +41,"Private",171550,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",165302,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Other","Female",0,0,40,"United-States","<=50K" +54,"Private",284952,"10th",6,"Separated","Sales","Unmarried","White","Female",0,0,43,"Italy","<=50K" +62,"Private",96099,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",198759,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +30,"Private",227886,"HS-grad",9,"Never-married","Exec-managerial","Own-child","Black","Female",0,0,35,"Jamaica","<=50K" +32,"Private",391874,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Self-emp-not-inc",184370,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +84,"Local-gov",135839,"Assoc-voc",11,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,14,"United-States","<=50K" +46,"Private",194698,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,60,"United-States","<=50K" +29,"Private",67218,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",205152,"Assoc-voc",11,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States",">50K" +23,"Private",434467,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,42,"United-States","<=50K" +63,"?",110150,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,55,"United-States",">50K" +42,"State-gov",404573,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +17,"Private",99462,"11th",7,"Never-married","Other-service","Own-child","Amer-Indian-Eskimo","Female",0,0,20,"United-States","<=50K" +60,"Private",170310,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",199883,"12th",8,"Divorced","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",70034,"7th-8th",4,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"Portugal","<=50K" +31,"Private",393357,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,48,"United-States","<=50K" +61,"Private",223133,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +43,"State-gov",345969,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +40,"State-gov",195520,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,49,"United-States","<=50K" +39,"Private",257942,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Local-gov",269300,"Some-college",10,"Married-spouse-absent","Adm-clerical","Unmarried","Black","Female",0,0,27,"United-States","<=50K" +47,"Private",137354,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +45,"Federal-gov",232997,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States",">50K" +30,"Private",77266,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +30,"Self-emp-not-inc",164190,"Prof-school",15,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Local-gov",26832,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",188096,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,72,"United-States",">50K" +48,"Self-emp-inc",369522,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,25,"United-States",">50K" +20,"Private",110998,"Some-college",10,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,30,"United-States","<=50K" +31,"?",163890,"Some-college",10,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",358631,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +50,"Private",185354,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +33,"Private",336061,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"?",47011,"Bachelors",13,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +30,"Private",59496,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",32950,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",199555,"Assoc-voc",11,"Never-married","Sales","Unmarried","White","Male",0,0,5,"United-States","<=50K" +28,"Private",91299,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,45,"United-States","<=50K" +38,"Private",242559,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +52,"Federal-gov",22428,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States",">50K" +32,"Private",239150,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +37,"Private",170563,"Assoc-voc",11,"Separated","Prof-specialty","Unmarried","White","Female",0,0,32,"United-States","<=50K" +36,"Private",173542,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",286026,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Local-gov",163229,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,56,"United-States","<=50K" +40,"Local-gov",165726,"Assoc-voc",11,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Private",70055,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +35,"Private",184655,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",139906,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,81,"United-States","<=50K" +32,"Local-gov",198211,"Assoc-voc",11,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",146540,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +53,"Local-gov",132304,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",190916,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"Never-worked",237272,"10th",6,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +44,"Private",755858,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States",">50K" +52,"Private",127315,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +42,"State-gov",304302,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +34,"Private",184942,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",267989,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",188377,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",340787,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",169071,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,28,"United-States","<=50K" +36,"Self-emp-not-inc",151094,"Assoc-voc",11,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +27,"Private",122922,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Private",151141,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,15,"United-States","<=50K" +30,"Private",136651,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +37,"Private",177285,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,48,"United-States",">50K" +31,"Local-gov",128016,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"Private",200318,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +32,"Private",250354,"10th",6,"Never-married","Craft-repair","Other-relative","White","Male",0,0,45,"United-States","<=50K" +58,"Private",191069,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",27856,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,8,"United-States","<=50K" +44,"Private",523484,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +42,"Private",196029,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States",">50K" +45,"Private",200471,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"United-States","<=50K" +20,"Private",353195,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +35,"Private",222868,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",221791,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","Black","Male",0,0,40,"United-States","<=50K" +56,"Private",197114,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,28,"United-States","<=50K" +48,"Private",160220,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Self-emp-not-inc",274917,"Masters",14,"Widowed","Other-service","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +32,"Private",348460,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +23,"Private",112683,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,12,"United-States","<=50K" +48,"Private",345831,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",105370,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +48,"Private",345006,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"Mexico","<=50K" +40,"Local-gov",108765,"Assoc-voc",11,"Never-married","Exec-managerial","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +50,"Private",138022,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",175029,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +19,"Private",189574,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +36,"Self-emp-not-inc",186035,"Prof-school",15,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States",">50K" +39,"Private",165235,"Bachelors",13,"Separated","Prof-specialty","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Philippines",">50K" +22,"Private",105043,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",248584,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Private",200153,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +50,"Private",398625,"11th",7,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",114043,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",169544,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"Private",343849,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +24,"Private",291578,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +46,"Private",136162,"Assoc-voc",11,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-inc",302612,"Masters",14,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +65,"Local-gov",240166,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States","<=50K" +44,"Private",119281,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +73,"Self-emp-not-inc",300404,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,6,"United-States",">50K" +21,"Private",82847,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +43,"Federal-gov",287008,"Masters",14,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,35,"United-States",">50K" +21,"Private",654141,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,32,"United-States","<=50K" +30,"Private",252646,"Some-college",10,"Separated","Transport-moving","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +54,"Private",171924,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,48,"United-States","<=50K" +19,"Private",219742,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +55,"State-gov",153788,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,37,"United-States","<=50K" +20,"Private",60639,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,28,"United-States","<=50K" +53,"Private",96062,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Greece","<=50K" +51,"Private",165614,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,55,"United-States",">50K" +33,"Private",159888,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Private",110586,"Some-college",10,"Widowed","Priv-house-serv","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Self-emp-not-inc",143062,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +17,"Self-emp-inc",413557,"9th",5,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",137658,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +36,"Private",398931,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",311764,"10th",6,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,35,"United-States","<=50K" +58,"Private",98725,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +38,"Private",140854,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Federal-gov",352768,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"?",27184,"HS-grad",9,"Widowed","?","Unmarried","White","Female",0,0,38,"United-States","<=50K" +72,"?",237229,"Assoc-voc",11,"Widowed","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +27,"Private",210313,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"Guatemala","<=50K" +38,"Private",194538,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States",">50K" +28,"Private",211032,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-inc",107909,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",136077,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +28,"Private",214689,"Bachelors",13,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,25,"United-States","<=50K" +70,"?",147558,"Bachelors",13,"Divorced","?","Not-in-family","White","Female",0,0,7,"United-States","<=50K" +40,"Self-emp-not-inc",93793,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",247025,"Assoc-voc",11,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",284403,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,60,"United-States","<=50K" +29,"Private",221977,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +25,"Federal-gov",339956,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",161097,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States",">50K" +60,"Private",223696,"1st-4th",2,"Divorced","Craft-repair","Not-in-family","Other","Male",0,0,38,"Dominican-Republic","<=50K" +31,"Private",234500,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +51,"Local-gov",97005,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",242615,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +36,"Private",174938,"Bachelors",13,"Divorced","Tech-support","Unmarried","White","Male",0,0,20,"United-States","<=50K" +35,"Private",160120,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +48,"Private",193775,"Bachelors",13,"Divorced","Adm-clerical","Own-child","White","Male",0,0,38,"United-States",">50K" +78,"Self-emp-not-inc",59583,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,25,"United-States","<=50K" +72,"Private",157913,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,17,"United-States","<=50K" +24,"Private",308205,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +58,"?",158506,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,16,"United-States","<=50K" +48,"Private",330470,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,30,"United-States","<=50K" +28,"Private",184078,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",123384,"Masters",14,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",330132,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +47,"Private",274720,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"Jamaica","<=50K" +50,"Private",129673,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +35,"Federal-gov",205584,"5th-6th",3,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +17,"Private",327127,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,20,"United-States","<=50K" +41,"Private",225892,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +37,"Private",224886,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,42,"United-States","<=50K" +35,"Local-gov",27763,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +56,"Private",73684,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Portugal","<=50K" +23,"Private",107452,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",23871,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,32,"United-States","<=50K" +79,"Self-emp-inc",309272,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",469864,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +55,"Private",286230,"11th",7,"Divorced","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +59,"State-gov",186308,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +22,"Private",113062,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",86150,"11th",7,"Never-married","Sales","Own-child","Asian-Pac-Islander","Female",0,0,19,"Philippines","<=50K" +41,"Private",262038,"5th-6th",3,"Married-spouse-absent","Farming-fishing","Not-in-family","White","Male",0,0,35,"Mexico","<=50K" +32,"Private",279231,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Italy","<=50K" +45,"Private",183786,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +61,"Private",339358,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Other-relative","White","Female",0,0,45,"Mexico","<=50K" +34,"Private",287737,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",99203,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",113481,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +65,"Private",204042,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +24,"Private",43387,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"England",">50K" +37,"Private",99233,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",313729,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +42,"Private",99679,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +18,"Private",169745,"7th-8th",4,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Federal-gov",19914,"Some-college",10,"Widowed","Exec-managerial","Unmarried","Amer-Indian-Eskimo","Female",0,0,15,"United-States","<=50K" +31,"Private",113543,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",224241,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +40,"Self-emp-inc",137367,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,50,"China","<=50K" +32,"Private",263908,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",280798,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Local-gov",203849,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-inc",62546,"Doctorate",16,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +40,"Private",197344,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +36,"Private",93225,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +33,"Private",187560,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,36,"United-States","<=50K" +23,"State-gov",61743,"5th-6th",3,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +21,"Private",186648,"10th",6,"Separated","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",173321,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,32,"United-States","<=50K" +53,"State-gov",246820,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +20,"?",424034,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,15,"United-States","<=50K" +53,"Self-emp-not-inc",291755,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,72,"United-States","<=50K" +58,"Private",104945,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,60,"United-States","<=50K" +51,"Private",85423,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +31,"Private",214235,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,65,"United-States","<=50K" +35,"Self-emp-not-inc",278632,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"?",27415,"11th",7,"Never-married","?","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +31,"Local-gov",143392,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +21,"Private",277408,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +39,"Self-emp-not-inc",336793,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +51,"Private",74660,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",395026,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,12,"United-States","<=50K" +32,"Private",171215,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +56,"Private",121362,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +35,"Private",409200,"Assoc-acdm",12,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +63,"Private",268965,"12th",8,"Widowed","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +61,"Private",136262,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",141323,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Local-gov",108083,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +19,"Private",82210,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +33,"State-gov",400943,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +35,"Private",308489,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,50,"United-States","<=50K" +35,"Private",187053,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Female",0,0,60,"United-States",">50K" +38,"Private",75826,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +23,"Private",413345,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +22,"Private",356567,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +20,"Private",223811,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",159313,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",250170,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States",">50K" +59,"Private",135617,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",187346,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",108103,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",255476,"5th-6th",3,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +24,"Private",68577,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",155961,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,35,"Jamaica","<=50K" +22,"State-gov",264102,"Some-college",10,"Never-married","Other-service","Other-relative","Black","Male",0,0,39,"Haiti","<=50K" +37,"Private",167777,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,52,"United-States","<=50K" +28,"Private",199998,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +55,"Private",199856,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,50,"United-States","<=50K" +29,"?",189765,"5th-6th",3,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States","<=50K" +32,"Private",193042,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States","<=50K" +66,"?",222810,"Some-college",10,"Divorced","?","Other-relative","White","Female",0,0,35,"United-States","<=50K" +47,"Local-gov",162595,"Some-college",10,"Married-spouse-absent","Craft-repair","Other-relative","White","Male",0,0,45,"United-States","<=50K" +23,"Private",208826,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Local-gov",120190,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +40,"Self-emp-not-inc",27242,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,84,"United-States","<=50K" +28,"Private",309196,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",240698,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",411797,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,35,"United-States",">50K" +25,"Private",178843,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,15,"United-States","<=50K" +42,"Private",136177,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +35,"Private",243409,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Germany","<=50K" +34,"Private",164748,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"State-gov",24185,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States",">50K" +30,"Private",167476,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +44,"Private",106900,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,44,"United-States",">50K" +52,"Private",53497,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",335704,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +36,"Private",211022,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +30,"Private",163003,"Bachelors",13,"Never-married","Exec-managerial","Own-child","Asian-Pac-Islander","Female",0,0,52,"Taiwan","<=50K" +39,"Private",67433,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",458549,"1st-4th",2,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,96,"Mexico","<=50K" +26,"Private",190469,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",195411,"HS-grad",9,"Never-married","Sales","Own-child","Black","Female",0,0,20,"United-States","<=50K" +20,"Private",216889,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +70,"?",336007,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +26,"Private",167350,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,50,"United-States","<=50K" +24,"Private",241857,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +48,"Private",125892,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +62,"Private",272209,"HS-grad",9,"Divorced","Priv-house-serv","Unmarried","Black","Female",0,0,99,"United-States","<=50K" +48,"Private",175221,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",180195,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",38090,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +58,"Private",310085,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Federal-gov",118686,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +29,"?",112963,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-inc",120131,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,52,"?","<=50K" +19,"Private",43937,"Some-college",10,"Never-married","Other-service","Other-relative","White","Female",0,0,20,"United-States","<=50K" +37,"Private",210438,"11th",7,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",176724,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +31,"Self-emp-not-inc",113364,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +64,"Self-emp-not-inc",73986,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +28,"Local-gov",197932,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,16,"United-States","<=50K" +32,"Private",193285,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"Local-gov",223342,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +35,"Private",49749,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States",">50K" +19,"?",211553,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +45,"Private",201865,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +46,"Self-emp-not-inc",275625,"Bachelors",13,"Divorced","Other-service","Unmarried","Asian-Pac-Islander","Female",0,0,60,"South",">50K" +19,"Private",206599,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,16,"United-States","<=50K" +29,"Private",89813,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"Scotland","<=50K" +25,"State-gov",156848,"HS-grad",9,"Married-civ-spouse","Protective-serv","Own-child","White","Male",0,0,35,"United-States","<=50K" +37,"Private",162494,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",205407,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +28,"Private",375313,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +32,"Private",127895,"Some-college",10,"Never-married","Exec-managerial","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +34,"Private",248754,"11th",7,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",188096,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +20,"Private",216811,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Self-emp-inc",113870,"Masters",14,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Federal-gov",343052,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +35,"Private",280966,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",42044,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +32,"Private",309513,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",163604,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +52,"Private",224198,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +50,"Private",338283,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",242375,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +25,"Private",81286,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +21,"Private",243368,"Preschool",1,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"Mexico","<=50K" +31,"Private",217803,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +31,"Self-emp-not-inc",323020,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,30,"United-States","<=50K" +41,"Private",34278,"Assoc-voc",11,"Separated","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",184579,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,60,"United-States","<=50K" +20,"?",210781,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,10,"United-States","<=50K" +20,"Private",142673,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +29,"Private",131714,"10th",6,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,25,"United-States","<=50K" +51,"Local-gov",74784,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Local-gov",181372,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,33,"United-States",">50K" +23,"?",62507,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +48,"Private",155664,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"United-States",">50K" +62,"Private",113440,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +22,"Private",147227,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +20,"Private",184678,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +31,"Private",98639,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",174201,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Private",123780,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,38,"United-States","<=50K" +20,"Private",374116,"HS-grad",9,"Never-married","Prof-specialty","Other-relative","White","Female",0,0,40,"United-States","<=50K" +37,"Local-gov",212005,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +65,"Private",123965,"Bachelors",13,"Widowed","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",113635,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"Ireland","<=50K" +62,"Private",664366,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +53,"Private",218311,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +38,"Private",278557,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +49,"Private",314773,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",194861,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",400616,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",208117,"Bachelors",13,"Never-married","Prof-specialty","Other-relative","White","Male",0,0,40,"United-States","<=50K" +36,"Private",184498,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",117674,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +19,"Private",162621,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,14,"United-States","<=50K" +23,"Private",368739,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +63,"Self-emp-not-inc",196994,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,15,"United-States","<=50K" +63,"Self-emp-not-inc",420629,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,45,"United-States","<=50K" +76,"Local-gov",169133,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +45,"Self-emp-inc",120131,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Self-emp-inc",456236,"Some-college",10,"Divorced","Sales","Own-child","White","Male",0,0,45,"United-States",">50K" +51,"Private",107123,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",36924,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",167065,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",53642,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",154668,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Federal-gov",102238,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +27,"Private",152951,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",257042,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +60,"Private",74243,"Assoc-voc",11,"Widowed","Craft-repair","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +33,"Private",117186,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +35,"Private",178322,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +31,"State-gov",286911,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,38,"United-States","<=50K" +57,"Self-emp-not-inc",177271,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States","<=50K" +30,"Private",149427,"9th",5,"Never-married","Craft-repair","Own-child","White","Male",0,0,45,"United-States","<=50K" +45,"Private",101656,"10th",6,"Never-married","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +25,"Private",241025,"Bachelors",13,"Never-married","Other-service","Own-child","White","Male",0,0,18,"United-States","<=50K" +51,"Self-emp-inc",338836,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",210534,"5th-6th",3,"Separated","Adm-clerical","Other-relative","White","Male",0,0,40,"El-Salvador","<=50K" +28,"Private",95725,"Assoc-voc",11,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +47,"?",178013,"10th",6,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"Cuba","<=50K" +53,"Federal-gov",167410,"Bachelors",13,"Divorced","Tech-support","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +25,"Federal-gov",406955,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +47,"Private",341762,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",239303,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"?","<=50K" +30,"Private",38848,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",54744,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",332194,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",154950,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +33,"Self-emp-not-inc",196342,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +31,"Private",201292,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",339767,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,20,"England",">50K" +26,"Private",250066,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",318886,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Black","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",124076,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +30,"State-gov",242122,"HS-grad",9,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +17,"Private",34019,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +35,"Local-gov",230754,"Masters",14,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",213842,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",62165,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"?","<=50K" +34,"Private",134737,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States",">50K" +32,"Private",515629,"HS-grad",9,"Separated","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Federal-gov",119199,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",90222,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",28443,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",159442,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"Ireland","<=50K" +54,"Private",315804,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",135840,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +38,"Private",81232,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"?",">50K" +43,"Private",118001,"7th-8th",4,"Separated","Farming-fishing","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",207875,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,20,"United-States","<=50K" +39,"Private",164898,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Local-gov",170066,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,25,"United-States",">50K" +47,"Private",111994,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,34,"United-States","<=50K" +45,"Private",166636,"HS-grad",9,"Divorced","Other-service","Other-relative","Black","Female",0,0,35,"United-States","<=50K" +24,"State-gov",61737,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",241885,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",234190,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +57,"Private",230899,"5th-6th",3,"Separated","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",222442,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,51,"Cuba","<=50K" +27,"Private",157612,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +28,"Private",199903,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +74,"?",292627,"1st-4th",2,"Married-civ-spouse","?","Husband","Black","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",156687,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Asian-Pac-Islander","Male",0,0,42,"Japan","<=50K" +27,"Private",369522,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,45,"United-States","<=50K" +61,"Private",226297,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",356017,"11th",7,"Never-married","Other-service","Not-in-family","White","Male",0,0,99,"United-States","<=50K" +28,"Private",189257,"9th",5,"Never-married","Handlers-cleaners","Own-child","Black","Female",0,0,24,"United-States","<=50K" +20,"Private",157541,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",69251,"Assoc-voc",11,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +38,"State-gov",272944,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",113667,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +40,"Private",222011,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States",">50K" +43,"Private",191196,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +38,"Private",169104,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +19,"Private",146679,"Some-college",10,"Never-married","Exec-managerial","Own-child","Black","Male",0,0,30,"United-States","<=50K" +56,"Private",226985,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +38,"Private",153066,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States",">50K" +30,"?",159303,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,4,"United-States","<=50K" +18,"State-gov",109445,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +68,"Private",99491,"Some-college",10,"Widowed","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +35,"Private",172571,"Assoc-voc",11,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +42,"Private",143582,"7th-8th",4,"Married-civ-spouse","Other-service","Other-relative","Asian-Pac-Islander","Female",0,0,48,"?","<=50K" +32,"Private",207113,"10th",6,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +43,"Federal-gov",192712,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +30,"Private",154297,"10th",6,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",110402,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",207213,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",606111,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"Germany",">50K" +26,"Private",34112,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",119156,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,20,"United-States","<=50K" +19,"Private",249787,"HS-grad",9,"Never-married","Other-service","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",153516,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +25,"State-gov",260754,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",155621,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"Columbia","<=50K" +36,"Private",33983,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,42,"United-States",">50K" +23,"Private",306601,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"Mexico","<=50K" +24,"Private",270075,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,50,"United-States","<=50K" +23,"Private",109430,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",187115,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"United-States","<=50K" +25,"Self-emp-not-inc",463667,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,8,"United-States","<=50K" +24,"Private",52262,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",144064,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,62,"United-States","<=50K" +26,"Private",147821,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,45,"?","<=50K" +62,"?",232719,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",268620,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,33,"United-States","<=50K" +45,"Private",81132,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +34,"Private",242984,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +65,"Self-emp-inc",172684,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,44,"Mexico",">50K" +42,"Private",103932,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"State-gov",431637,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +40,"Private",188942,"Some-college",10,"Married-civ-spouse","Sales","Wife","Black","Female",0,0,40,"Puerto-Rico","<=50K" +53,"Federal-gov",170354,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Private",28518,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +30,"State-gov",193380,"Bachelors",13,"Never-married","Prof-specialty","Other-relative","White","Male",0,0,35,"United-States","<=50K" +59,"Private",175942,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +42,"Self-emp-not-inc",53956,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,55,"United-States","<=50K" +23,"Private",120773,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",96219,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,15,"United-States","<=50K" +20,"Private",104164,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",190429,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +73,"?",243030,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States","<=50K" +44,"Private",368757,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",220563,"12th",8,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",233571,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,37,"United-States",">50K" +39,"Private",187847,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,50,"United-States","<=50K" +44,"Self-emp-not-inc",254303,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +27,"Private",109611,"9th",5,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,37,"Portugal","<=50K" +50,"Private",189183,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",206951,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",282882,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +55,"Private",377061,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",209906,"1st-4th",2,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,35,"Puerto-Rico","<=50K" +53,"Local-gov",176059,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,50,"United-States","<=50K" +21,"Private",347292,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",277314,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +74,"?",29887,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +53,"Private",341439,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,60,"United-States",">50K" +60,"Private",114263,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"Hungary",">50K" +59,"Private",230899,"9th",5,"Separated","Machine-op-inspct","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +37,"Private",271767,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,48,"United-States",">50K" +49,"Private",39986,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +73,"Local-gov",45784,"Some-college",10,"Never-married","Prof-specialty","Other-relative","White","Female",0,0,11,"United-States","<=50K" +58,"Private",126991,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +18,"?",234648,"11th",7,"Never-married","?","Own-child","Black","Male",0,0,15,"United-States","<=50K" +35,"Private",207676,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +24,"State-gov",413345,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States","<=50K" +62,"Private",122033,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +58,"Private",169611,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +21,"Private",372636,"HS-grad",9,"Never-married","Sales","Own-child","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",340917,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",99844,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",0,0,45,"United-States","<=50K" +31,"Private",207685,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,34,"United-States","<=50K" +30,"Private",36069,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",100563,"HS-grad",9,"Never-married","Transport-moving","Own-child","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",174308,"11th",7,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",109413,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +59,"Local-gov",212600,"Some-college",10,"Separated","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States",">50K" +55,"Private",271710,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +70,"?",230816,"Assoc-voc",11,"Never-married","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +22,"Private",103277,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +42,"Private",318947,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",187167,"Assoc-acdm",12,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +32,"Private",204742,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",282062,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"?",283510,"HS-grad",9,"Never-married","?","Unmarried","Black","Male",0,0,45,"United-States","<=50K" +25,"Private",280093,"11th",7,"Married-spouse-absent","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +31,"Private",202729,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +33,"Private",205950,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",392286,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +42,"Self-emp-not-inc",119207,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +49,"Private",195554,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,44,"United-States","<=50K" +30,"Private",173005,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,44,"United-States","<=50K" +54,"Private",192862,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +39,"Private",164712,"Some-college",10,"Never-married","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +24,"Private",195808,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",199444,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,44,"United-States","<=50K" +23,"Private",126346,"9th",5,"Never-married","Other-service","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +54,"Private",177675,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,42,"United-States","<=50K" +23,"Private",50341,"Masters",14,"Never-married","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +23,"Private",126945,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +67,"?",92061,"HS-grad",9,"Widowed","?","Other-relative","White","Female",0,0,8,"United-States","<=50K" +19,"?",109938,"11th",7,"Married-civ-spouse","?","Wife","Asian-Pac-Islander","Female",0,0,40,"Laos","<=50K" +32,"Private",174704,"11th",7,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +57,"Private",124771,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",200603,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,30,"United-States","<=50K" +21,"Private",301199,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +53,"Private",215790,"Some-college",10,"Widowed","Adm-clerical","Other-relative","White","Female",0,0,22,"United-States","<=50K" +21,"Private",111467,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",82646,"Doctorate",16,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States",">50K" +24,"Private",162282,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Federal-gov",239074,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",214925,"Masters",14,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,60,"United-States","<=50K" +23,"Private",194247,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",211531,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Local-gov",223267,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States","<=50K" +25,"Private",201635,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +41,"Self-emp-not-inc",188738,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,27,"United-States","<=50K" +18,"Private",133055,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +29,"Private",109814,"Bachelors",13,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",225294,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",97277,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,65,"United-States",">50K" +52,"Private",146711,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",286452,"10th",6,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",20308,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Private",224203,"Some-college",10,"Widowed","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",225978,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",237720,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +31,"Private",156743,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,76,"United-States",">50K" +31,"Private",509364,"5th-6th",3,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"Mexico","<=50K" +46,"Private",144351,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",375515,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +57,"Self-emp-not-inc",103529,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,38,"United-States",">50K" +25,"Private",199472,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +32,"Private",348152,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",221166,"9th",5,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"?",634226,"10th",6,"Never-married","?","Own-child","White","Female",0,0,17,"United-States","<=50K" +43,"State-gov",159449,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",110238,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +19,"Private",458558,"HS-grad",9,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,40,"United-States","<=50K" +20,"Federal-gov",340217,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +42,"Private",155106,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +90,"Private",90523,"HS-grad",9,"Widowed","Transport-moving","Unmarried","White","Male",0,0,99,"United-States","<=50K" +25,"Private",122756,"11th",7,"Separated","Machine-op-inspct","Not-in-family","Black","Male",0,0,35,"United-States","<=50K" +27,"Private",293828,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"Jamaica","<=50K" +48,"Private",299291,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,44,"United-States","<=50K" +48,"Federal-gov",483261,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",122038,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +46,"Private",160647,"Bachelors",13,"Widowed","Tech-support","Unmarried","White","Female",0,0,38,"United-States","<=50K" +32,"Private",106541,"5th-6th",3,"Married-civ-spouse","Other-service","Other-relative","White","Male",0,0,40,"United-States","<=50K" +22,"Private",126945,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",188505,"Bachelors",13,"Married-AF-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +31,"Private",377850,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States","<=50K" +20,"Private",193586,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,18,"United-States","<=50K" +40,"Self-emp-inc",57233,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +39,"Private",195253,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Local-gov",172991,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Local-gov",223215,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,42,"United-States","<=50K" +17,"Private",95799,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,18,"United-States","<=50K" +25,"Self-emp-not-inc",213385,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,80,"United-States","<=50K" +49,"Local-gov",202467,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",147548,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +67,"Private",105216,"Some-college",10,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +28,"Private",77760,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Male",0,0,40,"United-States","<=50K" +35,"Private",167990,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Canada","<=50K" +44,"Private",167005,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,48,"United-States",">50K" +51,"Private",108435,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,47,"United-States",">50K" +55,"Private",56645,"Bachelors",13,"Widowed","Farming-fishing","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +45,"Local-gov",304973,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,78,"United-States",">50K" +32,"Private",42596,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +45,"Private",220641,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",188888,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States",">50K" +55,"Local-gov",168790,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,44,"United-States","<=50K" +59,"Private",98361,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",401762,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +46,"Local-gov",160187,"Masters",14,"Widowed","Exec-managerial","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +23,"Private",203715,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",144351,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +34,"Private",420749,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"Germany","<=50K" +51,"Private",106151,"11th",7,"Divorced","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",362482,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"State-gov",38151,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,12,"United-States","<=50K" +20,"Private",42706,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,72,"United-States","<=50K" +26,"Private",165510,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +35,"Local-gov",216068,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +23,"Private",215624,"Some-college",10,"Never-married","Machine-op-inspct","Unmarried","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +40,"Private",239708,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +49,"Local-gov",199378,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",230420,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +28,"Private",395022,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +62,"Private",210142,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Private",446358,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +47,"Local-gov",352614,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",293528,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Female",0,0,3,"United-States","<=50K" +44,"State-gov",55395,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"?",128538,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +46,"Private",428405,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",126838,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",136836,"Assoc-acdm",12,"Divorced","Transport-moving","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +48,"Private",105838,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Private",139903,"Bachelors",13,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-inc",106103,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,60,"United-States",">50K" +33,"Private",186824,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",350387,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +17,"Private",142912,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +63,"?",321403,"9th",5,"Separated","?","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +31,"Self-emp-inc",114937,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +20,"Private",451996,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",149833,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +24,"Private",211968,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +33,"Private",287908,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,50,"United-States",">50K" +36,"Private",166549,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",25216,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Private",162034,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +34,"Private",82938,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +23,"Private",122048,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Female",0,0,40,"United-States","<=50K" +33,"Private",118710,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"Private",243226,"10th",6,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +67,"Self-emp-not-inc",268514,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",365289,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",219266,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Own-child","White","Female",0,0,36,"?","<=50K" +24,"Private",283757,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,39,"United-States","<=50K" +44,"Federal-gov",206553,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",113364,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",328949,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +19,"Private",83930,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +20,"Private",131852,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +64,"Private",119506,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +47,"State-gov",100818,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +36,"Private",162302,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +48,"Private",182211,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States",">50K" +19,"Self-emp-not-inc",194205,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"Mexico","<=50K" +22,"Private",141040,"HS-grad",9,"Never-married","Sales","Own-child","Black","Female",0,0,35,"United-States","<=50K" +56,"Private",346033,"9th",5,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",177125,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +37,"Private",241174,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,99,"United-States",">50K" +57,"Local-gov",130532,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +38,"Private",168496,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Private",362787,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +22,"?",244771,"11th",7,"Separated","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +38,"Federal-gov",48123,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",207201,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +29,"Private",37933,"12th",8,"Married-spouse-absent","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +56,"Private",33323,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +71,"Local-gov",229110,"HS-grad",9,"Widowed","Exec-managerial","Other-relative","White","Female",0,0,33,"United-States","<=50K" +20,"Private",113511,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",333677,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,36,"United-States","<=50K" +42,"Private",236021,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?",">50K" +20,"?",371089,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +61,"Private",115023,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +24,"State-gov",133586,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +51,"Private",91137,"9th",5,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +27,"Private",105598,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",204829,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",247733,"HS-grad",9,"Divorced","Priv-house-serv","Unmarried","Black","Female",0,0,16,"United-States","<=50K" +36,"?",370585,"HS-grad",9,"Married-civ-spouse","?","Husband","Black","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",103257,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",178915,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Private",54260,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",55395,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",318331,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",195985,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",38876,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +67,"Self-emp-inc",81413,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",172618,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +61,"Private",423297,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Local-gov",88856,"7th-8th",4,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"?",169104,"Assoc-acdm",12,"Never-married","?","Own-child","Asian-Pac-Islander","Male",0,0,16,"Philippines","<=50K" +35,"Federal-gov",39207,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",340018,"10th",6,"Never-married","Other-service","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +20,"State-gov",30796,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +51,"Private",155403,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",238092,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Private",225605,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,24,"United-States","<=50K" +36,"Private",289148,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Private",339863,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +27,"Private",178778,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,80,"United-States",">50K" +29,"Private",568490,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"State-gov",129345,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",447882,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +24,"Private",314165,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,20,"United-States","<=50K" +39,"Federal-gov",382859,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +51,"State-gov",82504,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Private",209844,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,30,"United-States","<=50K" +49,"Private",62546,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",228686,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",326587,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",202091,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",310774,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",450246,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"?",84375,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,45,"United-States","<=50K" +43,"Private",142444,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,55,"United-States",">50K" +24,"Private",192766,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",53109,"11th",7,"Never-married","Other-service","Own-child","Amer-Indian-Eskimo","Male",0,0,20,"United-States","<=50K" +45,"Self-emp-inc",121836,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"?",">50K" +45,"Self-emp-not-inc",298130,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,25,"United-States","<=50K" +26,"Private",135645,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",265275,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"?",410114,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Without-pay",232719,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",167716,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,99,"United-States","<=50K" +68,"Private",107627,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,15,"United-States","<=50K" +21,"Private",129674,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,48,"Mexico","<=50K" +28,"Self-emp-inc",114053,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +46,"Private",202560,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +35,"Private",219902,"HS-grad",9,"Separated","Transport-moving","Unmarried","Black","Female",0,0,48,"United-States","<=50K" +50,"Self-emp-not-inc",192654,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +48,"Self-emp-inc",238966,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"?",112942,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",161874,"Some-college",10,"Never-married","Exec-managerial","Own-child","Black","Male",0,0,40,"United-States","<=50K" +53,"Private",260106,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +50,"Self-emp-inc",240374,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +32,"?",251612,"5th-6th",3,"Never-married","?","Unmarried","White","Female",0,0,45,"Mexico","<=50K" +53,"Private",223696,"12th",8,"Married-spouse-absent","Handlers-cleaners","Not-in-family","Other","Male",0,0,56,"Dominican-Republic","<=50K" +52,"Private",176134,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,48,"United-States","<=50K" +38,"Private",186959,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +43,"Private",456236,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +35,"Private",98948,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,32,"United-States","<=50K" +41,"Private",166662,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",448626,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Private",167482,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,60,"United-States",">50K" +45,"Private",189792,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",399052,"9th",5,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,0,42,"United-States","<=50K" +47,"Self-emp-not-inc",152752,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,20,"United-States","<=50K" +53,"Private",268545,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"Jamaica","<=50K" +53,"Self-emp-inc",148532,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +24,"Private",225724,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +34,"Private",200192,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Self-emp-inc",170850,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +29,"Federal-gov",224858,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States","<=50K" +61,"State-gov",159908,"11th",7,"Widowed","Other-service","Unmarried","White","Female",0,0,32,"United-States",">50K" +31,"Private",115488,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",1268339,"HS-grad",9,"Married-spouse-absent","Tech-support","Own-child","Black","Male",0,0,40,"United-States","<=50K" +42,"Private",195755,"HS-grad",9,"Separated","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +50,"Federal-gov",186272,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",181388,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",177181,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +74,"Private",91488,"1st-4th",2,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,20,"United-States","<=50K" +40,"Private",230961,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Local-gov",63042,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +36,"Private",29814,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"?",116230,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +42,"?",167678,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,22,"Ecuador","<=50K" +28,"Private",191088,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +19,"Private",63814,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,18,"United-States","<=50K" +36,"Private",285865,"Assoc-acdm",12,"Separated","Other-service","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +33,"?",160776,"Assoc-voc",11,"Divorced","?","Not-in-family","White","Female",0,0,40,"France","<=50K" +48,"Private",204990,"HS-grad",9,"Never-married","Tech-support","Unmarried","Black","Female",0,0,33,"Jamaica","<=50K" +60,"Self-emp-inc",171315,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",296462,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,30,"United-States","<=50K" +32,"Private",103860,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +51,"Private",96586,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",202720,"9th",5,"Married-spouse-absent","Machine-op-inspct","Unmarried","Black","Male",0,0,75,"Haiti","<=50K" +34,"Private",202822,"Masters",14,"Never-married","Tech-support","Unmarried","Black","Female",0,0,40,"?","<=50K" +48,"Self-emp-not-inc",379883,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Mexico",">50K" +68,"?",123464,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,45,"United-States","<=50K" +32,"Private",294121,"Assoc-acdm",12,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +63,"?",179981,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,4,"United-States","<=50K" +31,"Private",234387,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",154537,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +32,"Private",125856,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +32,"Private",156015,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",116632,"Bachelors",13,"Divorced","Sales","Own-child","White","Male",0,0,80,"United-States","<=50K" +38,"Self-emp-not-inc",115215,"10th",6,"Separated","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",254905,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",195532,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +63,"Private",181828,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"?","<=50K" +25,"Private",322585,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +59,"Private",246262,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Local-gov",211129,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"?","<=50K" +49,"Private",139268,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",188540,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"?",251167,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,30,"Mexico","<=50K" +46,"Private",94809,"Some-college",10,"Divorced","Priv-house-serv","Unmarried","White","Female",0,0,30,"United-States","<=50K" +37,"Local-gov",265038,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +48,"Private",182566,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States",">50K" +41,"Private",208470,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",233571,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,4,"United-States","<=50K" +29,"Private",24562,"Bachelors",13,"Divorced","Other-service","Unmarried","Other","Female",0,0,40,"United-States","<=50K" +59,"Private",168569,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +62,"Private",167098,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",271579,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +28,"Private",191355,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +42,"State-gov",83411,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +60,"Private",40856,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,46,"United-States",">50K" +58,"Private",115605,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",132326,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",220213,"HS-grad",9,"Widowed","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Private",172511,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",156745,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",218916,"Prof-school",15,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +21,"Private",306114,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +24,"Private",196675,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,70,"United-States","<=50K" +59,"Self-emp-not-inc",73411,"Prof-school",15,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +36,"Private",184659,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +72,"?",75890,"Some-college",10,"Widowed","?","Unmarried","Asian-Pac-Islander","Female",0,0,4,"United-States","<=50K" +35,"Private",320451,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,65,"Hong",">50K" +33,"Private",172498,"Some-college",10,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",131588,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Female",0,0,45,"United-States","<=50K" +40,"Private",124520,"Assoc-voc",11,"Divorced","Craft-repair","Unmarried","White","Male",0,0,50,"United-States",">50K" +26,"Self-emp-not-inc",93806,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +37,"Federal-gov",173192,"Assoc-voc",11,"Separated","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +68,"Self-emp-not-inc",198554,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +45,"Private",26502,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,72,"United-States",">50K" +56,"Private",225267,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",150042,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Private",208358,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",58115,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,41,"United-States","<=50K" +28,"Private",219267,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,28,"United-States","<=50K" +39,"Federal-gov",129573,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Local-gov",27834,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Self-emp-inc",415037,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,65,"United-States",">50K" +52,"Private",191529,"Bachelors",13,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +84,"Private",132806,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,13,"United-States","<=50K" +33,"Federal-gov",137059,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +30,"Private",164309,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +38,"Private",40955,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"England",">50K" +66,"Private",141085,"HS-grad",9,"Widowed","Priv-house-serv","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +62,"Federal-gov",258124,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Italy",">50K" +31,"Private",145139,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +60,"Self-emp-not-inc",146674,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","Black","Male",0,0,50,"?","<=50K" +27,"Private",242207,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"?",102541,"Assoc-voc",11,"Married-civ-spouse","?","Wife","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +38,"Private",135416,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",267284,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +48,"Private",130812,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",183765,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"?","<=50K" +45,"Local-gov",188823,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",200593,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Private",124094,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Poland","<=50K" +21,"Private",50411,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Local-gov",101689,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +21,"?",107801,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,6,"United-States","<=50K" +51,"Private",176969,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +30,"Private",342709,"HS-grad",9,"Married-spouse-absent","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-not-inc",368561,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",26915,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +57,"Private",157974,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,48,"United-States","<=50K" +33,"Private",183000,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,24,"United-States","<=50K" +18,"?",151463,"11th",7,"Never-married","?","Other-relative","White","Male",0,0,7,"United-States","<=50K" +28,"Private",217200,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +32,"Private",31740,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +56,"Private",35520,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +36,"Private",369843,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",199227,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +25,"Private",254781,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",70657,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +33,"Self-emp-not-inc",222162,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-inc",94606,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,60,"United-States",">50K" +44,"Self-emp-not-inc",104196,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,84,"United-States","<=50K" +30,"Self-emp-not-inc",455995,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States",">50K" +27,"Private",166210,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +25,"Private",198986,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States",">50K" +30,"Self-emp-inc",292465,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",99388,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +38,"Private",698363,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",154940,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",401998,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,20,"United-States","<=50K" +62,"Private",162825,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Self-emp-not-inc",271795,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",134671,"HS-grad",9,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",87583,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,14,"United-States","<=50K" +50,"Private",248619,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",130200,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +45,"Private",178922,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +23,"Private",51985,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +38,"State-gov",104280,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +27,"Private",617860,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",122112,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,50,"United-States","<=50K" +45,"Local-gov",181758,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",140117,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +27,"Private",107458,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Federal-gov",215948,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","Other","Male",0,0,40,"?","<=50K" +44,"Federal-gov",306440,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Federal-gov",615893,"Masters",14,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"Nicaragua","<=50K" +32,"Private",37210,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +43,"Private",196084,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +45,"Local-gov",166181,"HS-grad",9,"Divorced","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +24,"Private",232841,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +19,"?",131982,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",408788,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",181091,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",200246,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"Private",282023,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Federal-gov",128990,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",106838,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",144750,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,18,"United-States","<=50K" +39,"Private",108140,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",103323,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",268022,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States",">50K" +58,"Private",197114,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Local-gov",176118,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +24,"Private",42401,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,47,"United-States","<=50K" +53,"State-gov",123011,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +35,"Private",210945,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Local-gov",130620,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Asian-Pac-Islander","Female",0,0,40,"China",">50K" +26,"Private",248990,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +33,"Private",132705,"9th",5,"Separated","Adm-clerical","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +29,"Private",94892,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",141858,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",114561,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Other-relative","Asian-Pac-Islander","Female",0,0,36,"Philippines",">50K" +45,"Local-gov",191776,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",128354,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",37088,"9th",5,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +21,"Private",414812,"7th-8th",4,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +63,"?",156799,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,4,"United-States","<=50K" +41,"Self-emp-inc",73431,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"?",182386,"11th",7,"Divorced","?","Unmarried","White","Female",0,0,35,"United-States","<=50K" +33,"Local-gov",248346,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +37,"Private",167482,"10th",6,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +18,"?",171088,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Federal-gov",211763,"Doctorate",16,"Separated","Prof-specialty","Unmarried","Black","Female",0,0,24,"United-States",">50K" +20,"Private",122166,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",370119,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Self-emp-not-inc",138940,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +38,"Private",292307,"Bachelors",13,"Married-spouse-absent","Craft-repair","Not-in-family","Black","Male",0,0,40,"Dominican-Republic","<=50K" +47,"Self-emp-not-inc",248776,"Masters",14,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,25,"United-States","<=50K" +39,"Private",314007,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",76845,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,35,"United-States","<=50K" +24,"Private",148320,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",54261,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,84,"United-States","<=50K" +21,"Private",211013,"9th",5,"Never-married","Other-service","Own-child","White","Female",0,0,50,"Mexico","<=50K" +40,"Private",209833,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",356272,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +38,"Private",143538,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",242960,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Local-gov",263871,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +20,"Private",151105,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +45,"Self-emp-inc",84324,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",224716,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",186269,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",143731,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,72,"United-States",">50K" +39,"Private",236391,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"Private",54560,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",266325,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,32,"United-States",">50K" +45,"State-gov",183710,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +23,"Private",278254,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,45,"United-States","<=50K" +35,"Private",119992,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +52,"Private",284329,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +55,"Private",368727,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",353696,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",110931,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",169532,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +21,"Private",285522,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",198774,"Bachelors",13,"Divorced","Sales","Other-relative","White","Female",0,0,35,"United-States","<=50K" +32,"Private",123291,"12th",8,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Private",146110,"Some-college",10,"Widowed","Other-service","Unmarried","White","Female",0,0,24,"United-States","<=50K" +37,"Self-emp-not-inc",29814,"HS-grad",9,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,50,"United-States","<=50K" +61,"Private",195595,"7th-8th",4,"Married-spouse-absent","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"Guatemala","<=50K" +44,"Private",92649,"HS-grad",9,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,40,"United-States",">50K" +53,"Private",290688,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States",">50K" +43,"Private",427382,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +23,"Private",276568,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",250038,"Masters",14,"Married-civ-spouse","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +29,"Private",150861,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Private",87205,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,55,"England","<=50K" +47,"Private",343579,"1st-4th",2,"Married-spouse-absent","Farming-fishing","Not-in-family","White","Male",0,0,12,"Mexico","<=50K" +20,"Private",94401,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",205440,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",198996,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",294253,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,27,"United-States","<=50K" +23,"Private",256628,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,32,"United-States","<=50K" +59,"Self-emp-not-inc",223131,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +46,"Private",207301,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +66,"?",270460,"7th-8th",4,"Divorced","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Local-gov",125457,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,38,"United-States",">50K" +36,"Local-gov",212856,"11th",7,"Never-married","Other-service","Unmarried","White","Female",0,0,23,"United-States","<=50K" +44,"Private",197389,"HS-grad",9,"Married-spouse-absent","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +17,"Private",73338,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +27,"Private",68037,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +32,"Private",185027,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",107123,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +22,"Private",109482,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,98,"United-States","<=50K" +30,"Private",174543,"Assoc-acdm",12,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +68,"Self-emp-not-inc",211584,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",108540,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",202416,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"Private",176178,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +21,"Private",265148,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,38,"Jamaica","<=50K" +34,"Private",220631,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Male",0,0,50,"?","<=50K" +30,"Self-emp-not-inc",303692,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,75,"United-States","<=50K" +25,"Private",135845,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"State-gov",199915,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,21,"United-States","<=50K" +40,"State-gov",150533,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Other-relative","White","Male",0,0,40,"United-States","<=50K" +26,"Federal-gov",85482,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",24473,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",272944,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +43,"?",82077,"Some-college",10,"Divorced","?","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +49,"State-gov",194895,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +58,"Private",314153,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",176253,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +59,"Private",113959,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +42,"State-gov",167581,"Bachelors",13,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +37,"Private",79586,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Iran","<=50K" +47,"Private",72896,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Private",345730,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +30,"Private",302473,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +42,"Private",42346,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +21,"Private",243921,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",131620,"HS-grad",9,"Married-spouse-absent","Machine-op-inspct","Own-child","White","Female",0,0,40,"Dominican-Republic","<=50K" +47,"Private",158924,"HS-grad",9,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States","<=50K" +22,"Self-emp-not-inc",32921,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,20,"United-States","<=50K" +41,"Private",155657,"11th",7,"Never-married","Handlers-cleaners","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +43,"Federal-gov",155106,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,53,"United-States","<=50K" +60,"Private",82775,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +73,"Private",26248,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States",">50K" +90,"Private",88991,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"England",">50K" +62,"Federal-gov",125155,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,38,"United-States","<=50K" +28,"Private",218039,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",53524,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",259352,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +30,"Private",296453,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +19,"Private",278915,"12th",8,"Never-married","Handlers-cleaners","Own-child","Black","Female",0,0,52,"United-States","<=50K" +22,"Federal-gov",274103,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,10,"United-States","<=50K" +19,"Private",271118,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,28,"United-States","<=50K" +26,"Local-gov",138597,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +62,"Self-emp-not-inc",159939,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +61,"Private",110920,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Local-gov",163205,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,53,"United-States","<=50K" +56,"Private",110003,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",229051,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"?",144898,"Some-college",10,"Never-married","?","Unmarried","White","Male",0,0,40,"United-States","<=50K" +26,"Private",211596,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Self-emp-not-inc",136450,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States",">50K" +23,"Private",193586,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +23,"Private",91189,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",227832,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",271936,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +35,"Private",61343,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",157778,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,25,"United-States",">50K" +23,"Private",201680,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",228320,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States",">50K" +72,"Private",33404,"10th",6,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +21,"Private",103205,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",279029,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Private",213092,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",119124,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +65,"Private",31924,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +22,"Private",253799,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"?","<=50K" +52,"Private",266138,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"?",">50K" +65,"Private",185001,"10th",6,"Widowed","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +33,"Self-emp-not-inc",34102,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +27,"Private",289484,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"State-gov",287908,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,42,"United-States","<=50K" +53,"Self-emp-not-inc",158284,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States","<=50K" +23,"Private",60668,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Portugal","<=50K" +43,"State-gov",222978,"Doctorate",16,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States",">50K" +26,"Private",199143,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +60,"Private",131681,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Federal-gov",391122,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +29,"Local-gov",280344,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"State-gov",188809,"Doctorate",16,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +41,"Private",277488,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,36,"United-States","<=50K" +63,"Self-emp-not-inc",181561,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +31,"Private",158545,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,27,"United-States","<=50K" +23,"Private",313573,"Bachelors",13,"Never-married","Sales","Own-child","Black","Female",0,0,25,"United-States","<=50K" +31,"Private",591711,"Some-college",10,"Married-spouse-absent","Transport-moving","Not-in-family","Black","Male",0,0,40,"?","<=50K" +41,"Private",268183,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +51,"Private",392286,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Private",233312,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",520231,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +24,"Self-emp-not-inc",186831,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,45,"United-States","<=50K" +67,"Self-emp-not-inc",141085,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +65,"?",198019,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +47,"Local-gov",198660,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",409230,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Guatemala","<=50K" +38,"Private",376025,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",80167,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",82847,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,50,"Portugal",">50K" +24,"Private",22201,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","Asian-Pac-Islander","Male",0,0,40,"Thailand","<=50K" +19,"Private",117595,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,24,"United-States","<=50K" +32,"Private",207668,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +63,"Self-emp-not-inc",179981,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +18,"Private",192583,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +36,"Private",66304,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +57,"Private",32365,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",28497,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",160261,"Some-college",10,"Never-married","Exec-managerial","Own-child","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +48,"Private",120724,"12th",8,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"Private",91733,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,8,"United-States","<=50K" +74,"Self-emp-not-inc",146929,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +44,"Private",205706,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",181666,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +54,"Local-gov",279452,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",207568,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,48,"United-States",">50K" +18,"Private",210026,"10th",6,"Never-married","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +32,"Local-gov",190889,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Other","Female",0,0,40,"?","<=50K" +24,"Private",109869,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Self-emp-not-inc",285263,"9th",5,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"Mexico","<=50K" +28,"Private",192588,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",232945,"HS-grad",9,"Separated","Handlers-cleaners","Not-in-family","Other","Male",0,0,30,"United-States","<=50K" +49,"Local-gov",31339,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",305147,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Private",188914,"HS-grad",9,"Widowed","Machine-op-inspct","Other-relative","Black","Female",0,0,40,"Haiti","<=50K" +58,"Self-emp-not-inc",141165,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +68,"Self-emp-inc",136218,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,15,"United-States","<=50K" +41,"Federal-gov",371382,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +21,"?",199177,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",403671,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",193871,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Private",306183,"Some-college",10,"Divorced","Other-service","Own-child","White","Female",0,0,44,"United-States","<=50K" +54,"Private",124194,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",69847,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,30,"United-States","<=50K" +26,"State-gov",169323,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"State-gov",172327,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +39,"Private",186420,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",192779,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States",">50K" +41,"Private",105616,"Some-college",10,"Widowed","Adm-clerical","Unmarried","Black","Female",0,0,48,"United-States","<=50K" +57,"Private",160275,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",164507,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"Columbia","<=50K" +41,"Private",207578,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,50,"India",">50K" +55,"Private",314592,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +41,"?",254630,"Assoc-voc",11,"Divorced","?","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +22,"Private",112130,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",206280,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +57,"Private",308861,"Some-college",10,"Separated","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",206066,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +48,"Self-emp-not-inc",309895,"Some-college",10,"Divorced","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Local-gov",216129,"Some-college",10,"Married-spouse-absent","Exec-managerial","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +26,"State-gov",287420,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +24,"Private",163595,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",170092,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +42,"Private",59474,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",99151,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +37,"Private",206888,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +28,"Private",177119,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,80,"?","<=50K" +22,"Private",173736,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",182163,"11th",7,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"Germany","<=50K" +45,"Local-gov",311080,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Self-emp-not-inc",389857,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States",">50K" +23,"Private",297152,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,25,"United-States","<=50K" +24,"Federal-gov",130534,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",137301,"Assoc-acdm",12,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +58,"Private",316235,"HS-grad",9,"Divorced","Sales","Other-relative","White","Female",0,0,32,"United-States","<=50K" +28,"Self-emp-inc",32922,"Assoc-voc",11,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +58,"Private",118303,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,35,"United-States",">50K" +18,"Private",188241,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +59,"Private",236731,"7th-8th",4,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +39,"Private",209397,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +53,"Self-emp-inc",290640,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +54,"Private",221915,"Prof-school",15,"Never-married","Prof-specialty","Other-relative","White","Female",0,0,65,"United-States","<=50K" +51,"Private",175246,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +42,"State-gov",160369,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States",">50K" +36,"Private",461337,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +37,"Private",187311,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +32,"Private",29312,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",197365,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States","<=50K" +19,"Private",301747,"HS-grad",9,"Separated","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +55,"Local-gov",135439,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +30,"Private",340917,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",155057,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +65,"?",200749,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States","<=50K" +44,"Private",323627,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,5,"United-States","<=50K" +23,"?",154921,"5th-6th",3,"Never-married","?","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +32,"Private",131425,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +60,"Private",184242,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +28,"Private",149769,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Cambodia","<=50K" +44,"Private",124924,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Mexico","<=50K" +29,"Private",253003,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,16,"United-States","<=50K" +57,"State-gov",250976,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",104196,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +34,"Self-emp-not-inc",250182,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +44,"Private",188331,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,42,"United-States","<=50K" +44,"Private",187322,"Bachelors",13,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Private",130714,"1st-4th",2,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,22,"United-States","<=50K" +37,"Private",40955,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +35,"Private",107125,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,16,"United-States",">50K" +27,"Private",133937,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +28,"?",203260,"Bachelors",13,"Never-married","?","Not-in-family","White","Male",0,0,8,"United-States","<=50K" +37,"Self-emp-not-inc",143368,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +18,"Private",51789,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,8,"United-States","<=50K" +24,"State-gov",211049,"7th-8th",4,"Never-married","Tech-support","Unmarried","White","Female",0,0,20,"United-States","<=50K" +53,"Private",81794,"12th",8,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +54,"Private",150999,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +22,"Private",332657,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",240043,"10th",6,"Married-spouse-absent","Adm-clerical","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +43,"Private",186188,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"Iran","<=50K" +58,"State-gov",223400,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,20,"United-States",">50K" +59,"Local-gov",102442,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +31,"Private",236599,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +35,"Private",283237,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"Private",150106,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +45,"Private",102076,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,32,"United-States","<=50K" +40,"Private",374764,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",32528,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"Federal-gov",50053,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +58,"Private",212864,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",30673,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"United-States",">50K" +69,"?",248248,"1st-4th",2,"Married-civ-spouse","?","Husband","Asian-Pac-Islander","Male",0,0,34,"Philippines","<=50K" +23,"Private",419554,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,54,"United-States","<=50K" +32,"State-gov",177216,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Private",118158,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,44,"United-States","<=50K" +41,"Private",116391,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Germany","<=50K" +74,"Private",194312,"9th",5,"Widowed","Craft-repair","Not-in-family","White","Male",0,0,10,"?","<=50K" +43,"Private",111895,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Federal-gov",287988,"Bachelors",13,"Never-married","Armed-Forces","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +58,"Private",147653,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,32,"United-States","<=50K" +54,"Private",117674,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +60,"Private",187458,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",410351,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",207578,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +62,"?",55621,"Some-college",10,"Married-civ-spouse","?","Husband","Black","Male",0,0,35,"United-States",">50K" +27,"State-gov",271243,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Male",0,0,40,"Jamaica","<=50K" +30,"Private",188798,"Some-college",10,"Divorced","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +63,"Local-gov",168656,"Bachelors",13,"Divorced","Craft-repair","Not-in-family","Black","Male",0,0,35,"Outlying-US(Guam-USVI-etc)","<=50K" +34,"Private",241885,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +20,"?",133061,"9th",5,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",194097,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",219137,"10th",6,"Never-married","Other-service","Own-child","Black","Male",0,0,25,"United-States","<=50K" +50,"Private",31621,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",207685,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",109854,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"?",369678,"HS-grad",9,"Never-married","?","Not-in-family","Other","Male",0,0,43,"United-States","<=50K" +17,"Private",53611,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,6,"United-States","<=50K" +47,"Private",344916,"Assoc-acdm",12,"Divorced","Transport-moving","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +25,"Local-gov",198813,"Bachelors",13,"Never-married","Adm-clerical","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +71,"Private",180733,"Masters",14,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +21,"Private",188073,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +69,"?",159077,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,48,"United-States","<=50K" +48,"Private",174829,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",188736,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Other-relative","Other","Female",0,0,20,"Columbia","<=50K" +33,"Local-gov",222654,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,66,"?","<=50K" +56,"Private",251836,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"?","<=50K" +40,"Federal-gov",112388,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",209641,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +42,"Private",313945,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Ecuador","<=50K" +19,"?",134974,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +28,"Self-emp-inc",153291,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +40,"Private",353432,"10th",6,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +23,"Private",96635,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","Asian-Pac-Islander","Male",0,0,30,"United-States","<=50K" +46,"?",202560,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States",">50K" +39,"Private",150057,"Masters",14,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +45,"Private",132847,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"?",41356,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +50,"Self-emp-not-inc",93705,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",309350,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",123084,"11th",7,"Married-civ-spouse","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +55,"Private",174662,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,32,"United-States","<=50K" +62,"Federal-gov",177295,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",211880,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",454915,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",232475,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Self-emp-inc",244605,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +51,"Private",257337,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +37,"Private",116960,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +58,"Private",267663,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Mexico","<=50K" +39,"Private",47871,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States",">50K" +34,"Private",295922,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"England",">50K" +45,"Private",175625,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +19,"?",129586,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",202662,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Private",101436,"HS-grad",9,"Divorced","Adm-clerical","Other-relative","Amer-Indian-Eskimo","Female",0,0,35,"United-States","<=50K" +19,"?",119234,"Some-college",10,"Never-married","?","Other-relative","White","Female",0,0,15,"United-States","<=50K" +37,"Private",360743,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States",">50K" +60,"Local-gov",93272,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Private",145574,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",135785,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +23,"?",218415,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,10,"United-States","<=50K" +19,"Private",127709,"HS-grad",9,"Never-married","Farming-fishing","Own-child","Black","Male",0,0,30,"United-States","<=50K" +37,"Federal-gov",448337,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +58,"Private",310320,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",251521,"11th",7,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +39,"Private",255503,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +26,"Private",71009,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +22,"Private",174975,"Assoc-voc",11,"Never-married","Tech-support","Own-child","White","Female",0,0,36,"United-States","<=50K" +32,"Private",108023,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"Private",204018,"11th",7,"Never-married","Sales","Unmarried","White","Male",0,0,15,"United-States","<=50K" +57,"?",366563,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +68,"Private",121846,"7th-8th",4,"Widowed","Other-service","Unmarried","Amer-Indian-Eskimo","Female",0,0,20,"United-States","<=50K" +30,"Private",114691,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"State-gov",536725,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,15,"Japan","<=50K" +51,"Private",94432,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",286002,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,30,"Nicaragua","<=50K" +47,"Private",101684,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",231413,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",158846,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +41,"Local-gov",190786,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +25,"Private",306513,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +62,"Private",152148,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",309580,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"?",130832,"Bachelors",13,"Never-married","?","Unmarried","White","Female",0,0,10,"United-States","<=50K" +30,"Private",130078,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +48,"Private",39986,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",379198,"HS-grad",9,"Never-married","Other-service","Other-relative","Other","Male",0,0,40,"Mexico","<=50K" +51,"Private",189762,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,15,"United-States",">50K" +19,"Private",178147,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,10,"United-States","<=50K" +31,"Private",332379,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"?",262062,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",275446,"HS-grad",9,"Never-married","Sales","Own-child","Black","Male",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",278522,"11th",7,"Never-married","Farming-fishing","Own-child","Black","Male",0,0,40,"United-States","<=50K" +57,"Private",136107,"9th",5,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +18,"Private",205894,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,15,"United-States","<=50K" +54,"Private",210736,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",166634,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +52,"Private",185283,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",180553,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Private",199058,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"?","<=50K" +18,"Private",145005,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +37,"Self-emp-not-inc",184655,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +52,"Private",358554,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States",">50K" +59,"Private",307423,"9th",5,"Never-married","Other-service","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +27,"Private",472070,"Assoc-voc",11,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Federal-gov",115562,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Private",32446,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Self-emp-not-inc",33121,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,72,"United-States","<=50K" +37,"Private",183345,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +48,"Self-emp-not-inc",97883,"HS-grad",9,"Separated","Other-service","Other-relative","White","Female",0,0,25,"United-States","<=50K" +58,"Self-emp-not-inc",31732,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",206250,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +37,"Private",103323,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-inc",135436,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Private",376455,"Assoc-voc",11,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +52,"Private",160703,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,48,"United-States","<=50K" +30,"Private",131699,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",243842,"9th",5,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",349910,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +33,"Private",184306,"HS-grad",9,"Divorced","Handlers-cleaners","Unmarried","White","Male",0,0,30,"United-States","<=50K" +46,"Private",224202,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +64,"Private",151540,"11th",7,"Widowed","Tech-support","Unmarried","White","Female",0,0,16,"United-States","<=50K" +28,"Private",231197,"10th",6,"Married-spouse-absent","Craft-repair","Unmarried","White","Male",0,0,40,"Mexico","<=50K" +19,"Private",279968,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +36,"Private",162651,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Male",0,0,40,"Columbia","<=50K" +43,"Self-emp-not-inc",130126,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Self-emp-not-inc",160120,"Doctorate",16,"Divorced","Adm-clerical","Other-relative","Other","Male",0,0,40,"?","<=50K" +56,"Private",161662,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States",">50K" +24,"Local-gov",201664,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",137142,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +45,"Self-emp-inc",122206,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +56,"Local-gov",183169,"Masters",14,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",126513,"HS-grad",9,"Separated","Craft-repair","Unmarried","Black","Female",0,0,40,"?","<=50K" +35,"Federal-gov",185053,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",408427,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +50,"Self-emp-not-inc",198581,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +61,"Private",199198,"7th-8th",4,"Widowed","Other-service","Not-in-family","Black","Female",0,0,21,"United-States","<=50K" +63,"Private",172740,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",205153,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",164964,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",162606,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +24,"Private",179627,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",103408,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","Black","Male",0,0,40,"Germany",">50K" +27,"Private",36440,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",57512,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,48,"United-States","<=50K" +27,"Private",187981,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Private",393768,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",108726,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",180551,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +51,"Self-emp-not-inc",176240,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Private",70720,"12th",8,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",35890,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",283676,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",57916,"HS-grad",9,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",177974,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,70,"United-States","<=50K" +34,"?",177304,"10th",6,"Divorced","?","Not-in-family","White","Male",0,0,40,"Columbia","<=50K" +18,"Private",115839,"12th",8,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +38,"Private",117802,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,65,"United-States",">50K" +19,"Private",211355,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,12,"United-States","<=50K" +46,"Private",173243,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",343200,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +22,"Private",401690,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"Mexico","<=50K" +38,"Private",196123,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +83,"Self-emp-not-inc",213866,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Male",0,0,8,"United-States","<=50K" +34,"Private",55176,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",153976,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",119176,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",156550,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +25,"Private",109609,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +38,"Private",26698,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",236497,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +33,"State-gov",306309,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +17,"Private",242773,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +52,"Local-gov",43909,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +25,"Private",148300,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,15,"United-States","<=50K" +17,"Private",133449,"9th",5,"Never-married","Other-service","Own-child","Black","Male",0,0,26,"United-States","<=50K" +22,"Private",263670,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,80,"United-States","<=50K" +22,"Private",276494,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +58,"Private",317479,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +39,"Private",151248,"Some-college",10,"Divorced","Sales","Other-relative","White","Female",0,0,35,"United-States","<=50K" +59,"Local-gov",130532,"Some-college",10,"Widowed","Other-service","Not-in-family","White","Female",0,0,40,"Poland","<=50K" +61,"Private",160062,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",299635,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +50,"Private",171225,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +51,"Private",33304,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",95634,"Bachelors",13,"Married-civ-spouse","Other-service","Wife","Asian-Pac-Islander","Female",0,0,45,"?","<=50K" +20,"Private",243878,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Local-gov",181721,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States","<=50K" +44,"Federal-gov",201435,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +28,"Private",334032,"Assoc-voc",11,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +50,"Private",220019,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +53,"Private",71772,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +42,"Self-emp-not-inc",27661,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +47,"Private",191411,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,45,"India","<=50K" +39,"Private",123945,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +38,"Self-emp-not-inc",37778,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +34,"State-gov",171216,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,50,"United-States","<=50K" +40,"Private",93955,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +63,"Private",163809,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +53,"Private",346754,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +43,"Private",188436,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +68,"Private",186350,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,10,"United-States",">50K" +22,"?",214238,"7th-8th",4,"Never-married","?","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +46,"State-gov",394860,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States","<=50K" +57,"Private",262642,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +38,"Private",125550,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +66,"Private",192504,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",131310,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Private",172755,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",209993,"11th",7,"Separated","Priv-house-serv","Unmarried","White","Female",0,0,8,"Mexico","<=50K" +30,"Private",166961,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,37,"United-States","<=50K" +39,"Private",315291,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",284703,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +50,"Private",166565,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Self-emp-not-inc",173854,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +25,"Private",189219,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +24,"Private",210781,"Bachelors",13,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,40,"France","<=50K" +45,"Private",199832,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,15,"United-States","<=50K" +64,"Private",251292,"5th-6th",3,"Separated","Other-service","Other-relative","White","Female",0,0,20,"Cuba","<=50K" +61,"Private",122246,"12th",8,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +42,"Private",190767,"Assoc-voc",11,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",278736,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +53,"Private",124963,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",167476,"11th",7,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,7,"United-States","<=50K" +34,"Local-gov",246104,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States","<=50K" +41,"Private",171615,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,48,"United-States","<=50K" +46,"Private",177114,"Assoc-acdm",12,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,27,"United-States","<=50K" +32,"Private",146154,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +41,"Private",198196,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",79712,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Other","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",154785,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +33,"Private",182423,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +20,"?",347292,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,32,"United-States","<=50K" +34,"Private",118584,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",219835,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,30,"?","<=50K" +17,"?",148769,"HS-grad",9,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +45,"Private",197418,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +21,"Private",253190,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",192273,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",129573,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,41,"United-States","<=50K" +17,"Private",173807,"11th",7,"Never-married","Craft-repair","Own-child","White","Female",0,0,15,"United-States","<=50K" +35,"Private",217893,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +38,"Private",102938,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Local-gov",407495,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,56,"United-States",">50K" +25,"Private",50053,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"Japan","<=50K" +57,"Private",233382,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"Cuba","<=50K" +32,"Private",270968,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +39,"Local-gov",272166,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","Black","Male",0,0,30,"United-States","<=50K" +23,"Private",199915,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +21,"Private",305781,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,45,"United-States","<=50K" +47,"Private",107682,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,48,"United-States","<=50K" +25,"Private",188507,"7th-8th",4,"Never-married","Machine-op-inspct","Other-relative","White","Female",0,0,40,"Dominican-Republic","<=50K" +18,"?",28311,"11th",7,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +19,"Private",177839,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +24,"Private",77665,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +32,"Private",106742,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",192838,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +40,"Private",79531,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,75,"United-States",">50K" +21,"State-gov",337766,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +45,"Self-emp-not-inc",33234,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +17,"?",34088,"12th",8,"Never-married","?","Own-child","White","Female",0,0,25,"United-States","<=50K" +55,"Private",176904,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +42,"Private",172148,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +49,"Private",199058,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,38,"United-States","<=50K" +38,"Private",48093,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",143664,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",168337,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States",">50K" +43,"Private",195212,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,40,"?","<=50K" +39,"Private",230329,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Canada",">50K" +42,"Private",376072,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States","<=50K" +32,"Private",430175,"HS-grad",9,"Divorced","Craft-repair","Other-relative","Black","Female",0,0,50,"United-States","<=50K" +55,"Private",28735,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Amer-Indian-Eskimo","Female",0,0,45,"United-States","<=50K" +37,"Private",167482,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +59,"Private",113203,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Private",103948,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",310525,"12th",8,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,32,"United-States","<=50K" +35,"Private",105138,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",153489,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Male",0,0,40,"United-States","<=50K" +57,"State-gov",254949,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",118149,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",267965,"11th",7,"Never-married","Sales","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +43,"Private",50646,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States","<=50K" +33,"Private",147700,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,40,"United-States","<=50K" +18,"Private",446771,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,25,"United-States","<=50K" +47,"Private",168262,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +53,"Private",117058,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",140957,"Assoc-voc",11,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,35,"United-States",">50K" +35,"Private",186126,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"?","<=50K" +49,"Private",268234,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",485117,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",31350,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,60,"England","<=50K" +36,"State-gov",210830,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,30,"United-States","<=50K" +29,"Private",196420,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +52,"Private",172165,"10th",6,"Divorced","Other-service","Other-relative","White","Female",0,0,25,"United-States","<=50K" +50,"Self-emp-not-inc",186565,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +22,"Private",119359,"Bachelors",13,"Never-married","Exec-managerial","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",109684,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",169589,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Private",125421,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +31,"Private",500002,"1st-4th",2,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"Mexico","<=50K" +33,"Private",224141,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",113290,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,15,"United-States","<=50K" +62,"?",123992,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"?",37672,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +49,"Federal-gov",35406,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +22,"Private",199419,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +43,"Private",145441,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States",">50K" +58,"Private",238438,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,42,"United-States","<=50K" +21,"Private",56582,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,50,"United-States","<=50K" +67,"Local-gov",176931,"7th-8th",4,"Widowed","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +39,"Self-emp-not-inc",188571,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Federal-gov",312500,"Assoc-voc",11,"Divorced","Farming-fishing","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",278404,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",114225,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States",">50K" +18,"Private",184016,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +41,"Local-gov",183009,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States",">50K" +59,"Private",205759,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +23,"Private",462294,"Assoc-acdm",12,"Never-married","Other-service","Own-child","Black","Male",0,0,44,"United-States","<=50K" +42,"Private",102085,"HS-grad",9,"Divorced","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +54,"Self-emp-not-inc",83311,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States",">50K" +39,"Private",248694,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +57,"Local-gov",190747,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",162988,"10th",6,"Divorced","Other-service","Unmarried","White","Female",0,0,25,"United-States","<=50K" +31,"Self-emp-not-inc",156890,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",310380,"Some-college",10,"Married-spouse-absent","Adm-clerical","Own-child","Black","Female",0,0,45,"United-States","<=50K" +35,"Private",172186,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",311497,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-inc",443508,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +31,"Private",152156,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +46,"Private",155890,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +38,"State-gov",312528,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,37,"United-States","<=50K" +51,"Private",282744,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Canada","<=50K" +27,"Private",205145,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"?",119918,"Bachelors",13,"Never-married","?","Not-in-family","Black","Male",0,0,45,"?","<=50K" +22,"Private",401451,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States",">50K" +72,"?",173427,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Cuba","<=50K" +25,"Private",189027,"Bachelors",13,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",35551,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States",">50K" +23,"Private",42706,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +63,"Private",106910,"5th-6th",3,"Widowed","Other-service","Other-relative","Asian-Pac-Islander","Female",0,0,19,"Philippines","<=50K" +23,"Private",53245,"9th",5,"Separated","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +75,"Private",71898,"Preschool",1,"Never-married","Priv-house-serv","Not-in-family","Asian-Pac-Islander","Female",0,0,48,"Philippines","<=50K" +52,"Private",222107,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,50,"United-States","<=50K" +69,"Private",277588,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,10,"United-States","<=50K" +52,"Private",178983,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?",">50K" +40,"Federal-gov",391744,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +34,"Private",418020,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +21,"State-gov",39236,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +30,"Private",86808,"Bachelors",13,"Never-married","Prof-specialty","Other-relative","White","Female",0,0,40,"United-States","<=50K" +21,"Private",184756,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,16,"United-States","<=50K" +44,"Private",191256,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",101272,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +33,"State-gov",175023,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,37,"United-States","<=50K" +22,"Self-emp-not-inc",357612,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +23,"Private",82777,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"United-States","<=50K" +75,"Self-emp-not-inc",218521,"Some-college",10,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +55,"Private",179534,"11th",7,"Widowed","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"?",33339,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +31,"Private",198069,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,24,"United-States","<=50K" +49,"Private",236586,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Local-gov",167261,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Local-gov",251854,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +79,"?",163140,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Private",302579,"HS-grad",9,"Divorced","Other-service","Other-relative","Black","Female",0,0,30,"United-States","<=50K" +44,"Self-emp-inc",64632,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +24,"Private",83141,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-inc",326048,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",83471,"HS-grad",9,"Widowed","Other-service","Unmarried","Asian-Pac-Islander","Female",0,0,20,"United-States","<=50K" +23,"Private",170070,"12th",8,"Never-married","Other-service","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +25,"Private",207875,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +48,"Private",119722,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,8,"United-States","<=50K" +18,"Private",335665,"11th",7,"Never-married","Other-service","Other-relative","Black","Female",0,0,24,"United-States","<=50K" +25,"Private",212522,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +33,"Private",236396,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,35,"United-States","<=50K" +42,"Private",159911,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",133833,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",226947,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",174201,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",49707,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +33,"Private",201988,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +62,"Self-emp-not-inc",162347,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,15,"United-States",">50K" +30,"Private",182833,"Some-college",10,"Never-married","Exec-managerial","Own-child","Black","Female",0,0,40,"United-States","<=50K" +22,"Private",383603,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",70466,"Assoc-voc",11,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",184846,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,60,"United-States","<=50K" +25,"Private",176756,"Bachelors",13,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",112512,"HS-grad",9,"Widowed","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"Private",137296,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",37821,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,45,"United-States","<=50K" +25,"Private",295108,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +40,"Private",408717,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",255635,"9th",5,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,40,"Mexico","<=50K" +48,"Self-emp-not-inc",177783,"7th-8th",4,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +31,"Private",240283,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +36,"Private",410034,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +39,"Private",180667,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",196332,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +32,"Local-gov",159187,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +46,"Private",225065,"Preschool",1,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"Mexico","<=50K" +19,"Private",178147,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +30,"Private",272669,"Some-college",10,"Never-married","Tech-support","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +35,"Private",347491,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"?",146399,"Bachelors",13,"Never-married","?","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +33,"Private",75167,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +25,"Private",133373,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +64,"Local-gov",84737,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,35,"United-States",">50K" +18,"Private",96483,"HS-grad",9,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Female",0,0,20,"United-States","<=50K" +59,"Private",368005,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"State-gov",36032,"HS-grad",9,"Divorced","Protective-serv","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +30,"Private",174215,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +24,"Private",228772,"5th-6th",3,"Never-married","Machine-op-inspct","Other-relative","White","Female",0,0,40,"Mexico","<=50K" +22,"Private",242912,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +49,"Self-emp-inc",86701,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,56,"United-States",">50K" +35,"Private",166549,"12th",8,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",201613,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +35,"Private",29874,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",168138,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",162404,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,60,"United-States","<=50K" +21,"?",162160,"Some-college",10,"Never-married","?","Own-child","Asian-Pac-Islander","Male",0,0,40,"Taiwan","<=50K" +26,"Private",139116,"Some-college",10,"Never-married","Other-service","Own-child","Black","Female",0,0,50,"United-States","<=50K" +39,"Private",370585,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +40,"State-gov",151038,"Bachelors",13,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",271933,"Masters",14,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States","<=50K" +34,"Private",182401,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +66,"Private",234743,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",182140,"HS-grad",9,"Separated","Transport-moving","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",96459,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"?",205562,"Masters",14,"Never-married","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +47,"Private",188081,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +33,"State-gov",121245,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +18,"Private",127273,"11th",7,"Never-married","Other-service","Other-relative","White","Male",0,0,20,"United-States","<=50K" +22,"Private",341227,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +40,"Local-gov",166893,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States",">50K" +68,"?",65730,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States","<=50K" +45,"Self-emp-not-inc",285335,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,10,"United-States","<=50K" +23,"Private",177087,"11th",7,"Never-married","Adm-clerical","Unmarried","Black","Male",0,0,35,"United-States","<=50K" +40,"Private",240504,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +23,"Private",384651,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",189551,"HS-grad",9,"Divorced","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +53,"Private",194791,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +24,"Private",194630,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +53,"Private",177647,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",51620,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +34,"Private",251421,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",180477,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,47,"United-States","<=50K" +40,"State-gov",391736,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"State-gov",170091,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,6,"United-States","<=50K" +53,"Federal-gov",105788,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,50,"United-States",">50K" +42,"Local-gov",248476,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,65,"United-States",">50K" +32,"Private",168443,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +33,"Private",120201,"HS-grad",9,"Divorced","Adm-clerical","Own-child","Other","Female",0,0,65,"United-States","<=50K" +59,"Private",114678,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,60,"United-States","<=50K" +36,"Private",167440,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,44,"United-States","<=50K" +37,"Self-emp-not-inc",265266,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Cuba",">50K" +31,"Private",212235,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +46,"Private",44671,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"State-gov",87282,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",0,0,38,"United-States","<=50K" +29,"Self-emp-not-inc",322238,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",65382,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Self-emp-not-inc",115176,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,65,"United-States","<=50K" +48,"Self-emp-not-inc",162236,"Masters",14,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,40,"?",">50K" +42,"Private",409902,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +60,"Local-gov",204062,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States",">50K" +35,"Private",283305,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",435638,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-inc",114733,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,36,"United-States","<=50K" +22,"Private",162343,"Some-college",10,"Never-married","Adm-clerical","Other-relative","Black","Male",0,0,22,"United-States","<=50K" +18,"?",195981,"HS-grad",9,"Widowed","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Private",79531,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +44,"State-gov",395078,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",159567,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +49,"Private",133917,"Assoc-voc",11,"Never-married","Sales","Other-relative","Black","Male",0,0,40,"?","<=50K" +52,"Private",196894,"11th",7,"Separated","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +23,"Private",190290,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"Private",102828,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,49,"United-States","<=50K" +31,"Private",128493,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +30,"State-gov",290677,"Masters",14,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +21,"Private",283757,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Local-gov",169104,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +51,"Private",171409,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Self-emp-not-inc",319165,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",203182,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,30,"United-States","<=50K" +20,"?",211968,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,45,"United-States","<=50K" +26,"Private",166666,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +41,"Private",156566,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",140564,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Local-gov",322208,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +65,"Private",420277,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",123430,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,65,"Mexico","<=50K" +45,"Self-emp-inc",151584,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +37,"Self-emp-not-inc",348960,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +47,"Self-emp-inc",201699,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Private",511517,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",118001,"10th",6,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +38,"Private",193961,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +21,"Private",32732,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",223548,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Mexico","<=50K" +33,"Private",389932,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","Black","Male",0,0,55,"United-States","<=50K" +29,"Private",102345,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +41,"Private",107584,"Some-college",10,"Separated","Transport-moving","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +20,"?",34321,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +20,"State-gov",39478,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,54,"United-States","<=50K" +34,"Self-emp-not-inc",276221,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",235646,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",123306,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Private",38573,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",216889,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",386705,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,24,"United-States","<=50K" +47,"Self-emp-not-inc",249585,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +31,"Local-gov",47276,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,38,"United-States",">50K" +42,"Self-emp-not-inc",162758,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,56,"United-States",">50K" +46,"Local-gov",146497,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",190765,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +21,"Private",186314,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",213615,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",162322,"Assoc-voc",11,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +44,"State-gov",115932,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-not-inc",392694,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +38,"State-gov",143517,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-inc",123429,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"Italy",">50K" +53,"Private",254285,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",238311,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,36,"United-States",">50K" +49,"Private",281647,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +30,"Private",75167,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",252862,"Assoc-voc",11,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",199240,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,20,"England","<=50K" +43,"Private",145762,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Local-gov",142443,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +49,"Private",99361,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +36,"Private",105138,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +18,"Private",151866,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +60,"Private",297261,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +43,"Private",148998,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Private",143046,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Private",183850,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +31,"Private",198452,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"Private",161092,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",112497,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Self-emp-not-inc",155963,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +24,"Private",376393,"Assoc-voc",11,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"State-gov",151790,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +21,"Private",438139,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +20,"?",163911,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",214896,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +30,"Private",102821,"Some-college",10,"Married-civ-spouse","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +44,"Self-emp-not-inc",90021,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +45,"Private",77085,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Japan",">50K" +42,"Private",158555,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"?",28160,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",462255,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",144949,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",116207,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,32,"United-States","<=50K" +17,"Private",187308,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +45,"Local-gov",189890,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",185267,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",63434,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +45,"Private",1366120,"Assoc-voc",11,"Divorced","Other-service","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +33,"Private",129707,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,60,"United-States",">50K" +17,"?",181337,"10th",6,"Never-married","?","Own-child","Other","Female",0,0,20,"United-States","<=50K" +51,"Private",74784,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +33,"Private",44392,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +23,"Private",406641,"Some-college",10,"Never-married","Handlers-cleaners","Other-relative","White","Female",0,0,18,"United-States","<=50K" +52,"Private",89041,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States",">50K" +36,"?",139770,"Some-college",10,"Divorced","?","Own-child","White","Female",0,0,32,"United-States","<=50K" +25,"Private",180212,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +38,"?",338212,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"United-States","<=50K" +64,"Self-emp-not-inc",178472,"9th",5,"Separated","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +29,"Private",168470,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Local-gov",80485,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +38,"?",181705,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,24,"United-States","<=50K" +24,"Private",216867,"10th",6,"Never-married","Other-service","Other-relative","White","Male",0,0,30,"Mexico","<=50K" +43,"Federal-gov",214541,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",70034,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +18,"?",266287,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,25,"United-States","<=50K" +44,"Private",128485,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +81,"?",89015,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,18,"United-States","<=50K" +55,"Private",106740,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",167527,"11th",7,"Widowed","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",19302,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",210150,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Private",179824,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,36,"United-States","<=50K" +27,"Private",420351,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"State-gov",215443,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +33,"Private",215306,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"Cuba","<=50K" +39,"Private",108069,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",260046,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",31053,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +18,"Private",362302,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +54,"Private",87205,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +45,"Private",191703,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",242968,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"India",">50K" +23,"Local-gov",185575,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",73585,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +45,"Private",301802,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +32,"Self-emp-inc",108467,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +47,"Private",431245,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",157217,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",204935,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"Private",277112,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +30,"Local-gov",159773,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,45,"United-States",">50K" +51,"Private",118793,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,70,"United-States",">50K" +26,"State-gov",152457,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",266529,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Private",113756,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +48,"Private",83444,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,43,"United-States",">50K" +51,"?",146325,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,28,"United-States","<=50K" +29,"Private",198825,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +69,"Private",71489,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,25,"United-States","<=50K" +56,"Private",111218,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +26,"?",221626,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",352196,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,22,"United-States","<=50K" +41,"Federal-gov",355918,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",182615,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",211482,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +34,"Private",386370,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +46,"Local-gov",180010,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +46,"Without-pay",142210,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,25,"United-States","<=50K" +33,"Private",415706,"5th-6th",3,"Separated","Other-service","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +46,"Private",237731,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",343506,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +49,"Local-gov",116163,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,50,"France","<=50K" +66,"?",206560,"HS-grad",9,"Widowed","?","Not-in-family","Other","Female",0,0,35,"Puerto-Rico","<=50K" +35,"Private",301862,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",33429,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",169583,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +47,"Private",146497,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,16,"Germany","<=50K" +48,"Self-emp-not-inc",383384,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",240809,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,56,"United-States","<=50K" +38,"Private",203763,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",218785,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +17,"Private",244602,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +44,"State-gov",175696,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",101027,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +37,"Private",99270,"HS-grad",9,"Never-married","Transport-moving","Other-relative","White","Female",0,0,40,"United-States","<=50K" +49,"Private",224393,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +42,"Private",192381,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",131686,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +73,"?",84390,"Assoc-voc",11,"Married-spouse-absent","?","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +44,"Private",277533,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",72880,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"?",149646,"Some-college",10,"Divorced","?","Own-child","White","Female",0,0,20,"?","<=50K" +49,"Private",209057,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"Private",108909,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +42,"Private",74949,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",235639,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"State-gov",137421,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,0,37,"Hong","<=50K" +53,"Private",122412,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",434894,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",379959,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",225330,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,50,"Poland",">50K" +40,"Private",32627,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +28,"Private",65171,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",193380,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Private",184823,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",81259,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +35,"Private",301369,"12th",8,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +21,"Private",190968,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",330715,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Local-gov",77698,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +24,"Private",109053,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,25,"United-States","<=50K" +69,"Private",312653,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,25,"United-States","<=50K" +35,"Self-emp-not-inc",193260,"Masters",14,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,40,"?",">50K" +35,"Private",331831,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",163948,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",36228,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +49,"Private",160167,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",104196,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",288353,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",187693,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",114988,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Local-gov",117392,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Private",121124,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",195638,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"State-gov",216734,"Prof-school",15,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"?",197827,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",49156,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",126133,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +24,"Private",304463,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States","<=50K" +34,"Private",214288,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",274969,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Female",0,0,42,"United-States","<=50K" +23,"Private",189072,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Black","Female",0,0,45,"United-States","<=50K" +46,"Private",128047,"Some-college",10,"Separated","Sales","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +20,"Private",210338,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +63,"Private",122442,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",251421,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +24,"Federal-gov",219519,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",33355,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,45,"United-States","<=50K" +25,"Private",441210,"HS-grad",9,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"Local-gov",178356,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",231196,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +58,"State-gov",40925,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",270587,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,20,"England","<=50K" +27,"Private",114967,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",344492,"HS-grad",9,"Separated","Sales","Own-child","White","Female",0,0,26,"United-States","<=50K" +22,"Private",369387,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +80,"Self-emp-not-inc",101771,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,25,"United-States","<=50K" +52,"Private",137428,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +48,"Private",139290,"10th",6,"Separated","Machine-op-inspct","Own-child","White","Female",0,0,48,"United-States","<=50K" +62,"Private",199193,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,25,"United-States","<=50K" +32,"Private",286689,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,42,"United-States",">50K" +21,"?",123727,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +58,"Federal-gov",208640,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Self-emp-not-inc",120130,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +29,"Self-emp-inc",241431,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +25,"Private",120450,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",152240,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Private",200960,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Federal-gov",314310,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Local-gov",44566,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,80,"United-States","<=50K" +59,"Private",21792,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +36,"Private",182074,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",221850,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"Ecuador",">50K" +42,"Private",240628,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +34,"Private",318641,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,45,"United-States",">50K" +27,"Self-emp-not-inc",140863,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",129150,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States",">50K" +41,"Private",244945,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",138514,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",92008,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Female",0,0,28,"United-States","<=50K" +23,"Private",207415,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,15,"United-States","<=50K" +26,"Private",188626,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +27,"Private",133696,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,88,"United-States","<=50K" +21,"Private",195919,"10th",6,"Never-married","Handlers-cleaners","Not-in-family","Other","Male",0,0,40,"Dominican-Republic","<=50K" +41,"Private",119266,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",140474,"Assoc-acdm",12,"Divorced","Craft-repair","Own-child","Amer-Indian-Eskimo","Male",0,0,35,"United-States","<=50K" +25,"Private",69739,"10th",6,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",293176,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",217961,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,15,"United-States","<=50K" +23,"Private",419394,"Some-college",10,"Never-married","Sales","Own-child","Black","Male",0,0,9,"United-States","<=50K" +18,"Private",220836,"11th",7,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +37,"Private",334291,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +36,"Private",200360,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",203482,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",87867,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +55,"Private",123515,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",175935,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",229456,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,38,"United-States","<=50K" +42,"Local-gov",99554,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",190227,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +25,"Private",29020,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,45,"United-States","<=50K" +31,"Private",306459,"1st-4th",2,"Separated","Handlers-cleaners","Unmarried","White","Male",0,0,35,"Honduras","<=50K" +42,"Private",193995,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +26,"Private",105059,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +34,"Private",342709,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",53838,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Local-gov",209482,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +44,"Private",214242,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +47,"?",34458,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,10,"United-States","<=50K" +35,"Private",100375,"Some-college",10,"Married-spouse-absent","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Private",149949,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",189762,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +46,"Private",79874,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,53,"United-States",">50K" +66,"Self-emp-not-inc",104576,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,8,"United-States",">50K" +34,"State-gov",355700,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,20,"United-States","<=50K" +26,"Private",213625,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",204984,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",144593,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"?","<=50K" +23,"Private",217169,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +46,"Private",184883,"9th",5,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +44,"?",136419,"10th",6,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",57758,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,68,"United-States",">50K" +54,"Self-emp-not-inc",30908,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +71,"Private",217971,"9th",5,"Widowed","Sales","Unmarried","White","Female",0,0,13,"United-States","<=50K" +51,"Private",160703,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +32,"Private",142675,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Private",171242,"11th",7,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"Canada","<=50K" +34,"Private",376979,"9th",5,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",277530,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Private",104501,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",94041,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,44,"Ireland","<=50K" +37,"Local-gov",593246,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +19,"Private",121074,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,99,"United-States","<=50K" +64,"Private",192596,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +17,"Private",142457,"11th",7,"Never-married","Other-service","Own-child","Black","Male",0,0,20,"United-States","<=50K" +37,"Private",136028,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",157894,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,20,"United-States","<=50K" +18,"Private",252993,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"Columbia","<=50K" +42,"Private",219591,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,55,"United-States",">50K" +53,"Local-gov",205005,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,60,"United-States",">50K" +52,"Private",221936,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",120914,"10th",6,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +77,"Self-emp-inc",155761,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,8,"United-States","<=50K" +38,"Local-gov",236687,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",318036,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",53306,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +27,"Private",174645,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",321817,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Private",206948,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Federal-gov",402975,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",143486,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Self-emp-inc",27187,"Masters",14,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +24,"Private",187717,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",378104,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",113870,"1st-4th",2,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"?","<=50K" +24,"Private",326334,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +41,"Private",279914,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +29,"Private",320451,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +36,"Private",207853,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +78,"Self-emp-inc",237294,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Male",0,0,45,"United-States",">50K" +34,"State-gov",259705,"Some-college",10,"Separated","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"?",117789,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +24,"Private",449432,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Federal-gov",89083,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",59612,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States","<=50K" +21,"Private",129980,"9th",5,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",108233,"Assoc-acdm",12,"Separated","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +30,"Private",342709,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",126675,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",141118,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",173243,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Local-gov",161092,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",209691,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,42,"United-States",">50K" +36,"Private",89508,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Private",399522,"11th",7,"Married-spouse-absent","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +60,"State-gov",136939,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Local-gov",264436,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"Private",199572,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Federal-gov",28291,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +50,"Private",215990,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Self-emp-not-inc",179594,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States","<=50K" +26,"Private",182308,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",51662,"11th",7,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +45,"Private",289468,"11th",7,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",201954,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,65,"United-States",">50K" +45,"Self-emp-not-inc",26781,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +58,"Private",100960,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",213811,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +49,"Private",124672,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",219300,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +22,"Private",270436,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",212619,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",84136,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,25,"United-States","<=50K" +55,"Federal-gov",264834,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"State-gov",98995,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",278254,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +28,"Private",167987,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Federal-gov",72887,"Bachelors",13,"Married-spouse-absent","Tech-support","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +17,"Private",176467,"9th",5,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +51,"Self-emp-not-inc",85902,"10th",6,"Widowed","Transport-moving","Other-relative","White","Female",0,0,40,"United-States","<=50K" +37,"Private",223433,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Self-emp-inc",108435,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",172496,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +35,"Private",241998,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",187513,"Assoc-voc",11,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",440138,"HS-grad",9,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,45,"England","<=50K" +24,"Private",218215,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +34,"Private",94413,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",183598,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",192664,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",392812,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +21,"Private",155818,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +32,"Private",195000,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",308205,"5th-6th",3,"Never-married","Farming-fishing","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +53,"Private",104879,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",152307,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",145964,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",97419,"HS-grad",9,"Married-civ-spouse","Protective-serv","Wife","Black","Female",0,0,40,"United-States","<=50K" +25,"?",12285,"Some-college",10,"Never-married","?","Not-in-family","Amer-Indian-Eskimo","Female",0,0,20,"United-States","<=50K" +30,"Private",263150,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,20,"United-States","<=50K" +49,"?",189885,"HS-grad",9,"Widowed","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",151888,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",254167,"10th",6,"Separated","Transport-moving","Own-child","White","Male",0,0,35,"United-States","<=50K" +45,"Local-gov",331482,"Assoc-acdm",12,"Divorced","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +61,"Local-gov",177189,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,42,"United-States","<=50K" +35,"Private",186886,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,55,"United-States","<=50K" +20,"Private",33221,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +27,"Private",188171,"10th",6,"Never-married","Adm-clerical","Own-child","White","Male",0,0,60,"United-States","<=50K" +23,"Private",209770,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",164488,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?","<=50K" +65,"Local-gov",180869,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +25,"Private",190350,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +45,"Private",204057,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"Germany","<=50K" +67,"Private",134906,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +40,"Private",174515,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +51,"Private",259363,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +35,"Private",209609,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +28,"Private",185127,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",462838,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +37,"Private",176967,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +54,"Private",284129,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +33,"Federal-gov",37546,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +46,"Private",116666,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Private",423222,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +51,"Private",201127,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +27,"Private",202239,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",209629,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",133520,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +66,"?",99888,"Assoc-voc",11,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",176410,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,38,"United-States","<=50K" +35,"Federal-gov",103214,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","Amer-Indian-Eskimo","Female",0,0,60,"United-States",">50K" +50,"Private",226735,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,70,"United-States",">50K" +43,"Self-emp-inc",151089,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +21,"Private",244312,"9th",5,"Never-married","Craft-repair","Own-child","White","Male",0,0,30,"El-Salvador","<=50K" +33,"Private",209317,"9th",5,"Never-married","Other-service","Not-in-family","White","Male",0,0,45,"El-Salvador","<=50K" +22,"Private",374116,"HS-grad",9,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,36,"United-States","<=50K" +29,"Private",205249,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Japan","<=50K" +42,"Self-emp-not-inc",326083,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",183523,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"Hungary","<=50K" +36,"Private",350783,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +66,"Local-gov",140849,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +44,"Private",175943,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,20,"United-States","<=50K" +45,"Local-gov",125933,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +49,"Private",225124,"HS-grad",9,"Divorced","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",272090,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,45,"El-Salvador","<=50K" +48,"Private",40666,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,60,"United-States","<=50K" +19,"Private",35245,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",167482,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",204662,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +32,"Private",291147,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +49,"Private",179869,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Self-emp-not-inc",205100,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +20,"Private",352139,"Some-college",10,"Divorced","Other-service","Own-child","White","Female",0,0,29,"United-States","<=50K" +39,"Private",111268,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Private",247111,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",271446,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +29,"Local-gov",132412,"Bachelors",13,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Self-emp-inc",74712,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +22,"Private",94662,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +44,"Self-emp-inc",33126,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,80,"United-States","<=50K" +43,"Private",133584,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +63,"?",64448,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",374367,"Assoc-voc",11,"Separated","Sales","Not-in-family","Black","Male",0,0,44,"United-States","<=50K" +40,"Private",179666,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,30,"Canada","<=50K" +18,"Private",99219,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +57,"Self-emp-inc",180211,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,50,"Taiwan",">50K" +54,"Local-gov",219276,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +44,"Private",150011,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",231231,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +40,"Private",182217,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"Scotland","<=50K" +29,"Private",277342,"Some-college",10,"Never-married","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +22,"Private",140001,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",223319,"Some-college",10,"Divorced","Sales","Own-child","White","Male",0,0,45,"United-States","<=50K" +52,"Private",235307,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Local-gov",156003,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",529223,"Bachelors",13,"Never-married","Sales","Own-child","Black","Male",0,0,10,"United-States","<=50K" +22,"Private",202871,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,44,"United-States","<=50K" +37,"Private",58337,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +58,"Federal-gov",298643,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +61,"Private",191188,"10th",6,"Widowed","Farming-fishing","Unmarried","White","Male",0,0,20,"United-States","<=50K" +30,"Private",96287,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +23,"Private",104443,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +30,"Private",323054,"10th",6,"Divorced","Other-service","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +18,"Private",95917,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,25,"Canada","<=50K" +23,"Private",49296,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",50953,"Some-college",10,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,10,"United-States","<=50K" +57,"Private",124507,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +58,"Private",239523,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +59,"Self-emp-not-inc",309124,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",240172,"Bachelors",13,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",105010,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States",">50K" +44,"Local-gov",135056,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,16,"?","<=50K" +25,"Private",178478,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +33,"Private",23871,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +22,"Private",362309,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +50,"Private",297906,"Some-college",10,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,50,"United-States",">50K" +44,"Private",230684,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +53,"?",123011,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",170866,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +54,"Local-gov",182543,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +60,"Self-emp-not-inc",236470,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",33725,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +43,"Private",206878,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,60,"United-States","<=50K" +33,"Local-gov",173806,"Assoc-acdm",12,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",190709,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States","<=50K" +41,"Private",149102,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"Poland","<=50K" +21,"Private",25265,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Private",100669,"Some-college",10,"Married-civ-spouse","Craft-repair","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +27,"Self-emp-inc",114158,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Private",228057,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",54012,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Federal-gov",219967,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Private",239865,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"State-gov",119421,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,35,"United-States",">50K" +56,"Self-emp-not-inc",220187,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,45,"United-States",">50K" +42,"Private",175515,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Local-gov",271795,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",70055,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",352806,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +57,"Private",266189,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,42,"United-States","<=50K" +49,"Private",102945,"7th-8th",4,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",173851,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Private",144092,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",198681,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,70,"United-States",">50K" +33,"Private",351810,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"Mexico","<=50K" +52,"Private",180142,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States","<=50K" +37,"Self-emp-inc",175360,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Self-emp-inc",224498,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Self-emp-inc",154641,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,60,"United-States","<=50K" +54,"Local-gov",152540,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,42,"United-States","<=50K" +52,"Private",217663,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +22,"Local-gov",138575,"HS-grad",9,"Never-married","Protective-serv","Unmarried","White","Male",0,0,56,"United-States","<=50K" +19,"?",32477,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +32,"Private",44677,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",456618,"7th-8th",4,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"El-Salvador","<=50K" +34,"Private",227282,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",27624,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +24,"Private",281403,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,98,"United-States","<=50K" +48,"Private",377140,"5th-6th",3,"Never-married","Priv-house-serv","Unmarried","White","Female",0,0,35,"Nicaragua","<=50K" +26,"Private",299810,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +28,"Private",181916,"Some-college",10,"Separated","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",237044,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,12,"United-States","<=50K" +64,"State-gov",269512,"Bachelors",13,"Divorced","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",44767,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,50,"United-States",">50K" +28,"Private",67218,"7th-8th",4,"Married-civ-spouse","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +34,"Private",176992,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",379919,"Assoc-acdm",12,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +18,"Private",212370,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,25,"United-States","<=50K" +36,"Private",179666,"12th",8,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,40,"United-States","<=50K" +24,"Private",197387,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"Mexico","<=50K" +29,"Local-gov",220656,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +33,"Private",181091,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Federal-gov",135028,"HS-grad",9,"Separated","Adm-clerical","Other-relative","Black","Female",0,0,35,"United-States","<=50K" +41,"Private",185057,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"?","<=50K" +55,"Private",106498,"10th",6,"Widowed","Transport-moving","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +21,"Private",203003,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",223789,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +26,"Private",184026,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Other","Male",0,0,50,"United-States","<=50K" +32,"?",335427,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"United-States",">50K" +32,"Private",372692,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",45607,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",212895,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +58,"Private",147989,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",145290,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +31,"Private",132601,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",30759,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +19,"Private",319889,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +66,"Private",29431,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Private",111483,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"Private",184756,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +30,"Private",187560,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",84848,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +75,"?",36243,"Doctorate",16,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"State-gov",88913,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","Asian-Pac-Islander","Female",0,0,36,"United-States","<=50K" +19,"Private",73190,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +60,"Private",132529,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",214542,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",217006,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",169785,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +30,"Private",75573,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"Germany","<=50K" +37,"Private",239171,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Self-emp-not-inc",53566,"Doctorate",16,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +20,"Private",117109,"Some-college",10,"Never-married","Adm-clerical","Other-relative","Black","Female",0,0,24,"United-States","<=50K" +32,"Private",398019,"7th-8th",4,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,15,"Mexico","<=50K" +18,"Private",114008,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +24,"Private",204653,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Local-gov",254935,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,45,"United-States","<=50K" +76,"?",84755,"Some-college",10,"Widowed","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +57,"Local-gov",198145,"Masters",14,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,14,"United-States",">50K" +19,"Private",451951,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Local-gov",172175,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",209472,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +40,"Private",336707,"Assoc-voc",11,"Separated","Craft-repair","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +26,"?",431861,"10th",6,"Separated","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-inc",156728,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +39,"Federal-gov",290321,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +49,"State-gov",206577,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",149324,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,7,"United-States","<=50K" +33,"?",49593,"Some-college",10,"Married-civ-spouse","?","Wife","Black","Female",0,0,30,"United-States","<=50K" +28,"Private",181659,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,50,"United-States","<=50K" +30,"Private",174789,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",184801,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",176014,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +50,"Private",256861,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,80,"United-States","<=50K" +37,"Private",239397,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +26,"Private",233777,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Private",236520,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",70754,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",245378,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +26,"Private",176729,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States",">50K" +19,"Private",517036,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,40,"El-Salvador","<=50K" +38,"Private",436361,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,75,"United-States","<=50K" +38,"Private",231037,"5th-6th",3,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Mexico","<=50K" +65,"Private",209831,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +48,"?",167381,"HS-grad",9,"Widowed","?","Unmarried","White","Female",0,0,25,"United-States","<=50K" +44,"Private",215468,"Bachelors",13,"Separated","Machine-op-inspct","Unmarried","Black","Female",0,0,7,"United-States","<=50K" +32,"Private",200700,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Local-gov",191777,"HS-grad",9,"Never-married","Protective-serv","Own-child","Black","Female",0,0,40,"United-States","<=50K" +49,"Federal-gov",195437,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,60,"United-States",">50K" +23,"Private",149396,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +25,"Private",104746,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,16,"United-States","<=50K" +19,"Private",108147,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +27,"Private",238859,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"State-gov",23157,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +38,"Private",497788,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +42,"Private",141558,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +33,"Federal-gov",117963,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,38,"United-States","<=50K" +30,"Private",232356,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",157941,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",103642,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",169727,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",274731,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",161572,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,45,"United-States","<=50K" +38,"Private",48779,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",141511,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",168334,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,30,"United-States","<=50K" +42,"Local-gov",267252,"Masters",14,"Separated","Exec-managerial","Unmarried","Black","Male",0,0,45,"United-States",">50K" +31,"Self-emp-not-inc",312055,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +32,"Private",207937,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",232653,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Private",246841,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",154087,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",199011,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,12,"United-States","<=50K" +51,"Self-emp-not-inc",205100,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,30,"United-States",">50K" +24,"Private",50400,"Some-college",10,"Married-civ-spouse","Sales","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",97064,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,44,"United-States","<=50K" +21,"Private",65038,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"Private",225211,"9th",5,"Never-married","Other-service","Own-child","Black","Male",0,0,35,"United-States","<=50K" +45,"Private",320192,"1st-4th",2,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +21,"Private",83580,"Some-college",10,"Never-married","Prof-specialty","Own-child","Amer-Indian-Eskimo","Female",0,0,4,"United-States","<=50K" +42,"Private",529216,"HS-grad",9,"Separated","Transport-moving","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +22,"Private",390817,"5th-6th",3,"Married-civ-spouse","Craft-repair","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +21,"?",85733,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +59,"Private",155976,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",221172,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +45,"Private",270842,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",82622,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +58,"Private",371064,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,20,"United-States","<=50K" +29,"Private",22641,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Amer-Indian-Eskimo","Male",0,0,45,"United-States","<=50K" +21,"Private",218957,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,45,"United-States","<=50K" +51,"Private",441637,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",143699,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +40,"Private",183096,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +45,"Private",97176,"11th",7,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,16,"United-States","<=50K" +22,"Private",311376,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +62,"Private",123582,"10th",6,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Federal-gov",174215,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +36,"Private",183902,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,4,"United-States",">50K" +43,"Private",247880,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",256636,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"?",152875,"Bachelors",13,"Married-civ-spouse","?","Wife","Asian-Pac-Islander","Female",0,0,40,"China","<=50K" +28,"Private",22422,"HS-grad",9,"Never-married","Transport-moving","Unmarried","White","Male",0,0,55,"United-States","<=50K" +49,"?",178215,"Some-college",10,"Widowed","?","Unmarried","White","Female",0,0,28,"United-States","<=50K" +47,"Local-gov",194360,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,7,"United-States",">50K" +59,"Private",247187,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",63921,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",224889,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",178564,"Bachelors",13,"Never-married","Prof-specialty","Other-relative","White","Male",0,0,40,"United-States","<=50K" +57,"Private",47619,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",92775,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +37,"Private",50837,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +20,"Local-gov",235894,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Private",244974,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +20,"Local-gov",526734,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +38,"Self-emp-not-inc",243484,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,28,"United-States",">50K" +23,"Private",201664,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Other-relative","White","Male",0,0,40,"United-States","<=50K" +24,"Private",234640,"HS-grad",9,"Married-spouse-absent","Sales","Own-child","White","Female",0,0,36,"United-States","<=50K" +46,"Private",268022,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Local-gov",223267,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Self-emp-not-inc",99199,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",137076,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",313146,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",271807,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",191196,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",264627,"11th",7,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,84,"United-States","<=50K" +32,"Private",183801,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",209227,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,21,"United-States","<=50K" +64,"Private",216208,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",377095,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +44,"Private",317535,"1st-4th",2,"Married-civ-spouse","Protective-serv","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +40,"Private",247880,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",152246,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +23,"Private",428299,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",161708,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +19,"Private",167859,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +61,"Private",85194,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,25,"United-States","<=50K" +47,"Self-emp-inc",119471,"7th-8th",4,"Never-married","Craft-repair","Not-in-family","Other","Male",0,0,40,"?","<=50K" +39,"Private",117683,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"Private",427744,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",122116,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +34,"State-gov",227931,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +54,"Self-emp-not-inc",226497,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Private",83783,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"Private",197113,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Other","Male",0,0,50,"Puerto-Rico","<=50K" +33,"Private",204742,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States","<=50K" +63,"?",331527,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,14,"United-States","<=50K" +31,"Private",213179,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +70,"Self-emp-inc",188260,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,16,"United-States","<=50K" +43,"Private",298161,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"Nicaragua","<=50K" +36,"Private",143774,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,12,"United-States",">50K" +50,"Local-gov",139296,"11th",7,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +21,"Private",152389,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Female",0,0,30,"United-States","<=50K" +31,"Private",309974,"Some-college",10,"Separated","Tech-support","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +19,"?",37085,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +39,"Private",270059,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +29,"Private",130045,"7th-8th",4,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +39,"Private",188038,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"Private",168203,"7th-8th",4,"Never-married","Farming-fishing","Other-relative","Other","Male",0,0,40,"Mexico","<=50K" +46,"Private",171807,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +62,"Private",186696,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",177531,"10th",6,"Divorced","Other-service","Unmarried","Black","Female",0,0,23,"United-States","<=50K" +28,"Private",115464,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",501144,"Some-college",10,"Never-married","Sales","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",205894,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,25,"?","<=50K" +24,"Local-gov",203924,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,45,"United-States","<=50K" +38,"Private",91857,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,41,"United-States","<=50K" +38,"Private",229700,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States",">50K" +17,"Private",158704,"10th",6,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +28,"Private",190911,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",139176,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,8,"United-States","<=50K" +19,"Private",168693,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +26,"Private",250038,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Self-emp-inc",353927,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",230248,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +43,"Private",117728,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +52,"Private",115851,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Private",193335,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",203894,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +55,"State-gov",157639,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Self-emp-inc",235320,"Masters",14,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States",">50K" +36,"Private",127686,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,37,"United-States","<=50K" +39,"Private",28572,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,48,"United-States","<=50K" +78,"?",91534,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,3,"United-States","<=50K" +30,"Private",184687,"HS-grad",9,"Never-married","Prof-specialty","Own-child","White","Female",0,0,30,"United-States","<=50K" +22,"Private",267945,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,16,"United-States","<=50K" +43,"Private",131899,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",192614,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +36,"Private",186808,"Bachelors",13,"Married-civ-spouse","Craft-repair","Own-child","White","Male",0,0,40,"United-States",">50K" +50,"Private",44116,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Federal-gov",46442,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +46,"Federal-gov",78022,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",417668,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +41,"Private",223763,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +68,"Private",223851,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,24,"United-States","<=50K" +38,"Local-gov",115634,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",114459,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",197093,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Male",0,0,20,"United-States","<=50K" +31,"Self-emp-not-inc",357145,"Doctorate",16,"Never-married","Prof-specialty","Own-child","White","Female",0,0,48,"United-States","<=50K" +29,"Private",59231,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,42,"United-States","<=50K" +26,"Private",292303,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Private",122288,"Some-college",10,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,36,"United-States","<=50K" +26,"Federal-gov",52322,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Other","Male",0,0,60,"United-States","<=50K" +27,"Local-gov",105830,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +36,"Private",107125,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"Federal-gov",281860,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Private",283320,"Bachelors",13,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"State-gov",26598,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",220783,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +21,"?",121694,"7th-8th",4,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +53,"Private",208302,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,34,"United-States","<=50K" +34,"Local-gov",172664,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",54611,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +64,"Private",631947,"10th",6,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",394484,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"?",239120,"Bachelors",13,"Never-married","?","Not-in-family","White","Male",0,0,13,"United-States","<=50K" +47,"Local-gov",193012,"Masters",14,"Divorced","Protective-serv","Not-in-family","Black","Male",0,0,50,"United-States",">50K" +57,"Private",84888,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +37,"Private",188503,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +37,"Private",337778,"11th",7,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",94432,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,55,"United-States",">50K" +32,"Private",168906,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Private",116143,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",128272,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,14,"United-States","<=50K" +46,"Private",174995,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +24,"State-gov",289909,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",154641,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +30,"Private",203488,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +34,"Private",141118,"Masters",14,"Divorced","Prof-specialty","Own-child","White","Female",0,0,60,"United-States",">50K" +30,"Private",169589,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",137645,"Bachelors",13,"Never-married","Sales","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +58,"Local-gov",489085,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",36302,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States","<=50K" +37,"Private",253420,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +35,"Private",269300,"HS-grad",9,"Separated","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",282609,"5th-6th",3,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,30,"Honduras","<=50K" +46,"Private",346978,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",205051,"10th",6,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Private",128736,"10th",6,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",236110,"12th",8,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Cuba",">50K" +38,"Private",312271,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Private",126978,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","Asian-Pac-Islander","Female",0,0,40,"China","<=50K" +47,"Private",204692,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",195956,"Bachelors",13,"Divorced","Tech-support","Unmarried","White","Female",0,0,35,"United-States","<=50K" +59,"State-gov",202682,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",231912,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,37,"United-States","<=50K" +44,"Local-gov",24982,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +76,"Private",278938,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +50,"Local-gov",36489,"10th",6,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Local-gov",154874,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",74581,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +37,"Self-emp-inc",162164,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",239708,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +49,"Self-emp-not-inc",162856,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-inc",85109,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +22,"Private",436798,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",345363,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"England","<=50K" +36,"Private",49837,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"?",296516,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"State-gov",180283,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +40,"Local-gov",95639,"HS-grad",9,"Never-married","Craft-repair","Other-relative","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +42,"Private",33155,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +56,"Private",329059,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Italy",">50K" +55,"Private",24694,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",443855,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +52,"?",294691,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",301867,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,35,"United-States","<=50K" +47,"Private",362835,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +23,"Private",180339,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Female",0,0,65,"United-States","<=50K" +55,"Self-emp-inc",207489,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,50,"Germany","<=50K" +43,"Private",336643,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +31,"Private",143653,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +62,"State-gov",101475,"Assoc-acdm",12,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Local-gov",263871,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,8,"United-States","<=50K" +38,"Self-emp-not-inc",77820,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",95465,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +26,"Private",257910,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +26,"Private",244372,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,52,"United-States",">50K" +37,"Self-emp-not-inc",126738,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,72,"United-States","<=50K" +61,"Private",133164,"7th-8th",4,"Never-married","Other-service","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +28,"Self-emp-not-inc",104617,"7th-8th",4,"Never-married","Other-service","Other-relative","White","Female",0,0,99,"Mexico","<=50K" +51,"Self-emp-inc",258735,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,81,"United-States","<=50K" +34,"Private",182926,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States",">50K" +35,"Private",166193,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Local-gov",206125,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +44,"Private",346594,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",108301,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +32,"Private",73498,"7th-8th",4,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",129150,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,20,"United-States",">50K" +27,"Private",181280,"Masters",14,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,30,"United-States","<=50K" +40,"Private",146908,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +43,"Private",183765,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Male",0,0,40,"?",">50K" +25,"Private",164488,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",307468,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",93884,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +52,"Private",137658,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",0,0,40,"Dominican-Republic","<=50K" +32,"Private",101562,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +33,"Private",136331,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",259846,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +48,"Private",98719,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +62,"Self-emp-not-inc",168682,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,5,"United-States","<=50K" +40,"Self-emp-not-inc",198953,"Assoc-acdm",12,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,2,"United-States","<=50K" +41,"?",29115,"Some-college",10,"Widowed","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +28,"Private",173673,"5th-6th",3,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +23,"Private",67958,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +51,"State-gov",94174,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +63,"Self-emp-not-inc",122442,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,48,"United-States","<=50K" +63,"Federal-gov",154675,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",116632,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States",">50K" +20,"?",238685,"11th",7,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",169031,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",237452,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,15,"Cuba",">50K" +41,"Private",216968,"Bachelors",13,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"?","<=50K" +27,"?",216479,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,24,"United-States",">50K" +20,"State-gov",126822,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,15,"United-States","<=50K" +35,"Private",54953,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",222654,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",37676,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +57,"Private",159319,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",125321,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",209609,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",224947,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"State-gov",438427,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +26,"Self-emp-not-inc",384276,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",196805,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,65,"United-States","<=50K" +27,"Private",242097,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +33,"Private",184306,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +45,"Private",161954,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"Germany","<=50K" +65,"Private",258561,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +59,"Private",212783,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +18,"Private",205004,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,26,"United-States","<=50K" +44,"Local-gov",387844,"12th",8,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",83880,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",161155,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",265698,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +59,"Self-emp-inc",146477,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",97261,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"State-gov",437890,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","Black","Male",0,0,90,"United-States","<=50K" +37,"Private",126675,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,57,"United-States","<=50K" +31,"Private",121768,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"Poland","<=50K" +23,"Private",180052,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",124454,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +36,"Private",222584,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",22245,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +24,"Private",228960,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",132572,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +47,"Private",103020,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Wife","Other","Female",0,0,40,"Puerto-Rico","<=50K" +31,"Local-gov",50649,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +42,"Private",137698,"5th-6th",3,"Married-spouse-absent","Farming-fishing","Not-in-family","White","Male",0,0,35,"Mexico","<=50K" +48,"Self-emp-inc",30575,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States",">50K" +56,"Private",202220,"Some-college",10,"Separated","Tech-support","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +50,"Private",50178,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",207791,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +50,"Private",321770,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Private",202053,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +34,"Private",143699,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,15,"United-States","<=50K" +32,"Self-emp-not-inc",115066,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +28,"Private",223751,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +62,"Self-emp-inc",354075,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",32732,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +24,"State-gov",390867,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",101697,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +36,"Private",279721,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",223400,"Assoc-acdm",12,"Married-civ-spouse","Priv-house-serv","Other-relative","White","Female",0,0,35,"Poland","<=50K" +46,"?",206357,"5th-6th",3,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"Mexico","<=50K" +39,"Private",76417,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +48,"?",184682,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,18,"United-States","<=50K" +21,"Private",78170,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +39,"Private",201410,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",189013,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +33,"Private",119913,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",549174,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +29,"Local-gov",214706,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"?",33811,"Bachelors",13,"Married-civ-spouse","?","Wife","Other","Female",0,0,40,"Taiwan",">50K" +43,"Private",234220,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Female",0,0,40,"Cuba","<=50K" +22,"Private",237720,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",185942,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States",">50K" +69,"Local-gov",286983,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",140027,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +18,"?",115258,"11th",7,"Never-married","?","Own-child","White","Male",0,0,12,"United-States","<=50K" +54,"Private",155408,"HS-grad",9,"Widowed","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +65,"?",117963,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,45,"United-States","<=50K" +28,"Private",158737,"12th",8,"Married-civ-spouse","Machine-op-inspct","Other-relative","Other","Male",0,0,40,"Ecuador","<=50K" +27,"Local-gov",199471,"Assoc-voc",11,"Never-married","Tech-support","Own-child","White","Female",0,0,38,"United-States","<=50K" +35,"Private",287701,"Assoc-acdm",12,"Divorced","Craft-repair","Unmarried","White","Male",0,0,45,"United-States",">50K" +38,"Private",137707,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States",">50K" +33,"State-gov",108116,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",366900,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-inc",187355,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,60,"Canada",">50K" +38,"Private",33105,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",0,0,70,"United-States",">50K" +26,"Private",358975,"Some-college",10,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,50,"Hungary","<=50K" +33,"Private",199227,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +44,"Private",248249,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",460437,"9th",5,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",187294,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +44,"Private",115932,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",27049,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +41,"Private",806552,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",160786,"11th",7,"Separated","Craft-repair","Not-in-family","White","Male",0,0,45,"Germany","<=50K" +38,"Private",219546,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +60,"Private",24872,"Some-college",10,"Separated","Transport-moving","Not-in-family","Amer-Indian-Eskimo","Female",0,0,30,"United-States","<=50K" +24,"Private",110371,"12th",8,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"Mexico","<=50K" +24,"?",376474,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",304602,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"?",143699,"Some-college",10,"Never-married","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",238917,"1st-4th",2,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,24,"Mexico","<=50K" +51,"Private",200618,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",209752,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +37,"Local-gov",98725,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Female",0,0,42,"United-States","<=50K" +37,"Self-emp-not-inc",180150,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +66,"Private",151227,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +18,"?",118847,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,24,"United-States","<=50K" +46,"Private",282538,"Assoc-voc",11,"Separated","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +52,"Private",89534,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",291011,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +67,"Private",166187,"HS-grad",9,"Widowed","Exec-managerial","Unmarried","White","Male",0,0,38,"United-States",">50K" +19,"Private",188669,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +37,"Private",178948,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +39,"Self-emp-not-inc",160808,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +46,"Private",318331,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"?",109921,"HS-grad",9,"Separated","?","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +33,"Private",87605,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +69,"Self-emp-not-inc",89477,"Some-college",10,"Widowed","Farming-fishing","Not-in-family","White","Female",0,0,14,"United-States","<=50K" +21,"Private",48301,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",220748,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","Black","Male",0,0,48,"United-States","<=50K" +39,"Private",387068,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",250743,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",78258,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,36,"United-States","<=50K" +42,"Private",31387,"Doctorate",16,"Married-spouse-absent","Prof-specialty","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +36,"Private",289190,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +24,"Private",604537,"HS-grad",9,"Never-married","Transport-moving","Unmarried","White","Male",0,0,40,"Mexico","<=50K" +35,"Private",328466,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +42,"Private",403187,"HS-grad",9,"Divorced","Handlers-cleaners","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",220531,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",204648,"Assoc-voc",11,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +44,"?",109912,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,16,"United-States",">50K" +18,"Private",365683,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,16,"United-States","<=50K" +41,"Private",175674,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",203488,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",106406,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",125167,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +51,"Private",249339,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",94652,"Some-college",10,"Never-married","Craft-repair","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +25,"Private",130302,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +38,"Private",66686,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",336042,"HS-grad",9,"Separated","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",193586,"Some-college",10,"Separated","Farming-fishing","Other-relative","White","Female",0,0,40,"United-States","<=50K" +60,"Local-gov",313852,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +21,"Local-gov",32639,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +18,"Private",234953,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +43,"Private",350379,"5th-6th",3,"Divorced","Priv-house-serv","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +26,"?",176967,"11th",7,"Never-married","?","Not-in-family","White","Female",0,0,65,"United-States","<=50K" +36,"Private",36423,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,25,"United-States",">50K" +38,"Private",130813,"HS-grad",9,"Divorced","Machine-op-inspct","Other-relative","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",35236,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,84,"United-States","<=50K" +58,"Private",33350,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +55,"Private",177380,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,29,"United-States","<=50K" +39,"Private",216129,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,35,"Jamaica","<=50K" +38,"Private",335104,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +57,"Self-emp-inc",165881,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Local-gov",387777,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,52,"United-States","<=50K" +44,"Self-emp-not-inc",149943,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,60,"Taiwan",">50K" +36,"Private",188834,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",290661,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",114838,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,8,"Italy","<=50K" +54,"Local-gov",168553,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",103064,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",123833,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +60,"Federal-gov",55621,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +66,"Local-gov",189834,"7th-8th",4,"Widowed","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +36,"Private",217926,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,50,"United-States","<=50K" +25,"Private",194352,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +62,"?",54878,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +23,"Private",393248,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",279315,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +33,"Private",392812,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States",">50K" +49,"Self-emp-inc",34998,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +57,"Self-emp-inc",51016,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +57,"Local-gov",132717,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +46,"Private",186078,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +37,"Self-emp-inc",196123,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States",">50K" +43,"Self-emp-inc",304906,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +26,"Private",41521,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +40,"Private",346847,"Assoc-voc",11,"Separated","Prof-specialty","Other-relative","White","Female",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",107233,"HS-grad",9,"Never-married","Craft-repair","Other-relative","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +39,"Private",150125,"Assoc-acdm",12,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",400535,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",409622,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",0,0,36,"Mexico","<=50K" +27,"Private",136448,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",202950,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"Iran","<=50K" +57,"Private",237691,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +24,"Private",170277,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +30,"Private",160784,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +28,"Private",33798,"12th",8,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +22,"Private",197838,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",223212,"7th-8th",4,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,50,"United-States","<=50K" +33,"Private",125762,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States",">50K" +20,"Private",283969,"Some-college",10,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,15,"United-States","<=50K" +25,"Private",374163,"12th",8,"Married-civ-spouse","Farming-fishing","Husband","Other","Male",0,0,60,"Mexico","<=50K" +49,"State-gov",118567,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",147655,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +45,"Private",82797,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +36,"Local-gov",142573,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +41,"Private",235167,"5th-6th",3,"Married-spouse-absent","Priv-house-serv","Not-in-family","White","Female",0,0,32,"Mexico","<=50K" +47,"Private",28035,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +41,"Private",247082,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Private",123397,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Local-gov",133327,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",102270,"7th-8th",4,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +64,"?",45817,"9th",5,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States","<=50K" +55,"Private",240988,"9th",5,"Married-civ-spouse","Machine-op-inspct","Other-relative","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +19,"Private",386378,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +31,"State-gov",350651,"12th",8,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States",">50K" +18,"State-gov",76142,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,8,"United-States","<=50K" +68,"Private",73773,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +50,"?",281504,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",293358,"Some-college",10,"Never-married","Exec-managerial","Unmarried","Black","Female",0,0,48,"United-States","<=50K" +44,"Private",146906,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +58,"Self-emp-not-inc",331474,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States",">50K" +20,"Private",213719,"HS-grad",9,"Never-married","Sales","Own-child","Black","Female",0,0,20,"United-States","<=50K" +18,"Private",101795,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",228265,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,30,"United-States","<=50K" +49,"Self-emp-not-inc",130206,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",324254,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",223019,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",189666,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,45,"United-States","<=50K" +35,"Private",139086,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",359327,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"?","<=50K" +44,"Self-emp-not-inc",75065,"12th",8,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,60,"Vietnam","<=50K" +55,"Private",139843,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +54,"Private",346014,"Some-college",10,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,40,"United-States","<=50K" +52,"Private",31460,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +57,"Self-emp-inc",33725,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +67,"?",63552,"7th-8th",4,"Widowed","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +58,"State-gov",300623,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Local-gov",177072,"Some-college",10,"Never-married","Prof-specialty","Other-relative","White","Male",0,0,16,"United-States","<=50K" +66,"?",37331,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,15,"United-States","<=50K" +41,"Private",167725,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",131180,"11th",7,"Never-married","Prof-specialty","Own-child","White","Female",0,0,16,"United-States","<=50K" +50,"Private",275181,"5th-6th",3,"Divorced","Other-service","Not-in-family","White","Male",0,0,37,"Cuba","<=50K" +31,"Private",398988,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",222654,"10th",6,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",111129,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +26,"Self-emp-not-inc",137795,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States","<=50K" +33,"Local-gov",242150,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"State-gov",237873,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +44,"Private",367749,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"Mexico","<=50K" +26,"Private",206600,"Bachelors",13,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"Mexico","<=50K" +48,"Federal-gov",247043,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",187702,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +62,"Private",41718,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +37,"Private",151835,"Prof-school",15,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +18,"Private",118938,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,18,"United-States","<=50K" +48,"Private",224870,"HS-grad",9,"Divorced","Machine-op-inspct","Other-relative","Other","Female",0,0,38,"Ecuador","<=50K" +45,"Private",178341,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Private",61343,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +35,"Private",36989,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",226296,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,51,"United-States","<=50K" +29,"Private",186624,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"Cuba","<=50K" +19,"Private",172582,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +53,"State-gov",227392,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States","<=50K" +49,"Private",187563,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +71,"Private",137499,"HS-grad",9,"Widowed","Sales","Other-relative","White","Female",0,0,16,"United-States","<=50K" +38,"Private",239397,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,36,"Mexico","<=50K" +39,"Local-gov",327164,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +23,"Private",140798,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Self-emp-inc",187450,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Private",194580,"5th-6th",3,"Divorced","Farming-fishing","Unmarried","White","Male",0,0,40,"United-States","<=50K" +41,"Private",372682,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +20,"Private",235442,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +30,"Private",128065,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States","<=50K" +56,"Private",91545,"10th",6,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,36,"United-States","<=50K" +26,"Private",154604,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Federal-gov",192150,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Local-gov",216522,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,42,"United-States","<=50K" +24,"Private",206861,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",97632,"Some-college",10,"Divorced","Sales","Not-in-family","Asian-Pac-Islander","Female",0,0,32,"United-States","<=50K" +27,"Private",189530,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +57,"Self-emp-inc",368797,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"State-gov",41183,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"United-States","<=50K" +50,"Private",191062,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",132963,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +58,"Private",153551,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +27,"Self-emp-not-inc",66473,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",240323,"HS-grad",9,"Separated","Sales","Unmarried","Black","Female",0,0,17,"United-States","<=50K" +33,"Self-emp-inc",128016,"HS-grad",9,"Widowed","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",29526,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,18,"United-States","<=50K" +26,"Private",342953,"HS-grad",9,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +37,"Private",215476,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +53,"Private",231919,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +32,"Private",52537,"Some-college",10,"Never-married","Tech-support","Not-in-family","Black","Male",0,0,38,"United-States","<=50K" +18,"Private",27920,"11th",7,"Never-married","Exec-managerial","Own-child","White","Female",0,0,25,"United-States","<=50K" +53,"Private",153052,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Self-emp-not-inc",199303,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",233369,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +60,"Private",238913,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,46,"United-States",">50K" +28,"Self-emp-not-inc",195607,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +37,"Private",138441,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",67467,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",37202,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +47,"Private",140219,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +18,"Private",298860,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +22,"Private",51362,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +36,"Private",199947,"Some-college",10,"Divorced","Machine-op-inspct","Own-child","White","Female",0,0,30,"United-States","<=50K" +59,"Self-emp-not-inc",32552,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States","<=50K" +33,"Private",183845,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,38,"El-Salvador","<=50K" +33,"Private",181091,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,35,"England","<=50K" +53,"Self-emp-inc",135643,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","Asian-Pac-Islander","Female",0,0,50,"South","<=50K" +55,"Private",181220,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +56,"Private",133025,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +54,"Self-emp-not-inc",124865,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +51,"Private",45599,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",102180,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Private",121130,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",138768,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,50,"United-States","<=50K" +43,"State-gov",98989,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +26,"State-gov",126327,"Assoc-acdm",12,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +30,"Private",113364,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,18,"United-States","<=50K" +46,"Private",376789,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +27,"Private",137063,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Private",279145,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Self-emp-not-inc",245369,"HS-grad",9,"Separated","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +30,"Federal-gov",49593,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +47,"Private",166181,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,48,"United-States",">50K" +43,"Private",156403,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +71,"?",128529,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +46,"?",148489,"HS-grad",9,"Married-spouse-absent","?","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +44,"Local-gov",387770,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,15,"United-States","<=50K" +42,"Private",115511,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",220585,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",280966,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",291586,"Bachelors",13,"Never-married","Transport-moving","Own-child","White","Male",0,0,20,"United-States","<=50K" +24,"Private",142227,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +17,"?",104025,"11th",7,"Never-married","?","Own-child","White","Male",0,0,18,"United-States","<=50K" +45,"Local-gov",148254,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +54,"Private",170562,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +22,"Private",222490,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +63,"Local-gov",57674,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States","<=50K" +22,"Private",233624,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States","<=50K" +27,"Private",42734,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +33,"Private",233107,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,33,"Mexico","<=50K" +64,"Private",143110,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +50,"Private",195844,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Self-emp-not-inc",115896,"Assoc-voc",11,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",303851,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Private",172475,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +53,"Self-emp-not-inc",30008,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +33,"Local-gov",147921,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Federal-gov",172716,"12th",8,"Married-civ-spouse","Armed-Forces","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",155057,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +80,"Self-emp-not-inc",132728,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +31,"Private",195136,"Assoc-acdm",12,"Divorced","Other-service","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +40,"Private",377322,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +53,"Local-gov",293941,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",182123,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,44,"United-States","<=50K" +38,"Private",32528,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",140206,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Local-gov",378221,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"Mexico",">50K" +23,"Private",211601,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",119411,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +52,"Self-emp-not-inc",240013,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States","<=50K" +24,"Private",95552,"HS-grad",9,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",183710,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",189382,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +52,"Private",380633,"5th-6th",3,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +54,"Private",53407,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",150480,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +40,"Private",175674,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",375313,"HS-grad",9,"Never-married","Tech-support","Not-in-family","Asian-Pac-Islander","Male",0,0,50,"United-States","<=50K" +21,"?",278391,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,16,"United-States","<=50K" +23,"Private",212888,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-inc",487085,"7th-8th",4,"Never-married","Craft-repair","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +22,"Private",174461,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +55,"Local-gov",133201,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +71,"Private",77253,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,17,"United-States","<=50K" +47,"Private",141511,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +17,"Self-emp-inc",181608,"10th",6,"Never-married","Sales","Own-child","White","Male",0,0,12,"United-States","<=50K" +31,"Private",127610,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +32,"Private",154571,"Some-college",10,"Never-married","Other-service","Other-relative","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +27,"Private",150080,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",151294,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +17,"Private",193769,"9th",5,"Never-married","Other-service","Unmarried","White","Male",0,0,20,"United-States","<=50K" +33,"Private",277455,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +72,"Private",225780,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +34,"Federal-gov",436341,"Some-college",10,"Married-AF-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +65,"Private",255386,"HS-grad",9,"Never-married","Craft-repair","Other-relative","Asian-Pac-Islander","Male",0,0,40,"Cambodia","<=50K" +32,"Private",174789,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +26,"Private",245628,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +22,"Private",228752,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",192900,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",190391,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +38,"Private",353263,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"Italy",">50K" +34,"Private",113198,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,28,"United-States","<=50K" +44,"Private",207578,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +27,"Private",93206,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",163998,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,44,"United-States",">50K" +47,"Private",111961,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,30,"United-States","<=50K" +20,"Private",219122,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",111445,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +29,"Federal-gov",309778,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Local-gov",223020,"Assoc-voc",11,"Never-married","Other-service","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +42,"Private",303155,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"?",41035,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +68,"Private",159191,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Local-gov",244408,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +72,"Self-emp-not-inc",473748,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +45,"Federal-gov",71823,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,20,"United-States","<=50K" +30,"Local-gov",83066,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +33,"Private",150154,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",190786,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Self-emp-not-inc",159909,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",190885,"HS-grad",9,"Divorced","Priv-house-serv","Not-in-family","White","Female",0,0,40,"Guatemala","<=50K" +25,"Private",243786,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +31,"State-gov",124020,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",159016,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,38,"United-States","<=50K" +37,"Private",183800,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Self-emp-not-inc",193434,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +26,"Private",245029,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +55,"Private",98746,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"Canada",">50K" +46,"Federal-gov",140664,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +44,"Private",169980,"11th",7,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,60,"United-States","<=50K" +28,"State-gov",155397,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +42,"Private",245317,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Private",74182,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",280570,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +64,"Self-emp-not-inc",30664,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +20,"Private",109952,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +45,"Local-gov",192793,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",243442,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Federal-gov",106297,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",328060,"9th",5,"Separated","Other-service","Unmarried","Other","Female",0,0,40,"Mexico","<=50K" +33,"Self-emp-not-inc",48702,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,65,"United-States","<=50K" +36,"Private",484024,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +40,"Private",208470,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",29927,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"England","<=50K" +46,"Private",98012,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",108468,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +26,"Private",168403,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",66935,"Bachelors",13,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",42044,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",184806,"Prof-school",15,"Never-married","Prof-specialty","Other-relative","White","Male",0,0,50,"United-States","<=50K" +39,"Private",1455435,"Assoc-acdm",12,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",445382,"Some-college",10,"Divorced","Other-service","Unmarried","White","Male",0,0,40,"United-States","<=50K" +37,"Private",278576,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"United-States",">50K" +79,"Self-emp-not-inc",84979,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"United-States",">50K" +36,"Private",659504,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,45,"United-States",">50K" +44,"Private",136986,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +27,"Private",96219,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +58,"Private",205410,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",416745,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +21,"Private",72119,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +49,"Federal-gov",195949,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",101345,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +29,"Private",439263,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,35,"Peru","<=50K" +63,"Private",213095,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +29,"Federal-gov",59932,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +65,"Private",172815,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",40915,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +42,"Private",139012,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Taiwan",">50K" +44,"Private",121781,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,37,"United-States","<=50K" +51,"?",130667,"HS-grad",9,"Separated","?","Not-in-family","Black","Male",0,0,6,"United-States","<=50K" +41,"Self-emp-not-inc",147110,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,25,"United-States","<=50K" +22,"Local-gov",237811,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,35,"Haiti","<=50K" +36,"?",128640,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,25,"United-States","<=50K" +18,"Private",111476,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Local-gov",289716,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Local-gov",141944,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +49,"Private",323773,"11th",7,"Married-civ-spouse","Priv-house-serv","Other-relative","White","Female",0,0,40,"United-States","<=50K" +41,"State-gov",176663,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +52,"Private",155233,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",143327,"Some-college",10,"Separated","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Federal-gov",177212,"Some-college",10,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",123088,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Local-gov",47085,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Private",102106,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",235894,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +71,"Self-emp-not-inc",172046,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"Self-emp-not-inc",197207,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +26,"Private",152452,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",172928,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States","<=50K" +36,"?",214896,"9th",5,"Divorced","?","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +22,"Private",59924,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Private",95128,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",292504,"Some-college",10,"Married-spouse-absent","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Self-emp-inc",45796,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +52,"State-gov",104280,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"Private",172291,"HS-grad",9,"Divorced","Adm-clerical","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",180988,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,39,"United-States","<=50K" +52,"Private",110748,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +59,"?",556688,"9th",5,"Divorced","?","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +36,"Private",22494,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",267859,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Cuba",">50K" +67,"Local-gov",256821,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","Black","Male",0,0,20,"United-States","<=50K" +31,"Self-emp-not-inc",117346,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +31,"Private",62374,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"Private",314659,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +72,"?",114761,"7th-8th",4,"Widowed","?","Unmarried","White","Female",0,0,20,"United-States","<=50K" +36,"Private",93225,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",165315,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States",">50K" +56,"Private",124771,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",27408,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",198841,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",271792,"Bachelors",13,"Married-spouse-absent","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",64289,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",183390,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",234919,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"El-Salvador","<=50K" +20,"Private",88231,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",154422,"Some-college",10,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +37,"Private",119098,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +54,"Private",118793,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +32,"?",30499,"Bachelors",13,"Divorced","?","Unmarried","White","Female",0,0,32,"United-States","<=50K" +43,"State-gov",308498,"HS-grad",9,"Married-spouse-absent","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +48,"Private",172695,"Assoc-voc",11,"Divorced","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",29962,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +62,"Private",200332,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",291702,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",67234,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +45,"Private",168038,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,32,"United-States","<=50K" +34,"Private",137814,"Some-college",10,"Separated","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +64,"Private",126233,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States","<=50K" +42,"Self-emp-not-inc",79036,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,65,"United-States","<=50K" +60,"Self-emp-not-inc",327474,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States","<=50K" +44,"Private",145160,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,58,"United-States","<=50K" +67,"?",37092,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,4,"United-States","<=50K" +45,"Private",129387,"Assoc-acdm",12,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"?","<=50K" +53,"Self-emp-not-inc",33304,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +32,"?",143162,"10th",6,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States","<=50K" +23,"Private",133515,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +28,"Private",168901,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Taiwan","<=50K" +55,"Private",750972,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,41,"United-States","<=50K" +58,"Private",142924,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,24,"United-States",">50K" +27,"Private",91189,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",290609,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +22,"?",31102,"Some-college",10,"Never-married","?","Own-child","Asian-Pac-Islander","Female",0,0,4,"South","<=50K" +44,"Self-emp-not-inc",216921,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,70,"United-States","<=50K" +23,"Private",120046,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",324629,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Yugoslavia","<=50K" +45,"Private",81132,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,0,55,"United-States",">50K" +29,"Private",160279,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +33,"Private",229732,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States",">50K" +22,"Private",160398,"Some-college",10,"Never-married","Sales","Other-relative","White","Male",0,0,38,"United-States","<=50K" +28,"Private",129460,"9th",5,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"El-Salvador","<=50K" +30,"Private",252752,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +20,"Private",58222,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +28,"?",424884,"10th",6,"Separated","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +45,"Private",114459,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +19,"?",46400,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +42,"Private",223934,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",84119,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",159123,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +23,"Private",195532,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Private",191299,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",198316,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",162301,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +24,"Private",92609,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,45,"United-States","<=50K" +27,"Private",247819,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +27,"Local-gov",229223,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Female",0,0,40,"United-States",">50K" +45,"Self-emp-inc",142719,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +80,"Private",86111,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States","<=50K" +23,"State-gov",35633,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +46,"Private",164749,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",607848,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",173630,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +90,"Private",311184,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"?","<=50K" +55,"Private",49737,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +72,"Private",183616,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"England","<=50K" +65,"Private",129426,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",454915,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"State-gov",55568,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +38,"Private",29874,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",143953,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States",">50K" +54,"Private",90363,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",53727,"Masters",14,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +50,"Private",173630,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +28,"Private",410351,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +34,"Private",399386,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,53,"United-States","<=50K" +55,"Private",157932,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",133061,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"?",46400,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +21,"Private",107895,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +39,"Private",63021,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +43,"Private",186144,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Local-gov",27959,"HS-grad",9,"Never-married","Other-service","Unmarried","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +26,"Private",179569,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"State-gov",101299,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +31,"State-gov",113129,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,65,"United-States","<=50K" +32,"Private",316470,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"Mexico","<=50K" +60,"Self-emp-not-inc",89884,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Private",32121,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",315303,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,20,"United-States","<=50K" +27,"Private",254500,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,36,"United-States","<=50K" +33,"Private",419895,"5th-6th",3,"Divorced","Handlers-cleaners","Unmarried","White","Male",0,0,40,"Mexico","<=50K" +43,"Private",159549,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Self-emp-not-inc",258474,"10th",6,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"Self-emp-not-inc",370119,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",50837,"7th-8th",4,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +58,"Private",137506,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",183594,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,40,"United-States","<=50K" +26,"Private",341353,"Bachelors",13,"Never-married","Other-service","Other-relative","White","Male",0,0,15,"United-States","<=50K" +34,"Private",193565,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",39606,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",127149,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States",">50K" +31,"?",233371,"HS-grad",9,"Married-civ-spouse","?","Wife","Black","Female",0,0,45,"United-States","<=50K" +49,"Self-emp-not-inc",182752,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,35,"United-States",">50K" +26,"Private",269060,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"Private",179949,"HS-grad",9,"Divorced","Transport-moving","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +26,"Private",160445,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",314539,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"?",337721,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +42,"Local-gov",100793,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +39,"Federal-gov",255407,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Federal-gov",92775,"Assoc-voc",11,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",33308,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +68,"State-gov",493363,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States","<=50K" +30,"?",159589,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,46,"United-States",">50K" +32,"Private",107218,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +25,"Private",123586,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Other","Male",0,0,40,"United-States","<=50K" +53,"Private",158352,"5th-6th",3,"Married-civ-spouse","Other-service","Other-relative","White","Female",0,0,24,"Italy","<=50K" +38,"Private",76317,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +62,"?",176753,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",122346,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",463194,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",162228,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"State-gov",115005,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"State-gov",183285,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,36,"United-States","<=50K" +34,"Private",169605,"10th",6,"Separated","Other-service","Unmarried","White","Female",0,0,36,"United-States","<=50K" +24,"Private",450695,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +44,"Local-gov",124692,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +19,"Private",63918,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",102569,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",289309,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +45,"Private",101825,"HS-grad",9,"Widowed","Sales","Unmarried","White","Female",0,0,45,"United-States","<=50K" +43,"Private",206833,"HS-grad",9,"Separated","Handlers-cleaners","Unmarried","Black","Female",0,0,45,"United-States","<=50K" +22,"?",77873,"9th",5,"Never-married","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +72,"?",194548,"Some-college",10,"Married-spouse-absent","?","Not-in-family","White","Male",0,0,3,"United-States","<=50K" +29,"Private",206351,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",198200,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +24,"Private",140001,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,35,"El-Salvador","<=50K" +22,"?",287988,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +21,"Private",143604,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +74,"Self-emp-not-inc",192413,"Prof-school",15,"Divorced","Prof-specialty","Other-relative","White","Male",0,0,40,"United-States","<=50K" +27,"Private",104917,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Local-gov",161478,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,46,"United-States","<=50K" +30,"Private",35644,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Local-gov",116751,"Assoc-voc",11,"Divorced","Protective-serv","Unmarried","White","Male",0,0,56,"United-States","<=50K" +39,"State-gov",179668,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,70,"United-States","<=50K" +21,"Private",57951,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +31,"Private",176711,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,38,"United-States","<=50K" +33,"Local-gov",368675,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",216149,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,70,"United-States",">50K" +29,"Private",173851,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"State-gov",216342,"Bachelors",13,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,55,"United-States","<=50K" +35,"Private",140752,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +33,"Private",116508,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"?",224361,"9th",5,"Divorced","?","Unmarried","White","Female",0,0,5,"Cuba","<=50K" +43,"Private",180303,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,50,"United-States",">50K" +66,"?",196736,"1st-4th",2,"Never-married","?","Not-in-family","Black","Male",0,0,30,"United-States","<=50K" +51,"Local-gov",110327,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",185607,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +17,"Local-gov",244856,"11th",7,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +32,"Private",198068,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",97136,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +19,"Self-emp-inc",164658,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,60,"United-States","<=50K" +54,"Private",235693,"11th",7,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States",">50K" +45,"Private",197038,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +47,"Local-gov",97419,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +32,"Private",205528,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Self-emp-inc",146042,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"Self-emp-inc",222641,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Self-emp-inc",376936,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +42,"Local-gov",138077,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,38,"United-States",">50K" +24,"Private",155913,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,44,"United-States","<=50K" +45,"Private",36006,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +19,"Private",214678,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +46,"Private",369538,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",166565,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",257043,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +43,"Self-emp-not-inc",38876,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",187073,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +90,"Private",313749,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,10,"United-States","<=50K" +41,"Private",331651,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"Japan",">50K" +24,"Private",243368,"Preschool",1,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,36,"Mexico","<=50K" +24,"Private",32921,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,50,"United-States","<=50K" +24,"Private",117167,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,53,"United-States","<=50K" +30,"Private",114691,"Bachelors",13,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,40,"United-States","<=50K" +46,"Private",99385,"Bachelors",13,"Separated","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Private",252327,"9th",5,"Separated","Craft-repair","Own-child","White","Male",0,0,35,"Mexico","<=50K" +43,"Private",90582,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",190194,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +65,"Private",264188,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +34,"Private",243776,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +41,"Private",67065,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Self-emp-not-inc",204209,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,60,"United-States","<=50K" +24,"Private",226668,"HS-grad",9,"Never-married","Other-service","Not-in-family","Amer-Indian-Eskimo","Male",0,0,35,"United-States","<=50K" +33,"Private",315143,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Cuba",">50K" +37,"Private",118681,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,38,"Puerto-Rico","<=50K" +39,"Self-emp-not-inc",208109,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +58,"Private",116901,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,25,"United-States","<=50K" +36,"Self-emp-not-inc",405644,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"Mexico","<=50K" +42,"Local-gov",328581,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +31,"Private",217962,"Some-college",10,"Never-married","Protective-serv","Other-relative","Black","Male",0,0,40,"?","<=50K" +57,"Private",158827,"HS-grad",9,"Separated","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +67,"Federal-gov",65475,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",159709,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",140474,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +43,"Private",144778,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"Italy",">50K" +39,"Self-emp-not-inc",83242,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +36,"Private",143385,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Local-gov",167544,"Assoc-acdm",12,"Divorced","Other-service","Unmarried","White","Female",0,0,13,"United-States","<=50K" +25,"Private",122175,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"Private",378747,"10th",6,"Separated","Transport-moving","Unmarried","Black","Male",0,0,45,"United-States",">50K" +24,"Private",230475,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +50,"Self-emp-inc",120781,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,60,"South",">50K" +70,"Private",206232,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +38,"Self-emp-not-inc",140583,"Masters",14,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +51,"Private",137253,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States",">50K" +28,"Private",246974,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +66,"Self-emp-not-inc",182470,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,25,"United-States",">50K" +57,"Self-emp-inc",107617,"HS-grad",9,"Separated","Farming-fishing","Not-in-family","White","Male",0,0,60,"United-States",">50K" +44,"Self-emp-inc",116358,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,50,"?",">50K" +29,"Private",250819,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",196508,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,40,"United-States","<=50K" +42,"Private",367533,"10th",6,"Married-civ-spouse","Craft-repair","Own-child","Other","Male",0,0,43,"United-States",">50K" +50,"Private",271160,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +65,"Private",173674,"HS-grad",9,"Divorced","Other-service","Other-relative","White","Female",0,0,14,"United-States","<=50K" +64,"?",257790,"HS-grad",9,"Divorced","?","Unmarried","White","Female",0,0,38,"United-States","<=50K" +44,"Private",322391,"11th",7,"Separated","Other-service","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +17,"Private",104232,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,10,"United-States","<=50K" +17,"?",86786,"10th",6,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Private",88233,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +32,"Private",240888,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",129240,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +23,"Private",160968,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,10,"United-States","<=50K" +34,"Private",236861,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Private",109282,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +32,"Private",215047,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",115932,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"Ireland",">50K" +28,"Private",55360,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +44,"Private",224658,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +29,"Local-gov",376302,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,35,"Nicaragua",">50K" +37,"Private",115289,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-inc",258883,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",69132,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",207301,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,20,"United-States","<=50K" +37,"Private",179671,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +66,"Self-emp-not-inc",140456,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",327397,"HS-grad",9,"Never-married","Prof-specialty","Own-child","White","Male",0,0,30,"United-States","<=50K" +60,"Private",200235,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Private",195978,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",329144,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,48,"United-States",">50K" +48,"Self-emp-inc",250674,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +57,"?",176897,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,60,"United-States","<=50K" +50,"Self-emp-inc",132716,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"Germany",">50K" +62,"Private",174201,"9th",5,"Widowed","Other-service","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +45,"Private",167617,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Local-gov",254949,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Private",319582,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +25,"Private",248990,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Guatemala","<=50K" +49,"Private",144396,"11th",7,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +25,"Federal-gov",55636,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +39,"Private",185624,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Local-gov",125442,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +43,"Private",160943,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States",">50K" +30,"Private",243841,"HS-grad",9,"Divorced","Other-service","Other-relative","Asian-Pac-Islander","Female",0,0,40,"South","<=50K" +21,"Private",34616,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +33,"Private",235847,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +33,"Private",174789,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +33,"Private",280111,"11th",7,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +70,"Private",236055,"7th-8th",4,"Widowed","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +25,"Private",237865,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,42,"United-States","<=50K" +17,"Private",194612,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +20,"Private",173851,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",372483,"Some-college",10,"Never-married","Other-service","Other-relative","Black","Male",0,0,35,"United-States","<=50K" +31,"Private",174201,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",272618,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +52,"Private",74660,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",201481,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",175232,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +25,"Private",336440,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",46645,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,9,"United-States","<=50K" +53,"Private",281425,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Self-emp-not-inc",31510,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +44,"Private",310255,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +32,"Federal-gov",82393,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,56,"United-States",">50K" +59,"Self-emp-not-inc",190514,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +49,"Private",165513,"Some-college",10,"Divorced","Handlers-cleaners","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",226696,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States",">50K" +44,"Private",165815,"9th",5,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",123983,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,55,"Japan",">50K" +36,"Private",235371,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",147258,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States",">50K" +29,"Private",255949,"Bachelors",13,"Never-married","Sales","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +52,"Private",186272,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",111676,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",199501,"Some-college",10,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +24,"Private",151443,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","Black","Female",0,0,30,"United-States","<=50K" +31,"Private",145935,"HS-grad",9,"Never-married","Exec-managerial","Own-child","Black","Male",0,0,40,"United-States","<=50K" +54,"Federal-gov",230387,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +44,"Private",127592,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",210828,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Other","Male",0,0,30,"United-States","<=50K" +41,"Private",297186,"HS-grad",9,"Married-civ-spouse","Transport-moving","Wife","White","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-inc",116554,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +30,"Private",144593,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"?","<=50K" +26,"State-gov",147719,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,20,"India","<=50K" +68,"Self-emp-not-inc",89011,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"Canada","<=50K" +31,"Private",38158,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",178686,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +80,"?",172826,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +26,"Private",155752,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +63,"Private",100099,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",231688,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,20,"United-States","<=50K" +30,"?",147215,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +42,"Self-emp-inc",50122,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +64,"Federal-gov",86837,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +32,"Private",113364,"Bachelors",13,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",289390,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,47,"United-States","<=50K" +73,"Private",77884,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +32,"Private",390157,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +58,"Private",234328,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",410439,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,15,"United-States","<=50K" +53,"Private",129525,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",166527,"Some-college",10,"Never-married","Exec-managerial","Own-child","Other","Female",0,0,40,"United-States","<=50K" +42,"?",109912,"Assoc-acdm",12,"Never-married","?","Other-relative","White","Female",0,0,40,"United-States","<=50K" +30,"Private",210906,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Other-relative","White","Female",0,0,40,"United-States","<=50K" +38,"Private",405284,"Bachelors",13,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +28,"Private",138269,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",25429,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +45,"Private",231672,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",258550,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",268147,"9th",5,"Never-married","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",54411,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"?","<=50K" +54,"Private",37289,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,55,"United-States",">50K" +23,"Private",157951,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +43,"Self-emp-inc",225165,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +37,"Private",238049,"9th",5,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,30,"El-Salvador","<=50K" +31,"Private",197252,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +25,"Private",183575,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"Private",19752,"11th",7,"Never-married","Other-service","Own-child","Black","Female",0,0,25,"United-States","<=50K" +37,"Private",103925,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,68,"United-States","<=50K" +60,"Private",31577,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Federal-gov",61298,"Bachelors",13,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +59,"Federal-gov",190541,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +28,"?",389857,"HS-grad",9,"Married-civ-spouse","?","Other-relative","White","Male",0,0,16,"United-States","<=50K" +33,"?",192644,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",67482,"Assoc-voc",11,"Divorced","Other-service","Unmarried","White","Female",0,0,99,"United-States","<=50K" +29,"?",108775,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Dominican-Republic","<=50K" +23,"State-gov",279243,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",278391,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,25,"Nicaragua","<=50K" +60,"Private",349898,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +44,"Private",219441,"10th",6,"Never-married","Sales","Unmarried","Other","Female",0,0,35,"Dominican-Republic","<=50K" +52,"Federal-gov",29623,"12th",8,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",217460,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +30,"Private",163604,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,55,"United-States",">50K" +20,"Private",238685,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +27,"?",251854,"Bachelors",13,"Married-civ-spouse","?","Wife","Black","Female",0,0,35,"?",">50K" +33,"Private",213308,"Assoc-voc",11,"Separated","Adm-clerical","Own-child","Black","Female",0,0,50,"United-States","<=50K" +25,"Private",193773,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +63,"Private",114011,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +63,"Self-emp-not-inc",52144,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +43,"Private",347934,"HS-grad",9,"Separated","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +58,"Private",293399,"11th",7,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +70,"?",118630,"Assoc-voc",11,"Widowed","?","Unmarried","White","Female",0,0,35,"United-States","<=50K" +42,"Private",366180,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +20,"Local-gov",188950,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,25,"United-States","<=50K" +35,"Private",189382,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +62,"Private",24515,"9th",5,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",182217,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,35,"United-States","<=50K" +19,"Private",552354,"12th",8,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Private",163021,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Private",183092,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +48,"Private",30289,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +29,"Private",77572,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +36,"Private",469056,"HS-grad",9,"Divorced","Sales","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +58,"Private",145574,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",302041,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +59,"Private",32552,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,4,"United-States","<=50K" +42,"Private",185413,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Federal-gov",26543,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Federal-gov",163870,"Some-college",10,"Never-married","Armed-Forces","Other-relative","White","Male",0,0,40,"United-States","<=50K" +21,"Private",240063,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +48,"Private",208748,"5th-6th",3,"Divorced","Machine-op-inspct","Unmarried","Other","Female",0,0,40,"Dominican-Republic","<=50K" +32,"Local-gov",84119,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",84130,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +66,"Local-gov",261062,"Masters",14,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Local-gov",336010,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +52,"Private",389270,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States",">50K" +17,"Private",138293,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,15,"United-States","<=50K" +35,"Private",240389,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,43,"United-States",">50K" +21,"?",170070,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +24,"Private",149457,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Private",81534,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,84,"Japan",">50K" +29,"Federal-gov",196912,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",80933,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +64,"Local-gov",190660,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States",">50K" +27,"Private",120155,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,39,"United-States","<=50K" +44,"Federal-gov",161240,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",126402,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","Black","Female",0,0,60,"United-States","<=50K" +23,"Private",148709,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Other-relative","White","Female",0,0,35,"United-States","<=50K" +31,"Local-gov",80058,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,64,"United-States","<=50K" +45,"Private",274689,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +42,"Private",157367,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,35,"?","<=50K" +33,"Private",217460,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Local-gov",33727,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",166961,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States",">50K" +25,"Private",146117,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +33,"Private",160216,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,32,"?","<=50K" +22,"Private",50163,"9th",5,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",235271,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Self-emp-not-inc",144218,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +37,"Private",94334,"7th-8th",4,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,25,"United-States","<=50K" +51,"Self-emp-not-inc",35295,"HS-grad",9,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,45,"United-States","<=50K" +36,"Private",35429,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +73,"Local-gov",205580,"5th-6th",3,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,6,"United-States","<=50K" +32,"Local-gov",177794,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",167474,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +51,"Local-gov",35211,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +20,"Private",117244,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,45,"United-States","<=50K" +57,"Private",194850,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Other","Male",0,0,40,"Mexico","<=50K" +19,"Private",144911,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +55,"Private",101338,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Private",148522,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +19,"Private",97261,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",166606,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",229414,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,30,"United-States","<=50K" +34,"Local-gov",209213,"Bachelors",13,"Never-married","Prof-specialty","Other-relative","Black","Male",0,0,15,"United-States","<=50K" +27,"Private",302406,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +37,"Self-emp-not-inc",29054,"Assoc-voc",11,"Never-married","Farming-fishing","Own-child","White","Male",0,0,84,"United-States","<=50K" +73,"Self-emp-not-inc",336007,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",101481,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",46704,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +49,"Private",233639,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +68,"Local-gov",31725,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",293512,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +28,"Private",375655,"Bachelors",13,"Never-married","Sales","Unmarried","White","Male",0,0,50,"United-States","<=50K" +28,"Private",105817,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Local-gov",203408,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",162302,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +40,"Private",163455,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,55,"United-States",">50K" +32,"Local-gov",100135,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +60,"?",41517,"11th",7,"Married-spouse-absent","?","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +18,"Private",102182,"12th",8,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +36,"Private",414683,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",194352,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +24,"Private",194096,"HS-grad",9,"Never-married","Prof-specialty","Own-child","White","Female",0,0,45,"United-States","<=50K" +20,"Private",215495,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"Mexico","<=50K" +27,"Private",164607,"Bachelors",13,"Separated","Tech-support","Own-child","White","Male",0,0,50,"United-States","<=50K" +58,"Local-gov",34878,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +28,"Private",22422,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",178222,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +45,"Local-gov",56841,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",300275,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +69,"Local-gov",197288,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States","<=50K" +58,"Self-emp-not-inc",157786,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",110684,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +58,"Self-emp-not-inc",140729,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +53,"Federal-gov",90127,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States",">50K" +44,"Self-emp-inc",37997,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +31,"Private",61308,"10th",6,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",171199,"Bachelors",13,"Divorced","Machine-op-inspct","Unmarried","Other","Female",0,0,40,"Puerto-Rico","<=50K" +48,"Private",128432,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Federal-gov",195023,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",171888,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Self-emp-inc",183784,"10th",6,"Never-married","Sales","Own-child","White","Male",0,0,15,"United-States","<=50K" +20,"Private",219262,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",71379,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +19,"?",234519,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,35,"United-States","<=50K" +35,"Private",96824,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",242597,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"?",127388,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",204536,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +54,"Private",143804,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",80680,"Some-college",10,"Married-civ-spouse","Sales","Own-child","White","Female",0,0,16,"United-States","<=50K" +36,"Private",301227,"5th-6th",3,"Separated","Priv-house-serv","Unmarried","Other","Female",0,0,35,"Mexico","<=50K" +26,"Self-emp-not-inc",201930,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Local-gov",176616,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Private",353219,"9th",5,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",126076,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +31,"Private",156493,"HS-grad",9,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"Federal-gov",435503,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Self-emp-inc",561489,"Masters",14,"Divorced","Exec-managerial","Not-in-family","Black","Female",0,0,50,"United-States","<=50K" +22,"Federal-gov",100345,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,43,"United-States","<=50K" +18,"Private",36275,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,25,"United-States","<=50K" +46,"Private",110794,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Local-gov",143766,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Federal-gov",76313,"HS-grad",9,"Married-civ-spouse","Armed-Forces","Other-relative","Amer-Indian-Eskimo","Male",0,0,48,"United-States","<=50K" +31,"Private",121308,"11th",7,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",216672,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"State-gov",158291,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",455361,"9th",5,"Never-married","Other-service","Unmarried","White","Male",0,0,35,"Mexico","<=50K" +54,"Private",225307,"11th",7,"Divorced","Craft-repair","Own-child","White","Female",0,0,50,"United-States",">50K" +36,"Private",286115,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",187830,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +26,"Private",142506,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +47,"Local-gov",148576,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States","<=50K" +36,"Private",185325,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,37,"United-States","<=50K" +32,"Self-emp-not-inc",27939,"Some-college",10,"Married-civ-spouse","Sales","Husband","Amer-Indian-Eskimo","Male",0,0,60,"United-States","<=50K" +21,"Private",383603,"10th",6,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +30,"Private",140790,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +34,"Private",226629,"HS-grad",9,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +51,"Private",228516,"HS-grad",9,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,45,"Columbia","<=50K" +55,"Self-emp-not-inc",119762,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +43,"Private",299197,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",149297,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Amer-Indian-Eskimo","Male",0,0,30,"United-States","<=50K" +28,"Local-gov",202558,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Private",175232,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Self-emp-not-inc",157473,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"?",409842,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +26,"Private",105787,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,36,"United-States","<=50K" +21,"Private",205838,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,37,"United-States","<=50K" +23,"Private",115326,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +17,"Private",186890,"10th",6,"Married-civ-spouse","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +23,"Local-gov",304386,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",24529,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Male",0,0,15,"United-States","<=50K" +33,"Private",183557,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",342730,"Assoc-acdm",12,"Separated","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +56,"Self-emp-not-inc",67841,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",351381,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",190027,"10th",6,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +41,"Private",343944,"11th",7,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +46,"Self-emp-inc",110457,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +47,"State-gov",72333,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",193494,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +35,"Private",334999,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +44,"Self-emp-not-inc",274363,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +44,"Private",187720,"Assoc-voc",11,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +57,"Private",104996,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +24,"Private",214555,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",52963,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +25,"Private",75821,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +33,"Private",123291,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,84,"United-States",">50K" +50,"Local-gov",226497,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,52,"United-States",">50K" +36,"Private",166549,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,55,"United-States",">50K" +27,"Private",187746,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",157145,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +30,"Private",227551,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +90,"Private",115306,"Masters",14,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Private",169249,"HS-grad",9,"Separated","Other-service","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +34,"State-gov",221966,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +39,"Private",224566,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +19,"Private",28119,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,4,"United-States","<=50K" +19,"Private",323810,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",210498,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",161141,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States","<=50K" +44,"Private",210534,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +34,"Self-emp-not-inc",112650,"7th-8th",4,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"State-gov",318891,"Assoc-acdm",12,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Local-gov",375655,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",228465,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +33,"?",102130,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",34037,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",116613,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,50,"United-States","<=50K" +25,"Private",175540,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +36,"Private",176634,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,35,"United-States",">50K" +36,"Private",209993,"1st-4th",2,"Widowed","Other-service","Other-relative","White","Female",0,0,20,"Mexico","<=50K" +25,"Local-gov",206002,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",201259,"11th",7,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +26,"Local-gov",202286,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",578377,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +53,"Local-gov",324021,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",107737,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +41,"State-gov",129865,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +53,"Private",103586,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,55,"United-States","<=50K" +23,"Private",187513,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,32,"United-States","<=50K" +28,"Private",172891,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +53,"Local-gov",207449,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",209103,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,20,"United-States",">50K" +33,"Private",408813,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +27,"Private",209292,"HS-grad",9,"Never-married","Sales","Other-relative","Black","Female",0,0,32,"Dominican-Republic","<=50K" +31,"Private",209538,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,55,"United-States","<=50K" +27,"Private",244402,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +37,"Self-emp-not-inc",298444,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",163237,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +18,"Private",311795,"12th",8,"Never-married","Sales","Own-child","Black","Female",0,0,20,"United-States","<=50K" +42,"Private",155972,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Private",291783,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",153535,"HS-grad",9,"Divorced","Handlers-cleaners","Unmarried","Black","Female",0,0,36,"United-States","<=50K" +43,"Private",249771,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Asian-Pac-Islander","Male",0,0,99,"United-States","<=50K" +31,"Private",308540,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",34701,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Federal-gov",106252,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +54,"Private",138944,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States","<=50K" +37,"Private",140713,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"Jamaica",">50K" +26,"Private",162312,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Male",0,0,20,"Philippines","<=50K" +59,"Self-emp-inc",253062,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +36,"Federal-gov",359249,"Some-college",10,"Separated","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",231413,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Local-gov",197054,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",130931,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",30565,"HS-grad",9,"Married-AF-spouse","Other-service","Wife","White","Female",0,0,40,"United-States",">50K" +48,"Private",105138,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +30,"Local-gov",178383,"Some-college",10,"Separated","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",196403,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,10,"United-States",">50K" +44,"Private",232421,"HS-grad",9,"Married-spouse-absent","Transport-moving","Not-in-family","Other","Male",0,0,32,"Canada","<=50K" +30,"Private",130369,"Assoc-voc",11,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +68,"Self-emp-not-inc",336329,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,10,"United-States","<=50K" +26,"Local-gov",337867,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,40,"United-States","<=50K" +26,"Local-gov",104614,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Private",223548,"1st-4th",2,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +48,"Private",64479,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,47,"United-States","<=50K" +55,"Private",284095,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +50,"Self-emp-not-inc",221336,"Some-college",10,"Divorced","Exec-managerial","Unmarried","Asian-Pac-Islander","Female",0,0,40,"?","<=50K" +52,"Private",208302,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,36,"United-States","<=50K" +24,"?",412156,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"Mexico","<=50K" +54,"Local-gov",129972,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,38,"United-States",">50K" +31,"Self-emp-not-inc",186420,"Masters",14,"Separated","Tech-support","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +31,"Self-emp-inc",203488,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +47,"Private",128796,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",55395,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +46,"State-gov",314770,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,48,"United-States","<=50K" +45,"Private",135044,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",319248,"10th",6,"Never-married","Other-service","Unmarried","White","Female",0,0,25,"Mexico","<=50K" +34,"Local-gov",236415,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,18,"United-States","<=50K" +19,"?",133983,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +56,"Private",81220,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"Canada","<=50K" +47,"Private",151087,"HS-grad",9,"Separated","Prof-specialty","Other-relative","Other","Female",0,0,40,"Puerto-Rico","<=50K" +35,"Private",322171,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States",">50K" +25,"Private",190628,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Columbia","<=50K" +43,"Local-gov",106982,"Bachelors",13,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +59,"Private",227856,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,37,"United-States",">50K" +66,"?",213477,"7th-8th",4,"Divorced","?","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +63,"Private",266083,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +32,"Private",257068,"Some-college",10,"Married-spouse-absent","Transport-moving","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +58,"?",37591,"Bachelors",13,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-inc",150533,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Other-relative","White","Male",0,0,50,"United-States",">50K" +27,"Private",211184,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,52,"United-States","<=50K" +21,"Private",136610,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,32,"United-States","<=50K" +44,"Federal-gov",244054,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,60,"United-States",">50K" +40,"Self-emp-not-inc",240698,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +65,"Private",172906,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +50,"Private",238959,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +18,"?",163085,"HS-grad",9,"Separated","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +51,"State-gov",172022,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +44,"Federal-gov",218062,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +20,"Private",201799,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,13,"United-States","<=50K" +29,"Private",150717,"Assoc-voc",11,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",94391,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Private",156771,"10th",6,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",216639,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",82161,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"?",159159,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,30,"United-States","<=50K" +58,"Self-emp-not-inc",310014,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,25,"United-States","<=50K" +50,"State-gov",133014,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",36214,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States",">50K" +21,"Private",399022,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,24,"United-States","<=50K" +33,"Private",179758,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,20,"United-States","<=50K" +52,"Private",48947,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +47,"Private",201865,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",155151,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",24106,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Philippines",">50K" +31,"Private",257863,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +19,"?",28967,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",379393,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +45,"Self-emp-not-inc",152752,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,3,"United-States","<=50K" +27,"Private",154210,"11th",7,"Married-spouse-absent","Sales","Own-child","Asian-Pac-Islander","Male",0,0,35,"India","<=50K" +37,"Private",335716,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",94744,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,20,"United-States","<=50K" +24,"Private",240137,"1st-4th",2,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,55,"Mexico","<=50K" +39,"Private",80004,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",109702,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +62,"Self-emp-not-inc",39610,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,80,"United-States","<=50K" +24,"Private",90046,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",193855,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +46,"Private",206889,"Bachelors",13,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +44,"Private",86298,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",323139,"Bachelors",13,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +44,"Private",237993,"Prof-school",15,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"?","<=50K" +24,"Private",36058,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +61,"Private",163393,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,20,"United-States","<=50K" +45,"Local-gov",93535,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",112952,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,48,"United-States","<=50K" +26,"Local-gov",73392,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Amer-Indian-Eskimo","Male",0,0,30,"United-States","<=50K" +40,"?",507086,"HS-grad",9,"Divorced","?","Not-in-family","Black","Female",0,0,32,"United-States","<=50K" +25,"?",39901,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,60,"United-States","<=50K" +31,"Local-gov",33124,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +55,"Private",419732,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,38,"United-States","<=50K" +46,"Private",171095,"Assoc-acdm",12,"Divorced","Sales","Unmarried","White","Female",0,0,38,"United-States","<=50K" +58,"Private",199278,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +56,"Private",235205,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Federal-gov",168232,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,55,"United-States",">50K" +24,"Private",145964,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States",">50K" +35,"Local-gov",72338,"HS-grad",9,"Divorced","Farming-fishing","Own-child","Asian-Pac-Islander","Male",0,0,56,"United-States","<=50K" +51,"Private",153870,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",198830,"11th",7,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,10,"United-States","<=50K" +21,"Private",267040,"10th",6,"Never-married","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +45,"Private",167187,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +56,"Private",659558,"12th",8,"Widowed","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +39,"Private",181661,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",186144,"7th-8th",4,"Never-married","Machine-op-inspct","Not-in-family","Other","Female",0,0,40,"Mexico","<=50K" +20,"Federal-gov",178517,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",57233,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +33,"Private",379798,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",122175,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +38,"Private",107302,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +33,"Self-emp-not-inc",102884,"Bachelors",13,"Married-civ-spouse","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +49,"Self-emp-not-inc",241753,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",173611,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",232666,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",352207,"Assoc-voc",11,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +37,"Self-emp-not-inc",241998,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,5,"United-States",">50K" +52,"Private",279129,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,37,"United-States",">50K" +27,"Private",177057,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",251603,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Federal-gov",19914,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","Asian-Pac-Islander","Female",0,0,40,"Philippines",">50K" +61,"Private",115023,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",101709,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +21,"Private",313702,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +63,"Private",250068,"12th",8,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",227359,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,42,"United-States","<=50K" +21,"State-gov",196827,"Assoc-acdm",12,"Never-married","Tech-support","Own-child","White","Male",0,0,10,"United-States","<=50K" +44,"Private",118550,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,33,"United-States","<=50K" +26,"Private",285004,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Male",0,0,35,"South","<=50K" +36,"Private",280169,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +39,"Private",144608,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"?",">50K" +52,"Private",76860,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Asian-Pac-Islander","Male",0,0,8,"Philippines","<=50K" +44,"Self-emp-not-inc",167280,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",334783,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +60,"?",141580,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Private",226443,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",366065,"Some-college",10,"Never-married","Craft-repair","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",225724,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,25,"United-States","<=50K" +81,"State-gov",132204,"1st-4th",2,"Widowed","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +38,"Private",197711,"10th",6,"Divorced","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Portugal","<=50K" +21,"Private",30619,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +28,"Local-gov",335015,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",61272,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",106544,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",144169,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",40295,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,99,"United-States","<=50K" +57,"Private",143030,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,30,"?","<=50K" +42,"State-gov",192397,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Female",0,0,38,"United-States","<=50K" +43,"Private",114351,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +48,"?",63466,"HS-grad",9,"Married-spouse-absent","?","Unmarried","White","Female",0,0,32,"United-States","<=50K" +53,"Private",132304,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"Scotland","<=50K" +58,"Private",128162,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +19,"Private",125938,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,40,"El-Salvador","<=50K" +37,"Private",170174,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,46,"United-States",">50K" +41,"Self-emp-not-inc",203451,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +31,"Private",109917,"7th-8th",4,"Separated","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",114937,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States","<=50K" +53,"Local-gov",231196,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",238474,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,25,"United-States","<=50K" +56,"Private",314149,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +55,"Federal-gov",31728,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +51,"Private",360131,"5th-6th",3,"Married-civ-spouse","Craft-repair","Other-relative","White","Female",0,0,40,"United-States","<=50K" +62,"Private",141308,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",83411,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +45,"?",119835,"7th-8th",4,"Divorced","?","Not-in-family","Amer-Indian-Eskimo","Male",0,0,48,"United-States","<=50K" +28,"Local-gov",296537,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +46,"Private",193047,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +62,"State-gov",39630,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Local-gov",213975,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +60,"Local-gov",259803,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +23,"Federal-gov",55465,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",211301,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,8,"United-States","<=50K" +51,"Private",200450,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,48,"United-States","<=50K" +61,"Local-gov",176731,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +76,"Private",125784,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",152176,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,39,"United-States","<=50K" +31,"Self-emp-not-inc",111423,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +58,"Federal-gov",30111,"Some-college",10,"Widowed","Prof-specialty","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +19,"Private",272800,"12th",8,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +44,"Private",195881,"Some-college",10,"Divorced","Exec-managerial","Other-relative","White","Female",0,0,45,"United-States","<=50K" +41,"Local-gov",170924,"Some-college",10,"Never-married","Prof-specialty","Other-relative","White","Male",0,0,7,"United-States","<=50K" +21,"Private",131473,"Some-college",10,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,20,"Vietnam","<=50K" +40,"Private",149466,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","Black","Male",0,0,35,"United-States","<=50K" +25,"Private",190418,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,30,"Canada","<=50K" +62,"Local-gov",167889,"Doctorate",16,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,40,"Iran","<=50K" +42,"Private",177989,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",186035,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",195805,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,12,"United-States","<=50K" +60,"Private",54800,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +20,"Private",100605,"HS-grad",9,"Never-married","Sales","Own-child","Other","Male",0,0,40,"Puerto-Rico","<=50K" +23,"Private",253190,"Assoc-acdm",12,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,25,"United-States","<=50K" +18,"Private",203301,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",175696,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +19,"Private",278304,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +51,"Private",93193,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Local-gov",158688,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,50,"United-States","<=50K" +18,"Private",327612,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +41,"Private",210844,"Some-college",10,"Married-spouse-absent","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +27,"Private",147340,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +71,"Self-emp-not-inc",130436,"1st-4th",2,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +25,"Private",206600,"12th",8,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +73,"Private",284680,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +45,"Private",127738,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",213412,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",287927,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,16,"United-States","<=50K" +44,"Private",249332,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Ecuador","<=50K" +44,"Local-gov",290403,"Assoc-voc",11,"Divorced","Protective-serv","Own-child","White","Female",0,0,40,"Cuba","<=50K" +42,"Federal-gov",178470,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",62865,"HS-grad",9,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +66,"Private",107196,"HS-grad",9,"Widowed","Tech-support","Not-in-family","White","Female",0,0,18,"United-States","<=50K" +19,"Private",86860,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,15,"United-States","<=50K" +60,"Private",130684,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +46,"Private",164682,"Assoc-voc",11,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",198316,"Assoc-voc",11,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +59,"Private",261816,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,52,"Outlying-US(Guam-USVI-etc)","<=50K" +47,"Private",97176,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +58,"Private",95835,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,36,"United-States","<=50K" +17,"?",280670,"10th",6,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",136306,"11th",7,"Never-married","Farming-fishing","Own-child","White","Male",0,0,24,"United-States","<=50K" +28,"Private",65171,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,70,"United-States","<=50K" +37,"Private",25864,"HS-grad",9,"Separated","Prof-specialty","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +30,"Private",149531,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",33887,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"Private",106748,"7th-8th",4,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,99,"United-States","<=50K" +45,"Private",131826,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",133328,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",164737,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Local-gov",99064,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"State-gov",59460,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,15,"United-States","<=50K" +27,"Private",208725,"Bachelors",13,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",138513,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",121055,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",149784,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",114495,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"?",133278,"12th",8,"Separated","?","Unmarried","Black","Female",0,0,53,"United-States","<=50K" +32,"Private",212276,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +32,"Private",440129,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,38,"Mexico","<=50K" +27,"Private",145284,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",177147,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",141537,"10th",6,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",48093,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,92,"United-States","<=50K" +23,"Local-gov",314819,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Private",123572,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +19,"Private",170800,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,60,"United-States","<=50K" +42,"Private",332401,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",193038,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,15,"United-States","<=50K" +45,"Federal-gov",106910,"HS-grad",9,"Never-married","Transport-moving","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +67,"?",163726,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,49,"United-States","<=50K" +36,"Self-emp-not-inc",609935,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,48,"?","<=50K" +52,"State-gov",314627,"Masters",14,"Divorced","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +28,"Private",115945,"Doctorate",16,"Never-married","Adm-clerical","Own-child","White","Male",0,0,18,"United-States","<=50K" +83,"Self-emp-inc",272248,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +17,"Private",167878,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +27,"Private",176972,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",31095,"Assoc-voc",11,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +40,"Private",130834,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",207415,"Assoc-acdm",12,"Married-civ-spouse","Sales","Wife","White","Female",0,0,25,"United-States","<=50K" +51,"Local-gov",264457,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +51,"Private",340588,"1st-4th",2,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,54,"Mexico","<=50K" +82,"?",42435,"10th",6,"Widowed","?","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +28,"Private",107411,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +53,"Private",290640,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"Germany",">50K" +29,"Private",106179,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"Canada","<=50K" +19,"Private",247679,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +30,"Private",171598,"Bachelors",13,"Married-spouse-absent","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +23,"Private",234460,"7th-8th",4,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,40,"Dominican-Republic","<=50K" +66,"Private",196674,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,15,"United-States",">50K" +27,"Private",182540,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",172694,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +17,"Private",29571,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,15,"United-States","<=50K" +27,"Private",130438,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",213421,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +64,"Private",133144,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,16,"United-States","<=50K" +62,"Self-emp-inc",24050,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +26,"Private",276967,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",184857,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +40,"Private",145160,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",192251,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",190650,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Male",0,0,40,"Taiwan","<=50K" +52,"Local-gov",255927,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +46,"Private",99086,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +30,"Private",216811,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +52,"Private",110563,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",120471,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","Other","Male",0,0,40,"United-States","<=50K" +17,"Private",183066,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +46,"State-gov",298786,"Some-college",10,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +45,"Private",297884,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +18,"Self-emp-not-inc",207438,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +90,"Private",139660,"Some-college",10,"Divorced","Sales","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +23,"Private",165474,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",120277,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Self-emp-not-inc",67929,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,50,"United-States","<=50K" +69,"Private",229418,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Federal-gov",41356,"Assoc-acdm",12,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,32,"United-States","<=50K" +28,"Private",185127,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",0,0,54,"United-States","<=50K" +57,"Private",148315,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +73,"Private",198526,"HS-grad",9,"Widowed","Other-service","Other-relative","White","Female",0,0,32,"United-States","<=50K" +25,"Private",521400,"5th-6th",3,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +33,"Private",100882,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +36,"Private",124818,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",71367,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",303032,"Some-college",10,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +35,"?",98989,"9th",5,"Divorced","?","Own-child","Amer-Indian-Eskimo","Male",0,0,38,"United-States","<=50K" +40,"State-gov",390781,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,0,48,"United-States","<=50K" +32,"Private",54782,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"?",202683,"Bachelors",13,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",213081,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"Jamaica","<=50K" +27,"Self-emp-inc",89718,"Some-college",10,"Separated","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",253262,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",78181,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +20,"Private",158206,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +69,"?",337720,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,24,"United-States","<=50K" +18,"State-gov",391257,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Private",134756,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +40,"Private",183404,"Some-college",10,"Separated","Other-service","Unmarried","White","Female",0,0,8,"United-States","<=50K" +46,"Private",192793,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",203943,"12th",8,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"?","<=50K" +53,"Private",89400,"Some-college",10,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +50,"Private",237868,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",139187,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,50,"United-States","<=50K" +40,"Private",126701,"Bachelors",13,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +54,"Self-emp-inc",172175,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",164210,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Local-gov",608184,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States",">50K" +17,"?",198797,"11th",7,"Never-married","?","Own-child","White","Male",0,0,20,"Peru","<=50K" +50,"Local-gov",425804,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +22,"?",117618,"Bachelors",13,"Never-married","?","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +30,"Private",119164,"Bachelors",13,"Never-married","Other-service","Unmarried","White","Male",0,0,40,"?","<=50K" +40,"Self-emp-inc",92036,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"State-gov",77146,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Self-emp-not-inc",191803,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +29,"Private",54932,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",251694,"Bachelors",13,"Never-married","Farming-fishing","Own-child","White","Male",0,0,50,"United-States","<=50K" +22,"Private",268145,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Private",104842,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,50,"Haiti","<=50K" +60,"Local-gov",227332,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",133436,"7th-8th",4,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"State-gov",309055,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +18,"Private",59202,"HS-grad",9,"Never-married","Priv-house-serv","Other-relative","White","Female",0,0,10,"United-States","<=50K" +31,"Private",117963,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +26,"Private",169121,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States",">50K" +18,"Private",308889,"11th",7,"Never-married","Adm-clerical","Other-relative","Asian-Pac-Islander","Female",0,0,20,"United-States","<=50K" +45,"Local-gov",144940,"Masters",14,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +64,"Private",102041,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",335998,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +53,"Private",29557,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",210313,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,28,"Guatemala","<=50K" +32,"Private",190784,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +59,"Private",97168,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +61,"Self-emp-not-inc",181033,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +41,"?",344572,"HS-grad",9,"Divorced","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +46,"State-gov",170165,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,37,"United-States","<=50K" +32,"Private",178835,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",118230,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +48,"Private",149640,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",30271,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,30,"United-States","<=50K" +21,"Private",154165,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,35,"United-States","<=50K" +50,"Self-emp-not-inc",341797,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Local-gov",145246,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,44,"United-States",">50K" +51,"Private",280093,"HS-grad",9,"Separated","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +42,"Private",373469,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",199172,"Bachelors",13,"Never-married","Protective-serv","Own-child","White","Female",0,0,40,"United-States","<=50K" +70,"Self-emp-not-inc",177199,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,3,"United-States","<=50K" +33,"Private",258932,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",258037,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"?","<=50K" +32,"Private",116677,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",59496,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-inc",34218,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",200246,"9th",5,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +64,"Federal-gov",316246,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +37,"Local-gov",239161,"Some-college",10,"Separated","Protective-serv","Own-child","Other","Male",0,0,52,"United-States","<=50K" +49,"Self-emp-not-inc",173411,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",259226,"11th",7,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,48,"United-States","<=50K" +35,"Local-gov",195516,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"State-gov",160369,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +21,"?",415913,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",147253,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Local-gov",199674,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +29,"State-gov",198493,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",377121,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,25,"United-States","<=50K" +21,"Private",400635,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"?","<=50K" +45,"Private",513660,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"?",175069,"Bachelors",13,"Never-married","?","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +28,"?",78388,"10th",6,"Never-married","?","Own-child","White","Female",0,0,38,"United-States","<=50K" +23,"Private",171705,"HS-grad",9,"Never-married","Sales","Unmarried","White","Female",0,0,48,"United-States","<=50K" +39,"Self-emp-not-inc",315640,"Bachelors",13,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,60,"Iran","<=50K" +68,"Private",192829,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +41,"Private",327606,"12th",8,"Separated","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +48,"Private",34845,"HS-grad",9,"Divorced","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +33,"Private",58582,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",155659,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Local-gov",210029,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +26,"Private",381618,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +35,"State-gov",226789,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,75,"United-States","<=50K" +46,"State-gov",111163,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +72,"?",76860,"HS-grad",9,"Married-civ-spouse","?","Husband","Asian-Pac-Islander","Male",0,0,1,"United-States","<=50K" +18,"Private",92112,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +62,"Local-gov",136787,"HS-grad",9,"Divorced","Transport-moving","Other-relative","White","Male",0,0,40,"United-States","<=50K" +22,"Private",29810,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Female",0,0,30,"United-States","<=50K" +26,"Private",266022,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Private",142874,"Assoc-acdm",12,"Married-spouse-absent","Sales","Own-child","Black","Female",0,0,36,"United-States","<=50K" +25,"Self-emp-not-inc",72338,"HS-grad",9,"Never-married","Sales","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +46,"?",177305,"Assoc-voc",11,"Married-civ-spouse","?","Wife","Black","Female",0,0,35,"United-States",">50K" +41,"Private",424478,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,45,"United-States",">50K" +59,"Private",189721,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Italy",">50K" +37,"Private",34180,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",183279,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States","<=50K" +33,"Private",35309,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +23,"Private",259109,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"Puerto-Rico","<=50K" +39,"Self-emp-inc",172538,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",322547,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +39,"Private",300760,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",0,0,50,"United-States","<=50K" +28,"Private",232782,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",174645,"11th",7,"Divorced","Craft-repair","Unmarried","White","Female",0,0,52,"United-States","<=50K" +43,"Private",164693,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +23,"Private",206861,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,25,"United-States","<=50K" +33,"Self-emp-not-inc",422960,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,60,"United-States",">50K" +45,"Private",116360,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +48,"Private",278530,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",163948,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +63,"Private",64544,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States",">50K" +22,"Private",107882,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,35,"United-States","<=50K" +32,"Self-emp-not-inc",182691,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Male",0,0,60,"United-States","<=50K" +27,"Private",203776,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +22,"Private",201268,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +44,"Private",29762,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,68,"United-States","<=50K" +34,"Private",186346,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",196690,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",194772,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +17,"Private",95446,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +53,"Self-emp-not-inc",257126,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +58,"Private",194733,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Self-emp-not-inc",98361,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +44,"Local-gov",124924,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +40,"Self-emp-not-inc",111971,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +58,"Self-emp-not-inc",130714,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +38,"Private",208358,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",164870,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +37,"Private",220314,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +58,"Local-gov",318537,"12th",8,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",183284,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +46,"Private",109227,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,70,"United-States","<=50K" +34,"Private",118551,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Self-emp-inc",163057,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,99,"United-States","<=50K" +61,"Self-emp-inc",253101,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +30,"Self-emp-not-inc",20098,"Assoc-voc",11,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",196227,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",175374,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Private",234037,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,58,"United-States","<=50K" +47,"Private",341762,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,33,"United-States","<=50K" +20,"Private",174714,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",222835,"Bachelors",13,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +46,"Private",251786,"1st-4th",2,"Separated","Other-service","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +20,"Private",164219,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,45,"United-States","<=50K" +30,"Private",236993,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,30,"United-States","<=50K" +43,"Local-gov",105896,"Some-college",10,"Divorced","Protective-serv","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",211527,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,60,"United-States","<=50K" +34,"Private",317809,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"?",">50K" +25,"Private",185287,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",31014,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +44,"Private",151985,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,24,"United-States",">50K" +26,"Private",89389,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",406051,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,80,"United-States",">50K" +48,"Self-emp-not-inc",171986,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +26,"Private",167848,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",213019,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",211424,"Bachelors",13,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",168981,"Assoc-voc",11,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,55,"United-States","<=50K" +24,"Private",122348,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +31,"Private",139753,"Bachelors",13,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Local-gov",176178,"Assoc-acdm",12,"Never-married","Prof-specialty","Own-child","White","Female",0,0,2,"United-States","<=50K" +41,"Private",145220,"9th",5,"Never-married","Priv-house-serv","Unmarried","White","Female",0,0,40,"Columbia","<=50K" +38,"Local-gov",188612,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +19,"Private",445728,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",318002,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",235722,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"?",367984,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +67,"Private",212705,"Masters",14,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States",">50K" +49,"Private",411273,"10th",6,"Divorced","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",103986,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",203761,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +22,"Private",116800,"Assoc-acdm",12,"Never-married","Protective-serv","Own-child","White","Male",0,0,60,"United-States","<=50K" +21,"State-gov",99199,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,10,"United-States","<=50K" +50,"Private",162327,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Local-gov",100479,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States","<=50K" +36,"Local-gov",32587,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +52,"Private",108914,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Self-emp-not-inc",61343,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,90,"United-States","<=50K" +48,"Local-gov",81154,"Assoc-voc",11,"Never-married","Protective-serv","Unmarried","White","Male",0,0,48,"United-States","<=50K" +37,"Private",225504,"Masters",14,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +44,"Private",176063,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Private",198587,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"State-gov",34965,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,12,"United-States","<=50K" +31,"Self-emp-inc",467108,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +23,"?",263899,"HS-grad",9,"Never-married","?","Own-child","Black","Male",0,0,12,"England","<=50K" +29,"Private",204984,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +53,"Private",217568,"HS-grad",9,"Widowed","Craft-repair","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +52,"Private",48343,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",253354,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"?",258026,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +64,"?",211360,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +55,"Private",191367,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",148995,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +20,"Private",123901,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-inc",32356,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,51,"United-States","<=50K" +17,"Private",206506,"10th",6,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,10,"El-Salvador","<=50K" +38,"Private",218729,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +43,"Private",52498,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States",">50K" +22,"Private",136767,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +63,"Private",219540,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",114059,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +56,"Private",247337,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +43,"State-gov",310969,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States","<=50K" +41,"Private",171546,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +41,"Private",217455,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",410489,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +59,"Private",146391,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +46,"Local-gov",165484,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,44,"United-States",">50K" +23,"Private",184271,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +46,"Self-emp-not-inc",231347,"Some-college",10,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +47,"Private",244025,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Amer-Indian-Eskimo","Male",0,0,56,"Puerto-Rico","<=50K" +46,"Federal-gov",46537,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",205730,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,56,"United-States",">50K" +32,"Private",328199,"Assoc-voc",11,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +90,"Private",84553,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Private",221072,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,49,"?","<=50K" +23,"Private",123983,"Assoc-voc",11,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +76,"?",191024,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States","<=50K" +23,"Private",167868,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",225879,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Other","Female",0,0,30,"Mexico",">50K" +17,"Private",143791,"10th",6,"Never-married","Other-service","Own-child","Black","Female",0,0,12,"United-States","<=50K" +56,"Private",177271,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Federal-gov",129786,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",31339,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +25,"Private",236267,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",130620,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","Asian-Pac-Islander","Female",0,0,35,"Philippines",">50K" +32,"Private",208180,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,24,"United-States",">50K" +25,"Private",292058,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,30,"United-States","<=50K" +29,"Federal-gov",142712,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",119665,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +41,"Private",116825,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +48,"State-gov",201177,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +29,"Private",118337,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +27,"?",173800,"Masters",14,"Never-married","?","Unmarried","Asian-Pac-Islander","Male",0,0,20,"Taiwan","<=50K" +55,"Private",289257,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",140581,"Some-college",10,"Widowed","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +50,"Private",174102,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"Puerto-Rico","<=50K" +22,"Private",316509,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +80,"Local-gov",20101,"HS-grad",9,"Widowed","Other-service","Unmarried","Amer-Indian-Eskimo","Female",0,0,32,"United-States","<=50K" +30,"Private",187279,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,44,"United-States","<=50K" +20,"Private",259496,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +29,"Self-emp-not-inc",181466,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +56,"Private",178202,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Private",188976,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",203027,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"State-gov",142022,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",119033,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",216181,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +47,"Private",178341,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,46,"United-States",">50K" +25,"Local-gov",244408,"Bachelors",13,"Never-married","Tech-support","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +31,"Private",198953,"Some-college",10,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +28,"Private",173110,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",66326,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,99,"United-States","<=50K" +30,"Local-gov",181091,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",133929,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,36,"?","<=50K" +26,"Private",86483,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",167787,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +43,"Private",216697,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Other","Male",0,0,32,"United-States","<=50K" +32,"Local-gov",118457,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +20,"Private",298635,"Some-college",10,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,30,"Philippines","<=50K" +21,"Local-gov",212780,"12th",8,"Never-married","Handlers-cleaners","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +32,"Private",159187,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",237995,"Assoc-voc",11,"Divorced","Machine-op-inspct","Not-in-family","Black","Male",0,0,48,"United-States","<=50K" +45,"Private",160724,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +54,"?",185936,"9th",5,"Divorced","?","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +24,"Private",161198,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +28,"?",113635,"11th",7,"Never-married","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +23,"Private",214542,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"?",172991,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",203761,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",161141,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +71,"Private",180117,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",317396,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",237868,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,5,"United-States","<=50K" +30,"Private",323069,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",309122,"10th",6,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",40024,"11th",7,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +24,"State-gov",184216,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"?",256211,"1st-4th",2,"Never-married","?","Own-child","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +55,"Private",205422,"10th",6,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,40,"United-States","<=50K" +43,"Local-gov",196308,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +28,"Private",389713,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Private",82566,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +47,"Private",199058,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",160440,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +47,"Private",76034,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,57,"United-States",">50K" +60,"Self-emp-not-inc",92845,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",29083,"HS-grad",9,"Never-married","Sales","Own-child","Amer-Indian-Eskimo","Female",0,0,25,"United-States","<=50K" +22,"Private",234474,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,25,"United-States","<=50K" +55,"Local-gov",107308,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",111891,"Some-college",10,"Separated","Sales","Other-relative","Black","Female",0,0,35,"United-States","<=50K" +28,"Federal-gov",188278,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Local-gov",303485,"Some-college",10,"Never-married","Transport-moving","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +39,"Local-gov",67187,"HS-grad",9,"Never-married","Exec-managerial","Own-child","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +43,"State-gov",114508,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",204172,"Bachelors",13,"Never-married","Sales","Other-relative","White","Female",0,0,40,"United-States","<=50K" +27,"Local-gov",162973,"Assoc-voc",11,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +64,"Self-emp-not-inc",192695,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"Canada","<=50K" +41,"Local-gov",89172,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",163320,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +61,"Private",128230,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States","<=50K" +27,"Private",246440,"11th",7,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Private",50567,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +20,"Private",117476,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Local-gov",214881,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",195516,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",218653,"Bachelors",13,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",164647,"Some-college",10,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +19,"Private",129151,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +54,"Private",319697,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",193374,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Private",167864,"Assoc-voc",11,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",197932,"Some-college",10,"Separated","Priv-house-serv","Not-in-family","White","Female",0,0,30,"Guatemala","<=50K" +51,"Private",102904,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,43,"United-States","<=50K" +44,"Private",216907,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +35,"Local-gov",331395,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,42,"United-States","<=50K" +40,"Private",171424,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",35406,"7th-8th",4,"Separated","Other-service","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +25,"Private",238964,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +22,"Private",340543,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",70240,"Some-college",10,"Married-civ-spouse","Sales","Wife","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +18,"Self-emp-not-inc",87169,"HS-grad",9,"Never-married","Farming-fishing","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +43,"Private",253759,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,45,"United-States","<=50K" +46,"Private",194431,"HS-grad",9,"Never-married","Tech-support","Other-relative","White","Male",0,0,40,"United-States","<=50K" +40,"?",170649,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +59,"Private",182460,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +40,"Local-gov",26929,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",399022,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +64,"?",50171,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,10,"United-States","<=50K" +36,"Private",218490,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +48,"Private",164423,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",124436,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +18,"Private",60981,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +17,"Private",70868,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,16,"United-States","<=50K" +36,"Private",150601,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"?","<=50K" +53,"Private",228500,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +36,"State-gov",76767,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,39,"United-States","<=50K" +20,"Private",218178,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",615367,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +34,"Private",150324,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",51264,"11th",7,"Divorced","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +57,"Private",197642,"Some-college",10,"Widowed","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",229895,"10th",6,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",167415,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +51,"Private",166934,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",305597,"HS-grad",9,"Never-married","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +34,"Private",301591,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,35,"United-States","<=50K" +47,"Federal-gov",229646,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Not-in-family","Black","Female",0,0,40,"Puerto-Rico","<=50K" +28,"Self-emp-not-inc",51461,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",206600,"10th",6,"Never-married","Other-service","Not-in-family","White","Male",0,0,24,"Nicaragua","<=50K" +25,"Private",176836,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +50,"Private",33304,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",174051,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +32,"Private",170017,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Private",98466,"10th",6,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,35,"United-States","<=50K" +19,"Private",188864,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +53,"Self-emp-inc",137815,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +21,"Private",43475,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",557236,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",171215,"Masters",14,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"?",52590,"HS-grad",9,"Never-married","?","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +24,"Private",183751,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States","<=50K" +30,"Private",149507,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,42,"United-States","<=50K" +49,"Private",98092,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",123714,"11th",7,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +30,"State-gov",190385,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +51,"Private",334273,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",343440,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",208302,"HS-grad",9,"Divorced","Other-service","Other-relative","White","Male",0,0,30,"United-States","<=50K" +23,"Local-gov",280164,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,32,"United-States","<=50K" +23,"Self-emp-not-inc",174714,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +36,"Private",184655,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +19,"Private",140459,"11th",7,"Never-married","Craft-repair","Other-relative","White","Male",0,0,25,"United-States","<=50K" +53,"Self-emp-not-inc",108815,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +17,"Private",152652,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +69,"Private",269499,"HS-grad",9,"Widowed","Handlers-cleaners","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +46,"Local-gov",33373,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",243674,"HS-grad",9,"Separated","Tech-support","Not-in-family","White","Male",0,0,46,"United-States","<=50K" +40,"Private",225432,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +56,"Private",215839,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"?","<=50K" +29,"Local-gov",195520,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",70092,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +22,"Private",189888,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +28,"Private",64307,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",94235,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,46,"United-States","<=50K" +35,"Private",62333,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",260997,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +17,"Private",146268,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,10,"United-States","<=50K" +39,"Private",147258,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",207948,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +50,"Private",180607,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +56,"Local-gov",104996,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +80,"Self-emp-not-inc",562336,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,20,"United-States","<=50K" +38,"Self-emp-not-inc",334366,"Some-college",10,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,0,15,"United-States","<=50K" +52,"State-gov",142757,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States",">50K" +26,"Local-gov",220656,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Male",0,0,38,"England","<=50K" +43,"Private",96483,"HS-grad",9,"Divorced","Other-service","Own-child","Asian-Pac-Islander","Female",0,0,40,"South","<=50K" +45,"Private",51744,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +41,"Self-emp-inc",114967,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +30,"Private",393965,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +43,"Local-gov",143046,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +44,"Private",209174,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States",">50K" +54,"Private",183248,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",427474,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +18,"Private",338632,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +38,"Private",89559,"Some-college",10,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"Germany","<=50K" +41,"Self-emp-not-inc",32533,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"?",255969,"12th",8,"Never-married","?","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +66,"Self-emp-inc",112376,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +70,"?",346053,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",44915,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,10,"United-States","<=50K" +24,"Local-gov",111450,"10th",6,"Never-married","Craft-repair","Unmarried","Black","Male",0,0,65,"Haiti","<=50K" +61,"Private",171429,"11th",7,"Divorced","Other-service","Unmarried","White","Female",0,0,36,"United-States","<=50K" +35,"Local-gov",190964,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",109005,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +52,"Private",404453,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",163204,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",192256,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +52,"Private",181755,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",183105,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","White","Female",0,0,44,"Cuba","<=50K" +37,"Private",335168,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +38,"Local-gov",86643,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +27,"Private",180262,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",127865,"Masters",14,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",102110,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,30,"United-States",">50K" +38,"Private",152237,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"?",">50K" +22,"Private",202745,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,55,"United-States","<=50K" +40,"Federal-gov",199303,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",266467,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Federal-gov",345259,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,99,"United-States","<=50K" +24,"Private",204935,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +24,"Private",190457,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Private",180138,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +38,"Private",166585,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +42,"Private",29962,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",191129,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",378707,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +48,"Private",240629,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +40,"Private",233320,"7th-8th",4,"Separated","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +57,"Private",29375,"HS-grad",9,"Separated","Sales","Not-in-family","Amer-Indian-Eskimo","Female",0,0,35,"United-States","<=50K" +36,"Local-gov",137314,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States",">50K" +41,"Private",140886,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +90,"Private",226968,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +66,"Private",151793,"7th-8th",4,"Widowed","Other-service","Not-in-family","Black","Female",0,0,10,"United-States","<=50K" +23,"Private",72887,"HS-grad",9,"Never-married","Craft-repair","Own-child","Asian-Pac-Islander","Male",0,0,1,"Vietnam","<=50K" +35,"Private",261646,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,55,"United-States","<=50K" +33,"Private",295589,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,50,"United-States",">50K" +32,"Self-emp-inc",377836,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",56510,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",337696,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",183765,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",107846,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +34,"Local-gov",22641,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +35,"Private",204590,"Assoc-voc",11,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,40,"United-States",">50K" +29,"Private",114801,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",190591,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +33,"State-gov",220066,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,48,"United-States",">50K" +22,"?",228480,"HS-grad",9,"Married-civ-spouse","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +52,"Private",128378,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",157595,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Local-gov",152171,"11th",7,"Never-married","Protective-serv","Own-child","White","Male",0,0,10,"United-States","<=50K" +63,"Private",339755,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"?",">50K" +49,"Private",240841,"7th-8th",4,"Divorced","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +58,"Private",94345,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Self-emp-not-inc",289116,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,50,"United-States","<=50K" +59,"Private",176647,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Self-emp-not-inc",79627,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Local-gov",210781,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,15,"United-States","<=50K" +17,"?",161981,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",493443,"11th",7,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +64,"Private",312242,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,3,"United-States","<=50K" +34,"Private",185408,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +63,"Private",101077,"Assoc-acdm",12,"Married-spouse-absent","Adm-clerical","Other-relative","White","Female",0,0,35,"United-States","<=50K" +51,"Private",147200,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +40,"State-gov",166327,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +55,"Private",178644,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +35,"Private",126675,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,46,"?","<=50K" +30,"Private",158420,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +47,"?",83046,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,18,"United-States","<=50K" +29,"Private",46609,"10th",6,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"?","<=50K" +17,"?",170320,"11th",7,"Never-married","?","Own-child","White","Female",0,0,8,"United-States","<=50K" +55,"Private",141877,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Local-gov",81654,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,56,"United-States",">50K" +50,"Private",177705,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",129497,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +60,"Private",114413,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +53,"Private",189511,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",246431,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +31,"Private",147654,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",443546,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",281751,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +28,"Private",263128,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +26,"Private",292692,"12th",8,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +47,"Self-emp-inc",96798,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,80,"United-States",">50K" +34,"Private",430554,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +42,"Private",317078,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",207400,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",187089,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,42,"United-States",">50K" +38,"Private",238980,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"?",407495,"HS-grad",9,"Married-spouse-absent","?","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +35,"Private",183800,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",287190,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","Black","Male",0,0,35,"United-States","<=50K" +31,"Private",111363,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Self-emp-inc",260938,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +20,"Private",183594,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,50,"United-States","<=50K" +64,"?",49194,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States","<=50K" +20,"?",117618,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",172496,"Masters",14,"Never-married","Tech-support","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +29,"Private",389713,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",174413,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"State-gov",189843,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",198546,"Masters",14,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +21,"Private",82497,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +23,"Private",193090,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +55,"Private",208451,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +42,"?",234277,"HS-grad",9,"Married-spouse-absent","?","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +37,"Private",434097,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +20,"State-gov",178628,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +53,"Private",96827,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"Canada","<=50K" +34,"Private",154667,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +43,"Private",160246,"Some-college",10,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +24,"Self-emp-not-inc",166036,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +23,"Private",186813,"HS-grad",9,"Never-married","Protective-serv","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +29,"Private",162312,"Assoc-voc",11,"Never-married","Machine-op-inspct","Not-in-family","Other","Male",0,0,40,"United-States","<=50K" +58,"Private",183893,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +40,"Private",111829,"Masters",14,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Federal-gov",175669,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +25,"State-gov",104097,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Local-gov",117618,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,24,"United-States","<=50K" +34,"Self-emp-inc",202450,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Private",109570,"Some-college",10,"Separated","Sales","Unmarried","White","Female",0,0,35,"United-States","<=50K" +60,"Private",101096,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,65,"United-States",">50K" +39,"Private",236391,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +21,"Private",136975,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",240979,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",248612,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,70,"United-States",">50K" +29,"?",153167,"Some-college",10,"Never-married","?","Own-child","Black","Female",0,0,40,"United-States","<=50K" +52,"Private",61735,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",243165,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States",">50K" +24,"Private",388885,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +34,"Self-emp-not-inc",87209,"Masters",14,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +53,"Self-emp-not-inc",168539,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +31,"Private",179013,"HS-grad",9,"Separated","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +58,"Private",196643,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +32,"Private",156464,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",35884,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",182714,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +77,"Private",344425,"9th",5,"Married-civ-spouse","Priv-house-serv","Wife","Black","Female",0,0,10,"United-States","<=50K" +37,"Self-emp-not-inc",177277,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Private",70767,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",520078,"Assoc-acdm",12,"Divorced","Sales","Unmarried","Black","Male",0,0,60,"United-States","<=50K" +53,"Local-gov",321770,"HS-grad",9,"Married-spouse-absent","Transport-moving","Other-relative","White","Female",0,0,35,"United-States","<=50K" +32,"Private",158416,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Private",312667,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",31481,"Bachelors",13,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,24,"United-States","<=50K" +31,"Private",259531,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",186239,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",162954,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +27,"Private",249315,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +21,"Private",308237,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +24,"Private",103064,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",185847,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,54,"United-States","<=50K" +31,"Private",168521,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"Private",198170,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",353628,"10th",6,"Separated","Sales","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +38,"?",273285,"11th",7,"Never-married","?","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +31,"Private",272069,"Assoc-voc",11,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",22328,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",309212,"HS-grad",9,"Divorced","Priv-house-serv","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +25,"Self-emp-inc",148888,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +23,"Local-gov",324637,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +53,"Self-emp-inc",55139,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",252079,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +70,"Private",315868,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"Private",126832,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +18,"Private",126071,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",265706,"Masters",14,"Never-married","Sales","Unmarried","White","Male",0,0,60,"United-States",">50K" +41,"Private",282964,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",328518,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"State-gov",283499,"HS-grad",9,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",286675,"Some-college",10,"Never-married","Exec-managerial","Other-relative","White","Male",0,0,40,"United-States","<=50K" +56,"Private",136472,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,48,"United-States","<=50K" +36,"Private",132879,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,45,"United-States","<=50K" +26,"Private",314798,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +62,"Private",143943,"Bachelors",13,"Widowed","Tech-support","Unmarried","White","Female",0,0,7,"United-States","<=50K" +35,"Private",134367,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Local-gov",366796,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",195573,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +21,"Private",33616,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +31,"Private",164190,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",380281,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Male",0,0,25,"Columbia","<=50K" +58,"Self-emp-inc",190763,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Local-gov",209535,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Private",156003,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",198790,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,30,"United-States","<=50K" +27,"Private",236481,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,10,"India","<=50K" +55,"Private",143266,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Male",0,0,25,"United-States","<=50K" +53,"Private",192386,"HS-grad",9,"Separated","Transport-moving","Unmarried","White","Male",0,0,45,"United-States","<=50K" +23,"Private",99543,"12th",8,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,46,"United-States","<=50K" +66,"Private",169435,"HS-grad",9,"Widowed","Craft-repair","Not-in-family","White","Male",0,0,16,"United-States","<=50K" +34,"Self-emp-not-inc",34572,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +39,"Private",119272,"10th",6,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",211601,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +26,"Private",154785,"Some-college",10,"Married-spouse-absent","Adm-clerical","Own-child","Other","Female",0,0,35,"United-States","<=50K" +21,"Private",213041,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"Cuba","<=50K" +59,"Private",229939,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",175331,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",226443,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",46561,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",161311,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,30,"United-States","<=50K" +50,"Private",98215,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"Local-gov",181242,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",356238,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","White","Female",0,0,80,"United-States",">50K" +28,"Private",315287,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","Black","Male",0,0,40,"?","<=50K" +63,"Private",34098,"10th",6,"Widowed","Farming-fishing","Unmarried","White","Female",0,0,56,"United-States","<=50K" +48,"Private",50880,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Germany","<=50K" +41,"Federal-gov",356934,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,44,"United-States",">50K" +26,"Private",276309,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Black","Female",0,0,20,"United-States","<=50K" +29,"Self-emp-not-inc",164607,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",224462,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",92863,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +27,"Private",179565,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +59,"Self-emp-not-inc",31137,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +19,"Private",199495,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",175262,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +37,"Private",220585,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Local-gov",231793,"Doctorate",16,"Married-spouse-absent","Prof-specialty","Unmarried","White","Female",0,0,38,"United-States","<=50K" +34,"Federal-gov",191342,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,38,"United-States","<=50K" +30,"Private",186420,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +30,"Private",328242,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Hong",">50K" +56,"Private",279340,"11th",7,"Separated","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",174478,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"Private",151771,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",120326,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",246439,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +27,"Private",144133,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Other-relative","White","Male",0,0,50,"United-States","<=50K" +44,"Local-gov",145522,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",312055,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",235847,"Some-college",10,"Never-married","Exec-managerial","Other-relative","White","Female",0,0,50,"United-States","<=50K" +37,"Private",187748,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",396482,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +20,"Private",39477,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +37,"Private",143058,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",216867,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"Mexico","<=50K" +44,"Private",230592,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +30,"Local-gov",40338,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Local-gov",115457,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",374983,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",285419,"12th",8,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"?",385901,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,22,"United-States","<=50K" +45,"State-gov",187581,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-inc",299036,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +42,"Private",68729,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +27,"Private",333990,"Assoc-voc",11,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"Private",117767,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,25,"United-States","<=50K" +43,"Private",184378,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States","<=50K" +21,"Private",232591,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",143851,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",89622,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,80,"United-States",">50K" +34,"Private",202498,"12th",8,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Dominican-Republic","<=50K" +72,"Private",268861,"7th-8th",4,"Widowed","Other-service","Not-in-family","White","Female",0,0,99,"?","<=50K" +54,"Private",343242,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,44,"United-States",">50K" +30,"Private",460408,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +63,"Private",205246,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",230329,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Private",197871,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +72,"?",201375,"Assoc-acdm",12,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Private",194290,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",191814,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +41,"Private",95168,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +20,"?",137876,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",386136,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",152529,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +35,"Private",214891,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Other","Male",0,0,40,"Dominican-Republic","<=50K" +18,"Private",133654,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"Private",147548,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +57,"Private",73051,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",60166,"1st-4th",2,"Never-married","Exec-managerial","Not-in-family","Amer-Indian-Eskimo","Male",0,0,65,"United-States","<=50K" +25,"Self-emp-inc",454934,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +64,"?",338355,"Assoc-voc",11,"Married-civ-spouse","?","Wife","White","Female",0,0,15,"United-States","<=50K" +35,"Self-emp-not-inc",185621,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +61,"Private",101500,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"State-gov",36397,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +18,"Private",276540,"12th",8,"Never-married","Sales","Own-child","Black","Female",0,0,15,"United-States","<=50K" +21,"Private",293968,"Some-college",10,"Married-spouse-absent","Sales","Own-child","Black","Female",0,0,20,"United-States","<=50K" +43,"?",35523,"Assoc-acdm",12,"Divorced","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +32,"Local-gov",186993,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",232132,"12th",8,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +48,"Private",176917,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +40,"Private",105936,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"?",34506,"Some-college",10,"Separated","?","Unmarried","White","Female",0,0,25,"United-States","<=50K" +42,"Private",178074,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"?",116961,"7th-8th",4,"Widowed","?","Unmarried","White","Female",0,0,20,"United-States","<=50K" +34,"Private",191930,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",130807,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",94100,"Bachelors",13,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +65,"Self-emp-not-inc",144822,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +61,"Self-emp-inc",102191,"Masters",14,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,99,"United-States","<=50K" +18,"Private",90934,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,28,"United-States","<=50K" +49,"?",296892,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +48,"Private",173243,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +30,"Private",189759,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +68,"Self-emp-not-inc",69249,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",133061,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,80,"United-States","<=50K" +65,"Self-emp-not-inc",175202,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,24,"United-States","<=50K" +32,"Private",27051,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,44,"United-States","<=50K" +44,"Private",60414,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Local-gov",317360,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +24,"Private",258298,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +58,"Private",174040,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Local-gov",177566,"Some-college",10,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",0,0,50,"Germany","<=50K" +54,"Private",162238,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +35,"Private",87556,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +35,"Private",144322,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +24,"Private",190015,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",151322,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Local-gov",47392,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",107125,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +49,"Private",265295,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",189219,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Female",0,0,16,"United-States","<=50K" +56,"Private",147989,"Some-college",10,"Married-spouse-absent","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",185732,"11th",7,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",153516,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"?",191910,"Some-college",10,"Never-married","?","Other-relative","White","Male",0,0,40,"United-States","<=50K" +33,"Private",216145,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",202872,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,12,"United-States","<=50K" +62,"Self-emp-not-inc",39630,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States","<=50K" +24,"?",114292,"9th",5,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Local-gov",206721,"Bachelors",13,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Private",358585,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States",">50K" +33,"Private",377283,"Bachelors",13,"Separated","Sales","Not-in-family","White","Female",0,0,50,"United-States",">50K" +65,"?",76043,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,1,"United-States",">50K" +43,"Local-gov",223861,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",163455,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",183892,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",47022,"HS-grad",9,"Widowed","Handlers-cleaners","Other-relative","White","Female",0,0,48,"United-States","<=50K" +55,"Federal-gov",145401,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",387074,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Federal-gov",195467,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"Local-gov",170217,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",156807,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,10,"United-States","<=50K" +38,"Private",273640,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",191177,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-inc",184787,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +37,"State-gov",239409,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +63,"Self-emp-not-inc",404547,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +27,"State-gov",23740,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","Amer-Indian-Eskimo","Male",0,0,38,"United-States",">50K" +20,"Private",382153,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,25,"United-States","<=50K" +21,"?",228424,"10th",6,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",168539,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",189530,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",89419,"Assoc-voc",11,"Divorced","Other-service","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"Columbia","<=50K" +35,"Private",224512,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +21,"?",314645,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +65,"Private",85787,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Local-gov",279881,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +24,"Private",141040,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",222294,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +70,"?",410980,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,10,"United-States",">50K" +52,"Private",38795,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States",">50K" +64,"Private",182979,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",223277,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Federal-gov",160647,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",45796,"12th",8,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",110597,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +33,"Private",166961,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +52,"Private",318975,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"Cuba","<=50K" +49,"Private",305657,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",120857,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,18,"United-States","<=50K" +62,"Self-emp-not-inc",158712,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,6,"United-States","<=50K" +44,"Private",304530,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +68,"Local-gov",233954,"Masters",14,"Widowed","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States",">50K" +40,"Federal-gov",26880,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +46,"Private",70754,"7th-8th",4,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +22,"Private",184665,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",245372,"Bachelors",13,"Divorced","Tech-support","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +62,"Private",252668,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +37,"Private",86551,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Private",106900,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,68,"United-States","<=50K" +41,"Private",204235,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Local-gov",127772,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +26,"Private",117217,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +48,"Federal-gov",215389,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States",">50K" +21,"Private",198050,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +44,"Private",377018,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Private",99894,"10th",6,"Married-civ-spouse","Sales","Wife","Asian-Pac-Islander","Female",0,0,30,"Japan",">50K" +25,"Private",170786,"9th",5,"Never-married","Transport-moving","Other-relative","White","Male",0,0,40,"United-States","<=50K" +32,"Local-gov",250585,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +47,"Private",198769,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States",">50K" +26,"Private",306513,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",109307,"Assoc-voc",11,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Federal-gov",106982,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States",">50K" +55,"Self-emp-not-inc",396878,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,25,"United-States","<=50K" +23,"Private",344278,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,25,"United-States","<=50K" +29,"Private",107812,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +48,"Private",185143,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",143068,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +46,"Private",266337,"Assoc-voc",11,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +34,"Private",321787,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"State-gov",21306,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"Germany","<=50K" +18,"Private",271935,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +18,"Private",148952,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,24,"United-States","<=50K" +42,"Private",196626,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"?",108082,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",199439,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +20,"?",304076,"11th",7,"Never-married","?","Own-child","Black","Female",0,0,20,"United-States","<=50K" +52,"Self-emp-inc",81436,"Prof-school",15,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Self-emp-inc",352971,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +53,"Private",375134,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +36,"Private",206521,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +27,"Private",330466,"Bachelors",13,"Never-married","Tech-support","Other-relative","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +52,"Private",208302,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"United-States","<=50K" +60,"Self-emp-not-inc",135285,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",171615,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +64,"Self-emp-not-inc",149698,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",71351,"1st-4th",2,"Never-married","Other-service","Other-relative","White","Male",0,0,25,"El-Salvador","<=50K" +63,"Private",84737,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +54,"Local-gov",375134,"Assoc-voc",11,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",207103,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",199314,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"Poland","<=50K" +37,"Private",240837,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +22,"Private",283499,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +54,"Private",97778,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",21698,"10th",6,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +60,"Local-gov",232618,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",175820,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +25,"Local-gov",63996,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Local-gov",182985,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +47,"Federal-gov",380127,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",111483,"10th",6,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +18,"?",31008,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +57,"Private",96346,"HS-grad",9,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,57,"United-States","<=50K" +22,"Private",317528,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,34,"United-States","<=50K" +36,"State-gov",223020,"Some-college",10,"Divorced","Other-service","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +39,"Private",115076,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",133969,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Other","Male",0,0,50,"United-States",">50K" +41,"Private",173858,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +35,"Private",193241,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,38,"United-States","<=50K" +30,"Private",178841,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Self-emp-not-inc",321865,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States",">50K" +34,"Self-emp-not-inc",321709,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +22,"Private",166371,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"?","<=50K" +18,"Private",210574,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +33,"Self-emp-inc",144949,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States","<=50K" +45,"State-gov",90803,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"State-gov",126701,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +40,"Private",178417,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +41,"Self-emp-not-inc",197176,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,75,"United-States",">50K" +22,"Private",117606,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,32,"United-States","<=50K" +52,"Private",349502,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,45,"United-States","<=50K" +45,"Federal-gov",81487,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Puerto-Rico",">50K" +32,"State-gov",169583,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +26,"Private",485117,"Bachelors",13,"Never-married","Transport-moving","Own-child","White","Male",0,0,20,"United-States","<=50K" +24,"Private",35603,"Some-college",10,"Divorced","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +37,"Private",175390,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +49,"Private",184986,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Local-gov",174395,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Private",187711,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",189878,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",224073,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +48,"Private",159726,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States",">50K" +40,"?",65545,"Masters",14,"Divorced","?","Own-child","White","Female",0,0,55,"United-States","<=50K" +35,"Private",202397,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +21,"Private",206681,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +54,"Private",222020,"10th",6,"Divorced","Other-service","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +40,"Private",137304,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +51,"Private",141645,"Some-college",10,"Separated","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",218085,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,50,"United-States","<=50K" +22,"Private",52596,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,8,"United-States","<=50K" +20,"Private",197997,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",191444,"11th",7,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,40,"United-States","<=50K" +21,"Private",40767,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",172577,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +36,"Private",241998,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +48,"Private",212120,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",224424,"12th",8,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"State-gov",214985,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",147098,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"Local-gov",149833,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +80,"Private",252466,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,24,"United-States","<=50K" +59,"State-gov",132717,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",138944,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Self-emp-not-inc",144380,"Some-college",10,"Married-spouse-absent","Prof-specialty","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +69,"Local-gov",660461,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +49,"Private",177211,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Self-emp-inc",31717,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +49,"Private",296849,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Local-gov",193720,"HS-grad",9,"Married-spouse-absent","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +42,"Private",106698,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,32,"United-States","<=50K" +66,"Private",214469,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,13,"United-States","<=50K" +44,"Private",185798,"Assoc-voc",11,"Separated","Craft-repair","Other-relative","White","Male",0,0,48,"United-States",">50K" +26,"Private",333108,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",35210,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"?",335376,"Bachelors",13,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +17,"Private",170455,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,8,"United-States","<=50K" +52,"Private",298215,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +34,"?",93834,"HS-grad",9,"Separated","?","Own-child","White","Female",0,0,8,"United-States","<=50K" +24,"Private",404416,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"?",206916,"Bachelors",13,"Married-spouse-absent","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +65,"Private",143175,"Some-college",10,"Widowed","Sales","Other-relative","White","Female",0,0,45,"United-States","<=50K" +36,"Self-emp-not-inc",409189,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",285750,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,30,"United-States","<=50K" +43,"Private",235556,"Some-college",10,"Married-spouse-absent","Sales","Not-in-family","White","Male",0,0,45,"Mexico","<=50K" +39,"Local-gov",170382,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"England",">50K" +48,"Private",195437,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Local-gov",191130,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",231160,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +36,"Private",47310,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",214635,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,36,"Haiti","<=50K" +50,"Federal-gov",65160,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",263307,"Bachelors",13,"Never-married","Sales","Unmarried","Black","Male",0,0,45,"?","<=50K" +70,"Self-emp-inc",272896,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",232854,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",442035,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",127875,"Bachelors",13,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States",">50K" +40,"Private",283724,"9th",5,"Never-married","Craft-repair","Other-relative","Black","Male",0,0,49,"United-States","<=50K" +21,"?",228649,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +47,"Private",249935,"11th",7,"Divorced","Craft-repair","Own-child","White","Male",0,0,8,"United-States","<=50K" +19,"Private",533147,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +22,"Private",137862,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,16,"United-States","<=50K" +20,"Private",249543,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Female",0,0,16,"United-States","<=50K" +17,"Private",147339,"10th",6,"Never-married","Prof-specialty","Own-child","Other","Female",0,0,15,"United-States","<=50K" +41,"Private",256647,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +20,"?",150084,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +24,"Private",285457,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",303867,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Federal-gov",113597,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +26,"Self-emp-not-inc",151626,"HS-grad",9,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",26145,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",176189,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Federal-gov",497253,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +38,"Self-emp-not-inc",282461,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States",">50K" +21,"Private",225541,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",203488,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,45,"United-States","<=50K" +23,"?",296613,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,32,"United-States","<=50K" +40,"Private",99373,"10th",6,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Local-gov",109705,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",144947,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",617898,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +50,"Private",38310,"7th-8th",4,"Divorced","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +45,"Private",248993,"HS-grad",9,"Married-spouse-absent","Farming-fishing","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +65,"?",149131,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Italy",">50K" +33,"Private",69311,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Federal-gov",143766,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +65,"Private",213477,"Masters",14,"Divorced","Sales","Not-in-family","White","Male",0,0,28,"United-States","<=50K" +24,"Private",275691,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,39,"United-States","<=50K" +26,"Private",59367,"Bachelors",13,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +55,"Private",35551,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +66,"Private",236784,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,8,"Cuba","<=50K" +43,"Local-gov",193755,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",315291,"Bachelors",13,"Never-married","Adm-clerical","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +22,"Private",290504,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",256240,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +69,"?",199591,"Prof-school",15,"Married-civ-spouse","?","Wife","White","Female",0,0,25,"?","<=50K" +27,"Private",178709,"Masters",14,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",187937,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +18,"Never-worked",157131,"11th",7,"Never-married","?","Own-child","White","Female",0,0,10,"United-States","<=50K" +53,"Local-gov",188772,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +26,"Private",157617,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Poland","<=50K" +60,"Private",96099,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",122322,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,60,"United-States","<=50K" +39,"Private",409189,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +45,"Private",175925,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +76,"Self-emp-not-inc",236878,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +19,"Private",216647,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +34,"Private",300681,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"Jamaica",">50K" +54,"Private",327769,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",194723,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Local-gov",31251,"7th-8th",4,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",212506,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",23037,"12th",8,"Never-married","Handlers-cleaners","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",29054,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Private",92733,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +21,"State-gov",184678,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +37,"Federal-gov",32528,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"England",">50K" +35,"Private",73715,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",209212,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,56,"?","<=50K" +41,"Private",287037,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",64667,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",0,0,60,"Vietnam","<=50K" +26,"Self-emp-inc",366662,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,50,"United-States","<=50K" +36,"Local-gov",113337,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,42,"United-States",">50K" +47,"Private",387468,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Scotland",">50K" +51,"Private",384248,"Some-college",10,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,50,"United-States","<=50K" +40,"Self-emp-inc",182629,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"Private",267652,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",410186,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",365411,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,42,"United-States","<=50K" +28,"Private",205337,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Self-emp-not-inc",100999,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +44,"Private",197462,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",191978,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",50178,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",72442,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",248512,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",178140,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,45,"United-States",">50K" +58,"Private",354024,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +35,"Private",143589,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +35,"Private",219902,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",132601,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +38,"Self-emp-not-inc",29430,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",30731,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +66,"Private",210825,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Local-gov",251091,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",219034,"11th",7,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Federal-gov",35723,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +46,"Private",358886,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",248708,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"?",77937,"12th",8,"Divorced","?","Not-in-family","White","Female",0,0,40,"Canada","<=50K" +30,"Private",30063,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,32,"United-States","<=50K" +29,"Private",253799,"12th",8,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,42,"England","<=50K" +60,"?",41553,"Some-college",10,"Widowed","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +24,"Private",59146,"HS-grad",9,"Separated","Sales","Unmarried","White","Female",0,0,48,"United-States","<=50K" +42,"Self-emp-not-inc",343609,"Some-college",10,"Separated","Other-service","Unmarried","Black","Female",0,0,50,"United-States","<=50K" +26,"Private",216010,"HS-grad",9,"Separated","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"Private",164526,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",150958,"5th-6th",3,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,48,"Guatemala","<=50K" +26,"Private",244495,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +23,"Private",199336,"Assoc-voc",11,"Never-married","Craft-repair","Unmarried","White","Male",0,0,50,"United-States","<=50K" +60,"Private",151369,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +49,"Federal-gov",118701,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +46,"Private",219611,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",184568,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Self-emp-not-inc",246891,"Prof-school",15,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +70,"Self-emp-inc",243436,"9th",5,"Divorced","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +44,"Local-gov",68318,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,55,"United-States","<=50K" +58,"Private",56331,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",190591,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","Black","Female",0,0,40,"Jamaica","<=50K" +28,"Private",122540,"10th",6,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +65,"Private",212562,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,20,"United-States","<=50K" +35,"Self-emp-not-inc",112497,"HS-grad",9,"Married-civ-spouse","Craft-repair","Other-relative","White","Male",0,0,35,"Ireland","<=50K" +82,"Private",147729,"5th-6th",3,"Widowed","Other-service","Unmarried","White","Male",0,0,20,"United-States","<=50K" +48,"Self-emp-not-inc",296066,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +42,"Private",306496,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",163894,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +22,"Private",113936,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",316820,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,84,"United-States","<=50K" +17,"Private",53367,"9th",5,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +46,"Self-emp-not-inc",95256,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +59,"Private",127728,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",66686,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"?",186805,"HS-grad",9,"Married-civ-spouse","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +31,"Private",154297,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,24,"United-States","<=50K" +23,"Private",103064,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +63,"Private",440607,"Preschool",1,"Married-civ-spouse","Prof-specialty","Husband","Other","Male",0,0,30,"Mexico","<=50K" +44,"Private",212894,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,55,"United-States",">50K" +30,"Private",167990,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +23,"Private",378460,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +24,"Private",153583,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",114639,"Some-college",10,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,20,"United-States","<=50K" +37,"Private",344480,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States","<=50K" +24,"Private",188300,"11th",7,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",105938,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",217826,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,25,"Jamaica","<=50K" +20,"Private",379525,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,10,"United-States","<=50K" +37,"Private",127918,"Some-college",10,"Never-married","Transport-moving","Unmarried","White","Female",0,0,20,"Puerto-Rico","<=50K" +47,"Federal-gov",27067,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",250038,"9th",5,"Never-married","Farming-fishing","Other-relative","White","Male",0,0,45,"Mexico","<=50K" +60,"Private",308608,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Local-gov",235109,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +33,"State-gov",374905,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +71,"Private",118876,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,14,"United-States","<=50K" +55,"Local-gov",223716,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +85,"Self-emp-not-inc",166027,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +57,"Self-emp-not-inc",275943,"7th-8th",4,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?","<=50K" +25,"Private",109080,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,55,"United-States","<=50K" +58,"Private",104333,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",195876,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",390879,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,36,"United-States","<=50K" +19,"Private",197748,"11th",7,"Divorced","Sales","Unmarried","White","Female",0,0,20,"United-States","<=50K" +40,"Private",442045,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",44216,"HS-grad",9,"Never-married","Protective-serv","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +43,"Federal-gov",114537,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"?",253370,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,35,"United-States",">50K" +19,"Private",274830,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +24,"Private",321763,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +34,"Private",213226,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,65,"United-States",">50K" +22,"Private",167787,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +64,"Self-emp-not-inc",352712,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,55,"United-States","<=50K" +55,"?",316027,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"?","<=50K" +26,"Private",213412,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +80,"Private",202483,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +79,"Local-gov",146244,"Doctorate",16,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",450544,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",195258,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",57929,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +35,"Private",953588,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +43,"Self-emp-inc",155293,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +68,"Private",204082,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +34,"State-gov",216283,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +37,"Private",355856,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Cambodia",">50K" +22,"Private",297380,"HS-grad",9,"Never-married","Sales","Own-child","Black","Female",0,0,40,"United-States","<=50K" +32,"Private",425622,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +65,"Self-emp-not-inc",145628,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",115549,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,60,"United-States","<=50K" +37,"Private",245482,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +40,"Self-emp-inc",142444,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +40,"Private",134026,"11th",7,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"United-States","<=50K" +52,"Private",177366,"HS-grad",9,"Separated","Other-service","Other-relative","White","Female",0,0,20,"United-States","<=50K" +35,"Private",38245,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +62,"Self-emp-not-inc",215944,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +49,"Private",115784,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States","<=50K" +49,"Private",170165,"HS-grad",9,"Divorced","Machine-op-inspct","Other-relative","White","Female",0,0,55,"United-States","<=50K" +45,"Private",116163,"HS-grad",9,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",405644,"1st-4th",2,"Married-spouse-absent","Farming-fishing","Other-relative","White","Male",0,0,77,"Mexico","<=50K" +36,"Local-gov",223433,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,53,"United-States",">50K" +36,"Private",41624,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"Mexico","<=50K" +25,"State-gov",108542,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",212318,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +57,"Private",173090,"HS-grad",9,"Widowed","Sales","Unmarried","White","Female",0,0,32,"United-States","<=50K" +46,"Private",26781,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +59,"Private",31782,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Private",189241,"11th",7,"Married-civ-spouse","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",240467,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +27,"Private",263614,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +29,"Private",74500,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Federal-gov",263502,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Federal-gov",47707,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +26,"Private",231638,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +55,"?",389479,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Private",111128,"HS-grad",9,"Separated","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",152307,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +23,"?",280134,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",609789,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"?","<=50K" +41,"Private",184466,"11th",7,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,55,"United-States","<=50K" +44,"Private",216411,"Assoc-voc",11,"Separated","Prof-specialty","Not-in-family","White","Female",0,0,40,"Dominican-Republic","<=50K" +48,"Self-emp-not-inc",324173,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +43,"Local-gov",598995,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,42,"United-States","<=50K" +57,"Federal-gov",140711,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Local-gov",262241,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +28,"Private",308136,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Private",148590,"10th",6,"Widowed","Craft-repair","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +30,"Private",228406,"HS-grad",9,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",136398,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,50,"Thailand",">50K" +21,"?",305466,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,70,"United-States","<=50K" +50,"Self-emp-inc",175070,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +43,"Self-emp-not-inc",34007,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States",">50K" +33,"Private",121195,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Other","Male",0,0,50,"United-States","<=50K" +23,"Federal-gov",216853,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,25,"United-States","<=50K" +35,"Private",81280,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,65,"Yugoslavia",">50K" +18,"Private",212936,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +21,"?",213055,"Some-college",10,"Never-married","?","Unmarried","Other","Female",0,0,40,"United-States","<=50K" +33,"Local-gov",220430,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,70,"United-States",">50K" +30,"Federal-gov",73514,"Bachelors",13,"Never-married","Exec-managerial","Other-relative","Asian-Pac-Islander","Female",0,0,45,"United-States","<=50K" +21,"Private",307371,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,15,"United-States","<=50K" +36,"Local-gov",380614,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"Germany",">50K" +38,"Private",119992,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",327518,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +24,"Private",220323,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",421633,"Some-college",10,"Divorced","Protective-serv","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +43,"Self-emp-not-inc",35034,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,21,"United-States","<=50K" +62,"?",378239,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,2,"United-States",">50K" +30,"State-gov",270218,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +25,"Private",254933,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",61751,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"United-States","<=50K" +22,"Private",137876,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +26,"Private",222539,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",233856,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","Black","Male",0,0,45,"United-States","<=50K" +22,"Private",203182,"Some-college",10,"Separated","Sales","Unmarried","White","Female",0,0,43,"United-States","<=50K" +28,"Private",221317,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +38,"Private",186934,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +68,"?",351402,"Doctorate",16,"Married-civ-spouse","?","Husband","White","Male",0,0,70,"United-States","<=50K" +40,"Local-gov",179580,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +32,"Private",26803,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,84,"United-States",">50K" +31,"State-gov",59969,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Other-relative","White","Female",0,0,35,"United-States","<=50K" +33,"Private",162930,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"Italy","<=50K" +54,"Self-emp-not-inc",192654,"Bachelors",13,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +63,"Private",117681,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +67,"Self-emp-not-inc",179285,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +47,"Private",217161,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,0,14,"United-States","<=50K" +67,"Self-emp-inc",116517,"Bachelors",13,"Widowed","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +33,"Private",170336,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Other","Female",0,0,19,"United-States","<=50K" +33,"Local-gov",256529,"HS-grad",9,"Separated","Other-service","Own-child","White","Female",0,0,80,"United-States","<=50K" +25,"Local-gov",227886,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",141706,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",361888,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",176101,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,80,"United-States",">50K" +18,"Private",216730,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,12,"United-States","<=50K" +30,"Private",609789,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"Mexico","<=50K" +29,"Private",136017,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +40,"Private",285787,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",160916,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,45,"United-States","<=50K" +42,"Private",227397,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +49,"Self-emp-not-inc",111066,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",189924,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",31740,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",172304,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +72,"?",166253,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,2,"United-States","<=50K" +31,"Private",86492,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States",">50K" +90,"Private",206667,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +27,"Self-emp-not-inc",153546,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +18,"?",189041,"HS-grad",9,"Never-married","?","Other-relative","White","Male",0,0,40,"United-States","<=50K" +27,"Local-gov",151626,"HS-grad",9,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",37302,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"Private",109001,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",195488,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,45,"United-States","<=50K" +43,"Local-gov",216116,"Masters",14,"Separated","Prof-specialty","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +26,"Private",118497,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +48,"Self-emp-not-inc",101233,"Assoc-voc",11,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,15,"United-States","<=50K" +41,"Private",349703,"Assoc-acdm",12,"Married-civ-spouse","Farming-fishing","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +32,"Private",226883,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Germany","<=50K" +23,"Private",214635,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",169672,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States","<=50K" +42,"Private",71458,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",125279,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",197303,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",69251,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +39,"Private",160123,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",137310,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"?","<=50K" +25,"Private",323229,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",102359,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",404661,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",99146,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?",">50K" +38,"Self-emp-not-inc",185325,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Self-emp-not-inc",230268,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-inc",38819,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",380614,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,13,"United-States",">50K" +45,"Private",319637,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +71,"Private",149040,"12th",8,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",320984,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +19,"?",117201,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,22,"United-States","<=50K" +38,"Private",81965,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Local-gov",182302,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",53434,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +48,"Private",216214,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-inc",24127,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,54,"United-States",">50K" +32,"Federal-gov",115066,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",120277,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +57,"Self-emp-not-inc",134286,"Some-college",10,"Separated","Sales","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +55,"Private",26716,"10th",6,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +48,"?",174533,"11th",7,"Separated","?","Unmarried","White","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-inc",175958,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"?","<=50K" +36,"Private",218948,"9th",5,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"?","<=50K" +66,"Private",117746,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",206199,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,40,"United-States","<=50K" +62,"Private",69867,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +31,"Private",109020,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","Other","Male",0,0,40,"United-States","<=50K" +77,"?",158847,"Assoc-voc",11,"Married-spouse-absent","?","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +25,"Private",130302,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",156728,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,56,"United-States","<=50K" +33,"Private",424719,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Federal-gov",217647,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +20,"Private",33087,"Assoc-voc",11,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Federal-gov",241895,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",38455,"10th",6,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",81054,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,25,"United-States","<=50K" +44,"Private",163215,"12th",8,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",156728,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",127930,"HS-grad",9,"Married-spouse-absent","Farming-fishing","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +46,"Federal-gov",227310,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +24,"Private",96844,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,17,"United-States","<=50K" +18,"Private",245199,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",46385,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",186385,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,8,"United-States","<=50K" +55,"Private",252714,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +68,"Private",154897,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +41,"Private",320744,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",102092,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"?",32533,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +45,"Private",278151,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",338290,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",34378,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +43,"Private",91959,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +36,"Private",265881,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +60,"Private",276009,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,30,"Philippines","<=50K" +27,"Private",193898,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +36,"Private",139364,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +47,"State-gov",306473,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",37232,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +19,"State-gov",56424,"12th",8,"Never-married","Transport-moving","Own-child","Black","Male",0,0,20,"United-States","<=50K" +33,"Private",165235,"Bachelors",13,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,35,"Thailand","<=50K" +34,"Private",153326,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",106976,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +57,"Private",109015,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +60,"Private",367695,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Local-gov",156015,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",185132,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +20,"Self-emp-not-inc",188274,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,10,"United-States","<=50K" +24,"State-gov",147719,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,20,"India","<=50K" +31,"Private",414525,"12th",8,"Never-married","Farming-fishing","Not-in-family","Black","Male",0,0,60,"United-States","<=50K" +38,"Private",289148,"HS-grad",9,"Married-spouse-absent","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",176069,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +55,"State-gov",199713,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,15,"United-States","<=50K" +33,"Private",204829,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +52,"Private",155433,"5th-6th",3,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"?","<=50K" +24,"Local-gov",32950,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +46,"Private",233511,"Bachelors",13,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +20,"Private",210781,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +50,"Private",190762,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +22,"Private",83315,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-inc",343872,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,35,"Haiti","<=50K" +46,"Private",185385,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States",">50K" +26,"Private",357933,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +20,"Private",211293,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,14,"United-States","<=50K" +37,"Self-emp-inc",199265,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",202872,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,24,"United-States","<=50K" +22,"Private",195075,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,38,"United-States","<=50K" +41,"Private",187802,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +24,"Private",97212,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +40,"Private",47902,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"State-gov",76767,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,39,"United-States",">50K" +56,"Private",274475,"9th",5,"Widowed","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",105244,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +55,"Local-gov",165695,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +29,"Private",253801,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +37,"Private",305597,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-not-inc",352448,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +26,"Private",242768,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +49,"Self-emp-inc",201080,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +18,"Local-gov",159032,"7th-8th",4,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",149568,"9th",5,"Never-married","Farming-fishing","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +24,"Private",229553,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,20,"?","<=50K" +24,"State-gov",155775,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",120074,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Local-gov",257588,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",177907,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,65,"United-States","<=50K" +40,"Private",309311,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",138975,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +43,"Self-emp-not-inc",187778,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +19,"Private",35865,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +17,"?",151141,"10th",6,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +39,"Private",144688,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,50,"United-States","<=50K" +43,"Private",248094,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +43,"Private",248094,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",213821,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +31,"State-gov",55849,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",121712,"Bachelors",13,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"Private",223127,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",190514,"7th-8th",4,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,75,"United-States","<=50K" +29,"Private",203797,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",105908,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",210526,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +71,"Private",193530,"11th",7,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,75,"United-States","<=50K" +22,"?",22966,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,6,"United-States","<=50K" +21,"Private",43535,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +62,"?",72486,"HS-grad",9,"Married-civ-spouse","?","Husband","Asian-Pac-Islander","Male",0,0,24,"China","<=50K" +22,"?",229997,"Some-college",10,"Married-spouse-absent","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +49,"Private",183013,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",113364,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,20,"United-States","<=50K" +27,"Private",197380,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",298635,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Hong",">50K" +26,"Private",213385,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +30,"?",108464,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",31007,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +26,"Private",35917,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +45,"Private",99385,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"Canada","<=50K" +31,"Private",241885,"HS-grad",9,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,45,"United-States","<=50K" +51,"Private",24344,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Private",149686,"9th",5,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"State-gov",154432,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +29,"Private",331875,"12th",8,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"Dominican-Republic","<=50K" +26,"Private",259585,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,24,"United-States","<=50K" +51,"Private",104748,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +32,"Local-gov",144949,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"State-gov",199512,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",302438,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"?",129155,"11th",7,"Widowed","?","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +49,"Federal-gov",115784,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",96509,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States",">50K" +62,"Private",226733,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Self-emp-inc",244945,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +76,"Private",243768,"5th-6th",3,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +40,"?",351161,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,60,"United-States",">50K" +35,"Private",186934,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",89813,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",184702,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",275291,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,12,"United-States","<=50K" +20,"Private",258298,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +39,"Private",139743,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +20,"Private",103840,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,42,"United-States","<=50K" +28,"Private",274579,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +56,"Federal-gov",156842,"Some-college",10,"Separated","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",101020,"12th",8,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Federal-gov",68729,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +55,"Private",141326,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Self-emp-not-inc",168723,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",213722,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,57,"United-States",">50K" +42,"Private",196797,"HS-grad",9,"Never-married","Transport-moving","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +50,"Self-emp-inc",207246,"Some-college",10,"Separated","Exec-managerial","Unmarried","White","Female",0,0,75,"United-States","<=50K" +34,"Federal-gov",199934,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States",">50K" +23,"Private",272185,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,33,"United-States","<=50K" +27,"?",190650,"Bachelors",13,"Never-married","?","Unmarried","Asian-Pac-Islander","Male",0,0,25,"Philippines","<=50K" +81,"?",147097,"Bachelors",13,"Widowed","?","Not-in-family","White","Male",0,0,5,"United-States","<=50K" +57,"Private",96779,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +65,"?",117162,"Assoc-voc",11,"Married-civ-spouse","?","Wife","White","Female",0,0,56,"United-States",">50K" +33,"Private",188352,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +37,"Private",359131,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,48,"United-States","<=50K" +53,"Private",198824,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"State-gov",68393,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",115613,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +42,"Private",45363,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +58,"Local-gov",292379,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",482732,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,24,"United-States","<=50K" +19,"Private",198663,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +39,"Private",230329,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +51,"Private",29887,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +52,"Private",194259,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"Germany","<=50K" +53,"Private",126368,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States",">50K" +50,"Private",108446,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",220696,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",32008,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,72,"United-States","<=50K" +30,"Private",191777,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"?","<=50K" +50,"Private",185846,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +76,"Private",127016,"7th-8th",4,"Widowed","Priv-house-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",157894,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +23,"Local-gov",212803,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +51,"Private",168660,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +58,"Private",234481,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",131461,"9th",5,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,24,"Haiti","<=50K" +45,"Private",408773,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Self-emp-not-inc",126117,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",155489,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +42,"Private",296749,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +44,"State-gov",185832,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,46,"United-States",">50K" +60,"Private",43235,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",213152,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Local-gov",334267,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +61,"?",253101,"Bachelors",13,"Divorced","?","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +63,"Private",71800,"7th-8th",4,"Widowed","Other-service","Not-in-family","White","Female",0,0,41,"United-States","<=50K" +46,"Local-gov",170092,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +47,"Private",198223,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",359796,"Some-college",10,"Divorced","Sales","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +43,"Private",110556,"HS-grad",9,"Separated","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +46,"Private",196858,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +48,"?",112860,"10th",6,"Married-civ-spouse","?","Wife","Black","Female",0,0,35,"United-States","<=50K" +61,"Self-emp-not-inc",224784,"Assoc-acdm",12,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Female",0,0,90,"United-States","<=50K" +44,"Private",221172,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +54,"Private",256916,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"Private",157332,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +47,"Federal-gov",192894,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,50,"United-States",">50K" +18,"Private",240183,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +25,"Private",204338,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +24,"Private",122166,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"Iran","<=50K" +37,"Local-gov",397877,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Private",171015,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,34,"United-States","<=50K" +46,"Private",91262,"Some-college",10,"Married-spouse-absent","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +45,"Local-gov",127678,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States",">50K" +19,"Private",263338,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +22,"Private",129508,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,28,"United-States","<=50K" +41,"Private",192107,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",93930,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Federal-gov",207537,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +22,"Private",138542,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,35,"United-States","<=50K" +29,"Self-emp-not-inc",116207,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,65,"United-States",">50K" +22,"Private",198244,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,39,"United-States","<=50K" +23,"Private",211160,"12th",8,"Married-civ-spouse","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",161478,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +59,"Private",144071,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Private",342121,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",124692,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",147236,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",145175,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",259323,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",154978,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Guatemala","<=50K" +60,"?",163946,"9th",5,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",127768,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Private",98588,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",192894,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",194848,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",34446,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +23,"Local-gov",177265,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,45,"United-States","<=50K" +30,"Private",142977,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +45,"Private",241350,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,48,"United-States",">50K" +30,"Private",154882,"Prof-school",15,"Widowed","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +17,"Private",60562,"9th",5,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +22,"Private",142566,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",176162,"Bachelors",13,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",237671,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States",">50K" +18,"?",184416,"10th",6,"Never-married","?","Own-child","Black","Male",0,0,30,"United-States","<=50K" +58,"Private",68624,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Private",229504,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",262208,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Female",0,0,30,"Jamaica","<=50K" +26,"Private",236008,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Local-gov",214284,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","Asian-Pac-Islander","Female",0,0,10,"Japan","<=50K" +33,"Private",169496,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +21,"?",205940,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",195179,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,24,"United-States","<=50K" +25,"Private",469697,"Some-college",10,"Married-civ-spouse","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"?",140242,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +44,"Private",214415,"Some-college",10,"Separated","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",452283,"HS-grad",9,"Divorced","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",244172,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",231972,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +37,"Private",412296,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"Mexico",">50K" +32,"Private",30497,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",189216,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +36,"Private",268292,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,41,"United-States","<=50K" +38,"Private",69306,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +57,"State-gov",111224,"Bachelors",13,"Divorced","Machine-op-inspct","Not-in-family","Black","Male",0,0,39,"United-States","<=50K" +22,"State-gov",309348,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +80,"?",174995,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"Canada","<=50K" +20,"Private",210781,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +40,"Private",286750,"11th",7,"Separated","Machine-op-inspct","Not-in-family","Black","Male",0,0,36,"United-States","<=50K" +36,"Self-emp-not-inc",321274,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",192936,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +52,"Private",72743,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +43,"Private",187861,"HS-grad",9,"Separated","Transport-moving","Unmarried","White","Female",0,0,44,"United-States","<=50K" +35,"Private",179579,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",663394,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",302422,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"?",154373,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,25,"United-States","<=50K" +49,"Local-gov",37353,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Self-emp-not-inc",109609,"Some-college",10,"Separated","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +47,"Private",184402,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +20,"Private",224640,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",405526,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",147884,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"Private",164231,"11th",7,"Separated","Prof-specialty","Own-child","White","Male",0,0,35,"United-States","<=50K" +25,"Private",383306,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",417668,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,36,"United-States","<=50K" +25,"Private",161007,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +63,"State-gov",99823,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,32,"United-States","<=50K" +25,"Private",37379,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +28,"Private",148645,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Private",180477,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States",">50K" +30,"Private",111415,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +41,"Local-gov",107327,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",194690,"9th",5,"Never-married","Other-service","Own-child","White","Male",0,0,50,"Mexico","<=50K" +32,"Federal-gov",145983,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States","<=50K" +50,"Private",128478,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,70,"United-States","<=50K" +21,"Private",250647,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,30,"Nicaragua","<=50K" +60,"Private",226949,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,37,"United-States","<=50K" +47,"Private",157901,"11th",7,"Married-civ-spouse","Other-service","Husband","Amer-Indian-Eskimo","Male",0,0,36,"United-States","<=50K" +54,"Self-emp-not-inc",33863,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +32,"Local-gov",40444,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +61,"Private",54373,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",305714,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,70,"United-States","<=50K" +38,"Local-gov",167440,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,20,"United-States","<=50K" +59,"Private",291529,"10th",6,"Widowed","Machine-op-inspct","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +43,"Private",243380,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",38619,"11th",7,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +33,"Private",132601,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +28,"Private",339372,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"Private",101265,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,43,"United-States","<=50K" +23,"Private",117789,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +31,"Private",312667,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",255503,"11th",7,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +21,"Private",221955,"9th",5,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +22,"Private",139190,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +53,"Federal-gov",84278,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +40,"Private",114580,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,24,"United-States",">50K" +36,"Private",185405,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Self-emp-not-inc",199539,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States","<=50K" +23,"Private",346480,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +31,"Private",219619,"HS-grad",9,"Never-married","Sales","Other-relative","White","Male",0,0,48,"United-States","<=50K" +26,"Self-emp-not-inc",253899,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",155232,"Bachelors",13,"Divorced","Protective-serv","Not-in-family","Black","Male",0,0,60,"United-States",">50K" +43,"Private",182437,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +19,"Private",530454,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +46,"Private",101430,"11th",7,"Divorced","Handlers-cleaners","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +49,"Local-gov",358668,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +31,"Private",90668,"10th",6,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",126141,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",238355,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +22,"Private",194031,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +46,"Private",249686,"Prof-school",15,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +44,"Self-emp-not-inc",219591,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",221757,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",80625,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Private",185407,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +34,"Private",163110,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +34,"?",24504,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",192936,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",145011,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-inc",181196,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Self-emp-not-inc",37778,"Masters",14,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +27,"Private",60288,"Masters",14,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",84231,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,48,"United-States","<=50K" +24,"Private",52028,"1st-4th",2,"Married-civ-spouse","Other-service","Own-child","Asian-Pac-Islander","Female",0,0,5,"Vietnam","<=50K" +63,"Private",318763,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,22,"United-States","<=50K" +29,"Private",168138,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",113530,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",321896,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",145791,"Assoc-voc",11,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",131425,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Local-gov",142166,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,99,"United-States","<=50K" +20,"Private",494784,"HS-grad",9,"Never-married","Sales","Other-relative","Black","Female",0,0,35,"United-States","<=50K" +35,"Private",184655,"11th",7,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +41,"Local-gov",26669,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",191479,"Some-college",10,"Divorced","Exec-managerial","Own-child","Black","Female",0,0,40,"United-States","<=50K" +21,"Private",86625,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"?","<=50K" +64,"State-gov",111795,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +31,"Private",364657,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"Germany",">50K" +42,"Self-emp-not-inc",436107,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Private",272476,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"United-States",">50K" +36,"Federal-gov",47310,"Some-college",10,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States",">50K" +23,"Private",283796,"12th",8,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,30,"Mexico","<=50K" +20,"Private",161092,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,14,"United-States","<=50K" +26,"Local-gov",265230,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +40,"Private",150471,"Assoc-acdm",12,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",183041,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,24,"United-States","<=50K" +33,"Private",176673,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +45,"Federal-gov",235891,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"Columbia","<=50K" +29,"Private",164040,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Local-gov",324561,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +48,"Private",99127,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +38,"Private",334999,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +29,"Private",543477,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",65876,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Local-gov",105866,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,30,"United-States","<=50K" +27,"Private",214858,"HS-grad",9,"Married-civ-spouse","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",154076,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +70,"Private",280307,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"Cuba","<=50K" +30,"Private",97723,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,45,"United-States","<=50K" +24,"Private",233499,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +76,"Local-gov",259612,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,15,"United-States","<=50K" +25,"Private",236977,"HS-grad",9,"Separated","Craft-repair","Own-child","White","Male",0,0,40,"Mexico","<=50K" +39,"Private",347814,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Female",0,0,56,"United-States","<=50K" +36,"Local-gov",197495,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",227594,"12th",8,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +60,"Private",165441,"7th-8th",4,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"?",337488,"Some-college",10,"Never-married","?","Own-child","Black","Male",0,0,30,"United-States","<=50K" +54,"Private",167552,"1st-4th",2,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"Haiti",">50K" +20,"Private",396722,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Federal-gov",146538,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",51973,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"United-States","<=50K" +41,"Private",144778,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",169672,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",240137,"5th-6th",3,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,55,"Mexico","<=50K" +17,"Private",172050,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,16,"United-States","<=50K" +43,"Private",178976,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",158200,"Prof-school",15,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Female",0,0,40,"?","<=50K" +38,"Federal-gov",172571,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States",">50K" +54,"Self-emp-not-inc",226735,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,45,"United-States","<=50K" +39,"Private",148015,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",0,0,52,"United-States","<=50K" +24,"?",67586,"Assoc-voc",11,"Married-civ-spouse","?","Wife","Black","Female",0,0,35,"United-States","<=50K" +22,"Private",88126,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",226296,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",452452,"10th",6,"Never-married","Priv-house-serv","Own-child","Black","Female",0,0,20,"United-States","<=50K" +20,"Private",378546,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,25,"United-States","<=50K" +53,"Federal-gov",186087,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Male",0,0,40,"United-States","<=50K" +32,"Private",27856,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +68,"Self-emp-not-inc",234859,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States","<=50K" +28,"Private",71733,"Some-college",10,"Separated","Other-service","Unmarried","White","Female",0,0,15,"United-States","<=50K" +28,"Private",207473,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +54,"Private",179291,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,56,"Haiti",">50K" +21,"?",253190,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,48,"United-States","<=50K" +52,"Private",92968,"Bachelors",13,"Separated","Exec-managerial","Unmarried","White","Female",0,0,40,"?","<=50K" +25,"Private",209286,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",122889,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,50,"India",">50K" +33,"Private",112358,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +49,"Private",176341,"Bachelors",13,"Never-married","Tech-support","Unmarried","Asian-Pac-Islander","Female",0,0,40,"India","<=50K" +58,"Private",247276,"7th-8th",4,"Widowed","Other-service","Not-in-family","Other","Female",0,0,30,"United-States","<=50K" +45,"Private",276087,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,24,"United-States",">50K" +42,"Local-gov",177937,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"?","<=50K" +69,"Self-emp-inc",106395,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +61,"Private",167138,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",213887,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",185647,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +19,"Private",143360,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,34,"United-States","<=50K" +31,"Self-emp-not-inc",176862,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Federal-gov",97614,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",196763,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +46,"Private",306183,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,37,"United-States","<=50K" +48,"?",193047,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Private",195835,"7th-8th",4,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",106273,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,38,"United-States","<=50K" +40,"Private",222756,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +63,"Self-emp-inc",110610,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"?",191982,"Some-college",10,"Divorced","?","Unmarried","White","Female",0,0,10,"Poland","<=50K" +46,"Private",247286,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",219042,"10th",6,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +57,"Private",204751,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Private",113398,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,25,"United-States","<=50K" +25,"?",170428,"Bachelors",13,"Never-married","?","Not-in-family","Asian-Pac-Islander","Male",0,0,28,"Taiwan","<=50K" +36,"Private",162424,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +29,"Private",263005,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"Germany","<=50K" +42,"Private",369131,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +43,"Local-gov",114859,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,17,"United-States","<=50K" +46,"Private",405309,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",323627,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +40,"Private",106698,"Assoc-acdm",12,"Divorced","Transport-moving","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",51506,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",117251,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +26,"Private",106705,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,28,"United-States","<=50K" +30,"Private",217296,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States","<=50K" +43,"Private",143368,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +53,"Local-gov",86600,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +74,"State-gov",117017,"Some-college",10,"Separated","Sales","Not-in-family","White","Male",0,0,16,"United-States","<=50K" +64,"?",104756,"Some-college",10,"Widowed","?","Unmarried","White","Female",0,0,8,"United-States","<=50K" +45,"Private",55720,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +32,"State-gov",481096,"5th-6th",3,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,10,"United-States","<=50K" +23,"?",281668,"10th",6,"Never-married","?","Own-child","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",186145,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +42,"Self-emp-not-inc",96524,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +63,"Private",181153,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +25,"Local-gov",375170,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,35,"United-States","<=50K" +37,"Private",360743,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",420054,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Italy","<=50K" +31,"Private",137681,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",101214,"Bachelors",13,"Divorced","Sales","Unmarried","White","Male",0,0,44,"United-States",">50K" +42,"Local-gov",213019,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +45,"Private",207540,"Doctorate",16,"Separated","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States",">50K" +52,"Private",145333,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +40,"Private",107306,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",195327,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Private",196126,"Bachelors",13,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"?","<=50K" +17,"Private",175465,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,14,"United-States","<=50K" +27,"Private",197905,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",172571,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +17,"Private",25051,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +26,"Private",210714,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,52,"United-States",">50K" +22,"Private",183083,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +51,"Private",99185,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +33,"Private",283921,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",396467,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,50,"United-States",">50K" +50,"Private",158680,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",202091,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +21,"Private",285127,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +53,"Private",218630,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Self-emp-inc",99309,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",165505,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +22,"Private",122272,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +47,"Federal-gov",44257,"Bachelors",13,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States",">50K" +51,"Self-emp-inc",194995,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +42,"State-gov",345969,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +28,"Private",31842,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",143582,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Asian-Pac-Islander","Female",0,0,35,"Vietnam","<=50K" +50,"Private",161438,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",317019,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +47,"Self-emp-not-inc",158451,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +60,"Private",225883,"Some-college",10,"Widowed","Sales","Unmarried","White","Female",0,0,27,"United-States","<=50K" +58,"Self-emp-inc",258883,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +62,"Private",26966,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",202812,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?",">50K" +59,"Private",35411,"HS-grad",9,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",190885,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +31,"Private",182162,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,37,"United-States","<=50K" +18,"Private",352640,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +64,"Self-emp-not-inc",213945,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +51,"Self-emp-not-inc",135102,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States","<=50K" +47,"Self-emp-not-inc",102583,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +68,"Private",225612,"Bachelors",13,"Widowed","Sales","Not-in-family","White","Male",0,0,35,"United-States",">50K" +32,"Private",241802,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Other","Female",0,0,40,"United-States","<=50K" +39,"Private",347434,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,43,"Mexico","<=50K" +37,"Private",305259,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +29,"Private",140830,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +44,"Private",291568,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Other","Male",0,0,40,"United-States","<=50K" +46,"Private",203067,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Self-emp-not-inc",155106,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +19,"?",252752,"HS-grad",9,"Never-married","?","Own-child","Black","Male",0,0,35,"United-States","<=50K" +52,"Local-gov",100226,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +40,"Private",63503,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +61,"Private",95929,"9th",5,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",187618,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +61,"Self-emp-not-inc",92178,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",220362,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,84,"United-States",">50K" +32,"Local-gov",209900,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,65,"United-States",">50K" +32,"Private",272376,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",173854,"Bachelors",13,"Divorced","Prof-specialty","Other-relative","White","Male",0,0,35,"United-States",">50K" +37,"Private",278924,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",324568,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +51,"Self-emp-inc",124963,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",211299,"Assoc-voc",11,"Never-married","Sales","Not-in-family","Black","Male",0,0,45,"United-States","<=50K" +48,"Private",192791,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",46868,"Masters",14,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Local-gov",31365,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +18,"Private",142647,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +60,"Private",116230,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",108907,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"?","<=50K" +19,"Private",495982,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,10,"United-States","<=50K" +18,"Private",334026,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,25,"United-States","<=50K" +33,"Private",268571,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",213813,"Some-college",10,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",241667,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +37,"Private",160920,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +50,"Private",107265,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +19,"?",41609,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,10,"United-States","<=50K" +43,"?",109912,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,7,"United-States",">50K" +23,"Private",167424,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +47,"Private",270079,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",325923,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,35,"United-States","<=50K" +19,"Private",194905,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,12,"United-States","<=50K" +47,"Local-gov",183486,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +36,"Federal-gov",153066,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +65,"Private",105252,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",146310,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",256504,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,6,"United-States","<=50K" +17,"Private",121425,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,16,"United-States","<=50K" +57,"?",155259,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Self-emp-not-inc",98829,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +47,"Self-emp-inc",239321,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +62,"Self-emp-inc",134768,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +35,"Private",556902,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",47907,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +23,"Private",114357,"HS-grad",9,"Never-married","Tech-support","Own-child","White","Male",0,0,50,"United-States","<=50K" +39,"Private",90646,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",232914,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,38,"United-States","<=50K" +24,"Private",192201,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +23,"Private",27776,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",137476,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,35,"United-States",">50K" +30,"Private",100734,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,38,"United-States","<=50K" +34,"Private",111746,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,45,"Portugal","<=50K" +32,"Private",184833,"10th",6,"Separated","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",151780,"Assoc-voc",11,"Never-married","Sales","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +38,"State-gov",203628,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +18,"Private",137363,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +41,"Private",172307,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",273403,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +36,"State-gov",37931,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,48,"United-States",">50K" +61,"Private",97030,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +30,"Private",54608,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +26,"Private",108542,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",253814,"Bachelors",13,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States",">50K" +45,"Private",421412,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +47,"Private",207140,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +19,"Private",138153,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +29,"Private",46987,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +51,"Self-emp-inc",183173,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States",">50K" +34,"Local-gov",229531,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +26,"Private",257405,"5th-6th",3,"Never-married","Farming-fishing","Other-relative","Black","Male",0,0,40,"Mexico","<=50K" +20,"State-gov",432052,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +43,"Private",397280,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +20,"Private",38001,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +27,"Private",101618,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +46,"Federal-gov",332727,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",115215,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",178449,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,49,"United-States","<=50K" +42,"Private",185267,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,32,"United-States","<=50K" +23,"Private",410439,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,25,"United-States","<=50K" +29,"Private",85572,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,42,"United-States",">50K" +27,"Private",83517,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,60,"United-States","<=50K" +43,"Self-emp-not-inc",194726,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +23,"Private",322674,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Local-gov",34540,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,44,"United-States","<=50K" +35,"Local-gov",211073,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,61,"United-States",">50K" +30,"Private",194901,"HS-grad",9,"Never-married","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +59,"Private",117059,"11th",7,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +28,"Private",51461,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +79,"Private",266119,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",92374,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,35,"United-States",">50K" +54,"Private",175262,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",208249,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,62,"United-States","<=50K" +22,"?",110622,"Bachelors",13,"Never-married","?","Own-child","Asian-Pac-Islander","Female",0,0,15,"Taiwan","<=50K" +34,"Private",146980,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,65,"United-States","<=50K" +18,"Private",112974,"11th",7,"Never-married","Prof-specialty","Other-relative","White","Male",0,0,3,"United-States","<=50K" +18,"Private",210932,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +46,"Private",145290,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",198992,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +77,"?",174887,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,6,"United-States","<=50K" +48,"Private",190072,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +29,"Private",49087,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +41,"Private",126622,"11th",7,"Divorced","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",174189,"9th",5,"Separated","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",118605,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +49,"Self-emp-not-inc",377622,"Assoc-acdm",12,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +49,"Private",157272,"HS-grad",9,"Separated","Sales","Unmarried","White","Male",0,0,50,"United-States","<=50K" +30,"Private",78530,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",190391,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +62,"State-gov",162678,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",103980,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,52,"United-States","<=50K" +20,"Private",293726,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"Private",98350,"Preschool",1,"Married-spouse-absent","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +30,"Private",207668,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,60,"Hungary","<=50K" +29,"Federal-gov",41013,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +44,"Federal-gov",320071,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",306908,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +62,"Private",167652,"Assoc-voc",11,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"Private",173580,"Some-college",10,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",273612,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +26,"Private",195555,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"Private",186446,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +22,"Private",418405,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Local-gov",41793,"Masters",14,"Separated","Prof-specialty","Not-in-family","White","Female",0,0,50,"?","<=50K" +26,"Private",183965,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",354784,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +32,"Private",732102,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +66,"Self-emp-not-inc",97847,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Private",196678,"Preschool",1,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,30,"United-States","<=50K" +19,"Private",320014,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +54,"Self-emp-inc",298215,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",295127,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",368140,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Self-emp-not-inc",187411,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"?","<=50K" +22,"?",121070,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,35,"United-States","<=50K" +34,"Private",212163,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,25,"United-States","<=50K" +35,"Self-emp-not-inc",108198,"HS-grad",9,"Divorced","Craft-repair","Own-child","Amer-Indian-Eskimo","Male",0,0,15,"United-States","<=50K" +42,"Federal-gov",294431,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Federal-gov",202560,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +29,"Self-emp-inc",266070,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,80,"United-States","<=50K" +34,"Private",346122,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-inc",308686,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,70,"United-States",">50K" +62,"Self-emp-inc",236096,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",187711,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",238959,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +47,"Private",93557,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",329980,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",125010,"Assoc-voc",11,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +60,"Self-emp-inc",90915,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",289731,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Private",206052,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",191385,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"?",268804,"HS-grad",9,"Married-civ-spouse","?","Husband","Black","Male",0,0,30,"United-States","<=50K" +35,"Self-emp-not-inc",199753,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,60,"United-States","<=50K" +50,"Local-gov",92486,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",171088,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,10,"United-States","<=50K" +33,"Private",112820,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",32855,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +17,"Private",142964,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +47,"Private",89146,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States",">50K" +51,"?",147015,"Some-college",10,"Divorced","?","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +26,"Private",291968,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Local-gov",29235,"Some-college",10,"Married-civ-spouse","Protective-serv","Wife","White","Female",0,0,40,"France",">50K" +55,"Private",238216,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"State-gov",323726,"Some-college",10,"Never-married","Tech-support","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +54,"Private",141663,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",118551,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States",">50K" +52,"Local-gov",35092,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",139703,"HS-grad",9,"Married-spouse-absent","Sales","Unmarried","Black","Female",0,0,28,"Jamaica","<=50K" +39,"Federal-gov",206190,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +59,"Self-emp-not-inc",178353,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +55,"Federal-gov",169133,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",103179,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +31,"Private",354464,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"?",124651,"11th",7,"Never-married","?","Own-child","Black","Male",0,0,25,"United-States","<=50K" +30,"Private",60426,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Own-child","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +47,"Federal-gov",98726,"Bachelors",13,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",133861,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",180303,"Bachelors",13,"Divorced","Craft-repair","Unmarried","Asian-Pac-Islander","Male",0,0,47,"Iran","<=50K" +33,"Private",221324,"Assoc-voc",11,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",325658,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +32,"Private",210562,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",152249,"HS-grad",9,"Married-spouse-absent","Other-service","Not-in-family","White","Male",0,0,35,"Mexico","<=50K" +29,"Private",178649,"HS-grad",9,"Married-spouse-absent","Other-service","Not-in-family","White","Female",0,0,20,"France","<=50K" +41,"State-gov",48997,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",243409,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +34,"Private",162442,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States",">50K" +23,"Private",203078,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,24,"United-States","<=50K" +53,"Self-emp-inc",155983,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States",">50K" +45,"Self-emp-not-inc",182677,"HS-grad",9,"Married-spouse-absent","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Thailand","<=50K" +34,"?",170276,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,10,"United-States",">50K" +47,"Private",105381,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"?",256240,"7th-8th",4,"Married-civ-spouse","?","Own-child","White","Male",0,0,60,"United-States","<=50K" +38,"Self-emp-inc",141584,"HS-grad",9,"Divorced","Sales","Unmarried","White","Male",0,0,55,"United-States","<=50K" +26,"Private",113571,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +18,"Private",154089,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +43,"Private",50197,"10th",6,"Separated","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +26,"Private",132572,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,32,"United-States","<=50K" +47,"Private",238185,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",112754,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States",">50K" +58,"Self-emp-inc",143266,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",68006,"7th-8th",4,"Never-married","Other-service","Other-relative","White","Female",0,0,60,"United-States","<=50K" +40,"Private",287079,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +33,"Private",223212,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +74,"Self-emp-not-inc",173929,"Doctorate",16,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",0,0,25,"United-States",">50K" +49,"Self-emp-not-inc",182211,"HS-grad",9,"Widowed","Farming-fishing","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +56,"Self-emp-not-inc",62539,"11th",7,"Widowed","Other-service","Unmarried","White","Female",0,0,65,"Greece",">50K" +25,"Private",305472,"Assoc-acdm",12,"Never-married","Machine-op-inspct","Own-child","Black","Male",0,0,48,"United-States","<=50K" +57,"Private",548256,"12th",8,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",40295,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Private",31137,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +28,"?",127833,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",201743,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +40,"Private",240027,"Some-college",10,"Never-married","Sales","Unmarried","Black","Female",0,0,45,"United-States","<=50K" +28,"Private",129882,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +48,"?",355890,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,55,"United-States",">50K" +20,"Private",107658,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,10,"Canada","<=50K" +19,"Private",146679,"Some-college",10,"Never-married","Exec-managerial","Own-child","Black","Male",0,0,30,"United-States","<=50K" +75,"?",35724,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +24,"Federal-gov",42251,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +31,"Private",113838,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +28,"Self-emp-not-inc",282398,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +41,"Private",33331,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +23,"Federal-gov",41031,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +46,"Private",155489,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,43,"United-States",">50K" +33,"Private",53042,"12th",8,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +34,"Private",174789,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +47,"Local-gov",203067,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +45,"Private",216626,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","Other","Male",0,0,40,"Columbia","<=50K" +35,"Private",93034,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Cambodia","<=50K" +59,"Self-emp-not-inc",188003,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States",">50K" +46,"Local-gov",65535,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +39,"Private",366757,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +23,"Private",414545,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",295919,"Assoc-acdm",12,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",34378,"1st-4th",2,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",476334,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +32,"Private",255424,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +34,"Local-gov",175856,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",124692,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",118551,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +78,"?",292019,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +31,"Private",288566,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,43,"United-States",">50K" +61,"Private",137733,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +22,"Private",39432,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",138537,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Laos","<=50K" +37,"Private",709445,"HS-grad",9,"Separated","Craft-repair","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",194809,"11th",7,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"?",299090,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +18,"Private",159561,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,20,"United-States","<=50K" +37,"Private",236328,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +46,"Private",269045,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States",">50K" +25,"?",196627,"11th",7,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Federal-gov",323798,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Private",463072,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +25,"Self-emp-inc",98756,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Female",0,0,50,"United-States","<=50K" +50,"State-gov",161075,"HS-grad",9,"Widowed","Tech-support","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",192485,"12th",8,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,20,"United-States","<=50K" +25,"Private",201579,"9th",5,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +23,"Private",117606,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"?",177487,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",60313,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +27,"Private",169958,"5th-6th",3,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"?","<=50K" +19,"Private",240686,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +52,"Local-gov",124793,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Self-emp-not-inc",113948,"Assoc-voc",11,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,45,"United-States","<=50K" +17,"?",241021,"12th",8,"Never-married","?","Own-child","Other","Female",0,0,40,"United-States","<=50K" +21,"Private",147655,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",38876,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +20,"?",114813,"10th",6,"Separated","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",136310,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Federal-gov",153132,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +23,"Private",197552,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +33,"Private",69748,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +29,"Private",175738,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States",">50K" +50,"State-gov",78649,"Some-college",10,"Married-spouse-absent","Adm-clerical","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-inc",188774,"11th",7,"Married-spouse-absent","Sales","Not-in-family","White","Male",0,0,60,"?","<=50K" +19,"Federal-gov",215891,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +40,"Private",144928,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +65,"Private",262446,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +44,"Federal-gov",191295,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,48,"United-States","<=50K" +32,"Private",279173,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +41,"Private",153031,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States",">50K" +28,"Private",202239,"7th-8th",4,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +39,"Local-gov",164156,"Assoc-acdm",12,"Divorced","Other-service","Unmarried","White","Female",0,0,55,"United-States","<=50K" +59,"Private",196482,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",176185,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"France",">50K" +34,"Private",287315,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",117210,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",41610,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",160703,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,65,"United-States",">50K" +31,"Private",80511,"Assoc-acdm",12,"Divorced","Tech-support","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +39,"Private",219155,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,43,"United-States","<=50K" +35,"Private",106347,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +44,"Self-emp-not-inc",163985,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,32,"United-States",">50K" +28,"Private",270887,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +17,"Private",205726,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +23,"Private",218899,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,60,"United-States","<=50K" +19,"Private",248749,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +30,"Private",197558,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",176514,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"?",116820,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,50,"United-States","<=50K" +44,"Private",226129,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Private",281138,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",98061,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",260560,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +23,"Private",289909,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +51,"Private",59590,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States","<=50K" +24,"Private",236769,"Assoc-acdm",12,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",423616,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,24,"United-States",">50K" +24,"Private",291407,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +53,"Self-emp-inc",100029,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",204494,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,56,"United-States",">50K" +24,"Private",201680,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",154308,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +31,"Private",150324,"11th",7,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +38,"Local-gov",331609,"Some-college",10,"Widowed","Transport-moving","Not-in-family","Black","Female",0,0,47,"United-States","<=50K" +28,"Private",100829,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +38,"Private",203169,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Private",122075,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +29,"Private",178778,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",276345,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +48,"Private",233511,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",289448,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +31,"Private",173350,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +36,"Private",130589,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +62,"Private",94318,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Private",297531,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +55,"Private",129762,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +21,"Private",182614,"Some-college",10,"Never-married","Sales","Other-relative","White","Female",0,0,40,"Poland","<=50K" +60,"Private",120067,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +41,"Private",182370,"Assoc-acdm",12,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"State-gov",60949,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",190511,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",188195,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",89534,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",183358,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Puerto-Rico","<=50K" +38,"?",75024,"7th-8th",4,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",251120,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"England","<=50K" +35,"Private",108946,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",93223,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,35,"United-States","<=50K" +61,"Private",147393,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States","<=50K" +71,"?",45801,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,70,"United-States","<=50K" +35,"State-gov",225385,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Federal-gov",23892,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",179668,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"Scotland","<=50K" +27,"Self-emp-not-inc",404998,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",68882,"1st-4th",2,"Widowed","Other-service","Unmarried","White","Female",0,0,35,"Portugal","<=50K" +55,"Self-emp-not-inc",194065,"Assoc-acdm",12,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",185336,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +25,"State-gov",152503,"Some-college",10,"Never-married","Tech-support","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +52,"Private",167794,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States",">50K" +46,"Private",96552,"Some-college",10,"Divorced","Machine-op-inspct","Own-child","White","Female",0,0,17,"United-States","<=50K" +52,"State-gov",254285,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",32509,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +46,"Private",125492,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-inc",186035,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +69,"?",168794,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,48,"United-States","<=50K" +36,"Private",215503,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +57,"Local-gov",190748,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,35,"United-States","<=50K" +24,"Private",117767,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +37,"Private",301070,"HS-grad",9,"Divorced","Farming-fishing","Unmarried","White","Male",0,0,45,"United-States","<=50K" +39,"Private",186183,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",131808,"Assoc-voc",11,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +34,"State-gov",156292,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",124589,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"Private",262819,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +61,"Private",95500,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",241306,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +29,"Private",238680,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Male",0,0,55,"Outlying-US(Guam-USVI-etc)","<=50K" +18,"?",42293,"10th",6,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +41,"Local-gov",168071,"HS-grad",9,"Divorced","Exec-managerial","Own-child","White","Male",0,0,45,"United-States","<=50K" +42,"Private",337629,"12th",8,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,60,"?",">50K" +52,"Private",168001,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +38,"Private",97759,"12th",8,"Never-married","Other-service","Unmarried","White","Female",0,0,17,"United-States","<=50K" +51,"Self-emp-not-inc",107096,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +55,"Private",76860,"HS-grad",9,"Married-civ-spouse","Other-service","Other-relative","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +20,"Private",70076,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"Private",312017,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",174138,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",125892,"Bachelors",13,"Divorced","Exec-managerial","Other-relative","White","Male",0,0,40,"United-States","<=50K" +22,"Private",210474,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"State-gov",157332,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +28,"Private",30771,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",319768,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"France",">50K" +25,"Private",324609,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +48,"Private",268234,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +32,"Local-gov",178109,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,43,"United-States","<=50K" +31,"Private",25955,"9th",5,"Never-married","Craft-repair","Own-child","Amer-Indian-Eskimo","Male",0,0,35,"United-States","<=50K" +65,"?",123484,"HS-grad",9,"Widowed","?","Other-relative","White","Female",0,0,25,"United-States","<=50K" +56,"Local-gov",129762,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +22,"Self-emp-not-inc",108506,"Assoc-voc",11,"Never-married","Farming-fishing","Not-in-family","Amer-Indian-Eskimo","Male",0,0,75,"United-States","<=50K" +27,"Private",241607,"Bachelors",13,"Never-married","Tech-support","Other-relative","White","Male",0,0,50,"United-States","<=50K" +27,"Federal-gov",214385,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +30,"Local-gov",183000,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +33,"Private",290763,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Private",171924,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,43,"United-States",">50K" +19,"Private",97189,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,22,"United-States","<=50K" +37,"Federal-gov",329088,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",58371,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"?",256371,"12th",8,"Never-married","?","Own-child","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",35824,"Some-college",10,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Private",173271,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",391349,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +24,"Private",86153,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",295855,"11th",7,"Divorced","Other-service","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +33,"Self-emp-not-inc",327902,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +35,"Private",285102,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Taiwan",">50K" +57,"Private",178353,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Private",28119,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,7,"United-States","<=50K" +42,"Private",197522,"Some-college",10,"Separated","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +25,"Private",108542,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,35,"United-States","<=50K" +56,"Private",179781,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",126974,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",180060,"Bachelors",13,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,50,"United-States","<=50K" +35,"Local-gov",38948,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"Private",271572,"9th",5,"Never-married","Other-service","Other-relative","White","Male",0,0,52,"United-States","<=50K" +41,"Private",177305,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +26,"Private",238367,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",172232,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,0,30,"United-States","<=50K" +22,"Private",153805,"HS-grad",9,"Never-married","Other-service","Unmarried","Other","Male",0,0,20,"Puerto-Rico","<=50K" +30,"Private",26543,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",109067,"Bachelors",13,"Separated","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",213716,"Assoc-voc",11,"Divorced","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +49,"Private",149809,"Preschool",1,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"?","<=50K" +27,"Private",185670,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +43,"Federal-gov",233851,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +25,"Private",213385,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",38238,"Bachelors",13,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +68,"Private",104438,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Ireland",">50K" +17,"Private",202344,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +45,"Self-emp-not-inc",43434,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",102147,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +30,"Private",231826,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +49,"State-gov",247378,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +29,"Private",184078,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +20,"Private",258430,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,19,"United-States","<=50K" +59,"Private",244554,"11th",7,"Divorced","Other-service","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +26,"Private",252565,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +25,"Private",262778,"Masters",14,"Never-married","Other-service","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +33,"Private",162572,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States",">50K" +35,"Private",65706,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Federal-gov",102569,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +66,"Private",350498,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,28,"United-States","<=50K" +67,"?",159542,"5th-6th",3,"Widowed","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",142383,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","Other","Male",0,0,36,"United-States","<=50K" +38,"Private",229236,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Other","Male",0,0,40,"Puerto-Rico","<=50K" +72,"Private",56559,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,12,"United-States","<=50K" +21,"Private",27049,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,12,"United-States","<=50K" +39,"Private",36376,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +22,"Private",246965,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,12,"United-States","<=50K" +24,"Private",268525,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +25,"Private",456604,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",223464,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",341797,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",174461,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",392167,"10th",6,"Divorced","Sales","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +60,"Private",210064,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +67,"?",233182,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,7,"United-States","<=50K" +62,"Private",143312,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +22,"Private",326334,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +37,"Private",179088,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Private",207637,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,10,"United-States","<=50K" +52,"Federal-gov",37289,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States",">50K" +31,"Private",36069,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +23,"Federal-gov",53245,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Self-emp-inc",399904,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,50,"Mexico","<=50K" +38,"Self-emp-inc",199346,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,45,"United-States","<=50K" +23,"Private",343019,"10th",6,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"State-gov",232742,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +61,"Self-emp-not-inc",390472,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",290124,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +39,"Private",70240,"5th-6th",3,"Married-spouse-absent","Other-service","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +25,"Private",153841,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",137367,"Bachelors",13,"Never-married","Sales","Unmarried","Asian-Pac-Islander","Male",0,0,44,"Philippines","<=50K" +66,"Private",313255,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,24,"United-States","<=50K" +30,"Private",100734,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +32,"Private",248584,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",60001,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",335065,"7th-8th",4,"Never-married","Sales","Own-child","White","Male",0,0,30,"Mexico","<=50K" +20,"Private",219262,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +20,"Private",186830,"HS-grad",9,"Never-married","Transport-moving","Other-relative","Black","Male",0,0,45,"United-States","<=50K" +34,"Private",226385,"Masters",14,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",609789,"Assoc-acdm",12,"Married-spouse-absent","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +40,"Private",307767,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +33,"Private",217460,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +41,"Local-gov",160893,"Preschool",1,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,30,"United-States","<=50K" +20,"Private",68358,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,12,"United-States","<=50K" +40,"Self-emp-not-inc",243636,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Self-emp-not-inc",71269,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",71898,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Wife","Asian-Pac-Islander","Female",0,0,35,"Philippines","<=50K" +38,"?",212048,"Prof-school",15,"Divorced","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +30,"Local-gov",115040,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Other-relative","White","Male",0,0,25,"United-States","<=50K" +25,"Private",210794,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"?",88126,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",570821,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"?",146196,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"State-gov",169482,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",63577,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +22,"Private",208946,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",26598,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",189203,"Assoc-voc",11,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",183892,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +82,"?",194590,"Assoc-voc",11,"Widowed","?","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +18,"Private",188616,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,15,"United-States","<=50K" +60,"Private",116707,"11th",7,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",99199,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +39,"Local-gov",183620,"Some-college",10,"Never-married","Protective-serv","Not-in-family","Black","Female",0,0,40,"United-States",">50K" +34,"Private",110476,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",150726,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",214695,"HS-grad",9,"Never-married","Sales","Own-child","Black","Male",0,0,60,"United-States","<=50K" +37,"Private",172694,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,50,"United-States","<=50K" +25,"Private",344804,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"Mexico","<=50K" +33,"Private",319422,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"Peru","<=50K" +34,"State-gov",327902,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +35,"Private",438176,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Female",0,0,65,"United-States","<=50K" +51,"Private",197656,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +33,"Private",219838,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",35561,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +25,"?",156848,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +56,"Private",190257,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",156464,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,85,"England",">50K" +36,"Private",65624,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",201699,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Private",349910,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States",">50K" +88,"Self-emp-not-inc",187097,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",264314,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"Columbia","<=50K" +40,"Self-emp-not-inc",282678,"Masters",14,"Separated","Exec-managerial","Unmarried","White","Female",0,0,20,"United-States","<=50K" +21,"Private",188923,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,55,"United-States","<=50K" +46,"Private",114797,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","Black","Female",0,0,36,"United-States","<=50K" +56,"Private",245215,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Self-emp-not-inc",36270,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +67,"Self-emp-not-inc",107138,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",77820,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +20,"Private",39477,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",359759,"HS-grad",9,"Never-married","Craft-repair","Own-child","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +19,"?",249147,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +19,"Private",44797,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +25,"Private",164488,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +53,"Private",48413,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",36592,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,91,"United-States","<=50K" +33,"Private",280923,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +33,"Federal-gov",29617,"Some-college",10,"Divorced","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",189240,"Some-college",10,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +20,"?",37932,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",181705,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",147548,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,85,"United-States","<=50K" +51,"Self-emp-not-inc",306784,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"United-States","<=50K" +45,"?",260953,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",230229,"5th-6th",3,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +63,"Private",301108,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,22,"United-States","<=50K" +35,"Private",263081,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,60,"United-States",">50K" +25,"Self-emp-not-inc",37741,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +44,"Private",150076,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +49,"Self-emp-not-inc",148254,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +52,"Private",183611,"1st-4th",2,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",258768,"Bachelors",13,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",287658,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +51,"Private",95946,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +49,"Private",31267,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",250135,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",176073,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +65,"Private",23580,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",163665,"Bachelors",13,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +30,"Federal-gov",43953,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",144860,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States","<=50K" +58,"Self-emp-not-inc",61474,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +40,"Private",225660,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,45,"United-States",">50K" +42,"Private",336891,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",210164,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",171080,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +42,"Private",143342,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",281627,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",157262,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +31,"Private",144949,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",104293,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",195481,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Other-relative","White","Male",0,0,40,"United-States","<=50K" +40,"Private",193995,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States","<=50K" +67,"Private",105216,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +40,"Private",147206,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",173585,"HS-grad",9,"Never-married","Sales","Own-child","Black","Female",0,0,18,"United-States","<=50K" +38,"Private",248919,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Guatemala","<=50K" +42,"Private",280410,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"Haiti","<=50K" +36,"State-gov",170861,"HS-grad",9,"Separated","Other-service","Own-child","White","Female",0,0,32,"United-States","<=50K" +23,"Self-emp-not-inc",409230,"1st-4th",2,"Married-civ-spouse","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +56,"Private",340171,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",41017,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,52,"United-States",">50K" +22,"Private",416356,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +39,"Private",261504,"12th",8,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"State-gov",205555,"Prof-school",15,"Divorced","Prof-specialty","Own-child","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +44,"Private",245317,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,56,"United-States",">50K" +38,"Private",153685,"11th",7,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,52,"United-States","<=50K" +19,"?",169758,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",99374,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +57,"Local-gov",139452,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +54,"Private",227832,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Self-emp-not-inc",213024,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,30,"United-States","<=50K" +22,"?",24008,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,72,"United-States","<=50K" +63,"Self-emp-not-inc",33487,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-inc",187934,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,20,"Poland","<=50K" +26,"Private",421561,"11th",7,"Married-civ-spouse","Other-service","Other-relative","White","Male",0,0,25,"United-States","<=50K" +40,"Private",109969,"11th",7,"Divorced","Other-service","Other-relative","White","Female",0,0,20,"United-States","<=50K" +20,"Private",116830,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",106951,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +30,"Private",89625,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","Asian-Pac-Islander","Female",0,0,5,"United-States",">50K" +42,"Private",194537,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Private",144002,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +21,"Private",202214,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",109762,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +36,"Private",292570,"11th",7,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +65,"Private",94552,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Local-gov",46401,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,50,"United-States","<=50K" +18,"Private",151150,"10th",6,"Never-married","Farming-fishing","Own-child","White","Male",0,0,27,"United-States","<=50K" +31,"Private",197689,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,38,"United-States","<=50K" +36,"Self-emp-inc",180477,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +20,"Private",181761,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",381153,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",165474,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,39,"United-States","<=50K" +38,"Federal-gov",190174,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +17,"Private",295991,"10th",6,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +52,"Without-pay",198262,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,30,"United-States","<=50K" +34,"Private",190385,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +30,"?",411560,"HS-grad",9,"Married-civ-spouse","?","Husband","Black","Male",0,0,40,"United-States","<=50K" +49,"Private",262116,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States","<=50K" +45,"Private",178922,"9th",5,"Never-married","Other-service","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +34,"Self-emp-inc",209538,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",216086,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +23,"Private",636017,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",155781,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",136873,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"State-gov",122066,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"United-States",">50K" +27,"State-gov",346406,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Male",0,0,50,"United-States","<=50K" +43,"Private",117915,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",19914,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Asian-Pac-Islander","Female",0,0,50,"Philippines","<=50K" +55,"Private",255364,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +31,"Private",703107,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +34,"Private",62374,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +34,"Private",96245,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",348796,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",136873,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,10,"United-States","<=50K" +35,"Private",388252,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +28,"Private",47783,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +40,"Federal-gov",544792,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",434463,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,39,"United-States","<=50K" +70,"Private",221603,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",0,0,34,"United-States","<=50K" +23,"Private",233711,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",111567,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,48,"United-States","<=50K" +57,"Private",79830,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",192259,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +24,"Private",239663,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +41,"Local-gov",34987,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +38,"Self-emp-not-inc",409189,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Mexico","<=50K" +48,"Private",135525,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",152159,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +18,"Private",141363,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",214816,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",42907,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,48,"United-States","<=50K" +30,"Private",161815,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +42,"Private",127314,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +48,"Private",395368,"Some-college",10,"Divorced","Handlers-cleaners","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +70,"Private",184176,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +37,"Private",112660,"9th",5,"Divorced","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +51,"Private",183709,"Assoc-voc",11,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",434114,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +57,"Private",190997,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",335533,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,20,"United-States","<=50K" +26,"Private",176146,"5th-6th",3,"Separated","Craft-repair","Not-in-family","Other","Male",0,0,35,"Mexico","<=50K" +19,"Private",272063,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +34,"Private",169564,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",69847,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +22,"Private",175431,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +32,"Private",228357,"Assoc-voc",11,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"?","<=50K" +72,"Self-emp-not-inc",284120,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",109133,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",167336,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,45,"United-States",">50K" +76,"?",42209,"9th",5,"Widowed","?","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +37,"Private",282951,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",303155,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Private",261899,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,44,"United-States","<=50K" +53,"State-gov",71417,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",239130,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +69,"Private",200560,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,20,"United-States","<=50K" +20,"Private",157541,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,27,"United-States","<=50K" +33,"Private",255004,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +47,"Private",230136,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,60,"United-States",">50K" +22,"Private",39615,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +20,"Private",47678,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",281315,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +23,"Private",176123,"HS-grad",9,"Never-married","Tech-support","Other-relative","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +24,"?",165350,"HS-grad",9,"Separated","?","Not-in-family","Black","Male",0,0,50,"Germany","<=50K" +32,"Private",235862,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +41,"Private",142579,"Bachelors",13,"Widowed","Sales","Unmarried","Black","Male",0,0,50,"United-States","<=50K" +35,"Private",38294,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",111483,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Private",189850,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","Black","Male",0,0,40,"United-States","<=50K" +34,"State-gov",145874,"Doctorate",16,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,0,20,"China","<=50K" +23,"Private",139012,"Assoc-voc",11,"Never-married","Transport-moving","Own-child","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +30,"Local-gov",211654,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Local-gov",173090,"Masters",14,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,45,"United-States","<=50K" +42,"?",195124,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,60,"Dominican-Republic","<=50K" +39,"Private",32146,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +52,"Private",282674,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States",">50K" +42,"Private",190403,"Some-college",10,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,60,"Canada","<=50K" +27,"Private",198258,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +30,"Self-emp-not-inc",172748,"7th-8th",4,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +58,"?",175017,"Bachelors",13,"Divorced","?","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +18,"Private",170183,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +52,"Private",150812,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +24,"Private",241185,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +58,"Self-emp-inc",174864,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +35,"Private",30529,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",301637,"Assoc-voc",11,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",242912,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Female",0,0,35,"United-States","<=50K" +24,"Private",117363,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +22,"Private",333158,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +39,"Private",193260,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,25,"Mexico","<=50K" +34,"State-gov",278378,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +58,"Private",111394,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",102476,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,25,"United-States","<=50K" +29,"Private",26451,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +67,"?",209137,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",210945,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,35,"Haiti","<=50K" +62,"Local-gov",115023,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",53833,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",150057,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States","<=50K" +18,"Private",128086,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,18,"United-States","<=50K" +25,"Private",28473,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",155509,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +56,"Private",165315,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"?","<=50K" +30,"Private",171889,"Prof-school",15,"Never-married","Tech-support","Own-child","White","Female",0,0,24,"United-States","<=50K" +41,"Local-gov",185057,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +59,"Private",277034,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Male",0,0,60,"United-States",">50K" +36,"Private",166606,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",97453,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,54,"United-States","<=50K" +27,"Private",136094,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"?",61855,"HS-grad",9,"Never-married","?","Other-relative","White","Female",0,0,30,"United-States","<=50K" +30,"Private",182771,"Bachelors",13,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,15,"China","<=50K" +47,"Private",418961,"Assoc-voc",11,"Divorced","Sales","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +39,"Private",106961,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",81846,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +44,"Private",105936,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",36425,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",595088,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,63,"United-States","<=50K" +38,"Private",149018,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",229613,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",33521,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +53,"State-gov",105728,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Amer-Indian-Eskimo","Female",0,0,28,"United-States",">50K" +31,"Private",193215,"Some-college",10,"Married-civ-spouse","Exec-managerial","Own-child","White","Male",0,0,50,"United-States","<=50K" +18,"Private",137363,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-inc",104892,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Private",149427,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +19,"State-gov",176634,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",183279,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"?",225775,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",202091,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,60,"United-States","<=50K" +36,"Private",123151,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +22,"Private",168187,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,50,"United-States","<=50K" +42,"Federal-gov",33521,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"State-gov",243678,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",164898,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"State-gov",290614,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",199265,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",207668,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +18,"State-gov",30687,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,10,"United-States","<=50K" +24,"State-gov",27939,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,24,"?","<=50K" +17,"Private",438996,"10th",6,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +48,"Private",152915,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +66,"?",186030,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,32,"United-States","<=50K" +46,"Local-gov",297759,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Private",171242,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States",">50K" +28,"Private",206088,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",182792,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",167725,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,24,"United-States","<=50K" +43,"Private",160674,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Private",194710,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",255027,"Assoc-voc",11,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",204641,"10th",6,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,50,"United-States","<=50K" +20,"State-gov",177787,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +29,"Private",54932,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,35,"United-States",">50K" +54,"Self-emp-not-inc",91506,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States","<=50K" +34,"Private",198634,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",227146,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Private",135647,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +40,"Private",55508,"7th-8th",4,"Divorced","Farming-fishing","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",174912,"HS-grad",9,"Separated","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",175925,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Local-gov",329144,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,44,"United-States",">50K" +67,"?",81761,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,2,"United-States","<=50K" +49,"Self-emp-not-inc",102318,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +30,"Federal-gov",266463,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Federal-gov",107314,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",114158,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",124052,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",144301,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,42,"United-States","<=50K" +28,"Private",176683,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,70,"United-States",">50K" +23,"Private",234663,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",178948,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,0,50,"United-States","<=50K" +37,"Self-emp-not-inc",607848,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",202937,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +32,"Federal-gov",83413,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"United-States",">50K" +26,"Private",212798,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +57,"Federal-gov",192258,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",112497,"9th",5,"Married-civ-spouse","Sales","Own-child","White","Male",0,0,50,"United-States",">50K" +30,"Private",97521,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",160972,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +21,"Private",322931,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +22,"Private",403519,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",330174,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",278155,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",39054,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +57,"Private",170287,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",336643,"Assoc-voc",11,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",264166,"Assoc-voc",11,"Divorced","Other-service","Unmarried","White","Female",0,0,45,"Columbia","<=50K" +44,"Local-gov",433705,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,52,"United-States",">50K" +28,"Private",27044,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +42,"Private",165599,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",159759,"Bachelors",13,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",385092,"Some-college",10,"Divorced","Prof-specialty","Own-child","White","Female",0,0,36,"United-States","<=50K" +42,"Private",188808,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Male",0,0,30,"United-States","<=50K" +30,"Private",167476,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +21,"State-gov",194096,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,10,"United-States","<=50K" +59,"Private",182460,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"United-States",">50K" +21,"?",102323,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +56,"Private",232139,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",341741,"Preschool",1,"Never-married","Other-service","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +21,"Private",206008,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,50,"United-States","<=50K" +48,"Private",344415,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",0,0,37,"United-States",">50K" +35,"State-gov",372130,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States","<=50K" +43,"Private",27766,"Bachelors",13,"Separated","Exec-managerial","Unmarried","White","Male",0,0,60,"United-States",">50K" +23,"Private",140764,"Assoc-voc",11,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +17,"?",161259,"10th",6,"Never-married","?","Other-relative","White","Male",0,0,12,"United-States","<=50K" +41,"Private",22201,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Japan",">50K" +35,"Self-emp-inc",187046,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States","<=50K" +22,"Private",137591,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +53,"Private",274276,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",341757,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",218542,"HS-grad",9,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +44,"Local-gov",190020,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",221436,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"Cuba",">50K" +39,"Self-emp-not-inc",52187,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Private",158776,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",51543,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +17,"Private",146329,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,23,"United-States","<=50K" +31,"Private",397467,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Private",105592,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,12,"United-States","<=50K" +39,"Private",78171,"Some-college",10,"Married-spouse-absent","Adm-clerical","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +46,"State-gov",55377,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States",">50K" +31,"Private",258932,"HS-grad",9,"Married-spouse-absent","Other-service","Not-in-family","White","Female",0,0,80,"Italy","<=50K" +18,"Private",219841,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,12,"United-States","<=50K" +46,"Private",156926,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +55,"Private",160362,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",192161,"Bachelors",13,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,43,"United-States","<=50K" +53,"Private",208570,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,26,"United-States","<=50K" +44,"Self-emp-not-inc",182771,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,48,"South",">50K" +43,"Private",151089,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +50,"Private",163002,"HS-grad",9,"Separated","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +56,"Private",155657,"7th-8th",4,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,20,"Yugoslavia","<=50K" +27,"Private",217530,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +20,"Private",244406,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +18,"Local-gov",152182,"10th",6,"Never-married","Protective-serv","Own-child","White","Female",0,0,6,"United-States","<=50K" +38,"Private",201454,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Self-emp-inc",144371,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,15,"United-States","<=50K" +55,"Private",277034,"Some-college",10,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",462832,"HS-grad",9,"Married-civ-spouse","Craft-repair","Wife","Black","Female",0,0,40,"United-States",">50K" +26,"Private",200681,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"State-gov",119565,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Puerto-Rico",">50K" +22,"Private",192017,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Local-gov",84808,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",100154,"10th",6,"Separated","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",169383,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Without-pay",43887,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,10,"United-States","<=50K" +45,"Private",54260,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,99,"United-States","<=50K" +25,"Private",476334,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +90,"Private",52386,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +33,"Private",83671,"HS-grad",9,"Never-married","Sales","Own-child","Black","Female",0,0,40,"United-States","<=50K" +45,"Private",172960,"Some-college",10,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +47,"Private",191957,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States",">50K" +38,"Local-gov",40955,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,43,"United-States","<=50K" +37,"Private",175643,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +53,"State-gov",197184,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States",">50K" +56,"Private",187295,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",40822,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,15,"United-States","<=50K" +44,"Private",228729,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"?","<=50K" +50,"Private",240496,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +26,"Private",51961,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,20,"United-States","<=50K" +36,"Private",174887,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",95855,"11th",7,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",362259,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",30916,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +62,"Private",153148,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,84,"United-States","<=50K" +46,"Private",167915,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",98776,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,15,"United-States","<=50K" +27,"Private",209801,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"?","<=50K" +38,"Private",183800,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",54595,"12th",8,"Never-married","Sales","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +34,"Private",79637,"Bachelors",13,"Never-married","Exec-managerial","Own-child","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +50,"Private",126566,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",527162,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"United-States","<=50K" +19,"Private",139466,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +23,"Private",64520,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +50,"Private",97741,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +17,"Private",350995,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +59,"?",182836,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States",">50K" +25,"Private",143267,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +21,"Private",346341,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Private",172175,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",153035,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +63,"Private",200127,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Local-gov",204470,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,43,"United-States","<=50K" +45,"Private",353012,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",194342,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",57898,"12th",8,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",164707,"Some-college",10,"Never-married","Sales","Other-relative","White","Female",0,0,40,"?","<=50K" +42,"Private",269028,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"France","<=50K" +56,"Private",83922,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",160647,"HS-grad",9,"Never-married","Farming-fishing","Unmarried","White","Female",0,0,46,"United-States","<=50K" +69,"Private",125437,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +42,"Private",246011,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,55,"United-States","<=50K" +19,"Private",216937,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","Other","Female",0,0,60,"Guatemala","<=50K" +56,"Self-emp-not-inc",66356,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +61,"Federal-gov",197311,"Masters",14,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",301743,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +39,"Private",98776,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +35,"Self-emp-not-inc",32528,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",177119,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,44,"United-States","<=50K" +40,"Self-emp-inc",193524,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +59,"State-gov",192258,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"?",145917,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +42,"Federal-gov",214838,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,30,"United-States",">50K" +59,"Private",176011,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-inc",147239,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +53,"Private",155963,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +20,"Private",360457,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,30,"United-States","<=50K" +54,"Federal-gov",114674,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Self-emp-not-inc",95708,"Masters",14,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Male",0,0,45,"United-States",">50K" +33,"Local-gov",100734,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +35,"Private",188972,"HS-grad",9,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,30,"United-States","<=50K" +22,"Private",162667,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,50,"Portugal","<=50K" +29,"Private",180758,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",46645,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +30,"Private",203258,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +17,"Private",134480,"11th",7,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,25,"United-States","<=50K" +35,"Local-gov",85548,"Some-college",10,"Separated","Adm-clerical","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +25,"Private",195994,"1st-4th",2,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,40,"Guatemala","<=50K" +42,"State-gov",148316,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",227466,"HS-grad",9,"Never-married","Other-service","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +19,"Private",68552,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +32,"Private",252257,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +44,"Private",30126,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +53,"Private",304353,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,36,"United-States",">50K" +47,"Self-emp-not-inc",171968,"Bachelors",13,"Widowed","Exec-managerial","Unmarried","Asian-Pac-Islander","Female",0,0,60,"Thailand","<=50K" +24,"Private",205839,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"State-gov",218640,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,40,"United-States",">50K" +42,"Private",150568,"HS-grad",9,"Separated","Sales","Unmarried","White","Female",0,0,45,"United-States","<=50K" +19,"Private",382738,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",138940,"11th",7,"Never-married","Farming-fishing","Own-child","White","Male",0,0,37,"United-States","<=50K" +26,"Self-emp-not-inc",258306,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,99,"United-States","<=50K" +52,"Private",152373,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",141875,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",157289,"HS-grad",9,"Married-spouse-absent","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +37,"Private",184498,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",199832,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",23545,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",175710,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +27,"Private",52028,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","Asian-Pac-Islander","Female",0,0,40,"South","<=50K" +61,"Self-emp-not-inc",315977,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +47,"Private",202322,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +30,"Private",251825,"Assoc-acdm",12,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +54,"Private",202115,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States",">50K" +56,"Local-gov",216824,"Prof-school",15,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +69,"Private",145656,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +30,"Private",137076,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",152621,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Canada",">50K" +42,"Self-emp-not-inc",27242,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +45,"Federal-gov",358242,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +26,"Private",300290,"11th",7,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"Local-gov",149991,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,42,"United-States",">50K" +31,"Private",189759,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",339482,"5th-6th",3,"Separated","Farming-fishing","Other-relative","White","Male",0,0,60,"Mexico","<=50K" +51,"Private",100933,"HS-grad",9,"Never-married","Exec-managerial","Other-relative","White","Female",0,0,40,"United-States","<=50K" +29,"Private",354558,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +64,"Private",285052,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +26,"State-gov",175044,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +68,"Private",45508,"5th-6th",3,"Married-spouse-absent","Sales","Not-in-family","White","Male",0,0,22,"United-States","<=50K" +32,"Private",173351,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +29,"Private",173611,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"?",182543,"1st-4th",2,"Separated","?","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +21,"Private",143062,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"?",137951,"10th",6,"Separated","?","Other-relative","White","Female",0,0,40,"Puerto-Rico","<=50K" +33,"Local-gov",293063,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Other-relative","Black","Male",0,0,40,"?","<=50K" +26,"Private",377754,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",193477,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +29,"Local-gov",277323,"HS-grad",9,"Never-married","Protective-serv","Unmarried","White","Male",0,0,45,"United-States","<=50K" +19,"Private",69182,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,27,"United-States","<=50K" +51,"Private",219599,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +45,"Private",129371,"9th",5,"Separated","Other-service","Unmarried","Other","Female",0,0,40,"Trinadad&Tobago","<=50K" +20,"Private",470875,"HS-grad",9,"Married-civ-spouse","Sales","Own-child","Black","Male",0,0,32,"United-States","<=50K" +40,"Private",201734,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +52,"Local-gov",91689,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",166546,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +24,"Private",293324,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",219262,"9th",5,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +38,"Self-emp-not-inc",403391,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +44,"Private",367749,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"Mexico","<=50K" +24,"Private",128487,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"State-gov",111363,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,75,"United-States",">50K" +49,"Private",240869,"7th-8th",4,"Never-married","Other-service","Other-relative","White","Male",0,0,35,"United-States","<=50K" +36,"Private",163278,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",416415,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +46,"?",280030,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Mexico","<=50K" +46,"Private",251243,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Local-gov",167159,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,70,"United-States",">50K" +29,"Private",161857,"HS-grad",9,"Married-spouse-absent","Other-service","Not-in-family","Other","Female",0,0,40,"Columbia","<=50K" +37,"Private",160035,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"?",190205,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States","<=50K" +28,"?",161290,"Some-college",10,"Never-married","?","Own-child","Black","Female",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",112403,"Bachelors",13,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"Private",238726,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +52,"Private",164530,"11th",7,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +19,"Private",456572,"HS-grad",9,"Never-married","Farming-fishing","Other-relative","White","Male",0,0,35,"United-States","<=50K" +31,"Self-emp-not-inc",177675,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",102953,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"?",224238,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,2,"United-States","<=50K" +46,"Private",155489,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States",">50K" +40,"Local-gov",261497,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,35,"United-States","<=50K" +58,"Private",365511,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","Other","Male",0,0,40,"Mexico","<=50K" +36,"Private",187999,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Local-gov",190350,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,35,"United-States","<=50K" +17,"?",166759,"12th",8,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +49,"Private",168262,"10th",6,"Divorced","Other-service","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +46,"Private",165953,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +26,"Private",375980,"HS-grad",9,"Separated","Sales","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +40,"Federal-gov",406463,"Masters",14,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"State-gov",231472,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +60,"Self-emp-not-inc",78913,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"Private",69107,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +22,"?",182387,"Some-college",10,"Never-married","?","Not-in-family","Asian-Pac-Islander","Female",0,0,12,"Thailand","<=50K" +31,"Private",169002,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,55,"United-States","<=50K" +34,"Private",422836,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,40,"Mexico","<=50K" +27,"State-gov",230922,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"Scotland","<=50K" +40,"Private",195892,"Some-college",10,"Divorced","Transport-moving","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +68,"Private",163346,"HS-grad",9,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +51,"Private",82566,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +55,"Private",86505,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,20,"United-States","<=50K" +43,"Private",178780,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +23,"State-gov",173945,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,27,"United-States","<=50K" +48,"Private",176810,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",113838,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +31,"Local-gov",121055,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States",">50K" +71,"?",52171,"7th-8th",4,"Divorced","?","Unmarried","White","Male",0,0,45,"United-States","<=50K" +17,"Private",566049,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,8,"United-States","<=50K" +37,"Private",67433,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +26,"Private",39014,"12th",8,"Married-civ-spouse","Priv-house-serv","Wife","Other","Female",0,0,40,"Dominican-Republic","<=50K" +17,"Private",51939,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +34,"Private",100669,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +33,"Private",112847,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +41,"Local-gov",32185,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Private",138370,"10th",6,"Married-spouse-absent","Protective-serv","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +46,"Private",180505,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +45,"Private",168262,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",85126,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",113838,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"Private",197905,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",316589,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",336367,"Assoc-acdm",12,"Never-married","Exec-managerial","Unmarried","White","Male",0,0,50,"United-States","<=50K" +23,"Private",209955,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",210013,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",224541,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",88061,"11th",7,"Married-spouse-absent","Machine-op-inspct","Unmarried","Asian-Pac-Islander","Female",0,0,40,"South","<=50K" +49,"Private",43206,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,55,"United-States",">50K" +37,"Private",202950,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",154093,"HS-grad",9,"Never-married","Transport-moving","Own-child","Black","Male",0,0,40,"United-States","<=50K" +51,"Private",355954,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +24,"Private",379418,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +67,"Self-emp-not-inc",286372,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",387270,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +21,"Private",270043,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +39,"Self-emp-not-inc",65738,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,15,"United-States",">50K" +33,"Private",159888,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",278039,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +21,"Private",265434,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,30,"United-States","<=50K" +24,"Private",208882,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",53513,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,45,"United-States","<=50K" +40,"Private",225193,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,63,"United-States","<=50K" +48,"Private",166809,"Bachelors",13,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +42,"Self-emp-not-inc",175674,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +45,"Federal-gov",368947,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",194901,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +53,"Private",203173,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"Private",267431,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,55,"United-States","<=50K" +32,"Private",111836,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,50,"United-States","<=50K" +34,"Private",198613,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,25,"?","<=50K" +41,"Self-emp-inc",149102,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +57,"Local-gov",121111,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",130397,"10th",6,"Never-married","Farming-fishing","Unmarried","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +17,"Private",184198,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,13,"United-States","<=50K" +17,"Private",121287,"9th",5,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +82,"Self-emp-inc",120408,"Some-college",10,"Widowed","Sales","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +40,"Private",164678,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,32,"United-States","<=50K" +26,"Private",388812,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Male",0,0,35,"United-States","<=50K" +37,"Private",294919,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",101684,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +65,"Private",36209,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,22,"United-States",">50K" +39,"Private",123983,"Bachelors",13,"Divorced","Sales","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +36,"Self-emp-not-inc",340001,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",203828,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +23,"Private",183789,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",305619,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +63,"Self-emp-not-inc",174181,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,20,"United-States","<=50K" +59,"Private",131869,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +49,"Self-emp-not-inc",43479,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"?",203126,"9th",5,"Never-married","?","Unmarried","White","Female",0,0,40,"Dominican-Republic","<=50K" +17,"Private",118792,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,9,"United-States","<=50K" +28,"Private",272913,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,30,"Mexico","<=50K" +45,"Federal-gov",222011,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Self-emp-inc",301007,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +45,"Private",197731,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",173736,"9th",5,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"?",182590,"10th",6,"Never-married","?","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +59,"Local-gov",93211,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,22,"United-States",">50K" +49,"Local-gov",219021,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,48,"United-States",">50K" +37,"Private",137229,"Assoc-voc",11,"Divorced","Sales","Not-in-family","White","Male",0,0,45,"United-States",">50K" +31,"Self-emp-not-inc",281030,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +21,"Private",234108,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",46868,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +20,"?",162667,"HS-grad",9,"Never-married","?","Other-relative","White","Male",0,0,40,"El-Salvador","<=50K" +51,"Private",173291,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",305160,"1st-4th",2,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +48,"Private",212954,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +39,"Local-gov",112284,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",152958,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",145389,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +54,"Self-emp-inc",119570,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +40,"Private",272343,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +44,"Private",187720,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,41,"United-States","<=50K" +50,"Private",145409,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +42,"Private",208726,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +34,"Private",203488,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",330416,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",25803,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",171150,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",329425,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",185452,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"Private",201179,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",182268,"Preschool",1,"Married-spouse-absent","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",95763,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +48,"Private",125892,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Poland","<=50K" +21,"Private",121407,"Assoc-voc",11,"Never-married","Other-service","Own-child","White","Female",0,0,36,"United-States","<=50K" +52,"Private",373367,"11th",7,"Widowed","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +60,"Local-gov",165982,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Private",165484,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +30,"Private",156890,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +43,"Private",244172,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,35,"?","<=50K" +36,"Private",219814,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"Guatemala","<=50K" +42,"Private",171841,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +62,"Private",205643,"Prof-school",15,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +65,"?",174904,"HS-grad",9,"Separated","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",102559,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Canada",">50K" +47,"Private",60267,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States",">50K" +43,"Private",388725,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",215712,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +44,"Private",171722,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,39,"United-States","<=50K" +25,"Private",193051,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Male",0,0,25,"United-States","<=50K" +21,"Private",305446,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",146949,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,43,"United-States","<=50K" +21,"Private",322144,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-inc",75742,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"El-Salvador",">50K" +64,"?",380687,"Bachelors",13,"Married-civ-spouse","?","Wife","Black","Female",0,0,8,"United-States","<=50K" +55,"Self-emp-not-inc",95149,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,99,"United-States","<=50K" +42,"Private",68469,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Self-emp-not-inc",27653,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +21,"Private",410439,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,24,"United-States","<=50K" +28,"Private",37821,"Assoc-voc",11,"Never-married","Sales","Unmarried","White","Female",0,0,55,"?","<=50K" +45,"Private",228570,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,35,"United-States","<=50K" +21,"Private",141453,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",88215,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","Asian-Pac-Islander","Female",0,0,40,"China",">50K" +53,"Private",48641,"12th",8,"Never-married","Other-service","Not-in-family","Other","Female",0,0,35,"United-States","<=50K" +45,"Private",185385,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",341471,"HS-grad",9,"Divorced","Priv-house-serv","Not-in-family","White","Female",0,0,4,"United-States","<=50K" +41,"Private",163322,"11th",7,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,36,"United-States","<=50K" +43,"Self-emp-inc",602513,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +53,"Local-gov",287192,"1st-4th",2,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,32,"Mexico","<=50K" +34,"Private",215047,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +59,"Private",308118,"Assoc-acdm",12,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +53,"Private",137192,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","Asian-Pac-Islander","Male",0,0,50,"United-States","<=50K" +33,"Private",275369,"7th-8th",4,"Separated","Handlers-cleaners","Not-in-family","Black","Male",0,0,35,"Haiti","<=50K" +45,"Private",99971,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +48,"Self-emp-inc",103713,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",253770,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +46,"Self-emp-not-inc",31267,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +17,"Private",198146,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,16,"United-States","<=50K" +23,"Private",178207,"Some-college",10,"Never-married","Handlers-cleaners","Unmarried","Amer-Indian-Eskimo","Female",0,0,35,"United-States","<=50K" +21,"Private",317175,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +53,"Federal-gov",221791,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-inc",187124,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States",">50K" +58,"State-gov",280519,"HS-grad",9,"Divorced","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",207568,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +45,"Local-gov",192684,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +39,"Private",103260,"Bachelors",13,"Married-civ-spouse","Craft-repair","Wife","White","Female",0,0,30,"United-States",">50K" +48,"Self-emp-inc",382242,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +41,"Private",106900,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,38,"United-States","<=50K" +50,"Private",55527,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","Black","Male",0,0,45,"United-States","<=50K" +23,"Private",33884,"Some-college",10,"Separated","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",29762,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +47,"Federal-gov",168109,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,70,"United-States","<=50K" +51,"Private",207449,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +60,"Self-emp-inc",189098,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",194259,"Bachelors",13,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Local-gov",194630,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Local-gov",179681,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Female",0,0,37,"United-States","<=50K" +42,"State-gov",136996,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,48,"United-States","<=50K" +32,"Private",143604,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,0,16,"United-States","<=50K" +34,"Private",261799,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,45,"United-States",">50K" +48,"Private",143281,"HS-grad",9,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +38,"Private",185556,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Italy","<=50K" +38,"Private",111499,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States",">50K" +40,"Self-emp-not-inc",280433,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"Private",37314,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +38,"Private",103408,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"?","<=50K" +26,"Private",270151,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"State-gov",96748,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,10,"United-States","<=50K" +20,"Private",164775,"5th-6th",3,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Guatemala","<=50K" +49,"Private",190319,"Bachelors",13,"Married-spouse-absent","Adm-clerical","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"Philippines","<=50K" +23,"Private",213115,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +47,"Private",156926,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"Canada",">50K" +43,"Private",112967,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Private",35373,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +60,"Self-emp-not-inc",220342,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +29,"Private",163167,"HS-grad",9,"Divorced","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",404951,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,38,"United-States","<=50K" +39,"Private",122032,"Assoc-voc",11,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",251508,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +50,"Self-emp-not-inc",197054,"Prof-school",15,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +64,"Self-emp-not-inc",36960,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",165930,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"?",178960,"11th",7,"Never-married","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Private",214503,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,44,"United-States",">50K" +51,"Private",110458,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",202125,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Self-emp-not-inc",284329,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +29,"Private",192924,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",340614,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +20,"Private",196678,"12th",8,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +18,"Private",266489,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +47,"?",99127,"Assoc-voc",11,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Self-emp-inc",215395,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +36,"Self-emp-inc",183898,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +48,"Private",97176,"HS-grad",9,"Divorced","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +40,"Private",145160,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,43,"United-States","<=50K" +51,"Private",357949,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +59,"Private",177120,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",288229,"Some-college",10,"Married-civ-spouse","Sales","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Greece","<=50K" +39,"Private",509060,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",47932,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",103925,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +44,"State-gov",183829,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +51,"Private",138852,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",188186,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Female",0,0,20,"Hungary","<=50K" +22,"Private",34616,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +19,"Private",220819,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Federal-gov",281540,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States","<=50K" +53,"Private",47396,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",141350,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +19,"Private",331433,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +40,"Federal-gov",346532,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States",">50K" +21,"Private",241367,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,10,"United-States","<=50K" +39,"Private",216256,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"Italy",">50K" +36,"Private",116138,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Cambodia","<=50K" +18,"Private",193166,"9th",5,"Never-married","Sales","Own-child","White","Female",0,0,42,"United-States","<=50K" +50,"Private",81548,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",167979,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,15,"United-States","<=50K" +19,"Private",67759,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,43,"United-States","<=50K" +53,"Private",200190,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States",">50K" +49,"Private",403112,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +40,"Private",214891,"Bachelors",13,"Married-spouse-absent","Transport-moving","Own-child","Other","Male",0,0,45,"?","<=50K" +31,"Private",142675,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",88500,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +35,"Local-gov",145308,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Local-gov",204377,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +43,"Self-emp-not-inc",260696,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +51,"Private",231181,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,21,"United-States","<=50K" +54,"Private",260052,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +76,"Local-gov",178665,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States","<=50K" +33,"Private",226267,"7th-8th",4,"Never-married","Sales","Not-in-family","White","Male",0,0,43,"Mexico","<=50K" +19,"Private",111232,"12th",8,"Never-married","Transport-moving","Own-child","White","Male",0,0,15,"United-States","<=50K" +26,"Private",212748,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",110677,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +24,"Private",306779,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +48,"Private",318331,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"State-gov",143385,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",94081,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,44,"United-States",">50K" +22,"Private",194723,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +43,"Private",163985,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",189759,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Italy","<=50K" +53,"State-gov",195922,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Federal-gov",54159,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +47,"Local-gov",166863,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",104501,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Germany",">50K" +39,"Private",210626,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",448026,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",189749,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",90934,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Male",0,0,64,"Philippines",">50K" +34,"State-gov",253121,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",181776,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +61,"Private",162397,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",70708,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,60,"United-States","<=50K" +47,"State-gov",103406,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",224658,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +26,"Local-gov",213451,"Some-college",10,"Never-married","Other-service","Own-child","Black","Female",0,0,10,"Jamaica","<=50K" +53,"Private",139671,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",36201,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +17,"Local-gov",173497,"11th",7,"Never-married","Prof-specialty","Own-child","Black","Male",0,0,15,"United-States","<=50K" +46,"Private",375606,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +45,"Self-emp-not-inc",107231,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,45,"France","<=50K" +23,"Private",216811,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,16,"United-States","<=50K" +41,"Private",288679,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",105516,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",282972,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,4,"United-States","<=50K" +18,"Self-emp-inc",117372,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,15,"United-States","<=50K" +38,"Private",112497,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +28,"Private",192384,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Private",43348,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +29,"Private",181822,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",216070,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","Amer-Indian-Eskimo","Female",0,0,50,"United-States",">50K" +34,"State-gov",112062,"Masters",14,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",218551,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +25,"Private",404616,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",169460,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",240081,"HS-grad",9,"Never-married","Sales","Own-child","Black","Male",0,0,40,"United-States","<=50K" +22,"Private",147655,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",90277,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"?","<=50K" +49,"Private",60751,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",491000,"Bachelors",13,"Never-married","Exec-managerial","Other-relative","Black","Male",0,0,45,"United-States","<=50K" +33,"Private",399088,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",34987,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,53,"United-States","<=50K" +26,"?",167835,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"United-States","<=50K" +31,"Private",288983,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",266070,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Local-gov",31873,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",294400,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +19,"?",184308,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,30,"United-States","<=50K" +36,"Self-emp-not-inc",175769,"Prof-school",15,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +56,"Private",182273,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",106541,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",138192,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",196791,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States",">50K" +22,"Private",223019,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +44,"Private",109273,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +60,"Self-emp-not-inc",95490,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +65,"Private",149131,"11th",7,"Divorced","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +44,"Private",219155,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"England",">50K" +53,"Local-gov",82783,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",214858,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",170230,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +40,"Self-emp-inc",209344,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,15,"?","<=50K" +35,"Private",90406,"11th",7,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +41,"Self-emp-inc",299813,"9th",5,"Married-civ-spouse","Sales","Wife","White","Female",0,0,70,"Dominican-Republic","<=50K" +28,"Private",188064,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"Canada","<=50K" +53,"Private",246117,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +26,"Private",132749,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,45,"United-States","<=50K" +28,"Local-gov",201099,"HS-grad",9,"Never-married","Transport-moving","Own-child","Black","Female",0,0,40,"United-States","<=50K" +27,"Private",97490,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",221252,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Amer-Indian-Eskimo","Female",0,0,8,"United-States","<=50K" +26,"Private",116991,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",161691,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +34,"Private",107793,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Germany",">50K" +50,"Self-emp-inc",194514,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,50,"Trinadad&Tobago","<=50K" +30,"Private",278502,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,62,"United-States","<=50K" +47,"Private",343742,"HS-grad",9,"Separated","Craft-repair","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +27,"?",204074,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"Federal-gov",31965,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",143604,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,29,"?","<=50K" +35,"Private",174308,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",162551,"12th",8,"Married-civ-spouse","Sales","Wife","Asian-Pac-Islander","Female",0,0,50,"?","<=50K" +39,"Self-emp-inc",372525,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +30,"Private",75167,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +19,"Private",93518,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +25,"?",126797,"HS-grad",9,"Married-spouse-absent","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",25124,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,60,"United-States","<=50K" +21,"Private",112137,"Some-college",10,"Never-married","Prof-specialty","Other-relative","Asian-Pac-Islander","Female",0,0,20,"South","<=50K" +30,"?",58798,"7th-8th",4,"Widowed","?","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +25,"Self-emp-not-inc",21472,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,22,"United-States","<=50K" +32,"Private",90969,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +42,"Private",52849,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",106347,"Some-college",10,"Divorced","Sales","Unmarried","White","Male",0,0,47,"United-States","<=50K" +48,"Private",199735,"Bachelors",13,"Divorced","Priv-house-serv","Not-in-family","White","Female",0,0,44,"Germany","<=50K" +24,"Private",488541,"Some-college",10,"Never-married","Other-service","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +46,"Private",403911,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +53,"Private",172991,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,25,"United-States","<=50K" +36,"Federal-gov",210945,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,70,"United-States","<=50K" +34,"Private",157446,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,45,"United-States","<=50K" +25,"Private",109390,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,70,"United-States","<=50K" +45,"Private",144579,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Federal-gov",203488,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",202871,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,20,"United-States","<=50K" +44,"Private",336906,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",177596,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"Puerto-Rico",">50K" +30,"Private",79448,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,10,"United-States","<=50K" +32,"Local-gov",191731,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +46,"?",233014,"HS-grad",9,"Divorced","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",133937,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",219211,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +35,"State-gov",94529,"HS-grad",9,"Divorced","Protective-serv","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",247547,"HS-grad",9,"Separated","Prof-specialty","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",29361,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +21,"Private",166851,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +43,"Federal-gov",197069,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Philippines",">50K" +33,"Private",153588,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Federal-gov",151369,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +42,"Private",174112,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",520033,"12th",8,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +35,"State-gov",194828,"Some-college",10,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,40,"United-States","<=50K" +32,"?",216908,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,24,"United-States","<=50K" +22,"Private",126613,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +61,"Private",26254,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",67804,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +58,"Local-gov",53481,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +42,"Private",412379,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Private",220187,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +26,"?",256141,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",268222,"HS-grad",9,"Separated","Handlers-cleaners","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +59,"Private",99131,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +36,"Private",98389,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,44,"United-States",">50K" +18,"?",211177,"12th",8,"Never-married","?","Other-relative","Black","Male",0,0,20,"United-States","<=50K" +18,"Private",115443,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",65078,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",24896,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States","<=50K" +19,"Private",184710,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,30,"United-States","<=50K" +28,"Private",410450,"Bachelors",13,"Divorced","Other-service","Unmarried","White","Female",0,0,48,"England",">50K" +37,"Private",83893,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",113309,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +60,"Private",160625,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,47,"United-States","<=50K" +17,"Local-gov",340043,"12th",8,"Never-married","Adm-clerical","Own-child","White","Female",0,0,12,"United-States","<=50K" +29,"State-gov",243875,"Assoc-voc",11,"Divorced","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",554206,"HS-grad",9,"Separated","Transport-moving","Not-in-family","Black","Male",0,0,20,"United-States","<=50K" +36,"Private",361888,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?",">50K" +37,"Self-emp-not-inc",205359,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,15,"United-States","<=50K" +47,"State-gov",167281,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",35663,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +61,"Private",357437,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",390856,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"Mexico","<=50K" +54,"Private",202415,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",77247,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +40,"Local-gov",101795,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +32,"Private",198068,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",199326,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +31,"Private",178841,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +58,"Private",136951,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +26,"Self-emp-inc",109240,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +35,"Self-emp-not-inc",128876,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",103358,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"India","<=50K" +43,"Private",354408,"12th",8,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",206051,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +45,"Private",155659,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +48,"Private",143299,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +31,"Private",252210,"5th-6th",3,"Never-married","Other-service","Own-child","White","Male",0,0,40,"Mexico","<=50K" +20,"?",129240,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,25,"United-States","<=50K" +28,"Private",398918,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",240612,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +22,"Private",429346,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +19,"Private",123718,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +38,"Private",455379,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,63,"United-States",">50K" +23,"Private",376416,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Self-emp-inc",234663,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",282142,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +45,"State-gov",208049,"HS-grad",9,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +88,"Private",68539,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",126501,"11th",7,"Never-married","Adm-clerical","Own-child","Amer-Indian-Eskimo","Female",0,0,15,"South","<=50K" +24,"Private",186452,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +84,"?",127184,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +48,"Private",165267,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","Black","Male",0,0,40,"United-States","<=50K" +46,"Private",124733,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +31,"Self-emp-inc",149726,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +58,"Private",41374,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +35,"Local-gov",329759,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",212433,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",185099,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +47,"Local-gov",126754,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",122497,"9th",5,"Widowed","Other-service","Unmarried","Black","Male",0,0,52,"?","<=50K" +30,"Private",118056,"Some-college",10,"Married-spouse-absent","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +30,"Local-gov",200892,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Self-emp-inc",84119,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,43,"United-States","<=50K" +23,"Local-gov",197918,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States",">50K" +41,"Self-emp-not-inc",150533,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Private",443742,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +27,"Private",104423,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"Private",169133,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +21,"Private",185551,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,36,"United-States","<=50K" +60,"Private",174486,"HS-grad",9,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +69,"State-gov",50468,"Prof-school",15,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,34,"United-States",">50K" +24,"Private",196943,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",120691,"HS-grad",9,"Never-married","Sales","Own-child","Black","Male",0,0,25,"United-States","<=50K" +60,"State-gov",198815,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,20,"Mexico","<=50K" +64,"Private",22186,"Some-college",10,"Widowed","Tech-support","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +39,"Self-emp-inc",188069,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +51,"Private",233149,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +51,"Private",138358,"10th",6,"Divorced","Craft-repair","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +25,"Private",338013,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"?",332666,"10th",6,"Never-married","?","Own-child","White","Female",0,0,4,"United-States","<=50K" +37,"Private",166339,"Some-college",10,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +74,"Self-emp-not-inc",392886,"HS-grad",9,"Widowed","Farming-fishing","Not-in-family","White","Female",0,0,14,"United-States","<=50K" +26,"State-gov",141838,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +23,"Private",520759,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,30,"United-States","<=50K" +57,"Self-emp-inc",37345,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,36,"United-States",">50K" +20,"Private",387779,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,15,"United-States","<=50K" +37,"Private",201531,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",123598,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",380614,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States",">50K" +40,"Private",83859,"HS-grad",9,"Widowed","Machine-op-inspct","Own-child","White","Female",0,0,30,"United-States","<=50K" +50,"State-gov",24790,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",266820,"Preschool",1,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,35,"Mexico","<=50K" +44,"Private",85440,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +41,"Private",421837,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",224566,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +54,"Private",294991,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Federal-gov",189610,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,52,"United-States","<=50K" +38,"Private",70995,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +20,"Private",215232,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,10,"United-States","<=50K" +71,"?",178295,"Assoc-acdm",12,"Married-civ-spouse","?","Husband","White","Male",0,0,3,"United-States","<=50K" +35,"Private",56201,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +62,"Private",98076,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",351810,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"Cuba","<=50K" +56,"Self-emp-not-inc",144351,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,90,"United-States","<=50K" +30,"State-gov",137613,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,20,"Taiwan","<=50K" +17,"Private",54257,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +35,"Private",98389,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",184135,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Male",0,0,1,"United-States","<=50K" +46,"Self-emp-not-inc",140121,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +33,"Self-emp-not-inc",24504,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +27,"Private",129528,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",415578,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",97142,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",201328,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Private",256620,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Federal-gov",96854,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",95519,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,42,"United-States",">50K" +47,"Private",112791,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",291407,"11th",7,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",239659,"Some-college",10,"Separated","Machine-op-inspct","Unmarried","Black","Female",0,0,70,"United-States","<=50K" +28,"Private",183151,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +58,"?",97634,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",143807,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",186934,"Masters",14,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +30,"Private",170065,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"State-gov",83696,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Female",0,0,38,"?","<=50K" +21,"Private",204596,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +56,"?",32604,"Some-college",10,"Never-married","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +20,"Private",85041,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,20,"United-States","<=50K" +62,"Local-gov",140851,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",196280,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +52,"Federal-gov",38973,"Bachelors",13,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",39182,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",198841,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",694812,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",247444,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Nicaragua","<=50K" +41,"Private",294270,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States","<=50K" +59,"Private",195820,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",329426,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +19,"?",174871,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,23,"United-States","<=50K" +41,"Private",116103,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +27,"Private",206903,"Bachelors",13,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,35,"United-States","<=50K" +50,"Private",217577,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",337693,"5th-6th",3,"Never-married","Other-service","Own-child","White","Female",0,0,40,"El-Salvador","<=50K" +38,"Private",204501,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +30,"Private",169186,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,60,"United-States","<=50K" +48,"Private",109421,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +40,"Private",200479,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Local-gov",221317,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +59,"Self-emp-not-inc",132925,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +31,"?",283531,"HS-grad",9,"Divorced","?","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +34,"Private",170769,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +47,"Self-emp-inc",186410,"Prof-school",15,"Never-married","Other-service","Not-in-family","White","Male",0,0,60,"United-States",">50K" +64,"Self-emp-inc",307786,"1st-4th",2,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"United-States","<=50K" +29,"Private",380560,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +38,"Local-gov",147258,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",124356,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +53,"Private",98791,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",216473,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +70,"?",135339,"Bachelors",13,"Married-civ-spouse","?","Husband","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +38,"Private",107303,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",152744,"Bachelors",13,"Divorced","Sales","Other-relative","Asian-Pac-Islander","Female",0,0,40,"South","<=50K" +34,"Self-emp-not-inc",100079,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,55,"India","<=50K" +24,"Private",117779,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,10,"Hungary","<=50K" +23,"Private",197613,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",411068,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +47,"Private",192984,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Federal-gov",137184,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,50,"United-States",">50K" +63,"Self-emp-not-inc",231105,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,35,"United-States",">50K" +18,"Local-gov",146586,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,60,"United-States","<=50K" +32,"Private",32406,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +33,"Private",578701,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"?","<=50K" +19,"Private",206777,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +27,"Local-gov",133495,"HS-grad",9,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",34722,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,48,"United-States",">50K" +38,"Self-emp-not-inc",133299,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",24967,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,47,"United-States","<=50K" +35,"Self-emp-not-inc",171968,"HS-grad",9,"Separated","Transport-moving","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +22,"Private",412156,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",51290,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",293565,"10th",6,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",226288,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Self-emp-inc",110445,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +34,"Private",160634,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",174242,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",390316,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +18,"Private",298860,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +65,"Private",171584,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",232664,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +64,"Private",63676,"10th",6,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +68,"Private",170376,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Self-emp-not-inc",175964,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",105813,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States",">50K" +50,"Federal-gov",306707,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,12,"United-States","<=50K" +45,"Private",177543,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,28,"United-States","<=50K" +43,"Private",320277,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",129495,"Some-college",10,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +45,"Private",275995,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States",">50K" +20,"?",86318,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,10,"United-States","<=50K" +36,"Private",280440,"Assoc-acdm",12,"Never-married","Tech-support","Unmarried","White","Female",0,0,45,"United-States","<=50K" +26,"Private",371556,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",408229,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +47,"Private",149337,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +53,"Private",355802,"Some-college",10,"Widowed","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +44,"Self-emp-not-inc",112507,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",462869,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +35,"Private",413648,"5th-6th",3,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,36,"United-States","<=50K" +34,"Private",29235,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",149823,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",39530,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,4,"United-States","<=50K" +23,"Private",197387,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,37,"Mexico","<=50K" +56,"Local-gov",255406,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",168322,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +46,"Private",278322,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",115813,"Assoc-acdm",12,"Separated","Adm-clerical","Unmarried","White","Female",0,0,57,"United-States","<=50K" +42,"Private",289636,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,46,"United-States","<=50K" +48,"Private",101684,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",133425,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +40,"Private",349405,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,36,"United-States","<=50K" +75,"Self-emp-not-inc",165968,"Assoc-voc",11,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +39,"Private",185099,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States",">50K" +46,"Federal-gov",268281,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +51,"Private",154949,"HS-grad",9,"Widowed","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +34,"Private",176711,"HS-grad",9,"Divorced","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",165064,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",213750,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +45,"Self-emp-not-inc",77132,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +21,"Private",109667,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",162164,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +40,"Private",219591,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"?",327462,"10th",6,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +68,"Private",236943,"9th",5,"Divorced","Farming-fishing","Not-in-family","Black","Male",0,0,20,"United-States","<=50K" +40,"Private",89226,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",124751,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,24,"United-States","<=50K" +48,"Local-gov",144122,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +27,"Private",98769,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +57,"Federal-gov",170066,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-inc",162439,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,98,"United-States",">50K" +47,"Private",22900,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Local-gov",102130,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"?",215743,"11th",7,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",381583,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,45,"United-States",">50K" +56,"Local-gov",198277,"12th",8,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",243178,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,28,"United-States","<=50K" +38,"Local-gov",177305,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States","<=50K" +19,"Private",167149,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +31,"Private",382368,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"Germany","<=50K" +44,"Local-gov",277144,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,60,"United-States","<=50K" +41,"Private",171351,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",265099,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +23,"Private",105617,"9th",5,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Local-gov",217689,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Amer-Indian-Eskimo","Male",0,0,32,"United-States","<=50K" +46,"?",81136,"Assoc-voc",11,"Divorced","?","Unmarried","White","Male",0,0,30,"United-States","<=50K" +43,"Self-emp-not-inc",73883,"Bachelors",13,"Divorced","Sales","Unmarried","White","Male",0,0,45,"United-States","<=50K" +31,"Private",339482,"1st-4th",2,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +40,"Private",326232,"Some-college",10,"Divorced","Transport-moving","Unmarried","White","Male",0,0,40,"United-States",">50K" +27,"Private",106316,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +64,"Local-gov",198728,"Some-college",10,"Never-married","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +31,"Federal-gov",126501,"Assoc-voc",11,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"Private",233802,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,45,"United-States","<=50K" +37,"Self-emp-not-inc",204501,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"Canada",">50K" +28,"Private",208249,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Male",0,0,24,"United-States","<=50K" +42,"Private",188693,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-inc",93272,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +17,"Private",159299,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +21,"?",303588,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +46,"Private",35136,"10th",6,"Divorced","Adm-clerical","Own-child","Black","Male",0,0,40,"United-States","<=50K" +18,"Private",139576,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",252355,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,27,"United-States","<=50K" +44,"Self-emp-not-inc",83812,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +36,"Private",89718,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +65,"Private",222810,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",456618,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +21,"Private",296158,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,25,"United-States","<=50K" +28,"Private",36601,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +27,"Private",195337,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"State-gov",282721,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Male",0,0,12,"United-States","<=50K" +40,"Private",206049,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",223392,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,15,"United-States","<=50K" +37,"Private",131827,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +33,"Private",549413,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States",">50K" +34,"Private",69491,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Local-gov",193755,"Assoc-acdm",12,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",598802,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",266255,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +59,"Private",32954,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +40,"Private",291808,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",190728,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",59184,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +41,"Private",196456,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +59,"Private",147989,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States",">50K" +50,"Private",195784,"12th",8,"Divorced","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +21,"Private",202214,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +40,"Self-emp-inc",225165,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",54825,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",188905,"5th-6th",3,"Separated","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +17,"Private",132636,"11th",7,"Never-married","Transport-moving","Own-child","White","Female",0,0,16,"United-States","<=50K" +42,"Local-gov",228320,"7th-8th",4,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",415500,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States",">50K" +19,"Private",254247,"12th",8,"Never-married","Adm-clerical","Own-child","White","Male",0,0,38,"?","<=50K" +43,"Private",255635,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",0,0,40,"Mexico","<=50K" +46,"Private",96080,"9th",5,"Separated","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +18,"?",78181,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +50,"Local-gov",339547,"Prof-school",15,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Laos",">50K" +47,"Self-emp-not-inc",126500,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +33,"Private",159574,"7th-8th",4,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +59,"Self-emp-not-inc",128105,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +39,"Local-gov",89508,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",370242,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",67257,"Bachelors",13,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +24,"Private",62952,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",29235,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,20,"United-States","<=50K" +52,"State-gov",101119,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Federal-gov",140516,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",159888,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States",">50K" +19,"?",45643,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,25,"United-States","<=50K" +23,"Private",166371,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,60,"United-States","<=50K" +37,"State-gov",160910,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"State-gov",257064,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,38,"United-States","<=50K" +30,"Private",83253,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +40,"Private",128700,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",243010,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","Other","Male",0,0,32,"United-States","<=50K" +24,"Private",132320,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,45,"United-States","<=50K" +32,"Private",234755,"HS-grad",9,"Separated","Craft-repair","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",142616,"HS-grad",9,"Separated","Other-service","Own-child","Black","Female",0,0,30,"United-States","<=50K" +20,"Private",148509,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"State-gov",240738,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",32276,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,28,"United-States","<=50K" +50,"Local-gov",163921,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",464103,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Local-gov",327825,"HS-grad",9,"Divorced","Protective-serv","Own-child","White","Female",0,0,32,"United-States","<=50K" +37,"Private",267085,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",234663,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +55,"Private",104996,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +61,"Private",101265,"12th",8,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,40,"Italy","<=50K" +22,"Private",184975,"HS-grad",9,"Married-spouse-absent","Other-service","Own-child","White","Female",0,0,3,"United-States","<=50K" +23,"Private",246965,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,12,"United-States","<=50K" +39,"Private",301867,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,24,"Philippines","<=50K" +21,"Private",185948,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +52,"Self-emp-inc",134854,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Self-emp-not-inc",95949,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +51,"Self-emp-not-inc",88528,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,99,"United-States","<=50K" +47,"Private",24723,"10th",6,"Divorced","Exec-managerial","Not-in-family","Amer-Indian-Eskimo","Female",0,0,45,"United-States","<=50K" +49,"?",171411,"9th",5,"Divorced","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",184581,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Federal-gov",100067,"Some-college",10,"Widowed","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",182863,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +20,"Never-worked",462294,"Some-college",10,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +61,"Private",85434,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +72,"Private",158092,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +19,"Private",104844,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +47,"?",89806,"Some-college",10,"Divorced","?","Not-in-family","Amer-Indian-Eskimo","Female",0,0,35,"United-States","<=50K" +24,"Private",89347,"11th",7,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",157236,"Some-college",10,"Married-spouse-absent","Handlers-cleaners","Unmarried","White","Male",0,0,40,"Poland","<=50K" +19,"Private",261259,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +20,"Private",286166,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +23,"Private",122272,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Female",0,0,40,"United-States","<=50K" +58,"Private",248739,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,53,"United-States",">50K" +20,"Private",224238,"12th",8,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +62,"Private",138157,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,12,"United-States","<=50K" +67,"Private",236627,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,2,"United-States","<=50K" +37,"Local-gov",191364,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"France",">50K" +38,"Private",391040,"Assoc-voc",11,"Separated","Tech-support","Unmarried","White","Female",0,0,20,"United-States","<=50K" +23,"Private",134997,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,80,"United-States","<=50K" +28,"Private",392487,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +25,"Private",216724,"HS-grad",9,"Divorced","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",96073,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +31,"Self-emp-inc",103435,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Self-emp-not-inc",96718,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,37,"United-States","<=50K" +51,"Private",173987,"9th",5,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",224849,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",249857,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +34,"Private",340458,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"?",440417,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,15,"United-States","<=50K" +36,"Private",175643,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +35,"Private",297485,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",232954,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"Private",109419,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",127768,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,32,"United-States",">50K" +41,"Private",252986,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +20,"Private",380544,"Assoc-acdm",12,"Never-married","Transport-moving","Own-child","White","Male",0,0,20,"United-States","<=50K" +52,"Private",306108,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",232855,"Some-college",10,"Separated","Other-service","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +44,"Private",130126,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +50,"Private",194231,"Masters",14,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States",">50K" +49,"Self-emp-inc",197038,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +36,"?",168223,"Bachelors",13,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +71,"State-gov",26109,"Prof-school",15,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,28,"United-States","<=50K" +20,"Private",285671,"HS-grad",9,"Never-married","Other-service","Other-relative","Black","Male",0,0,25,"United-States","<=50K" +20,"Private",153583,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"?","<=50K" +59,"Self-emp-inc",103948,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +38,"Private",40319,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +55,"Local-gov",159028,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",98675,"9th",5,"Never-married","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +45,"Private",90758,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +43,"Self-emp-not-inc",75435,"HS-grad",9,"Divorced","Craft-repair","Unmarried","Amer-Indian-Eskimo","Male",0,0,30,"United-States","<=50K" +19,"Private",219189,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +33,"Private",203463,"HS-grad",9,"Divorced","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +63,"Private",187635,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",27153,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",150324,"Assoc-acdm",12,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +21,"Private",83704,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",176262,"Assoc-voc",11,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,36,"United-States","<=50K" +20,"Private",179423,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,8,"United-States","<=50K" +45,"Private",168038,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States",">50K" +59,"Private",108765,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +66,"Local-gov",188220,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States",">50K" +29,"Private",114870,"Some-college",10,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"State-gov",77723,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +57,"Private",133902,"HS-grad",9,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +57,"Private",191318,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Self-emp-inc",67794,"HS-grad",9,"Married-spouse-absent","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +56,"Private",117872,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +26,"Private",55929,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +22,"?",165065,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"Italy","<=50K" +26,"Self-emp-not-inc",34307,"Assoc-voc",11,"Never-married","Farming-fishing","Own-child","White","Male",0,0,65,"United-States","<=50K" +33,"Private",246038,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Self-emp-not-inc",147258,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +45,"Private",329144,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",216181,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,36,"Iran","<=50K" +23,"Private",391171,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Male",0,0,25,"United-States","<=50K" +35,"Local-gov",223242,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",38240,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",148444,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +56,"State-gov",110257,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Federal-gov",101345,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +44,"Private",268098,"12th",8,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,36,"United-States","<=50K" +21,"?",369084,"Some-college",10,"Never-married","?","Other-relative","White","Male",0,0,10,"United-States","<=50K" +20,"Private",162688,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,38,"United-States","<=50K" +17,"?",48751,"11th",7,"Never-married","?","Own-child","Black","Female",0,0,40,"United-States","<=50K" +44,"Federal-gov",184099,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",307496,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,23,"United-States","<=50K" +71,"?",176986,"HS-grad",9,"Widowed","?","Unmarried","White","Male",0,0,24,"United-States","<=50K" +23,"Private",267955,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",283969,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"Mexico","<=50K" +29,"State-gov",204516,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,15,"United-States","<=50K" +33,"Private",167771,"Some-college",10,"Separated","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +46,"Private",345073,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,48,"United-States",">50K" +21,"?",380219,"Some-college",10,"Never-married","?","Own-child","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",185097,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +29,"Private",144808,"Some-college",10,"Married-civ-spouse","Exec-managerial","Own-child","Black","Female",0,0,40,"United-States","<=50K" +34,"Private",187203,"Assoc-acdm",12,"Never-married","Sales","Unmarried","White","Male",0,0,50,"United-States","<=50K" +26,"Private",125089,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",289458,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",144798,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"?",172152,"Bachelors",13,"Never-married","?","Not-in-family","Asian-Pac-Islander","Male",0,0,25,"Taiwan","<=50K" +28,"Private",207513,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,48,"United-States","<=50K" +24,"?",164574,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",213024,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Self-emp-not-inc",83374,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,30,"United-States",">50K" +37,"Private",192939,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",424494,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States","<=50K" +24,"Private",215243,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +40,"Private",30682,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +20,"Private",306639,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +23,"Local-gov",218678,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",219130,"Some-college",10,"Never-married","Other-service","Not-in-family","Other","Female",0,0,40,"United-States","<=50K" +64,"Private",180624,"Assoc-acdm",12,"Never-married","Prof-specialty","Other-relative","White","Female",0,0,30,"United-States","<=50K" +28,"Private",194472,"Some-college",10,"Married-civ-spouse","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +52,"Local-gov",205767,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States",">50K" +28,"Private",249870,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +31,"Private",211242,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +77,"Private",149912,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +22,"Private",85389,"HS-grad",9,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"?",806316,"11th",7,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +38,"Private",329980,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +45,"?",236612,"11th",7,"Divorced","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +25,"Local-gov",249214,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +50,"Private",257126,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Local-gov",204397,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +24,"Private",291979,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",138667,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +30,"Private",94413,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +31,"Federal-gov",166626,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +39,"State-gov",326566,"Some-college",10,"Never-married","Transport-moving","Own-child","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",165503,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,65,"United-States","<=50K" +48,"Private",102597,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,44,"United-States","<=50K" +62,"?",113234,"Masters",14,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States","<=50K" +39,"Private",177277,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +45,"Private",260490,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +32,"Private",237478,"11th",7,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Federal-gov",36885,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +17,"Private",166242,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +19,"?",158603,"10th",6,"Never-married","?","Own-child","Black","Male",0,0,25,"United-States","<=50K" +25,"Private",274228,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,84,"United-States","<=50K" +42,"Private",185145,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,57,"United-States","<=50K" +66,"Private",28367,"Bachelors",13,"Married-civ-spouse","Priv-house-serv","Other-relative","White","Male",0,0,99,"United-States","<=50K" +63,"Self-emp-not-inc",28612,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +43,"Private",191429,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,25,"United-States","<=50K" +26,"Private",459548,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,20,"Mexico","<=50K" +23,"Private",65481,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States",">50K" +39,"Private",186130,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +47,"Self-emp-inc",350759,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",359678,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",0,0,48,"United-States","<=50K" +35,"Private",220595,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",29599,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"State-gov",299153,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +46,"Private",75256,"HS-grad",9,"Married-civ-spouse","Priv-house-serv","Wife","White","Female",0,0,40,"United-States","<=50K" +43,"Private",143583,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +41,"Private",308550,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,60,"United-States","<=50K" +50,"Private",145717,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +36,"Private",334366,"11th",7,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +31,"?",76198,"HS-grad",9,"Separated","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +45,"Self-emp-not-inc",155489,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +50,"Private",197322,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Private",194259,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States","<=50K" +40,"Private",346189,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +64,"?",178556,"10th",6,"Married-civ-spouse","?","Husband","White","Male",0,0,56,"United-States",">50K" +51,"Self-emp-inc",162943,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +56,"State-gov",67662,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,39,"United-States","<=50K" +35,"Private",126675,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States","<=50K" +55,"Self-emp-not-inc",278228,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +30,"Private",169152,"HS-grad",9,"Never-married","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",204052,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",215392,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +43,"Self-emp-inc",83348,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +24,"Local-gov",196816,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Private",541343,"10th",6,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +33,"Local-gov",55921,"Assoc-voc",11,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +32,"Private",251701,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"?","<=50K" +29,"Federal-gov",119848,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",25837,"11th",7,"Never-married","Prof-specialty","Own-child","White","Male",0,0,15,"United-States","<=50K" +20,"Private",236592,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +45,"State-gov",199326,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +22,"Private",341610,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,35,"?","<=50K" +45,"Private",175958,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",198965,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",193537,"7th-8th",4,"Married-spouse-absent","Other-service","Not-in-family","White","Female",0,0,35,"Puerto-Rico","<=50K" +24,"Private",438839,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",298227,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,35,"United-States","<=50K" +28,"Private",271466,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +23,"Private",335570,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +21,"Private",206891,"7th-8th",4,"Never-married","Farming-fishing","Own-child","White","Female",0,0,38,"United-States","<=50K" +23,"Private",162551,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,20,"United-States","<=50K" +45,"Private",145637,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,48,"United-States","<=50K" +41,"Private",101290,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Federal-gov",229376,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",439592,"Some-college",10,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +37,"Private",161141,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +70,"Private",304570,"Bachelors",13,"Widowed","Machine-op-inspct","Other-relative","Asian-Pac-Islander","Male",0,0,32,"Philippines","<=50K" +28,"Local-gov",407672,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",73928,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,20,"United-States","<=50K" +69,"Private",230417,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"China",">50K" +37,"Private",260093,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",96020,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +54,"Private",104421,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"State-gov",93415,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +27,"Local-gov",282664,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Other","Female",0,0,45,"?","<=50K" +21,"Private",202871,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,44,"United-States","<=50K" +29,"Private",169683,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",271603,"7th-8th",4,"Never-married","Other-service","Not-in-family","White","Male",0,0,24,"?","<=50K" +32,"Private",340917,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +31,"Private",329874,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"State-gov",120781,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"India",">50K" +48,"Private",138069,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +58,"Self-emp-not-inc",33309,"HS-grad",9,"Widowed","Farming-fishing","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +23,"Private",76432,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"State-gov",277635,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +49,"Local-gov",123088,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,46,"United-States","<=50K" +51,"Private",57698,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",181820,"HS-grad",9,"Separated","Craft-repair","Own-child","White","Male",0,0,53,"United-States","<=50K" +40,"Self-emp-not-inc",98985,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +59,"Private",98350,"HS-grad",9,"Divorced","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +47,"Private",125120,"Bachelors",13,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +37,"Private",243409,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +43,"Private",62857,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +40,"Private",283174,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +48,"Private",107373,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",201155,"9th",5,"Never-married","Sales","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +48,"Private",187505,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",61778,"Bachelors",13,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +28,"Private",149652,"10th",6,"Never-married","Other-service","Own-child","Black","Female",0,0,30,"United-States","<=50K" +56,"Private",170324,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"Trinadad&Tobago","<=50K" +45,"Private",165937,"HS-grad",9,"Divorced","Transport-moving","Own-child","White","Male",0,0,60,"United-States","<=50K" +60,"State-gov",114060,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"State-gov",58913,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States",">50K" +37,"State-gov",378916,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",241885,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",224421,"Assoc-voc",11,"Married-AF-spouse","Farming-fishing","Husband","White","Male",0,0,44,"United-States",">50K" +31,"?",213771,"HS-grad",9,"Widowed","?","Unmarried","White","Female",0,0,36,"United-States","<=50K" +39,"Private",315565,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"Cuba","<=50K" +31,"Local-gov",153005,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",198606,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,16,"United-States","<=50K" +19,"Private",260333,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +24,"Private",219510,"Bachelors",13,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,32,"United-States","<=50K" +34,"Private",136862,"1st-4th",2,"Never-married","Other-service","Other-relative","White","Female",0,0,40,"Guatemala","<=50K" +58,"Private",187067,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,62,"Canada","<=50K" +23,"Private",325921,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +33,"Private",268127,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +76,"Private",142535,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Male",0,0,6,"United-States","<=50K" +40,"Private",177083,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States","<=50K" +28,"Private",77009,"7th-8th",4,"Divorced","Other-service","Unmarried","White","Female",0,0,50,"United-States","<=50K" +41,"Private",306405,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States","<=50K" +22,"Federal-gov",262819,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",49087,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",53833,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Male",0,0,40,"United-States","<=50K" +22,"Private",81145,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +41,"Private",215479,"Some-college",10,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,43,"United-States","<=50K" +29,"Private",113464,"HS-grad",9,"Never-married","Transport-moving","Other-relative","Other","Male",0,0,40,"Dominican-Republic","<=50K" +72,"Federal-gov",217864,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Self-emp-inc",117721,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,65,"United-States","<=50K" +19,"Private",199484,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +25,"Private",248851,"Bachelors",13,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",116968,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +59,"Private",366618,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States","<=50K" +17,"Private",240143,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,30,"United-States","<=50K" +59,"?",424468,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +50,"?",194186,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,60,"United-States","<=50K" +29,"Private",247053,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",180599,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +29,"Local-gov",190330,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,10,"United-States","<=50K" +29,"State-gov",199450,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +32,"Local-gov",199539,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +17,"?",94366,"10th",6,"Never-married","?","Other-relative","White","Male",0,0,6,"United-States","<=50K" +50,"Self-emp-not-inc",29231,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +43,"Private",33126,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Private",102085,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",212064,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +54,"State-gov",166774,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States",">50K" +65,"Private",95303,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +18,"?",379768,"HS-grad",9,"Never-married","?","Own-child","Other","Female",0,0,40,"United-States","<=50K" +70,"Self-emp-inc",247383,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",229465,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +21,"Private",180052,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,30,"United-States","<=50K" +20,"Private",214387,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"State-gov",149337,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Male",0,0,38,"United-States","<=50K" +31,"Private",34374,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +45,"Self-emp-not-inc",58683,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",403037,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +55,"Private",32365,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +49,"Private",155489,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Self-emp-inc",289886,"HS-grad",9,"Never-married","Other-service","Unmarried","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +30,"Federal-gov",54684,"Prof-school",15,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"?","<=50K" +19,"Private",101549,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +48,"Self-emp-inc",51579,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +41,"Private",40151,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States",">50K" +29,"Private",244721,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,35,"United-States",">50K" +47,"Local-gov",228372,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States",">50K" +53,"Local-gov",236873,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +19,"Private",250249,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +71,"Private",93202,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +29,"Private",176723,"Some-college",10,"Never-married","Sales","Unmarried","White","Female",0,0,25,"United-States","<=50K" +43,"Local-gov",175526,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",91842,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +52,"Private",71768,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Private",181220,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",204516,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",89172,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,80,"United-States","<=50K" +37,"Federal-gov",143547,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",310889,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Local-gov",150324,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",216472,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +64,"Private",212838,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States",">50K" +45,"Private",168283,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",187702,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +19,"Private",60661,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,52,"United-States","<=50K" +54,"Private",115284,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,45,"United-States",">50K" +61,"Self-emp-inc",98350,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Taiwan",">50K" +18,"Private",195372,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +62,"?",81578,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",111567,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Private",244572,"HS-grad",9,"Separated","Other-service","Not-in-family","Black","Female",0,0,37,"United-States","<=50K" +54,"Private",230919,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",282604,"Some-college",10,"Married-civ-spouse","Protective-serv","Other-relative","White","Male",0,0,24,"United-States","<=50K" +54,"Private",320196,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"Germany","<=50K" +42,"Private",201466,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +51,"Federal-gov",254211,"Masters",14,"Widowed","Sales","Unmarried","White","Male",0,0,50,"El-Salvador",">50K" +41,"Private",599629,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States",">50K" +31,"State-gov",161631,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +21,"Private",202373,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +52,"Private",169549,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",127185,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,15,"United-States","<=50K" +18,"Private",184277,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +58,"Private",119751,"HS-grad",9,"Married-civ-spouse","Priv-house-serv","Other-relative","Asian-Pac-Islander","Female",0,0,60,"Philippines","<=50K" +23,"Private",294701,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +21,"Private",26842,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +43,"State-gov",114537,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",126386,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",163787,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +44,"Private",98211,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",175509,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +48,"Private",159854,"1st-4th",2,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Self-emp-inc",120920,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +24,"Private",187551,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,20,"United-States","<=50K" +41,"State-gov",27305,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",216711,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Local-gov",218596,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +54,"Private",280292,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,32,"United-States","<=50K" +40,"Private",200496,"Bachelors",13,"Separated","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",78090,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,48,"United-States","<=50K" +23,"Private",118693,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",203488,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +27,"Local-gov",172091,"HS-grad",9,"Never-married","Craft-repair","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",113364,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +72,"Self-emp-not-inc",139889,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,74,"United-States","<=50K" +32,"Private",110279,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +53,"Private",242859,"Some-college",10,"Separated","Adm-clerical","Own-child","White","Male",0,0,40,"Cuba","<=50K" +18,"Private",132986,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,10,"United-States","<=50K" +41,"Federal-gov",187462,"Assoc-voc",11,"Divorced","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",264961,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,45,"United-States","<=50K" +70,"?",148065,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,4,"United-States",">50K" +46,"Self-emp-inc",200949,"Bachelors",13,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,50,"?","<=50K" +47,"Private",47247,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +56,"Local-gov",571017,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,15,"United-States","<=50K" +47,"Private",302711,"11th",7,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-inc",50356,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",199336,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,25,"United-States","<=50K" +42,"Private",341178,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,44,"Mexico","<=50K" +42,"Federal-gov",70240,"Some-college",10,"Divorced","Exec-managerial","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +46,"Private",229394,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Private",82098,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,55,"United-States","<=50K" +57,"Private",170411,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",109532,"12th",8,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",142682,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"Dominican-Republic","<=50K" +34,"Self-emp-inc",127651,"Bachelors",13,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +27,"Local-gov",236472,"Bachelors",13,"Divorced","Prof-specialty","Other-relative","White","Female",0,0,40,"United-States","<=50K" +37,"Private",111499,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Private",425199,"Some-college",10,"Divorced","Sales","Unmarried","White","Male",0,0,45,"United-States","<=50K" +38,"Private",229009,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,45,"United-States","<=50K" +37,"Private",234807,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,37,"United-States","<=50K" +45,"Private",738812,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,46,"United-States","<=50K" +56,"Private",204816,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +64,"Private",342494,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Local-gov",226311,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Female",0,0,38,"United-States","<=50K" +23,"Private",143062,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",125155,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,90,"United-States","<=50K" +23,"Private",329925,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +26,"?",208994,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,12,"United-States","<=50K" +56,"Local-gov",212864,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",118693,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",253593,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +32,"State-gov",206051,"Some-college",10,"Married-spouse-absent","Farming-fishing","Own-child","White","Male",0,0,50,"United-States","<=50K" +72,"Private",497280,"9th",5,"Widowed","Other-service","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +19,"Private",140985,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,25,"United-States","<=50K" +25,"Local-gov",191921,"Bachelors",13,"Never-married","Craft-repair","Own-child","White","Male",0,0,25,"United-States","<=50K" +58,"Private",142158,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,35,"United-States","<=50K" +24,"Private",249046,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",213019,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,38,"United-States",">50K" +40,"Private",199599,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",186191,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,45,"?","<=50K" +25,"Private",28008,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-inc",82488,"Bachelors",13,"Married-civ-spouse","Sales","Own-child","Asian-Pac-Islander","Female",0,0,40,"Philippines",">50K" +36,"Private",117073,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",325786,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",37546,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",204226,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",133299,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",29702,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",307812,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +25,"Private",174545,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,46,"United-States","<=50K" +23,"Private",233472,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",184147,"HS-grad",9,"Separated","Sales","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +33,"Private",200246,"Some-college",10,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",166585,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +21,"Private",335570,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,30,"?","<=50K" +39,"Private",53569,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",167065,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",113364,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +40,"Federal-gov",219266,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",205975,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +56,"Private",65325,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Local-gov",194740,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",99065,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,39,"United-States","<=50K" +25,"Private",212793,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +33,"Private",112941,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +41,"State-gov",187322,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",283676,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",173682,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",168470,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +58,"Private",141807,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Italy","<=50K" +25,"Private",245628,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,15,"Mexico","<=50K" +31,"Private",264864,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +39,"Private",262841,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +55,"Private",37438,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",170800,"Assoc-voc",11,"Never-married","Other-service","Own-child","White","Female",0,0,12,"United-States","<=50K" +44,"Private",152150,"Assoc-acdm",12,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",159580,"12th",8,"Divorced","Transport-moving","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +61,"Private",477209,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,54,"United-States","<=50K" +32,"Private",70985,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",241998,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Private",249541,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",135339,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +32,"Private",44675,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,65,"United-States",">50K" +46,"State-gov",247992,"7th-8th",4,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-inc",48087,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Local-gov",114045,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +60,"State-gov",69251,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,38,"China",">50K" +67,"Private",192670,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +19,"Private",268392,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +55,"?",170994,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Private",431513,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States",">50K" +19,"State-gov",37332,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +19,"Private",35865,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +43,"Private",183891,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",150309,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,90,"United-States","<=50K" +65,"Private",93318,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,45,"United-States","<=50K" +32,"Private",171814,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"State-gov",183735,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",353541,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +72,"?",271352,"10th",6,"Divorced","?","Not-in-family","White","Male",0,0,12,"United-States","<=50K" +27,"Private",223751,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +75,"Self-emp-inc",164570,"11th",7,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +39,"?",281363,"10th",6,"Widowed","?","Unmarried","White","Female",0,0,15,"United-States","<=50K" +47,"Private",34458,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",254293,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",270147,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +48,"Private",195491,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +36,"Local-gov",255454,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +18,"Private",126125,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +33,"Private",618191,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",163110,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"State-gov",235379,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",55465,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +67,"Local-gov",181220,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +42,"Private",26672,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +59,"Private",98361,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Local-gov",219883,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +47,"Private",33865,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +68,"Private",168794,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States","<=50K" +30,"Private",94245,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",34572,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +49,"Private",348751,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",65382,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Private",178054,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"?",">50K" +24,"Private",140001,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",117789,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"Private",238917,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +52,"Local-gov",330799,"9th",5,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +48,"Private",209460,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",184779,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,20,"United-States","<=50K" +31,"Private",139000,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,25,"United-States","<=50K" +30,"Private",361742,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",260782,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"?","<=50K" +51,"Private",203435,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",100579,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",356067,"Masters",14,"Never-married","Sales","Not-in-family","White","Male",0,0,16,"United-States","<=50K" +46,"Private",87250,"Bachelors",13,"Separated","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",255817,"5th-6th",3,"Never-married","Other-service","Other-relative","White","Female",0,0,40,"El-Salvador","<=50K" +48,"Self-emp-not-inc",243631,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,30,"South","<=50K" +34,"Self-emp-inc",544268,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +42,"Self-emp-not-inc",98061,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Private",95691,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,30,"Columbia","<=50K" +47,"Private",145868,"11th",7,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",65038,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",227734,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,22,"United-States","<=50K" +19,"Local-gov",176831,"Some-college",10,"Never-married","Other-service","Own-child","Black","Female",0,0,35,"United-States","<=50K" +22,"Private",211678,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Local-gov",157240,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,70,"United-States","<=50K" +41,"Self-emp-not-inc",145441,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Yugoslavia","<=50K" +42,"Private",76487,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +31,"State-gov",557853,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,47,"United-States","<=50K" +69,"?",262352,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,32,"United-States","<=50K" +58,"Self-emp-not-inc",118253,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +36,"Private",146625,"11th",7,"Widowed","Other-service","Unmarried","Black","Female",0,0,12,"United-States","<=50K" +31,"Private",174201,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States","<=50K" +41,"Private",121130,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",385847,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"?",83439,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",114158,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,15,"United-States","<=50K" +27,"Private",381789,"12th",8,"Married-civ-spouse","Farming-fishing","Own-child","White","Male",0,0,55,"United-States","<=50K" +17,"Private",82041,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"Canada","<=50K" +35,"Self-emp-not-inc",115618,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +45,"Self-emp-not-inc",106110,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,99,"United-States","<=50K" +44,"Private",267521,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",90692,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +51,"Private",57101,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",236913,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +64,"Self-emp-not-inc",388625,"10th",6,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,10,"United-States",">50K" +54,"Self-emp-not-inc",261207,"7th-8th",4,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,45,"Cuba","<=50K" +43,"Private",245487,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,40,"Mexico","<=50K" +32,"Private",262153,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,35,"United-States","<=50K" +26,"Self-emp-not-inc",68729,"HS-grad",9,"Never-married","Sales","Other-relative","Asian-Pac-Islander","Male",0,0,50,"United-States",">50K" +37,"Private",126954,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +38,"Private",85074,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",383306,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",99373,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +66,"Local-gov",157942,"HS-grad",9,"Widowed","Transport-moving","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",241928,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","Black","Female",0,0,32,"United-States","<=50K" +37,"Private",348739,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +37,"Private",95654,"10th",6,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,35,"United-States","<=50K" +25,"Private",367306,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",270421,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +63,"?",221592,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +42,"State-gov",39239,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +32,"Private",72744,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"State-gov",367292,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Self-emp-not-inc",408498,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +65,"Self-emp-inc",157403,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",231263,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",244147,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,10,"United-States","<=50K" +24,"Private",220944,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +51,"Federal-gov",314007,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +67,"?",200862,"10th",6,"Never-married","?","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +28,"Private",33374,"11th",7,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +32,"Self-emp-inc",345489,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +77,"Private",83601,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",162302,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,20,"United-States","<=50K" +26,"Private",112847,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",147344,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +57,"State-gov",183657,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,35,"United-States",">50K" +40,"Private",130760,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +50,"Private",163948,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",316797,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Own-child","White","Male",0,0,45,"Mexico","<=50K" +54,"Federal-gov",332243,"12th",8,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Local-gov",195844,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Local-gov",387250,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +68,"?",40956,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States","<=50K" +17,"Private",178953,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +32,"Private",398988,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",535978,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +42,"Private",296982,"Some-college",10,"Divorced","Sales","Unmarried","White","Male",0,0,40,"United-States","<=50K" +40,"Private",231991,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",295799,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"State-gov",201569,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"United-States","<=50K" +58,"Private",193568,"11th",7,"Widowed","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +61,"Private",97128,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +42,"Private",203393,"Bachelors",13,"Married-civ-spouse","Craft-repair","Wife","Black","Female",0,0,35,"United-States",">50K" +49,"Private",138370,"Masters",14,"Married-spouse-absent","Protective-serv","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +41,"Self-emp-inc",120277,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"?","<=50K" +43,"Private",91949,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +46,"Private",228372,"Bachelors",13,"Divorced","Sales","Unmarried","White","Male",0,0,40,"United-States",">50K" +28,"Private",132191,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +57,"Private",195835,"Some-college",10,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",185399,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,38,"United-States","<=50K" +79,"Self-emp-not-inc",103684,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",140559,"HS-grad",9,"Married-civ-spouse","Priv-house-serv","Wife","White","Female",0,0,45,"United-States","<=50K" +35,"Federal-gov",110188,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +30,"Private",112358,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,60,"United-States",">50K" +26,"Private",151810,"10th",6,"Never-married","Farming-fishing","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +48,"Private",144844,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",205839,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +22,"Private",113760,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +50,"Private",138358,"10th",6,"Separated","Adm-clerical","Not-in-family","Black","Female",0,0,47,"Jamaica","<=50K" +47,"Self-emp-not-inc",216657,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +36,"Private",278576,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Private",174373,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +73,"Private",220019,"9th",5,"Widowed","Other-service","Unmarried","White","Female",0,0,9,"United-States","<=50K" +24,"?",311949,"HS-grad",9,"Never-married","?","Not-in-family","Asian-Pac-Islander","Female",0,0,45,"?","<=50K" +34,"Private",303867,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",154210,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Hong","<=50K" +28,"?",131310,"12th",8,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"Germany","<=50K" +46,"Private",202560,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +20,"?",358783,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +29,"Private",423024,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +24,"Private",206671,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"State-gov",245310,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +18,"Private",31983,"12th",8,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +41,"Private",124956,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,90,"United-States",">50K" +59,"Private",118358,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",491421,"5th-6th",3,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,50,"United-States","<=50K" +50,"Private",151580,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"Private",248990,"1st-4th",2,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,24,"Mexico","<=50K" +42,"Private",157425,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +36,"Private",221650,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Japan","<=50K" +62,"Private",88055,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,60,"United-States",">50K" +71,"Private",216608,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",682947,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States",">50K" +44,"Private",228124,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +19,"?",217194,"10th",6,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +49,"Self-emp-not-inc",171540,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +28,"Self-emp-not-inc",410351,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Poland","<=50K" +26,"Private",163747,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +18,"Private",108892,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,12,"United-States","<=50K" +43,"Private",180096,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",117480,"10th",6,"Never-married","Craft-repair","Own-child","White","Male",0,0,44,"United-States","<=50K" +21,"Private",163333,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +20,"Self-emp-not-inc",306710,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",150553,"Some-college",10,"Never-married","Sales","Own-child","Asian-Pac-Islander","Female",0,0,18,"Philippines","<=50K" +77,"Private",123959,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +32,"Private",24961,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Local-gov",327120,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States","<=50K" +29,"Self-emp-not-inc",33798,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"Private",298489,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"?",101697,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"United-States","<=50K" +31,"Private",144064,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +59,"Self-emp-not-inc",195835,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +29,"Federal-gov",184723,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States",">50K" +56,"Private",265086,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +19,"Private",235909,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +37,"Private",42645,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"State-gov",279878,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",104892,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",137063,"HS-grad",9,"Never-married","Sales","Unmarried","White","Male",0,0,38,"United-States","<=50K" +38,"Self-emp-not-inc",58972,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +46,"Private",191389,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,28,"United-States",">50K" +42,"Private",183241,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +29,"Private",91547,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",210959,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",365516,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +37,"Private",112271,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",269455,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +46,"Private",164379,"Bachelors",13,"Divorced","Sales","Unmarried","Black","Female",0,0,35,"United-States",">50K" +28,"Private",109621,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",104858,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,56,"United-States",">50K" +39,"Private",99270,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +44,"Private",193524,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"State-gov",313946,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",162358,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +59,"Private",200700,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,48,"United-States",">50K" +21,"Private",116489,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,60,"United-States","<=50K" +22,"Private",118310,"Assoc-acdm",12,"Never-married","Prof-specialty","Own-child","White","Female",0,0,16,"United-States","<=50K" +33,"Private",296538,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +41,"Local-gov",195897,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +31,"Self-emp-not-inc",216283,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"United-States",">50K" +62,"Private",345780,"Assoc-voc",11,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",216685,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,35,"United-States","<=50K" +28,"Local-gov",210945,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,60,"United-States","<=50K" +42,"Private",192712,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,25,"United-States","<=50K" +23,"Private",178272,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Federal-gov",321333,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",294029,"11th",7,"Never-married","Sales","Own-child","Other","Female",0,0,32,"Nicaragua","<=50K" +23,"Private",112819,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",152636,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,50,"United-States","<=50K" +63,"?",301611,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +51,"Private",134808,"HS-grad",9,"Separated","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Private",64216,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,90,"United-States","<=50K" +29,"State-gov",214284,"Masters",14,"Never-married","Prof-specialty","Unmarried","Asian-Pac-Islander","Female",0,0,20,"Taiwan","<=50K" +17,"Private",231439,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +42,"Self-emp-inc",120277,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",364685,"11th",7,"Never-married","Tech-support","Own-child","White","Female",0,0,35,"United-States","<=50K" +26,"Private",18827,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",169129,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",202051,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States",">50K" +19,"Private",574271,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,28,"United-States","<=50K" +65,"State-gov",29276,"7th-8th",4,"Widowed","Other-service","Other-relative","White","Female",0,0,24,"United-States","<=50K" +52,"Self-emp-not-inc",104501,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,60,"United-States",">50K" +17,"Private",394176,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +27,"Private",85625,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,22,"United-States","<=50K" +53,"Private",340723,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",149342,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",73715,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",143083,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,18,"United-States","<=50K" +49,"Local-gov",98738,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +86,"Private",149912,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",96129,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,60,"United-States","<=50K" +47,"Private",216096,"Some-college",10,"Married-spouse-absent","Exec-managerial","Unmarried","White","Female",0,0,35,"Puerto-Rico","<=50K" +32,"Private",171091,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +30,"Self-emp-not-inc",79303,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +25,"Local-gov",182380,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Private",36271,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +60,"Private",118197,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States","<=50K" +39,"Local-gov",193815,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",222637,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,55,"Puerto-Rico","<=50K" +27,"Private",118230,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +59,"Private",174040,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +64,"State-gov",105748,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",205100,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,45,"United-States",">50K" +39,"Private",130620,"7th-8th",4,"Married-spouse-absent","Machine-op-inspct","Unmarried","Other","Female",0,0,40,"Dominican-Republic","<=50K" +30,"?",361817,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +47,"Self-emp-not-inc",235646,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",53277,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +24,"Private",456460,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +23,"Private",293091,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +62,"Private",210935,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +48,"?",199763,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"United-States","<=50K" +62,"?",223447,"12th",8,"Divorced","?","Not-in-family","White","Male",0,0,40,"Canada","<=50K" +35,"Self-emp-not-inc",233533,"Bachelors",13,"Separated","Craft-repair","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +27,"Private",95647,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +49,"Private",199763,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +18,"Private",74539,"10th",6,"Never-married","Sales","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +19,"Private",84610,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +63,"Self-emp-inc",96930,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Private",115602,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,40,"United-States","<=50K" +24,"Private",237341,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +61,"Private",143800,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +50,"Self-emp-inc",163921,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States",">50K" +36,"Private",68273,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",113163,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,50,"United-States","<=50K" +30,"Private",345705,"Some-college",10,"Married-civ-spouse","Exec-managerial","Other-relative","White","Male",0,0,40,"United-States","<=50K" +33,"Private",192286,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,52,"United-States","<=50K" +39,"Local-gov",236391,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,38,"United-States",">50K" +42,"Private",106679,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +47,"?",308242,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",46094,"Bachelors",13,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,33,"United-States","<=50K" +29,"Private",194940,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",341643,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +23,"Private",210474,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +28,"Private",76313,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,0,60,"United-States","<=50K" +34,"Private",115858,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",55191,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +67,"Self-emp-not-inc",364862,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +49,"Private",334787,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",205733,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"?",120163,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",208591,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",115422,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",92262,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",91964,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",107682,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",597843,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"Columbia","<=50K" +19,"Private",389942,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",442274,"12th",8,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +23,"Private",595461,"7th-8th",4,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +33,"Self-emp-not-inc",127894,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +35,"Private",196899,"Bachelors",13,"Never-married","Handlers-cleaners","Not-in-family","Asian-Pac-Islander","Female",0,0,50,"Haiti","<=50K" +58,"Private",212534,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",71209,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +38,"Private",190759,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",344624,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +27,"?",194024,"9th",5,"Separated","?","Unmarried","White","Female",0,0,50,"United-States","<=50K" +19,"Private",87497,"11th",7,"Never-married","Transport-moving","Other-relative","White","Male",0,0,10,"United-States","<=50K" +22,"Private",236907,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +59,"Private",169639,"Assoc-acdm",12,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",149507,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States","<=50K" +18,"Private",294387,"11th",7,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",161708,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +28,"Private",282389,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +28,"Private",64940,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +49,"Private",195727,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Local-gov",37931,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",170720,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +41,"Private",39581,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,24,"El-Salvador","<=50K" +50,"Private",206862,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +46,"Private",216934,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"Portugal","<=50K" +20,"Private",143062,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",242391,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +28,"Private",165030,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +37,"Private",199251,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +66,"Private",174491,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"?",333305,"Some-college",10,"Married-civ-spouse","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Private",203138,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,50,"United-States",">50K" +25,"Private",220220,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,45,"United-States","<=50K" +56,"Private",201344,"Some-college",10,"Widowed","Craft-repair","Unmarried","White","Female",0,0,38,"United-States","<=50K" +47,"Self-emp-not-inc",218676,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +55,"Self-emp-not-inc",141807,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +41,"State-gov",222434,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",266860,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States",">50K" +41,"Private",159549,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",195248,"Some-college",10,"Never-married","Sales","Own-child","Other","Female",0,0,20,"United-States","<=50K" +52,"Private",109413,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",185291,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States",">50K" +21,"?",140012,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +35,"Self-emp-not-inc",114366,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",169631,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",312232,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +46,"Private",229737,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"India",">50K" +70,"?",306563,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",106014,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +21,"Private",25265,"Assoc-voc",11,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +29,"Private",71860,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +41,"Self-emp-inc",94113,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +51,"Self-emp-not-inc",208003,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",113550,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +47,"Private",83046,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",205830,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"El-Salvador","<=50K" +23,"Private",245147,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +49,"Private",274720,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",163047,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"State-gov",47902,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +50,"Private",128798,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +77,"Private",154205,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +27,"Private",176683,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,60,"United-States","<=50K" +29,"Self-emp-inc",104737,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +54,"Private",349340,"Preschool",1,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +39,"State-gov",218249,"Some-college",10,"Separated","Prof-specialty","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +32,"Private",281540,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Federal-gov",112847,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +24,"Local-gov",126613,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"United-States","<=50K" +32,"Self-emp-not-inc",34572,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +26,"Private",104045,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"?",57665,"Bachelors",13,"Divorced","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Private",359001,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,42,"United-States","<=50K" +31,"Private",201122,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",160035,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +50,"Private",167886,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",32059,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +59,"Self-emp-inc",200453,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",403072,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Private",37210,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,50,"United-States","<=50K" +32,"Private",199416,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",413227,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +29,"?",188675,"Some-college",10,"Divorced","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +42,"Private",226902,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +37,"Private",195189,"Some-college",10,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",116608,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +59,"Private",99131,"Masters",14,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +52,"Local-gov",186117,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,56,"United-States",">50K" +29,"State-gov",67053,"HS-grad",9,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Thailand","<=50K" +39,"Private",325374,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",111949,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"United-States","<=50K" +19,"Private",194905,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +60,"Local-gov",195453,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +75,"Private",316119,"Some-college",10,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +24,"State-gov",506329,"Some-college",10,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +58,"Federal-gov",319733,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,70,"United-States","<=50K" +21,"State-gov",99199,"Masters",14,"Never-married","Transport-moving","Own-child","White","Male",0,0,15,"United-States","<=50K" +28,"Private",204600,"HS-grad",9,"Separated","Protective-serv","Other-relative","White","Male",0,0,40,"United-States","<=50K" +40,"Private",173307,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",34446,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Private",175642,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +58,"Private",203735,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",197967,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States","<=50K" +29,"Private",413297,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"Mexico","<=50K" +45,"Private",240841,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",152189,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"State-gov",85874,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",362623,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +67,"?",37170,"7th-8th",4,"Divorced","?","Not-in-family","White","Male",0,0,3,"United-States","<=50K" +28,"Private",30912,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",35448,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,25,"United-States","<=50K" +33,"Private",173248,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,35,"United-States","<=50K" +37,"Private",49626,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,43,"United-States","<=50K" +19,"Private",102723,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +90,"?",166343,"1st-4th",2,"Widowed","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",168322,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Private",131117,"7th-8th",4,"Divorced","Tech-support","Unmarried","White","Female",0,0,38,"Columbia","<=50K" +20,"?",210474,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,15,"United-States","<=50K" +25,"Private",110138,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",107452,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +32,"Private",160594,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +70,"Local-gov",334666,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +57,"Private",104272,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",19491,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",128715,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +34,"Private",128063,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,36,"United-States","<=50K" +26,"Self-emp-not-inc",37023,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,78,"United-States","<=50K" +44,"Private",68748,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +66,"Private",140576,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Local-gov",327435,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",202729,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",277471,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",189670,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,50,"United-States","<=50K" +61,"Private",204908,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",171841,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",78247,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",68895,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,50,"Mexico","<=50K" +27,"Private",56658,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Amer-Indian-Eskimo","Male",0,0,8,"United-States","<=50K" +58,"Local-gov",259216,"9th",5,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"State-gov",270278,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,12,"Puerto-Rico","<=50K" +56,"Private",238806,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,26,"United-States","<=50K" +36,"Private",111128,"Some-college",10,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States",">50K" +29,"Private",119429,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +28,"Private",73037,"10th",6,"Never-married","Transport-moving","Unmarried","White","Male",0,0,30,"United-States","<=50K" +61,"Self-emp-not-inc",84409,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +66,"Self-emp-not-inc",274451,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,25,"United-States",">50K" +21,"Private",124242,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",159732,"HS-grad",9,"Widowed","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",161415,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +33,"Private",157568,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",168030,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,32,"United-States","<=50K" +82,"Self-emp-inc",130329,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"State-gov",56964,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +29,"Private",370509,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"France",">50K" +19,"Private",106306,"Some-college",10,"Divorced","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",56480,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,1,"United-States","<=50K" +27,"Private",404421,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +33,"Private",194901,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +43,"State-gov",164790,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Male",0,0,50,"United-States",">50K" +72,"Federal-gov",94242,"Some-college",10,"Widowed","Tech-support","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +68,"Self-emp-not-inc",365020,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",160512,"HS-grad",9,"Separated","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Private",170331,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +30,"Private",101266,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",217718,"5th-6th",3,"Married-spouse-absent","Other-service","Unmarried","Black","Female",0,0,30,"Haiti","<=50K" +39,"?",361838,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,6,"United-States",">50K" +41,"State-gov",283917,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +48,"Private",39530,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +66,"Self-emp-not-inc",212185,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,48,"United-States","<=50K" +25,"Self-emp-inc",90752,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +22,"?",210802,"Some-college",10,"Never-married","?","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +31,"Private",340880,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +43,"Self-emp-not-inc",113211,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +42,"Private",134509,"Some-college",10,"Never-married","Transport-moving","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +20,"State-gov",147280,"HS-grad",9,"Never-married","Other-service","Other-relative","Other","Male",0,0,40,"United-States","<=50K" +40,"Private",145441,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +65,"Private",398001,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +53,"Private",31588,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,52,"United-States",">50K" +38,"?",121135,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",186916,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",115244,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +41,"Local-gov",169995,"Some-college",10,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +48,"Self-emp-not-inc",52240,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,25,"United-States",">50K" +52,"Private",35305,"7th-8th",4,"Never-married","Other-service","Own-child","White","Female",0,0,7,"United-States","<=50K" +45,"Self-emp-not-inc",160724,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,45,"China",">50K" +29,"Private",210464,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",207685,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,21,"United-States","<=50K" +38,"Private",233717,"Some-college",10,"Divorced","Exec-managerial","Unmarried","Black","Male",0,0,60,"United-States","<=50K" +32,"Private",222205,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +37,"Private",167613,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",148773,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Local-gov",68268,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",174533,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",273230,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Private",187502,"HS-grad",9,"Never-married","Sales","Own-child","Black","Male",0,0,24,"United-States","<=50K" +47,"Private",209320,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",56841,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States","<=50K" +55,"Private",254627,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",42703,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",374137,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",196385,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",192930,"HS-grad",9,"Separated","Sales","Unmarried","White","Female",0,0,10,"United-States","<=50K" +39,"Private",99527,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",185437,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +43,"Private",247162,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Federal-gov",131534,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",184693,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"Mexico","<=50K" +27,"Private",704108,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Private",220262,"Assoc-acdm",12,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",95654,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,60,"United-States","<=50K" +67,"Private",89346,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",94392,"11th",7,"Separated","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +21,"Private",334113,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"Private",32763,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +31,"Private",136651,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +51,"Self-emp-not-inc",240236,"Assoc-acdm",12,"Separated","Sales","Not-in-family","Black","Male",0,0,30,"United-States","<=50K" +29,"Private",53271,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",31493,"Bachelors",13,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States",">50K" +32,"Private",195891,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +26,"Private",211424,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Local-gov",84657,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",151408,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Private",106819,"7th-8th",4,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,19,"United-States","<=50K" +62,"Private",132917,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,20,"United-States","<=50K" +54,"Private",146834,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"United-States","<=50K" +55,"Private",164332,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +24,"Private",30656,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +27,"Private",113501,"Masters",14,"Never-married","Adm-clerical","Own-child","White","Male",0,0,45,"United-States","<=50K" +18,"Private",165316,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,30,"United-States","<=50K" +21,"Private",126613,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Self-emp-not-inc",361280,"Some-college",10,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,80,"Philippines",">50K" +50,"?",123044,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,60,"United-States",">50K" +38,"Private",165472,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",99452,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",84977,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",240458,"11th",7,"Divorced","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +60,"Private",123218,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",115289,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",373895,"Some-college",10,"Separated","Handlers-cleaners","Not-in-family","Black","Male",0,0,35,"United-States","<=50K" +43,"Private",152617,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +49,"State-gov",72619,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States","<=50K" +17,"Private",41865,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +32,"Private",190228,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +23,"Private",193090,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +25,"Private",181896,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +46,"Local-gov",213668,"11th",7,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",99369,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Other","Female",0,0,50,"United-States","<=50K" +44,"Private",104196,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +60,"Self-emp-not-inc",176839,"Prof-school",15,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +30,"Local-gov",99502,"Assoc-voc",11,"Divorced","Protective-serv","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +24,"Private",183410,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,17,"United-States","<=50K" +17,"Private",25690,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,10,"United-States","<=50K" +76,"?",201986,"11th",7,"Widowed","?","Other-relative","White","Female",0,0,16,"United-States","<=50K" +31,"Private",188961,"Assoc-acdm",12,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +52,"Private",114971,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",121468,"Bachelors",13,"Never-married","Exec-managerial","Own-child","Asian-Pac-Islander","Female",0,0,35,"United-States","<=50K" +73,"Self-emp-inc",191540,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +38,"Private",146398,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,24,"United-States","<=50K" +48,"Private",193553,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +60,"Private",121127,"10th",6,"Widowed","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",389856,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",290504,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"United-States","<=50K" +54,"State-gov",137065,"Doctorate",16,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +50,"Local-gov",212685,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",71475,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"Private",111450,"Some-college",10,"Never-married","Adm-clerical","Other-relative","Black","Male",0,0,22,"United-States","<=50K" +35,"Private",225860,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",129853,"10th",6,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +50,"Private",99925,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,32,"United-States","<=50K" +58,"Private",227800,"1st-4th",2,"Separated","Farming-fishing","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +55,"State-gov",111130,"Assoc-acdm",12,"Divorced","Adm-clerical","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +29,"Private",100764,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +47,"Private",275095,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",147500,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,40,"United-States","<=50K" +63,"Local-gov",150079,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States",">50K" +27,"Private",140863,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +62,"?",199198,"11th",7,"Divorced","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",193372,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",196771,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +31,"Private",231826,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,52,"Mexico","<=50K" +40,"Federal-gov",196456,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +42,"Private",34037,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +52,"Private",174964,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",91608,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",403468,"Some-college",10,"Separated","Other-service","Unmarried","White","Female",0,0,50,"Mexico","<=50K" +33,"Private",112900,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +58,"Private",242670,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +54,"Private",343242,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",200733,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Self-emp-not-inc",236769,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",22494,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"Federal-gov",129379,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",239098,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",167501,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",77146,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +47,"Private",82797,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +33,"Self-emp-not-inc",134886,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +40,"Self-emp-inc",218558,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +26,"Private",196899,"Assoc-acdm",12,"Separated","Craft-repair","Not-in-family","Other","Female",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",200960,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +39,"Private",188069,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"?","<=50K" +60,"Private",232337,"7th-8th",4,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",98656,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"State-gov",194260,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +49,"?",481987,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,60,"United-States","<=50K" +31,"Private",234976,"11th",7,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,48,"United-States","<=50K" +29,"Private",349116,"HS-grad",9,"Separated","Sales","Unmarried","White","Female",0,0,25,"United-States","<=50K" +39,"Private",175390,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +26,"Private",214637,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +27,"Private",185127,"Assoc-voc",11,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Private",98752,"9th",5,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +50,"Local-gov",218382,"Some-college",10,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +51,"Private",153486,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +51,"Federal-gov",174102,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",137142,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +61,"Private",241013,"7th-8th",4,"Widowed","Farming-fishing","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",267798,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +41,"?",152880,"HS-grad",9,"Divorced","?","Not-in-family","Black","Female",0,0,28,"United-States","<=50K" +31,"Private",263561,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",39764,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",172186,"Some-college",10,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Private",61270,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Self-emp-inc",124685,"Masters",14,"Divorced","Exec-managerial","Not-in-family","Asian-Pac-Islander","Male",0,0,99,"Japan",">50K" +69,"Self-emp-not-inc",76968,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,25,"United-States","<=50K" +21,"Private",38772,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +24,"Private",172496,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +55,"Private",306164,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",33795,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +48,"Private",47686,"11th",7,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +31,"Private",193132,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +52,"Private",400004,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",101283,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",192384,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",113838,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Private",199713,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",236021,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",138938,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,10,"United-States","<=50K" +36,"Private",126946,"Some-college",10,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Private",44791,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",31964,"9th",5,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"State-gov",352156,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +70,"Self-emp-not-inc",205860,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",113106,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +57,"Private",89182,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",250782,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +28,"Private",177955,"11th",7,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"Mexico","<=50K" +32,"Private",198660,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",168740,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +45,"Private",199625,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,20,"United-States","<=50K" +22,"Private",213902,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +38,"Private",208379,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +37,"Private",113120,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",57827,"Bachelors",13,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +59,"Private",515712,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",396270,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,25,"United-States","<=50K" +30,"Private",231620,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +50,"Private",174655,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +63,"?",97823,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",176732,"9th",5,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"Private",143932,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",551962,"HS-grad",9,"Separated","Handlers-cleaners","Unmarried","White","Female",0,0,50,"Peru","<=50K" +30,"?",298577,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +39,"Private",257942,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +55,"Local-gov",253062,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",193748,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,15,"United-States","<=50K" +46,"Private",368561,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +50,"Private",192964,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,65,"United-States","<=50K" +32,"Private",217304,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","Black","Male",0,0,30,"United-States","<=50K" +18,"Private",120029,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",62124,"HS-grad",9,"Separated","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +50,"Private",94885,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +32,"Private",192565,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +23,"Local-gov",220912,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +26,"Private",184120,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +46,"Private",140782,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +43,"Self-emp-inc",170785,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +32,"Private",90705,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +37,"State-gov",108293,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,38,"United-States","<=50K" +48,"Private",168283,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +43,"Private",193672,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Local-gov",143865,"10th",6,"Widowed","Other-service","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +30,"Private",209317,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,50,"Dominican-Republic","<=50K" +34,"State-gov",204461,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Private",137088,"HS-grad",9,"Married-civ-spouse","Craft-repair","Other-relative","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +41,"Private",149102,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +53,"Private",182855,"10th",6,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,48,"United-States","<=50K" +42,"Private",572751,"Preschool",1,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Nicaragua","<=50K" +18,"Private",83451,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +81,"Private",98116,"Bachelors",13,"Widowed","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +40,"Private",119225,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",134888,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Female",0,0,35,"United-States","<=50K" +20,"Private",745817,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,15,"United-States","<=50K" +41,"Private",88368,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +49,"State-gov",122066,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +22,"Private",363219,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +46,"Private",84402,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +35,"Private",150042,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +34,"Private",48014,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +29,"Local-gov",177398,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +28,"Private",373698,"12th",8,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"?","<=50K" +35,"Private",422933,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +29,"Private",131088,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",178255,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"Columbia","<=50K" +52,"Self-emp-not-inc",129311,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,95,"United-States",">50K" +45,"Private",473171,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",236985,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +35,"?",226379,"HS-grad",9,"Married-civ-spouse","?","Other-relative","White","Female",0,0,25,"United-States","<=50K" +21,"?",277700,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +35,"Private",207568,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",85708,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",98765,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"Canada","<=50K" +29,"Private",192283,"Some-college",10,"Never-married","Other-service","Other-relative","White","Female",0,0,20,"United-States","<=50K" +29,"State-gov",271012,"10th",6,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",189265,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Private",321880,"10th",6,"Never-married","Other-service","Own-child","Black","Male",0,0,15,"United-States","<=50K" +52,"Private",177465,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,25,"United-States","<=50K" +24,"Private",127647,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +32,"State-gov",119033,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",209317,"HS-grad",9,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,40,"?","<=50K" +33,"Private",284531,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",251120,"7th-8th",4,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +28,"Private",113870,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +62,"Without-pay",170114,"Assoc-acdm",12,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",328199,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Female",0,0,64,"United-States","<=50K" +26,"Private",206307,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Federal-gov",170603,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Self-emp-not-inc",112271,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +19,"Private",118306,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,16,"United-States","<=50K" +49,"Private",126754,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States",">50K" +47,"Private",267205,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"?",">50K" +38,"Private",205359,"11th",7,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,32,"United-States","<=50K" +30,"Private",398662,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",202498,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Columbia","<=50K" +32,"Private",105650,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +46,"Private",191204,"Assoc-voc",11,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",56582,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +47,"Local-gov",51579,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,50,"United-States","<=50K" +57,"Self-emp-not-inc",152030,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,25,"United-States",">50K" +47,"Private",227310,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",55854,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,56,"United-States",">50K" +36,"Local-gov",28996,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",160634,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +37,"Private",222450,"11th",7,"Married-spouse-absent","Other-service","Other-relative","White","Male",0,0,40,"El-Salvador","<=50K" +36,"Self-emp-inc",180419,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +17,"Private",202521,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +23,"Private",186014,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +37,"Self-emp-not-inc",35330,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,42,"United-States","<=50K" +35,"Federal-gov",84848,"Some-college",10,"Never-married","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",176280,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +52,"Private",145271,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +37,"Local-gov",108320,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +48,"State-gov",106377,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,65,"United-States",">50K" +24,"Private",258730,"HS-grad",9,"Divorced","Other-service","Own-child","White","Female",0,0,40,"Japan","<=50K" +33,"Private",58305,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",341672,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +34,"Private",176648,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Black","Male",0,0,42,"United-States","<=50K" +24,"?",32616,"Bachelors",13,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",481175,"Some-college",10,"Never-married","Exec-managerial","Own-child","Other","Male",0,0,24,"Peru","<=50K" +18,"Private",25837,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +20,"Private",385077,"12th",8,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"Private",68985,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +19,"Private",181572,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +53,"Private",23698,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,46,"United-States",">50K" +34,"?",268127,"12th",8,"Separated","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",162298,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",144608,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",250630,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +31,"Private",150441,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +37,"Private",189251,"Doctorate",16,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +64,"Private",260082,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Columbia","<=50K" +42,"Private",139126,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",50132,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +36,"Self-emp-not-inc",167691,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,50,"United-States","<=50K" +36,"Private",77820,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",156513,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +24,"Private",283092,"11th",7,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,35,"Jamaica","<=50K" +22,"Private",175883,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +62,"Private",232308,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",269991,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"Puerto-Rico","<=50K" +20,"Private",305446,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +57,"Private",78707,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",351802,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,35,"United-States","<=50K" +37,"Local-gov",196529,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +35,"Self-emp-inc",175769,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States",">50K" +17,"Private",153021,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +36,"Local-gov",331902,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +50,"Private",279461,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +27,"State-gov",205499,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,77,"United-States","<=50K" +25,"Private",113099,"HS-grad",9,"Separated","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-inc",206947,"Assoc-acdm",12,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,67,"United-States","<=50K" +29,"State-gov",159782,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +19,"Private",410543,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Private",34446,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",209101,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,25,"United-States",">50K" +43,"Federal-gov",95902,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",214323,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",236323,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Federal-gov",201127,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,56,"United-States",">50K" +40,"Private",142886,"Bachelors",13,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",77313,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +17,"?",212125,"10th",6,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +36,"Private",187098,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",196857,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +53,"Local-gov",155314,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +72,"Self-emp-not-inc",203289,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +46,"Private",117059,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,60,"United-States","<=50K" +33,"Private",178587,"Some-college",10,"Separated","Prof-specialty","Unmarried","White","Female",0,0,37,"United-States","<=50K" +22,"Private",82393,"9th",5,"Never-married","Handlers-cleaners","Own-child","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +17,"?",145258,"11th",7,"Never-married","?","Other-relative","White","Female",0,0,25,"United-States","<=50K" +41,"Private",185145,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"?",">50K" +46,"Private",72896,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,43,"United-States","<=50K" +33,"Private",134886,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +32,"Private",223212,"Preschool",1,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +52,"Self-emp-not-inc",174752,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",230563,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +48,"State-gov",353824,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,72,"United-States",">50K" +22,"Private",117363,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +25,"Private",285367,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +60,"?",139391,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,42,"United-States","<=50K" +38,"Private",198170,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",38948,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +49,"Private",188515,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Self-emp-not-inc",177810,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +31,"Private",178506,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +40,"Self-emp-not-inc",129298,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"Private",165315,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,37,"United-States","<=50K" +18,"?",172214,"HS-grad",9,"Never-married","?","Own-child","Black","Female",0,0,20,"United-States","<=50K" +19,"Private",63434,"12th",8,"Never-married","Farming-fishing","Own-child","White","Female",0,0,30,"United-States","<=50K" +35,"Self-emp-inc",140854,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +28,"Private",133043,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States","<=50K" +33,"Private",259301,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,41,"United-States","<=50K" +20,"Private",196643,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",364365,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +36,"Private",269318,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Private",108454,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +32,"Private",171637,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",183589,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,25,"United-States","<=50K" +24,"Private",107801,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",179877,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",168981,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,35,"United-States","<=50K" +37,"Private",120590,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +31,"Private",310773,"Some-college",10,"Separated","Sales","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +21,"Private",197050,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +47,"Private",159726,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,85,"United-States",">50K" +23,"Private",210797,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",55291,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",276718,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +67,"Private",336163,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,24,"United-States","<=50K" +57,"Private",112840,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +17,"Private",165918,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"Peru","<=50K" +53,"Private",165745,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"State-gov",197731,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,49,"United-States",">50K" +48,"Self-emp-not-inc",197702,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",213260,"HS-grad",9,"Separated","Protective-serv","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +51,"Private",53833,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,46,"United-States",">50K" +18,"Private",89419,"HS-grad",9,"Never-married","Tech-support","Own-child","White","Female",0,0,10,"United-States","<=50K" +23,"Private",119704,"Some-college",10,"Separated","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Private",433170,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +34,"Private",182714,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,35,"?","<=50K" +39,"Private",172538,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +20,"?",220115,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,12,"United-States","<=50K" +39,"Private",158956,"Some-college",10,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +21,"Self-emp-not-inc",25631,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",476558,"7th-8th",4,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +54,"Federal-gov",35576,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",203463,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"State-gov",317647,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",170411,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"?",174182,"11th",7,"Married-civ-spouse","?","Wife","Other","Female",0,0,24,"United-States","<=50K" +54,"Private",220055,"Bachelors",13,"Widowed","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +54,"Private",231482,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",279173,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +37,"Private",89559,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +47,"Private",161950,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Female",0,0,25,"Germany","<=50K" +51,"Private",131068,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",219632,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",175507,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +58,"Self-emp-inc",182062,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,24,"United-States",">50K" +20,"?",189203,"Assoc-acdm",12,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Private",21698,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",328051,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +59,"Private",121865,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",420986,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +43,"?",218558,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"?",189740,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,32,"United-States","<=50K" +29,"Local-gov",188909,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,42,"United-States","<=50K" +28,"Private",213081,"11th",7,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"Jamaica","<=50K" +18,"Self-emp-not-inc",157131,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +49,"Private",98010,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +46,"Private",207677,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +58,"?",361870,"HS-grad",9,"Married-civ-spouse","?","Husband","Black","Male",0,0,30,"United-States","<=50K" +56,"Private",266091,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"Mexico","<=50K" +41,"Private",106627,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,50,"United-States","<=50K" +30,"Private",243165,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Private",201928,"HS-grad",9,"Widowed","Craft-repair","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",128346,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +29,"Private",197288,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +20,"?",169184,"Some-college",10,"Never-married","?","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",245521,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"Mexico","<=50K" +36,"Private",129591,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",184710,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",63734,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +18,"Private",111256,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +40,"Self-emp-inc",111483,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Self-emp-inc",266639,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",93853,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +32,"Private",184207,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",238002,"9th",5,"Married-civ-spouse","Transport-moving","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +28,"?",30237,"Some-college",10,"Never-married","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Private",144844,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",280500,"Some-college",10,"Never-married","Tech-support","Own-child","Black","Female",0,0,40,"United-States","<=50K" +73,"?",135601,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,10,"United-States","<=50K" +37,"Private",409189,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"Mexico","<=50K" +50,"Private",23686,"Some-college",10,"Married-civ-spouse","Adm-clerical","Other-relative","White","Female",0,0,35,"United-States",">50K" +19,"Private",229756,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,50,"United-States","<=50K" +32,"Local-gov",95530,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Local-gov",73199,"Assoc-voc",11,"Divorced","Tech-support","Unmarried","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +20,"Private",196745,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +29,"Private",79481,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"?",116934,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",100950,"Assoc-voc",11,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,40,"Germany","<=50K" +44,"Local-gov",56651,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,52,"United-States","<=50K" +18,"Private",186954,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +22,"Private",264874,"Some-college",10,"Never-married","Tech-support","Other-relative","White","Female",0,0,40,"United-States","<=50K" +39,"State-gov",183092,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +26,"Local-gov",273399,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"Peru","<=50K" +29,"?",142443,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States","<=50K" +21,"Private",177526,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"Local-gov",31267,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Private",321666,"Assoc-acdm",12,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,20,"United-States","<=50K" +26,"Private",331861,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,60,"?","<=50K" +25,"Private",283515,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +30,"Private",54608,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",162238,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +30,"Private",175931,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",236804,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",168782,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",227065,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Self-emp-inc",285335,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +31,"Private",259705,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Female",0,0,40,"United-States","<=50K" +57,"Private",24384,"7th-8th",4,"Widowed","Other-service","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +58,"Private",322013,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",49797,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",52566,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",266275,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Federal-gov",183804,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",173679,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Local-gov",163965,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",173585,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,15,"Peru","<=50K" +27,"Private",172009,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",44363,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +45,"Private",246392,"HS-grad",9,"Never-married","Priv-house-serv","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +53,"Private",167033,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +54,"Private",143822,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +23,"Private",447488,"9th",5,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,35,"Mexico","<=50K" +17,"Private",239346,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,18,"United-States","<=50K" +42,"Private",245975,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",34632,"12th",8,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"State-gov",24008,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +44,"Private",165492,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",326048,"Assoc-acdm",12,"Divorced","Other-service","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +46,"Private",250821,"Prof-school",15,"Divorced","Farming-fishing","Unmarried","White","Male",0,0,48,"United-States","<=50K" +37,"Self-emp-not-inc",154641,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,86,"United-States","<=50K" +35,"Private",198202,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,54,"United-States","<=50K" +27,"Local-gov",170504,"Bachelors",13,"Never-married","Transport-moving","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",191342,"Some-college",10,"Never-married","Sales","Not-in-family","Other","Male",0,0,40,"India","<=50K" +19,"Private",238969,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,10,"United-States","<=50K" +63,"Self-emp-not-inc",344128,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +69,"?",148694,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +69,"?",180187,"Assoc-acdm",12,"Widowed","?","Not-in-family","White","Female",0,0,6,"Italy","<=50K" +36,"State-gov",168894,"Assoc-voc",11,"Married-spouse-absent","Protective-serv","Own-child","White","Female",0,0,40,"Germany","<=50K" +20,"Private",203263,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +28,"State-gov",89564,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,50,"United-States","<=50K" +58,"Private",97562,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,38,"United-States","<=50K" +48,"Private",336540,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",139647,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,56,"United-States","<=50K" +50,"Local-gov",320386,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",32126,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",275445,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,50,"United-States","<=50K" +38,"Self-emp-inc",54953,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,38,"United-States","<=50K" +54,"Private",103580,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,55,"United-States",">50K" +42,"Private",245565,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,12,"England","<=50K" +32,"Private",39223,"10th",6,"Separated","Craft-repair","Unmarried","Black","Female",0,0,40,"?","<=50K" +55,"State-gov",117357,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,70,"?",">50K" +63,"Private",207385,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +21,"Private",355287,"9th",5,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,48,"Mexico","<=50K" +62,"?",141218,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States",">50K" +46,"Local-gov",207677,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",102114,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",60269,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +37,"Private",278632,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",355551,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Female",0,0,45,"Mexico","<=50K" +45,"Private",246891,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,72,"Canada",">50K" +61,"Private",191417,"9th",5,"Widowed","Exec-managerial","Not-in-family","Black","Male",0,0,65,"United-States","<=50K" +21,"Private",184543,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",122206,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",229015,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",130067,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +40,"Local-gov",306495,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States","<=50K" +32,"Private",232855,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +55,"Local-gov",171328,"Some-college",10,"Married-spouse-absent","Adm-clerical","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +64,"Private",144182,"HS-grad",9,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,23,"United-States","<=50K" +34,"Private",102858,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +19,"?",199495,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,60,"United-States","<=50K" +58,"Private",209438,"Some-college",10,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +44,"Private",184378,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",446512,"Some-college",10,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +31,"Federal-gov",113688,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +39,"Private",333305,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,45,"United-States",">50K" +19,"Private",118535,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,18,"United-States","<=50K" +56,"Private",76142,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +53,"Local-gov",38795,"9th",5,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +68,"Private",208478,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,18,"?","<=50K" +62,"Private",247483,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +62,"State-gov",198686,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",56118,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Federal-gov",359808,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",231554,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,50,"United-States","<=50K" +33,"Private",34848,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",196243,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",189487,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +22,"Private",194848,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Private",192878,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",70209,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,20,"United-States","<=50K" +52,"Federal-gov",123011,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +25,"Private",178478,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"Private",103323,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"Private",239404,"10th",6,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,45,"United-States","<=50K" +67,"Private",165082,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +36,"Private",389725,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +47,"Private",374580,"HS-grad",9,"Separated","Sales","Not-in-family","White","Female",0,0,52,"United-States","<=50K" +36,"?",187983,"HS-grad",9,"Never-married","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",259300,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +19,"Private",277695,"9th",5,"Never-married","Farming-fishing","Other-relative","White","Male",0,0,16,"Mexico","<=50K" +24,"Private",230248,"7th-8th",4,"Separated","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",196342,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,25,"United-States","<=50K" +17,"Private",160968,"11th",7,"Never-married","Adm-clerical","Own-child","White","Male",0,0,16,"United-States","<=50K" +28,"Private",115438,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",129597,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,46,"United-States","<=50K" +24,"Local-gov",387108,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States","<=50K" +43,"Private",105936,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States",">50K" +20,"Private",107242,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"?","<=50K" +55,"Private",125000,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States",">50K" +22,"Private",229456,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,35,"United-States","<=50K" +20,"Private",230113,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,50,"United-States","<=50K" +44,"Private",106698,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",133454,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",295520,"9th",5,"Widowed","Sales","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +23,"Private",320294,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",162381,"1st-4th",2,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Self-emp-inc",32016,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,62,"United-States","<=50K" +31,"Private",117028,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",280278,"HS-grad",9,"Widowed","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +57,"Private",342906,"9th",5,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,55,"United-States",">50K" +25,"Private",181598,"11th",7,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",224059,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",148549,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +34,"Private",97355,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +37,"Private",154571,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +43,"Self-emp-inc",140988,"Bachelors",13,"Married-civ-spouse","Sales","Other-relative","Asian-Pac-Islander","Male",0,0,45,"India","<=50K" +35,"Private",112158,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",121488,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"State-gov",283635,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",69758,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +54,"Private",88019,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +28,"Private",31935,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Private",323055,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",189498,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Private",89041,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",112507,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +19,"Private",236940,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",278514,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Female",0,0,42,"United-States","<=50K" +21,"?",433330,"Some-college",10,"Never-married","?","Unmarried","White","Male",0,0,40,"United-States","<=50K" +25,"Private",258379,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,32,"United-States","<=50K" +44,"Private",162028,"11th",7,"Divorced","Sales","Unmarried","White","Female",0,0,44,"United-States","<=50K" +20,"Private",197997,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Private",98350,"10th",6,"Married-spouse-absent","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,37,"China","<=50K" +39,"Private",165848,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",178615,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",228939,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +53,"Private",154891,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",165937,"Assoc-voc",11,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +39,"Private",160120,"Some-college",10,"Never-married","Machine-op-inspct","Other-relative","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +30,"Private",382368,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",123011,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +33,"Private",119033,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",496856,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +44,"Private",194049,"Some-college",10,"Divorced","Other-service","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +30,"Private",299223,"Some-college",10,"Divorced","Sales","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +66,"Private",174788,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +39,"Private",176101,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",38948,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Private",271933,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Wife","White","Female",0,0,40,"United-States","<=50K" +17,"Private",122041,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,20,"United-States","<=50K" +43,"Private",115932,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States",">50K" +46,"Private",265105,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",100828,"11th",7,"Never-married","Other-service","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +42,"Private",213214,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",348618,"9th",5,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,40,"Mexico","<=50K" +33,"Private",275632,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",239161,"Some-college",10,"Married-civ-spouse","Sales","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +20,"Private",215495,"9th",5,"Never-married","Exec-managerial","Other-relative","White","Female",0,0,40,"Mexico","<=50K" +30,"Private",214063,"Some-college",10,"Never-married","Farming-fishing","Other-relative","Black","Male",0,0,72,"United-States","<=50K" +37,"Private",122493,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +33,"?",211699,"Some-college",10,"Divorced","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",175622,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +65,"Private",153522,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,17,"United-States","<=50K" +35,"Private",258339,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +27,"Private",119793,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",162840,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +41,"Local-gov",67671,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +45,"Private",140644,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"?",126154,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",245659,"Some-college",10,"Separated","Other-service","Unmarried","White","Female",0,0,38,"El-Salvador","<=50K" +28,"Private",129624,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"?","<=50K" +47,"Private",104068,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +30,"Private",337908,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,20,"United-States","<=50K" +36,"Private",161141,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",162228,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +44,"Private",116391,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",314310,"HS-grad",9,"Married-spouse-absent","Sales","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +61,"?",394534,"HS-grad",9,"Married-civ-spouse","?","Husband","Black","Male",0,0,6,"United-States","<=50K" +29,"Private",308136,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",194698,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +18,"?",67793,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,60,"United-States","<=50K" +27,"Private",289147,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"Private",229826,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,20,"United-States","<=50K" +49,"Self-emp-inc",246739,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +35,"Private",188041,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +37,"Local-gov",105266,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",249208,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,48,"United-States",">50K" +26,"Private",203492,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"?",71076,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Federal-gov",146477,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +59,"Private",205949,"HS-grad",9,"Separated","Craft-repair","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +70,"Private",90245,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,5,"United-States","<=50K" +53,"Federal-gov",177647,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"France",">50K" +39,"Private",126494,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",257735,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",1161363,"Some-college",10,"Separated","Tech-support","Unmarried","White","Female",0,0,50,"Columbia","<=50K" +19,"?",257343,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",221452,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +74,"Private",260669,"10th",6,"Divorced","Other-service","Not-in-family","White","Female",0,0,1,"United-States","<=50K" +40,"Private",192344,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",80479,"Assoc-voc",11,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",108808,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +41,"Private",175674,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",272950,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +29,"Self-emp-not-inc",160786,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States",">50K" +46,"Self-emp-not-inc",122206,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +46,"Private",121168,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",209547,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +39,"Private",176296,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,60,"United-States","<=50K" +31,"Private",91666,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Male",0,0,60,"United-States","<=50K" +31,"State-gov",63704,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",31659,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +27,"Private",191230,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,25,"United-States","<=50K" +28,"Private",56340,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +21,"Private",221157,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,30,"United-States","<=50K" +57,"Local-gov",143910,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"Local-gov",435836,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"?",61499,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Private",209182,"Preschool",1,"Separated","Other-service","Unmarried","White","Female",0,0,40,"El-Salvador","<=50K" +36,"Self-emp-inc",107218,"Some-college",10,"Divorced","Sales","Unmarried","Asian-Pac-Islander","Male",0,0,55,"United-States","<=50K" +51,"Private",55500,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Local-gov",357962,"Assoc-acdm",12,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +43,"Private",200355,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,70,"United-States",">50K" +38,"Private",320451,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +51,"Local-gov",184542,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"State-gov",206927,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",208165,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States","<=50K" +39,"Private",318416,"10th",6,"Separated","Other-service","Own-child","Black","Female",0,0,12,"United-States","<=50K" +47,"Self-emp-inc",207540,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?","<=50K" +23,"Private",69911,"Preschool",1,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +26,"Private",305304,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Local-gov",295289,"HS-grad",9,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",275110,"Some-college",10,"Separated","Handlers-cleaners","Not-in-family","Black","Male",0,0,42,"United-States","<=50K" +30,"Private",339773,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +37,"Self-emp-inc",51264,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",178100,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +45,"?",215943,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",176178,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,16,"United-States","<=50K" +25,"State-gov",180884,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +61,"State-gov",130466,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +28,"Private",142712,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",176321,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Private",145041,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Cuba",">50K" +29,"Private",95423,"HS-grad",9,"Married-AF-spouse","Transport-moving","Husband","White","Male",0,0,80,"United-States","<=50K" +49,"Self-emp-not-inc",215096,"9th",5,"Divorced","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +41,"Local-gov",177599,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,35,"United-States","<=50K" +33,"Private",123920,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +20,"?",201490,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",388672,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,16,"United-States","<=50K" +48,"Private",149210,"Bachelors",13,"Divorced","Sales","Not-in-family","Black","Male",0,0,40,"United-States",">50K" +24,"Private",134787,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Private",185407,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,38,"United-States",">50K" +31,"State-gov",86143,"HS-grad",9,"Never-married","Protective-serv","Other-relative","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +23,"Private",41721,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +35,"Private",195744,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",96062,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",215150,"9th",5,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +52,"Private",270728,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,48,"Cuba","<=50K" +44,"Private",75012,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,80,"United-States","<=50K" +43,"Private",206139,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +39,"Private",50700,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",224258,"7th-8th",4,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"Mexico",">50K" +40,"Self-emp-not-inc",406811,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +28,"Local-gov",34452,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",361341,"12th",8,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Female",0,0,25,"Thailand","<=50K" +35,"Private",78247,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Private",106900,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +40,"Self-emp-not-inc",165108,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"England","<=50K" +20,"Private",406641,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +55,"Private",171467,"HS-grad",9,"Divorced","Craft-repair","Unmarried","Black","Male",0,0,48,"United-States",">50K" +30,"Private",341187,"7th-8th",4,"Separated","Transport-moving","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +38,"Private",119177,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +17,"Private",342752,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +20,"Private",47541,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +25,"Private",233461,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +27,"Private",303954,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +19,"Private",163015,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +21,"Private",75763,"Some-college",10,"Married-civ-spouse","Sales","Wife","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +19,"Private",43003,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +42,"Private",328239,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",130856,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,36,"United-States","<=50K" +47,"Self-emp-not-inc",190072,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Iran",">50K" +59,"Private",170148,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,32,"United-States","<=50K" +50,"Private",104501,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Self-emp-inc",213140,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,80,"United-States","<=50K" +33,"Local-gov",175509,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",173611,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",64520,"7th-8th",4,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",139822,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +24,"Private",258700,"5th-6th",3,"Never-married","Farming-fishing","Other-relative","Black","Male",0,0,40,"Mexico","<=50K" +29,"Private",34796,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",124963,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,30,"United-States","<=50K" +24,"Private",65743,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +28,"Private",161087,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,45,"Jamaica","<=50K" +63,"?",424591,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Federal-gov",203836,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +58,"State-gov",110199,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",316059,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +42,"Private",255667,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +39,"Private",193689,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",60722,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +39,"Private",187847,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",233275,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +45,"Private",201865,"Bachelors",13,"Married-spouse-absent","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +45,"Private",118889,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"State-gov",368739,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",171344,"11th",7,"Married-spouse-absent","Transport-moving","Own-child","White","Male",0,0,36,"Mexico","<=50K" +39,"Private",153976,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",374883,"Assoc-voc",11,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +17,"Private",167658,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,6,"United-States","<=50K" +31,"Private",348504,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +22,"Private",258509,"HS-grad",9,"Never-married","Transport-moving","Own-child","Black","Male",0,0,24,"United-States","<=50K" +28,"Private",188236,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"?",355571,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",425049,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +29,"Private",142555,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,42,"United-States","<=50K" +42,"Self-emp-not-inc",29320,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,60,"United-States",">50K" +52,"Federal-gov",207841,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",187329,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",270973,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Local-gov",160187,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +21,"Private",197918,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +74,"Private",192290,"10th",6,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,20,"United-States","<=50K" +29,"Private",241895,"HS-grad",9,"Married-civ-spouse","Transport-moving","Other-relative","White","Male",0,0,40,"United-States","<=50K" +39,"Local-gov",164515,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Self-emp-inc",306868,"Bachelors",13,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Local-gov",169837,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +61,"?",124648,"10th",6,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",185057,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,30,"United-States",">50K" +23,"Private",240049,"Preschool",1,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Laos","<=50K" +18,"Private",164441,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,38,"United-States","<=50K" +38,"Private",179314,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Self-emp-inc",148955,"Some-college",10,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Female",0,0,35,"South","<=50K" +37,"Private",206699,"HS-grad",9,"Divorced","Tech-support","Own-child","White","Male",0,0,45,"United-States","<=50K" +25,"Private",385646,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",31438,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Male",0,0,43,"?","<=50K" +32,"Private",97306,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +65,"?",106910,"11th",7,"Divorced","?","Not-in-family","Asian-Pac-Islander","Female",0,0,15,"United-States","<=50K" +18,"Self-emp-not-inc",29582,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",220284,"HS-grad",9,"Never-married","Transport-moving","Unmarried","White","Male",0,0,40,"Mexico","<=50K" +29,"Private",110226,"Masters",14,"Never-married","Sales","Not-in-family","White","Male",0,0,65,"?","<=50K" +53,"Private",240914,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",115496,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +27,"Private",105817,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +24,"State-gov",330836,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",36327,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +23,"Private",33423,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +45,"Private",75673,"Assoc-voc",11,"Widowed","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +36,"Private",185744,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,35,"United-States",">50K" +24,"Private",111450,"HS-grad",9,"Never-married","Transport-moving","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +50,"Private",74879,"HS-grad",9,"Married-spouse-absent","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +58,"Private",272902,"Bachelors",13,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Self-emp-inc",220230,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,48,"United-States","<=50K" +24,"Private",90934,"Bachelors",13,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,55,"United-States","<=50K" +34,"Private",195602,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +40,"Private",70761,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +53,"Private",142717,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",124242,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +58,"?",53481,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,70,"United-States","<=50K" +26,"Private",287797,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"Private",188274,"Assoc-acdm",12,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",171968,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +78,"?",74795,"Assoc-acdm",12,"Widowed","?","Not-in-family","White","Female",0,0,4,"United-States","<=50K" +36,"Private",218490,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"Germany",">50K" +43,"Local-gov",94937,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,28,"United-States","<=50K" +60,"Private",109511,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",120672,"7th-8th",4,"Never-married","Handlers-cleaners","Unmarried","Black","Male",0,0,10,"United-States","<=50K" +46,"Private",130779,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Local-gov",441542,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +69,"Private",114801,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +32,"Private",180284,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Local-gov",27444,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +56,"Private",143266,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",139268,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",126208,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +37,"Private",186191,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,46,"United-States","<=50K" +33,"Private",181388,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",124963,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,80,"United-States",">50K" +24,"Private",188925,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",149230,"Assoc-voc",11,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +40,"Private",388725,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",113543,"Masters",14,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +61,"?",187636,"Bachelors",13,"Divorced","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +56,"Self-emp-inc",267763,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"?","<=50K" +69,"Federal-gov",143849,"11th",7,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +41,"Self-emp-not-inc",97277,"Assoc-voc",11,"Divorced","Other-service","Unmarried","White","Female",0,0,10,"United-States","<=50K" +40,"Private",199303,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",124852,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",50053,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +53,"Private",97005,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,46,"United-States",">50K" +90,"?",175444,"7th-8th",4,"Separated","?","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +39,"Private",337898,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +51,"Federal-gov",124076,"Bachelors",13,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Federal-gov",277420,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Puerto-Rico",">50K" +51,"Private",280278,"10th",6,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +17,"Private",241185,"12th",8,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +42,"Private",198422,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +33,"Private",178429,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",185866,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"?",">50K" +43,"Private",212847,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +64,"Self-emp-not-inc",219661,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,9,"United-States",">50K" +40,"Private",321856,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States",">50K" +21,"Private",313873,"5th-6th",3,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +31,"Private",144064,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Private",139586,"Assoc-voc",11,"Widowed","Exec-managerial","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States",">50K" +32,"Private",419691,"12th",8,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",195562,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,20,"United-States","<=50K" +40,"Private",205706,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +27,"Private",131310,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States",">50K" +18,"Private",54440,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +43,"Private",200734,"HS-grad",9,"Separated","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +52,"Private",81859,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States",">50K" +31,"Private",159589,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,85,"United-States","<=50K" +28,"Private",300915,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +44,"Private",185057,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +37,"Self-emp-not-inc",42044,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,84,"United-States","<=50K" +35,"Private",166416,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +42,"Private",212737,"9th",5,"Separated","Craft-repair","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +18,"Private",236069,"10th",6,"Never-married","Other-service","Own-child","Black","Male",0,0,10,"United-States","<=50K" +54,"Federal-gov",27432,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Private",147202,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,45,"Germany","<=50K" +27,"Private",29261,"Some-college",10,"Never-married","Sales","Unmarried","White","Male",0,0,50,"United-States","<=50K" +26,"Private",359543,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"Mexico","<=50K" +41,"Local-gov",227644,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",90021,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"?","<=50K" +32,"Private",188154,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +18,"Private",110142,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +36,"Private",186415,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,65,"United-States","<=50K" +37,"Private",175720,"10th",6,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",172865,"5th-6th",3,"Never-married","Farming-fishing","Own-child","White","Male",0,0,25,"Mexico","<=50K" +46,"Private",35969,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,51,"United-States","<=50K" +24,"Private",433330,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Self-emp-inc",160261,"Bachelors",13,"Never-married","Exec-managerial","Own-child","Asian-Pac-Islander","Male",0,0,35,"Taiwan","<=50K" +55,"Private",189528,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +64,"Local-gov",113324,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Local-gov",118500,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +65,"Private",89681,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,99,"United-States","<=50K" +46,"Federal-gov",199925,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",444607,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +32,"Private",176998,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"State-gov",366198,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"Germany",">50K" +24,"Private",153542,"Some-college",10,"Never-married","Sales","Other-relative","White","Male",0,0,35,"United-States","<=50K" +36,"Private",185394,"10th",6,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,34,"United-States","<=50K" +44,"Private",222703,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",0,0,40,"Nicaragua","<=50K" +23,"Private",183945,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +57,"Private",161964,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +41,"Self-emp-not-inc",375574,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"Mexico",">50K" +20,"Local-gov",312427,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,30,"Puerto-Rico","<=50K" +32,"Private",53373,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,36,"United-States","<=50K" +38,"Self-emp-inc",124665,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +29,"Private",146719,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +22,"Private",306593,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",156687,"Some-college",10,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,30,"India","<=50K" +45,"State-gov",127089,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +76,"Local-gov",329355,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,13,"United-States","<=50K" +45,"Private",178319,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Local-gov",304246,"Masters",14,"Separated","Prof-specialty","Unmarried","White","Female",0,0,70,"United-States","<=50K" +36,"Local-gov",174640,"Assoc-voc",11,"Never-married","Protective-serv","Not-in-family","Black","Female",0,0,60,"United-States",">50K" +22,"Private",148294,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +47,"Private",298037,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,44,"United-States","<=50K" +26,"Private",98155,"HS-grad",9,"Married-AF-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +21,"Private",102766,"Some-college",10,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",78529,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Female",0,0,15,"United-States","<=50K" +26,"Private",136309,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",275357,"Assoc-voc",11,"Never-married","Tech-support","Own-child","White","Female",0,0,25,"United-States","<=50K" +31,"Self-emp-not-inc",33117,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"England","<=50K" +57,"Local-gov",199546,"Masters",14,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +39,"Private",184128,"11th",7,"Divorced","Sales","Other-relative","White","Female",0,0,40,"United-States","<=50K" +66,"Private",126511,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +34,"Local-gov",325792,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +80,"?",91901,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States","<=50K" +21,"Private",119474,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +49,"Local-gov",321851,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +42,"Private",195508,"11th",7,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +59,"Private",102193,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +63,"Private",20323,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",122206,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +41,"Private",200652,"9th",5,"Divorced","Other-service","Other-relative","White","Female",0,0,35,"United-States","<=50K" +19,"Private",184121,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +45,"Local-gov",53123,"11th",7,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,25,"United-States","<=50K" +47,"Private",175990,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,30,"United-States",">50K" +47,"Private",316101,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",34080,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"England","<=50K" +36,"Private",126954,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",99185,"HS-grad",9,"Widowed","Craft-repair","Unmarried","White","Male",0,0,40,"United-States",">50K" +39,"Private",120074,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",77336,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Private",77884,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +50,"Private",65408,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Private",173279,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +52,"?",318351,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States",">50K" +41,"Self-emp-not-inc",157686,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",277434,"Assoc-acdm",12,"Widowed","Tech-support","Unmarried","White","Male",0,0,40,"United-States",">50K" +54,"Local-gov",184620,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",34443,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +20,"?",41356,"Assoc-acdm",12,"Never-married","?","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +43,"Private",459342,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Local-gov",148549,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",238367,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",180439,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +32,"State-gov",111567,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,49,"United-States",">50K" +46,"Private",319163,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +60,"?",160155,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,12,"United-States","<=50K" +52,"Local-gov",378045,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +44,"Private",177083,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"Private",127779,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",299353,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +30,"Private",63861,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",112403,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +28,"Private",452808,"10th",6,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",176871,"Some-college",10,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +17,"Private",266134,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,12,"United-States","<=50K" +54,"Local-gov",196307,"10th",6,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",87891,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"?",136819,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",181666,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Own-child","White","Female",0,0,40,"?","<=50K" +37,"Private",179671,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",27494,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",0,0,48,"United-States",">50K" +38,"Private",338320,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Canada","<=50K" +51,"Private",199688,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +41,"Private",96635,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Male",0,0,60,"United-States","<=50K" +24,"Private",165064,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",82393,"HS-grad",9,"Never-married","Craft-repair","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +31,"Private",209538,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",209891,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +32,"Self-emp-not-inc",56026,"Bachelors",13,"Married-civ-spouse","Sales","Other-relative","White","Male",0,0,45,"United-States","<=50K" +35,"Private",210844,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +43,"Private",117158,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +40,"Private",193144,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,36,"United-States","<=50K" +19,"Self-emp-not-inc",137578,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,53,"United-States","<=50K" +23,"Private",234108,"Assoc-acdm",12,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,32,"United-States","<=50K" +40,"Private",155767,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +59,"Private",110820,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,38,"United-States",">50K" +43,"Private",403276,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",147269,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"?","<=50K" +53,"Private",123092,"HS-grad",9,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",165673,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",204415,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States",">50K" +32,"Self-emp-not-inc",92531,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +25,"State-gov",157028,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",228649,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",147253,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +33,"Private",160784,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Local-gov",163189,"Some-college",10,"Married-civ-spouse","Other-service","Other-relative","White","Male",0,0,40,"United-States","<=50K" +29,"Private",146343,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +20,"Private",225811,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,23,"United-States","<=50K" +58,"Private",374108,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",93930,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",412248,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +30,"Private",427474,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +67,"State-gov",160158,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,8,"United-States","<=50K" +26,"Private",159603,"Assoc-acdm",12,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,32,"United-States","<=50K" +53,"Self-emp-not-inc",101017,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States","<=50K" +27,"Local-gov",163862,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +29,"Without-pay",212588,"Some-college",10,"Married-civ-spouse","Farming-fishing","Own-child","White","Male",0,0,65,"United-States","<=50K" +38,"State-gov",321943,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",317702,"9th",5,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +48,"Private",287480,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",135607,"Some-college",10,"Widowed","Other-service","Unmarried","Black","Female",0,0,40,"?","<=50K" +28,"Private",168514,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +18,"Private",88642,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,15,"United-States","<=50K" +28,"Private",227104,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +34,"Private",157289,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Private",213321,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",294907,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +30,"Private",251411,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +20,"Private",183594,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Private",217802,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,25,"United-States","<=50K" +20,"Private",388156,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,24,"United-States","<=50K" +54,"Private",447555,"10th",6,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",204098,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +43,"Private",193882,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +17,"?",89870,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"State-gov",49595,"Masters",14,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,72,"United-States","<=50K" +34,"Private",228873,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +66,"?",108185,"9th",5,"Married-civ-spouse","?","Husband","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",176027,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"?",405374,"Some-college",10,"Separated","?","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +37,"Private",39606,"Assoc-voc",11,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +56,"Private",178353,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Private",160662,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Self-emp-inc",196328,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"Jamaica","<=50K" +45,"Private",20534,"Some-college",10,"Separated","Craft-repair","Not-in-family","White","Male",0,0,41,"United-States","<=50K" +29,"Self-emp-inc",156815,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",360252,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +43,"Private",245056,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States",">50K" +33,"Local-gov",422718,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",262978,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +25,"Private",187577,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +69,"?",259323,"Prof-school",15,"Divorced","?","Not-in-family","White","Male",0,0,5,"United-States","<=50K" +37,"Private",160920,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",194247,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +17,"Private",123335,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +27,"Local-gov",332249,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",358124,"HS-grad",9,"Never-married","Other-service","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +55,"Private",208019,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +39,"Private",318452,"11th",7,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +41,"Private",207779,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",238376,"1st-4th",2,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +51,"Private",673764,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +67,"State-gov",239705,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,12,"?","<=50K" +40,"Private",133974,"Some-college",10,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",152140,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Local-gov",287920,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +43,"State-gov",78765,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +58,"Private",206532,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +33,"Private",129529,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +60,"Local-gov",202473,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",162312,"HS-grad",9,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +45,"Private",72844,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,46,"United-States","<=50K" +49,"Private",206947,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",64112,"12th",8,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"State-gov",20057,"Some-college",10,"Married-spouse-absent","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,38,"Philippines","<=50K" +42,"State-gov",222884,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",132683,"HS-grad",9,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +73,"?",177773,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,15,"United-States","<=50K" +19,"Private",168601,"11th",7,"Never-married","Other-service","Other-relative","White","Male",0,0,30,"United-States","<=50K" +31,"State-gov",78291,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +58,"Federal-gov",243929,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +21,"Private",215039,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,13,"?","<=50K" +47,"Self-emp-not-inc",185673,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +30,"Private",121142,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States",">50K" +41,"Private",173858,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +59,"?",87247,"10th",6,"Divorced","?","Not-in-family","White","Female",0,0,40,"England","<=50K" +44,"Private",174283,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Private",128676,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +24,"Private",205844,"Bachelors",13,"Never-married","Exec-managerial","Own-child","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",62535,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States","<=50K" +50,"Private",240612,"HS-grad",9,"Married-spouse-absent","Exec-managerial","Unmarried","White","Female",0,0,10,"United-States","<=50K" +33,"Private",176992,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Local-gov",254127,"Bachelors",13,"Never-married","Prof-specialty","Other-relative","White","Female",0,0,50,"United-States","<=50K" +30,"?",138744,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Private",128460,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"State-gov",56582,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,10,"United-States","<=50K" +52,"Private",153751,"9th",5,"Separated","Other-service","Not-in-family","Black","Female",0,0,30,"United-States","<=50K" +26,"Private",284343,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +27,"State-gov",312692,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,12,"United-States","<=50K" +28,"Private",111520,"11th",7,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"Nicaragua","<=50K" +50,"Self-emp-inc",304955,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +28,"Private",288598,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +61,"Self-emp-not-inc",117387,"11th",7,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States","<=50K" +32,"Private",230484,"7th-8th",4,"Separated","Sales","Unmarried","White","Female",0,0,35,"United-States","<=50K" +30,"Federal-gov",319280,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Local-gov",186416,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",110164,"Some-college",10,"Divorced","Other-service","Other-relative","Black","Male",0,0,24,"United-States","<=50K" +49,"Private",225454,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +61,"Self-emp-not-inc",220342,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States","<=50K" +41,"Self-emp-not-inc",144002,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +55,"Private",225365,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +36,"Private",187983,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +21,"Private",89991,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",225913,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +59,"Private",145574,"11th",7,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",274363,"Some-college",10,"Separated","Sales","Not-in-family","White","Male",0,0,80,"United-States",">50K" +59,"Private",365390,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",266467,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +42,"Private",183384,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +41,"Local-gov",112797,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,60,"United-States","<=50K" +45,"Federal-gov",76008,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Private",156780,"HS-grad",9,"Never-married","Sales","Other-relative","Asian-Pac-Islander","Female",0,0,40,"?","<=50K" +42,"Local-gov",186909,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,45,"United-States",">50K" +25,"Private",25497,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",30916,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",123270,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Self-emp-not-inc",210165,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",222596,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Male",0,0,50,"United-States",">50K" +53,"Self-emp-inc",188067,"Some-college",10,"Widowed","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",250314,"9th",5,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"Guatemala","<=50K" +60,"Private",205934,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +56,"Private",147653,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,32,"United-States","<=50K" +35,"?",195946,"Some-college",10,"Married-civ-spouse","?","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +19,"Private",151801,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,39,"United-States","<=50K" +38,"Private",177154,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Federal-gov",73883,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",175714,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +22,"Private",43535,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +32,"State-gov",104509,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +27,"Private",118230,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",152046,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"Guatemala","<=50K" +36,"Private",52327,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Other","Male",0,0,40,"Iran",">50K" +22,"Private",218886,"12th",8,"Never-married","Handlers-cleaners","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",84119,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +37,"Private",189674,"Bachelors",13,"Separated","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +22,"Private",222993,"HS-grad",9,"Never-married","Prof-specialty","Own-child","White","Male",0,0,54,"United-States","<=50K" +29,"Private",47429,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +42,"Private",144995,"Preschool",1,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +45,"Private",187969,"Assoc-voc",11,"Never-married","Sales","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +33,"Private",288398,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +39,"Private",114591,"Some-college",10,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",167737,"12th",8,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +53,"Local-gov",248834,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +30,"Private",165686,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +52,"Self-emp-not-inc",40200,"Some-college",10,"Widowed","Craft-repair","Not-in-family","Black","Male",0,0,35,"United-States","<=50K" +47,"Local-gov",216657,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States",">50K" +61,"Private",124242,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"India","<=50K" +39,"Local-gov",239119,"Masters",14,"Divorced","Prof-specialty","Not-in-family","Black","Male",0,0,40,"Dominican-Republic","<=50K" +47,"Private",190072,"Some-college",10,"Divorced","Sales","Unmarried","White","Male",0,0,50,"United-States","<=50K" +19,"Private",378114,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,25,"United-States","<=50K" +31,"Private",101761,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,51,"United-States","<=50K" +69,"Self-emp-not-inc",37745,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,8,"United-States","<=50K" +22,"?",424494,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +29,"Private",130438,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",100605,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","Other","Male",0,0,14,"United-States","<=50K" +42,"Private",220776,"HS-grad",9,"Separated","Handlers-cleaners","Unmarried","White","Male",0,0,40,"Poland","<=50K" +30,"Local-gov",154950,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,72,"United-States",">50K" +28,"Private",192283,"Masters",14,"Married-spouse-absent","Sales","Not-in-family","White","Female",0,0,80,"United-States",">50K" +27,"Private",210765,"Assoc-voc",11,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",147476,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +22,"Private",109053,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",265618,"HS-grad",9,"Separated","Protective-serv","Own-child","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",68848,"Bachelors",13,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +30,"Private",229051,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,37,"United-States","<=50K" +27,"Private",106039,"Bachelors",13,"Divorced","Prof-specialty","Own-child","White","Female",0,0,50,"United-States","<=50K" +25,"Private",112835,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"?",205396,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,4,"United-States","<=50K" +32,"Private",283400,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +70,"Private",195739,"10th",6,"Widowed","Craft-repair","Unmarried","White","Male",0,0,45,"United-States","<=50K" +50,"Private",36480,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",303291,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"United-States","<=50K" +34,"Private",293900,"11th",7,"Married-spouse-absent","Craft-repair","Not-in-family","Black","Male",0,0,55,"United-States","<=50K" +57,"Self-emp-not-inc",165922,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"Private",65738,"Masters",14,"Never-married","Other-service","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +49,"Private",175070,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",150132,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +31,"Private",377374,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"Japan","<=50K" +60,"Self-emp-not-inc",166153,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Private",194243,"Prof-school",15,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Private",106347,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +59,"Private",214865,"HS-grad",9,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States","<=50K" +19,"?",185619,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +18,"Private",96445,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,24,"United-States","<=50K" +22,"Private",102632,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +24,"Private",209034,"Assoc-acdm",12,"Married-civ-spouse","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +53,"State-gov",153486,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",144371,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,42,"United-States",">50K" +24,"Private",186213,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States",">50K" +60,"Private",188236,"10th",6,"Widowed","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",418405,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Federal-gov",125796,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",183304,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,99,"United-States",">50K" +34,"Private",329587,"10th",6,"Separated","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +35,"Local-gov",182570,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",446654,"9th",5,"Married-spouse-absent","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +53,"Local-gov",131258,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States",">50K" +23,"Private",103632,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",241895,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",244945,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",20795,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +17,"Private",347322,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +32,"Private",53206,"Bachelors",13,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States",">50K" +43,"?",387839,"HS-grad",9,"Never-married","?","Other-relative","White","Female",0,0,40,"United-States","<=50K" +18,"Private",57108,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,16,"United-States","<=50K" +62,"Private",177791,"10th",6,"Divorced","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Private",33794,"Masters",14,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",249935,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,70,"United-States","<=50K" +73,"Self-emp-not-inc",241121,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Private",98586,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +26,"Private",181920,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +23,"Private",434467,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +30,"Private",113364,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"Vietnam","<=50K" +51,"Private",249706,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",95455,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,55,"United-States","<=50K" +35,"Self-emp-inc",79586,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"India",">50K" +41,"Private",289669,"HS-grad",9,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",53835,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +46,"Local-gov",14878,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +31,"Private",266126,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +41,"Self-emp-inc",146659,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"Honduras","<=50K" +23,"Private",173535,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"?",77665,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,35,"United-States","<=50K" +49,"Private",280525,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +53,"Private",479621,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",247600,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Taiwan","<=50K" +32,"Private",258406,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,72,"Mexico","<=50K" +20,"Private",107746,"11th",7,"Never-married","Transport-moving","Other-relative","White","Male",0,0,40,"Guatemala","<=50K" +17,"?",47407,"11th",7,"Never-married","?","Own-child","White","Male",0,0,10,"United-States","<=50K" +22,"Private",229987,"Some-college",10,"Never-married","Tech-support","Other-relative","Asian-Pac-Islander","Female",0,0,32,"United-States","<=50K" +25,"Private",312338,"Assoc-voc",11,"Never-married","Craft-repair","Unmarried","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +24,"Private",373718,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +20,"Private",472789,"1st-4th",2,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,30,"El-Salvador","<=50K" +60,"Self-emp-not-inc",27886,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",138352,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,30,"United-States","<=50K" +52,"Private",123011,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +36,"Private",306567,"HS-grad",9,"Married-civ-spouse","Transport-moving","Wife","White","Female",0,0,40,"United-States",">50K" +46,"Local-gov",187749,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +22,"Private",260594,"11th",7,"Never-married","Sales","Unmarried","White","Female",0,0,25,"United-States","<=50K" +19,"Private",236879,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,35,"United-States","<=50K" +37,"Private",186808,"HS-grad",9,"Never-married","Sales","Unmarried","White","Male",0,0,40,"United-States","<=50K" +30,"Private",373213,"Assoc-voc",11,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States",">50K" +44,"Private",187629,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +63,"?",106648,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States","<=50K" +22,"Private",305781,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"Canada","<=50K" +17,"Private",239947,"11th",7,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",349041,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +67,"Private",105252,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",182715,"7th-8th",4,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",166210,"HS-grad",9,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,50,"United-States","<=50K" +20,"Private",113200,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,6,"United-States","<=50K" +27,"Private",142075,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,24,"United-States","<=50K" +35,"Private",454843,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",142219,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +36,"Private",112512,"12th",8,"Separated","Other-service","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +62,"State-gov",265201,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",170627,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +37,"Private",259089,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",21856,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +46,"Local-gov",207946,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,43,"United-States","<=50K" +33,"Private",36539,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +62,"Private",176811,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",277746,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",288132,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +34,"Private",198091,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,72,"United-States","<=50K" +67,"?",150264,"Doctorate",16,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"Canada",">50K" +62,"Private",588484,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"United-States",">50K" +30,"Private",113364,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Poland","<=50K" +19,"Private",270551,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +49,"?",31478,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,99,"United-States","<=50K" +27,"Private",190525,"Assoc-voc",11,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,45,"United-States","<=50K" +36,"Private",153066,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Private",150393,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",99911,"12th",8,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +57,"Local-gov",343447,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +64,"Private",169482,"Some-college",10,"Married-spouse-absent","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +56,"?",32855,"HS-grad",9,"Divorced","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",194501,"11th",7,"Widowed","Other-service","Own-child","White","Female",0,0,47,"United-States","<=50K" +53,"Private",177705,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States",">50K" +31,"Private",123983,"Some-college",10,"Separated","Sales","Unmarried","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +45,"Local-gov",235431,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +45,"State-gov",130206,"HS-grad",9,"Divorced","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +23,"Private",210053,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +39,"Local-gov",249392,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,72,"United-States","<=50K" +31,"Private",87418,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",190387,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"?",211013,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"Mexico","<=50K" +55,"Self-emp-not-inc",185195,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",173495,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-inc",78634,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +46,"Self-emp-not-inc",82572,"HS-grad",9,"Widowed","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +38,"Private",154641,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"?",64785,"10th",6,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +48,"Self-emp-not-inc",179337,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"England","<=50K" +73,"Private",173047,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,15,"United-States","<=50K" +25,"Private",264012,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +53,"Federal-gov",227836,"Some-college",10,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",146398,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +30,"Private",324120,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",367329,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"State-gov",301582,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +75,"?",222789,"Bachelors",13,"Widowed","?","Not-in-family","White","Female",0,0,6,"United-States","<=50K" +58,"Private",170108,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Self-emp-not-inc",82297,"7th-8th",4,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,50,"United-States","<=50K" +62,"Local-gov",180162,"9th",5,"Divorced","Protective-serv","Not-in-family","Black","Male",0,0,24,"United-States","<=50K" +38,"Private",809585,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Self-emp-not-inc",67728,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +42,"Self-emp-not-inc",102069,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +42,"Self-emp-not-inc",109273,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +43,"Private",393354,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,38,"United-States",">50K" +37,"Private",226947,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",493689,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Black","Female",0,0,40,"France","<=50K" +54,"Private",299324,"5th-6th",3,"Married-spouse-absent","Machine-op-inspct","Unmarried","White","Male",0,0,40,"Mexico","<=50K" +29,"Private",174419,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +29,"Private",209472,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,38,"United-States","<=50K" +37,"Private",295127,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,47,"United-States","<=50K" +55,"Self-emp-inc",182273,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +67,"Private",228200,"HS-grad",9,"Married-civ-spouse","Priv-house-serv","Wife","Black","Female",0,0,20,"United-States","<=50K" +51,"Private",263836,"HS-grad",9,"Widowed","Handlers-cleaners","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +35,"Private",178948,"Masters",14,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,32,"United-States","<=50K" +41,"Private",43945,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?","<=50K" +64,"Self-emp-not-inc",253296,"HS-grad",9,"Widowed","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +23,"Private",240137,"5th-6th",3,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,55,"Mexico","<=50K" +49,"Private",24712,"Bachelors",13,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,35,"Philippines","<=50K" +38,"Self-emp-not-inc",342635,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,70,"United-States","<=50K" +62,"Private",115387,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +62,"Self-emp-not-inc",182998,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,10,"United-States","<=50K" +70,"?",133248,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,14,"United-States","<=50K" +45,"Self-emp-not-inc",246891,"Masters",14,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",30035,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Private",175232,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +50,"Self-emp-inc",140516,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",64980,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,55,"United-States",">50K" +30,"Private",155781,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States","<=50K" +52,"Federal-gov",192065,"Some-college",10,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",227890,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,50,"United-States",">50K" +62,"Self-emp-not-inc",162249,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States","<=50K" +31,"Private",165949,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",445382,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",163678,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",89413,"12th",8,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",289700,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,25,"United-States","<=50K" +51,"Private",163826,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Private",185385,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Private",169031,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",54611,"Some-college",10,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",130620,"11th",7,"Married-spouse-absent","Sales","Own-child","Asian-Pac-Islander","Female",0,0,40,"India","<=50K" +26,"Private",328663,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Other","Male",0,0,40,"United-States","<=50K" +50,"Private",169646,"Bachelors",13,"Separated","Prof-specialty","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +35,"Private",186815,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",103925,"Some-college",10,"Never-married","Tech-support","Other-relative","White","Female",0,0,40,"United-States","<=50K" +20,"Private",82777,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,16,"United-States","<=50K" +31,"Local-gov",178449,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",51672,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +46,"Private",380162,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","Black","Male",0,0,40,"United-States",">50K" +21,"Private",212114,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,8,"United-States","<=50K" +30,"Private",162572,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,70,"United-States",">50K" +66,"Self-emp-inc",179951,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +37,"Self-emp-inc",190759,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +74,"State-gov",236012,"7th-8th",4,"Widowed","Handlers-cleaners","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +46,"State-gov",164023,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,70,"United-States",">50K" +47,"Self-emp-inc",362835,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +49,"Private",97883,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +53,"Private",91911,"HS-grad",9,"Divorced","Craft-repair","Unmarried","Black","Female",0,0,48,"United-States","<=50K" +24,"Private",278130,"Assoc-voc",11,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Private",146310,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",379412,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",37987,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +37,"State-gov",482927,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +48,"State-gov",44434,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,61,"United-States",">50K" +25,"Private",255474,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"?",195488,"12th",8,"Separated","?","Not-in-family","White","Female",0,0,36,"Puerto-Rico","<=50K" +58,"?",114362,"Some-college",10,"Married-civ-spouse","?","Husband","Black","Male",0,0,30,"United-States","<=50K" +27,"Private",341504,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +69,"Private",197080,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Male",0,0,8,"United-States","<=50K" +38,"Private",102945,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,52,"United-States",">50K" +47,"Private",503454,"12th",8,"Never-married","Adm-clerical","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",87561,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +27,"Private",252813,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +19,"Private",574271,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +24,"Private",235071,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +32,"Private",158242,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",299810,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +19,"Private",277695,"Preschool",1,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,36,"Hong","<=50K" +28,"Private",23324,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Local-gov",316582,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +38,"Self-emp-not-inc",176657,"Some-college",10,"Separated","Sales","Not-in-family","Asian-Pac-Islander","Male",0,0,60,"Japan","<=50K" +42,"Private",93770,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States",">50K" +31,"Private",124569,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +46,"Private",117313,"9th",5,"Separated","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"Ireland","<=50K" +53,"Private",53812,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,54,"United-States","<=50K" +21,"Private",170456,"Assoc-acdm",12,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,15,"United-States","<=50K" +48,"Self-emp-not-inc",115971,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +30,"Private",112383,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +24,"Private",283092,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","Black","Male",0,0,40,"Jamaica","<=50K" +32,"Private",27207,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Private",46712,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"State-gov",19520,"Doctorate",16,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,50,"United-States","<=50K" +56,"Private",98630,"7th-8th",4,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",159897,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,37,"United-States","<=50K" +38,"Private",136629,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Iran","<=50K" +19,"Private",407759,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-not-inc",221884,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +49,"Private",148475,"Assoc-voc",11,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",274964,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,38,"United-States","<=50K" +50,"Self-emp-inc",160107,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +43,"Private",167265,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,84,"United-States",">50K" +34,"Private",148226,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,48,"United-States","<=50K" +28,"Private",153869,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",208881,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",256953,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","Black","Female",0,0,44,"United-States","<=50K" +26,"Private",100147,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,45,"United-States",">50K" +51,"Local-gov",166461,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,40,"United-States",">50K" +35,"Private",171327,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",297335,"Assoc-acdm",12,"Married-spouse-absent","Exec-managerial","Unmarried","Asian-Pac-Islander","Female",0,0,31,"Laos","<=50K" +63,"?",133166,"Doctorate",16,"Married-civ-spouse","?","Husband","White","Male",0,0,12,"United-States","<=50K" +31,"Private",169589,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +22,"Local-gov",273734,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,20,"United-States","<=50K" +67,"Private",158301,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +50,"?",257117,"9th",5,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States","<=50K" +63,"Private",196725,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,24,"United-States","<=50K" +31,"Private",137444,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",286960,"11th",7,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",201435,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +53,"Local-gov",216931,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,38,"United-States","<=50K" +44,"Local-gov",212665,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,99,"United-States","<=50K" +24,"Private",462820,"Bachelors",13,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",198841,"Assoc-voc",11,"Divorced","Tech-support","Own-child","White","Male",0,0,35,"United-States","<=50K" +61,"Private",219886,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States",">50K" +31,"Private",163003,"Assoc-acdm",12,"Never-married","Prof-specialty","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +56,"Private",213105,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,36,"United-States",">50K" +66,"Private",302072,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Private",338105,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +64,"Private",125684,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",215419,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,36,"United-States",">50K" +43,"Local-gov",413760,"Some-college",10,"Separated","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +37,"Private",205339,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,49,"United-States","<=50K" +19,"Private",236570,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,16,"United-States","<=50K" +59,"Self-emp-not-inc",247552,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Federal-gov",184007,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",341187,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +56,"Private",220187,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Private",198258,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",175821,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,34,"United-States","<=50K" +42,"Private",92288,"Masters",14,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +34,"Private",261418,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",203319,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +68,"Self-emp-not-inc",166083,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",109001,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +81,"?",106765,"Some-college",10,"Widowed","?","Unmarried","White","Female",0,0,4,"United-States","<=50K" +22,"Self-emp-not-inc",197387,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +58,"Private",284834,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",87535,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +17,"Local-gov",175587,"11th",7,"Never-married","Protective-serv","Own-child","White","Male",0,0,30,"United-States","<=50K" +23,"Private",161478,"Some-college",10,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Female",0,0,23,"United-States","<=50K" +25,"Private",51498,"12th",8,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"United-States","<=50K" +47,"Private",220124,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",188503,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,60,"United-States",">50K" +44,"Private",113324,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",208872,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Self-emp-not-inc",34180,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +23,"Private",292023,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,30,"United-States","<=50K" +34,"Private",141118,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +33,"Private",348592,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States",">50K" +38,"Private",185203,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +52,"Self-emp-not-inc",165278,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",116933,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,33,"United-States","<=50K" +35,"Private",84787,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",206878,"HS-grad",9,"Never-married","Sales","Other-relative","White","Female",0,0,15,"United-States","<=50K" +38,"Self-emp-not-inc",127772,"HS-grad",9,"Divorced","Farming-fishing","Own-child","White","Male",0,0,50,"United-States","<=50K" +29,"Private",208577,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",40681,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"?",95108,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",280603,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +43,"Private",188436,"Prof-school",15,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",134220,"Assoc-voc",11,"Divorced","Exec-managerial","Own-child","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +42,"Private",177989,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",164190,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,30,"United-States","<=50K" +36,"Private",90897,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"State-gov",33126,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",270886,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"Private",216129,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +33,"Private",189368,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States",">50K" +19,"?",141418,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,15,"United-States","<=50K" +19,"Private",306225,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +35,"Private",330664,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",191765,"HS-grad",9,"Divorced","Tech-support","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +45,"Private",289353,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,24,"United-States","<=50K" +25,"Private",53147,"Bachelors",13,"Never-married","Exec-managerial","Own-child","Black","Male",0,0,50,"United-States","<=50K" +39,"Self-emp-not-inc",122353,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",188767,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +60,"Private",239576,"Masters",14,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,10,"United-States","<=50K" +52,"Local-gov",155141,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +22,"Private",64520,"12th",8,"Never-married","Transport-moving","Unmarried","White","Male",0,0,30,"United-States","<=50K" +23,"Private",478994,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +46,"Private",155654,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",124052,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States","<=50K" +39,"Private",245053,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +38,"Private",183585,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",323639,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,25,"United-States","<=50K" +55,"Federal-gov",186791,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",186666,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",200153,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",180931,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,30,"United-States","<=50K" +51,"Self-emp-not-inc",183173,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Self-emp-inc",120131,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"Cuba",">50K" +25,"Self-emp-not-inc",263300,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +34,"Private",226443,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +19,"Private",208506,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,28,"United-States","<=50K" +32,"Private",46746,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +49,"Private",246183,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +40,"?",165309,"7th-8th",4,"Separated","?","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +43,"Private",122749,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +59,"Private",167963,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +32,"Private",273241,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +25,"Private",120238,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",167990,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Ireland","<=50K" +17,"Private",225507,"11th",7,"Never-married","Handlers-cleaners","Not-in-family","Black","Female",0,0,15,"United-States","<=50K" +57,"Self-emp-inc",125000,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +17,"Self-emp-not-inc",174120,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,15,"United-States","<=50K" +27,"Private",230959,"Bachelors",13,"Never-married","Tech-support","Own-child","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +41,"Local-gov",132125,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"?",68461,"Doctorate",16,"Married-civ-spouse","?","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States",">50K" +19,"Private",227178,"11th",7,"Never-married","Sales","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +41,"Private",165798,"5th-6th",3,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"Puerto-Rico","<=50K" +39,"Private",129573,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +30,"Private",224377,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",179481,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",434268,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +40,"Self-emp-not-inc",173716,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Private",114230,"HS-grad",9,"Never-married","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +33,"Private",188661,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +48,"Private",216093,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",124963,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",85341,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",193490,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +34,"Private",80058,"Prof-school",15,"Never-married","Exec-managerial","Own-child","White","Male",0,0,50,"United-States","<=50K" +41,"Private",139907,"Assoc-voc",11,"Separated","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +25,"Private",188767,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",117222,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,50,"United-States","<=50K" +35,"Private",187119,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +42,"Local-gov",97277,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Local-gov",219760,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,16,"United-States","<=50K" +46,"Private",63299,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"State-gov",171482,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +18,"?",344742,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",210869,"Some-college",10,"Never-married","Sales","Own-child","Black","Male",0,0,80,"United-States","<=50K" +39,"Private",38312,"Some-college",10,"Married-spouse-absent","Craft-repair","Unmarried","White","Male",0,0,40,"United-States",">50K" +47,"Private",119939,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",83953,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +43,"State-gov",101383,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",204374,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",176831,"10th",6,"Divorced","Sales","Other-relative","White","Female",0,0,40,"United-States","<=50K" +19,"?",60688,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,35,"United-States","<=50K" +44,"Federal-gov",251305,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Local-gov",200947,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Self-emp-not-inc",46704,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Private",119721,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"State-gov",58930,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",247750,"HS-grad",9,"Widowed","Other-service","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +48,"Private",67725,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +28,"State-gov",200775,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +44,"Private",183542,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,32,"United-States","<=50K" +20,"?",25139,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Local-gov",123325,"Prof-school",15,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",269786,"HS-grad",9,"Never-married","Transport-moving","Unmarried","White","Male",0,0,50,"United-States","<=50K" +36,"Private",51089,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +28,"Private",136985,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"United-States","<=50K" +21,"Private",129350,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"?",35595,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States","<=50K" +36,"Local-gov",61299,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"?",192321,"Assoc-acdm",12,"Never-married","?","Own-child","White","Female",0,0,80,"United-States","<=50K" +31,"Private",257644,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,43,"United-States","<=50K" +44,"Self-emp-not-inc",70884,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +49,"Local-gov",159726,"11th",7,"Divorced","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +40,"Private",174395,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Federal-gov",175534,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"China",">50K" +27,"Private",32519,"Some-college",10,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,55,"South","<=50K" +18,"Private",322999,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +68,"Private",148874,"9th",5,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,44,"United-States","<=50K" +64,"Private",43738,"Doctorate",16,"Widowed","Prof-specialty","Not-in-family","White","Male",0,0,80,"United-States",">50K" +36,"Private",195385,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +21,"Private",149809,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,24,"United-States","<=50K" +22,"Private",51985,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,30,"United-States","<=50K" +61,"Private",105384,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",137591,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,10,"Greece","<=50K" +49,"State-gov",324791,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Private",184303,"Some-college",10,"Separated","Priv-house-serv","Other-relative","White","Female",0,0,30,"El-Salvador","<=50K" +66,"?",314347,"HS-grad",9,"Married-civ-spouse","?","Husband","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",274010,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +22,"Private",321031,"HS-grad",9,"Never-married","Sales","Own-child","Black","Female",0,0,40,"United-States","<=50K" +57,"Federal-gov",313929,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +29,"Private",152951,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",247115,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +47,"Private",175958,"Prof-school",15,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +22,"Private",109039,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +59,"Self-emp-inc",141326,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States",">50K" +42,"State-gov",74334,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States",">50K" +64,"Self-emp-not-inc",47462,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +29,"Federal-gov",182344,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +25,"State-gov",295912,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +62,"Private",311495,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",187643,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",501671,"10th",6,"Divorced","Machine-op-inspct","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",301556,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,19,"United-States","<=50K" +18,"Private",187240,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,18,"United-States","<=50K" +33,"Private",594187,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +63,"Private",200474,"1st-4th",2,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Local-gov",152795,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,52,"United-States",">50K" +17,"Private",230789,"9th",5,"Never-married","Sales","Own-child","Black","Male",0,0,22,"United-States","<=50K" +31,"Private",114691,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",194591,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",114691,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +51,"State-gov",42017,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Local-gov",383384,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +28,"Private",29444,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +42,"Federal-gov",53727,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"?","<=50K" +38,"Private",277022,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"Columbia","<=50K" +43,"Local-gov",113324,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",342709,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",179203,"12th",8,"Never-married","Sales","Other-relative","White","Male",0,0,55,"United-States","<=50K" +46,"Private",251474,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +50,"Private",93730,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +22,"Private",37894,"HS-grad",9,"Separated","Other-service","Other-relative","White","Male",0,0,35,"United-States","<=50K" +18,"State-gov",272918,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,15,"United-States","<=50K" +53,"Private",151411,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +40,"Private",210648,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,44,"United-States",">50K" +36,"Self-emp-not-inc",347491,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States","<=50K" +32,"Private",255885,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,43,"United-States",">50K" +39,"Private",356838,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,12,"United-States","<=50K" +46,"Private",216164,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Local-gov",288781,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +19,"Private",439779,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,15,"United-States","<=50K" +24,"Private",161638,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"Ecuador","<=50K" +28,"Private",190525,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Local-gov",276249,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +44,"Private",147265,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",245090,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Nicaragua","<=50K" +42,"State-gov",219682,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +28,"Private",392100,"HS-grad",9,"Married-civ-spouse","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",358682,"Bachelors",13,"Never-married","Exec-managerial","Other-relative","White","Male",0,0,50,"?","<=50K" +47,"Private",262244,"Bachelors",13,"Never-married","Sales","Not-in-family","Black","Male",0,0,60,"United-States",">50K" +21,"Local-gov",218445,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"Mexico","<=50K" +19,"?",182609,"HS-grad",9,"Never-married","?","Own-child","Black","Female",0,0,25,"United-States","<=50K" +35,"Private",509462,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +26,"Private",213258,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",118401,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +67,"Self-emp-not-inc",45814,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",329733,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States",">50K" +26,"Private",29957,"Masters",14,"Never-married","Tech-support","Other-relative","White","Male",0,0,25,"United-States","<=50K" +51,"Private",215854,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +27,"Private",327766,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +27,"Private",405765,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?",">50K" +39,"Private",80680,"Some-college",10,"Divorced","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +32,"Private",177792,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,48,"United-States",">50K" +52,"Private",273514,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",202373,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +27,"Local-gov",332785,"HS-grad",9,"Never-married","Protective-serv","Own-child","White","Male",0,0,38,"United-States","<=50K" +46,"Private",149640,"7th-8th",4,"Married-spouse-absent","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +42,"Private",40151,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States","<=50K" +79,"Self-emp-inc",183686,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"United-States",">50K" +50,"Federal-gov",32801,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","Amer-Indian-Eskimo","Female",0,0,40,"United-States",">50K" +19,"?",195282,"HS-grad",9,"Never-married","?","Own-child","Black","Female",0,0,20,"United-States","<=50K" +51,"Local-gov",96678,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +66,"Private",186324,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,5,"United-States",">50K" +36,"Self-emp-not-inc",257250,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,99,"United-States","<=50K" +26,"Private",212800,"Assoc-acdm",12,"Never-married","Prof-specialty","Own-child","White","Female",0,0,36,"United-States","<=50K" +28,"Private",55360,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Male",0,0,50,"United-States","<=50K" +39,"Self-emp-not-inc",195253,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +43,"Private",45156,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +20,"Private",435469,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"Mexico","<=50K" +29,"Private",231287,"Some-college",10,"Divorced","Tech-support","Unmarried","White","Male",0,0,40,"United-States","<=50K" +18,"?",91670,"Some-college",10,"Never-married","?","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +60,"Private",165517,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",73161,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +60,"Private",178792,"HS-grad",9,"Widowed","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",32897,"11th",7,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +29,"Private",250967,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",379779,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Private",217838,"5th-6th",3,"Separated","Other-service","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +43,"Private",198965,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,38,"United-States",">50K" +37,"Private",220644,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"?","<=50K" +19,"Private",175081,"9th",5,"Never-married","Craft-repair","Other-relative","White","Male",0,0,60,"United-States","<=50K" +29,"Private",180299,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States","<=50K" +40,"Self-emp-not-inc",548664,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,15,"United-States","<=50K" +53,"Private",278114,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",394927,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +29,"Private",236938,"Assoc-acdm",12,"Divorced","Craft-repair","Unmarried","White","Female",0,0,38,"United-States","<=50K" +25,"Private",232991,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",0,0,40,"Mexico","<=50K" +38,"Private",34378,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +48,"Self-emp-inc",81513,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +18,"Private",106780,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,12,"United-States","<=50K" +37,"Private",329026,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +48,"Private",26490,"Bachelors",13,"Widowed","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +50,"Private",338033,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +24,"Private",21154,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +34,"Private",209449,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","Black","Male",0,0,40,"United-States",">50K" +19,"Private",389143,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Private",101260,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",198270,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",45781,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",134566,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"?",283806,"9th",5,"Divorced","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +46,"Private",422813,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Local-gov",103277,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,50,"United-States","<=50K" +18,"Private",201871,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +50,"Self-emp-not-inc",167728,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +42,"Private",211517,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",118212,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",98926,"Some-college",10,"Widowed","Tech-support","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +27,"Private",207352,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,0,40,"India",">50K" +31,"Private",206609,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",104509,"Masters",14,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",170350,"HS-grad",9,"Divorced","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +56,"Private",183884,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"State-gov",154410,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +63,"?",257659,"Masters",14,"Never-married","?","Not-in-family","White","Female",0,0,3,"United-States","<=50K" +28,"Private",274679,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +38,"Private",252662,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Self-emp-inc",356689,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,60,"United-States","<=50K" +18,"Private",205218,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +35,"Private",241306,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",139127,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",175625,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Private",206459,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",176123,"10th",6,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,60,"India","<=50K" +41,"Private",111483,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",106118,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States",">50K" +19,"Private",162094,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",145284,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +29,"Private",242482,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +35,"Self-emp-not-inc",160192,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"?",280699,"Some-college",10,"Never-married","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +18,"Private",156950,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,35,"United-States","<=50K" +53,"Private",215572,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",173593,"Masters",14,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,20,"Canada","<=50K" +55,"Private",193374,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Local-gov",334039,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",337664,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",113504,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",177072,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",174503,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",214807,"HS-grad",9,"Divorced","Handlers-cleaners","Unmarried","White","Female",0,0,37,"United-States","<=50K" +23,"Private",100345,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +22,"Private",409230,"12th",8,"Never-married","Transport-moving","Other-relative","White","Male",0,0,40,"United-States","<=50K" +65,"Self-emp-inc",115922,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +59,"?",375049,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,41,"United-States",">50K" +25,"Private",243560,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"Columbia","<=50K" +31,"Private",127215,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"State-gov",276241,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +49,"State-gov",175109,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Private",498079,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Federal-gov",344394,"Some-college",10,"Married-civ-spouse","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +23,"Private",245302,"Some-college",10,"Divorced","Sales","Own-child","Black","Female",0,0,40,"United-States","<=50K" +63,"Private",43313,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",188467,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-inc",351278,"Bachelors",13,"Divorced","Farming-fishing","Unmarried","White","Male",0,0,50,"United-States","<=50K" +31,"Private",182246,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +48,"?",353824,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"?",">50K" +31,"Private",387116,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,36,"Jamaica","<=50K" +47,"Private",34248,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +54,"State-gov",198741,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",32950,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",381153,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",100067,"11th",7,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,35,"United-States",">50K" +34,"Private",208785,"Assoc-acdm",12,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +31,"Private",61559,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +41,"Private",176452,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"Peru","<=50K" +41,"?",128700,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",328518,"Assoc-voc",11,"Never-married","Prof-specialty","Other-relative","White","Male",0,0,30,"United-States","<=50K" +30,"?",201196,"11th",7,"Never-married","?","Own-child","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",378546,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Local-gov",212210,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"?","<=50K" +59,"Federal-gov",178660,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-not-inc",22641,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +59,"Private",316027,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,45,"Cuba","<=50K" +47,"Private",431515,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Self-emp-not-inc",149770,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +42,"Private",165916,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +29,"Federal-gov",107411,"Some-college",10,"Married-spouse-absent","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"Private",217961,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,45,"Outlying-US(Guam-USVI-etc)","<=50K" +43,"Self-emp-not-inc",350387,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +46,"Private",325372,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",156718,"Some-college",10,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",216472,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,20,"United-States","<=50K" +29,"State-gov",106972,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +33,"Private",131934,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +46,"Local-gov",359193,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +35,"Private",261012,"Some-college",10,"Married-spouse-absent","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +25,"Private",113654,"HS-grad",9,"Separated","Exec-managerial","Unmarried","White","Female",0,0,37,"United-States","<=50K" +35,"Private",218955,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",115963,"7th-8th",4,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,42,"United-States","<=50K" +39,"Private",80638,"Some-college",10,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,84,"United-States",">50K" +37,"Private",147258,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +22,"Private",214635,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +25,"Private",200318,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +50,"Private",138270,"HS-grad",9,"Married-civ-spouse","Sales","Wife","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",103435,"Assoc-voc",11,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +59,"Self-emp-inc",133201,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Italy","<=50K" +24,"Private",175183,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",99870,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +38,"?",107479,"9th",5,"Never-married","?","Own-child","White","Female",0,0,12,"United-States","<=50K" +60,"Private",113440,"Bachelors",13,"Divorced","Exec-managerial","Own-child","White","Male",0,0,60,"United-States","<=50K" +19,"Private",85690,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,30,"United-States","<=50K" +23,"Private",45713,"Some-college",10,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +17,"?",67808,"10th",6,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",113936,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",158291,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",193898,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +43,"Private",191982,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,55,"United-States","<=50K" +21,"?",72953,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +54,"Private",271160,"Assoc-voc",11,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",33087,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +29,"Private",106153,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +22,"Private",29444,"12th",8,"Never-married","Farming-fishing","Not-in-family","Amer-Indian-Eskimo","Male",0,0,50,"United-States","<=50K" +37,"Private",105021,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +38,"Self-emp-not-inc",239045,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +34,"Private",94413,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",20534,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,84,"United-States",">50K" +28,"Private",350254,"1st-4th",2,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +68,"Private",194746,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"Cuba","<=50K" +36,"Private",269042,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,40,"Laos","<=50K" +20,"Private",447488,"9th",5,"Never-married","Other-service","Unmarried","White","Male",0,0,30,"Mexico","<=50K" +24,"Private",267706,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Female",0,0,45,"United-States","<=50K" +38,"Private",198216,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",227931,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",181776,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +32,"Private",132601,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Private",205410,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",292570,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,50,"United-States","<=50K" +43,"Private",76460,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",295163,"12th",8,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",27255,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"?","<=50K" +23,"Private",69847,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Female",0,0,20,"United-States","<=50K" +24,"?",390608,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +41,"Private",317539,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",195678,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",466502,"7th-8th",4,"Widowed","Other-service","Unmarried","White","Male",0,0,30,"United-States","<=50K" +28,"Local-gov",220754,"HS-grad",9,"Separated","Transport-moving","Own-child","White","Female",0,0,25,"United-States","<=50K" +36,"Private",343476,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +60,"Self-emp-not-inc",38622,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"State-gov",173730,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States","<=50K" +32,"Private",178623,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"?","<=50K" +27,"Private",300783,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,42,"United-States",">50K" +60,"Private",224644,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",191502,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Private",61885,"12th",8,"Divorced","Transport-moving","Other-relative","Black","Male",0,0,35,"United-States","<=50K" +34,"Self-emp-not-inc",213887,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,32,"Canada",">50K" +36,"Private",331395,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",145098,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",123075,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",216804,"7th-8th",4,"Never-married","Other-service","Own-child","White","Male",0,0,33,"United-States","<=50K" +40,"Private",188291,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",33610,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +39,"Private",234901,"Assoc-acdm",12,"Separated","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",349148,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",168443,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +43,"Private",211860,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,24,"United-States","<=50K" +35,"Private",193961,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +59,"Self-emp-not-inc",75804,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,65,"United-States",">50K" +33,"Self-emp-not-inc",176185,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",306779,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,50,"United-States","<=50K" +48,"Private",265192,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +54,"Private",139347,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Private",107682,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +37,"Private",34173,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",128378,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-inc",195638,"Some-college",10,"Separated","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",59287,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",162442,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +29,"?",350603,"10th",6,"Never-married","?","Own-child","White","Female",0,0,38,"United-States","<=50K" +39,"Private",344743,"Some-college",10,"Married-civ-spouse","Adm-clerical","Own-child","Black","Female",0,0,50,"United-States",">50K" +26,"Private",176795,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States",">50K" +31,"Private",309620,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,6,"South","<=50K" +39,"Private",336880,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",206600,"11th",7,"Never-married","Other-service","Other-relative","White","Male",0,0,30,"Mexico","<=50K" +25,"Private",193051,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,35,"United-States","<=50K" +49,"Private",62793,"HS-grad",9,"Divorced","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +53,"Private",264939,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"Mexico","<=50K" +52,"Private",370552,"Preschool",1,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +52,"Private",163678,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +74,"?",89667,"Bachelors",13,"Widowed","?","Not-in-family","Other","Female",0,0,35,"United-States","<=50K" +50,"Private",558490,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +76,"Private",208843,"7th-8th",4,"Widowed","Protective-serv","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +19,"Private",95078,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +25,"Private",169679,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",101320,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",168906,"Assoc-acdm",12,"Divorced","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +20,"Private",212582,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +66,"?",170617,"Masters",14,"Widowed","?","Not-in-family","White","Male",0,0,6,"United-States","<=50K" +63,"?",170529,"Bachelors",13,"Married-civ-spouse","?","Wife","Black","Female",0,0,45,"United-States","<=50K" +27,"Private",99897,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",175224,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,60,"Nicaragua","<=50K" +23,"Private",149704,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"Federal-gov",214542,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",167319,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"State-gov",43716,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,4,"United-States","<=50K" +28,"Private",191935,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +35,"Private",338611,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",136419,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,75,"United-States",">50K" +17,"Private",72321,"11th",7,"Never-married","Other-service","Other-relative","White","Female",0,0,12,"United-States","<=50K" +41,"Local-gov",189956,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,40,"United-States",">50K" +44,"Private",403782,"Assoc-voc",11,"Divorced","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +47,"Private",456661,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +24,"Private",279041,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",65716,"Assoc-voc",11,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",189809,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,52,"Jamaica","<=50K" +62,"Local-gov",223637,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +27,"Local-gov",199343,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,38,"United-States","<=50K" +59,"Private",139344,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +35,"Private",119098,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",195025,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +28,"Private",186720,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,50,"United-States","<=50K" +28,"Private",328923,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,38,"United-States","<=50K" +59,"State-gov",159472,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",138662,"Some-college",10,"Separated","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +54,"Local-gov",286342,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,32,"United-States",">50K" +39,"Private",181705,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +41,"Private",193882,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",216497,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"Germany","<=50K" +32,"Self-emp-inc",124919,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,50,"Iran",">50K" +58,"Private",256274,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",326379,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",243142,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +51,"Local-gov",155118,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,70,"United-States",">50K" +54,"Private",189607,"Bachelors",13,"Never-married","Other-service","Own-child","Black","Female",0,0,36,"United-States","<=50K" +20,"Private",39478,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +35,"Private",206951,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",127647,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,36,"United-States","<=50K" +42,"Private",182302,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"State-gov",166597,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Self-emp-not-inc",33363,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States",">50K" +74,"Self-emp-inc",167537,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +34,"Private",179378,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,40,"United-States","<=50K" +50,"State-gov",297551,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,52,"United-States","<=50K" +50,"Private",198362,"Assoc-voc",11,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +43,"Private",240504,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",169662,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"?",164940,"HS-grad",9,"Separated","?","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +61,"Private",210488,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +21,"Private",154835,"Some-college",10,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +27,"Private",333296,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"?","<=50K" +47,"Private",192793,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Iran",">50K" +33,"Private",136331,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",509048,"HS-grad",9,"Never-married","Sales","Other-relative","Black","Female",0,0,37,"United-States","<=50K" +38,"Private",318610,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +45,"Private",104521,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",247695,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +35,"Private",219546,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"Germany","<=50K" +21,"Private",169699,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"State-gov",131302,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,44,"United-States","<=50K" +50,"Private",171852,"Bachelors",13,"Separated","Prof-specialty","Own-child","Other","Female",0,0,40,"United-States","<=50K" +36,"State-gov",340091,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,36,"United-States",">50K" +20,"Private",204641,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +49,"Private",213431,"HS-grad",9,"Separated","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +40,"State-gov",377018,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +22,"Private",184543,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +60,"?",188236,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +67,"Private",233022,"11th",7,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,20,"United-States","<=50K" +21,"Private",177420,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Other","Female",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",21101,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Amer-Indian-Eskimo","Male",0,0,50,"United-States","<=50K" +17,"Private",52486,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,12,"United-States","<=50K" +49,"State-gov",36177,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +38,"Private",102350,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +38,"Private",165930,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",297574,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,99,"United-States",">50K" +40,"Private",120277,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"?",87569,"Some-college",10,"Separated","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",155972,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +46,"State-gov",162852,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",64860,"Some-college",10,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",0,0,22,"United-States","<=50K" +24,"Private",322674,"Assoc-acdm",12,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +62,"Private",202242,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +54,"Private",175262,"Preschool",1,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +23,"Private",201682,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +60,"Private",166330,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +18,"Self-emp-inc",147612,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Female",0,0,8,"United-States","<=50K" +41,"Local-gov",213154,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,40,"United-States","<=50K" +45,"Local-gov",33798,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +62,"State-gov",199198,"Assoc-voc",11,"Widowed","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",90915,"Bachelors",13,"Married-spouse-absent","Tech-support","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-inc",337778,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"Yugoslavia",">50K" +31,"Private",187203,"HS-grad",9,"Never-married","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +44,"Private",261497,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"?","<=50K" +33,"Self-emp-not-inc",361817,"HS-grad",9,"Separated","Craft-repair","Unmarried","White","Male",0,0,50,"United-States","<=50K" +62,"Self-emp-not-inc",226546,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,16,"United-States","<=50K" +27,"Private",100168,"7th-8th",4,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +42,"Federal-gov",272625,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States",">50K" +55,"Private",254516,"9th",5,"Never-married","Handlers-cleaners","Other-relative","Black","Male",0,0,37,"United-States","<=50K" +41,"Private",207375,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +45,"Private",48271,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +67,"Self-emp-not-inc",152102,"HS-grad",9,"Widowed","Farming-fishing","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +25,"Private",234665,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"Private",180060,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +19,"Private",32477,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +26,"Private",137658,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +61,"Private",228287,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +43,"Private",33310,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +53,"Private",270546,"HS-grad",9,"Divorced","Priv-house-serv","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +53,"Federal-gov",290290,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +42,"Self-emp-inc",287037,"12th",8,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +36,"Private",128516,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +55,"Self-emp-not-inc",185195,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,99,"United-States","<=50K" +17,"Private",98005,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,16,"United-States","<=50K" +55,"Self-emp-not-inc",283635,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +36,"Private",98360,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Local-gov",202872,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +54,"Self-emp-not-inc",118365,"10th",6,"Divorced","Other-service","Not-in-family","Black","Female",0,0,10,"United-States","<=50K" +45,"Self-emp-not-inc",184285,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +48,"Private",345831,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Local-gov",99679,"Prof-school",15,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States",">50K" +31,"Private",253354,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Private",190650,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Male",0,0,40,"Taiwan","<=50K" +19,"Private",204389,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Other","Female",0,0,25,"Puerto-Rico","<=50K" +31,"Federal-gov",294870,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",159442,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +55,"Local-gov",161662,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +38,"Private",52738,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",252024,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,20,"Mexico","<=50K" +27,"Private",189702,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",407913,"HS-grad",9,"Separated","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",166527,"Some-college",10,"Never-married","Adm-clerical","Own-child","Other","Female",0,0,20,"United-States","<=50K" +24,"Self-emp-not-inc",34918,"Assoc-voc",11,"Never-married","Other-service","Unmarried","White","Female",0,0,38,"United-States","<=50K" +27,"Private",142712,"Masters",14,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"?","<=50K" +18,"Federal-gov",201686,"11th",7,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,4,"United-States","<=50K" +28,"Local-gov",179759,"Some-college",10,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",94954,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",201743,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +59,"Self-emp-not-inc",119344,"10th",6,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,36,"United-States","<=50K" +33,"Private",149726,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,46,"United-States","<=50K" +28,"Private",419146,"7th-8th",4,"Separated","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +41,"Private",171234,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +30,"Private",206325,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +59,"Private",202682,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",121055,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +29,"Private",84366,"10th",6,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +60,"Private",139391,"Some-college",10,"Married-spouse-absent","Machine-op-inspct","Not-in-family","White","Male",0,0,50,"United-States",">50K" +41,"Private",30759,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +32,"Private",137875,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +73,"?",139049,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,22,"United-States",">50K" +20,"Private",238384,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +49,"Private",340755,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Local-gov",224947,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +33,"State-gov",111994,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +25,"Private",125491,"Some-college",10,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Female",0,0,34,"United-States","<=50K" +34,"?",310525,"HS-grad",9,"Married-civ-spouse","?","Husband","Black","Male",0,0,10,"United-States","<=50K" +19,"?",71592,"Some-college",10,"Never-married","?","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +40,"Local-gov",99185,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",249935,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,44,"United-States","<=50K" +51,"Private",206775,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +22,"Private",230704,"Assoc-acdm",12,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,20,"Jamaica","<=50K" +34,"Private",242361,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,50,"United-States","<=50K" +22,"Private",134746,"10th",6,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +56,"Private",174040,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",273604,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"Private",192409,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +26,"Self-emp-not-inc",102476,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +48,"Private",234504,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Self-emp-not-inc",468713,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",84560,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",148995,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",34816,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,12,"United-States","<=50K" +28,"Private",211184,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +53,"Private",33304,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +65,"Federal-gov",179985,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",219815,"Some-college",10,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",106548,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +70,"Private",89787,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,20,"United-States","<=50K" +55,"Private",164857,"Some-college",10,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Federal-gov",257124,"Bachelors",13,"Never-married","Transport-moving","Other-relative","White","Male",0,0,35,"United-States","<=50K" +31,"Private",227446,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Cuba",">50K" +24,"Private",189749,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",176321,"7th-8th",4,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +26,"Private",284250,"HS-grad",9,"Never-married","Craft-repair","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",101885,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",134130,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +52,"Private",260938,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",238184,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",148626,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +65,"Private",113323,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Local-gov",34246,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +31,"Private",279680,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States","<=50K" +84,"Private",188328,"HS-grad",9,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +51,"Private",96609,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Local-gov",84257,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Private",275632,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"Private",385540,"10th",6,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +30,"Private",196342,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"Ireland","<=50K" +47,"Private",97176,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",197714,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +43,"Self-emp-not-inc",147099,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,36,"United-States","<=50K" +30,"Private",186346,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +46,"Private",73434,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +49,"Local-gov",275074,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +37,"Private",209214,"5th-6th",3,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +42,"Private",210525,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",176684,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",210474,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +26,"Private",293690,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,58,"United-States",">50K" +64,"Private",149775,"Masters",14,"Never-married","Prof-specialty","Other-relative","White","Female",0,0,8,"United-States","<=50K" +20,"Private",323009,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"Germany","<=50K" +31,"Private",126950,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",115411,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",265356,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +31,"Local-gov",192565,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,90,"United-States",">50K" +35,"Self-emp-not-inc",348771,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,36,"United-States","<=50K" +30,"Self-emp-not-inc",148959,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +35,"Private",126569,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,20,"United-States","<=50K" +40,"Private",105936,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Own-child","White","Female",0,0,38,"United-States","<=50K" +18,"Private",188076,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +23,"Private",184400,"10th",6,"Never-married","Transport-moving","Own-child","Asian-Pac-Islander","Male",0,0,30,"?","<=50K" +63,"Private",124242,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +20,"State-gov",200819,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",100480,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +49,"Private",129513,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +53,"Self-emp-not-inc",297796,"10th",6,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",195488,"HS-grad",9,"Separated","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +54,"Private",153486,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,56,"United-States",">50K" +40,"Private",126845,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",206974,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",412149,"10th",6,"Never-married","Farming-fishing","Other-relative","White","Male",0,0,35,"Mexico","<=50K" +24,"Private",653574,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"El-Salvador","<=50K" +37,"Private",70562,"1st-4th",2,"Never-married","Other-service","Unmarried","White","Female",0,0,48,"El-Salvador","<=50K" +62,"Private",197514,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,16,"United-States","<=50K" +19,"?",309284,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Private",334679,"Assoc-voc",11,"Widowed","Prof-specialty","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +31,"Private",151484,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,8,"United-States","<=50K" +42,"Self-emp-inc",78765,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,90,"United-States",">50K" +42,"Private",98427,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,35,"United-States","<=50K" +54,"Private",230767,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Cuba","<=50K" +23,"Private",117606,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,60,"United-States","<=50K" +28,"Private",68642,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,46,"United-States","<=50K" +42,"Private",341638,"11th",7,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",65920,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +33,"Federal-gov",188246,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",198727,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",706026,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"?",348148,"11th",7,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +62,"Private",77884,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +17,"Private",160758,"10th",6,"Never-married","Sales","Other-relative","White","Male",0,0,30,"United-States","<=50K" +58,"Private",201112,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,55,"United-States",">50K" +34,"Private",230246,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,42,"United-States",">50K" +20,"Private",373935,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +64,"Federal-gov",341695,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +27,"Private",119793,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"?","<=50K" +41,"Private",178002,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +40,"Private",233130,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +53,"Local-gov",192982,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,38,"United-States",">50K" +44,"Private",33155,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +37,"Private",187346,"5th-6th",3,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"Mexico","<=50K" +46,"Private",78529,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,60,"United-States",">50K" +17,"Private",101626,"9th",5,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,20,"United-States","<=50K" +35,"Private",117567,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",110791,"Assoc-acdm",12,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"State-gov",207120,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Private",43206,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,25,"United-States","<=50K" +26,"Private",120238,"Bachelors",13,"Never-married","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +26,"Private",189219,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +35,"State-gov",190895,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",83517,"9th",5,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Local-gov",59313,"Some-college",10,"Separated","Adm-clerical","Own-child","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",202033,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Local-gov",55658,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +21,"Private",118186,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,20,"United-States","<=50K" +22,"Private",279901,"HS-grad",9,"Married-civ-spouse","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +52,"Private",110954,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"El-Salvador",">50K" +36,"Self-emp-not-inc",90159,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +42,"Private",34278,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",37778,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,54,"United-States","<=50K" +39,"Private",160623,"Assoc-acdm",12,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",342458,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +53,"Private",64322,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",373914,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",205884,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States",">50K" +62,"Local-gov",208266,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",222450,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +23,"Private",348420,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Federal-gov",197284,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"?",204773,"Assoc-acdm",12,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States","<=50K" +41,"Private",206066,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",61885,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",299908,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,40,"United-States",">50K" +35,"Private",46028,"Assoc-acdm",12,"Divorced","Other-service","Unmarried","White","Female",0,0,50,"United-States","<=50K" +30,"Private",154587,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"Puerto-Rico","<=50K" +36,"Private",32334,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +42,"Private",319588,"Bachelors",13,"Married-spouse-absent","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +51,"Private",226735,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +34,"Private",226443,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-inc",359259,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"Portugal","<=50K" +27,"Private",36851,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,41,"United-States","<=50K" +39,"Private",393480,"HS-grad",9,"Separated","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +31,"Private",231569,"Bachelors",13,"Never-married","Sales","Not-in-family","Black","Female",0,0,50,"United-States","<=50K" +23,"Private",353010,"11th",7,"Never-married","Craft-repair","Unmarried","White","Male",0,0,35,"United-States","<=50K" +66,"Private",262285,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,99,"United-States","<=50K" +26,"Private",160300,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Private",156953,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Self-emp-inc",136823,"11th",7,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +48,"Self-emp-not-inc",160724,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"Japan","<=50K" +37,"Self-emp-inc",86459,"Assoc-acdm",12,"Separated","Exec-managerial","Unmarried","White","Male",0,0,50,"United-States","<=50K" +17,"Private",238628,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,5,"United-States","<=50K" +50,"Private",339954,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +28,"?",222005,"HS-grad",9,"Never-married","?","Other-relative","White","Female",0,0,40,"Mexico","<=50K" +39,"Private",214117,"Some-college",10,"Divorced","Craft-repair","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +28,"Federal-gov",298661,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",179488,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Local-gov",100270,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",126701,"9th",5,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +20,"Private",209131,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"State-gov",400132,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +23,"State-gov",278155,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",178431,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Taiwan","<=50K" +36,"Private",115700,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",167832,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",218164,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,44,"United-States","<=50K" +36,"Self-emp-inc",242080,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,80,"United-States",">50K" +67,"Federal-gov",223257,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Male",0,0,40,"United-States","<=50K" +45,"Private",140644,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States",">50K" +22,"Private",205970,"10th",6,"Separated","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +25,"Private",216583,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,43,"United-States","<=50K" +61,"Private",162432,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Local-gov",83671,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +47,"Self-emp-inc",205100,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"Germany","<=50K" +31,"Private",195750,"1st-4th",2,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +17,"Private",220562,"9th",5,"Never-married","Sales","Other-relative","Other","Female",0,0,32,"Mexico","<=50K" +38,"Self-emp-inc",312232,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",386337,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"?","<=50K" +42,"Private",86185,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +78,"Private",105586,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","Asian-Pac-Islander","Male",0,0,36,"United-States","<=50K" +54,"Private",103345,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Local-gov",150553,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,50,"United-States","<=50K" +30,"Private",26009,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +46,"Private",149388,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",151626,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,45,"United-States","<=50K" +30,"Private",169583,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +25,"Private",213383,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-inc",103078,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Local-gov",109526,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,38,"United-States","<=50K" +51,"Private",142835,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"State-gov",43475,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",190916,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"Private",175987,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Local-gov",214385,"11th",7,"Divorced","Other-service","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +26,"Private",192652,"Bachelors",13,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Federal-gov",207685,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +19,"Private",143857,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +39,"Private",163392,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,26,"?","<=50K" +51,"Private",310774,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +29,"?",427965,"HS-grad",9,"Separated","?","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +27,"Private",279608,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +33,"Private",312881,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States",">50K" +19,"Private",175083,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,8,"United-States","<=50K" +67,"?",132057,"HS-grad",9,"Married-civ-spouse","?","Husband","Black","Male",0,0,20,"United-States","<=50K" +41,"Private",32878,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +29,"Federal-gov",360527,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",99478,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",113035,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Federal-gov",99199,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,36,"United-States","<=50K" +48,"Private",236858,"11th",7,"Divorced","Other-service","Not-in-family","White","Female",0,0,31,"United-States","<=50K" +46,"Self-emp-inc",201865,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +35,"Private",268661,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Federal-gov",475324,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",117295,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",65704,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"?","<=50K" +45,"Private",192835,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Local-gov",76720,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +33,"Local-gov",133876,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +22,"Private",123727,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +50,"Private",129956,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +25,"Private",96268,"11th",7,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",317320,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",86872,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +31,"State-gov",100863,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States",">50K" +56,"Private",164332,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,15,"United-States","<=50K" +49,"Self-emp-not-inc",122584,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",34377,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Private",162030,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,43,"United-States","<=50K" +33,"Private",199170,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",470203,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +40,"Private",266803,"Assoc-acdm",12,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +72,"?",188009,"7th-8th",4,"Divorced","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +32,"State-gov",513416,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +44,"Private",98211,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +48,"Private",196107,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +17,"Private",108273,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,12,"United-States","<=50K" +22,"Local-gov",412316,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +17,"Private",120068,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,17,"United-States","<=50K" +49,"Self-emp-inc",101722,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +26,"Private",120268,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +19,"State-gov",144429,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,10,"United-States","<=50K" +17,"Private",271122,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +38,"Private",255621,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",90934,"Assoc-voc",11,"Divorced","Protective-serv","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +48,"Private",128460,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,42,"United-States",">50K" +63,"Private",30813,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +19,"Private",164585,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Private",215647,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +54,"Private",421561,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",66755,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,40,"United-States","<=50K" +20,"?",117222,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"State-gov",29145,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +51,"Self-emp-not-inc",20795,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",311376,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"State-gov",122660,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,40,"United-States","<=50K" +19,"?",137578,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,16,"United-States","<=50K" +37,"Private",193689,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,42,"United-States",">50K" +29,"Private",144556,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +22,"Private",243178,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" +60,"State-gov",190682,"Assoc-voc",11,"Widowed","Other-service","Not-in-family","Black","Female",0,0,37,"United-States","<=50K" +35,"Private",233786,"11th",7,"Separated","Other-service","Unmarried","White","Male",0,0,20,"United-States","<=50K" +45,"Private",102202,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",95299,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,40,"Vietnam",">50K" +43,"Self-emp-inc",240504,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States",">50K" +32,"State-gov",169973,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +35,"Private",144937,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,42,"United-States","<=50K" +32,"Private",211751,"Assoc-voc",11,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +61,"Private",84587,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +20,"?",187332,"10th",6,"Never-married","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +42,"Self-emp-inc",188615,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +21,"Private",119704,"Some-college",10,"Never-married","Sales","Unmarried","White","Female",0,0,35,"United-States","<=50K" +21,"Private",275190,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +26,"Private",417941,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"State-gov",196348,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +24,"Private",221955,"Bachelors",13,"Married-civ-spouse","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +47,"Private",173938,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,57,"United-States",">50K" +51,"Private",123429,"Assoc-acdm",12,"Divorced","Tech-support","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +65,"?",143732,"HS-grad",9,"Widowed","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +61,"Private",203126,"Bachelors",13,"Divorced","Priv-house-serv","Not-in-family","White","Female",0,0,12,"?","<=50K" +67,"Private",174693,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",0,0,25,"Nicaragua","<=50K" +49,"Private",357540,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,25,"United-States","<=50K" +61,"Private",280088,"7th-8th",4,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",257380,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,35,"United-States","<=50K" +19,"Private",165306,"Some-college",10,"Never-married","Tech-support","Other-relative","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +29,"Self-emp-not-inc",109001,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +21,"Private",32950,"Some-college",10,"Never-married","Sales","Unmarried","White","Male",0,0,40,"United-States","<=50K" +22,"Private",182163,"HS-grad",9,"Separated","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",188246,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +36,"Private",297335,"Bachelors",13,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Female",0,0,50,"China","<=50K" +37,"Private",108366,"Bachelors",13,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,46,"United-States","<=50K" +35,"Private",328301,"Assoc-acdm",12,"Married-AF-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +17,"Private",182158,"10th",6,"Never-married","Priv-house-serv","Own-child","White","Male",0,0,30,"United-States","<=50K" +37,"Private",169426,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +22,"?",330571,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +28,"Private",535978,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",29393,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",369166,"Some-college",10,"Never-married","Farming-fishing","Other-relative","White","Female",0,0,65,"United-States","<=50K" +45,"Local-gov",257855,"11th",7,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,50,"United-States","<=50K" +32,"Private",164197,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States",">50K" +63,"Private",109517,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,43,"United-States","<=50K" +22,"Private",112137,"Some-college",10,"Never-married","Prof-specialty","Other-relative","Asian-Pac-Islander","Female",0,0,20,"South","<=50K" +36,"Private",160035,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +45,"State-gov",50567,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",140011,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +27,"State-gov",271328,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +20,"?",183083,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +47,"Self-emp-not-inc",159869,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,56,"United-States",">50K" +46,"Private",102542,"7th-8th",4,"Never-married","Other-service","Own-child","White","Male",0,0,52,"United-States","<=50K" +28,"Private",297742,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Private",176917,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +26,"Private",165235,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,40,"Thailand","<=50K" +32,"Self-emp-not-inc",52647,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Local-gov",48542,"12th",8,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +59,"Private",279232,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +58,"State-gov",259929,"Doctorate",16,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,43,"United-States",">50K" +45,"Private",221780,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +76,"Self-emp-not-inc",253408,"Some-college",10,"Widowed","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",298841,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +32,"Private",321313,"Masters",14,"Never-married","Sales","Own-child","Black","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",64875,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Private",275232,"Assoc-acdm",12,"Never-married","Prof-specialty","Unmarried","Black","Female",0,0,36,"United-States","<=50K" +53,"Self-emp-inc",134854,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Greece",">50K" +41,"Private",67339,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"?","<=50K" +27,"State-gov",192355,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +44,"Local-gov",208528,"Assoc-acdm",12,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +35,"Private",160120,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,50,"United-States",">50K" +36,"Private",250238,"1st-4th",2,"Never-married","Other-service","Other-relative","Other","Female",0,0,40,"El-Salvador","<=50K" +51,"Private",25031,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,10,"United-States",">50K" +42,"Local-gov",255847,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",111979,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",231037,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Federal-gov",30030,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +27,"Private",292120,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +29,"Private",190777,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +38,"Self-emp-not-inc",41591,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",0,0,30,"United-States","<=50K" +29,"Private",186733,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +18,"?",78567,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +19,"?",140590,"12th",8,"Never-married","?","Own-child","Black","Male",0,0,30,"United-States","<=50K" +25,"Private",182227,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +34,"Local-gov",205704,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +37,"State-gov",24342,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States","<=50K" +37,"Private",138192,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +18,"Private",334676,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +24,"Private",177526,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +17,"Private",152696,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +35,"Private",114765,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",265509,"Assoc-voc",11,"Separated","Tech-support","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +29,"Private",180758,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +49,"Self-emp-not-inc",127921,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +71,"?",177906,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,10,"United-States",">50K" +35,"Federal-gov",182898,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",422249,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +37,"Private",222450,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +33,"Local-gov",190027,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,18,"United-States","<=50K" +49,"Private",281647,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +32,"Private",117963,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States","<=50K" +63,"?",319121,"11th",7,"Separated","?","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",225504,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",104334,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +30,"State-gov",48214,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +30,"Private",145714,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Self-emp-inc",38240,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Self-emp-not-inc",27385,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,10,"United-States","<=50K" +56,"Private",204254,"10th",6,"Divorced","Other-service","Unmarried","Black","Female",0,0,45,"United-States","<=50K" +28,"Private",411587,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"Honduras","<=50K" +43,"Private",221172,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,24,"United-States",">50K" +46,"Private",54190,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +50,"Local-gov",24139,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,65,"United-States","<=50K" +37,"Private",112497,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +41,"Private",138907,"HS-grad",9,"Divorced","Priv-house-serv","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",186325,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,38,"United-States",">50K" +23,"Private",199452,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +59,"Private",126677,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +47,"Local-gov",93618,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,33,"United-States","<=50K" +29,"Private",353352,"Assoc-voc",11,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +35,"Private",143058,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +24,"Private",239663,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,15,"United-States","<=50K" +22,"Private",167615,"HS-grad",9,"Never-married","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",442274,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Federal-gov",174533,"Bachelors",13,"Separated","Other-service","Unmarried","White","Female",0,0,72,"?","<=50K" +40,"State-gov",50093,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,20,"United-States","<=50K" +61,"Private",270056,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Japan","<=50K" +58,"Self-emp-not-inc",131991,"Bachelors",13,"Never-married","Farming-fishing","Own-child","White","Male",0,0,72,"United-States","<=50K" +39,"State-gov",126336,"HS-grad",9,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",341117,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +25,"Private",108505,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +69,"?",106566,"Doctorate",16,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Private",74791,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Male",0,0,60,"?","<=50K" +45,"Private",267967,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +27,"?",181284,"12th",8,"Married-civ-spouse","?","Husband","Black","Male",0,0,45,"United-States","<=50K" +28,"Private",102533,"Some-college",10,"Separated","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",69757,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +41,"State-gov",210094,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"State-gov",389147,"HS-grad",9,"Never-married","Sales","Not-in-family","Black","Female",0,0,30,"United-States","<=50K" +44,"Private",210648,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",94809,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,45,"United-States",">50K" +36,"Local-gov",298717,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +66,"Private",236879,"Preschool",1,"Widowed","Priv-house-serv","Other-relative","White","Female",0,0,40,"Guatemala","<=50K" +33,"Private",170148,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +39,"Local-gov",166497,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States",">50K" +30,"Private",247156,"HS-grad",9,"Never-married","Transport-moving","Own-child","Black","Male",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",204052,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +62,"Self-emp-not-inc",122246,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,32,"United-States","<=50K" +21,"Private",180339,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +43,"Private",193882,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",112269,"Some-college",10,"Never-married","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +26,"Federal-gov",171928,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"Japan","<=50K" +45,"Federal-gov",179638,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +46,"Self-emp-inc",125892,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",721712,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,15,"United-States","<=50K" +56,"Private",197369,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",334679,"Masters",14,"Separated","Machine-op-inspct","Unmarried","Asian-Pac-Islander","Female",0,0,42,"India","<=50K" +23,"Private",235853,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +51,"Self-emp-not-inc",353281,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +19,"Private",203061,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +33,"Self-emp-not-inc",62932,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",118551,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,80,"United-States","<=50K" +52,"Private",99184,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",189674,"Some-college",10,"Separated","Other-service","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +34,"Private",226883,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"?",109564,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Self-emp-inc",66872,"12th",8,"Married-civ-spouse","Sales","Husband","Other","Male",0,0,98,"Dominican-Republic","<=50K" +35,"Local-gov",268292,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Federal-gov",139290,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",206541,"11th",7,"Divorced","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +23,"Private",203139,"Some-college",10,"Never-married","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",294398,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",386864,"10th",6,"Never-married","Other-service","Other-relative","White","Male",0,0,35,"Mexico","<=50K" +17,"Private",369909,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +26,"Private",176008,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",174426,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +54,"Private",292673,"1st-4th",2,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"Mexico","<=50K" +51,"Local-gov",134808,"HS-grad",9,"Widowed","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",95763,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +21,"Private",222490,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +44,"Private",29115,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",66638,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +39,"Private",53926,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"?",43739,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",104359,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",124604,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +45,"Private",114797,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +60,"Federal-gov",67320,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +28,"Federal-gov",53147,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",13769,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Amer-Indian-Eskimo","Male",0,0,30,"United-States","<=50K" +44,"Private",202872,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +19,"State-gov",149528,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,12,"United-States","<=50K" +37,"Private",132879,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Self-emp-not-inc",112362,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,38,"United-States","<=50K" +44,"Private",131650,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,54,"United-States",">50K" +30,"Private",154568,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,36,"Vietnam",">50K" +23,"Private",132300,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",135134,"Masters",14,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +32,"Local-gov",113838,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,99,"United-States","<=50K" +76,"Federal-gov",25319,"Masters",14,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +57,"Local-gov",190561,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","Black","Female",0,0,30,"United-States","<=50K" +58,"?",150031,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Private",211116,"10th",6,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +38,"Private",226311,"HS-grad",9,"Married-AF-spouse","Other-service","Wife","White","Female",0,0,25,"United-States","<=50K" +59,"Self-emp-not-inc",64102,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +23,"Private",234663,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",615367,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",163090,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +44,"Private",192225,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",370183,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",242482,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",169953,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Local-gov",144182,"Preschool",1,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,25,"United-States","<=50K" +26,"Private",203777,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Female",0,0,37,"United-States","<=50K" +39,"Private",210991,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",472580,"Some-college",10,"Never-married","Sales","Own-child","Black","Male",0,0,40,"United-States","<=50K" +33,"State-gov",200289,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,19,"India","<=50K" +30,"Private",110622,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"China","<=50K" +59,"State-gov",139616,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",39212,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +28,"Private",51961,"Some-college",10,"Never-married","Tech-support","Own-child","Black","Male",0,0,24,"United-States","<=50K" +48,"Self-emp-not-inc",117849,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",151790,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,30,"United-States","<=50K" +49,"Private",168211,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +37,"State-gov",117651,"Bachelors",13,"Never-married","Prof-specialty","Other-relative","White","Male",0,0,40,"United-States","<=50K" +18,"Private",157131,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,8,"United-States","<=50K" +61,"Private",225970,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",177951,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,48,"United-States","<=50K" +66,"Private",134130,"Bachelors",13,"Widowed","Other-service","Not-in-family","White","Male",0,0,12,"United-States","<=50K" +27,"Local-gov",199172,"HS-grad",9,"Married-civ-spouse","Protective-serv","Wife","White","Female",0,0,40,"United-States","<=50K" +66,"Self-emp-not-inc",262552,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,7,"United-States","<=50K" +28,"Private",66434,"10th",6,"Never-married","Other-service","Unmarried","White","Female",0,0,15,"United-States","<=50K" +26,"Private",77661,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"?",230856,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +46,"Private",192835,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States","<=50K" +62,"?",181014,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Self-emp-not-inc",37918,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,60,"United-States","<=50K" +40,"Private",111020,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",244665,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"Honduras","<=50K" +52,"Private",312477,"HS-grad",9,"Widowed","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-not-inc",243493,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,12,"United-States","<=50K" +39,"State-gov",152023,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",170850,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,48,"United-States","<=50K" +33,"Private",137088,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",0,0,40,"Ecuador","<=50K" +17,"Private",340557,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +26,"Private",298225,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"Private",114150,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",194668,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,16,"United-States","<=50K" +46,"Federal-gov",330901,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",80165,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,20,"United-States","<=50K" +29,"Self-emp-not-inc",85572,"11th",7,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,5,"United-States","<=50K" +40,"Private",116632,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",139989,"Bachelors",13,"Never-married","Sales","Own-child","Black","Male",0,0,40,"United-States","<=50K" +56,"Private",75785,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",248612,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +36,"Private",28572,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Self-emp-not-inc",31143,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +37,"Private",216924,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,44,"United-States",">50K" +36,"Private",549174,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Self-emp-not-inc",111296,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"Mexico","<=50K" +25,"Private",208881,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +36,"State-gov",243666,"HS-grad",9,"Divorced","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",327164,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"?","<=50K" +35,"Private",257416,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +33,"Private",215288,"11th",7,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +31,"Private",58582,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,46,"United-States","<=50K" +49,"Private",199378,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,22,"United-States","<=50K" +34,"Self-emp-not-inc",114185,"Bachelors",13,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,50,"?","<=50K" +40,"Private",137421,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Asian-Pac-Islander","Male",0,0,60,"Trinadad&Tobago","<=50K" +27,"Private",216481,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",196504,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,23,"United-States","<=50K" +38,"Private",357870,"12th",8,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",0,0,50,"United-States","<=50K" +55,"State-gov",256335,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",168191,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,70,"Italy","<=50K" +40,"Private",215596,"Bachelors",13,"Married-spouse-absent","Other-service","Not-in-family","Other","Male",0,0,40,"Mexico","<=50K" +42,"Private",184682,"Assoc-voc",11,"Divorced","Tech-support","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +51,"Private",171914,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",288229,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,50,"Laos","<=50K" +30,"State-gov",144064,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +70,"?",54849,"Doctorate",16,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States",">50K" +40,"Private",141583,"10th",6,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",180985,"Bachelors",13,"Separated","Craft-repair","Unmarried","White","Male",0,0,35,"United-States","<=50K" +24,"Private",148709,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"?",174626,"7th-8th",4,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",184801,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +52,"Private",89054,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",147284,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Private",169973,"Assoc-voc",11,"Separated","Protective-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",222993,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",41099,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +31,"Private",33117,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +29,"Private",162551,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","Asian-Pac-Islander","Female",0,0,40,"Hong",">50K" +61,"?",42938,"Bachelors",13,"Never-married","?","Not-in-family","White","Male",0,0,7,"United-States",">50K" +46,"Private",389843,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"Germany",">50K" +37,"Private",138940,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Federal-gov",141877,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",172722,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Self-emp-not-inc",118523,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",227886,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +36,"Private",80743,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Asian-Pac-Islander","Female",0,0,40,"South","<=50K" +52,"Private",199688,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States","<=50K" +40,"Private",225823,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +21,"Private",176486,"HS-grad",9,"Married-spouse-absent","Exec-managerial","Other-relative","White","Female",0,0,60,"United-States","<=50K" +63,"Private",175777,"10th",6,"Separated","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",295010,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",437825,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"Peru","<=50K" +50,"Private",270194,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +41,"Private",242089,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +39,"Self-emp-inc",117555,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +23,"Private",146499,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","White","Female",0,0,48,"United-States","<=50K" +17,"?",216595,"11th",7,"Never-married","?","Own-child","Black","Female",0,0,20,"United-States","<=50K" +26,"Private",373553,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,42,"United-States","<=50K" +23,"Private",60331,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +21,"State-gov",96483,"Some-college",10,"Never-married","Adm-clerical","Own-child","Asian-Pac-Islander","Female",0,0,12,"United-States","<=50K" +39,"Private",211154,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +37,"Local-gov",247750,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States","<=50K" +38,"Private",197113,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +20,"Private",293297,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +35,"Private",35330,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",61898,"11th",7,"Divorced","Other-service","Unmarried","White","Female",0,0,15,"United-States","<=50K" +42,"Self-emp-inc",1097453,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +32,"Private",176992,"10th",6,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +27,"Private",295289,"Some-college",10,"Never-married","Other-service","Own-child","Black","Female",0,0,30,"United-States","<=50K" +53,"Self-emp-inc",298215,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Self-emp-not-inc",209934,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,25,"Mexico","<=50K" +26,"Private",164938,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",423222,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +23,"Private",124259,"Some-college",10,"Never-married","Protective-serv","Own-child","Black","Female",0,0,40,"United-States","<=50K" +70,"Self-emp-inc",232871,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"United-States","<=50K" +41,"State-gov",73199,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +43,"State-gov",27661,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +65,"Private",461715,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,25,"?","<=50K" +64,"Self-emp-not-inc",31826,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +40,"Private",279679,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +43,"Private",221172,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +50,"Federal-gov",222020,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,48,"United-States","<=50K" +19,"?",181265,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +32,"Private",204792,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",288568,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",182714,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"England","<=50K" +20,"Private",471452,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +45,"State-gov",264052,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",203027,"Assoc-acdm",12,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",218309,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +28,"Private",133625,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +35,"Private",45937,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"?",389850,"HS-grad",9,"Married-spouse-absent","?","Unmarried","Black","Male",0,0,50,"United-States","<=50K" +38,"Federal-gov",201617,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Local-gov",114733,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,35,"United-States","<=50K" +50,"State-gov",97778,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",149507,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +35,"Private",82622,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",48014,"Masters",14,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"France","<=50K" +61,"State-gov",162678,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",213842,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,38,"United-States","<=50K" +61,"Private",221447,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",426836,"5th-6th",3,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +31,"Local-gov",206609,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",50276,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +20,"Private",180497,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +35,"Private",220585,"12th",8,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",202752,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +18,"Private",170544,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +59,"Private",24384,"HS-grad",9,"Widowed","Priv-house-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",209067,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",65225,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +60,"Federal-gov",27466,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"England","<=50K" +49,"Federal-gov",179869,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Private",442131,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +61,"Private",243283,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Private",316627,"5th-6th",3,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +63,"Private",208862,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Federal-gov",38645,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",141272,"Bachelors",13,"Never-married","Other-service","Own-child","Black","Female",0,0,30,"United-States","<=50K" +41,"State-gov",29324,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +18,"?",348588,"12th",8,"Never-married","?","Own-child","Black","Male",0,0,25,"United-States","<=50K" +55,"Self-emp-not-inc",477867,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",267945,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +30,"Private",35724,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +29,"Private",187188,"Masters",14,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Male",0,0,60,"United-States","<=50K" +52,"Private",155983,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Federal-gov",414994,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",103474,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +43,"Private",211128,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +61,"Private",203445,"Some-college",10,"Widowed","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +51,"Private",178241,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States",">50K" +40,"Private",260761,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Mexico","<=50K" +41,"Local-gov",36924,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",292590,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +28,"Private",461929,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +59,"Private",189664,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"State-gov",190577,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Private",344200,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",337494,"Assoc-acdm",12,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +54,"Self-emp-not-inc",52634,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",170091,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +27,"?",189399,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",205072,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States","<=50K" +35,"Private",310290,"HS-grad",9,"Married-civ-spouse","Transport-moving","Wife","Black","Female",0,0,40,"United-States","<=50K" +27,"Private",134048,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +40,"Private",91959,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,46,"United-States",">50K" +34,"Private",153942,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Local-gov",234096,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",185330,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Female",0,0,25,"United-States","<=50K" +28,"Private",163772,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Other","Male",0,0,40,"United-States","<=50K" +65,"Private",83800,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,27,"United-States","<=50K" +61,"Private",139391,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,16,"United-States","<=50K" +18,"Private",478380,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +45,"Private",262802,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +68,"?",152157,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +25,"Private",114483,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +48,"Private",118023,"Prof-school",15,"Divorced","Sales","Not-in-family","White","Male",0,0,13,"United-States","<=50K" +19,"Private",220101,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",219424,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,50,"United-States",">50K" +54,"Private",186117,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +47,"Self-emp-not-inc",479611,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +30,"Private",108386,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +67,"?",125926,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +35,"Private",177102,"HS-grad",9,"Divorced","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",190762,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,18,"United-States","<=50K" +61,"Private",180632,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",88019,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Male",0,0,32,"United-States","<=50K" +50,"Private",135339,"12th",8,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,40,"Cambodia",">50K" +32,"Private",100662,"9th",5,"Separated","Machine-op-inspct","Unmarried","White","Female",0,0,40,"Columbia","<=50K" +34,"Private",183557,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +36,"Private",160035,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",306790,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",269246,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",308334,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,19,"United-States","<=50K" +58,"Private",215190,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +27,"Private",419146,"5th-6th",3,"Never-married","Other-service","Not-in-family","White","Male",0,0,75,"Mexico","<=50K" +62,"Private",176839,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,38,"United-States","<=50K" +41,"Private",56795,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"England","<=50K" +28,"Private",201861,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +33,"Private",179509,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",291755,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +76,"Self-emp-not-inc",117169,"7th-8th",4,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +25,"?",100903,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,25,"United-States","<=50K" +34,"Private",159322,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +40,"Private",262872,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",187052,"11th",7,"Never-married","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +17,"Private",277583,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,15,"United-States","<=50K" +55,"Private",169071,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +51,"Local-gov",96190,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +26,"Private",61603,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","Other","Male",0,0,40,"Mexico","<=50K" +44,"Private",43711,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +65,"?",197883,"10th",6,"Married-civ-spouse","?","Husband","White","Male",0,0,70,"United-States","<=50K" +54,"Private",99434,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Self-emp-not-inc",177639,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",201723,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +26,"Private",222248,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +39,"Private",86143,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +46,"?",228620,"11th",7,"Widowed","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +34,"Private",346034,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"El-Salvador","<=50K" +59,"Private",87510,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",37932,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,50,"United-States","<=50K" +34,"Private",185063,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +51,"Private",159755,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +34,"Private",108837,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",110669,"Bachelors",13,"Separated","Prof-specialty","Unmarried","White","Female",0,0,50,"United-States","<=50K" +21,"?",220115,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +30,"Self-emp-not-inc",45427,"Assoc-voc",11,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,49,"United-States","<=50K" +38,"Private",154669,"HS-grad",9,"Separated","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +23,"Private",71864,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +34,"Private",173495,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +22,"Private",254293,"12th",8,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",111883,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +50,"Private",146429,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",472807,"1st-4th",2,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,52,"Mexico","<=50K" +23,"Private",184665,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +35,"Private",205852,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",83879,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",178564,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +46,"Self-emp-inc",168796,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +27,"Private",269444,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",47353,"10th",6,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-inc",29254,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States","<=50K" +33,"Private",155343,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +36,"Private",234271,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +30,"Private",257849,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +23,"Private",228230,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,47,"United-States","<=50K" +36,"Private",227615,"5th-6th",3,"Married-spouse-absent","Craft-repair","Other-relative","White","Male",0,0,32,"Mexico","<=50K" +29,"Private",406826,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +19,"Private",97261,"12th",8,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"?",232022,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +52,"Federal-gov",168539,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",515797,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",351381,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",161018,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +60,"Private",26721,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",164123,"11th",7,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",98418,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,20,"United-States","<=50K" +36,"Private",29814,"HS-grad",9,"Never-married","Transport-moving","Other-relative","White","Male",0,0,50,"United-States","<=50K" +25,"Private",254613,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"Cuba","<=50K" +49,"Private",207677,"7th-8th",4,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +25,"Self-emp-not-inc",217030,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +50,"Private",171199,"11th",7,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",198270,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +28,"?",131310,"HS-grad",9,"Separated","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",79923,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"United-States","<=50K" +40,"Self-emp-inc",475322,"Bachelors",13,"Separated","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +56,"Private",134286,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +56,"Self-emp-not-inc",73746,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",125525,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,42,"United-States","<=50K" +38,"?",155676,"HS-grad",9,"Divorced","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +21,"Private",304949,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,10,"United-States","<=50K" +67,"Private",150516,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,24,"United-States","<=50K" +54,"State-gov",249096,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",164127,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +59,"Private",304779,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",157043,"11th",7,"Widowed","Handlers-cleaners","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +30,"Private",396538,"HS-grad",9,"Separated","Exec-managerial","Unmarried","White","Female",0,0,29,"United-States","<=50K" +42,"Private",510072,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +64,"?",200017,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +61,"?",60641,"Bachelors",13,"Never-married","?","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +26,"Private",89326,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +78,"Self-emp-not-inc",82815,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,3,"United-States",">50K" +24,"Self-emp-not-inc",117210,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +27,"Private",202206,"11th",7,"Separated","Farming-fishing","Other-relative","White","Male",0,0,40,"Puerto-Rico","<=50K" +51,"Private",123429,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +46,"Private",353512,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Self-emp-not-inc",26683,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +20,"Private",204641,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",225053,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"?",98776,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +19,"Private",263932,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +30,"Private",108247,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Self-emp-not-inc",369648,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States",">50K" +26,"Private",339324,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,96,"United-States","<=50K" +59,"?",145574,"Assoc-acdm",12,"Married-civ-spouse","?","Husband","White","Male",0,0,35,"United-States",">50K" +53,"Private",317313,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +24,"Local-gov",162919,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",186314,"Some-college",10,"Separated","Prof-specialty","Own-child","White","Male",0,0,54,"United-States","<=50K" +36,"Private",254202,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States","<=50K" +39,"Private",108140,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +53,"Private",287317,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","Black","Male",0,0,32,"United-States","<=50K" +75,"Self-emp-inc",81534,"HS-grad",9,"Widowed","Sales","Other-relative","Asian-Pac-Islander","Male",0,0,35,"United-States",">50K" +36,"Private",35945,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +46,"Self-emp-inc",204928,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",133625,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +60,"Private",71683,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,49,"United-States","<=50K" +58,"Private",570562,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +67,"Self-emp-not-inc",36876,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,55,"United-States","<=50K" +39,"Self-emp-not-inc",50096,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,80,"United-States","<=50K" +37,"Private",336880,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +54,"?",135840,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States","<=50K" +63,"Self-emp-not-inc",168048,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States","<=50K" +47,"Private",187969,"11th",7,"Divorced","Other-service","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +23,"Private",117363,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +49,"Private",304416,"11th",7,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +23,"Private",229826,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",159796,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,12,"United-States","<=50K" +44,"Private",165346,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",25386,"Assoc-voc",11,"Never-married","Other-service","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +35,"Private",491000,"Assoc-voc",11,"Divorced","Prof-specialty","Own-child","Black","Male",0,0,40,"United-States","<=50K" +23,"Local-gov",247731,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"Cuba","<=50K" +48,"Private",180532,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",419134,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",170166,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,25,"United-States","<=50K" +33,"Self-emp-not-inc",173495,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +18,"Private",423024,"12th",8,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +32,"Local-gov",19302,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,56,"England",">50K" +24,"State-gov",257621,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +27,"Private",259840,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +39,"Private",115289,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"France",">50K" +26,"Local-gov",159662,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",379798,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +41,"State-gov",36999,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,75,"United-States",">50K" +73,"?",131982,"Bachelors",13,"Married-civ-spouse","?","Husband","Asian-Pac-Islander","Male",0,0,5,"Vietnam","<=50K" +32,"Self-emp-inc",124052,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +56,"Local-gov",273084,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +44,"Private",96249,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +23,"Private",117767,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",79827,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +38,"Private",103925,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +68,"Private",161744,"10th",6,"Married-civ-spouse","Sales","Husband","White","Male",0,0,16,"United-States","<=50K" +42,"Self-emp-not-inc",196514,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"?",61985,"9th",5,"Separated","?","Not-in-family","Amer-Indian-Eskimo","Female",0,0,20,"United-States","<=50K" +19,"Private",157605,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",137367,"11th",7,"Married-spouse-absent","Handlers-cleaners","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +32,"Private",74883,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +44,"Local-gov",144778,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",177787,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,30,"England","<=50K" +30,"?",103651,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,35,"United-States","<=50K" +44,"Private",162108,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +24,"Private",217602,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +34,"Private",473133,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +17,"Private",113301,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,12,"?","<=50K" +61,"Private",80896,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,45,"India",">50K" +30,"Local-gov",168387,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",38950,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",107801,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +49,"Private",191277,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",205359,"Assoc-acdm",12,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +39,"?",240226,"HS-grad",9,"Married-civ-spouse","?","Husband","Black","Male",0,0,40,"United-States","<=50K" +34,"Private",203357,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +52,"Local-gov",153064,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",202959,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",105150,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +19,"Private",238474,"11th",7,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",1085515,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +25,"Private",82560,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Male",0,0,43,"United-States","<=50K" +71,"Private",55965,"7th-8th",4,"Widowed","Transport-moving","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +27,"Private",161087,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",261278,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +18,"Private",138917,"11th",7,"Never-married","Sales","Own-child","Black","Female",0,0,10,"United-States","<=50K" +49,"Private",200198,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",205359,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,25,"United-States","<=50K" +57,"Private",250201,"HS-grad",9,"Widowed","Transport-moving","Unmarried","White","Male",0,0,50,"United-States","<=50K" +56,"Federal-gov",67153,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Portugal",">50K" +17,"Private",244523,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +30,"Private",236599,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Private",108713,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",177147,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +61,"Private",129246,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +50,"?",222381,"Some-college",10,"Divorced","?","Unmarried","White","Male",0,0,40,"United-States","<=50K" +24,"Private",145111,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +44,"Private",62258,"11th",7,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"State-gov",108293,"Masters",14,"Never-married","Prof-specialty","Other-relative","White","Female",0,0,40,"United-States","<=50K" +61,"?",167284,"7th-8th",4,"Widowed","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +25,"Private",97789,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,50,"United-States","<=50K" +34,"Private",111415,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States","<=50K" +38,"Private",374524,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",287244,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +17,"?",341395,"10th",6,"Never-married","?","Own-child","Black","Male",0,0,20,"United-States","<=50K" +48,"Private",278039,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",98360,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",317032,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +41,"Self-emp-not-inc",240900,"HS-grad",9,"Divorced","Farming-fishing","Other-relative","White","Male",0,0,20,"United-States","<=50K" +45,"Private",32896,"5th-6th",3,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,35,"United-States","<=50K" +49,"Private",97411,"7th-8th",4,"Never-married","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Male",0,0,45,"Laos","<=50K" +19,"Private",72355,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +39,"Private",342448,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +42,"Private",303388,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States","<=50K" +17,"Private",112291,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,12,"United-States","<=50K" +30,"Private",208668,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,25,"United-States","<=50K" +61,"Local-gov",28375,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +60,"?",88675,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",47857,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",372500,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"Mexico","<=50K" +24,"Private",190968,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +41,"Private",37997,"12th",8,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,84,"United-States",">50K" +42,"Private",257328,"HS-grad",9,"Widowed","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +34,"Private",127610,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,15,"United-States","<=50K" +22,"?",139324,"9th",5,"Never-married","?","Unmarried","Black","Female",0,0,36,"United-States","<=50K" +47,"Private",164423,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,43,"United-States","<=50K" +30,"Private",56121,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",296212,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +31,"Private",157640,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +44,"Private",222504,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,45,"United-States",">50K" +34,"Private",116910,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +31,"Private",132601,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +68,"Private",185537,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +22,"Private",500720,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"Mexico","<=50K" +42,"Private",182108,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +37,"Private",231491,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +36,"Self-emp-not-inc",239415,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +38,"Private",179262,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,30,"United-States","<=50K" +72,"Without-pay",121004,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,55,"United-States","<=50K" +40,"Private",252392,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +19,"Private",163578,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +55,"Private",143266,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"Hungary",">50K" +30,"Private",285902,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",174540,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,4,"United-States","<=50K" +29,"Private",188729,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +24,"Private",72143,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +46,"Self-emp-not-inc",328216,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +44,"Private",165815,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +17,"Private",317702,"10th",6,"Never-married","Sales","Own-child","Black","Female",0,0,15,"United-States","<=50K" +35,"Private",215323,"Assoc-voc",11,"Divorced","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +38,"Private",192939,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +36,"Private",156352,"9th",5,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",155066,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"United-States","<=50K" +38,"Self-emp-not-inc",152621,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,99,"United-States","<=50K" +19,"Private",298891,"11th",7,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"Honduras","<=50K" +30,"Private",193298,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +36,"Local-gov",150309,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +27,"Private",384308,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +27,"Private",305647,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +66,"?",182378,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,30,"United-States","<=50K" +37,"Private",421633,"Masters",14,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States",">50K" +17,"Private",57723,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,30,"United-States","<=50K" +19,"?",307837,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +57,"Private",103540,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,50,"United-States","<=50K" +54,"Self-emp-not-inc",136224,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +21,"Private",231573,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",242804,"HS-grad",9,"Separated","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",163671,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",287701,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,48,"United-States",">50K" +41,"Private",222504,"Prof-school",15,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,38,"United-States","<=50K" +20,"Private",41356,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",59335,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Other-relative","White","Female",0,0,15,"United-States","<=50K" +62,"Private",84756,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"United-States","<=50K" +41,"Private",407425,"12th",8,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +37,"Private",162424,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +53,"Self-emp-not-inc",175456,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +28,"Private",52603,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",250630,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +46,"Self-emp-not-inc",233974,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +28,"Private",376302,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +50,"Private",195638,"10th",6,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",225775,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"Mexico","<=50K" +84,"Private",388384,"7th-8th",4,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,10,"United-States","<=50K" +48,"Self-emp-not-inc",219021,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +61,"Self-emp-not-inc",168654,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,20,"United-States","<=50K" +44,"Private",180609,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +32,"Private",114746,"HS-grad",9,"Separated","Handlers-cleaners","Unmarried","Asian-Pac-Islander","Female",0,0,60,"South","<=50K" +25,"Private",178037,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,35,"United-States","<=50K" +47,"State-gov",160045,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",268524,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +37,"Private",174844,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,17,"United-States","<=50K" +28,"Private",82488,"HS-grad",9,"Divorced","Tech-support","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +34,"Private",221167,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +32,"Self-emp-not-inc",48014,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +24,"Private",217226,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +22,"?",177902,"Some-college",10,"Never-married","?","Not-in-family","Asian-Pac-Islander","Female",0,0,25,"United-States","<=50K" +30,"Private",39386,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,99,"United-States","<=50K" +56,"Private",37394,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",115426,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",114158,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,26,"United-States","<=50K" +28,"Private",360527,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +39,"Private",225544,"12th",8,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",108438,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",230315,"Some-college",10,"Never-married","Other-service","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Dominican-Republic","<=50K" +32,"Private",158002,"Some-college",10,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,55,"Ecuador","<=50K" +37,"Private",179468,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +71,"Private",99894,"5th-6th",3,"Widowed","Priv-house-serv","Not-in-family","Asian-Pac-Islander","Female",0,0,75,"United-States","<=50K" +30,"Private",270889,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",42279,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",274913,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,45,"United-States","<=50K" +26,"Private",68001,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",27162,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,16,"United-States","<=50K" +37,"Self-emp-not-inc",286146,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +36,"Local-gov",95462,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",50103,"HS-grad",9,"Never-married","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Self-emp-inc",189679,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +29,"Private",115064,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"State-gov",215443,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,38,"United-States","<=50K" +32,"Private",174789,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,50,"United-States","<=50K" +24,"Private",91999,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +59,"Federal-gov",100931,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Self-emp-not-inc",119069,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Self-emp-not-inc",277488,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,84,"United-States","<=50K" +35,"Private",265662,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",227594,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +61,"?",175032,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",133569,"1st-4th",2,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +20,"Local-gov",308654,"Some-college",10,"Never-married","Protective-serv","Own-child","Asian-Pac-Islander","Female",0,0,20,"United-States","<=50K" +36,"Private",156084,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Federal-gov",380127,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",210781,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",258675,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",223367,"11th",7,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +42,"?",204817,"9th",5,"Never-married","?","Own-child","Black","Male",0,0,35,"United-States","<=50K" +23,"Private",409230,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +46,"Federal-gov",308077,"Prof-school",15,"Separated","Prof-specialty","Unmarried","White","Female",0,0,40,"Germany",">50K" +60,"Private",159049,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,70,"Germany",">50K" +40,"Private",353142,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +55,"Private",143030,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",30912,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,43,"United-States","<=50K" +55,"Private",125000,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +47,"Private",181363,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Private",338620,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,52,"United-States",">50K" +32,"Private",115989,"11th",7,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,60,"United-States","<=50K" +38,"Private",111128,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +61,"Self-emp-not-inc",201273,"Some-college",10,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +62,"Self-emp-inc",137354,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +26,"Private",192208,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","Black","Female",0,0,32,"United-States","<=50K" +19,"Private",220001,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,50,"United-States","<=50K" +40,"Private",352612,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",119751,"Masters",14,"Never-married","Prof-specialty","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Thailand","<=50K" +43,"Self-emp-not-inc",99220,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",111275,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Federal-gov",261241,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Private",261725,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +36,"Private",182013,"Some-college",10,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Private",40666,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Private",216461,"Some-college",10,"Divorced","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +60,"Private",320376,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +35,"Private",282951,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +36,"State-gov",166697,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +51,"Private",290856,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",455361,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"Guatemala","<=50K" +51,"Private",82783,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",109959,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,25,"United-States","<=50K" +50,"Private",177927,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",192337,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",236272,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +26,"Private",33610,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",209483,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,47,"United-States","<=50K" +26,"Private",247006,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,52,"United-States","<=50K" +30,"Local-gov",311913,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +39,"?",204756,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +33,"Local-gov",300681,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +42,"State-gov",24264,"Some-college",10,"Divorced","Transport-moving","Unmarried","White","Male",0,0,38,"United-States","<=50K" +28,"Private",266070,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +20,"Private",226978,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +31,"Private",341672,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,50,"India","<=50K" +36,"Private",179488,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Male",0,0,40,"Canada","<=50K" +39,"Federal-gov",243872,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +52,"Private",259583,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",219863,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",206947,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +21,"Private",245572,"9th",5,"Never-married","Other-service","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +25,"Private",38488,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +24,"Private",182504,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +38,"Private",193815,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"Italy","<=50K" +51,"?",521665,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,24,"United-States","<=50K" +45,"Private",60267,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +59,"Private",264357,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +41,"Private",191814,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",107882,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +43,"Private",174575,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +17,"Private",143331,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +42,"Private",198619,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",257780,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",183355,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",148429,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",71221,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,60,"United-States","<=50K" +21,"Self-emp-not-inc",236769,"7th-8th",4,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",32146,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"?",188877,"9th",5,"Divorced","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",306747,"Bachelors",13,"Divorced","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +21,"State-gov",478457,"Some-college",10,"Never-married","Other-service","Own-child","Black","Female",0,0,12,"United-States","<=50K" +25,"Private",248990,"5th-6th",3,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +51,"Self-emp-inc",46281,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +35,"Private",148015,"Bachelors",13,"Never-married","Sales","Own-child","Black","Female",0,0,40,"United-States","<=50K" +19,"Private",278115,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,12,"United-States","<=50K" +34,"Private",176673,"Some-college",10,"Never-married","Sales","Other-relative","Black","Female",0,0,35,"United-States","<=50K" +33,"?",202366,"HS-grad",9,"Divorced","?","Unmarried","White","Female",0,0,32,"United-States","<=50K" +36,"Private",238415,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",37939,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +60,"Self-emp-not-inc",35649,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Federal-gov",204900,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,40,"United-States","<=50K" +42,"Private",20809,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,75,"United-States",">50K" +34,"Private",148207,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +21,"Private",200153,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,32,"United-States","<=50K" +30,"Private",169496,"Masters",14,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,15,"United-States",">50K" +53,"Private",22978,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +34,"Private",366898,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Germany","<=50K" +37,"Private",324947,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",321577,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",241360,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",207564,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +33,"Private",220860,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +41,"Local-gov",336571,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"State-gov",56402,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States","<=50K" +65,"Private",180280,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +30,"Private",81282,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Local-gov",27051,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Private",100800,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +62,"Private",155094,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,45,"United-States",">50K" +50,"Private",548361,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,20,"United-States",">50K" +33,"Private",173858,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Other-relative","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +27,"Private",347153,"Some-college",10,"Never-married","Transport-moving","Other-relative","White","Male",0,0,40,"United-States","<=50K" +35,"Private",197719,"Some-college",10,"Never-married","Machine-op-inspct","Other-relative","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +55,"Private",197114,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,6,"United-States",">50K" +56,"Private",182062,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,48,"United-States",">50K" +21,"Private",184543,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +66,"Private",175558,"7th-8th",4,"Widowed","Other-service","Not-in-family","White","Female",0,0,20,"Germany","<=50K" +46,"Private",122026,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +23,"Private",340543,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +43,"Private",101950,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +40,"Private",179508,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,55,"United-States","<=50K" +52,"Private",225317,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +59,"Local-gov",53304,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Local-gov",282602,"Assoc-voc",11,"Separated","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",184016,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",250165,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",196467,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +59,"?",220783,"10th",6,"Widowed","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",178780,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +62,"Private",65868,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +54,"Private",35459,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",98986,"7th-8th",4,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,30,"United-States","<=50K" +36,"Private",282092,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",140764,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,45,"United-States","<=50K" +30,"Private",33124,"HS-grad",9,"Separated","Farming-fishing","Unmarried","White","Female",0,0,14,"United-States","<=50K" +46,"Private",90042,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",102986,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Wife","Asian-Pac-Islander","Female",0,0,40,"Laos",">50K" +21,"Private",214387,"Some-college",10,"Never-married","Sales","Other-relative","White","Male",0,0,64,"United-States","<=50K" +39,"Private",180667,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Private",278329,"HS-grad",9,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +23,"Private",140462,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Private",202565,"1st-4th",2,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Italy","<=50K" +62,"?",181063,"10th",6,"Widowed","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +28,"Private",287268,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +28,"Private",215955,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",82552,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",41745,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Private",73587,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,35,"United-States","<=50K" +54,"Private",263925,"1st-4th",2,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +19,"Private",196119,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +27,"Private",284741,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +30,"Private",293936,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,50,"?","<=50K" +35,"Private",340428,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +66,"?",175891,"9th",5,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Local-gov",276973,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,20,"United-States","<=50K" +30,"Private",161599,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",144064,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",236391,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",224943,"Assoc-voc",11,"Never-married","Sales","Other-relative","Black","Male",0,0,65,"United-States","<=50K" +44,"Private",151294,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +52,"Private",68982,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +30,"Private",241885,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",189461,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +19,"Self-emp-not-inc",36012,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +33,"Private",85355,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +20,"Private",157595,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"Private",197286,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",362747,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Female",0,0,35,"United-States","<=50K" +24,"Private",395297,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +31,"Self-emp-not-inc",144949,"Bachelors",13,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +20,"?",163665,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +32,"Private",141490,"Assoc-voc",11,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States","<=50K" +29,"Private",147889,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States","<=50K" +61,"Private",232808,"10th",6,"Divorced","Other-service","Not-in-family","White","Male",0,0,24,"United-States","<=50K" +48,"Private",70668,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,50,"United-States","<=50K" +29,"Federal-gov",33315,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +61,"?",63526,"12th",8,"Never-married","?","Not-in-family","Black","Male",0,0,52,"United-States","<=50K" +34,"Private",591711,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,48,"?","<=50K" +22,"Private",200318,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +38,"Private",109231,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",102889,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +26,"Private",167106,"HS-grad",9,"Never-married","Craft-repair","Other-relative","Asian-Pac-Islander","Male",0,0,40,"Hong","<=50K" +62,"Private",197918,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",67386,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +50,"Private",126592,"HS-grad",9,"Separated","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",119929,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Private",158199,"1st-4th",2,"Widowed","Machine-op-inspct","Unmarried","White","Female",0,0,44,"Portugal","<=50K" +35,"Private",341102,"9th",5,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +55,"Private",101524,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",202872,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +25,"Private",195201,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Other","Male",0,0,50,"United-States","<=50K" +51,"Private",128272,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Local-gov",102628,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",171114,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +46,"Private",216414,"Assoc-voc",11,"Married-spouse-absent","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +24,"Private",127753,"12th",8,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +19,"Private",282698,"7th-8th",4,"Never-married","Adm-clerical","Own-child","White","Male",0,0,80,"United-States","<=50K" +36,"Local-gov",312785,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Male",0,0,35,"United-States","<=50K" +18,"Private",92864,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +46,"Local-gov",175428,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",104223,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +29,"Private",144784,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +65,"Private",178934,"HS-grad",9,"Widowed","Other-service","Unmarried","Black","Female",0,0,20,"Jamaica","<=50K" +41,"Private",211253,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +34,"Private",133122,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",103540,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +39,"State-gov",172700,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +21,"Private",282484,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Private",323055,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +33,"State-gov",291494,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +28,"Private",214702,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +32,"Private",226696,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States",">50K" +31,"Private",216827,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +48,"Private",307440,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,0,45,"Philippines",">50K" +27,"Private",278122,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",122195,"HS-grad",9,"Widowed","Craft-repair","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-not-inc",156890,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +17,"Private",36877,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,10,"United-States","<=50K" +25,"Private",131178,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,23,"United-States","<=50K" +34,"Self-emp-inc",62396,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,62,"United-States",">50K" +33,"Private",73054,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +21,"Private",96844,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +22,"Private",324922,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +61,"Private",130684,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,42,"United-States","<=50K" +40,"Private",178983,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,30,"United-States",">50K" +58,"Private",81038,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,12,"United-States","<=50K" +30,"Private",151967,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,58,"United-States","<=50K" +24,"Private",278107,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,60,"United-States","<=50K" +52,"Self-emp-not-inc",183146,"12th",8,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +50,"Private",183638,"HS-grad",9,"Widowed","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Private",247892,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,30,"United-States","<=50K" +22,"Private",221480,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +32,"Private",118551,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"?",">50K" +21,"Private",518530,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",193787,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,50,"United-States","<=50K" +34,"Self-emp-inc",157466,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +48,"Private",141511,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +61,"?",158712,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,99,"United-States","<=50K" +21,"Private",252253,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +20,"Private",200450,"7th-8th",4,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,52,"United-States","<=50K" +30,"State-gov",343789,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +44,"Private",291566,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,60,"United-States","<=50K" +29,"Private",151382,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +31,"Private",221167,"Prof-school",15,"Divorced","Tech-support","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +35,"Private",196178,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",302422,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",37379,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +37,"Self-emp-not-inc",82540,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,70,"United-States",">50K" +33,"Self-emp-not-inc",182926,"Bachelors",13,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"?","<=50K" +44,"Private",159911,"7th-8th",4,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,55,"United-States","<=50K" +34,"Private",212781,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Local-gov",207213,"Assoc-acdm",12,"Never-married","Craft-repair","Own-child","White","Male",0,0,5,"United-States","<=50K" +30,"Private",200192,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,45,"United-States","<=50K" +41,"Local-gov",180096,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States","<=50K" +23,"Private",192812,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",105908,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,70,"United-States","<=50K" +26,"State-gov",234190,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +32,"Private",260868,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States",">50K" +26,"Private",109097,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,48,"United-States","<=50K" +49,"Private",209146,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",172281,"Masters",14,"Divorced","Tech-support","Not-in-family","White","Male",0,0,40,"United-States",">50K" +36,"Private",73023,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +41,"Private",122626,"HS-grad",9,"Divorced","Handlers-cleaners","Unmarried","White","Male",0,0,48,"United-States","<=50K" +27,"Private",113635,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +21,"?",191806,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,75,"United-States","<=50K" +56,"?",35723,"HS-grad",9,"Divorced","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Self-emp-not-inc",30759,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +46,"Private",105327,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"?",376058,"9th",5,"Never-married","?","Own-child","White","Female",0,0,45,"United-States","<=50K" +43,"Private",219307,"9th",5,"Divorced","Transport-moving","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +46,"Private",208067,"HS-grad",9,"Divorced","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",78631,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Amer-Indian-Eskimo","Male",0,0,60,"United-States","<=50K" +19,"Private",210308,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +31,"Private",594187,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",228476,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +21,"Private",126613,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",30267,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +23,"Private",216811,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,16,"United-States","<=50K" +62,"Local-gov",115763,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +31,"Local-gov",199368,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,50,"United-States",">50K" +39,"Self-emp-not-inc",188335,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",417668,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,30,"United-States","<=50K" +38,"Private",296317,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +36,"Private",164898,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",452406,"11th",7,"Never-married","Sales","Own-child","Black","Female",0,0,15,"United-States","<=50K" +27,"Private",42696,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",262994,"Some-college",10,"Divorced","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +43,"State-gov",167298,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +51,"Private",103529,"11th",7,"Divorced","Other-service","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +34,"Private",199539,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +19,"?",39460,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,60,"United-States","<=50K" +79,"Federal-gov",62176,"Doctorate",16,"Widowed","Exec-managerial","Not-in-family","White","Male",0,0,6,"United-States",">50K" +28,"State-gov",239130,"Some-college",10,"Divorced","Other-service","Unmarried","White","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-inc",151089,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +21,"Private",331611,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +31,"Self-emp-not-inc",203463,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",151518,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +23,"Self-emp-inc",39844,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +32,"Private",299635,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"Germany","<=50K" +67,"Private",123393,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",209538,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +35,"Self-emp-not-inc",238802,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",499197,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",200220,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",114059,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +18,"Private",434430,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +22,"Private",225156,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"?",133359,"Bachelors",13,"Married-spouse-absent","?","Not-in-family","White","Male",0,0,50,"?","<=50K" +28,"Private",226891,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,30,"?","<=50K" +25,"Private",231714,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",178866,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,25,"United-States",">50K" +33,"Private",148261,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",217902,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Self-emp-not-inc",77207,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +32,"?",377017,"Assoc-acdm",12,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +64,"Self-emp-inc",80333,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Private",265086,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +55,"?",102058,"12th",8,"Widowed","?","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +20,"Private",333843,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +35,"Private",296478,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Local-gov",116662,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",142424,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Local-gov",200808,"12th",8,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"Puerto-Rico","<=50K" +29,"Private",119052,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",168981,"1st-4th",2,"Never-married","Sales","Own-child","White","Female",0,0,24,"United-States","<=50K" +44,"Private",151780,"Some-college",10,"Widowed","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +25,"Private",509866,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,78,"United-States","<=50K" +24,"State-gov",249385,"Bachelors",13,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,10,"United-States","<=50K" +53,"Private",250034,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,50,"United-States",">50K" +39,"Private",249720,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,60,"United-States","<=50K" +72,"Self-emp-not-inc",258761,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-inc",64048,"9th",5,"Never-married","Sales","Own-child","White","Female",0,0,44,"Portugal","<=50K" +25,"State-gov",153534,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",193815,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +27,"Private",255582,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",204527,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +29,"Self-emp-not-inc",229341,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States",">50K" +50,"Private",128143,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Private",175479,"5th-6th",3,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +18,"Private",301814,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +20,"Private",238917,"11th",7,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,32,"Mexico","<=50K" +32,"Private",205581,"Some-college",10,"Separated","Tech-support","Unmarried","White","Female",0,0,50,"United-States","<=50K" +45,"Private",340341,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +48,"Private",147860,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Wife","Black","Female",0,0,40,"United-States","<=50K" +20,"?",121023,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +23,"Private",259496,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +44,"Private",116358,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +47,"Self-emp-not-inc",180446,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","Black","Male",0,0,40,"United-States",">50K" +47,"Private",264244,"HS-grad",9,"Married-spouse-absent","Craft-repair","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +46,"Local-gov",197988,"1st-4th",2,"Never-married","Other-service","Not-in-family","Amer-Indian-Eskimo","Female",0,0,20,"United-States","<=50K" +19,"Private",206599,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Private",313146,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-inc",99212,"HS-grad",9,"Separated","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +37,"Private",340599,"11th",7,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",62932,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",44861,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",53893,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Local-gov",128401,"Doctorate",16,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",336951,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Private",54611,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",210313,"10th",6,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +19,"Private",181020,"11th",7,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,30,"United-States","<=50K" +19,"Private",256979,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,35,"United-States","<=50K" +64,"Private",47298,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +44,"Private",125461,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +21,"Private",209955,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +33,"Private",182246,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +63,"Private",76860,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +44,"?",91949,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +28,"Federal-gov",183445,"HS-grad",9,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,70,"Puerto-Rico","<=50K" +24,"Private",130741,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Federal-gov",191878,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,20,"United-States","<=50K" +21,"?",233923,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,24,"United-States","<=50K" +20,"Private",48121,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",304302,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +34,"Federal-gov",284703,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,52,"United-States","<=50K" +17,"Private",401198,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +35,"Private",243357,"11th",7,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +26,"Private",32276,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",110538,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +25,"Private",257310,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",411950,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Local-gov",392668,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Self-emp-not-inc",52498,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,50,"United-States","<=50K" +37,"Private",87076,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +58,"Private",224854,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",193379,"Assoc-acdm",12,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +54,"Private",98436,"Masters",14,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"?",116632,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,60,"United-States","<=50K" +44,"Private",90688,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Female",0,0,45,"Laos","<=50K" +61,"Private",229744,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +29,"Private",59732,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +34,"Private",192900,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +24,"State-gov",90046,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"Canada","<=50K" +40,"Private",272960,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,42,"United-States",">50K" +42,"Self-emp-inc",152071,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"Cuba",">50K" +50,"Private",301583,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",315984,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",241962,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",131591,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,45,"United-States","<=50K" +70,"Self-emp-inc",207938,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,5,"United-States","<=50K" +51,"Private",53197,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",121023,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",287229,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +22,"Private",163911,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +31,"Private",191834,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",204734,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",220978,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"Private",365739,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",50103,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",283293,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +19,"Private",263338,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +36,"?",504871,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",348592,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,44,"United-States","<=50K" +28,"Private",173944,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",226135,"9th",5,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"Jamaica","<=50K" +32,"Private",172375,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +47,"Private",347025,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",191335,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,56,"United-States","<=50K" +21,"Private",247779,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,38,"United-States","<=50K" +25,"State-gov",262664,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",95855,"HS-grad",9,"Divorced","Protective-serv","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",74501,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +43,"Private",245317,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +56,"Private",200316,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"United-States","<=50K" +35,"Private",198341,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +59,"Private",100453,"7th-8th",4,"Separated","Other-service","Own-child","Black","Female",0,0,38,"United-States","<=50K" +47,"Private",235683,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",83237,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +64,"Private",88470,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",198801,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +53,"Private",168107,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",196193,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?","<=50K" +30,"?",205418,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"United-States","<=50K" +46,"Private",695411,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +45,"Self-emp-inc",139268,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Federal-gov",192771,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",180837,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",159548,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +34,"Private",110554,"HS-grad",9,"Divorced","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +38,"Private",103474,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +62,"Private",178249,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +21,"Private",138768,"Some-college",10,"Never-married","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +41,"Private",321824,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,8,"United-States","<=50K" +35,"Private",244803,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Peru","<=50K" +62,"Local-gov",206063,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +53,"Private",167651,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +69,"State-gov",163689,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,16,"United-States","<=50K" +19,"Self-emp-not-inc",45546,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,16,"United-States","<=50K" +47,"Private",420986,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Self-emp-inc",68015,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,90,"United-States",">50K" +54,"Private",175594,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"?",148673,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,10,"United-States","<=50K" +30,"Private",206322,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,73,"United-States",">50K" +39,"Private",272338,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,25,"United-States","<=50K" +64,"Private",312498,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",177675,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",152810,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",319122,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",212304,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +39,"Private",240841,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +49,"Private",208978,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,16,"United-States","<=50K" +28,"Private",198197,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,55,"United-States",">50K" +40,"Private",72791,"Some-college",10,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +24,"Private",275395,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"?",195767,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +50,"Private",462966,"10th",6,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,8,"El-Salvador","<=50K" +24,"?",265434,"Bachelors",13,"Never-married","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",31269,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Local-gov",246291,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,46,"United-States","<=50K" +54,"Federal-gov",128378,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Local-gov",231180,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +31,"Local-gov",206297,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Self-emp-inc",337050,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",193075,"HS-grad",9,"Divorced","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +35,"Private",35945,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +20,"?",141453,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,10,"United-States","<=50K" +36,"Private",252231,"Preschool",1,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"Puerto-Rico","<=50K" +30,"Private",128016,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +39,"Private",150057,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +25,"Private",258276,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +40,"Private",188465,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +25,"Self-emp-inc",161007,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",403468,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"Mexico","<=50K" +53,"Federal-gov",181677,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",120243,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,10,"United-States","<=50K" +41,"Private",157025,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",306908,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +66,"Self-emp-not-inc",28061,"7th-8th",4,"Widowed","Farming-fishing","Unmarried","White","Male",0,0,50,"United-States","<=50K" +27,"Private",135001,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",293398,"HS-grad",9,"Separated","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",185106,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",245790,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +26,"Private",134004,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +26,"Private",205036,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +26,"Private",244495,"9th",5,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +38,"Private",159179,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",405155,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +32,"Federal-gov",402361,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",184553,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Private",302626,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",99138,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +39,"Private",112731,"HS-grad",9,"Divorced","Other-service","Not-in-family","Other","Female",0,0,40,"Dominican-Republic","<=50K" +18,"Private",761006,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +75,"?",125784,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +28,"Private",182344,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",117012,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +39,"Federal-gov",30673,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Federal-gov",484669,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"State-gov",314052,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +43,"State-gov",38537,"Some-college",10,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,38,"?","<=50K" +27,"Private",165412,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",116635,"Bachelors",13,"Separated","Prof-specialty","Unmarried","Black","Female",0,0,36,"United-States","<=50K" +20,"Private",185452,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +42,"Private",118686,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,20,"United-States","<=50K" +69,"Private",76939,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Federal-gov",160646,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,35,"United-States","<=50K" +49,"State-gov",126754,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Portugal","<=50K" +20,"Private",211049,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,30,"United-States","<=50K" +52,"Private",311931,"5th-6th",3,"Married-civ-spouse","Sales","Wife","White","Female",0,0,15,"El-Salvador","<=50K" +33,"Private",283602,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,59,"Mexico","<=50K" +18,"Private",155021,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,6,"United-States","<=50K" +55,"Self-emp-not-inc",100569,"HS-grad",9,"Separated","Farming-fishing","Unmarried","White","Female",0,0,55,"United-States","<=50K" +61,"Private",380462,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",114544,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States",">50K" +30,"Private",248584,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Private",227468,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",66173,"Assoc-acdm",12,"Married-civ-spouse","Sales","Wife","White","Female",0,0,15,"United-States","<=50K" +34,"Private",107624,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +38,"Private",423616,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,36,"United-States",">50K" +27,"Local-gov",216013,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",210926,"11th",7,"Separated","Handlers-cleaners","Unmarried","White","Female",0,0,40,"Nicaragua","<=50K" +60,"Local-gov",255711,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,60,"United-States",">50K" +23,"Private",77581,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",203263,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +25,"Private",261519,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +29,"Private",91189,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +90,"Federal-gov",195433,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"United-States","<=50K" +37,"Local-gov",272471,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",311524,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,38,"United-States","<=50K" +18,"Private",151386,"HS-grad",9,"Married-spouse-absent","Other-service","Own-child","Black","Male",0,0,40,"Jamaica","<=50K" +35,"Private",187625,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,65,"United-States","<=50K" +43,"Private",169383,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Self-emp-inc",191129,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,65,"United-States",">50K" +51,"Private",467611,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +31,"Private",373185,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,42,"Mexico","<=50K" +57,"Private",199934,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +71,"?",116165,"Some-college",10,"Widowed","?","Not-in-family","White","Female",0,0,14,"Canada","<=50K" +28,"Private",42881,"10th",6,"Divorced","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"?",174666,"10th",6,"Separated","?","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +25,"Private",169759,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,95,"United-States","<=50K" +49,"Self-emp-not-inc",181547,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,30,"Columbia","<=50K" +52,"Private",95704,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",237432,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"?","<=50K" +32,"Private",226267,"5th-6th",3,"Married-spouse-absent","Craft-repair","Other-relative","White","Male",0,0,40,"El-Salvador","<=50K" +31,"Private",159979,"Some-college",10,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Female",0,0,50,"United-States","<=50K" +30,"Private",203488,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +24,"Private",403671,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +45,"Private",192323,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,66,"Yugoslavia","<=50K" +30,"Private",167832,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"State-gov",155657,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,25,"United-States","<=50K" +49,"Private",116789,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",39234,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +25,"Private",124111,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"Private",172828,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,55,"Outlying-US(Guam-USVI-etc)","<=50K" +55,"Private",143372,"HS-grad",9,"Divorced","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +25,"State-gov",218184,"Bachelors",13,"Never-married","Protective-serv","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +32,"Private",154087,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Federal-gov",440647,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,40,"United-States","<=50K" +37,"Private",193952,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,0,40,"?","<=50K" +52,"Private",125932,"7th-8th",4,"Widowed","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",284652,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +21,"?",214635,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,24,"United-States","<=50K" +43,"Private",173316,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"State-gov",65390,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"?","<=50K" +40,"Self-emp-inc",45054,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Private",185042,"1st-4th",2,"Separated","Priv-house-serv","Other-relative","White","Female",0,0,40,"Mexico","<=50K" +35,"Private",117381,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",179668,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",127277,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Taiwan",">50K" +26,"Private",192022,"Bachelors",13,"Never-married","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",99551,"Bachelors",13,"Widowed","Sales","Unmarried","White","Female",0,0,15,"United-States","<=50K" +51,"Private",208899,"Bachelors",13,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +35,"Private",287658,"Assoc-acdm",12,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,30,"Jamaica","<=50K" +31,"Private",196125,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",275051,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,8,"United-States","<=50K" +38,"Private",23892,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +29,"Private",267989,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +39,"Private",30269,"Assoc-voc",11,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +42,"Private",204235,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +46,"Local-gov",209057,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +73,"Private",349347,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,25,"United-States","<=50K" +28,"Private",124680,"HS-grad",9,"Never-married","Sales","Unmarried","White","Female",0,0,70,"United-States","<=50K" +38,"Private",99233,"Prof-school",15,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +19,"Private",224849,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +60,"Local-gov",101110,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States",">50K" +24,"Private",184839,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Private",302847,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",181322,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +26,"Local-gov",192213,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"Canada","<=50K" +28,"State-gov",37250,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,16,"United-States","<=50K" +38,"Self-emp-inc",140854,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +47,"Private",158286,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +50,"Private",269095,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States",">50K" +27,"Private",279960,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",176239,"Some-college",10,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Private",337666,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +68,"?",255276,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,48,"United-States",">50K" +63,"Private",145212,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",185099,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,70,"United-States",">50K" +42,"Private",142756,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +28,"Private",156300,"Masters",14,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,45,"United-States","<=50K" +68,"?",186266,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,8,"United-States","<=50K" +38,"Private",219137,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,22,"United-States","<=50K" +49,"Private",203067,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Private",148844,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",154941,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",124111,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +59,"Private",157303,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +34,"Private",113838,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +34,"Private",165737,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,43,"India",">50K" +67,"Private",140849,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,24,"United-States","<=50K" +45,"Private",200363,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +64,"Private",180247,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +51,"Private",82578,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"Canada",">50K" +31,"Private",227146,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +42,"Self-emp-inc",348886,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +65,"Private",90907,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +23,"Private",142766,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +31,"Private",246439,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +33,"Private",184784,"10th",6,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Local-gov",195262,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +63,"Private",167967,"Masters",14,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,46,"United-States","<=50K" +48,"Private",145636,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"United-States",">50K" +45,"Local-gov",170099,"Assoc-acdm",12,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +17,"Private",228253,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,10,"United-States","<=50K" +26,"Local-gov",205570,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Federal-gov",506830,"Some-college",10,"Divorced","Tech-support","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",412435,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"Outlying-US(Guam-USVI-etc)","<=50K" +44,"Private",163331,"Some-college",10,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,32,"United-States","<=50K" +43,"Federal-gov",222756,"Masters",14,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"State-gov",318918,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",105188,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"Haiti","<=50K" +23,"Private",199884,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,45,"United-States","<=50K" +19,"Private",96483,"HS-grad",9,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",192203,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Canada","<=50K" +32,"Private",99646,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"?",210095,"5th-6th",3,"Never-married","?","Unmarried","White","Female",0,0,25,"El-Salvador","<=50K" +44,"Private",219591,"Some-college",10,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +63,"Private",30270,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",226020,"HS-grad",9,"Separated","Other-service","Not-in-family","Black","Female",0,0,60,"?","<=50K" +21,"Private",314165,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"Columbia","<=50K" +32,"Private",330715,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Self-emp-not-inc",35448,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,50,"United-States","<=50K" +50,"State-gov",172970,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +26,"Self-emp-inc",189502,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,80,"United-States",">50K" +35,"Private",61518,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States","<=50K" +31,"Private",574005,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States",">50K" +24,"Private",281356,"1st-4th",2,"Never-married","Farming-fishing","Not-in-family","Other","Male",0,0,66,"Mexico","<=50K" +40,"Private",138975,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,56,"United-States","<=50K" +31,"Private",176969,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +43,"Private",132393,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"Poland","<=50K" +44,"Private",194924,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States",">50K" +40,"Private",478205,"Bachelors",13,"Never-married","Prof-specialty","Other-relative","White","Female",0,0,40,"United-States","<=50K" +75,"?",128224,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States","<=50K" +51,"Self-emp-not-inc",290688,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"State-gov",85566,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Self-emp-not-inc",29036,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +33,"Private",348152,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Local-gov",73715,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States",">50K" +29,"Private",151382,"Assoc-voc",11,"Divorced","Handlers-cleaners","Unmarried","White","Male",0,0,50,"United-States","<=50K" +37,"Private",236359,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,37,"United-States","<=50K" +19,"Private",138760,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Local-gov",354962,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +46,"Private",181363,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",393360,"Some-college",10,"Never-married","Protective-serv","Own-child","Black","Male",0,0,30,"United-States","<=50K" +34,"Private",210736,"Some-college",10,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"?","<=50K" +38,"Private",110013,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,43,"United-States","<=50K" +26,"Private",193304,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",118551,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +57,"Private",201991,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",157446,"11th",7,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +26,"Local-gov",283217,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",247794,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,84,"United-States","<=50K" +61,"Private",35649,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,6,"United-States","<=50K" +36,"Self-emp-not-inc",342719,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"?",">50K" +17,"Private",271837,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,16,"United-States","<=50K" +40,"Private",400061,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Other","Male",0,0,40,"United-States",">50K" +18,"Private",62972,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +21,"Private",174907,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Female",0,0,32,"United-States","<=50K" +41,"Private",176452,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"Peru","<=50K" +46,"Private",268358,"11th",7,"Separated","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Federal-gov",176904,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",176683,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +39,"Private",98077,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,42,"United-States","<=50K" +36,"Private",266461,"HS-grad",9,"Never-married","Transport-moving","Own-child","Black","Male",0,0,48,"United-States","<=50K" +27,"Private",604045,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Local-gov",131568,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",97688,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,47,"United-States","<=50K" +23,"Private",373628,"Bachelors",13,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +41,"Self-emp-not-inc",193459,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +49,"Private",250733,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,46,"United-States","<=50K" +46,"Federal-gov",199725,"Assoc-voc",11,"Divorced","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Female",0,0,60,"United-States","<=50K" +54,"Private",156877,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Greece","<=50K" +45,"Self-emp-not-inc",216402,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,50,"India",">50K" +22,"Private",315974,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",63437,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"Ireland","<=50K" +27,"Private",160786,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +34,"Private",85374,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",465974,"11th",7,"Never-married","Transport-moving","Own-child","White","Male",0,0,30,"United-States","<=50K" +47,"Private",78529,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +36,"State-gov",98037,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +22,"Private",178390,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",64506,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +54,"Private",128378,"Some-college",10,"Widowed","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +24,"Private",234460,"9th",5,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,40,"Dominican-Republic","<=50K" +29,"Private",176760,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,55,"United-States","<=50K" +40,"State-gov",59460,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +18,"Private",234428,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +31,"Private",215047,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +32,"Private",191777,"Masters",14,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +48,"Private",148995,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",229773,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +24,"Private",174461,"Assoc-acdm",12,"Divorced","Other-service","Not-in-family","White","Female",0,0,22,"United-States","<=50K" +24,"Private",250647,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Guatemala","<=50K" +37,"Private",184556,"Some-college",10,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",263561,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +19,"Private",177945,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,25,"United-States","<=50K" +45,"Private",306889,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +54,"Local-gov",54377,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",95566,"Some-college",10,"Married-spouse-absent","Sales","Own-child","Other","Female",0,0,22,"Dominican-Republic","<=50K" +20,"Private",181675,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",172129,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"?",350759,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",105592,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +20,"?",200061,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"?","<=50K" +34,"Self-emp-inc",200689,"Bachelors",13,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Local-gov",282753,"Assoc-voc",11,"Divorced","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Private",137367,"11th",7,"Never-married","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +35,"Self-emp-inc",153976,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +51,"Self-emp-inc",96062,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +33,"Private",152933,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +71,"Private",97870,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,15,"Germany","<=50K" +48,"Private",254291,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Self-emp-not-inc",101432,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",125776,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +64,"Self-emp-not-inc",165479,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,5,"United-States","<=50K" +42,"Federal-gov",172307,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,48,"United-States",">50K" +25,"Private",176729,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +66,"Private",174276,"Some-college",10,"Widowed","Sales","Unmarried","White","Female",0,0,50,"United-States",">50K" +59,"Federal-gov",48102,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"?",">50K" +42,"Self-emp-not-inc",79531,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +24,"Private",306460,"HS-grad",9,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,40,"United-States","<=50K" +19,"Private",55284,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,25,"United-States","<=50K" +26,"Private",172063,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,24,"United-States","<=50K" +22,"Private",141028,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,30,"United-States","<=50K" +33,"Private",37274,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Private",31389,"11th",7,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,12,"United-States","<=50K" +20,"Private",415913,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +33,"Private",295591,"5th-6th",3,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +56,"Private",159770,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +70,"Self-emp-not-inc",268832,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,24,"United-States",">50K" +42,"Private",126003,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Local-gov",225193,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",297735,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",605502,"10th",6,"Never-married","Transport-moving","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +37,"Private",174150,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",165466,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,60,"United-States",">50K" +52,"State-gov",189728,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +49,"Private",360491,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",115040,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +70,"Self-emp-inc",158437,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States",">50K" +25,"Private",149875,"Bachelors",13,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +59,"Private",131916,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"Italy",">50K" +22,"Private",60668,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",153132,"Assoc-acdm",12,"Separated","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +62,"Private",155256,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +54,"Private",244770,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +38,"Private",312108,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +36,"Private",93225,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +74,"Self-emp-inc",231002,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"United-States",">50K" +35,"Self-emp-not-inc",256992,"5th-6th",3,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,15,"Mexico","<=50K" +41,"Private",118721,"12th",8,"Divorced","Adm-clerical","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +30,"Private",151989,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States","<=50K" +25,"Private",109112,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +48,"Private",204629,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +50,"Self-emp-not-inc",99894,"5th-6th",3,"Never-married","Tech-support","Not-in-family","Asian-Pac-Islander","Female",0,0,15,"United-States","<=50K" +19,"Private",369463,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +51,"Private",79324,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",61178,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +20,"Private",204226,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +17,"Private",183110,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,16,"United-States","<=50K" +42,"Private",96321,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Private",167031,"Some-college",10,"Never-married","Other-service","Other-relative","Other","Female",0,0,25,"Ecuador","<=50K" +36,"Private",108997,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +65,"Private",176796,"Doctorate",16,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",134737,"Bachelors",13,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,70,"United-States",">50K" +33,"Self-emp-inc",49795,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +32,"State-gov",131588,"Some-college",10,"Never-married","Tech-support","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +25,"Private",307643,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",351350,"Some-college",10,"Divorced","Protective-serv","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",260761,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",207789,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +24,"Private",196269,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","Other","Male",0,0,40,"United-States","<=50K" +17,"Private",46402,"7th-8th",4,"Never-married","Sales","Own-child","White","Male",0,0,8,"United-States","<=50K" +32,"Self-emp-not-inc",267161,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +67,"Private",160456,"11th",7,"Widowed","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"?",123983,"Some-college",10,"Never-married","?","Other-relative","Asian-Pac-Islander","Male",0,0,10,"Vietnam","<=50K" +39,"Private",269323,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Self-emp-not-inc",42857,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +50,"Self-emp-not-inc",183915,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Private",211391,"10th",6,"Never-married","Sales","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +21,"Local-gov",193130,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",86745,"Bachelors",13,"Never-married","Adm-clerical","Other-relative","Asian-Pac-Islander","Female",0,0,16,"United-States","<=50K" +34,"Private",226525,"Assoc-voc",11,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +68,"?",270339,"10th",6,"Married-civ-spouse","?","Husband","White","Male",0,0,35,"United-States","<=50K" +49,"Self-emp-not-inc",343742,"10th",6,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,32,"United-States","<=50K" +50,"Private",150975,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +33,"Private",207301,"Assoc-acdm",12,"Divorced","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +18,"Private",135924,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",184277,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,55,"United-States",">50K" +20,"Private",142233,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +64,"Local-gov",158412,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",126161,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +35,"Private",149347,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +21,"Private",322674,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,32,"United-States","<=50K" +29,"Private",55390,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +38,"State-gov",200904,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,30,"United-States",">50K" +45,"Private",166056,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",116666,"Masters",14,"Divorced","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,50,"India",">50K" +41,"Private",168324,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +37,"Private",121772,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Hong","<=50K" +20,"?",401690,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +45,"Self-emp-inc",117605,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +20,"Federal-gov",410446,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,20,"United-States","<=50K" +35,"Self-emp-not-inc",335704,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",70261,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +19,"Private",47577,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +23,"Private",117767,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +34,"Private",179641,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +23,"?",343553,"11th",7,"Never-married","?","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",328466,"5th-6th",3,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"Mexico",">50K" +46,"Private",265097,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,5,"United-States","<=50K" +38,"Local-gov",414791,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States",">50K" +55,"Local-gov",48055,"12th",8,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",341672,"Some-college",10,"Never-married","Adm-clerical","Other-relative","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +48,"Private",266764,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +35,"Private",233571,"HS-grad",9,"Divorced","Other-service","Own-child","White","Female",0,0,50,"United-States","<=50K" +47,"Private",70754,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",175856,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",193494,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,46,"United-States","<=50K" +41,"Private",104334,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +47,"Federal-gov",197332,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",205844,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,25,"United-States","<=50K" +45,"Local-gov",206459,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"United-States","<=50K" +33,"Private",202822,"7th-8th",4,"Never-married","Other-service","Unmarried","Black","Female",0,0,14,"Trinadad&Tobago","<=50K" +68,"Without-pay",174695,"Some-college",10,"Married-spouse-absent","Farming-fishing","Unmarried","White","Female",0,0,25,"United-States","<=50K" +44,"Private",183342,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +49,"Private",105614,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +45,"Private",329603,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Poland",">50K" +29,"Private",207473,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Mexico","<=50K" +46,"Private",149161,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,60,"?","<=50K" +19,"Private",311974,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,25,"Mexico","<=50K" +56,"Private",175127,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",111625,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +29,"Private",48895,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +21,"Private",27049,"HS-grad",9,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +38,"Private",108907,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"?","<=50K" +52,"Private",94988,"5th-6th",3,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +22,"Private",218343,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +20,"Private",227626,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,60,"United-States","<=50K" +31,"Private",272856,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,50,"England","<=50K" +39,"Private",30916,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",276229,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",289106,"Assoc-acdm",12,"Separated","Sales","Unmarried","White","Male",0,0,40,"United-States","<=50K" +67,"?",39100,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,5,"United-States","<=50K" +61,"Private",147280,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +18,"Private",187770,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +51,"State-gov",213296,"Bachelors",13,"Widowed","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",107410,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"?",170272,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,25,"United-States","<=50K" +32,"Private",86808,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,38,"United-States","<=50K" +48,"Private",149210,"HS-grad",9,"Separated","Craft-repair","Unmarried","Black","Male",0,0,45,"United-States","<=50K" +62,"Private",123411,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,53,"United-States","<=50K" +21,"?",306779,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +28,"Private",487347,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +20,"Private",375698,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +41,"Private",271753,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",251854,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +43,"State-gov",28451,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,37,"United-States",">50K" +20,"Private",282604,"Some-college",10,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,20,"United-States","<=50K" +29,"Private",185908,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,55,"United-States",">50K" +51,"Federal-gov",198186,"Bachelors",13,"Widowed","Prof-specialty","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +40,"Private",242521,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",337940,"5th-6th",3,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +30,"Private",212064,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",129263,"HS-grad",9,"Widowed","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",109912,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States",">50K" +41,"Private",113324,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",187795,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +20,"Private",173724,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +43,"Private",185129,"Bachelors",13,"Divorced","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",236040,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",74194,"HS-grad",9,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,40,"United-States","<=50K" +31,"Local-gov",102130,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +23,"Private",140915,"Some-college",10,"Never-married","Sales","Other-relative","Asian-Pac-Islander","Male",0,0,25,"Philippines","<=50K" +38,"State-gov",34364,"Masters",14,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",258037,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"Cuba",">50K" +18,"Private",391585,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Female",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",233130,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"Mexico","<=50K" +23,"?",32897,"Assoc-acdm",12,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +26,"Private",248612,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,30,"United-States","<=50K" +37,"Private",212465,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",405913,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Peru",">50K" +31,"Private",46807,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",210498,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,80,"United-States","<=50K" +35,"Private",206951,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Self-emp-not-inc",237466,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,30,"United-States",">50K" +59,"Private",279636,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,50,"Guatemala","<=50K" +42,"Private",29320,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",271262,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +27,"?",29361,"Assoc-acdm",12,"Never-married","?","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +32,"Private",76773,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",109004,"HS-grad",9,"Separated","Craft-repair","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +43,"Private",226902,"Bachelors",13,"Divorced","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +46,"Private",176552,"11th",7,"Divorced","Prof-specialty","Unmarried","Amer-Indian-Eskimo","Male",0,0,40,"United-States",">50K" +41,"Private",182303,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +20,"Private",218215,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +57,"Private",165695,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"?",">50K" +45,"Private",96100,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",248978,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +55,"?",200235,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States",">50K" +58,"Private",94429,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",87282,"Assoc-voc",11,"Never-married","Exec-managerial","Other-relative","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +29,"Private",119793,"Some-college",10,"Never-married","Sales","Other-relative","White","Male",0,0,50,"United-States","<=50K" +57,"?",85815,"HS-grad",9,"Divorced","?","Own-child","Asian-Pac-Islander","Male",0,0,20,"United-States","<=50K" +26,"Local-gov",197764,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",306982,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +61,"Private",80896,"HS-grad",9,"Separated","Transport-moving","Unmarried","Asian-Pac-Islander","Male",0,0,45,"United-States",">50K" +43,"Private",355728,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"State-gov",193720,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,56,"United-States",">50K" +23,"Private",347292,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",34506,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",326370,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,38,"?","<=50K" +22,"?",269221,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",63509,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +48,"Private",148254,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Wife","White","Female",0,0,16,"United-States",">50K" +33,"Private",190511,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +46,"Private",268022,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"?",">50K" +18,"Private",20057,"7th-8th",4,"Never-married","Other-service","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +52,"Private",206862,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",166320,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Private",289886,"Some-college",10,"Never-married","Other-service","Other-relative","Asian-Pac-Islander","Male",0,0,30,"Vietnam","<=50K" +23,"?",86337,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +45,"Local-gov",54190,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +17,"Private",147069,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,16,"United-States","<=50K" +56,"Private",282023,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Self-emp-inc",379485,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,45,"United-States","<=50K" +81,"Private",129338,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,10,"United-States","<=50K" +22,"Private",99829,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,30,"United-States","<=50K" +43,"State-gov",182254,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +66,"?",210750,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States","<=50K" +50,"Private",132716,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",242984,"Some-college",10,"Separated","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",101509,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"?",509629,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,35,"United-States","<=50K" +36,"Private",119957,"Bachelors",13,"Separated","Other-service","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +33,"Private",69727,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +37,"?",50862,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,55,"United-States","<=50K" +50,"Private",182907,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +55,"Private",206487,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",168015,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",149396,"Some-college",10,"Never-married","Other-service","Other-relative","Black","Female",0,0,30,"Haiti","<=50K" +39,"Federal-gov",184964,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States",">50K" +34,"Private",398988,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",128777,"7th-8th",4,"Divorced","Craft-repair","Unmarried","White","Female",0,0,55,"United-States","<=50K" +60,"Private",252413,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,32,"United-States",">50K" +33,"Private",181372,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +58,"Private",216851,"9th",5,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"El-Salvador","<=50K" +27,"Private",106935,"Some-college",10,"Separated","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"State-gov",363875,"Some-college",10,"Divorced","Protective-serv","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +63,"Private",287277,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",172342,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",308498,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,15,"United-States","<=50K" +31,"Private",106437,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,60,"United-States",">50K" +49,"Self-emp-inc",306289,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Self-emp-inc",201699,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +42,"Private",282062,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",235108,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",339482,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",181820,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",99335,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +50,"Private",269095,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",100999,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +18,"Private",34125,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,28,"United-States","<=50K" +20,"Private",115057,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Private",139126,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",104632,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,40,"Cambodia",">50K" +40,"Federal-gov",178866,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States",">50K" +54,"Private",139850,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,45,"United-States",">50K" +28,"Private",61435,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +38,"Private",309230,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",45613,"Some-college",10,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",272615,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",54318,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",165519,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",48495,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,42,"United-States",">50K" +38,"Private",143123,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +75,"Private",256474,"Masters",14,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,16,"United-States","<=50K" +41,"Private",191451,"Masters",14,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,60,"United-States",">50K" +37,"Private",99146,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +47,"Private",235986,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,50,"Cuba","<=50K" +34,"Local-gov",429897,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"Mexico",">50K" +25,"Private",189897,"HS-grad",9,"Married-civ-spouse","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Private",145155,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",194960,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","Other","Male",0,0,40,"Puerto-Rico","<=50K" +44,"Local-gov",357814,"12th",8,"Married-civ-spouse","Other-service","Other-relative","White","Female",0,0,35,"Mexico","<=50K" +27,"Local-gov",137629,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,80,"United-States",">50K" +42,"Private",156526,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",0,0,33,"United-States","<=50K" +26,"Private",189238,"9th",5,"Never-married","Other-service","Own-child","White","Female",0,0,38,"El-Salvador","<=50K" +23,"Private",202989,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"Canada","<=50K" +28,"Private",25684,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",192939,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"Private",138692,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,50,"United-States","<=50K" +29,"Private",222249,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +23,"?",190650,"Bachelors",13,"Never-married","?","Not-in-family","Asian-Pac-Islander","Male",0,0,35,"United-States","<=50K" +30,"Private",56004,"Some-college",10,"Never-married","Exec-managerial","Own-child","Black","Female",0,0,40,"United-States","<=50K" +48,"Private",182313,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",138962,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,72,"?","<=50K" +38,"Private",277248,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"Cuba",">50K" +24,"Private",125031,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +47,"State-gov",216414,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",171176,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,48,"?","<=50K" +29,"Private",356133,"Some-college",10,"Never-married","Prof-specialty","Other-relative","White","Female",0,0,40,"United-States","<=50K" +45,"Private",185397,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",308285,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",56651,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Local-gov",154863,"9th",5,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"Trinadad&Tobago",">50K" +46,"Federal-gov",44706,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,50,"United-States",">50K" +34,"?",222548,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,4,"United-States","<=50K" +32,"Private",248754,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",104981,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",315065,"Some-college",10,"Never-married","Other-service","Unmarried","White","Male",0,0,35,"Mexico","<=50K" +46,"Private",188325,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",221661,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,35,"United-States","<=50K" +59,"Private",81973,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +31,"Private",169122,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +48,"Private",216734,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",98101,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",292511,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +20,"Private",122971,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,35,"United-States","<=50K" +29,"Private",124953,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,50,"United-States","<=50K" +54,"Private",123011,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",76417,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States","<=50K" +43,"Private",351576,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +33,"Private",79923,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +33,"Private",117983,"10th",6,"Divorced","Other-service","Unmarried","White","Female",0,0,45,"United-States","<=50K" +36,"Private",186110,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"?",319685,"Assoc-voc",11,"Married-civ-spouse","?","Husband","White","Male",0,0,54,"United-States",">50K" +64,"?",64101,"12th",8,"Married-civ-spouse","?","Husband","White","Male",0,0,24,"United-States","<=50K" +45,"Self-emp-not-inc",162923,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +25,"Private",288519,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",33798,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",214120,"HS-grad",9,"Never-married","Priv-house-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",113515,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +58,"Self-emp-not-inc",261230,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",98515,"Assoc-voc",11,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +46,"Private",187715,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +23,"?",214238,"7th-8th",4,"Never-married","?","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +26,"Private",68991,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +52,"Private",292110,"5th-6th",3,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",198320,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +33,"Private",709798,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +60,"Private",372838,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",160402,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +45,"Private",98475,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +37,"Local-gov",97136,"Some-college",10,"Married-spouse-absent","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",136985,"Assoc-acdm",12,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +53,"Private",187356,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,66,"United-States","<=50K" +20,"Private",305874,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Private",290922,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",247321,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +53,"Private",247651,"7th-8th",4,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,56,"United-States","<=50K" +34,"Private",561334,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +36,"?",224886,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",401134,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",258170,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,38,"United-States","<=50K" +68,"?",141181,"9th",5,"Married-civ-spouse","?","Husband","White","Male",0,0,2,"United-States","<=50K" +37,"Private",292370,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Other","Male",0,0,50,"?",">50K" +22,"Private",300871,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",136721,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"?",140399,"Some-college",10,"Never-married","?","Other-relative","White","Female",0,0,30,"United-States","<=50K" +36,"Private",109133,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",186534,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +25,"Private",226891,"Assoc-voc",11,"Never-married","Other-service","Other-relative","Asian-Pac-Islander","Female",0,0,40,"?","<=50K" +33,"Private",241885,"Some-college",10,"Separated","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",97165,"Some-college",10,"Never-married","Machine-op-inspct","Other-relative","White","Female",0,0,40,"United-States","<=50K" +33,"Private",212918,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +24,"Private",211585,"HS-grad",9,"Married-civ-spouse","Transport-moving","Own-child","White","Female",0,0,40,"United-States","<=50K" +47,"Local-gov",178309,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-inc",481987,"10th",6,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",215211,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +33,"Local-gov",194901,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Local-gov",190290,"Assoc-voc",11,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,56,"United-States","<=50K" +26,"Private",188569,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +22,"Private",162282,"Assoc-voc",11,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",287315,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +31,"Self-emp-inc",304212,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,45,"United-States","<=50K" +73,"?",200878,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +38,"Local-gov",256864,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",46401,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +36,"Private",37778,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Self-emp-not-inc",103643,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,15,"United-States",">50K" +24,"Private",143766,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,55,"United-States","<=50K" +21,"State-gov",204425,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,20,"United-States","<=50K" +28,"Private",156257,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +18,"?",113185,"11th",7,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +41,"Self-emp-inc",112262,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +17,"Private",28031,"9th",5,"Never-married","Other-service","Own-child","White","Male",0,0,16,"United-States","<=50K" +58,"Private",320102,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +50,"Self-emp-not-inc",334273,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,8,"United-States","<=50K" +30,"Private",356015,"11th",7,"Married-spouse-absent","Handlers-cleaners","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"Mexico","<=50K" +47,"Private",278900,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",142528,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +50,"Federal-gov",343014,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States","<=50K" +29,"Private",201017,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,55,"Scotland","<=50K" +31,"Self-emp-not-inc",81030,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Self-emp-not-inc",34007,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States",">50K" +31,"Private",29662,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +53,"Private",347446,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +33,"Private",90668,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",190403,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",234807,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +18,"Private",157131,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +50,"Private",94081,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Private",103164,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",570002,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +24,"State-gov",215797,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",239461,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Male",0,0,35,"United-States","<=50K" +34,"Private",101510,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,50,"United-States",">50K" +30,"Self-emp-inc",443546,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +37,"Federal-gov",141029,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",207202,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States",">50K" +67,"Without-pay",137192,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,12,"Philippines","<=50K" +35,"Private",222989,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States","<=50K" +75,"Self-emp-not-inc",36325,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +47,"Private",73394,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States","<=50K" +23,"Private",249046,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Federal-gov",100653,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +42,"Local-gov",1125613,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",101352,"Some-college",10,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,32,"United-States",">50K" +54,"Private",340476,"HS-grad",9,"Separated","Sales","Unmarried","White","Female",0,0,35,"United-States","<=50K" +20,"Private",192711,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Private",273362,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",85399,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Local-gov",168191,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States",">50K" +27,"Private",153475,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +61,"Self-emp-not-inc",196773,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States",">50K" +41,"Private",180138,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +22,"Private",48347,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +66,"?",129476,"Bachelors",13,"Married-civ-spouse","?","Husband","White","Male",0,0,6,"United-States","<=50K" +25,"Private",181772,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",284317,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +20,"Private",237305,"Some-college",10,"Never-married","Machine-op-inspct","Other-relative","Black","Female",0,0,35,"United-States","<=50K" +67,"Self-emp-inc",111321,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,16,"United-States","<=50K" +44,"Private",278476,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +42,"Private",39060,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +29,"Local-gov",205262,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Other","Male",0,0,40,"Ecuador","<=50K" +48,"Private",198000,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Female",0,0,38,"United-States",">50K" +25,"Private",397962,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",178370,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,99,"United-States",">50K" +40,"Private",56072,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +26,"Private",176756,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",60374,"HS-grad",9,"Married-civ-spouse","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +52,"Private",165681,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Self-emp-not-inc",287037,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Self-emp-not-inc",55568,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Wife","White","Female",0,0,50,"United-States","<=50K" +48,"Private",155509,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,16,"Trinadad&Tobago","<=50K" +19,"Private",201178,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +19,"Private",264593,"Some-college",10,"Never-married","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +32,"Private",159589,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,50,"United-States","<=50K" +39,"Private",454915,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +33,"Private",285131,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",150057,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",55390,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,45,"United-States","<=50K" +23,"Private",314894,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,45,"United-States","<=50K" +59,"?",184948,"Assoc-voc",11,"Divorced","?","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +25,"Local-gov",124483,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Male",0,0,20,"India","<=50K" +37,"Self-emp-inc",97986,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,68,"United-States","<=50K" +31,"Private",210562,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States","<=50K" +24,"Private",233280,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Female",0,0,37,"United-States","<=50K" +53,"Local-gov",164300,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"Dominican-Republic","<=50K" +26,"Private",227489,"Some-college",10,"Never-married","Handlers-cleaners","Other-relative","Black","Male",0,0,40,"?","<=50K" +25,"Private",263773,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +59,"Private",96459,"11th",7,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Federal-gov",116608,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Private",180007,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",305466,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",238917,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"El-Salvador","<=50K" +25,"Private",129784,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Private",367390,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,50,"United-States","<=50K" +20,"Private",235691,"HS-grad",9,"Never-married","Sales","Unmarried","White","Male",0,0,40,"United-States","<=50K" +63,"?",166425,"Some-college",10,"Widowed","?","Not-in-family","Black","Female",0,0,24,"United-States","<=50K" +43,"Self-emp-not-inc",160369,"10th",6,"Divorced","Farming-fishing","Unmarried","White","Male",0,0,25,"United-States","<=50K" +39,"Private",206298,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",183523,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +17,"Private",217342,"10th",6,"Never-married","Sales","Own-child","White","Female",0,0,5,"United-States","<=50K" +40,"State-gov",141858,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,72,"United-States","<=50K" +50,"Private",213296,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +23,"Self-emp-inc",201682,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +30,"Private",269723,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",200593,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +23,"Private",32616,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +45,"Self-emp-not-inc",271828,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +22,"Private",113703,"Some-college",10,"Never-married","Sales","Other-relative","White","Male",0,0,20,"United-States","<=50K" +41,"Private",187802,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",440706,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",191834,"HS-grad",9,"Divorced","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-inc",315998,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +38,"Private",60313,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +58,"Local-gov",32855,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States","<=50K" +58,"Private",142326,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +61,"Self-emp-not-inc",201965,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",206541,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +33,"Self-emp-not-inc",177828,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +28,"Private",303440,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +22,"Private",89991,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,11,"United-States","<=50K" +35,"Private",186009,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Private",170988,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +50,"Self-emp-not-inc",213654,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-inc",32316,"12th",8,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",150371,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"?",387871,"10th",6,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +28,"Private",314649,"Some-college",10,"Married-civ-spouse","Sales","Husband","Amer-Indian-Eskimo","Male",0,0,60,"United-States","<=50K" +42,"Private",240255,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States",">50K" +60,"Private",206339,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-inc",230168,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,91,"United-States","<=50K" +36,"Private",148581,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +52,"Local-gov",89705,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Self-emp-not-inc",248406,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Local-gov",72594,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,55,"United-States",">50K" +31,"Local-gov",137537,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Private",225065,"5th-6th",3,"Separated","Sales","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +35,"Private",217274,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +19,"Private",69151,"9th",5,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +59,"Self-emp-not-inc",81107,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,80,"United-States",">50K" +38,"Private",205852,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",201117,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Private",397307,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +39,"Private",115422,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +64,"Private",114994,"Some-college",10,"Separated","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"Local-gov",39815,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +49,"Private",151584,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,32,"United-States","<=50K" +19,"Private",164938,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +26,"Private",253841,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +38,"Private",320305,"7th-8th",4,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",229287,"Bachelors",13,"Never-married","Exec-managerial","Other-relative","White","Female",0,0,25,"United-States","<=50K" +19,"Private",100790,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",171419,"Assoc-voc",11,"Never-married","Exec-managerial","Unmarried","Asian-Pac-Islander","Male",0,0,40,"South","<=50K" +60,"Private",202226,"Some-college",10,"Divorced","Craft-repair","Own-child","White","Male",0,0,44,"United-States",">50K" +46,"Private",220124,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +33,"State-gov",31703,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Local-gov",153908,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +18,"?",252046,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +60,"Self-emp-inc",160062,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,25,"United-States","<=50K" +39,"Self-emp-not-inc",148443,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +39,"Private",176634,"Assoc-acdm",12,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Local-gov",74949,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",165484,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +24,"Private",44738,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +32,"Private",130040,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",234537,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +39,"Private",179016,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",335421,"Masters",14,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"State-gov",312678,"Masters",14,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,38,"United-States","<=50K" +22,"?",313786,"HS-grad",9,"Divorced","?","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +31,"Private",198751,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Vietnam","<=50K" +63,"Private",131519,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",285060,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +28,"State-gov",189765,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States","<=50K" +23,"Private",130905,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Private",146325,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States",">50K" +33,"Private",102821,"12th",8,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"?",137876,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",82910,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",309122,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +60,"Private",532845,"1st-4th",2,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico",">50K" +46,"Private",195833,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"?","<=50K" +67,"?",98882,"Masters",14,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"?",133515,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,15,"France","<=50K" +23,"Private",55215,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,55,"United-States","<=50K" +38,"Self-emp-inc",176357,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +60,"Private",185836,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Self-emp-not-inc",54152,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +37,"Private",212437,"Some-college",10,"Widowed","Machine-op-inspct","Unmarried","Black","Female",0,0,48,"United-States","<=50K" +37,"Private",224566,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +58,"Private",200040,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",41526,"Bachelors",13,"Never-married","Craft-repair","Own-child","White","Male",0,0,30,"Canada","<=50K" +27,"Private",89598,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,60,"United-States","<=50K" +33,"Private",323811,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,55,"United-States","<=50K" +43,"State-gov",30824,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Federal-gov",181096,"Some-college",10,"Never-married","Tech-support","Own-child","Black","Male",0,0,20,"United-States","<=50K" +45,"Private",217953,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Other","Male",0,0,40,"Mexico","<=50K" +44,"Private",222635,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +52,"?",121942,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",184889,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,20,"United-States","<=50K" +18,"Federal-gov",101709,"11th",7,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Male",0,0,15,"Philippines","<=50K" +20,"Private",125010,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +32,"Private",53135,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",498328,"10th",6,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +46,"Private",604380,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +28,"Private",174327,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +27,"Self-emp-not-inc",357283,"HS-grad",9,"Never-married","Sales","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +18,"Federal-gov",280728,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,32,"United-States","<=50K" +50,"Self-emp-inc",251240,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",143046,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"Greece","<=50K" +32,"Private",210541,"Bachelors",13,"Divorced","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +43,"Private",172364,"HS-grad",9,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +50,"Private",176227,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"?",">50K" +35,"Private",139647,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +20,"?",174461,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,5,"United-States","<=50K" +73,"?",123345,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,65,"United-States","<=50K" +46,"Private",164427,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,45,"United-States","<=50K" +58,"Private",205235,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +40,"Private",163434,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +25,"Private",264055,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",336215,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +33,"Federal-gov",78307,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Federal-gov",233059,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Private",91433,"10th",6,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +56,"Local-gov",157525,"Some-college",10,"Divorced","Protective-serv","Not-in-family","Black","Male",0,0,48,"United-States","<=50K" +24,"Private",86065,"HS-grad",9,"Never-married","Transport-moving","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +42,"Private",22831,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",180181,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",212617,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,66,"Ecuador","<=50K" +22,"?",125905,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Private",336793,"Bachelors",13,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,40,"United-States","<=50K" +42,"Private",314649,"HS-grad",9,"Married-spouse-absent","Handlers-cleaners","Other-relative","Asian-Pac-Islander","Male",0,0,40,"?","<=50K" +22,"Private",283969,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"Mexico","<=50K" +32,"Self-emp-not-inc",35595,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Private",410240,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +66,"Private",178120,"5th-6th",3,"Divorced","Priv-house-serv","Not-in-family","Black","Female",0,0,15,"United-States","<=50K" +26,"State-gov",294400,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,38,"United-States","<=50K" +55,"Private",189719,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Private",23438,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",178037,"HS-grad",9,"Never-married","Sales","Unmarried","White","Male",0,0,40,"United-States","<=50K" +22,"Private",109815,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",197860,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",271933,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +54,"Private",141663,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,15,"United-States","<=50K" +19,"?",199609,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +56,"Private",92215,"9th",5,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States",">50K" +47,"Private",93449,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,60,"Japan","<=50K" +29,"Private",235393,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +53,"Private",151864,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",189277,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +42,"Private",344572,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States",">50K" +21,"Private",265356,"Some-college",10,"Never-married","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +36,"Self-emp-inc",166880,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +60,"Private",188650,"5th-6th",3,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"?",">50K" +69,"Private",213249,"Assoc-voc",11,"Widowed","Sales","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +31,"Private",112627,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +48,"Private",125120,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,55,"United-States","<=50K" +23,"Private",60409,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",583755,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States",">50K" +36,"Private",68089,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +39,"Private",306646,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",186573,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Female",0,0,46,"United-States","<=50K" +36,"Private",437909,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",420691,"1st-4th",2,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +33,"Federal-gov",94193,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +52,"Private",145879,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States","<=50K" +23,"Private",208946,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,32,"United-States","<=50K" +33,"Private",231826,"1st-4th",2,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Mexico","<=50K" +30,"Private",178587,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +35,"Private",213208,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","Black","Male",0,0,38,"Jamaica","<=50K" +35,"?",139770,"Assoc-voc",11,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"United-States",">50K" +27,"Private",153869,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,37,"United-States","<=50K" +24,"Private",88676,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +44,"Local-gov",151089,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Private",138621,"Assoc-voc",11,"Separated","Priv-house-serv","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +75,"Self-emp-not-inc",213349,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,20,"United-States","<=50K" +47,"Private",192776,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +64,"Private",192884,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +54,"Private",103024,"HS-grad",9,"Divorced","Tech-support","Not-in-family","White","Male",0,0,42,"United-States",">50K" +41,"Federal-gov",510072,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",178615,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",249956,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +51,"Private",177705,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +45,"Self-emp-inc",121124,"Prof-school",15,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States",">50K" +18,"?",25837,"11th",7,"Never-married","?","Own-child","White","Male",0,0,72,"United-States","<=50K" +43,"Private",557349,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Yugoslavia","<=50K" +32,"Private",222548,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +61,"Private",316359,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",200089,"1st-4th",2,"Married-civ-spouse","Other-service","Other-relative","White","Male",0,0,40,"England","<=50K" +56,"Private",271795,"11th",7,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,49,"United-States","<=50K" +28,"Private",31801,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,60,"United-States","<=50K" +23,"Private",196508,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Black","Female",0,0,40,"United-States","<=50K" +55,"Private",189933,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,84,"United-States","<=50K" +33,"Private",361497,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,70,"United-States","<=50K" +22,"Private",150175,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +43,"Local-gov",155106,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",62272,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",189916,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +18,"Private",324011,"9th",5,"Never-married","Farming-fishing","Own-child","White","Male",0,0,20,"United-States","<=50K" +35,"Private",105803,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +67,"?",53588,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",107998,"HS-grad",9,"Divorced","Machine-op-inspct","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",340567,"1st-4th",2,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,55,"Mexico","<=50K" +39,"Private",167777,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +45,"Self-emp-inc",40666,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +42,"Local-gov",195897,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",242984,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Local-gov",236497,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"?",312634,"11th",7,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +64,"Private",59829,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,25,"France","<=50K" +30,"Private",24292,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +43,"Local-gov",180407,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,42,"Germany","<=50K" +49,"Self-emp-not-inc",121238,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +35,"Private",281982,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Self-emp-not-inc",348739,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +49,"Private",194189,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Private",329130,"11th",7,"Separated","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +31,"Private",62165,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +26,"Private",224361,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",34722,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +38,"Private",175972,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",359428,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +24,"?",138504,"HS-grad",9,"Separated","?","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +18,"Private",268952,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +32,"Private",257978,"Assoc-voc",11,"Widowed","Tech-support","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +27,"Private",118799,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"State-gov",78356,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"Jamaica","<=50K" +30,"Self-emp-not-inc",609789,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",123157,"HS-grad",9,"Never-married","Other-service","Not-in-family","Black","Male",0,0,38,"United-States","<=50K" +74,"Private",84197,"Masters",14,"Divorced","Sales","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +36,"Private",162312,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Asian-Pac-Islander","Male",0,0,70,"South","<=50K" +36,"Private",138441,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,55,"United-States","<=50K" +39,"Private",262158,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +25,"Self-emp-inc",133373,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +21,"Private",57916,"HS-grad",9,"Separated","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"State-gov",142897,"Assoc-voc",11,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,50,"United-States","<=50K" +38,"Private",161016,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +20,"Private",227491,"HS-grad",9,"Never-married","Sales","Not-in-family","Asian-Pac-Islander","Female",0,0,25,"United-States","<=50K" +51,"Private",306790,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",33831,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",188972,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Private",313546,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",220585,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +25,"Local-gov",476599,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",163665,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +36,"Private",306646,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +41,"Private",206470,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Germany","<=50K" +34,"Private",169583,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +19,"State-gov",127085,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,10,"United-States","<=50K" +18,"Private",152044,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,3,"United-States","<=50K" +36,"Private",111387,"10th",6,"Divorced","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"Private",213692,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,45,"United-States","<=50K" +23,"Private",163665,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +35,"Private",30529,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",290226,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",182136,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",73266,"Some-college",10,"Never-married","Transport-moving","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +19,"State-gov",60412,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,15,"United-States","<=50K" +70,"Private",187891,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",194304,"Some-college",10,"Divorced","Transport-moving","Not-in-family","Black","Male",0,0,55,"United-States","<=50K" +35,"Private",160910,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Private",148300,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +39,"Private",165743,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +50,"Private",123174,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,37,"?",">50K" +43,"Private",184018,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +37,"Federal-gov",188069,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Philippines",">50K" +29,"?",78529,"10th",6,"Separated","?","Unmarried","White","Female",0,0,12,"United-States","<=50K" +20,"Private",164441,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",199419,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",181342,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Wife","Black","Female",0,0,40,"United-States","<=50K" +44,"Private",173382,"Assoc-acdm",12,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",215384,"11th",7,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"State-gov",424094,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Federal-gov",212120,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",185764,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"United-States","<=50K" +46,"Local-gov",133969,"Masters",14,"Divorced","Prof-specialty","Not-in-family","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +22,"Private",32616,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +49,"Private",149210,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",161210,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +53,"Private",285621,"Masters",14,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +43,"Private",282069,"Some-college",10,"Divorced","Craft-repair","Unmarried","White","Male",0,0,42,"United-States","<=50K" +22,"Private",97508,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,50,"United-States","<=50K" +28,"Private",171133,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +25,"Private",231638,"Some-college",10,"Never-married","Tech-support","Unmarried","White","Female",0,0,24,"United-States","<=50K" +40,"Private",191342,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"China",">50K" +50,"Private",226497,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +48,"Self-emp-not-inc",373606,"Some-college",10,"Divorced","Sales","Unmarried","White","Male",0,0,65,"United-States",">50K" +30,"Private",39150,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",288840,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +34,"Private",293703,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +42,"Private",79586,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +48,"Self-emp-not-inc",82098,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,65,"United-States","<=50K" +29,"Private",78261,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",355996,"10th",6,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",110908,"Assoc-voc",11,"Married-civ-spouse","Transport-moving","Wife","White","Female",0,0,25,"United-States","<=50K" +49,"Private",248895,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +25,"Private",363707,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",272411,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",128033,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +20,"Private",177287,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +44,"Private",197344,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +45,"Private",285858,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Self-emp-inc",193868,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +18,"Private",232082,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +38,"Private",27408,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,50,"United-States","<=50K" +45,"Private",247043,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,42,"United-States","<=50K" +64,"Private",236341,"5th-6th",3,"Widowed","Other-service","Not-in-family","Black","Female",0,0,16,"United-States","<=50K" +34,"Private",30433,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +45,"Self-emp-not-inc",102771,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Self-emp-not-inc",221172,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",375499,"10th",6,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,20,"United-States","<=50K" +27,"Private",178688,"Assoc-voc",11,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +21,"Private",276709,"Some-college",10,"Never-married","Sales","Other-relative","White","Female",0,0,40,"United-States","<=50K" +23,"?",238087,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,30,"United-States","<=50K" +47,"Private",84790,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"State-gov",37482,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +46,"State-gov",178686,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +35,"?",153926,"HS-grad",9,"Married-civ-spouse","?","Wife","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",116613,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,24,"United-States","<=50K" +21,"Private",108687,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +36,"Private",365739,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",195284,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States",">50K" +38,"Private",125933,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"?",">50K" +37,"Private",140854,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +81,"Self-emp-not-inc",193237,"1st-4th",2,"Widowed","Sales","Other-relative","White","Male",0,0,45,"Mexico","<=50K" +41,"Private",46870,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",351324,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",189265,"Assoc-acdm",12,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",236564,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +42,"Federal-gov",557644,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",374454,"HS-grad",9,"Divorced","Transport-moving","Own-child","Black","Male",0,0,40,"United-States","<=50K" +65,"?",160654,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +18,"Private",122775,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +30,"Private",329425,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,48,"United-States","<=50K" +61,"Private",178312,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States","<=50K" +21,"Private",241951,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +53,"Private",130143,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +60,"Private",399387,"7th-8th",4,"Separated","Priv-house-serv","Unmarried","Black","Female",0,0,15,"United-States","<=50K" +47,"Private",163814,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",69586,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",237903,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"?",219897,"Masters",14,"Never-married","?","Not-in-family","White","Female",0,0,35,"Canada","<=50K" +31,"Private",243165,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +33,"State-gov",173806,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +27,"Self-emp-not-inc",65308,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Private",408531,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States",">50K" +37,"Private",314963,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",81206,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +51,"Federal-gov",293196,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Private",95329,"Masters",14,"Divorced","Protective-serv","Unmarried","White","Male",0,0,40,"United-States","<=50K" +25,"Local-gov",45474,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +25,"Private",372728,"Bachelors",13,"Never-married","Other-service","Not-in-family","Black","Female",0,0,24,"Jamaica","<=50K" +29,"Federal-gov",116394,"Bachelors",13,"Married-AF-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Self-emp-not-inc",34180,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,70,"United-States",">50K" +55,"Private",327589,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",706180,"Bachelors",13,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +31,"Private",32550,"10th",6,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",173858,"Prof-school",15,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +51,"Self-emp-inc",230095,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +62,"Private",174711,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +27,"Private",193898,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +23,"Private",303121,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +35,"Self-emp-not-inc",188540,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +46,"Private",158656,"Assoc-acdm",12,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,36,"United-States","<=50K" +45,"Self-emp-inc",204196,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Male",0,0,50,"United-States",">50K" +27,"Private",183802,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",148995,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",190903,"11th",7,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States","<=50K" +37,"State-gov",173780,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,30,"United-States","<=50K" +42,"Private",251239,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"Puerto-Rico","<=50K" +45,"Private",112761,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"State-gov",425785,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",197731,"Assoc-voc",11,"Married-spouse-absent","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States","<=50K" +24,"Private",119156,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,50,"United-States","<=50K" +56,"Private",133819,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",185556,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,12,"United-States",">50K" +50,"Private",109277,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Self-emp-inc",36020,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +45,"Private",45857,"11th",7,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,36,"United-States","<=50K" +41,"State-gov",342834,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +66,"Private",234743,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,24,"United-States","<=50K" +63,"?",257876,"Prof-school",15,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",138441,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,35,"United-States","<=50K" +22,"Private",279802,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +58,"Private",31732,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Private",204172,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,48,"United-States","<=50K" +34,"Private",100593,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,6,"United-States","<=50K" +33,"Local-gov",162623,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +33,"Self-emp-not-inc",80933,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States","<=50K" +17,"Private",47425,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +27,"Private",107812,"Bachelors",13,"Married-civ-spouse","Sales","Other-relative","White","Male",0,0,40,"United-States",">50K" +20,"Self-emp-inc",104443,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +30,"Private",209691,"7th-8th",4,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",314525,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",190772,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +64,"Local-gov",199298,"5th-6th",3,"Divorced","Other-service","Not-in-family","White","Female",0,0,45,"?","<=50K" +38,"Private",216129,"Bachelors",13,"Divorced","Other-service","Not-in-family","Black","Female",0,0,60,"?","<=50K" +46,"Federal-gov",219293,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,80,"United-States",">50K" +17,"Private",136363,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +45,"Private",233799,"1st-4th",2,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +27,"Private",207611,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-inc",178344,"Assoc-voc",11,"Divorced","Sales","Unmarried","White","Female",0,0,30,"United-States","<=50K" +26,"Self-emp-inc",187652,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,78,"United-States",">50K" +44,"Local-gov",58124,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,45,"United-States","<=50K" +35,"Private",206253,"9th",5,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"?",152140,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States","<=50K" +56,"Private",76281,"Bachelors",13,"Married-spouse-absent","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +47,"Private",606752,"Masters",14,"Divorced","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +32,"Private",29933,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States",">50K" +55,"?",227203,"Assoc-acdm",12,"Married-spouse-absent","?","Not-in-family","White","Female",0,0,5,"United-States","<=50K" +35,"Self-emp-inc",65624,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +37,"Private",34146,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,68,"United-States","<=50K" +33,"Private",141490,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,45,"United-States","<=50K" +34,"Private",199227,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +24,"Private",224954,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",231357,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Self-emp-inc",113530,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +38,"Private",22245,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",36383,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Mexico",">50K" +35,"Private",320305,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,32,"United-States","<=50K" +67,"?",201657,"Bachelors",13,"Divorced","?","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +34,"Private",48935,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +46,"Private",101455,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +19,"Local-gov",243960,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,16,"United-States","<=50K" +26,"Private",90915,"Assoc-acdm",12,"Never-married","Other-service","Own-child","Black","Female",0,0,15,"United-States","<=50K" +28,"Private",315287,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +47,"Private",106255,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Local-gov",215895,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"Italy",">50K" +44,"Private",210525,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",195488,"HS-grad",9,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,40,"Guatemala","<=50K" +18,"Private",152246,"Some-college",10,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Male",0,0,16,"United-States","<=50K" +81,"?",89391,"Prof-school",15,"Married-civ-spouse","?","Husband","White","Male",0,0,24,"United-States",">50K" +43,"State-gov",254817,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",41777,"12th",8,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +58,"Self-emp-not-inc",234841,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,72,"United-States","<=50K" +32,"Private",79586,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"India","<=50K" +40,"Private",115331,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States","<=50K" +32,"Private",63564,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +44,"Private",370502,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,25,"Mexico","<=50K" +25,"Private",69413,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +42,"Private",32981,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",176683,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +62,"?",144116,"10th",6,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Self-emp-not-inc",209213,"HS-grad",9,"Never-married","Sales","Not-in-family","Black","Male",0,0,40,"?","<=50K" +33,"State-gov",150657,"Bachelors",13,"Never-married","Prof-specialty","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +50,"Self-emp-not-inc",124793,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +46,"Private",270565,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +22,"Private",38251,"Assoc-acdm",12,"Never-married","Other-service","Unmarried","White","Female",0,0,35,"United-States","<=50K" +52,"Private",195638,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,45,"United-States","<=50K" +41,"Self-emp-not-inc",44006,"Assoc-voc",11,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",333953,"12th",8,"Never-married","Other-service","Other-relative","White","Female",0,0,30,"United-States","<=50K" +45,"Local-gov",172111,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,60,"United-States","<=50K" +51,"Self-emp-not-inc",32372,"12th",8,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,99,"United-States","<=50K" +69,"?",117525,"Assoc-acdm",12,"Divorced","?","Unmarried","White","Female",0,0,1,"United-States","<=50K" +45,"Self-emp-not-inc",123681,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States","<=50K" +48,"Private",317360,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +42,"Private",135056,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"State-gov",135162,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +39,"Self-emp-not-inc",194004,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,70,"United-States","<=50K" +46,"Private",177633,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States",">50K" +36,"Private",30509,"Some-college",10,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,45,"United-States","<=50K" +21,"Private",118712,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,35,"United-States","<=50K" +41,"Private",199018,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",151799,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +29,"Private",181280,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Private",232024,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +33,"Private",226267,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"Mexico","<=50K" +38,"Private",240467,"Masters",14,"Never-married","Exec-managerial","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +42,"Private",154374,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +24,"State-gov",231473,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,30,"United-States","<=50K" +59,"Private",158813,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +42,"Self-emp-not-inc",238188,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,96,"United-States","<=50K" +54,"Self-emp-not-inc",156800,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Private",130620,"Assoc-acdm",12,"Married-spouse-absent","Craft-repair","Other-relative","Asian-Pac-Islander","Female",0,0,40,"?","<=50K" +50,"Private",175339,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",37937,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,45,"United-States","<=50K" +31,"Private",221167,"Bachelors",13,"Widowed","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +56,"Private",179641,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +28,"Local-gov",213195,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +34,"Private",157747,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Private",227840,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",169104,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"?",">50K" +34,"Private",37646,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,65,"United-States","<=50K" +26,"Private",157028,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,55,"United-States",">50K" +25,"Private",182656,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +48,"Self-emp-not-inc",200471,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",358465,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Private",78602,"11th",7,"Never-married","Other-service","Other-relative","White","Female",0,0,20,"United-States","<=50K" +44,"Private",213416,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +46,"Local-gov",345911,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +32,"?",119522,"Bachelors",13,"Divorced","?","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +42,"Federal-gov",126320,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +33,"Self-emp-not-inc",235271,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +61,"Private",141745,"HS-grad",9,"Divorced","Other-service","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +47,"Private",359461,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Private",148113,"10th",6,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +62,"Self-emp-not-inc",75478,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"?",28455,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +33,"Private",231413,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Local-gov",119421,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,42,"United-States","<=50K" +17,"Private",206998,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,10,"United-States","<=50K" +58,"Private",183810,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-inc",187053,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +55,"?",193895,"7th-8th",4,"Divorced","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",48520,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"Self-emp-inc",170125,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",107584,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",196742,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +52,"?",244214,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,35,"United-States","<=50K" +48,"Local-gov",127921,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",42617,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +47,"Local-gov",191389,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +38,"Private",187983,"Prof-school",15,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States","<=50K" +18,"Private",215110,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"United-States","<=50K" +25,"Private",230292,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",90159,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,32,"United-States",">50K" +40,"Private",175398,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +56,"Self-emp-not-inc",53366,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +50,"Private",46155,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States",">50K" +32,"Local-gov",112650,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",173682,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,43,"United-States",">50K" +28,"Private",160981,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,52,"United-States","<=50K" +53,"Private",72257,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +26,"?",182332,"Assoc-voc",11,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States","<=50K" +21,"Private",417668,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +29,"Private",107458,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-inc",33729,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +45,"Private",101977,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +35,"?",374716,"9th",5,"Married-civ-spouse","?","Wife","White","Female",0,0,35,"United-States","<=50K" +36,"Private",214378,"HS-grad",9,"Divorced","Prof-specialty","Own-child","White","Female",0,0,40,"United-States",">50K" +25,"Private",111243,"HS-grad",9,"Never-married","Sales","Other-relative","White","Female",0,0,50,"United-States","<=50K" +38,"Private",252947,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,40,"United-States","<=50K" +30,"Local-gov",118500,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Local-gov",174575,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",190391,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Private",166715,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States","<=50K" +41,"Self-emp-not-inc",142725,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +51,"Private",241745,"5th-6th",3,"Separated","Machine-op-inspct","Unmarried","White","Female",0,0,40,"Mexico","<=50K" +61,"Local-gov",248595,"1st-4th",2,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +52,"Private",90189,"7th-8th",4,"Divorced","Priv-house-serv","Own-child","Black","Female",0,0,16,"United-States","<=50K" +40,"Private",205195,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +20,"Private",148940,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Local-gov",298035,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",154728,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Private",166809,"Bachelors",13,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States",">50K" +36,"State-gov",97136,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",347623,"Masters",14,"Never-married","Exec-managerial","Unmarried","White","Male",0,0,40,"United-States","<=50K" +40,"Private",117917,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",0,0,50,"United-States","<=50K" +45,"Private",266860,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",71864,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Female",0,0,35,"United-States","<=50K" +47,"Private",158451,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,2,"United-States",">50K" +24,"Private",229826,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +19,"Private",121788,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +40,"Private",151365,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +40,"Private",360884,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,50,"United-States",">50K" +43,"Self-emp-not-inc",116666,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Other","Male",0,0,35,"United-States",">50K" +63,"Local-gov",214143,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Cuba","<=50K" +18,"Private",45316,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +19,"Private",311974,"1st-4th",2,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +49,"Self-emp-not-inc",48495,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +27,"Private",115945,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +49,"Local-gov",170846,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"Private",142922,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +71,"?",181301,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",286675,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",233168,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,46,"United-States",">50K" +30,"Private",177304,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States","<=50K" +46,"Private",336984,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,17,"United-States","<=50K" +32,"Self-emp-not-inc",379412,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",180778,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,75,"United-States","<=50K" +25,"Private",141876,"Masters",14,"Never-married","Prof-specialty","Unmarried","White","Male",0,0,45,"?","<=50K" +22,"Private",228306,"Some-college",10,"Married-AF-spouse","Other-service","Wife","White","Female",0,0,40,"United-States",">50K" +32,"Private",329993,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +40,"Private",247469,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,30,"United-States",">50K" +20,"Private",155775,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,30,"United-States","<=50K" +34,"Private",81223,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +40,"Private",236021,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +34,"State-gov",103371,"Assoc-voc",11,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",199480,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +53,"Private",152657,"10th",6,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +42,"Federal-gov",460214,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",91039,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +41,"Private",197372,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +64,"?",267198,"Prof-school",15,"Married-civ-spouse","?","Husband","White","Male",0,0,16,"United-States","<=50K" +30,"State-gov",111883,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",66917,"11th",7,"Married-civ-spouse","Farming-fishing","Own-child","White","Male",0,0,40,"Mexico","<=50K" +19,"Private",292583,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +20,"Private",391679,"HS-grad",9,"Never-married","Sales","Other-relative","White","Male",0,0,60,"United-States","<=50K" +35,"Private",475324,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +33,"Self-emp-not-inc",218164,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Federal-gov",65706,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,38,"United-States","<=50K" +50,"Self-emp-not-inc",156606,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,30,"United-States","<=50K" +23,"Private",200967,"HS-grad",9,"Divorced","Other-service","Own-child","White","Female",0,0,10,"United-States","<=50K" +30,"Local-gov",164493,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,10,"United-States","<=50K" +33,"Private",547886,"Bachelors",13,"Separated","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +48,"Private",232145,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",96421,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,24,"Outlying-US(Guam-USVI-etc)","<=50K" +33,"Private",554206,"Some-college",10,"Never-married","Tech-support","Not-in-family","Black","Male",0,0,40,"Philippines","<=50K" +50,"Local-gov",234143,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,45,"United-States",">50K" +23,"Private",380544,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Local-gov",103886,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +50,"State-gov",54709,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,46,"United-States","<=50K" +26,"Private",276548,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,20,"United-States","<=50K" +37,"Private",114605,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",323713,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",261382,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",223548,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,30,"Mexico","<=50K" +44,"Private",107218,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",31717,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",328947,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Private",148431,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",121602,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",83425,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",57898,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +40,"State-gov",175304,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +66,"Self-emp-inc",102663,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +17,"Private",99175,"11th",7,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +37,"Private",208358,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +69,"Private",361561,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,3,"United-States","<=50K" +23,"Private",215115,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Federal-gov",207066,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States",">50K" +37,"Federal-gov",160910,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",64879,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",430035,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,54,"Mexico","<=50K" +37,"State-gov",74163,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-inc",98389,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",386019,"9th",5,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,70,"United-States","<=50K" +17,"Private",112795,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +48,"Private",332465,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"United-States","<=50K" +17,"Private",38611,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,23,"United-States","<=50K" +35,"Private",24106,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +68,"?",108683,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,12,"United-States",">50K" +35,"Self-emp-not-inc",241998,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +53,"Private",312446,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +43,"Private",69333,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +36,"Private",172538,"Masters",14,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",275884,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +45,"Private",43479,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States","<=50K" +56,"Private",235197,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +36,"Private",170376,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +22,"Private",325179,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,50,"United-States","<=50K" +33,"Private",141841,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,36,"United-States","<=50K" +48,"Private",207817,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,32,"Columbia","<=50K" +20,"Private",137974,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +47,"Private",293623,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Dominican-Republic","<=50K" +20,"Private",37783,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +44,"Federal-gov",308027,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",149218,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,77,"United-States","<=50K" +45,"Local-gov",61885,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,37,"United-States",">50K" +27,"State-gov",291196,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +41,"Private",45366,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,72,"United-States",">50K" +20,"Private",203027,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +50,"Private",155574,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +31,"State-gov",193565,"Masters",14,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",123598,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +44,"Private",456236,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",163229,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +28,"Local-gov",419740,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +33,"Private",31449,"Assoc-acdm",12,"Divorced","Machine-op-inspct","Unmarried","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +35,"Private",204163,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,55,"United-States","<=50K" +17,"Private",177629,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +25,"Private",186370,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",188307,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",55481,"Masters",14,"Never-married","Tech-support","Unmarried","White","Male",0,0,45,"Nicaragua","<=50K" +48,"Private",119471,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,56,"Philippines",">50K" +61,"Local-gov",167347,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"United-States","<=50K" +41,"Private",184378,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",348960,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +24,"Local-gov",69640,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",297457,"HS-grad",9,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,40,"United-States","<=50K" +18,"Private",279593,"11th",7,"Never-married","Prof-specialty","Own-child","White","Female",0,0,2,"United-States","<=50K" +20,"Private",211968,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Female",0,0,15,"United-States","<=50K" +18,"Private",194561,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,12,"United-States","<=50K" +23,"Private",140414,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"State-gov",462832,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","Black","Female",0,0,40,"Trinadad&Tobago","<=50K" +36,"Private",48972,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Self-emp-not-inc",35032,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +47,"Private",228583,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"?","<=50K" +35,"Private",108140,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"State-gov",112497,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States","<=50K" +47,"Federal-gov",142581,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States",">50K" +26,"Private",147982,"11th",7,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"State-gov",440129,"Some-college",10,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States",">50K" +46,"Private",200734,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,35,"Trinadad&Tobago","<=50K" +49,"Private",31807,"Some-college",10,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",166153,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +45,"Self-emp-inc",212954,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +70,"Self-emp-not-inc",303588,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,20,"United-States","<=50K" +19,"Private",96176,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +46,"Private",184632,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"Private",137618,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,35,"United-States","<=50K" +17,"Private",160029,"11th",7,"Never-married","Other-service","Other-relative","White","Female",0,0,22,"United-States","<=50K" +43,"Private",178780,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,49,"United-States",">50K" +19,"Private",39756,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +37,"Private",35309,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",117253,"HS-grad",9,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Local-gov",303212,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",214542,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,60,"Canada","<=50K" +31,"Private",342019,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",401508,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",85708,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",115677,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","White","Male",0,0,32,"United-States","<=50K" +25,"Private",144259,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,50,"United-States","<=50K" +22,"Private",197583,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +21,"State-gov",142766,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +67,"?",132626,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,6,"United-States","<=50K" +35,"Self-emp-inc",185621,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,60,"United-States",">50K" +54,"Local-gov",29887,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,56,"United-States","<=50K" +36,"Private",117381,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",211482,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",209535,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +56,"Federal-gov",187873,"Masters",14,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +19,"Private",174732,"Some-college",10,"Never-married","Other-service","Own-child","Black","Male",0,0,25,"United-States","<=50K" +58,"Private",110213,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States",">50K" +35,"Private",162601,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",108438,"10th",6,"Separated","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +40,"Self-emp-inc",132222,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",174394,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +71,"Self-emp-not-inc",322789,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Amer-Indian-Eskimo","Male",0,0,35,"United-States","<=50K" +51,"Federal-gov",72436,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,57,"United-States",">50K" +27,"?",60726,"HS-grad",9,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +20,"Private",190273,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +33,"?",393376,"11th",7,"Never-married","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",140571,"Assoc-voc",11,"Divorced","Tech-support","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",584790,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",197666,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,24,"Greece","<=50K" +42,"Private",192569,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,39,"United-States",">50K" +19,"?",113915,"HS-grad",9,"Never-married","?","Own-child","Black","Male",0,0,10,"United-States","<=50K" +38,"Local-gov",287658,"Masters",14,"Divorced","Prof-specialty","Not-in-family","Black","Male",0,0,40,"Jamaica","<=50K" +22,"Private",192455,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +36,"Private",317040,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,54,"United-States","<=50K" +30,"Federal-gov",48458,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +54,"Private",425804,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States",">50K" +58,"Private",72812,"10th",6,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",89040,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Local-gov",164518,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +51,"Private",182740,"HS-grad",9,"Divorced","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +52,"Private",361875,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +25,"Private",197130,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +26,"Private",340335,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",293984,"10th",6,"Married-civ-spouse","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +59,"State-gov",261584,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,40,"Outlying-US(Guam-USVI-etc)","<=50K" +21,"Private",170302,"HS-grad",9,"Never-married","Farming-fishing","Other-relative","White","Male",0,0,50,"United-States","<=50K" +45,"Private",481987,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,18,"United-States",">50K" +26,"Private",88449,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,36,"United-States","<=50K" +68,"Self-emp-not-inc",261897,"10th",6,"Widowed","Farming-fishing","Unmarried","White","Male",0,0,20,"United-States","<=50K" +60,"Private",250552,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +65,"Private",88513,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,18,"United-States","<=50K" +41,"Private",168293,"Masters",14,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +34,"Private",283921,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"Private",407043,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +40,"Private",63745,"Assoc-voc",11,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +57,"Private",49893,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +37,"Private",241962,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",338416,"10th",6,"Divorced","Machine-op-inspct","Not-in-family","Black","Male",0,0,60,"United-States","<=50K" +21,"?",212888,"11th",7,"Married-civ-spouse","?","Wife","White","Female",0,0,56,"United-States","<=50K" +57,"Federal-gov",310320,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,48,"United-States",">50K" +51,"Private",64643,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,60,"?","<=50K" +56,"Private",125000,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",286675,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +18,"Private",165532,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,15,"United-States","<=50K" +48,"Private",349986,"Assoc-voc",11,"Married-spouse-absent","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +46,"Private",213140,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?",">50K" +41,"Federal-gov",219155,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"India",">50K" +33,"Private",183612,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,20,"United-States","<=50K" +33,"Private",391114,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",219632,"5th-6th",3,"Married-spouse-absent","Machine-op-inspct","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +40,"Private",799281,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,38,"United-States","<=50K" +42,"Private",657397,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +51,"Private",168660,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Private",191149,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,57,"United-States","<=50K" +37,"Private",356824,"HS-grad",9,"Separated","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +25,"Private",191782,"11th",7,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,40,"United-States","<=50K" +52,"Private",204226,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +28,"Private",496526,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",84154,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +37,"Federal-gov",45937,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +31,"Private",130021,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +35,"Private",63021,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +25,"Private",367306,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Private",65624,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",144928,"HS-grad",9,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +22,"Private",117747,"Some-college",10,"Never-married","Craft-repair","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +18,"Private",266681,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +26,"Private",152035,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",190023,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +43,"Private",233130,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +21,"Private",149637,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +62,"Federal-gov",224277,"Some-college",10,"Widowed","Protective-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",121559,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Self-emp-not-inc",230951,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",345285,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +65,"Self-emp-not-inc",28367,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +31,"Private",243773,"9th",5,"Never-married","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +56,"Private",151474,"9th",5,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +50,"Private",135465,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +22,"Private",210781,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +36,"Local-gov",359001,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,48,"United-States","<=50K" +48,"Private",119471,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"India",">50K" +30,"Private",226396,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,30,"United-States","<=50K" +35,"Private",283122,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States","<=50K" +37,"Self-emp-not-inc",326400,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States","<=50K" +32,"?",169186,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,5,"United-States","<=50K" +56,"Private",158752,"Masters",14,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States","<=50K" +29,"?",208406,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +41,"Private",96741,"Assoc-acdm",12,"Divorced","Sales","Unmarried","White","Male",0,0,40,"United-States","<=50K" +38,"State-gov",255191,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",177733,"9th",5,"Separated","Machine-op-inspct","Unmarried","White","Female",0,0,35,"Dominican-Republic","<=50K" +36,"?",187203,"Assoc-voc",11,"Divorced","?","Own-child","White","Male",0,0,50,"United-States","<=50K" +42,"Private",168515,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",122672,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +21,"Private",195199,"HS-grad",9,"Never-married","Prof-specialty","Own-child","White","Female",0,0,30,"United-States","<=50K" +69,"Local-gov",179813,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,10,"United-States","<=50K" +32,"Private",178623,"Assoc-acdm",12,"Never-married","Sales","Not-in-family","Black","Female",0,0,46,"Trinadad&Tobago","<=50K" +50,"Private",41890,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",373050,"12th",8,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"?","<=50K" +45,"Private",80430,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +31,"Private",198613,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,35,"United-States","<=50K" +24,"Private",330571,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States","<=50K" +28,"Private",209205,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States",">50K" +21,"Private",132243,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Female",0,0,5,"United-States","<=50K" +43,"Self-emp-not-inc",237670,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +22,"Private",193586,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +21,"Self-emp-not-inc",74538,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +37,"Private",89718,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +34,"Private",93169,"Some-college",10,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +43,"Private",328570,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +25,"Private",312157,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",193459,"11th",7,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",236804,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",126223,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +51,"State-gov",172281,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,35,"United-States",">50K" +64,"Private",153894,"Bachelors",13,"Never-married","Sales","Unmarried","White","Female",0,0,40,"Peru","<=50K" +35,"Private",331395,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +32,"Private",318647,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +20,"Private",332931,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"United-States","<=50K" +66,"Self-emp-inc",76212,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Private",301168,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Italy","<=50K" +22,"Private",440969,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,24,"United-States","<=50K" +32,"Private",154950,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",218343,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"Private",239577,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",247936,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Asian-Pac-Islander","Female",0,0,2,"Taiwan","<=50K" +24,"Private",182342,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"?",289116,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,5,"United-States","<=50K" +30,"Private",487330,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,30,"United-States","<=50K" +17,"?",34019,"10th",6,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +17,"?",250541,"11th",7,"Never-married","?","Own-child","Black","Male",0,0,8,"United-States","<=50K" +21,"Self-emp-not-inc",318987,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"Self-emp-not-inc",140558,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",76855,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +52,"Private",308764,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +50,"Federal-gov",339905,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Private",156430,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +45,"?",98265,"HS-grad",9,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",187167,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",184078,"12th",8,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",108140,"Bachelors",13,"Divorced","Tech-support","Other-relative","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",313702,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",252752,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +52,"Private",111700,"Some-college",10,"Divorced","Sales","Other-relative","White","Female",0,0,20,"United-States",">50K" +45,"Private",361842,"HS-grad",9,"Widowed","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +17,"Private",231438,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,12,"United-States","<=50K" +20,"Private",178469,"HS-grad",9,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Female",0,0,15,"?","<=50K" +64,"Local-gov",116620,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,25,"United-States","<=50K" +74,"Self-emp-not-inc",109101,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,4,"United-States","<=50K" +44,"Private",147265,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +23,"State-gov",314645,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +23,"Private",444554,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,50,"United-States","<=50K" +27,"Private",129629,"Assoc-voc",11,"Never-married","Tech-support","Other-relative","White","Female",0,0,36,"United-States","<=50K" +34,"Private",106761,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +18,"Private",189924,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,24,"United-States","<=50K" +33,"Private",311194,"11th",7,"Never-married","Sales","Unmarried","Black","Female",0,0,17,"United-States","<=50K" +50,"Self-emp-not-inc",89737,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +47,"Private",49298,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +18,"Private",251923,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +34,"Private",180284,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,50,"United-States","<=50K" +56,"State-gov",68658,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +64,"Private",203783,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,8,"United-States","<=50K" +23,"Private",250037,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +33,"Private",158688,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",214781,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +57,"State-gov",109015,"12th",8,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",194630,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +23,"Private",239375,"Bachelors",13,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-not-inc",182926,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",117222,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,15,"United-States","<=50K" +30,"Private",110643,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +56,"Self-emp-not-inc",170217,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,45,"United-States","<=50K" +34,"Private",193285,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",161075,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +59,"Private",322691,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +19,"Private",229431,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,11,"United-States","<=50K" +60,"?",106282,"9th",5,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",105694,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,42,"United-States","<=50K" +24,"Private",199883,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +41,"State-gov",100800,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +23,"Private",256278,"7th-8th",4,"Married-civ-spouse","Handlers-cleaners","Other-relative","Other","Female",0,0,30,"El-Salvador","<=50K" +51,"Self-emp-inc",129525,"HS-grad",9,"Never-married","Sales","Other-relative","White","Male",0,0,40,"?","<=50K" +18,"Private",285013,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,10,"United-States","<=50K" +28,"Private",248911,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"?","<=50K" +38,"Private",219902,"HS-grad",9,"Separated","Transport-moving","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +29,"Private",375482,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"England","<=50K" +25,"Private",169124,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +31,"Private",183000,"Prof-school",15,"Never-married","Tech-support","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +34,"Private",28053,"Bachelors",13,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +41,"Private",212894,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Guatemala","<=50K" +62,"Private",223975,"7th-8th",4,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,20,"United-States","<=50K" +58,"Private",357788,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +40,"Private",406811,"HS-grad",9,"Separated","Exec-managerial","Unmarried","White","Female",0,0,40,"Canada","<=50K" +24,"Private",154422,"Bachelors",13,"Never-married","Exec-managerial","Own-child","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +47,"Private",140644,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",355477,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Male",0,0,25,"United-States","<=50K" +32,"Private",151773,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +51,"State-gov",341548,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",512771,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +60,"?",141580,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",48988,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",201022,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,50,"United-States",">50K" +20,"Private",82777,"HS-grad",9,"Married-civ-spouse","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Private",152676,"7th-8th",4,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"Puerto-Rico","<=50K" +18,"Private",115815,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,20,"United-States","<=50K" +23,"Private",168009,"10th",6,"Married-civ-spouse","Machine-op-inspct","Own-child","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +28,"Private",213152,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"?",">50K" +55,"Private",89690,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +40,"Private",126868,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +52,"Private",95128,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +37,"Private",185567,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,40,"United-States",">50K" +35,"Private",216256,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +45,"Private",182541,"Some-college",10,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,48,"United-States","<=50K" +39,"Private",172855,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +54,"Private",68684,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +42,"Private",364832,"7th-8th",4,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"?",264300,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,20,"United-States","<=50K" +59,"Self-emp-inc",349910,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",276218,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +22,"Private",251196,"Some-college",10,"Never-married","Protective-serv","Own-child","Black","Female",0,0,20,"United-States","<=50K" +33,"Private",196898,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",58343,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Self-emp-inc",101061,"11th",7,"Never-married","Farming-fishing","Own-child","White","Male",0,0,70,"United-States","<=50K" +46,"Private",415051,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,60,"United-States",">50K" +24,"Private",174043,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",129460,"Assoc-voc",11,"Married-civ-spouse","Handlers-cleaners","Wife","White","Female",0,0,30,"Ecuador","<=50K" +21,"State-gov",110946,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,43,"United-States","<=50K" +22,"Private",313873,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,30,"United-States","<=50K" +56,"Federal-gov",255386,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Laos","<=50K" +21,"Private",191497,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +17,"Private",128617,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,26,"United-States","<=50K" +29,"Private",368949,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"?",">50K" +28,"Local-gov",263600,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +62,"Private",257277,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +30,"Local-gov",289442,"HS-grad",9,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"?",162667,"11th",7,"Never-married","?","Unmarried","White","Male",0,0,40,"El-Salvador","<=50K" +18,"Local-gov",466325,"11th",7,"Never-married","Adm-clerical","Own-child","White","Male",0,0,12,"United-States","<=50K" +54,"Private",142169,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"Private",252079,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +33,"State-gov",119628,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,50,"Hong","<=50K" +50,"Private",175804,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Private",70720,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,78,"United-States","<=50K" +50,"State-gov",201513,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +45,"Private",257609,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",124692,"Some-college",10,"Married-civ-spouse","Exec-managerial","Own-child","White","Male",0,0,40,"United-States",">50K" +23,"Private",268525,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +23,"Private",250630,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",180277,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"Hungary","<=50K" +39,"Self-emp-not-inc",191342,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,50,"South","<=50K" +46,"Private",153254,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +18,"Private",362600,"5th-6th",3,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +68,"Private",171933,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +62,"Private",211408,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",48193,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",22463,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",440969,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +21,"State-gov",164922,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",134524,"Assoc-voc",11,"Divorced","Craft-repair","Unmarried","White","Female",0,0,45,"United-States","<=50K" +61,"Private",176689,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",220993,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +21,"Private",512828,"HS-grad",9,"Never-married","Protective-serv","Own-child","Black","Male",0,0,40,"United-States","<=50K" +36,"State-gov",422275,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Mexico","<=50K" +37,"Local-gov",65291,"Assoc-voc",11,"Never-married","Protective-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Federal-gov",181657,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +55,"Private",190257,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,53,"United-States",">50K" +21,"Private",238068,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",337046,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",187248,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +20,"?",250037,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,18,"?","<=50K" +23,"Private",260617,"10th",6,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",216999,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +42,"State-gov",121265,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",184466,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +45,"Private",297676,"Assoc-acdm",12,"Widowed","Sales","Unmarried","White","Female",0,0,40,"Cuba","<=50K" +22,"Local-gov",121144,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,18,"United-States","<=50K" +27,"Private",113054,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","White","Male",0,0,43,"United-States","<=50K" +36,"Private",256636,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",152246,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Amer-Indian-Eskimo","Male",0,0,52,"United-States","<=50K" +38,"Private",108140,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +20,"?",203353,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +47,"Private",207207,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,45,"United-States","<=50K" +21,"Private",115420,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +33,"Private",80058,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Local-gov",48520,"Assoc-acdm",12,"Never-married","Protective-serv","Unmarried","White","Male",0,0,40,"United-States","<=50K" +61,"Private",411652,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Mexico","<=50K" +46,"Private",154405,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,45,"United-States","<=50K" +55,"Local-gov",104917,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States",">50K" +19,"State-gov",261422,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +39,"Private",48915,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +61,"Private",172037,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",144833,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",275116,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"?",72886,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,38,"United-States",">50K" +61,"Private",103575,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,37,"United-States","<=50K" +54,"Private",200783,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Self-emp-inc",152810,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,70,"Germany","<=50K" +37,"Local-gov",44694,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,45,"United-States",">50K" +17,"?",48703,"11th",7,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +56,"Private",91905,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,4,"United-States","<=50K" +31,"Private",168906,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States",">50K" +32,"State-gov",147215,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,55,"United-States",">50K" +28,"Private",153546,"11th",7,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",35595,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",225507,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +42,"Private",345504,"Assoc-voc",11,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +64,"Private",137205,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +29,"Private",327779,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,20,"United-States","<=50K" +41,"?",213416,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,32,"Mexico","<=50K" +45,"Private",362883,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Private",131309,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +44,"Private",188331,"Some-college",10,"Separated","Tech-support","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +34,"Federal-gov",194740,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",43711,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +23,"Private",233923,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +51,"Private",84278,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +34,"Private",180284,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States",">50K" +56,"Self-emp-inc",75214,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,32,"United-States",">50K" +42,"Private",284758,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-inc",188330,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +40,"Private",198096,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",163265,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Federal-gov",128608,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",107460,"HS-grad",9,"Separated","Exec-managerial","Unmarried","White","Female",0,0,37,"United-States","<=50K" +51,"Private",251841,"Assoc-voc",11,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +28,"Private",403671,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +58,"Private",159378,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Private",170070,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,25,"United-States","<=50K" +46,"State-gov",192323,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"Private",135796,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,48,"United-States","<=50K" +22,"Private",232985,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,20,"United-States","<=50K" +28,"Private",34532,"Bachelors",13,"Never-married","Tech-support","Not-in-family","Black","Male",0,0,30,"Jamaica","<=50K" +17,"?",371316,"10th",6,"Never-married","?","Own-child","White","Male",0,0,25,"United-States","<=50K" +23,"Private",236994,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,60,"United-States","<=50K" +19,"Private",208366,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +66,"State-gov",102640,"HS-grad",9,"Widowed","Prof-specialty","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +38,"Private",111377,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States","<=50K" +39,"Federal-gov",472166,"Some-college",10,"Divorced","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +39,"?",86551,"12th",8,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",294919,"HS-grad",9,"Divorced","Transport-moving","Own-child","White","Male",0,0,60,"United-States","<=50K" +22,"Private",408383,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +36,"Private",255454,"HS-grad",9,"Never-married","Craft-repair","Own-child","Black","Male",0,0,30,"United-States","<=50K" +32,"Private",193260,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +29,"?",191935,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Local-gov",125461,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +51,"Private",97005,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",183319,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +32,"State-gov",167049,"12th",8,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",185216,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +51,"Private",161838,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,57,"United-States","<=50K" +38,"Private",165848,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,44,"United-States","<=50K" +21,"Private",138816,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,20,"United-States","<=50K" +33,"Self-emp-not-inc",99761,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +34,"Private",112139,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",129020,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"?",365465,"Assoc-voc",11,"Never-married","?","Own-child","White","Male",0,0,15,"United-States","<=50K" +27,"Self-emp-not-inc",259873,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,60,"United-States",">50K" +35,"Self-emp-inc",89622,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +29,"State-gov",201556,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +40,"Private",176286,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",192894,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","Black","Male",0,0,30,"United-States","<=50K" +37,"Private",172232,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +44,"Private",215304,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +25,"Private",185952,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +38,"Private",216845,"HS-grad",9,"Never-married","Sales","Unmarried","White","Male",0,0,42,"United-States","<=50K" +34,"Local-gov",35683,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,10,"United-States","<=50K" +46,"Private",102359,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +20,"Private",200089,"5th-6th",3,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,30,"Guatemala","<=50K" +47,"State-gov",207120,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,38,"United-States",">50K" +46,"Private",295334,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +34,"Private",234537,"Assoc-acdm",12,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +61,"Private",142922,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"State-gov",181641,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","Black","Female",0,0,37,"United-States","<=50K" +36,"Private",185325,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +22,"Private",379778,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",176117,"Some-college",10,"Never-married","Sales","Own-child","Black","Female",0,0,35,"United-States","<=50K" +33,"Private",100228,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",150296,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,32,"United-States","<=50K" +20,"Private",653574,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,33,"El-Salvador","<=50K" +38,"Private",175441,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +30,"Private",333119,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",89154,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,42,"El-Salvador","<=50K" +60,"Private",198727,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,30,"United-States","<=50K" +43,"Private",87284,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",180686,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +23,"Private",227070,"Some-college",10,"Never-married","Other-service","Unmarried","White","Female",0,0,48,"El-Salvador","<=50K" +25,"Local-gov",348986,"HS-grad",9,"Never-married","Handlers-cleaners","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +38,"Private",96185,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +22,"Private",112693,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +23,"Private",417605,"5th-6th",3,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +61,"Self-emp-not-inc",140300,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,44,"United-States","<=50K" +28,"Private",340408,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,46,"United-States","<=50K" +17,"?",187539,"11th",7,"Never-married","?","Own-child","White","Female",0,0,10,"United-States","<=50K" +21,"Private",237051,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +49,"Private",175622,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",389725,"12th",8,"Divorced","Craft-repair","Own-child","White","Male",0,0,35,"United-States","<=50K" +23,"Private",182812,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"Dominican-Republic","<=50K" +34,"Local-gov",93886,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,46,"United-States",">50K" +21,"Private",502837,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Female",0,0,40,"Peru","<=50K" +27,"State-gov",212232,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,40,"United-States",">50K" +57,"Private",300104,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,84,"United-States",">50K" +22,"Private",156933,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,25,"United-States","<=50K" +20,"Private",286734,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Other","Female",0,0,35,"United-States","<=50K" +49,"Self-emp-inc",143482,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,65,"United-States",">50K" +38,"Private",226357,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",104892,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",272090,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States","<=50K" +57,"Private",204816,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +56,"Private",230039,"7th-8th",4,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +41,"Private",242619,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,80,"United-States","<=50K" +50,"Self-emp-not-inc",131982,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Asian-Pac-Islander","Male",0,0,60,"South","<=50K" +33,"Private",87310,"9th",5,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +29,"Private",134566,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"United-States","<=50K" +35,"Private",239409,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",203717,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",65278,"Assoc-acdm",12,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +35,"Self-emp-inc",135289,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,60,"United-States","<=50K" +27,"Private",246974,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",180060,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"Yugoslavia","<=50K" +24,"Private",118023,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +47,"Private",102308,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +47,"Private",45564,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",137646,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +18,"Private",237646,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +31,"Local-gov",189843,"HS-grad",9,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,47,"United-States",">50K" +43,"Self-emp-not-inc",118261,"Masters",14,"Divorced","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +39,"Private",106347,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",316471,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +22,"Private",50058,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +30,"Self-emp-not-inc",182089,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,85,"United-States","<=50K" +36,"Private",186865,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +20,"State-gov",158206,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +59,"Local-gov",50929,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +60,"Private",132529,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",260696,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",231180,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +40,"Private",223277,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,50,"United-States",">50K" +47,"Private",46044,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",168071,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +20,"Private",79691,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +75,"?",114204,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,13,"United-States","<=50K" +25,"Private",124111,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +47,"Private",104521,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Self-emp-not-inc",128516,"Assoc-acdm",12,"Widowed","Sales","Unmarried","White","Female",0,0,40,"United-States",">50K" +34,"Private",112564,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +45,"State-gov",32186,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",269284,"Assoc-acdm",12,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"State-gov",175537,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","Black","Female",0,0,38,"United-States","<=50K" +29,"Private",444304,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",27415,"11th",7,"Never-married","Handlers-cleaners","Own-child","Amer-Indian-Eskimo","Male",0,0,20,"United-States","<=50K" +39,"Private",174343,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",148143,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +34,"Private",209213,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"?","<=50K" +20,"Private",165097,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Private",167651,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Local-gov",29075,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Wife","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +22,"Private",396895,"5th-6th",3,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"Mexico","<=50K" +66,"State-gov",71075,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +35,"Private",129573,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States","<=50K" +40,"Local-gov",183765,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States",">50K" +21,"Private",164991,"HS-grad",9,"Divorced","Sales","Unmarried","Amer-Indian-Eskimo","Female",0,0,38,"United-States","<=50K" +51,"Local-gov",154891,"HS-grad",9,"Divorced","Protective-serv","Unmarried","White","Male",0,0,52,"United-States","<=50K" +34,"Private",200117,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",176389,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",342567,"Bachelors",13,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",178841,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +42,"Local-gov",191149,"Masters",14,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",29702,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +21,"Private",157893,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Female",0,0,40,"United-States","<=50K" +64,"Local-gov",31993,"7th-8th",4,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,10,"United-States","<=50K" +23,"Private",39615,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,10,"United-States","<=50K" +29,"Private",200511,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +44,"Self-emp-not-inc",47818,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,60,"United-States","<=50K" +28,"Private",183155,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +33,"Self-emp-inc",374905,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +35,"Private",128876,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",202872,"10th",6,"Married-spouse-absent","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +42,"Private",153414,"Bachelors",13,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States",">50K" +51,"Self-emp-not-inc",24790,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,99,"United-States",">50K" +32,"Private",316769,"11th",7,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"Jamaica","<=50K" +37,"Private",126569,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",128538,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +24,"Private",234640,"Assoc-voc",11,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +29,"?",65372,"Some-college",10,"Divorced","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +45,"Private",343377,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +52,"Federal-gov",30731,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +35,"Private",412379,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Self-emp-inc",112320,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +63,"Private",181929,"HS-grad",9,"Widowed","Exec-managerial","Unmarried","White","Male",0,0,50,"United-States",">50K" +32,"Local-gov",100135,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,35,"United-States",">50K" +72,"?",402306,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,32,"Canada","<=50K" +35,"?",98389,"Some-college",10,"Never-married","?","Unmarried","White","Male",0,0,10,"United-States","<=50K" +29,"Private",179565,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +70,"Private",102610,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,32,"United-States","<=50K" +36,"Private",150548,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +49,"Local-gov",67001,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",138557,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",170456,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,35,"Italy","<=50K" +42,"Private",66006,"10th",6,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +25,"State-gov",176077,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +32,"Private",218322,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Self-emp-inc",181691,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"?","<=50K" +30,"Private",161690,"Assoc-voc",11,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"?",242736,"Assoc-acdm",12,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",67317,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +37,"Private",99357,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +56,"Private",170070,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +52,"State-gov",231166,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",62339,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"State-gov",118520,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,42,"United-States","<=50K" +45,"Private",155659,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Local-gov",157331,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",341762,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +30,"Private",164190,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +45,"Private",83064,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Private",304283,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",436798,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",29302,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,40,"?","<=50K" +42,"Private",79036,"HS-grad",9,"Divorced","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +72,"Private",165622,"Some-college",10,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +21,"?",177287,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +24,"Private",22966,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +27,"Private",59068,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",77336,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Local-gov",96524,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +17,"Private",143868,"9th",5,"Never-married","Other-service","Own-child","Black","Male",0,0,40,"United-States","<=50K" +48,"Private",121424,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +39,"Private",176279,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Private",205100,"7th-8th",4,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"?","<=50K" +57,"Private",353881,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +44,"Local-gov",177937,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,36,"United-States",">50K" +20,"?",122244,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +49,"Private",125892,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",355728,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +18,"?",245274,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,16,"United-States","<=50K" +18,"Private",240330,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,18,"United-States","<=50K" +51,"Private",182944,"HS-grad",9,"Widowed","Tech-support","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",264498,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",166971,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,52,"United-States","<=50K" +39,"Private",33975,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Self-emp-not-inc",215219,"11th",7,"Separated","Other-service","Unmarried","White","Female",0,0,30,"United-States","<=50K" +63,"?",331527,"10th",6,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",162494,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,45,"United-States",">50K" +27,"Local-gov",85918,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,68,"United-States","<=50K" +20,"Private",182342,"Some-college",10,"Never-married","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +49,"Private",129640,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +70,"?",133536,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,28,"United-States","<=50K" +47,"Private",102583,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States",">50K" +35,"Private",111387,"9th",5,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",241752,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"?",334593,"Some-college",10,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +43,"Private",101950,"Bachelors",13,"Divorced","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +60,"Local-gov",212856,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?",">50K" +53,"Private",183973,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States",">50K" +47,"Private",142061,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",158615,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",29145,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",40135,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +23,"Private",224640,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"?",146651,"HS-grad",9,"Married-civ-spouse","?","Own-child","White","Female",0,0,15,"United-States","<=50K" +29,"Private",167737,"HS-grad",9,"Never-married","Transport-moving","Other-relative","White","Male",0,0,50,"United-States","<=50K" +23,"Private",60331,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",187167,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +18,"?",157131,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,12,"United-States","<=50K" +27,"Local-gov",255237,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +56,"?",192325,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +40,"Private",163342,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,70,"United-States","<=50K" +31,"Private",129775,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States","<=50K" +25,"Private",397317,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",745768,"Some-college",10,"Never-married","Protective-serv","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",141550,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Private",35576,"HS-grad",9,"Widowed","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",376383,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Male",0,0,35,"Mexico","<=50K" +48,"Self-emp-not-inc",200825,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,30,"United-States",">50K" +34,"?",362787,"HS-grad",9,"Never-married","?","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +46,"Private",116789,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",160300,"HS-grad",9,"Married-spouse-absent","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +47,"Private",362654,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"?",107801,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,3,"United-States","<=50K" +31,"Local-gov",224234,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +68,"Private",211162,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",147638,"Bachelors",13,"Never-married","Adm-clerical","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Hong","<=50K" +42,"Private",104647,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",67365,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Self-emp-not-inc",268482,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"State-gov",288731,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,20,"United-States","<=50K" +36,"Private",231082,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +42,"State-gov",333530,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States",">50K" +62,"Private",214288,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",118023,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,24,"United-States","<=50K" +21,"Private",187088,"Some-college",10,"Never-married","Adm-clerical","Own-child","Other","Female",0,0,20,"Cuba","<=50K" +60,"?",174073,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",133833,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +30,"Private",229772,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"Private",210082,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",122999,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Male",0,0,40,"United-States","<=50K" +27,"Private",44767,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",200574,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,44,"United-States","<=50K" +58,"Private",236596,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",33124,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,99,"United-States","<=50K" +50,"Local-gov",308764,"HS-grad",9,"Widowed","Transport-moving","Unmarried","White","Female",0,0,40,"United-States","<=50K" +27,"Private",103524,"HS-grad",9,"Separated","Handlers-cleaners","Unmarried","White","Male",0,0,40,"United-States","<=50K" +31,"?",99483,"HS-grad",9,"Never-married","?","Own-child","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +50,"Private",230951,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",99355,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States",">50K" +33,"Private",857532,"12th",8,"Never-married","Protective-serv","Own-child","Black","Male",0,0,40,"United-States","<=50K" +19,"Private",198943,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,35,"United-States","<=50K" +30,"Private",311696,"11th",7,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,30,"United-States","<=50K" +38,"Private",252897,"Some-college",10,"Divorced","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +42,"Self-emp-not-inc",39539,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,99,"United-States",">50K" +49,"Self-emp-inc",122066,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +24,"Private",202721,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +29,"Private",197565,"Assoc-voc",11,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +38,"Federal-gov",190895,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"?",">50K" +25,"Self-emp-inc",158751,"Assoc-voc",11,"Never-married","Transport-moving","Unmarried","White","Male",0,0,55,"United-States","<=50K" +51,"State-gov",243631,"10th",6,"Married-civ-spouse","Craft-repair","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +17,"?",219277,"11th",7,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +19,"Private",45381,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,8,"United-States","<=50K" +38,"Private",167482,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States",">50K" +60,"Private",225014,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",405083,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Federal-gov",24153,"10th",6,"Married-civ-spouse","Other-service","Wife","Amer-Indian-Eskimo","Female",0,0,40,"United-States","<=50K" +36,"Private",126569,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"Ecuador",">50K" +57,"?",137658,"HS-grad",9,"Married-civ-spouse","?","Husband","Other","Male",0,0,5,"Columbia","<=50K" +24,"Private",315476,"Assoc-acdm",12,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",248186,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +29,"Self-emp-inc",206903,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States",">50K" +20,"Private",191910,"HS-grad",9,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +21,"Private",145119,"Some-college",10,"Never-married","Other-service","Own-child","Asian-Pac-Islander","Male",0,0,20,"United-States","<=50K" +20,"Private",130840,"10th",6,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Private",33126,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +20,"Private",334105,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,10,"United-States","<=50K" +19,"Local-gov",354104,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,35,"United-States","<=50K" +34,"Private",111985,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +40,"Local-gov",321187,"Bachelors",13,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,45,"United-States","<=50K" +33,"Private",138142,"Some-college",10,"Separated","Other-service","Unmarried","Black","Female",0,0,25,"United-States","<=50K" +36,"Private",296999,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +41,"Local-gov",174491,"HS-grad",9,"Separated","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +34,"State-gov",173266,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +33,"Private",25610,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","Other","Male",0,0,40,"Japan",">50K" +47,"Private",187563,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",196344,"1st-4th",2,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"Mexico","<=50K" +40,"Private",205047,"HS-grad",9,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States",">50K" +28,"Private",715938,"Bachelors",13,"Never-married","Craft-repair","Own-child","Black","Male",0,0,40,"United-States","<=50K" +62,"Self-emp-not-inc",224520,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,90,"United-States",">50K" +29,"Private",229656,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States","<=50K" +46,"Private",97883,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",131298,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +57,"Federal-gov",197875,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",172766,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +28,"Local-gov",175796,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",51973,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +22,"Private",291979,"11th",7,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"State-gov",180752,"Bachelors",13,"Never-married","Protective-serv","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +50,"Private",234657,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +18,"Private",39411,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,24,"United-States","<=50K" +52,"State-gov",334273,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +41,"Private",192779,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"?","<=50K" +21,"?",105312,"HS-grad",9,"Never-married","?","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +34,"Self-emp-not-inc",182714,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,55,"United-States",">50K" +21,"Private",231866,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Private",102102,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +57,"?",50248,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Local-gov",195519,"Masters",14,"Never-married","Prof-specialty","Unmarried","White","Female",0,0,25,"United-States","<=50K" +22,"State-gov",34310,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,25,"United-States","<=50K" +33,"?",314913,"11th",7,"Divorced","?","Own-child","White","Male",0,0,53,"United-States","<=50K" +25,"Private",110978,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","Asian-Pac-Islander","Female",0,0,37,"India",">50K" +17,"Private",79682,"10th",6,"Never-married","Priv-house-serv","Other-relative","White","Male",0,0,30,"United-States","<=50K" +40,"Private",192259,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +31,"Local-gov",190228,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +42,"Private",118947,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +53,"Private",55861,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",238433,"1st-4th",2,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"Cuba","<=50K" +37,"State-gov",166744,"HS-grad",9,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,20,"United-States","<=50K" +54,"Private",144586,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +36,"Private",134367,"HS-grad",9,"Divorced","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +46,"Private",133616,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +46,"Private",203039,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +32,"Private",217460,"9th",5,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +42,"State-gov",212027,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +37,"Local-gov",126569,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",289960,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +54,"Private",174102,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",181716,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +46,"Local-gov",172822,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",293091,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",107443,"1st-4th",2,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Portugal","<=50K" +59,"Private",95283,"1st-4th",2,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",65278,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",134945,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,40,"United-States","<=50K" +46,"Private",169324,"HS-grad",9,"Separated","Other-service","Not-in-family","Black","Female",0,0,45,"Jamaica","<=50K" +44,"State-gov",98989,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Amer-Indian-Eskimo","Male",0,0,38,"United-States",">50K" +24,"Private",143436,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,24,"United-States","<=50K" +32,"Private",143604,"10th",6,"Married-spouse-absent","Other-service","Not-in-family","Black","Female",0,0,37,"United-States","<=50K" +35,"Private",226311,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +67,"Private",94610,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,30,"United-States",">50K" +56,"Self-emp-not-inc",26716,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States",">50K" +26,"Private",160261,"Masters",14,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,20,"India","<=50K" +52,"Private",154342,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +38,"Self-emp-not-inc",89202,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",174704,"HS-grad",9,"Divorced","Sales","Unmarried","Black","Male",0,0,50,"United-States","<=50K" +53,"Private",153486,"HS-grad",9,"Separated","Transport-moving","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +27,"Private",360097,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",230356,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",163870,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",199753,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States",">50K" +20,"Private",333505,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"Nicaragua","<=50K" +60,"Local-gov",149281,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",138514,"Assoc-voc",11,"Divorced","Tech-support","Unmarried","Black","Female",0,0,48,"United-States","<=50K" +57,"Federal-gov",66504,"Prof-school",15,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States",">50K" +59,"Private",206487,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Private",170020,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",217605,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Wife","White","Female",0,0,40,"United-States","<=50K" +43,"Private",145711,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,72,"United-States",">50K" +17,"Private",169155,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +45,"Private",34127,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +18,"Private",110142,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +52,"Private",222646,"12th",8,"Separated","Machine-op-inspct","Other-relative","White","Female",0,0,40,"Cuba","<=50K" +18,"Private",182643,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,9,"United-States","<=50K" +20,"Private",303565,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,40,"Germany","<=50K" +34,"Private",140092,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +19,"Private",178811,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Female",0,0,20,"United-States","<=50K" +18,"?",267399,"12th",8,"Never-married","?","Own-child","White","Female",0,0,12,"United-States","<=50K" +17,"Local-gov",192387,"9th",5,"Never-married","Other-service","Own-child","White","Male",0,0,45,"United-States","<=50K" +30,"Federal-gov",127610,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +29,"Private",258862,"Bachelors",13,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +18,"Private",174926,"9th",5,"Never-married","Other-service","Own-child","White","Male",0,0,15,"?","<=50K" +50,"State-gov",238187,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","Black","Female",0,0,37,"United-States","<=50K" +22,"Private",191444,"HS-grad",9,"Never-married","Sales","Other-relative","White","Male",0,0,40,"United-States","<=50K" +21,"Private",198822,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,35,"United-States","<=50K" +39,"Self-emp-not-inc",251323,"9th",5,"Married-civ-spouse","Farming-fishing","Other-relative","White","Male",0,0,40,"Cuba","<=50K" +62,"Private",370881,"Assoc-acdm",12,"Widowed","Other-service","Not-in-family","White","Female",0,0,7,"United-States","<=50K" +32,"Private",198183,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +38,"Private",210610,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Private",46746,"11th",7,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +28,"Private",120475,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +26,"Private",135845,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +41,"Private",310255,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",211013,"Assoc-voc",11,"Married-civ-spouse","Other-service","Other-relative","White","Female",0,0,50,"Mexico","<=50K" +50,"Private",175029,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +49,"Self-emp-inc",119539,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"?",">50K" +26,"Private",247025,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,65,"United-States","<=50K" +39,"Private",252327,"7th-8th",4,"Never-married","Other-service","Own-child","White","Male",0,0,40,"Mexico","<=50K" +24,"Self-emp-not-inc",375313,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +56,"Private",107165,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,18,"United-States","<=50K" +17,"Private",108470,"11th",7,"Never-married","Other-service","Own-child","Black","Male",0,0,17,"United-States","<=50K" +37,"Private",150057,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States",">50K" +23,"Private",189468,"Assoc-voc",11,"Married-civ-spouse","Machine-op-inspct","Own-child","White","Female",0,0,30,"United-States","<=50K" +28,"?",198393,"HS-grad",9,"Never-married","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +57,"Self-emp-not-inc",181031,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +42,"Local-gov",569930,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States",">50K" +25,"Private",27411,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",147397,"Bachelors",13,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +39,"Private",242922,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +54,"Private",154949,"11th",7,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,40,"United-States",">50K" +41,"Self-emp-inc",423217,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +43,"Federal-gov",195385,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +19,"Private",100009,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",191628,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",340880,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"Philippines",">50K" +19,"Private",207173,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,30,"United-States","<=50K" +33,"Private",48010,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",229051,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,52,"United-States","<=50K" +49,"Private",193366,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +31,"Private",57781,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States","<=50K" +69,"?",121136,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,13,"United-States","<=50K" +24,"Private",136687,"HS-grad",9,"Separated","Machine-op-inspct","Unmarried","Other","Female",0,0,40,"United-States","<=50K" +45,"State-gov",154117,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,38,"United-States",">50K" +75,"Private",239038,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,16,"United-States","<=50K" +34,"Private",244064,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +33,"Private",66278,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",162643,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,43,"United-States","<=50K" +18,"Private",205218,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +48,"Private",154033,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Female",0,0,52,"United-States","<=50K" +43,"Private",158528,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +35,"Private",301862,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,50,"United-States","<=50K" +34,"Private",228406,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +48,"Private",120131,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,70,"United-States",">50K" +54,"Local-gov",127943,"HS-grad",9,"Widowed","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +57,"Private",301514,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",156980,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,60,"United-States","<=50K" +28,"Private",124685,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","Amer-Indian-Eskimo","Male",0,0,55,"United-States","<=50K" +51,"Private",305673,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Canada",">50K" +34,"Local-gov",31391,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,53,"United-States",">50K" +41,"Local-gov",33658,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,45,"United-States",">50K" +21,"Private",211391,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,27,"United-States","<=50K" +26,"Private",402998,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,58,"United-States",">50K" +66,"Private",78855,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +48,"Private",49278,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"?",248876,"Bachelors",13,"Divorced","?","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +41,"Private",242586,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Local-gov",296085,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +43,"Private",233130,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Male",0,0,40,"United-States",">50K" +51,"Private",189511,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"Germany",">50K" +31,"Private",124420,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",194908,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +31,"Local-gov",94991,"HS-grad",9,"Divorced","Other-service","Unmarried","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +18,"Private",194561,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,37,"United-States","<=50K" +29,"Private",60722,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +33,"Private",59944,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",220840,"5th-6th",3,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"Mexico","<=50K" +40,"Self-emp-inc",104235,"Masters",14,"Never-married","Other-service","Own-child","White","Male",0,0,99,"United-States","<=50K" +57,"Private",142714,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +55,"Local-gov",110490,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,60,"United-States","<=50K" +40,"Self-emp-not-inc",154076,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +26,"State-gov",130557,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +29,"Private",107108,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +30,"Private",207172,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"Mexico","<=50K" +29,"Private",304595,"Masters",14,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +43,"Private",475322,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +65,"Private",107620,"11th",7,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +19,"Private",301911,"Some-college",10,"Never-married","Sales","Own-child","Asian-Pac-Islander","Male",0,0,35,"Laos","<=50K" +28,"Private",269786,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",167474,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +63,"Local-gov",86590,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,32,"United-States","<=50K" +47,"State-gov",187087,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",184307,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",57889,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +59,"Private",157932,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",187830,"Masters",14,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,62,"United-States",">50K" +60,"Private",317083,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +35,"Self-emp-not-inc",190895,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +48,"Federal-gov",328606,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"?",403860,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",215479,"HS-grad",9,"Separated","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +56,"Private",157639,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"Private",152129,"12th",8,"Never-married","Other-service","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +53,"Private",239284,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +23,"Private",234302,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +58,"Private",218724,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +61,"Private",106330,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",35032,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,60,"United-States","<=50K" +22,"Private",234641,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",218322,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +90,"Private",47929,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",142411,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"?",219122,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"State-gov",44464,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +22,"?",199426,"Some-college",10,"Never-married","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",139703,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +33,"Private",202642,"Bachelors",13,"Separated","Prof-specialty","Other-relative","Black","Female",0,0,40,"Jamaica","<=50K" +17,"Private",160049,"10th",6,"Never-married","Other-service","Own-child","White","Female",0,0,12,"United-States","<=50K" +38,"Private",239755,"11th",7,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +60,"Private",152369,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +34,"Private",42900,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +72,"?",117017,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,8,"United-States","<=50K" +57,"Private",175017,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Italy","<=50K" +39,"Private",342642,"HS-grad",9,"Divorced","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +50,"Self-emp-not-inc",143730,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,80,"United-States","<=50K" +45,"Private",191098,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +37,"Private",208106,"Bachelors",13,"Separated","Exec-managerial","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +27,"Private",167737,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +43,"Private",315971,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States",">50K" +41,"Private",142717,"Some-college",10,"Divorced","Tech-support","Unmarried","Black","Female",0,0,36,"United-States","<=50K" +20,"Private",190227,"Masters",14,"Never-married","Exec-managerial","Own-child","White","Male",0,0,25,"United-States","<=50K" +44,"Private",79864,"Masters",14,"Separated","Exec-managerial","Unmarried","White","Female",0,0,20,"United-States","<=50K" +50,"Private",34067,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +54,"Private",222882,"HS-grad",9,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,45,"United-States","<=50K" +33,"Private",256062,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,35,"Puerto-Rico","<=50K" +22,"Private",251073,"9th",5,"Never-married","Other-service","Own-child","White","Male",0,0,50,"United-States","<=50K" +46,"Private",149949,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",165235,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","Asian-Pac-Islander","Female",0,0,40,"Philippines",">50K" +22,"?",243190,"Some-college",10,"Never-married","?","Own-child","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +57,"Self-emp-not-inc",175942,"Some-college",10,"Widowed","Exec-managerial","Other-relative","White","Male",0,0,25,"United-States","<=50K" +26,"Private",212793,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Local-gov",153312,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +55,"Local-gov",173296,"Masters",14,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,45,"United-States","<=50K" +47,"Private",120131,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",117444,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",226196,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Private",202872,"Assoc-acdm",12,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +42,"Private",176716,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States",">50K" +39,"Private",82540,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States","<=50K" +17,"?",41643,"11th",7,"Never-married","?","Own-child","White","Female",0,0,15,"United-States","<=50K" +26,"Private",197292,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +26,"Private",76491,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,20,"United-States","<=50K" +50,"Self-emp-inc",101094,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States","<=50K" +46,"Self-emp-not-inc",119944,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +26,"Private",122575,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","Asian-Pac-Islander","Male",0,0,60,"Vietnam","<=50K" +50,"Private",263200,"5th-6th",3,"Married-spouse-absent","Other-service","Unmarried","White","Female",0,0,34,"Mexico","<=50K" +47,"Local-gov",140644,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",202115,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,25,"United-States","<=50K" +25,"Federal-gov",27142,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Local-gov",318046,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",276369,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +30,"Private",67187,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Amer-Indian-Eskimo","Female",0,0,8,"United-States","<=50K" +23,"Private",133582,"1st-4th",2,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,36,"Mexico","<=50K" +23,"Private",216672,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,30,"?","<=50K" +32,"Private",45796,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States","<=50K" +29,"Self-emp-inc",31778,"HS-grad",9,"Separated","Prof-specialty","Other-relative","White","Male",0,0,25,"United-States","<=50K" +40,"Private",190044,"Assoc-acdm",12,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"State-gov",144351,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +17,"?",172145,"10th",6,"Never-married","?","Own-child","Black","Female",0,0,40,"United-States","<=50K" +55,"Private",193130,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Local-gov",140478,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +23,"Private",116830,"12th",8,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +37,"Local-gov",117683,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",106491,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +22,"?",39803,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +27,"Private",363053,"9th",5,"Never-married","Priv-house-serv","Unmarried","White","Female",0,0,24,"Mexico","<=50K" +21,"Private",54472,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +38,"Private",54317,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,60,"United-States","<=50K" +27,"Private",159623,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"?",161235,"Assoc-voc",11,"Never-married","?","Own-child","White","Male",0,0,90,"United-States","<=50K" +27,"Private",247978,"HS-grad",9,"Never-married","Other-service","Own-child","Black","Female",0,0,40,"United-States","<=50K" +40,"Private",305846,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +33,"Private",226525,"HS-grad",9,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +28,"Private",247819,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,5,"United-States","<=50K" +28,"Private",194940,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",289991,"HS-grad",9,"Never-married","Transport-moving","Unmarried","White","Male",0,0,55,"United-States","<=50K" +46,"Private",585361,"9th",5,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",91145,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +65,"?",231604,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,45,"Germany","<=50K" +28,"Private",273269,"Some-college",10,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +39,"Private",202683,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",159179,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Private",28952,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,39,"United-States","<=50K" +25,"?",214925,"10th",6,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +63,"Private",163708,"9th",5,"Widowed","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +56,"Private",200235,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +46,"Private",109209,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +19,"Private",166153,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,30,"United-States","<=50K" +56,"Local-gov",268213,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,35,"?",">50K" +31,"Private",69056,"HS-grad",9,"Divorced","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +51,"State-gov",237141,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +17,"Private",277541,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,5,"United-States","<=50K" +27,"Local-gov",289039,"Some-college",10,"Never-married","Protective-serv","Unmarried","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +30,"Private",134737,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,45,"United-States","<=50K" +18,"Private",56613,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Female",0,0,20,"United-States","<=50K" +40,"Local-gov",333530,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,40,"United-States",">50K" +35,"Private",185366,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +29,"Private",154017,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,10,"United-States","<=50K" +53,"Private",191565,"1st-4th",2,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"Dominican-Republic","<=50K" +53,"Private",111939,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"United-States","<=50K" +26,"State-gov",53903,"HS-grad",9,"Never-married","Craft-repair","Unmarried","White","Male",0,0,50,"United-States","<=50K" +41,"Private",146659,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,70,"United-States","<=50K" +28,"Private",194200,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +48,"State-gov",78529,"Masters",14,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +22,"Private",194829,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +57,"Private",300908,"Assoc-acdm",12,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,75,"United-States","<=50K" +53,"Self-emp-not-inc",187830,"Assoc-voc",11,"Separated","Craft-repair","Not-in-family","White","Male",0,0,40,"Poland","<=50K" +23,"Private",201138,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,8,"United-States","<=50K" +31,"Self-emp-not-inc",44503,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",381357,"9th",5,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,28,"United-States","<=50K" +25,"Private",311124,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +37,"Private",96330,"Some-college",10,"Never-married","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +50,"Private",228238,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +34,"Self-emp-not-inc",56964,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States","<=50K" +37,"Private",127772,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Private",386397,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +29,"Self-emp-not-inc",404998,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,90,"United-States","<=50K" +31,"Private",157886,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,40,"United-States","<=50K" +47,"Private",101299,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",134447,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,70,"United-States","<=50K" +27,"Private",191822,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,50,"United-States","<=50K" +23,"Private",70919,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"Private",266343,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,46,"United-States","<=50K" +28,"Private",87239,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Local-gov",236487,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"Germany","<=50K" +30,"Private",224147,"HS-grad",9,"Never-married","Transport-moving","Own-child","Black","Male",0,0,40,"United-States","<=50K" +23,"Private",197200,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,60,"United-States","<=50K" +19,"Private",124265,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,50,"United-States","<=50K" +22,"Private",79980,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,25,"United-States","<=50K" +50,"Private",128814,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,25,"United-States","<=50K" +64,"?",208862,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,50,"United-States",">50K" +21,"Private",51262,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,35,"United-States","<=50K" +75,"Self-emp-inc",98116,"Some-college",10,"Widowed","Sales","Not-in-family","White","Male",0,0,40,"United-States",">50K" +29,"Private",82393,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Asian-Pac-Islander","Male",0,0,40,"Germany","<=50K" +47,"Private",57534,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +20,"Private",218962,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",204752,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +45,"Private",243631,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,45,"China",">50K" +41,"Private",170299,"Assoc-voc",11,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,43,"United-States","<=50K" +23,"Private",60331,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +67,"State-gov",132819,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,41,"United-States",">50K" +21,"Private",119665,"Some-college",10,"Never-married","Tech-support","Own-child","White","Male",0,0,35,"United-States","<=50K" +38,"Private",150057,"Some-college",10,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +31,"Private",128567,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +19,"?",230874,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +59,"Self-emp-not-inc",148526,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"Private",160192,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",74660,"Some-college",10,"Widowed","Prof-specialty","Unmarried","White","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-inc",142494,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",122042,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Self-emp-inc",37088,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +36,"Private",61778,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +21,"?",176356,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,10,"Germany","<=50K" +27,"Private",123302,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"Poland","<=50K" +18,"Private",89760,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +56,"Private",104945,"7th-8th",4,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-inc",192973,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States",">50K" +48,"Private",97863,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"Italy",">50K" +31,"Private",73585,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +35,"Private",29145,"Assoc-voc",11,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +35,"Private",175232,"HS-grad",9,"Divorced","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +36,"Private",325374,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",129345,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,25,"United-States","<=50K" +21,"Private",228395,"Some-college",10,"Never-married","Sales","Other-relative","Black","Female",0,0,20,"United-States","<=50K" +49,"Private",452402,"Some-college",10,"Separated","Exec-managerial","Unmarried","Black","Female",0,0,60,"United-States","<=50K" +46,"Private",165138,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",193122,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"?",425497,"Assoc-acdm",12,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +48,"Private",191858,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",297155,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +29,"Local-gov",181282,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +50,"Federal-gov",111700,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +18,"Private",35065,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","Black","Male",0,0,35,"United-States","<=50K" +51,"Self-emp-not-inc",95435,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +31,"Private",162160,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,47,"United-States","<=50K" +48,"Private",197683,"Some-college",10,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States",">50K" +39,"Private",290321,"10th",6,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Local-gov",44064,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +27,"?",174163,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"United-States",">50K" +42,"Private",374790,"9th",5,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",231562,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,33,"United-States","<=50K" +27,"Private",376150,"Some-college",10,"Married-spouse-absent","Sales","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +51,"Private",99987,"10th",6,"Separated","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +27,"Self-emp-not-inc",120126,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Self-emp-not-inc",33717,"11th",7,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +36,"Private",132879,"1st-4th",2,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Italy","<=50K" +45,"Private",304570,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,60,"China",">50K" +40,"Private",100292,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,52,"United-States",">50K" +41,"Private",239833,"HS-grad",9,"Married-spouse-absent","Transport-moving","Unmarried","Black","Male",0,0,50,"United-States","<=50K" +53,"?",155233,"12th",8,"Married-civ-spouse","?","Wife","White","Female",0,0,40,"Italy","<=50K" +34,"Private",347166,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",502752,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States",">50K" +22,"State-gov",255575,"Assoc-acdm",12,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,15,"United-States","<=50K" +49,"Private",277946,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +43,"?",214541,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,35,"United-States","<=50K" +36,"Private",143123,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +27,"Private",69132,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,37,"United-States","<=50K" +29,"Private",236992,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,50,"United-States","<=50K" +27,"Private",492263,"10th",6,"Separated","Machine-op-inspct","Own-child","White","Male",0,0,35,"Mexico","<=50K" +42,"Private",180019,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,65,"United-States","<=50K" +49,"Self-emp-not-inc",47086,"Bachelors",13,"Widowed","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",222853,"Some-college",10,"Never-married","Craft-repair","Unmarried","White","Male",0,0,50,"United-States","<=50K" +22,"Private",344176,"HS-grad",9,"Never-married","Sales","Unmarried","White","Male",0,0,20,"United-States","<=50K" +30,"Self-emp-not-inc",223212,"Bachelors",13,"Never-married","Sales","Unmarried","White","Male",0,0,40,"United-States","<=50K" +28,"Private",110981,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +20,"Private",162688,"Assoc-voc",11,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",306440,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,66,"France","<=50K" +18,"Private",210311,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +53,"Private",127117,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +74,"Private",54732,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,20,"United-States",">50K" +39,"Private",271521,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,48,"Philippines",">50K" +33,"?",216908,"10th",6,"Never-married","?","Other-relative","White","Male",0,0,40,"United-States","<=50K" +49,"Private",543922,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,42,"United-States",">50K" +21,"Private",766115,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,35,"United-States","<=50K" +65,"?",52728,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"Private",122206,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,25,"United-States","<=50K" +20,"?",95989,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +46,"Self-emp-not-inc",225456,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-not-inc",171840,"HS-grad",9,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,16,"United-States","<=50K" +48,"Private",180695,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +44,"Private",121012,"9th",5,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-inc",126569,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +51,"Self-emp-not-inc",290290,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +33,"Local-gov",251521,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +55,"Self-emp-not-inc",41938,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,8,"United-States","<=50K" +25,"Private",27678,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,60,"United-States","<=50K" +26,"Private",133756,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +54,"Private",215990,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",461337,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,33,"United-States","<=50K" +20,"State-gov",214542,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Private",258170,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Federal-gov",242147,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","Other","Male",0,0,45,"United-States","<=50K" +42,"Private",235700,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",278130,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"Private",261241,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States",">50K" +60,"Private",85995,"Masters",14,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,50,"South",">50K" +42,"Private",340885,"HS-grad",9,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,44,"United-States","<=50K" +42,"Private",152889,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +46,"Private",195023,"HS-grad",9,"Married-spouse-absent","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"Columbia","<=50K" +27,"?",249463,"Assoc-voc",11,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +43,"Private",158177,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +43,"State-gov",47818,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",391468,"11th",7,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",231043,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +38,"?",281768,"7th-8th",4,"Divorced","?","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +44,"Private",267790,"9th",5,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +27,"Private",217379,"Some-college",10,"Divorced","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +50,"Private",421561,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",50953,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +22,"Private",138504,"Some-college",10,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +36,"State-gov",177064,"Some-college",10,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +59,"Private",184493,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",104089,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",149204,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Local-gov",137296,"Assoc-acdm",12,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,38,"United-States","<=50K" +31,"Private",59083,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,35,"United-States","<=50K" +28,"Local-gov",138332,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +24,"Private",198914,"HS-grad",9,"Never-married","Sales","Unmarried","Black","Male",0,0,25,"United-States","<=50K" +29,"Private",123677,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","Asian-Pac-Islander","Female",0,0,40,"Laos","<=50K" +38,"Federal-gov",325538,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +53,"Private",251063,"Some-college",10,"Separated","Exec-managerial","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +39,"Private",175681,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,60,"?","<=50K" +44,"Private",165599,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +46,"Private",149640,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Male",0,0,45,"England",">50K" +30,"Private",143526,"Bachelors",13,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +24,"Private",211160,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",342989,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +62,"Self-emp-not-inc",173631,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States","<=50K" +25,"Private",141876,"HS-grad",9,"Married-spouse-absent","Exec-managerial","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +45,"Private",137604,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +21,"Private",129232,"Some-college",10,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +64,"Federal-gov",271550,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",456922,"Bachelors",13,"Divorced","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +60,"Private",232242,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",352188,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",114967,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Private",201981,"HS-grad",9,"Divorced","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +32,"State-gov",159247,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Private",125905,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",186824,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Local-gov",121012,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +58,"Private",110844,"Masters",14,"Widowed","Sales","Not-in-family","White","Female",0,0,27,"United-States","<=50K" +31,"Federal-gov",59732,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +28,"Private",178489,"Bachelors",13,"Never-married","Exec-managerial","Unmarried","Black","Female",0,0,45,"?","<=50K" +41,"?",252127,"Some-college",10,"Widowed","?","Unmarried","Black","Female",0,0,20,"United-States","<=50K" +37,"Private",109633,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,16,"United-States",">50K" +19,"Private",160811,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,38,"United-States","<=50K" +27,"Self-emp-not-inc",365110,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +61,"Self-emp-not-inc",113080,"9th",5,"Married-civ-spouse","Sales","Husband","White","Male",0,0,58,"United-States",">50K" +39,"Private",206074,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +25,"Private",173062,"Bachelors",13,"Never-married","Handlers-cleaners","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +58,"Private",117273,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +27,"Self-emp-not-inc",153805,"Some-college",10,"Married-civ-spouse","Transport-moving","Other-relative","Other","Male",0,0,50,"Ecuador",">50K" +51,"Private",293802,"5th-6th",3,"Married-civ-spouse","Handlers-cleaners","Husband","Black","Male",0,0,52,"United-States","<=50K" +46,"Private",166809,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +67,"?",34122,"5th-6th",3,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Local-gov",231725,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",63210,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,15,"United-States","<=50K" +35,"Private",108293,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,32,"United-States",">50K" +57,"Private",116878,"1st-4th",2,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Italy","<=50K" +40,"Private",110622,"Prof-school",15,"Married-civ-spouse","Adm-clerical","Other-relative","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +42,"Local-gov",180318,"10th",6,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,35,"United-States","<=50K" +67,"Self-emp-inc",112318,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",27153,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +26,"Private",73312,"11th",7,"Never-married","Machine-op-inspct","Unmarried","White","Female",0,0,15,"United-States","<=50K" +51,"Private",145409,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +38,"Private",167882,"Some-college",10,"Widowed","Other-service","Other-relative","Black","Female",0,0,45,"Haiti","<=50K" +24,"Private",236696,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Own-child","White","Male",0,0,35,"United-States","<=50K" +48,"Self-emp-not-inc",28791,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,50,"United-States","<=50K" +35,"Private",189922,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"?",584259,"Masters",14,"Married-civ-spouse","?","Husband","White","Male",0,0,2,"United-States",">50K" +26,"Private",173992,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +64,"Private",253759,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,3,"United-States","<=50K" +26,"Private",111243,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +39,"Self-emp-not-inc",147850,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,30,"United-States","<=50K" +55,"Private",171015,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,36,"United-States","<=50K" +23,"Private",118023,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,45,"?","<=50K" +33,"Self-emp-not-inc",361497,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",137290,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +28,"Local-gov",401886,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,20,"United-States","<=50K" +50,"Private",201882,"Masters",14,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,30,"United-States","<=50K" +26,"Local-gov",30793,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,55,"United-States",">50K" +51,"Private",210736,"HS-grad",9,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +34,"Private",167781,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",144592,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",493034,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +27,"Private",184078,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +44,"Private",191814,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +24,"Private",329852,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Private",223660,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +47,"Private",177087,"Some-college",10,"Separated","Adm-clerical","Unmarried","White","Female",0,0,50,"United-States",">50K" +30,"Private",143766,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +35,"Private",234271,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Federal-gov",314822,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +42,"Private",195584,"Assoc-acdm",12,"Separated","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",126850,"Prof-school",15,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +36,"Private",279485,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +44,"Private",267717,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,42,"United-States",">50K" +42,"?",175935,"HS-grad",9,"Separated","?","Unmarried","White","Male",0,0,40,"United-States","<=50K" +20,"Private",163665,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Female",0,0,17,"United-States","<=50K" +29,"Private",200468,"10th",6,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",91501,"HS-grad",9,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,40,"United-States","<=50K" +30,"Private",182771,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +31,"Private",20511,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +21,"Private",538822,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +26,"Private",332008,"Some-college",10,"Never-married","Craft-repair","Unmarried","Asian-Pac-Islander","Male",0,0,37,"Taiwan","<=50K" +57,"Self-emp-inc",220789,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +59,"Self-emp-not-inc",114760,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States",">50K" +87,"?",90338,"HS-grad",9,"Widowed","?","Not-in-family","White","Male",0,0,2,"United-States","<=50K" +25,"Private",181576,"Some-college",10,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +32,"State-gov",542265,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",193026,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",25505,"Assoc-voc",11,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,35,"United-States","<=50K" +17,"Private",375657,"11th",7,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,30,"United-States","<=50K" +44,"Private",201599,"11th",7,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",181820,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,20,"United-States","<=50K" +30,"State-gov",54318,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",141388,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,55,"United-States","<=50K" +54,"Self-emp-not-inc",57101,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,35,"United-States","<=50K" +44,"Private",168515,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"Germany","<=50K" +60,"Private",163665,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,16,"United-States",">50K" +39,"Private",293291,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,50,"United-States",">50K" +55,"Private",70088,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",199346,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +33,"Private",207201,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,55,"United-States",">50K" +40,"Local-gov",293809,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,20,"United-States","<=50K" +30,"Private",378009,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +40,"Private",226608,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Male",0,0,30,"Guatemala",">50K" +24,"Private",314182,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +18,"Private",170544,"11th",7,"Never-married","Sales","Own-child","White","Male",0,0,20,"United-States","<=50K" +18,"Private",94196,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,25,"United-States","<=50K" +49,"Private",193047,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +42,"Private",112607,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +28,"Local-gov",146949,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",309513,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +48,"Self-emp-not-inc",191389,"Some-college",10,"Separated","Sales","Unmarried","White","Female",0,0,50,"United-States","<=50K" +24,"Private",213902,"7th-8th",4,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,32,"El-Salvador","<=50K" +73,"Self-emp-not-inc",46514,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,25,"United-States","<=50K" +23,"Private",38707,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,60,"United-States",">50K" +19,"Private",188568,"Some-college",10,"Never-married","Priv-house-serv","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",215014,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"Mexico","<=50K" +27,"Private",184477,"12th",8,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",204235,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Private",39054,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,20,"United-States","<=50K" +64,"Self-emp-inc",272531,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",358701,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,10,"Mexico","<=50K" +47,"Private",217750,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,35,"United-States","<=50K" +22,"Private",200374,"HS-grad",9,"Never-married","Machine-op-inspct","Other-relative","White","Male",0,0,35,"United-States","<=50K" +24,"Private",498349,"Bachelors",13,"Never-married","Transport-moving","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +69,"State-gov",170458,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,20,"United-States","<=50K" +40,"Self-emp-not-inc",57233,"Assoc-voc",11,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +45,"Private",188432,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Private",225779,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +48,"Private",46677,"Assoc-acdm",12,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,42,"United-States","<=50K" +41,"Private",227968,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","Black","Female",0,0,35,"Haiti",">50K" +34,"Private",85355,"Bachelors",13,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"Private",207120,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",224640,"Assoc-acdm",12,"Never-married","Exec-managerial","Own-child","White","Female",0,0,40,"United-States","<=50K" +39,"Private",139012,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +40,"Federal-gov",130749,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",204516,"10th",6,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +20,"Private",105479,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +41,"Private",197093,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-inc",431245,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",155150,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"State-gov",216035,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",388247,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Private",208908,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +23,"Private",259301,"HS-grad",9,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",167893,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,64,"United-States",">50K" +54,"Private",146551,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,54,"United-States",">50K" +48,"Private",238360,"Bachelors",13,"Separated","Adm-clerical","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +38,"Private",187748,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +48,"State-gov",50748,"Bachelors",13,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",50136,"5th-6th",3,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +42,"Private",111483,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States",">50K" +31,"Private",298871,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"China","<=50K" +27,"Private",147340,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,50,"United-States",">50K" +44,"Federal-gov",243636,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Local-gov",194417,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +24,"Private",236696,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Private",337130,"1st-4th",2,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +29,"Private",273051,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,52,"Yugoslavia",">50K" +38,"Private",186191,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States","<=50K" +33,"Private",268451,"Some-college",10,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +61,"Private",154600,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,4,"United-States","<=50K" +49,"Local-gov",405309,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Self-emp-not-inc",99185,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",191765,"HS-grad",9,"Divorced","Other-service","Other-relative","Black","Female",0,0,35,"United-States","<=50K" +21,"Private",253583,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +29,"?",297054,"HS-grad",9,"Divorced","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +54,"Private",204397,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +23,"Private",288771,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +52,"Private",173987,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +23,"Private",91658,"Some-college",10,"Divorced","Handlers-cleaners","Own-child","White","Male",0,0,40,"United-States","<=50K" +43,"Private",226902,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,80,"United-States",">50K" +45,"Private",232586,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +51,"Self-emp-not-inc",291755,"7th-8th",4,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States","<=50K" +29,"?",207032,"HS-grad",9,"Married-spouse-absent","?","Unmarried","Black","Female",0,0,42,"Haiti","<=50K" +23,"Private",161478,"Some-college",10,"Never-married","Sales","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +73,"Self-emp-not-inc",109833,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +47,"Self-emp-not-inc",229394,"11th",7,"Divorced","Exec-managerial","Unmarried","White","Female",0,0,55,"United-States","<=50K" +61,"?",69285,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,37,"United-States","<=50K" +26,"Private",491862,"Assoc-voc",11,"Never-married","Exec-managerial","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +40,"Private",311534,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Self-emp-not-inc",420895,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,47,"United-States","<=50K" +39,"Private",226374,"10th",6,"Divorced","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +33,"Federal-gov",101345,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +35,"Private",48779,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,35,"United-States","<=50K" +42,"Private",152676,"HS-grad",9,"Divorced","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Private",164877,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +33,"Private",97521,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +47,"Private",88564,"5th-6th",3,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,20,"United-States","<=50K" +33,"Private",188246,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",189185,"HS-grad",9,"Divorced","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +42,"State-gov",163069,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +28,"Private",251905,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",112403,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"?","<=50K" +18,"Private",36882,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +33,"Self-emp-not-inc",195891,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +36,"Private",194905,"Bachelors",13,"Widowed","Prof-specialty","Unmarried","White","Female",0,0,44,"United-States","<=50K" +40,"Private",31621,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Private",196029,"HS-grad",9,"Divorced","Transport-moving","Unmarried","White","Male",0,0,45,"United-States","<=50K" +36,"Private",107302,"HS-grad",9,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,50,"United-States","<=50K" +45,"Private",151267,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","Black","Female",0,0,40,"United-States",">50K" +52,"Private",256861,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Private",82777,"HS-grad",9,"Separated","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Private",147430,"HS-grad",9,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"?",60726,"HS-grad",9,"Never-married","?","Own-child","Black","Male",0,0,40,"United-States","<=50K" +46,"Self-emp-not-inc",165754,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +36,"Private",448337,"HS-grad",9,"Separated","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +48,"Private",185079,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +36,"Private",418702,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +48,"Private",41504,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States",">50K" +18,"Private",261720,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +38,"Private",133963,"Bachelors",13,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States",">50K" +66,"?",357750,"11th",7,"Widowed","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +38,"Private",60135,"HS-grad",9,"Never-married","Transport-moving","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +55,"Self-emp-not-inc",308746,"Prof-school",15,"Widowed","Prof-specialty","Not-in-family","White","Male",0,0,55,"United-States",">50K" +27,"Private",278720,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States",">50K" +22,"State-gov",477505,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +29,"Private",164711,"Some-college",10,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"United-States","<=50K" +40,"Private",208277,"Some-college",10,"Never-married","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States","<=50K" +21,"Private",39943,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +49,"Private",104542,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +29,"Private",286634,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,50,"United-States",">50K" +28,"Private",142712,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +26,"Private",336404,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +33,"Private",117983,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,41,"United-States","<=50K" +72,"?",108796,"Prof-school",15,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Private",59469,"Masters",14,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"Iran","<=50K" +37,"Private",171968,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +56,"?",119254,"10th",6,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",278617,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +39,"Private",72338,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +49,"Local-gov",343231,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,80,"United-States","<=50K" +30,"Private",63910,"HS-grad",9,"Married-civ-spouse","Sales","Own-child","Asian-Pac-Islander","Female",0,0,40,"United-States","<=50K" +28,"Private",190350,"9th",5,"Married-civ-spouse","Protective-serv","Wife","Black","Female",0,0,40,"United-States","<=50K" +25,"State-gov",176162,"Bachelors",13,"Never-married","Protective-serv","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",37720,"10th",6,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +25,"Private",421467,"Assoc-acdm",12,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,26,"United-States","<=50K" +36,"Private",138441,"Some-college",10,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +52,"Private",146767,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +25,"Private",160445,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Private",211695,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +48,"Private",128796,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +39,"Private",111129,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Local-gov",44566,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",118497,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +49,"Private",237920,"Doctorate",16,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +34,"Local-gov",136331,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States","<=50K" +28,"Private",187397,"HS-grad",9,"Never-married","Other-service","Other-relative","Other","Male",0,0,48,"Mexico","<=50K" +28,"Self-emp-not-inc",119793,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +26,"Self-emp-not-inc",231714,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +54,"Private",229272,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States",">50K" +66,"?",68219,"9th",5,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Self-emp-not-inc",268831,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,53,"United-States","<=50K" +45,"Self-emp-not-inc",149640,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,30,"United-States",">50K" +29,"Private",261725,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +74,"Private",161387,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +61,"Local-gov",260167,"HS-grad",9,"Widowed","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",200928,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,22,"United-States","<=50K" +53,"Federal-gov",155594,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +57,"Self-emp-not-inc",79539,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +41,"Private",469454,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",331482,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +43,"Private",225193,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",82393,"HS-grad",9,"Married-civ-spouse","Other-service","Own-child","Asian-Pac-Islander","Male",0,0,25,"Philippines","<=50K" +65,"?",37170,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,20,"United-States","<=50K" +41,"Private",58484,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,40,"United-States","<=50K" +31,"Local-gov",156464,"Bachelors",13,"Never-married","Prof-specialty","Other-relative","White","Male",0,0,40,"?","<=50K" +50,"Private",344621,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +52,"Private",174752,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +18,"Self-emp-inc",174202,"HS-grad",9,"Never-married","Transport-moving","Own-child","White","Male",0,0,60,"United-States","<=50K" +26,"Private",261203,"7th-8th",4,"Never-married","Other-service","Unmarried","Other","Female",0,0,30,"?","<=50K" +57,"Private",316000,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",246933,"HS-grad",9,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +34,"Private",264651,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",99185,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,58,"United-States","<=50K" +39,"Private",176186,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",100219,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,45,"United-States","<=50K" +32,"Private",46691,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"State-gov",297735,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,90,"United-States","<=50K" +25,"Private",189656,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,60,"United-States",">50K" +54,"Local-gov",224934,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +48,"Self-emp-inc",149218,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,70,"United-States",">50K" +51,"Private",158508,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +67,"State-gov",261203,"7th-8th",4,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,35,"United-States","<=50K" +17,"Private",309504,"10th",6,"Never-married","Sales","Unmarried","White","Female",0,0,24,"United-States","<=50K" +24,"State-gov",324637,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",267426,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +68,"?",229016,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,25,"United-States","<=50K" +54,"Private",46401,"Some-college",10,"Divorced","Other-service","Not-in-family","White","Female",0,0,47,"United-States","<=50K" +32,"Private",114288,"HS-grad",9,"Divorced","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +61,"?",203849,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Federal-gov",193882,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +53,"Private",311269,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Private",156117,"Assoc-voc",11,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +64,"?",169917,"7th-8th",4,"Widowed","?","Not-in-family","White","Female",0,0,4,"United-States","<=50K" +51,"Private",222615,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Federal-gov",78036,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,65,"United-States",">50K" +27,"Private",380560,"HS-grad",9,"Never-married","Farming-fishing","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +51,"Private",289436,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +36,"Private",749636,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-inc",154120,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,55,"United-States","<=50K" +43,"Private",105119,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +61,"Federal-gov",181081,"HS-grad",9,"Divorced","Adm-clerical","Own-child","Black","Female",0,0,20,"United-States","<=50K" +31,"Private",182237,"10th",6,"Separated","Transport-moving","Unmarried","White","Male",0,0,40,"United-States","<=50K" +34,"Private",102130,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,65,"United-States",">50K" +52,"Private",170562,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",240543,"11th",7,"Never-married","Other-service","Own-child","White","Female",0,0,20,"United-States","<=50K" +37,"Federal-gov",187046,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +60,"Private",389254,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +47,"Private",179955,"Some-college",10,"Widowed","Transport-moving","Unmarried","White","Female",0,0,25,"Outlying-US(Guam-USVI-etc)","<=50K" +21,"Private",197997,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,30,"United-States","<=50K" +40,"Local-gov",141649,"Assoc-voc",11,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",433906,"Assoc-acdm",12,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +48,"Private",207982,"Some-college",10,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +46,"Private",175925,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,40,"United-States","<=50K" +58,"Private",85767,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,48,"United-States","<=50K" +32,"Self-emp-inc",281030,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +90,"?",313986,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +38,"Private",396595,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States",">50K" +20,"?",189203,"Assoc-acdm",12,"Never-married","?","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +43,"Self-emp-not-inc",163108,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,99,"United-States","<=50K" +17,"Private",141590,"11th",7,"Never-married","Priv-house-serv","Own-child","White","Female",0,0,12,"United-States","<=50K" +36,"Private",137421,"12th",8,"Never-married","Transport-moving","Not-in-family","Asian-Pac-Islander","Male",0,0,45,"?","<=50K" +45,"Private",330087,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",204322,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",50295,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States","<=50K" +35,"Self-emp-not-inc",147258,"Assoc-voc",11,"Never-married","Farming-fishing","Own-child","White","Male",0,0,65,"United-States","<=50K" +19,"Private",194260,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +56,"Private",437727,"9th",5,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +64,"?",34100,"Some-college",10,"Widowed","?","Not-in-family","White","Male",0,0,4,"United-States","<=50K" +62,"?",186611,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +24,"Private",280960,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,24,"United-States","<=50K" +33,"Private",33117,"Assoc-acdm",12,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",169628,"Bachelors",13,"Never-married","Sales","Unmarried","Black","Female",0,0,35,"United-States",">50K" +22,"State-gov",124942,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,45,"United-States","<=50K" +44,"Private",143368,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Male",0,0,55,"United-States","<=50K" +37,"Private",255621,"HS-grad",9,"Separated","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +34,"Self-emp-inc",154227,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,75,"United-States","<=50K" +43,"Private",171438,"Assoc-voc",11,"Separated","Sales","Unmarried","White","Female",0,0,45,"United-States","<=50K" +39,"Private",191524,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +30,"Private",377017,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,32,"United-States","<=50K" +58,"Private",192806,"7th-8th",4,"Never-married","Handlers-cleaners","Not-in-family","White","Female",0,0,33,"United-States","<=50K" +31,"?",259120,"Some-college",10,"Married-civ-spouse","?","Wife","White","Female",0,0,10,"United-States","<=50K" +45,"Local-gov",234195,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +30,"Private",147596,"Some-college",10,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +42,"Private",147251,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,36,"United-States","<=50K" +50,"Private",176157,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +25,"Local-gov",176162,"Assoc-voc",11,"Never-married","Protective-serv","Own-child","White","Male",0,0,30,"United-States","<=50K" +34,"Private",384150,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",107665,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +72,"?",82635,"11th",7,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"State-gov",165827,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +71,"Self-emp-not-inc",78786,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,10,"United-States","<=50K" +22,"Private",349368,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Female",0,0,30,"United-States","<=50K" +52,"Private",117674,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +30,"Private",310889,"Some-college",10,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +36,"?",187167,"HS-grad",9,"Separated","?","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +40,"Private",379919,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +31,"Federal-gov",34862,"Assoc-acdm",12,"Married-civ-spouse","Sales","Husband","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +38,"Local-gov",161463,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","Black","Male",0,0,40,"United-States",">50K" +46,"Private",186410,"Prof-school",15,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States",">50K" +57,"Federal-gov",62020,"Prof-school",15,"Divorced","Exec-managerial","Not-in-family","Black","Male",0,0,55,"United-States",">50K" +39,"Private",42044,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"Private",170230,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States",">50K" +43,"Private",341358,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",199426,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,17,"United-States","<=50K" +44,"Private",89172,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +22,"?",148955,"Some-college",10,"Never-married","?","Own-child","Asian-Pac-Islander","Female",0,0,15,"South","<=50K" +37,"Private",140673,"Some-college",10,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +20,"?",71788,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,18,"United-States","<=50K" +26,"State-gov",326033,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,80,"United-States","<=50K" +35,"Private",129305,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +28,"Private",171067,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","White","Female",0,0,40,"United-States","<=50K" +34,"Private",143582,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Asian-Pac-Islander","Female",0,0,35,"Japan","<=50K" +17,"?",171461,"10th",6,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +18,"Private",257980,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +25,"Private",182866,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-inc",69333,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +61,"Private",668362,"1st-4th",2,"Widowed","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +39,"Private",132879,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +19,"?",166018,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",120518,"HS-grad",9,"Widowed","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +19,"Private",183532,"Some-college",10,"Never-married","Handlers-cleaners","Own-child","White","Male",0,0,25,"United-States","<=50K" +45,"Private",49298,"Bachelors",13,"Never-married","Tech-support","Own-child","White","Male",0,0,40,"United-States","<=50K" +20,"Private",157332,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +37,"Private",213726,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +26,"Private",31143,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +17,"?",256173,"10th",6,"Never-married","?","Own-child","White","Female",0,0,15,"United-States","<=50K" +26,"Private",184872,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,55,"United-States",">50K" +58,"Private",202652,"HS-grad",9,"Separated","Other-service","Unmarried","White","Female",0,0,40,"Dominican-Republic","<=50K" +61,"?",101602,"Doctorate",16,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States",">50K" +19,"Private",292590,"HS-grad",9,"Married-civ-spouse","Sales","Other-relative","White","Female",0,0,25,"United-States","<=50K" +36,"Private",141420,"Bachelors",13,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +47,"Private",159389,"Assoc-acdm",12,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +62,"Private",254534,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"State-gov",89508,"Prof-school",15,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +38,"Self-emp-not-inc",238980,"Some-college",10,"Never-married","Sales","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +54,"Private",178946,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States",">50K" +31,"Private",204752,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +26,"Private",290213,"Some-college",10,"Separated","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",291965,"Some-college",10,"Never-married","Tech-support","Unmarried","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +52,"Local-gov",175339,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +28,"Private",90547,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,23,"United-States","<=50K" +23,"?",449101,"HS-grad",9,"Married-civ-spouse","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +32,"?",981628,"HS-grad",9,"Divorced","?","Unmarried","Black","Male",0,0,40,"United-States","<=50K" +59,"?",147989,"HS-grad",9,"Widowed","?","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +30,"Self-emp-inc",204470,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,36,"United-States",">50K" +31,"Private",190027,"HS-grad",9,"Never-married","Other-service","Other-relative","Black","Female",0,0,40,"?","<=50K" +36,"Private",218015,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,48,"United-States","<=50K" +31,"State-gov",77634,"Preschool",1,"Never-married","Other-service","Not-in-family","White","Male",0,0,24,"United-States","<=50K" +52,"Self-emp-not-inc",42984,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,70,"United-States",">50K" +48,"Self-emp-not-inc",218835,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"England","<=50K" +58,"Private",252419,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States","<=50K" +20,"Federal-gov",347935,"Some-college",10,"Never-married","Protective-serv","Own-child","Black","Male",0,0,40,"United-States","<=50K" +19,"Private",237848,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,3,"United-States","<=50K" +63,"Private",174826,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +51,"Self-emp-not-inc",170086,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,45,"United-States",">50K" +53,"Private",470368,"Assoc-acdm",12,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,48,"United-States","<=50K" +35,"?",35854,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,40,"United-States","<=50K" +26,"Private",746432,"HS-grad",9,"Never-married","Handlers-cleaners","Own-child","Black","Male",0,0,48,"United-States","<=50K" +47,"Self-emp-not-inc",258498,"Some-college",10,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,52,"United-States","<=50K" +44,"Private",176063,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +80,"Self-emp-not-inc",26865,"7th-8th",4,"Never-married","Farming-fishing","Unmarried","White","Male",0,0,20,"United-States","<=50K" +55,"Private",104724,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +43,"Private",346321,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +49,"Private",402462,"Bachelors",13,"Married-spouse-absent","Transport-moving","Unmarried","White","Male",0,0,30,"Columbia","<=50K" +27,"Private",153078,"Prof-school",15,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Male",0,0,40,"United-States","<=50K" +39,"Private",451059,"9th",5,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"?",229533,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",106437,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +58,"Local-gov",294313,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","Black","Female",0,0,55,"United-States","<=50K" +63,"Private",67903,"9th",5,"Separated","Farming-fishing","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +49,"Private",133669,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Self-emp-inc",251730,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,60,"United-States",">50K" +46,"Private",72896,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +39,"Private",206520,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +33,"Private",72338,"Prof-school",15,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,65,"Japan",">50K" +30,"Private",236543,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,68,"United-States","<=50K" +39,"Local-gov",43702,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,37,"United-States","<=50K" +44,"Private",335248,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",198197,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +80,"?",281768,"Assoc-acdm",12,"Married-civ-spouse","?","Husband","White","Male",0,0,4,"United-States","<=50K" +31,"Private",160594,"Assoc-acdm",12,"Never-married","Prof-specialty","Own-child","White","Male",0,0,3,"United-States","<=50K" +34,"Local-gov",231826,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"El-Salvador","<=50K" +28,"Private",188171,"Assoc-acdm",12,"Never-married","Transport-moving","Own-child","White","Male",0,0,60,"United-States","<=50K" +55,"Private",125000,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Private",166509,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +67,"Local-gov",204123,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,10,"United-States","<=50K" +53,"Self-emp-inc",220786,"Some-college",10,"Widowed","Sales","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +29,"Local-gov",152461,"Bachelors",13,"Never-married","Tech-support","Not-in-family","White","Female",0,0,42,"United-States","<=50K" +19,"Private",223669,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +51,"Private",120270,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +21,"Self-emp-not-inc",304602,"Assoc-voc",11,"Never-married","Farming-fishing","Own-child","White","Male",0,0,98,"United-States","<=50K" +54,"Private",24108,"Some-college",10,"Separated","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +41,"Private",93885,"Some-college",10,"Divorced","Sales","Unmarried","White","Female",0,0,48,"United-States","<=50K" +28,"Private",210765,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",191276,"Assoc-voc",11,"Divorced","Handlers-cleaners","Unmarried","White","Female",0,0,40,"United-States","<=50K" +82,"Self-emp-not-inc",71438,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,20,"United-States","<=50K" +23,"Private",330571,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,16,"United-States","<=50K" +40,"Local-gov",138634,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Private",112264,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +24,"Private",205865,"HS-grad",9,"Never-married","Sales","Unmarried","White","Male",0,0,45,"United-States","<=50K" +21,"Private",224640,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +27,"Private",180758,"Some-college",10,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,30,"United-States","<=50K" +29,"?",499935,"Assoc-voc",11,"Never-married","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +40,"Self-emp-not-inc",107762,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +17,"Private",214787,"12th",8,"Never-married","Adm-clerical","Own-child","White","Female",0,0,25,"United-States","<=50K" +27,"Private",211032,"1st-4th",2,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +34,"Private",208353,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +18,"Private",157273,"10th",6,"Never-married","Other-service","Other-relative","Black","Male",0,0,15,"United-States","<=50K" +39,"Private",75891,"Bachelors",13,"Divorced","Tech-support","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Self-emp-inc",177675,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,65,"United-States",">50K" +44,"Private",182370,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"?",200525,"11th",7,"Never-married","?","Own-child","White","Female",0,0,25,"United-States","<=50K" +28,"Private",95566,"1st-4th",2,"Married-spouse-absent","Other-service","Own-child","Other","Female",0,0,35,"Dominican-Republic","<=50K" +30,"Private",30290,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +60,"Private",240951,"HS-grad",9,"Divorced","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +58,"Private",183810,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,24,"United-States","<=50K" +49,"Private",94342,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States","<=50K" +61,"Self-emp-inc",148577,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +27,"Private",103634,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +59,"Self-emp-not-inc",83542,"Assoc-acdm",12,"Divorced","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +52,"Federal-gov",76131,"Some-college",10,"Married-civ-spouse","Exec-managerial","Wife","Asian-Pac-Islander","Female",0,0,40,"United-States",">50K" +42,"Federal-gov",262402,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +27,"Private",198286,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,34,"United-States","<=50K" +41,"Self-emp-inc",145441,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +35,"?",273558,"Some-college",10,"Never-married","?","Not-in-family","Black","Male",0,0,30,"United-States","<=50K" +50,"Local-gov",117496,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,24,"United-States","<=50K" +36,"Private",128876,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"Private",199698,"HS-grad",9,"Never-married","Farming-fishing","Own-child","White","Male",0,0,45,"United-States","<=50K" +38,"Private",65390,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +46,"Private",128645,"Some-college",10,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +59,"Private",53481,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +55,"Private",92215,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +59,"Self-emp-inc",187502,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +38,"Private",242080,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,55,"United-States",">50K" +22,"Private",41837,"Some-college",10,"Never-married","Transport-moving","Own-child","White","Male",0,0,25,"United-States","<=50K" +28,"Private",291374,"12th",8,"Never-married","Sales","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +59,"Private",159008,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,56,"United-States","<=50K" +37,"Private",271013,"HS-grad",9,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",199046,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +34,"Private",164280,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"Portugal","<=50K" +55,"Private",100054,"10th",6,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +18,"Private",183824,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,30,"United-States","<=50K" +48,"Private",313925,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,30,"United-States",">50K" +48,"Private",379883,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Cuba",">50K" +70,"?",92593,"Some-college",10,"Widowed","?","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +27,"Private",189777,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",198330,"Masters",14,"Widowed","Prof-specialty","Unmarried","Black","Female",0,0,37,"United-States","<=50K" +32,"Private",127451,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,38,"United-States",">50K" +62,"?",31577,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,18,"United-States","<=50K" +18,"?",90230,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,20,"United-States","<=50K" +50,"Private",301024,"Bachelors",13,"Separated","Sales","Not-in-family","White","Male",0,0,40,"United-States",">50K" +38,"Self-emp-not-inc",175732,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",0,0,15,"United-States","<=50K" +18,"Private",218889,"9th",5,"Never-married","Other-service","Own-child","Black","Male",0,0,35,"United-States","<=50K" +46,"Private",117605,"9th",5,"Divorced","Sales","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +26,"Private",154571,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","Asian-Pac-Islander","Male",0,0,45,"United-States",">50K" +44,"Private",228057,"7th-8th",4,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"Dominican-Republic","<=50K" +32,"Private",173998,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +25,"Private",90752,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +55,"Private",51008,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +55,"Federal-gov",113398,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Male",0,0,40,"United-States","<=50K" +25,"Private",74977,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,40,"United-States","<=50K" +40,"Private",101593,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +29,"Private",228346,"Assoc-voc",11,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +60,"Private",180418,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",44489,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States","<=50K" +43,"Self-emp-not-inc",277488,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +24,"Private",103064,"HS-grad",9,"Never-married","Sales","Own-child","White","Female",0,0,55,"United-States","<=50K" +34,"Private",226872,"Bachelors",13,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Self-emp-not-inc",330416,"Some-college",10,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +24,"Private",186495,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +47,"State-gov",205712,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,38,"United-States","<=50K" +18,"Private",217743,"11th",7,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +22,"Private",239954,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Male",0,0,40,"United-States","<=50K" +49,"Self-emp-not-inc",349986,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +68,"Self-emp-not-inc",122094,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,15,"United-States","<=50K" +62,"Self-emp-not-inc",26857,"7th-8th",4,"Widowed","Farming-fishing","Other-relative","White","Female",0,0,35,"United-States","<=50K" +25,"Local-gov",192321,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +24,"Private",88095,"Some-college",10,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,24,"Mexico","<=50K" +44,"Private",144067,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,12,"?","<=50K" +32,"Private",124187,"9th",5,"Married-civ-spouse","Farming-fishing","Husband","Black","Male",0,0,40,"United-States","<=50K" +49,"Private",123681,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,43,"United-States",">50K" +68,"Private",145638,"Some-college",10,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",130513,"Assoc-acdm",12,"Never-married","Sales","Own-child","White","Female",0,0,40,"Peru","<=50K" +47,"Federal-gov",197038,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +35,"Private",189092,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +37,"Self-emp-not-inc",198841,"11th",7,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",317969,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States","<=50K" +34,"Private",111589,"10th",6,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"Jamaica","<=50K" +46,"Local-gov",267952,"Assoc-voc",11,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,36,"United-States","<=50K" +21,"Private",63899,"11th",7,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +26,"Private",473625,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","White","Female",0,0,30,"United-States","<=50K" +17,"Private",24090,"HS-grad",9,"Never-married","Exec-managerial","Own-child","White","Female",0,0,35,"United-States","<=50K" +36,"Self-emp-inc",102729,"Assoc-acdm",12,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,70,"United-States","<=50K" +33,"Private",91666,"12th",8,"Divorced","Exec-managerial","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",215873,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","Black","Male",0,0,40,"United-States","<=50K" +32,"Private",152109,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +24,"Private",175586,"HS-grad",9,"Never-married","Machine-op-inspct","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +37,"Private",232614,"HS-grad",9,"Divorced","Other-service","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +53,"State-gov",229465,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +43,"Local-gov",161240,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,45,"United-States",">50K" +29,"Private",358124,"HS-grad",9,"Never-married","Other-service","Other-relative","Black","Female",0,0,52,"United-States","<=50K" +47,"Private",222529,"Bachelors",13,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,65,"United-States","<=50K" +37,"Self-emp-not-inc",338320,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +23,"Private",263886,"Some-college",10,"Never-married","Sales","Not-in-family","Black","Female",0,0,20,"United-States","<=50K" +50,"Private",310774,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,35,"United-States","<=50K" +25,"Private",98155,"Some-college",10,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +40,"Private",259307,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +41,"Private",29762,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States",">50K" +32,"Private",202729,"HS-grad",9,"Married-civ-spouse","Transport-moving","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",28790,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"Private",53209,"HS-grad",9,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Local-gov",169020,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +34,"Private",127195,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Private",211731,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"Mexico","<=50K" +42,"Self-emp-not-inc",126614,"Bachelors",13,"Divorced","Exec-managerial","Not-in-family","Other","Male",0,0,30,"Iran","<=50K" +45,"Private",259463,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",228411,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +25,"Private",117827,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Federal-gov",57216,"Some-college",10,"Never-married","Adm-clerical","Own-child","Black","Male",0,0,20,"United-States","<=50K" +48,"Self-emp-inc",88564,"Some-college",10,"Divorced","Farming-fishing","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +45,"Private",172822,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,52,"United-States",">50K" +19,"Private",251579,"Some-college",10,"Never-married","Other-service","Own-child","White","Male",0,0,14,"United-States","<=50K" +31,"Private",118399,"11th",7,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Self-emp-inc",178383,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,70,"United-States","<=50K" +40,"Self-emp-not-inc",170866,"Assoc-acdm",12,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States",">50K" +60,"?",268954,"Some-college",10,"Married-civ-spouse","?","Husband","White","Male",0,0,12,"United-States",">50K" +52,"?",89951,"12th",8,"Married-civ-spouse","?","Wife","Black","Female",0,0,40,"United-States",">50K" +22,"Private",203894,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,15,"United-States","<=50K" +25,"Private",237065,"Some-college",10,"Divorced","Other-service","Own-child","Black","Male",0,0,38,"United-States","<=50K" +51,"Local-gov",108435,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,80,"United-States",">50K" +32,"Private",93213,"Assoc-acdm",12,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,62,"United-States","<=50K" +51,"Self-emp-inc",231230,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,25,"United-States","<=50K" +42,"Private",386175,"Some-college",10,"Divorced","Sales","Not-in-family","White","Male",0,0,50,"United-States",">50K" +24,"Private",223515,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +58,"?",97969,"1st-4th",2,"Married-spouse-absent","?","Unmarried","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +43,"Private",174295,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +31,"Private",60229,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +28,"Private",66095,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +26,"Private",192022,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Female",0,0,40,"United-States","<=50K" +46,"Private",45288,"Bachelors",13,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +62,"?",178764,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",99476,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +18,"Private",41973,"11th",7,"Never-married","Adm-clerical","Own-child","White","Female",0,0,5,"United-States","<=50K" +23,"Private",162228,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,48,"United-States","<=50K" +46,"Private",211226,"Assoc-acdm",12,"Married-civ-spouse","Transport-moving","Husband","Other","Male",0,0,36,"United-States","<=50K" +38,"Private",33397,"HS-grad",9,"Divorced","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +53,"Private",120839,"12th",8,"Divorced","Farming-fishing","Own-child","White","Male",0,0,40,"United-States","<=50K" +53,"Private",36327,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +50,"Private",139703,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +26,"Private",107827,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Male",0,0,25,"United-States","<=50K" +44,"Local-gov",203761,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +36,"Local-gov",114719,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +20,"Private",344394,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +35,"Private",195516,"7th-8th",4,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"Mexico","<=50K" +40,"State-gov",31627,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,20,"United-States","<=50K" +70,"Private",174032,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +57,"Private",226875,"7th-8th",4,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States","<=50K" +18,"Private",36162,"11th",7,"Never-married","Craft-repair","Own-child","White","Male",0,0,5,"United-States","<=50K" +52,"Private",294991,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +24,"?",108495,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +42,"Self-emp-inc",161532,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,60,"United-States","<=50K" +28,"Local-gov",332249,"HS-grad",9,"Separated","Transport-moving","Own-child","White","Male",0,0,45,"United-States","<=50K" +32,"Private",268147,"Assoc-voc",11,"Never-married","Tech-support","Unmarried","White","Female",0,0,60,"United-States","<=50K" +56,"Federal-gov",317847,"Bachelors",13,"Divorced","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +44,"Private",52028,"1st-4th",2,"Married-civ-spouse","Other-service","Wife","Asian-Pac-Islander","Female",0,0,40,"Vietnam","<=50K" +20,"Private",184045,"Some-college",10,"Never-married","Sales","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +32,"Private",206609,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +32,"Private",313835,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +51,"Self-emp-inc",260938,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +23,"Private",335067,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +34,"Private",331126,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Male",0,0,30,"United-States","<=50K" +53,"Private",156612,"12th",8,"Divorced","Transport-moving","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",188436,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,45,"United-States","<=50K" +60,"Private",227468,"Some-college",10,"Widowed","Protective-serv","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +55,"Private",183580,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,38,"United-States","<=50K" +57,"Self-emp-not-inc",50990,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,30,"United-States","<=50K" +59,"Private",384246,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +26,"?",375313,"Some-college",10,"Never-married","?","Own-child","Asian-Pac-Islander","Male",0,0,40,"Philippines","<=50K" +49,"Private",93639,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,43,"United-States","<=50K" +45,"Private",30289,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Self-emp-inc",124950,"Bachelors",13,"Never-married","Sales","Own-child","White","Female",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",126675,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,60,"United-States",">50K" +21,"Private",145964,"12th",8,"Never-married","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +36,"State-gov",345712,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"?",97474,"HS-grad",9,"Never-married","?","Own-child","White","Female",0,0,20,"United-States","<=50K" +37,"Private",180342,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +19,"Private",167087,"HS-grad",9,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +65,"?",192825,"7th-8th",4,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States","<=50K" +30,"Private",318749,"Assoc-voc",11,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,35,"Germany","<=50K" +27,"?",147638,"Masters",14,"Never-married","?","Not-in-family","Other","Female",0,0,40,"Japan","<=50K" +59,"Federal-gov",293971,"Some-college",10,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States",">50K" +32,"Private",229566,"Assoc-voc",11,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,60,"United-States",">50K" +25,"Private",242464,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",111067,"Bachelors",13,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,80,"United-States",">50K" +21,"?",155697,"9th",5,"Never-married","?","Own-child","White","Male",0,0,42,"United-States","<=50K" +49,"Local-gov",106554,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,40,"United-States",">50K" +49,"Private",23776,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"?",43909,"HS-grad",9,"Divorced","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +48,"Private",105808,"9th",5,"Widowed","Transport-moving","Unmarried","White","Male",0,0,40,"United-States",">50K" +42,"Private",169995,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States","<=50K" +53,"Private",141388,"11th",7,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Self-emp-not-inc",241431,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +21,"?",78374,"HS-grad",9,"Never-married","?","Other-relative","Asian-Pac-Islander","Female",0,0,24,"United-States","<=50K" +54,"Self-emp-not-inc",158948,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,15,"United-States","<=50K" +34,"Private",272411,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +62,"?",263374,"Assoc-voc",11,"Married-civ-spouse","?","Husband","White","Male",0,0,40,"Canada","<=50K" +30,"Private",190228,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",126060,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +25,"Private",391192,"Assoc-voc",11,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +26,"Private",214069,"HS-grad",9,"Separated","Farming-fishing","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +55,"Private",118993,"Some-college",10,"Separated","Exec-managerial","Unmarried","White","Female",0,0,10,"United-States","<=50K" +26,"Private",245880,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,40,"United-States","<=50K" +45,"Private",174794,"Bachelors",13,"Separated","Prof-specialty","Unmarried","White","Female",0,0,56,"Germany","<=50K" +61,"Local-gov",153408,"Masters",14,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States",">50K" +34,"?",330301,"7th-8th",4,"Separated","?","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +26,"Private",385278,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Black","Male",0,0,60,"United-States","<=50K" +44,"Federal-gov",38434,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +45,"Self-emp-not-inc",111679,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,30,"United-States","<=50K" +55,"Private",168956,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",86143,"Some-college",10,"Never-married","Other-service","Other-relative","Asian-Pac-Islander","Male",0,0,30,"United-States","<=50K" +48,"Private",99835,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +33,"Private",263561,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,60,"United-States","<=50K" +44,"Private",118536,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +32,"Self-emp-inc",209691,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"Canada","<=50K" +54,"Private",123374,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +40,"Private",137225,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +29,"Private",119359,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Wife","Asian-Pac-Islander","Female",0,0,10,"China",">50K" +56,"Private",134153,"10th",6,"Married-civ-spouse","Adm-clerical","Husband","Black","Male",0,0,40,"United-States","<=50K" +47,"Private",121124,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",147655,"Some-college",10,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +46,"Private",165138,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Federal-gov",312017,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +37,"Private",272950,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",259323,"HS-grad",9,"Divorced","Craft-repair","Unmarried","White","Male",0,0,40,"United-States","<=50K" +21,"Private",119156,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,40,"United-States","<=50K" +55,"Private",165881,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +23,"State-gov",136075,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +50,"Private",187465,"11th",7,"Divorced","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +44,"Private",328561,"Assoc-voc",11,"Married-civ-spouse","Adm-clerical","Other-relative","White","Female",0,0,20,"United-States","<=50K" +48,"Private",350440,"Some-college",10,"Married-civ-spouse","Craft-repair","Other-relative","Asian-Pac-Islander","Male",0,0,40,"Cambodia",">50K" +38,"Self-emp-not-inc",109133,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,70,"United-States",">50K" +39,"Private",86643,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +52,"Federal-gov",154521,"HS-grad",9,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,44,"United-States",">50K" +63,"Private",45912,"HS-grad",9,"Widowed","Other-service","Other-relative","White","Female",0,0,40,"United-States","<=50K" +37,"Private",338033,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +26,"State-gov",158963,"Masters",14,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",119964,"HS-grad",9,"Never-married","Craft-repair","Other-relative","White","Female",0,0,15,"United-States","<=50K" +34,"Private",193344,"Some-college",10,"Never-married","Adm-clerical","Unmarried","White","Female",0,0,40,"Germany","<=50K" +29,"Local-gov",45554,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +33,"Private",249716,"HS-grad",9,"Never-married","Tech-support","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +53,"Private",58985,"Some-college",10,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,24,"United-States","<=50K" +24,"Private",456367,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +39,"Private",117381,"Some-college",10,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +31,"Private",226443,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",364342,"Assoc-voc",11,"Never-married","Sales","Not-in-family","Black","Female",0,0,25,"United-States","<=50K" +42,"Local-gov",101593,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,42,"United-States","<=50K" +23,"Private",267471,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,25,"United-States","<=50K" +22,"Private",186849,"11th",7,"Divorced","Sales","Own-child","White","Male",0,0,50,"United-States","<=50K" +65,"Private",174603,"5th-6th",3,"Widowed","Machine-op-inspct","Not-in-family","White","Female",0,0,10,"Italy","<=50K" +34,"Private",115040,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,44,"United-States","<=50K" +45,"Self-emp-not-inc",49595,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,80,"United-States","<=50K" +19,"Private",127491,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +23,"Private",122272,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,20,"United-States","<=50K" +37,"Private",143771,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +59,"Private",91384,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"State-gov",135874,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +51,"Private",172493,"Some-college",10,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,12,"United-States","<=50K" +42,"Local-gov",189956,"Bachelors",13,"Divorced","Prof-specialty","Unmarried","Black","Female",0,0,30,"United-States","<=50K" +35,"Private",106967,"Masters",14,"Never-married","Sales","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +20,"Private",200153,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,38,"United-States","<=50K" +41,"Private",151736,"10th",6,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +40,"Private",67852,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +36,"Private",54229,"Assoc-acdm",12,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,37,"United-States","<=50K" +34,"Self-emp-inc",154120,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States",">50K" +44,"Self-emp-not-inc",157217,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,42,"United-States","<=50K" +31,"Federal-gov",381645,"Bachelors",13,"Separated","Prof-specialty","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +41,"Local-gov",160785,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",133584,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +43,"Private",170230,"Masters",14,"Never-married","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +19,"Private",128363,"Some-college",10,"Never-married","Sales","Own-child","White","Female",0,0,30,"United-States","<=50K" +43,"Local-gov",163434,"Bachelors",13,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,55,"United-States",">50K" +50,"Private",195690,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,45,"United-States","<=50K" +44,"Self-emp-inc",138991,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +46,"Private",118419,"HS-grad",9,"Divorced","Machine-op-inspct","Unmarried","White","Male",0,0,38,"United-States","<=50K" +52,"Self-emp-not-inc",185407,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +52,"Self-emp-not-inc",283079,"HS-grad",9,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +18,"Private",119655,"12th",8,"Never-married","Adm-clerical","Own-child","White","Female",0,0,12,"United-States","<=50K" +29,"Private",153416,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States","<=50K" +19,"?",204868,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,36,"United-States","<=50K" +34,"Private",220362,"Bachelors",13,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +23,"Local-gov",203078,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","Black","Male",0,0,40,"United-States","<=50K" +64,"State-gov",104361,"Some-college",10,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,65,"United-States","<=50K" +68,"Private",274096,"10th",6,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +42,"State-gov",455553,"HS-grad",9,"Never-married","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",112283,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,60,"United-States",">50K" +41,"Self-emp-inc",64506,"HS-grad",9,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States","<=50K" +22,"State-gov",24395,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States","<=50K" +27,"Private",100669,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","Asian-Pac-Islander","Male",0,0,40,"Philippines",">50K" +25,"Private",178025,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +49,"?",113913,"HS-grad",9,"Married-civ-spouse","?","Wife","White","Female",0,0,60,"United-States","<=50K" +28,"Private",55191,"Assoc-acdm",12,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +23,"Local-gov",162551,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Asian-Pac-Islander","Female",0,0,35,"China","<=50K" +19,"Private",693066,"12th",8,"Never-married","Other-service","Own-child","White","Female",0,0,15,"United-States","<=50K" +72,"?",96867,"5th-6th",3,"Widowed","?","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",256362,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +53,"Private",539864,"Some-college",10,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,20,"United-States","<=50K" +35,"Private",241153,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",284395,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +18,"Private",180039,"12th",8,"Never-married","Sales","Own-child","White","Female",0,0,20,"United-States","<=50K" +45,"Private",178416,"Assoc-voc",11,"Divorced","Handlers-cleaners","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",175710,"Bachelors",13,"Never-married","Adm-clerical","Not-in-family","White","Female",0,0,30,"?","<=50K" +22,"Local-gov",164775,"5th-6th",3,"Never-married","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Guatemala",">50K" +55,"Private",176897,"Some-college",10,"Divorced","Tech-support","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +22,"Private",193090,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +28,"Private",175262,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +19,"Private",109928,"11th",7,"Never-married","Sales","Own-child","Black","Female",0,0,35,"United-States","<=50K" +50,"Private",177896,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States",">50K" +31,"Private",181372,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,35,"United-States","<=50K" +40,"Private",70645,"Preschool",1,"Never-married","Other-service","Not-in-family","White","Female",0,0,20,"United-States","<=50K" +51,"Private",128272,"9th",5,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +56,"Private",106723,"HS-grad",9,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +21,"Private",122348,"Some-college",10,"Never-married","Tech-support","Own-child","White","Female",0,0,35,"United-States","<=50K" +22,"Private",254547,"Some-college",10,"Never-married","Exec-managerial","Unmarried","Black","Female",0,0,40,"Jamaica","<=50K" +44,"Private",33105,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +30,"Private",215441,"Some-college",10,"Never-married","Adm-clerical","Not-in-family","Other","Male",0,0,40,"?","<=50K" +44,"Local-gov",197919,"Some-college",10,"Divorced","Other-service","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",206139,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States",">50K" +47,"Private",117849,"Assoc-acdm",12,"Divorced","Sales","Own-child","White","Male",0,0,44,"United-States","<=50K" +26,"Private",323044,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"Germany",">50K" +34,"Private",90415,"Assoc-voc",11,"Never-married","Tech-support","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +36,"Private",127573,"HS-grad",9,"Separated","Adm-clerical","Not-in-family","White","Female",0,0,38,"United-States","<=50K" +21,"Private",180190,"Assoc-voc",11,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,46,"United-States","<=50K" +45,"State-gov",231013,"Bachelors",13,"Divorced","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +33,"Private",356015,"HS-grad",9,"Separated","Craft-repair","Not-in-family","Amer-Indian-Eskimo","Male",0,0,35,"Hong","<=50K" +33,"Private",198069,"HS-grad",9,"Never-married","Machine-op-inspct","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +58,"Self-emp-not-inc",99141,"HS-grad",9,"Divorced","Farming-fishing","Unmarried","White","Female",0,0,10,"United-States","<=50K" +31,"Private",188246,"Assoc-acdm",12,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States",">50K" +32,"Self-emp-not-inc",116508,"Some-college",10,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,50,"United-States",">50K" +44,"Federal-gov",38434,"Bachelors",13,"Widowed","Exec-managerial","Unmarried","White","Female",0,0,40,"United-States",">50K" +24,"Private",128477,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +49,"Private",185041,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Self-emp-not-inc",103925,"Bachelors",13,"Married-civ-spouse","Sales","Wife","White","Female",0,0,50,"United-States","<=50K" +42,"Self-emp-not-inc",34037,"Bachelors",13,"Never-married","Farming-fishing","Own-child","White","Male",0,0,35,"United-States","<=50K" +19,"Private",57145,"HS-grad",9,"Never-married","Other-service","Own-child","White","Female",0,0,25,"United-States","<=50K" +41,"Private",182108,"Doctorate",16,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States",">50K" +51,"Self-emp-inc",213296,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,30,"United-States","<=50K" +51,"Self-emp-inc",28765,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +63,"Private",37792,"10th",6,"Widowed","Other-service","Not-in-family","White","Female",0,0,31,"United-States","<=50K" +39,"Federal-gov",232036,"Some-college",10,"Married-civ-spouse","Adm-clerical","Husband","White","Male",0,0,40,"United-States",">50K" +30,"Private",33678,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +62,"Without-pay",159908,"Some-college",10,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,16,"United-States","<=50K" +27,"Private",176761,"HS-grad",9,"Never-married","Craft-repair","Other-relative","Other","Male",0,0,40,"Nicaragua","<=50K" +37,"Local-gov",180342,"Bachelors",13,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States",">50K" +42,"Private",204235,"HS-grad",9,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",249720,"Assoc-voc",11,"Married-spouse-absent","Sales","Unmarried","Black","Female",0,0,32,"United-States","<=50K" +42,"Local-gov",201495,"Some-college",10,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,72,"United-States",">50K" +38,"Private",447346,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,36,"United-States",">50K" +24,"Private",206008,"Assoc-acdm",12,"Never-married","Prof-specialty","Own-child","Black","Male",0,0,20,"United-States","<=50K" +34,"Private",286020,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,45,"United-States","<=50K" +20,"?",99891,"Some-college",10,"Never-married","?","Own-child","White","Female",0,0,30,"United-States","<=50K" +29,"Local-gov",169544,"Some-college",10,"Never-married","Protective-serv","Own-child","White","Male",0,0,48,"United-States","<=50K" +90,"Private",313749,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,25,"United-States","<=50K" +55,"Private",89182,"12th",8,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"Italy","<=50K" +36,"Private",258102,"HS-grad",9,"Never-married","Handlers-cleaners","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +49,"Private",255466,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,60,"United-States","<=50K" +50,"Private",38795,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +17,"Private",311907,"11th",7,"Never-married","Other-service","Own-child","White","Male",0,0,25,"United-States","<=50K" +54,"Private",171924,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,70,"United-States","<=50K" +26,"Private",164488,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,10,"United-States","<=50K" +44,"Private",297991,"Assoc-acdm",12,"Never-married","Exec-managerial","Not-in-family","Asian-Pac-Islander","Female",0,0,50,"United-States","<=50K" +28,"Private",478315,"Bachelors",13,"Never-married","Prof-specialty","Own-child","Black","Female",0,0,40,"United-States","<=50K" +54,"Local-gov",34832,"Doctorate",16,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +21,"Private",67804,"9th",5,"Never-married","Machine-op-inspct","Own-child","Black","Male",0,0,20,"United-States","<=50K" +24,"Private",34568,"Assoc-voc",11,"Never-married","Transport-moving","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",47151,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,56,"United-States","<=50K" +59,"?",120617,"Some-college",10,"Never-married","?","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",318046,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,48,"United-States",">50K" +29,"Private",363963,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +50,"Private",92811,"Bachelors",13,"Married-civ-spouse","Tech-support","Husband","White","Male",0,0,40,"United-States","<=50K" +32,"Private",33678,"Some-college",10,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,50,"United-States",">50K" +42,"Private",66118,"Some-college",10,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +47,"Private",160474,"HS-grad",9,"Married-civ-spouse","Exec-managerial","Wife","White","Female",0,0,30,"United-States",">50K" +44,"Private",159960,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +49,"Private",242987,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"Columbia","<=50K" +61,"Private",232719,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +45,"Local-gov",162187,"HS-grad",9,"Married-civ-spouse","Protective-serv","Husband","White","Male",0,0,40,"United-States",">50K" +59,"Private",207391,"HS-grad",9,"Divorced","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +30,"Never-worked",176673,"HS-grad",9,"Married-civ-spouse","?","Wife","Black","Female",0,0,40,"United-States","<=50K" +34,"Private",356882,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +24,"Private",427686,"1st-4th",2,"Married-civ-spouse","Handlers-cleaners","Other-relative","White","Male",0,0,40,"Mexico","<=50K" +36,"Private",43712,"10th",6,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +21,"?",205939,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +34,"Private",346034,"12th",8,"Married-spouse-absent","Handlers-cleaners","Unmarried","White","Male",0,0,35,"Mexico","<=50K" +41,"Private",144460,"Some-college",10,"Divorced","Machine-op-inspct","Own-child","White","Male",0,0,40,"Italy","<=50K" +18,"Never-worked",153663,"Some-college",10,"Never-married","?","Own-child","White","Male",0,0,4,"United-States","<=50K" +26,"Private",262617,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +23,"Federal-gov",173851,"HS-grad",9,"Never-married","Armed-Forces","Not-in-family","White","Male",0,0,8,"United-States","<=50K" +63,"?",126540,"Some-college",10,"Divorced","?","Not-in-family","White","Female",0,0,5,"United-States","<=50K" +34,"Private",117963,"Bachelors",13,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States",">50K" +54,"Private",219737,"HS-grad",9,"Widowed","Sales","Not-in-family","White","Female",0,0,37,"United-States","<=50K" +37,"Private",328466,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,72,"Mexico","<=50K" +54,"State-gov",138852,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Local-gov",195532,"Some-college",10,"Never-married","Protective-serv","Other-relative","White","Female",0,0,43,"United-States","<=50K" +32,"Private",188246,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +42,"State-gov",138162,"Some-college",10,"Divorced","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"State-gov",110714,"Some-college",10,"Never-married","Other-service","Own-child","White","Female",0,0,37,"United-States","<=50K" +48,"Private",123075,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"United-States",">50K" +28,"Private",330466,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,40,"Hong","<=50K" +31,"Private",254304,"10th",6,"Divorced","Craft-repair","Not-in-family","White","Male",0,0,38,"United-States","<=50K" +28,"Private",435842,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States","<=50K" +24,"Private",118657,"12th",8,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",278188,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +26,"Private",233777,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,72,"Mexico","<=50K" +37,"Self-emp-inc",328466,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,50,"United-States",">50K" +24,"Private",176580,"5th-6th",3,"Married-spouse-absent","Farming-fishing","Not-in-family","White","Male",0,0,40,"Mexico","<=50K" +18,"?",156608,"11th",7,"Never-married","?","Own-child","White","Female",0,0,25,"United-States","<=50K" +32,"Private",172415,"HS-grad",9,"Never-married","Other-service","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +23,"Private",194951,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","Asian-Pac-Islander","Male",0,0,55,"Ireland","<=50K" +33,"Local-gov",318921,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Female",0,0,35,"United-States","<=50K" +49,"Private",189462,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +75,"Self-emp-not-inc",192813,"Masters",14,"Widowed","Sales","Not-in-family","White","Male",0,0,45,"United-States","<=50K" +26,"Private",156805,"Some-college",10,"Married-civ-spouse","Machine-op-inspct","Husband","Black","Male",0,0,40,"United-States","<=50K" +66,"?",93318,"HS-grad",9,"Widowed","?","Unmarried","White","Female",0,0,40,"United-States","<=50K" +34,"Private",121966,"Bachelors",13,"Married-spouse-absent","Adm-clerical","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +18,"Private",347336,"12th",8,"Never-married","Other-service","Own-child","White","Male",0,0,12,"United-States","<=50K" +33,"Private",205950,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +36,"State-gov",212143,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States",">50K" +44,"Private",187821,"Bachelors",13,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,55,"United-States","<=50K" +36,"Private",250807,"11th",7,"Never-married","Craft-repair","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +53,"Private",291755,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +60,"Private",36077,"7th-8th",4,"Married-spouse-absent","Machine-op-inspct","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +28,"Private",119793,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"Portugal","<=50K" +36,"Private",184655,"10th",6,"Divorced","Transport-moving","Unmarried","White","Male",0,0,48,"United-States","<=50K" +45,"Self-emp-not-inc",204405,"Assoc-voc",11,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,20,"United-States","<=50K" +23,"Private",133355,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,15,"United-States","<=50K" +35,"Private",89559,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,55,"United-States","<=50K" +34,"Private",115066,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,42,"United-States",">50K" +46,"Private",139514,"Preschool",1,"Married-civ-spouse","Machine-op-inspct","Other-relative","Black","Male",0,0,75,"Dominican-Republic","<=50K" +58,"State-gov",200316,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Local-gov",166502,"Masters",14,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +63,"Private",226422,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +41,"Self-emp-not-inc",251305,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",190482,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,76,"United-States","<=50K" +42,"Private",248356,"HS-grad",9,"Never-married","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +41,"Private",220460,"HS-grad",9,"Never-married","Sales","Own-child","White","Male",0,0,40,"United-States","<=50K" +22,"Private",174043,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +49,"Self-emp-not-inc",111959,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"Scotland",">50K" +51,"Private",40641,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,60,"United-States",">50K" +22,"Private",205940,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +23,"Private",265077,"Assoc-voc",11,"Never-married","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +59,"Private",395736,"HS-grad",9,"Married-civ-spouse","Handlers-cleaners","Husband","White","Male",0,0,40,"United-States",">50K" +40,"Private",306225,"HS-grad",9,"Divorced","Craft-repair","Not-in-family","Asian-Pac-Islander","Female",0,0,40,"Japan","<=50K" +28,"Private",180299,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,70,"United-States","<=50K" +39,"Private",214896,"HS-grad",9,"Separated","Other-service","Not-in-family","White","Female",0,0,40,"El-Salvador","<=50K" +25,"Private",273792,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,37,"United-States","<=50K" +48,"State-gov",224474,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +62,"Private",271431,"9th",5,"Married-civ-spouse","Other-service","Husband","Black","Male",0,0,42,"United-States","<=50K" +44,"Local-gov",150171,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +28,"Federal-gov",381789,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +62,"Private",170984,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,45,"United-States","<=50K" +32,"Private",108256,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +59,"Federal-gov",23789,"HS-grad",9,"Married-civ-spouse","Sales","Wife","White","Female",0,0,40,"United-States",">50K" +20,"Private",176321,"Some-college",10,"Never-married","Adm-clerical","Other-relative","White","Female",0,0,20,"United-States","<=50K" +47,"Private",248059,"Some-college",10,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,47,"United-States",">50K" +60,"Private",56248,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +55,"Private",199763,"HS-grad",9,"Separated","Protective-serv","Not-in-family","White","Male",0,0,81,"United-States","<=50K" +18,"Private",200047,"12th",8,"Never-married","Adm-clerical","Own-child","White","Male",0,0,35,"United-States","<=50K" +31,"Self-emp-not-inc",156033,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Male",0,0,35,"United-States","<=50K" +22,"Private",173736,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +56,"Private",135458,"HS-grad",9,"Divorced","Tech-support","Not-in-family","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",185660,"HS-grad",9,"Separated","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +24,"Private",222005,"HS-grad",9,"Never-married","Other-service","Other-relative","White","Male",0,0,30,"United-States","<=50K" +52,"Local-gov",143533,"7th-8th",4,"Never-married","Other-service","Other-relative","Black","Female",0,0,40,"United-States","<=50K" +42,"Private",288154,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,89,"United-States",">50K" +48,"Private",325372,"1st-4th",2,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Portugal","<=50K" +35,"Private",379959,"HS-grad",9,"Divorced","Other-service","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +33,"Private",168387,"11th",7,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +20,"Private",234640,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +33,"Private",232475,"Some-college",10,"Never-married","Sales","Own-child","White","Male",0,0,45,"United-States","<=50K" +30,"Private",205152,"Bachelors",13,"Never-married","Sales","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +31,"Private",112115,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +29,"Private",183854,"HS-grad",9,"Never-married","Sales","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +26,"Private",164386,"HS-grad",9,"Never-married","Craft-repair","Own-child","White","Male",0,0,48,"United-States","<=50K" +61,"Private",149620,"Some-college",10,"Divorced","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +45,"Private",199590,"5th-6th",3,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"?","<=50K" +29,"Private",83742,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,45,"United-States","<=50K" +57,"Self-emp-not-inc",65080,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States",">50K" +20,"Private",227778,"Some-college",10,"Never-married","Sales","Not-in-family","White","Female",0,0,56,"United-States","<=50K" +26,"Private",48280,"Bachelors",13,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Private",66304,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,55,"United-States",">50K" +23,"Private",45834,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +31,"Private",298995,"HS-grad",9,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,35,"United-States","<=50K" +47,"Private",161950,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,32,"United-States","<=50K" +61,"Private",98776,"11th",7,"Widowed","Handlers-cleaners","Not-in-family","White","Female",0,0,30,"United-States","<=50K" +35,"Private",102268,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States","<=50K" +23,"Private",180771,"1st-4th",2,"Married-civ-spouse","Machine-op-inspct","Wife","Amer-Indian-Eskimo","Female",0,0,35,"Mexico","<=50K" +20,"?",203992,"HS-grad",9,"Never-married","?","Own-child","White","Male",0,0,40,"United-States","<=50K" +41,"Private",206878,"HS-grad",9,"Divorced","Other-service","Unmarried","White","Female",0,0,32,"United-States","<=50K" +39,"Federal-gov",110622,"Bachelors",13,"Married-civ-spouse","Adm-clerical","Wife","Asian-Pac-Islander","Female",0,0,40,"Philippines","<=50K" +51,"Local-gov",203334,"Doctorate",16,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,45,"United-States",">50K" +61,"Self-emp-not-inc",50483,"7th-8th",4,"Married-civ-spouse","Farming-fishing","Husband","White","Male",0,0,56,"United-States","<=50K" +51,"Private",274502,"7th-8th",4,"Divorced","Machine-op-inspct","Not-in-family","White","Female",0,0,48,"United-States","<=50K" +36,"Private",208068,"Preschool",1,"Divorced","Other-service","Not-in-family","Other","Male",0,0,72,"Mexico","<=50K" +41,"Self-emp-not-inc",168098,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +25,"Private",175128,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +37,"Private",40955,"Prof-school",15,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States",">50K" +19,"Private",60890,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,49,"United-States","<=50K" +66,"Self-emp-not-inc",102686,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,20,"United-States",">50K" +23,"Private",190273,"Bachelors",13,"Never-married","Prof-specialty","Own-child","White","Male",0,0,40,"United-States","<=50K" +30,"Self-emp-not-inc",176185,"Some-college",10,"Married-spouse-absent","Craft-repair","Own-child","White","Male",0,0,60,"United-States",">50K" +25,"Private",390657,"Some-college",10,"Never-married","Other-service","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +51,"Private",101432,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +53,"Private",158993,"HS-grad",9,"Widowed","Machine-op-inspct","Unmarried","Black","Female",0,0,38,"United-States","<=50K" +17,"Private",117798,"10th",6,"Never-married","Other-service","Own-child","White","Male",0,0,20,"United-States","<=50K" +61,"Private",137554,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +44,"Self-emp-inc",71556,"Masters",14,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"?",">50K" +38,"Private",257416,"9th",5,"Married-civ-spouse","Transport-moving","Husband","Black","Male",0,0,40,"United-States","<=50K" +40,"Private",195617,"Some-college",10,"Separated","Exec-managerial","Unmarried","White","Female",0,0,20,"United-States","<=50K" +32,"Private",236318,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,32,"United-States","<=50K" +46,"Private",42251,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States",">50K" +50,"Private",257933,"Some-college",10,"Divorced","Adm-clerical","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +36,"Self-emp-not-inc",109133,"Bachelors",13,"Married-civ-spouse","Sales","Husband","White","Male",0,0,50,"United-States",">50K" +30,"Self-emp-not-inc",261943,"11th",7,"Married-spouse-absent","Craft-repair","Not-in-family","White","Male",0,0,30,"Honduras","<=50K" +33,"Private",139057,"Masters",14,"Married-civ-spouse","Tech-support","Husband","Asian-Pac-Islander","Male",0,0,50,"United-States",">50K" +85,"Private",98611,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,3,"Poland","<=50K" +62,"Private",128092,"HS-grad",9,"Widowed","Adm-clerical","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +24,"Private",284317,"Bachelors",13,"Never-married","Machine-op-inspct","Not-in-family","White","Female",0,0,32,"United-States","<=50K" +58,"Local-gov",223214,"HS-grad",9,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Self-emp-inc",173664,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,45,"United-States",">50K" +66,"Private",269665,"HS-grad",9,"Widowed","Exec-managerial","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +55,"Private",199713,"9th",5,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,48,"United-States","<=50K" +39,"Self-emp-not-inc",193689,"HS-grad",9,"Never-married","Exec-managerial","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +58,"Self-emp-inc",181974,"Doctorate",16,"Never-married","Prof-specialty","Not-in-family","White","Female",0,0,99,"?","<=50K" +50,"Private",485710,"Doctorate",16,"Divorced","Prof-specialty","Not-in-family","White","Female",0,0,50,"United-States","<=50K" +28,"Private",185647,"Some-college",10,"Divorced","Handlers-cleaners","Not-in-family","White","Male",0,0,50,"United-States","<=50K" +34,"Private",30673,"Masters",14,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,55,"United-States","<=50K" +36,"Private",186819,"Assoc-acdm",12,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,52,"United-States",">50K" +22,"Private",67234,"HS-grad",9,"Never-married","Handlers-cleaners","Unmarried","White","Male",0,0,45,"United-States","<=50K" +35,"Private",30673,"12th",8,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,84,"United-States","<=50K" +49,"?",114648,"12th",8,"Divorced","?","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +21,"Private",182117,"Assoc-acdm",12,"Never-married","Other-service","Own-child","White","Male",0,0,40,"United-States","<=50K" +64,"State-gov",222966,"7th-8th",4,"Married-civ-spouse","Other-service","Wife","Black","Female",0,0,40,"United-States","<=50K" +41,"Private",201495,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +52,"Private",301229,"Assoc-voc",11,"Separated","Sales","Unmarried","White","Female",0,0,40,"United-States","<=50K" +32,"Private",157747,"Some-college",10,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +27,"Private",155382,"Some-college",10,"Never-married","Other-service","Not-in-family","White","Female",0,0,25,"United-States","<=50K" +48,"Private",268083,"Some-college",10,"Divorced","Exec-managerial","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +28,"Private",113987,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +24,"Private",216984,"Some-college",10,"Married-civ-spouse","Other-service","Own-child","Asian-Pac-Islander","Female",0,0,35,"United-States","<=50K" +51,"Private",177669,"Some-college",10,"Married-civ-spouse","Sales","Husband","White","Male",0,0,60,"United-States","<=50K" +32,"Private",164190,"Some-college",10,"Never-married","Exec-managerial","Own-child","White","Male",0,0,40,"United-States","<=50K" +61,"Private",355645,"HS-grad",9,"Married-civ-spouse","Sales","Husband","Black","Male",0,0,40,"United-States","<=50K" +60,"?",134152,"9th",5,"Divorced","?","Not-in-family","Black","Male",0,0,35,"United-States","<=50K" +33,"Private",63079,"HS-grad",9,"Divorced","Adm-clerical","Unmarried","Black","Female",0,0,40,"United-States","<=50K" +42,"Self-emp-not-inc",217597,"HS-grad",9,"Divorced","Sales","Own-child","White","Male",0,0,50,"?","<=50K" +24,"Private",381895,"11th",7,"Divorced","Machine-op-inspct","Unmarried","White","Female",0,0,40,"United-States","<=50K" +82,"?",403910,"HS-grad",9,"Never-married","?","Not-in-family","White","Male",0,0,3,"United-States","<=50K" +26,"Private",179010,"Some-college",10,"Never-married","Craft-repair","Not-in-family","White","Male",0,0,65,"United-States","<=50K" +18,"Private",436163,"11th",7,"Never-married","Prof-specialty","Own-child","White","Male",0,0,20,"United-States","<=50K" +34,"Private",321709,"HS-grad",9,"Never-married","Other-service","Not-in-family","White","Female",0,0,28,"United-States","<=50K" +57,"Private",153918,"HS-grad",9,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +25,"Private",403788,"HS-grad",9,"Never-married","Craft-repair","Other-relative","Black","Male",0,0,40,"United-States","<=50K" +71,"Private",138145,"9th",5,"Married-civ-spouse","Other-service","Husband","White","Male",0,0,40,"United-States","<=50K" +35,"Local-gov",79649,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,50,"United-States","<=50K" +47,"Private",312088,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +50,"Private",208630,"Masters",14,"Divorced","Sales","Not-in-family","White","Female",0,0,50,"United-States",">50K" +33,"Private",182401,"10th",6,"Never-married","Adm-clerical","Not-in-family","Black","Male",0,0,40,"United-States","<=50K" +38,"Private",32916,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,55,"United-States",">50K" +50,"Private",302372,"Bachelors",13,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,40,"United-States","<=50K" +45,"Private",155093,"10th",6,"Divorced","Other-service","Not-in-family","Black","Female",0,0,38,"Dominican-Republic","<=50K" +32,"Private",192965,"HS-grad",9,"Separated","Sales","Not-in-family","White","Female",0,0,45,"United-States","<=50K" +39,"Private",107302,"HS-grad",9,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,45,"?",">50K" +25,"Local-gov",514716,"Bachelors",13,"Never-married","Adm-clerical","Own-child","Black","Female",0,0,40,"United-States","<=50K" +20,"Private",270436,"HS-grad",9,"Never-married","Machine-op-inspct","Own-child","White","Male",0,0,40,"United-States","<=50K" +46,"Private",42972,"Masters",14,"Married-civ-spouse","Prof-specialty","Wife","White","Female",0,0,22,"United-States",">50K" +40,"Private",142657,"Assoc-voc",11,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,45,"United-States","<=50K" +30,"Private",176175,"Assoc-voc",11,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,24,"United-States","<=50K" +36,"Private",131459,"7th-8th",4,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,40,"United-States","<=50K" +46,"Private",364548,"Some-college",10,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,48,"United-States",">50K" +27,"Private",177398,"HS-grad",9,"Never-married","Other-service","Unmarried","White","Female",0,0,64,"United-States","<=50K" +33,"Private",273243,"HS-grad",9,"Married-civ-spouse","Craft-repair","Husband","Black","Male",0,0,40,"United-States","<=50K" +58,"Private",147707,"11th",7,"Married-civ-spouse","Sales","Husband","White","Male",0,0,40,"United-States","<=50K" +30,"Private",77266,"HS-grad",9,"Divorced","Transport-moving","Not-in-family","White","Male",0,0,55,"United-States","<=50K" +26,"Private",191648,"Assoc-acdm",12,"Never-married","Machine-op-inspct","Other-relative","White","Female",0,0,15,"United-States","<=50K" +81,"?",120478,"Assoc-voc",11,"Divorced","?","Unmarried","White","Female",0,0,1,"?","<=50K" +32,"Private",211349,"10th",6,"Married-civ-spouse","Transport-moving","Husband","White","Male",0,0,40,"United-States","<=50K" +22,"Private",203715,"Some-college",10,"Never-married","Adm-clerical","Own-child","White","Male",0,0,40,"United-States","<=50K" +31,"Private",292592,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Wife","White","Female",0,0,40,"United-States","<=50K" +29,"Private",125976,"HS-grad",9,"Separated","Sales","Unmarried","White","Female",0,0,35,"United-States","<=50K" +35,"?",320084,"Bachelors",13,"Married-civ-spouse","?","Wife","White","Female",0,0,55,"United-States",">50K" +30,"?",33811,"Bachelors",13,"Never-married","?","Not-in-family","Asian-Pac-Islander","Female",0,0,99,"United-States","<=50K" +34,"Private",204461,"Doctorate",16,"Married-civ-spouse","Prof-specialty","Husband","White","Male",0,0,60,"United-States",">50K" +54,"Private",337992,"Bachelors",13,"Married-civ-spouse","Exec-managerial","Husband","Asian-Pac-Islander","Male",0,0,50,"Japan",">50K" +37,"Private",179137,"Some-college",10,"Divorced","Adm-clerical","Unmarried","White","Female",0,0,39,"United-States","<=50K" +22,"Private",325033,"12th",8,"Never-married","Protective-serv","Own-child","Black","Male",0,0,35,"United-States","<=50K" +34,"Private",160216,"Bachelors",13,"Never-married","Exec-managerial","Not-in-family","White","Female",0,0,55,"United-States",">50K" +30,"Private",345898,"HS-grad",9,"Never-married","Craft-repair","Not-in-family","Black","Male",0,0,46,"United-States","<=50K" +71,"?",287372,"Doctorate",16,"Married-civ-spouse","?","Husband","White","Male",0,0,10,"United-States",">50K" +45,"State-gov",252208,"HS-grad",9,"Separated","Adm-clerical","Own-child","White","Female",0,0,40,"United-States","<=50K" +41,"?",202822,"HS-grad",9,"Separated","?","Not-in-family","Black","Female",0,0,32,"United-States","<=50K" +72,"?",129912,"HS-grad",9,"Married-civ-spouse","?","Husband","White","Male",0,0,25,"United-States","<=50K" +45,"Local-gov",119199,"Assoc-acdm",12,"Divorced","Prof-specialty","Unmarried","White","Female",0,0,48,"United-States","<=50K" +31,"Private",199655,"Masters",14,"Divorced","Other-service","Not-in-family","Other","Female",0,0,30,"United-States","<=50K" +39,"Local-gov",111499,"Assoc-acdm",12,"Married-civ-spouse","Adm-clerical","Wife","White","Female",0,0,20,"United-States",">50K" +37,"Private",198216,"Assoc-acdm",12,"Divorced","Tech-support","Not-in-family","White","Female",0,0,40,"United-States","<=50K" +43,"Private",260761,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"Mexico","<=50K" +43,"State-gov",255835,"Some-college",10,"Divorced","Adm-clerical","Other-relative","White","Female",0,0,40,"United-States","<=50K" +43,"Self-emp-not-inc",27242,"Some-college",10,"Married-civ-spouse","Craft-repair","Husband","White","Male",0,0,50,"United-States","<=50K" +32,"Private",34066,"10th",6,"Married-civ-spouse","Handlers-cleaners","Husband","Amer-Indian-Eskimo","Male",0,0,40,"United-States","<=50K" +43,"Private",84661,"Assoc-voc",11,"Married-civ-spouse","Sales","Husband","White","Male",0,0,45,"United-States","<=50K" +32,"Private",116138,"Masters",14,"Never-married","Tech-support","Not-in-family","Asian-Pac-Islander","Male",0,0,11,"Taiwan","<=50K" +53,"Private",321865,"Masters",14,"Married-civ-spouse","Exec-managerial","Husband","White","Male",0,0,40,"United-States",">50K" +22,"Private",310152,"Some-college",10,"Never-married","Protective-serv","Not-in-family","White","Male",0,0,40,"United-States","<=50K" +27,"Private",257302,"Assoc-acdm",12,"Married-civ-spouse","Tech-support","Wife","White","Female",0,0,38,"United-States","<=50K" +40,"Private",154374,"HS-grad",9,"Married-civ-spouse","Machine-op-inspct","Husband","White","Male",0,0,40,"United-States",">50K" +58,"Private",151910,"HS-grad",9,"Widowed","Adm-clerical","Unmarried","White","Female",0,0,40,"United-States","<=50K" +22,"Private",201490,"HS-grad",9,"Never-married","Adm-clerical","Own-child","White","Male",0,0,20,"United-States","<=50K" diff --git a/tests/fixtures/compas-scores-raw.csv b/tests/fixtures/compas-scores-raw.csv new file mode 100644 index 0000000..6dc3b18 --- /dev/null +++ b/tests/fixtures/compas-scores-raw.csv @@ -0,0 +1,60844 @@ +Person_ID,AssessmentID,Case_ID,Agency_Text,LastName,FirstName,MiddleName,Sex_Code_Text,Ethnic_Code_Text,DateOfBirth,ScaleSet_ID,ScaleSet,AssessmentReason,Language,LegalStatus,CustodyStatus,MaritalStatus,Screening_Date,RecSupervisionLevel,RecSupervisionLevelText,Scale_ID,DisplayText,RawScore,DecileScore,ScoreText,AssessmentType,IsCompleted,IsDeleted +50844,57167,51950,PRETRIAL,Fisher,Kevin,NULL,Male,Caucasian,12/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +50844,57167,51950,PRETRIAL,Fisher,Kevin,NULL,Male,Caucasian,12/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +50844,57167,51950,PRETRIAL,Fisher,Kevin,NULL,Male,Caucasian,12/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50848,57174,51956,PRETRIAL,KENDALL,KEVIN,NULL,Male,Caucasian,09/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +50848,57174,51956,PRETRIAL,KENDALL,KEVIN,NULL,Male,Caucasian,09/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +50848,57174,51956,PRETRIAL,KENDALL,KEVIN,NULL,Male,Caucasian,09/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50855,57181,51963,PRETRIAL,DAYES,DANIEL,NULL,Male,African-American,08/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +50855,57181,51963,PRETRIAL,DAYES,DANIEL,NULL,Male,African-American,08/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,4,High,8,Risk of Recidivism,0.18,8,High,New,1,0 +50855,57181,51963,PRETRIAL,DAYES,DANIEL,NULL,Male,African-American,08/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50850,57176,51958,PRETRIAL,Debe,Mikerlie,George,Female,African-American,10/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/1/13 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +50850,57176,51958,PRETRIAL,Debe,Mikerlie,George,Female,African-American,10/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +50850,57176,51958,PRETRIAL,Debe,Mikerlie,George,Female,African-American,10/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/1/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +50839,57162,51945,PRETRIAL,McLaurin,Stephanie,Nicole,Female,African-American,06/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +50839,57162,51945,PRETRIAL,McLaurin,Stephanie,Nicole,Female,African-American,06/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +50839,57162,51945,PRETRIAL,McLaurin,Stephanie,Nicole,Female,African-American,06/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50852,57179,51961,PRETRIAL,Holland,Terrance,NULL,Male,Hispanic,01/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,New,1,0 +50852,57179,51961,PRETRIAL,Holland,Terrance,NULL,Male,Hispanic,01/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.71,10,High,New,1,0 +50852,57179,51961,PRETRIAL,Holland,Terrance,NULL,Male,Hispanic,01/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +50840,57163,51946,PRETRIAL,Colon,Susana,NULL,Female,Caucasian,10/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +50840,57163,51946,PRETRIAL,Colon,Susana,NULL,Female,Caucasian,10/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +50840,57163,51946,PRETRIAL,Colon,Susana,NULL,Female,Caucasian,10/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50853,57178,51960,PRETRIAL,Brown,Devaughn,NULL,Male,African-American,07/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +50853,57178,51960,PRETRIAL,Brown,Devaughn,NULL,Male,African-American,07/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +50853,57178,51960,PRETRIAL,Brown,Devaughn,NULL,Male,African-American,07/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50847,57170,51953,PRETRIAL,Walters,Patwayne,B,Male,Other,10/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +50847,57170,51953,PRETRIAL,Walters,Patwayne,B,Male,Other,10/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +50847,57170,51953,PRETRIAL,Walters,Patwayne,B,Male,Other,10/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50842,57165,51948,PRETRIAL,Mulligan,William,Joseph,Male,Caucasian,10/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +50842,57165,51948,PRETRIAL,Mulligan,William,Joseph,Male,Caucasian,10/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +50842,57165,51948,PRETRIAL,Mulligan,William,Joseph,Male,Caucasian,10/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50843,57166,51949,PRETRIAL,Davis,Michael,Lavon,Male,African-American,11/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.92,9,High,New,1,0 +50843,57166,51949,PRETRIAL,Davis,Michael,Lavon,Male,African-American,11/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +50843,57166,51949,PRETRIAL,Davis,Michael,Lavon,Male,African-American,11/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50854,57180,51962,PRETRIAL,MARTINEZ,MARTIN,OLVERA,Male,Caucasian,01/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +50854,57180,51962,PRETRIAL,MARTINEZ,MARTIN,OLVERA,Male,Caucasian,01/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +50854,57180,51962,PRETRIAL,MARTINEZ,MARTIN,OLVERA,Male,Caucasian,01/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50849,57175,51957,PRETRIAL,Coleman,Kortney,Brooke,Female,Caucasian,08/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +50849,57175,51957,PRETRIAL,Coleman,Kortney,Brooke,Female,Caucasian,08/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +50849,57175,51957,PRETRIAL,Coleman,Kortney,Brooke,Female,Caucasian,08/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50841,57164,51947,PRETRIAL,Battle,Regina,NULL,Female,African-American,06/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +50841,57164,51947,PRETRIAL,Battle,Regina,NULL,Female,African-American,06/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +50841,57164,51947,PRETRIAL,Battle,Regina,NULL,Female,African-American,06/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50851,57177,51959,PRETRIAL,NAIRN,DOREAN,NULL,Female,African-American,11/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +50851,57177,51959,PRETRIAL,NAIRN,DOREAN,NULL,Female,African-American,11/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +50851,57177,51959,PRETRIAL,NAIRN,DOREAN,NULL,Female,African-American,11/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50856,57182,51964,PRETRIAL,AIME,EVIENCE,B,Male,African-American,12/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/2/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +50856,57182,51964,PRETRIAL,AIME,EVIENCE,B,Male,African-American,12/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/2/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +50856,57182,51964,PRETRIAL,AIME,EVIENCE,B,Male,African-American,12/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50862,57190,51972,PRETRIAL,Reijonen,Mckenzie,NULL,Male,Caucasian,07/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +50862,57190,51972,PRETRIAL,Reijonen,Mckenzie,NULL,Male,Caucasian,07/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +50862,57190,51972,PRETRIAL,Reijonen,Mckenzie,NULL,Male,Caucasian,07/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50873,57203,51984,PRETRIAL,sells,louis,NULL,Male,Caucasian,05/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +50873,57203,51984,PRETRIAL,sells,louis,NULL,Male,Caucasian,05/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +50873,57203,51984,PRETRIAL,sells,louis,NULL,Male,Caucasian,05/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50868,57198,51979,Probation,Jorfe,Nadia,NULL,Male,Caucasian,10/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +50868,57198,51979,Probation,Jorfe,Nadia,NULL,Male,Caucasian,10/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +50868,57198,51979,Probation,Jorfe,Nadia,NULL,Male,Caucasian,10/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +44757,57211,51992,PRETRIAL,Jacques,Herns,NULL,Male,African-American,12/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +44757,57211,51992,PRETRIAL,Jacques,Herns,NULL,Male,African-American,12/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +44757,57211,51992,PRETRIAL,Jacques,Herns,NULL,Male,African-American,12/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50880,57213,51993,PRETRIAL,Weeks,Demetrius,NULL,Male,African-American,11/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/2/13 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +50880,57213,51993,PRETRIAL,Weeks,Demetrius,NULL,Male,African-American,11/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +50880,57213,51993,PRETRIAL,Weeks,Demetrius,NULL,Male,African-American,11/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/2/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +46600,57214,47026,PRETRIAL,Virgile,Wacaltos,NULL,Male,Other,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,Copy,1,0 +46600,57214,47026,PRETRIAL,Virgile,Wacaltos,NULL,Male,Other,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,4,High,8,Risk of Recidivism,0.79,10,High,Copy,1,0 +46600,57214,47026,PRETRIAL,Virgile,Wacaltos,NULL,Male,Other,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +50858,57185,51967,PRETRIAL,Maddox,Elizabeth,NULL,Female,Caucasian,02/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +50858,57185,51967,PRETRIAL,Maddox,Elizabeth,NULL,Female,Caucasian,02/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +50858,57185,51967,PRETRIAL,Maddox,Elizabeth,NULL,Female,Caucasian,02/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50864,57192,51974,PRETRIAL,Canuet,Jules,NULL,Male,Caucasian,10/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +50864,57192,51974,PRETRIAL,Canuet,Jules,NULL,Male,Caucasian,10/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +50864,57192,51974,PRETRIAL,Canuet,Jules,NULL,Male,Caucasian,10/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50865,57193,51975,PRETRIAL,CHERENFANT,NATACHA,NULL,Female,African-American,03/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +50865,57193,51975,PRETRIAL,CHERENFANT,NATACHA,NULL,Female,African-American,03/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +50865,57193,51975,PRETRIAL,CHERENFANT,NATACHA,NULL,Female,African-American,03/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50871,57200,51981,PRETRIAL,Brownlee,Ricky,NULL,Male,African-American,11/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,4,High,7,Risk of Violence,-0.15,10,High,New,1,0 +50871,57200,51981,PRETRIAL,Brownlee,Ricky,NULL,Male,African-American,11/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,4,High,8,Risk of Recidivism,0.31,9,High,New,1,0 +50871,57200,51981,PRETRIAL,Brownlee,Ricky,NULL,Male,African-American,11/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +50875,57206,51987,Probation,renz,daniel,NULL,Male,Caucasian,12/20/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,New,1,0 +50875,57206,51987,Probation,renz,daniel,NULL,Male,Caucasian,12/20/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +50875,57206,51987,Probation,renz,daniel,NULL,Male,Caucasian,12/20/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +29205,57184,51966,Probation,Banner,Akeine,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +29205,57184,51966,Probation,Banner,Akeine,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +29205,57184,51966,Probation,Banner,Akeine,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +31285,57205,51986,PRETRIAL,deutsch,zackery,NULL,Male,Caucasian,12/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +31285,57205,51986,PRETRIAL,deutsch,zackery,NULL,Male,Caucasian,12/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +31285,57205,51986,PRETRIAL,deutsch,zackery,NULL,Male,Caucasian,12/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +50872,57201,51982,Probation,cross,tracy,NULL,Male,African-American,08/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +50872,57201,51982,Probation,cross,tracy,NULL,Male,African-American,08/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +50872,57201,51982,Probation,cross,tracy,NULL,Male,African-American,08/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +50860,57187,51969,PRETRIAL,STEWART,MELVIN,LENARD,Male,African-American,02/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.09,4,Low,New,1,0 +50860,57187,51969,PRETRIAL,STEWART,MELVIN,LENARD,Male,African-American,02/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +50860,57187,51969,PRETRIAL,STEWART,MELVIN,LENARD,Male,African-American,02/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50861,57189,51971,PRETRIAL,LOWERY,REBECCA,GAIL,Female,Caucasian,04/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,New,1,0 +50861,57189,51971,PRETRIAL,LOWERY,REBECCA,GAIL,Female,Caucasian,04/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.11,8,High,New,1,0 +50861,57189,51971,PRETRIAL,LOWERY,REBECCA,GAIL,Female,Caucasian,04/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +50879,57210,51991,PRETRIAL,BUSH,FREDDIE,NULL,Male,African-American,07/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +50879,57210,51991,PRETRIAL,BUSH,FREDDIE,NULL,Male,African-American,07/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +50879,57210,51991,PRETRIAL,BUSH,FREDDIE,NULL,Male,African-American,07/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50866,57194,51976,PRETRIAL,SCHWAB,GARY,NULL,Male,Caucasian,10/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Married,1/2/13 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +50866,57194,51976,PRETRIAL,SCHWAB,GARY,NULL,Male,Caucasian,10/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Married,1/2/13 0:00,1,Low,8,Risk of Recidivism,-2.61,1,Low,New,1,0 +50866,57194,51976,PRETRIAL,SCHWAB,GARY,NULL,Male,Caucasian,10/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Married,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +46280,57212,46670,PRETRIAL,MORALES,VICTOR,NULL,Male,Hispanic,10/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,Copy,1,0 +46280,57212,46670,PRETRIAL,MORALES,VICTOR,NULL,Male,Hispanic,10/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,Copy,1,0 +46280,57212,46670,PRETRIAL,MORALES,VICTOR,NULL,Male,Hispanic,10/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +50876,57207,51988,PRETRIAL,ALBINO,VANESSA,NULL,Female,Caucasian,07/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +50876,57207,51988,PRETRIAL,ALBINO,VANESSA,NULL,Female,Caucasian,07/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +50876,57207,51988,PRETRIAL,ALBINO,VANESSA,NULL,Female,Caucasian,07/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +50859,57186,51968,PRETRIAL,Lee,Victor,Bernard,Male,African-American,12/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +50859,57186,51968,PRETRIAL,Lee,Victor,Bernard,Male,African-American,12/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +50859,57186,51968,PRETRIAL,Lee,Victor,Bernard,Male,African-American,12/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50863,57191,51973,PRETRIAL,McCord,Charles,Robert,Male,African-American,04/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +50863,57191,51973,PRETRIAL,McCord,Charles,Robert,Male,African-American,04/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +50863,57191,51973,PRETRIAL,McCord,Charles,Robert,Male,African-American,04/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50869,57199,51980,Probation,RUFF,FRED,E,Male,Caucasian,08/28/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/2/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +50869,57199,51980,Probation,RUFF,FRED,E,Male,Caucasian,08/28/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/2/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +50869,57199,51980,Probation,RUFF,FRED,E,Male,Caucasian,08/28/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +42067,57197,51978,PRETRIAL,Casselman,Craig,Daniel,Male,Caucasian,05/26/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +42067,57197,51978,PRETRIAL,Casselman,Craig,Daniel,Male,Caucasian,05/26/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +42067,57197,51978,PRETRIAL,Casselman,Craig,Daniel,Male,Caucasian,05/26/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50857,57183,51965,PRETRIAL,Doe,Jenay,NULL,Female,African-American,10/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +50857,57183,51965,PRETRIAL,Doe,Jenay,NULL,Female,African-American,10/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,9,High,New,1,0 +50857,57183,51965,PRETRIAL,Doe,Jenay,NULL,Female,African-American,10/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +43080,57188,51970,PRETRIAL,DAVIS,TAQUAWN,NULL,Male,African-American,01/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,New,1,0 +43080,57188,51970,PRETRIAL,DAVIS,TAQUAWN,NULL,Male,African-American,01/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +43080,57188,51970,PRETRIAL,DAVIS,TAQUAWN,NULL,Male,African-American,01/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +50870,57202,51983,DRRD,Wiggins,Michael,NULL,Male,African-American,07/31/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/2/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +50870,57202,51983,DRRD,Wiggins,Michael,NULL,Male,African-American,07/31/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/2/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +50870,57202,51983,DRRD,Wiggins,Michael,NULL,Male,African-American,07/31/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/2/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50874,57204,51985,PRETRIAL,talavera,veronica,NULL,Female,African-American,10/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +50874,57204,51985,PRETRIAL,talavera,veronica,NULL,Female,African-American,10/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +50874,57204,51985,PRETRIAL,talavera,veronica,NULL,Female,African-American,10/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50886,57223,52002,PRETRIAL,Wallace,Leon,Rohan,Male,Other,04/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +50886,57223,52002,PRETRIAL,Wallace,Leon,Rohan,Male,Other,04/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +50886,57223,52002,PRETRIAL,Wallace,Leon,Rohan,Male,Other,04/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50907,57253,52026,PRETRIAL,Estey,Frederick,NULL,Male,Caucasian,05/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +50907,57253,52026,PRETRIAL,Estey,Frederick,NULL,Male,Caucasian,05/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +50907,57253,52026,PRETRIAL,Estey,Frederick,NULL,Male,Caucasian,05/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +50887,57225,52004,PRETRIAL,Alleyne,Theona,NULL,Female,African-American,01/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +50887,57225,52004,PRETRIAL,Alleyne,Theona,NULL,Female,African-American,01/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +50887,57225,52004,PRETRIAL,Alleyne,Theona,NULL,Female,African-American,01/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,New,1,0 +50892,57232,52011,PRETRIAL,Yunis,Omar,Nassim,Male,Caucasian,08/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +50892,57232,52011,PRETRIAL,Yunis,Omar,Nassim,Male,Caucasian,08/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,4,High,8,Risk of Recidivism,0.37,9,High,New,1,0 +50892,57232,52011,PRETRIAL,Yunis,Omar,Nassim,Male,Caucasian,08/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +18293,57246,35116,PRETRIAL,HOLIDAY,NORRIS,ERROL,Male,African-American,10/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +18293,57246,35116,PRETRIAL,HOLIDAY,NORRIS,ERROL,Male,African-American,10/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,Copy,1,0 +18293,57246,35116,PRETRIAL,HOLIDAY,NORRIS,ERROL,Male,African-American,10/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +50913,57260,52032,PRETRIAL,Augustin,James,NULL,Male,African-American,07/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/3/13 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +50913,57260,52032,PRETRIAL,Augustin,James,NULL,Male,African-American,07/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +50913,57260,52032,PRETRIAL,Augustin,James,NULL,Male,African-American,07/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/3/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +50882,57218,51997,PRETRIAL,Mobley,Milton,Brian,Male,African-American,08/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +50882,57218,51997,PRETRIAL,Mobley,Milton,Brian,Male,African-American,08/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,4,High,8,Risk of Recidivism,0.32,9,High,New,1,0 +50882,57218,51997,PRETRIAL,Mobley,Milton,Brian,Male,African-American,08/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50899,57244,52018,Probation,wiegley,christian,NULL,Male,Caucasian,07/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +50899,57244,52018,Probation,wiegley,christian,NULL,Male,Caucasian,07/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +50899,57244,52018,Probation,wiegley,christian,NULL,Male,Caucasian,07/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50905,57251,52024,Probation,Delva,Ernso,NULL,Male,African-American,01/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +50905,57251,52024,Probation,Delva,Ernso,NULL,Male,African-American,01/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +50905,57251,52024,Probation,Delva,Ernso,NULL,Male,African-American,01/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50890,57230,52009,PRETRIAL,Brown,Paul,Christophe,Male,African-American,06/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +50890,57230,52009,PRETRIAL,Brown,Paul,Christophe,Male,African-American,06/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +50890,57230,52009,PRETRIAL,Brown,Paul,Christophe,Male,African-American,06/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50902,57248,52021,PRETRIAL,Leon,Gina,NULL,Female,Hispanic,03/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/3/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +50902,57248,52021,PRETRIAL,Leon,Gina,NULL,Female,Hispanic,03/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +50902,57248,52021,PRETRIAL,Leon,Gina,NULL,Female,Hispanic,03/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +50903,57249,52022,PRETRIAL,Pericles,Evens,NULL,Male,African-American,10/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +50903,57249,52022,PRETRIAL,Pericles,Evens,NULL,Male,African-American,10/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +50903,57249,52022,PRETRIAL,Pericles,Evens,NULL,Male,African-American,10/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50889,57228,52007,PRETRIAL,Galvis,Eimar,NULL,Male,Hispanic,03/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +50889,57228,52007,PRETRIAL,Galvis,Eimar,NULL,Male,Hispanic,03/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +50889,57228,52007,PRETRIAL,Galvis,Eimar,NULL,Male,Hispanic,03/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50911,57257,52030,Probation,HESLOP,CLAUDINE,NULL,Female,African-American,09/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +50911,57257,52030,Probation,HESLOP,CLAUDINE,NULL,Female,African-American,09/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +50911,57257,52030,Probation,HESLOP,CLAUDINE,NULL,Female,African-American,09/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50884,57220,51999,PRETRIAL,Buchanan,Jermaine,NULL,Male,African-American,11/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +50884,57220,51999,PRETRIAL,Buchanan,Jermaine,NULL,Male,African-American,11/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +50884,57220,51999,PRETRIAL,Buchanan,Jermaine,NULL,Male,African-American,11/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +50909,57254,52027,PRETRIAL,Bedell,Frederick,NULL,Male,Caucasian,11/28/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +50909,57254,52027,PRETRIAL,Bedell,Frederick,NULL,Male,Caucasian,11/28/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +50909,57254,52027,PRETRIAL,Bedell,Frederick,NULL,Male,Caucasian,11/28/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50896,57241,52015,Probation,lutz,douglas,NULL,Male,Caucasian,08/07/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/3/13 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +50896,57241,52015,Probation,lutz,douglas,NULL,Male,Caucasian,08/07/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +50896,57241,52015,Probation,lutz,douglas,NULL,Male,Caucasian,08/07/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50881,57215,51994,PRETRIAL,Wiggins,Willie,NULL,Male,African-American,05/02/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +50881,57215,51994,PRETRIAL,Wiggins,Willie,NULL,Male,African-American,05/02/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +50881,57215,51994,PRETRIAL,Wiggins,Willie,NULL,Male,African-American,05/02/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50893,57233,52012,PRETRIAL,warman,cristina,NULL,Female,Caucasian,01/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +50893,57233,52012,PRETRIAL,warman,cristina,NULL,Female,Caucasian,01/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +50893,57233,52012,PRETRIAL,warman,cristina,NULL,Female,Caucasian,01/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +19327,57217,51996,PRETRIAL,Gonzalez,Paul,NULL,Male,Hispanic,01/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +19327,57217,51996,PRETRIAL,Gonzalez,Paul,NULL,Male,Hispanic,01/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +19327,57217,51996,PRETRIAL,Gonzalez,Paul,NULL,Male,Hispanic,01/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +38240,57224,52003,PRETRIAL,Williams,Kenata,NULL,Male,African-American,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +38240,57224,52003,PRETRIAL,Williams,Kenata,NULL,Male,African-American,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +38240,57224,52003,PRETRIAL,Williams,Kenata,NULL,Male,African-American,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50891,57231,52010,PRETRIAL,Rich,Christopher,NULL,Male,African-American,09/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +50891,57231,52010,PRETRIAL,Rich,Christopher,NULL,Male,African-American,09/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +50891,57231,52010,PRETRIAL,Rich,Christopher,NULL,Male,African-American,09/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50900,57245,52019,PRETRIAL,Phelan,Michael,NULL,Male,Caucasian,05/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +50900,57245,52019,PRETRIAL,Phelan,Michael,NULL,Male,Caucasian,05/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +50900,57245,52019,PRETRIAL,Phelan,Michael,NULL,Male,Caucasian,05/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50895,57238,52014,Probation,Rinchere,Joshua,NULL,Male,African-American,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +50895,57238,52014,Probation,Rinchere,Joshua,NULL,Male,African-American,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +50895,57238,52014,Probation,Rinchere,Joshua,NULL,Male,African-American,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +48511,57240,49208,PRETRIAL,Rossi,Jonathon,NULL,Male,Caucasian,01/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,Copy,1,0 +48511,57240,49208,PRETRIAL,Rossi,Jonathon,NULL,Male,Caucasian,01/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,Copy,1,0 +48511,57240,49208,PRETRIAL,Rossi,Jonathon,NULL,Male,Caucasian,01/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +50888,57226,52005,PRETRIAL,Pena,Nolasco,NULL,Male,African-American,06/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +50888,57226,52005,PRETRIAL,Pena,Nolasco,NULL,Male,African-American,06/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +50888,57226,52005,PRETRIAL,Pena,Nolasco,NULL,Male,African-American,06/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50901,57247,52020,Probation,CLERMONT,MARICA,NULL,Female,African-American,10/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +50901,57247,52020,Probation,CLERMONT,MARICA,NULL,Female,African-American,10/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +50901,57247,52020,Probation,CLERMONT,MARICA,NULL,Female,African-American,10/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +50885,57222,52001,PRETRIAL,Phillips,Adrian,NULL,Male,Other,03/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +50885,57222,52001,PRETRIAL,Phillips,Adrian,NULL,Male,Other,03/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +50885,57222,52001,PRETRIAL,Phillips,Adrian,NULL,Male,Other,03/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50910,57256,52029,Probation,fussell,lafayette,NULL,Male,African-American,10/03/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,New,1,0 +50910,57256,52029,Probation,fussell,lafayette,NULL,Male,African-American,10/03/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +50910,57256,52029,Probation,fussell,lafayette,NULL,Male,African-American,10/03/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +50898,57243,52017,Probation,Riley,Sade,shenelle,Female,African-American,12/17/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +50898,57243,52017,Probation,Riley,Sade,shenelle,Female,African-American,12/17/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +50898,57243,52017,Probation,Riley,Sade,shenelle,Female,African-American,12/17/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +9825,57221,52000,PRETRIAL,MURRAY,JAMAAL,RADHAD,Male,African-American,06/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,4,High,7,Risk of Violence,-0.95,9,High,New,1,0 +9825,57221,52000,PRETRIAL,MURRAY,JAMAAL,RADHAD,Male,African-American,06/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,4,High,8,Risk of Recidivism,0.95,10,High,New,1,0 +9825,57221,52000,PRETRIAL,MURRAY,JAMAAL,RADHAD,Male,African-American,06/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +32426,57255,52028,PRETRIAL,ahearn,robert,NULL,Male,Caucasian,09/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +32426,57255,52028,PRETRIAL,ahearn,robert,NULL,Male,Caucasian,09/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +32426,57255,52028,PRETRIAL,ahearn,robert,NULL,Male,Caucasian,09/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +29747,57227,52006,PRETRIAL,RICHLAND,WENDY,NULL,Female,Caucasian,12/28/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +29747,57227,52006,PRETRIAL,RICHLAND,WENDY,NULL,Female,Caucasian,12/28/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +29747,57227,52006,PRETRIAL,RICHLAND,WENDY,NULL,Female,Caucasian,12/28/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,29,9,High,New,1,0 +38682,57234,38137,PRETRIAL,CULBERTSON,DARYL,NULL,Male,Caucasian,08/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,Copy,1,0 +38682,57234,38137,PRETRIAL,CULBERTSON,DARYL,NULL,Male,Caucasian,08/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,Copy,1,0 +38682,57234,38137,PRETRIAL,CULBERTSON,DARYL,NULL,Male,Caucasian,08/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +50897,57242,52016,PRETRIAL,Fisher,Jomar,Oneil,Male,African-American,06/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +50897,57242,52016,PRETRIAL,Fisher,Jomar,Oneil,Male,African-American,06/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +50897,57242,52016,PRETRIAL,Fisher,Jomar,Oneil,Male,African-American,06/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +19348,57229,52008,PRETRIAL,Ford,Ernest,NULL,Male,African-American,05/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.93,9,High,New,1,0 +19348,57229,52008,PRETRIAL,Ford,Ernest,NULL,Male,African-American,05/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +19348,57229,52008,PRETRIAL,Ford,Ernest,NULL,Male,African-American,05/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +52124,58751,53382,Probation,cesconeto,altamiro,NULL,Male,Other,05/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +52124,58751,53382,Probation,cesconeto,altamiro,NULL,Male,Other,05/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +52124,58751,53382,Probation,cesconeto,altamiro,NULL,Male,Other,05/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50883,57219,51998,PRETRIAL,Brown,Tyrone,NULL,Male,African-American,01/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +50883,57219,51998,PRETRIAL,Brown,Tyrone,NULL,Male,African-American,01/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +50883,57219,51998,PRETRIAL,Brown,Tyrone,NULL,Male,African-American,01/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +50912,57258,52031,Probation,Dale,Tiffany,NULL,Female,Caucasian,09/21/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +50912,57258,52031,Probation,Dale,Tiffany,NULL,Female,Caucasian,09/21/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,7,Medium,New,1,0 +50912,57258,52031,Probation,Dale,Tiffany,NULL,Female,Caucasian,09/21/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +50894,57237,52013,Probation,lake,fermin,NULL,Male,African-American,01/28/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +50894,57237,52013,Probation,lake,fermin,NULL,Male,African-American,01/28/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,6,Medium,New,1,0 +50894,57237,52013,Probation,lake,fermin,NULL,Male,African-American,01/28/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/3/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +16609,57216,51995,PRETRIAL,Chin,Bobby,David,Male,Asian,04/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +16609,57216,51995,PRETRIAL,Chin,Bobby,David,Male,Asian,04/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +16609,57216,51995,PRETRIAL,Chin,Bobby,David,Male,Asian,04/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +50904,57250,52023,PRETRIAL,Rouse,Franklin,NULL,Male,African-American,09/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +50904,57250,52023,PRETRIAL,Rouse,Franklin,NULL,Male,African-American,09/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +50904,57250,52023,PRETRIAL,Rouse,Franklin,NULL,Male,African-American,09/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50924,57284,52054,PRETRIAL,Rodriguez,Williams,NULL,Male,Hispanic,06/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +50924,57284,52054,PRETRIAL,Rodriguez,Williams,NULL,Male,Hispanic,06/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +50924,57284,52054,PRETRIAL,Rodriguez,Williams,NULL,Male,Hispanic,06/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50917,57271,52043,PRETRIAL,Ifill,Oba,Sheba,Male,African-American,06/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +50917,57271,52043,PRETRIAL,Ifill,Oba,Sheba,Male,African-American,06/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +50917,57271,52043,PRETRIAL,Ifill,Oba,Sheba,Male,African-American,06/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50936,57305,52072,Probation,morgan,stephen,NULL,Male,Caucasian,10/09/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +50936,57305,52072,Probation,morgan,stephen,NULL,Male,Caucasian,10/09/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +50936,57305,52072,Probation,morgan,stephen,NULL,Male,Caucasian,10/09/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +25699,57276,24869,PRETRIAL,MEDLOCK,LARRY,NULL,Male,African-American,08/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,Copy,1,0 +25699,57276,24869,PRETRIAL,MEDLOCK,LARRY,NULL,Male,African-American,08/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,Copy,1,0 +25699,57276,24869,PRETRIAL,MEDLOCK,LARRY,NULL,Male,African-American,08/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +50921,57279,52049,PRETRIAL,Jean,Benjamin,Montreuil,Male,African-American,12/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +50921,57279,52049,PRETRIAL,Jean,Benjamin,Montreuil,Male,African-American,12/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +50921,57279,52049,PRETRIAL,Jean,Benjamin,Montreuil,Male,African-American,12/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +49011,57297,52064,Probation,gosnell,mark,NULL,Male,Caucasian,12/16/64,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +49011,57297,52064,Probation,gosnell,mark,NULL,Male,Caucasian,12/16/64,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +49011,57297,52064,Probation,gosnell,mark,NULL,Male,Caucasian,12/16/64,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +50914,57263,52035,PRETRIAL,Neal,Tony,W,Male,African-American,07/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.68,2,Low,New,1,0 +50914,57263,52035,PRETRIAL,Neal,Tony,W,Male,African-American,07/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +50914,57263,52035,PRETRIAL,Neal,Tony,W,Male,African-American,07/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +40929,44410,40579,PRETRIAL,Velazquez,Jayson,NULL,Male,Caucasian,11/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +40929,44410,40579,PRETRIAL,Velazquez,Jayson,NULL,Male,Caucasian,11/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +40929,44410,40579,PRETRIAL,Velazquez,Jayson,NULL,Male,Caucasian,11/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +50933,57300,52067,PRETRIAL,Lear,Ryan,NULL,Male,Caucasian,04/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +50933,57300,52067,PRETRIAL,Lear,Ryan,NULL,Male,Caucasian,04/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +50933,57300,52067,PRETRIAL,Lear,Ryan,NULL,Male,Caucasian,04/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +50920,57277,52048,PRETRIAL,Brown,Justin,A,Male,Other,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +50920,57277,52048,PRETRIAL,Brown,Justin,A,Male,Other,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +50920,57277,52048,PRETRIAL,Brown,Justin,A,Male,Other,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50923,57282,52052,PRETRIAL,Daphnis,Rovens,NULL,Male,African-American,07/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +50923,57282,52052,PRETRIAL,Daphnis,Rovens,NULL,Male,African-American,07/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +50923,57282,52052,PRETRIAL,Daphnis,Rovens,NULL,Male,African-American,07/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +10568,57273,52045,PRETRIAL,Louis,Lorenzo,Braziel,Male,African-American,01/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +10568,57273,52045,PRETRIAL,Louis,Lorenzo,Braziel,Male,African-American,01/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +10568,57273,52045,PRETRIAL,Louis,Lorenzo,Braziel,Male,African-American,01/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50935,57303,52070,Probation,Ramos,John,NULL,Male,Hispanic,12/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +50935,57303,52070,Probation,Ramos,John,NULL,Male,Hispanic,12/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +50935,57303,52070,Probation,Ramos,John,NULL,Male,Hispanic,12/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +22457,57298,52065,PRETRIAL,Thomas,Derrick,NULL,Male,African-American,11/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +22457,57298,52065,PRETRIAL,Thomas,Derrick,NULL,Male,African-American,11/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +22457,57298,52065,PRETRIAL,Thomas,Derrick,NULL,Male,African-American,11/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50930,57294,52062,Probation,Moreno,Maria,NULL,Female,Hispanic,12/24/80,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,1/4/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +50930,57294,52062,Probation,Moreno,Maria,NULL,Female,Hispanic,12/24/80,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,1/4/13 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +50930,57294,52062,Probation,Moreno,Maria,NULL,Female,Hispanic,12/24/80,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50238,57287,51226,Probation,Jenkins,Allan,NULL,Male,African-American,01/04/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +50238,57287,51226,Probation,Jenkins,Allan,NULL,Male,African-American,01/04/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +50238,57287,51226,Probation,Jenkins,Allan,NULL,Male,African-American,01/04/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +6924,57289,6515,Probation,Moss,Jimmie,L,Male,African-American,05/13/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/4/13 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,Copy,1,0 +6924,57289,6515,Probation,Moss,Jimmie,L,Male,African-American,05/13/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/4/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,Copy,1,0 +6924,57289,6515,Probation,Moss,Jimmie,L,Male,African-American,05/13/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +48501,57261,52033,PRETRIAL,Mccormick,Terry,NULL,Male,Caucasian,04/26/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/4/13 0:00,2,Medium,7,Risk of Violence,-2.92,2,Low,New,1,0 +48501,57261,52033,PRETRIAL,Mccormick,Terry,NULL,Male,Caucasian,04/26/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +48501,57261,52033,PRETRIAL,Mccormick,Terry,NULL,Male,Caucasian,04/26/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,35,10,High,New,1,0 +3060,57266,52038,PRETRIAL,BURNETTE,EPRHIRAM,NULL,Male,African-American,05/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +3060,57266,52038,PRETRIAL,BURNETTE,EPRHIRAM,NULL,Male,African-American,05/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +3060,57266,52038,PRETRIAL,BURNETTE,EPRHIRAM,NULL,Male,African-American,05/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +18644,57268,52040,PRETRIAL,WATSON,CHRISTOPHER,NULL,Male,African-American,07/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +18644,57268,52040,PRETRIAL,WATSON,CHRISTOPHER,NULL,Male,African-American,07/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +18644,57268,52040,PRETRIAL,WATSON,CHRISTOPHER,NULL,Male,African-American,07/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +50842,57296,51948,PRETRIAL,Mulligan,William,Joseph,Male,Caucasian,10/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,Copy,1,0 +50842,57296,51948,PRETRIAL,Mulligan,William,Joseph,Male,Caucasian,10/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,Copy,1,0 +50842,57296,51948,PRETRIAL,Mulligan,William,Joseph,Male,Caucasian,10/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +48820,57283,52053,PRETRIAL,Jacsaint,Jermai,NULL,Male,African-American,12/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +48820,57283,52053,PRETRIAL,Jacsaint,Jermai,NULL,Male,African-American,12/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +48820,57283,52053,PRETRIAL,Jacsaint,Jermai,NULL,Male,African-American,12/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50934,57301,52068,Probation,Escalante,Jose,NULL,Male,Hispanic,07/02/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/4/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +50934,57301,52068,Probation,Escalante,Jose,NULL,Male,Hispanic,07/02/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/4/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +50934,57301,52068,Probation,Escalante,Jose,NULL,Male,Hispanic,07/02/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +40027,57262,52034,PRETRIAL,Bennett,Marvin,NULL,Male,Caucasian,07/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/4/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +40027,57262,52034,PRETRIAL,Bennett,Marvin,NULL,Male,Caucasian,07/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/4/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +40027,57262,52034,PRETRIAL,Bennett,Marvin,NULL,Male,Caucasian,07/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +43496,57280,52050,PRETRIAL,Jean,Kevin,NULL,Male,African-American,11/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +43496,57280,52050,PRETRIAL,Jean,Kevin,NULL,Male,African-American,11/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +43496,57280,52050,PRETRIAL,Jean,Kevin,NULL,Male,African-American,11/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +30818,57275,52047,PRETRIAL,MCREED,JONATHAN,NULL,Male,African-American,05/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +30818,57275,52047,PRETRIAL,MCREED,JONATHAN,NULL,Male,African-American,05/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +30818,57275,52047,PRETRIAL,MCREED,JONATHAN,NULL,Male,African-American,05/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +40907,57288,52057,PRETRIAL,Singletary,Ronald,NULL,Male,African-American,03/24/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +40907,57288,52057,PRETRIAL,Singletary,Ronald,NULL,Male,African-American,03/24/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +40907,57288,52057,PRETRIAL,Singletary,Ronald,NULL,Male,African-American,03/24/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +34505,57291,52059,PRETRIAL,Judge,Samuel,NULL,Male,African-American,09/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +34505,57291,52059,PRETRIAL,Judge,Samuel,NULL,Male,African-American,09/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +34505,57291,52059,PRETRIAL,Judge,Samuel,NULL,Male,African-American,09/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50929,57293,52061,PRETRIAL,RINCON,LENIN,NULL,Male,Caucasian,03/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +50929,57293,52061,PRETRIAL,RINCON,LENIN,NULL,Male,Caucasian,03/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +50929,57293,52061,PRETRIAL,RINCON,LENIN,NULL,Male,Caucasian,03/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50916,57270,52042,PRETRIAL,Meli,Paul,NULL,Male,Caucasian,07/06/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/13 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +50916,57270,52042,PRETRIAL,Meli,Paul,NULL,Male,Caucasian,07/06/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/13 0:00,1,Low,8,Risk of Recidivism,-2.79,1,Low,New,1,0 +50916,57270,52042,PRETRIAL,Meli,Paul,NULL,Male,Caucasian,07/06/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50918,57272,52044,PRETRIAL,Montgomery,Tevin,NULL,Male,African-American,01/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/4/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +50918,57272,52044,PRETRIAL,Montgomery,Tevin,NULL,Male,African-American,01/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/4/13 0:00,4,High,8,Risk of Recidivism,0.33,9,High,New,1,0 +50918,57272,52044,PRETRIAL,Montgomery,Tevin,NULL,Male,African-American,01/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/4/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +19206,57306,52073,PRETRIAL,Murphy,Janard,NULL,Male,African-American,09/16/92,17,All Scales,Intake,English,Post Sentence,Residential Program,Single,1/4/13 0:00,4,High,7,Risk of Violence,-0.92,9,High,New,1,0 +19206,57306,52073,PRETRIAL,Murphy,Janard,NULL,Male,African-American,09/16/92,17,All Scales,Intake,English,Post Sentence,Residential Program,Single,1/4/13 0:00,4,High,8,Risk of Recidivism,0.76,10,High,New,1,0 +19206,57306,52073,PRETRIAL,Murphy,Janard,NULL,Male,African-American,09/16/92,17,All Scales,Intake,English,Post Sentence,Residential Program,Single,1/4/13 0:00,4,High,18,Risk of Failure to Appear,23,4,Low,New,1,0 +48829,57264,52036,DRRD,Pino,Angel,Rafael,Male,Hispanic,03/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +48829,57264,52036,DRRD,Pino,Angel,Rafael,Male,Hispanic,03/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +48829,57264,52036,DRRD,Pino,Angel,Rafael,Male,Hispanic,03/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +34054,57278,33188,PRETRIAL,Harris,David,Chandler,Male,Caucasian,04/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,Copy,1,0 +34054,57278,33188,PRETRIAL,Harris,David,Chandler,Male,Caucasian,04/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,Copy,1,0 +34054,57278,33188,PRETRIAL,Harris,David,Chandler,Male,Caucasian,04/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +50925,57285,52055,PRETRIAL,James,Keon,NULL,Male,African-American,11/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/4/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +50925,57285,52055,PRETRIAL,James,Keon,NULL,Male,African-American,11/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +50925,57285,52055,PRETRIAL,James,Keon,NULL,Male,African-American,11/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +6225,57265,52037,PRETRIAL,McReed,Derion,Pernell,Male,African-American,07/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +6225,57265,52037,PRETRIAL,McReed,Derion,Pernell,Male,African-American,07/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +6225,57265,52037,PRETRIAL,McReed,Derion,Pernell,Male,African-American,07/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50915,57269,52041,PRETRIAL,joy,Derek,NULL,Male,African-American,11/17/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +50915,57269,52041,PRETRIAL,joy,Derek,NULL,Male,African-American,11/17/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +50915,57269,52041,PRETRIAL,joy,Derek,NULL,Male,African-American,11/17/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +50926,57286,52056,Probation,GADSON,PATRICK,B,Male,African-American,10/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +50926,57286,52056,Probation,GADSON,PATRICK,B,Male,African-American,10/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +50926,57286,52056,Probation,GADSON,PATRICK,B,Male,African-American,10/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50927,57290,52058,Probation,garcia,jeffrey,NULL,Male,Hispanic,01/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +50927,57290,52058,Probation,garcia,jeffrey,NULL,Male,Hispanic,01/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +50927,57290,52058,Probation,garcia,jeffrey,NULL,Male,Hispanic,01/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50937,57307,52074,Probation,Williams,Andrew,Michael,Male,African-American,07/30/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +50937,57307,52074,Probation,Williams,Andrew,Michael,Male,African-American,07/30/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +50937,57307,52074,Probation,Williams,Andrew,Michael,Male,African-American,07/30/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +6431,57267,52039,PRETRIAL,HOWARD,BARON,NULL,Male,African-American,05/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +6431,57267,52039,PRETRIAL,HOWARD,BARON,NULL,Male,African-American,05/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +6431,57267,52039,PRETRIAL,HOWARD,BARON,NULL,Male,African-American,05/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50919,57274,52046,PRETRIAL,Adderley,Dernard,Edward,Male,African-American,05/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +50919,57274,52046,PRETRIAL,Adderley,Dernard,Edward,Male,African-American,05/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +50919,57274,52046,PRETRIAL,Adderley,Dernard,Edward,Male,African-American,05/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50922,57281,52051,PRETRIAL,Foley,Ronnie,NULL,Male,Caucasian,09/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +50922,57281,52051,PRETRIAL,Foley,Ronnie,NULL,Male,Caucasian,09/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +50922,57281,52051,PRETRIAL,Foley,Ronnie,NULL,Male,Caucasian,09/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50931,57295,52063,Probation,MARTINS,ANA,P,Female,Hispanic,10/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +50931,57295,52063,Probation,MARTINS,ANA,P,Female,Hispanic,10/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +50931,57295,52063,Probation,MARTINS,ANA,P,Female,Hispanic,10/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +28061,57304,52071,PRETRIAL,MARTINO,STACEY,ANN,Female,Caucasian,07/02/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +28061,57304,52071,PRETRIAL,MARTINO,STACEY,ANN,Female,Caucasian,07/02/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +28061,57304,52071,PRETRIAL,MARTINO,STACEY,ANN,Female,Caucasian,07/02/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50948,57320,52085,PRETRIAL,Roberson,Lakemia,NULL,Female,African-American,06/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +50948,57320,52085,PRETRIAL,Roberson,Lakemia,NULL,Female,African-American,06/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,7,Medium,New,1,0 +50948,57320,52085,PRETRIAL,Roberson,Lakemia,NULL,Female,African-American,06/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +41515,57311,41222,PRETRIAL,perry,anthony,NULL,Male,African-American,08/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,Copy,1,0 +41515,57311,41222,PRETRIAL,perry,anthony,NULL,Male,African-American,08/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,Copy,1,0 +41515,57311,41222,PRETRIAL,perry,anthony,NULL,Male,African-American,08/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +50945,57316,52082,PRETRIAL,Breedlove,Pierre,Qwauvez,Male,African-American,03/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,2,Medium,7,Risk of Violence,-1.34,7,Medium,New,1,0 +50945,57316,52082,PRETRIAL,Breedlove,Pierre,Qwauvez,Male,African-American,03/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +50945,57316,52082,PRETRIAL,Breedlove,Pierre,Qwauvez,Male,African-American,03/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +50943,57314,52080,PRETRIAL,Atkinstall,Sean,NULL,Male,Other,06/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.33,3,Low,New,1,0 +50943,57314,52080,PRETRIAL,Atkinstall,Sean,NULL,Male,Other,06/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +50943,57314,52080,PRETRIAL,Atkinstall,Sean,NULL,Male,Other,06/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +50939,57309,52076,PRETRIAL,Moncrieffe,Shieem,NULL,Male,African-American,06/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +50939,57309,52076,PRETRIAL,Moncrieffe,Shieem,NULL,Male,African-American,06/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +50939,57309,52076,PRETRIAL,Moncrieffe,Shieem,NULL,Male,African-American,06/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50940,57310,52077,PRETRIAL,Childress,Lonnie,NULL,Male,African-American,10/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +50940,57310,52077,PRETRIAL,Childress,Lonnie,NULL,Male,African-American,10/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +50940,57310,52077,PRETRIAL,Childress,Lonnie,NULL,Male,African-American,10/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +50946,57317,52083,PRETRIAL,Williams,Jonathan,NULL,Male,African-American,02/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,New,1,0 +50946,57317,52083,PRETRIAL,Williams,Jonathan,NULL,Male,African-American,02/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +50946,57317,52083,PRETRIAL,Williams,Jonathan,NULL,Male,African-American,02/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50938,57308,52075,PRETRIAL,Hernandez,Brenda,NULL,Female,Caucasian,02/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +50938,57308,52075,PRETRIAL,Hernandez,Brenda,NULL,Female,Caucasian,02/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +50938,57308,52075,PRETRIAL,Hernandez,Brenda,NULL,Female,Caucasian,02/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50947,57319,52084,PRETRIAL,Brown,Shantoya,NULL,Male,African-American,08/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +50947,57319,52084,PRETRIAL,Brown,Shantoya,NULL,Male,African-American,08/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +50947,57319,52084,PRETRIAL,Brown,Shantoya,NULL,Male,African-American,08/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50941,57312,52078,PRETRIAL,Vegarivera,Miguel,NULL,Male,Caucasian,02/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/5/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +50941,57312,52078,PRETRIAL,Vegarivera,Miguel,NULL,Male,Caucasian,02/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/5/13 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +50941,57312,52078,PRETRIAL,Vegarivera,Miguel,NULL,Male,Caucasian,02/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50944,57315,52081,PRETRIAL,Burgess,Marketta,NULL,Female,African-American,04/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,New,1,0 +50944,57315,52081,PRETRIAL,Burgess,Marketta,NULL,Female,African-American,04/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,10,High,New,1,0 +50944,57315,52081,PRETRIAL,Burgess,Marketta,NULL,Female,African-American,04/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +50949,57321,52086,PRETRIAL,lux,steven,NULL,Male,Caucasian,06/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/5/13 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +50949,57321,52086,PRETRIAL,lux,steven,NULL,Male,Caucasian,06/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/5/13 0:00,1,Low,8,Risk of Recidivism,-2.77,1,Low,New,1,0 +50949,57321,52086,PRETRIAL,lux,steven,NULL,Male,Caucasian,06/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50942,57313,52079,PRETRIAL,Gerald,Pancia,E,Female,Other,02/18/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/5/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +50942,57313,52079,PRETRIAL,Gerald,Pancia,E,Female,Other,02/18/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/5/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +50942,57313,52079,PRETRIAL,Gerald,Pancia,E,Female,Other,02/18/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +8812,57318,48865,PRETRIAL,CARTER,DONALD,NULL,Male,African-American,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/5/13 0:00,4,High,7,Risk of Violence,-0.73,9,High,Copy,1,0 +8812,57318,48865,PRETRIAL,CARTER,DONALD,NULL,Male,African-American,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/5/13 0:00,4,High,8,Risk of Recidivism,0.82,10,High,Copy,1,0 +8812,57318,48865,PRETRIAL,CARTER,DONALD,NULL,Male,African-American,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/5/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +50962,57339,52101,PRETRIAL,Rivera,Elio,NULL,Male,Caucasian,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +50962,57339,52101,PRETRIAL,Rivera,Elio,NULL,Male,Caucasian,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +50962,57339,52101,PRETRIAL,Rivera,Elio,NULL,Male,Caucasian,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +50953,57326,52091,PRETRIAL,WALDEN,TOMMY,LEE,Male,African-American,10/04/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +50953,57326,52091,PRETRIAL,WALDEN,TOMMY,LEE,Male,African-American,10/04/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +50953,57326,52091,PRETRIAL,WALDEN,TOMMY,LEE,Male,African-American,10/04/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +50955,57328,52093,PRETRIAL,burdin,Bruce,allen,Male,Caucasian,10/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +50955,57328,52093,PRETRIAL,burdin,Bruce,allen,Male,Caucasian,10/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +50955,57328,52093,PRETRIAL,burdin,Bruce,allen,Male,Caucasian,10/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +15195,57334,47385,PRETRIAL,JOHNSON,CLINTON,E,Male,Caucasian,01/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,4,High,7,Risk of Violence,-0.85,9,High,Copy,1,0 +15195,57334,47385,PRETRIAL,JOHNSON,CLINTON,E,Male,Caucasian,01/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,4,High,8,Risk of Recidivism,0.61,9,High,Copy,1,0 +15195,57334,47385,PRETRIAL,JOHNSON,CLINTON,E,Male,Caucasian,01/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +50959,57336,52098,PRETRIAL,PUELLO,ALFONSO,NULL,Male,Hispanic,03/07/33,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,7,Risk of Violence,-4.5,1,Low,New,1,0 +50959,57336,52098,PRETRIAL,PUELLO,ALFONSO,NULL,Male,Hispanic,03/07/33,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,8,Risk of Recidivism,-2.82,1,Low,New,1,0 +50959,57336,52098,PRETRIAL,PUELLO,ALFONSO,NULL,Male,Hispanic,03/07/33,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50956,57329,52094,PRETRIAL,SEWELL,KENNETH,NULL,Male,African-American,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,4,High,7,Risk of Violence,-0.62,10,High,New,1,0 +50956,57329,52094,PRETRIAL,SEWELL,KENNETH,NULL,Male,African-American,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +50956,57329,52094,PRETRIAL,SEWELL,KENNETH,NULL,Male,African-American,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +50958,57333,52097,PRETRIAL,GOUDREAU,AUTA,NULL,Female,African-American,06/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +50958,57333,52097,PRETRIAL,GOUDREAU,AUTA,NULL,Female,African-American,06/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +50958,57333,52097,PRETRIAL,GOUDREAU,AUTA,NULL,Female,African-American,06/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50951,57324,52089,PRETRIAL,Austin,Robert,NULL,Male,African-American,05/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +50951,57324,52089,PRETRIAL,Austin,Robert,NULL,Male,African-American,05/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +50951,57324,52089,PRETRIAL,Austin,Robert,NULL,Male,African-American,05/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +8550,57331,52096,PRETRIAL,Jackson,Leon,NULL,Male,African-American,01/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +8550,57331,52096,PRETRIAL,Jackson,Leon,NULL,Male,African-American,01/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +8550,57331,52096,PRETRIAL,Jackson,Leon,NULL,Male,African-American,01/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +50961,57338,52100,PRETRIAL,Pena- Gonzalez,Reinaldo,Enrique,Male,Caucasian,04/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +50961,57338,52100,PRETRIAL,Pena- Gonzalez,Reinaldo,Enrique,Male,Caucasian,04/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +50961,57338,52100,PRETRIAL,Pena- Gonzalez,Reinaldo,Enrique,Male,Caucasian,04/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +37680,57322,52087,PRETRIAL,GUERRIER,JEAN,NULL,Male,African-American,03/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +37680,57322,52087,PRETRIAL,GUERRIER,JEAN,NULL,Male,African-American,03/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +37680,57322,52087,PRETRIAL,GUERRIER,JEAN,NULL,Male,African-American,03/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50957,57330,52095,PRETRIAL,JONES III,JOHN,W,Male,African-American,06/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +50957,57330,52095,PRETRIAL,JONES III,JOHN,W,Male,African-American,06/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +50957,57330,52095,PRETRIAL,JONES III,JOHN,W,Male,African-American,06/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +15195,52046,47385,PRETRIAL,JOHNSON,CLINTON,E,Male,Caucasian,01/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +15195,52046,47385,PRETRIAL,JOHNSON,CLINTON,E,Male,Caucasian,01/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +15195,52046,47385,PRETRIAL,JOHNSON,CLINTON,E,Male,Caucasian,01/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +11820,57335,11337,PRETRIAL,cypress,jason,NULL,Male,Caucasian,01/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/6/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,Copy,1,0 +11820,57335,11337,PRETRIAL,cypress,jason,NULL,Male,Caucasian,01/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/6/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,Copy,1,0 +11820,57335,11337,PRETRIAL,cypress,jason,NULL,Male,Caucasian,01/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +50954,57327,52092,PRETRIAL,Coppin,Roylon,NULL,Male,Other,06/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +50954,57327,52092,PRETRIAL,Coppin,Roylon,NULL,Male,Other,06/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +50954,57327,52092,PRETRIAL,Coppin,Roylon,NULL,Male,Other,06/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50960,57337,52099,PRETRIAL,Burke,Shelani,NULL,Female,African-American,09/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +50960,57337,52099,PRETRIAL,Burke,Shelani,NULL,Female,African-American,09/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +50960,57337,52099,PRETRIAL,Burke,Shelani,NULL,Female,African-American,09/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +50950,57323,52088,PRETRIAL,Power,Andres,NULL,Male,Hispanic,01/13/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +50950,57323,52088,PRETRIAL,Power,Andres,NULL,Male,Hispanic,01/13/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,8,Risk of Recidivism,-2.74,1,Low,New,1,0 +50950,57323,52088,PRETRIAL,Power,Andres,NULL,Male,Hispanic,01/13/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50952,57325,52090,PRETRIAL,ROBERTS,SUSAN,NULL,Female,African-American,09/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +50952,57325,52090,PRETRIAL,ROBERTS,SUSAN,NULL,Female,African-American,09/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,New,1,0 +50952,57325,52090,PRETRIAL,ROBERTS,SUSAN,NULL,Female,African-American,09/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +8888,57332,8421,PRETRIAL,WALKER,DAVE,NULL,Male,African-American,01/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,Copy,1,0 +8888,57332,8421,PRETRIAL,WALKER,DAVE,NULL,Male,African-American,01/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,Copy,1,0 +8888,57332,8421,PRETRIAL,WALKER,DAVE,NULL,Male,African-American,01/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +50967,57346,52108,PRETRIAL,MCKENZIE,RICHARD,S,Male,African-American,11/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +50967,57346,52108,PRETRIAL,MCKENZIE,RICHARD,S,Male,African-American,11/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +50967,57346,52108,PRETRIAL,MCKENZIE,RICHARD,S,Male,African-American,11/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50973,57353,52113,Probation,maimone,christina,NULL,Female,Hispanic,03/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/7/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +50973,57353,52113,Probation,maimone,christina,NULL,Female,Hispanic,03/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/7/13 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +50973,57353,52113,Probation,maimone,christina,NULL,Female,Hispanic,03/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50980,57360,52120,Probation,Ferrebee,Dawn,NULL,Female,Caucasian,07/10/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/7/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +50980,57360,52120,Probation,Ferrebee,Dawn,NULL,Female,Caucasian,07/10/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/7/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +50980,57360,52120,Probation,Ferrebee,Dawn,NULL,Female,Caucasian,07/10/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +50987,57367,52127,Probation,SOLLINGER,ANTHONY,JAMES,Male,Caucasian,02/02/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +50987,57367,52127,Probation,SOLLINGER,ANTHONY,JAMES,Male,Caucasian,02/02/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +50987,57367,52127,Probation,SOLLINGER,ANTHONY,JAMES,Male,Caucasian,02/02/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50993,57374,52134,PRETRIAL,REINOSO AMAYA,JUAN,CARLOS,Male,Hispanic,02/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +50993,57374,52134,PRETRIAL,REINOSO AMAYA,JUAN,CARLOS,Male,Hispanic,02/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +50993,57374,52134,PRETRIAL,REINOSO AMAYA,JUAN,CARLOS,Male,Hispanic,02/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +50963,57341,52103,PRETRIAL,EDWARDS,KERON,ORLANDO,Male,Other,05/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/7/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +50963,57341,52103,PRETRIAL,EDWARDS,KERON,ORLANDO,Male,Other,05/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/7/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +50963,57341,52103,PRETRIAL,EDWARDS,KERON,ORLANDO,Male,Other,05/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50978,57358,52118,PRETRIAL,MATTHEWS,TACCULAR,NULL,Male,African-American,08/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +50978,57358,52118,PRETRIAL,MATTHEWS,TACCULAR,NULL,Male,African-American,08/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +50978,57358,52118,PRETRIAL,MATTHEWS,TACCULAR,NULL,Male,African-American,08/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50981,57362,52122,PRETRIAL,Strickland,Anthony,Tyrone,Male,African-American,12/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,4,High,7,Risk of Violence,-0.69,9,High,New,1,0 +50981,57362,52122,PRETRIAL,Strickland,Anthony,Tyrone,Male,African-American,12/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,New,1,0 +50981,57362,52122,PRETRIAL,Strickland,Anthony,Tyrone,Male,African-American,12/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,4,High,18,Risk of Failure to Appear,37,10,High,New,1,0 +42925,57372,52132,PRETRIAL,Baska,Eliguisz,NULL,Male,Caucasian,05/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/7/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +42925,57372,52132,PRETRIAL,Baska,Eliguisz,NULL,Male,Caucasian,05/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/7/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +42925,57372,52132,PRETRIAL,Baska,Eliguisz,NULL,Male,Caucasian,05/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50984,57364,52124,PRETRIAL,GREENE,BAILEY,NULL,Female,Caucasian,04/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.23,8,High,New,1,0 +50984,57364,52124,PRETRIAL,GREENE,BAILEY,NULL,Female,Caucasian,04/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +50984,57364,52124,PRETRIAL,GREENE,BAILEY,NULL,Female,Caucasian,04/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,11,1,Low,New,1,0 +25604,57369,52129,PRETRIAL,INMAN,THOMAS,NULL,Male,Caucasian,05/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/7/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +25604,57369,52129,PRETRIAL,INMAN,THOMAS,NULL,Male,Caucasian,05/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +25604,57369,52129,PRETRIAL,INMAN,THOMAS,NULL,Male,Caucasian,05/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/7/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50972,57351,52112,Probation,ZOLNOWSKI,THOMAS,M,Male,Caucasian,01/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/7/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +50972,57351,52112,Probation,ZOLNOWSKI,THOMAS,M,Male,Caucasian,01/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/7/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +50972,57351,52112,Probation,ZOLNOWSKI,THOMAS,M,Male,Caucasian,01/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +50969,57348,52110,PRETRIAL,Alcime,McKenzie,NULL,Male,African-American,08/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +50969,57348,52110,PRETRIAL,Alcime,McKenzie,NULL,Male,African-American,08/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +50969,57348,52110,PRETRIAL,Alcime,McKenzie,NULL,Male,African-American,08/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50977,57356,52116,Probation,cobbs,nathaniel,NULL,Male,African-American,04/27/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/7/13 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,New,1,0 +50977,57356,52116,Probation,cobbs,nathaniel,NULL,Male,African-American,04/27/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/7/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +50977,57356,52116,Probation,cobbs,nathaniel,NULL,Male,African-American,04/27/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/7/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +49128,57343,52105,PRETRIAL,Whitehead,Devon,NULL,Male,African-American,10/18/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +49128,57343,52105,PRETRIAL,Whitehead,Devon,NULL,Male,African-American,10/18/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +49128,57343,52105,PRETRIAL,Whitehead,Devon,NULL,Male,African-American,10/18/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +19434,57340,52102,PRETRIAL,STRATTON,BRET,TRAVIS,Male,Caucasian,12/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.41,3,Low,New,1,0 +19434,57340,52102,PRETRIAL,STRATTON,BRET,TRAVIS,Male,Caucasian,12/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +19434,57340,52102,PRETRIAL,STRATTON,BRET,TRAVIS,Male,Caucasian,12/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +50979,57359,52119,Probation,YUKNUS,MARGARET,ASHLEY,Female,Caucasian,05/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +50979,57359,52119,Probation,YUKNUS,MARGARET,ASHLEY,Female,Caucasian,05/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/13 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +50979,57359,52119,Probation,YUKNUS,MARGARET,ASHLEY,Female,Caucasian,05/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50982,57361,52121,PRETRIAL,Sisto,Joseph,NULL,Male,Caucasian,03/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/7/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +50982,57361,52121,PRETRIAL,Sisto,Joseph,NULL,Male,Caucasian,03/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/7/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +50982,57361,52121,PRETRIAL,Sisto,Joseph,NULL,Male,Caucasian,03/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50986,57366,52126,PRETRIAL,grant,john,hayward,Male,African-American,03/04/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +50986,57366,52126,PRETRIAL,grant,john,hayward,Male,African-American,03/04/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +50986,57366,52126,PRETRIAL,grant,john,hayward,Male,African-American,03/04/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +50988,57368,52128,Probation,Carty,Anne,Marie,Female,African-American,09/10/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/7/13 0:00,2,Medium,7,Risk of Violence,-2.23,4,Low,New,1,0 +50988,57368,52128,Probation,Carty,Anne,Marie,Female,African-American,09/10/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +50988,57368,52128,Probation,Carty,Anne,Marie,Female,African-American,09/10/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/7/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50966,57345,52107,PRETRIAL,CARR,KEVIN,NULL,Male,Caucasian,05/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +50966,57345,52107,PRETRIAL,CARR,KEVIN,NULL,Male,Caucasian,05/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +50966,57345,52107,PRETRIAL,CARR,KEVIN,NULL,Male,Caucasian,05/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +50974,57354,52114,PRETRIAL,Augistin,Aslet,Kevin,Male,African-American,09/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/7/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +50974,57354,52114,PRETRIAL,Augistin,Aslet,Kevin,Male,African-American,09/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/7/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +50974,57354,52114,PRETRIAL,Augistin,Aslet,Kevin,Male,African-American,09/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51023,57422,52177,Probation,Guillen,patricio,NULL,Male,Hispanic,06/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/7/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +51023,57422,52177,Probation,Guillen,patricio,NULL,Male,Hispanic,06/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/7/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +51023,57422,52177,Probation,Guillen,patricio,NULL,Male,Hispanic,06/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50990,57371,52131,Probation,Gilez Lopez,alfredo,NULL,Male,Hispanic,01/12/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/7/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +50990,57371,52131,Probation,Gilez Lopez,alfredo,NULL,Male,Hispanic,01/12/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/7/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +50990,57371,52131,Probation,Gilez Lopez,alfredo,NULL,Male,Hispanic,01/12/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +41888,57350,41631,Probation,Gollette,Tishanna,NULL,Female,African-American,11/06/77,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/7/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +41888,57350,41631,Probation,Gollette,Tishanna,NULL,Female,African-American,11/06/77,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/7/13 0:00,1,Low,8,Risk of Recidivism,-0.53,5,Medium,New,1,0 +41888,57350,41631,Probation,Gollette,Tishanna,NULL,Female,African-American,11/06/77,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +50975,57355,52115,PRETRIAL,Placil,Kennol,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +50975,57355,52115,PRETRIAL,Placil,Kennol,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +50975,57355,52115,PRETRIAL,Placil,Kennol,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50976,57357,52117,PRETRIAL,YOUN,BRANDON,NULL,Male,African-American,03/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +50976,57357,52117,PRETRIAL,YOUN,BRANDON,NULL,Male,African-American,03/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +50976,57357,52117,PRETRIAL,YOUN,BRANDON,NULL,Male,African-American,03/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50989,57370,52130,PRETRIAL,lovato,gabriel,NULL,Male,Hispanic,10/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/7/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +50989,57370,52130,PRETRIAL,lovato,gabriel,NULL,Male,Hispanic,10/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/7/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +50989,57370,52130,PRETRIAL,lovato,gabriel,NULL,Male,Hispanic,10/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,37,10,High,New,1,0 +50983,57363,52123,PRETRIAL,Masses,Johnny,NULL,Female,African-American,09/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +50983,57363,52123,PRETRIAL,Masses,Johnny,NULL,Female,African-American,09/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.79,10,High,New,1,0 +50983,57363,52123,PRETRIAL,Masses,Johnny,NULL,Female,African-American,09/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +50964,57342,52104,PRETRIAL,LEONARD,VERONICA,NULL,Female,Caucasian,09/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +50964,57342,52104,PRETRIAL,LEONARD,VERONICA,NULL,Female,Caucasian,09/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +50964,57342,52104,PRETRIAL,LEONARD,VERONICA,NULL,Female,Caucasian,09/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50970,57349,52111,PRETRIAL,Kinchen,Syrefia,NULL,Female,Other,10/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +50970,57349,52111,PRETRIAL,Kinchen,Syrefia,NULL,Female,Other,10/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +50970,57349,52111,PRETRIAL,Kinchen,Syrefia,NULL,Female,Other,10/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50965,57344,52106,PRETRIAL,Gordon,Percival,NULL,Male,African-American,09/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +50965,57344,52106,PRETRIAL,Gordon,Percival,NULL,Male,African-American,09/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +50965,57344,52106,PRETRIAL,Gordon,Percival,NULL,Male,African-American,09/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +50968,57347,52109,PRETRIAL,NAAR,SEAN,LORENZO,Male,African-American,01/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +50968,57347,52109,PRETRIAL,NAAR,SEAN,LORENZO,Male,African-American,01/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +50968,57347,52109,PRETRIAL,NAAR,SEAN,LORENZO,Male,African-American,01/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50985,57365,52125,Probation,Queen,Mark,Spencer,Male,Caucasian,11/15/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/7/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +50985,57365,52125,Probation,Queen,Mark,Spencer,Male,Caucasian,11/15/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/7/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +50985,57365,52125,Probation,Queen,Mark,Spencer,Male,Caucasian,11/15/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50992,57373,52133,Probation,QUISPE,WALTER,NULL,Male,Hispanic,04/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +50992,57373,52133,Probation,QUISPE,WALTER,NULL,Male,Hispanic,04/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +50992,57373,52133,Probation,QUISPE,WALTER,NULL,Male,Hispanic,04/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50240,57352,51228,PRETRIAL,Graham,Melanie,P,Female,Caucasian,04/29/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,Copy,1,0 +50240,57352,51228,PRETRIAL,Graham,Melanie,P,Female,Caucasian,04/29/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/13 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,Copy,1,0 +50240,57352,51228,PRETRIAL,Graham,Melanie,P,Female,Caucasian,04/29/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +44870,57386,45012,PRETRIAL,Patterson,Aaron,NULL,Male,Caucasian,09/13/65,17,All Scales,Intake,English,Other,Probation,Divorced,1/8/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,Copy,1,0 +44870,57386,45012,PRETRIAL,Patterson,Aaron,NULL,Male,Caucasian,09/13/65,17,All Scales,Intake,English,Other,Probation,Divorced,1/8/13 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,Copy,1,0 +44870,57386,45012,PRETRIAL,Patterson,Aaron,NULL,Male,Caucasian,09/13/65,17,All Scales,Intake,English,Other,Probation,Divorced,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +5754,57378,52138,PRETRIAL,BARRETT,SHIVAUGHN,NULL,Male,African-American,09/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +5754,57378,52138,PRETRIAL,BARRETT,SHIVAUGHN,NULL,Male,African-American,09/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +5754,57378,52138,PRETRIAL,BARRETT,SHIVAUGHN,NULL,Male,African-American,09/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +20741,57399,52156,Probation,Kerr,Donovan,NULL,Male,African-American,02/10/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +20741,57399,52156,Probation,Kerr,Donovan,NULL,Male,African-American,02/10/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +20741,57399,52156,Probation,Kerr,Donovan,NULL,Male,African-American,02/10/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +51012,57391,52148,PRETRIAL,Eriz,David,Edward,Male,Caucasian,09/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/8/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +51012,57391,52148,PRETRIAL,Eriz,David,Edward,Male,Caucasian,09/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/8/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +51012,57391,52148,PRETRIAL,Eriz,David,Edward,Male,Caucasian,09/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50994,57375,52135,PRETRIAL,Still,Gregory,NULL,Male,Caucasian,08/26/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,1/8/13 0:00,1,Low,7,Risk of Violence,-4.32,1,Low,New,1,0 +50994,57375,52135,PRETRIAL,Still,Gregory,NULL,Male,Caucasian,08/26/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,1/8/13 0:00,1,Low,8,Risk of Recidivism,-2.7,1,Low,New,1,0 +50994,57375,52135,PRETRIAL,Still,Gregory,NULL,Male,Caucasian,08/26/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51001,57384,52143,PRETRIAL,Willamson,Shawntee,NULL,Female,African-American,09/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +51001,57384,52143,PRETRIAL,Willamson,Shawntee,NULL,Female,African-American,09/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +51001,57384,52143,PRETRIAL,Willamson,Shawntee,NULL,Female,African-American,09/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +45298,57405,52161,Probation,GRANDE,DELANO,SANTO,Male,Other,01/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +45298,57405,52161,Probation,GRANDE,DELANO,SANTO,Male,Other,01/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +45298,57405,52161,Probation,GRANDE,DELANO,SANTO,Male,Other,01/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +38484,57401,52157,PRETRIAL,Martinez,Miguel,A,Male,Caucasian,09/08/60,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/8/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +38484,57401,52157,PRETRIAL,Martinez,Miguel,A,Male,Caucasian,09/08/60,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/8/13 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +38484,57401,52157,PRETRIAL,Martinez,Miguel,A,Male,Caucasian,09/08/60,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50998,57380,52140,PRETRIAL,Hernandez,Jesus,NULL,Male,Hispanic,05/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +50998,57380,52140,PRETRIAL,Hernandez,Jesus,NULL,Male,Hispanic,05/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +50998,57380,52140,PRETRIAL,Hernandez,Jesus,NULL,Male,Hispanic,05/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50999,57382,52141,PRETRIAL,Cabrermacias,Victor,NULL,Male,Hispanic,01/26/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +50999,57382,52141,PRETRIAL,Cabrermacias,Victor,NULL,Male,Hispanic,01/26/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +50999,57382,52141,PRETRIAL,Cabrermacias,Victor,NULL,Male,Hispanic,01/26/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51017,57396,52153,PRETRIAL,irvin,onterriun,NULL,Male,African-American,11/25/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.24,8,High,New,1,0 +51017,57396,52153,PRETRIAL,irvin,onterriun,NULL,Male,African-American,11/25/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.6,3,Low,New,1,0 +51017,57396,52153,PRETRIAL,irvin,onterriun,NULL,Male,African-American,11/25/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51020,57403,52159,Probation,Coelho,Cristina,NULL,Female,Hispanic,07/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +51020,57403,52159,Probation,Coelho,Cristina,NULL,Female,Hispanic,07/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +51020,57403,52159,Probation,Coelho,Cristina,NULL,Female,Hispanic,07/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51002,57387,52145,Probation,Segura,Xavier,NULL,Male,Hispanic,11/06/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/13 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +51002,57387,52145,Probation,Segura,Xavier,NULL,Male,Hispanic,11/06/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/13 0:00,4,High,8,Risk of Recidivism,0.67,10,High,New,1,0 +51002,57387,52145,Probation,Segura,Xavier,NULL,Male,Hispanic,11/06/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51010,57389,52146,DRRD,Adams,Demetrius,Eugene,Male,African-American,12/23/77,17,All Scales,Intake,English,Probation Violator,Probation,Single,1/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +51010,57389,52146,DRRD,Adams,Demetrius,Eugene,Male,African-American,12/23/77,17,All Scales,Intake,English,Probation Violator,Probation,Single,1/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.24,10,High,New,1,0 +51010,57389,52146,DRRD,Adams,Demetrius,Eugene,Male,African-American,12/23/77,17,All Scales,Intake,English,Probation Violator,Probation,Single,1/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +50996,57377,52137,PRETRIAL,Kirlew,Orlando,NULL,Male,Other,09/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +50996,57377,52137,PRETRIAL,Kirlew,Orlando,NULL,Male,Other,09/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +50996,57377,52137,PRETRIAL,Kirlew,Orlando,NULL,Male,Other,09/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51011,57390,52147,Probation,Bell,Chamora,NULL,Female,African-American,08/31/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +51011,57390,52147,Probation,Bell,Chamora,NULL,Female,African-American,08/31/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/13 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +51011,57390,52147,Probation,Bell,Chamora,NULL,Female,African-American,08/31/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51019,57398,52155,Probation,Scheurich,Diego,NULL,Male,Caucasian,03/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +51019,57398,52155,Probation,Scheurich,Diego,NULL,Male,Caucasian,03/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +51019,57398,52155,Probation,Scheurich,Diego,NULL,Male,Caucasian,03/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +29315,57385,52144,PRETRIAL,Smith,Terry,Daniel,Male,Caucasian,08/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,2,Medium,7,Risk of Violence,-1.34,7,Medium,New,1,0 +29315,57385,52144,PRETRIAL,Smith,Terry,Daniel,Male,Caucasian,08/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +29315,57385,52144,PRETRIAL,Smith,Terry,Daniel,Male,Caucasian,08/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51013,57392,52149,Probation,Darby,Gregory,Bruce,Male,Caucasian,05/27/50,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/8/13 0:00,1,Low,7,Risk of Violence,-4.38,1,Low,New,1,0 +51013,57392,52149,Probation,Darby,Gregory,Bruce,Male,Caucasian,05/27/50,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/8/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +51013,57392,52149,Probation,Darby,Gregory,Bruce,Male,Caucasian,05/27/50,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51022,57406,52162,Probation,Vasquez Gonzalez,Denis,NULL,Male,Hispanic,12/19/79,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,1/8/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +51022,57406,52162,Probation,Vasquez Gonzalez,Denis,NULL,Male,Hispanic,12/19/79,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,1/8/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +51022,57406,52162,Probation,Vasquez Gonzalez,Denis,NULL,Male,Hispanic,12/19/79,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51014,57393,52150,Probation,Curley,Adam,NULL,Male,Caucasian,06/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +51014,57393,52150,Probation,Curley,Adam,NULL,Male,Caucasian,06/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +51014,57393,52150,Probation,Curley,Adam,NULL,Male,Caucasian,06/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +46539,57400,46961,Probation,HARRIGAN,JEAN,NULL,Male,African-American,06/10/70,17,All Scales,Intake,English,Conditional Release,Probation,Married,1/8/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +46539,57400,46961,Probation,HARRIGAN,JEAN,NULL,Male,African-American,06/10/70,17,All Scales,Intake,English,Conditional Release,Probation,Married,1/8/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +46539,57400,46961,Probation,HARRIGAN,JEAN,NULL,Male,African-American,06/10/70,17,All Scales,Intake,English,Conditional Release,Probation,Married,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50997,57379,52139,PRETRIAL,Demeritte,Raphale,NULL,Male,African-American,10/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +50997,57379,52139,PRETRIAL,Demeritte,Raphale,NULL,Male,African-American,10/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,4,High,8,Risk of Recidivism,0.19,8,High,New,1,0 +50997,57379,52139,PRETRIAL,Demeritte,Raphale,NULL,Male,African-American,10/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51018,57397,52154,Probation,Amedee,Yves,NULL,Male,African-American,05/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +51018,57397,52154,Probation,Amedee,Yves,NULL,Male,African-American,05/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +51018,57397,52154,Probation,Amedee,Yves,NULL,Male,African-American,05/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50995,57376,52136,PRETRIAL,Bergeron,Paul,NULL,Male,Caucasian,08/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +50995,57376,52136,PRETRIAL,Bergeron,Paul,NULL,Male,Caucasian,08/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +50995,57376,52136,PRETRIAL,Bergeron,Paul,NULL,Male,Caucasian,08/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51000,57383,52142,PRETRIAL,JEAN-BAPTIST,BRIAN,NULL,Male,African-American,05/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.22,8,High,New,1,0 +51000,57383,52142,PRETRIAL,JEAN-BAPTIST,BRIAN,NULL,Male,African-American,05/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +51000,57383,52142,PRETRIAL,JEAN-BAPTIST,BRIAN,NULL,Male,African-American,05/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +8675,57381,8209,PRETRIAL,CHAMBLIS,Calvin,NULL,Male,African-American,05/18/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/8/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,Copy,1,0 +8675,57381,8209,PRETRIAL,CHAMBLIS,Calvin,NULL,Male,African-American,05/18/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/8/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,Copy,1,0 +8675,57381,8209,PRETRIAL,CHAMBLIS,Calvin,NULL,Male,African-American,05/18/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +51016,57395,52152,PRETRIAL,Francis,William,NULL,Male,Caucasian,10/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +51016,57395,52152,PRETRIAL,Francis,William,NULL,Male,Caucasian,10/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +51016,57395,52152,PRETRIAL,Francis,William,NULL,Male,Caucasian,10/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +9938,57402,52158,PRETRIAL,Richards,Andre,NULL,Female,African-American,09/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +9938,57402,52158,PRETRIAL,Richards,Andre,NULL,Female,African-American,09/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,8,High,New,1,0 +9938,57402,52158,PRETRIAL,Richards,Andre,NULL,Female,African-American,09/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +34810,57404,52160,PRETRIAL,veach,annamarie,NULL,Female,Caucasian,10/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,2,Medium,7,Risk of Violence,-2.84,2,Low,New,1,0 +34810,57404,52160,PRETRIAL,veach,annamarie,NULL,Female,Caucasian,10/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.41,6,Medium,New,1,0 +34810,57404,52160,PRETRIAL,veach,annamarie,NULL,Female,Caucasian,10/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51036,57423,52178,Probation,Battle,Rochelle,NULL,Female,African-American,02/09/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/9/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +51036,57423,52178,Probation,Battle,Rochelle,NULL,Female,African-American,02/09/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +51036,57423,52178,Probation,Battle,Rochelle,NULL,Female,African-American,02/09/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/9/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51042,57432,52184,PRETRIAL,Taylor,Ebony,NULL,Female,African-American,01/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/13 0:00,4,High,7,Risk of Violence,-0.31,10,High,New,1,0 +51042,57432,52184,PRETRIAL,Taylor,Ebony,NULL,Female,African-American,01/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/13 0:00,4,High,8,Risk of Recidivism,0.44,10,High,New,1,0 +51042,57432,52184,PRETRIAL,Taylor,Ebony,NULL,Female,African-American,01/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51053,57446,52196,PRETRIAL,Lewis,Michael,NULL,Male,African-American,09/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +51053,57446,52196,PRETRIAL,Lewis,Michael,NULL,Male,African-American,09/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +51053,57446,52196,PRETRIAL,Lewis,Michael,NULL,Male,African-American,09/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51052,57444,52195,Probation,lena,lorena,NULL,Female,Caucasian,04/28/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/9/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +51052,57444,52195,Probation,lena,lorena,NULL,Female,Caucasian,04/28/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/9/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +51052,57444,52195,Probation,lena,lorena,NULL,Female,Caucasian,04/28/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50928,57430,52060,PRETRIAL,Dorsett,Adrian,NULL,Male,African-American,11/29/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.78,9,High,Copy,1,0 +50928,57430,52060,PRETRIAL,Dorsett,Adrian,NULL,Male,African-American,11/29/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.31,6,Medium,Copy,1,0 +50928,57430,52060,PRETRIAL,Dorsett,Adrian,NULL,Male,African-American,11/29/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +51024,57409,52165,PRETRIAL,Compton,Kavin,NULL,Male,Caucasian,01/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +51024,57409,52165,PRETRIAL,Compton,Kavin,NULL,Male,Caucasian,01/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +51024,57409,52165,PRETRIAL,Compton,Kavin,NULL,Male,Caucasian,01/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51032,57418,52173,PRETRIAL,Lowery,Shameka,NULL,Female,African-American,09/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +51032,57418,52173,PRETRIAL,Lowery,Shameka,NULL,Female,African-American,09/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,8,Risk of Recidivism,-1.62,2,Low,New,1,0 +51032,57418,52173,PRETRIAL,Lowery,Shameka,NULL,Female,African-American,09/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51047,57439,52190,Probation,HOANG,KELLY,NULL,Female,Asian,09/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/9/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +51047,57439,52190,Probation,HOANG,KELLY,NULL,Female,Asian,09/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/9/13 0:00,1,Low,8,Risk of Recidivism,-1.53,2,Low,New,1,0 +51047,57439,52190,Probation,HOANG,KELLY,NULL,Female,Asian,09/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50928,57427,52060,PRETRIAL,Dorsett,Adrian,NULL,Male,African-American,11/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.57,10,High,Copy,1,0 +50928,57427,52060,PRETRIAL,Dorsett,Adrian,NULL,Male,African-American,11/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.31,6,Medium,Copy,1,0 +50928,57427,52060,PRETRIAL,Dorsett,Adrian,NULL,Male,African-American,11/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +45938,57434,46280,PRETRIAL,Green,Curtis,Lindell,Male,African-American,11/28/89,17,All Scales,Intake,English,Pretrial,Probation,Single,1/9/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,Copy,1,0 +45938,57434,46280,PRETRIAL,Green,Curtis,Lindell,Male,African-American,11/28/89,17,All Scales,Intake,English,Pretrial,Probation,Single,1/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.68,4,Low,Copy,1,0 +45938,57434,46280,PRETRIAL,Green,Curtis,Lindell,Male,African-American,11/28/89,17,All Scales,Intake,English,Pretrial,Probation,Single,1/9/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +51035,57421,52176,PRETRIAL,Edwards,Timothy,NULL,Male,African-American,06/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +51035,57421,52176,PRETRIAL,Edwards,Timothy,NULL,Male,African-American,06/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +51035,57421,52176,PRETRIAL,Edwards,Timothy,NULL,Male,African-American,06/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51050,57442,52193,PRETRIAL,IBANEZ,JULIO,NULL,Male,Hispanic,10/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +51050,57442,52193,PRETRIAL,IBANEZ,JULIO,NULL,Male,Hispanic,10/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +51050,57442,52193,PRETRIAL,IBANEZ,JULIO,NULL,Male,Hispanic,10/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51026,57413,52168,PRETRIAL,Rogers,Terell,Lenard,Male,African-American,08/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +51026,57413,52168,PRETRIAL,Rogers,Terell,Lenard,Male,African-American,08/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +51026,57413,52168,PRETRIAL,Rogers,Terell,Lenard,Male,African-American,08/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51028,57414,52169,PRETRIAL,Simonds,Louis,NULL,Male,Other,09/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +51028,57414,52169,PRETRIAL,Simonds,Louis,NULL,Male,Other,09/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +51028,57414,52169,PRETRIAL,Simonds,Louis,NULL,Male,Other,09/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51040,57429,52182,Probation,Quintana,Fancisco,NULL,Male,Hispanic,03/16/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/13 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +51040,57429,52182,Probation,Quintana,Fancisco,NULL,Male,Hispanic,03/16/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +51040,57429,52182,Probation,Quintana,Fancisco,NULL,Male,Hispanic,03/16/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +51025,57408,52164,PRETRIAL,Dozil,Etienne,NULL,Male,African-American,12/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +51025,57408,52164,PRETRIAL,Dozil,Etienne,NULL,Male,African-American,12/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +51025,57408,52164,PRETRIAL,Dozil,Etienne,NULL,Male,African-American,12/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51033,57419,52174,PRETRIAL,Rollins,Derriviann,NULL,Male,African-American,03/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/9/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +51033,57419,52174,PRETRIAL,Rollins,Derriviann,NULL,Male,African-American,03/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/9/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +51033,57419,52174,PRETRIAL,Rollins,Derriviann,NULL,Male,African-American,03/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51037,57424,52179,Probation,Walls,Sergio,NULL,Male,African-American,05/29/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +51037,57424,52179,Probation,Walls,Sergio,NULL,Male,African-American,05/29/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,10,High,New,1,0 +51037,57424,52179,Probation,Walls,Sergio,NULL,Male,African-American,05/29/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51046,57437,52188,DRRD,Silva,Jose,NULL,Male,Hispanic,01/28/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/9/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +51046,57437,52188,DRRD,Silva,Jose,NULL,Male,Hispanic,01/28/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/9/13 0:00,1,Low,8,Risk of Recidivism,-0.28,5,Medium,New,1,0 +51046,57437,52188,DRRD,Silva,Jose,NULL,Male,Hispanic,01/28/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +39656,57411,39197,PRETRIAL,Lake,Horace,NULL,Male,African-American,06/16/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,Copy,1,0 +39656,57411,39197,PRETRIAL,Lake,Horace,NULL,Male,African-American,06/16/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,Copy,1,0 +39656,57411,39197,PRETRIAL,Lake,Horace,NULL,Male,African-American,06/16/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +51030,57416,52171,PRETRIAL,AMENTA,EMANUEL,NULL,Male,Hispanic,04/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/9/13 0:00,2,Medium,7,Risk of Violence,-2.78,2,Low,New,1,0 +51030,57416,52171,PRETRIAL,AMENTA,EMANUEL,NULL,Male,Hispanic,04/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +51030,57416,52171,PRETRIAL,AMENTA,EMANUEL,NULL,Male,Hispanic,04/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/9/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +8591,57438,52189,Probation,Rodriguez,Felix,NULL,Male,Hispanic,08/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/9/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +8591,57438,52189,Probation,Rodriguez,Felix,NULL,Male,Hispanic,08/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/9/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +8591,57438,52189,Probation,Rodriguez,Felix,NULL,Male,Hispanic,08/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51048,57440,52191,Probation,ALBURY,RICHARD,NULL,Male,Caucasian,12/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/9/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +51048,57440,52191,Probation,ALBURY,RICHARD,NULL,Male,Caucasian,12/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/9/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +51048,57440,52191,Probation,ALBURY,RICHARD,NULL,Male,Caucasian,12/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +42676,57410,52166,PRETRIAL,TAVERAS,MANUEL,EUGENIO,Male,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +42676,57410,52166,PRETRIAL,TAVERAS,MANUEL,EUGENIO,Male,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +42676,57410,52166,PRETRIAL,TAVERAS,MANUEL,EUGENIO,Male,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51031,57417,52172,PRETRIAL,CAMPBELL,KATTEAL,JONSHAUN,Male,African-American,01/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +51031,57417,52172,PRETRIAL,CAMPBELL,KATTEAL,JONSHAUN,Male,African-American,01/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +51031,57417,52172,PRETRIAL,CAMPBELL,KATTEAL,JONSHAUN,Male,African-American,01/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51041,57431,52183,Probation,rojas,hildiana,NULL,Female,Hispanic,01/03/91,22,Risk and Prescreen,Intake,Spanish,Post Sentence,Probation,Single,1/9/13 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +51041,57431,52183,Probation,rojas,hildiana,NULL,Female,Hispanic,01/03/91,22,Risk and Prescreen,Intake,Spanish,Post Sentence,Probation,Single,1/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +51041,57431,52183,Probation,rojas,hildiana,NULL,Female,Hispanic,01/03/91,22,Risk and Prescreen,Intake,Spanish,Post Sentence,Probation,Single,1/9/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +7301,57445,48130,PRETRIAL,GORE,JOHNNY,NULL,Male,African-American,10/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/9/13 0:00,4,High,7,Risk of Violence,0.03,10,High,Copy,1,0 +7301,57445,48130,PRETRIAL,GORE,JOHNNY,NULL,Male,African-American,10/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/9/13 0:00,4,High,8,Risk of Recidivism,1.29,10,High,Copy,1,0 +7301,57445,48130,PRETRIAL,GORE,JOHNNY,NULL,Male,African-American,10/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/9/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +51038,57426,52180,PRETRIAL,Higgs,Anthony,NULL,Male,African-American,02/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/9/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +51038,57426,52180,PRETRIAL,Higgs,Anthony,NULL,Male,African-American,02/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/9/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +51038,57426,52180,PRETRIAL,Higgs,Anthony,NULL,Male,African-American,02/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51051,57443,52194,Probation,Robinson,Rudolph,NULL,Male,African-American,12/08/56,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/9/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +51051,57443,52194,Probation,Robinson,Rudolph,NULL,Male,African-American,12/08/56,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/9/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +51051,57443,52194,Probation,Robinson,Rudolph,NULL,Male,African-American,12/08/56,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51039,57428,52181,PRETRIAL,Wilson,Wendy,NULL,Female,Caucasian,01/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/9/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +51039,57428,52181,PRETRIAL,Wilson,Wendy,NULL,Female,Caucasian,01/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/9/13 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +51039,57428,52181,PRETRIAL,Wilson,Wendy,NULL,Female,Caucasian,01/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51034,57420,52175,PRETRIAL,CARTER,TOMMIE,LEE,Male,African-American,07/08/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/9/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +51034,57420,52175,PRETRIAL,CARTER,TOMMIE,LEE,Male,African-American,07/08/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/9/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +51034,57420,52175,PRETRIAL,CARTER,TOMMIE,LEE,Male,African-American,07/08/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51027,57412,52167,PRETRIAL,Person,Sydonie,Iesha,Female,African-American,06/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +51027,57412,52167,PRETRIAL,Person,Sydonie,Iesha,Female,African-American,06/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +51027,57412,52167,PRETRIAL,Person,Sydonie,Iesha,Female,African-American,06/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51029,57415,52170,PRETRIAL,Joseph,Travis,Lamont,Male,African-American,05/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/9/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +51029,57415,52170,PRETRIAL,Joseph,Travis,Lamont,Male,African-American,05/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/9/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +51029,57415,52170,PRETRIAL,Joseph,Travis,Lamont,Male,African-American,05/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51043,57433,52185,Probation,tavera,oskar,NULL,Male,Hispanic,01/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +51043,57433,52185,Probation,tavera,oskar,NULL,Male,Hispanic,01/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +51043,57433,52185,Probation,tavera,oskar,NULL,Male,Hispanic,01/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51078,57483,52230,PRETRIAL,SAINTILUS,SAVANNA,NULL,Female,African-American,06/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +51078,57483,52230,PRETRIAL,SAINTILUS,SAVANNA,NULL,Female,African-American,06/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +51078,57483,52230,PRETRIAL,SAINTILUS,SAVANNA,NULL,Female,African-American,06/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +24039,57462,52211,PRETRIAL,Rucker,Celdrick,Jarrod,Male,African-American,06/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +24039,57462,52211,PRETRIAL,Rucker,Celdrick,Jarrod,Male,African-American,06/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +24039,57462,52211,PRETRIAL,Rucker,Celdrick,Jarrod,Male,African-American,06/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51076,57480,52227,PRETRIAL,Smithberg,Eric,NULL,Male,Caucasian,11/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +51076,57480,52227,PRETRIAL,Smithberg,Eric,NULL,Male,Caucasian,11/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +51076,57480,52227,PRETRIAL,Smithberg,Eric,NULL,Male,Caucasian,11/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51059,57454,52204,PRETRIAL,CERVANTES,MAIKEL,NULL,Male,Caucasian,09/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +51059,57454,52204,PRETRIAL,CERVANTES,MAIKEL,NULL,Male,Caucasian,09/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +51059,57454,52204,PRETRIAL,CERVANTES,MAIKEL,NULL,Male,Caucasian,09/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51081,57488,52235,PRETRIAL,Luxama,James,NULL,Male,African-American,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +51081,57488,52235,PRETRIAL,Luxama,James,NULL,Male,African-American,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +51081,57488,52235,PRETRIAL,Luxama,James,NULL,Male,African-American,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51072,57475,52222,PRETRIAL,Humphrey,Rabina,NULL,Female,Other,07/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/10/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +51072,57475,52222,PRETRIAL,Humphrey,Rabina,NULL,Female,Other,07/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/10/13 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +51072,57475,52222,PRETRIAL,Humphrey,Rabina,NULL,Female,Other,07/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51075,57478,52225,PRETRIAL,Piperwang,Christopher,Brendan,Male,Asian,12/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +51075,57478,52225,PRETRIAL,Piperwang,Christopher,Brendan,Male,Asian,12/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +51075,57478,52225,PRETRIAL,Piperwang,Christopher,Brendan,Male,Asian,12/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +6727,57485,52232,PRETRIAL,DANIELS,SHAQWANA,T,Female,African-American,11/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +6727,57485,52232,PRETRIAL,DANIELS,SHAQWANA,T,Female,African-American,11/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,8,High,New,1,0 +6727,57485,52232,PRETRIAL,DANIELS,SHAQWANA,T,Female,African-American,11/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +51055,57449,52199,PRETRIAL,Costino,Joseph,NULL,Male,Caucasian,03/12/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +51055,57449,52199,PRETRIAL,Costino,Joseph,NULL,Male,Caucasian,03/12/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +51055,57449,52199,PRETRIAL,Costino,Joseph,NULL,Male,Caucasian,03/12/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51067,57464,52213,PRETRIAL,Henry,Timothy,NULL,Male,African-American,07/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +51067,57464,52213,PRETRIAL,Henry,Timothy,NULL,Male,African-American,07/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +51067,57464,52213,PRETRIAL,Henry,Timothy,NULL,Male,African-American,07/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51082,57491,52238,PRETRIAL,johnson,clinton,NULL,Male,African-American,02/08/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +51082,57491,52238,PRETRIAL,johnson,clinton,NULL,Male,African-American,02/08/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +51082,57491,52238,PRETRIAL,johnson,clinton,NULL,Male,African-American,02/08/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +51062,57457,52207,PRETRIAL,SANDERNS,OCON,NULL,Male,Caucasian,04/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +51062,57457,52207,PRETRIAL,SANDERNS,OCON,NULL,Male,Caucasian,04/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +51062,57457,52207,PRETRIAL,SANDERNS,OCON,NULL,Male,Caucasian,04/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51070,57470,52218,Probation,Estopinan,Emilio,NULL,Male,Hispanic,08/04/47,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +51070,57470,52218,Probation,Estopinan,Emilio,NULL,Male,Hispanic,08/04/47,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +51070,57470,52218,Probation,Estopinan,Emilio,NULL,Male,Hispanic,08/04/47,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +23615,57472,23939,PRETRIAL,Simmons,Brandon,NULL,Male,African-American,06/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,4,High,7,Risk of Violence,-0.94,9,High,Copy,1,0 +23615,57472,23939,PRETRIAL,Simmons,Brandon,NULL,Male,African-American,06/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,4,High,8,Risk of Recidivism,0.45,9,High,Copy,1,0 +23615,57472,23939,PRETRIAL,Simmons,Brandon,NULL,Male,African-American,06/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +51057,57452,52202,PRETRIAL,Petit-Frere,Kensley,NULL,Male,African-American,08/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +51057,57452,52202,PRETRIAL,Petit-Frere,Kensley,NULL,Male,African-American,08/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +51057,57452,52202,PRETRIAL,Petit-Frere,Kensley,NULL,Male,African-American,08/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51074,57477,52224,Probation,rojas,pablo,NULL,Male,Hispanic,03/26/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/10/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +51074,57477,52224,Probation,rojas,pablo,NULL,Male,Hispanic,03/26/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/10/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +51074,57477,52224,Probation,rojas,pablo,NULL,Male,Hispanic,03/26/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51061,57456,52206,PRETRIAL,MAROLD,MICHAEL,ROBERT,Male,Caucasian,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,4,High,7,Risk of Violence,-1.23,8,High,New,1,0 +51061,57456,52206,PRETRIAL,MAROLD,MICHAEL,ROBERT,Male,Caucasian,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,4,High,8,Risk of Recidivism,0.62,10,High,New,1,0 +51061,57456,52206,PRETRIAL,MAROLD,MICHAEL,ROBERT,Male,Caucasian,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +28711,57473,52220,Probation,Kane,Alex,NULL,Male,Caucasian,06/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +28711,57473,52220,Probation,Kane,Alex,NULL,Male,Caucasian,06/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +28711,57473,52220,Probation,Kane,Alex,NULL,Male,Caucasian,06/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +1499,57447,52197,PRETRIAL,SEVIL,STEVE,NULL,Male,African-American,07/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +1499,57447,52197,PRETRIAL,SEVIL,STEVE,NULL,Male,African-American,07/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +1499,57447,52197,PRETRIAL,SEVIL,STEVE,NULL,Male,African-American,07/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +44828,57482,52229,Probation,Anderson,Jason,Stephen,Male,Caucasian,03/24/75,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/10/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +44828,57482,52229,Probation,Anderson,Jason,Stephen,Male,Caucasian,03/24/75,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/10/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +44828,57482,52229,Probation,Anderson,Jason,Stephen,Male,Caucasian,03/24/75,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +51080,57487,52234,PRETRIAL,Milbry,Ryan,NULL,Male,African-American,03/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +51080,57487,52234,PRETRIAL,Milbry,Ryan,NULL,Male,African-American,03/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +51080,57487,52234,PRETRIAL,Milbry,Ryan,NULL,Male,African-American,03/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51063,57459,52208,PRETRIAL,Blue,Ladarius,NULL,Male,African-American,02/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.07,8,High,New,1,0 +51063,57459,52208,PRETRIAL,Blue,Ladarius,NULL,Male,African-American,02/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +51063,57459,52208,PRETRIAL,Blue,Ladarius,NULL,Male,African-American,02/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51065,57461,52210,PRETRIAL,GLISSON,JALINQUKA,NULL,Female,African-American,09/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +51065,57461,52210,PRETRIAL,GLISSON,JALINQUKA,NULL,Female,African-American,09/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,9,High,New,1,0 +51065,57461,52210,PRETRIAL,GLISSON,JALINQUKA,NULL,Female,African-American,09/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +45061,57466,52215,PRETRIAL,Johnstone,Kristine,NULL,Female,Caucasian,05/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,2,Medium,7,Risk of Violence,-2.7,2,Low,New,1,0 +45061,57466,52215,PRETRIAL,Johnstone,Kristine,NULL,Female,Caucasian,05/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,6,Medium,New,1,0 +45061,57466,52215,PRETRIAL,Johnstone,Kristine,NULL,Female,Caucasian,05/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +51056,57450,52200,PRETRIAL,Parra,Ivan,Alexander,Male,Caucasian,10/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +51056,57450,52200,PRETRIAL,Parra,Ivan,Alexander,Male,Caucasian,10/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +51056,57450,52200,PRETRIAL,Parra,Ivan,Alexander,Male,Caucasian,10/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51079,57484,52231,PRETRIAL,fulton,brittany,NULL,Female,African-American,07/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +51079,57484,52231,PRETRIAL,fulton,brittany,NULL,Female,African-American,07/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +51079,57484,52231,PRETRIAL,fulton,brittany,NULL,Female,African-American,07/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51071,57471,52219,Probation,Holland,Terry,NULL,Male,Caucasian,09/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +51071,57471,52219,Probation,Holland,Terry,NULL,Male,Caucasian,09/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +51071,57471,52219,Probation,Holland,Terry,NULL,Male,Caucasian,09/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +46767,57458,50377,PRETRIAL,Torres,Adrian,Jose,Male,Caucasian,02/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,Copy,1,0 +46767,57458,50377,PRETRIAL,Torres,Adrian,Jose,Male,Caucasian,02/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,Copy,1,0 +46767,57458,50377,PRETRIAL,Torres,Adrian,Jose,Male,Caucasian,02/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +6071,57479,52226,PRETRIAL,Farrell,Siegel,NULL,Male,African-American,06/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +6071,57479,52226,PRETRIAL,Farrell,Siegel,NULL,Male,African-American,06/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.86,10,High,New,1,0 +6071,57479,52226,PRETRIAL,Farrell,Siegel,NULL,Male,African-American,06/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51066,57463,52212,PRETRIAL,Thomas,Denim,NULL,Male,Caucasian,08/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +51066,57463,52212,PRETRIAL,Thomas,Denim,NULL,Male,Caucasian,08/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +51066,57463,52212,PRETRIAL,Thomas,Denim,NULL,Male,Caucasian,08/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51084,57492,52239,PRETRIAL,Lynch,Justin,NULL,Male,African-American,02/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +51084,57492,52239,PRETRIAL,Lynch,Justin,NULL,Male,African-American,02/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +51084,57492,52239,PRETRIAL,Lynch,Justin,NULL,Male,African-American,02/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51060,57455,52205,PRETRIAL,Magnus,Nicole,NULL,Female,Caucasian,11/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +51060,57455,52205,PRETRIAL,Magnus,Nicole,NULL,Female,Caucasian,11/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +51060,57455,52205,PRETRIAL,Magnus,Nicole,NULL,Female,Caucasian,11/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51083,57490,52237,Probation,Sellas,Paul,NULL,Male,Caucasian,12/05/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +51083,57490,52237,Probation,Sellas,Paul,NULL,Male,Caucasian,12/05/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +51083,57490,52237,Probation,Sellas,Paul,NULL,Male,Caucasian,12/05/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +9980,57486,52233,Probation,Cuccio,Jason,NULL,Male,Caucasian,09/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,1/10/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +9980,57486,52233,Probation,Cuccio,Jason,NULL,Male,Caucasian,09/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,1/10/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +9980,57486,52233,Probation,Cuccio,Jason,NULL,Male,Caucasian,09/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51054,57448,52198,PRETRIAL,Labonte,Rashid,NULL,Male,African-American,03/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +51054,57448,52198,PRETRIAL,Labonte,Rashid,NULL,Male,African-American,03/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +51054,57448,52198,PRETRIAL,Labonte,Rashid,NULL,Male,African-American,03/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54580,61992,56265,Probation,Traendly,George,NULL,Male,Caucasian,07/03/56,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +54580,61992,56265,Probation,Traendly,George,NULL,Male,Caucasian,07/03/56,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +54580,61992,56265,Probation,Traendly,George,NULL,Male,Caucasian,07/03/56,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +5748,57451,52201,PRETRIAL,LIBERIS,DAVID,NULL,Male,Other,07/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +5748,57451,52201,PRETRIAL,LIBERIS,DAVID,NULL,Male,Other,07/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +5748,57451,52201,PRETRIAL,LIBERIS,DAVID,NULL,Male,Other,07/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51077,57481,52228,PRETRIAL,sutton,rochelle,NULL,Female,African-American,12/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +51077,57481,52228,PRETRIAL,sutton,rochelle,NULL,Female,African-American,12/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,8,High,New,1,0 +51077,57481,52228,PRETRIAL,sutton,rochelle,NULL,Female,African-American,12/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51058,57453,52203,PRETRIAL,Higgs,Donnalie,NULL,Female,African-American,03/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +51058,57453,52203,PRETRIAL,Higgs,Donnalie,NULL,Female,African-American,03/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +51058,57453,52203,PRETRIAL,Higgs,Donnalie,NULL,Female,African-American,03/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51064,57460,52209,PRETRIAL,Bonair,Giovanni,NULL,Male,African-American,11/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +51064,57460,52209,PRETRIAL,Bonair,Giovanni,NULL,Male,African-American,11/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +51064,57460,52209,PRETRIAL,Bonair,Giovanni,NULL,Male,African-American,11/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51069,57467,52216,Probation,Cook,Antwon,NULL,Male,African-American,11/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +51069,57467,52216,Probation,Cook,Antwon,NULL,Male,African-American,11/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +51069,57467,52216,Probation,Cook,Antwon,NULL,Male,African-American,11/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +44784,57474,52221,PRETRIAL,STOKES,TAVON,NULL,Male,African-American,09/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +44784,57474,52221,PRETRIAL,STOKES,TAVON,NULL,Male,African-American,09/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +44784,57474,52221,PRETRIAL,STOKES,TAVON,NULL,Male,African-American,09/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +23615,28845,23939,PRETRIAL,Simmons,Brandon,NULL,Male,African-American,06/08/85,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,4,High,7,Risk of Violence,-0.74,9,High,Copy,1,0 +23615,28845,23939,PRETRIAL,Simmons,Brandon,NULL,Male,African-American,06/08/85,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,Copy,1,0 +23615,28845,23939,PRETRIAL,Simmons,Brandon,NULL,Male,African-American,06/08/85,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +51097,57504,52250,PRETRIAL,Willey,Allen,NULL,Male,Caucasian,04/15/42,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-4.45,1,Low,New,1,0 +51097,57504,52250,PRETRIAL,Willey,Allen,NULL,Male,Caucasian,04/15/42,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-2.81,1,Low,New,1,0 +51097,57504,52250,PRETRIAL,Willey,Allen,NULL,Male,Caucasian,04/15/42,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51113,57523,52267,PRETRIAL,ATWELL,WALTER,LEE,Male,African-American,06/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +51113,57523,52267,PRETRIAL,ATWELL,WALTER,LEE,Male,African-American,06/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +51113,57523,52267,PRETRIAL,ATWELL,WALTER,LEE,Male,African-American,06/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +4411,57502,52248,PRETRIAL,PICOU,NAFISA,NULL,Female,African-American,04/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +4411,57502,52248,PRETRIAL,PICOU,NAFISA,NULL,Female,African-American,04/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,4,High,8,Risk of Recidivism,0.21,9,High,New,1,0 +4411,57502,52248,PRETRIAL,PICOU,NAFISA,NULL,Female,African-American,04/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,4,High,18,Risk of Failure to Appear,29,9,High,New,1,0 +51114,57525,52269,PRETRIAL,FLOYD,TRAVIS,NULL,Male,African-American,01/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +51114,57525,52269,PRETRIAL,FLOYD,TRAVIS,NULL,Male,African-American,01/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +51114,57525,52269,PRETRIAL,FLOYD,TRAVIS,NULL,Male,African-American,01/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +25717,57532,52275,PRETRIAL,Caldwell,Gregory,Lee,Male,African-American,08/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +25717,57532,52275,PRETRIAL,Caldwell,Gregory,Lee,Male,African-American,08/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,4,High,8,Risk of Recidivism,0.65,10,High,New,1,0 +25717,57532,52275,PRETRIAL,Caldwell,Gregory,Lee,Male,African-American,08/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51104,57511,52257,PRETRIAL,Trinh,Huy,Kien,Male,Asian,02/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +51104,57511,52257,PRETRIAL,Trinh,Huy,Kien,Male,Asian,02/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +51104,57511,52257,PRETRIAL,Trinh,Huy,Kien,Male,Asian,02/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +35922,57516,49580,PRETRIAL,Goldsby,Avis,NULL,Male,African-American,07/08/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +35922,57516,49580,PRETRIAL,Goldsby,Avis,NULL,Male,African-American,07/08/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,4,High,8,Risk of Recidivism,0.55,9,High,New,1,0 +35922,57516,49580,PRETRIAL,Goldsby,Avis,NULL,Male,African-American,07/08/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +43400,57520,49946,PRETRIAL,Kelly,Jaime,NULL,Male,Caucasian,02/09/76,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +43400,57520,49946,PRETRIAL,Kelly,Jaime,NULL,Male,Caucasian,02/09/76,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.45,4,Low,New,1,0 +43400,57520,49946,PRETRIAL,Kelly,Jaime,NULL,Male,Caucasian,02/09/76,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +51100,57507,52253,PRETRIAL,Johnson,Tavia,NULL,Female,African-American,10/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +51100,57507,52253,PRETRIAL,Johnson,Tavia,NULL,Female,African-American,10/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +51100,57507,52253,PRETRIAL,Johnson,Tavia,NULL,Female,African-American,10/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51111,57521,52265,Probation,Lewis,Carlyne,NULL,Female,African-American,01/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +51111,57521,52265,Probation,Lewis,Carlyne,NULL,Female,African-American,01/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +51111,57521,52265,Probation,Lewis,Carlyne,NULL,Female,African-American,01/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51090,57500,52246,PRETRIAL,Slater,Justin,NULL,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +51090,57500,52246,PRETRIAL,Slater,Justin,NULL,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +51090,57500,52246,PRETRIAL,Slater,Justin,NULL,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +39814,57528,39377,PRETRIAL,Joseph,Shirlene,NULL,Female,African-American,06/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,Copy,1,0 +39814,57528,39377,PRETRIAL,Joseph,Shirlene,NULL,Female,African-American,06/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,Copy,1,0 +39814,57528,39377,PRETRIAL,Joseph,Shirlene,NULL,Female,African-American,06/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +51106,57513,52259,PRETRIAL,Justice,Juwan,NULL,Male,African-American,11/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +51106,57513,52259,PRETRIAL,Justice,Juwan,NULL,Male,African-American,11/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +51106,57513,52259,PRETRIAL,Justice,Juwan,NULL,Male,African-American,11/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51087,57497,52243,PRETRIAL,Metayer,Markendy,NULL,Male,African-American,12/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +51087,57497,52243,PRETRIAL,Metayer,Markendy,NULL,Male,African-American,12/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.66,10,High,New,1,0 +51087,57497,52243,PRETRIAL,Metayer,Markendy,NULL,Male,African-American,12/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51115,57526,52270,Probation,Moore,Precious,NULL,Female,African-American,01/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +51115,57526,52270,Probation,Moore,Precious,NULL,Female,African-American,01/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,10,High,New,1,0 +51115,57526,52270,Probation,Moore,Precious,NULL,Female,African-American,01/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +51098,57505,52251,PRETRIAL,Forbes,Laricka,NULL,Male,African-American,10/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,2,Medium,7,Risk of Violence,-2.79,2,Low,New,1,0 +51098,57505,52251,PRETRIAL,Forbes,Laricka,NULL,Male,African-American,10/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +51098,57505,52251,PRETRIAL,Forbes,Laricka,NULL,Male,African-American,10/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51109,57518,52263,PRETRIAL,Gamali,Josh,NULL,Male,Caucasian,08/10/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/11/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +51109,57518,52263,PRETRIAL,Gamali,Josh,NULL,Male,Caucasian,08/10/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +51109,57518,52263,PRETRIAL,Gamali,Josh,NULL,Male,Caucasian,08/10/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/11/13 0:00,2,Medium,18,Risk of Failure to Appear,47,10,High,New,1,0 +51086,57496,52242,PRETRIAL,Brewster,Michael,NULL,Male,Caucasian,08/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/11/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +51086,57496,52242,PRETRIAL,Brewster,Michael,NULL,Male,Caucasian,08/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +51086,57496,52242,PRETRIAL,Brewster,Michael,NULL,Male,Caucasian,08/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/11/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51119,57531,52274,Probation,Paredes,DIONISQUI,NULL,Female,Hispanic,05/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +51119,57531,52274,Probation,Paredes,DIONISQUI,NULL,Female,Hispanic,05/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +51119,57531,52274,Probation,Paredes,DIONISQUI,NULL,Female,Hispanic,05/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51096,57503,52249,PRETRIAL,Laboyrodriguez,Roy,NULL,Male,Caucasian,12/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +51096,57503,52249,PRETRIAL,Laboyrodriguez,Roy,NULL,Male,Caucasian,12/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +51096,57503,52249,PRETRIAL,Laboyrodriguez,Roy,NULL,Male,Caucasian,12/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51103,57510,52256,PRETRIAL,Garrincha,Merizier,NULL,Male,Other,10/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +51103,57510,52256,PRETRIAL,Garrincha,Merizier,NULL,Male,Other,10/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +51103,57510,52256,PRETRIAL,Garrincha,Merizier,NULL,Male,Other,10/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51108,57517,52262,Probation,owens,chiquita,NULL,Female,African-American,03/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +51108,57517,52262,Probation,owens,chiquita,NULL,Female,African-American,03/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,7,Medium,New,1,0 +51108,57517,52262,Probation,owens,chiquita,NULL,Female,African-American,03/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +51088,57498,52244,PRETRIAL,Richard,Kerry,NULL,Male,Caucasian,11/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +51088,57498,52244,PRETRIAL,Richard,Kerry,NULL,Male,Caucasian,11/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +51088,57498,52244,PRETRIAL,Richard,Kerry,NULL,Male,Caucasian,11/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51105,57512,52258,PRETRIAL,Warner,JoDarian,NULL,Male,African-American,02/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +51105,57512,52258,PRETRIAL,Warner,JoDarian,NULL,Male,African-American,02/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +51105,57512,52258,PRETRIAL,Warner,JoDarian,NULL,Male,African-American,02/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51107,57515,52261,PRETRIAL,CLARRISA,DENORD,NULL,Female,African-American,07/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/11/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +51107,57515,52261,PRETRIAL,CLARRISA,DENORD,NULL,Female,African-American,07/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +51107,57515,52261,PRETRIAL,CLARRISA,DENORD,NULL,Female,African-American,07/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +51117,57529,52272,PRETRIAL,Ecklund,Bradley,NULL,Male,Caucasian,06/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/11/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +51117,57529,52272,PRETRIAL,Ecklund,Bradley,NULL,Male,Caucasian,06/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +51117,57529,52272,PRETRIAL,Ecklund,Bradley,NULL,Male,Caucasian,06/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51101,57508,52254,PRETRIAL,Beltran,Juan,NULL,Male,African-American,05/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,New,1,0 +51101,57508,52254,PRETRIAL,Beltran,Juan,NULL,Male,African-American,05/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +51101,57508,52254,PRETRIAL,Beltran,Juan,NULL,Male,African-American,05/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51110,57519,52264,PRETRIAL,SENA,JODIE,NULL,Female,Caucasian,01/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +51110,57519,52264,PRETRIAL,SENA,JODIE,NULL,Female,Caucasian,01/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +51110,57519,52264,PRETRIAL,SENA,JODIE,NULL,Female,Caucasian,01/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +45057,57524,52268,PRETRIAL,SINGLETARY,MARCUS,NULL,Male,African-American,03/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/11/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +45057,57524,52268,PRETRIAL,SINGLETARY,MARCUS,NULL,Male,African-American,03/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/11/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +45057,57524,52268,PRETRIAL,SINGLETARY,MARCUS,NULL,Male,African-American,03/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51099,57506,52252,PRETRIAL,Sparks,Eric,NULL,Male,African-American,07/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +51099,57506,52252,PRETRIAL,Sparks,Eric,NULL,Male,African-American,07/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +51099,57506,52252,PRETRIAL,Sparks,Eric,NULL,Male,African-American,07/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51085,57493,52240,PRETRIAL,Shiver,Soloman,NULL,Male,African-American,10/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/11/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +51085,57493,52240,PRETRIAL,Shiver,Soloman,NULL,Male,African-American,10/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +51085,57493,52240,PRETRIAL,Shiver,Soloman,NULL,Male,African-American,10/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51116,57527,52271,PRETRIAL,Blanco,Eduard,NULL,Male,Hispanic,08/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/11/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +51116,57527,52271,PRETRIAL,Blanco,Eduard,NULL,Male,Hispanic,08/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/11/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +51116,57527,52271,PRETRIAL,Blanco,Eduard,NULL,Male,Hispanic,08/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51089,57499,52245,PRETRIAL,Sutton,Alexander,NULL,Male,African-American,02/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +51089,57499,52245,PRETRIAL,Sutton,Alexander,NULL,Male,African-American,02/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +51089,57499,52245,PRETRIAL,Sutton,Alexander,NULL,Male,African-American,02/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +43166,57514,52260,PRETRIAL,Evans,Dontavious,NULL,Male,African-American,09/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +43166,57514,52260,PRETRIAL,Evans,Dontavious,NULL,Male,African-American,09/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +43166,57514,52260,PRETRIAL,Evans,Dontavious,NULL,Male,African-American,09/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51102,57509,52255,PRETRIAL,Robinson,Earnest,NULL,Male,African-American,09/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +51102,57509,52255,PRETRIAL,Robinson,Earnest,NULL,Male,African-American,09/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +51102,57509,52255,PRETRIAL,Robinson,Earnest,NULL,Male,African-American,09/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51112,57522,52266,Probation,leto,valerie,NULL,Female,Caucasian,11/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +51112,57522,52266,Probation,leto,valerie,NULL,Female,Caucasian,11/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +51112,57522,52266,Probation,leto,valerie,NULL,Female,Caucasian,11/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51118,57530,52273,PRETRIAL,brainard,corinne,NULL,Female,Caucasian,12/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/11/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +51118,57530,52273,PRETRIAL,brainard,corinne,NULL,Female,Caucasian,12/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/11/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +51118,57530,52273,PRETRIAL,brainard,corinne,NULL,Female,Caucasian,12/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51095,57501,52247,PRETRIAL,Herchi,Michel,NULL,Male,Caucasian,10/01/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/11/13 0:00,1,Low,7,Risk of Violence,-4.27,1,Low,New,1,0 +51095,57501,52247,PRETRIAL,Herchi,Michel,NULL,Male,Caucasian,10/01/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/11/13 0:00,1,Low,8,Risk of Recidivism,-2.69,1,Low,New,1,0 +51095,57501,52247,PRETRIAL,Herchi,Michel,NULL,Male,Caucasian,10/01/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +15576,57551,14899,DRRD,Patterson,Marvin,Jenkins,Male,African-American,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,7,Risk of Violence,-0.59,10,High,Copy,1,0 +15576,57551,14899,DRRD,Patterson,Marvin,Jenkins,Male,African-American,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,8,Risk of Recidivism,1.09,10,High,Copy,1,0 +15576,57551,14899,DRRD,Patterson,Marvin,Jenkins,Male,African-American,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,18,Risk of Failure to Appear,24,5,Medium,Copy,1,0 +4086,57548,52288,PRETRIAL,MOZIE,CHRISTOPHER,ROBERT,Male,African-American,09/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +4086,57548,52288,PRETRIAL,MOZIE,CHRISTOPHER,ROBERT,Male,African-American,09/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,8,Risk of Recidivism,0.25,8,High,New,1,0 +4086,57548,52288,PRETRIAL,MOZIE,CHRISTOPHER,ROBERT,Male,African-American,09/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +14288,57556,13674,PRETRIAL,YATES,MICHAEL,NULL,Male,African-American,10/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,7,Risk of Violence,-1.05,8,High,Copy,1,0 +14288,57556,13674,PRETRIAL,YATES,MICHAEL,NULL,Male,African-American,10/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,8,Risk of Recidivism,0.72,10,High,Copy,1,0 +14288,57556,13674,PRETRIAL,YATES,MICHAEL,NULL,Male,African-American,10/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +51126,57543,52284,PRETRIAL,King,Elliot,NULL,Male,African-American,06/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.29,3,Low,New,1,0 +51126,57543,52284,PRETRIAL,King,Elliot,NULL,Male,African-American,06/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +51126,57543,52284,PRETRIAL,King,Elliot,NULL,Male,African-American,06/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +5285,57535,32489,PRETRIAL,BREZNER,ELLEN,NULL,Female,Caucasian,11/02/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/12/13 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,Copy,1,0 +5285,57535,32489,PRETRIAL,BREZNER,ELLEN,NULL,Female,Caucasian,11/02/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,Copy,1,0 +5285,57535,32489,PRETRIAL,BREZNER,ELLEN,NULL,Female,Caucasian,11/02/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/12/13 0:00,2,Medium,18,Risk of Failure to Appear,40,10,High,Copy,1,0 +51133,57554,52293,PRETRIAL,Lee,Jong,Chul,Male,Caucasian,04/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +51133,57554,52293,PRETRIAL,Lee,Jong,Chul,Male,Caucasian,04/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +51133,57554,52293,PRETRIAL,Lee,Jong,Chul,Male,Caucasian,04/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51128,57545,52286,PRETRIAL,Rasskazov,Phillip,NULL,Male,Caucasian,08/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +51128,57545,52286,PRETRIAL,Rasskazov,Phillip,NULL,Male,Caucasian,08/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +51128,57545,52286,PRETRIAL,Rasskazov,Phillip,NULL,Male,Caucasian,08/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +43756,57550,52290,PRETRIAL,GAET-JENS,POLTNICE,NULL,Male,African-American,03/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,7,Risk of Violence,-2.73,2,Low,New,1,0 +43756,57550,52290,PRETRIAL,GAET-JENS,POLTNICE,NULL,Male,African-American,03/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +43756,57550,52290,PRETRIAL,GAET-JENS,POLTNICE,NULL,Male,African-American,03/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51120,57533,52276,PRETRIAL,MURRAY,BRANDON,ANTHONY,Male,African-American,09/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +51120,57533,52276,PRETRIAL,MURRAY,BRANDON,ANTHONY,Male,African-American,09/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +51120,57533,52276,PRETRIAL,MURRAY,BRANDON,ANTHONY,Male,African-American,09/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51136,57559,52296,PRETRIAL,Beach,Kevin,NULL,Male,African-American,12/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +51136,57559,52296,PRETRIAL,Beach,Kevin,NULL,Male,African-American,12/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +51136,57559,52296,PRETRIAL,Beach,Kevin,NULL,Male,African-American,12/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51138,57561,52298,PRETRIAL,Addison,Ricky,NULL,Male,African-American,09/25/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,7,Risk of Violence,-0.71,9,High,New,1,0 +51138,57561,52298,PRETRIAL,Addison,Ricky,NULL,Male,African-American,09/25/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,8,Risk of Recidivism,0.2,8,High,New,1,0 +51138,57561,52298,PRETRIAL,Addison,Ricky,NULL,Male,African-American,09/25/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +51123,57538,52279,PRETRIAL,WALKER,SAMUEL,MAGIG,Male,African-American,02/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.26,3,Low,New,1,0 +51123,57538,52279,PRETRIAL,WALKER,SAMUEL,MAGIG,Male,African-American,02/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +51123,57538,52279,PRETRIAL,WALKER,SAMUEL,MAGIG,Male,African-American,02/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51125,57540,52281,PRETRIAL,Minder,Dayna,NULL,Female,Caucasian,06/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +51125,57540,52281,PRETRIAL,Minder,Dayna,NULL,Female,Caucasian,06/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +51125,57540,52281,PRETRIAL,Minder,Dayna,NULL,Female,Caucasian,06/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51131,57552,52291,PRETRIAL,Rosenbaum,Thomas,Allen,Male,Caucasian,11/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +51131,57552,52291,PRETRIAL,Rosenbaum,Thomas,Allen,Male,Caucasian,11/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +51131,57552,52291,PRETRIAL,Rosenbaum,Thomas,Allen,Male,Caucasian,11/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51124,57539,52280,PRETRIAL,LAUF,JONATHAN,DOUGLAS,Male,Caucasian,11/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.43,3,Low,New,1,0 +51124,57539,52280,PRETRIAL,LAUF,JONATHAN,DOUGLAS,Male,Caucasian,11/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +51124,57539,52280,PRETRIAL,LAUF,JONATHAN,DOUGLAS,Male,Caucasian,11/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51127,57544,52285,PRETRIAL,Bleier,Michael,NULL,Male,Caucasian,10/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +51127,57544,52285,PRETRIAL,Bleier,Michael,NULL,Male,Caucasian,10/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +51127,57544,52285,PRETRIAL,Bleier,Michael,NULL,Male,Caucasian,10/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51129,57547,52287,PRETRIAL,Davila,Rico,NULL,Male,Caucasian,03/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,7,Risk of Violence,-2.76,2,Low,New,1,0 +51129,57547,52287,PRETRIAL,Davila,Rico,NULL,Male,Caucasian,03/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +51129,57547,52287,PRETRIAL,Davila,Rico,NULL,Male,Caucasian,03/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51130,57549,52289,PRETRIAL,Garber,Jonathan,NULL,Male,African-American,06/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,1/12/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +51130,57549,52289,PRETRIAL,Garber,Jonathan,NULL,Male,African-American,06/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,1/12/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +51130,57549,52289,PRETRIAL,Garber,Jonathan,NULL,Male,African-American,06/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,1/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51140,57563,52300,PRETRIAL,LAMBERT,FREDRICK,NULL,Male,African-American,04/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +51140,57563,52300,PRETRIAL,LAMBERT,FREDRICK,NULL,Male,African-American,04/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +51140,57563,52300,PRETRIAL,LAMBERT,FREDRICK,NULL,Male,African-American,04/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +20491,57542,52283,PRETRIAL,MERCADO,JOSHUA,TAYLOR,Male,Caucasian,06/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +20491,57542,52283,PRETRIAL,MERCADO,JOSHUA,TAYLOR,Male,Caucasian,06/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +20491,57542,52283,PRETRIAL,MERCADO,JOSHUA,TAYLOR,Male,Caucasian,06/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51121,57536,52277,PRETRIAL,Wierengo,Anthony,NULL,Male,Caucasian,08/20/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +51121,57536,52277,PRETRIAL,Wierengo,Anthony,NULL,Male,Caucasian,08/20/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +51121,57536,52277,PRETRIAL,Wierengo,Anthony,NULL,Male,Caucasian,08/20/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51134,57555,52294,PRETRIAL,Papacosmas,Thomas,NULL,Male,Caucasian,04/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +51134,57555,52294,PRETRIAL,Papacosmas,Thomas,NULL,Male,Caucasian,04/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +51134,57555,52294,PRETRIAL,Papacosmas,Thomas,NULL,Male,Caucasian,04/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51135,57557,52295,PRETRIAL,Pierre-Louis,Fabienne,NULL,Female,Other,08/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +51135,57557,52295,PRETRIAL,Pierre-Louis,Fabienne,NULL,Female,Other,08/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,7,Medium,New,1,0 +51135,57557,52295,PRETRIAL,Pierre-Louis,Fabienne,NULL,Female,Other,08/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +51122,57537,52278,PRETRIAL,Fanea,Emanoil,NULL,Male,Caucasian,09/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +51122,57537,52278,PRETRIAL,Fanea,Emanoil,NULL,Male,Caucasian,09/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +51122,57537,52278,PRETRIAL,Fanea,Emanoil,NULL,Male,Caucasian,09/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +7022,57541,52282,PRETRIAL,mickles,keion,NULL,Male,African-American,10/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +7022,57541,52282,PRETRIAL,mickles,keion,NULL,Male,African-American,10/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +7022,57541,52282,PRETRIAL,mickles,keion,NULL,Male,African-American,10/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +18382,57558,17654,PRETRIAL,ADAN,ALEJANDRO,A,Male,African-American,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,7,Risk of Violence,-1.01,8,High,Copy,1,0 +18382,57558,17654,PRETRIAL,ADAN,ALEJANDRO,A,Male,African-American,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,8,Risk of Recidivism,0.58,9,High,Copy,1,0 +18382,57558,17654,PRETRIAL,ADAN,ALEJANDRO,A,Male,African-American,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,18,Risk of Failure to Appear,28,7,Medium,Copy,1,0 +51139,57562,52299,PRETRIAL,CARPENTER,EDWIN,NULL,Male,Caucasian,05/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.15,4,Low,New,1,0 +51139,57562,52299,PRETRIAL,CARPENTER,EDWIN,NULL,Male,Caucasian,05/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +51139,57562,52299,PRETRIAL,CARPENTER,EDWIN,NULL,Male,Caucasian,05/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +46011,57546,46360,PRETRIAL,BONES,ANTHONY,NULL,Male,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,7,Risk of Violence,-0.98,9,High,Copy,1,0 +46011,57546,46360,PRETRIAL,BONES,ANTHONY,NULL,Male,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,Copy,1,0 +46011,57546,46360,PRETRIAL,BONES,ANTHONY,NULL,Male,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +51132,57553,52292,PRETRIAL,Cruz,Daniel,NULL,Male,Caucasian,12/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/12/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +51132,57553,52292,PRETRIAL,Cruz,Daniel,NULL,Male,Caucasian,12/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/12/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +51132,57553,52292,PRETRIAL,Cruz,Daniel,NULL,Male,Caucasian,12/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51137,57560,52297,PRETRIAL,Brent,George,NULL,Male,Caucasian,03/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +51137,57560,52297,PRETRIAL,Brent,George,NULL,Male,Caucasian,03/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +51137,57560,52297,PRETRIAL,Brent,George,NULL,Male,Caucasian,03/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51143,57567,52304,PRETRIAL,Wright,Joe,NULL,Male,African-American,01/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +51143,57567,52304,PRETRIAL,Wright,Joe,NULL,Male,African-American,01/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +51143,57567,52304,PRETRIAL,Wright,Joe,NULL,Male,African-American,01/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +51159,57581,52318,PRETRIAL,Sneed,Jammie,NULL,Male,African-American,09/14/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +51159,57581,52318,PRETRIAL,Sneed,Jammie,NULL,Male,African-American,09/14/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +51159,57581,52318,PRETRIAL,Sneed,Jammie,NULL,Male,African-American,09/14/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51153,57574,52311,PRETRIAL,Alleyne,Jamaal,NULL,Male,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +51153,57574,52311,PRETRIAL,Alleyne,Jamaal,NULL,Male,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +51153,57574,52311,PRETRIAL,Alleyne,Jamaal,NULL,Male,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51157,57579,52316,PRETRIAL,Dephillipo,Anthony,NULL,Male,African-American,09/14/29,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +51157,57579,52316,PRETRIAL,Dephillipo,Anthony,NULL,Male,African-American,09/14/29,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +51157,57579,52316,PRETRIAL,Dephillipo,Anthony,NULL,Male,African-American,09/14/29,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +30652,57576,52313,PRETRIAL,LEVY,michael,NULL,Male,Caucasian,12/22/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +30652,57576,52313,PRETRIAL,LEVY,michael,NULL,Male,Caucasian,12/22/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +30652,57576,52313,PRETRIAL,LEVY,michael,NULL,Male,Caucasian,12/22/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +35453,57583,52320,PRETRIAL,GRACE,ROBERT,NULL,Male,Caucasian,01/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +35453,57583,52320,PRETRIAL,GRACE,ROBERT,NULL,Male,Caucasian,01/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +35453,57583,52320,PRETRIAL,GRACE,ROBERT,NULL,Male,Caucasian,01/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +51165,57588,52325,PRETRIAL,Del-Carmen,Valentin,V,Male,Hispanic,03/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +51165,57588,52325,PRETRIAL,Del-Carmen,Valentin,V,Male,Hispanic,03/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +51165,57588,52325,PRETRIAL,Del-Carmen,Valentin,V,Male,Hispanic,03/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51150,57570,52307,PRETRIAL,Lamb,Bess,NULL,Female,Caucasian,03/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +51150,57570,52307,PRETRIAL,Lamb,Bess,NULL,Female,Caucasian,03/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +51150,57570,52307,PRETRIAL,Lamb,Bess,NULL,Female,Caucasian,03/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51156,57578,52315,PRETRIAL,VANSTEENKISTE,JOHN,HENRI,Male,Caucasian,08/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/13/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +51156,57578,52315,PRETRIAL,VANSTEENKISTE,JOHN,HENRI,Male,Caucasian,08/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/13/13 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +51156,57578,52315,PRETRIAL,VANSTEENKISTE,JOHN,HENRI,Male,Caucasian,08/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51142,57565,52302,PRETRIAL,Fils-Aime,Jean,NULL,Male,African-American,07/31/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +51142,57565,52302,PRETRIAL,Fils-Aime,Jean,NULL,Male,African-American,07/31/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +51142,57565,52302,PRETRIAL,Fils-Aime,Jean,NULL,Male,African-American,07/31/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +17967,57573,52310,PRETRIAL,TOUSSAINT,STEVEN,NULL,Male,African-American,08/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,4,High,7,Risk of Violence,-0.53,10,High,New,1,0 +17967,57573,52310,PRETRIAL,TOUSSAINT,STEVEN,NULL,Male,African-American,08/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,4,High,8,Risk of Recidivism,0.84,10,High,New,1,0 +17967,57573,52310,PRETRIAL,TOUSSAINT,STEVEN,NULL,Male,African-American,08/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51163,57586,52323,PRETRIAL,MANZE,GREGORY,ROBERT,Male,Caucasian,12/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +51163,57586,52323,PRETRIAL,MANZE,GREGORY,ROBERT,Male,Caucasian,12/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +51163,57586,52323,PRETRIAL,MANZE,GREGORY,ROBERT,Male,Caucasian,12/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51164,57587,52324,PRETRIAL,Lynn,Lewis,Bernard,Male,African-American,01/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +51164,57587,52324,PRETRIAL,Lynn,Lewis,Bernard,Male,African-American,01/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +51164,57587,52324,PRETRIAL,Lynn,Lewis,Bernard,Male,African-American,01/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51166,57589,52326,PRETRIAL,Mcdaniel,Christian,L,Male,Caucasian,11/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,New,1,0 +51166,57589,52326,PRETRIAL,Mcdaniel,Christian,L,Male,Caucasian,11/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +51166,57589,52326,PRETRIAL,Mcdaniel,Christian,L,Male,Caucasian,11/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51148,57568,52305,PRETRIAL,Thomas,Henson,NULL,Male,African-American,08/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +51148,57568,52305,PRETRIAL,Thomas,Henson,NULL,Male,African-American,08/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +51148,57568,52305,PRETRIAL,Thomas,Henson,NULL,Male,African-American,08/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51160,57582,52319,PRETRIAL,MATOS,JOSE,MANUEL,Male,Caucasian,05/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +51160,57582,52319,PRETRIAL,MATOS,JOSE,MANUEL,Male,Caucasian,05/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +51160,57582,52319,PRETRIAL,MATOS,JOSE,MANUEL,Male,Caucasian,05/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51158,57580,52317,PRETRIAL,BROWN,MARCU,ALEXANDER,Male,African-American,01/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +51158,57580,52317,PRETRIAL,BROWN,MARCU,ALEXANDER,Male,African-American,01/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +51158,57580,52317,PRETRIAL,BROWN,MARCU,ALEXANDER,Male,African-American,01/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51154,57575,52312,PRETRIAL,Meixner,Walter,NULL,Male,Caucasian,02/18/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +51154,57575,52312,PRETRIAL,Meixner,Walter,NULL,Male,Caucasian,02/18/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,8,Risk of Recidivism,-2.83,1,Low,New,1,0 +51154,57575,52312,PRETRIAL,Meixner,Walter,NULL,Male,Caucasian,02/18/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51161,57584,52321,PRETRIAL,CASIMIR,DELAMA,NULL,Male,African-American,12/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,2,Medium,7,Risk of Violence,-2.63,2,Low,New,1,0 +51161,57584,52321,PRETRIAL,CASIMIR,DELAMA,NULL,Male,African-American,12/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +51161,57584,52321,PRETRIAL,CASIMIR,DELAMA,NULL,Male,African-American,12/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51151,57571,52308,PRETRIAL,Rodriguez,Pedro,NULL,Male,Hispanic,05/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +51151,57571,52308,PRETRIAL,Rodriguez,Pedro,NULL,Male,Hispanic,05/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +51151,57571,52308,PRETRIAL,Rodriguez,Pedro,NULL,Male,Hispanic,05/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51162,57585,52322,PRETRIAL,SATAHOO,DENNIS,OBRIEN,Male,Caucasian,02/23/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +51162,57585,52322,PRETRIAL,SATAHOO,DENNIS,OBRIEN,Male,Caucasian,02/23/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,8,Risk of Recidivism,-2.6,1,Low,New,1,0 +51162,57585,52322,PRETRIAL,SATAHOO,DENNIS,OBRIEN,Male,Caucasian,02/23/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51141,57564,52301,PRETRIAL,Hampel,Michael,NULL,Male,Caucasian,01/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +51141,57564,52301,PRETRIAL,Hampel,Michael,NULL,Male,Caucasian,01/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +51141,57564,52301,PRETRIAL,Hampel,Michael,NULL,Male,Caucasian,01/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51152,57572,52309,PRETRIAL,Peterman,Pete,NULL,Male,African-American,03/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +51152,57572,52309,PRETRIAL,Peterman,Pete,NULL,Male,African-American,03/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +51152,57572,52309,PRETRIAL,Peterman,Pete,NULL,Male,African-American,03/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +51155,57577,52314,PRETRIAL,Lawrence,Odean,NULL,Male,African-American,07/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +51155,57577,52314,PRETRIAL,Lawrence,Odean,NULL,Male,African-American,07/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +51155,57577,52314,PRETRIAL,Lawrence,Odean,NULL,Male,African-American,07/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51149,57569,52306,PRETRIAL,Christopher,Bonilla,NULL,Male,Caucasian,02/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +51149,57569,52306,PRETRIAL,Christopher,Bonilla,NULL,Male,Caucasian,02/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +51149,57569,52306,PRETRIAL,Christopher,Bonilla,NULL,Male,Caucasian,02/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51179,57608,52342,Probation,Palmer,Douglas,NULL,Male,Caucasian,08/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +51179,57608,52342,Probation,Palmer,Douglas,NULL,Male,Caucasian,08/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +51179,57608,52342,Probation,Palmer,Douglas,NULL,Male,Caucasian,08/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51188,57619,52349,Probation,Seese,Matthew,NULL,Male,Caucasian,02/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +51188,57619,52349,Probation,Seese,Matthew,NULL,Male,Caucasian,02/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +51188,57619,52349,Probation,Seese,Matthew,NULL,Male,Caucasian,02/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51205,57637,52365,DRRD,Barnes,Destiny,NULL,Female,Caucasian,05/05/94,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,1/14/13 0:00,4,High,7,Risk of Violence,-0.05,10,High,New,1,0 +51205,57637,52365,DRRD,Barnes,Destiny,NULL,Female,Caucasian,05/05/94,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,1/14/13 0:00,4,High,8,Risk of Recidivism,0.16,8,High,New,1,0 +51205,57637,52365,DRRD,Barnes,Destiny,NULL,Female,Caucasian,05/05/94,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,1/14/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51172,57598,52333,PRETRIAL,VANHUSS,EMILY,NULL,Female,Caucasian,01/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +51172,57598,52333,PRETRIAL,VANHUSS,EMILY,NULL,Female,Caucasian,01/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +51172,57598,52333,PRETRIAL,VANHUSS,EMILY,NULL,Female,Caucasian,01/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +49582,57616,50456,PRETRIAL,slager,leslie,NULL,Female,Caucasian,11/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/14/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,Copy,1,0 +49582,57616,50456,PRETRIAL,slager,leslie,NULL,Female,Caucasian,11/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/14/13 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,Copy,1,0 +49582,57616,50456,PRETRIAL,slager,leslie,NULL,Female,Caucasian,11/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +51197,57629,52358,Probation,Drayton,Elijah,NULL,Male,African-American,06/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +51197,57629,52358,Probation,Drayton,Elijah,NULL,Male,African-American,06/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +51197,57629,52358,Probation,Drayton,Elijah,NULL,Male,African-American,06/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51167,57590,52327,PRETRIAL,CUEVAS,MIREYA,NULL,Female,Caucasian,01/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +51167,57590,52327,PRETRIAL,CUEVAS,MIREYA,NULL,Female,Caucasian,01/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/13 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +51167,57590,52327,PRETRIAL,CUEVAS,MIREYA,NULL,Female,Caucasian,01/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51192,57624,52353,Probation,Ferrera,Michael,NULL,Male,Hispanic,04/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +51192,57624,52353,Probation,Ferrera,Michael,NULL,Male,Hispanic,04/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +51192,57624,52353,Probation,Ferrera,Michael,NULL,Male,Hispanic,04/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +37645,57606,52341,PRETRIAL,Johnson,Randy,NULL,Male,African-American,01/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/14/13 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +37645,57606,52341,PRETRIAL,Johnson,Randy,NULL,Male,African-American,01/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +37645,57606,52341,PRETRIAL,Johnson,Randy,NULL,Male,African-American,01/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51189,57621,52350,PRETRIAL,williams,kevon,NULL,Male,African-American,08/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +51189,57621,52350,PRETRIAL,williams,kevon,NULL,Male,African-American,08/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +51189,57621,52350,PRETRIAL,williams,kevon,NULL,Male,African-American,08/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +22566,57593,49485,PRETRIAL,FORBES,STACEY,RAINER,Male,African-American,06/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.41,3,Low,Copy,1,0 +22566,57593,49485,PRETRIAL,FORBES,STACEY,RAINER,Male,African-American,06/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,Copy,1,0 +22566,57593,49485,PRETRIAL,FORBES,STACEY,RAINER,Male,African-American,06/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +51173,57600,52335,PRETRIAL,Castro,Rene,NULL,Male,Hispanic,06/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +51173,57600,52335,PRETRIAL,Castro,Rene,NULL,Male,Hispanic,06/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +51173,57600,52335,PRETRIAL,Castro,Rene,NULL,Male,Hispanic,06/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51195,57627,52356,PRETRIAL,brown,ssecrette,NULL,Female,African-American,10/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +51195,57627,52356,PRETRIAL,brown,ssecrette,NULL,Female,African-American,10/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,9,High,New,1,0 +51195,57627,52356,PRETRIAL,brown,ssecrette,NULL,Female,African-American,10/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +11885,57613,25119,PRETRIAL,HOSEIN,MUJAHID,NULL,Male,Other,11/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,Copy,1,0 +11885,57613,25119,PRETRIAL,HOSEIN,MUJAHID,NULL,Male,Other,11/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,Copy,1,0 +11885,57613,25119,PRETRIAL,HOSEIN,MUJAHID,NULL,Male,Other,11/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +11885,57614,25119,PRETRIAL,HOSEIN,MUJAHID,NULL,Male,Other,11/22/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,Copy,1,0 +11885,57614,25119,PRETRIAL,HOSEIN,MUJAHID,NULL,Male,Other,11/22/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,Copy,1,0 +11885,57614,25119,PRETRIAL,HOSEIN,MUJAHID,NULL,Male,Other,11/22/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +1186,57592,52329,PRETRIAL,HEIL,ROBERT,ANDERSON,Male,African-American,05/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +1186,57592,52329,PRETRIAL,HEIL,ROBERT,ANDERSON,Male,African-American,05/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +1186,57592,52329,PRETRIAL,HEIL,ROBERT,ANDERSON,Male,African-American,05/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51209,57642,52370,Probation,martin,jaifet,NULL,Female,Hispanic,01/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +51209,57642,52370,Probation,martin,jaifet,NULL,Female,Hispanic,01/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,New,1,0 +51209,57642,52370,Probation,martin,jaifet,NULL,Female,Hispanic,01/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51178,57605,52340,PRETRIAL,Banquero,Luis,Eduardo,Male,Hispanic,05/19/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +51178,57605,52340,PRETRIAL,Banquero,Luis,Eduardo,Male,Hispanic,05/19/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +51178,57605,52340,PRETRIAL,Banquero,Luis,Eduardo,Male,Hispanic,05/19/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51174,57601,52336,PRETRIAL,Oneal,Candace,NULL,Female,African-American,07/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +51174,57601,52336,PRETRIAL,Oneal,Candace,NULL,Female,African-American,07/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +51174,57601,52336,PRETRIAL,Oneal,Candace,NULL,Female,African-American,07/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51194,57626,52355,PRETRIAL,DELGADO,RUSLAN,NULL,Male,Other,12/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +51194,57626,52355,PRETRIAL,DELGADO,RUSLAN,NULL,Male,Other,12/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +51194,57626,52355,PRETRIAL,DELGADO,RUSLAN,NULL,Male,Other,12/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51170,57596,52331,PRETRIAL,Glass,Allyson,NULL,Female,Caucasian,12/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +51170,57596,52331,PRETRIAL,Glass,Allyson,NULL,Female,Caucasian,12/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +51170,57596,52331,PRETRIAL,Glass,Allyson,NULL,Female,Caucasian,12/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51199,57631,52360,Probation,Cunningham,Richard,NULL,Male,African-American,12/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +51199,57631,52360,Probation,Cunningham,Richard,NULL,Male,African-American,12/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +51199,57631,52360,Probation,Cunningham,Richard,NULL,Male,African-American,12/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51176,57603,52338,PRETRIAL,TORRES,ALFONSO,A,Male,Hispanic,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +51176,57603,52338,PRETRIAL,TORRES,ALFONSO,A,Male,Hispanic,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.01,10,High,New,1,0 +51176,57603,52338,PRETRIAL,TORRES,ALFONSO,A,Male,Hispanic,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +51187,57617,52347,Probation,Sam,Sam,NULL,Male,Asian,06/15/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +51187,57617,52347,Probation,Sam,Sam,NULL,Male,Asian,06/15/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +51187,57617,52347,Probation,Sam,Sam,NULL,Male,Asian,06/15/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +19657,57668,52394,PRETRIAL,Rousseau,Thomas,NULL,Male,Caucasian,02/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +19657,57668,52394,PRETRIAL,Rousseau,Thomas,NULL,Male,Caucasian,02/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +19657,57668,52394,PRETRIAL,Rousseau,Thomas,NULL,Male,Caucasian,02/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +40064,57638,52366,PRETRIAL,Kobel,James,NULL,Male,Caucasian,04/11/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +40064,57638,52366,PRETRIAL,Kobel,James,NULL,Male,Caucasian,04/11/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +40064,57638,52366,PRETRIAL,Kobel,James,NULL,Male,Caucasian,04/11/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51207,57640,52368,Probation,DUPLESSIS,MONIQUE,NULL,Female,African-American,10/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +51207,57640,52368,Probation,DUPLESSIS,MONIQUE,NULL,Female,African-American,10/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +51207,57640,52368,Probation,DUPLESSIS,MONIQUE,NULL,Female,African-American,10/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +49677,57620,50574,Probation,STARK,ANDREW,NULL,Male,Caucasian,03/09/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +49677,57620,50574,Probation,STARK,ANDREW,NULL,Male,Caucasian,03/09/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +49677,57620,50574,Probation,STARK,ANDREW,NULL,Male,Caucasian,03/09/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +32237,57607,31263,PRETRIAL,wahlshapiro,jnai,farrah,Female,Caucasian,07/04/76,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,1/14/13 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +32237,57607,31263,PRETRIAL,wahlshapiro,jnai,farrah,Female,Caucasian,07/04/76,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,1/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,6,Medium,New,1,0 +32237,57607,31263,PRETRIAL,wahlshapiro,jnai,farrah,Female,Caucasian,07/04/76,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51208,57641,52369,Probation,Eustache,Rodrigue,NULL,Male,African-American,03/17/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +51208,57641,52369,Probation,Eustache,Rodrigue,NULL,Male,African-American,03/17/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +51208,57641,52369,Probation,Eustache,Rodrigue,NULL,Male,African-American,03/17/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51186,57615,52346,Probation,guerrerocorral,juan,NULL,Male,Hispanic,11/21/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +51186,57615,52346,Probation,guerrerocorral,juan,NULL,Male,Hispanic,11/21/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +51186,57615,52346,Probation,guerrerocorral,juan,NULL,Male,Hispanic,11/21/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51169,57594,52330,PRETRIAL,Brown,Roger,NULL,Male,African-American,09/06/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +51169,57594,52330,PRETRIAL,Brown,Roger,NULL,Male,African-American,09/06/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +51169,57594,52330,PRETRIAL,Brown,Roger,NULL,Male,African-American,09/06/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +11885,57612,25119,PRETRIAL,HOSEIN,MUJAHID,NULL,Male,Other,11/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,Copy,1,0 +11885,57612,25119,PRETRIAL,HOSEIN,MUJAHID,NULL,Male,Other,11/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,Copy,1,0 +11885,57612,25119,PRETRIAL,HOSEIN,MUJAHID,NULL,Male,Other,11/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +51202,57633,52362,Probation,Ammirata,Salvatore,NULL,Male,Hispanic,03/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +51202,57633,52362,Probation,Ammirata,Salvatore,NULL,Male,Hispanic,03/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +51202,57633,52362,Probation,Ammirata,Salvatore,NULL,Male,Hispanic,03/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51196,57628,52357,PRETRIAL,MEDDERS,MARQUES,NULL,Male,African-American,11/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +51196,57628,52357,PRETRIAL,MEDDERS,MARQUES,NULL,Male,African-American,11/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +51196,57628,52357,PRETRIAL,MEDDERS,MARQUES,NULL,Male,African-American,11/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +12229,57599,52334,PRETRIAL,SEMIL,BRAIN,ALLEN,Male,African-American,10/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,4,High,7,Risk of Violence,-0.35,10,High,New,1,0 +12229,57599,52334,PRETRIAL,SEMIL,BRAIN,ALLEN,Male,African-American,10/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,4,High,8,Risk of Recidivism,0.71,10,High,New,1,0 +12229,57599,52334,PRETRIAL,SEMIL,BRAIN,ALLEN,Male,African-American,10/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +42460,57636,42283,Probation,ROLLE,TERRELL,NULL,Male,African-American,07/28/75,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/14/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +42460,57636,42283,Probation,ROLLE,TERRELL,NULL,Male,African-American,07/28/75,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/14/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +42460,57636,42283,Probation,ROLLE,TERRELL,NULL,Male,African-American,07/28/75,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +51168,57591,52328,PRETRIAL,GOMEZ,JOSE,NULL,Male,Hispanic,02/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +51168,57591,52328,PRETRIAL,GOMEZ,JOSE,NULL,Male,Hispanic,02/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +51168,57591,52328,PRETRIAL,GOMEZ,JOSE,NULL,Male,Hispanic,02/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51206,57639,52367,PRETRIAL,Williams,Jennifer,NULL,Female,African-American,09/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,New,1,0 +51206,57639,52367,PRETRIAL,Williams,Jennifer,NULL,Female,African-American,09/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,8,High,New,1,0 +51206,57639,52367,PRETRIAL,Williams,Jennifer,NULL,Female,African-American,09/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +51180,57609,52343,PRETRIAL,Thurman,Markita,NULL,Female,African-American,09/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +51180,57609,52343,PRETRIAL,Thurman,Markita,NULL,Female,African-American,09/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,New,1,0 +51180,57609,52343,PRETRIAL,Thurman,Markita,NULL,Female,African-American,09/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +39956,57618,52348,PRETRIAL,Galindo,Denys,NULL,Male,Hispanic,09/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +39956,57618,52348,PRETRIAL,Galindo,Denys,NULL,Male,Hispanic,09/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +39956,57618,52348,PRETRIAL,Galindo,Denys,NULL,Male,Hispanic,09/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51171,57597,52332,PRETRIAL,Jones,Lisa,Ann,Female,Caucasian,03/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +51171,57597,52332,PRETRIAL,Jones,Lisa,Ann,Female,Caucasian,03/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +51171,57597,52332,PRETRIAL,Jones,Lisa,Ann,Female,Caucasian,03/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +51198,57630,52359,Probation,white,kristy,NULL,Female,African-American,11/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +51198,57630,52359,Probation,white,kristy,NULL,Female,African-American,11/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +51198,57630,52359,Probation,white,kristy,NULL,Female,African-American,11/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51177,57604,52339,PRETRIAL,Garland,Gwendolyn,NULL,Female,African-American,10/27/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +51177,57604,52339,PRETRIAL,Garland,Gwendolyn,NULL,Female,African-American,10/27/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +51177,57604,52339,PRETRIAL,Garland,Gwendolyn,NULL,Female,African-American,10/27/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51191,57623,52352,PRETRIAL,Brinson,Jameel,NULL,Male,African-American,02/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +51191,57623,52352,PRETRIAL,Brinson,Jameel,NULL,Male,African-American,02/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,4,High,8,Risk of Recidivism,0.66,10,High,New,1,0 +51191,57623,52352,PRETRIAL,Brinson,Jameel,NULL,Male,African-American,02/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +30243,57595,29207,Probation,mitchell,aquaria,NULL,Female,African-American,01/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,Copy,1,0 +30243,57595,29207,Probation,mitchell,aquaria,NULL,Female,African-American,01/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,10,High,Copy,1,0 +30243,57595,29207,Probation,mitchell,aquaria,NULL,Female,African-American,01/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +51175,57602,52337,PRETRIAL,Baumann,William,NULL,Male,Caucasian,09/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-1.77,5,Medium,New,1,0 +51175,57602,52337,PRETRIAL,Baumann,William,NULL,Male,Caucasian,09/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +51175,57602,52337,PRETRIAL,Baumann,William,NULL,Male,Caucasian,09/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51193,57625,52354,Probation,MORAN,STEPHANIE,DELCARMEN,Female,Hispanic,01/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +51193,57625,52354,Probation,MORAN,STEPHANIE,DELCARMEN,Female,Hispanic,01/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +51193,57625,52354,Probation,MORAN,STEPHANIE,DELCARMEN,Female,Hispanic,01/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51200,57632,52361,Probation,vasquez,stephen,NULL,Male,African-American,10/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.33,3,Low,New,1,0 +51200,57632,52361,Probation,vasquez,stephen,NULL,Male,African-American,10/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +51200,57632,52361,Probation,vasquez,stephen,NULL,Male,African-American,10/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +51212,57646,52374,PRETRIAL,Smith,Ronald,NULL,Male,African-American,11/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +51212,57646,52374,PRETRIAL,Smith,Ronald,NULL,Male,African-American,11/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +51212,57646,52374,PRETRIAL,Smith,Ronald,NULL,Male,African-American,11/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51238,57681,52407,Probation,Allen,Daniel,NULL,Male,Caucasian,12/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/15/13 0:00,2,Medium,7,Risk of Violence,-2.76,2,Low,New,1,0 +51238,57681,52407,Probation,Allen,Daniel,NULL,Male,Caucasian,12/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +51238,57681,52407,Probation,Allen,Daniel,NULL,Male,Caucasian,12/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +18577,57653,52381,PRETRIAL,WATKINS,MATTHEW,NULL,Male,Caucasian,12/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +18577,57653,52381,PRETRIAL,WATKINS,MATTHEW,NULL,Male,Caucasian,12/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +18577,57653,52381,PRETRIAL,WATKINS,MATTHEW,NULL,Male,Caucasian,12/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51221,57660,52386,PRETRIAL,Charles,Stevenson,NULL,Male,Other,03/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +51221,57660,52386,PRETRIAL,Charles,Stevenson,NULL,Male,Other,03/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +51221,57660,52386,PRETRIAL,Charles,Stevenson,NULL,Male,Other,03/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51227,57667,52393,PRETRIAL,Norris,Andrea,NULL,Female,Caucasian,03/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +51227,57667,52393,PRETRIAL,Norris,Andrea,NULL,Female,Caucasian,03/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +51227,57667,52393,PRETRIAL,Norris,Andrea,NULL,Female,Caucasian,03/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51231,57674,52400,PRETRIAL,lopezmunoz,alexis,NULL,Male,Caucasian,07/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/15/13 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +51231,57674,52400,PRETRIAL,lopezmunoz,alexis,NULL,Male,Caucasian,07/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +51231,57674,52400,PRETRIAL,lopezmunoz,alexis,NULL,Male,Caucasian,07/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51213,57648,52376,PRETRIAL,Haye,Christopher,NULL,Male,African-American,02/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +51213,57648,52376,PRETRIAL,Haye,Christopher,NULL,Male,African-American,02/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +51213,57648,52376,PRETRIAL,Haye,Christopher,NULL,Male,African-American,02/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51225,57665,52391,PRETRIAL,Lewis,Shavoria,NULL,Female,African-American,07/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +51225,57665,52391,PRETRIAL,Lewis,Shavoria,NULL,Female,African-American,07/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +51225,57665,52391,PRETRIAL,Lewis,Shavoria,NULL,Female,African-American,07/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +44720,57644,52372,PRETRIAL,Thomas,Darrell,NULL,Male,African-American,02/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +44720,57644,52372,PRETRIAL,Thomas,Darrell,NULL,Male,African-American,02/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +44720,57644,52372,PRETRIAL,Thomas,Darrell,NULL,Male,African-American,02/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51215,57651,52379,PRETRIAL,McDowell,James,NULL,Male,Caucasian,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +51215,57651,52379,PRETRIAL,McDowell,James,NULL,Male,Caucasian,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +51215,57651,52379,PRETRIAL,McDowell,James,NULL,Male,Caucasian,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51228,57669,52395,Probation,Grant,Matthew,NULL,Male,Caucasian,07/29/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/15/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +51228,57669,52395,Probation,Grant,Matthew,NULL,Male,Caucasian,07/29/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/15/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +51228,57669,52395,Probation,Grant,Matthew,NULL,Male,Caucasian,07/29/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +38827,57686,38288,Probation,Lorenzo,Jones,NULL,Male,African-American,09/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,Copy,1,0 +38827,57686,38288,Probation,Lorenzo,Jones,NULL,Male,African-American,09/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,Copy,1,0 +38827,57686,38288,Probation,Lorenzo,Jones,NULL,Male,African-American,09/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +37453,57657,36819,PRETRIAL,STEVENS,MAKEEL,NULL,Male,African-American,12/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,Copy,1,0 +37453,57657,36819,PRETRIAL,STEVENS,MAKEEL,NULL,Male,African-American,12/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,Copy,1,0 +37453,57657,36819,PRETRIAL,STEVENS,MAKEEL,NULL,Male,African-American,12/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +51229,57672,52398,Probation,WEBSTER,JAMIE,L,Female,Caucasian,04/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +51229,57672,52398,Probation,WEBSTER,JAMIE,L,Female,Caucasian,04/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +51229,57672,52398,Probation,WEBSTER,JAMIE,L,Female,Caucasian,04/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51214,57649,52377,PRETRIAL,LERNER,MAX,BENJAMIN,Male,Caucasian,04/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +51214,57649,52377,PRETRIAL,LERNER,MAX,BENJAMIN,Male,Caucasian,04/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +51214,57649,52377,PRETRIAL,LERNER,MAX,BENJAMIN,Male,Caucasian,04/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51224,57664,52390,PRETRIAL,Garrison,David,NULL,Male,Caucasian,01/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +51224,57664,52390,PRETRIAL,Garrison,David,NULL,Male,Caucasian,01/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +51224,57664,52390,PRETRIAL,Garrison,David,NULL,Male,Caucasian,01/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51235,57678,52404,PRETRIAL,Key,Derrick,Allen,Male,Caucasian,08/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +51235,57678,52404,PRETRIAL,Key,Derrick,Allen,Male,Caucasian,08/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +51235,57678,52404,PRETRIAL,Key,Derrick,Allen,Male,Caucasian,08/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +13863,57685,52411,Probation,Austin,John,Anthony,Male,Caucasian,10/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/15/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +13863,57685,52411,Probation,Austin,John,Anthony,Male,Caucasian,10/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/15/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +13863,57685,52411,Probation,Austin,John,Anthony,Male,Caucasian,10/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51222,57662,52388,PRETRIAL,CADET,LINCOLN,NULL,Male,African-American,01/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/15/13 0:00,2,Medium,7,Risk of Violence,-2.63,2,Low,New,1,0 +51222,57662,52388,PRETRIAL,CADET,LINCOLN,NULL,Male,African-American,01/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +51222,57662,52388,PRETRIAL,CADET,LINCOLN,NULL,Male,African-American,01/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51237,57680,52406,Probation,lee,lomar,NULL,Male,African-American,03/05/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +51237,57680,52406,Probation,lee,lomar,NULL,Male,African-American,03/05/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +51237,57680,52406,Probation,lee,lomar,NULL,Male,African-American,03/05/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51240,57683,52409,Probation,lipschutz,blake,NULL,Male,Caucasian,10/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +51240,57683,52409,Probation,lipschutz,blake,NULL,Male,Caucasian,10/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +51240,57683,52409,Probation,lipschutz,blake,NULL,Male,Caucasian,10/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +31994,57654,30990,PRETRIAL,Myrie,Kirk,Anthony,Male,Other,06/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.81,9,High,Copy,1,0 +31994,57654,30990,PRETRIAL,Myrie,Kirk,Anthony,Male,Other,06/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,7,Medium,Copy,1,0 +31994,57654,30990,PRETRIAL,Myrie,Kirk,Anthony,Male,Other,06/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +51232,57675,52401,PRETRIAL,BETHEA,DYWAHN,NULL,Male,African-American,10/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +51232,57675,52401,PRETRIAL,BETHEA,DYWAHN,NULL,Male,African-American,10/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +51232,57675,52401,PRETRIAL,BETHEA,DYWAHN,NULL,Male,African-American,10/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51220,57659,52385,PRETRIAL,Hernandez,Walter,NULL,Male,Caucasian,04/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +51220,57659,52385,PRETRIAL,Hernandez,Walter,NULL,Male,Caucasian,04/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +51220,57659,52385,PRETRIAL,Hernandez,Walter,NULL,Male,Caucasian,04/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +17692,57661,52387,PRETRIAL,SERGIO,SERGIO,NULL,Male,Hispanic,09/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +17692,57661,52387,PRETRIAL,SERGIO,SERGIO,NULL,Male,Hispanic,09/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +17692,57661,52387,PRETRIAL,SERGIO,SERGIO,NULL,Male,Hispanic,09/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +51239,57682,52408,Probation,Madison,Jamar,NULL,Male,African-American,02/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +51239,57682,52408,Probation,Madison,Jamar,NULL,Male,African-American,02/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +51239,57682,52408,Probation,Madison,Jamar,NULL,Male,African-American,02/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +34102,57647,52375,PRETRIAL,smith,william,NULL,Male,African-American,06/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +34102,57647,52375,PRETRIAL,smith,william,NULL,Male,African-American,06/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +34102,57647,52375,PRETRIAL,smith,william,NULL,Male,African-American,06/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +51218,57656,52383,PRETRIAL,MYRICK,WYLE,NULL,Male,African-American,12/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.33,3,Low,New,1,0 +51218,57656,52383,PRETRIAL,MYRICK,WYLE,NULL,Male,African-American,12/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +51218,57656,52383,PRETRIAL,MYRICK,WYLE,NULL,Male,African-American,12/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51230,57673,52399,DRRD,Boyd,Antwon,NULL,Male,African-American,09/02/92,17,All Scales,Intake,English,Pretrial,Probation,Single,1/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.95,9,High,New,1,0 +51230,57673,52399,DRRD,Boyd,Antwon,NULL,Male,African-American,09/02/92,17,All Scales,Intake,English,Pretrial,Probation,Single,1/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,7,Medium,New,1,0 +51230,57673,52399,DRRD,Boyd,Antwon,NULL,Male,African-American,09/02/92,17,All Scales,Intake,English,Pretrial,Probation,Single,1/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,3,Low,New,1,0 +51210,57643,52371,PRETRIAL,Fischer,Travis,Lee,Male,Caucasian,10/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +51210,57643,52371,PRETRIAL,Fischer,Travis,Lee,Male,Caucasian,10/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,9,High,New,1,0 +51210,57643,52371,PRETRIAL,Fischer,Travis,Lee,Male,Caucasian,10/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51216,57652,52380,PRETRIAL,Moore,Jerrod,D,Male,African-American,11/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +51216,57652,52380,PRETRIAL,Moore,Jerrod,D,Male,African-American,11/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +51216,57652,52380,PRETRIAL,Moore,Jerrod,D,Male,African-American,11/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51223,57663,52389,PRETRIAL,Elliott,Desmond,Jarrod,Male,African-American,08/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +51223,57663,52389,PRETRIAL,Elliott,Desmond,Jarrod,Male,African-American,08/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +51223,57663,52389,PRETRIAL,Elliott,Desmond,Jarrod,Male,African-American,08/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51217,57655,52382,PRETRIAL,ROBERTS,ROOSEVELT,A,Male,African-American,02/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +51217,57655,52382,PRETRIAL,ROBERTS,ROOSEVELT,A,Male,African-American,02/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,4,High,8,Risk of Recidivism,0.45,9,High,New,1,0 +51217,57655,52382,PRETRIAL,ROBERTS,ROOSEVELT,A,Male,African-American,02/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51219,57658,52384,PRETRIAL,Davis,Alphonso,NULL,Male,African-American,06/29/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +51219,57658,52384,PRETRIAL,Davis,Alphonso,NULL,Male,African-American,06/29/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +51219,57658,52384,PRETRIAL,Davis,Alphonso,NULL,Male,African-American,06/29/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +21137,57671,52397,PRETRIAL,LOCKHART,CLIFTON,NULL,Male,African-American,09/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +21137,57671,52397,PRETRIAL,LOCKHART,CLIFTON,NULL,Male,African-American,09/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +21137,57671,52397,PRETRIAL,LOCKHART,CLIFTON,NULL,Male,African-American,09/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51211,57645,52373,PRETRIAL,Williams,James,NULL,Male,African-American,07/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +51211,57645,52373,PRETRIAL,Williams,James,NULL,Male,African-American,07/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +51211,57645,52373,PRETRIAL,Williams,James,NULL,Male,African-American,07/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +48235,57650,52378,PRETRIAL,Harris,Daniel,NULL,Male,Caucasian,04/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,New,1,0 +48235,57650,52378,PRETRIAL,Harris,Daniel,NULL,Male,Caucasian,04/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +48235,57650,52378,PRETRIAL,Harris,Daniel,NULL,Male,Caucasian,04/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51226,57666,52392,PRETRIAL,STSURIA,SAMANTHA,NULL,Female,African-American,01/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +51226,57666,52392,PRETRIAL,STSURIA,SAMANTHA,NULL,Female,African-American,01/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +51226,57666,52392,PRETRIAL,STSURIA,SAMANTHA,NULL,Female,African-American,01/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51236,57679,52405,Probation,JEANBAPTISTE,RUDOLPH,NULL,Male,African-American,03/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +51236,57679,52405,Probation,JEANBAPTISTE,RUDOLPH,NULL,Male,African-American,03/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +51236,57679,52405,Probation,JEANBAPTISTE,RUDOLPH,NULL,Male,African-American,03/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51233,57676,52402,Probation,CRUPI,JANENE,NULL,Female,Caucasian,07/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +51233,57676,52402,Probation,CRUPI,JANENE,NULL,Female,Caucasian,07/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +51233,57676,52402,Probation,CRUPI,JANENE,NULL,Female,Caucasian,07/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50828,57687,51931,PRETRIAL,Lockhart,Feddie,Ladaris,Male,African-American,06/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,Copy,1,0 +50828,57687,51931,PRETRIAL,Lockhart,Feddie,Ladaris,Male,African-American,06/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,Copy,1,0 +50828,57687,51931,PRETRIAL,Lockhart,Feddie,Ladaris,Male,African-American,06/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +51271,57726,52447,Probation,SABRA,LORI,J,Female,Caucasian,04/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +51271,57726,52447,Probation,SABRA,LORI,J,Female,Caucasian,04/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +51271,57726,52447,Probation,SABRA,LORI,J,Female,Caucasian,04/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51248,57697,52420,PRETRIAL,Joseph,Claudy,NULL,Male,African-American,01/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +51248,57697,52420,PRETRIAL,Joseph,Claudy,NULL,Male,African-American,01/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +51248,57697,52420,PRETRIAL,Joseph,Claudy,NULL,Male,African-American,01/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51255,57705,52428,Probation,Dbaron,Abraham,NULL,Male,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +51255,57705,52428,Probation,Dbaron,Abraham,NULL,Male,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,New,1,0 +51255,57705,52428,Probation,Dbaron,Abraham,NULL,Male,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +51258,57708,52431,Probation,AMORUSO,STEVEN,A,Male,Caucasian,03/20/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/16/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +51258,57708,52431,Probation,AMORUSO,STEVEN,A,Male,Caucasian,03/20/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +51258,57708,52431,Probation,AMORUSO,STEVEN,A,Male,Caucasian,03/20/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51267,57721,52442,Probation,Page,Robert,NULL,Male,African-American,03/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +51267,57721,52442,Probation,Page,Robert,NULL,Male,African-American,03/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +51267,57721,52442,Probation,Page,Robert,NULL,Male,African-American,03/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51249,57700,52423,PRETRIAL,ALVARENGA,LEONARDO,NULL,Male,Caucasian,03/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +51249,57700,52423,PRETRIAL,ALVARENGA,LEONARDO,NULL,Male,Caucasian,03/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +51249,57700,52423,PRETRIAL,ALVARENGA,LEONARDO,NULL,Male,Caucasian,03/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51272,57729,52450,PRETRIAL,Madia,Michael,NULL,Male,Caucasian,03/10/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/16/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +51272,57729,52450,PRETRIAL,Madia,Michael,NULL,Male,Caucasian,03/10/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +51272,57729,52450,PRETRIAL,Madia,Michael,NULL,Male,Caucasian,03/10/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +51244,57692,52416,PRETRIAL,Gellert,Michael,NULL,Male,Caucasian,11/03/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +51244,57692,52416,PRETRIAL,Gellert,Michael,NULL,Male,Caucasian,11/03/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +51244,57692,52416,PRETRIAL,Gellert,Michael,NULL,Male,Caucasian,11/03/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +41997,57728,52449,Probation,Pandol,Wikenson,NULL,Male,African-American,10/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +41997,57728,52449,Probation,Pandol,Wikenson,NULL,Male,African-American,10/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +41997,57728,52449,Probation,Pandol,Wikenson,NULL,Male,African-American,10/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +4074,57724,52445,PRETRIAL,pratt,michael,NULL,Male,African-Am,03/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,4,High,7,Risk of Violence,-0.67,9,High,New,1,0 +4074,57724,52445,PRETRIAL,pratt,michael,NULL,Male,African-Am,03/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,4,High,8,Risk of Recidivism,0.83,10,High,New,1,0 +4074,57724,52445,PRETRIAL,pratt,michael,NULL,Male,African-Am,03/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +23473,57698,52421,Probation,howlett,edson,NULL,Male,Caucasian,11/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +23473,57698,52421,Probation,howlett,edson,NULL,Male,Caucasian,11/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +23473,57698,52421,Probation,howlett,edson,NULL,Male,Caucasian,11/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +14080,57715,13477,PRETRIAL,Aguilera,Richard,NULL,Male,Caucasian,10/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/16/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +14080,57715,13477,PRETRIAL,Aguilera,Richard,NULL,Male,Caucasian,10/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,Copy,1,0 +14080,57715,13477,PRETRIAL,Aguilera,Richard,NULL,Male,Caucasian,10/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/16/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +51245,57694,52418,PRETRIAL,BOUCHER,JASON,NULL,Male,Caucasian,05/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +51245,57694,52418,PRETRIAL,BOUCHER,JASON,NULL,Male,Caucasian,05/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +51245,57694,52418,PRETRIAL,BOUCHER,JASON,NULL,Male,Caucasian,05/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51261,57712,52435,Probation,Gonzalez,Anthony,NULL,Male,Hispanic,07/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +51261,57712,52435,Probation,Gonzalez,Anthony,NULL,Male,Hispanic,07/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +51261,57712,52435,Probation,Gonzalez,Anthony,NULL,Male,Hispanic,07/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51265,57719,52440,PRETRIAL,Ayers,Christian,NULL,Male,Caucasian,09/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,Copy,1,0 +51265,57719,52440,PRETRIAL,Ayers,Christian,NULL,Male,Caucasian,09/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,Copy,1,0 +51265,57719,52440,PRETRIAL,Ayers,Christian,NULL,Male,Caucasian,09/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +9364,57696,37806,PRETRIAL,TURNQUEST,KEVIN,M,Male,African-American,06/29/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,Copy,1,0 +9364,57696,37806,PRETRIAL,TURNQUEST,KEVIN,M,Male,African-American,06/29/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,Copy,1,0 +9364,57696,37806,PRETRIAL,TURNQUEST,KEVIN,M,Male,African-American,06/29/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,42,10,High,Copy,1,0 +51253,57703,52426,PRETRIAL,Madrano,Darling,Jose,Male,Caucasian,04/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +51253,57703,52426,PRETRIAL,Madrano,Darling,Jose,Male,Caucasian,04/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +51253,57703,52426,PRETRIAL,Madrano,Darling,Jose,Male,Caucasian,04/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51259,57710,52433,Probation,mondesir,wilson,NULL,Male,African-American,06/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +51259,57710,52433,Probation,mondesir,wilson,NULL,Male,African-American,06/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +51259,57710,52433,Probation,mondesir,wilson,NULL,Male,African-American,06/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51264,57717,52439,PRETRIAL,WARREN,BRIK,ANTHONY,Male,African-American,09/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +51264,57717,52439,PRETRIAL,WARREN,BRIK,ANTHONY,Male,African-American,09/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +51264,57717,52439,PRETRIAL,WARREN,BRIK,ANTHONY,Male,African-American,09/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +20833,57689,52413,PRETRIAL,Bradwell,Maurice,D,Male,African-American,07/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +20833,57689,52413,PRETRIAL,Bradwell,Maurice,D,Male,African-American,07/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +20833,57689,52413,PRETRIAL,Bradwell,Maurice,D,Male,African-American,07/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +37864,57709,52432,PRETRIAL,WEST,JOEL,NULL,Male,African-American,08/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,4,High,7,Risk of Violence,-0.43,10,High,New,1,0 +37864,57709,52432,PRETRIAL,WEST,JOEL,NULL,Male,African-American,08/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +37864,57709,52432,PRETRIAL,WEST,JOEL,NULL,Male,African-American,08/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51242,57688,52412,PRETRIAL,Shaw,Eric,James,Male,African-American,12/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +51242,57688,52412,PRETRIAL,Shaw,Eric,James,Male,African-American,12/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +51242,57688,52412,PRETRIAL,Shaw,Eric,James,Male,African-American,12/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51268,57722,52443,Probation,RODRIGUEZ,ROBERTO,NULL,Male,Hispanic,07/17/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +51268,57722,52443,Probation,RODRIGUEZ,ROBERTO,NULL,Male,Hispanic,07/17/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +51268,57722,52443,Probation,RODRIGUEZ,ROBERTO,NULL,Male,Hispanic,07/17/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51251,57701,52424,PRETRIAL,Ramsay,Kishu,NULL,Male,African-American,01/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +51251,57701,52424,PRETRIAL,Ramsay,Kishu,NULL,Male,African-American,01/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +51251,57701,52424,PRETRIAL,Ramsay,Kishu,NULL,Male,African-American,01/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +45346,57699,52422,PRETRIAL,Watson,Kennan,NULL,Male,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +45346,57699,52422,PRETRIAL,Watson,Kennan,NULL,Male,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +45346,57699,52422,PRETRIAL,Watson,Kennan,NULL,Male,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +19617,57714,52437,PRETRIAL,DELVA,TRACY,NULL,Female,African-American,07/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,1/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +19617,57714,52437,PRETRIAL,DELVA,TRACY,NULL,Female,African-American,07/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,1/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +19617,57714,52437,PRETRIAL,DELVA,TRACY,NULL,Female,African-American,07/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,1/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51243,57691,52415,PRETRIAL,Teplicki,Jesse,A,Male,Caucasian,04/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +51243,57691,52415,PRETRIAL,Teplicki,Jesse,A,Male,Caucasian,04/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +51243,57691,52415,PRETRIAL,Teplicki,Jesse,A,Male,Caucasian,04/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51256,57706,52429,Probation,DOUGLAS,FITZROY,NULL,Male,African-American,12/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +51256,57706,52429,Probation,DOUGLAS,FITZROY,NULL,Male,African-American,12/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +51256,57706,52429,Probation,DOUGLAS,FITZROY,NULL,Male,African-American,12/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51246,57693,52417,PRETRIAL,Williams,Sha-de,NULL,Male,African-American,02/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +51246,57693,52417,PRETRIAL,Williams,Sha-de,NULL,Male,African-American,02/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +51246,57693,52417,PRETRIAL,Williams,Sha-de,NULL,Male,African-American,02/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +13840,57727,52448,DRRD,Albury,Scott,NULL,Male,Caucasian,12/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +13840,57727,52448,DRRD,Albury,Scott,NULL,Male,Caucasian,12/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +13840,57727,52448,DRRD,Albury,Scott,NULL,Male,Caucasian,12/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51260,57711,52434,Probation,ROURKE,TERESA,M,Female,Hispanic,10/16/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/16/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +51260,57711,52434,Probation,ROURKE,TERESA,M,Female,Hispanic,10/16/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/16/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +51260,57711,52434,Probation,ROURKE,TERESA,M,Female,Hispanic,10/16/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51266,57720,52441,Probation,KRUEGER,KIMBERLEE,ANN,Female,Caucasian,01/17/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +51266,57720,52441,Probation,KRUEGER,KIMBERLEE,ANN,Female,Caucasian,01/17/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +51266,57720,52441,Probation,KRUEGER,KIMBERLEE,ANN,Female,Caucasian,01/17/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +35353,57690,52414,PRETRIAL,Stuart,Joshua,NULL,Male,African-American,08/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +35353,57690,52414,PRETRIAL,Stuart,Joshua,NULL,Male,African-American,08/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +35353,57690,52414,PRETRIAL,Stuart,Joshua,NULL,Male,African-American,08/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51257,57707,52430,PRETRIAL,Kepke,Elaine,NULL,Female,Caucasian,12/06/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/16/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +51257,57707,52430,PRETRIAL,Kepke,Elaine,NULL,Female,Caucasian,12/06/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/16/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +51257,57707,52430,PRETRIAL,Kepke,Elaine,NULL,Female,Caucasian,12/06/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51263,57716,52438,Probation,Gebru,Araya,NULL,Male,African-American,06/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +51263,57716,52438,Probation,Gebru,Araya,NULL,Male,African-American,06/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +51263,57716,52438,Probation,Gebru,Araya,NULL,Male,African-American,06/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51254,57704,52427,PRETRIAL,BRAZEAL,RICKY,LEROY,Male,Caucasian,06/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +51254,57704,52427,PRETRIAL,BRAZEAL,RICKY,LEROY,Male,Caucasian,06/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +51254,57704,52427,PRETRIAL,BRAZEAL,RICKY,LEROY,Male,Caucasian,06/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51269,57723,52444,PRETRIAL,clingan,christopher,NULL,Male,Caucasian,02/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +51269,57723,52444,PRETRIAL,clingan,christopher,NULL,Male,Caucasian,02/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +51269,57723,52444,PRETRIAL,clingan,christopher,NULL,Male,Caucasian,02/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51247,57695,52419,PRETRIAL,Snipes,Johnnie,NULL,Male,African-American,09/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +51247,57695,52419,PRETRIAL,Snipes,Johnnie,NULL,Male,African-American,09/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +51247,57695,52419,PRETRIAL,Snipes,Johnnie,NULL,Male,African-American,09/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51252,57702,52425,PRETRIAL,Chambers,Deandre,NULL,Male,African-American,11/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.82,9,High,New,1,0 +51252,57702,52425,PRETRIAL,Chambers,Deandre,NULL,Male,African-American,11/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +51252,57702,52425,PRETRIAL,Chambers,Deandre,NULL,Male,African-American,11/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51270,57725,52446,Probation,WHEELER,KENDALL,W,Male,African-American,06/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +51270,57725,52446,Probation,WHEELER,KENDALL,W,Male,African-American,06/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +51270,57725,52446,Probation,WHEELER,KENDALL,W,Male,African-American,06/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52322,58997,53605,Probation,Torres,Juilan,NULL,Male,Hispanic,01/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +52322,58997,53605,Probation,Torres,Juilan,NULL,Male,Hispanic,01/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +52322,58997,53605,Probation,Torres,Juilan,NULL,Male,Hispanic,01/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51304,57774,52489,Probation,MICCO,SHERRI,MARIE,Female,Native American,03/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +51304,57774,52489,Probation,MICCO,SHERRI,MARIE,Female,Native American,03/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +51304,57774,52489,Probation,MICCO,SHERRI,MARIE,Female,Native American,03/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +43553,57753,43522,PRETRIAL,Edmond,Jean,Junior,Male,African-American,02/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/17/13 0:00,4,High,7,Risk of Violence,-0.9,9,High,Copy,1,0 +43553,57753,43522,PRETRIAL,Edmond,Jean,Junior,Male,African-American,02/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/17/13 0:00,4,High,8,Risk of Recidivism,1.17,10,High,Copy,1,0 +43553,57753,43522,PRETRIAL,Edmond,Jean,Junior,Male,African-American,02/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/17/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +51293,57760,52477,PRETRIAL,Churchill,Joseph,Edward,Male,Caucasian,11/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-1.28,7,Medium,New,1,0 +51293,57760,52477,PRETRIAL,Churchill,Joseph,Edward,Male,Caucasian,11/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +51293,57760,52477,PRETRIAL,Churchill,Joseph,Edward,Male,Caucasian,11/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +28758,57767,52482,PRETRIAL,Murphy,Terrance,NULL,Male,African-American,09/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +28758,57767,52482,PRETRIAL,Murphy,Terrance,NULL,Male,African-American,09/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +28758,57767,52482,PRETRIAL,Murphy,Terrance,NULL,Male,African-American,09/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51274,57732,52452,PRETRIAL,Flanders,Brandon,NULL,Male,African-American,04/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +51274,57732,52452,PRETRIAL,Flanders,Brandon,NULL,Male,African-American,04/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +51274,57732,52452,PRETRIAL,Flanders,Brandon,NULL,Male,African-American,04/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51282,57746,52466,Probation,Papale,Joseph,NULL,Male,Caucasian,08/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +51282,57746,52466,Probation,Papale,Joseph,NULL,Male,Caucasian,08/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +51282,57746,52466,Probation,Papale,Joseph,NULL,Male,Caucasian,08/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51313,57781,52496,DRRD,Sanabria,Joshua,Jesus,Male,Hispanic,01/13/93,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +51313,57781,52496,DRRD,Sanabria,Joshua,Jesus,Male,Hispanic,01/13/93,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +51313,57781,52496,DRRD,Sanabria,Joshua,Jesus,Male,Hispanic,01/13/93,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +51278,57737,52457,PRETRIAL,Garcia,Eduardo,NULL,Male,Caucasian,02/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +51278,57737,52457,PRETRIAL,Garcia,Eduardo,NULL,Male,Caucasian,02/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +51278,57737,52457,PRETRIAL,Garcia,Eduardo,NULL,Male,Caucasian,02/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +11111,57762,52479,Probation,schuertzmann,robin,NULL,Female,Caucasian,09/01/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +11111,57762,52479,Probation,schuertzmann,robin,NULL,Female,Caucasian,09/01/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +11111,57762,52479,Probation,schuertzmann,robin,NULL,Female,Caucasian,09/01/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51305,57776,52491,Probation,ELLIS,MITCHELL,NULL,Male,Caucasian,09/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,1/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +51305,57776,52491,Probation,ELLIS,MITCHELL,NULL,Male,Caucasian,09/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,1/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +51305,57776,52491,Probation,ELLIS,MITCHELL,NULL,Male,Caucasian,09/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,1/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +33606,57741,52461,PRETRIAL,boone,kena,NULL,Male,African-American,07/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +33606,57741,52461,PRETRIAL,boone,kena,NULL,Male,African-American,07/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +33606,57741,52461,PRETRIAL,boone,kena,NULL,Male,African-American,07/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +48428,57758,49119,Probation,GABLE,THOMAS,JOSEPH,Male,Caucasian,12/25/61,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +48428,57758,49119,Probation,GABLE,THOMAS,JOSEPH,Male,Caucasian,12/25/61,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-0.51,4,Low,New,1,0 +48428,57758,49119,Probation,GABLE,THOMAS,JOSEPH,Male,Caucasian,12/25/61,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51308,57779,52494,Probation,Watson,Michael,James,Male,Caucasian,06/04/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +51308,57779,52494,Probation,Watson,Michael,James,Male,Caucasian,06/04/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +51308,57779,52494,Probation,Watson,Michael,James,Male,Caucasian,06/04/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51301,57772,52487,Probation,farias,roberto,NULL,Male,Caucasian,01/26/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/17/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +51301,57772,52487,Probation,farias,roberto,NULL,Male,Caucasian,01/26/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/17/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +51301,57772,52487,Probation,farias,roberto,NULL,Male,Caucasian,01/26/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51277,57735,52455,PRETRIAL,Giuison,Steven,NULL,Male,African-American,01/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +51277,57735,52455,PRETRIAL,Giuison,Steven,NULL,Male,African-American,01/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +51277,57735,52455,PRETRIAL,Giuison,Steven,NULL,Male,African-American,01/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +50997,57751,52139,PRETRIAL,Demeritte,Raphale,NULL,Male,African-American,10/16/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/13 0:00,4,High,7,Risk of Violence,-1.18,8,High,Copy,1,0 +50997,57751,52139,PRETRIAL,Demeritte,Raphale,NULL,Male,African-American,10/16/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/13 0:00,4,High,8,Risk of Recidivism,0.19,8,High,Copy,1,0 +50997,57751,52139,PRETRIAL,Demeritte,Raphale,NULL,Male,African-American,10/16/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +51298,57769,52484,Probation,foley,kevin,NULL,Male,Caucasian,12/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +51298,57769,52484,Probation,foley,kevin,NULL,Male,Caucasian,12/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +51298,57769,52484,Probation,foley,kevin,NULL,Male,Caucasian,12/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51273,57730,52451,PRETRIAL,Fletcher,Kalif,NULL,Male,African-American,06/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +51273,57730,52451,PRETRIAL,Fletcher,Kalif,NULL,Male,African-American,06/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +51273,57730,52451,PRETRIAL,Fletcher,Kalif,NULL,Male,African-American,06/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51284,57748,52468,Probation,candelario,william,NULL,Male,Caucasian,01/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +51284,57748,52468,Probation,candelario,william,NULL,Male,Caucasian,01/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +51284,57748,52468,Probation,candelario,william,NULL,Male,Caucasian,01/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51290,57756,52474,PRETRIAL,SPENCER,ZICO,NULL,Male,African-American,03/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +51290,57756,52474,PRETRIAL,SPENCER,ZICO,NULL,Male,African-American,03/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +51290,57756,52474,PRETRIAL,SPENCER,ZICO,NULL,Male,African-American,03/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +51280,57743,52463,PRETRIAL,Lewis,Joshua,NULL,Male,African-American,09/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +51280,57743,52463,PRETRIAL,Lewis,Joshua,NULL,Male,African-American,09/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +51280,57743,52463,PRETRIAL,Lewis,Joshua,NULL,Male,African-American,09/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51306,57777,52492,Probation,Rama,Daniel,NULL,Male,Hispanic,10/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/17/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +51306,57777,52492,Probation,Rama,Daniel,NULL,Male,Hispanic,10/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/17/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +51306,57777,52492,Probation,Rama,Daniel,NULL,Male,Hispanic,10/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +41408,57738,52458,PRETRIAL,Chamberlain,Deborah,NULL,Female,Caucasian,06/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +41408,57738,52458,PRETRIAL,Chamberlain,Deborah,NULL,Female,Caucasian,06/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,8,High,New,1,0 +41408,57738,52458,PRETRIAL,Chamberlain,Deborah,NULL,Female,Caucasian,06/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +9795,57740,52460,PRETRIAL,ILUS,ANTOINE,NULL,Male,African-American,08/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +9795,57740,52460,PRETRIAL,ILUS,ANTOINE,NULL,Male,African-American,08/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +9795,57740,52460,PRETRIAL,ILUS,ANTOINE,NULL,Male,African-American,08/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +51292,57759,52476,PRETRIAL,Brown,Corey,NULL,Male,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +51292,57759,52476,PRETRIAL,Brown,Corey,NULL,Male,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +51292,57759,52476,PRETRIAL,Brown,Corey,NULL,Male,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51294,57761,52478,Probation,Jean Baptiste,Examon,NULL,Male,African-Am,12/25/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +51294,57761,52478,Probation,Jean Baptiste,Examon,NULL,Male,African-Am,12/25/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +51294,57761,52478,Probation,Jean Baptiste,Examon,NULL,Male,African-Am,12/25/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51297,57768,52483,PRETRIAL,gonzalez,roberto,NULL,Male,Hispanic,09/26/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +51297,57768,52483,PRETRIAL,gonzalez,roberto,NULL,Male,Hispanic,09/26/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +51297,57768,52483,PRETRIAL,gonzalez,roberto,NULL,Male,Hispanic,09/26/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +32702,57731,45718,PRETRIAL,Delhomme,Dekorian,M,Male,African-American,03/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,Copy,1,0 +32702,57731,45718,PRETRIAL,Delhomme,Dekorian,M,Male,African-American,03/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,4,High,8,Risk of Recidivism,0.92,10,High,Copy,1,0 +32702,57731,45718,PRETRIAL,Delhomme,Dekorian,M,Male,African-American,03/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +51275,57733,52453,PRETRIAL,BROWN,JENNIFER,NULL,Female,Caucasian,05/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +51275,57733,52453,PRETRIAL,BROWN,JENNIFER,NULL,Female,Caucasian,05/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +51275,57733,52453,PRETRIAL,BROWN,JENNIFER,NULL,Female,Caucasian,05/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51296,57766,52481,Probation,MENDIZ,STACY,NULL,Female,Hispanic,12/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +51296,57766,52481,Probation,MENDIZ,STACY,NULL,Female,Hispanic,12/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +51296,57766,52481,Probation,MENDIZ,STACY,NULL,Female,Hispanic,12/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51309,57780,52495,Probation,MULLIGAN,CINDY,NULL,Female,Caucasian,10/24/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/17/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +51309,57780,52495,Probation,MULLIGAN,CINDY,NULL,Female,Caucasian,10/24/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +51309,57780,52495,Probation,MULLIGAN,CINDY,NULL,Female,Caucasian,10/24/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51300,57771,52486,Probation,HILL,ANTHONY,D,Male,African-American,06/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.05,8,High,New,1,0 +51300,57771,52486,Probation,HILL,ANTHONY,D,Male,African-American,06/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +51300,57771,52486,Probation,HILL,ANTHONY,D,Male,African-American,06/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +51281,57745,52465,Probation,Dennis,Demario,Terrez,Male,African-American,01/07/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-3.07,1,Low,New,1,0 +51281,57745,52465,Probation,Dennis,Demario,Terrez,Male,African-American,01/07/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +51281,57745,52465,Probation,Dennis,Demario,Terrez,Male,African-American,01/07/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51286,57750,52470,Probation,gonzales,richard,NULL,Male,Caucasian,05/07/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +51286,57750,52470,Probation,gonzales,richard,NULL,Male,Caucasian,05/07/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +51286,57750,52470,Probation,gonzales,richard,NULL,Male,Caucasian,05/07/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51288,57754,52472,Probation,COCHRAN,DANIEL,W,Male,Caucasian,04/18/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/13 0:00,2,Medium,7,Risk of Violence,-2.74,2,Low,New,1,0 +51288,57754,52472,Probation,COCHRAN,DANIEL,W,Male,Caucasian,04/18/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +51288,57754,52472,Probation,COCHRAN,DANIEL,W,Male,Caucasian,04/18/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +51303,57775,52490,Probation,Blige,lasheika,NULL,Female,African-American,06/27/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +51303,57775,52490,Probation,Blige,lasheika,NULL,Female,African-American,06/27/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +51303,57775,52490,Probation,Blige,lasheika,NULL,Female,African-American,06/27/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +12222,57742,52462,PRETRIAL,TERRY,WILLIE,JAMES,Male,African-American,03/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +12222,57742,52462,PRETRIAL,TERRY,WILLIE,JAMES,Male,African-American,03/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +12222,57742,52462,PRETRIAL,TERRY,WILLIE,JAMES,Male,African-American,03/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51307,57778,52493,Probation,Bosket,keisha,NULL,Female,African-American,06/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +51307,57778,52493,Probation,Bosket,keisha,NULL,Female,African-American,06/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,10,High,New,1,0 +51307,57778,52493,Probation,Bosket,keisha,NULL,Female,African-American,06/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51285,57749,52469,Probation,Jones,Michael,Lynn,Male,African-American,07/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Separated,1/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +51285,57749,52469,Probation,Jones,Michael,Lynn,Male,African-American,07/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Separated,1/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +51285,57749,52469,Probation,Jones,Michael,Lynn,Male,African-American,07/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Separated,1/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +25191,57734,52454,PRETRIAL,PULLIAM,LORENZO,JAIME,Male,African-American,09/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +25191,57734,52454,PRETRIAL,PULLIAM,LORENZO,JAIME,Male,African-American,09/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +25191,57734,52454,PRETRIAL,PULLIAM,LORENZO,JAIME,Male,African-American,09/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +2018,57736,52456,PRETRIAL,LEBRIGHT,JACQUELIE,NULL,Female,Caucasian,08/31/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +2018,57736,52456,PRETRIAL,LEBRIGHT,JACQUELIE,NULL,Female,Caucasian,08/31/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +2018,57736,52456,PRETRIAL,LEBRIGHT,JACQUELIE,NULL,Female,Caucasian,08/31/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,29,9,High,New,1,0 +51299,57770,52485,Probation,Harel Canada,Dietrick,NULL,Female,Caucasian,06/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +51299,57770,52485,Probation,Harel Canada,Dietrick,NULL,Female,Caucasian,06/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +51299,57770,52485,Probation,Harel Canada,Dietrick,NULL,Female,Caucasian,06/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51289,57755,52473,Probation,Lakhram,Shamnarine,NULL,Male,Other,06/12/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +51289,57755,52473,Probation,Lakhram,Shamnarine,NULL,Male,Other,06/12/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +51289,57755,52473,Probation,Lakhram,Shamnarine,NULL,Male,Other,06/12/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51291,57757,52475,Probation,floyd,christopher,NULL,Male,Caucasian,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,New,1,0 +51291,57757,52475,Probation,floyd,christopher,NULL,Male,Caucasian,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +51291,57757,52475,Probation,floyd,christopher,NULL,Male,Caucasian,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +3037,57739,52459,PRETRIAL,joiner,leonard,c,Male,African-American,12/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,4,High,7,Risk of Violence,-0.92,9,High,New,1,0 +3037,57739,52459,PRETRIAL,joiner,leonard,c,Male,African-American,12/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,4,High,8,Risk of Recidivism,0.62,10,High,New,1,0 +3037,57739,52459,PRETRIAL,joiner,leonard,c,Male,African-American,12/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51302,57773,52488,Probation,Nogueira,Patricia,Bezerra,Female,Hispanic,10/07/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +51302,57773,52488,Probation,Nogueira,Patricia,Bezerra,Female,Hispanic,10/07/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +51302,57773,52488,Probation,Nogueira,Patricia,Bezerra,Female,Hispanic,10/07/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51287,57752,52471,Probation,Freeborn-Hanks,Samantha,NULL,Female,Caucasian,05/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-1.87,5,Medium,New,1,0 +51287,57752,52471,Probation,Freeborn-Hanks,Samantha,NULL,Female,Caucasian,05/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +51287,57752,52471,Probation,Freeborn-Hanks,Samantha,NULL,Female,Caucasian,05/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +51283,57747,52467,PRETRIAL,Randazzo,Paula,NULL,Female,Caucasian,11/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/17/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +51283,57747,52467,PRETRIAL,Randazzo,Paula,NULL,Female,Caucasian,11/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/17/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +51283,57747,52467,PRETRIAL,Randazzo,Paula,NULL,Female,Caucasian,11/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51295,57765,52480,PRETRIAL,STROBRIDGE,KRYSTAL,NULL,Female,African-American,01/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +51295,57765,52480,PRETRIAL,STROBRIDGE,KRYSTAL,NULL,Female,African-American,01/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +51295,57765,52480,PRETRIAL,STROBRIDGE,KRYSTAL,NULL,Female,African-American,01/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51279,57744,52464,PRETRIAL,HORNE,ELIJAH,NULL,Male,African-American,11/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +51279,57744,52464,PRETRIAL,HORNE,ELIJAH,NULL,Male,African-American,11/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +51279,57744,52464,PRETRIAL,HORNE,ELIJAH,NULL,Male,African-American,11/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +49253,57794,52509,PRETRIAL,BAKER,PARET,ANTOINE,Male,African-American,10/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,4,High,7,Risk of Violence,-0.47,10,High,New,1,0 +49253,57794,52509,PRETRIAL,BAKER,PARET,ANTOINE,Male,African-American,10/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,4,High,8,Risk of Recidivism,0.77,10,High,New,1,0 +49253,57794,52509,PRETRIAL,BAKER,PARET,ANTOINE,Male,African-American,10/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51342,57812,52526,Probation,feeney,kevin,NULL,Male,Caucasian,03/24/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/18/13 0:00,2,Medium,7,Risk of Violence,-3.28,1,Low,New,1,0 +51342,57812,52526,Probation,feeney,kevin,NULL,Male,Caucasian,03/24/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +51342,57812,52526,Probation,feeney,kevin,NULL,Male,Caucasian,03/24/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/18/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51346,57815,52529,PRETRIAL,Jordan,Mildred,NULL,Female,Caucasian,11/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/18/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +51346,57815,52529,PRETRIAL,Jordan,Mildred,NULL,Female,Caucasian,11/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/18/13 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +51346,57815,52529,PRETRIAL,Jordan,Mildred,NULL,Female,Caucasian,11/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51318,57786,52501,PRETRIAL,Owens,Keandre,L,Male,African-American,10/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +51318,57786,52501,PRETRIAL,Owens,Keandre,L,Male,African-American,10/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +51318,57786,52501,PRETRIAL,Owens,Keandre,L,Male,African-American,10/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51350,57820,52533,PRETRIAL,Turcios,Cesar,NULL,Male,Caucasian,02/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +51350,57820,52533,PRETRIAL,Turcios,Cesar,NULL,Male,Caucasian,02/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +51350,57820,52533,PRETRIAL,Turcios,Cesar,NULL,Male,Caucasian,02/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51339,57807,52522,Probation,bilecki,lorraine,NULL,Female,Caucasian,04/15/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/18/13 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +51339,57807,52522,Probation,bilecki,lorraine,NULL,Female,Caucasian,04/15/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/18/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +51339,57807,52522,Probation,bilecki,lorraine,NULL,Female,Caucasian,04/15/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51323,57791,52506,PRETRIAL,Brooks,Luke,NULL,Male,African-American,11/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,4,High,7,Risk of Violence,-1.23,8,High,New,1,0 +51323,57791,52506,PRETRIAL,Brooks,Luke,NULL,Male,African-American,11/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,4,High,8,Risk of Recidivism,0.2,8,High,New,1,0 +51323,57791,52506,PRETRIAL,Brooks,Luke,NULL,Male,African-American,11/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +20203,57799,52514,PRETRIAL,SIMMONS,KELTRON,J,Male,African-American,08/28/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +20203,57799,52514,PRETRIAL,SIMMONS,KELTRON,J,Male,African-American,08/28/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +20203,57799,52514,PRETRIAL,SIMMONS,KELTRON,J,Male,African-American,08/28/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51360,57828,52541,PRETRIAL,CHURCHILL,MONICA,NULL,Female,Caucasian,10/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +51360,57828,52541,PRETRIAL,CHURCHILL,MONICA,NULL,Female,Caucasian,10/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +51360,57828,52541,PRETRIAL,CHURCHILL,MONICA,NULL,Female,Caucasian,10/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +27239,29991,26350,PRETRIAL,Wesley,Jerome,NULL,Male,African-American,03/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,Copy,1,0 +27239,29991,26350,PRETRIAL,Wesley,Jerome,NULL,Male,African-American,03/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,Copy,1,0 +27239,29991,26350,PRETRIAL,Wesley,Jerome,NULL,Male,African-American,03/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +51316,57784,52499,PRETRIAL,Bunsie,Kevin,NULL,Male,Other,05/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/18/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +51316,57784,52499,PRETRIAL,Bunsie,Kevin,NULL,Male,Other,05/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/18/13 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +51316,57784,52499,PRETRIAL,Bunsie,Kevin,NULL,Male,Other,05/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51336,57805,52520,PRETRIAL,Flowers,Terry,NULL,Male,Caucasian,06/08/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,2,Medium,7,Risk of Violence,-3.09,1,Low,New,1,0 +51336,57805,52520,PRETRIAL,Flowers,Terry,NULL,Male,Caucasian,06/08/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +51336,57805,52520,PRETRIAL,Flowers,Terry,NULL,Male,Caucasian,06/08/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +39025,57822,52535,PRETRIAL,Brandenburg,Gerald,NULL,Male,Caucasian,12/07/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +39025,57822,52535,PRETRIAL,Brandenburg,Gerald,NULL,Male,Caucasian,12/07/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +39025,57822,52535,PRETRIAL,Brandenburg,Gerald,NULL,Male,Caucasian,12/07/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51319,57787,52502,PRETRIAL,Mccloud,Jarvis,NULL,Male,African-American,06/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +51319,57787,52502,PRETRIAL,Mccloud,Jarvis,NULL,Male,African-American,06/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +51319,57787,52502,PRETRIAL,Mccloud,Jarvis,NULL,Male,African-American,06/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51355,57826,52539,Probation,paladugu,harish,NULL,Male,Asian,10/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +51355,57826,52539,Probation,paladugu,harish,NULL,Male,Asian,10/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +51355,57826,52539,Probation,paladugu,harish,NULL,Male,Asian,10/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51314,57782,52497,PRETRIAL,Gaskin,Russell,Bernard,Male,African-American,08/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +51314,57782,52497,PRETRIAL,Gaskin,Russell,Bernard,Male,African-American,08/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +51314,57782,52497,PRETRIAL,Gaskin,Russell,Bernard,Male,African-American,08/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51326,57796,52511,PRETRIAL,Panduro-Rojas,Ernesto,NULL,Male,Hispanic,10/26/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +51326,57796,52511,PRETRIAL,Panduro-Rojas,Ernesto,NULL,Male,Hispanic,10/26/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +51326,57796,52511,PRETRIAL,Panduro-Rojas,Ernesto,NULL,Male,Hispanic,10/26/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51335,57803,52518,PRETRIAL,vanderwynkle,jason,john,Male,Caucasian,07/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +51335,57803,52518,PRETRIAL,vanderwynkle,jason,john,Male,Caucasian,07/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +51335,57803,52518,PRETRIAL,vanderwynkle,jason,john,Male,Caucasian,07/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50081,57810,51044,Probation,Moody,Joseph,NULL,Male,African-American,09/27/81,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +50081,57810,51044,Probation,Moody,Joseph,NULL,Male,African-American,09/27/81,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +50081,57810,51044,Probation,Moody,Joseph,NULL,Male,African-American,09/27/81,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,1,Low,New,1,0 +51348,57817,52531,Probation,Edden,Felton,NULL,Male,African-American,10/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +51348,57817,52531,Probation,Edden,Felton,NULL,Male,African-American,10/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +51348,57817,52531,Probation,Edden,Felton,NULL,Male,African-American,10/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51321,57789,52504,PRETRIAL,Fairclough,Tupac,NULL,Male,African-American,12/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +51321,57789,52504,PRETRIAL,Fairclough,Tupac,NULL,Male,African-American,12/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +51321,57789,52504,PRETRIAL,Fairclough,Tupac,NULL,Male,African-American,12/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51343,57811,52525,PRETRIAL,Franco,Angel,Ignacio,Male,Caucasian,04/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +51343,57811,52525,PRETRIAL,Franco,Angel,Ignacio,Male,Caucasian,04/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +51343,57811,52525,PRETRIAL,Franco,Angel,Ignacio,Male,Caucasian,04/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +42220,57790,52505,PRETRIAL,Tejera,Andres,E,Male,Hispanic,03/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +42220,57790,52505,PRETRIAL,Tejera,Andres,E,Male,Hispanic,03/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +42220,57790,52505,PRETRIAL,Tejera,Andres,E,Male,Hispanic,03/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51353,57824,52537,PRETRIAL,Ethridge,Shanice,NULL,Female,African-American,09/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +51353,57824,52537,PRETRIAL,Ethridge,Shanice,NULL,Female,African-American,09/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,7,Medium,New,1,0 +51353,57824,52537,PRETRIAL,Ethridge,Shanice,NULL,Female,African-American,09/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51332,57798,52513,Probation,Cayetano,Cruz,NULL,Male,Hispanic,08/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/18/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +51332,57798,52513,Probation,Cayetano,Cruz,NULL,Male,Hispanic,08/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +51332,57798,52513,Probation,Cayetano,Cruz,NULL,Male,Hispanic,08/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51317,57785,52500,PRETRIAL,Fazio,Craig,NULL,Male,African-American,06/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +51317,57785,52500,PRETRIAL,Fazio,Craig,NULL,Male,African-American,06/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +51317,57785,52500,PRETRIAL,Fazio,Craig,NULL,Male,African-American,06/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51324,57792,52507,PRETRIAL,Toussaint,Carl,NULL,Male,African-American,09/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +51324,57792,52507,PRETRIAL,Toussaint,Carl,NULL,Male,African-American,09/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +51324,57792,52507,PRETRIAL,Toussaint,Carl,NULL,Male,African-American,09/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51344,57813,52527,Probation,Hendfield,Vernard,NULL,Male,African-American,03/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +51344,57813,52527,Probation,Hendfield,Vernard,NULL,Male,African-American,03/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +51344,57813,52527,Probation,Hendfield,Vernard,NULL,Male,African-American,03/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51345,57814,52528,Probation,haynes,steven,NULL,Male,African-American,01/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/18/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +51345,57814,52528,Probation,haynes,steven,NULL,Male,African-American,01/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/18/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +51345,57814,52528,Probation,haynes,steven,NULL,Male,African-American,01/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51337,57806,52521,Probation,monterio,kevin,NULL,Male,Caucasian,05/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/18/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +51337,57806,52521,Probation,monterio,kevin,NULL,Male,Caucasian,05/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/18/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +51337,57806,52521,Probation,monterio,kevin,NULL,Male,Caucasian,05/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51340,57808,52523,Probation,Sequra,Ashley,NULL,Female,Hispanic,10/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +51340,57808,52523,Probation,Sequra,Ashley,NULL,Female,Hispanic,10/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,7,Medium,New,1,0 +51340,57808,52523,Probation,Sequra,Ashley,NULL,Female,Hispanic,10/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +51351,57821,52534,PRETRIAL,Taffe,Horace,NULL,Male,African-American,11/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/18/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +51351,57821,52534,PRETRIAL,Taffe,Horace,NULL,Male,African-American,11/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/18/13 0:00,2,Medium,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +51351,57821,52534,PRETRIAL,Taffe,Horace,NULL,Male,African-American,11/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/18/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51325,57793,52508,PRETRIAL,Grant,Fredrick,Blais,Male,Caucasian,03/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +51325,57793,52508,PRETRIAL,Grant,Fredrick,Blais,Male,Caucasian,03/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +51325,57793,52508,PRETRIAL,Grant,Fredrick,Blais,Male,Caucasian,03/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51359,57827,52540,PRETRIAL,rivera,antonio,NULL,Male,African-American,04/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +51359,57827,52540,PRETRIAL,rivera,antonio,NULL,Male,African-American,04/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +51359,57827,52540,PRETRIAL,rivera,antonio,NULL,Male,African-American,04/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51361,57829,52542,PRETRIAL,Whittington,Matthew,NULL,Male,Caucasian,02/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +51361,57829,52542,PRETRIAL,Whittington,Matthew,NULL,Male,Caucasian,02/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +51361,57829,52542,PRETRIAL,Whittington,Matthew,NULL,Male,Caucasian,02/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +51341,57809,52524,PRETRIAL,maldonado,oscar,NULL,Male,Hispanic,07/14/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/18/13 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +51341,57809,52524,PRETRIAL,maldonado,oscar,NULL,Male,Hispanic,07/14/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/18/13 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +51341,57809,52524,PRETRIAL,maldonado,oscar,NULL,Male,Hispanic,07/14/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51320,57788,52503,PRETRIAL,Scott,Johhnie,NULL,Male,African-American,06/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/18/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +51320,57788,52503,PRETRIAL,Scott,Johhnie,NULL,Male,African-American,06/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/18/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +51320,57788,52503,PRETRIAL,Scott,Johhnie,NULL,Male,African-American,06/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51315,57783,52498,PRETRIAL,Terry,Maurice,Edward,Male,African-American,06/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/18/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +51315,57783,52498,PRETRIAL,Terry,Maurice,Edward,Male,African-American,06/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/18/13 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +51315,57783,52498,PRETRIAL,Terry,Maurice,Edward,Male,African-American,06/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51331,57797,52512,Probation,Jackson,Frank,NULL,Male,African-American,07/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +51331,57797,52512,Probation,Jackson,Frank,NULL,Male,African-American,07/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +51331,57797,52512,Probation,Jackson,Frank,NULL,Male,African-American,07/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +10944,57830,52543,Probation,whipple,adrian,NULL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +10944,57830,52543,Probation,whipple,adrian,NULL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +10944,57830,52543,Probation,whipple,adrian,NULL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +42940,57832,42827,PRETRIAL,Mcleod,Kevin,NULL,Male,African-American,10/18/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/18/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +42940,57832,42827,PRETRIAL,Mcleod,Kevin,NULL,Male,African-American,10/18/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,6,Medium,New,1,0 +42940,57832,42827,PRETRIAL,Mcleod,Kevin,NULL,Male,African-American,10/18/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/18/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51352,57823,52536,Probation,mason,ryan,NULL,Male,Caucasian,02/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/18/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +51352,57823,52536,Probation,mason,ryan,NULL,Male,Caucasian,02/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +51352,57823,52536,Probation,mason,ryan,NULL,Male,Caucasian,02/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51354,57825,52538,Probation,Bodurka,Lynn,NULL,Female,Caucasian,09/26/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/18/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +51354,57825,52538,Probation,Bodurka,Lynn,NULL,Female,Caucasian,09/26/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/18/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +51354,57825,52538,Probation,Bodurka,Lynn,NULL,Female,Caucasian,09/26/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51330,57795,52510,PRETRIAL,LITTMAN,JOHN,NULL,Male,Caucasian,10/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +51330,57795,52510,PRETRIAL,LITTMAN,JOHN,NULL,Male,Caucasian,10/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +51330,57795,52510,PRETRIAL,LITTMAN,JOHN,NULL,Male,Caucasian,10/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51334,57802,52517,Probation,nichols,earnest,NULL,Male,Caucasian,04/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +51334,57802,52517,Probation,nichols,earnest,NULL,Male,Caucasian,04/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +51334,57802,52517,Probation,nichols,earnest,NULL,Male,Caucasian,04/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +1307,57804,52519,PRETRIAL,MARROQUINPASCACIO,JUAN,NULL,Male,Hispanic,06/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +1307,57804,52519,PRETRIAL,MARROQUINPASCACIO,JUAN,NULL,Male,Hispanic,06/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +1307,57804,52519,PRETRIAL,MARROQUINPASCACIO,JUAN,NULL,Male,Hispanic,06/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/18/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +51375,57846,52558,PRETRIAL,Harris,Christy,H,Female,African-American,11/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +51375,57846,52558,PRETRIAL,Harris,Christy,H,Female,African-American,11/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +51375,57846,52558,PRETRIAL,Harris,Christy,H,Female,African-American,11/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +40605,57853,40225,PRETRIAL,JACKSON,ALEXUS,NULL,Female,African-American,01/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/19/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +40605,57853,40225,PRETRIAL,JACKSON,ALEXUS,NULL,Female,African-American,01/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,Copy,1,0 +40605,57853,40225,PRETRIAL,JACKSON,ALEXUS,NULL,Female,African-American,01/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/19/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +51377,57848,52560,PRETRIAL,Knight,Kory,NULL,Male,African-American,11/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +51377,57848,52560,PRETRIAL,Knight,Kory,NULL,Male,African-American,11/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +51377,57848,52560,PRETRIAL,Knight,Kory,NULL,Male,African-American,11/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51373,57844,52556,PRETRIAL,Mullins,Alan,Latorren,Male,African-American,08/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +51373,57844,52556,PRETRIAL,Mullins,Alan,Latorren,Male,African-American,08/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +51373,57844,52556,PRETRIAL,Mullins,Alan,Latorren,Male,African-American,08/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +29185,57851,28211,PRETRIAL,RAWLINS,JAHMARA,NULL,Male,African-American,07/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/19/13 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,Copy,1,0 +29185,57851,28211,PRETRIAL,RAWLINS,JAHMARA,NULL,Male,African-American,07/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/19/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,Copy,1,0 +29185,57851,28211,PRETRIAL,RAWLINS,JAHMARA,NULL,Male,African-American,07/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +51369,57839,52551,PRETRIAL,Bass,Timothy,NULL,Male,African-American,02/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +51369,57839,52551,PRETRIAL,Bass,Timothy,NULL,Male,African-American,02/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +51369,57839,52551,PRETRIAL,Bass,Timothy,NULL,Male,African-American,02/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51364,57834,52546,PRETRIAL,Bowers,Micheal,NULL,Male,Caucasian,03/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +51364,57834,52546,PRETRIAL,Bowers,Micheal,NULL,Male,Caucasian,03/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +51364,57834,52546,PRETRIAL,Bowers,Micheal,NULL,Male,Caucasian,03/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51382,57855,52565,PRETRIAL,Hovey,Joseph,NULL,Male,Caucasian,08/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +51382,57855,52565,PRETRIAL,Hovey,Joseph,NULL,Male,Caucasian,08/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +51382,57855,52565,PRETRIAL,Hovey,Joseph,NULL,Male,Caucasian,08/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +51378,57850,52562,PRETRIAL,exume,marie,anne,Female,African-American,07/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +51378,57850,52562,PRETRIAL,exume,marie,anne,Female,African-American,07/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,4,High,8,Risk of Recidivism,0.53,10,High,New,1,0 +51378,57850,52562,PRETRIAL,exume,marie,anne,Female,African-American,07/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +51365,57835,52547,PRETRIAL,Dowling,Terrashika,NULL,Female,African-American,03/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +51365,57835,52547,PRETRIAL,Dowling,Terrashika,NULL,Female,African-American,03/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,10,High,New,1,0 +51365,57835,52547,PRETRIAL,Dowling,Terrashika,NULL,Female,African-American,03/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +2620,57842,52554,PRETRIAL,PICARD,JESSY,LEO,Male,Caucasian,09/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +2620,57842,52554,PRETRIAL,PICARD,JESSY,LEO,Male,Caucasian,09/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +2620,57842,52554,PRETRIAL,PICARD,JESSY,LEO,Male,Caucasian,09/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51367,57837,52549,PRETRIAL,Stephan,Paul,NULL,Male,Caucasian,07/12/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/19/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +51367,57837,52549,PRETRIAL,Stephan,Paul,NULL,Male,Caucasian,07/12/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/19/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +51367,57837,52549,PRETRIAL,Stephan,Paul,NULL,Male,Caucasian,07/12/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51374,57845,52557,PRETRIAL,Miller,Charles,NULL,Male,Caucasian,08/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/13 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +51374,57845,52557,PRETRIAL,Miller,Charles,NULL,Male,Caucasian,08/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +51374,57845,52557,PRETRIAL,Miller,Charles,NULL,Male,Caucasian,08/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51368,57838,52550,PRETRIAL,Martinez,Anthony,NULL,Male,Hispanic,11/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +51368,57838,52550,PRETRIAL,Martinez,Anthony,NULL,Male,Hispanic,11/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +51368,57838,52550,PRETRIAL,Martinez,Anthony,NULL,Male,Hispanic,11/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51370,57840,52552,PRETRIAL,Johnson,Xavier,NULL,Male,African-American,10/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.67,9,High,New,1,0 +51370,57840,52552,PRETRIAL,Johnson,Xavier,NULL,Male,African-American,10/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +51370,57840,52552,PRETRIAL,Johnson,Xavier,NULL,Male,African-American,10/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51376,57847,52559,PRETRIAL,Brand,Henry,NULL,Male,African-American,11/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +51376,57847,52559,PRETRIAL,Brand,Henry,NULL,Male,African-American,11/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +51376,57847,52559,PRETRIAL,Brand,Henry,NULL,Male,African-American,11/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51372,57843,52555,PRETRIAL,Ewing,Regina,NULL,Female,African-American,12/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +51372,57843,52555,PRETRIAL,Ewing,Regina,NULL,Female,African-American,12/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +51372,57843,52555,PRETRIAL,Ewing,Regina,NULL,Female,African-American,12/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51380,57852,52563,PRETRIAL,Ayala,Christopher,NULL,Male,Caucasian,10/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,New,1,0 +51380,57852,52563,PRETRIAL,Ayala,Christopher,NULL,Male,Caucasian,10/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +51380,57852,52563,PRETRIAL,Ayala,Christopher,NULL,Male,Caucasian,10/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51379,57849,52561,PRETRIAL,Roach,Tedra,NULL,Female,African-American,05/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/19/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +51379,57849,52561,PRETRIAL,Roach,Tedra,NULL,Female,African-American,05/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/19/13 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +51379,57849,52561,PRETRIAL,Roach,Tedra,NULL,Female,African-American,05/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +51366,57836,52548,PRETRIAL,Germain,Raphael,NULL,Male,Caucasian,12/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +51366,57836,52548,PRETRIAL,Germain,Raphael,NULL,Male,Caucasian,12/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +51366,57836,52548,PRETRIAL,Germain,Raphael,NULL,Male,Caucasian,12/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51371,57841,52553,PRETRIAL,Ambroise,Dudley,NULL,Male,African-American,09/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +51371,57841,52553,PRETRIAL,Ambroise,Dudley,NULL,Male,African-American,09/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +51371,57841,52553,PRETRIAL,Ambroise,Dudley,NULL,Male,African-American,09/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51381,57854,52564,PRETRIAL,Osceloa,Nelson,NULL,Male,Native American,10/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +51381,57854,52564,PRETRIAL,Osceloa,Nelson,NULL,Male,Native American,10/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,9,High,New,1,0 +51381,57854,52564,PRETRIAL,Osceloa,Nelson,NULL,Male,Native American,10/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51363,57833,52545,PRETRIAL,Gonzalez,Ivan,NULL,Male,Caucasian,10/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +51363,57833,52545,PRETRIAL,Gonzalez,Ivan,NULL,Male,Caucasian,10/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +51363,57833,52545,PRETRIAL,Gonzalez,Ivan,NULL,Male,Caucasian,10/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51393,57862,52571,PRETRIAL,Aponte,Joseph,NULL,Male,Caucasian,12/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +51393,57862,52571,PRETRIAL,Aponte,Joseph,NULL,Male,Caucasian,12/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +51393,57862,52571,PRETRIAL,Aponte,Joseph,NULL,Male,Caucasian,12/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51400,57870,52579,PRETRIAL,Joseph,Benjamin,NULL,Male,African-American,11/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,4,High,7,Risk of Violence,-0.2,10,High,New,1,0 +51400,57870,52579,PRETRIAL,Joseph,Benjamin,NULL,Male,African-American,11/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +51400,57870,52579,PRETRIAL,Joseph,Benjamin,NULL,Male,African-American,11/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51384,57857,52567,PRETRIAL,Alfred,Andre,NULL,Male,Other,02/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +51384,57857,52567,PRETRIAL,Alfred,Andre,NULL,Male,Other,02/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +51384,57857,52567,PRETRIAL,Alfred,Andre,NULL,Male,Other,02/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51394,57864,52573,PRETRIAL,SIMMONS,RICKY,NULL,Male,African-American,05/01/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +51394,57864,52573,PRETRIAL,SIMMONS,RICKY,NULL,Male,African-American,05/01/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +51394,57864,52573,PRETRIAL,SIMMONS,RICKY,NULL,Male,African-American,05/01/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +51383,57856,52566,PRETRIAL,Ferrari,Edson,NULL,Male,Hispanic,02/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +51383,57856,52566,PRETRIAL,Ferrari,Edson,NULL,Male,Hispanic,02/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +51383,57856,52566,PRETRIAL,Ferrari,Edson,NULL,Male,Hispanic,02/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51386,57859,52569,PRETRIAL,PEREZ,MAURO,NULL,Male,Caucasian,03/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +51386,57859,52569,PRETRIAL,PEREZ,MAURO,NULL,Male,Caucasian,03/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,New,1,0 +51386,57859,52569,PRETRIAL,PEREZ,MAURO,NULL,Male,Caucasian,03/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51387,57861,52570,PRETRIAL,Cooks,James,NULL,Male,African-Am,05/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.02,1,Low,New,1,0 +51387,57861,52570,PRETRIAL,Cooks,James,NULL,Male,African-Am,05/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +51387,57861,52570,PRETRIAL,Cooks,James,NULL,Male,African-Am,05/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51398,57868,52577,PRETRIAL,Nesbitt,Ian,NULL,Male,African-American,01/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +51398,57868,52577,PRETRIAL,Nesbitt,Ian,NULL,Male,African-American,01/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +51398,57868,52577,PRETRIAL,Nesbitt,Ian,NULL,Male,African-American,01/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51385,57858,52568,PRETRIAL,BATISTE,ASHLIEGH,NULL,Female,African-American,04/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +51385,57858,52568,PRETRIAL,BATISTE,ASHLIEGH,NULL,Female,African-American,04/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +51385,57858,52568,PRETRIAL,BATISTE,ASHLIEGH,NULL,Female,African-American,04/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +51396,57866,52575,PRETRIAL,Cunningham,Brian,NULL,Male,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +51396,57866,52575,PRETRIAL,Cunningham,Brian,NULL,Male,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +51396,57866,52575,PRETRIAL,Cunningham,Brian,NULL,Male,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51401,57871,52580,PRETRIAL,rOMEROBARRIENTOS,Jonny,A,Male,Hispanic,01/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +51401,57871,52580,PRETRIAL,rOMEROBARRIENTOS,Jonny,A,Male,Hispanic,01/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +51401,57871,52580,PRETRIAL,rOMEROBARRIENTOS,Jonny,A,Male,Hispanic,01/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +32421,57863,52572,PRETRIAL,DIAZ,DANIEL,NULL,Male,Hispanic,04/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.21,4,Low,New,1,0 +32421,57863,52572,PRETRIAL,DIAZ,DANIEL,NULL,Male,Hispanic,04/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +32421,57863,52572,PRETRIAL,DIAZ,DANIEL,NULL,Male,Hispanic,04/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +51399,57869,52578,PRETRIAL,McManus,Kevin,NULL,Male,Caucasian,08/03/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +51399,57869,52578,PRETRIAL,McManus,Kevin,NULL,Male,Caucasian,08/03/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +51399,57869,52578,PRETRIAL,McManus,Kevin,NULL,Male,Caucasian,08/03/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +51395,57865,52574,PRETRIAL,Roland,Dantae,NULL,Male,African-American,08/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +51395,57865,52574,PRETRIAL,Roland,Dantae,NULL,Male,African-American,08/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +51395,57865,52574,PRETRIAL,Roland,Dantae,NULL,Male,African-American,08/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +49873,57860,50804,PRETRIAL,Duncan,Almond,Rashas,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,Copy,1,0 +49873,57860,50804,PRETRIAL,Duncan,Almond,Rashas,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,Copy,1,0 +49873,57860,50804,PRETRIAL,Duncan,Almond,Rashas,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +51397,57867,52576,PRETRIAL,Gonzalez,Ricardo,NULL,Male,Hispanic,10/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +51397,57867,52576,PRETRIAL,Gonzalez,Ricardo,NULL,Male,Hispanic,10/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +51397,57867,52576,PRETRIAL,Gonzalez,Ricardo,NULL,Male,Hispanic,10/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +49164,57881,52590,Probation,Smith,Tariq,NULL,Male,African-American,02/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,4,High,7,Risk of Violence,-0.62,10,High,New,1,0 +49164,57881,52590,Probation,Smith,Tariq,NULL,Male,African-American,02/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +49164,57881,52590,Probation,Smith,Tariq,NULL,Male,African-American,02/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +40031,43328,39615,PRETRIAL,Harris,Javon,D,Male,African-American,05/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +40031,43328,39615,PRETRIAL,Harris,Javon,D,Male,African-American,05/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +40031,43328,39615,PRETRIAL,Harris,Javon,D,Male,African-American,05/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51404,57874,52583,PRETRIAL,Walls,Khameron,NULL,Male,African-American,02/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +51404,57874,52583,PRETRIAL,Walls,Khameron,NULL,Male,African-American,02/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +51404,57874,52583,PRETRIAL,Walls,Khameron,NULL,Male,African-American,02/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +42171,57886,52594,PRETRIAL,Price,Leoplean,NULL,Male,African-American,08/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +42171,57886,52594,PRETRIAL,Price,Leoplean,NULL,Male,African-American,08/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +42171,57886,52594,PRETRIAL,Price,Leoplean,NULL,Male,African-American,08/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51406,57876,52585,PRETRIAL,Cramer,Steve,NULL,Male,Caucasian,11/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +51406,57876,52585,PRETRIAL,Cramer,Steve,NULL,Male,Caucasian,11/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +51406,57876,52585,PRETRIAL,Cramer,Steve,NULL,Male,Caucasian,11/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51413,57887,52595,PRETRIAL,FELDER,JOEL,NULL,Male,African-American,08/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,4,High,7,Risk of Violence,-0.73,9,High,New,1,0 +51413,57887,52595,PRETRIAL,FELDER,JOEL,NULL,Male,African-American,08/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +51413,57887,52595,PRETRIAL,FELDER,JOEL,NULL,Male,African-American,08/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51408,57879,52588,PRETRIAL,Cross,Allan,NULL,Male,Caucasian,02/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +51408,57879,52588,PRETRIAL,Cross,Allan,NULL,Male,Caucasian,02/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +51408,57879,52588,PRETRIAL,Cross,Allan,NULL,Male,Caucasian,02/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +40031,57884,39615,PRETRIAL,Harris,Javon,D,Male,African-American,05/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,Copy,1,0 +40031,57884,39615,PRETRIAL,Harris,Javon,D,Male,African-American,05/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,Copy,1,0 +40031,57884,39615,PRETRIAL,Harris,Javon,D,Male,African-American,05/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +51410,57882,52591,PRETRIAL,FICHTNER,CHARLES,CLIFTON,Male,Caucasian,03/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +51410,57882,52591,PRETRIAL,FICHTNER,CHARLES,CLIFTON,Male,Caucasian,03/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,8,Risk of Recidivism,-2.56,1,Low,New,1,0 +51410,57882,52591,PRETRIAL,FICHTNER,CHARLES,CLIFTON,Male,Caucasian,03/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51402,57873,52582,PRETRIAL,Davis,Nigel,J,Male,Other,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/21/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +51402,57873,52582,PRETRIAL,Davis,Nigel,J,Male,Other,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/21/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +51402,57873,52582,PRETRIAL,Davis,Nigel,J,Male,Other,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51405,57877,52586,PRETRIAL,DOMAN,ALVYN,NULL,Male,Other,09/22/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/21/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +51405,57877,52586,PRETRIAL,DOMAN,ALVYN,NULL,Male,Other,09/22/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/21/13 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +51405,57877,52586,PRETRIAL,DOMAN,ALVYN,NULL,Male,Other,09/22/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51407,57878,52587,PRETRIAL,Hall,Jermaine,NULL,Male,African-American,03/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +51407,57878,52587,PRETRIAL,Hall,Jermaine,NULL,Male,African-American,03/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +51407,57878,52587,PRETRIAL,Hall,Jermaine,NULL,Male,African-American,03/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51412,57885,52593,PRETRIAL,Salmeronoliva,Isaac,NULL,Male,Hispanic,08/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +51412,57885,52593,PRETRIAL,Salmeronoliva,Isaac,NULL,Male,Hispanic,08/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +51412,57885,52593,PRETRIAL,Salmeronoliva,Isaac,NULL,Male,Hispanic,08/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +36468,57872,52581,PRETRIAL,Dozil,Franck,Antoine,Male,African-American,11/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +36468,57872,52581,PRETRIAL,Dozil,Franck,Antoine,Male,African-American,11/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +36468,57872,52581,PRETRIAL,Dozil,Franck,Antoine,Male,African-American,11/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51409,57880,52589,PRETRIAL,PARKER,BERNARD,NULL,Male,African-American,08/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,New,1,0 +51409,57880,52589,PRETRIAL,PARKER,BERNARD,NULL,Male,African-American,08/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.77,10,High,New,1,0 +51409,57880,52589,PRETRIAL,PARKER,BERNARD,NULL,Male,African-American,08/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51411,57883,52592,PRETRIAL,Farruggia,Jenifer,NULL,Female,Caucasian,08/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +51411,57883,52592,PRETRIAL,Farruggia,Jenifer,NULL,Female,Caucasian,08/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +51411,57883,52592,PRETRIAL,Farruggia,Jenifer,NULL,Female,Caucasian,08/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51403,57875,52584,PRETRIAL,ASH,DEANGELO,NULL,Male,African-American,10/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +51403,57875,52584,PRETRIAL,ASH,DEANGELO,NULL,Male,African-American,10/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +51403,57875,52584,PRETRIAL,ASH,DEANGELO,NULL,Male,African-American,10/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +30377,57888,52596,PRETRIAL,CARRIER,MICHAEL,A,Male,Caucasian,11/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +30377,57888,52596,PRETRIAL,CARRIER,MICHAEL,A,Male,Caucasian,11/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +30377,57888,52596,PRETRIAL,CARRIER,MICHAEL,A,Male,Caucasian,11/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51446,57922,52625,Probation,Tabraue,Joshua,NULL,Male,Hispanic,01/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,New,1,0 +51446,57922,52625,Probation,Tabraue,Joshua,NULL,Male,Hispanic,01/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +51446,57922,52625,Probation,Tabraue,Joshua,NULL,Male,Hispanic,01/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51437,57909,52617,Probation,Chavez,Jeanette,NULL,Female,Hispanic,03/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +51437,57909,52617,Probation,Chavez,Jeanette,NULL,Female,Hispanic,03/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +51437,57909,52617,Probation,Chavez,Jeanette,NULL,Female,Hispanic,03/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +42681,57930,42535,PRETRIAL,Scott,Kenneth,W,Male,Caucasian,10/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,Copy,1,0 +42681,57930,42535,PRETRIAL,Scott,Kenneth,W,Male,Caucasian,10/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,Copy,1,0 +42681,57930,42535,PRETRIAL,Scott,Kenneth,W,Male,Caucasian,10/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +51422,57901,52609,PRETRIAL,WOODS,KHAREE,NULL,Male,African-American,10/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +51422,57901,52609,PRETRIAL,WOODS,KHAREE,NULL,Male,African-American,10/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +51422,57901,52609,PRETRIAL,WOODS,KHAREE,NULL,Male,African-American,10/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +44767,49252,44910,PRETRIAL,Turner,Perry,NULL,Male,African-American,10/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +44767,49252,44910,PRETRIAL,Turner,Perry,NULL,Male,African-American,10/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.89,10,High,New,1,0 +44767,49252,44910,PRETRIAL,Turner,Perry,NULL,Male,African-American,10/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +51415,57891,52599,PRETRIAL,Hamilton,Alfonso,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +51415,57891,52599,PRETRIAL,Hamilton,Alfonso,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +51415,57891,52599,PRETRIAL,Hamilton,Alfonso,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51435,57906,52614,Probation,Mcauliffe,John,NULL,Male,Caucasian,08/28/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +51435,57906,52614,Probation,Mcauliffe,John,NULL,Male,Caucasian,08/28/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +51435,57906,52614,Probation,Mcauliffe,John,NULL,Male,Caucasian,08/28/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +42501,57893,52601,PRETRIAL,George,Donnell,NULL,Male,African-American,08/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +42501,57893,52601,PRETRIAL,George,Donnell,NULL,Male,African-American,08/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +42501,57893,52601,PRETRIAL,George,Donnell,NULL,Male,African-American,08/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51450,57927,52630,PRETRIAL,HARRIS,TONY,DWAYNE,Male,African-American,06/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +51450,57927,52630,PRETRIAL,HARRIS,TONY,DWAYNE,Male,African-American,06/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +51450,57927,52630,PRETRIAL,HARRIS,TONY,DWAYNE,Male,African-American,06/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51456,57935,52637,Probation,Brown,Lorenzo,NULL,Male,African-American,01/08/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/22/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +51456,57935,52637,Probation,Brown,Lorenzo,NULL,Male,African-American,01/08/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +51456,57935,52637,Probation,Brown,Lorenzo,NULL,Male,African-American,01/08/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +37810,57914,50111,PRETRIAL,Amico,Marc,NULL,Male,Caucasian,05/21/80,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,1/22/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +37810,57914,50111,PRETRIAL,Amico,Marc,NULL,Male,Caucasian,05/21/80,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,1/22/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,Copy,1,0 +37810,57914,50111,PRETRIAL,Amico,Marc,NULL,Male,Caucasian,05/21/80,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +42681,46590,42535,PRETRIAL,Scott,Kenneth,W,Male,Caucasian,10/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +42681,46590,42535,PRETRIAL,Scott,Kenneth,W,Male,Caucasian,10/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +42681,46590,42535,PRETRIAL,Scott,Kenneth,W,Male,Caucasian,10/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51448,57924,52627,Probation,molina,carlos,NULL,Male,Hispanic,02/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +51448,57924,52627,Probation,molina,carlos,NULL,Male,Hispanic,02/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +51448,57924,52627,Probation,molina,carlos,NULL,Male,Hispanic,02/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51420,57898,52606,PRETRIAL,Queensbourrows,Lamar,NULL,Female,Other,12/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +51420,57898,52606,PRETRIAL,Queensbourrows,Lamar,NULL,Female,Other,12/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.53,2,Low,New,1,0 +51420,57898,52606,PRETRIAL,Queensbourrows,Lamar,NULL,Female,Other,12/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51442,57915,52621,Probation,youngson,scott,NULL,Male,Caucasian,08/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +51442,57915,52621,Probation,youngson,scott,NULL,Male,Caucasian,08/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +51442,57915,52621,Probation,youngson,scott,NULL,Male,Caucasian,08/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51417,57894,52602,PRETRIAL,Charles,Johny,NULL,Male,Other,05/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +51417,57894,52602,PRETRIAL,Charles,Johny,NULL,Male,Other,05/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +51417,57894,52602,PRETRIAL,Charles,Johny,NULL,Male,Other,05/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51438,57912,52619,PRETRIAL,SABORIT,JOSE,NULL,Male,African-American,07/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +51438,57912,52619,PRETRIAL,SABORIT,JOSE,NULL,Male,African-American,07/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +51438,57912,52619,PRETRIAL,SABORIT,JOSE,NULL,Male,African-American,07/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +48321,57919,49002,PRETRIAL,Mackey,Garrick,NULL,Male,African-American,02/02/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +48321,57919,49002,PRETRIAL,Mackey,Garrick,NULL,Male,African-American,02/02/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +48321,57919,49002,PRETRIAL,Mackey,Garrick,NULL,Male,African-American,02/02/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,4,High,18,Risk of Failure to Appear,21,3,Low,New,1,0 +51443,57917,52622,Probation,Eliejr,Jean,NULL,Male,African-American,09/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +51443,57917,52622,Probation,Eliejr,Jean,NULL,Male,African-American,09/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +51443,57917,52622,Probation,Eliejr,Jean,NULL,Male,African-American,09/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +37227,57931,52633,PRETRIAL,VARGASARAYA,GUSTAVO,A,Male,Caucasian,02/20/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +37227,57931,52633,PRETRIAL,VARGASARAYA,GUSTAVO,A,Male,Caucasian,02/20/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +37227,57931,52633,PRETRIAL,VARGASARAYA,GUSTAVO,A,Male,Caucasian,02/20/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +42530,57896,52604,PRETRIAL,Daley,Matthew,NULL,Male,Other,07/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +42530,57896,52604,PRETRIAL,Daley,Matthew,NULL,Male,Other,07/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,4,High,8,Risk of Recidivism,0.31,9,High,New,1,0 +42530,57896,52604,PRETRIAL,Daley,Matthew,NULL,Male,Other,07/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51432,57903,52611,PRETRIAL,Dean,James,T,Male,Caucasian,11/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +51432,57903,52611,PRETRIAL,Dean,James,T,Male,Caucasian,11/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +51432,57903,52611,PRETRIAL,Dean,James,T,Male,Caucasian,11/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51440,57910,52618,DRRD,Ray,Erik,Lawayne,Male,African-American,04/04/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,New,1,0 +51440,57910,52618,DRRD,Ray,Erik,Lawayne,Male,African-American,04/04/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,7,Medium,New,1,0 +51440,57910,52618,DRRD,Ray,Erik,Lawayne,Male,African-American,04/04/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,3,Low,New,1,0 +32276,57889,52597,PRETRIAL,Kitchen,Paul,NULL,Male,Caucasian,07/03/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +32276,57889,52597,PRETRIAL,Kitchen,Paul,NULL,Male,Caucasian,07/03/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +32276,57889,52597,PRETRIAL,Kitchen,Paul,NULL,Male,Caucasian,07/03/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +8637,57938,52640,DRRD,Sanders,Anthony,L.,Male,African-American,04/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,4,High,7,Risk of Violence,-0.84,9,High,New,1,0 +8637,57938,52640,DRRD,Sanders,Anthony,L.,Male,African-American,04/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +8637,57938,52640,DRRD,Sanders,Anthony,L.,Male,African-American,04/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51444,57918,52623,PRETRIAL,Bollman,Rachel,NULL,Female,Caucasian,08/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +51444,57918,52623,PRETRIAL,Bollman,Rachel,NULL,Female,Caucasian,08/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +51444,57918,52623,PRETRIAL,Bollman,Rachel,NULL,Female,Caucasian,08/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51459,57939,52641,Probation,AUGUSTINE,LOUIS,NULL,Male,Caucasian,03/01/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +51459,57939,52641,Probation,AUGUSTINE,LOUIS,NULL,Male,Caucasian,03/01/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +51459,57939,52641,Probation,AUGUSTINE,LOUIS,NULL,Male,Caucasian,03/01/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +51449,57926,52629,Probation,walters,lucas,NULL,Male,Caucasian,07/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/22/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +51449,57926,52629,Probation,walters,lucas,NULL,Male,Caucasian,07/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +51449,57926,52629,Probation,walters,lucas,NULL,Male,Caucasian,07/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51419,57897,52605,PRETRIAL,MUZZI,ROLAND,NULL,Male,Caucasian,09/02/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +51419,57897,52605,PRETRIAL,MUZZI,ROLAND,NULL,Male,Caucasian,09/02/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +51419,57897,52605,PRETRIAL,MUZZI,ROLAND,NULL,Male,Caucasian,09/02/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51421,57900,52608,PRETRIAL,Zaremba,Thomas,Anthony,Male,Caucasian,08/28/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +51421,57900,52608,PRETRIAL,Zaremba,Thomas,Anthony,Male,Caucasian,08/28/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +51421,57900,52608,PRETRIAL,Zaremba,Thomas,Anthony,Male,Caucasian,08/28/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51441,57913,52620,Probation,etienne,juniar,NULL,Female,African-American,06/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +51441,57913,52620,Probation,etienne,juniar,NULL,Female,African-American,06/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +51441,57913,52620,Probation,etienne,juniar,NULL,Female,African-American,06/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51416,57892,52600,PRETRIAL,Gough,John,NULL,Male,Caucasian,04/18/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +51416,57892,52600,PRETRIAL,Gough,John,NULL,Male,Caucasian,04/18/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +51416,57892,52600,PRETRIAL,Gough,John,NULL,Male,Caucasian,04/18/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30687,57908,52616,PRETRIAL,bray,leroy,NULL,Male,African-American,11/19/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.01,4,Low,New,1,0 +30687,57908,52616,PRETRIAL,bray,leroy,NULL,Male,African-American,11/19/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +30687,57908,52616,PRETRIAL,bray,leroy,NULL,Male,African-American,11/19/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51452,57929,52632,Probation,smith,easton,NULL,Male,African-American,08/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +51452,57929,52632,Probation,smith,easton,NULL,Male,African-American,08/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +51452,57929,52632,Probation,smith,easton,NULL,Male,African-American,08/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51455,57934,52636,Probation,isaacs,trenton,NULL,Male,African-American,09/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +51455,57934,52636,Probation,isaacs,trenton,NULL,Male,African-American,09/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +51455,57934,52636,Probation,isaacs,trenton,NULL,Male,African-American,09/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51457,57936,52638,PRETRIAL,CHANG,ANTONIO,NULL,Male,African-American,07/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.31,7,Medium,New,1,0 +51457,57936,52638,PRETRIAL,CHANG,ANTONIO,NULL,Male,African-American,07/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.7,10,High,New,1,0 +51457,57936,52638,PRETRIAL,CHANG,ANTONIO,NULL,Male,African-American,07/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +51445,57920,52624,Probation,Shell,Laquilla,NULL,Female,African-American,07/16/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/22/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +51445,57920,52624,Probation,Shell,Laquilla,NULL,Female,African-American,07/16/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +51445,57920,52624,Probation,Shell,Laquilla,NULL,Female,African-American,07/16/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/22/13 0:00,2,Medium,18,Risk of Failure to Appear,30,9,High,New,1,0 +51414,57890,52598,PRETRIAL,Payne,Gary,NULL,Male,African-American,07/26/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +51414,57890,52598,PRETRIAL,Payne,Gary,NULL,Male,African-American,07/26/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +51414,57890,52598,PRETRIAL,Payne,Gary,NULL,Male,African-American,07/26/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51436,57907,52615,Probation,rowland,niles,NULL,Male,Caucasian,10/17/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +51436,57907,52615,Probation,rowland,niles,NULL,Male,Caucasian,10/17/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +51436,57907,52615,Probation,rowland,niles,NULL,Male,Caucasian,10/17/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51458,57937,52639,Probation,Holland,Debra,Select,Female,African-American,11/09/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/22/13 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,New,1,0 +51458,57937,52639,Probation,Holland,Debra,Select,Female,African-American,11/09/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +51458,57937,52639,Probation,Holland,Debra,Select,Female,African-American,11/09/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/22/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51447,57923,52626,PRETRIAL,Olek,Amanda,NULL,Female,Caucasian,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/22/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +51447,57923,52626,PRETRIAL,Olek,Amanda,NULL,Female,Caucasian,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/22/13 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +51447,57923,52626,PRETRIAL,Olek,Amanda,NULL,Female,Caucasian,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +12511,57925,52628,PRETRIAL,Malone,Micheal,NULL,Male,Caucasian,01/20/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/22/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +12511,57925,52628,PRETRIAL,Malone,Micheal,NULL,Male,Caucasian,01/20/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +12511,57925,52628,PRETRIAL,Malone,Micheal,NULL,Male,Caucasian,01/20/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51418,57895,52603,PRETRIAL,Hicks,Kenneth,T,Male,African-American,12/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +51418,57895,52603,PRETRIAL,Hicks,Kenneth,T,Male,African-American,12/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +51418,57895,52603,PRETRIAL,Hicks,Kenneth,T,Male,African-American,12/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51429,57902,52610,PRETRIAL,Rich,Courtland,Bernard,Male,African-American,04/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +51429,57902,52610,PRETRIAL,Rich,Courtland,Bernard,Male,African-American,04/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +51429,57902,52610,PRETRIAL,Rich,Courtland,Bernard,Male,African-American,04/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51433,57904,52612,PRETRIAL,Louis,Samuel,NULL,Male,Other,07/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +51433,57904,52612,PRETRIAL,Louis,Samuel,NULL,Male,Other,07/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +51433,57904,52612,PRETRIAL,Louis,Samuel,NULL,Male,Other,07/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51454,57932,52634,Probation,michael,marlon,NULL,Male,Hispanic,09/25/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +51454,57932,52634,Probation,michael,marlon,NULL,Male,Hispanic,09/25/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +51454,57932,52634,Probation,michael,marlon,NULL,Male,Hispanic,09/25/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51485,57967,52669,Probation,Park,Kyung,NULL,Male,Oriental,06/27/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +51485,57967,52669,Probation,Park,Kyung,NULL,Male,Oriental,06/27/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +51485,57967,52669,Probation,Park,Kyung,NULL,Male,Oriental,06/27/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +19704,57981,52683,PRETRIAL,GREEN,LOUIS,JEROME,Male,African-American,07/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +19704,57981,52683,PRETRIAL,GREEN,LOUIS,JEROME,Male,African-American,07/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,4,High,8,Risk of Recidivism,0.92,10,High,New,1,0 +19704,57981,52683,PRETRIAL,GREEN,LOUIS,JEROME,Male,African-American,07/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +51466,57946,52648,PRETRIAL,LAMPLEY,SHEM,NULL,Male,African-American,02/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +51466,57946,52648,PRETRIAL,LAMPLEY,SHEM,NULL,Male,African-American,02/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +51466,57946,52648,PRETRIAL,LAMPLEY,SHEM,NULL,Male,African-American,02/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +51475,57953,52655,PRETRIAL,Osceola,Ravenne,NULL,Female,Native American,08/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +51475,57953,52655,PRETRIAL,Osceola,Ravenne,NULL,Female,Native American,08/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +51475,57953,52655,PRETRIAL,Osceola,Ravenne,NULL,Female,Native American,08/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51482,57962,52664,Probation,Henry,Sonia,Althia,Female,African-American,02/11/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +51482,57962,52664,Probation,Henry,Sonia,Althia,Female,African-American,02/11/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +51482,57962,52664,Probation,Henry,Sonia,Althia,Female,African-American,02/11/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51493,57976,52678,Probation,MUDIE,GARY,A,Male,African-American,01/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,New,1,0 +51493,57976,52678,Probation,MUDIE,GARY,A,Male,African-American,01/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +51493,57976,52678,Probation,MUDIE,GARY,A,Male,African-American,01/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51461,57941,52643,PRETRIAL,Brewer,Fuquan,NULL,Male,African-American,04/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +51461,57941,52643,PRETRIAL,Brewer,Fuquan,NULL,Male,African-American,04/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +51461,57941,52643,PRETRIAL,Brewer,Fuquan,NULL,Male,African-American,04/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51479,57958,52660,Probation,Kaplan,jacquelyn,Renee,Female,Caucasian,08/21/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +51479,57958,52660,Probation,Kaplan,jacquelyn,Renee,Female,Caucasian,08/21/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +51479,57958,52660,Probation,Kaplan,jacquelyn,Renee,Female,Caucasian,08/21/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51496,57979,52681,Probation,Sacacian,Emanuel,NULL,Male,Caucasian,07/15/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +51496,57979,52681,Probation,Sacacian,Emanuel,NULL,Male,Caucasian,07/15/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +51496,57979,52681,Probation,Sacacian,Emanuel,NULL,Male,Caucasian,07/15/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51488,57970,52672,PRETRIAL,Cataldo,Joseph,Michael,Male,Caucasian,10/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +51488,57970,52672,PRETRIAL,Cataldo,Joseph,Michael,Male,Caucasian,10/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +51488,57970,52672,PRETRIAL,Cataldo,Joseph,Michael,Male,Caucasian,10/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51462,57942,52644,PRETRIAL,Ramsook,Dechand,NULL,Male,Other,08/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +51462,57942,52644,PRETRIAL,Ramsook,Dechand,NULL,Male,Other,08/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +51462,57942,52644,PRETRIAL,Ramsook,Dechand,NULL,Male,Other,08/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51476,57955,52657,Probation,SAULSBY,SAMANTHA,E,Female,African-American,02/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +51476,57955,52657,Probation,SAULSBY,SAMANTHA,E,Female,African-American,02/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +51476,57955,52657,Probation,SAULSBY,SAMANTHA,E,Female,African-American,02/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51489,57971,52673,Probation,Caruso,Michael,NULL,Male,Caucasian,07/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +51489,57971,52673,Probation,Caruso,Michael,NULL,Male,Caucasian,07/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +51489,57971,52673,Probation,Caruso,Michael,NULL,Male,Caucasian,07/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51495,57978,52680,Probation,hyppolite,chimidley,NULL,Male,African-American,10/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +51495,57978,52680,Probation,hyppolite,chimidley,NULL,Male,African-American,10/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +51495,57978,52680,Probation,hyppolite,chimidley,NULL,Male,African-American,10/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51469,57949,52651,PRETRIAL,SIMMONS,JEFFREY,NULL,Male,African-American,01/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +51469,57949,52651,PRETRIAL,SIMMONS,JEFFREY,NULL,Male,African-American,01/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +51469,57949,52651,PRETRIAL,SIMMONS,JEFFREY,NULL,Male,African-American,01/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51470,57950,52652,Probation,Gammage,Sherman,Leonard,Male,African-American,09/21/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +51470,57950,52652,Probation,Gammage,Sherman,Leonard,Male,African-American,09/21/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +51470,57950,52652,Probation,Gammage,Sherman,Leonard,Male,African-American,09/21/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51467,57947,52649,PRETRIAL,ARCHER,KENNETH,LEONARD,Male,African-American,08/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +51467,57947,52649,PRETRIAL,ARCHER,KENNETH,LEONARD,Male,African-American,08/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +51467,57947,52649,PRETRIAL,ARCHER,KENNETH,LEONARD,Male,African-American,08/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51484,57965,52667,Probation,MURRAY,MELISSA,DENISE,Female,African-American,12/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +51484,57965,52667,Probation,MURRAY,MELISSA,DENISE,Female,African-American,12/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +51484,57965,52667,Probation,MURRAY,MELISSA,DENISE,Female,African-American,12/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51464,57944,52646,PRETRIAL,Hernandez,Jose,NULL,Male,Hispanic,06/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +51464,57944,52646,PRETRIAL,Hernandez,Jose,NULL,Male,Hispanic,06/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +51464,57944,52646,PRETRIAL,Hernandez,Jose,NULL,Male,Hispanic,06/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51460,57940,52642,PRETRIAL,Faton,Yonel,NULL,Male,African-American,05/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +51460,57940,52642,PRETRIAL,Faton,Yonel,NULL,Male,African-American,05/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +51460,57940,52642,PRETRIAL,Faton,Yonel,NULL,Male,African-American,05/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51480,57959,52661,Probation,henry,christopher,NULL,Male,African-American,07/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/23/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +51480,57959,52661,Probation,henry,christopher,NULL,Male,African-American,07/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/23/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +51480,57959,52661,Probation,henry,christopher,NULL,Male,African-American,07/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51481,57961,52663,PRETRIAL,Bankston,Tamera,NULL,Female,African-American,07/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.06,8,High,New,1,0 +51481,57961,52663,PRETRIAL,Bankston,Tamera,NULL,Female,African-American,07/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +51481,57961,52663,PRETRIAL,Bankston,Tamera,NULL,Female,African-American,07/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51486,57968,52670,Probation,kahn,david,NULL,Male,Other,07/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +51486,57968,52670,Probation,kahn,david,NULL,Male,Other,07/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +51486,57968,52670,Probation,kahn,david,NULL,Male,Other,07/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51497,57980,52682,PRETRIAL,Reid,Merlene,NULL,Female,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +51497,57980,52682,PRETRIAL,Reid,Merlene,NULL,Female,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +51497,57980,52682,PRETRIAL,Reid,Merlene,NULL,Female,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51492,57975,52677,Probation,brooks,stephen,NULL,Male,Caucasian,07/19/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.29,3,Low,New,1,0 +51492,57975,52677,Probation,brooks,stephen,NULL,Male,Caucasian,07/19/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +51492,57975,52677,Probation,brooks,stephen,NULL,Male,Caucasian,07/19/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +51465,57945,52647,PRETRIAL,KENDRICK,TIMOTHY,DRAKE,Male,African-American,01/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/23/13 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +51465,57945,52647,PRETRIAL,KENDRICK,TIMOTHY,DRAKE,Male,African-American,01/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/23/13 0:00,4,High,8,Risk of Recidivism,0.45,9,High,New,1,0 +51465,57945,52647,PRETRIAL,KENDRICK,TIMOTHY,DRAKE,Male,African-American,01/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/23/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +41181,57954,52656,PRETRIAL,Palatnikow,Vladislav,NULL,Male,Caucasian,06/22/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +41181,57954,52656,PRETRIAL,Palatnikow,Vladislav,NULL,Male,Caucasian,06/22/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +41181,57954,52656,PRETRIAL,Palatnikow,Vladislav,NULL,Male,Caucasian,06/22/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +39442,57964,52666,PRETRIAL,MORIN,EMMANUEL,NULL,Male,African-American,09/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +39442,57964,52666,PRETRIAL,MORIN,EMMANUEL,NULL,Male,African-American,09/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +39442,57964,52666,PRETRIAL,MORIN,EMMANUEL,NULL,Male,African-American,09/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51490,57972,52674,Probation,Maya,Zully,NULL,Female,Caucasian,12/10/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +51490,57972,52674,Probation,Maya,Zully,NULL,Female,Caucasian,12/10/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +51490,57972,52674,Probation,Maya,Zully,NULL,Female,Caucasian,12/10/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51471,57951,52653,Probation,Mccabe,Sean,NULL,Male,Hispanic,04/22/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +51471,57951,52653,Probation,Mccabe,Sean,NULL,Male,Hispanic,04/22/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +51471,57951,52653,Probation,Mccabe,Sean,NULL,Male,Hispanic,04/22/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +51487,57969,52671,Probation,Martinez,Giovanni,Joel,Male,Hispanic,12/08/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,New,1,0 +51487,57969,52671,Probation,Martinez,Giovanni,Joel,Male,Hispanic,12/08/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +51487,57969,52671,Probation,Martinez,Giovanni,Joel,Male,Hispanic,12/08/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51468,57948,52650,PRETRIAL,Hernandez,Christian,Leonel,Male,Caucasian,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +51468,57948,52650,PRETRIAL,Hernandez,Christian,Leonel,Male,Caucasian,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +51468,57948,52650,PRETRIAL,Hernandez,Christian,Leonel,Male,Caucasian,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51463,57943,52645,PRETRIAL,Howard,Kimberly,N,Female,African-American,09/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +51463,57943,52645,PRETRIAL,Howard,Kimberly,N,Female,African-American,09/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +51463,57943,52645,PRETRIAL,Howard,Kimberly,N,Female,African-American,09/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51494,57977,52679,Probation,Weston,Kim,NULL,Female,African-American,01/04/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.34,3,Low,New,1,0 +51494,57977,52679,Probation,Weston,Kim,NULL,Female,African-American,01/04/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,10,High,New,1,0 +51494,57977,52679,Probation,Weston,Kim,NULL,Female,African-American,01/04/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51477,57956,52658,Probation,montero,russell,NULL,Male,Caucasian,06/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +51477,57956,52658,Probation,montero,russell,NULL,Male,Caucasian,06/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +51477,57956,52658,Probation,montero,russell,NULL,Male,Caucasian,06/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51503,57990,52691,PRETRIAL,Rickard,Cody,Ross,Male,Caucasian,10/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +51503,57990,52691,PRETRIAL,Rickard,Cody,Ross,Male,Caucasian,10/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +51503,57990,52691,PRETRIAL,Rickard,Cody,Ross,Male,Caucasian,10/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51531,58024,52723,Probation,Figueroa,Luis,Alberto,Male,Hispanic,07/11/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +51531,58024,52723,Probation,Figueroa,Luis,Alberto,Male,Hispanic,07/11/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +51531,58024,52723,Probation,Figueroa,Luis,Alberto,Male,Hispanic,07/11/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51523,58011,52711,PRETRIAL,MARTINEZ,LISBET,DIAZ,Female,Hispanic,10/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +51523,58011,52711,PRETRIAL,MARTINEZ,LISBET,DIAZ,Female,Hispanic,10/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +51523,58011,52711,PRETRIAL,MARTINEZ,LISBET,DIAZ,Female,Hispanic,10/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51511,57998,52699,PRETRIAL,PEREZ-ALEJO,DENNYS,A,Male,Hispanic,08/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +51511,57998,52699,PRETRIAL,PEREZ-ALEJO,DENNYS,A,Male,Hispanic,08/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +51511,57998,52699,PRETRIAL,PEREZ-ALEJO,DENNYS,A,Male,Hispanic,08/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51527,58016,52716,Probation,Martinez,Amillar,Enrique,Male,Hispanic,05/06/82,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +51527,58016,52716,Probation,Martinez,Amillar,Enrique,Male,Hispanic,05/06/82,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +51527,58016,52716,Probation,Martinez,Amillar,Enrique,Male,Hispanic,05/06/82,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +33903,58019,52719,PRETRIAL,Jeanpierre,Roosevelt,NULL,Male,African-American,07/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +33903,58019,52719,PRETRIAL,Jeanpierre,Roosevelt,NULL,Male,African-American,07/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +33903,58019,52719,PRETRIAL,Jeanpierre,Roosevelt,NULL,Male,African-American,07/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51518,58006,52707,PRETRIAL,Tauber,Gregory,Lee,Male,Caucasian,10/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,1/24/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +51518,58006,52707,PRETRIAL,Tauber,Gregory,Lee,Male,Caucasian,10/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +51518,58006,52707,PRETRIAL,Tauber,Gregory,Lee,Male,Caucasian,10/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51520,58008,52709,PRETRIAL,MORGAN,ROSANNE,NULL,Female,Caucasian,03/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.85,2,Low,New,1,0 +51520,58008,52709,PRETRIAL,MORGAN,ROSANNE,NULL,Female,Caucasian,03/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,9,High,New,1,0 +51520,58008,52709,PRETRIAL,MORGAN,ROSANNE,NULL,Female,Caucasian,03/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +51505,57993,52694,PRETRIAL,Rosas,Yesenia,NULL,Female,Hispanic,03/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +51505,57993,52694,PRETRIAL,Rosas,Yesenia,NULL,Female,Hispanic,03/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +51505,57993,52694,PRETRIAL,Rosas,Yesenia,NULL,Female,Hispanic,03/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51537,58027,52726,PRETRIAL,STEVENS,KENNEDY,NULL,Male,African-American,03/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +51537,58027,52726,PRETRIAL,STEVENS,KENNEDY,NULL,Male,African-American,03/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +51537,58027,52726,PRETRIAL,STEVENS,KENNEDY,NULL,Male,African-American,03/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +32627,58029,52728,PRETRIAL,ANDRADE,JHONATHAN,NULL,Male,Caucasian,01/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +32627,58029,52728,PRETRIAL,ANDRADE,JHONATHAN,NULL,Male,Caucasian,01/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +32627,58029,52728,PRETRIAL,ANDRADE,JHONATHAN,NULL,Male,Caucasian,01/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51313,58000,52701,DRRD,Sanabria,Joshua,Jesus,Male,Hispanic,01/13/93,17,All Scales,Intake,English,Probation Violator,Probation,Single,1/24/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +51313,58000,52701,DRRD,Sanabria,Joshua,Jesus,Male,Hispanic,01/13/93,17,All Scales,Intake,English,Probation Violator,Probation,Single,1/24/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +51313,58000,52701,DRRD,Sanabria,Joshua,Jesus,Male,Hispanic,01/13/93,17,All Scales,Intake,English,Probation Violator,Probation,Single,1/24/13 0:00,2,Medium,18,Risk of Failure to Appear,23,4,Low,New,1,0 +51525,58014,52714,PRETRIAL,Brady,Parris,A,Male,African-American,01/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/24/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +51525,58014,52714,PRETRIAL,Brady,Parris,A,Male,African-American,01/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +51525,58014,52714,PRETRIAL,Brady,Parris,A,Male,African-American,01/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51500,57985,52687,PRETRIAL,Adams,Adam,Jerome,Male,African-American,06/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +51500,57985,52687,PRETRIAL,Adams,Adam,Jerome,Male,African-American,06/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +51500,57985,52687,PRETRIAL,Adams,Adam,Jerome,Male,African-American,06/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +43159,58021,52720,PRETRIAL,Richardson,Edward,NULL,Male,African-American,09/17/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +43159,58021,52720,PRETRIAL,Richardson,Edward,NULL,Male,African-American,09/17/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +43159,58021,52720,PRETRIAL,Richardson,Edward,NULL,Male,African-American,09/17/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +15635,57984,52686,PRETRIAL,JOHNSON,BOBBY,NULL,Male,African-American,01/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,7,Risk of Violence,-1.43,7,Medium,New,1,0 +15635,57984,52686,PRETRIAL,JOHNSON,BOBBY,NULL,Male,African-American,01/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +15635,57984,52686,PRETRIAL,JOHNSON,BOBBY,NULL,Male,African-American,01/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51517,58005,52706,PRETRIAL,hamilton,gabrielle,NULL,Female,Caucasian,08/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.25,3,Low,New,1,0 +51517,58005,52706,PRETRIAL,hamilton,gabrielle,NULL,Female,Caucasian,08/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.03,8,High,New,1,0 +51517,58005,52706,PRETRIAL,hamilton,gabrielle,NULL,Female,Caucasian,08/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51529,58022,52721,Probation,Bishop,Jason,NULL,Male,Caucasian,02/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +51529,58022,52721,Probation,Bishop,Jason,NULL,Male,Caucasian,02/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +51529,58022,52721,Probation,Bishop,Jason,NULL,Male,Caucasian,02/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +6588,57987,52688,PRETRIAL,SWEETINGS,LEONARD,NULL,Male,African-American,08/13/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/24/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +6588,57987,52688,PRETRIAL,SWEETINGS,LEONARD,NULL,Male,African-American,08/13/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +6588,57987,52688,PRETRIAL,SWEETINGS,LEONARD,NULL,Male,African-American,08/13/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/24/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +51513,58001,52702,Probation,narace,harry,NULL,Male,Other,09/08/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +51513,58001,52702,Probation,narace,harry,NULL,Male,Other,09/08/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +51513,58001,52702,Probation,narace,harry,NULL,Male,Other,09/08/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51536,58026,52725,Probation,Comarcho,Kyle,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +51536,58026,52725,Probation,Comarcho,Kyle,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +51536,58026,52725,Probation,Comarcho,Kyle,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51502,57989,52690,PRETRIAL,Gray,Dwight,NULL,Male,African-American,06/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +51502,57989,52690,PRETRIAL,Gray,Dwight,NULL,Male,African-American,06/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +51502,57989,52690,PRETRIAL,Gray,Dwight,NULL,Male,African-American,06/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51508,57996,52697,Probation,Waymire,Michael,NULL,Male,Caucasian,06/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +51508,57996,52697,Probation,Waymire,Michael,NULL,Male,Caucasian,06/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +51508,57996,52697,Probation,Waymire,Michael,NULL,Male,Caucasian,06/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51498,57982,52684,PRETRIAL,Downing,Betty,NULL,Male,African-American,04/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +51498,57982,52684,PRETRIAL,Downing,Betty,NULL,Male,African-American,04/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +51498,57982,52684,PRETRIAL,Downing,Betty,NULL,Male,African-American,04/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51510,58017,52717,PRETRIAL,Hampton,Alfred,NULL,Male,Caucasian,11/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +51510,58017,52717,PRETRIAL,Hampton,Alfred,NULL,Male,Caucasian,11/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +51510,58017,52717,PRETRIAL,Hampton,Alfred,NULL,Male,Caucasian,11/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +35006,58031,52730,Probation,NIXON,ERIC,T,Male,African-American,09/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +35006,58031,52730,Probation,NIXON,ERIC,T,Male,African-American,09/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +35006,58031,52730,Probation,NIXON,ERIC,T,Male,African-American,09/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,40,10,High,New,1,0 +51506,57994,52695,PRETRIAL,fontaine,ursula,NULL,Female,Caucasian,04/05/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/24/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +51506,57994,52695,PRETRIAL,fontaine,ursula,NULL,Female,Caucasian,04/05/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +51506,57994,52695,PRETRIAL,fontaine,ursula,NULL,Female,Caucasian,04/05/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51520,58012,52712,PRETRIAL,MORGAN,ROSANNE,NULL,Female,Caucasian,03/25/68,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.89,2,Low,New,1,0 +51520,58012,52712,PRETRIAL,MORGAN,ROSANNE,NULL,Female,Caucasian,03/25/68,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +51520,58012,52712,PRETRIAL,MORGAN,ROSANNE,NULL,Female,Caucasian,03/25/68,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,8,High,New,1,0 +51526,58015,52715,PRETRIAL,Bickis,Thomas,NULL,Male,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +51526,58015,52715,PRETRIAL,Bickis,Thomas,NULL,Male,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +51526,58015,52715,PRETRIAL,Bickis,Thomas,NULL,Male,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51543,58033,52732,Probation,bohler,alexus,NULL,Female,African-American,07/09/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +51543,58033,52732,Probation,bohler,alexus,NULL,Female,African-American,07/09/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.67,10,High,New,1,0 +51543,58033,52732,Probation,bohler,alexus,NULL,Female,African-American,07/09/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51521,58007,52708,PRETRIAL,Burgos,David,Anthony,Male,Caucasian,06/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +51521,58007,52708,PRETRIAL,Burgos,David,Anthony,Male,Caucasian,06/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +51521,58007,52708,PRETRIAL,Burgos,David,Anthony,Male,Caucasian,06/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +23847,57986,50659,PRETRIAL,reynolds,jeffery,NULL,Male,African-American,10/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,Copy,1,0 +23847,57986,50659,PRETRIAL,reynolds,jeffery,NULL,Male,African-American,10/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,Copy,1,0 +23847,57986,50659,PRETRIAL,reynolds,jeffery,NULL,Male,African-American,10/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +18509,58020,43238,Probation,medley,andrew,NULL,Male,African-American,01/03/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,4,High,7,Risk of Violence,0.11,10,High,Copy,1,0 +18509,58020,43238,Probation,medley,andrew,NULL,Male,African-American,01/03/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,Copy,1,0 +18509,58020,43238,Probation,medley,andrew,NULL,Male,African-American,01/03/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +51512,57999,52700,PRETRIAL,Torres,Entique,NULL,Male,Hispanic,12/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +51512,57999,52700,PRETRIAL,Torres,Entique,NULL,Male,Hispanic,12/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +51512,57999,52700,PRETRIAL,Torres,Entique,NULL,Male,Hispanic,12/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51538,58028,52727,Probation,nelson,jarrett,NULL,Male,Caucasian,01/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +51538,58028,52727,Probation,nelson,jarrett,NULL,Male,Caucasian,01/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +51538,58028,52727,Probation,nelson,jarrett,NULL,Male,Caucasian,01/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51504,57991,52692,PRETRIAL,Cortez,Michael,Angelo,Male,Caucasian,04/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +51504,57991,52692,PRETRIAL,Cortez,Michael,Angelo,Male,Caucasian,04/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +51504,57991,52692,PRETRIAL,Cortez,Michael,Angelo,Male,Caucasian,04/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51501,57988,52689,PRETRIAL,Jones,Johnny,NULL,Male,African-Am,10/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +51501,57988,52689,PRETRIAL,Jones,Johnny,NULL,Male,African-Am,10/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +51501,57988,52689,PRETRIAL,Jones,Johnny,NULL,Male,African-Am,10/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51522,58009,52710,PRETRIAL,KISER,ROOSEVELT,JEVON,Male,African-American,05/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +51522,58009,52710,PRETRIAL,KISER,ROOSEVELT,JEVON,Male,African-American,05/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +51522,58009,52710,PRETRIAL,KISER,ROOSEVELT,JEVON,Male,African-American,05/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51524,58013,52713,Probation,Thompson,Duwon,NULL,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +51524,58013,52713,Probation,Thompson,Duwon,NULL,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +51524,58013,52713,Probation,Thompson,Duwon,NULL,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51528,58018,52718,PRETRIAL,Merico,Daniel,Ray,Male,Caucasian,01/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +51528,58018,52718,PRETRIAL,Merico,Daniel,Ray,Male,Caucasian,01/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +51528,58018,52718,PRETRIAL,Merico,Daniel,Ray,Male,Caucasian,01/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +27433,57992,52693,PRETRIAL,greensdale,atley,NULL,Male,African-American,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +27433,57992,52693,PRETRIAL,greensdale,atley,NULL,Male,African-American,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +27433,57992,52693,PRETRIAL,greensdale,atley,NULL,Male,African-American,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51499,57983,52685,PRETRIAL,Carter,Willie,NULL,Male,African-American,04/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +51499,57983,52685,PRETRIAL,Carter,Willie,NULL,Male,African-American,04/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +51499,57983,52685,PRETRIAL,Carter,Willie,NULL,Male,African-American,04/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51509,57997,52698,Probation,Bibliowicz,Jason,Adam,Male,Caucasian,11/07/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/24/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +51509,57997,52698,Probation,Bibliowicz,Jason,Adam,Male,Caucasian,11/07/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/24/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +51509,57997,52698,Probation,Bibliowicz,Jason,Adam,Male,Caucasian,11/07/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51540,58030,52729,Probation,Espinosa,Jonathan,NULL,Male,Hispanic,08/18/87,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,1/24/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +51540,58030,52729,Probation,Espinosa,Jonathan,NULL,Male,Hispanic,08/18/87,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,1/24/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +51540,58030,52729,Probation,Espinosa,Jonathan,NULL,Male,Hispanic,08/18/87,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51544,58034,52733,PRETRIAL,Turner-Davis,Reneca,NULL,Female,African-American,09/30/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +51544,58034,52733,PRETRIAL,Turner-Davis,Reneca,NULL,Female,African-American,09/30/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +51544,58034,52733,PRETRIAL,Turner-Davis,Reneca,NULL,Female,African-American,09/30/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51542,58032,52731,Probation,Pilorge,Elizabeth,NULL,Female,African-American,06/24/59,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/24/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +51542,58032,52731,Probation,Pilorge,Elizabeth,NULL,Female,African-American,06/24/59,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +51542,58032,52731,Probation,Pilorge,Elizabeth,NULL,Female,African-American,06/24/59,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51507,57995,52696,PRETRIAL,Newton,Leonard,NULL,Male,African-American,09/05/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/24/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +51507,57995,52696,PRETRIAL,Newton,Leonard,NULL,Male,African-American,09/05/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +51507,57995,52696,PRETRIAL,Newton,Leonard,NULL,Male,African-American,09/05/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51514,58002,52703,Probation,INGALLS,ANDREW,T,Male,Caucasian,04/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +51514,58002,52703,Probation,INGALLS,ANDREW,T,Male,Caucasian,04/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +51514,58002,52703,Probation,INGALLS,ANDREW,T,Male,Caucasian,04/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51516,58004,52705,Probation,Price,Todd,NULL,Male,Caucasian,04/29/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +51516,58004,52705,Probation,Price,Todd,NULL,Male,Caucasian,04/29/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +51516,58004,52705,Probation,Price,Todd,NULL,Male,Caucasian,04/29/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51530,58023,52722,Probation,HOUSTON,ALDRIC,R,Male,African-American,08/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,4,High,7,Risk of Violence,-1.03,8,High,New,1,0 +51530,58023,52722,Probation,HOUSTON,ALDRIC,R,Male,African-American,08/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,4,High,8,Risk of Recidivism,0.41,9,High,New,1,0 +51530,58023,52722,Probation,HOUSTON,ALDRIC,R,Male,African-American,08/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51535,58025,52724,DRRD,VargasMartnez,Raul,Antonio,Male,Hispanic,02/01/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +51535,58025,52724,DRRD,VargasMartnez,Raul,Antonio,Male,Hispanic,02/01/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,6,Medium,New,1,0 +51535,58025,52724,DRRD,VargasMartnez,Raul,Antonio,Male,Hispanic,02/01/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/24/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51580,58074,52771,Probation,Lawson,Patrick,NULL,Male,Caucasian,04/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +51580,58074,52771,Probation,Lawson,Patrick,NULL,Male,Caucasian,04/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,New,1,0 +51580,58074,52771,Probation,Lawson,Patrick,NULL,Male,Caucasian,04/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51574,58067,52764,PRETRIAL,Dameron,Matthew,NULL,Male,Caucasian,07/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +51574,58067,52764,PRETRIAL,Dameron,Matthew,NULL,Male,Caucasian,07/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +51574,58067,52764,PRETRIAL,Dameron,Matthew,NULL,Male,Caucasian,07/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51556,58046,52745,Probation,FARLOW,LARRY,NULL,Male,African-American,06/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +51556,58046,52745,Probation,FARLOW,LARRY,NULL,Male,African-American,06/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +51556,58046,52745,Probation,FARLOW,LARRY,NULL,Male,African-American,06/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51567,58060,52757,Probation,Mandeville,David,NULL,Male,Caucasian,12/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +51567,58060,52757,Probation,Mandeville,David,NULL,Male,Caucasian,12/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +51567,58060,52757,Probation,Mandeville,David,NULL,Male,Caucasian,12/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51558,58048,52747,Probation,Clark,Timia,Jonae,Female,African-American,01/08/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +51558,58048,52747,Probation,Clark,Timia,Jonae,Female,African-American,01/08/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +51558,58048,52747,Probation,Clark,Timia,Jonae,Female,African-American,01/08/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51572,58065,52762,Probation,Ellington,Royrick,NULL,Male,African-American,11/16/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/25/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +51572,58065,52762,Probation,Ellington,Royrick,NULL,Male,African-American,11/16/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +51572,58065,52762,Probation,Ellington,Royrick,NULL,Male,African-American,11/16/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51554,58044,52743,PRETRIAL,Crawford,Laquana,NULL,Female,African-American,03/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,4,High,7,Risk of Violence,-0.48,10,High,New,1,0 +51554,58044,52743,PRETRIAL,Crawford,Laquana,NULL,Female,African-American,03/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,4,High,8,Risk of Recidivism,-0.11,8,High,New,1,0 +51554,58044,52743,PRETRIAL,Crawford,Laquana,NULL,Female,African-American,03/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +28829,58051,51696,PRETRIAL,Stewart,Travis,NULL,Male,African-American,07/23/80,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,4,High,7,Risk of Violence,-1.15,8,High,Copy,1,0 +28829,58051,51696,PRETRIAL,Stewart,Travis,NULL,Male,African-American,07/23/80,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,4,High,8,Risk of Recidivism,0.93,10,High,Copy,1,0 +28829,58051,51696,PRETRIAL,Stewart,Travis,NULL,Male,African-American,07/23/80,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,4,High,18,Risk of Failure to Appear,37,10,High,Copy,1,0 +5689,58069,52766,DRRD,Thompkins,Delton,NULL,Male,African-American,05/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +5689,58069,52766,DRRD,Thompkins,Delton,NULL,Male,African-American,05/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +5689,58069,52766,DRRD,Thompkins,Delton,NULL,Male,African-American,05/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51549,58039,52738,PRETRIAL,Sottile,Russell,NULL,Male,Caucasian,01/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/25/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +51549,58039,52738,PRETRIAL,Sottile,Russell,NULL,Male,Caucasian,01/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +51549,58039,52738,PRETRIAL,Sottile,Russell,NULL,Male,Caucasian,01/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51564,58057,52754,Probation,Seminara,Thomas,NULL,Male,Caucasian,07/01/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +51564,58057,52754,Probation,Seminara,Thomas,NULL,Male,Caucasian,07/01/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +51564,58057,52754,Probation,Seminara,Thomas,NULL,Male,Caucasian,07/01/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51546,58036,52735,PRETRIAL,Tanner,Marcus,NULL,Male,Caucasian,11/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +51546,58036,52735,PRETRIAL,Tanner,Marcus,NULL,Male,Caucasian,11/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +51546,58036,52735,PRETRIAL,Tanner,Marcus,NULL,Male,Caucasian,11/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51576,58070,52767,Probation,RAMPERSAD,KENTH,NULL,Male,Other,10/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +51576,58070,52767,Probation,RAMPERSAD,KENTH,NULL,Male,Other,10/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +51576,58070,52767,Probation,RAMPERSAD,KENTH,NULL,Male,Other,10/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51559,58049,52748,PRETRIAL,morla,joshua,NULL,Male,Caucasian,06/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +51559,58049,52748,PRETRIAL,morla,joshua,NULL,Male,Caucasian,06/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +51559,58049,52748,PRETRIAL,morla,joshua,NULL,Male,Caucasian,06/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51571,58064,52761,Probation,Shell,Brett,NULL,Male,Caucasian,07/14/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/25/13 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +51571,58064,52761,Probation,Shell,Brett,NULL,Male,Caucasian,07/14/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +51571,58064,52761,Probation,Shell,Brett,NULL,Male,Caucasian,07/14/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/25/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51561,58054,52751,PRETRIAL,Weisberger,Daniel,NULL,Male,Caucasian,07/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +51561,58054,52751,PRETRIAL,Weisberger,Daniel,NULL,Male,Caucasian,07/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +51561,58054,52751,PRETRIAL,Weisberger,Daniel,NULL,Male,Caucasian,07/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51551,58041,52740,PRETRIAL,Nettleford,Steven,NULL,Male,African-American,02/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +51551,58041,52740,PRETRIAL,Nettleford,Steven,NULL,Male,African-American,02/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +51551,58041,52740,PRETRIAL,Nettleford,Steven,NULL,Male,African-American,02/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51581,58075,52772,Probation,malloy,grace,NULL,Female,Caucasian,07/19/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/25/13 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +51581,58075,52772,Probation,malloy,grace,NULL,Female,Caucasian,07/19/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/25/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +51581,58075,52772,Probation,malloy,grace,NULL,Female,Caucasian,07/19/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51569,58062,52759,Probation,ALVAREZ,CARLOS,A,Male,Hispanic,09/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +51569,58062,52759,Probation,ALVAREZ,CARLOS,A,Male,Hispanic,09/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +51569,58062,52759,Probation,ALVAREZ,CARLOS,A,Male,Hispanic,09/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51550,58040,52739,PRETRIAL,CoferRivera,Karl,Andrew,Male,Caucasian,03/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +51550,58040,52739,PRETRIAL,CoferRivera,Karl,Andrew,Male,Caucasian,03/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +51550,58040,52739,PRETRIAL,CoferRivera,Karl,Andrew,Male,Caucasian,03/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51566,58059,52756,Probation,MILLER,PARRISH,D,Male,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +51566,58059,52756,Probation,MILLER,PARRISH,D,Male,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +51566,58059,52756,Probation,MILLER,PARRISH,D,Male,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51548,58038,52737,PRETRIAL,Cruz,Lee,NULL,Male,Caucasian,10/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +51548,58038,52737,PRETRIAL,Cruz,Lee,NULL,Male,Caucasian,10/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +51548,58038,52737,PRETRIAL,Cruz,Lee,NULL,Male,Caucasian,10/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51568,58061,52758,PRETRIAL,KILGORE,WILLIAM,NULL,Male,African-American,07/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +51568,58061,52758,PRETRIAL,KILGORE,WILLIAM,NULL,Male,African-American,07/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +51568,58061,52758,PRETRIAL,KILGORE,WILLIAM,NULL,Male,African-American,07/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51575,58068,52765,Probation,HOOKS,LAMPOUS,NULL,Male,African-American,03/02/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/25/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +51575,58068,52765,Probation,HOOKS,LAMPOUS,NULL,Male,African-American,03/02/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/25/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +51575,58068,52765,Probation,HOOKS,LAMPOUS,NULL,Male,African-American,03/02/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51557,58047,52746,Probation,Black,Ashley,Shantel,Female,African-American,12/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +51557,58047,52746,Probation,Black,Ashley,Shantel,Female,African-American,12/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +51557,58047,52746,Probation,Black,Ashley,Shantel,Female,African-American,12/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51563,58056,52753,PRETRIAL,Jackson,Linda,M,Female,African-American,08/30/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +51563,58056,52753,PRETRIAL,Jackson,Linda,M,Female,African-American,08/30/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +51563,58056,52753,PRETRIAL,Jackson,Linda,M,Female,African-American,08/30/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51579,58073,52770,Probation,Alvarez,Gerald,Alberet,Male,Hispanic,09/16/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/25/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +51579,58073,52770,Probation,Alvarez,Gerald,Alberet,Male,Hispanic,09/16/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +51579,58073,52770,Probation,Alvarez,Gerald,Alberet,Male,Hispanic,09/16/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51553,58043,52742,PRETRIAL,Rowe,Florizel,NULL,Male,African-American,12/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +51553,58043,52742,PRETRIAL,Rowe,Florizel,NULL,Male,African-American,12/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +51553,58043,52742,PRETRIAL,Rowe,Florizel,NULL,Male,African-American,12/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51560,58052,52750,PRETRIAL,pierre,majorie,NULL,Female,African-American,10/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/25/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +51560,58052,52750,PRETRIAL,pierre,majorie,NULL,Female,African-American,10/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +51560,58052,52750,PRETRIAL,pierre,majorie,NULL,Female,African-American,10/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/25/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51583,58077,52774,PRETRIAL,Oro,Juan,NULL,Male,Hispanic,03/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +51583,58077,52774,PRETRIAL,Oro,Juan,NULL,Male,Hispanic,03/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +51583,58077,52774,PRETRIAL,Oro,Juan,NULL,Male,Hispanic,03/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51545,58035,52734,PRETRIAL,Williams,Tawana,Yvette,Female,African-American,07/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +51545,58035,52734,PRETRIAL,Williams,Tawana,Yvette,Female,African-American,07/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +51545,58035,52734,PRETRIAL,Williams,Tawana,Yvette,Female,African-American,07/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51570,58063,52760,Probation,Ingram,Eddie,NULL,Male,African-American,01/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.22,4,Low,New,1,0 +51570,58063,52760,Probation,Ingram,Eddie,NULL,Male,African-American,01/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +51570,58063,52760,Probation,Ingram,Eddie,NULL,Male,African-American,01/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51552,58042,52741,PRETRIAL,Gopher,Shannon,NULL,Male,Caucasian,08/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +51552,58042,52741,PRETRIAL,Gopher,Shannon,NULL,Male,Caucasian,08/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +51552,58042,52741,PRETRIAL,Gopher,Shannon,NULL,Male,Caucasian,08/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51562,58055,52752,Probation,Lee,Kimberly,E,Female,African-American,09/06/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +51562,58055,52752,Probation,Lee,Kimberly,E,Female,African-American,09/06/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +51562,58055,52752,Probation,Lee,Kimberly,E,Female,African-American,09/06/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51547,58037,52736,PRETRIAL,Sterling,Teron,NULL,Male,Other,10/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +51547,58037,52736,PRETRIAL,Sterling,Teron,NULL,Male,Other,10/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +51547,58037,52736,PRETRIAL,Sterling,Teron,NULL,Male,Other,10/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +45225,58076,52773,PRETRIAL,Smalls,Lavonta,NULL,Male,African-American,11/08/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,4,High,7,Risk of Violence,-0.62,10,High,New,1,0 +45225,58076,52773,PRETRIAL,Smalls,Lavonta,NULL,Male,African-American,11/08/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,4,High,8,Risk of Recidivism,0.38,9,High,New,1,0 +45225,58076,52773,PRETRIAL,Smalls,Lavonta,NULL,Male,African-American,11/08/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51573,58066,52763,PRETRIAL,Ramos,Ismael,NULL,Male,Caucasian,12/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/25/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +51573,58066,52763,PRETRIAL,Ramos,Ismael,NULL,Male,Caucasian,12/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +51573,58066,52763,PRETRIAL,Ramos,Ismael,NULL,Male,Caucasian,12/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51565,58058,52755,Probation,WALTER,JILL,NULL,Female,African-American,02/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +51565,58058,52755,Probation,WALTER,JILL,NULL,Female,African-American,02/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +51565,58058,52755,Probation,WALTER,JILL,NULL,Female,African-American,02/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51591,58092,52786,PRETRIAL,Smith,Nema,NULL,Male,African-American,08/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +51591,58092,52786,PRETRIAL,Smith,Nema,NULL,Male,African-American,08/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +51591,58092,52786,PRETRIAL,Smith,Nema,NULL,Male,African-American,08/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +38881,58079,52776,PRETRIAL,SMITH,JOVAUGH,NULL,Male,African-American,12/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +38881,58079,52776,PRETRIAL,SMITH,JOVAUGH,NULL,Male,African-American,12/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +38881,58079,52776,PRETRIAL,SMITH,JOVAUGH,NULL,Male,African-American,12/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +21268,58084,52779,PRETRIAL,Rahm,Jonathan,NULL,Male,Caucasian,02/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +21268,58084,52779,PRETRIAL,Rahm,Jonathan,NULL,Male,Caucasian,02/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +21268,58084,52779,PRETRIAL,Rahm,Jonathan,NULL,Male,Caucasian,02/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51587,58087,52781,PRETRIAL,Knight,Emmanuel,Preston,Male,African-American,09/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +51587,58087,52781,PRETRIAL,Knight,Emmanuel,Preston,Male,African-American,09/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +51587,58087,52781,PRETRIAL,Knight,Emmanuel,Preston,Male,African-American,09/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51593,58094,52788,PRETRIAL,WILLIAMS,MICHAEL,NULL,Male,African-American,01/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +51593,58094,52788,PRETRIAL,WILLIAMS,MICHAEL,NULL,Male,African-American,01/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +51593,58094,52788,PRETRIAL,WILLIAMS,MICHAEL,NULL,Male,African-American,01/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51588,58089,52783,PRETRIAL,Ricatti,Denny,S,Female,Caucasian,02/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +51588,58089,52783,PRETRIAL,Ricatti,Denny,S,Female,Caucasian,02/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +51588,58089,52783,PRETRIAL,Ricatti,Denny,S,Female,Caucasian,02/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51584,58082,52777,PRETRIAL,GRENON,CLAUDE,NULL,Male,Caucasian,02/18/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +51584,58082,52777,PRETRIAL,GRENON,CLAUDE,NULL,Male,Caucasian,02/18/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,8,Risk of Recidivism,-2.68,1,Low,New,1,0 +51584,58082,52777,PRETRIAL,GRENON,CLAUDE,NULL,Male,Caucasian,02/18/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51595,58096,52790,PRETRIAL,Penn,Roderick,NULL,Male,African-American,10/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +51595,58096,52790,PRETRIAL,Penn,Roderick,NULL,Male,African-American,10/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +51595,58096,52790,PRETRIAL,Penn,Roderick,NULL,Male,African-American,10/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +42656,58080,42508,PRETRIAL,Quimbley,Bradley,NULL,Male,African-American,05/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,Copy,1,0 +42656,58080,42508,PRETRIAL,Quimbley,Bradley,NULL,Male,African-American,05/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,Copy,1,0 +42656,58080,42508,PRETRIAL,Quimbley,Bradley,NULL,Male,African-American,05/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +51585,58083,52778,PRETRIAL,Montalvo,Mark,NULL,Male,Caucasian,04/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +51585,58083,52778,PRETRIAL,Montalvo,Mark,NULL,Male,Caucasian,04/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +51585,58083,52778,PRETRIAL,Montalvo,Mark,NULL,Male,Caucasian,04/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +42702,58088,52782,PRETRIAL,Wilson,Travis,NULL,Male,African-American,07/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +42702,58088,52782,PRETRIAL,Wilson,Travis,NULL,Male,African-American,07/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,4,High,8,Risk of Recidivism,0.43,9,High,New,1,0 +42702,58088,52782,PRETRIAL,Wilson,Travis,NULL,Male,African-American,07/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +31233,58078,52775,PRETRIAL,Monos,George,NULL,Male,Hispanic,10/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/26/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +31233,58078,52775,PRETRIAL,Monos,George,NULL,Male,Hispanic,10/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +31233,58078,52775,PRETRIAL,Monos,George,NULL,Male,Hispanic,10/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/26/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51586,58085,52780,PRETRIAL,Garcia,Hugo,NULL,Male,Hispanic,10/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +51586,58085,52780,PRETRIAL,Garcia,Hugo,NULL,Male,Hispanic,10/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +51586,58085,52780,PRETRIAL,Garcia,Hugo,NULL,Male,Hispanic,10/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51592,58093,52787,PRETRIAL,Dossantos,Tiago,NULL,Male,Hispanic,01/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +51592,58093,52787,PRETRIAL,Dossantos,Tiago,NULL,Male,Hispanic,01/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +51592,58093,52787,PRETRIAL,Dossantos,Tiago,NULL,Male,Hispanic,01/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51590,58091,52785,PRETRIAL,Dawson,Linda,NULL,Female,Caucasian,01/19/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/26/13 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +51590,58091,52785,PRETRIAL,Dawson,Linda,NULL,Female,Caucasian,01/19/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/26/13 0:00,1,Low,8,Risk of Recidivism,-2.63,1,Low,New,1,0 +51590,58091,52785,PRETRIAL,Dawson,Linda,NULL,Female,Caucasian,01/19/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/26/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51589,58090,52784,PRETRIAL,Kirksey,Jacoby,NULL,Male,African-American,02/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +51589,58090,52784,PRETRIAL,Kirksey,Jacoby,NULL,Male,African-American,02/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +51589,58090,52784,PRETRIAL,Kirksey,Jacoby,NULL,Male,African-American,02/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +6953,58086,6544,PRETRIAL,Chavez,Jose,S,Male,Caucasian,11/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/26/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,Copy,1,0 +6953,58086,6544,PRETRIAL,Chavez,Jose,S,Male,Caucasian,11/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/26/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,Copy,1,0 +6953,58086,6544,PRETRIAL,Chavez,Jose,S,Male,Caucasian,11/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +2247,58081,1967,PRETRIAL,MONTIEL,OLAYO,A,Male,Caucasian,03/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,Copy,1,0 +2247,58081,1967,PRETRIAL,MONTIEL,OLAYO,A,Male,Caucasian,03/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,Copy,1,0 +2247,58081,1967,PRETRIAL,MONTIEL,OLAYO,A,Male,Caucasian,03/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +51594,58095,52789,PRETRIAL,Wilkerson,Jeramey,NULL,Male,Caucasian,01/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +51594,58095,52789,PRETRIAL,Wilkerson,Jeramey,NULL,Male,Caucasian,01/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +51594,58095,52789,PRETRIAL,Wilkerson,Jeramey,NULL,Male,Caucasian,01/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51601,58102,52796,PRETRIAL,DIXON,KEVON,NULL,Male,African-American,01/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +51601,58102,52796,PRETRIAL,DIXON,KEVON,NULL,Male,African-American,01/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +51601,58102,52796,PRETRIAL,DIXON,KEVON,NULL,Male,African-American,01/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51603,58104,52798,PRETRIAL,JOHNSTON,CHRISTOPHER,MOSES,Male,African-American,03/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +51603,58104,52798,PRETRIAL,JOHNSTON,CHRISTOPHER,MOSES,Male,African-American,03/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +51603,58104,52798,PRETRIAL,JOHNSTON,CHRISTOPHER,MOSES,Male,African-American,03/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +36720,58111,36021,PRETRIAL,Pierre,David,NULL,Male,African-American,01/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,Copy,1,0 +36720,58111,36021,PRETRIAL,Pierre,David,NULL,Male,African-American,01/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,Copy,1,0 +36720,58111,36021,PRETRIAL,Pierre,David,NULL,Male,African-American,01/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +51605,58107,52800,PRETRIAL,HICKS,JASON,LEMORRIS,Male,African-American,10/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +51605,58107,52800,PRETRIAL,HICKS,JASON,LEMORRIS,Male,African-American,10/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +51605,58107,52800,PRETRIAL,HICKS,JASON,LEMORRIS,Male,African-American,10/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51615,58116,52808,PRETRIAL,Caldwell,Alan-Michael,NULL,Male,African-American,05/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +51615,58116,52808,PRETRIAL,Caldwell,Alan-Michael,NULL,Male,African-American,05/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +51615,58116,52808,PRETRIAL,Caldwell,Alan-Michael,NULL,Male,African-American,05/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51604,58106,52799,PRETRIAL,FEMIA,LAUREL,NULL,Female,Caucasian,10/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +51604,58106,52799,PRETRIAL,FEMIA,LAUREL,NULL,Female,Caucasian,10/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +51604,58106,52799,PRETRIAL,FEMIA,LAUREL,NULL,Female,Caucasian,10/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51597,58099,52793,PRETRIAL,PHILLIPS,ANTHONY,W,Male,Caucasian,07/31/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +51597,58099,52793,PRETRIAL,PHILLIPS,ANTHONY,W,Male,Caucasian,07/31/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +51597,58099,52793,PRETRIAL,PHILLIPS,ANTHONY,W,Male,Caucasian,07/31/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51613,58114,52806,PRETRIAL,Herring,Thomas,NULL,Male,Caucasian,04/23/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +51613,58114,52806,PRETRIAL,Herring,Thomas,NULL,Male,Caucasian,04/23/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +51613,58114,52806,PRETRIAL,Herring,Thomas,NULL,Male,Caucasian,04/23/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +49107,58109,52802,PRETRIAL,Bent,Jason,NULL,Male,African-American,01/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +49107,58109,52802,PRETRIAL,Bent,Jason,NULL,Male,African-American,01/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +49107,58109,52802,PRETRIAL,Bent,Jason,NULL,Male,African-American,01/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51600,58101,52795,PRETRIAL,SIMON,ZACHARY,NULL,Male,African-American,05/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +51600,58101,52795,PRETRIAL,SIMON,ZACHARY,NULL,Male,African-American,05/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +51600,58101,52795,PRETRIAL,SIMON,ZACHARY,NULL,Male,African-American,05/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51602,58103,52797,PRETRIAL,TAYLOR,ROBERT,VERNON,Male,Caucasian,05/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +51602,58103,52797,PRETRIAL,TAYLOR,ROBERT,VERNON,Male,Caucasian,05/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +51602,58103,52797,PRETRIAL,TAYLOR,ROBERT,VERNON,Male,Caucasian,05/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51610,58110,52803,PRETRIAL,HOLSTON,CORNELIUS,LAKWAN,Male,African-American,07/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.94,9,High,New,1,0 +51610,58110,52803,PRETRIAL,HOLSTON,CORNELIUS,LAKWAN,Male,African-American,07/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +51610,58110,52803,PRETRIAL,HOLSTON,CORNELIUS,LAKWAN,Male,African-American,07/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51611,58112,52804,PRETRIAL,BRADLEY,JAMES,L,Male,African-American,06/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +51611,58112,52804,PRETRIAL,BRADLEY,JAMES,L,Male,African-American,06/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +51611,58112,52804,PRETRIAL,BRADLEY,JAMES,L,Male,African-American,06/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51598,58098,52792,PRETRIAL,Humes,Jacob,NULL,Male,African-American,01/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/27/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +51598,58098,52792,PRETRIAL,Humes,Jacob,NULL,Male,African-American,01/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/27/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +51598,58098,52792,PRETRIAL,Humes,Jacob,NULL,Male,African-American,01/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51614,58115,52807,PRETRIAL,JAMISON,WILLIAM,NULL,Male,African-American,10/07/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/27/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +51614,58115,52807,PRETRIAL,JAMISON,WILLIAM,NULL,Male,African-American,10/07/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/27/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +51614,58115,52807,PRETRIAL,JAMISON,WILLIAM,NULL,Male,African-American,10/07/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +27056,58105,26168,DRRD,frazier,raymon,NULL,Male,African-American,12/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,Copy,1,0 +27056,58105,26168,DRRD,frazier,raymon,NULL,Male,African-American,12/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,Copy,1,0 +27056,58105,26168,DRRD,frazier,raymon,NULL,Male,African-American,12/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,7,Medium,Copy,1,0 +51596,58097,52791,PRETRIAL,Jagpal,Sunil,NULL,Female,African-American,01/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,2,Medium,7,Risk of Violence,-2.86,2,Low,New,1,0 +51596,58097,52791,PRETRIAL,Jagpal,Sunil,NULL,Female,African-American,01/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +51596,58097,52791,PRETRIAL,Jagpal,Sunil,NULL,Female,African-American,01/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51612,58113,52805,PRETRIAL,MOORE,ZACHARY,NULL,Male,Caucasian,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +51612,58113,52805,PRETRIAL,MOORE,ZACHARY,NULL,Male,Caucasian,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +51612,58113,52805,PRETRIAL,MOORE,ZACHARY,NULL,Male,Caucasian,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51606,58108,52801,PRETRIAL,CASCO,ADOLFO,GASPER,Male,Caucasian,01/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/27/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +51606,58108,52801,PRETRIAL,CASCO,ADOLFO,GASPER,Male,Caucasian,01/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/27/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +51606,58108,52801,PRETRIAL,CASCO,ADOLFO,GASPER,Male,Caucasian,01/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51599,58100,52794,PRETRIAL,VELASQUES,LUIS,NULL,Male,Caucasian,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +51599,58100,52794,PRETRIAL,VELASQUES,LUIS,NULL,Male,Caucasian,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +51599,58100,52794,PRETRIAL,VELASQUES,LUIS,NULL,Male,Caucasian,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51637,58149,52835,Probation,Lugo,Josue,NULL,Male,Hispanic,04/04/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +51637,58149,52835,Probation,Lugo,Josue,NULL,Male,Hispanic,04/04/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +51637,58149,52835,Probation,Lugo,Josue,NULL,Male,Hispanic,04/04/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51638,58150,52836,Probation,FRANCIS,JAKETHA,NULL,Female,African-American,03/10/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +51638,58150,52836,Probation,FRANCIS,JAKETHA,NULL,Female,African-American,03/10/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +51638,58150,52836,Probation,FRANCIS,JAKETHA,NULL,Female,African-American,03/10/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51619,58121,52813,PRETRIAL,SALTER,CARRIE,NULL,Female,African-American,10/16/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,1/28/13 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +51619,58121,52813,PRETRIAL,SALTER,CARRIE,NULL,Female,African-American,10/16/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,1/28/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +51619,58121,52813,PRETRIAL,SALTER,CARRIE,NULL,Female,African-American,10/16/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +25072,58128,52819,PRETRIAL,TURNER,JANOI,ANDRE,Male,African-American,08/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +25072,58128,52819,PRETRIAL,TURNER,JANOI,ANDRE,Male,African-American,08/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +25072,58128,52819,PRETRIAL,TURNER,JANOI,ANDRE,Male,African-American,08/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51656,58171,52857,Probation,dustin,richardson,NULL,Male,Caucasian,12/23/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +51656,58171,52857,Probation,dustin,richardson,NULL,Male,Caucasian,12/23/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,4,High,8,Risk of Recidivism,1.14,10,High,New,1,0 +51656,58171,52857,Probation,dustin,richardson,NULL,Male,Caucasian,12/23/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +51644,58157,52843,PRETRIAL,arias,mauricio,NULL,Male,Hispanic,10/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +51644,58157,52843,PRETRIAL,arias,mauricio,NULL,Male,Hispanic,10/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +51644,58157,52843,PRETRIAL,arias,mauricio,NULL,Male,Hispanic,10/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51625,58129,52820,PRETRIAL,MUNOZ,DAVID,A,Male,Caucasian,10/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/28/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +51625,58129,52820,PRETRIAL,MUNOZ,DAVID,A,Male,Caucasian,10/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/28/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +51625,58129,52820,PRETRIAL,MUNOZ,DAVID,A,Male,Caucasian,10/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51630,58136,52826,Probation,Perez,Alejandro,NULL,Male,Hispanic,07/17/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +51630,58136,52826,Probation,Perez,Alejandro,NULL,Male,Hispanic,07/17/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +51630,58136,52826,Probation,Perez,Alejandro,NULL,Male,Hispanic,07/17/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51616,58118,52810,PRETRIAL,Hamilton,Andre,NULL,Male,African-American,09/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +51616,58118,52810,PRETRIAL,Hamilton,Andre,NULL,Male,African-American,09/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +51616,58118,52810,PRETRIAL,Hamilton,Andre,NULL,Male,African-American,09/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51639,58152,52838,Probation,Herrington,Levert,NULL,Male,African-American,01/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,2,Medium,7,Risk of Violence,-2.96,1,Low,New,1,0 +51639,58152,52838,Probation,Herrington,Levert,NULL,Male,African-American,01/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +51639,58152,52838,Probation,Herrington,Levert,NULL,Male,African-American,01/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +41024,57075,51870,PRETRIAL,AMATO,BRANDON,BARCLAY,Male,Caucasian,08/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +41024,57075,51870,PRETRIAL,AMATO,BRANDON,BARCLAY,Male,Caucasian,08/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +41024,57075,51870,PRETRIAL,AMATO,BRANDON,BARCLAY,Male,Caucasian,08/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +13589,58139,52829,PRETRIAL,Madge,Geoffrey,NULL,Male,Caucasian,04/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +13589,58139,52829,PRETRIAL,Madge,Geoffrey,NULL,Male,Caucasian,04/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.84,10,High,New,1,0 +13589,58139,52829,PRETRIAL,Madge,Geoffrey,NULL,Male,Caucasian,04/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +50057,58134,51005,Probation,ramos,steven,NULL,Male,Caucasian,09/08/76,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,1/28/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +50057,58134,51005,Probation,ramos,steven,NULL,Male,Caucasian,09/08/76,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,1/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +50057,58134,51005,Probation,ramos,steven,NULL,Male,Caucasian,09/08/76,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,1/28/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +40315,58147,39906,PRETRIAL,PIRKLE,WILLIAM,NULL,Male,Caucasian,10/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,4,High,7,Risk of Violence,-0.43,10,High,Copy,1,0 +40315,58147,39906,PRETRIAL,PIRKLE,WILLIAM,NULL,Male,Caucasian,10/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,4,High,8,Risk of Recidivism,0.55,9,High,Copy,1,0 +40315,58147,39906,PRETRIAL,PIRKLE,WILLIAM,NULL,Male,Caucasian,10/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +51623,58126,52817,PRETRIAL,GALLAWAY,FREDERICK,NULL,Male,African-American,09/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +51623,58126,52817,PRETRIAL,GALLAWAY,FREDERICK,NULL,Male,African-American,09/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +51623,58126,52817,PRETRIAL,GALLAWAY,FREDERICK,NULL,Male,African-American,09/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51634,58144,52832,PRETRIAL,Moralesherrera,Edwin,NULL,Male,Hispanic,03/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/28/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,Copy,1,0 +51634,58144,52832,PRETRIAL,Moralesherrera,Edwin,NULL,Male,Hispanic,03/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/28/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,Copy,1,0 +51634,58144,52832,PRETRIAL,Moralesherrera,Edwin,NULL,Male,Hispanic,03/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +51642,58155,52841,PRETRIAL,Perry,Lauren,S.,Female,Caucasian,04/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +51642,58155,52841,PRETRIAL,Perry,Lauren,S.,Female,Caucasian,04/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,7,Medium,New,1,0 +51642,58155,52841,PRETRIAL,Perry,Lauren,S.,Female,Caucasian,04/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51628,58133,52824,Probation,Stott,aaron,NULL,Male,Caucasian,07/11/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +51628,58133,52824,Probation,Stott,aaron,NULL,Male,Caucasian,07/11/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.31,10,High,New,1,0 +51628,58133,52824,Probation,Stott,aaron,NULL,Male,Caucasian,07/11/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +51617,58119,52811,PRETRIAL,FALLON,JOSEPH,IVAN,Male,African-American,02/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +51617,58119,52811,PRETRIAL,FALLON,JOSEPH,IVAN,Male,African-American,02/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +51617,58119,52811,PRETRIAL,FALLON,JOSEPH,IVAN,Male,African-American,02/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +41024,58145,51870,PRETRIAL,AMATO,BRANDON,BARCLAY,Male,Caucasian,08/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,Copy,1,0 +41024,58145,51870,PRETRIAL,AMATO,BRANDON,BARCLAY,Male,Caucasian,08/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.71,10,High,Copy,1,0 +41024,58145,51870,PRETRIAL,AMATO,BRANDON,BARCLAY,Male,Caucasian,08/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +51641,58154,52840,PRETRIAL,GOKUN DIAZ PENA,ELENA,NULL,Female,Caucasian,02/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/28/13 0:00,2,Medium,7,Risk of Violence,-2.79,2,Low,New,1,0 +51641,58154,52840,PRETRIAL,GOKUN DIAZ PENA,ELENA,NULL,Female,Caucasian,02/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +51641,58154,52840,PRETRIAL,GOKUN DIAZ PENA,ELENA,NULL,Female,Caucasian,02/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/28/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +4994,58124,4676,PRETRIAL,MCBRIDE,DANIEL,NULL,Male,African-American,01/05/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/28/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,Copy,1,0 +4994,58124,4676,PRETRIAL,MCBRIDE,DANIEL,NULL,Male,African-American,01/05/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,Copy,1,0 +4994,58124,4676,PRETRIAL,MCBRIDE,DANIEL,NULL,Male,African-American,01/05/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/28/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +40315,43650,39906,PRETRIAL,PIRKLE,WILLIAM,NULL,Male,Caucasian,10/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,4,High,7,Risk of Violence,-0.21,10,High,New,1,0 +40315,43650,39906,PRETRIAL,PIRKLE,WILLIAM,NULL,Male,Caucasian,10/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +40315,43650,39906,PRETRIAL,PIRKLE,WILLIAM,NULL,Male,Caucasian,10/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +48640,58117,52809,PRETRIAL,Lewis,Alonzo,NULL,Male,African-American,06/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +48640,58117,52809,PRETRIAL,Lewis,Alonzo,NULL,Male,African-American,06/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +48640,58117,52809,PRETRIAL,Lewis,Alonzo,NULL,Male,African-American,06/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +9633,58131,52822,PRETRIAL,mccray,marcus,NULL,Male,African-American,07/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +9633,58131,52822,PRETRIAL,mccray,marcus,NULL,Male,African-American,07/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +9633,58131,52822,PRETRIAL,mccray,marcus,NULL,Male,African-American,07/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51632,58140,52830,Probation,Bachan,Jereme,NULL,Male,Other,10/20/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +51632,58140,52830,Probation,Bachan,Jereme,NULL,Male,Other,10/20/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +51632,58140,52830,Probation,Bachan,Jereme,NULL,Male,Other,10/20/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51646,58159,52845,Probation,Pierre,Ronald,NULL,Male,African-American,02/22/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +51646,58159,52845,Probation,Pierre,Ronald,NULL,Male,African-American,02/22/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +51646,58159,52845,Probation,Pierre,Ronald,NULL,Male,African-American,02/22/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +45531,58138,52828,PRETRIAL,Ruiz,Raymond,NULL,Male,Caucasian,12/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,New,1,0 +45531,58138,52828,PRETRIAL,Ruiz,Raymond,NULL,Male,Caucasian,12/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +45531,58138,52828,PRETRIAL,Ruiz,Raymond,NULL,Male,Caucasian,12/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51626,58130,52821,PRETRIAL,GARDNER,MICHAEL,ROBERT,Male,Caucasian,04/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +51626,58130,52821,PRETRIAL,GARDNER,MICHAEL,ROBERT,Male,Caucasian,04/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +51626,58130,52821,PRETRIAL,GARDNER,MICHAEL,ROBERT,Male,Caucasian,04/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51636,58148,52834,PRETRIAL,Cureton,Jasmine,Christine,Female,African-American,08/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +51636,58148,52834,PRETRIAL,Cureton,Jasmine,Christine,Female,African-American,08/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +51636,58148,52834,PRETRIAL,Cureton,Jasmine,Christine,Female,African-American,08/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +20568,58151,52837,DRRD,Ferry,Brad,Richard,Male,Caucasian,06/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,2,Medium,7,Risk of Violence,-1.51,6,Medium,New,1,0 +20568,58151,52837,DRRD,Ferry,Brad,Richard,Male,Caucasian,06/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +20568,58151,52837,DRRD,Ferry,Brad,Richard,Male,Caucasian,06/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51643,58156,52842,Probation,PETERSON,LEONARD,J,Male,Caucasian,09/11/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +51643,58156,52842,Probation,PETERSON,LEONARD,J,Male,Caucasian,09/11/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +51643,58156,52842,Probation,PETERSON,LEONARD,J,Male,Caucasian,09/11/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51629,58135,52825,Probation,Fischer,Mike,NULL,Male,Hispanic,07/31/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/28/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +51629,58135,52825,Probation,Fischer,Mike,NULL,Male,Hispanic,07/31/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/28/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +51629,58135,52825,Probation,Fischer,Mike,NULL,Male,Hispanic,07/31/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51624,58127,52818,PRETRIAL,Marra,Carlo,NULL,Male,Caucasian,04/20/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +51624,58127,52818,PRETRIAL,Marra,Carlo,NULL,Male,Caucasian,04/20/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +51624,58127,52818,PRETRIAL,Marra,Carlo,NULL,Male,Caucasian,04/20/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51631,58137,52827,Probation,FIGUEROA,ROSALY,NULL,Female,Hispanic,03/23/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +51631,58137,52827,Probation,FIGUEROA,ROSALY,NULL,Female,Hispanic,03/23/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +51631,58137,52827,Probation,FIGUEROA,ROSALY,NULL,Female,Hispanic,03/23/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +51633,58141,52831,PRETRIAL,PALMER,JANICE,NULL,Female,Caucasian,04/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +51633,58141,52831,PRETRIAL,PALMER,JANICE,NULL,Female,Caucasian,04/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +51633,58141,52831,PRETRIAL,PALMER,JANICE,NULL,Female,Caucasian,04/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51645,58158,52844,Probation,White,Danny,NULL,Male,Caucasian,12/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +51645,58158,52844,Probation,White,Danny,NULL,Male,Caucasian,12/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +51645,58158,52844,Probation,White,Danny,NULL,Male,Caucasian,12/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51618,58120,52812,PRETRIAL,DAVIS,EVERLEY,NULL,Female,African-American,04/17/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-4.39,1,Low,New,1,0 +51618,58120,52812,PRETRIAL,DAVIS,EVERLEY,NULL,Female,African-American,04/17/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +51618,58120,52812,PRETRIAL,DAVIS,EVERLEY,NULL,Female,African-American,04/17/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51621,58123,52815,PRETRIAL,HAYNES,DWAYNE,A,Male,African-American,07/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/28/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +51621,58123,52815,PRETRIAL,HAYNES,DWAYNE,A,Male,African-American,07/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/28/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +51621,58123,52815,PRETRIAL,HAYNES,DWAYNE,A,Male,African-American,07/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51622,58125,52816,PRETRIAL,VICTOR- REMEDOR,SANDRA,NULL,Female,African-American,08/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +51622,58125,52816,PRETRIAL,VICTOR- REMEDOR,SANDRA,NULL,Female,African-American,08/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +51622,58125,52816,PRETRIAL,VICTOR- REMEDOR,SANDRA,NULL,Female,African-American,08/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51635,58146,52833,PRETRIAL,Morales,James,NULL,Male,Hispanic,10/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +51635,58146,52833,PRETRIAL,Morales,James,NULL,Male,Hispanic,10/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +51635,58146,52833,PRETRIAL,Morales,James,NULL,Male,Hispanic,10/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51640,58153,52839,Probation,BERRIOS,RAMON,NULL,Male,Hispanic,04/30/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,2,Medium,7,Risk of Violence,-2.27,3,Low,New,1,0 +51640,58153,52839,Probation,BERRIOS,RAMON,NULL,Male,Hispanic,04/30/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +51640,58153,52839,Probation,BERRIOS,RAMON,NULL,Male,Hispanic,04/30/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51647,58160,52846,PRETRIAL,Cuggio,Nicole,NULL,Female,Caucasian,09/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/28/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +51647,58160,52846,PRETRIAL,Cuggio,Nicole,NULL,Female,Caucasian,09/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/28/13 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +51647,58160,52846,PRETRIAL,Cuggio,Nicole,NULL,Female,Caucasian,09/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51651,58167,52853,PRETRIAL,Flowers,Jeffrey,Robert,Male,Caucasian,08/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/29/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +51651,58167,52853,PRETRIAL,Flowers,Jeffrey,Robert,Male,Caucasian,08/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/29/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +51651,58167,52853,PRETRIAL,Flowers,Jeffrey,Robert,Male,Caucasian,08/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51658,58174,52860,Probation,Velez,Luis,NULL,Male,Hispanic,08/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +51658,58174,52860,Probation,Velez,Luis,NULL,Male,Hispanic,08/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +51658,58174,52860,Probation,Velez,Luis,NULL,Male,Hispanic,08/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51660,58176,52862,PRETRIAL,WILLIAMS,GREGORY,NULL,Male,Caucasian,09/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/29/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +51660,58176,52862,PRETRIAL,WILLIAMS,GREGORY,NULL,Male,Caucasian,09/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/29/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +51660,58176,52862,PRETRIAL,WILLIAMS,GREGORY,NULL,Male,Caucasian,09/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51675,58195,52879,Probation,Salerno,John,NULL,Male,Caucasian,09/29/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +51675,58195,52879,Probation,Salerno,John,NULL,Male,Caucasian,09/29/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +51675,58195,52879,Probation,Salerno,John,NULL,Male,Caucasian,09/29/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +51662,58179,52864,PRETRIAL,GOODLEY,DERRICK,FONDEL,Male,African-American,11/14/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +51662,58179,52864,PRETRIAL,GOODLEY,DERRICK,FONDEL,Male,African-American,11/14/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +51662,58179,52864,PRETRIAL,GOODLEY,DERRICK,FONDEL,Male,African-American,11/14/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51669,58188,52873,Probation,Flowers,Denaris,NULL,Male,African-American,12/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +51669,58188,52873,Probation,Flowers,Denaris,NULL,Male,African-American,12/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +51669,58188,52873,Probation,Flowers,Denaris,NULL,Male,African-American,12/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51648,58162,52848,PRETRIAL,OSMAN,GREGORY,NULL,Male,Caucasian,03/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/29/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +51648,58162,52848,PRETRIAL,OSMAN,GREGORY,NULL,Male,Caucasian,03/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/29/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +51648,58162,52848,PRETRIAL,OSMAN,GREGORY,NULL,Male,Caucasian,03/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +26520,58183,52868,PRETRIAL,Hostetler,Georgette,NULL,Female,African-American,11/06/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/29/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +26520,58183,52868,PRETRIAL,Hostetler,Georgette,NULL,Female,African-American,11/06/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/29/13 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +26520,58183,52868,PRETRIAL,Hostetler,Georgette,NULL,Female,African-American,11/06/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51673,58193,52877,PRETRIAL,Forestal,Ernest,NULL,Male,African-American,01/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +51673,58193,52877,PRETRIAL,Forestal,Ernest,NULL,Male,African-American,01/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/13 0:00,4,High,8,Risk of Recidivism,0.41,9,High,New,1,0 +51673,58193,52877,PRETRIAL,Forestal,Ernest,NULL,Male,African-American,01/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51655,58172,52858,Probation,Castro,Mulio,NULL,Male,Hispanic,03/09/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/29/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +51655,58172,52858,Probation,Castro,Mulio,NULL,Male,Hispanic,03/09/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/29/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +51655,58172,52858,Probation,Castro,Mulio,NULL,Male,Hispanic,03/09/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44114,58185,52870,PRETRIAL,LABADY,ERNST,NULL,Male,African-American,01/16/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/13 0:00,1,Low,7,Risk of Violence,-4.19,1,Low,New,1,0 +44114,58185,52870,PRETRIAL,LABADY,ERNST,NULL,Male,African-American,01/16/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/13 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +44114,58185,52870,PRETRIAL,LABADY,ERNST,NULL,Male,African-American,01/16/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51650,58164,52850,PRETRIAL,GISPERT,ANGELA,NULL,Female,Caucasian,03/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +51650,58164,52850,PRETRIAL,GISPERT,ANGELA,NULL,Female,Caucasian,03/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +51650,58164,52850,PRETRIAL,GISPERT,ANGELA,NULL,Female,Caucasian,03/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51671,58190,52875,PRETRIAL,FALLON,CRYSTAL,NULL,Male,Other,06/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +51671,58190,52875,PRETRIAL,FALLON,CRYSTAL,NULL,Male,Other,06/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +51671,58190,52875,PRETRIAL,FALLON,CRYSTAL,NULL,Male,Other,06/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +37905,59738,37307,PRETRIAL,WRIGHT,GEORGE,NULL,Male,African-American,03/13/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/29/13 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,Copy,1,0 +37905,59738,37307,PRETRIAL,WRIGHT,GEORGE,NULL,Male,African-American,03/13/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/29/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,Copy,1,0 +37905,59738,37307,PRETRIAL,WRIGHT,GEORGE,NULL,Male,African-American,03/13/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/29/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +51653,58169,52855,PRETRIAL,Gamble,Ricky,NULL,Male,African-American,03/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +51653,58169,52855,PRETRIAL,Gamble,Ricky,NULL,Male,African-American,03/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +51653,58169,52855,PRETRIAL,Gamble,Ricky,NULL,Male,African-American,03/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +6436,58161,52847,PRETRIAL,DEMPS,JANICE,NULL,Female,African-American,09/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +6436,58161,52847,PRETRIAL,DEMPS,JANICE,NULL,Female,African-American,09/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,4,High,8,Risk of Recidivism,-0.02,8,High,New,1,0 +6436,58161,52847,PRETRIAL,DEMPS,JANICE,NULL,Female,African-American,09/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51652,58168,52854,PRETRIAL,Wright,Byron,Moctavius,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +51652,58168,52854,PRETRIAL,Wright,Byron,Moctavius,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +51652,58168,52854,PRETRIAL,Wright,Byron,Moctavius,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51670,58189,52874,PRETRIAL,Salnave,Fidel,NULL,Male,Caucasian,07/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +51670,58189,52874,PRETRIAL,Salnave,Fidel,NULL,Male,Caucasian,07/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +51670,58189,52874,PRETRIAL,Salnave,Fidel,NULL,Male,Caucasian,07/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51665,58182,52867,PRETRIAL,Vigniero,Luis,NULL,Male,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +51665,58182,52867,PRETRIAL,Vigniero,Luis,NULL,Male,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +51665,58182,52867,PRETRIAL,Vigniero,Luis,NULL,Male,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51676,58196,52880,Probation,payne,robert,NULL,Male,Caucasian,10/25/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +51676,58196,52880,Probation,payne,robert,NULL,Male,Caucasian,10/25/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +51676,58196,52880,Probation,payne,robert,NULL,Male,Caucasian,10/25/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51659,58175,52861,Probation,orr,bryan,NULL,Male,Other,03/07/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +51659,58175,52861,Probation,orr,bryan,NULL,Male,Other,03/07/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +51659,58175,52861,Probation,orr,bryan,NULL,Male,Other,03/07/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51663,58180,52865,Probation,Maxcena,Rita,NULL,Female,African-American,05/09/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +51663,58180,52865,Probation,Maxcena,Rita,NULL,Female,African-American,05/09/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +51663,58180,52865,Probation,Maxcena,Rita,NULL,Female,African-American,05/09/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51668,58187,52872,PRETRIAL,Rivas,Jaime,NULL,Male,Hispanic,12/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +51668,58187,52872,PRETRIAL,Rivas,Jaime,NULL,Male,Hispanic,12/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +51668,58187,52872,PRETRIAL,Rivas,Jaime,NULL,Male,Hispanic,12/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +21126,58166,52852,PRETRIAL,Cyrus,Terry,Lomar,Male,African-American,10/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +21126,58166,52852,PRETRIAL,Cyrus,Terry,Lomar,Male,African-American,10/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +21126,58166,52852,PRETRIAL,Cyrus,Terry,Lomar,Male,African-American,10/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51666,58184,52869,PRETRIAL,JACQUES,JASMINE,NULL,Female,Caucasian,12/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +51666,58184,52869,PRETRIAL,JACQUES,JASMINE,NULL,Female,Caucasian,12/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,4,High,8,Risk of Recidivism,0.94,10,High,New,1,0 +51666,58184,52869,PRETRIAL,JACQUES,JASMINE,NULL,Female,Caucasian,12/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,4,High,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +51674,58194,52878,Probation,cramer,richard,NULL,Male,Caucasian,07/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +51674,58194,52878,Probation,cramer,richard,NULL,Male,Caucasian,07/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +51674,58194,52878,Probation,cramer,richard,NULL,Male,Caucasian,07/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +46430,58165,52851,PRETRIAL,Wallace,Allerick,NULL,Male,African-American,03/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,4,High,7,Risk of Violence,-0.67,9,High,New,1,0 +46430,58165,52851,PRETRIAL,Wallace,Allerick,NULL,Male,African-American,03/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,4,High,8,Risk of Recidivism,0.15,8,High,New,1,0 +46430,58165,52851,PRETRIAL,Wallace,Allerick,NULL,Male,African-American,03/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51657,58173,52859,DRRD,Cucci,Marianna,NULL,Female,Caucasian,12/12/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/29/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +51657,58173,52859,DRRD,Cucci,Marianna,NULL,Female,Caucasian,12/12/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,6,Medium,New,1,0 +51657,58173,52859,DRRD,Cucci,Marianna,NULL,Female,Caucasian,12/12/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/29/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51667,58186,52871,Probation,LUCAN,FRANK,BILLIE,Male,Native American,10/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +51667,58186,52871,Probation,LUCAN,FRANK,BILLIE,Male,Native American,10/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +51667,58186,52871,Probation,LUCAN,FRANK,BILLIE,Male,Native American,10/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51649,58163,52849,PRETRIAL,Denby,Brian,NULL,Male,Caucasian,02/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +51649,58163,52849,PRETRIAL,Denby,Brian,NULL,Male,Caucasian,02/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +51649,58163,52849,PRETRIAL,Denby,Brian,NULL,Male,Caucasian,02/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51654,58170,52856,PRETRIAL,DOMKOSKI,JACOB,NULL,Male,Caucasian,11/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +51654,58170,52856,PRETRIAL,DOMKOSKI,JACOB,NULL,Male,Caucasian,11/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +51654,58170,52856,PRETRIAL,DOMKOSKI,JACOB,NULL,Male,Caucasian,11/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +31864,58191,30869,PRETRIAL,FREEMAN,ANTHONY,NULL,Male,African-American,08/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,Copy,1,0 +31864,58191,30869,PRETRIAL,FREEMAN,ANTHONY,NULL,Male,African-American,08/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,Copy,1,0 +31864,58191,30869,PRETRIAL,FREEMAN,ANTHONY,NULL,Male,African-American,08/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +34047,58178,33181,PRETRIAL,Lewis,Kurt,NULL,Male,Other,08/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,Copy,1,0 +34047,58178,33181,PRETRIAL,Lewis,Kurt,NULL,Male,Other,08/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,Copy,1,0 +34047,58178,33181,PRETRIAL,Lewis,Kurt,NULL,Male,Other,08/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +51689,58220,52902,PRETRIAL,Desinor,Ronel,NULL,Male,African-American,10/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +51689,58220,52902,PRETRIAL,Desinor,Ronel,NULL,Male,African-American,10/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +51689,58220,52902,PRETRIAL,Desinor,Ronel,NULL,Male,African-American,10/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +20962,58254,52928,Probation,Martin,Shaporia,La'shay,Female,African-American,05/25/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +20962,58254,52928,Probation,Martin,Shaporia,La'shay,Female,African-American,05/25/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,4,High,8,Risk of Recidivism,0.43,9,High,New,1,0 +20962,58254,52928,Probation,Martin,Shaporia,La'shay,Female,African-American,05/25/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51683,58207,52890,PRETRIAL,Gillet,Brent,NULL,Male,Caucasian,07/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +51683,58207,52890,PRETRIAL,Gillet,Brent,NULL,Male,Caucasian,07/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +51683,58207,52890,PRETRIAL,Gillet,Brent,NULL,Male,Caucasian,07/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +43541,58233,43508,PRETRIAL,Forte,Jaime,NULL,Female,African-American,03/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,Copy,1,0 +43541,58233,43508,PRETRIAL,Forte,Jaime,NULL,Female,African-American,03/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,Copy,1,0 +43541,58233,43508,PRETRIAL,Forte,Jaime,NULL,Female,African-American,03/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +30938,58212,52895,PRETRIAL,west,anthony,NULL,Male,African-American,10/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +30938,58212,52895,PRETRIAL,west,anthony,NULL,Male,African-American,10/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +30938,58212,52895,PRETRIAL,west,anthony,NULL,Male,African-American,10/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +47553,58201,52884,PRETRIAL,ROBINS,MARVIN,NULL,Male,African-American,02/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +47553,58201,52884,PRETRIAL,ROBINS,MARVIN,NULL,Male,African-American,02/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +47553,58201,52884,PRETRIAL,ROBINS,MARVIN,NULL,Male,African-American,02/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51681,58205,52888,PRETRIAL,BLOUNT,THEODORE,NULL,Male,African-American,11/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/30/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +51681,58205,52888,PRETRIAL,BLOUNT,THEODORE,NULL,Male,African-American,11/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/30/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +51681,58205,52888,PRETRIAL,BLOUNT,THEODORE,NULL,Male,African-American,11/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/30/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51693,58226,52908,PRETRIAL,Brooks,Antwan,NULL,Male,African-American,03/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/30/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +51693,58226,52908,PRETRIAL,Brooks,Antwan,NULL,Male,African-American,03/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/30/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +51693,58226,52908,PRETRIAL,Brooks,Antwan,NULL,Male,African-American,03/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51679,58203,52886,PRETRIAL,Gordon-Taylor,Jeremy,NULL,Male,Oriental,04/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +51679,58203,52886,PRETRIAL,Gordon-Taylor,Jeremy,NULL,Male,Oriental,04/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +51679,58203,52886,PRETRIAL,Gordon-Taylor,Jeremy,NULL,Male,Oriental,04/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51684,58210,52893,PRETRIAL,Harris,Cortez,NULL,Male,African-American,02/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +51684,58210,52893,PRETRIAL,Harris,Cortez,NULL,Male,African-American,02/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +51684,58210,52893,PRETRIAL,Harris,Cortez,NULL,Male,African-American,02/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +33422,58217,32526,Probation,moore,dionte,NULL,Male,African-American,12/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,Copy,1,0 +33422,58217,32526,Probation,moore,dionte,NULL,Male,African-American,12/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,Copy,1,0 +33422,58217,32526,Probation,moore,dionte,NULL,Male,African-American,12/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +51688,58219,52901,PRETRIAL,Murray,Patrick,NULL,Male,Caucasian,09/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +51688,58219,52901,PRETRIAL,Murray,Patrick,NULL,Male,Caucasian,09/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +51688,58219,52901,PRETRIAL,Murray,Patrick,NULL,Male,Caucasian,09/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51687,58216,52899,PRETRIAL,Flowers,Andrew,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +51687,58216,52899,PRETRIAL,Flowers,Andrew,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +51687,58216,52899,PRETRIAL,Flowers,Andrew,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51691,58224,52906,Probation,Pagan,Ramon,NULL,Male,Hispanic,08/26/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/30/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +51691,58224,52906,Probation,Pagan,Ramon,NULL,Male,Hispanic,08/26/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/30/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +51691,58224,52906,Probation,Pagan,Ramon,NULL,Male,Hispanic,08/26/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51685,58211,52894,PRETRIAL,MELENDEZ,LUIS,NULL,Male,Caucasian,04/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +51685,58211,52894,PRETRIAL,MELENDEZ,LUIS,NULL,Male,Caucasian,04/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +51685,58211,52894,PRETRIAL,MELENDEZ,LUIS,NULL,Male,Caucasian,04/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +17687,58200,52883,PRETRIAL,ALEXANDER,LEONARD,A,Male,African-American,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +17687,58200,52883,PRETRIAL,ALEXANDER,LEONARD,A,Male,African-American,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +17687,58200,52883,PRETRIAL,ALEXANDER,LEONARD,A,Male,African-American,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51686,58214,52897,PRETRIAL,Kissoonlai,Ian,NULL,Male,African-American,03/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +51686,58214,52897,PRETRIAL,Kissoonlai,Ian,NULL,Male,African-American,03/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +51686,58214,52897,PRETRIAL,Kissoonlai,Ian,NULL,Male,African-American,03/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +45286,58235,52916,PRETRIAL,Blanco,Jose,E,Male,Caucasian,05/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +45286,58235,52916,PRETRIAL,Blanco,Jose,E,Male,Caucasian,05/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +45286,58235,52916,PRETRIAL,Blanco,Jose,E,Male,Caucasian,05/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51682,58206,52889,PRETRIAL,Gonzalez,Javier,NULL,Male,Caucasian,10/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.22,8,High,New,1,0 +51682,58206,52889,PRETRIAL,Gonzalez,Javier,NULL,Male,Caucasian,10/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +51682,58206,52889,PRETRIAL,Gonzalez,Javier,NULL,Male,Caucasian,10/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49853,58208,52891,PRETRIAL,FOWLER,DEVONTE,T,Male,African-American,06/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +49853,58208,52891,PRETRIAL,FOWLER,DEVONTE,T,Male,African-American,06/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +49853,58208,52891,PRETRIAL,FOWLER,DEVONTE,T,Male,African-American,06/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +14300,58242,52922,Probation,campisano,frank,NULL,Male,Caucasian,03/20/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +14300,58242,52922,Probation,campisano,frank,NULL,Male,Caucasian,03/20/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +14300,58242,52922,Probation,campisano,frank,NULL,Male,Caucasian,03/20/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51694,58227,52909,Probation,LYMAN,ERIN,A,Female,Caucasian,01/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +51694,58227,52909,Probation,LYMAN,ERIN,A,Female,Caucasian,01/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +51694,58227,52909,Probation,LYMAN,ERIN,A,Female,Caucasian,01/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51704,58248,52924,PRETRIAL,WIESS,ELIZABETH,NULL,Female,Caucasian,04/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/13 0:00,2,Medium,7,Risk of Violence,-2.64,2,Low,New,1,0 +51704,58248,52924,PRETRIAL,WIESS,ELIZABETH,NULL,Female,Caucasian,04/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +51704,58248,52924,PRETRIAL,WIESS,ELIZABETH,NULL,Female,Caucasian,04/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +24262,58230,52912,PRETRIAL,CREDINCIOSU,AUDREY,NULL,Female,Caucasian,06/11/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +24262,58230,52912,PRETRIAL,CREDINCIOSU,AUDREY,NULL,Female,Caucasian,06/11/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,8,High,New,1,0 +24262,58230,52912,PRETRIAL,CREDINCIOSU,AUDREY,NULL,Female,Caucasian,06/11/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +51698,58255,52929,PRETRIAL,eaton,yashell,NULL,Female,African-American,10/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +51698,58255,52929,PRETRIAL,eaton,yashell,NULL,Female,African-American,10/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +51698,58255,52929,PRETRIAL,eaton,yashell,NULL,Female,African-American,10/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50843,58213,52896,PRETRIAL,Davis,Michael,Lavon,Male,African-American,11/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +50843,58213,52896,PRETRIAL,Davis,Michael,Lavon,Male,African-American,11/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +50843,58213,52896,PRETRIAL,Davis,Michael,Lavon,Male,African-American,11/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +9274,58218,52900,PRETRIAL,SOTO,VICTOR,NULL,Male,Hispanic,07/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +9274,58218,52900,PRETRIAL,SOTO,VICTOR,NULL,Male,Hispanic,07/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +9274,58218,52900,PRETRIAL,SOTO,VICTOR,NULL,Male,Hispanic,07/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +40493,58209,52892,PRETRIAL,DOYLEY,DANE,NULL,Male,African-American,02/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +40493,58209,52892,PRETRIAL,DOYLEY,DANE,NULL,Male,African-American,02/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +40493,58209,52892,PRETRIAL,DOYLEY,DANE,NULL,Male,African-American,02/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +30512,58202,52885,PRETRIAL,DUNKLIN,OCTAVIUS,NULL,Male,African-American,01/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +30512,58202,52885,PRETRIAL,DUNKLIN,OCTAVIUS,NULL,Male,African-American,01/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +30512,58202,52885,PRETRIAL,DUNKLIN,OCTAVIUS,NULL,Male,African-American,01/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51680,58204,52887,PRETRIAL,Burnett,Bryan,NULL,Male,Caucasian,09/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +51680,58204,52887,PRETRIAL,Burnett,Bryan,NULL,Male,Caucasian,09/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +51680,58204,52887,PRETRIAL,Burnett,Bryan,NULL,Male,Caucasian,09/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51692,58225,52907,PRETRIAL,House,Tina,NULL,Female,Caucasian,06/11/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +51692,58225,52907,PRETRIAL,House,Tina,NULL,Female,Caucasian,06/11/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,8,High,New,1,0 +51692,58225,52907,PRETRIAL,House,Tina,NULL,Female,Caucasian,06/11/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +51723,58274,52947,Probation,CAMPBELL,JEROME,K,Male,African-American,10/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +51723,58274,52947,Probation,CAMPBELL,JEROME,K,Male,African-American,10/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +51723,58274,52947,Probation,CAMPBELL,JEROME,K,Male,African-American,10/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +51740,58295,52967,PRETRIAL,allen,carlos,NULL,Male,Hispanic,01/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +51740,58295,52967,PRETRIAL,allen,carlos,NULL,Male,Hispanic,01/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +51740,58295,52967,PRETRIAL,allen,carlos,NULL,Male,Hispanic,01/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51741,58297,52969,Probation,perez,daniel,NULL,Male,Hispanic,03/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,1/31/13 0:00,2,Medium,7,Risk of Violence,-2.45,3,Low,New,1,0 +51741,58297,52969,Probation,perez,daniel,NULL,Male,Hispanic,03/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,1/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +51741,58297,52969,Probation,perez,daniel,NULL,Male,Hispanic,03/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,1/31/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51745,58302,52974,Probation,Perdoza,Jason,NULL,Male,Hispanic,04/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/31/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +51745,58302,52974,Probation,Perdoza,Jason,NULL,Male,Hispanic,04/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +51745,58302,52974,Probation,Perdoza,Jason,NULL,Male,Hispanic,04/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +44418,58304,52976,Probation,Diaz,Anthony,sean,Male,Hispanic,10/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +44418,58304,52976,Probation,Diaz,Anthony,sean,Male,Hispanic,10/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +44418,58304,52976,Probation,Diaz,Anthony,sean,Male,Hispanic,10/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51716,58267,52940,PRETRIAL,Harcum,Bria,NULL,Female,African-American,06/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +51716,58267,52940,PRETRIAL,Harcum,Bria,NULL,Female,African-American,06/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +51716,58267,52940,PRETRIAL,Harcum,Bria,NULL,Female,African-American,06/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +16779,58260,52933,PRETRIAL,mompremier,monica,NULL,Female,African-American,04/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +16779,58260,52933,PRETRIAL,mompremier,monica,NULL,Female,African-American,04/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +16779,58260,52933,PRETRIAL,mompremier,monica,NULL,Female,African-American,04/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51737,58290,52962,Probation,Degore,Richard,Anthony,Male,Caucasian,06/04/53,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +51737,58290,52962,Probation,Degore,Richard,Anthony,Male,Caucasian,06/04/53,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +51737,58290,52962,Probation,Degore,Richard,Anthony,Male,Caucasian,06/04/53,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +12165,58307,52979,PRETRIAL,MATHES,MICHOLAS,DAVID,Male,Caucasian,05/18/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +12165,58307,52979,PRETRIAL,MATHES,MICHOLAS,DAVID,Male,Caucasian,05/18/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +12165,58307,52979,PRETRIAL,MATHES,MICHOLAS,DAVID,Male,Caucasian,05/18/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +45036,49602,45224,PRETRIAL,Brown,Marie,NULL,Female,Caucasian,01/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +45036,49602,45224,PRETRIAL,Brown,Marie,NULL,Female,Caucasian,01/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,8,Risk of Recidivism,0.08,8,High,New,1,0 +45036,49602,45224,PRETRIAL,Brown,Marie,NULL,Female,Caucasian,01/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +47826,58286,48437,PRETRIAL,BOWLEG,AHMAD,NULL,Male,African-American,03/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,Copy,1,0 +47826,58286,48437,PRETRIAL,BOWLEG,AHMAD,NULL,Male,African-American,03/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,Copy,1,0 +47826,58286,48437,PRETRIAL,BOWLEG,AHMAD,NULL,Male,African-American,03/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +51718,58269,52942,PRETRIAL,OWENS,JOHNNY,L,Male,African-American,06/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +51718,58269,52942,PRETRIAL,OWENS,JOHNNY,L,Male,African-American,06/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +51718,58269,52942,PRETRIAL,OWENS,JOHNNY,L,Male,African-American,06/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +47288,58265,52938,PRETRIAL,Porzio,Lori,NULL,Female,Caucasian,11/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +47288,58265,52938,PRETRIAL,Porzio,Lori,NULL,Female,Caucasian,11/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +47288,58265,52938,PRETRIAL,Porzio,Lori,NULL,Female,Caucasian,11/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +51714,58263,52936,PRETRIAL,Moss,Travis,Jamal,Male,Other,01/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +51714,58263,52936,PRETRIAL,Moss,Travis,Jamal,Male,Other,01/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +51714,58263,52936,PRETRIAL,Moss,Travis,Jamal,Male,Other,01/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51748,58308,52980,Probation,orourke,aiden,NULL,Male,Caucasian,09/18/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +51748,58308,52980,Probation,orourke,aiden,NULL,Male,Caucasian,09/18/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,8,Risk of Recidivism,-2.83,1,Low,New,1,0 +51748,58308,52980,Probation,orourke,aiden,NULL,Male,Caucasian,09/18/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +41921,58271,52944,PRETRIAL,BAKER,HASSAN,NULL,Male,African-American,01/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +41921,58271,52944,PRETRIAL,BAKER,HASSAN,NULL,Male,African-American,01/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +41921,58271,52944,PRETRIAL,BAKER,HASSAN,NULL,Male,African-American,01/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51743,58300,52972,Probation,ROJAS,MARCO,NULL,Male,Hispanic,11/20/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +51743,58300,52972,Probation,ROJAS,MARCO,NULL,Male,Hispanic,11/20/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +51743,58300,52972,Probation,ROJAS,MARCO,NULL,Male,Hispanic,11/20/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51729,58279,52952,PRETRIAL,HAYNES,ERIC,NULL,Male,African-American,08/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +51729,58279,52952,PRETRIAL,HAYNES,ERIC,NULL,Male,African-American,08/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +51729,58279,52952,PRETRIAL,HAYNES,ERIC,NULL,Male,African-American,08/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +28599,58258,47852,PRETRIAL,Sewell,Garfield,NULL,Male,African-American,09/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,7,Risk of Violence,-0.26,10,High,Copy,1,0 +28599,58258,47852,PRETRIAL,Sewell,Garfield,NULL,Male,African-American,09/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,Copy,1,0 +28599,58258,47852,PRETRIAL,Sewell,Garfield,NULL,Male,African-American,09/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +6456,58292,52964,PRETRIAL,MCDONALD,EVERALD,R,Male,African-American,05/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/31/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +6456,58292,52964,PRETRIAL,MCDONALD,EVERALD,R,Male,African-American,05/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +6456,58292,52964,PRETRIAL,MCDONALD,EVERALD,R,Male,African-American,05/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +25262,58266,52939,PRETRIAL,DUKES,MARCUS,NULL,Male,African-American,09/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +25262,58266,52939,PRETRIAL,DUKES,MARCUS,NULL,Male,African-American,09/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +25262,58266,52939,PRETRIAL,DUKES,MARCUS,NULL,Male,African-American,09/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +45513,58284,52957,PRETRIAL,LAWTON,PJ,NULL,Male,African-American,06/22/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/31/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +45513,58284,52957,PRETRIAL,LAWTON,PJ,NULL,Male,African-American,06/22/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +45513,58284,52957,PRETRIAL,LAWTON,PJ,NULL,Male,African-American,06/22/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51734,58287,52959,Probation,LAZAR,MIRCEA,C,Male,Caucasian,06/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +51734,58287,52959,Probation,LAZAR,MIRCEA,C,Male,Caucasian,06/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +51734,58287,52959,Probation,LAZAR,MIRCEA,C,Male,Caucasian,06/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51747,58305,52977,Probation,Jennings,Thadeus,NULL,Male,African-American,03/28/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +51747,58305,52977,Probation,Jennings,Thadeus,NULL,Male,African-American,03/28/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +51747,58305,52977,Probation,Jennings,Thadeus,NULL,Male,African-American,03/28/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +51717,58268,52941,PRETRIAL,Laidlaw,Andre,NULL,Male,African-American,08/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +51717,58268,52941,PRETRIAL,Laidlaw,Andre,NULL,Male,African-American,08/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +51717,58268,52941,PRETRIAL,Laidlaw,Andre,NULL,Male,African-American,08/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +12811,58282,52955,PRETRIAL,CLOUSE,JON,NULL,Male,Caucasian,01/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/31/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +12811,58282,52955,PRETRIAL,CLOUSE,JON,NULL,Male,Caucasian,01/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/31/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +12811,58282,52955,PRETRIAL,CLOUSE,JON,NULL,Male,Caucasian,01/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +42247,58296,52968,PRETRIAL,SHATTEEN,JASMINE,J,Female,African-American,09/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +42247,58296,52968,PRETRIAL,SHATTEEN,JASMINE,J,Female,African-American,09/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +42247,58296,52968,PRETRIAL,SHATTEEN,JASMINE,J,Female,African-American,09/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51746,58303,52975,Probation,Mekpisan,Nachparon,NULL,Male,Asian,10/20/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +51746,58303,52975,Probation,Mekpisan,Nachparon,NULL,Male,Asian,10/20/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +51746,58303,52975,Probation,Mekpisan,Nachparon,NULL,Male,Asian,10/20/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51750,58310,52982,Probation,MOHIP,VISHAM,NULL,Male,Other,07/23/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +51750,58310,52982,Probation,MOHIP,VISHAM,NULL,Male,Other,07/23/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +51750,58310,52982,Probation,MOHIP,VISHAM,NULL,Male,Other,07/23/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +31084,58259,52932,PRETRIAL,Greene,James,NULL,Male,African-American,10/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/31/13 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +31084,58259,52932,PRETRIAL,Greene,James,NULL,Male,African-American,10/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/31/13 0:00,4,High,8,Risk of Recidivism,0.1,8,High,New,1,0 +31084,58259,52932,PRETRIAL,Greene,James,NULL,Male,African-American,10/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/31/13 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +51736,58289,52961,Probation,Manzano,Alexander,NULL,Male,Caucasian,03/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +51736,58289,52961,Probation,Manzano,Alexander,NULL,Male,Caucasian,03/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +51736,58289,52961,Probation,Manzano,Alexander,NULL,Male,Caucasian,03/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51712,58261,52934,PRETRIAL,Dent,Dominique,NULL,Female,Caucasian,01/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +51712,58261,52934,PRETRIAL,Dent,Dominique,NULL,Female,Caucasian,01/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +51712,58261,52934,PRETRIAL,Dent,Dominique,NULL,Female,Caucasian,01/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +51706,58256,52930,PRETRIAL,Fleury,Deandre,NULL,Male,African-American,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +51706,58256,52930,PRETRIAL,Fleury,Deandre,NULL,Male,African-American,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,8,Risk of Recidivism,0.31,9,High,New,1,0 +51706,58256,52930,PRETRIAL,Fleury,Deandre,NULL,Male,African-American,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51722,58273,52946,Probation,KLEIER,GEORGE,W,Male,Caucasian,09/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +51722,58273,52946,Probation,KLEIER,GEORGE,W,Male,Caucasian,09/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +51722,58273,52946,Probation,KLEIER,GEORGE,W,Male,Caucasian,09/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51739,58294,52966,PRETRIAL,Jackson,Briani,NULL,Female,African-American,09/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +51739,58294,52966,PRETRIAL,Jackson,Briani,NULL,Female,African-American,09/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,8,Risk of Recidivism,0.44,10,High,New,1,0 +51739,58294,52966,PRETRIAL,Jackson,Briani,NULL,Female,African-American,09/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +51742,58298,52970,Probation,RAMLAL,ANNIL,RYAN,Male,Caucasian,01/30/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +51742,58298,52970,Probation,RAMLAL,ANNIL,RYAN,Male,Caucasian,01/30/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +51742,58298,52970,Probation,RAMLAL,ANNIL,RYAN,Male,Caucasian,01/30/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51713,58262,52935,PRETRIAL,Rabinowitz,Barry,NULL,Male,Caucasian,11/16/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/31/13 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +51713,58262,52935,PRETRIAL,Rabinowitz,Barry,NULL,Male,Caucasian,11/16/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/31/13 0:00,1,Low,8,Risk of Recidivism,-2.68,1,Low,New,1,0 +51713,58262,52935,PRETRIAL,Rabinowitz,Barry,NULL,Male,Caucasian,11/16/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51730,58280,52953,Probation,Barquero,Benjamin,NULL,Male,Hispanic,11/30/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +51730,58280,52953,Probation,Barquero,Benjamin,NULL,Male,Hispanic,11/30/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +51730,58280,52953,Probation,Barquero,Benjamin,NULL,Male,Hispanic,11/30/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51732,58283,52956,Probation,NcCauley,Reese,NULL,Male,Caucasian,02/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +51732,58283,52956,Probation,NcCauley,Reese,NULL,Male,Caucasian,02/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +51732,58283,52956,Probation,NcCauley,Reese,NULL,Male,Caucasian,02/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51744,58301,52973,Probation,Benitez,Florentino,NULL,Male,Hispanic,10/26/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +51744,58301,52973,Probation,Benitez,Florentino,NULL,Male,Hispanic,10/26/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +51744,58301,52973,Probation,Benitez,Florentino,NULL,Male,Hispanic,10/26/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51724,58275,52948,Probation,Massetti,Maryann,NULL,Female,Caucasian,04/01/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +51724,58275,52948,Probation,Massetti,Maryann,NULL,Female,Caucasian,04/01/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +51724,58275,52948,Probation,Massetti,Maryann,NULL,Female,Caucasian,04/01/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51749,58309,52981,Probation,Andrews,Donna,J,Female,Caucasian,08/25/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/31/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +51749,58309,52981,Probation,Andrews,Donna,J,Female,Caucasian,08/25/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/31/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +51749,58309,52981,Probation,Andrews,Donna,J,Female,Caucasian,08/25/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51735,58288,52960,PRETRIAL,Scott,James,Stewart,Male,African-American,01/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +51735,58288,52960,PRETRIAL,Scott,James,Stewart,Male,African-American,01/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +51735,58288,52960,PRETRIAL,Scott,James,Stewart,Male,African-American,01/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51728,58278,52951,Probation,Oneill,Carol,NULL,Female,Caucasian,10/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +51728,58278,52951,Probation,Oneill,Carol,NULL,Female,Caucasian,10/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +51728,58278,52951,Probation,Oneill,Carol,NULL,Female,Caucasian,10/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51733,58285,52958,PRETRIAL,Vanzandt,Miles,Christian,Male,Caucasian,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +51733,58285,52958,PRETRIAL,Vanzandt,Miles,Christian,Male,Caucasian,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +51733,58285,52958,PRETRIAL,Vanzandt,Miles,Christian,Male,Caucasian,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51715,58264,52937,PRETRIAL,Johnson,Carlo,NULL,Male,African-American,12/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +51715,58264,52937,PRETRIAL,Johnson,Carlo,NULL,Male,African-American,12/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +51715,58264,52937,PRETRIAL,Johnson,Carlo,NULL,Male,African-American,12/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +36636,58299,52971,PRETRIAL,Dejesus,Manuel,NULL,Male,Hispanic,07/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +36636,58299,52971,PRETRIAL,Dejesus,Manuel,NULL,Male,Hispanic,07/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +36636,58299,52971,PRETRIAL,Dejesus,Manuel,NULL,Male,Hispanic,07/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51707,58257,52931,PRETRIAL,Franco,Jhonatan,NULL,Male,Hispanic,05/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +51707,58257,52931,PRETRIAL,Franco,Jhonatan,NULL,Male,Hispanic,05/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +51707,58257,52931,PRETRIAL,Franco,Jhonatan,NULL,Male,Hispanic,05/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51738,58291,52963,Probation,sniffen,ronald,NULL,Male,Caucasian,04/14/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/31/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +51738,58291,52963,Probation,sniffen,ronald,NULL,Male,Caucasian,04/14/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/31/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +51738,58291,52963,Probation,sniffen,ronald,NULL,Male,Caucasian,04/14/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +45426,58293,52965,PRETRIAL,SWINTON,EZEKIEL,NULL,Male,African-American,03/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.77,9,High,New,1,0 +45426,58293,52965,PRETRIAL,SWINTON,EZEKIEL,NULL,Male,African-American,03/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +45426,58293,52965,PRETRIAL,SWINTON,EZEKIEL,NULL,Male,African-American,03/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +38794,58306,52978,PRETRIAL,Accius,Diomene,NULL,Male,African-American,01/09/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +38794,58306,52978,PRETRIAL,Accius,Diomene,NULL,Male,African-American,01/09/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +38794,58306,52978,PRETRIAL,Accius,Diomene,NULL,Male,African-American,01/09/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51719,58270,52943,PRETRIAL,Lestrade,Kelly,NULL,Male,African-American,11/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +51719,58270,52943,PRETRIAL,Lestrade,Kelly,NULL,Male,African-American,11/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +51719,58270,52943,PRETRIAL,Lestrade,Kelly,NULL,Male,African-American,11/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51720,58272,52945,PRETRIAL,Velasco,Luis,A,Male,Caucasian,04/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +51720,58272,52945,PRETRIAL,Velasco,Luis,A,Male,Caucasian,04/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +51720,58272,52945,PRETRIAL,Velasco,Luis,A,Male,Caucasian,04/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51762,58327,52997,PRETRIAL,Debriae,Carol,NULL,Female,Caucasian,08/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +51762,58327,52997,PRETRIAL,Debriae,Carol,NULL,Female,Caucasian,08/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +51762,58327,52997,PRETRIAL,Debriae,Carol,NULL,Female,Caucasian,08/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51752,58314,52985,PRETRIAL,Vasquez,Sean,NULL,Male,Caucasian,09/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +51752,58314,52985,PRETRIAL,Vasquez,Sean,NULL,Male,Caucasian,09/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +51752,58314,52985,PRETRIAL,Vasquez,Sean,NULL,Male,Caucasian,09/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51767,58335,53005,Probation,wilson,tabitha,NULL,Female,African-American,01/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +51767,58335,53005,Probation,wilson,tabitha,NULL,Female,African-American,01/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +51767,58335,53005,Probation,wilson,tabitha,NULL,Female,African-American,01/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51758,58322,52992,PRETRIAL,Bell,Gerraro,NULL,Male,African-American,12/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +51758,58322,52992,PRETRIAL,Bell,Gerraro,NULL,Male,African-American,12/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +51758,58322,52992,PRETRIAL,Bell,Gerraro,NULL,Male,African-American,12/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +51774,58343,53012,PRETRIAL,ARVINGER,SHANTEKA,NULL,Female,African-American,07/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +51774,58343,53012,PRETRIAL,ARVINGER,SHANTEKA,NULL,Female,African-American,07/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +51774,58343,53012,PRETRIAL,ARVINGER,SHANTEKA,NULL,Female,African-American,07/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +18324,58348,53017,PRETRIAL,SAUNDERS,JAMES,NULL,Male,Caucasian,07/08/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +18324,58348,53017,PRETRIAL,SAUNDERS,JAMES,NULL,Male,Caucasian,07/08/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.63,10,High,New,1,0 +18324,58348,53017,PRETRIAL,SAUNDERS,JAMES,NULL,Male,Caucasian,07/08/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +51778,58351,53020,Probation,CELOWANCHICK,WILLIAM,J,Male,Caucasian,03/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +51778,58351,53020,Probation,CELOWANCHICK,WILLIAM,J,Male,Caucasian,03/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +51778,58351,53020,Probation,CELOWANCHICK,WILLIAM,J,Male,Caucasian,03/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +51753,58315,52986,PRETRIAL,Campbell,Shad,NULL,Male,Caucasian,12/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +51753,58315,52986,PRETRIAL,Campbell,Shad,NULL,Male,Caucasian,12/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +51753,58315,52986,PRETRIAL,Campbell,Shad,NULL,Male,Caucasian,12/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51766,58333,53003,Probation,Merker,Agnes,NULL,Female,Caucasian,05/02/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/1/13 0:00,1,Low,7,Risk of Violence,-4.19,1,Low,New,1,0 +51766,58333,53003,Probation,Merker,Agnes,NULL,Female,Caucasian,05/02/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/1/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +51766,58333,53003,Probation,Merker,Agnes,NULL,Female,Caucasian,05/02/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +24234,58312,23419,PRETRIAL,JOHNSON,NIESHA,NULL,Female,African-American,03/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +24234,58312,23419,PRETRIAL,JOHNSON,NIESHA,NULL,Female,African-American,03/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,Copy,1,0 +24234,58312,23419,PRETRIAL,JOHNSON,NIESHA,NULL,Female,African-American,03/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +9625,58319,9154,Probation,Jackson,Michael,NULL,Male,African-American,09/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/1/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,Copy,1,0 +9625,58319,9154,Probation,Jackson,Michael,NULL,Male,African-American,09/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,Copy,1,0 +9625,58319,9154,Probation,Jackson,Michael,NULL,Male,African-American,09/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +51760,58324,52994,PRETRIAL,Rodriguez,Alexander,NULL,Male,Hispanic,05/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/1/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +51760,58324,52994,PRETRIAL,Rodriguez,Alexander,NULL,Male,Hispanic,05/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +51760,58324,52994,PRETRIAL,Rodriguez,Alexander,NULL,Male,Hispanic,05/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +39111,58345,53014,PRETRIAL,Campbell,Demar,NULL,Male,Other,09/08/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +39111,58345,53014,PRETRIAL,Campbell,Demar,NULL,Male,Other,09/08/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +39111,58345,53014,PRETRIAL,Campbell,Demar,NULL,Male,Other,09/08/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51770,58338,53008,PRETRIAL,BENNETTWEST,TAMIKA,SHANICE,Female,African-American,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +51770,58338,53008,PRETRIAL,BENNETTWEST,TAMIKA,SHANICE,Female,African-American,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +51770,58338,53008,PRETRIAL,BENNETTWEST,TAMIKA,SHANICE,Female,African-American,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51772,58340,53010,PRETRIAL,BURGESS,DARYLL,JAMAR,Male,African-American,06/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +51772,58340,53010,PRETRIAL,BURGESS,DARYLL,JAMAR,Male,African-American,06/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +51772,58340,53010,PRETRIAL,BURGESS,DARYLL,JAMAR,Male,African-American,06/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51755,58317,52988,PRETRIAL,Sookhoo,Sanjay,NULL,Male,African-American,07/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +51755,58317,52988,PRETRIAL,Sookhoo,Sanjay,NULL,Male,African-American,07/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +51755,58317,52988,PRETRIAL,Sookhoo,Sanjay,NULL,Male,African-American,07/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +41518,58331,53001,PRETRIAL,Preston,Melissa,Jean,Female,African-American,01/25/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +41518,58331,53001,PRETRIAL,Preston,Melissa,Jean,Female,African-American,01/25/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +41518,58331,53001,PRETRIAL,Preston,Melissa,Jean,Female,African-American,01/25/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +39858,58344,53013,PRETRIAL,Wahlberg,David,NULL,Male,Caucasian,10/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +39858,58344,53013,PRETRIAL,Wahlberg,David,NULL,Male,Caucasian,10/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +39858,58344,53013,PRETRIAL,Wahlberg,David,NULL,Male,Caucasian,10/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +36196,58334,53004,PRETRIAL,Winter,Carrie,NULL,Female,Caucasian,03/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +36196,58334,53004,PRETRIAL,Winter,Carrie,NULL,Female,Caucasian,03/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +36196,58334,53004,PRETRIAL,Winter,Carrie,NULL,Female,Caucasian,03/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +17607,58326,52996,PRETRIAL,Osorio,Jamie,Alberto,Male,Hispanic,07/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/1/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +17607,58326,52996,PRETRIAL,Osorio,Jamie,Alberto,Male,Hispanic,07/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +17607,58326,52996,PRETRIAL,Osorio,Jamie,Alberto,Male,Hispanic,07/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51751,58313,52984,PRETRIAL,Pratt,Glenika,C,Female,Other,04/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +51751,58313,52984,PRETRIAL,Pratt,Glenika,C,Female,Other,04/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +51751,58313,52984,PRETRIAL,Pratt,Glenika,C,Female,Other,04/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51775,58347,53016,Probation,bevell,allison,NULL,Female,Caucasian,03/19/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/1/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +51775,58347,53016,Probation,bevell,allison,NULL,Female,Caucasian,03/19/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +51775,58347,53016,Probation,bevell,allison,NULL,Female,Caucasian,03/19/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51779,58352,53021,Probation,nazien,wilnique,NULL,Male,Caucasian,05/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/1/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +51779,58352,53021,Probation,nazien,wilnique,NULL,Male,Caucasian,05/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +51779,58352,53021,Probation,nazien,wilnique,NULL,Male,Caucasian,05/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51776,58349,53018,Probation,Tirado,Christopher,NULL,Male,Hispanic,06/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +51776,58349,53018,Probation,Tirado,Christopher,NULL,Male,Hispanic,06/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +51776,58349,53018,Probation,Tirado,Christopher,NULL,Male,Hispanic,06/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51777,58350,53019,Probation,ELBERTH,STEVEN,NULL,Male,Caucasian,04/28/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +51777,58350,53019,Probation,ELBERTH,STEVEN,NULL,Male,Caucasian,04/28/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +51777,58350,53019,Probation,ELBERTH,STEVEN,NULL,Male,Caucasian,04/28/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51757,58321,52991,PRETRIAL,Stover,Wayne,Lee,Male,African-American,01/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +51757,58321,52991,PRETRIAL,Stover,Wayne,Lee,Male,African-American,01/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +51757,58321,52991,PRETRIAL,Stover,Wayne,Lee,Male,African-American,01/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51763,58328,52998,Probation,Mcbride,Daniel,NULL,Male,African-American,01/05/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/1/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +51763,58328,52998,Probation,Mcbride,Daniel,NULL,Male,African-American,01/05/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +51763,58328,52998,Probation,Mcbride,Daniel,NULL,Male,African-American,01/05/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +49159,58342,49957,Probation,Delgado,Frank,NULL,Male,Hispanic,01/31/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/1/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,Copy,1,0 +49159,58342,49957,Probation,Delgado,Frank,NULL,Male,Hispanic,01/31/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/1/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,Copy,1,0 +49159,58342,49957,Probation,Delgado,Frank,NULL,Male,Hispanic,01/31/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +29496,58329,52999,PRETRIAL,DUNCAN,EVERTON,NULL,Male,African-American,10/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +29496,58329,52999,PRETRIAL,DUNCAN,EVERTON,NULL,Male,African-American,10/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +29496,58329,52999,PRETRIAL,DUNCAN,EVERTON,NULL,Male,African-American,10/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51768,58336,53006,Probation,Chavez,fidel,NULL,Male,Hispanic,04/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +51768,58336,53006,Probation,Chavez,fidel,NULL,Male,Hispanic,04/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +51768,58336,53006,Probation,Chavez,fidel,NULL,Male,Hispanic,04/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51754,58316,52987,PRETRIAL,Davis,Emma,NULL,Female,Hispanic,06/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/1/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +51754,58316,52987,PRETRIAL,Davis,Emma,NULL,Female,Hispanic,06/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/1/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +51754,58316,52987,PRETRIAL,Davis,Emma,NULL,Female,Hispanic,06/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +51769,58337,53007,Probation,Rivera,Omar,NULL,Male,Hispanic,07/17/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +51769,58337,53007,Probation,Rivera,Omar,NULL,Male,Hispanic,07/17/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +51769,58337,53007,Probation,Rivera,Omar,NULL,Male,Hispanic,07/17/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +27420,58311,52983,PRETRIAL,FLEMING,ANTONE,NULL,Male,African-American,01/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +27420,58311,52983,PRETRIAL,FLEMING,ANTONE,NULL,Male,African-American,01/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +27420,58311,52983,PRETRIAL,FLEMING,ANTONE,NULL,Male,African-American,01/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51773,58341,53011,PRETRIAL,Stjeantatro,Scott,pierre,Male,Caucasian,04/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +51773,58341,53011,PRETRIAL,Stjeantatro,Scott,pierre,Male,Caucasian,04/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +51773,58341,53011,PRETRIAL,Stjeantatro,Scott,pierre,Male,Caucasian,04/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51771,58339,53009,PRETRIAL,Martinez,Carlos,NULL,Male,Hispanic,10/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +51771,58339,53009,PRETRIAL,Martinez,Carlos,NULL,Male,Hispanic,10/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +51771,58339,53009,PRETRIAL,Martinez,Carlos,NULL,Male,Hispanic,10/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +2368,58346,53015,PRETRIAL,SMITH,JEREMY,NULL,Male,African-American,03/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +2368,58346,53015,PRETRIAL,SMITH,JEREMY,NULL,Male,African-American,03/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,4,High,8,Risk of Recidivism,0.75,10,High,New,1,0 +2368,58346,53015,PRETRIAL,SMITH,JEREMY,NULL,Male,African-American,03/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51756,58318,52989,PRETRIAL,Russo,Michael,Alexander,Male,Caucasian,03/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +51756,58318,52989,PRETRIAL,Russo,Michael,Alexander,Male,Caucasian,03/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +51756,58318,52989,PRETRIAL,Russo,Michael,Alexander,Male,Caucasian,03/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51764,58332,53002,Probation,HORVATH,ERWIN,NULL,Male,Caucasian,05/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +51764,58332,53002,Probation,HORVATH,ERWIN,NULL,Male,Caucasian,05/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +51764,58332,53002,Probation,HORVATH,ERWIN,NULL,Male,Caucasian,05/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51759,58323,52993,PRETRIAL,Amboise,James,NULL,Male,African-American,02/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +51759,58323,52993,PRETRIAL,Amboise,James,NULL,Male,African-American,02/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +51759,58323,52993,PRETRIAL,Amboise,James,NULL,Male,African-American,02/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51761,58325,52995,PRETRIAL,knight,Maurice,NULL,Male,African-American,05/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/1/13 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +51761,58325,52995,PRETRIAL,knight,Maurice,NULL,Male,African-American,05/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +51761,58325,52995,PRETRIAL,knight,Maurice,NULL,Male,African-American,05/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/1/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51796,58374,53040,PRETRIAL,Ayoub,Eid,NULL,Male,Caucasian,12/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +51796,58374,53040,PRETRIAL,Ayoub,Eid,NULL,Male,Caucasian,12/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +51796,58374,53040,PRETRIAL,Ayoub,Eid,NULL,Male,Caucasian,12/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51798,58376,53042,PRETRIAL,gonzalez,roberto,NULL,Male,Hispanic,07/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +51798,58376,53042,PRETRIAL,gonzalez,roberto,NULL,Male,Hispanic,07/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +51798,58376,53042,PRETRIAL,gonzalez,roberto,NULL,Male,Hispanic,07/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51790,58367,53033,PRETRIAL,Davis,Timothy,Samuel,Male,African-American,10/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/2/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +51790,58367,53033,PRETRIAL,Davis,Timothy,Samuel,Male,African-American,10/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/2/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +51790,58367,53033,PRETRIAL,Davis,Timothy,Samuel,Male,African-American,10/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51780,58353,53022,PRETRIAL,Hightower,Alexander,NULL,Male,Caucasian,05/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +51780,58353,53022,PRETRIAL,Hightower,Alexander,NULL,Male,Caucasian,05/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +51780,58353,53022,PRETRIAL,Hightower,Alexander,NULL,Male,Caucasian,05/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +1923,58360,1626,PRETRIAL,OLIPHANT,KELVIN,NULL,Male,African-American,09/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,Copy,1,0 +1923,58360,1626,PRETRIAL,OLIPHANT,KELVIN,NULL,Male,African-American,09/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.88,10,High,Copy,1,0 +1923,58360,1626,PRETRIAL,OLIPHANT,KELVIN,NULL,Male,African-American,09/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +21732,58358,20892,PRETRIAL,Oliver,Joshua,Travon,Male,African-American,03/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,Copy,1,0 +21732,58358,20892,PRETRIAL,Oliver,Joshua,Travon,Male,African-American,03/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,Copy,1,0 +21732,58358,20892,PRETRIAL,Oliver,Joshua,Travon,Male,African-American,03/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +48340,58362,53029,PRETRIAL,WORTHY,SAMMY,NULL,Male,African-American,04/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +48340,58362,53029,PRETRIAL,WORTHY,SAMMY,NULL,Male,African-American,04/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +48340,58362,53029,PRETRIAL,WORTHY,SAMMY,NULL,Male,African-American,04/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +42967,58363,50602,PRETRIAL,francis,juliet,NULL,Female,African-American,06/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.16,8,High,Copy,1,0 +42967,58363,50602,PRETRIAL,francis,juliet,NULL,Female,African-American,06/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.17,7,Medium,Copy,1,0 +42967,58363,50602,PRETRIAL,francis,juliet,NULL,Female,African-American,06/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +51793,58370,53036,PRETRIAL,Chevelon,Kenauld,NULL,Male,Other,11/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +51793,58370,53036,PRETRIAL,Chevelon,Kenauld,NULL,Male,Other,11/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +51793,58370,53036,PRETRIAL,Chevelon,Kenauld,NULL,Male,Other,11/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51784,58357,53026,PRETRIAL,WILLIAMS,BRIAN,E,Male,African-American,04/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,2,Medium,7,Risk of Violence,-2.79,2,Low,New,1,0 +51784,58357,53026,PRETRIAL,WILLIAMS,BRIAN,E,Male,African-American,04/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +51784,58357,53026,PRETRIAL,WILLIAMS,BRIAN,E,Male,African-American,04/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +51794,58371,53037,PRETRIAL,BARRY,JOSEPH,NULL,Male,African-American,10/13/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +51794,58371,53037,PRETRIAL,BARRY,JOSEPH,NULL,Male,African-American,10/13/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +51794,58371,53037,PRETRIAL,BARRY,JOSEPH,NULL,Male,African-American,10/13/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +12001,58373,53039,PRETRIAL,COVINGTON,GINA,MAE,Female,African-American,09/17/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.15,4,Low,New,1,0 +12001,58373,53039,PRETRIAL,COVINGTON,GINA,MAE,Female,African-American,09/17/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,8,High,New,1,0 +12001,58373,53039,PRETRIAL,COVINGTON,GINA,MAE,Female,African-American,09/17/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51788,58365,53031,PRETRIAL,Espinoza,Porfirio,NULL,Male,Hispanic,09/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +51788,58365,53031,PRETRIAL,Espinoza,Porfirio,NULL,Male,Hispanic,09/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +51788,58365,53031,PRETRIAL,Espinoza,Porfirio,NULL,Male,Hispanic,09/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51782,58355,53024,PRETRIAL,Robinson,Benjamin,Leon,Male,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +51782,58355,53024,PRETRIAL,Robinson,Benjamin,Leon,Male,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +51782,58355,53024,PRETRIAL,Robinson,Benjamin,Leon,Male,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51791,58368,53034,PRETRIAL,Fairclough,Casman,NULL,Male,African-American,06/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +51791,58368,53034,PRETRIAL,Fairclough,Casman,NULL,Male,African-American,06/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +51791,58368,53034,PRETRIAL,Fairclough,Casman,NULL,Male,African-American,06/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51785,58359,53027,PRETRIAL,RIVERA-GARCIA,EDWIN,A,Male,Caucasian,01/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/2/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +51785,58359,53027,PRETRIAL,RIVERA-GARCIA,EDWIN,A,Male,Caucasian,01/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/2/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +51785,58359,53027,PRETRIAL,RIVERA-GARCIA,EDWIN,A,Male,Caucasian,01/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51786,58361,53028,PRETRIAL,Ford,Ian,NULL,Male,African-American,08/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +51786,58361,53028,PRETRIAL,Ford,Ian,NULL,Male,African-American,08/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,4,High,8,Risk of Recidivism,0.18,8,High,New,1,0 +51786,58361,53028,PRETRIAL,Ford,Ian,NULL,Male,African-American,08/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51781,58354,53023,PRETRIAL,Cruz,Carlos,Jose,Male,Hispanic,01/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.46,3,Low,New,1,0 +51781,58354,53023,PRETRIAL,Cruz,Carlos,Jose,Male,Hispanic,01/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.86,10,High,New,1,0 +51781,58354,53023,PRETRIAL,Cruz,Carlos,Jose,Male,Hispanic,01/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51797,58375,53041,PRETRIAL,Francois,Wilkinson,NULL,Male,African-American,03/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +51797,58375,53041,PRETRIAL,Francois,Wilkinson,NULL,Male,African-American,03/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +51797,58375,53041,PRETRIAL,Francois,Wilkinson,NULL,Male,African-American,03/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51789,58366,53032,PRETRIAL,Gonzalez,Pedro,NULL,Male,Hispanic,05/17/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/2/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +51789,58366,53032,PRETRIAL,Gonzalez,Pedro,NULL,Male,Hispanic,05/17/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/2/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +51789,58366,53032,PRETRIAL,Gonzalez,Pedro,NULL,Male,Hispanic,05/17/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51792,58369,53035,PRETRIAL,Smith,Erica,NULL,Male,African-American,12/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +51792,58369,53035,PRETRIAL,Smith,Erica,NULL,Male,African-American,12/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +51792,58369,53035,PRETRIAL,Smith,Erica,NULL,Male,African-American,12/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51783,58356,53025,PRETRIAL,Cowley,Kristina,NULL,Female,Caucasian,08/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/2/13 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +51783,58356,53025,PRETRIAL,Cowley,Kristina,NULL,Female,Caucasian,08/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +51783,58356,53025,PRETRIAL,Cowley,Kristina,NULL,Female,Caucasian,08/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/2/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +15256,58377,53043,PRETRIAL,LAVOIX,SHARLEND,NULL,Male,African-American,12/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,4,High,7,Risk of Violence,-0.14,10,High,New,1,0 +15256,58377,53043,PRETRIAL,LAVOIX,SHARLEND,NULL,Male,African-American,12/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,4,High,8,Risk of Recidivism,1.39,10,High,New,1,0 +15256,58377,53043,PRETRIAL,LAVOIX,SHARLEND,NULL,Male,African-American,12/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +51787,58364,53030,PRETRIAL,NEAL,LATOYA,M,Female,African-American,11/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +51787,58364,53030,PRETRIAL,NEAL,LATOYA,M,Female,African-American,11/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +51787,58364,53030,PRETRIAL,NEAL,LATOYA,M,Female,African-American,11/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +51795,58372,53038,PRETRIAL,Venisss,Lamesha,NULL,Female,African-American,10/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,New,1,0 +51795,58372,53038,PRETRIAL,Venisss,Lamesha,NULL,Female,African-American,10/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,10,High,New,1,0 +51795,58372,53038,PRETRIAL,Venisss,Lamesha,NULL,Female,African-American,10/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51804,58385,53050,PRETRIAL,HALL,MICHELLE,L,Female,African-American,02/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +51804,58385,53050,PRETRIAL,HALL,MICHELLE,L,Female,African-American,02/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +51804,58385,53050,PRETRIAL,HALL,MICHELLE,L,Female,African-American,02/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51807,58390,53055,PRETRIAL,SHAW,JEROME,NULL,Male,African-American,05/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +51807,58390,53055,PRETRIAL,SHAW,JEROME,NULL,Male,African-American,05/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,4,High,8,Risk of Recidivism,0.95,10,High,New,1,0 +51807,58390,53055,PRETRIAL,SHAW,JEROME,NULL,Male,African-American,05/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51803,58384,53049,PRETRIAL,Sanders,Gregory,NULL,Male,African-American,01/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +51803,58384,53049,PRETRIAL,Sanders,Gregory,NULL,Male,African-American,01/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +51803,58384,53049,PRETRIAL,Sanders,Gregory,NULL,Male,African-American,01/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51800,58380,53045,PRETRIAL,Jones,Douglas,NULL,Male,African-American,05/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.2,1,Low,New,1,0 +51800,58380,53045,PRETRIAL,Jones,Douglas,NULL,Male,African-American,05/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +51800,58380,53045,PRETRIAL,Jones,Douglas,NULL,Male,African-American,05/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51805,58387,53052,PRETRIAL,Hall,Latura,NULL,Female,African-American,09/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +51805,58387,53052,PRETRIAL,Hall,Latura,NULL,Female,African-American,09/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +51805,58387,53052,PRETRIAL,Hall,Latura,NULL,Female,African-American,09/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51801,58382,53047,PRETRIAL,TAYLOR,TRAVIS,NULL,Male,African-American,09/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,4,High,7,Risk of Violence,-0.55,10,High,New,1,0 +51801,58382,53047,PRETRIAL,TAYLOR,TRAVIS,NULL,Male,African-American,09/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,4,High,8,Risk of Recidivism,1.12,10,High,New,1,0 +51801,58382,53047,PRETRIAL,TAYLOR,TRAVIS,NULL,Male,African-American,09/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +41111,58389,53054,PRETRIAL,Blake,Delroy,NULL,Male,Other,06/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +41111,58389,53054,PRETRIAL,Blake,Delroy,NULL,Male,Other,06/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +41111,58389,53054,PRETRIAL,Blake,Delroy,NULL,Male,Other,06/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +13097,58386,53051,DRRD,Morgan,Daniel,NULL,Male,Caucasian,04/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,4,High,7,Risk of Violence,-0.7,9,High,New,1,0 +13097,58386,53051,DRRD,Morgan,Daniel,NULL,Male,Caucasian,04/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,4,High,8,Risk of Recidivism,0.24,8,High,New,1,0 +13097,58386,53051,DRRD,Morgan,Daniel,NULL,Male,Caucasian,04/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +18546,58378,17806,PRETRIAL,CARTER,TARIK,DEMTRIUS,Male,African-American,08/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,2,Medium,7,Risk of Violence,-1.51,6,Medium,Copy,1,0 +18546,58378,17806,PRETRIAL,CARTER,TARIK,DEMTRIUS,Male,African-American,08/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,Copy,1,0 +18546,58378,17806,PRETRIAL,CARTER,TARIK,DEMTRIUS,Male,African-American,08/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +51802,58383,53048,PRETRIAL,MALLARD,BRANDON,NULL,Male,African-American,01/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,4,High,7,Risk of Violence,-1.05,8,High,New,1,0 +51802,58383,53048,PRETRIAL,MALLARD,BRANDON,NULL,Male,African-American,01/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,4,High,8,Risk of Recidivism,0.17,8,High,New,1,0 +51802,58383,53048,PRETRIAL,MALLARD,BRANDON,NULL,Male,African-American,01/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51799,58379,53044,PRETRIAL,Cantwell,James,NULL,Male,Caucasian,11/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +51799,58379,53044,PRETRIAL,Cantwell,James,NULL,Male,Caucasian,11/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +51799,58379,53044,PRETRIAL,Cantwell,James,NULL,Male,Caucasian,11/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51806,58388,53053,PRETRIAL,Schultz,David,NULL,Male,African-American,09/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/3/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +51806,58388,53053,PRETRIAL,Schultz,David,NULL,Male,African-American,09/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/3/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +51806,58388,53053,PRETRIAL,Schultz,David,NULL,Male,African-American,09/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/3/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +19056,58381,53046,PRETRIAL,FELDER,TAVARES,NULL,Male,African-American,03/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +19056,58381,53046,PRETRIAL,FELDER,TAVARES,NULL,Male,African-American,03/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +19056,58381,53046,PRETRIAL,FELDER,TAVARES,NULL,Male,African-American,03/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +3570,58418,53081,PRETRIAL,dalonzo,merle,v,Male,Caucasian,03/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +3570,58418,53081,PRETRIAL,dalonzo,merle,v,Male,Caucasian,03/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +3570,58418,53081,PRETRIAL,dalonzo,merle,v,Male,Caucasian,03/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +35352,58432,43832,PRETRIAL,Black,Derrick,NULL,Male,African-American,06/11/90,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/4/13 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +35352,58432,43832,PRETRIAL,Black,Derrick,NULL,Male,African-American,06/11/90,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/4/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +35352,58432,43832,PRETRIAL,Black,Derrick,NULL,Male,African-American,06/11/90,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/4/13 0:00,2,Medium,18,Risk of Failure to Appear,23,4,Low,New,1,0 +51831,58423,53085,PRETRIAL,dygert,erick,NULL,Male,Caucasian,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +51831,58423,53085,PRETRIAL,dygert,erick,NULL,Male,Caucasian,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +51831,58423,53085,PRETRIAL,dygert,erick,NULL,Male,Caucasian,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51833,58425,53087,PRETRIAL,Kirker,Bradley,NULL,Male,Caucasian,08/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +51833,58425,53087,PRETRIAL,Kirker,Bradley,NULL,Male,Caucasian,08/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +51833,58425,53087,PRETRIAL,Kirker,Bradley,NULL,Male,Caucasian,08/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51810,58395,53060,PRETRIAL,DOWNS,EVA,NULL,Female,Other,02/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +51810,58395,53060,PRETRIAL,DOWNS,EVA,NULL,Female,Other,02/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +51810,58395,53060,PRETRIAL,DOWNS,EVA,NULL,Female,Other,02/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51812,58397,53062,PRETRIAL,JACKSON,LLOYD,NULL,Male,African-American,06/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,2,Medium,7,Risk of Violence,-1.39,7,Medium,New,1,0 +51812,58397,53062,PRETRIAL,JACKSON,LLOYD,NULL,Male,African-American,06/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +51812,58397,53062,PRETRIAL,JACKSON,LLOYD,NULL,Male,African-American,06/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,2,Medium,18,Risk of Failure to Appear,38,10,High,New,1,0 +51817,58402,53067,PRETRIAL,Merlo,Robert,Lyle,Male,Caucasian,09/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +51817,58402,53067,PRETRIAL,Merlo,Robert,Lyle,Male,Caucasian,09/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +51817,58402,53067,PRETRIAL,Merlo,Robert,Lyle,Male,Caucasian,09/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +37668,58404,53069,PRETRIAL,CUNNINGHAM,GARY,M,Male,African-American,01/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +37668,58404,53069,PRETRIAL,CUNNINGHAM,GARY,M,Male,African-American,01/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +37668,58404,53069,PRETRIAL,CUNNINGHAM,GARY,M,Male,African-American,01/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51825,58413,53076,PRETRIAL,REID,LATYRUIS,NULL,Male,African-American,04/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +51825,58413,53076,PRETRIAL,REID,LATYRUIS,NULL,Male,African-American,04/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +51825,58413,53076,PRETRIAL,REID,LATYRUIS,NULL,Male,African-American,04/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +44123,58392,53057,PRETRIAL,Padron,Fernando,NULL,Male,Hispanic,01/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +44123,58392,53057,PRETRIAL,Padron,Fernando,NULL,Male,Hispanic,01/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +44123,58392,53057,PRETRIAL,Padron,Fernando,NULL,Male,Hispanic,01/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51822,58409,53074,PRETRIAL,Suarez,David,NULL,Male,Hispanic,02/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +51822,58409,53074,PRETRIAL,Suarez,David,NULL,Male,Hispanic,02/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +51822,58409,53074,PRETRIAL,Suarez,David,NULL,Male,Hispanic,02/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51838,58434,53095,Probation,Linton,Shelby,Antonio,Male,African-American,10/12/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +51838,58434,53095,Probation,Linton,Shelby,Antonio,Male,African-American,10/12/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +51838,58434,53095,Probation,Linton,Shelby,Antonio,Male,African-American,10/12/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51836,58430,53092,PRETRIAL,Bankston,Kadeidra,NULL,Female,African-American,07/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +51836,58430,53092,PRETRIAL,Bankston,Kadeidra,NULL,Female,African-American,07/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +51836,58430,53092,PRETRIAL,Bankston,Kadeidra,NULL,Female,African-American,07/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +43775,58428,53090,Probation,Cameron,Brian,NULL,Male,Caucasian,03/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +43775,58428,53090,Probation,Cameron,Brian,NULL,Male,Caucasian,03/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +43775,58428,53090,Probation,Cameron,Brian,NULL,Male,Caucasian,03/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51814,58399,53064,PRETRIAL,CURI,CARLOS,A,Male,Caucasian,03/29/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +51814,58399,53064,PRETRIAL,CURI,CARLOS,A,Male,Caucasian,03/29/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +51814,58399,53064,PRETRIAL,CURI,CARLOS,A,Male,Caucasian,03/29/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +12368,58391,53056,PRETRIAL,SIMMON,TERRON,NULL,Male,African-American,01/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +12368,58391,53056,PRETRIAL,SIMMON,TERRON,NULL,Male,African-American,01/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,4,High,8,Risk of Recidivism,0.93,10,High,New,1,0 +12368,58391,53056,PRETRIAL,SIMMON,TERRON,NULL,Male,African-American,01/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51840,58436,53097,Probation,SPEAR,KRISTINA,W,Female,Caucasian,07/06/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +51840,58436,53097,Probation,SPEAR,KRISTINA,W,Female,Caucasian,07/06/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +51840,58436,53097,Probation,SPEAR,KRISTINA,W,Female,Caucasian,07/06/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51829,58420,53083,PRETRIAL,rosenberg,eveline,e,Female,Caucasian,09/04/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +51829,58420,53083,PRETRIAL,rosenberg,eveline,e,Female,Caucasian,09/04/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/13 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +51829,58420,53083,PRETRIAL,rosenberg,eveline,e,Female,Caucasian,09/04/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51820,58407,53072,Probation,murphy,lloyd,NULL,Male,African-American,01/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +51820,58407,53072,Probation,murphy,lloyd,NULL,Male,African-American,01/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +51820,58407,53072,Probation,murphy,lloyd,NULL,Male,African-American,01/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51844,58441,53102,Probation,DOSSANTOS,ROGERIO,NULL,Male,Other,03/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +51844,58441,53102,Probation,DOSSANTOS,ROGERIO,NULL,Male,Other,03/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +51844,58441,53102,Probation,DOSSANTOS,ROGERIO,NULL,Male,Other,03/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51809,58394,53059,PRETRIAL,Schwartz,Alexander,NULL,Male,Caucasian,10/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/4/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +51809,58394,53059,PRETRIAL,Schwartz,Alexander,NULL,Male,Caucasian,10/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +51809,58394,53059,PRETRIAL,Schwartz,Alexander,NULL,Male,Caucasian,10/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51036,58412,52178,Probation,Battle,Rochelle,NULL,Female,African-American,02/09/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +51036,58412,52178,Probation,Battle,Rochelle,NULL,Female,African-American,02/09/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +51036,58412,52178,Probation,Battle,Rochelle,NULL,Female,African-American,02/09/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +7574,58415,53078,PRETRIAL,BROWN,CORNELIUS,M,Male,African-American,09/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +7574,58415,53078,PRETRIAL,BROWN,CORNELIUS,M,Male,African-American,09/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,4,High,8,Risk of Recidivism,0.17,8,High,New,1,0 +7574,58415,53078,PRETRIAL,BROWN,CORNELIUS,M,Male,African-American,09/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51837,58433,53094,PRETRIAL,JACKSON,FRANCINE,NULL,Female,Caucasian,12/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/4/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +51837,58433,53094,PRETRIAL,JACKSON,FRANCINE,NULL,Female,Caucasian,12/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +51837,58433,53094,PRETRIAL,JACKSON,FRANCINE,NULL,Female,Caucasian,12/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +51811,58396,53061,PRETRIAL,ROBINSON,BLAKE,NULL,Male,African-American,06/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +51811,58396,53061,PRETRIAL,ROBINSON,BLAKE,NULL,Male,African-American,06/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +51811,58396,53061,PRETRIAL,ROBINSON,BLAKE,NULL,Male,African-American,06/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51818,58403,53068,PRETRIAL,Posey,Marcus,NULL,Male,African-American,08/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/4/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +51818,58403,53068,PRETRIAL,Posey,Marcus,NULL,Male,African-American,08/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +51818,58403,53068,PRETRIAL,Posey,Marcus,NULL,Male,African-American,08/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51827,58417,53080,Probation,Joseph,Charles,NULL,Male,African-American,07/29/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/4/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +51827,58417,53080,Probation,Joseph,Charles,NULL,Male,African-American,07/29/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/4/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +51827,58417,53080,Probation,Joseph,Charles,NULL,Male,African-American,07/29/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44430,58431,53093,PRETRIAL,Black,Jimmy,NULL,Male,African-American,03/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,New,1,0 +44430,58431,53093,PRETRIAL,Black,Jimmy,NULL,Male,African-American,03/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +44430,58431,53093,PRETRIAL,Black,Jimmy,NULL,Male,African-American,03/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51823,58410,53075,PRETRIAL,Florial,Mamose,NULL,Female,African-American,04/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/4/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +51823,58410,53075,PRETRIAL,Florial,Mamose,NULL,Female,African-American,04/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +51823,58410,53075,PRETRIAL,Florial,Mamose,NULL,Female,African-American,04/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51842,58440,53101,PRETRIAL,WALTERS,BRIAN,NULL,Male,Caucasian,07/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +51842,58440,53101,PRETRIAL,WALTERS,BRIAN,NULL,Male,Caucasian,07/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +51842,58440,53101,PRETRIAL,WALTERS,BRIAN,NULL,Male,Caucasian,07/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51816,58401,53066,PRETRIAL,Hadley,Linda,Ann,Female,African-American,02/02/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +51816,58401,53066,PRETRIAL,Hadley,Linda,Ann,Female,African-American,02/02/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +51816,58401,53066,PRETRIAL,Hadley,Linda,Ann,Female,African-American,02/02/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51834,58426,53088,Probation,Thomas,Meguel,NULL,Male,African-American,06/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +51834,58426,53088,Probation,Thomas,Meguel,NULL,Male,African-American,06/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +51834,58426,53088,Probation,Thomas,Meguel,NULL,Male,African-American,06/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +23410,58422,34050,Probation,ponczkowski,david,NULL,Male,Caucasian,02/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,4,High,7,Risk of Violence,-1.15,8,High,Copy,1,0 +23410,58422,34050,Probation,ponczkowski,david,NULL,Male,Caucasian,02/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,Copy,1,0 +23410,58422,34050,Probation,ponczkowski,david,NULL,Male,Caucasian,02/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,4,High,18,Risk of Failure to Appear,35,9,High,Copy,1,0 +51832,58424,53086,PRETRIAL,Bianchini,Pedro,NULL,Male,Hispanic,07/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +51832,58424,53086,PRETRIAL,Bianchini,Pedro,NULL,Male,Hispanic,07/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/13 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +51832,58424,53086,PRETRIAL,Bianchini,Pedro,NULL,Male,Hispanic,07/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +40929,58411,40579,PRETRIAL,Velazquez,Jayson,NULL,Male,Caucasian,11/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,Copy,1,0 +40929,58411,40579,PRETRIAL,Velazquez,Jayson,NULL,Male,Caucasian,11/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,Copy,1,0 +40929,58411,40579,PRETRIAL,Velazquez,Jayson,NULL,Male,Caucasian,11/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +51841,58437,53098,Probation,mILANO,tHOMAS,jAMES,Male,Caucasian,09/29/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +51841,58437,53098,Probation,mILANO,tHOMAS,jAMES,Male,Caucasian,09/29/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +51841,58437,53098,Probation,mILANO,tHOMAS,jAMES,Male,Caucasian,09/29/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51813,58398,53063,PRETRIAL,REED,MICHAEL,KEVIN,Male,Caucasian,01/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/4/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +51813,58398,53063,PRETRIAL,REED,MICHAEL,KEVIN,Male,Caucasian,01/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/4/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +51813,58398,53063,PRETRIAL,REED,MICHAEL,KEVIN,Male,Caucasian,01/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51826,58416,53079,PRETRIAL,Barnes,Gregory,NULL,Male,African-American,07/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +51826,58416,53079,PRETRIAL,Barnes,Gregory,NULL,Male,African-American,07/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +51826,58416,53079,PRETRIAL,Barnes,Gregory,NULL,Male,African-American,07/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51815,58400,53065,PRETRIAL,CASTEEL,GEOVANNI,DAVON,Male,African-American,09/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +51815,58400,53065,PRETRIAL,CASTEEL,GEOVANNI,DAVON,Male,African-American,09/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +51815,58400,53065,PRETRIAL,CASTEEL,GEOVANNI,DAVON,Male,African-American,09/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51839,58435,53096,Probation,THOMPSON,BRETT,NULL,Male,Caucasian,10/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/4/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +51839,58435,53096,Probation,THOMPSON,BRETT,NULL,Male,Caucasian,10/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +51839,58435,53096,Probation,THOMPSON,BRETT,NULL,Male,Caucasian,10/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +3759,58414,53077,PRETRIAL,FULLARD,CORNELL,NULL,Male,African-American,05/03/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.38,3,Low,New,1,0 +3759,58414,53077,PRETRIAL,FULLARD,CORNELL,NULL,Male,African-American,05/03/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +3759,58414,53077,PRETRIAL,FULLARD,CORNELL,NULL,Male,African-American,05/03/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51835,58427,53089,Probation,Rivas,Erick,NULL,Male,Hispanic,05/11/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +51835,58427,53089,Probation,Rivas,Erick,NULL,Male,Hispanic,05/11/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +51835,58427,53089,Probation,Rivas,Erick,NULL,Male,Hispanic,05/11/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +8968,58429,53091,PRETRIAL,LANE,DEMONDA,NULL,Female,African-American,09/12/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +8968,58429,53091,PRETRIAL,LANE,DEMONDA,NULL,Female,African-American,09/12/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,10,High,New,1,0 +8968,58429,53091,PRETRIAL,LANE,DEMONDA,NULL,Female,African-American,09/12/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,9,High,New,1,0 +51808,58393,53058,PRETRIAL,Andreu,Arthur,NULL,Male,Caucasian,02/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/4/13 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +51808,58393,53058,PRETRIAL,Andreu,Arthur,NULL,Male,Caucasian,02/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +51808,58393,53058,PRETRIAL,Andreu,Arthur,NULL,Male,Caucasian,02/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/4/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51819,58406,53071,PRETRIAL,Jean-Francois,Karl,NULL,Male,African-American,03/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +51819,58406,53071,PRETRIAL,Jean-Francois,Karl,NULL,Male,African-American,03/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +51819,58406,53071,PRETRIAL,Jean-Francois,Karl,NULL,Male,African-American,03/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51845,58442,53103,PRETRIAL,RAYSOR,ROGER,ALEXANDER,Male,African-American,01/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +51845,58442,53103,PRETRIAL,RAYSOR,ROGER,ALEXANDER,Male,African-American,01/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +51845,58442,53103,PRETRIAL,RAYSOR,ROGER,ALEXANDER,Male,African-American,01/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51133,58463,52293,PRETRIAL,Lee,Jong,Chul,Male,Caucasian,04/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/5/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,Copy,1,0 +51133,58463,52293,PRETRIAL,Lee,Jong,Chul,Male,Caucasian,04/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/5/13 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,Copy,1,0 +51133,58463,52293,PRETRIAL,Lee,Jong,Chul,Male,Caucasian,04/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +44922,58471,53125,PRETRIAL,Odonnell,Steven,D,Male,Caucasian,09/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +44922,58471,53125,PRETRIAL,Odonnell,Steven,D,Male,Caucasian,09/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +44922,58471,53125,PRETRIAL,Odonnell,Steven,D,Male,Caucasian,09/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51850,58450,53109,PRETRIAL,Butler,Reginald,Elsworth,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +51850,58450,53109,PRETRIAL,Butler,Reginald,Elsworth,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +51850,58450,53109,PRETRIAL,Butler,Reginald,Elsworth,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51863,58466,53120,Probation,Zimmerman,Lawrence,NULL,Male,Caucasian,09/08/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +51863,58466,53120,Probation,Zimmerman,Lawrence,NULL,Male,Caucasian,09/08/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +51863,58466,53120,Probation,Zimmerman,Lawrence,NULL,Male,Caucasian,09/08/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +43018,58445,44250,PRETRIAL,Waller,Damien,NULL,Male,African-American,02/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,4,High,7,Risk of Violence,-0.94,9,High,Copy,1,0 +43018,58445,44250,PRETRIAL,Waller,Damien,NULL,Male,African-American,02/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,4,High,8,Risk of Recidivism,0.6,9,High,Copy,1,0 +43018,58445,44250,PRETRIAL,Waller,Damien,NULL,Male,African-American,02/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +8739,8816,8273,PRETRIAL,HARWOOD,CHRISTOPHER,NULL,Male,Caucasian,06/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +8739,8816,8273,PRETRIAL,HARWOOD,CHRISTOPHER,NULL,Male,Caucasian,06/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +8739,8816,8273,PRETRIAL,HARWOOD,CHRISTOPHER,NULL,Male,Caucasian,06/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51848,58447,53106,PRETRIAL,Russell,Jonathan,L,Male,African-American,07/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +51848,58447,53106,PRETRIAL,Russell,Jonathan,L,Male,African-American,07/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +51848,58447,53106,PRETRIAL,Russell,Jonathan,L,Male,African-American,07/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51853,58452,53111,PRETRIAL,Mcafee,Steven,NULL,Male,Caucasian,02/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +51853,58452,53111,PRETRIAL,Mcafee,Steven,NULL,Male,Caucasian,02/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.07,10,High,New,1,0 +51853,58452,53111,PRETRIAL,Mcafee,Steven,NULL,Male,Caucasian,02/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51857,58456,53114,PRETRIAL,BRUNETTO,TROY,R,Male,Caucasian,05/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +51857,58456,53114,PRETRIAL,BRUNETTO,TROY,R,Male,Caucasian,05/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +51857,58456,53114,PRETRIAL,BRUNETTO,TROY,R,Male,Caucasian,05/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +36600,58477,53131,PRETRIAL,Rhone,Derryel,NULL,Male,African-American,02/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +36600,58477,53131,PRETRIAL,Rhone,Derryel,NULL,Male,African-American,02/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +36600,58477,53131,PRETRIAL,Rhone,Derryel,NULL,Male,African-American,02/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51846,58443,53104,PRETRIAL,MORENCY,EVENSON,NULL,Male,African-American,06/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +51846,58443,53104,PRETRIAL,MORENCY,EVENSON,NULL,Male,African-American,06/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,4,High,8,Risk of Recidivism,0.55,9,High,New,1,0 +51846,58443,53104,PRETRIAL,MORENCY,EVENSON,NULL,Male,African-American,06/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51868,58473,53127,PRETRIAL,Curtis,Peticia,Katreca,Female,African-American,10/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/13 0:00,4,High,7,Risk of Violence,0.04,10,High,New,1,0 +51868,58473,53127,PRETRIAL,Curtis,Peticia,Katreca,Female,African-American,10/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/13 0:00,4,High,8,Risk of Recidivism,0.63,10,High,New,1,0 +51868,58473,53127,PRETRIAL,Curtis,Peticia,Katreca,Female,African-American,10/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +51860,58459,53117,Probation,HUSEY,CHARLES,SCOTT,Male,Caucasian,08/31/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +51860,58459,53117,Probation,HUSEY,CHARLES,SCOTT,Male,Caucasian,08/31/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +51860,58459,53117,Probation,HUSEY,CHARLES,SCOTT,Male,Caucasian,08/31/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51862,58461,53119,Probation,Torres,Daniel,NULL,Male,Hispanic,11/14/83,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +51862,58461,53119,Probation,Torres,Daniel,NULL,Male,Hispanic,11/14/83,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +51862,58461,53119,Probation,Torres,Daniel,NULL,Male,Hispanic,11/14/83,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51865,58468,53122,PRETRIAL,Wheeler,Brian,NULL,Male,Caucasian,02/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +51865,58468,53122,PRETRIAL,Wheeler,Brian,NULL,Male,Caucasian,02/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +51865,58468,53122,PRETRIAL,Wheeler,Brian,NULL,Male,Caucasian,02/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +41751,58462,51127,PRETRIAL,Boulahanis,Alexander,NULL,Male,Caucasian,11/07/77,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +41751,58462,51127,PRETRIAL,Boulahanis,Alexander,NULL,Male,Caucasian,11/07/77,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-0.2,5,Medium,New,1,0 +41751,58462,51127,PRETRIAL,Boulahanis,Alexander,NULL,Male,Caucasian,11/07/77,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +51870,58475,53129,PRETRIAL,Hernandez-Castro,Roberto,NULL,Male,Hispanic,05/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +51870,58475,53129,PRETRIAL,Hernandez-Castro,Roberto,NULL,Male,Hispanic,05/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +51870,58475,53129,PRETRIAL,Hernandez-Castro,Roberto,NULL,Male,Hispanic,05/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50375,58454,51386,PRETRIAL,ROSS,CURTIS,NULL,Male,African-American,02/20/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,Copy,1,0 +50375,58454,51386,PRETRIAL,ROSS,CURTIS,NULL,Male,African-American,02/20/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,Copy,1,0 +50375,58454,51386,PRETRIAL,ROSS,CURTIS,NULL,Male,African-American,02/20/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +51866,58470,53124,Probation,SMITH,WILKENSON,NULL,Male,African-American,11/06/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +51866,58470,53124,Probation,SMITH,WILKENSON,NULL,Male,African-American,11/06/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +51866,58470,53124,Probation,SMITH,WILKENSON,NULL,Male,African-American,11/06/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51867,58472,53126,DRRD,Myles,Jordi,NULL,Male,African-American,08/17/93,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,2/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +51867,58472,53126,DRRD,Myles,Jordi,NULL,Male,African-American,08/17/93,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,2/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,6,Medium,New,1,0 +51867,58472,53126,DRRD,Myles,Jordi,NULL,Male,African-American,08/17/93,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,2/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,New,1,0 +51851,58449,53108,PRETRIAL,Brayboy,Thelbert,NULL,Male,African-American,11/17/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/5/13 0:00,2,Medium,7,Risk of Violence,-2.94,2,Low,New,1,0 +51851,58449,53108,PRETRIAL,Brayboy,Thelbert,NULL,Male,African-American,11/17/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +51851,58449,53108,PRETRIAL,Brayboy,Thelbert,NULL,Male,African-American,11/17/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/5/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +41617,58464,51260,PRETRIAL,klein,amanda,NULL,Female,Caucasian,06/27/87,17,All Scales,Intake,English,Conditional Release,Probation,Married,2/5/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +41617,58464,51260,PRETRIAL,klein,amanda,NULL,Female,Caucasian,06/27/87,17,All Scales,Intake,English,Conditional Release,Probation,Married,2/5/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +41617,58464,51260,PRETRIAL,klein,amanda,NULL,Female,Caucasian,06/27/87,17,All Scales,Intake,English,Conditional Release,Probation,Married,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +4694,58444,4384,PRETRIAL,Roques,Perle,C,Male,Other,04/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/5/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,Copy,1,0 +4694,58444,4384,PRETRIAL,Roques,Perle,C,Male,Other,04/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/5/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,Copy,1,0 +4694,58444,4384,PRETRIAL,Roques,Perle,C,Male,Other,04/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +47971,58455,53113,PRETRIAL,Ross,Brandon,David,Male,Caucasian,02/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +47971,58455,53113,PRETRIAL,Ross,Brandon,David,Male,Caucasian,02/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +47971,58455,53113,PRETRIAL,Ross,Brandon,David,Male,Caucasian,02/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +45920,58469,53123,PRETRIAL,Smith,Kevin,NULL,Male,African-American,02/14/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +45920,58469,53123,PRETRIAL,Smith,Kevin,NULL,Male,African-American,02/14/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +45920,58469,53123,PRETRIAL,Smith,Kevin,NULL,Male,African-American,02/14/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51849,58448,53107,PRETRIAL,Gay,Gerard,Mineo,Male,African-American,08/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +51849,58448,53107,PRETRIAL,Gay,Gerard,Mineo,Male,African-American,08/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +51849,58448,53107,PRETRIAL,Gay,Gerard,Mineo,Male,African-American,08/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51852,58451,53110,PRETRIAL,Duhaney,Trevor,NULL,Male,Other,02/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/5/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +51852,58451,53110,PRETRIAL,Duhaney,Trevor,NULL,Male,Other,02/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/5/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +51852,58451,53110,PRETRIAL,Duhaney,Trevor,NULL,Male,Other,02/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51133,58465,52293,PRETRIAL,Lee,Jong,Chul,Male,Caucasian,04/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/5/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,Copy,1,0 +51133,58465,52293,PRETRIAL,Lee,Jong,Chul,Male,Caucasian,04/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/5/13 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,Copy,1,0 +51133,58465,52293,PRETRIAL,Lee,Jong,Chul,Male,Caucasian,04/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +51861,58460,53118,Probation,Palloo,Strishtaam,NULL,Male,Other,07/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +51861,58460,53118,Probation,Palloo,Strishtaam,NULL,Male,Other,07/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +51861,58460,53118,Probation,Palloo,Strishtaam,NULL,Male,Other,07/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51869,58474,53128,PRETRIAL,CARLISLE,WILLIAM,NULL,Male,Caucasian,10/01/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +51869,58474,53128,PRETRIAL,CARLISLE,WILLIAM,NULL,Male,Caucasian,10/01/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +51869,58474,53128,PRETRIAL,CARLISLE,WILLIAM,NULL,Male,Caucasian,10/01/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51886,58476,53130,DRRD,Moore,Patrick,Bernard,Male,African-American,04/18/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.77,9,High,New,1,0 +51886,58476,53130,DRRD,Moore,Patrick,Bernard,Male,African-American,04/18/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,6,Medium,New,1,0 +51886,58476,53130,DRRD,Moore,Patrick,Bernard,Male,African-American,04/18/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +51864,58467,53121,Probation,stone,jessica,NULL,Female,African-American,09/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +51864,58467,53121,Probation,stone,jessica,NULL,Female,African-American,09/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +51864,58467,53121,Probation,stone,jessica,NULL,Female,African-American,09/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51847,58446,53105,PRETRIAL,Puertas,Roberto,NULL,Male,Caucasian,01/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +51847,58446,53105,PRETRIAL,Puertas,Roberto,NULL,Male,Caucasian,01/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +51847,58446,53105,PRETRIAL,Puertas,Roberto,NULL,Male,Caucasian,01/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51856,58453,53112,PRETRIAL,RAPHAEL,KEON,WASHINGTON,Male,African-American,08/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +51856,58453,53112,PRETRIAL,RAPHAEL,KEON,WASHINGTON,Male,African-American,08/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +51856,58453,53112,PRETRIAL,RAPHAEL,KEON,WASHINGTON,Male,African-American,08/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51924,58518,53171,PRETRIAL,Scott,Ronald,NULL,Male,African-American,07/01/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +51924,58518,53171,PRETRIAL,Scott,Ronald,NULL,Male,African-American,07/01/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +51924,58518,53171,PRETRIAL,Scott,Ronald,NULL,Male,African-American,07/01/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +10298,58523,53176,DRRD,Perry,Jamal,NULL,Male,African-American,01/21/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +10298,58523,53176,DRRD,Perry,Jamal,NULL,Male,African-American,01/21/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +10298,58523,53176,DRRD,Perry,Jamal,NULL,Male,African-American,01/21/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +37450,58525,41365,PRETRIAL,MALLORY,COURTNEY,NULL,Male,African-American,03/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,4,High,7,Risk of Violence,-0.77,9,High,Copy,1,0 +37450,58525,41365,PRETRIAL,MALLORY,COURTNEY,NULL,Male,African-American,03/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,4,High,8,Risk of Recidivism,0.35,8,High,Copy,1,0 +37450,58525,41365,PRETRIAL,MALLORY,COURTNEY,NULL,Male,African-American,03/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,4,High,18,Risk of Failure to Appear,28,7,Medium,Copy,1,0 +51901,58495,53149,PRETRIAL,Reed,Travis,toshama,Male,African-American,12/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/6/13 0:00,2,Medium,7,Risk of Violence,-2.83,2,Low,New,1,0 +51901,58495,53149,PRETRIAL,Reed,Travis,toshama,Male,African-American,12/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +51901,58495,53149,PRETRIAL,Reed,Travis,toshama,Male,African-American,12/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/6/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51182,58497,52345,PRETRIAL,CHACON,RICHARD,NULL,Male,Hispanic,08/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,Copy,1,0 +51182,58497,52345,PRETRIAL,CHACON,RICHARD,NULL,Male,Hispanic,08/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,Copy,1,0 +51182,58497,52345,PRETRIAL,CHACON,RICHARD,NULL,Male,Hispanic,08/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +51908,58502,53155,DRRD,Fisher Jr,Frankie,Lang,Male,African-American,11/13/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.96,9,High,New,1,0 +51908,58502,53155,DRRD,Fisher Jr,Frankie,Lang,Male,African-American,11/13/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,7,Medium,New,1,0 +51908,58502,53155,DRRD,Fisher Jr,Frankie,Lang,Male,African-American,11/13/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +51910,58504,53157,Probation,Parry,Lois,NULL,Female,Caucasian,06/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +51910,58504,53157,Probation,Parry,Lois,NULL,Female,Caucasian,06/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,9,High,New,1,0 +51910,58504,53157,Probation,Parry,Lois,NULL,Female,Caucasian,06/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51896,58490,53144,PRETRIAL,Mercado-Comacho,Edwin,NULL,Male,Hispanic,04/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +51896,58490,53144,PRETRIAL,Mercado-Comacho,Edwin,NULL,Male,Hispanic,04/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +51896,58490,53144,PRETRIAL,Mercado-Comacho,Edwin,NULL,Male,Hispanic,04/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51913,58507,53160,PRETRIAL,Ross,Tiara,NULL,Female,African-American,03/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/6/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +51913,58507,53160,PRETRIAL,Ross,Tiara,NULL,Female,African-American,03/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/6/13 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +51913,58507,53160,PRETRIAL,Ross,Tiara,NULL,Female,African-American,03/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +17427,58486,53140,PRETRIAL,BELL,BARRY,NULL,Male,African-American,01/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/6/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +17427,58486,53140,PRETRIAL,BELL,BARRY,NULL,Male,African-American,01/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/6/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +17427,58486,53140,PRETRIAL,BELL,BARRY,NULL,Male,African-American,01/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51917,58511,53164,Probation,hendry,brian,NULL,Male,Caucasian,03/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +51917,58511,53164,Probation,hendry,brian,NULL,Male,Caucasian,03/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +51917,58511,53164,Probation,hendry,brian,NULL,Male,Caucasian,03/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51922,58516,53169,Probation,Balkin,Karen,NULL,Female,Caucasian,12/28/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/6/13 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +51922,58516,53169,Probation,Balkin,Karen,NULL,Female,Caucasian,12/28/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/6/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +51922,58516,53169,Probation,Balkin,Karen,NULL,Female,Caucasian,12/28/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51888,58478,53132,PRETRIAL,Garland,Elijah,NULL,Male,African-American,01/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +51888,58478,53132,PRETRIAL,Garland,Elijah,NULL,Male,African-American,01/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +51888,58478,53132,PRETRIAL,Garland,Elijah,NULL,Male,African-American,01/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51920,58514,53167,PRETRIAL,Falcon,Javier,Eduardo,Male,Hispanic,06/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +51920,58514,53167,PRETRIAL,Falcon,Javier,Eduardo,Male,Hispanic,06/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +51920,58514,53167,PRETRIAL,Falcon,Javier,Eduardo,Male,Hispanic,06/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51892,58485,53139,PRETRIAL,Joesph,Fabienne,NULL,Female,Other,02/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +51892,58485,53139,PRETRIAL,Joesph,Fabienne,NULL,Female,Other,02/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +51892,58485,53139,PRETRIAL,Joesph,Fabienne,NULL,Female,Other,02/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51904,58499,53152,Probation,Makarski,Maria,NULL,Female,Hispanic,12/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +51904,58499,53152,Probation,Makarski,Maria,NULL,Female,Hispanic,12/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,8,High,New,1,0 +51904,58499,53152,Probation,Makarski,Maria,NULL,Female,Hispanic,12/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51911,58506,53159,Probation,MCCABE,JOHN,NULL,Male,Caucasian,11/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +51911,58506,53159,Probation,MCCABE,JOHN,NULL,Male,Caucasian,11/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +51911,58506,53159,Probation,MCCABE,JOHN,NULL,Male,Caucasian,11/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51897,58491,53145,PRETRIAL,Turner,Tommy,NULL,Male,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +51897,58491,53145,PRETRIAL,Turner,Tommy,NULL,Male,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.74,10,High,New,1,0 +51897,58491,53145,PRETRIAL,Turner,Tommy,NULL,Male,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +18100,58493,53147,PRETRIAL,CRESPO,FREDDY,ANTONIO,Male,African-American,11/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +18100,58493,53147,PRETRIAL,CRESPO,FREDDY,ANTONIO,Male,African-American,11/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,4,High,8,Risk of Recidivism,1.05,10,High,New,1,0 +18100,58493,53147,PRETRIAL,CRESPO,FREDDY,ANTONIO,Male,African-American,11/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51929,58527,53178,Probation,shaw,kelvin,NULL,Male,African-American,09/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.01,4,Low,New,1,0 +51929,58527,53178,Probation,shaw,kelvin,NULL,Male,African-American,09/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +51929,58527,53178,Probation,shaw,kelvin,NULL,Male,African-American,09/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51894,58488,53142,PRETRIAL,TISMEUS,LUC,NULL,Male,Other,09/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +51894,58488,53142,PRETRIAL,TISMEUS,LUC,NULL,Male,Other,09/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +51894,58488,53142,PRETRIAL,TISMEUS,LUC,NULL,Male,Other,09/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51927,58522,53175,Probation,MORONY,JEFFREY,SCOTT,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +51927,58522,53175,Probation,MORONY,JEFFREY,SCOTT,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +51927,58522,53175,Probation,MORONY,JEFFREY,SCOTT,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51915,58509,53162,Probation,JOHNSON,JESSICA,LEIGH,Female,Caucasian,03/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +51915,58509,53162,Probation,JOHNSON,JESSICA,LEIGH,Female,Caucasian,03/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +51915,58509,53162,Probation,JOHNSON,JESSICA,LEIGH,Female,Caucasian,03/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51890,58480,53134,PRETRIAL,Dudas,John,Michael,Male,Caucasian,03/23/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +51890,58480,53134,PRETRIAL,Dudas,John,Michael,Male,Caucasian,03/23/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +51890,58480,53134,PRETRIAL,Dudas,John,Michael,Male,Caucasian,03/23/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +10247,58483,53137,PRETRIAL,Mills,Shain,NULL,Male,African-American,11/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +10247,58483,53137,PRETRIAL,Mills,Shain,NULL,Male,African-American,11/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +10247,58483,53137,PRETRIAL,Mills,Shain,NULL,Male,African-American,11/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51905,58501,53154,Probation,broder,shahar,NULL,Male,Caucasian,09/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +51905,58501,53154,Probation,broder,shahar,NULL,Male,Caucasian,09/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +51905,58501,53154,Probation,broder,shahar,NULL,Male,Caucasian,09/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51891,58482,53136,PRETRIAL,Picard,Philip,NULL,Male,Caucasian,08/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +51891,58482,53136,PRETRIAL,Picard,Philip,NULL,Male,Caucasian,08/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +51891,58482,53136,PRETRIAL,Picard,Philip,NULL,Male,Caucasian,08/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51923,58517,53170,Probation,Turturo,Frank,NULL,Male,Caucasian,12/11/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/6/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +51923,58517,53170,Probation,Turturo,Frank,NULL,Male,Caucasian,12/11/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/6/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +51923,58517,53170,Probation,Turturo,Frank,NULL,Male,Caucasian,12/11/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51895,58489,53143,PRETRIAL,Sloan,Aurora,NULL,Female,Caucasian,06/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +51895,58489,53143,PRETRIAL,Sloan,Aurora,NULL,Female,Caucasian,06/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +51895,58489,53143,PRETRIAL,Sloan,Aurora,NULL,Female,Caucasian,06/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51902,58496,53150,PRETRIAL,Watson,Mikhail,A,Male,Other,06/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +51902,58496,53150,PRETRIAL,Watson,Mikhail,A,Male,Other,06/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +51902,58496,53150,PRETRIAL,Watson,Mikhail,A,Male,Other,06/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51928,58524,53177,Probation,Musgrave,Joseph,NULL,Male,Caucasian,03/08/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +51928,58524,53177,Probation,Musgrave,Joseph,NULL,Male,Caucasian,03/08/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +51928,58524,53177,Probation,Musgrave,Joseph,NULL,Male,Caucasian,03/08/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51903,58498,53151,Probation,Wiggins,Rodney,NULL,Male,African-American,10/11/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/6/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +51903,58498,53151,Probation,Wiggins,Rodney,NULL,Male,African-American,10/11/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/6/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +51903,58498,53151,Probation,Wiggins,Rodney,NULL,Male,African-American,10/11/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51921,58515,53168,Probation,Neal,Shamika,Hilda,Female,African-American,09/19/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +51921,58515,53168,Probation,Neal,Shamika,Hilda,Female,African-American,09/19/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +51921,58515,53168,Probation,Neal,Shamika,Hilda,Female,African-American,09/19/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51900,58494,53148,PRETRIAL,Rattray,Latosha,NULL,Female,African-American,12/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,7,Risk of Violence,-2.78,2,Low,New,1,0 +51900,58494,53148,PRETRIAL,Rattray,Latosha,NULL,Female,African-American,12/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,6,Medium,New,1,0 +51900,58494,53148,PRETRIAL,Rattray,Latosha,NULL,Female,African-American,12/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51918,58512,53165,PRETRIAL,DELVA,KEN,NULL,Male,African-American,08/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +51918,58512,53165,PRETRIAL,DELVA,KEN,NULL,Male,African-American,08/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +51918,58512,53165,PRETRIAL,DELVA,KEN,NULL,Male,African-American,08/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +43765,58519,53172,Probation,baitz,natalie,NULL,Female,Caucasian,01/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +43765,58519,53172,Probation,baitz,natalie,NULL,Female,Caucasian,01/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,8,High,New,1,0 +43765,58519,53172,Probation,baitz,natalie,NULL,Female,Caucasian,01/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51889,58479,53133,PRETRIAL,SPENCE,TERRENCE,NULL,Male,African-American,11/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +51889,58479,53133,PRETRIAL,SPENCE,TERRENCE,NULL,Male,African-American,11/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +51889,58479,53133,PRETRIAL,SPENCE,TERRENCE,NULL,Male,African-American,11/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +51919,58513,53166,PRETRIAL,Mohammad,Attique,NULL,Male,Caucasian,12/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +51919,58513,53166,PRETRIAL,Mohammad,Attique,NULL,Male,Caucasian,12/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +51919,58513,53166,PRETRIAL,Mohammad,Attique,NULL,Male,Caucasian,12/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51898,58492,53146,PRETRIAL,WALTERS,DONOVAN,NULL,Male,Caucasian,01/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +51898,58492,53146,PRETRIAL,WALTERS,DONOVAN,NULL,Male,Caucasian,01/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +51898,58492,53146,PRETRIAL,WALTERS,DONOVAN,NULL,Male,Caucasian,01/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +6462,58484,53138,PRETRIAL,JOHNSON,CRAIG,NULL,Male,African-American,11/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +6462,58484,53138,PRETRIAL,JOHNSON,CRAIG,NULL,Male,African-American,11/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +6462,58484,53138,PRETRIAL,JOHNSON,CRAIG,NULL,Male,African-American,11/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +51893,58487,53141,PRETRIAL,Scott,Brian,NULL,Male,African-American,09/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,7,Risk of Violence,-1.87,5,Medium,New,1,0 +51893,58487,53141,PRETRIAL,Scott,Brian,NULL,Male,African-American,09/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +51893,58487,53141,PRETRIAL,Scott,Brian,NULL,Male,African-American,09/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51914,58508,53161,Probation,Hunter,Keith,NULL,Male,African-American,09/19/69,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,2/6/13 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +51914,58508,53161,Probation,Hunter,Keith,NULL,Male,African-American,09/19/69,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,2/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +51914,58508,53161,Probation,Hunter,Keith,NULL,Male,African-American,09/19/69,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,2/6/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51940,58542,53192,PRETRIAL,SANDS,EMMET,NULL,Male,African-American,03/24/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +51940,58542,53192,PRETRIAL,SANDS,EMMET,NULL,Male,African-American,03/24/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +51940,58542,53192,PRETRIAL,SANDS,EMMET,NULL,Male,African-American,03/24/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51951,58557,53206,PRETRIAL,Morales,Angie,NULL,Female,Caucasian,04/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +51951,58557,53206,PRETRIAL,Morales,Angie,NULL,Female,Caucasian,04/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +51951,58557,53206,PRETRIAL,Morales,Angie,NULL,Female,Caucasian,04/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51931,58529,53179,PRETRIAL,Gilliam,Aaron,NULL,Male,African-American,07/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +51931,58529,53179,PRETRIAL,Gilliam,Aaron,NULL,Male,African-American,07/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +51931,58529,53179,PRETRIAL,Gilliam,Aaron,NULL,Male,African-American,07/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +16964,58536,53186,PRETRIAL,LAMONS,TREVOR,NULL,Male,African-American,09/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +16964,58536,53186,PRETRIAL,LAMONS,TREVOR,NULL,Male,African-American,09/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +16964,58536,53186,PRETRIAL,LAMONS,TREVOR,NULL,Male,African-American,09/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51958,58563,53211,PRETRIAL,Diz,Jose,Alfredo,Male,Caucasian,01/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2,4,Low,New,1,0 +51958,58563,53211,PRETRIAL,Diz,Jose,Alfredo,Male,Caucasian,01/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +51958,58563,53211,PRETRIAL,Diz,Jose,Alfredo,Male,Caucasian,01/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51964,58570,53218,Probation,Hansen,Heidi,NULL,Female,Caucasian,06/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +51964,58570,53218,Probation,Hansen,Heidi,NULL,Female,Caucasian,06/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +51964,58570,53218,Probation,Hansen,Heidi,NULL,Female,Caucasian,06/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51947,58550,53199,Probation,HENRY,D'AUNDRE,NULL,Male,African-American,06/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +51947,58550,53199,Probation,HENRY,D'AUNDRE,NULL,Male,African-American,06/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +51947,58550,53199,Probation,HENRY,D'AUNDRE,NULL,Male,African-American,06/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +34002,58528,33126,PRETRIAL,HOWELL,RODERICK,KELVIN JR,Male,African-American,05/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,4,High,7,Risk of Violence,-1.17,8,High,Copy,1,0 +34002,58528,33126,PRETRIAL,HOWELL,RODERICK,KELVIN JR,Male,African-American,05/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,4,High,8,Risk of Recidivism,0.36,9,High,Copy,1,0 +34002,58528,33126,PRETRIAL,HOWELL,RODERICK,KELVIN JR,Male,African-American,05/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +51965,58571,53219,PRETRIAL,Wilson,Andre,Tavarious,Male,African-American,11/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +51965,58571,53219,PRETRIAL,Wilson,Andre,Tavarious,Male,African-American,11/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +51965,58571,53219,PRETRIAL,Wilson,Andre,Tavarious,Male,African-American,11/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51971,58578,53226,Probation,Soto,Elmer,NULL,Male,Hispanic,07/23/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +51971,58578,53226,Probation,Soto,Elmer,NULL,Male,Hispanic,07/23/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +51971,58578,53226,Probation,Soto,Elmer,NULL,Male,Hispanic,07/23/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51943,58544,53194,PRETRIAL,Wright,Franklin,NULL,Male,African-American,03/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +51943,58544,53194,PRETRIAL,Wright,Franklin,NULL,Male,African-American,03/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +51943,58544,53194,PRETRIAL,Wright,Franklin,NULL,Male,African-American,03/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +32253,58555,53204,PRETRIAL,Larzak,Christine,L,Female,Caucasian,02/12/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/7/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +32253,58555,53204,PRETRIAL,Larzak,Christine,L,Female,Caucasian,02/12/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +32253,58555,53204,PRETRIAL,Larzak,Christine,L,Female,Caucasian,02/12/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51967,58573,53221,Probation,Lopez,Gloria,Esther,Female,Hispanic,01/12/58,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/7/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +51967,58573,53221,Probation,Lopez,Gloria,Esther,Female,Hispanic,01/12/58,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +51967,58573,53221,Probation,Lopez,Gloria,Esther,Female,Hispanic,01/12/58,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51935,58534,53184,PRETRIAL,Wilson,Wilnika,NULL,Female,African-American,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +51935,58534,53184,PRETRIAL,Wilson,Wilnika,NULL,Female,African-American,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +51935,58534,53184,PRETRIAL,Wilson,Wilnika,NULL,Female,African-American,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51948,58552,53201,Probation,FAZAKERLEY,MICHAEL,NULL,Male,Caucasian,11/28/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +51948,58552,53201,Probation,FAZAKERLEY,MICHAEL,NULL,Male,Caucasian,11/28/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-2.64,1,Low,New,1,0 +51948,58552,53201,Probation,FAZAKERLEY,MICHAEL,NULL,Male,Caucasian,11/28/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51959,58565,53213,Probation,fogle,cassandra,NULL,Female,Caucasian,09/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/7/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +51959,58565,53213,Probation,fogle,cassandra,NULL,Female,Caucasian,09/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/7/13 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +51959,58565,53213,Probation,fogle,cassandra,NULL,Female,Caucasian,09/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51953,58560,53208,PRETRIAL,Allmond,Bryon,NULL,Male,Caucasian,12/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +51953,58560,53208,PRETRIAL,Allmond,Bryon,NULL,Male,Caucasian,12/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +51953,58560,53208,PRETRIAL,Allmond,Bryon,NULL,Male,Caucasian,12/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51945,58547,53197,PRETRIAL,Black,Ike,Issac,Male,African-American,08/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +51945,58547,53197,PRETRIAL,Black,Ike,Issac,Male,African-American,08/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +51945,58547,53197,PRETRIAL,Black,Ike,Issac,Male,African-American,08/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +39355,58581,53229,Probation,bellino,jack,NULL,Male,Caucasian,05/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +39355,58581,53229,Probation,bellino,jack,NULL,Male,Caucasian,05/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +39355,58581,53229,Probation,bellino,jack,NULL,Male,Caucasian,05/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51973,58580,53228,Probation,Cruz,Felix,NULL,Male,Hispanic,08/26/83,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Married,2/7/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +51973,58580,53228,Probation,Cruz,Felix,NULL,Male,Hispanic,08/26/83,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Married,2/7/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +51973,58580,53228,Probation,Cruz,Felix,NULL,Male,Hispanic,08/26/83,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Married,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51934,58533,53183,PRETRIAL,Ortiz,Tommy,NULL,Male,Hispanic,01/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +51934,58533,53183,PRETRIAL,Ortiz,Tommy,NULL,Male,Hispanic,01/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +51934,58533,53183,PRETRIAL,Ortiz,Tommy,NULL,Male,Hispanic,01/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +5512,58575,53223,Probation,Caneus,Ephrain,NULL,Male,African-American,03/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +5512,58575,53223,Probation,Caneus,Ephrain,NULL,Male,African-American,03/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +5512,58575,53223,Probation,Caneus,Ephrain,NULL,Male,African-American,03/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51942,58545,53195,PRETRIAL,DAVIS,MARION,NULL,Male,African-American,02/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +51942,58545,53195,PRETRIAL,DAVIS,MARION,NULL,Male,African-American,02/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +51942,58545,53195,PRETRIAL,DAVIS,MARION,NULL,Male,African-American,02/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51950,58554,53203,Probation,remy,heather,NULL,Female,Caucasian,04/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +51950,58554,53203,Probation,remy,heather,NULL,Female,Caucasian,04/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +51950,58554,53203,Probation,remy,heather,NULL,Female,Caucasian,04/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51961,58568,53216,Probation,Martinez,Marvin,Danilo,Male,Hispanic,05/22/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +51961,58568,53216,Probation,Martinez,Marvin,Danilo,Male,Hispanic,05/22/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +51961,58568,53216,Probation,Martinez,Marvin,Danilo,Male,Hispanic,05/22/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51932,58531,53181,PRETRIAL,MIMS,JOSEPH,A,Male,African-American,11/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +51932,58531,53181,PRETRIAL,MIMS,JOSEPH,A,Male,African-American,11/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +51932,58531,53181,PRETRIAL,MIMS,JOSEPH,A,Male,African-American,11/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +51937,58538,53188,PRETRIAL,Hughes,Kristina,NULL,Female,African-American,07/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +51937,58538,53188,PRETRIAL,Hughes,Kristina,NULL,Female,African-American,07/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,8,High,New,1,0 +51937,58538,53188,PRETRIAL,Hughes,Kristina,NULL,Female,African-American,07/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51954,58561,53209,PRETRIAL,rossi,casey,NULL,Female,Caucasian,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +51954,58561,53209,PRETRIAL,rossi,casey,NULL,Female,Caucasian,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +51954,58561,53209,PRETRIAL,rossi,casey,NULL,Female,Caucasian,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51939,58540,53190,PRETRIAL,Rose,Alvin,NULL,Male,African-American,05/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +51939,58540,53190,PRETRIAL,Rose,Alvin,NULL,Male,African-American,05/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +51939,58540,53190,PRETRIAL,Rose,Alvin,NULL,Male,African-American,05/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51952,58559,53207,Probation,Handberry,Henry,NULL,Male,African-American,07/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-2.72,2,Low,New,1,0 +51952,58559,53207,Probation,Handberry,Henry,NULL,Male,African-American,07/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +51952,58559,53207,Probation,Handberry,Henry,NULL,Male,African-American,07/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,New,1,0 +50906,58548,52025,PRETRIAL,DUBOSE,RASHAUN,NULL,Male,African-American,12/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,Copy,1,0 +50906,58548,52025,PRETRIAL,DUBOSE,RASHAUN,NULL,Male,African-American,12/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,Copy,1,0 +50906,58548,52025,PRETRIAL,DUBOSE,RASHAUN,NULL,Male,African-American,12/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +29528,58551,53200,PRETRIAL,Bertrand,Latavia,NULL,Female,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +29528,58551,53200,PRETRIAL,Bertrand,Latavia,NULL,Female,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,4,High,8,Risk of Recidivism,1.14,10,High,New,1,0 +29528,58551,53200,PRETRIAL,Bertrand,Latavia,NULL,Female,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51930,58530,53180,PRETRIAL,MAYOL,CELLIE,NULL,Female,Caucasian,11/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-2.79,2,Low,New,1,0 +51930,58530,53180,PRETRIAL,MAYOL,CELLIE,NULL,Female,Caucasian,11/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +51930,58530,53180,PRETRIAL,MAYOL,CELLIE,NULL,Female,Caucasian,11/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51963,58569,53217,PRETRIAL,Reynolds,Robert,NULL,Male,Caucasian,03/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +51963,58569,53217,PRETRIAL,Reynolds,Robert,NULL,Male,Caucasian,03/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +51963,58569,53217,PRETRIAL,Reynolds,Robert,NULL,Male,Caucasian,03/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +25420,58543,53193,PRETRIAL,PINNOCK,JOVAN,NULL,Male,African-American,01/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +25420,58543,53193,PRETRIAL,PINNOCK,JOVAN,NULL,Male,African-American,01/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,4,High,8,Risk of Recidivism,0.25,8,High,New,1,0 +25420,58543,53193,PRETRIAL,PINNOCK,JOVAN,NULL,Male,African-American,01/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51970,58577,53225,Probation,ORANGE,JERMANE,LASHAWN,Male,African-American,01/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-2.63,2,Low,New,1,0 +51970,58577,53225,Probation,ORANGE,JERMANE,LASHAWN,Male,African-American,01/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +51970,58577,53225,Probation,ORANGE,JERMANE,LASHAWN,Male,African-American,01/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +45252,58556,53205,PRETRIAL,Vasilut,Monica,NULL,Female,Caucasian,06/01/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/7/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +45252,58556,53205,PRETRIAL,Vasilut,Monica,NULL,Female,Caucasian,06/01/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +45252,58556,53205,PRETRIAL,Vasilut,Monica,NULL,Female,Caucasian,06/01/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51966,58572,53220,PRETRIAL,Roberts,Paul,Wesley,Male,African-American,08/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +51966,58572,53220,PRETRIAL,Roberts,Paul,Wesley,Male,African-American,08/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +51966,58572,53220,PRETRIAL,Roberts,Paul,Wesley,Male,African-American,08/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51782,58535,53185,PRETRIAL,Robinson,Benjamin,Leon,Male,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +51782,58535,53185,PRETRIAL,Robinson,Benjamin,Leon,Male,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +51782,58535,53185,PRETRIAL,Robinson,Benjamin,Leon,Male,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51957,58564,53212,Probation,EVANS,CHANEL,PATRICE,Female,African-American,12/01/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +51957,58564,53212,Probation,EVANS,CHANEL,PATRICE,Female,African-American,12/01/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +51957,58564,53212,Probation,EVANS,CHANEL,PATRICE,Female,African-American,12/01/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51936,58537,53187,PRETRIAL,Noel,Henry,NULL,Male,African-American,08/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +51936,58537,53187,PRETRIAL,Noel,Henry,NULL,Male,African-American,08/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +51936,58537,53187,PRETRIAL,Noel,Henry,NULL,Male,African-American,08/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +31059,58562,53210,PRETRIAL,Leone,Vincent,Anthony,Male,Caucasian,12/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-2.23,4,Low,New,1,0 +31059,58562,53210,PRETRIAL,Leone,Vincent,Anthony,Male,Caucasian,12/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +31059,58562,53210,PRETRIAL,Leone,Vincent,Anthony,Male,Caucasian,12/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51972,58579,53227,Probation,Londono,Carranza,NULL,Male,Hispanic,06/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +51972,58579,53227,Probation,Londono,Carranza,NULL,Male,Hispanic,06/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +51972,58579,53227,Probation,Londono,Carranza,NULL,Male,Hispanic,06/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51941,58541,53191,PRETRIAL,Deal,Ashley,NULL,Female,Caucasian,01/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +51941,58541,53191,PRETRIAL,Deal,Ashley,NULL,Female,Caucasian,01/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,7,Medium,New,1,0 +51941,58541,53191,PRETRIAL,Deal,Ashley,NULL,Female,Caucasian,01/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +46606,58558,47032,PRETRIAL,Tyndale,Damien,Michael,Male,African-American,01/02/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +46606,58558,47032,PRETRIAL,Tyndale,Damien,Michael,Male,African-American,01/02/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +46606,58558,47032,PRETRIAL,Tyndale,Damien,Michael,Male,African-American,01/02/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +51969,58576,53224,PRETRIAL,MORENO,JORGE,NULL,Male,Hispanic,09/15/57,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +51969,58576,53224,PRETRIAL,MORENO,JORGE,NULL,Male,Hispanic,09/15/57,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +51969,58576,53224,PRETRIAL,MORENO,JORGE,NULL,Male,Hispanic,09/15/57,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51933,58532,53182,PRETRIAL,Fields,Brian,NULL,Male,African-American,01/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +51933,58532,53182,PRETRIAL,Fields,Brian,NULL,Male,African-American,01/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +51933,58532,53182,PRETRIAL,Fields,Brian,NULL,Male,African-American,01/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51962,58567,53215,PRETRIAL,Hawks,Marques,NULL,Male,African-American,03/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,4,High,7,Risk of Violence,-0.66,9,High,New,1,0 +51962,58567,53215,PRETRIAL,Hawks,Marques,NULL,Male,African-American,03/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,4,High,8,Risk of Recidivism,1.34,10,High,New,1,0 +51962,58567,53215,PRETRIAL,Hawks,Marques,NULL,Male,African-American,03/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51938,58539,53189,PRETRIAL,Robinson,Cheryl,NULL,Female,African-American,12/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +51938,58539,53189,PRETRIAL,Robinson,Cheryl,NULL,Female,African-American,12/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,9,High,New,1,0 +51938,58539,53189,PRETRIAL,Robinson,Cheryl,NULL,Female,African-American,12/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51944,58546,53196,PRETRIAL,Plews,Keith,NULL,Male,Caucasian,12/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +51944,58546,53196,PRETRIAL,Plews,Keith,NULL,Male,Caucasian,12/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +51944,58546,53196,PRETRIAL,Plews,Keith,NULL,Male,Caucasian,12/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51949,58553,53202,Probation,Woodbine,Kemar,NULL,Male,African-American,01/14/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/7/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +51949,58553,53202,Probation,Woodbine,Kemar,NULL,Male,African-American,01/14/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/7/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +51949,58553,53202,Probation,Woodbine,Kemar,NULL,Male,African-American,01/14/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52014,58618,53261,PRETRIAL,Cash,Kenneth,NULL,Male,Caucasian,01/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,2/8/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +52014,58618,53261,PRETRIAL,Cash,Kenneth,NULL,Male,Caucasian,01/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,2/8/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +52014,58618,53261,PRETRIAL,Cash,Kenneth,NULL,Male,Caucasian,01/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51984,58595,53241,PRETRIAL,Powell,Varian,NULL,Male,African-American,08/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +51984,58595,53241,PRETRIAL,Powell,Varian,NULL,Male,African-American,08/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +51984,58595,53241,PRETRIAL,Powell,Varian,NULL,Male,African-American,08/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +15735,58604,53249,PRETRIAL,Lee,Jasmine,K,Female,African-American,12/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +15735,58604,53249,PRETRIAL,Lee,Jasmine,K,Female,African-American,12/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +15735,58604,53249,PRETRIAL,Lee,Jasmine,K,Female,African-American,12/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51981,58592,53238,PRETRIAL,Stephenson,Eric,Westley,Male,Other,03/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +51981,58592,53238,PRETRIAL,Stephenson,Eric,Westley,Male,Other,03/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +51981,58592,53238,PRETRIAL,Stephenson,Eric,Westley,Male,Other,03/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52008,58609,53254,DRRD,Wesley,Toussaint,NULL,Male,African-American,01/23/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/8/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +52008,58609,53254,DRRD,Wesley,Toussaint,NULL,Male,African-American,01/23/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,6,Medium,New,1,0 +52008,58609,53254,DRRD,Wesley,Toussaint,NULL,Male,African-American,01/23/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/8/13 0:00,2,Medium,18,Risk of Failure to Appear,16,1,Low,New,1,0 +51978,58588,53234,PRETRIAL,Burrows,Jermaine,Demetris,Male,African-American,02/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +51978,58588,53234,PRETRIAL,Burrows,Jermaine,Demetris,Male,African-American,02/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +51978,58588,53234,PRETRIAL,Burrows,Jermaine,Demetris,Male,African-American,02/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52011,58613,53256,PRETRIAL,Marceau,Michael,NULL,Male,Hispanic,07/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/8/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +52011,58613,53256,PRETRIAL,Marceau,Michael,NULL,Male,Hispanic,07/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +52011,58613,53256,PRETRIAL,Marceau,Michael,NULL,Male,Hispanic,07/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +51975,58583,53230,PRETRIAL,Mcneil,Tony,NULL,Male,African-American,11/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +51975,58583,53230,PRETRIAL,Mcneil,Tony,NULL,Male,African-American,11/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +51975,58583,53230,PRETRIAL,Mcneil,Tony,NULL,Male,African-American,11/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52010,58614,53257,DRRD,George,Chilove,None,Male,African-American,06/15/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.15,8,High,New,1,0 +52010,58614,53257,DRRD,George,Chilove,None,Male,African-American,06/15/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,7,Medium,New,1,0 +52010,58614,53257,DRRD,George,Chilove,None,Male,African-American,06/15/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +12452,58621,53264,PRETRIAL,Yee,Fernando,NULL,Male,African-American,07/20/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,2,Medium,7,Risk of Violence,-2.76,2,Low,New,1,0 +12452,58621,53264,PRETRIAL,Yee,Fernando,NULL,Male,African-American,07/20/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +12452,58621,53264,PRETRIAL,Yee,Fernando,NULL,Male,African-American,07/20/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +48223,58585,48898,PRETRIAL,Smith,Oshane,Oran,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/8/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,Copy,1,0 +48223,58585,48898,PRETRIAL,Smith,Oshane,Oran,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,Copy,1,0 +48223,58585,48898,PRETRIAL,Smith,Oshane,Oran,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +52001,58600,53246,PRETRIAL,Uvarov,Aleksander,NULL,Male,Caucasian,03/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +52001,58600,53246,PRETRIAL,Uvarov,Aleksander,NULL,Male,Caucasian,03/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +52001,58600,53246,PRETRIAL,Uvarov,Aleksander,NULL,Male,Caucasian,03/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52005,58606,53251,Probation,Berke,Andrea,NULL,Female,Caucasian,02/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/8/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +52005,58606,53251,Probation,Berke,Andrea,NULL,Female,Caucasian,02/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +52005,58606,53251,Probation,Berke,Andrea,NULL,Female,Caucasian,02/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +10137,58629,53272,PRETRIAL,gerena,william,NULL,Male,Caucasian,07/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/8/13 0:00,4,High,7,Risk of Violence,-0.48,10,High,New,1,0 +10137,58629,53272,PRETRIAL,gerena,william,NULL,Male,Caucasian,07/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/8/13 0:00,4,High,8,Risk of Recidivism,0.92,10,High,New,1,0 +10137,58629,53272,PRETRIAL,gerena,william,NULL,Male,Caucasian,07/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/8/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +51982,58593,53239,PRETRIAL,Hoover,Edward,Jose,Male,Caucasian,06/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +51982,58593,53239,PRETRIAL,Hoover,Edward,Jose,Male,Caucasian,06/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +51982,58593,53239,PRETRIAL,Hoover,Edward,Jose,Male,Caucasian,06/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52007,58608,53253,Probation,JOHNSON,ANTONIO,CORTEZ,Male,African-American,08/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.57,2,Low,New,1,0 +52007,58608,53253,Probation,JOHNSON,ANTONIO,CORTEZ,Male,African-American,08/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +52007,58608,53253,Probation,JOHNSON,ANTONIO,CORTEZ,Male,African-American,08/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +52020,58627,53270,PRETRIAL,Burca,Sonia,NULL,Female,Caucasian,06/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +52020,58627,53270,PRETRIAL,Burca,Sonia,NULL,Female,Caucasian,06/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +52020,58627,53270,PRETRIAL,Burca,Sonia,NULL,Female,Caucasian,06/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +44066,58611,53255,PRETRIAL,Espinal,John,NULL,Male,Caucasian,06/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/8/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +44066,58611,53255,PRETRIAL,Espinal,John,NULL,Male,Caucasian,06/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/8/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +44066,58611,53255,PRETRIAL,Espinal,John,NULL,Male,Caucasian,06/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51979,58590,53236,PRETRIAL,Spetsieris,Michael,NULL,Male,Caucasian,12/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/8/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +51979,58590,53236,PRETRIAL,Spetsieris,Michael,NULL,Male,Caucasian,12/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/8/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +51979,58590,53236,PRETRIAL,Spetsieris,Michael,NULL,Male,Caucasian,12/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +2055,58616,53259,PRETRIAL,JONES,MYRON,NULL,Male,African-American,07/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +2055,58616,53259,PRETRIAL,JONES,MYRON,NULL,Male,African-American,07/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +2055,58616,53259,PRETRIAL,JONES,MYRON,NULL,Male,African-American,07/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +34206,58610,42129,Probation,Botkin,Scott,Paul,Male,Caucasian,10/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.55,3,Low,Copy,1,0 +34206,58610,42129,Probation,Botkin,Scott,Paul,Male,Caucasian,10/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,Copy,1,0 +34206,58610,42129,Probation,Botkin,Scott,Paul,Male,Caucasian,10/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +9014,58582,8546,PRETRIAL,George,Cleve,NULL,Male,African-American,11/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,Copy,1,0 +9014,58582,8546,PRETRIAL,George,Cleve,NULL,Male,African-American,11/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,Copy,1,0 +9014,58582,8546,PRETRIAL,George,Cleve,NULL,Male,African-American,11/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +52013,58617,53260,PRETRIAL,Alejo-Dominguez,Wilfredo,NULL,Male,Hispanic,05/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +52013,58617,53260,PRETRIAL,Alejo-Dominguez,Wilfredo,NULL,Male,Hispanic,05/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +52013,58617,53260,PRETRIAL,Alejo-Dominguez,Wilfredo,NULL,Male,Hispanic,05/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +6277,58589,53235,PRETRIAL,Johnson,Jerry,NULL,Male,African-American,12/15/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +6277,58589,53235,PRETRIAL,Johnson,Jerry,NULL,Male,African-American,12/15/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +6277,58589,53235,PRETRIAL,Johnson,Jerry,NULL,Male,African-American,12/15/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +48897,54552,49649,PRETRIAL,JOHNSON,JAMES,MICHAEL,Male,Caucasian,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +48897,54552,49649,PRETRIAL,JOHNSON,JAMES,MICHAEL,Male,Caucasian,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,4,High,8,Risk of Recidivism,0.55,9,High,New,1,0 +48897,54552,49649,PRETRIAL,JOHNSON,JAMES,MICHAEL,Male,Caucasian,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52003,58603,53248,PRETRIAL,Gonzalez,Marcus,NULL,Male,Hispanic,11/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +52003,58603,53248,PRETRIAL,Gonzalez,Marcus,NULL,Male,Hispanic,11/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +52003,58603,53248,PRETRIAL,Gonzalez,Marcus,NULL,Male,Hispanic,11/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +30250,58626,53269,Probation,lindner,kimberly,NULL,Female,Caucasian,08/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +30250,58626,53269,Probation,lindner,kimberly,NULL,Female,Caucasian,08/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +30250,58626,53269,Probation,lindner,kimberly,NULL,Female,Caucasian,08/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +7602,58584,53231,PRETRIAL,CARTER,JOSE,NULL,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/8/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +7602,58584,53231,PRETRIAL,CARTER,JOSE,NULL,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +7602,58584,53231,PRETRIAL,CARTER,JOSE,NULL,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52002,58601,53247,PRETRIAL,Polanco,Jairo,Naviz,Male,Hispanic,10/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +52002,58601,53247,PRETRIAL,Polanco,Jairo,Naviz,Male,Hispanic,10/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +52002,58601,53247,PRETRIAL,Polanco,Jairo,Naviz,Male,Hispanic,10/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51977,58587,53233,PRETRIAL,Rigaud,Ariana,NULL,Female,African-American,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/8/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +51977,58587,53233,PRETRIAL,Rigaud,Ariana,NULL,Female,African-American,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +51977,58587,53233,PRETRIAL,Rigaud,Ariana,NULL,Female,African-American,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52004,58605,53250,Probation,scala,joseph,NULL,Male,Caucasian,09/21/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +52004,58605,53250,Probation,scala,joseph,NULL,Male,Caucasian,09/21/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +52004,58605,53250,Probation,scala,joseph,NULL,Male,Caucasian,09/21/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51976,58586,53232,PRETRIAL,Broadway,Eric,NULL,Male,Caucasian,11/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/8/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +51976,58586,53232,PRETRIAL,Broadway,Eric,NULL,Male,Caucasian,11/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +51976,58586,53232,PRETRIAL,Broadway,Eric,NULL,Male,Caucasian,11/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52016,58620,53263,Probation,Pimentel,Ralph,NULL,Male,Hispanic,10/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +52016,58620,53263,Probation,Pimentel,Ralph,NULL,Male,Hispanic,10/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +52016,58620,53263,Probation,Pimentel,Ralph,NULL,Male,Hispanic,10/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52006,58607,53252,Probation,castro,martha,NULL,Female,Hispanic,04/09/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/8/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +52006,58607,53252,Probation,castro,martha,NULL,Female,Hispanic,04/09/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/8/13 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +52006,58607,53252,Probation,castro,martha,NULL,Female,Hispanic,04/09/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51347,58602,52530,PRETRIAL,SINISTERRA,JORGE,NULL,Male,Hispanic,04/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,Copy,1,0 +51347,58602,52530,PRETRIAL,SINISTERRA,JORGE,NULL,Male,Hispanic,04/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,Copy,1,0 +51347,58602,52530,PRETRIAL,SINISTERRA,JORGE,NULL,Male,Hispanic,04/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +52012,58615,53258,PRETRIAL,PABON,DOMINIC,NULL,Male,Hispanic,01/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +52012,58615,53258,PRETRIAL,PABON,DOMINIC,NULL,Male,Hispanic,01/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +52012,58615,53258,PRETRIAL,PABON,DOMINIC,NULL,Male,Hispanic,01/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51983,58594,53240,PRETRIAL,Ware,Leroy,NULL,Male,African-American,06/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +51983,58594,53240,PRETRIAL,Ware,Leroy,NULL,Male,African-American,06/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +51983,58594,53240,PRETRIAL,Ware,Leroy,NULL,Male,African-American,06/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +14487,58612,13862,Probation,SCOTT,BERNARD,NULL,Male,African-American,05/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,2/8/13 0:00,4,High,7,Risk of Violence,-0.98,9,High,Copy,1,0 +14487,58612,13862,Probation,SCOTT,BERNARD,NULL,Male,African-American,05/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,2/8/13 0:00,4,High,8,Risk of Recidivism,0.25,8,High,Copy,1,0 +14487,58612,13862,Probation,SCOTT,BERNARD,NULL,Male,African-American,05/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,2/8/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +52018,58623,53266,Probation,Richardson,Gregory,NULL,Male,Caucasian,10/26/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/8/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +52018,58623,53266,Probation,Richardson,Gregory,NULL,Male,Caucasian,10/26/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/8/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +52018,58623,53266,Probation,Richardson,Gregory,NULL,Male,Caucasian,10/26/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +1918,58628,53271,PRETRIAL,OBRIEN,JOHN,NULL,Male,Caucasian,07/20/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +1918,58628,53271,PRETRIAL,OBRIEN,JOHN,NULL,Male,Caucasian,07/20/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +1918,58628,53271,PRETRIAL,OBRIEN,JOHN,NULL,Male,Caucasian,07/20/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51986,58599,53245,PRETRIAL,Farr,Clee,NULL,Male,Caucasian,12/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/8/13 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +51986,58599,53245,PRETRIAL,Farr,Clee,NULL,Male,Caucasian,12/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/8/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +51986,58599,53245,PRETRIAL,Farr,Clee,NULL,Male,Caucasian,12/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51980,58591,53237,PRETRIAL,pena,Luis,Raul,Male,Hispanic,07/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/8/13 0:00,2,Medium,7,Risk of Violence,-3.09,1,Low,New,1,0 +51980,58591,53237,PRETRIAL,pena,Luis,Raul,Male,Hispanic,07/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +51980,58591,53237,PRETRIAL,pena,Luis,Raul,Male,Hispanic,07/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/8/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +44871,58644,45013,PRETRIAL,GOODMAN,KENNETH,NULL,Male,African-American,12/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,Copy,1,0 +44871,58644,45013,PRETRIAL,GOODMAN,KENNETH,NULL,Male,African-American,12/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,Copy,1,0 +44871,58644,45013,PRETRIAL,GOODMAN,KENNETH,NULL,Male,African-American,12/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +52041,58657,53297,PRETRIAL,Cruse,Leevon,NULL,Male,African-American,06/13/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +52041,58657,53297,PRETRIAL,Cruse,Leevon,NULL,Male,African-American,06/13/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +52041,58657,53297,PRETRIAL,Cruse,Leevon,NULL,Male,African-American,06/13/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +34944,58636,53278,Probation,salomon,eclaire,NULL,Male,African-American,07/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +34944,58636,53278,Probation,salomon,eclaire,NULL,Male,African-American,07/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +34944,58636,53278,Probation,salomon,eclaire,NULL,Male,African-American,07/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +52035,58649,53290,PRETRIAL,King,Aleshea,M,Female,African-American,04/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +52035,58649,53290,PRETRIAL,King,Aleshea,M,Female,African-American,04/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +52035,58649,53290,PRETRIAL,King,Aleshea,M,Female,African-American,04/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52024,58633,53276,PRETRIAL,Wilkinson,Kimiko,NULL,Male,African-American,12/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +52024,58633,53276,PRETRIAL,Wilkinson,Kimiko,NULL,Male,African-American,12/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +52024,58633,53276,PRETRIAL,Wilkinson,Kimiko,NULL,Male,African-American,12/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52029,58641,53283,PRETRIAL,Baldocchi,Albert,NULL,Male,Caucasian,01/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +52029,58641,53283,PRETRIAL,Baldocchi,Albert,NULL,Male,Caucasian,01/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +52029,58641,53283,PRETRIAL,Baldocchi,Albert,NULL,Male,Caucasian,01/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52040,58654,53295,PRETRIAL,GRAF,MATTHEW,LEE,Male,Caucasian,08/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +52040,58654,53295,PRETRIAL,GRAF,MATTHEW,LEE,Male,Caucasian,08/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +52040,58654,53295,PRETRIAL,GRAF,MATTHEW,LEE,Male,Caucasian,08/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52038,58652,53293,PRETRIAL,Bennington,George,NULL,Male,Caucasian,02/06/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/9/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +52038,58652,53293,PRETRIAL,Bennington,George,NULL,Male,Caucasian,02/06/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +52038,58652,53293,PRETRIAL,Bennington,George,NULL,Male,Caucasian,02/06/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/9/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52031,58643,53285,PRETRIAL,Capers,James,Edward,Male,African-American,02/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +52031,58643,53285,PRETRIAL,Capers,James,Edward,Male,African-American,02/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +52031,58643,53285,PRETRIAL,Capers,James,Edward,Male,African-American,02/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +39518,58647,53288,PRETRIAL,Varnum,Daniel,NULL,Male,Caucasian,03/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +39518,58647,53288,PRETRIAL,Varnum,Daniel,NULL,Male,Caucasian,03/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +39518,58647,53288,PRETRIAL,Varnum,Daniel,NULL,Male,Caucasian,03/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +33278,58656,32376,PRETRIAL,BRYANT,DEMETRIUS,NULL,Female,African-American,08/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/13 0:00,2,Medium,7,Risk of Violence,-2.73,2,Low,Copy,1,0 +33278,58656,32376,PRETRIAL,BRYANT,DEMETRIUS,NULL,Female,African-American,08/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,Copy,1,0 +33278,58656,32376,PRETRIAL,BRYANT,DEMETRIUS,NULL,Female,African-American,08/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +52028,58640,53282,PRETRIAL,Aman,Donovan,NULL,Male,African-American,11/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +52028,58640,53282,PRETRIAL,Aman,Donovan,NULL,Male,African-American,11/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +52028,58640,53282,PRETRIAL,Aman,Donovan,NULL,Male,African-American,11/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52022,58631,53274,PRETRIAL,Young,Tracey,NULL,Male,African-American,01/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +52022,58631,53274,PRETRIAL,Young,Tracey,NULL,Male,African-American,01/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +52022,58631,53274,PRETRIAL,Young,Tracey,NULL,Male,African-American,01/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52026,58638,53280,PRETRIAL,BALAN,ALEXANDER,NULL,Male,African-American,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +52026,58638,53280,PRETRIAL,BALAN,ALEXANDER,NULL,Male,African-American,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +52026,58638,53280,PRETRIAL,BALAN,ALEXANDER,NULL,Male,African-American,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +34854,58637,53279,PRETRIAL,CALDERARO,ANDREW,NULL,Male,Caucasian,10/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +34854,58637,53279,PRETRIAL,CALDERARO,ANDREW,NULL,Male,Caucasian,10/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +34854,58637,53279,PRETRIAL,CALDERARO,ANDREW,NULL,Male,Caucasian,10/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52032,58645,53286,PRETRIAL,Forchin,Kymar,Andre,Male,Other,10/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +52032,58645,53286,PRETRIAL,Forchin,Kymar,Andre,Male,Other,10/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +52032,58645,53286,PRETRIAL,Forchin,Kymar,Andre,Male,Other,10/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52030,58642,53284,PRETRIAL,Orne,Jodelyn,NULL,Male,African-American,09/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +52030,58642,53284,PRETRIAL,Orne,Jodelyn,NULL,Male,African-American,09/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +52030,58642,53284,PRETRIAL,Orne,Jodelyn,NULL,Male,African-American,09/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +1810,58635,1509,PRETRIAL,PETITHOMME,JOSUE,NULL,Male,Caucasian,10/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,Copy,1,0 +1810,58635,1509,PRETRIAL,PETITHOMME,JOSUE,NULL,Male,Caucasian,10/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,Copy,1,0 +1810,58635,1509,PRETRIAL,PETITHOMME,JOSUE,NULL,Male,Caucasian,10/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +52036,58650,53291,PRETRIAL,JOSEPH,JAY,KEARSCH,Male,Caucasian,01/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +52036,58650,53291,PRETRIAL,JOSEPH,JAY,KEARSCH,Male,Caucasian,01/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +52036,58650,53291,PRETRIAL,JOSEPH,JAY,KEARSCH,Male,Caucasian,01/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52025,58634,53277,PRETRIAL,WALLER,MATTHEW,DEHN,Male,African-American,12/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +52025,58634,53277,PRETRIAL,WALLER,MATTHEW,DEHN,Male,African-American,12/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +52025,58634,53277,PRETRIAL,WALLER,MATTHEW,DEHN,Male,African-American,12/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52037,58651,53292,PRETRIAL,Rosume,Windeline,NULL,Female,African-American,09/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +52037,58651,53292,PRETRIAL,Rosume,Windeline,NULL,Female,African-American,09/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,7,Medium,New,1,0 +52037,58651,53292,PRETRIAL,Rosume,Windeline,NULL,Female,African-American,09/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30936,58630,53273,PRETRIAL,Asbury,LaRicky,NULL,Male,African-American,12/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +30936,58630,53273,PRETRIAL,Asbury,LaRicky,NULL,Male,African-American,12/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +30936,58630,53273,PRETRIAL,Asbury,LaRicky,NULL,Male,African-American,12/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52034,58648,53289,PRETRIAL,ALEXANDER,JONATHAN,ARCE,Male,Caucasian,08/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +52034,58648,53289,PRETRIAL,ALEXANDER,JONATHAN,ARCE,Male,Caucasian,08/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +52034,58648,53289,PRETRIAL,ALEXANDER,JONATHAN,ARCE,Male,Caucasian,08/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +33245,58655,53296,PRETRIAL,Maxwell,Stephen,NULL,Male,African-American,09/02/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +33245,58655,53296,PRETRIAL,Maxwell,Stephen,NULL,Male,African-American,09/02/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +33245,58655,53296,PRETRIAL,Maxwell,Stephen,NULL,Male,African-American,09/02/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52023,58632,53275,PRETRIAL,Monsalve,Jordan,NULL,Male,Caucasian,04/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +52023,58632,53275,PRETRIAL,Monsalve,Jordan,NULL,Male,Caucasian,04/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +52023,58632,53275,PRETRIAL,Monsalve,Jordan,NULL,Male,Caucasian,04/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52027,58639,53281,PRETRIAL,Benjamin,Abnel,NULL,Male,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +52027,58639,53281,PRETRIAL,Benjamin,Abnel,NULL,Male,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +52027,58639,53281,PRETRIAL,Benjamin,Abnel,NULL,Male,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52033,58646,53287,PRETRIAL,Ramos,Raphael,NULL,Male,African-American,03/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/9/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +52033,58646,53287,PRETRIAL,Ramos,Raphael,NULL,Male,African-American,03/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/9/13 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +52033,58646,53287,PRETRIAL,Ramos,Raphael,NULL,Male,African-American,03/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/9/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52039,58653,53294,PRETRIAL,Lewis,Ceven,NULL,Male,African-American,04/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +52039,58653,53294,PRETRIAL,Lewis,Ceven,NULL,Male,African-American,04/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +52039,58653,53294,PRETRIAL,Lewis,Ceven,NULL,Male,African-American,04/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52051,58667,53307,PRETRIAL,Ahmed,Hassan,NULL,Male,Other,09/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +52051,58667,53307,PRETRIAL,Ahmed,Hassan,NULL,Male,Other,09/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,1,Low,8,Risk of Recidivism,-2.67,1,Low,New,1,0 +52051,58667,53307,PRETRIAL,Ahmed,Hassan,NULL,Male,Other,09/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52049,58665,53305,PRETRIAL,campbell,arthur,NULL,Male,African-American,01/11/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +52049,58665,53305,PRETRIAL,campbell,arthur,NULL,Male,African-American,01/11/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +52049,58665,53305,PRETRIAL,campbell,arthur,NULL,Male,African-American,01/11/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52044,58660,53300,PRETRIAL,Graf,Lizzette,NULL,Female,Caucasian,12/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +52044,58660,53300,PRETRIAL,Graf,Lizzette,NULL,Female,Caucasian,12/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +52044,58660,53300,PRETRIAL,Graf,Lizzette,NULL,Female,Caucasian,12/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52047,58663,53303,PRETRIAL,Frye,Charles,NULL,Male,Native American,01/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +52047,58663,53303,PRETRIAL,Frye,Charles,NULL,Male,Native American,01/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +52047,58663,53303,PRETRIAL,Frye,Charles,NULL,Male,Native American,01/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52042,58658,53298,PRETRIAL,Billie,Derek,NULL,Male,Native American,02/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +52042,58658,53298,PRETRIAL,Billie,Derek,NULL,Male,Native American,02/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +52042,58658,53298,PRETRIAL,Billie,Derek,NULL,Male,Native American,02/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52050,58666,53306,PRETRIAL,Ryan,Donald,NULL,Male,Caucasian,08/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +52050,58666,53306,PRETRIAL,Ryan,Donald,NULL,Male,Caucasian,08/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +52050,58666,53306,PRETRIAL,Ryan,Donald,NULL,Male,Caucasian,08/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52045,58661,53301,PRETRIAL,JUSTICE,DARIEN,NULL,Male,African-American,05/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +52045,58661,53301,PRETRIAL,JUSTICE,DARIEN,NULL,Male,African-American,05/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +52045,58661,53301,PRETRIAL,JUSTICE,DARIEN,NULL,Male,African-American,05/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52043,58659,53299,PRETRIAL,Dominguez,Joel,NULL,Male,Hispanic,04/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +52043,58659,53299,PRETRIAL,Dominguez,Joel,NULL,Male,Hispanic,04/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +52043,58659,53299,PRETRIAL,Dominguez,Joel,NULL,Male,Hispanic,04/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52046,58662,53302,PRETRIAL,Concepcion,Guadalupe,NULL,Male,Hispanic,12/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +52046,58662,53302,PRETRIAL,Concepcion,Guadalupe,NULL,Male,Hispanic,12/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +52046,58662,53302,PRETRIAL,Concepcion,Guadalupe,NULL,Male,Hispanic,12/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52048,58664,53304,PRETRIAL,STEPHENS,DIRRICK,NULL,Male,African-American,08/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +52048,58664,53304,PRETRIAL,STEPHENS,DIRRICK,NULL,Male,African-American,08/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +52048,58664,53304,PRETRIAL,STEPHENS,DIRRICK,NULL,Male,African-American,08/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +33064,58678,53318,PRETRIAL,Filossaint,Adeler,NULL,Male,Other,11/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,7,Risk of Violence,-0.63,9,High,New,1,0 +33064,58678,53318,PRETRIAL,Filossaint,Adeler,NULL,Male,Other,11/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,8,Risk of Recidivism,0.8,10,High,New,1,0 +33064,58678,53318,PRETRIAL,Filossaint,Adeler,NULL,Male,Other,11/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52068,58685,53325,PRETRIAL,Fodul,Turgay,NULL,Male,Other,07/01/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +52068,58685,53325,PRETRIAL,Fodul,Turgay,NULL,Male,Other,07/01/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/13 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +52068,58685,53325,PRETRIAL,Fodul,Turgay,NULL,Male,Other,07/01/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52077,58699,53337,PRETRIAL,Camilo,Gary,Alberto,Male,Hispanic,12/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +52077,58699,53337,PRETRIAL,Camilo,Gary,Alberto,Male,Hispanic,12/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +52077,58699,53337,PRETRIAL,Camilo,Gary,Alberto,Male,Hispanic,12/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52052,58670,53310,PRETRIAL,Singletary,Ronald,NULL,Male,African-American,06/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/11/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +52052,58670,53310,PRETRIAL,Singletary,Ronald,NULL,Male,African-American,06/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/11/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +52052,58670,53310,PRETRIAL,Singletary,Ronald,NULL,Male,African-American,06/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52054,58672,53312,PRETRIAL,LOWE,KEVIN,NULL,Male,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +52054,58672,53312,PRETRIAL,LOWE,KEVIN,NULL,Male,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +52054,58672,53312,PRETRIAL,LOWE,KEVIN,NULL,Male,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52085,58706,53344,Probation,pence,john,NULL,Male,Caucasian,09/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/11/13 0:00,2,Medium,7,Risk of Violence,-2.89,2,Low,New,1,0 +52085,58706,53344,Probation,pence,john,NULL,Male,Caucasian,09/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +52085,58706,53344,Probation,pence,john,NULL,Male,Caucasian,09/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/11/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52072,58691,53330,PRETRIAL,Cleevens,Frederick,NULL,Male,African-American,08/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +52072,58691,53330,PRETRIAL,Cleevens,Frederick,NULL,Male,African-American,08/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +52072,58691,53330,PRETRIAL,Cleevens,Frederick,NULL,Male,African-American,08/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +52074,58693,53332,PRETRIAL,Echeniquepadilla,Jackson,Douglas,Male,Hispanic,12/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +52074,58693,53332,PRETRIAL,Echeniquepadilla,Jackson,Douglas,Male,Hispanic,12/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +52074,58693,53332,PRETRIAL,Echeniquepadilla,Jackson,Douglas,Male,Hispanic,12/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +47710,58680,53320,PRETRIAL,Hawkins,Herbert,NULL,Male,Caucasian,12/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/11/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +47710,58680,53320,PRETRIAL,Hawkins,Herbert,NULL,Male,Caucasian,12/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +47710,58680,53320,PRETRIAL,Hawkins,Herbert,NULL,Male,Caucasian,12/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +41847,58683,53323,PRETRIAL,Tarquino,Chandler,NULL,Male,Hispanic,12/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,7,Risk of Violence,-0.85,9,High,New,1,0 +41847,58683,53323,PRETRIAL,Tarquino,Chandler,NULL,Male,Hispanic,12/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +41847,58683,53323,PRETRIAL,Tarquino,Chandler,NULL,Male,Hispanic,12/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52081,58701,53339,PRETRIAL,Avramides,Shaneen,NULL,Female,Caucasian,04/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/11/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +52081,58701,53339,PRETRIAL,Avramides,Shaneen,NULL,Female,Caucasian,04/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/11/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +52081,58701,53339,PRETRIAL,Avramides,Shaneen,NULL,Female,Caucasian,04/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52071,58688,53328,PRETRIAL,Rodriguez,Jose,Miguel,Male,Caucasian,07/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.46,3,Low,New,1,0 +52071,58688,53328,PRETRIAL,Rodriguez,Jose,Miguel,Male,Caucasian,07/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +52071,58688,53328,PRETRIAL,Rodriguez,Jose,Miguel,Male,Caucasian,07/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52057,58675,53315,PRETRIAL,DELOTORO,ORLIS,NULL,Male,Caucasian,11/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +52057,58675,53315,PRETRIAL,DELOTORO,ORLIS,NULL,Male,Caucasian,11/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +52057,58675,53315,PRETRIAL,DELOTORO,ORLIS,NULL,Male,Caucasian,11/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52087,58709,53347,Probation,Kulansky,Mark,NULL,Male,Caucasian,02/11/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +52087,58709,53347,Probation,Kulansky,Mark,NULL,Male,Caucasian,02/11/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +52087,58709,53347,Probation,Kulansky,Mark,NULL,Male,Caucasian,02/11/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52088,58710,53348,Probation,TYLER,JAMES,PAUL,Male,Caucasian,05/03/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/11/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +52088,58710,53348,Probation,TYLER,JAMES,PAUL,Male,Caucasian,05/03/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/11/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +52088,58710,53348,Probation,TYLER,JAMES,PAUL,Male,Caucasian,05/03/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +34827,58689,53329,PRETRIAL,JOHNSON,ROBERT,NULL,Male,Caucasian,10/24/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,New,1,0 +34827,58689,53329,PRETRIAL,JOHNSON,ROBERT,NULL,Male,Caucasian,10/24/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +34827,58689,53329,PRETRIAL,JOHNSON,ROBERT,NULL,Male,Caucasian,10/24/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52076,58696,53334,PRETRIAL,Dorsett,Darrelll,NULL,Male,African-American,07/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/11/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +52076,58696,53334,PRETRIAL,Dorsett,Darrelll,NULL,Male,African-American,07/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +52076,58696,53334,PRETRIAL,Dorsett,Darrelll,NULL,Male,African-American,07/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +30485,58703,53341,PRETRIAL,Smith,Antwain,Lamar,Male,African-American,04/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +30485,58703,53341,PRETRIAL,Smith,Antwain,Lamar,Male,African-American,04/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +30485,58703,53341,PRETRIAL,Smith,Antwain,Lamar,Male,African-American,04/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +7560,58668,53308,PRETRIAL,JONES,JOSHUA,ISHUMALE,Male,African-American,04/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +7560,58668,53308,PRETRIAL,JONES,JOSHUA,ISHUMALE,Male,African-American,04/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,8,Risk of Recidivism,0.2,8,High,New,1,0 +7560,58668,53308,PRETRIAL,JONES,JOSHUA,ISHUMALE,Male,African-American,04/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52060,58682,53322,PRETRIAL,CASTRO,RAUL,A,Male,Hispanic,03/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +52060,58682,53322,PRETRIAL,CASTRO,RAUL,A,Male,Hispanic,03/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +52060,58682,53322,PRETRIAL,CASTRO,RAUL,A,Male,Hispanic,03/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52058,58677,53317,PRETRIAL,Slason,Melissa,NULL,Female,Caucasian,08/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/11/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +52058,58677,53317,PRETRIAL,Slason,Melissa,NULL,Female,Caucasian,08/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +52058,58677,53317,PRETRIAL,Slason,Melissa,NULL,Female,Caucasian,08/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52075,58694,53333,PRETRIAL,HOPKINSON,CAROL,NULL,Female,Caucasian,08/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +52075,58694,53333,PRETRIAL,HOPKINSON,CAROL,NULL,Female,Caucasian,08/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +52075,58694,53333,PRETRIAL,HOPKINSON,CAROL,NULL,Female,Caucasian,08/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52055,58673,53313,PRETRIAL,BURROWS,TEDDY,TEDDY,Male,African-American,12/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +52055,58673,53313,PRETRIAL,BURROWS,TEDDY,TEDDY,Male,African-American,12/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +52055,58673,53313,PRETRIAL,BURROWS,TEDDY,TEDDY,Male,African-American,12/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +41773,58698,53336,PRETRIAL,SULLIVAN,JEANNIE,NULL,Female,Caucasian,08/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +41773,58698,53336,PRETRIAL,SULLIVAN,JEANNIE,NULL,Female,Caucasian,08/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +41773,58698,53336,PRETRIAL,SULLIVAN,JEANNIE,NULL,Female,Caucasian,08/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52067,58684,53324,PRETRIAL,REED,TAYLER,NULL,Male,Caucasian,08/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +52067,58684,53324,PRETRIAL,REED,TAYLER,NULL,Male,Caucasian,08/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +52067,58684,53324,PRETRIAL,REED,TAYLER,NULL,Male,Caucasian,08/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52070,58687,53327,PRETRIAL,Nelson,Oneil,Michael,Male,African-American,05/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +52070,58687,53327,PRETRIAL,Nelson,Oneil,Michael,Male,African-American,05/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +52070,58687,53327,PRETRIAL,Nelson,Oneil,Michael,Male,African-American,05/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52084,58705,53343,Probation,MANIGO,ELLIOTT,NULL,Male,African-American,12/02/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/11/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +52084,58705,53343,Probation,MANIGO,ELLIOTT,NULL,Male,African-American,12/02/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/11/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +52084,58705,53343,Probation,MANIGO,ELLIOTT,NULL,Male,African-American,12/02/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +52073,58692,53331,Probation,Cannon,Quatavia,NULL,Female,African-American,08/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +52073,58692,53331,Probation,Cannon,Quatavia,NULL,Female,African-American,08/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +52073,58692,53331,Probation,Cannon,Quatavia,NULL,Female,African-American,08/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +44585,58679,53319,PRETRIAL,Anthony,Rashad,Lorenzo,Male,African-American,01/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.47,3,Low,New,1,0 +44585,58679,53319,PRETRIAL,Anthony,Rashad,Lorenzo,Male,African-American,01/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +44585,58679,53319,PRETRIAL,Anthony,Rashad,Lorenzo,Male,African-American,01/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52090,58713,53351,Probation,Yondolino,Anthony,NULL,Male,Caucasian,05/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.42,3,Low,New,1,0 +52090,58713,53351,Probation,Yondolino,Anthony,NULL,Male,Caucasian,05/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +52090,58713,53351,Probation,Yondolino,Anthony,NULL,Male,Caucasian,05/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52086,58708,53346,Probation,Solis,Luis,Leonardo,Male,Hispanic,09/23/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/11/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +52086,58708,53346,Probation,Solis,Luis,Leonardo,Male,Hispanic,09/23/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +52086,58708,53346,Probation,Solis,Luis,Leonardo,Male,Hispanic,09/23/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52053,58671,53311,PRETRIAL,WRIGHT,CHAMOY,LLOYD,Male,African-American,07/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +52053,58671,53311,PRETRIAL,WRIGHT,CHAMOY,LLOYD,Male,African-American,07/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +52053,58671,53311,PRETRIAL,WRIGHT,CHAMOY,LLOYD,Male,African-American,07/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52059,58681,53321,PRETRIAL,ABRAHAM,ROSNY,NULL,Male,African-American,06/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +52059,58681,53321,PRETRIAL,ABRAHAM,ROSNY,NULL,Male,African-American,06/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +52059,58681,53321,PRETRIAL,ABRAHAM,ROSNY,NULL,Male,African-American,06/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52069,58686,53326,PRETRIAL,HOPE,TERAS,NULL,Male,African-American,11/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +52069,58686,53326,PRETRIAL,HOPE,TERAS,NULL,Male,African-American,11/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +52069,58686,53326,PRETRIAL,HOPE,TERAS,NULL,Male,African-American,11/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51203,58690,52363,PRETRIAL,Fuller,Brian,NULL,Male,Caucasian,03/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,Copy,1,0 +51203,58690,52363,PRETRIAL,Fuller,Brian,NULL,Male,Caucasian,03/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,Copy,1,0 +51203,58690,52363,PRETRIAL,Fuller,Brian,NULL,Male,Caucasian,03/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +43782,58711,53349,Probation,Battle,shannon,NULL,Female,Caucasian,06/14/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/11/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +43782,58711,53349,Probation,Battle,shannon,NULL,Female,Caucasian,06/14/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/11/13 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +43782,58711,53349,Probation,Battle,shannon,NULL,Female,Caucasian,06/14/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +18516,58669,53309,PRETRIAL,WRIGHT,JAMAR,NULL,Male,African-American,05/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,7,Risk of Violence,-0.43,10,High,New,1,0 +18516,58669,53309,PRETRIAL,WRIGHT,JAMAR,NULL,Male,African-American,05/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,8,Risk of Recidivism,0.79,10,High,New,1,0 +18516,58669,53309,PRETRIAL,WRIGHT,JAMAR,NULL,Male,African-American,05/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52082,58702,53340,PRETRIAL,ESTELHOMME,RALPH,NULL,Male,African-American,09/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +52082,58702,53340,PRETRIAL,ESTELHOMME,RALPH,NULL,Male,African-American,09/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +52082,58702,53340,PRETRIAL,ESTELHOMME,RALPH,NULL,Male,African-American,09/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +41024,58695,51870,PRETRIAL,AMATO,BRANDON,BARCLAY,Male,Caucasian,08/05/92,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +41024,58695,51870,PRETRIAL,AMATO,BRANDON,BARCLAY,Male,Caucasian,08/05/92,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/13 0:00,2,Medium,8,Risk of Recidivism,0.16,7,Medium,New,1,0 +41024,58695,51870,PRETRIAL,AMATO,BRANDON,BARCLAY,Male,Caucasian,08/05/92,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/13 0:00,2,Medium,18,Risk of Failure to Appear,22,4,Low,New,1,0 +38204,58697,53335,PRETRIAL,Williams,Alicia,A,Female,African-American,07/05/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +38204,58697,53335,PRETRIAL,Williams,Alicia,A,Female,African-American,07/05/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +38204,58697,53335,PRETRIAL,Williams,Alicia,A,Female,African-American,07/05/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52083,58704,53342,Probation,segura,ashley,NULL,Female,Hispanic,10/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +52083,58704,53342,Probation,segura,ashley,NULL,Female,Hispanic,10/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,8,High,New,1,0 +52083,58704,53342,Probation,segura,ashley,NULL,Female,Hispanic,10/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52056,58674,53314,PRETRIAL,ARMENTI,MICHAEL,NULL,Male,Caucasian,04/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +52056,58674,53314,PRETRIAL,ARMENTI,MICHAEL,NULL,Male,Caucasian,04/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +52056,58674,53314,PRETRIAL,ARMENTI,MICHAEL,NULL,Male,Caucasian,04/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +4211,58676,53316,PRETRIAL,BLACK,BEAU,CHARLES,Male,Caucasian,07/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/11/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +4211,58676,53316,PRETRIAL,BLACK,BEAU,CHARLES,Male,Caucasian,07/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/11/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +4211,58676,53316,PRETRIAL,BLACK,BEAU,CHARLES,Male,Caucasian,07/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/11/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +49945,58725,50886,PRETRIAL,Hay,Victoria,Lynn,Female,Caucasian,05/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.07,1,Low,Copy,1,0 +49945,58725,50886,PRETRIAL,Hay,Victoria,Lynn,Female,Caucasian,05/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,8,High,Copy,1,0 +49945,58725,50886,PRETRIAL,Hay,Victoria,Lynn,Female,Caucasian,05/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,Copy,1,0 +52093,58718,53356,PRETRIAL,Brown,Shatara,NULL,Female,African-American,11/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +52093,58718,53356,PRETRIAL,Brown,Shatara,NULL,Female,African-American,11/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,9,High,New,1,0 +52093,58718,53356,PRETRIAL,Brown,Shatara,NULL,Female,African-American,11/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +38559,58732,53369,PRETRIAL,Salcedo,Marwinn,NULL,Male,Caucasian,08/07/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +38559,58732,53369,PRETRIAL,Salcedo,Marwinn,NULL,Male,Caucasian,08/07/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +38559,58732,53369,PRETRIAL,Salcedo,Marwinn,NULL,Male,Caucasian,08/07/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52117,58739,53374,PRETRIAL,Smiley,Alexandria,NULL,Female,Caucasian,04/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.53,3,Low,New,1,0 +52117,58739,53374,PRETRIAL,Smiley,Alexandria,NULL,Female,Caucasian,04/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,8,High,New,1,0 +52117,58739,53374,PRETRIAL,Smiley,Alexandria,NULL,Female,Caucasian,04/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +46497,58746,46911,PRETRIAL,Thomas,Roderick,NULL,Male,African-American,05/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,Copy,1,0 +46497,58746,46911,PRETRIAL,Thomas,Roderick,NULL,Male,African-American,05/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,Copy,1,0 +46497,58746,46911,PRETRIAL,Thomas,Roderick,NULL,Male,African-American,05/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +47524,58716,53354,PRETRIAL,Cornelius,Jarvis,NULL,Male,African-American,01/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +47524,58716,53354,PRETRIAL,Cornelius,Jarvis,NULL,Male,African-American,01/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +47524,58716,53354,PRETRIAL,Cornelius,Jarvis,NULL,Male,African-American,01/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52098,58723,53361,PRETRIAL,Reynolds,Mernarita,NULL,Female,Other,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/12/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +52098,58723,53361,PRETRIAL,Reynolds,Mernarita,NULL,Female,Other,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/12/13 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +52098,58723,53361,PRETRIAL,Reynolds,Mernarita,NULL,Female,Other,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52115,58737,53372,Probation,Cuecha,Helmut,Alexander,Male,Hispanic,04/26/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +52115,58737,53372,Probation,Cuecha,Helmut,Alexander,Male,Hispanic,04/26/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +52115,58737,53372,Probation,Cuecha,Helmut,Alexander,Male,Hispanic,04/26/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52095,58720,53358,PRETRIAL,Shanafelt,Darell,Lee,Male,Caucasian,10/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +52095,58720,53358,PRETRIAL,Shanafelt,Darell,Lee,Male,Caucasian,10/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +52095,58720,53358,PRETRIAL,Shanafelt,Darell,Lee,Male,Caucasian,10/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52119,58741,53376,Probation,Ramos,Magda,NULL,Female,Hispanic,10/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/12/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +52119,58741,53376,Probation,Ramos,Magda,NULL,Female,Hispanic,10/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/12/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +52119,58741,53376,Probation,Ramos,Magda,NULL,Female,Hispanic,10/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52103,58728,53365,PRETRIAL,LAMOUR,RONEL,JUNIOR,Male,African-American,10/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +52103,58728,53365,PRETRIAL,LAMOUR,RONEL,JUNIOR,Male,African-American,10/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +52103,58728,53365,PRETRIAL,LAMOUR,RONEL,JUNIOR,Male,African-American,10/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52122,58749,53380,Probation,saavedra,jose,NULL,Male,Caucasian,07/15/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +52122,58749,53380,Probation,saavedra,jose,NULL,Male,Caucasian,07/15/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +52122,58749,53380,Probation,saavedra,jose,NULL,Male,Caucasian,07/15/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52123,58750,53381,Probation,JACKSON,LYDELL,A,Male,African-American,09/12/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +52123,58750,53381,Probation,JACKSON,LYDELL,A,Male,African-American,09/12/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +52123,58750,53381,Probation,JACKSON,LYDELL,A,Male,African-American,09/12/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +52120,58744,53377,PRETRIAL,OBRIEN,CHRISTOPHER,NULL,Male,Caucasian,12/08/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/12/13 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +52120,58744,53377,PRETRIAL,OBRIEN,CHRISTOPHER,NULL,Male,Caucasian,12/08/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/12/13 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +52120,58744,53377,PRETRIAL,OBRIEN,CHRISTOPHER,NULL,Male,Caucasian,12/08/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52104,58729,53366,PRETRIAL,Vergaga,Lazaro,NULL,Male,Caucasian,05/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +52104,58729,53366,PRETRIAL,Vergaga,Lazaro,NULL,Male,Caucasian,05/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +52104,58729,53366,PRETRIAL,Vergaga,Lazaro,NULL,Male,Caucasian,05/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52114,58736,53371,Probation,taylor,nicholas,NULL,Male,Caucasian,03/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +52114,58736,53371,Probation,taylor,nicholas,NULL,Male,Caucasian,03/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +52114,58736,53371,Probation,taylor,nicholas,NULL,Male,Caucasian,03/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52121,58747,53378,Probation,Aceropolanco,juan,NULL,Male,Hispanic,12/18/88,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/12/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +52121,58747,53378,Probation,Aceropolanco,juan,NULL,Male,Hispanic,12/18/88,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/12/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +52121,58747,53378,Probation,Aceropolanco,juan,NULL,Male,Hispanic,12/18/88,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52101,58726,53363,PRETRIAL,Gologorsky,Todd,NULL,Male,Caucasian,03/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +52101,58726,53363,PRETRIAL,Gologorsky,Todd,NULL,Male,Caucasian,03/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +52101,58726,53363,PRETRIAL,Gologorsky,Todd,NULL,Male,Caucasian,03/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +46497,51510,46911,PRETRIAL,Thomas,Roderick,NULL,Male,African-American,05/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +46497,51510,46911,PRETRIAL,Thomas,Roderick,NULL,Male,African-American,05/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +46497,51510,46911,PRETRIAL,Thomas,Roderick,NULL,Male,African-American,05/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51451,58734,52631,PRETRIAL,Miebach,Kaitlyn,NULL,Female,Caucasian,11/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +51451,58734,52631,PRETRIAL,Miebach,Kaitlyn,NULL,Female,Caucasian,11/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.7,5,Medium,Copy,1,0 +51451,58734,52631,PRETRIAL,Miebach,Kaitlyn,NULL,Female,Caucasian,11/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +52125,58752,53383,Probation,Johnson,Willie,NULL,Male,African-American,10/14/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +52125,58752,53383,Probation,Johnson,Willie,NULL,Male,African-American,10/14/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +52125,58752,53383,Probation,Johnson,Willie,NULL,Male,African-American,10/14/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +52094,58719,53357,PRETRIAL,Ogarro,Kimani,NULL,Male,African-American,05/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,New,1,0 +52094,58719,53357,PRETRIAL,Ogarro,Kimani,NULL,Male,African-American,05/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +52094,58719,53357,PRETRIAL,Ogarro,Kimani,NULL,Male,African-American,05/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +31142,58733,53370,PRETRIAL,Williams,Shawn,NULL,Male,African-American,10/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,2/12/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +31142,58733,53370,PRETRIAL,Williams,Shawn,NULL,Male,African-American,10/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,2/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +31142,58733,53370,PRETRIAL,Williams,Shawn,NULL,Male,African-American,10/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,2/12/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52099,58724,53362,PRETRIAL,Charite,Dervin,NULL,Male,Other,09/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +52099,58724,53362,PRETRIAL,Charite,Dervin,NULL,Male,Other,09/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,4,High,8,Risk of Recidivism,0.28,8,High,New,1,0 +52099,58724,53362,PRETRIAL,Charite,Dervin,NULL,Male,Other,09/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52091,58715,53353,PRETRIAL,EVERETT,PAMELA,YVETTE,Female,African-American,09/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +52091,58715,53353,PRETRIAL,EVERETT,PAMELA,YVETTE,Female,African-American,09/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +52091,58715,53353,PRETRIAL,EVERETT,PAMELA,YVETTE,Female,African-American,09/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51925,58745,53173,PRETRIAL,Carlheinz,Caprice,NULL,Male,African-American,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,Copy,1,0 +51925,58745,53173,PRETRIAL,Carlheinz,Caprice,NULL,Male,African-American,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,Copy,1,0 +51925,58745,53173,PRETRIAL,Carlheinz,Caprice,NULL,Male,African-American,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +42188,58754,53385,PRETRIAL,Brantley,Jerome,NULL,Male,African-American,12/21/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +42188,58754,53385,PRETRIAL,Brantley,Jerome,NULL,Male,African-American,12/21/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +42188,58754,53385,PRETRIAL,Brantley,Jerome,NULL,Male,African-American,12/21/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52092,58717,53355,PRETRIAL,Jackson,Russell,NULL,Male,African-American,08/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +52092,58717,53355,PRETRIAL,Jackson,Russell,NULL,Male,African-American,08/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +52092,58717,53355,PRETRIAL,Jackson,Russell,NULL,Male,African-American,08/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +10134,58731,53368,PRETRIAL,robinson,ahmad,NULL,Male,African-American,04/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +10134,58731,53368,PRETRIAL,robinson,ahmad,NULL,Male,African-American,04/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +10134,58731,53368,PRETRIAL,robinson,ahmad,NULL,Male,African-American,04/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52116,58738,53373,DRRD,Maxwell,Luther,NULL,Male,African-American,11/26/85,17,All Scales,Intake,English,Post Sentence,Probation,Married,2/12/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +52116,58738,53373,DRRD,Maxwell,Luther,NULL,Male,African-American,11/26/85,17,All Scales,Intake,English,Post Sentence,Probation,Married,2/12/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +52116,58738,53373,DRRD,Maxwell,Luther,NULL,Male,African-American,11/26/85,17,All Scales,Intake,English,Post Sentence,Probation,Married,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +52118,58740,53375,PRETRIAL,Rainey,Dashawniese,NULL,Female,African-American,08/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +52118,58740,53375,PRETRIAL,Rainey,Dashawniese,NULL,Female,African-American,08/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +52118,58740,53375,PRETRIAL,Rainey,Dashawniese,NULL,Female,African-American,08/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +18391,58743,53153,Probation,anthony,kim,NULL,Female,Caucasian,11/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/12/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,Copy,1,0 +18391,58743,53153,Probation,anthony,kim,NULL,Female,Caucasian,11/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/12/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,Copy,1,0 +18391,58743,53153,Probation,anthony,kim,NULL,Female,Caucasian,11/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +52097,58722,53360,PRETRIAL,Wright,Nicholas,NULL,Male,African-American,08/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +52097,58722,53360,PRETRIAL,Wright,Nicholas,NULL,Male,African-American,08/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +52097,58722,53360,PRETRIAL,Wright,Nicholas,NULL,Male,African-American,08/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52105,58730,53367,PRETRIAL,Brooks,James,Wilbert,Male,African-American,11/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +52105,58730,53367,PRETRIAL,Brooks,James,Wilbert,Male,African-American,11/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +52105,58730,53367,PRETRIAL,Brooks,James,Wilbert,Male,African-American,11/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +18587,58748,53379,PRETRIAL,DAVIS,ANTHONY,NULL,Male,African-American,10/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,2,Medium,7,Risk of Violence,-2.81,2,Low,New,1,0 +18587,58748,53379,PRETRIAL,DAVIS,ANTHONY,NULL,Male,African-American,10/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +18587,58748,53379,PRETRIAL,DAVIS,ANTHONY,NULL,Male,African-American,10/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52102,58727,53364,PRETRIAL,BENNIE,DAVID,NULL,Male,African-American,11/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +52102,58727,53364,PRETRIAL,BENNIE,DAVID,NULL,Male,African-American,11/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +52102,58727,53364,PRETRIAL,BENNIE,DAVID,NULL,Male,African-American,11/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +27690,58735,38512,Probation,moorman,vincent,NULL,Male,African-American,09/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,Copy,1,0 +27690,58735,38512,Probation,moorman,vincent,NULL,Male,African-American,09/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,Copy,1,0 +27690,58735,38512,Probation,moorman,vincent,NULL,Male,African-American,09/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +52155,58785,53414,Probation,Jones,Anthony,Allen,Male,Caucasian,06/14/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/13/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +52155,58785,53414,Probation,Jones,Anthony,Allen,Male,Caucasian,06/14/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/13/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +52155,58785,53414,Probation,Jones,Anthony,Allen,Male,Caucasian,06/14/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +52135,58764,53395,PRETRIAL,Suarez,Joseph,NULL,Male,Caucasian,02/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +52135,58764,53395,PRETRIAL,Suarez,Joseph,NULL,Male,Caucasian,02/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +52135,58764,53395,PRETRIAL,Suarez,Joseph,NULL,Male,Caucasian,02/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +33316,58793,32410,PRETRIAL,Mackey,Henry,B,Male,African-American,08/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,2,Medium,7,Risk of Violence,-2.88,2,Low,Copy,1,0 +33316,58793,32410,PRETRIAL,Mackey,Henry,B,Male,African-American,08/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,Copy,1,0 +33316,58793,32410,PRETRIAL,Mackey,Henry,B,Male,African-American,08/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +52145,58772,53402,PRETRIAL,cuba,ana,NULL,Female,Hispanic,12/30/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/13/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +52145,58772,53402,PRETRIAL,cuba,ana,NULL,Female,Hispanic,12/30/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/13/13 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +52145,58772,53402,PRETRIAL,cuba,ana,NULL,Female,Hispanic,12/30/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51491,58769,52675,PRETRIAL,Robinson,Tommy,NULL,Male,African-American,03/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/13/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,Copy,1,0 +51491,58769,52675,PRETRIAL,Robinson,Tommy,NULL,Male,African-American,03/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/13/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,Copy,1,0 +51491,58769,52675,PRETRIAL,Robinson,Tommy,NULL,Male,African-American,03/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +47322,58756,53387,PRETRIAL,Payne,Antwan,NULL,Male,African-American,12/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +47322,58756,53387,PRETRIAL,Payne,Antwan,NULL,Male,African-American,12/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +47322,58756,53387,PRETRIAL,Payne,Antwan,NULL,Male,African-American,12/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +41489,58790,41189,PRETRIAL,MOORER,CLINTON,NULL,Male,African-American,02/18/94,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,2/13/13 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +41489,58790,41189,PRETRIAL,MOORER,CLINTON,NULL,Male,African-American,02/18/94,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,2/13/13 0:00,4,High,8,Risk of Recidivism,0.31,8,High,New,1,0 +41489,58790,41189,PRETRIAL,MOORER,CLINTON,NULL,Male,African-American,02/18/94,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,2/13/13 0:00,4,High,18,Risk of Failure to Appear,18,2,Low,New,1,0 +52149,58777,53407,Probation,FRANCIS,GERALYN,NULL,Female,Caucasian,01/06/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +52149,58777,53407,Probation,FRANCIS,GERALYN,NULL,Female,Caucasian,01/06/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +52149,58777,53407,Probation,FRANCIS,GERALYN,NULL,Female,Caucasian,01/06/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52130,58759,53390,PRETRIAL,Garciacoto,Rainel,NULL,Male,Caucasian,05/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +52130,58759,53390,PRETRIAL,Garciacoto,Rainel,NULL,Male,Caucasian,05/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +52130,58759,53390,PRETRIAL,Garciacoto,Rainel,NULL,Male,Caucasian,05/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52132,58761,53392,PRETRIAL,Allen,Robby,NULL,Male,African-American,12/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,4,High,7,Risk of Violence,-0.56,10,High,New,1,0 +52132,58761,53392,PRETRIAL,Allen,Robby,NULL,Male,African-American,12/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +52132,58761,53392,PRETRIAL,Allen,Robby,NULL,Male,African-American,12/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52139,58768,53399,PRETRIAL,Rankin,Brian,NULL,Male,Caucasian,12/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +52139,58768,53399,PRETRIAL,Rankin,Brian,NULL,Male,Caucasian,12/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +52139,58768,53399,PRETRIAL,Rankin,Brian,NULL,Male,Caucasian,12/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52153,58782,53412,PRETRIAL,SANCHEZ,KENNETH,NULL,Male,Hispanic,02/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +52153,58782,53412,PRETRIAL,SANCHEZ,KENNETH,NULL,Male,Hispanic,02/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +52153,58782,53412,PRETRIAL,SANCHEZ,KENNETH,NULL,Male,Hispanic,02/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +36547,58789,35833,PRETRIAL,SHELLMAN,TROY,LEON,Male,African-American,01/31/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,Copy,1,0 +36547,58789,35833,PRETRIAL,SHELLMAN,TROY,LEON,Male,African-American,01/31/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,Copy,1,0 +36547,58789,35833,PRETRIAL,SHELLMAN,TROY,LEON,Male,African-American,01/31/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +52148,58775,53405,Probation,Ramos,Ramon,NULL,Male,Hispanic,01/23/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/13/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +52148,58775,53405,Probation,Ramos,Ramon,NULL,Male,Hispanic,01/23/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/13/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +52148,58775,53405,Probation,Ramos,Ramon,NULL,Male,Hispanic,01/23/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52137,58766,53397,PRETRIAL,Liberatore,Peter,NULL,Male,Caucasian,06/09/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +52137,58766,53397,PRETRIAL,Liberatore,Peter,NULL,Male,Caucasian,06/09/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +52137,58766,53397,PRETRIAL,Liberatore,Peter,NULL,Male,Caucasian,06/09/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52154,58784,53413,Probation,Taylor,Keith,NULL,Male,Caucasian,07/24/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +52154,58784,53413,Probation,Taylor,Keith,NULL,Male,Caucasian,07/24/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +52154,58784,53413,Probation,Taylor,Keith,NULL,Male,Caucasian,07/24/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,2,Medium,18,Risk of Failure to Appear,39,10,High,New,1,0 +52152,58780,53410,Probation,POOLE,VINCENT,M,Male,Caucasian,07/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +52152,58780,53410,Probation,POOLE,VINCENT,M,Male,Caucasian,07/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +52152,58780,53410,Probation,POOLE,VINCENT,M,Male,Caucasian,07/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52157,58787,53416,Probation,Bowens,Travon,NULL,Male,African-American,07/22/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +52157,58787,53416,Probation,Bowens,Travon,NULL,Male,African-American,07/22/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +52157,58787,53416,Probation,Bowens,Travon,NULL,Male,African-American,07/22/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52127,58755,53386,PRETRIAL,Perpall,Deangelo,Robert,Male,African-American,04/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +52127,58755,53386,PRETRIAL,Perpall,Deangelo,Robert,Male,African-American,04/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +52127,58755,53386,PRETRIAL,Perpall,Deangelo,Robert,Male,African-American,04/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52146,58773,53403,Probation,Manley,Michael,Joseph,Male,African-American,11/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +52146,58773,53403,Probation,Manley,Michael,Joseph,Male,African-American,11/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +52146,58773,53403,Probation,Manley,Michael,Joseph,Male,African-American,11/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52131,58760,53391,PRETRIAL,Gallo,Luis,NULL,Male,Hispanic,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +52131,58760,53391,PRETRIAL,Gallo,Luis,NULL,Male,Hispanic,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +52131,58760,53391,PRETRIAL,Gallo,Luis,NULL,Male,Hispanic,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +33316,58794,32410,PRETRIAL,Mackey,Henry,B,Male,African-American,08/25/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,Copy,1,0 +33316,58794,32410,PRETRIAL,Mackey,Henry,B,Male,African-American,08/25/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,Copy,1,0 +33316,58794,32410,PRETRIAL,Mackey,Henry,B,Male,African-American,08/25/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +41574,58781,53411,PRETRIAL,TAFFEE,RICHARD,NULL,Male,African-American,11/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/13 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +41574,58781,53411,PRETRIAL,TAFFEE,RICHARD,NULL,Male,African-American,11/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +41574,58781,53411,PRETRIAL,TAFFEE,RICHARD,NULL,Male,African-American,11/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +52134,58763,53394,PRETRIAL,Arocho,Irangel,NULL,Male,Caucasian,10/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +52134,58763,53394,PRETRIAL,Arocho,Irangel,NULL,Male,Caucasian,10/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +52134,58763,53394,PRETRIAL,Arocho,Irangel,NULL,Male,Caucasian,10/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52136,58765,53396,PRETRIAL,Blade,Johnnie,NULL,Male,African-American,06/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.74,2,Low,New,1,0 +52136,58765,53396,PRETRIAL,Blade,Johnnie,NULL,Male,African-American,06/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +52136,58765,53396,PRETRIAL,Blade,Johnnie,NULL,Male,African-American,06/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52140,58770,53400,Probation,Vaughn,Robert,NULL,Male,African-American,07/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,4,High,7,Risk of Violence,-1.01,8,High,New,1,0 +52140,58770,53400,Probation,Vaughn,Robert,NULL,Male,African-American,07/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,4,High,8,Risk of Recidivism,1.49,10,High,New,1,0 +52140,58770,53400,Probation,Vaughn,Robert,NULL,Male,African-American,07/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +52128,58757,53388,PRETRIAL,Brownlee,Courtney,NULL,Male,African-American,10/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +52128,58757,53388,PRETRIAL,Brownlee,Courtney,NULL,Male,African-American,10/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +52128,58757,53388,PRETRIAL,Brownlee,Courtney,NULL,Male,African-American,10/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52159,58791,53418,PRETRIAL,Kohler,Micahel,NULL,Male,Caucasian,08/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +52159,58791,53418,PRETRIAL,Kohler,Micahel,NULL,Male,Caucasian,08/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +52159,58791,53418,PRETRIAL,Kohler,Micahel,NULL,Male,Caucasian,08/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52156,58786,53415,PRETRIAL,MEJARODRIGUEZ,ANA,NULL,Female,Hispanic,06/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/13/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +52156,58786,53415,PRETRIAL,MEJARODRIGUEZ,ANA,NULL,Female,Hispanic,06/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/13/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +52156,58786,53415,PRETRIAL,MEJARODRIGUEZ,ANA,NULL,Female,Hispanic,06/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52141,58771,53401,PRETRIAL,MAGLIOCCA,JOSEPH,NULL,Male,Caucasian,03/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +52141,58771,53401,PRETRIAL,MAGLIOCCA,JOSEPH,NULL,Male,Caucasian,03/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +52141,58771,53401,PRETRIAL,MAGLIOCCA,JOSEPH,NULL,Male,Caucasian,03/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52150,58778,53408,Probation,SOLARES,KORALL,NULL,Female,Caucasian,08/28/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/13/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +52150,58778,53408,Probation,SOLARES,KORALL,NULL,Female,Caucasian,08/28/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/13/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +52150,58778,53408,Probation,SOLARES,KORALL,NULL,Female,Caucasian,08/28/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +52129,58758,53389,PRETRIAL,Bolton,Heather,NULL,Female,Caucasian,08/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +52129,58758,53389,PRETRIAL,Bolton,Heather,NULL,Female,Caucasian,08/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +52129,58758,53389,PRETRIAL,Bolton,Heather,NULL,Female,Caucasian,08/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52160,58792,53419,Probation,Best,Stephen,NULL,Male,Caucasian,06/22/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +52160,58792,53419,Probation,Best,Stephen,NULL,Male,Caucasian,06/22/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +52160,58792,53419,Probation,Best,Stephen,NULL,Male,Caucasian,06/22/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52151,58779,53409,PRETRIAL,Smith,Crystal,Lynn,Female,Caucasian,02/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +52151,58779,53409,PRETRIAL,Smith,Crystal,Lynn,Female,Caucasian,02/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,8,High,New,1,0 +52151,58779,53409,PRETRIAL,Smith,Crystal,Lynn,Female,Caucasian,02/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52158,58788,53417,Probation,Rice,Allison,NULL,Female,Caucasian,06/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/13/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +52158,58788,53417,Probation,Rice,Allison,NULL,Female,Caucasian,06/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/13/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +52158,58788,53417,Probation,Rice,Allison,NULL,Female,Caucasian,06/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52133,58762,53393,PRETRIAL,DAVID,LAKEINYAS,S,Female,African-American,01/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +52133,58762,53393,PRETRIAL,DAVID,LAKEINYAS,S,Female,African-American,01/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +52133,58762,53393,PRETRIAL,DAVID,LAKEINYAS,S,Female,African-American,01/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +43536,58783,43500,PRETRIAL,Wilson,Willie,James,Male,African-American,09/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,Copy,1,0 +43536,58783,43500,PRETRIAL,Wilson,Willie,James,Male,African-American,09/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,Copy,1,0 +43536,58783,43500,PRETRIAL,Wilson,Willie,James,Male,African-American,09/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +52138,58767,53398,PRETRIAL,JOHNSON,ALEXANDER,H,Male,Caucasian,09/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +52138,58767,53398,PRETRIAL,JOHNSON,ALEXANDER,H,Male,Caucasian,09/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +52138,58767,53398,PRETRIAL,JOHNSON,ALEXANDER,H,Male,Caucasian,09/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52147,58774,53404,PRETRIAL,morgan,ron,NULL,Male,Caucasian,03/07/38,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +52147,58774,53404,PRETRIAL,morgan,ron,NULL,Male,Caucasian,03/07/38,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +52147,58774,53404,PRETRIAL,morgan,ron,NULL,Male,Caucasian,03/07/38,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +30625,58776,53406,PRETRIAL,Curry,Jonathan,NULL,Male,African-American,03/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +30625,58776,53406,PRETRIAL,Curry,Jonathan,NULL,Male,African-American,03/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +30625,58776,53406,PRETRIAL,Curry,Jonathan,NULL,Male,African-American,03/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52182,58825,53447,Probation,PAGAN,ROBERTO,NULL,Male,Hispanic,05/11/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +52182,58825,53447,Probation,PAGAN,ROBERTO,NULL,Male,Hispanic,05/11/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +52182,58825,53447,Probation,PAGAN,ROBERTO,NULL,Male,Hispanic,05/11/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +45437,58797,53422,PRETRIAL,FERNANDEZ,FAUSTO,E,Male,Caucasian,01/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +45437,58797,53422,PRETRIAL,FERNANDEZ,FAUSTO,E,Male,Caucasian,01/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +45437,58797,53422,PRETRIAL,FERNANDEZ,FAUSTO,E,Male,Caucasian,01/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +15371,58804,53429,PRETRIAL,Thomas,Jermaine,T,Male,African-American,11/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +15371,58804,53429,PRETRIAL,Thomas,Jermaine,T,Male,African-American,11/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +15371,58804,53429,PRETRIAL,Thomas,Jermaine,T,Male,African-American,11/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52176,58818,53441,Probation,SHIFLET,TRACY,NULL,Female,African-American,01/30/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +52176,58818,53441,Probation,SHIFLET,TRACY,NULL,Female,African-American,01/30/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +52176,58818,53441,Probation,SHIFLET,TRACY,NULL,Female,African-American,01/30/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +52188,58832,53454,Probation,Mellad,Garth,NULL,Male,African-American,02/29/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +52188,58832,53454,Probation,Mellad,Garth,NULL,Male,African-American,02/29/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +52188,58832,53454,Probation,Mellad,Garth,NULL,Male,African-American,02/29/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52199,58846,53468,Probation,Alocer,Maria,Guadalupe,Female,Hispanic,01/14/66,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,2/14/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +52199,58846,53468,Probation,Alocer,Maria,Guadalupe,Female,Hispanic,01/14/66,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +52199,58846,53468,Probation,Alocer,Maria,Guadalupe,Female,Hispanic,01/14/66,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52190,58834,53456,PRETRIAL,Kirkpatrick,Andriane,NULL,Female,Hispanic,10/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/14/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +52190,58834,53456,PRETRIAL,Kirkpatrick,Andriane,NULL,Female,Hispanic,10/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +52190,58834,53456,PRETRIAL,Kirkpatrick,Andriane,NULL,Female,Hispanic,10/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52204,58851,53473,Probation,graham,omar,NULL,Male,African-American,01/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +52204,58851,53473,Probation,graham,omar,NULL,Male,African-American,01/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +52204,58851,53473,Probation,graham,omar,NULL,Male,African-American,01/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52185,58830,53452,Probation,Vernon,Lloyd,Anthony,Male,African-American,07/26/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +52185,58830,53452,Probation,Vernon,Lloyd,Anthony,Male,African-American,07/26/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +52185,58830,53452,Probation,Vernon,Lloyd,Anthony,Male,African-American,07/26/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52172,58813,53436,PRETRIAL,Woods,Roderick,NULL,Male,African-American,11/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +52172,58813,53436,PRETRIAL,Woods,Roderick,NULL,Male,African-American,11/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +52172,58813,53436,PRETRIAL,Woods,Roderick,NULL,Male,African-American,11/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52168,58809,53432,PRETRIAL,KELLY,KAMRY,NULL,Male,African-American,08/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,4,High,7,Risk of Violence,-0.67,9,High,New,1,0 +52168,58809,53432,PRETRIAL,KELLY,KAMRY,NULL,Male,African-American,08/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,4,High,8,Risk of Recidivism,0.88,10,High,New,1,0 +52168,58809,53432,PRETRIAL,KELLY,KAMRY,NULL,Male,African-American,08/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52184,58828,53450,Probation,Seltzer,Paul,NULL,Male,Caucasian,05/01/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +52184,58828,53450,Probation,Seltzer,Paul,NULL,Male,Caucasian,05/01/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +52184,58828,53450,Probation,Seltzer,Paul,NULL,Male,Caucasian,05/01/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +41849,58799,53424,PRETRIAL,Scott,Bernard,Nickolas,Male,African-American,11/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +41849,58799,53424,PRETRIAL,Scott,Bernard,Nickolas,Male,African-American,11/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +41849,58799,53424,PRETRIAL,Scott,Bernard,Nickolas,Male,African-American,11/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52191,58836,53458,PRETRIAL,Moore,Matthew,NULL,Male,African-American,03/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +52191,58836,53458,PRETRIAL,Moore,Matthew,NULL,Male,African-American,03/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +52191,58836,53458,PRETRIAL,Moore,Matthew,NULL,Male,African-American,03/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52202,58849,53471,Probation,Algaze,Ryan,NULL,Male,Caucasian,09/29/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/14/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +52202,58849,53471,Probation,Algaze,Ryan,NULL,Male,Caucasian,09/29/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/14/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +52202,58849,53471,Probation,Algaze,Ryan,NULL,Male,Caucasian,09/29/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +11374,58844,53466,Probation,Woodard,Bianca,L,Female,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +11374,58844,53466,Probation,Woodard,Bianca,L,Female,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,10,High,New,1,0 +11374,58844,53466,Probation,Woodard,Bianca,L,Female,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +52173,58815,53438,PRETRIAL,Maquez,Joseph,NULL,Male,African-American,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/14/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +52173,58815,53438,PRETRIAL,Maquez,Joseph,NULL,Male,African-American,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/14/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +52173,58815,53438,PRETRIAL,Maquez,Joseph,NULL,Male,African-American,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51112,58854,52266,Probation,leto,valerie,NULL,Female,Caucasian,11/17/68,17,All Scales,Intake,English,Conditional Release,Probation,Widowed,2/14/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +51112,58854,52266,Probation,leto,valerie,NULL,Female,Caucasian,11/17/68,17,All Scales,Intake,English,Conditional Release,Probation,Widowed,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +51112,58854,52266,Probation,leto,valerie,NULL,Female,Caucasian,11/17/68,17,All Scales,Intake,English,Conditional Release,Probation,Widowed,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,1,Low,New,1,0 +12708,58807,31039,PRETRIAL,edwards,kendrick,NULL,Male,African-American,07/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,4,High,7,Risk of Violence,-0.92,9,High,Copy,1,0 +12708,58807,31039,PRETRIAL,edwards,kendrick,NULL,Male,African-American,07/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,4,High,8,Risk of Recidivism,1.16,10,High,Copy,1,0 +12708,58807,31039,PRETRIAL,edwards,kendrick,NULL,Male,African-American,07/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +52194,58841,53463,Probation,Broche,Jose,Manuel,Male,Hispanic,10/13/89,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/14/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +52194,58841,53463,Probation,Broche,Jose,Manuel,Male,Hispanic,10/13/89,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +52194,58841,53463,Probation,Broche,Jose,Manuel,Male,Hispanic,10/13/89,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/14/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52171,58812,53435,PRETRIAL,Plummer,Brenda,NULL,Female,African-American,11/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/14/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +52171,58812,53435,PRETRIAL,Plummer,Brenda,NULL,Female,African-American,11/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +52171,58812,53435,PRETRIAL,Plummer,Brenda,NULL,Female,African-American,11/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52180,58823,53445,Probation,Polikandriotis,Spiridon,NULL,Male,Other,09/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +52180,58823,53445,Probation,Polikandriotis,Spiridon,NULL,Male,Other,09/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +52180,58823,53445,Probation,Polikandriotis,Spiridon,NULL,Male,Other,09/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +48192,58802,53427,PRETRIAL,Major,Roosevelt,NULL,Male,African-American,09/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/14/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +48192,58802,53427,PRETRIAL,Major,Roosevelt,NULL,Male,African-American,09/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +48192,58802,53427,PRETRIAL,Major,Roosevelt,NULL,Male,African-American,09/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +26753,58833,53455,PRETRIAL,PARODI,PATRICO,NULL,Male,Caucasian,06/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +26753,58833,53455,PRETRIAL,PARODI,PATRICO,NULL,Male,Caucasian,06/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +26753,58833,53455,PRETRIAL,PARODI,PATRICO,NULL,Male,Caucasian,06/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52166,58805,53430,PRETRIAL,Henderson,Nicole,NULL,Female,African-American,02/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +52166,58805,53430,PRETRIAL,Henderson,Nicole,NULL,Female,African-American,02/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +52166,58805,53430,PRETRIAL,Henderson,Nicole,NULL,Female,African-American,02/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52164,58801,53426,PRETRIAL,Mackenie,Douglas,Allen,Male,Caucasian,09/06/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/14/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +52164,58801,53426,PRETRIAL,Mackenie,Douglas,Allen,Male,Caucasian,09/06/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/14/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +52164,58801,53426,PRETRIAL,Mackenie,Douglas,Allen,Male,Caucasian,09/06/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52205,58852,53474,DRRD,Saintuelus,Saintony,NULL,Male,African-American,04/20/90,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/14/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +52205,58852,53474,DRRD,Saintuelus,Saintony,NULL,Male,African-American,04/20/90,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.73,3,Low,New,1,0 +52205,58852,53474,DRRD,Saintuelus,Saintony,NULL,Male,African-American,04/20/90,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/14/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52197,58843,53465,PRETRIAL,Mccalligan,Justin,Elliot,Male,Caucasian,06/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +52197,58843,53465,PRETRIAL,Mccalligan,Justin,Elliot,Male,Caucasian,06/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +52197,58843,53465,PRETRIAL,Mccalligan,Justin,Elliot,Male,Caucasian,06/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +52208,58856,53477,PRETRIAL,Ford,Devion,NULL,Male,African-American,08/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +52208,58856,53477,PRETRIAL,Ford,Devion,NULL,Male,African-American,08/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +52208,58856,53477,PRETRIAL,Ford,Devion,NULL,Male,African-American,08/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52161,58796,53421,PRETRIAL,Williams,Seymour,NULL,Male,African-American,12/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +52161,58796,53421,PRETRIAL,Williams,Seymour,NULL,Male,African-American,12/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +52161,58796,53421,PRETRIAL,Williams,Seymour,NULL,Male,African-American,12/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52165,58803,53428,PRETRIAL,Ellison,Ernest,Lee,Male,African-American,01/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +52165,58803,53428,PRETRIAL,Ellison,Ernest,Lee,Male,African-American,01/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +52165,58803,53428,PRETRIAL,Ellison,Ernest,Lee,Male,African-American,01/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52175,58817,53440,PRETRIAL,BRUNSON,NEYESHA,NULL,Female,African-American,05/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/14/13 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +52175,58817,53440,PRETRIAL,BRUNSON,NEYESHA,NULL,Female,African-American,05/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/14/13 0:00,4,High,8,Risk of Recidivism,0.88,10,High,New,1,0 +52175,58817,53440,PRETRIAL,BRUNSON,NEYESHA,NULL,Female,African-American,05/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/14/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52169,58810,53433,PRETRIAL,Gibbons,Michael,NULL,Male,African-American,09/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +52169,58810,53433,PRETRIAL,Gibbons,Michael,NULL,Male,African-American,09/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +52169,58810,53433,PRETRIAL,Gibbons,Michael,NULL,Male,African-American,09/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +52187,58831,53453,Probation,GRANT,CASSANDRA,RYAN,Male,African-American,11/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +52187,58831,53453,Probation,GRANT,CASSANDRA,RYAN,Male,African-American,11/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +52187,58831,53453,Probation,GRANT,CASSANDRA,RYAN,Male,African-American,11/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +23813,58838,53460,PRETRIAL,AGUIAR,PATRICIA,NULL,Female,Caucasian,01/01/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +23813,58838,53460,PRETRIAL,AGUIAR,PATRICIA,NULL,Female,Caucasian,01/01/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +23813,58838,53460,PRETRIAL,AGUIAR,PATRICIA,NULL,Female,Caucasian,01/01/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52195,58840,53462,PRETRIAL,Hergert,Kenneth,C,Male,Caucasian,07/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +52195,58840,53462,PRETRIAL,Hergert,Kenneth,C,Male,Caucasian,07/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +52195,58840,53462,PRETRIAL,Hergert,Kenneth,C,Male,Caucasian,07/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +52170,58811,53434,PRETRIAL,Ribeiro,Mark,NULL,Male,Other,05/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +52170,58811,53434,PRETRIAL,Ribeiro,Mark,NULL,Male,Other,05/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +52170,58811,53434,PRETRIAL,Ribeiro,Mark,NULL,Male,Other,05/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52181,58824,53446,Probation,GONZALEZ,EVAN,L,Male,Hispanic,08/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +52181,58824,53446,Probation,GONZALEZ,EVAN,L,Male,Hispanic,08/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +52181,58824,53446,Probation,GONZALEZ,EVAN,L,Male,Hispanic,08/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +52198,58845,53467,Probation,MITCHELL,SHARON,P,Female,Caucasian,05/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +52198,58845,53467,Probation,MITCHELL,SHARON,P,Female,Caucasian,05/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +52198,58845,53467,Probation,MITCHELL,SHARON,P,Female,Caucasian,05/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52174,58816,53439,PRETRIAL,Keeble,Samantha,NULL,Female,Caucasian,07/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +52174,58816,53439,PRETRIAL,Keeble,Samantha,NULL,Female,Caucasian,07/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,6,Medium,New,1,0 +52174,58816,53439,PRETRIAL,Keeble,Samantha,NULL,Female,Caucasian,07/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +52162,58798,53423,PRETRIAL,COLEY,MICHAEL,NULL,Male,African-American,10/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +52162,58798,53423,PRETRIAL,COLEY,MICHAEL,NULL,Male,African-American,10/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +52162,58798,53423,PRETRIAL,COLEY,MICHAEL,NULL,Male,African-American,10/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +36630,58806,35931,PRETRIAL,Walters,Orville,NULL,Male,African-American,10/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,Copy,1,0 +36630,58806,35931,PRETRIAL,Walters,Orville,NULL,Male,African-American,10/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,Copy,1,0 +36630,58806,35931,PRETRIAL,Walters,Orville,NULL,Male,African-American,10/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +52186,58829,53451,PRETRIAL,Perez-Vidal,Agustin,NULL,Male,Hispanic,12/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/14/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +52186,58829,53451,PRETRIAL,Perez-Vidal,Agustin,NULL,Male,Hispanic,12/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/14/13 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +52186,58829,53451,PRETRIAL,Perez-Vidal,Agustin,NULL,Male,Hispanic,12/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52167,58808,53431,PRETRIAL,Herard,Casey,NULL,Female,African-American,08/05/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,New,1,0 +52167,58808,53431,PRETRIAL,Herard,Casey,NULL,Female,African-American,08/05/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +52167,58808,53431,PRETRIAL,Herard,Casey,NULL,Female,African-American,08/05/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +40032,58827,53449,PRETRIAL,Ramsaran,Gary,NULL,Male,Caucasian,08/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +40032,58827,53449,PRETRIAL,Ramsaran,Gary,NULL,Male,Caucasian,08/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +40032,58827,53449,PRETRIAL,Ramsaran,Gary,NULL,Male,Caucasian,08/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52196,58842,53464,Probation,LLOYD,PAIGE,NULL,Female,African-American,01/30/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +52196,58842,53464,Probation,LLOYD,PAIGE,NULL,Female,African-American,01/30/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +52196,58842,53464,Probation,LLOYD,PAIGE,NULL,Female,African-American,01/30/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +27663,58814,53437,PRETRIAL,martin,cedrick,NULL,Male,African-American,10/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +27663,58814,53437,PRETRIAL,martin,cedrick,NULL,Male,African-American,10/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +27663,58814,53437,PRETRIAL,martin,cedrick,NULL,Male,African-American,10/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52178,58821,53443,Probation,Reyes,Juan,Coc,Male,Hispanic,07/12/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/14/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +52178,58821,53443,Probation,Reyes,Juan,Coc,Male,Hispanic,07/12/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/14/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +52178,58821,53443,Probation,Reyes,Juan,Coc,Male,Hispanic,07/12/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52163,58800,53425,PRETRIAL,Williams,Mack,NULL,Male,African-American,09/08/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +52163,58800,53425,PRETRIAL,Williams,Mack,NULL,Male,African-American,09/08/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +52163,58800,53425,PRETRIAL,Williams,Mack,NULL,Male,African-American,09/08/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +52189,58835,53457,Probation,BUSEKIST,WYATT,W,Male,Caucasian,09/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +52189,58835,53457,Probation,BUSEKIST,WYATT,W,Male,Caucasian,09/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +52189,58835,53457,Probation,BUSEKIST,WYATT,W,Male,Caucasian,09/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52224,58871,53492,Probation,Montalvo,Kelly,Marie,Female,Hispanic,10/22/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/15/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +52224,58871,53492,Probation,Montalvo,Kelly,Marie,Female,Hispanic,10/22/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/15/13 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +52224,58871,53492,Probation,Montalvo,Kelly,Marie,Female,Hispanic,10/22/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/15/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52213,58863,53484,PRETRIAL,Ginnie,Kimberly,NULL,Female,African-American,10/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +52213,58863,53484,PRETRIAL,Ginnie,Kimberly,NULL,Female,African-American,10/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +52213,58863,53484,PRETRIAL,Ginnie,Kimberly,NULL,Female,African-American,10/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52219,58866,53487,PRETRIAL,Castro,Michael,NULL,Male,Caucasian,03/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +52219,58866,53487,PRETRIAL,Castro,Michael,NULL,Male,Caucasian,03/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +52219,58866,53487,PRETRIAL,Castro,Michael,NULL,Male,Caucasian,03/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +27125,58879,53499,PRETRIAL,Johnson,Ernest,J,Male,African-American,10/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,New,1,0 +27125,58879,53499,PRETRIAL,Johnson,Ernest,J,Male,African-American,10/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +27125,58879,53499,PRETRIAL,Johnson,Ernest,J,Male,African-American,10/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +52210,58858,53479,PRETRIAL,Richardson,Isnor,NULL,Male,Other,11/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +52210,58858,53479,PRETRIAL,Richardson,Isnor,NULL,Male,Other,11/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +52210,58858,53479,PRETRIAL,Richardson,Isnor,NULL,Male,Other,11/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +42000,45727,41759,PRETRIAL,Jackson,Anthony,Beretta,Male,African-American,02/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/15/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +42000,45727,41759,PRETRIAL,Jackson,Anthony,Beretta,Male,African-American,02/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/15/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +42000,45727,41759,PRETRIAL,Jackson,Anthony,Beretta,Male,African-American,02/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/15/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +39888,58859,53480,PRETRIAL,Morales,Joshua,NULL,Male,Hispanic,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +39888,58859,53480,PRETRIAL,Morales,Joshua,NULL,Male,Hispanic,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +39888,58859,53480,PRETRIAL,Morales,Joshua,NULL,Male,Hispanic,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +3506,58861,53482,PRETRIAL,Gallimore,Shafon,Alexander,Male,African-American,09/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +3506,58861,53482,PRETRIAL,Gallimore,Shafon,Alexander,Male,African-American,09/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.68,10,High,New,1,0 +3506,58861,53482,PRETRIAL,Gallimore,Shafon,Alexander,Male,African-American,09/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52221,58868,53489,Probation,Shin,Hahnah,Adele,Female,Asian,08/30/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/15/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +52221,58868,53489,Probation,Shin,Hahnah,Adele,Female,Asian,08/30/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/15/13 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +52221,58868,53489,Probation,Shin,Hahnah,Adele,Female,Asian,08/30/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/15/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +52227,58877,53497,Probation,Saddo,Hasheem,Antonio,Male,African-American,12/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,2/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +52227,58877,53497,Probation,Saddo,Hasheem,Antonio,Male,African-American,12/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,2/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +52227,58877,53497,Probation,Saddo,Hasheem,Antonio,Male,African-American,12/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,2/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +44630,58873,53494,PRETRIAL,MCGONIGAL,ROBERT,NULL,Male,Caucasian,12/07/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/15/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +44630,58873,53494,PRETRIAL,MCGONIGAL,ROBERT,NULL,Male,Caucasian,12/07/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/15/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +44630,58873,53494,PRETRIAL,MCGONIGAL,ROBERT,NULL,Male,Caucasian,12/07/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/15/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52212,58862,53483,PRETRIAL,Brown,Jerry,NULL,Male,African-American,10/30/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,2,Medium,7,Risk of Violence,-2.23,4,Low,New,1,0 +52212,58862,53483,PRETRIAL,Brown,Jerry,NULL,Male,African-American,10/30/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +52212,58862,53483,PRETRIAL,Brown,Jerry,NULL,Male,African-American,10/30/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +15099,58875,48635,PRETRIAL,Jeanbaptiste,Franel,NULL,Male,African-American,10/22/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,Copy,1,0 +15099,58875,48635,PRETRIAL,Jeanbaptiste,Franel,NULL,Male,African-American,10/22/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,8,High,Copy,1,0 +15099,58875,48635,PRETRIAL,Jeanbaptiste,Franel,NULL,Male,African-American,10/22/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,2,Low,Copy,1,0 +52229,58878,53498,PRETRIAL,Montalvomolina,Joseph,NULL,Male,Caucasian,02/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +52229,58878,53498,PRETRIAL,Montalvomolina,Joseph,NULL,Male,Caucasian,02/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +52229,58878,53498,PRETRIAL,Montalvomolina,Joseph,NULL,Male,Caucasian,02/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52218,58865,53486,PRETRIAL,Jones,Stephen,NULL,Male,Caucasian,06/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +52218,58865,53486,PRETRIAL,Jones,Stephen,NULL,Male,Caucasian,06/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +52218,58865,53486,PRETRIAL,Jones,Stephen,NULL,Male,Caucasian,06/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52223,58870,53491,Probation,Aguilar,Elias,NULL,Male,Hispanic,11/22/85,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/15/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +52223,58870,53491,Probation,Aguilar,Elias,NULL,Male,Hispanic,11/22/85,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/15/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +52223,58870,53491,Probation,Aguilar,Elias,NULL,Male,Hispanic,11/22/85,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/15/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52225,58872,53493,PRETRIAL,STEELE,GREGORY,NULL,Male,Caucasian,11/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/15/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +52225,58872,53493,PRETRIAL,STEELE,GREGORY,NULL,Male,Caucasian,11/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/15/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +52225,58872,53493,PRETRIAL,STEELE,GREGORY,NULL,Male,Caucasian,11/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/15/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +52209,58857,53478,PRETRIAL,Bryant,Devan,NULL,Male,African-American,03/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,4,High,7,Risk of Violence,-1.19,8,High,New,1,0 +52209,58857,53478,PRETRIAL,Bryant,Devan,NULL,Male,African-American,03/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,4,High,8,Risk of Recidivism,0.55,9,High,New,1,0 +52209,58857,53478,PRETRIAL,Bryant,Devan,NULL,Male,African-American,03/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52214,58864,53485,PRETRIAL,Tolliver,Tevin,NULL,Male,African-American,05/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.02,8,High,New,1,0 +52214,58864,53485,PRETRIAL,Tolliver,Tevin,NULL,Male,African-American,05/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +52214,58864,53485,PRETRIAL,Tolliver,Tevin,NULL,Male,African-American,05/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52211,58860,53481,PRETRIAL,Mckenzie,Dainsley,NULL,Male,African-American,09/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +52211,58860,53481,PRETRIAL,Mckenzie,Dainsley,NULL,Male,African-American,09/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +52211,58860,53481,PRETRIAL,Mckenzie,Dainsley,NULL,Male,African-American,09/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52222,58869,53490,Probation,Anderson,John,NULL,Male,African-American,07/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +52222,58869,53490,Probation,Anderson,John,NULL,Male,African-American,07/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +52222,58869,53490,Probation,Anderson,John,NULL,Male,African-American,07/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52220,58867,53488,PRETRIAL,Henry,Richard,NULL,Male,African-American,02/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +52220,58867,53488,PRETRIAL,Henry,Richard,NULL,Male,African-American,02/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +52220,58867,53488,PRETRIAL,Henry,Richard,NULL,Male,African-American,02/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52226,58874,53495,Probation,maclaughlin,pamela,NULL,Female,Caucasian,09/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/15/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +52226,58874,53495,Probation,maclaughlin,pamela,NULL,Female,Caucasian,09/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/15/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +52226,58874,53495,Probation,maclaughlin,pamela,NULL,Female,Caucasian,09/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52228,58876,53496,PRETRIAL,NORRIS,JONATHAN,NULL,Male,Caucasian,08/31/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +52228,58876,53496,PRETRIAL,NORRIS,JONATHAN,NULL,Male,Caucasian,08/31/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +52228,58876,53496,PRETRIAL,NORRIS,JONATHAN,NULL,Male,Caucasian,08/31/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52242,58895,53514,PRETRIAL,Segura,Xavier,NULL,Male,Caucasian,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/16/13 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +52242,58895,53514,PRETRIAL,Segura,Xavier,NULL,Male,Caucasian,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/16/13 0:00,4,High,8,Risk of Recidivism,0.99,10,High,New,1,0 +52242,58895,53514,PRETRIAL,Segura,Xavier,NULL,Male,Caucasian,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/16/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52244,58897,53516,PRETRIAL,Mayor,Vashty,NULL,Female,Caucasian,07/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +52244,58897,53516,PRETRIAL,Mayor,Vashty,NULL,Female,Caucasian,07/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +52244,58897,53516,PRETRIAL,Mayor,Vashty,NULL,Female,Caucasian,07/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52238,58890,53510,PRETRIAL,Fialkowsky,Kristine,NULL,Male,Caucasian,05/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +52238,58890,53510,PRETRIAL,Fialkowsky,Kristine,NULL,Male,Caucasian,05/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +52238,58890,53510,PRETRIAL,Fialkowsky,Kristine,NULL,Male,Caucasian,05/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +49851,58885,53505,PRETRIAL,PINKNEY,FREDERICK,NULL,Male,African-American,09/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +49851,58885,53505,PRETRIAL,PINKNEY,FREDERICK,NULL,Male,African-American,09/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +49851,58885,53505,PRETRIAL,PINKNEY,FREDERICK,NULL,Male,African-American,09/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +52234,58886,53506,PRETRIAL,Abdo,Mories,NULL,Male,Arabic,10/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/16/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +52234,58886,53506,PRETRIAL,Abdo,Mories,NULL,Male,Arabic,10/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/16/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +52234,58886,53506,PRETRIAL,Abdo,Mories,NULL,Male,Arabic,10/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52246,58899,53518,PRETRIAL,Taylor,Eric,NULL,Male,African-American,08/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +52246,58899,53518,PRETRIAL,Taylor,Eric,NULL,Male,African-American,08/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +52246,58899,53518,PRETRIAL,Taylor,Eric,NULL,Male,African-American,08/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52239,58891,53511,PRETRIAL,GEORGE,MATTHEW,VIDICAN,Male,Caucasian,11/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +52239,58891,53511,PRETRIAL,GEORGE,MATTHEW,VIDICAN,Male,Caucasian,11/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +52239,58891,53511,PRETRIAL,GEORGE,MATTHEW,VIDICAN,Male,Caucasian,11/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52241,58893,53513,PRETRIAL,LATTIMORE,CRAIG,E,Male,African-American,09/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +52241,58893,53513,PRETRIAL,LATTIMORE,CRAIG,E,Male,African-American,09/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +52241,58893,53513,PRETRIAL,LATTIMORE,CRAIG,E,Male,African-American,09/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52236,58888,53508,PRETRIAL,Buchheit,John,NULL,Male,Caucasian,03/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +52236,58888,53508,PRETRIAL,Buchheit,John,NULL,Male,Caucasian,03/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +52236,58888,53508,PRETRIAL,Buchheit,John,NULL,Male,Caucasian,03/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52230,58880,53500,PRETRIAL,Weston,Glenn,NULL,Male,African-American,01/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +52230,58880,53500,PRETRIAL,Weston,Glenn,NULL,Male,African-American,01/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +52230,58880,53500,PRETRIAL,Weston,Glenn,NULL,Male,African-American,01/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52232,58883,53503,PRETRIAL,Turello,Richard,NULL,Male,Caucasian,11/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/16/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +52232,58883,53503,PRETRIAL,Turello,Richard,NULL,Male,Caucasian,11/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/16/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +52232,58883,53503,PRETRIAL,Turello,Richard,NULL,Male,Caucasian,11/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52248,58901,53520,PRETRIAL,Gallagher,Tracy,NULL,Male,Caucasian,04/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +52248,58901,53520,PRETRIAL,Gallagher,Tracy,NULL,Male,Caucasian,04/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +52248,58901,53520,PRETRIAL,Gallagher,Tracy,NULL,Male,Caucasian,04/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52245,58898,53517,PRETRIAL,Vasquez,Jevon,NULL,Male,African-American,01/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +52245,58898,53517,PRETRIAL,Vasquez,Jevon,NULL,Male,African-American,01/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +52245,58898,53517,PRETRIAL,Vasquez,Jevon,NULL,Male,African-American,01/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +4349,58894,4053,PRETRIAL,FORERO,STEFANO,GAETANO,Male,Hispanic,11/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,Copy,1,0 +4349,58894,4053,PRETRIAL,FORERO,STEFANO,GAETANO,Male,Hispanic,11/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,Copy,1,0 +4349,58894,4053,PRETRIAL,FORERO,STEFANO,GAETANO,Male,Hispanic,11/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +52231,58882,53502,PRETRIAL,Louis,Cassandra,NULL,Female,Other,02/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/16/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +52231,58882,53502,PRETRIAL,Louis,Cassandra,NULL,Female,Other,02/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/16/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +52231,58882,53502,PRETRIAL,Louis,Cassandra,NULL,Female,Other,02/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52237,58889,53509,PRETRIAL,ALTENRIED,BRANDON,NULL,Male,African-American,03/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +52237,58889,53509,PRETRIAL,ALTENRIED,BRANDON,NULL,Male,African-American,03/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +52237,58889,53509,PRETRIAL,ALTENRIED,BRANDON,NULL,Male,African-American,03/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52243,58896,53515,PRETRIAL,Stephens,Keyanna,NULL,Female,African-American,09/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +52243,58896,53515,PRETRIAL,Stephens,Keyanna,NULL,Female,African-American,09/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +52243,58896,53515,PRETRIAL,Stephens,Keyanna,NULL,Female,African-American,09/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52240,58892,53512,PRETRIAL,AZIM,AHARON,NULL,Male,Caucasian,01/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/16/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +52240,58892,53512,PRETRIAL,AZIM,AHARON,NULL,Male,Caucasian,01/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/16/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +52240,58892,53512,PRETRIAL,AZIM,AHARON,NULL,Male,Caucasian,01/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52233,58884,53504,PRETRIAL,Pena,Gerald,NULL,Male,Hispanic,04/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +52233,58884,53504,PRETRIAL,Pena,Gerald,NULL,Male,Hispanic,04/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +52233,58884,53504,PRETRIAL,Pena,Gerald,NULL,Male,Hispanic,04/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52235,58887,53507,PRETRIAL,TRACEY,COURTNEY,ABBDULE,Male,African-American,07/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +52235,58887,53507,PRETRIAL,TRACEY,COURTNEY,ABBDULE,Male,African-American,07/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +52235,58887,53507,PRETRIAL,TRACEY,COURTNEY,ABBDULE,Male,African-American,07/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52247,58900,53519,PRETRIAL,Hidalgo,Juan,C,Male,Caucasian,08/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +52247,58900,53519,PRETRIAL,Hidalgo,Juan,C,Male,Caucasian,08/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +52247,58900,53519,PRETRIAL,Hidalgo,Juan,C,Male,Caucasian,08/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52265,58921,53537,PRETRIAL,JOHNSON,JAMAR,ANTONIO,Male,African-American,08/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +52265,58921,53537,PRETRIAL,JOHNSON,JAMAR,ANTONIO,Male,African-American,08/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +52265,58921,53537,PRETRIAL,JOHNSON,JAMAR,ANTONIO,Male,African-American,08/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50045,58908,50993,PRETRIAL,Brown,Jetadia,NULL,Female,African-American,10/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,Copy,1,0 +50045,58908,50993,PRETRIAL,Brown,Jetadia,NULL,Female,African-American,10/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,Copy,1,0 +50045,58908,50993,PRETRIAL,Brown,Jetadia,NULL,Female,African-American,10/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +52266,58926,53540,PRETRIAL,Alexander,Courtney,Errol,Male,African-American,05/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +52266,58926,53540,PRETRIAL,Alexander,Courtney,Errol,Male,African-American,05/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +52266,58926,53540,PRETRIAL,Alexander,Courtney,Errol,Male,African-American,05/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52259,58913,53531,PRETRIAL,Hunter,Taric,NULL,Male,African-American,07/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +52259,58913,53531,PRETRIAL,Hunter,Taric,NULL,Male,African-American,07/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +52259,58913,53531,PRETRIAL,Hunter,Taric,NULL,Male,African-American,07/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52250,58903,53522,PRETRIAL,Bailey,Jovan,NULL,Male,African-American,11/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +52250,58903,53522,PRETRIAL,Bailey,Jovan,NULL,Male,African-American,11/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +52250,58903,53522,PRETRIAL,Bailey,Jovan,NULL,Male,African-American,11/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52262,58917,53534,PRETRIAL,Abouhana,Talal,NULL,Male,Arabic,04/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +52262,58917,53534,PRETRIAL,Abouhana,Talal,NULL,Male,Arabic,04/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +52262,58917,53534,PRETRIAL,Abouhana,Talal,NULL,Male,Arabic,04/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52256,58910,53528,PRETRIAL,NOREUS,EMMANUEL,NULL,Male,African-American,05/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +52256,58910,53528,PRETRIAL,NOREUS,EMMANUEL,NULL,Male,African-American,05/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +52256,58910,53528,PRETRIAL,NOREUS,EMMANUEL,NULL,Male,African-American,05/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +33731,58924,32834,PRETRIAL,Smith,Gordon,NULL,Male,African-American,01/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,Copy,1,0 +33731,58924,32834,PRETRIAL,Smith,Gordon,NULL,Male,African-American,01/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,Copy,1,0 +33731,58924,32834,PRETRIAL,Smith,Gordon,NULL,Male,African-American,01/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +31208,58915,30225,PRETRIAL,Zafir,Wayne,NULL,Male,Caucasian,04/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,Copy,1,0 +31208,58915,30225,PRETRIAL,Zafir,Wayne,NULL,Male,Caucasian,04/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,Copy,1,0 +31208,58915,30225,PRETRIAL,Zafir,Wayne,NULL,Male,Caucasian,04/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +52258,58912,53530,PRETRIAL,STUBBS,KIP,NULL,Male,African-American,04/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +52258,58912,53530,PRETRIAL,STUBBS,KIP,NULL,Male,African-American,04/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +52258,58912,53530,PRETRIAL,STUBBS,KIP,NULL,Male,African-American,04/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +40820,58919,40463,PRETRIAL,SIMMONS,DWAYNE,NULL,Male,African-American,04/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,Copy,1,0 +40820,58919,40463,PRETRIAL,SIMMONS,DWAYNE,NULL,Male,African-American,04/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,Copy,1,0 +40820,58919,40463,PRETRIAL,SIMMONS,DWAYNE,NULL,Male,African-American,04/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +41800,58922,53538,Probation,monserrate,jose,NULL,Male,Hispanic,05/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +41800,58922,53538,Probation,monserrate,jose,NULL,Male,Hispanic,05/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +41800,58922,53538,Probation,monserrate,jose,NULL,Male,Hispanic,05/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52255,58909,53527,PRETRIAL,Kelly,Shawanna,NULL,Female,African-American,03/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +52255,58909,53527,PRETRIAL,Kelly,Shawanna,NULL,Female,African-American,03/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,8,High,New,1,0 +52255,58909,53527,PRETRIAL,Kelly,Shawanna,NULL,Female,African-American,03/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52253,58906,53525,PRETRIAL,Olreidge,Jason,NULL,Male,African-American,03/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +52253,58906,53525,PRETRIAL,Olreidge,Jason,NULL,Male,African-American,03/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +52253,58906,53525,PRETRIAL,Olreidge,Jason,NULL,Male,African-American,03/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52254,58907,53526,PRETRIAL,MORGAN,LUKE,ANTHONY,Male,African-American,10/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +52254,58907,53526,PRETRIAL,MORGAN,LUKE,ANTHONY,Male,African-American,10/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +52254,58907,53526,PRETRIAL,MORGAN,LUKE,ANTHONY,Male,African-American,10/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +52260,58914,53532,PRETRIAL,TOUSSAINT,GUY,NULL,Male,African-American,01/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/17/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +52260,58914,53532,PRETRIAL,TOUSSAINT,GUY,NULL,Male,African-American,01/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/17/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +52260,58914,53532,PRETRIAL,TOUSSAINT,GUY,NULL,Male,African-American,01/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52264,58920,53536,PRETRIAL,Black,Daniel,NULL,Male,African-American,09/02/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/17/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +52264,58920,53536,PRETRIAL,Black,Daniel,NULL,Male,African-American,09/02/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/17/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +52264,58920,53536,PRETRIAL,Black,Daniel,NULL,Male,African-American,09/02/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/17/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52257,58911,53529,PRETRIAL,Smith,Willie,NULL,Male,African-American,01/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +52257,58911,53529,PRETRIAL,Smith,Willie,NULL,Male,African-American,01/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +52257,58911,53529,PRETRIAL,Smith,Willie,NULL,Male,African-American,01/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52249,58902,53521,PRETRIAL,Delvecchio,Louis,NULL,Male,Caucasian,09/20/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +52249,58902,53521,PRETRIAL,Delvecchio,Louis,NULL,Male,Caucasian,09/20/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +52249,58902,53521,PRETRIAL,Delvecchio,Louis,NULL,Male,Caucasian,09/20/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +52261,58916,53533,PRETRIAL,Duvignaud,Jacques,NULL,Male,Other,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +52261,58916,53533,PRETRIAL,Duvignaud,Jacques,NULL,Male,Other,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +52261,58916,53533,PRETRIAL,Duvignaud,Jacques,NULL,Male,Other,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +25116,58923,53539,PRETRIAL,Boyd,Demetrius,NULL,Male,African-American,07/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,4,High,7,Risk of Violence,-0.84,9,High,New,1,0 +25116,58923,53539,PRETRIAL,Boyd,Demetrius,NULL,Male,African-American,07/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +25116,58923,53539,PRETRIAL,Boyd,Demetrius,NULL,Male,African-American,07/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +35407,58925,34624,PRETRIAL,ayala-adorno,luis,angel,Male,Hispanic,12/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,Copy,1,0 +35407,58925,34624,PRETRIAL,ayala-adorno,luis,angel,Male,Hispanic,12/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,8,High,Copy,1,0 +35407,58925,34624,PRETRIAL,ayala-adorno,luis,angel,Male,Hispanic,12/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,8,High,Copy,1,0 +52263,58918,53535,PRETRIAL,Espinosa,Josue,NULL,Male,Hispanic,04/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/17/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +52263,58918,53535,PRETRIAL,Espinosa,Josue,NULL,Male,Hispanic,04/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/17/13 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +52263,58918,53535,PRETRIAL,Espinosa,Josue,NULL,Male,Hispanic,04/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52271,58932,53546,PRETRIAL,WARE,KIMBERLY,NULL,Female,African-American,03/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/18/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +52271,58932,53546,PRETRIAL,WARE,KIMBERLY,NULL,Female,African-American,03/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/18/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +52271,58932,53546,PRETRIAL,WARE,KIMBERLY,NULL,Female,African-American,03/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52276,58939,53552,PRETRIAL,Wilson,Jeremiah,NULL,Male,African-American,06/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +52276,58939,53552,PRETRIAL,Wilson,Jeremiah,NULL,Male,African-American,06/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +52276,58939,53552,PRETRIAL,Wilson,Jeremiah,NULL,Male,African-American,06/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52284,58946,53559,PRETRIAL,Lockrage,Eli,NULL,Male,African-American,09/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +52284,58946,53559,PRETRIAL,Lockrage,Eli,NULL,Male,African-American,09/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +52284,58946,53559,PRETRIAL,Lockrage,Eli,NULL,Male,African-American,09/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52275,58937,53550,PRETRIAL,CARRINGTON,ANDERSON,DELROY,Male,African-American,01/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,7,Risk of Violence,-2.7,2,Low,New,1,0 +52275,58937,53550,PRETRIAL,CARRINGTON,ANDERSON,DELROY,Male,African-American,01/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +52275,58937,53550,PRETRIAL,CARRINGTON,ANDERSON,DELROY,Male,African-American,01/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52279,58941,53554,PRETRIAL,VIANA,FABIO,SILVA,Male,Caucasian,12/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +52279,58941,53554,PRETRIAL,VIANA,FABIO,SILVA,Male,Caucasian,12/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +52279,58941,53554,PRETRIAL,VIANA,FABIO,SILVA,Male,Caucasian,12/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52274,58935,53549,PRETRIAL,MOSLEY,DEON,MAURRICE,Male,African-American,10/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +52274,58935,53549,PRETRIAL,MOSLEY,DEON,MAURRICE,Male,African-American,10/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +52274,58935,53549,PRETRIAL,MOSLEY,DEON,MAURRICE,Male,African-American,10/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +31193,58927,53541,PRETRIAL,JOHNSON,VERNON,ANTONIO,Male,African-American,11/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,7,Risk of Violence,-3.12,1,Low,New,1,0 +31193,58927,53541,PRETRIAL,JOHNSON,VERNON,ANTONIO,Male,African-American,11/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +31193,58927,53541,PRETRIAL,JOHNSON,VERNON,ANTONIO,Male,African-American,11/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +52281,58943,53556,PRETRIAL,Bandie,Andre,NULL,Male,African-American,02/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/18/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +52281,58943,53556,PRETRIAL,Bandie,Andre,NULL,Male,African-American,02/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/18/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +52281,58943,53556,PRETRIAL,Bandie,Andre,NULL,Male,African-American,02/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52269,58930,53544,PRETRIAL,Dillon,Paul,NULL,Male,Other,07/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/18/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +52269,58930,53544,PRETRIAL,Dillon,Paul,NULL,Male,Other,07/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/18/13 0:00,1,Low,8,Risk of Recidivism,-2.73,1,Low,New,1,0 +52269,58930,53544,PRETRIAL,Dillon,Paul,NULL,Male,Other,07/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52272,58933,53547,PRETRIAL,BUTLER,CARLOS,NULL,Male,African-American,05/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +52272,58933,53547,PRETRIAL,BUTLER,CARLOS,NULL,Male,African-American,05/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +52272,58933,53547,PRETRIAL,BUTLER,CARLOS,NULL,Male,African-American,05/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52283,58945,53558,PRETRIAL,Willis,Grover,NULL,Male,African-American,10/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +52283,58945,53558,PRETRIAL,Willis,Grover,NULL,Male,African-American,10/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +52283,58945,53558,PRETRIAL,Willis,Grover,NULL,Male,African-American,10/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52267,58928,53542,PRETRIAL,Wilson,Vanessa,NULL,Female,African-American,02/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/18/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +52267,58928,53542,PRETRIAL,Wilson,Vanessa,NULL,Female,African-American,02/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/18/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +52267,58928,53542,PRETRIAL,Wilson,Vanessa,NULL,Female,African-American,02/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52270,58931,53545,PRETRIAL,WILSON,GREGORY,NULL,Male,African-American,08/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/18/13 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +52270,58931,53545,PRETRIAL,WILSON,GREGORY,NULL,Male,African-American,08/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/18/13 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +52270,58931,53545,PRETRIAL,WILSON,GREGORY,NULL,Male,African-American,08/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52277,58938,53551,PRETRIAL,MARIANO,JESUS,NULL,Male,Hispanic,03/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +52277,58938,53551,PRETRIAL,MARIANO,JESUS,NULL,Male,Hispanic,03/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,4,High,8,Risk of Recidivism,0.48,9,High,New,1,0 +52277,58938,53551,PRETRIAL,MARIANO,JESUS,NULL,Male,Hispanic,03/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +52278,58940,53553,PRETRIAL,GASPARD,YVON,NULL,Male,African-American,12/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +52278,58940,53553,PRETRIAL,GASPARD,YVON,NULL,Male,African-American,12/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,4,High,8,Risk of Recidivism,0.36,9,High,New,1,0 +52278,58940,53553,PRETRIAL,GASPARD,YVON,NULL,Male,African-American,12/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52273,58934,53548,PRETRIAL,HERNANDEZ,JULISSA,NULL,Male,Caucasian,07/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +52273,58934,53548,PRETRIAL,HERNANDEZ,JULISSA,NULL,Male,Caucasian,07/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +52273,58934,53548,PRETRIAL,HERNANDEZ,JULISSA,NULL,Male,Caucasian,07/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52280,58942,53555,PRETRIAL,WILSON,CRISSIE,NULL,Female,African-American,01/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +52280,58942,53555,PRETRIAL,WILSON,CRISSIE,NULL,Female,African-American,01/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,7,Medium,New,1,0 +52280,58942,53555,PRETRIAL,WILSON,CRISSIE,NULL,Female,African-American,01/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +52282,58944,53557,PRETRIAL,goffee,caswell,antonio,Male,African-American,10/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +52282,58944,53557,PRETRIAL,goffee,caswell,antonio,Male,African-American,10/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +52282,58944,53557,PRETRIAL,goffee,caswell,antonio,Male,African-American,10/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52268,58929,53543,PRETRIAL,De La Rosa,Froilan,NULL,Male,Hispanic,03/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/18/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +52268,58929,53543,PRETRIAL,De La Rosa,Froilan,NULL,Male,Hispanic,03/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/18/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +52268,58929,53543,PRETRIAL,De La Rosa,Froilan,NULL,Male,Hispanic,03/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/18/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +4367,58936,4072,PRETRIAL,bacon,michael,NULL,Male,African-American,05/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,Copy,1,0 +4367,58936,4072,PRETRIAL,bacon,michael,NULL,Male,African-American,05/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,Copy,1,0 +4367,58936,4072,PRETRIAL,bacon,michael,NULL,Male,African-American,05/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +52289,58950,53563,PRETRIAL,Pine,Artie,NULL,Male,Caucasian,05/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +52289,58950,53563,PRETRIAL,Pine,Artie,NULL,Male,Caucasian,05/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +52289,58950,53563,PRETRIAL,Pine,Artie,NULL,Male,Caucasian,05/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51446,58986,53594,Probation,Tabraue,Joshua,NULL,Male,Hispanic,01/21/93,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,2/19/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +51446,58986,53594,Probation,Tabraue,Joshua,NULL,Male,Hispanic,01/21/93,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,2/19/13 0:00,2,Medium,8,Risk of Recidivism,0.1,7,Medium,New,1,0 +51446,58986,53594,Probation,Tabraue,Joshua,NULL,Male,Hispanic,01/21/93,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,2/19/13 0:00,2,Medium,18,Risk of Failure to Appear,22,4,Low,New,1,0 +52295,58957,53570,PRETRIAL,Wickman,James,Hubbard,Male,Caucasian,10/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +52295,58957,53570,PRETRIAL,Wickman,James,Hubbard,Male,Caucasian,10/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +52295,58957,53570,PRETRIAL,Wickman,James,Hubbard,Male,Caucasian,10/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52304,58971,53581,PRETRIAL,jackson,deon,NULL,Male,African-American,10/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,4,High,7,Risk of Violence,-0.64,9,High,New,1,0 +52304,58971,53581,PRETRIAL,jackson,deon,NULL,Male,African-American,10/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,4,High,8,Risk of Recidivism,0.73,10,High,New,1,0 +52304,58971,53581,PRETRIAL,jackson,deon,NULL,Male,African-American,10/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52299,58963,53576,PRETRIAL,Oussifi,Shawanna,Y,Female,African-American,08/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/19/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +52299,58963,53576,PRETRIAL,Oussifi,Shawanna,Y,Female,African-American,08/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/19/13 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +52299,58963,53576,PRETRIAL,Oussifi,Shawanna,Y,Female,African-American,08/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50514,58965,51552,Probation,Willet,Charles,Delano,Male,Caucasian,12/10/83,17,All Scales,Intake,English,Conditional Release,Probation,Separated,2/19/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +50514,58965,51552,Probation,Willet,Charles,Delano,Male,Caucasian,12/10/83,17,All Scales,Intake,English,Conditional Release,Probation,Separated,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.38,4,Low,New,1,0 +50514,58965,51552,Probation,Willet,Charles,Delano,Male,Caucasian,12/10/83,17,All Scales,Intake,English,Conditional Release,Probation,Separated,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +52303,58970,53580,Probation,surrago,jason,NULL,Male,Caucasian,11/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +52303,58970,53580,Probation,surrago,jason,NULL,Male,Caucasian,11/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +52303,58970,53580,Probation,surrago,jason,NULL,Male,Caucasian,11/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52324,58999,53607,PRETRIAL,SOMERS,MICHAEL,NULL,Male,Caucasian,10/31/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.51,3,Low,New,1,0 +52324,58999,53607,PRETRIAL,SOMERS,MICHAEL,NULL,Male,Caucasian,10/31/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +52324,58999,53607,PRETRIAL,SOMERS,MICHAEL,NULL,Male,Caucasian,10/31/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52309,58978,53587,PRETRIAL,JAIGOBIN,JASON,AKASH,Male,Caucasian,03/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +52309,58978,53587,PRETRIAL,JAIGOBIN,JASON,AKASH,Male,Caucasian,03/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +52309,58978,53587,PRETRIAL,JAIGOBIN,JASON,AKASH,Male,Caucasian,03/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52318,58991,53599,Probation,nigro,albert,NULL,Male,Caucasian,01/11/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +52318,58991,53599,Probation,nigro,albert,NULL,Male,Caucasian,01/11/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +52318,58991,53599,Probation,nigro,albert,NULL,Male,Caucasian,01/11/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52290,58952,53565,PRETRIAL,Clarke,Alphanso,Augustine,Male,Other,04/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +52290,58952,53565,PRETRIAL,Clarke,Alphanso,Augustine,Male,Other,04/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +52290,58952,53565,PRETRIAL,Clarke,Alphanso,Augustine,Male,Other,04/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52293,58955,53568,PRETRIAL,Johnson,Vashay,NULL,Male,African-American,05/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,4,High,7,Risk of Violence,-0.27,10,High,New,1,0 +52293,58955,53568,PRETRIAL,Johnson,Vashay,NULL,Male,African-American,05/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +52293,58955,53568,PRETRIAL,Johnson,Vashay,NULL,Male,African-American,05/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +4720,58973,53583,PRETRIAL,GRIFFIN,JAMAL,NULL,Male,African-American,08/29/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +4720,58973,53583,PRETRIAL,GRIFFIN,JAMAL,NULL,Male,African-American,08/29/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.2,5,Medium,New,1,0 +4720,58973,53583,PRETRIAL,GRIFFIN,JAMAL,NULL,Male,African-American,08/29/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52285,58947,53560,PRETRIAL,Major,Antwon,Demetrick,Male,African-American,02/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/19/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +52285,58947,53560,PRETRIAL,Major,Antwon,Demetrick,Male,African-American,02/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/19/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +52285,58947,53560,PRETRIAL,Major,Antwon,Demetrick,Male,African-American,02/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52313,58981,53590,PRETRIAL,FARROW,MICHAEL,NULL,Male,Caucasian,07/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +52313,58981,53590,PRETRIAL,FARROW,MICHAEL,NULL,Male,Caucasian,07/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +52313,58981,53590,PRETRIAL,FARROW,MICHAEL,NULL,Male,Caucasian,07/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +11298,58960,53573,Probation,Twiggs,Keandre,Juwann,Male,African-American,03/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +11298,58960,53573,Probation,Twiggs,Keandre,Juwann,Male,African-American,03/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +11298,58960,53573,Probation,Twiggs,Keandre,Juwann,Male,African-American,03/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +12349,58994,53602,PRETRIAL,GONZALEZ,JOSE,NULL,Male,Hispanic,08/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +12349,58994,53602,PRETRIAL,GONZALEZ,JOSE,NULL,Male,Hispanic,08/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +12349,58994,53602,PRETRIAL,GONZALEZ,JOSE,NULL,Male,Hispanic,08/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52297,58959,53572,PRETRIAL,Grant,Kevin,E,Male,Other,10/07/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +52297,58959,53572,PRETRIAL,Grant,Kevin,E,Male,Other,10/07/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +52297,58959,53572,PRETRIAL,Grant,Kevin,E,Male,Other,10/07/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +5194,58961,53574,Probation,Delacruz,Jose,Francisco,Male,Hispanic,02/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +5194,58961,53574,Probation,Delacruz,Jose,Francisco,Male,Hispanic,02/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +5194,58961,53574,Probation,Delacruz,Jose,Francisco,Male,Hispanic,02/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50892,58968,52011,PRETRIAL,Yunis,Omar,Nassim,Male,Caucasian,08/29/92,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,Copy,1,0 +50892,58968,52011,PRETRIAL,Yunis,Omar,Nassim,Male,Caucasian,08/29/92,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,4,High,8,Risk of Recidivism,0.37,9,High,Copy,1,0 +50892,58968,52011,PRETRIAL,Yunis,Omar,Nassim,Male,Caucasian,08/29/92,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +52321,58996,53604,Probation,Cole,Sandy,NULL,Female,African-American,12/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +52321,58996,53604,Probation,Cole,Sandy,NULL,Female,African-American,12/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +52321,58996,53604,Probation,Cole,Sandy,NULL,Female,African-American,12/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +52307,58975,53585,Probation,MOSS,LEVY,NULL,Male,African-American,03/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/19/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +52307,58975,53585,Probation,MOSS,LEVY,NULL,Male,African-American,03/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/19/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +52307,58975,53585,Probation,MOSS,LEVY,NULL,Male,African-American,03/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52287,58949,53562,PRETRIAL,FRANCOIS,FELIX,NULL,Male,African-American,08/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/19/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +52287,58949,53562,PRETRIAL,FRANCOIS,FELIX,NULL,Male,African-American,08/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/19/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +52287,58949,53562,PRETRIAL,FRANCOIS,FELIX,NULL,Male,African-American,08/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52292,58954,53567,PRETRIAL,Jean,Marc,NULL,Male,African-American,09/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +52292,58954,53567,PRETRIAL,Jean,Marc,NULL,Male,African-American,09/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +52292,58954,53567,PRETRIAL,Jean,Marc,NULL,Male,African-American,09/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52301,58966,53578,PRETRIAL,Colon,Brayan,NULL,Male,Hispanic,12/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +52301,58966,53578,PRETRIAL,Colon,Brayan,NULL,Male,Hispanic,12/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +52301,58966,53578,PRETRIAL,Colon,Brayan,NULL,Male,Hispanic,12/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52311,58980,53589,PRETRIAL,ASHTON,TYLER,AARON,Male,Caucasian,03/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +52311,58980,53589,PRETRIAL,ASHTON,TYLER,AARON,Male,Caucasian,03/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +52311,58980,53589,PRETRIAL,ASHTON,TYLER,AARON,Male,Caucasian,03/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52316,58987,53595,Probation,elmquist,jason,NULL,Male,Caucasian,08/03/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/19/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +52316,58987,53595,Probation,elmquist,jason,NULL,Male,Caucasian,08/03/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +52316,58987,53595,Probation,elmquist,jason,NULL,Male,Caucasian,08/03/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52286,58948,53561,PRETRIAL,PHILLIPS,MARSHALL,NULL,Male,African-American,09/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +52286,58948,53561,PRETRIAL,PHILLIPS,MARSHALL,NULL,Male,African-American,09/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +52286,58948,53561,PRETRIAL,PHILLIPS,MARSHALL,NULL,Male,African-American,09/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52323,58998,53606,Probation,andrews,devon,NULL,Male,African-American,11/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.14,4,Low,New,1,0 +52323,58998,53606,Probation,andrews,devon,NULL,Male,African-American,11/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +52323,58998,53606,Probation,andrews,devon,NULL,Male,African-American,11/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52288,58951,53564,PRETRIAL,SCHARENBROICH,JUSTIN,JEFFREY,Male,Caucasian,11/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +52288,58951,53564,PRETRIAL,SCHARENBROICH,JUSTIN,JEFFREY,Male,Caucasian,11/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +52288,58951,53564,PRETRIAL,SCHARENBROICH,JUSTIN,JEFFREY,Male,Caucasian,11/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52302,58969,53579,Probation,Roden,James,Harold,Male,Caucasian,04/28/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +52302,58969,53579,Probation,Roden,James,Harold,Male,Caucasian,04/28/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +52302,58969,53579,Probation,Roden,James,Harold,Male,Caucasian,04/28/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +52308,58977,53586,PRETRIAL,Gallego,Stefany,NULL,Female,Caucasian,05/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +52308,58977,53586,PRETRIAL,Gallego,Stefany,NULL,Female,Caucasian,05/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +52308,58977,53586,PRETRIAL,Gallego,Stefany,NULL,Female,Caucasian,05/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52294,58956,53569,PRETRIAL,fountain,andreas,NULL,Male,African-American,08/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.41,3,Low,New,1,0 +52294,58956,53569,PRETRIAL,fountain,andreas,NULL,Male,African-American,08/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +52294,58956,53569,PRETRIAL,fountain,andreas,NULL,Male,African-American,08/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +33551,58990,53598,PRETRIAL,Blanco,Elmer,NULL,Male,Hispanic,10/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/19/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +33551,58990,53598,PRETRIAL,Blanco,Elmer,NULL,Male,Hispanic,10/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +33551,58990,53598,PRETRIAL,Blanco,Elmer,NULL,Male,Hispanic,10/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52320,58993,53601,PRETRIAL,FRASCA,AGOSTINA,NULL,Female,Caucasian,03/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +52320,58993,53601,PRETRIAL,FRASCA,AGOSTINA,NULL,Female,Caucasian,03/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +52320,58993,53601,PRETRIAL,FRASCA,AGOSTINA,NULL,Female,Caucasian,03/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52305,58972,53582,Probation,Bruch,Brain,NULL,Male,Caucasian,05/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +52305,58972,53582,Probation,Bruch,Brain,NULL,Male,Caucasian,05/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +52305,58972,53582,Probation,Bruch,Brain,NULL,Male,Caucasian,05/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52315,58985,53593,PRETRIAL,bradshaw,nina,NULL,Female,Caucasian,01/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +52315,58985,53593,PRETRIAL,bradshaw,nina,NULL,Female,Caucasian,01/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +52315,58985,53593,PRETRIAL,bradshaw,nina,NULL,Female,Caucasian,01/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52327,59000,53608,PRETRIAL,cruz,moises,NULL,Male,Hispanic,06/27/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +52327,59000,53608,PRETRIAL,cruz,moises,NULL,Male,Hispanic,06/27/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +52327,59000,53608,PRETRIAL,cruz,moises,NULL,Male,Hispanic,06/27/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,2,Medium,18,Risk of Failure to Appear,18,2,Low,New,1,0 +52300,58964,53577,PRETRIAL,Velasquezhernandez,Fernando,Antonio,Male,Hispanic,05/30/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/19/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +52300,58964,53577,PRETRIAL,Velasquezhernandez,Fernando,Antonio,Male,Hispanic,05/30/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/19/13 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +52300,58964,53577,PRETRIAL,Velasquezhernandez,Fernando,Antonio,Male,Hispanic,05/30/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52296,58958,53571,PRETRIAL,SHULER,RICKY,LEE,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,4,High,7,Risk of Violence,-0.53,10,High,New,1,0 +52296,58958,53571,PRETRIAL,SHULER,RICKY,LEE,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,4,High,8,Risk of Recidivism,0.32,9,High,New,1,0 +52296,58958,53571,PRETRIAL,SHULER,RICKY,LEE,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52319,58992,53600,Probation,Winski,George,Alexander,Male,Caucasian,06/12/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +52319,58992,53600,Probation,Winski,George,Alexander,Male,Caucasian,06/12/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +52319,58992,53600,Probation,Winski,George,Alexander,Male,Caucasian,06/12/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52310,58979,53588,PRETRIAL,Wright,Thomas,NULL,Male,Caucasian,01/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/19/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +52310,58979,53588,PRETRIAL,Wright,Thomas,NULL,Male,Caucasian,01/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/19/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +52310,58979,53588,PRETRIAL,Wright,Thomas,NULL,Male,Caucasian,01/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +52317,58988,53596,PRETRIAL,abdelquader,emad,NULL,Male,Caucasian,12/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,New,1,0 +52317,58988,53596,PRETRIAL,abdelquader,emad,NULL,Male,Caucasian,12/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +52317,58988,53596,PRETRIAL,abdelquader,emad,NULL,Male,Caucasian,12/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52298,58962,53575,PRETRIAL,Dawson,Levar,NULL,Male,African-American,05/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +52298,58962,53575,PRETRIAL,Dawson,Levar,NULL,Male,African-American,05/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +52298,58962,53575,PRETRIAL,Dawson,Levar,NULL,Male,African-American,05/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +52291,58953,53566,PRETRIAL,Wilson,Ronnie,Matthew,Male,African-American,09/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +52291,58953,53566,PRETRIAL,Wilson,Ronnie,Matthew,Male,African-American,09/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +52291,58953,53566,PRETRIAL,Wilson,Ronnie,Matthew,Male,African-American,09/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50892,58967,52011,PRETRIAL,Yunis,Omar,Nassim,Male,Caucasian,08/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,Copy,1,0 +50892,58967,52011,PRETRIAL,Yunis,Omar,Nassim,Male,Caucasian,08/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,4,High,8,Risk of Recidivism,0.37,9,High,Copy,1,0 +50892,58967,52011,PRETRIAL,Yunis,Omar,Nassim,Male,Caucasian,08/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +48502,58976,49199,Probation,Montgomery,Robert,NULL,Male,African-American,07/14/83,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +48502,58976,49199,Probation,Montgomery,Robert,NULL,Male,African-American,07/14/83,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +48502,58976,49199,Probation,Montgomery,Robert,NULL,Male,African-American,07/14/83,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +16958,58995,53603,PRETRIAL,MAURI,DANIEL,NULL,Male,Caucasian,02/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +16958,58995,53603,PRETRIAL,MAURI,DANIEL,NULL,Male,Caucasian,02/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +16958,58995,53603,PRETRIAL,MAURI,DANIEL,NULL,Male,Caucasian,02/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52346,59025,53633,PRETRIAL,williams,chad,NULL,Male,African-American,01/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/13 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +52346,59025,53633,PRETRIAL,williams,chad,NULL,Male,African-American,01/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +52346,59025,53633,PRETRIAL,williams,chad,NULL,Male,African-American,01/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52331,59004,53612,PRETRIAL,Demps,Bradley,NULL,Male,African-American,10/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +52331,59004,53612,PRETRIAL,Demps,Bradley,NULL,Male,African-American,10/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +52331,59004,53612,PRETRIAL,Demps,Bradley,NULL,Male,African-American,10/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +52341,59018,53626,PRETRIAL,Brown,Breon,NULL,Male,African-American,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,2,Medium,7,Risk of Violence,-1.43,7,Medium,New,1,0 +52341,59018,53626,PRETRIAL,Brown,Breon,NULL,Male,African-American,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +52341,59018,53626,PRETRIAL,Brown,Breon,NULL,Male,African-American,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +40381,59053,39990,PRETRIAL,KORELISHA,STEPHEN,NULL,Male,Caucasian,12/08/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/20/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,Copy,1,0 +40381,59053,39990,PRETRIAL,KORELISHA,STEPHEN,NULL,Male,Caucasian,12/08/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/20/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,Copy,1,0 +40381,59053,39990,PRETRIAL,KORELISHA,STEPHEN,NULL,Male,Caucasian,12/08/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +44965,59032,45133,PRETRIAL,Headly,Deanna,NULL,Female,Caucasian,08/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,Copy,1,0 +44965,59032,45133,PRETRIAL,Headly,Deanna,NULL,Female,Caucasian,08/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,9,High,Copy,1,0 +44965,59032,45133,PRETRIAL,Headly,Deanna,NULL,Female,Caucasian,08/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +52350,59039,53639,PRETRIAL,Fanfan,Benjamin,NULL,Male,African-American,04/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,Copy,1,0 +52350,59039,53639,PRETRIAL,Fanfan,Benjamin,NULL,Male,African-American,04/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,Copy,1,0 +52350,59039,53639,PRETRIAL,Fanfan,Benjamin,NULL,Male,African-American,04/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +52359,59046,53648,Probation,Igus,Tavare,A,Male,African-American,01/08/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/20/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +52359,59046,53648,Probation,Igus,Tavare,A,Male,African-American,01/08/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/20/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +52359,59046,53648,Probation,Igus,Tavare,A,Male,African-American,01/08/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52349,59030,53638,PRETRIAL,simon,tanis,NULL,Male,African-American,05/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/20/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +52349,59030,53638,PRETRIAL,simon,tanis,NULL,Male,African-American,05/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +52349,59030,53638,PRETRIAL,simon,tanis,NULL,Male,African-American,05/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +44763,59048,53650,Probation,Ortega,Vladimir,NULL,Male,Hispanic,01/30/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/20/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +44763,59048,53650,Probation,Ortega,Vladimir,NULL,Male,Hispanic,01/30/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/20/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +44763,59048,53650,Probation,Ortega,Vladimir,NULL,Male,Hispanic,01/30/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52363,59055,53654,Probation,Zwick,Daniel,NULL,Male,Caucasian,08/31/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +52363,59055,53654,Probation,Zwick,Daniel,NULL,Male,Caucasian,08/31/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +52363,59055,53654,Probation,Zwick,Daniel,NULL,Male,Caucasian,08/31/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52342,59051,53628,PRETRIAL,Larosa,Francesca,NULL,Female,Caucasian,05/27/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/20/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,Copy,1,0 +52342,59051,53628,PRETRIAL,Larosa,Francesca,NULL,Female,Caucasian,05/27/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,Copy,1,0 +52342,59051,53628,PRETRIAL,Larosa,Francesca,NULL,Female,Caucasian,05/27/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +52338,59013,53621,PRETRIAL,JENKINS,ANTHONY,EDWARDS,Male,African-American,04/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,4,High,7,Risk of Violence,-0.92,9,High,New,1,0 +52338,59013,53621,PRETRIAL,JENKINS,ANTHONY,EDWARDS,Male,African-American,04/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,4,High,8,Risk of Recidivism,0.14,8,High,New,1,0 +52338,59013,53621,PRETRIAL,JENKINS,ANTHONY,EDWARDS,Male,African-American,04/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52334,59009,53617,PRETRIAL,BORDEN,JOHNNY,L,Male,African-American,06/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +52334,59009,53617,PRETRIAL,BORDEN,JOHNNY,L,Male,African-American,06/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +52334,59009,53617,PRETRIAL,BORDEN,JOHNNY,L,Male,African-American,06/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52367,59060,53658,PRETRIAL,evans,darrell,NULL,Male,Caucasian,06/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +52367,59060,53658,PRETRIAL,evans,darrell,NULL,Male,Caucasian,06/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +52367,59060,53658,PRETRIAL,evans,darrell,NULL,Male,Caucasian,06/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52339,59014,53622,PRETRIAL,Sean,Claesgens,NULL,Male,Caucasian,08/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +52339,59014,53622,PRETRIAL,Sean,Claesgens,NULL,Male,Caucasian,08/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +52339,59014,53622,PRETRIAL,Sean,Claesgens,NULL,Male,Caucasian,08/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52343,59021,53629,Probation,Forcer,Dawn,Alexandra,Female,African-American,09/19/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +52343,59021,53629,Probation,Forcer,Dawn,Alexandra,Female,African-American,09/19/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +52343,59021,53629,Probation,Forcer,Dawn,Alexandra,Female,African-American,09/19/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +52351,59035,53641,Probation,Geisler,Michael,NULL,Male,Caucasian,01/21/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/20/13 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +52351,59035,53641,Probation,Geisler,Michael,NULL,Male,Caucasian,01/21/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/20/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +52351,59035,53641,Probation,Geisler,Michael,NULL,Male,Caucasian,01/21/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +45514,59050,53652,PRETRIAL,MIKELAIT,RICKEY,NULL,Male,Caucasian,01/29/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +45514,59050,53652,PRETRIAL,MIKELAIT,RICKEY,NULL,Male,Caucasian,01/29/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +45514,59050,53652,PRETRIAL,MIKELAIT,RICKEY,NULL,Male,Caucasian,01/29/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52332,59006,53614,PRETRIAL,Freckleton,Errol,NULL,Male,Other,08/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +52332,59006,53614,PRETRIAL,Freckleton,Errol,NULL,Male,Other,08/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/13 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +52332,59006,53614,PRETRIAL,Freckleton,Errol,NULL,Male,Other,08/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52371,59063,53661,PRETRIAL,Moye,John,NULL,Male,African-American,12/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,4,High,7,Risk of Violence,-0.37,10,High,New,1,0 +52371,59063,53661,PRETRIAL,Moye,John,NULL,Male,African-American,12/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +52371,59063,53661,PRETRIAL,Moye,John,NULL,Male,African-American,12/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52333,59008,53616,PRETRIAL,Dawson,Demarquize,NULL,Male,African-American,11/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,2,Medium,7,Risk of Violence,-2.27,3,Low,New,1,0 +52333,59008,53616,PRETRIAL,Dawson,Demarquize,NULL,Male,African-American,11/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +52333,59008,53616,PRETRIAL,Dawson,Demarquize,NULL,Male,African-American,11/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52347,59027,53635,PRETRIAL,PIERRELOUIS,JAMES,NULL,Male,African-American,09/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +52347,59027,53635,PRETRIAL,PIERRELOUIS,JAMES,NULL,Male,African-American,09/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +52347,59027,53635,PRETRIAL,PIERRELOUIS,JAMES,NULL,Male,African-American,09/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52355,59042,53644,PRETRIAL,Kennedy,Patsy,NULL,Female,African-American,02/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +52355,59042,53644,PRETRIAL,Kennedy,Patsy,NULL,Female,African-American,02/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +52355,59042,53644,PRETRIAL,Kennedy,Patsy,NULL,Female,African-American,02/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52345,59024,53632,Probation,MARKS,CHERYL,NULL,Female,Caucasian,01/10/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/20/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +52345,59024,53632,Probation,MARKS,CHERYL,NULL,Female,Caucasian,01/10/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/20/13 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +52345,59024,53632,Probation,MARKS,CHERYL,NULL,Female,Caucasian,01/10/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52336,59011,53619,PRETRIAL,ELIZEE,FERNAND,NULL,Male,Other,01/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +52336,59011,53619,PRETRIAL,ELIZEE,FERNAND,NULL,Male,Other,01/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +52336,59011,53619,PRETRIAL,ELIZEE,FERNAND,NULL,Male,Other,01/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52358,59045,53647,Probation,METZGER,BUDD,W,Male,Caucasian,07/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +52358,59045,53647,Probation,METZGER,BUDD,W,Male,Caucasian,07/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +52358,59045,53647,Probation,METZGER,BUDD,W,Male,Caucasian,07/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52365,59058,53656,Probation,Pekhtereva,Anna,NULL,Female,Caucasian,04/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +52365,59058,53656,Probation,Pekhtereva,Anna,NULL,Female,Caucasian,04/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +52365,59058,53656,Probation,Pekhtereva,Anna,NULL,Female,Caucasian,04/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +15395,59016,53624,PRETRIAL,AVERY,ERIC,NULL,Male,Caucasian,06/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +15395,59016,53624,PRETRIAL,AVERY,ERIC,NULL,Male,Caucasian,06/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +15395,59016,53624,PRETRIAL,AVERY,ERIC,NULL,Male,Caucasian,06/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +45823,59019,53627,PRETRIAL,Batista,Reynaldo,NULL,Male,African-American,04/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,4,High,7,Risk of Violence,-0.63,9,High,New,1,0 +45823,59019,53627,PRETRIAL,Batista,Reynaldo,NULL,Male,African-American,04/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +45823,59019,53627,PRETRIAL,Batista,Reynaldo,NULL,Male,African-American,04/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +13278,59005,53613,PRETRIAL,SWINT,ADAM,NULL,Male,African-American,01/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +13278,59005,53613,PRETRIAL,SWINT,ADAM,NULL,Male,African-American,01/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +13278,59005,53613,PRETRIAL,SWINT,ADAM,NULL,Male,African-American,01/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52328,59001,53609,PRETRIAL,Briscoe,Duval,Oneal,Male,African-American,10/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +52328,59001,53609,PRETRIAL,Briscoe,Duval,Oneal,Male,African-American,10/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +52328,59001,53609,PRETRIAL,Briscoe,Duval,Oneal,Male,African-American,10/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +42899,59022,53630,PRETRIAL,Rosin,Paul,Steven,Male,Caucasian,08/10/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +42899,59022,53630,PRETRIAL,Rosin,Paul,Steven,Male,Caucasian,08/10/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +42899,59022,53630,PRETRIAL,Rosin,Paul,Steven,Male,Caucasian,08/10/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52360,59047,53649,Probation,Castano,Ivan,NULL,Male,Hispanic,03/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +52360,59047,53649,Probation,Castano,Ivan,NULL,Male,Hispanic,03/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +52360,59047,53649,Probation,Castano,Ivan,NULL,Male,Hispanic,03/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52364,59056,53655,Probation,Holston,Eunice,NULL,Female,African-American,06/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +52364,59056,53655,Probation,Holston,Eunice,NULL,Female,African-American,06/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.41,6,Medium,New,1,0 +52364,59056,53655,Probation,Holston,Eunice,NULL,Female,African-American,06/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +44287,59026,53634,PRETRIAL,Ferguson,Lascelles,NULL,Male,African-American,01/17/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/20/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +44287,59026,53634,PRETRIAL,Ferguson,Lascelles,NULL,Male,African-American,01/17/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/20/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +44287,59026,53634,PRETRIAL,Ferguson,Lascelles,NULL,Male,African-American,01/17/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52356,59043,53645,PRETRIAL,Stancil,John,NULL,Male,Caucasian,12/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +52356,59043,53645,PRETRIAL,Stancil,John,NULL,Male,Caucasian,12/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +52356,59043,53645,PRETRIAL,Stancil,John,NULL,Male,Caucasian,12/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52330,59003,53611,PRETRIAL,Ali,Fazeena,NULL,Female,Other,04/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +52330,59003,53611,PRETRIAL,Ali,Fazeena,NULL,Female,Other,04/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +52330,59003,53611,PRETRIAL,Ali,Fazeena,NULL,Female,Other,04/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52340,59017,53625,PRETRIAL,DUMEY,KEVIN,LEE,Male,Caucasian,09/13/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +52340,59017,53625,PRETRIAL,DUMEY,KEVIN,LEE,Male,Caucasian,09/13/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +52340,59017,53625,PRETRIAL,DUMEY,KEVIN,LEE,Male,Caucasian,09/13/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +25103,59038,29643,PRETRIAL,DURIZIL,EDDIE,NULL,Male,African-American,03/03/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,Copy,1,0 +25103,59038,29643,PRETRIAL,DURIZIL,EDDIE,NULL,Male,African-American,03/03/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,Copy,1,0 +25103,59038,29643,PRETRIAL,DURIZIL,EDDIE,NULL,Male,African-American,03/03/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +52353,59040,53642,Probation,KEELS,CEDRICK,MAURICE,Male,African-American,11/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +52353,59040,53642,Probation,KEELS,CEDRICK,MAURICE,Male,African-American,11/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +52353,59040,53642,Probation,KEELS,CEDRICK,MAURICE,Male,African-American,11/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52348,59028,53636,Probation,Louisa,Sandy,NULL,Male,African-American,09/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +52348,59028,53636,Probation,Louisa,Sandy,NULL,Male,African-American,09/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +52348,59028,53636,Probation,Louisa,Sandy,NULL,Male,African-American,09/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +52354,59041,53643,Probation,Bak,Jason,M,Male,Caucasian,03/27/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +52354,59041,53643,Probation,Bak,Jason,M,Male,Caucasian,03/27/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +52354,59041,53643,Probation,Bak,Jason,M,Male,Caucasian,03/27/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +34614,59015,53623,PRETRIAL,farrow,haywood,NULL,Male,African-American,11/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +34614,59015,53623,PRETRIAL,farrow,haywood,NULL,Male,African-American,11/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +34614,59015,53623,PRETRIAL,farrow,haywood,NULL,Male,African-American,11/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52361,59049,53651,Probation,MICHEL,COLLEEN,NULL,Female,Caucasian,02/28/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +52361,59049,53651,Probation,MICHEL,COLLEEN,NULL,Female,Caucasian,02/28/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +52361,59049,53651,Probation,MICHEL,COLLEEN,NULL,Female,Caucasian,02/28/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52337,59012,53620,PRETRIAL,OCTELUS,DANIELLA,NULL,Female,Other,01/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +52337,59012,53620,PRETRIAL,OCTELUS,DANIELLA,NULL,Female,Other,01/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +52337,59012,53620,PRETRIAL,OCTELUS,DANIELLA,NULL,Female,Other,01/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52344,59023,53631,PRETRIAL,MCLEMORE,ADRIAN,NULL,Male,African-American,06/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/13 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +52344,59023,53631,PRETRIAL,MCLEMORE,ADRIAN,NULL,Male,African-American,06/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/13 0:00,4,High,8,Risk of Recidivism,0.1,8,High,New,1,0 +52344,59023,53631,PRETRIAL,MCLEMORE,ADRIAN,NULL,Male,African-American,06/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52369,59062,53660,PRETRIAL,Siegel,Bruce,NULL,Male,Caucasian,05/31/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +52369,59062,53660,PRETRIAL,Siegel,Bruce,NULL,Male,Caucasian,05/31/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +52369,59062,53660,PRETRIAL,Siegel,Bruce,NULL,Male,Caucasian,05/31/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52329,59002,53610,PRETRIAL,BRACK,ROBERT,DANIEL,Male,Caucasian,06/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +52329,59002,53610,PRETRIAL,BRACK,ROBERT,DANIEL,Male,Caucasian,06/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.64,10,High,New,1,0 +52329,59002,53610,PRETRIAL,BRACK,ROBERT,DANIEL,Male,Caucasian,06/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52357,59044,53646,Probation,perez,Wesley,NULL,Male,Caucasian,05/18/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +52357,59044,53646,Probation,perez,Wesley,NULL,Male,Caucasian,05/18/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +52357,59044,53646,Probation,perez,Wesley,NULL,Male,Caucasian,05/18/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +9691,59007,53615,PRETRIAL,SAPP,NAJEE,JAMAL,Male,African-American,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,2,Medium,7,Risk of Violence,-1.27,7,Medium,New,1,0 +9691,59007,53615,PRETRIAL,SAPP,NAJEE,JAMAL,Male,African-American,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +9691,59007,53615,PRETRIAL,SAPP,NAJEE,JAMAL,Male,African-American,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52370,59064,53662,PRETRIAL,Perdomo,Johnny,NULL,Male,African-American,09/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +52370,59064,53662,PRETRIAL,Perdomo,Johnny,NULL,Male,African-American,09/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +52370,59064,53662,PRETRIAL,Perdomo,Johnny,NULL,Male,African-American,09/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52352,59036,53640,PRETRIAL,DURIZIL,EDWARD,NULL,Male,African-American,02/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,Copy,1,0 +52352,59036,53640,PRETRIAL,DURIZIL,EDWARD,NULL,Male,African-American,02/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,Copy,1,0 +52352,59036,53640,PRETRIAL,DURIZIL,EDWARD,NULL,Male,African-American,02/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +52387,59085,53681,PRETRIAL,ODAK,DAVID,NULL,Male,Caucasian,07/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/21/13 0:00,2,Medium,7,Risk of Violence,-2.98,1,Low,New,1,0 +52387,59085,53681,PRETRIAL,ODAK,DAVID,NULL,Male,Caucasian,07/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +52387,59085,53681,PRETRIAL,ODAK,DAVID,NULL,Male,Caucasian,07/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/21/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +51677,59086,52881,PRETRIAL,SPINNEY,ALEXANDRA,NULL,Female,Caucasian,02/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/21/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,Copy,1,0 +51677,59086,52881,PRETRIAL,SPINNEY,ALEXANDRA,NULL,Female,Caucasian,02/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,Copy,1,0 +51677,59086,52881,PRETRIAL,SPINNEY,ALEXANDRA,NULL,Female,Caucasian,02/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +52408,59114,53706,Probation,Melgar,Eduardo,NULL,Male,Hispanic,09/27/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/21/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +52408,59114,53706,Probation,Melgar,Eduardo,NULL,Male,Hispanic,09/27/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/21/13 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +52408,59114,53706,Probation,Melgar,Eduardo,NULL,Male,Hispanic,09/27/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52382,59078,53674,PRETRIAL,Green,Arrantes,NULL,Male,Other,05/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +52382,59078,53674,PRETRIAL,Green,Arrantes,NULL,Male,Other,05/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +52382,59078,53674,PRETRIAL,Green,Arrantes,NULL,Male,Other,05/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52392,59093,53687,Probation,NEAL,BRIAN,A,Male,African-American,09/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +52392,59093,53687,Probation,NEAL,BRIAN,A,Male,African-American,09/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +52392,59093,53687,Probation,NEAL,BRIAN,A,Male,African-American,09/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52372,59065,53663,PRETRIAL,Hall,Shakeem,NULL,Male,African-American,05/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +52372,59065,53663,PRETRIAL,Hall,Shakeem,NULL,Male,African-American,05/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +52372,59065,53663,PRETRIAL,Hall,Shakeem,NULL,Male,African-American,05/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52378,59072,53670,PRETRIAL,LESNIEWSKI,ADRIAN,NULL,Male,Caucasian,12/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +52378,59072,53670,PRETRIAL,LESNIEWSKI,ADRIAN,NULL,Male,Caucasian,12/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +52378,59072,53670,PRETRIAL,LESNIEWSKI,ADRIAN,NULL,Male,Caucasian,12/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +37878,59099,53692,PRETRIAL,GROSSMAN,MARK,NULL,Male,Caucasian,11/14/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +37878,59099,53692,PRETRIAL,GROSSMAN,MARK,NULL,Male,Caucasian,11/14/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +37878,59099,53692,PRETRIAL,GROSSMAN,MARK,NULL,Male,Caucasian,11/14/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52401,59106,53699,Probation,eckhardt,richard,NULL,Male,Caucasian,04/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +52401,59106,53699,Probation,eckhardt,richard,NULL,Male,Caucasian,04/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +52401,59106,53699,Probation,eckhardt,richard,NULL,Male,Caucasian,04/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +6890,59070,53668,PRETRIAL,Cooper,Tyrone,Ronnie,Female,African-American,12/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,4,High,7,Risk of Violence,-0.43,10,High,New,1,0 +6890,59070,53668,PRETRIAL,Cooper,Tyrone,Ronnie,Female,African-American,12/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,4,High,8,Risk of Recidivism,0.61,10,High,New,1,0 +6890,59070,53668,PRETRIAL,Cooper,Tyrone,Ronnie,Female,African-American,12/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +52384,59080,53676,PRETRIAL,Bryan,Wilfred,NULL,Male,Other,08/19/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +52384,59080,53676,PRETRIAL,Bryan,Wilfred,NULL,Male,Other,08/19/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +52384,59080,53676,PRETRIAL,Bryan,Wilfred,NULL,Male,Other,08/19/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +23071,59088,53682,Probation,Cutler,Jake,NULL,Male,Caucasian,08/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +23071,59088,53682,Probation,Cutler,Jake,NULL,Male,Caucasian,08/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +23071,59088,53682,Probation,Cutler,Jake,NULL,Male,Caucasian,08/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52415,59122,53714,PRETRIAL,Hammonds,Michael,NULL,Male,African-American,06/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +52415,59122,53714,PRETRIAL,Hammonds,Michael,NULL,Male,African-American,06/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +52415,59122,53714,PRETRIAL,Hammonds,Michael,NULL,Male,African-American,06/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52381,59075,53673,PRETRIAL,Petit-Frere,Brunel,NULL,Male,Other,02/09/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/21/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +52381,59075,53673,PRETRIAL,Petit-Frere,Brunel,NULL,Male,Other,02/09/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/21/13 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +52381,59075,53673,PRETRIAL,Petit-Frere,Brunel,NULL,Male,Other,02/09/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52404,59109,53702,Probation,Malpiedi,Paulo,Joseph,Male,Caucasian,09/18/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +52404,59109,53702,Probation,Malpiedi,Paulo,Joseph,Male,Caucasian,09/18/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +52404,59109,53702,Probation,Malpiedi,Paulo,Joseph,Male,Caucasian,09/18/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +46076,59110,53703,PRETRIAL,Munoz,Thania,NULL,Female,Caucasian,09/05/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +46076,59110,53703,PRETRIAL,Munoz,Thania,NULL,Female,Caucasian,09/05/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +46076,59110,53703,PRETRIAL,Munoz,Thania,NULL,Female,Caucasian,09/05/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52375,59068,53666,PRETRIAL,Thomas,Murvin,J,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +52375,59068,53666,PRETRIAL,Thomas,Murvin,J,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +52375,59068,53666,PRETRIAL,Thomas,Murvin,J,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52398,59103,53696,PRETRIAL,Dean,Laura,NULL,Female,African-American,02/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,7,Risk of Violence,-2.47,3,Low,New,1,0 +52398,59103,53696,PRETRIAL,Dean,Laura,NULL,Female,African-American,02/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +52398,59103,53696,PRETRIAL,Dean,Laura,NULL,Female,African-American,02/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52411,59117,53709,Probation,Roundtree,Nina,NULL,Female,African-American,06/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/21/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +52411,59117,53709,Probation,Roundtree,Nina,NULL,Female,African-American,06/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +52411,59117,53709,Probation,Roundtree,Nina,NULL,Female,African-American,06/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51761,59082,53678,PRETRIAL,knight,Maurice,NULL,Male,African-American,05/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,New,1,0 +51761,59082,53678,PRETRIAL,knight,Maurice,NULL,Male,African-American,05/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +51761,59082,53678,PRETRIAL,knight,Maurice,NULL,Male,African-American,05/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +52388,59089,53683,Probation,spain,lashondra,NULL,Female,African-American,09/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.33,3,Low,New,1,0 +52388,59089,53683,Probation,spain,lashondra,NULL,Female,African-American,09/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,8,High,New,1,0 +52388,59089,53683,Probation,spain,lashondra,NULL,Female,African-American,09/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +6981,59096,53689,PRETRIAL,Antonio,Christopher,Shawn,Male,African-American,09/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +6981,59096,53689,PRETRIAL,Antonio,Christopher,Shawn,Male,African-American,09/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +6981,59096,53689,PRETRIAL,Antonio,Christopher,Shawn,Male,African-American,09/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +44182,59077,48670,PRETRIAL,Hughes,Jamel,Devon,Male,African-American,05/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,Copy,1,0 +44182,59077,48670,PRETRIAL,Hughes,Jamel,Devon,Male,African-American,05/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,Copy,1,0 +44182,59077,48670,PRETRIAL,Hughes,Jamel,Devon,Male,African-American,05/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +51365,59094,52547,PRETRIAL,Dowling,Terrashika,NULL,Female,African-American,03/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,Copy,1,0 +51365,59094,52547,PRETRIAL,Dowling,Terrashika,NULL,Female,African-American,03/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,10,High,Copy,1,0 +51365,59094,52547,PRETRIAL,Dowling,Terrashika,NULL,Female,African-American,03/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +52409,59115,53707,Probation,Archambault,Matthew,NULL,Male,Caucasian,09/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +52409,59115,53707,Probation,Archambault,Matthew,NULL,Male,Caucasian,09/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.76,10,High,New,1,0 +52409,59115,53707,Probation,Archambault,Matthew,NULL,Male,Caucasian,09/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52413,59119,53711,Probation,BOCKER,MARK,NULL,Male,Caucasian,11/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +52413,59119,53711,Probation,BOCKER,MARK,NULL,Male,Caucasian,11/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +52413,59119,53711,Probation,BOCKER,MARK,NULL,Male,Caucasian,11/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52379,59073,53671,PRETRIAL,HABERSHAM,MICHAEL,NULL,Male,African-American,06/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +52379,59073,53671,PRETRIAL,HABERSHAM,MICHAEL,NULL,Male,African-American,06/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.64,10,High,New,1,0 +52379,59073,53671,PRETRIAL,HABERSHAM,MICHAEL,NULL,Male,African-American,06/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +43978,59098,53691,PRETRIAL,Allette,John,Shelford,Male,Other,07/27/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/21/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +43978,59098,53691,PRETRIAL,Allette,John,Shelford,Male,Other,07/27/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/21/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +43978,59098,53691,PRETRIAL,Allette,John,Shelford,Male,Other,07/27/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52407,59112,53705,PRETRIAL,Wagner,Kayli,NULL,Female,Caucasian,10/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +52407,59112,53705,PRETRIAL,Wagner,Kayli,NULL,Female,Caucasian,10/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +52407,59112,53705,PRETRIAL,Wagner,Kayli,NULL,Female,Caucasian,10/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52373,59066,53664,PRETRIAL,Sabogal,Jeffrey,M,Male,Hispanic,03/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +52373,59066,53664,PRETRIAL,Sabogal,Jeffrey,M,Male,Hispanic,03/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +52373,59066,53664,PRETRIAL,Sabogal,Jeffrey,M,Male,Hispanic,03/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52391,59092,53686,Probation,Pauciullo,Mark,NULL,Male,Hispanic,06/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +52391,59092,53686,Probation,Pauciullo,Mark,NULL,Male,Hispanic,06/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +52391,59092,53686,Probation,Pauciullo,Mark,NULL,Male,Hispanic,06/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52383,59079,53675,PRETRIAL,Thompson,Brad,NULL,Male,Caucasian,09/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +52383,59079,53675,PRETRIAL,Thompson,Brad,NULL,Male,Caucasian,09/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +52383,59079,53675,PRETRIAL,Thompson,Brad,NULL,Male,Caucasian,09/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52389,59113,53684,PRETRIAL,Quinones,Lee,NULL,Male,Hispanic,02/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,Copy,1,0 +52389,59113,53684,PRETRIAL,Quinones,Lee,NULL,Male,Hispanic,02/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,Copy,1,0 +52389,59113,53684,PRETRIAL,Quinones,Lee,NULL,Male,Hispanic,02/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +52403,59108,53701,Probation,blue,james,NULL,Male,African-American,10/12/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +52403,59108,53701,Probation,blue,james,NULL,Male,African-American,10/12/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +52403,59108,53701,Probation,blue,james,NULL,Male,African-American,10/12/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52395,59100,53693,Probation,Cadet,Jean,NULL,Male,African-American,02/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +52395,59100,53693,Probation,Cadet,Jean,NULL,Male,African-American,02/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +52395,59100,53693,Probation,Cadet,Jean,NULL,Male,African-American,02/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52377,59071,53669,PRETRIAL,Moralessantos,Juan,NULL,Male,Hispanic,11/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/21/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +52377,59071,53669,PRETRIAL,Moralessantos,Juan,NULL,Male,Hispanic,11/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +52377,59071,53669,PRETRIAL,Moralessantos,Juan,NULL,Male,Hispanic,11/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +12071,59121,53713,PRETRIAL,Taylor,Shasha,Marlianne,Female,African-American,07/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +12071,59121,53713,PRETRIAL,Taylor,Shasha,Marlianne,Female,African-American,07/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +12071,59121,53713,PRETRIAL,Taylor,Shasha,Marlianne,Female,African-American,07/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52405,59111,53704,PRETRIAL,riverakim,rosa,NULL,Female,Hispanic,09/21/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/21/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +52405,59111,53704,PRETRIAL,riverakim,rosa,NULL,Female,Hispanic,09/21/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +52405,59111,53704,PRETRIAL,riverakim,rosa,NULL,Female,Hispanic,09/21/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52385,59081,53677,PRETRIAL,KIRKELEIT,INGER,NULL,Female,Caucasian,01/21/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +52385,59081,53677,PRETRIAL,KIRKELEIT,INGER,NULL,Female,Caucasian,01/21/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +52385,59081,53677,PRETRIAL,KIRKELEIT,INGER,NULL,Female,Caucasian,01/21/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52376,59069,53667,PRETRIAL,Williams,John,Morgan,Male,African-American,10/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +52376,59069,53667,PRETRIAL,Williams,John,Morgan,Male,African-American,10/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +52376,59069,53667,PRETRIAL,Williams,John,Morgan,Male,African-American,10/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +52397,59102,53695,PRETRIAL,Deravine,Gueslly,NULL,Male,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +52397,59102,53695,PRETRIAL,Deravine,Gueslly,NULL,Male,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +52397,59102,53695,PRETRIAL,Deravine,Gueslly,NULL,Male,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52414,59120,53712,Probation,Destine,Rasheda,NULL,Female,African-American,10/31/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/21/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +52414,59120,53712,Probation,Destine,Rasheda,NULL,Female,African-American,10/31/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +52414,59120,53712,Probation,Destine,Rasheda,NULL,Female,African-American,10/31/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/21/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52410,59116,53708,Probation,Bernier,Erik,NULL,Male,Caucasian,06/26/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +52410,59116,53708,Probation,Bernier,Erik,NULL,Male,Caucasian,06/26/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +52410,59116,53708,Probation,Bernier,Erik,NULL,Male,Caucasian,06/26/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +11934,12311,11448,PRETRIAL,JEAN,MAOUSHKA,NULL,Female,African-American,10/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +11934,12311,11448,PRETRIAL,JEAN,MAOUSHKA,NULL,Female,African-American,10/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +11934,12311,11448,PRETRIAL,JEAN,MAOUSHKA,NULL,Female,African-American,10/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52374,59067,53665,PRETRIAL,Mitchell,Anthony,NULL,Male,African-American,03/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +52374,59067,53665,PRETRIAL,Mitchell,Anthony,NULL,Male,African-American,03/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +52374,59067,53665,PRETRIAL,Mitchell,Anthony,NULL,Male,African-American,03/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52412,59118,53710,Probation,KUNNEL,PRASAD,T,Male,Asian,05/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +52412,59118,53710,Probation,KUNNEL,PRASAD,T,Male,Asian,05/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +52412,59118,53710,Probation,KUNNEL,PRASAD,T,Male,Asian,05/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52380,59074,53672,PRETRIAL,Moore,Marissa,NULL,Female,African-American,06/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +52380,59074,53672,PRETRIAL,Moore,Marissa,NULL,Female,African-American,06/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +52380,59074,53672,PRETRIAL,Moore,Marissa,NULL,Female,African-American,06/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52394,59097,53690,Probation,slack,daniel,NULL,Male,Caucasian,08/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +52394,59097,53690,Probation,slack,daniel,NULL,Male,Caucasian,08/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +52394,59097,53690,Probation,slack,daniel,NULL,Male,Caucasian,08/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52399,59104,53697,Probation,GAETEROLDAN,MARIO,NULL,Male,Hispanic,02/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +52399,59104,53697,Probation,GAETEROLDAN,MARIO,NULL,Male,Hispanic,02/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +52399,59104,53697,Probation,GAETEROLDAN,MARIO,NULL,Male,Hispanic,02/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50338,59076,51343,PRETRIAL,berry,cameron,NULL,Male,Caucasian,07/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,Copy,1,0 +50338,59076,51343,PRETRIAL,berry,cameron,NULL,Male,Caucasian,07/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,Copy,1,0 +50338,59076,51343,PRETRIAL,berry,cameron,NULL,Male,Caucasian,07/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +52393,59095,53688,Probation,SANGSTER,TORIAN,NULL,Male,African-American,04/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +52393,59095,53688,Probation,SANGSTER,TORIAN,NULL,Male,African-American,04/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +52393,59095,53688,Probation,SANGSTER,TORIAN,NULL,Male,African-American,04/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52220,59125,53488,PRETRIAL,Henry,Richard,NULL,Male,African-American,02/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,Copy,1,0 +52220,59125,53488,PRETRIAL,Henry,Richard,NULL,Male,African-American,02/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,Copy,1,0 +52220,59125,53488,PRETRIAL,Henry,Richard,NULL,Male,African-American,02/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +52458,59176,53763,Probation,Zalaya,David,NULL,Male,Caucasian,07/17/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,New,1,0 +52458,59176,53763,Probation,Zalaya,David,NULL,Male,Caucasian,07/17/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +52458,59176,53763,Probation,Zalaya,David,NULL,Male,Caucasian,07/17/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51701,59153,53637,PRETRIAL,KATHARY,ROBERT,NULL,Male,African-American,01/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/22/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,Copy,1,0 +51701,59153,53637,PRETRIAL,KATHARY,ROBERT,NULL,Male,African-American,01/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/22/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,Copy,1,0 +51701,59153,53637,PRETRIAL,KATHARY,ROBERT,NULL,Male,African-American,01/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +52449,59167,53754,Probation,Germain,Mina,NULL,Female,African-American,06/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +52449,59167,53754,Probation,Germain,Mina,NULL,Female,African-American,06/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,7,Medium,New,1,0 +52449,59167,53754,Probation,Germain,Mina,NULL,Female,African-American,06/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52426,59139,53729,PRETRIAL,Parker,Earl,NULL,Male,African-American,11/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +52426,59139,53729,PRETRIAL,Parker,Earl,NULL,Male,African-American,11/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +52426,59139,53729,PRETRIAL,Parker,Earl,NULL,Male,African-American,11/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +7683,59146,53736,PRETRIAL,DAVIS,JEREMY,ROBERT,Male,Caucasian,08/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +7683,59146,53736,PRETRIAL,DAVIS,JEREMY,ROBERT,Male,Caucasian,08/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +7683,59146,53736,PRETRIAL,DAVIS,JEREMY,ROBERT,Male,Caucasian,08/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51028,59123,53715,PRETRIAL,Simonds,Louis,NULL,Male,Other,09/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +51028,59123,53715,PRETRIAL,Simonds,Louis,NULL,Male,Other,09/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +51028,59123,53715,PRETRIAL,Simonds,Louis,NULL,Male,Other,09/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52427,59141,53731,PRETRIAL,Fugett,Dylan,NULL,Male,Caucasian,08/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +52427,59141,53731,PRETRIAL,Fugett,Dylan,NULL,Male,Caucasian,08/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +52427,59141,53731,PRETRIAL,Fugett,Dylan,NULL,Male,Caucasian,08/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +36505,59137,35784,PRETRIAL,YOUNG,URIEL,T,Male,African-American,04/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,Copy,1,0 +36505,59137,35784,PRETRIAL,YOUNG,URIEL,T,Male,African-American,04/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.68,10,High,Copy,1,0 +36505,59137,35784,PRETRIAL,YOUNG,URIEL,T,Male,African-American,04/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +52443,59158,53746,PRETRIAL,Soto,Katherine,NULL,Female,Caucasian,07/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/22/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +52443,59158,53746,PRETRIAL,Soto,Katherine,NULL,Female,Caucasian,07/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/22/13 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +52443,59158,53746,PRETRIAL,Soto,Katherine,NULL,Female,Caucasian,07/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52445,59162,53749,PRETRIAL,Mansourie,Reza,NULL,Male,Other,12/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +52445,59162,53749,PRETRIAL,Mansourie,Reza,NULL,Male,Other,12/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +52445,59162,53749,PRETRIAL,Mansourie,Reza,NULL,Male,Other,12/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52441,59157,53745,PRETRIAL,gabrie,ramses,NULL,Male,Hispanic,08/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +52441,59157,53745,PRETRIAL,gabrie,ramses,NULL,Male,Hispanic,08/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,4,High,8,Risk of Recidivism,0.66,10,High,New,1,0 +52441,59157,53745,PRETRIAL,gabrie,ramses,NULL,Male,Hispanic,08/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +52453,59171,53758,Probation,GALLO,JUAN,P,Male,Hispanic,05/03/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +52453,59171,53758,Probation,GALLO,JUAN,P,Male,Hispanic,05/03/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +52453,59171,53758,Probation,GALLO,JUAN,P,Male,Hispanic,05/03/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50411,59136,53727,PRETRIAL,GUSTAVE,EVENS,NULL,Male,African-American,08/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/22/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +50411,59136,53727,PRETRIAL,GUSTAVE,EVENS,NULL,Male,African-American,08/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/22/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +50411,59136,53727,PRETRIAL,GUSTAVE,EVENS,NULL,Male,African-American,08/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52434,59150,53739,PRETRIAL,Cordero,Martin,NULL,Male,Hispanic,07/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +52434,59150,53739,PRETRIAL,Cordero,Martin,NULL,Male,Hispanic,07/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +52434,59150,53739,PRETRIAL,Cordero,Martin,NULL,Male,Hispanic,07/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52428,59142,53732,PRETRIAL,Luff,Gregory,NULL,Male,Caucasian,11/07/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +52428,59142,53732,PRETRIAL,Luff,Gregory,NULL,Male,Caucasian,11/07/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +52428,59142,53732,PRETRIAL,Luff,Gregory,NULL,Male,Caucasian,11/07/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52430,59144,53734,PRETRIAL,Dees,Anthony,NULL,Male,African-American,02/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +52430,59144,53734,PRETRIAL,Dees,Anthony,NULL,Male,African-American,02/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +52430,59144,53734,PRETRIAL,Dees,Anthony,NULL,Male,African-American,02/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52418,59129,53720,PRETRIAL,Dent,Tammy,NULL,Female,African-American,01/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,4,High,7,Risk of Violence,-1.07,8,High,New,1,0 +52418,59129,53720,PRETRIAL,Dent,Tammy,NULL,Female,African-American,01/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,4,High,8,Risk of Recidivism,0.16,9,High,New,1,0 +52418,59129,53720,PRETRIAL,Dent,Tammy,NULL,Female,African-American,01/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52446,59163,53750,PRETRIAL,MANARITE,CATHERINE,NULL,Female,Caucasian,01/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +52446,59163,53750,PRETRIAL,MANARITE,CATHERINE,NULL,Female,Caucasian,01/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +52446,59163,53750,PRETRIAL,MANARITE,CATHERINE,NULL,Female,Caucasian,01/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +4476,59165,53752,PRETRIAL,Fortune,Jamal,R,Male,African-American,04/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.14,4,Low,New,1,0 +4476,59165,53752,PRETRIAL,Fortune,Jamal,R,Male,African-American,04/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +4476,59165,53752,PRETRIAL,Fortune,Jamal,R,Male,African-American,04/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52432,59147,53737,PRETRIAL,Colon,Joshua,NULL,Male,Caucasian,07/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +52432,59147,53737,PRETRIAL,Colon,Joshua,NULL,Male,Caucasian,07/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +52432,59147,53737,PRETRIAL,Colon,Joshua,NULL,Male,Caucasian,07/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52416,59126,53717,PRETRIAL,Kearney,Kevin,NULL,Male,Caucasian,04/11/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +52416,59126,53717,PRETRIAL,Kearney,Kevin,NULL,Male,Caucasian,04/11/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +52416,59126,53717,PRETRIAL,Kearney,Kevin,NULL,Male,Caucasian,04/11/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52439,59155,53743,PRETRIAL,Diers,Robert,NULL,Male,Caucasian,03/30/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +52439,59155,53743,PRETRIAL,Diers,Robert,NULL,Male,Caucasian,03/30/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +52439,59155,53743,PRETRIAL,Diers,Robert,NULL,Male,Caucasian,03/30/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52422,59134,53725,PRETRIAL,Gorman,Derrick,NULL,Male,Caucasian,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +52422,59134,53725,PRETRIAL,Gorman,Derrick,NULL,Male,Caucasian,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +52422,59134,53725,PRETRIAL,Gorman,Derrick,NULL,Male,Caucasian,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52448,59166,53753,Probation,martinez,zachary,NULL,Male,Caucasian,04/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-2.72,2,Low,New,1,0 +52448,59166,53753,Probation,martinez,zachary,NULL,Male,Caucasian,04/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +52448,59166,53753,Probation,martinez,zachary,NULL,Male,Caucasian,04/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52459,59180,53765,Probation,Lopez,Edilberto,NULL,Male,Hispanic,04/23/87,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +52459,59180,53765,Probation,Lopez,Edilberto,NULL,Male,Hispanic,04/23/87,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +52459,59180,53765,Probation,Lopez,Edilberto,NULL,Male,Hispanic,04/23/87,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52421,59133,53724,PRETRIAL,St Fleur,William,NULL,Male,African-American,09/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +52421,59133,53724,PRETRIAL,St Fleur,William,NULL,Male,African-American,09/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +52421,59133,53724,PRETRIAL,St Fleur,William,NULL,Male,African-American,09/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52452,59170,53757,Probation,marcelino,keli,NULL,Female,Caucasian,12/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +52452,59170,53757,Probation,marcelino,keli,NULL,Female,Caucasian,12/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +52452,59170,53757,Probation,marcelino,keli,NULL,Female,Caucasian,12/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50295,59149,51292,PRETRIAL,Espino,Alberto,NULL,Male,Hispanic,05/11/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/22/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,Copy,1,0 +50295,59149,51292,PRETRIAL,Espino,Alberto,NULL,Male,Hispanic,05/11/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/22/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,Copy,1,0 +50295,59149,51292,PRETRIAL,Espino,Alberto,NULL,Male,Hispanic,05/11/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +52438,59154,53742,PRETRIAL,Dunn,Michael,NULL,Male,Caucasian,06/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/22/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +52438,59154,53742,PRETRIAL,Dunn,Michael,NULL,Male,Caucasian,06/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/22/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +52438,59154,53742,PRETRIAL,Dunn,Michael,NULL,Male,Caucasian,06/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52417,59128,53719,PRETRIAL,Perez,Maria,NULL,Female,Hispanic,09/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/22/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +52417,59128,53719,PRETRIAL,Perez,Maria,NULL,Female,Hispanic,09/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/22/13 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +52417,59128,53719,PRETRIAL,Perez,Maria,NULL,Female,Hispanic,09/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52431,59145,53735,PRETRIAL,Sylvain,Scott,NULL,Male,African-American,03/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +52431,59145,53735,PRETRIAL,Sylvain,Scott,NULL,Male,African-American,03/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +52431,59145,53735,PRETRIAL,Sylvain,Scott,NULL,Male,African-American,03/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52457,59175,53762,Probation,Cadoso,caue,NULL,Male,Hispanic,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +52457,59175,53762,Probation,Cadoso,caue,NULL,Male,Hispanic,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +52457,59175,53762,Probation,Cadoso,caue,NULL,Male,Hispanic,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52450,59168,53755,Probation,scott,shalika,NULL,Female,African-American,06/19/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +52450,59168,53755,Probation,scott,shalika,NULL,Female,African-American,06/19/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,4,High,8,Risk of Recidivism,1.06,10,High,New,1,0 +52450,59168,53755,Probation,scott,shalika,NULL,Female,African-American,06/19/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +44688,59159,44824,PRETRIAL,Jimenez,michael,NULL,Male,Hispanic,03/06/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +44688,59159,44824,PRETRIAL,Jimenez,michael,NULL,Male,Hispanic,03/06/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,6,Medium,New,1,0 +44688,59159,44824,PRETRIAL,Jimenez,michael,NULL,Male,Hispanic,03/06/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +34380,59161,53748,PRETRIAL,Leandre,Clyde,NULL,Male,African-American,08/20/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +34380,59161,53748,PRETRIAL,Leandre,Clyde,NULL,Male,African-American,08/20/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,5,Medium,New,1,0 +34380,59161,53748,PRETRIAL,Leandre,Clyde,NULL,Male,African-American,08/20/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52420,59131,53722,PRETRIAL,Fritzmaurice,John,NULL,Male,Caucasian,05/11/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +52420,59131,53722,PRETRIAL,Fritzmaurice,John,NULL,Male,Caucasian,05/11/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +52420,59131,53722,PRETRIAL,Fritzmaurice,John,NULL,Male,Caucasian,05/11/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52425,59138,53728,PRETRIAL,Edwards,Linda,NULL,Male,African-American,07/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/22/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +52425,59138,53728,PRETRIAL,Edwards,Linda,NULL,Male,African-American,07/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/22/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +52425,59138,53728,PRETRIAL,Edwards,Linda,NULL,Male,African-American,07/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +44921,59140,53730,Probation,whitehead,travis,NULL,Male,African-American,05/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +44921,59140,53730,Probation,whitehead,travis,NULL,Male,African-American,05/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +44921,59140,53730,Probation,whitehead,travis,NULL,Male,African-American,05/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52429,59143,53733,PRETRIAL,Walker,Jason,NULL,Male,African-American,11/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +52429,59143,53733,PRETRIAL,Walker,Jason,NULL,Male,African-American,11/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +52429,59143,53733,PRETRIAL,Walker,Jason,NULL,Male,African-American,11/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +46426,59177,53764,PRETRIAL,Obin,Gene,NULL,Male,African-American,12/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-2.45,3,Low,New,1,0 +46426,59177,53764,PRETRIAL,Obin,Gene,NULL,Male,African-American,12/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +46426,59177,53764,PRETRIAL,Obin,Gene,NULL,Male,African-American,12/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +52419,59130,53721,PRETRIAL,Hunter,Tiwan,NULL,Male,African-American,09/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.92,2,Low,New,1,0 +52419,59130,53721,PRETRIAL,Hunter,Tiwan,NULL,Male,African-American,09/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +52419,59130,53721,PRETRIAL,Hunter,Tiwan,NULL,Male,African-American,09/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52433,59148,53738,PRETRIAL,Tharpe,Secunda,NULL,Female,African-American,06/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +52433,59148,53738,PRETRIAL,Tharpe,Secunda,NULL,Female,African-American,06/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +52433,59148,53738,PRETRIAL,Tharpe,Secunda,NULL,Female,African-American,06/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52435,59151,53740,Probation,HAYS,CORTNEY,T,Female,Caucasian,07/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +52435,59151,53740,Probation,HAYS,CORTNEY,T,Female,Caucasian,07/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +52435,59151,53740,Probation,HAYS,CORTNEY,T,Female,Caucasian,07/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52454,59172,53759,Probation,CONTSTANT,ANSSE,NULL,Male,African-American,01/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +52454,59172,53759,Probation,CONTSTANT,ANSSE,NULL,Male,African-American,01/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +52454,59172,53759,Probation,CONTSTANT,ANSSE,NULL,Male,African-American,01/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/22/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +37797,59127,53718,PRETRIAL,Cooper,Linton,NULL,Male,African-American,01/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/22/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +37797,59127,53718,PRETRIAL,Cooper,Linton,NULL,Male,African-American,01/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/22/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +37797,59127,53718,PRETRIAL,Cooper,Linton,NULL,Male,African-American,01/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52447,59164,53751,PRETRIAL,Ramirez,Isaac,NULL,Male,Hispanic,01/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +52447,59164,53751,PRETRIAL,Ramirez,Isaac,NULL,Male,Hispanic,01/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +52447,59164,53751,PRETRIAL,Ramirez,Isaac,NULL,Male,Hispanic,01/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52423,59135,53726,PRETRIAL,Thibault,Kristopher,NULL,Male,Caucasian,06/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +52423,59135,53726,PRETRIAL,Thibault,Kristopher,NULL,Male,Caucasian,06/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +52423,59135,53726,PRETRIAL,Thibault,Kristopher,NULL,Male,Caucasian,06/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +43864,59185,53770,PRETRIAL,Johnson,Jazzy,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,7,Risk of Violence,-0.67,9,High,New,1,0 +43864,59185,53770,PRETRIAL,Johnson,Jazzy,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,8,Risk of Recidivism,0.86,10,High,New,1,0 +43864,59185,53770,PRETRIAL,Johnson,Jazzy,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +34493,59200,53785,PRETRIAL,MERELLO,YOSHIHIRO,NULL,Male,Hispanic,07/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +34493,59200,53785,PRETRIAL,MERELLO,YOSHIHIRO,NULL,Male,Hispanic,07/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +34493,59200,53785,PRETRIAL,MERELLO,YOSHIHIRO,NULL,Male,Hispanic,07/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52468,59193,53778,PRETRIAL,Stinson,Niki,NULL,Female,Caucasian,08/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/23/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +52468,59193,53778,PRETRIAL,Stinson,Niki,NULL,Female,Caucasian,08/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/23/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +52468,59193,53778,PRETRIAL,Stinson,Niki,NULL,Female,Caucasian,08/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52475,59206,53790,PRETRIAL,Gornall,Stephen,NULL,Male,African-American,10/08/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/23/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +52475,59206,53790,PRETRIAL,Gornall,Stephen,NULL,Male,African-American,10/08/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/23/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +52475,59206,53790,PRETRIAL,Gornall,Stephen,NULL,Male,African-American,10/08/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +43195,59208,43105,PRETRIAL,FLORES,MICHAEL,NULL,Male,Caucasian,11/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,Copy,1,0 +43195,59208,43105,PRETRIAL,FLORES,MICHAEL,NULL,Male,Caucasian,11/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.73,10,High,Copy,1,0 +43195,59208,43105,PRETRIAL,FLORES,MICHAEL,NULL,Male,Caucasian,11/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +33139,59211,32217,PRETRIAL,Jones,Cornelius,NULL,Male,African-American,04/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,Copy,1,0 +33139,59211,32217,PRETRIAL,Jones,Cornelius,NULL,Male,African-American,04/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,Copy,1,0 +33139,59211,32217,PRETRIAL,Jones,Cornelius,NULL,Male,African-American,04/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +52465,59190,53775,PRETRIAL,vermilus,macayose,NULL,Male,African-American,03/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +52465,59190,53775,PRETRIAL,vermilus,macayose,NULL,Male,African-American,03/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.87,10,High,New,1,0 +52465,59190,53775,PRETRIAL,vermilus,macayose,NULL,Male,African-American,03/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52478,59210,53793,PRETRIAL,TAYLOR,DANIEL,NULL,Male,African-American,11/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,7,Risk of Violence,-0.58,10,High,New,1,0 +52478,59210,53793,PRETRIAL,TAYLOR,DANIEL,NULL,Male,African-American,11/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,8,Risk of Recidivism,0.35,9,High,New,1,0 +52478,59210,53793,PRETRIAL,TAYLOR,DANIEL,NULL,Male,African-American,11/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +33391,59203,32495,PRETRIAL,HOLDEN,KEENAN,VENDRYES,Male,African-American,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,Copy,1,0 +33391,59203,32495,PRETRIAL,HOLDEN,KEENAN,VENDRYES,Male,African-American,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +33391,59203,32495,PRETRIAL,HOLDEN,KEENAN,VENDRYES,Male,African-American,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +7805,59182,53767,PRETRIAL,Roberts,Samuel,NULL,Male,African-American,01/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +7805,59182,53767,PRETRIAL,Roberts,Samuel,NULL,Male,African-American,01/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,8,Risk of Recidivism,0.96,10,High,New,1,0 +7805,59182,53767,PRETRIAL,Roberts,Samuel,NULL,Male,African-American,01/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52464,59189,53774,PRETRIAL,Gomez,Orlando,NULL,Male,Caucasian,11/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/23/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +52464,59189,53774,PRETRIAL,Gomez,Orlando,NULL,Male,Caucasian,11/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/23/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +52464,59189,53774,PRETRIAL,Gomez,Orlando,NULL,Male,Caucasian,11/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52470,59196,53781,PRETRIAL,Serrano,Roberto,NULL,Male,Caucasian,06/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +52470,59196,53781,PRETRIAL,Serrano,Roberto,NULL,Male,Caucasian,06/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +52470,59196,53781,PRETRIAL,Serrano,Roberto,NULL,Male,Caucasian,06/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +21513,59184,53769,PRETRIAL,Reyes,Eliasin,NULL,Male,African-American,02/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.34,3,Low,New,1,0 +21513,59184,53769,PRETRIAL,Reyes,Eliasin,NULL,Male,African-American,02/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +21513,59184,53769,PRETRIAL,Reyes,Eliasin,NULL,Male,African-American,02/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52462,59187,53772,PRETRIAL,Comete,Yolette,NULL,Female,African-American,04/26/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +52462,59187,53772,PRETRIAL,Comete,Yolette,NULL,Female,African-American,04/26/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +52462,59187,53772,PRETRIAL,Comete,Yolette,NULL,Female,African-American,04/26/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52472,59201,53786,PRETRIAL,Sterlin,Roseson,NULL,Male,African-American,06/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +52472,59201,53786,PRETRIAL,Sterlin,Roseson,NULL,Male,African-American,06/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +52472,59201,53786,PRETRIAL,Sterlin,Roseson,NULL,Male,African-American,06/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52466,59191,53776,PRETRIAL,Collins,Charles,Dontaie,Male,African-American,10/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,7,Risk of Violence,-1.03,8,High,New,1,0 +52466,59191,53776,PRETRIAL,Collins,Charles,Dontaie,Male,African-American,10/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,8,Risk of Recidivism,0.15,8,High,New,1,0 +52466,59191,53776,PRETRIAL,Collins,Charles,Dontaie,Male,African-American,10/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49457,59205,53789,PRETRIAL,Fleming,Carl,NULL,Male,African-American,11/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +49457,59205,53789,PRETRIAL,Fleming,Carl,NULL,Male,African-American,11/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +49457,59205,53789,PRETRIAL,Fleming,Carl,NULL,Male,African-American,11/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52473,59202,53787,PRETRIAL,Chattman,Ally,NULL,Male,African-American,09/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/23/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +52473,59202,53787,PRETRIAL,Chattman,Ally,NULL,Male,African-American,09/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/23/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +52473,59202,53787,PRETRIAL,Chattman,Ally,NULL,Male,African-American,09/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +40741,59186,53771,PRETRIAL,andrew,williams,NULL,Male,African-American,07/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +40741,59186,53771,PRETRIAL,andrew,williams,NULL,Male,African-American,07/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +40741,59186,53771,PRETRIAL,andrew,williams,NULL,Male,African-American,07/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52476,59207,53791,PRETRIAL,Montaque,Jaquez,NULL,Male,African-American,04/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.22,8,High,New,1,0 +52476,59207,53791,PRETRIAL,Montaque,Jaquez,NULL,Male,African-American,04/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +52476,59207,53791,PRETRIAL,Montaque,Jaquez,NULL,Male,African-American,04/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52467,59192,53777,PRETRIAL,Richardson,Mercedes,NULL,Male,African-American,03/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +52467,59192,53777,PRETRIAL,Richardson,Mercedes,NULL,Male,African-American,03/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +52467,59192,53777,PRETRIAL,Richardson,Mercedes,NULL,Male,African-American,03/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52477,59209,53792,PRETRIAL,Evans,Timothy,NULL,Male,Caucasian,06/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,7,Risk of Violence,-0.43,10,High,New,1,0 +52477,59209,53792,PRETRIAL,Evans,Timothy,NULL,Male,Caucasian,06/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,8,Risk of Recidivism,0.14,8,High,New,1,0 +52477,59209,53792,PRETRIAL,Evans,Timothy,NULL,Male,Caucasian,06/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,4,High,18,Risk of Failure to Appear,36,10,High,New,1,0 +52461,59183,53768,PRETRIAL,Mihelich,George,NULL,Male,Caucasian,07/07/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/23/13 0:00,1,Low,7,Risk of Violence,-4.49,1,Low,New,1,0 +52461,59183,53768,PRETRIAL,Mihelich,George,NULL,Male,Caucasian,07/07/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/23/13 0:00,1,Low,8,Risk of Recidivism,-2.9,1,Low,New,1,0 +52461,59183,53768,PRETRIAL,Mihelich,George,NULL,Male,Caucasian,07/07/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52463,59188,53773,PRETRIAL,Orellano-Barrios,Raisha,NULL,Female,Hispanic,02/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +52463,59188,53773,PRETRIAL,Orellano-Barrios,Raisha,NULL,Female,Hispanic,02/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +52463,59188,53773,PRETRIAL,Orellano-Barrios,Raisha,NULL,Female,Hispanic,02/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30274,59195,53780,PRETRIAL,BROWN,TERRENCE,NULL,Male,African-American,06/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +30274,59195,53780,PRETRIAL,BROWN,TERRENCE,NULL,Male,African-American,06/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +30274,59195,53780,PRETRIAL,BROWN,TERRENCE,NULL,Male,African-American,06/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52471,59197,53782,PRETRIAL,Igelesias,Clara,NULL,Female,Caucasian,08/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/23/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +52471,59197,53782,PRETRIAL,Igelesias,Clara,NULL,Female,Caucasian,08/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/23/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +52471,59197,53782,PRETRIAL,Igelesias,Clara,NULL,Female,Caucasian,08/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52474,59204,53788,PRETRIAL,Patterson,Lejuan,NULL,Male,African-American,05/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +52474,59204,53788,PRETRIAL,Patterson,Lejuan,NULL,Male,African-American,05/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.82,10,High,New,1,0 +52474,59204,53788,PRETRIAL,Patterson,Lejuan,NULL,Male,African-American,05/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52488,59225,53804,PRETRIAL,CHERISCA,DEVE,NULL,Male,African-American,10/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +52488,59225,53804,PRETRIAL,CHERISCA,DEVE,NULL,Male,African-American,10/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,4,High,8,Risk of Recidivism,0.19,8,High,New,1,0 +52488,59225,53804,PRETRIAL,CHERISCA,DEVE,NULL,Male,African-American,10/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52484,59218,53799,PRETRIAL,SANTOS,JOSE,ALFREDO,Male,Caucasian,04/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +52484,59218,53799,PRETRIAL,SANTOS,JOSE,ALFREDO,Male,Caucasian,04/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +52484,59218,53799,PRETRIAL,SANTOS,JOSE,ALFREDO,Male,Caucasian,04/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52480,59213,53795,PRETRIAL,Moncur,Nicole,NULL,Female,African-American,09/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +52480,59213,53795,PRETRIAL,Moncur,Nicole,NULL,Female,African-American,09/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +52480,59213,53795,PRETRIAL,Moncur,Nicole,NULL,Female,African-American,09/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52493,59230,53809,PRETRIAL,Williams,Troy,NULL,Male,African-American,09/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/24/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +52493,59230,53809,PRETRIAL,Williams,Troy,NULL,Male,African-American,09/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/24/13 0:00,4,High,8,Risk of Recidivism,0.92,10,High,New,1,0 +52493,59230,53809,PRETRIAL,Williams,Troy,NULL,Male,African-American,09/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/24/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +7858,59220,7442,DRRD,Mujico,Juan,NULL,Male,Caucasian,09/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,Copy,1,0 +7858,59220,7442,DRRD,Mujico,Juan,NULL,Male,Caucasian,09/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,8,Risk of Recidivism,-0.45,4,Low,Copy,1,0 +7858,59220,7442,DRRD,Mujico,Juan,NULL,Male,Caucasian,09/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +46899,59223,53803,PRETRIAL,Clarke,Mark,Goldbron,Male,African-American,08/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +46899,59223,53803,PRETRIAL,Clarke,Mark,Goldbron,Male,African-American,08/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +46899,59223,53803,PRETRIAL,Clarke,Mark,Goldbron,Male,African-American,08/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52491,59228,53807,PRETRIAL,Thomas,Wendell,L,Male,African-American,04/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/24/13 0:00,2,Medium,7,Risk of Violence,-2.71,2,Low,New,1,0 +52491,59228,53807,PRETRIAL,Thomas,Wendell,L,Male,African-American,04/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +52491,59228,53807,PRETRIAL,Thomas,Wendell,L,Male,African-American,04/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/24/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +5239,59215,4912,PRETRIAL,KEITH,HOLZ,WAYNE,Male,Caucasian,12/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,Copy,1,0 +5239,59215,4912,PRETRIAL,KEITH,HOLZ,WAYNE,Male,Caucasian,12/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,Copy,1,0 +5239,59215,4912,PRETRIAL,KEITH,HOLZ,WAYNE,Male,Caucasian,12/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +52489,59226,53805,PRETRIAL,ORTIZ,RAY,NULL,Male,Hispanic,11/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +52489,59226,53805,PRETRIAL,ORTIZ,RAY,NULL,Male,Hispanic,11/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +52489,59226,53805,PRETRIAL,ORTIZ,RAY,NULL,Male,Hispanic,11/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52487,59222,53802,PRETRIAL,HENRY,STEVEN,NULL,Male,African-American,02/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +52487,59222,53802,PRETRIAL,HENRY,STEVEN,NULL,Male,African-American,02/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +52487,59222,53802,PRETRIAL,HENRY,STEVEN,NULL,Male,African-American,02/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52483,59217,53798,PRETRIAL,DONOVAN,ALEXANDRA,C,Female,Caucasian,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +52483,59217,53798,PRETRIAL,DONOVAN,ALEXANDRA,C,Female,Caucasian,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +52483,59217,53798,PRETRIAL,DONOVAN,ALEXANDRA,C,Female,Caucasian,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52479,59212,53794,PRETRIAL,Carter,Kimberly,NULL,Female,Caucasian,08/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +52479,59212,53794,PRETRIAL,Carter,Kimberly,NULL,Female,Caucasian,08/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +52479,59212,53794,PRETRIAL,Carter,Kimberly,NULL,Female,Caucasian,08/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +32047,59224,31051,PRETRIAL,Jones,Terrance,NULL,Male,African-American,11/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,Copy,1,0 +32047,59224,31051,PRETRIAL,Jones,Terrance,NULL,Male,African-American,11/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,Copy,1,0 +32047,59224,31051,PRETRIAL,Jones,Terrance,NULL,Male,African-American,11/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +52485,59219,53800,PRETRIAL,NOAH,LEMORE,ESTHER,Female,Caucasian,11/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,4,High,7,Risk of Violence,-0.7,9,High,New,1,0 +52485,59219,53800,PRETRIAL,NOAH,LEMORE,ESTHER,Female,Caucasian,11/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,4,High,8,Risk of Recidivism,0.88,10,High,New,1,0 +52485,59219,53800,PRETRIAL,NOAH,LEMORE,ESTHER,Female,Caucasian,11/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52482,59216,53797,PRETRIAL,Reyes,Eduardo,NULL,Male,Hispanic,03/19/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/24/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +52482,59216,53797,PRETRIAL,Reyes,Eduardo,NULL,Male,Hispanic,03/19/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/24/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +52482,59216,53797,PRETRIAL,Reyes,Eduardo,NULL,Male,Hispanic,03/19/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/24/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52492,59229,53808,PRETRIAL,THOMAS,KENNETH,NULL,Male,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +52492,59229,53808,PRETRIAL,THOMAS,KENNETH,NULL,Male,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.7,10,High,New,1,0 +52492,59229,53808,PRETRIAL,THOMAS,KENNETH,NULL,Male,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52490,59227,53806,PRETRIAL,EVERETT,BYRON,NULL,Male,African-American,01/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/24/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +52490,59227,53806,PRETRIAL,EVERETT,BYRON,NULL,Male,African-American,01/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/24/13 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +52490,59227,53806,PRETRIAL,EVERETT,BYRON,NULL,Male,African-American,01/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/24/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52481,59214,53796,PRETRIAL,Wilson,Steven,NULL,Male,Caucasian,06/29/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,New,1,0 +52481,59214,53796,PRETRIAL,Wilson,Steven,NULL,Male,Caucasian,06/29/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +52481,59214,53796,PRETRIAL,Wilson,Steven,NULL,Male,Caucasian,06/29/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52486,59221,53801,PRETRIAL,HUNTER,KEITHON,CRAIG,Male,African-American,12/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +52486,59221,53801,PRETRIAL,HUNTER,KEITHON,CRAIG,Male,African-American,12/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +52486,59221,53801,PRETRIAL,HUNTER,KEITHON,CRAIG,Male,African-American,12/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52496,59235,53814,PRETRIAL,Levine,Tavarus,lamar,Male,African-American,11/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/25/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +52496,59235,53814,PRETRIAL,Levine,Tavarus,lamar,Male,African-American,11/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/25/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +52496,59235,53814,PRETRIAL,Levine,Tavarus,lamar,Male,African-American,11/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52509,59250,53829,Probation,Allen,Deborah,NULL,Female,African-American,12/01/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +52509,59250,53829,Probation,Allen,Deborah,NULL,Female,African-American,12/01/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +52509,59250,53829,Probation,Allen,Deborah,NULL,Female,African-American,12/01/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +52503,59242,53821,PRETRIAL,Severe,Mariot,NULL,Male,Other,06/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/25/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +52503,59242,53821,PRETRIAL,Severe,Mariot,NULL,Male,Other,06/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +52503,59242,53821,PRETRIAL,Severe,Mariot,NULL,Male,Other,06/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52498,59237,53816,PRETRIAL,Ip,Darren,C,Male,Asian,10/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +52498,59237,53816,PRETRIAL,Ip,Darren,C,Male,Asian,10/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +52498,59237,53816,PRETRIAL,Ip,Darren,C,Male,Asian,10/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52515,59258,53837,Probation,Hayes,Austin,NULL,Male,Caucasian,01/28/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +52515,59258,53837,Probation,Hayes,Austin,NULL,Male,Caucasian,01/28/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,4,High,8,Risk of Recidivism,0.43,9,High,New,1,0 +52515,59258,53837,Probation,Hayes,Austin,NULL,Male,Caucasian,01/28/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52505,59245,53824,PRETRIAL,WOLF,RAYMOND,NULL,Male,Caucasian,06/10/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/25/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +52505,59245,53824,PRETRIAL,WOLF,RAYMOND,NULL,Male,Caucasian,06/10/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/25/13 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +52505,59245,53824,PRETRIAL,WOLF,RAYMOND,NULL,Male,Caucasian,06/10/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50615,59259,51667,Probation,miller,cindy,NULL,Female,Caucasian,02/12/75,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +50615,59259,51667,Probation,miller,cindy,NULL,Female,Caucasian,02/12/75,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +50615,59259,51667,Probation,miller,cindy,NULL,Female,Caucasian,02/12/75,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52517,59261,53839,PRETRIAL,Lopez,Angel,NULL,Male,Hispanic,11/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/25/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +52517,59261,53839,PRETRIAL,Lopez,Angel,NULL,Male,Hispanic,11/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/25/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +52517,59261,53839,PRETRIAL,Lopez,Angel,NULL,Male,Hispanic,11/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52495,59233,53812,PRETRIAL,Romero,Manuel,NULL,Male,Hispanic,01/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +52495,59233,53812,PRETRIAL,Romero,Manuel,NULL,Male,Hispanic,01/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +52495,59233,53812,PRETRIAL,Romero,Manuel,NULL,Male,Hispanic,01/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52499,59238,53817,PRETRIAL,DAVIS,PASSHA,BIANCA,Female,African-American,02/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +52499,59238,53817,PRETRIAL,DAVIS,PASSHA,BIANCA,Female,African-American,02/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +52499,59238,53817,PRETRIAL,DAVIS,PASSHA,BIANCA,Female,African-American,02/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52501,59240,53819,PRETRIAL,GARCIABONILLE,NESTOR,R,Male,Caucasian,03/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +52501,59240,53819,PRETRIAL,GARCIABONILLE,NESTOR,R,Male,Caucasian,03/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +52501,59240,53819,PRETRIAL,GARCIABONILLE,NESTOR,R,Male,Caucasian,03/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52507,59247,53826,PRETRIAL,Valle,Nelson,NULL,Male,Hispanic,04/13/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/25/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +52507,59247,53826,PRETRIAL,Valle,Nelson,NULL,Male,Hispanic,04/13/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +52507,59247,53826,PRETRIAL,Valle,Nelson,NULL,Male,Hispanic,04/13/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +34339,59256,53835,Probation,jones,precious,NULL,Female,African-American,11/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +34339,59256,53835,Probation,jones,precious,NULL,Female,African-American,11/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +34339,59256,53835,Probation,jones,precious,NULL,Female,African-American,11/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52504,59243,53822,PRETRIAL,Crot,Robert,NULL,Male,Caucasian,01/10/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +52504,59243,53822,PRETRIAL,Crot,Robert,NULL,Male,Caucasian,01/10/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +52504,59243,53822,PRETRIAL,Crot,Robert,NULL,Male,Caucasian,01/10/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52510,59252,53831,PRETRIAL,Martinez,Maria,E.,Female,Hispanic,09/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +52510,59252,53831,PRETRIAL,Martinez,Maria,E.,Female,Hispanic,09/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +52510,59252,53831,PRETRIAL,Martinez,Maria,E.,Female,Hispanic,09/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52508,59249,53828,PRETRIAL,dimitrakis,stacy,NULL,Female,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +52508,59249,53828,PRETRIAL,dimitrakis,stacy,NULL,Female,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +52508,59249,53828,PRETRIAL,dimitrakis,stacy,NULL,Female,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52502,59241,53820,PRETRIAL,JONES,DANNY,THOMAS,Male,African-American,08/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +52502,59241,53820,PRETRIAL,JONES,DANNY,THOMAS,Male,African-American,08/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +52502,59241,53820,PRETRIAL,JONES,DANNY,THOMAS,Male,African-American,08/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52514,59257,53836,Probation,BRUCE,NATALIE,D,Female,Caucasian,12/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +52514,59257,53836,Probation,BRUCE,NATALIE,D,Female,Caucasian,12/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +52514,59257,53836,Probation,BRUCE,NATALIE,D,Female,Caucasian,12/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52497,59236,53815,PRETRIAL,Petrov,Nikolay,NULL,Male,Caucasian,06/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +52497,59236,53815,PRETRIAL,Petrov,Nikolay,NULL,Male,Caucasian,06/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +52497,59236,53815,PRETRIAL,Petrov,Nikolay,NULL,Male,Caucasian,06/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +40286,59244,53823,PRETRIAL,Bryant,Anton,NULL,Male,African-American,06/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +40286,59244,53823,PRETRIAL,Bryant,Anton,NULL,Male,African-American,06/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,4,High,8,Risk of Recidivism,0.35,9,High,New,1,0 +40286,59244,53823,PRETRIAL,Bryant,Anton,NULL,Male,African-American,06/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52513,59255,53834,Probation,Sullivan,Christopher,James,Male,Caucasian,03/14/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +52513,59255,53834,Probation,Sullivan,Christopher,James,Male,Caucasian,03/14/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +52513,59255,53834,Probation,Sullivan,Christopher,James,Male,Caucasian,03/14/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51415,59234,53813,PRETRIAL,Hamilton,Alfonso,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +51415,59234,53813,PRETRIAL,Hamilton,Alfonso,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +51415,59234,53813,PRETRIAL,Hamilton,Alfonso,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +17482,59251,53830,PRETRIAL,Schaad,Casey,NULL,Male,Caucasian,11/09/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +17482,59251,53830,PRETRIAL,Schaad,Casey,NULL,Male,Caucasian,11/09/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +17482,59251,53830,PRETRIAL,Schaad,Casey,NULL,Male,Caucasian,11/09/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52516,59260,53838,Probation,SIMMONS,MORGAN,NULL,Female,Caucasian,10/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +52516,59260,53838,Probation,SIMMONS,MORGAN,NULL,Female,Caucasian,10/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +52516,59260,53838,Probation,SIMMONS,MORGAN,NULL,Female,Caucasian,10/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52511,59253,53832,Probation,DIXON,LAKEEDAH,S,Male,Caucasian,02/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +52511,59253,53832,Probation,DIXON,LAKEEDAH,S,Male,Caucasian,02/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +52511,59253,53832,Probation,DIXON,LAKEEDAH,S,Male,Caucasian,02/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52494,59232,53811,PRETRIAL,Aguilar,Donnie,NULL,Male,Hispanic,01/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +52494,59232,53811,PRETRIAL,Aguilar,Donnie,NULL,Male,Hispanic,01/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +52494,59232,53811,PRETRIAL,Aguilar,Donnie,NULL,Male,Hispanic,01/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52500,59239,53818,PRETRIAL,LAZO,LILIAN,AZUCENA,Female,Hispanic,11/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/25/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +52500,59239,53818,PRETRIAL,LAZO,LILIAN,AZUCENA,Female,Hispanic,11/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/25/13 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +52500,59239,53818,PRETRIAL,LAZO,LILIAN,AZUCENA,Female,Hispanic,11/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52506,59246,53825,PRETRIAL,Marcelin,Steve,duste,Male,African-American,09/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/25/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +52506,59246,53825,PRETRIAL,Marcelin,Steve,duste,Male,African-American,09/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/25/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +52506,59246,53825,PRETRIAL,Marcelin,Steve,duste,Male,African-American,09/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52520,59267,53845,PRETRIAL,McKinney,Sean,Emmanuel,Male,African-American,08/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +52520,59267,53845,PRETRIAL,McKinney,Sean,Emmanuel,Male,African-American,08/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +52520,59267,53845,PRETRIAL,McKinney,Sean,Emmanuel,Male,African-American,08/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52552,59304,53877,Probation,Da Silva,Roger,NULL,Male,Hispanic,03/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +52552,59304,53877,Probation,Da Silva,Roger,NULL,Male,Hispanic,03/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +52552,59304,53877,Probation,Da Silva,Roger,NULL,Male,Hispanic,03/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51859,59276,53116,PRETRIAL,Sosaangelbello,Raul,NULL,Male,Hispanic,03/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,Copy,1,0 +51859,59276,53116,PRETRIAL,Sosaangelbello,Raul,NULL,Male,Hispanic,03/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,Copy,1,0 +51859,59276,53116,PRETRIAL,Sosaangelbello,Raul,NULL,Male,Hispanic,03/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +27391,59295,26509,PRETRIAL,Bodden,Jahmal,Carlon,Male,African-American,05/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,Copy,1,0 +27391,59295,26509,PRETRIAL,Bodden,Jahmal,Carlon,Male,African-American,05/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,4,High,8,Risk of Recidivism,0.83,10,High,Copy,1,0 +27391,59295,26509,PRETRIAL,Bodden,Jahmal,Carlon,Male,African-American,05/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +52526,59274,53852,PRETRIAL,BOWEN,QUAICE,ANTHONY,Male,African-American,10/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +52526,59274,53852,PRETRIAL,BOWEN,QUAICE,ANTHONY,Male,African-American,10/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +52526,59274,53852,PRETRIAL,BOWEN,QUAICE,ANTHONY,Male,African-American,10/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52544,59297,53870,Probation,Grunther,Jesse,NULL,Male,Caucasian,10/15/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/26/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +52544,59297,53870,Probation,Grunther,Jesse,NULL,Male,Caucasian,10/15/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/26/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +52544,59297,53870,Probation,Grunther,Jesse,NULL,Male,Caucasian,10/15/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52531,59281,53858,Probation,Puranda,Wendy,NULL,Female,Hispanic,11/18/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/26/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +52531,59281,53858,Probation,Puranda,Wendy,NULL,Female,Hispanic,11/18/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +52531,59281,53858,Probation,Puranda,Wendy,NULL,Female,Hispanic,11/18/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +35988,59290,53865,PRETRIAL,Hall,Tyler,H,Male,Caucasian,06/11/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/26/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +35988,59290,53865,PRETRIAL,Hall,Tyler,H,Male,Caucasian,06/11/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +35988,59290,53865,PRETRIAL,Hall,Tyler,H,Male,Caucasian,06/11/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/26/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +39116,59269,53847,PRETRIAL,McHugh,Matthew,NULL,Male,Caucasian,10/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +39116,59269,53847,PRETRIAL,McHugh,Matthew,NULL,Male,Caucasian,10/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +39116,59269,53847,PRETRIAL,McHugh,Matthew,NULL,Male,Caucasian,10/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52528,59278,53855,Probation,Williams,Ricky,NULL,Male,African-American,07/10/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/26/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +52528,59278,53855,Probation,Williams,Ricky,NULL,Male,African-American,07/10/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +52528,59278,53855,Probation,Williams,Ricky,NULL,Male,African-American,07/10/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52542,59293,53868,Probation,larkin,tonisha,NULL,Female,African-American,01/04/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +52542,59293,53868,Probation,larkin,tonisha,NULL,Female,African-American,01/04/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +52542,59293,53868,Probation,larkin,tonisha,NULL,Female,African-American,01/04/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +44649,59265,53843,PRETRIAL,Rodriguez,Deanna,NULL,Female,Caucasian,12/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +44649,59265,53843,PRETRIAL,Rodriguez,Deanna,NULL,Female,Caucasian,12/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,4,High,8,Risk of Recidivism,0.54,10,High,New,1,0 +44649,59265,53843,PRETRIAL,Rodriguez,Deanna,NULL,Female,Caucasian,12/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52524,59272,53850,PRETRIAL,Blackett,Reyaz,NULL,Male,Other,05/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +52524,59272,53850,PRETRIAL,Blackett,Reyaz,NULL,Male,Other,05/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +52524,59272,53850,PRETRIAL,Blackett,Reyaz,NULL,Male,Other,05/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52546,59299,53872,Probation,WILSON,ANDREW,NULL,Male,Caucasian,08/19/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +52546,59299,53872,Probation,WILSON,ANDREW,NULL,Male,Caucasian,08/19/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +52546,59299,53872,Probation,WILSON,ANDREW,NULL,Male,Caucasian,08/19/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52554,59306,53879,PRETRIAL,CENTOLELLA,ALLISON,NULL,Female,Caucasian,07/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +52554,59306,53879,PRETRIAL,CENTOLELLA,ALLISON,NULL,Female,Caucasian,07/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +52554,59306,53879,PRETRIAL,CENTOLELLA,ALLISON,NULL,Female,Caucasian,07/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52534,59286,53862,Probation,SEYMOUR,kELLY,NULL,Female,Caucasian,10/12/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/26/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +52534,59286,53862,Probation,SEYMOUR,kELLY,NULL,Female,Caucasian,10/12/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +52534,59286,53862,Probation,SEYMOUR,kELLY,NULL,Female,Caucasian,10/12/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +18072,59264,53842,PRETRIAL,MINCEY,APRIL,NULL,Female,Caucasian,09/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +18072,59264,53842,PRETRIAL,MINCEY,APRIL,NULL,Female,Caucasian,09/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +18072,59264,53842,PRETRIAL,MINCEY,APRIL,NULL,Female,Caucasian,09/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52555,59307,53880,Probation,welte,shannon,NULL,Female,Caucasian,05/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +52555,59307,53880,Probation,welte,shannon,NULL,Female,Caucasian,05/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +52555,59307,53880,Probation,welte,shannon,NULL,Female,Caucasian,05/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52530,59280,53857,Probation,Pryer,Fulton,NULL,Male,African-American,12/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/26/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +52530,59280,53857,Probation,Pryer,Fulton,NULL,Male,African-American,12/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +52530,59280,53857,Probation,Pryer,Fulton,NULL,Male,African-American,12/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +42938,59291,53866,PRETRIAL,Barron,Madeline,NULL,Female,Hispanic,02/27/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/26/13 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +42938,59291,53866,PRETRIAL,Barron,Madeline,NULL,Female,Hispanic,02/27/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/26/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +42938,59291,53866,PRETRIAL,Barron,Madeline,NULL,Female,Hispanic,02/27/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52522,59270,53848,PRETRIAL,Bittelman,Joshe,NULL,Male,Caucasian,04/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +52522,59270,53848,PRETRIAL,Bittelman,Joshe,NULL,Male,Caucasian,04/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +52522,59270,53848,PRETRIAL,Bittelman,Joshe,NULL,Male,Caucasian,04/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52549,59301,53874,Probation,Devenuto,Henry,NULL,Male,Caucasian,09/19/37,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/26/13 0:00,1,Low,7,Risk of Violence,-4.65,1,Low,New,1,0 +52549,59301,53874,Probation,Devenuto,Henry,NULL,Male,Caucasian,09/19/37,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/26/13 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +52549,59301,53874,Probation,Devenuto,Henry,NULL,Male,Caucasian,09/19/37,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +23181,59283,53859,PRETRIAL,ABLES,SHARLENE,NULL,Female,African-American,05/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +23181,59283,53859,PRETRIAL,ABLES,SHARLENE,NULL,Female,African-American,05/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +23181,59283,53859,PRETRIAL,ABLES,SHARLENE,NULL,Female,African-American,05/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +42102,59288,41874,Probation,Park,Jacquelyn,NULL,Female,Caucasian,03/14/79,17,All Scales,Intake,English,Pretrial,Jail Inmate,Divorced,2/26/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +42102,59288,41874,Probation,Park,Jacquelyn,NULL,Female,Caucasian,03/14/79,17,All Scales,Intake,English,Pretrial,Jail Inmate,Divorced,2/26/13 0:00,1,Low,8,Risk of Recidivism,-0.77,4,Low,New,1,0 +42102,59288,41874,Probation,Park,Jacquelyn,NULL,Female,Caucasian,03/14/79,17,All Scales,Intake,English,Pretrial,Jail Inmate,Divorced,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52518,59262,53840,PRETRIAL,Hauselt,Robert,NULL,Male,Caucasian,03/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +52518,59262,53840,PRETRIAL,Hauselt,Robert,NULL,Male,Caucasian,03/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.71,10,High,New,1,0 +52518,59262,53840,PRETRIAL,Hauselt,Robert,NULL,Male,Caucasian,03/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52527,59275,53853,PRETRIAL,SWEET-FOY,CHERCOLBY,NULL,Female,African-American,12/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +52527,59275,53853,PRETRIAL,SWEET-FOY,CHERCOLBY,NULL,Female,African-American,12/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +52527,59275,53853,PRETRIAL,SWEET-FOY,CHERCOLBY,NULL,Female,African-American,12/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52525,59273,53851,PRETRIAL,DANIELS,DEVONAH,NULL,Male,African-American,11/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.01,4,Low,New,1,0 +52525,59273,53851,PRETRIAL,DANIELS,DEVONAH,NULL,Male,African-American,11/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,9,High,New,1,0 +52525,59273,53851,PRETRIAL,DANIELS,DEVONAH,NULL,Male,African-American,11/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +52545,59298,53871,Probation,Besada,Manuel,Alejandro,Male,Hispanic,11/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +52545,59298,53871,Probation,Besada,Manuel,Alejandro,Male,Hispanic,11/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +52545,59298,53871,Probation,Besada,Manuel,Alejandro,Male,Hispanic,11/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +42612,59277,53854,Probation,Byrd,Vanessa,Joyce,Female,African-American,10/21/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/26/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +42612,59277,53854,Probation,Byrd,Vanessa,Joyce,Female,African-American,10/21/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +42612,59277,53854,Probation,Byrd,Vanessa,Joyce,Female,African-American,10/21/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +52543,59294,53869,Probation,patino,jonathan,NULL,Male,Caucasian,12/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/26/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +52543,59294,53869,Probation,patino,jonathan,NULL,Male,Caucasian,12/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/26/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +52543,59294,53869,Probation,patino,jonathan,NULL,Male,Caucasian,12/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52521,59268,53846,PRETRIAL,Lindsey,Nicholas,NULL,Male,African-American,10/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +52521,59268,53846,PRETRIAL,Lindsey,Nicholas,NULL,Male,African-American,10/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +52521,59268,53846,PRETRIAL,Lindsey,Nicholas,NULL,Male,African-American,10/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52551,59303,53876,Probation,Ayala,Nancy,NULL,Female,Hispanic,09/10/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +52551,59303,53876,Probation,Ayala,Nancy,NULL,Female,Hispanic,09/10/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +52551,59303,53876,Probation,Ayala,Nancy,NULL,Female,Hispanic,09/10/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51656,59282,52857,Probation,dustin,richardson,NULL,Male,Caucasian,12/23/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,4,High,7,Risk of Violence,-1.03,8,High,New,1,0 +51656,59282,52857,Probation,dustin,richardson,NULL,Male,Caucasian,12/23/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,4,High,8,Risk of Recidivism,0.89,10,High,New,1,0 +51656,59282,52857,Probation,dustin,richardson,NULL,Male,Caucasian,12/23/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,4,High,18,Risk of Failure to Appear,36,10,High,New,1,0 +29314,59289,53864,PRETRIAL,Perez,Efrain,NULL,Male,Caucasian,11/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +29314,59289,53864,PRETRIAL,Perez,Efrain,NULL,Male,Caucasian,11/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +29314,59289,53864,PRETRIAL,Perez,Efrain,NULL,Male,Caucasian,11/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +51530,59296,52722,Probation,HOUSTON,ALDRIC,R,Male,African-American,08/17/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +51530,59296,52722,Probation,HOUSTON,ALDRIC,R,Male,African-American,08/17/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,8,High,New,1,0 +51530,59296,52722,Probation,HOUSTON,ALDRIC,R,Male,African-American,08/17/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +52529,59279,53856,PRETRIAL,turner,sequan,NULL,Male,African-American,01/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.04,8,High,New,1,0 +52529,59279,53856,PRETRIAL,turner,sequan,NULL,Male,African-American,01/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +52529,59279,53856,PRETRIAL,turner,sequan,NULL,Male,African-American,01/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52541,59292,53867,DRRD,Pierre,Hal,Edwin,Male,African-American,01/06/78,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +52541,59292,53867,DRRD,Pierre,Hal,Edwin,Male,African-American,01/06/78,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +52541,59292,53867,DRRD,Pierre,Hal,Edwin,Male,African-American,01/06/78,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +52532,59284,53860,PRETRIAL,Marconi,Jason,NULL,Male,Caucasian,12/11/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,2,Medium,7,Risk of Violence,-2.97,1,Low,New,1,0 +52532,59284,53860,PRETRIAL,Marconi,Jason,NULL,Male,Caucasian,12/11/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +52532,59284,53860,PRETRIAL,Marconi,Jason,NULL,Male,Caucasian,12/11/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52535,59287,53863,Probation,McNabb,Rodney,NULL,Male,African-American,11/16/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +52535,59287,53863,Probation,McNabb,Rodney,NULL,Male,African-American,11/16/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +52535,59287,53863,Probation,McNabb,Rodney,NULL,Male,African-American,11/16/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +27399,59266,53844,PRETRIAL,Garrett,Samuel,NULL,Male,African-American,11/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,2,Medium,7,Risk of Violence,-3.01,1,Low,New,1,0 +27399,59266,53844,PRETRIAL,Garrett,Samuel,NULL,Male,African-American,11/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +27399,59266,53844,PRETRIAL,Garrett,Samuel,NULL,Male,African-American,11/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52553,59305,53878,Probation,acosta,daniel,NULL,Male,Hispanic,06/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +52553,59305,53878,Probation,acosta,daniel,NULL,Male,Hispanic,06/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +52553,59305,53878,Probation,acosta,daniel,NULL,Male,Hispanic,06/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52519,59263,53841,PRETRIAL,AUGUSTE,GUITEAU,NULL,Male,African-American,05/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +52519,59263,53841,PRETRIAL,AUGUSTE,GUITEAU,NULL,Male,African-American,05/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +52519,59263,53841,PRETRIAL,AUGUSTE,GUITEAU,NULL,Male,African-American,05/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52523,59271,53849,PRETRIAL,Perez,Azli,NULL,Male,Caucasian,11/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +52523,59271,53849,PRETRIAL,Perez,Azli,NULL,Male,Caucasian,11/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +52523,59271,53849,PRETRIAL,Perez,Azli,NULL,Male,Caucasian,11/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52547,59300,53873,PRETRIAL,Louima,Marleme,NULL,Male,African-American,07/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +52547,59300,53873,PRETRIAL,Louima,Marleme,NULL,Male,African-American,07/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +52547,59300,53873,PRETRIAL,Louima,Marleme,NULL,Male,African-American,07/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52564,59321,53891,PRETRIAL,Rivera-Owens,Jason,NULL,Male,Caucasian,11/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +52564,59321,53891,PRETRIAL,Rivera-Owens,Jason,NULL,Male,Caucasian,11/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +52564,59321,53891,PRETRIAL,Rivera-Owens,Jason,NULL,Male,Caucasian,11/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52573,59336,53904,PRETRIAL,ravitz,sharon,NULL,Female,Caucasian,12/11/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/27/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +52573,59336,53904,PRETRIAL,ravitz,sharon,NULL,Female,Caucasian,12/11/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/27/13 0:00,1,Low,8,Risk of Recidivism,-2.64,1,Low,New,1,0 +52573,59336,53904,PRETRIAL,ravitz,sharon,NULL,Female,Caucasian,12/11/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +44612,59308,53881,PRETRIAL,Hill,Sanford,NULL,Male,African-American,03/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +44612,59308,53881,PRETRIAL,Hill,Sanford,NULL,Male,African-American,03/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +44612,59308,53881,PRETRIAL,Hill,Sanford,NULL,Male,African-American,03/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +6069,59329,53899,PRETRIAL,TELUSMAN,KERRENSLEY,NULL,Male,African-American,03/12/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +6069,59329,53899,PRETRIAL,TELUSMAN,KERRENSLEY,NULL,Male,African-American,03/12/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +6069,59329,53899,PRETRIAL,TELUSMAN,KERRENSLEY,NULL,Male,African-American,03/12/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +8687,59342,53909,PRETRIAL,HIGGS,MARSHALL,E,Male,African-American,11/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +8687,59342,53909,PRETRIAL,HIGGS,MARSHALL,E,Male,African-American,11/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,4,High,8,Risk of Recidivism,1.05,10,High,New,1,0 +8687,59342,53909,PRETRIAL,HIGGS,MARSHALL,E,Male,African-American,11/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52577,59344,53911,Probation,schembari,nelson,NULL,Male,Caucasian,05/07/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +52577,59344,53911,Probation,schembari,nelson,NULL,Male,Caucasian,05/07/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +52577,59344,53911,Probation,schembari,nelson,NULL,Male,Caucasian,05/07/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +33552,59334,32652,PRETRIAL,Reveille,Jeff,NULL,Male,African-American,10/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,4,High,7,Risk of Violence,-0.73,9,High,Copy,1,0 +33552,59334,32652,PRETRIAL,Reveille,Jeff,NULL,Male,African-American,10/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,4,High,8,Risk of Recidivism,0.58,9,High,Copy,1,0 +33552,59334,32652,PRETRIAL,Reveille,Jeff,NULL,Male,African-American,10/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +52586,59352,53918,PRETRIAL,PHILLIPS,RODRICK,NULL,Male,African-American,02/24/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +52586,59352,53918,PRETRIAL,PHILLIPS,RODRICK,NULL,Male,African-American,02/24/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +52586,59352,53918,PRETRIAL,PHILLIPS,RODRICK,NULL,Male,African-American,02/24/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52568,59326,53896,Probation,smith,omar,NULL,Male,African-American,08/16/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +52568,59326,53896,Probation,smith,omar,NULL,Male,African-American,08/16/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +52568,59326,53896,Probation,smith,omar,NULL,Male,African-American,08/16/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +7352,59313,6938,PRETRIAL,Pastoriza,Nelson,NULL,Male,Caucasian,01/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,Copy,1,0 +7352,59313,6938,PRETRIAL,Pastoriza,Nelson,NULL,Male,Caucasian,01/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,Copy,1,0 +7352,59313,6938,PRETRIAL,Pastoriza,Nelson,NULL,Male,Caucasian,01/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +52580,59347,53914,Probation,Castillo,Ismael,NULL,Male,Hispanic,04/01/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +52580,59347,53914,Probation,Castillo,Ismael,NULL,Male,Hispanic,04/01/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +52580,59347,53914,Probation,Castillo,Ismael,NULL,Male,Hispanic,04/01/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52560,59317,53887,PRETRIAL,BELOTTE,VANESSA,NULL,Female,African-American,10/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +52560,59317,53887,PRETRIAL,BELOTTE,VANESSA,NULL,Female,African-American,10/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +52560,59317,53887,PRETRIAL,BELOTTE,VANESSA,NULL,Female,African-American,10/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +22640,59354,53920,PRETRIAL,Ford,Andrew,NULL,Male,African-Am,08/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.99,4,Low,New,1,0 +22640,59354,53920,PRETRIAL,Ford,Andrew,NULL,Male,African-Am,08/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +22640,59354,53920,PRETRIAL,Ford,Andrew,NULL,Male,African-Am,08/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52570,59331,53900,PRETRIAL,Peeples,Sharonada,Redding,Female,African-American,06/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/27/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +52570,59331,53900,PRETRIAL,Peeples,Sharonada,Redding,Female,African-American,06/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +52570,59331,53900,PRETRIAL,Peeples,Sharonada,Redding,Female,African-American,06/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +41229,59333,53902,PRETRIAL,KVAMME,TORVALD,NULL,Male,Caucasian,01/18/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +41229,59333,53902,PRETRIAL,KVAMME,TORVALD,NULL,Male,Caucasian,01/18/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +41229,59333,53902,PRETRIAL,KVAMME,TORVALD,NULL,Male,Caucasian,01/18/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52574,59338,53906,Probation,Burgos,Laura,NULL,Female,Hispanic,05/21/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/13 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +52574,59338,53906,Probation,Burgos,Laura,NULL,Female,Hispanic,05/21/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +52574,59338,53906,Probation,Burgos,Laura,NULL,Female,Hispanic,05/21/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +40919,59312,40569,PRETRIAL,TAYLOR,FLOYD,NULL,Male,African-American,12/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,Copy,1,0 +40919,59312,40569,PRETRIAL,TAYLOR,FLOYD,NULL,Male,African-American,12/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,Copy,1,0 +40919,59312,40569,PRETRIAL,TAYLOR,FLOYD,NULL,Male,African-American,12/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +52578,59345,53912,PRETRIAL,KING,PAUL,NULL,Male,African-American,09/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/13 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +52578,59345,53912,PRETRIAL,KING,PAUL,NULL,Male,African-American,09/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +52578,59345,53912,PRETRIAL,KING,PAUL,NULL,Male,African-American,09/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +36753,59315,36056,PRETRIAL,GOODRUM,TIMOTHY,L,Male,African-American,07/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/27/13 0:00,2,Medium,7,Risk of Violence,-3.18,1,Low,Copy,1,0 +36753,59315,36056,PRETRIAL,GOODRUM,TIMOTHY,L,Male,African-American,07/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/27/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,Copy,1,0 +36753,59315,36056,PRETRIAL,GOODRUM,TIMOTHY,L,Male,African-American,07/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/27/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +47687,59324,53894,PRETRIAL,RHODEN,SHANE,NULL,Male,African-American,07/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +47687,59324,53894,PRETRIAL,RHODEN,SHANE,NULL,Male,African-American,07/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +47687,59324,53894,PRETRIAL,RHODEN,SHANE,NULL,Male,African-American,07/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +25291,59349,25137,PRETRIAL,ANDERSON,MICHAEL,NULL,Male,African-American,01/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,Copy,1,0 +25291,59349,25137,PRETRIAL,ANDERSON,MICHAEL,NULL,Male,African-American,01/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,Copy,1,0 +25291,59349,25137,PRETRIAL,ANDERSON,MICHAEL,NULL,Male,African-American,01/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +52562,59319,53889,PRETRIAL,SAPP,TRACI,L,Male,African-American,04/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +52562,59319,53889,PRETRIAL,SAPP,TRACI,L,Male,African-American,04/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +52562,59319,53889,PRETRIAL,SAPP,TRACI,L,Male,African-American,04/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +33083,59309,53882,PRETRIAL,Sanchezferrans,Francisco,NULL,Male,Caucasian,08/09/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +33083,59309,53882,PRETRIAL,Sanchezferrans,Francisco,NULL,Male,Caucasian,08/09/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +33083,59309,53882,PRETRIAL,Sanchezferrans,Francisco,NULL,Male,Caucasian,08/09/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +52576,59343,53910,Probation,doytier,maxence,NULL,Male,Caucasian,02/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +52576,59343,53910,Probation,doytier,maxence,NULL,Male,Caucasian,02/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +52576,59343,53910,Probation,doytier,maxence,NULL,Male,Caucasian,02/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52565,59322,53892,PRETRIAL,Everett,Leory,NULL,Male,African-American,10/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +52565,59322,53892,PRETRIAL,Everett,Leory,NULL,Male,African-American,10/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +52565,59322,53892,PRETRIAL,Everett,Leory,NULL,Male,African-American,10/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52585,59351,53917,DRRD,Auguste,Kareem,Iliones,Male,African-American,05/03/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.01,8,High,New,1,0 +52585,59351,53917,DRRD,Auguste,Kareem,Iliones,Male,African-American,05/03/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,6,Medium,New,1,0 +52585,59351,53917,DRRD,Auguste,Kareem,Iliones,Male,African-American,05/03/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,New,1,0 +15256,59330,53043,PRETRIAL,LAVOIX,SHARLEND,NULL,Male,African-American,12/13/81,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/13 0:00,4,High,7,Risk of Violence,-0.2,10,High,Copy,1,0 +15256,59330,53043,PRETRIAL,LAVOIX,SHARLEND,NULL,Male,African-American,12/13/81,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/13 0:00,4,High,8,Risk of Recidivism,1.39,10,High,Copy,1,0 +15256,59330,53043,PRETRIAL,LAVOIX,SHARLEND,NULL,Male,African-American,12/13/81,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/13 0:00,4,High,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +52581,59348,53915,Probation,crist,william,NULL,Male,Caucasian,11/03/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +52581,59348,53915,Probation,crist,william,NULL,Male,Caucasian,11/03/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +52581,59348,53915,Probation,crist,william,NULL,Male,Caucasian,11/03/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52558,59314,53885,PRETRIAL,SHAW,PETER,ROY,Male,African-American,05/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/27/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +52558,59314,53885,PRETRIAL,SHAW,PETER,ROY,Male,African-American,05/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +52558,59314,53885,PRETRIAL,SHAW,PETER,ROY,Male,African-American,05/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52572,59335,53903,Probation,Riman,Jeffrey,NULL,Male,Caucasian,07/14/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +52572,59335,53903,Probation,Riman,Jeffrey,NULL,Male,Caucasian,07/14/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +52572,59335,53903,Probation,Riman,Jeffrey,NULL,Male,Caucasian,07/14/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +25291,27454,25137,PRETRIAL,ANDERSON,MICHAEL,NULL,Male,African-American,01/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +25291,27454,25137,PRETRIAL,ANDERSON,MICHAEL,NULL,Male,African-American,01/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +25291,27454,25137,PRETRIAL,ANDERSON,MICHAEL,NULL,Male,African-American,01/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52563,59320,53890,PRETRIAL,Campbell,Vivienne,NULL,Female,Other,11/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +52563,59320,53890,PRETRIAL,Campbell,Vivienne,NULL,Female,Other,11/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +52563,59320,53890,PRETRIAL,Campbell,Vivienne,NULL,Female,Other,11/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52548,59337,53905,Probation,Latortue,Michele,NULL,Female,African-American,09/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.41,3,Low,New,1,0 +52548,59337,53905,Probation,Latortue,Michele,NULL,Female,African-American,09/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.11,8,High,New,1,0 +52548,59337,53905,Probation,Latortue,Michele,NULL,Female,African-American,09/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52566,59323,53893,PRETRIAL,Boyce,Zacchius,NULL,Male,African-American,09/17/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +52566,59323,53893,PRETRIAL,Boyce,Zacchius,NULL,Male,African-American,09/17/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +52566,59323,53893,PRETRIAL,Boyce,Zacchius,NULL,Male,African-American,09/17/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52557,59311,53884,PRETRIAL,Nunes,Peyton,NULL,Female,Caucasian,10/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +52557,59311,53884,PRETRIAL,Nunes,Peyton,NULL,Female,Caucasian,10/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,9,High,New,1,0 +52557,59311,53884,PRETRIAL,Nunes,Peyton,NULL,Female,Caucasian,10/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52561,59318,53888,PRETRIAL,VALDEZ,LUIS,NULL,Male,Hispanic,11/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.06,8,High,New,1,0 +52561,59318,53888,PRETRIAL,VALDEZ,LUIS,NULL,Male,Hispanic,11/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +52561,59318,53888,PRETRIAL,VALDEZ,LUIS,NULL,Male,Hispanic,11/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52587,59353,53919,Probation,Jackson,Dexter,NULL,Male,African-American,10/20/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +52587,59353,53919,Probation,Jackson,Dexter,NULL,Male,African-American,10/20/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +52587,59353,53919,Probation,Jackson,Dexter,NULL,Male,African-American,10/20/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52567,59325,53895,PRETRIAL,JOHNSON,THOLOME,NULL,Male,African-American,11/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.73,2,Low,New,1,0 +52567,59325,53895,PRETRIAL,JOHNSON,THOLOME,NULL,Male,African-American,11/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +52567,59325,53895,PRETRIAL,JOHNSON,THOLOME,NULL,Male,African-American,11/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52571,59332,53901,Probation,Medcraft,Deborah,NULL,Female,Caucasian,12/17/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +52571,59332,53901,Probation,Medcraft,Deborah,NULL,Female,Caucasian,12/17/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +52571,59332,53901,Probation,Medcraft,Deborah,NULL,Female,Caucasian,12/17/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +52575,59339,53907,Probation,hillis,barbara,NULL,Female,Caucasian,04/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +52575,59339,53907,Probation,hillis,barbara,NULL,Female,Caucasian,04/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +52575,59339,53907,Probation,hillis,barbara,NULL,Female,Caucasian,04/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52579,59346,53913,PRETRIAL,Innocent,Diana,NULL,Female,African-American,04/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +52579,59346,53913,PRETRIAL,Innocent,Diana,NULL,Female,African-American,04/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +52579,59346,53913,PRETRIAL,Innocent,Diana,NULL,Female,African-American,04/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52243,59367,53932,PRETRIAL,Stephens,Keyanna,NULL,Female,African-American,09/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +52243,59367,53932,PRETRIAL,Stephens,Keyanna,NULL,Female,African-American,09/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +52243,59367,53932,PRETRIAL,Stephens,Keyanna,NULL,Female,African-American,09/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +46011,59374,46360,PRETRIAL,BONES,ANTHONY,NULL,Male,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/13 0:00,4,High,7,Risk of Violence,-1.14,8,High,Copy,1,0 +46011,59374,46360,PRETRIAL,BONES,ANTHONY,NULL,Male,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,Copy,1,0 +46011,59374,46360,PRETRIAL,BONES,ANTHONY,NULL,Male,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +52600,59376,53938,Probation,Perez,Oscar,NULL,Male,Hispanic,01/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,4,High,7,Risk of Violence,-1.05,8,High,New,1,0 +52600,59376,53938,Probation,Perez,Oscar,NULL,Male,Hispanic,01/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +52600,59376,53938,Probation,Perez,Oscar,NULL,Male,Hispanic,01/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,4,High,18,Risk of Failure to Appear,44,10,High,New,1,0 +52592,59362,53928,PRETRIAL,Edwards,Shawn,NULL,Male,African-American,09/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +52592,59362,53928,PRETRIAL,Edwards,Shawn,NULL,Male,African-American,09/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +52592,59362,53928,PRETRIAL,Edwards,Shawn,NULL,Male,African-American,09/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52604,59379,53941,Probation,doyle,ryan,NULL,Male,Caucasian,01/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +52604,59379,53941,Probation,doyle,ryan,NULL,Male,Caucasian,01/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +52604,59379,53941,Probation,doyle,ryan,NULL,Male,Caucasian,01/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52614,59392,53953,Probation,GALAN,EZEQUIEL,NULL,Male,Hispanic,01/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +52614,59392,53953,Probation,GALAN,EZEQUIEL,NULL,Male,Hispanic,01/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +52614,59392,53953,Probation,GALAN,EZEQUIEL,NULL,Male,Hispanic,01/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +17083,59358,53924,PRETRIAL,BENITEZ,ANTHONY,NULL,Male,Caucasian,01/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,4,High,7,Risk of Violence,-0.4,10,High,New,1,0 +17083,59358,53924,PRETRIAL,BENITEZ,ANTHONY,NULL,Male,Caucasian,01/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +17083,59358,53924,PRETRIAL,BENITEZ,ANTHONY,NULL,Male,Caucasian,01/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52609,59383,53945,PRETRIAL,Ovidio,Vasquez,NULL,Male,Hispanic,01/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/28/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +52609,59383,53945,PRETRIAL,Ovidio,Vasquez,NULL,Male,Hispanic,01/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/28/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +52609,59383,53945,PRETRIAL,Ovidio,Vasquez,NULL,Male,Hispanic,01/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +37439,59388,53949,PRETRIAL,petithomme,loudy,NULL,Male,African-American,12/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +37439,59388,53949,PRETRIAL,petithomme,loudy,NULL,Male,African-American,12/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +37439,59388,53949,PRETRIAL,petithomme,loudy,NULL,Male,African-American,12/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52599,59372,53936,Probation,peterson,russell,NULL,Male,Caucasian,05/09/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/28/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +52599,59372,53936,Probation,peterson,russell,NULL,Male,Caucasian,05/09/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/28/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +52599,59372,53936,Probation,peterson,russell,NULL,Male,Caucasian,05/09/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52615,59393,53954,Probation,carney,douglas,NULL,Male,Caucasian,11/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +52615,59393,53954,Probation,carney,douglas,NULL,Male,Caucasian,11/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +52615,59393,53954,Probation,carney,douglas,NULL,Male,Caucasian,11/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52612,59385,53947,Probation,Caban,Alberto,NULL,Male,Hispanic,10/22/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/28/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +52612,59385,53947,Probation,Caban,Alberto,NULL,Male,Hispanic,10/22/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/28/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +52612,59385,53947,Probation,Caban,Alberto,NULL,Male,Hispanic,10/22/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +21614,59364,53930,PRETRIAL,GREEN,GARETH,SHELDON,Male,African-American,02/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +21614,59364,53930,PRETRIAL,GREEN,GARETH,SHELDON,Male,African-American,02/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +21614,59364,53930,PRETRIAL,GREEN,GARETH,SHELDON,Male,African-American,02/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52597,59369,53934,PRETRIAL,Dove,Ewexta,Clive,Male,African-American,12/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/28/13 0:00,4,High,7,Risk of Violence,-1.05,8,High,New,1,0 +52597,59369,53934,PRETRIAL,Dove,Ewexta,Clive,Male,African-American,12/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/28/13 0:00,4,High,8,Risk of Recidivism,0.81,10,High,New,1,0 +52597,59369,53934,PRETRIAL,Dove,Ewexta,Clive,Male,African-American,12/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/28/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +13888,59356,53922,PRETRIAL,NANCE,STEVEN,NULL,Male,African-American,03/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +13888,59356,53922,PRETRIAL,NANCE,STEVEN,NULL,Male,African-American,03/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +13888,59356,53922,PRETRIAL,NANCE,STEVEN,NULL,Male,African-American,03/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +45744,59390,53951,PRETRIAL,MERCADO,JAVIER,NULL,Male,Caucasian,10/11/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +45744,59390,53951,PRETRIAL,MERCADO,JAVIER,NULL,Male,Caucasian,10/11/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +45744,59390,53951,PRETRIAL,MERCADO,JAVIER,NULL,Male,Caucasian,10/11/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +52601,59377,53939,PRETRIAL,johnson,Sharon,NULL,Female,African-American,12/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,New,1,0 +52601,59377,53939,PRETRIAL,johnson,Sharon,NULL,Female,African-American,12/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,10,High,New,1,0 +52601,59377,53939,PRETRIAL,johnson,Sharon,NULL,Female,African-American,12/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,New,1,0 +44688,59370,44824,PRETRIAL,Jimenez,michael,NULL,Male,Hispanic,03/06/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/28/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +44688,59370,44824,PRETRIAL,Jimenez,michael,NULL,Male,Hispanic,03/06/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,6,Medium,New,1,0 +44688,59370,44824,PRETRIAL,Jimenez,michael,NULL,Male,Hispanic,03/06/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/28/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52610,59384,53946,Probation,Moreno,Alan,NULL,Male,Hispanic,05/30/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/28/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +52610,59384,53946,Probation,Moreno,Alan,NULL,Male,Hispanic,05/30/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/28/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +52610,59384,53946,Probation,Moreno,Alan,NULL,Male,Hispanic,05/30/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51037,59387,52179,Probation,Walls,Sergio,NULL,Male,African-American,05/29/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,Copy,1,0 +51037,59387,52179,Probation,Walls,Sergio,NULL,Male,African-American,05/29/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,10,High,Copy,1,0 +51037,59387,52179,Probation,Walls,Sergio,NULL,Male,African-American,05/29/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +52594,59366,53931,PRETRIAL,Ellis,Demetrious,NULL,Male,African-American,06/28/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +52594,59366,53931,PRETRIAL,Ellis,Demetrious,NULL,Male,African-American,06/28/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +52594,59366,53931,PRETRIAL,Ellis,Demetrious,NULL,Male,African-American,06/28/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52603,59380,53942,Probation,Hurst,Heather,Lynn,Female,Caucasian,06/14/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/28/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +52603,59380,53942,Probation,Hurst,Heather,Lynn,Female,Caucasian,06/14/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/28/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +52603,59380,53942,Probation,Hurst,Heather,Lynn,Female,Caucasian,06/14/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +21816,59391,53952,Probation,Leon,Johnell,Enrique,Male,Hispanic,02/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.27,3,Low,New,1,0 +21816,59391,53952,Probation,Leon,Johnell,Enrique,Male,Hispanic,02/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +21816,59391,53952,Probation,Leon,Johnell,Enrique,Male,Hispanic,02/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52591,59359,53925,PRETRIAL,Felinor,Jean,Clotaireso,Male,Other,02/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +52591,59359,53925,PRETRIAL,Felinor,Jean,Clotaireso,Male,Other,02/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +52591,59359,53925,PRETRIAL,Felinor,Jean,Clotaireso,Male,Other,02/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +16156,59361,53927,PRETRIAL,FLEMING,MICHAEL,NULL,Male,African-American,07/12/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +16156,59361,53927,PRETRIAL,FLEMING,MICHAEL,NULL,Male,African-American,07/12/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +16156,59361,53927,PRETRIAL,FLEMING,MICHAEL,NULL,Male,African-American,07/12/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52595,59368,53933,PRETRIAL,Peterson,Tyrone,N,Male,African-American,08/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +52595,59368,53933,PRETRIAL,Peterson,Tyrone,N,Male,African-American,08/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +52595,59368,53933,PRETRIAL,Peterson,Tyrone,N,Male,African-American,08/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +46011,59375,46360,PRETRIAL,BONES,ANTHONY,NULL,Male,African-American,08/19/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/13 0:00,4,High,7,Risk of Violence,-1.14,8,High,Copy,1,0 +46011,59375,46360,PRETRIAL,BONES,ANTHONY,NULL,Male,African-American,08/19/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,Copy,1,0 +46011,59375,46360,PRETRIAL,BONES,ANTHONY,NULL,Male,African-American,08/19/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +52613,59389,53950,Probation,Ramirez,Rolando,Marroquin,Male,Hispanic,01/31/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +52613,59389,53950,Probation,Ramirez,Rolando,Marroquin,Male,Hispanic,01/31/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +52613,59389,53950,Probation,Ramirez,Rolando,Marroquin,Male,Hispanic,01/31/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52605,59381,53943,PRETRIAL,Nougues,Davidson,NULL,Male,African-American,08/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,4,High,7,Risk of Violence,-0.9,9,High,New,1,0 +52605,59381,53943,PRETRIAL,Nougues,Davidson,NULL,Male,African-American,08/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,4,High,8,Risk of Recidivism,0.35,9,High,New,1,0 +52605,59381,53943,PRETRIAL,Nougues,Davidson,NULL,Male,African-American,08/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52590,59360,53926,PRETRIAL,Robinson,Shariyf,Basil,Male,African-American,10/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +52590,59360,53926,PRETRIAL,Robinson,Shariyf,Basil,Male,African-American,10/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +52590,59360,53926,PRETRIAL,Robinson,Shariyf,Basil,Male,African-American,10/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +52616,59394,53955,PRETRIAL,Woodfork,JAMES,NULL,Male,African-American,11/11/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/28/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +52616,59394,53955,PRETRIAL,Woodfork,JAMES,NULL,Male,African-American,11/11/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/28/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +52616,59394,53955,PRETRIAL,Woodfork,JAMES,NULL,Male,African-American,11/11/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52588,59355,53921,PRETRIAL,Davis,Dennis,NULL,Male,African-American,09/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +52588,59355,53921,PRETRIAL,Davis,Dennis,NULL,Male,African-American,09/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +52588,59355,53921,PRETRIAL,Davis,Dennis,NULL,Male,African-American,09/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +44817,59373,53937,PRETRIAL,Nayda,Alexander,NULL,Male,Caucasian,12/16/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/28/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +44817,59373,53937,PRETRIAL,Nayda,Alexander,NULL,Male,Caucasian,12/16/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/28/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +44817,59373,53937,PRETRIAL,Nayda,Alexander,NULL,Male,Caucasian,12/16/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52602,59378,53940,PRETRIAL,Baloch,Shuhun,NULL,Male,African-American,12/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +52602,59378,53940,PRETRIAL,Baloch,Shuhun,NULL,Male,African-American,12/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +52602,59378,53940,PRETRIAL,Baloch,Shuhun,NULL,Male,African-American,12/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52593,59363,53929,PRETRIAL,Griffin,Louis,NULL,Male,African-American,06/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +52593,59363,53929,PRETRIAL,Griffin,Louis,NULL,Male,African-American,06/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +52593,59363,53929,PRETRIAL,Griffin,Louis,NULL,Male,African-American,06/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +22489,59365,21658,Probation,Ivey,Timmie,NULL,Male,African-American,09/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,Copy,1,0 +22489,59365,21658,Probation,Ivey,Timmie,NULL,Male,African-American,09/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.83,10,High,Copy,1,0 +22489,59365,21658,Probation,Ivey,Timmie,NULL,Male,African-American,09/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,Copy,1,0 +52611,59386,53948,Probation,kelly,nyecha,NULL,Female,African-American,09/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +52611,59386,53948,Probation,kelly,nyecha,NULL,Female,African-American,09/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +52611,59386,53948,Probation,kelly,nyecha,NULL,Female,African-American,09/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52589,59357,53923,PRETRIAL,Zamot,Porfirio,NULL,Male,African-American,11/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +52589,59357,53923,PRETRIAL,Zamot,Porfirio,NULL,Male,African-American,11/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +52589,59357,53923,PRETRIAL,Zamot,Porfirio,NULL,Male,African-American,11/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +43819,59407,53967,PRETRIAL,Barros,Jalen,NULL,Male,African-American,04/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.01,8,High,New,1,0 +43819,59407,53967,PRETRIAL,Barros,Jalen,NULL,Male,African-American,04/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +43819,59407,53967,PRETRIAL,Barros,Jalen,NULL,Male,African-American,04/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +8187,59399,53960,PRETRIAL,Daniel,Jeremy,T,Male,African-American,04/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +8187,59399,53960,PRETRIAL,Daniel,Jeremy,T,Male,African-American,04/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,4,High,8,Risk of Recidivism,0.42,9,High,New,1,0 +8187,59399,53960,PRETRIAL,Daniel,Jeremy,T,Male,African-American,04/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52638,59423,53981,PRETRIAL,SPUNGER,TERRY,NULL,Male,Caucasian,02/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +52638,59423,53981,PRETRIAL,SPUNGER,TERRY,NULL,Male,Caucasian,02/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +52638,59423,53981,PRETRIAL,SPUNGER,TERRY,NULL,Male,Caucasian,02/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52620,59402,53962,PRETRIAL,Lowe,Michael,NULL,Male,Caucasian,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,New,1,0 +52620,59402,53962,PRETRIAL,Lowe,Michael,NULL,Male,Caucasian,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +52620,59402,53962,PRETRIAL,Lowe,Michael,NULL,Male,Caucasian,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52636,59420,53978,PRETRIAL,SCOTT,KYLE,ANTHONY,Male,African-American,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +52636,59420,53978,PRETRIAL,SCOTT,KYLE,ANTHONY,Male,African-American,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +52636,59420,53978,PRETRIAL,SCOTT,KYLE,ANTHONY,Male,African-American,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52643,59428,53986,Probation,fiddeman,jeronald,NULL,Male,African-American,07/29/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +52643,59428,53986,Probation,fiddeman,jeronald,NULL,Male,African-American,07/29/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +52643,59428,53986,Probation,fiddeman,jeronald,NULL,Male,African-American,07/29/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52017,59415,53265,PRETRIAL,VASQUEZ,CARLOS,ALBERTO,Male,Caucasian,05/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/1/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,Copy,1,0 +52017,59415,53265,PRETRIAL,VASQUEZ,CARLOS,ALBERTO,Male,Caucasian,05/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/1/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,Copy,1,0 +52017,59415,53265,PRETRIAL,VASQUEZ,CARLOS,ALBERTO,Male,Caucasian,05/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +52621,59403,53963,PRETRIAL,Morgan,Maurico,NULL,Male,Other,08/14/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +52621,59403,53963,PRETRIAL,Morgan,Maurico,NULL,Male,Other,08/14/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +52621,59403,53963,PRETRIAL,Morgan,Maurico,NULL,Male,Other,08/14/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52627,59410,53969,PRETRIAL,Mosco,Rose,NULL,Female,Caucasian,08/30/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/1/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +52627,59410,53969,PRETRIAL,Mosco,Rose,NULL,Female,Caucasian,08/30/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/1/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +52627,59410,53969,PRETRIAL,Mosco,Rose,NULL,Female,Caucasian,08/30/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52645,59431,53989,PRETRIAL,torres,arlene,NULL,Female,Hispanic,03/18/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +52645,59431,53989,PRETRIAL,torres,arlene,NULL,Female,Hispanic,03/18/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +52645,59431,53989,PRETRIAL,torres,arlene,NULL,Female,Hispanic,03/18/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +52623,59405,53965,PRETRIAL,Griffin,Zachery,NULL,Male,African-American,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +52623,59405,53965,PRETRIAL,Griffin,Zachery,NULL,Male,African-American,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +52623,59405,53965,PRETRIAL,Griffin,Zachery,NULL,Male,African-American,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52619,59401,53961,PRETRIAL,Walters,Anthony,NULL,Male,Caucasian,11/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +52619,59401,53961,PRETRIAL,Walters,Anthony,NULL,Male,Caucasian,11/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +52619,59401,53961,PRETRIAL,Walters,Anthony,NULL,Male,Caucasian,11/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52637,59422,53980,PRETRIAL,COLLADO-IZQUIERDO,PAOLA,INGRID,Female,Caucasian,11/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +52637,59422,53980,PRETRIAL,COLLADO-IZQUIERDO,PAOLA,INGRID,Female,Caucasian,11/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +52637,59422,53980,PRETRIAL,COLLADO-IZQUIERDO,PAOLA,INGRID,Female,Caucasian,11/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +10749,59396,53957,PRETRIAL,BROWN,KEVIN,LYMAN,Male,Caucasian,10/27/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +10749,59396,53957,PRETRIAL,BROWN,KEVIN,LYMAN,Male,Caucasian,10/27/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +10749,59396,53957,PRETRIAL,BROWN,KEVIN,LYMAN,Male,Caucasian,10/27/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,New,1,0 +52626,59411,53970,Probation,Sibelle,Michael,NULL,Male,Caucasian,04/17/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/1/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +52626,59411,53970,Probation,Sibelle,Michael,NULL,Male,Caucasian,04/17/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/1/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +52626,59411,53970,Probation,Sibelle,Michael,NULL,Male,Caucasian,04/17/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52639,59424,53982,PRETRIAL,ST.LOUIS,BRANDON,NULL,Male,African-American,07/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +52639,59424,53982,PRETRIAL,ST.LOUIS,BRANDON,NULL,Male,African-American,07/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,4,High,8,Risk of Recidivism,0.27,8,High,New,1,0 +52639,59424,53982,PRETRIAL,ST.LOUIS,BRANDON,NULL,Male,African-American,07/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52634,59419,53977,Probation,Campodonico,Christian,NULL,Male,Hispanic,10/04/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/1/13 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +52634,59419,53977,Probation,Campodonico,Christian,NULL,Male,Hispanic,10/04/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/1/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +52634,59419,53977,Probation,Campodonico,Christian,NULL,Male,Hispanic,10/04/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/1/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52618,59398,53959,PRETRIAL,Richardson,Julian,NULL,Male,African-American,01/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +52618,59398,53959,PRETRIAL,Richardson,Julian,NULL,Male,African-American,01/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +52618,59398,53959,PRETRIAL,Richardson,Julian,NULL,Male,African-American,01/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52631,59416,53974,DRRD,Ayoub,Alex,NULL,Male,Arabic,06/11/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/1/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +52631,59416,53974,DRRD,Ayoub,Alex,NULL,Male,Arabic,06/11/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/1/13 0:00,4,High,8,Risk of Recidivism,0.89,10,High,New,1,0 +52631,59416,53974,DRRD,Ayoub,Alex,NULL,Male,Arabic,06/11/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/1/13 0:00,4,High,18,Risk of Failure to Appear,22,4,Low,New,1,0 +27487,59400,47659,PRETRIAL,Philmore,Antonio,M,Male,African-American,12/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,Copy,1,0 +27487,59400,47659,PRETRIAL,Philmore,Antonio,M,Male,African-American,12/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.97,10,High,Copy,1,0 +27487,59400,47659,PRETRIAL,Philmore,Antonio,M,Male,African-American,12/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +52630,59414,53973,Probation,Moreyra,Luz,NULL,Female,Hispanic,06/16/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/1/13 0:00,1,Low,7,Risk of Violence,-4.32,1,Low,New,1,0 +52630,59414,53973,Probation,Moreyra,Luz,NULL,Female,Hispanic,06/16/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/1/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +52630,59414,53973,Probation,Moreyra,Luz,NULL,Female,Hispanic,06/16/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52635,59421,53979,PRETRIAL,Brown,Daniel,Kendrick,Male,Caucasian,12/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/1/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +52635,59421,53979,PRETRIAL,Brown,Daniel,Kendrick,Male,Caucasian,12/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/1/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +52635,59421,53979,PRETRIAL,Brown,Daniel,Kendrick,Male,Caucasian,12/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52642,59427,53985,Probation,JAIKARAN,YOGINDRA,NULL,Male,Other,08/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/1/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +52642,59427,53985,Probation,JAIKARAN,YOGINDRA,NULL,Male,Other,08/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/1/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +52642,59427,53985,Probation,JAIKARAN,YOGINDRA,NULL,Male,Other,08/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +41633,59429,53987,PRETRIAL,Anderson,Tyler,D,Male,Caucasian,02/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +41633,59429,53987,PRETRIAL,Anderson,Tyler,D,Male,Caucasian,02/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +41633,59429,53987,PRETRIAL,Anderson,Tyler,D,Male,Caucasian,02/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52624,59406,53966,PRETRIAL,Bartley,Jason,Anthony,Male,African-American,07/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +52624,59406,53966,PRETRIAL,Bartley,Jason,Anthony,Male,African-American,07/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +52624,59406,53966,PRETRIAL,Bartley,Jason,Anthony,Male,African-American,07/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +28273,59408,51187,PRETRIAL,MONTEIRO,JOSEPH,A,Male,Hispanic,04/09/52,17,All Scales,Intake,English,Conditional Release,Probation,Married,3/1/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +28273,59408,51187,PRETRIAL,MONTEIRO,JOSEPH,A,Male,Hispanic,04/09/52,17,All Scales,Intake,English,Conditional Release,Probation,Married,3/1/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +28273,59408,51187,PRETRIAL,MONTEIRO,JOSEPH,A,Male,Hispanic,04/09/52,17,All Scales,Intake,English,Conditional Release,Probation,Married,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52625,59409,53968,PRETRIAL,Junck,Daryl,NULL,Male,Caucasian,05/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/1/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +52625,59409,53968,PRETRIAL,Junck,Daryl,NULL,Male,Caucasian,05/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/1/13 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +52625,59409,53968,PRETRIAL,Junck,Daryl,NULL,Male,Caucasian,05/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52644,59430,53988,PRETRIAL,Edwards,Bernard,NULL,Male,African-American,12/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/1/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +52644,59430,53988,PRETRIAL,Edwards,Bernard,NULL,Male,African-American,12/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/1/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +52644,59430,53988,PRETRIAL,Edwards,Bernard,NULL,Male,African-American,12/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +2361,59395,53956,Probation,Morales,Richard,Edward,Male,Hispanic,10/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +2361,59395,53956,Probation,Morales,Richard,Edward,Male,Hispanic,10/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +2361,59395,53956,Probation,Morales,Richard,Edward,Male,Hispanic,10/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52617,59397,53958,PRETRIAL,Smith,Romaine,NULL,Male,Other,01/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.22,8,High,New,1,0 +52617,59397,53958,PRETRIAL,Smith,Romaine,NULL,Male,Other,01/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +52617,59397,53958,PRETRIAL,Smith,Romaine,NULL,Male,Other,01/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52622,59404,53964,PRETRIAL,Rivera,Kyle,NULL,Male,Caucasian,12/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +52622,59404,53964,PRETRIAL,Rivera,Kyle,NULL,Male,Caucasian,12/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +52622,59404,53964,PRETRIAL,Rivera,Kyle,NULL,Male,Caucasian,12/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52633,59418,53976,PRETRIAL,mason,douglas,NULL,Male,Caucasian,10/05/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +52633,59418,53976,PRETRIAL,mason,douglas,NULL,Male,Caucasian,10/05/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,8,Risk of Recidivism,-2.79,1,Low,New,1,0 +52633,59418,53976,PRETRIAL,mason,douglas,NULL,Male,Caucasian,10/05/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52640,59425,53983,PRETRIAL,CHASE,BENJAMIN,NULL,Male,Caucasian,06/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +52640,59425,53983,PRETRIAL,CHASE,BENJAMIN,NULL,Male,Caucasian,06/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +52640,59425,53983,PRETRIAL,CHASE,BENJAMIN,NULL,Male,Caucasian,06/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52646,59432,53990,PRETRIAL,Wilson,Brandon,NULL,Male,African-American,06/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +52646,59432,53990,PRETRIAL,Wilson,Brandon,NULL,Male,African-American,06/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +52646,59432,53990,PRETRIAL,Wilson,Brandon,NULL,Male,African-American,06/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +7258,59439,53996,PRETRIAL,BOYD,LARRY,NULL,Male,Caucasian,04/08/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +7258,59439,53996,PRETRIAL,BOYD,LARRY,NULL,Male,Caucasian,04/08/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +7258,59439,53996,PRETRIAL,BOYD,LARRY,NULL,Male,Caucasian,04/08/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52656,59453,54009,PRETRIAL,black,michael,NULL,Male,African-American,09/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +52656,59453,54009,PRETRIAL,black,michael,NULL,Male,African-American,09/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,4,High,8,Risk of Recidivism,0.92,10,High,New,1,0 +52656,59453,54009,PRETRIAL,black,michael,NULL,Male,African-American,09/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52655,59446,54003,PRETRIAL,Dearmas,Adelmis,NULL,Male,Caucasian,06/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +52655,59446,54003,PRETRIAL,Dearmas,Adelmis,NULL,Male,Caucasian,06/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +52655,59446,54003,PRETRIAL,Dearmas,Adelmis,NULL,Male,Caucasian,06/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52657,59455,54010,PRETRIAL,jean,jeffery,NULL,Male,African-American,05/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,New,1,0 +52657,59455,54010,PRETRIAL,jean,jeffery,NULL,Male,African-American,05/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +52657,59455,54010,PRETRIAL,jean,jeffery,NULL,Male,African-American,05/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +45569,59434,53992,PRETRIAL,Williams,Terrance,NULL,Male,African-American,11/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +45569,59434,53992,PRETRIAL,Williams,Terrance,NULL,Male,African-American,11/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +45569,59434,53992,PRETRIAL,Williams,Terrance,NULL,Male,African-American,11/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52651,59442,53999,PRETRIAL,Boothe,Hasani,NULL,Male,Other,12/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +52651,59442,53999,PRETRIAL,Boothe,Hasani,NULL,Male,Other,12/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +52651,59442,53999,PRETRIAL,Boothe,Hasani,NULL,Male,Other,12/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51321,59435,53993,PRETRIAL,Fairclough,Tupac,NULL,Male,African-American,12/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +51321,59435,53993,PRETRIAL,Fairclough,Tupac,NULL,Male,African-American,12/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +51321,59435,53993,PRETRIAL,Fairclough,Tupac,NULL,Male,African-American,12/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +17682,59437,53995,PRETRIAL,WRIGHT,KENNETH,WARREN,Male,African-American,01/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +17682,59437,53995,PRETRIAL,WRIGHT,KENNETH,WARREN,Male,African-American,01/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +17682,59437,53995,PRETRIAL,WRIGHT,KENNETH,WARREN,Male,African-American,01/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52654,59445,54002,PRETRIAL,Bain,Gilton,NULL,Male,African-American,09/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +52654,59445,54002,PRETRIAL,Bain,Gilton,NULL,Male,African-American,09/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +52654,59445,54002,PRETRIAL,Bain,Gilton,NULL,Male,African-American,09/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52652,59443,54000,PRETRIAL,Gutierrez,Eleasar,NULL,Male,Hispanic,10/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +52652,59443,54000,PRETRIAL,Gutierrez,Eleasar,NULL,Male,Hispanic,10/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +52652,59443,54000,PRETRIAL,Gutierrez,Eleasar,NULL,Male,Hispanic,10/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +3656,59447,3373,PRETRIAL,Ferdinand,Thony,NULL,Male,African-American,05/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,Copy,1,0 +3656,59447,3373,PRETRIAL,Ferdinand,Thony,NULL,Male,African-American,05/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,Copy,1,0 +3656,59447,3373,PRETRIAL,Ferdinand,Thony,NULL,Male,African-American,05/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +16099,59452,54008,PRETRIAL,pryor,joseph,NULL,Male,African-American,09/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +16099,59452,54008,PRETRIAL,pryor,joseph,NULL,Male,African-American,09/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +16099,59452,54008,PRETRIAL,pryor,joseph,NULL,Male,African-American,09/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52647,59433,53991,PRETRIAL,Rabold,Christopher,Michael,Male,Caucasian,11/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +52647,59433,53991,PRETRIAL,Rabold,Christopher,Michael,Male,Caucasian,11/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +52647,59433,53991,PRETRIAL,Rabold,Christopher,Michael,Male,Caucasian,11/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +9305,59438,22462,PRETRIAL,brown,theophilus,NULL,Male,African-American,12/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,4,High,7,Risk of Violence,-1.04,8,High,Copy,1,0 +9305,59438,22462,PRETRIAL,brown,theophilus,NULL,Male,African-American,12/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,4,High,8,Risk of Recidivism,0.64,10,High,Copy,1,0 +9305,59438,22462,PRETRIAL,brown,theophilus,NULL,Male,African-American,12/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,4,High,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +52649,59440,53997,PRETRIAL,Reed,Ernest,NULL,Male,Caucasian,02/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/2/13 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +52649,59440,53997,PRETRIAL,Reed,Ernest,NULL,Male,Caucasian,02/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +52649,59440,53997,PRETRIAL,Reed,Ernest,NULL,Male,Caucasian,02/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/2/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +52650,59441,53998,PRETRIAL,OLaechea,Peter,Anthony,Male,Caucasian,09/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +52650,59441,53998,PRETRIAL,OLaechea,Peter,Anthony,Male,Caucasian,09/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +52650,59441,53998,PRETRIAL,OLaechea,Peter,Anthony,Male,Caucasian,09/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52653,59444,54001,PRETRIAL,Lewandowski,Anthony,NULL,Male,Caucasian,05/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +52653,59444,54001,PRETRIAL,Lewandowski,Anthony,NULL,Male,Caucasian,05/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +52653,59444,54001,PRETRIAL,Lewandowski,Anthony,NULL,Male,Caucasian,05/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52648,59436,53994,PRETRIAL,Pierre,Archange,NULL,Male,African-American,08/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +52648,59436,53994,PRETRIAL,Pierre,Archange,NULL,Male,African-American,08/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +52648,59436,53994,PRETRIAL,Pierre,Archange,NULL,Male,African-American,08/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52662,59462,54018,PRETRIAL,phillips,bernard,NULL,Male,African-American,07/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +52662,59462,54018,PRETRIAL,phillips,bernard,NULL,Male,African-American,07/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +52662,59462,54018,PRETRIAL,phillips,bernard,NULL,Male,African-American,07/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52701,59509,54063,PRETRIAL,Baquedano-Rivera,Ronald,NULL,Male,Hispanic,12/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +52701,59509,54063,PRETRIAL,Baquedano-Rivera,Ronald,NULL,Male,Hispanic,12/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +52701,59509,54063,PRETRIAL,Baquedano-Rivera,Ronald,NULL,Male,Hispanic,12/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52678,59483,54038,Probation,PADRON,LAZARO,NELSON,Male,Hispanic,07/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +52678,59483,54038,Probation,PADRON,LAZARO,NELSON,Male,Hispanic,07/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +52678,59483,54038,Probation,PADRON,LAZARO,NELSON,Male,Hispanic,07/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +35899,59480,54035,PRETRIAL,Turner,Malcolm,J,Male,African-American,08/05/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +35899,59480,54035,PRETRIAL,Turner,Malcolm,J,Male,African-American,08/05/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,4,Low,New,1,0 +35899,59480,54035,PRETRIAL,Turner,Malcolm,J,Male,African-American,08/05/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,2,Medium,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +52684,59491,54046,Probation,DRUCKER,CHRISTOPHER,M,Male,Caucasian,05/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +52684,59491,54046,Probation,DRUCKER,CHRISTOPHER,M,Male,Caucasian,05/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +52684,59491,54046,Probation,DRUCKER,CHRISTOPHER,M,Male,Caucasian,05/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52669,59470,54025,PRETRIAL,Kemp,Jennifer,NULL,Female,Caucasian,01/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.6,2,Low,New,1,0 +52669,59470,54025,PRETRIAL,Kemp,Jennifer,NULL,Female,Caucasian,01/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +52669,59470,54025,PRETRIAL,Kemp,Jennifer,NULL,Female,Caucasian,01/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,New,1,0 +52682,59488,54043,PRETRIAL,RODNEY,MELEK,NULL,Male,African-American,01/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +52682,59488,54043,PRETRIAL,RODNEY,MELEK,NULL,Male,African-American,01/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +52682,59488,54043,PRETRIAL,RODNEY,MELEK,NULL,Male,African-American,01/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52694,59501,54055,PRETRIAL,PRADERA,MAURICIO,NULL,Male,Hispanic,04/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +52694,59501,54055,PRETRIAL,PRADERA,MAURICIO,NULL,Male,Hispanic,04/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +52694,59501,54055,PRETRIAL,PRADERA,MAURICIO,NULL,Male,Hispanic,04/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52681,59485,54040,Probation,bartholomew,michael,NULL,Male,Caucasian,10/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +52681,59485,54040,Probation,bartholomew,michael,NULL,Male,Caucasian,10/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.32,10,High,New,1,0 +52681,59485,54040,Probation,bartholomew,michael,NULL,Male,Caucasian,10/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52680,59486,54041,Probation,grzyb,marcin,NULL,Male,Caucasian,12/07/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/4/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +52680,59486,54041,Probation,grzyb,marcin,NULL,Male,Caucasian,12/07/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/4/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +52680,59486,54041,Probation,grzyb,marcin,NULL,Male,Caucasian,12/07/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52664,59464,54020,PRETRIAL,Harris,Jerriann,NULL,Female,Caucasian,03/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/13 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +52664,59464,54020,PRETRIAL,Harris,Jerriann,NULL,Female,Caucasian,03/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +52664,59464,54020,PRETRIAL,Harris,Jerriann,NULL,Female,Caucasian,03/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +52699,59507,54061,PRETRIAL,Bear,Charles,NULL,Male,Caucasian,09/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +52699,59507,54061,PRETRIAL,Bear,Charles,NULL,Male,Caucasian,09/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +52699,59507,54061,PRETRIAL,Bear,Charles,NULL,Male,Caucasian,09/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52686,59493,54048,PRETRIAL,MUSTAFA,MELTON,NULL,Male,African-American,01/17/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/4/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +52686,59493,54048,PRETRIAL,MUSTAFA,MELTON,NULL,Male,African-American,01/17/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/4/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +52686,59493,54048,PRETRIAL,MUSTAFA,MELTON,NULL,Male,African-American,01/17/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52665,59465,54021,PRETRIAL,Montes,Benjamin,NULL,Male,Hispanic,07/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +52665,59465,54021,PRETRIAL,Montes,Benjamin,NULL,Male,Hispanic,07/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +52665,59465,54021,PRETRIAL,Montes,Benjamin,NULL,Male,Hispanic,07/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52670,59472,54027,PRETRIAL,Joseph,Donald,NULL,Male,African-American,05/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +52670,59472,54027,PRETRIAL,Joseph,Donald,NULL,Male,African-American,05/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +52670,59472,54027,PRETRIAL,Joseph,Donald,NULL,Male,African-American,05/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52691,59499,54053,Probation,SINGH,RAVI,NULL,Male,African-American,10/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +52691,59499,54053,Probation,SINGH,RAVI,NULL,Male,African-American,10/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +52691,59499,54053,Probation,SINGH,RAVI,NULL,Male,African-American,10/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52698,59506,54060,Probation,Mauricette,Jackson,NULL,Male,African-American,09/26/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +52698,59506,54060,Probation,Mauricette,Jackson,NULL,Male,African-American,09/26/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +52698,59506,54060,Probation,Mauricette,Jackson,NULL,Male,African-American,09/26/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52702,59510,54064,PRETRIAL,CAPLE,SUSAN,NULL,Female,Caucasian,04/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +52702,59510,54064,PRETRIAL,CAPLE,SUSAN,NULL,Female,Caucasian,04/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +52702,59510,54064,PRETRIAL,CAPLE,SUSAN,NULL,Female,Caucasian,04/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +27796,59512,54066,PRETRIAL,Mitchell,Steve,NULL,Male,African-American,11/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +27796,59512,54066,PRETRIAL,Mitchell,Steve,NULL,Male,African-American,11/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +27796,59512,54066,PRETRIAL,Mitchell,Steve,NULL,Male,African-American,11/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52668,59468,54024,PRETRIAL,LOUIS,COURTNEY,NULL,Male,African-American,05/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +52668,59468,54024,PRETRIAL,LOUIS,COURTNEY,NULL,Male,African-American,05/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +52668,59468,54024,PRETRIAL,LOUIS,COURTNEY,NULL,Male,African-American,05/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52695,59503,54057,PRETRIAL,Lewis,Van,NULL,Male,African-American,05/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +52695,59503,54057,PRETRIAL,Lewis,Van,NULL,Male,African-American,05/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +52695,59503,54057,PRETRIAL,Lewis,Van,NULL,Male,African-American,05/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52672,59475,54030,PRETRIAL,Williams,Pierre,Enrico,Male,African-American,09/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +52672,59475,54030,PRETRIAL,Williams,Pierre,Enrico,Male,African-American,09/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +52672,59475,54030,PRETRIAL,Williams,Pierre,Enrico,Male,African-American,09/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52671,59473,54028,PRETRIAL,kOYA,SHAMEEL,FRANCIS,Male,Caucasian,10/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +52671,59473,54028,PRETRIAL,kOYA,SHAMEEL,FRANCIS,Male,Caucasian,10/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +52671,59473,54028,PRETRIAL,kOYA,SHAMEEL,FRANCIS,Male,Caucasian,10/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52690,59498,54052,Probation,payne,derek,NULL,Male,African-American,01/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +52690,59498,54052,Probation,payne,derek,NULL,Male,African-American,01/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +52690,59498,54052,Probation,payne,derek,NULL,Male,African-American,01/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52674,59477,54032,PRETRIAL,Canovaca,Richard,NULL,Male,Caucasian,01/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +52674,59477,54032,PRETRIAL,Canovaca,Richard,NULL,Male,Caucasian,01/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +52674,59477,54032,PRETRIAL,Canovaca,Richard,NULL,Male,Caucasian,01/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52688,59494,54049,PRETRIAL,balta,erin,lori,Female,Caucasian,02/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/4/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +52688,59494,54049,PRETRIAL,balta,erin,lori,Female,Caucasian,02/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/4/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +52688,59494,54049,PRETRIAL,balta,erin,lori,Female,Caucasian,02/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +1393,59479,54034,PRETRIAL,WALSH,JOHN,J,Male,Caucasian,02/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +1393,59479,54034,PRETRIAL,WALSH,JOHN,J,Male,Caucasian,02/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +1393,59479,54034,PRETRIAL,WALSH,JOHN,J,Male,Caucasian,02/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52685,59492,54047,PRETRIAL,wilson,christopher,allen,Male,African-American,09/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +52685,59492,54047,PRETRIAL,wilson,christopher,allen,Male,African-American,09/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +52685,59492,54047,PRETRIAL,wilson,christopher,allen,Male,African-American,09/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52679,59484,54039,PRETRIAL,TURNER,DAVID,NULL,Male,Caucasian,08/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +52679,59484,54039,PRETRIAL,TURNER,DAVID,NULL,Male,Caucasian,08/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +52679,59484,54039,PRETRIAL,TURNER,DAVID,NULL,Male,Caucasian,08/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +29112,59487,54042,PRETRIAL,GUERRERO,PAUL,NULL,Male,Caucasian,01/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +29112,59487,54042,PRETRIAL,GUERRERO,PAUL,NULL,Male,Caucasian,01/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +29112,59487,54042,PRETRIAL,GUERRERO,PAUL,NULL,Male,Caucasian,01/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52666,59466,54022,PRETRIAL,THROPES,SHAWN,L,Male,African-American,05/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +52666,59466,54022,PRETRIAL,THROPES,SHAWN,L,Male,African-American,05/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +52666,59466,54022,PRETRIAL,THROPES,SHAWN,L,Male,African-American,05/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52697,59505,54059,PRETRIAL,Santoro-Davis,Lisa,NULL,Female,Caucasian,03/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.37,3,Low,New,1,0 +52697,59505,54059,PRETRIAL,Santoro-Davis,Lisa,NULL,Female,Caucasian,03/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,8,High,New,1,0 +52697,59505,54059,PRETRIAL,Santoro-Davis,Lisa,NULL,Female,Caucasian,03/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,New,1,0 +52467,59471,54026,PRETRIAL,Richardson,Mercedes,NULL,Male,African-American,03/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +52467,59471,54026,PRETRIAL,Richardson,Mercedes,NULL,Male,African-American,03/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +52467,59471,54026,PRETRIAL,Richardson,Mercedes,NULL,Male,African-American,03/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52663,59463,54019,PRETRIAL,Hodges,Ahmaad,NULL,Male,African-American,06/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +52663,59463,54019,PRETRIAL,Hodges,Ahmaad,NULL,Male,African-American,06/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +52663,59463,54019,PRETRIAL,Hodges,Ahmaad,NULL,Male,African-American,06/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52700,59508,54062,PRETRIAL,Doyle,Joshua,NULL,Male,Caucasian,11/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +52700,59508,54062,PRETRIAL,Doyle,Joshua,NULL,Male,Caucasian,11/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +52700,59508,54062,PRETRIAL,Doyle,Joshua,NULL,Male,Caucasian,11/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +26857,59469,25961,PRETRIAL,Warren,Kenneth,NULL,Female,Caucasian,09/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,Copy,1,0 +26857,59469,25961,PRETRIAL,Warren,Kenneth,NULL,Female,Caucasian,09/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,Copy,1,0 +26857,59469,25961,PRETRIAL,Warren,Kenneth,NULL,Female,Caucasian,09/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,30,9,High,Copy,1,0 +52693,59502,54056,PRETRIAL,Raidi,Roy,Mansour,Male,Caucasian,04/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/4/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +52693,59502,54056,PRETRIAL,Raidi,Roy,Mansour,Male,Caucasian,04/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/4/13 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +52693,59502,54056,PRETRIAL,Raidi,Roy,Mansour,Male,Caucasian,04/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +24408,59523,54077,Probation,Lamothe,Freud,NULL,Male,African-American,05/11/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +24408,59523,54077,Probation,Lamothe,Freud,NULL,Male,African-American,05/11/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +24408,59523,54077,Probation,Lamothe,Freud,NULL,Male,African-American,05/11/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +45465,59511,54065,PRETRIAL,Augustinparks,Christopher,NULL,Male,Other,07/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +45465,59511,54065,PRETRIAL,Augustinparks,Christopher,NULL,Male,Other,07/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +45465,59511,54065,PRETRIAL,Augustinparks,Christopher,NULL,Male,Other,07/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +44459,59481,54036,PRETRIAL,Mangiardi,Paul,M,Male,Caucasian,08/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +44459,59481,54036,PRETRIAL,Mangiardi,Paul,M,Male,Caucasian,08/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +44459,59481,54036,PRETRIAL,Mangiardi,Paul,M,Male,Caucasian,08/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +52673,59476,54031,PRETRIAL,Mora,Michael,Steven,Male,Hispanic,01/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +52673,59476,54031,PRETRIAL,Mora,Michael,Steven,Male,Hispanic,01/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +52673,59476,54031,PRETRIAL,Mora,Michael,Steven,Male,Hispanic,01/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52687,59495,54050,PRETRIAL,Adelmann,Kristen,NULL,Female,Caucasian,03/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +52687,59495,54050,PRETRIAL,Adelmann,Kristen,NULL,Female,Caucasian,03/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +52687,59495,54050,PRETRIAL,Adelmann,Kristen,NULL,Female,Caucasian,03/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +52667,59467,54023,PRETRIAL,MELTON,CEPHUS,NULL,Male,African-American,11/12/45,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,7,Risk of Violence,-4.53,1,Low,New,1,0 +52667,59467,54023,PRETRIAL,MELTON,CEPHUS,NULL,Male,African-American,11/12/45,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,8,Risk of Recidivism,-2.94,1,Low,New,1,0 +52667,59467,54023,PRETRIAL,MELTON,CEPHUS,NULL,Male,African-American,11/12/45,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +1680,59474,54029,PRETRIAL,Palmer,Storm,Petronilla,Female,African-American,01/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +1680,59474,54029,PRETRIAL,Palmer,Storm,Petronilla,Female,African-American,01/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +1680,59474,54029,PRETRIAL,Palmer,Storm,Petronilla,Female,African-American,01/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +8654,59497,45626,Probation,Weather,Jimmy,NULL,Male,African-American,06/03/81,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +8654,59497,45626,Probation,Weather,Jimmy,NULL,Male,African-American,06/03/81,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +8654,59497,45626,Probation,Weather,Jimmy,NULL,Male,African-American,06/03/81,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52696,59504,54058,PRETRIAL,JONES,ANDREW,DARNELL,Male,African-American,10/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,4,High,7,Risk of Violence,-0.85,9,High,New,1,0 +52696,59504,54058,PRETRIAL,JONES,ANDREW,DARNELL,Male,African-American,10/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,4,High,8,Risk of Recidivism,0.26,8,High,New,1,0 +52696,59504,54058,PRETRIAL,JONES,ANDREW,DARNELL,Male,African-American,10/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +52706,59518,54072,PRETRIAL,HYNES,CEDRIC,LEE,Male,African-American,05/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +52706,59518,54072,PRETRIAL,HYNES,CEDRIC,LEE,Male,African-American,05/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +52706,59518,54072,PRETRIAL,HYNES,CEDRIC,LEE,Male,African-American,05/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +41691,59532,54085,PRETRIAL,Iezza,Scott,NULL,Male,Caucasian,07/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +41691,59532,54085,PRETRIAL,Iezza,Scott,NULL,Male,Caucasian,07/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +41691,59532,54085,PRETRIAL,Iezza,Scott,NULL,Male,Caucasian,07/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +52720,59539,54091,PRETRIAL,Sylvester,Crystal,NULL,Female,African-American,02/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +52720,59539,54091,PRETRIAL,Sylvester,Crystal,NULL,Female,African-American,02/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +52720,59539,54091,PRETRIAL,Sylvester,Crystal,NULL,Female,African-American,02/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52725,59546,54098,PRETRIAL,Farrow,Marion,NULL,Male,African-American,11/05/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/5/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +52725,59546,54098,PRETRIAL,Farrow,Marion,NULL,Male,African-American,11/05/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/5/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +52725,59546,54098,PRETRIAL,Farrow,Marion,NULL,Male,African-American,11/05/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52722,59541,54093,Probation,GARGUILO,CHRISTIAN,NULL,Male,Hispanic,11/03/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +52722,59541,54093,Probation,GARGUILO,CHRISTIAN,NULL,Male,Hispanic,11/03/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +52722,59541,54093,Probation,GARGUILO,CHRISTIAN,NULL,Male,Hispanic,11/03/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52704,59516,54070,PRETRIAL,Grimmer,Steven,NULL,Male,Caucasian,12/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +52704,59516,54070,PRETRIAL,Grimmer,Steven,NULL,Male,Caucasian,12/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +52704,59516,54070,PRETRIAL,Grimmer,Steven,NULL,Male,Caucasian,12/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +45929,59520,54074,PRETRIAL,Laundy,Hancy,NULL,Male,African-American,07/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +45929,59520,54074,PRETRIAL,Laundy,Hancy,NULL,Male,African-American,07/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +45929,59520,54074,PRETRIAL,Laundy,Hancy,NULL,Male,African-American,07/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +50365,59537,51373,PRETRIAL,Otolo,Jimmy,NULL,Female,African-American,04/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,Copy,1,0 +50365,59537,51373,PRETRIAL,Otolo,Jimmy,NULL,Female,African-American,04/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,Copy,1,0 +50365,59537,51373,PRETRIAL,Otolo,Jimmy,NULL,Female,African-American,04/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +52723,59542,54094,DRRD,Todd,Kevon,NULL,Male,African-American,07/14/90,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,3/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.03,8,High,New,1,0 +52723,59542,54094,DRRD,Todd,Kevon,NULL,Male,African-American,07/14/90,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,3/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +52723,59542,54094,DRRD,Todd,Kevon,NULL,Male,African-American,07/14/90,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,3/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +52712,59529,54082,PRETRIAL,Mathis,John,NULL,Male,African-American,08/31/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +52712,59529,54082,PRETRIAL,Mathis,John,NULL,Male,African-American,08/31/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +52712,59529,54082,PRETRIAL,Mathis,John,NULL,Male,African-American,08/31/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52707,59521,54075,PRETRIAL,SOUARIN,GERVENS,LEE,Male,African-American,12/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +52707,59521,54075,PRETRIAL,SOUARIN,GERVENS,LEE,Male,African-American,12/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.75,10,High,New,1,0 +52707,59521,54075,PRETRIAL,SOUARIN,GERVENS,LEE,Male,African-American,12/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52718,59536,54089,PRETRIAL,Bushay,Norman,NULL,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +52718,59536,54089,PRETRIAL,Bushay,Norman,NULL,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +52718,59536,54089,PRETRIAL,Bushay,Norman,NULL,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52730,59550,54102,Probation,KIRWAN,CHRISTOPHER,L,Male,Caucasian,04/04/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +52730,59550,54102,Probation,KIRWAN,CHRISTOPHER,L,Male,Caucasian,04/04/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +52730,59550,54102,Probation,KIRWAN,CHRISTOPHER,L,Male,Caucasian,04/04/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50365,56506,51373,PRETRIAL,Otolo,Jimmy,NULL,Female,African-American,04/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,New,1,0 +50365,56506,51373,PRETRIAL,Otolo,Jimmy,NULL,Female,African-American,04/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +50365,56506,51373,PRETRIAL,Otolo,Jimmy,NULL,Female,African-American,04/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52716,59534,54087,PRETRIAL,ROJAS,EDGARD,NULL,Male,Caucasian,03/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +52716,59534,54087,PRETRIAL,ROJAS,EDGARD,NULL,Male,Caucasian,03/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +52716,59534,54087,PRETRIAL,ROJAS,EDGARD,NULL,Male,Caucasian,03/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52726,59547,54099,Probation,EVANS,DOMINICK,NULL,Male,Caucasian,02/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +52726,59547,54099,Probation,EVANS,DOMINICK,NULL,Male,Caucasian,02/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,4,High,8,Risk of Recidivism,0.32,9,High,New,1,0 +52726,59547,54099,Probation,EVANS,DOMINICK,NULL,Male,Caucasian,02/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +31916,59513,54067,PRETRIAL,Whitfield,Brandon,Kash,Male,African-American,07/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +31916,59513,54067,PRETRIAL,Whitfield,Brandon,Kash,Male,African-American,07/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +31916,59513,54067,PRETRIAL,Whitfield,Brandon,Kash,Male,African-American,07/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51926,59526,53174,PRETRIAL,Brown,Keith,NULL,Male,African-American,03/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,Copy,1,0 +51926,59526,53174,PRETRIAL,Brown,Keith,NULL,Male,African-American,03/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,Copy,1,0 +51926,59526,53174,PRETRIAL,Brown,Keith,NULL,Male,African-American,03/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +52711,59528,54081,PRETRIAL,HUTCHINS,TERRY,NULL,Male,Caucasian,12/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +52711,59528,54081,PRETRIAL,HUTCHINS,TERRY,NULL,Male,Caucasian,12/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +52711,59528,54081,PRETRIAL,HUTCHINS,TERRY,NULL,Male,Caucasian,12/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +40964,59545,54097,PRETRIAL,Amayamolina,Jose,Antonio,Male,Hispanic,05/08/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +40964,59545,54097,PRETRIAL,Amayamolina,Jose,Antonio,Male,Hispanic,05/08/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +40964,59545,54097,PRETRIAL,Amayamolina,Jose,Antonio,Male,Hispanic,05/08/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52705,59515,54069,PRETRIAL,Livingston,Robert,McDonald,Male,Other,08/22/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +52705,59515,54069,PRETRIAL,Livingston,Robert,McDonald,Male,Other,08/22/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +52705,59515,54069,PRETRIAL,Livingston,Robert,McDonald,Male,Other,08/22/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52708,59524,54078,Probation,JONES,TIERRA,NULL,Female,African-American,01/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +52708,59524,54078,Probation,JONES,TIERRA,NULL,Female,African-American,01/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +52708,59524,54078,Probation,JONES,TIERRA,NULL,Female,African-American,01/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52729,59549,54101,Probation,alford,danny,NULL,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.31,7,Medium,New,1,0 +52729,59549,54101,Probation,alford,danny,NULL,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +52729,59549,54101,Probation,alford,danny,NULL,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +50385,59519,54073,PRETRIAL,Arias,Justo,NULL,Male,Hispanic,12/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +50385,59519,54073,PRETRIAL,Arias,Justo,NULL,Male,Hispanic,12/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +50385,59519,54073,PRETRIAL,Arias,Justo,NULL,Male,Hispanic,12/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +29615,59531,54084,Probation,truax,bryan,NULL,Male,Caucasian,05/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +29615,59531,54084,Probation,truax,bryan,NULL,Male,Caucasian,05/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +29615,59531,54084,Probation,truax,bryan,NULL,Male,Caucasian,05/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52715,59533,54086,PRETRIAL,Slaving,Logan,NULL,Male,Caucasian,08/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +52715,59533,54086,PRETRIAL,Slaving,Logan,NULL,Male,Caucasian,08/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +52715,59533,54086,PRETRIAL,Slaving,Logan,NULL,Male,Caucasian,08/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52721,59540,54092,Probation,TWIGGS,OLIVIA,NULL,Male,African-American,11/17/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +52721,59540,54092,Probation,TWIGGS,OLIVIA,NULL,Male,African-American,11/17/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +52721,59540,54092,Probation,TWIGGS,OLIVIA,NULL,Male,African-American,11/17/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52703,59514,54068,PRETRIAL,Salamone,Zackary,Joseph,Male,Caucasian,05/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +52703,59514,54068,PRETRIAL,Salamone,Zackary,Joseph,Male,Caucasian,05/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +52703,59514,54068,PRETRIAL,Salamone,Zackary,Joseph,Male,Caucasian,05/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52717,59535,54088,PRETRIAL,LEWIS,GYLIER,NULL,Male,African-American,05/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +52717,59535,54088,PRETRIAL,LEWIS,GYLIER,NULL,Male,African-American,05/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +52717,59535,54088,PRETRIAL,LEWIS,GYLIER,NULL,Male,African-American,05/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52719,59538,54090,PRETRIAL,HAYNE,OBRIAN,NULL,Male,African-American,01/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +52719,59538,54090,PRETRIAL,HAYNE,OBRIAN,NULL,Male,African-American,01/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +52719,59538,54090,PRETRIAL,HAYNE,OBRIAN,NULL,Male,African-American,01/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +30858,59551,54103,PRETRIAL,tiger,charlie,NULL,Male,Native American,12/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/5/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +30858,59551,54103,PRETRIAL,tiger,charlie,NULL,Male,Native American,12/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/5/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +30858,59551,54103,PRETRIAL,tiger,charlie,NULL,Male,Native American,12/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52728,59548,54100,Probation,Kirksey,Minnie,NULL,Female,African-American,09/29/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +52728,59548,54100,Probation,Kirksey,Minnie,NULL,Female,African-American,09/29/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +52728,59548,54100,Probation,Kirksey,Minnie,NULL,Female,African-American,09/29/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52415,59517,54071,PRETRIAL,Hammonds,Michael,NULL,Male,African-American,06/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +52415,59517,54071,PRETRIAL,Hammonds,Michael,NULL,Male,African-American,06/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +52415,59517,54071,PRETRIAL,Hammonds,Michael,NULL,Male,African-American,06/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50735,59522,54076,PRETRIAL,Paulk,Clarence,NULL,Male,African-American,07/23/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +50735,59522,54076,PRETRIAL,Paulk,Clarence,NULL,Male,African-American,07/23/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +50735,59522,54076,PRETRIAL,Paulk,Clarence,NULL,Male,African-American,07/23/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +52724,59543,54095,PRETRIAL,Tillman,Richard,NULL,Male,African-American,10/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +52724,59543,54095,PRETRIAL,Tillman,Richard,NULL,Male,African-American,10/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +52724,59543,54095,PRETRIAL,Tillman,Richard,NULL,Male,African-American,10/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52753,59577,54128,Probation,Carpio,Albin,NULL,Male,Hispanic,10/29/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/6/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +52753,59577,54128,Probation,Carpio,Albin,NULL,Male,Hispanic,10/29/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +52753,59577,54128,Probation,Carpio,Albin,NULL,Male,Hispanic,10/29/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52734,59556,54108,Probation,Deabenderfer,ANdrew,Tyler,Male,Caucasian,08/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +52734,59556,54108,Probation,Deabenderfer,ANdrew,Tyler,Male,Caucasian,08/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +52734,59556,54108,Probation,Deabenderfer,ANdrew,Tyler,Male,Caucasian,08/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52762,59590,54140,PRETRIAL,weal,marquita,NULL,Female,African-American,12/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +52762,59590,54140,PRETRIAL,weal,marquita,NULL,Female,African-American,12/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +52762,59590,54140,PRETRIAL,weal,marquita,NULL,Female,African-American,12/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52737,59559,54111,PRETRIAL,Hutchins,Tevaughn,Vincent,Male,African-American,03/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +52737,59559,54111,PRETRIAL,Hutchins,Tevaughn,Vincent,Male,African-American,03/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +52737,59559,54111,PRETRIAL,Hutchins,Tevaughn,Vincent,Male,African-American,03/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52766,59598,54148,Probation,Maldonadoadozayas,Luis,NULL,Male,Hispanic,03/29/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +52766,59598,54148,Probation,Maldonadoadozayas,Luis,NULL,Male,Hispanic,03/29/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +52766,59598,54148,Probation,Maldonadoadozayas,Luis,NULL,Male,Hispanic,03/29/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52742,59564,54116,PRETRIAL,Isaac,Alquan,NULL,Male,African-American,07/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +52742,59564,54116,PRETRIAL,Isaac,Alquan,NULL,Male,African-American,07/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +52742,59564,54116,PRETRIAL,Isaac,Alquan,NULL,Male,African-American,07/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52750,59572,54124,PRETRIAL,OLAZABAL,CARBALLO,NULL,Male,Hispanic,02/23/84,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +52750,59572,54124,PRETRIAL,OLAZABAL,CARBALLO,NULL,Male,Hispanic,02/23/84,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +52750,59572,54124,PRETRIAL,OLAZABAL,CARBALLO,NULL,Male,Hispanic,02/23/84,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52763,59593,54143,PRETRIAL,william,king,NULL,Male,Caucasian,08/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +52763,59593,54143,PRETRIAL,william,king,NULL,Male,Caucasian,08/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +52763,59593,54143,PRETRIAL,william,king,NULL,Male,Caucasian,08/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52739,59561,54113,PRETRIAL,VAVAL,BRADLEY,JORDAN,Male,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +52739,59561,54113,PRETRIAL,VAVAL,BRADLEY,JORDAN,Male,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +52739,59561,54113,PRETRIAL,VAVAL,BRADLEY,JORDAN,Male,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52752,59575,54127,DRRD,Kearny,Bernard,James,Male,Caucasian,12/04/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +52752,59575,54127,DRRD,Kearny,Bernard,James,Male,Caucasian,12/04/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1,2,Low,New,1,0 +52752,59575,54127,DRRD,Kearny,Bernard,James,Male,Caucasian,12/04/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,23,4,Low,New,1,0 +52757,59582,54132,PRETRIAL,Jacob,Jake,NULL,Male,Caucasian,05/15/38,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/6/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +52757,59582,54132,PRETRIAL,Jacob,Jake,NULL,Male,Caucasian,05/15/38,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/6/13 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +52757,59582,54132,PRETRIAL,Jacob,Jake,NULL,Male,Caucasian,05/15/38,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +35213,59589,54139,PRETRIAL,HANSLER,THOMAS,NULL,Male,Caucasian,08/30/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +35213,59589,54139,PRETRIAL,HANSLER,THOMAS,NULL,Male,Caucasian,08/30/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +35213,59589,54139,PRETRIAL,HANSLER,THOMAS,NULL,Male,Caucasian,08/30/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52732,59554,54106,PRETRIAL,Ortiz,Tony,NULL,Male,Caucasian,05/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +52732,59554,54106,PRETRIAL,Ortiz,Tony,NULL,Male,Caucasian,05/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +52732,59554,54106,PRETRIAL,Ortiz,Tony,NULL,Male,Caucasian,05/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52746,59568,54120,Probation,vanbronkhorst,daniel,NULL,Male,Caucasian,05/15/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +52746,59568,54120,Probation,vanbronkhorst,daniel,NULL,Male,Caucasian,05/15/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +52746,59568,54120,Probation,vanbronkhorst,daniel,NULL,Male,Caucasian,05/15/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52748,59570,54122,Probation,Thompson,Jeancarlo,NULL,Male,Hispanic,09/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +52748,59570,54122,Probation,Thompson,Jeancarlo,NULL,Male,Hispanic,09/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +52748,59570,54122,Probation,Thompson,Jeancarlo,NULL,Male,Hispanic,09/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +20236,59587,54137,PRETRIAL,HARRIS,MONTREZ,NULL,Male,African-American,11/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +20236,59587,54137,PRETRIAL,HARRIS,MONTREZ,NULL,Male,African-American,11/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +20236,59587,54137,PRETRIAL,HARRIS,MONTREZ,NULL,Male,African-American,11/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52744,59566,54118,PRETRIAL,CANNON,CHRISTOPHER,NULL,Male,Caucasian,11/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +52744,59566,54118,PRETRIAL,CANNON,CHRISTOPHER,NULL,Male,Caucasian,11/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +52744,59566,54118,PRETRIAL,CANNON,CHRISTOPHER,NULL,Male,Caucasian,11/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52755,59580,54130,PRETRIAL,MCPHERSON,PAUL,JAMES,Male,African-American,02/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +52755,59580,54130,PRETRIAL,MCPHERSON,PAUL,JAMES,Male,African-American,02/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +52755,59580,54130,PRETRIAL,MCPHERSON,PAUL,JAMES,Male,African-American,02/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +33332,59584,54134,PRETRIAL,FIGUEROA,LUIS,NULL,Male,Hispanic,11/19/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/6/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +33332,59584,54134,PRETRIAL,FIGUEROA,LUIS,NULL,Male,Hispanic,11/19/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +33332,59584,54134,PRETRIAL,FIGUEROA,LUIS,NULL,Male,Hispanic,11/19/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +36435,59591,54141,PRETRIAL,Corcoran,James,Joseph,Male,Caucasian,06/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,New,1,0 +36435,59591,54141,PRETRIAL,Corcoran,James,Joseph,Male,Caucasian,06/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +36435,59591,54141,PRETRIAL,Corcoran,James,Joseph,Male,Caucasian,06/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +52764,59596,54146,Probation,diazramirez,Jose,Landry,Male,Hispanic,09/09/86,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/6/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +52764,59596,54146,Probation,diazramirez,Jose,Landry,Male,Hispanic,09/09/86,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/6/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +52764,59596,54146,Probation,diazramirez,Jose,Landry,Male,Hispanic,09/09/86,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52738,59560,54112,PRETRIAL,Revolus,Mackenson,NULL,Male,Other,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +52738,59560,54112,PRETRIAL,Revolus,Mackenson,NULL,Male,Other,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +52738,59560,54112,PRETRIAL,Revolus,Mackenson,NULL,Male,Other,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +39432,59594,54144,PRETRIAL,Harvard,Martavis,NULL,Male,Caucasian,11/29/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,New,1,0 +39432,59594,54144,PRETRIAL,Harvard,Martavis,NULL,Male,Caucasian,11/29/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,New,1,0 +39432,59594,54144,PRETRIAL,Harvard,Martavis,NULL,Male,Caucasian,11/29/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +52756,59581,54131,Probation,HAWKINS,DION,NULL,Male,African-American,05/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/6/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +52756,59581,54131,Probation,HAWKINS,DION,NULL,Male,African-American,05/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +52756,59581,54131,Probation,HAWKINS,DION,NULL,Male,African-American,05/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +50867,59552,54104,PRETRIAL,Riess,Gary,Richard,Male,Caucasian,07/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/6/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +50867,59552,54104,PRETRIAL,Riess,Gary,Richard,Male,Caucasian,07/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/6/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +50867,59552,54104,PRETRIAL,Riess,Gary,Richard,Male,Caucasian,07/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/6/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +52733,59555,54107,PRETRIAL,Israel,Guadalupe,NULL,Male,Hispanic,03/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +52733,59555,54107,PRETRIAL,Israel,Guadalupe,NULL,Male,Hispanic,03/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +52733,59555,54107,PRETRIAL,Israel,Guadalupe,NULL,Male,Hispanic,03/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52751,59573,54125,PRETRIAL,Ruiz,Lazaro,NULL,Male,Hispanic,12/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +52751,59573,54125,PRETRIAL,Ruiz,Lazaro,NULL,Male,Hispanic,12/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +52751,59573,54125,PRETRIAL,Ruiz,Lazaro,NULL,Male,Hispanic,12/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +49366,55186,50199,PRETRIAL,GEORGE,RAHEIM,NULL,Male,African-American,08/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +49366,55186,50199,PRETRIAL,GEORGE,RAHEIM,NULL,Male,African-American,08/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +49366,55186,50199,PRETRIAL,GEORGE,RAHEIM,NULL,Male,African-American,08/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52735,59557,54109,PRETRIAL,Cambridge,Alon,James,Male,African-American,07/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +52735,59557,54109,PRETRIAL,Cambridge,Alon,James,Male,African-American,07/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +52735,59557,54109,PRETRIAL,Cambridge,Alon,James,Male,African-American,07/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52749,59571,54123,PRETRIAL,Boston,Jerry,NULL,Male,African-American,06/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +52749,59571,54123,PRETRIAL,Boston,Jerry,NULL,Male,African-American,06/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,4,High,8,Risk of Recidivism,0.54,9,High,New,1,0 +52749,59571,54123,PRETRIAL,Boston,Jerry,NULL,Male,African-American,06/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52760,59586,54136,Probation,Diaz,Jahaira,NULL,Female,Hispanic,01/16/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-1,-1,N/A,New,1,0 +52760,59586,54136,Probation,Diaz,Jahaira,NULL,Female,Hispanic,01/16/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +52760,59586,54136,Probation,Diaz,Jahaira,NULL,Female,Hispanic,01/16/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52741,59563,54115,PRETRIAL,Prudent,Reginald,NULL,Male,African-American,07/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +52741,59563,54115,PRETRIAL,Prudent,Reginald,NULL,Male,African-American,07/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +52741,59563,54115,PRETRIAL,Prudent,Reginald,NULL,Male,African-American,07/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52754,59578,54129,Probation,dixon,james,NULL,Male,African-American,10/30/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/6/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +52754,59578,54129,Probation,dixon,james,NULL,Male,African-American,10/30/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +52754,59578,54129,Probation,dixon,james,NULL,Male,African-American,10/30/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52743,59565,54117,PRETRIAL,FERNANDEZ,JORGE,LUIS,Male,Hispanic,01/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +52743,59565,54117,PRETRIAL,FERNANDEZ,JORGE,LUIS,Male,Hispanic,01/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +52743,59565,54117,PRETRIAL,FERNANDEZ,JORGE,LUIS,Male,Hispanic,01/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52761,59588,54138,PRETRIAL,Beasley,Sheveal,NULL,Female,African-American,01/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +52761,59588,54138,PRETRIAL,Beasley,Sheveal,NULL,Female,African-American,01/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +52761,59588,54138,PRETRIAL,Beasley,Sheveal,NULL,Female,African-American,01/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52736,59558,54110,PRETRIAL,Castillo,Brandon,NULL,Male,Caucasian,12/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +52736,59558,54110,PRETRIAL,Castillo,Brandon,NULL,Male,Caucasian,12/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +52736,59558,54110,PRETRIAL,Castillo,Brandon,NULL,Male,Caucasian,12/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52758,59583,54133,PRETRIAL,CAMPBELL,KIMOY,NULL,Male,African-American,09/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +52758,59583,54133,PRETRIAL,CAMPBELL,KIMOY,NULL,Male,African-American,09/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +52758,59583,54133,PRETRIAL,CAMPBELL,KIMOY,NULL,Male,African-American,09/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +41644,59592,54142,PRETRIAL,Villeda,Zamir,NULL,Male,Hispanic,09/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +41644,59592,54142,PRETRIAL,Villeda,Zamir,NULL,Male,Hispanic,09/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,4,High,8,Risk of Recidivism,0.28,8,High,New,1,0 +41644,59592,54142,PRETRIAL,Villeda,Zamir,NULL,Male,Hispanic,09/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52740,59562,54114,PRETRIAL,Jones,Roy,NULL,Male,African-American,02/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +52740,59562,54114,PRETRIAL,Jones,Roy,NULL,Male,African-American,02/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +52740,59562,54114,PRETRIAL,Jones,Roy,NULL,Male,African-American,02/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +9376,59579,8909,PRETRIAL,Daniels,Tyrell,Rashad,Male,African-American,01/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,Copy,1,0 +9376,59579,8909,PRETRIAL,Daniels,Tyrell,Rashad,Male,African-American,01/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.39,5,Medium,Copy,1,0 +9376,59579,8909,PRETRIAL,Daniels,Tyrell,Rashad,Male,African-American,01/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +46647,59595,54145,PRETRIAL,Burress,Mary,NULL,Female,Caucasian,03/31/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/6/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +46647,59595,54145,PRETRIAL,Burress,Mary,NULL,Female,Caucasian,03/31/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/6/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +46647,59595,54145,PRETRIAL,Burress,Mary,NULL,Female,Caucasian,03/31/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52745,59567,54119,Probation,Zavala,Leonidas,NULL,Male,Hispanic,11/16/58,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +52745,59567,54119,Probation,Zavala,Leonidas,NULL,Male,Hispanic,11/16/58,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/13 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +52745,59567,54119,Probation,Zavala,Leonidas,NULL,Male,Hispanic,11/16/58,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +2102,59574,54126,PRETRIAL,FRAZIER,VAUGHN,NULL,Male,Caucasian,12/27/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +2102,59574,54126,PRETRIAL,FRAZIER,VAUGHN,NULL,Male,Caucasian,12/27/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +2102,59574,54126,PRETRIAL,FRAZIER,VAUGHN,NULL,Male,Caucasian,12/27/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52731,59553,54105,PRETRIAL,NEWTON,BRADLEY,C,Male,African-American,02/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +52731,59553,54105,PRETRIAL,NEWTON,BRADLEY,C,Male,African-American,02/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +52731,59553,54105,PRETRIAL,NEWTON,BRADLEY,C,Male,African-American,02/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52769,59604,54153,PRETRIAL,Baldinger,Alexis,NULL,Female,Caucasian,07/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +52769,59604,54153,PRETRIAL,Baldinger,Alexis,NULL,Female,Caucasian,07/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +52769,59604,54153,PRETRIAL,Baldinger,Alexis,NULL,Female,Caucasian,07/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52193,59618,53461,PRETRIAL,Gibboney,Sean,NULL,Male,Caucasian,11/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,4,High,7,Risk of Violence,-0.69,9,High,Copy,1,0 +52193,59618,53461,PRETRIAL,Gibboney,Sean,NULL,Male,Caucasian,11/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,4,High,8,Risk of Recidivism,0.13,8,High,Copy,1,0 +52193,59618,53461,PRETRIAL,Gibboney,Sean,NULL,Male,Caucasian,11/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +52781,59625,54171,Probation,Wobschall,Michael,NULL,Male,Caucasian,03/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +52781,59625,54171,Probation,Wobschall,Michael,NULL,Male,Caucasian,03/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +52781,59625,54171,Probation,Wobschall,Michael,NULL,Male,Caucasian,03/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52763,59632,54177,PRETRIAL,william,king,NULL,Male,Caucasian,08/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +52763,59632,54177,PRETRIAL,william,king,NULL,Male,Caucasian,08/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +52763,59632,54177,PRETRIAL,william,king,NULL,Male,Caucasian,08/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52795,59639,54183,Probation,CLARKE,DAWN,ELAINE,Male,African-American,09/21/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/7/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +52795,59639,54183,Probation,CLARKE,DAWN,ELAINE,Male,African-American,09/21/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/7/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +52795,59639,54183,Probation,CLARKE,DAWN,ELAINE,Male,African-American,09/21/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52800,59646,54189,PRETRIAL,semino,alexander,NULL,Male,Caucasian,05/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.7,2,Low,New,1,0 +52800,59646,54189,PRETRIAL,semino,alexander,NULL,Male,Caucasian,05/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +52800,59646,54189,PRETRIAL,semino,alexander,NULL,Male,Caucasian,05/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52775,59613,54162,PRETRIAL,HOLSTON,SHELIA,NULL,Female,African-American,05/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +52775,59613,54162,PRETRIAL,HOLSTON,SHELIA,NULL,Female,African-American,05/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.07,8,High,New,1,0 +52775,59613,54162,PRETRIAL,HOLSTON,SHELIA,NULL,Female,African-American,05/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +32316,59630,31346,PRETRIAL,BELGRAVE,JOSEPH,NULL,Male,African-American,08/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.98,9,High,Copy,1,0 +32316,59630,31346,PRETRIAL,BELGRAVE,JOSEPH,NULL,Male,African-American,08/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,7,Medium,Copy,1,0 +32316,59630,31346,PRETRIAL,BELGRAVE,JOSEPH,NULL,Male,African-American,08/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +39757,59609,54158,PRETRIAL,Seays,Brandon,T,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +39757,59609,54158,PRETRIAL,Seays,Brandon,T,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +39757,59609,54158,PRETRIAL,Seays,Brandon,T,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52791,59634,54179,PRETRIAL,Park,Minsoo,NULL,Male,Asian,11/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +52791,59634,54179,PRETRIAL,Park,Minsoo,NULL,Male,Asian,11/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +52791,59634,54179,PRETRIAL,Park,Minsoo,NULL,Male,Asian,11/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49848,59599,54149,PRETRIAL,Henry,Neville,Paul,Male,African-American,11/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,4,High,7,Risk of Violence,-0.72,9,High,New,1,0 +49848,59599,54149,PRETRIAL,Henry,Neville,Paul,Male,African-American,11/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,4,High,8,Risk of Recidivism,0.43,9,High,New,1,0 +49848,59599,54149,PRETRIAL,Henry,Neville,Paul,Male,African-American,11/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52759,59644,54187,PRETRIAL,Symonette,Dematris,NULL,Male,African-American,12/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +52759,59644,54187,PRETRIAL,Symonette,Dematris,NULL,Male,African-American,12/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +52759,59644,54187,PRETRIAL,Symonette,Dematris,NULL,Male,African-American,12/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52789,59636,54181,Probation,SCOTT,HAYW00D,NULL,Male,African-American,10/03/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +52789,59636,54181,Probation,SCOTT,HAYW00D,NULL,Male,African-American,10/03/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +52789,59636,54181,Probation,SCOTT,HAYW00D,NULL,Male,African-American,10/03/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +13921,59607,54156,PRETRIAL,Operle,Jason,NULL,Male,Caucasian,06/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,4,High,7,Risk of Violence,-0.41,10,High,New,1,0 +13921,59607,54156,PRETRIAL,Operle,Jason,NULL,Male,Caucasian,06/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,New,1,0 +13921,59607,54156,PRETRIAL,Operle,Jason,NULL,Male,Caucasian,06/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +52780,59623,54169,Probation,Stephen,Clenete,Yvette,Female,African-American,10/05/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/7/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +52780,59623,54169,Probation,Stephen,Clenete,Yvette,Female,African-American,10/05/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +52780,59623,54169,Probation,Stephen,Clenete,Yvette,Female,African-American,10/05/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/7/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52797,59641,54185,Probation,Dierks,Margaret,Anstine,Female,Caucasian,09/15/54,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +52797,59641,54185,Probation,Dierks,Margaret,Anstine,Female,Caucasian,09/15/54,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +52797,59641,54185,Probation,Dierks,Margaret,Anstine,Female,Caucasian,09/15/54,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +52768,59602,54152,PRETRIAL,Bell,Douglas,NULL,Male,Caucasian,07/10/41,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,3/7/13 0:00,1,Low,7,Risk of Violence,-4.34,1,Low,New,1,0 +52768,59602,54152,PRETRIAL,Bell,Douglas,NULL,Male,Caucasian,07/10/41,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,3/7/13 0:00,1,Low,8,Risk of Recidivism,-2.97,1,Low,New,1,0 +52768,59602,54152,PRETRIAL,Bell,Douglas,NULL,Male,Caucasian,07/10/41,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52193,59620,53461,PRETRIAL,Gibboney,Sean,NULL,Male,Caucasian,11/10/75,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,Copy,1,0 +52193,59620,53461,PRETRIAL,Gibboney,Sean,NULL,Male,Caucasian,11/10/75,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,Copy,1,0 +52193,59620,53461,PRETRIAL,Gibboney,Sean,NULL,Male,Caucasian,11/10/75,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +48820,59615,54164,PRETRIAL,Jacsaint,Jermai,NULL,Male,African-American,12/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,New,1,0 +48820,59615,54164,PRETRIAL,Jacsaint,Jermai,NULL,Male,African-American,12/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +48820,59615,54164,PRETRIAL,Jacsaint,Jermai,NULL,Male,African-American,12/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52783,59628,54174,Probation,MARTINEZ,PEDRO,NULL,Male,Hispanic,05/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +52783,59628,54174,Probation,MARTINEZ,PEDRO,NULL,Male,Hispanic,05/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +52783,59628,54174,Probation,MARTINEZ,PEDRO,NULL,Male,Hispanic,05/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52782,59626,54172,Probation,LAVATE,DANIEL,BRIAN,Male,Caucasian,08/16/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +52782,59626,54172,Probation,LAVATE,DANIEL,BRIAN,Male,Caucasian,08/16/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +52782,59626,54172,Probation,LAVATE,DANIEL,BRIAN,Male,Caucasian,08/16/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +43367,59643,43306,PRETRIAL,holmes,jerome,NULL,Male,African-American,04/06/88,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,3/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.96,9,High,New,1,0 +43367,59643,43306,PRETRIAL,holmes,jerome,NULL,Male,African-American,04/06/88,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,3/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,6,Medium,New,1,0 +43367,59643,43306,PRETRIAL,holmes,jerome,NULL,Male,African-American,04/06/88,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,3/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +52777,59617,54166,PRETRIAL,Green,Michael,NULL,Male,African-American,05/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +52777,59617,54166,PRETRIAL,Green,Michael,NULL,Male,African-American,05/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +52777,59617,54166,PRETRIAL,Green,Michael,NULL,Male,African-American,05/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52779,59622,54168,PRETRIAL,falcon,monique,NULL,Female,Native American,07/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/7/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +52779,59622,54168,PRETRIAL,falcon,monique,NULL,Female,Native American,07/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/7/13 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +52779,59622,54168,PRETRIAL,falcon,monique,NULL,Female,Native American,07/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +19164,59601,54151,PRETRIAL,Baker,Giorgio,Dijon,Male,African-American,01/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +19164,59601,54151,PRETRIAL,Baker,Giorgio,Dijon,Male,African-American,01/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +19164,59601,54151,PRETRIAL,Baker,Giorgio,Dijon,Male,African-American,01/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52770,59605,54154,PRETRIAL,Contreras,Kelby,NULL,Male,Hispanic,08/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/7/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +52770,59605,54154,PRETRIAL,Contreras,Kelby,NULL,Male,Hispanic,08/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/7/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +52770,59605,54154,PRETRIAL,Contreras,Kelby,NULL,Male,Hispanic,08/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52200,59638,53469,PRETRIAL,Webb,Shenika,NULL,Female,African-American,01/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,Copy,1,0 +52200,59638,53469,PRETRIAL,Webb,Shenika,NULL,Female,African-American,01/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,Copy,1,0 +52200,59638,53469,PRETRIAL,Webb,Shenika,NULL,Female,African-American,01/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +48468,59603,49163,PRETRIAL,HADDAD,PAUL,MICHAEL,Male,Caucasian,03/01/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,2,Medium,7,Risk of Violence,-3.24,1,Low,Copy,1,0 +48468,59603,49163,PRETRIAL,HADDAD,PAUL,MICHAEL,Male,Caucasian,03/01/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,Copy,1,0 +48468,59603,49163,PRETRIAL,HADDAD,PAUL,MICHAEL,Male,Caucasian,03/01/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +34859,59610,54159,PRETRIAL,Debe,Ryan,R,Male,African-American,01/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.81,9,High,New,1,0 +34859,59610,54159,PRETRIAL,Debe,Ryan,R,Male,African-American,01/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +34859,59610,54159,PRETRIAL,Debe,Ryan,R,Male,African-American,01/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52774,59612,54161,PRETRIAL,Morgan,Alfonzo,NULL,Male,African-American,11/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +52774,59612,54161,PRETRIAL,Morgan,Alfonzo,NULL,Male,African-American,11/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +52774,59612,54161,PRETRIAL,Morgan,Alfonzo,NULL,Male,African-American,11/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52785,59631,54176,Probation,harris,jessica,NULL,Female,Caucasian,05/31/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +52785,59631,54176,Probation,harris,jessica,NULL,Female,Caucasian,05/31/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,8,High,New,1,0 +52785,59631,54176,Probation,harris,jessica,NULL,Female,Caucasian,05/31/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52790,59633,54178,Probation,Reyes,Gladys,Lessenia,Female,Hispanic,11/05/63,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +52790,59633,54178,Probation,Reyes,Gladys,Lessenia,Female,Hispanic,11/05/63,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +52790,59633,54178,Probation,Reyes,Gladys,Lessenia,Female,Hispanic,11/05/63,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52796,59640,54184,Probation,konstantinou,Barbara,NULL,Female,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +52796,59640,54184,Probation,konstantinou,Barbara,NULL,Female,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +52796,59640,54184,Probation,konstantinou,Barbara,NULL,Female,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +4855,59627,54173,Probation,Sanders,Antvonte,Rashad,Male,African-American,02/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +4855,59627,54173,Probation,Sanders,Antvonte,Rashad,Male,African-American,02/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +4855,59627,54173,Probation,Sanders,Antvonte,Rashad,Male,African-American,02/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52784,59629,54175,PRETRIAL,ALDERS,ERIC,MICHAEL,Male,Caucasian,03/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +52784,59629,54175,PRETRIAL,ALDERS,ERIC,MICHAEL,Male,Caucasian,03/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +52784,59629,54175,PRETRIAL,ALDERS,ERIC,MICHAEL,Male,Caucasian,03/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52771,59606,54155,PRETRIAL,DAVIS,RAKESH,A,Male,African-American,04/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +52771,59606,54155,PRETRIAL,DAVIS,RAKESH,A,Male,African-American,04/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +52771,59606,54155,PRETRIAL,DAVIS,RAKESH,A,Male,African-American,04/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52772,59608,54157,PRETRIAL,Small,Rachael,NULL,Female,African-American,09/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +52772,59608,54157,PRETRIAL,Small,Rachael,NULL,Female,African-American,09/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-1.61,2,Low,New,1,0 +52772,59608,54157,PRETRIAL,Small,Rachael,NULL,Female,African-American,09/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52798,59642,54186,Probation,Arcos,Jorge,Enrique,Male,Hispanic,01/23/76,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/7/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +52798,59642,54186,Probation,Arcos,Jorge,Enrique,Male,Hispanic,01/23/76,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/7/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +52798,59642,54186,Probation,Arcos,Jorge,Enrique,Male,Hispanic,01/23/76,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52767,59600,54150,PRETRIAL,Fabre,Gaellen,NULL,Male,African-American,12/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +52767,59600,54150,PRETRIAL,Fabre,Gaellen,NULL,Male,African-American,12/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +52767,59600,54150,PRETRIAL,Fabre,Gaellen,NULL,Male,African-American,12/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +7491,59614,54163,PRETRIAL,domville,pierre,NULL,Male,Other,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +7491,59614,54163,PRETRIAL,domville,pierre,NULL,Male,Other,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +7491,59614,54163,PRETRIAL,domville,pierre,NULL,Male,Other,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52778,59621,54167,Probation,gray,talaya,NULL,Female,African-American,10/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +52778,59621,54167,Probation,gray,talaya,NULL,Female,African-American,10/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +52778,59621,54167,Probation,gray,talaya,NULL,Female,African-American,10/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/7/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52792,59635,54180,Probation,Styren,Peter,NULL,Male,Caucasian,05/17/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/7/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +52792,59635,54180,Probation,Styren,Peter,NULL,Male,Caucasian,05/17/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/7/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +52792,59635,54180,Probation,Styren,Peter,NULL,Male,Caucasian,05/17/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52776,59616,54165,PRETRIAL,Curry,Jeffery,NULL,Male,African-American,03/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,4,High,7,Risk of Violence,-0.19,10,High,New,1,0 +52776,59616,54165,PRETRIAL,Curry,Jeffery,NULL,Male,African-American,03/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,4,High,8,Risk of Recidivism,0.87,10,High,New,1,0 +52776,59616,54165,PRETRIAL,Curry,Jeffery,NULL,Male,African-American,03/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +40257,59624,54170,Probation,ingram,benjamin,NULL,Male,African-American,07/23/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/7/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +40257,59624,54170,Probation,ingram,benjamin,NULL,Male,African-American,07/23/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/7/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +40257,59624,54170,Probation,ingram,benjamin,NULL,Male,African-American,07/23/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/7/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52773,59611,54160,PRETRIAL,Colvin,Timothy,NULL,Male,Caucasian,10/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +52773,59611,54160,PRETRIAL,Colvin,Timothy,NULL,Male,Caucasian,10/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +52773,59611,54160,PRETRIAL,Colvin,Timothy,NULL,Male,Caucasian,10/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +36993,59679,54214,PRETRIAL,Mombranche,Mikey,NULL,Male,African-American,09/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +36993,59679,54214,PRETRIAL,Mombranche,Mikey,NULL,Male,African-American,09/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +36993,59679,54214,PRETRIAL,Mombranche,Mikey,NULL,Male,African-American,09/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +52825,59671,54209,Probation,Jaggernath,Jessica,NULL,Female,Other,01/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/8/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +52825,59671,54209,Probation,Jaggernath,Jessica,NULL,Female,Other,01/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/8/13 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +52825,59671,54209,Probation,Jaggernath,Jessica,NULL,Female,Other,01/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52806,59650,54193,PRETRIAL,Brewer,Nancy,NULL,Female,African-American,06/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +52806,59650,54193,PRETRIAL,Brewer,Nancy,NULL,Female,African-American,06/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +52806,59650,54193,PRETRIAL,Brewer,Nancy,NULL,Female,African-American,06/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52817,59663,54205,Probation,Pagan,Anthony,NULL,Male,Hispanic,08/09/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/8/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +52817,59663,54205,Probation,Pagan,Anthony,NULL,Male,Hispanic,08/09/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/8/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +52817,59663,54205,Probation,Pagan,Anthony,NULL,Male,Hispanic,08/09/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52815,59661,54203,PRETRIAL,HUNT,PHILLIP,NULL,Male,Other,05/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +52815,59661,54203,PRETRIAL,HUNT,PHILLIP,NULL,Male,Other,05/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +52815,59661,54203,PRETRIAL,HUNT,PHILLIP,NULL,Male,Other,05/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +36508,59654,54197,PRETRIAL,JOHNSON,JAMEKA,SHARNETT,Male,African-American,01/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,4,High,7,Risk of Violence,-0.84,9,High,New,1,0 +36508,59654,54197,PRETRIAL,JOHNSON,JAMEKA,SHARNETT,Male,African-American,01/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,4,High,8,Risk of Recidivism,0.27,8,High,New,1,0 +36508,59654,54197,PRETRIAL,JOHNSON,JAMEKA,SHARNETT,Male,African-American,01/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +20962,59675,52928,Probation,Martin,Shaporia,La'shay,Female,African-American,05/25/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/8/13 0:00,4,High,7,Risk of Violence,-1.08,8,High,Copy,1,0 +20962,59675,52928,Probation,Martin,Shaporia,La'shay,Female,African-American,05/25/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/8/13 0:00,4,High,8,Risk of Recidivism,0.29,9,High,Copy,1,0 +20962,59675,52928,Probation,Martin,Shaporia,La'shay,Female,African-American,05/25/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/8/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +52808,59652,54195,PRETRIAL,Hilaire,Gregory,NULL,Male,Other,04/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +52808,59652,54195,PRETRIAL,Hilaire,Gregory,NULL,Male,Other,04/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +52808,59652,54195,PRETRIAL,Hilaire,Gregory,NULL,Male,Other,04/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52813,59659,54201,Probation,Deoliveira,Amarildo,NULL,Male,Other,04/15/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,3/8/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +52813,59659,54201,Probation,Deoliveira,Amarildo,NULL,Male,Other,04/15/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,3/8/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +52813,59659,54201,Probation,Deoliveira,Amarildo,NULL,Male,Other,04/15/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52810,59656,54199,PRETRIAL,Peebles,Ranell,A,Male,African-American,06/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/8/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +52810,59656,54199,PRETRIAL,Peebles,Ranell,A,Male,African-American,06/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/8/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +52810,59656,54199,PRETRIAL,Peebles,Ranell,A,Male,African-American,06/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +46582,59677,47006,PRETRIAL,McIntyre,Charles,NULL,Male,African-American,11/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,Copy,1,0 +46582,59677,47006,PRETRIAL,McIntyre,Charles,NULL,Male,African-American,11/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,Copy,1,0 +46582,59677,47006,PRETRIAL,McIntyre,Charles,NULL,Male,African-American,11/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +52816,59662,54204,Probation,hazen,desiree,NULL,Female,Caucasian,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Parole,Single,3/8/13 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +52816,59662,54204,Probation,hazen,desiree,NULL,Female,Caucasian,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Parole,Single,3/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +52816,59662,54204,Probation,hazen,desiree,NULL,Female,Caucasian,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Parole,Single,3/8/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +41847,59649,54192,PRETRIAL,Tarquino,Chandler,NULL,Male,Hispanic,12/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,4,High,7,Risk of Violence,-0.55,10,High,New,1,0 +41847,59649,54192,PRETRIAL,Tarquino,Chandler,NULL,Male,Hispanic,12/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,4,High,8,Risk of Recidivism,0.67,10,High,New,1,0 +41847,59649,54192,PRETRIAL,Tarquino,Chandler,NULL,Male,Hispanic,12/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +7774,59670,7357,PRETRIAL,Gauier,Justin,NULL,Male,Caucasian,07/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,Copy,1,0 +7774,59670,7357,PRETRIAL,Gauier,Justin,NULL,Male,Caucasian,07/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,Copy,1,0 +7774,59670,7357,PRETRIAL,Gauier,Justin,NULL,Male,Caucasian,07/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +52812,59657,54200,PRETRIAL,Bahadosingh,Krishna,NULL,Male,Other,12/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +52812,59657,54200,PRETRIAL,Bahadosingh,Krishna,NULL,Male,Other,12/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +52812,59657,54200,PRETRIAL,Bahadosingh,Krishna,NULL,Male,Other,12/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52824,59678,54213,PRETRIAL,Turcotte,Jeffery,NULL,Male,Other,02/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.16,8,High,New,1,0 +52824,59678,54213,PRETRIAL,Turcotte,Jeffery,NULL,Male,Other,02/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +52824,59678,54213,PRETRIAL,Turcotte,Jeffery,NULL,Male,Other,02/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52819,59665,54207,PRETRIAL,Andrews,Michael,NULL,Male,Caucasian,02/01/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +52819,59665,54207,PRETRIAL,Andrews,Michael,NULL,Male,Caucasian,02/01/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +52819,59665,54207,PRETRIAL,Andrews,Michael,NULL,Male,Caucasian,02/01/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52826,59672,54210,Probation,SANCHEZ,ANGEL,M,Male,Hispanic,05/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/8/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +52826,59672,54210,Probation,SANCHEZ,ANGEL,M,Male,Hispanic,05/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/8/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +52826,59672,54210,Probation,SANCHEZ,ANGEL,M,Male,Hispanic,05/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52805,59648,54191,PRETRIAL,Thomas,Torrey,NULL,Male,African-American,08/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,2,Medium,7,Risk of Violence,-2.9,2,Low,New,1,0 +52805,59648,54191,PRETRIAL,Thomas,Torrey,NULL,Male,African-American,08/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +52805,59648,54191,PRETRIAL,Thomas,Torrey,NULL,Male,African-American,08/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52807,59651,54194,PRETRIAL,Calvert,Ernest,NULL,Male,African-American,08/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +52807,59651,54194,PRETRIAL,Calvert,Ernest,NULL,Male,African-American,08/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +52807,59651,54194,PRETRIAL,Calvert,Ernest,NULL,Male,African-American,08/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52811,59655,54198,PRETRIAL,Jacobs,Javon,NULL,Male,African-American,05/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +52811,59655,54198,PRETRIAL,Jacobs,Javon,NULL,Male,African-American,05/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +52811,59655,54198,PRETRIAL,Jacobs,Javon,NULL,Male,African-American,05/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +49070,59667,49848,PRETRIAL,jackson,marlon,NULL,Male,African-American,07/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,Copy,1,0 +49070,59667,49848,PRETRIAL,jackson,marlon,NULL,Male,African-American,07/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.76,3,Low,Copy,1,0 +49070,59667,49848,PRETRIAL,jackson,marlon,NULL,Male,African-American,07/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/8/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +52809,59653,54196,PRETRIAL,Dresch,Robert,NULL,Male,Caucasian,11/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +52809,59653,54196,PRETRIAL,Dresch,Robert,NULL,Male,Caucasian,11/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +52809,59653,54196,PRETRIAL,Dresch,Robert,NULL,Male,Caucasian,11/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +39175,42270,38673,PRETRIAL,PALMORE,DWAYNE,ANTONIO,Male,African-American,10/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +39175,42270,38673,PRETRIAL,PALMORE,DWAYNE,ANTONIO,Male,African-American,10/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +39175,42270,38673,PRETRIAL,PALMORE,DWAYNE,ANTONIO,Male,African-American,10/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52842,59697,54229,PRETRIAL,Moye,Syreta,R,Female,African-American,02/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +52842,59697,54229,PRETRIAL,Moye,Syreta,R,Female,African-American,02/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +52842,59697,54229,PRETRIAL,Moye,Syreta,R,Female,African-American,02/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52840,59695,54227,PRETRIAL,Thompson,Krystal,NULL,Female,African-American,09/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +52840,59695,54227,PRETRIAL,Thompson,Krystal,NULL,Female,African-American,09/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,7,Medium,New,1,0 +52840,59695,54227,PRETRIAL,Thompson,Krystal,NULL,Female,African-American,09/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +39175,59702,38673,PRETRIAL,PALMORE,DWAYNE,ANTONIO,Male,African-American,10/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,Copy,1,0 +39175,59702,38673,PRETRIAL,PALMORE,DWAYNE,ANTONIO,Male,African-American,10/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,Copy,1,0 +39175,59702,38673,PRETRIAL,PALMORE,DWAYNE,ANTONIO,Male,African-American,10/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +52830,59681,54216,PRETRIAL,Mills,Alphonse,NULL,Male,African-American,04/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/9/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +52830,59681,54216,PRETRIAL,Mills,Alphonse,NULL,Male,African-American,04/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/9/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +52830,59681,54216,PRETRIAL,Mills,Alphonse,NULL,Male,African-American,04/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52837,59690,54224,PRETRIAL,Young,Timothy,NULL,Male,African-American,03/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +52837,59690,54224,PRETRIAL,Young,Timothy,NULL,Male,African-American,03/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +52837,59690,54224,PRETRIAL,Young,Timothy,NULL,Male,African-American,03/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52844,59699,54231,PRETRIAL,zachary,libman,NULL,Male,Caucasian,02/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +52844,59699,54231,PRETRIAL,zachary,libman,NULL,Male,Caucasian,02/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +52844,59699,54231,PRETRIAL,zachary,libman,NULL,Male,Caucasian,02/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52846,59701,54233,PRETRIAL,Rosario,Daniel,NULL,Male,Caucasian,12/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +52846,59701,54233,PRETRIAL,Rosario,Daniel,NULL,Male,Caucasian,12/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +52846,59701,54233,PRETRIAL,Rosario,Daniel,NULL,Male,Caucasian,12/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52829,59680,54215,PRETRIAL,Liberatore,Michael,NULL,Male,Caucasian,11/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/9/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +52829,59680,54215,PRETRIAL,Liberatore,Michael,NULL,Male,Caucasian,11/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/9/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +52829,59680,54215,PRETRIAL,Liberatore,Michael,NULL,Male,Caucasian,11/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52839,59693,54226,PRETRIAL,Upp,James,NULL,Male,Caucasian,10/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +52839,59693,54226,PRETRIAL,Upp,James,NULL,Male,Caucasian,10/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +52839,59693,54226,PRETRIAL,Upp,James,NULL,Male,Caucasian,10/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52833,59685,54220,PRETRIAL,Rojas,Andrea,Katerine,Female,Hispanic,10/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/9/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +52833,59685,54220,PRETRIAL,Rojas,Andrea,Katerine,Female,Hispanic,10/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/9/13 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +52833,59685,54220,PRETRIAL,Rojas,Andrea,Katerine,Female,Hispanic,10/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52834,59686,54221,PRETRIAL,KENNEDY,DIANA,NULL,Female,Caucasian,05/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +52834,59686,54221,PRETRIAL,KENNEDY,DIANA,NULL,Female,Caucasian,05/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +52834,59686,54221,PRETRIAL,KENNEDY,DIANA,NULL,Female,Caucasian,05/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +7874,59688,7458,PRETRIAL,MCMINN,KENNETH,NULL,Male,Caucasian,04/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,Copy,1,0 +7874,59688,7458,PRETRIAL,MCMINN,KENNETH,NULL,Male,Caucasian,04/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,Copy,1,0 +7874,59688,7458,PRETRIAL,MCMINN,KENNETH,NULL,Male,Caucasian,04/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +52838,59691,54225,PRETRIAL,Calle,Carlos,NULL,Male,Caucasian,04/13/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +52838,59691,54225,PRETRIAL,Calle,Carlos,NULL,Male,Caucasian,04/13/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +52838,59691,54225,PRETRIAL,Calle,Carlos,NULL,Male,Caucasian,04/13/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +25222,59683,54218,PRETRIAL,Hamin,Asim,NULL,Male,African-American,10/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.12,8,High,New,1,0 +25222,59683,54218,PRETRIAL,Hamin,Asim,NULL,Male,African-American,10/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +25222,59683,54218,PRETRIAL,Hamin,Asim,NULL,Male,African-American,10/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52841,59696,54228,PRETRIAL,Perez,Santos,NULL,Male,Caucasian,08/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +52841,59696,54228,PRETRIAL,Perez,Santos,NULL,Male,Caucasian,08/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +52841,59696,54228,PRETRIAL,Perez,Santos,NULL,Male,Caucasian,08/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +31249,59694,30265,PRETRIAL,jeffery,richardson,NULL,Male,African-American,12/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +31249,59694,30265,PRETRIAL,jeffery,richardson,NULL,Male,African-American,12/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,Copy,1,0 +31249,59694,30265,PRETRIAL,jeffery,richardson,NULL,Male,African-American,12/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +52843,59698,54230,PRETRIAL,Singletary,Jermain,Lacharlie,Male,African-American,06/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +52843,59698,54230,PRETRIAL,Singletary,Jermain,Lacharlie,Male,African-American,06/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +52843,59698,54230,PRETRIAL,Singletary,Jermain,Lacharlie,Male,African-American,06/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52831,59682,54217,PRETRIAL,Burton,Lawanneka,NULL,Female,African-American,12/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/9/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +52831,59682,54217,PRETRIAL,Burton,Lawanneka,NULL,Female,African-American,12/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/9/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +52831,59682,54217,PRETRIAL,Burton,Lawanneka,NULL,Female,African-American,12/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52836,59689,54223,PRETRIAL,Session,Trevaris,NULL,Male,African-American,12/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.02,8,High,New,1,0 +52836,59689,54223,PRETRIAL,Session,Trevaris,NULL,Male,African-American,12/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +52836,59689,54223,PRETRIAL,Session,Trevaris,NULL,Male,African-American,12/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52845,59700,54232,PRETRIAL,Boyd,Alexander,NULL,Male,African-American,08/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,4,High,7,Risk of Violence,-0.66,9,High,New,1,0 +52845,59700,54232,PRETRIAL,Boyd,Alexander,NULL,Male,African-American,08/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,4,High,8,Risk of Recidivism,1.22,10,High,New,1,0 +52845,59700,54232,PRETRIAL,Boyd,Alexander,NULL,Male,African-American,08/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +7104,59692,38846,PRETRIAL,barber,michael,jevon,Male,African-American,12/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,Copy,1,0 +7104,59692,38846,PRETRIAL,barber,michael,jevon,Male,African-American,12/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.07,10,High,Copy,1,0 +7104,59692,38846,PRETRIAL,barber,michael,jevon,Male,African-American,12/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,38,10,High,Copy,1,0 +52832,59684,54219,PRETRIAL,BURR,RAYMOND,NULL,Male,Caucasian,02/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +52832,59684,54219,PRETRIAL,BURR,RAYMOND,NULL,Male,Caucasian,02/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +52832,59684,54219,PRETRIAL,BURR,RAYMOND,NULL,Male,Caucasian,02/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52835,59687,54222,PRETRIAL,Benjamin,Alex,Benjamin,Male,Caucasian,06/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +52835,59687,54222,PRETRIAL,Benjamin,Alex,Benjamin,Male,Caucasian,06/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +52835,59687,54222,PRETRIAL,Benjamin,Alex,Benjamin,Male,Caucasian,06/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +12700,59705,54236,PRETRIAL,JOHNSON,JEFFERY,NULL,Male,African-American,10/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +12700,59705,54236,PRETRIAL,JOHNSON,JEFFERY,NULL,Male,African-American,10/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +12700,59705,54236,PRETRIAL,JOHNSON,JEFFERY,NULL,Male,African-American,10/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52853,59713,54244,PRETRIAL,FLORENCE,BRANDON,NULL,Male,African-American,09/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +52853,59713,54244,PRETRIAL,FLORENCE,BRANDON,NULL,Male,African-American,09/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +52853,59713,54244,PRETRIAL,FLORENCE,BRANDON,NULL,Male,African-American,09/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52848,59708,54238,PRETRIAL,PETERSEN,ANTHONY,BRUCE,Male,Caucasian,02/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +52848,59708,54238,PRETRIAL,PETERSEN,ANTHONY,BRUCE,Male,Caucasian,02/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +52848,59708,54238,PRETRIAL,PETERSEN,ANTHONY,BRUCE,Male,Caucasian,02/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45351,59703,54234,PRETRIAL,POIRIER,ROSALIA,NULL,Female,Caucasian,07/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +45351,59703,54234,PRETRIAL,POIRIER,ROSALIA,NULL,Female,Caucasian,07/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +45351,59703,54234,PRETRIAL,POIRIER,ROSALIA,NULL,Female,Caucasian,07/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52850,59710,54241,PRETRIAL,Pierre,Derrick,NULL,Male,African-American,02/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/10/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +52850,59710,54241,PRETRIAL,Pierre,Derrick,NULL,Male,African-American,02/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/10/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +52850,59710,54241,PRETRIAL,Pierre,Derrick,NULL,Male,African-American,02/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52852,59712,54243,PRETRIAL,Smith,Christopher,NULL,Male,Caucasian,01/21/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +52852,59712,54243,PRETRIAL,Smith,Christopher,NULL,Male,Caucasian,01/21/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +52852,59712,54243,PRETRIAL,Smith,Christopher,NULL,Male,Caucasian,01/21/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52855,59715,54246,PRETRIAL,whittaker,kenneth,NULL,Male,Caucasian,08/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +52855,59715,54246,PRETRIAL,whittaker,kenneth,NULL,Male,Caucasian,08/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +52855,59715,54246,PRETRIAL,whittaker,kenneth,NULL,Male,Caucasian,08/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52849,59709,54239,PRETRIAL,Melvin,Pilar,NULL,Female,African-American,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +52849,59709,54239,PRETRIAL,Melvin,Pilar,NULL,Female,African-American,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +52849,59709,54239,PRETRIAL,Melvin,Pilar,NULL,Female,African-American,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52847,59707,54237,PRETRIAL,Hill,Stephen,NULL,Male,Caucasian,01/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +52847,59707,54237,PRETRIAL,Hill,Stephen,NULL,Male,Caucasian,01/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +52847,59707,54237,PRETRIAL,Hill,Stephen,NULL,Male,Caucasian,01/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52854,59714,54245,PRETRIAL,Molina,Mauricio,R,Male,Caucasian,01/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +52854,59714,54245,PRETRIAL,Molina,Mauricio,R,Male,Caucasian,01/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +52854,59714,54245,PRETRIAL,Molina,Mauricio,R,Male,Caucasian,01/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +11169,59706,49558,PRETRIAL,LEWIS,BRANDON,NULL,Male,African-American,07/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,Copy,1,0 +11169,59706,49558,PRETRIAL,LEWIS,BRANDON,NULL,Male,African-American,07/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.64,10,High,Copy,1,0 +11169,59706,49558,PRETRIAL,LEWIS,BRANDON,NULL,Male,African-American,07/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,Copy,1,0 +52851,59711,54242,PRETRIAL,WILSON,CARLWELL,NULL,Male,African-American,10/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +52851,59711,54242,PRETRIAL,WILSON,CARLWELL,NULL,Male,African-American,10/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +52851,59711,54242,PRETRIAL,WILSON,CARLWELL,NULL,Male,African-American,10/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52859,59720,54250,PRETRIAL,Acevedo,Joseph,NULL,Male,Hispanic,06/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +52859,59720,54250,PRETRIAL,Acevedo,Joseph,NULL,Male,Hispanic,06/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +52859,59720,54250,PRETRIAL,Acevedo,Joseph,NULL,Male,Hispanic,06/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52856,59716,54247,PRETRIAL,Altuve,Horace,NULL,Male,Caucasian,02/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/10/13 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,New,1,0 +52856,59716,54247,PRETRIAL,Altuve,Horace,NULL,Male,Caucasian,02/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +52856,59716,54247,PRETRIAL,Altuve,Horace,NULL,Male,Caucasian,02/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/10/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +29068,59704,54235,PRETRIAL,ford,waldo,NULL,Male,African-American,10/01/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +29068,59704,54235,PRETRIAL,ford,waldo,NULL,Male,African-American,10/01/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +29068,59704,54235,PRETRIAL,ford,waldo,NULL,Male,African-American,10/01/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52857,59718,54248,PRETRIAL,LOPEZ,NOEL,NULL,Male,Hispanic,11/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,Copy,1,0 +52857,59718,54248,PRETRIAL,LOPEZ,NOEL,NULL,Male,Hispanic,11/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,Copy,1,0 +52857,59718,54248,PRETRIAL,LOPEZ,NOEL,NULL,Male,Hispanic,11/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +52884,59753,54279,Probation,michel,veronique,NULL,Female,African-American,01/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/11/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +52884,59753,54279,Probation,michel,veronique,NULL,Female,African-American,01/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +52884,59753,54279,Probation,michel,veronique,NULL,Female,African-American,01/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52864,59725,54255,PRETRIAL,SPELLS,SHAUN,NULL,Male,Caucasian,12/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +52864,59725,54255,PRETRIAL,SPELLS,SHAUN,NULL,Male,Caucasian,12/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +52864,59725,54255,PRETRIAL,SPELLS,SHAUN,NULL,Male,Caucasian,12/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52871,59732,54262,PRETRIAL,ROBERT,SHAUN,ADIL-KUMAR,Male,Caucasian,06/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +52871,59732,54262,PRETRIAL,ROBERT,SHAUN,ADIL-KUMAR,Male,Caucasian,06/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +52871,59732,54262,PRETRIAL,ROBERT,SHAUN,ADIL-KUMAR,Male,Caucasian,06/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +2190,59739,54268,DRRD,Ruidiaz,Rigo,NULL,Male,Hispanic,02/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +2190,59739,54268,DRRD,Ruidiaz,Rigo,NULL,Male,Hispanic,02/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +2190,59739,54268,DRRD,Ruidiaz,Rigo,NULL,Male,Hispanic,02/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52879,59746,54273,Probation,Vecino,Manuel,NULL,Male,Hispanic,08/27/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +52879,59746,54273,Probation,Vecino,Manuel,NULL,Male,Hispanic,08/27/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +52879,59746,54273,Probation,Vecino,Manuel,NULL,Male,Hispanic,08/27/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52862,59723,54253,PRETRIAL,VASQUEZ,BRIAN,NULL,Male,Caucasian,05/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +52862,59723,54253,PRETRIAL,VASQUEZ,BRIAN,NULL,Male,Caucasian,05/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +52862,59723,54253,PRETRIAL,VASQUEZ,BRIAN,NULL,Male,Caucasian,05/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52878,59741,54270,Probation,Bruolmos,Silena,NULL,Female,Hispanic,06/22/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +52878,59741,54270,Probation,Bruolmos,Silena,NULL,Female,Hispanic,06/22/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +52878,59741,54270,Probation,Bruolmos,Silena,NULL,Female,Hispanic,06/22/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +52876,59737,54267,PRETRIAL,Chauncey,Martin,NULL,Male,Caucasian,06/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +52876,59737,54267,PRETRIAL,Chauncey,Martin,NULL,Male,Caucasian,06/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +52876,59737,54267,PRETRIAL,Chauncey,Martin,NULL,Male,Caucasian,06/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +52889,59758,54284,PRETRIAL,davis,john,NULL,Male,Caucasian,06/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/11/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +52889,59758,54284,PRETRIAL,davis,john,NULL,Male,Caucasian,06/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +52889,59758,54284,PRETRIAL,davis,john,NULL,Male,Caucasian,06/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52866,59727,54257,PRETRIAL,Pierre,Frantz,NULL,Male,African-American,12/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/11/13 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +52866,59727,54257,PRETRIAL,Pierre,Frantz,NULL,Male,African-American,12/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/11/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +52866,59727,54257,PRETRIAL,Pierre,Frantz,NULL,Male,African-American,12/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52861,59722,54252,PRETRIAL,Kerlew,Nicholas,Andew,Male,Other,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/11/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +52861,59722,54252,PRETRIAL,Kerlew,Nicholas,Andew,Male,Other,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +52861,59722,54252,PRETRIAL,Kerlew,Nicholas,Andew,Male,Other,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52874,59735,54265,Probation,Smith,Gary,Edward,Male,Caucasian,04/21/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/13 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +52874,59735,54265,Probation,Smith,Gary,Edward,Male,Caucasian,04/21/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +52874,59735,54265,Probation,Smith,Gary,Edward,Male,Caucasian,04/21/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52880,59748,54275,Probation,MCINTYRE,IAN,N,Male,Caucasian,12/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +52880,59748,54275,Probation,MCINTYRE,IAN,N,Male,Caucasian,12/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +52880,59748,54275,Probation,MCINTYRE,IAN,N,Male,Caucasian,12/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +52890,59759,54285,Probation,Lopez,Edward,Alan,Male,Hispanic,05/20/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +52890,59759,54285,Probation,Lopez,Edward,Alan,Male,Hispanic,05/20/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +52890,59759,54285,Probation,Lopez,Edward,Alan,Male,Hispanic,05/20/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52869,59730,54260,PRETRIAL,VICTOR,JULO,NULL,Male,Other,09/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +52869,59730,54260,PRETRIAL,VICTOR,JULO,NULL,Male,Other,09/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +52869,59730,54260,PRETRIAL,VICTOR,JULO,NULL,Male,Other,09/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51042,59743,52184,PRETRIAL,Taylor,Ebony,NULL,Female,African-American,01/12/87,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,4,High,7,Risk of Violence,-0.43,10,High,New,1,0 +51042,59743,52184,PRETRIAL,Taylor,Ebony,NULL,Female,African-American,01/12/87,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,4,High,8,Risk of Recidivism,0.22,8,High,New,1,0 +51042,59743,52184,PRETRIAL,Taylor,Ebony,NULL,Female,African-American,01/12/87,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52887,59756,54282,Probation,Gatz,Joseph,William,Male,Caucasian,11/12/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/11/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +52887,59756,54282,Probation,Gatz,Joseph,William,Male,Caucasian,11/12/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +52887,59756,54282,Probation,Gatz,Joseph,William,Male,Caucasian,11/12/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52863,59724,54254,PRETRIAL,FALS,VICTOR,MANUEL,Male,Caucasian,08/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/11/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +52863,59724,54254,PRETRIAL,FALS,VICTOR,MANUEL,Male,Caucasian,08/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/11/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +52863,59724,54254,PRETRIAL,FALS,VICTOR,MANUEL,Male,Caucasian,08/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52867,59728,54258,PRETRIAL,KANE,KYLE,KEITH,Male,Caucasian,06/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/11/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +52867,59728,54258,PRETRIAL,KANE,KYLE,KEITH,Male,Caucasian,06/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/11/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +52867,59728,54258,PRETRIAL,KANE,KYLE,KEITH,Male,Caucasian,06/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +19692,59745,54272,Probation,Davis,Lakia,Juianay,Female,African-American,08/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +19692,59745,54272,Probation,Davis,Lakia,Juianay,Female,African-American,08/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,9,High,New,1,0 +19692,59745,54272,Probation,Davis,Lakia,Juianay,Female,African-American,08/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +52870,59731,54261,PRETRIAL,BOHANNON,SHANE,NULL,Male,Caucasian,07/04/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +52870,59731,54261,PRETRIAL,BOHANNON,SHANE,NULL,Male,Caucasian,07/04/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +52870,59731,54261,PRETRIAL,BOHANNON,SHANE,NULL,Male,Caucasian,07/04/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52872,59733,54263,PRETRIAL,Oliver,Juan,NULL,Male,Hispanic,01/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +52872,59733,54263,PRETRIAL,Oliver,Juan,NULL,Male,Hispanic,01/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +52872,59733,54263,PRETRIAL,Oliver,Juan,NULL,Male,Hispanic,01/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52877,59740,54269,Probation,settle,barbara,NULL,Female,Caucasian,05/20/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/11/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +52877,59740,54269,Probation,settle,barbara,NULL,Female,Caucasian,05/20/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +52877,59740,54269,Probation,settle,barbara,NULL,Female,Caucasian,05/20/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52885,59754,54280,Probation,Santiago,Eric,NULL,Male,Hispanic,04/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +52885,59754,54280,Probation,Santiago,Eric,NULL,Male,Hispanic,04/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.77,10,High,New,1,0 +52885,59754,54280,Probation,Santiago,Eric,NULL,Male,Hispanic,04/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +24240,59742,54271,Probation,stern,samara,NULL,Female,Caucasian,10/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,2,Medium,7,Risk of Violence,-2.71,2,Low,New,1,0 +24240,59742,54271,Probation,stern,samara,NULL,Female,Caucasian,10/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,New,1,0 +24240,59742,54271,Probation,stern,samara,NULL,Female,Caucasian,10/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +15365,59744,30237,PRETRIAL,James,Donathan,Keith,Male,African-American,12/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,Copy,1,0 +15365,59744,30237,PRETRIAL,James,Donathan,Keith,Male,African-American,12/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,Copy,1,0 +15365,59744,30237,PRETRIAL,James,Donathan,Keith,Male,African-American,12/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +5798,59750,51770,PRETRIAL,LOMBARDI,ANGELO,NULL,Male,Caucasian,11/25/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,2,Medium,7,Risk of Violence,-2.81,2,Low,Copy,1,0 +5798,59750,51770,PRETRIAL,LOMBARDI,ANGELO,NULL,Male,Caucasian,11/25/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,Copy,1,0 +5798,59750,51770,PRETRIAL,LOMBARDI,ANGELO,NULL,Male,Caucasian,11/25/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +52860,59721,54251,PRETRIAL,Duarte,Douglas,E,Male,Hispanic,12/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/11/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +52860,59721,54251,PRETRIAL,Duarte,Douglas,E,Male,Hispanic,12/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +52860,59721,54251,PRETRIAL,Duarte,Douglas,E,Male,Hispanic,12/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52875,59736,54266,Probation,Riggins,Joe,NULL,Male,African-American,09/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +52875,59736,54266,Probation,Riggins,Joe,NULL,Male,African-American,09/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +52875,59736,54266,Probation,Riggins,Joe,NULL,Male,African-American,09/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +19579,59747,54274,PRETRIAL,Baker,Chad,NULL,Male,African-American,05/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,New,1,0 +19579,59747,54274,PRETRIAL,Baker,Chad,NULL,Male,African-American,05/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +19579,59747,54274,PRETRIAL,Baker,Chad,NULL,Male,African-American,05/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52865,59726,54256,PRETRIAL,jolly,jelissa,NULL,Female,African-American,10/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +52865,59726,54256,PRETRIAL,jolly,jelissa,NULL,Female,African-American,10/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +52865,59726,54256,PRETRIAL,jolly,jelissa,NULL,Female,African-American,10/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52883,59752,54278,PRETRIAL,baca,brandy,NULL,Female,Caucasian,04/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +52883,59752,54278,PRETRIAL,baca,brandy,NULL,Female,Caucasian,04/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +52883,59752,54278,PRETRIAL,baca,brandy,NULL,Female,Caucasian,04/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52873,59734,54264,PRETRIAL,bonilla,cony,NULL,Female,Hispanic,06/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +52873,59734,54264,PRETRIAL,bonilla,cony,NULL,Female,Hispanic,06/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +52873,59734,54264,PRETRIAL,bonilla,cony,NULL,Female,Hispanic,06/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52902,59773,54299,PRETRIAL,MTEI,EDWIN,SELESTIN,Male,African-American,06/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +52902,59773,54299,PRETRIAL,MTEI,EDWIN,SELESTIN,Male,African-American,06/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +52902,59773,54299,PRETRIAL,MTEI,EDWIN,SELESTIN,Male,African-American,06/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52909,59781,54306,DRRD,Headly,Lorraine,NULL,Female,Caucasian,07/19/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +52909,59781,54306,DRRD,Headly,Lorraine,NULL,Female,Caucasian,07/19/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +52909,59781,54306,DRRD,Headly,Lorraine,NULL,Female,Caucasian,07/19/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52891,59760,54286,PRETRIAL,Degiovanni,Dillon,NULL,Male,Caucasian,09/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +52891,59760,54286,PRETRIAL,Degiovanni,Dillon,NULL,Male,Caucasian,09/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +52891,59760,54286,PRETRIAL,Degiovanni,Dillon,NULL,Male,Caucasian,09/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52920,59794,54318,Probation,Valdez,Carlos,Lenin,Male,Hispanic,02/28/76,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +52920,59794,54318,Probation,Valdez,Carlos,Lenin,Male,Hispanic,02/28/76,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +52920,59794,54318,Probation,Valdez,Carlos,Lenin,Male,Hispanic,02/28/76,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52900,59771,54297,PRETRIAL,Jean,Willy,NULL,Male,Other,09/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +52900,59771,54297,PRETRIAL,Jean,Willy,NULL,Male,Other,09/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +52900,59771,54297,PRETRIAL,Jean,Willy,NULL,Male,Other,09/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52913,59786,54310,Probation,Nicodem,Thomas,NULL,Male,Caucasian,12/20/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +52913,59786,54310,Probation,Nicodem,Thomas,NULL,Male,Caucasian,12/20/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +52913,59786,54310,Probation,Nicodem,Thomas,NULL,Male,Caucasian,12/20/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52892,59763,54289,PRETRIAL,Burga,Alan,NULL,Male,Hispanic,01/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +52892,59763,54289,PRETRIAL,Burga,Alan,NULL,Male,Hispanic,01/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +52892,59763,54289,PRETRIAL,Burga,Alan,NULL,Male,Hispanic,01/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52907,59778,54304,PRETRIAL,downs,barry,NULL,Male,African-American,08/06/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +52907,59778,54304,PRETRIAL,downs,barry,NULL,Male,African-American,08/06/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +52907,59778,54304,PRETRIAL,downs,barry,NULL,Male,African-American,08/06/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52894,59765,54291,PRETRIAL,SCRIVEN,MARION,CORNELIUS,Male,African-American,06/08/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.1,1,Low,New,1,0 +52894,59765,54291,PRETRIAL,SCRIVEN,MARION,CORNELIUS,Male,African-American,06/08/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +52894,59765,54291,PRETRIAL,SCRIVEN,MARION,CORNELIUS,Male,African-American,06/08/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +52925,59799,54323,Probation,dancy,leon,NULL,Male,African-American,08/10/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +52925,59799,54323,Probation,dancy,leon,NULL,Male,African-American,08/10/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +52925,59799,54323,Probation,dancy,leon,NULL,Male,African-American,08/10/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52897,59768,54294,PRETRIAL,ROBERSON,ELLIOT,ANTHONY,Male,African-American,08/20/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.2,1,Low,New,1,0 +52897,59768,54294,PRETRIAL,ROBERSON,ELLIOT,ANTHONY,Male,African-American,08/20/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +52897,59768,54294,PRETRIAL,ROBERSON,ELLIOT,ANTHONY,Male,African-American,08/20/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52930,59803,54327,Probation,Osorto,Hector,Orlando,Male,Hispanic,06/13/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +52930,59803,54327,Probation,Osorto,Hector,Orlando,Male,Hispanic,06/13/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +52930,59803,54327,Probation,Osorto,Hector,Orlando,Male,Hispanic,06/13/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52904,59775,54301,PRETRIAL,TORRES,ISRAEL,JR,Male,Caucasian,01/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/12/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +52904,59775,54301,PRETRIAL,TORRES,ISRAEL,JR,Male,Caucasian,01/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/12/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +52904,59775,54301,PRETRIAL,TORRES,ISRAEL,JR,Male,Caucasian,01/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +15644,59782,24699,PRETRIAL,GRANT,CHAVON,G,Male,African-American,10/23/90,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,4,High,7,Risk of Violence,-0.35,10,High,Copy,1,0 +15644,59782,24699,PRETRIAL,GRANT,CHAVON,G,Male,African-American,10/23/90,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,4,High,8,Risk of Recidivism,0.88,10,High,Copy,1,0 +15644,59782,24699,PRETRIAL,GRANT,CHAVON,G,Male,African-American,10/23/90,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +41460,59789,54313,PRETRIAL,Santiago,Wilson,NULL,Male,Hispanic,11/01/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +41460,59789,54313,PRETRIAL,Santiago,Wilson,NULL,Male,Hispanic,11/01/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +41460,59789,54313,PRETRIAL,Santiago,Wilson,NULL,Male,Hispanic,11/01/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +15784,59761,54287,PRETRIAL,SANTANA,ALEXANDER,NULL,Male,African-American,05/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +15784,59761,54287,PRETRIAL,SANTANA,ALEXANDER,NULL,Male,African-American,05/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +15784,59761,54287,PRETRIAL,SANTANA,ALEXANDER,NULL,Male,African-American,05/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52922,59796,54320,Probation,Ruiz,Fidel,Duque,Male,Hispanic,10/03/88,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +52922,59796,54320,Probation,Ruiz,Fidel,Duque,Male,Hispanic,10/03/88,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +52922,59796,54320,Probation,Ruiz,Fidel,Duque,Male,Hispanic,10/03/88,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52895,59766,54292,PRETRIAL,BRYAN,ELVIS,NULL,Male,African-American,10/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,7,Risk of Violence,-2.65,2,Low,New,1,0 +52895,59766,54292,PRETRIAL,BRYAN,ELVIS,NULL,Male,African-American,10/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +52895,59766,54292,PRETRIAL,BRYAN,ELVIS,NULL,Male,African-American,10/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52911,59784,54308,Probation,Minotti,James,NULL,Male,Caucasian,03/04/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +52911,59784,54308,Probation,Minotti,James,NULL,Male,Caucasian,03/04/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +52911,59784,54308,Probation,Minotti,James,NULL,Male,Caucasian,03/04/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52917,59791,54315,Probation,Safaie,Bobak,Charles,Male,Caucasian,02/21/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +52917,59791,54315,Probation,Safaie,Bobak,Charles,Male,Caucasian,02/21/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +52917,59791,54315,Probation,Safaie,Bobak,Charles,Male,Caucasian,02/21/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52899,59770,54296,PRETRIAL,Toussaint,Johnny,NULL,Male,Other,11/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +52899,59770,54296,PRETRIAL,Toussaint,Johnny,NULL,Male,Other,11/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +52899,59770,54296,PRETRIAL,Toussaint,Johnny,NULL,Male,Other,11/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52914,59787,54311,PRETRIAL,Hutchinson,Jamelia,NULL,Female,Other,12/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,2,Medium,7,Risk of Violence,-1.33,7,Medium,New,1,0 +52914,59787,54311,PRETRIAL,Hutchinson,Jamelia,NULL,Female,Other,12/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +52914,59787,54311,PRETRIAL,Hutchinson,Jamelia,NULL,Female,Other,12/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +15098,59805,14445,PRETRIAL,Bailey,Jeffrey,NULL,Male,African-American,02/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,Copy,1,0 +15098,59805,14445,PRETRIAL,Bailey,Jeffrey,NULL,Male,African-American,02/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,Copy,1,0 +15098,59805,14445,PRETRIAL,Bailey,Jeffrey,NULL,Male,African-American,02/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,39,10,High,Copy,1,0 +52916,59790,54314,Probation,Polykronis,Mark,NULL,Male,Caucasian,09/28/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/12/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +52916,59790,54314,Probation,Polykronis,Mark,NULL,Male,Caucasian,09/28/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +52916,59790,54314,Probation,Polykronis,Mark,NULL,Male,Caucasian,09/28/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52906,59777,54303,PRETRIAL,brown,jermaine,NULL,Male,African-American,12/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +52906,59777,54303,PRETRIAL,brown,jermaine,NULL,Male,African-American,12/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,4,High,8,Risk of Recidivism,0.19,8,High,New,1,0 +52906,59777,54303,PRETRIAL,brown,jermaine,NULL,Male,African-American,12/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52924,59798,54322,PRETRIAL,gay,diamond,NULL,Female,Caucasian,02/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/12/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +52924,59798,54322,PRETRIAL,gay,diamond,NULL,Female,Caucasian,02/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/12/13 0:00,1,Low,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +52924,59798,54322,PRETRIAL,gay,diamond,NULL,Female,Caucasian,02/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +52898,59769,54295,PRETRIAL,Fowler,Gerard,NULL,Male,Other,04/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +52898,59769,54295,PRETRIAL,Fowler,Gerard,NULL,Male,Other,04/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +52898,59769,54295,PRETRIAL,Fowler,Gerard,NULL,Male,Other,04/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52901,59772,54298,PRETRIAL,Kirkland,Gary,NULL,Male,African-American,05/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +52901,59772,54298,PRETRIAL,Kirkland,Gary,NULL,Male,African-American,05/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +52901,59772,54298,PRETRIAL,Kirkland,Gary,NULL,Male,African-American,05/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52912,59785,54309,PRETRIAL,CASHES,MICHAEL,NULL,Male,Caucasian,05/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +52912,59785,54309,PRETRIAL,CASHES,MICHAEL,NULL,Male,Caucasian,05/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +52912,59785,54309,PRETRIAL,CASHES,MICHAEL,NULL,Male,Caucasian,05/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52893,59764,54290,PRETRIAL,TYLER,BRANDEN,NULL,Male,African-American,01/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,New,1,0 +52893,59764,54290,PRETRIAL,TYLER,BRANDEN,NULL,Male,African-American,01/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +52893,59764,54290,PRETRIAL,TYLER,BRANDEN,NULL,Male,African-American,01/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52919,59793,54317,Probation,halsey,james,NULL,Male,Caucasian,02/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +52919,59793,54317,Probation,halsey,james,NULL,Male,Caucasian,02/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +52919,59793,54317,Probation,halsey,james,NULL,Male,Caucasian,02/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52926,59800,54324,Probation,Gootam,Vinod,NULL,Male,Other,11/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +52926,59800,54324,Probation,Gootam,Vinod,NULL,Male,Other,11/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +52926,59800,54324,Probation,Gootam,Vinod,NULL,Male,Other,11/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +15644,59780,24699,PRETRIAL,GRANT,CHAVON,G,Male,African-American,10/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,4,High,7,Risk of Violence,-0.35,10,High,Copy,1,0 +15644,59780,24699,PRETRIAL,GRANT,CHAVON,G,Male,African-American,10/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,4,High,8,Risk of Recidivism,0.88,10,High,Copy,1,0 +15644,59780,24699,PRETRIAL,GRANT,CHAVON,G,Male,African-American,10/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +52927,59801,54325,PRETRIAL,Peterson,Tierra,NULL,Female,African-American,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +52927,59801,54325,PRETRIAL,Peterson,Tierra,NULL,Female,African-American,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +52927,59801,54325,PRETRIAL,Peterson,Tierra,NULL,Female,African-American,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +52932,59806,54329,PRETRIAL,Ramos,William,NULL,Male,African-American,12/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +52932,59806,54329,PRETRIAL,Ramos,William,NULL,Male,African-American,12/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +52932,59806,54329,PRETRIAL,Ramos,William,NULL,Male,African-American,12/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52910,59783,54307,PRETRIAL,MILLER,MIKHAIL,LEONARD,Male,African-American,10/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-1,-1,N/A,New,1,0 +52910,59783,54307,PRETRIAL,MILLER,MIKHAIL,LEONARD,Male,African-American,10/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +52910,59783,54307,PRETRIAL,MILLER,MIKHAIL,LEONARD,Male,African-American,10/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +2160,59762,54288,PRETRIAL,MOODY,JORDAN,J,Male,African-American,11/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,4,High,7,Risk of Violence,-0.63,9,High,New,1,0 +2160,59762,54288,PRETRIAL,MOODY,JORDAN,J,Male,African-American,11/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,4,High,8,Risk of Recidivism,0.44,9,High,New,1,0 +2160,59762,54288,PRETRIAL,MOODY,JORDAN,J,Male,African-American,11/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52908,59779,54305,PRETRIAL,ADELPHON,NASHLEY,NULL,Female,African-American,10/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +52908,59779,54305,PRETRIAL,ADELPHON,NASHLEY,NULL,Female,African-American,10/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +52908,59779,54305,PRETRIAL,ADELPHON,NASHLEY,NULL,Female,African-American,10/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52915,59788,54312,PRETRIAL,Solomon,Kelvin,NULL,Male,African-American,12/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +52915,59788,54312,PRETRIAL,Solomon,Kelvin,NULL,Male,African-American,12/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +52915,59788,54312,PRETRIAL,Solomon,Kelvin,NULL,Male,African-American,12/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52921,59795,54319,PRETRIAL,Orta,Alba,Naomi,Female,Hispanic,11/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +52921,59795,54319,PRETRIAL,Orta,Alba,Naomi,Female,Hispanic,11/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,8,High,New,1,0 +52921,59795,54319,PRETRIAL,Orta,Alba,Naomi,Female,Hispanic,11/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52923,59797,54321,Probation,montese,simon,NULL,Male,African-American,02/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +52923,59797,54321,Probation,montese,simon,NULL,Male,African-American,02/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +52923,59797,54321,Probation,montese,simon,NULL,Male,African-American,02/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52896,59767,54293,PRETRIAL,ADDERLEY,JAMEAL,NULL,Male,African-American,08/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +52896,59767,54293,PRETRIAL,ADDERLEY,JAMEAL,NULL,Male,African-American,08/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +52896,59767,54293,PRETRIAL,ADDERLEY,JAMEAL,NULL,Male,African-American,08/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52903,59774,54300,PRETRIAL,Harris,Reginald,NULL,Male,African-American,08/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +52903,59774,54300,PRETRIAL,Harris,Reginald,NULL,Male,African-American,08/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +52903,59774,54300,PRETRIAL,Harris,Reginald,NULL,Male,African-American,08/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52905,59776,54302,PRETRIAL,MANZUETA,FELIX,ARNALDO,Male,Hispanic,09/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +52905,59776,54302,PRETRIAL,MANZUETA,FELIX,ARNALDO,Male,Hispanic,09/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +52905,59776,54302,PRETRIAL,MANZUETA,FELIX,ARNALDO,Male,Hispanic,09/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52931,59804,54328,Probation,brooks,leonard,NULL,Male,African-American,05/28/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +52931,59804,54328,Probation,brooks,leonard,NULL,Male,African-American,05/28/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +52931,59804,54328,Probation,brooks,leonard,NULL,Male,African-American,05/28/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52969,59853,54371,PRETRIAL,Crenshaw,Bernard,NULL,Male,African-American,02/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/13/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +52969,59853,54371,PRETRIAL,Crenshaw,Bernard,NULL,Male,African-American,02/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/13/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +52969,59853,54371,PRETRIAL,Crenshaw,Bernard,NULL,Male,African-American,02/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52942,59825,54344,Probation,Harper,Janet,Denise,Male,African-American,10/26/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +52942,59825,54344,Probation,Harper,Janet,Denise,Male,African-American,10/26/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +52942,59825,54344,Probation,Harper,Janet,Denise,Male,African-American,10/26/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +22086,59832,54351,PRETRIAL,THOMAS,KAKEEN,NULL,Female,African-American,08/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +22086,59832,54351,PRETRIAL,THOMAS,KAKEEN,NULL,Female,African-American,08/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,8,High,New,1,0 +22086,59832,54351,PRETRIAL,THOMAS,KAKEEN,NULL,Female,African-American,08/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +52958,59839,54358,PRETRIAL,BONHOMETRE,KERVIN,NULL,Male,African-American,07/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +52958,59839,54358,PRETRIAL,BONHOMETRE,KERVIN,NULL,Male,African-American,07/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +52958,59839,54358,PRETRIAL,BONHOMETRE,KERVIN,NULL,Male,African-American,07/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52964,59846,54364,Probation,Oliphat,Stacey,NULL,Female,African-American,02/10/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +52964,59846,54364,Probation,Oliphat,Stacey,NULL,Female,African-American,02/10/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/13 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +52964,59846,54364,Probation,Oliphat,Stacey,NULL,Female,African-American,02/10/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +15638,59809,54332,PRETRIAL,DUNHAM,THOMAS,J,Male,African-American,07/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +15638,59809,54332,PRETRIAL,DUNHAM,THOMAS,J,Male,African-American,07/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +15638,59809,54332,PRETRIAL,DUNHAM,THOMAS,J,Male,African-American,07/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52951,59834,54353,PRETRIAL,PAUL,TROY,NULL,Male,African-American,08/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +52951,59834,54353,PRETRIAL,PAUL,TROY,NULL,Male,African-American,08/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +52951,59834,54353,PRETRIAL,PAUL,TROY,NULL,Male,African-American,08/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52966,59848,54366,PRETRIAL,MORENO,CHRISTOPHER,NULL,Male,Caucasian,03/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/13/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +52966,59848,54366,PRETRIAL,MORENO,CHRISTOPHER,NULL,Male,Caucasian,03/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/13/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +52966,59848,54366,PRETRIAL,MORENO,CHRISTOPHER,NULL,Male,Caucasian,03/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +5023,59813,4705,PRETRIAL,Nicholls,Grantley,hengrick,Male,African-American,06/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,Copy,1,0 +5023,59813,4705,PRETRIAL,Nicholls,Grantley,hengrick,Male,African-American,06/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.09,10,High,Copy,1,0 +5023,59813,4705,PRETRIAL,Nicholls,Grantley,hengrick,Male,African-American,06/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +52948,59830,54349,Probation,Mellard,Anthony,Raymond,Male,Caucasian,01/21/56,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/13/13 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +52948,59830,54349,Probation,Mellard,Anthony,Raymond,Male,Caucasian,01/21/56,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/13/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +52948,59830,54349,Probation,Mellard,Anthony,Raymond,Male,Caucasian,01/21/56,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52968,59851,54369,Probation,Buncome,Ray,NULL,Male,African-American,10/18/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +52968,59851,54369,Probation,Buncome,Ray,NULL,Male,African-American,10/18/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +52968,59851,54369,Probation,Buncome,Ray,NULL,Male,African-American,10/18/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52933,59808,54331,PRETRIAL,Holness,Teresa-Marie,NULL,Female,African-American,01/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +52933,59808,54331,PRETRIAL,Holness,Teresa-Marie,NULL,Female,African-American,01/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +52933,59808,54331,PRETRIAL,Holness,Teresa-Marie,NULL,Female,African-American,01/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52961,59842,54361,Probation,pluff,cindy,NULL,Female,Caucasian,11/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.41,3,Low,New,1,0 +52961,59842,54361,Probation,pluff,cindy,NULL,Female,Caucasian,11/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,9,High,New,1,0 +52961,59842,54361,Probation,pluff,cindy,NULL,Female,Caucasian,11/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52947,59829,54348,PRETRIAL,BENNETT,TERESA,NULL,Male,Caucasian,05/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/13/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +52947,59829,54348,PRETRIAL,BENNETT,TERESA,NULL,Male,Caucasian,05/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/13/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +52947,59829,54348,PRETRIAL,BENNETT,TERESA,NULL,Male,Caucasian,05/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52937,59814,54336,PRETRIAL,DECOLINE,SAMUEL,JOHN,Male,African-American,10/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +52937,59814,54336,PRETRIAL,DECOLINE,SAMUEL,JOHN,Male,African-American,10/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +52937,59814,54336,PRETRIAL,DECOLINE,SAMUEL,JOHN,Male,African-American,10/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52962,59843,54362,Probation,Bolton,Melinda,NULL,Female,Caucasian,08/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.14,4,Low,New,1,0 +52962,59843,54362,Probation,Bolton,Melinda,NULL,Female,Caucasian,08/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.1,8,High,New,1,0 +52962,59843,54362,Probation,Bolton,Melinda,NULL,Female,Caucasian,08/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52940,59821,54341,Probation,caraballo,julio,NULL,Male,Hispanic,06/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +52940,59821,54341,Probation,caraballo,julio,NULL,Male,Hispanic,06/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +52940,59821,54341,Probation,caraballo,julio,NULL,Male,Hispanic,06/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +48900,59822,49653,PRETRIAL,FIELDS,ANTHONY,NULL,Male,Caucasian,02/20/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/13/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,Copy,1,0 +48900,59822,49653,PRETRIAL,FIELDS,ANTHONY,NULL,Male,Caucasian,02/20/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/13/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,Copy,1,0 +48900,59822,49653,PRETRIAL,FIELDS,ANTHONY,NULL,Male,Caucasian,02/20/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +52952,59835,54354,PRETRIAL,MENELAS,TRACY,NULL,Female,African-American,04/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +52952,59835,54354,PRETRIAL,MENELAS,TRACY,NULL,Female,African-American,04/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-1.61,2,Low,New,1,0 +52952,59835,54354,PRETRIAL,MENELAS,TRACY,NULL,Female,African-American,04/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52956,59837,54356,Probation,Wynter,Kalonji,NULL,Male,African-American,05/19/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,2,Medium,7,Risk of Violence,-2.71,2,Low,New,1,0 +52956,59837,54356,Probation,Wynter,Kalonji,NULL,Male,African-American,05/19/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +52956,59837,54356,Probation,Wynter,Kalonji,NULL,Male,African-American,05/19/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52938,59816,54338,Probation,Jennings,Sandy,Ross,Male,Caucasian,01/18/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/13/13 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +52938,59816,54338,Probation,Jennings,Sandy,Ross,Male,Caucasian,01/18/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/13/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +52938,59816,54338,Probation,Jennings,Sandy,Ross,Male,Caucasian,01/18/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/13/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +52935,59811,54334,PRETRIAL,Steven,Carcana,NULL,Male,Hispanic,12/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/13/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +52935,59811,54334,PRETRIAL,Steven,Carcana,NULL,Male,Hispanic,12/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/13/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +52935,59811,54334,PRETRIAL,Steven,Carcana,NULL,Male,Hispanic,12/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52943,59824,54343,Probation,Corbitt,Tyler,NULL,Male,Caucasian,05/04/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +52943,59824,54343,Probation,Corbitt,Tyler,NULL,Male,Caucasian,05/04/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +52943,59824,54343,Probation,Corbitt,Tyler,NULL,Male,Caucasian,05/04/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +52957,59838,54357,PRETRIAL,DORVIL,DEVIN,NULL,Male,African-American,06/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +52957,59838,54357,PRETRIAL,DORVIL,DEVIN,NULL,Male,African-American,06/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +52957,59838,54357,PRETRIAL,DORVIL,DEVIN,NULL,Male,African-American,06/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +46272,59852,54370,PRETRIAL,Willard,James,NULL,Male,Caucasian,05/09/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +46272,59852,54370,PRETRIAL,Willard,James,NULL,Male,Caucasian,05/09/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +46272,59852,54370,PRETRIAL,Willard,James,NULL,Male,Caucasian,05/09/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +52965,59847,54365,Probation,Wright,tionette,NULL,Female,African-American,05/08/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +52965,59847,54365,Probation,Wright,tionette,NULL,Female,African-American,05/08/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +52965,59847,54365,Probation,Wright,tionette,NULL,Female,African-American,05/08/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52939,59817,54339,DRRD,Burgess,Voltaire,NULL,Male,African-American,07/25/73,17,All Scales,Intake,English,Other,Pretrial Defendant,Single,3/13/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +52939,59817,54339,DRRD,Burgess,Voltaire,NULL,Male,African-American,07/25/73,17,All Scales,Intake,English,Other,Pretrial Defendant,Single,3/13/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +52939,59817,54339,DRRD,Burgess,Voltaire,NULL,Male,African-American,07/25/73,17,All Scales,Intake,English,Other,Pretrial Defendant,Single,3/13/13 0:00,4,High,18,Risk of Failure to Appear,36,10,High,New,1,0 +52944,59826,54345,Probation,Louisjacques,wood,NULL,Male,African-American,03/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +52944,59826,54345,Probation,Louisjacques,wood,NULL,Male,African-American,03/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +52944,59826,54345,Probation,Louisjacques,wood,NULL,Male,African-American,03/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52934,59810,54333,PRETRIAL,Shand,Rodrick,NULL,Male,African-American,01/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +52934,59810,54333,PRETRIAL,Shand,Rodrick,NULL,Male,African-American,01/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +52934,59810,54333,PRETRIAL,Shand,Rodrick,NULL,Male,African-American,01/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52936,59812,54335,PRETRIAL,Simmons,Gregory,NULL,Male,African-American,09/22/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +52936,59812,54335,PRETRIAL,Simmons,Gregory,NULL,Male,African-American,09/22/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +52936,59812,54335,PRETRIAL,Simmons,Gregory,NULL,Male,African-American,09/22/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52949,59831,54350,Probation,SMITH,DARRELL,NULL,Male,African-American,11/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +52949,59831,54350,Probation,SMITH,DARRELL,NULL,Male,African-American,11/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +52949,59831,54350,Probation,SMITH,DARRELL,NULL,Male,African-American,11/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52950,59833,54352,PRETRIAL,Dunbar,Janelle,NULL,Female,Caucasian,10/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +52950,59833,54352,PRETRIAL,Dunbar,Janelle,NULL,Female,Caucasian,10/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +52950,59833,54352,PRETRIAL,Dunbar,Janelle,NULL,Female,Caucasian,10/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52959,59840,54359,Probation,achille,vladimir,NULL,Male,African-American,08/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/13 0:00,2,Medium,7,Risk of Violence,-2.74,2,Low,New,1,0 +52959,59840,54359,Probation,achille,vladimir,NULL,Male,African-American,08/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +52959,59840,54359,Probation,achille,vladimir,NULL,Male,African-American,08/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +29099,59854,54372,PRETRIAL,Carswell,Ellis,NULL,Male,African-American,08/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +29099,59854,54372,PRETRIAL,Carswell,Ellis,NULL,Male,African-American,08/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,4,High,8,Risk of Recidivism,0.31,9,High,New,1,0 +29099,59854,54372,PRETRIAL,Carswell,Ellis,NULL,Male,African-American,08/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52953,59836,54355,PRETRIAL,PETER,MICHAEL,NULL,Male,African-American,01/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +52953,59836,54355,PRETRIAL,PETER,MICHAEL,NULL,Male,African-American,01/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +52953,59836,54355,PRETRIAL,PETER,MICHAEL,NULL,Male,African-American,01/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +15317,59807,54330,PRETRIAL,Wyatt,Trabazo,Antonio,Male,Caucasian,09/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +15317,59807,54330,PRETRIAL,Wyatt,Trabazo,Antonio,Male,Caucasian,09/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +15317,59807,54330,PRETRIAL,Wyatt,Trabazo,Antonio,Male,Caucasian,09/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52946,59828,54347,PRETRIAL,Santibanez-Cruz,Sergio,NULL,Male,Hispanic,09/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/13/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +52946,59828,54347,PRETRIAL,Santibanez-Cruz,Sergio,NULL,Male,Hispanic,09/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/13/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +52946,59828,54347,PRETRIAL,Santibanez-Cruz,Sergio,NULL,Male,Hispanic,09/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +45763,59815,54337,PRETRIAL,Mann,Larry,NULL,Male,African-American,08/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +45763,59815,54337,PRETRIAL,Mann,Larry,NULL,Male,African-American,08/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +45763,59815,54337,PRETRIAL,Mann,Larry,NULL,Male,African-American,08/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52967,59849,54367,Probation,irvin,kendal,NULL,Male,African-American,07/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +52967,59849,54367,Probation,irvin,kendal,NULL,Male,African-American,07/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +52967,59849,54367,Probation,irvin,kendal,NULL,Male,African-American,07/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52941,59823,54342,PRETRIAL,Pierce,Arthur,NULL,Male,Caucasian,05/13/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/13/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +52941,59823,54342,PRETRIAL,Pierce,Arthur,NULL,Male,Caucasian,05/13/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/13/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +52941,59823,54342,PRETRIAL,Pierce,Arthur,NULL,Male,Caucasian,05/13/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52960,59841,54360,Probation,sanchez,leticia,NULL,Female,Caucasian,11/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +52960,59841,54360,Probation,sanchez,leticia,NULL,Female,Caucasian,11/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +52960,59841,54360,Probation,sanchez,leticia,NULL,Female,Caucasian,11/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52437,59820,53741,PRETRIAL,Marold,Andrew,J,Male,Caucasian,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/13 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,Copy,1,0 +52437,59820,53741,PRETRIAL,Marold,Andrew,J,Male,Caucasian,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,Copy,1,0 +52437,59820,53741,PRETRIAL,Marold,Andrew,J,Male,Caucasian,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +52982,59870,54386,PRETRIAL,White,Carmen,NULL,Female,African-American,11/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,2,Medium,7,Risk of Violence,-3.05,1,Low,New,1,0 +52982,59870,54386,PRETRIAL,White,Carmen,NULL,Female,African-American,11/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +52982,59870,54386,PRETRIAL,White,Carmen,NULL,Female,African-American,11/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52950,59883,54352,PRETRIAL,Dunbar,Janelle,NULL,Female,Caucasian,10/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,Copy,1,0 +52950,59883,54352,PRETRIAL,Dunbar,Janelle,NULL,Female,Caucasian,10/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,Copy,1,0 +52950,59883,54352,PRETRIAL,Dunbar,Janelle,NULL,Female,Caucasian,10/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +30353,59862,54379,PRETRIAL,Allen,Atare,NULL,Male,African-American,03/08/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/14/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +30353,59862,54379,PRETRIAL,Allen,Atare,NULL,Male,African-American,03/08/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/14/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +30353,59862,54379,PRETRIAL,Allen,Atare,NULL,Male,African-American,03/08/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52974,59857,54375,PRETRIAL,Roberts,Jordan,NULL,Male,African-American,10/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +52974,59857,54375,PRETRIAL,Roberts,Jordan,NULL,Male,African-American,10/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +52974,59857,54375,PRETRIAL,Roberts,Jordan,NULL,Male,African-American,10/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52984,59872,54388,PRETRIAL,VALENZUELA,JORGE,A,Female,Caucasian,10/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +52984,59872,54388,PRETRIAL,VALENZUELA,JORGE,A,Female,Caucasian,10/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +52984,59872,54388,PRETRIAL,VALENZUELA,JORGE,A,Female,Caucasian,10/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +45924,59885,54400,PRETRIAL,Salamanca,Avisay,NULL,Male,Hispanic,08/09/65,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/14/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +45924,59885,54400,PRETRIAL,Salamanca,Avisay,NULL,Male,Hispanic,08/09/65,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/14/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +45924,59885,54400,PRETRIAL,Salamanca,Avisay,NULL,Male,Hispanic,08/09/65,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52992,59886,54401,Probation,Caraballo,Nelson,NULL,Male,Hispanic,09/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +52992,59886,54401,Probation,Caraballo,Nelson,NULL,Male,Hispanic,09/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +52992,59886,54401,Probation,Caraballo,Nelson,NULL,Male,Hispanic,09/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52977,59865,54381,Probation,Mobley,Christopher,NULL,Male,Caucasian,12/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/14/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +52977,59865,54381,Probation,Mobley,Christopher,NULL,Male,Caucasian,12/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/14/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +52977,59865,54381,Probation,Mobley,Christopher,NULL,Male,Caucasian,12/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52988,59878,54394,Probation,elizalde,Joaquin,NULL,Male,Hispanic,08/17/71,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/14/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +52988,59878,54394,Probation,elizalde,Joaquin,NULL,Male,Hispanic,08/17/71,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/14/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +52988,59878,54394,Probation,elizalde,Joaquin,NULL,Male,Hispanic,08/17/71,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52989,59880,54396,Probation,rose,tonya,NULL,Female,Caucasian,10/25/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +52989,59880,54396,Probation,rose,tonya,NULL,Female,Caucasian,10/25/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +52989,59880,54396,Probation,rose,tonya,NULL,Female,Caucasian,10/25/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +52980,59868,54384,PRETRIAL,Edwards,Kelvin,Jamal,Male,African-American,07/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +52980,59868,54384,PRETRIAL,Edwards,Kelvin,Jamal,Male,African-American,07/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +52980,59868,54384,PRETRIAL,Edwards,Kelvin,Jamal,Male,African-American,07/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52986,59875,54391,Probation,flores,steven,NULL,Male,Caucasian,06/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/14/13 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +52986,59875,54391,Probation,flores,steven,NULL,Male,Caucasian,06/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +52986,59875,54391,Probation,flores,steven,NULL,Male,Caucasian,06/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/14/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +38527,59882,54398,PRETRIAL,Mcelroy,Robert,NULL,Male,Caucasian,07/23/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +38527,59882,54398,PRETRIAL,Mcelroy,Robert,NULL,Male,Caucasian,07/23/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +38527,59882,54398,PRETRIAL,Mcelroy,Robert,NULL,Male,Caucasian,07/23/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52456,59861,53761,PRETRIAL,CONAHAN,ASHLEY,NULL,Female,Caucasian,10/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,Copy,1,0 +52456,59861,53761,PRETRIAL,CONAHAN,ASHLEY,NULL,Female,Caucasian,10/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,Copy,1,0 +52456,59861,53761,PRETRIAL,CONAHAN,ASHLEY,NULL,Female,Caucasian,10/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +52970,59856,54374,PRETRIAL,Wright,Jeffery,NULL,Male,African-American,11/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.44,3,Low,New,1,0 +52970,59856,54374,PRETRIAL,Wright,Jeffery,NULL,Male,African-American,11/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +52970,59856,54374,PRETRIAL,Wright,Jeffery,NULL,Male,African-American,11/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +31536,59859,54377,PRETRIAL,Williams,Glenn,NULL,Male,African-American,03/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +31536,59859,54377,PRETRIAL,Williams,Glenn,NULL,Male,African-American,03/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.81,10,High,New,1,0 +31536,59859,54377,PRETRIAL,Williams,Glenn,NULL,Male,African-American,03/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52975,59858,54376,PRETRIAL,Denis,Christopher,Sergo,Male,African-American,01/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +52975,59858,54376,PRETRIAL,Denis,Christopher,Sergo,Male,African-American,01/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +52975,59858,54376,PRETRIAL,Denis,Christopher,Sergo,Male,African-American,01/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +25207,59879,54395,PRETRIAL,Sutton,Andrew,NULL,Male,Caucasian,11/18/88,17,All Scales,Intake,English,Pretrial,Probation,Single,3/14/13 0:00,4,High,7,Risk of Violence,-0.92,9,High,New,1,0 +25207,59879,54395,PRETRIAL,Sutton,Andrew,NULL,Male,Caucasian,11/18/88,17,All Scales,Intake,English,Pretrial,Probation,Single,3/14/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +25207,59879,54395,PRETRIAL,Sutton,Andrew,NULL,Male,Caucasian,11/18/88,17,All Scales,Intake,English,Pretrial,Probation,Single,3/14/13 0:00,4,High,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +52991,59884,54399,PRETRIAL,MARTINEZ,DOMINGO,NULL,Male,Hispanic,08/04/57,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +52991,59884,54399,PRETRIAL,MARTINEZ,DOMINGO,NULL,Male,Hispanic,08/04/57,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +52991,59884,54399,PRETRIAL,MARTINEZ,DOMINGO,NULL,Male,Hispanic,08/04/57,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +52993,59887,54402,Probation,Anderson,Blair,NULL,Male,Caucasian,05/01/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/14/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +52993,59887,54402,Probation,Anderson,Blair,NULL,Male,Caucasian,05/01/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/14/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +52993,59887,54402,Probation,Anderson,Blair,NULL,Male,Caucasian,05/01/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +49437,59863,50783,PRETRIAL,Davis,Daquan,Anthony,Male,African-American,04/11/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,4,High,7,Risk of Violence,-0.65,9,High,Copy,1,0 +49437,59863,50783,PRETRIAL,Davis,Daquan,Anthony,Male,African-American,04/11/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,4,High,8,Risk of Recidivism,0.84,10,High,Copy,1,0 +49437,59863,50783,PRETRIAL,Davis,Daquan,Anthony,Male,African-American,04/11/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +52990,59881,54397,Probation,Martin,Glenda,NULL,Female,African-American,01/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +52990,59881,54397,Probation,Martin,Glenda,NULL,Female,African-American,01/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +52990,59881,54397,Probation,Martin,Glenda,NULL,Female,African-American,01/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +36306,59860,54378,Probation,Rudzik,Thomas,NULL,Male,Caucasian,01/27/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/14/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +36306,59860,54378,Probation,Rudzik,Thomas,NULL,Male,Caucasian,01/27/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/14/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +36306,59860,54378,Probation,Rudzik,Thomas,NULL,Male,Caucasian,01/27/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52976,59864,54380,PRETRIAL,anderson,terrance,NULL,Male,African-American,07/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +52976,59864,54380,PRETRIAL,anderson,terrance,NULL,Male,African-American,07/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.38,10,High,New,1,0 +52976,59864,54380,PRETRIAL,anderson,terrance,NULL,Male,African-American,07/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +50308,59855,54373,PRETRIAL,Wilson,Kadeem,NULL,Male,African-American,09/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +50308,59855,54373,PRETRIAL,Wilson,Kadeem,NULL,Male,African-American,09/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +50308,59855,54373,PRETRIAL,Wilson,Kadeem,NULL,Male,African-American,09/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52981,59869,54385,Probation,Williams,Wayne,Anthony,Male,African-American,12/25/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/14/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +52981,59869,54385,Probation,Williams,Wayne,Anthony,Male,African-American,12/25/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/14/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +52981,59869,54385,Probation,Williams,Wayne,Anthony,Male,African-American,12/25/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52979,59867,54383,Probation,Perez,Gerardo,NULL,Male,Hispanic,03/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +52979,59867,54383,Probation,Perez,Gerardo,NULL,Male,Hispanic,03/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +52979,59867,54383,Probation,Perez,Gerardo,NULL,Male,Hispanic,03/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52985,59874,54390,PRETRIAL,Cajilus,Frenel,NULL,Male,Caucasian,06/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/14/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +52985,59874,54390,PRETRIAL,Cajilus,Frenel,NULL,Male,Caucasian,06/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/14/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +52985,59874,54390,PRETRIAL,Cajilus,Frenel,NULL,Male,Caucasian,06/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +37521,59876,54392,Probation,Artiga,Louis,NULL,Male,Caucasian,06/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +37521,59876,54392,Probation,Artiga,Louis,NULL,Male,Caucasian,06/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.7,10,High,New,1,0 +37521,59876,54392,Probation,Artiga,Louis,NULL,Male,Caucasian,06/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52999,59895,54409,PRETRIAL,Luke,Dewayne,M,Male,African-American,10/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +52999,59895,54409,PRETRIAL,Luke,Dewayne,M,Male,African-American,10/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,4,High,8,Risk of Recidivism,0.42,9,High,New,1,0 +52999,59895,54409,PRETRIAL,Luke,Dewayne,M,Male,African-American,10/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53001,59897,54411,PRETRIAL,Smith,Anthony,NULL,Male,African-American,07/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.56,2,Low,New,1,0 +53001,59897,54411,PRETRIAL,Smith,Anthony,NULL,Male,African-American,07/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,New,1,0 +53001,59897,54411,PRETRIAL,Smith,Anthony,NULL,Male,African-American,07/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53010,59904,54418,PRETRIAL,TAYLOR,TREVANT,ANTONIO,Male,African-American,03/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,7,Risk of Violence,-1.28,7,Medium,New,1,0 +53010,59904,54418,PRETRIAL,TAYLOR,TREVANT,ANTONIO,Male,African-American,03/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +53010,59904,54418,PRETRIAL,TAYLOR,TREVANT,ANTONIO,Male,African-American,03/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53008,59902,54416,PRETRIAL,Corallo,Vincent,NULL,Male,Caucasian,03/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +53008,59902,54416,PRETRIAL,Corallo,Vincent,NULL,Male,Caucasian,03/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +53008,59902,54416,PRETRIAL,Corallo,Vincent,NULL,Male,Caucasian,03/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51943,59890,53194,PRETRIAL,Wright,Franklin,NULL,Male,African-American,03/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,Copy,1,0 +51943,59890,53194,PRETRIAL,Wright,Franklin,NULL,Male,African-American,03/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,Copy,1,0 +51943,59890,53194,PRETRIAL,Wright,Franklin,NULL,Male,African-American,03/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +53014,59908,54422,Probation,Cole,Robert,NULL,Male,Caucasian,11/30/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/15/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +53014,59908,54422,Probation,Cole,Robert,NULL,Male,Caucasian,11/30/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/15/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +53014,59908,54422,Probation,Cole,Robert,NULL,Male,Caucasian,11/30/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53006,59900,54414,PRETRIAL,HILL,RODALE,TIMAY,Male,African-American,09/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +53006,59900,54414,PRETRIAL,HILL,RODALE,TIMAY,Male,African-American,09/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +53006,59900,54414,PRETRIAL,HILL,RODALE,TIMAY,Male,African-American,09/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53011,59905,54419,Probation,Lock,Leland,Matthew,Male,Caucasian,02/23/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/15/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +53011,59905,54419,Probation,Lock,Leland,Matthew,Male,Caucasian,02/23/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/15/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +53011,59905,54419,Probation,Lock,Leland,Matthew,Male,Caucasian,02/23/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +19347,20112,18588,PRETRIAL,Richardson,Demetrius,NULL,Male,Caucasian,03/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +19347,20112,18588,PRETRIAL,Richardson,Demetrius,NULL,Male,Caucasian,03/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +19347,20112,18588,PRETRIAL,Richardson,Demetrius,NULL,Male,Caucasian,03/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52997,59892,54406,PRETRIAL,Bossier,Jamon,NULL,Male,African-American,01/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +52997,59892,54406,PRETRIAL,Bossier,Jamon,NULL,Male,African-American,01/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +52997,59892,54406,PRETRIAL,Bossier,Jamon,NULL,Male,African-American,01/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53004,59898,54412,PRETRIAL,Tisdale,Issac,NULL,Male,African-American,10/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +53004,59898,54412,PRETRIAL,Tisdale,Issac,NULL,Male,African-American,10/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +53004,59898,54412,PRETRIAL,Tisdale,Issac,NULL,Male,African-American,10/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +46313,59894,54408,Probation,KARM,DIANE,NULL,Female,Caucasian,08/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/15/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +46313,59894,54408,Probation,KARM,DIANE,NULL,Female,Caucasian,08/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/15/13 0:00,1,Low,8,Risk of Recidivism,-1.61,2,Low,New,1,0 +46313,59894,54408,Probation,KARM,DIANE,NULL,Female,Caucasian,08/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53018,59912,54426,PRETRIAL,Cook,Bobby,NULL,Male,Caucasian,08/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +53018,59912,54426,PRETRIAL,Cook,Bobby,NULL,Male,Caucasian,08/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +53018,59912,54426,PRETRIAL,Cook,Bobby,NULL,Male,Caucasian,08/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53015,59910,54424,Probation,Simprevail,Winsky,NULL,Male,African-American,08/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/15/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +53015,59910,54424,Probation,Simprevail,Winsky,NULL,Male,African-American,08/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/15/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +53015,59910,54424,Probation,Simprevail,Winsky,NULL,Male,African-American,08/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52995,59889,54404,PRETRIAL,Dean,Lamonte,NULL,Male,African-American,11/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,4,High,7,Risk of Violence,-0.72,9,High,New,1,0 +52995,59889,54404,PRETRIAL,Dean,Lamonte,NULL,Male,African-American,11/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,4,High,8,Risk of Recidivism,0.74,10,High,New,1,0 +52995,59889,54404,PRETRIAL,Dean,Lamonte,NULL,Male,African-American,11/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53009,59903,54417,PRETRIAL,Holloway,Michael,NULL,Male,Caucasian,01/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +53009,59903,54417,PRETRIAL,Holloway,Michael,NULL,Male,Caucasian,01/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +53009,59903,54417,PRETRIAL,Holloway,Michael,NULL,Male,Caucasian,01/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53005,59899,54413,PRETRIAL,JEANBAPTISTE,CHANDLER,NULL,Male,African-American,11/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +53005,59899,54413,PRETRIAL,JEANBAPTISTE,CHANDLER,NULL,Male,African-American,11/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,4,High,8,Risk of Recidivism,0.77,10,High,New,1,0 +53005,59899,54413,PRETRIAL,JEANBAPTISTE,CHANDLER,NULL,Male,African-American,11/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53007,59901,54415,PRETRIAL,GALAVOTTI,MARK,NULL,Male,Caucasian,10/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/15/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +53007,59901,54415,PRETRIAL,GALAVOTTI,MARK,NULL,Male,Caucasian,10/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/15/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +53007,59901,54415,PRETRIAL,GALAVOTTI,MARK,NULL,Male,Caucasian,10/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53012,59906,54420,PRETRIAL,Baptiste,minouche,NULL,Female,African-American,11/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/15/13 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +53012,59906,54420,PRETRIAL,Baptiste,minouche,NULL,Female,African-American,11/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,7,Medium,New,1,0 +53012,59906,54420,PRETRIAL,Baptiste,minouche,NULL,Female,African-American,11/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/15/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52998,59893,54407,PRETRIAL,Pearson,Brain,NULL,Male,Caucasian,09/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/15/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +52998,59893,54407,PRETRIAL,Pearson,Brain,NULL,Male,Caucasian,09/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/15/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +52998,59893,54407,PRETRIAL,Pearson,Brain,NULL,Male,Caucasian,09/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53000,59896,54410,PRETRIAL,Pazgarcia,Kevin,NULL,Male,Caucasian,02/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +53000,59896,54410,PRETRIAL,Pazgarcia,Kevin,NULL,Male,Caucasian,02/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +53000,59896,54410,PRETRIAL,Pazgarcia,Kevin,NULL,Male,Caucasian,02/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +36015,59888,54403,PRETRIAL,Uragavidal,Orranda,NULL,Male,Hispanic,09/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +36015,59888,54403,PRETRIAL,Uragavidal,Orranda,NULL,Male,Hispanic,09/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +36015,59888,54403,PRETRIAL,Uragavidal,Orranda,NULL,Male,Hispanic,09/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52996,59891,54405,PRETRIAL,Zackery,Dominic,NULL,Male,African-American,09/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +52996,59891,54405,PRETRIAL,Zackery,Dominic,NULL,Male,African-American,09/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +52996,59891,54405,PRETRIAL,Zackery,Dominic,NULL,Male,African-American,09/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53016,59909,54423,Probation,Jpohnson,Andre,NULL,Male,African-American,01/13/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/15/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +53016,59909,54423,Probation,Jpohnson,Andre,NULL,Male,African-American,01/13/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/15/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +53016,59909,54423,Probation,Jpohnson,Andre,NULL,Male,African-American,01/13/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/15/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +3294,59917,3008,PRETRIAL,manning,kenneth,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,4,High,7,Risk of Violence,-1.18,8,High,Copy,1,0 +3294,59917,3008,PRETRIAL,manning,kenneth,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,4,High,8,Risk of Recidivism,0.74,10,High,Copy,1,0 +3294,59917,3008,PRETRIAL,manning,kenneth,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +53023,59922,54434,PRETRIAL,COLON,RICKY,GAMIEL,Male,Caucasian,02/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/16/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +53023,59922,54434,PRETRIAL,COLON,RICKY,GAMIEL,Male,Caucasian,02/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/16/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +53023,59922,54434,PRETRIAL,COLON,RICKY,GAMIEL,Male,Caucasian,02/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53020,59914,54428,PRETRIAL,Mitchell,Sam,NULL,Male,Caucasian,07/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +53020,59914,54428,PRETRIAL,Mitchell,Sam,NULL,Male,Caucasian,07/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +53020,59914,54428,PRETRIAL,Mitchell,Sam,NULL,Male,Caucasian,07/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +8832,59927,8366,PRETRIAL,JOSEPH,NORMAN,NULL,Male,Other,06/13/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,Copy,1,0 +8832,59927,8366,PRETRIAL,JOSEPH,NORMAN,NULL,Male,Other,06/13/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,Copy,1,0 +8832,59927,8366,PRETRIAL,JOSEPH,NORMAN,NULL,Male,Other,06/13/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +51324,59915,52507,PRETRIAL,Toussaint,Carl,NULL,Male,African-American,09/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,Copy,1,0 +51324,59915,52507,PRETRIAL,Toussaint,Carl,NULL,Male,African-American,09/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,Copy,1,0 +51324,59915,52507,PRETRIAL,Toussaint,Carl,NULL,Male,African-American,09/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +28921,59924,27944,PRETRIAL,Tokay,John,NULL,Male,Caucasian,08/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/16/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,Copy,1,0 +28921,59924,27944,PRETRIAL,Tokay,John,NULL,Male,Caucasian,08/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/16/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,Copy,1,0 +28921,59924,27944,PRETRIAL,Tokay,John,NULL,Male,Caucasian,08/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +36178,59919,54431,PRETRIAL,Phan,Trung,NULL,Male,Asian,05/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +36178,59919,54431,PRETRIAL,Phan,Trung,NULL,Male,Asian,05/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +36178,59919,54431,PRETRIAL,Phan,Trung,NULL,Male,Asian,05/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +53019,59913,54427,PRETRIAL,Zevolo,James,NULL,Male,Hispanic,12/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +53019,59913,54427,PRETRIAL,Zevolo,James,NULL,Male,Hispanic,12/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +53019,59913,54427,PRETRIAL,Zevolo,James,NULL,Male,Hispanic,12/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52238,59921,54433,PRETRIAL,Fialkowsky,Kristine,NULL,Male,Caucasian,05/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +52238,59921,54433,PRETRIAL,Fialkowsky,Kristine,NULL,Male,Caucasian,05/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +52238,59921,54433,PRETRIAL,Fialkowsky,Kristine,NULL,Male,Caucasian,05/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53022,59920,54432,PRETRIAL,Wright,Shameka,NULL,Female,African-American,06/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +53022,59920,54432,PRETRIAL,Wright,Shameka,NULL,Female,African-American,06/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +53022,59920,54432,PRETRIAL,Wright,Shameka,NULL,Female,African-American,06/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53021,59916,54429,PRETRIAL,HOWARD,JULIUS,MICHAEL,Male,African-American,01/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.27,3,Low,New,1,0 +53021,59916,54429,PRETRIAL,HOWARD,JULIUS,MICHAEL,Male,African-American,01/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +53021,59916,54429,PRETRIAL,HOWARD,JULIUS,MICHAEL,Male,African-American,01/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +43829,59923,43853,PRETRIAL,SANMARCO,ANTHONY,NULL,Male,Caucasian,03/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,3/16/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,Copy,1,0 +43829,59923,43853,PRETRIAL,SANMARCO,ANTHONY,NULL,Male,Caucasian,03/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,3/16/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,Copy,1,0 +43829,59923,43853,PRETRIAL,SANMARCO,ANTHONY,NULL,Male,Caucasian,03/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,3/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +27194,59918,54430,DRRD,Vixama,Franki,NULL,Male,Other,07/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,4,High,7,Risk of Violence,-0.43,10,High,New,1,0 +27194,59918,54430,DRRD,Vixama,Franki,NULL,Male,Other,07/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,4,High,8,Risk of Recidivism,0.79,10,High,New,1,0 +27194,59918,54430,DRRD,Vixama,Franki,NULL,Male,Other,07/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53024,59925,54435,PRETRIAL,Welly,Dylan,NULL,Male,Caucasian,04/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +53024,59925,54435,PRETRIAL,Welly,Dylan,NULL,Male,Caucasian,04/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +53024,59925,54435,PRETRIAL,Welly,Dylan,NULL,Male,Caucasian,04/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +24152,59932,23337,Probation,Golding,Douglas,George,Male,African-American,05/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,Copy,1,0 +24152,59932,23337,Probation,Golding,Douglas,George,Male,African-American,05/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,Copy,1,0 +24152,59932,23337,Probation,Golding,Douglas,George,Male,African-American,05/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +53033,59939,54446,PRETRIAL,Thorpe,Leighton,NULL,Male,Other,09/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/17/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +53033,59939,54446,PRETRIAL,Thorpe,Leighton,NULL,Male,Other,09/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/17/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +53033,59939,54446,PRETRIAL,Thorpe,Leighton,NULL,Male,Other,09/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53031,59937,54444,PRETRIAL,Smith,Andre,NULL,Male,African-American,04/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +53031,59937,54444,PRETRIAL,Smith,Andre,NULL,Male,African-American,04/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +53031,59937,54444,PRETRIAL,Smith,Andre,NULL,Male,African-American,04/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53030,59936,54443,PRETRIAL,HORTON,EDWARD,CORROL,Male,African-American,11/01/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +53030,59936,54443,PRETRIAL,HORTON,EDWARD,CORROL,Male,African-American,11/01/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +53030,59936,54443,PRETRIAL,HORTON,EDWARD,CORROL,Male,African-American,11/01/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53026,59929,54438,PRETRIAL,Jarbour,Joseph,NULL,Male,Caucasian,09/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +53026,59929,54438,PRETRIAL,Jarbour,Joseph,NULL,Male,Caucasian,09/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/13 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +53026,59929,54438,PRETRIAL,Jarbour,Joseph,NULL,Male,Caucasian,09/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53029,59934,54442,PRETRIAL,Parra,Stephen,NULL,Male,African-American,04/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +53029,59934,54442,PRETRIAL,Parra,Stephen,NULL,Male,African-American,04/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +53029,59934,54442,PRETRIAL,Parra,Stephen,NULL,Male,African-American,04/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53025,59928,54437,PRETRIAL,Comesana,Korim,NULL,Female,Caucasian,01/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +53025,59928,54437,PRETRIAL,Comesana,Korim,NULL,Female,Caucasian,01/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +53025,59928,54437,PRETRIAL,Comesana,Korim,NULL,Female,Caucasian,01/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53027,59931,54440,PRETRIAL,STFLEUR,BERMAN,NULL,Male,African-American,02/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +53027,59931,54440,PRETRIAL,STFLEUR,BERMAN,NULL,Male,African-American,02/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +53027,59931,54440,PRETRIAL,STFLEUR,BERMAN,NULL,Male,African-American,02/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53028,59933,54441,PRETRIAL,FERNANDO,CHRISTOPHER,NULL,Male,African-American,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +53028,59933,54441,PRETRIAL,FERNANDO,CHRISTOPHER,NULL,Male,African-American,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +53028,59933,54441,PRETRIAL,FERNANDO,CHRISTOPHER,NULL,Male,African-American,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53034,59940,54447,PRETRIAL,Carrasco,Cynthia,NULL,Female,Caucasian,01/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/13 0:00,2,Medium,7,Risk of Violence,-2.69,2,Low,New,1,0 +53034,59940,54447,PRETRIAL,Carrasco,Cynthia,NULL,Female,Caucasian,01/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +53034,59940,54447,PRETRIAL,Carrasco,Cynthia,NULL,Female,Caucasian,01/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +27121,59935,26232,PRETRIAL,Lopez,Mason,Ernest,Male,Hispanic,10/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,Copy,1,0 +27121,59935,26232,PRETRIAL,Lopez,Mason,Ernest,Male,Hispanic,10/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,Copy,1,0 +27121,59935,26232,PRETRIAL,Lopez,Mason,Ernest,Male,Hispanic,10/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +51845,59930,54439,PRETRIAL,RAYSOR,ROGER,ALEXANDER,Male,African-American,01/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/17/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +51845,59930,54439,PRETRIAL,RAYSOR,ROGER,ALEXANDER,Male,African-American,01/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +51845,59930,54439,PRETRIAL,RAYSOR,ROGER,ALEXANDER,Male,African-American,01/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/17/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +46130,59938,54445,PRETRIAL,KOLBJORNSEN,STEVE,NULL,Male,African-American,12/12/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +46130,59938,54445,PRETRIAL,KOLBJORNSEN,STEVE,NULL,Male,African-American,12/12/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +46130,59938,54445,PRETRIAL,KOLBJORNSEN,STEVE,NULL,Male,African-American,12/12/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/13 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +53057,59969,54473,Probation,Bauer,charles,M,Male,Caucasian,08/21/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/18/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +53057,59969,54473,Probation,Bauer,charles,M,Male,Caucasian,08/21/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/18/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +53057,59969,54473,Probation,Bauer,charles,M,Male,Caucasian,08/21/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53040,59948,54455,PRETRIAL,FROST,PHILLIP,BERNARD,Male,African-American,04/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +53040,59948,54455,PRETRIAL,FROST,PHILLIP,BERNARD,Male,African-American,04/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +53040,59948,54455,PRETRIAL,FROST,PHILLIP,BERNARD,Male,African-American,04/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53049,59959,54465,PRETRIAL,GOMEZ,PHILLIP,NULL,Male,Caucasian,05/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +53049,59959,54465,PRETRIAL,GOMEZ,PHILLIP,NULL,Male,Caucasian,05/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +53049,59959,54465,PRETRIAL,GOMEZ,PHILLIP,NULL,Male,Caucasian,05/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53053,59964,54469,Probation,Fajardo,David,A,Male,Hispanic,02/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/18/13 0:00,2,Medium,7,Risk of Violence,-2.7,2,Low,New,1,0 +53053,59964,54469,Probation,Fajardo,David,A,Male,Hispanic,02/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +53053,59964,54469,Probation,Fajardo,David,A,Male,Hispanic,02/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/18/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53064,59977,54481,PRETRIAL,Isaac,Erika,Jesscia,Female,African-American,06/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,2,Medium,7,Risk of Violence,-2.45,3,Low,New,1,0 +53064,59977,54481,PRETRIAL,Isaac,Erika,Jesscia,Female,African-American,06/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,7,Medium,New,1,0 +53064,59977,54481,PRETRIAL,Isaac,Erika,Jesscia,Female,African-American,06/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +27354,59951,54458,PRETRIAL,nelson,mackenson,NULL,Male,African-American,09/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +27354,59951,54458,PRETRIAL,nelson,mackenson,NULL,Male,African-American,09/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +27354,59951,54458,PRETRIAL,nelson,mackenson,NULL,Male,African-American,09/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53046,59956,54463,PRETRIAL,Bastian,Julian,NULL,Male,Other,02/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +53046,59956,54463,PRETRIAL,Bastian,Julian,NULL,Male,Other,02/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +53046,59956,54463,PRETRIAL,Bastian,Julian,NULL,Male,Other,02/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +2986,59985,54489,PRETRIAL,MCCLAIN,SHAUN,TAVIS,Male,Caucasian,12/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +2986,59985,54489,PRETRIAL,MCCLAIN,SHAUN,TAVIS,Male,Caucasian,12/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +2986,59985,54489,PRETRIAL,MCCLAIN,SHAUN,TAVIS,Male,Caucasian,12/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51258,59990,52431,Probation,AMORUSO,STEVEN,A,Male,Caucasian,03/20/62,17,All Scales,Intake,English,Conditional Release,Probation,Separated,3/18/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +51258,59990,52431,Probation,AMORUSO,STEVEN,A,Male,Caucasian,03/20/62,17,All Scales,Intake,English,Conditional Release,Probation,Separated,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.27,1,Low,New,1,0 +51258,59990,52431,Probation,AMORUSO,STEVEN,A,Male,Caucasian,03/20/62,17,All Scales,Intake,English,Conditional Release,Probation,Separated,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +53067,59980,54484,PRETRIAL,Uva,Brian,NULL,Male,Caucasian,02/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +53067,59980,54484,PRETRIAL,Uva,Brian,NULL,Male,Caucasian,02/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +53067,59980,54484,PRETRIAL,Uva,Brian,NULL,Male,Caucasian,02/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53059,59972,54476,Probation,Jacoboeleuterio,Luis,Miguel,Male,Hispanic,01/28/91,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/18/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +53059,59972,54476,Probation,Jacoboeleuterio,Luis,Miguel,Male,Hispanic,01/28/91,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/18/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +53059,59972,54476,Probation,Jacoboeleuterio,Luis,Miguel,Male,Hispanic,01/28/91,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53036,59943,54450,PRETRIAL,SINGLETARY,ROSCOE,T,Male,African-American,07/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +53036,59943,54450,PRETRIAL,SINGLETARY,ROSCOE,T,Male,African-American,07/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +53036,59943,54450,PRETRIAL,SINGLETARY,ROSCOE,T,Male,African-American,07/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53074,59993,54493,Probation,Stambul,David,NULL,Male,Caucasian,08/14/48,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/18/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +53074,59993,54493,Probation,Stambul,David,NULL,Male,Caucasian,08/14/48,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/18/13 0:00,1,Low,8,Risk of Recidivism,-2.73,1,Low,New,1,0 +53074,59993,54493,Probation,Stambul,David,NULL,Male,Caucasian,08/14/48,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53051,59961,54467,Probation,Burdge,Sharon,NULL,Female,Caucasian,01/14/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/18/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +53051,59961,54467,Probation,Burdge,Sharon,NULL,Female,Caucasian,01/14/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/18/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +53051,59961,54467,Probation,Burdge,Sharon,NULL,Female,Caucasian,01/14/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +17175,59954,54461,PRETRIAL,Bispham,Darasan,Joel,Male,African-American,05/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/18/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +17175,59954,54461,PRETRIAL,Bispham,Darasan,Joel,Male,African-American,05/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +17175,59954,54461,PRETRIAL,Bispham,Darasan,Joel,Male,African-American,05/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/18/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +49240,59989,50052,Probation,GARWOOD,TAMOY,S,Female,African-American,12/23/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +49240,59989,50052,Probation,GARWOOD,TAMOY,S,Female,African-American,12/23/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-0.54,5,Medium,New,1,0 +49240,59989,50052,Probation,GARWOOD,TAMOY,S,Female,African-American,12/23/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +53056,59968,54472,PRETRIAL,Kemp,Richard,NULL,Male,African-American,08/27/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,4,High,7,Risk of Violence,-0.97,9,High,New,1,0 +53056,59968,54472,PRETRIAL,Kemp,Richard,NULL,Male,African-American,08/27/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +53056,59968,54472,PRETRIAL,Kemp,Richard,NULL,Male,African-American,08/27/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,4,High,18,Risk of Failure to Appear,45,10,High,New,1,0 +53062,59975,54479,Probation,telcine,milene,NULL,Female,African-American,08/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +53062,59975,54479,Probation,telcine,milene,NULL,Female,African-American,08/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +53062,59975,54479,Probation,telcine,milene,NULL,Female,African-American,08/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53069,59982,54486,Probation,DELLAPORTA,MARY,E,Female,Caucasian,10/16/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/18/13 0:00,1,Low,7,Risk of Violence,-4.45,1,Low,New,1,0 +53069,59982,54486,Probation,DELLAPORTA,MARY,E,Female,Caucasian,10/16/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/18/13 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +53069,59982,54486,Probation,DELLAPORTA,MARY,E,Female,Caucasian,10/16/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53038,59945,54452,PRETRIAL,Sofer,Richard,NULL,Male,Caucasian,12/24/35,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/13 0:00,1,Low,7,Risk of Violence,-4.63,1,Low,New,1,0 +53038,59945,54452,PRETRIAL,Sofer,Richard,NULL,Male,Caucasian,12/24/35,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/13 0:00,1,Low,8,Risk of Recidivism,-2.96,1,Low,New,1,0 +53038,59945,54452,PRETRIAL,Sofer,Richard,NULL,Male,Caucasian,12/24/35,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53076,59996,54496,Probation,Davey,Mark,S,Male,Caucasian,06/28/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/18/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +53076,59996,54496,Probation,Davey,Mark,S,Male,Caucasian,06/28/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +53076,59996,54496,Probation,Davey,Mark,S,Male,Caucasian,06/28/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53041,59949,54456,PRETRIAL,Rolle,Forlisha,Tabitha,Female,Other,09/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +53041,59949,54456,PRETRIAL,Rolle,Forlisha,Tabitha,Female,Other,09/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +53041,59949,54456,PRETRIAL,Rolle,Forlisha,Tabitha,Female,Other,09/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +17167,59970,54474,PRETRIAL,SAMAROO,JONATHAN,NULL,Male,Other,09/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/18/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +17167,59970,54474,PRETRIAL,SAMAROO,JONATHAN,NULL,Male,Other,09/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/18/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +17167,59970,54474,PRETRIAL,SAMAROO,JONATHAN,NULL,Male,Other,09/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +38704,59987,38160,PRETRIAL,Noel,Ronny,NULL,Male,African-American,09/22/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/18/13 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +38704,59987,38160,PRETRIAL,Noel,Ronny,NULL,Male,African-American,09/22/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/18/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +38704,59987,38160,PRETRIAL,Noel,Ronny,NULL,Male,African-American,09/22/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/18/13 0:00,4,High,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +53070,59984,54488,Probation,stephenson,stefan,NULL,Male,African-American,12/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +53070,59984,54488,Probation,stephenson,stefan,NULL,Male,African-American,12/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +53070,59984,54488,Probation,stephenson,stefan,NULL,Male,African-American,12/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +48227,59991,48904,PRETRIAL,Francisco,Rudolfo,NULL,Male,Hispanic,07/06/81,17,All Scales,Intake,English,Post Sentence,Probation,Separated,3/18/13 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +48227,59991,48904,PRETRIAL,Francisco,Rudolfo,NULL,Male,Hispanic,07/06/81,17,All Scales,Intake,English,Post Sentence,Probation,Separated,3/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,6,Medium,New,1,0 +48227,59991,48904,PRETRIAL,Francisco,Rudolfo,NULL,Male,Hispanic,07/06/81,17,All Scales,Intake,English,Post Sentence,Probation,Separated,3/18/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +53060,59973,54477,Probation,GODRIDGE,JANET,E,Female,Caucasian,07/13/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/18/13 0:00,1,Low,7,Risk of Violence,-4.27,1,Low,New,1,0 +53060,59973,54477,Probation,GODRIDGE,JANET,E,Female,Caucasian,07/13/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/18/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +53060,59973,54477,Probation,GODRIDGE,JANET,E,Female,Caucasian,07/13/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53043,59952,54459,PRETRIAL,HARVEY,CHARLES,MIQUEL,Male,African-American,04/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.99,4,Low,New,1,0 +53043,59952,54459,PRETRIAL,HARVEY,CHARLES,MIQUEL,Male,African-American,04/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,New,1,0 +53043,59952,54459,PRETRIAL,HARVEY,CHARLES,MIQUEL,Male,African-American,04/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53045,59955,54462,PRETRIAL,JARDINE,BRENT,NULL,Male,Caucasian,10/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +53045,59955,54462,PRETRIAL,JARDINE,BRENT,NULL,Male,Caucasian,10/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +53045,59955,54462,PRETRIAL,JARDINE,BRENT,NULL,Male,Caucasian,10/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53039,59947,54454,PRETRIAL,ROLLE,DELRETA,NULL,Female,African-American,02/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/18/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +53039,59947,54454,PRETRIAL,ROLLE,DELRETA,NULL,Female,African-American,02/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/18/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +53039,59947,54454,PRETRIAL,ROLLE,DELRETA,NULL,Female,African-American,02/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53068,59981,54485,PRETRIAL,SOLTAU,VICTORIA,NULL,Female,Caucasian,09/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +53068,59981,54485,PRETRIAL,SOLTAU,VICTORIA,NULL,Female,Caucasian,09/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +53068,59981,54485,PRETRIAL,SOLTAU,VICTORIA,NULL,Female,Caucasian,09/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +53075,59994,54494,PRETRIAL,McClain,Edward,NULL,Male,African-American,09/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/18/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +53075,59994,54494,PRETRIAL,McClain,Edward,NULL,Male,African-American,09/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +53075,59994,54494,PRETRIAL,McClain,Edward,NULL,Male,African-American,09/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53050,59960,54466,Probation,griffin,roderick,NULL,Male,African-American,11/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.42,3,Low,New,1,0 +53050,59960,54466,Probation,griffin,roderick,NULL,Male,African-American,11/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +53050,59960,54466,Probation,griffin,roderick,NULL,Male,African-American,11/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53037,59944,54451,PRETRIAL,Collier,Trena,NULL,Female,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/18/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +53037,59944,54451,PRETRIAL,Collier,Trena,NULL,Female,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +53037,59944,54451,PRETRIAL,Collier,Trena,NULL,Female,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53065,59978,54482,PRETRIAL,Chidsey,Jeffrey,NULL,Male,Caucasian,11/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +53065,59978,54482,PRETRIAL,Chidsey,Jeffrey,NULL,Male,Caucasian,11/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +53065,59978,54482,PRETRIAL,Chidsey,Jeffrey,NULL,Male,Caucasian,11/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53054,59965,54470,Probation,staab,benjamin,NULL,Male,Caucasian,06/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +53054,59965,54470,Probation,staab,benjamin,NULL,Male,Caucasian,06/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +53054,59965,54470,Probation,staab,benjamin,NULL,Male,Caucasian,06/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53058,59971,54475,Probation,mitchnick,kelly,NULL,Female,Caucasian,01/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.28,3,Low,New,1,0 +53058,59971,54475,Probation,mitchnick,kelly,NULL,Female,Caucasian,01/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,8,High,New,1,0 +53058,59971,54475,Probation,mitchnick,kelly,NULL,Female,Caucasian,01/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +53042,59950,54457,PRETRIAL,Elliott,Donovan,NULL,Male,Other,10/17/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +53042,59950,54457,PRETRIAL,Elliott,Donovan,NULL,Male,Other,10/17/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +53042,59950,54457,PRETRIAL,Elliott,Donovan,NULL,Male,Other,10/17/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53047,59957,54464,Probation,Rogers,Charles,NULL,Male,Caucasian,12/13/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/18/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +53047,59957,54464,Probation,Rogers,Charles,NULL,Male,Caucasian,12/13/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +53047,59957,54464,Probation,Rogers,Charles,NULL,Male,Caucasian,12/13/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +40225,59988,54491,PRETRIAL,Martinez,Luis,Daniel,Male,Caucasian,09/24/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/18/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +40225,59988,54491,PRETRIAL,Martinez,Luis,Daniel,Male,Caucasian,09/24/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +40225,59988,54491,PRETRIAL,Martinez,Luis,Daniel,Male,Caucasian,09/24/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +46593,59941,54448,PRETRIAL,Parris,Bernard,NULL,Male,African-American,03/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,4,High,7,Risk of Violence,-0.41,10,High,New,1,0 +46593,59941,54448,PRETRIAL,Parris,Bernard,NULL,Male,African-American,03/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +46593,59941,54448,PRETRIAL,Parris,Bernard,NULL,Male,African-American,03/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52512,59958,53833,PRETRIAL,SMITH,YOLANDA,NULL,Female,African-American,03/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,Copy,1,0 +52512,59958,53833,PRETRIAL,SMITH,YOLANDA,NULL,Female,African-American,03/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,Copy,1,0 +52512,59958,53833,PRETRIAL,SMITH,YOLANDA,NULL,Female,African-American,03/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +53073,59992,54492,Probation,BUTLER,SHAQUILLE,ONEAL,Male,African-American,07/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/18/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +53073,59992,54492,Probation,BUTLER,SHAQUILLE,ONEAL,Male,African-American,07/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/18/13 0:00,4,High,8,Risk of Recidivism,1.09,10,High,New,1,0 +53073,59992,54492,Probation,BUTLER,SHAQUILLE,ONEAL,Male,African-American,07/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/18/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +53052,59962,54468,PRETRIAL,Pardo,Isaac,NULL,Male,Hispanic,01/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +53052,59962,54468,PRETRIAL,Pardo,Isaac,NULL,Male,Hispanic,01/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +53052,59962,54468,PRETRIAL,Pardo,Isaac,NULL,Male,Hispanic,01/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53066,59979,54483,PRETRIAL,Gray,Isaac,Devon,Male,African-American,04/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +53066,59979,54483,PRETRIAL,Gray,Isaac,Devon,Male,African-American,04/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +53066,59979,54483,PRETRIAL,Gray,Isaac,Devon,Male,African-American,04/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53044,59953,54460,PRETRIAL,Abukablan,Khalid,NULL,Male,Arabic,10/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +53044,59953,54460,PRETRIAL,Abukablan,Khalid,NULL,Male,Arabic,10/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +53044,59953,54460,PRETRIAL,Abukablan,Khalid,NULL,Male,Arabic,10/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +43041,59946,54453,PRETRIAL,Sykes,Tiffany,NULL,Female,Caucasian,07/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/18/13 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +43041,59946,54453,PRETRIAL,Sykes,Tiffany,NULL,Female,Caucasian,07/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +43041,59946,54453,PRETRIAL,Sykes,Tiffany,NULL,Female,Caucasian,07/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/18/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +22126,59995,54495,Probation,Barreto,Xavier,NULL,Male,African-American,03/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +22126,59995,54495,Probation,Barreto,Xavier,NULL,Male,African-American,03/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +22126,59995,54495,Probation,Barreto,Xavier,NULL,Male,African-American,03/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53055,59967,54471,Broward County,Felix,Jacqueline,NULL,Female,Hispanic,02/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +53055,59967,54471,Broward County,Felix,Jacqueline,NULL,Female,Hispanic,02/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +53055,59967,54471,Broward County,Felix,Jacqueline,NULL,Female,Hispanic,02/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53061,59974,54478,PRETRIAL,HUMPHERIES,GARLAND,NULL,Male,African-American,11/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +53061,59974,54478,PRETRIAL,HUMPHERIES,GARLAND,NULL,Male,African-American,11/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +53061,59974,54478,PRETRIAL,HUMPHERIES,GARLAND,NULL,Male,African-American,11/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53063,59976,54480,PRETRIAL,Caton,Wade,NULL,Male,African-American,07/27/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/18/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +53063,59976,54480,PRETRIAL,Caton,Wade,NULL,Male,African-American,07/27/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/18/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +53063,59976,54480,PRETRIAL,Caton,Wade,NULL,Male,African-American,07/27/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +43420,59997,43363,PRETRIAL,Brown,Stephen,NULL,Male,African-American,04/25/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +43420,59997,43363,PRETRIAL,Brown,Stephen,NULL,Male,African-American,04/25/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,Copy,1,0 +43420,59997,43363,PRETRIAL,Brown,Stephen,NULL,Male,African-American,04/25/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +11191,60046,10711,PRETRIAL,SAWYER,SCOTT,NULL,Male,Caucasian,05/22/90,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,3/19/13 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +11191,60046,10711,PRETRIAL,SAWYER,SCOTT,NULL,Male,Caucasian,05/22/90,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,3/19/13 0:00,4,High,8,Risk of Recidivism,1.24,10,High,New,1,0 +11191,60046,10711,PRETRIAL,SAWYER,SCOTT,NULL,Male,Caucasian,05/22/90,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,3/19/13 0:00,4,High,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +53081,60004,54502,PRETRIAL,Soto,Ruben,NULL,Male,Caucasian,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/19/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +53081,60004,54502,PRETRIAL,Soto,Ruben,NULL,Male,Caucasian,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +53081,60004,54502,PRETRIAL,Soto,Ruben,NULL,Male,Caucasian,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/19/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +43285,60025,54522,PRETRIAL,GIRON,LAURA,NULL,Female,Caucasian,12/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +43285,60025,54522,PRETRIAL,GIRON,LAURA,NULL,Female,Caucasian,12/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +43285,60025,54522,PRETRIAL,GIRON,LAURA,NULL,Female,Caucasian,12/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53102,60032,54529,Probation,bolanosbauer,lilia,NULL,Female,Caucasian,09/16/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +53102,60032,54529,Probation,bolanosbauer,lilia,NULL,Female,Caucasian,09/16/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +53102,60032,54529,Probation,bolanosbauer,lilia,NULL,Female,Caucasian,09/16/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53090,60013,54511,PRETRIAL,Flores,Jose,Miguel,Male,Hispanic,12/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +53090,60013,54511,PRETRIAL,Flores,Jose,Miguel,Male,Hispanic,12/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +53090,60013,54511,PRETRIAL,Flores,Jose,Miguel,Male,Hispanic,12/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +15935,60030,54527,Probation,RAYA,JESSE,JOSEPH,Male,Caucasian,12/07/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +15935,60030,54527,Probation,RAYA,JESSE,JOSEPH,Male,Caucasian,12/07/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +15935,60030,54527,Probation,RAYA,JESSE,JOSEPH,Male,Caucasian,12/07/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53086,60009,54507,PRETRIAL,TARR,ANDREW,IAN,Male,Caucasian,06/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,4,High,7,Risk of Violence,-0.58,10,High,New,1,0 +53086,60009,54507,PRETRIAL,TARR,ANDREW,IAN,Male,Caucasian,06/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,4,High,8,Risk of Recidivism,1.1,10,High,New,1,0 +53086,60009,54507,PRETRIAL,TARR,ANDREW,IAN,Male,Caucasian,06/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53116,60048,54543,Probation,Giron,Juan,Miguel,Male,Hispanic,05/18/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/19/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +53116,60048,54543,Probation,Giron,Juan,Miguel,Male,Hispanic,05/18/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +53116,60048,54543,Probation,Giron,Juan,Miguel,Male,Hispanic,05/18/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53084,60007,54505,PRETRIAL,Lamarche,Renee,NULL,Female,Caucasian,02/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/19/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +53084,60007,54505,PRETRIAL,Lamarche,Renee,NULL,Female,Caucasian,02/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/19/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +53084,60007,54505,PRETRIAL,Lamarche,Renee,NULL,Female,Caucasian,02/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +42424,60036,54533,PRETRIAL,Beedle,Daniel,Joseph,Male,Caucasian,09/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +42424,60036,54533,PRETRIAL,Beedle,Daniel,Joseph,Male,Caucasian,09/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +42424,60036,54533,PRETRIAL,Beedle,Daniel,Joseph,Male,Caucasian,09/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53077,59999,54497,PRETRIAL,Richardson,Devin,Detrell,Male,African-American,08/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +53077,59999,54497,PRETRIAL,Richardson,Devin,Detrell,Male,African-American,08/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +53077,59999,54497,PRETRIAL,Richardson,Devin,Detrell,Male,African-American,08/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52410,60044,53708,Probation,Bernier,Erik,NULL,Male,Caucasian,06/26/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +52410,60044,53708,Probation,Bernier,Erik,NULL,Male,Caucasian,06/26/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +52410,60044,53708,Probation,Bernier,Erik,NULL,Male,Caucasian,06/26/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +53117,60049,54544,Probation,Simpson,Daniese,NULL,Male,African-American,01/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +53117,60049,54544,Probation,Simpson,Daniese,NULL,Male,African-American,01/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +53117,60049,54544,Probation,Simpson,Daniese,NULL,Male,African-American,01/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +40950,60028,54525,PRETRIAL,GIBSON,POLLY,NULL,Female,Caucasian,01/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +40950,60028,54525,PRETRIAL,GIBSON,POLLY,NULL,Female,Caucasian,01/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +40950,60028,54525,PRETRIAL,GIBSON,POLLY,NULL,Female,Caucasian,01/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53079,60002,54500,PRETRIAL,Mitchell,Michael,Shayne,Male,African-American,05/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +53079,60002,54500,PRETRIAL,Mitchell,Michael,Shayne,Male,African-American,05/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +53079,60002,54500,PRETRIAL,Mitchell,Michael,Shayne,Male,African-American,05/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53097,60020,54518,Probation,drakas,debra,NULL,Female,Caucasian,11/08/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,2,Medium,7,Risk of Violence,-3.69,1,Low,New,1,0 +53097,60020,54518,Probation,drakas,debra,NULL,Female,Caucasian,11/08/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +53097,60020,54518,Probation,drakas,debra,NULL,Female,Caucasian,11/08/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +35755,60023,54520,PRETRIAL,Miller,Kay,NULL,Female,Caucasian,03/30/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/19/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +35755,60023,54520,PRETRIAL,Miller,Kay,NULL,Female,Caucasian,03/30/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/19/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +35755,60023,54520,PRETRIAL,Miller,Kay,NULL,Female,Caucasian,03/30/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +4495,60041,54538,PRETRIAL,Ortzsik,Christian,Curtis,Male,Caucasian,05/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,New,1,0 +4495,60041,54538,PRETRIAL,Ortzsik,Christian,Curtis,Male,Caucasian,05/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +4495,60041,54538,PRETRIAL,Ortzsik,Christian,Curtis,Male,Caucasian,05/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +53082,60005,54503,PRETRIAL,Duchet,Hantz,NULL,Male,Other,10/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +53082,60005,54503,PRETRIAL,Duchet,Hantz,NULL,Male,Other,10/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +53082,60005,54503,PRETRIAL,Duchet,Hantz,NULL,Male,Other,10/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53107,60038,54535,PRETRIAL,Shaffer,John,NULL,Male,Caucasian,06/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/19/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +53107,60038,54535,PRETRIAL,Shaffer,John,NULL,Male,Caucasian,06/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +53107,60038,54535,PRETRIAL,Shaffer,John,NULL,Male,Caucasian,06/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53093,60017,54515,PRETRIAL,Ferrell,Lee,NULL,Male,Caucasian,04/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +53093,60017,54515,PRETRIAL,Ferrell,Lee,NULL,Male,Caucasian,04/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +53093,60017,54515,PRETRIAL,Ferrell,Lee,NULL,Male,Caucasian,04/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53099,60026,54523,PRETRIAL,DARRALL,JUSTIN,CHARLES,Male,Caucasian,08/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +53099,60026,54523,PRETRIAL,DARRALL,JUSTIN,CHARLES,Male,Caucasian,08/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +53099,60026,54523,PRETRIAL,DARRALL,JUSTIN,CHARLES,Male,Caucasian,08/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47374,60047,54542,PRETRIAL,tinsley,gregory,NULL,Male,Caucasian,04/13/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/19/13 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +47374,60047,54542,PRETRIAL,tinsley,gregory,NULL,Male,Caucasian,04/13/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/19/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +47374,60047,54542,PRETRIAL,tinsley,gregory,NULL,Male,Caucasian,04/13/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53080,60003,54501,PRETRIAL,Savoir,Junior,NULL,Male,Other,05/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +53080,60003,54501,PRETRIAL,Savoir,Junior,NULL,Male,Other,05/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +53080,60003,54501,PRETRIAL,Savoir,Junior,NULL,Male,Other,05/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53089,60012,54510,PRETRIAL,LOUIS,ANTHONY,NULL,Male,African-American,07/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +53089,60012,54510,PRETRIAL,LOUIS,ANTHONY,NULL,Male,African-American,07/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +53089,60012,54510,PRETRIAL,LOUIS,ANTHONY,NULL,Male,African-American,07/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53101,60031,54528,PRETRIAL,Hernandez,Michael,NULL,Male,Caucasian,03/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +53101,60031,54528,PRETRIAL,Hernandez,Michael,NULL,Male,Caucasian,03/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +53101,60031,54528,PRETRIAL,Hernandez,Michael,NULL,Male,Caucasian,03/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53087,60010,54508,PRETRIAL,monroe,renee,NULL,Female,African-American,07/27/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +53087,60010,54508,PRETRIAL,monroe,renee,NULL,Female,African-American,07/27/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,8,High,New,1,0 +53087,60010,54508,PRETRIAL,monroe,renee,NULL,Female,African-American,07/27/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,New,1,0 +37236,60033,54530,PRETRIAL,Swilling,Nakai,NULL,Male,Caucasian,02/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +37236,60033,54530,PRETRIAL,Swilling,Nakai,NULL,Male,Caucasian,02/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +37236,60033,54530,PRETRIAL,Swilling,Nakai,NULL,Male,Caucasian,02/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53108,60040,54537,Probation,Newson,Timothy,NULL,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +53108,60040,54537,Probation,Newson,Timothy,NULL,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +53108,60040,54537,Probation,Newson,Timothy,NULL,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53078,60000,54498,PRETRIAL,Newton,Joshua,Laronzo,Male,African-American,04/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +53078,60000,54498,PRETRIAL,Newton,Joshua,Laronzo,Male,African-American,04/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +53078,60000,54498,PRETRIAL,Newton,Joshua,Laronzo,Male,African-American,04/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +37428,60043,54540,PRETRIAL,Lariccia,Savintino,Anthony,Male,Caucasian,04/16/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +37428,60043,54540,PRETRIAL,Lariccia,Savintino,Anthony,Male,Caucasian,04/16/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +37428,60043,54540,PRETRIAL,Lariccia,Savintino,Anthony,Male,Caucasian,04/16/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +53118,60050,54545,Probation,AURICCHIO,WILLIAM,NULL,Male,Caucasian,06/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +53118,60050,54545,Probation,AURICCHIO,WILLIAM,NULL,Male,Caucasian,06/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.36,10,High,New,1,0 +53118,60050,54545,Probation,AURICCHIO,WILLIAM,NULL,Male,Caucasian,06/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +53098,60021,54519,Probation,Joseph,Preslere,NULL,Male,African-American,08/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/13 0:00,2,Medium,7,Risk of Violence,-2.79,2,Low,New,1,0 +53098,60021,54519,Probation,Joseph,Preslere,NULL,Male,African-American,08/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +53098,60021,54519,Probation,Joseph,Preslere,NULL,Male,African-American,08/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +42197,60022,41992,PRETRIAL,Russell,Winston,NULL,Male,African-American,01/17/94,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/19/13 0:00,4,High,7,Risk of Violence,-0.66,9,High,New,1,0 +42197,60022,41992,PRETRIAL,Russell,Winston,NULL,Male,African-American,01/17/94,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/19/13 0:00,4,High,8,Risk of Recidivism,0.38,8,High,New,1,0 +42197,60022,41992,PRETRIAL,Russell,Winston,NULL,Male,African-American,01/17/94,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/19/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +42327,60014,54512,PRETRIAL,Jeanlouis,Romel,Al,Male,African-American,12/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +42327,60014,54512,PRETRIAL,Jeanlouis,Romel,Al,Male,African-American,12/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,4,High,8,Risk of Recidivism,0.15,8,High,New,1,0 +42327,60014,54512,PRETRIAL,Jeanlouis,Romel,Al,Male,African-American,12/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +23755,60029,54526,Probation,Saldana,Karl,NULL,Male,Hispanic,12/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/19/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +23755,60029,54526,Probation,Saldana,Karl,NULL,Male,Hispanic,12/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +23755,60029,54526,Probation,Saldana,Karl,NULL,Male,Hispanic,12/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +43829,60001,54499,PRETRIAL,SANMARCO,ANTHONY,NULL,Male,Caucasian,03/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/19/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +43829,60001,54499,PRETRIAL,SANMARCO,ANTHONY,NULL,Male,Caucasian,03/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +43829,60001,54499,PRETRIAL,SANMARCO,ANTHONY,NULL,Male,Caucasian,03/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53085,60008,54506,PRETRIAL,Baillia,Bruce,NULL,Male,Caucasian,10/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +53085,60008,54506,PRETRIAL,Baillia,Bruce,NULL,Male,Caucasian,10/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +53085,60008,54506,PRETRIAL,Baillia,Bruce,NULL,Male,Caucasian,10/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53104,60035,54532,PRETRIAL,aldridge,david,NULL,Male,Caucasian,05/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +53104,60035,54532,PRETRIAL,aldridge,david,NULL,Male,Caucasian,05/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.13,10,High,New,1,0 +53104,60035,54532,PRETRIAL,aldridge,david,NULL,Male,Caucasian,05/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +53109,60042,54539,Probation,Chandler,Christopher,NULL,Male,African-American,03/22/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +53109,60042,54539,Probation,Chandler,Christopher,NULL,Male,African-American,03/22/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +53109,60042,54539,Probation,Chandler,Christopher,NULL,Male,African-American,03/22/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +53088,60011,54509,PRETRIAL,KAISER,HANS,NULL,Male,Caucasian,06/21/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +53088,60011,54509,PRETRIAL,KAISER,HANS,NULL,Male,Caucasian,06/21/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +53088,60011,54509,PRETRIAL,KAISER,HANS,NULL,Male,Caucasian,06/21/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +53115,60045,54541,Probation,Savich,Tatsiana,Aleksandrouna,Female,Caucasian,07/06/79,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/19/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +53115,60045,54541,Probation,Savich,Tatsiana,Aleksandrouna,Female,Caucasian,07/06/79,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/19/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +53115,60045,54541,Probation,Savich,Tatsiana,Aleksandrouna,Female,Caucasian,07/06/79,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +41908,59998,41656,PRETRIAL,Flintroy,James,NULL,Male,African-American,11/09/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,Copy,1,0 +41908,59998,41656,PRETRIAL,Flintroy,James,NULL,Male,African-American,11/09/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.85,10,High,Copy,1,0 +41908,59998,41656,PRETRIAL,Flintroy,James,NULL,Male,African-American,11/09/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +53094,60016,54514,Probation,Malone,Robert,NULL,Male,Caucasian,09/27/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +53094,60016,54514,Probation,Malone,Robert,NULL,Male,Caucasian,09/27/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +53094,60016,54514,Probation,Malone,Robert,NULL,Male,Caucasian,09/27/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53100,60027,54524,Probation,rOBERTS,kEINYATTA,NULL,Female,African-American,01/19/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +53100,60027,54524,Probation,rOBERTS,kEINYATTA,NULL,Female,African-American,01/19/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +53100,60027,54524,Probation,rOBERTS,kEINYATTA,NULL,Female,African-American,01/19/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53083,60006,54504,PRETRIAL,Anderson,Jeremy,Fitzgerald,Male,African-American,07/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +53083,60006,54504,PRETRIAL,Anderson,Jeremy,Fitzgerald,Male,African-American,07/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +53083,60006,54504,PRETRIAL,Anderson,Jeremy,Fitzgerald,Male,African-American,07/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53106,60037,54534,Probation,Fowks,Kurt,NULL,Male,Caucasian,02/11/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +53106,60037,54534,Probation,Fowks,Kurt,NULL,Male,Caucasian,02/11/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +53106,60037,54534,Probation,Fowks,Kurt,NULL,Male,Caucasian,02/11/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52454,60087,53759,Probation,CONTSTANT,ANSSE,NULL,Male,African-American,01/03/82,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +52454,60087,53759,Probation,CONTSTANT,ANSSE,NULL,Male,African-American,01/03/82,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-0.19,5,Medium,New,1,0 +52454,60087,53759,Probation,CONTSTANT,ANSSE,NULL,Male,African-American,01/03/82,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,2,Low,New,1,0 +53159,60105,54592,Probation,Ferrerjaramillo,Sara,NULL,Female,Hispanic,07/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +53159,60105,54592,Probation,Ferrerjaramillo,Sara,NULL,Female,Hispanic,07/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +53159,60105,54592,Probation,Ferrerjaramillo,Sara,NULL,Female,Hispanic,07/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53131,60066,54560,PRETRIAL,HAMILTON,SAYON,TASHAMBI,Male,African-American,06/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +53131,60066,54560,PRETRIAL,HAMILTON,SAYON,TASHAMBI,Male,African-American,06/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +53131,60066,54560,PRETRIAL,HAMILTON,SAYON,TASHAMBI,Male,African-American,06/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53144,60084,54575,PRETRIAL,deluca,christina,NULL,Female,Caucasian,01/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +53144,60084,54575,PRETRIAL,deluca,christina,NULL,Female,Caucasian,01/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +53144,60084,54575,PRETRIAL,deluca,christina,NULL,Female,Caucasian,01/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +5810,60079,54570,PRETRIAL,hunter,bryant,NULL,Male,African-American,08/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +5810,60079,54570,PRETRIAL,hunter,bryant,NULL,Male,African-American,08/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +5810,60079,54570,PRETRIAL,hunter,bryant,NULL,Male,African-American,08/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53167,60113,54600,PRETRIAL,Mayer,Fernando,NULL,Male,African-American,06/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +53167,60113,54600,PRETRIAL,Mayer,Fernando,NULL,Male,African-American,06/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +53167,60113,54600,PRETRIAL,Mayer,Fernando,NULL,Male,African-American,06/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53123,60058,54552,PRETRIAL,Domingo,Raymond,NULL,Male,Caucasian,01/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +53123,60058,54552,PRETRIAL,Domingo,Raymond,NULL,Male,Caucasian,01/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +53123,60058,54552,PRETRIAL,Domingo,Raymond,NULL,Male,Caucasian,01/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +26020,60092,54581,PRETRIAL,SHAMIK,DAVIS,NULL,Male,African-American,10/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +26020,60092,54581,PRETRIAL,SHAMIK,DAVIS,NULL,Male,African-American,10/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +26020,60092,54581,PRETRIAL,SHAMIK,DAVIS,NULL,Male,African-American,10/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53164,60108,54595,Probation,Daniels,Marva,Denise,Female,African-American,10/13/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +53164,60108,54595,Probation,Daniels,Marva,Denise,Female,African-American,10/13/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +53164,60108,54595,Probation,Daniels,Marva,Denise,Female,African-American,10/13/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53126,60063,54557,PRETRIAL,Krimmel,Whitney,NULL,Female,Caucasian,12/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,3/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.96,5,Medium,New,1,0 +53126,60063,54557,PRETRIAL,Krimmel,Whitney,NULL,Female,Caucasian,12/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,3/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,10,High,New,1,0 +53126,60063,54557,PRETRIAL,Krimmel,Whitney,NULL,Female,Caucasian,12/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,3/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52569,60071,53897,PRETRIAL,Lewis,Darryl,NULL,Male,African-American,08/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,Copy,1,0 +52569,60071,53897,PRETRIAL,Lewis,Darryl,NULL,Male,African-American,08/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,Copy,1,0 +52569,60071,53897,PRETRIAL,Lewis,Darryl,NULL,Male,African-American,08/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +53155,60100,54588,PRETRIAL,Cardoza,Cynthia,Mary,Female,Caucasian,02/27/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,New,1,0 +53155,60100,54588,PRETRIAL,Cardoza,Cynthia,Mary,Female,Caucasian,02/27/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +53155,60100,54588,PRETRIAL,Cardoza,Cynthia,Mary,Female,Caucasian,02/27/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +53165,60110,54597,Probation,Fisher,Christopher,NULL,Male,Caucasian,06/07/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +53165,60110,54597,Probation,Fisher,Christopher,NULL,Male,Caucasian,06/07/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +53165,60110,54597,Probation,Fisher,Christopher,NULL,Male,Caucasian,06/07/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53127,60061,54555,PRETRIAL,MCBRIDE,DARREN,L,Male,African-American,12/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +53127,60061,54555,PRETRIAL,MCBRIDE,DARREN,L,Male,African-American,12/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,New,1,0 +53127,60061,54555,PRETRIAL,MCBRIDE,DARREN,L,Male,African-American,12/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +10819,60112,54599,Probation,Chapman,Jonathan,Ross,Male,Caucasian,09/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +10819,60112,54599,Probation,Chapman,Jonathan,Ross,Male,Caucasian,09/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +10819,60112,54599,Probation,Chapman,Jonathan,Ross,Male,Caucasian,09/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +29210,60054,54548,PRETRIAL,Mohorn,Kevin,NULL,Male,African-American,06/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,4,High,7,Risk of Violence,-0.48,10,High,New,1,0 +29210,60054,54548,PRETRIAL,Mohorn,Kevin,NULL,Male,African-American,06/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,4,High,8,Risk of Recidivism,0.2,8,High,New,1,0 +29210,60054,54548,PRETRIAL,Mohorn,Kevin,NULL,Male,African-American,06/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53147,60089,54578,Probation,Flounary,James,NULL,Male,African-American,03/24/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +53147,60089,54578,Probation,Flounary,James,NULL,Male,African-American,03/24/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +53147,60089,54578,Probation,Flounary,James,NULL,Male,African-American,03/24/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +53157,60103,54590,Probation,GRAB,ANTHONY,A,Male,Hispanic,07/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +53157,60103,54590,Probation,GRAB,ANTHONY,A,Male,Hispanic,07/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +53157,60103,54590,Probation,GRAB,ANTHONY,A,Male,Hispanic,07/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53132,60068,54562,PRETRIAL,Ferrer,Lea,NULL,Female,Caucasian,01/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +53132,60068,54562,PRETRIAL,Ferrer,Lea,NULL,Female,Caucasian,01/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +53132,60068,54562,PRETRIAL,Ferrer,Lea,NULL,Female,Caucasian,01/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53137,60075,54567,PRETRIAL,Fried,Jon,NULL,Male,Caucasian,10/19/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/20/13 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +53137,60075,54567,PRETRIAL,Fried,Jon,NULL,Male,Caucasian,10/19/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/20/13 0:00,1,Low,8,Risk of Recidivism,-2.61,1,Low,New,1,0 +53137,60075,54567,PRETRIAL,Fried,Jon,NULL,Male,Caucasian,10/19/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53142,60082,54573,Probation,WOOTEN,DUJUAN,NULL,Male,African-American,08/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +53142,60082,54573,Probation,WOOTEN,DUJUAN,NULL,Male,African-American,08/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +53142,60082,54573,Probation,WOOTEN,DUJUAN,NULL,Male,African-American,08/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +53150,60094,54583,PRETRIAL,Barrett,Daniel,NULL,Male,Caucasian,02/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +53150,60094,54583,PRETRIAL,Barrett,Daniel,NULL,Male,Caucasian,02/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +53150,60094,54583,PRETRIAL,Barrett,Daniel,NULL,Male,Caucasian,02/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53153,60098,54586,PRETRIAL,Navarro,Abe,J,Male,African-American,12/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,7,Risk of Violence,-2.99,1,Low,New,1,0 +53153,60098,54586,PRETRIAL,Navarro,Abe,J,Male,African-American,12/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +53153,60098,54586,PRETRIAL,Navarro,Abe,J,Male,African-American,12/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +39564,60056,54550,PRETRIAL,Abelard,Frantz,NULL,Male,African-American,11/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,New,1,0 +39564,60056,54550,PRETRIAL,Abelard,Frantz,NULL,Male,African-American,11/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.8,10,High,New,1,0 +39564,60056,54550,PRETRIAL,Abelard,Frantz,NULL,Male,African-American,11/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53120,60052,54547,PRETRIAL,CRAIG,DAMOND,LATEEF,Male,African-American,06/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/20/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +53120,60052,54547,PRETRIAL,CRAIG,DAMOND,LATEEF,Male,African-American,06/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +53120,60052,54547,PRETRIAL,CRAIG,DAMOND,LATEEF,Male,African-American,06/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53124,60059,54553,PRETRIAL,Maniscalso,Nick,Eugene,Male,Caucasian,12/28/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +53124,60059,54553,PRETRIAL,Maniscalso,Nick,Eugene,Male,Caucasian,12/28/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +53124,60059,54553,PRETRIAL,Maniscalso,Nick,Eugene,Male,Caucasian,12/28/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53138,60077,54568,Probation,Johnson,lasandra,NULL,Female,African-American,10/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +53138,60077,54568,Probation,Johnson,lasandra,NULL,Female,African-American,10/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,9,High,New,1,0 +53138,60077,54568,Probation,Johnson,lasandra,NULL,Female,African-American,10/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53148,60091,54580,Probation,Smith,Jaime,NULL,Female,Caucasian,11/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/20/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +53148,60091,54580,Probation,Smith,Jaime,NULL,Female,Caucasian,11/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/20/13 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +53148,60091,54580,Probation,Smith,Jaime,NULL,Female,Caucasian,11/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +19108,60109,54596,Probation,hall,edison,NULL,Male,African-American,06/08/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,2,Medium,7,Risk of Violence,-1.43,7,Medium,New,1,0 +19108,60109,54596,Probation,hall,edison,NULL,Male,African-American,06/08/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +19108,60109,54596,Probation,hall,edison,NULL,Male,African-American,06/08/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53134,60070,54564,PRETRIAL,LUBIN,DONTAY,LATRON,Male,African-American,01/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +53134,60070,54564,PRETRIAL,LUBIN,DONTAY,LATRON,Male,African-American,01/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,4,High,8,Risk of Recidivism,0.33,9,High,New,1,0 +53134,60070,54564,PRETRIAL,LUBIN,DONTAY,LATRON,Male,African-American,01/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +42090,60088,41858,PRETRIAL,Walters,Eric,NULL,Male,African-American,12/09/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +42090,60088,41858,PRETRIAL,Walters,Eric,NULL,Male,African-American,12/09/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +42090,60088,41858,PRETRIAL,Walters,Eric,NULL,Male,African-American,12/09/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53128,60062,54556,PRETRIAL,JOSEPH,ALENS,NULL,Male,African-American,05/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +53128,60062,54556,PRETRIAL,JOSEPH,ALENS,NULL,Male,African-American,05/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +53128,60062,54556,PRETRIAL,JOSEPH,ALENS,NULL,Male,African-American,05/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53152,60096,54585,PRETRIAL,Joseph,Peter,NULL,Male,African-American,10/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/13 0:00,2,Medium,7,Risk of Violence,-2.57,2,Low,New,1,0 +53152,60096,54585,PRETRIAL,Joseph,Peter,NULL,Male,African-American,10/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +53152,60096,54585,PRETRIAL,Joseph,Peter,NULL,Male,African-American,10/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53143,60083,54574,PRETRIAL,Nesmith,Charletha,NULL,Female,African-American,02/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +53143,60083,54574,PRETRIAL,Nesmith,Charletha,NULL,Female,African-American,02/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +53143,60083,54574,PRETRIAL,Nesmith,Charletha,NULL,Female,African-American,02/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53139,60078,54569,Probation,Merson,Steven,A,Male,Other,05/08/53,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +53139,60078,54569,Probation,Merson,Steven,A,Male,Other,05/08/53,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +53139,60078,54569,Probation,Merson,Steven,A,Male,Other,05/08/53,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53140,60080,54571,PRETRIAL,English,Joanna,Fabiola,Female,Caucasian,04/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/20/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +53140,60080,54571,PRETRIAL,English,Joanna,Fabiola,Female,Caucasian,04/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +53140,60080,54571,PRETRIAL,English,Joanna,Fabiola,Female,Caucasian,04/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +47021,60065,54559,PRETRIAL,FULLER,DEREK,L,Male,African-American,10/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,New,1,0 +47021,60065,54559,PRETRIAL,FULLER,DEREK,L,Male,African-American,10/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +47021,60065,54559,PRETRIAL,FULLER,DEREK,L,Male,African-American,10/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53154,60099,54587,PRETRIAL,LUEYOUNG,LESTER,NULL,Male,African-American,01/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,7,Risk of Violence,-1.33,7,Medium,New,1,0 +53154,60099,54587,PRETRIAL,LUEYOUNG,LESTER,NULL,Male,African-American,01/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +53154,60099,54587,PRETRIAL,LUEYOUNG,LESTER,NULL,Male,African-American,01/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +5346,60101,39839,PRETRIAL,HATHCOCK,HERBERT,NULL,Male,African-American,09/09/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/20/13 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,Copy,1,0 +5346,60101,39839,PRETRIAL,HATHCOCK,HERBERT,NULL,Male,African-American,09/09/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,Copy,1,0 +5346,60101,39839,PRETRIAL,HATHCOCK,HERBERT,NULL,Male,African-American,09/09/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +53146,60086,54577,PRETRIAL,PENNACHIO,ROSARIO,NULL,Male,Caucasian,09/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +53146,60086,54577,PRETRIAL,PENNACHIO,ROSARIO,NULL,Male,Caucasian,09/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +53146,60086,54577,PRETRIAL,PENNACHIO,ROSARIO,NULL,Male,Caucasian,09/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53122,60057,54551,PRETRIAL,Nesbitt,Henry,Arthur,Male,Caucasian,12/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/20/13 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +53122,60057,54551,PRETRIAL,Nesbitt,Henry,Arthur,Male,Caucasian,12/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/20/13 0:00,1,Low,8,Risk of Recidivism,-2.73,1,Low,New,1,0 +53122,60057,54551,PRETRIAL,Nesbitt,Henry,Arthur,Male,Caucasian,12/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53149,60093,54582,PRETRIAL,Austin,Malcolm,NULL,Male,Caucasian,10/11/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +53149,60093,54582,PRETRIAL,Austin,Malcolm,NULL,Male,Caucasian,10/11/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +53149,60093,54582,PRETRIAL,Austin,Malcolm,NULL,Male,Caucasian,10/11/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53160,60107,54594,Probation,Bernard,Ariese,NULL,Male,African-American,12/01/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +53160,60107,54594,Probation,Bernard,Ariese,NULL,Male,African-American,12/01/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +53160,60107,54594,Probation,Bernard,Ariese,NULL,Male,African-American,12/01/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53156,60102,54589,PRETRIAL,Louis,Evans,NULL,Male,African-American,03/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +53156,60102,54589,PRETRIAL,Louis,Evans,NULL,Male,African-American,03/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +53156,60102,54589,PRETRIAL,Louis,Evans,NULL,Male,African-American,03/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53121,60055,54549,PRETRIAL,Theoc,Saloman,NULL,Male,African-American,06/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +53121,60055,54549,PRETRIAL,Theoc,Saloman,NULL,Male,African-American,06/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +53121,60055,54549,PRETRIAL,Theoc,Saloman,NULL,Male,African-American,06/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53133,60069,54563,PRETRIAL,Jenkins,Clearence,NULL,Male,African-American,03/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/20/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +53133,60069,54563,PRETRIAL,Jenkins,Clearence,NULL,Male,African-American,03/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +53133,60069,54563,PRETRIAL,Jenkins,Clearence,NULL,Male,African-American,03/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53163,60106,54593,DRRD,Webb,Latasia,NULL,Female,African-American,09/13/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +53163,60106,54593,DRRD,Webb,Latasia,NULL,Female,African-American,09/13/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +53163,60106,54593,DRRD,Webb,Latasia,NULL,Female,African-American,09/13/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53129,60064,54558,PRETRIAL,Johnson,Desi,NULL,Male,African-American,06/06/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +53129,60064,54558,PRETRIAL,Johnson,Desi,NULL,Male,African-American,06/06/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.85,10,High,New,1,0 +53129,60064,54558,PRETRIAL,Johnson,Desi,NULL,Male,African-American,06/06/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +53166,60111,54598,Probation,velez,kristina,NULL,Female,African-American,10/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +53166,60111,54598,Probation,velez,kristina,NULL,Female,African-American,10/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +53166,60111,54598,Probation,velez,kristina,NULL,Female,African-American,10/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53119,60051,54546,PRETRIAL,Shields,Ryan,NULL,Male,Caucasian,03/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +53119,60051,54546,PRETRIAL,Shields,Ryan,NULL,Male,Caucasian,03/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +53119,60051,54546,PRETRIAL,Shields,Ryan,NULL,Male,Caucasian,03/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53125,60060,54554,PRETRIAL,Valdemas,Juno,NULL,Male,African-American,05/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +53125,60060,54554,PRETRIAL,Valdemas,Juno,NULL,Male,African-American,05/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +53125,60060,54554,PRETRIAL,Valdemas,Juno,NULL,Male,African-American,05/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53145,60085,54576,Probation,Stennett,Michelle,Marie,Female,African-American,10/13/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +53145,60085,54576,Probation,Stennett,Michelle,Marie,Female,African-American,10/13/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +53145,60085,54576,Probation,Stennett,Michelle,Marie,Female,African-American,10/13/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +28566,60090,54579,PRETRIAL,MELCHOR,ALFRED,NULL,Male,Hispanic,10/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +28566,60090,54579,PRETRIAL,MELCHOR,ALFRED,NULL,Male,Hispanic,10/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +28566,60090,54579,PRETRIAL,MELCHOR,ALFRED,NULL,Male,Hispanic,10/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +2716,60053,22202,PRETRIAL,LEON,CORNELIUS,HOLSTON,Male,African-American,03/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/20/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,Copy,1,0 +2716,60053,22202,PRETRIAL,LEON,CORNELIUS,HOLSTON,Male,African-American,03/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,Copy,1,0 +2716,60053,22202,PRETRIAL,LEON,CORNELIUS,HOLSTON,Male,African-American,03/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/20/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +53158,60104,54591,Probation,Pierce,Aaron,Joseph,Male,Caucasian,03/25/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +53158,60104,54591,Probation,Pierce,Aaron,Joseph,Male,Caucasian,03/25/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +53158,60104,54591,Probation,Pierce,Aaron,Joseph,Male,Caucasian,03/25/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53151,60095,54584,PRETRIAL,Campbell,Malina,Dacene,Female,African-American,09/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +53151,60095,54584,PRETRIAL,Campbell,Malina,Dacene,Female,African-American,09/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +53151,60095,54584,PRETRIAL,Campbell,Malina,Dacene,Female,African-American,09/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +22920,60097,22097,Probation,Floreno,Matthew,NULL,Male,Caucasian,08/06/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/20/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,Copy,1,0 +22920,60097,22097,Probation,Floreno,Matthew,NULL,Male,Caucasian,08/06/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/20/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,Copy,1,0 +22920,60097,22097,Probation,Floreno,Matthew,NULL,Male,Caucasian,08/06/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +53130,60067,54561,PRETRIAL,Vitale,Mark,NULL,Male,Caucasian,12/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +53130,60067,54561,PRETRIAL,Vitale,Mark,NULL,Male,Caucasian,12/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/13 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +53130,60067,54561,PRETRIAL,Vitale,Mark,NULL,Male,Caucasian,12/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53136,60074,54566,Probation,Nevarez,Jorge,W,Male,Hispanic,01/26/60,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Divorced,3/20/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +53136,60074,54566,Probation,Nevarez,Jorge,W,Male,Hispanic,01/26/60,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Divorced,3/20/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +53136,60074,54566,Probation,Nevarez,Jorge,W,Male,Hispanic,01/26/60,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Divorced,3/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53207,60167,54652,Probation,Phillips,Jessica,NULL,Female,African-American,10/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.99,4,Low,New,1,0 +53207,60167,54652,Probation,Phillips,Jessica,NULL,Female,African-American,10/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,9,High,New,1,0 +53207,60167,54652,Probation,Phillips,Jessica,NULL,Female,African-American,10/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53211,60174,54658,Probation,Zayas,annalyse,NULL,Female,Hispanic,03/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +53211,60174,54658,Probation,Zayas,annalyse,NULL,Female,Hispanic,03/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +53211,60174,54658,Probation,Zayas,annalyse,NULL,Female,Hispanic,03/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53213,60176,54660,PRETRIAL,Hilbert,James,Edward,Male,African-American,09/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +53213,60176,54660,PRETRIAL,Hilbert,James,Edward,Male,African-American,09/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +53213,60176,54660,PRETRIAL,Hilbert,James,Edward,Male,African-American,09/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53194,60146,54633,Probation,coney,bradley,NULL,Male,Caucasian,04/10/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.38,3,Low,New,1,0 +53194,60146,54633,Probation,coney,bradley,NULL,Male,Caucasian,04/10/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +53194,60146,54633,Probation,coney,bradley,NULL,Male,Caucasian,04/10/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +53197,60148,54635,Probation,Young,Alvin,C,Male,African-American,03/24/62,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +53197,60148,54635,Probation,Young,Alvin,C,Male,African-American,03/24/62,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +53197,60148,54635,Probation,Young,Alvin,C,Male,African-American,03/24/62,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53188,60139,54626,Probation,Sullivan,Kyle,NULL,Male,Caucasian,09/20/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +53188,60139,54626,Probation,Sullivan,Kyle,NULL,Male,Caucasian,09/20/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +53188,60139,54626,Probation,Sullivan,Kyle,NULL,Male,Caucasian,09/20/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +13862,60153,54640,Probation,KAYE,ROBERT,JEFFREY,Male,Caucasian,07/04/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +13862,60153,54640,Probation,KAYE,ROBERT,JEFFREY,Male,Caucasian,07/04/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +13862,60153,54640,Probation,KAYE,ROBERT,JEFFREY,Male,Caucasian,07/04/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53171,60118,54605,PRETRIAL,Salerno,Dino,Leonard,Male,Caucasian,09/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +53171,60118,54605,PRETRIAL,Salerno,Dino,Leonard,Male,Caucasian,09/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +53171,60118,54605,PRETRIAL,Salerno,Dino,Leonard,Male,Caucasian,09/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53177,60125,54612,PRETRIAL,Ciccarelli,Philip,NULL,Male,Caucasian,06/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/21/13 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +53177,60125,54612,PRETRIAL,Ciccarelli,Philip,NULL,Male,Caucasian,06/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +53177,60125,54612,PRETRIAL,Ciccarelli,Philip,NULL,Male,Caucasian,06/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/21/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53181,60132,54619,PRETRIAL,Oneal,Mary,NULL,Female,African-American,02/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +53181,60132,54619,PRETRIAL,Oneal,Mary,NULL,Female,African-American,02/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +53181,60132,54619,PRETRIAL,Oneal,Mary,NULL,Female,African-American,02/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53202,60158,54645,Probation,Benninghoff,Cynthia,NULL,Female,Caucasian,11/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,3/21/13 0:00,2,Medium,7,Risk of Violence,-3.3,1,Low,New,1,0 +53202,60158,54645,Probation,Benninghoff,Cynthia,NULL,Female,Caucasian,11/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,3/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +53202,60158,54645,Probation,Benninghoff,Cynthia,NULL,Female,Caucasian,11/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,3/21/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +35617,60162,54648,Probation,Brown,Kurt,Walterlee,Male,African-American,03/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +35617,60162,54648,Probation,Brown,Kurt,Walterlee,Male,African-American,03/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +35617,60162,54648,Probation,Brown,Kurt,Walterlee,Male,African-American,03/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53215,60179,54662,PRETRIAL,Fields,Lamondrio,NULL,Male,African-American,03/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,7,Risk of Violence,-0.72,9,High,New,1,0 +53215,60179,54662,PRETRIAL,Fields,Lamondrio,NULL,Male,African-American,03/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +53215,60179,54662,PRETRIAL,Fields,Lamondrio,NULL,Male,African-American,03/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53172,60120,54607,PRETRIAL,Wright,Damian,NULL,Male,Other,12/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +53172,60120,54607,PRETRIAL,Wright,Damian,NULL,Male,Other,12/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +53172,60120,54607,PRETRIAL,Wright,Damian,NULL,Male,Other,12/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53175,60123,54610,PRETRIAL,Wallack,Keith,NULL,Male,Caucasian,08/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/21/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +53175,60123,54610,PRETRIAL,Wallack,Keith,NULL,Male,Caucasian,08/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +53175,60123,54610,PRETRIAL,Wallack,Keith,NULL,Male,Caucasian,08/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +44912,60137,54624,PRETRIAL,Wahrmann,Ralph,NULL,Male,Other,03/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +44912,60137,54624,PRETRIAL,Wahrmann,Ralph,NULL,Male,Other,03/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +44912,60137,54624,PRETRIAL,Wahrmann,Ralph,NULL,Male,Other,03/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50843,60116,54603,PRETRIAL,Davis,Michael,Lavon,Male,African-American,11/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,7,Risk of Violence,-0.67,9,High,New,1,0 +50843,60116,54603,PRETRIAL,Davis,Michael,Lavon,Male,African-American,11/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,8,Risk of Recidivism,0.48,9,High,New,1,0 +50843,60116,54603,PRETRIAL,Davis,Michael,Lavon,Male,African-American,11/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +48274,60127,54614,PRETRIAL,Vedder,Nicholas,NULL,Male,African-American,08/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +48274,60127,54614,PRETRIAL,Vedder,Nicholas,NULL,Male,African-American,08/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,8,Risk of Recidivism,0.45,9,High,New,1,0 +48274,60127,54614,PRETRIAL,Vedder,Nicholas,NULL,Male,African-American,08/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53190,60141,54628,PRETRIAL,SMITH,JON,NULL,Male,Caucasian,11/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +53190,60141,54628,PRETRIAL,SMITH,JON,NULL,Male,Caucasian,11/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +53190,60141,54628,PRETRIAL,SMITH,JON,NULL,Male,Caucasian,11/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +36461,60143,54630,PRETRIAL,davis,lance,NULL,Male,African-American,12/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +36461,60143,54630,PRETRIAL,davis,lance,NULL,Male,African-American,12/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +36461,60143,54630,PRETRIAL,davis,lance,NULL,Male,African-American,12/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +53174,60122,54609,PRETRIAL,Ward,Raheme,NULL,Male,African-American,03/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +53174,60122,54609,PRETRIAL,Ward,Raheme,NULL,Male,African-American,03/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +53174,60122,54609,PRETRIAL,Ward,Raheme,NULL,Male,African-American,03/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53184,60135,54622,PRETRIAL,Patterson,Courtney,NULL,Male,African-American,03/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +53184,60135,54622,PRETRIAL,Patterson,Courtney,NULL,Male,African-American,03/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +53184,60135,54622,PRETRIAL,Patterson,Courtney,NULL,Male,African-American,03/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53168,60114,54601,PRETRIAL,Grohs,Michael,Albert,Male,Caucasian,10/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +53168,60114,54601,PRETRIAL,Grohs,Michael,Albert,Male,Caucasian,10/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +53168,60114,54601,PRETRIAL,Grohs,Michael,Albert,Male,Caucasian,10/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53216,60180,54663,PRETRIAL,Reeves,Robert,NULL,Male,Caucasian,01/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/21/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +53216,60180,54663,PRETRIAL,Reeves,Robert,NULL,Male,Caucasian,01/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/21/13 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +53216,60180,54663,PRETRIAL,Reeves,Robert,NULL,Male,Caucasian,01/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53170,60117,54604,PRETRIAL,PABON,RAFAEL,A,Male,Caucasian,12/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,7,Risk of Violence,-0.2,10,High,New,1,0 +53170,60117,54604,PRETRIAL,PABON,RAFAEL,A,Male,Caucasian,12/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +53170,60117,54604,PRETRIAL,PABON,RAFAEL,A,Male,Caucasian,12/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +45230,60151,54638,PRETRIAL,Bueford,Jermaine,NULL,Male,African-American,06/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +45230,60151,54638,PRETRIAL,Bueford,Jermaine,NULL,Male,African-American,06/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +45230,60151,54638,PRETRIAL,Bueford,Jermaine,NULL,Male,African-American,06/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53180,60130,54617,PRETRIAL,Gregory,Dakota,Jacob,Male,Caucasian,02/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.16,8,High,New,1,0 +53180,60130,54617,PRETRIAL,Gregory,Dakota,Jacob,Male,Caucasian,02/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +53180,60130,54617,PRETRIAL,Gregory,Dakota,Jacob,Male,Caucasian,02/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +36456,60164,35733,PRETRIAL,Jones,Anothony,NULL,Male,African-American,01/07/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,Copy,1,0 +36456,60164,35733,PRETRIAL,Jones,Anothony,NULL,Male,African-American,01/07/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.62,4,Low,Copy,1,0 +36456,60164,35733,PRETRIAL,Jones,Anothony,NULL,Male,African-American,01/07/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +53187,60138,54625,Probation,Mason,Brittney,R,Female,African-American,10/19/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +53187,60138,54625,Probation,Mason,Brittney,R,Female,African-American,10/19/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +53187,60138,54625,Probation,Mason,Brittney,R,Female,African-American,10/19/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +792,60156,54643,PRETRIAL,conlee,xavier,robertson,Male,Caucasian,12/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +792,60156,54643,PRETRIAL,conlee,xavier,robertson,Male,Caucasian,12/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +792,60156,54643,PRETRIAL,conlee,xavier,robertson,Male,Caucasian,12/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +53214,60177,54661,PRETRIAL,Brown,Everton,NULL,Male,Other,01/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/21/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +53214,60177,54661,PRETRIAL,Brown,Everton,NULL,Male,Other,01/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +53214,60177,54661,PRETRIAL,Brown,Everton,NULL,Male,Other,01/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53206,60166,54651,DRRD,Manfredi,Kenneth,NULL,Male,Caucasian,08/29/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +53206,60166,54651,DRRD,Manfredi,Kenneth,NULL,Male,Caucasian,08/29/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +53206,60166,54651,DRRD,Manfredi,Kenneth,NULL,Male,Caucasian,08/29/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +7881,60119,54606,PRETRIAL,albritton,marcus,NULL,Male,African-American,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +7881,60119,54606,PRETRIAL,albritton,marcus,NULL,Male,African-American,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +7881,60119,54606,PRETRIAL,albritton,marcus,NULL,Male,African-American,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53209,60170,54654,Probation,MELENDEZ,KENNETH,NULL,Male,Hispanic,08/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +53209,60170,54654,Probation,MELENDEZ,KENNETH,NULL,Male,Hispanic,08/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +53209,60170,54654,Probation,MELENDEZ,KENNETH,NULL,Male,Hispanic,08/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +30501,60128,54615,PRETRIAL,Francois,Moses,NULL,Male,African-American,10/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +30501,60128,54615,PRETRIAL,Francois,Moses,NULL,Male,African-American,10/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.92,10,High,New,1,0 +30501,60128,54615,PRETRIAL,Francois,Moses,NULL,Male,African-American,10/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53193,60145,54632,PRETRIAL,MCEWAN,CHRISTOPHER,NULL,Male,African-American,03/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +53193,60145,54632,PRETRIAL,MCEWAN,CHRISTOPHER,NULL,Male,African-American,03/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +53193,60145,54632,PRETRIAL,MCEWAN,CHRISTOPHER,NULL,Male,African-American,03/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53169,60115,54602,PRETRIAL,CHARLES,SICO,NULL,Male,African-American,04/23/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +53169,60115,54602,PRETRIAL,CHARLES,SICO,NULL,Male,African-American,04/23/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +53169,60115,54602,PRETRIAL,CHARLES,SICO,NULL,Male,African-American,04/23/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53176,60124,54611,PRETRIAL,Francois,Calvin,NULL,Male,African-American,05/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +53176,60124,54611,PRETRIAL,Francois,Calvin,NULL,Male,African-American,05/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +53176,60124,54611,PRETRIAL,Francois,Calvin,NULL,Male,African-American,05/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53208,60168,54653,Probation,silvaurresti,sergio,NULL,Male,Caucasian,08/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +53208,60168,54653,Probation,silvaurresti,sergio,NULL,Male,Caucasian,08/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +53208,60168,54653,Probation,silvaurresti,sergio,NULL,Male,Caucasian,08/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53212,60175,54659,PRETRIAL,Jackson,Anthony,NULL,Male,African-American,04/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +53212,60175,54659,PRETRIAL,Jackson,Anthony,NULL,Male,African-American,04/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +53212,60175,54659,PRETRIAL,Jackson,Anthony,NULL,Male,African-American,04/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53200,60154,54641,Probation,robertson,floyd,NULL,Male,African-American,07/20/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/21/13 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +53200,60154,54641,Probation,robertson,floyd,NULL,Male,African-American,07/20/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/21/13 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +53200,60154,54641,Probation,robertson,floyd,NULL,Male,African-American,07/20/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +32083,60131,54618,PRETRIAL,flournoy,ryan,NULL,Male,African-American,08/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,7,Risk of Violence,-0.73,9,High,New,1,0 +32083,60131,54618,PRETRIAL,flournoy,ryan,NULL,Male,African-American,08/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,8,Risk of Recidivism,0.35,9,High,New,1,0 +32083,60131,54618,PRETRIAL,flournoy,ryan,NULL,Male,African-American,08/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +34401,60161,33551,PRETRIAL,Asmar,Dana,NULL,Female,Caucasian,08/28/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,Copy,1,0 +34401,60161,33551,PRETRIAL,Asmar,Dana,NULL,Female,Caucasian,08/28/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,Copy,1,0 +34401,60161,33551,PRETRIAL,Asmar,Dana,NULL,Female,Caucasian,08/28/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +53182,60133,54620,PRETRIAL,Nelson,Raymond,NULL,Male,Hispanic,06/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/21/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +53182,60133,54620,PRETRIAL,Nelson,Raymond,NULL,Male,Hispanic,06/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/21/13 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +53182,60133,54620,PRETRIAL,Nelson,Raymond,NULL,Male,Hispanic,06/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53189,60140,54627,Probation,FEARS,GARY,R,Male,Caucasian,06/08/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/13 0:00,1,Low,7,Risk of Violence,-4.56,1,Low,New,1,0 +53189,60140,54627,Probation,FEARS,GARY,R,Male,Caucasian,06/08/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/13 0:00,1,Low,8,Risk of Recidivism,-2.67,1,Low,New,1,0 +53189,60140,54627,Probation,FEARS,GARY,R,Male,Caucasian,06/08/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53198,60150,54637,Broward County,Jones,Timmy,NULL,Male,African-American,09/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +53198,60150,54637,Broward County,Jones,Timmy,NULL,Male,African-American,09/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +53198,60150,54637,Broward County,Jones,Timmy,NULL,Male,African-American,09/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +38658,60157,54644,PRETRIAL,WEIMER,TIMOTHY,NULL,Male,Caucasian,07/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +38658,60157,54644,PRETRIAL,WEIMER,TIMOTHY,NULL,Male,Caucasian,07/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +38658,60157,54644,PRETRIAL,WEIMER,TIMOTHY,NULL,Male,Caucasian,07/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53173,60121,54608,PRETRIAL,Jackson,James,NULL,Male,African-American,03/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +53173,60121,54608,PRETRIAL,Jackson,James,NULL,Male,African-American,03/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +53173,60121,54608,PRETRIAL,Jackson,James,NULL,Male,African-American,03/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53185,60136,54623,Probation,HERRERA,RENE,DAVID,Male,Hispanic,05/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +53185,60136,54623,Probation,HERRERA,RENE,DAVID,Male,Hispanic,05/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +53185,60136,54623,Probation,HERRERA,RENE,DAVID,Male,Hispanic,05/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +5065,60129,54616,PRETRIAL,NIETO,BRADON,R,Male,Hispanic,07/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +5065,60129,54616,PRETRIAL,NIETO,BRADON,R,Male,Hispanic,07/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +5065,60129,54616,PRETRIAL,NIETO,BRADON,R,Male,Hispanic,07/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53192,60144,54631,Probation,MOODY,CHELSEA,NULL,Female,Caucasian,05/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +53192,60144,54631,Probation,MOODY,CHELSEA,NULL,Female,Caucasian,05/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +53192,60144,54631,Probation,MOODY,CHELSEA,NULL,Female,Caucasian,05/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +44536,60163,54649,PRETRIAL,Daniels,Willie,NULL,Male,African-American,02/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/21/13 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +44536,60163,54649,PRETRIAL,Daniels,Willie,NULL,Male,African-American,02/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +44536,60163,54649,PRETRIAL,Daniels,Willie,NULL,Male,African-American,02/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +19329,60178,18570,PRETRIAL,FRUSTER,ZACHARY,NULL,Male,African-American,09/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,Copy,1,0 +19329,60178,18570,PRETRIAL,FRUSTER,ZACHARY,NULL,Male,African-American,09/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +19329,60178,18570,PRETRIAL,FRUSTER,ZACHARY,NULL,Male,African-American,09/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +53191,60142,54629,Probation,milosh,kandic,NULL,Male,Caucasian,10/02/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/21/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +53191,60142,54629,Probation,milosh,kandic,NULL,Male,Caucasian,10/02/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +53191,60142,54629,Probation,milosh,kandic,NULL,Male,Caucasian,10/02/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53205,60165,54650,Probation,Manning,William,Alva,Male,Caucasian,04/09/67,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/21/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +53205,60165,54650,Probation,Manning,William,Alva,Male,Caucasian,04/09/67,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +53205,60165,54650,Probation,Manning,William,Alva,Male,Caucasian,04/09/67,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53178,60126,54613,PRETRIAL,Smith,Alexander,D,Male,Caucasian,09/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +53178,60126,54613,PRETRIAL,Smith,Alexander,D,Male,Caucasian,09/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +53178,60126,54613,PRETRIAL,Smith,Alexander,D,Male,Caucasian,09/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53204,60160,54647,Probation,Duperry,Clint,Carl,Male,Caucasian,12/20/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/21/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +53204,60160,54647,Probation,Duperry,Clint,Carl,Male,Caucasian,12/20/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/21/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +53204,60160,54647,Probation,Duperry,Clint,Carl,Male,Caucasian,12/20/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53183,60134,54621,PRETRIAL,Francois,Kerry,NULL,Male,African-American,10/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +53183,60134,54621,PRETRIAL,Francois,Kerry,NULL,Male,African-American,10/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1,10,High,New,1,0 +53183,60134,54621,PRETRIAL,Francois,Kerry,NULL,Male,African-American,10/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +53199,60152,54639,PRETRIAL,STEENSON,ATLANTIS,NULL,Female,Other,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +53199,60152,54639,PRETRIAL,STEENSON,ATLANTIS,NULL,Female,Other,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +53199,60152,54639,PRETRIAL,STEENSON,ATLANTIS,NULL,Female,Other,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53201,60155,54642,Probation,AVILA,MIGUEL,A,Male,Hispanic,09/30/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +53201,60155,54642,Probation,AVILA,MIGUEL,A,Male,Hispanic,09/30/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +53201,60155,54642,Probation,AVILA,MIGUEL,A,Male,Hispanic,09/30/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53210,60173,54657,Probation,Gibboney,Alicia,NULL,Female,Caucasian,04/20/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/21/13 0:00,2,Medium,7,Risk of Violence,-2.79,2,Low,New,1,0 +53210,60173,54657,Probation,Gibboney,Alicia,NULL,Female,Caucasian,04/20/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,7,Medium,New,1,0 +53210,60173,54657,Probation,Gibboney,Alicia,NULL,Female,Caucasian,04/20/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/21/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +53230,60202,54683,PRETRIAL,Cuello,Madeline,NULL,Female,Caucasian,04/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +53230,60202,54683,PRETRIAL,Cuello,Madeline,NULL,Female,Caucasian,04/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +53230,60202,54683,PRETRIAL,Cuello,Madeline,NULL,Female,Caucasian,04/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53225,60194,54675,PRETRIAL,Koepke,Kameron,NULL,Male,Caucasian,10/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +53225,60194,54675,PRETRIAL,Koepke,Kameron,NULL,Male,Caucasian,10/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +53225,60194,54675,PRETRIAL,Koepke,Kameron,NULL,Male,Caucasian,10/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +42847,60181,42715,PRETRIAL,Dominguez,Raymond,NULL,Male,African-American,04/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,Copy,1,0 +42847,60181,42715,PRETRIAL,Dominguez,Raymond,NULL,Male,African-American,04/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,Copy,1,0 +42847,60181,42715,PRETRIAL,Dominguez,Raymond,NULL,Male,African-American,04/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +36618,60215,54696,Probation,taylor,Andrew,NULL,Male,African-American,08/06/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +36618,60215,54696,Probation,taylor,Andrew,NULL,Male,African-American,08/06/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +36618,60215,54696,Probation,taylor,Andrew,NULL,Male,African-American,08/06/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53253,60228,54707,Probation,Tahulian,Ivan,NULL,Male,Hispanic,11/13/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/22/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +53253,60228,54707,Probation,Tahulian,Ivan,NULL,Male,Hispanic,11/13/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/22/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +53253,60228,54707,Probation,Tahulian,Ivan,NULL,Male,Hispanic,11/13/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53228,60199,54680,PRETRIAL,Babbit,Michael,NULL,Male,Caucasian,06/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +53228,60199,54680,PRETRIAL,Babbit,Michael,NULL,Male,Caucasian,06/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +53228,60199,54680,PRETRIAL,Babbit,Michael,NULL,Male,Caucasian,06/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +6954,60186,54668,PRETRIAL,Thorpe,Ann,NULL,Female,Caucasian,10/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,7,Risk of Violence,-2.77,2,Low,New,1,0 +6954,60186,54668,PRETRIAL,Thorpe,Ann,NULL,Female,Caucasian,10/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +6954,60186,54668,PRETRIAL,Thorpe,Ann,NULL,Female,Caucasian,10/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +53234,60207,54688,Probation,Baker,Terrence,NULL,Male,African-American,06/12/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +53234,60207,54688,Probation,Baker,Terrence,NULL,Male,African-American,06/12/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +53234,60207,54688,Probation,Baker,Terrence,NULL,Male,African-American,06/12/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53237,60210,54691,Probation,Benjamine,Tony,R,Male,African-American,08/24/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +53237,60210,54691,Probation,Benjamine,Tony,R,Male,African-American,08/24/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +53237,60210,54691,Probation,Benjamine,Tony,R,Male,African-American,08/24/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53240,60212,54693,PRETRIAL,visbal,joshua,NULL,Male,Caucasian,12/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/22/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +53240,60212,54693,PRETRIAL,visbal,joshua,NULL,Male,Caucasian,12/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +53240,60212,54693,PRETRIAL,visbal,joshua,NULL,Male,Caucasian,12/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53256,60231,54710,Probation,Codrington,Annmarie,NULL,Female,African-American,03/30/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +53256,60231,54710,Probation,Codrington,Annmarie,NULL,Female,African-American,03/30/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +53256,60231,54710,Probation,Codrington,Annmarie,NULL,Female,African-American,03/30/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53222,60189,54671,PRETRIAL,Duncan,Bernard,NULL,Male,African-American,04/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/22/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +53222,60189,54671,PRETRIAL,Duncan,Bernard,NULL,Male,African-American,04/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +53222,60189,54671,PRETRIAL,Duncan,Bernard,NULL,Male,African-American,04/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +53231,60203,54684,PRETRIAL,Fixalant,Nadege,NULL,Male,African-American,11/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +53231,60203,54684,PRETRIAL,Fixalant,Nadege,NULL,Male,African-American,11/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +53231,60203,54684,PRETRIAL,Fixalant,Nadege,NULL,Male,African-American,11/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +14073,60182,54664,PRETRIAL,STSURIN,RUDY,EXADEJESUS,Male,African-American,12/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/13 0:00,4,High,7,Risk of Violence,-0.69,9,High,New,1,0 +14073,60182,54664,PRETRIAL,STSURIN,RUDY,EXADEJESUS,Male,African-American,12/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/13 0:00,4,High,8,Risk of Recidivism,0.37,9,High,New,1,0 +14073,60182,54664,PRETRIAL,STSURIN,RUDY,EXADEJESUS,Male,African-American,12/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53245,60217,54698,Probation,PRIBYL,FRED,NULL,Male,Caucasian,12/26/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/22/13 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +53245,60217,54698,Probation,PRIBYL,FRED,NULL,Male,Caucasian,12/26/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/22/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +53245,60217,54698,Probation,PRIBYL,FRED,NULL,Male,Caucasian,12/26/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53227,60196,54677,PRETRIAL,Rhodes,Christopher,NULL,Male,Caucasian,05/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +53227,60196,54677,PRETRIAL,Rhodes,Christopher,NULL,Male,Caucasian,05/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +53227,60196,54677,PRETRIAL,Rhodes,Christopher,NULL,Male,Caucasian,05/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53220,60187,54669,PRETRIAL,Chance,Oliver,NULL,Male,African-American,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +53220,60187,54669,PRETRIAL,Chance,Oliver,NULL,Male,African-American,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +53220,60187,54669,PRETRIAL,Chance,Oliver,NULL,Male,African-American,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53218,60184,54666,PRETRIAL,Bouquette,Junior,NULL,Male,Other,08/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +53218,60184,54666,PRETRIAL,Bouquette,Junior,NULL,Male,Other,08/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +53218,60184,54666,PRETRIAL,Bouquette,Junior,NULL,Male,Other,08/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +37303,60191,54673,PRETRIAL,Smith,Troy,R,Male,African-American,09/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +37303,60191,54673,PRETRIAL,Smith,Troy,R,Male,African-American,09/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +37303,60191,54673,PRETRIAL,Smith,Troy,R,Male,African-American,09/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53233,60206,54687,PRETRIAL,Cuello,Marilyn,NULL,Female,Caucasian,04/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +53233,60206,54687,PRETRIAL,Cuello,Marilyn,NULL,Female,Caucasian,04/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +53233,60206,54687,PRETRIAL,Cuello,Marilyn,NULL,Female,Caucasian,04/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +40921,60198,54679,PRETRIAL,ALDRIDGE,FERNAND,NULL,Male,African-American,08/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +40921,60198,54679,PRETRIAL,ALDRIDGE,FERNAND,NULL,Male,African-American,08/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +40921,60198,54679,PRETRIAL,ALDRIDGE,FERNAND,NULL,Male,African-American,08/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53239,60211,54692,Probation,Romero,Joel,NULL,Male,Hispanic,08/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/22/13 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,New,1,0 +53239,60211,54692,Probation,Romero,Joel,NULL,Male,Hispanic,08/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +53239,60211,54692,Probation,Romero,Joel,NULL,Male,Hispanic,08/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/22/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53219,60185,54667,PRETRIAL,Martinez,Johnny,NULL,Male,African-American,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +53219,60185,54667,PRETRIAL,Martinez,Johnny,NULL,Male,African-American,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +53219,60185,54667,PRETRIAL,Martinez,Johnny,NULL,Male,African-American,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53223,60190,54672,PRETRIAL,Bartron,Darren,NULL,Male,Caucasian,12/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +53223,60190,54672,PRETRIAL,Bartron,Darren,NULL,Male,Caucasian,12/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +53223,60190,54672,PRETRIAL,Bartron,Darren,NULL,Male,Caucasian,12/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +44915,60219,54699,PRETRIAL,Bassler,Scott,C,Male,Caucasian,12/01/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +44915,60219,54699,PRETRIAL,Bassler,Scott,C,Male,Caucasian,12/01/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +44915,60219,54699,PRETRIAL,Bassler,Scott,C,Male,Caucasian,12/01/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53251,60224,54704,Probation,SOTO,FRANKLIN,NULL,Male,Hispanic,07/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +53251,60224,54704,Probation,SOTO,FRANKLIN,NULL,Male,Hispanic,07/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +53251,60224,54704,Probation,SOTO,FRANKLIN,NULL,Male,Hispanic,07/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53254,60229,54708,Probation,Jackson,Terreka,NULL,Female,African-American,06/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +53254,60229,54708,Probation,Jackson,Terreka,NULL,Female,African-American,06/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +53254,60229,54708,Probation,Jackson,Terreka,NULL,Female,African-American,06/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +31342,60201,54682,PRETRIAL,Cobb,Edward,NULL,Male,African-American,11/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.11,8,High,New,1,0 +31342,60201,54682,PRETRIAL,Cobb,Edward,NULL,Male,African-American,11/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +31342,60201,54682,PRETRIAL,Cobb,Edward,NULL,Male,African-American,11/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +46506,60208,54689,Probation,roldan,william,NULL,Male,Caucasian,05/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +46506,60208,54689,Probation,roldan,william,NULL,Male,Caucasian,05/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +46506,60208,54689,Probation,roldan,william,NULL,Male,Caucasian,05/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53248,60221,54701,Probation,STEWART,STEFAN,NULL,Male,African-American,03/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +53248,60221,54701,Probation,STEWART,STEFAN,NULL,Male,African-American,03/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +53248,60221,54701,Probation,STEWART,STEFAN,NULL,Male,African-American,03/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53249,60222,54702,Probation,schupe,martha,NULL,Female,Hispanic,06/27/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/22/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +53249,60222,54702,Probation,schupe,martha,NULL,Female,Hispanic,06/27/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/22/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +53249,60222,54702,Probation,schupe,martha,NULL,Female,Hispanic,06/27/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53224,60193,54674,PRETRIAL,Allah,Cipher,Theend,Male,African-American,12/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,Copy,1,0 +53224,60193,54674,PRETRIAL,Allah,Cipher,Theend,Male,African-American,12/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,Copy,1,0 +53224,60193,54674,PRETRIAL,Allah,Cipher,Theend,Male,African-American,12/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +48014,60200,54681,PRETRIAL,PEW,DONTAE,NULL,Male,African-American,08/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.55,3,Low,New,1,0 +48014,60200,54681,PRETRIAL,PEW,DONTAE,NULL,Male,African-American,08/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +48014,60200,54681,PRETRIAL,PEW,DONTAE,NULL,Male,African-American,08/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53236,60209,54690,Probation,dean,omar,NULL,Male,African-American,11/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +53236,60209,54690,Probation,dean,omar,NULL,Male,African-American,11/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +53236,60209,54690,Probation,dean,omar,NULL,Male,African-American,11/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53257,60234,54713,Probation,Alococer,Juvenal,NULL,Male,Hispanic,04/10/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +53257,60234,54713,Probation,Alococer,Juvenal,NULL,Male,Hispanic,04/10/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +53257,60234,54713,Probation,Alococer,Juvenal,NULL,Male,Hispanic,04/10/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53221,60188,54670,PRETRIAL,Davis,Herman,NULL,Male,African-American,12/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,4,High,7,Risk of Violence,-0.68,9,High,New,1,0 +53221,60188,54670,PRETRIAL,Davis,Herman,NULL,Male,African-American,12/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,4,High,8,Risk of Recidivism,0.38,9,High,New,1,0 +53221,60188,54670,PRETRIAL,Davis,Herman,NULL,Male,African-American,12/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53241,60213,54694,Probation,mccray,rodney,NULL,Male,African-American,07/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +53241,60213,54694,Probation,mccray,rodney,NULL,Male,African-American,07/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +53241,60213,54694,Probation,mccray,rodney,NULL,Male,African-American,07/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53255,60230,54709,Probation,Prophilis,Walson,NULL,Male,African-American,10/07/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +53255,60230,54709,Probation,Prophilis,Walson,NULL,Male,African-American,10/07/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.67,10,High,New,1,0 +53255,60230,54709,Probation,Prophilis,Walson,NULL,Male,African-American,10/07/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53217,60183,54665,PRETRIAL,Stephens,Shaquille,NULL,Male,African-American,07/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +53217,60183,54665,PRETRIAL,Stephens,Shaquille,NULL,Male,African-American,07/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +53217,60183,54665,PRETRIAL,Stephens,Shaquille,NULL,Male,African-American,07/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50242,60225,51231,DRRD,Hunt,Anthony,NULL,Male,African-American,03/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,Copy,1,0 +50242,60225,51231,DRRD,Hunt,Anthony,NULL,Male,African-American,03/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,4,High,8,Risk of Recidivism,0.65,9,High,Copy,1,0 +50242,60225,51231,DRRD,Hunt,Anthony,NULL,Male,African-American,03/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +45084,60232,54711,Probation,scott,michael,NULL,Male,Caucasian,01/14/79,17,All Scales,Intake,English,Probation Violator,Probation,Single,3/22/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +45084,60232,54711,Probation,scott,michael,NULL,Male,Caucasian,01/14/79,17,All Scales,Intake,English,Probation Violator,Probation,Single,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.97,2,Low,New,1,0 +45084,60232,54711,Probation,scott,michael,NULL,Male,Caucasian,01/14/79,17,All Scales,Intake,English,Probation Violator,Probation,Single,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,1,Low,New,1,0 +37963,60204,54685,PRETRIAL,McCutchen,Brandon,NULL,Male,African-American,03/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,4,High,7,Risk of Violence,-1.03,8,High,New,1,0 +37963,60204,54685,PRETRIAL,McCutchen,Brandon,NULL,Male,African-American,03/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +37963,60204,54685,PRETRIAL,McCutchen,Brandon,NULL,Male,African-American,03/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53226,60195,54676,PRETRIAL,White,Vaughn,NULL,Male,Other,06/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +53226,60195,54676,PRETRIAL,White,Vaughn,NULL,Male,Other,06/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +53226,60195,54676,PRETRIAL,White,Vaughn,NULL,Male,Other,06/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +13917,60197,54678,PRETRIAL,WHITE,DANIEL,NULL,Male,Caucasian,08/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/22/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +13917,60197,54678,PRETRIAL,WHITE,DANIEL,NULL,Male,Caucasian,08/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/22/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +13917,60197,54678,PRETRIAL,WHITE,DANIEL,NULL,Male,Caucasian,08/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/22/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53268,60246,54722,PRETRIAL,Anderson,Anthony,NULL,Male,African-American,02/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +53268,60246,54722,PRETRIAL,Anderson,Anthony,NULL,Male,African-American,02/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +53268,60246,54722,PRETRIAL,Anderson,Anthony,NULL,Male,African-American,02/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53270,60248,54724,PRETRIAL,Edwards,Silburn,NULL,Male,African-American,11/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/23/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +53270,60248,54724,PRETRIAL,Edwards,Silburn,NULL,Male,African-American,11/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/23/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +53270,60248,54724,PRETRIAL,Edwards,Silburn,NULL,Male,African-American,11/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53259,60239,54718,PRETRIAL,Slowden,Cassio,Orville,Male,Other,10/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +53259,60239,54718,PRETRIAL,Slowden,Cassio,Orville,Male,Other,10/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +53259,60239,54718,PRETRIAL,Slowden,Cassio,Orville,Male,Other,10/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +44206,60253,54729,PRETRIAL,Singh,Robert,Taylor,Male,African-American,01/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,7,Risk of Violence,-0.9,9,High,New,1,0 +44206,60253,54729,PRETRIAL,Singh,Robert,Taylor,Male,African-American,01/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,8,Risk of Recidivism,0.32,9,High,New,1,0 +44206,60253,54729,PRETRIAL,Singh,Robert,Taylor,Male,African-American,01/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53272,60251,54727,PRETRIAL,Bortnovskiy,Sergey,NULL,Male,Caucasian,01/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +53272,60251,54727,PRETRIAL,Bortnovskiy,Sergey,NULL,Male,Caucasian,01/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +53272,60251,54727,PRETRIAL,Bortnovskiy,Sergey,NULL,Male,Caucasian,01/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53278,60260,54734,PRETRIAL,Montefrante,Daniel,NULL,Male,Caucasian,04/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +53278,60260,54734,PRETRIAL,Montefrante,Daniel,NULL,Male,Caucasian,04/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +53278,60260,54734,PRETRIAL,Montefrante,Daniel,NULL,Male,Caucasian,04/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53275,60255,54731,PRETRIAL,Aragona,Kim,NULL,Female,Caucasian,03/10/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/23/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +53275,60255,54731,PRETRIAL,Aragona,Kim,NULL,Female,Caucasian,03/10/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/23/13 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +53275,60255,54731,PRETRIAL,Aragona,Kim,NULL,Female,Caucasian,03/10/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +3580,60243,3294,PRETRIAL,GONZALEZ,MICHAEL,PAUL,Male,Caucasian,06/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,Copy,1,0 +3580,60243,3294,PRETRIAL,GONZALEZ,MICHAEL,PAUL,Male,Caucasian,06/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.82,10,High,Copy,1,0 +3580,60243,3294,PRETRIAL,GONZALEZ,MICHAEL,PAUL,Male,Caucasian,06/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +53271,60250,54726,PRETRIAL,DAGNELL,CARMINE,NULL,Male,Caucasian,09/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +53271,60250,54726,PRETRIAL,DAGNELL,CARMINE,NULL,Male,Caucasian,09/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +53271,60250,54726,PRETRIAL,DAGNELL,CARMINE,NULL,Male,Caucasian,09/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +16766,60235,54714,PRETRIAL,Worthy,Jeffrey,Kenneth,Male,African-American,07/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +16766,60235,54714,PRETRIAL,Worthy,Jeffrey,Kenneth,Male,African-American,07/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,New,1,0 +16766,60235,54714,PRETRIAL,Worthy,Jeffrey,Kenneth,Male,African-American,07/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +13274,60242,12694,PRETRIAL,MILLER,TONY,BERNARD,Male,African-American,07/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,Copy,1,0 +13274,60242,12694,PRETRIAL,MILLER,TONY,BERNARD,Male,African-American,07/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,8,Risk of Recidivism,0.18,8,High,Copy,1,0 +13274,60242,12694,PRETRIAL,MILLER,TONY,BERNARD,Male,African-American,07/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +53276,60258,54732,PRETRIAL,Orr,Daryll,NULL,Male,African-American,12/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +53276,60258,54732,PRETRIAL,Orr,Daryll,NULL,Male,African-American,12/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +53276,60258,54732,PRETRIAL,Orr,Daryll,NULL,Male,African-American,12/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53267,60245,54721,PRETRIAL,Davis,Jessie,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +53267,60245,54721,PRETRIAL,Davis,Jessie,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +53267,60245,54721,PRETRIAL,Davis,Jessie,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53264,60237,54716,PRETRIAL,Owens,William,Erroll,Male,Caucasian,08/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +53264,60237,54716,PRETRIAL,Owens,William,Erroll,Male,Caucasian,08/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +53264,60237,54716,PRETRIAL,Owens,William,Erroll,Male,Caucasian,08/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53273,60252,54728,PRETRIAL,Jacksonminott,Denise,NULL,Female,African-American,07/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +53273,60252,54728,PRETRIAL,Jacksonminott,Denise,NULL,Female,African-American,07/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +53273,60252,54728,PRETRIAL,Jacksonminott,Denise,NULL,Female,African-American,07/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53277,60259,54733,PRETRIAL,Dreval,Stanislav,NULL,Male,Caucasian,11/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +53277,60259,54733,PRETRIAL,Dreval,Stanislav,NULL,Male,Caucasian,11/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +53277,60259,54733,PRETRIAL,Dreval,Stanislav,NULL,Male,Caucasian,11/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53265,60238,54717,PRETRIAL,Howard,James,Reannea,Male,African-American,10/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +53265,60238,54717,PRETRIAL,Howard,James,Reannea,Male,African-American,10/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,8,Risk of Recidivism,0.71,10,High,New,1,0 +53265,60238,54717,PRETRIAL,Howard,James,Reannea,Male,African-American,10/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +9544,60256,37725,PRETRIAL,YOPP,FRANSHUN,DEVON,Male,African-American,08/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,Copy,1,0 +9544,60256,37725,PRETRIAL,YOPP,FRANSHUN,DEVON,Male,African-American,08/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.87,10,High,Copy,1,0 +9544,60256,37725,PRETRIAL,YOPP,FRANSHUN,DEVON,Male,African-American,08/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +53269,60247,54723,PRETRIAL,Christie,Nathan,NULL,Male,African-American,12/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +53269,60247,54723,PRETRIAL,Christie,Nathan,NULL,Male,African-American,12/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +53269,60247,54723,PRETRIAL,Christie,Nathan,NULL,Male,African-American,12/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +45761,60240,54719,PRETRIAL,Juan,Rojas-Soto,Felipe,Male,Hispanic,12/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +45761,60240,54719,PRETRIAL,Juan,Rojas-Soto,Felipe,Male,Hispanic,12/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +45761,60240,54719,PRETRIAL,Juan,Rojas-Soto,Felipe,Male,Hispanic,12/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53274,60254,54730,PRETRIAL,Smith,Mark,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +53274,60254,54730,PRETRIAL,Smith,Mark,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +53274,60254,54730,PRETRIAL,Smith,Mark,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53279,60261,54735,PRETRIAL,DELSOLAR,PIERO,NULL,Male,Caucasian,05/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +53279,60261,54735,PRETRIAL,DELSOLAR,PIERO,NULL,Male,Caucasian,05/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +53279,60261,54735,PRETRIAL,DELSOLAR,PIERO,NULL,Male,Caucasian,05/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +3251,60257,2964,Probation,Campbell,Gregory,NULL,Male,African-American,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,Copy,1,0 +3251,60257,2964,Probation,Campbell,Gregory,NULL,Male,African-American,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,8,Risk of Recidivism,0.53,9,High,Copy,1,0 +3251,60257,2964,Probation,Campbell,Gregory,NULL,Male,African-American,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +53258,60236,54715,PRETRIAL,Peatman,Kevin,NULL,Male,Caucasian,03/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +53258,60236,54715,PRETRIAL,Peatman,Kevin,NULL,Male,Caucasian,03/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +53258,60236,54715,PRETRIAL,Peatman,Kevin,NULL,Male,Caucasian,03/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +11522,60244,11048,Probation,Thompson,Jeanette,NULL,Female,African-American,01/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,Copy,1,0 +11522,60244,11048,Probation,Thompson,Jeanette,NULL,Female,African-American,01/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,10,High,Copy,1,0 +11522,60244,11048,Probation,Thompson,Jeanette,NULL,Female,African-American,01/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +19282,60249,54725,PRETRIAL,Candelaria,Lester,F,Male,Hispanic,12/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +19282,60249,54725,PRETRIAL,Candelaria,Lester,F,Male,Hispanic,12/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +19282,60249,54725,PRETRIAL,Candelaria,Lester,F,Male,Hispanic,12/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53266,60241,54720,PRETRIAL,Allen,Sugar,Ray,Male,African-American,06/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +53266,60241,54720,PRETRIAL,Allen,Sugar,Ray,Male,African-American,06/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +53266,60241,54720,PRETRIAL,Allen,Sugar,Ray,Male,African-American,06/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53286,60270,54742,PRETRIAL,Conser,Eric,NULL,Male,Caucasian,01/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +53286,60270,54742,PRETRIAL,Conser,Eric,NULL,Male,Caucasian,01/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +53286,60270,54742,PRETRIAL,Conser,Eric,NULL,Male,Caucasian,01/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +1502,1310,1198,PRETRIAL,DIXON,DUVAL,J,Male,African-American,01/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +1502,1310,1198,PRETRIAL,DIXON,DUVAL,J,Male,African-American,01/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +1502,1310,1198,PRETRIAL,DIXON,DUVAL,J,Male,African-American,01/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53280,60262,54736,PRETRIAL,Montgomery,Mark,NULL,Male,African-American,11/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.22,4,Low,New,1,0 +53280,60262,54736,PRETRIAL,Montgomery,Mark,NULL,Male,African-American,11/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +53280,60262,54736,PRETRIAL,Montgomery,Mark,NULL,Male,African-American,11/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +28188,60265,27253,PRETRIAL,Cameron,Leevaughn,A,Male,African-American,03/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,Copy,1,0 +28188,60265,27253,PRETRIAL,Cameron,Leevaughn,A,Male,African-American,03/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,Copy,1,0 +28188,60265,27253,PRETRIAL,Cameron,Leevaughn,A,Male,African-American,03/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +53293,60278,54748,PRETRIAL,MALARIC,VICTOR,NULL,Male,Caucasian,01/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +53293,60278,54748,PRETRIAL,MALARIC,VICTOR,NULL,Male,Caucasian,01/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +53293,60278,54748,PRETRIAL,MALARIC,VICTOR,NULL,Male,Caucasian,01/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53295,60280,54750,PRETRIAL,Alvarez,Prem,NULL,Male,Hispanic,04/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +53295,60280,54750,PRETRIAL,Alvarez,Prem,NULL,Male,Hispanic,04/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +53295,60280,54750,PRETRIAL,Alvarez,Prem,NULL,Male,Hispanic,04/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53288,60272,54744,PRETRIAL,CAFFARILLA,NICHOLAS,NULL,Male,Caucasian,12/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +53288,60272,54744,PRETRIAL,CAFFARILLA,NICHOLAS,NULL,Male,Caucasian,12/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +53288,60272,54744,PRETRIAL,CAFFARILLA,NICHOLAS,NULL,Male,Caucasian,12/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +13795,60268,47397,PRETRIAL,Crowley,James,NULL,Male,Caucasian,09/22/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.42,3,Low,Copy,1,0 +13795,60268,47397,PRETRIAL,Crowley,James,NULL,Male,Caucasian,09/22/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,Copy,1,0 +13795,60268,47397,PRETRIAL,Crowley,James,NULL,Male,Caucasian,09/22/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +16814,60275,54746,PRETRIAL,Torres,Rafael,Ernesto,Male,Caucasian,02/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +16814,60275,54746,PRETRIAL,Torres,Rafael,Ernesto,Male,Caucasian,02/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +16814,60275,54746,PRETRIAL,Torres,Rafael,Ernesto,Male,Caucasian,02/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +8156,60273,7712,PRETRIAL,JEUDY,LEONCE,V,Male,African-American,08/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,Copy,1,0 +8156,60273,7712,PRETRIAL,JEUDY,LEONCE,V,Male,African-American,08/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,Copy,1,0 +8156,60273,7712,PRETRIAL,JEUDY,LEONCE,V,Male,African-American,08/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +1502,60277,1198,PRETRIAL,DIXON,DUVAL,J,Male,African-American,01/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,Copy,1,0 +1502,60277,1198,PRETRIAL,DIXON,DUVAL,J,Male,African-American,01/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,Copy,1,0 +1502,60277,1198,PRETRIAL,DIXON,DUVAL,J,Male,African-American,01/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +53283,60266,54739,PRETRIAL,HOLLMANN,MARIALYS,NULL,Female,Caucasian,07/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/24/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +53283,60266,54739,PRETRIAL,HOLLMANN,MARIALYS,NULL,Female,Caucasian,07/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/24/13 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +53283,60266,54739,PRETRIAL,HOLLMANN,MARIALYS,NULL,Female,Caucasian,07/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53294,60279,54749,PRETRIAL,Brantley,James,NULL,Male,African-American,01/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/24/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +53294,60279,54749,PRETRIAL,Brantley,James,NULL,Male,African-American,01/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/24/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +53294,60279,54749,PRETRIAL,Brantley,James,NULL,Male,African-American,01/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53281,60263,54737,PRETRIAL,BROWN,MELVIN,NULL,Male,African-American,07/31/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +53281,60263,54737,PRETRIAL,BROWN,MELVIN,NULL,Male,African-American,07/31/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +53281,60263,54737,PRETRIAL,BROWN,MELVIN,NULL,Male,African-American,07/31/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53287,60271,54743,PRETRIAL,Norfus,Coral,NULL,Male,African-American,05/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/24/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +53287,60271,54743,PRETRIAL,Norfus,Coral,NULL,Male,African-American,05/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +53287,60271,54743,PRETRIAL,Norfus,Coral,NULL,Male,African-American,05/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/24/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53282,60264,54738,PRETRIAL,Donner,Jhims,NULL,Male,African-American,04/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +53282,60264,54738,PRETRIAL,Donner,Jhims,NULL,Male,African-American,04/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +53282,60264,54738,PRETRIAL,Donner,Jhims,NULL,Male,African-American,04/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53284,60267,54740,PRETRIAL,KIFFIN,CLEVOR,NULL,Male,Caucasian,04/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +53284,60267,54740,PRETRIAL,KIFFIN,CLEVOR,NULL,Male,Caucasian,04/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +53284,60267,54740,PRETRIAL,KIFFIN,CLEVOR,NULL,Male,Caucasian,04/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53285,60269,54741,PRETRIAL,PENNANT,DAVID,NULL,Male,Other,03/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/24/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +53285,60269,54741,PRETRIAL,PENNANT,DAVID,NULL,Male,Other,03/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/24/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +53285,60269,54741,PRETRIAL,PENNANT,DAVID,NULL,Male,Other,03/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53289,60274,54745,PRETRIAL,Alvarez,Nicholas,NULL,Male,Hispanic,04/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +53289,60274,54745,PRETRIAL,Alvarez,Nicholas,NULL,Male,Hispanic,04/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +53289,60274,54745,PRETRIAL,Alvarez,Nicholas,NULL,Male,Hispanic,04/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53290,60276,54747,PRETRIAL,Zephir,Daniel,NULL,Male,African-American,12/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +53290,60276,54747,PRETRIAL,Zephir,Daniel,NULL,Male,African-American,12/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +53290,60276,54747,PRETRIAL,Zephir,Daniel,NULL,Male,African-American,12/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53309,60295,54764,PRETRIAL,Garcia-Fernandez,Yanielys,NULL,Female,Hispanic,08/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +53309,60295,54764,PRETRIAL,Garcia-Fernandez,Yanielys,NULL,Female,Hispanic,08/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +53309,60295,54764,PRETRIAL,Garcia-Fernandez,Yanielys,NULL,Female,Hispanic,08/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53311,60297,54766,Probation,O'Neill,Steven,George,Male,Caucasian,06/18/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.57,2,Low,New,1,0 +53311,60297,54766,Probation,O'Neill,Steven,George,Male,Caucasian,06/18/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +53311,60297,54766,Probation,O'Neill,Steven,George,Male,Caucasian,06/18/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +53305,60290,54760,PRETRIAL,Smith,Darvin,NULL,Male,African-American,12/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +53305,60290,54760,PRETRIAL,Smith,Darvin,NULL,Male,African-American,12/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +53305,60290,54760,PRETRIAL,Smith,Darvin,NULL,Male,African-American,12/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53317,60304,54772,Probation,SHELTON,JAMERSON,NULL,Male,African-American,03/24/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/25/13 0:00,2,Medium,7,Risk of Violence,-2.85,2,Low,New,1,0 +53317,60304,54772,Probation,SHELTON,JAMERSON,NULL,Male,African-American,03/24/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +53317,60304,54772,Probation,SHELTON,JAMERSON,NULL,Male,African-American,03/24/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/25/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +13580,13976,12975,PRETRIAL,HUMPHREY,LEE,ANDREW,Male,African-American,08/31/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +13580,13976,12975,PRETRIAL,HUMPHREY,LEE,ANDREW,Male,African-American,08/31/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +13580,13976,12975,PRETRIAL,HUMPHREY,LEE,ANDREW,Male,African-American,08/31/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53323,60311,54779,Probation,Gonzalez Cruz,Carlos,Ivan,Male,Hispanic,08/03/75,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +53323,60311,54779,Probation,Gonzalez Cruz,Carlos,Ivan,Male,Hispanic,08/03/75,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +53323,60311,54779,Probation,Gonzalez Cruz,Carlos,Ivan,Male,Hispanic,08/03/75,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53328,60318,54785,Probation,SOUTO,ULYSSES,NULL,Male,Hispanic,11/14/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/25/13 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +53328,60318,54785,Probation,SOUTO,ULYSSES,NULL,Male,Hispanic,11/14/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/25/13 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +53328,60318,54785,Probation,SOUTO,ULYSSES,NULL,Male,Hispanic,11/14/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53296,60281,54751,PRETRIAL,Prince-Newland,Okeel,NULL,Male,Other,07/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +53296,60281,54751,PRETRIAL,Prince-Newland,Okeel,NULL,Male,Other,07/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +53296,60281,54751,PRETRIAL,Prince-Newland,Okeel,NULL,Male,Other,07/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53301,60285,54755,PRETRIAL,Dukes,Jamar,Torrynce,Male,African-American,02/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.86,9,High,New,1,0 +53301,60285,54755,PRETRIAL,Dukes,Jamar,Torrynce,Male,African-American,02/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +53301,60285,54755,PRETRIAL,Dukes,Jamar,Torrynce,Male,African-American,02/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53318,60306,54774,Probation,Ponz,Nelson,NULL,Male,Hispanic,06/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +53318,60306,54774,Probation,Ponz,Nelson,NULL,Male,Hispanic,06/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +53318,60306,54774,Probation,Ponz,Nelson,NULL,Male,Hispanic,06/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53330,60320,54787,Probation,ROBINSON,KRYSTAL,NULL,Female,African-American,01/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +53330,60320,54787,Probation,ROBINSON,KRYSTAL,NULL,Female,African-American,01/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +53330,60320,54787,Probation,ROBINSON,KRYSTAL,NULL,Female,African-American,01/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +31948,60323,54790,PRETRIAL,Charlier,Ford,NULL,Male,African-American,11/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,4,High,7,Risk of Violence,-0.71,9,High,New,1,0 +31948,60323,54790,PRETRIAL,Charlier,Ford,NULL,Male,African-American,11/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,4,High,8,Risk of Recidivism,0.99,10,High,New,1,0 +31948,60323,54790,PRETRIAL,Charlier,Ford,NULL,Male,African-American,11/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53315,60302,54771,PRETRIAL,Stepp,Jaime,NULL,Female,Caucasian,06/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +53315,60302,54771,PRETRIAL,Stepp,Jaime,NULL,Female,Caucasian,06/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +53315,60302,54771,PRETRIAL,Stepp,Jaime,NULL,Female,Caucasian,06/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +42183,60316,54783,PRETRIAL,Maxielee,Rachel,NULL,Female,African-American,10/21/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/25/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +42183,60316,54783,PRETRIAL,Maxielee,Rachel,NULL,Female,African-American,10/21/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +42183,60316,54783,PRETRIAL,Maxielee,Rachel,NULL,Female,African-American,10/21/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +46286,60300,54769,PRETRIAL,Gordon,Alton,NULL,Male,African-American,08/16/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +46286,60300,54769,PRETRIAL,Gordon,Alton,NULL,Male,African-American,08/16/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +46286,60300,54769,PRETRIAL,Gordon,Alton,NULL,Male,African-American,08/16/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53320,60308,54776,PRETRIAL,RODRIGUEZ,ROSE,NULL,Female,Caucasian,01/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +53320,60308,54776,PRETRIAL,RODRIGUEZ,ROSE,NULL,Female,Caucasian,01/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +53320,60308,54776,PRETRIAL,RODRIGUEZ,ROSE,NULL,Female,Caucasian,01/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53307,60292,54762,PRETRIAL,Ramsey,Mark,Anthony,Male,African-American,02/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +53307,60292,54762,PRETRIAL,Ramsey,Mark,Anthony,Male,African-American,02/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +53307,60292,54762,PRETRIAL,Ramsey,Mark,Anthony,Male,African-American,02/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53300,60284,54754,PRETRIAL,Perez,Juan,NULL,Male,Hispanic,05/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +53300,60284,54754,PRETRIAL,Perez,Juan,NULL,Male,Hispanic,05/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +53300,60284,54754,PRETRIAL,Perez,Juan,NULL,Male,Hispanic,05/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53302,60287,54757,PRETRIAL,WILLIAMS,EARL,C,Male,African-American,07/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/25/13 0:00,2,Medium,7,Risk of Violence,-2.79,2,Low,New,1,0 +53302,60287,54757,PRETRIAL,WILLIAMS,EARL,C,Male,African-American,07/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +53302,60287,54757,PRETRIAL,WILLIAMS,EARL,C,Male,African-American,07/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/25/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53316,60305,54773,Broward County,Aragon,Michael,NULL,Male,Caucasian,04/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +53316,60305,54773,Broward County,Aragon,Michael,NULL,Male,Caucasian,04/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +53316,60305,54773,Broward County,Aragon,Michael,NULL,Male,Caucasian,04/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53326,60315,54782,PRETRIAL,Vargas,Alexander,NULL,Male,Hispanic,11/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/25/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +53326,60315,54782,PRETRIAL,Vargas,Alexander,NULL,Male,Hispanic,11/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +53326,60315,54782,PRETRIAL,Vargas,Alexander,NULL,Male,Hispanic,11/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/25/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53308,60294,54763,PRETRIAL,Martinez,Wendy,NULL,Female,Caucasian,09/18/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/25/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +53308,60294,54763,PRETRIAL,Martinez,Wendy,NULL,Female,Caucasian,09/18/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +53308,60294,54763,PRETRIAL,Martinez,Wendy,NULL,Female,Caucasian,09/18/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53329,60319,54786,Probation,Robinson,Alexander,NULL,Male,African-American,01/22/38,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/25/13 0:00,1,Low,7,Risk of Violence,-4.64,1,Low,New,1,0 +53329,60319,54786,Probation,Robinson,Alexander,NULL,Male,African-American,01/22/38,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/25/13 0:00,1,Low,8,Risk of Recidivism,-2.82,1,Low,New,1,0 +53329,60319,54786,Probation,Robinson,Alexander,NULL,Male,African-American,01/22/38,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53333,60324,54791,Broward County,Brooks,Brandon,NULL,Male,African-American,06/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +53333,60324,54791,Broward County,Brooks,Brandon,NULL,Male,African-American,06/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +53333,60324,54791,Broward County,Brooks,Brandon,NULL,Male,African-American,06/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53297,60282,54752,PRETRIAL,MCEACHRANE,KIM,NICOLE,Female,African-American,06/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +53297,60282,54752,PRETRIAL,MCEACHRANE,KIM,NICOLE,Female,African-American,06/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +53297,60282,54752,PRETRIAL,MCEACHRANE,KIM,NICOLE,Female,African-American,06/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53304,60289,54759,PRETRIAL,Rickard,Marion,NULL,Male,Asian,04/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +53304,60289,54759,PRETRIAL,Rickard,Marion,NULL,Male,Asian,04/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +53304,60289,54759,PRETRIAL,Rickard,Marion,NULL,Male,Asian,04/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +13580,60312,12975,PRETRIAL,HUMPHREY,LEE,ANDREW,Male,African-American,08/31/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,Copy,1,0 +13580,60312,12975,PRETRIAL,HUMPHREY,LEE,ANDREW,Male,African-American,08/31/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,Copy,1,0 +13580,60312,12975,PRETRIAL,HUMPHREY,LEE,ANDREW,Male,African-American,08/31/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +53322,60310,54778,Probation,Bailey,Sherrie,NULL,Female,Caucasian,06/28/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +53322,60310,54778,Probation,Bailey,Sherrie,NULL,Female,Caucasian,06/28/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +53322,60310,54778,Probation,Bailey,Sherrie,NULL,Female,Caucasian,06/28/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53332,60322,54789,Probation,Marcel,Annie,Ercilia,Female,Hispanic,03/22/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +53332,60322,54789,Probation,Marcel,Annie,Ercilia,Female,Hispanic,03/22/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +53332,60322,54789,Probation,Marcel,Annie,Ercilia,Female,Hispanic,03/22/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +38924,60286,54756,PRETRIAL,Robinson,Tanisha,NULL,Female,African-American,07/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +38924,60286,54756,PRETRIAL,Robinson,Tanisha,NULL,Female,African-American,07/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.1,8,High,New,1,0 +38924,60286,54756,PRETRIAL,Robinson,Tanisha,NULL,Female,African-American,07/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +7197,60293,6783,PRETRIAL,vanfossen,timothy,NULL,Male,Caucasian,03/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,Copy,1,0 +7197,60293,6783,PRETRIAL,vanfossen,timothy,NULL,Male,Caucasian,03/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,Copy,1,0 +7197,60293,6783,PRETRIAL,vanfossen,timothy,NULL,Male,Caucasian,03/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,2,Medium,18,Risk of Failure to Appear,19,2,Low,Copy,1,0 +53319,60307,54775,PRETRIAL,RIVERA,EVELYN,NULL,Female,Caucasian,04/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +53319,60307,54775,PRETRIAL,RIVERA,EVELYN,NULL,Female,Caucasian,04/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +53319,60307,54775,PRETRIAL,RIVERA,EVELYN,NULL,Female,Caucasian,04/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53312,60299,54768,PRETRIAL,Gonzalez-Estrella,Carlos,J,Male,Hispanic,09/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +53312,60299,54768,PRETRIAL,Gonzalez-Estrella,Carlos,J,Male,Hispanic,09/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +53312,60299,54768,PRETRIAL,Gonzalez-Estrella,Carlos,J,Male,Hispanic,09/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53314,60301,54770,Probation,Perkins,Thomas,NULL,Male,African-American,02/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +53314,60301,54770,Probation,Perkins,Thomas,NULL,Male,African-American,02/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +53314,60301,54770,Probation,Perkins,Thomas,NULL,Male,African-American,02/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53299,60283,54753,PRETRIAL,REDMOND,ERIC,S,Male,Caucasian,06/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +53299,60283,54753,PRETRIAL,REDMOND,ERIC,S,Male,Caucasian,06/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +53299,60283,54753,PRETRIAL,REDMOND,ERIC,S,Male,Caucasian,06/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +53327,60317,54784,PRETRIAL,velasquez,stephanie,NULL,Female,Hispanic,01/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +53327,60317,54784,PRETRIAL,velasquez,stephanie,NULL,Female,Hispanic,01/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +53327,60317,54784,PRETRIAL,velasquez,stephanie,NULL,Female,Hispanic,01/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53303,60288,54758,PRETRIAL,WARRINGTON,WILLIAM,T,Male,Caucasian,07/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +53303,60288,54758,PRETRIAL,WARRINGTON,WILLIAM,T,Male,Caucasian,07/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +53303,60288,54758,PRETRIAL,WARRINGTON,WILLIAM,T,Male,Caucasian,07/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53306,60291,54761,PRETRIAL,Vanasse,Kurt,NULL,Male,Caucasian,08/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +53306,60291,54761,PRETRIAL,Vanasse,Kurt,NULL,Male,Caucasian,08/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +53306,60291,54761,PRETRIAL,Vanasse,Kurt,NULL,Male,Caucasian,08/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53321,60309,54777,Probation,YAMBO,EDWARD,NULL,Male,Hispanic,02/12/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/25/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +53321,60309,54777,Probation,YAMBO,EDWARD,NULL,Male,Hispanic,02/12/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/25/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +53321,60309,54777,Probation,YAMBO,EDWARD,NULL,Male,Hispanic,02/12/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/25/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +40798,60359,54823,PRETRIAL,Quigley,William,NULL,Male,Caucasian,11/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +40798,60359,54823,PRETRIAL,Quigley,William,NULL,Male,Caucasian,11/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +40798,60359,54823,PRETRIAL,Quigley,William,NULL,Male,Caucasian,11/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +41260,60338,54805,PRETRIAL,Almanza,Jorge,NULL,Male,Caucasian,05/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +41260,60338,54805,PRETRIAL,Almanza,Jorge,NULL,Male,Caucasian,05/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +41260,60338,54805,PRETRIAL,Almanza,Jorge,NULL,Male,Caucasian,05/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53354,60356,54820,PRETRIAL,Mcneil,Brandon,Fayon,Male,African-American,11/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +53354,60356,54820,PRETRIAL,Mcneil,Brandon,Fayon,Male,African-American,11/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +53354,60356,54820,PRETRIAL,Mcneil,Brandon,Fayon,Male,African-American,11/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53335,60330,54797,PRETRIAL,Forbes,Lamuel,Samuel,Male,African-American,03/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +53335,60330,54797,PRETRIAL,Forbes,Lamuel,Samuel,Male,African-American,03/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +53335,60330,54797,PRETRIAL,Forbes,Lamuel,Samuel,Male,African-American,03/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53361,60364,54828,Probation,Deluca,Linda,NULL,Female,Caucasian,10/26/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +53361,60364,54828,Probation,Deluca,Linda,NULL,Female,Caucasian,10/26/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,New,1,0 +53361,60364,54828,Probation,Deluca,Linda,NULL,Female,Caucasian,10/26/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53339,60335,54802,PRETRIAL,REID,ADREAN,NULL,Male,African-American,08/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +53339,60335,54802,PRETRIAL,REID,ADREAN,NULL,Male,African-American,08/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +53339,60335,54802,PRETRIAL,REID,ADREAN,NULL,Male,African-American,08/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53345,60343,54810,Probation,GADMAN,FRANK,NULL,Male,Caucasian,01/27/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,3/26/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +53345,60343,54810,Probation,GADMAN,FRANK,NULL,Male,Caucasian,01/27/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,3/26/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +53345,60343,54810,Probation,GADMAN,FRANK,NULL,Male,Caucasian,01/27/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +20656,60333,54800,PRETRIAL,CLEMONS,COY,ERIC,Male,African-American,06/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +20656,60333,54800,PRETRIAL,CLEMONS,COY,ERIC,Male,African-American,06/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +20656,60333,54800,PRETRIAL,CLEMONS,COY,ERIC,Male,African-American,06/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +53336,60331,54798,PRETRIAL,Mason,Michael,Gerod,Male,African-American,04/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/26/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +53336,60331,54798,PRETRIAL,Mason,Michael,Gerod,Male,African-American,04/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/26/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +53336,60331,54798,PRETRIAL,Mason,Michael,Gerod,Male,African-American,04/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/26/13 0:00,4,High,18,Risk of Failure to Appear,35,10,High,New,1,0 +53342,60340,54807,Probation,WRIGHT,ANTHONY,NULL,Male,African-American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +53342,60340,54807,Probation,WRIGHT,ANTHONY,NULL,Male,African-American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +53342,60340,54807,Probation,WRIGHT,ANTHONY,NULL,Male,African-American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53352,60354,54818,PRETRIAL,triana,belinda,NULL,Male,Caucasian,01/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/26/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +53352,60354,54818,PRETRIAL,triana,belinda,NULL,Male,Caucasian,01/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/26/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +53352,60354,54818,PRETRIAL,triana,belinda,NULL,Male,Caucasian,01/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53357,60361,54825,Probation,OBRIEN,DEVIN,NULL,Male,Caucasian,09/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.24,8,High,New,1,0 +53357,60361,54825,Probation,OBRIEN,DEVIN,NULL,Male,Caucasian,09/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +53357,60361,54825,Probation,OBRIEN,DEVIN,NULL,Male,Caucasian,09/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53363,60368,54831,Probation,Ramos,Giselle,NULL,Female,Hispanic,05/27/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/26/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +53363,60368,54831,Probation,Ramos,Giselle,NULL,Female,Hispanic,05/27/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +53363,60368,54831,Probation,Ramos,Giselle,NULL,Female,Hispanic,05/27/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53347,60349,54813,Probation,Williams,Erica,Nicole,Female,African-American,10/13/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +53347,60349,54813,Probation,Williams,Erica,Nicole,Female,African-American,10/13/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +53347,60349,54813,Probation,Williams,Erica,Nicole,Female,African-American,10/13/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +52848,60328,54795,PRETRIAL,PETERSEN,ANTHONY,BRUCE,Male,Caucasian,02/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +52848,60328,54795,PRETRIAL,PETERSEN,ANTHONY,BRUCE,Male,Caucasian,02/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +52848,60328,54795,PRETRIAL,PETERSEN,ANTHONY,BRUCE,Male,Caucasian,02/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53346,60345,54812,Probation,Miller,Edgar,NULL,Male,Caucasian,07/01/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +53346,60345,54812,Probation,Miller,Edgar,NULL,Male,Caucasian,07/01/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +53346,60345,54812,Probation,Miller,Edgar,NULL,Male,Caucasian,07/01/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53348,60366,54814,PRETRIAL,Gayle,Lorenzo,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.64,9,High,Copy,1,0 +53348,60366,54814,PRETRIAL,Gayle,Lorenzo,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,7,Medium,Copy,1,0 +53348,60366,54814,PRETRIAL,Gayle,Lorenzo,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +22856,60370,54833,PRETRIAL,Collins,James,Christophe,Male,Caucasian,02/23/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +22856,60370,54833,PRETRIAL,Collins,James,Christophe,Male,Caucasian,02/23/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +22856,60370,54833,PRETRIAL,Collins,James,Christophe,Male,Caucasian,02/23/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53353,60355,54819,PRETRIAL,Oneal,John,Henry,Male,African-American,02/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +53353,60355,54819,PRETRIAL,Oneal,John,Henry,Male,African-American,02/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +53353,60355,54819,PRETRIAL,Oneal,John,Henry,Male,African-American,02/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +53350,60352,54816,Probation,Manzano,Alberto,NULL,Male,Hispanic,05/26/47,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/26/13 0:00,1,Low,7,Risk of Violence,-4.5,1,Low,New,1,0 +53350,60352,54816,Probation,Manzano,Alberto,NULL,Male,Hispanic,05/26/47,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/26/13 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +53350,60352,54816,Probation,Manzano,Alberto,NULL,Male,Hispanic,05/26/47,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50976,60326,54793,PRETRIAL,YOUN,BRANDON,NULL,Male,African-American,03/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +50976,60326,54793,PRETRIAL,YOUN,BRANDON,NULL,Male,African-American,03/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +50976,60326,54793,PRETRIAL,YOUN,BRANDON,NULL,Male,African-American,03/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53356,60360,54824,Probation,Lakes,Harry,Bernard,Male,African-American,02/26/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +53356,60360,54824,Probation,Lakes,Harry,Bernard,Male,African-American,02/26/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +53356,60360,54824,Probation,Lakes,Harry,Bernard,Male,African-American,02/26/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +3145,60347,2859,PRETRIAL,pierrelouis,bouthy,NULL,Male,Other,01/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/26/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,Copy,1,0 +3145,60347,2859,PRETRIAL,pierrelouis,bouthy,NULL,Male,Other,01/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/26/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,Copy,1,0 +3145,60347,2859,PRETRIAL,pierrelouis,bouthy,NULL,Male,Other,01/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +32922,60344,54811,PRETRIAL,Keefer,Gary,NULL,Male,Caucasian,01/03/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +32922,60344,54811,PRETRIAL,Keefer,Gary,NULL,Male,Caucasian,01/03/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +32922,60344,54811,PRETRIAL,Keefer,Gary,NULL,Male,Caucasian,01/03/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +18210,60329,54796,PRETRIAL,BASS,ANTHONY,NULL,Male,African-American,05/08/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/26/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +18210,60329,54796,PRETRIAL,BASS,ANTHONY,NULL,Male,African-American,05/08/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +18210,60329,54796,PRETRIAL,BASS,ANTHONY,NULL,Male,African-American,05/08/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/26/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53360,60363,54827,Probation,STEIN,JOSHUA,L,Male,Caucasian,04/16/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +53360,60363,54827,Probation,STEIN,JOSHUA,L,Male,Caucasian,04/16/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +53360,60363,54827,Probation,STEIN,JOSHUA,L,Male,Caucasian,04/16/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +38907,60365,54829,PRETRIAL,Lui,Wing,NULL,Male,Asian,06/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/26/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +38907,60365,54829,PRETRIAL,Lui,Wing,NULL,Male,Asian,06/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +38907,60365,54829,PRETRIAL,Lui,Wing,NULL,Male,Asian,06/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53340,60336,54803,PRETRIAL,SERPHIN,ANTHONY,NULL,Male,African-American,04/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +53340,60336,54803,PRETRIAL,SERPHIN,ANTHONY,NULL,Male,African-American,04/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +53340,60336,54803,PRETRIAL,SERPHIN,ANTHONY,NULL,Male,African-American,04/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52646,60357,54821,PRETRIAL,Wilson,Brandon,NULL,Male,African-American,06/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,4,High,7,Risk of Violence,-1.03,8,High,New,1,0 +52646,60357,54821,PRETRIAL,Wilson,Brandon,NULL,Male,African-American,06/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +52646,60357,54821,PRETRIAL,Wilson,Brandon,NULL,Male,African-American,06/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53364,60371,54834,Probation,Covert,Laurie,NULL,Female,Caucasian,04/15/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/26/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +53364,60371,54834,Probation,Covert,Laurie,NULL,Female,Caucasian,04/15/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/26/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +53364,60371,54834,Probation,Covert,Laurie,NULL,Female,Caucasian,04/15/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51599,60327,54794,PRETRIAL,VELASQUES,LUIS,NULL,Male,Caucasian,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +51599,60327,54794,PRETRIAL,VELASQUES,LUIS,NULL,Male,Caucasian,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +51599,60327,54794,PRETRIAL,VELASQUES,LUIS,NULL,Male,Caucasian,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53343,60341,54808,Probation,Princilus,Denis,NULL,Male,African-American,09/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +53343,60341,54808,Probation,Princilus,Denis,NULL,Male,African-American,09/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +53343,60341,54808,Probation,Princilus,Denis,NULL,Male,African-American,09/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +8021,60337,54804,PRETRIAL,BROCK,JOSEPH,NULL,Male,Caucasian,10/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +8021,60337,54804,PRETRIAL,BROCK,JOSEPH,NULL,Male,Caucasian,10/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +8021,60337,54804,PRETRIAL,BROCK,JOSEPH,NULL,Male,Caucasian,10/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53355,60358,54822,Probation,Harden,Hezekiah,NULL,Male,African-American,08/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +53355,60358,54822,Probation,Harden,Hezekiah,NULL,Male,African-American,08/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +53355,60358,54822,Probation,Harden,Hezekiah,NULL,Male,African-American,08/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +53337,60332,54799,PRETRIAL,Davenport,Najeh,NULL,Male,African-American,02/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/26/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +53337,60332,54799,PRETRIAL,Davenport,Najeh,NULL,Male,African-American,02/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +53337,60332,54799,PRETRIAL,Davenport,Najeh,NULL,Male,African-American,02/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53358,60362,54826,Probation,mccann,joanne,NULL,Female,Caucasian,04/11/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +53358,60362,54826,Probation,mccann,joanne,NULL,Female,Caucasian,04/11/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +53358,60362,54826,Probation,mccann,joanne,NULL,Female,Caucasian,04/11/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53334,60325,54792,PRETRIAL,Hilliard,Xavier,NULL,Male,African-American,05/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +53334,60325,54792,PRETRIAL,Hilliard,Xavier,NULL,Male,African-American,05/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +53334,60325,54792,PRETRIAL,Hilliard,Xavier,NULL,Male,African-American,05/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53351,60353,54817,Probation,Voyages,Harry,NULL,Male,Caucasian,02/08/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/26/13 0:00,1,Low,7,Risk of Violence,-4.38,1,Low,New,1,0 +53351,60353,54817,Probation,Voyages,Harry,NULL,Male,Caucasian,02/08/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/26/13 0:00,1,Low,8,Risk of Recidivism,-2.6,1,Low,New,1,0 +53351,60353,54817,Probation,Voyages,Harry,NULL,Male,Caucasian,02/08/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +45354,60346,45587,PRETRIAL,SMITH,JASON,NULL,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,Copy,1,0 +45354,60346,45587,PRETRIAL,SMITH,JASON,NULL,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.41,5,Medium,Copy,1,0 +45354,60346,45587,PRETRIAL,SMITH,JASON,NULL,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +23719,60348,22921,PRETRIAL,Bynes,Jarel,Bernard,Male,African-American,01/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,Copy,1,0 +23719,60348,22921,PRETRIAL,Bynes,Jarel,Bernard,Male,African-American,01/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,Copy,1,0 +23719,60348,22921,PRETRIAL,Bynes,Jarel,Bernard,Male,African-American,01/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +53362,60367,54830,Probation,Williamsrose,Paquita,D,Female,African-American,10/20/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/26/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +53362,60367,54830,Probation,Williamsrose,Paquita,D,Female,African-American,10/20/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +53362,60367,54830,Probation,Williamsrose,Paquita,D,Female,African-American,10/20/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +26692,60369,54832,Probation,PRYCE,CLEVE,ANTHONY,Male,African-American,09/23/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +26692,60369,54832,Probation,PRYCE,CLEVE,ANTHONY,Male,African-American,09/23/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +26692,60369,54832,Probation,PRYCE,CLEVE,ANTHONY,Male,African-American,09/23/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53366,60374,54837,PRETRIAL,WRIGHT,ISAAC,NULL,Male,African-American,07/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +53366,60374,54837,PRETRIAL,WRIGHT,ISAAC,NULL,Male,African-American,07/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +53366,60374,54837,PRETRIAL,WRIGHT,ISAAC,NULL,Male,African-American,07/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53367,60376,54839,PRETRIAL,Grajales,Fermin,NULL,Male,Hispanic,10/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +53367,60376,54839,PRETRIAL,Grajales,Fermin,NULL,Male,Hispanic,10/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +53367,60376,54839,PRETRIAL,Grajales,Fermin,NULL,Male,Hispanic,10/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +17015,60395,54856,PRETRIAL,BRISTOL,SHENARD,NULL,Male,African-American,12/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +17015,60395,54856,PRETRIAL,BRISTOL,SHENARD,NULL,Male,African-American,12/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +17015,60395,54856,PRETRIAL,BRISTOL,SHENARD,NULL,Male,African-American,12/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53381,60397,54858,PRETRIAL,deravines,gueslly,NULL,Male,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-1.43,7,Medium,New,1,0 +53381,60397,54858,PRETRIAL,deravines,gueslly,NULL,Male,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +53381,60397,54858,PRETRIAL,deravines,gueslly,NULL,Male,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +12087,60390,54851,Probation,Mateo,Jeffrey,NULL,Male,Hispanic,08/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,4,High,7,Risk of Violence,-1.23,8,High,New,1,0 +12087,60390,54851,Probation,Mateo,Jeffrey,NULL,Male,Hispanic,08/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,4,High,8,Risk of Recidivism,1.39,10,High,New,1,0 +12087,60390,54851,Probation,Mateo,Jeffrey,NULL,Male,Hispanic,08/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,4,High,18,Risk of Failure to Appear,38,10,High,New,1,0 +38396,60404,54863,PRETRIAL,Duperier,Claudel,NULL,Male,African-American,07/01/86,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +38396,60404,54863,PRETRIAL,Duperier,Claudel,NULL,Male,African-American,07/01/86,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +38396,60404,54863,PRETRIAL,Duperier,Claudel,NULL,Male,African-American,07/01/86,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52867,60379,54842,PRETRIAL,KANE,KYLE,KEITH,Male,Caucasian,06/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +52867,60379,54842,PRETRIAL,KANE,KYLE,KEITH,Male,Caucasian,06/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +52867,60379,54842,PRETRIAL,KANE,KYLE,KEITH,Male,Caucasian,06/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53371,60383,54846,PRETRIAL,Gayle,Troy,NULL,Male,African-American,11/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +53371,60383,54846,PRETRIAL,Gayle,Troy,NULL,Male,African-American,11/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +53371,60383,54846,PRETRIAL,Gayle,Troy,NULL,Male,African-American,11/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53378,60392,54853,PRETRIAL,Alfonso,Emilio,NULL,Male,Caucasian,09/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +53378,60392,54853,PRETRIAL,Alfonso,Emilio,NULL,Male,Caucasian,09/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +53378,60392,54853,PRETRIAL,Alfonso,Emilio,NULL,Male,Caucasian,09/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +1918,60388,53271,PRETRIAL,OBRIEN,JOHN,NULL,Male,Caucasian,07/20/77,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +1918,60388,53271,PRETRIAL,OBRIEN,JOHN,NULL,Male,Caucasian,07/20/77,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +1918,60388,53271,PRETRIAL,OBRIEN,JOHN,NULL,Male,Caucasian,07/20/77,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +34944,60409,53278,Probation,salomon,eclaire,NULL,Male,African-American,07/10/86,17,All Scales,Intake,English,Post Sentence,Probation,Married,3/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +34944,60409,53278,Probation,salomon,eclaire,NULL,Male,African-American,07/10/86,17,All Scales,Intake,English,Post Sentence,Probation,Married,3/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +34944,60409,53278,Probation,salomon,eclaire,NULL,Male,African-American,07/10/86,17,All Scales,Intake,English,Post Sentence,Probation,Married,3/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +29445,60407,54866,Probation,Bergamini,Rafaela,NULL,Female,Caucasian,07/10/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +29445,60407,54866,Probation,Bergamini,Rafaela,NULL,Female,Caucasian,07/10/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,7,Medium,New,1,0 +29445,60407,54866,Probation,Bergamini,Rafaela,NULL,Female,Caucasian,07/10/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53373,60386,54849,Probation,Bruno,Christian,Fabian,Male,Hispanic,10/13/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-2.71,2,Low,New,1,0 +53373,60386,54849,Probation,Bruno,Christian,Fabian,Male,Hispanic,10/13/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +53373,60386,54849,Probation,Bruno,Christian,Fabian,Male,Hispanic,10/13/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +53369,60378,54841,PRETRIAL,Joseph,Lawrence,NULL,Male,African-American,07/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +53369,60378,54841,PRETRIAL,Joseph,Lawrence,NULL,Male,African-American,07/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +53369,60378,54841,PRETRIAL,Joseph,Lawrence,NULL,Male,African-American,07/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53383,60399,54860,PRETRIAL,ANDERSON,WALTER,NULL,Male,African-American,11/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/27/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +53383,60399,54860,PRETRIAL,ANDERSON,WALTER,NULL,Male,African-American,11/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/27/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +53383,60399,54860,PRETRIAL,ANDERSON,WALTER,NULL,Male,African-American,11/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +53370,60381,54844,PRETRIAL,Stinson,Gregory,Wayne,Male,Caucasian,10/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +53370,60381,54844,PRETRIAL,Stinson,Gregory,Wayne,Male,Caucasian,10/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +53370,60381,54844,PRETRIAL,Stinson,Gregory,Wayne,Male,Caucasian,10/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53379,60394,54855,Probation,Cooper,Fatimah,NULL,Female,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +53379,60394,54855,Probation,Cooper,Fatimah,NULL,Female,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +53379,60394,54855,Probation,Cooper,Fatimah,NULL,Female,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53385,60402,54862,Probation,HAKH,MOHAMMED,S,Male,African-American,08/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/27/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +53385,60402,54862,Probation,HAKH,MOHAMMED,S,Male,African-American,08/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/27/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +53385,60402,54862,Probation,HAKH,MOHAMMED,S,Male,African-American,08/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53365,60373,54836,PRETRIAL,Madison,Sherif,NULL,Male,African-American,10/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +53365,60373,54836,PRETRIAL,Madison,Sherif,NULL,Male,African-American,10/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +53365,60373,54836,PRETRIAL,Madison,Sherif,NULL,Male,African-American,10/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +7663,60387,7249,DRRD,bienaime,bendik,NULL,Male,African-American,08/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +7663,60387,7249,DRRD,bienaime,bendik,NULL,Male,African-American,08/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +7663,60387,7249,DRRD,bienaime,bendik,NULL,Male,African-American,08/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +53386,60405,54864,Probation,Cason,Bridgett,NULL,Female,African-American,11/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +53386,60405,54864,Probation,Cason,Bridgett,NULL,Female,African-American,11/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +53386,60405,54864,Probation,Cason,Bridgett,NULL,Female,African-American,11/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +33556,60384,54847,PRETRIAL,HUERTA,KERVIN,GUTIERREZ,Male,Caucasian,09/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.09,4,Low,New,1,0 +33556,60384,54847,PRETRIAL,HUERTA,KERVIN,GUTIERREZ,Male,Caucasian,09/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +33556,60384,54847,PRETRIAL,HUERTA,KERVIN,GUTIERREZ,Male,Caucasian,09/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53376,60391,54852,Probation,johnson,samantha,NULL,Female,African-American,03/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +53376,60391,54852,Probation,johnson,samantha,NULL,Female,African-American,03/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +53376,60391,54852,Probation,johnson,samantha,NULL,Female,African-American,03/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +53380,60396,54857,PRETRIAL,TOKARZ,CHRISTOPHER,NULL,Male,Caucasian,05/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +53380,60396,54857,PRETRIAL,TOKARZ,CHRISTOPHER,NULL,Male,Caucasian,05/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +53380,60396,54857,PRETRIAL,TOKARZ,CHRISTOPHER,NULL,Male,Caucasian,05/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +5512,60375,54838,Probation,Caneus,Ephrain,NULL,Male,African-American,03/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-1.34,7,Medium,New,1,0 +5512,60375,54838,Probation,Caneus,Ephrain,NULL,Male,African-American,03/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +5512,60375,54838,Probation,Caneus,Ephrain,NULL,Male,African-American,03/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53374,60389,54850,Probation,Martinez,Michael,NULL,Male,Hispanic,07/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +53374,60389,54850,Probation,Martinez,Michael,NULL,Male,Hispanic,07/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +53374,60389,54850,Probation,Martinez,Michael,NULL,Male,Hispanic,07/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +47035,60382,54845,Probation,Legros,Eveno,NULL,Male,African-American,05/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +47035,60382,54845,Probation,Legros,Eveno,NULL,Male,African-American,05/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +47035,60382,54845,Probation,Legros,Eveno,NULL,Male,African-American,05/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +946,60410,54868,PRETRIAL,Young,Antonio,Vlepo,Male,African-American,07/10/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +946,60410,54868,PRETRIAL,Young,Antonio,Vlepo,Male,African-American,07/10/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +946,60410,54868,PRETRIAL,Young,Antonio,Vlepo,Male,African-American,07/10/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,37,10,High,New,1,0 +53377,60393,54854,PRETRIAL,Cancinos,Yuri,NULL,Male,Hispanic,01/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +53377,60393,54854,PRETRIAL,Cancinos,Yuri,NULL,Male,Hispanic,01/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +53377,60393,54854,PRETRIAL,Cancinos,Yuri,NULL,Male,Hispanic,01/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52574,60400,53906,Probation,Burgos,Laura,NULL,Female,Hispanic,05/21/53,17,All Scales,Intake,English,Other,Probation,Divorced,3/27/13 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +52574,60400,53906,Probation,Burgos,Laura,NULL,Female,Hispanic,05/21/53,17,All Scales,Intake,English,Other,Probation,Divorced,3/27/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +52574,60400,53906,Probation,Burgos,Laura,NULL,Female,Hispanic,05/21/53,17,All Scales,Intake,English,Other,Probation,Divorced,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +37158,60372,54835,PRETRIAL,West,Jermaine,NULL,Male,African-American,01/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.22,4,Low,New,1,0 +37158,60372,54835,PRETRIAL,West,Jermaine,NULL,Male,African-American,01/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,New,1,0 +37158,60372,54835,PRETRIAL,West,Jermaine,NULL,Male,African-American,01/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53384,60401,54861,PRETRIAL,Schuster,Edward,NULL,Male,Caucasian,06/29/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/27/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +53384,60401,54861,PRETRIAL,Schuster,Edward,NULL,Male,Caucasian,06/29/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/27/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +53384,60401,54861,PRETRIAL,Schuster,Edward,NULL,Male,Caucasian,06/29/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45460,60408,54867,Probation,Mayfield,James,Otis,Male,African-American,04/11/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/27/13 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +45460,60408,54867,Probation,Mayfield,James,Otis,Male,African-American,04/11/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/27/13 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +45460,60408,54867,Probation,Mayfield,James,Otis,Male,African-American,04/11/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +10274,60380,54843,PRETRIAL,NEELY,JIMMY,L,Male,African-American,06/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +10274,60380,54843,PRETRIAL,NEELY,JIMMY,L,Male,African-American,06/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +10274,60380,54843,PRETRIAL,NEELY,JIMMY,L,Male,African-American,06/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53382,60398,54859,Probation,Frasier,Bryan,NULL,Male,Hispanic,08/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +53382,60398,54859,Probation,Frasier,Bryan,NULL,Male,Hispanic,08/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +53382,60398,54859,Probation,Frasier,Bryan,NULL,Male,Hispanic,08/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53372,60385,54848,Probation,WEISS,MARTIN,W,Male,Caucasian,12/07/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-2.65,2,Low,New,1,0 +53372,60385,54848,Probation,WEISS,MARTIN,W,Male,Caucasian,12/07/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +53372,60385,54848,Probation,WEISS,MARTIN,W,Male,Caucasian,12/07/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +47388,60406,54865,Probation,guntert,maria,NULL,Female,Hispanic,11/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,7,Risk of Violence,-2.71,2,Low,New,1,0 +47388,60406,54865,Probation,guntert,maria,NULL,Female,Hispanic,11/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,New,1,0 +47388,60406,54865,Probation,guntert,maria,NULL,Female,Hispanic,11/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +53368,60377,54840,PRETRIAL,Dalton,Tyrone,NULL,Male,African-American,07/30/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +53368,60377,54840,PRETRIAL,Dalton,Tyrone,NULL,Male,African-American,07/30/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +53368,60377,54840,PRETRIAL,Dalton,Tyrone,NULL,Male,African-American,07/30/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53392,60416,54874,PRETRIAL,Moody,Terrence,Lawrence,Male,African-American,03/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +53392,60416,54874,PRETRIAL,Moody,Terrence,Lawrence,Male,African-American,03/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +53392,60416,54874,PRETRIAL,Moody,Terrence,Lawrence,Male,African-American,03/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53399,60427,54885,PRETRIAL,Lee,Rashidi,NULL,Male,African-American,10/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +53399,60427,54885,PRETRIAL,Lee,Rashidi,NULL,Male,African-American,10/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +53399,60427,54885,PRETRIAL,Lee,Rashidi,NULL,Male,African-American,10/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53507,60573,55018,Probation,Brown,Curtis,NULL,Male,African-American,11/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +53507,60573,55018,Probation,Brown,Curtis,NULL,Male,African-American,11/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +53507,60573,55018,Probation,Brown,Curtis,NULL,Male,African-American,11/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +27631,60419,54877,PRETRIAL,SIMPSON,JONNIE,NULL,Male,African-American,02/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +27631,60419,54877,PRETRIAL,SIMPSON,JONNIE,NULL,Male,African-American,02/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +27631,60419,54877,PRETRIAL,SIMPSON,JONNIE,NULL,Male,African-American,02/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53397,60424,54882,PRETRIAL,Moreland,Azell,Charles,Male,African-American,07/12/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.29,3,Low,New,1,0 +53397,60424,54882,PRETRIAL,Moreland,Azell,Charles,Male,African-American,07/12/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +53397,60424,54882,PRETRIAL,Moreland,Azell,Charles,Male,African-American,07/12/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53417,60453,54909,Probation,birch,barrett,NULL,Male,Caucasian,04/08/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +53417,60453,54909,Probation,birch,barrett,NULL,Male,Caucasian,04/08/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +53417,60453,54909,Probation,birch,barrett,NULL,Male,Caucasian,04/08/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53404,60432,54890,PRETRIAL,Frazier,Patrick,J,Male,African-American,08/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +53404,60432,54890,PRETRIAL,Frazier,Patrick,J,Male,African-American,08/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +53404,60432,54890,PRETRIAL,Frazier,Patrick,J,Male,African-American,08/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +16589,60414,54872,Probation,MATHIS,ROBERT,WARREN,Male,African-American,09/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +16589,60414,54872,Probation,MATHIS,ROBERT,WARREN,Male,African-American,09/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +16589,60414,54872,Probation,MATHIS,ROBERT,WARREN,Male,African-American,09/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53401,60429,54887,PRETRIAL,PERDUE,DONALD,A,Male,African-American,01/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +53401,60429,54887,PRETRIAL,PERDUE,DONALD,A,Male,African-American,01/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +53401,60429,54887,PRETRIAL,PERDUE,DONALD,A,Male,African-American,01/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +3832,60421,54879,Probation,Wallace,Joe,Lewis,Male,African-American,05/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,7,Risk of Violence,-3.05,1,Low,New,1,0 +3832,60421,54879,Probation,Wallace,Joe,Lewis,Male,African-American,05/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +3832,60421,54879,Probation,Wallace,Joe,Lewis,Male,African-American,05/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53302,60422,54880,PRETRIAL,WILLIAMS,EARL,C,Male,African-American,07/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +53302,60422,54880,PRETRIAL,WILLIAMS,EARL,C,Male,African-American,07/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +53302,60422,54880,PRETRIAL,WILLIAMS,EARL,C,Male,African-American,07/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +2861,60443,54900,PRETRIAL,HIBBERT,KIPLYN,NULL,Male,African-American,07/11/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +2861,60443,54900,PRETRIAL,HIBBERT,KIPLYN,NULL,Male,African-American,07/11/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +2861,60443,54900,PRETRIAL,HIBBERT,KIPLYN,NULL,Male,African-American,07/11/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53412,60450,54906,Probation,Goldstrom,Steven,NULL,Male,Caucasian,12/26/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/13 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +53412,60450,54906,Probation,Goldstrom,Steven,NULL,Male,Caucasian,12/26/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/13 0:00,1,Low,8,Risk of Recidivism,-2.71,1,Low,New,1,0 +53412,60450,54906,Probation,Goldstrom,Steven,NULL,Male,Caucasian,12/26/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53405,60433,54891,PRETRIAL,JARJOUR,WILLIAM,NULL,Male,Caucasian,08/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +53405,60433,54891,PRETRIAL,JARJOUR,WILLIAM,NULL,Male,Caucasian,08/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +53405,60433,54891,PRETRIAL,JARJOUR,WILLIAM,NULL,Male,Caucasian,08/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53389,60412,54870,PRETRIAL,Arango,Miguel,NULL,Male,Hispanic,09/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +53389,60412,54870,PRETRIAL,Arango,Miguel,NULL,Male,Hispanic,09/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +53389,60412,54870,PRETRIAL,Arango,Miguel,NULL,Male,Hispanic,09/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53403,60431,54889,PRETRIAL,ROBINSON,NATHAN,DAVIS,Male,Caucasian,06/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +53403,60431,54889,PRETRIAL,ROBINSON,NATHAN,DAVIS,Male,Caucasian,06/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +53403,60431,54889,PRETRIAL,ROBINSON,NATHAN,DAVIS,Male,Caucasian,06/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54343,61647,55957,Probation,werhle,richard,NULL,Male,Caucasian,06/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +54343,61647,55957,Probation,werhle,richard,NULL,Male,Caucasian,06/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +54343,61647,55957,Probation,werhle,richard,NULL,Male,Caucasian,06/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53414,60447,54904,Probation,burello,todd,NULL,Male,Caucasian,08/11/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +53414,60447,54904,Probation,burello,todd,NULL,Male,Caucasian,08/11/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +53414,60447,54904,Probation,burello,todd,NULL,Male,Caucasian,08/11/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53393,60417,54875,PRETRIAL,PELEHOWSKI,JEREMY,G,Male,Caucasian,03/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +53393,60417,54875,PRETRIAL,PELEHOWSKI,JEREMY,G,Male,Caucasian,03/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +53393,60417,54875,PRETRIAL,PELEHOWSKI,JEREMY,G,Male,Caucasian,03/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53398,60426,54884,PRETRIAL,Emmons,Rashad,NULL,Male,African-American,09/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +53398,60426,54884,PRETRIAL,Emmons,Rashad,NULL,Male,African-American,09/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +53398,60426,54884,PRETRIAL,Emmons,Rashad,NULL,Male,African-American,09/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +43270,60452,54908,PRETRIAL,Esfakis,George,NULL,Male,Hispanic,11/19/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +43270,60452,54908,PRETRIAL,Esfakis,George,NULL,Male,Hispanic,11/19/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +43270,60452,54908,PRETRIAL,Esfakis,George,NULL,Male,Hispanic,11/19/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53395,60420,54878,PRETRIAL,Williams,Brandon,NULL,Male,African-American,04/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,4,High,7,Risk of Violence,-0.76,9,High,New,1,0 +53395,60420,54878,PRETRIAL,Williams,Brandon,NULL,Male,African-American,04/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,4,High,8,Risk of Recidivism,0.16,8,High,New,1,0 +53395,60420,54878,PRETRIAL,Williams,Brandon,NULL,Male,African-American,04/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53396,60423,54881,PRETRIAL,Prehay,Glasford,NULL,Male,African-American,07/27/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/13 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +53396,60423,54881,PRETRIAL,Prehay,Glasford,NULL,Male,African-American,07/27/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/13 0:00,1,Low,8,Risk of Recidivism,-2.69,1,Low,New,1,0 +53396,60423,54881,PRETRIAL,Prehay,Glasford,NULL,Male,African-American,07/27/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +47136,60441,54899,PRETRIAL,Lamanna,Alexander,NULL,Male,Caucasian,12/17/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +47136,60441,54899,PRETRIAL,Lamanna,Alexander,NULL,Male,Caucasian,12/17/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +47136,60441,54899,PRETRIAL,Lamanna,Alexander,NULL,Male,Caucasian,12/17/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53400,60428,54886,PRETRIAL,Hannah,Quanesia,S,Female,African-American,12/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +53400,60428,54886,PRETRIAL,Hannah,Quanesia,S,Female,African-American,12/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,4,High,8,Risk of Recidivism,0.12,8,High,New,1,0 +53400,60428,54886,PRETRIAL,Hannah,Quanesia,S,Female,African-American,12/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53391,60415,54873,PRETRIAL,Stoney,Clinton,NULL,Male,African-American,01/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.11,8,High,New,1,0 +53391,60415,54873,PRETRIAL,Stoney,Clinton,NULL,Male,African-American,01/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +53391,60415,54873,PRETRIAL,Stoney,Clinton,NULL,Male,African-American,01/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +53411,60444,54901,PRETRIAL,Terri,Justin,NULL,Male,Caucasian,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +53411,60444,54901,PRETRIAL,Terri,Justin,NULL,Male,Caucasian,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +53411,60444,54901,PRETRIAL,Terri,Justin,NULL,Male,Caucasian,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53506,60572,55017,Probation,Hill,Dwayne,NULL,Male,African-American,01/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +53506,60572,55017,Probation,Hill,Dwayne,NULL,Male,African-American,01/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +53506,60572,55017,Probation,Hill,Dwayne,NULL,Male,African-American,01/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53406,60434,54892,PRETRIAL,sheffield,stevie,NULL,Male,African-American,05/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +53406,60434,54892,PRETRIAL,sheffield,stevie,NULL,Male,African-American,05/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +53406,60434,54892,PRETRIAL,sheffield,stevie,NULL,Male,African-American,05/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53416,60451,54907,Probation,Badour-Williams,Ariane,NULL,Female,Caucasian,01/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +53416,60451,54907,Probation,Badour-Williams,Ariane,NULL,Female,Caucasian,01/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +53416,60451,54907,Probation,Badour-Williams,Ariane,NULL,Female,Caucasian,01/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53390,60413,54871,PRETRIAL,Ocasio,Gerald,NULL,Male,Hispanic,12/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +53390,60413,54871,PRETRIAL,Ocasio,Gerald,NULL,Male,Hispanic,12/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +53390,60413,54871,PRETRIAL,Ocasio,Gerald,NULL,Male,Hispanic,12/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53402,60430,54888,PRETRIAL,Frontini,Santiago,NULL,Male,Hispanic,12/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +53402,60430,54888,PRETRIAL,Frontini,Santiago,NULL,Male,Hispanic,12/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +53402,60430,54888,PRETRIAL,Frontini,Santiago,NULL,Male,Hispanic,12/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53388,60411,54869,PRETRIAL,Guitar,David,R,Male,Caucasian,03/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/28/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +53388,60411,54869,PRETRIAL,Guitar,David,R,Male,Caucasian,03/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/28/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +53388,60411,54869,PRETRIAL,Guitar,David,R,Male,Caucasian,03/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53394,60418,54876,PRETRIAL,CAMPOS,CLAUDIA,A,Female,Caucasian,12/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +53394,60418,54876,PRETRIAL,CAMPOS,CLAUDIA,A,Female,Caucasian,12/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +53394,60418,54876,PRETRIAL,CAMPOS,CLAUDIA,A,Female,Caucasian,12/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +2598,60425,54883,PRETRIAL,coleman,robert,NULL,Male,African-American,01/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +2598,60425,54883,PRETRIAL,coleman,robert,NULL,Male,African-American,01/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +2598,60425,54883,PRETRIAL,coleman,robert,NULL,Male,African-American,01/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53413,60446,54903,PRETRIAL,Diaz,Angel,NULL,Male,Hispanic,04/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/28/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +53413,60446,54903,PRETRIAL,Diaz,Angel,NULL,Male,Hispanic,04/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/28/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +53413,60446,54903,PRETRIAL,Diaz,Angel,NULL,Male,Hispanic,04/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53415,60448,54905,Probation,McIntosh,Dwight,NULL,Male,African-American,07/19/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/13 0:00,2,Medium,7,Risk of Violence,-3.08,1,Low,New,1,0 +53415,60448,54905,Probation,McIntosh,Dwight,NULL,Male,African-American,07/19/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +53415,60448,54905,Probation,McIntosh,Dwight,NULL,Male,African-American,07/19/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53429,60467,54922,DRRD,Dennis,Michael,Lamort,Male,African-American,03/29/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/29/13 0:00,4,High,7,Risk of Violence,-0.06,10,High,New,1,0 +53429,60467,54922,DRRD,Dennis,Michael,Lamort,Male,African-American,03/29/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/29/13 0:00,4,High,8,Risk of Recidivism,1.1,10,High,New,1,0 +53429,60467,54922,DRRD,Dennis,Michael,Lamort,Male,African-American,03/29/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/29/13 0:00,4,High,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +40811,60469,54923,PRETRIAL,Aldahonda,Alan,NULL,Male,Caucasian,11/20/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +40811,60469,54923,PRETRIAL,Aldahonda,Alan,NULL,Male,Caucasian,11/20/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +40811,60469,54923,PRETRIAL,Aldahonda,Alan,NULL,Male,Caucasian,11/20/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +53427,60464,54920,PRETRIAL,Berrios,Daniel,NULL,Male,Caucasian,09/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,New,1,0 +53427,60464,54920,PRETRIAL,Berrios,Daniel,NULL,Male,Caucasian,09/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +53427,60464,54920,PRETRIAL,Berrios,Daniel,NULL,Male,Caucasian,09/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53423,60460,54916,PRETRIAL,Willis,Norman,NULL,Male,Other,11/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/29/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +53423,60460,54916,PRETRIAL,Willis,Norman,NULL,Male,Other,11/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/29/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +53423,60460,54916,PRETRIAL,Willis,Norman,NULL,Male,Other,11/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/29/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53420,60457,54913,PRETRIAL,Pierre,Dieuseul,NULL,Male,African-American,09/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +53420,60457,54913,PRETRIAL,Pierre,Dieuseul,NULL,Male,African-American,09/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +53420,60457,54913,PRETRIAL,Pierre,Dieuseul,NULL,Male,African-American,09/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +27710,60472,54926,PRETRIAL,BUTLER,BARETTA,NULL,Male,African-American,03/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,New,1,0 +27710,60472,54926,PRETRIAL,BUTLER,BARETTA,NULL,Male,African-American,03/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +27710,60472,54926,PRETRIAL,BUTLER,BARETTA,NULL,Male,African-American,03/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +32809,60465,31863,PRETRIAL,vives,brittani,m,Female,Hispanic,05/19/93,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,3/29/13 0:00,4,High,7,Risk of Violence,-0.41,10,High,New,1,0 +32809,60465,31863,PRETRIAL,vives,brittani,m,Female,Hispanic,05/19/93,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,3/29/13 0:00,4,High,8,Risk of Recidivism,1.48,10,High,New,1,0 +32809,60465,31863,PRETRIAL,vives,brittani,m,Female,Hispanic,05/19/93,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,3/29/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53425,60462,54918,PRETRIAL,Palacios,Miguel,Andres,Male,Caucasian,07/21/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +53425,60462,54918,PRETRIAL,Palacios,Miguel,Andres,Male,Caucasian,07/21/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +53425,60462,54918,PRETRIAL,Palacios,Miguel,Andres,Male,Caucasian,07/21/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53430,60470,54924,Probation,Luis,Ernesto,Torres,Male,Hispanic,09/05/63,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/29/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +53430,60470,54924,Probation,Luis,Ernesto,Torres,Male,Hispanic,09/05/63,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/29/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +53430,60470,54924,Probation,Luis,Ernesto,Torres,Male,Hispanic,09/05/63,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,3/29/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53422,60459,54915,PRETRIAL,Edward,John,D,Male,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +53422,60459,54915,PRETRIAL,Edward,John,D,Male,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +53422,60459,54915,PRETRIAL,Edward,John,D,Male,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +6015,60456,54912,PRETRIAL,ALLEN,ANTWAN,NULL,Male,African-American,12/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +6015,60456,54912,PRETRIAL,ALLEN,ANTWAN,NULL,Male,African-American,12/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.85,10,High,New,1,0 +6015,60456,54912,PRETRIAL,ALLEN,ANTWAN,NULL,Male,African-American,12/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53424,60461,54917,PRETRIAL,Jones,Laxavier,L,Male,African-American,09/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +53424,60461,54917,PRETRIAL,Jones,Laxavier,L,Male,African-American,09/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +53424,60461,54917,PRETRIAL,Jones,Laxavier,L,Male,African-American,09/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53418,60454,54910,PRETRIAL,Martinez,Raymond,NULL,Male,Hispanic,12/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/29/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +53418,60454,54910,PRETRIAL,Martinez,Raymond,NULL,Male,Hispanic,12/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/29/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +53418,60454,54910,PRETRIAL,Martinez,Raymond,NULL,Male,Hispanic,12/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53431,60471,54925,PRETRIAL,Cross,Alan,NULL,Male,Caucasian,02/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/29/13 0:00,1,Low,7,Risk of Violence,-1.81,5,Medium,New,1,0 +53431,60471,54925,PRETRIAL,Cross,Alan,NULL,Male,Caucasian,02/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/29/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +53431,60471,54925,PRETRIAL,Cross,Alan,NULL,Male,Caucasian,02/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/29/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53426,60463,54919,PRETRIAL,Ball,Adam,Joseph,Male,Caucasian,04/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +53426,60463,54919,PRETRIAL,Ball,Adam,Joseph,Male,Caucasian,04/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +53426,60463,54919,PRETRIAL,Ball,Adam,Joseph,Male,Caucasian,04/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53421,60458,54914,PRETRIAL,Guagliardo,Frank,NULL,Male,African-American,04/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +53421,60458,54914,PRETRIAL,Guagliardo,Frank,NULL,Male,African-American,04/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +53421,60458,54914,PRETRIAL,Guagliardo,Frank,NULL,Male,African-American,04/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53428,60466,54921,Probation,Poulos,Steven,NULL,Male,Caucasian,02/01/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.01,1,Low,New,1,0 +53428,60466,54921,Probation,Poulos,Steven,NULL,Male,Caucasian,02/01/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +53428,60466,54921,Probation,Poulos,Steven,NULL,Male,Caucasian,02/01/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,38,10,High,New,1,0 +7175,60484,54938,PRETRIAL,President,Rufus,Morris,Male,African-American,08/04/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +7175,60484,54938,PRETRIAL,President,Rufus,Morris,Male,African-American,08/04/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +7175,60484,54938,PRETRIAL,President,Rufus,Morris,Male,African-American,08/04/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +53432,60474,54928,PRETRIAL,Reid,Jason,NULL,Male,African-American,05/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +53432,60474,54928,PRETRIAL,Reid,Jason,NULL,Male,African-American,05/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +53432,60474,54928,PRETRIAL,Reid,Jason,NULL,Male,African-American,05/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53444,60487,54941,PRETRIAL,Dalessandro,Doriano,NULL,Male,Caucasian,07/26/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +53444,60487,54941,PRETRIAL,Dalessandro,Doriano,NULL,Male,Caucasian,07/26/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +53444,60487,54941,PRETRIAL,Dalessandro,Doriano,NULL,Male,Caucasian,07/26/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53448,60492,54946,PRETRIAL,Murray,Mark,NULL,Male,African-American,02/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +53448,60492,54946,PRETRIAL,Murray,Mark,NULL,Male,African-American,02/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +53448,60492,54946,PRETRIAL,Murray,Mark,NULL,Male,African-American,02/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53437,60479,54933,PRETRIAL,HICKS,ROMULISS,JARQUIVES,Male,African-American,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +53437,60479,54933,PRETRIAL,HICKS,ROMULISS,JARQUIVES,Male,African-American,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +53437,60479,54933,PRETRIAL,HICKS,ROMULISS,JARQUIVES,Male,African-American,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53445,60489,54943,PRETRIAL,Arteaga,Octavio,NULL,Male,Hispanic,12/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +53445,60489,54943,PRETRIAL,Arteaga,Octavio,NULL,Male,Hispanic,12/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +53445,60489,54943,PRETRIAL,Arteaga,Octavio,NULL,Male,Hispanic,12/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53433,60475,54929,PRETRIAL,Hamilton,Terri,NULL,Female,African-American,09/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +53433,60475,54929,PRETRIAL,Hamilton,Terri,NULL,Female,African-American,09/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,8,Risk of Recidivism,-1.53,2,Low,New,1,0 +53433,60475,54929,PRETRIAL,Hamilton,Terri,NULL,Female,African-American,09/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53440,60482,54936,PRETRIAL,Gabriel,John,NULL,Male,African-American,12/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +53440,60482,54936,PRETRIAL,Gabriel,John,NULL,Male,African-American,12/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +53440,60482,54936,PRETRIAL,Gabriel,John,NULL,Male,African-American,12/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +8924,60473,54927,PRETRIAL,DUKE,DONALD,AUSTIN,Male,Caucasian,04/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/30/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +8924,60473,54927,PRETRIAL,DUKE,DONALD,AUSTIN,Male,Caucasian,04/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +8924,60473,54927,PRETRIAL,DUKE,DONALD,AUSTIN,Male,Caucasian,04/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/30/13 0:00,2,Medium,18,Risk of Failure to Appear,37,10,High,New,1,0 +53435,60477,54931,PRETRIAL,Ferris,Jonnie,NULL,Male,African-American,10/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,New,1,0 +53435,60477,54931,PRETRIAL,Ferris,Jonnie,NULL,Male,African-American,10/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +53435,60477,54931,PRETRIAL,Ferris,Jonnie,NULL,Male,African-American,10/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +4035,60494,54948,PRETRIAL,LUCERO,MORIS,NULL,Male,Caucasian,11/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +4035,60494,54948,PRETRIAL,LUCERO,MORIS,NULL,Male,Caucasian,11/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +4035,60494,54948,PRETRIAL,LUCERO,MORIS,NULL,Male,Caucasian,11/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +23508,60488,54942,Probation,simon,mark,NULL,Male,African-American,08/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +23508,60488,54942,Probation,simon,mark,NULL,Male,African-American,08/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +23508,60488,54942,Probation,simon,mark,NULL,Male,African-American,08/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53447,60491,54945,PRETRIAL,Jones,Andre,M,Male,African-American,02/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +53447,60491,54945,PRETRIAL,Jones,Andre,M,Male,African-American,02/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +53447,60491,54945,PRETRIAL,Jones,Andre,M,Male,African-American,02/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +18382,60496,17654,PRETRIAL,ADAN,ALEJANDRO,A,Male,African-American,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,Copy,1,0 +18382,60496,17654,PRETRIAL,ADAN,ALEJANDRO,A,Male,African-American,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,4,High,8,Risk of Recidivism,0.9,10,High,Copy,1,0 +18382,60496,17654,PRETRIAL,ADAN,ALEJANDRO,A,Male,African-American,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +53441,60483,54937,PRETRIAL,Gonzalez-Rodriguez,Georbel,NULL,Male,Caucasian,12/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +53441,60483,54937,PRETRIAL,Gonzalez-Rodriguez,Georbel,NULL,Male,Caucasian,12/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +53441,60483,54937,PRETRIAL,Gonzalez-Rodriguez,Georbel,NULL,Male,Caucasian,12/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53438,60480,54934,PRETRIAL,Accetta,Michael,NULL,Male,Caucasian,03/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +53438,60480,54934,PRETRIAL,Accetta,Michael,NULL,Male,Caucasian,03/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +53438,60480,54934,PRETRIAL,Accetta,Michael,NULL,Male,Caucasian,03/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53436,60478,54932,PRETRIAL,CASTELLI,STEPHEN,J,Male,Caucasian,06/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +53436,60478,54932,PRETRIAL,CASTELLI,STEPHEN,J,Male,Caucasian,06/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +53436,60478,54932,PRETRIAL,CASTELLI,STEPHEN,J,Male,Caucasian,06/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53443,60486,54940,PRETRIAL,ACCETTA,PETER,T,Male,Caucasian,01/27/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/30/13 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +53443,60486,54940,PRETRIAL,ACCETTA,PETER,T,Male,Caucasian,01/27/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/30/13 0:00,1,Low,8,Risk of Recidivism,-3,1,Low,New,1,0 +53443,60486,54940,PRETRIAL,ACCETTA,PETER,T,Male,Caucasian,01/27/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +9139,60493,54947,PRETRIAL,GODDARD,RODERICK,NULL,Male,African-American,05/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +9139,60493,54947,PRETRIAL,GODDARD,RODERICK,NULL,Male,African-American,05/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +9139,60493,54947,PRETRIAL,GODDARD,RODERICK,NULL,Male,African-American,05/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53442,60485,54939,PRETRIAL,Cockroft,Enrico,NULL,Male,African-American,07/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +53442,60485,54939,PRETRIAL,Cockroft,Enrico,NULL,Male,African-American,07/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +53442,60485,54939,PRETRIAL,Cockroft,Enrico,NULL,Male,African-American,07/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53439,60481,54935,PRETRIAL,Lynch,Michael,Thomas,Male,Caucasian,07/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +53439,60481,54935,PRETRIAL,Lynch,Michael,Thomas,Male,Caucasian,07/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +53439,60481,54935,PRETRIAL,Lynch,Michael,Thomas,Male,Caucasian,07/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53434,60476,54930,PRETRIAL,Smith,James,NULL,Male,African-American,04/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +53434,60476,54930,PRETRIAL,Smith,James,NULL,Male,African-American,04/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +53434,60476,54930,PRETRIAL,Smith,James,NULL,Male,African-American,04/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +27923,60495,27024,PRETRIAL,BURWELL,BRANDON,NULL,Male,Caucasian,08/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,Copy,1,0 +27923,60495,27024,PRETRIAL,BURWELL,BRANDON,NULL,Male,Caucasian,08/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,Copy,1,0 +27923,60495,27024,PRETRIAL,BURWELL,BRANDON,NULL,Male,Caucasian,08/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +53446,60490,54944,PRETRIAL,Silva,Caesar,NULL,Male,Caucasian,11/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +53446,60490,54944,PRETRIAL,Silva,Caesar,NULL,Male,Caucasian,11/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +53446,60490,54944,PRETRIAL,Silva,Caesar,NULL,Male,Caucasian,11/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +8374,60504,54956,PRETRIAL,BERRY,MYRON,LATAVIS,Male,African-American,03/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +8374,60504,54956,PRETRIAL,BERRY,MYRON,LATAVIS,Male,African-American,03/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +8374,60504,54956,PRETRIAL,BERRY,MYRON,LATAVIS,Male,African-American,03/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +53460,60511,54963,PRETRIAL,Holmes,Fred,NULL,Male,African-American,07/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +53460,60511,54963,PRETRIAL,Holmes,Fred,NULL,Male,African-American,07/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +53460,60511,54963,PRETRIAL,Holmes,Fred,NULL,Male,African-American,07/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53466,60518,54969,PRETRIAL,Gonzalez,Idalia,NULL,Female,Caucasian,12/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +53466,60518,54969,PRETRIAL,Gonzalez,Idalia,NULL,Female,Caucasian,12/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +53466,60518,54969,PRETRIAL,Gonzalez,Idalia,NULL,Female,Caucasian,12/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +47855,60497,54949,PRETRIAL,Rhoomes,Brian,NULL,Male,African-American,08/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +47855,60497,54949,PRETRIAL,Rhoomes,Brian,NULL,Male,African-American,08/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +47855,60497,54949,PRETRIAL,Rhoomes,Brian,NULL,Male,African-American,08/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53453,60502,54954,PRETRIAL,Edwards,Dahron,NULL,Male,African-American,03/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +53453,60502,54954,PRETRIAL,Edwards,Dahron,NULL,Male,African-American,03/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +53453,60502,54954,PRETRIAL,Edwards,Dahron,NULL,Male,African-American,03/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +53465,60516,54968,PRETRIAL,Gomez,Ceasar,NULL,Male,Hispanic,02/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +53465,60516,54968,PRETRIAL,Gomez,Ceasar,NULL,Male,Hispanic,02/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +53465,60516,54968,PRETRIAL,Gomez,Ceasar,NULL,Male,Hispanic,02/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +32347,60520,54971,PRETRIAL,Mcclary,Walkina,NULL,Female,African-American,02/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +32347,60520,54971,PRETRIAL,Mcclary,Walkina,NULL,Female,African-American,02/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,8,High,New,1,0 +32347,60520,54971,PRETRIAL,Mcclary,Walkina,NULL,Female,African-American,02/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +53455,60506,54958,PRETRIAL,GASKINS,BRADLEY,NULL,Male,Caucasian,02/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.61,10,High,New,1,0 +53455,60506,54958,PRETRIAL,GASKINS,BRADLEY,NULL,Male,Caucasian,02/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +53455,60506,54958,PRETRIAL,GASKINS,BRADLEY,NULL,Male,Caucasian,02/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53456,60507,54959,PRETRIAL,GORNY,YUREK,NULL,Male,Caucasian,07/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +53456,60507,54959,PRETRIAL,GORNY,YUREK,NULL,Male,Caucasian,07/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +53456,60507,54959,PRETRIAL,GORNY,YUREK,NULL,Male,Caucasian,07/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53452,60501,54953,PRETRIAL,PALMER,GAIRY,ANTHONY,Male,African-American,12/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +53452,60501,54953,PRETRIAL,PALMER,GAIRY,ANTHONY,Male,African-American,12/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +53452,60501,54953,PRETRIAL,PALMER,GAIRY,ANTHONY,Male,African-American,12/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53450,60499,54951,PRETRIAL,KETTLE,SHANNA,NULL,Male,African-American,09/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +53450,60499,54951,PRETRIAL,KETTLE,SHANNA,NULL,Male,African-American,09/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +53450,60499,54951,PRETRIAL,KETTLE,SHANNA,NULL,Male,African-American,09/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53463,60514,54966,PRETRIAL,Edwards,Jamol,NULL,Male,African-American,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +53463,60514,54966,PRETRIAL,Edwards,Jamol,NULL,Male,African-American,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +53463,60514,54966,PRETRIAL,Edwards,Jamol,NULL,Male,African-American,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +8925,60517,8459,PRETRIAL,GRANT,JULIUS,TYRRELL,Male,African-American,01/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,Copy,1,0 +8925,60517,8459,PRETRIAL,GRANT,JULIUS,TYRRELL,Male,African-American,01/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,Copy,1,0 +8925,60517,8459,PRETRIAL,GRANT,JULIUS,TYRRELL,Male,African-American,01/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,Copy,1,0 +53458,60509,54961,PRETRIAL,JEAN,NACKSON,NULL,Male,African-American,12/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +53458,60509,54961,PRETRIAL,JEAN,NACKSON,NULL,Male,African-American,12/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +53458,60509,54961,PRETRIAL,JEAN,NACKSON,NULL,Male,African-American,12/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53467,60519,54970,PRETRIAL,HERNANDEZ,HECTOR,JOSE,Male,Caucasian,01/28/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +53467,60519,54970,PRETRIAL,HERNANDEZ,HECTOR,JOSE,Male,Caucasian,01/28/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +53467,60519,54970,PRETRIAL,HERNANDEZ,HECTOR,JOSE,Male,Caucasian,01/28/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53449,60498,54950,PRETRIAL,James,Romario,NULL,Male,Other,01/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +53449,60498,54950,PRETRIAL,James,Romario,NULL,Male,Other,01/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +53449,60498,54950,PRETRIAL,James,Romario,NULL,Male,Other,01/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53464,60515,54967,PRETRIAL,zacarias,jesus,NULL,Male,Hispanic,11/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +53464,60515,54967,PRETRIAL,zacarias,jesus,NULL,Male,Hispanic,11/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +53464,60515,54967,PRETRIAL,zacarias,jesus,NULL,Male,Hispanic,11/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53461,60512,54964,PRETRIAL,MOTTA,DANIEL,ALBERTO,Male,Caucasian,12/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +53461,60512,54964,PRETRIAL,MOTTA,DANIEL,ALBERTO,Male,Caucasian,12/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +53461,60512,54964,PRETRIAL,MOTTA,DANIEL,ALBERTO,Male,Caucasian,12/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53454,60503,54955,PRETRIAL,CABRERA,ISAAC,ANTONIO,Male,Caucasian,12/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +53454,60503,54955,PRETRIAL,CABRERA,ISAAC,ANTONIO,Male,Caucasian,12/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +53454,60503,54955,PRETRIAL,CABRERA,ISAAC,ANTONIO,Male,Caucasian,12/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53459,60510,54962,PRETRIAL,WILLEY,GREGORY,NULL,Male,African-American,11/26/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +53459,60510,54962,PRETRIAL,WILLEY,GREGORY,NULL,Male,African-American,11/26/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +53459,60510,54962,PRETRIAL,WILLEY,GREGORY,NULL,Male,African-American,11/26/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53462,60513,54965,PRETRIAL,PITTS,TERRENCE,RASHAD,Male,African-American,08/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +53462,60513,54965,PRETRIAL,PITTS,TERRENCE,RASHAD,Male,African-American,08/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +53462,60513,54965,PRETRIAL,PITTS,TERRENCE,RASHAD,Male,African-American,08/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +36886,60505,54957,PRETRIAL,Cameron,Lennox,NULL,Male,African-American,01/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +36886,60505,54957,PRETRIAL,Cameron,Lennox,NULL,Male,African-American,01/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +36886,60505,54957,PRETRIAL,Cameron,Lennox,NULL,Male,African-American,01/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53457,60508,54960,PRETRIAL,OCONNELL,DAVID,NULL,Male,Caucasian,01/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +53457,60508,54960,PRETRIAL,OCONNELL,DAVID,NULL,Male,Caucasian,01/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.63,10,High,New,1,0 +53457,60508,54960,PRETRIAL,OCONNELL,DAVID,NULL,Male,Caucasian,01/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53451,60500,54952,PRETRIAL,Boyd,Mark,NULL,Male,Caucasian,10/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,New,1,0 +53451,60500,54952,PRETRIAL,Boyd,Mark,NULL,Male,Caucasian,10/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +53451,60500,54952,PRETRIAL,Boyd,Mark,NULL,Male,Caucasian,10/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53480,60536,54986,Probation,LopesP,Carlos,NULL,Male,Hispanic,03/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +53480,60536,54986,Probation,LopesP,Carlos,NULL,Male,Hispanic,03/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +53480,60536,54986,Probation,LopesP,Carlos,NULL,Male,Hispanic,03/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53490,60550,54998,Probation,Williams,Brian,David,Male,African-American,02/03/75,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/1/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +53490,60550,54998,Probation,Williams,Brian,David,Male,African-American,02/03/75,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/1/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +53490,60550,54998,Probation,Williams,Brian,David,Male,African-American,02/03/75,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53468,60521,54972,PRETRIAL,Pache,Felix,NULL,Male,Hispanic,08/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +53468,60521,54972,PRETRIAL,Pache,Felix,NULL,Male,Hispanic,08/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +53468,60521,54972,PRETRIAL,Pache,Felix,NULL,Male,Hispanic,08/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53497,60557,55005,Probation,Nails,Whitney,NULL,Female,African-American,07/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/13 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +53497,60557,55005,Probation,Nails,Whitney,NULL,Female,African-American,07/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +53497,60557,55005,Probation,Nails,Whitney,NULL,Female,African-American,07/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +53486,60542,54992,Probation,RUCKER,HENRY,ELLIS,Male,African-American,09/05/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +53486,60542,54992,Probation,RUCKER,HENRY,ELLIS,Male,African-American,09/05/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +53486,60542,54992,Probation,RUCKER,HENRY,ELLIS,Male,African-American,09/05/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53472,60529,54979,PRETRIAL,WILLIAMS,REGGIE,L,Male,African-American,10/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +53472,60529,54979,PRETRIAL,WILLIAMS,REGGIE,L,Male,African-American,10/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +53472,60529,54979,PRETRIAL,WILLIAMS,REGGIE,L,Male,African-American,10/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53495,60555,55003,Probation,BEDOYA,LAURA,N,Female,Hispanic,11/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +53495,60555,55003,Probation,BEDOYA,LAURA,N,Female,Hispanic,11/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +53495,60555,55003,Probation,BEDOYA,LAURA,N,Female,Hispanic,11/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53478,60534,54984,PRETRIAL,SANDERS,JOE,NULL,Male,African-American,09/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +53478,60534,54984,PRETRIAL,SANDERS,JOE,NULL,Male,African-American,09/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +53478,60534,54984,PRETRIAL,SANDERS,JOE,NULL,Male,African-American,09/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +19588,60552,55000,PRETRIAL,PASTRANA,CARLOS,ADOLFO,Male,Caucasian,10/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +19588,60552,55000,PRETRIAL,PASTRANA,CARLOS,ADOLFO,Male,Caucasian,10/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +19588,60552,55000,PRETRIAL,PASTRANA,CARLOS,ADOLFO,Male,Caucasian,10/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +48677,60547,49392,PRETRIAL,Kims,Shanekra,NULL,Female,African-American,06/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,Copy,1,0 +48677,60547,49392,PRETRIAL,Kims,Shanekra,NULL,Female,African-American,06/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,Copy,1,0 +48677,60547,49392,PRETRIAL,Kims,Shanekra,NULL,Female,African-American,06/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +53470,60526,54977,PRETRIAL,GILHAULEY,JOHN,NULL,Male,Caucasian,06/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +53470,60526,54977,PRETRIAL,GILHAULEY,JOHN,NULL,Male,Caucasian,06/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +53470,60526,54977,PRETRIAL,GILHAULEY,JOHN,NULL,Male,Caucasian,06/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53476,60533,54983,PRETRIAL,JIMENEZ,JOSE,ANTHONY,Male,Caucasian,06/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +53476,60533,54983,PRETRIAL,JIMENEZ,JOSE,ANTHONY,Male,Caucasian,06/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +53476,60533,54983,PRETRIAL,JIMENEZ,JOSE,ANTHONY,Male,Caucasian,06/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53474,60531,54981,PRETRIAL,Holloway,Vincent,NULL,Male,African-American,10/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +53474,60531,54981,PRETRIAL,Holloway,Vincent,NULL,Male,African-American,10/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +53474,60531,54981,PRETRIAL,Holloway,Vincent,NULL,Male,African-American,10/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +53484,60540,54990,Probation,Williams,Peter,NULL,Male,African-American,10/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +53484,60540,54990,Probation,Williams,Peter,NULL,Male,African-American,10/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +53484,60540,54990,Probation,Williams,Peter,NULL,Male,African-American,10/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53494,60554,55002,PRETRIAL,Corley,Marc,Alan,Male,Caucasian,07/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +53494,60554,55002,PRETRIAL,Corley,Marc,Alan,Male,Caucasian,07/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +53494,60554,55002,PRETRIAL,Corley,Marc,Alan,Male,Caucasian,07/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +4750,60528,4440,PRETRIAL,THOMAS,FREDERICK,NULL,Male,Other,04/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,Copy,1,0 +4750,60528,4440,PRETRIAL,THOMAS,FREDERICK,NULL,Male,Other,04/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.55,4,Low,Copy,1,0 +4750,60528,4440,PRETRIAL,THOMAS,FREDERICK,NULL,Male,Other,04/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +53489,60545,54995,PRETRIAL,sullivan,michael,NULL,Male,Caucasian,05/06/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +53489,60545,54995,PRETRIAL,sullivan,michael,NULL,Male,Caucasian,05/06/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +53489,60545,54995,PRETRIAL,sullivan,michael,NULL,Male,Caucasian,05/06/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50981,60524,54975,PRETRIAL,Strickland,Anthony,Tyrone,Male,African-American,12/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +50981,60524,54975,PRETRIAL,Strickland,Anthony,Tyrone,Male,African-American,12/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +50981,60524,54975,PRETRIAL,Strickland,Anthony,Tyrone,Male,African-American,12/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/13 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +53499,60559,55007,PRETRIAL,Johnson,Demetrius,Alexa,Male,African-American,08/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +53499,60559,55007,PRETRIAL,Johnson,Demetrius,Alexa,Male,African-American,08/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +53499,60559,55007,PRETRIAL,Johnson,Demetrius,Alexa,Male,African-American,08/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53482,60538,54988,Broward County,Ferguson,Cowania,NULL,Female,African-American,03/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +53482,60538,54988,Broward County,Ferguson,Cowania,NULL,Female,African-American,03/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +53482,60538,54988,Broward County,Ferguson,Cowania,NULL,Female,African-American,03/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53492,60551,54999,PRETRIAL,Butler,Ryan,NULL,Male,Caucasian,05/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +53492,60551,54999,PRETRIAL,Butler,Ryan,NULL,Male,Caucasian,05/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +53492,60551,54999,PRETRIAL,Butler,Ryan,NULL,Male,Caucasian,05/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53473,60530,54980,PRETRIAL,LEBRUN,LINDA,NULL,Female,African-American,03/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +53473,60530,54980,PRETRIAL,LEBRUN,LINDA,NULL,Female,African-American,03/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +53473,60530,54980,PRETRIAL,LEBRUN,LINDA,NULL,Female,African-American,03/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +4961,4956,4645,PRETRIAL,GARRETT,GAYVON,LAMAR,Male,African-American,07/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +4961,4956,4645,PRETRIAL,GARRETT,GAYVON,LAMAR,Male,African-American,07/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +4961,4956,4645,PRETRIAL,GARRETT,GAYVON,LAMAR,Male,African-American,07/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +38845,60522,54973,PRETRIAL,Rodriguez,Asael,NULL,Male,Hispanic,11/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +38845,60522,54973,PRETRIAL,Rodriguez,Asael,NULL,Male,Hispanic,11/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +38845,60522,54973,PRETRIAL,Rodriguez,Asael,NULL,Male,Hispanic,11/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53487,60543,54993,Probation,Espinosaazabache,Flora,NULL,Female,Hispanic,10/21/60,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,4/1/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +53487,60543,54993,Probation,Espinosaazabache,Flora,NULL,Female,Hispanic,10/21/60,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,4/1/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +53487,60543,54993,Probation,Espinosaazabache,Flora,NULL,Female,Hispanic,10/21/60,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53469,60523,54974,PRETRIAL,MACDONALD,MARLON,HUGH,Male,African-American,10/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +53469,60523,54974,PRETRIAL,MACDONALD,MARLON,HUGH,Male,African-American,10/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +53469,60523,54974,PRETRIAL,MACDONALD,MARLON,HUGH,Male,African-American,10/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53481,60537,54987,Probation,Rojas,Henry,NULL,Male,Hispanic,03/16/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/1/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +53481,60537,54987,Probation,Rojas,Henry,NULL,Male,Hispanic,03/16/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/1/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +53481,60537,54987,Probation,Rojas,Henry,NULL,Male,Hispanic,03/16/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +53471,60527,54978,PRETRIAL,Jarmon,Timothy,NULL,Male,African-American,07/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +53471,60527,54978,PRETRIAL,Jarmon,Timothy,NULL,Male,African-American,07/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +53471,60527,54978,PRETRIAL,Jarmon,Timothy,NULL,Male,African-American,07/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53485,60541,54991,PRETRIAL,Hawkins,Gina,NULL,Female,Caucasian,07/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/1/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +53485,60541,54991,PRETRIAL,Hawkins,Gina,NULL,Female,Caucasian,07/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/1/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +53485,60541,54991,PRETRIAL,Hawkins,Gina,NULL,Female,Caucasian,07/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53475,60532,54982,PRETRIAL,PENDLEBURY,KRISTOPHER,NULL,Male,Caucasian,02/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/1/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +53475,60532,54982,PRETRIAL,PENDLEBURY,KRISTOPHER,NULL,Male,Caucasian,02/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/1/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +53475,60532,54982,PRETRIAL,PENDLEBURY,KRISTOPHER,NULL,Male,Caucasian,02/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53493,60553,55001,PRETRIAL,Nieves,Glenn,Joseph,Male,Hispanic,05/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +53493,60553,55001,PRETRIAL,Nieves,Glenn,Joseph,Male,Hispanic,05/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +53493,60553,55001,PRETRIAL,Nieves,Glenn,Joseph,Male,Hispanic,05/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53498,60558,55006,PRETRIAL,Kelley,Joseph,NULL,Male,African-American,11/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/13 0:00,2,Medium,7,Risk of Violence,-3.26,1,Low,New,1,0 +53498,60558,55006,PRETRIAL,Kelley,Joseph,NULL,Male,African-American,11/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +53498,60558,55006,PRETRIAL,Kelley,Joseph,NULL,Male,African-American,11/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +30942,60546,54996,PRETRIAL,BOOKER,TOBY,NULL,Male,African-American,10/14/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/1/13 0:00,2,Medium,7,Risk of Violence,-1.26,7,Medium,New,1,0 +30942,60546,54996,PRETRIAL,BOOKER,TOBY,NULL,Male,African-American,10/14/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +30942,60546,54996,PRETRIAL,BOOKER,TOBY,NULL,Male,African-American,10/14/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/1/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +4961,60548,4645,PRETRIAL,GARRETT,GAYVON,LAMAR,Male,African-American,07/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,Copy,1,0 +4961,60548,4645,PRETRIAL,GARRETT,GAYVON,LAMAR,Male,African-American,07/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,Copy,1,0 +4961,60548,4645,PRETRIAL,GARRETT,GAYVON,LAMAR,Male,African-American,07/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +37721,60525,54976,PRETRIAL,Westbrook,Broderick,D,Male,African-American,05/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +37721,60525,54976,PRETRIAL,Westbrook,Broderick,D,Male,African-American,05/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +37721,60525,54976,PRETRIAL,Westbrook,Broderick,D,Male,African-American,05/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53483,60539,54989,PRETRIAL,Spencer,Sessaly,NULL,Female,African-American,08/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.29,3,Low,New,1,0 +53483,60539,54989,PRETRIAL,Spencer,Sessaly,NULL,Female,African-American,08/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,8,High,New,1,0 +53483,60539,54989,PRETRIAL,Spencer,Sessaly,NULL,Female,African-American,08/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +47358,60590,55028,PRETRIAL,ORELLANA,MAURICIO,NULL,Male,Caucasian,12/06/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +47358,60590,55028,PRETRIAL,ORELLANA,MAURICIO,NULL,Male,Caucasian,12/06/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +47358,60590,55028,PRETRIAL,ORELLANA,MAURICIO,NULL,Male,Caucasian,12/06/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +2691,60604,55041,PRETRIAL,BAILEY,RALPH,NULL,Male,African-American,07/14/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +2691,60604,55041,PRETRIAL,BAILEY,RALPH,NULL,Male,African-American,07/14/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +2691,60604,55041,PRETRIAL,BAILEY,RALPH,NULL,Male,African-American,07/14/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +36555,60597,55035,PRETRIAL,Furbush,John,Thomas,Male,Caucasian,03/19/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +36555,60597,55035,PRETRIAL,Furbush,John,Thomas,Male,Caucasian,03/19/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +36555,60597,55035,PRETRIAL,Furbush,John,Thomas,Male,Caucasian,03/19/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +29762,60567,55013,PRETRIAL,taylor,william,NULL,Male,Caucasian,06/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/2/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +29762,60567,55013,PRETRIAL,taylor,william,NULL,Male,Caucasian,06/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +29762,60567,55013,PRETRIAL,taylor,william,NULL,Male,Caucasian,06/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53503,60569,55014,PRETRIAL,Ling,Devin,NULL,Male,African-American,12/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +53503,60569,55014,PRETRIAL,Ling,Devin,NULL,Male,African-American,12/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,4,High,8,Risk of Recidivism,0.16,8,High,New,1,0 +53503,60569,55014,PRETRIAL,Ling,Devin,NULL,Male,African-American,12/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47133,60576,55020,PRETRIAL,Mcmullen,Kory,NULL,Male,Caucasian,12/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +47133,60576,55020,PRETRIAL,Mcmullen,Kory,NULL,Male,Caucasian,12/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +47133,60576,55020,PRETRIAL,Mcmullen,Kory,NULL,Male,Caucasian,12/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53519,60592,55030,Probation,Palma,Lesther,NULL,Male,Hispanic,10/03/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/2/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +53519,60592,55030,Probation,Palma,Lesther,NULL,Male,Hispanic,10/03/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +53519,60592,55030,Probation,Palma,Lesther,NULL,Male,Hispanic,10/03/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +23336,60562,55010,PRETRIAL,Julien,Kinson,NULL,Male,African-American,11/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +23336,60562,55010,PRETRIAL,Julien,Kinson,NULL,Male,African-American,11/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +23336,60562,55010,PRETRIAL,Julien,Kinson,NULL,Male,African-American,11/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53510,60579,55023,PRETRIAL,Kennedy,Attilla,NULL,Female,African-American,03/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/13 0:00,4,High,7,Risk of Violence,-0.65,9,High,New,1,0 +53510,60579,55023,PRETRIAL,Kennedy,Attilla,NULL,Female,African-American,03/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/13 0:00,4,High,8,Risk of Recidivism,0.89,10,High,New,1,0 +53510,60579,55023,PRETRIAL,Kennedy,Attilla,NULL,Female,African-American,03/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/13 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +53541,60595,55033,PRETRIAL,Pulsifer,Christopher,NULL,Male,Caucasian,09/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/2/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +53541,60595,55033,PRETRIAL,Pulsifer,Christopher,NULL,Male,Caucasian,09/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +53541,60595,55033,PRETRIAL,Pulsifer,Christopher,NULL,Male,Caucasian,09/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53406,60588,54892,PRETRIAL,sheffield,stevie,NULL,Male,African-American,05/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/2/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,Copy,1,0 +53406,60588,54892,PRETRIAL,sheffield,stevie,NULL,Male,African-American,05/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,Copy,1,0 +53406,60588,54892,PRETRIAL,sheffield,stevie,NULL,Male,African-American,05/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +53520,60593,55031,Probation,ciavatto,jason,NULL,Male,Caucasian,07/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/2/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +53520,60593,55031,Probation,ciavatto,jason,NULL,Male,Caucasian,07/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +53520,60593,55031,Probation,ciavatto,jason,NULL,Male,Caucasian,07/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53544,60601,55038,Probation,MONICO,ANZELA,NULL,Female,Caucasian,09/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/2/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +53544,60601,55038,Probation,MONICO,ANZELA,NULL,Female,Caucasian,09/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +53544,60601,55038,Probation,MONICO,ANZELA,NULL,Female,Caucasian,09/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +37309,60608,55045,PRETRIAL,Caldswell,Lamount,NULL,Male,African-American,09/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +37309,60608,55045,PRETRIAL,Caldswell,Lamount,NULL,Male,African-American,09/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +37309,60608,55045,PRETRIAL,Caldswell,Lamount,NULL,Male,African-American,09/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53508,60580,55019,PRETRIAL,WEAVER,CAROLYN,NULL,Female,Caucasian,01/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/2/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,Copy,1,0 +53508,60580,55019,PRETRIAL,WEAVER,CAROLYN,NULL,Female,Caucasian,01/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,Copy,1,0 +53508,60580,55019,PRETRIAL,WEAVER,CAROLYN,NULL,Female,Caucasian,01/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +43590,60564,55012,PRETRIAL,Charlemagne,Kenny,NULL,Male,African-American,07/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,2,Medium,7,Risk of Violence,-1.51,6,Medium,New,1,0 +43590,60564,55012,PRETRIAL,Charlemagne,Kenny,NULL,Male,African-American,07/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +43590,60564,55012,PRETRIAL,Charlemagne,Kenny,NULL,Male,African-American,07/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +27328,60598,55036,Probation,ARMSTRONG,WOODROW,NULL,Male,African-Am,10/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +27328,60598,55036,Probation,ARMSTRONG,WOODROW,NULL,Male,African-Am,10/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.18,10,High,New,1,0 +27328,60598,55036,Probation,ARMSTRONG,WOODROW,NULL,Male,African-Am,10/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +47162,60585,55025,PRETRIAL,Williams,Sam,NULL,Male,Caucasian,02/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +47162,60585,55025,PRETRIAL,Williams,Sam,NULL,Male,Caucasian,02/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +47162,60585,55025,PRETRIAL,Williams,Sam,NULL,Male,Caucasian,02/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53547,60606,55043,PRETRIAL,Shore,Jay,NULL,Male,Caucasian,01/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +53547,60606,55043,PRETRIAL,Shore,Jay,NULL,Male,Caucasian,01/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +53547,60606,55043,PRETRIAL,Shore,Jay,NULL,Male,Caucasian,01/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53407,60577,55021,Probation,GREEN,JOHN,NULL,Male,African-American,04/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +53407,60577,55021,Probation,GREEN,JOHN,NULL,Male,African-American,04/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +53407,60577,55021,Probation,GREEN,JOHN,NULL,Male,African-American,04/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53515,60587,55027,PRETRIAL,davis,john,NULL,Male,Caucasian,06/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/2/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +53515,60587,55027,PRETRIAL,davis,john,NULL,Male,Caucasian,06/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/2/13 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +53515,60587,55027,PRETRIAL,davis,john,NULL,Male,Caucasian,06/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53516,60591,55029,Probation,dominguez,alexis,NULL,Female,Hispanic,02/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +53516,60591,55029,Probation,dominguez,alexis,NULL,Female,Hispanic,02/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +53516,60591,55029,Probation,dominguez,alexis,NULL,Female,Hispanic,02/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53546,60605,55042,Probation,Suris,Adam,NULL,Male,Caucasian,12/21/84,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/2/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +53546,60605,55042,Probation,Suris,Adam,NULL,Male,Caucasian,12/21/84,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/2/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +53546,60605,55042,Probation,Suris,Adam,NULL,Male,Caucasian,12/21/84,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +8012,60566,25426,PRETRIAL,KENT,RAYNARD,NULL,Male,African-American,10/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,Copy,1,0 +8012,60566,25426,PRETRIAL,KENT,RAYNARD,NULL,Male,African-American,10/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,Copy,1,0 +8012,60566,25426,PRETRIAL,KENT,RAYNARD,NULL,Male,African-American,10/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +53504,60570,55015,PRETRIAL,MONSIGNORE,ROBERT,NULL,Male,Caucasian,06/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +53504,60570,55015,PRETRIAL,MONSIGNORE,ROBERT,NULL,Male,Caucasian,06/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +53504,60570,55015,PRETRIAL,MONSIGNORE,ROBERT,NULL,Male,Caucasian,06/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +2368,60584,53015,PRETRIAL,SMITH,JEREMY,NULL,Male,African-American,03/23/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,4,High,7,Risk of Violence,-0.8,9,High,Copy,1,0 +2368,60584,53015,PRETRIAL,SMITH,JEREMY,NULL,Male,African-American,03/23/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,4,High,8,Risk of Recidivism,0.64,10,High,Copy,1,0 +2368,60584,53015,PRETRIAL,SMITH,JEREMY,NULL,Male,African-American,03/23/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +53542,60596,55034,Probation,Hernandez,Henry,NULL,Male,Hispanic,07/18/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +53542,60596,55034,Probation,Hernandez,Henry,NULL,Male,Hispanic,07/18/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +53542,60596,55034,Probation,Hernandez,Henry,NULL,Male,Hispanic,07/18/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53501,60561,55009,PRETRIAL,MOSS,STEVEN,WILLIAM,Male,African-American,07/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,4,High,7,Risk of Violence,0.13,10,High,New,1,0 +53501,60561,55009,PRETRIAL,MOSS,STEVEN,WILLIAM,Male,African-American,07/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +53501,60561,55009,PRETRIAL,MOSS,STEVEN,WILLIAM,Male,African-American,07/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +8206,60568,7762,PRETRIAL,MCCLOUD,RENARD,NULL,Male,African-American,01/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,Copy,1,0 +8206,60568,7762,PRETRIAL,MCCLOUD,RENARD,NULL,Male,African-American,01/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.63,10,High,Copy,1,0 +8206,60568,7762,PRETRIAL,MCCLOUD,RENARD,NULL,Male,African-American,01/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +52886,60575,54281,PRETRIAL,Jussim,Joao,NULL,Male,Hispanic,10/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,Copy,1,0 +52886,60575,54281,PRETRIAL,Jussim,Joao,NULL,Male,Hispanic,10/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,Copy,1,0 +52886,60575,54281,PRETRIAL,Jussim,Joao,NULL,Male,Hispanic,10/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +30320,60603,55040,PRETRIAL,RABEN,LAWRENCE,KAI,Male,Caucasian,02/09/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +30320,60603,55040,PRETRIAL,RABEN,LAWRENCE,KAI,Male,Caucasian,02/09/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +30320,60603,55040,PRETRIAL,RABEN,LAWRENCE,KAI,Male,Caucasian,02/09/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53500,60560,55008,PRETRIAL,Simmins,Jerome,NULL,Male,African-American,11/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +53500,60560,55008,PRETRIAL,Simmins,Jerome,NULL,Male,African-American,11/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +53500,60560,55008,PRETRIAL,Simmins,Jerome,NULL,Male,African-American,11/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53511,60581,55024,Probation,THOMAS,OCTVIOUA,NULL,Female,African-American,05/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +53511,60581,55024,Probation,THOMAS,OCTVIOUA,NULL,Female,African-American,05/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +53511,60581,55024,Probation,THOMAS,OCTVIOUA,NULL,Female,African-American,05/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53545,60602,55039,Probation,mikolashek,matthew,NULL,Male,African-American,10/31/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +53545,60602,55039,Probation,mikolashek,matthew,NULL,Male,African-American,10/31/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +53545,60602,55039,Probation,mikolashek,matthew,NULL,Male,African-American,10/31/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53502,60563,55011,PRETRIAL,JUSTIN,GYMMY,NULL,Male,African-American,01/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +53502,60563,55011,PRETRIAL,JUSTIN,GYMMY,NULL,Male,African-American,01/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +53502,60563,55011,PRETRIAL,JUSTIN,GYMMY,NULL,Male,African-American,01/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +6980,60565,43939,PRETRIAL,FOSTER,DONALD,RAY,Male,African-American,12/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,Copy,1,0 +6980,60565,43939,PRETRIAL,FOSTER,DONALD,RAY,Male,African-American,12/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,Copy,1,0 +6980,60565,43939,PRETRIAL,FOSTER,DONALD,RAY,Male,African-American,12/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,Copy,1,0 +16819,60599,16126,PRETRIAL,Jones,Debra,A,Female,African-American,09/16/63,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,4/2/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,Copy,1,0 +16819,60599,16126,PRETRIAL,Jones,Debra,A,Female,African-American,09/16/63,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,4/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.66,5,Medium,Copy,1,0 +16819,60599,16126,PRETRIAL,Jones,Debra,A,Female,African-American,09/16/63,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,4/2/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +16819,17394,16126,PRETRIAL,Jones,Debra,A,Female,African-American,09/16/63,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +16819,17394,16126,PRETRIAL,Jones,Debra,A,Female,African-American,09/16/63,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +16819,17394,16126,PRETRIAL,Jones,Debra,A,Female,African-American,09/16/63,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53509,60578,55022,Probation,GERACI,DENISE,L,Female,Caucasian,08/29/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/2/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +53509,60578,55022,Probation,GERACI,DENISE,L,Female,Caucasian,08/29/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/2/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +53509,60578,55022,Probation,GERACI,DENISE,L,Female,Caucasian,08/29/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +53505,60571,55016,PRETRIAL,Hanson,Slade,K,Male,Caucasian,02/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +53505,60571,55016,PRETRIAL,Hanson,Slade,K,Male,Caucasian,02/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +53505,60571,55016,PRETRIAL,Hanson,Slade,K,Male,Caucasian,02/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53548,60607,55044,Probation,Spiro,Elyse,Dawn,Female,Caucasian,11/10/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/2/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +53548,60607,55044,Probation,Spiro,Elyse,Dawn,Female,Caucasian,11/10/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/2/13 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +53548,60607,55044,Probation,Spiro,Elyse,Dawn,Female,Caucasian,11/10/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53514,60586,55026,Probation,Wallin,Lindsay,NULL,Female,Caucasian,02/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +53514,60586,55026,Probation,Wallin,Lindsay,NULL,Female,Caucasian,02/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,6,Medium,New,1,0 +53514,60586,55026,Probation,Wallin,Lindsay,NULL,Female,Caucasian,02/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53616,60636,55069,DRRD,Syvestre,Kristen,NULL,Female,African-American,11/08/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +53616,60636,55069,DRRD,Syvestre,Kristen,NULL,Female,African-American,11/08/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +53616,60636,55069,DRRD,Syvestre,Kristen,NULL,Female,African-American,11/08/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53628,60657,55084,PRETRIAL,previlus,pedro,NULL,Male,African-American,04/02/90,17,All Scales,Intake,English,Post Sentence,Residential Program,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +53628,60657,55084,PRETRIAL,previlus,pedro,NULL,Male,African-American,04/02/90,17,All Scales,Intake,English,Post Sentence,Residential Program,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.41,4,Low,New,1,0 +53628,60657,55084,PRETRIAL,previlus,pedro,NULL,Male,African-American,04/02/90,17,All Scales,Intake,English,Post Sentence,Residential Program,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,19,2,Low,New,1,0 +53622,60644,55075,Probation,Barbosa,Lucas,NULL,Male,Hispanic,07/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +53622,60644,55075,Probation,Barbosa,Lucas,NULL,Male,Hispanic,07/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +53622,60644,55075,Probation,Barbosa,Lucas,NULL,Male,Hispanic,07/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53566,60620,55057,PRETRIAL,DINAPOLI,STEVEN,NULL,Male,Caucasian,04/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/3/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +53566,60620,55057,PRETRIAL,DINAPOLI,STEVEN,NULL,Male,Caucasian,04/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/3/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +53566,60620,55057,PRETRIAL,DINAPOLI,STEVEN,NULL,Male,Caucasian,04/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +12542,44962,24806,PRETRIAL,Davey,Dennis,Anthony,Male,African-American,08/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/3/13 0:00,4,High,7,Risk of Violence,-0.13,10,High,Copy,1,0 +12542,44962,24806,PRETRIAL,Davey,Dennis,Anthony,Male,African-American,08/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/3/13 0:00,4,High,8,Risk of Recidivism,1.07,10,High,Copy,1,0 +12542,44962,24806,PRETRIAL,Davey,Dennis,Anthony,Male,African-American,08/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/3/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +53568,60623,55059,PRETRIAL,Moore,Leterra,NULL,Female,African-American,02/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +53568,60623,55059,PRETRIAL,Moore,Leterra,NULL,Female,African-American,02/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +53568,60623,55059,PRETRIAL,Moore,Leterra,NULL,Female,African-American,02/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53620,60641,55073,DRRD,Anderson,Brianna,NULL,Female,African-American,08/10/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +53620,60641,55073,DRRD,Anderson,Brianna,NULL,Female,African-American,08/10/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,6,Medium,New,1,0 +53620,60641,55073,DRRD,Anderson,Brianna,NULL,Female,African-American,08/10/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53555,60615,55052,PRETRIAL,Hill,Charniece,NULL,Female,African-American,01/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +53555,60615,55052,PRETRIAL,Hill,Charniece,NULL,Female,African-American,01/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +53555,60615,55052,PRETRIAL,Hill,Charniece,NULL,Female,African-American,01/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53625,60649,55079,PRETRIAL,Elvie,Winston,NULL,Male,African-American,01/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/3/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +53625,60649,55079,PRETRIAL,Elvie,Winston,NULL,Male,African-American,01/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +53625,60649,55079,PRETRIAL,Elvie,Winston,NULL,Male,African-American,01/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53348,60628,54814,PRETRIAL,Gayle,Lorenzo,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.64,9,High,Copy,1,0 +53348,60628,54814,PRETRIAL,Gayle,Lorenzo,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,7,Medium,Copy,1,0 +53348,60628,54814,PRETRIAL,Gayle,Lorenzo,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +53550,60610,55047,PRETRIAL,Williams,Erwin,NULL,Male,African-American,03/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.19,4,Low,New,1,0 +53550,60610,55047,PRETRIAL,Williams,Erwin,NULL,Male,African-American,03/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +53550,60610,55047,PRETRIAL,Williams,Erwin,NULL,Male,African-American,03/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53613,60633,55068,Probation,Guzman,Andres,NULL,Male,Hispanic,11/30/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +53613,60633,55068,Probation,Guzman,Andres,NULL,Male,Hispanic,11/30/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +53613,60633,55068,Probation,Guzman,Andres,NULL,Male,Hispanic,11/30/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53552,60612,55049,PRETRIAL,Brown,Henry,Lamar,Male,African-American,10/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +53552,60612,55049,PRETRIAL,Brown,Henry,Lamar,Male,African-American,10/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,4,High,8,Risk of Recidivism,0.14,8,High,New,1,0 +53552,60612,55049,PRETRIAL,Brown,Henry,Lamar,Male,African-American,10/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53612,60631,55066,Probation,WILLIAMS,SHAVELLA,NULL,Female,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +53612,60631,55066,Probation,WILLIAMS,SHAVELLA,NULL,Female,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +53612,60631,55066,Probation,WILLIAMS,SHAVELLA,NULL,Female,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53618,60640,55072,Probation,Vega,Samuel,NULL,Male,Hispanic,06/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +53618,60640,55072,Probation,Vega,Samuel,NULL,Male,Hispanic,06/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +53618,60640,55072,Probation,Vega,Samuel,NULL,Male,Hispanic,06/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +43993,60654,44038,Probation,Escardon,Pedro,NULL,Male,Hispanic,11/27/56,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +43993,60654,44038,Probation,Escardon,Pedro,NULL,Male,Hispanic,11/27/56,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-1.27,1,Low,New,1,0 +43993,60654,44038,Probation,Escardon,Pedro,NULL,Male,Hispanic,11/27/56,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +44662,60647,55077,PRETRIAL,Maring,Alicia,NULL,Male,Caucasian,12/31/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +44662,60647,55077,PRETRIAL,Maring,Alicia,NULL,Male,Caucasian,12/31/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +44662,60647,55077,PRETRIAL,Maring,Alicia,NULL,Male,Caucasian,12/31/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53557,60617,55054,PRETRIAL,Billie,Daniel,NULL,Male,Native American,03/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,2,Medium,7,Risk of Violence,-2.86,2,Low,New,1,0 +53557,60617,55054,PRETRIAL,Billie,Daniel,NULL,Male,Native American,03/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +53557,60617,55054,PRETRIAL,Billie,Daniel,NULL,Male,Native American,03/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53571,60626,55062,PRETRIAL,Baum,Olga,NULL,Female,Caucasian,06/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/3/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +53571,60626,55062,PRETRIAL,Baum,Olga,NULL,Female,Caucasian,06/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/3/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +53571,60626,55062,PRETRIAL,Baum,Olga,NULL,Female,Caucasian,06/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +30618,60652,29591,PRETRIAL,Johnson,Eddie,NULL,Male,African-American,10/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,Copy,1,0 +30618,60652,29591,PRETRIAL,Johnson,Eddie,NULL,Male,African-American,10/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,Copy,1,0 +30618,60652,29591,PRETRIAL,Johnson,Eddie,NULL,Male,African-American,10/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +28405,60656,46395,PRETRIAL,KARPIN,MICHELLE,NULL,Male,Hispanic,05/14/78,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +28405,60656,46395,PRETRIAL,KARPIN,MICHELLE,NULL,Male,Hispanic,05/14/78,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +28405,60656,46395,PRETRIAL,KARPIN,MICHELLE,NULL,Male,Hispanic,05/14/78,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53572,60627,55063,PRETRIAL,Savinon,Napoleon,NULL,Male,Hispanic,09/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +53572,60627,55063,PRETRIAL,Savinon,Napoleon,NULL,Male,Hispanic,09/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +53572,60627,55063,PRETRIAL,Savinon,Napoleon,NULL,Male,Hispanic,09/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53623,60645,55076,PRETRIAL,Duguay,Boyd,NULL,Male,Caucasian,10/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +53623,60645,55076,PRETRIAL,Duguay,Boyd,NULL,Male,Caucasian,10/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +53623,60645,55076,PRETRIAL,Duguay,Boyd,NULL,Male,Caucasian,10/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53569,60624,55060,PRETRIAL,Scarborough,Nathaniel,NULL,Male,African-American,09/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +53569,60624,55060,PRETRIAL,Scarborough,Nathaniel,NULL,Male,African-American,09/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +53569,60624,55060,PRETRIAL,Scarborough,Nathaniel,NULL,Male,African-American,09/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53562,60619,55056,PRETRIAL,GARTH,CHRISTOPHER,NULL,Male,African-American,01/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +53562,60619,55056,PRETRIAL,GARTH,CHRISTOPHER,NULL,Male,African-American,01/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +53562,60619,55056,PRETRIAL,GARTH,CHRISTOPHER,NULL,Male,African-American,01/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53627,60653,55082,PRETRIAL,McDonald,Viven,NULL,Male,African-American,10/03/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +53627,60653,55082,PRETRIAL,McDonald,Viven,NULL,Male,African-American,10/03/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.8,10,High,New,1,0 +53627,60653,55082,PRETRIAL,McDonald,Viven,NULL,Male,African-American,10/03/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +15360,60632,55067,PRETRIAL,LENCIONI,RICHARD,J,Male,Caucasian,10/12/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +15360,60632,55067,PRETRIAL,LENCIONI,RICHARD,J,Male,Caucasian,10/12/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +15360,60632,55067,PRETRIAL,LENCIONI,RICHARD,J,Male,Caucasian,10/12/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53554,60614,55051,PRETRIAL,WILLIAMS,SHAWN,NULL,Male,African-American,09/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/3/13 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +53554,60614,55051,PRETRIAL,WILLIAMS,SHAWN,NULL,Male,African-American,09/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +53554,60614,55051,PRETRIAL,WILLIAMS,SHAWN,NULL,Male,African-American,09/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/3/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53556,60616,55053,PRETRIAL,MORENO,RICARDO,NULL,Male,Caucasian,10/20/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/3/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +53556,60616,55053,PRETRIAL,MORENO,RICARDO,NULL,Male,Caucasian,10/20/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/3/13 0:00,1,Low,8,Risk of Recidivism,-2.64,1,Low,New,1,0 +53556,60616,55053,PRETRIAL,MORENO,RICARDO,NULL,Male,Caucasian,10/20/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +43142,60635,43043,PRETRIAL,MARQUEZ,RAFAEL,NULL,Male,Hispanic,07/15/74,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Divorced,4/3/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,Copy,1,0 +43142,60635,43043,PRETRIAL,MARQUEZ,RAFAEL,NULL,Male,Hispanic,07/15/74,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Divorced,4/3/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,Copy,1,0 +43142,60635,43043,PRETRIAL,MARQUEZ,RAFAEL,NULL,Male,Hispanic,07/15/74,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Divorced,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +15933,60637,55070,Probation,Goldenberg,Christopher,NULL,Male,Caucasian,03/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +15933,60637,55070,Probation,Goldenberg,Christopher,NULL,Male,Caucasian,03/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +15933,60637,55070,Probation,Goldenberg,Christopher,NULL,Male,Caucasian,03/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53621,60643,55074,PRETRIAL,Greenwood,Ryan,Eleazar,Male,African-American,01/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/3/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,Copy,1,0 +53621,60643,55074,PRETRIAL,Greenwood,Ryan,Eleazar,Male,African-American,01/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,Copy,1,0 +53621,60643,55074,PRETRIAL,Greenwood,Ryan,Eleazar,Male,African-American,01/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +53626,60650,55080,Probation,Kasson,Renee,NULL,Female,Caucasian,02/06/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +53626,60650,55080,Probation,Kasson,Renee,NULL,Female,Caucasian,02/06/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,New,1,0 +53626,60650,55080,Probation,Kasson,Renee,NULL,Female,Caucasian,02/06/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53567,60621,55058,PRETRIAL,FRENCH,ERVIN,LESTER,Male,African-American,12/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/3/13 0:00,2,Medium,7,Risk of Violence,-1.43,7,Medium,New,1,0 +53567,60621,55058,PRETRIAL,FRENCH,ERVIN,LESTER,Male,African-American,12/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +53567,60621,55058,PRETRIAL,FRENCH,ERVIN,LESTER,Male,African-American,12/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/3/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +36713,60622,42575,Probation,barbary,frederick,NULL,Male,African-American,10/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,4,High,7,Risk of Violence,-1.24,8,High,Copy,1,0 +36713,60622,42575,Probation,barbary,frederick,NULL,Male,African-American,10/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,4,High,8,Risk of Recidivism,0.55,9,High,Copy,1,0 +36713,60622,42575,Probation,barbary,frederick,NULL,Male,African-American,10/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +53549,60609,55046,PRETRIAL,Cooper,Kelley,Major,Male,African-American,08/29/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +53549,60609,55046,PRETRIAL,Cooper,Kelley,Major,Male,African-American,08/29/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +53549,60609,55046,PRETRIAL,Cooper,Kelley,Major,Male,African-American,08/29/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +19692,60634,54272,Probation,Davis,Lakia,Juianay,Female,African-American,08/23/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +19692,60634,54272,Probation,Davis,Lakia,Juianay,Female,African-American,08/23/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +19692,60634,54272,Probation,Davis,Lakia,Juianay,Female,African-American,08/23/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53553,60613,55050,PRETRIAL,Holmes,Willie,NULL,Male,African-American,10/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/3/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +53553,60613,55050,PRETRIAL,Holmes,Willie,NULL,Male,African-American,10/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +53553,60613,55050,PRETRIAL,Holmes,Willie,NULL,Male,African-American,10/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +39175,60630,55065,PRETRIAL,PALMORE,DWAYNE,ANTONIO,Male,African-American,10/14/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/3/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +39175,60630,55065,PRETRIAL,PALMORE,DWAYNE,ANTONIO,Male,African-American,10/14/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,4,Low,New,1,0 +39175,60630,55065,PRETRIAL,PALMORE,DWAYNE,ANTONIO,Male,African-American,10/14/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/3/13 0:00,2,Medium,18,Risk of Failure to Appear,18,2,Low,New,1,0 +24316,60651,55081,PRETRIAL,Dimeco,David,Paul,Male,Caucasian,12/07/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +24316,60651,55081,PRETRIAL,Dimeco,David,Paul,Male,Caucasian,12/07/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +24316,60651,55081,PRETRIAL,Dimeco,David,Paul,Male,Caucasian,12/07/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +49608,60646,50488,Probation,YOLMAN,HAYLEY,RAY,Female,Caucasian,10/30/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/3/13 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +49608,60646,50488,Probation,YOLMAN,HAYLEY,RAY,Female,Caucasian,10/30/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,7,Medium,New,1,0 +49608,60646,50488,Probation,YOLMAN,HAYLEY,RAY,Female,Caucasian,10/30/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/3/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +53624,60648,55078,PRETRIAL,SAINTJEAN,GEORGE,NULL,Male,African-American,09/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-1,-1,N/A,New,1,0 +53624,60648,55078,PRETRIAL,SAINTJEAN,GEORGE,NULL,Male,African-American,09/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +53624,60648,55078,PRETRIAL,SAINTJEAN,GEORGE,NULL,Male,African-American,09/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +12542,60639,24806,PRETRIAL,Davey,Dennis,Anthony,Male,African-American,08/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/3/13 0:00,4,High,7,Risk of Violence,-0.45,10,High,Copy,1,0 +12542,60639,24806,PRETRIAL,Davey,Dennis,Anthony,Male,African-American,08/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/3/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,Copy,1,0 +12542,60639,24806,PRETRIAL,Davey,Dennis,Anthony,Male,African-American,08/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/3/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +53551,60611,55048,PRETRIAL,Small,Andre,NULL,Male,African-American,10/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/3/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +53551,60611,55048,PRETRIAL,Small,Andre,NULL,Male,African-American,10/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/3/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +53551,60611,55048,PRETRIAL,Small,Andre,NULL,Male,African-American,10/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53565,60618,55055,PRETRIAL,Ballard,John,NULL,Male,Caucasian,11/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +53565,60618,55055,PRETRIAL,Ballard,John,NULL,Male,Caucasian,11/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +53565,60618,55055,PRETRIAL,Ballard,John,NULL,Male,Caucasian,11/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53570,60625,55061,PRETRIAL,ROBERTS,JAQUELINE,ARLENE,Male,Caucasian,08/06/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +53570,60625,55061,PRETRIAL,ROBERTS,JAQUELINE,ARLENE,Male,Caucasian,08/06/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +53570,60625,55061,PRETRIAL,ROBERTS,JAQUELINE,ARLENE,Male,Caucasian,08/06/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53653,60690,55114,Probation,YOUNG,LAQUINA,R,Female,African-American,02/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +53653,60690,55114,Probation,YOUNG,LAQUINA,R,Female,African-American,02/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +53653,60690,55114,Probation,YOUNG,LAQUINA,R,Female,African-American,02/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53657,60697,55120,Probation,Becker,Keith,NULL,Male,Caucasian,11/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +53657,60697,55120,Probation,Becker,Keith,NULL,Male,Caucasian,11/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +53657,60697,55120,Probation,Becker,Keith,NULL,Male,Caucasian,11/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53636,60667,55093,PRETRIAL,DEBBIK,SAMIH,NULL,Male,Arabic,06/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +53636,60667,55093,PRETRIAL,DEBBIK,SAMIH,NULL,Male,Arabic,06/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +53636,60667,55093,PRETRIAL,DEBBIK,SAMIH,NULL,Male,Arabic,06/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53638,60669,55095,PRETRIAL,Brekke,Jessica,NULL,Male,Caucasian,04/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +53638,60669,55095,PRETRIAL,Brekke,Jessica,NULL,Male,Caucasian,04/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +53638,60669,55095,PRETRIAL,Brekke,Jessica,NULL,Male,Caucasian,04/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53643,60676,55101,Probation,HERNANDEZ,CHRISTIAN,A,Male,Hispanic,08/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +53643,60676,55101,Probation,HERNANDEZ,CHRISTIAN,A,Male,Hispanic,08/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +53643,60676,55101,Probation,HERNANDEZ,CHRISTIAN,A,Male,Hispanic,08/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53631,60660,55087,PRETRIAL,Laute,Alexander,NULL,Male,Caucasian,06/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +53631,60660,55087,PRETRIAL,Laute,Alexander,NULL,Male,Caucasian,06/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +53631,60660,55087,PRETRIAL,Laute,Alexander,NULL,Male,Caucasian,06/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53648,60685,55109,PRETRIAL,jackson,nicole,NULL,Female,African-American,11/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +53648,60685,55109,PRETRIAL,jackson,nicole,NULL,Female,African-American,11/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +53648,60685,55109,PRETRIAL,jackson,nicole,NULL,Female,African-American,11/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53634,60664,55091,PRETRIAL,Jean,Ronal,NULL,Male,African-American,05/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/4/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +53634,60664,55091,PRETRIAL,Jean,Ronal,NULL,Male,African-American,05/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/4/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +53634,60664,55091,PRETRIAL,Jean,Ronal,NULL,Male,African-American,05/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53645,60681,55105,PRETRIAL,Stokes,Vicki,NULL,Female,Caucasian,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/13 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +53645,60681,55105,PRETRIAL,Stokes,Vicki,NULL,Female,Caucasian,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +53645,60681,55105,PRETRIAL,Stokes,Vicki,NULL,Female,Caucasian,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +43362,60702,43302,PRETRIAL,Mcnair,Joshua,NULL,Male,African-American,07/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,4,High,7,Risk of Violence,-0.73,9,High,Copy,1,0 +43362,60702,43302,PRETRIAL,Mcnair,Joshua,NULL,Male,African-American,07/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,4,High,8,Risk of Recidivism,1.11,10,High,Copy,1,0 +43362,60702,43302,PRETRIAL,Mcnair,Joshua,NULL,Male,African-American,07/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +53660,60700,55123,PRETRIAL,Grier,Arealious,NULL,Male,African-American,03/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +53660,60700,55123,PRETRIAL,Grier,Arealious,NULL,Male,African-American,03/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +53660,60700,55123,PRETRIAL,Grier,Arealious,NULL,Male,African-American,03/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53633,60663,55090,PRETRIAL,Watson,Maurice,Oliver,Male,Other,07/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +53633,60663,55090,PRETRIAL,Watson,Maurice,Oliver,Male,Other,07/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +53633,60663,55090,PRETRIAL,Watson,Maurice,Oliver,Male,Other,07/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +7790,60666,39650,PRETRIAL,CAREY,STEVEN,NULL,Male,African-American,01/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,Copy,1,0 +7790,60666,39650,PRETRIAL,CAREY,STEVEN,NULL,Male,African-American,01/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,Copy,1,0 +7790,60666,39650,PRETRIAL,CAREY,STEVEN,NULL,Male,African-American,01/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +53629,60658,55085,PRETRIAL,Schossler,Renato,NULL,Male,Caucasian,04/24/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/4/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +53629,60658,55085,PRETRIAL,Schossler,Renato,NULL,Male,Caucasian,04/24/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/4/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +53629,60658,55085,PRETRIAL,Schossler,Renato,NULL,Male,Caucasian,04/24/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53650,60687,55111,Probation,BOHACEK,WALTER,JOSEPH,Male,Caucasian,05/28/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/4/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +53650,60687,55111,Probation,BOHACEK,WALTER,JOSEPH,Male,Caucasian,05/28/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/4/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +53650,60687,55111,Probation,BOHACEK,WALTER,JOSEPH,Male,Caucasian,05/28/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +19639,60692,55115,PRETRIAL,Coulsting,Tristan,NULL,Male,Caucasian,01/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +19639,60692,55115,PRETRIAL,Coulsting,Tristan,NULL,Male,Caucasian,01/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +19639,60692,55115,PRETRIAL,Coulsting,Tristan,NULL,Male,Caucasian,01/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53641,60674,55099,Probation,Guerra,Michael,NULL,Male,Hispanic,07/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +53641,60674,55099,Probation,Guerra,Michael,NULL,Male,Hispanic,07/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +53641,60674,55099,Probation,Guerra,Michael,NULL,Male,Hispanic,07/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +20143,60684,55108,PRETRIAL,Torres,Thadious,NULL,Male,African-American,01/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.11,8,High,New,1,0 +20143,60684,55108,PRETRIAL,Torres,Thadious,NULL,Male,African-American,01/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +20143,60684,55108,PRETRIAL,Torres,Thadious,NULL,Male,African-American,01/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +53656,60695,55118,Probation,STEWARD,CORNELL,NULL,Male,African-American,02/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +53656,60695,55118,Probation,STEWARD,CORNELL,NULL,Male,African-American,02/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +53656,60695,55118,Probation,STEWARD,CORNELL,NULL,Male,African-American,02/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +30332,60659,55086,PRETRIAL,Hines,Delwance,NULL,Male,African-American,09/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,4,High,7,Risk of Violence,-0.2,10,High,New,1,0 +30332,60659,55086,PRETRIAL,Hines,Delwance,NULL,Male,African-American,09/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,4,High,8,Risk of Recidivism,1.53,10,High,New,1,0 +30332,60659,55086,PRETRIAL,Hines,Delwance,NULL,Male,African-American,09/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53488,60677,54994,PRETRIAL,COLLINS,ASHLEY,NICOLE,Female,African-American,10/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,Copy,1,0 +53488,60677,54994,PRETRIAL,COLLINS,ASHLEY,NICOLE,Female,African-American,10/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,Copy,1,0 +53488,60677,54994,PRETRIAL,COLLINS,ASHLEY,NICOLE,Female,African-American,10/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +53655,60694,55117,Probation,Saunders,Marquis,NULL,Male,African-American,03/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +53655,60694,55117,Probation,Saunders,Marquis,NULL,Male,African-American,03/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +53655,60694,55117,Probation,Saunders,Marquis,NULL,Male,African-American,03/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53658,60698,55121,Probation,ARY,NARAYANA,NULL,Male,Caucasian,02/11/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +53658,60698,55121,Probation,ARY,NARAYANA,NULL,Male,Caucasian,02/11/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.98,10,High,New,1,0 +53658,60698,55121,Probation,ARY,NARAYANA,NULL,Male,Caucasian,02/11/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53652,60689,55113,Probation,schindler,joseph,NULL,Male,Caucasian,12/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +53652,60689,55113,Probation,schindler,joseph,NULL,Male,Caucasian,12/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +53652,60689,55113,Probation,schindler,joseph,NULL,Male,Caucasian,12/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53630,60661,55088,PRETRIAL,Kenneth,Littlejohn,NULL,Male,African-American,07/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +53630,60661,55088,PRETRIAL,Kenneth,Littlejohn,NULL,Male,African-American,07/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +53630,60661,55088,PRETRIAL,Kenneth,Littlejohn,NULL,Male,African-American,07/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +53637,60668,55094,PRETRIAL,GARCIA,ALEX,NULL,Male,Caucasian,05/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +53637,60668,55094,PRETRIAL,GARCIA,ALEX,NULL,Male,Caucasian,05/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +53637,60668,55094,PRETRIAL,GARCIA,ALEX,NULL,Male,Caucasian,05/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53647,60682,55106,Probation,MOORE,TOBIAS,NULL,Male,African-American,08/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +53647,60682,55106,Probation,MOORE,TOBIAS,NULL,Male,African-American,08/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +53647,60682,55106,Probation,MOORE,TOBIAS,NULL,Male,African-American,08/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53632,60662,55089,PRETRIAL,Garcia,Juan,NULL,Male,Caucasian,02/02/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.15,8,High,New,1,0 +53632,60662,55089,PRETRIAL,Garcia,Juan,NULL,Male,Caucasian,02/02/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +53632,60662,55089,PRETRIAL,Garcia,Juan,NULL,Male,Caucasian,02/02/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +53646,60683,55107,Probation,Cavalanti,Daniel,Wellington,Male,Hispanic,11/28/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +53646,60683,55107,Probation,Cavalanti,Daniel,Wellington,Male,Hispanic,11/28/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +53646,60683,55107,Probation,Cavalanti,Daniel,Wellington,Male,Hispanic,11/28/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +24200,60696,55119,Probation,rattray,wilbur,NULL,Male,African-American,11/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +24200,60696,55119,Probation,rattray,wilbur,NULL,Male,African-American,11/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +24200,60696,55119,Probation,rattray,wilbur,NULL,Male,African-American,11/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51148,60691,52305,PRETRIAL,Thomas,Henson,NULL,Male,African-American,08/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/4/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,Copy,1,0 +51148,60691,52305,PRETRIAL,Thomas,Henson,NULL,Male,African-American,08/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/4/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,Copy,1,0 +51148,60691,52305,PRETRIAL,Thomas,Henson,NULL,Male,African-American,08/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +53639,60670,55096,PRETRIAL,Carrillo,Helen,NULL,Female,Hispanic,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +53639,60670,55096,PRETRIAL,Carrillo,Helen,NULL,Female,Hispanic,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +53639,60670,55096,PRETRIAL,Carrillo,Helen,NULL,Female,Hispanic,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53644,60678,55102,Probation,ochart,john,NULL,Male,Caucasian,07/09/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/13 0:00,2,Medium,7,Risk of Violence,-3.46,1,Low,New,1,0 +53644,60678,55102,Probation,ochart,john,NULL,Male,Caucasian,07/09/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +53644,60678,55102,Probation,ochart,john,NULL,Male,Caucasian,07/09/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +28758,60701,55124,PRETRIAL,Murphy,Terrance,NULL,Male,African-American,09/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/4/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +28758,60701,55124,PRETRIAL,Murphy,Terrance,NULL,Male,African-American,09/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/4/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +28758,60701,55124,PRETRIAL,Murphy,Terrance,NULL,Male,African-American,09/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53635,60665,55092,PRETRIAL,Hawkins,Charles,NULL,Male,African-American,12/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +53635,60665,55092,PRETRIAL,Hawkins,Charles,NULL,Male,African-American,12/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +53635,60665,55092,PRETRIAL,Hawkins,Charles,NULL,Male,African-American,12/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +35213,60680,55104,PRETRIAL,HANSLER,THOMAS,NULL,Male,Caucasian,08/30/66,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +35213,60680,55104,PRETRIAL,HANSLER,THOMAS,NULL,Male,Caucasian,08/30/66,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +35213,60680,55104,PRETRIAL,HANSLER,THOMAS,NULL,Male,Caucasian,08/30/66,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,1,Low,New,1,0 +53659,60699,55122,PRETRIAL,Hart,Walter,NULL,Male,African-American,01/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,4,High,7,Risk of Violence,-1.01,8,High,New,1,0 +53659,60699,55122,PRETRIAL,Hart,Walter,NULL,Male,African-American,01/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +53659,60699,55122,PRETRIAL,Hart,Walter,NULL,Male,African-American,01/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44418,60672,55097,Probation,Diaz,Anthony,sean,Male,Hispanic,10/08/83,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +44418,60672,55097,Probation,Diaz,Anthony,sean,Male,Hispanic,10/08/83,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,8,Risk of Recidivism,0.13,7,Medium,New,1,0 +44418,60672,55097,Probation,Diaz,Anthony,sean,Male,Hispanic,10/08/83,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/4/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53649,60686,55110,PRETRIAL,Fasano,Anthony,P,Male,Caucasian,03/06/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/4/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +53649,60686,55110,PRETRIAL,Fasano,Anthony,P,Male,Caucasian,03/06/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/4/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +53649,60686,55110,PRETRIAL,Fasano,Anthony,P,Male,Caucasian,03/06/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53654,60693,55116,Probation,martin,ranjeet,NULL,Male,African-American,11/07/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +53654,60693,55116,Probation,martin,ranjeet,NULL,Male,African-American,11/07/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.79,10,High,New,1,0 +53654,60693,55116,Probation,martin,ranjeet,NULL,Male,African-American,11/07/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,46,10,High,New,1,0 +53665,60707,55129,PRETRIAL,Holmes,Thaddaus,NULL,Male,African-American,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +53665,60707,55129,PRETRIAL,Holmes,Thaddaus,NULL,Male,African-American,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +53665,60707,55129,PRETRIAL,Holmes,Thaddaus,NULL,Male,African-American,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53675,60722,55141,PRETRIAL,castro,maximo,NULL,Male,Hispanic,09/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/5/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +53675,60722,55141,PRETRIAL,castro,maximo,NULL,Male,Hispanic,09/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +53675,60722,55141,PRETRIAL,castro,maximo,NULL,Male,Hispanic,09/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +38559,60714,53369,PRETRIAL,Salcedo,Marwinn,NULL,Male,Caucasian,08/07/86,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +38559,60714,53369,PRETRIAL,Salcedo,Marwinn,NULL,Male,Caucasian,08/07/86,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.28,1,Low,New,1,0 +38559,60714,53369,PRETRIAL,Salcedo,Marwinn,NULL,Male,Caucasian,08/07/86,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53683,60735,55152,Probation,PEREZ ROBLES,ROBERT,A,Male,Hispanic,07/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +53683,60735,55152,Probation,PEREZ ROBLES,ROBERT,A,Male,Hispanic,07/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +53683,60735,55152,Probation,PEREZ ROBLES,ROBERT,A,Male,Hispanic,07/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53668,60709,55131,PRETRIAL,Quintero,Luis,NULL,Male,Caucasian,07/07/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +53668,60709,55131,PRETRIAL,Quintero,Luis,NULL,Male,Caucasian,07/07/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +53668,60709,55131,PRETRIAL,Quintero,Luis,NULL,Male,Caucasian,07/07/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53684,60738,55155,Probation,RODRIGUEZ,Giovanna,NULL,Female,Hispanic,09/07/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/5/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +53684,60738,55155,Probation,RODRIGUEZ,Giovanna,NULL,Female,Hispanic,09/07/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +53684,60738,55155,Probation,RODRIGUEZ,Giovanna,NULL,Female,Hispanic,09/07/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +27170,60730,55148,Probation,brinson,aaron,NULL,Male,African-American,07/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +27170,60730,55148,Probation,brinson,aaron,NULL,Male,African-American,07/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +27170,60730,55148,Probation,brinson,aaron,NULL,Male,African-American,07/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53673,60717,55138,PRETRIAL,Lejean,Guignard,NULL,Male,African-American,09/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +53673,60717,55138,PRETRIAL,Lejean,Guignard,NULL,Male,African-American,09/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +53673,60717,55138,PRETRIAL,Lejean,Guignard,NULL,Male,African-American,09/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53680,60731,55149,Probation,NORWOOD,SHONA,L,Female,African-American,09/28/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/5/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +53680,60731,55149,Probation,NORWOOD,SHONA,L,Female,African-American,09/28/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +53680,60731,55149,Probation,NORWOOD,SHONA,L,Female,African-American,09/28/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +53661,60703,55125,PRETRIAL,Soto,Jessica,NULL,Female,Hispanic,03/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +53661,60703,55125,PRETRIAL,Soto,Jessica,NULL,Female,Hispanic,03/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +53661,60703,55125,PRETRIAL,Soto,Jessica,NULL,Female,Hispanic,03/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53667,60710,55132,PRETRIAL,Larmond,Christopher,Llewelyn,Male,African-American,04/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +53667,60710,55132,PRETRIAL,Larmond,Christopher,Llewelyn,Male,African-American,04/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +53667,60710,55132,PRETRIAL,Larmond,Christopher,Llewelyn,Male,African-American,04/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53669,60712,55134,PRETRIAL,Hogan,Allatia,NULL,Male,Caucasian,01/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +53669,60712,55134,PRETRIAL,Hogan,Allatia,NULL,Male,Caucasian,01/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +53669,60712,55134,PRETRIAL,Hogan,Allatia,NULL,Male,Caucasian,01/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53686,60740,55157,Probation,Sosa,David,NULL,Male,Hispanic,11/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +53686,60740,55157,Probation,Sosa,David,NULL,Male,Hispanic,11/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +53686,60740,55157,Probation,Sosa,David,NULL,Male,Hispanic,11/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53672,60715,55136,Probation,Reeves,Kierra,Montez,Female,African-American,08/29/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +53672,60715,55136,Probation,Reeves,Kierra,Montez,Female,African-American,08/29/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +53672,60715,55136,Probation,Reeves,Kierra,Montez,Female,African-American,08/29/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53679,60728,55147,Probation,Ruiz,Luis,Armando,Male,Hispanic,01/22/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,4/5/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +53679,60728,55147,Probation,Ruiz,Luis,Armando,Male,Hispanic,01/22/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +53679,60728,55147,Probation,Ruiz,Luis,Armando,Male,Hispanic,01/22/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52730,60745,55162,Probation,KIRWAN,CHRISTOPHER,L,Male,Caucasian,04/04/69,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +52730,60745,55162,Probation,KIRWAN,CHRISTOPHER,L,Male,Caucasian,04/04/69,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +52730,60745,55162,Probation,KIRWAN,CHRISTOPHER,L,Male,Caucasian,04/04/69,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53676,60724,55143,PRETRIAL,Buttler,Radcliffe,NULL,Male,African-American,05/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/5/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +53676,60724,55143,PRETRIAL,Buttler,Radcliffe,NULL,Male,African-American,05/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +53676,60724,55143,PRETRIAL,Buttler,Radcliffe,NULL,Male,African-American,05/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53682,60734,55151,Probation,frankson,alexander,NULL,Male,African-American,12/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +53682,60734,55151,Probation,frankson,alexander,NULL,Male,African-American,12/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +53682,60734,55151,Probation,frankson,alexander,NULL,Male,African-American,12/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53663,60705,55127,PRETRIAL,Kuchta,Gary,NULL,Male,Caucasian,04/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +53663,60705,55127,PRETRIAL,Kuchta,Gary,NULL,Male,Caucasian,04/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +53663,60705,55127,PRETRIAL,Kuchta,Gary,NULL,Male,Caucasian,04/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53670,60716,55137,PRETRIAL,Ewing,Regina,NULL,Female,African-American,12/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +53670,60716,55137,PRETRIAL,Ewing,Regina,NULL,Female,African-American,12/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +53670,60716,55137,PRETRIAL,Ewing,Regina,NULL,Female,African-American,12/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +45744,60729,53951,PRETRIAL,MERCADO,JAVIER,NULL,Male,Caucasian,10/11/59,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +45744,60729,53951,PRETRIAL,MERCADO,JAVIER,NULL,Male,Caucasian,10/11/59,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +45744,60729,53951,PRETRIAL,MERCADO,JAVIER,NULL,Male,Caucasian,10/11/59,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +42992,60737,55154,PRETRIAL,bethell,union,NULL,Male,Caucasian,05/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +42992,60737,55154,PRETRIAL,bethell,union,NULL,Male,Caucasian,05/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +42992,60737,55154,PRETRIAL,bethell,union,NULL,Male,Caucasian,05/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53688,60742,55159,Probation,OCONNOR,JAMES,ENNIS,Male,Caucasian,11/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +53688,60742,55159,Probation,OCONNOR,JAMES,ENNIS,Male,Caucasian,11/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +53688,60742,55159,Probation,OCONNOR,JAMES,ENNIS,Male,Caucasian,11/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53691,60744,55161,PRETRIAL,Walthour,Davon,NULL,Male,African-American,04/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +53691,60744,55161,PRETRIAL,Walthour,Davon,NULL,Male,African-American,04/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +53691,60744,55161,PRETRIAL,Walthour,Davon,NULL,Male,African-American,04/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45560,60736,55153,PRETRIAL,Johnson,Demetrius,NULL,Male,African-American,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +45560,60736,55153,PRETRIAL,Johnson,Demetrius,NULL,Male,African-American,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +45560,60736,55153,PRETRIAL,Johnson,Demetrius,NULL,Male,African-American,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53666,60708,55130,PRETRIAL,Rodriguez,Nicky,NULL,Male,Hispanic,12/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/5/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +53666,60708,55130,PRETRIAL,Rodriguez,Nicky,NULL,Male,Hispanic,12/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +53666,60708,55130,PRETRIAL,Rodriguez,Nicky,NULL,Male,Hispanic,12/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +33061,60721,55140,PRETRIAL,jones,clarissa,NULL,Female,African-American,01/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +33061,60721,55140,PRETRIAL,jones,clarissa,NULL,Female,African-American,01/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,8,High,New,1,0 +33061,60721,55140,PRETRIAL,jones,clarissa,NULL,Female,African-American,01/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,New,1,0 +51722,60720,52946,Probation,KLEIER,GEORGE,W,Male,Caucasian,09/29/69,17,All Scales,Intake,English,Conditional Release,Probation,Married,4/5/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +51722,60720,52946,Probation,KLEIER,GEORGE,W,Male,Caucasian,09/29/69,17,All Scales,Intake,English,Conditional Release,Probation,Married,4/5/13 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +51722,60720,52946,Probation,KLEIER,GEORGE,W,Male,Caucasian,09/29/69,17,All Scales,Intake,English,Conditional Release,Probation,Married,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53664,60706,55128,PRETRIAL,myers,Alfranzwell,NULL,Male,African-American,05/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +53664,60706,55128,PRETRIAL,myers,Alfranzwell,NULL,Male,African-American,05/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +53664,60706,55128,PRETRIAL,myers,Alfranzwell,NULL,Male,African-American,05/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +39150,60723,55142,PRETRIAL,Kopsaftis,Philip,NULL,Male,Caucasian,01/22/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +39150,60723,55142,PRETRIAL,Kopsaftis,Philip,NULL,Male,Caucasian,01/22/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +39150,60723,55142,PRETRIAL,Kopsaftis,Philip,NULL,Male,Caucasian,01/22/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53687,60741,55158,Probation,Cordero,Wilfredo,NULL,Male,Hispanic,09/13/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +53687,60741,55158,Probation,Cordero,Wilfredo,NULL,Male,Hispanic,09/13/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +53687,60741,55158,Probation,Cordero,Wilfredo,NULL,Male,Hispanic,09/13/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53677,60732,55145,PRETRIAL,salcedo,alexis,NULL,Male,Caucasian,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/5/13 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,Copy,1,0 +53677,60732,55145,PRETRIAL,salcedo,alexis,NULL,Male,Caucasian,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,Copy,1,0 +53677,60732,55145,PRETRIAL,salcedo,alexis,NULL,Male,Caucasian,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/5/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +49180,60746,49981,PRETRIAL,Eason,Kevin,Lester,Male,African-American,09/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,Copy,1,0 +49180,60746,49981,PRETRIAL,Eason,Kevin,Lester,Male,African-American,09/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,Copy,1,0 +49180,60746,49981,PRETRIAL,Eason,Kevin,Lester,Male,African-American,09/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +53685,60739,55156,Probation,Shih,Johnathan,Kvo,Male,Asian,11/07/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/5/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +53685,60739,55156,Probation,Shih,Johnathan,Kvo,Male,Asian,11/07/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +53685,60739,55156,Probation,Shih,Johnathan,Kvo,Male,Asian,11/07/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +42445,60711,55133,PRETRIAL,Labordeaux,Demarr,NULL,Male,African-American,04/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +42445,60711,55133,PRETRIAL,Labordeaux,Demarr,NULL,Male,African-American,04/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +42445,60711,55133,PRETRIAL,Labordeaux,Demarr,NULL,Male,African-American,04/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53674,60718,55139,Probation,Palmer,Steven,NULL,Male,African-American,03/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +53674,60718,55139,Probation,Palmer,Steven,NULL,Male,African-American,03/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,4,High,8,Risk of Recidivism,0.79,10,High,New,1,0 +53674,60718,55139,Probation,Palmer,Steven,NULL,Male,African-American,03/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/5/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +47912,60725,55144,Probation,mejia,rene,NULL,Male,Caucasian,02/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/5/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +47912,60725,55144,Probation,mejia,rene,NULL,Male,Caucasian,02/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/5/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +47912,60725,55144,Probation,mejia,rene,NULL,Male,Caucasian,02/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53692,60748,55164,PRETRIAL,Robinson,Rennard,NULL,Male,African-American,11/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +53692,60748,55164,PRETRIAL,Robinson,Rennard,NULL,Male,African-American,11/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +53692,60748,55164,PRETRIAL,Robinson,Rennard,NULL,Male,African-American,11/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53706,60767,55179,PRETRIAL,huffman,randy,NULL,Male,Caucasian,05/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +53706,60767,55179,PRETRIAL,huffman,randy,NULL,Male,Caucasian,05/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +53706,60767,55179,PRETRIAL,huffman,randy,NULL,Male,Caucasian,05/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53707,60769,55181,PRETRIAL,Marti,Michael,NULL,Male,African-American,08/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +53707,60769,55181,PRETRIAL,Marti,Michael,NULL,Male,African-American,08/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +53707,60769,55181,PRETRIAL,Marti,Michael,NULL,Male,African-American,08/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +49253,60753,52509,PRETRIAL,BAKER,PARET,ANTOINE,Male,African-American,10/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,4,High,7,Risk of Violence,-0.55,10,High,Copy,1,0 +49253,60753,52509,PRETRIAL,BAKER,PARET,ANTOINE,Male,African-American,10/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,4,High,8,Risk of Recidivism,0.83,10,High,Copy,1,0 +49253,60753,52509,PRETRIAL,BAKER,PARET,ANTOINE,Male,African-American,10/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +53702,60762,55175,PRETRIAL,Cooke,Patricia,NULL,Female,Caucasian,01/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +53702,60762,55175,PRETRIAL,Cooke,Patricia,NULL,Female,Caucasian,01/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,8,Risk of Recidivism,-1.61,2,Low,New,1,0 +53702,60762,55175,PRETRIAL,Cooke,Patricia,NULL,Female,Caucasian,01/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53699,60757,55171,PRETRIAL,Reeves,James,NULL,Male,Caucasian,07/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +53699,60757,55171,PRETRIAL,Reeves,James,NULL,Male,Caucasian,07/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +53699,60757,55171,PRETRIAL,Reeves,James,NULL,Male,Caucasian,07/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53700,60758,55172,PRETRIAL,Harrigan,Bernirust,NULL,Male,African-American,09/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +53700,60758,55172,PRETRIAL,Harrigan,Bernirust,NULL,Male,African-American,09/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +53700,60758,55172,PRETRIAL,Harrigan,Bernirust,NULL,Male,African-American,09/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +20922,60750,20102,PRETRIAL,Coney,Steven,James,Male,African-American,08/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,Copy,1,0 +20922,60750,20102,PRETRIAL,Coney,Steven,James,Male,African-American,08/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,4,High,8,Risk of Recidivism,0.25,8,High,Copy,1,0 +20922,60750,20102,PRETRIAL,Coney,Steven,James,Male,African-American,08/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +53703,60763,55176,PRETRIAL,Scolo,John,NULL,Male,Caucasian,06/09/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +53703,60763,55176,PRETRIAL,Scolo,John,NULL,Male,Caucasian,06/09/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +53703,60763,55176,PRETRIAL,Scolo,John,NULL,Male,Caucasian,06/09/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53704,60765,55177,PRETRIAL,Joyce,Theopholus,NULL,Male,African-American,03/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,7,Risk of Violence,-1.27,7,Medium,New,1,0 +53704,60765,55177,PRETRIAL,Joyce,Theopholus,NULL,Male,African-American,03/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +53704,60765,55177,PRETRIAL,Joyce,Theopholus,NULL,Male,African-American,03/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +53697,60755,55169,PRETRIAL,Jaakson,Shawn,NULL,Male,Caucasian,06/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +53697,60755,55169,PRETRIAL,Jaakson,Shawn,NULL,Male,Caucasian,06/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +53697,60755,55169,PRETRIAL,Jaakson,Shawn,NULL,Male,Caucasian,06/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53695,60752,55167,PRETRIAL,Ervin,Mikel,NULL,Male,African-American,12/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +53695,60752,55167,PRETRIAL,Ervin,Mikel,NULL,Male,African-American,12/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +53695,60752,55167,PRETRIAL,Ervin,Mikel,NULL,Male,African-American,12/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +8105,60760,55173,PRETRIAL,THOMAS,TAROD,JEROME,Male,African-American,10/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +8105,60760,55173,PRETRIAL,THOMAS,TAROD,JEROME,Male,African-American,10/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +8105,60760,55173,PRETRIAL,THOMAS,TAROD,JEROME,Male,African-American,10/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +50698,60747,55163,PRETRIAL,Smith,Deandre,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +50698,60747,55163,PRETRIAL,Smith,Deandre,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +50698,60747,55163,PRETRIAL,Smith,Deandre,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53693,60749,55165,PRETRIAL,Wilson,Michael,NULL,Male,African-American,08/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +53693,60749,55165,PRETRIAL,Wilson,Michael,NULL,Male,African-American,08/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.99,10,High,New,1,0 +53693,60749,55165,PRETRIAL,Wilson,Michael,NULL,Male,African-American,08/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53705,60766,55178,PRETRIAL,Gabriel,Renet,NULL,Male,African-American,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +53705,60766,55178,PRETRIAL,Gabriel,Renet,NULL,Male,African-American,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +53705,60766,55178,PRETRIAL,Gabriel,Renet,NULL,Male,African-American,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53696,60754,55168,PRETRIAL,MOYE,TERRANCE,LAMAR,Male,African-American,08/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +53696,60754,55168,PRETRIAL,MOYE,TERRANCE,LAMAR,Male,African-American,08/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +53696,60754,55168,PRETRIAL,MOYE,TERRANCE,LAMAR,Male,African-American,08/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53701,60761,55174,PRETRIAL,Mcgee,Cedric,NULL,Male,African-American,11/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +53701,60761,55174,PRETRIAL,Mcgee,Cedric,NULL,Male,African-American,11/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +53701,60761,55174,PRETRIAL,Mcgee,Cedric,NULL,Male,African-American,11/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53694,60751,55166,PRETRIAL,Cuellar,David,NULL,Male,Hispanic,02/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +53694,60751,55166,PRETRIAL,Cuellar,David,NULL,Male,Hispanic,02/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +53694,60751,55166,PRETRIAL,Cuellar,David,NULL,Male,Hispanic,02/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +42346,60764,42164,PRETRIAL,Mendez,Richard,NULL,Male,Caucasian,03/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/6/13 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,Copy,1,0 +42346,60764,42164,PRETRIAL,Mendez,Richard,NULL,Male,Caucasian,03/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,6,Medium,Copy,1,0 +42346,60764,42164,PRETRIAL,Mendez,Richard,NULL,Male,Caucasian,03/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/6/13 0:00,2,Medium,18,Risk of Failure to Appear,29,7,Medium,Copy,1,0 +53698,60756,55170,PRETRIAL,NIEVES,STEVE,ALEXANDER,Male,Hispanic,03/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +53698,60756,55170,PRETRIAL,NIEVES,STEVE,ALEXANDER,Male,Hispanic,03/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +53698,60756,55170,PRETRIAL,NIEVES,STEVE,ALEXANDER,Male,Hispanic,03/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45796,60759,46116,PRETRIAL,Walker,Antonio,NULL,Male,African-American,12/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,Copy,1,0 +45796,60759,46116,PRETRIAL,Walker,Antonio,NULL,Male,African-American,12/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,Copy,1,0 +45796,60759,46116,PRETRIAL,Walker,Antonio,NULL,Male,African-American,12/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +28573,60777,27616,PRETRIAL,ANDERSON,LUDOVINO,NULL,Male,African-American,05/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,Copy,1,0 +28573,60777,27616,PRETRIAL,ANDERSON,LUDOVINO,NULL,Male,African-American,05/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,Copy,1,0 +28573,60777,27616,PRETRIAL,ANDERSON,LUDOVINO,NULL,Male,African-American,05/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +53716,60785,55193,PRETRIAL,Lewis,Nicholas,NULL,Male,Caucasian,10/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +53716,60785,55193,PRETRIAL,Lewis,Nicholas,NULL,Male,Caucasian,10/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +53716,60785,55193,PRETRIAL,Lewis,Nicholas,NULL,Male,Caucasian,10/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53712,60780,55189,PRETRIAL,Tessler,Eric,NULL,Male,Caucasian,01/16/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/7/13 0:00,1,Low,7,Risk of Violence,-4.47,1,Low,New,1,0 +53712,60780,55189,PRETRIAL,Tessler,Eric,NULL,Male,Caucasian,01/16/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/7/13 0:00,1,Low,8,Risk of Recidivism,-2.9,1,Low,New,1,0 +53712,60780,55189,PRETRIAL,Tessler,Eric,NULL,Male,Caucasian,01/16/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +47596,60772,55183,PRETRIAL,mele,patricia,NULL,Female,Caucasian,10/06/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/7/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +47596,60772,55183,PRETRIAL,mele,patricia,NULL,Female,Caucasian,10/06/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/7/13 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +47596,60772,55183,PRETRIAL,mele,patricia,NULL,Female,Caucasian,10/06/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53721,60793,55199,PRETRIAL,Young,Arrik,j,Male,African-American,12/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +53721,60793,55199,PRETRIAL,Young,Arrik,j,Male,African-American,12/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +53721,60793,55199,PRETRIAL,Young,Arrik,j,Male,African-American,12/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53709,60775,55186,PRETRIAL,Henriquez,Christian,NULL,Male,Hispanic,05/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +53709,60775,55186,PRETRIAL,Henriquez,Christian,NULL,Male,Hispanic,05/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +53709,60775,55186,PRETRIAL,Henriquez,Christian,NULL,Male,Hispanic,05/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53713,60782,55190,PRETRIAL,Elliot,Jamie,NULL,Male,African-American,12/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +53713,60782,55190,PRETRIAL,Elliot,Jamie,NULL,Male,African-American,12/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +53713,60782,55190,PRETRIAL,Elliot,Jamie,NULL,Male,African-American,12/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +24649,60787,23824,PRETRIAL,Youvens,Horace,NULL,Male,Other,05/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.12,8,High,Copy,1,0 +24649,60787,23824,PRETRIAL,Youvens,Horace,NULL,Male,Other,05/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.14,6,Medium,Copy,1,0 +24649,60787,23824,PRETRIAL,Youvens,Horace,NULL,Male,Other,05/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +53719,60791,55197,PRETRIAL,Roberts,Roy,NULL,Male,Caucasian,08/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +53719,60791,55197,PRETRIAL,Roberts,Roy,NULL,Male,Caucasian,08/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,4,High,8,Risk of Recidivism,0.36,9,High,New,1,0 +53719,60791,55197,PRETRIAL,Roberts,Roy,NULL,Male,Caucasian,08/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +39796,60770,55182,PRETRIAL,KENDRICK,JARRETT,NULL,Male,African-American,01/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.22,4,Low,New,1,0 +39796,60770,55182,PRETRIAL,KENDRICK,JARRETT,NULL,Male,African-American,01/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +39796,60770,55182,PRETRIAL,KENDRICK,JARRETT,NULL,Male,African-American,01/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53715,60784,55192,PRETRIAL,Gomez,Eriberto,NULL,Male,Caucasian,10/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/7/13 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +53715,60784,55192,PRETRIAL,Gomez,Eriberto,NULL,Male,Caucasian,10/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/7/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +53715,60784,55192,PRETRIAL,Gomez,Eriberto,NULL,Male,Caucasian,10/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/7/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +12257,60781,11748,PRETRIAL,BURKE,WILLIAM,EDWARD,Male,African-American,04/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,4,High,7,Risk of Violence,-0.82,9,High,Copy,1,0 +12257,60781,11748,PRETRIAL,BURKE,WILLIAM,EDWARD,Male,African-American,04/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,4,High,8,Risk of Recidivism,0.6,9,High,Copy,1,0 +12257,60781,11748,PRETRIAL,BURKE,WILLIAM,EDWARD,Male,African-American,04/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +53722,60794,55200,PRETRIAL,Simon,Michall,NULL,Male,African-American,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +53722,60794,55200,PRETRIAL,Simon,Michall,NULL,Male,African-American,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +53722,60794,55200,PRETRIAL,Simon,Michall,NULL,Male,African-American,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53708,60773,55184,PRETRIAL,WILLIAMS,DAVID,V,Male,African-American,11/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +53708,60773,55184,PRETRIAL,WILLIAMS,DAVID,V,Male,African-American,11/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/13 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +53708,60773,55184,PRETRIAL,WILLIAMS,DAVID,V,Male,African-American,11/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53711,60778,55187,PRETRIAL,Brooks,Roy,NULL,Male,African-American,07/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.23,8,High,New,1,0 +53711,60778,55187,PRETRIAL,Brooks,Roy,NULL,Male,African-American,07/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +53711,60778,55187,PRETRIAL,Brooks,Roy,NULL,Male,African-American,07/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53717,60786,55194,PRETRIAL,Diaz Acosta,Eusebio,NULL,Male,Hispanic,12/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/7/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +53717,60786,55194,PRETRIAL,Diaz Acosta,Eusebio,NULL,Male,Hispanic,12/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/7/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +53717,60786,55194,PRETRIAL,Diaz Acosta,Eusebio,NULL,Male,Hispanic,12/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/7/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +24690,60771,23866,PRETRIAL,PROCTOR,CLIFFORD,NULL,Male,African-American,12/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,Copy,1,0 +24690,60771,23866,PRETRIAL,PROCTOR,CLIFFORD,NULL,Male,African-American,12/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,Copy,1,0 +24690,60771,23866,PRETRIAL,PROCTOR,CLIFFORD,NULL,Male,African-American,12/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +53720,60792,55198,PRETRIAL,Aulet,Magalys,NULL,Female,Hispanic,12/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/7/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +53720,60792,55198,PRETRIAL,Aulet,Magalys,NULL,Female,Hispanic,12/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/7/13 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +53720,60792,55198,PRETRIAL,Aulet,Magalys,NULL,Female,Hispanic,12/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53714,60783,55191,PRETRIAL,Scafidi,Nicholas,Albert,Male,Caucasian,12/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +53714,60783,55191,PRETRIAL,Scafidi,Nicholas,Albert,Male,Caucasian,12/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +53714,60783,55191,PRETRIAL,Scafidi,Nicholas,Albert,Male,Caucasian,12/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +14531,60774,55185,PRETRIAL,Jackson,Trenard,Lavar,Male,African-American,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +14531,60774,55185,PRETRIAL,Jackson,Trenard,Lavar,Male,African-American,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +14531,60774,55185,PRETRIAL,Jackson,Trenard,Lavar,Male,African-American,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/13 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +7024,60776,6615,PRETRIAL,BIRCHLAGRAIN,TVARIS,ALVEREZ,Male,African-American,12/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,Copy,1,0 +7024,60776,6615,PRETRIAL,BIRCHLAGRAIN,TVARIS,ALVEREZ,Male,African-American,12/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,Copy,1,0 +7024,60776,6615,PRETRIAL,BIRCHLAGRAIN,TVARIS,ALVEREZ,Male,African-American,12/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +53718,60790,55196,PRETRIAL,Rodriguez-Cabreja,Hamlet,NULL,Male,Hispanic,12/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/7/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +53718,60790,55196,PRETRIAL,Rodriguez-Cabreja,Hamlet,NULL,Male,Hispanic,12/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/7/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +53718,60790,55196,PRETRIAL,Rodriguez-Cabreja,Hamlet,NULL,Male,Hispanic,12/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +44921,60825,53730,Probation,whitehead,travis,NULL,Male,African-American,05/03/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +44921,60825,53730,Probation,whitehead,travis,NULL,Male,African-American,05/03/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +44921,60825,53730,Probation,whitehead,travis,NULL,Male,African-American,05/03/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,2,Medium,18,Risk of Failure to Appear,19,2,Low,New,1,0 +53753,60839,55239,Probation,Tinoco,Leonardo,Jesus,Male,Hispanic,11/06/58,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,4/8/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +53753,60839,55239,Probation,Tinoco,Leonardo,Jesus,Male,Hispanic,11/06/58,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,4/8/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +53753,60839,55239,Probation,Tinoco,Leonardo,Jesus,Male,Hispanic,11/06/58,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +9130,60804,55210,PRETRIAL,MILLER,THERESA,NULL,Female,African-American,10/06/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,7,Risk of Violence,-2.61,2,Low,New,1,0 +9130,60804,55210,PRETRIAL,MILLER,THERESA,NULL,Female,African-American,10/06/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +9130,60804,55210,PRETRIAL,MILLER,THERESA,NULL,Female,African-American,10/06/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,18,Risk of Failure to Appear,29,9,High,New,1,0 +35882,60811,42272,PRETRIAL,Bass,Kevin,NULL,Male,Caucasian,03/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,Copy,1,0 +35882,60811,42272,PRETRIAL,Bass,Kevin,NULL,Male,Caucasian,03/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,4,High,8,Risk of Recidivism,0.23,8,High,Copy,1,0 +35882,60811,42272,PRETRIAL,Bass,Kevin,NULL,Male,Caucasian,03/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +53737,60818,55221,Probation,Torres Rivera,Jose,M,Male,Hispanic,11/17/67,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +53737,60818,55221,Probation,Torres Rivera,Jose,M,Male,Hispanic,11/17/67,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +53737,60818,55221,Probation,Torres Rivera,Jose,M,Male,Hispanic,11/17/67,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +35171,60797,55203,PRETRIAL,Brown,Jack,NULL,Male,African-American,03/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +35171,60797,55203,PRETRIAL,Brown,Jack,NULL,Male,African-American,03/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +35171,60797,55203,PRETRIAL,Brown,Jack,NULL,Male,African-American,03/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +23204,60846,55245,PRETRIAL,Tucker,Shawntavian,NULL,Male,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +23204,60846,55245,PRETRIAL,Tucker,Shawntavian,NULL,Male,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.73,10,High,New,1,0 +23204,60846,55245,PRETRIAL,Tucker,Shawntavian,NULL,Male,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53763,60848,55247,Probation,Jackson,Judith,C,Female,African-American,03/19/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/8/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +53763,60848,55247,Probation,Jackson,Judith,C,Female,African-American,03/19/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +53763,60848,55247,Probation,Jackson,Judith,C,Female,African-American,03/19/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53723,60795,55201,PRETRIAL,dixon,charles,NULL,Male,African-American,02/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.7,2,Low,New,1,0 +53723,60795,55201,PRETRIAL,dixon,charles,NULL,Male,African-American,02/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +53723,60795,55201,PRETRIAL,dixon,charles,NULL,Male,African-American,02/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +53730,60809,55213,PRETRIAL,Hrinda,Gary,NULL,Male,Caucasian,06/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +53730,60809,55213,PRETRIAL,Hrinda,Gary,NULL,Male,Caucasian,06/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +53730,60809,55213,PRETRIAL,Hrinda,Gary,NULL,Male,Caucasian,06/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +53733,60813,55216,PRETRIAL,BOYD,KENNETH,THERON,Male,African-American,07/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/8/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +53733,60813,55216,PRETRIAL,BOYD,KENNETH,THERON,Male,African-American,07/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +53733,60813,55216,PRETRIAL,BOYD,KENNETH,THERON,Male,African-American,07/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53745,60830,55230,PRETRIAL,Young,Jasmine,Nicole,Female,African-American,10/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +53745,60830,55230,PRETRIAL,Young,Jasmine,Nicole,Female,African-American,10/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +53745,60830,55230,PRETRIAL,Young,Jasmine,Nicole,Female,African-American,10/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53770,60851,55250,DRRD,Wilson,Willie,James,Male,African-American,09/14/87,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/8/13 0:00,4,High,7,Risk of Violence,-0.52,10,High,New,1,0 +53770,60851,55250,DRRD,Wilson,Willie,James,Male,African-American,09/14/87,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/8/13 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +53770,60851,55250,DRRD,Wilson,Willie,James,Male,African-American,09/14/87,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/8/13 0:00,4,High,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +4551,60807,4246,Probation,Robinson,Anthony,Leon,Male,African-American,07/13/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,Copy,1,0 +4551,60807,4246,Probation,Robinson,Anthony,Leon,Male,African-American,07/13/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,Copy,1,0 +4551,60807,4246,Probation,Robinson,Anthony,Leon,Male,African-American,07/13/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +53750,60836,55236,PRETRIAL,Sanchez,Cinthya,NULL,Female,Hispanic,08/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +53750,60836,55236,PRETRIAL,Sanchez,Cinthya,NULL,Female,Hispanic,08/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +53750,60836,55236,PRETRIAL,Sanchez,Cinthya,NULL,Female,Hispanic,08/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53760,60844,55243,Probation,Rider,Leigh,NULL,Female,Caucasian,07/22/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/8/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +53760,60844,55243,Probation,Rider,Leigh,NULL,Female,Caucasian,07/22/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +53760,60844,55243,Probation,Rider,Leigh,NULL,Female,Caucasian,07/22/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +53725,60799,55205,PRETRIAL,HOPSON,PHILLIP,CRAIG,Male,African-American,08/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +53725,60799,55205,PRETRIAL,HOPSON,PHILLIP,CRAIG,Male,African-American,08/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +53725,60799,55205,PRETRIAL,HOPSON,PHILLIP,CRAIG,Male,African-American,08/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +22310,60823,55226,PRETRIAL,Riedy,Thomas,NULL,Male,Caucasian,12/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/13 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,New,1,0 +22310,60823,55226,PRETRIAL,Riedy,Thomas,NULL,Male,Caucasian,12/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +22310,60823,55226,PRETRIAL,Riedy,Thomas,NULL,Male,Caucasian,12/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53758,60841,55241,Probation,Williams,Antrinique,NULL,Female,African-American,01/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +53758,60841,55241,Probation,Williams,Antrinique,NULL,Female,African-American,01/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +53758,60841,55241,Probation,Williams,Antrinique,NULL,Female,African-American,01/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53727,60802,55208,PRETRIAL,McCullough,Timothy,Darryl,Male,African-American,08/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +53727,60802,55208,PRETRIAL,McCullough,Timothy,Darryl,Male,African-American,08/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +53727,60802,55208,PRETRIAL,McCullough,Timothy,Darryl,Male,African-American,08/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53742,60820,55223,PRETRIAL,nguyen,johnny,NULL,Male,Asian,07/11/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +53742,60820,55223,PRETRIAL,nguyen,johnny,NULL,Male,Asian,07/11/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,4,High,8,Risk of Recidivism,0.55,9,High,New,1,0 +53742,60820,55223,PRETRIAL,nguyen,johnny,NULL,Male,Asian,07/11/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,4,High,18,Risk of Failure to Appear,21,3,Low,New,1,0 +29456,60815,55218,PRETRIAL,Graham,Antwoin,NULL,Male,African-American,12/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,4,High,7,Risk of Violence,-0.72,9,High,New,1,0 +29456,60815,55218,PRETRIAL,Graham,Antwoin,NULL,Male,African-American,12/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,4,High,8,Risk of Recidivism,0.32,9,High,New,1,0 +29456,60815,55218,PRETRIAL,Graham,Antwoin,NULL,Male,African-American,12/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52887,60852,54282,Probation,Gatz,Joseph,William,Male,Caucasian,11/12/68,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,4/8/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +52887,60852,54282,Probation,Gatz,Joseph,William,Male,Caucasian,11/12/68,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +52887,60852,54282,Probation,Gatz,Joseph,William,Male,Caucasian,11/12/68,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +53728,60805,55211,PRETRIAL,Martinez,Tiffany,NULL,Female,Hispanic,01/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.34,3,Low,New,1,0 +53728,60805,55211,PRETRIAL,Martinez,Tiffany,NULL,Female,Hispanic,01/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +53728,60805,55211,PRETRIAL,Martinez,Tiffany,NULL,Female,Hispanic,01/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53752,60838,55238,Probation,adrian,ryan,NULL,Male,Caucasian,06/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +53752,60838,55238,Probation,adrian,ryan,NULL,Male,Caucasian,06/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +53752,60838,55238,Probation,adrian,ryan,NULL,Male,Caucasian,06/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53736,60817,55220,PRETRIAL,joseph,elizabeth,NULL,Female,African-American,02/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +53736,60817,55220,PRETRIAL,joseph,elizabeth,NULL,Female,African-American,02/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +53736,60817,55220,PRETRIAL,joseph,elizabeth,NULL,Female,African-American,02/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +9064,60796,55202,PRETRIAL,BRADFORD,TRAVIS,NULL,Male,Caucasian,04/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +9064,60796,55202,PRETRIAL,BRADFORD,TRAVIS,NULL,Male,Caucasian,04/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +9064,60796,55202,PRETRIAL,BRADFORD,TRAVIS,NULL,Male,Caucasian,04/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53762,60847,55246,Probation,cazeau,Judge,NULL,Male,African-American,08/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.27,3,Low,New,1,0 +53762,60847,55246,Probation,cazeau,Judge,NULL,Male,African-American,08/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +53762,60847,55246,Probation,cazeau,Judge,NULL,Male,African-American,08/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +27410,60831,55231,PRETRIAL,Diaz,Ernesto,Alonso,Male,Caucasian,05/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/8/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +27410,60831,55231,PRETRIAL,Diaz,Ernesto,Alonso,Male,Caucasian,05/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +27410,60831,55231,PRETRIAL,Diaz,Ernesto,Alonso,Male,Caucasian,05/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53746,60833,55233,Probation,Carreno,Bryant,NULL,Male,Caucasian,11/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +53746,60833,55233,Probation,Carreno,Bryant,NULL,Male,Caucasian,11/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +53746,60833,55233,Probation,Carreno,Bryant,NULL,Male,Caucasian,11/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +19804,60803,55209,PRETRIAL,Page,Eric,NULL,Male,African-American,04/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +19804,60803,55209,PRETRIAL,Page,Eric,NULL,Male,African-American,04/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +19804,60803,55209,PRETRIAL,Page,Eric,NULL,Male,African-American,04/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +53731,60810,55214,PRETRIAL,Carter,Brian,Edward,Male,Caucasian,11/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +53731,60810,55214,PRETRIAL,Carter,Brian,Edward,Male,Caucasian,11/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +53731,60810,55214,PRETRIAL,Carter,Brian,Edward,Male,Caucasian,11/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +53732,60812,55215,PRETRIAL,Calder,William,NULL,Male,Caucasian,08/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +53732,60812,55215,PRETRIAL,Calder,William,NULL,Male,Caucasian,08/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +53732,60812,55215,PRETRIAL,Calder,William,NULL,Male,Caucasian,08/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53757,60840,55240,DRRD,Craig,Kevis,Savon,Male,African-American,06/17/93,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/8/13 0:00,4,High,7,Risk of Violence,-0.26,10,High,New,1,0 +53757,60840,55240,DRRD,Craig,Kevis,Savon,Male,African-American,06/17/93,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/8/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +53757,60840,55240,DRRD,Craig,Kevis,Savon,Male,African-American,06/17/93,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/8/13 0:00,4,High,18,Risk of Failure to Appear,18,2,Low,New,1,0 +51652,60800,55206,PRETRIAL,Wright,Byron,Moctavius,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +51652,60800,55206,PRETRIAL,Wright,Byron,Moctavius,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +51652,60800,55206,PRETRIAL,Wright,Byron,Moctavius,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53744,60829,55229,PRETRIAL,delgadoleal,jose,NULL,Male,Hispanic,01/14/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/8/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +53744,60829,55229,PRETRIAL,delgadoleal,jose,NULL,Male,Hispanic,01/14/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/8/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +53744,60829,55229,PRETRIAL,delgadoleal,jose,NULL,Male,Hispanic,01/14/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53759,60843,55242,Probation,Smith,Lucas,NULL,Male,African-American,02/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +53759,60843,55242,Probation,Smith,Lucas,NULL,Male,African-American,02/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +53759,60843,55242,Probation,Smith,Lucas,NULL,Male,African-American,02/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53729,60808,55212,PRETRIAL,Elsy,Laura,NULL,Female,African-American,03/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +53729,60808,55212,PRETRIAL,Elsy,Laura,NULL,Female,African-American,03/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +53729,60808,55212,PRETRIAL,Elsy,Laura,NULL,Female,African-American,03/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +35323,60821,55224,PRETRIAL,HEALY,DEBBIE,D,Female,Caucasian,02/20/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/8/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +35323,60821,55224,PRETRIAL,HEALY,DEBBIE,D,Female,Caucasian,02/20/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/8/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +35323,60821,55224,PRETRIAL,HEALY,DEBBIE,D,Female,Caucasian,02/20/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53743,60822,55225,Probation,Lindstrand,christine,NULL,Female,Caucasian,10/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +53743,60822,55225,Probation,Lindstrand,christine,NULL,Female,Caucasian,10/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +53743,60822,55225,Probation,Lindstrand,christine,NULL,Female,Caucasian,10/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53734,60814,55217,PRETRIAL,REEVES,KEISHON,ISAIAH,Male,African-American,06/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +53734,60814,55217,PRETRIAL,REEVES,KEISHON,ISAIAH,Male,African-American,06/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +53734,60814,55217,PRETRIAL,REEVES,KEISHON,ISAIAH,Male,African-American,06/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53735,60816,55219,PRETRIAL,Pugliese,Katherine,NULL,Female,Caucasian,03/05/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +53735,60816,55219,PRETRIAL,Pugliese,Katherine,NULL,Female,Caucasian,03/05/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +53735,60816,55219,PRETRIAL,Pugliese,Katherine,NULL,Female,Caucasian,03/05/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53768,60850,55249,Probation,cruz,andreina,NULL,Female,Caucasian,10/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +53768,60850,55249,Probation,cruz,andreina,NULL,Female,Caucasian,10/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +53768,60850,55249,Probation,cruz,andreina,NULL,Female,Caucasian,10/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55359,63052,57208,Probation,Motiei,Hamid,NULL,Male,Other,02/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +55359,63052,57208,Probation,Motiei,Hamid,NULL,Male,Other,02/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +55359,63052,57208,Probation,Motiei,Hamid,NULL,Male,Other,02/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53726,60801,55207,PRETRIAL,ROJAS,WALTER,CESAR,Male,Caucasian,04/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +53726,60801,55207,PRETRIAL,ROJAS,WALTER,CESAR,Male,Caucasian,04/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +53726,60801,55207,PRETRIAL,ROJAS,WALTER,CESAR,Male,Caucasian,04/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53751,60837,55237,PRETRIAL,Gambuzza,John,NULL,Male,Caucasian,03/26/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/8/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +53751,60837,55237,PRETRIAL,Gambuzza,John,NULL,Male,Caucasian,03/26/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +53751,60837,55237,PRETRIAL,Gambuzza,John,NULL,Male,Caucasian,03/26/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53724,60798,55204,PRETRIAL,Reid,Daniel,NULL,Male,African-American,08/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +53724,60798,55204,PRETRIAL,Reid,Daniel,NULL,Male,African-American,08/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +53724,60798,55204,PRETRIAL,Reid,Daniel,NULL,Male,African-American,08/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +30858,60827,54103,PRETRIAL,tiger,charlie,NULL,Male,Native American,12/26/81,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,4/8/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,Copy,1,0 +30858,60827,54103,PRETRIAL,tiger,charlie,NULL,Male,Native American,12/26/81,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,4/8/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,Copy,1,0 +30858,60827,54103,PRETRIAL,tiger,charlie,NULL,Male,Native American,12/26/81,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +53761,60845,55244,Probation,Arroyo,Jason,NULL,Male,Hispanic,09/06/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.6,2,Low,New,1,0 +53761,60845,55244,Probation,Arroyo,Jason,NULL,Male,Hispanic,09/06/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +53761,60845,55244,Probation,Arroyo,Jason,NULL,Male,Hispanic,09/06/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +9310,60806,8844,PRETRIAL,EHLEN,KARL,G,Male,Caucasian,04/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/8/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,Copy,1,0 +9310,60806,8844,PRETRIAL,EHLEN,KARL,G,Male,Caucasian,04/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/8/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,Copy,1,0 +9310,60806,8844,PRETRIAL,EHLEN,KARL,G,Male,Caucasian,04/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +5416,60824,55227,PRETRIAL,BRIZUELA,JASON,NULL,Male,Caucasian,07/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +5416,60824,55227,PRETRIAL,BRIZUELA,JASON,NULL,Male,Caucasian,07/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +5416,60824,55227,PRETRIAL,BRIZUELA,JASON,NULL,Male,Caucasian,07/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53324,60874,54781,PRETRIAL,Ryan,Micahel,NULL,Male,Caucasian,06/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,Copy,1,0 +53324,60874,54781,PRETRIAL,Ryan,Micahel,NULL,Male,Caucasian,06/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,Copy,1,0 +53324,60874,54781,PRETRIAL,Ryan,Micahel,NULL,Male,Caucasian,06/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +25500,60884,24664,PRETRIAL,rosado,incencio,NULL,Male,Hispanic,01/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/9/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,Copy,1,0 +25500,60884,24664,PRETRIAL,rosado,incencio,NULL,Male,Hispanic,01/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/9/13 0:00,4,High,8,Risk of Recidivism,0.32,9,High,Copy,1,0 +25500,60884,24664,PRETRIAL,rosado,incencio,NULL,Male,Hispanic,01/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/9/13 0:00,4,High,18,Risk of Failure to Appear,38,10,High,Copy,1,0 +53778,60866,55263,PRETRIAL,SANDERS,BERRY,NULL,Male,African-American,05/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +53778,60866,55263,PRETRIAL,SANDERS,BERRY,NULL,Male,African-American,05/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +53778,60866,55263,PRETRIAL,SANDERS,BERRY,NULL,Male,African-American,05/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53771,60853,55251,PRETRIAL,CELINE,JEAN,NULL,Male,African-American,06/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/9/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +53771,60853,55251,PRETRIAL,CELINE,JEAN,NULL,Male,African-American,06/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/9/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +53771,60853,55251,PRETRIAL,CELINE,JEAN,NULL,Male,African-American,06/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53789,60887,55279,PRETRIAL,MIONE,HEIDI,NULL,Female,Caucasian,01/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +53789,60887,55279,PRETRIAL,MIONE,HEIDI,NULL,Female,Caucasian,01/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +53789,60887,55279,PRETRIAL,MIONE,HEIDI,NULL,Female,Caucasian,01/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +37870,60892,55283,PRETRIAL,Guzman,Lesandra,NULL,Female,African-American,11/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +37870,60892,55283,PRETRIAL,Guzman,Lesandra,NULL,Female,African-American,11/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +37870,60892,55283,PRETRIAL,Guzman,Lesandra,NULL,Female,African-American,11/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +53774,60858,55256,PRETRIAL,Obrien,James,NULL,Male,Caucasian,05/30/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/9/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +53774,60858,55256,PRETRIAL,Obrien,James,NULL,Male,Caucasian,05/30/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/9/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +53774,60858,55256,PRETRIAL,Obrien,James,NULL,Male,Caucasian,05/30/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53091,60871,54513,PRETRIAL,WILLIAMS,KEITH,NULL,Male,African-American,12/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/9/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,Copy,1,0 +53091,60871,54513,PRETRIAL,WILLIAMS,KEITH,NULL,Male,African-American,12/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,Copy,1,0 +53091,60871,54513,PRETRIAL,WILLIAMS,KEITH,NULL,Male,African-American,12/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/9/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +14875,60879,55273,PRETRIAL,Walsh,Lina,P,Female,Caucasian,11/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +14875,60879,55273,PRETRIAL,Walsh,Lina,P,Female,Caucasian,11/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,9,High,New,1,0 +14875,60879,55273,PRETRIAL,Walsh,Lina,P,Female,Caucasian,11/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +53782,60875,55270,Probation,Sekosan,John,NULL,Male,Caucasian,01/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/9/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +53782,60875,55270,Probation,Sekosan,John,NULL,Male,Caucasian,01/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/9/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +53782,60875,55270,Probation,Sekosan,John,NULL,Male,Caucasian,01/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53791,60889,55281,Probation,hUTCHENS,DEANNA,NULL,Female,African-American,09/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +53791,60889,55281,Probation,hUTCHENS,DEANNA,NULL,Female,African-American,09/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +53791,60889,55281,Probation,hUTCHENS,DEANNA,NULL,Female,African-American,09/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +39729,60854,55252,PRETRIAL,ROBERTS,ALTON,NULL,Male,African-American,10/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,4,High,7,Risk of Violence,-0.4,10,High,New,1,0 +39729,60854,55252,PRETRIAL,ROBERTS,ALTON,NULL,Male,African-American,10/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,4,High,8,Risk of Recidivism,0.95,10,High,New,1,0 +39729,60854,55252,PRETRIAL,ROBERTS,ALTON,NULL,Male,African-American,10/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +36631,60861,35932,PRETRIAL,Bass,Joshua,NULL,Male,African-American,11/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,Copy,1,0 +36631,60861,35932,PRETRIAL,Bass,Joshua,NULL,Male,African-American,11/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,Copy,1,0 +36631,60861,35932,PRETRIAL,Bass,Joshua,NULL,Male,African-American,11/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +53105,60868,55265,Probation,fowks,kurt,NULL,Male,Caucasian,02/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +53105,60868,55265,Probation,fowks,kurt,NULL,Male,Caucasian,02/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,4,High,8,Risk of Recidivism,0.1,8,High,New,1,0 +53105,60868,55265,Probation,fowks,kurt,NULL,Male,Caucasian,02/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53794,60894,55285,PRETRIAL,Gambino,Ross,NULL,Male,Caucasian,12/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +53794,60894,55285,PRETRIAL,Gambino,Ross,NULL,Male,Caucasian,12/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +53794,60894,55285,PRETRIAL,Gambino,Ross,NULL,Male,Caucasian,12/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53772,60856,55254,PRETRIAL,Herron,Richard,Joseph,Male,Caucasian,12/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +53772,60856,55254,PRETRIAL,Herron,Richard,Joseph,Male,Caucasian,12/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +53772,60856,55254,PRETRIAL,Herron,Richard,Joseph,Male,Caucasian,12/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53781,60873,55269,Probation,Harris,Christopher,NULL,Male,Caucasian,02/14/54,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/9/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +53781,60873,55269,Probation,Harris,Christopher,NULL,Male,Caucasian,02/14/54,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/9/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +53781,60873,55269,Probation,Harris,Christopher,NULL,Male,Caucasian,02/14/54,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +3579,60859,55257,PRETRIAL,ROBINSON,SHANTAVIA,NULL,Female,African-American,07/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,4,High,7,Risk of Violence,-0.9,9,High,New,1,0 +3579,60859,55257,PRETRIAL,ROBINSON,SHANTAVIA,NULL,Female,African-American,07/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +3579,60859,55257,PRETRIAL,ROBINSON,SHANTAVIA,NULL,Female,African-American,07/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53784,60877,55272,Probation,TUN,CHRISTOPHER,A,Male,Caucasian,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,4,High,7,Risk of Violence,-0.27,10,High,New,1,0 +53784,60877,55272,Probation,TUN,CHRISTOPHER,A,Male,Caucasian,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,4,High,8,Risk of Recidivism,0.83,10,High,New,1,0 +53784,60877,55272,Probation,TUN,CHRISTOPHER,A,Male,Caucasian,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +46035,60883,55276,Probation,Mckinnes,Olden,NULL,Male,African-American,03/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +46035,60883,55276,Probation,Mckinnes,Olden,NULL,Male,African-American,03/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +46035,60883,55276,Probation,Mckinnes,Olden,NULL,Male,African-American,03/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53775,60862,55259,PRETRIAL,ALSHIBI,MOHAMMED,NULL,Male,Other,06/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +53775,60862,55259,PRETRIAL,ALSHIBI,MOHAMMED,NULL,Male,Other,06/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +53775,60862,55259,PRETRIAL,ALSHIBI,MOHAMMED,NULL,Male,Other,06/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +27381,60870,55267,PRETRIAL,Quince,Larry,NULL,Male,African-American,11/13/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +27381,60870,55267,PRETRIAL,Quince,Larry,NULL,Male,African-American,11/13/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +27381,60870,55267,PRETRIAL,Quince,Larry,NULL,Male,African-American,11/13/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +53790,60888,55280,Probation,Randall,Jeffrey,Robert,Male,Caucasian,05/20/82,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/9/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +53790,60888,55280,Probation,Randall,Jeffrey,Robert,Male,Caucasian,05/20/82,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/9/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +53790,60888,55280,Probation,Randall,Jeffrey,Robert,Male,Caucasian,05/20/82,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53792,60891,55282,Probation,HARBISON,COURTNEY,NULL,Male,Caucasian,12/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/9/13 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +53792,60891,55282,Probation,HARBISON,COURTNEY,NULL,Male,Caucasian,12/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +53792,60891,55282,Probation,HARBISON,COURTNEY,NULL,Male,Caucasian,12/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/9/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53777,60865,55262,PRETRIAL,GRANT,KEISHA,NULL,Female,African-American,11/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/9/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +53777,60865,55262,PRETRIAL,GRANT,KEISHA,NULL,Female,African-American,11/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/9/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +53777,60865,55262,PRETRIAL,GRANT,KEISHA,NULL,Female,African-American,11/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53785,60880,55274,PRETRIAL,Yisael,Jesse,Zion,Male,African-American,10/26/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,2,Medium,7,Risk of Violence,-2.85,2,Low,New,1,0 +53785,60880,55274,PRETRIAL,Yisael,Jesse,Zion,Male,African-American,10/26/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +53785,60880,55274,PRETRIAL,Yisael,Jesse,Zion,Male,African-American,10/26/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +10206,60878,9729,PRETRIAL,ARMENTEROS,JOVANNY,NULL,Male,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +10206,60878,9729,PRETRIAL,ARMENTEROS,JOVANNY,NULL,Male,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,Copy,1,0 +10206,60878,9729,PRETRIAL,ARMENTEROS,JOVANNY,NULL,Male,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +53788,60886,55278,PRETRIAL,Garcia,Angelica,NULL,Female,Caucasian,03/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +53788,60886,55278,PRETRIAL,Garcia,Angelica,NULL,Female,Caucasian,03/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +53788,60886,55278,PRETRIAL,Garcia,Angelica,NULL,Female,Caucasian,03/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53793,60893,55284,Probation,grocock,peter,NULL,Male,Caucasian,06/17/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +53793,60893,55284,Probation,grocock,peter,NULL,Male,Caucasian,06/17/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +53793,60893,55284,Probation,grocock,peter,NULL,Male,Caucasian,06/17/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53773,60857,55255,PRETRIAL,Green,Cornelius,NULL,Male,African-American,05/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.22,4,Low,New,1,0 +53773,60857,55255,PRETRIAL,Green,Cornelius,NULL,Male,African-American,05/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +53773,60857,55255,PRETRIAL,Green,Cornelius,NULL,Male,African-American,05/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +45706,60872,55268,PRETRIAL,Arnold,John,NULL,Male,Caucasian,11/14/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +45706,60872,55268,PRETRIAL,Arnold,John,NULL,Male,Caucasian,11/14/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +45706,60872,55268,PRETRIAL,Arnold,John,NULL,Male,Caucasian,11/14/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +4584,60860,55258,PRETRIAL,SAMUELS,RICHARD,S,Male,African-American,01/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +4584,60860,55258,PRETRIAL,SAMUELS,RICHARD,S,Male,African-American,01/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +4584,60860,55258,PRETRIAL,SAMUELS,RICHARD,S,Male,African-American,01/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53787,60885,55277,PRETRIAL,Ali,Ayub,NULL,Male,Other,09/29/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/9/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +53787,60885,55277,PRETRIAL,Ali,Ayub,NULL,Male,Other,09/29/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/9/13 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +53787,60885,55277,PRETRIAL,Ali,Ayub,NULL,Male,Other,09/29/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53776,60864,55261,PRETRIAL,Jones,Jarvis,NULL,Male,African-American,03/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +53776,60864,55261,PRETRIAL,Jones,Jarvis,NULL,Male,African-American,03/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +53776,60864,55261,PRETRIAL,Jones,Jarvis,NULL,Male,African-American,03/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53786,60881,55275,Probation,rushetsky,Adam,Scott,Male,Caucasian,06/29/74,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/9/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +53786,60881,55275,Probation,rushetsky,Adam,Scott,Male,Caucasian,06/29/74,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/9/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +53786,60881,55275,Probation,rushetsky,Adam,Scott,Male,Caucasian,06/29/74,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +45420,60855,55253,Probation,peterson,jerald,NULL,Male,African-American,04/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +45420,60855,55253,Probation,peterson,jerald,NULL,Male,African-American,04/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +45420,60855,55253,Probation,peterson,jerald,NULL,Male,African-American,04/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53779,60867,55264,PRETRIAL,Thompson,Colter,Chase,Male,Caucasian,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +53779,60867,55264,PRETRIAL,Thompson,Colter,Chase,Male,Caucasian,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +53779,60867,55264,PRETRIAL,Thompson,Colter,Chase,Male,Caucasian,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53780,60869,55266,PRETRIAL,virgili,sandra,NULL,Female,Hispanic,06/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/9/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +53780,60869,55266,PRETRIAL,virgili,sandra,NULL,Female,Hispanic,06/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/9/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +53780,60869,55266,PRETRIAL,virgili,sandra,NULL,Female,Hispanic,06/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53783,60876,55271,PRETRIAL,sepulveda,robert,NULL,Male,Caucasian,02/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +53783,60876,55271,PRETRIAL,sepulveda,robert,NULL,Male,Caucasian,02/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +53783,60876,55271,PRETRIAL,sepulveda,robert,NULL,Male,Caucasian,02/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +14425,60890,13807,Probation,WARRICK,JACQUELINE,NICOLE,Female,Caucasian,08/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,Copy,1,0 +14425,60890,13807,Probation,WARRICK,JACQUELINE,NICOLE,Female,Caucasian,08/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,Copy,1,0 +14425,60890,13807,Probation,WARRICK,JACQUELINE,NICOLE,Female,Caucasian,08/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +53816,60925,55312,Probation,BAPTISTE,VENESSA,CAROL,Female,African-American,02/23/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/10/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +53816,60925,55312,Probation,BAPTISTE,VENESSA,CAROL,Female,African-American,02/23/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/10/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +53816,60925,55312,Probation,BAPTISTE,VENESSA,CAROL,Female,African-American,02/23/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53800,60904,55294,PRETRIAL,KNOX,KENTRAVIAN,JAMON,Male,African-American,10/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/10/13 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +53800,60904,55294,PRETRIAL,KNOX,KENTRAVIAN,JAMON,Male,African-American,10/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/10/13 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +53800,60904,55294,PRETRIAL,KNOX,KENTRAVIAN,JAMON,Male,African-American,10/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/10/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53804,60911,55300,PRETRIAL,Delgado-Roger,Juan,NULL,Male,Caucasian,04/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +53804,60911,55300,PRETRIAL,Delgado-Roger,Juan,NULL,Male,Caucasian,04/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +53804,60911,55300,PRETRIAL,Delgado-Roger,Juan,NULL,Male,Caucasian,04/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53809,60918,55305,PRETRIAL,BATISTA,CHRISTOPHER,NULL,Male,Hispanic,12/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/10/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +53809,60918,55305,PRETRIAL,BATISTA,CHRISTOPHER,NULL,Male,Hispanic,12/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/10/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +53809,60918,55305,PRETRIAL,BATISTA,CHRISTOPHER,NULL,Male,Hispanic,12/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +44969,60897,55287,PRETRIAL,Agostino,Valerie,NULL,Female,Caucasian,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +44969,60897,55287,PRETRIAL,Agostino,Valerie,NULL,Female,Caucasian,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,4,High,8,Risk of Recidivism,0.94,10,High,New,1,0 +44969,60897,55287,PRETRIAL,Agostino,Valerie,NULL,Female,Caucasian,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,4,High,18,Risk of Failure to Appear,20,4,Low,New,1,0 +19580,60906,39580,PRETRIAL,WASHINGTON,TRAVIS,M,Male,African-American,04/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,Copy,1,0 +19580,60906,39580,PRETRIAL,WASHINGTON,TRAVIS,M,Male,African-American,04/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +19580,60906,39580,PRETRIAL,WASHINGTON,TRAVIS,M,Male,African-American,04/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +53814,60923,55310,PRETRIAL,Santos,Daniele,NULL,Male,Caucasian,04/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +53814,60923,55310,PRETRIAL,Santos,Daniele,NULL,Male,Caucasian,04/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +53814,60923,55310,PRETRIAL,Santos,Daniele,NULL,Male,Caucasian,04/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53798,60902,55292,PRETRIAL,SAUER,JAMES,NULL,Male,Caucasian,11/08/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +53798,60902,55292,PRETRIAL,SAUER,JAMES,NULL,Male,Caucasian,11/08/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +53798,60902,55292,PRETRIAL,SAUER,JAMES,NULL,Male,Caucasian,11/08/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53811,60920,55307,PRETRIAL,Brown,Rapheal,NULL,Male,African-American,11/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/10/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +53811,60920,55307,PRETRIAL,Brown,Rapheal,NULL,Male,African-American,11/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/10/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +53811,60920,55307,PRETRIAL,Brown,Rapheal,NULL,Male,African-American,11/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47388,60927,54865,Probation,guntert,maria,NULL,Female,Hispanic,11/30/81,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/10/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +47388,60927,54865,Probation,guntert,maria,NULL,Female,Hispanic,11/30/81,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/10/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +47388,60927,54865,Probation,guntert,maria,NULL,Female,Hispanic,11/30/81,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53801,60907,55296,PRETRIAL,Curry,Brent,NULL,Male,African-American,10/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +53801,60907,55296,PRETRIAL,Curry,Brent,NULL,Male,African-American,10/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +53801,60907,55296,PRETRIAL,Curry,Brent,NULL,Male,African-American,10/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +9674,60901,55291,PRETRIAL,hansberry,anthony,NULL,Male,African-American,09/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +9674,60901,55291,PRETRIAL,hansberry,anthony,NULL,Male,African-American,09/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +9674,60901,55291,PRETRIAL,hansberry,anthony,NULL,Male,African-American,09/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53797,60899,55289,PRETRIAL,Robinson,Michael,NULL,Male,African-American,11/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +53797,60899,55289,PRETRIAL,Robinson,Michael,NULL,Male,African-American,11/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +53797,60899,55289,PRETRIAL,Robinson,Michael,NULL,Male,African-American,11/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53103,60914,54531,PRETRIAL,GONZALEZ,ANTHONY,NULL,Male,Caucasian,08/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,Copy,1,0 +53103,60914,54531,PRETRIAL,GONZALEZ,ANTHONY,NULL,Male,Caucasian,08/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,Copy,1,0 +53103,60914,54531,PRETRIAL,GONZALEZ,ANTHONY,NULL,Male,Caucasian,08/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +30295,32021,29258,PRETRIAL,WILSON,CHARLES,EARL,Male,African-American,12/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +30295,32021,29258,PRETRIAL,WILSON,CHARLES,EARL,Male,African-American,12/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,4,High,8,Risk of Recidivism,0.16,8,High,New,1,0 +30295,32021,29258,PRETRIAL,WILSON,CHARLES,EARL,Male,African-American,12/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +48433,60909,55298,PRETRIAL,Stewart,Christopher,NULL,Male,African-American,09/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +48433,60909,55298,PRETRIAL,Stewart,Christopher,NULL,Male,African-American,09/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +48433,60909,55298,PRETRIAL,Stewart,Christopher,NULL,Male,African-American,09/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +48272,60896,48952,PRETRIAL,Clayborne,Spencer,NULL,Male,African-American,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,Copy,1,0 +48272,60896,48952,PRETRIAL,Clayborne,Spencer,NULL,Male,African-American,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,Copy,1,0 +48272,60896,48952,PRETRIAL,Clayborne,Spencer,NULL,Male,African-American,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +53808,60917,55304,DRRD,Bodrick,Bobby,NULL,Male,African-American,12/08/91,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,4/10/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +53808,60917,55304,DRRD,Bodrick,Bobby,NULL,Male,African-American,12/08/91,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,4/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +53808,60917,55304,DRRD,Bodrick,Bobby,NULL,Male,African-American,12/08/91,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,4/10/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53815,60924,55311,PRETRIAL,Orbera,Hugo,NULL,Male,Hispanic,04/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +53815,60924,55311,PRETRIAL,Orbera,Hugo,NULL,Male,Hispanic,04/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +53815,60924,55311,PRETRIAL,Orbera,Hugo,NULL,Male,Hispanic,04/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53810,60919,55306,PRETRIAL,ANDERSON,ANTON,DESHAWN,Male,African-American,09/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +53810,60919,55306,PRETRIAL,ANDERSON,ANTON,DESHAWN,Male,African-American,09/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +53810,60919,55306,PRETRIAL,ANDERSON,ANTON,DESHAWN,Male,African-American,09/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +46276,60928,46666,PRETRIAL,STROMAN,ZAIRE,NULL,Male,Hispanic,03/02/94,17,All Scales,Intake,English,Pretrial,Jail Inmate,Married,4/10/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +46276,60928,46666,PRETRIAL,STROMAN,ZAIRE,NULL,Male,Hispanic,03/02/94,17,All Scales,Intake,English,Pretrial,Jail Inmate,Married,4/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.63,3,Low,New,1,0 +46276,60928,46666,PRETRIAL,STROMAN,ZAIRE,NULL,Male,Hispanic,03/02/94,17,All Scales,Intake,English,Pretrial,Jail Inmate,Married,4/10/13 0:00,2,Medium,18,Risk of Failure to Appear,19,2,Low,New,1,0 +53796,60898,55288,PRETRIAL,JIMENEZ,STANLEY,NULL,Male,Caucasian,08/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +53796,60898,55288,PRETRIAL,JIMENEZ,STANLEY,NULL,Male,Caucasian,08/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +53796,60898,55288,PRETRIAL,JIMENEZ,STANLEY,NULL,Male,Caucasian,08/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53806,60915,55302,PRETRIAL,ALCIME,EVELYN,NULL,Male,African-American,11/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +53806,60915,55302,PRETRIAL,ALCIME,EVELYN,NULL,Male,African-American,11/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/13 0:00,4,High,8,Risk of Recidivism,0.43,9,High,New,1,0 +53806,60915,55302,PRETRIAL,ALCIME,EVELYN,NULL,Male,African-American,11/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53799,60903,55293,PRETRIAL,Telfair,Travis,NULL,Male,African-American,03/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +53799,60903,55293,PRETRIAL,Telfair,Travis,NULL,Male,African-American,03/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,4,High,8,Risk of Recidivism,0.38,9,High,New,1,0 +53799,60903,55293,PRETRIAL,Telfair,Travis,NULL,Male,African-American,03/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53803,60910,55299,PRETRIAL,Chavers,Jammie,NULL,Male,African-American,02/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +53803,60910,55299,PRETRIAL,Chavers,Jammie,NULL,Male,African-American,02/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +53803,60910,55299,PRETRIAL,Chavers,Jammie,NULL,Male,African-American,02/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53805,60912,55301,PRETRIAL,ISMAEL,JEAN,JOSIE,Male,African-American,02/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +53805,60912,55301,PRETRIAL,ISMAEL,JEAN,JOSIE,Male,African-American,02/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.67,10,High,New,1,0 +53805,60912,55301,PRETRIAL,ISMAEL,JEAN,JOSIE,Male,African-American,02/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53802,60908,55297,PRETRIAL,ALONSO,LINETTE,MARIA,Female,Caucasian,08/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +53802,60908,55297,PRETRIAL,ALONSO,LINETTE,MARIA,Female,Caucasian,08/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +53802,60908,55297,PRETRIAL,ALONSO,LINETTE,MARIA,Female,Caucasian,08/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53807,60916,55303,Probation,SINGLETARY,CORNELIUS,JAMAL,Male,African-American,02/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +53807,60916,55303,Probation,SINGLETARY,CORNELIUS,JAMAL,Male,African-American,02/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +53807,60916,55303,Probation,SINGLETARY,CORNELIUS,JAMAL,Male,African-American,02/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53812,60921,55308,Probation,RIVERA,JORGE,NULL,Male,Hispanic,10/13/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/10/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +53812,60921,55308,Probation,RIVERA,JORGE,NULL,Male,Hispanic,10/13/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/10/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +53812,60921,55308,Probation,RIVERA,JORGE,NULL,Male,Hispanic,10/13/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53817,60926,55313,Probation,Foght,James,NULL,Male,Caucasian,01/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +53817,60926,55313,Probation,Foght,James,NULL,Male,Caucasian,01/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +53817,60926,55313,Probation,Foght,James,NULL,Male,Caucasian,01/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +35145,60900,55290,PRETRIAL,MCFADDEN,FREDERICK,LEE,Male,African-American,07/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +35145,60900,55290,PRETRIAL,MCFADDEN,FREDERICK,LEE,Male,African-American,07/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +35145,60900,55290,PRETRIAL,MCFADDEN,FREDERICK,LEE,Male,African-American,07/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52799,60913,54208,PRETRIAL,Smith,Indiana,NULL,Male,Caucasian,02/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,Copy,1,0 +52799,60913,54208,PRETRIAL,Smith,Indiana,NULL,Male,Caucasian,02/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,Copy,1,0 +52799,60913,54208,PRETRIAL,Smith,Indiana,NULL,Male,Caucasian,02/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +53795,60895,55286,PRETRIAL,PINZON,SANTIAGO,NULL,Male,Caucasian,07/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +53795,60895,55286,PRETRIAL,PINZON,SANTIAGO,NULL,Male,Caucasian,07/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +53795,60895,55286,PRETRIAL,PINZON,SANTIAGO,NULL,Male,Caucasian,07/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47963,60905,55295,PRETRIAL,Jackson,Michael,Dennis,Male,Other,04/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +47963,60905,55295,PRETRIAL,Jackson,Michael,Dennis,Male,Other,04/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +47963,60905,55295,PRETRIAL,Jackson,Michael,Dennis,Male,Other,04/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53828,60942,55327,PRETRIAL,Saulsby,Tarzan,NULL,Male,African-American,07/27/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/11/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +53828,60942,55327,PRETRIAL,Saulsby,Tarzan,NULL,Male,African-American,07/27/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +53828,60942,55327,PRETRIAL,Saulsby,Tarzan,NULL,Male,African-American,07/27/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53835,60955,55339,PRETRIAL,Martin,James,E,Male,African-American,10/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/11/13 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +53835,60955,55339,PRETRIAL,Martin,James,E,Male,African-American,10/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/11/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +53835,60955,55339,PRETRIAL,Martin,James,E,Male,African-American,10/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/11/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +53847,60973,55355,Probation,Delgado,Misti,NULL,Female,Hispanic,07/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +53847,60973,55355,Probation,Delgado,Misti,NULL,Female,Hispanic,07/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +53847,60973,55355,Probation,Delgado,Misti,NULL,Female,Hispanic,07/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +42409,60934,55319,PRETRIAL,Minor,Herman,NULL,Male,African-American,06/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +42409,60934,55319,PRETRIAL,Minor,Herman,NULL,Male,African-American,06/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,4,High,8,Risk of Recidivism,0.11,8,High,New,1,0 +42409,60934,55319,PRETRIAL,Minor,Herman,NULL,Male,African-American,06/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +31084,60952,52932,PRETRIAL,Greene,James,NULL,Male,African-American,10/01/73,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +31084,60952,52932,PRETRIAL,Greene,James,NULL,Male,African-American,10/01/73,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.31,5,Medium,New,1,0 +31084,60952,52932,PRETRIAL,Greene,James,NULL,Male,African-American,10/01/73,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +48928,60947,55332,PRETRIAL,Gnau,Donald,NULL,Male,Caucasian,04/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +48928,60947,55332,PRETRIAL,Gnau,Donald,NULL,Male,Caucasian,04/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +48928,60947,55332,PRETRIAL,Gnau,Donald,NULL,Male,Caucasian,04/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +42657,60960,55344,PRETRIAL,KHERAJ,SABRINA,LEE,Female,Hispanic,05/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +42657,60960,55344,PRETRIAL,KHERAJ,SABRINA,LEE,Female,Hispanic,05/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +42657,60960,55344,PRETRIAL,KHERAJ,SABRINA,LEE,Female,Hispanic,05/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +34031,60950,55335,PRETRIAL,Kinsey,Michael,NULL,Male,African-American,06/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/11/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +34031,60950,55335,PRETRIAL,Kinsey,Michael,NULL,Male,African-American,06/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +34031,60950,55335,PRETRIAL,Kinsey,Michael,NULL,Male,African-American,06/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53839,60963,55346,Probation,Missiodealmeida,Vinicius,NULL,Male,Other,06/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +53839,60963,55346,Probation,Missiodealmeida,Vinicius,NULL,Male,Other,06/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +53839,60963,55346,Probation,Missiodealmeida,Vinicius,NULL,Male,Other,06/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53824,60937,55322,PRETRIAL,Dobney,Jovanie,NULL,Male,African-American,09/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +53824,60937,55322,PRETRIAL,Dobney,Jovanie,NULL,Male,African-American,09/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +53824,60937,55322,PRETRIAL,Dobney,Jovanie,NULL,Male,African-American,09/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53830,60944,55329,PRETRIAL,Booth,Earl,NULL,Male,Caucasian,10/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +53830,60944,55329,PRETRIAL,Booth,Earl,NULL,Male,Caucasian,10/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +53830,60944,55329,PRETRIAL,Booth,Earl,NULL,Male,Caucasian,10/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53846,60971,55353,Probation,posada,daniel,NULL,Male,Hispanic,01/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,New,1,0 +53846,60971,55353,Probation,posada,daniel,NULL,Male,Hispanic,01/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +53846,60971,55353,Probation,posada,daniel,NULL,Male,Hispanic,01/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +40151,60957,55341,PRETRIAL,Hoffmann,Mandi,NULL,Female,Caucasian,08/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/11/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +40151,60957,55341,PRETRIAL,Hoffmann,Mandi,NULL,Female,Caucasian,08/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +40151,60957,55341,PRETRIAL,Hoffmann,Mandi,NULL,Female,Caucasian,08/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53823,60936,55321,PRETRIAL,Dobney,Jason,Lee,Male,Other,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +53823,60936,55321,PRETRIAL,Dobney,Jason,Lee,Male,Other,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +53823,60936,55321,PRETRIAL,Dobney,Jason,Lee,Male,Other,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53821,60931,55316,PRETRIAL,Talley,Bret,NULL,Male,African-American,08/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +53821,60931,55316,PRETRIAL,Talley,Bret,NULL,Male,African-American,08/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +53821,60931,55316,PRETRIAL,Talley,Bret,NULL,Male,African-American,08/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53822,60933,55318,PRETRIAL,Rohrs,Michael,NULL,Male,Caucasian,02/06/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +53822,60933,55318,PRETRIAL,Rohrs,Michael,NULL,Male,Caucasian,02/06/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +53822,60933,55318,PRETRIAL,Rohrs,Michael,NULL,Male,Caucasian,02/06/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53838,60961,55345,Probation,davidson,tuesday,NULL,Female,Caucasian,09/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.92,2,Low,New,1,0 +53838,60961,55345,Probation,davidson,tuesday,NULL,Female,Caucasian,09/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,10,High,New,1,0 +53838,60961,55345,Probation,davidson,tuesday,NULL,Female,Caucasian,09/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53843,60968,55350,Probation,ARISTIZABAL,LORENA,NULL,Female,Hispanic,06/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +53843,60968,55350,Probation,ARISTIZABAL,LORENA,NULL,Female,Hispanic,06/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +53843,60968,55350,Probation,ARISTIZABAL,LORENA,NULL,Female,Hispanic,06/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53826,60940,55325,PRETRIAL,Jabr,Belal,NULL,Male,Caucasian,02/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +53826,60940,55325,PRETRIAL,Jabr,Belal,NULL,Male,Caucasian,02/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +53826,60940,55325,PRETRIAL,Jabr,Belal,NULL,Male,Caucasian,02/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53849,60975,55357,Probation,LOPEZ,EDWIN,A,Male,Hispanic,02/14/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +53849,60975,55357,Probation,LOPEZ,EDWIN,A,Male,Hispanic,02/14/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +53849,60975,55357,Probation,LOPEZ,EDWIN,A,Male,Hispanic,02/14/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53833,60949,55334,PRETRIAL,CASTANO,GIOVANI,NULL,Male,Caucasian,05/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +53833,60949,55334,PRETRIAL,CASTANO,GIOVANI,NULL,Male,Caucasian,05/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +53833,60949,55334,PRETRIAL,CASTANO,GIOVANI,NULL,Male,Caucasian,05/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +7248,60966,21875,PRETRIAL,Demner,Perer,NULL,Male,Caucasian,05/21/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/11/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,Copy,1,0 +7248,60966,21875,PRETRIAL,Demner,Perer,NULL,Male,Caucasian,05/21/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,Copy,1,0 +7248,60966,21875,PRETRIAL,Demner,Perer,NULL,Male,Caucasian,05/21/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +53831,60945,55330,PRETRIAL,Bucknor,Alexander,NULL,Male,African-American,12/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +53831,60945,55330,PRETRIAL,Bucknor,Alexander,NULL,Male,African-American,12/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +53831,60945,55330,PRETRIAL,Bucknor,Alexander,NULL,Male,African-American,12/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53845,60970,55352,Probation,mieles,melissa,NULL,Female,Hispanic,10/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +53845,60970,55352,Probation,mieles,melissa,NULL,Female,Hispanic,10/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +53845,60970,55352,Probation,mieles,melissa,NULL,Female,Hispanic,10/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53834,60951,55336,Probation,JEFFERSON,TAMEIKA,NULL,Female,African-American,02/25/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +53834,60951,55336,Probation,JEFFERSON,TAMEIKA,NULL,Female,African-American,02/25/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +53834,60951,55336,Probation,JEFFERSON,TAMEIKA,NULL,Female,African-American,02/25/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +53819,60930,55315,PRETRIAL,Lliteras,Teresa,Mary,Female,Caucasian,10/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/11/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +53819,60930,55315,PRETRIAL,Lliteras,Teresa,Mary,Female,Caucasian,10/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/11/13 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +53819,60930,55315,PRETRIAL,Lliteras,Teresa,Mary,Female,Caucasian,10/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53840,60964,55347,Probation,scheick,susan,NULL,Female,Caucasian,11/07/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +53840,60964,55347,Probation,scheick,susan,NULL,Female,Caucasian,11/07/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +53840,60964,55347,Probation,scheick,susan,NULL,Female,Caucasian,11/07/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53837,60959,55343,Probation,Curci,Roger,NULL,Male,Hispanic,10/16/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +53837,60959,55343,Probation,Curci,Roger,NULL,Male,Hispanic,10/16/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +53837,60959,55343,Probation,Curci,Roger,NULL,Male,Hispanic,10/16/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53851,60977,55359,PRETRIAL,Pratt,Tajdrick,NULL,Male,African-American,11/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,4,High,7,Risk of Violence,-0.65,9,High,New,1,0 +53851,60977,55359,PRETRIAL,Pratt,Tajdrick,NULL,Male,African-American,11/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,4,High,8,Risk of Recidivism,0.73,10,High,New,1,0 +53851,60977,55359,PRETRIAL,Pratt,Tajdrick,NULL,Male,African-American,11/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +14331,60938,55323,PRETRIAL,Carbone,Vincent,Jeffrey,Male,Caucasian,10/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +14331,60938,55323,PRETRIAL,Carbone,Vincent,Jeffrey,Male,Caucasian,10/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +14331,60938,55323,PRETRIAL,Carbone,Vincent,Jeffrey,Male,Caucasian,10/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53836,60956,55340,Probation,GALETTE,CLAUDEL,C,Male,African-American,05/15/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +53836,60956,55340,Probation,GALETTE,CLAUDEL,C,Male,African-American,05/15/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +53836,60956,55340,Probation,GALETTE,CLAUDEL,C,Male,African-American,05/15/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +44888,60972,55354,DRRD,Hardin,Leon,NULL,Male,African-American,09/27/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +44888,60972,55354,DRRD,Hardin,Leon,NULL,Male,African-American,09/27/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.63,10,High,New,1,0 +44888,60972,55354,DRRD,Hardin,Leon,NULL,Male,African-American,09/27/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +53829,60943,55328,PRETRIAL,Wagner,Brian,NULL,Male,Caucasian,03/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +53829,60943,55328,PRETRIAL,Wagner,Brian,NULL,Male,Caucasian,03/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +53829,60943,55328,PRETRIAL,Wagner,Brian,NULL,Male,Caucasian,03/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53827,60941,55326,PRETRIAL,Oliphant,John,NULL,Male,African-American,07/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +53827,60941,55326,PRETRIAL,Oliphant,John,NULL,Male,African-American,07/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +53827,60941,55326,PRETRIAL,Oliphant,John,NULL,Male,African-American,07/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53820,60932,55317,PRETRIAL,Mitchell,Tacaris,NULL,Male,African-American,10/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +53820,60932,55317,PRETRIAL,Mitchell,Tacaris,NULL,Male,African-American,10/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.88,10,High,New,1,0 +53820,60932,55317,PRETRIAL,Mitchell,Tacaris,NULL,Male,African-American,10/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +38931,60953,55337,PRETRIAL,GLANCY,CRISTEN,D,Male,Caucasian,11/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +38931,60953,55337,PRETRIAL,GLANCY,CRISTEN,D,Male,Caucasian,11/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +38931,60953,55337,PRETRIAL,GLANCY,CRISTEN,D,Male,Caucasian,11/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51923,60962,53170,Probation,Turturo,Frank,NULL,Male,Caucasian,12/11/54,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,4/11/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +51923,60962,53170,Probation,Turturo,Frank,NULL,Male,Caucasian,12/11/54,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.86,2,Low,New,1,0 +51923,60962,53170,Probation,Turturo,Frank,NULL,Male,Caucasian,12/11/54,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,23,4,Low,New,1,0 +49164,60948,55333,Probation,Smith,Tariq,NULL,Male,African-American,02/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,4,High,7,Risk of Violence,-0.24,10,High,New,1,0 +49164,60948,55333,Probation,Smith,Tariq,NULL,Male,African-American,02/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +49164,60948,55333,Probation,Smith,Tariq,NULL,Male,African-American,02/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53842,60967,55349,Probation,Broussard,Peter,NULL,Male,African-American,03/14/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +53842,60967,55349,Probation,Broussard,Peter,NULL,Male,African-American,03/14/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +53842,60967,55349,Probation,Broussard,Peter,NULL,Male,African-American,03/14/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53832,60946,55331,PRETRIAL,Guyer,Christopher,NULL,Male,African-American,07/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/11/13 0:00,2,Medium,7,Risk of Violence,-2.91,2,Low,New,1,0 +53832,60946,55331,PRETRIAL,Guyer,Christopher,NULL,Male,African-American,07/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +53832,60946,55331,PRETRIAL,Guyer,Christopher,NULL,Male,African-American,07/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/11/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53844,60969,55351,PRETRIAL,Conboy,Christian,NULL,Male,Caucasian,04/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/11/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +53844,60969,55351,PRETRIAL,Conboy,Christian,NULL,Male,Caucasian,04/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/11/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +53844,60969,55351,PRETRIAL,Conboy,Christian,NULL,Male,Caucasian,04/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53850,60976,55358,Probation,foltz,richard,NULL,Male,Caucasian,08/06/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,7,Risk of Violence,-4.19,1,Low,New,1,0 +53850,60976,55358,Probation,foltz,richard,NULL,Male,Caucasian,08/06/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +53850,60976,55358,Probation,foltz,richard,NULL,Male,Caucasian,08/06/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53825,60939,55324,PRETRIAL,Morgan,Arthur,NULL,Male,African-American,01/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +53825,60939,55324,PRETRIAL,Morgan,Arthur,NULL,Male,African-American,01/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +53825,60939,55324,PRETRIAL,Morgan,Arthur,NULL,Male,African-American,01/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53861,60990,55372,PRETRIAL,Coleman,Demetrius,NULL,Male,African-American,11/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +53861,60990,55372,PRETRIAL,Coleman,Demetrius,NULL,Male,African-American,11/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +53861,60990,55372,PRETRIAL,Coleman,Demetrius,NULL,Male,African-American,11/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53872,61004,55386,PRETRIAL,Evans,Donny,NULL,Male,Caucasian,09/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +53872,61004,55386,PRETRIAL,Evans,Donny,NULL,Male,Caucasian,09/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +53872,61004,55386,PRETRIAL,Evans,Donny,NULL,Male,Caucasian,09/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53876,61011,55393,Probation,TORRES,MARTIN,NULL,Male,Hispanic,05/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +53876,61011,55393,Probation,TORRES,MARTIN,NULL,Male,Hispanic,05/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +53876,61011,55393,Probation,TORRES,MARTIN,NULL,Male,Hispanic,05/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53880,61018,55400,PRETRIAL,SHARPE,TASHESHIA,NULL,Female,African-American,07/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,New,1,0 +53880,61018,55400,PRETRIAL,SHARPE,TASHESHIA,NULL,Female,African-American,07/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,7,Medium,New,1,0 +53880,61018,55400,PRETRIAL,SHARPE,TASHESHIA,NULL,Female,African-American,07/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +53866,60997,55379,PRETRIAL,morales,jose,NULL,Male,Hispanic,05/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/12/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +53866,60997,55379,PRETRIAL,morales,jose,NULL,Male,Hispanic,05/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/12/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +53866,60997,55379,PRETRIAL,morales,jose,NULL,Male,Hispanic,05/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +49154,60983,55364,PRETRIAL,BAIN,VERNON,NULL,Male,African-American,03/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +49154,60983,55364,PRETRIAL,BAIN,VERNON,NULL,Male,African-American,03/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +49154,60983,55364,PRETRIAL,BAIN,VERNON,NULL,Male,African-American,03/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53859,60988,55370,PRETRIAL,Tuckus,Stuart,NULL,Male,Caucasian,08/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +53859,60988,55370,PRETRIAL,Tuckus,Stuart,NULL,Male,Caucasian,08/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +53859,60988,55370,PRETRIAL,Tuckus,Stuart,NULL,Male,Caucasian,08/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53862,60992,55374,PRETRIAL,carroll,anthony,NULL,Male,African-American,09/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +53862,60992,55374,PRETRIAL,carroll,anthony,NULL,Male,African-American,09/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +53862,60992,55374,PRETRIAL,carroll,anthony,NULL,Male,African-American,09/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +42202,61009,55391,PRETRIAL,Green,Stephone,Christopher,Male,African-American,01/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +42202,61009,55391,PRETRIAL,Green,Stephone,Christopher,Male,African-American,01/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +42202,61009,55391,PRETRIAL,Green,Stephone,Christopher,Male,African-American,01/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +9395,61013,55395,Probation,camino,eduardo,NULL,Male,Hispanic,11/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/12/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +9395,61013,55395,Probation,camino,eduardo,NULL,Male,Hispanic,11/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/12/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +9395,61013,55395,Probation,camino,eduardo,NULL,Male,Hispanic,11/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53863,60993,55375,PRETRIAL,Richards,Juvuan,NULL,Male,African-American,06/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +53863,60993,55375,PRETRIAL,Richards,Juvuan,NULL,Male,African-American,06/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +53863,60993,55375,PRETRIAL,Richards,Juvuan,NULL,Male,African-American,06/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53875,61008,55390,PRETRIAL,Myers,Bruce,e,Male,Caucasian,08/23/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +53875,61008,55390,PRETRIAL,Myers,Bruce,e,Male,Caucasian,08/23/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +53875,61008,55390,PRETRIAL,Myers,Bruce,e,Male,Caucasian,08/23/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +53883,61022,55404,PRETRIAL,Gelidon,Dennis,NULL,Male,Caucasian,07/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +53883,61022,55404,PRETRIAL,Gelidon,Dennis,NULL,Male,Caucasian,07/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +53883,61022,55404,PRETRIAL,Gelidon,Dennis,NULL,Male,Caucasian,07/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53853,60980,55361,PRETRIAL,Cox,Rainer,NULL,Male,African-American,07/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +53853,60980,55361,PRETRIAL,Cox,Rainer,NULL,Male,African-American,07/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +53853,60980,55361,PRETRIAL,Cox,Rainer,NULL,Male,African-American,07/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +47837,61014,55396,Probation,DANON,BEN,NULL,Male,Caucasian,04/12/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +47837,61014,55396,Probation,DANON,BEN,NULL,Male,Caucasian,04/12/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +47837,61014,55396,Probation,DANON,BEN,NULL,Male,Caucasian,04/12/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53879,61016,55398,Probation,CASTELLON,ANTHONY,NULL,Male,Caucasian,10/31/93,22,Risk and Prescreen,Intake,English,Post Sentence,Parole,Single,4/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +53879,61016,55398,Probation,CASTELLON,ANTHONY,NULL,Male,Caucasian,10/31/93,22,Risk and Prescreen,Intake,English,Post Sentence,Parole,Single,4/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.66,10,High,New,1,0 +53879,61016,55398,Probation,CASTELLON,ANTHONY,NULL,Male,Caucasian,10/31/93,22,Risk and Prescreen,Intake,English,Post Sentence,Parole,Single,4/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53873,61006,55388,Probation,castello,john,NULL,Male,Caucasian,03/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +53873,61006,55388,Probation,castello,john,NULL,Male,Caucasian,03/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +53873,61006,55388,Probation,castello,john,NULL,Male,Caucasian,03/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53867,60998,55380,PRETRIAL,Charles,King,Clyde,Male,African-American,05/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +53867,60998,55380,PRETRIAL,Charles,King,Clyde,Male,African-American,05/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +53867,60998,55380,PRETRIAL,Charles,King,Clyde,Male,African-American,05/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53856,60985,55366,PRETRIAL,Daley,Joann,NULL,Female,Caucasian,10/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +53856,60985,55366,PRETRIAL,Daley,Joann,NULL,Female,Caucasian,10/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +53856,60985,55366,PRETRIAL,Daley,Joann,NULL,Female,Caucasian,10/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53881,61019,55401,PRETRIAL,MCCARTHY,JUSTIN,NULL,Male,Caucasian,01/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +53881,61019,55401,PRETRIAL,MCCARTHY,JUSTIN,NULL,Male,Caucasian,01/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +53881,61019,55401,PRETRIAL,MCCARTHY,JUSTIN,NULL,Male,Caucasian,01/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53855,60984,55365,PRETRIAL,Rolle,Aaron,Christopher,Male,African-American,09/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +53855,60984,55365,PRETRIAL,Rolle,Aaron,Christopher,Male,African-American,09/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +53855,60984,55365,PRETRIAL,Rolle,Aaron,Christopher,Male,African-American,09/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51517,60991,55373,PRETRIAL,hamilton,gabrielle,NULL,Female,Caucasian,08/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +51517,60991,55373,PRETRIAL,hamilton,gabrielle,NULL,Female,Caucasian,08/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +51517,60991,55373,PRETRIAL,hamilton,gabrielle,NULL,Female,Caucasian,08/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +44331,61000,55382,PRETRIAL,Clouse,Ronald,NULL,Male,Caucasian,05/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +44331,61000,55382,PRETRIAL,Clouse,Ronald,NULL,Male,Caucasian,05/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +44331,61000,55382,PRETRIAL,Clouse,Ronald,NULL,Male,Caucasian,05/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +41027,61017,55399,PRETRIAL,RICHARDSON,COOLITO,NULL,Male,African-American,09/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,4,High,7,Risk of Violence,-0.67,9,High,New,1,0 +41027,61017,55399,PRETRIAL,RICHARDSON,COOLITO,NULL,Male,African-American,09/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,4,High,8,Risk of Recidivism,0.47,9,High,New,1,0 +41027,61017,55399,PRETRIAL,RICHARDSON,COOLITO,NULL,Male,African-American,09/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53858,60987,55368,PRETRIAL,Demus,Paul,Andrey,Male,Caucasian,03/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +53858,60987,55368,PRETRIAL,Demus,Paul,Andrey,Male,Caucasian,03/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +53858,60987,55368,PRETRIAL,Demus,Paul,Andrey,Male,Caucasian,03/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53865,60996,55378,Probation,RAMOS,JOSE,MANUEL,Male,Hispanic,10/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +53865,60996,55378,Probation,RAMOS,JOSE,MANUEL,Male,Hispanic,10/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +53865,60996,55378,Probation,RAMOS,JOSE,MANUEL,Male,Hispanic,10/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +46713,61021,55403,PRETRIAL,Parker,Rachard,NULL,Male,African-American,09/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +46713,61021,55403,PRETRIAL,Parker,Rachard,NULL,Male,African-American,09/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +46713,61021,55403,PRETRIAL,Parker,Rachard,NULL,Male,African-American,09/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53860,60989,55371,PRETRIAL,Joseph,Auguste,NULL,Male,African-American,08/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +53860,60989,55371,PRETRIAL,Joseph,Auguste,NULL,Male,African-American,08/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.78,10,High,New,1,0 +53860,60989,55371,PRETRIAL,Joseph,Auguste,NULL,Male,African-American,08/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +42708,60982,55363,PRETRIAL,RODRIGUEZ,EMIGDIO,NULL,Male,Caucasian,02/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +42708,60982,55363,PRETRIAL,RODRIGUEZ,EMIGDIO,NULL,Male,Caucasian,02/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +42708,60982,55363,PRETRIAL,RODRIGUEZ,EMIGDIO,NULL,Male,Caucasian,02/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53871,61003,55385,Probation,grantham,jeremiah,NULL,Male,Caucasian,01/16/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +53871,61003,55385,Probation,grantham,jeremiah,NULL,Male,Caucasian,01/16/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +53871,61003,55385,Probation,grantham,jeremiah,NULL,Male,Caucasian,01/16/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53877,61012,55394,PRETRIAL,COSMAN,TIMOTHY,NULL,Male,Caucasian,01/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +53877,61012,55394,PRETRIAL,COSMAN,TIMOTHY,NULL,Male,Caucasian,01/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +53877,61012,55394,PRETRIAL,COSMAN,TIMOTHY,NULL,Male,Caucasian,01/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53852,60979,55360,PRETRIAL,Midence,Marcos,NULL,Male,Hispanic,11/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +53852,60979,55360,PRETRIAL,Midence,Marcos,NULL,Male,Hispanic,11/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +53852,60979,55360,PRETRIAL,Midence,Marcos,NULL,Male,Hispanic,11/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53857,60986,55367,PRETRIAL,Bozman,Zarian,NULL,Male,African-American,09/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +53857,60986,55367,PRETRIAL,Bozman,Zarian,NULL,Male,African-American,09/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +53857,60986,55367,PRETRIAL,Bozman,Zarian,NULL,Male,African-American,09/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53874,61007,55389,Probation,BOYER,CATIE,NICOLE,Female,Caucasian,06/30/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +53874,61007,55389,Probation,BOYER,CATIE,NICOLE,Female,Caucasian,06/30/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,9,High,New,1,0 +53874,61007,55389,Probation,BOYER,CATIE,NICOLE,Female,Caucasian,06/30/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +32759,60978,31809,PRETRIAL,SMITH,GIDEON,NULL,Male,African-American,02/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,Copy,1,0 +32759,60978,31809,PRETRIAL,SMITH,GIDEON,NULL,Male,African-American,02/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,Copy,1,0 +32759,60978,31809,PRETRIAL,SMITH,GIDEON,NULL,Male,African-American,02/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +53868,60999,55381,PRETRIAL,hurtado,david,NULL,Male,Caucasian,05/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/12/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +53868,60999,55381,PRETRIAL,hurtado,david,NULL,Male,Caucasian,05/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/12/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +53868,60999,55381,PRETRIAL,hurtado,david,NULL,Male,Caucasian,05/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53864,60994,55376,PRETRIAL,Centurion,Ricardo,NULL,Male,Hispanic,11/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/12/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +53864,60994,55376,PRETRIAL,Centurion,Ricardo,NULL,Male,Hispanic,11/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/12/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +53864,60994,55376,PRETRIAL,Centurion,Ricardo,NULL,Male,Hispanic,11/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53854,60981,55362,PRETRIAL,Williams,James,Warren,Male,Caucasian,12/18/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +53854,60981,55362,PRETRIAL,Williams,James,Warren,Male,Caucasian,12/18/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +53854,60981,55362,PRETRIAL,Williams,James,Warren,Male,Caucasian,12/18/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53878,61015,55397,PRETRIAL,Bergeron,Kayla,NULL,Female,Caucasian,11/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +53878,61015,55397,PRETRIAL,Bergeron,Kayla,NULL,Female,Caucasian,11/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +53878,61015,55397,PRETRIAL,Bergeron,Kayla,NULL,Female,Caucasian,11/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53870,61002,55384,Probation,GRAIBE,MARC,ALEXANDER,Male,Hispanic,08/15/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +53870,61002,55384,Probation,GRAIBE,MARC,ALEXANDER,Male,Hispanic,08/15/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +53870,61002,55384,Probation,GRAIBE,MARC,ALEXANDER,Male,Hispanic,08/15/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/12/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53882,61020,55402,PRETRIAL,Watson,Ervin,NULL,Male,African-American,02/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +53882,61020,55402,PRETRIAL,Watson,Ervin,NULL,Male,African-American,02/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +53882,61020,55402,PRETRIAL,Watson,Ervin,NULL,Male,African-American,02/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53884,61023,55405,PRETRIAL,Benn,Trevor,NULL,Male,Caucasian,04/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +53884,61023,55405,PRETRIAL,Benn,Trevor,NULL,Male,Caucasian,04/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +53884,61023,55405,PRETRIAL,Benn,Trevor,NULL,Male,Caucasian,04/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +53898,61041,55420,PRETRIAL,Mickens,Megan,NULL,Male,African-American,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,New,1,0 +53898,61041,55420,PRETRIAL,Mickens,Megan,NULL,Male,African-American,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +53898,61041,55420,PRETRIAL,Mickens,Megan,NULL,Male,African-American,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53888,61028,55410,PRETRIAL,Hayas,Rafael,NULL,Male,Hispanic,10/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +53888,61028,55410,PRETRIAL,Hayas,Rafael,NULL,Male,Hispanic,10/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +53888,61028,55410,PRETRIAL,Hayas,Rafael,NULL,Male,Hispanic,10/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53895,61036,55417,PRETRIAL,Barnett,Sheleike,Roxan,Female,African-American,04/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/13/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +53895,61036,55417,PRETRIAL,Barnett,Sheleike,Roxan,Female,African-American,04/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/13/13 0:00,1,Low,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +53895,61036,55417,PRETRIAL,Barnett,Sheleike,Roxan,Female,African-American,04/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53890,61031,55413,PRETRIAL,Green,Vincent,NULL,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +53890,61031,55413,PRETRIAL,Green,Vincent,NULL,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +53890,61031,55413,PRETRIAL,Green,Vincent,NULL,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53893,61033,55415,PRETRIAL,Ayala,Pedro,NULL,Male,Hispanic,03/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,4,High,7,Risk of Violence,-0.52,10,High,New,1,0 +53893,61033,55415,PRETRIAL,Ayala,Pedro,NULL,Male,Hispanic,03/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,4,High,8,Risk of Recidivism,0.87,10,High,New,1,0 +53893,61033,55415,PRETRIAL,Ayala,Pedro,NULL,Male,Hispanic,03/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53897,61040,55419,PRETRIAL,Mitchell,Eric,NULL,Male,African-American,11/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +53897,61040,55419,PRETRIAL,Mitchell,Eric,NULL,Male,African-American,11/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +53897,61040,55419,PRETRIAL,Mitchell,Eric,NULL,Male,African-American,11/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53886,61026,55408,PRETRIAL,FERNANDEZ,DIEGO,NULL,Male,Caucasian,01/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +53886,61026,55408,PRETRIAL,FERNANDEZ,DIEGO,NULL,Male,Caucasian,01/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +53886,61026,55408,PRETRIAL,FERNANDEZ,DIEGO,NULL,Male,Caucasian,01/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53896,61038,55418,PRETRIAL,WILSON,DARRON,NULL,Male,African-American,09/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/13/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +53896,61038,55418,PRETRIAL,WILSON,DARRON,NULL,Male,African-American,09/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/13/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +53896,61038,55418,PRETRIAL,WILSON,DARRON,NULL,Male,African-American,09/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53892,61032,55414,PRETRIAL,Bryant,Michael,NULL,Male,African-American,07/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +53892,61032,55414,PRETRIAL,Bryant,Michael,NULL,Male,African-American,07/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +53892,61032,55414,PRETRIAL,Bryant,Michael,NULL,Male,African-American,07/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50698,61024,55406,PRETRIAL,Smith,Deandre,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +50698,61024,55406,PRETRIAL,Smith,Deandre,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +50698,61024,55406,PRETRIAL,Smith,Deandre,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53887,61027,55409,PRETRIAL,MILLS,JASON,COLE,Male,Caucasian,05/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/13/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +53887,61027,55409,PRETRIAL,MILLS,JASON,COLE,Male,Caucasian,05/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/13/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +53887,61027,55409,PRETRIAL,MILLS,JASON,COLE,Male,Caucasian,05/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +11081,61035,10598,PRETRIAL,SMITH,ZAVIAUS,LEARTIS,Male,African-American,07/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +11081,61035,10598,PRETRIAL,SMITH,ZAVIAUS,LEARTIS,Male,African-American,07/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,5,Medium,Copy,1,0 +11081,61035,10598,PRETRIAL,SMITH,ZAVIAUS,LEARTIS,Male,African-American,07/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +50308,61037,54373,PRETRIAL,Wilson,Kadeem,NULL,Male,African-American,09/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,7,Risk of Violence,-1.26,7,Medium,Copy,1,0 +50308,61037,54373,PRETRIAL,Wilson,Kadeem,NULL,Male,African-American,09/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,Copy,1,0 +50308,61037,54373,PRETRIAL,Wilson,Kadeem,NULL,Male,African-American,09/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +7761,61029,55411,PRETRIAL,KLOMAN,ANGELINA,NULL,Female,Caucasian,11/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +7761,61029,55411,PRETRIAL,KLOMAN,ANGELINA,NULL,Female,Caucasian,11/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +7761,61029,55411,PRETRIAL,KLOMAN,ANGELINA,NULL,Female,Caucasian,11/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53894,61034,55416,PRETRIAL,Clarke,Keontrae,NULL,Female,African-American,08/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,4,High,7,Risk of Violence,-0.85,9,High,New,1,0 +53894,61034,55416,PRETRIAL,Clarke,Keontrae,NULL,Female,African-American,08/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,4,High,8,Risk of Recidivism,0.47,10,High,New,1,0 +53894,61034,55416,PRETRIAL,Clarke,Keontrae,NULL,Female,African-American,08/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53889,61030,55412,PRETRIAL,Celestin,Desta,NULL,Male,African-American,11/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +53889,61030,55412,PRETRIAL,Celestin,Desta,NULL,Male,African-American,11/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +53889,61030,55412,PRETRIAL,Celestin,Desta,NULL,Male,African-American,11/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53885,61025,55407,PRETRIAL,MCGHIE,CHRISTOPHER,JAMES,Male,Caucasian,02/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +53885,61025,55407,PRETRIAL,MCGHIE,CHRISTOPHER,JAMES,Male,Caucasian,02/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +53885,61025,55407,PRETRIAL,MCGHIE,CHRISTOPHER,JAMES,Male,Caucasian,02/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +41934,61039,45197,PRETRIAL,Ruiz,Miguel,NULL,Male,Hispanic,09/04/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,Copy,1,0 +41934,61039,45197,PRETRIAL,Ruiz,Miguel,NULL,Male,Hispanic,09/04/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,Copy,1,0 +41934,61039,45197,PRETRIAL,Ruiz,Miguel,NULL,Male,Hispanic,09/04/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +11449,61048,10974,PRETRIAL,bunn,george,NULL,Male,African-American,03/15/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/14/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,Copy,1,0 +11449,61048,10974,PRETRIAL,bunn,george,NULL,Male,African-American,03/15/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/14/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,Copy,1,0 +11449,61048,10974,PRETRIAL,bunn,george,NULL,Male,African-American,03/15/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +2305,61046,55425,PRETRIAL,MITCHELL,EDDIE,WILLIE,Male,African-American,08/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +2305,61046,55425,PRETRIAL,MITCHELL,EDDIE,WILLIE,Male,African-American,08/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,4,High,8,Risk of Recidivism,0.45,9,High,New,1,0 +2305,61046,55425,PRETRIAL,MITCHELL,EDDIE,WILLIE,Male,African-American,08/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53905,61051,55429,PRETRIAL,EDWARDS,TESA,NULL,Female,African-American,11/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +53905,61051,55429,PRETRIAL,EDWARDS,TESA,NULL,Female,African-American,11/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +53905,61051,55429,PRETRIAL,EDWARDS,TESA,NULL,Female,African-American,11/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53911,61060,55435,PRETRIAL,Daley,Leonard,NULL,Male,African-American,09/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +53911,61060,55435,PRETRIAL,Daley,Leonard,NULL,Male,African-American,09/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +53911,61060,55435,PRETRIAL,Daley,Leonard,NULL,Male,African-American,09/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +42487,61055,42312,Probation,murrell,sondra,NULL,Female,African-American,09/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,Copy,1,0 +42487,61055,42312,Probation,murrell,sondra,NULL,Female,African-American,09/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,Copy,1,0 +42487,61055,42312,Probation,murrell,sondra,NULL,Female,African-American,09/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +53899,61043,55422,PRETRIAL,SAGADO,JOSHUA,NULL,Male,Caucasian,02/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +53899,61043,55422,PRETRIAL,SAGADO,JOSHUA,NULL,Male,Caucasian,02/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +53899,61043,55422,PRETRIAL,SAGADO,JOSHUA,NULL,Male,Caucasian,02/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +36003,61058,35239,PRETRIAL,Cox,Trevor,NULL,Male,Caucasian,12/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/14/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,Copy,1,0 +36003,61058,35239,PRETRIAL,Cox,Trevor,NULL,Male,Caucasian,12/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/14/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,Copy,1,0 +36003,61058,35239,PRETRIAL,Cox,Trevor,NULL,Male,Caucasian,12/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +53904,61050,55428,PRETRIAL,Herrera,Justin,NULL,Male,Hispanic,08/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +53904,61050,55428,PRETRIAL,Herrera,Justin,NULL,Male,Hispanic,08/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +53904,61050,55428,PRETRIAL,Herrera,Justin,NULL,Male,Hispanic,08/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53901,61045,55424,PRETRIAL,Rodgers,Adam,NULL,Male,Caucasian,02/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +53901,61045,55424,PRETRIAL,Rodgers,Adam,NULL,Male,Caucasian,02/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +53901,61045,55424,PRETRIAL,Rodgers,Adam,NULL,Male,Caucasian,02/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53907,61053,55431,PRETRIAL,PAREJA,JOSE,NULL,Male,Caucasian,10/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +53907,61053,55431,PRETRIAL,PAREJA,JOSE,NULL,Male,Caucasian,10/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +53907,61053,55431,PRETRIAL,PAREJA,JOSE,NULL,Male,Caucasian,10/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53906,61052,55430,PRETRIAL,Saleh,Nasser,NULL,Male,African-American,08/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +53906,61052,55430,PRETRIAL,Saleh,Nasser,NULL,Male,African-American,08/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +53906,61052,55430,PRETRIAL,Saleh,Nasser,NULL,Male,African-American,08/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53910,61059,55434,PRETRIAL,wilson,Brian,NULL,Male,Caucasian,01/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/14/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +53910,61059,55434,PRETRIAL,wilson,Brian,NULL,Male,Caucasian,01/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/14/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +53910,61059,55434,PRETRIAL,wilson,Brian,NULL,Male,Caucasian,01/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +38864,61042,55421,PRETRIAL,Philo,Ed,NULL,Male,African-American,05/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +38864,61042,55421,PRETRIAL,Philo,Ed,NULL,Male,African-American,05/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +38864,61042,55421,PRETRIAL,Philo,Ed,NULL,Male,African-American,05/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53909,61056,55433,PRETRIAL,TAMAREZ,CLAUDIO,NULL,Male,Caucasian,02/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +53909,61056,55433,PRETRIAL,TAMAREZ,CLAUDIO,NULL,Male,Caucasian,02/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +53909,61056,55433,PRETRIAL,TAMAREZ,CLAUDIO,NULL,Male,Caucasian,02/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53902,61047,55426,PRETRIAL,Douse,Jarone,NULL,Male,African-American,10/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,2,Medium,7,Risk of Violence,-2.99,1,Low,New,1,0 +53902,61047,55426,PRETRIAL,Douse,Jarone,NULL,Male,African-American,10/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +53902,61047,55426,PRETRIAL,Douse,Jarone,NULL,Male,African-American,10/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53908,61054,55432,PRETRIAL,Zurz,Lavinel,NULL,Male,Caucasian,06/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +53908,61054,55432,PRETRIAL,Zurz,Lavinel,NULL,Male,Caucasian,06/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +53908,61054,55432,PRETRIAL,Zurz,Lavinel,NULL,Male,Caucasian,06/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53912,61061,55436,PRETRIAL,Garrish,Terry,Lee,Male,Caucasian,10/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +53912,61061,55436,PRETRIAL,Garrish,Terry,Lee,Male,Caucasian,10/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +53912,61061,55436,PRETRIAL,Garrish,Terry,Lee,Male,Caucasian,10/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +18100,61057,53147,PRETRIAL,CRESPO,FREDDY,ANTONIO,Male,African-American,11/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,4,High,7,Risk of Violence,-0.6,10,High,Copy,1,0 +18100,61057,53147,PRETRIAL,CRESPO,FREDDY,ANTONIO,Male,African-American,11/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,4,High,8,Risk of Recidivism,0.97,10,High,Copy,1,0 +18100,61057,53147,PRETRIAL,CRESPO,FREDDY,ANTONIO,Male,African-American,11/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +53900,61044,55423,PRETRIAL,LAURENT,PHYLLIS,VERA,Female,African-American,05/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +53900,61044,55423,PRETRIAL,LAURENT,PHYLLIS,VERA,Female,African-American,05/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +53900,61044,55423,PRETRIAL,LAURENT,PHYLLIS,VERA,Female,African-American,05/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53903,61049,55427,PRETRIAL,ABRAHAM,HOWELL,NULL,Male,African-American,02/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +53903,61049,55427,PRETRIAL,ABRAHAM,HOWELL,NULL,Male,African-American,02/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +53903,61049,55427,PRETRIAL,ABRAHAM,HOWELL,NULL,Male,African-American,02/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52078,61083,53338,PRETRIAL,Judy,Taylor,A,Female,Caucasian,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,Copy,1,0 +52078,61083,53338,PRETRIAL,Judy,Taylor,A,Female,Caucasian,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,10,High,Copy,1,0 +52078,61083,53338,PRETRIAL,Judy,Taylor,A,Female,Caucasian,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +53913,61062,55437,PRETRIAL,Running,Rodger,Hall,Male,Caucasian,12/08/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/15/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +53913,61062,55437,PRETRIAL,Running,Rodger,Hall,Male,Caucasian,12/08/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +53913,61062,55437,PRETRIAL,Running,Rodger,Hall,Male,Caucasian,12/08/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53940,61096,55466,Probation,Mendez,Ricardo,NULL,Male,Hispanic,05/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +53940,61096,55466,Probation,Mendez,Ricardo,NULL,Male,Hispanic,05/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +53940,61096,55466,Probation,Mendez,Ricardo,NULL,Male,Hispanic,05/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53937,61091,55462,Probation,EUBANKS,RODNEY,CARL,Male,African-American,10/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +53937,61091,55462,Probation,EUBANKS,RODNEY,CARL,Male,African-American,10/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +53937,61091,55462,Probation,EUBANKS,RODNEY,CARL,Male,African-American,10/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +53949,61109,55478,Probation,Keel,Matthew,NULL,Male,Caucasian,11/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +53949,61109,55478,Probation,Keel,Matthew,NULL,Male,Caucasian,11/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +53949,61109,55478,Probation,Keel,Matthew,NULL,Male,Caucasian,11/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53920,61070,55445,PRETRIAL,Higgins,Nicholas,Claude,Male,Caucasian,05/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +53920,61070,55445,PRETRIAL,Higgins,Nicholas,Claude,Male,Caucasian,05/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +53920,61070,55445,PRETRIAL,Higgins,Nicholas,Claude,Male,Caucasian,05/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +53925,61078,55452,PRETRIAL,RENSHAW,ANDREW,NULL,Male,Caucasian,12/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +53925,61078,55452,PRETRIAL,RENSHAW,ANDREW,NULL,Male,Caucasian,12/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +53925,61078,55452,PRETRIAL,RENSHAW,ANDREW,NULL,Male,Caucasian,12/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53942,61101,55470,PRETRIAL,Avila,Jose,NULL,Male,Hispanic,07/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/13 0:00,2,Medium,7,Risk of Violence,-2.63,2,Low,New,1,0 +53942,61101,55470,PRETRIAL,Avila,Jose,NULL,Male,Hispanic,07/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +53942,61101,55470,PRETRIAL,Avila,Jose,NULL,Male,Hispanic,07/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +7023,61065,55440,PRETRIAL,WRIGHT,JEFFERY,NULL,Male,Caucasian,05/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/15/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +7023,61065,55440,PRETRIAL,WRIGHT,JEFFERY,NULL,Male,Caucasian,05/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/15/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +7023,61065,55440,PRETRIAL,WRIGHT,JEFFERY,NULL,Male,Caucasian,05/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53928,61080,55454,PRETRIAL,Burgess,Michael,NULL,Male,Caucasian,03/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +53928,61080,55454,PRETRIAL,Burgess,Michael,NULL,Male,Caucasian,03/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/13 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +53928,61080,55454,PRETRIAL,Burgess,Michael,NULL,Male,Caucasian,03/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +37866,61099,55468,PRETRIAL,RANDELL,MARQUIVES,NULL,Male,African-American,11/22/93,17,All Scales,Intake,English,Post Sentence,Residential Program,Single,4/15/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +37866,61099,55468,PRETRIAL,RANDELL,MARQUIVES,NULL,Male,African-American,11/22/93,17,All Scales,Intake,English,Post Sentence,Residential Program,Single,4/15/13 0:00,4,High,8,Risk of Recidivism,0.28,8,High,New,1,0 +37866,61099,55468,PRETRIAL,RANDELL,MARQUIVES,NULL,Male,African-American,11/22/93,17,All Scales,Intake,English,Post Sentence,Residential Program,Single,4/15/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53953,61114,55483,Probation,Feliciano,Thomas,NULL,Male,Caucasian,07/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.6,2,Low,New,1,0 +53953,61114,55483,Probation,Feliciano,Thomas,NULL,Male,Caucasian,07/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +53953,61114,55483,Probation,Feliciano,Thomas,NULL,Male,Caucasian,07/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53921,61072,55447,PRETRIAL,WIGGINS,MICHAEL,TRAVONN,Male,African-American,06/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/15/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +53921,61072,55447,PRETRIAL,WIGGINS,MICHAEL,TRAVONN,Male,African-American,06/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +53921,61072,55447,PRETRIAL,WIGGINS,MICHAEL,TRAVONN,Male,African-American,06/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53947,61107,55476,PRETRIAL,Murphy,Deanna,NULL,Female,Caucasian,11/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/15/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +53947,61107,55476,PRETRIAL,Murphy,Deanna,NULL,Female,Caucasian,11/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/15/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +53947,61107,55476,PRETRIAL,Murphy,Deanna,NULL,Female,Caucasian,11/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53938,61093,55464,Probation,charlton,gordon,NULL,Male,Caucasian,11/04/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/15/13 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +53938,61093,55464,Probation,charlton,gordon,NULL,Male,Caucasian,11/04/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +53938,61093,55464,Probation,charlton,gordon,NULL,Male,Caucasian,11/04/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53917,61068,55443,PRETRIAL,Rosario,Joan,NULL,Male,Hispanic,08/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +53917,61068,55443,PRETRIAL,Rosario,Joan,NULL,Male,Hispanic,08/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +53917,61068,55443,PRETRIAL,Rosario,Joan,NULL,Male,Hispanic,08/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +46830,61075,47281,PRETRIAL,Angella,Louis,NULL,Male,Caucasian,06/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +46830,61075,47281,PRETRIAL,Angella,Louis,NULL,Male,Caucasian,06/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,Copy,1,0 +46830,61075,47281,PRETRIAL,Angella,Louis,NULL,Male,Caucasian,06/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +53934,61089,55461,PRETRIAL,Cecere,Vincent,NULL,Male,Caucasian,07/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,4/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +53934,61089,55461,PRETRIAL,Cecere,Vincent,NULL,Male,Caucasian,07/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,4/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +53934,61089,55461,PRETRIAL,Cecere,Vincent,NULL,Male,Caucasian,07/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,4/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +53930,61082,55456,PRETRIAL,walsh,kevin,NULL,Male,Caucasian,06/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +53930,61082,55456,PRETRIAL,walsh,kevin,NULL,Male,Caucasian,06/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +53930,61082,55456,PRETRIAL,walsh,kevin,NULL,Male,Caucasian,06/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53944,61103,55472,Probation,Skoreparodriguez,Jose,NULL,Male,Hispanic,07/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +53944,61103,55472,Probation,Skoreparodriguez,Jose,NULL,Male,Hispanic,07/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +53944,61103,55472,Probation,Skoreparodriguez,Jose,NULL,Male,Hispanic,07/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +43542,61112,55481,PRETRIAL,Polcha,Stephen,NULL,Male,Caucasian,08/17/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/15/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +43542,61112,55481,PRETRIAL,Polcha,Stephen,NULL,Male,Caucasian,08/17/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/15/13 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +43542,61112,55481,PRETRIAL,Polcha,Stephen,NULL,Male,Caucasian,08/17/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53954,61115,55484,Probation,VANSTONE,ROBERT,DREW,Male,Caucasian,11/27/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +53954,61115,55484,Probation,VANSTONE,ROBERT,DREW,Male,Caucasian,11/27/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +53954,61115,55484,Probation,VANSTONE,ROBERT,DREW,Male,Caucasian,11/27/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53094,61094,54514,Probation,Malone,Robert,NULL,Male,Caucasian,09/27/69,17,All Scales,Intake,English,Post Sentence,Probation,Married,4/15/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +53094,61094,54514,Probation,Malone,Robert,NULL,Male,Caucasian,09/27/69,17,All Scales,Intake,English,Post Sentence,Probation,Married,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +53094,61094,54514,Probation,Malone,Robert,NULL,Male,Caucasian,09/27/69,17,All Scales,Intake,English,Post Sentence,Probation,Married,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,2,Low,New,1,0 +29358,61119,55488,PRETRIAL,ROYES,BRADLEY,DANARO,Male,African-American,12/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.67,2,Low,New,1,0 +29358,61119,55488,PRETRIAL,ROYES,BRADLEY,DANARO,Male,African-American,12/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +29358,61119,55488,PRETRIAL,ROYES,BRADLEY,DANARO,Male,African-American,12/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53922,61073,55448,PRETRIAL,WIGGS,JENNIFER,DENISE,Female,African-American,08/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +53922,61073,55448,PRETRIAL,WIGGS,JENNIFER,DENISE,Female,African-American,08/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +53922,61073,55448,PRETRIAL,WIGGS,JENNIFER,DENISE,Female,African-American,08/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53926,61077,55451,PRETRIAL,Tarin,Woodson,NULL,Male,Other,03/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/15/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +53926,61077,55451,PRETRIAL,Tarin,Woodson,NULL,Male,Other,03/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +53926,61077,55451,PRETRIAL,Tarin,Woodson,NULL,Male,Other,03/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +4549,61066,55441,Probation,Kerwit,Richard,D,Male,Caucasian,01/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,2,Medium,7,Risk of Violence,-1.27,7,Medium,New,1,0 +4549,61066,55441,Probation,Kerwit,Richard,D,Male,Caucasian,01/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +4549,61066,55441,Probation,Kerwit,Richard,D,Male,Caucasian,01/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,2,Medium,18,Risk of Failure to Appear,37,10,High,New,1,0 +53933,61100,55469,Probation,Margarito,Jose,NULL,Male,Hispanic,06/17/69,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Married,4/15/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +53933,61100,55469,Probation,Margarito,Jose,NULL,Male,Hispanic,06/17/69,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Married,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +53933,61100,55469,Probation,Margarito,Jose,NULL,Male,Hispanic,06/17/69,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Married,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53939,61095,55465,Probation,Anderson,Jaime,Danielle,Female,Caucasian,04/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +53939,61095,55465,Probation,Anderson,Jaime,Danielle,Female,Caucasian,04/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +53939,61095,55465,Probation,Anderson,Jaime,Danielle,Female,Caucasian,04/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53923,61074,55449,PRETRIAL,St Jean,Wesley,NULL,Male,African-American,09/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.01,4,Low,New,1,0 +53923,61074,55449,PRETRIAL,St Jean,Wesley,NULL,Male,African-American,09/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.82,10,High,New,1,0 +53923,61074,55449,PRETRIAL,St Jean,Wesley,NULL,Male,African-American,09/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +16682,61092,55463,PRETRIAL,MCINTYRE,ARDELL,LUCAINO,Male,African-American,11/30/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/15/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +16682,61092,55463,PRETRIAL,MCINTYRE,ARDELL,LUCAINO,Male,African-American,11/30/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/15/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +16682,61092,55463,PRETRIAL,MCINTYRE,ARDELL,LUCAINO,Male,African-American,11/30/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53946,61105,55474,PRETRIAL,Aries,Yahaira,NULL,Female,Hispanic,04/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +53946,61105,55474,PRETRIAL,Aries,Yahaira,NULL,Female,Hispanic,04/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +53946,61105,55474,PRETRIAL,Aries,Yahaira,NULL,Female,Hispanic,04/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53955,61116,55485,Probation,JOHN,LAWRENCE,ANTHONY,Male,African-American,01/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +53955,61116,55485,Probation,JOHN,LAWRENCE,ANTHONY,Male,African-American,01/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,4,High,8,Risk of Recidivism,0.48,9,High,New,1,0 +53955,61116,55485,Probation,JOHN,LAWRENCE,ANTHONY,Male,African-American,01/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49485,61071,55446,PRETRIAL,Jackson,Keya,NULL,Female,African-American,03/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +49485,61071,55446,PRETRIAL,Jackson,Keya,NULL,Female,African-American,03/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +49485,61071,55446,PRETRIAL,Jackson,Keya,NULL,Female,African-American,03/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53948,61108,55477,Probation,PRADO,MANUEL,A,Male,Hispanic,09/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +53948,61108,55477,Probation,PRADO,MANUEL,A,Male,Hispanic,09/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +53948,61108,55477,Probation,PRADO,MANUEL,A,Male,Hispanic,09/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53927,61079,55453,PRETRIAL,Chambers,Ryan,NULL,Male,Other,08/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,4,High,7,Risk of Violence,-1.19,8,High,New,1,0 +53927,61079,55453,PRETRIAL,Chambers,Ryan,NULL,Male,Other,08/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +53927,61079,55453,PRETRIAL,Chambers,Ryan,NULL,Male,Other,08/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53943,61102,55471,Probation,Garland,Deandre,NULL,Male,African-American,09/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +53943,61102,55471,Probation,Garland,Deandre,NULL,Male,African-American,09/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +53943,61102,55471,Probation,Garland,Deandre,NULL,Male,African-American,09/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53932,61085,55458,PRETRIAL,Regueiro,Jesus,NULL,Male,Hispanic,09/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/13 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +53932,61085,55458,PRETRIAL,Regueiro,Jesus,NULL,Male,Hispanic,09/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +53932,61085,55458,PRETRIAL,Regueiro,Jesus,NULL,Male,Hispanic,09/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +53914,61064,55439,PRETRIAL,HARDEN,EMORY,F,Male,African-American,10/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +53914,61064,55439,PRETRIAL,HARDEN,EMORY,F,Male,African-American,10/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +53914,61064,55439,PRETRIAL,HARDEN,EMORY,F,Male,African-American,10/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53916,61069,55444,PRETRIAL,SWEETLAND-PITTER,FABION,ANTHONY,Male,African-American,07/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +53916,61069,55444,PRETRIAL,SWEETLAND-PITTER,FABION,ANTHONY,Male,African-American,07/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +53916,61069,55444,PRETRIAL,SWEETLAND-PITTER,FABION,ANTHONY,Male,African-American,07/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53924,61076,55450,PRETRIAL,SCHULT,ADAM,NULL,Male,Caucasian,05/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +53924,61076,55450,PRETRIAL,SCHULT,ADAM,NULL,Male,Caucasian,05/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +53924,61076,55450,PRETRIAL,SCHULT,ADAM,NULL,Male,Caucasian,05/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53915,61067,55442,PRETRIAL,Lewis,Broderick,NULL,Male,African-American,08/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +53915,61067,55442,PRETRIAL,Lewis,Broderick,NULL,Male,African-American,08/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +53915,61067,55442,PRETRIAL,Lewis,Broderick,NULL,Male,African-American,08/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +26174,61097,55467,PRETRIAL,Hankerson,Levi,Leon,Male,African-American,08/28/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.47,3,Low,New,1,0 +26174,61097,55467,PRETRIAL,Hankerson,Levi,Leon,Male,African-American,08/28/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +26174,61097,55467,PRETRIAL,Hankerson,Levi,Leon,Male,African-American,08/28/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53197,61090,54635,Probation,Young,Alvin,C,Male,African-American,03/24/62,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +53197,61090,54635,Probation,Young,Alvin,C,Male,African-American,03/24/62,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +53197,61090,54635,Probation,Young,Alvin,C,Male,African-American,03/24/62,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,19,2,Low,New,1,0 +53951,61111,55480,Probation,Flowers,Mitchell,NULL,Male,Caucasian,03/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +53951,61111,55480,Probation,Flowers,Mitchell,NULL,Male,Caucasian,03/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +53951,61111,55480,Probation,Flowers,Mitchell,NULL,Male,Caucasian,03/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53957,61118,55487,PRETRIAL,MOLINA,WILLIE,HUMBERTO,Male,Caucasian,03/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/15/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +53957,61118,55487,PRETRIAL,MOLINA,WILLIE,HUMBERTO,Male,Caucasian,03/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/15/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +53957,61118,55487,PRETRIAL,MOLINA,WILLIE,HUMBERTO,Male,Caucasian,03/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/15/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53962,61125,55494,PRETRIAL,Wyngaarde,Johan,Anson,Male,African-American,07/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +53962,61125,55494,PRETRIAL,Wyngaarde,Johan,Anson,Male,African-American,07/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +53962,61125,55494,PRETRIAL,Wyngaarde,Johan,Anson,Male,African-American,07/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53136,61139,54566,Probation,Nevarez,Jorge,W,Male,Hispanic,01/26/60,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,4/16/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +53136,61139,54566,Probation,Nevarez,Jorge,W,Male,Hispanic,01/26/60,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,4/16/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +53136,61139,54566,Probation,Nevarez,Jorge,W,Male,Hispanic,01/26/60,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53976,61146,55512,Probation,FALCONE,JOSEPH,NICHOLAS,Male,Caucasian,12/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +53976,61146,55512,Probation,FALCONE,JOSEPH,NICHOLAS,Male,Caucasian,12/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +53976,61146,55512,Probation,FALCONE,JOSEPH,NICHOLAS,Male,Caucasian,12/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +37685,61132,55500,PRETRIAL,SYLFORT,JONEL,NULL,Male,African-American,02/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +37685,61132,55500,PRETRIAL,SYLFORT,JONEL,NULL,Male,African-American,02/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +37685,61132,55500,PRETRIAL,SYLFORT,JONEL,NULL,Male,African-American,02/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +35299,61153,55518,PRETRIAL,Paul,Ariel,NULL,Male,Other,01/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +35299,61153,55518,PRETRIAL,Paul,Ariel,NULL,Male,Other,01/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +35299,61153,55518,PRETRIAL,Paul,Ariel,NULL,Male,Other,01/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53958,61120,55489,PRETRIAL,WILLIAMS,JEFFREY,J,Male,African-American,06/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +53958,61120,55489,PRETRIAL,WILLIAMS,JEFFREY,J,Male,African-American,06/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +53958,61120,55489,PRETRIAL,WILLIAMS,JEFFREY,J,Male,African-American,06/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53963,61127,55496,PRETRIAL,Lopez,Nelson,NULL,Male,Caucasian,11/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +53963,61127,55496,PRETRIAL,Lopez,Nelson,NULL,Male,Caucasian,11/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +53963,61127,55496,PRETRIAL,Lopez,Nelson,NULL,Male,Caucasian,11/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53960,61123,55492,PRETRIAL,Corker,Michael,NULL,Male,African-American,09/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,4,High,7,Risk of Violence,-1.03,8,High,New,1,0 +53960,61123,55492,PRETRIAL,Corker,Michael,NULL,Male,African-American,09/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +53960,61123,55492,PRETRIAL,Corker,Michael,NULL,Male,African-American,09/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53972,61141,55507,PRETRIAL,Paredes,Ivan,NULL,Male,Hispanic,04/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +53972,61141,55507,PRETRIAL,Paredes,Ivan,NULL,Male,Hispanic,04/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +53972,61141,55507,PRETRIAL,Paredes,Ivan,NULL,Male,Hispanic,04/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53348,61129,54814,PRETRIAL,Gayle,Lorenzo,NULL,Male,African-American,03/04/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.76,9,High,Copy,1,0 +53348,61129,54814,PRETRIAL,Gayle,Lorenzo,NULL,Male,African-American,03/04/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,7,Medium,Copy,1,0 +53348,61129,54814,PRETRIAL,Gayle,Lorenzo,NULL,Male,African-American,03/04/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +53347,61136,54813,Probation,Williams,Erica,Nicole,Female,African-American,10/13/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +53347,61136,54813,Probation,Williams,Erica,Nicole,Female,African-American,10/13/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +53347,61136,54813,Probation,Williams,Erica,Nicole,Female,African-American,10/13/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53969,61137,55504,Probation,ORTIZ,ANGELIQUE,MARIA,Male,Hispanic,11/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +53969,61137,55504,Probation,ORTIZ,ANGELIQUE,MARIA,Male,Hispanic,11/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +53969,61137,55504,Probation,ORTIZ,ANGELIQUE,MARIA,Male,Hispanic,11/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53974,61144,55510,Probation,symonette,DUSTIN,NULL,Male,African-American,09/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +53974,61144,55510,Probation,symonette,DUSTIN,NULL,Male,African-American,09/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +53974,61144,55510,Probation,symonette,DUSTIN,NULL,Male,African-American,09/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53977,61150,55515,Probation,LOUISDON,NADERGE,NULL,Female,African-American,10/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,2,Medium,7,Risk of Violence,-2.73,2,Low,New,1,0 +53977,61150,55515,Probation,LOUISDON,NADERGE,NULL,Female,African-American,10/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +53977,61150,55515,Probation,LOUISDON,NADERGE,NULL,Female,African-American,10/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53967,61134,55502,Probation,Lindsay,Robert,NULL,Male,Caucasian,06/05/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +53967,61134,55502,Probation,Lindsay,Robert,NULL,Male,Caucasian,06/05/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +53967,61134,55502,Probation,Lindsay,Robert,NULL,Male,Caucasian,06/05/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +41223,61147,55513,PRETRIAL,Wilkinson,Corina,Lynn,Female,Caucasian,04/15/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +41223,61147,55513,PRETRIAL,Wilkinson,Corina,Lynn,Female,Caucasian,04/15/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +41223,61147,55513,PRETRIAL,Wilkinson,Corina,Lynn,Female,Caucasian,04/15/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +53959,61121,55490,PRETRIAL,ORTIZ,HUMBERTO,NULL,Male,Hispanic,01/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/16/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +53959,61121,55490,PRETRIAL,ORTIZ,HUMBERTO,NULL,Male,Hispanic,01/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +53959,61121,55490,PRETRIAL,ORTIZ,HUMBERTO,NULL,Male,Hispanic,01/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/16/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +38763,61126,55495,PRETRIAL,Deliard,Ronald,NULL,Male,African-American,10/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,New,1,0 +38763,61126,55495,PRETRIAL,Deliard,Ronald,NULL,Male,African-American,10/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +38763,61126,55495,PRETRIAL,Deliard,Ronald,NULL,Male,African-American,10/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53984,61155,55520,Probation,BELL,ERIC,L,Male,African-American,05/04/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +53984,61155,55520,Probation,BELL,ERIC,L,Male,African-American,05/04/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +53984,61155,55520,Probation,BELL,ERIC,L,Male,African-American,05/04/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53975,61145,55511,Probation,Glover,Leeron,Defay,Male,African-American,04/10/77,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/16/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +53975,61145,55511,Probation,Glover,Leeron,Defay,Male,African-American,04/10/77,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/16/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +53975,61145,55511,Probation,Glover,Leeron,Defay,Male,African-American,04/10/77,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53961,61124,55493,PRETRIAL,ST FLEUR,FRENZY,NULL,Male,African-American,09/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +53961,61124,55493,PRETRIAL,ST FLEUR,FRENZY,NULL,Male,African-American,09/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +53961,61124,55493,PRETRIAL,ST FLEUR,FRENZY,NULL,Male,African-American,09/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53964,61128,55497,PRETRIAL,Lubin,Gabriele,NULL,Male,African-American,03/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +53964,61128,55497,PRETRIAL,Lubin,Gabriele,NULL,Male,African-American,03/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +53964,61128,55497,PRETRIAL,Lubin,Gabriele,NULL,Male,African-American,03/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +41893,61149,55514,Probation,brown,romanye,NULL,Male,African-American,03/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +41893,61149,55514,Probation,brown,romanye,NULL,Male,African-American,03/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +41893,61149,55514,Probation,brown,romanye,NULL,Male,African-American,03/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +30275,61131,55499,PRETRIAL,HAMPTON,RALPH,NULL,Male,Caucasian,07/23/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/16/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +30275,61131,55499,PRETRIAL,HAMPTON,RALPH,NULL,Male,Caucasian,07/23/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/16/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +30275,61131,55499,PRETRIAL,HAMPTON,RALPH,NULL,Male,Caucasian,07/23/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53966,61133,55501,Probation,ramirez,Jose,NULL,Male,Hispanic,12/05/85,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +53966,61133,55501,Probation,ramirez,Jose,NULL,Male,Hispanic,12/05/85,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +53966,61133,55501,Probation,ramirez,Jose,NULL,Male,Hispanic,12/05/85,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53971,61140,55506,PRETRIAL,Wasserman,Geoffrey,NULL,Male,Caucasian,03/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +53971,61140,55506,PRETRIAL,Wasserman,Geoffrey,NULL,Male,Caucasian,03/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +53971,61140,55506,PRETRIAL,Wasserman,Geoffrey,NULL,Male,Caucasian,03/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53973,61143,55509,Probation,Nunez,Kioma,NULL,Male,Hispanic,05/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/16/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +53973,61143,55509,Probation,Nunez,Kioma,NULL,Male,Hispanic,05/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/16/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +53973,61143,55509,Probation,Nunez,Kioma,NULL,Male,Hispanic,05/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +23218,61122,55491,PRETRIAL,DUFREME,LEWIS,NULL,Male,African-American,02/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/16/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +23218,61122,55491,PRETRIAL,DUFREME,LEWIS,NULL,Male,African-American,02/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/16/13 0:00,2,Medium,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +23218,61122,55491,PRETRIAL,DUFREME,LEWIS,NULL,Male,African-American,02/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/16/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53968,61135,55503,PRETRIAL,Mckenzie,Vernee,Alena,Female,African-American,09/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +53968,61135,55503,PRETRIAL,Mckenzie,Vernee,Alena,Female,African-American,09/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +53968,61135,55503,PRETRIAL,Mckenzie,Vernee,Alena,Female,African-American,09/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53970,61138,55505,PRETRIAL,Owens,Janay,NULL,Female,African-American,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/16/13 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +53970,61138,55505,PRETRIAL,Owens,Janay,NULL,Female,African-American,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +53970,61138,55505,PRETRIAL,Owens,Janay,NULL,Female,African-American,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/16/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +39369,61156,38878,PRETRIAL,Hope,Jason,NULL,Male,Caucasian,01/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,Copy,1,0 +39369,61156,38878,PRETRIAL,Hope,Jason,NULL,Male,Caucasian,01/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,9,High,Copy,1,0 +39369,61156,38878,PRETRIAL,Hope,Jason,NULL,Male,Caucasian,01/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +53965,61130,55498,Probation,MILLER,MICHAEL,NULL,Male,Caucasian,01/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +53965,61130,55498,Probation,MILLER,MICHAEL,NULL,Male,Caucasian,01/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +53965,61130,55498,Probation,MILLER,MICHAEL,NULL,Male,Caucasian,01/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53978,61151,55516,PRETRIAL,Elmoutawayei,Mohamed,NULL,Male,Other,07/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,4,High,7,Risk of Violence,-1.23,8,High,New,1,0 +53978,61151,55516,PRETRIAL,Elmoutawayei,Mohamed,NULL,Male,Other,07/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,4,High,8,Risk of Recidivism,1.4,10,High,New,1,0 +53978,61151,55516,PRETRIAL,Elmoutawayei,Mohamed,NULL,Male,Other,07/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +41842,61185,55549,Probation,Davis,Naomi,Antionete,Female,African-American,06/13/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/17/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +41842,61185,55549,Probation,Davis,Naomi,Antionete,Female,African-American,06/13/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/17/13 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +41842,61185,55549,Probation,Davis,Naomi,Antionete,Female,African-American,06/13/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53991,61164,55528,PRETRIAL,Lovett,Carl,NULL,Male,African-American,01/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +53991,61164,55528,PRETRIAL,Lovett,Carl,NULL,Male,African-American,01/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +53991,61164,55528,PRETRIAL,Lovett,Carl,NULL,Male,African-American,01/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +26021,61198,55562,PRETRIAL,SHAWN,RHEAL,THOMAS,Male,Caucasian,08/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +26021,61198,55562,PRETRIAL,SHAWN,RHEAL,THOMAS,Male,Caucasian,08/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +26021,61198,55562,PRETRIAL,SHAWN,RHEAL,THOMAS,Male,Caucasian,08/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53987,61159,55523,PRETRIAL,Dixon,Natalie,J,Female,African-American,11/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +53987,61159,55523,PRETRIAL,Dixon,Natalie,J,Female,African-American,11/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +53987,61159,55523,PRETRIAL,Dixon,Natalie,J,Female,African-American,11/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54000,61177,55541,Probation,Bobb,Nicole,NULL,Female,Caucasian,10/12/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +54000,61177,55541,Probation,Bobb,Nicole,NULL,Female,Caucasian,10/12/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +54000,61177,55541,Probation,Bobb,Nicole,NULL,Female,Caucasian,10/12/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54003,61180,55544,PRETRIAL,Tremaine,Hutchinson,NULL,Male,African-American,10/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +54003,61180,55544,PRETRIAL,Tremaine,Hutchinson,NULL,Male,African-American,10/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +54003,61180,55544,PRETRIAL,Tremaine,Hutchinson,NULL,Male,African-American,10/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +47433,61172,55536,PRETRIAL,Turnbull,Ian,NULL,Male,African-American,03/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,4,High,7,Risk of Violence,-0.64,9,High,New,1,0 +47433,61172,55536,PRETRIAL,Turnbull,Ian,NULL,Male,African-American,03/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,4,High,8,Risk of Recidivism,0.27,8,High,New,1,0 +47433,61172,55536,PRETRIAL,Turnbull,Ian,NULL,Male,African-American,03/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54012,61193,55557,Probation,IRVIN,KENNETH,NULL,Male,African-American,11/07/61,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.28,3,Low,New,1,0 +54012,61193,55557,Probation,IRVIN,KENNETH,NULL,Male,African-American,11/07/61,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +54012,61193,55557,Probation,IRVIN,KENNETH,NULL,Male,African-American,11/07/61,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +8968,61175,55539,PRETRIAL,LANE,DEMONDA,NULL,Female,African-American,09/12/77,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +8968,61175,55539,PRETRIAL,LANE,DEMONDA,NULL,Female,African-American,09/12/77,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +8968,61175,55539,PRETRIAL,LANE,DEMONDA,NULL,Female,African-American,09/12/77,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,New,1,0 +54008,61189,55553,Probation,vorozhbit,pavel,NULL,Male,Caucasian,10/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +54008,61189,55553,Probation,vorozhbit,pavel,NULL,Male,Caucasian,10/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +54008,61189,55553,Probation,vorozhbit,pavel,NULL,Male,Caucasian,10/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53989,61161,55525,PRETRIAL,Dill,Carlene,NULL,Female,Other,05/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +53989,61161,55525,PRETRIAL,Dill,Carlene,NULL,Female,Other,05/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +53989,61161,55525,PRETRIAL,Dill,Carlene,NULL,Female,Other,05/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53995,61168,55532,PRETRIAL,RIVERA,RAFAEL,PEREZ,Male,African-American,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +53995,61168,55532,PRETRIAL,RIVERA,RAFAEL,PEREZ,Male,African-American,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +53995,61168,55532,PRETRIAL,RIVERA,RAFAEL,PEREZ,Male,African-American,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54004,61182,55546,Probation,Conlon,Joseph,NULL,Male,Caucasian,05/12/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/17/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +54004,61182,55546,Probation,Conlon,Joseph,NULL,Male,Caucasian,05/12/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +54004,61182,55546,Probation,Conlon,Joseph,NULL,Male,Caucasian,05/12/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54006,61184,55548,Probation,ELLISON,CHELSEA,NICOLE,Female,African-American,10/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.01,4,Low,New,1,0 +54006,61184,55548,Probation,ELLISON,CHELSEA,NICOLE,Female,African-American,10/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,8,High,New,1,0 +54006,61184,55548,Probation,ELLISON,CHELSEA,NICOLE,Female,African-American,10/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,New,1,0 +53993,61166,55530,PRETRIAL,Kantzelis,Alex,NULL,Male,Caucasian,06/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +53993,61166,55530,PRETRIAL,Kantzelis,Alex,NULL,Male,Caucasian,06/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +53993,61166,55530,PRETRIAL,Kantzelis,Alex,NULL,Male,Caucasian,06/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +46847,61196,55560,Probation,delevery,jean,NULL,Male,African-American,01/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +46847,61196,55560,Probation,delevery,jean,NULL,Male,African-American,01/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +46847,61196,55560,Probation,delevery,jean,NULL,Male,African-American,01/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54010,61191,55555,Probation,thomas,elridge,NULL,Male,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +54010,61191,55555,Probation,thomas,elridge,NULL,Male,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +54010,61191,55555,Probation,thomas,elridge,NULL,Male,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53997,61170,55534,PRETRIAL,AVERY,HOPE,NULL,Female,Caucasian,06/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +53997,61170,55534,PRETRIAL,AVERY,HOPE,NULL,Female,Caucasian,06/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +53997,61170,55534,PRETRIAL,AVERY,HOPE,NULL,Female,Caucasian,06/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53988,61160,55524,PRETRIAL,Serrano,Ismael,Giovanni,Male,Hispanic,08/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +53988,61160,55524,PRETRIAL,Serrano,Ismael,Giovanni,Male,Hispanic,08/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +53988,61160,55524,PRETRIAL,Serrano,Ismael,Giovanni,Male,Hispanic,08/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54013,61194,55558,Probation,SHUMATE,ROBERT,NULL,Male,Caucasian,08/15/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/17/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +54013,61194,55558,Probation,SHUMATE,ROBERT,NULL,Male,Caucasian,08/15/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +54013,61194,55558,Probation,SHUMATE,ROBERT,NULL,Male,Caucasian,08/15/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +42103,61181,55545,PRETRIAL,CARPINELLI,CHARLES,NULL,Male,Caucasian,01/17/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +42103,61181,55545,PRETRIAL,CARPINELLI,CHARLES,NULL,Male,Caucasian,01/17/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +42103,61181,55545,PRETRIAL,CARPINELLI,CHARLES,NULL,Male,Caucasian,01/17/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53998,61173,55537,PRETRIAL,Greene,Marlon,Lanorris,Male,Caucasian,01/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.96,5,Medium,New,1,0 +53998,61173,55537,PRETRIAL,Greene,Marlon,Lanorris,Male,Caucasian,01/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +53998,61173,55537,PRETRIAL,Greene,Marlon,Lanorris,Male,Caucasian,01/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53990,61163,55527,PRETRIAL,Williams,Rodrick,NULL,Male,African-American,11/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +53990,61163,55527,PRETRIAL,Williams,Rodrick,NULL,Male,African-American,11/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +53990,61163,55527,PRETRIAL,Williams,Rodrick,NULL,Male,African-American,11/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +53992,61165,55529,PRETRIAL,Pierre,Sarrah,NULL,Female,African-American,03/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +53992,61165,55529,PRETRIAL,Pierre,Sarrah,NULL,Female,African-American,03/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +53992,61165,55529,PRETRIAL,Pierre,Sarrah,NULL,Female,African-American,03/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54016,61199,55563,PRETRIAL,Torres,Miguel,NULL,Male,Hispanic,05/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +54016,61199,55563,PRETRIAL,Torres,Miguel,NULL,Male,Hispanic,05/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +54016,61199,55563,PRETRIAL,Torres,Miguel,NULL,Male,Hispanic,05/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +25296,61171,55535,PRETRIAL,Gadsen,James,NULL,Male,African-American,08/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +25296,61171,55535,PRETRIAL,Gadsen,James,NULL,Male,African-American,08/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +25296,61171,55535,PRETRIAL,Gadsen,James,NULL,Male,African-American,08/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54001,61178,55542,Probation,RIVAS,PRISCILLA,NULL,Female,Hispanic,11/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +54001,61178,55542,Probation,RIVAS,PRISCILLA,NULL,Female,Hispanic,11/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +54001,61178,55542,Probation,RIVAS,PRISCILLA,NULL,Female,Hispanic,11/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54002,61179,55543,PRETRIAL,Williams,Daniel,NULL,Male,Caucasian,07/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +54002,61179,55543,PRETRIAL,Williams,Daniel,NULL,Male,Caucasian,07/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +54002,61179,55543,PRETRIAL,Williams,Daniel,NULL,Male,Caucasian,07/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54007,61186,55550,PRETRIAL,Brown,Richard,NULL,Male,African-American,12/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/17/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +54007,61186,55550,PRETRIAL,Brown,Richard,NULL,Male,African-American,12/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/17/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +54007,61186,55550,PRETRIAL,Brown,Richard,NULL,Male,African-American,12/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53985,61157,55521,PRETRIAL,Elder,Neil,Lawrance,Male,Caucasian,11/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +53985,61157,55521,PRETRIAL,Elder,Neil,Lawrance,Male,Caucasian,11/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +53985,61157,55521,PRETRIAL,Elder,Neil,Lawrance,Male,Caucasian,11/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53986,61158,55522,PRETRIAL,Barbary,Lashunda,NULL,Female,African-American,03/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +53986,61158,55522,PRETRIAL,Barbary,Lashunda,NULL,Female,African-American,03/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.61,2,Low,New,1,0 +53986,61158,55522,PRETRIAL,Barbary,Lashunda,NULL,Female,African-American,03/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53999,61174,55538,PRETRIAL,Hernandez,Maricelis,NULL,Female,Caucasian,01/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/17/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +53999,61174,55538,PRETRIAL,Hernandez,Maricelis,NULL,Female,Caucasian,01/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +53999,61174,55538,PRETRIAL,Hernandez,Maricelis,NULL,Female,Caucasian,01/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54011,61192,55556,Probation,Burke,Jennifer,Alice,Female,Caucasian,11/12/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +54011,61192,55556,Probation,Burke,Jennifer,Alice,Female,Caucasian,11/12/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +54011,61192,55556,Probation,Burke,Jennifer,Alice,Female,Caucasian,11/12/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,New,1,0 +26725,61188,55552,Probation,Ely,Stephanie,Nicole,Female,Caucasian,06/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +26725,61188,55552,Probation,Ely,Stephanie,Nicole,Female,Caucasian,06/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,8,High,New,1,0 +26725,61188,55552,Probation,Ely,Stephanie,Nicole,Female,Caucasian,06/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +35605,61162,55526,PRETRIAL,Fuller,Dovaun,Erdine,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +35605,61162,55526,PRETRIAL,Fuller,Dovaun,Erdine,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.67,10,High,New,1,0 +35605,61162,55526,PRETRIAL,Fuller,Dovaun,Erdine,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54005,61183,55547,Probation,LAKINS,DAVID,NULL,Male,Caucasian,02/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,2,Medium,7,Risk of Violence,-2.87,2,Low,New,1,0 +54005,61183,55547,Probation,LAKINS,DAVID,NULL,Male,Caucasian,02/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +54005,61183,55547,Probation,LAKINS,DAVID,NULL,Male,Caucasian,02/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53996,61169,55533,PRETRIAL,MOTON,MATTHEW,NULL,Male,African-American,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +53996,61169,55533,PRETRIAL,MOTON,MATTHEW,NULL,Male,African-American,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +53996,61169,55533,PRETRIAL,MOTON,MATTHEW,NULL,Male,African-American,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +21869,61176,55540,PRETRIAL,Waech,Nicholas,Alan,Male,Caucasian,05/16/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +21869,61176,55540,PRETRIAL,Waech,Nicholas,Alan,Male,Caucasian,05/16/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +21869,61176,55540,PRETRIAL,Waech,Nicholas,Alan,Male,Caucasian,05/16/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53994,61167,55531,PRETRIAL,Jorden,Constance,NULL,Female,African-American,04/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +53994,61167,55531,PRETRIAL,Jorden,Constance,NULL,Female,African-American,04/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +53994,61167,55531,PRETRIAL,Jorden,Constance,NULL,Female,African-American,04/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54015,61197,55561,Probation,Petkovski,Hebert,NULL,Male,Caucasian,05/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +54015,61197,55561,Probation,Petkovski,Hebert,NULL,Male,Caucasian,05/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +54015,61197,55561,Probation,Petkovski,Hebert,NULL,Male,Caucasian,05/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +23578,61190,55554,PRETRIAL,Jean,Marc,NULL,Male,African-American,11/11/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +23578,61190,55554,PRETRIAL,Jean,Marc,NULL,Male,African-American,11/11/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +23578,61190,55554,PRETRIAL,Jean,Marc,NULL,Male,African-American,11/11/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54038,61225,55587,Probation,FAULK,DARRIN,LEE,Male,Caucasian,01/19/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +54038,61225,55587,Probation,FAULK,DARRIN,LEE,Male,Caucasian,01/19/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +54038,61225,55587,Probation,FAULK,DARRIN,LEE,Male,Caucasian,01/19/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +39677,61239,39221,PRETRIAL,STARR,SCOTT,NULL,Male,Caucasian,12/26/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,Copy,1,0 +39677,61239,39221,PRETRIAL,STARR,SCOTT,NULL,Male,Caucasian,12/26/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,Copy,1,0 +39677,61239,39221,PRETRIAL,STARR,SCOTT,NULL,Male,Caucasian,12/26/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +52375,61204,55568,PRETRIAL,Thomas,Murvin,J,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,7,Risk of Violence,-0.56,10,High,New,1,0 +52375,61204,55568,PRETRIAL,Thomas,Murvin,J,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,8,Risk of Recidivism,0.93,10,High,New,1,0 +52375,61204,55568,PRETRIAL,Thomas,Murvin,J,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +52033,61211,55575,PRETRIAL,Ramos,Raphael,NULL,Male,African-American,03/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +52033,61211,55575,PRETRIAL,Ramos,Raphael,NULL,Male,African-American,03/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +52033,61211,55575,PRETRIAL,Ramos,Raphael,NULL,Male,African-American,03/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54031,61218,55582,PRETRIAL,Napoli,Andrew,NULL,Male,Caucasian,06/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +54031,61218,55582,PRETRIAL,Napoli,Andrew,NULL,Male,Caucasian,06/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +54031,61218,55582,PRETRIAL,Napoli,Andrew,NULL,Male,Caucasian,06/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +17391,61248,55606,PRETRIAL,TOBIN,EDWARD,NULL,Male,Caucasian,05/07/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/18/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +17391,61248,55606,PRETRIAL,TOBIN,EDWARD,NULL,Male,Caucasian,05/07/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +17391,61248,55606,PRETRIAL,TOBIN,EDWARD,NULL,Male,Caucasian,05/07/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54062,61246,55604,Probation,Rouss,Diana,NULL,Female,Hispanic,04/13/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +54062,61246,55604,Probation,Rouss,Diana,NULL,Female,Hispanic,04/13/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +54062,61246,55604,Probation,Rouss,Diana,NULL,Female,Hispanic,04/13/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54066,61251,55609,PRETRIAL,PARKER,KEVIN,NULL,Male,Caucasian,01/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +54066,61251,55609,PRETRIAL,PARKER,KEVIN,NULL,Male,Caucasian,01/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +54066,61251,55609,PRETRIAL,PARKER,KEVIN,NULL,Male,Caucasian,01/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54041,61230,55591,PRETRIAL,Kaplan,Kenneth,NULL,Male,Caucasian,11/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/18/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +54041,61230,55591,PRETRIAL,Kaplan,Kenneth,NULL,Male,Caucasian,11/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/18/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +54041,61230,55591,PRETRIAL,Kaplan,Kenneth,NULL,Male,Caucasian,11/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/18/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +17505,61213,55577,PRETRIAL,Soto,Kevin,NULL,Male,African-American,07/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,7,Risk of Violence,-0.68,9,High,New,1,0 +17505,61213,55577,PRETRIAL,Soto,Kevin,NULL,Male,African-American,07/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,8,Risk of Recidivism,1.16,10,High,New,1,0 +17505,61213,55577,PRETRIAL,Soto,Kevin,NULL,Male,African-American,07/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54025,61209,55573,PRETRIAL,Freeman,Lynell,NULL,Female,African-American,10/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +54025,61209,55573,PRETRIAL,Freeman,Lynell,NULL,Female,African-American,10/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +54025,61209,55573,PRETRIAL,Freeman,Lynell,NULL,Female,African-American,10/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54023,61207,55571,PRETRIAL,Pinto-Collazo,Lizabeth,NULL,Female,Caucasian,11/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +54023,61207,55571,PRETRIAL,Pinto-Collazo,Lizabeth,NULL,Female,Caucasian,11/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +54023,61207,55571,PRETRIAL,Pinto-Collazo,Lizabeth,NULL,Female,Caucasian,11/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54044,61236,55595,Probation,Hall Jr.,George,Barry,Male,Caucasian,11/26/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/18/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +54044,61236,55595,Probation,Hall Jr.,George,Barry,Male,Caucasian,11/26/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +54044,61236,55595,Probation,Hall Jr.,George,Barry,Male,Caucasian,11/26/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54060,61244,55602,Probation,rois,Briana,Michelle,Female,Hispanic,03/22/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +54060,61244,55602,Probation,rois,Briana,Michelle,Female,Hispanic,03/22/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +54060,61244,55602,Probation,rois,Briana,Michelle,Female,Hispanic,03/22/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54019,61202,55566,PRETRIAL,Borbos,Martha,NULL,Female,Caucasian,12/22/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.71,2,Low,New,1,0 +54019,61202,55566,PRETRIAL,Borbos,Martha,NULL,Female,Caucasian,12/22/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,9,High,New,1,0 +54019,61202,55566,PRETRIAL,Borbos,Martha,NULL,Female,Caucasian,12/22/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +47683,61223,48256,PRETRIAL,Wilson,Valarie,NULL,Female,African-American,04/09/77,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,4/18/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +47683,61223,48256,PRETRIAL,Wilson,Valarie,NULL,Female,African-American,04/09/77,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +47683,61223,48256,PRETRIAL,Wilson,Valarie,NULL,Female,African-American,04/09/77,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +22888,61241,55599,PRETRIAL,Glinton,Afred,NULL,Male,African-American,04/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +22888,61241,55599,PRETRIAL,Glinton,Afred,NULL,Male,African-American,04/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +22888,61241,55599,PRETRIAL,Glinton,Afred,NULL,Male,African-American,04/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54029,61215,55579,PRETRIAL,ROBINSON,SOPHIE,NULL,Male,African-American,07/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +54029,61215,55579,PRETRIAL,ROBINSON,SOPHIE,NULL,Male,African-American,07/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +54029,61215,55579,PRETRIAL,ROBINSON,SOPHIE,NULL,Male,African-American,07/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +22998,61249,55607,PRETRIAL,CALLE-BERNAL,RUBEN,C,Male,Hispanic,01/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +22998,61249,55607,PRETRIAL,CALLE-BERNAL,RUBEN,C,Male,Hispanic,01/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +22998,61249,55607,PRETRIAL,CALLE-BERNAL,RUBEN,C,Male,Hispanic,01/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54040,61228,55589,Probation,WRIGHTBUTLER,JESSICA,MARIE,Female,Caucasian,08/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +54040,61228,55589,Probation,WRIGHTBUTLER,JESSICA,MARIE,Female,Caucasian,08/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +54040,61228,55589,Probation,WRIGHTBUTLER,JESSICA,MARIE,Female,Caucasian,08/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +53211,61238,55597,Probation,Zayas,annalyse,NULL,Female,Hispanic,03/07/91,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +53211,61238,55597,Probation,Zayas,annalyse,NULL,Female,Hispanic,03/07/91,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +53211,61238,55597,Probation,Zayas,annalyse,NULL,Female,Hispanic,03/07/91,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +41480,61242,55600,PRETRIAL,Valdes,Charlie,NULL,Male,Caucasian,10/14/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/18/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +41480,61242,55600,PRETRIAL,Valdes,Charlie,NULL,Male,Caucasian,10/14/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +41480,61242,55600,PRETRIAL,Valdes,Charlie,NULL,Male,Caucasian,10/14/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54033,61221,55584,Probation,Hurst,Wallace,NULL,Male,Caucasian,08/23/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/18/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +54033,61221,55584,Probation,Hurst,Wallace,NULL,Male,Caucasian,08/23/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +54033,61221,55584,Probation,Hurst,Wallace,NULL,Male,Caucasian,08/23/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54017,61200,55564,PRETRIAL,Jonas,Scott,NULL,Male,Caucasian,09/17/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +54017,61200,55564,PRETRIAL,Jonas,Scott,NULL,Male,Caucasian,09/17/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +54017,61200,55564,PRETRIAL,Jonas,Scott,NULL,Male,Caucasian,09/17/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +7290,61217,55581,PRETRIAL,PHILHOWER,ERICK,NULL,Male,Caucasian,04/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +7290,61217,55581,PRETRIAL,PHILHOWER,ERICK,NULL,Male,Caucasian,04/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +7290,61217,55581,PRETRIAL,PHILHOWER,ERICK,NULL,Male,Caucasian,04/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52995,61231,54404,PRETRIAL,Dean,Lamonte,NULL,Male,African-American,11/09/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,4,High,7,Risk of Violence,-0.72,9,High,New,1,0 +52995,61231,54404,PRETRIAL,Dean,Lamonte,NULL,Male,African-American,11/09/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,New,1,0 +52995,61231,54404,PRETRIAL,Dean,Lamonte,NULL,Male,African-American,11/09/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,4,High,18,Risk of Failure to Appear,23,4,Low,New,1,0 +54042,61233,55592,Probation,Moshe-Romano,Michael,NULL,Male,Hispanic,06/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +54042,61233,55592,Probation,Moshe-Romano,Michael,NULL,Male,Hispanic,06/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +54042,61233,55592,Probation,Moshe-Romano,Michael,NULL,Male,Hispanic,06/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54020,61203,55567,PRETRIAL,Benitez,Ryan,NULL,Male,Caucasian,09/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +54020,61203,55567,PRETRIAL,Benitez,Ryan,NULL,Male,Caucasian,09/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +54020,61203,55567,PRETRIAL,Benitez,Ryan,NULL,Male,Caucasian,09/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54021,61205,55569,PRETRIAL,Williams,Vandivuiet,NULL,Male,African-American,11/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,7,Risk of Violence,-0.63,9,High,New,1,0 +54021,61205,55569,PRETRIAL,Williams,Vandivuiet,NULL,Male,African-American,11/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +54021,61205,55569,PRETRIAL,Williams,Vandivuiet,NULL,Male,African-American,11/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54026,61210,55574,PRETRIAL,Rivas,Tomas,NULL,Male,Caucasian,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +54026,61210,55574,PRETRIAL,Rivas,Tomas,NULL,Male,Caucasian,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +54026,61210,55574,PRETRIAL,Rivas,Tomas,NULL,Male,Caucasian,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54027,61212,55576,PRETRIAL,Sexton,Michael,NULL,Male,African-American,04/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +54027,61212,55576,PRETRIAL,Sexton,Michael,NULL,Male,African-American,04/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,8,Risk of Recidivism,0.87,10,High,New,1,0 +54027,61212,55576,PRETRIAL,Sexton,Michael,NULL,Male,African-American,04/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54063,61247,55605,PRETRIAL,FRANCO,JASON,NULL,Male,Caucasian,03/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +54063,61247,55605,PRETRIAL,FRANCO,JASON,NULL,Male,Caucasian,03/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +54063,61247,55605,PRETRIAL,FRANCO,JASON,NULL,Male,Caucasian,03/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54039,61226,55588,Probation,saladino,kevin,NULL,Male,Caucasian,02/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +54039,61226,55588,Probation,saladino,kevin,NULL,Male,Caucasian,02/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.7,10,High,New,1,0 +54039,61226,55588,Probation,saladino,kevin,NULL,Male,Caucasian,02/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +37708,61240,55598,PRETRIAL,Bonin,Danielle,NULL,Female,Caucasian,04/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,4/18/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +37708,61240,55598,PRETRIAL,Bonin,Danielle,NULL,Female,Caucasian,04/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +37708,61240,55598,PRETRIAL,Bonin,Danielle,NULL,Female,Caucasian,04/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +44777,61229,55590,PRETRIAL,Moise,Josue,NULL,Male,Other,03/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +44777,61229,55590,PRETRIAL,Moise,Josue,NULL,Male,Other,03/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +44777,61229,55590,PRETRIAL,Moise,Josue,NULL,Male,Other,03/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54059,61243,55601,Probation,Martinez,Jessica,NULL,Female,Hispanic,09/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/18/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +54059,61243,55601,Probation,Martinez,Jessica,NULL,Female,Hispanic,09/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +54059,61243,55601,Probation,Martinez,Jessica,NULL,Female,Hispanic,09/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54024,61208,55572,PRETRIAL,Humberto,David,NULL,Male,Hispanic,01/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +54024,61208,55572,PRETRIAL,Humberto,David,NULL,Male,Hispanic,01/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +54024,61208,55572,PRETRIAL,Humberto,David,NULL,Male,Hispanic,01/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54034,61222,55585,PRETRIAL,Weimar,Karl,NULL,Male,Caucasian,03/20/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/18/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +54034,61222,55585,PRETRIAL,Weimar,Karl,NULL,Male,Caucasian,03/20/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +54034,61222,55585,PRETRIAL,Weimar,Karl,NULL,Male,Caucasian,03/20/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +54018,61201,55565,PRETRIAL,Williams,Troy,NULL,Male,African-American,04/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +54018,61201,55565,PRETRIAL,Williams,Troy,NULL,Male,African-American,04/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +54018,61201,55565,PRETRIAL,Williams,Troy,NULL,Male,African-American,04/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54028,61214,55578,PRETRIAL,PHILLIPS,VICTOR,L,Male,African-American,09/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +54028,61214,55578,PRETRIAL,PHILLIPS,VICTOR,L,Male,African-American,09/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +54028,61214,55578,PRETRIAL,PHILLIPS,VICTOR,L,Male,African-American,09/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54030,61216,55580,PRETRIAL,GILL,MARKIESHA,NULL,Female,African-American,09/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +54030,61216,55580,PRETRIAL,GILL,MARKIESHA,NULL,Female,African-American,09/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,8,Risk of Recidivism,0.26,9,High,New,1,0 +54030,61216,55580,PRETRIAL,GILL,MARKIESHA,NULL,Female,African-American,09/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,4,High,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +54065,61250,55608,Probation,rodriguez,leonardo,NULL,Male,Hispanic,10/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +54065,61250,55608,Probation,rodriguez,leonardo,NULL,Male,Hispanic,10/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +54065,61250,55608,Probation,rodriguez,leonardo,NULL,Male,Hispanic,10/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53642,61227,55100,PRETRIAL,VIDOT,ALEXIS,NULL,Female,African-American,12/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,Copy,1,0 +53642,61227,55100,PRETRIAL,VIDOT,ALEXIS,NULL,Female,African-American,12/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,Copy,1,0 +53642,61227,55100,PRETRIAL,VIDOT,ALEXIS,NULL,Female,African-American,12/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +54061,61245,55603,Probation,Neri,David,NULL,Male,Caucasian,07/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +54061,61245,55603,Probation,Neri,David,NULL,Male,Caucasian,07/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +54061,61245,55603,Probation,Neri,David,NULL,Male,Caucasian,07/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54022,61206,55570,PRETRIAL,Rowe,Danny,Dayton,Male,African-American,02/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +54022,61206,55570,PRETRIAL,Rowe,Danny,Dayton,Male,African-American,02/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +54022,61206,55570,PRETRIAL,Rowe,Danny,Dayton,Male,African-American,02/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54037,61224,55586,DRRD,McPherson,Phillop,D,Male,Other,04/09/84,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +54037,61224,55586,DRRD,McPherson,Phillop,D,Male,Other,04/09/84,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.49,4,Low,New,1,0 +54037,61224,55586,DRRD,McPherson,Phillop,D,Male,Other,04/09/84,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +36479,61232,35757,PRETRIAL,Tate,Dale,NULL,Male,African-American,07/21/68,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +36479,61232,35757,PRETRIAL,Tate,Dale,NULL,Male,African-American,07/21/68,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-0.63,3,Low,New,1,0 +36479,61232,35757,PRETRIAL,Tate,Dale,NULL,Male,African-American,07/21/68,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54032,61219,55583,PRETRIAL,Navasmejia,Jhonatan,NULL,Male,Hispanic,07/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +54032,61219,55583,PRETRIAL,Navasmejia,Jhonatan,NULL,Male,Hispanic,07/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +54032,61219,55583,PRETRIAL,Navasmejia,Jhonatan,NULL,Male,Hispanic,07/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54067,61253,55610,PRETRIAL,Sims,Greg,NULL,Male,African-American,02/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,4,High,7,Risk of Violence,-0.64,9,High,New,1,0 +54067,61253,55610,PRETRIAL,Sims,Greg,NULL,Male,African-American,02/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,4,High,8,Risk of Recidivism,0.21,8,High,New,1,0 +54067,61253,55610,PRETRIAL,Sims,Greg,NULL,Male,African-American,02/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54093,61287,55643,PRETRIAL,Allegretti,Anthony,NULL,Male,Caucasian,09/09/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +54093,61287,55643,PRETRIAL,Allegretti,Anthony,NULL,Male,Caucasian,09/09/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +54093,61287,55643,PRETRIAL,Allegretti,Anthony,NULL,Male,Caucasian,09/09/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54075,61266,55622,PRETRIAL,Ayres,Sterlyn,NULL,Male,African-American,09/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +54075,61266,55622,PRETRIAL,Ayres,Sterlyn,NULL,Male,African-American,09/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +54075,61266,55622,PRETRIAL,Ayres,Sterlyn,NULL,Male,African-American,09/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54082,61274,55630,PRETRIAL,Fox,Robert,NULL,Male,Caucasian,11/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +54082,61274,55630,PRETRIAL,Fox,Robert,NULL,Male,Caucasian,11/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +54082,61274,55630,PRETRIAL,Fox,Robert,NULL,Male,Caucasian,11/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +34412,61292,55647,Probation,FORBES,IEASHA,E,Female,African-American,02/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +34412,61292,55647,Probation,FORBES,IEASHA,E,Female,African-American,02/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,New,1,0 +34412,61292,55647,Probation,FORBES,IEASHA,E,Female,African-American,02/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54069,61258,55615,PRETRIAL,Salas,Benedicio,NULL,Male,Hispanic,07/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/19/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +54069,61258,55615,PRETRIAL,Salas,Benedicio,NULL,Male,Hispanic,07/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/19/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +54069,61258,55615,PRETRIAL,Salas,Benedicio,NULL,Male,Hispanic,07/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54087,61279,55635,PRETRIAL,moscovich,loren,NULL,Male,Caucasian,07/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +54087,61279,55635,PRETRIAL,moscovich,loren,NULL,Male,Caucasian,07/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +54087,61279,55635,PRETRIAL,moscovich,loren,NULL,Male,Caucasian,07/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54083,61275,55631,Probation,Obrien,Tyler,NULL,Male,Caucasian,01/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/19/13 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +54083,61275,55631,Probation,Obrien,Tyler,NULL,Male,Caucasian,01/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +54083,61275,55631,Probation,Obrien,Tyler,NULL,Male,Caucasian,01/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/19/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +2028,61289,55645,PRETRIAL,camacho,stephen,j,Male,Caucasian,11/05/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +2028,61289,55645,PRETRIAL,camacho,stephen,j,Male,Caucasian,11/05/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +2028,61289,55645,PRETRIAL,camacho,stephen,j,Male,Caucasian,11/05/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54071,61261,55618,PRETRIAL,Ponce,Gregory,NULL,Male,Caucasian,04/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +54071,61261,55618,PRETRIAL,Ponce,Gregory,NULL,Male,Caucasian,04/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +54071,61261,55618,PRETRIAL,Ponce,Gregory,NULL,Male,Caucasian,04/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54077,61268,55624,PRETRIAL,Tongyai,Virgina,Lee,Male,Caucasian,11/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +54077,61268,55624,PRETRIAL,Tongyai,Virgina,Lee,Male,Caucasian,11/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +54077,61268,55624,PRETRIAL,Tongyai,Virgina,Lee,Male,Caucasian,11/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54089,61282,55638,PRETRIAL,Benghiat,Steven,NULL,Male,Caucasian,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +54089,61282,55638,PRETRIAL,Benghiat,Steven,NULL,Male,Caucasian,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +54089,61282,55638,PRETRIAL,Benghiat,Steven,NULL,Male,Caucasian,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54091,61284,55640,Probation,Gilberto,Claudio,NULL,Male,Hispanic,11/07/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/19/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +54091,61284,55640,Probation,Gilberto,Claudio,NULL,Male,Hispanic,11/07/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/19/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +54091,61284,55640,Probation,Gilberto,Claudio,NULL,Male,Hispanic,11/07/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54070,61259,55616,PRETRIAL,Simpson,Kela,NULL,Female,Other,09/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +54070,61259,55616,PRETRIAL,Simpson,Kela,NULL,Female,Other,09/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +54070,61259,55616,PRETRIAL,Simpson,Kela,NULL,Female,Other,09/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54081,61273,55629,PRETRIAL,Wilsonbrown,Valencia,NULL,Female,African-American,08/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +54081,61273,55629,PRETRIAL,Wilsonbrown,Valencia,NULL,Female,African-American,08/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +54081,61273,55629,PRETRIAL,Wilsonbrown,Valencia,NULL,Female,African-American,08/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54072,61263,55619,PRETRIAL,Battie,Leroy,NULL,Male,African-American,02/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +54072,61263,55619,PRETRIAL,Battie,Leroy,NULL,Male,African-American,02/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +54072,61263,55619,PRETRIAL,Battie,Leroy,NULL,Male,African-American,02/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54085,61277,55633,Probation,Santos,Jimmy,NULL,Male,Hispanic,05/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/19/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +54085,61277,55633,Probation,Santos,Jimmy,NULL,Male,Hispanic,05/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/19/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +54085,61277,55633,Probation,Santos,Jimmy,NULL,Male,Hispanic,05/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54090,61283,55639,PRETRIAL,Savage,Lisa,NULL,Female,Caucasian,09/02/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/19/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +54090,61283,55639,PRETRIAL,Savage,Lisa,NULL,Female,Caucasian,09/02/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/19/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +54090,61283,55639,PRETRIAL,Savage,Lisa,NULL,Female,Caucasian,09/02/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +1994,61291,1700,Probation,Alvardo,Joseph,NULL,Male,African-American,01/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,Copy,1,0 +1994,61291,1700,Probation,Alvardo,Joseph,NULL,Male,African-American,01/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,Copy,1,0 +1994,61291,1700,Probation,Alvardo,Joseph,NULL,Male,African-American,01/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +54079,61270,55626,PRETRIAL,Youngbell,Ina,Maud,Female,Other,10/24/45,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/19/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +54079,61270,55626,PRETRIAL,Youngbell,Ina,Maud,Female,Other,10/24/45,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/19/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +54079,61270,55626,PRETRIAL,Youngbell,Ina,Maud,Female,Other,10/24/45,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54094,61288,55644,Probation,VEGOTSKY,MOLLY,NULL,Female,Caucasian,05/06/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/19/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +54094,61288,55644,Probation,VEGOTSKY,MOLLY,NULL,Female,Caucasian,05/06/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/19/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +54094,61288,55644,Probation,VEGOTSKY,MOLLY,NULL,Female,Caucasian,05/06/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54086,61278,55634,Probation,uragacastillo,stacy,NULL,Female,Hispanic,02/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/19/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +54086,61278,55634,Probation,uragacastillo,stacy,NULL,Female,Hispanic,02/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/19/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +54086,61278,55634,Probation,uragacastillo,stacy,NULL,Female,Hispanic,02/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54088,61280,55636,Probation,MAXIME,MANOUCHKA,F,Female,African-American,04/24/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/19/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +54088,61280,55636,Probation,MAXIME,MANOUCHKA,F,Female,African-American,04/24/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +54088,61280,55636,Probation,MAXIME,MANOUCHKA,F,Female,African-American,04/24/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/19/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54074,61265,55621,PRETRIAL,Burgess,Dorothy,NULL,Female,African-American,07/30/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/19/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +54074,61265,55621,PRETRIAL,Burgess,Dorothy,NULL,Female,African-American,07/30/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/19/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +54074,61265,55621,PRETRIAL,Burgess,Dorothy,NULL,Female,African-American,07/30/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54080,61272,55628,PRETRIAL,Martin,Louine,NULL,Male,African-American,09/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.34,3,Low,New,1,0 +54080,61272,55628,PRETRIAL,Martin,Louine,NULL,Male,African-American,09/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +54080,61272,55628,PRETRIAL,Martin,Louine,NULL,Male,African-American,09/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54092,61286,55642,PRETRIAL,Middleton,Raynard,NULL,Male,African-American,10/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +54092,61286,55642,PRETRIAL,Middleton,Raynard,NULL,Male,African-American,10/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +54092,61286,55642,PRETRIAL,Middleton,Raynard,NULL,Male,African-American,10/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +48197,61257,55614,PRETRIAL,Ortiz,Joel,NULL,Male,Hispanic,06/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +48197,61257,55614,PRETRIAL,Ortiz,Joel,NULL,Male,Hispanic,06/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +48197,61257,55614,PRETRIAL,Ortiz,Joel,NULL,Male,Hispanic,06/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54068,61255,55612,PRETRIAL,Williams,Finest,NULL,Male,African-American,03/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,4,High,7,Risk of Violence,-0.38,10,High,New,1,0 +54068,61255,55612,PRETRIAL,Williams,Finest,NULL,Male,African-American,03/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,4,High,8,Risk of Recidivism,0.88,10,High,New,1,0 +54068,61255,55612,PRETRIAL,Williams,Finest,NULL,Male,African-American,03/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +6731,61260,55617,PRETRIAL,Rudolph,Ellis,NULL,Male,African-American,01/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/19/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +6731,61260,55617,PRETRIAL,Rudolph,Ellis,NULL,Male,African-American,01/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +6731,61260,55617,PRETRIAL,Rudolph,Ellis,NULL,Male,African-American,01/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/19/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54073,61264,55620,PRETRIAL,Moreno,Fernando,NULL,Male,Hispanic,04/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +54073,61264,55620,PRETRIAL,Moreno,Fernando,NULL,Male,Hispanic,04/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +54073,61264,55620,PRETRIAL,Moreno,Fernando,NULL,Male,Hispanic,04/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +29788,61281,55637,PRETRIAL,Daniel,Cyril,NULL,Male,African-American,07/11/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +29788,61281,55637,PRETRIAL,Daniel,Cyril,NULL,Male,African-American,07/11/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +29788,61281,55637,PRETRIAL,Daniel,Cyril,NULL,Male,African-American,07/11/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54078,61269,55625,PRETRIAL,States,Douglas,NULL,Male,Caucasian,01/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +54078,61269,55625,PRETRIAL,States,Douglas,NULL,Male,Caucasian,01/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +54078,61269,55625,PRETRIAL,States,Douglas,NULL,Male,Caucasian,01/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54076,61267,55623,PRETRIAL,Diaz,Maximo,NULL,Male,Caucasian,03/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +54076,61267,55623,PRETRIAL,Diaz,Maximo,NULL,Male,Caucasian,03/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +54076,61267,55623,PRETRIAL,Diaz,Maximo,NULL,Male,Caucasian,03/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54084,61276,55632,Probation,DAVIS,COURTNEY,TAVARIS,Male,African-American,01/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +54084,61276,55632,Probation,DAVIS,COURTNEY,TAVARIS,Male,African-American,01/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +54084,61276,55632,Probation,DAVIS,COURTNEY,TAVARIS,Male,African-American,01/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54095,61290,55646,PRETRIAL,Hall,Falisha,NULL,Female,African-American,12/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +54095,61290,55646,PRETRIAL,Hall,Falisha,NULL,Female,African-American,12/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,4,High,8,Risk of Recidivism,0.36,9,High,New,1,0 +54095,61290,55646,PRETRIAL,Hall,Falisha,NULL,Female,African-American,12/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54118,61325,55679,PRETRIAL,carvallo,vincent,NULL,Male,Caucasian,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +54118,61325,55679,PRETRIAL,carvallo,vincent,NULL,Male,Caucasian,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +54118,61325,55679,PRETRIAL,carvallo,vincent,NULL,Male,Caucasian,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54098,61297,55652,PRETRIAL,Rodney,Dobronozenk,NULL,Male,African-American,03/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +54098,61297,55652,PRETRIAL,Rodney,Dobronozenk,NULL,Male,African-American,03/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,8,Risk of Recidivism,1.14,10,High,New,1,0 +54098,61297,55652,PRETRIAL,Rodney,Dobronozenk,NULL,Male,African-American,03/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +33999,61304,55659,PRETRIAL,Francis,Dwight,Everton,Male,Other,07/07/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +33999,61304,55659,PRETRIAL,Francis,Dwight,Everton,Male,Other,07/07/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +33999,61304,55659,PRETRIAL,Francis,Dwight,Everton,Male,Other,07/07/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +29986,61311,55666,PRETRIAL,TARVER,KAMBREL,RASHAAD,Male,African-American,01/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,7,Risk of Violence,-0.25,10,High,New,1,0 +29986,61311,55666,PRETRIAL,TARVER,KAMBREL,RASHAAD,Male,African-American,01/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,8,Risk of Recidivism,0.73,10,High,New,1,0 +29986,61311,55666,PRETRIAL,TARVER,KAMBREL,RASHAAD,Male,African-American,01/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54112,61318,55673,PRETRIAL,Williams,Alvin,Jerome,Male,African-American,11/26/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +54112,61318,55673,PRETRIAL,Williams,Alvin,Jerome,Male,African-American,11/26/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +54112,61318,55673,PRETRIAL,Williams,Alvin,Jerome,Male,African-American,11/26/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +43301,47360,43228,PRETRIAL,Dwyer,Dwayne,NULL,Male,African-American,05/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.88,9,High,New,1,0 +43301,47360,43228,PRETRIAL,Dwyer,Dwayne,NULL,Male,African-American,05/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +43301,47360,43228,PRETRIAL,Dwyer,Dwayne,NULL,Male,African-American,05/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +4403,61306,55661,PRETRIAL,SIFUENTES,PAUL,NULL,Male,Caucasian,07/19/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +4403,61306,55661,PRETRIAL,SIFUENTES,PAUL,NULL,Male,Caucasian,07/19/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +4403,61306,55661,PRETRIAL,SIFUENTES,PAUL,NULL,Male,Caucasian,07/19/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54116,61323,55677,PRETRIAL,LYN,RUPERT,NULL,Male,African-American,06/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +54116,61323,55677,PRETRIAL,LYN,RUPERT,NULL,Male,African-American,06/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +54116,61323,55677,PRETRIAL,LYN,RUPERT,NULL,Male,African-American,06/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54101,61302,55657,PRETRIAL,Christie,Edgar,Keron,Male,African-American,09/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +54101,61302,55657,PRETRIAL,Christie,Edgar,Keron,Male,African-American,09/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +54101,61302,55657,PRETRIAL,Christie,Edgar,Keron,Male,African-American,09/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54114,61320,55675,PRETRIAL,MATTHEWS,KASHA,NULL,Female,African-American,06/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +54114,61320,55675,PRETRIAL,MATTHEWS,KASHA,NULL,Female,African-American,06/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,7,Medium,New,1,0 +54114,61320,55675,PRETRIAL,MATTHEWS,KASHA,NULL,Female,African-American,06/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54120,61327,55681,PRETRIAL,segal,matthew,NULL,Male,Caucasian,08/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +54120,61327,55681,PRETRIAL,segal,matthew,NULL,Male,Caucasian,08/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +54120,61327,55681,PRETRIAL,segal,matthew,NULL,Male,Caucasian,08/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54103,61307,55662,PRETRIAL,Boucher,Neil,NULL,Male,Caucasian,04/19/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +54103,61307,55662,PRETRIAL,Boucher,Neil,NULL,Male,Caucasian,04/19/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +54103,61307,55662,PRETRIAL,Boucher,Neil,NULL,Male,Caucasian,04/19/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54096,61293,55648,PRETRIAL,Smith,Ricoh,NULL,Male,African-American,01/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +54096,61293,55648,PRETRIAL,Smith,Ricoh,NULL,Male,African-American,01/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +54096,61293,55648,PRETRIAL,Smith,Ricoh,NULL,Male,African-American,01/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54115,61322,55676,PRETRIAL,CLAROS,SEBASTIAN,NULL,Male,Hispanic,04/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +54115,61322,55676,PRETRIAL,CLAROS,SEBASTIAN,NULL,Male,Hispanic,04/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +54115,61322,55676,PRETRIAL,CLAROS,SEBASTIAN,NULL,Male,Hispanic,04/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +18326,61299,55654,PRETRIAL,SILVERA,DAVION,NULL,Male,African-American,06/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +18326,61299,55654,PRETRIAL,SILVERA,DAVION,NULL,Male,African-American,06/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +18326,61299,55654,PRETRIAL,SILVERA,DAVION,NULL,Male,African-American,06/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +28290,61301,55656,PRETRIAL,Burrows,Patrick,NULL,Male,Caucasian,10/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/20/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +28290,61301,55656,PRETRIAL,Burrows,Patrick,NULL,Male,Caucasian,10/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/20/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +28290,61301,55656,PRETRIAL,Burrows,Patrick,NULL,Male,Caucasian,10/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +54108,61314,55669,PRETRIAL,Banton,Kadeem,NULL,Male,African-American,03/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +54108,61314,55669,PRETRIAL,Banton,Kadeem,NULL,Male,African-American,03/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +54108,61314,55669,PRETRIAL,Banton,Kadeem,NULL,Male,African-American,03/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +49422,61309,55664,PRETRIAL,Shazier,Lovett,NULL,Male,African-American,01/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/13 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +49422,61309,55664,PRETRIAL,Shazier,Lovett,NULL,Male,African-American,01/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +49422,61309,55664,PRETRIAL,Shazier,Lovett,NULL,Male,African-American,01/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54111,61317,55672,PRETRIAL,Ruddock,Shaka,NULL,Male,African-American,02/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +54111,61317,55672,PRETRIAL,Ruddock,Shaka,NULL,Male,African-American,02/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +54111,61317,55672,PRETRIAL,Ruddock,Shaka,NULL,Male,African-American,02/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54097,61296,55651,PRETRIAL,May,Jason,NULL,Male,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +54097,61296,55651,PRETRIAL,May,Jason,NULL,Male,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +54097,61296,55651,PRETRIAL,May,Jason,NULL,Male,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54123,61330,55684,PRETRIAL,Thompson,Anthony,NULL,Male,African-American,06/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,New,1,0 +54123,61330,55684,PRETRIAL,Thompson,Anthony,NULL,Male,African-American,06/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +54123,61330,55684,PRETRIAL,Thompson,Anthony,NULL,Male,African-American,06/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54117,61324,55678,PRETRIAL,caraveo,cedgar,NULL,Male,Hispanic,10/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +54117,61324,55678,PRETRIAL,caraveo,cedgar,NULL,Male,Hispanic,10/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +54117,61324,55678,PRETRIAL,caraveo,cedgar,NULL,Male,Hispanic,10/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54099,61298,55653,PRETRIAL,Vacca Ramirez,Juan,NULL,Male,Hispanic,09/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +54099,61298,55653,PRETRIAL,Vacca Ramirez,Juan,NULL,Male,Hispanic,09/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +54099,61298,55653,PRETRIAL,Vacca Ramirez,Juan,NULL,Male,Hispanic,09/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54109,61315,55670,PRETRIAL,Melbourne,George,NULL,Male,Caucasian,07/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +54109,61315,55670,PRETRIAL,Melbourne,George,NULL,Male,Caucasian,07/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +54109,61315,55670,PRETRIAL,Melbourne,George,NULL,Male,Caucasian,07/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +32226,61294,55649,PRETRIAL,Parker,Calvin,D,Male,African-American,03/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +32226,61294,55649,PRETRIAL,Parker,Calvin,D,Male,African-American,03/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +32226,61294,55649,PRETRIAL,Parker,Calvin,D,Male,African-American,03/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54113,61319,55674,PRETRIAL,Rose,Kemar,NULL,Male,Other,09/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +54113,61319,55674,PRETRIAL,Rose,Kemar,NULL,Male,Other,09/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +54113,61319,55674,PRETRIAL,Rose,Kemar,NULL,Male,Other,09/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54121,61328,55682,PRETRIAL,palmer,terence,NULL,Male,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,7,Risk of Violence,-2.63,2,Low,New,1,0 +54121,61328,55682,PRETRIAL,palmer,terence,NULL,Male,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +54121,61328,55682,PRETRIAL,palmer,terence,NULL,Male,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +40618,61303,55658,PRETRIAL,Philistin,Tanns,NULL,Male,African-American,06/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +40618,61303,55658,PRETRIAL,Philistin,Tanns,NULL,Male,African-American,06/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +40618,61303,55658,PRETRIAL,Philistin,Tanns,NULL,Male,African-American,06/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54102,61305,55660,PRETRIAL,Rogers,Quintavious,NULL,Male,African-American,05/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +54102,61305,55660,PRETRIAL,Rogers,Quintavious,NULL,Male,African-American,05/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +54102,61305,55660,PRETRIAL,Rogers,Quintavious,NULL,Male,African-American,05/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54105,61310,55665,PRETRIAL,Ferdinand,Jude,NULL,Male,African-American,06/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +54105,61310,55665,PRETRIAL,Ferdinand,Jude,NULL,Male,African-American,06/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +54105,61310,55665,PRETRIAL,Ferdinand,Jude,NULL,Male,African-American,06/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54106,61312,55667,PRETRIAL,Biasucci,Michael,NULL,Male,Caucasian,02/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +54106,61312,55667,PRETRIAL,Biasucci,Michael,NULL,Male,Caucasian,02/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +54106,61312,55667,PRETRIAL,Biasucci,Michael,NULL,Male,Caucasian,02/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54119,61326,55680,PRETRIAL,carvallo,daniel,NULL,Male,Caucasian,07/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +54119,61326,55680,PRETRIAL,carvallo,daniel,NULL,Male,Caucasian,07/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +54119,61326,55680,PRETRIAL,carvallo,daniel,NULL,Male,Caucasian,07/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54122,61329,55683,PRETRIAL,CASH,LEROY,JOSE,Male,Caucasian,04/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +54122,61329,55683,PRETRIAL,CASH,LEROY,JOSE,Male,Caucasian,04/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +54122,61329,55683,PRETRIAL,CASH,LEROY,JOSE,Male,Caucasian,04/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54104,61308,55663,PRETRIAL,Benamor,Ilyess,NULL,Male,Other,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +54104,61308,55663,PRETRIAL,Benamor,Ilyess,NULL,Male,Other,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +54104,61308,55663,PRETRIAL,Benamor,Ilyess,NULL,Male,Other,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54110,61316,55671,PRETRIAL,Bechina,Brandon,NULL,Male,Caucasian,08/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +54110,61316,55671,PRETRIAL,Bechina,Brandon,NULL,Male,Caucasian,08/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,8,Risk of Recidivism,0.93,10,High,New,1,0 +54110,61316,55671,PRETRIAL,Bechina,Brandon,NULL,Male,Caucasian,08/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +13747,61295,55650,PRETRIAL,HAMILTON,DEMETRICE,NULL,Male,African-American,11/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +13747,61295,55650,PRETRIAL,HAMILTON,DEMETRICE,NULL,Male,African-American,11/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +13747,61295,55650,PRETRIAL,HAMILTON,DEMETRICE,NULL,Male,African-American,11/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54107,61313,55668,PRETRIAL,Haggains,Kenneth,NULL,Male,African-American,04/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +54107,61313,55668,PRETRIAL,Haggains,Kenneth,NULL,Male,African-American,04/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +54107,61313,55668,PRETRIAL,Haggains,Kenneth,NULL,Male,African-American,04/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54100,61300,55655,PRETRIAL,Sanchez,Gustavo,NULL,Male,Caucasian,11/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +54100,61300,55655,PRETRIAL,Sanchez,Gustavo,NULL,Male,Caucasian,11/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +54100,61300,55655,PRETRIAL,Sanchez,Gustavo,NULL,Male,Caucasian,11/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +43301,61321,43228,PRETRIAL,Dwyer,Dwayne,NULL,Male,African-American,05/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,Copy,1,0 +43301,61321,43228,PRETRIAL,Dwyer,Dwayne,NULL,Male,African-American,05/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +43301,61321,43228,PRETRIAL,Dwyer,Dwayne,NULL,Male,African-American,05/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +54125,61334,55688,PRETRIAL,Sanchez,Luis,NULL,Male,Hispanic,10/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +54125,61334,55688,PRETRIAL,Sanchez,Luis,NULL,Male,Hispanic,10/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +54125,61334,55688,PRETRIAL,Sanchez,Luis,NULL,Male,Hispanic,10/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54132,61342,55696,PRETRIAL,Walker,Jontavis,NULL,Male,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +54132,61342,55696,PRETRIAL,Walker,Jontavis,NULL,Male,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,4,High,8,Risk of Recidivism,0.25,8,High,New,1,0 +54132,61342,55696,PRETRIAL,Walker,Jontavis,NULL,Male,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54128,61337,55691,PRETRIAL,Vanzant,Tyra,NULL,Female,Caucasian,10/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +54128,61337,55691,PRETRIAL,Vanzant,Tyra,NULL,Female,Caucasian,10/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +54128,61337,55691,PRETRIAL,Vanzant,Tyra,NULL,Female,Caucasian,10/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54127,61336,55690,PRETRIAL,SAWYER,JUANITA,SHINNIKA,Female,African-American,05/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,New,1,0 +54127,61336,55690,PRETRIAL,SAWYER,JUANITA,SHINNIKA,Female,African-American,05/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,8,High,New,1,0 +54127,61336,55690,PRETRIAL,SAWYER,JUANITA,SHINNIKA,Female,African-American,05/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +31396,61340,55694,PRETRIAL,COLLINS,SHAKERA,K,Female,African-American,10/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +31396,61340,55694,PRETRIAL,COLLINS,SHAKERA,K,Female,African-American,10/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,4,High,8,Risk of Recidivism,0.07,8,High,New,1,0 +31396,61340,55694,PRETRIAL,COLLINS,SHAKERA,K,Female,African-American,10/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54124,61331,55685,PRETRIAL,Wallace,Jamie,NULL,Male,African-American,03/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +54124,61331,55685,PRETRIAL,Wallace,Jamie,NULL,Male,African-American,03/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +54124,61331,55685,PRETRIAL,Wallace,Jamie,NULL,Male,African-American,03/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +48248,61333,55687,PRETRIAL,Davis,Crystal,Ann,Female,African-American,12/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +48248,61333,55687,PRETRIAL,Davis,Crystal,Ann,Female,African-American,12/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,New,1,0 +48248,61333,55687,PRETRIAL,Davis,Crystal,Ann,Female,African-American,12/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54129,61338,55692,PRETRIAL,Lawson,Philip,NULL,Male,Caucasian,04/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +54129,61338,55692,PRETRIAL,Lawson,Philip,NULL,Male,Caucasian,04/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +54129,61338,55692,PRETRIAL,Lawson,Philip,NULL,Male,Caucasian,04/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54126,61335,55689,PRETRIAL,Johnson,Carlton,NULL,Male,African-American,04/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +54126,61335,55689,PRETRIAL,Johnson,Carlton,NULL,Male,African-American,04/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +54126,61335,55689,PRETRIAL,Johnson,Carlton,NULL,Male,African-American,04/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52304,61343,55697,PRETRIAL,jackson,deon,NULL,Male,African-American,10/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,4,High,7,Risk of Violence,-0.64,9,High,New,1,0 +52304,61343,55697,PRETRIAL,jackson,deon,NULL,Male,African-American,10/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,4,High,8,Risk of Recidivism,0.84,10,High,New,1,0 +52304,61343,55697,PRETRIAL,jackson,deon,NULL,Male,African-American,10/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54131,61341,55695,PRETRIAL,Jeff,Myesha,NULL,Female,African-American,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +54131,61341,55695,PRETRIAL,Jeff,Myesha,NULL,Female,African-American,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,8,High,New,1,0 +54131,61341,55695,PRETRIAL,Jeff,Myesha,NULL,Female,African-American,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +49179,61332,55686,PRETRIAL,BLAUMAN,THOMAS,EDWARD,Male,Caucasian,08/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +49179,61332,55686,PRETRIAL,BLAUMAN,THOMAS,EDWARD,Male,Caucasian,08/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +49179,61332,55686,PRETRIAL,BLAUMAN,THOMAS,EDWARD,Male,Caucasian,08/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54130,61339,55693,PRETRIAL,Coronell,Yonnatan,NULL,Male,Hispanic,08/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/21/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +54130,61339,55693,PRETRIAL,Coronell,Yonnatan,NULL,Male,Hispanic,08/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/21/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +54130,61339,55693,PRETRIAL,Coronell,Yonnatan,NULL,Male,Hispanic,08/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54158,61376,55726,Probation,mansfield,marquisha,NULL,Female,African-American,11/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,New,1,0 +54158,61376,55726,Probation,mansfield,marquisha,NULL,Female,African-American,11/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,8,High,New,1,0 +54158,61376,55726,Probation,mansfield,marquisha,NULL,Female,African-American,11/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54136,61348,55702,PRETRIAL,Cardona,Freddy,NULL,Male,Caucasian,02/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/22/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +54136,61348,55702,PRETRIAL,Cardona,Freddy,NULL,Male,Caucasian,02/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/22/13 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +54136,61348,55702,PRETRIAL,Cardona,Freddy,NULL,Male,Caucasian,02/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54150,61367,55718,PRETRIAL,Eisner,Shane,E,Male,Caucasian,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +54150,61367,55718,PRETRIAL,Eisner,Shane,E,Male,Caucasian,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +54150,61367,55718,PRETRIAL,Eisner,Shane,E,Male,Caucasian,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +54135,61346,55700,PRETRIAL,Jones,Sheldon,Oniel,Male,African-American,05/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/22/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +54135,61346,55700,PRETRIAL,Jones,Sheldon,Oniel,Male,African-American,05/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +54135,61346,55700,PRETRIAL,Jones,Sheldon,Oniel,Male,African-American,05/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54151,61369,55719,Probation,brown,alex,NULL,Male,African-American,12/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +54151,61369,55719,Probation,brown,alex,NULL,Male,African-American,12/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +54151,61369,55719,Probation,brown,alex,NULL,Male,African-American,12/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54163,61383,55732,Probation,burton,exavier,NULL,Male,African-American,08/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +54163,61383,55732,Probation,burton,exavier,NULL,Male,African-American,08/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.88,10,High,New,1,0 +54163,61383,55732,Probation,burton,exavier,NULL,Male,African-American,08/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54140,61353,55707,Probation,Sanrana,Rene,NULL,Male,Hispanic,01/12/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/22/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +54140,61353,55707,Probation,Sanrana,Rene,NULL,Male,Hispanic,01/12/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +54140,61353,55707,Probation,Sanrana,Rene,NULL,Male,Hispanic,01/12/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54146,61362,55714,Probation,perry,bennie,NULL,Male,Caucasian,05/23/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/22/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +54146,61362,55714,Probation,perry,bennie,NULL,Male,Caucasian,05/23/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +54146,61362,55714,Probation,perry,bennie,NULL,Male,Caucasian,05/23/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54156,61374,55724,Probation,capote,michael,NULL,Male,Caucasian,07/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +54156,61374,55724,Probation,capote,michael,NULL,Male,Caucasian,07/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +54156,61374,55724,Probation,capote,michael,NULL,Male,Caucasian,07/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54165,61388,55735,PRETRIAL,MCGIRT,DERICKY,NULL,Male,African-American,09/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +54165,61388,55735,PRETRIAL,MCGIRT,DERICKY,NULL,Male,African-American,09/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,4,High,8,Risk of Recidivism,0.22,8,High,New,1,0 +54165,61388,55735,PRETRIAL,MCGIRT,DERICKY,NULL,Male,African-American,09/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +13596,61380,55730,PRETRIAL,linares,luis,NULL,Male,Hispanic,12/30/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +13596,61380,55730,PRETRIAL,linares,luis,NULL,Male,Hispanic,12/30/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +13596,61380,55730,PRETRIAL,linares,luis,NULL,Male,Hispanic,12/30/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +42909,61356,55709,PRETRIAL,Rodriguez,Natassia,NULL,Female,Hispanic,04/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +42909,61356,55709,PRETRIAL,Rodriguez,Natassia,NULL,Female,Hispanic,04/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +42909,61356,55709,PRETRIAL,Rodriguez,Natassia,NULL,Female,Hispanic,04/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54144,61359,55712,Probation,OCONNOR,SHANNON,SCOTT,Female,Caucasian,11/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +54144,61359,55712,Probation,OCONNOR,SHANNON,SCOTT,Female,Caucasian,11/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +54144,61359,55712,Probation,OCONNOR,SHANNON,SCOTT,Female,Caucasian,11/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54148,61364,55716,PRETRIAL,ESCOBAR,JOSE,NULL,Male,Hispanic,03/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +54148,61364,55716,PRETRIAL,ESCOBAR,JOSE,NULL,Male,Hispanic,03/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +54148,61364,55716,PRETRIAL,ESCOBAR,JOSE,NULL,Male,Hispanic,03/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54138,61351,55705,PRETRIAL,McHelen,James,NULL,Male,African-American,07/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +54138,61351,55705,PRETRIAL,McHelen,James,NULL,Male,African-American,07/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +54138,61351,55705,PRETRIAL,McHelen,James,NULL,Male,African-American,07/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54161,61382,55731,PRETRIAL,JOHNSON,RONALD,NULL,Male,African-American,07/30/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +54161,61382,55731,PRETRIAL,JOHNSON,RONALD,NULL,Male,African-American,07/30/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +54161,61382,55731,PRETRIAL,JOHNSON,RONALD,NULL,Male,African-American,07/30/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +54162,61384,55733,Probation,Hutchins,William,Vincent,Male,Caucasian,10/23/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +54162,61384,55733,Probation,Hutchins,William,Vincent,Male,Caucasian,10/23/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +54162,61384,55733,Probation,Hutchins,William,Vincent,Male,Caucasian,10/23/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54157,61375,55725,Probation,Aman,Donavan,NULL,Male,African-American,11/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +54157,61375,55725,Probation,Aman,Donavan,NULL,Male,African-American,11/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +54157,61375,55725,Probation,Aman,Donavan,NULL,Male,African-American,11/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50653,61347,55701,PRETRIAL,GUEVARA,JUAN,P,Male,Caucasian,10/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +50653,61347,55701,PRETRIAL,GUEVARA,JUAN,P,Male,Caucasian,10/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +50653,61347,55701,PRETRIAL,GUEVARA,JUAN,P,Male,Caucasian,10/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53208,61361,54653,Probation,silvaurresti,sergio,NULL,Male,Caucasian,08/30/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,Copy,1,0 +53208,61361,54653,Probation,silvaurresti,sergio,NULL,Male,Caucasian,08/30/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,Copy,1,0 +53208,61361,54653,Probation,silvaurresti,sergio,NULL,Male,Caucasian,08/30/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +54164,61387,55734,PRETRIAL,SAINVIL,EVANS,NULL,Male,African-American,05/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,New,1,0 +54164,61387,55734,PRETRIAL,SAINVIL,EVANS,NULL,Male,African-American,05/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +54164,61387,55734,PRETRIAL,SAINVIL,EVANS,NULL,Male,African-American,05/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +31075,61349,55703,PRETRIAL,maywa,nakiea,NULL,Male,African-American,01/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +31075,61349,55703,PRETRIAL,maywa,nakiea,NULL,Male,African-American,01/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +31075,61349,55703,PRETRIAL,maywa,nakiea,NULL,Male,African-American,01/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53207,61366,54652,Probation,Phillips,Jessica,NULL,Female,African-American,10/25/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +53207,61366,54652,Probation,Phillips,Jessica,NULL,Female,African-American,10/25/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +53207,61366,54652,Probation,Phillips,Jessica,NULL,Female,African-American,10/25/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54134,61345,55699,PRETRIAL,GOMEZ,JOSHUA,DAVID,Male,Caucasian,12/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +54134,61345,55699,PRETRIAL,GOMEZ,JOSHUA,DAVID,Male,Caucasian,12/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +54134,61345,55699,PRETRIAL,GOMEZ,JOSHUA,DAVID,Male,Caucasian,12/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54152,61370,55720,PRETRIAL,Eugene,Lefort,NULL,Male,African-American,03/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +54152,61370,55720,PRETRIAL,Eugene,Lefort,NULL,Male,African-American,03/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/13 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +54152,61370,55720,PRETRIAL,Eugene,Lefort,NULL,Male,African-American,03/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54160,61379,55729,Probation,Rodriguez,Christopher,NULL,Male,Hispanic,02/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +54160,61379,55729,Probation,Rodriguez,Christopher,NULL,Male,Hispanic,02/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +54160,61379,55729,Probation,Rodriguez,Christopher,NULL,Male,Hispanic,02/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +23755,61386,54526,Probation,Saldana,Karl,NULL,Male,Hispanic,12/26/59,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,4/22/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,Copy,1,0 +23755,61386,54526,Probation,Saldana,Karl,NULL,Male,Hispanic,12/26/59,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,4/22/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,Copy,1,0 +23755,61386,54526,Probation,Saldana,Karl,NULL,Male,Hispanic,12/26/59,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,2,Low,Copy,1,0 +54142,61357,55710,Probation,Stagnaro,Sidney,NULL,Male,Hispanic,03/07/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +54142,61357,55710,Probation,Stagnaro,Sidney,NULL,Male,Hispanic,03/07/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +54142,61357,55710,Probation,Stagnaro,Sidney,NULL,Male,Hispanic,03/07/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +54143,61358,55711,Probation,williams,steven,NULL,Male,African-American,05/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/22/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +54143,61358,55711,Probation,williams,steven,NULL,Male,African-American,05/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +54143,61358,55711,Probation,williams,steven,NULL,Male,African-American,05/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54133,61344,55698,PRETRIAL,JACKSON,ALFONSO,NULL,Male,African-American,12/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +54133,61344,55698,PRETRIAL,JACKSON,ALFONSO,NULL,Male,African-American,12/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +54133,61344,55698,PRETRIAL,JACKSON,ALFONSO,NULL,Male,African-American,12/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54153,61371,55721,Probation,HEEG,MARY,G,Female,Caucasian,08/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/22/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +54153,61371,55721,Probation,HEEG,MARY,G,Female,Caucasian,08/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +54153,61371,55721,Probation,HEEG,MARY,G,Female,Caucasian,08/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54159,61378,55728,Probation,Martin,Dominick,NULL,Male,African-American,12/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +54159,61378,55728,Probation,Martin,Dominick,NULL,Male,African-American,12/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +54159,61378,55728,Probation,Martin,Dominick,NULL,Male,African-American,12/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54137,61350,55704,PRETRIAL,Oktavec,Gregory,NULL,Male,Caucasian,01/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +54137,61350,55704,PRETRIAL,Oktavec,Gregory,NULL,Male,Caucasian,01/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +54137,61350,55704,PRETRIAL,Oktavec,Gregory,NULL,Male,Caucasian,01/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54155,61373,55723,PRETRIAL,Ford,Melody,NULL,Female,Caucasian,08/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.22,4,Low,New,1,0 +54155,61373,55723,PRETRIAL,Ford,Melody,NULL,Female,Caucasian,08/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,10,High,New,1,0 +54155,61373,55723,PRETRIAL,Ford,Melody,NULL,Female,Caucasian,08/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +54139,61352,55706,PRETRIAL,King,Larry,Ervin,Male,African-American,08/16/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/22/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +54139,61352,55706,PRETRIAL,King,Larry,Ervin,Male,African-American,08/16/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/22/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +54139,61352,55706,PRETRIAL,King,Larry,Ervin,Male,African-American,08/16/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54147,61363,55715,Probation,KAPLAN,BRETT,ALAN,Male,Caucasian,01/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +54147,61363,55715,Probation,KAPLAN,BRETT,ALAN,Male,Caucasian,01/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +54147,61363,55715,Probation,KAPLAN,BRETT,ALAN,Male,Caucasian,01/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +23755,61355,54526,Probation,Saldana,Karl,NULL,Male,Hispanic,12/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Divorced,4/22/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +23755,61355,54526,Probation,Saldana,Karl,NULL,Male,Hispanic,12/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Divorced,4/22/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +23755,61355,54526,Probation,Saldana,Karl,NULL,Male,Hispanic,12/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Divorced,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54145,61360,55713,PRETRIAL,SALVANT,FEDDY,NULL,Male,Other,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +54145,61360,55713,PRETRIAL,SALVANT,FEDDY,NULL,Male,Other,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +54145,61360,55713,PRETRIAL,SALVANT,FEDDY,NULL,Male,Other,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54166,61389,55736,PRETRIAL,Weekley,Kenneth,Eugene,Male,African-American,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +54166,61389,55736,PRETRIAL,Weekley,Kenneth,Eugene,Male,African-American,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,9,High,New,1,0 +54166,61389,55736,PRETRIAL,Weekley,Kenneth,Eugene,Male,African-American,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +36935,61394,55740,PRETRIAL,Wolfe,Taffi,NULL,Male,Other,11/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.22,8,High,New,1,0 +36935,61394,55740,PRETRIAL,Wolfe,Taffi,NULL,Male,Other,11/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +36935,61394,55740,PRETRIAL,Wolfe,Taffi,NULL,Male,Other,11/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54181,61415,55758,PRETRIAL,Bunton,Terri,NULL,Female,Caucasian,03/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/23/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +54181,61415,55758,PRETRIAL,Bunton,Terri,NULL,Female,Caucasian,03/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/23/13 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +54181,61415,55758,PRETRIAL,Bunton,Terri,NULL,Female,Caucasian,03/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +54173,61402,55747,PRETRIAL,Martin,Jason,NULL,Male,African-American,07/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +54173,61402,55747,PRETRIAL,Martin,Jason,NULL,Male,African-American,07/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +54173,61402,55747,PRETRIAL,Martin,Jason,NULL,Male,African-American,07/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +12368,61420,53056,PRETRIAL,SIMMON,TERRON,NULL,Male,African-American,01/27/86,17,All Scales,Intake,English,Pretrial,Probation,Single,4/23/13 0:00,4,High,7,Risk of Violence,-0.78,9,High,Copy,1,0 +12368,61420,53056,PRETRIAL,SIMMON,TERRON,NULL,Male,African-American,01/27/86,17,All Scales,Intake,English,Pretrial,Probation,Single,4/23/13 0:00,4,High,8,Risk of Recidivism,0.93,10,High,Copy,1,0 +12368,61420,53056,PRETRIAL,SIMMON,TERRON,NULL,Male,African-American,01/27/86,17,All Scales,Intake,English,Pretrial,Probation,Single,4/23/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +1561,61399,55745,PRETRIAL,SEMPER,SAMUELS,D,Male,African-American,11/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +1561,61399,55745,PRETRIAL,SEMPER,SAMUELS,D,Male,African-American,11/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +1561,61399,55745,PRETRIAL,SEMPER,SAMUELS,D,Male,African-American,11/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54177,61407,55752,Probation,Meridien,Linda,NULL,Female,African-American,02/10/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/23/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +54177,61407,55752,Probation,Meridien,Linda,NULL,Female,African-American,02/10/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/23/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +54177,61407,55752,Probation,Meridien,Linda,NULL,Female,African-American,02/10/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54167,61391,55737,PRETRIAL,MARCELIN,RONALD,NULL,Male,African-American,11/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +54167,61391,55737,PRETRIAL,MARCELIN,RONALD,NULL,Male,African-American,11/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +54167,61391,55737,PRETRIAL,MARCELIN,RONALD,NULL,Male,African-American,11/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54182,61417,55759,Probation,kalb,lauren,NULL,Female,Caucasian,06/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.79,2,Low,New,1,0 +54182,61417,55759,Probation,kalb,lauren,NULL,Female,Caucasian,06/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +54182,61417,55759,Probation,kalb,lauren,NULL,Female,Caucasian,06/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +27494,61396,55742,PRETRIAL,SMART,JAMAL,NULL,Male,African-American,07/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +27494,61396,55742,PRETRIAL,SMART,JAMAL,NULL,Male,African-American,07/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.43,10,High,New,1,0 +27494,61396,55742,PRETRIAL,SMART,JAMAL,NULL,Male,African-American,07/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +42731,46645,42589,Probation,BASTANTE,ALEXANDRA,F,Female,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +42731,46645,42589,Probation,BASTANTE,ALEXANDRA,F,Female,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +42731,46645,42589,Probation,BASTANTE,ALEXANDRA,F,Female,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54188,61426,55767,PRETRIAL,MCCALL,JEMEIL,NULL,Female,African-American,04/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +54188,61426,55767,PRETRIAL,MCCALL,JEMEIL,NULL,Female,African-American,04/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +54188,61426,55767,PRETRIAL,MCCALL,JEMEIL,NULL,Female,African-American,04/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54174,61403,55748,Probation,McCarthy,Heather,NULL,Female,Caucasian,11/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +54174,61403,55748,Probation,McCarthy,Heather,NULL,Female,Caucasian,11/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +54174,61403,55748,Probation,McCarthy,Heather,NULL,Female,Caucasian,11/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54175,61405,55750,Probation,rodriguez,german,NULL,Male,Hispanic,08/31/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/23/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +54175,61405,55750,Probation,rodriguez,german,NULL,Male,Hispanic,08/31/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/23/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +54175,61405,55750,Probation,rodriguez,german,NULL,Male,Hispanic,08/31/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +13625,61410,55754,Probation,gonzales,miguel,NULL,Male,Other,07/06/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +13625,61410,55754,Probation,gonzales,miguel,NULL,Male,Other,07/06/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +13625,61410,55754,Probation,gonzales,miguel,NULL,Male,Other,07/06/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54179,61412,55755,Probation,TIMPY,KEVIN,C,Male,Caucasian,06/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/23/13 0:00,1,Low,7,Risk of Violence,-4.36,1,Low,New,1,0 +54179,61412,55755,Probation,TIMPY,KEVIN,C,Male,Caucasian,06/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/23/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +54179,61412,55755,Probation,TIMPY,KEVIN,C,Male,Caucasian,06/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54171,61398,55744,PRETRIAL,Rodney,Scott,Kevin,Male,Caucasian,10/01/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/23/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +54171,61398,55744,PRETRIAL,Rodney,Scott,Kevin,Male,Caucasian,10/01/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/23/13 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +54171,61398,55744,PRETRIAL,Rodney,Scott,Kevin,Male,Caucasian,10/01/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53624,61419,55761,PRETRIAL,SAINTJEAN,GEORGE,NULL,Male,African-American,09/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/13 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +53624,61419,55761,PRETRIAL,SAINTJEAN,GEORGE,NULL,Male,African-American,09/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/13 0:00,1,Low,8,Risk of Recidivism,-2.6,1,Low,New,1,0 +53624,61419,55761,PRETRIAL,SAINTJEAN,GEORGE,NULL,Male,African-American,09/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54176,61406,55751,Probation,SADOWSKI,CHRISTIE,NULL,Female,Caucasian,03/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +54176,61406,55751,Probation,SADOWSKI,CHRISTIE,NULL,Female,Caucasian,03/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +54176,61406,55751,Probation,SADOWSKI,CHRISTIE,NULL,Female,Caucasian,03/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +29382,61414,55757,PRETRIAL,Porter,Juan,Antonio,Male,African-American,03/12/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/23/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +29382,61414,55757,PRETRIAL,Porter,Juan,Antonio,Male,African-American,03/12/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +29382,61414,55757,PRETRIAL,Porter,Juan,Antonio,Male,African-American,03/12/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/23/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +47256,61401,47779,PRETRIAL,Carter,Jeffrey,NULL,Male,Caucasian,12/04/63,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/23/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +47256,61401,47779,PRETRIAL,Carter,Jeffrey,NULL,Male,Caucasian,12/04/63,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/23/13 0:00,1,Low,8,Risk of Recidivism,-0.96,2,Low,New,1,0 +47256,61401,47779,PRETRIAL,Carter,Jeffrey,NULL,Male,Caucasian,12/04/63,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,2,Low,New,1,0 +39783,61416,39334,PRETRIAL,Montooth,Jesse,Dean,Male,Caucasian,11/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,Copy,1,0 +39783,61416,39334,PRETRIAL,Montooth,Jesse,Dean,Male,Caucasian,11/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,Copy,1,0 +39783,61416,39334,PRETRIAL,Montooth,Jesse,Dean,Male,Caucasian,11/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +54168,61393,55739,PRETRIAL,Williams,Salvatoris,David,Female,African-American,07/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +54168,61393,55739,PRETRIAL,Williams,Salvatoris,David,Female,African-American,07/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +54168,61393,55739,PRETRIAL,Williams,Salvatoris,David,Female,African-American,07/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54184,61422,55763,Probation,Mayorquin- Tellez,Jose,Martin,Male,Hispanic,10/17/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/23/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +54184,61422,55763,Probation,Mayorquin- Tellez,Jose,Martin,Male,Hispanic,10/17/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/23/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +54184,61422,55763,Probation,Mayorquin- Tellez,Jose,Martin,Male,Hispanic,10/17/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54169,61395,55741,PRETRIAL,Chatman,Jarvis,NULL,Male,African-American,07/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +54169,61395,55741,PRETRIAL,Chatman,Jarvis,NULL,Male,African-American,07/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +54169,61395,55741,PRETRIAL,Chatman,Jarvis,NULL,Male,African-American,07/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54180,61413,55756,PRETRIAL,DARLING,ALAN,NULL,Male,Caucasian,02/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/23/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +54180,61413,55756,PRETRIAL,DARLING,ALAN,NULL,Male,Caucasian,02/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/23/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +54180,61413,55756,PRETRIAL,DARLING,ALAN,NULL,Male,Caucasian,02/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +30613,61392,55738,PRETRIAL,WELLS,JABARI,NULL,Male,African-American,08/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +30613,61392,55738,PRETRIAL,WELLS,JABARI,NULL,Male,African-American,08/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +30613,61392,55738,PRETRIAL,WELLS,JABARI,NULL,Male,African-American,08/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +2067,10434,1775,PRETRIAL,DIXON,NICOLA,TANYA,Female,African-American,04/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,Copy,1,0 +2067,10434,1775,PRETRIAL,DIXON,NICOLA,TANYA,Female,African-American,04/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,8,High,Copy,1,0 +2067,10434,1775,PRETRIAL,DIXON,NICOLA,TANYA,Female,African-American,04/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +54183,61418,55760,Probation,wasserman-rubin,diana,NULL,Female,Hispanic,02/11/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/23/13 0:00,1,Low,7,Risk of Violence,-4.27,1,Low,New,1,0 +54183,61418,55760,Probation,wasserman-rubin,diana,NULL,Female,Hispanic,02/11/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/23/13 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +54183,61418,55760,Probation,wasserman-rubin,diana,NULL,Female,Hispanic,02/11/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52739,61390,54113,PRETRIAL,VAVAL,BRADLEY,JORDAN,Male,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,Copy,1,0 +52739,61390,54113,PRETRIAL,VAVAL,BRADLEY,JORDAN,Male,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.29,6,Medium,Copy,1,0 +52739,61390,54113,PRETRIAL,VAVAL,BRADLEY,JORDAN,Male,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +54187,61425,55766,Probation,LOISY,BRANDON,MORGAN,Male,African-American,02/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +54187,61425,55766,Probation,LOISY,BRANDON,MORGAN,Male,African-American,02/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +54187,61425,55766,Probation,LOISY,BRANDON,MORGAN,Male,African-American,02/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54170,61397,55743,PRETRIAL,MARTIN,REGINALD,NULL,Male,African-American,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +54170,61397,55743,PRETRIAL,MARTIN,REGINALD,NULL,Male,African-American,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +54170,61397,55743,PRETRIAL,MARTIN,REGINALD,NULL,Male,African-American,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +34340,61404,55749,Probation,flores,alexander,NULL,Male,Hispanic,05/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/23/13 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +34340,61404,55749,Probation,flores,alexander,NULL,Male,Hispanic,05/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +34340,61404,55749,Probation,flores,alexander,NULL,Male,Hispanic,05/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/23/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +53767,61411,55248,PRETRIAL,Roberts,Chantel,NULL,Female,African-American,06/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,Copy,1,0 +53767,61411,55248,PRETRIAL,Roberts,Chantel,NULL,Female,African-American,06/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/13 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,Copy,1,0 +53767,61411,55248,PRETRIAL,Roberts,Chantel,NULL,Female,African-American,06/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +54219,61476,55808,PRETRIAL,Murphy,Jean,NULL,Female,Caucasian,02/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +54219,61476,55808,PRETRIAL,Murphy,Jean,NULL,Female,Caucasian,02/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +54219,61476,55808,PRETRIAL,Murphy,Jean,NULL,Female,Caucasian,02/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +54204,61448,55786,Probation,Bankston,Stevell,NULL,Male,African-American,05/10/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +54204,61448,55786,Probation,Bankston,Stevell,NULL,Male,African-American,05/10/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +54204,61448,55786,Probation,Bankston,Stevell,NULL,Male,African-American,05/10/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54214,61467,55799,PRETRIAL,HOLLOMAN,RIONNE,DEVONTE,Male,African-American,01/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +54214,61467,55799,PRETRIAL,HOLLOMAN,RIONNE,DEVONTE,Male,African-American,01/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +54214,61467,55799,PRETRIAL,HOLLOMAN,RIONNE,DEVONTE,Male,African-American,01/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54196,61439,55778,PRETRIAL,WALLACE,OMAR,NATHANIEL,Male,African-American,07/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.22,4,Low,New,1,0 +54196,61439,55778,PRETRIAL,WALLACE,OMAR,NATHANIEL,Male,African-American,07/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +54196,61439,55778,PRETRIAL,WALLACE,OMAR,NATHANIEL,Male,African-American,07/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +5548,61446,5199,PRETRIAL,PRESTON,LADSON JR.,MARVIN,Male,African-American,06/07/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,Copy,1,0 +5548,61446,5199,PRETRIAL,PRESTON,LADSON JR.,MARVIN,Male,African-American,06/07/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,Copy,1,0 +5548,61446,5199,PRETRIAL,PRESTON,LADSON JR.,MARVIN,Male,African-American,06/07/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,2,Medium,18,Risk of Failure to Appear,28,7,Medium,Copy,1,0 +54215,61469,55801,PRETRIAL,Echevarria,Nathaniel,Omar,Male,Hispanic,01/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +54215,61469,55801,PRETRIAL,Echevarria,Nathaniel,Omar,Male,Hispanic,01/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,8,Risk of Recidivism,1.02,10,High,New,1,0 +54215,61469,55801,PRETRIAL,Echevarria,Nathaniel,Omar,Male,Hispanic,01/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54210,61460,55794,Probation,Prieto,Mihahil,NULL,Male,Hispanic,09/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +54210,61460,55794,Probation,Prieto,Mihahil,NULL,Male,Hispanic,09/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +54210,61460,55794,Probation,Prieto,Mihahil,NULL,Male,Hispanic,09/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54190,61430,55771,PRETRIAL,seymore,john,NULL,Male,African-American,11/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.47,3,Low,New,1,0 +54190,61430,55771,PRETRIAL,seymore,john,NULL,Male,African-American,11/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +54190,61430,55771,PRETRIAL,seymore,john,NULL,Male,African-American,11/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +54208,61455,55791,PRETRIAL,PARKER,ALEXIS,NULL,Female,African-American,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,2,Medium,7,Risk of Violence,-1.26,7,Medium,New,1,0 +54208,61455,55791,PRETRIAL,PARKER,ALEXIS,NULL,Female,African-American,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +54208,61455,55791,PRETRIAL,PARKER,ALEXIS,NULL,Female,African-American,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54213,61464,55797,PRETRIAL,MCCARTHY,ADAM,NULL,Male,African-American,10/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +54213,61464,55797,PRETRIAL,MCCARTHY,ADAM,NULL,Male,African-American,10/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +54213,61464,55797,PRETRIAL,MCCARTHY,ADAM,NULL,Male,African-American,10/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54192,61434,55773,PRETRIAL,Herrington,Aajah,NULL,Female,African-American,06/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +54192,61434,55773,PRETRIAL,Herrington,Aajah,NULL,Female,African-American,06/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +54192,61434,55773,PRETRIAL,Herrington,Aajah,NULL,Female,African-American,06/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +46417,61451,46830,PRETRIAL,GILLYARD,JAMEEL,NULL,Male,African-American,01/22/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +46417,61451,46830,PRETRIAL,GILLYARD,JAMEEL,NULL,Male,African-American,01/22/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,2,Medium,8,Risk of Recidivism,0.14,7,Medium,New,1,0 +46417,61451,46830,PRETRIAL,GILLYARD,JAMEEL,NULL,Male,African-American,01/22/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +50127,61429,55770,PRETRIAL,Nunnery,kevin,NULL,Male,African-American,01/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +50127,61429,55770,PRETRIAL,Nunnery,kevin,NULL,Male,African-American,01/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +50127,61429,55770,PRETRIAL,Nunnery,kevin,NULL,Male,African-American,01/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51450,61443,55782,PRETRIAL,HARRIS,TONY,DWAYNE,Male,African-American,06/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +51450,61443,55782,PRETRIAL,HARRIS,TONY,DWAYNE,Male,African-American,06/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +51450,61443,55782,PRETRIAL,HARRIS,TONY,DWAYNE,Male,African-American,06/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54209,61458,55792,PRETRIAL,Cruz,Kassandra,NULL,Female,Hispanic,08/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +54209,61458,55792,PRETRIAL,Cruz,Kassandra,NULL,Female,Hispanic,08/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +54209,61458,55792,PRETRIAL,Cruz,Kassandra,NULL,Female,Hispanic,08/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54193,61435,55774,PRETRIAL,Murphy,Sheena,Michelle,Female,African-American,07/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.62,2,Low,New,1,0 +54193,61435,55774,PRETRIAL,Murphy,Sheena,Michelle,Female,African-American,07/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,8,High,New,1,0 +54193,61435,55774,PRETRIAL,Murphy,Sheena,Michelle,Female,African-American,07/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54203,61450,55788,Probation,nikiforova,olga,NULL,Female,Caucasian,11/26/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +54203,61450,55788,Probation,nikiforova,olga,NULL,Female,Caucasian,11/26/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +54203,61450,55788,Probation,nikiforova,olga,NULL,Female,Caucasian,11/26/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54195,61437,55776,PRETRIAL,Fuller,Jason,Anthony,Male,African-American,11/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +54195,61437,55776,PRETRIAL,Fuller,Jason,Anthony,Male,African-American,11/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +54195,61437,55776,PRETRIAL,Fuller,Jason,Anthony,Male,African-American,11/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +43578,61474,55806,PRETRIAL,Vargas,Luis,NULL,Male,Hispanic,08/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +43578,61474,55806,PRETRIAL,Vargas,Luis,NULL,Male,Hispanic,08/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +43578,61474,55806,PRETRIAL,Vargas,Luis,NULL,Male,Hispanic,08/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54189,61427,55768,PRETRIAL,Reynolds,Jasmine,NULL,Female,African-American,04/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +54189,61427,55768,PRETRIAL,Reynolds,Jasmine,NULL,Female,African-American,04/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +54189,61427,55768,PRETRIAL,Reynolds,Jasmine,NULL,Female,African-American,04/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +30818,61432,52047,PRETRIAL,MCREED,JONATHAN,NULL,Male,African-American,05/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,Copy,1,0 +30818,61432,52047,PRETRIAL,MCREED,JONATHAN,NULL,Male,African-American,05/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,Copy,1,0 +30818,61432,52047,PRETRIAL,MCREED,JONATHAN,NULL,Male,African-American,05/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +53689,61466,55160,PRETRIAL,Winkelmann,William,NULL,Male,Caucasian,12/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,Copy,1,0 +53689,61466,55160,PRETRIAL,Winkelmann,William,NULL,Male,Caucasian,12/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,Copy,1,0 +53689,61466,55160,PRETRIAL,Winkelmann,William,NULL,Male,Caucasian,12/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +37805,61431,37207,PRETRIAL,Alavarez,Claudio,NULL,Male,Hispanic,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,7,Risk of Violence,-0.52,10,High,Copy,1,0 +37805,61431,37207,PRETRIAL,Alavarez,Claudio,NULL,Male,Hispanic,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,8,Risk of Recidivism,0.2,8,High,Copy,1,0 +37805,61431,37207,PRETRIAL,Alavarez,Claudio,NULL,Male,Hispanic,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +54191,61433,55772,PRETRIAL,Burns,Quanshonta,NULL,Male,African-American,05/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +54191,61433,55772,PRETRIAL,Burns,Quanshonta,NULL,Male,African-American,05/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +54191,61433,55772,PRETRIAL,Burns,Quanshonta,NULL,Male,African-American,05/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54197,61440,55779,PRETRIAL,Christil,Jerry,NULL,Male,African-American,09/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,7,Risk of Violence,-0.65,9,High,New,1,0 +54197,61440,55779,PRETRIAL,Christil,Jerry,NULL,Male,African-American,09/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +54197,61440,55779,PRETRIAL,Christil,Jerry,NULL,Male,African-American,09/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +40920,61475,55807,PRETRIAL,DAVIS,KERBY,NULL,Male,African-American,05/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +40920,61475,55807,PRETRIAL,DAVIS,KERBY,NULL,Male,African-American,05/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +40920,61475,55807,PRETRIAL,DAVIS,KERBY,NULL,Male,African-American,05/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54207,61454,55790,Probation,Wynn,David,NULL,Male,Caucasian,11/05/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +54207,61454,55790,Probation,Wynn,David,NULL,Male,Caucasian,11/05/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +54207,61454,55790,Probation,Wynn,David,NULL,Male,Caucasian,11/05/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51707,61461,52931,PRETRIAL,Franco,Jhonatan,NULL,Male,Hispanic,05/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,Copy,1,0 +51707,61461,52931,PRETRIAL,Franco,Jhonatan,NULL,Male,Hispanic,05/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,Copy,1,0 +51707,61461,52931,PRETRIAL,Franco,Jhonatan,NULL,Male,Hispanic,05/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +54199,61442,55781,PRETRIAL,MCKINNEY,TERRANCE,NULL,Male,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,7,Risk of Violence,-0.45,10,High,New,1,0 +54199,61442,55781,PRETRIAL,MCKINNEY,TERRANCE,NULL,Male,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +54199,61442,55781,PRETRIAL,MCKINNEY,TERRANCE,NULL,Male,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +52293,61456,53568,PRETRIAL,Johnson,Vashay,NULL,Male,African-American,05/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,4/24/13 0:00,4,High,7,Risk of Violence,-0.27,10,High,Copy,1,0 +52293,61456,53568,PRETRIAL,Johnson,Vashay,NULL,Male,African-American,05/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,4/24/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,Copy,1,0 +52293,61456,53568,PRETRIAL,Johnson,Vashay,NULL,Male,African-American,05/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,4/24/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +11881,61459,55793,PRETRIAL,STEVENS,BENJAMIN,NULL,Male,Caucasian,10/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +11881,61459,55793,PRETRIAL,STEVENS,BENJAMIN,NULL,Male,Caucasian,10/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +11881,61459,55793,PRETRIAL,STEVENS,BENJAMIN,NULL,Male,Caucasian,10/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54218,61473,55805,Probation,Frazier,Yvonne,NULL,Female,African-American,07/25/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +54218,61473,55805,Probation,Frazier,Yvonne,NULL,Female,African-American,07/25/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +54218,61473,55805,Probation,Frazier,Yvonne,NULL,Female,African-American,07/25/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +53439,61438,55777,PRETRIAL,Lynch,Michael,Thomas,Male,Caucasian,07/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +53439,61438,55777,PRETRIAL,Lynch,Michael,Thomas,Male,Caucasian,07/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +53439,61438,55777,PRETRIAL,Lynch,Michael,Thomas,Male,Caucasian,07/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54206,61452,55789,Probation,bornheimer,rick,NULL,Male,Caucasian,04/16/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/24/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +54206,61452,55789,Probation,bornheimer,rick,NULL,Male,Caucasian,04/16/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/24/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +54206,61452,55789,Probation,bornheimer,rick,NULL,Male,Caucasian,04/16/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54212,61463,55796,PRETRIAL,Pierre,Jeffrey,NULL,Male,African-American,10/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/24/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +54212,61463,55796,PRETRIAL,Pierre,Jeffrey,NULL,Male,African-American,10/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/24/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +54212,61463,55796,PRETRIAL,Pierre,Jeffrey,NULL,Male,African-American,10/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52293,61457,53568,PRETRIAL,Johnson,Vashay,NULL,Male,African-American,05/21/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,4,High,7,Risk of Violence,-0.27,10,High,Copy,1,0 +52293,61457,53568,PRETRIAL,Johnson,Vashay,NULL,Male,African-American,05/21/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,Copy,1,0 +52293,61457,53568,PRETRIAL,Johnson,Vashay,NULL,Male,African-American,05/21/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +54194,61436,55775,PRETRIAL,Chambers,LynVAL,NULL,Male,African-American,01/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +54194,61436,55775,PRETRIAL,Chambers,LynVAL,NULL,Male,African-American,01/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,8,Risk of Recidivism,0.15,8,High,New,1,0 +54194,61436,55775,PRETRIAL,Chambers,LynVAL,NULL,Male,African-American,01/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54217,61472,55804,Probation,gomez,winter,NULL,Female,Hispanic,10/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +54217,61472,55804,Probation,gomez,winter,NULL,Female,Hispanic,10/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +54217,61472,55804,Probation,gomez,winter,NULL,Female,Hispanic,10/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +9741,61465,55798,PRETRIAL,mouring,JENNIFER,NULL,Female,Caucasian,07/15/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.45,3,Low,New,1,0 +9741,61465,55798,PRETRIAL,mouring,JENNIFER,NULL,Female,Caucasian,07/15/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,9,High,New,1,0 +9741,61465,55798,PRETRIAL,mouring,JENNIFER,NULL,Female,Caucasian,07/15/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +54200,61444,55783,PRETRIAL,THEISS,BRITNEE,NULL,Female,Caucasian,12/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +54200,61444,55783,PRETRIAL,THEISS,BRITNEE,NULL,Female,Caucasian,12/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +54200,61444,55783,PRETRIAL,THEISS,BRITNEE,NULL,Female,Caucasian,12/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +40811,61478,54923,PRETRIAL,Aldahonda,Alan,NULL,Male,Caucasian,11/20/86,17,All Scales,Intake,English,Other,Probation,Single,4/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,Copy,1,0 +40811,61478,54923,PRETRIAL,Aldahonda,Alan,NULL,Male,Caucasian,11/20/86,17,All Scales,Intake,English,Other,Probation,Single,4/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,Copy,1,0 +40811,61478,54923,PRETRIAL,Aldahonda,Alan,NULL,Male,Caucasian,11/20/86,17,All Scales,Intake,English,Other,Probation,Single,4/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +44322,61470,55802,Probation,JOHNSON,THOMAS,G,Male,African-American,08/27/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/24/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +44322,61470,55802,Probation,JOHNSON,THOMAS,G,Male,African-American,08/27/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/24/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +44322,61470,55802,Probation,JOHNSON,THOMAS,G,Male,African-American,08/27/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54198,61441,55780,PRETRIAL,LATORRE-GALAN,NICOLAS,E,Male,Caucasian,03/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +54198,61441,55780,PRETRIAL,LATORRE-GALAN,NICOLAS,E,Male,Caucasian,03/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +54198,61441,55780,PRETRIAL,LATORRE-GALAN,NICOLAS,E,Male,Caucasian,03/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54205,61449,55787,Probation,PETRIE,JOHN,BYRON,Male,Caucasian,09/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +54205,61449,55787,Probation,PETRIE,JOHN,BYRON,Male,Caucasian,09/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +54205,61449,55787,Probation,PETRIE,JOHN,BYRON,Male,Caucasian,09/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52214,61428,55769,PRETRIAL,Tolliver,Tevin,NULL,Male,African-American,05/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.92,9,High,New,1,0 +52214,61428,55769,PRETRIAL,Tolliver,Tevin,NULL,Male,African-American,05/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +52214,61428,55769,PRETRIAL,Tolliver,Tevin,NULL,Male,African-American,05/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54211,61462,55795,PRETRIAL,MOYER,BRIGITTE,ELIZABETH,Female,Caucasian,03/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/24/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +54211,61462,55795,PRETRIAL,MOYER,BRIGITTE,ELIZABETH,Female,Caucasian,03/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +54211,61462,55795,PRETRIAL,MOYER,BRIGITTE,ELIZABETH,Female,Caucasian,03/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/24/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54234,61496,55826,PRETRIAL,Mizrachi,Fay,NULL,Female,Caucasian,01/16/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/25/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +54234,61496,55826,PRETRIAL,Mizrachi,Fay,NULL,Female,Caucasian,01/16/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/25/13 0:00,1,Low,8,Risk of Recidivism,-2.58,1,Low,New,1,0 +54234,61496,55826,PRETRIAL,Mizrachi,Fay,NULL,Female,Caucasian,01/16/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54258,61530,55856,Probation,SHARON,RUTH,NULL,Female,Caucasian,08/13/32,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-4.43,1,Low,New,1,0 +54258,61530,55856,Probation,SHARON,RUTH,NULL,Female,Caucasian,08/13/32,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-2.82,1,Low,New,1,0 +54258,61530,55856,Probation,SHARON,RUTH,NULL,Female,Caucasian,08/13/32,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54222,61483,55813,PRETRIAL,Rodriguez,Jordan,NULL,Male,Caucasian,12/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +54222,61483,55813,PRETRIAL,Rodriguez,Jordan,NULL,Male,Caucasian,12/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +54222,61483,55813,PRETRIAL,Rodriguez,Jordan,NULL,Male,Caucasian,12/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54249,61517,55844,PRETRIAL,Campbell,John,William,Male,Caucasian,10/03/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +54249,61517,55844,PRETRIAL,Campbell,John,William,Male,Caucasian,10/03/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +54249,61517,55844,PRETRIAL,Campbell,John,William,Male,Caucasian,10/03/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54229,61491,55821,PRETRIAL,Willis,Dorcas,NULL,Male,African-American,08/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,7,Risk of Violence,-2.71,2,Low,New,1,0 +54229,61491,55821,PRETRIAL,Willis,Dorcas,NULL,Male,African-American,08/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +54229,61491,55821,PRETRIAL,Willis,Dorcas,NULL,Male,African-American,08/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54242,61509,55837,Probation,Nikander,Robert,James,Male,Caucasian,06/07/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +54242,61509,55837,Probation,Nikander,Robert,James,Male,Caucasian,06/07/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +54242,61509,55837,Probation,Nikander,Robert,James,Male,Caucasian,06/07/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54227,61488,55818,PRETRIAL,Fedotov,Vladimir,NULL,Male,Caucasian,09/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +54227,61488,55818,PRETRIAL,Fedotov,Vladimir,NULL,Male,Caucasian,09/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +54227,61488,55818,PRETRIAL,Fedotov,Vladimir,NULL,Male,Caucasian,09/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54220,61480,55810,PRETRIAL,Olivo,Brandon,NULL,Male,Caucasian,11/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +54220,61480,55810,PRETRIAL,Olivo,Brandon,NULL,Male,Caucasian,11/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +54220,61480,55810,PRETRIAL,Olivo,Brandon,NULL,Male,Caucasian,11/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54247,61514,55842,Probation,WILLIAMS,CATINA,A,Female,African-American,08/24/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +54247,61514,55842,Probation,WILLIAMS,CATINA,A,Female,African-American,08/24/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +54247,61514,55842,Probation,WILLIAMS,CATINA,A,Female,African-American,08/24/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,29,9,High,New,1,0 +38573,61499,55829,Probation,Lemma,Joseph,NULL,Male,Caucasian,09/28/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +38573,61499,55829,Probation,Lemma,Joseph,NULL,Male,Caucasian,09/28/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +38573,61499,55829,Probation,Lemma,Joseph,NULL,Male,Caucasian,09/28/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +6733,61535,15286,Probation,Martin,Fredrick,NULL,Male,African-American,10/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,Copy,1,0 +6733,61535,15286,Probation,Martin,Fredrick,NULL,Male,African-American,10/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,4,High,8,Risk of Recidivism,0.13,8,High,Copy,1,0 +6733,61535,15286,Probation,Martin,Fredrick,NULL,Male,African-American,10/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +54225,61486,55816,PRETRIAL,Scott,Patrick,NULL,Male,African-American,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +54225,61486,55816,PRETRIAL,Scott,Patrick,NULL,Male,African-American,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +54225,61486,55816,PRETRIAL,Scott,Patrick,NULL,Male,African-American,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54254,61522,55849,Probation,Gualtieri,John,NULL,Male,Caucasian,01/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +54254,61522,55849,Probation,Gualtieri,John,NULL,Male,Caucasian,01/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +54254,61522,55849,Probation,Gualtieri,John,NULL,Male,Caucasian,01/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54231,61493,55823,PRETRIAL,Russell,Marcus,Jmarei,Male,African-American,04/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +54231,61493,55823,PRETRIAL,Russell,Marcus,Jmarei,Male,African-American,04/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +54231,61493,55823,PRETRIAL,Russell,Marcus,Jmarei,Male,African-American,04/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54240,61507,55835,PRETRIAL,Sinert,Bruce,NULL,Male,Caucasian,05/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,2,Medium,7,Risk of Violence,-3.05,1,Low,New,1,0 +54240,61507,55835,PRETRIAL,Sinert,Bruce,NULL,Male,Caucasian,05/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +54240,61507,55835,PRETRIAL,Sinert,Bruce,NULL,Male,Caucasian,05/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +54259,61531,55857,DRRD,Richardson,Christopher,Lee,Male,African-American,07/08/72,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/25/13 0:00,4,High,7,Risk of Violence,-0.62,10,High,New,1,0 +54259,61531,55857,DRRD,Richardson,Christopher,Lee,Male,African-American,07/08/72,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/25/13 0:00,4,High,8,Risk of Recidivism,0.89,10,High,New,1,0 +54259,61531,55857,DRRD,Richardson,Christopher,Lee,Male,African-American,07/08/72,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/25/13 0:00,4,High,18,Risk of Failure to Appear,35,9,High,New,1,0 +33976,61524,55851,PRETRIAL,KING,FRANCISCO,NULL,Male,African-American,07/15/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +33976,61524,55851,PRETRIAL,KING,FRANCISCO,NULL,Male,African-American,07/15/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +33976,61524,55851,PRETRIAL,KING,FRANCISCO,NULL,Male,African-American,07/15/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +21705,61489,55819,PRETRIAL,TERRY,JAMAR,NULL,Male,African-American,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +21705,61489,55819,PRETRIAL,TERRY,JAMAR,NULL,Male,African-American,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,4,High,8,Risk of Recidivism,0.63,10,High,New,1,0 +21705,61489,55819,PRETRIAL,TERRY,JAMAR,NULL,Male,African-American,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54232,61494,55824,PRETRIAL,Jaramillo,Adiel,NULL,Male,Caucasian,11/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +54232,61494,55824,PRETRIAL,Jaramillo,Adiel,NULL,Male,Caucasian,11/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +54232,61494,55824,PRETRIAL,Jaramillo,Adiel,NULL,Male,Caucasian,11/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54251,61519,55846,Probation,BURZACHIELLO,ROSE,NULL,Female,Caucasian,03/03/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +54251,61519,55846,Probation,BURZACHIELLO,ROSE,NULL,Female,Caucasian,03/03/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +54251,61519,55846,Probation,BURZACHIELLO,ROSE,NULL,Female,Caucasian,03/03/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,New,1,0 +41531,61528,55854,Probation,Fleurimy,Carl,NULL,Male,African-American,01/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +41531,61528,55854,Probation,Fleurimy,Carl,NULL,Male,African-American,01/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +41531,61528,55854,Probation,Fleurimy,Carl,NULL,Male,African-American,01/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54236,61498,55828,PRETRIAL,Kildea,Martin,NULL,Male,Caucasian,09/17/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/25/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +54236,61498,55828,PRETRIAL,Kildea,Martin,NULL,Male,Caucasian,09/17/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +54236,61498,55828,PRETRIAL,Kildea,Martin,NULL,Male,Caucasian,09/17/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53108,61515,54537,Probation,Newson,Timothy,NULL,Male,African-American,06/13/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/25/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +53108,61515,54537,Probation,Newson,Timothy,NULL,Male,African-American,06/13/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,6,Medium,New,1,0 +53108,61515,54537,Probation,Newson,Timothy,NULL,Male,African-American,06/13/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +54256,61526,55853,Probation,Membranogomez,Juan,NULL,Male,Hispanic,01/30/79,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +54256,61526,55853,Probation,Membranogomez,Juan,NULL,Male,Hispanic,01/30/79,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +54256,61526,55853,Probation,Membranogomez,Juan,NULL,Male,Hispanic,01/30/79,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54223,61482,55812,PRETRIAL,Knight,Deonte,NULL,Male,African-American,01/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +54223,61482,55812,PRETRIAL,Knight,Deonte,NULL,Male,African-American,01/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +54223,61482,55812,PRETRIAL,Knight,Deonte,NULL,Male,African-American,01/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +46052,61484,55814,PRETRIAL,jones,greg,NULL,Male,African-American,05/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +46052,61484,55814,PRETRIAL,jones,greg,NULL,Male,African-American,05/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +46052,61484,55814,PRETRIAL,jones,greg,NULL,Male,African-American,05/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54239,61503,55832,Probation,weiss,robert,NULL,Male,Caucasian,12/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/13 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +54239,61503,55832,Probation,weiss,robert,NULL,Male,Caucasian,12/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +54239,61503,55832,Probation,weiss,robert,NULL,Male,Caucasian,12/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +45154,61505,55833,PRETRIAL,Darman,David,NULL,Male,Caucasian,01/06/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +45154,61505,55833,PRETRIAL,Darman,David,NULL,Male,Caucasian,01/06/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +45154,61505,55833,PRETRIAL,Darman,David,NULL,Male,Caucasian,01/06/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54245,61512,55840,Probation,Machin,Sueheily,NULL,Female,Hispanic,01/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/25/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +54245,61512,55840,Probation,Machin,Sueheily,NULL,Female,Hispanic,01/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +54245,61512,55840,Probation,Machin,Sueheily,NULL,Female,Hispanic,01/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54237,61500,55830,PRETRIAL,Gray,Terri-Ann,NULL,Female,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +54237,61500,55830,PRETRIAL,Gray,Terri-Ann,NULL,Female,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +54237,61500,55830,PRETRIAL,Gray,Terri-Ann,NULL,Female,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54261,61534,55859,Probation,VILLAMAR,NILO,NULL,Male,Hispanic,09/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/25/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +54261,61534,55859,Probation,VILLAMAR,NILO,NULL,Male,Hispanic,09/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +54261,61534,55859,Probation,VILLAMAR,NILO,NULL,Male,Hispanic,09/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54226,61487,55817,PRETRIAL,Charles,Duson,NULL,Male,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,New,1,0 +54226,61487,55817,PRETRIAL,Charles,Duson,NULL,Male,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +54226,61487,55817,PRETRIAL,Charles,Duson,NULL,Male,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54253,61521,55848,Probation,Kelley,Matthew,James,Male,Caucasian,09/21/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +54253,61521,55848,Probation,Kelley,Matthew,James,Male,Caucasian,09/21/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +54253,61521,55848,Probation,Kelley,Matthew,James,Male,Caucasian,09/21/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54233,61495,55825,PRETRIAL,Holmes,Dennis,NULL,Male,African-American,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +54233,61495,55825,PRETRIAL,Holmes,Dennis,NULL,Male,African-American,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +54233,61495,55825,PRETRIAL,Holmes,Dennis,NULL,Male,African-American,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54246,61513,55841,PRETRIAL,thomas,Brandon,NULL,Male,African-American,05/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/25/13 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +54246,61513,55841,PRETRIAL,thomas,Brandon,NULL,Male,African-American,05/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/25/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +54246,61513,55841,PRETRIAL,thomas,Brandon,NULL,Male,African-American,05/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54230,61492,55822,PRETRIAL,Rogers,Calvin,NULL,Female,African-American,02/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +54230,61492,55822,PRETRIAL,Rogers,Calvin,NULL,Female,African-American,02/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +54230,61492,55822,PRETRIAL,Rogers,Calvin,NULL,Female,African-American,02/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54248,61516,55843,Probation,rousseau,francesca,NULL,Female,Caucasian,04/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +54248,61516,55843,Probation,rousseau,francesca,NULL,Female,Caucasian,04/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,New,1,0 +54248,61516,55843,Probation,rousseau,francesca,NULL,Female,Caucasian,04/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54241,61508,55836,Probation,PAUL,VANESSA,LISSA,Female,Caucasian,08/04/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +54241,61508,55836,Probation,PAUL,VANESSA,LISSA,Female,Caucasian,08/04/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +54241,61508,55836,Probation,PAUL,VANESSA,LISSA,Female,Caucasian,08/04/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +42066,61479,55809,PRETRIAL,Gantt,Anton,NULL,Male,African-American,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +42066,61479,55809,PRETRIAL,Gantt,Anton,NULL,Male,African-American,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +42066,61479,55809,PRETRIAL,Gantt,Anton,NULL,Male,African-American,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54257,61529,55855,Probation,MESYEUX,CHRISTINE,NULL,Female,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,4,High,7,Risk of Violence,-0.95,9,High,New,1,0 +54257,61529,55855,Probation,MESYEUX,CHRISTINE,NULL,Female,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,4,High,8,Risk of Recidivism,0.14,9,High,New,1,0 +54257,61529,55855,Probation,MESYEUX,CHRISTINE,NULL,Female,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +54221,61481,55811,PRETRIAL,Taylor,Derric,NULL,Male,African-American,03/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +54221,61481,55811,PRETRIAL,Taylor,Derric,NULL,Male,African-American,03/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +54221,61481,55811,PRETRIAL,Taylor,Derric,NULL,Male,African-American,03/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54224,61485,55815,PRETRIAL,Colson,Emmanuel,NULL,Male,African-American,10/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +54224,61485,55815,PRETRIAL,Colson,Emmanuel,NULL,Male,African-American,10/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +54224,61485,55815,PRETRIAL,Colson,Emmanuel,NULL,Male,African-American,10/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54260,61532,55858,Probation,Alvarez,Emanuel,Isaac,Male,Hispanic,09/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/25/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +54260,61532,55858,Probation,Alvarez,Emanuel,Isaac,Male,Hispanic,09/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +54260,61532,55858,Probation,Alvarez,Emanuel,Isaac,Male,Hispanic,09/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +42085,61523,55850,PRETRIAL,Oviedo,Karina,A,Female,Hispanic,08/27/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/25/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +42085,61523,55850,PRETRIAL,Oviedo,Karina,A,Female,Hispanic,08/27/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +42085,61523,55850,PRETRIAL,Oviedo,Karina,A,Female,Hispanic,08/27/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54238,61502,55831,Probation,rayan,jamal,NULL,Male,Caucasian,05/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +54238,61502,55831,Probation,rayan,jamal,NULL,Male,Caucasian,05/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +54238,61502,55831,Probation,rayan,jamal,NULL,Male,Caucasian,05/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54252,61520,55847,PRETRIAL,Wilson,Gibrian,N,Male,African-American,08/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +54252,61520,55847,PRETRIAL,Wilson,Gibrian,N,Male,African-American,08/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +54252,61520,55847,PRETRIAL,Wilson,Gibrian,N,Male,African-American,08/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52364,61527,53655,Probation,Holston,Eunice,NULL,Female,African-American,06/22/72,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +52364,61527,53655,Probation,Holston,Eunice,NULL,Female,African-American,06/22/72,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +52364,61527,53655,Probation,Holston,Eunice,NULL,Female,African-American,06/22/72,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54250,61518,55845,Probation,lawrence,ashleigh,NULL,Female,African-American,10/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +54250,61518,55845,Probation,lawrence,ashleigh,NULL,Female,African-American,10/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +54250,61518,55845,Probation,lawrence,ashleigh,NULL,Female,African-American,10/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54228,61490,55820,PRETRIAL,Russaw,Demetris,NULL,Male,African-American,05/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +54228,61490,55820,PRETRIAL,Russaw,Demetris,NULL,Male,African-American,05/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +54228,61490,55820,PRETRIAL,Russaw,Demetris,NULL,Male,African-American,05/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54255,61525,55852,PRETRIAL,Carvalho,Frank,NULL,Male,Hispanic,05/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +54255,61525,55852,PRETRIAL,Carvalho,Frank,NULL,Male,Hispanic,05/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +54255,61525,55852,PRETRIAL,Carvalho,Frank,NULL,Male,Hispanic,05/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54235,61497,55827,PRETRIAL,Peralta,Victor,NULL,Male,Hispanic,07/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/25/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +54235,61497,55827,PRETRIAL,Peralta,Victor,NULL,Male,Hispanic,07/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +54235,61497,55827,PRETRIAL,Peralta,Victor,NULL,Male,Hispanic,07/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53196,61504,54634,PRETRIAL,WILLIAMS,TAMMI,NULL,Female,Caucasian,01/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,Copy,1,0 +53196,61504,54634,PRETRIAL,WILLIAMS,TAMMI,NULL,Female,Caucasian,01/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,Copy,1,0 +53196,61504,54634,PRETRIAL,WILLIAMS,TAMMI,NULL,Female,Caucasian,01/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +54244,61511,55839,PRETRIAL,Brown,Lloyd,NULL,Male,African-American,11/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +54244,61511,55839,PRETRIAL,Brown,Lloyd,NULL,Male,African-American,11/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +54244,61511,55839,PRETRIAL,Brown,Lloyd,NULL,Male,African-American,11/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54295,61576,55899,Probation,mcintyre,jonathan,NULL,Male,Caucasian,08/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +54295,61576,55899,Probation,mcintyre,jonathan,NULL,Male,Caucasian,08/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +54295,61576,55899,Probation,mcintyre,jonathan,NULL,Male,Caucasian,08/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54273,61548,55872,PRETRIAL,Billie,Reuben,H,Male,Native American,12/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/26/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +54273,61548,55872,PRETRIAL,Billie,Reuben,H,Male,Native American,12/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/26/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +54273,61548,55872,PRETRIAL,Billie,Reuben,H,Male,Native American,12/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54289,61567,55891,PRETRIAL,Alftred,Kenneth,Marcus,Male,African-American,09/23/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +54289,61567,55891,PRETRIAL,Alftred,Kenneth,Marcus,Male,African-American,09/23/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +54289,61567,55891,PRETRIAL,Alftred,Kenneth,Marcus,Male,African-American,09/23/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52772,61539,55863,PRETRIAL,Small,Rachael,NULL,Female,African-American,09/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +52772,61539,55863,PRETRIAL,Small,Rachael,NULL,Female,African-American,09/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +52772,61539,55863,PRETRIAL,Small,Rachael,NULL,Female,African-American,09/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54271,61546,55870,PRETRIAL,Stone,Cynthia,Ann,Female,Caucasian,05/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +54271,61546,55870,PRETRIAL,Stone,Cynthia,Ann,Female,Caucasian,05/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +54271,61546,55870,PRETRIAL,Stone,Cynthia,Ann,Female,Caucasian,05/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54290,61569,55893,Probation,GIFFORD,DONALD,THOMAS,Male,Native American,05/01/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +54290,61569,55893,Probation,GIFFORD,DONALD,THOMAS,Male,Native American,05/01/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +54290,61569,55893,Probation,GIFFORD,DONALD,THOMAS,Male,Native American,05/01/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54267,61541,55865,PRETRIAL,Machado,Mitchell,NULL,Male,Hispanic,02/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +54267,61541,55865,PRETRIAL,Machado,Mitchell,NULL,Male,Hispanic,02/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +54267,61541,55865,PRETRIAL,Machado,Mitchell,NULL,Male,Hispanic,02/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54293,61574,55897,Probation,Thorne,christopher,NULL,Male,Hispanic,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +54293,61574,55897,Probation,Thorne,christopher,NULL,Male,Hispanic,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +54293,61574,55897,Probation,Thorne,christopher,NULL,Male,Hispanic,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +46587,61553,55877,PRETRIAL,DIAZ,AMANDA,NULL,Female,Hispanic,02/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +46587,61553,55877,PRETRIAL,DIAZ,AMANDA,NULL,Female,Hispanic,02/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,8,High,New,1,0 +46587,61553,55877,PRETRIAL,DIAZ,AMANDA,NULL,Female,Hispanic,02/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54285,61562,55886,PRETRIAL,Crespo,Christopher,Shaun,Male,Caucasian,09/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +54285,61562,55886,PRETRIAL,Crespo,Christopher,Shaun,Male,Caucasian,09/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +54285,61562,55886,PRETRIAL,Crespo,Christopher,Shaun,Male,Caucasian,09/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54262,61536,55860,PRETRIAL,Farina,Joseph,NULL,Male,Caucasian,06/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +54262,61536,55860,PRETRIAL,Farina,Joseph,NULL,Male,Caucasian,06/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +54262,61536,55860,PRETRIAL,Farina,Joseph,NULL,Male,Caucasian,06/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54298,61579,55902,PRETRIAL,Owens,Justine,NULL,Female,Caucasian,01/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/26/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +54298,61579,55902,PRETRIAL,Owens,Justine,NULL,Female,Caucasian,01/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +54298,61579,55902,PRETRIAL,Owens,Justine,NULL,Female,Caucasian,01/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54281,61557,55881,Probation,Herrera,Allina,NULL,Female,Hispanic,12/09/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +54281,61557,55881,Probation,Herrera,Allina,NULL,Female,Hispanic,12/09/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +54281,61557,55881,Probation,Herrera,Allina,NULL,Female,Hispanic,12/09/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +18632,19309,17890,Probation,Germain,James,NULL,Male,African-American,11/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +18632,19309,17890,Probation,Germain,James,NULL,Male,African-American,11/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +18632,19309,17890,Probation,Germain,James,NULL,Male,African-American,11/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54275,61550,55874,PRETRIAL,Taylor,Dwayne,NULL,Male,Other,01/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/26/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +54275,61550,55874,PRETRIAL,Taylor,Dwayne,NULL,Male,Other,01/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +54275,61550,55874,PRETRIAL,Taylor,Dwayne,NULL,Male,Other,01/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54288,61565,55889,Probation,MCGOWAN,JAMES,RICHARD,Male,African-American,11/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +54288,61565,55889,Probation,MCGOWAN,JAMES,RICHARD,Male,African-American,11/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,4,High,8,Risk of Recidivism,0.43,9,High,New,1,0 +54288,61565,55889,Probation,MCGOWAN,JAMES,RICHARD,Male,African-American,11/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +54263,61537,55861,PRETRIAL,Davis,Shawn,NULL,Male,Caucasian,01/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +54263,61537,55861,PRETRIAL,Davis,Shawn,NULL,Male,Caucasian,01/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +54263,61537,55861,PRETRIAL,Davis,Shawn,NULL,Male,Caucasian,01/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54269,61544,55868,PRETRIAL,Harris,Melissa,NULL,Female,Caucasian,08/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +54269,61544,55868,PRETRIAL,Harris,Melissa,NULL,Female,Caucasian,08/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +54269,61544,55868,PRETRIAL,Harris,Melissa,NULL,Female,Caucasian,08/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54291,61571,55894,Probation,uriate,CHRISTOPHER,NULL,Male,Hispanic,12/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +54291,61571,55894,Probation,uriate,CHRISTOPHER,NULL,Male,Hispanic,12/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +54291,61571,55894,Probation,uriate,CHRISTOPHER,NULL,Male,Hispanic,12/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54297,61578,55901,Probation,Hall,Willie,Dennard,Male,African-American,03/11/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.53,3,Low,New,1,0 +54297,61578,55901,Probation,Hall,Willie,Dennard,Male,African-American,03/11/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +54297,61578,55901,Probation,Hall,Willie,Dennard,Male,African-American,03/11/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +40675,61542,55866,PRETRIAL,Lamar,Keon,NULL,Male,African-American,08/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +40675,61542,55866,PRETRIAL,Lamar,Keon,NULL,Male,African-American,08/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +40675,61542,55866,PRETRIAL,Lamar,Keon,NULL,Male,African-American,08/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54282,61560,55884,DRRD,Williams,Tremaine,NULL,Male,African-American,06/25/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/26/13 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +54282,61560,55884,DRRD,Williams,Tremaine,NULL,Male,African-American,06/25/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/26/13 0:00,4,High,8,Risk of Recidivism,0.54,9,High,New,1,0 +54282,61560,55884,DRRD,Williams,Tremaine,NULL,Male,African-American,06/25/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/26/13 0:00,4,High,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +9659,61573,55896,PRETRIAL,MURRAY,ANTONIO,JARROD,Male,African-American,05/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +9659,61573,55896,PRETRIAL,MURRAY,ANTONIO,JARROD,Male,African-American,05/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +9659,61573,55896,PRETRIAL,MURRAY,ANTONIO,JARROD,Male,African-American,05/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54286,61563,55887,PRETRIAL,JENKINS,KIRK,NULL,Male,African-American,01/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +54286,61563,55887,PRETRIAL,JENKINS,KIRK,NULL,Male,African-American,01/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +54286,61563,55887,PRETRIAL,JENKINS,KIRK,NULL,Male,African-American,01/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54279,61555,55879,Probation,Evans,Ricky,NULL,Male,African-American,12/07/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/26/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +54279,61555,55879,Probation,Evans,Ricky,NULL,Male,African-American,12/07/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/26/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +54279,61555,55879,Probation,Evans,Ricky,NULL,Male,African-American,12/07/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54266,61540,55864,PRETRIAL,Zeke,Zikria,NULL,Male,Caucasian,11/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +54266,61540,55864,PRETRIAL,Zeke,Zikria,NULL,Male,Caucasian,11/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +54266,61540,55864,PRETRIAL,Zeke,Zikria,NULL,Male,Caucasian,11/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54294,61575,55898,PRETRIAL,Echevarria,Lisette,NULL,Female,Caucasian,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +54294,61575,55898,PRETRIAL,Echevarria,Lisette,NULL,Female,Caucasian,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +54294,61575,55898,PRETRIAL,Echevarria,Lisette,NULL,Female,Caucasian,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54272,61547,55871,PRETRIAL,Lightfoot,Corey,NULL,Male,African-American,11/04/18,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +54272,61547,55871,PRETRIAL,Lightfoot,Corey,NULL,Male,African-American,11/04/18,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +54272,61547,55871,PRETRIAL,Lightfoot,Corey,NULL,Male,African-American,11/04/18,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54278,61554,55878,Probation,janvier,ludger,NULL,Male,African-American,07/07/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +54278,61554,55878,Probation,janvier,ludger,NULL,Male,African-American,07/07/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +54278,61554,55878,Probation,janvier,ludger,NULL,Male,African-American,07/07/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +54284,61561,55885,PRETRIAL,Baubriant,Samantha,NULL,Female,Other,12/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/26/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +54284,61561,55885,PRETRIAL,Baubriant,Samantha,NULL,Female,Other,12/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/26/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +54284,61561,55885,PRETRIAL,Baubriant,Samantha,NULL,Female,Other,12/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54274,61549,55873,PRETRIAL,Stubbs,Christian,NULL,Male,African-American,01/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +54274,61549,55873,PRETRIAL,Stubbs,Christian,NULL,Male,African-American,01/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,4,High,8,Risk of Recidivism,0.15,8,High,New,1,0 +54274,61549,55873,PRETRIAL,Stubbs,Christian,NULL,Male,African-American,01/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +40230,61566,55890,PRETRIAL,Singh,Dwayne,Demar,Male,Caucasian,10/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +40230,61566,55890,PRETRIAL,Singh,Dwayne,Demar,Male,Caucasian,10/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +40230,61566,55890,PRETRIAL,Singh,Dwayne,Demar,Male,Caucasian,10/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54270,61545,55869,PRETRIAL,Lucas,Oswaldo,NULL,Male,Hispanic,08/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +54270,61545,55869,PRETRIAL,Lucas,Oswaldo,NULL,Male,Hispanic,08/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +54270,61545,55869,PRETRIAL,Lucas,Oswaldo,NULL,Male,Hispanic,08/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +38149,61570,37566,PRETRIAL,HALL,RANDY,RHOAN,Male,African-American,11/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,Copy,1,0 +38149,61570,37566,PRETRIAL,HALL,RANDY,RHOAN,Male,African-American,11/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,Copy,1,0 +38149,61570,37566,PRETRIAL,HALL,RANDY,RHOAN,Male,African-American,11/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +54268,61543,55867,PRETRIAL,Nihal,Mohan,NULL,Male,African-American,11/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +54268,61543,55867,PRETRIAL,Nihal,Mohan,NULL,Male,African-American,11/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +54268,61543,55867,PRETRIAL,Nihal,Mohan,NULL,Male,African-American,11/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +31100,61572,55895,PRETRIAL,SANCHEZ,PETER,NULL,Male,Caucasian,08/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +31100,61572,55895,PRETRIAL,SANCHEZ,PETER,NULL,Male,Caucasian,08/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +31100,61572,55895,PRETRIAL,SANCHEZ,PETER,NULL,Male,Caucasian,08/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54149,61365,55717,PRETRIAL,BRITT,RICARDO,NULL,Male,Caucasian,04/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +54149,61365,55717,PRETRIAL,BRITT,RICARDO,NULL,Male,Caucasian,04/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +54149,61365,55717,PRETRIAL,BRITT,RICARDO,NULL,Male,Caucasian,04/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +35899,61580,55903,PRETRIAL,Turner,Malcolm,J,Male,African-American,08/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,7,Risk of Violence,-1.27,7,Medium,New,1,0 +35899,61580,55903,PRETRIAL,Turner,Malcolm,J,Male,African-American,08/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +35899,61580,55903,PRETRIAL,Turner,Malcolm,J,Male,African-American,08/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54264,61538,55862,PRETRIAL,Michaud,Mikemsonn,NULL,Male,Other,08/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +54264,61538,55862,PRETRIAL,Michaud,Mikemsonn,NULL,Male,Other,08/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +54264,61538,55862,PRETRIAL,Michaud,Mikemsonn,NULL,Male,Other,08/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54280,61556,55880,Probation,boyd,venetrice,NULL,Female,African-American,08/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.45,3,Low,New,1,0 +54280,61556,55880,Probation,boyd,venetrice,NULL,Female,African-American,08/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,9,High,New,1,0 +54280,61556,55880,Probation,boyd,venetrice,NULL,Female,African-American,08/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +36803,61559,55883,Probation,Bonifocic,Timothy,NULL,Male,Caucasian,06/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +36803,61559,55883,Probation,Bonifocic,Timothy,NULL,Male,Caucasian,06/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,4,High,8,Risk of Recidivism,0.48,9,High,New,1,0 +36803,61559,55883,Probation,Bonifocic,Timothy,NULL,Male,Caucasian,06/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/26/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54296,61577,55900,Probation,Aguero-Pacheco,Rigoberto,NULL,Male,Hispanic,08/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/26/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +54296,61577,55900,Probation,Aguero-Pacheco,Rigoberto,NULL,Male,Hispanic,08/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +54296,61577,55900,Probation,Aguero-Pacheco,Rigoberto,NULL,Male,Hispanic,08/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54276,61551,55875,PRETRIAL,Bogans,Rashad,Antwan,Male,African-American,10/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +54276,61551,55875,PRETRIAL,Bogans,Rashad,Antwan,Male,African-American,10/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +54276,61551,55875,PRETRIAL,Bogans,Rashad,Antwan,Male,African-American,10/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54287,61564,55888,Probation,Torres,Mario,Bello,Male,Hispanic,01/19/80,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,4/26/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +54287,61564,55888,Probation,Torres,Mario,Bello,Male,Hispanic,01/19/80,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,4/26/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +54287,61564,55888,Probation,Torres,Mario,Bello,Male,Hispanic,01/19/80,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,4/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +6248,61585,5843,PRETRIAL,HIGDON,ERIC,NULL,Male,African-American,03/20/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,Copy,1,0 +6248,61585,5843,PRETRIAL,HIGDON,ERIC,NULL,Male,African-American,03/20/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.86,10,High,Copy,1,0 +6248,61585,5843,PRETRIAL,HIGDON,ERIC,NULL,Male,African-American,03/20/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +54313,61598,55920,PRETRIAL,BANTON,JASON,NULL,Male,African-American,06/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +54313,61598,55920,PRETRIAL,BANTON,JASON,NULL,Male,African-American,06/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +54313,61598,55920,PRETRIAL,BANTON,JASON,NULL,Male,African-American,06/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54314,61601,55921,PRETRIAL,SEQUEIRA,NOEL,NULL,Male,Caucasian,03/29/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +54314,61601,55921,PRETRIAL,SEQUEIRA,NOEL,NULL,Male,Caucasian,03/29/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +54314,61601,55921,PRETRIAL,SEQUEIRA,NOEL,NULL,Male,Caucasian,03/29/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54310,61593,55915,PRETRIAL,Natta,Tazomi,NULL,Male,African-American,07/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +54310,61593,55915,PRETRIAL,Natta,Tazomi,NULL,Male,African-American,07/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +54310,61593,55915,PRETRIAL,Natta,Tazomi,NULL,Male,African-American,07/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54308,61591,55913,PRETRIAL,JONES,KYRON,NULL,Male,African-American,10/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +54308,61591,55913,PRETRIAL,JONES,KYRON,NULL,Male,African-American,10/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +54308,61591,55913,PRETRIAL,JONES,KYRON,NULL,Male,African-American,10/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +6881,61600,22829,Probation,Hernandez,Ulisses,NULL,Male,Hispanic,11/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/27/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,Copy,1,0 +6881,61600,22829,Probation,Hernandez,Ulisses,NULL,Male,Hispanic,11/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/27/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,Copy,1,0 +6881,61600,22829,Probation,Hernandez,Ulisses,NULL,Male,Hispanic,11/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +54304,61587,55909,PRETRIAL,Chovan,Peter,NULL,Male,Caucasian,10/10/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +54304,61587,55909,PRETRIAL,Chovan,Peter,NULL,Male,Caucasian,10/10/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,8,Risk of Recidivism,-2.67,1,Low,New,1,0 +54304,61587,55909,PRETRIAL,Chovan,Peter,NULL,Male,Caucasian,10/10/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +44458,61596,55918,PRETRIAL,Mcfadden,Denzell,NULL,Male,African-American,05/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +44458,61596,55918,PRETRIAL,Mcfadden,Denzell,NULL,Male,African-American,05/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +44458,61596,55918,PRETRIAL,Mcfadden,Denzell,NULL,Male,African-American,05/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54315,61603,55923,PRETRIAL,JONES,JARROD,NULL,Male,African-American,04/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +54315,61603,55923,PRETRIAL,JONES,JARROD,NULL,Male,African-American,04/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +54315,61603,55923,PRETRIAL,JONES,JARROD,NULL,Male,African-American,04/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +27066,61605,55925,PRETRIAL,Hicks,Sylvester,NULL,Male,African-American,04/06/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +27066,61605,55925,PRETRIAL,Hicks,Sylvester,NULL,Male,African-American,04/06/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +27066,61605,55925,PRETRIAL,Hicks,Sylvester,NULL,Male,African-American,04/06/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54300,61582,55905,PRETRIAL,VEDRINE,VANESSA,NULL,Male,African-American,10/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +54300,61582,55905,PRETRIAL,VEDRINE,VANESSA,NULL,Male,African-American,10/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +54300,61582,55905,PRETRIAL,VEDRINE,VANESSA,NULL,Male,African-American,10/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54302,61584,55907,PRETRIAL,WATSON,MATTHEW,NULL,Male,African-American,02/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +54302,61584,55907,PRETRIAL,WATSON,MATTHEW,NULL,Male,African-American,02/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +54302,61584,55907,PRETRIAL,WATSON,MATTHEW,NULL,Male,African-American,02/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54305,61589,55911,PRETRIAL,Moses,Gloria,NULL,Female,African-American,12/12/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/27/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +54305,61589,55911,PRETRIAL,Moses,Gloria,NULL,Female,African-American,12/12/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/27/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +54305,61589,55911,PRETRIAL,Moses,Gloria,NULL,Female,African-American,12/12/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +54311,61594,55916,PRETRIAL,hayes,Lance,Alan,Male,Caucasian,12/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +54311,61594,55916,PRETRIAL,hayes,Lance,Alan,Male,Caucasian,12/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +54311,61594,55916,PRETRIAL,hayes,Lance,Alan,Male,Caucasian,12/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +44153,61602,55922,PRETRIAL,Lewis,Christopher,Walter,Male,African-American,01/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +44153,61602,55922,PRETRIAL,Lewis,Christopher,Walter,Male,African-American,01/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +44153,61602,55922,PRETRIAL,Lewis,Christopher,Walter,Male,African-American,01/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54299,61581,55904,PRETRIAL,Collazos,Leonardo,NULL,Male,Hispanic,07/21/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +54299,61581,55904,PRETRIAL,Collazos,Leonardo,NULL,Male,Hispanic,07/21/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +54299,61581,55904,PRETRIAL,Collazos,Leonardo,NULL,Male,Hispanic,07/21/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +36967,61599,36301,PRETRIAL,Francisco,Sanchezlago,NULL,Male,Hispanic,12/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,Copy,1,0 +36967,61599,36301,PRETRIAL,Francisco,Sanchezlago,NULL,Male,Hispanic,12/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,Copy,1,0 +36967,61599,36301,PRETRIAL,Francisco,Sanchezlago,NULL,Male,Hispanic,12/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +6881,32413,22829,Probation,Hernandez,Ulisses,NULL,Male,Hispanic,11/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/27/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,Copy,1,0 +6881,32413,22829,Probation,Hernandez,Ulisses,NULL,Male,Hispanic,11/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/27/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,Copy,1,0 +6881,32413,22829,Probation,Hernandez,Ulisses,NULL,Male,Hispanic,11/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +54303,61586,55908,PRETRIAL,Morival,Jerry,NULL,Male,African-American,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +54303,61586,55908,PRETRIAL,Morival,Jerry,NULL,Male,African-American,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +54303,61586,55908,PRETRIAL,Morival,Jerry,NULL,Male,African-American,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54301,61583,55906,PRETRIAL,GRAY,CYNTHIA,NULL,Female,African-American,11/14/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/27/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +54301,61583,55906,PRETRIAL,GRAY,CYNTHIA,NULL,Female,African-American,11/14/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/27/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +54301,61583,55906,PRETRIAL,GRAY,CYNTHIA,NULL,Female,African-American,11/14/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54309,61592,55914,PRETRIAL,Davell,William,NULL,Male,Caucasian,08/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +54309,61592,55914,PRETRIAL,Davell,William,NULL,Male,Caucasian,08/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +54309,61592,55914,PRETRIAL,Davell,William,NULL,Male,Caucasian,08/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54306,61588,55910,PRETRIAL,Young,Annmarie,NULL,Female,Other,11/29/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +54306,61588,55910,PRETRIAL,Young,Annmarie,NULL,Female,Other,11/29/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +54306,61588,55910,PRETRIAL,Young,Annmarie,NULL,Female,Other,11/29/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54312,61595,55917,PRETRIAL,Rivera,Christian,Nicholas,Male,Hispanic,06/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +54312,61595,55917,PRETRIAL,Rivera,Christian,Nicholas,Male,Hispanic,06/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +54312,61595,55917,PRETRIAL,Rivera,Christian,Nicholas,Male,Hispanic,06/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54307,61590,55912,PRETRIAL,WARD,TRIMAINE,NULL,Female,African-American,11/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +54307,61590,55912,PRETRIAL,WARD,TRIMAINE,NULL,Female,African-American,11/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +54307,61590,55912,PRETRIAL,WARD,TRIMAINE,NULL,Female,African-American,11/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +38566,61597,55919,PRETRIAL,Samuels,Peter,NULL,Male,Other,12/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +38566,61597,55919,PRETRIAL,Samuels,Peter,NULL,Male,Other,12/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +38566,61597,55919,PRETRIAL,Samuels,Peter,NULL,Male,Other,12/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +13059,61604,55924,PRETRIAL,WALLACE,TELFORD,NULL,Male,African-American,05/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/27/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +13059,61604,55924,PRETRIAL,WALLACE,TELFORD,NULL,Male,African-American,05/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/27/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +13059,61604,55924,PRETRIAL,WALLACE,TELFORD,NULL,Male,African-American,05/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +39731,61611,55928,PRETRIAL,FOLWER,MICHAEL,NULL,Male,African-American,11/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +39731,61611,55928,PRETRIAL,FOLWER,MICHAEL,NULL,Male,African-American,11/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +39731,61611,55928,PRETRIAL,FOLWER,MICHAEL,NULL,Male,African-American,11/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +36393,61618,35655,PRETRIAL,Hines,Dexter,A,Male,African-American,07/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.32,3,Low,Copy,1,0 +36393,61618,35655,PRETRIAL,Hines,Dexter,A,Male,African-American,07/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,Copy,1,0 +36393,61618,35655,PRETRIAL,Hines,Dexter,A,Male,African-American,07/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +46244,61613,55930,PRETRIAL,Johnson,Stephanie,NULL,Female,African-American,05/19/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +46244,61613,55930,PRETRIAL,Johnson,Stephanie,NULL,Female,African-American,05/19/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +46244,61613,55930,PRETRIAL,Johnson,Stephanie,NULL,Female,African-American,05/19/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +54316,61609,55927,PRETRIAL,OBRIEN,DENZEL,NULL,Male,African-American,01/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +54316,61609,55927,PRETRIAL,OBRIEN,DENZEL,NULL,Male,African-American,01/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +54316,61609,55927,PRETRIAL,OBRIEN,DENZEL,NULL,Male,African-American,01/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +3523,61607,3237,PRETRIAL,STEPHENS,ARMOND,RASHIED,Male,African-American,07/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,Copy,1,0 +3523,61607,3237,PRETRIAL,STEPHENS,ARMOND,RASHIED,Male,African-American,07/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,Copy,1,0 +3523,61607,3237,PRETRIAL,STEPHENS,ARMOND,RASHIED,Male,African-American,07/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +21295,61620,55933,PRETRIAL,Burgos,Michael,NULL,Male,African-American,09/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +21295,61620,55933,PRETRIAL,Burgos,Michael,NULL,Male,African-American,09/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +21295,61620,55933,PRETRIAL,Burgos,Michael,NULL,Male,African-American,09/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +41986,61610,41744,PRETRIAL,Davis,Travis,Anthony,Male,African-American,04/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,4,High,7,Risk of Violence,-0.99,9,High,Copy,1,0 +41986,61610,41744,PRETRIAL,Davis,Travis,Anthony,Male,African-American,04/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,4,High,8,Risk of Recidivism,0.16,8,High,Copy,1,0 +41986,61610,41744,PRETRIAL,Davis,Travis,Anthony,Male,African-American,04/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +54321,61615,55932,PRETRIAL,Montalvo,Cynthia,Theresa,Female,Caucasian,04/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +54321,61615,55932,PRETRIAL,Montalvo,Cynthia,Theresa,Female,Caucasian,04/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +54321,61615,55932,PRETRIAL,Montalvo,Cynthia,Theresa,Female,Caucasian,04/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +7258,61612,55929,PRETRIAL,BOYD,LARRY,NULL,Male,Caucasian,04/08/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +7258,61612,55929,PRETRIAL,BOYD,LARRY,NULL,Male,Caucasian,04/08/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +7258,61612,55929,PRETRIAL,BOYD,LARRY,NULL,Male,Caucasian,04/08/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,1,Low,18,Risk of Failure to Appear,39,10,High,New,1,0 +54322,61621,55934,PRETRIAL,Boyd,Eben,NULL,Male,Caucasian,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/28/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +54322,61621,55934,PRETRIAL,Boyd,Eben,NULL,Male,Caucasian,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/28/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +54322,61621,55934,PRETRIAL,Boyd,Eben,NULL,Male,Caucasian,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/28/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +33668,61608,55926,PRETRIAL,pelaez,hebert,NULL,Male,Caucasian,04/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +33668,61608,55926,PRETRIAL,pelaez,hebert,NULL,Male,Caucasian,04/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +33668,61608,55926,PRETRIAL,pelaez,hebert,NULL,Male,Caucasian,04/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54320,61614,55931,PRETRIAL,Jordan,Shantelle,Nikia,Female,Hispanic,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/28/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +54320,61614,55931,PRETRIAL,Jordan,Shantelle,Nikia,Female,Hispanic,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/28/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +54320,61614,55931,PRETRIAL,Jordan,Shantelle,Nikia,Female,Hispanic,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +36393,61619,35655,PRETRIAL,Hines,Dexter,A,Male,African-American,07/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.32,3,Low,Copy,1,0 +36393,61619,35655,PRETRIAL,Hines,Dexter,A,Male,African-American,07/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,Copy,1,0 +36393,61619,35655,PRETRIAL,Hines,Dexter,A,Male,African-American,07/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +27261,61606,26371,DRRD,Harris,Jamie,NULL,Female,Caucasian,12/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,Copy,1,0 +27261,61606,26371,DRRD,Harris,Jamie,NULL,Female,Caucasian,12/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,Copy,1,0 +27261,61606,26371,DRRD,Harris,Jamie,NULL,Female,Caucasian,12/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +54341,61645,55955,PRETRIAL,Lemorin,Stanley,NULL,Male,African-American,09/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +54341,61645,55955,PRETRIAL,Lemorin,Stanley,NULL,Male,African-American,09/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +54341,61645,55955,PRETRIAL,Lemorin,Stanley,NULL,Male,African-American,09/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54324,61624,55937,PRETRIAL,TOUSSAINT,JIMMY,JAMESQ,Male,African-American,05/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +54324,61624,55937,PRETRIAL,TOUSSAINT,JIMMY,JAMESQ,Male,African-American,05/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +54324,61624,55937,PRETRIAL,TOUSSAINT,JIMMY,JAMESQ,Male,African-American,05/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54326,61627,55940,PRETRIAL,METAYER,MAX,NULL,Male,African-American,08/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/29/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +54326,61627,55940,PRETRIAL,METAYER,MAX,NULL,Male,African-American,08/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +54326,61627,55940,PRETRIAL,METAYER,MAX,NULL,Male,African-American,08/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54331,61632,55945,PRETRIAL,Vento,Michael,NULL,Male,Caucasian,03/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +54331,61632,55945,PRETRIAL,Vento,Michael,NULL,Male,Caucasian,03/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +54331,61632,55945,PRETRIAL,Vento,Michael,NULL,Male,Caucasian,03/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54356,61666,55974,Probation,Carballo,Charles,NULL,Male,Hispanic,11/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +54356,61666,55974,Probation,Carballo,Charles,NULL,Male,Hispanic,11/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +54356,61666,55974,Probation,Carballo,Charles,NULL,Male,Hispanic,11/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54335,61637,55949,PRETRIAL,BERNHARDDT,WILLIAM,NULL,Male,Caucasian,12/03/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/29/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +54335,61637,55949,PRETRIAL,BERNHARDDT,WILLIAM,NULL,Male,Caucasian,12/03/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/29/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +54335,61637,55949,PRETRIAL,BERNHARDDT,WILLIAM,NULL,Male,Caucasian,12/03/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +18560,61671,55979,PRETRIAL,BUSTAMENTE,ELVIS,NULL,Male,Caucasian,10/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.82,9,High,New,1,0 +18560,61671,55979,PRETRIAL,BUSTAMENTE,ELVIS,NULL,Male,Caucasian,10/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +18560,61671,55979,PRETRIAL,BUSTAMENTE,ELVIS,NULL,Male,Caucasian,10/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54333,61635,55947,PRETRIAL,CADET,REYNOLD,NULL,Male,African-American,03/27/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +54333,61635,55947,PRETRIAL,CADET,REYNOLD,NULL,Male,African-American,03/27/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +54333,61635,55947,PRETRIAL,CADET,REYNOLD,NULL,Male,African-American,03/27/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +11743,61650,55959,PRETRIAL,MORALES,KEVIN,J,Male,Hispanic,09/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +11743,61650,55959,PRETRIAL,MORALES,KEVIN,J,Male,Hispanic,09/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +11743,61650,55959,PRETRIAL,MORALES,KEVIN,J,Male,Hispanic,09/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +44864,61658,55967,PRETRIAL,Meadows,Christopher,Michael,Male,Caucasian,09/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/29/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +44864,61658,55967,PRETRIAL,Meadows,Christopher,Michael,Male,Caucasian,09/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +44864,61658,55967,PRETRIAL,Meadows,Christopher,Michael,Male,Caucasian,09/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54323,61622,55935,PRETRIAL,Henderson,Paul,NULL,Male,African-American,07/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +54323,61622,55935,PRETRIAL,Henderson,Paul,NULL,Male,African-American,07/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +54323,61622,55935,PRETRIAL,Henderson,Paul,NULL,Male,African-American,07/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54328,61629,55942,PRETRIAL,Charles,Carleb,NULL,Male,African-American,10/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +54328,61629,55942,PRETRIAL,Charles,Carleb,NULL,Male,African-American,10/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +54328,61629,55942,PRETRIAL,Charles,Carleb,NULL,Male,African-American,10/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54358,61668,55976,Probation,HODGSON,WILHELMINA,NULL,Female,Caucasian,04/15/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-4.37,1,Low,New,1,0 +54358,61668,55976,Probation,HODGSON,WILHELMINA,NULL,Female,Caucasian,04/15/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +54358,61668,55976,Probation,HODGSON,WILHELMINA,NULL,Female,Caucasian,04/15/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54350,61659,55968,Probation,hankins,stephen,NULL,Male,Caucasian,06/25/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/29/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +54350,61659,55968,Probation,hankins,stephen,NULL,Male,Caucasian,06/25/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +54350,61659,55968,Probation,hankins,stephen,NULL,Male,Caucasian,06/25/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54336,61638,55950,PRETRIAL,Pitre,John,J,Male,Caucasian,01/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +54336,61638,55950,PRETRIAL,Pitre,John,J,Male,Caucasian,01/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +54336,61638,55950,PRETRIAL,Pitre,John,J,Male,Caucasian,01/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54348,61656,55965,PRETRIAL,SHUPE,JAMES,NULL,Male,Caucasian,10/29/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/29/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +54348,61656,55965,PRETRIAL,SHUPE,JAMES,NULL,Male,Caucasian,10/29/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +54348,61656,55965,PRETRIAL,SHUPE,JAMES,NULL,Male,Caucasian,10/29/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52839,61633,54226,PRETRIAL,Upp,James,NULL,Male,Caucasian,10/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,Copy,1,0 +52839,61633,54226,PRETRIAL,Upp,James,NULL,Male,Caucasian,10/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,Copy,1,0 +52839,61633,54226,PRETRIAL,Upp,James,NULL,Male,Caucasian,10/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +54346,61654,55963,PRETRIAL,Clark,Brad,NULL,Male,Caucasian,03/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +54346,61654,55963,PRETRIAL,Clark,Brad,NULL,Male,Caucasian,03/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +54346,61654,55963,PRETRIAL,Clark,Brad,NULL,Male,Caucasian,03/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54352,61661,55970,PRETRIAL,PANTOJA,CHRISTOPHER,NULL,Male,Hispanic,06/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +54352,61661,55970,PRETRIAL,PANTOJA,CHRISTOPHER,NULL,Male,Hispanic,06/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +54352,61661,55970,PRETRIAL,PANTOJA,CHRISTOPHER,NULL,Male,Hispanic,06/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +46149,61626,55939,PRETRIAL,Merritt,Deneil,NULL,Male,African-American,01/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +46149,61626,55939,PRETRIAL,Merritt,Deneil,NULL,Male,African-American,01/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +46149,61626,55939,PRETRIAL,Merritt,Deneil,NULL,Male,African-American,01/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +17015,61640,54856,PRETRIAL,BRISTOL,SHENARD,NULL,Male,African-American,12/11/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +17015,61640,54856,PRETRIAL,BRISTOL,SHENARD,NULL,Male,African-American,12/11/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,4,High,8,Risk of Recidivism,0.34,8,High,New,1,0 +17015,61640,54856,PRETRIAL,BRISTOL,SHENARD,NULL,Male,African-American,12/11/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,4,High,18,Risk of Failure to Appear,23,4,Low,New,1,0 +54344,61649,55958,Probation,miller,michael,NULL,Male,Caucasian,06/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +54344,61649,55958,Probation,miller,michael,NULL,Male,Caucasian,06/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +54344,61649,55958,Probation,miller,michael,NULL,Male,Caucasian,06/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52983,61623,55936,PRETRIAL,SCARLETTE,SUSAN,NULL,Female,Caucasian,07/06/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +52983,61623,55936,PRETRIAL,SCARLETTE,SUSAN,NULL,Female,Caucasian,07/06/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +52983,61623,55936,PRETRIAL,SCARLETTE,SUSAN,NULL,Female,Caucasian,07/06/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54327,61628,55941,PRETRIAL,CHURCH,DAVID,W,Male,Caucasian,03/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/29/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +54327,61628,55941,PRETRIAL,CHURCH,DAVID,W,Male,Caucasian,03/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/29/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +54327,61628,55941,PRETRIAL,CHURCH,DAVID,W,Male,Caucasian,03/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54353,61662,55971,Probation,Quimby,Dale,M,Male,Caucasian,01/10/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +54353,61662,55971,Probation,Quimby,Dale,M,Male,Caucasian,01/10/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +54353,61662,55971,Probation,Quimby,Dale,M,Male,Caucasian,01/10/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53738,61641,55222,PRETRIAL,FANNING,LESLIE,NULL,Female,Caucasian,07/29/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/29/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,Copy,1,0 +53738,61641,55222,PRETRIAL,FANNING,LESLIE,NULL,Female,Caucasian,07/29/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/29/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,Copy,1,0 +53738,61641,55222,PRETRIAL,FANNING,LESLIE,NULL,Female,Caucasian,07/29/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +54330,61631,55944,PRETRIAL,Lightbourn,Antonio,NULL,Male,African-American,07/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +54330,61631,55944,PRETRIAL,Lightbourn,Antonio,NULL,Male,African-American,07/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +54330,61631,55944,PRETRIAL,Lightbourn,Antonio,NULL,Male,African-American,07/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54349,61657,55966,Probation,Sarmiento,Maricela,NULL,Female,Hispanic,12/21/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/29/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +54349,61657,55966,Probation,Sarmiento,Maricela,NULL,Female,Hispanic,12/21/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +54349,61657,55966,Probation,Sarmiento,Maricela,NULL,Female,Hispanic,12/21/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54334,61636,55948,PRETRIAL,Armbrister,Angelo,NULL,Male,African-American,10/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +54334,61636,55948,PRETRIAL,Armbrister,Angelo,NULL,Male,African-American,10/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +54334,61636,55948,PRETRIAL,Armbrister,Angelo,NULL,Male,African-American,10/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54360,61672,55980,PRETRIAL,CADDELL,JAQUA,DEBRAN,Male,African-American,02/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +54360,61672,55980,PRETRIAL,CADDELL,JAQUA,DEBRAN,Male,African-American,02/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +54360,61672,55980,PRETRIAL,CADDELL,JAQUA,DEBRAN,Male,African-American,02/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53414,61665,54904,Probation,burello,todd,NULL,Male,Caucasian,08/11/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +53414,61665,54904,Probation,burello,todd,NULL,Male,Caucasian,08/11/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +53414,61665,54904,Probation,burello,todd,NULL,Male,Caucasian,08/11/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,19,2,Low,New,1,0 +54340,61644,55954,Probation,mcginnis,brian,NULL,Male,Caucasian,03/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.73,2,Low,New,1,0 +54340,61644,55954,Probation,mcginnis,brian,NULL,Male,Caucasian,03/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +54340,61644,55954,Probation,mcginnis,brian,NULL,Male,Caucasian,03/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54351,61660,55969,PRETRIAL,Bush,Christopher,NULL,Male,African-American,11/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,4/29/13 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +54351,61660,55969,PRETRIAL,Bush,Christopher,NULL,Male,African-American,11/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,4/29/13 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +54351,61660,55969,PRETRIAL,Bush,Christopher,NULL,Male,African-American,11/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,4/29/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54332,61634,55946,PRETRIAL,DENT,LAVER,TIMESHA,Female,African-American,10/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/29/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +54332,61634,55946,PRETRIAL,DENT,LAVER,TIMESHA,Female,African-American,10/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/29/13 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +54332,61634,55946,PRETRIAL,DENT,LAVER,TIMESHA,Female,African-American,10/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +31201,61651,55960,PRETRIAL,nuotilla,james,NULL,Male,Other,10/12/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,2,Medium,7,Risk of Violence,-2.64,2,Low,New,1,0 +31201,61651,55960,PRETRIAL,nuotilla,james,NULL,Male,Other,10/12/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,6,Medium,New,1,0 +31201,61651,55960,PRETRIAL,nuotilla,james,NULL,Male,Other,10/12/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/29/13 0:00,2,Medium,18,Risk of Failure to Appear,35,9,High,New,1,0 +54329,61630,55943,PRETRIAL,Craig-Hallam,Tera,NULL,Female,Other,09/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/29/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +54329,61630,55943,PRETRIAL,Craig-Hallam,Tera,NULL,Female,Other,09/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +54329,61630,55943,PRETRIAL,Craig-Hallam,Tera,NULL,Female,Other,09/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54355,61664,55973,PRETRIAL,LOPEZ-GAYA,PEDRO,NULL,Male,Hispanic,06/12/66,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +54355,61664,55973,PRETRIAL,LOPEZ-GAYA,PEDRO,NULL,Male,Hispanic,06/12/66,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +54355,61664,55973,PRETRIAL,LOPEZ-GAYA,PEDRO,NULL,Male,Hispanic,06/12/66,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54357,61667,55975,Probation,Hernandez,Maynor,Doming,Male,Hispanic,04/20/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,4/29/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +54357,61667,55975,Probation,Hernandez,Maynor,Doming,Male,Hispanic,04/20/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +54357,61667,55975,Probation,Hernandez,Maynor,Doming,Male,Hispanic,04/20/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +17027,61669,55977,Probation,STUBBS,GLENARDO,LETROY,Male,African-American,03/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,4/29/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +17027,61669,55977,Probation,STUBBS,GLENARDO,LETROY,Male,African-American,03/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,4/29/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +17027,61669,55977,Probation,STUBBS,GLENARDO,LETROY,Male,African-American,03/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54337,61639,55951,PRETRIAL,Valle,Maritza,NULL,Female,Hispanic,03/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +54337,61639,55951,PRETRIAL,Valle,Maritza,NULL,Female,Hispanic,03/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +54337,61639,55951,PRETRIAL,Valle,Maritza,NULL,Female,Hispanic,03/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53749,61648,55235,PRETRIAL,Swartz,Cyril,NULL,Male,Caucasian,02/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,Copy,1,0 +53749,61648,55235,PRETRIAL,Swartz,Cyril,NULL,Male,Caucasian,02/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,Copy,1,0 +53749,61648,55235,PRETRIAL,Swartz,Cyril,NULL,Male,Caucasian,02/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +54325,61625,55938,PRETRIAL,Previl,Eugene,Junior,Male,African-American,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/29/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +54325,61625,55938,PRETRIAL,Previl,Eugene,Junior,Male,African-American,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/29/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +54325,61625,55938,PRETRIAL,Previl,Eugene,Junior,Male,African-American,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54361,61676,55984,PRETRIAL,Jacobs,Stephanie,Lynn,Female,Caucasian,01/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +54361,61676,55984,PRETRIAL,Jacobs,Stephanie,Lynn,Female,Caucasian,01/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +54361,61676,55984,PRETRIAL,Jacobs,Stephanie,Lynn,Female,Caucasian,01/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +41698,61690,55997,PRETRIAL,Stilley,Justin,NULL,Male,Caucasian,06/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.31,7,Medium,New,1,0 +41698,61690,55997,PRETRIAL,Stilley,Justin,NULL,Male,Caucasian,06/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +41698,61690,55997,PRETRIAL,Stilley,Justin,NULL,Male,Caucasian,06/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +40644,61725,56026,Probation,TOMSELLI,ISADORE,SAL,Male,Caucasian,10/18/53,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/30/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +40644,61725,56026,Probation,TOMSELLI,ISADORE,SAL,Male,Caucasian,10/18/53,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +40644,61725,56026,Probation,TOMSELLI,ISADORE,SAL,Male,Caucasian,10/18/53,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +31619,61697,56003,PRETRIAL,Lozano,Juxael,NULL,Male,Hispanic,04/17/81,17,All Scales,Intake,English,Post Sentence,Probation,Separated,4/30/13 0:00,2,Medium,7,Risk of Violence,-2.76,2,Low,New,1,0 +31619,61697,56003,PRETRIAL,Lozano,Juxael,NULL,Male,Hispanic,04/17/81,17,All Scales,Intake,English,Post Sentence,Probation,Separated,4/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +31619,61697,56003,PRETRIAL,Lozano,Juxael,NULL,Male,Hispanic,04/17/81,17,All Scales,Intake,English,Post Sentence,Probation,Separated,4/30/13 0:00,2,Medium,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +54381,61704,56010,PRETRIAL,Martinez,Oscar,NULL,Male,Hispanic,07/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,4/30/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +54381,61704,56010,PRETRIAL,Martinez,Oscar,NULL,Male,Hispanic,07/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +54381,61704,56010,PRETRIAL,Martinez,Oscar,NULL,Male,Hispanic,07/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +48594,61711,56016,PRETRIAL,Queiroz,Diego,Alisson,Male,Caucasian,06/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +48594,61711,56016,PRETRIAL,Queiroz,Diego,Alisson,Male,Caucasian,06/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +48594,61711,56016,PRETRIAL,Queiroz,Diego,Alisson,Male,Caucasian,06/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +34393,61718,33542,PRETRIAL,Alton,James,NULL,Male,Caucasian,07/22/59,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,Copy,1,0 +34393,61718,33542,PRETRIAL,Alton,James,NULL,Male,Caucasian,07/22/59,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,Copy,1,0 +34393,61718,33542,PRETRIAL,Alton,James,NULL,Male,Caucasian,07/22/59,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +33010,61723,56024,PRETRIAL,Kjelson,Christopher,NULL,Male,Caucasian,10/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,New,1,0 +33010,61723,56024,PRETRIAL,Kjelson,Christopher,NULL,Male,Caucasian,10/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.8,10,High,New,1,0 +33010,61723,56024,PRETRIAL,Kjelson,Christopher,NULL,Male,Caucasian,10/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +54369,61685,55993,PRETRIAL,HIN,MICHAEL,H,Male,Caucasian,01/23/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +54369,61685,55993,PRETRIAL,HIN,MICHAEL,H,Male,Caucasian,01/23/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-2.67,1,Low,New,1,0 +54369,61685,55993,PRETRIAL,HIN,MICHAEL,H,Male,Caucasian,01/23/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +40975,61702,56008,PRETRIAL,Floberg,Kimberly,NULL,Female,Caucasian,08/08/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/30/13 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +40975,61702,56008,PRETRIAL,Floberg,Kimberly,NULL,Female,Caucasian,08/08/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/30/13 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +40975,61702,56008,PRETRIAL,Floberg,Kimberly,NULL,Female,Caucasian,08/08/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54396,61727,56028,Probation,Carballosa,Edward,NULL,Male,Hispanic,12/13/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +54396,61727,56028,Probation,Carballosa,Edward,NULL,Male,Hispanic,12/13/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +54396,61727,56028,Probation,Carballosa,Edward,NULL,Male,Hispanic,12/13/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +12528,61681,55989,PRETRIAL,McDonald,Latta,NULL,Male,African-American,10/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +12528,61681,55989,PRETRIAL,McDonald,Latta,NULL,Male,African-American,10/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +12528,61681,55989,PRETRIAL,McDonald,Latta,NULL,Male,African-American,10/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54392,61720,56021,Probation,BILES,JOHN,EDMUND,Male,Caucasian,02/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +54392,61720,56021,Probation,BILES,JOHN,EDMUND,Male,Caucasian,02/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +54392,61720,56021,Probation,BILES,JOHN,EDMUND,Male,Caucasian,02/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +46563,61673,55981,PRETRIAL,STEVENS,TIMOTHY,NULL,Male,African-American,07/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +46563,61673,55981,PRETRIAL,STEVENS,TIMOTHY,NULL,Male,African-American,07/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,4,High,8,Risk of Recidivism,0.16,8,High,New,1,0 +46563,61673,55981,PRETRIAL,STEVENS,TIMOTHY,NULL,Male,African-American,07/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,4,High,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54363,61678,55986,PRETRIAL,WALKER,TYRIE,DEVANTE,Male,African-American,01/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +54363,61678,55986,PRETRIAL,WALKER,TYRIE,DEVANTE,Male,African-American,01/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,4,High,8,Risk of Recidivism,0.09,8,High,New,1,0 +54363,61678,55986,PRETRIAL,WALKER,TYRIE,DEVANTE,Male,African-American,01/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54365,61680,55988,PRETRIAL,Saintval,Ovento,NULL,Male,Other,03/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/30/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +54365,61680,55988,PRETRIAL,Saintval,Ovento,NULL,Male,Other,03/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +54365,61680,55988,PRETRIAL,Saintval,Ovento,NULL,Male,Other,03/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54378,61699,56005,Probation,Cabrera,Rafael,NULL,Male,Hispanic,05/31/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/30/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +54378,61699,56005,Probation,Cabrera,Rafael,NULL,Male,Hispanic,05/31/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +54378,61699,56005,Probation,Cabrera,Rafael,NULL,Male,Hispanic,05/31/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54380,61701,56007,Probation,MATHEWS,TACCULAR,A,Male,African-American,08/17/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +54380,61701,56007,Probation,MATHEWS,TACCULAR,A,Male,African-American,08/17/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +54380,61701,56007,Probation,MATHEWS,TACCULAR,A,Male,African-American,08/17/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54370,61686,55994,PRETRIAL,Munoz,Ronald,NULL,Male,Hispanic,10/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +54370,61686,55994,PRETRIAL,Munoz,Ronald,NULL,Male,Hispanic,10/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +54370,61686,55994,PRETRIAL,Munoz,Ronald,NULL,Male,Hispanic,10/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54393,61722,56023,Probation,navoy,chad,NULL,Male,Caucasian,08/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +54393,61722,56023,Probation,navoy,chad,NULL,Male,Caucasian,08/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +54393,61722,56023,Probation,navoy,chad,NULL,Male,Caucasian,08/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54374,61693,56000,Probation,ELIAS,ERIKA,NULL,Female,Hispanic,08/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +54374,61693,56000,Probation,ELIAS,ERIKA,NULL,Female,Hispanic,08/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +54374,61693,56000,Probation,ELIAS,ERIKA,NULL,Female,Hispanic,08/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54375,61694,56001,Probation,DiNatale,Carla,Lynn,Female,Caucasian,08/05/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +54375,61694,56001,Probation,DiNatale,Carla,Lynn,Female,Caucasian,08/05/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +54375,61694,56001,Probation,DiNatale,Carla,Lynn,Female,Caucasian,08/05/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54384,61707,56012,PRETRIAL,Perkins,Sidney,NULL,Male,Caucasian,11/21/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/30/13 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +54384,61707,56012,PRETRIAL,Perkins,Sidney,NULL,Male,Caucasian,11/21/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/30/13 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +54384,61707,56012,PRETRIAL,Perkins,Sidney,NULL,Male,Caucasian,11/21/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53139,61688,55996,Probation,Merson,Steven,A,Male,Other,05/08/53,17,All Scales,Intake,English,Other,Probation,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +53139,61688,55996,Probation,Merson,Steven,A,Male,Other,05/08/53,17,All Scales,Intake,English,Other,Probation,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +53139,61688,55996,Probation,Merson,Steven,A,Male,Other,05/08/53,17,All Scales,Intake,English,Other,Probation,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,1,Low,New,1,0 +54372,61691,55998,Probation,federici,james,NULL,Male,Caucasian,12/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +54372,61691,55998,Probation,federici,james,NULL,Male,Caucasian,12/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +54372,61691,55998,Probation,federici,james,NULL,Male,Caucasian,12/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54385,61709,56014,PRETRIAL,Nesbitt,Edwin,Karlos,Male,African-American,01/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +54385,61709,56014,PRETRIAL,Nesbitt,Edwin,Karlos,Male,African-American,01/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +54385,61709,56014,PRETRIAL,Nesbitt,Edwin,Karlos,Male,African-American,01/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +49794,61696,50714,Probation,ventura,brian,NULL,Male,Caucasian,12/03/71,17,All Scales,Intake,English,Conditional Release,Probation,Married,4/30/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +49794,61696,50714,Probation,ventura,brian,NULL,Male,Caucasian,12/03/71,17,All Scales,Intake,English,Conditional Release,Probation,Married,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.69,3,Low,New,1,0 +49794,61696,50714,Probation,ventura,brian,NULL,Male,Caucasian,12/03/71,17,All Scales,Intake,English,Conditional Release,Probation,Married,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54399,61730,56029,DRRD,Belford,Nathaniel,Lamar,Male,African-American,11/21/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,4,High,7,Risk of Violence,-0.56,10,High,New,1,0 +54399,61730,56029,DRRD,Belford,Nathaniel,Lamar,Male,African-American,11/21/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,4,High,8,Risk of Recidivism,1.52,10,High,New,1,0 +54399,61730,56029,DRRD,Belford,Nathaniel,Lamar,Male,African-American,11/21/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,4,High,18,Risk of Failure to Appear,22,4,Low,New,1,0 +54367,61683,55991,PRETRIAL,ROPER,SABRINA,NULL,Female,African-American,10/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +54367,61683,55991,PRETRIAL,ROPER,SABRINA,NULL,Female,African-American,10/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +54367,61683,55991,PRETRIAL,ROPER,SABRINA,NULL,Female,African-American,10/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54390,61717,56019,Probation,ULHERR,MICHAEL,NULL,Male,Caucasian,08/31/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/30/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +54390,61717,56019,Probation,ULHERR,MICHAEL,NULL,Male,Caucasian,08/31/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/30/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +54390,61717,56019,Probation,ULHERR,MICHAEL,NULL,Male,Caucasian,08/31/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +19693,61675,55983,Broward County,griffin,brendon,NULL,Male,African-American,03/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +19693,61675,55983,Broward County,griffin,brendon,NULL,Male,African-American,03/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +19693,61675,55983,Broward County,griffin,brendon,NULL,Male,African-American,03/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +54395,61726,56027,Probation,Paul,Eric,NULL,Male,African-American,11/20/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +54395,61726,56027,Probation,Paul,Eric,NULL,Male,African-American,11/20/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +54395,61726,56027,Probation,Paul,Eric,NULL,Male,African-American,11/20/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54366,61682,55990,PRETRIAL,Fullerton,Ruth,NULL,Female,Other,07/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +54366,61682,55990,PRETRIAL,Fullerton,Ruth,NULL,Female,Other,07/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +54366,61682,55990,PRETRIAL,Fullerton,Ruth,NULL,Female,Other,07/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54368,61684,55992,PRETRIAL,Davis,Martin,NULL,Male,African-American,10/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +54368,61684,55992,PRETRIAL,Davis,Martin,NULL,Male,African-American,10/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +54368,61684,55992,PRETRIAL,Davis,Martin,NULL,Male,African-American,10/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +40911,61703,56009,PRETRIAL,GLASS,DEGARRIAN,RASHAD,Male,African-American,03/19/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +40911,61703,56009,PRETRIAL,GLASS,DEGARRIAN,RASHAD,Male,African-American,03/19/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +40911,61703,56009,PRETRIAL,GLASS,DEGARRIAN,RASHAD,Male,African-American,03/19/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50923,61705,52052,PRETRIAL,Daphnis,Rovens,NULL,Male,African-American,07/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,Copy,1,0 +50923,61705,52052,PRETRIAL,Daphnis,Rovens,NULL,Male,African-American,07/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,Copy,1,0 +50923,61705,52052,PRETRIAL,Daphnis,Rovens,NULL,Male,African-American,07/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +54386,61712,56017,PRETRIAL,SMITH,CHARLES,EVANS,Male,African-American,01/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +54386,61712,56017,PRETRIAL,SMITH,CHARLES,EVANS,Male,African-American,01/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +54386,61712,56017,PRETRIAL,SMITH,CHARLES,EVANS,Male,African-American,01/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54362,61677,55985,PRETRIAL,KEMP,JOHANE,NULL,Female,Other,10/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/30/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +54362,61677,55985,PRETRIAL,KEMP,JOHANE,NULL,Female,Other,10/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +54362,61677,55985,PRETRIAL,KEMP,JOHANE,NULL,Female,Other,10/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54394,61724,56025,Probation,Refsnideraveiga,Tiffany,NULL,Male,Caucasian,10/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +54394,61724,56025,Probation,Refsnideraveiga,Tiffany,NULL,Male,Caucasian,10/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +54394,61724,56025,Probation,Refsnideraveiga,Tiffany,NULL,Male,Caucasian,10/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +30938,61715,52895,PRETRIAL,west,anthony,NULL,Male,African-American,10/13/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +30938,61715,52895,PRETRIAL,west,anthony,NULL,Male,African-American,10/13/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,6,Medium,New,1,0 +30938,61715,52895,PRETRIAL,west,anthony,NULL,Male,African-American,10/13/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54391,61719,56020,Probation,valenzuela,vincent,NULL,Male,Hispanic,07/10/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +54391,61719,56020,Probation,valenzuela,vincent,NULL,Male,Hispanic,07/10/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +54391,61719,56020,Probation,valenzuela,vincent,NULL,Male,Hispanic,07/10/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +35823,61689,35044,PRETRIAL,Serafin,Jaquan,NULL,Male,African-American,07/05/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,4,High,7,Risk of Violence,-0.88,9,High,Copy,1,0 +35823,61689,35044,PRETRIAL,Serafin,Jaquan,NULL,Male,African-American,07/05/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,4,High,8,Risk of Recidivism,1.06,10,High,Copy,1,0 +35823,61689,35044,PRETRIAL,Serafin,Jaquan,NULL,Male,African-American,07/05/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +54377,61698,56004,Probation,cambria,mary,NULL,Female,Caucasian,09/06/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,7,Risk of Violence,-4.37,1,Low,New,1,0 +54377,61698,56004,Probation,cambria,mary,NULL,Female,Caucasian,09/06/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +54377,61698,56004,Probation,cambria,mary,NULL,Female,Caucasian,09/06/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +42622,61728,42468,PRETRIAL,McCullough,Marsell,NULL,Male,Caucasian,01/02/89,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,4,High,7,Risk of Violence,0.18,10,High,New,1,0 +42622,61728,42468,PRETRIAL,McCullough,Marsell,NULL,Male,Caucasian,01/02/89,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +42622,61728,42468,PRETRIAL,McCullough,Marsell,NULL,Male,Caucasian,01/02/89,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,4,High,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +54364,61679,55987,PRETRIAL,WILLIS,MARC,ANTHONY,Male,African-American,01/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +54364,61679,55987,PRETRIAL,WILLIS,MARC,ANTHONY,Male,African-American,01/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +54364,61679,55987,PRETRIAL,WILLIS,MARC,ANTHONY,Male,African-American,01/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +48633,61729,49340,Probation,Geraldine,Glover,NULL,Female,African-American,01/03/68,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +48633,61729,49340,Probation,Geraldine,Glover,NULL,Female,African-American,01/03/68,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +48633,61729,49340,Probation,Geraldine,Glover,NULL,Female,African-American,01/03/68,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +51191,61716,52352,PRETRIAL,Brinson,Jameel,NULL,Male,African-American,02/18/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,4,High,7,Risk of Violence,-0.67,9,High,Copy,1,0 +51191,61716,52352,PRETRIAL,Brinson,Jameel,NULL,Male,African-American,02/18/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,4,High,8,Risk of Recidivism,0.38,9,High,Copy,1,0 +51191,61716,52352,PRETRIAL,Brinson,Jameel,NULL,Male,African-American,02/18/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +54379,61700,56006,PRETRIAL,SOHIT,CHRISTOPHER,NULL,Male,Other,08/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +54379,61700,56006,PRETRIAL,SOHIT,CHRISTOPHER,NULL,Male,Other,08/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +54379,61700,56006,PRETRIAL,SOHIT,CHRISTOPHER,NULL,Male,Other,08/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54371,61687,55995,PRETRIAL,Sisler,George,Randolph,Male,Caucasian,08/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +54371,61687,55995,PRETRIAL,Sisler,George,Randolph,Male,Caucasian,08/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +54371,61687,55995,PRETRIAL,Sisler,George,Randolph,Male,Caucasian,08/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +48988,61721,56022,PRETRIAL,Sumpter,Aqueelah,Naquay,Female,African-American,05/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +48988,61721,56022,PRETRIAL,Sumpter,Aqueelah,Naquay,Female,African-American,05/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +48988,61721,56022,PRETRIAL,Sumpter,Aqueelah,Naquay,Female,African-American,05/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52166,61674,55982,PRETRIAL,Henderson,Nicole,NULL,Female,African-American,02/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +52166,61674,55982,PRETRIAL,Henderson,Nicole,NULL,Female,African-American,02/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +52166,61674,55982,PRETRIAL,Henderson,Nicole,NULL,Female,African-American,02/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54373,61692,55999,Probation,Barthelmy,Judeline,NULL,Female,African-American,10/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +54373,61692,55999,Probation,Barthelmy,Judeline,NULL,Female,African-American,10/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +54373,61692,55999,Probation,Barthelmy,Judeline,NULL,Female,African-American,10/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54376,61695,56002,PRETRIAL,Beard,Joanne,NULL,Female,African-American,06/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +54376,61695,56002,PRETRIAL,Beard,Joanne,NULL,Female,African-American,06/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,10,High,New,1,0 +54376,61695,56002,PRETRIAL,Beard,Joanne,NULL,Female,African-American,06/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54387,61713,56018,PRETRIAL,wilson,ronald,NULL,Male,African-American,07/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.38,3,Low,New,1,0 +54387,61713,56018,PRETRIAL,wilson,ronald,NULL,Male,African-American,07/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +54387,61713,56018,PRETRIAL,wilson,ronald,NULL,Male,African-American,07/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54424,61781,56071,Probation,cumpton,gary,NULL,Male,Caucasian,01/15/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/1/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +54424,61781,56071,Probation,cumpton,gary,NULL,Male,Caucasian,01/15/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +54424,61781,56071,Probation,cumpton,gary,NULL,Male,Caucasian,01/15/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +3467,61742,3181,PRETRIAL,jackson,jermaine,NULL,Male,African-American,06/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,Copy,1,0 +3467,61742,3181,PRETRIAL,jackson,jermaine,NULL,Male,African-American,06/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,Copy,1,0 +3467,61742,3181,PRETRIAL,jackson,jermaine,NULL,Male,African-American,06/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +54416,61760,56054,Probation,hammock,walter,NULL,Male,Caucasian,03/23/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/1/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +54416,61760,56054,Probation,hammock,walter,NULL,Male,Caucasian,03/23/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +54416,61760,56054,Probation,hammock,walter,NULL,Male,Caucasian,03/23/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +46599,61755,47023,PRETRIAL,Thomas,Archie,NULL,Male,African-American,05/20/94,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/1/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +46599,61755,47023,PRETRIAL,Thomas,Archie,NULL,Male,African-American,05/20/94,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.69,3,Low,New,1,0 +46599,61755,47023,PRETRIAL,Thomas,Archie,NULL,Male,African-American,05/20/94,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/1/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54430,61789,56079,PRETRIAL,Williams,Maurice,Lamar,Male,African-American,08/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +54430,61789,56079,PRETRIAL,Williams,Maurice,Lamar,Male,African-American,08/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +54430,61789,56079,PRETRIAL,Williams,Maurice,Lamar,Male,African-American,08/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54402,61734,56033,PRETRIAL,Fraser,Paul,NULL,Male,African-American,09/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +54402,61734,56033,PRETRIAL,Fraser,Paul,NULL,Male,African-American,09/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +54402,61734,56033,PRETRIAL,Fraser,Paul,NULL,Male,African-American,09/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +41651,61768,56060,PRETRIAL,Chalashtori,Alexander,NULL,Male,Caucasian,12/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +41651,61768,56060,PRETRIAL,Chalashtori,Alexander,NULL,Male,Caucasian,12/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +41651,61768,56060,PRETRIAL,Chalashtori,Alexander,NULL,Male,Caucasian,12/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53475,61750,56047,PRETRIAL,PENDLEBURY,KRISTOPHER,NULL,Male,Caucasian,02/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +53475,61750,56047,PRETRIAL,PENDLEBURY,KRISTOPHER,NULL,Male,Caucasian,02/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +53475,61750,56047,PRETRIAL,PENDLEBURY,KRISTOPHER,NULL,Male,Caucasian,02/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53750,61752,55236,PRETRIAL,Sanchez,Cinthya,NULL,Female,Hispanic,08/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,Copy,1,0 +53750,61752,55236,PRETRIAL,Sanchez,Cinthya,NULL,Female,Hispanic,08/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,Copy,1,0 +53750,61752,55236,PRETRIAL,Sanchez,Cinthya,NULL,Female,Hispanic,08/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +54405,61737,56036,PRETRIAL,Brown,James,NULL,Male,African-American,11/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +54405,61737,56036,PRETRIAL,Brown,James,NULL,Male,African-American,11/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +54405,61737,56036,PRETRIAL,Brown,James,NULL,Male,African-American,11/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +23166,61771,36722,PRETRIAL,Laing,Tevin,Damar,Male,African-American,04/09/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +23166,61771,36722,PRETRIAL,Laing,Tevin,Damar,Male,African-American,04/09/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,4,High,8,Risk of Recidivism,0.73,10,High,New,1,0 +23166,61771,36722,PRETRIAL,Laing,Tevin,Damar,Male,African-American,04/09/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,4,High,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +46505,61773,56063,PRETRIAL,Brioso,Abraham,NULL,Male,Hispanic,06/21/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/1/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +46505,61773,56063,PRETRIAL,Brioso,Abraham,NULL,Male,Hispanic,06/21/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/1/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +46505,61773,56063,PRETRIAL,Brioso,Abraham,NULL,Male,Hispanic,06/21/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54422,61778,56068,Probation,CHEPINSKA,ANETA,NULL,Female,Caucasian,07/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/1/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +54422,61778,56068,Probation,CHEPINSKA,ANETA,NULL,Female,Caucasian,07/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +54422,61778,56068,Probation,CHEPINSKA,ANETA,NULL,Female,Caucasian,07/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54404,61736,56035,PRETRIAL,Fox,John,NULL,Male,Caucasian,02/13/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +54404,61736,56035,PRETRIAL,Fox,John,NULL,Male,Caucasian,02/13/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +54404,61736,56035,PRETRIAL,Fox,John,NULL,Male,Caucasian,02/13/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +19663,61765,56058,PRETRIAL,QUINITCHETT,LANCE,BOUVIER,Male,African-American,07/15/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +19663,61765,56058,PRETRIAL,QUINITCHETT,LANCE,BOUVIER,Male,African-American,07/15/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +19663,61765,56058,PRETRIAL,QUINITCHETT,LANCE,BOUVIER,Male,African-American,07/15/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +40967,61779,56069,PRETRIAL,Villa,Jose,Gomez,Male,Hispanic,11/26/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/1/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +40967,61779,56069,PRETRIAL,Villa,Jose,Gomez,Male,Hispanic,11/26/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/1/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +40967,61779,56069,PRETRIAL,Villa,Jose,Gomez,Male,Hispanic,11/26/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54427,61786,56076,PRETRIAL,Smith,Erica,NULL,Female,African-American,10/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +54427,61786,56076,PRETRIAL,Smith,Erica,NULL,Female,African-American,10/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,8,Risk of Recidivism,0.94,10,High,New,1,0 +54427,61786,56076,PRETRIAL,Smith,Erica,NULL,Female,African-American,10/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +54413,61757,56051,Probation,collazo,Leonel,NULL,Male,Hispanic,01/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +54413,61757,56051,Probation,collazo,Leonel,NULL,Male,Hispanic,01/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +54413,61757,56051,Probation,collazo,Leonel,NULL,Male,Hispanic,01/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54428,61787,56077,PRETRIAL,Pratt,Nicole,NULL,Female,African-American,02/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +54428,61787,56077,PRETRIAL,Pratt,Nicole,NULL,Female,African-American,02/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +54428,61787,56077,PRETRIAL,Pratt,Nicole,NULL,Female,African-American,02/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54411,61749,56046,PRETRIAL,HARRIS,GRACE,MCEWAN,Female,African-American,09/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +54411,61749,56046,PRETRIAL,HARRIS,GRACE,MCEWAN,Female,African-American,09/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +54411,61749,56046,PRETRIAL,HARRIS,GRACE,MCEWAN,Female,African-American,09/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +24814,61766,56059,PRETRIAL,Aguilar,Abimael,NULL,Female,Caucasian,05/27/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.83,2,Low,New,1,0 +24814,61766,56059,PRETRIAL,Aguilar,Abimael,NULL,Female,Caucasian,05/27/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +24814,61766,56059,PRETRIAL,Aguilar,Abimael,NULL,Female,Caucasian,05/27/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +18283,18926,17550,PRETRIAL,SISTRUNK,STEVEN,NULL,Male,Caucasian,01/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.12,4,Low,New,1,0 +18283,18926,17550,PRETRIAL,SISTRUNK,STEVEN,NULL,Male,Caucasian,01/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +18283,18926,17550,PRETRIAL,SISTRUNK,STEVEN,NULL,Male,Caucasian,01/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54400,61731,56030,PRETRIAL,BUCKHANAN,TERRY,NULL,Male,African-American,03/14/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +54400,61731,56030,PRETRIAL,BUCKHANAN,TERRY,NULL,Male,African-American,03/14/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,New,1,0 +54400,61731,56030,PRETRIAL,BUCKHANAN,TERRY,NULL,Male,African-American,03/14/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +18325,61745,56042,PRETRIAL,DIXON,LAMONT,A,Male,African-American,06/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/1/13 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +18325,61745,56042,PRETRIAL,DIXON,LAMONT,A,Male,African-American,06/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +18325,61745,56042,PRETRIAL,DIXON,LAMONT,A,Male,African-American,06/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/1/13 0:00,2,Medium,18,Risk of Failure to Appear,41,10,High,New,1,0 +21846,61770,56062,PRETRIAL,LUUS,NICKOLAS,LAWRENCE,Male,Other,07/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +21846,61770,56062,PRETRIAL,LUUS,NICKOLAS,LAWRENCE,Male,Other,07/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +21846,61770,56062,PRETRIAL,LUUS,NICKOLAS,LAWRENCE,Male,Other,07/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54401,61733,56032,PRETRIAL,Cezaire,Patrick,NULL,Male,Other,03/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +54401,61733,56032,PRETRIAL,Cezaire,Patrick,NULL,Male,Other,03/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +54401,61733,56032,PRETRIAL,Cezaire,Patrick,NULL,Male,Other,03/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54425,61782,56072,Probation,Forrest,Marjorie,NULL,Female,African-American,02/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +54425,61782,56072,Probation,Forrest,Marjorie,NULL,Female,African-American,02/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +54425,61782,56072,Probation,Forrest,Marjorie,NULL,Female,African-American,02/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +21294,61784,56074,PRETRIAL,Wilson,Fredrick,Geoffrey,Male,African-American,12/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,2,Medium,7,Risk of Violence,-2.65,2,Low,New,1,0 +21294,61784,56074,PRETRIAL,Wilson,Fredrick,Geoffrey,Male,African-American,12/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +21294,61784,56074,PRETRIAL,Wilson,Fredrick,Geoffrey,Male,African-American,12/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +41374,61775,56065,Probation,castor,clifford,NULL,Male,Caucasian,11/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +41374,61775,56065,Probation,castor,clifford,NULL,Male,Caucasian,11/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +41374,61775,56065,Probation,castor,clifford,NULL,Male,Caucasian,11/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54408,61740,56039,PRETRIAL,RIVERA,ASHLEY,NULL,Female,Caucasian,08/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +54408,61740,56039,PRETRIAL,RIVERA,ASHLEY,NULL,Female,Caucasian,08/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,8,High,New,1,0 +54408,61740,56039,PRETRIAL,RIVERA,ASHLEY,NULL,Female,Caucasian,08/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +48684,61747,56044,PRETRIAL,Oneal,Chaslin,NULL,Female,African-American,11/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +48684,61747,56044,PRETRIAL,Oneal,Chaslin,NULL,Female,African-American,11/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,9,High,New,1,0 +48684,61747,56044,PRETRIAL,Oneal,Chaslin,NULL,Female,African-American,11/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +33653,61761,56055,PRETRIAL,POPE,DONALD,NULL,Male,African-American,12/10/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +33653,61761,56055,PRETRIAL,POPE,DONALD,NULL,Male,African-American,12/10/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +33653,61761,56055,PRETRIAL,POPE,DONALD,NULL,Male,African-American,12/10/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +15541,16019,14862,PRETRIAL,SAMUELS,RICARDO,WINSTON,Male,African-American,08/18/80,22,Risk and Prescreen,Intake,English,Other,Probation,Significant Other,5/1/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +15541,16019,14862,PRETRIAL,SAMUELS,RICARDO,WINSTON,Male,African-American,08/18/80,22,Risk and Prescreen,Intake,English,Other,Probation,Significant Other,5/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +15541,16019,14862,PRETRIAL,SAMUELS,RICARDO,WINSTON,Male,African-American,08/18/80,22,Risk and Prescreen,Intake,English,Other,Probation,Significant Other,5/1/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +18363,61751,56048,PRETRIAL,SCHNEIDER,BRUCE,NULL,Male,Caucasian,10/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,5/1/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +18363,61751,56048,PRETRIAL,SCHNEIDER,BRUCE,NULL,Male,Caucasian,10/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +18363,61751,56048,PRETRIAL,SCHNEIDER,BRUCE,NULL,Male,Caucasian,10/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +42528,61785,56075,PRETRIAL,MILLER,CASANDRA,NULL,Female,Caucasian,02/27/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,4,High,7,Risk of Violence,-1.19,8,High,New,1,0 +42528,61785,56075,PRETRIAL,MILLER,CASANDRA,NULL,Female,Caucasian,02/27/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +42528,61785,56075,PRETRIAL,MILLER,CASANDRA,NULL,Female,Caucasian,02/27/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54418,61764,56057,Probation,jean,camillia,NULL,Female,African-American,05/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.28,3,Low,New,1,0 +54418,61764,56057,Probation,jean,camillia,NULL,Female,African-American,05/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +54418,61764,56057,Probation,jean,camillia,NULL,Female,African-American,05/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +54415,61759,56053,PRETRIAL,Levesen,Andrew,NULL,Male,Caucasian,03/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +54415,61759,56053,PRETRIAL,Levesen,Andrew,NULL,Male,Caucasian,03/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +54415,61759,56053,PRETRIAL,Levesen,Andrew,NULL,Male,Caucasian,03/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +10649,61738,56037,PRETRIAL,Guerrier,Herlin,NULL,Male,African-American,01/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,New,1,0 +10649,61738,56037,PRETRIAL,Guerrier,Herlin,NULL,Male,African-American,01/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +10649,61738,56037,PRETRIAL,Guerrier,Herlin,NULL,Male,African-American,01/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54412,61756,56050,Probation,Matos,Francisco,Garcia,Male,Hispanic,05/05/56,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/1/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +54412,61756,56050,Probation,Matos,Francisco,Garcia,Male,Hispanic,05/05/56,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +54412,61756,56050,Probation,Matos,Francisco,Garcia,Male,Hispanic,05/05/56,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +47312,61743,56041,PRETRIAL,Walcott,Keevin,NULL,Male,African-American,04/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,7,Risk of Violence,-0.44,10,High,New,1,0 +47312,61743,56041,PRETRIAL,Walcott,Keevin,NULL,Male,African-American,04/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +47312,61743,56041,PRETRIAL,Walcott,Keevin,NULL,Male,African-American,04/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +18283,61772,17550,PRETRIAL,SISTRUNK,STEVEN,NULL,Male,Caucasian,01/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,2,Medium,7,Risk of Violence,-2.76,2,Low,Copy,1,0 +18283,61772,17550,PRETRIAL,SISTRUNK,STEVEN,NULL,Male,Caucasian,01/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,Copy,1,0 +18283,61772,17550,PRETRIAL,SISTRUNK,STEVEN,NULL,Male,Caucasian,01/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +54403,61735,56034,PRETRIAL,Bauza,Nelson,NULL,Male,Caucasian,10/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/1/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +54403,61735,56034,PRETRIAL,Bauza,Nelson,NULL,Male,Caucasian,10/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +54403,61735,56034,PRETRIAL,Bauza,Nelson,NULL,Male,Caucasian,10/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54423,61780,56070,Probation,MARCELLUS,GEORGES,A,Male,African-American,07/30/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/13 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +54423,61780,56070,Probation,MARCELLUS,GEORGES,A,Male,African-American,07/30/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +54423,61780,56070,Probation,MARCELLUS,GEORGES,A,Male,African-American,07/30/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54429,61788,56078,PRETRIAL,Smellie,Sheldon,NULL,Male,Other,11/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +54429,61788,56078,PRETRIAL,Smellie,Sheldon,NULL,Male,Other,11/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +54429,61788,56078,PRETRIAL,Smellie,Sheldon,NULL,Male,Other,11/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54407,61741,56040,PRETRIAL,ROSS,SEDRICK,NULL,Male,African-American,11/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +54407,61741,56040,PRETRIAL,ROSS,SEDRICK,NULL,Male,African-American,11/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,8,Risk of Recidivism,0.41,9,High,New,1,0 +54407,61741,56040,PRETRIAL,ROSS,SEDRICK,NULL,Male,African-American,11/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +54421,61774,56064,PRETRIAL,HANKERSON,GREGORY,NULL,Male,African-American,03/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +54421,61774,56064,PRETRIAL,HANKERSON,GREGORY,NULL,Male,African-American,03/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +54421,61774,56064,PRETRIAL,HANKERSON,GREGORY,NULL,Male,African-American,03/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +11314,61732,56031,PRETRIAL,Shimko,TImothey,John,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,7,Risk of Violence,-0.54,10,High,New,1,0 +11314,61732,56031,PRETRIAL,Shimko,TImothey,John,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +11314,61732,56031,PRETRIAL,Shimko,TImothey,John,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +54426,61783,56073,Probation,rowe,anastasia,NULL,Female,Caucasian,08/21/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/1/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +54426,61783,56073,Probation,rowe,anastasia,NULL,Female,Caucasian,08/21/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,New,1,0 +54426,61783,56073,Probation,rowe,anastasia,NULL,Female,Caucasian,08/21/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53203,61753,54646,PRETRIAL,Brown,Joshua,NULL,Male,Caucasian,05/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/1/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,Copy,1,0 +53203,61753,54646,PRETRIAL,Brown,Joshua,NULL,Male,Caucasian,05/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,Copy,1,0 +53203,61753,54646,PRETRIAL,Brown,Joshua,NULL,Male,Caucasian,05/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +6594,61767,6189,PRETRIAL,MCBURROWS,MARCO,L,Male,African-American,08/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,Copy,1,0 +6594,61767,6189,PRETRIAL,MCBURROWS,MARCO,L,Male,African-American,08/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.64,10,High,Copy,1,0 +6594,61767,6189,PRETRIAL,MCBURROWS,MARCO,L,Male,African-American,08/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +54420,61769,56061,PRETRIAL,Chimera,Anthony,Edward,Male,Caucasian,09/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +54420,61769,56061,PRETRIAL,Chimera,Anthony,Edward,Male,Caucasian,09/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +54420,61769,56061,PRETRIAL,Chimera,Anthony,Edward,Male,Caucasian,09/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54406,61739,56038,PRETRIAL,Suggs,Shemeka,NULL,Female,African-American,06/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +54406,61739,56038,PRETRIAL,Suggs,Shemeka,NULL,Female,African-American,06/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +54406,61739,56038,PRETRIAL,Suggs,Shemeka,NULL,Female,African-American,06/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54409,61746,56043,PRETRIAL,Mack,Michael,NULL,Male,African-American,02/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.53,3,Low,New,1,0 +54409,61746,56043,PRETRIAL,Mack,Michael,NULL,Male,African-American,02/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +54409,61746,56043,PRETRIAL,Mack,Michael,NULL,Male,African-American,02/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54410,61748,56045,PRETRIAL,Khan,Sayyid,NULL,Male,Caucasian,10/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +54410,61748,56045,PRETRIAL,Khan,Sayyid,NULL,Male,Caucasian,10/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +54410,61748,56045,PRETRIAL,Khan,Sayyid,NULL,Male,Caucasian,10/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +41335,61776,56066,PRETRIAL,Santana,Miguel,NULL,Male,Hispanic,01/27/64,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Married,5/1/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +41335,61776,56066,PRETRIAL,Santana,Miguel,NULL,Male,Hispanic,01/27/64,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Married,5/1/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +41335,61776,56066,PRETRIAL,Santana,Miguel,NULL,Male,Hispanic,01/27/64,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Married,5/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +43697,61825,56111,PRETRIAL,PIERRE,JEFF,GARY,Male,African-American,07/24/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +43697,61825,56111,PRETRIAL,PIERRE,JEFF,GARY,Male,African-American,07/24/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +43697,61825,56111,PRETRIAL,PIERRE,JEFF,GARY,Male,African-American,07/24/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53024,61790,54435,PRETRIAL,Welly,Dylan,NULL,Male,Caucasian,04/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,Copy,1,0 +53024,61790,54435,PRETRIAL,Welly,Dylan,NULL,Male,Caucasian,04/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.16,6,Medium,Copy,1,0 +53024,61790,54435,PRETRIAL,Welly,Dylan,NULL,Male,Caucasian,04/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +25191,61797,56086,PRETRIAL,PULLIAM,LORENZO,JAIME,Male,African-American,09/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +25191,61797,56086,PRETRIAL,PULLIAM,LORENZO,JAIME,Male,African-American,09/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,4,High,8,Risk of Recidivism,0.45,9,High,New,1,0 +25191,61797,56086,PRETRIAL,PULLIAM,LORENZO,JAIME,Male,African-American,09/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54440,61804,56093,Probation,Ortiz,Manuel,NULL,Male,Hispanic,08/09/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +54440,61804,56093,Probation,Ortiz,Manuel,NULL,Male,Hispanic,08/09/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +54440,61804,56093,Probation,Ortiz,Manuel,NULL,Male,Hispanic,08/09/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54450,61818,56105,Probation,bingham,brenda,NULL,Female,African-American,10/04/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +54450,61818,56105,Probation,bingham,brenda,NULL,Female,African-American,10/04/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +54450,61818,56105,Probation,bingham,brenda,NULL,Female,African-American,10/04/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +54459,61830,56116,Probation,Falcon,Ulyses,NULL,Male,Caucasian,02/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +54459,61830,56116,Probation,Falcon,Ulyses,NULL,Male,Caucasian,02/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +54459,61830,56116,Probation,Falcon,Ulyses,NULL,Male,Caucasian,02/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +47819,61834,48429,PRETRIAL,Anchia,Christopher,NULL,Male,Caucasian,11/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,Copy,1,0 +47819,61834,48429,PRETRIAL,Anchia,Christopher,NULL,Male,Caucasian,11/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,Copy,1,0 +47819,61834,48429,PRETRIAL,Anchia,Christopher,NULL,Male,Caucasian,11/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +29231,61792,56081,PRETRIAL,knauff,elloitt,NULL,Male,Caucasian,05/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +29231,61792,56081,PRETRIAL,knauff,elloitt,NULL,Male,Caucasian,05/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +29231,61792,56081,PRETRIAL,knauff,elloitt,NULL,Male,Caucasian,05/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +40847,61809,40491,PRETRIAL,Gamaa,Ahmed,Ali,Male,Caucasian,04/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,Copy,1,0 +40847,61809,40491,PRETRIAL,Gamaa,Ahmed,Ali,Male,Caucasian,04/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,Copy,1,0 +40847,61809,40491,PRETRIAL,Gamaa,Ahmed,Ali,Male,Caucasian,04/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +54433,61795,56084,PRETRIAL,Christie,Barrington,NULL,Male,Other,03/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/2/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +54433,61795,56084,PRETRIAL,Christie,Barrington,NULL,Male,Other,03/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +54433,61795,56084,PRETRIAL,Christie,Barrington,NULL,Male,Other,03/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54446,61813,56100,Probation,TRONOLONE,VICTORIA,A,Female,Caucasian,04/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +54446,61813,56100,Probation,TRONOLONE,VICTORIA,A,Female,Caucasian,04/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +54446,61813,56100,Probation,TRONOLONE,VICTORIA,A,Female,Caucasian,04/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +48040,61814,56101,Probation,fennell,robert,NULL,Male,Caucasian,11/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +48040,61814,56101,Probation,fennell,robert,NULL,Male,Caucasian,11/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +48040,61814,56101,Probation,fennell,robert,NULL,Male,Caucasian,11/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54438,61801,56090,PRETRIAL,Bigger,Clayton,NULL,Male,Caucasian,11/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +54438,61801,56090,PRETRIAL,Bigger,Clayton,NULL,Male,Caucasian,11/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +54438,61801,56090,PRETRIAL,Bigger,Clayton,NULL,Male,Caucasian,11/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54448,61816,56103,Probation,Denard,Shanice,NULL,Female,African-American,01/03/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +54448,61816,56103,Probation,Denard,Shanice,NULL,Female,African-American,01/03/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +54448,61816,56103,Probation,Denard,Shanice,NULL,Female,African-American,01/03/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54453,61822,56108,Probation,DEJESUS,ANGEL,LUIS,Male,Hispanic,09/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +54453,61822,56108,Probation,DEJESUS,ANGEL,LUIS,Male,Hispanic,09/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +54453,61822,56108,Probation,DEJESUS,ANGEL,LUIS,Male,Hispanic,09/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54458,61829,56115,Probation,cummins,lazaro,NULL,Male,Caucasian,07/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-2.99,1,Low,New,1,0 +54458,61829,56115,Probation,cummins,lazaro,NULL,Male,Caucasian,07/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +54458,61829,56115,Probation,cummins,lazaro,NULL,Male,Caucasian,07/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54432,61793,56082,PRETRIAL,Banton,Carey,Anthony,Male,African-American,06/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +54432,61793,56082,PRETRIAL,Banton,Carey,Anthony,Male,African-American,06/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +54432,61793,56082,PRETRIAL,Banton,Carey,Anthony,Male,African-American,06/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +15192,61808,14531,PRETRIAL,ISMAEL,GASNER,PECOIS,Male,African-American,10/11/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +15192,61808,14531,PRETRIAL,ISMAEL,GASNER,PECOIS,Male,African-American,10/11/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,0.16,7,Medium,New,1,0 +15192,61808,14531,PRETRIAL,ISMAEL,GASNER,PECOIS,Male,African-American,10/11/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,21,3,Low,New,1,0 +54443,61806,56095,PRETRIAL,YOUNG,MONIQUE,NULL,Female,Caucasian,07/13/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/2/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +54443,61806,56095,PRETRIAL,YOUNG,MONIQUE,NULL,Female,Caucasian,07/13/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.62,2,Low,New,1,0 +54443,61806,56095,PRETRIAL,YOUNG,MONIQUE,NULL,Female,Caucasian,07/13/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53338,60334,54801,PRETRIAL,Otto,Rachel,NULL,Female,Caucasian,07/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +53338,60334,54801,PRETRIAL,Otto,Rachel,NULL,Female,Caucasian,07/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +53338,60334,54801,PRETRIAL,Otto,Rachel,NULL,Female,Caucasian,07/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +33333,61824,56110,PRETRIAL,Rhoomes,Shawn,NULL,Male,African-American,09/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +33333,61824,56110,PRETRIAL,Rhoomes,Shawn,NULL,Male,African-American,09/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,4,High,8,Risk of Recidivism,0.33,9,High,New,1,0 +33333,61824,56110,PRETRIAL,Rhoomes,Shawn,NULL,Male,African-American,09/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54456,61827,56113,Probation,wax,eddy,NULL,Male,Caucasian,10/15/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/2/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +54456,61827,56113,Probation,wax,eddy,NULL,Male,Caucasian,10/15/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +54456,61827,56113,Probation,wax,eddy,NULL,Male,Caucasian,10/15/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54435,61798,56087,PRETRIAL,Nelson,James,NULL,Male,Other,06/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +54435,61798,56087,PRETRIAL,Nelson,James,NULL,Male,Other,06/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +54435,61798,56087,PRETRIAL,Nelson,James,NULL,Male,Other,06/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53428,61819,54921,Probation,Poulos,Steven,NULL,Male,Caucasian,02/01/61,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.97,1,Low,New,1,0 +53428,61819,54921,Probation,Poulos,Steven,NULL,Male,Caucasian,02/01/61,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +53428,61819,54921,Probation,Poulos,Steven,NULL,Male,Caucasian,02/01/61,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,38,10,High,New,1,0 +31349,61832,56118,PRETRIAL,Newell,Yackcain,Hugh,Male,Other,07/05/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +31349,61832,56118,PRETRIAL,Newell,Yackcain,Hugh,Male,Other,07/05/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +31349,61832,56118,PRETRIAL,Newell,Yackcain,Hugh,Male,Other,07/05/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54455,61826,56112,Probation,Martinez,Odalis,NULL,Female,Hispanic,12/03/66,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,5/2/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +54455,61826,56112,Probation,Martinez,Odalis,NULL,Female,Hispanic,12/03/66,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +54455,61826,56112,Probation,Martinez,Odalis,NULL,Female,Hispanic,12/03/66,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54461,61833,56119,Probation,Housen,Russell,NULL,Male,Hispanic,10/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/2/13 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +54461,61833,56119,Probation,Housen,Russell,NULL,Male,Hispanic,10/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/2/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +54461,61833,56119,Probation,Housen,Russell,NULL,Male,Hispanic,10/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +23691,61803,56092,PRETRIAL,Battle,Jacqueline,NULL,Female,African-American,08/16/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +23691,61803,56092,PRETRIAL,Battle,Jacqueline,NULL,Female,African-American,08/16/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,9,High,New,1,0 +23691,61803,56092,PRETRIAL,Battle,Jacqueline,NULL,Female,African-American,08/16/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +54441,61805,56094,Probation,SANCHEZ,JACQUELINE,M,Female,Hispanic,10/07/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +54441,61805,56094,Probation,SANCHEZ,JACQUELINE,M,Female,Hispanic,10/07/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +54441,61805,56094,Probation,SANCHEZ,JACQUELINE,M,Female,Hispanic,10/07/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +27310,61812,56099,Probation,garcia,george,NULL,Male,Hispanic,09/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +27310,61812,56099,Probation,garcia,george,NULL,Male,Hispanic,09/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +27310,61812,56099,Probation,garcia,george,NULL,Male,Hispanic,09/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54431,61791,56080,PRETRIAL,Miller,Ivory,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,New,1,0 +54431,61791,56080,PRETRIAL,Miller,Ivory,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +54431,61791,56080,PRETRIAL,Miller,Ivory,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54437,61800,56089,PRETRIAL,PETUSEVSKY,MONICA,NULL,Male,Caucasian,10/26/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +54437,61800,56089,PRETRIAL,PETUSEVSKY,MONICA,NULL,Male,Caucasian,10/26/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-2.62,1,Low,New,1,0 +54437,61800,56089,PRETRIAL,PETUSEVSKY,MONICA,NULL,Male,Caucasian,10/26/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54449,61817,56104,Probation,Santiago,Myra,NULL,Female,Hispanic,10/06/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +54449,61817,56104,Probation,Santiago,Myra,NULL,Female,Hispanic,10/06/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +54449,61817,56104,Probation,Santiago,Myra,NULL,Female,Hispanic,10/06/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +54434,61796,56085,PRETRIAL,KOSKI,JEFFERY,NULL,Male,Caucasian,02/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +54434,61796,56085,PRETRIAL,KOSKI,JEFFERY,NULL,Male,Caucasian,02/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +54434,61796,56085,PRETRIAL,KOSKI,JEFFERY,NULL,Male,Caucasian,02/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54452,61821,56107,Probation,siaglo,heather,NULL,Female,Caucasian,11/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +54452,61821,56107,Probation,siaglo,heather,NULL,Female,Caucasian,11/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +54452,61821,56107,Probation,siaglo,heather,NULL,Female,Caucasian,11/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +8915,61794,56083,PRETRIAL,POWELL,DERRICK,NULL,Male,African-American,07/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +8915,61794,56083,PRETRIAL,POWELL,DERRICK,NULL,Male,African-American,07/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +8915,61794,56083,PRETRIAL,POWELL,DERRICK,NULL,Male,African-American,07/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54444,61807,56096,PRETRIAL,Jackson,Jeffrey,NULL,Male,African-American,09/08/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-3.17,1,Low,New,1,0 +54444,61807,56096,PRETRIAL,Jackson,Jeffrey,NULL,Male,African-American,09/08/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +54444,61807,56096,PRETRIAL,Jackson,Jeffrey,NULL,Male,African-American,09/08/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +54447,61815,56102,Probation,Da Silva,Edson,NULL,Male,Hispanic,10/14/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +54447,61815,56102,Probation,Da Silva,Edson,NULL,Male,Hispanic,10/14/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +54447,61815,56102,Probation,Da Silva,Edson,NULL,Male,Hispanic,10/14/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54436,61799,56088,PRETRIAL,FORBES,WINSTON,ALEX,Male,African-American,06/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +54436,61799,56088,PRETRIAL,FORBES,WINSTON,ALEX,Male,African-American,06/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +54436,61799,56088,PRETRIAL,FORBES,WINSTON,ALEX,Male,African-American,06/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54439,61802,56091,PRETRIAL,Nicholls,Marco,Alexander,Male,Caucasian,08/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/2/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +54439,61802,56091,PRETRIAL,Nicholls,Marco,Alexander,Male,Caucasian,08/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/2/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +54439,61802,56091,PRETRIAL,Nicholls,Marco,Alexander,Male,Caucasian,08/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54454,61823,56109,PRETRIAL,HAWTHORNE,TYRONE,NULL,Male,Caucasian,02/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +54454,61823,56109,PRETRIAL,HAWTHORNE,TYRONE,NULL,Male,Caucasian,02/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +54454,61823,56109,PRETRIAL,HAWTHORNE,TYRONE,NULL,Male,Caucasian,02/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54457,61828,56114,Probation,Barrett,Rashid,NULL,Male,African-American,01/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/2/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +54457,61828,56114,Probation,Barrett,Rashid,NULL,Male,African-American,01/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/2/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +54457,61828,56114,Probation,Barrett,Rashid,NULL,Male,African-American,01/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +29515,61810,56097,PRETRIAL,PUFF,JOHN,NULL,Male,Caucasian,08/14/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/2/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +29515,61810,56097,PRETRIAL,PUFF,JOHN,NULL,Male,Caucasian,08/14/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +29515,61810,56097,PRETRIAL,PUFF,JOHN,NULL,Male,Caucasian,08/14/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54451,61820,56106,Probation,WILLIAMS,GITA,NULL,Female,Other,08/31/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/2/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +54451,61820,56106,Probation,WILLIAMS,GITA,NULL,Female,Other,08/31/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/2/13 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +54451,61820,56106,Probation,WILLIAMS,GITA,NULL,Female,Other,08/31/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54460,61831,56117,Probation,Rodriguez,Roberto,NULL,Male,Hispanic,12/21/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +54460,61831,56117,Probation,Rodriguez,Roberto,NULL,Male,Hispanic,12/21/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +54460,61831,56117,Probation,Rodriguez,Roberto,NULL,Male,Hispanic,12/21/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +46522,61870,56151,PRETRIAL,NEAL,AARON,J,Male,African-American,08/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +46522,61870,56151,PRETRIAL,NEAL,AARON,J,Male,African-American,08/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +46522,61870,56151,PRETRIAL,NEAL,AARON,J,Male,African-American,08/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54468,61841,56126,PRETRIAL,Demard,Makendy,NULL,Male,Other,06/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +54468,61841,56126,PRETRIAL,Demard,Makendy,NULL,Male,Other,06/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +54468,61841,56126,PRETRIAL,Demard,Makendy,NULL,Male,Other,06/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54477,61857,56139,Probation,Malfe,Thomas,Burt,Male,Caucasian,08/28/54,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +54477,61857,56139,Probation,Malfe,Thomas,Burt,Male,Caucasian,08/28/54,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +54477,61857,56139,Probation,Malfe,Thomas,Burt,Male,Caucasian,08/28/54,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +4698,61862,4388,PRETRIAL,Knight,Cemar,NULL,Male,African-American,01/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.99,4,Low,Copy,1,0 +4698,61862,4388,PRETRIAL,Knight,Cemar,NULL,Male,African-American,01/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,Copy,1,0 +4698,61862,4388,PRETRIAL,Knight,Cemar,NULL,Male,African-American,01/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +54464,61836,56121,PRETRIAL,Collins,Norma,NULL,Female,African-American,03/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +54464,61836,56121,PRETRIAL,Collins,Norma,NULL,Female,African-American,03/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +54464,61836,56121,PRETRIAL,Collins,Norma,NULL,Female,African-American,03/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52713,61849,54083,PRETRIAL,Soden,Joshua,NULL,Male,Caucasian,10/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,4,High,7,Risk of Violence,-0.57,10,High,Copy,1,0 +52713,61849,54083,PRETRIAL,Soden,Joshua,NULL,Male,Caucasian,10/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,4,High,8,Risk of Recidivism,0.78,10,High,Copy,1,0 +52713,61849,54083,PRETRIAL,Soden,Joshua,NULL,Male,Caucasian,10/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,4,High,18,Risk of Failure to Appear,35,10,High,Copy,1,0 +52713,61852,54083,PRETRIAL,Soden,Joshua,NULL,Male,Caucasian,10/01/87,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,4,High,7,Risk of Violence,-0.57,10,High,Copy,1,0 +52713,61852,54083,PRETRIAL,Soden,Joshua,NULL,Male,Caucasian,10/01/87,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,4,High,8,Risk of Recidivism,0.78,10,High,Copy,1,0 +52713,61852,54083,PRETRIAL,Soden,Joshua,NULL,Male,Caucasian,10/01/87,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,4,High,18,Risk of Failure to Appear,35,10,High,Copy,1,0 +54488,61873,56154,Probation,Henderson,Joseph,NULL,Male,Hispanic,12/10/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +54488,61873,56154,Probation,Henderson,Joseph,NULL,Male,Hispanic,12/10/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +54488,61873,56154,Probation,Henderson,Joseph,NULL,Male,Hispanic,12/10/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52140,61865,56146,Probation,Vaughn,Robert,NULL,Male,African-American,07/25/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +52140,61865,56146,Probation,Vaughn,Robert,NULL,Male,African-American,07/25/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,4,High,8,Risk of Recidivism,1.24,10,High,New,1,0 +52140,61865,56146,Probation,Vaughn,Robert,NULL,Male,African-American,07/25/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,4,High,18,Risk of Failure to Appear,31,8,High,New,1,0 +54487,61872,56153,Probation,Trew,William,NULL,Male,Caucasian,11/15/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +54487,61872,56153,Probation,Trew,William,NULL,Male,Caucasian,11/15/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +54487,61872,56153,Probation,Trew,William,NULL,Male,Caucasian,11/15/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +54470,61844,56129,PRETRIAL,Germain,JeanPierre,NULL,Male,African-American,11/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +54470,61844,56129,PRETRIAL,Germain,JeanPierre,NULL,Male,African-American,11/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +54470,61844,56129,PRETRIAL,Germain,JeanPierre,NULL,Male,African-American,11/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +15207,61868,56149,PRETRIAL,Miller,Anthony,NULL,Male,African-American,05/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,2,Medium,7,Risk of Violence,-2.65,2,Low,New,1,0 +15207,61868,56149,PRETRIAL,Miller,Anthony,NULL,Male,African-American,05/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +15207,61868,56149,PRETRIAL,Miller,Anthony,NULL,Male,African-American,05/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +5287,61842,56127,DRRD,Melville,Crystal,Carissa,Female,African-American,09/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.39,3,Low,New,1,0 +5287,61842,56127,DRRD,Melville,Crystal,Carissa,Female,African-American,09/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,8,High,New,1,0 +5287,61842,56127,DRRD,Melville,Crystal,Carissa,Female,African-American,09/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54479,61859,56141,PRETRIAL,MOORE,AHKEEN,SHAQUILLE,Male,African-American,06/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +54479,61859,56141,PRETRIAL,MOORE,AHKEEN,SHAQUILLE,Male,African-American,06/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +54479,61859,56141,PRETRIAL,MOORE,AHKEEN,SHAQUILLE,Male,African-American,06/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50472,65603,51498,Probation,PARAGUE,JUNE,S,Female,African-American,06/29/64,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +50472,65603,51498,Probation,PARAGUE,JUNE,S,Female,African-American,06/29/64,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,New,1,0 +50472,65603,51498,Probation,PARAGUE,JUNE,S,Female,African-American,06/29/64,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54467,61838,56123,PRETRIAL,Singleton,Terrance,NULL,Male,African-American,03/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +54467,61838,56123,PRETRIAL,Singleton,Terrance,NULL,Male,African-American,03/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +54467,61838,56123,PRETRIAL,Singleton,Terrance,NULL,Male,African-American,03/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54476,61856,56138,Probation,wain,linda,NULL,Female,Caucasian,09/25/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +54476,61856,56138,Probation,wain,linda,NULL,Female,Caucasian,09/25/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +54476,61856,56138,Probation,wain,linda,NULL,Female,Caucasian,09/25/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54482,61863,56144,Probation,TINTORI,TIMOTHY,NEIL,Male,Caucasian,03/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +54482,61863,56144,Probation,TINTORI,TIMOTHY,NEIL,Male,Caucasian,03/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +54482,61863,56144,Probation,TINTORI,TIMOTHY,NEIL,Male,Caucasian,03/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54480,61861,56143,Probation,HAINES,KYLE,M,Male,Caucasian,11/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +54480,61861,56143,Probation,HAINES,KYLE,M,Male,Caucasian,11/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +54480,61861,56143,Probation,HAINES,KYLE,M,Male,Caucasian,11/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +35385,61840,56125,PRETRIAL,Johnson,Billy,Eugene,Male,Caucasian,01/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +35385,61840,56125,PRETRIAL,Johnson,Billy,Eugene,Male,Caucasian,01/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +35385,61840,56125,PRETRIAL,Johnson,Billy,Eugene,Male,Caucasian,01/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +54170,61847,55743,PRETRIAL,MARTIN,REGINALD,NULL,Male,African-American,12/27/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +54170,61847,55743,PRETRIAL,MARTIN,REGINALD,NULL,Male,African-American,12/27/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +54170,61847,55743,PRETRIAL,MARTIN,REGINALD,NULL,Male,African-American,12/27/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,2,Low,New,1,0 +54484,61866,56147,Probation,mancuso,lisa,NULL,Female,Caucasian,02/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +54484,61866,56147,Probation,mancuso,lisa,NULL,Female,Caucasian,02/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +54484,61866,56147,Probation,mancuso,lisa,NULL,Female,Caucasian,02/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54471,61845,56130,PRETRIAL,Tinnell,Patrick,NULL,Male,Caucasian,12/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +54471,61845,56130,PRETRIAL,Tinnell,Patrick,NULL,Male,Caucasian,12/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +54471,61845,56130,PRETRIAL,Tinnell,Patrick,NULL,Male,Caucasian,12/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54469,61843,56128,PRETRIAL,Yount,Malcolm,John,Male,Caucasian,02/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +54469,61843,56128,PRETRIAL,Yount,Malcolm,John,Male,Caucasian,02/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +54469,61843,56128,PRETRIAL,Yount,Malcolm,John,Male,Caucasian,02/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +54478,61858,56140,Probation,duquette,ronald,NULL,Male,Caucasian,09/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +54478,61858,56140,Probation,duquette,ronald,NULL,Male,Caucasian,09/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +54478,61858,56140,Probation,duquette,ronald,NULL,Male,Caucasian,09/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54463,61835,56120,PRETRIAL,Thompson,Timothy,NULL,Male,African-American,11/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/3/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +54463,61835,56120,PRETRIAL,Thompson,Timothy,NULL,Male,African-American,11/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/3/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +54463,61835,56120,PRETRIAL,Thompson,Timothy,NULL,Male,African-American,11/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54473,61850,56133,Probation,Callins,Kendrick,NULL,Male,African-American,11/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.83,2,Low,New,1,0 +54473,61850,56133,Probation,Callins,Kendrick,NULL,Male,African-American,11/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +54473,61850,56133,Probation,Callins,Kendrick,NULL,Male,African-American,11/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54465,61837,56122,PRETRIAL,Telsaint,Jeffrey,NULL,Male,African-American,04/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +54465,61837,56122,PRETRIAL,Telsaint,Jeffrey,NULL,Male,African-American,04/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,4,High,8,Risk of Recidivism,0.93,10,High,New,1,0 +54465,61837,56122,PRETRIAL,Telsaint,Jeffrey,NULL,Male,African-American,04/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54486,61871,56152,PRETRIAL,PACCIONE,LONNIE,NULL,Male,Caucasian,04/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/3/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +54486,61871,56152,PRETRIAL,PACCIONE,LONNIE,NULL,Male,Caucasian,04/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/3/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +54486,61871,56152,PRETRIAL,PACCIONE,LONNIE,NULL,Male,Caucasian,04/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54481,61860,56142,PRETRIAL,YOUNG,GREGORY,S,Male,Caucasian,08/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +54481,61860,56142,PRETRIAL,YOUNG,GREGORY,S,Male,Caucasian,08/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +54481,61860,56142,PRETRIAL,YOUNG,GREGORY,S,Male,Caucasian,08/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +35251,61851,56134,PRETRIAL,Jeannestal,Ismael,NULL,Male,Other,03/05/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/3/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +35251,61851,56134,PRETRIAL,Jeannestal,Ismael,NULL,Male,Other,03/05/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +35251,61851,56134,PRETRIAL,Jeannestal,Ismael,NULL,Male,Other,03/05/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/3/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +43102,61855,56137,PRETRIAL,Ricciardi,Michael,NULL,Male,Caucasian,07/08/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +43102,61855,56137,PRETRIAL,Ricciardi,Michael,NULL,Male,Caucasian,07/08/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +43102,61855,56137,PRETRIAL,Ricciardi,Michael,NULL,Male,Caucasian,07/08/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54483,61864,56145,Probation,Espinosa,Jose,B,Male,Hispanic,11/19/53,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/3/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +54483,61864,56145,Probation,Espinosa,Jose,B,Male,Hispanic,11/19/53,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/3/13 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +54483,61864,56145,Probation,Espinosa,Jose,B,Male,Hispanic,11/19/53,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +46546,61867,56148,PRETRIAL,HILT,ALBERT,NULL,Male,African-American,11/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +46546,61867,56148,PRETRIAL,HILT,ALBERT,NULL,Male,African-American,11/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +46546,61867,56148,PRETRIAL,HILT,ALBERT,NULL,Male,African-American,11/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54485,61869,56150,Probation,espinal,joadny,NULL,Male,Other,01/31/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +54485,61869,56150,Probation,espinal,joadny,NULL,Male,Other,01/31/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +54485,61869,56150,Probation,espinal,joadny,NULL,Male,Other,01/31/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/3/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54466,61839,56124,PRETRIAL,Jones,Tangela,NULL,Female,African-American,09/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +54466,61839,56124,PRETRIAL,Jones,Tangela,NULL,Female,African-American,09/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +54466,61839,56124,PRETRIAL,Jones,Tangela,NULL,Female,African-American,09/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54472,61846,56131,PRETRIAL,Hoofatt,Peter,NULL,Male,Other,05/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +54472,61846,56131,PRETRIAL,Hoofatt,Peter,NULL,Male,Other,05/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +54472,61846,56131,PRETRIAL,Hoofatt,Peter,NULL,Male,Other,05/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45453,61848,56132,PRETRIAL,Rubel,Jeffrey,Paul,Male,Caucasian,07/05/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/3/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +45453,61848,56132,PRETRIAL,Rubel,Jeffrey,Paul,Male,Caucasian,07/05/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/3/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +45453,61848,56132,PRETRIAL,Rubel,Jeffrey,Paul,Male,Caucasian,07/05/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/3/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54502,61890,56170,PRETRIAL,christopher,loosier,NULL,Male,Caucasian,07/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +54502,61890,56170,PRETRIAL,christopher,loosier,NULL,Male,Caucasian,07/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +54502,61890,56170,PRETRIAL,christopher,loosier,NULL,Male,Caucasian,07/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54490,61876,56157,PRETRIAL,Bienaime,Mckenzy,NULL,Male,Caucasian,05/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +54490,61876,56157,PRETRIAL,Bienaime,Mckenzy,NULL,Male,Caucasian,05/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +54490,61876,56157,PRETRIAL,Bienaime,Mckenzy,NULL,Male,Caucasian,05/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54497,61885,56165,PRETRIAL,Quinones,Miguel,NULL,Male,Hispanic,07/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +54497,61885,56165,PRETRIAL,Quinones,Miguel,NULL,Male,Hispanic,07/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +54497,61885,56165,PRETRIAL,Quinones,Miguel,NULL,Male,Hispanic,07/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,4,High,18,Risk of Failure to Appear,36,10,High,New,1,0 +54494,61881,56162,PRETRIAL,Janki,Dale,Jason,Male,Other,01/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +54494,61881,56162,PRETRIAL,Janki,Dale,Jason,Male,Other,01/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +54494,61881,56162,PRETRIAL,Janki,Dale,Jason,Male,Other,01/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54492,61879,56160,PRETRIAL,Grant,Cleon,NULL,Male,Other,03/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +54492,61879,56160,PRETRIAL,Grant,Cleon,NULL,Male,Other,03/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +54492,61879,56160,PRETRIAL,Grant,Cleon,NULL,Male,Other,03/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54504,61892,56172,PRETRIAL,MENESES,JOHN,NULL,Male,Hispanic,02/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/4/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +54504,61892,56172,PRETRIAL,MENESES,JOHN,NULL,Male,Hispanic,02/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/4/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +54504,61892,56172,PRETRIAL,MENESES,JOHN,NULL,Male,Hispanic,02/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54499,61887,56167,PRETRIAL,Satterfield,Kimberly,NULL,Male,Caucasian,11/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,2,Medium,7,Risk of Violence,-1.87,5,Medium,New,1,0 +54499,61887,56167,PRETRIAL,Satterfield,Kimberly,NULL,Male,Caucasian,11/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +54499,61887,56167,PRETRIAL,Satterfield,Kimberly,NULL,Male,Caucasian,11/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54489,61875,56156,PRETRIAL,Lucien,Tony,NULL,Male,African-American,03/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +54489,61875,56156,PRETRIAL,Lucien,Tony,NULL,Male,African-American,03/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +54489,61875,56156,PRETRIAL,Lucien,Tony,NULL,Male,African-American,03/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54495,61882,56163,PRETRIAL,TILLIT,SUZETTE,M,Male,Other,07/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +54495,61882,56163,PRETRIAL,TILLIT,SUZETTE,M,Male,Other,07/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +54495,61882,56163,PRETRIAL,TILLIT,SUZETTE,M,Male,Other,07/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54496,61884,56164,PRETRIAL,Johnson,Stevie,NULL,Male,African-American,07/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,Copy,1,0 +54496,61884,56164,PRETRIAL,Johnson,Stevie,NULL,Male,African-American,07/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,Copy,1,0 +54496,61884,56164,PRETRIAL,Johnson,Stevie,NULL,Male,African-American,07/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +54491,61877,56158,PRETRIAL,Pendergrass,Joseph,NULL,Male,African-American,05/11/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +54491,61877,56158,PRETRIAL,Pendergrass,Joseph,NULL,Male,African-American,05/11/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +54491,61877,56158,PRETRIAL,Pendergrass,Joseph,NULL,Male,African-American,05/11/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +54501,61889,56169,PRETRIAL,WONG,BRANDON,TAYLOR,Male,Caucasian,03/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +54501,61889,56169,PRETRIAL,WONG,BRANDON,TAYLOR,Male,Caucasian,03/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +54501,61889,56169,PRETRIAL,WONG,BRANDON,TAYLOR,Male,Caucasian,03/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54505,61893,56173,PRETRIAL,VADEN,DARIUS,NULL,Male,African-American,01/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,New,1,0 +54505,61893,56173,PRETRIAL,VADEN,DARIUS,NULL,Male,African-American,01/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +54505,61893,56173,PRETRIAL,VADEN,DARIUS,NULL,Male,African-American,01/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53955,61878,56159,Probation,JOHN,LAWRENCE,ANTHONY,Male,African-American,01/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +53955,61878,56159,Probation,JOHN,LAWRENCE,ANTHONY,Male,African-American,01/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,4,High,8,Risk of Recidivism,0.43,9,High,New,1,0 +53955,61878,56159,Probation,JOHN,LAWRENCE,ANTHONY,Male,African-American,01/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54493,61880,56161,PRETRIAL,Moorman,Vincent,Renard,Male,African-American,09/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,4,High,7,Risk of Violence,-0.69,9,High,New,1,0 +54493,61880,56161,PRETRIAL,Moorman,Vincent,Renard,Male,African-American,09/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +54493,61880,56161,PRETRIAL,Moorman,Vincent,Renard,Male,African-American,09/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54498,61886,56166,PRETRIAL,Larson,William,NULL,Male,Caucasian,04/24/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +54498,61886,56166,PRETRIAL,Larson,William,NULL,Male,Caucasian,04/24/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,8,Risk of Recidivism,-2.8,1,Low,New,1,0 +54498,61886,56166,PRETRIAL,Larson,William,NULL,Male,Caucasian,04/24/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54503,61891,56171,PRETRIAL,ramirez-diaz,carlos,NULL,Male,Caucasian,10/11/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/4/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +54503,61891,56171,PRETRIAL,ramirez-diaz,carlos,NULL,Male,Caucasian,10/11/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/4/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +54503,61891,56171,PRETRIAL,ramirez-diaz,carlos,NULL,Male,Caucasian,10/11/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54500,61888,56168,PRETRIAL,Hill,Steven,Raynard,Male,African-American,08/02/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +54500,61888,56168,PRETRIAL,Hill,Steven,Raynard,Male,African-American,08/02/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +54500,61888,56168,PRETRIAL,Hill,Steven,Raynard,Male,African-American,08/02/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54518,61909,56186,PRETRIAL,HOAGLAND,TERESA,NULL,Male,Caucasian,03/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/5/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +54518,61909,56186,PRETRIAL,HOAGLAND,TERESA,NULL,Male,Caucasian,03/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/5/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +54518,61909,56186,PRETRIAL,HOAGLAND,TERESA,NULL,Male,Caucasian,03/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54508,61896,56176,PRETRIAL,Guide,Rachard,NULL,Male,African-American,11/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.08,8,High,New,1,0 +54508,61896,56176,PRETRIAL,Guide,Rachard,NULL,Male,African-American,11/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +54508,61896,56176,PRETRIAL,Guide,Rachard,NULL,Male,African-American,11/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54510,61899,56179,PRETRIAL,WARE,LASHA,NULL,Female,African-American,10/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +54510,61899,56179,PRETRIAL,WARE,LASHA,NULL,Female,African-American,10/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +54510,61899,56179,PRETRIAL,WARE,LASHA,NULL,Female,African-American,10/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +8269,61907,51520,PRETRIAL,HYDE,JUSTIN,WALLACE,Male,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/5/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,Copy,1,0 +8269,61907,51520,PRETRIAL,HYDE,JUSTIN,WALLACE,Male,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/5/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,Copy,1,0 +8269,61907,51520,PRETRIAL,HYDE,JUSTIN,WALLACE,Male,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +47826,61894,56174,PRETRIAL,BOWLEG,AHMAD,NULL,Male,African-American,03/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +47826,61894,56174,PRETRIAL,BOWLEG,AHMAD,NULL,Male,African-American,03/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +47826,61894,56174,PRETRIAL,BOWLEG,AHMAD,NULL,Male,African-American,03/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54509,61898,56178,PRETRIAL,MILLS,MIESHA,NULL,Female,African-American,04/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +54509,61898,56178,PRETRIAL,MILLS,MIESHA,NULL,Female,African-American,04/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +54509,61898,56178,PRETRIAL,MILLS,MIESHA,NULL,Female,African-American,04/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54512,61903,56182,PRETRIAL,Nevels,Stephanie,NULL,Male,African-American,07/22/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +54512,61903,56182,PRETRIAL,Nevels,Stephanie,NULL,Male,African-American,07/22/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +54512,61903,56182,PRETRIAL,Nevels,Stephanie,NULL,Male,African-American,07/22/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54516,61905,56184,PRETRIAL,mountain,lesean,NULL,Male,African-American,06/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +54516,61905,56184,PRETRIAL,mountain,lesean,NULL,Male,African-American,06/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +54516,61905,56184,PRETRIAL,mountain,lesean,NULL,Male,African-American,06/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54511,61900,56180,PRETRIAL,Downing,Donald,James,Male,Caucasian,02/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +54511,61900,56180,PRETRIAL,Downing,Donald,James,Male,Caucasian,02/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +54511,61900,56180,PRETRIAL,Downing,Donald,James,Male,Caucasian,02/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54506,61895,56175,PRETRIAL,Dessalines,Gerald,NULL,Male,African-American,02/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +54506,61895,56175,PRETRIAL,Dessalines,Gerald,NULL,Male,African-American,02/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +54506,61895,56175,PRETRIAL,Dessalines,Gerald,NULL,Male,African-American,02/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54517,61908,56185,PRETRIAL,Rosen,Jamie,M,Male,Caucasian,04/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +54517,61908,56185,PRETRIAL,Rosen,Jamie,M,Male,Caucasian,04/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +54517,61908,56185,PRETRIAL,Rosen,Jamie,M,Male,Caucasian,04/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54507,61897,56177,PRETRIAL,GUERRERO,NELSON,NULL,Male,Caucasian,12/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/5/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +54507,61897,56177,PRETRIAL,GUERRERO,NELSON,NULL,Male,Caucasian,12/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/5/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +54507,61897,56177,PRETRIAL,GUERRERO,NELSON,NULL,Male,Caucasian,12/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54515,61904,56183,PRETRIAL,Constant,Donald,NULL,Male,African-American,12/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +54515,61904,56183,PRETRIAL,Constant,Donald,NULL,Male,African-American,12/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +54515,61904,56183,PRETRIAL,Constant,Donald,NULL,Male,African-American,12/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54520,61911,56188,PRETRIAL,Baldwin,Timothy,NULL,Male,Caucasian,01/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +54520,61911,56188,PRETRIAL,Baldwin,Timothy,NULL,Male,Caucasian,01/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +54520,61911,56188,PRETRIAL,Baldwin,Timothy,NULL,Male,Caucasian,01/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +27139,61925,56202,PRETRIAL,CLAYTON,JONATHAN,T,Male,African-American,10/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +27139,61925,56202,PRETRIAL,CLAYTON,JONATHAN,T,Male,African-American,10/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +27139,61925,56202,PRETRIAL,CLAYTON,JONATHAN,T,Male,African-American,10/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53195,61939,54636,PRETRIAL,jacksono,shanta,NULL,Female,African-American,05/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,Copy,1,0 +53195,61939,54636,PRETRIAL,jacksono,shanta,NULL,Female,African-American,05/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,Copy,1,0 +53195,61939,54636,PRETRIAL,jacksono,shanta,NULL,Female,African-American,05/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +54543,61946,56220,Probation,baboolal,sharma,NULL,Male,Other,05/27/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +54543,61946,56220,Probation,baboolal,sharma,NULL,Male,Other,05/27/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +54543,61946,56220,Probation,baboolal,sharma,NULL,Male,Other,05/27/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +6427,61948,56222,PRETRIAL,Irvin,Corey,NULL,Male,African-American,11/12/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +6427,61948,56222,PRETRIAL,Irvin,Corey,NULL,Male,African-American,11/12/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,0.17,7,Medium,New,1,0 +6427,61948,56222,PRETRIAL,Irvin,Corey,NULL,Male,African-American,11/12/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54527,61918,56195,PRETRIAL,Marchal,Rosemary,NULL,Female,Other,06/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +54527,61918,56195,PRETRIAL,Marchal,Rosemary,NULL,Female,Other,06/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +54527,61918,56195,PRETRIAL,Marchal,Rosemary,NULL,Female,Other,06/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +34873,61920,56197,PRETRIAL,Atkins,Demarcus,L,Male,African-American,06/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +34873,61920,56197,PRETRIAL,Atkins,Demarcus,L,Male,African-American,06/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +34873,61920,56197,PRETRIAL,Atkins,Demarcus,L,Male,African-American,06/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54532,61927,56204,PRETRIAL,Parker,Trevor,Nathaniel,Male,African-American,04/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +54532,61927,56204,PRETRIAL,Parker,Trevor,Nathaniel,Male,African-American,04/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +54532,61927,56204,PRETRIAL,Parker,Trevor,Nathaniel,Male,African-American,04/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54540,61941,56216,PRETRIAL,ABSOLU,ARISNO,NULL,Male,African-American,07/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +54540,61941,56216,PRETRIAL,ABSOLU,ARISNO,NULL,Male,African-American,07/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +54540,61941,56216,PRETRIAL,ABSOLU,ARISNO,NULL,Male,African-American,07/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54536,61936,56212,PRETRIAL,AUGUSME,BERNARD,NULL,Male,African-American,03/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,4,High,7,Risk of Violence,-0.39,10,High,New,1,0 +54536,61936,56212,PRETRIAL,AUGUSME,BERNARD,NULL,Male,African-American,03/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,4,High,8,Risk of Recidivism,1,10,High,New,1,0 +54536,61936,56212,PRETRIAL,AUGUSME,BERNARD,NULL,Male,African-American,03/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54548,61953,56227,Probation,Laverde,Adriana,NULL,Female,Hispanic,02/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +54548,61953,56227,Probation,Laverde,Adriana,NULL,Female,Hispanic,02/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/13 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +54548,61953,56227,Probation,Laverde,Adriana,NULL,Female,Hispanic,02/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +33171,61923,56200,PRETRIAL,mcgill,dwayne,NULL,Male,African-American,07/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +33171,61923,56200,PRETRIAL,mcgill,dwayne,NULL,Male,African-American,07/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +33171,61923,56200,PRETRIAL,mcgill,dwayne,NULL,Male,African-American,07/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +44649,61932,53843,PRETRIAL,Rodriguez,Deanna,NULL,Female,Caucasian,12/27/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/6/13 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +44649,61932,53843,PRETRIAL,Rodriguez,Deanna,NULL,Female,Caucasian,12/27/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/6/13 0:00,4,High,8,Risk of Recidivism,0.54,9,High,New,1,0 +44649,61932,53843,PRETRIAL,Rodriguez,Deanna,NULL,Female,Caucasian,12/27/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/6/13 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +54141,61944,55708,PRETRIAL,Johnson,Latia,NULL,Female,African-American,10/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,Copy,1,0 +54141,61944,55708,PRETRIAL,Johnson,Latia,NULL,Female,African-American,10/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,Copy,1,0 +54141,61944,55708,PRETRIAL,Johnson,Latia,NULL,Female,African-American,10/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +30833,61929,56206,PRETRIAL,MCGIBBON,JENNIFER,NULL,Female,Caucasian,10/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-1.43,7,Medium,New,1,0 +30833,61929,56206,PRETRIAL,MCGIBBON,JENNIFER,NULL,Female,Caucasian,10/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +30833,61929,56206,PRETRIAL,MCGIBBON,JENNIFER,NULL,Female,Caucasian,10/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54537,61937,56213,Probation,MURPHY,MICHAEL,D,Male,Caucasian,11/07/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/6/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +54537,61937,56213,Probation,MURPHY,MICHAEL,D,Male,Caucasian,11/07/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/6/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +54537,61937,56213,Probation,MURPHY,MICHAEL,D,Male,Caucasian,11/07/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54525,61916,56193,PRETRIAL,Martinez,Roberto,NULL,Male,Hispanic,09/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +54525,61916,56193,PRETRIAL,Martinez,Roberto,NULL,Male,Hispanic,09/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +54525,61916,56193,PRETRIAL,Martinez,Roberto,NULL,Male,Hispanic,09/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54547,61950,56224,Probation,FRANKY,PETER,NULL,Male,African-American,01/20/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +54547,61950,56224,Probation,FRANKY,PETER,NULL,Male,African-American,01/20/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +54547,61950,56224,Probation,FRANKY,PETER,NULL,Male,African-American,01/20/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +27748,61952,56226,PRETRIAL,Randall,David,NULL,Male,Caucasian,03/20/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +27748,61952,56226,PRETRIAL,Randall,David,NULL,Male,Caucasian,03/20/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +27748,61952,56226,PRETRIAL,Randall,David,NULL,Male,Caucasian,03/20/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54522,61913,56190,PRETRIAL,Angel,Melisa,NULL,Female,Hispanic,11/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +54522,61913,56190,PRETRIAL,Angel,Melisa,NULL,Female,Hispanic,11/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +54522,61913,56190,PRETRIAL,Angel,Melisa,NULL,Female,Hispanic,11/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54535,61934,56210,Probation,GANTT,CYRUS,ALEX,Male,African-American,11/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +54535,61934,56210,Probation,GANTT,CYRUS,ALEX,Male,African-American,11/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +54535,61934,56210,Probation,GANTT,CYRUS,ALEX,Male,African-American,11/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +33406,61921,56198,PRETRIAL,ANDERSON,ANTWOYN,NULL,Male,African-American,11/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +33406,61921,56198,PRETRIAL,ANDERSON,ANTWOYN,NULL,Male,African-American,11/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +33406,61921,56198,PRETRIAL,ANDERSON,ANTWOYN,NULL,Male,African-American,11/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54521,61912,56189,PRETRIAL,Turner,George,NULL,Male,African-American,05/23/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +54521,61912,56189,PRETRIAL,Turner,George,NULL,Male,African-American,05/23/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +54521,61912,56189,PRETRIAL,Turner,George,NULL,Male,African-American,05/23/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54534,61933,56209,Probation,Zilberberg,Max,L,Male,Caucasian,02/22/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +54534,61933,56209,Probation,Zilberberg,Max,L,Male,Caucasian,02/22/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +54534,61933,56209,Probation,Zilberberg,Max,L,Male,Caucasian,02/22/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54531,61926,56203,PRETRIAL,Perez,Zachary,Isidro,Male,Caucasian,09/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +54531,61926,56203,PRETRIAL,Perez,Zachary,Isidro,Male,Caucasian,09/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +54531,61926,56203,PRETRIAL,Perez,Zachary,Isidro,Male,Caucasian,09/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54539,61940,56215,PRETRIAL,JOSEPH,MERRILL,NULL,Male,African-American,04/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +54539,61940,56215,PRETRIAL,JOSEPH,MERRILL,NULL,Male,African-American,04/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +54539,61940,56215,PRETRIAL,JOSEPH,MERRILL,NULL,Male,African-American,04/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +42305,61954,56228,Probation,mullins,kayla,NULL,Female,African-American,06/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/6/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +42305,61954,56228,Probation,mullins,kayla,NULL,Female,African-American,06/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/6/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +42305,61954,56228,Probation,mullins,kayla,NULL,Female,African-American,06/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53195,60149,54636,PRETRIAL,jacksono,shanta,NULL,Female,African-American,05/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +53195,60149,54636,PRETRIAL,jacksono,shanta,NULL,Female,African-American,05/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +53195,60149,54636,PRETRIAL,jacksono,shanta,NULL,Female,African-American,05/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,30,9,High,New,1,0 +54528,61919,56196,PRETRIAL,Cheatham,Ramonda,NULL,Female,African-American,09/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +54528,61919,56196,PRETRIAL,Cheatham,Ramonda,NULL,Female,African-American,09/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,New,1,0 +54528,61919,56196,PRETRIAL,Cheatham,Ramonda,NULL,Female,African-American,09/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54519,61910,56187,PRETRIAL,BROWN,SAMUEL,NULL,Male,African-American,02/12/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,7,Risk of Violence,-4.39,1,Low,New,1,0 +54519,61910,56187,PRETRIAL,BROWN,SAMUEL,NULL,Male,African-American,02/12/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,8,Risk of Recidivism,-2.81,1,Low,New,1,0 +54519,61910,56187,PRETRIAL,BROWN,SAMUEL,NULL,Male,African-American,02/12/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54530,61924,56201,PRETRIAL,COUNTS,DEANDRAE,NULL,Male,African-American,02/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +54530,61924,56201,PRETRIAL,COUNTS,DEANDRAE,NULL,Male,African-American,02/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +54530,61924,56201,PRETRIAL,COUNTS,DEANDRAE,NULL,Male,African-American,02/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54533,61931,56208,Probation,Romero,Marcos,NULL,Male,Hispanic,06/26/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +54533,61931,56208,Probation,Romero,Marcos,NULL,Male,Hispanic,06/26/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +54533,61931,56208,Probation,Romero,Marcos,NULL,Male,Hispanic,06/26/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +35907,61945,56219,PRETRIAL,Salazaravellaneda,Miguel,NULL,Male,Caucasian,09/06/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +35907,61945,56219,PRETRIAL,Salazaravellaneda,Miguel,NULL,Male,Caucasian,09/06/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +35907,61945,56219,PRETRIAL,Salazaravellaneda,Miguel,NULL,Male,Caucasian,09/06/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54542,61943,56218,PRETRIAL,cruz,xiomara,NULL,Female,Hispanic,11/25/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/6/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +54542,61943,56218,PRETRIAL,cruz,xiomara,NULL,Female,Hispanic,11/25/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/6/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +54542,61943,56218,PRETRIAL,cruz,xiomara,NULL,Female,Hispanic,11/25/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54524,61915,56192,PRETRIAL,RODRIQUEZ,KIA,NULL,Female,African-American,07/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +54524,61915,56192,PRETRIAL,RODRIQUEZ,KIA,NULL,Female,African-American,07/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,7,Medium,New,1,0 +54524,61915,56192,PRETRIAL,RODRIQUEZ,KIA,NULL,Female,African-American,07/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54529,61922,56199,PRETRIAL,Warrens,Jerry,NULL,Male,Caucasian,07/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +54529,61922,56199,PRETRIAL,Warrens,Jerry,NULL,Male,Caucasian,07/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +54529,61922,56199,PRETRIAL,Warrens,Jerry,NULL,Male,Caucasian,07/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +54523,61914,56191,PRETRIAL,Farooq,Umar,NULL,Male,Other,03/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +54523,61914,56191,PRETRIAL,Farooq,Umar,NULL,Male,Other,03/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +54523,61914,56191,PRETRIAL,Farooq,Umar,NULL,Male,Other,03/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +23303,61935,56211,PRETRIAL,SAVIOX,RICARDO,NULL,Male,African-American,09/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +23303,61935,56211,PRETRIAL,SAVIOX,RICARDO,NULL,Male,African-American,09/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +23303,61935,56211,PRETRIAL,SAVIOX,RICARDO,NULL,Male,African-American,09/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +54526,61917,56194,PRETRIAL,SEILER,SARAH,E,Female,Caucasian,03/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +54526,61917,56194,PRETRIAL,SEILER,SARAH,E,Female,Caucasian,03/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,9,High,New,1,0 +54526,61917,56194,PRETRIAL,SEILER,SARAH,E,Female,Caucasian,03/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54538,61938,56214,Probation,Castano,Juan,NULL,Male,Hispanic,11/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +54538,61938,56214,Probation,Castano,Juan,NULL,Male,Hispanic,11/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +54538,61938,56214,Probation,Castano,Juan,NULL,Male,Hispanic,11/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +54550,61956,56230,PRETRIAL,Michel,Jean,NULL,Male,Other,01/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +54550,61956,56230,PRETRIAL,Michel,Jean,NULL,Male,Other,01/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +54550,61956,56230,PRETRIAL,Michel,Jean,NULL,Male,Other,01/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +30936,61959,56233,PRETRIAL,Asbury,LaRicky,NULL,Male,African-American,12/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +30936,61959,56233,PRETRIAL,Asbury,LaRicky,NULL,Male,African-American,12/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +30936,61959,56233,PRETRIAL,Asbury,LaRicky,NULL,Male,African-American,12/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54570,61977,56251,PRETRIAL,Carino,Richard,Anthony,Male,Hispanic,03/24/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +54570,61977,56251,PRETRIAL,Carino,Richard,Anthony,Male,Hispanic,03/24/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +54570,61977,56251,PRETRIAL,Carino,Richard,Anthony,Male,Hispanic,03/24/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +54575,61985,56259,Probation,Jean,Steve,NULL,Male,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +54575,61985,56259,Probation,Jean,Steve,NULL,Male,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,2,Medium,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +54575,61985,56259,Probation,Jean,Steve,NULL,Male,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54555,61964,56238,PRETRIAL,Caro,Luis,NULL,Male,Hispanic,02/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +54555,61964,56238,PRETRIAL,Caro,Luis,NULL,Male,Hispanic,02/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +54555,61964,56238,PRETRIAL,Caro,Luis,NULL,Male,Hispanic,02/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54583,61998,56268,Probation,adkins,CHRISTOPHER,NULL,Male,Caucasian,01/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,2,Medium,7,Risk of Violence,-3.13,1,Low,New,1,0 +54583,61998,56268,Probation,adkins,CHRISTOPHER,NULL,Male,Caucasian,01/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +54583,61998,56268,Probation,adkins,CHRISTOPHER,NULL,Male,Caucasian,01/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54572,61980,56254,Probation,BONILLA,MATTHEW,THOMAS,Male,Hispanic,11/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +54572,61980,56254,Probation,BONILLA,MATTHEW,THOMAS,Male,Hispanic,11/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +54572,61980,56254,Probation,BONILLA,MATTHEW,THOMAS,Male,Hispanic,11/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54564,61972,56246,PRETRIAL,Aguiar,Frank,NULL,Male,Hispanic,02/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +54564,61972,56246,PRETRIAL,Aguiar,Frank,NULL,Male,Hispanic,02/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +54564,61972,56246,PRETRIAL,Aguiar,Frank,NULL,Male,Hispanic,02/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54581,61993,56266,PRETRIAL,Sherman,Maria,M,Female,Caucasian,07/29/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/7/13 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +54581,61993,56266,PRETRIAL,Sherman,Maria,M,Female,Caucasian,07/29/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/7/13 0:00,1,Low,8,Risk of Recidivism,-2.87,1,Low,New,1,0 +54581,61993,56266,PRETRIAL,Sherman,Maria,M,Female,Caucasian,07/29/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54579,61991,56264,PRETRIAL,Hiott,Clifton,S,Male,Caucasian,08/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +54579,61991,56264,PRETRIAL,Hiott,Clifton,S,Male,Caucasian,08/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +54579,61991,56264,PRETRIAL,Hiott,Clifton,S,Male,Caucasian,08/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54557,61966,56240,PRETRIAL,Bailey,Ledarian,Julian,Male,African-American,06/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,4,High,7,Risk of Violence,-0.69,9,High,New,1,0 +54557,61966,56240,PRETRIAL,Bailey,Ledarian,Julian,Male,African-American,06/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,4,High,8,Risk of Recidivism,0.42,9,High,New,1,0 +54557,61966,56240,PRETRIAL,Bailey,Ledarian,Julian,Male,African-American,06/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54585,62000,56270,Probation,Exum,stanley,NULL,Male,African-American,02/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/13 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +54585,62000,56270,Probation,Exum,stanley,NULL,Male,African-American,02/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +54585,62000,56270,Probation,Exum,stanley,NULL,Male,African-American,02/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54576,61987,56261,Probation,perez,jason,NULL,Male,Caucasian,11/25/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +54576,61987,56261,Probation,perez,jason,NULL,Male,Caucasian,11/25/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +54576,61987,56261,Probation,perez,jason,NULL,Male,Caucasian,11/25/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54575,61996,56259,Probation,Jean,Steve,NULL,Male,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +54575,61996,56259,Probation,Jean,Steve,NULL,Male,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,Copy,1,0 +54575,61996,56259,Probation,Jean,Steve,NULL,Male,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +17678,61961,56235,PRETRIAL,Siler,Shawn,Lamont,Male,African-American,08/23/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +17678,61961,56235,PRETRIAL,Siler,Shawn,Lamont,Male,African-American,08/23/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,4,High,8,Risk of Recidivism,0.54,9,High,New,1,0 +17678,61961,56235,PRETRIAL,Siler,Shawn,Lamont,Male,African-American,08/23/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +54566,61975,56249,PRETRIAL,Lawerence,Akil,NULL,Male,African-American,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +54566,61975,56249,PRETRIAL,Lawerence,Akil,NULL,Male,African-American,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +54566,61975,56249,PRETRIAL,Lawerence,Akil,NULL,Male,African-American,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54590,62003,56273,PRETRIAL,HOLLOWAY,BRYAN,NULL,Male,Caucasian,02/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +54590,62003,56273,PRETRIAL,HOLLOWAY,BRYAN,NULL,Male,Caucasian,02/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +54590,62003,56273,PRETRIAL,HOLLOWAY,BRYAN,NULL,Male,Caucasian,02/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54574,61982,56256,Probation,Mathieu,Roland,NULL,Male,African-American,10/11/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/7/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +54574,61982,56256,Probation,Mathieu,Roland,NULL,Male,African-American,10/11/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/7/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +54574,61982,56256,Probation,Mathieu,Roland,NULL,Male,African-American,10/11/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54549,61955,56229,PRETRIAL,Calloway,Devorist,NULL,Male,African-American,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +54549,61955,56229,PRETRIAL,Calloway,Devorist,NULL,Male,African-American,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.92,10,High,New,1,0 +54549,61955,56229,PRETRIAL,Calloway,Devorist,NULL,Male,African-American,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +54558,61968,56242,PRETRIAL,Mack,Bryeon,Shannae,Female,African-American,08/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +54558,61968,56242,PRETRIAL,Mack,Bryeon,Shannae,Female,African-American,08/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +54558,61968,56242,PRETRIAL,Mack,Bryeon,Shannae,Female,African-American,08/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54589,62002,56272,PRETRIAL,FIELDS,LOKI,NULL,Male,African-American,03/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +54589,62002,56272,PRETRIAL,FIELDS,LOKI,NULL,Male,African-American,03/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +54589,62002,56272,PRETRIAL,FIELDS,LOKI,NULL,Male,African-American,03/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +13745,61963,56237,PRETRIAL,TUTES,RICKY,NULL,Male,African-American,07/21/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +13745,61963,56237,PRETRIAL,TUTES,RICKY,NULL,Male,African-American,07/21/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +13745,61963,56237,PRETRIAL,TUTES,RICKY,NULL,Male,African-American,07/21/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,40,10,High,New,1,0 +54573,61981,56255,PRETRIAL,CONROY,DEBORAH,A,Female,Caucasian,09/05/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-1,-1,N/A,New,1,0 +54573,61981,56255,PRETRIAL,CONROY,DEBORAH,A,Female,Caucasian,09/05/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +54573,61981,56255,PRETRIAL,CONROY,DEBORAH,A,Female,Caucasian,09/05/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +37617,61960,56234,Probation,Findley,Wesley,NULL,Male,African-American,10/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +37617,61960,56234,Probation,Findley,Wesley,NULL,Male,African-American,10/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +37617,61960,56234,Probation,Findley,Wesley,NULL,Male,African-American,10/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +46514,61986,56260,PRETRIAL,WALKER,JONATHAN,NULL,Male,African-American,05/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +46514,61986,56260,PRETRIAL,WALKER,JONATHAN,NULL,Male,African-American,05/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,4,High,8,Risk of Recidivism,0.73,10,High,New,1,0 +46514,61986,56260,PRETRIAL,WALKER,JONATHAN,NULL,Male,African-American,05/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54563,61971,56245,PRETRIAL,o'brien,lauren,Margret,Female,Caucasian,10/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +54563,61971,56245,PRETRIAL,o'brien,lauren,Margret,Female,Caucasian,10/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +54563,61971,56245,PRETRIAL,o'brien,lauren,Margret,Female,Caucasian,10/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54556,61965,56239,PRETRIAL,KANGIESER,STEPHANIE,NULL,Female,Caucasian,03/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +54556,61965,56239,PRETRIAL,KANGIESER,STEPHANIE,NULL,Female,Caucasian,03/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +54556,61965,56239,PRETRIAL,KANGIESER,STEPHANIE,NULL,Female,Caucasian,03/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54553,61958,56232,PRETRIAL,Bienaime,Edwidge,NULL,Male,Other,05/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +54553,61958,56232,PRETRIAL,Bienaime,Edwidge,NULL,Male,Other,05/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +54553,61958,56232,PRETRIAL,Bienaime,Edwidge,NULL,Male,Other,05/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +34167,61994,33312,PRETRIAL,foster,derrick,NULL,Male,Other,10/07/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +34167,61994,33312,PRETRIAL,foster,derrick,NULL,Male,Other,10/07/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +34167,61994,33312,PRETRIAL,foster,derrick,NULL,Male,Other,10/07/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,2,Medium,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +54552,61957,56231,PRETRIAL,Emmanuel,Irving,NULL,Male,African-American,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +54552,61957,56231,PRETRIAL,Emmanuel,Irving,NULL,Male,African-American,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +54552,61957,56231,PRETRIAL,Emmanuel,Irving,NULL,Male,African-American,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54554,61962,56236,PRETRIAL,Belgrod,Brian,NULL,Male,Caucasian,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/7/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +54554,61962,56236,PRETRIAL,Belgrod,Brian,NULL,Male,Caucasian,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/7/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +54554,61962,56236,PRETRIAL,Belgrod,Brian,NULL,Male,Caucasian,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +40237,61983,56257,PRETRIAL,BAKER,CURTIS,NULL,Male,African-American,08/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +40237,61983,56257,PRETRIAL,BAKER,CURTIS,NULL,Male,African-American,08/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +40237,61983,56257,PRETRIAL,BAKER,CURTIS,NULL,Male,African-American,08/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54569,61978,56252,Probation,Brinkley,Amber,NULL,Female,Caucasian,01/26/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +54569,61978,56252,Probation,Brinkley,Amber,NULL,Female,Caucasian,01/26/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +54569,61978,56252,Probation,Brinkley,Amber,NULL,Female,Caucasian,01/26/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54565,61974,56248,Probation,ABREU,PABLO,S,Male,Hispanic,04/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +54565,61974,56248,Probation,ABREU,PABLO,S,Male,Hispanic,04/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +54565,61974,56248,Probation,ABREU,PABLO,S,Male,Hispanic,04/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54577,61988,56262,Probation,HODGEN,KRISTOPHER,NULL,Male,Caucasian,06/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +54577,61988,56262,Probation,HODGEN,KRISTOPHER,NULL,Male,Caucasian,06/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +54577,61988,56262,Probation,HODGEN,KRISTOPHER,NULL,Male,Caucasian,06/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54584,61999,56269,PRETRIAL,Dimartino,Elvera,NULL,Female,Caucasian,10/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +54584,61999,56269,PRETRIAL,Dimartino,Elvera,NULL,Female,Caucasian,10/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +54584,61999,56269,PRETRIAL,Dimartino,Elvera,NULL,Female,Caucasian,10/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51560,61967,56241,PRETRIAL,pierre,majorie,NULL,Female,African-American,10/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/7/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +51560,61967,56241,PRETRIAL,pierre,majorie,NULL,Female,African-American,10/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +51560,61967,56241,PRETRIAL,pierre,majorie,NULL,Female,African-American,10/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/7/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54559,61969,56243,PRETRIAL,Clay,Tyophi,Terrill,Male,African-American,10/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +54559,61969,56243,PRETRIAL,Clay,Tyophi,Terrill,Male,African-American,10/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,4,High,8,Risk of Recidivism,0.09,8,High,New,1,0 +54559,61969,56243,PRETRIAL,Clay,Tyophi,Terrill,Male,African-American,10/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54567,61976,56250,Probation,apraez,alexander,NULL,Male,Hispanic,04/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +54567,61976,56250,Probation,apraez,alexander,NULL,Male,Hispanic,04/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +54567,61976,56250,Probation,apraez,alexander,NULL,Male,Hispanic,04/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +35736,61990,34966,PRETRIAL,Mackiewicz,Marianne,NULL,Female,Caucasian,12/08/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,5/7/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,Copy,1,0 +35736,61990,34966,PRETRIAL,Mackiewicz,Marianne,NULL,Female,Caucasian,12/08/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,5/7/13 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,Copy,1,0 +35736,61990,34966,PRETRIAL,Mackiewicz,Marianne,NULL,Female,Caucasian,12/08/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,5/7/13 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,Copy,1,0 +54591,62004,56274,PRETRIAL,JACKSON,JEFFREY,NULL,Male,African-American,12/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.89,2,Low,New,1,0 +54591,62004,56274,PRETRIAL,JACKSON,JEFFREY,NULL,Male,African-American,12/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,New,1,0 +54591,62004,56274,PRETRIAL,JACKSON,JEFFREY,NULL,Male,African-American,12/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54595,62011,56281,PRETRIAL,BARR,WILLIAM,NULL,Male,African-American,12/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,New,1,0 +54595,62011,56281,PRETRIAL,BARR,WILLIAM,NULL,Male,African-American,12/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +54595,62011,56281,PRETRIAL,BARR,WILLIAM,NULL,Male,African-American,12/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54606,62025,56292,Probation,Bryson,Anthony,Stuart,Male,Hispanic,05/12/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +54606,62025,56292,Probation,Bryson,Anthony,Stuart,Male,Hispanic,05/12/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,10,High,New,1,0 +54606,62025,56292,Probation,Bryson,Anthony,Stuart,Male,Hispanic,05/12/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54603,62018,56288,PRETRIAL,RODRIGUEZ,JOHY,AYALA,Male,Caucasian,12/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +54603,62018,56288,PRETRIAL,RODRIGUEZ,JOHY,AYALA,Male,Caucasian,12/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +54603,62018,56288,PRETRIAL,RODRIGUEZ,JOHY,AYALA,Male,Caucasian,12/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +46508,62039,56301,PRETRIAL,McFarlane,James,NULL,Male,Caucasian,10/22/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/8/13 0:00,2,Medium,7,Risk of Violence,-2.61,2,Low,New,1,0 +46508,62039,56301,PRETRIAL,McFarlane,James,NULL,Male,Caucasian,10/22/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +46508,62039,56301,PRETRIAL,McFarlane,James,NULL,Male,Caucasian,10/22/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/8/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54622,62046,56307,PRETRIAL,Farah,Imad,NULL,Male,Caucasian,11/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +54622,62046,56307,PRETRIAL,Farah,Imad,NULL,Male,Caucasian,11/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +54622,62046,56307,PRETRIAL,Farah,Imad,NULL,Male,Caucasian,11/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54599,62013,56283,PRETRIAL,Spitler,Richard,Draa,Male,Caucasian,06/08/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +54599,62013,56283,PRETRIAL,Spitler,Richard,Draa,Male,Caucasian,06/08/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +54599,62013,56283,PRETRIAL,Spitler,Richard,Draa,Male,Caucasian,06/08/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54593,62009,56279,PRETRIAL,Coldfelter,James,NULL,Male,Caucasian,09/28/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +54593,62009,56279,PRETRIAL,Coldfelter,James,NULL,Male,Caucasian,09/28/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +54593,62009,56279,PRETRIAL,Coldfelter,James,NULL,Male,Caucasian,09/28/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54614,62034,56296,PRETRIAL,Geddes,Lance,Michael,Male,African-American,04/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,5/8/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +54614,62034,56296,PRETRIAL,Geddes,Lance,Michael,Male,African-American,04/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,5/8/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +54614,62034,56296,PRETRIAL,Geddes,Lance,Michael,Male,African-American,04/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52413,62044,53711,Probation,BOCKER,MARK,NULL,Male,Caucasian,11/12/63,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,5/8/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +52413,62044,53711,Probation,BOCKER,MARK,NULL,Male,Caucasian,11/12/63,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,5/8/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +52413,62044,53711,Probation,BOCKER,MARK,NULL,Male,Caucasian,11/12/63,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +54600,62015,56285,PRETRIAL,Lemley,Allan,NULL,Male,Caucasian,10/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +54600,62015,56285,PRETRIAL,Lemley,Allan,NULL,Male,Caucasian,10/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +54600,62015,56285,PRETRIAL,Lemley,Allan,NULL,Male,Caucasian,10/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54592,62007,56277,PRETRIAL,Valdivia,Oscar,Cesar,Male,Caucasian,03/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +54592,62007,56277,PRETRIAL,Valdivia,Oscar,Cesar,Male,Caucasian,03/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +54592,62007,56277,PRETRIAL,Valdivia,Oscar,Cesar,Male,Caucasian,03/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54594,62010,56280,PRETRIAL,Do,Aleksandr,NULL,Male,Caucasian,09/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +54594,62010,56280,PRETRIAL,Do,Aleksandr,NULL,Male,Caucasian,09/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +54594,62010,56280,PRETRIAL,Do,Aleksandr,NULL,Male,Caucasian,09/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54619,62041,56303,Probation,Danelczyk,Pawel,W,Male,Caucasian,06/05/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +54619,62041,56303,Probation,Danelczyk,Pawel,W,Male,Caucasian,06/05/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +54619,62041,56303,Probation,Danelczyk,Pawel,W,Male,Caucasian,06/05/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53929,62020,55455,PRETRIAL,Belmont,Estella,NULL,Female,Hispanic,01/22/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,Copy,1,0 +53929,62020,55455,PRETRIAL,Belmont,Estella,NULL,Female,Hispanic,01/22/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,Copy,1,0 +53929,62020,55455,PRETRIAL,Belmont,Estella,NULL,Female,Hispanic,01/22/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +54616,62036,56298,Probation,Alvarez,Mauricio,NULL,Male,Hispanic,03/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/8/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +54616,62036,56298,Probation,Alvarez,Mauricio,NULL,Male,Hispanic,03/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/8/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +54616,62036,56298,Probation,Alvarez,Mauricio,NULL,Male,Hispanic,03/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +44428,62005,56275,PRETRIAL,Wright,Jamar,NULL,Male,African-American,06/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +44428,62005,56275,PRETRIAL,Wright,Jamar,NULL,Male,African-American,06/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,4,High,8,Risk of Recidivism,0.8,10,High,New,1,0 +44428,62005,56275,PRETRIAL,Wright,Jamar,NULL,Male,African-American,06/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54596,62012,56282,PRETRIAL,Johnson,Travis,NULL,Male,African-American,08/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +54596,62012,56282,PRETRIAL,Johnson,Travis,NULL,Male,African-American,08/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +54596,62012,56282,PRETRIAL,Johnson,Travis,NULL,Male,African-American,08/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +5390,62033,5054,PRETRIAL,Myers,Carl,Dennis,Male,African-American,09/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,Copy,1,0 +5390,62033,5054,PRETRIAL,Myers,Carl,Dennis,Male,African-American,09/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,Copy,1,0 +5390,62033,5054,PRETRIAL,Myers,Carl,Dennis,Male,African-American,09/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +41419,62026,46452,PRETRIAL,Santiago,Zachary,L,Male,African-American,07/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,4,High,7,Risk of Violence,-0.47,10,High,Copy,1,0 +41419,62026,46452,PRETRIAL,Santiago,Zachary,L,Male,African-American,07/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,Copy,1,0 +41419,62026,46452,PRETRIAL,Santiago,Zachary,L,Male,African-American,07/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +35683,62040,56302,PRETRIAL,Bowens,Shenay,NULL,Female,African-American,04/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +35683,62040,56302,PRETRIAL,Bowens,Shenay,NULL,Female,African-American,04/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +35683,62040,56302,PRETRIAL,Bowens,Shenay,NULL,Female,African-American,04/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54604,62021,56290,Probation,Hicks,Donald,NULL,Male,Caucasian,06/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/13 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +54604,62021,56290,Probation,Hicks,Donald,NULL,Male,Caucasian,06/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +54604,62021,56290,Probation,Hicks,Donald,NULL,Male,Caucasian,06/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +54602,62017,56287,PRETRIAL,SUTTON,MICHAEL,VERNARD,Male,African-American,05/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +54602,62017,56287,PRETRIAL,SUTTON,MICHAEL,VERNARD,Male,African-American,05/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +54602,62017,56287,PRETRIAL,SUTTON,MICHAEL,VERNARD,Male,African-American,05/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +21061,62008,56278,PRETRIAL,blackwell,reginald,NULL,Male,African-American,01/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +21061,62008,56278,PRETRIAL,blackwell,reginald,NULL,Male,African-American,01/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +21061,62008,56278,PRETRIAL,blackwell,reginald,NULL,Male,African-American,01/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54620,62043,56305,PRETRIAL,Vargas,Eddie,NULL,Male,Hispanic,11/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +54620,62043,56305,PRETRIAL,Vargas,Eddie,NULL,Male,Hispanic,11/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +54620,62043,56305,PRETRIAL,Vargas,Eddie,NULL,Male,Hispanic,11/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54609,62029,56294,PRETRIAL,Gelsey,Edward,NULL,Male,African-American,01/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +54609,62029,56294,PRETRIAL,Gelsey,Edward,NULL,Male,African-American,01/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +54609,62029,56294,PRETRIAL,Gelsey,Edward,NULL,Male,African-American,01/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +46396,62014,56284,PRETRIAL,Johnson,Joseph,NULL,Male,African-American,01/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +46396,62014,56284,PRETRIAL,Johnson,Joseph,NULL,Male,African-American,01/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,4,High,8,Risk of Recidivism,0.09,8,High,New,1,0 +46396,62014,56284,PRETRIAL,Johnson,Joseph,NULL,Male,African-American,01/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54617,62037,56299,PRETRIAL,Allen,Mark,B,Male,Caucasian,03/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +54617,62037,56299,PRETRIAL,Allen,Mark,B,Male,Caucasian,03/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +54617,62037,56299,PRETRIAL,Allen,Mark,B,Male,Caucasian,03/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54601,62016,56286,PRETRIAL,REESE,CRAIG,TAVARIS,Male,African-American,02/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +54601,62016,56286,PRETRIAL,REESE,CRAIG,TAVARIS,Male,African-American,02/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +54601,62016,56286,PRETRIAL,REESE,CRAIG,TAVARIS,Male,African-American,02/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54615,62035,56297,Probation,anderl,johnathan,NULL,Male,Caucasian,09/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +54615,62035,56297,Probation,anderl,johnathan,NULL,Male,Caucasian,09/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +54615,62035,56297,Probation,anderl,johnathan,NULL,Male,Caucasian,09/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54610,62032,56295,Probation,Pless,Diamond,NULL,Male,African-American,04/28/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +54610,62032,56295,Probation,Pless,Diamond,NULL,Male,African-American,04/28/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +54610,62032,56295,Probation,Pless,Diamond,NULL,Male,African-American,04/28/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +10752,62019,56289,PRETRIAL,DYLAN,RAS,A,Male,Caucasian,06/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +10752,62019,56289,PRETRIAL,DYLAN,RAS,A,Male,Caucasian,06/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +10752,62019,56289,PRETRIAL,DYLAN,RAS,A,Male,Caucasian,06/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54607,62027,56293,PRETRIAL,GUEVARA-MOLINA,VICTOR,NULL,Male,Hispanic,11/23/84,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +54607,62027,56293,PRETRIAL,GUEVARA-MOLINA,VICTOR,NULL,Male,Hispanic,11/23/84,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +54607,62027,56293,PRETRIAL,GUEVARA-MOLINA,VICTOR,NULL,Male,Hispanic,11/23/84,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54621,62045,56306,PRETRIAL,Spann,Ciprianna,NULL,Female,African-American,12/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +54621,62045,56306,PRETRIAL,Spann,Ciprianna,NULL,Female,African-American,12/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +54621,62045,56306,PRETRIAL,Spann,Ciprianna,NULL,Female,African-American,12/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +41077,62006,56276,PRETRIAL,Adams,Russell,John,Male,Caucasian,11/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/8/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +41077,62006,56276,PRETRIAL,Adams,Russell,John,Male,Caucasian,11/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/8/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +41077,62006,56276,PRETRIAL,Adams,Russell,John,Male,Caucasian,11/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54014,62024,55559,PRETRIAL,SELBY,SAMUEL,NULL,Male,Caucasian,09/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,5/8/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,Copy,1,0 +54014,62024,55559,PRETRIAL,SELBY,SAMUEL,NULL,Male,Caucasian,09/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,5/8/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,Copy,1,0 +54014,62024,55559,PRETRIAL,SELBY,SAMUEL,NULL,Male,Caucasian,09/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,5/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +54639,62074,56333,PRETRIAL,Falcon,Joseph,Angel,Male,Caucasian,06/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +54639,62074,56333,PRETRIAL,Falcon,Joseph,Angel,Male,Caucasian,06/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +54639,62074,56333,PRETRIAL,Falcon,Joseph,Angel,Male,Caucasian,06/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +23628,62092,56349,PRETRIAL,swedelson,mitchell,NULL,Male,Caucasian,02/07/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/9/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +23628,62092,56349,PRETRIAL,swedelson,mitchell,NULL,Male,Caucasian,02/07/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +23628,62092,56349,PRETRIAL,swedelson,mitchell,NULL,Male,Caucasian,02/07/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +54654,62095,56352,Probation,Santos,joao,Dos,Male,Other,10/23/62,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,5/9/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +54654,62095,56352,Probation,Santos,joao,Dos,Male,Other,10/23/62,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,5/9/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +54654,62095,56352,Probation,Santos,joao,Dos,Male,Other,10/23/62,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52758,62053,56314,PRETRIAL,CAMPBELL,KIMOY,NULL,Male,African-American,09/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +52758,62053,56314,PRETRIAL,CAMPBELL,KIMOY,NULL,Male,African-American,09/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +52758,62053,56314,PRETRIAL,CAMPBELL,KIMOY,NULL,Male,African-American,09/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54632,62066,56325,Probation,karas,kara,NULL,Female,Caucasian,11/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +54632,62066,56325,Probation,karas,kara,NULL,Female,Caucasian,11/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +54632,62066,56325,Probation,karas,kara,NULL,Female,Caucasian,11/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54657,62100,56357,Probation,Hagar,Robert,Perry,Male,Hispanic,06/22/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +54657,62100,56357,Probation,Hagar,Robert,Perry,Male,Hispanic,06/22/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +54657,62100,56357,Probation,Hagar,Robert,Perry,Male,Hispanic,06/22/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +49524,62087,56345,PRETRIAL,Jones,Sjon,NULL,Male,Other,09/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +49524,62087,56345,PRETRIAL,Jones,Sjon,NULL,Male,Other,09/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +49524,62087,56345,PRETRIAL,Jones,Sjon,NULL,Male,Other,09/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +46315,62050,56311,PRETRIAL,DOUGLAS,KRISTON,K,Male,African-American,08/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +46315,62050,56311,PRETRIAL,DOUGLAS,KRISTON,K,Male,African-American,08/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +46315,62050,56311,PRETRIAL,DOUGLAS,KRISTON,K,Male,African-American,08/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54636,62071,56330,Probation,Monroe,Londell,Alphonzo,Male,African-American,07/20/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +54636,62071,56330,Probation,Monroe,Londell,Alphonzo,Male,African-American,07/20/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +54636,62071,56330,Probation,Monroe,Londell,Alphonzo,Male,African-American,07/20/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53422,62058,56318,PRETRIAL,Edward,John,D,Male,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +53422,62058,56318,PRETRIAL,Edward,John,D,Male,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +53422,62058,56318,PRETRIAL,Edward,John,D,Male,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +54634,62068,56327,Probation,Jorge,Aragon,Mario,Male,Hispanic,08/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +54634,62068,56327,Probation,Jorge,Aragon,Mario,Male,Hispanic,08/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +54634,62068,56327,Probation,Jorge,Aragon,Mario,Male,Hispanic,08/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +43470,62089,56347,PRETRIAL,LEWIS,RIVELINO,NULL,Male,African-American,10/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +43470,62089,56347,PRETRIAL,LEWIS,RIVELINO,NULL,Male,African-American,10/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +43470,62089,56347,PRETRIAL,LEWIS,RIVELINO,NULL,Male,African-American,10/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +39346,62098,56355,Probation,JOOST,EUGENE,N,Male,Caucasian,06/19/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +39346,62098,56355,Probation,JOOST,EUGENE,N,Male,Caucasian,06/19/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +39346,62098,56355,Probation,JOOST,EUGENE,N,Male,Caucasian,06/19/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54627,62059,56319,PRETRIAL,Watts,Robert,NULL,Male,African-American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +54627,62059,56319,PRETRIAL,Watts,Robert,NULL,Male,African-American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +54627,62059,56319,PRETRIAL,Watts,Robert,NULL,Male,African-American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54642,62077,56336,PRETRIAL,Joseph,Wilner,NULL,Male,Other,11/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/9/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +54642,62077,56336,PRETRIAL,Joseph,Wilner,NULL,Male,Other,11/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +54642,62077,56336,PRETRIAL,Joseph,Wilner,NULL,Male,Other,11/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +8641,62056,56316,PRETRIAL,Mejia,Christopher,Fabian,Male,African-American,07/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +8641,62056,56316,PRETRIAL,Mejia,Christopher,Fabian,Male,African-American,07/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +8641,62056,56316,PRETRIAL,Mejia,Christopher,Fabian,Male,African-American,07/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54046,62063,55596,PRETRIAL,Petithomme,Bedson,NULL,Male,African-American,09/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,Copy,1,0 +54046,62063,55596,PRETRIAL,Petithomme,Bedson,NULL,Male,African-American,09/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,Copy,1,0 +54046,62063,55596,PRETRIAL,Petithomme,Bedson,NULL,Male,African-American,09/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +54623,62047,56308,PRETRIAL,Williams,Matias,NULL,Male,African-American,09/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +54623,62047,56308,PRETRIAL,Williams,Matias,NULL,Male,African-American,09/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +54623,62047,56308,PRETRIAL,Williams,Matias,NULL,Male,African-American,09/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +54625,62054,56315,PRETRIAL,Heck,Dale,NULL,Male,African-American,12/08/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +54625,62054,56315,PRETRIAL,Heck,Dale,NULL,Male,African-American,12/08/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +54625,62054,56315,PRETRIAL,Heck,Dale,NULL,Male,African-American,12/08/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54629,62061,56321,PRETRIAL,KEANE,PATRICK,T,Male,Caucasian,06/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +54629,62061,56321,PRETRIAL,KEANE,PATRICK,T,Male,Caucasian,06/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +54629,62061,56321,PRETRIAL,KEANE,PATRICK,T,Male,Caucasian,06/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54640,62075,56334,PRETRIAL,Esquiagola,Julio,C,Male,Hispanic,08/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/9/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +54640,62075,56334,PRETRIAL,Esquiagola,Julio,C,Male,Hispanic,08/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +54640,62075,56334,PRETRIAL,Esquiagola,Julio,C,Male,Hispanic,08/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54647,62084,56342,Probation,Maisenberg,Paul,NULL,Male,Caucasian,05/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +54647,62084,56342,Probation,Maisenberg,Paul,NULL,Male,Caucasian,05/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +54647,62084,56342,Probation,Maisenberg,Paul,NULL,Male,Caucasian,05/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +46756,62103,47194,Probation,araque,elizabeth,NULL,Male,Hispanic,12/27/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +46756,62103,47194,Probation,araque,elizabeth,NULL,Male,Hispanic,12/27/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +46756,62103,47194,Probation,araque,elizabeth,NULL,Male,Hispanic,12/27/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54645,62082,56340,Probation,padilla,maria,NULL,Male,Hispanic,05/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/9/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +54645,62082,56340,Probation,padilla,maria,NULL,Male,Hispanic,05/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/9/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +54645,62082,56340,Probation,padilla,maria,NULL,Male,Hispanic,05/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54635,62070,56329,PRETRIAL,Clark,Brittany,NULL,Female,African-American,10/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +54635,62070,56329,PRETRIAL,Clark,Brittany,NULL,Female,African-American,10/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +54635,62070,56329,PRETRIAL,Clark,Brittany,NULL,Female,African-American,10/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54646,62083,56341,PRETRIAL,Rodriguez,William,NULL,Male,Hispanic,08/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +54646,62083,56341,PRETRIAL,Rodriguez,William,NULL,Male,Hispanic,08/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +54646,62083,56341,PRETRIAL,Rodriguez,William,NULL,Male,Hispanic,08/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +46804,62062,56322,PRETRIAL,BUFFORD,BRADEN,NULL,Male,Caucasian,05/30/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/13 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +46804,62062,56322,PRETRIAL,BUFFORD,BRADEN,NULL,Male,Caucasian,05/30/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/13 0:00,4,High,8,Risk of Recidivism,0.15,8,High,New,1,0 +46804,62062,56322,PRETRIAL,BUFFORD,BRADEN,NULL,Male,Caucasian,05/30/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54655,62096,56353,PRETRIAL,Giganti,Danielle,NULL,Female,Caucasian,07/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,New,1,0 +54655,62096,56353,PRETRIAL,Giganti,Danielle,NULL,Female,Caucasian,07/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +54655,62096,56353,PRETRIAL,Giganti,Danielle,NULL,Female,Caucasian,07/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +5113,62049,56310,PRETRIAL,McLamore,Justin,Breon,Male,African-American,04/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +5113,62049,56310,PRETRIAL,McLamore,Justin,Breon,Male,African-American,04/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +5113,62049,56310,PRETRIAL,McLamore,Justin,Breon,Male,African-American,04/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54650,62088,56346,Probation,pacheco,ashley,NULL,Female,Hispanic,11/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +54650,62088,56346,Probation,pacheco,ashley,NULL,Female,Hispanic,11/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +54650,62088,56346,Probation,pacheco,ashley,NULL,Female,Hispanic,11/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +46338,62099,56356,PRETRIAL,PESQUERA,JORGE,ANTONIO,Male,Caucasian,05/09/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +46338,62099,56356,PRETRIAL,PESQUERA,JORGE,ANTONIO,Male,Caucasian,05/09/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +46338,62099,56356,PRETRIAL,PESQUERA,JORGE,ANTONIO,Male,Caucasian,05/09/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54643,62078,56337,PRETRIAL,GRANT,JERRY,NULL,Male,African-American,02/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +54643,62078,56337,PRETRIAL,GRANT,JERRY,NULL,Male,African-American,02/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +54643,62078,56337,PRETRIAL,GRANT,JERRY,NULL,Male,African-American,02/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +47208,62073,56332,PRETRIAL,Higgs,Dequan,R,Male,African-American,04/21/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/9/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +47208,62073,56332,PRETRIAL,Higgs,Dequan,R,Male,African-American,04/21/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/9/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +47208,62073,56332,PRETRIAL,Higgs,Dequan,R,Male,African-American,04/21/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +54641,62080,56338,Probation,Ferry,Brittany,NULL,Female,Caucasian,10/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +54641,62080,56338,Probation,Ferry,Brittany,NULL,Female,Caucasian,10/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +54641,62080,56338,Probation,Ferry,Brittany,NULL,Female,Caucasian,10/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54304,62052,56313,PRETRIAL,Chovan,Peter,NULL,Male,Caucasian,10/10/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +54304,62052,56313,PRETRIAL,Chovan,Peter,NULL,Male,Caucasian,10/10/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +54304,62052,56313,PRETRIAL,Chovan,Peter,NULL,Male,Caucasian,10/10/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54649,62086,56344,PRETRIAL,Ingram,David,NULL,Male,African-American,10/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +54649,62086,56344,PRETRIAL,Ingram,David,NULL,Male,African-American,10/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +54649,62086,56344,PRETRIAL,Ingram,David,NULL,Male,African-American,10/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54658,62101,56358,Probation,smith,debby,NULL,Female,Caucasian,05/24/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/9/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +54658,62101,56358,Probation,smith,debby,NULL,Female,Caucasian,05/24/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +54658,62101,56358,Probation,smith,debby,NULL,Female,Caucasian,05/24/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54630,62065,56324,Probation,Solomon,Erwin,NULL,Male,Caucasian,05/02/55,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/9/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +54630,62065,56324,Probation,Solomon,Erwin,NULL,Male,Caucasian,05/02/55,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/9/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +54630,62065,56324,Probation,Solomon,Erwin,NULL,Male,Caucasian,05/02/55,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54637,62072,56331,Probation,garcia,baldomero,NULL,Male,Hispanic,07/07/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/9/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +54637,62072,56331,Probation,garcia,baldomero,NULL,Male,Hispanic,07/07/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +54637,62072,56331,Probation,garcia,baldomero,NULL,Male,Hispanic,07/07/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54624,62051,56312,PRETRIAL,Mayo,David,NULL,Male,African-American,10/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.31,3,Low,New,1,0 +54624,62051,56312,PRETRIAL,Mayo,David,NULL,Male,African-American,10/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +54624,62051,56312,PRETRIAL,Mayo,David,NULL,Male,African-American,10/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54648,62085,56343,Probation,pitter,dwayne,NULL,Male,African-American,09/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +54648,62085,56343,Probation,pitter,dwayne,NULL,Male,African-American,09/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +54648,62085,56343,Probation,pitter,dwayne,NULL,Male,African-American,09/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54660,62102,56359,PRETRIAL,Taylor,Travis,Christohper,Male,African-American,09/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +54660,62102,56359,PRETRIAL,Taylor,Travis,Christohper,Male,African-American,09/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +54660,62102,56359,PRETRIAL,Taylor,Travis,Christohper,Male,African-American,09/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +2203,62055,47538,PRETRIAL,BARRETT,TREVOR,ANTHONY,Male,African-American,02/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,4,High,7,Risk of Violence,-0.77,9,High,Copy,1,0 +2203,62055,47538,PRETRIAL,BARRETT,TREVOR,ANTHONY,Male,African-American,02/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,Copy,1,0 +2203,62055,47538,PRETRIAL,BARRETT,TREVOR,ANTHONY,Male,African-American,02/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +54631,62064,56323,Probation,PACHON,DIANA,MARCELA,Female,Hispanic,08/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +54631,62064,56323,Probation,PACHON,DIANA,MARCELA,Female,Hispanic,08/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +54631,62064,56323,Probation,PACHON,DIANA,MARCELA,Female,Hispanic,08/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54628,62060,56320,PRETRIAL,Kochnev,Yevgeniy,NULL,Male,Caucasian,08/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +54628,62060,56320,PRETRIAL,Kochnev,Yevgeniy,NULL,Male,Caucasian,08/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +54628,62060,56320,PRETRIAL,Kochnev,Yevgeniy,NULL,Male,Caucasian,08/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54644,62081,56339,Probation,SCHUSTER,LISA,C,Female,Caucasian,12/08/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/9/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +54644,62081,56339,Probation,SCHUSTER,LISA,C,Female,Caucasian,12/08/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +54644,62081,56339,Probation,SCHUSTER,LISA,C,Female,Caucasian,12/08/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +5244,62048,56309,PRETRIAL,Hankerson,Shawn,NULL,Male,African-American,10/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +5244,62048,56309,PRETRIAL,Hankerson,Shawn,NULL,Male,African-American,10/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,4,High,8,Risk of Recidivism,0.28,8,High,New,1,0 +5244,62048,56309,PRETRIAL,Hankerson,Shawn,NULL,Male,African-American,10/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54633,62067,56326,Probation,LASTER,WILLIE,ALVIN,Male,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +54633,62067,56326,Probation,LASTER,WILLIE,ALVIN,Male,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +54633,62067,56326,Probation,LASTER,WILLIE,ALVIN,Male,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +32963,62069,56328,Probation,ozual,catherine,NULL,Female,African-American,07/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +32963,62069,56328,Probation,ozual,catherine,NULL,Female,African-American,07/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +32963,62069,56328,Probation,ozual,catherine,NULL,Female,African-American,07/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54651,62090,56348,Probation,Guzman,Angel,Geovonny,Male,Hispanic,08/10/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/9/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +54651,62090,56348,Probation,Guzman,Angel,Geovonny,Male,Hispanic,08/10/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/9/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +54651,62090,56348,Probation,Guzman,Angel,Geovonny,Male,Hispanic,08/10/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54656,62097,56354,Probation,Reyes,Ryan,NULL,Male,Hispanic,12/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,5/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +54656,62097,56354,Probation,Reyes,Ryan,NULL,Male,Hispanic,12/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,5/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +54656,62097,56354,Probation,Reyes,Ryan,NULL,Male,Hispanic,12/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,5/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54665,62104,56360,Probation,HUMPHRIES,GRETTA,NULL,Female,Hispanic,02/10/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +54665,62104,56360,Probation,HUMPHRIES,GRETTA,NULL,Female,Hispanic,02/10/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +54665,62104,56360,Probation,HUMPHRIES,GRETTA,NULL,Female,Hispanic,02/10/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +8215,62111,7771,DRRD,McCutcheon,Clinton,Tavaris,Male,African-American,05/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,Copy,1,0 +8215,62111,7771,DRRD,McCutcheon,Clinton,Tavaris,Male,African-American,05/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,Copy,1,0 +8215,62111,7771,DRRD,McCutcheon,Clinton,Tavaris,Male,African-American,05/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +44276,62125,56379,Probation,rivers,emily,NULL,Female,Caucasian,07/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +44276,62125,56379,Probation,rivers,emily,NULL,Female,Caucasian,07/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +44276,62125,56379,Probation,rivers,emily,NULL,Female,Caucasian,07/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54677,62118,56373,PRETRIAL,Desarme,Jino,NULL,Male,Other,03/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +54677,62118,56373,PRETRIAL,Desarme,Jino,NULL,Male,Other,03/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +54677,62118,56373,PRETRIAL,Desarme,Jino,NULL,Male,Other,03/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51402,62120,56375,PRETRIAL,Davis,Nigel,J,Male,Other,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +51402,62120,56375,PRETRIAL,Davis,Nigel,J,Male,Other,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +51402,62120,56375,PRETRIAL,Davis,Nigel,J,Male,Other,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +34856,62139,46987,PRETRIAL,oneil,daniel,NULL,Male,Caucasian,08/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,Copy,1,0 +34856,62139,46987,PRETRIAL,oneil,daniel,NULL,Male,Caucasian,08/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,Copy,1,0 +34856,62139,46987,PRETRIAL,oneil,daniel,NULL,Male,Caucasian,08/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +25062,62141,56391,PRETRIAL,Overby,Christopher,NULL,Male,Caucasian,04/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +25062,62141,56391,PRETRIAL,Overby,Christopher,NULL,Male,Caucasian,04/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,4,High,8,Risk of Recidivism,0.66,10,High,New,1,0 +25062,62141,56391,PRETRIAL,Overby,Christopher,NULL,Male,Caucasian,04/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54693,62146,56396,PRETRIAL,Bishop,Gregory,NULL,Male,African-American,06/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +54693,62146,56396,PRETRIAL,Bishop,Gregory,NULL,Male,African-American,06/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +54693,62146,56396,PRETRIAL,Bishop,Gregory,NULL,Male,African-American,06/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +40528,62148,56398,PRETRIAL,FIGUEROA,MARCELINO,NULL,Male,Caucasian,10/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +40528,62148,56398,PRETRIAL,FIGUEROA,MARCELINO,NULL,Male,Caucasian,10/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +40528,62148,56398,PRETRIAL,FIGUEROA,MARCELINO,NULL,Male,Caucasian,10/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +54666,62106,56362,PRETRIAL,Nicholas,Doreena,NULL,Female,Caucasian,08/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +54666,62106,56362,PRETRIAL,Nicholas,Doreena,NULL,Female,Caucasian,08/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +54666,62106,56362,PRETRIAL,Nicholas,Doreena,NULL,Female,Caucasian,08/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +48079,62127,51015,PRETRIAL,Zackery,Kaleb,NULL,Male,African-American,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2,4,Low,Copy,1,0 +48079,62127,51015,PRETRIAL,Zackery,Kaleb,NULL,Male,African-American,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.01,10,High,Copy,1,0 +48079,62127,51015,PRETRIAL,Zackery,Kaleb,NULL,Male,African-American,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +54679,62123,56377,Probation,SCHNUPP,ERIC,NULL,Male,Caucasian,03/24/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +54679,62123,56377,Probation,SCHNUPP,ERIC,NULL,Male,Caucasian,03/24/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +54679,62123,56377,Probation,SCHNUPP,ERIC,NULL,Male,Caucasian,03/24/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54688,62136,56388,Probation,Barrett,Calvin,NULL,Male,African-American,07/22/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +54688,62136,56388,Probation,Barrett,Calvin,NULL,Male,African-American,07/22/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +54688,62136,56388,Probation,Barrett,Calvin,NULL,Male,African-American,07/22/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54674,62115,56370,PRETRIAL,Spoth,Deborah,NULL,Female,Caucasian,04/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +54674,62115,56370,PRETRIAL,Spoth,Deborah,NULL,Female,Caucasian,04/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +54674,62115,56370,PRETRIAL,Spoth,Deborah,NULL,Female,Caucasian,04/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54678,62122,56376,Probation,Andrews,Willie,Bernard,Male,African-American,10/18/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +54678,62122,56376,Probation,Andrews,Willie,Bernard,Male,African-American,10/18/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +54678,62122,56376,Probation,Andrews,Willie,Bernard,Male,African-American,10/18/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +9579,62143,56393,PRETRIAL,SCUTT,ENRICO,GEDEON,Male,Other,04/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,New,1,0 +9579,62143,56393,PRETRIAL,SCUTT,ENRICO,GEDEON,Male,Other,04/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +9579,62143,56393,PRETRIAL,SCUTT,ENRICO,GEDEON,Male,Other,04/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54687,62135,56387,PRETRIAL,ABEL,SHARON,NULL,Female,Caucasian,06/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +54687,62135,56387,PRETRIAL,ABEL,SHARON,NULL,Female,Caucasian,06/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +54687,62135,56387,PRETRIAL,ABEL,SHARON,NULL,Female,Caucasian,06/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54667,62107,56363,PRETRIAL,Kuang,Ciro,NULL,Male,Caucasian,02/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +54667,62107,56363,PRETRIAL,Kuang,Ciro,NULL,Male,Caucasian,02/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +54667,62107,56363,PRETRIAL,Kuang,Ciro,NULL,Male,Caucasian,02/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54673,62114,56369,PRETRIAL,Nicolas,Mimmose,NULL,Female,Other,11/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/10/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +54673,62114,56369,PRETRIAL,Nicolas,Mimmose,NULL,Female,Other,11/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/10/13 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +54673,62114,56369,PRETRIAL,Nicolas,Mimmose,NULL,Female,Other,11/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54669,62109,56365,PRETRIAL,Aziles,Jorge,NULL,Male,African-American,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,4,High,7,Risk of Violence,-0.62,10,High,New,1,0 +54669,62109,56365,PRETRIAL,Aziles,Jorge,NULL,Male,African-American,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,4,High,8,Risk of Recidivism,1.18,10,High,New,1,0 +54669,62109,56365,PRETRIAL,Aziles,Jorge,NULL,Male,African-American,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54690,62138,56390,PRETRIAL,DAVIS,ANTWAN,NULL,Male,Caucasian,03/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,4,High,7,Risk of Violence,-0.38,10,High,New,1,0 +54690,62138,56390,PRETRIAL,DAVIS,ANTWAN,NULL,Male,Caucasian,03/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,4,High,8,Risk of Recidivism,0.12,8,High,New,1,0 +54690,62138,56390,PRETRIAL,DAVIS,ANTWAN,NULL,Male,Caucasian,03/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54684,62130,56383,PRETRIAL,Scott,Lisa,NULL,Female,African-American,07/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.99,9,High,New,1,0 +54684,62130,56383,PRETRIAL,Scott,Lisa,NULL,Female,African-American,07/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.17,7,Medium,New,1,0 +54684,62130,56383,PRETRIAL,Scott,Lisa,NULL,Female,African-American,07/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54676,62117,56372,PRETRIAL,Means,Dwayne,NULL,Male,African-American,10/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +54676,62117,56372,PRETRIAL,Means,Dwayne,NULL,Male,African-American,10/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +54676,62117,56372,PRETRIAL,Means,Dwayne,NULL,Male,African-American,10/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +4389,62105,56361,PRETRIAL,nightingale,rashidi,NULL,Male,African-American,04/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/10/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +4389,62105,56361,PRETRIAL,nightingale,rashidi,NULL,Male,African-American,04/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +4389,62105,56361,PRETRIAL,nightingale,rashidi,NULL,Male,African-American,04/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54671,62112,56367,PRETRIAL,Vega,Alexander,NULL,Male,Caucasian,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,New,1,0 +54671,62112,56367,PRETRIAL,Vega,Alexander,NULL,Male,Caucasian,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +54671,62112,56367,PRETRIAL,Vega,Alexander,NULL,Male,Caucasian,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54685,62133,56385,Probation,Valle,Francisco,NULL,Male,Hispanic,11/13/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +54685,62133,56385,Probation,Valle,Francisco,NULL,Male,Hispanic,11/13/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +54685,62133,56385,Probation,Valle,Francisco,NULL,Male,Hispanic,11/13/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54681,62126,56380,Probation,Beck,Barbra,Deliah,Female,Caucasian,03/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/10/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +54681,62126,56380,Probation,Beck,Barbra,Deliah,Female,Caucasian,03/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +54681,62126,56380,Probation,Beck,Barbra,Deliah,Female,Caucasian,03/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +43996,62140,44041,Probation,Alderson,Dale,NULL,Male,Caucasian,02/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,Copy,1,0 +43996,62140,44041,Probation,Alderson,Dale,NULL,Male,Caucasian,02/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,Copy,1,0 +43996,62140,44041,Probation,Alderson,Dale,NULL,Male,Caucasian,02/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +54680,62124,56378,Probation,Smith,christian,NULL,Male,Caucasian,03/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +54680,62124,56378,Probation,Smith,christian,NULL,Male,Caucasian,03/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +54680,62124,56378,Probation,Smith,christian,NULL,Male,Caucasian,03/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54684,62131,56383,PRETRIAL,Scott,Lisa,NULL,Female,African-American,07/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.14,8,High,Copy,1,0 +54684,62131,56383,PRETRIAL,Scott,Lisa,NULL,Female,African-American,07/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.17,7,Medium,Copy,1,0 +54684,62131,56383,PRETRIAL,Scott,Lisa,NULL,Female,African-American,07/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +54670,62110,56366,PRETRIAL,Brevett,Samuel,Erasmus,Male,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +54670,62110,56366,PRETRIAL,Brevett,Samuel,Erasmus,Male,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +54670,62110,56366,PRETRIAL,Brevett,Samuel,Erasmus,Male,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54682,62128,56381,PRETRIAL,Jacobs,Cythia,Alicia,Male,African-American,04/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/10/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +54682,62128,56381,PRETRIAL,Jacobs,Cythia,Alicia,Male,African-American,04/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/10/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +54682,62128,56381,PRETRIAL,Jacobs,Cythia,Alicia,Male,African-American,04/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54692,62145,56395,PRETRIAL,MAGAZINIK,DAVID,NULL,Male,Caucasian,10/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +54692,62145,56395,PRETRIAL,MAGAZINIK,DAVID,NULL,Male,Caucasian,10/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +54692,62145,56395,PRETRIAL,MAGAZINIK,DAVID,NULL,Male,Caucasian,10/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +37097,62119,56374,PRETRIAL,Richmond,Keith,NULL,Male,African-American,01/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/10/13 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +37097,62119,56374,PRETRIAL,Richmond,Keith,NULL,Male,African-American,01/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/10/13 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +37097,62119,56374,PRETRIAL,Richmond,Keith,NULL,Male,African-American,01/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/10/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54668,62108,56364,PRETRIAL,Gonzalez,Orlando,NULL,Male,Hispanic,07/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +54668,62108,56364,PRETRIAL,Gonzalez,Orlando,NULL,Male,Hispanic,07/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +54668,62108,56364,PRETRIAL,Gonzalez,Orlando,NULL,Male,Hispanic,07/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +45584,62144,56394,Probation,BEHN,SHAUN,NULL,Male,Caucasian,10/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +45584,62144,56394,Probation,BEHN,SHAUN,NULL,Male,Caucasian,10/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +45584,62144,56394,Probation,BEHN,SHAUN,NULL,Male,Caucasian,10/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54683,62129,56382,PRETRIAL,Sanchez,David,NULL,Male,Hispanic,11/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +54683,62129,56382,PRETRIAL,Sanchez,David,NULL,Male,Hispanic,11/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +54683,62129,56382,PRETRIAL,Sanchez,David,NULL,Male,Hispanic,11/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54675,62116,56371,PRETRIAL,Rosemberg,Jeff,NULL,Male,African-American,04/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +54675,62116,56371,PRETRIAL,Rosemberg,Jeff,NULL,Male,African-American,04/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +54675,62116,56371,PRETRIAL,Rosemberg,Jeff,NULL,Male,African-American,04/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54689,62137,56389,Probation,wilson,adreanna,NULL,Female,African-American,01/11/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +54689,62137,56389,Probation,wilson,adreanna,NULL,Female,African-American,01/11/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,8,High,New,1,0 +54689,62137,56389,Probation,wilson,adreanna,NULL,Female,African-American,01/11/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52826,62121,54210,Probation,SANCHEZ,ANGEL,M,Male,Hispanic,05/02/88,17,All Scales,Intake,English,Conditional Release,Probation,Married,5/10/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +52826,62121,54210,Probation,SANCHEZ,ANGEL,M,Male,Hispanic,05/02/88,17,All Scales,Intake,English,Conditional Release,Probation,Married,5/10/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +52826,62121,54210,Probation,SANCHEZ,ANGEL,M,Male,Hispanic,05/02/88,17,All Scales,Intake,English,Conditional Release,Probation,Married,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54686,62134,56386,PRETRIAL,FERRI,WILLIAM,NULL,Male,Caucasian,08/31/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +54686,62134,56386,PRETRIAL,FERRI,WILLIAM,NULL,Male,Caucasian,08/31/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +54686,62134,56386,PRETRIAL,FERRI,WILLIAM,NULL,Male,Caucasian,08/31/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54691,62142,56392,Probation,POOLE,RANDY,NULL,Male,Caucasian,09/28/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +54691,62142,56392,Probation,POOLE,RANDY,NULL,Male,Caucasian,09/28/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +54691,62142,56392,Probation,POOLE,RANDY,NULL,Male,Caucasian,09/28/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/10/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54672,62113,56368,PRETRIAL,Mitchell,Nikevis,Shanorris,Male,African-American,05/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +54672,62113,56368,PRETRIAL,Mitchell,Nikevis,Shanorris,Male,African-American,05/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +54672,62113,56368,PRETRIAL,Mitchell,Nikevis,Shanorris,Male,African-American,05/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54705,62163,56411,PRETRIAL,MARINEY,GERARD,KEITH,Male,African-American,12/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/11/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +54705,62163,56411,PRETRIAL,MARINEY,GERARD,KEITH,Male,African-American,12/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/11/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +54705,62163,56411,PRETRIAL,MARINEY,GERARD,KEITH,Male,African-American,12/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/11/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +41060,62160,56409,Probation,LASKO,JOHN,M,Male,Caucasian,05/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +41060,62160,56409,Probation,LASKO,JOHN,M,Male,Caucasian,05/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +41060,62160,56409,Probation,LASKO,JOHN,M,Male,Caucasian,05/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54700,62155,56405,PRETRIAL,Amezquita,Juan,NULL,Male,Hispanic,11/23/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,7,Risk of Violence,-4.44,1,Low,New,1,0 +54700,62155,56405,PRETRIAL,Amezquita,Juan,NULL,Male,Hispanic,11/23/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,8,Risk of Recidivism,-2.85,1,Low,New,1,0 +54700,62155,56405,PRETRIAL,Amezquita,Juan,NULL,Male,Hispanic,11/23/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54696,62150,56400,PRETRIAL,Hill,Tamikia,NULL,Female,African-American,05/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +54696,62150,56400,PRETRIAL,Hill,Tamikia,NULL,Female,African-American,05/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +54696,62150,56400,PRETRIAL,Hill,Tamikia,NULL,Female,African-American,05/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53927,62152,56402,PRETRIAL,Chambers,Ryan,NULL,Male,Other,08/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +53927,62152,56402,PRETRIAL,Chambers,Ryan,NULL,Male,Other,08/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +53927,62152,56402,PRETRIAL,Chambers,Ryan,NULL,Male,Other,08/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +54707,62165,56413,PRETRIAL,VIERA,GUSTAVO,M,Male,Caucasian,09/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/11/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +54707,62165,56413,PRETRIAL,VIERA,GUSTAVO,M,Male,Caucasian,09/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +54707,62165,56413,PRETRIAL,VIERA,GUSTAVO,M,Male,Caucasian,09/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/11/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +38514,62158,37957,PRETRIAL,Marcelin,Moses,NULL,Male,African-American,10/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,Copy,1,0 +38514,62158,37957,PRETRIAL,Marcelin,Moses,NULL,Male,African-American,10/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.74,10,High,Copy,1,0 +38514,62158,37957,PRETRIAL,Marcelin,Moses,NULL,Male,African-American,10/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +8698,62166,42433,PRETRIAL,MEDLOCK,TEVARRIS,NULL,Male,African-American,10/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/11/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,Copy,1,0 +8698,62166,42433,PRETRIAL,MEDLOCK,TEVARRIS,NULL,Male,African-American,10/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/11/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,Copy,1,0 +8698,62166,42433,PRETRIAL,MEDLOCK,TEVARRIS,NULL,Male,African-American,10/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/11/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +54695,62149,56399,PRETRIAL,Zuniga,Carlos,NULL,Male,African-American,08/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +54695,62149,56399,PRETRIAL,Zuniga,Carlos,NULL,Male,African-American,08/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +54695,62149,56399,PRETRIAL,Zuniga,Carlos,NULL,Male,African-American,08/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54699,62154,56404,PRETRIAL,Lynch,Neil,NULL,Male,African-American,01/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +54699,62154,56404,PRETRIAL,Lynch,Neil,NULL,Male,African-American,01/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +54699,62154,56404,PRETRIAL,Lynch,Neil,NULL,Male,African-American,01/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54704,62161,56410,PRETRIAL,Monero,Antonio,NULL,Male,Caucasian,08/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +54704,62161,56410,PRETRIAL,Monero,Antonio,NULL,Male,Caucasian,08/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +54704,62161,56410,PRETRIAL,Monero,Antonio,NULL,Male,Caucasian,08/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54697,62151,56401,PRETRIAL,Cadet,Joel,Anthony,Male,Other,03/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +54697,62151,56401,PRETRIAL,Cadet,Joel,Anthony,Male,Other,03/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +54697,62151,56401,PRETRIAL,Cadet,Joel,Anthony,Male,Other,03/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54706,62164,56412,PRETRIAL,REGALDO,PATRICIO,NULL,Male,Caucasian,10/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/11/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +54706,62164,56412,PRETRIAL,REGALDO,PATRICIO,NULL,Male,Caucasian,10/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/11/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +54706,62164,56412,PRETRIAL,REGALDO,PATRICIO,NULL,Male,Caucasian,10/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54701,62156,56406,PRETRIAL,Morant,Ashley,NULL,Female,African-American,09/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/11/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +54701,62156,56406,PRETRIAL,Morant,Ashley,NULL,Female,African-American,09/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/11/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +54701,62156,56406,PRETRIAL,Morant,Ashley,NULL,Female,African-American,09/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54703,62159,56408,PRETRIAL,Vidal,Yoandy,NULL,Male,Caucasian,04/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/11/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +54703,62159,56408,PRETRIAL,Vidal,Yoandy,NULL,Male,Caucasian,04/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/11/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +54703,62159,56408,PRETRIAL,Vidal,Yoandy,NULL,Male,Caucasian,04/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54698,62153,56403,PRETRIAL,Ashley,Andre,Leighton,Male,Other,08/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +54698,62153,56403,PRETRIAL,Ashley,Andre,Leighton,Male,Other,08/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +54698,62153,56403,PRETRIAL,Ashley,Andre,Leighton,Male,Other,08/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54702,62157,56407,PRETRIAL,HOWARD,DELPONJARAI,DONELLE,Male,African-American,06/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/11/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +54702,62157,56407,PRETRIAL,HOWARD,DELPONJARAI,DONELLE,Male,African-American,06/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/11/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +54702,62157,56407,PRETRIAL,HOWARD,DELPONJARAI,DONELLE,Male,African-American,06/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +20064,62167,44081,PRETRIAL,Jacques,Keliassa,NULL,Male,African-American,10/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,Copy,1,0 +20064,62167,44081,PRETRIAL,Jacques,Keliassa,NULL,Male,African-American,10/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,Copy,1,0 +20064,62167,44081,PRETRIAL,Jacques,Keliassa,NULL,Male,African-American,10/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +30104,62162,33141,PRETRIAL,Moore,Frank,NULL,Male,Caucasian,05/09/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,Copy,1,0 +30104,62162,33141,PRETRIAL,Moore,Frank,NULL,Male,Caucasian,05/09/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,Copy,1,0 +30104,62162,33141,PRETRIAL,Moore,Frank,NULL,Male,Caucasian,05/09/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +54714,62176,56421,PRETRIAL,ONIQUE,WILLIAMS,NULL,Male,African-American,01/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/12/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +54714,62176,56421,PRETRIAL,ONIQUE,WILLIAMS,NULL,Male,African-American,01/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/12/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +54714,62176,56421,PRETRIAL,ONIQUE,WILLIAMS,NULL,Male,African-American,01/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54709,62169,56415,PRETRIAL,GUARENO-CORONA,ARISMENDY,I,Male,Caucasian,02/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +54709,62169,56415,PRETRIAL,GUARENO-CORONA,ARISMENDY,I,Male,Caucasian,02/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +54709,62169,56415,PRETRIAL,GUARENO-CORONA,ARISMENDY,I,Male,Caucasian,02/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54727,62183,56429,PRETRIAL,Culp,Daniel,NULL,Male,Caucasian,11/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +54727,62183,56429,PRETRIAL,Culp,Daniel,NULL,Male,Caucasian,11/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +54727,62183,56429,PRETRIAL,Culp,Daniel,NULL,Male,Caucasian,11/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54715,62178,56423,PRETRIAL,McNish,Katt,NULL,Female,Caucasian,05/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +54715,62178,56423,PRETRIAL,McNish,Katt,NULL,Female,Caucasian,05/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +54715,62178,56423,PRETRIAL,McNish,Katt,NULL,Female,Caucasian,05/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +11077,62174,10593,PRETRIAL,White,Gregory,NULL,Male,African-American,04/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,Copy,1,0 +11077,62174,10593,PRETRIAL,White,Gregory,NULL,Male,African-American,04/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,Copy,1,0 +11077,62174,10593,PRETRIAL,White,Gregory,NULL,Male,African-American,04/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +54731,62188,56434,PRETRIAL,Gant,tyreak,Jamar,Male,African-American,04/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +54731,62188,56434,PRETRIAL,Gant,tyreak,Jamar,Male,African-American,04/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +54731,62188,56434,PRETRIAL,Gant,tyreak,Jamar,Male,African-American,04/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54729,62185,56431,PRETRIAL,Sene,Gorvens,NULL,Male,African-American,02/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +54729,62185,56431,PRETRIAL,Sene,Gorvens,NULL,Male,African-American,02/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +54729,62185,56431,PRETRIAL,Sene,Gorvens,NULL,Male,African-American,02/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54712,62172,56418,PRETRIAL,SANTANA,BRYAN,NULL,Male,Hispanic,06/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +54712,62172,56418,PRETRIAL,SANTANA,BRYAN,NULL,Male,Hispanic,06/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +54712,62172,56418,PRETRIAL,SANTANA,BRYAN,NULL,Male,Hispanic,06/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54713,62175,56420,PRETRIAL,Walker,Carlos,NULL,Male,African-American,03/18/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +54713,62175,56420,PRETRIAL,Walker,Carlos,NULL,Male,African-American,03/18/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +54713,62175,56420,PRETRIAL,Walker,Carlos,NULL,Male,African-American,03/18/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54728,62184,56430,PRETRIAL,KITCHEN,RENARD,NULL,Male,African-American,07/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +54728,62184,56430,PRETRIAL,KITCHEN,RENARD,NULL,Male,African-American,07/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +54728,62184,56430,PRETRIAL,KITCHEN,RENARD,NULL,Male,African-American,07/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54726,62182,56428,PRETRIAL,Robert,Sloan,NULL,Male,Caucasian,03/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +54726,62182,56428,PRETRIAL,Robert,Sloan,NULL,Male,Caucasian,03/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +54726,62182,56428,PRETRIAL,Robert,Sloan,NULL,Male,Caucasian,03/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54710,62170,56416,PRETRIAL,Reid,Cordale,NULL,Male,African-American,07/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +54710,62170,56416,PRETRIAL,Reid,Cordale,NULL,Male,African-American,07/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,New,1,0 +54710,62170,56416,PRETRIAL,Reid,Cordale,NULL,Male,African-American,07/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54730,62186,56432,PRETRIAL,JACKSON,DESMOND,ANTONIO,Male,African-American,06/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +54730,62186,56432,PRETRIAL,JACKSON,DESMOND,ANTONIO,Male,African-American,06/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +54730,62186,56432,PRETRIAL,JACKSON,DESMOND,ANTONIO,Male,African-American,06/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54711,62171,56417,PRETRIAL,Johnson,Shane,NULL,Male,African-American,11/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.45,3,Low,New,1,0 +54711,62171,56417,PRETRIAL,Johnson,Shane,NULL,Male,African-American,11/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,9,High,New,1,0 +54711,62171,56417,PRETRIAL,Johnson,Shane,NULL,Male,African-American,11/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +34179,62173,56419,PRETRIAL,DEMORE,BRIAN,NULL,Male,Caucasian,02/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +34179,62173,56419,PRETRIAL,DEMORE,BRIAN,NULL,Male,Caucasian,02/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +34179,62173,56419,PRETRIAL,DEMORE,BRIAN,NULL,Male,Caucasian,02/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54732,62189,56435,PRETRIAL,Catuadella,George,NULL,Male,Caucasian,02/14/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +54732,62189,56435,PRETRIAL,Catuadella,George,NULL,Male,Caucasian,02/14/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +54732,62189,56435,PRETRIAL,Catuadella,George,NULL,Male,Caucasian,02/14/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54708,62168,56414,PRETRIAL,Sisco,Jenice,NULL,Female,Caucasian,03/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +54708,62168,56414,PRETRIAL,Sisco,Jenice,NULL,Female,Caucasian,03/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +54708,62168,56414,PRETRIAL,Sisco,Jenice,NULL,Female,Caucasian,03/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54723,62181,56427,PRETRIAL,GRISSETT,SARAH,JANE,Female,African-Am,05/28/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,7,Risk of Violence,-3.01,1,Low,New,1,0 +54723,62181,56427,PRETRIAL,GRISSETT,SARAH,JANE,Female,African-Am,05/28/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +54723,62181,56427,PRETRIAL,GRISSETT,SARAH,JANE,Female,African-Am,05/28/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +54748,62210,56454,PRETRIAL,Rodriguezcruz,Julio,NULL,Male,Hispanic,07/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +54748,62210,56454,PRETRIAL,Rodriguezcruz,Julio,NULL,Male,Hispanic,07/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +54748,62210,56454,PRETRIAL,Rodriguezcruz,Julio,NULL,Male,Hispanic,07/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54762,62228,56472,Probation,McCarthy,Julian,NULL,Male,African-American,06/18/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +54762,62228,56472,Probation,McCarthy,Julian,NULL,Male,African-American,06/18/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +54762,62228,56472,Probation,McCarthy,Julian,NULL,Male,African-American,06/18/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +37774,62202,37171,PRETRIAL,Montoya,Juan,NULL,Male,Caucasian,11/11/92,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,7,Risk of Violence,-1.33,7,Medium,New,1,0 +37774,62202,37171,PRETRIAL,Montoya,Juan,NULL,Male,Caucasian,11/11/92,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,8,Risk of Recidivism,0.12,7,Medium,New,1,0 +37774,62202,37171,PRETRIAL,Montoya,Juan,NULL,Male,Caucasian,11/11/92,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54758,62223,56467,Probation,Rodriguez,karen,NULL,Female,Hispanic,04/03/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +54758,62223,56467,Probation,Rodriguez,karen,NULL,Female,Hispanic,04/03/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +54758,62223,56467,Probation,Rodriguez,karen,NULL,Female,Hispanic,04/03/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54746,62207,56451,Probation,DOLINY,PATRICK,J,Male,African-American,08/26/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +54746,62207,56451,Probation,DOLINY,PATRICK,J,Male,African-American,08/26/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +54746,62207,56451,Probation,DOLINY,PATRICK,J,Male,African-American,08/26/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +22888,62194,56440,PRETRIAL,Glinton,Afred,NULL,Male,African-American,04/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +22888,62194,56440,PRETRIAL,Glinton,Afred,NULL,Male,African-American,04/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +22888,62194,56440,PRETRIAL,Glinton,Afred,NULL,Male,African-American,04/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54740,62200,56445,Probation,CALHOUN,JAKARI,A,Male,African-American,08/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +54740,62200,56445,Probation,CALHOUN,JAKARI,A,Male,African-American,08/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +54740,62200,56445,Probation,CALHOUN,JAKARI,A,Male,African-American,08/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +54734,62191,56437,PRETRIAL,TUMMINGS,DENNIS,NULL,Male,Other,09/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +54734,62191,56437,PRETRIAL,TUMMINGS,DENNIS,NULL,Male,Other,09/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +54734,62191,56437,PRETRIAL,TUMMINGS,DENNIS,NULL,Male,Other,09/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +22507,62196,56441,PRETRIAL,Golden,Scotty,NULL,Male,African-American,02/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +22507,62196,56441,PRETRIAL,Golden,Scotty,NULL,Male,African-American,02/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,4,High,8,Risk of Recidivism,0.89,10,High,New,1,0 +22507,62196,56441,PRETRIAL,Golden,Scotty,NULL,Male,African-American,02/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +54757,62221,56465,Probation,salerno,angela,NULL,Female,Caucasian,11/19/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +54757,62221,56465,Probation,salerno,angela,NULL,Female,Caucasian,11/19/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +54757,62221,56465,Probation,salerno,angela,NULL,Female,Caucasian,11/19/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54744,62205,56449,Probation,sarabia,adrian,NULL,Male,Hispanic,07/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +54744,62205,56449,Probation,sarabia,adrian,NULL,Male,Hispanic,07/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +54744,62205,56449,Probation,sarabia,adrian,NULL,Male,Hispanic,07/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54742,62203,56447,Probation,SANTOS,PABLO,NULL,Male,Hispanic,06/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/13/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +54742,62203,56447,Probation,SANTOS,PABLO,NULL,Male,Hispanic,06/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +54742,62203,56447,Probation,SANTOS,PABLO,NULL,Male,Hispanic,06/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54750,62212,56456,PRETRIAL,De Souza,Robson,NULL,Male,Caucasian,03/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +54750,62212,56456,PRETRIAL,De Souza,Robson,NULL,Male,Caucasian,03/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +54750,62212,56456,PRETRIAL,De Souza,Robson,NULL,Male,Caucasian,03/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54761,62226,56470,Probation,SCHENKEL,SUSAN,NULL,Female,Caucasian,05/07/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +54761,62226,56470,Probation,SCHENKEL,SUSAN,NULL,Female,Caucasian,05/07/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +54761,62226,56470,Probation,SCHENKEL,SUSAN,NULL,Female,Caucasian,05/07/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50019,62222,56466,Probation,BERMUDEZ,ANDY,NULL,Male,Hispanic,12/31/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +50019,62222,56466,Probation,BERMUDEZ,ANDY,NULL,Male,Hispanic,12/31/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +50019,62222,56466,Probation,BERMUDEZ,ANDY,NULL,Male,Hispanic,12/31/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54736,62193,56439,PRETRIAL,CHARNEL,JESSICA,SIMONE,Female,African-American,07/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +54736,62193,56439,PRETRIAL,CHARNEL,JESSICA,SIMONE,Female,African-American,07/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +54736,62193,56439,PRETRIAL,CHARNEL,JESSICA,SIMONE,Female,African-American,07/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +35268,62208,56452,PRETRIAL,Goodwin,Israel,NULL,Male,African-American,12/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +35268,62208,56452,PRETRIAL,Goodwin,Israel,NULL,Male,African-American,12/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +35268,62208,56452,PRETRIAL,Goodwin,Israel,NULL,Male,African-American,12/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54751,62214,56458,PRETRIAL,Szerkins,Michael,NULL,Male,Caucasian,12/01/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/13/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +54751,62214,56458,PRETRIAL,Szerkins,Michael,NULL,Male,Caucasian,12/01/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/13/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +54751,62214,56458,PRETRIAL,Szerkins,Michael,NULL,Male,Caucasian,12/01/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +39146,62216,56460,PRETRIAL,Cortez,Robert,Louis,Male,Caucasian,03/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,5/13/13 0:00,1,Low,7,Risk of Violence,-1,-1,N/A,New,1,0 +39146,62216,56460,PRETRIAL,Cortez,Robert,Louis,Male,Caucasian,03/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +39146,62216,56460,PRETRIAL,Cortez,Robert,Louis,Male,Caucasian,03/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54741,62201,56446,Probation,Gay,Diane,M,Female,Caucasian,05/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Divorced,5/13/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +54741,62201,56446,Probation,Gay,Diane,M,Female,Caucasian,05/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Divorced,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +54741,62201,56446,Probation,Gay,Diane,M,Female,Caucasian,05/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Divorced,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54755,62219,56463,PRETRIAL,Paez,Gina,NULL,Female,Hispanic,07/28/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +54755,62219,56463,PRETRIAL,Paez,Gina,NULL,Female,Hispanic,07/28/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +54755,62219,56463,PRETRIAL,Paez,Gina,NULL,Female,Hispanic,07/28/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54738,62198,56443,PRETRIAL,Hill,Fredrick,NULL,Male,African-American,06/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +54738,62198,56443,PRETRIAL,Hill,Fredrick,NULL,Male,African-American,06/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +54738,62198,56443,PRETRIAL,Hill,Fredrick,NULL,Male,African-American,06/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +51912,62227,56471,PRETRIAL,Tavis,Paul,NULL,Male,Caucasian,11/02/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/13/13 0:00,2,Medium,7,Risk of Violence,-3.29,1,Low,New,1,0 +51912,62227,56471,PRETRIAL,Tavis,Paul,NULL,Male,Caucasian,11/02/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +51912,62227,56471,PRETRIAL,Tavis,Paul,NULL,Male,Caucasian,11/02/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/13/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54759,62224,56468,PRETRIAL,Gourdet,Sindy,NULL,Male,African-American,10/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +54759,62224,56468,PRETRIAL,Gourdet,Sindy,NULL,Male,African-American,10/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +54759,62224,56468,PRETRIAL,Gourdet,Sindy,NULL,Male,African-American,10/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54739,62199,56444,PRETRIAL,CHAPMAN,KODY,MICHAEL,Male,Caucasian,02/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +54739,62199,56444,PRETRIAL,CHAPMAN,KODY,MICHAEL,Male,Caucasian,02/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +54739,62199,56444,PRETRIAL,CHAPMAN,KODY,MICHAEL,Male,Caucasian,02/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +45746,62213,56457,PRETRIAL,Camire,Mario,NULL,Male,Caucasian,08/17/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/13/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +45746,62213,56457,PRETRIAL,Camire,Mario,NULL,Male,Caucasian,08/17/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +45746,62213,56457,PRETRIAL,Camire,Mario,NULL,Male,Caucasian,08/17/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54735,62192,56438,PRETRIAL,Schoen,Robert,NULL,Male,Caucasian,12/03/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/13/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +54735,62192,56438,PRETRIAL,Schoen,Robert,NULL,Male,Caucasian,12/03/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/13/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +54735,62192,56438,PRETRIAL,Schoen,Robert,NULL,Male,Caucasian,12/03/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +19361,62195,18602,PRETRIAL,HENDRICKS,HOWARD,NULL,Male,African-American,03/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,Copy,1,0 +19361,62195,18602,PRETRIAL,HENDRICKS,HOWARD,NULL,Male,African-American,03/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,Copy,1,0 +19361,62195,18602,PRETRIAL,HENDRICKS,HOWARD,NULL,Male,African-American,03/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +54747,62209,56453,PRETRIAL,Pericles,Miguelson,NULL,Male,African-American,07/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +54747,62209,56453,PRETRIAL,Pericles,Miguelson,NULL,Male,African-American,07/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +54747,62209,56453,PRETRIAL,Pericles,Miguelson,NULL,Male,African-American,07/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54753,62220,56464,Probation,Manuel,thomas,NULL,Male,Hispanic,05/08/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/13/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +54753,62220,56464,Probation,Manuel,thomas,NULL,Male,Hispanic,05/08/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +54753,62220,56464,Probation,Manuel,thomas,NULL,Male,Hispanic,05/08/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54749,62211,56455,Probation,SUTCLIFFE,JOSEPH,B,Male,Caucasian,06/12/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/13/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +54749,62211,56455,Probation,SUTCLIFFE,JOSEPH,B,Male,Caucasian,06/12/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/13/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +54749,62211,56455,Probation,SUTCLIFFE,JOSEPH,B,Male,Caucasian,06/12/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54733,62190,56436,PRETRIAL,Clark,John,NULL,Male,African-American,10/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,7,Risk of Violence,-2.49,3,Low,New,1,0 +54733,62190,56436,PRETRIAL,Clark,John,NULL,Male,African-American,10/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +54733,62190,56436,PRETRIAL,Clark,John,NULL,Male,African-American,10/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54737,62197,56442,PRETRIAL,Jodlowski,Jacek,NULL,Male,Caucasian,12/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +54737,62197,56442,PRETRIAL,Jodlowski,Jacek,NULL,Male,Caucasian,12/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +54737,62197,56442,PRETRIAL,Jodlowski,Jacek,NULL,Male,Caucasian,12/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54743,62204,56448,Probation,Conley,Tramaine,NULL,Male,African-American,05/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,5/13/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +54743,62204,56448,Probation,Conley,Tramaine,NULL,Male,African-American,05/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,5/13/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +54743,62204,56448,Probation,Conley,Tramaine,NULL,Male,African-American,05/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,5/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +22560,23657,21734,PRETRIAL,OZUNA,ABEL,ANTONIO,Male,Hispanic,11/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +22560,23657,21734,PRETRIAL,OZUNA,ABEL,ANTONIO,Male,Hispanic,11/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +22560,23657,21734,PRETRIAL,OZUNA,ABEL,ANTONIO,Male,Hispanic,11/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54787,62262,56504,PRETRIAL,Dreiss,Gia,NULL,Female,Caucasian,03/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +54787,62262,56504,PRETRIAL,Dreiss,Gia,NULL,Female,Caucasian,03/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +54787,62262,56504,PRETRIAL,Dreiss,Gia,NULL,Female,Caucasian,03/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +32997,62267,56508,PRETRIAL,perez,eduardo,NULL,Male,Hispanic,04/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +32997,62267,56508,PRETRIAL,perez,eduardo,NULL,Male,Hispanic,04/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +32997,62267,56508,PRETRIAL,perez,eduardo,NULL,Male,Hispanic,04/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54769,62239,56483,PRETRIAL,VASSELL,ANDRIA,M,Female,African-American,07/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +54769,62239,56483,PRETRIAL,VASSELL,ANDRIA,M,Female,African-American,07/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +54769,62239,56483,PRETRIAL,VASSELL,ANDRIA,M,Female,African-American,07/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54770,62241,56485,PRETRIAL,Grant,Mikhail,NULL,Male,Other,02/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,New,1,0 +54770,62241,56485,PRETRIAL,Grant,Mikhail,NULL,Male,Other,02/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +54770,62241,56485,PRETRIAL,Grant,Mikhail,NULL,Male,Other,02/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54774,62246,56490,PRETRIAL,Emerson,William,Eugene,Male,Caucasian,12/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +54774,62246,56490,PRETRIAL,Emerson,William,Eugene,Male,Caucasian,12/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +54774,62246,56490,PRETRIAL,Emerson,William,Eugene,Male,Caucasian,12/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54776,62248,56492,Probation,Rowe,Hugh,NULL,Male,African-American,01/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +54776,62248,56492,Probation,Rowe,Hugh,NULL,Male,African-American,01/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +54776,62248,56492,Probation,Rowe,Hugh,NULL,Male,African-American,01/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +34642,62260,40668,PRETRIAL,Willingham,Joey,NULL,Male,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,Copy,1,0 +34642,62260,40668,PRETRIAL,Willingham,Joey,NULL,Male,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,Copy,1,0 +34642,62260,40668,PRETRIAL,Willingham,Joey,NULL,Male,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +54764,62234,56478,PRETRIAL,Johnson,Jazze,NULL,Male,African-American,09/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.22,4,Low,New,1,0 +54764,62234,56478,PRETRIAL,Johnson,Jazze,NULL,Male,African-American,09/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +54764,62234,56478,PRETRIAL,Johnson,Jazze,NULL,Male,African-American,09/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54779,62251,56495,Probation,Myers,Eric,NULL,Male,Caucasian,04/15/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +54779,62251,56495,Probation,Myers,Eric,NULL,Male,Caucasian,04/15/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +54779,62251,56495,Probation,Myers,Eric,NULL,Male,Caucasian,04/15/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +41482,62230,56474,Probation,Thiena,Antrell,NULL,Male,African-American,11/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +41482,62230,56474,Probation,Thiena,Antrell,NULL,Male,African-American,11/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +41482,62230,56474,Probation,Thiena,Antrell,NULL,Male,African-American,11/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54783,62255,56499,PRETRIAL,TELLO,JOFFRE,ANDRES,Male,Caucasian,04/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +54783,62255,56499,PRETRIAL,TELLO,JOFFRE,ANDRES,Male,Caucasian,04/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +54783,62255,56499,PRETRIAL,TELLO,JOFFRE,ANDRES,Male,Caucasian,04/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54653,62264,56351,PRETRIAL,Jackson,Tyrone,NULL,Male,African-American,09/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,Copy,1,0 +54653,62264,56351,PRETRIAL,Jackson,Tyrone,NULL,Male,African-American,09/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.1,10,High,Copy,1,0 +54653,62264,56351,PRETRIAL,Jackson,Tyrone,NULL,Male,African-American,09/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +54773,62245,56489,PRETRIAL,Kosinskii,Vitali,NULL,Male,Caucasian,08/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +54773,62245,56489,PRETRIAL,Kosinskii,Vitali,NULL,Male,Caucasian,08/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +54773,62245,56489,PRETRIAL,Kosinskii,Vitali,NULL,Male,Caucasian,08/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54763,62232,56476,PRETRIAL,Peralta,Ivan,NULL,Male,Hispanic,09/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +54763,62232,56476,PRETRIAL,Peralta,Ivan,NULL,Male,Hispanic,09/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +54763,62232,56476,PRETRIAL,Peralta,Ivan,NULL,Male,Hispanic,09/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +19187,62266,56507,Probation,staley,joshua,NULL,Male,African-American,09/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +19187,62266,56507,Probation,staley,joshua,NULL,Male,African-American,09/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +19187,62266,56507,Probation,staley,joshua,NULL,Male,African-American,09/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54781,62253,56497,PRETRIAL,Parker,Jahmal,NULL,Male,African-American,12/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +54781,62253,56497,PRETRIAL,Parker,Jahmal,NULL,Male,African-American,12/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +54781,62253,56497,PRETRIAL,Parker,Jahmal,NULL,Male,African-American,12/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54765,62235,56479,PRETRIAL,Kelly,Darron,NULL,Male,African-American,03/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/14/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +54765,62235,56479,PRETRIAL,Kelly,Darron,NULL,Male,African-American,03/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +54765,62235,56479,PRETRIAL,Kelly,Darron,NULL,Male,African-American,03/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54767,62237,56481,PRETRIAL,MCKENZIE,JAMES,LUCIUS,Male,African-American,03/29/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +54767,62237,56481,PRETRIAL,MCKENZIE,JAMES,LUCIUS,Male,African-American,03/29/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +54767,62237,56481,PRETRIAL,MCKENZIE,JAMES,LUCIUS,Male,African-American,03/29/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54778,62250,56494,Probation,PENN,VIVIAN,NULL,Female,Hispanic,04/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +54778,62250,56494,Probation,PENN,VIVIAN,NULL,Female,Hispanic,04/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +54778,62250,56494,Probation,PENN,VIVIAN,NULL,Female,Hispanic,04/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54772,62243,56487,PRETRIAL,MADAIRE,VESTIN,NULL,Male,African-American,03/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +54772,62243,56487,PRETRIAL,MADAIRE,VESTIN,NULL,Male,African-American,03/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +54772,62243,56487,PRETRIAL,MADAIRE,VESTIN,NULL,Male,African-American,03/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54786,62258,56502,Probation,DANIEL,ALONSO,NULL,Male,Hispanic,01/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +54786,62258,56502,Probation,DANIEL,ALONSO,NULL,Male,Hispanic,01/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +54786,62258,56502,Probation,DANIEL,ALONSO,NULL,Male,Hispanic,01/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +22560,62261,21734,PRETRIAL,OZUNA,ABEL,ANTONIO,Male,Hispanic,11/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,Copy,1,0 +22560,62261,21734,PRETRIAL,OZUNA,ABEL,ANTONIO,Male,Hispanic,11/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,Copy,1,0 +22560,62261,21734,PRETRIAL,OZUNA,ABEL,ANTONIO,Male,Hispanic,11/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +39749,62233,56477,PRETRIAL,Williams,Terry,NULL,Male,African-American,09/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +39749,62233,56477,PRETRIAL,Williams,Terry,NULL,Male,African-American,09/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +39749,62233,56477,PRETRIAL,Williams,Terry,NULL,Male,African-American,09/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54188,62240,56484,PRETRIAL,MCCALL,JEMEIL,NULL,Female,African-American,04/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,7,Risk of Violence,-2.65,2,Low,New,1,0 +54188,62240,56484,PRETRIAL,MCCALL,JEMEIL,NULL,Female,African-American,04/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +54188,62240,56484,PRETRIAL,MCCALL,JEMEIL,NULL,Female,African-American,04/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54775,62247,56491,Probation,rex,leslie,NULL,Female,Caucasian,08/24/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/14/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +54775,62247,56491,Probation,rex,leslie,NULL,Female,Caucasian,08/24/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +54775,62247,56491,Probation,rex,leslie,NULL,Female,Caucasian,08/24/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54782,62254,56498,Probation,CIRILLO,DYLAN,NULL,Male,Caucasian,09/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +54782,62254,56498,Probation,CIRILLO,DYLAN,NULL,Male,Caucasian,09/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +54782,62254,56498,Probation,CIRILLO,DYLAN,NULL,Male,Caucasian,09/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54789,62268,56509,Probation,Hamilton,Telekia,NULL,Female,African-American,05/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +54789,62268,56509,Probation,Hamilton,Telekia,NULL,Female,African-American,05/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +54789,62268,56509,Probation,Hamilton,Telekia,NULL,Female,African-American,05/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54768,62238,56482,PRETRIAL,Grimes,Adrian,Oneal,Male,African-American,12/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,4,High,7,Risk of Violence,-0.42,10,High,New,1,0 +54768,62238,56482,PRETRIAL,Grimes,Adrian,Oneal,Male,African-American,12/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +54768,62238,56482,PRETRIAL,Grimes,Adrian,Oneal,Male,African-American,12/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54784,62256,56500,Probation,Whiteley,David,NULL,Male,Caucasian,07/18/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/14/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +54784,62256,56500,Probation,Whiteley,David,NULL,Male,Caucasian,07/18/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +54784,62256,56500,Probation,Whiteley,David,NULL,Male,Caucasian,07/18/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54788,62263,56505,PRETRIAL,scott,william,NULL,Male,African-American,07/02/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +54788,62263,56505,PRETRIAL,scott,william,NULL,Male,African-American,07/02/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +54788,62263,56505,PRETRIAL,scott,william,NULL,Male,African-American,07/02/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +54771,62242,56486,PRETRIAL,ABELL,KEVIN,LEE,Male,Caucasian,01/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +54771,62242,56486,PRETRIAL,ABELL,KEVIN,LEE,Male,Caucasian,01/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +54771,62242,56486,PRETRIAL,ABELL,KEVIN,LEE,Male,Caucasian,01/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +13122,62259,56503,PRETRIAL,Longway,Michael,NULL,Male,Caucasian,03/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,New,1,0 +13122,62259,56503,PRETRIAL,Longway,Michael,NULL,Male,Caucasian,03/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +13122,62259,56503,PRETRIAL,Longway,Michael,NULL,Male,Caucasian,03/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +30040,62244,56488,PRETRIAL,simpson,giovanni,NULL,Male,Other,07/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +30040,62244,56488,PRETRIAL,simpson,giovanni,NULL,Male,Other,07/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +30040,62244,56488,PRETRIAL,simpson,giovanni,NULL,Male,Other,07/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +46945,62265,56506,PRETRIAL,COWELL,MARY,BARBARA,Female,Caucasian,05/30/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +46945,62265,56506,PRETRIAL,COWELL,MARY,BARBARA,Female,Caucasian,05/30/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +46945,62265,56506,PRETRIAL,COWELL,MARY,BARBARA,Female,Caucasian,05/30/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +54780,62252,56496,PRETRIAL,Clarke,Barissa,NULL,Female,Other,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +54780,62252,56496,PRETRIAL,Clarke,Barissa,NULL,Female,Other,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +54780,62252,56496,PRETRIAL,Clarke,Barissa,NULL,Female,Other,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54785,62257,56501,PRETRIAL,STEPHAN,DUANE,NULL,Male,Caucasian,10/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/14/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +54785,62257,56501,PRETRIAL,STEPHAN,DUANE,NULL,Male,Caucasian,10/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/14/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +54785,62257,56501,PRETRIAL,STEPHAN,DUANE,NULL,Male,Caucasian,10/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54766,62236,56480,PRETRIAL,Bell,Louveni,Clemons,Female,African-American,10/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +54766,62236,56480,PRETRIAL,Bell,Louveni,Clemons,Female,African-American,10/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +54766,62236,56480,PRETRIAL,Bell,Louveni,Clemons,Female,African-American,10/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54366,62231,56475,PRETRIAL,Fullerton,Ruth,NULL,Female,Other,07/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +54366,62231,56475,PRETRIAL,Fullerton,Ruth,NULL,Female,Other,07/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +54366,62231,56475,PRETRIAL,Fullerton,Ruth,NULL,Female,Other,07/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54777,62249,56493,Probation,hoyt,anthony,NULL,Male,Caucasian,06/12/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +54777,62249,56493,Probation,hoyt,anthony,NULL,Male,Caucasian,06/12/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +54777,62249,56493,Probation,hoyt,anthony,NULL,Male,Caucasian,06/12/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54804,62288,56528,Probation,Hall,Rexford,NULL,Male,African-American,05/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +54804,62288,56528,Probation,Hall,Rexford,NULL,Male,African-American,05/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +54804,62288,56528,Probation,Hall,Rexford,NULL,Male,African-American,05/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54796,62278,56518,PRETRIAL,Rosewell,Steve,NULL,Male,Other,11/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +54796,62278,56518,PRETRIAL,Rosewell,Steve,NULL,Male,Other,11/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +54796,62278,56518,PRETRIAL,Rosewell,Steve,NULL,Male,Other,11/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54790,62270,56510,PRETRIAL,FRANCIS,ALRICK,NULL,Male,Other,02/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +54790,62270,56510,PRETRIAL,FRANCIS,ALRICK,NULL,Male,Other,02/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +54790,62270,56510,PRETRIAL,FRANCIS,ALRICK,NULL,Male,Other,02/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54806,62291,56530,Probation,Turner,timorrean,NULL,Male,African-American,02/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +54806,62291,56530,Probation,Turner,timorrean,NULL,Male,African-American,02/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +54806,62291,56530,Probation,Turner,timorrean,NULL,Male,African-American,02/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54339,62296,55953,PRETRIAL,Pegnatore,Joseph,NULL,Male,Caucasian,11/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.96,9,High,Copy,1,0 +54339,62296,55953,PRETRIAL,Pegnatore,Joseph,NULL,Male,Caucasian,11/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +54339,62296,55953,PRETRIAL,Pegnatore,Joseph,NULL,Male,Caucasian,11/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +54803,62286,56526,Probation,wilson,KENNETH,NULL,Male,African-American,11/19/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +54803,62286,56526,Probation,wilson,KENNETH,NULL,Male,African-American,11/19/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +54803,62286,56526,Probation,wilson,KENNETH,NULL,Male,African-American,11/19/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54792,62273,56513,PRETRIAL,FELIX,DOSHAN,NULL,Female,Caucasian,06/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/15/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +54792,62273,56513,PRETRIAL,FELIX,DOSHAN,NULL,Female,Caucasian,06/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/15/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +54792,62273,56513,PRETRIAL,FELIX,DOSHAN,NULL,Female,Caucasian,06/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54798,62280,56520,PRETRIAL,MILLER,DEANDRE,NULL,Male,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +54798,62280,56520,PRETRIAL,MILLER,DEANDRE,NULL,Male,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +54798,62280,56520,PRETRIAL,MILLER,DEANDRE,NULL,Male,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54821,62307,56542,PRETRIAL,Duggins,Lancy,NULL,Male,African-American,12/27/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +54821,62307,56542,PRETRIAL,Duggins,Lancy,NULL,Male,African-American,12/27/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +54821,62307,56542,PRETRIAL,Duggins,Lancy,NULL,Male,African-American,12/27/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +54791,62272,56512,PRETRIAL,duran,elvis,NULL,Male,Hispanic,05/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +54791,62272,56512,PRETRIAL,duran,elvis,NULL,Male,Hispanic,05/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +54791,62272,56512,PRETRIAL,duran,elvis,NULL,Male,Hispanic,05/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54809,62293,56532,Probation,FELIX,NOEL,NULL,Male,Hispanic,09/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +54809,62293,56532,Probation,FELIX,NOEL,NULL,Male,Hispanic,09/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +54809,62293,56532,Probation,FELIX,NOEL,NULL,Male,Hispanic,09/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54808,62294,56533,Probation,Wood,Michael,NULL,Male,Caucasian,06/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +54808,62294,56533,Probation,Wood,Michael,NULL,Male,Caucasian,06/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +54808,62294,56533,Probation,Wood,Michael,NULL,Male,Caucasian,06/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54795,62277,56517,PRETRIAL,Goss,Alonzo,NULL,Male,African-American,02/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +54795,62277,56517,PRETRIAL,Goss,Alonzo,NULL,Male,African-American,02/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +54795,62277,56517,PRETRIAL,Goss,Alonzo,NULL,Male,African-American,02/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54815,62298,56535,PRETRIAL,Smith,Karl,NULL,Male,Caucasian,11/12/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/15/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +54815,62298,56535,PRETRIAL,Smith,Karl,NULL,Male,Caucasian,11/12/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/15/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +54815,62298,56535,PRETRIAL,Smith,Karl,NULL,Male,Caucasian,11/12/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54794,62275,56515,PRETRIAL,Bracey,Derrian,Monette,Female,African-American,09/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +54794,62275,56515,PRETRIAL,Bracey,Derrian,Monette,Female,African-American,09/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +54794,62275,56515,PRETRIAL,Bracey,Derrian,Monette,Female,African-American,09/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54800,62284,56524,Probation,Grant,Raymond,NULL,Male,African-American,10/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +54800,62284,56524,Probation,Grant,Raymond,NULL,Male,African-American,10/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +54800,62284,56524,Probation,Grant,Raymond,NULL,Male,African-American,10/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54818,62303,56538,Probation,TILLMAN,GARY,NULL,Male,Caucasian,12/16/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/15/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +54818,62303,56538,Probation,TILLMAN,GARY,NULL,Male,Caucasian,12/16/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/15/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +54818,62303,56538,Probation,TILLMAN,GARY,NULL,Male,Caucasian,12/16/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +41542,62282,56522,PRETRIAL,Barbary,Curtis,NULL,Male,African-American,10/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,4,High,7,Risk of Violence,-1.23,8,High,New,1,0 +41542,62282,56522,PRETRIAL,Barbary,Curtis,NULL,Male,African-American,10/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +41542,62282,56522,PRETRIAL,Barbary,Curtis,NULL,Male,African-American,10/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +54820,62305,56540,Probation,Bharat,Thulsie,NULL,Male,Other,08/28/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/15/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +54820,62305,56540,Probation,Bharat,Thulsie,NULL,Male,Other,08/28/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/15/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +54820,62305,56540,Probation,Bharat,Thulsie,NULL,Male,Other,08/28/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54822,62308,56543,PRETRIAL,SMITH,KELLI,NULL,Female,Caucasian,08/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +54822,62308,56543,PRETRIAL,SMITH,KELLI,NULL,Female,Caucasian,08/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +54822,62308,56543,PRETRIAL,SMITH,KELLI,NULL,Female,Caucasian,08/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +54797,62279,56519,PRETRIAL,MAZMANIAN,JOHN,ALBERT,Male,Caucasian,11/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +54797,62279,56519,PRETRIAL,MAZMANIAN,JOHN,ALBERT,Male,Caucasian,11/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +54797,62279,56519,PRETRIAL,MAZMANIAN,JOHN,ALBERT,Male,Caucasian,11/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +24628,62271,56511,PRETRIAL,Simpson,Paul,NULL,Male,Other,07/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +24628,62271,56511,PRETRIAL,Simpson,Paul,NULL,Male,Other,07/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +24628,62271,56511,PRETRIAL,Simpson,Paul,NULL,Male,Other,07/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +54802,62287,56527,Probation,McLaughlin,Jennifer,NULL,Male,Caucasian,07/16/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +54802,62287,56527,Probation,McLaughlin,Jennifer,NULL,Male,Caucasian,07/16/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +54802,62287,56527,Probation,McLaughlin,Jennifer,NULL,Male,Caucasian,07/16/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54816,62300,56536,Probation,PUENTES,SERGIO,ROBERTO,Male,Hispanic,10/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +54816,62300,56536,Probation,PUENTES,SERGIO,ROBERTO,Male,Hispanic,10/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +54816,62300,56536,Probation,PUENTES,SERGIO,ROBERTO,Male,Hispanic,10/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54807,62292,56531,Probation,Medina,Juan,NULL,Male,Hispanic,05/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +54807,62292,56531,Probation,Medina,Juan,NULL,Male,Hispanic,05/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +54807,62292,56531,Probation,Medina,Juan,NULL,Male,Hispanic,05/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54793,62274,56514,PRETRIAL,PERRY,JUSTIN,DION,Male,African-American,06/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +54793,62274,56514,PRETRIAL,PERRY,JUSTIN,DION,Male,African-American,06/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +54793,62274,56514,PRETRIAL,PERRY,JUSTIN,DION,Male,African-American,06/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54817,62302,56537,PRETRIAL,Champ,Danald,NULL,Male,Caucasian,01/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/15/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +54817,62302,56537,PRETRIAL,Champ,Danald,NULL,Male,Caucasian,01/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/15/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +54817,62302,56537,PRETRIAL,Champ,Danald,NULL,Male,Caucasian,01/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54799,62281,56521,PRETRIAL,Jensen,Clifford,Michael,Male,Caucasian,08/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +54799,62281,56521,PRETRIAL,Jensen,Clifford,Michael,Male,Caucasian,08/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +54799,62281,56521,PRETRIAL,Jensen,Clifford,Michael,Male,Caucasian,08/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +6330,62306,56541,PRETRIAL,BROUN,ROBERT,A,Male,Caucasian,04/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +6330,62306,56541,PRETRIAL,BROUN,ROBERT,A,Male,Caucasian,04/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +6330,62306,56541,PRETRIAL,BROUN,ROBERT,A,Male,Caucasian,04/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +2160,62269,54288,PRETRIAL,MOODY,JORDAN,J,Male,African-American,11/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,4,High,7,Risk of Violence,-0.62,10,High,Copy,1,0 +2160,62269,54288,PRETRIAL,MOODY,JORDAN,J,Male,African-American,11/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,4,High,8,Risk of Recidivism,0.46,9,High,Copy,1,0 +2160,62269,54288,PRETRIAL,MOODY,JORDAN,J,Male,African-American,11/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +49848,62276,56516,PRETRIAL,Henry,Neville,Paul,Male,African-American,11/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,4,High,7,Risk of Violence,-0.85,9,High,New,1,0 +49848,62276,56516,PRETRIAL,Henry,Neville,Paul,Male,African-American,11/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +49848,62276,56516,PRETRIAL,Henry,Neville,Paul,Male,African-American,11/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +46409,62283,56523,PRETRIAL,Desrouleaux,Jack,NULL,Male,African-American,01/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +46409,62283,56523,PRETRIAL,Desrouleaux,Jack,NULL,Male,African-American,01/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +46409,62283,56523,PRETRIAL,Desrouleaux,Jack,NULL,Male,African-American,01/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52880,62290,54275,Probation,MCINTYRE,IAN,N,Male,Caucasian,12/22/66,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +52880,62290,54275,Probation,MCINTYRE,IAN,N,Male,Caucasian,12/22/66,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,8,Risk of Recidivism,-0.93,2,Low,New,1,0 +52880,62290,54275,Probation,MCINTYRE,IAN,N,Male,Caucasian,12/22/66,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/15/13 0:00,1,Low,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +54825,62311,56546,PRETRIAL,Intindola,John,NULL,Male,Caucasian,08/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/16/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +54825,62311,56546,PRETRIAL,Intindola,John,NULL,Male,Caucasian,08/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +54825,62311,56546,PRETRIAL,Intindola,John,NULL,Male,Caucasian,08/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54837,62325,56560,PRETRIAL,PEDERSEN,SEAN,NULL,Male,Caucasian,01/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +54837,62325,56560,PRETRIAL,PEDERSEN,SEAN,NULL,Male,Caucasian,01/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +54837,62325,56560,PRETRIAL,PEDERSEN,SEAN,NULL,Male,Caucasian,01/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54862,62362,56596,Probation,simon,marquez,NULL,Male,Hispanic,11/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +54862,62362,56596,Probation,simon,marquez,NULL,Male,Hispanic,11/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +54862,62362,56596,Probation,simon,marquez,NULL,Male,Hispanic,11/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54831,62318,56553,PRETRIAL,Do,Cuong,My,Male,Asian,03/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +54831,62318,56553,PRETRIAL,Do,Cuong,My,Male,Asian,03/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +54831,62318,56553,PRETRIAL,Do,Cuong,My,Male,Asian,03/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +54833,62320,56555,PRETRIAL,Roberts,Holly,NULL,Female,Caucasian,01/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +54833,62320,56555,PRETRIAL,Roberts,Holly,NULL,Female,Caucasian,01/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,6,Medium,New,1,0 +54833,62320,56555,PRETRIAL,Roberts,Holly,NULL,Female,Caucasian,01/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54844,62339,56573,Probation,renick,jackie,NULL,Female,Caucasian,06/30/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +54844,62339,56573,Probation,renick,jackie,NULL,Female,Caucasian,06/30/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +54844,62339,56573,Probation,renick,jackie,NULL,Female,Caucasian,06/30/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54850,62346,56580,Probation,DEROCHE,HENRY,T,Male,African-American,10/22/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +54850,62346,56580,Probation,DEROCHE,HENRY,T,Male,African-American,10/22/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +54850,62346,56580,Probation,DEROCHE,HENRY,T,Male,African-American,10/22/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54851,62348,56582,Probation,LEE,MARK,G,Male,Caucasian,03/27/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +54851,62348,56582,Probation,LEE,MARK,G,Male,Caucasian,03/27/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +54851,62348,56582,Probation,LEE,MARK,G,Male,Caucasian,03/27/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +31536,62327,56562,PRETRIAL,Williams,Glenn,NULL,Male,African-American,03/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +31536,62327,56562,PRETRIAL,Williams,Glenn,NULL,Male,African-American,03/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.78,10,High,New,1,0 +31536,62327,56562,PRETRIAL,Williams,Glenn,NULL,Male,African-American,03/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54842,62336,56571,Probation,simeon,tiffany,NULL,Female,African-American,11/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,2,Medium,7,Risk of Violence,-3,1,Low,New,1,0 +54842,62336,56571,Probation,simeon,tiffany,NULL,Female,African-American,11/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +54842,62336,56571,Probation,simeon,tiffany,NULL,Female,African-American,11/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +54855,62353,56587,Probation,Allison,Brian,NULL,Male,Caucasian,05/31/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +54855,62353,56587,Probation,Allison,Brian,NULL,Male,Caucasian,05/31/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +54855,62353,56587,Probation,Allison,Brian,NULL,Male,Caucasian,05/31/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +54835,62323,56558,PRETRIAL,ROBINSON,JOHNNIE,NULL,Male,African-American,08/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +54835,62323,56558,PRETRIAL,ROBINSON,JOHNNIE,NULL,Male,African-American,08/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +54835,62323,56558,PRETRIAL,ROBINSON,JOHNNIE,NULL,Male,African-American,08/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54859,62357,56591,Probation,Spickard,Robin,NULL,Female,Caucasian,05/27/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/13 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +54859,62357,56591,Probation,Spickard,Robin,NULL,Female,Caucasian,05/27/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +54859,62357,56591,Probation,Spickard,Robin,NULL,Female,Caucasian,05/27/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54827,62313,56548,PRETRIAL,SMITH,EDWARD,NULL,Male,African-American,10/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.06,8,High,New,1,0 +54827,62313,56548,PRETRIAL,SMITH,EDWARD,NULL,Male,African-American,10/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +54827,62313,56548,PRETRIAL,SMITH,EDWARD,NULL,Male,African-American,10/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +22501,62363,56597,Probation,oswald,michael,NULL,Male,Caucasian,07/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +22501,62363,56597,Probation,oswald,michael,NULL,Male,Caucasian,07/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +22501,62363,56597,Probation,oswald,michael,NULL,Male,Caucasian,07/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54846,62342,56576,PRETRIAL,WYCHE,ALLEN,NULL,Male,African-American,08/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +54846,62342,56576,PRETRIAL,WYCHE,ALLEN,NULL,Male,African-American,08/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +54846,62342,56576,PRETRIAL,WYCHE,ALLEN,NULL,Male,African-American,08/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54841,62334,56569,Probation,ALONSO,IVELYS,NULL,Female,Hispanic,09/06/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +54841,62334,56569,Probation,ALONSO,IVELYS,NULL,Female,Hispanic,09/06/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +54841,62334,56569,Probation,ALONSO,IVELYS,NULL,Female,Hispanic,09/06/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54834,62321,56556,PRETRIAL,Daniels,Toccara,Roshon,Female,African-American,09/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +54834,62321,56556,PRETRIAL,Daniels,Toccara,Roshon,Female,African-American,09/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +54834,62321,56556,PRETRIAL,Daniels,Toccara,Roshon,Female,African-American,09/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54857,62355,56589,Probation,TALBOTT,GREGORY,L,Male,Caucasian,10/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +54857,62355,56589,Probation,TALBOTT,GREGORY,L,Male,Caucasian,10/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +54857,62355,56589,Probation,TALBOTT,GREGORY,L,Male,Caucasian,10/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54830,62316,56551,PRETRIAL,Russell,Shane,NULL,Male,African-American,02/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +54830,62316,56551,PRETRIAL,Russell,Shane,NULL,Male,African-American,02/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +54830,62316,56551,PRETRIAL,Russell,Shane,NULL,Male,African-American,02/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54853,62350,56584,Probation,vallejo,lorena,NULL,Female,Hispanic,08/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +54853,62350,56584,Probation,vallejo,lorena,NULL,Female,Hispanic,08/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +54853,62350,56584,Probation,vallejo,lorena,NULL,Female,Hispanic,08/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +40176,62337,39760,PRETRIAL,Dunlap,Monica,NULL,Female,African-American,08/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,Copy,1,0 +40176,62337,39760,PRETRIAL,Dunlap,Monica,NULL,Female,African-American,08/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,Copy,1,0 +40176,62337,39760,PRETRIAL,Dunlap,Monica,NULL,Female,African-American,08/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +49593,62352,56586,PRETRIAL,Fisher,Michael,Carter,Male,Caucasian,04/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +49593,62352,56586,PRETRIAL,Fisher,Michael,Carter,Male,Caucasian,04/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +49593,62352,56586,PRETRIAL,Fisher,Michael,Carter,Male,Caucasian,04/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +54838,62329,56564,PRETRIAL,CONNELL,EDWARD,M,Male,Caucasian,02/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +54838,62329,56564,PRETRIAL,CONNELL,EDWARD,M,Male,Caucasian,02/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +54838,62329,56564,PRETRIAL,CONNELL,EDWARD,M,Male,Caucasian,02/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54849,62344,56578,PRETRIAL,VAIA,MICHAEL,NULL,Male,Caucasian,08/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +54849,62344,56578,PRETRIAL,VAIA,MICHAEL,NULL,Male,Caucasian,08/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +54849,62344,56578,PRETRIAL,VAIA,MICHAEL,NULL,Male,Caucasian,08/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54863,62365,56599,Probation,santos,ariel,NULL,Male,Caucasian,08/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/16/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +54863,62365,56599,Probation,santos,ariel,NULL,Male,Caucasian,08/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +54863,62365,56599,Probation,santos,ariel,NULL,Male,Caucasian,08/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54856,62354,56588,Probation,maldonado,milagros,NULL,Female,Hispanic,03/25/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/16/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +54856,62354,56588,Probation,maldonado,milagros,NULL,Female,Hispanic,03/25/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/16/13 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +54856,62354,56588,Probation,maldonado,milagros,NULL,Female,Hispanic,03/25/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54826,62312,56547,PRETRIAL,Bryan,Devaughn,Travis,Male,African-American,04/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +54826,62312,56547,PRETRIAL,Bryan,Devaughn,Travis,Male,African-American,04/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +54826,62312,56547,PRETRIAL,Bryan,Devaughn,Travis,Male,African-American,04/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +47480,62326,56561,PRETRIAL,Morrison,Patrick,NULL,Male,African-American,05/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +47480,62326,56561,PRETRIAL,Morrison,Patrick,NULL,Male,African-American,05/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +47480,62326,56561,PRETRIAL,Morrison,Patrick,NULL,Male,African-American,05/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54861,62361,56595,Probation,Desiderio,Joseph,NULL,Male,Caucasian,12/10/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +54861,62361,56595,Probation,Desiderio,Joseph,NULL,Male,Caucasian,12/10/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +54861,62361,56595,Probation,Desiderio,Joseph,NULL,Male,Caucasian,12/10/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +17397,62333,56568,PRETRIAL,Howell,Tyrone,Chacellor,Male,African-American,06/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +17397,62333,56568,PRETRIAL,Howell,Tyrone,Chacellor,Male,African-American,06/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +17397,62333,56568,PRETRIAL,Howell,Tyrone,Chacellor,Male,African-American,06/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54845,62340,56574,Probation,lewis,andrew,NULL,Male,African-American,06/28/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +54845,62340,56574,Probation,lewis,andrew,NULL,Male,African-American,06/28/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +54845,62340,56574,Probation,lewis,andrew,NULL,Male,African-American,06/28/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +42961,62347,56581,PRETRIAL,Presmy,Theodis,Lorenzo,Male,African-American,06/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,New,1,0 +42961,62347,56581,PRETRIAL,Presmy,Theodis,Lorenzo,Male,African-American,06/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +42961,62347,56581,PRETRIAL,Presmy,Theodis,Lorenzo,Male,African-American,06/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54832,62319,56554,PRETRIAL,Hough,Richard,Paul,Male,Caucasian,09/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +54832,62319,56554,PRETRIAL,Hough,Richard,Paul,Male,Caucasian,09/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +54832,62319,56554,PRETRIAL,Hough,Richard,Paul,Male,Caucasian,09/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +54824,62310,56545,PRETRIAL,Brantley,Marquis,Ellis,Male,African-American,05/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +54824,62310,56545,PRETRIAL,Brantley,Marquis,Ellis,Male,African-American,05/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +54824,62310,56545,PRETRIAL,Brantley,Marquis,Ellis,Male,African-American,05/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +11440,62328,56563,PRETRIAL,Atkins,Jeremy,Louis,Male,African-American,08/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.15,8,High,New,1,0 +11440,62328,56563,PRETRIAL,Atkins,Jeremy,Louis,Male,African-American,08/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +11440,62328,56563,PRETRIAL,Atkins,Jeremy,Louis,Male,African-American,08/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54848,62345,56579,Probation,KNIGHT,COREY,NULL,Male,African-American,07/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +54848,62345,56579,Probation,KNIGHT,COREY,NULL,Male,African-American,07/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +54848,62345,56579,Probation,KNIGHT,COREY,NULL,Male,African-American,07/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54836,62324,56559,PRETRIAL,ACEVEDO,CHASITY,JASALENE,Female,Caucasian,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +54836,62324,56559,PRETRIAL,ACEVEDO,CHASITY,JASALENE,Female,Caucasian,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +54836,62324,56559,PRETRIAL,ACEVEDO,CHASITY,JASALENE,Female,Caucasian,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54839,62331,56566,Probation,LEWIS,QUEEN,L,Female,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +54839,62331,56566,Probation,LEWIS,QUEEN,L,Female,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +54839,62331,56566,Probation,LEWIS,QUEEN,L,Female,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54852,62349,56583,Probation,Davis,Joe,NULL,Male,African-American,11/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +54852,62349,56583,Probation,Davis,Joe,NULL,Male,African-American,11/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +54852,62349,56583,Probation,Davis,Joe,NULL,Male,African-American,11/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54847,62343,56577,PRETRIAL,Victor,Antz,Israle,Male,African-American,03/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +54847,62343,56577,PRETRIAL,Victor,Antz,Israle,Male,African-American,03/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +54847,62343,56577,PRETRIAL,Victor,Antz,Israle,Male,African-American,03/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +22752,62315,56550,Probation,Issac,Valdyn,NULL,Male,African-American,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +22752,62315,56550,Probation,Issac,Valdyn,NULL,Male,African-American,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,4,High,8,Risk of Recidivism,0.15,8,High,New,1,0 +22752,62315,56550,Probation,Issac,Valdyn,NULL,Male,African-American,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +19311,62322,56557,PRETRIAL,DOZIER,JERMAINE,NULL,Male,African-American,03/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,New,1,0 +19311,62322,56557,PRETRIAL,DOZIER,JERMAINE,NULL,Male,African-American,03/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +19311,62322,56557,PRETRIAL,DOZIER,JERMAINE,NULL,Male,African-American,03/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54828,62314,56549,PRETRIAL,Zargos,George,NULL,Male,Caucasian,08/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +54828,62314,56549,PRETRIAL,Zargos,George,NULL,Male,Caucasian,08/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +54828,62314,56549,PRETRIAL,Zargos,George,NULL,Male,Caucasian,08/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54840,62335,56570,Probation,cisneros,cindy,NULL,Female,Hispanic,06/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/16/13 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +54840,62335,56570,Probation,cisneros,cindy,NULL,Female,Hispanic,06/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +54840,62335,56570,Probation,cisneros,cindy,NULL,Female,Hispanic,06/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/16/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45121,62330,56565,PRETRIAL,mosley,walter,NULL,Male,African-American,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,7,Risk of Violence,-1.27,7,Medium,New,1,0 +45121,62330,56565,PRETRIAL,mosley,walter,NULL,Male,African-American,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +45121,62330,56565,PRETRIAL,mosley,walter,NULL,Male,African-American,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +3913,62364,56598,PRETRIAL,AGUIRE,FRANCISCO,NULL,Male,Caucasian,05/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +3913,62364,56598,PRETRIAL,AGUIRE,FRANCISCO,NULL,Male,Caucasian,05/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +3913,62364,56598,PRETRIAL,AGUIRE,FRANCISCO,NULL,Male,Caucasian,05/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54829,62317,56552,PRETRIAL,Ryan,Willie,Lee,Male,African-American,10/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +54829,62317,56552,PRETRIAL,Ryan,Willie,Lee,Male,African-American,10/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,4,High,8,Risk of Recidivism,0.45,9,High,New,1,0 +54829,62317,56552,PRETRIAL,Ryan,Willie,Lee,Male,African-American,10/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45838,62359,56593,Probation,PAZ,REUBEN,ALEXANDER,Male,Hispanic,12/25/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +45838,62359,56593,Probation,PAZ,REUBEN,ALEXANDER,Male,Hispanic,12/25/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +45838,62359,56593,Probation,PAZ,REUBEN,ALEXANDER,Male,Hispanic,12/25/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54843,62338,56572,PRETRIAL,Lane,Marcus,NULL,Male,African-American,03/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +54843,62338,56572,PRETRIAL,Lane,Marcus,NULL,Male,African-American,03/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/13 0:00,4,High,8,Risk of Recidivism,0.48,9,High,New,1,0 +54843,62338,56572,PRETRIAL,Lane,Marcus,NULL,Male,African-American,03/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54858,62356,56590,Probation,lopez,martin,NULL,Male,Hispanic,03/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/16/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +54858,62356,56590,Probation,lopez,martin,NULL,Male,Hispanic,03/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/16/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +54858,62356,56590,Probation,lopez,martin,NULL,Male,Hispanic,03/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54886,62406,56634,Probation,marks,michael,NULL,Male,Caucasian,09/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +54886,62406,56634,Probation,marks,michael,NULL,Male,Caucasian,09/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +54886,62406,56634,Probation,marks,michael,NULL,Male,Caucasian,09/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +46682,62377,56611,PRETRIAL,Starling,Alfonso,NULL,Male,Caucasian,01/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +46682,62377,56611,PRETRIAL,Starling,Alfonso,NULL,Male,Caucasian,01/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +46682,62377,56611,PRETRIAL,Starling,Alfonso,NULL,Male,Caucasian,01/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54881,62398,56627,Probation,Mcrill,Clinton,David,Male,Caucasian,11/29/56,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +54881,62398,56627,Probation,Mcrill,Clinton,David,Male,Caucasian,11/29/56,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +54881,62398,56627,Probation,Mcrill,Clinton,David,Male,Caucasian,11/29/56,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54883,62401,56629,PRETRIAL,Cunningham,Michael,NULL,Male,Caucasian,07/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +54883,62401,56629,PRETRIAL,Cunningham,Michael,NULL,Male,Caucasian,07/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +54883,62401,56629,PRETRIAL,Cunningham,Michael,NULL,Male,Caucasian,07/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54868,62380,56614,PRETRIAL,Meilleur,Keaira,NULL,Female,African-American,07/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +54868,62380,56614,PRETRIAL,Meilleur,Keaira,NULL,Female,African-American,07/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +54868,62380,56614,PRETRIAL,Meilleur,Keaira,NULL,Female,African-American,07/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54864,62372,56606,PRETRIAL,Gordon,Erricka,NULL,Female,African-American,11/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +54864,62372,56606,PRETRIAL,Gordon,Erricka,NULL,Female,African-American,11/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +54864,62372,56606,PRETRIAL,Gordon,Erricka,NULL,Female,African-American,11/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54890,62408,56636,DRRD,Parrish,Jason,Tyrone,Male,African-American,04/29/88,17,All Scales,Intake,English,Probation Violator,Probation,Single,5/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +54890,62408,56636,DRRD,Parrish,Jason,Tyrone,Male,African-American,04/29/88,17,All Scales,Intake,English,Probation Violator,Probation,Single,5/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,8,High,New,1,0 +54890,62408,56636,DRRD,Parrish,Jason,Tyrone,Male,African-American,04/29/88,17,All Scales,Intake,English,Probation Violator,Probation,Single,5/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +9825,62393,55508,PRETRIAL,MURRAY,JAMAAL,RADHAD,Male,African-American,06/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,4,High,7,Risk of Violence,-0.4,10,High,Copy,1,0 +9825,62393,55508,PRETRIAL,MURRAY,JAMAAL,RADHAD,Male,African-American,06/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,4,High,8,Risk of Recidivism,1.2,10,High,Copy,1,0 +9825,62393,55508,PRETRIAL,MURRAY,JAMAAL,RADHAD,Male,African-American,06/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,4,High,18,Risk of Failure to Appear,29,7,Medium,Copy,1,0 +1306,62370,56604,PRETRIAL,KNIGHT,DEMETRIUS,NULL,Male,African-American,09/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +1306,62370,56604,PRETRIAL,KNIGHT,DEMETRIUS,NULL,Male,African-American,09/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +1306,62370,56604,PRETRIAL,KNIGHT,DEMETRIUS,NULL,Male,African-American,09/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54271,62387,55870,PRETRIAL,Stone,Cynthia,Ann,Female,Caucasian,05/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,Copy,1,0 +54271,62387,55870,PRETRIAL,Stone,Cynthia,Ann,Female,Caucasian,05/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,Copy,1,0 +54271,62387,55870,PRETRIAL,Stone,Cynthia,Ann,Female,Caucasian,05/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +54877,62391,56622,PRETRIAL,NORALUS,TONY,NULL,Male,African-American,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,2,Medium,7,Risk of Violence,-2.86,2,Low,New,1,0 +54877,62391,56622,PRETRIAL,NORALUS,TONY,NULL,Male,African-American,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +54877,62391,56622,PRETRIAL,NORALUS,TONY,NULL,Male,African-American,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54880,62396,56625,PRETRIAL,Robinson,Darren,NULL,Male,African-American,06/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/17/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +54880,62396,56625,PRETRIAL,Robinson,Darren,NULL,Male,African-American,06/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +54880,62396,56625,PRETRIAL,Robinson,Darren,NULL,Male,African-American,06/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54892,62412,56640,Probation,shell,reginald,NULL,Male,African-American,07/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +54892,62412,56640,Probation,shell,reginald,NULL,Male,African-American,07/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +54892,62412,56640,Probation,shell,reginald,NULL,Male,African-American,07/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54871,62384,56617,Probation,bonito,michael,NULL,Male,Caucasian,08/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +54871,62384,56617,Probation,bonito,michael,NULL,Male,Caucasian,08/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +54871,62384,56617,Probation,bonito,michael,NULL,Male,Caucasian,08/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54885,62403,56631,Probation,hyppolite,alande,NULL,Male,Other,01/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/17/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +54885,62403,56631,Probation,hyppolite,alande,NULL,Male,Other,01/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +54885,62403,56631,Probation,hyppolite,alande,NULL,Male,Other,01/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54865,62375,56609,PRETRIAL,Valmyr,Antoine,Tony,Male,African-American,06/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +54865,62375,56609,PRETRIAL,Valmyr,Antoine,Tony,Male,African-American,06/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +54865,62375,56609,PRETRIAL,Valmyr,Antoine,Tony,Male,African-American,06/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54870,62382,56616,Probation,Mitchell,Lashay,NULL,Female,African-American,08/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +54870,62382,56616,Probation,Mitchell,Lashay,NULL,Female,African-American,08/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +54870,62382,56616,Probation,Mitchell,Lashay,NULL,Female,African-American,08/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +30033,62405,56633,PRETRIAL,Russell,Jerome,NULL,Male,African-American,01/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +30033,62405,56633,PRETRIAL,Russell,Jerome,NULL,Male,African-American,01/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +30033,62405,56633,PRETRIAL,Russell,Jerome,NULL,Male,African-American,01/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54867,62379,56613,PRETRIAL,Kelly,Latoya,Elain,Female,African-American,03/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +54867,62379,56613,PRETRIAL,Kelly,Latoya,Elain,Female,African-American,03/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +54867,62379,56613,PRETRIAL,Kelly,Latoya,Elain,Female,African-American,03/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54879,62394,56624,PRETRIAL,BURTON,JAMAR,NULL,Male,African-American,12/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +54879,62394,56624,PRETRIAL,BURTON,JAMAR,NULL,Male,African-American,12/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +54879,62394,56624,PRETRIAL,BURTON,JAMAR,NULL,Male,African-American,12/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54872,62386,56618,PRETRIAL,Barfield,Michael,NULL,Male,African-Am,09/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,5/17/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +54872,62386,56618,PRETRIAL,Barfield,Michael,NULL,Male,African-Am,09/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +54872,62386,56618,PRETRIAL,Barfield,Michael,NULL,Male,African-Am,09/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +38597,62373,56607,PRETRIAL,Swinton,Edwin,NULL,Male,African-American,05/30/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/17/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +38597,62373,56607,PRETRIAL,Swinton,Edwin,NULL,Male,African-American,05/30/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +38597,62373,56607,PRETRIAL,Swinton,Edwin,NULL,Male,African-American,05/30/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54887,62407,56635,Probation,johnston,logan,NULL,Male,Caucasian,11/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +54887,62407,56635,Probation,johnston,logan,NULL,Male,Caucasian,11/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +54887,62407,56635,Probation,johnston,logan,NULL,Male,Caucasian,11/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +34677,62389,56620,Probation,dawson,dina,NULL,Female,Caucasian,02/27/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.87,2,Low,New,1,0 +34677,62389,56620,Probation,dawson,dina,NULL,Female,Caucasian,02/27/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,9,High,New,1,0 +34677,62389,56620,Probation,dawson,dina,NULL,Female,Caucasian,02/27/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +8772,62368,56602,PRETRIAL,Walker,Marcus,NULL,Male,African-American,11/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,4,High,7,Risk of Violence,-0.53,10,High,New,1,0 +8772,62368,56602,PRETRIAL,Walker,Marcus,NULL,Male,African-American,11/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,4,High,8,Risk of Recidivism,0.7,10,High,New,1,0 +8772,62368,56602,PRETRIAL,Walker,Marcus,NULL,Male,African-American,11/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54884,62402,56630,Probation,reckner,MICHAEL,NULL,Male,Caucasian,07/16/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +54884,62402,56630,Probation,reckner,MICHAEL,NULL,Male,Caucasian,07/16/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +54884,62402,56630,Probation,reckner,MICHAEL,NULL,Male,Caucasian,07/16/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47174,62410,56638,PRETRIAL,Jones,Buddie,NULL,Male,Caucasian,01/23/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +47174,62410,56638,PRETRIAL,Jones,Buddie,NULL,Male,Caucasian,01/23/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +47174,62410,56638,PRETRIAL,Jones,Buddie,NULL,Male,Caucasian,01/23/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54869,62381,56615,Probation,kahn,danielle,NULL,Female,Caucasian,07/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +54869,62381,56615,Probation,kahn,danielle,NULL,Female,Caucasian,07/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +54869,62381,56615,Probation,kahn,danielle,NULL,Female,Caucasian,07/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +47088,62404,56632,PRETRIAL,Spence,Charles,NULL,Male,African-American,03/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/17/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +47088,62404,56632,PRETRIAL,Spence,Charles,NULL,Male,African-American,03/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/17/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +47088,62404,56632,PRETRIAL,Spence,Charles,NULL,Male,African-American,03/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54878,62392,56623,PRETRIAL,Saddler,Eric,Charles,Male,African-American,08/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/17/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +54878,62392,56623,PRETRIAL,Saddler,Eric,Charles,Male,African-American,08/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +54878,62392,56623,PRETRIAL,Saddler,Eric,Charles,Male,African-American,08/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +6776,62395,6370,PRETRIAL,LAWHORN,TANARVIS,A,Male,African-American,01/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,Copy,1,0 +6776,62395,6370,PRETRIAL,LAWHORN,TANARVIS,A,Male,African-American,01/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,Copy,1,0 +6776,62395,6370,PRETRIAL,LAWHORN,TANARVIS,A,Male,African-American,01/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +54891,62409,56637,Probation,hosper,marcia,NULL,Female,Caucasian,07/30/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +54891,62409,56637,Probation,hosper,marcia,NULL,Female,Caucasian,07/30/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +54891,62409,56637,Probation,hosper,marcia,NULL,Female,Caucasian,07/30/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +1116,62374,56608,PRETRIAL,Pardee,James,Lawrence,Male,Caucasian,11/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/17/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +1116,62374,56608,PRETRIAL,Pardee,James,Lawrence,Male,Caucasian,11/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +1116,62374,56608,PRETRIAL,Pardee,James,Lawrence,Male,Caucasian,11/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54875,62388,56619,Probation,castro,isis,NULL,Female,Hispanic,08/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +54875,62388,56619,Probation,castro,isis,NULL,Female,Hispanic,08/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +54875,62388,56619,Probation,castro,isis,NULL,Female,Hispanic,08/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54882,62399,56628,PRETRIAL,Benjamin,Tanisha,NULL,Female,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +54882,62399,56628,PRETRIAL,Benjamin,Tanisha,NULL,Female,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +54882,62399,56628,PRETRIAL,Benjamin,Tanisha,NULL,Female,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +3438,62367,56601,PRETRIAL,sylvain,ismael,NULL,Male,African-American,03/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +3438,62367,56601,PRETRIAL,sylvain,ismael,NULL,Male,African-American,03/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.95,10,High,New,1,0 +3438,62367,56601,PRETRIAL,sylvain,ismael,NULL,Male,African-American,03/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +39879,62369,56603,PRETRIAL,Motts,Larry,NULL,Male,African-American,04/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,4,High,7,Risk of Violence,-0.47,10,High,New,1,0 +39879,62369,56603,PRETRIAL,Motts,Larry,NULL,Male,African-American,04/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,4,High,8,Risk of Recidivism,0.55,9,High,New,1,0 +39879,62369,56603,PRETRIAL,Motts,Larry,NULL,Male,African-American,04/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +54866,62376,56610,PRETRIAL,Bergman,Douglas,H,Male,Caucasian,01/31/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +54866,62376,56610,PRETRIAL,Bergman,Douglas,H,Male,Caucasian,01/31/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +54866,62376,56610,PRETRIAL,Bergman,Douglas,H,Male,Caucasian,01/31/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +24535,62411,56639,PRETRIAL,SMITH,DEMETRIUS,NULL,Male,African-American,03/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.35,3,Low,New,1,0 +24535,62411,56639,PRETRIAL,SMITH,DEMETRIUS,NULL,Male,African-American,03/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +24535,62411,56639,PRETRIAL,SMITH,DEMETRIUS,NULL,Male,African-American,03/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54876,62390,56621,PRETRIAL,HERNANDEZ,RAYMOND,NULL,Male,Caucasian,06/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +54876,62390,56621,PRETRIAL,HERNANDEZ,RAYMOND,NULL,Male,Caucasian,06/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +54876,62390,56621,PRETRIAL,HERNANDEZ,RAYMOND,NULL,Male,Caucasian,06/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +29393,62418,56646,PRETRIAL,Mcglashan,Gervan,NULL,Male,African-American,10/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +29393,62418,56646,PRETRIAL,Mcglashan,Gervan,NULL,Male,African-American,10/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +29393,62418,56646,PRETRIAL,Mcglashan,Gervan,NULL,Male,African-American,10/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54895,62420,56648,PRETRIAL,Kidd,Joy,NULL,Female,Caucasian,01/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,2,Medium,7,Risk of Violence,-2.73,2,Low,New,1,0 +54895,62420,56648,PRETRIAL,Kidd,Joy,NULL,Female,Caucasian,01/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +54895,62420,56648,PRETRIAL,Kidd,Joy,NULL,Female,Caucasian,01/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +19904,62413,56641,PRETRIAL,WALKINS,DARIN,GREGORY,Male,African-American,08/07/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +19904,62413,56641,PRETRIAL,WALKINS,DARIN,GREGORY,Male,African-American,08/07/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +19904,62413,56641,PRETRIAL,WALKINS,DARIN,GREGORY,Male,African-American,08/07/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +54898,62425,56651,PRETRIAL,lozandier,wilnick,NULL,Male,African-American,06/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.52,10,High,New,1,0 +54898,62425,56651,PRETRIAL,lozandier,wilnick,NULL,Male,African-American,06/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +54898,62425,56651,PRETRIAL,lozandier,wilnick,NULL,Male,African-American,06/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54897,62423,56650,PRETRIAL,JAMISON,PHILIP,NULL,Male,Caucasian,01/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +54897,62423,56650,PRETRIAL,JAMISON,PHILIP,NULL,Male,Caucasian,01/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +54897,62423,56650,PRETRIAL,JAMISON,PHILIP,NULL,Male,Caucasian,01/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54893,62415,56643,PRETRIAL,Cruz-Neves,Andrew,NULL,Male,Hispanic,05/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +54893,62415,56643,PRETRIAL,Cruz-Neves,Andrew,NULL,Male,Hispanic,05/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +54893,62415,56643,PRETRIAL,Cruz-Neves,Andrew,NULL,Male,Hispanic,05/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +16300,62417,56645,PRETRIAL,SMITH,HERMAN,J,Male,African-American,03/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,4,High,7,Risk of Violence,-0.58,10,High,New,1,0 +16300,62417,56645,PRETRIAL,SMITH,HERMAN,J,Male,African-American,03/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,4,High,8,Risk of Recidivism,1.17,10,High,New,1,0 +16300,62417,56645,PRETRIAL,SMITH,HERMAN,J,Male,African-American,03/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54896,62421,56649,PRETRIAL,YATES,PATRICIA,ANN,Female,Caucasian,01/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +54896,62421,56649,PRETRIAL,YATES,PATRICIA,ANN,Female,Caucasian,01/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/13 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +54896,62421,56649,PRETRIAL,YATES,PATRICIA,ANN,Female,Caucasian,01/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53836,62422,55340,Probation,GALETTE,CLAUDEL,C,Male,African-American,05/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,Copy,1,0 +53836,62422,55340,Probation,GALETTE,CLAUDEL,C,Male,African-American,05/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,Copy,1,0 +53836,62422,55340,Probation,GALETTE,CLAUDEL,C,Male,African-American,05/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +45045,62414,56642,PRETRIAL,Gonzalez,Michael,Anthony,Male,Hispanic,11/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,4,High,7,Risk of Violence,-0.65,9,High,New,1,0 +45045,62414,56642,PRETRIAL,Gonzalez,Michael,Anthony,Male,Hispanic,11/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,4,High,8,Risk of Recidivism,0.9,10,High,New,1,0 +45045,62414,56642,PRETRIAL,Gonzalez,Michael,Anthony,Male,Hispanic,11/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +23528,62416,56644,PRETRIAL,RIVERS,STANLEY,NULL,Male,African-American,12/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,4,High,7,Risk of Violence,-0.47,10,High,New,1,0 +23528,62416,56644,PRETRIAL,RIVERS,STANLEY,NULL,Male,African-American,12/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,4,High,8,Risk of Recidivism,1.01,10,High,New,1,0 +23528,62416,56644,PRETRIAL,RIVERS,STANLEY,NULL,Male,African-American,12/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54894,62419,56647,PRETRIAL,Robinson,Renoir,NULL,Male,Other,09/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +54894,62419,56647,PRETRIAL,Robinson,Renoir,NULL,Male,Other,09/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +54894,62419,56647,PRETRIAL,Robinson,Renoir,NULL,Male,Other,09/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +21565,62424,20717,PRETRIAL,CARTER,HENRY,L,Male,African-American,10/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,Copy,1,0 +21565,62424,20717,PRETRIAL,CARTER,HENRY,L,Male,African-American,10/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,Copy,1,0 +21565,62424,20717,PRETRIAL,CARTER,HENRY,L,Male,African-American,10/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +54899,62427,56653,PRETRIAL,DUNDAS,RYAN,JOSEOH,Male,Caucasian,05/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +54899,62427,56653,PRETRIAL,DUNDAS,RYAN,JOSEOH,Male,Caucasian,05/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +54899,62427,56653,PRETRIAL,DUNDAS,RYAN,JOSEOH,Male,Caucasian,05/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +36402,62432,56656,PRETRIAL,McDougle,Anthony,NULL,Male,African-American,08/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +36402,62432,56656,PRETRIAL,McDougle,Anthony,NULL,Male,African-American,08/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +36402,62432,56656,PRETRIAL,McDougle,Anthony,NULL,Male,African-American,08/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,4,High,18,Risk of Failure to Appear,42,10,High,New,1,0 +13385,62435,21992,PRETRIAL,KILLINGS,ALLEN,ALEXANDER,Male,African-American,09/27/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.06,8,High,Copy,1,0 +13385,62435,21992,PRETRIAL,KILLINGS,ALLEN,ALEXANDER,Male,African-American,09/27/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,Copy,1,0 +13385,62435,21992,PRETRIAL,KILLINGS,ALLEN,ALEXANDER,Male,African-American,09/27/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +54905,62437,56660,PRETRIAL,GILLETT,WALTER,M,Male,Caucasian,02/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,2,Medium,7,Risk of Violence,-2.63,2,Low,New,1,0 +54905,62437,56660,PRETRIAL,GILLETT,WALTER,M,Male,Caucasian,02/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +54905,62437,56660,PRETRIAL,GILLETT,WALTER,M,Male,Caucasian,02/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54906,62438,56661,PRETRIAL,CARTER,SHAWN,NULL,Male,Caucasian,08/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/19/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +54906,62438,56661,PRETRIAL,CARTER,SHAWN,NULL,Male,Caucasian,08/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/19/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +54906,62438,56661,PRETRIAL,CARTER,SHAWN,NULL,Male,Caucasian,08/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/19/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54900,62426,56652,PRETRIAL,Desilus,Jimmy,NULL,Male,Other,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +54900,62426,56652,PRETRIAL,Desilus,Jimmy,NULL,Male,Other,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +54900,62426,56652,PRETRIAL,Desilus,Jimmy,NULL,Male,Other,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54902,62433,56657,PRETRIAL,REED,ROBERT,NULL,Male,African-American,02/17/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +54902,62433,56657,PRETRIAL,REED,ROBERT,NULL,Male,African-American,02/17/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +54902,62433,56657,PRETRIAL,REED,ROBERT,NULL,Male,African-American,02/17/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54904,62436,56659,PRETRIAL,WILLIAMS,GERALD,NULL,Male,African-American,10/15/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +54904,62436,56659,PRETRIAL,WILLIAMS,GERALD,NULL,Male,African-American,10/15/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +54904,62436,56659,PRETRIAL,WILLIAMS,GERALD,NULL,Male,African-American,10/15/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +13771,62431,56655,PRETRIAL,Exalus,Jackson,NULL,Male,Other,11/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +13771,62431,56655,PRETRIAL,Exalus,Jackson,NULL,Male,Other,11/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +13771,62431,56655,PRETRIAL,Exalus,Jackson,NULL,Male,Other,11/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54901,62428,56654,PRETRIAL,Jackson,Clarence,NULL,Male,African-American,12/29/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/19/13 0:00,2,Medium,7,Risk of Violence,-3.34,1,Low,New,1,0 +54901,62428,56654,PRETRIAL,Jackson,Clarence,NULL,Male,African-American,12/29/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +54901,62428,56654,PRETRIAL,Jackson,Clarence,NULL,Male,African-American,12/29/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/19/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +44498,62430,45849,PRETRIAL,Breedlove,Leotis,NULL,Male,African-American,10/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,4,High,7,Risk of Violence,-1.05,8,High,Copy,1,0 +44498,62430,45849,PRETRIAL,Breedlove,Leotis,NULL,Male,African-American,10/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,4,High,8,Risk of Recidivism,0.43,9,High,Copy,1,0 +44498,62430,45849,PRETRIAL,Breedlove,Leotis,NULL,Male,African-American,10/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +54903,62434,56658,PRETRIAL,Tuck,Edward,NULL,Male,African-American,03/18/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +54903,62434,56658,PRETRIAL,Tuck,Edward,NULL,Male,African-American,03/18/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +54903,62434,56658,PRETRIAL,Tuck,Edward,NULL,Male,African-American,03/18/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +54907,62439,56662,PRETRIAL,GRAHAM,JAHARA,VERSHUN,Male,African-American,01/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.48,3,Low,New,1,0 +54907,62439,56662,PRETRIAL,GRAHAM,JAHARA,VERSHUN,Male,African-American,01/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +54907,62439,56662,PRETRIAL,GRAHAM,JAHARA,VERSHUN,Male,African-American,01/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54909,62441,56664,PRETRIAL,Young,Rudolph,NULL,Male,African-American,01/02/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.38,3,Low,New,1,0 +54909,62441,56664,PRETRIAL,Young,Rudolph,NULL,Male,African-American,01/02/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +54909,62441,56664,PRETRIAL,Young,Rudolph,NULL,Male,African-American,01/02/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +54914,62448,56671,PRETRIAL,Rodrigues,Benedictihe,NULL,Male,Caucasian,05/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/20/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +54914,62448,56671,PRETRIAL,Rodrigues,Benedictihe,NULL,Male,Caucasian,05/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/20/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +54914,62448,56671,PRETRIAL,Rodrigues,Benedictihe,NULL,Male,Caucasian,05/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +49056,62462,56684,Probation,mcneal,james,NULL,Male,Caucasian,08/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/20/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +49056,62462,56684,Probation,mcneal,james,NULL,Male,Caucasian,08/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/20/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +49056,62462,56684,Probation,mcneal,james,NULL,Male,Caucasian,08/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +36277,62451,56673,PRETRIAL,GRAY,COURTNEY,NULL,Male,African-American,02/08/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +36277,62451,56673,PRETRIAL,GRAY,COURTNEY,NULL,Male,African-American,02/08/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +36277,62451,56673,PRETRIAL,GRAY,COURTNEY,NULL,Male,African-American,02/08/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54917,62455,56677,Probation,Melendez Guzman,Rodrigo,NULL,Male,Hispanic,03/13/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +54917,62455,56677,Probation,Melendez Guzman,Rodrigo,NULL,Male,Hispanic,03/13/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +54917,62455,56677,Probation,Melendez Guzman,Rodrigo,NULL,Male,Hispanic,03/13/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54922,62464,56686,Probation,Carter,William,NULL,Male,Caucasian,06/28/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +54922,62464,56686,Probation,Carter,William,NULL,Male,Caucasian,06/28/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +54922,62464,56686,Probation,Carter,William,NULL,Male,Caucasian,06/28/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +44649,62446,56669,PRETRIAL,Rodriguez,Deanna,NULL,Female,Caucasian,12/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,4,High,7,Risk of Violence,-0.66,9,High,New,1,0 +44649,62446,56669,PRETRIAL,Rodriguez,Deanna,NULL,Female,Caucasian,12/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,4,High,8,Risk of Recidivism,0.37,9,High,New,1,0 +44649,62446,56669,PRETRIAL,Rodriguez,Deanna,NULL,Female,Caucasian,12/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +48253,62460,56682,PRETRIAL,Jones,Cecil,NULL,Male,African-American,11/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +48253,62460,56682,PRETRIAL,Jones,Cecil,NULL,Male,African-American,11/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +48253,62460,56682,PRETRIAL,Jones,Cecil,NULL,Male,African-American,11/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54915,62449,56672,PRETRIAL,Ebanks,Roxana,Alvarez,Female,Hispanic,06/28/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/20/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +54915,62449,56672,PRETRIAL,Ebanks,Roxana,Alvarez,Female,Hispanic,06/28/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/20/13 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +54915,62449,56672,PRETRIAL,Ebanks,Roxana,Alvarez,Female,Hispanic,06/28/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54918,62457,56679,Probation,Crisan,Giovanni,NULL,Male,Hispanic,11/11/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +54918,62457,56679,Probation,Crisan,Giovanni,NULL,Male,Hispanic,11/11/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +54918,62457,56679,Probation,Crisan,Giovanni,NULL,Male,Hispanic,11/11/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54923,62465,56687,PRETRIAL,FOLEY,SEAN,RYAN,Male,Caucasian,02/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,4,High,7,Risk of Violence,-0.68,9,High,New,1,0 +54923,62465,56687,PRETRIAL,FOLEY,SEAN,RYAN,Male,Caucasian,02/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,4,High,8,Risk of Recidivism,0.8,10,High,New,1,0 +54923,62465,56687,PRETRIAL,FOLEY,SEAN,RYAN,Male,Caucasian,02/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +16608,62444,56667,PRETRIAL,Morris,Leonard,NULL,Male,African-American,06/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +16608,62444,56667,PRETRIAL,Morris,Leonard,NULL,Male,African-American,06/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +16608,62444,56667,PRETRIAL,Morris,Leonard,NULL,Male,African-American,06/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +54908,62440,56663,PRETRIAL,Lapa,Paulo,NULL,Male,Hispanic,08/16/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/20/13 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +54908,62440,56663,PRETRIAL,Lapa,Paulo,NULL,Male,Hispanic,08/16/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/20/13 0:00,1,Low,8,Risk of Recidivism,-2.93,1,Low,New,1,0 +54908,62440,56663,PRETRIAL,Lapa,Paulo,NULL,Male,Hispanic,08/16/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54913,62447,56670,PRETRIAL,Torres,Jason,NULL,Male,Hispanic,09/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +54913,62447,56670,PRETRIAL,Torres,Jason,NULL,Male,Hispanic,09/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +54913,62447,56670,PRETRIAL,Torres,Jason,NULL,Male,Hispanic,09/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +45589,62461,56683,Probation,camejo,erica,NULL,Female,Hispanic,01/19/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +45589,62461,56683,Probation,camejo,erica,NULL,Female,Hispanic,01/19/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +45589,62461,56683,Probation,camejo,erica,NULL,Female,Hispanic,01/19/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54916,62454,56676,Probation,Jones,Dwight,NULL,Male,African-American,02/24/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/20/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +54916,62454,56676,Probation,Jones,Dwight,NULL,Male,African-American,02/24/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/20/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +54916,62454,56676,Probation,Jones,Dwight,NULL,Male,African-American,02/24/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +44404,62456,56678,PRETRIAL,JULIEN,JEAN,NULL,Male,African-American,01/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +44404,62456,56678,PRETRIAL,JULIEN,JEAN,NULL,Male,African-American,01/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +44404,62456,56678,PRETRIAL,JULIEN,JEAN,NULL,Male,African-American,01/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54921,62463,56685,Probation,SAMPEDRO TORRES,VICTOR,NULL,Male,Hispanic,10/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +54921,62463,56685,Probation,SAMPEDRO TORRES,VICTOR,NULL,Male,Hispanic,10/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +54921,62463,56685,Probation,SAMPEDRO TORRES,VICTOR,NULL,Male,Hispanic,10/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +54910,62442,56665,PRETRIAL,MCINTOSH,DOMINIC,S,Male,African-American,03/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +54910,62442,56665,PRETRIAL,MCINTOSH,DOMINIC,S,Male,African-American,03/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +54910,62442,56665,PRETRIAL,MCINTOSH,DOMINIC,S,Male,African-American,03/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54920,62459,56681,PRETRIAL,Dean,Taneka,NULL,Female,African-American,09/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +54920,62459,56681,PRETRIAL,Dean,Taneka,NULL,Female,African-American,09/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +54920,62459,56681,PRETRIAL,Dean,Taneka,NULL,Female,African-American,09/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +14321,62450,13705,Probation,Morales,Gian,NULL,Male,Caucasian,07/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,Copy,1,0 +14321,62450,13705,Probation,Morales,Gian,NULL,Male,Caucasian,07/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,Copy,1,0 +14321,62450,13705,Probation,Morales,Gian,NULL,Male,Caucasian,07/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +54919,62458,56680,Probation,mckinnis,olden,NULL,Male,African-American,03/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +54919,62458,56680,Probation,mckinnis,olden,NULL,Male,African-American,03/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +54919,62458,56680,Probation,mckinnis,olden,NULL,Male,African-American,03/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54911,62443,56666,PRETRIAL,WOODWARD,JUSTINE,NULL,Female,Caucasian,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +54911,62443,56666,PRETRIAL,WOODWARD,JUSTINE,NULL,Female,Caucasian,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +54911,62443,56666,PRETRIAL,WOODWARD,JUSTINE,NULL,Female,Caucasian,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +12333,62453,56675,PRETRIAL,RODRIGUEZ,VICTOR,NULL,Male,Caucasian,03/13/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +12333,62453,56675,PRETRIAL,RODRIGUEZ,VICTOR,NULL,Male,Caucasian,03/13/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +12333,62453,56675,PRETRIAL,RODRIGUEZ,VICTOR,NULL,Male,Caucasian,03/13/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54912,62445,56668,PRETRIAL,AriasTabima,Carlos,NULL,Male,Caucasian,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +54912,62445,56668,PRETRIAL,AriasTabima,Carlos,NULL,Male,Caucasian,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +54912,62445,56668,PRETRIAL,AriasTabima,Carlos,NULL,Male,Caucasian,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54345,62474,55961,PRETRIAL,Marciniak,Kristen,NULL,Female,Caucasian,04/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,Copy,1,0 +54345,62474,55961,PRETRIAL,Marciniak,Kristen,NULL,Female,Caucasian,04/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/13 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,Copy,1,0 +54345,62474,55961,PRETRIAL,Marciniak,Kristen,NULL,Female,Caucasian,04/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +54948,62492,56710,Probation,Benabdallah,Siham,NULL,Female,Caucasian,04/25/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/21/13 0:00,2,Medium,7,Risk of Violence,-2.63,2,Low,New,1,0 +54948,62492,56710,Probation,Benabdallah,Siham,NULL,Female,Caucasian,04/25/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,New,1,0 +54948,62492,56710,Probation,Benabdallah,Siham,NULL,Female,Caucasian,04/25/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/21/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +46523,62487,56705,PRETRIAL,Saintil,Jimson,NULL,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +46523,62487,56705,PRETRIAL,Saintil,Jimson,NULL,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +46523,62487,56705,PRETRIAL,Saintil,Jimson,NULL,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +25778,62466,24942,DRRD,Frazier,Joshua,NULL,Male,African-American,04/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,Copy,1,0 +25778,62466,24942,DRRD,Frazier,Joshua,NULL,Male,African-American,04/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,2,Medium,8,Risk of Recidivism,0.19,7,Medium,Copy,1,0 +25778,62466,24942,DRRD,Frazier,Joshua,NULL,Male,African-American,04/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +54933,62479,56698,Probation,prasad,sangieve,NULL,Male,Other,03/12/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/21/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +54933,62479,56698,Probation,prasad,sangieve,NULL,Male,Other,03/12/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/21/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +54933,62479,56698,Probation,prasad,sangieve,NULL,Male,Other,03/12/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54927,62471,56692,PRETRIAL,WATTS,CAITLIN,NULL,Female,Caucasian,07/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +54927,62471,56692,PRETRIAL,WATTS,CAITLIN,NULL,Female,Caucasian,07/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +54927,62471,56692,PRETRIAL,WATTS,CAITLIN,NULL,Female,Caucasian,07/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54931,62477,56696,PRETRIAL,Hamilton,Marie,NULL,Female,Caucasian,07/25/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/21/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +54931,62477,56696,PRETRIAL,Hamilton,Marie,NULL,Female,Caucasian,07/25/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/21/13 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +54931,62477,56696,PRETRIAL,Hamilton,Marie,NULL,Female,Caucasian,07/25/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54925,62468,56689,PRETRIAL,Gonzalez,Brenda,NULL,Female,Caucasian,01/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +54925,62468,56689,PRETRIAL,Gonzalez,Brenda,NULL,Female,Caucasian,01/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +54925,62468,56689,PRETRIAL,Gonzalez,Brenda,NULL,Female,Caucasian,01/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54937,62484,56702,PRETRIAL,Arteaga,Yuniel,NULL,Male,Hispanic,01/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +54937,62484,56702,PRETRIAL,Arteaga,Yuniel,NULL,Male,Hispanic,01/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +54937,62484,56702,PRETRIAL,Arteaga,Yuniel,NULL,Male,Hispanic,01/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54930,62475,56695,Probation,Pollock,Kenneth,NULL,Male,Caucasian,05/01/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/21/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +54930,62475,56695,Probation,Pollock,Kenneth,NULL,Male,Caucasian,05/01/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/21/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +54930,62475,56695,Probation,Pollock,Kenneth,NULL,Male,Caucasian,05/01/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54936,62482,56700,Probation,Hood,Yuri,NULL,Male,Caucasian,06/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/21/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +54936,62482,56700,Probation,Hood,Yuri,NULL,Male,Caucasian,06/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/21/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +54936,62482,56700,Probation,Hood,Yuri,NULL,Male,Caucasian,06/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52435,62493,53740,Probation,HAYS,CORTNEY,T,Female,Caucasian,07/14/78,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +52435,62493,53740,Probation,HAYS,CORTNEY,T,Female,Caucasian,07/14/78,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,6,Medium,New,1,0 +52435,62493,53740,Probation,HAYS,CORTNEY,T,Female,Caucasian,07/14/78,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +32881,62494,56711,Probation,Miller,Daniel,NULL,Male,Caucasian,08/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/21/13 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +32881,62494,56711,Probation,Miller,Daniel,NULL,Male,Caucasian,08/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +32881,62494,56711,Probation,Miller,Daniel,NULL,Male,Caucasian,08/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/21/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +41454,62472,56693,PRETRIAL,Dieuveut,Larry,NULL,Male,Other,02/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +41454,62472,56693,PRETRIAL,Dieuveut,Larry,NULL,Male,Other,02/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +41454,62472,56693,PRETRIAL,Dieuveut,Larry,NULL,Male,Other,02/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54928,62473,56694,PRETRIAL,Floyd,Justin,NULL,Male,African-American,01/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +54928,62473,56694,PRETRIAL,Floyd,Justin,NULL,Male,African-American,01/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,4,High,8,Risk of Recidivism,0.44,9,High,New,1,0 +54928,62473,56694,PRETRIAL,Floyd,Justin,NULL,Male,African-American,01/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54935,62480,56699,Probation,Moreno-Delfosse,Maria,Magdelina,Female,Hispanic,09/30/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/21/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +54935,62480,56699,Probation,Moreno-Delfosse,Maria,Magdelina,Female,Hispanic,09/30/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/21/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +54935,62480,56699,Probation,Moreno-Delfosse,Maria,Magdelina,Female,Hispanic,09/30/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54938,62486,56704,Probation,rossi,rafael,NULL,Male,Caucasian,04/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +54938,62486,56704,Probation,rossi,rafael,NULL,Male,Caucasian,04/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +54938,62486,56704,Probation,rossi,rafael,NULL,Male,Caucasian,04/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54947,62491,56709,PRETRIAL,St. Surin,Michelle,NULL,Female,African-American,02/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +54947,62491,56709,PRETRIAL,St. Surin,Michelle,NULL,Female,African-American,02/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +54947,62491,56709,PRETRIAL,St. Surin,Michelle,NULL,Female,African-American,02/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54926,62470,56691,PRETRIAL,Georges,Jean,NULL,Male,Other,05/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/21/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +54926,62470,56691,PRETRIAL,Georges,Jean,NULL,Male,Other,05/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/21/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +54926,62470,56691,PRETRIAL,Georges,Jean,NULL,Male,Other,05/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54940,62488,56706,Probation,MICHEL,JEAN,NULL,Male,African-American,09/15/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/21/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +54940,62488,56706,Probation,MICHEL,JEAN,NULL,Male,African-American,09/15/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/21/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +54940,62488,56706,Probation,MICHEL,JEAN,NULL,Male,African-American,09/15/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54932,62478,56697,PRETRIAL,ingraham,chris,NULL,Male,African-American,12/25/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/21/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +54932,62478,56697,PRETRIAL,ingraham,chris,NULL,Male,African-American,12/25/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/21/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +54932,62478,56697,PRETRIAL,ingraham,chris,NULL,Male,African-American,12/25/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54924,62467,56688,PRETRIAL,Duranfernandez,Christian,NULL,Male,Hispanic,02/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/21/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +54924,62467,56688,PRETRIAL,Duranfernandez,Christian,NULL,Male,Hispanic,02/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/21/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +54924,62467,56688,PRETRIAL,Duranfernandez,Christian,NULL,Male,Hispanic,02/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +20309,62481,19533,Probation,Keel,Joseph,NULL,Male,African-American,04/17/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Significant Other,5/21/13 0:00,4,High,7,Risk of Violence,-0.02,10,High,Copy,1,0 +20309,62481,19533,Probation,Keel,Joseph,NULL,Male,African-American,04/17/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Significant Other,5/21/13 0:00,4,High,8,Risk of Recidivism,1.23,10,High,Copy,1,0 +20309,62481,19533,Probation,Keel,Joseph,NULL,Male,African-American,04/17/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Significant Other,5/21/13 0:00,4,High,18,Risk of Failure to Appear,35,10,High,Copy,1,0 +29716,62485,56703,PRETRIAL,laffiteau,Guillermo,N,Male,Hispanic,05/23/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/21/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +29716,62485,56703,PRETRIAL,laffiteau,Guillermo,N,Male,Hispanic,05/23/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/21/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +29716,62485,56703,PRETRIAL,laffiteau,Guillermo,N,Male,Hispanic,05/23/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +9015,62483,56701,PRETRIAL,Peeples,Alex,NULL,Male,African-American,10/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +9015,62483,56701,PRETRIAL,Peeples,Alex,NULL,Male,African-American,10/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +9015,62483,56701,PRETRIAL,Peeples,Alex,NULL,Male,African-American,10/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +10715,62490,56708,PRETRIAL,Merchant,Ivey,NULL,Male,Caucasian,01/01/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +10715,62490,56708,PRETRIAL,Merchant,Ivey,NULL,Male,Caucasian,01/01/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +10715,62490,56708,PRETRIAL,Merchant,Ivey,NULL,Male,Caucasian,01/01/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +18689,62469,56690,PRETRIAL,Cook,Jamal,Ronnel,Male,African-American,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +18689,62469,56690,PRETRIAL,Cook,Jamal,Ronnel,Male,African-American,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +18689,62469,56690,PRETRIAL,Cook,Jamal,Ronnel,Male,African-American,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54969,62518,56731,Probation,SMERIGLIO,MARIANO,WILLIAM,Male,Caucasian,04/18/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +54969,62518,56731,Probation,SMERIGLIO,MARIANO,WILLIAM,Male,Caucasian,04/18/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +54969,62518,56731,Probation,SMERIGLIO,MARIANO,WILLIAM,Male,Caucasian,04/18/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +54970,62520,56732,Probation,Heran,CHRISTIAN,NULL,Male,Hispanic,04/14/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +54970,62520,56732,Probation,Heran,CHRISTIAN,NULL,Male,Hispanic,04/14/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +54970,62520,56732,Probation,Heran,CHRISTIAN,NULL,Male,Hispanic,04/14/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54987,62541,56751,PRETRIAL,Hicks,Herbert,Anthony,Male,African-American,11/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +54987,62541,56751,PRETRIAL,Hicks,Herbert,Anthony,Male,African-American,11/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +54987,62541,56751,PRETRIAL,Hicks,Herbert,Anthony,Male,African-American,11/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54990,62548,56755,Probation,Thompson,James,NULL,Male,Caucasian,06/08/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +54990,62548,56755,Probation,Thompson,James,NULL,Male,Caucasian,06/08/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +54990,62548,56755,Probation,Thompson,James,NULL,Male,Caucasian,06/08/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54954,62497,56713,PRETRIAL,Harris,Donarth,Keith,Male,Other,12/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +54954,62497,56713,PRETRIAL,Harris,Donarth,Keith,Male,Other,12/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +54954,62497,56713,PRETRIAL,Harris,Donarth,Keith,Male,Other,12/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54414,62511,56052,PRETRIAL,Sutton,Kayla,NULL,Female,Caucasian,11/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,Copy,1,0 +54414,62511,56052,PRETRIAL,Sutton,Kayla,NULL,Female,Caucasian,11/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,Copy,1,0 +54414,62511,56052,PRETRIAL,Sutton,Kayla,NULL,Female,Caucasian,11/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +54957,62502,56716,PRETRIAL,Lustig,Corey,Alexi,Male,Caucasian,03/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +54957,62502,56716,PRETRIAL,Lustig,Corey,Alexi,Male,Caucasian,03/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +54957,62502,56716,PRETRIAL,Lustig,Corey,Alexi,Male,Caucasian,03/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54984,62536,56746,Probation,therrell,Kevin,John,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/13 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +54984,62536,56746,Probation,therrell,Kevin,John,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +54984,62536,56746,Probation,therrell,Kevin,John,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54995,62553,56760,PRETRIAL,Aviles,Julio,NULL,Male,Hispanic,07/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/22/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +54995,62553,56760,PRETRIAL,Aviles,Julio,NULL,Male,Hispanic,07/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/22/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +54995,62553,56760,PRETRIAL,Aviles,Julio,NULL,Male,Hispanic,07/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54972,62523,56735,Probation,Seoane,Kevin,NULL,Male,Hispanic,08/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,New,1,0 +54972,62523,56735,Probation,Seoane,Kevin,NULL,Male,Hispanic,08/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +54972,62523,56735,Probation,Seoane,Kevin,NULL,Male,Hispanic,08/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54982,62532,56743,DRRD,Bradley,Krystal,NULL,Female,Caucasian,09/05/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +54982,62532,56743,DRRD,Bradley,Krystal,NULL,Female,Caucasian,09/05/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +54982,62532,56743,DRRD,Bradley,Krystal,NULL,Female,Caucasian,09/05/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,New,1,0 +54998,62557,56763,Probation,Koscak,James,NULL,Male,Caucasian,05/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +54998,62557,56763,Probation,Koscak,James,NULL,Male,Caucasian,05/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,New,1,0 +54998,62557,56763,Probation,Koscak,James,NULL,Male,Caucasian,05/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +54961,62506,56720,PRETRIAL,Figueiredo,Robson,NULL,Male,Hispanic,06/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +54961,62506,56720,PRETRIAL,Figueiredo,Robson,NULL,Male,Hispanic,06/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +54961,62506,56720,PRETRIAL,Figueiredo,Robson,NULL,Male,Hispanic,06/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54976,62527,56739,Probation,taylor,brandy,NULL,Male,Caucasian,10/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +54976,62527,56739,Probation,taylor,brandy,NULL,Male,Caucasian,10/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +54976,62527,56739,Probation,taylor,brandy,NULL,Male,Caucasian,10/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54953,62496,56712,PRETRIAL,Brown,Bryant,NULL,Male,African-American,03/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +54953,62496,56712,PRETRIAL,Brown,Bryant,NULL,Male,African-American,03/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +54953,62496,56712,PRETRIAL,Brown,Bryant,NULL,Male,African-American,03/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54964,62509,56723,PRETRIAL,Roae,Shalev,NULL,Male,Caucasian,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/22/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +54964,62509,56723,PRETRIAL,Roae,Shalev,NULL,Male,Caucasian,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +54964,62509,56723,PRETRIAL,Roae,Shalev,NULL,Male,Caucasian,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54956,62499,56715,PRETRIAL,Smith,Kamal,NULL,Male,African-American,05/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +54956,62499,56715,PRETRIAL,Smith,Kamal,NULL,Male,African-American,05/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,4,High,8,Risk of Recidivism,0.38,9,High,New,1,0 +54956,62499,56715,PRETRIAL,Smith,Kamal,NULL,Male,African-American,05/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54968,62517,56730,PRETRIAL,Molony,Sara,NULL,Male,Caucasian,07/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +54968,62517,56730,PRETRIAL,Molony,Sara,NULL,Male,Caucasian,07/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +54968,62517,56730,PRETRIAL,Molony,Sara,NULL,Male,Caucasian,07/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54997,62556,56762,Probation,Isaza,Maria,NULL,Female,Caucasian,04/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +54997,62556,56762,Probation,Isaza,Maria,NULL,Female,Caucasian,04/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +54997,62556,56762,Probation,Isaza,Maria,NULL,Female,Caucasian,04/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54959,62504,56718,PRETRIAL,Brown,Emmanuel,Louis,Male,African-American,08/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.59,2,Low,New,1,0 +54959,62504,56718,PRETRIAL,Brown,Emmanuel,Louis,Male,African-American,08/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +54959,62504,56718,PRETRIAL,Brown,Emmanuel,Louis,Male,African-American,08/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +36291,62538,56748,Probation,Romero,Waldo,NULL,Male,Caucasian,04/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +36291,62538,56748,Probation,Romero,Waldo,NULL,Male,Caucasian,04/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +36291,62538,56748,Probation,Romero,Waldo,NULL,Male,Caucasian,04/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54993,62551,56758,Probation,Bryan,Michael,NULL,Male,Caucasian,03/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +54993,62551,56758,Probation,Bryan,Michael,NULL,Male,Caucasian,03/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +54993,62551,56758,Probation,Bryan,Michael,NULL,Male,Caucasian,03/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,36,10,High,New,1,0 +54975,62525,56737,PRETRIAL,Waun,Kristen,a,Female,Caucasian,04/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +54975,62525,56737,PRETRIAL,Waun,Kristen,a,Female,Caucasian,04/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +54975,62525,56737,PRETRIAL,Waun,Kristen,a,Female,Caucasian,04/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54979,62530,56741,Probation,Johnson,Jonathan,NULL,Male,African-American,07/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,New,1,0 +54979,62530,56741,Probation,Johnson,Jonathan,NULL,Male,African-American,07/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +54979,62530,56741,Probation,Johnson,Jonathan,NULL,Male,African-American,07/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +13379,62501,12788,PRETRIAL,Feast,Benjamin,NULL,Male,African-American,10/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/22/13 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,Copy,1,0 +13379,62501,12788,PRETRIAL,Feast,Benjamin,NULL,Male,African-American,10/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,Copy,1,0 +13379,62501,12788,PRETRIAL,Feast,Benjamin,NULL,Male,African-American,10/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/22/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +54962,62507,56721,PRETRIAL,Fleming,Nicholas,NULL,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +54962,62507,56721,PRETRIAL,Fleming,Nicholas,NULL,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +54962,62507,56721,PRETRIAL,Fleming,Nicholas,NULL,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +46288,62514,56727,PRETRIAL,JORGENSEN,EDWARD,NULL,Male,Caucasian,07/14/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +46288,62514,56727,PRETRIAL,JORGENSEN,EDWARD,NULL,Male,Caucasian,07/14/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +46288,62514,56727,PRETRIAL,JORGENSEN,EDWARD,NULL,Male,Caucasian,07/14/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54967,62515,56728,Probation,Cayo,Carmen,tatiana,Female,Hispanic,09/03/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,5/22/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +54967,62515,56728,Probation,Cayo,Carmen,tatiana,Female,Hispanic,09/03/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +54967,62515,56728,Probation,Cayo,Carmen,tatiana,Female,Hispanic,09/03/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54971,62522,56734,Probation,Gago,Brian,NULL,Male,Hispanic,06/24/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +54971,62522,56734,Probation,Gago,Brian,NULL,Male,Hispanic,06/24/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +54971,62522,56734,Probation,Gago,Brian,NULL,Male,Hispanic,06/24/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54989,62543,56753,PRETRIAL,Brackney,Michael,Scott,Male,Caucasian,03/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +54989,62543,56753,PRETRIAL,Brackney,Michael,Scott,Male,Caucasian,03/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +54989,62543,56753,PRETRIAL,Brackney,Michael,Scott,Male,Caucasian,03/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54960,62505,56719,PRETRIAL,Norman,Jayson,Patrick,Male,Caucasian,09/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +54960,62505,56719,PRETRIAL,Norman,Jayson,Patrick,Male,Caucasian,09/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +54960,62505,56719,PRETRIAL,Norman,Jayson,Patrick,Male,Caucasian,09/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54958,62503,56717,PRETRIAL,Wiggins,Schante,NULL,Female,African-American,02/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.37,3,Low,New,1,0 +54958,62503,56717,PRETRIAL,Wiggins,Schante,NULL,Female,African-American,02/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,New,1,0 +54958,62503,56717,PRETRIAL,Wiggins,Schante,NULL,Female,African-American,02/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54966,62512,56725,Probation,Zambrano,Cristhian,NULL,Male,Caucasian,05/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +54966,62512,56725,Probation,Zambrano,Cristhian,NULL,Male,Caucasian,05/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +54966,62512,56725,Probation,Zambrano,Cristhian,NULL,Male,Caucasian,05/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54977,62526,56738,PRETRIAL,Smith,Travis,NULL,Male,African-American,06/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +54977,62526,56738,PRETRIAL,Smith,Travis,NULL,Male,African-American,06/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +54977,62526,56738,PRETRIAL,Smith,Travis,NULL,Male,African-American,06/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +46794,62533,47238,PRETRIAL,Murdock,Lorenzo,J.,Male,Other,11/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +46794,62533,47238,PRETRIAL,Murdock,Lorenzo,J.,Male,Other,11/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,5,Medium,Copy,1,0 +46794,62533,47238,PRETRIAL,Murdock,Lorenzo,J.,Male,Other,11/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +49805,62540,56750,PRETRIAL,Nestor,Bertin,NULL,Male,Hispanic,06/06/72,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,5/22/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +49805,62540,56750,PRETRIAL,Nestor,Bertin,NULL,Male,Hispanic,06/06/72,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +49805,62540,56750,PRETRIAL,Nestor,Bertin,NULL,Male,Hispanic,06/06/72,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +7329,62547,30015,PRETRIAL,VENTURA,JAQUELINE,NULL,Female,Caucasian,05/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,2,Medium,7,Risk of Violence,-2.65,2,Low,Copy,1,0 +7329,62547,30015,PRETRIAL,VENTURA,JAQUELINE,NULL,Female,Caucasian,05/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,Copy,1,0 +7329,62547,30015,PRETRIAL,VENTURA,JAQUELINE,NULL,Female,Caucasian,05/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +54955,62498,56714,PRETRIAL,Sharp,Earl,Raymond,Male,Caucasian,02/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/22/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +54955,62498,56714,PRETRIAL,Sharp,Earl,Raymond,Male,Caucasian,02/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +54955,62498,56714,PRETRIAL,Sharp,Earl,Raymond,Male,Caucasian,02/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54965,62510,56724,PRETRIAL,Pauda,Gilberto,NULL,Male,Caucasian,01/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +54965,62510,56724,PRETRIAL,Pauda,Gilberto,NULL,Male,Caucasian,01/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +54965,62510,56724,PRETRIAL,Pauda,Gilberto,NULL,Male,Caucasian,01/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54978,62528,56740,Probation,Whimley,Shauntavia,Nekisha,Female,African-American,07/04/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +54978,62528,56740,Probation,Whimley,Shauntavia,Nekisha,Female,African-American,07/04/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +54978,62528,56740,Probation,Whimley,Shauntavia,Nekisha,Female,African-American,07/04/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54973,62524,56736,Probation,ross,rebecca,NULL,Female,Caucasian,10/13/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +54973,62524,56736,Probation,ross,rebecca,NULL,Female,Caucasian,10/13/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +54973,62524,56736,Probation,ross,rebecca,NULL,Female,Caucasian,10/13/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54991,62549,56756,Probation,ramirezbain,joan,marie,Female,Hispanic,04/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/22/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +54991,62549,56756,Probation,ramirezbain,joan,marie,Female,Hispanic,04/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +54991,62549,56756,Probation,ramirezbain,joan,marie,Female,Hispanic,04/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54985,62537,56747,PRETRIAL,Greenaway,Alesia,NULL,Female,African-American,09/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +54985,62537,56747,PRETRIAL,Greenaway,Alesia,NULL,Female,African-American,09/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +54985,62537,56747,PRETRIAL,Greenaway,Alesia,NULL,Female,African-American,09/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54994,62552,56759,Probation,Singh,Rajendra,NULL,Male,Other,04/10/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/22/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +54994,62552,56759,Probation,Singh,Rajendra,NULL,Male,Other,04/10/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +54994,62552,56759,Probation,Singh,Rajendra,NULL,Male,Other,04/10/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +40883,62516,56729,PRETRIAL,Chisholm,Brandon,NULL,Male,Caucasian,02/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +40883,62516,56729,PRETRIAL,Chisholm,Brandon,NULL,Male,Caucasian,02/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +40883,62516,56729,PRETRIAL,Chisholm,Brandon,NULL,Male,Caucasian,02/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54992,62550,56757,Probation,torres,jose,NULL,Male,Caucasian,09/09/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +54992,62550,56757,Probation,torres,jose,NULL,Male,Caucasian,09/09/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +54992,62550,56757,Probation,torres,jose,NULL,Male,Caucasian,09/09/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +49551,62529,50415,PRETRIAL,Dalton,Alexandria,NULL,Female,Caucasian,12/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,Copy,1,0 +49551,62529,50415,PRETRIAL,Dalton,Alexandria,NULL,Female,Caucasian,12/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,4,High,8,Risk of Recidivism,0.55,10,High,Copy,1,0 +49551,62529,50415,PRETRIAL,Dalton,Alexandria,NULL,Female,Caucasian,12/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,4,High,18,Risk of Failure to Appear,29,9,High,Copy,1,0 +54988,62544,56754,Probation,Williams,Liliana,NULL,Female,Caucasian,02/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +54988,62544,56754,Probation,Williams,Liliana,NULL,Female,Caucasian,02/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +54988,62544,56754,Probation,Williams,Liliana,NULL,Female,Caucasian,02/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54963,62508,56722,PRETRIAL,Taylor,Glen,Matthew,Male,African-American,03/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +54963,62508,56722,PRETRIAL,Taylor,Glen,Matthew,Male,African-American,03/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +54963,62508,56722,PRETRIAL,Taylor,Glen,Matthew,Male,African-American,03/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54999,62558,56764,PRETRIAL,Telfort,John,NULL,Male,African-American,07/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,New,1,0 +54999,62558,56764,PRETRIAL,Telfort,John,NULL,Male,African-American,07/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +54999,62558,56764,PRETRIAL,Telfort,John,NULL,Male,African-American,07/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +34175,62500,33321,PRETRIAL,Obas,Kevon,NULL,Male,African-American,03/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,4,High,7,Risk of Violence,-0.97,9,High,Copy,1,0 +34175,62500,33321,PRETRIAL,Obas,Kevon,NULL,Male,African-American,03/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,4,High,8,Risk of Recidivism,0.23,8,High,Copy,1,0 +34175,62500,33321,PRETRIAL,Obas,Kevon,NULL,Male,African-American,03/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +54996,62555,56761,PRETRIAL,GONZALEZ,ARLENE,NULL,Female,Hispanic,12/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +54996,62555,56761,PRETRIAL,GONZALEZ,ARLENE,NULL,Female,Hispanic,12/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +54996,62555,56761,PRETRIAL,GONZALEZ,ARLENE,NULL,Female,Hispanic,12/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +30961,62521,56733,Probation,hunter,otis,NULL,Male,African-American,05/31/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.1,1,Low,New,1,0 +30961,62521,56733,Probation,hunter,otis,NULL,Male,African-American,05/31/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +30961,62521,56733,Probation,hunter,otis,NULL,Male,African-American,05/31/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54983,62534,56744,Probation,Green,Jasmine,NULL,Female,African-American,07/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +54983,62534,56744,Probation,Green,Jasmine,NULL,Female,African-American,07/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +54983,62534,56744,Probation,Green,Jasmine,NULL,Female,African-American,07/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +38601,62513,56726,PRETRIAL,Williams,Cassandra,NULL,Female,Caucasian,12/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +38601,62513,56726,PRETRIAL,Williams,Cassandra,NULL,Female,Caucasian,12/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +38601,62513,56726,PRETRIAL,Williams,Cassandra,NULL,Female,Caucasian,12/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +26144,62495,25242,Probation,foskin,suniel,NULL,Male,African-American,01/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,Copy,1,0 +26144,62495,25242,Probation,foskin,suniel,NULL,Male,African-American,01/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,Copy,1,0 +26144,62495,25242,Probation,foskin,suniel,NULL,Male,African-American,01/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +55000,62560,56766,PRETRIAL,SCOTT,CEDRIC,THEOPOLUS,Male,African-American,04/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/23/13 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +55000,62560,56766,PRETRIAL,SCOTT,CEDRIC,THEOPOLUS,Male,African-American,04/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/23/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +55000,62560,56766,PRETRIAL,SCOTT,CEDRIC,THEOPOLUS,Male,African-American,04/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/23/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55002,62563,56768,PRETRIAL,Hall,Freddy,NULL,Male,African-American,12/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +55002,62563,56768,PRETRIAL,Hall,Freddy,NULL,Male,African-American,12/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +55002,62563,56768,PRETRIAL,Hall,Freddy,NULL,Male,African-American,12/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55034,62610,56810,Probation,DUCRAN,CHAKA,NULL,Male,African-American,10/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +55034,62610,56810,Probation,DUCRAN,CHAKA,NULL,Male,African-American,10/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +55034,62610,56810,Probation,DUCRAN,CHAKA,NULL,Male,African-American,10/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +1225,62581,56784,PRETRIAL,sthilaire,stanley,NULL,Male,African-American,03/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +1225,62581,56784,PRETRIAL,sthilaire,stanley,NULL,Male,African-American,03/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +1225,62581,56784,PRETRIAL,sthilaire,stanley,NULL,Male,African-American,03/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +38904,62568,56771,PRETRIAL,CRIANZA,CHRISTINA,NULL,Male,Caucasian,08/17/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +38904,62568,56771,PRETRIAL,CRIANZA,CHRISTINA,NULL,Male,Caucasian,08/17/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +38904,62568,56771,PRETRIAL,CRIANZA,CHRISTINA,NULL,Male,Caucasian,08/17/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55029,62602,56804,Probation,Kempinwhite,Ryan,NULL,Male,Caucasian,12/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +55029,62602,56804,Probation,Kempinwhite,Ryan,NULL,Male,Caucasian,12/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +55029,62602,56804,Probation,Kempinwhite,Ryan,NULL,Male,Caucasian,12/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +46469,62589,56792,PRETRIAL,Canales,Johnny,NULL,Male,Caucasian,06/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/23/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +46469,62589,56792,PRETRIAL,Canales,Johnny,NULL,Male,Caucasian,06/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +46469,62589,56792,PRETRIAL,Canales,Johnny,NULL,Male,Caucasian,06/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55003,62565,56769,PRETRIAL,seymore,leroy,marcus,Male,African-American,08/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/23/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +55003,62565,56769,PRETRIAL,seymore,leroy,marcus,Male,African-American,08/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +55003,62565,56769,PRETRIAL,seymore,leroy,marcus,Male,African-American,08/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +25679,62615,56814,PRETRIAL,MANOSALVA,LIZANDRO,NULL,Male,Caucasian,05/18/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +25679,62615,56814,PRETRIAL,MANOSALVA,LIZANDRO,NULL,Male,Caucasian,05/18/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +25679,62615,56814,PRETRIAL,MANOSALVA,LIZANDRO,NULL,Male,Caucasian,05/18/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55013,62579,56782,Probation,neira,franklin,NULL,Male,Hispanic,11/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/23/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +55013,62579,56782,Probation,neira,franklin,NULL,Male,Hispanic,11/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +55013,62579,56782,Probation,neira,franklin,NULL,Male,Hispanic,11/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55023,62594,56796,Probation,Neto,Michelle,NULL,Female,African-American,08/10/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +55023,62594,56796,Probation,Neto,Michelle,NULL,Female,African-American,08/10/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +55023,62594,56796,Probation,Neto,Michelle,NULL,Female,African-American,08/10/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55008,62573,56776,PRETRIAL,RASCO,ALFREDO,FERNANDO,Male,Caucasian,03/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +55008,62573,56776,PRETRIAL,RASCO,ALFREDO,FERNANDO,Male,Caucasian,03/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +55008,62573,56776,PRETRIAL,RASCO,ALFREDO,FERNANDO,Male,Caucasian,03/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55032,62607,56807,Probation,Crosby,Chimere,NULL,Female,African-American,06/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +55032,62607,56807,Probation,Crosby,Chimere,NULL,Female,African-American,06/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,9,High,New,1,0 +55032,62607,56807,Probation,Crosby,Chimere,NULL,Female,African-American,06/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55006,62571,56774,PRETRIAL,Hill,Marvin,NULL,Male,African-American,02/11/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +55006,62571,56774,PRETRIAL,Hill,Marvin,NULL,Male,African-American,02/11/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +55006,62571,56774,PRETRIAL,Hill,Marvin,NULL,Male,African-American,02/11/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55018,62586,56789,Probation,Perez,Tammy,Lynn,Female,Hispanic,08/15/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/23/13 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +55018,62586,56789,Probation,Perez,Tammy,Lynn,Female,Hispanic,08/15/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +55018,62586,56789,Probation,Perez,Tammy,Lynn,Female,Hispanic,08/15/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +7466,62566,7058,PRETRIAL,SCOTT,MARIE,ANTOINETTE,Female,African-American,05/18/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/23/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,Copy,1,0 +7466,62566,7058,PRETRIAL,SCOTT,MARIE,ANTOINETTE,Female,African-American,05/18/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,Copy,1,0 +7466,62566,7058,PRETRIAL,SCOTT,MARIE,ANTOINETTE,Female,African-American,05/18/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +55027,62600,56802,Probation,CHARLES,JAMESLEY,NULL,Male,African-American,02/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +55027,62600,56802,Probation,CHARLES,JAMESLEY,NULL,Male,African-American,02/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +55027,62600,56802,Probation,CHARLES,JAMESLEY,NULL,Male,African-American,02/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51612,62570,56773,PRETRIAL,MOORE,ZACHARY,NULL,Male,Caucasian,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +51612,62570,56773,PRETRIAL,MOORE,ZACHARY,NULL,Male,Caucasian,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +51612,62570,56773,PRETRIAL,MOORE,ZACHARY,NULL,Male,Caucasian,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55019,62587,56790,Probation,NGUYEN,LUONG,VAN,Male,Asian,05/06/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/23/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +55019,62587,56790,Probation,NGUYEN,LUONG,VAN,Male,Asian,05/06/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +55019,62587,56790,Probation,NGUYEN,LUONG,VAN,Male,Asian,05/06/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52232,62561,53503,PRETRIAL,Turello,Richard,NULL,Male,Caucasian,11/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/23/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,Copy,1,0 +52232,62561,53503,PRETRIAL,Turello,Richard,NULL,Male,Caucasian,11/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,Copy,1,0 +52232,62561,53503,PRETRIAL,Turello,Richard,NULL,Male,Caucasian,11/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +24998,62612,56812,PRETRIAL,RODGERS,DESIREE,NULL,Female,Caucasian,06/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,New,1,0 +24998,62612,56812,PRETRIAL,RODGERS,DESIREE,NULL,Female,Caucasian,06/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,8,High,New,1,0 +24998,62612,56812,PRETRIAL,RODGERS,DESIREE,NULL,Female,Caucasian,06/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +55010,62575,56778,PRETRIAL,CLARK,LISA,NULL,Female,Caucasian,08/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +55010,62575,56778,PRETRIAL,CLARK,LISA,NULL,Female,Caucasian,08/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +55010,62575,56778,PRETRIAL,CLARK,LISA,NULL,Female,Caucasian,08/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +38066,62582,56785,PRETRIAL,Rodriguez,Jim,NULL,Male,Hispanic,07/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +38066,62582,56785,PRETRIAL,Rodriguez,Jim,NULL,Male,Hispanic,07/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +38066,62582,56785,PRETRIAL,Rodriguez,Jim,NULL,Male,Hispanic,07/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55015,62584,56787,Probation,IBRAHIM,OMAR,NULL,Male,Hispanic,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +55015,62584,56787,Probation,IBRAHIM,OMAR,NULL,Male,Hispanic,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +55015,62584,56787,Probation,IBRAHIM,OMAR,NULL,Male,Hispanic,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55031,62605,56805,PRETRIAL,Byrnehenry,Monica,NULL,Female,Caucasian,02/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,Copy,1,0 +55031,62605,56805,PRETRIAL,Byrnehenry,Monica,NULL,Female,Caucasian,02/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,Copy,1,0 +55031,62605,56805,PRETRIAL,Byrnehenry,Monica,NULL,Female,Caucasian,02/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +55022,62593,56795,Probation,HORRABIN,JAMES,NULL,Male,African-American,09/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +55022,62593,56795,Probation,HORRABIN,JAMES,NULL,Male,African-American,09/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +55022,62593,56795,Probation,HORRABIN,JAMES,NULL,Male,African-American,09/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55007,62572,56775,PRETRIAL,White,Marshal,Wesley,Male,Caucasian,02/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +55007,62572,56775,PRETRIAL,White,Marshal,Wesley,Male,Caucasian,02/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +55007,62572,56775,PRETRIAL,White,Marshal,Wesley,Male,Caucasian,02/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55033,62608,56808,Probation,carbone,anthony,NULL,Male,Caucasian,10/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +55033,62608,56808,Probation,carbone,anthony,NULL,Male,Caucasian,10/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +55033,62608,56808,Probation,carbone,anthony,NULL,Male,Caucasian,10/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +39947,62580,56783,PRETRIAL,Hallam,Lora,NULL,Female,Caucasian,09/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +39947,62580,56783,PRETRIAL,Hallam,Lora,NULL,Female,Caucasian,09/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +39947,62580,56783,PRETRIAL,Hallam,Lora,NULL,Female,Caucasian,09/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +27086,62609,56809,PRETRIAL,SCHWARTZMAN,MICHAEL,NULL,Male,Caucasian,05/21/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +27086,62609,56809,PRETRIAL,SCHWARTZMAN,MICHAEL,NULL,Male,Caucasian,05/21/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +27086,62609,56809,PRETRIAL,SCHWARTZMAN,MICHAEL,NULL,Male,Caucasian,05/21/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55020,62588,56791,Probation,Cruz,Joseph,NULL,Male,Hispanic,04/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +55020,62588,56791,Probation,Cruz,Joseph,NULL,Male,Hispanic,04/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +55020,62588,56791,Probation,Cruz,Joseph,NULL,Male,Hispanic,04/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +29781,31485,28773,PRETRIAL,ELMA,JEAN,C,Male,African-American,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,4,High,7,Risk of Violence,-0.55,10,High,New,1,0 +29781,31485,28773,PRETRIAL,ELMA,JEAN,C,Male,African-American,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +29781,31485,28773,PRETRIAL,ELMA,JEAN,C,Male,African-American,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +3176,62564,17823,PRETRIAL,STEPHENSON,MICHAEL,NULL,Male,African-American,07/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/23/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,Copy,1,0 +3176,62564,17823,PRETRIAL,STEPHENSON,MICHAEL,NULL,Male,African-American,07/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +3176,62564,17823,PRETRIAL,STEPHENSON,MICHAEL,NULL,Male,African-American,07/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +55017,62585,56788,Probation,Urburtis,Erin,NULL,Female,Caucasian,09/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +55017,62585,56788,Probation,Urburtis,Erin,NULL,Female,Caucasian,09/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +55017,62585,56788,Probation,Urburtis,Erin,NULL,Female,Caucasian,09/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55004,62567,56770,PRETRIAL,Mccall,Dandre,S,Male,Other,07/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +55004,62567,56770,PRETRIAL,Mccall,Dandre,S,Male,Other,07/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +55004,62567,56770,PRETRIAL,Mccall,Dandre,S,Male,Other,07/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55031,62606,56805,PRETRIAL,Byrnehenry,Monica,NULL,Female,Caucasian,02/06/62,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,Copy,1,0 +55031,62606,56805,PRETRIAL,Byrnehenry,Monica,NULL,Female,Caucasian,02/06/62,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,Copy,1,0 +55031,62606,56805,PRETRIAL,Byrnehenry,Monica,NULL,Female,Caucasian,02/06/62,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +28533,62559,56765,PRETRIAL,MCDONALD,TERRYANN,NULL,Female,Other,12/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +28533,62559,56765,PRETRIAL,MCDONALD,TERRYANN,NULL,Female,Other,12/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +28533,62559,56765,PRETRIAL,MCDONALD,TERRYANN,NULL,Female,Other,12/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55012,62577,56780,PRETRIAL,James,Anthony,Lavon,Male,African-American,12/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/23/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +55012,62577,56780,PRETRIAL,James,Anthony,Lavon,Male,African-American,12/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +55012,62577,56780,PRETRIAL,James,Anthony,Lavon,Male,African-American,12/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30711,62578,56781,PRETRIAL,Fowler,Kala,NULL,Female,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +30711,62578,56781,PRETRIAL,Fowler,Kala,NULL,Female,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,4,High,8,Risk of Recidivism,0.61,10,High,New,1,0 +30711,62578,56781,PRETRIAL,Fowler,Kala,NULL,Female,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55024,62595,56797,Probation,Martinez,Carlos,NULL,Male,Hispanic,09/01/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +55024,62595,56797,Probation,Martinez,Carlos,NULL,Male,Hispanic,09/01/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +55024,62595,56797,Probation,Martinez,Carlos,NULL,Male,Hispanic,09/01/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +40810,62613,56813,PRETRIAL,Ellis,Robert,NULL,Male,African-American,09/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +40810,62613,56813,PRETRIAL,Ellis,Robert,NULL,Male,African-American,09/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +40810,62613,56813,PRETRIAL,Ellis,Robert,NULL,Male,African-American,09/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55009,62574,56777,PRETRIAL,KUZA,PAUL,ALEX,Male,Caucasian,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,4,High,7,Risk of Violence,-1.07,8,High,New,1,0 +55009,62574,56777,PRETRIAL,KUZA,PAUL,ALEX,Male,Caucasian,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +55009,62574,56777,PRETRIAL,KUZA,PAUL,ALEX,Male,Caucasian,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44970,62599,56801,PRETRIAL,Blackwood,Alshey,NULL,Female,African-American,01/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +44970,62599,56801,PRETRIAL,Blackwood,Alshey,NULL,Female,African-American,01/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,8,High,New,1,0 +44970,62599,56801,PRETRIAL,Blackwood,Alshey,NULL,Female,African-American,01/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55030,62604,56806,Probation,habe,christopher,NULL,Male,Caucasian,03/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/23/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +55030,62604,56806,Probation,habe,christopher,NULL,Male,Caucasian,03/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +55030,62604,56806,Probation,habe,christopher,NULL,Male,Caucasian,03/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55001,62562,56767,PRETRIAL,Schmiedeknicht,Eli,NULL,Male,Caucasian,03/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +55001,62562,56767,PRETRIAL,Schmiedeknicht,Eli,NULL,Male,Caucasian,03/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +55001,62562,56767,PRETRIAL,Schmiedeknicht,Eli,NULL,Male,Caucasian,03/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55011,62576,56779,PRETRIAL,Inman,Brenda,NULL,Female,Caucasian,06/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,New,1,0 +55011,62576,56779,PRETRIAL,Inman,Brenda,NULL,Female,Caucasian,06/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,7,Medium,New,1,0 +55011,62576,56779,PRETRIAL,Inman,Brenda,NULL,Female,Caucasian,06/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,New,1,0 +55035,62611,56811,Probation,Dookeran,Himraj,NULL,Male,Other,07/07/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/23/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +55035,62611,56811,Probation,Dookeran,Himraj,NULL,Male,Other,07/07/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/23/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +55035,62611,56811,Probation,Dookeran,Himraj,NULL,Male,Other,07/07/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55014,62583,56786,Probation,Gomez,Mike,NULL,Male,Hispanic,11/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.34,3,Low,New,1,0 +55014,62583,56786,Probation,Gomez,Mike,NULL,Male,Hispanic,11/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +55014,62583,56786,Probation,Gomez,Mike,NULL,Male,Hispanic,11/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55016,62590,56793,Broward County,Newson,Anthony,NULL,Male,African-American,04/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +55016,62590,56793,Broward County,Newson,Anthony,NULL,Male,African-American,04/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +55016,62590,56793,Broward County,Newson,Anthony,NULL,Male,African-American,04/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55025,62597,56799,Probation,Charles,Jimmy,NULL,Male,African-American,08/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +55025,62597,56799,Probation,Charles,Jimmy,NULL,Male,African-American,08/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +55025,62597,56799,Probation,Charles,Jimmy,NULL,Male,African-American,08/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +35351,62341,56575,PRETRIAL,White,Anthony,NULL,Male,African-American,07/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.13,8,High,New,1,0 +35351,62341,56575,PRETRIAL,White,Anthony,NULL,Male,African-American,07/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +35351,62341,56575,PRETRIAL,White,Anthony,NULL,Male,African-American,07/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55005,62569,56772,PRETRIAL,Estevez,Jane,NULL,Female,Caucasian,02/06/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.41,3,Low,New,1,0 +55005,62569,56772,PRETRIAL,Estevez,Jane,NULL,Female,Caucasian,02/06/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +55005,62569,56772,PRETRIAL,Estevez,Jane,NULL,Female,Caucasian,02/06/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +55038,62618,56816,PRETRIAL,Conille,Wilfred,NULL,Male,African-American,04/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +55038,62618,56816,PRETRIAL,Conille,Wilfred,NULL,Male,African-American,04/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +55038,62618,56816,PRETRIAL,Conille,Wilfred,NULL,Male,African-American,04/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55039,62620,56818,PRETRIAL,Farraj,Eihab,NULL,Male,Arabic,08/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +55039,62620,56818,PRETRIAL,Farraj,Eihab,NULL,Male,Arabic,08/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +55039,62620,56818,PRETRIAL,Farraj,Eihab,NULL,Male,Arabic,08/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55056,62639,56836,PRETRIAL,Billie,Allen,NULL,Male,Native American,02/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +55056,62639,56836,PRETRIAL,Billie,Allen,NULL,Male,Native American,02/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +55056,62639,56836,PRETRIAL,Billie,Allen,NULL,Male,Native American,02/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55058,62641,56838,PRETRIAL,Santos,Alex,NULL,Male,Hispanic,05/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +55058,62641,56838,PRETRIAL,Santos,Alex,NULL,Male,Hispanic,05/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +55058,62641,56838,PRETRIAL,Santos,Alex,NULL,Male,Hispanic,05/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55062,62648,56844,Probation,Mack,Preston,NULL,Male,African-American,01/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/24/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +55062,62648,56844,Probation,Mack,Preston,NULL,Male,African-American,01/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/24/13 0:00,4,High,8,Risk of Recidivism,0.31,9,High,New,1,0 +55062,62648,56844,Probation,Mack,Preston,NULL,Male,African-American,01/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/24/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55044,62625,56823,PRETRIAL,Maxwell,Yanique,NULL,Male,African-American,10/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +55044,62625,56823,PRETRIAL,Maxwell,Yanique,NULL,Male,African-American,10/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +55044,62625,56823,PRETRIAL,Maxwell,Yanique,NULL,Male,African-American,10/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +8763,62630,56827,PRETRIAL,MARION,CHRISTOPHER,NULL,Male,African-American,04/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/24/13 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +8763,62630,56827,PRETRIAL,MARION,CHRISTOPHER,NULL,Male,African-American,04/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/24/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +8763,62630,56827,PRETRIAL,MARION,CHRISTOPHER,NULL,Male,African-American,04/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/24/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55052,62634,56831,Probation,mazard,nancy,NULL,Female,African-American,11/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/24/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +55052,62634,56831,Probation,mazard,nancy,NULL,Female,African-American,11/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/24/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +55052,62634,56831,Probation,mazard,nancy,NULL,Female,African-American,11/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55061,62646,56842,Probation,leigh,marcy,NULL,Female,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.56,2,Low,New,1,0 +55061,62646,56842,Probation,leigh,marcy,NULL,Female,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +55061,62646,56842,Probation,leigh,marcy,NULL,Female,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +55045,62627,56824,PRETRIAL,Menos,Mario,NULL,Male,Other,12/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +55045,62627,56824,PRETRIAL,Menos,Mario,NULL,Male,Other,12/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +55045,62627,56824,PRETRIAL,Menos,Mario,NULL,Male,Other,12/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55043,62624,56822,PRETRIAL,Thomas,Matthew,Leon,Male,African-American,11/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +55043,62624,56822,PRETRIAL,Thomas,Matthew,Leon,Male,African-American,11/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +55043,62624,56822,PRETRIAL,Thomas,Matthew,Leon,Male,African-American,11/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55040,62619,56817,PRETRIAL,Williams,Gavin,NULL,Male,African-American,10/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +55040,62619,56817,PRETRIAL,Williams,Gavin,NULL,Male,African-American,10/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +55040,62619,56817,PRETRIAL,Williams,Gavin,NULL,Male,African-American,10/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55049,62632,56829,Probation,Morris,Randall,NULL,Male,Caucasian,08/18/71,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Married,5/24/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +55049,62632,56829,Probation,Morris,Randall,NULL,Male,Caucasian,08/18/71,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Married,5/24/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +55049,62632,56829,Probation,Morris,Randall,NULL,Male,Caucasian,08/18/71,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Married,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55053,62635,56832,Probation,USSA,ANDRES,NULL,Male,Hispanic,04/16/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +55053,62635,56832,Probation,USSA,ANDRES,NULL,Male,Hispanic,04/16/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +55053,62635,56832,Probation,USSA,ANDRES,NULL,Male,Hispanic,04/16/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +36673,62637,56834,Probation,Gonzalez,Antonio,NULL,Female,Hispanic,01/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +36673,62637,56834,Probation,Gonzalez,Antonio,NULL,Female,Hispanic,01/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,8,High,New,1,0 +36673,62637,56834,Probation,Gonzalez,Antonio,NULL,Female,Hispanic,01/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,9,High,New,1,0 +55042,62622,56820,PRETRIAL,Freire,Lucas,NULL,Male,Caucasian,05/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +55042,62622,56820,PRETRIAL,Freire,Lucas,NULL,Male,Caucasian,05/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +55042,62622,56820,PRETRIAL,Freire,Lucas,NULL,Male,Caucasian,05/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +43281,47332,43206,PRETRIAL,crayton,bradford,michael,Male,African-American,10/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +43281,47332,43206,PRETRIAL,crayton,bradford,michael,Male,African-American,10/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +43281,47332,43206,PRETRIAL,crayton,bradford,michael,Male,African-American,10/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55047,62629,56826,PRETRIAL,Gonzalez,Anthony,NULL,Male,Hispanic,03/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +55047,62629,56826,PRETRIAL,Gonzalez,Anthony,NULL,Male,Hispanic,03/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.7,10,High,New,1,0 +55047,62629,56826,PRETRIAL,Gonzalez,Anthony,NULL,Male,Hispanic,03/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55059,62643,56840,Probation,SHELTON,JASON,MICHAEL,Male,Caucasian,03/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +55059,62643,56840,Probation,SHELTON,JASON,MICHAEL,Male,Caucasian,03/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +55059,62643,56840,Probation,SHELTON,JASON,MICHAEL,Male,Caucasian,03/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +33823,62626,32929,PRETRIAL,perdue,dequontra,NULL,Male,African-American,07/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,Copy,1,0 +33823,62626,32929,PRETRIAL,perdue,dequontra,NULL,Male,African-American,07/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,Copy,1,0 +33823,62626,32929,PRETRIAL,perdue,dequontra,NULL,Male,African-American,07/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +55057,62640,56837,Probation,Crespo,Hector,NULL,Male,Hispanic,07/21/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +55057,62640,56837,Probation,Crespo,Hector,NULL,Male,Hispanic,07/21/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +55057,62640,56837,Probation,Crespo,Hector,NULL,Male,Hispanic,07/21/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +46321,62647,56843,PRETRIAL,Davis,Gregory,NULL,Male,African-American,09/12/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +46321,62647,56843,PRETRIAL,Davis,Gregory,NULL,Male,African-American,09/12/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +46321,62647,56843,PRETRIAL,Davis,Gregory,NULL,Male,African-American,09/12/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55041,62621,56819,PRETRIAL,Penha,Asefa,NULL,Male,Hispanic,03/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +55041,62621,56819,PRETRIAL,Penha,Asefa,NULL,Male,Hispanic,03/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +55041,62621,56819,PRETRIAL,Penha,Asefa,NULL,Male,Hispanic,03/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55055,62638,56835,PRETRIAL,CARMONA,ANDRES,NULL,Male,Caucasian,02/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +55055,62638,56835,PRETRIAL,CARMONA,ANDRES,NULL,Male,Caucasian,02/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +55055,62638,56835,PRETRIAL,CARMONA,ANDRES,NULL,Male,Caucasian,02/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +15606,62617,41826,PRETRIAL,durpee,corey,NULL,Male,African-American,10/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,Copy,1,0 +15606,62617,41826,PRETRIAL,durpee,corey,NULL,Male,African-American,10/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,4,High,8,Risk of Recidivism,0.17,8,High,Copy,1,0 +15606,62617,41826,PRETRIAL,durpee,corey,NULL,Male,African-American,10/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +15347,62642,56839,Probation,stinson,carolyn,NULL,Female,Caucasian,10/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +15347,62642,56839,Probation,stinson,carolyn,NULL,Female,Caucasian,10/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,10,High,New,1,0 +15347,62642,56839,Probation,stinson,carolyn,NULL,Female,Caucasian,10/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +17227,17815,16524,Probation,vigo,steven,NULL,Male,Hispanic,10/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +17227,17815,16524,Probation,vigo,steven,NULL,Male,Hispanic,10/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +17227,17815,16524,Probation,vigo,steven,NULL,Male,Hispanic,10/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +39772,62644,48706,PRETRIAL,Williams,Michael,NULL,Male,African-American,02/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,4,High,7,Risk of Violence,-1,8,High,Copy,1,0 +39772,62644,48706,PRETRIAL,Williams,Michael,NULL,Male,African-American,02/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,4,High,8,Risk of Recidivism,0.83,10,High,Copy,1,0 +39772,62644,48706,PRETRIAL,Williams,Michael,NULL,Male,African-American,02/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +10787,62623,56821,PRETRIAL,FREDERICK,JAMES,L,Male,African-American,02/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +10787,62623,56821,PRETRIAL,FREDERICK,JAMES,L,Male,African-American,02/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +10787,62623,56821,PRETRIAL,FREDERICK,JAMES,L,Male,African-American,02/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,35,10,High,New,1,0 +55054,62636,56833,Probation,Senich,Stephen,NULL,Male,Caucasian,09/11/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/24/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +55054,62636,56833,Probation,Senich,Stephen,NULL,Male,Caucasian,09/11/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/24/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +55054,62636,56833,Probation,Senich,Stephen,NULL,Male,Caucasian,09/11/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55048,62631,56828,PRETRIAL,Lopes,Marta,NULL,Female,Other,01/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/24/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +55048,62631,56828,PRETRIAL,Lopes,Marta,NULL,Female,Other,01/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/24/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +55048,62631,56828,PRETRIAL,Lopes,Marta,NULL,Female,Other,01/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +41265,62649,56845,Probation,Burgess,Shelby,NULL,Female,Caucasian,12/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +41265,62649,56845,Probation,Burgess,Shelby,NULL,Female,Caucasian,12/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +41265,62649,56845,Probation,Burgess,Shelby,NULL,Female,Caucasian,12/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/24/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55046,62628,56825,PRETRIAL,marion,bernice,NULL,Female,African-American,02/16/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +55046,62628,56825,PRETRIAL,marion,bernice,NULL,Female,African-American,02/16/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +55046,62628,56825,PRETRIAL,marion,bernice,NULL,Female,African-American,02/16/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,9,High,New,1,0 +55068,62657,56852,PRETRIAL,Garcia,Elexis,NULL,Female,Caucasian,06/14/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +55068,62657,56852,PRETRIAL,Garcia,Elexis,NULL,Female,Caucasian,06/14/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +55068,62657,56852,PRETRIAL,Garcia,Elexis,NULL,Female,Caucasian,06/14/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +44355,62665,44449,PRETRIAL,McCullough,Lamar,James,Male,African-American,04/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,Copy,1,0 +44355,62665,44449,PRETRIAL,McCullough,Lamar,James,Male,African-American,04/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,Copy,1,0 +44355,62665,44449,PRETRIAL,McCullough,Lamar,James,Male,African-American,04/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +30377,62652,56848,PRETRIAL,CARRIER,MICHAEL,A,Male,Caucasian,11/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +30377,62652,56848,PRETRIAL,CARRIER,MICHAEL,A,Male,Caucasian,11/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +30377,62652,56848,PRETRIAL,CARRIER,MICHAEL,A,Male,Caucasian,11/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55067,62656,56851,PRETRIAL,Washington,Arthur,NULL,Male,African-American,12/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +55067,62656,56851,PRETRIAL,Washington,Arthur,NULL,Male,African-American,12/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +55067,62656,56851,PRETRIAL,Washington,Arthur,NULL,Male,African-American,12/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55074,62663,56858,PRETRIAL,Chaturvedi,Pankaj,NULL,Male,Other,06/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/25/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +55074,62663,56858,PRETRIAL,Chaturvedi,Pankaj,NULL,Male,Other,06/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/25/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +55074,62663,56858,PRETRIAL,Chaturvedi,Pankaj,NULL,Male,Other,06/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +40689,62668,45508,PRETRIAL,Cesaire,William,NULL,Male,African-American,07/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,4,High,7,Risk of Violence,-0.98,9,High,Copy,1,0 +40689,62668,45508,PRETRIAL,Cesaire,William,NULL,Male,African-American,07/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,4,High,8,Risk of Recidivism,1.14,10,High,Copy,1,0 +40689,62668,45508,PRETRIAL,Cesaire,William,NULL,Male,African-American,07/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +55070,62659,56854,PRETRIAL,ARBOLEDA,MATTHEW,NULL,Male,Caucasian,02/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +55070,62659,56854,PRETRIAL,ARBOLEDA,MATTHEW,NULL,Male,Caucasian,02/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +55070,62659,56854,PRETRIAL,ARBOLEDA,MATTHEW,NULL,Male,Caucasian,02/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55072,62661,56856,PRETRIAL,Hubbard,Paul,NULL,Male,Caucasian,03/06/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/25/13 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +55072,62661,56856,PRETRIAL,Hubbard,Paul,NULL,Male,Caucasian,03/06/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/25/13 0:00,1,Low,8,Risk of Recidivism,-2.79,1,Low,New,1,0 +55072,62661,56856,PRETRIAL,Hubbard,Paul,NULL,Male,Caucasian,03/06/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55066,62654,56850,PRETRIAL,Carter,Caitlin,NULL,Female,Caucasian,10/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +55066,62654,56850,PRETRIAL,Carter,Caitlin,NULL,Female,Caucasian,10/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +55066,62654,56850,PRETRIAL,Carter,Caitlin,NULL,Female,Caucasian,10/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55069,62658,56853,PRETRIAL,BAYAS,ANFES,JOSUE,Male,Hispanic,10/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +55069,62658,56853,PRETRIAL,BAYAS,ANFES,JOSUE,Male,Hispanic,10/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +55069,62658,56853,PRETRIAL,BAYAS,ANFES,JOSUE,Male,Hispanic,10/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55063,62650,56846,PRETRIAL,McCray,Stanley,NULL,Male,African-American,07/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +55063,62650,56846,PRETRIAL,McCray,Stanley,NULL,Male,African-American,07/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +55063,62650,56846,PRETRIAL,McCray,Stanley,NULL,Male,African-American,07/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55076,62666,56860,PRETRIAL,Howard,Jamar,NULL,Male,African-American,08/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +55076,62666,56860,PRETRIAL,Howard,Jamar,NULL,Male,African-American,08/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,4,High,8,Risk of Recidivism,0.25,8,High,New,1,0 +55076,62666,56860,PRETRIAL,Howard,Jamar,NULL,Male,African-American,08/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55065,62653,56849,PRETRIAL,Lionakis,Samantha,NULL,Female,Caucasian,09/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +55065,62653,56849,PRETRIAL,Lionakis,Samantha,NULL,Female,Caucasian,09/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +55065,62653,56849,PRETRIAL,Lionakis,Samantha,NULL,Female,Caucasian,09/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55071,62660,56855,PRETRIAL,QUIGGINS,LISA,GAIL,Female,Caucasian,10/12/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +55071,62660,56855,PRETRIAL,QUIGGINS,LISA,GAIL,Female,Caucasian,10/12/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +55071,62660,56855,PRETRIAL,QUIGGINS,LISA,GAIL,Female,Caucasian,10/12/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +27232,62667,26343,PRETRIAL,Shuman,David,Eric,Male,African-American,04/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,4,High,7,Risk of Violence,0.11,10,High,Copy,1,0 +27232,62667,26343,PRETRIAL,Shuman,David,Eric,Male,African-American,04/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,4,High,8,Risk of Recidivism,0.95,10,High,Copy,1,0 +27232,62667,26343,PRETRIAL,Shuman,David,Eric,Male,African-American,04/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,4,High,18,Risk of Failure to Appear,34,10,High,Copy,1,0 +55075,62664,56859,PRETRIAL,POPE,LENARIS,MARQUI,Male,African-American,12/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.34,3,Low,New,1,0 +55075,62664,56859,PRETRIAL,POPE,LENARIS,MARQUI,Male,African-American,12/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +55075,62664,56859,PRETRIAL,POPE,LENARIS,MARQUI,Male,African-American,12/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55064,62651,56847,PRETRIAL,Kelly,Brandon,NULL,Male,African-American,08/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +55064,62651,56847,PRETRIAL,Kelly,Brandon,NULL,Male,African-American,08/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +55064,62651,56847,PRETRIAL,Kelly,Brandon,NULL,Male,African-American,08/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52289,62655,53563,PRETRIAL,Pine,Artie,NULL,Male,Caucasian,05/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,Copy,1,0 +52289,62655,53563,PRETRIAL,Pine,Artie,NULL,Male,Caucasian,05/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,Copy,1,0 +52289,62655,53563,PRETRIAL,Pine,Artie,NULL,Male,Caucasian,05/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +55073,62662,56857,PRETRIAL,MARAGH,CHADWAYNE,NULL,Male,African-American,10/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +55073,62662,56857,PRETRIAL,MARAGH,CHADWAYNE,NULL,Male,African-American,10/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +55073,62662,56857,PRETRIAL,MARAGH,CHADWAYNE,NULL,Male,African-American,10/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55083,62676,56868,PRETRIAL,SANTIAGO,ANGEL,NULL,Male,Caucasian,04/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +55083,62676,56868,PRETRIAL,SANTIAGO,ANGEL,NULL,Male,Caucasian,04/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +55083,62676,56868,PRETRIAL,SANTIAGO,ANGEL,NULL,Male,Caucasian,04/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55086,62683,56875,PRETRIAL,JOSEPH,KERBY,NULL,Male,African-American,02/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/26/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +55086,62683,56875,PRETRIAL,JOSEPH,KERBY,NULL,Male,African-American,02/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/26/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +55086,62683,56875,PRETRIAL,JOSEPH,KERBY,NULL,Male,African-American,02/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +38737,62669,56861,PRETRIAL,CuLver,Napoleon,NULL,Male,African-American,01/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/26/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +38737,62669,56861,PRETRIAL,CuLver,Napoleon,NULL,Male,African-American,01/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +38737,62669,56861,PRETRIAL,CuLver,Napoleon,NULL,Male,African-American,01/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/26/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +7549,62685,56877,PRETRIAL,ROBINSON,DEMARCUS,NULL,Male,African-American,06/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,4,High,7,Risk of Violence,-0.5,10,High,New,1,0 +7549,62685,56877,PRETRIAL,ROBINSON,DEMARCUS,NULL,Male,African-American,06/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,4,High,8,Risk of Recidivism,1.06,10,High,New,1,0 +7549,62685,56877,PRETRIAL,ROBINSON,DEMARCUS,NULL,Male,African-American,06/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55088,62681,56873,PRETRIAL,Perez,Joseph,NULL,Male,Caucasian,11/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +55088,62681,56873,PRETRIAL,Perez,Joseph,NULL,Male,Caucasian,11/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +55088,62681,56873,PRETRIAL,Perez,Joseph,NULL,Male,Caucasian,11/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55092,62687,56879,PRETRIAL,WANSCHEK,LAWRENCE,NULL,Male,Caucasian,12/24/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +55092,62687,56879,PRETRIAL,WANSCHEK,LAWRENCE,NULL,Male,Caucasian,12/24/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +55092,62687,56879,PRETRIAL,WANSCHEK,LAWRENCE,NULL,Male,Caucasian,12/24/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55081,62674,56866,PRETRIAL,JONES,RICHARD,NULL,Male,Caucasian,10/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +55081,62674,56866,PRETRIAL,JONES,RICHARD,NULL,Male,Caucasian,10/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +55081,62674,56866,PRETRIAL,JONES,RICHARD,NULL,Male,Caucasian,10/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55078,62671,56863,PRETRIAL,Lewis,Stacey,NULL,Male,African-American,02/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +55078,62671,56863,PRETRIAL,Lewis,Stacey,NULL,Male,African-American,02/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +55078,62671,56863,PRETRIAL,Lewis,Stacey,NULL,Male,African-American,02/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55085,62679,56871,PRETRIAL,BISHOP,TERRIL,NULL,Male,African-American,11/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/26/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +55085,62679,56871,PRETRIAL,BISHOP,TERRIL,NULL,Male,African-American,11/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/26/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +55085,62679,56871,PRETRIAL,BISHOP,TERRIL,NULL,Male,African-American,11/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55082,62675,56867,PRETRIAL,Simons,Joshua,NULL,Male,Caucasian,02/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +55082,62675,56867,PRETRIAL,Simons,Joshua,NULL,Male,Caucasian,02/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +55082,62675,56867,PRETRIAL,Simons,Joshua,NULL,Male,Caucasian,02/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55089,62682,56874,PRETRIAL,Pagan,Alberto,NULL,Male,Hispanic,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +55089,62682,56874,PRETRIAL,Pagan,Alberto,NULL,Male,Hispanic,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +55089,62682,56874,PRETRIAL,Pagan,Alberto,NULL,Male,Hispanic,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55090,62684,56876,PRETRIAL,Cardona,Gian,NULL,Male,Hispanic,01/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,4,High,7,Risk of Violence,-0.57,10,High,New,1,0 +55090,62684,56876,PRETRIAL,Cardona,Gian,NULL,Male,Hispanic,01/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +55090,62684,56876,PRETRIAL,Cardona,Gian,NULL,Male,Hispanic,01/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55093,62689,56880,PRETRIAL,Currier,Brittany,t,Female,Caucasian,03/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +55093,62689,56880,PRETRIAL,Currier,Brittany,t,Female,Caucasian,03/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +55093,62689,56880,PRETRIAL,Currier,Brittany,t,Female,Caucasian,03/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +16757,62677,56869,PRETRIAL,KALLMAN,PATRICK,NULL,Male,Caucasian,04/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +16757,62677,56869,PRETRIAL,KALLMAN,PATRICK,NULL,Male,Caucasian,04/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +16757,62677,56869,PRETRIAL,KALLMAN,PATRICK,NULL,Male,Caucasian,04/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55091,62686,56878,PRETRIAL,HANNON,STEPHEN,NULL,Male,African-American,10/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +55091,62686,56878,PRETRIAL,HANNON,STEPHEN,NULL,Male,African-American,10/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +55091,62686,56878,PRETRIAL,HANNON,STEPHEN,NULL,Male,African-American,10/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +44850,62688,44990,PRETRIAL,Barker,Eric,NULL,Male,African-American,06/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,Copy,1,0 +44850,62688,44990,PRETRIAL,Barker,Eric,NULL,Male,African-American,06/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,Copy,1,0 +44850,62688,44990,PRETRIAL,Barker,Eric,NULL,Male,African-American,06/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +55080,62673,56865,PRETRIAL,Carter,Thomas,NULL,Male,Caucasian,01/17/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +55080,62673,56865,PRETRIAL,Carter,Thomas,NULL,Male,Caucasian,01/17/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +55080,62673,56865,PRETRIAL,Carter,Thomas,NULL,Male,Caucasian,01/17/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55079,62672,56864,PRETRIAL,Johnson,Steven,NULL,Male,African-American,10/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +55079,62672,56864,PRETRIAL,Johnson,Steven,NULL,Male,African-American,10/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +55079,62672,56864,PRETRIAL,Johnson,Steven,NULL,Male,African-American,10/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55077,62670,56862,PRETRIAL,Coutain,Alison,NULL,Female,Other,12/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +55077,62670,56862,PRETRIAL,Coutain,Alison,NULL,Female,Other,12/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +55077,62670,56862,PRETRIAL,Coutain,Alison,NULL,Female,Other,12/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55084,62678,56870,PRETRIAL,Wright,Lee,NULL,Male,African-American,09/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/26/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +55084,62678,56870,PRETRIAL,Wright,Lee,NULL,Male,African-American,09/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/26/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +55084,62678,56870,PRETRIAL,Wright,Lee,NULL,Male,African-American,09/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55100,62696,56887,PRETRIAL,Brown,Calvin,Kelly,Male,African-American,07/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +55100,62696,56887,PRETRIAL,Brown,Calvin,Kelly,Male,African-American,07/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +55100,62696,56887,PRETRIAL,Brown,Calvin,Kelly,Male,African-American,07/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55102,62699,56890,PRETRIAL,MALONE,ALAN,MICHAEL,Male,Caucasian,04/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +55102,62699,56890,PRETRIAL,MALONE,ALAN,MICHAEL,Male,Caucasian,04/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +55102,62699,56890,PRETRIAL,MALONE,ALAN,MICHAEL,Male,Caucasian,04/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55106,62704,56895,PRETRIAL,MATHIS,COREY,NULL,Male,African-American,11/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/13 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +55106,62704,56895,PRETRIAL,MATHIS,COREY,NULL,Male,African-American,11/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +55106,62704,56895,PRETRIAL,MATHIS,COREY,NULL,Male,African-American,11/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55095,62691,56882,PRETRIAL,Swan,David,NULL,Male,Caucasian,09/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/27/13 0:00,1,Low,7,Risk of Violence,-4.29,1,Low,New,1,0 +55095,62691,56882,PRETRIAL,Swan,David,NULL,Male,Caucasian,09/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/27/13 0:00,1,Low,8,Risk of Recidivism,-2.72,1,Low,New,1,0 +55095,62691,56882,PRETRIAL,Swan,David,NULL,Male,Caucasian,09/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55097,62693,56884,PRETRIAL,Mullins,Antwane,Jarvis,Male,African-American,08/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,New,1,0 +55097,62693,56884,PRETRIAL,Mullins,Antwane,Jarvis,Male,African-American,08/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +55097,62693,56884,PRETRIAL,Mullins,Antwane,Jarvis,Male,African-American,08/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55098,62694,56885,PRETRIAL,HUBERT,JOSEPH,NULL,Male,African-American,08/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/27/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +55098,62694,56885,PRETRIAL,HUBERT,JOSEPH,NULL,Male,African-American,08/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/27/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +55098,62694,56885,PRETRIAL,HUBERT,JOSEPH,NULL,Male,African-American,08/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55104,62701,56892,PRETRIAL,Pearson,Randy,NULL,Male,Caucasian,02/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +55104,62701,56892,PRETRIAL,Pearson,Randy,NULL,Male,Caucasian,02/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +55104,62701,56892,PRETRIAL,Pearson,Randy,NULL,Male,Caucasian,02/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55101,62698,56889,PRETRIAL,HOLMES,HERMAN,NULL,Female,African-American,01/08/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +55101,62698,56889,PRETRIAL,HOLMES,HERMAN,NULL,Female,African-American,01/08/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +55101,62698,56889,PRETRIAL,HOLMES,HERMAN,NULL,Female,African-American,01/08/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +20922,62703,56894,PRETRIAL,Coney,Steven,James,Male,African-American,08/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.11,8,High,New,1,0 +20922,62703,56894,PRETRIAL,Coney,Steven,James,Male,African-American,08/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +20922,62703,56894,PRETRIAL,Coney,Steven,James,Male,African-American,08/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55107,62705,56896,PRETRIAL,GUERRIER,FRANTZ,NULL,Male,African-American,08/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +55107,62705,56896,PRETRIAL,GUERRIER,FRANTZ,NULL,Male,African-American,08/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/13 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +55107,62705,56896,PRETRIAL,GUERRIER,FRANTZ,NULL,Male,African-American,08/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55096,62692,56883,PRETRIAL,SALESMAN,GEOFFREY,NULL,Male,African-American,07/18/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +55096,62692,56883,PRETRIAL,SALESMAN,GEOFFREY,NULL,Male,African-American,07/18/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +55096,62692,56883,PRETRIAL,SALESMAN,GEOFFREY,NULL,Male,African-American,07/18/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55099,62695,56886,PRETRIAL,LUCK,LYNDA,RUTH,Female,Caucasian,06/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +55099,62695,56886,PRETRIAL,LUCK,LYNDA,RUTH,Female,Caucasian,06/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +55099,62695,56886,PRETRIAL,LUCK,LYNDA,RUTH,Female,Caucasian,06/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,18,Risk of Failure to Appear,29,9,High,New,1,0 +55103,62700,56891,PRETRIAL,FOURNIER,CHRISTOPHER,NULL,Male,Caucasian,11/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +55103,62700,56891,PRETRIAL,FOURNIER,CHRISTOPHER,NULL,Male,Caucasian,11/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +55103,62700,56891,PRETRIAL,FOURNIER,CHRISTOPHER,NULL,Male,Caucasian,11/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55108,62706,56897,PRETRIAL,Hough,Fredrick,NULL,Male,African-American,10/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +55108,62706,56897,PRETRIAL,Hough,Fredrick,NULL,Male,African-American,10/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +55108,62706,56897,PRETRIAL,Hough,Fredrick,NULL,Male,African-American,10/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55105,62702,56893,PRETRIAL,Obrien,Adam,NULL,Male,Caucasian,11/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +55105,62702,56893,PRETRIAL,Obrien,Adam,NULL,Male,Caucasian,11/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +55105,62702,56893,PRETRIAL,Obrien,Adam,NULL,Male,Caucasian,11/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55094,62690,56881,PRETRIAL,CULMER,ARIANA,Q,Female,African-American,02/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +55094,62690,56881,PRETRIAL,CULMER,ARIANA,Q,Female,African-American,02/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +55094,62690,56881,PRETRIAL,CULMER,ARIANA,Q,Female,African-American,02/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +17489,62697,56888,PRETRIAL,Anderson,Fitzgerald,NULL,Male,African-American,03/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,4,High,7,Risk of Violence,-1.03,8,High,New,1,0 +17489,62697,56888,PRETRIAL,Anderson,Fitzgerald,NULL,Male,African-American,03/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,4,High,8,Risk of Recidivism,0.77,10,High,New,1,0 +17489,62697,56888,PRETRIAL,Anderson,Fitzgerald,NULL,Male,African-American,03/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/13 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +55113,62711,56902,PRETRIAL,VALENTINE,ALICIA,SIMONE,Female,African-American,01/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,4,High,7,Risk of Violence,-0.7,9,High,New,1,0 +55113,62711,56902,PRETRIAL,VALENTINE,ALICIA,SIMONE,Female,African-American,01/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,4,High,8,Risk of Recidivism,0.03,8,High,New,1,0 +55113,62711,56902,PRETRIAL,VALENTINE,ALICIA,SIMONE,Female,African-American,01/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55119,62718,56909,PRETRIAL,Funchess,Brittany,NULL,Female,African-American,05/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +55119,62718,56909,PRETRIAL,Funchess,Brittany,NULL,Female,African-American,05/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +55119,62718,56909,PRETRIAL,Funchess,Brittany,NULL,Female,African-American,05/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55120,62720,56911,PRETRIAL,Demenezes,Deborah,NULL,Female,Caucasian,01/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +55120,62720,56911,PRETRIAL,Demenezes,Deborah,NULL,Female,Caucasian,01/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +55120,62720,56911,PRETRIAL,Demenezes,Deborah,NULL,Female,Caucasian,01/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +29597,62736,56925,PRETRIAL,Anello,Anthony,NULL,Male,Caucasian,01/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +29597,62736,56925,PRETRIAL,Anello,Anthony,NULL,Male,Caucasian,01/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +29597,62736,56925,PRETRIAL,Anello,Anthony,NULL,Male,Caucasian,01/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53784,62723,55272,Probation,TUN,CHRISTOPHER,A,Male,Caucasian,04/28/92,17,All Scales,Intake,English,Pretrial,Parole,Single,5/28/13 0:00,4,High,7,Risk of Violence,-0.67,9,High,New,1,0 +53784,62723,55272,Probation,TUN,CHRISTOPHER,A,Male,Caucasian,04/28/92,17,All Scales,Intake,English,Pretrial,Parole,Single,5/28/13 0:00,4,High,8,Risk of Recidivism,0.79,10,High,New,1,0 +53784,62723,55272,Probation,TUN,CHRISTOPHER,A,Male,Caucasian,04/28/92,17,All Scales,Intake,English,Pretrial,Parole,Single,5/28/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55132,62732,56921,Probation,Mcclain,Linda,NULL,Female,Caucasian,12/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/28/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +55132,62732,56921,Probation,Mcclain,Linda,NULL,Female,Caucasian,12/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +55132,62732,56921,Probation,Mcclain,Linda,NULL,Female,Caucasian,12/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55126,62727,56916,PRETRIAL,Pauleuc,Alexander,NULL,Male,Caucasian,06/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +55126,62727,56916,PRETRIAL,Pauleuc,Alexander,NULL,Male,Caucasian,06/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +55126,62727,56916,PRETRIAL,Pauleuc,Alexander,NULL,Male,Caucasian,06/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55134,62734,56923,Probation,HARRIS,CALVIN,NULL,Male,African-American,03/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +55134,62734,56923,Probation,HARRIS,CALVIN,NULL,Male,African-American,03/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +55134,62734,56923,Probation,HARRIS,CALVIN,NULL,Male,African-American,03/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54248,62721,55843,Probation,rousseau,francesca,NULL,Female,Caucasian,04/28/94,17,All Scales,Intake,English,Pretrial,Probation,Single,5/28/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +54248,62721,55843,Probation,rousseau,francesca,NULL,Female,Caucasian,04/28/94,17,All Scales,Intake,English,Pretrial,Probation,Single,5/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +54248,62721,55843,Probation,rousseau,francesca,NULL,Female,Caucasian,04/28/94,17,All Scales,Intake,English,Pretrial,Probation,Single,5/28/13 0:00,2,Medium,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +55115,62713,56904,PRETRIAL,DAVIS,UTWAIN,NULL,Male,African-American,08/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +55115,62713,56904,PRETRIAL,DAVIS,UTWAIN,NULL,Male,African-American,08/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +55115,62713,56904,PRETRIAL,DAVIS,UTWAIN,NULL,Male,African-American,08/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55129,62729,56918,Probation,PEREZ,RICHARD,NULL,Male,Hispanic,05/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +55129,62729,56918,Probation,PEREZ,RICHARD,NULL,Male,Hispanic,05/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +55129,62729,56918,Probation,PEREZ,RICHARD,NULL,Male,Hispanic,05/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55110,62708,56899,PRETRIAL,Carlson,Cody,Brian,Male,Caucasian,10/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +55110,62708,56899,PRETRIAL,Carlson,Cody,Brian,Male,Caucasian,10/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +55110,62708,56899,PRETRIAL,Carlson,Cody,Brian,Male,Caucasian,10/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55117,62716,56907,PRETRIAL,Lara,Carlos,Andres,Male,Hispanic,05/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +55117,62716,56907,PRETRIAL,Lara,Carlos,Andres,Male,Hispanic,05/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +55117,62716,56907,PRETRIAL,Lara,Carlos,Andres,Male,Hispanic,05/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55114,62712,56903,PRETRIAL,BROWN,RASHUN,MALIK,Male,African-American,07/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +55114,62712,56903,PRETRIAL,BROWN,RASHUN,MALIK,Male,African-American,07/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +55114,62712,56903,PRETRIAL,BROWN,RASHUN,MALIK,Male,African-American,07/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55124,62726,56915,Probation,Helvie,Robert,NULL,Male,Caucasian,12/07/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/28/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +55124,62726,56915,Probation,Helvie,Robert,NULL,Male,Caucasian,12/07/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +55124,62726,56915,Probation,Helvie,Robert,NULL,Male,Caucasian,12/07/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +48725,62733,56922,Probation,May,Anthony,NULL,Male,African-American,12/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +48725,62733,56922,Probation,May,Anthony,NULL,Male,African-American,12/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +48725,62733,56922,Probation,May,Anthony,NULL,Male,African-American,12/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55121,62719,56910,PRETRIAL,Olson,Walter,NULL,Male,Caucasian,12/07/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +55121,62719,56910,PRETRIAL,Olson,Walter,NULL,Male,Caucasian,12/07/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +55121,62719,56910,PRETRIAL,Olson,Walter,NULL,Male,Caucasian,12/07/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55112,62710,56901,PRETRIAL,Raudales,Mario,NULL,Male,Hispanic,11/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/28/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +55112,62710,56901,PRETRIAL,Raudales,Mario,NULL,Male,Hispanic,11/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/28/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +55112,62710,56901,PRETRIAL,Raudales,Mario,NULL,Male,Hispanic,11/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55123,62724,56913,Probation,Tanelus,Diana,Stacy,Female,African-American,01/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/13 0:00,2,Medium,7,Risk of Violence,-2.7,2,Low,New,1,0 +55123,62724,56913,Probation,Tanelus,Diana,Stacy,Female,African-American,01/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +55123,62724,56913,Probation,Tanelus,Diana,Stacy,Female,African-American,01/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55131,62731,56920,PRETRIAL,DAVIS,MELISSA,M,Female,Caucasian,03/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/28/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +55131,62731,56920,PRETRIAL,DAVIS,MELISSA,M,Female,Caucasian,03/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +55131,62731,56920,PRETRIAL,DAVIS,MELISSA,M,Female,Caucasian,03/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55133,62735,56924,PRETRIAL,SERRANO,ANGEL,NULL,Male,Hispanic,07/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +55133,62735,56924,PRETRIAL,SERRANO,ANGEL,NULL,Male,Hispanic,07/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +55133,62735,56924,PRETRIAL,SERRANO,ANGEL,NULL,Male,Hispanic,07/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55109,62707,56898,PRETRIAL,Moore,John,Henry,Male,African-American,06/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,2,Medium,7,Risk of Violence,-3.32,1,Low,New,1,0 +55109,62707,56898,PRETRIAL,Moore,John,Henry,Male,African-American,06/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +55109,62707,56898,PRETRIAL,Moore,John,Henry,Male,African-American,06/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55111,62709,56900,PRETRIAL,Aguilar,Rene,F,Male,Caucasian,03/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/28/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +55111,62709,56900,PRETRIAL,Aguilar,Rene,F,Male,Caucasian,03/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +55111,62709,56900,PRETRIAL,Aguilar,Rene,F,Male,Caucasian,03/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +30172,62714,56905,PRETRIAL,BROWN,AKIL,ADISA,Male,African-American,11/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +30172,62714,56905,PRETRIAL,BROWN,AKIL,ADISA,Male,African-American,11/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +30172,62714,56905,PRETRIAL,BROWN,AKIL,ADISA,Male,African-American,11/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55130,62730,56919,Probation,willits,donna,m,Female,Caucasian,06/04/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/28/13 0:00,1,Low,7,Risk of Violence,-4.37,1,Low,New,1,0 +55130,62730,56919,Probation,willits,donna,m,Female,Caucasian,06/04/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/28/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +55130,62730,56919,Probation,willits,donna,m,Female,Caucasian,06/04/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55116,62715,56906,PRETRIAL,Roberti,Asher,NULL,Male,Caucasian,10/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +55116,62715,56906,PRETRIAL,Roberti,Asher,NULL,Male,Caucasian,10/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +55116,62715,56906,PRETRIAL,Roberti,Asher,NULL,Male,Caucasian,10/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55125,62725,56914,Probation,arias,ariess,NULL,Female,Hispanic,03/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +55125,62725,56914,Probation,arias,ariess,NULL,Female,Hispanic,03/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,7,Medium,New,1,0 +55125,62725,56914,Probation,arias,ariess,NULL,Female,Hispanic,03/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/13 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,New,1,0 +55118,62717,56908,PRETRIAL,Lipper,Carly,NULL,Female,Caucasian,10/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +55118,62717,56908,PRETRIAL,Lipper,Carly,NULL,Female,Caucasian,10/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +55118,62717,56908,PRETRIAL,Lipper,Carly,NULL,Female,Caucasian,10/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +35141,62756,34325,PRETRIAL,RUCKER,ANNQUINETTE,NULL,Female,African-American,05/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,Copy,1,0 +35141,62756,34325,PRETRIAL,RUCKER,ANNQUINETTE,NULL,Female,African-American,05/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,8,High,Copy,1,0 +35141,62756,34325,PRETRIAL,RUCKER,ANNQUINETTE,NULL,Female,African-American,05/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +55157,62767,56951,Probation,PHELPS,CHRISTIAN,ALEX,Male,African-American,01/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +55157,62767,56951,Probation,PHELPS,CHRISTIAN,ALEX,Male,African-American,01/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +55157,62767,56951,Probation,PHELPS,CHRISTIAN,ALEX,Male,African-American,01/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55141,62746,56933,PRETRIAL,badanoy,alejandro,NULL,Male,Asian,10/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/29/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +55141,62746,56933,PRETRIAL,badanoy,alejandro,NULL,Male,Asian,10/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +55141,62746,56933,PRETRIAL,badanoy,alejandro,NULL,Male,Asian,10/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55162,62777,56961,Probation,Tolle,Jerome,A,Male,Caucasian,12/02/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +55162,62777,56961,Probation,Tolle,Jerome,A,Male,Caucasian,12/02/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +55162,62777,56961,Probation,Tolle,Jerome,A,Male,Caucasian,12/02/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +17398,62759,56945,PRETRIAL,CARTWRIGHT,RASHAN,NULL,Male,African-American,05/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +17398,62759,56945,PRETRIAL,CARTWRIGHT,RASHAN,NULL,Male,African-American,05/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +17398,62759,56945,PRETRIAL,CARTWRIGHT,RASHAN,NULL,Male,African-American,05/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55156,62764,56949,Probation,nelson,christopher,NULL,Male,African-American,11/11/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +55156,62764,56949,Probation,nelson,christopher,NULL,Male,African-American,11/11/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +55156,62764,56949,Probation,nelson,christopher,NULL,Male,African-American,11/11/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55135,62738,56926,PRETRIAL,HOLMES,GREGORY,NULL,Male,African-American,07/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +55135,62738,56926,PRETRIAL,HOLMES,GREGORY,NULL,Male,African-American,07/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +55135,62738,56926,PRETRIAL,HOLMES,GREGORY,NULL,Male,African-American,07/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55160,62772,56956,Probation,SASOWSKINORMAN,SUSAN,M,Female,Caucasian,01/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +55160,62772,56956,Probation,SASOWSKINORMAN,SUSAN,M,Female,Caucasian,01/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +55160,62772,56956,Probation,SASOWSKINORMAN,SUSAN,M,Female,Caucasian,01/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55168,62785,56969,Probation,JEANLOUIS,PARNELL,NULL,Male,African-American,10/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.12,4,Low,New,1,0 +55168,62785,56969,Probation,JEANLOUIS,PARNELL,NULL,Male,African-American,10/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +55168,62785,56969,Probation,JEANLOUIS,PARNELL,NULL,Male,African-American,10/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55146,62751,56938,PRETRIAL,Lopez,Jonathan,NULL,Male,Hispanic,05/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +55146,62751,56938,PRETRIAL,Lopez,Jonathan,NULL,Male,Hispanic,05/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +55146,62751,56938,PRETRIAL,Lopez,Jonathan,NULL,Male,Hispanic,05/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55139,62743,56931,PRETRIAL,Daniels,Richard,NULL,Male,Caucasian,06/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/29/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +55139,62743,56931,PRETRIAL,Daniels,Richard,NULL,Male,Caucasian,06/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +55139,62743,56931,PRETRIAL,Daniels,Richard,NULL,Male,Caucasian,06/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55170,62788,56971,Probation,Anth,Brian,Michael,Male,Caucasian,10/24/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/29/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +55170,62788,56971,Probation,Anth,Brian,Michael,Male,Caucasian,10/24/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +55170,62788,56971,Probation,Anth,Brian,Michael,Male,Caucasian,10/24/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55144,62749,56936,PRETRIAL,VELEZ,KRISTINA,NULL,Female,African-American,10/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/29/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +55144,62749,56936,PRETRIAL,VELEZ,KRISTINA,NULL,Female,African-American,10/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +55144,62749,56936,PRETRIAL,VELEZ,KRISTINA,NULL,Female,African-American,10/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55140,62745,56932,PRETRIAL,Lopez,Israel,NULL,Male,Hispanic,01/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +55140,62745,56932,PRETRIAL,Lopez,Israel,NULL,Male,Hispanic,01/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +55140,62745,56932,PRETRIAL,Lopez,Israel,NULL,Male,Hispanic,01/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55169,62787,56970,Probation,Wright,Anthony,Patrick,Male,Other,03/11/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/29/13 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +55169,62787,56970,Probation,Wright,Anthony,Patrick,Male,Other,03/11/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +55169,62787,56970,Probation,Wright,Anthony,Patrick,Male,Other,03/11/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/29/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +41432,62766,41132,PRETRIAL,TORRES,MARVEL,J,Male,Hispanic,01/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,Copy,1,0 +41432,62766,41132,PRETRIAL,TORRES,MARVEL,J,Male,Hispanic,01/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,Copy,1,0 +41432,62766,41132,PRETRIAL,TORRES,MARVEL,J,Male,Hispanic,01/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +55137,62740,56928,PRETRIAL,Peart,Maxine,NULL,Female,Other,05/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/29/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +55137,62740,56928,PRETRIAL,Peart,Maxine,NULL,Female,Other,05/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/29/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +55137,62740,56928,PRETRIAL,Peart,Maxine,NULL,Female,Other,05/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55142,62747,56934,PRETRIAL,MATRONE,LOUIS,NULL,Male,Caucasian,02/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +55142,62747,56934,PRETRIAL,MATRONE,LOUIS,NULL,Male,Caucasian,02/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +55142,62747,56934,PRETRIAL,MATRONE,LOUIS,NULL,Male,Caucasian,02/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +48965,62761,56947,Probation,rivera,noel,NULL,Male,Hispanic,05/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +48965,62761,56947,Probation,rivera,noel,NULL,Male,Hispanic,05/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +48965,62761,56947,Probation,rivera,noel,NULL,Male,Hispanic,05/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +48446,62754,56941,PRETRIAL,Holliday,Daniel,Scott,Male,Caucasian,03/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +48446,62754,56941,PRETRIAL,Holliday,Daniel,Scott,Male,Caucasian,03/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +48446,62754,56941,PRETRIAL,Holliday,Daniel,Scott,Male,Caucasian,03/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55163,62775,56959,PRETRIAL,navarro,ernest,NULL,Male,African-American,07/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +55163,62775,56959,PRETRIAL,navarro,ernest,NULL,Male,African-American,07/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.97,10,High,New,1,0 +55163,62775,56959,PRETRIAL,navarro,ernest,NULL,Male,African-American,07/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +55167,62782,56966,PRETRIAL,Molina,Luis,NULL,Male,Caucasian,11/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/29/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +55167,62782,56966,PRETRIAL,Molina,Luis,NULL,Male,Caucasian,11/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +55167,62782,56966,PRETRIAL,Molina,Luis,NULL,Male,Caucasian,11/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +45188,62784,56968,PRETRIAL,Zapata-Mancilla,Yeison,Yamir,Male,Hispanic,04/10/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/29/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +45188,62784,56968,PRETRIAL,Zapata-Mancilla,Yeison,Yamir,Male,Hispanic,04/10/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +45188,62784,56968,PRETRIAL,Zapata-Mancilla,Yeison,Yamir,Male,Hispanic,04/10/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55145,62750,56937,PRETRIAL,Stlouis,Yves,NULL,Male,African-American,11/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +55145,62750,56937,PRETRIAL,Stlouis,Yves,NULL,Male,African-American,11/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +55145,62750,56937,PRETRIAL,Stlouis,Yves,NULL,Male,African-American,11/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55161,62773,56957,Probation,boland,delberts,NULL,Male,African-American,03/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +55161,62773,56957,Probation,boland,delberts,NULL,Male,African-American,03/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +55161,62773,56957,Probation,boland,delberts,NULL,Male,African-American,03/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +30909,62737,29904,PRETRIAL,Westbrook,Clarence,NULL,Male,African-American,08/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,Copy,1,0 +30909,62737,29904,PRETRIAL,Westbrook,Clarence,NULL,Male,African-American,08/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,Copy,1,0 +30909,62737,29904,PRETRIAL,Westbrook,Clarence,NULL,Male,African-American,08/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +55147,62752,56939,PRETRIAL,Brown,Ronnie,NULL,Male,African-American,12/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +55147,62752,56939,PRETRIAL,Brown,Ronnie,NULL,Male,African-American,12/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +55147,62752,56939,PRETRIAL,Brown,Ronnie,NULL,Male,African-American,12/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55159,62771,56955,DRRD,Fiddemon,Jeronald,NULL,Male,African-American,07/29/77,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +55159,62771,56955,DRRD,Fiddemon,Jeronald,NULL,Male,African-American,07/29/77,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +55159,62771,56955,DRRD,Fiddemon,Jeronald,NULL,Male,African-American,07/29/77,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +55151,62758,56944,Probation,hughes,brandon,NULL,Male,Caucasian,07/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +55151,62758,56944,Probation,hughes,brandon,NULL,Male,Caucasian,07/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +55151,62758,56944,Probation,hughes,brandon,NULL,Male,Caucasian,07/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55155,62765,56950,Probation,Edwards,Bernard,NULL,Male,African-American,12/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +55155,62765,56950,Probation,Edwards,Bernard,NULL,Male,African-American,12/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +55155,62765,56950,Probation,Edwards,Bernard,NULL,Male,African-American,12/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +47622,62744,48194,PRETRIAL,Chin,Steve,L,Male,African-American,10/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/29/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,Copy,1,0 +47622,62744,48194,PRETRIAL,Chin,Steve,L,Male,African-American,10/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,Copy,1,0 +47622,62744,48194,PRETRIAL,Chin,Steve,L,Male,African-American,10/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +44505,62779,56963,PRETRIAL,Rosado,Elioel,NULL,Male,Caucasian,10/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +44505,62779,56963,PRETRIAL,Rosado,Elioel,NULL,Male,Caucasian,10/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +44505,62779,56963,PRETRIAL,Rosado,Elioel,NULL,Male,Caucasian,10/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55152,62760,56946,Probation,CORSER,DEREK,JAMES,Male,Caucasian,05/28/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +55152,62760,56946,Probation,CORSER,DEREK,JAMES,Male,Caucasian,05/28/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +55152,62760,56946,Probation,CORSER,DEREK,JAMES,Male,Caucasian,05/28/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +27789,62742,56930,Probation,Paris,David,NULL,Male,Caucasian,09/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +27789,62742,56930,Probation,Paris,David,NULL,Male,Caucasian,09/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +27789,62742,56930,Probation,Paris,David,NULL,Male,Caucasian,09/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55166,62781,56965,Probation,HUBSON,DONOVAN,A,Male,African-American,05/18/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +55166,62781,56965,Probation,HUBSON,DONOVAN,A,Male,African-American,05/18/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +55166,62781,56965,Probation,HUBSON,DONOVAN,A,Male,African-American,05/18/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55149,62755,56942,PRETRIAL,Williams,Lawrence,Jacob,Male,African-American,07/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +55149,62755,56942,PRETRIAL,Williams,Lawrence,Jacob,Male,African-American,07/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +55149,62755,56942,PRETRIAL,Williams,Lawrence,Jacob,Male,African-American,07/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55158,62768,56952,Probation,STATON,JORY,NULL,Male,Caucasian,11/07/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +55158,62768,56952,Probation,STATON,JORY,NULL,Male,Caucasian,11/07/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +55158,62768,56952,Probation,STATON,JORY,NULL,Male,Caucasian,11/07/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +55171,62789,56972,Probation,eugene,nicolle,NULL,Female,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +55171,62789,56972,Probation,eugene,nicolle,NULL,Female,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +55171,62789,56972,Probation,eugene,nicolle,NULL,Female,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55164,62778,56962,PRETRIAL,Roman,Angel,Aaron,Male,Hispanic,09/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +55164,62778,56962,PRETRIAL,Roman,Angel,Aaron,Male,Hispanic,09/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +55164,62778,56962,PRETRIAL,Roman,Angel,Aaron,Male,Hispanic,09/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +37612,62774,56958,PRETRIAL,Berrios,Amaury,NULL,Male,Caucasian,08/29/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +37612,62774,56958,PRETRIAL,Berrios,Amaury,NULL,Male,Caucasian,08/29/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +37612,62774,56958,PRETRIAL,Berrios,Amaury,NULL,Male,Caucasian,08/29/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +17482,62792,53830,PRETRIAL,Schaad,Casey,NULL,Male,Caucasian,11/09/79,17,All Scales,Intake,English,Post Sentence,Probation,Separated,5/29/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +17482,62792,53830,PRETRIAL,Schaad,Casey,NULL,Male,Caucasian,11/09/79,17,All Scales,Intake,English,Post Sentence,Probation,Separated,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +17482,62792,53830,PRETRIAL,Schaad,Casey,NULL,Male,Caucasian,11/09/79,17,All Scales,Intake,English,Post Sentence,Probation,Separated,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +55150,62757,56943,PRETRIAL,Milunec,Thomas,NULL,Male,Caucasian,06/27/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/29/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +55150,62757,56943,PRETRIAL,Milunec,Thomas,NULL,Male,Caucasian,06/27/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/29/13 0:00,1,Low,8,Risk of Recidivism,-2.65,1,Low,New,1,0 +55150,62757,56943,PRETRIAL,Milunec,Thomas,NULL,Male,Caucasian,06/27/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55148,62753,56940,PRETRIAL,Shelton,Ronald,Lee,Male,African-American,06/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,New,1,0 +55148,62753,56940,PRETRIAL,Shelton,Ronald,Lee,Male,African-American,06/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +55148,62753,56940,PRETRIAL,Shelton,Ronald,Lee,Male,African-American,06/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +44851,62769,56953,Probation,SMITH,JESSICA,NULL,Female,Caucasian,02/09/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +44851,62769,56953,Probation,SMITH,JESSICA,NULL,Female,Caucasian,02/09/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,7,Medium,New,1,0 +44851,62769,56953,Probation,SMITH,JESSICA,NULL,Female,Caucasian,02/09/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55136,62739,56927,PRETRIAL,JOhnson,Antwan,Anthony,Male,African-American,12/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +55136,62739,56927,PRETRIAL,JOhnson,Antwan,Anthony,Male,African-American,12/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +55136,62739,56927,PRETRIAL,JOhnson,Antwan,Anthony,Male,African-American,12/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55138,62741,56929,PRETRIAL,Calvet,Raul,Diaz,Male,Caucasian,04/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/29/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +55138,62741,56929,PRETRIAL,Calvet,Raul,Diaz,Male,Caucasian,04/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +55138,62741,56929,PRETRIAL,Calvet,Raul,Diaz,Male,Caucasian,04/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/29/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55143,62748,56935,PRETRIAL,RICKS,MALCOLM,NULL,Male,African-American,09/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +55143,62748,56935,PRETRIAL,RICKS,MALCOLM,NULL,Male,African-American,09/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +55143,62748,56935,PRETRIAL,RICKS,MALCOLM,NULL,Male,African-American,09/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55153,62762,56948,Probation,Cheeseboro,Chaz,NULL,Male,African-American,01/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +55153,62762,56948,Probation,Cheeseboro,Chaz,NULL,Male,African-American,01/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +55153,62762,56948,Probation,Cheeseboro,Chaz,NULL,Male,African-American,01/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +30669,62783,56967,PRETRIAL,MYERS,JEFFREY,HENRY,Male,Caucasian,03/02/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/29/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +30669,62783,56967,PRETRIAL,MYERS,JEFFREY,HENRY,Male,Caucasian,03/02/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/29/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +30669,62783,56967,PRETRIAL,MYERS,JEFFREY,HENRY,Male,Caucasian,03/02/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55172,62790,56973,Probation,QUIMBLEY,JOSEPH,NULL,Male,African-American,11/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +55172,62790,56973,Probation,QUIMBLEY,JOSEPH,NULL,Male,African-American,11/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +55172,62790,56973,Probation,QUIMBLEY,JOSEPH,NULL,Male,African-American,11/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54393,62797,56023,Probation,navoy,chad,NULL,Male,Caucasian,08/17/79,17,All Scales,Intake,English,Post Sentence,Probation,Separated,5/30/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +54393,62797,56023,Probation,navoy,chad,NULL,Male,Caucasian,08/17/79,17,All Scales,Intake,English,Post Sentence,Probation,Separated,5/30/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +54393,62797,56023,Probation,navoy,chad,NULL,Male,Caucasian,08/17/79,17,All Scales,Intake,English,Post Sentence,Probation,Separated,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +41661,62818,56994,PRETRIAL,Goodman,Zachary,NULL,Male,Caucasian,05/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +41661,62818,56994,PRETRIAL,Goodman,Zachary,NULL,Male,Caucasian,05/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +41661,62818,56994,PRETRIAL,Goodman,Zachary,NULL,Male,Caucasian,05/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55190,62820,56996,Probation,Vargas,Nicolas,NULL,Male,Hispanic,11/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +55190,62820,56996,Probation,Vargas,Nicolas,NULL,Male,Hispanic,11/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +55190,62820,56996,Probation,Vargas,Nicolas,NULL,Male,Hispanic,11/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55179,62804,56982,Probation,Canizalez,Maximo,NULL,Male,Hispanic,11/27/73,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Divorced,5/30/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +55179,62804,56982,Probation,Canizalez,Maximo,NULL,Male,Hispanic,11/27/73,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Divorced,5/30/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +55179,62804,56982,Probation,Canizalez,Maximo,NULL,Male,Hispanic,11/27/73,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Divorced,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55194,62825,57000,Probation,JOHN,JERMAINE,A,Male,African-American,06/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +55194,62825,57000,Probation,JOHN,JERMAINE,A,Male,African-American,06/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +55194,62825,57000,Probation,JOHN,JERMAINE,A,Male,African-American,06/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +43813,62799,56979,PRETRIAL,Blumberg,Franklin,NULL,Male,Caucasian,10/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.18,8,High,New,1,0 +43813,62799,56979,PRETRIAL,Blumberg,Franklin,NULL,Male,Caucasian,10/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +43813,62799,56979,PRETRIAL,Blumberg,Franklin,NULL,Male,Caucasian,10/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55175,62795,56977,Probation,williams,brantil,NULL,Female,African-American,02/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +55175,62795,56977,Probation,williams,brantil,NULL,Female,African-American,02/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,8,High,New,1,0 +55175,62795,56977,Probation,williams,brantil,NULL,Female,African-American,02/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55186,62813,56990,Probation,osullivan,john,NULL,Male,Caucasian,12/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +55186,62813,56990,Probation,osullivan,john,NULL,Male,Caucasian,12/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +55186,62813,56990,Probation,osullivan,john,NULL,Male,Caucasian,12/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55177,62802,56980,Probation,Woods,Patricia,NULL,Female,Caucasian,03/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +55177,62802,56980,Probation,Woods,Patricia,NULL,Female,Caucasian,03/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.87,10,High,New,1,0 +55177,62802,56980,Probation,Woods,Patricia,NULL,Female,Caucasian,03/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +55183,62810,56987,DRRD,Adderley,Michael,NULL,Male,African-American,03/03/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +55183,62810,56987,DRRD,Adderley,Michael,NULL,Male,African-American,03/03/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,6,Medium,New,1,0 +55183,62810,56987,DRRD,Adderley,Michael,NULL,Male,African-American,03/03/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,2,Medium,18,Risk of Failure to Appear,16,1,Low,New,1,0 +55196,62828,57003,Probation,pierre,james,NULL,Male,African-American,10/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +55196,62828,57003,Probation,pierre,james,NULL,Male,African-American,10/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +55196,62828,57003,Probation,pierre,james,NULL,Male,African-American,10/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55174,62794,56976,Probation,Dixon,Johnnie,Lee,Male,African-American,12/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/30/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +55174,62794,56976,Probation,Dixon,Johnnie,Lee,Male,African-American,12/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/30/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +55174,62794,56976,Probation,Dixon,Johnnie,Lee,Male,African-American,12/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55016,62815,56793,Broward County,Newson,Anthony,NULL,Male,African-American,04/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,Copy,1,0 +55016,62815,56793,Broward County,Newson,Anthony,NULL,Male,African-American,04/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,Copy,1,0 +55016,62815,56793,Broward County,Newson,Anthony,NULL,Male,African-American,04/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +55181,62807,56984,Probation,lilly,thomas,f,Male,Caucasian,07/15/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,7,Risk of Violence,-4.54,1,Low,New,1,0 +55181,62807,56984,Probation,lilly,thomas,f,Male,Caucasian,07/15/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +55181,62807,56984,Probation,lilly,thomas,f,Male,Caucasian,07/15/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55173,62803,56981,Broward County,Levy,David,NULL,Male,Caucasian,03/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +55173,62803,56981,Broward County,Levy,David,NULL,Male,Caucasian,03/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +55173,62803,56981,Broward County,Levy,David,NULL,Male,Caucasian,03/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55180,62805,56983,Probation,HENTLEY,LASHANDRA,NULL,Female,African-American,04/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +55180,62805,56983,Probation,HENTLEY,LASHANDRA,NULL,Female,African-American,04/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +55180,62805,56983,Probation,HENTLEY,LASHANDRA,NULL,Female,African-American,04/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55185,62812,56989,Probation,McDonald,Stephen,NULL,Male,Caucasian,04/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +55185,62812,56989,Probation,McDonald,Stephen,NULL,Male,Caucasian,04/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +55185,62812,56989,Probation,McDonald,Stephen,NULL,Male,Caucasian,04/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55195,62826,57001,Probation,Gaskin,Tiara,NULL,Female,African-American,02/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +55195,62826,57001,Probation,Gaskin,Tiara,NULL,Female,African-American,02/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,7,Medium,New,1,0 +55195,62826,57001,Probation,Gaskin,Tiara,NULL,Female,African-American,02/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54638,62800,56335,PRETRIAL,CLARK,ZAYSHA,NULL,Female,African-American,04/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,Copy,1,0 +54638,62800,56335,PRETRIAL,CLARK,ZAYSHA,NULL,Female,African-American,04/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/13 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,Copy,1,0 +54638,62800,56335,PRETRIAL,CLARK,ZAYSHA,NULL,Female,African-American,04/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +55191,62821,56997,Probation,KEELER,STEVEN,NULL,Male,Caucasian,03/04/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/30/13 0:00,2,Medium,7,Risk of Violence,-2.63,2,Low,New,1,0 +55191,62821,56997,Probation,KEELER,STEVEN,NULL,Male,Caucasian,03/04/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +55191,62821,56997,Probation,KEELER,STEVEN,NULL,Male,Caucasian,03/04/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/30/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +10413,62796,9933,PRETRIAL,HARROLD,JIMMIE,NULL,Male,African-American,07/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,Copy,1,0 +10413,62796,9933,PRETRIAL,HARROLD,JIMMIE,NULL,Male,African-American,07/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,Copy,1,0 +10413,62796,9933,PRETRIAL,HARROLD,JIMMIE,NULL,Male,African-American,07/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +55189,62817,56993,Probation,Smith,Antwone,NULL,Male,African-American,01/20/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +55189,62817,56993,Probation,Smith,Antwone,NULL,Male,African-American,01/20/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +55189,62817,56993,Probation,Smith,Antwone,NULL,Male,African-American,01/20/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55192,62822,56998,Probation,Dematos,Altair,NULL,Male,Hispanic,04/10/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/30/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +55192,62822,56998,Probation,Dematos,Altair,NULL,Male,Hispanic,04/10/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/30/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +55192,62822,56998,Probation,Dematos,Altair,NULL,Male,Hispanic,04/10/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55187,62814,56991,Probation,smith,alicia,NULL,Female,Caucasian,03/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/30/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +55187,62814,56991,Probation,smith,alicia,NULL,Female,Caucasian,03/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/30/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +55187,62814,56991,Probation,smith,alicia,NULL,Female,Caucasian,03/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55188,62816,56992,Probation,CONSTANTION,JANET,V,Female,Hispanic,12/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/30/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +55188,62816,56992,Probation,CONSTANTION,JANET,V,Female,Hispanic,12/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/30/13 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +55188,62816,56992,Probation,CONSTANTION,JANET,V,Female,Hispanic,12/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55197,62830,57005,Probation,VARIN,DONNA,M,Female,Caucasian,05/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +55197,62830,57005,Probation,VARIN,DONNA,M,Female,Caucasian,05/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +55197,62830,57005,Probation,VARIN,DONNA,M,Female,Caucasian,05/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +10097,62801,9621,PRETRIAL,SHAW,WILLIAM,NULL,Male,African-American,12/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,Copy,1,0 +10097,62801,9621,PRETRIAL,SHAW,WILLIAM,NULL,Male,African-American,12/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,Copy,1,0 +10097,62801,9621,PRETRIAL,SHAW,WILLIAM,NULL,Male,African-American,12/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +55182,62808,56985,Probation,Lorenz,Jared,NULL,Male,Hispanic,07/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +55182,62808,56985,Probation,Lorenz,Jared,NULL,Male,Hispanic,07/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +55182,62808,56985,Probation,Lorenz,Jared,NULL,Male,Hispanic,07/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +25844,62819,56995,PRETRIAL,MATOS,RICHARD,MAX,Male,Caucasian,12/08/88,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Married,5/30/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +25844,62819,56995,PRETRIAL,MATOS,RICHARD,MAX,Male,Caucasian,12/08/88,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Married,5/30/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +25844,62819,56995,PRETRIAL,MATOS,RICHARD,MAX,Male,Caucasian,12/08/88,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Married,5/30/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55176,62798,56978,Probation,PALUMBO,PATRICK,D,Male,Caucasian,03/07/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/30/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +55176,62798,56978,Probation,PALUMBO,PATRICK,D,Male,Caucasian,03/07/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/30/13 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +55176,62798,56978,Probation,PALUMBO,PATRICK,D,Male,Caucasian,03/07/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +4417,62827,57002,PRETRIAL,Sheffield,Tony,N,Male,African-American,06/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +4417,62827,57002,PRETRIAL,Sheffield,Tony,N,Male,African-American,06/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +4417,62827,57002,PRETRIAL,Sheffield,Tony,N,Male,African-American,06/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52746,62806,54120,Probation,vanbronkhorst,daniel,NULL,Male,Caucasian,05/15/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,Copy,1,0 +52746,62806,54120,Probation,vanbronkhorst,daniel,NULL,Male,Caucasian,05/15/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,Copy,1,0 +52746,62806,54120,Probation,vanbronkhorst,daniel,NULL,Male,Caucasian,05/15/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +55193,62824,56999,PRETRIAL,Blaise,James,NULL,Male,African-American,12/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +55193,62824,56999,PRETRIAL,Blaise,James,NULL,Male,African-American,12/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +55193,62824,56999,PRETRIAL,Blaise,James,NULL,Male,African-American,12/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55199,62832,57007,Probation,McFarlane,Ronald,NULL,Male,Caucasian,10/02/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/31/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +55199,62832,57007,Probation,McFarlane,Ronald,NULL,Male,Caucasian,10/02/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/31/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +55199,62832,57007,Probation,McFarlane,Ronald,NULL,Male,Caucasian,10/02/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/31/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55213,62843,57017,Probation,Beaupre,Daniel,Ramond,Male,Caucasian,03/25/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/31/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +55213,62843,57017,Probation,Beaupre,Daniel,Ramond,Male,Caucasian,03/25/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/31/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +55213,62843,57017,Probation,Beaupre,Daniel,Ramond,Male,Caucasian,03/25/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/31/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55206,62835,57010,PRETRIAL,Rubin,Stuart,NULL,Male,Caucasian,10/24/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/31/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +55206,62835,57010,PRETRIAL,Rubin,Stuart,NULL,Male,Caucasian,10/24/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/31/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +55206,62835,57010,PRETRIAL,Rubin,Stuart,NULL,Male,Caucasian,10/24/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/31/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55209,62837,57012,DRRD,Scott,Bernard,NULL,Male,African-American,11/25/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,New,1,0 +55209,62837,57012,DRRD,Scott,Bernard,NULL,Male,African-American,11/25/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,8,High,New,1,0 +55209,62837,57012,DRRD,Scott,Bernard,NULL,Male,African-American,11/25/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51514,62838,52703,Probation,INGALLS,ANDREW,T,Male,Caucasian,04/21/80,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,5/31/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +51514,62838,52703,Probation,INGALLS,ANDREW,T,Male,Caucasian,04/21/80,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,5/31/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +51514,62838,52703,Probation,INGALLS,ANDREW,T,Male,Caucasian,04/21/80,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,5/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55210,62840,57014,Probation,Vazquez,Cruz,NULL,Male,Hispanic,08/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.15,4,Low,New,1,0 +55210,62840,57014,Probation,Vazquez,Cruz,NULL,Male,Hispanic,08/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +55210,62840,57014,Probation,Vazquez,Cruz,NULL,Male,Hispanic,08/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +55198,62831,57006,Probation,osborn,richard,NULL,Male,Caucasian,01/15/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/31/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +55198,62831,57006,Probation,osborn,richard,NULL,Male,Caucasian,01/15/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/31/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +55198,62831,57006,Probation,osborn,richard,NULL,Male,Caucasian,01/15/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/31/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +48867,62836,57011,PRETRIAL,Spellman,Monique,NULL,Female,African-American,09/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +48867,62836,57011,PRETRIAL,Spellman,Monique,NULL,Female,African-American,09/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +48867,62836,57011,PRETRIAL,Spellman,Monique,NULL,Female,African-American,09/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,9,High,New,1,0 +55201,62834,57009,Probation,Lindsay,Ralford,Floyd,Male,African-American,12/30/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/31/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +55201,62834,57009,Probation,Lindsay,Ralford,Floyd,Male,African-American,12/30/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/31/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +55201,62834,57009,Probation,Lindsay,Ralford,Floyd,Male,African-American,12/30/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/31/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +38616,62839,57013,PRETRIAL,Bugress,Katrina,NULL,Female,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +38616,62839,57013,PRETRIAL,Bugress,Katrina,NULL,Female,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,9,High,New,1,0 +38616,62839,57013,PRETRIAL,Bugress,Katrina,NULL,Female,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55211,62841,57015,PRETRIAL,King,Dalonnte,NULL,Male,African-American,01/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/31/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +55211,62841,57015,PRETRIAL,King,Dalonnte,NULL,Male,African-American,01/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/31/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +55211,62841,57015,PRETRIAL,King,Dalonnte,NULL,Male,African-American,01/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/31/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54754,62848,56462,PRETRIAL,Martorano,Joseph,NULL,Male,Caucasian,07/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,Copy,1,0 +54754,62848,56462,PRETRIAL,Martorano,Joseph,NULL,Male,Caucasian,07/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,Copy,1,0 +54754,62848,56462,PRETRIAL,Martorano,Joseph,NULL,Male,Caucasian,07/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +55232,62869,57040,Probation,page,travis,NULL,Male,Caucasian,09/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,New,1,0 +55232,62869,57040,Probation,page,travis,NULL,Male,Caucasian,09/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +55232,62869,57040,Probation,page,travis,NULL,Male,Caucasian,09/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +33718,62876,57047,PRETRIAL,gayle,keisha,NULL,Female,African-American,12/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +33718,62876,57047,PRETRIAL,gayle,keisha,NULL,Female,African-American,12/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +33718,62876,57047,PRETRIAL,gayle,keisha,NULL,Female,African-American,12/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +46920,62883,57054,PRETRIAL,Altman,Gary,Ronald,Male,Hispanic,06/18/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +46920,62883,57054,PRETRIAL,Altman,Gary,Ronald,Male,Hispanic,06/18/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,4,High,8,Risk of Recidivism,0.32,9,High,New,1,0 +46920,62883,57054,PRETRIAL,Altman,Gary,Ronald,Male,Hispanic,06/18/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +51728,62864,52951,Probation,Oneill,Carol,NULL,Female,Caucasian,10/27/60,17,All Scales,Intake,English,Post Sentence,Probation,Married,6/3/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +51728,62864,52951,Probation,Oneill,Carol,NULL,Female,Caucasian,10/27/60,17,All Scales,Intake,English,Post Sentence,Probation,Married,6/3/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +51728,62864,52951,Probation,Oneill,Carol,NULL,Female,Caucasian,10/27/60,17,All Scales,Intake,English,Post Sentence,Probation,Married,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +33909,62855,57028,PRETRIAL,MOHAMMED,FAZEED,NULL,Male,Caucasian,09/25/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +33909,62855,57028,PRETRIAL,MOHAMMED,FAZEED,NULL,Male,Caucasian,09/25/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +33909,62855,57028,PRETRIAL,MOHAMMED,FAZEED,NULL,Male,Caucasian,09/25/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55230,62867,57038,Probation,Jonas,Raymond,NULL,Male,African-American,03/24/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +55230,62867,57038,Probation,Jonas,Raymond,NULL,Male,African-American,03/24/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +55230,62867,57038,Probation,Jonas,Raymond,NULL,Male,African-American,03/24/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +46487,62881,57052,PRETRIAL,Christine,Hughes-Stoll,NULL,Female,African-American,05/20/65,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/3/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +46487,62881,57052,PRETRIAL,Christine,Hughes-Stoll,NULL,Female,African-American,05/20/65,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/3/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +46487,62881,57052,PRETRIAL,Christine,Hughes-Stoll,NULL,Female,African-American,05/20/65,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55222,62857,57030,PRETRIAL,GONZALEZ,JAZMIN,NULL,Female,Hispanic,10/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +55222,62857,57030,PRETRIAL,GONZALEZ,JAZMIN,NULL,Female,Hispanic,10/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +55222,62857,57030,PRETRIAL,GONZALEZ,JAZMIN,NULL,Female,Hispanic,10/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55217,62849,57022,Probation,Nieves,Norberto,NULL,Male,Hispanic,01/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +55217,62849,57022,Probation,Nieves,Norberto,NULL,Male,Hispanic,01/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +55217,62849,57022,Probation,Nieves,Norberto,NULL,Male,Hispanic,01/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55238,62878,57049,Probation,Michelson,Kyle,David,Male,Caucasian,02/08/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +55238,62878,57049,Probation,Michelson,Kyle,David,Male,Caucasian,02/08/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.97,10,High,New,1,0 +55238,62878,57049,Probation,Michelson,Kyle,David,Male,Caucasian,02/08/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +24642,62873,57044,DRRD,McWhite,Albert,NULL,Male,African-American,01/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +24642,62873,57044,DRRD,McWhite,Albert,NULL,Male,African-American,01/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,4,High,8,Risk of Recidivism,0.24,8,High,New,1,0 +24642,62873,57044,DRRD,McWhite,Albert,NULL,Male,African-American,01/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,4,High,18,Risk of Failure to Appear,35,10,High,New,1,0 +55218,62852,57025,PRETRIAL,robinson,james,NULL,Male,African-American,08/19/93,17,All Scales,Intake,English,Post Sentence,Residential Program,Single,6/3/13 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +55218,62852,57025,PRETRIAL,robinson,james,NULL,Male,African-American,08/19/93,17,All Scales,Intake,English,Post Sentence,Residential Program,Single,6/3/13 0:00,4,High,8,Risk of Recidivism,0.7,10,High,New,1,0 +55218,62852,57025,PRETRIAL,robinson,james,NULL,Male,African-American,08/19/93,17,All Scales,Intake,English,Post Sentence,Residential Program,Single,6/3/13 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +55240,62880,57051,Probation,Daleo,Francesco,NULL,Male,Caucasian,02/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +55240,62880,57051,Probation,Daleo,Francesco,NULL,Male,Caucasian,02/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +55240,62880,57051,Probation,Daleo,Francesco,NULL,Male,Caucasian,02/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55216,62847,57021,PRETRIAL,LOPEZ,SILVIO,NULL,Male,Hispanic,11/10/51,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +55216,62847,57021,PRETRIAL,LOPEZ,SILVIO,NULL,Male,Hispanic,11/10/51,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +55216,62847,57021,PRETRIAL,LOPEZ,SILVIO,NULL,Male,Hispanic,11/10/51,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55225,62861,57033,Probation,Wilson,Reginald,Labruce,Male,African-American,11/04/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.65,2,Low,New,1,0 +55225,62861,57033,Probation,Wilson,Reginald,Labruce,Male,African-American,11/04/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +55225,62861,57033,Probation,Wilson,Reginald,Labruce,Male,African-American,11/04/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55220,62854,57027,Probation,Chin,Anthony,NULL,Male,African-American,02/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +55220,62854,57027,Probation,Chin,Anthony,NULL,Male,African-American,02/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +55220,62854,57027,Probation,Chin,Anthony,NULL,Male,African-American,02/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55236,62875,57046,Probation,Pigatt,Dino,Lamart,Male,African-American,05/17/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +55236,62875,57046,Probation,Pigatt,Dino,Lamart,Male,African-American,05/17/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +55236,62875,57046,Probation,Pigatt,Dino,Lamart,Male,African-American,05/17/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +12418,62882,57053,PRETRIAL,JOSEPH,JUDE,NULL,Male,African-American,08/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +12418,62882,57053,PRETRIAL,JOSEPH,JUDE,NULL,Male,African-American,08/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +12418,62882,57053,PRETRIAL,JOSEPH,JUDE,NULL,Male,African-American,08/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55234,62872,57043,PRETRIAL,Burks,Edward,NULL,Male,Caucasian,12/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +55234,62872,57043,PRETRIAL,Burks,Edward,NULL,Male,Caucasian,12/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +55234,62872,57043,PRETRIAL,Burks,Edward,NULL,Male,Caucasian,12/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +32337,62859,44509,Probation,Lamour,Frantz,NULL,Male,African-American,01/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.52,3,Low,Copy,1,0 +32337,62859,44509,Probation,Lamour,Frantz,NULL,Male,African-American,01/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,Copy,1,0 +32337,62859,44509,Probation,Lamour,Frantz,NULL,Male,African-American,01/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +55231,62868,57039,Probation,McKissick,William,J,Male,Caucasian,02/12/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +55231,62868,57039,Probation,McKissick,William,J,Male,Caucasian,02/12/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +55231,62868,57039,Probation,McKissick,William,J,Male,Caucasian,02/12/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55221,62856,57029,PRETRIAL,TIPPETT,CHRISTOPHER,NULL,Male,Caucasian,03/21/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +55221,62856,57029,PRETRIAL,TIPPETT,CHRISTOPHER,NULL,Male,Caucasian,03/21/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +55221,62856,57029,PRETRIAL,TIPPETT,CHRISTOPHER,NULL,Male,Caucasian,03/21/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55237,62877,57048,Probation,Samson,Chenet,NULL,Male,African-American,08/27/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +55237,62877,57048,Probation,Samson,Chenet,NULL,Male,African-American,08/27/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +55237,62877,57048,Probation,Samson,Chenet,NULL,Male,African-American,08/27/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +3509,62851,57024,PRETRIAL,Harris,Ramon,K,Male,African-American,07/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +3509,62851,57024,PRETRIAL,Harris,Ramon,K,Male,African-American,07/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +3509,62851,57024,PRETRIAL,Harris,Ramon,K,Male,African-American,07/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55223,62858,57031,PRETRIAL,Veliz,Isabel,NULL,Female,Hispanic,02/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +55223,62858,57031,PRETRIAL,Veliz,Isabel,NULL,Female,Hispanic,02/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +55223,62858,57031,PRETRIAL,Veliz,Isabel,NULL,Female,Hispanic,02/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55239,62879,57050,Probation,Nogueira,Amanda,NULL,Female,Caucasian,03/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/3/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +55239,62879,57050,Probation,Nogueira,Amanda,NULL,Female,Caucasian,03/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/3/13 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +55239,62879,57050,Probation,Nogueira,Amanda,NULL,Female,Caucasian,03/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55229,62866,57037,PRETRIAL,Lee,Jessica,NULL,Female,Caucasian,06/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +55229,62866,57037,PRETRIAL,Lee,Jessica,NULL,Female,Caucasian,06/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/13 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +55229,62866,57037,PRETRIAL,Lee,Jessica,NULL,Female,Caucasian,06/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55219,62853,57026,Probation,irving,dennis,NULL,Male,African-American,07/13/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/3/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +55219,62853,57026,Probation,irving,dennis,NULL,Male,African-American,07/13/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/3/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +55219,62853,57026,Probation,irving,dennis,NULL,Male,African-American,07/13/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55235,62874,57045,Probation,Tyler,Frenchi,B,Female,African-American,05/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +55235,62874,57045,Probation,Tyler,Frenchi,B,Female,African-American,05/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +55235,62874,57045,Probation,Tyler,Frenchi,B,Female,African-American,05/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/3/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55248,62895,57064,PRETRIAL,RIVAS,LIZZETHE,NULL,Female,Hispanic,01/26/83,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,6/4/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +55248,62895,57064,PRETRIAL,RIVAS,LIZZETHE,NULL,Female,Hispanic,01/26/83,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,6/4/13 0:00,1,Low,8,Risk of Recidivism,-1.43,2,Low,New,1,0 +55248,62895,57064,PRETRIAL,RIVAS,LIZZETHE,NULL,Female,Hispanic,01/26/83,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55252,62900,57069,Probation,spence,tmara,NULL,Female,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +55252,62900,57069,Probation,spence,tmara,NULL,Female,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,4,High,8,Risk of Recidivism,0.81,10,High,New,1,0 +55252,62900,57069,Probation,spence,tmara,NULL,Female,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,4,High,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +49869,62893,57062,PRETRIAL,HEATH,DERRIK,WESTLEY,Male,Caucasian,06/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +49869,62893,57062,PRETRIAL,HEATH,DERRIK,WESTLEY,Male,Caucasian,06/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +49869,62893,57062,PRETRIAL,HEATH,DERRIK,WESTLEY,Male,Caucasian,06/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +37188,62898,57067,PRETRIAL,SHERROD,ROBERT,LEE,Male,African-American,04/10/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.35,3,Low,New,1,0 +37188,62898,57067,PRETRIAL,SHERROD,ROBERT,LEE,Male,African-American,04/10/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +37188,62898,57067,PRETRIAL,SHERROD,ROBERT,LEE,Male,African-American,04/10/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +55244,62889,57059,Probation,GONZALEZ,ALBERTO,ALLEN,Male,Hispanic,10/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/4/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +55244,62889,57059,Probation,GONZALEZ,ALBERTO,ALLEN,Male,Hispanic,10/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/4/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +55244,62889,57059,Probation,GONZALEZ,ALBERTO,ALLEN,Male,Hispanic,10/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55241,62884,57055,PRETRIAL,Silva,Flavio,NULL,Male,Hispanic,08/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/4/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +55241,62884,57055,PRETRIAL,Silva,Flavio,NULL,Male,Hispanic,08/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/4/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +55241,62884,57055,PRETRIAL,Silva,Flavio,NULL,Male,Hispanic,08/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +45250,62903,57072,PRETRIAL,Deleon,Julio,NULL,Male,Hispanic,01/03/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +45250,62903,57072,PRETRIAL,Deleon,Julio,NULL,Male,Hispanic,01/03/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +45250,62903,57072,PRETRIAL,Deleon,Julio,NULL,Male,Hispanic,01/03/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55247,62894,57063,Probation,Venereo,Albert,NULL,Male,Hispanic,12/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +55247,62894,57063,Probation,Venereo,Albert,NULL,Male,Hispanic,12/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +55247,62894,57063,Probation,Venereo,Albert,NULL,Male,Hispanic,12/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55253,62901,57070,Probation,puccio,joseph,NULL,Male,Caucasian,10/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/4/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +55253,62901,57070,Probation,puccio,joseph,NULL,Male,Caucasian,10/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/4/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +55253,62901,57070,Probation,puccio,joseph,NULL,Male,Caucasian,10/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55243,62886,57057,PRETRIAL,Young,Kenneth,NULL,Male,Caucasian,10/31/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +55243,62886,57057,PRETRIAL,Young,Kenneth,NULL,Male,Caucasian,10/31/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +55243,62886,57057,PRETRIAL,Young,Kenneth,NULL,Male,Caucasian,10/31/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +49216,62888,57058,PRETRIAL,Lafontant,Maxymus,M,Male,Other,01/12/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/4/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +49216,62888,57058,PRETRIAL,Lafontant,Maxymus,M,Male,Other,01/12/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/4/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +49216,62888,57058,PRETRIAL,Lafontant,Maxymus,M,Male,Other,01/12/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55249,62896,57065,Probation,Leyva,Humberto,NULL,Male,Hispanic,06/10/65,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/4/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +55249,62896,57065,Probation,Leyva,Humberto,NULL,Male,Hispanic,06/10/65,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/4/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +55249,62896,57065,Probation,Leyva,Humberto,NULL,Male,Hispanic,06/10/65,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +45247,62899,57068,PRETRIAL,Cuellar,Jorge,NULL,Male,Hispanic,04/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +45247,62899,57068,PRETRIAL,Cuellar,Jorge,NULL,Male,Hispanic,04/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +45247,62899,57068,PRETRIAL,Cuellar,Jorge,NULL,Male,Hispanic,04/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +39502,62891,57061,PRETRIAL,Mckenzie,Lipton,NULL,Male,African-American,11/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/4/13 0:00,2,Medium,7,Risk of Violence,-3.32,1,Low,New,1,0 +39502,62891,57061,PRETRIAL,Mckenzie,Lipton,NULL,Male,African-American,11/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +39502,62891,57061,PRETRIAL,Mckenzie,Lipton,NULL,Male,African-American,11/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/4/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55671,63427,57557,PRETRIAL,Smitley,Robert,NULL,Male,Caucasian,03/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/4/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +55671,63427,57557,PRETRIAL,Smitley,Robert,NULL,Male,Caucasian,03/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/4/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +55671,63427,57557,PRETRIAL,Smitley,Robert,NULL,Male,Caucasian,03/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55255,62904,57073,Probation,WISHART,WENDY,RUTH,Female,Caucasian,09/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +55255,62904,57073,Probation,WISHART,WENDY,RUTH,Female,Caucasian,09/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +55255,62904,57073,Probation,WISHART,WENDY,RUTH,Female,Caucasian,09/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55242,62885,57056,Broward County,Farrell,John,NULL,Female,African-American,09/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +55242,62885,57056,Broward County,Farrell,John,NULL,Female,African-American,09/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/13 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +55242,62885,57056,Broward County,Farrell,John,NULL,Female,African-American,09/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55254,62902,57071,Probation,Burke,Riana,NULL,Female,Caucasian,10/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/4/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +55254,62902,57071,Probation,Burke,Riana,NULL,Female,Caucasian,10/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/4/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +55254,62902,57071,Probation,Burke,Riana,NULL,Female,Caucasian,10/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55251,62897,57066,DRRD,Dallas,Frankie,Markale,Male,African-American,08/26/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +55251,62897,57066,DRRD,Dallas,Frankie,Markale,Male,African-American,08/26/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +55251,62897,57066,DRRD,Dallas,Frankie,Markale,Male,African-American,08/26/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/4/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55260,62911,57078,Probation,Gurge,Dorothy,NULL,Female,Caucasian,05/20/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/5/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +55260,62911,57078,Probation,Gurge,Dorothy,NULL,Female,Caucasian,05/20/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/5/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +55260,62911,57078,Probation,Gurge,Dorothy,NULL,Female,Caucasian,05/20/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +48562,62920,57086,PRETRIAL,Casale,Domonick,NULL,Male,Caucasian,04/19/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/5/13 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +48562,62920,57086,PRETRIAL,Casale,Domonick,NULL,Male,Caucasian,04/19/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/5/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +48562,62920,57086,PRETRIAL,Casale,Domonick,NULL,Male,Caucasian,04/19/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55263,62918,57084,Probation,Smith,Kenisha,NULL,Female,African-American,12/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +55263,62918,57084,Probation,Smith,Kenisha,NULL,Female,African-American,12/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +55263,62918,57084,Probation,Smith,Kenisha,NULL,Female,African-American,12/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55267,62923,57089,Probation,Grieco,Justin,NULL,Male,Caucasian,06/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +55267,62923,57089,Probation,Grieco,Justin,NULL,Male,Caucasian,06/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +55267,62923,57089,Probation,Grieco,Justin,NULL,Male,Caucasian,06/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54823,62906,56544,PRETRIAL,Fleuridor,Renand,NULL,Male,African-American,12/08/81,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,Copy,1,0 +54823,62906,56544,PRETRIAL,Fleuridor,Renand,NULL,Male,African-American,12/08/81,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,Copy,1,0 +54823,62906,56544,PRETRIAL,Fleuridor,Renand,NULL,Male,African-American,12/08/81,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +55269,62925,57091,PRETRIAL,Boulet,Jennifer,NULL,Female,Caucasian,09/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +55269,62925,57091,PRETRIAL,Boulet,Jennifer,NULL,Female,Caucasian,09/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +55269,62925,57091,PRETRIAL,Boulet,Jennifer,NULL,Female,Caucasian,09/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55262,62917,57083,PRETRIAL,Crumpler,Shanti,NULL,Male,African-American,11/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +55262,62917,57083,PRETRIAL,Crumpler,Shanti,NULL,Male,African-American,11/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +55262,62917,57083,PRETRIAL,Crumpler,Shanti,NULL,Male,African-American,11/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55266,62922,57088,Probation,SMALL,SHANSE,NULL,Male,African-American,03/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/5/13 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +55266,62922,57088,Probation,SMALL,SHANSE,NULL,Male,African-American,03/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/5/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +55266,62922,57088,Probation,SMALL,SHANSE,NULL,Male,African-American,03/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55256,62907,57074,Probation,ALLEN,MARCUS,NULL,Male,African-American,06/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +55256,62907,57074,Probation,ALLEN,MARCUS,NULL,Male,African-American,06/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +55256,62907,57074,Probation,ALLEN,MARCUS,NULL,Male,African-American,06/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55258,62909,57076,Probation,JAGROOP,SAMANTHA,D,Female,Other,01/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +55258,62909,57076,Probation,JAGROOP,SAMANTHA,D,Female,Other,01/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +55258,62909,57076,Probation,JAGROOP,SAMANTHA,D,Female,Other,01/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55261,62915,57081,Probation,Nunes,Kadeem,NULL,Male,African-American,09/08/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/5/13 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +55261,62915,57081,Probation,Nunes,Kadeem,NULL,Male,African-American,09/08/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/5/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +55261,62915,57081,Probation,Nunes,Kadeem,NULL,Male,African-American,09/08/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55273,62930,57096,Probation,Watson,Careem,NULL,Male,African-American,09/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +55273,62930,57096,Probation,Watson,Careem,NULL,Male,African-American,09/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +55273,62930,57096,Probation,Watson,Careem,NULL,Male,African-American,09/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54823,62905,56544,PRETRIAL,Fleuridor,Renand,NULL,Male,African-American,12/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,Copy,1,0 +54823,62905,56544,PRETRIAL,Fleuridor,Renand,NULL,Male,African-American,12/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,Copy,1,0 +54823,62905,56544,PRETRIAL,Fleuridor,Renand,NULL,Male,African-American,12/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +28146,62912,57079,PRETRIAL,ROSS,THELMA,NULL,Female,Caucasian,11/11/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/5/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +28146,62912,57079,PRETRIAL,ROSS,THELMA,NULL,Female,Caucasian,11/11/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/5/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +28146,62912,57079,PRETRIAL,ROSS,THELMA,NULL,Female,Caucasian,11/11/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55270,62926,57092,Probation,Sophin,Michael,NULL,Male,Caucasian,04/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +55270,62926,57092,Probation,Sophin,Michael,NULL,Male,Caucasian,04/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +55270,62926,57092,Probation,Sophin,Michael,NULL,Male,Caucasian,04/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55264,62919,57085,Probation,Manuel,Marc,NULL,Male,African-American,07/23/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/5/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +55264,62919,57085,Probation,Manuel,Marc,NULL,Male,African-American,07/23/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/5/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +55264,62919,57085,Probation,Manuel,Marc,NULL,Male,African-American,07/23/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55259,62910,57077,PRETRIAL,Butler,Cori,NULL,Male,African-American,07/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +55259,62910,57077,PRETRIAL,Butler,Cori,NULL,Male,African-American,07/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +55259,62910,57077,PRETRIAL,Butler,Cori,NULL,Male,African-American,07/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53652,62914,55113,Probation,schindler,joseph,NULL,Male,Caucasian,12/03/68,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,Copy,1,0 +53652,62914,55113,Probation,schindler,joseph,NULL,Male,Caucasian,12/03/68,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,Copy,1,0 +53652,62914,55113,Probation,schindler,joseph,NULL,Male,Caucasian,12/03/68,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +55268,62924,57090,PRETRIAL,McCaffery,Melissa,NULL,Female,Caucasian,06/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/5/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +55268,62924,57090,PRETRIAL,McCaffery,Melissa,NULL,Female,Caucasian,06/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/5/13 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +55268,62924,57090,PRETRIAL,McCaffery,Melissa,NULL,Female,Caucasian,06/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55275,62931,57097,Probation,Stupart,Nichole,Andrea,Female,African-American,01/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +55275,62931,57097,Probation,Stupart,Nichole,Andrea,Female,African-American,01/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +55275,62931,57097,Probation,Stupart,Nichole,Andrea,Female,African-American,01/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55265,62921,57087,PRETRIAL,Fetters,Jeffery,NULL,Male,Caucasian,07/18/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +55265,62921,57087,PRETRIAL,Fetters,Jeffery,NULL,Male,Caucasian,07/18/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +55265,62921,57087,PRETRIAL,Fetters,Jeffery,NULL,Male,Caucasian,07/18/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +36071,62913,57080,PRETRIAL,Walters,Tyler,NULL,Male,Caucasian,12/01/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/5/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +36071,62913,57080,PRETRIAL,Walters,Tyler,NULL,Male,Caucasian,12/01/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/5/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +36071,62913,57080,PRETRIAL,Walters,Tyler,NULL,Male,Caucasian,12/01/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55274,62929,57095,Probation,SCREEN,RODERICK,NULL,Male,African-American,04/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +55274,62929,57095,Probation,SCREEN,RODERICK,NULL,Male,African-American,04/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +55274,62929,57095,Probation,SCREEN,RODERICK,NULL,Male,African-American,04/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +30808,62916,57082,Probation,kennedy,gregory,NULL,Male,African-American,03/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +30808,62916,57082,Probation,kennedy,gregory,NULL,Male,African-American,03/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +30808,62916,57082,Probation,kennedy,gregory,NULL,Male,African-American,03/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55287,62950,57115,Probation,summers,robin,NULL,Female,Caucasian,06/15/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +55287,62950,57115,Probation,summers,robin,NULL,Female,Caucasian,06/15/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +55287,62950,57115,Probation,summers,robin,NULL,Female,Caucasian,06/15/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +33431,62937,57102,PRETRIAL,Rodriguez,Dennis,NULL,Male,Hispanic,03/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +33431,62937,57102,PRETRIAL,Rodriguez,Dennis,NULL,Male,Hispanic,03/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +33431,62937,57102,PRETRIAL,Rodriguez,Dennis,NULL,Male,Hispanic,03/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55289,62952,57117,PRETRIAL,Gouldboarne,David,NULL,Male,African-American,11/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +55289,62952,57117,PRETRIAL,Gouldboarne,David,NULL,Male,African-American,11/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +55289,62952,57117,PRETRIAL,Gouldboarne,David,NULL,Male,African-American,11/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55282,62944,57109,Probation,mendoza,alejandro,NULL,Male,Hispanic,02/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/6/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +55282,62944,57109,Probation,mendoza,alejandro,NULL,Male,Hispanic,02/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/6/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +55282,62944,57109,Probation,mendoza,alejandro,NULL,Male,Hispanic,02/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55294,62958,57123,Probation,Lopez,myrtis,NULL,Female,African-American,02/11/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +55294,62958,57123,Probation,Lopez,myrtis,NULL,Female,African-American,02/11/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +55294,62958,57123,Probation,Lopez,myrtis,NULL,Female,African-American,02/11/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55298,62965,57130,PRETRIAL,Hepburn,Derrick,NULL,Male,African-American,03/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +55298,62965,57130,PRETRIAL,Hepburn,Derrick,NULL,Male,African-American,03/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +55298,62965,57130,PRETRIAL,Hepburn,Derrick,NULL,Male,African-American,03/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +6207,62963,57128,PRETRIAL,MULHALL,STEVEN,PATRICK,Male,Caucasian,12/07/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +6207,62963,57128,PRETRIAL,MULHALL,STEVEN,PATRICK,Male,Caucasian,12/07/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +6207,62963,57128,PRETRIAL,MULHALL,STEVEN,PATRICK,Male,Caucasian,12/07/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +49955,62942,57107,PRETRIAL,ADME,JEAN,DEQUANS,Male,African-American,02/23/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +49955,62942,57107,PRETRIAL,ADME,JEAN,DEQUANS,Male,African-American,02/23/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +49955,62942,57107,PRETRIAL,ADME,JEAN,DEQUANS,Male,African-American,02/23/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +3461,62960,57125,PRETRIAL,richardson,jonathan,joell,Male,African-American,11/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,New,1,0 +3461,62960,57125,PRETRIAL,richardson,jonathan,joell,Male,African-American,11/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +3461,62960,57125,PRETRIAL,richardson,jonathan,joell,Male,African-American,11/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55292,62955,57120,Probation,Robinson,Tavarius,NULL,Male,African-American,11/08/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +55292,62955,57120,Probation,Robinson,Tavarius,NULL,Male,African-American,11/08/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +55292,62955,57120,Probation,Robinson,Tavarius,NULL,Male,African-American,11/08/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +45075,62934,57099,PRETRIAL,Thomas,Dwayne,Dillino,Male,African-American,09/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +45075,62934,57099,PRETRIAL,Thomas,Dwayne,Dillino,Male,African-American,09/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +45075,62934,57099,PRETRIAL,Thomas,Dwayne,Dillino,Male,African-American,09/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44253,62949,57114,PRETRIAL,Eldemire,Jason,NULL,Male,African-American,09/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +44253,62949,57114,PRETRIAL,Eldemire,Jason,NULL,Male,African-American,09/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +44253,62949,57114,PRETRIAL,Eldemire,Jason,NULL,Male,African-American,09/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +2543,62966,57131,DRRD,Ervin,Latavious,Shwon,Male,African-American,06/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +2543,62966,57131,DRRD,Ervin,Latavious,Shwon,Male,African-American,06/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +2543,62966,57131,DRRD,Ervin,Latavious,Shwon,Male,African-American,06/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +55276,62933,57098,PRETRIAL,Gonzalez,Margarita,NULL,Female,Hispanic,11/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/6/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +55276,62933,57098,PRETRIAL,Gonzalez,Margarita,NULL,Female,Hispanic,11/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +55276,62933,57098,PRETRIAL,Gonzalez,Margarita,NULL,Female,Hispanic,11/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +42990,62940,57105,PRETRIAL,Blane,Alysse,NULL,Female,Caucasian,06/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +42990,62940,57105,PRETRIAL,Blane,Alysse,NULL,Female,Caucasian,06/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +42990,62940,57105,PRETRIAL,Blane,Alysse,NULL,Female,Caucasian,06/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55285,62947,57112,Probation,salinas,jose,NULL,Male,Hispanic,10/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +55285,62947,57112,Probation,salinas,jose,NULL,Male,Hispanic,10/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +55285,62947,57112,Probation,salinas,jose,NULL,Male,Hispanic,10/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55296,62961,57126,Probation,smith,herbert,NULL,Male,African-American,11/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +55296,62961,57126,Probation,smith,herbert,NULL,Male,African-American,11/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +55296,62961,57126,Probation,smith,herbert,NULL,Male,African-American,11/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55291,62954,57119,Probation,tidwell,george,NULL,Male,Caucasian,05/30/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +55291,62954,57119,Probation,tidwell,george,NULL,Male,Caucasian,05/30/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +55291,62954,57119,Probation,tidwell,george,NULL,Male,Caucasian,05/30/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55288,62951,57116,Probation,Jones,Johhnt,Lee,Male,African-American,10/13/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/13 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +55288,62951,57116,Probation,Jones,Johhnt,Lee,Male,African-American,10/13/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +55288,62951,57116,Probation,Jones,Johhnt,Lee,Male,African-American,10/13/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55281,62943,57108,Probation,Deatley,Paul,NULL,Male,Caucasian,08/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +55281,62943,57108,Probation,Deatley,Paul,NULL,Male,Caucasian,08/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +55281,62943,57108,Probation,Deatley,Paul,NULL,Male,Caucasian,08/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55277,62935,57100,Probation,Jordan,Mildred,NULL,Female,Caucasian,11/20/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +55277,62935,57100,Probation,Jordan,Mildred,NULL,Female,Caucasian,11/20/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +55277,62935,57100,Probation,Jordan,Mildred,NULL,Female,Caucasian,11/20/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +47369,62956,57121,PRETRIAL,Jaiseri,Vishnudat,NULL,Male,Other,10/12/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,7,Risk of Violence,-4.29,1,Low,New,1,0 +47369,62956,57121,PRETRIAL,Jaiseri,Vishnudat,NULL,Male,Other,10/12/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +47369,62956,57121,PRETRIAL,Jaiseri,Vishnudat,NULL,Male,Other,10/12/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55299,62967,57132,Probation,VELASQUEZ,CRISTHEL,NULL,Female,Hispanic,08/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +55299,62967,57132,Probation,VELASQUEZ,CRISTHEL,NULL,Female,Hispanic,08/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +55299,62967,57132,Probation,VELASQUEZ,CRISTHEL,NULL,Female,Hispanic,08/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55284,62946,57111,Probation,MORALES,BARBARA,ANN,Female,Caucasian,05/30/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/6/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +55284,62946,57111,Probation,MORALES,BARBARA,ANN,Female,Caucasian,05/30/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +55284,62946,57111,Probation,MORALES,BARBARA,ANN,Female,Caucasian,05/30/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +32055,62964,57129,Probation,cribas,brian,NULL,Male,Hispanic,07/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +32055,62964,57129,Probation,cribas,brian,NULL,Male,Hispanic,07/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +32055,62964,57129,Probation,cribas,brian,NULL,Male,Hispanic,07/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55295,62959,57124,Probation,Aparicio,Francisco,NULL,Male,Hispanic,02/01/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +55295,62959,57124,Probation,Aparicio,Francisco,NULL,Male,Hispanic,02/01/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +55295,62959,57124,Probation,Aparicio,Francisco,NULL,Male,Hispanic,02/01/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54860,62932,56594,PRETRIAL,Peele,Bennie,NULL,Male,African-American,09/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/6/13 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,Copy,1,0 +54860,62932,56594,PRETRIAL,Peele,Bennie,NULL,Male,African-American,09/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/6/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,Copy,1,0 +54860,62932,56594,PRETRIAL,Peele,Bennie,NULL,Male,African-American,09/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +55293,62957,57122,Probation,Cuevas,Johnny,NULL,Male,Hispanic,03/20/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +55293,62957,57122,Probation,Cuevas,Johnny,NULL,Male,Hispanic,03/20/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +55293,62957,57122,Probation,Cuevas,Johnny,NULL,Male,Hispanic,03/20/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55278,62936,57101,PRETRIAL,DAY,WILLIAM,NULL,Male,African-American,07/26/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +55278,62936,57101,PRETRIAL,DAY,WILLIAM,NULL,Male,African-American,07/26/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +55278,62936,57101,PRETRIAL,DAY,WILLIAM,NULL,Male,African-American,07/26/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55290,62953,57118,Probation,menon,siju,NULL,Male,Asian,06/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +55290,62953,57118,Probation,menon,siju,NULL,Male,Asian,06/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +55290,62953,57118,Probation,menon,siju,NULL,Male,Asian,06/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55286,62948,57113,Probation,KONG,RICHARD,G,Male,African-American,09/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +55286,62948,57113,Probation,KONG,RICHARD,G,Male,African-American,09/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,4,High,8,Risk of Recidivism,1.06,10,High,New,1,0 +55286,62948,57113,Probation,KONG,RICHARD,G,Male,African-American,09/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +42435,62939,57104,PRETRIAL,KAKONIKOS,XRISTAL,NULL,Female,Caucasian,03/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +42435,62939,57104,PRETRIAL,KAKONIKOS,XRISTAL,NULL,Female,Caucasian,03/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +42435,62939,57104,PRETRIAL,KAKONIKOS,XRISTAL,NULL,Female,Caucasian,03/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55297,62962,57127,Probation,oliver,melneisha,NULL,Female,African-American,08/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,New,1,0 +55297,62962,57127,Probation,oliver,melneisha,NULL,Female,African-American,08/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,8,High,New,1,0 +55297,62962,57127,Probation,oliver,melneisha,NULL,Female,African-American,08/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55306,62976,57141,PRETRIAL,FIGUEROA,ELSIE,NULL,Female,Hispanic,03/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/7/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +55306,62976,57141,PRETRIAL,FIGUEROA,ELSIE,NULL,Female,Hispanic,03/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +55306,62976,57141,PRETRIAL,FIGUEROA,ELSIE,NULL,Female,Hispanic,03/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/7/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +55301,62969,57134,Probation,Payakachat,Wachira,NULL,Male,Asian,01/21/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/7/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +55301,62969,57134,Probation,Payakachat,Wachira,NULL,Male,Asian,01/21/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/7/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +55301,62969,57134,Probation,Payakachat,Wachira,NULL,Male,Asian,01/21/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55305,62974,57139,Probation,Ospina,Luis,E,Male,Hispanic,02/06/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/7/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +55305,62974,57139,Probation,Ospina,Luis,E,Male,Hispanic,02/06/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/7/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +55305,62974,57139,Probation,Ospina,Luis,E,Male,Hispanic,02/06/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55319,62992,57156,Probation,Weiner,Richard,NULL,Male,Caucasian,06/30/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/7/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +55319,62992,57156,Probation,Weiner,Richard,NULL,Male,Caucasian,06/30/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/7/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +55319,62992,57156,Probation,Weiner,Richard,NULL,Male,Caucasian,06/30/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55308,62978,57143,Probation,monge-silva,deborah,NULL,Female,Hispanic,10/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/7/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +55308,62978,57143,Probation,monge-silva,deborah,NULL,Female,Hispanic,10/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/7/13 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +55308,62978,57143,Probation,monge-silva,deborah,NULL,Female,Hispanic,10/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +55321,62995,57158,Probation,charlot,jimmy,NULL,Male,African-American,04/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/7/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +55321,62995,57158,Probation,charlot,jimmy,NULL,Male,African-American,04/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/7/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +55321,62995,57158,Probation,charlot,jimmy,NULL,Male,African-American,04/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55320,62993,57157,Probation,Peralta,Melvin,De Jesus,Male,Hispanic,06/12/84,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/7/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +55320,62993,57157,Probation,Peralta,Melvin,De Jesus,Male,Hispanic,06/12/84,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/7/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +55320,62993,57157,Probation,Peralta,Melvin,De Jesus,Male,Hispanic,06/12/84,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55303,62972,57137,Probation,Tynes,Tenesia,Sade,Female,African-American,07/21/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/7/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +55303,62972,57137,Probation,Tynes,Tenesia,Sade,Female,African-American,07/21/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/7/13 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +55303,62972,57137,Probation,Tynes,Tenesia,Sade,Female,African-American,07/21/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55307,62977,57142,Probation,Anderson,Markland,NULL,Male,African-American,09/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +55307,62977,57142,Probation,Anderson,Markland,NULL,Male,African-American,09/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +55307,62977,57142,Probation,Anderson,Markland,NULL,Male,African-American,09/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55313,62985,57150,Probation,Naing,Maung,NULL,Male,Oriental,12/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/7/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +55313,62985,57150,Probation,Naing,Maung,NULL,Male,Oriental,12/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/7/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +55313,62985,57150,Probation,Naing,Maung,NULL,Male,Oriental,12/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55317,62988,57153,Probation,SLADE,TRAVIS,NULL,Male,African-American,04/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +55317,62988,57153,Probation,SLADE,TRAVIS,NULL,Male,African-American,04/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +55317,62988,57153,Probation,SLADE,TRAVIS,NULL,Male,African-American,04/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +34446,62980,57145,PRETRIAL,Smith,Synteria,NULL,Female,African-American,12/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.99,4,Low,New,1,0 +34446,62980,57145,PRETRIAL,Smith,Synteria,NULL,Female,African-American,12/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,8,High,New,1,0 +34446,62980,57145,PRETRIAL,Smith,Synteria,NULL,Female,African-American,12/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +49856,62975,57140,PRETRIAL,MONTGOMERY,DARAL,NULL,Male,African-American,02/21/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,4,High,7,Risk of Violence,-0.54,10,High,New,1,0 +49856,62975,57140,PRETRIAL,MONTGOMERY,DARAL,NULL,Male,African-American,02/21/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,4,High,8,Risk of Recidivism,0.42,9,High,New,1,0 +49856,62975,57140,PRETRIAL,MONTGOMERY,DARAL,NULL,Male,African-American,02/21/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55311,62982,57147,Probation,DAVIS,THERESA,NULL,Female,Caucasian,05/29/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +55311,62982,57147,Probation,DAVIS,THERESA,NULL,Female,Caucasian,05/29/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +55311,62982,57147,Probation,DAVIS,THERESA,NULL,Female,Caucasian,05/29/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55314,62984,57149,PRETRIAL,Peterson,Timothy,NULL,Male,Caucasian,09/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/7/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +55314,62984,57149,PRETRIAL,Peterson,Timothy,NULL,Male,Caucasian,09/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/7/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +55314,62984,57149,PRETRIAL,Peterson,Timothy,NULL,Male,Caucasian,09/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55318,62991,57155,Probation,Vassor Stewart,Amy,NULL,Female,African-American,06/04/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/7/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +55318,62991,57155,Probation,Vassor Stewart,Amy,NULL,Female,African-American,06/04/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/7/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +55318,62991,57155,Probation,Vassor Stewart,Amy,NULL,Female,African-American,06/04/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55316,62987,57152,Probation,MORAN,PAUL,NULL,Male,Caucasian,11/14/90,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,6/7/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +55316,62987,57152,Probation,MORAN,PAUL,NULL,Male,Caucasian,11/14/90,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,6/7/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +55316,62987,57152,Probation,MORAN,PAUL,NULL,Male,Caucasian,11/14/90,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55322,62996,57159,Probation,Beasley,Tanisha,NULL,Female,African-American,06/27/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +55322,62996,57159,Probation,Beasley,Tanisha,NULL,Female,African-American,06/27/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.07,8,High,New,1,0 +55322,62996,57159,Probation,Beasley,Tanisha,NULL,Female,African-American,06/27/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55300,62968,57133,Probation,Standifer,Roosevelt,NULL,Male,African-American,01/07/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.83,2,Low,New,1,0 +55300,62968,57133,Probation,Standifer,Roosevelt,NULL,Male,African-American,01/07/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +55300,62968,57133,Probation,Standifer,Roosevelt,NULL,Male,African-American,01/07/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55310,62981,57146,Probation,Hall,Jennifer,Gail,Female,Caucasian,01/15/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/7/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +55310,62981,57146,Probation,Hall,Jennifer,Gail,Female,Caucasian,01/15/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/7/13 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +55310,62981,57146,Probation,Hall,Jennifer,Gail,Female,Caucasian,01/15/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55309,62979,57144,Probation,Caruso,Tara,NULL,Female,Caucasian,03/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +55309,62979,57144,Probation,Caruso,Tara,NULL,Female,Caucasian,03/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +55309,62979,57144,Probation,Caruso,Tara,NULL,Female,Caucasian,03/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +29143,62994,44652,Probation,Walker,Jonathan,Jamal,Male,African-American,09/05/90,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,Copy,1,0 +29143,62994,44652,Probation,Walker,Jonathan,Jamal,Male,African-American,09/05/90,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,Copy,1,0 +29143,62994,44652,Probation,Walker,Jonathan,Jamal,Male,African-American,09/05/90,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +55302,62971,57136,DRRD,Pierre,Taneka,NULL,Female,African-American,08/30/91,17,All Scales,Intake,English,Conditional Release,Probation,Married,6/7/13 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +55302,62971,57136,DRRD,Pierre,Taneka,NULL,Female,African-American,08/30/91,17,All Scales,Intake,English,Conditional Release,Probation,Married,6/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,6,Medium,New,1,0 +55302,62971,57136,DRRD,Pierre,Taneka,NULL,Female,African-American,08/30/91,17,All Scales,Intake,English,Conditional Release,Probation,Married,6/7/13 0:00,2,Medium,18,Risk of Failure to Appear,18,2,Low,New,1,0 +55315,62986,57151,Probation,Johnson,Lucious,NULL,Male,African-American,03/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +55315,62986,57151,Probation,Johnson,Lucious,NULL,Male,African-American,03/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +55315,62986,57151,Probation,Johnson,Lucious,NULL,Male,African-American,03/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/7/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +55327,63007,57167,Probation,young,stephine,NULL,Female,Caucasian,03/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/10/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +55327,63007,57167,Probation,young,stephine,NULL,Female,Caucasian,03/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/10/13 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +55327,63007,57167,Probation,young,stephine,NULL,Female,Caucasian,03/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55332,63015,57174,PRETRIAL,Luque,Manuel,NULL,Male,Hispanic,10/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/10/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +55332,63015,57174,PRETRIAL,Luque,Manuel,NULL,Male,Hispanic,10/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/10/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +55332,63015,57174,PRETRIAL,Luque,Manuel,NULL,Male,Hispanic,10/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +48679,63010,57170,PRETRIAL,Allen,Youlanda,NULL,Female,African-American,02/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +48679,63010,57170,PRETRIAL,Allen,Youlanda,NULL,Female,African-American,02/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +48679,63010,57170,PRETRIAL,Allen,Youlanda,NULL,Female,African-American,02/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +55338,63023,57181,Probation,fulcher,matthew,NULL,Male,African-American,02/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +55338,63023,57181,Probation,fulcher,matthew,NULL,Male,African-American,02/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +55338,63023,57181,Probation,fulcher,matthew,NULL,Male,African-American,02/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +3001,63002,57163,PRETRIAL,MALLARD,ERWIN,LEE,Male,African-American,04/09/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +3001,63002,57163,PRETRIAL,MALLARD,ERWIN,LEE,Male,African-American,04/09/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +3001,63002,57163,PRETRIAL,MALLARD,ERWIN,LEE,Male,African-American,04/09/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +55334,63017,57176,Probation,worthy,shanika,NULL,Female,African-American,03/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +55334,63017,57176,Probation,worthy,shanika,NULL,Female,African-American,03/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,10,High,New,1,0 +55334,63017,57176,Probation,worthy,shanika,NULL,Female,African-American,03/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53251,63021,54704,Probation,SOTO,FRANKLIN,NULL,Male,Hispanic,07/18/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +53251,63021,54704,Probation,SOTO,FRANKLIN,NULL,Male,Hispanic,07/18/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +53251,63021,54704,Probation,SOTO,FRANKLIN,NULL,Male,Hispanic,07/18/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +12715,63000,56674,PRETRIAL,tomlinson,roberto,NULL,Male,Hispanic,05/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/10/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,Copy,1,0 +12715,63000,56674,PRETRIAL,tomlinson,roberto,NULL,Male,Hispanic,05/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,Copy,1,0 +12715,63000,56674,PRETRIAL,tomlinson,roberto,NULL,Male,Hispanic,05/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/10/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +55325,63003,57164,Probation,Green,Duaine,NULL,Male,African-American,12/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +55325,63003,57164,Probation,Green,Duaine,NULL,Male,African-American,12/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +55325,63003,57164,Probation,Green,Duaine,NULL,Male,African-American,12/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54062,63005,55604,Probation,Rouss,Diana,NULL,Female,Hispanic,04/13/83,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +54062,63005,55604,Probation,Rouss,Diana,NULL,Female,Hispanic,04/13/83,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-0.75,4,Low,New,1,0 +54062,63005,55604,Probation,Rouss,Diana,NULL,Female,Hispanic,04/13/83,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55341,63026,57184,Probation,Joseph,Ilonic,NULL,Male,African-American,08/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +55341,63026,57184,Probation,Joseph,Ilonic,NULL,Male,African-American,08/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +55341,63026,57184,Probation,Joseph,Ilonic,NULL,Male,African-American,08/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55324,63001,57162,Probation,GASKINS,TRAVIS,NULL,Male,Caucasian,01/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +55324,63001,57162,Probation,GASKINS,TRAVIS,NULL,Male,Caucasian,01/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +55324,63001,57162,Probation,GASKINS,TRAVIS,NULL,Male,Caucasian,01/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55328,63008,57168,Probation,PLACIDE,DAKENSON,NULL,Male,African-American,12/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/10/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +55328,63008,57168,Probation,PLACIDE,DAKENSON,NULL,Male,African-American,12/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/10/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +55328,63008,57168,Probation,PLACIDE,DAKENSON,NULL,Male,African-American,12/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55337,63022,57180,Probation,gomes,Peter,NULL,Male,Hispanic,11/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +55337,63022,57180,Probation,gomes,Peter,NULL,Male,Hispanic,11/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +55337,63022,57180,Probation,gomes,Peter,NULL,Male,Hispanic,11/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55329,63009,57169,PRETRIAL,Martinez,Edwin,NULL,Male,Hispanic,10/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/10/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +55329,63009,57169,PRETRIAL,Martinez,Edwin,NULL,Male,Hispanic,10/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/10/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +55329,63009,57169,PRETRIAL,Martinez,Edwin,NULL,Male,Hispanic,10/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55333,63016,57175,Probation,DIAZ,JONATHAN,NULL,Male,Hispanic,10/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +55333,63016,57175,Probation,DIAZ,JONATHAN,NULL,Male,Hispanic,10/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +55333,63016,57175,Probation,DIAZ,JONATHAN,NULL,Male,Hispanic,10/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55339,63024,57182,Probation,Jaco,Michael,NULL,Male,Caucasian,03/01/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +55339,63024,57182,Probation,Jaco,Michael,NULL,Male,Caucasian,03/01/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +55339,63024,57182,Probation,Jaco,Michael,NULL,Male,Caucasian,03/01/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +47037,63014,47522,Probation,jones,serena,NULL,Female,African-American,09/07/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +47037,63014,47522,Probation,jones,serena,NULL,Female,African-American,09/07/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +47037,63014,47522,Probation,jones,serena,NULL,Female,African-American,09/07/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +55342,63027,57185,Probation,LESTER,HENERY,NULL,Male,African-American,04/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +55342,63027,57185,Probation,LESTER,HENERY,NULL,Male,African-American,04/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +55342,63027,57185,Probation,LESTER,HENERY,NULL,Male,African-American,04/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55326,63006,57166,Probation,Cleary,Daniel,NULL,Male,Caucasian,09/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/10/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +55326,63006,57166,Probation,Cleary,Daniel,NULL,Male,Caucasian,09/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/10/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +55326,63006,57166,Probation,Cleary,Daniel,NULL,Male,Caucasian,09/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55335,63019,57178,Probation,RAMDAT,VISHNU,NULL,Male,Other,05/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +55335,63019,57178,Probation,RAMDAT,VISHNU,NULL,Male,Other,05/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +55335,63019,57178,Probation,RAMDAT,VISHNU,NULL,Male,Other,05/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +17711,62998,16988,PRETRIAL,schmidt,frank,NULL,Male,Caucasian,03/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,Copy,1,0 +17711,62998,16988,PRETRIAL,schmidt,frank,NULL,Male,Caucasian,03/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,Copy,1,0 +17711,62998,16988,PRETRIAL,schmidt,frank,NULL,Male,Caucasian,03/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +48860,63013,57173,PRETRIAL,Evans,Kenneth,NULL,Male,African-American,01/08/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/10/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +48860,63013,57173,PRETRIAL,Evans,Kenneth,NULL,Male,African-American,01/08/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/10/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +48860,63013,57173,PRETRIAL,Evans,Kenneth,NULL,Male,African-American,01/08/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +6754,62999,57161,PRETRIAL,Gross,Bradley,NULL,Male,African-American,05/17/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +6754,62999,57161,PRETRIAL,Gross,Bradley,NULL,Male,African-American,05/17/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +6754,62999,57161,PRETRIAL,Gross,Bradley,NULL,Male,African-American,05/17/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +39723,63004,57165,PRETRIAL,Greene,Elijah,NULL,Male,African-American,02/18/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +39723,63004,57165,PRETRIAL,Greene,Elijah,NULL,Male,African-American,02/18/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +39723,63004,57165,PRETRIAL,Greene,Elijah,NULL,Male,African-American,02/18/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55340,63025,57183,Probation,CLEMENTS,RHONDA,NULL,Female,African-American,05/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +55340,63025,57183,Probation,CLEMENTS,RHONDA,NULL,Female,African-American,05/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +55340,63025,57183,Probation,CLEMENTS,RHONDA,NULL,Female,African-American,05/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55336,63020,57179,PRETRIAL,Paul,Rondha,NULL,Female,African-American,09/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/13 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +55336,63020,57179,PRETRIAL,Paul,Rondha,NULL,Female,African-American,09/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/13 0:00,4,High,8,Risk of Recidivism,0.88,10,High,New,1,0 +55336,63020,57179,PRETRIAL,Paul,Rondha,NULL,Female,African-American,09/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/13 0:00,4,High,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +5491,63018,57177,PRETRIAL,JOSEPH,BOB,NULL,Male,African-American,08/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +5491,63018,57177,PRETRIAL,JOSEPH,BOB,NULL,Male,African-American,08/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +5491,63018,57177,PRETRIAL,JOSEPH,BOB,NULL,Male,African-American,08/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55323,62997,57160,Probation,Vina-Villaquiran,Carlos,NULL,Male,Hispanic,12/08/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +55323,62997,57160,Probation,Vina-Villaquiran,Carlos,NULL,Male,Hispanic,12/08/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +55323,62997,57160,Probation,Vina-Villaquiran,Carlos,NULL,Male,Hispanic,12/08/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55330,63011,57171,Probation,Thompson,Oral,NULL,Male,African-American,04/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +55330,63011,57171,Probation,Thompson,Oral,NULL,Male,African-American,04/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +55330,63011,57171,Probation,Thompson,Oral,NULL,Male,African-American,04/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55349,63041,57197,Probation,RODRIGUEZ,ERNESTO,NULL,Male,Hispanic,10/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +55349,63041,57197,Probation,RODRIGUEZ,ERNESTO,NULL,Male,Hispanic,10/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +55349,63041,57197,Probation,RODRIGUEZ,ERNESTO,NULL,Male,Hispanic,10/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +31440,63048,57204,Probation,jones,lekeveya,NULL,Female,African-American,12/11/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +31440,63048,57204,Probation,jones,lekeveya,NULL,Female,African-American,12/11/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +31440,63048,57204,Probation,jones,lekeveya,NULL,Female,African-American,12/11/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55347,63039,57195,Probation,ritchie,wallace,NULL,Male,African-American,01/08/42,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/11/13 0:00,1,Low,7,Risk of Violence,-4.53,1,Low,New,1,0 +55347,63039,57195,Probation,ritchie,wallace,NULL,Male,African-American,01/08/42,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/11/13 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +55347,63039,57195,Probation,ritchie,wallace,NULL,Male,African-American,01/08/42,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55362,63055,57211,Probation,Berrios,Evelyn,NULL,Female,Hispanic,06/16/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/11/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +55362,63055,57211,Probation,Berrios,Evelyn,NULL,Female,Hispanic,06/16/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/11/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +55362,63055,57211,Probation,Berrios,Evelyn,NULL,Female,Hispanic,06/16/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +55354,63046,57202,Probation,taribo,richard,NULL,Male,Caucasian,08/24/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/11/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +55354,63046,57202,Probation,taribo,richard,NULL,Male,Caucasian,08/24/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/11/13 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +55354,63046,57202,Probation,taribo,richard,NULL,Male,Caucasian,08/24/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55344,63032,57188,Probation,ramnarain,ravi,NULL,Male,Asian,12/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +55344,63032,57188,Probation,ramnarain,ravi,NULL,Male,Asian,12/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +55344,63032,57188,Probation,ramnarain,ravi,NULL,Male,Asian,12/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55360,63053,57209,PRETRIAL,Sanchez,Melissa,NULL,Female,Hispanic,06/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +55360,63053,57209,PRETRIAL,Sanchez,Melissa,NULL,Female,Hispanic,06/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +55360,63053,57209,PRETRIAL,Sanchez,Melissa,NULL,Female,Hispanic,06/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55353,63045,57201,Probation,KEENYA,WATKINS,COLETTE,Female,African-American,01/22/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +55353,63045,57201,Probation,KEENYA,WATKINS,COLETTE,Female,African-American,01/22/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +55353,63045,57201,Probation,KEENYA,WATKINS,COLETTE,Female,African-American,01/22/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55343,63035,57191,Broward County,Bower,Ernest,NULL,Male,Hispanic,10/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +55343,63035,57191,Broward County,Bower,Ernest,NULL,Male,Hispanic,10/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +55343,63035,57191,Broward County,Bower,Ernest,NULL,Male,Hispanic,10/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55350,63043,57199,PRETRIAL,Dees,Tony,NULL,Male,African-American,06/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +55350,63043,57199,PRETRIAL,Dees,Tony,NULL,Male,African-American,06/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +55350,63043,57199,PRETRIAL,Dees,Tony,NULL,Male,African-American,06/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55357,63050,57206,Probation,glatz,daniel,NULL,Male,Caucasian,06/13/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/11/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +55357,63050,57206,Probation,glatz,daniel,NULL,Male,Caucasian,06/13/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/11/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +55357,63050,57206,Probation,glatz,daniel,NULL,Male,Caucasian,06/13/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55346,63037,57193,Probation,Harris,Shawn,Anthony,Male,African-American,06/14/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/11/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +55346,63037,57193,Probation,Harris,Shawn,Anthony,Male,African-American,06/14/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/11/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +55346,63037,57193,Probation,Harris,Shawn,Anthony,Male,African-American,06/14/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55358,63051,57207,Probation,PANJWANI,SHAMSHAH,NULL,Female,Asian,03/10/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/11/13 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +55358,63051,57207,Probation,PANJWANI,SHAMSHAH,NULL,Female,Asian,03/10/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/11/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +55358,63051,57207,Probation,PANJWANI,SHAMSHAH,NULL,Female,Asian,03/10/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +27739,63029,57186,Probation,parrish,craig,NULL,Male,African-American,10/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +27739,63029,57186,Probation,parrish,craig,NULL,Male,African-American,10/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +27739,63029,57186,Probation,parrish,craig,NULL,Male,African-American,10/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51369,63030,52551,PRETRIAL,Bass,Timothy,NULL,Male,African-American,02/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,Copy,1,0 +51369,63030,52551,PRETRIAL,Bass,Timothy,NULL,Male,African-American,02/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,Copy,1,0 +51369,63030,52551,PRETRIAL,Bass,Timothy,NULL,Male,African-American,02/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +55355,63047,57203,Probation,OWENS,KYLE,NULL,Male,African-American,12/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +55355,63047,57203,Probation,OWENS,KYLE,NULL,Male,African-American,12/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +55355,63047,57203,Probation,OWENS,KYLE,NULL,Male,African-American,12/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55361,63054,57210,Probation,Rodriguez,Ernesto,A,Male,Hispanic,08/16/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/11/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +55361,63054,57210,Probation,Rodriguez,Ernesto,A,Male,Hispanic,08/16/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/11/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +55361,63054,57210,Probation,Rodriguez,Ernesto,A,Male,Hispanic,08/16/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50426,63038,57194,PRETRIAL,Dawkins,Elroy,Reckville,Male,African-American,08/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/11/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +50426,63038,57194,PRETRIAL,Dawkins,Elroy,Reckville,Male,African-American,08/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/11/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +50426,63038,57194,PRETRIAL,Dawkins,Elroy,Reckville,Male,African-American,08/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +55351,63042,57198,PRETRIAL,Rodriguez,Ricardo,NULL,Male,Hispanic,12/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +55351,63042,57198,PRETRIAL,Rodriguez,Ricardo,NULL,Male,Hispanic,12/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +55351,63042,57198,PRETRIAL,Rodriguez,Ricardo,NULL,Male,Hispanic,12/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +50059,63036,57192,Probation,Acevedo,Jose,Enrique,Male,Hispanic,02/06/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,2,Medium,7,Risk of Violence,-2.74,2,Low,New,1,0 +50059,63036,57192,Probation,Acevedo,Jose,Enrique,Male,Hispanic,02/06/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +50059,63036,57192,Probation,Acevedo,Jose,Enrique,Male,Hispanic,02/06/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55356,63049,57205,Probation,Miranda,Heriberdo,NULL,Male,Hispanic,08/24/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/11/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +55356,63049,57205,Probation,Miranda,Heriberdo,NULL,Male,Hispanic,08/24/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/11/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +55356,63049,57205,Probation,Miranda,Heriberdo,NULL,Male,Hispanic,08/24/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55233,63028,57041,PRETRIAL,Roberts,Richard,NULL,Male,African-American,09/14/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/11/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,Copy,1,0 +55233,63028,57041,PRETRIAL,Roberts,Richard,NULL,Male,African-American,09/14/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/11/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,Copy,1,0 +55233,63028,57041,PRETRIAL,Roberts,Richard,NULL,Male,African-American,09/14/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +55352,63044,57200,Probation,Contreras,Kathya,NULL,Female,Hispanic,06/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +55352,63044,57200,Probation,Contreras,Kathya,NULL,Female,Hispanic,06/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +55352,63044,57200,Probation,Contreras,Kathya,NULL,Female,Hispanic,06/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55367,63065,57218,PRETRIAL,Barteau,Roger,Allan,Male,Caucasian,07/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/12/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +55367,63065,57218,PRETRIAL,Barteau,Roger,Allan,Male,Caucasian,07/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/12/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +55367,63065,57218,PRETRIAL,Barteau,Roger,Allan,Male,Caucasian,07/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55373,63073,57226,Probation,LAURENT,SVENTZ,NULL,Male,African-American,10/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +55373,63073,57226,Probation,LAURENT,SVENTZ,NULL,Male,African-American,10/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +55373,63073,57226,Probation,LAURENT,SVENTZ,NULL,Male,African-American,10/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +14898,63070,57223,Probation,lethridge,zebbie,NULL,Male,African-American,01/31/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +14898,63070,57223,Probation,lethridge,zebbie,NULL,Male,African-American,01/31/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +14898,63070,57223,Probation,lethridge,zebbie,NULL,Male,African-American,01/31/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +40028,63057,57213,PRETRIAL,Volcy,Renaldy,R,Male,African-American,07/31/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +40028,63057,57213,PRETRIAL,Volcy,Renaldy,R,Male,African-American,07/31/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +40028,63057,57213,PRETRIAL,Volcy,Renaldy,R,Male,African-American,07/31/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55365,63063,57216,Probation,McCullough,Rose,Kathy,Female,Caucasian,10/30/58,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/12/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +55365,63063,57216,Probation,McCullough,Rose,Kathy,Female,Caucasian,10/30/58,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/12/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +55365,63063,57216,Probation,McCullough,Rose,Kathy,Female,Caucasian,10/30/58,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55372,63072,57225,Probation,watson,allison,NULL,Female,African-American,02/01/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/12/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +55372,63072,57225,Probation,watson,allison,NULL,Female,African-American,02/01/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/12/13 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +55372,63072,57225,Probation,watson,allison,NULL,Female,African-American,02/01/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55368,63068,57221,PRETRIAL,Frantz,Pointdujour,NULL,Male,African-American,01/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/12/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +55368,63068,57221,PRETRIAL,Frantz,Pointdujour,NULL,Male,African-American,01/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/12/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +55368,63068,57221,PRETRIAL,Frantz,Pointdujour,NULL,Male,African-American,01/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55375,63075,57228,Probation,Berry,Charmaine,L,Female,African-American,06/14/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +55375,63075,57228,Probation,Berry,Charmaine,L,Female,African-American,06/14/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +55375,63075,57228,Probation,Berry,Charmaine,L,Female,African-American,06/14/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55371,63071,57224,Probation,Reid,Edward,NULL,Male,African-American,02/27/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +55371,63071,57224,Probation,Reid,Edward,NULL,Male,African-American,02/27/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +55371,63071,57224,Probation,Reid,Edward,NULL,Male,African-American,02/27/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55374,63074,57227,PRETRIAL,LOPEZ,ELIZABETH,NULL,Female,Hispanic,11/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +55374,63074,57227,PRETRIAL,LOPEZ,ELIZABETH,NULL,Female,Hispanic,11/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/13 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +55374,63074,57227,PRETRIAL,LOPEZ,ELIZABETH,NULL,Female,Hispanic,11/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55369,63066,57219,Probation,peters,melissa,a,Female,Caucasian,11/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/12/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +55369,63066,57219,Probation,peters,melissa,a,Female,Caucasian,11/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/12/13 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +55369,63066,57219,Probation,peters,melissa,a,Female,Caucasian,11/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55366,63064,57217,Probation,Hendersongilbert,Robin,NULL,Female,African-American,04/13/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/12/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +55366,63064,57217,Probation,Hendersongilbert,Robin,NULL,Female,African-American,04/13/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/12/13 0:00,1,Low,8,Risk of Recidivism,-1.62,2,Low,New,1,0 +55366,63064,57217,Probation,Hendersongilbert,Robin,NULL,Female,African-American,04/13/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +55364,63060,57215,Probation,Gaudio,Paul,NULL,Male,Hispanic,02/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +55364,63060,57215,Probation,Gaudio,Paul,NULL,Male,Hispanic,02/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +55364,63060,57215,Probation,Gaudio,Paul,NULL,Male,Hispanic,02/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55370,63067,57220,Probation,De La Riva,Arlyns,NULL,Female,Hispanic,02/21/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/12/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +55370,63067,57220,Probation,De La Riva,Arlyns,NULL,Female,Hispanic,02/21/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/12/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +55370,63067,57220,Probation,De La Riva,Arlyns,NULL,Female,Hispanic,02/21/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49315,63069,57222,PRETRIAL,Peters,Edward,NULL,Male,Caucasian,11/20/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/12/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +49315,63069,57222,PRETRIAL,Peters,Edward,NULL,Male,Caucasian,11/20/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/12/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +49315,63069,57222,PRETRIAL,Peters,Edward,NULL,Male,Caucasian,11/20/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54580,63062,56265,Probation,Traendly,George,NULL,Male,Caucasian,07/03/56,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,6/12/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +54580,63062,56265,Probation,Traendly,George,NULL,Male,Caucasian,07/03/56,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,6/12/13 0:00,1,Low,8,Risk of Recidivism,-0.7,3,Low,New,1,0 +54580,63062,56265,Probation,Traendly,George,NULL,Male,Caucasian,07/03/56,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +55376,63076,57229,Probation,Vilceus,Widler,NULL,Male,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +55376,63076,57229,Probation,Vilceus,Widler,NULL,Male,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +55376,63076,57229,Probation,Vilceus,Widler,NULL,Male,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +42902,63083,57236,PRETRIAL,HARDNETT,ALLEN,E,Male,African-American,11/11/76,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/13/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +42902,63083,57236,PRETRIAL,HARDNETT,ALLEN,E,Male,African-American,11/11/76,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/13/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +42902,63083,57236,PRETRIAL,HARDNETT,ALLEN,E,Male,African-American,11/11/76,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55393,63090,57243,Probation,Hasse,Timothy,NULL,Male,Caucasian,07/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +55393,63090,57243,Probation,Hasse,Timothy,NULL,Male,Caucasian,07/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +55393,63090,57243,Probation,Hasse,Timothy,NULL,Male,Caucasian,07/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55399,63097,57249,Probation,mcneal,issac,NULL,Male,African-American,11/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +55399,63097,57249,Probation,mcneal,issac,NULL,Male,African-American,11/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +55399,63097,57249,Probation,mcneal,issac,NULL,Male,African-American,11/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55383,63085,57238,Probation,Moreno,Jasmines,NULL,Female,Hispanic,03/31/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +55383,63085,57238,Probation,Moreno,Jasmines,NULL,Female,Hispanic,03/31/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +55383,63085,57238,Probation,Moreno,Jasmines,NULL,Female,Hispanic,03/31/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55380,63081,57234,Probation,Barron,Stephanie,Yvonne,Female,Caucasian,05/02/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/13/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +55380,63081,57234,Probation,Barron,Stephanie,Yvonne,Female,Caucasian,05/02/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/13/13 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +55380,63081,57234,Probation,Barron,Stephanie,Yvonne,Female,Caucasian,05/02/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55404,63102,57254,PRETRIAL,Lewis,Rodney,NULL,Male,African-American,06/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/13 0:00,2,Medium,7,Risk of Violence,-2.83,2,Low,New,1,0 +55404,63102,57254,PRETRIAL,Lewis,Rodney,NULL,Male,African-American,06/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +55404,63102,57254,PRETRIAL,Lewis,Rodney,NULL,Male,African-American,06/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55403,63100,57252,Probation,PEREDA,JORGE,NULL,Female,Hispanic,12/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/13/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +55403,63100,57252,Probation,PEREDA,JORGE,NULL,Female,Hispanic,12/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/13/13 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +55403,63100,57252,Probation,PEREDA,JORGE,NULL,Female,Hispanic,12/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55397,63095,57247,Probation,Joseph-Desarden,Alpheus,NULL,Male,Hispanic,09/07/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/13/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +55397,63095,57247,Probation,Joseph-Desarden,Alpheus,NULL,Male,Hispanic,09/07/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/13/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +55397,63095,57247,Probation,Joseph-Desarden,Alpheus,NULL,Male,Hispanic,09/07/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +43141,63079,57232,Probation,Hott,Deborah,NULL,Female,Caucasian,01/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/13/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +43141,63079,57232,Probation,Hott,Deborah,NULL,Female,Caucasian,01/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/13/13 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +43141,63079,57232,Probation,Hott,Deborah,NULL,Female,Caucasian,01/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55377,63077,57230,PRETRIAL,Heard,Authry,NULL,Male,African-American,09/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +55377,63077,57230,PRETRIAL,Heard,Authry,NULL,Male,African-American,09/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +55377,63077,57230,PRETRIAL,Heard,Authry,NULL,Male,African-American,09/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +55381,63082,57235,Probation,Carrick,Westley,NULL,Male,Caucasian,03/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +55381,63082,57235,Probation,Carrick,Westley,NULL,Male,Caucasian,03/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +55381,63082,57235,Probation,Carrick,Westley,NULL,Male,Caucasian,03/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55382,63084,57237,Probation,Dannenberg,Jeffrey,NULL,Male,Caucasian,08/15/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +55382,63084,57237,Probation,Dannenberg,Jeffrey,NULL,Male,Caucasian,08/15/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +55382,63084,57237,Probation,Dannenberg,Jeffrey,NULL,Male,Caucasian,08/15/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55405,63103,57255,Probation,Galeano,Ricardo,NULL,Male,Hispanic,09/30/66,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/13/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +55405,63103,57255,Probation,Galeano,Ricardo,NULL,Male,Hispanic,09/30/66,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/13/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +55405,63103,57255,Probation,Galeano,Ricardo,NULL,Male,Hispanic,09/30/66,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50017,63105,57257,PRETRIAL,Smith,Latefah,NULL,Female,African-American,01/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +50017,63105,57257,PRETRIAL,Smith,Latefah,NULL,Female,African-American,01/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +50017,63105,57257,PRETRIAL,Smith,Latefah,NULL,Female,African-American,01/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55396,63093,57245,Probation,lemanski,jake,NULL,Male,Caucasian,11/06/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +55396,63093,57245,Probation,lemanski,jake,NULL,Male,Caucasian,11/06/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +55396,63093,57245,Probation,lemanski,jake,NULL,Male,Caucasian,11/06/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55400,63098,57250,Probation,Perez,Jose,NULL,Male,Hispanic,03/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +55400,63098,57250,Probation,Perez,Jose,NULL,Male,Hispanic,03/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +55400,63098,57250,Probation,Perez,Jose,NULL,Male,Hispanic,03/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55390,63089,57242,Probation,Roca,Jacob,NULL,Male,Hispanic,10/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +55390,63089,57242,Probation,Roca,Jacob,NULL,Male,Hispanic,10/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +55390,63089,57242,Probation,Roca,Jacob,NULL,Male,Hispanic,10/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55394,63091,57244,Probation,thomas,fernanda,NULL,Female,Caucasian,11/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/13/13 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +55394,63091,57244,Probation,thomas,fernanda,NULL,Female,Caucasian,11/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +55394,63091,57244,Probation,thomas,fernanda,NULL,Female,Caucasian,11/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/13/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +37999,63104,57256,PRETRIAL,Christian,Jaron,NULL,Male,African-American,10/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +37999,63104,57256,PRETRIAL,Christian,Jaron,NULL,Male,African-American,10/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,4,High,8,Risk of Recidivism,0.22,8,High,New,1,0 +37999,63104,57256,PRETRIAL,Christian,Jaron,NULL,Male,African-American,10/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55378,63078,57231,Probation,Alexander,Annmarie,NULL,Male,African-American,06/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +55378,63078,57231,Probation,Alexander,Annmarie,NULL,Male,African-American,06/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +55378,63078,57231,Probation,Alexander,Annmarie,NULL,Male,African-American,06/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55398,63096,57248,PRETRIAL,Francois,Mickenson,NULL,Male,African-American,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/13 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +55398,63096,57248,PRETRIAL,Francois,Mickenson,NULL,Male,African-American,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/13 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +55398,63096,57248,PRETRIAL,Francois,Mickenson,NULL,Male,African-American,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55401,63099,57251,Probation,gomez,alex,NULL,Male,Caucasian,06/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +55401,63099,57251,Probation,gomez,alex,NULL,Male,Caucasian,06/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.03,10,High,New,1,0 +55401,63099,57251,Probation,gomez,alex,NULL,Male,Caucasian,06/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +55384,63086,57239,Probation,kovacs,frank,NULL,Male,Caucasian,08/17/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/13/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +55384,63086,57239,Probation,kovacs,frank,NULL,Male,Caucasian,08/17/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/13/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +55384,63086,57239,Probation,kovacs,frank,NULL,Male,Caucasian,08/17/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55389,63088,57241,Probation,Almador,Felix,NULL,Male,Hispanic,05/02/71,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,6/13/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +55389,63088,57241,Probation,Almador,Felix,NULL,Male,Hispanic,05/02/71,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,6/13/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +55389,63088,57241,Probation,Almador,Felix,NULL,Male,Hispanic,05/02/71,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +55402,63101,57253,Probation,Johnson,Shemise,NULL,Female,Hispanic,03/04/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/13/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +55402,63101,57253,Probation,Johnson,Shemise,NULL,Female,Hispanic,03/04/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +55402,63101,57253,Probation,Johnson,Shemise,NULL,Female,Hispanic,03/04/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/13/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55379,63080,57233,Probation,OCASIO,MIGUEL,NULL,Male,African-American,08/16/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/13 0:00,2,Medium,7,Risk of Violence,-2.84,2,Low,New,1,0 +55379,63080,57233,Probation,OCASIO,MIGUEL,NULL,Male,African-American,08/16/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +55379,63080,57233,Probation,OCASIO,MIGUEL,NULL,Male,African-American,08/16/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +43488,63094,57246,PRETRIAL,Brizuela,Efrain,NULL,Male,Caucasian,04/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/13/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +43488,63094,57246,PRETRIAL,Brizuela,Efrain,NULL,Male,Caucasian,04/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/13/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +43488,63094,57246,PRETRIAL,Brizuela,Efrain,NULL,Male,Caucasian,04/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55412,63115,57266,Probation,Marshall,Aaron,Andrew,Male,Caucasian,07/17/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +55412,63115,57266,Probation,Marshall,Aaron,Andrew,Male,Caucasian,07/17/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +55412,63115,57266,Probation,Marshall,Aaron,Andrew,Male,Caucasian,07/17/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55418,63122,57273,PRETRIAL,CHITWOOD,RYAN,NULL,Male,Caucasian,02/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +55418,63122,57273,PRETRIAL,CHITWOOD,RYAN,NULL,Male,Caucasian,02/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +55418,63122,57273,PRETRIAL,CHITWOOD,RYAN,NULL,Male,Caucasian,02/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +55406,63107,57258,Probation,byrd,John,NULL,Male,African-American,06/11/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.32,3,Low,New,1,0 +55406,63107,57258,Probation,byrd,John,NULL,Male,African-American,06/11/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.63,10,High,New,1,0 +55406,63107,57258,Probation,byrd,John,NULL,Male,African-American,06/11/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55408,63109,57260,Probation,McQuillen,Richard,NULL,Male,Caucasian,09/23/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/14/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +55408,63109,57260,Probation,McQuillen,Richard,NULL,Male,Caucasian,09/23/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/14/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +55408,63109,57260,Probation,McQuillen,Richard,NULL,Male,Caucasian,09/23/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +49444,63117,57268,PRETRIAL,PRADA-SALAUES,CARLOS,NULL,Male,Other,11/07/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +49444,63117,57268,PRETRIAL,PRADA-SALAUES,CARLOS,NULL,Male,Other,11/07/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-2.69,1,Low,New,1,0 +49444,63117,57268,PRETRIAL,PRADA-SALAUES,CARLOS,NULL,Male,Other,11/07/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55420,63125,57276,PRETRIAL,Fearon,Jermane,NULL,Male,Other,02/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +55420,63125,57276,PRETRIAL,Fearon,Jermane,NULL,Male,Other,02/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +55420,63125,57276,PRETRIAL,Fearon,Jermane,NULL,Male,Other,02/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55415,63119,57270,Probation,Jones,Kody,Julio,Male,Hispanic,12/31/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/14/13 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +55415,63119,57270,Probation,Jones,Kody,Julio,Male,Hispanic,12/31/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +55415,63119,57270,Probation,Jones,Kody,Julio,Male,Hispanic,12/31/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/14/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +13742,63114,57265,PRETRIAL,James,Patrick,NULL,Male,African-American,11/29/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +13742,63114,57265,PRETRIAL,James,Patrick,NULL,Male,African-American,11/29/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.41,4,Low,New,1,0 +13742,63114,57265,PRETRIAL,James,Patrick,NULL,Male,African-American,11/29/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55423,63128,57279,Probation,Young,Tafari,NULL,Male,African-American,10/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,New,1,0 +55423,63128,57279,Probation,Young,Tafari,NULL,Male,African-American,10/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +55423,63128,57279,Probation,Young,Tafari,NULL,Male,African-American,10/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +41123,63110,57261,PRETRIAL,Ervin,Joshua,NULL,Male,Caucasian,08/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +41123,63110,57261,PRETRIAL,Ervin,Joshua,NULL,Male,Caucasian,08/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +41123,63110,57261,PRETRIAL,Ervin,Joshua,NULL,Male,Caucasian,08/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +32188,63124,57275,PRETRIAL,bueler,brian,g,Male,Caucasian,01/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +32188,63124,57275,PRETRIAL,bueler,brian,g,Male,Caucasian,01/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,4,High,8,Risk of Recidivism,0.32,9,High,New,1,0 +32188,63124,57275,PRETRIAL,bueler,brian,g,Male,Caucasian,01/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55410,63112,57263,Probation,FANFAN,CHRISTOPHER,NULL,Male,African-American,04/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +55410,63112,57263,Probation,FANFAN,CHRISTOPHER,NULL,Male,African-American,04/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +55410,63112,57263,Probation,FANFAN,CHRISTOPHER,NULL,Male,African-American,04/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55421,63126,57277,Probation,Rocha,Diego,NULL,Male,Hispanic,04/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +55421,63126,57277,Probation,Rocha,Diego,NULL,Male,Hispanic,04/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +55421,63126,57277,Probation,Rocha,Diego,NULL,Male,Hispanic,04/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +46168,63129,57280,Probation,SCOTT,SHERRY,NULL,Female,Caucasian,10/31/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/14/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +46168,63129,57280,Probation,SCOTT,SHERRY,NULL,Female,Caucasian,10/31/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/14/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +46168,63129,57280,Probation,SCOTT,SHERRY,NULL,Female,Caucasian,10/31/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55407,63108,57259,PRETRIAL,Detrie,Dushane,NULL,Female,African-American,01/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,New,1,0 +55407,63108,57259,PRETRIAL,Detrie,Dushane,NULL,Female,African-American,01/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +55407,63108,57259,PRETRIAL,Detrie,Dushane,NULL,Female,African-American,01/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +55413,63116,57267,Probation,HOOD,REBECCA,JANE,Female,Caucasian,11/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +55413,63116,57267,Probation,HOOD,REBECCA,JANE,Female,Caucasian,11/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +55413,63116,57267,Probation,HOOD,REBECCA,JANE,Female,Caucasian,11/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55411,63113,57264,Probation,Campbell,Krystal,NULL,Female,African-American,04/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +55411,63113,57264,Probation,Campbell,Krystal,NULL,Female,African-American,04/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +55411,63113,57264,Probation,Campbell,Krystal,NULL,Female,African-American,04/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55417,63121,57272,Probation,CORZO,SANDRA,P,Female,Hispanic,06/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/14/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +55417,63121,57272,Probation,CORZO,SANDRA,P,Female,Hispanic,06/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/14/13 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +55417,63121,57272,Probation,CORZO,SANDRA,P,Female,Hispanic,06/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55419,63123,57274,Probation,barnard,erik,NULL,Male,Caucasian,04/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +55419,63123,57274,Probation,barnard,erik,NULL,Male,Caucasian,04/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +55419,63123,57274,Probation,barnard,erik,NULL,Male,Caucasian,04/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55422,63127,57278,Probation,Gavett,Albert,NULL,Male,Caucasian,07/04/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +55422,63127,57278,Probation,Gavett,Albert,NULL,Male,Caucasian,07/04/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +55422,63127,57278,Probation,Gavett,Albert,NULL,Male,Caucasian,07/04/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +15956,63106,15281,PRETRIAL,Coleman,Sheldon,Lamar,Male,Caucasian,09/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,Copy,1,0 +15956,63106,15281,PRETRIAL,Coleman,Sheldon,Lamar,Male,Caucasian,09/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,7,Medium,Copy,1,0 +15956,63106,15281,PRETRIAL,Coleman,Sheldon,Lamar,Male,Caucasian,09/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +55409,63111,57262,Probation,BENTLEY,JUSTIN,NULL,Male,African-American,10/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +55409,63111,57262,Probation,BENTLEY,JUSTIN,NULL,Male,African-American,10/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +55409,63111,57262,Probation,BENTLEY,JUSTIN,NULL,Male,African-American,10/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55416,63120,57271,Probation,pereira,rachel,NULL,Female,Asian,08/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +55416,63120,57271,Probation,pereira,rachel,NULL,Female,Asian,08/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +55416,63120,57271,Probation,pereira,rachel,NULL,Female,Asian,08/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55414,63118,57269,Probation,Rodriguez Jr,Marcos,NULL,Male,Hispanic,11/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +55414,63118,57269,Probation,Rodriguez Jr,Marcos,NULL,Male,Hispanic,11/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +55414,63118,57269,Probation,Rodriguez Jr,Marcos,NULL,Male,Hispanic,11/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/14/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +31944,63139,57288,PRETRIAL,HINNANT,RODERICK,NULL,Male,African-American,01/21/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +31944,63139,57288,PRETRIAL,HINNANT,RODERICK,NULL,Male,African-American,01/21/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +31944,63139,57288,PRETRIAL,HINNANT,RODERICK,NULL,Male,African-American,01/21/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55440,63148,57297,PRETRIAL,LOWDER,DARREN,NULL,Female,Caucasian,08/26/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +55440,63148,57297,PRETRIAL,LOWDER,DARREN,NULL,Female,Caucasian,08/26/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +55440,63148,57297,PRETRIAL,LOWDER,DARREN,NULL,Female,Caucasian,08/26/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55429,63136,57285,Probation,Vazquez,Jesus,NULL,Male,Hispanic,03/21/95,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,6/17/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +55429,63136,57285,Probation,Vazquez,Jesus,NULL,Male,Hispanic,03/21/95,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,6/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +55429,63136,57285,Probation,Vazquez,Jesus,NULL,Male,Hispanic,03/21/95,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,6/17/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55445,63153,57302,Probation,flores,manuel,NULL,Male,Hispanic,07/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/17/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +55445,63153,57302,Probation,flores,manuel,NULL,Male,Hispanic,07/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +55445,63153,57302,Probation,flores,manuel,NULL,Male,Hispanic,07/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55424,63132,57281,PRETRIAL,IRANZO,YAQUELYN,NULL,Female,Hispanic,10/08/78,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +55424,63132,57281,PRETRIAL,IRANZO,YAQUELYN,NULL,Female,Hispanic,10/08/78,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +55424,63132,57281,PRETRIAL,IRANZO,YAQUELYN,NULL,Female,Hispanic,10/08/78,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55448,63157,57305,PRETRIAL,Franz,Ryan,NULL,Male,Caucasian,11/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +55448,63157,57305,PRETRIAL,Franz,Ryan,NULL,Male,Caucasian,11/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +55448,63157,57305,PRETRIAL,Franz,Ryan,NULL,Male,Caucasian,11/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55447,63155,57304,Probation,hernandez,ervin,NULL,Male,Caucasian,11/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +55447,63155,57304,Probation,hernandez,ervin,NULL,Male,Caucasian,11/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +55447,63155,57304,Probation,hernandez,ervin,NULL,Male,Caucasian,11/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55427,63134,57283,PRETRIAL,Thornton,Gregory,Lance,Male,Caucasian,12/16/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/13 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +55427,63134,57283,PRETRIAL,Thornton,Gregory,Lance,Male,Caucasian,12/16/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/13 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +55427,63134,57283,PRETRIAL,Thornton,Gregory,Lance,Male,Caucasian,12/16/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55433,63142,57291,Probation,michelin,donald,NULL,Male,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +55433,63142,57291,Probation,michelin,donald,NULL,Male,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +55433,63142,57291,Probation,michelin,donald,NULL,Male,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55450,63160,57308,Probation,Stainkamp,clint,NULL,Male,Caucasian,07/01/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +55450,63160,57308,Probation,Stainkamp,clint,NULL,Male,Caucasian,07/01/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +55450,63160,57308,Probation,Stainkamp,clint,NULL,Male,Caucasian,07/01/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55442,63150,57299,Probation,Vasquez,juan,NULL,Male,Hispanic,01/25/70,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,6/17/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +55442,63150,57299,Probation,Vasquez,juan,NULL,Male,Hispanic,01/25/70,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +55442,63150,57299,Probation,Vasquez,juan,NULL,Male,Hispanic,01/25/70,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55444,63152,57301,PRETRIAL,Diana,Emily,NULL,Female,Caucasian,02/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/17/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +55444,63152,57301,PRETRIAL,Diana,Emily,NULL,Female,Caucasian,02/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +55444,63152,57301,PRETRIAL,Diana,Emily,NULL,Female,Caucasian,02/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55430,63137,57286,Probation,Coar,Yuri,NULL,Male,African-American,02/10/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +55430,63137,57286,Probation,Coar,Yuri,NULL,Male,African-American,02/10/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +55430,63137,57286,Probation,Coar,Yuri,NULL,Male,African-American,02/10/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55449,63158,57306,PRETRIAL,NEAL,CHRISTOPHER,NULL,Male,African-American,07/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/13 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +55449,63158,57306,PRETRIAL,NEAL,CHRISTOPHER,NULL,Male,African-American,07/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +55449,63158,57306,PRETRIAL,NEAL,CHRISTOPHER,NULL,Male,African-American,07/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55436,63144,57293,DRRD,Rodriguez,Paul,NULL,Male,Hispanic,12/18/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,6/17/13 0:00,4,High,7,Risk of Violence,1.32,10,High,New,1,0 +55436,63144,57293,DRRD,Rodriguez,Paul,NULL,Male,Hispanic,12/18/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,6/17/13 0:00,4,High,8,Risk of Recidivism,1.22,10,High,New,1,0 +55436,63144,57293,DRRD,Rodriguez,Paul,NULL,Male,Hispanic,12/18/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,6/17/13 0:00,4,High,18,Risk of Failure to Appear,36,10,High,New,1,0 +55425,63133,57282,PRETRIAL,SMITH,NEWTON,ALAN,Male,African-American,01/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +55425,63133,57282,PRETRIAL,SMITH,NEWTON,ALAN,Male,African-American,01/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +55425,63133,57282,PRETRIAL,SMITH,NEWTON,ALAN,Male,African-American,01/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55432,63140,57289,Probation,Davis,Tray,NULL,Male,Caucasian,04/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +55432,63140,57289,Probation,Davis,Tray,NULL,Male,Caucasian,04/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +55432,63140,57289,Probation,Davis,Tray,NULL,Male,Caucasian,04/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55439,63147,57296,PRETRIAL,ALINSTANT,JACQUES,NULL,Male,Other,08/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +55439,63147,57296,PRETRIAL,ALINSTANT,JACQUES,NULL,Male,Other,08/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +55439,63147,57296,PRETRIAL,ALINSTANT,JACQUES,NULL,Male,Other,08/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55451,63161,57309,Probation,getch,tina,NULL,Female,Caucasian,09/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +55451,63161,57309,Probation,getch,tina,NULL,Female,Caucasian,09/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,7,Medium,New,1,0 +55451,63161,57309,Probation,getch,tina,NULL,Female,Caucasian,09/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55446,63154,57303,Probation,Papp,David,NULL,Male,Caucasian,03/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/17/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +55446,63154,57303,Probation,Papp,David,NULL,Male,Caucasian,03/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +55446,63154,57303,Probation,Papp,David,NULL,Male,Caucasian,03/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55122,63156,56912,PRETRIAL,McMahon,Joseph,NULL,Male,Caucasian,12/30/43,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/17/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,Copy,1,0 +55122,63156,56912,PRETRIAL,McMahon,Joseph,NULL,Male,Caucasian,12/30/43,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,Copy,1,0 +55122,63156,56912,PRETRIAL,McMahon,Joseph,NULL,Male,Caucasian,12/30/43,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +55428,63135,57284,PRETRIAL,Marshall,Clinton,NULL,Male,African-American,03/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +55428,63135,57284,PRETRIAL,Marshall,Clinton,NULL,Male,African-American,03/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +55428,63135,57284,PRETRIAL,Marshall,Clinton,NULL,Male,African-American,03/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55441,63149,57298,Probation,Brown,Carnell,NULL,Male,African-American,02/07/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +55441,63149,57298,Probation,Brown,Carnell,NULL,Male,African-American,02/07/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,4,High,8,Risk of Recidivism,0.26,8,High,New,1,0 +55441,63149,57298,Probation,Brown,Carnell,NULL,Male,African-American,02/07/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55437,63145,57294,Probation,Peyton,Travaughn,NULL,Male,African-American,03/24/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +55437,63145,57294,Probation,Peyton,Travaughn,NULL,Male,African-American,03/24/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +55437,63145,57294,Probation,Peyton,Travaughn,NULL,Male,African-American,03/24/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +6758,63159,57307,Probation,Poitier,Romalice,Frank,Male,African-American,11/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +6758,63159,57307,Probation,Poitier,Romalice,Frank,Male,African-American,11/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,4,High,8,Risk of Recidivism,0.94,10,High,New,1,0 +6758,63159,57307,Probation,Poitier,Romalice,Frank,Male,African-American,11/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +55438,63146,57295,Probation,TAYLOR,BRIAN,NULL,Male,African-American,06/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +55438,63146,57295,Probation,TAYLOR,BRIAN,NULL,Male,African-American,06/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +55438,63146,57295,Probation,TAYLOR,BRIAN,NULL,Male,African-American,06/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55434,63143,57292,Probation,Boos-Patton,Christina,NULL,Female,Caucasian,01/04/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +55434,63143,57292,Probation,Boos-Patton,Christina,NULL,Female,Caucasian,01/04/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +55434,63143,57292,Probation,Boos-Patton,Christina,NULL,Female,Caucasian,01/04/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55443,63151,57300,Probation,whynes,albert,NULL,Male,African-American,02/19/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/17/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +55443,63151,57300,Probation,whynes,albert,NULL,Male,African-American,02/19/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/17/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +55443,63151,57300,Probation,whynes,albert,NULL,Male,African-American,02/19/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +5533,63130,38923,PRETRIAL,GAINES,GROVER,CLEVELAND,Male,African-American,09/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/17/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,Copy,1,0 +5533,63130,38923,PRETRIAL,GAINES,GROVER,CLEVELAND,Male,African-American,09/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/17/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,Copy,1,0 +5533,63130,38923,PRETRIAL,GAINES,GROVER,CLEVELAND,Male,African-American,09/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/17/13 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,Copy,1,0 +55471,63180,57327,PRETRIAL,Wilson,Malachi,NULL,Male,African-American,11/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/18/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +55471,63180,57327,PRETRIAL,Wilson,Malachi,NULL,Male,African-American,11/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/18/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +55471,63180,57327,PRETRIAL,Wilson,Malachi,NULL,Male,African-American,11/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +55453,63164,57312,Probation,farje,monica,NULL,Female,Hispanic,07/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/18/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +55453,63164,57312,Probation,farje,monica,NULL,Female,Hispanic,07/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/18/13 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +55453,63164,57312,Probation,farje,monica,NULL,Female,Hispanic,07/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55455,63167,57314,PRETRIAL,botkin,scott,NULL,Male,Caucasian,10/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +55455,63167,57314,PRETRIAL,botkin,scott,NULL,Male,Caucasian,10/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +55455,63167,57314,PRETRIAL,botkin,scott,NULL,Male,Caucasian,10/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +55475,63185,57332,Probation,perscott,blessing,NULL,Female,Caucasian,11/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +55475,63185,57332,Probation,perscott,blessing,NULL,Female,Caucasian,11/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +55475,63185,57332,Probation,perscott,blessing,NULL,Female,Caucasian,11/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55464,63172,57319,Probation,farquharson,dwayne,NULL,Male,African-American,01/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +55464,63172,57319,Probation,farquharson,dwayne,NULL,Male,African-American,01/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +55464,63172,57319,Probation,farquharson,dwayne,NULL,Male,African-American,01/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55458,63170,57317,Probation,Reaves,Neal,Javier,Male,Hispanic,06/26/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,New,1,0 +55458,63170,57317,Probation,Reaves,Neal,Javier,Male,Hispanic,06/26/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +55458,63170,57317,Probation,Reaves,Neal,Javier,Male,Hispanic,06/26/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55467,63175,57322,Probation,Tita,Narcis,NULL,Male,Caucasian,12/10/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/18/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +55467,63175,57322,Probation,Tita,Narcis,NULL,Male,Caucasian,12/10/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/18/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +55467,63175,57322,Probation,Tita,Narcis,NULL,Male,Caucasian,12/10/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +34204,63177,57324,PRETRIAL,irvine,mary,NULL,Female,Caucasian,09/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/18/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +34204,63177,57324,PRETRIAL,irvine,mary,NULL,Female,Caucasian,09/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/18/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +34204,63177,57324,PRETRIAL,irvine,mary,NULL,Female,Caucasian,09/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55472,63182,57329,Probation,Frazier,Brock,NULL,Male,Caucasian,05/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +55472,63182,57329,Probation,Frazier,Brock,NULL,Male,Caucasian,05/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +55472,63182,57329,Probation,Frazier,Brock,NULL,Male,Caucasian,05/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55474,63184,57331,Probation,Moscoso,William,NULL,Male,Hispanic,05/09/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +55474,63184,57331,Probation,Moscoso,William,NULL,Male,Hispanic,05/09/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +55474,63184,57331,Probation,Moscoso,William,NULL,Male,Hispanic,05/09/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55469,63179,57326,Probation,Baldwin,Thomas,NULL,Male,African-American,01/20/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +55469,63179,57326,Probation,Baldwin,Thomas,NULL,Male,African-American,01/20/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +55469,63179,57326,Probation,Baldwin,Thomas,NULL,Male,African-American,01/20/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +7114,63165,6705,PRETRIAL,baxley,lanis,NULL,Male,African-American,04/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,Copy,1,0 +7114,63165,6705,PRETRIAL,baxley,lanis,NULL,Male,African-American,04/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,Copy,1,0 +7114,63165,6705,PRETRIAL,baxley,lanis,NULL,Male,African-American,04/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +55463,63171,57318,Probation,Keen,Macy,NULL,Female,African-American,01/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +55463,63171,57318,Probation,Keen,Macy,NULL,Female,African-American,01/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +55463,63171,57318,Probation,Keen,Macy,NULL,Female,African-American,01/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55465,63173,57320,Probation,MASS,GARY,STEVEN,Male,Caucasian,08/18/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/18/13 0:00,1,Low,7,Risk of Violence,-4.36,1,Low,New,1,0 +55465,63173,57320,Probation,MASS,GARY,STEVEN,Male,Caucasian,08/18/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/18/13 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +55465,63173,57320,Probation,MASS,GARY,STEVEN,Male,Caucasian,08/18/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +27451,63186,26563,PRETRIAL,Brewer,Ronald,NULL,Male,Caucasian,12/20/70,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +27451,63186,26563,PRETRIAL,Brewer,Ronald,NULL,Male,Caucasian,12/20/70,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,8,Risk of Recidivism,-0.18,5,Medium,New,1,0 +27451,63186,26563,PRETRIAL,Brewer,Ronald,NULL,Male,Caucasian,12/20/70,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,31,8,High,New,1,0 +43482,63163,57311,PRETRIAL,WALKERFINCH,MONET,NULL,Female,African-American,10/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +43482,63163,57311,PRETRIAL,WALKERFINCH,MONET,NULL,Female,African-American,10/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,7,Medium,New,1,0 +43482,63163,57311,PRETRIAL,WALKERFINCH,MONET,NULL,Female,African-American,10/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +32511,63181,57328,PRETRIAL,Terlonge,Junior,NULL,Male,African-American,01/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +32511,63181,57328,PRETRIAL,Terlonge,Junior,NULL,Male,African-American,01/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +32511,63181,57328,PRETRIAL,Terlonge,Junior,NULL,Male,African-American,01/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55456,63168,57315,Probation,HOYOS,CARLOS,EMILIO,Male,Hispanic,08/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +55456,63168,57315,Probation,HOYOS,CARLOS,EMILIO,Male,Hispanic,08/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +55456,63168,57315,Probation,HOYOS,CARLOS,EMILIO,Male,Hispanic,08/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55470,63178,57325,Probation,FRADIN,KEISHA,NULL,Female,African-American,12/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +55470,63178,57325,Probation,FRADIN,KEISHA,NULL,Female,African-American,12/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +55470,63178,57325,Probation,FRADIN,KEISHA,NULL,Female,African-American,12/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55452,63162,57310,Probation,Hosang,Mark,NULL,Male,African-American,09/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +55452,63162,57310,Probation,Hosang,Mark,NULL,Male,African-American,09/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +55452,63162,57310,Probation,Hosang,Mark,NULL,Male,African-American,09/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55468,63176,57323,Probation,ardoin,corbin,NULL,Male,Caucasian,02/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +55468,63176,57323,Probation,ardoin,corbin,NULL,Male,Caucasian,02/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +55468,63176,57323,Probation,ardoin,corbin,NULL,Male,Caucasian,02/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55473,63183,57330,Probation,Balestrieri,Kory,NULL,Male,Caucasian,07/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +55473,63183,57330,Probation,Balestrieri,Kory,NULL,Male,Caucasian,07/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +55473,63183,57330,Probation,Balestrieri,Kory,NULL,Male,Caucasian,07/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55457,63169,57316,Probation,Guzdek,David,NULL,Male,Caucasian,03/16/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +55457,63169,57316,Probation,Guzdek,David,NULL,Male,Caucasian,03/16/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +55457,63169,57316,Probation,Guzdek,David,NULL,Male,Caucasian,03/16/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55478,63190,57335,PRETRIAL,fleurinord,iffanise,NULL,Female,African-American,07/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/19/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +55478,63190,57335,PRETRIAL,fleurinord,iffanise,NULL,Female,African-American,07/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/19/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +55478,63190,57335,PRETRIAL,fleurinord,iffanise,NULL,Female,African-American,07/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55489,63197,57342,PRETRIAL,Francois,Eric,NULL,Male,African-American,08/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +55489,63197,57342,PRETRIAL,Francois,Eric,NULL,Male,African-American,08/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +55489,63197,57342,PRETRIAL,Francois,Eric,NULL,Male,African-American,08/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55487,63195,57340,Probation,Rapp,John,NULL,Male,Caucasian,06/11/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/13 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +55487,63195,57340,Probation,Rapp,John,NULL,Male,Caucasian,06/11/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +55487,63195,57340,Probation,Rapp,John,NULL,Male,Caucasian,06/11/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55481,63192,57337,Probation,Arango,Jhon,NULL,Male,Hispanic,07/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +55481,63192,57337,Probation,Arango,Jhon,NULL,Male,Hispanic,07/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +55481,63192,57337,Probation,Arango,Jhon,NULL,Male,Hispanic,07/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55491,63199,57344,Probation,Guido,Rebecca,NULL,Female,Hispanic,01/20/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/19/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +55491,63199,57344,Probation,Guido,Rebecca,NULL,Female,Hispanic,01/20/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/19/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +55491,63199,57344,Probation,Guido,Rebecca,NULL,Female,Hispanic,01/20/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55482,63194,57339,Probation,Pereira,Andres,NULL,Male,Hispanic,04/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +55482,63194,57339,Probation,Pereira,Andres,NULL,Male,Hispanic,04/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +55482,63194,57339,Probation,Pereira,Andres,NULL,Male,Hispanic,04/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55490,63198,57343,Probation,johns,tranivia,NULL,Female,African-American,11/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +55490,63198,57343,Probation,johns,tranivia,NULL,Female,African-American,11/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/13 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +55490,63198,57343,Probation,johns,tranivia,NULL,Female,African-American,11/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55476,63187,57333,PRETRIAL,CALDERON,RICARDO,NULL,Male,Hispanic,01/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +55476,63187,57333,PRETRIAL,CALDERON,RICARDO,NULL,Male,Hispanic,01/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +55476,63187,57333,PRETRIAL,CALDERON,RICARDO,NULL,Male,Hispanic,01/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55479,63191,57336,Probation,Hernandez,Adam,David,Male,Hispanic,10/20/49,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/19/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +55479,63191,57336,Probation,Hernandez,Adam,David,Male,Hispanic,10/20/49,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/19/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +55479,63191,57336,Probation,Hernandez,Adam,David,Male,Hispanic,10/20/49,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55492,63200,57345,Probation,Johnson,Vinesha,NULL,Female,African-American,08/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +55492,63200,57345,Probation,Johnson,Vinesha,NULL,Female,African-American,08/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +55492,63200,57345,Probation,Johnson,Vinesha,NULL,Female,African-American,08/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55488,63196,57341,PRETRIAL,Laurent,Adolfo,NULL,Male,Hispanic,02/22/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +55488,63196,57341,PRETRIAL,Laurent,Adolfo,NULL,Male,Hispanic,02/22/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +55488,63196,57341,PRETRIAL,Laurent,Adolfo,NULL,Male,Hispanic,02/22/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55480,63193,57338,Probation,Tempelarr,Janet,NULL,Female,Hispanic,05/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/19/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +55480,63193,57338,Probation,Tempelarr,Janet,NULL,Female,Hispanic,05/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/19/13 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +55480,63193,57338,Probation,Tempelarr,Janet,NULL,Female,Hispanic,05/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55498,63206,57351,Probation,NIXON,RIKKEEMA,NULL,Female,African-American,03/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +55498,63206,57351,Probation,NIXON,RIKKEEMA,NULL,Female,African-American,03/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +55498,63206,57351,Probation,NIXON,RIKKEEMA,NULL,Female,African-American,03/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55493,63201,57346,PRETRIAL,lawrence,craig,NULL,Male,African-American,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +55493,63201,57346,PRETRIAL,lawrence,craig,NULL,Male,African-American,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +55493,63201,57346,PRETRIAL,lawrence,craig,NULL,Male,African-American,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55500,63208,57353,Probation,Guarcas-Castro,Fernando,NULL,Male,Hispanic,09/06/85,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,6/20/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +55500,63208,57353,Probation,Guarcas-Castro,Fernando,NULL,Male,Hispanic,09/06/85,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,6/20/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +55500,63208,57353,Probation,Guarcas-Castro,Fernando,NULL,Male,Hispanic,09/06/85,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55501,63209,57354,Probation,DAY,STANLEY,B,Male,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +55501,63209,57354,Probation,DAY,STANLEY,B,Male,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +55501,63209,57354,Probation,DAY,STANLEY,B,Male,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55506,63216,57361,Probation,Sopon Lopez,Juan,NULL,Male,Hispanic,02/21/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/20/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +55506,63216,57361,Probation,Sopon Lopez,Juan,NULL,Male,Hispanic,02/21/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/20/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +55506,63216,57361,Probation,Sopon Lopez,Juan,NULL,Male,Hispanic,02/21/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55507,63217,57362,PRETRIAL,Ward,Andrew,NULL,Female,Caucasian,04/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/13 0:00,2,Medium,7,Risk of Violence,-2.87,2,Low,New,1,0 +55507,63217,57362,PRETRIAL,Ward,Andrew,NULL,Female,Caucasian,04/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +55507,63217,57362,PRETRIAL,Ward,Andrew,NULL,Female,Caucasian,04/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/13 0:00,2,Medium,18,Risk of Failure to Appear,29,9,High,New,1,0 +55510,63221,57366,Probation,sofranec,linda,NULL,Female,Caucasian,12/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/20/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +55510,63221,57366,Probation,sofranec,linda,NULL,Female,Caucasian,12/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/20/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +55510,63221,57366,Probation,sofranec,linda,NULL,Female,Caucasian,12/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55503,63212,57357,Probation,hines,shauna,NULL,Female,African-American,02/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +55503,63212,57357,Probation,hines,shauna,NULL,Female,African-American,02/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +55503,63212,57357,Probation,hines,shauna,NULL,Female,African-American,02/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +49346,63219,57364,PRETRIAL,SLUYTER,WALTER,NULL,Male,Caucasian,05/22/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/20/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +49346,63219,57364,PRETRIAL,SLUYTER,WALTER,NULL,Male,Caucasian,05/22/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/20/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +49346,63219,57364,PRETRIAL,SLUYTER,WALTER,NULL,Male,Caucasian,05/22/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55495,63203,57348,Probation,MARSH,ALONZO,DEXTER,Male,African-American,06/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +55495,63203,57348,Probation,MARSH,ALONZO,DEXTER,Male,African-American,06/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +55495,63203,57348,Probation,MARSH,ALONZO,DEXTER,Male,African-American,06/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55497,63205,57350,Probation,Downey,Dorrine,NULL,Female,Caucasian,09/08/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/20/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +55497,63205,57350,Probation,Downey,Dorrine,NULL,Female,Caucasian,09/08/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/20/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +55497,63205,57350,Probation,Downey,Dorrine,NULL,Female,Caucasian,09/08/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55505,63215,57360,Probation,Schoolfield,Javier,NULL,Male,Hispanic,03/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +55505,63215,57360,Probation,Schoolfield,Javier,NULL,Male,Hispanic,03/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +55505,63215,57360,Probation,Schoolfield,Javier,NULL,Male,Hispanic,03/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55499,63207,57352,Probation,Franceschini,Rafael,NULL,Male,Hispanic,03/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +55499,63207,57352,Probation,Franceschini,Rafael,NULL,Male,Hispanic,03/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +55499,63207,57352,Probation,Franceschini,Rafael,NULL,Male,Hispanic,03/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55494,63202,57347,Probation,Bartra,Leyden,NULL,Male,Hispanic,03/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +55494,63202,57347,Probation,Bartra,Leyden,NULL,Male,Hispanic,03/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +55494,63202,57347,Probation,Bartra,Leyden,NULL,Male,Hispanic,03/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +43755,63210,57355,PRETRIAL,Ross,Jordan,Benjamin,Male,Caucasian,02/05/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +43755,63210,57355,PRETRIAL,Ross,Jordan,Benjamin,Male,Caucasian,02/05/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +43755,63210,57355,PRETRIAL,Ross,Jordan,Benjamin,Male,Caucasian,02/05/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55496,63204,57349,Probation,Belloso,Enrique,NULL,Male,Hispanic,03/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/20/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +55496,63204,57349,Probation,Belloso,Enrique,NULL,Male,Hispanic,03/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/20/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +55496,63204,57349,Probation,Belloso,Enrique,NULL,Male,Hispanic,03/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55502,63211,57356,Probation,Rodriguez,Geesel,NULL,Female,Hispanic,04/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +55502,63211,57356,Probation,Rodriguez,Geesel,NULL,Female,Hispanic,04/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +55502,63211,57356,Probation,Rodriguez,Geesel,NULL,Female,Hispanic,04/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55509,63220,57365,Probation,Kuessell,Joseph,NULL,Male,Caucasian,02/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +55509,63220,57365,Probation,Kuessell,Joseph,NULL,Male,Caucasian,02/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +55509,63220,57365,Probation,Kuessell,Joseph,NULL,Male,Caucasian,02/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +55508,63218,57363,Probation,Ventura Espinoza,Andres,NULL,Male,Hispanic,05/10/85,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,6/20/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +55508,63218,57363,Probation,Ventura Espinoza,Andres,NULL,Male,Hispanic,05/10/85,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,6/20/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +55508,63218,57363,Probation,Ventura Espinoza,Andres,NULL,Male,Hispanic,05/10/85,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,6/20/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55514,63225,57370,PRETRIAL,Farmer,Leroy,Darion,Male,African-American,04/21/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/21/13 0:00,2,Medium,7,Risk of Violence,-1.39,7,Medium,New,1,0 +55514,63225,57370,PRETRIAL,Farmer,Leroy,Darion,Male,African-American,04/21/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.6,3,Low,New,1,0 +55514,63225,57370,PRETRIAL,Farmer,Leroy,Darion,Male,African-American,04/21/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/21/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55519,63234,57379,Probation,Desinor,Kesenel,NULL,Male,African-American,09/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/21/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +55519,63234,57379,Probation,Desinor,Kesenel,NULL,Male,African-American,09/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/21/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +55519,63234,57379,Probation,Desinor,Kesenel,NULL,Male,African-American,09/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55517,63231,57376,PRETRIAL,JONES,FELISHA,NULL,Female,African-American,01/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/21/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +55517,63231,57376,PRETRIAL,JONES,FELISHA,NULL,Female,African-American,01/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/21/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +55517,63231,57376,PRETRIAL,JONES,FELISHA,NULL,Female,African-American,01/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55521,63236,57381,PRETRIAL,Corriveau,Pamela,NULL,Female,Caucasian,09/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/21/13 0:00,1,Low,7,Risk of Violence,-4.19,1,Low,New,1,0 +55521,63236,57381,PRETRIAL,Corriveau,Pamela,NULL,Female,Caucasian,09/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/21/13 0:00,1,Low,8,Risk of Recidivism,-2.62,1,Low,New,1,0 +55521,63236,57381,PRETRIAL,Corriveau,Pamela,NULL,Female,Caucasian,09/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +33107,63226,57371,PRETRIAL,SHAW,KIMBERLY,NULL,Female,Caucasian,07/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/21/13 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +33107,63226,57371,PRETRIAL,SHAW,KIMBERLY,NULL,Female,Caucasian,07/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +33107,63226,57371,PRETRIAL,SHAW,KIMBERLY,NULL,Female,Caucasian,07/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/21/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +29502,63233,57378,PRETRIAL,OSBURN,JAMES,WILLIAM,Male,Caucasian,02/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/21/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +29502,63233,57378,PRETRIAL,OSBURN,JAMES,WILLIAM,Male,Caucasian,02/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +29502,63233,57378,PRETRIAL,OSBURN,JAMES,WILLIAM,Male,Caucasian,02/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/21/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55511,63222,57367,PRETRIAL,Manganiotis,Raymond,NULL,Male,Caucasian,01/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,6/21/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +55511,63222,57367,PRETRIAL,Manganiotis,Raymond,NULL,Male,Caucasian,01/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,6/21/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +55511,63222,57367,PRETRIAL,Manganiotis,Raymond,NULL,Male,Caucasian,01/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,6/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55516,63229,57374,Probation,Clouse,Kelli,NULL,Female,Caucasian,06/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/21/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +55516,63229,57374,Probation,Clouse,Kelli,NULL,Female,Caucasian,06/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/21/13 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +55516,63229,57374,Probation,Clouse,Kelli,NULL,Female,Caucasian,06/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/21/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +20402,63230,57375,PRETRIAL,ORTEGA,VICTOR,NULL,Male,Hispanic,07/26/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/21/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +20402,63230,57375,PRETRIAL,ORTEGA,VICTOR,NULL,Male,Hispanic,07/26/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/21/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +20402,63230,57375,PRETRIAL,ORTEGA,VICTOR,NULL,Male,Hispanic,07/26/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/21/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +20363,63227,57372,Probation,Thomas,Shawn,William,Male,Caucasian,01/28/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +20363,63227,57372,Probation,Thomas,Shawn,William,Male,Caucasian,01/28/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.97,10,High,New,1,0 +20363,63227,57372,Probation,Thomas,Shawn,William,Male,Caucasian,01/28/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +55518,63232,57377,Probation,ohare,james,NULL,Male,Caucasian,05/06/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/21/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +55518,63232,57377,Probation,ohare,james,NULL,Male,Caucasian,05/06/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/21/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +55518,63232,57377,Probation,ohare,james,NULL,Male,Caucasian,05/06/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55520,63235,57380,PRETRIAL,Diaz,Rolando,NULL,Male,Hispanic,09/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/21/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +55520,63235,57380,PRETRIAL,Diaz,Rolando,NULL,Male,Hispanic,09/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/21/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +55520,63235,57380,PRETRIAL,Diaz,Rolando,NULL,Male,Hispanic,09/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/21/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55526,63245,57389,Probation,LAMB,DENNIS,WILLARD,Male,Caucasian,12/11/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/13 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +55526,63245,57389,Probation,LAMB,DENNIS,WILLARD,Male,Caucasian,12/11/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/13 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +55526,63245,57389,Probation,LAMB,DENNIS,WILLARD,Male,Caucasian,12/11/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55547,63266,57409,PRETRIAL,Hanrahan,Sean,NULL,Male,Caucasian,08/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +55547,63266,57409,PRETRIAL,Hanrahan,Sean,NULL,Male,Caucasian,08/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +55547,63266,57409,PRETRIAL,Hanrahan,Sean,NULL,Male,Caucasian,08/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +32337,63253,44509,Probation,Lamour,Frantz,NULL,Male,African-American,01/31/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.52,3,Low,Copy,1,0 +32337,63253,44509,Probation,Lamour,Frantz,NULL,Male,African-American,01/31/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,Copy,1,0 +32337,63253,44509,Probation,Lamour,Frantz,NULL,Male,African-American,01/31/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +39743,63251,57395,PRETRIAL,Querze,Paul,NULL,Male,Caucasian,02/28/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +39743,63251,57395,PRETRIAL,Querze,Paul,NULL,Male,Caucasian,02/28/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +39743,63251,57395,PRETRIAL,Querze,Paul,NULL,Male,Caucasian,02/28/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55539,63258,57401,Probation,King,Charlie,NULL,Male,African-American,05/17/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +55539,63258,57401,Probation,King,Charlie,NULL,Male,African-American,05/17/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +55539,63258,57401,Probation,King,Charlie,NULL,Male,African-American,05/17/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +54277,63237,55876,PRETRIAL,ORTEGACHIN,HEATHER,NULL,Female,Hispanic,11/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,Copy,1,0 +54277,63237,55876,PRETRIAL,ORTEGACHIN,HEATHER,NULL,Female,Hispanic,11/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,Copy,1,0 +54277,63237,55876,PRETRIAL,ORTEGACHIN,HEATHER,NULL,Female,Hispanic,11/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +55531,63250,57394,Probation,kelly,andre,NULL,Male,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +55531,63250,57394,Probation,kelly,andre,NULL,Male,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.94,10,High,New,1,0 +55531,63250,57394,Probation,kelly,andre,NULL,Male,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +55522,63240,57384,Probation,harris,bryan,NULL,Male,Caucasian,03/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +55522,63240,57384,Probation,harris,bryan,NULL,Male,Caucasian,03/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +55522,63240,57384,Probation,harris,bryan,NULL,Male,Caucasian,03/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55528,63247,57391,Probation,Green,Shevon,NULL,Male,African-American,02/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +55528,63247,57391,Probation,Green,Shevon,NULL,Male,African-American,02/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +55528,63247,57391,Probation,Green,Shevon,NULL,Male,African-American,02/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55543,63261,57404,PRETRIAL,Floris,kathy,NULL,Female,Caucasian,02/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/24/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +55543,63261,57404,PRETRIAL,Floris,kathy,NULL,Female,Caucasian,02/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/24/13 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +55543,63261,57404,PRETRIAL,Floris,kathy,NULL,Female,Caucasian,02/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55536,63254,57397,PRETRIAL,GUTIERREZ,ABRAHAM,NULL,Male,Hispanic,03/24/62,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,6/24/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +55536,63254,57397,PRETRIAL,GUTIERREZ,ABRAHAM,NULL,Male,Hispanic,03/24/62,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,6/24/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +55536,63254,57397,PRETRIAL,GUTIERREZ,ABRAHAM,NULL,Male,Hispanic,03/24/62,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +55540,63259,57402,Probation,Dorivaal,Adolfo,NULL,Male,Hispanic,01/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/24/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +55540,63259,57402,Probation,Dorivaal,Adolfo,NULL,Male,Hispanic,01/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/24/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +55540,63259,57402,Probation,Dorivaal,Adolfo,NULL,Male,Hispanic,01/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55524,63242,57386,Probation,CLAUDIO,WANDA,L,Female,Hispanic,10/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +55524,63242,57386,Probation,CLAUDIO,WANDA,L,Female,Hispanic,10/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +55524,63242,57386,Probation,CLAUDIO,WANDA,L,Female,Hispanic,10/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55545,63263,57406,Probation,Williams,Robert,Dean,Male,Caucasian,02/24/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +55545,63263,57406,Probation,Williams,Robert,Dean,Male,Caucasian,02/24/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +55545,63263,57406,Probation,Williams,Robert,Dean,Male,Caucasian,02/24/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55538,63257,57400,PRETRIAL,mccray,johnnie,NULL,Male,African-American,02/11/76,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +55538,63257,57400,PRETRIAL,mccray,johnnie,NULL,Male,African-American,02/11/76,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +55538,63257,57400,PRETRIAL,mccray,johnnie,NULL,Male,African-American,02/11/76,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,29,7,Medium,New,1,0 +55530,63249,57393,Probation,Stockton,Adriel,NULL,Male,Hispanic,08/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/13 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +55530,63249,57393,Probation,Stockton,Adriel,NULL,Male,Hispanic,08/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +55530,63249,57393,Probation,Stockton,Adriel,NULL,Male,Hispanic,08/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +1674,63252,57396,PRETRIAL,LHOTA,WAYNE,WILLIAM,Male,Caucasian,11/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +1674,63252,57396,PRETRIAL,LHOTA,WAYNE,WILLIAM,Male,Caucasian,11/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +1674,63252,57396,PRETRIAL,LHOTA,WAYNE,WILLIAM,Male,Caucasian,11/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,45,10,High,New,1,0 +55525,63244,57388,PRETRIAL,LeCain,Colby,NULL,Male,Caucasian,10/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +55525,63244,57388,PRETRIAL,LeCain,Colby,NULL,Male,Caucasian,10/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +55525,63244,57388,PRETRIAL,LeCain,Colby,NULL,Male,Caucasian,10/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55546,63265,57408,Probation,shaw,jeffrey,NULL,Male,African-American,09/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.02,1,Low,New,1,0 +55546,63265,57408,Probation,shaw,jeffrey,NULL,Male,African-American,09/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +55546,63265,57408,Probation,shaw,jeffrey,NULL,Male,African-American,09/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +55537,63255,57398,Probation,Varghese,Aji,NULL,Male,Asian,05/24/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +55537,63255,57398,Probation,Varghese,Aji,NULL,Male,Asian,05/24/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +55537,63255,57398,Probation,Varghese,Aji,NULL,Male,Asian,05/24/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55541,63260,57403,Probation,Quinones,Joshua,NULL,Male,Hispanic,08/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +55541,63260,57403,Probation,Quinones,Joshua,NULL,Male,Hispanic,08/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +55541,63260,57403,Probation,Quinones,Joshua,NULL,Male,Hispanic,08/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55527,63246,57390,Probation,Favitta,Eric,NULL,Male,Caucasian,09/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +55527,63246,57390,Probation,Favitta,Eric,NULL,Male,Caucasian,09/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +55527,63246,57390,Probation,Favitta,Eric,NULL,Male,Caucasian,09/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +42244,63264,57407,PRETRIAL,Homes,Tiffany,NULL,Female,African-American,12/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +42244,63264,57407,PRETRIAL,Homes,Tiffany,NULL,Female,African-American,12/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +42244,63264,57407,PRETRIAL,Homes,Tiffany,NULL,Female,African-American,12/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50387,63241,57385,PRETRIAL,Noel,Moriah,NULL,Female,Other,11/29/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/24/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +50387,63241,57385,PRETRIAL,Noel,Moriah,NULL,Female,Other,11/29/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/24/13 0:00,1,Low,8,Risk of Recidivism,-1.43,2,Low,New,1,0 +50387,63241,57385,PRETRIAL,Noel,Moriah,NULL,Female,Other,11/29/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55523,63239,57383,PRETRIAL,flooyd,randy,NULL,Male,African-American,07/22/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +55523,63239,57383,PRETRIAL,flooyd,randy,NULL,Male,African-American,07/22/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-0.7,3,Low,New,1,0 +55523,63239,57383,PRETRIAL,flooyd,randy,NULL,Male,African-American,07/22/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +55529,63248,57392,Probation,chance,CHRISTOPHER,NULL,Male,Caucasian,10/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +55529,63248,57392,Probation,chance,CHRISTOPHER,NULL,Male,Caucasian,10/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +55529,63248,57392,Probation,chance,CHRISTOPHER,NULL,Male,Caucasian,10/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55544,63262,57405,Probation,Tellez,Javier,NULL,Male,Hispanic,12/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +55544,63262,57405,Probation,Tellez,Javier,NULL,Male,Hispanic,12/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +55544,63262,57405,Probation,Tellez,Javier,NULL,Male,Hispanic,12/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55550,63269,57412,Probation,Dominguez,Julio,NULL,Male,Hispanic,10/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +55550,63269,57412,Probation,Dominguez,Julio,NULL,Male,Hispanic,10/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +55550,63269,57412,Probation,Dominguez,Julio,NULL,Male,Hispanic,10/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +44818,63276,57418,PRETRIAL,PIGOTT,GARY,GEORGE,Male,African-American,01/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +44818,63276,57418,PRETRIAL,PIGOTT,GARY,GEORGE,Male,African-American,01/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +44818,63276,57418,PRETRIAL,PIGOTT,GARY,GEORGE,Male,African-American,01/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55259,63283,57425,PRETRIAL,Butler,Cori,NULL,Male,African-American,07/05/77,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,New,1,0 +55259,63283,57425,PRETRIAL,Butler,Cori,NULL,Male,African-American,07/05/77,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +55259,63283,57425,PRETRIAL,Butler,Cori,NULL,Male,African-American,07/05/77,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +55558,63281,57423,Probation,foster,kevin,NULL,Male,Caucasian,09/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +55558,63281,57423,Probation,foster,kevin,NULL,Male,Caucasian,09/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +55558,63281,57423,Probation,foster,kevin,NULL,Male,Caucasian,09/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55548,63267,57410,Probation,Silva,Igor,NULL,Male,Hispanic,11/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +55548,63267,57410,Probation,Silva,Igor,NULL,Male,Hispanic,11/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +55548,63267,57410,Probation,Silva,Igor,NULL,Male,Hispanic,11/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +55557,63280,57422,Probation,vogt,brantley,NULL,Female,Caucasian,05/07/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/25/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +55557,63280,57422,Probation,vogt,brantley,NULL,Female,Caucasian,05/07/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/25/13 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +55557,63280,57422,Probation,vogt,brantley,NULL,Female,Caucasian,05/07/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +44971,63273,57415,PRETRIAL,Golden,Jennifer,NULL,Female,Caucasian,11/06/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +44971,63273,57415,PRETRIAL,Golden,Jennifer,NULL,Female,Caucasian,11/06/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +44971,63273,57415,PRETRIAL,Golden,Jennifer,NULL,Female,Caucasian,11/06/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55561,63286,57428,PRETRIAL,CAMBARERI,KATHERINE,NULL,Female,Caucasian,02/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +55561,63286,57428,PRETRIAL,CAMBARERI,KATHERINE,NULL,Female,Caucasian,02/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/13 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +55561,63286,57428,PRETRIAL,CAMBARERI,KATHERINE,NULL,Female,Caucasian,02/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55564,63288,57430,PRETRIAL,Massie,George,NULL,Male,Caucasian,10/09/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/13 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +55564,63288,57430,PRETRIAL,Massie,George,NULL,Male,Caucasian,10/09/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/13 0:00,1,Low,8,Risk of Recidivism,-2.75,1,Low,New,1,0 +55564,63288,57430,PRETRIAL,Massie,George,NULL,Male,Caucasian,10/09/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55555,63278,57420,Probation,VILLALOBOS,ELVIN,ALEJANDRO,Male,Hispanic,12/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +55555,63278,57420,Probation,VILLALOBOS,ELVIN,ALEJANDRO,Male,Hispanic,12/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +55555,63278,57420,Probation,VILLALOBOS,ELVIN,ALEJANDRO,Male,Hispanic,12/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55551,63270,57413,PRETRIAL,Braziel,Jimmy,NULL,Male,African-American,06/14/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,6/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +55551,63270,57413,PRETRIAL,Braziel,Jimmy,NULL,Male,African-American,06/14/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,6/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +55551,63270,57413,PRETRIAL,Braziel,Jimmy,NULL,Male,African-American,06/14/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,6/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +55549,63268,57411,Probation,jones,cliff,NULL,Male,African-American,04/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +55549,63268,57411,Probation,jones,cliff,NULL,Male,African-American,04/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +55549,63268,57411,Probation,jones,cliff,NULL,Male,African-American,04/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55552,63272,57414,Probation,Revelo,Bobby,NULL,Male,Hispanic,10/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +55552,63272,57414,Probation,Revelo,Bobby,NULL,Male,Hispanic,10/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +55552,63272,57414,Probation,Revelo,Bobby,NULL,Male,Hispanic,10/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +37817,63275,57417,PRETRIAL,Singh,Navin,NULL,Male,Caucasian,01/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +37817,63275,57417,PRETRIAL,Singh,Navin,NULL,Male,Caucasian,01/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +37817,63275,57417,PRETRIAL,Singh,Navin,NULL,Male,Caucasian,01/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55554,63277,57419,Probation,milligan,john,NULL,Male,Caucasian,05/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +55554,63277,57419,Probation,milligan,john,NULL,Male,Caucasian,05/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +55554,63277,57419,Probation,milligan,john,NULL,Male,Caucasian,05/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55559,63282,57424,Probation,BOZEMAN,MICHAEL,L,Male,Caucasian,05/27/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +55559,63282,57424,Probation,BOZEMAN,MICHAEL,L,Male,Caucasian,05/27/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +55559,63282,57424,Probation,BOZEMAN,MICHAEL,L,Male,Caucasian,05/27/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +1356,63271,57023,PRETRIAL,JAMES,TINA,BERNICE,Female,Other,08/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,Copy,1,0 +1356,63271,57023,PRETRIAL,JAMES,TINA,BERNICE,Female,Other,08/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,Copy,1,0 +1356,63271,57023,PRETRIAL,JAMES,TINA,BERNICE,Female,Other,08/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +55556,63279,57421,Probation,gaspard,kaycy,NULL,Male,African-American,11/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +55556,63279,57421,Probation,gaspard,kaycy,NULL,Male,African-American,11/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +55556,63279,57421,Probation,gaspard,kaycy,NULL,Male,African-American,11/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +50569,63287,57429,PRETRIAL,Terrero,Raul,E.,Male,Hispanic,11/05/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/25/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +50569,63287,57429,PRETRIAL,Terrero,Raul,E.,Male,Hispanic,11/05/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/25/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +50569,63287,57429,PRETRIAL,Terrero,Raul,E.,Male,Hispanic,11/05/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55553,63274,57416,Probation,Downing,Terrell,NULL,Male,African-American,05/24/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,7,Risk of Violence,-2.66,2,Low,New,1,0 +55553,63274,57416,Probation,Downing,Terrell,NULL,Male,African-American,05/24/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +55553,63274,57416,Probation,Downing,Terrell,NULL,Male,African-American,05/24/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55568,63292,57434,Probation,Johnson,Herbert,NULL,Male,African-American,03/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/26/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +55568,63292,57434,Probation,Johnson,Herbert,NULL,Male,African-American,03/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/26/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +55568,63292,57434,Probation,Johnson,Herbert,NULL,Male,African-American,03/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +38759,63295,57437,PRETRIAL,Lindsay,Robert,NULL,Male,Caucasian,05/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +38759,63295,57437,PRETRIAL,Lindsay,Robert,NULL,Male,Caucasian,05/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +38759,63295,57437,PRETRIAL,Lindsay,Robert,NULL,Male,Caucasian,05/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55584,63313,57454,Probation,madrid,carlos,NULL,Male,Hispanic,05/31/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +55584,63313,57454,Probation,madrid,carlos,NULL,Male,Hispanic,05/31/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +55584,63313,57454,Probation,madrid,carlos,NULL,Male,Hispanic,05/31/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55591,63321,57462,Probation,britton,patrick,NULL,Male,African-American,07/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +55591,63321,57462,Probation,britton,patrick,NULL,Male,African-American,07/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +55591,63321,57462,Probation,britton,patrick,NULL,Male,African-American,07/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55572,63300,57442,Probation,Jones,Rhonda,NULL,Female,African-American,05/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +55572,63300,57442,Probation,Jones,Rhonda,NULL,Female,African-American,05/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +55572,63300,57442,Probation,Jones,Rhonda,NULL,Female,African-American,05/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47136,63308,54899,PRETRIAL,Lamanna,Alexander,NULL,Male,Caucasian,12/17/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +47136,63308,54899,PRETRIAL,Lamanna,Alexander,NULL,Male,Caucasian,12/17/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.72,3,Low,New,1,0 +47136,63308,54899,PRETRIAL,Lamanna,Alexander,NULL,Male,Caucasian,12/17/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +55586,63316,57457,Probation,Berendowsky,Derek,NULL,Male,Caucasian,08/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +55586,63316,57457,Probation,Berendowsky,Derek,NULL,Male,Caucasian,08/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +55586,63316,57457,Probation,Berendowsky,Derek,NULL,Male,Caucasian,08/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55576,63303,57445,PRETRIAL,Gurden,Cunningham,NULL,Male,African-American,03/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.82,2,Low,New,1,0 +55576,63303,57445,PRETRIAL,Gurden,Cunningham,NULL,Male,African-American,03/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +55576,63303,57445,PRETRIAL,Gurden,Cunningham,NULL,Male,African-American,03/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55575,63305,57447,PRETRIAL,Diaz-gomez,Yan,NULL,Male,Hispanic,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +55575,63305,57447,PRETRIAL,Diaz-gomez,Yan,NULL,Male,Hispanic,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +55575,63305,57447,PRETRIAL,Diaz-gomez,Yan,NULL,Male,Hispanic,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55571,63298,57440,PRETRIAL,Ward,Nathaniel,NULL,Male,African-American,04/05/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/26/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +55571,63298,57440,PRETRIAL,Ward,Nathaniel,NULL,Male,African-American,04/05/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/26/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +55571,63298,57440,PRETRIAL,Ward,Nathaniel,NULL,Male,African-American,04/05/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55583,63312,57453,Probation,boyd,treyon,NULL,Male,African-American,10/17/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,4,High,7,Risk of Violence,-0.97,9,High,New,1,0 +55583,63312,57453,Probation,boyd,treyon,NULL,Male,African-American,10/17/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +55583,63312,57453,Probation,boyd,treyon,NULL,Male,African-American,10/17/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55589,63319,57460,Probation,Barresi,Michael,NULL,Male,Caucasian,01/21/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/26/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +55589,63319,57460,Probation,Barresi,Michael,NULL,Male,Caucasian,01/21/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/26/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +55589,63319,57460,Probation,Barresi,Michael,NULL,Male,Caucasian,01/21/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +11871,63293,57435,Probation,Vanhorne,Courtney,R,Male,African-American,10/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/26/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +11871,63293,57435,Probation,Vanhorne,Courtney,R,Male,African-American,10/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +11871,63293,57435,Probation,Vanhorne,Courtney,R,Male,African-American,10/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +7448,63314,57455,PRETRIAL,Hernandez,Edward,Charles,Male,Caucasian,11/17/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +7448,63314,57455,PRETRIAL,Hernandez,Edward,Charles,Male,Caucasian,11/17/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +7448,63314,57455,PRETRIAL,Hernandez,Edward,Charles,Male,Caucasian,11/17/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55581,63310,57451,Probation,hull,joseph,NULL,Male,Caucasian,02/28/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/26/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +55581,63310,57451,Probation,hull,joseph,NULL,Male,Caucasian,02/28/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/26/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +55581,63310,57451,Probation,hull,joseph,NULL,Male,Caucasian,02/28/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55591,63324,57462,Probation,britton,patrick,NULL,Male,African-American,07/20/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,Copy,1,0 +55591,63324,57462,Probation,britton,patrick,NULL,Male,African-American,07/20/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,Copy,1,0 +55591,63324,57462,Probation,britton,patrick,NULL,Male,African-American,07/20/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +55578,63304,57446,Probation,Gayle,Joanna,NULL,Female,African-American,05/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/13 0:00,2,Medium,7,Risk of Violence,-2.72,2,Low,New,1,0 +55578,63304,57446,Probation,Gayle,Joanna,NULL,Female,African-American,05/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +55578,63304,57446,Probation,Gayle,Joanna,NULL,Female,African-American,05/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55567,63291,57433,PRETRIAL,Ellis,David,NULL,Male,Caucasian,09/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +55567,63291,57433,PRETRIAL,Ellis,David,NULL,Male,Caucasian,09/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +55567,63291,57433,PRETRIAL,Ellis,David,NULL,Male,Caucasian,09/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55570,63296,57438,Probation,Singh,Alvin,Jaipanl,Male,Hispanic,03/22/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/26/13 0:00,2,Medium,7,Risk of Violence,-2.45,3,Low,New,1,0 +55570,63296,57438,Probation,Singh,Alvin,Jaipanl,Male,Hispanic,03/22/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +55570,63296,57438,Probation,Singh,Alvin,Jaipanl,Male,Hispanic,03/22/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/26/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +49574,63299,57441,PRETRIAL,Dixon,Jelani,Anwar,Male,African-American,11/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +49574,63299,57441,PRETRIAL,Dixon,Jelani,Anwar,Male,African-American,11/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +49574,63299,57441,PRETRIAL,Dixon,Jelani,Anwar,Male,African-American,11/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55587,63317,57458,PRETRIAL,Ingber,Ryan,NULL,Male,Caucasian,04/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +55587,63317,57458,PRETRIAL,Ingber,Ryan,NULL,Male,Caucasian,04/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +55587,63317,57458,PRETRIAL,Ingber,Ryan,NULL,Male,Caucasian,04/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +43501,63307,57449,PRETRIAL,JOHNSON,JOSHUA,NULL,Male,African-American,08/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,New,1,0 +43501,63307,57449,PRETRIAL,JOHNSON,JOSHUA,NULL,Male,African-American,08/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +43501,63307,57449,PRETRIAL,JOHNSON,JOSHUA,NULL,Male,African-American,08/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55580,63309,57450,Probation,Forte,Natalia,Melanie,Female,Hispanic,07/05/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +55580,63309,57450,Probation,Forte,Natalia,Melanie,Female,Hispanic,07/05/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +55580,63309,57450,Probation,Forte,Natalia,Melanie,Female,Hispanic,07/05/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55585,63315,57456,Probation,Ruiz,Israel,NULL,Male,Hispanic,12/07/57,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,6/26/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +55585,63315,57456,Probation,Ruiz,Israel,NULL,Male,Hispanic,12/07/57,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,6/26/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +55585,63315,57456,Probation,Ruiz,Israel,NULL,Male,Hispanic,12/07/57,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55569,63294,57436,Probation,Sarmiento,Juan,NULL,Male,Hispanic,01/31/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +55569,63294,57436,Probation,Sarmiento,Juan,NULL,Male,Hispanic,01/31/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +55569,63294,57436,Probation,Sarmiento,Juan,NULL,Male,Hispanic,01/31/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55579,63306,57448,Probation,johnston,stuart,NULL,Male,Caucasian,05/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +55579,63306,57448,Probation,johnston,stuart,NULL,Male,Caucasian,05/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +55579,63306,57448,Probation,johnston,stuart,NULL,Male,Caucasian,05/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55331,63323,57463,PRETRIAL,gillis,derrick,NULL,Male,African-American,01/11/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/26/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +55331,63323,57463,PRETRIAL,gillis,derrick,NULL,Male,African-American,01/11/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +55331,63323,57463,PRETRIAL,gillis,derrick,NULL,Male,African-American,01/11/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55574,63302,57444,PRETRIAL,Demps,Anthony,NULL,Male,African-American,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +55574,63302,57444,PRETRIAL,Demps,Anthony,NULL,Male,African-American,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +55574,63302,57444,PRETRIAL,Demps,Anthony,NULL,Male,African-American,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +42233,63297,57439,PRETRIAL,Kramer,Sarah,NULL,Female,Caucasian,10/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +42233,63297,57439,PRETRIAL,Kramer,Sarah,NULL,Female,Caucasian,10/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +42233,63297,57439,PRETRIAL,Kramer,Sarah,NULL,Female,Caucasian,10/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55566,63290,57432,Probation,Givens,Caroline,NULL,Female,Caucasian,01/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.15,4,Low,New,1,0 +55566,63290,57432,Probation,Givens,Caroline,NULL,Female,Caucasian,01/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,8,High,New,1,0 +55566,63290,57432,Probation,Givens,Caroline,NULL,Female,Caucasian,01/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55582,63311,57452,Probation,hay,stevette,NULL,Female,Caucasian,03/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +55582,63311,57452,Probation,hay,stevette,NULL,Female,Caucasian,03/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +55582,63311,57452,Probation,hay,stevette,NULL,Female,Caucasian,03/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55588,63318,57459,PRETRIAL,Bradley,David,NULL,Male,Caucasian,07/31/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/26/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +55588,63318,57459,PRETRIAL,Bradley,David,NULL,Male,Caucasian,07/31/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/26/13 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +55588,63318,57459,PRETRIAL,Bradley,David,NULL,Male,Caucasian,07/31/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/26/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55603,63341,57478,Probation,Zinn,Brent,NULL,Male,Caucasian,07/16/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +55603,63341,57478,Probation,Zinn,Brent,NULL,Male,Caucasian,07/16/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +55603,63341,57478,Probation,Zinn,Brent,NULL,Male,Caucasian,07/16/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +26825,63339,57476,PRETRIAL,Molina,Lamar,NULL,Male,African-American,12/28/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +26825,63339,57476,PRETRIAL,Molina,Lamar,NULL,Male,African-American,12/28/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +26825,63339,57476,PRETRIAL,Molina,Lamar,NULL,Male,African-American,12/28/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55610,63348,57485,Probation,gomez,janet,NULL,Male,Caucasian,10/18/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +55610,63348,57485,Probation,gomez,janet,NULL,Male,Caucasian,10/18/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +55610,63348,57485,Probation,gomez,janet,NULL,Male,Caucasian,10/18/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55594,63327,57465,Probation,OWENS,SAMANTHA,NULL,Female,Caucasian,09/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +55594,63327,57465,Probation,OWENS,SAMANTHA,NULL,Female,Caucasian,09/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +55594,63327,57465,Probation,OWENS,SAMANTHA,NULL,Female,Caucasian,09/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55280,63332,57106,PRETRIAL,Pollard,Derik,NULL,Male,Caucasian,06/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,Copy,1,0 +55280,63332,57106,PRETRIAL,Pollard,Derik,NULL,Male,Caucasian,06/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,Copy,1,0 +55280,63332,57106,PRETRIAL,Pollard,Derik,NULL,Male,Caucasian,06/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +55599,63336,57473,Probation,COSTA,LIZZETTE,NULL,Male,Hispanic,03/10/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +55599,63336,57473,Probation,COSTA,LIZZETTE,NULL,Male,Hispanic,03/10/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +55599,63336,57473,Probation,COSTA,LIZZETTE,NULL,Male,Hispanic,03/10/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55615,63353,57490,Probation,BOURQUE,KELLY,MARIE,Female,Caucasian,11/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +55615,63353,57490,Probation,BOURQUE,KELLY,MARIE,Female,Caucasian,11/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +55615,63353,57490,Probation,BOURQUE,KELLY,MARIE,Female,Caucasian,11/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55613,63351,57488,Probation,apgar,robert,NULL,Male,Caucasian,02/05/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/27/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +55613,63351,57488,Probation,apgar,robert,NULL,Male,Caucasian,02/05/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/27/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +55613,63351,57488,Probation,apgar,robert,NULL,Male,Caucasian,02/05/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55596,63330,57468,Probation,Juarezdomingo,Pedro,NULL,Male,Hispanic,08/28/88,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,6/27/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +55596,63330,57468,Probation,Juarezdomingo,Pedro,NULL,Male,Hispanic,08/28/88,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,6/27/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +55596,63330,57468,Probation,Juarezdomingo,Pedro,NULL,Male,Hispanic,08/28/88,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55605,63343,57480,Probation,BHIM,ANEIL,NULL,Male,Other,01/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +55605,63343,57480,Probation,BHIM,ANEIL,NULL,Male,Other,01/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +55605,63343,57480,Probation,BHIM,ANEIL,NULL,Male,Other,01/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55608,63346,57483,Probation,laboriel,herman,NULL,Male,African-American,05/29/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +55608,63346,57483,Probation,laboriel,herman,NULL,Male,African-American,05/29/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +55608,63346,57483,Probation,laboriel,herman,NULL,Male,African-American,05/29/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +44331,63325,55382,PRETRIAL,Clouse,Ronald,NULL,Male,Caucasian,05/22/68,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +44331,63325,55382,PRETRIAL,Clouse,Ronald,NULL,Male,Caucasian,05/22/68,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +44331,63325,55382,PRETRIAL,Clouse,Ronald,NULL,Male,Caucasian,05/22/68,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55601,63338,57475,Probation,lydting,dennis,NULL,Male,Caucasian,08/09/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,7,Risk of Violence,-4.39,1,Low,New,1,0 +55601,63338,57475,Probation,lydting,dennis,NULL,Male,Caucasian,08/09/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +55601,63338,57475,Probation,lydting,dennis,NULL,Male,Caucasian,08/09/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +41718,63335,57472,PRETRIAL,FALLA,TAMMY,LORRAINE,Female,Caucasian,09/12/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +41718,63335,57472,PRETRIAL,FALLA,TAMMY,LORRAINE,Female,Caucasian,09/12/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +41718,63335,57472,PRETRIAL,FALLA,TAMMY,LORRAINE,Female,Caucasian,09/12/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55611,63349,57486,Probation,Morganti,Daniel,NULL,Male,Caucasian,03/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +55611,63349,57486,Probation,Morganti,Daniel,NULL,Male,Caucasian,03/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.92,10,High,New,1,0 +55611,63349,57486,Probation,Morganti,Daniel,NULL,Male,Caucasian,03/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,43,10,High,New,1,0 +55595,63328,57466,Probation,Ferguson,Amanda,NULL,Female,Caucasian,09/25/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +55595,63328,57466,Probation,Ferguson,Amanda,NULL,Female,Caucasian,09/25/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +55595,63328,57466,Probation,Ferguson,Amanda,NULL,Female,Caucasian,09/25/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55597,63331,57469,PRETRIAL,Powell,Dwayne,NULL,Male,African-American,09/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +55597,63331,57469,PRETRIAL,Powell,Dwayne,NULL,Male,African-American,09/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +55597,63331,57469,PRETRIAL,Powell,Dwayne,NULL,Male,African-American,09/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55607,63345,57482,Probation,JOHNSON,DAVID,NULL,Male,African-American,08/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +55607,63345,57482,Probation,JOHNSON,DAVID,NULL,Male,African-American,08/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +55607,63345,57482,Probation,JOHNSON,DAVID,NULL,Male,African-American,08/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55592,63326,57464,Probation,Mcfarland,Gregory,NULL,Male,Caucasian,12/12/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +55592,63326,57464,Probation,Mcfarland,Gregory,NULL,Male,Caucasian,12/12/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +55592,63326,57464,Probation,Mcfarland,Gregory,NULL,Male,Caucasian,12/12/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50198,63333,57470,PRETRIAL,vanniekek,rocio,NULL,Female,Caucasian,10/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +50198,63333,57470,PRETRIAL,vanniekek,rocio,NULL,Female,Caucasian,10/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +50198,63333,57470,PRETRIAL,vanniekek,rocio,NULL,Female,Caucasian,10/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55609,63347,57484,Probation,JEAN-PIERRE,MICHY,NULL,Male,African-American,07/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +55609,63347,57484,Probation,JEAN-PIERRE,MICHY,NULL,Male,African-American,07/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +55609,63347,57484,Probation,JEAN-PIERRE,MICHY,NULL,Male,African-American,07/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55616,63354,57491,Probation,Thomas,Lloyd,NULL,Male,African-American,06/24/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +55616,63354,57491,Probation,Thomas,Lloyd,NULL,Male,African-American,06/24/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/13 0:00,1,Low,8,Risk of Recidivism,-2.75,1,Low,New,1,0 +55616,63354,57491,Probation,Thomas,Lloyd,NULL,Male,African-American,06/24/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +44888,63356,55354,DRRD,Hardin,Leon,NULL,Male,African-American,09/27/67,17,All Scales,Intake,English,Post Sentence,Probation,Significant Other,6/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +44888,63356,55354,DRRD,Hardin,Leon,NULL,Male,African-American,09/27/67,17,All Scales,Intake,English,Post Sentence,Probation,Significant Other,6/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,9,High,New,1,0 +44888,63356,55354,DRRD,Hardin,Leon,NULL,Male,African-American,09/27/67,17,All Scales,Intake,English,Post Sentence,Probation,Significant Other,6/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +55612,63350,57487,Probation,Jimenez,Kari,NULL,Female,Hispanic,10/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +55612,63350,57487,Probation,Jimenez,Kari,NULL,Female,Hispanic,10/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +55612,63350,57487,Probation,Jimenez,Kari,NULL,Female,Hispanic,10/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55614,63352,57489,Probation,Prieto,Alejandro,NULL,Male,Hispanic,06/07/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +55614,63352,57489,Probation,Prieto,Alejandro,NULL,Male,Hispanic,06/07/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +55614,63352,57489,Probation,Prieto,Alejandro,NULL,Male,Hispanic,06/07/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55600,63337,57474,PRETRIAL,Obriant,Jameeka,NULL,Female,African-American,05/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +55600,63337,57474,PRETRIAL,Obriant,Jameeka,NULL,Female,African-American,05/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +55600,63337,57474,PRETRIAL,Obriant,Jameeka,NULL,Female,African-American,05/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +55606,63344,57481,Probation,TROLL,HENRY,NULL,Male,Hispanic,03/17/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +55606,63344,57481,Probation,TROLL,HENRY,NULL,Male,Hispanic,03/17/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +55606,63344,57481,Probation,TROLL,HENRY,NULL,Male,Hispanic,03/17/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55593,63329,57467,PRETRIAL,dunn,brian,NULL,Male,Caucasian,06/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +55593,63329,57467,PRETRIAL,dunn,brian,NULL,Male,Caucasian,06/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +55593,63329,57467,PRETRIAL,dunn,brian,NULL,Male,Caucasian,06/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55598,63334,57471,Probation,Marrow,Gary,NULL,Male,Caucasian,10/04/52,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +55598,63334,57471,Probation,Marrow,Gary,NULL,Male,Caucasian,10/04/52,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +55598,63334,57471,Probation,Marrow,Gary,NULL,Male,Caucasian,10/04/52,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +46804,63355,56322,PRETRIAL,BUFFORD,BRADEN,NULL,Male,Caucasian,05/30/94,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/27/13 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +46804,63355,56322,PRETRIAL,BUFFORD,BRADEN,NULL,Male,Caucasian,05/30/94,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/27/13 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +46804,63355,56322,PRETRIAL,BUFFORD,BRADEN,NULL,Male,Caucasian,05/30/94,17,All Scales,Intake,English,Conditional Release,Probation,Single,6/27/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55604,63342,57479,Probation,Ashraf,Fatima,NULL,Female,Asian,11/30/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/27/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +55604,63342,57479,Probation,Ashraf,Fatima,NULL,Female,Asian,11/30/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/27/13 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +55604,63342,57479,Probation,Ashraf,Fatima,NULL,Female,Asian,11/30/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55620,63360,57495,PRETRIAL,Burley,Ricky,NULL,Male,African-American,01/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/28/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +55620,63360,57495,PRETRIAL,Burley,Ricky,NULL,Male,African-American,01/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/28/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +55620,63360,57495,PRETRIAL,Burley,Ricky,NULL,Male,African-American,01/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/28/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55621,63363,57498,Probation,JENNINGS,LATOYA,NULL,Female,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/28/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +55621,63363,57498,Probation,JENNINGS,LATOYA,NULL,Female,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/28/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +55621,63363,57498,Probation,JENNINGS,LATOYA,NULL,Female,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55623,63368,57502,Probation,Barnett,Keionis,NULL,Male,African-American,10/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +55623,63368,57502,Probation,Barnett,Keionis,NULL,Male,African-American,10/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +55623,63368,57502,Probation,Barnett,Keionis,NULL,Male,African-American,10/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55618,63358,57493,Probation,Gunn,Pamela,Denise,Female,African-American,06/23/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/28/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +55618,63358,57493,Probation,Gunn,Pamela,Denise,Female,African-American,06/23/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/28/13 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +55618,63358,57493,Probation,Gunn,Pamela,Denise,Female,African-American,06/23/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/28/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55625,63371,57505,Probation,Scott,Victor,NULL,Male,African-American,04/12/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +55625,63371,57505,Probation,Scott,Victor,NULL,Male,African-American,04/12/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +55625,63371,57505,Probation,Scott,Victor,NULL,Male,African-American,04/12/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55626,63373,57507,Probation,BECKLES,PETER,ERVIN,Male,African-American,02/13/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +55626,63373,57507,Probation,BECKLES,PETER,ERVIN,Male,African-American,02/13/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +55626,63373,57507,Probation,BECKLES,PETER,ERVIN,Male,African-American,02/13/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55628,63375,57509,Probation,Helverson,Brandon,NULL,Male,Caucasian,08/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +55628,63375,57509,Probation,Helverson,Brandon,NULL,Male,Caucasian,08/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +55628,63375,57509,Probation,Helverson,Brandon,NULL,Male,Caucasian,08/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55630,63377,57511,Probation,Drucker,Heather,NULL,Female,Caucasian,08/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +55630,63377,57511,Probation,Drucker,Heather,NULL,Female,Caucasian,08/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +55630,63377,57511,Probation,Drucker,Heather,NULL,Female,Caucasian,08/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +2015,63361,57496,PRETRIAL,Duncan,Darnell,Lin,Male,African-American,04/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +2015,63361,57496,PRETRIAL,Duncan,Darnell,Lin,Male,African-American,04/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +2015,63361,57496,PRETRIAL,Duncan,Darnell,Lin,Male,African-American,04/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +37654,63366,57500,PRETRIAL,Plunkett,Paul,NULL,Male,Other,02/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.12,4,Low,New,1,0 +37654,63366,57500,PRETRIAL,Plunkett,Paul,NULL,Male,Other,02/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +37654,63366,57500,PRETRIAL,Plunkett,Paul,NULL,Male,Other,02/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55624,63370,57504,Probation,gonzalez,michael,NULL,Male,Hispanic,07/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +55624,63370,57504,Probation,gonzalez,michael,NULL,Male,Hispanic,07/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +55624,63370,57504,Probation,gonzalez,michael,NULL,Male,Hispanic,07/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +8962,63372,57506,PRETRIAL,BURKE,BRIAN,MAURICE,Male,African-American,08/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +8962,63372,57506,PRETRIAL,BURKE,BRIAN,MAURICE,Male,African-American,08/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,9,High,New,1,0 +8962,63372,57506,PRETRIAL,BURKE,BRIAN,MAURICE,Male,African-American,08/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +55619,63359,57494,PRETRIAL,Alegria,Wilberto,NULL,Male,Hispanic,01/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,6/28/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +55619,63359,57494,PRETRIAL,Alegria,Wilberto,NULL,Male,Hispanic,01/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,6/28/13 0:00,4,High,8,Risk of Recidivism,0.7,10,High,New,1,0 +55619,63359,57494,PRETRIAL,Alegria,Wilberto,NULL,Male,Hispanic,01/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,6/28/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55622,63364,57499,Probation,thomas,crystal,NULL,Female,African-American,09/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.63,2,Low,New,1,0 +55622,63364,57499,Probation,thomas,crystal,NULL,Female,African-American,09/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,9,High,New,1,0 +55622,63364,57499,Probation,thomas,crystal,NULL,Female,African-American,09/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,New,1,0 +55617,63357,57492,PRETRIAL,floyd,jacolby,NULL,Male,African-American,03/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/28/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +55617,63357,57492,PRETRIAL,floyd,jacolby,NULL,Male,African-American,03/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/28/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +55617,63357,57492,PRETRIAL,floyd,jacolby,NULL,Male,African-American,03/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/28/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55627,63374,57508,PRETRIAL,Masselli,John,NULL,Male,Caucasian,04/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/28/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +55627,63374,57508,PRETRIAL,Masselli,John,NULL,Male,Caucasian,04/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/28/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +55627,63374,57508,PRETRIAL,Masselli,John,NULL,Male,Caucasian,04/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +8488,63362,57497,PRETRIAL,Francis,Michael,Melvin,Male,African-American,11/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,New,1,0 +8488,63362,57497,PRETRIAL,Francis,Michael,Melvin,Male,African-American,11/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +8488,63362,57497,PRETRIAL,Francis,Michael,Melvin,Male,African-American,11/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55636,63383,57517,PRETRIAL,Pierresaint,Gregory,NULL,Male,African-American,10/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +55636,63383,57517,PRETRIAL,Pierresaint,Gregory,NULL,Male,African-American,10/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +55636,63383,57517,PRETRIAL,Pierresaint,Gregory,NULL,Male,African-American,10/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +38508,63390,57524,Probation,Pendergrass,Sheronnye,NULL,Female,African-American,04/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +38508,63390,57524,Probation,Pendergrass,Sheronnye,NULL,Female,African-American,04/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,9,High,New,1,0 +38508,63390,57524,Probation,Pendergrass,Sheronnye,NULL,Female,African-American,04/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +55631,63378,57512,PRETRIAL,CHISWELL,DANIEL,NULL,Male,Caucasian,08/31/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/1/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +55631,63378,57512,PRETRIAL,CHISWELL,DANIEL,NULL,Male,Caucasian,08/31/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/1/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +55631,63378,57512,PRETRIAL,CHISWELL,DANIEL,NULL,Male,Caucasian,08/31/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55644,63395,57529,Probation,riebe,robert,lee,Male,Caucasian,07/17/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/1/13 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +55644,63395,57529,Probation,riebe,robert,lee,Male,Caucasian,07/17/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/1/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +55644,63395,57529,Probation,riebe,robert,lee,Male,Caucasian,07/17/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/1/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +55649,63404,57536,Probation,LINDOR,GERCLURE,NULL,Female,African-American,03/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +55649,63404,57536,Probation,LINDOR,GERCLURE,NULL,Female,African-American,03/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +55649,63404,57536,Probation,LINDOR,GERCLURE,NULL,Female,African-American,03/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55637,63385,57519,PRETRIAL,Dejesus,Joseph,NULL,Male,Hispanic,09/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/1/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +55637,63385,57519,PRETRIAL,Dejesus,Joseph,NULL,Male,Hispanic,09/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +55637,63385,57519,PRETRIAL,Dejesus,Joseph,NULL,Male,Hispanic,09/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/1/13 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,New,1,0 +55642,63393,57527,PRETRIAL,Vaughn,Eugene,NULL,Male,African-American,06/10/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/1/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +55642,63393,57527,PRETRIAL,Vaughn,Eugene,NULL,Male,African-American,06/10/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/1/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +55642,63393,57527,PRETRIAL,Vaughn,Eugene,NULL,Male,African-American,06/10/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +43566,63388,57522,PRETRIAL,Claudio,Mario,NULL,Male,Caucasian,06/16/73,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,7/1/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +43566,63388,57522,PRETRIAL,Claudio,Mario,NULL,Male,Caucasian,06/16/73,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,7/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +43566,63388,57522,PRETRIAL,Claudio,Mario,NULL,Male,Caucasian,06/16/73,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,7/1/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +55633,63380,57514,Broward County,Hill,Michael,NULL,Male,African-American,01/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/1/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +55633,63380,57514,Broward County,Hill,Michael,NULL,Male,African-American,01/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/1/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +55633,63380,57514,Broward County,Hill,Michael,NULL,Male,African-American,01/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55646,63401,57533,PRETRIAL,almeida,anthony,NULL,Male,Caucasian,08/29/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +55646,63401,57533,PRETRIAL,almeida,anthony,NULL,Male,Caucasian,08/29/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +55646,63401,57533,PRETRIAL,almeida,anthony,NULL,Male,Caucasian,08/29/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,3,Low,New,1,0 +55638,63387,57521,Probation,dufrene,marjorie,NULL,Female,African-American,01/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/1/13 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +55638,63387,57521,Probation,dufrene,marjorie,NULL,Female,African-American,01/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +55638,63387,57521,Probation,dufrene,marjorie,NULL,Female,African-American,01/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/1/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55645,63400,57532,Probation,ANDREWS,WILEY,M,Male,Caucasian,12/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +55645,63400,57532,Probation,ANDREWS,WILEY,M,Male,Caucasian,12/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +55645,63400,57532,Probation,ANDREWS,WILEY,M,Male,Caucasian,12/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +4729,63382,57516,PRETRIAL,KYLES,TERRILL,ALBERT,Male,African-American,10/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +4729,63382,57516,PRETRIAL,KYLES,TERRILL,ALBERT,Male,African-American,10/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +4729,63382,57516,PRETRIAL,KYLES,TERRILL,ALBERT,Male,African-American,10/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +35921,63396,57530,PRETRIAL,Mcdowell,Aston,NULL,Male,African-American,04/04/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/1/13 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +35921,63396,57530,PRETRIAL,Mcdowell,Aston,NULL,Male,African-American,04/04/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/1/13 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +35921,63396,57530,PRETRIAL,Mcdowell,Aston,NULL,Male,African-American,04/04/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55635,63384,57518,Probation,Serrano,Luis,A,Male,Hispanic,01/29/64,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,7/1/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +55635,63384,57518,Probation,Serrano,Luis,A,Male,Hispanic,01/29/64,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,7/1/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +55635,63384,57518,Probation,Serrano,Luis,A,Male,Hispanic,01/29/64,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55648,63403,57535,Probation,Parker,Brian,Keith,Male,African-American,07/30/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/1/13 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +55648,63403,57535,Probation,Parker,Brian,Keith,Male,African-American,07/30/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +55648,63403,57535,Probation,Parker,Brian,Keith,Male,African-American,07/30/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/1/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +45346,63398,52422,PRETRIAL,Watson,Kennan,NULL,Male,African-American,12/20/88,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/1/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +45346,63398,52422,PRETRIAL,Watson,Kennan,NULL,Male,African-American,12/20/88,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/1/13 0:00,1,Low,8,Risk of Recidivism,-0.6,3,Low,New,1,0 +45346,63398,52422,PRETRIAL,Watson,Kennan,NULL,Male,African-American,12/20/88,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +39319,63386,57520,PRETRIAL,Higgins,Kwameel,NULL,Male,African-American,12/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +39319,63386,57520,PRETRIAL,Higgins,Kwameel,NULL,Male,African-American,12/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +39319,63386,57520,PRETRIAL,Higgins,Kwameel,NULL,Male,African-American,12/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55643,63394,57528,Probation,korzun,tatyana,NULL,Female,Caucasian,06/29/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +55643,63394,57528,Probation,korzun,tatyana,NULL,Female,Caucasian,06/29/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +55643,63394,57528,Probation,korzun,tatyana,NULL,Female,Caucasian,06/29/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55632,63379,57513,Probation,BROEK,DAVID,NULL,Male,Caucasian,06/01/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +55632,63379,57513,Probation,BROEK,DAVID,NULL,Male,Caucasian,06/01/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +55632,63379,57513,Probation,BROEK,DAVID,NULL,Male,Caucasian,06/01/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55647,63402,57534,Probation,Oconnell,Cristina,NULL,Female,Caucasian,12/06/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +55647,63402,57534,Probation,Oconnell,Cristina,NULL,Female,Caucasian,12/06/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +55647,63402,57534,Probation,Oconnell,Cristina,NULL,Female,Caucasian,12/06/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55639,63389,57523,Probation,Lovio hernandez,Narciel,NULL,Male,Hispanic,04/01/91,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,7/1/13 0:00,2,Medium,7,Risk of Violence,-1.51,6,Medium,New,1,0 +55639,63389,57523,Probation,Lovio hernandez,Narciel,NULL,Male,Hispanic,04/01/91,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,7/1/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +55639,63389,57523,Probation,Lovio hernandez,Narciel,NULL,Male,Hispanic,04/01/91,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,7/1/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55634,63381,57515,Probation,Orozco,Alberto,NULL,Male,Hispanic,10/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +55634,63381,57515,Probation,Orozco,Alberto,NULL,Male,Hispanic,10/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +55634,63381,57515,Probation,Orozco,Alberto,NULL,Male,Hispanic,10/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55674,63431,57561,Probation,Leon,Diana,Rosa,Female,Hispanic,11/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +55674,63431,57561,Probation,Leon,Diana,Rosa,Female,Hispanic,11/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +55674,63431,57561,Probation,Leon,Diana,Rosa,Female,Hispanic,11/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55654,63410,57541,PRETRIAL,KLIM,RICHARD,NULL,Male,Caucasian,08/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,7/2/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +55654,63410,57541,PRETRIAL,KLIM,RICHARD,NULL,Male,Caucasian,08/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,7/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +55654,63410,57541,PRETRIAL,KLIM,RICHARD,NULL,Male,Caucasian,08/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,7/2/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55661,63415,57545,Probation,FACEY,DERON,O,Male,African-American,08/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +55661,63415,57545,Probation,FACEY,DERON,O,Male,African-American,08/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +55661,63415,57545,Probation,FACEY,DERON,O,Male,African-American,08/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,39,10,High,New,1,0 +55652,63407,57539,PRETRIAL,slocum,danielle,NULL,Female,Caucasian,08/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/2/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +55652,63407,57539,PRETRIAL,slocum,danielle,NULL,Female,Caucasian,08/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +55652,63407,57539,PRETRIAL,slocum,danielle,NULL,Female,Caucasian,08/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/2/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55656,63412,57543,Probation,Abrams,Gary,NULL,Male,African-American,11/28/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +55656,63412,57543,Probation,Abrams,Gary,NULL,Male,African-American,11/28/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +55656,63412,57543,Probation,Abrams,Gary,NULL,Male,African-American,11/28/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +44533,63419,57549,PRETRIAL,SILVA,JONATHAS,A,Male,Caucasian,10/30/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/2/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +44533,63419,57549,PRETRIAL,SILVA,JONATHAS,A,Male,Caucasian,10/30/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/2/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +44533,63419,57549,PRETRIAL,SILVA,JONATHAS,A,Male,Caucasian,10/30/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55670,63426,57556,Probation,LEWIS,STEFAN,C,Male,African-American,02/16/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +55670,63426,57556,Probation,LEWIS,STEFAN,C,Male,African-American,02/16/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +55670,63426,57556,Probation,LEWIS,STEFAN,C,Male,African-American,02/16/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55650,63405,57537,PRETRIAL,Crowe,Jennifer,Ann,Female,Caucasian,03/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/2/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +55650,63405,57537,PRETRIAL,Crowe,Jennifer,Ann,Female,Caucasian,03/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/2/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +55650,63405,57537,PRETRIAL,Crowe,Jennifer,Ann,Female,Caucasian,03/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55663,63417,57547,PRETRIAL,Francis,Richard,G,Male,African-American,12/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/2/13 0:00,2,Medium,7,Risk of Violence,-2.86,2,Low,New,1,0 +55663,63417,57547,PRETRIAL,Francis,Richard,G,Male,African-American,12/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +55663,63417,57547,PRETRIAL,Francis,Richard,G,Male,African-American,12/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/2/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +55665,63421,57551,Probation,Bundrick,Kenneth,Roscoe,Male,Caucasian,08/08/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/2/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +55665,63421,57551,Probation,Bundrick,Kenneth,Roscoe,Male,Caucasian,08/08/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/2/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +55665,63421,57551,Probation,Bundrick,Kenneth,Roscoe,Male,Caucasian,08/08/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +55673,63429,57559,DRRD,Craig,Glenroy,NULL,Male,African-American,08/22/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +55673,63429,57559,DRRD,Craig,Glenroy,NULL,Male,African-American,08/22/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,7,Medium,New,1,0 +55673,63429,57559,DRRD,Craig,Glenroy,NULL,Male,African-American,08/22/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,New,1,0 +55666,63422,57552,Probation,Thiele,Darrin,NULL,Male,Caucasian,05/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +55666,63422,57552,Probation,Thiele,Darrin,NULL,Male,Caucasian,05/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +55666,63422,57552,Probation,Thiele,Darrin,NULL,Male,Caucasian,05/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54350,63409,55968,Probation,hankins,stephen,NULL,Male,Caucasian,06/25/60,17,All Scales,Intake,English,Conditional Release,Probation,Married,7/2/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +54350,63409,55968,Probation,hankins,stephen,NULL,Male,Caucasian,06/25/60,17,All Scales,Intake,English,Conditional Release,Probation,Married,7/2/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +54350,63409,55968,Probation,hankins,stephen,NULL,Male,Caucasian,06/25/60,17,All Scales,Intake,English,Conditional Release,Probation,Married,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +55662,63416,57546,Probation,Chirrono,John,NULL,Male,Caucasian,11/23/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +55662,63416,57546,Probation,Chirrono,John,NULL,Male,Caucasian,11/23/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +55662,63416,57546,Probation,Chirrono,John,NULL,Male,Caucasian,11/23/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55651,63406,57538,PRETRIAL,holt,brittany,NULL,Female,Caucasian,01/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/2/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +55651,63406,57538,PRETRIAL,holt,brittany,NULL,Female,Caucasian,01/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/2/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +55651,63406,57538,PRETRIAL,holt,brittany,NULL,Female,Caucasian,01/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55668,63424,57554,PRETRIAL,izzo,brenda,NULL,Female,Caucasian,06/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/2/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +55668,63424,57554,PRETRIAL,izzo,brenda,NULL,Female,Caucasian,06/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/2/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +55668,63424,57554,PRETRIAL,izzo,brenda,NULL,Female,Caucasian,06/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +40230,63414,55890,PRETRIAL,Singh,Dwayne,Demar,Male,Caucasian,10/19/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +40230,63414,55890,PRETRIAL,Singh,Dwayne,Demar,Male,Caucasian,10/19/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +40230,63414,55890,PRETRIAL,Singh,Dwayne,Demar,Male,Caucasian,10/19/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +50443,63432,57562,PRETRIAL,Honaker,Danny,NULL,Male,Caucasian,09/17/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/2/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +50443,63432,57562,PRETRIAL,Honaker,Danny,NULL,Male,Caucasian,09/17/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/2/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +50443,63432,57562,PRETRIAL,Honaker,Danny,NULL,Male,Caucasian,09/17/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +55669,63425,57555,Probation,LANGSTEN,ROBERT,D,Male,Caucasian,12/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +55669,63425,57555,Probation,LANGSTEN,ROBERT,D,Male,Caucasian,12/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +55669,63425,57555,Probation,LANGSTEN,ROBERT,D,Male,Caucasian,12/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55657,63413,57544,Probation,Lebrun,Gesper,NULL,Male,African-American,06/25/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/2/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +55657,63413,57544,Probation,Lebrun,Gesper,NULL,Male,African-American,06/25/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/2/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +55657,63413,57544,Probation,Lebrun,Gesper,NULL,Male,African-American,06/25/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55664,63420,57550,PRETRIAL,SOLORIO,ALBERTO,NULL,Male,Other,11/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +55664,63420,57550,PRETRIAL,SOLORIO,ALBERTO,NULL,Male,Other,11/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/13 0:00,1,Low,8,Risk of Recidivism,-2.63,1,Low,New,1,0 +55664,63420,57550,PRETRIAL,SOLORIO,ALBERTO,NULL,Male,Other,11/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +31318,63418,57548,Probation,gillion,latasha,NULL,Female,African-American,10/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +31318,63418,57548,Probation,gillion,latasha,NULL,Female,African-American,10/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +31318,63418,57548,Probation,gillion,latasha,NULL,Female,African-American,10/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +39232,63441,57571,PRETRIAL,TORRES,CHARLEY,NULL,Male,Caucasian,05/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +39232,63441,57571,PRETRIAL,TORRES,CHARLEY,NULL,Male,Caucasian,05/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.84,10,High,New,1,0 +39232,63441,57571,PRETRIAL,TORRES,CHARLEY,NULL,Male,Caucasian,05/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +55691,63439,57569,Probation,Burch,Demond,NULL,Male,African-American,05/31/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +55691,63439,57569,Probation,Burch,Demond,NULL,Male,African-American,05/31/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +55691,63439,57569,Probation,Burch,Demond,NULL,Male,African-American,05/31/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55686,63434,57564,PRETRIAL,GRAB,ANTHOMNY,NULL,Male,Caucasian,07/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +55686,63434,57564,PRETRIAL,GRAB,ANTHOMNY,NULL,Male,Caucasian,07/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +55686,63434,57564,PRETRIAL,GRAB,ANTHOMNY,NULL,Male,Caucasian,07/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55695,63445,57575,Probation,VALERIO,UCIEL,NULL,Male,Hispanic,11/18/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +55695,63445,57575,Probation,VALERIO,UCIEL,NULL,Male,Hispanic,11/18/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +55695,63445,57575,Probation,VALERIO,UCIEL,NULL,Male,Hispanic,11/18/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55687,63435,57565,Probation,Newsome,Vashti,NULL,Female,African-American,04/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +55687,63435,57565,Probation,Newsome,Vashti,NULL,Female,African-American,04/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +55687,63435,57565,Probation,Newsome,Vashti,NULL,Female,African-American,04/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +55692,63440,57570,Probation,mazzarella,michael,NULL,Male,Caucasian,10/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +55692,63440,57570,Probation,mazzarella,michael,NULL,Male,Caucasian,10/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +55692,63440,57570,Probation,mazzarella,michael,NULL,Male,Caucasian,10/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +18430,63443,57573,Probation,sweeten,michael,NULL,Male,Caucasian,02/09/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/3/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +18430,63443,57573,Probation,sweeten,michael,NULL,Male,Caucasian,02/09/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/3/13 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +18430,63443,57573,Probation,sweeten,michael,NULL,Male,Caucasian,02/09/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55700,63450,57580,Probation,Erb,Dylan,NULL,Male,Caucasian,06/09/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +55700,63450,57580,Probation,Erb,Dylan,NULL,Male,Caucasian,06/09/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,4,High,8,Risk of Recidivism,0.65,10,High,New,1,0 +55700,63450,57580,Probation,Erb,Dylan,NULL,Male,Caucasian,06/09/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55689,63437,57567,Probation,LEVARITY,DAVID,NULL,Male,African-American,09/07/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +55689,63437,57567,Probation,LEVARITY,DAVID,NULL,Male,African-American,09/07/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +55689,63437,57567,Probation,LEVARITY,DAVID,NULL,Male,African-American,09/07/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55701,63451,57581,PRETRIAL,imperato,michael,NULL,Male,Caucasian,06/14/76,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +55701,63451,57581,PRETRIAL,imperato,michael,NULL,Male,Caucasian,06/14/76,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,8,Risk of Recidivism,-0.66,3,Low,New,1,0 +55701,63451,57581,PRETRIAL,imperato,michael,NULL,Male,Caucasian,06/14/76,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +55690,63438,57568,Probation,AZUAJE,CARLOS,A,Male,Hispanic,03/08/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +55690,63438,57568,Probation,AZUAJE,CARLOS,A,Male,Hispanic,03/08/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +55690,63438,57568,Probation,AZUAJE,CARLOS,A,Male,Hispanic,03/08/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55693,63442,57572,Probation,FLETCHER,MARK,ANTHONY,Male,African-American,08/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +55693,63442,57572,Probation,FLETCHER,MARK,ANTHONY,Male,African-American,08/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +55693,63442,57572,Probation,FLETCHER,MARK,ANTHONY,Male,African-American,08/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55694,63444,57574,Probation,parrish,david,NULL,Male,African-American,10/10/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +55694,63444,57574,Probation,parrish,david,NULL,Male,African-American,10/10/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +55694,63444,57574,Probation,parrish,david,NULL,Male,African-American,10/10/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55699,63449,57579,PRETRIAL,STEEN,ANDREA,NULL,Female,Caucasian,08/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/3/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +55699,63449,57579,PRETRIAL,STEEN,ANDREA,NULL,Female,Caucasian,08/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/3/13 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +55699,63449,57579,PRETRIAL,STEEN,ANDREA,NULL,Female,Caucasian,08/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/3/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +55688,63436,57566,Probation,calderon,cristian,NULL,Male,Hispanic,04/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +55688,63436,57566,Probation,calderon,cristian,NULL,Male,Hispanic,04/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +55688,63436,57566,Probation,calderon,cristian,NULL,Male,Hispanic,04/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55708,63459,57589,Probation,Bain,Kevin,NULL,Male,African-American,10/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +55708,63459,57589,Probation,Bain,Kevin,NULL,Male,African-American,10/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.78,10,High,New,1,0 +55708,63459,57589,Probation,Bain,Kevin,NULL,Male,African-American,10/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +23243,63456,57586,PRETRIAL,PENDLETON,JOHN,NULL,Male,African-American,11/07/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +23243,63456,57586,PRETRIAL,PENDLETON,JOHN,NULL,Male,African-American,11/07/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +23243,63456,57586,PRETRIAL,PENDLETON,JOHN,NULL,Male,African-American,11/07/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +55707,63458,57588,PRETRIAL,Cioffi,Joseph,NULL,Male,Caucasian,05/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/5/13 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +55707,63458,57588,PRETRIAL,Cioffi,Joseph,NULL,Male,Caucasian,05/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/5/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +55707,63458,57588,PRETRIAL,Cioffi,Joseph,NULL,Male,Caucasian,05/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55703,63453,57583,Probation,Lomas,Bryan,NULL,Male,Caucasian,06/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/5/13 0:00,1,Low,7,Risk of Violence,-1,-1,N/A,New,1,0 +55703,63453,57583,Probation,Lomas,Bryan,NULL,Male,Caucasian,06/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/5/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +55703,63453,57583,Probation,Lomas,Bryan,NULL,Male,Caucasian,06/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55705,63455,57585,Probation,Jackson,Joe,Davis,Male,African-American,11/16/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/5/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +55705,63455,57585,Probation,Jackson,Joe,Davis,Male,African-American,11/16/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/5/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +55705,63455,57585,Probation,Jackson,Joe,Davis,Male,African-American,11/16/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55709,63460,57590,PRETRIAL,WANTUCK,ERIK,NULL,Male,Caucasian,08/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +55709,63460,57590,PRETRIAL,WANTUCK,ERIK,NULL,Male,Caucasian,08/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +55709,63460,57590,PRETRIAL,WANTUCK,ERIK,NULL,Male,Caucasian,08/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55714,63467,57597,Probation,JUNCO,JOSE,PABLO,Male,Hispanic,06/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +55714,63467,57597,Probation,JUNCO,JOSE,PABLO,Male,Hispanic,06/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +55714,63467,57597,Probation,JUNCO,JOSE,PABLO,Male,Hispanic,06/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55729,63485,57614,DRRD,Moore,Jimmie,Lee,Male,African-American,10/06/55,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.79,2,Low,New,1,0 +55729,63485,57614,DRRD,Moore,Jimmie,Lee,Male,African-American,10/06/55,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +55729,63485,57614,DRRD,Moore,Jimmie,Lee,Male,African-American,10/06/55,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55712,63464,57594,PRETRIAL,nguyen,jennifer,NULL,Female,Caucasian,05/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +55712,63464,57594,PRETRIAL,nguyen,jennifer,NULL,Female,Caucasian,05/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +55712,63464,57594,PRETRIAL,nguyen,jennifer,NULL,Female,Caucasian,05/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55724,63481,57610,PRETRIAL,sharp,kyle,NULL,Male,Caucasian,12/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +55724,63481,57610,PRETRIAL,sharp,kyle,NULL,Male,Caucasian,12/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +55724,63481,57610,PRETRIAL,sharp,kyle,NULL,Male,Caucasian,12/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55734,63490,57619,Probation,Sanchez,German,NULL,Male,Hispanic,03/01/56,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/8/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +55734,63490,57619,Probation,Sanchez,German,NULL,Male,Hispanic,03/01/56,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/8/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +55734,63490,57619,Probation,Sanchez,German,NULL,Male,Hispanic,03/01/56,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +13149,63476,57605,PRETRIAL,Santiago,Celestino,NULL,Male,Caucasian,12/28/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/8/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +13149,63476,57605,PRETRIAL,Santiago,Celestino,NULL,Male,Caucasian,12/28/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/8/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +13149,63476,57605,PRETRIAL,Santiago,Celestino,NULL,Male,Caucasian,12/28/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55726,63483,57612,Probation,Loy,Melanie,NULL,Female,Caucasian,09/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,New,1,0 +55726,63483,57612,Probation,Loy,Melanie,NULL,Female,Caucasian,09/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,10,High,New,1,0 +55726,63483,57612,Probation,Loy,Melanie,NULL,Female,Caucasian,09/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +21161,63482,57611,PRETRIAL,RAYMOND,LOUISGENS,NULL,Male,African-American,09/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +21161,63482,57611,PRETRIAL,RAYMOND,LOUISGENS,NULL,Male,African-American,09/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +21161,63482,57611,PRETRIAL,RAYMOND,LOUISGENS,NULL,Male,African-American,09/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55731,63487,57616,Probation,Allen,Oneil,NULL,Male,African-American,01/02/77,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/8/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +55731,63487,57616,Probation,Allen,Oneil,NULL,Male,African-American,01/02/77,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/8/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +55731,63487,57616,Probation,Allen,Oneil,NULL,Male,African-American,01/02/77,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +39981,63479,57608,PRETRIAL,owens,makenya,NULL,Female,African-American,11/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +39981,63479,57608,PRETRIAL,owens,makenya,NULL,Female,African-American,11/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +39981,63479,57608,PRETRIAL,owens,makenya,NULL,Female,African-American,11/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55718,63471,57601,Probation,COLEY,LATOYA,RENEE,Female,African-American,10/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +55718,63471,57601,Probation,COLEY,LATOYA,RENEE,Female,African-American,10/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +55718,63471,57601,Probation,COLEY,LATOYA,RENEE,Female,African-American,10/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55720,63475,57604,Probation,TELCINE,JUNIOR,NULL,Male,African-American,09/03/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +55720,63475,57604,Probation,TELCINE,JUNIOR,NULL,Male,African-American,09/03/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +55720,63475,57604,Probation,TELCINE,JUNIOR,NULL,Male,African-American,09/03/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55721,63477,57606,Probation,Jeannestal,Estina,NULL,Female,African-American,07/27/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +55721,63477,57606,Probation,Jeannestal,Estina,NULL,Female,African-American,07/27/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +55721,63477,57606,Probation,Jeannestal,Estina,NULL,Female,African-American,07/27/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55727,63484,57613,PRETRIAL,CORVIL,ADLER,NULL,Male,African-American,01/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +55727,63484,57613,PRETRIAL,CORVIL,ADLER,NULL,Male,African-American,01/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +55727,63484,57613,PRETRIAL,CORVIL,ADLER,NULL,Male,African-American,01/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +46241,63472,57602,PRETRIAL,ROPER,TAI,NULL,Male,African-American,02/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +46241,63472,57602,PRETRIAL,ROPER,TAI,NULL,Male,African-American,02/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +46241,63472,57602,PRETRIAL,ROPER,TAI,NULL,Male,African-American,02/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +55733,63489,57618,Probation,woodlief,sara,frances,Female,Caucasian,04/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +55733,63489,57618,Probation,woodlief,sara,frances,Female,Caucasian,04/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +55733,63489,57618,Probation,woodlief,sara,frances,Female,Caucasian,04/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55713,63463,57593,Probation,Miniel,Yalitza,NULL,Female,Hispanic,03/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +55713,63463,57593,Probation,Miniel,Yalitza,NULL,Female,Hispanic,03/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,8,High,New,1,0 +55713,63463,57593,Probation,Miniel,Yalitza,NULL,Female,Hispanic,03/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55717,63470,57600,Probation,Miranda,Alisa,Blanca,Female,Hispanic,12/08/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/8/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +55717,63470,57600,Probation,Miranda,Alisa,Blanca,Female,Hispanic,12/08/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/8/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +55717,63470,57600,Probation,Miranda,Alisa,Blanca,Female,Hispanic,12/08/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55722,63478,57607,Probation,Cesar,Johnny,NULL,Male,African-American,10/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +55722,63478,57607,Probation,Cesar,Johnny,NULL,Male,African-American,10/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +55722,63478,57607,Probation,Cesar,Johnny,NULL,Male,African-American,10/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +49019,63465,57595,PRETRIAL,Gallagher,Kevin,NULL,Male,Caucasian,06/04/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/8/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +49019,63465,57595,PRETRIAL,Gallagher,Kevin,NULL,Male,Caucasian,06/04/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/8/13 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +49019,63465,57595,PRETRIAL,Gallagher,Kevin,NULL,Male,Caucasian,06/04/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55723,63480,57609,Probation,Abnel,Benjamin,NULL,Male,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +55723,63480,57609,Probation,Abnel,Benjamin,NULL,Male,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +55723,63480,57609,Probation,Abnel,Benjamin,NULL,Male,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55715,63473,57598,PRETRIAL,Alberto,Valerie,NULL,Female,Hispanic,12/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,Copy,1,0 +55715,63473,57598,PRETRIAL,Alberto,Valerie,NULL,Female,Hispanic,12/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,Copy,1,0 +55715,63473,57598,PRETRIAL,Alberto,Valerie,NULL,Female,Hispanic,12/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +55732,63488,57617,Probation,noel,Franquaill,NULL,Female,African-American,11/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +55732,63488,57617,Probation,noel,Franquaill,NULL,Female,African-American,11/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,8,High,New,1,0 +55732,63488,57617,Probation,noel,Franquaill,NULL,Female,African-American,11/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +55730,63486,57615,PRETRIAL,Dunn,Christopher,NULL,Male,Caucasian,02/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +55730,63486,57615,PRETRIAL,Dunn,Christopher,NULL,Male,Caucasian,02/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +55730,63486,57615,PRETRIAL,Dunn,Christopher,NULL,Male,Caucasian,02/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55749,63509,57637,PRETRIAL,markland,blackwood,NULL,Male,African-American,07/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +55749,63509,57637,PRETRIAL,markland,blackwood,NULL,Male,African-American,07/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +55749,63509,57637,PRETRIAL,markland,blackwood,NULL,Male,African-American,07/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55748,63507,57635,Probation,hamilton,jasmine,NULL,Female,African-American,06/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +55748,63507,57635,Probation,hamilton,jasmine,NULL,Female,African-American,06/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +55748,63507,57635,Probation,hamilton,jasmine,NULL,Female,African-American,06/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55737,63494,57623,PRETRIAL,MCMAHON,LAIRD,NULL,Male,Caucasian,11/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +55737,63494,57623,PRETRIAL,MCMAHON,LAIRD,NULL,Male,Caucasian,11/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +55737,63494,57623,PRETRIAL,MCMAHON,LAIRD,NULL,Male,Caucasian,11/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55742,63501,57629,PRETRIAL,lewis,shannon,NULL,Female,African-American,12/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +55742,63501,57629,PRETRIAL,lewis,shannon,NULL,Female,African-American,12/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +55742,63501,57629,PRETRIAL,lewis,shannon,NULL,Female,African-American,12/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55740,63499,57627,Probation,John,Emmanuel,NULL,Male,African-American,05/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/9/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +55740,63499,57627,Probation,John,Emmanuel,NULL,Male,African-American,05/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/9/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +55740,63499,57627,Probation,John,Emmanuel,NULL,Male,African-American,05/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55745,63504,57632,Probation,carver,christopher,NULL,Male,Caucasian,04/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +55745,63504,57632,Probation,carver,christopher,NULL,Male,Caucasian,04/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +55745,63504,57632,Probation,carver,christopher,NULL,Male,Caucasian,04/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55755,63514,57642,Probation,rauer,daniel,NULL,Male,Caucasian,10/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +55755,63514,57642,Probation,rauer,daniel,NULL,Male,Caucasian,10/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +55755,63514,57642,Probation,rauer,daniel,NULL,Male,Caucasian,10/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55751,63510,57638,PRETRIAL,hernandez,Christopher,Michael,Male,Caucasian,02/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +55751,63510,57638,PRETRIAL,hernandez,Christopher,Michael,Male,Caucasian,02/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +55751,63510,57638,PRETRIAL,hernandez,Christopher,Michael,Male,Caucasian,02/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55746,63505,57633,Probation,Moreland,Marlana,NULL,Female,African-American,09/09/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/9/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +55746,63505,57633,Probation,Moreland,Marlana,NULL,Female,African-American,09/09/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/9/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +55746,63505,57633,Probation,Moreland,Marlana,NULL,Female,African-American,09/09/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55739,63498,57626,Probation,Clemente,Jose,NULL,Male,Hispanic,11/28/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/9/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +55739,63498,57626,Probation,Clemente,Jose,NULL,Male,Hispanic,11/28/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/9/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +55739,63498,57626,Probation,Clemente,Jose,NULL,Male,Hispanic,11/28/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55753,63512,57640,Probation,carter,marcel,NULL,Male,African-American,12/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +55753,63512,57640,Probation,carter,marcel,NULL,Male,African-American,12/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1,10,High,New,1,0 +55753,63512,57640,Probation,carter,marcel,NULL,Male,African-American,12/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55750,63508,57636,PRETRIAL,Harper,Daniel,NULL,Male,Caucasian,06/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/13 0:00,2,Medium,7,Risk of Violence,-1.33,7,Medium,New,1,0 +55750,63508,57636,PRETRIAL,Harper,Daniel,NULL,Male,Caucasian,06/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +55750,63508,57636,PRETRIAL,Harper,Daniel,NULL,Male,Caucasian,06/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/13 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +55741,63500,57628,Probation,MURPHY,MATTHEW,ROBERT,Male,Caucasian,12/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +55741,63500,57628,Probation,MURPHY,MATTHEW,ROBERT,Male,Caucasian,12/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +55741,63500,57628,Probation,MURPHY,MATTHEW,ROBERT,Male,Caucasian,12/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55738,63495,57624,PRETRIAL,CRAWFORD,CHARLES,NULL,Male,African-American,07/24/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +55738,63495,57624,PRETRIAL,CRAWFORD,CHARLES,NULL,Male,African-American,07/24/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +55738,63495,57624,PRETRIAL,CRAWFORD,CHARLES,NULL,Male,African-American,07/24/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55754,63513,57641,Probation,Bishop,Troy,E,Male,Caucasian,08/28/74,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,7/9/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +55754,63513,57641,Probation,Bishop,Troy,E,Male,Caucasian,08/28/74,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,7/9/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +55754,63513,57641,Probation,Bishop,Troy,E,Male,Caucasian,08/28/74,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55744,63503,57631,Probation,Vasquez,Jorge,NULL,Male,Hispanic,12/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +55744,63503,57631,Probation,Vasquez,Jorge,NULL,Male,Hispanic,12/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +55744,63503,57631,Probation,Vasquez,Jorge,NULL,Male,Hispanic,12/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55738,63497,57624,PRETRIAL,CRAWFORD,CHARLES,NULL,Male,African-American,07/24/56,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,Copy,1,0 +55738,63497,57624,PRETRIAL,CRAWFORD,CHARLES,NULL,Male,African-American,07/24/56,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,Copy,1,0 +55738,63497,57624,PRETRIAL,CRAWFORD,CHARLES,NULL,Male,African-American,07/24/56,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,7/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +55752,63511,57639,Probation,Peruzzi,Kyle,NULL,Male,Caucasian,05/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +55752,63511,57639,Probation,Peruzzi,Kyle,NULL,Male,Caucasian,05/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +55752,63511,57639,Probation,Peruzzi,Kyle,NULL,Male,Caucasian,05/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55747,63506,57634,Probation,stewart,edwin,w,Male,African-American,03/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +55747,63506,57634,Probation,stewart,edwin,w,Male,African-American,03/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +55747,63506,57634,Probation,stewart,edwin,w,Male,African-American,03/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55743,63502,57630,Probation,hart,kristin,NULL,Female,Caucasian,02/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +55743,63502,57630,Probation,hart,kristin,NULL,Female,Caucasian,02/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +55743,63502,57630,Probation,hart,kristin,NULL,Female,Caucasian,02/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55764,63527,57653,Probation,BECERRA,SANLY,NULL,Female,Hispanic,08/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +55764,63527,57653,Probation,BECERRA,SANLY,NULL,Female,Hispanic,08/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-1.53,2,Low,New,1,0 +55764,63527,57653,Probation,BECERRA,SANLY,NULL,Female,Hispanic,08/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +34398,63523,57649,PRETRIAL,Riley,Jamal,NULL,Male,African-American,03/21/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +34398,63523,57649,PRETRIAL,Riley,Jamal,NULL,Male,African-American,03/21/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +34398,63523,57649,PRETRIAL,Riley,Jamal,NULL,Male,African-American,03/21/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55768,63532,57658,Probation,rangel,tomas,NULL,Male,Hispanic,09/29/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/10/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +55768,63532,57658,Probation,rangel,tomas,NULL,Male,Hispanic,09/29/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/10/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +55768,63532,57658,Probation,rangel,tomas,NULL,Male,Hispanic,09/29/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55757,63518,57644,Probation,Lemelin,Lucien,Edmond,Male,Caucasian,09/10/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +55757,63518,57644,Probation,Lemelin,Lucien,Edmond,Male,Caucasian,09/10/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +55757,63518,57644,Probation,Lemelin,Lucien,Edmond,Male,Caucasian,09/10/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55773,63541,57666,PRETRIAL,Jacob,Robert,NULL,Male,Caucasian,02/09/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-4.46,1,Low,New,1,0 +55773,63541,57666,PRETRIAL,Jacob,Robert,NULL,Male,Caucasian,02/09/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-2.87,1,Low,New,1,0 +55773,63541,57666,PRETRIAL,Jacob,Robert,NULL,Male,Caucasian,02/09/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55759,63520,57646,Probation,Neal,Michael,NULL,Male,Caucasian,03/16/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/10/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +55759,63520,57646,Probation,Neal,Michael,NULL,Male,Caucasian,03/16/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/10/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +55759,63520,57646,Probation,Neal,Michael,NULL,Male,Caucasian,03/16/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55771,63539,57664,Probation,zelaya,ana,NULL,Female,Hispanic,06/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +55771,63539,57664,Probation,zelaya,ana,NULL,Female,Hispanic,06/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +55771,63539,57664,Probation,zelaya,ana,NULL,Female,Hispanic,06/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +48956,63534,57659,PRETRIAL,STYPULA,CHRISTOPHER,GEORGE,Male,Caucasian,09/16/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +48956,63534,57659,PRETRIAL,STYPULA,CHRISTOPHER,GEORGE,Male,Caucasian,09/16/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +48956,63534,57659,PRETRIAL,STYPULA,CHRISTOPHER,GEORGE,Male,Caucasian,09/16/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55760,63521,57647,Probation,Dasilvabraga,Kamila,NULL,Female,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/10/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +55760,63521,57647,Probation,Dasilvabraga,Kamila,NULL,Female,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/10/13 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +55760,63521,57647,Probation,Dasilvabraga,Kamila,NULL,Female,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55765,63529,57655,PRETRIAL,valletta,valerie,NULL,Female,Caucasian,06/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +55765,63529,57655,PRETRIAL,valletta,valerie,NULL,Female,Caucasian,06/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +55765,63529,57655,PRETRIAL,valletta,valerie,NULL,Female,Caucasian,06/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55770,63537,57662,PRETRIAL,Ketant,Bach,NULL,Male,African-American,01/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +55770,63537,57662,PRETRIAL,Ketant,Bach,NULL,Male,African-American,01/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +55770,63537,57662,PRETRIAL,Ketant,Bach,NULL,Male,African-American,01/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55758,63519,57645,Probation,DAVIS,JERROD,NULL,Male,African-American,02/21/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +55758,63519,57645,Probation,DAVIS,JERROD,NULL,Male,African-American,02/21/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +55758,63519,57645,Probation,DAVIS,JERROD,NULL,Male,African-American,02/21/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +40770,63526,57652,PRETRIAL,Charles,Lionel,Burchel,Male,African-American,12/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +40770,63526,57652,PRETRIAL,Charles,Lionel,Burchel,Male,African-American,12/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +40770,63526,57652,PRETRIAL,Charles,Lionel,Burchel,Male,African-American,12/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +14846,63533,50319,Probation,TUBBS,JEFFREY,NULL,Male,African-American,06/05/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,4,High,7,Risk of Violence,0.13,10,High,New,1,0 +14846,63533,50319,Probation,TUBBS,JEFFREY,NULL,Male,African-American,06/05/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,4,High,8,Risk of Recidivism,1.15,10,High,New,1,0 +14846,63533,50319,Probation,TUBBS,JEFFREY,NULL,Male,African-American,06/05/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,4,High,18,Risk of Failure to Appear,38,10,High,New,1,0 +18016,63528,57654,Probation,Torresquinonez,Victor,Jonathan,Male,Hispanic,05/12/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +18016,63528,57654,Probation,Torresquinonez,Victor,Jonathan,Male,Hispanic,05/12/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +18016,63528,57654,Probation,Torresquinonez,Victor,Jonathan,Male,Hispanic,05/12/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55769,63535,57660,Probation,Valle,Luis,NULL,Male,Hispanic,03/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +55769,63535,57660,Probation,Valle,Luis,NULL,Male,Hispanic,03/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +55769,63535,57660,Probation,Valle,Luis,NULL,Male,Hispanic,03/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55767,63531,57657,Probation,Altamiranozarate,Cristian,NULL,Male,Hispanic,12/05/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,7/10/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +55767,63531,57657,Probation,Altamiranozarate,Cristian,NULL,Male,Hispanic,12/05/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,7/10/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +55767,63531,57657,Probation,Altamiranozarate,Cristian,NULL,Male,Hispanic,12/05/81,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55772,63540,57665,PRETRIAL,Nokta,Motilall,NULL,Male,Other,03/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/10/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +55772,63540,57665,PRETRIAL,Nokta,Motilall,NULL,Male,Other,03/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/10/13 0:00,1,Low,8,Risk of Recidivism,-2.58,1,Low,New,1,0 +55772,63540,57665,PRETRIAL,Nokta,Motilall,NULL,Male,Other,03/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +12201,63538,57663,DRRD,Daniels,Brion,NULL,Male,African-American,02/13/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.31,7,Medium,New,1,0 +12201,63538,57663,DRRD,Daniels,Brion,NULL,Male,African-American,02/13/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +12201,63538,57663,DRRD,Daniels,Brion,NULL,Male,African-American,02/13/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,2,Low,New,1,0 +55763,63525,57651,Probation,Tapia,Edward,De Jesus,Male,Hispanic,03/20/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +55763,63525,57651,Probation,Tapia,Edward,De Jesus,Male,Hispanic,03/20/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +55763,63525,57651,Probation,Tapia,Edward,De Jesus,Male,Hispanic,03/20/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55756,63517,57643,PRETRIAL,Andesron,Kathryn,NULL,Female,Caucasian,03/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,Copy,1,0 +55756,63517,57643,PRETRIAL,Andesron,Kathryn,NULL,Female,Caucasian,03/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,6,Medium,Copy,1,0 +55756,63517,57643,PRETRIAL,Andesron,Kathryn,NULL,Female,Caucasian,03/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +52368,63515,53659,PRETRIAL,allegretti,robert,NULL,Male,Caucasian,07/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,Copy,1,0 +52368,63515,53659,PRETRIAL,allegretti,robert,NULL,Male,Caucasian,07/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,Copy,1,0 +52368,63515,53659,PRETRIAL,allegretti,robert,NULL,Male,Caucasian,07/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +55766,63530,57656,Probation,Fields,Monyca,NULL,Female,African-American,02/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +55766,63530,57656,Probation,Fields,Monyca,NULL,Female,African-American,02/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +55766,63530,57656,Probation,Fields,Monyca,NULL,Female,African-American,02/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55761,63522,57648,Probation,Janes,Daniel,NULL,Male,Caucasian,07/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +55761,63522,57648,Probation,Janes,Daniel,NULL,Male,Caucasian,07/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +55761,63522,57648,Probation,Janes,Daniel,NULL,Male,Caucasian,07/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55774,63543,57667,Probation,Contreras,Raul,NULL,Male,African-American,06/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +55774,63543,57667,Probation,Contreras,Raul,NULL,Male,African-American,06/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +55774,63543,57667,Probation,Contreras,Raul,NULL,Male,African-American,06/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55778,63551,57673,DRRD,Brady,Corey,Devon,Male,African-American,05/07/82,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/11/13 0:00,4,High,7,Risk of Violence,1.52,10,High,New,1,0 +55778,63551,57673,DRRD,Brady,Corey,Devon,Male,African-American,05/07/82,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/11/13 0:00,4,High,8,Risk of Recidivism,0.89,10,High,New,1,0 +55778,63551,57673,DRRD,Brady,Corey,Devon,Male,African-American,05/07/82,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/11/13 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +55792,63567,57688,Probation,SHERRELL,AMBROSIA,NULL,Female,African-American,01/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +55792,63567,57688,Probation,SHERRELL,AMBROSIA,NULL,Female,African-American,01/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +55792,63567,57688,Probation,SHERRELL,AMBROSIA,NULL,Female,African-American,01/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55776,63546,57670,Probation,cavallini,philip,NULL,Male,Caucasian,04/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +55776,63546,57670,Probation,cavallini,philip,NULL,Male,Caucasian,04/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +55776,63546,57670,Probation,cavallini,philip,NULL,Male,Caucasian,04/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55791,63564,57685,Probation,DESILVA,BRANON,NULL,Male,Caucasian,10/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +55791,63564,57685,Probation,DESILVA,BRANON,NULL,Male,Caucasian,10/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +55791,63564,57685,Probation,DESILVA,BRANON,NULL,Male,Caucasian,10/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55786,63559,57681,PRETRIAL,JORDAN,ANDREA,NULL,Female,African-American,09/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/13 0:00,2,Medium,7,Risk of Violence,-2.23,4,Low,New,1,0 +55786,63559,57681,PRETRIAL,JORDAN,ANDREA,NULL,Female,African-American,09/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +55786,63559,57681,PRETRIAL,JORDAN,ANDREA,NULL,Female,African-American,09/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +44032,63566,57687,PRETRIAL,Jackson,Jalen,NULL,Male,African-American,06/24/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/11/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +44032,63566,57687,PRETRIAL,Jackson,Jalen,NULL,Male,African-American,06/24/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +44032,63566,57687,PRETRIAL,Jackson,Jalen,NULL,Male,African-American,06/24/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/11/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55775,63545,57669,PRETRIAL,BALDWIN,THOMAS,NULL,Male,African-American,08/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +55775,63545,57669,PRETRIAL,BALDWIN,THOMAS,NULL,Male,African-American,08/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +55775,63545,57669,PRETRIAL,BALDWIN,THOMAS,NULL,Male,African-American,08/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55781,63554,57676,Probation,Torres,Jazmin,NULL,Female,Hispanic,07/15/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/11/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +55781,63554,57676,Probation,Torres,Jazmin,NULL,Female,Hispanic,07/15/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/11/13 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +55781,63554,57676,Probation,Torres,Jazmin,NULL,Female,Hispanic,07/15/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55783,63556,57678,Probation,Gibbs,Larry,NULL,Male,Caucasian,08/29/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +55783,63556,57678,Probation,Gibbs,Larry,NULL,Male,Caucasian,08/29/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +55783,63556,57678,Probation,Gibbs,Larry,NULL,Male,Caucasian,08/29/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55779,63552,57674,Probation,McNorton,Le-Otis,NULL,Male,African-American,11/14/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +55779,63552,57674,Probation,McNorton,Le-Otis,NULL,Male,African-American,11/14/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +55779,63552,57674,Probation,McNorton,Le-Otis,NULL,Male,African-American,11/14/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55790,63565,57686,PRETRIAL,white,miazotiann,NULL,Female,African-American,01/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +55790,63565,57686,PRETRIAL,white,miazotiann,NULL,Female,African-American,01/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,New,1,0 +55790,63565,57686,PRETRIAL,white,miazotiann,NULL,Female,African-American,01/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55785,63558,57680,Probation,Enriquez,Noel,NULL,Male,Hispanic,07/30/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/11/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +55785,63558,57680,Probation,Enriquez,Noel,NULL,Male,Hispanic,07/30/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/11/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +55785,63558,57680,Probation,Enriquez,Noel,NULL,Male,Hispanic,07/30/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55782,63555,57677,Probation,GRAYHARPER,APRIL,MARIE,Male,African-American,04/25/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/11/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +55782,63555,57677,Probation,GRAYHARPER,APRIL,MARIE,Male,African-American,04/25/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/11/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +55782,63555,57677,Probation,GRAYHARPER,APRIL,MARIE,Male,African-American,04/25/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55793,63568,57689,PRETRIAL,Joseph,Sem,NULL,Male,African-American,12/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +55793,63568,57689,PRETRIAL,Joseph,Sem,NULL,Male,African-American,12/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +55793,63568,57689,PRETRIAL,Joseph,Sem,NULL,Male,African-American,12/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55655,63542,57542,PRETRIAL,Del Pozo,Cheryl,NULL,Female,Caucasian,08/10/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/11/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,Copy,1,0 +55655,63542,57542,PRETRIAL,Del Pozo,Cheryl,NULL,Female,Caucasian,08/10/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/11/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,Copy,1,0 +55655,63542,57542,PRETRIAL,Del Pozo,Cheryl,NULL,Female,Caucasian,08/10/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +55787,63560,57682,Probation,Joseph,Fernand,NULL,Male,African-American,01/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/11/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +55787,63560,57682,Probation,Joseph,Fernand,NULL,Male,African-American,01/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/11/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +55787,63560,57682,Probation,Joseph,Fernand,NULL,Male,African-American,01/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55789,63563,57684,Probation,Gutierrez,Robert,Michael,Male,Hispanic,03/26/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/11/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +55789,63563,57684,Probation,Gutierrez,Robert,Michael,Male,Hispanic,03/26/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/11/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +55789,63563,57684,Probation,Gutierrez,Robert,Michael,Male,Hispanic,03/26/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55777,63548,57672,PRETRIAL,gonzalez,rodolfo,NULL,Male,Caucasian,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/13 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +55777,63548,57672,PRETRIAL,gonzalez,rodolfo,NULL,Male,Caucasian,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +55777,63548,57672,PRETRIAL,gonzalez,rodolfo,NULL,Male,Caucasian,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55788,63562,57683,Probation,SALOKAR,LISA,JEAN,Female,Caucasian,12/02/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +55788,63562,57683,Probation,SALOKAR,LISA,JEAN,Female,Caucasian,12/02/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +55788,63562,57683,Probation,SALOKAR,LISA,JEAN,Female,Caucasian,12/02/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55780,63553,57675,Probation,guzman,gabriella,allison,Female,Hispanic,06/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +55780,63553,57675,Probation,guzman,gabriella,allison,Female,Hispanic,06/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +55780,63553,57675,Probation,guzman,gabriella,allison,Female,Hispanic,06/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55784,63557,57679,DRRD,Bell,Robert,Clayton,Male,African-American,11/06/77,17,All Scales,Intake,English,Probation Violator,Probation,Single,7/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +55784,63557,57679,DRRD,Bell,Robert,Clayton,Male,African-American,11/06/77,17,All Scales,Intake,English,Probation Violator,Probation,Single,7/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,9,High,New,1,0 +55784,63557,57679,DRRD,Bell,Robert,Clayton,Male,African-American,11/06/77,17,All Scales,Intake,English,Probation Violator,Probation,Single,7/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +55799,63578,57697,PRETRIAL,Clark,Christon,NULL,Male,African-American,09/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,7/12/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +55799,63578,57697,PRETRIAL,Clark,Christon,NULL,Male,African-American,09/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,7/12/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +55799,63578,57697,PRETRIAL,Clark,Christon,NULL,Male,African-American,09/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,7/12/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +39850,63576,57695,PRETRIAL,Vannostrand,Matthew,NULL,Male,Caucasian,03/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,2,Medium,7,Risk of Violence,-1.26,7,Medium,New,1,0 +39850,63576,57695,PRETRIAL,Vannostrand,Matthew,NULL,Male,Caucasian,03/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +39850,63576,57695,PRETRIAL,Vannostrand,Matthew,NULL,Male,Caucasian,03/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55802,63583,57702,Probation,LEVINE,JESSICA,NULL,Female,Caucasian,04/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +55802,63583,57702,Probation,LEVINE,JESSICA,NULL,Female,Caucasian,04/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +55802,63583,57702,Probation,LEVINE,JESSICA,NULL,Female,Caucasian,04/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +2116,63590,57708,PRETRIAL,HANSON,JOHN,NULL,Male,Hispanic,04/15/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +2116,63590,57708,PRETRIAL,HANSON,JOHN,NULL,Male,Hispanic,04/15/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +2116,63590,57708,PRETRIAL,HANSON,JOHN,NULL,Male,Hispanic,04/15/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55804,63589,57707,Probation,AMMON,CHRISTINE,NULL,Female,Caucasian,02/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +55804,63589,57707,Probation,AMMON,CHRISTINE,NULL,Female,Caucasian,02/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +55804,63589,57707,Probation,AMMON,CHRISTINE,NULL,Female,Caucasian,02/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55800,63579,57698,Probation,Danson,Angela,NULL,Female,African-American,08/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.6,2,Low,New,1,0 +55800,63579,57698,Probation,Danson,Angela,NULL,Female,African-American,08/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +55800,63579,57698,Probation,Danson,Angela,NULL,Female,African-American,08/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +12418,63586,57053,PRETRIAL,JOSEPH,JUDE,NULL,Male,African-American,08/02/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +12418,63586,57053,PRETRIAL,JOSEPH,JUDE,NULL,Male,African-American,08/02/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +12418,63586,57053,PRETRIAL,JOSEPH,JUDE,NULL,Male,African-American,08/02/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +55795,63571,57691,PRETRIAL,Roche,Caritasse,NULL,Female,African-American,05/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +55795,63571,57691,PRETRIAL,Roche,Caritasse,NULL,Female,African-American,05/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +55795,63571,57691,PRETRIAL,Roche,Caritasse,NULL,Female,African-American,05/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +13400,63573,12809,PRETRIAL,FRAZIER,FABIAN,D,Male,African-American,07/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,Copy,1,0 +13400,63573,12809,PRETRIAL,FRAZIER,FABIAN,D,Male,African-American,07/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,Copy,1,0 +13400,63573,12809,PRETRIAL,FRAZIER,FABIAN,D,Male,African-American,07/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +27424,63577,57696,PRETRIAL,Minguer,Efren,NULL,Male,Hispanic,07/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +27424,63577,57696,PRETRIAL,Minguer,Efren,NULL,Male,Hispanic,07/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +27424,63577,57696,PRETRIAL,Minguer,Efren,NULL,Male,Hispanic,07/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +49420,63584,57703,PRETRIAL,Bray,Perry,NULL,Male,Caucasian,05/23/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/12/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +49420,63584,57703,PRETRIAL,Bray,Perry,NULL,Male,Caucasian,05/23/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/12/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +49420,63584,57703,PRETRIAL,Bray,Perry,NULL,Male,Caucasian,05/23/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +46908,63582,57701,PRETRIAL,Mcbride,Oswald,NULL,Male,African-American,02/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +46908,63582,57701,PRETRIAL,Mcbride,Oswald,NULL,Male,African-American,02/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +46908,63582,57701,PRETRIAL,Mcbride,Oswald,NULL,Male,African-American,02/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55794,63570,57690,PRETRIAL,cooper,bertram,NULL,Male,African-American,01/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.52,3,Low,New,1,0 +55794,63570,57690,PRETRIAL,cooper,bertram,NULL,Male,African-American,01/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +55794,63570,57690,PRETRIAL,cooper,bertram,NULL,Male,African-American,01/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +16641,63587,57705,PRETRIAL,lopez,jonathan,NULL,Male,Hispanic,10/03/83,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,7/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.34,3,Low,New,1,0 +16641,63587,57705,PRETRIAL,lopez,jonathan,NULL,Male,Hispanic,10/03/83,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,7/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +16641,63587,57705,PRETRIAL,lopez,jonathan,NULL,Male,Hispanic,10/03/83,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,7/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55796,63572,57692,PRETRIAL,Pope,Oscar,NULL,Male,African-American,09/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.79,2,Low,New,1,0 +55796,63572,57692,PRETRIAL,Pope,Oscar,NULL,Male,African-American,09/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +55796,63572,57692,PRETRIAL,Pope,Oscar,NULL,Male,African-American,09/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +1460,63585,57704,PRETRIAL,Prince,Howard,NULL,Male,African-American,05/23/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +1460,63585,57704,PRETRIAL,Prince,Howard,NULL,Male,African-American,05/23/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +1460,63585,57704,PRETRIAL,Prince,Howard,NULL,Male,African-American,05/23/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +13972,63580,57699,DRRD,Diaz,Ivan,NULL,Male,Hispanic,05/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,2,Medium,7,Risk of Violence,-2.74,2,Low,New,1,0 +13972,63580,57699,DRRD,Diaz,Ivan,NULL,Male,Hispanic,05/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +13972,63580,57699,DRRD,Diaz,Ivan,NULL,Male,Hispanic,05/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/12/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55818,63608,57722,PRETRIAL,Gersbach,Jehan,NULL,Female,Caucasian,08/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +55818,63608,57722,PRETRIAL,Gersbach,Jehan,NULL,Female,Caucasian,08/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +55818,63608,57722,PRETRIAL,Gersbach,Jehan,NULL,Female,Caucasian,08/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55819,63609,57723,PRETRIAL,Keaty,Mark,C,Male,Caucasian,05/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +55819,63609,57723,PRETRIAL,Keaty,Mark,C,Male,Caucasian,05/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +55819,63609,57723,PRETRIAL,Keaty,Mark,C,Male,Caucasian,05/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55822,63614,57727,PRETRIAL,GEORGE,MATTHEW,NULL,Male,African-American,05/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +55822,63614,57727,PRETRIAL,GEORGE,MATTHEW,NULL,Male,African-American,05/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +55822,63614,57727,PRETRIAL,GEORGE,MATTHEW,NULL,Male,African-American,05/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55816,63606,57720,Probation,Stickle,Jason,NULL,Male,Caucasian,11/11/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/13 0:00,4,High,7,Risk of Violence,-1.17,8,High,New,1,0 +55816,63606,57720,Probation,Stickle,Jason,NULL,Male,Caucasian,11/11/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/13 0:00,4,High,8,Risk of Recidivism,0.89,10,High,New,1,0 +55816,63606,57720,Probation,Stickle,Jason,NULL,Male,Caucasian,11/11/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +55805,63591,57709,PRETRIAL,conroy,james,NULL,Male,Caucasian,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +55805,63591,57709,PRETRIAL,conroy,james,NULL,Male,Caucasian,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +55805,63591,57709,PRETRIAL,conroy,james,NULL,Male,Caucasian,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55811,63600,57715,Probation,waldrop,stephanie,NULL,Female,Caucasian,11/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +55811,63600,57715,Probation,waldrop,stephanie,NULL,Female,Caucasian,11/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/13 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +55811,63600,57715,Probation,waldrop,stephanie,NULL,Female,Caucasian,11/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54342,63596,55956,PRETRIAL,Bocksey,Lawrence,NULL,Male,Caucasian,07/02/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/15/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,Copy,1,0 +54342,63596,55956,PRETRIAL,Bocksey,Lawrence,NULL,Male,Caucasian,07/02/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/15/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,Copy,1,0 +54342,63596,55956,PRETRIAL,Bocksey,Lawrence,NULL,Male,Caucasian,07/02/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +55803,63603,57706,PRETRIAL,WILSON,KENNETH,NULL,Male,African-American,05/21/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.24,8,High,Copy,1,0 +55803,63603,57706,PRETRIAL,WILSON,KENNETH,NULL,Male,African-American,05/21/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.1,7,Medium,Copy,1,0 +55803,63603,57706,PRETRIAL,WILSON,KENNETH,NULL,Male,African-American,05/21/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,48,10,High,Copy,1,0 +55815,63605,57719,PRETRIAL,Irving,Jonathon,NULL,Male,African-American,07/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +55815,63605,57719,PRETRIAL,Irving,Jonathon,NULL,Male,African-American,07/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +55815,63605,57719,PRETRIAL,Irving,Jonathon,NULL,Male,African-American,07/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +45248,63598,57714,PRETRIAL,RAMSAY,KAPIL,MAHENDRA,Male,African-American,04/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +45248,63598,57714,PRETRIAL,RAMSAY,KAPIL,MAHENDRA,Male,African-American,04/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +45248,63598,57714,PRETRIAL,RAMSAY,KAPIL,MAHENDRA,Male,African-American,04/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55820,63612,57725,PRETRIAL,Robles,Wilkins,NULL,Male,Hispanic,08/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +55820,63612,57725,PRETRIAL,Robles,Wilkins,NULL,Male,Hispanic,08/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +55820,63612,57725,PRETRIAL,Robles,Wilkins,NULL,Male,Hispanic,08/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55817,63607,57721,PRETRIAL,rochester,rochelle,NULL,Female,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +55817,63607,57721,PRETRIAL,rochester,rochelle,NULL,Female,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +55817,63607,57721,PRETRIAL,rochester,rochelle,NULL,Female,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55823,63615,57728,Probation,Jackson,Christina,NULL,Female,African-American,06/24/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/13 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +55823,63615,57728,Probation,Jackson,Christina,NULL,Female,African-American,06/24/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +55823,63615,57728,Probation,Jackson,Christina,NULL,Female,African-American,06/24/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +55813,63602,57717,Probation,farmer,brenton,NULL,Female,African-American,12/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/15/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +55813,63602,57717,Probation,farmer,brenton,NULL,Female,African-American,12/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/15/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +55813,63602,57717,Probation,farmer,brenton,NULL,Female,African-American,12/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/15/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +50907,63610,57724,PRETRIAL,Estey,Frederick,NULL,Male,Caucasian,05/12/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/15/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +50907,63610,57724,PRETRIAL,Estey,Frederick,NULL,Male,Caucasian,05/12/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/15/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +50907,63610,57724,PRETRIAL,Estey,Frederick,NULL,Male,Caucasian,05/12/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/15/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55806,63592,57710,PRETRIAL,Granados,Jose,Gilbert,Male,Hispanic,01/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/15/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +55806,63592,57710,PRETRIAL,Granados,Jose,Gilbert,Male,Hispanic,01/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/15/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +55806,63592,57710,PRETRIAL,Granados,Jose,Gilbert,Male,Hispanic,01/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/15/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54636,63599,56330,Probation,Monroe,Londell,Alphonzo,Male,African-American,07/20/67,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/15/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +54636,63599,56330,Probation,Monroe,Londell,Alphonzo,Male,African-American,07/20/67,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/15/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +54636,63599,56330,Probation,Monroe,Londell,Alphonzo,Male,African-American,07/20/67,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/15/13 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +55821,63613,57726,PRETRIAL,HOWARD,BRUCE,NULL,Male,African-American,04/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/15/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +55821,63613,57726,PRETRIAL,HOWARD,BRUCE,NULL,Male,African-American,04/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/15/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +55821,63613,57726,PRETRIAL,HOWARD,BRUCE,NULL,Male,African-American,04/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55814,63604,57718,Probation,Davis,Krystal,NULL,Female,African-American,01/21/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,New,1,0 +55814,63604,57718,Probation,Davis,Krystal,NULL,Female,African-American,01/21/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,8,High,New,1,0 +55814,63604,57718,Probation,Davis,Krystal,NULL,Female,African-American,01/21/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55828,63625,57734,PRETRIAL,Hines,Shedrich,Micah,Male,African-American,10/09/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,Copy,1,0 +55828,63625,57734,PRETRIAL,Hines,Shedrich,Micah,Male,African-American,10/09/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,Copy,1,0 +55828,63625,57734,PRETRIAL,Hines,Shedrich,Micah,Male,African-American,10/09/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +55826,63620,57732,PRETRIAL,TURK,ANTHONY,NULL,Male,Caucasian,07/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/16/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +55826,63620,57732,PRETRIAL,TURK,ANTHONY,NULL,Male,Caucasian,07/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/16/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +55826,63620,57732,PRETRIAL,TURK,ANTHONY,NULL,Male,Caucasian,07/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +30078,63628,57736,Probation,MARTIN,DEMETRICE,S,Male,African-American,12/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +30078,63628,57736,Probation,MARTIN,DEMETRICE,S,Male,African-American,12/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +30078,63628,57736,Probation,MARTIN,DEMETRICE,S,Male,African-American,12/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50180,63619,57731,PRETRIAL,Woods,Jevon,Leon,Male,African-American,02/06/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/13 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +50180,63619,57731,PRETRIAL,Woods,Jevon,Leon,Male,African-American,02/06/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +50180,63619,57731,PRETRIAL,Woods,Jevon,Leon,Male,African-American,02/06/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +55824,63617,57729,PRETRIAL,Rapoport,Gershon,NULL,Male,Caucasian,09/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/16/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +55824,63617,57729,PRETRIAL,Rapoport,Gershon,NULL,Male,Caucasian,09/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/16/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +55824,63617,57729,PRETRIAL,Rapoport,Gershon,NULL,Male,Caucasian,09/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/16/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55827,63621,57733,PRETRIAL,Brady,Nicholas,NULL,Male,Caucasian,08/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +55827,63621,57733,PRETRIAL,Brady,Nicholas,NULL,Male,Caucasian,08/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +55827,63621,57733,PRETRIAL,Brady,Nicholas,NULL,Male,Caucasian,08/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +6525,63627,57735,Probation,McGoey,Terence,William,Male,Caucasian,04/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/16/13 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +6525,63627,57735,Probation,McGoey,Terence,William,Male,Caucasian,04/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +6525,63627,57735,Probation,McGoey,Terence,William,Male,Caucasian,04/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/16/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +46737,63632,57740,PRETRIAL,Viveiros,Patricia,NULL,Female,Caucasian,03/31/46,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/16/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +46737,63632,57740,PRETRIAL,Viveiros,Patricia,NULL,Female,Caucasian,03/31/46,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/16/13 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +46737,63632,57740,PRETRIAL,Viveiros,Patricia,NULL,Female,Caucasian,03/31/46,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/16/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +55828,63622,57734,PRETRIAL,Hines,Shedrich,Micah,Male,African-American,10/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +55828,63622,57734,PRETRIAL,Hines,Shedrich,Micah,Male,African-American,10/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +55828,63622,57734,PRETRIAL,Hines,Shedrich,Micah,Male,African-American,10/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +26733,63624,55475,PRETRIAL,CLAUDIO,HECTOR,NULL,Male,Hispanic,06/04/63,17,All Scales,Intake,English,Conditional Release,Residential Program,Divorced,7/16/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +26733,63624,55475,PRETRIAL,CLAUDIO,HECTOR,NULL,Male,Hispanic,06/04/63,17,All Scales,Intake,English,Conditional Release,Residential Program,Divorced,7/16/13 0:00,1,Low,8,Risk of Recidivism,-0.44,4,Low,New,1,0 +26733,63624,55475,PRETRIAL,CLAUDIO,HECTOR,NULL,Male,Hispanic,06/04/63,17,All Scales,Intake,English,Conditional Release,Residential Program,Divorced,7/16/13 0:00,1,Low,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +3810,63616,3525,PRETRIAL,BODDIE,EMEREY,TYRONE,Male,African-American,06/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,Copy,1,0 +3810,63616,3525,PRETRIAL,BODDIE,EMEREY,TYRONE,Male,African-American,06/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,9,High,Copy,1,0 +3810,63616,3525,PRETRIAL,BODDIE,EMEREY,TYRONE,Male,African-American,06/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,Copy,1,0 +55830,63630,57738,PRETRIAL,MIRANDA,LUIS,NULL,Male,Other,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/16/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +55830,63630,57738,PRETRIAL,MIRANDA,LUIS,NULL,Male,Other,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +55830,63630,57738,PRETRIAL,MIRANDA,LUIS,NULL,Male,Other,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/16/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +13790,63637,57744,Probation,Bruno,Jose,NULL,Male,Caucasian,03/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/13 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +13790,63637,57744,Probation,Bruno,Jose,NULL,Male,Caucasian,03/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/13 0:00,4,High,8,Risk of Recidivism,0.55,9,High,New,1,0 +13790,63637,57744,Probation,Bruno,Jose,NULL,Male,Caucasian,03/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55837,63643,57748,PRETRIAL,Raphael,Phylipe,NULL,Male,African-American,03/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +55837,63643,57748,PRETRIAL,Raphael,Phylipe,NULL,Male,African-American,03/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +55837,63643,57748,PRETRIAL,Raphael,Phylipe,NULL,Male,African-American,03/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55832,63635,57742,PRETRIAL,Gurlanik,Yuli,NULL,Male,Caucasian,10/04/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/17/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +55832,63635,57742,PRETRIAL,Gurlanik,Yuli,NULL,Male,Caucasian,10/04/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/17/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +55832,63635,57742,PRETRIAL,Gurlanik,Yuli,NULL,Male,Caucasian,10/04/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55560,63640,57426,PRETRIAL,troppello,brant,NULL,Male,Caucasian,01/22/79,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.68,2,Low,Copy,1,0 +55560,63640,57426,PRETRIAL,troppello,brant,NULL,Male,Caucasian,01/22/79,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,Copy,1,0 +55560,63640,57426,PRETRIAL,troppello,brant,NULL,Male,Caucasian,01/22/79,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +55836,63642,57747,PRETRIAL,Burdell,Richard,NULL,Male,Caucasian,06/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/17/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +55836,63642,57747,PRETRIAL,Burdell,Richard,NULL,Male,Caucasian,06/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/17/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +55836,63642,57747,PRETRIAL,Burdell,Richard,NULL,Male,Caucasian,06/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/17/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +24607,63633,23787,PRETRIAL,mcgowin,steven,NULL,Male,Caucasian,03/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,Copy,1,0 +24607,63633,23787,PRETRIAL,mcgowin,steven,NULL,Male,Caucasian,03/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,Copy,1,0 +24607,63633,23787,PRETRIAL,mcgowin,steven,NULL,Male,Caucasian,03/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +55833,63636,57743,PRETRIAL,Bristol,Jaynell,NULL,Male,African-American,07/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/17/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +55833,63636,57743,PRETRIAL,Bristol,Jaynell,NULL,Male,African-American,07/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/17/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +55833,63636,57743,PRETRIAL,Bristol,Jaynell,NULL,Male,African-American,07/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55838,63644,57749,Probation,Richardson,Emanuel,NULL,Male,African-American,06/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +55838,63644,57749,Probation,Richardson,Emanuel,NULL,Male,African-American,06/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +55838,63644,57749,Probation,Richardson,Emanuel,NULL,Male,African-American,06/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55835,63641,57746,PRETRIAL,Malden,George,Kenneth,Male,Caucasian,05/04/40,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/17/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +55835,63641,57746,PRETRIAL,Malden,George,Kenneth,Male,Caucasian,05/04/40,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/17/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +55835,63641,57746,PRETRIAL,Malden,George,Kenneth,Male,Caucasian,05/04/40,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +22098,63634,57741,PRETRIAL,Plowright,Frank,NULL,Male,Caucasian,07/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +22098,63634,57741,PRETRIAL,Plowright,Frank,NULL,Male,Caucasian,07/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +22098,63634,57741,PRETRIAL,Plowright,Frank,NULL,Male,Caucasian,07/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55848,63655,57759,Probation,Moore,Richard,NULL,Male,Caucasian,10/24/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/13 0:00,1,Low,7,Risk of Violence,-4.38,1,Low,New,1,0 +55848,63655,57759,Probation,Moore,Richard,NULL,Male,Caucasian,10/24/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/13 0:00,1,Low,8,Risk of Recidivism,-2.56,1,Low,New,1,0 +55848,63655,57759,Probation,Moore,Richard,NULL,Male,Caucasian,10/24/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55685,63646,57563,PRETRIAL,Miller,Veronica,NULL,Female,African-American,11/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,Copy,1,0 +55685,63646,57563,PRETRIAL,Miller,Veronica,NULL,Female,African-American,11/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,1,Low,8,Risk of Recidivism,-0.81,5,Medium,Copy,1,0 +55685,63646,57563,PRETRIAL,Miller,Veronica,NULL,Female,African-American,11/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +55852,63660,57763,PRETRIAL,Maxwell,Alicja,NULL,Female,Caucasian,11/25/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,7/18/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +55852,63660,57763,PRETRIAL,Maxwell,Alicja,NULL,Female,Caucasian,11/25/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,7/18/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +55852,63660,57763,PRETRIAL,Maxwell,Alicja,NULL,Female,Caucasian,11/25/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,7/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55842,63648,57752,PRETRIAL,vera,ivan,NULL,Male,Caucasian,02/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/18/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +55842,63648,57752,PRETRIAL,vera,ivan,NULL,Male,Caucasian,02/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/18/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +55842,63648,57752,PRETRIAL,vera,ivan,NULL,Male,Caucasian,02/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55854,63662,57765,PRETRIAL,Voltaire,Jacky,NULL,Male,African-American,05/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +55854,63662,57765,PRETRIAL,Voltaire,Jacky,NULL,Male,African-American,05/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +55854,63662,57765,PRETRIAL,Voltaire,Jacky,NULL,Male,African-American,05/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55841,63649,57753,Probation,Mooney,Dponna,Lynn,Female,Caucasian,12/11/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/18/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +55841,63649,57753,Probation,Mooney,Dponna,Lynn,Female,Caucasian,12/11/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/18/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +55841,63649,57753,Probation,Mooney,Dponna,Lynn,Female,Caucasian,12/11/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55840,63647,57751,PRETRIAL,Oberman,Bridgette,NULL,Female,Caucasian,12/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +55840,63647,57751,PRETRIAL,Oberman,Bridgette,NULL,Female,Caucasian,12/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +55840,63647,57751,PRETRIAL,Oberman,Bridgette,NULL,Female,Caucasian,12/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55846,63654,57758,Probation,KNOX,NICOLE,NULL,Female,African-American,09/03/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +55846,63654,57758,Probation,KNOX,NICOLE,NULL,Female,African-American,09/03/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +55846,63654,57758,Probation,KNOX,NICOLE,NULL,Female,African-American,09/03/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55849,63656,57760,PRETRIAL,RABY,THOMAS,NULL,Male,Caucasian,08/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +55849,63656,57760,PRETRIAL,RABY,THOMAS,NULL,Male,Caucasian,08/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +55849,63656,57760,PRETRIAL,RABY,THOMAS,NULL,Male,Caucasian,08/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55801,63663,57766,PRETRIAL,Fekete,Jeno,NULL,Male,Caucasian,05/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +55801,63663,57766,PRETRIAL,Fekete,Jeno,NULL,Male,Caucasian,05/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +55801,63663,57766,PRETRIAL,Fekete,Jeno,NULL,Male,Caucasian,05/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +41868,63659,41611,PRETRIAL,Darnell,Karen,NULL,Female,Caucasian,02/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.25,3,Low,Copy,1,0 +41868,63659,41611,PRETRIAL,Darnell,Karen,NULL,Female,Caucasian,02/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,10,High,Copy,1,0 +41868,63659,41611,PRETRIAL,Darnell,Karen,NULL,Female,Caucasian,02/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +55847,63653,57757,PRETRIAL,Corporal,Fredrick,R,Male,African-American,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +55847,63653,57757,PRETRIAL,Corporal,Fredrick,R,Male,African-American,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +55847,63653,57757,PRETRIAL,Corporal,Fredrick,R,Male,African-American,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55839,63645,57750,PRETRIAL,Cadet,David,NULL,Male,African-American,03/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +55839,63645,57750,PRETRIAL,Cadet,David,NULL,Male,African-American,03/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +55839,63645,57750,PRETRIAL,Cadet,David,NULL,Male,African-American,03/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55844,63651,57755,Probation,Gpomez,Rosa,Barrel,Female,Hispanic,07/08/82,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/18/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +55844,63651,57755,Probation,Gpomez,Rosa,Barrel,Female,Hispanic,07/08/82,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/18/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +55844,63651,57755,Probation,Gpomez,Rosa,Barrel,Female,Hispanic,07/08/82,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55851,63658,57762,Probation,reilly,roger,NULL,Male,Caucasian,04/22/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +55851,63658,57762,Probation,reilly,roger,NULL,Male,Caucasian,04/22/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +55851,63658,57762,Probation,reilly,roger,NULL,Male,Caucasian,04/22/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55862,63671,57774,Probation,BUSBY,GENEVIEVE,M,Female,Caucasian,03/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/19/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +55862,63671,57774,Probation,BUSBY,GENEVIEVE,M,Female,Caucasian,03/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/19/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +55862,63671,57774,Probation,BUSBY,GENEVIEVE,M,Female,Caucasian,03/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55859,63668,57771,PRETRIAL,PROBBER,MICHAEL,NULL,Male,Caucasian,10/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/19/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +55859,63668,57771,PRETRIAL,PROBBER,MICHAEL,NULL,Male,Caucasian,10/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/19/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +55859,63668,57771,PRETRIAL,PROBBER,MICHAEL,NULL,Male,Caucasian,10/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/19/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +49159,63675,49957,Probation,Delgado,Frank,NULL,Male,Hispanic,01/31/74,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/19/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,Copy,1,0 +49159,63675,49957,Probation,Delgado,Frank,NULL,Male,Hispanic,01/31/74,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/19/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,Copy,1,0 +49159,63675,49957,Probation,Delgado,Frank,NULL,Male,Hispanic,01/31/74,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +55861,63670,57773,Probation,spencer,norman,NULL,Male,African-American,09/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/19/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +55861,63670,57773,Probation,spencer,norman,NULL,Male,African-American,09/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/19/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +55861,63670,57773,Probation,spencer,norman,NULL,Male,African-American,09/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +10495,63673,10019,Probation,McInerney,Chris,NULL,Male,Caucasian,09/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/19/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,Copy,1,0 +10495,63673,10019,Probation,McInerney,Chris,NULL,Male,Caucasian,09/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/19/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,Copy,1,0 +10495,63673,10019,Probation,McInerney,Chris,NULL,Male,Caucasian,09/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +55860,63669,57772,Probation,Newkirk,Desmond,NULL,Male,African-American,12/03/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.27,3,Low,New,1,0 +55860,63669,57772,Probation,Newkirk,Desmond,NULL,Male,African-American,12/03/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +55860,63669,57772,Probation,Newkirk,Desmond,NULL,Male,African-American,12/03/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +55858,63667,57770,Probation,Arauz,Bayron,NULL,Male,Hispanic,06/08/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/19/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +55858,63667,57770,Probation,Arauz,Bayron,NULL,Male,Hispanic,06/08/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/19/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +55858,63667,57770,Probation,Arauz,Bayron,NULL,Male,Hispanic,06/08/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/19/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55855,63664,57767,PRETRIAL,Lucas,Jermonte,Joseph,Male,African-American,03/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/19/13 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +55855,63664,57767,PRETRIAL,Lucas,Jermonte,Joseph,Male,African-American,03/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/19/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +55855,63664,57767,PRETRIAL,Lucas,Jermonte,Joseph,Male,African-American,03/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55869,63681,57781,Probation,mosier,sebastian,NULL,Female,Caucasian,11/01/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +55869,63681,57781,Probation,mosier,sebastian,NULL,Female,Caucasian,11/01/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,9,High,New,1,0 +55869,63681,57781,Probation,mosier,sebastian,NULL,Female,Caucasian,11/01/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55885,63706,57802,Probation,sabo,christine,NULL,Female,Caucasian,01/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +55885,63706,57802,Probation,sabo,christine,NULL,Female,Caucasian,01/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +55885,63706,57802,Probation,sabo,christine,NULL,Female,Caucasian,01/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55421,63702,57277,Probation,Rocha,Diego,NULL,Male,Hispanic,04/13/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +55421,63702,57277,Probation,Rocha,Diego,NULL,Male,Hispanic,04/13/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +55421,63702,57277,Probation,Rocha,Diego,NULL,Male,Hispanic,04/13/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55863,63676,57776,PRETRIAL,ASSARIAN,MICHAEL,NULL,Male,Caucasian,11/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +55863,63676,57776,PRETRIAL,ASSARIAN,MICHAEL,NULL,Male,Caucasian,11/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +55863,63676,57776,PRETRIAL,ASSARIAN,MICHAEL,NULL,Male,Caucasian,11/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55871,63683,57783,Probation,COFRESI,ALBERTO,WILLIAM,Male,Hispanic,05/22/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +55871,63683,57783,Probation,COFRESI,ALBERTO,WILLIAM,Male,Hispanic,05/22/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +55871,63683,57783,Probation,COFRESI,ALBERTO,WILLIAM,Male,Hispanic,05/22/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47089,63697,57795,PRETRIAL,Crespo,Pedro,L,Male,Other,09/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/22/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +47089,63697,57795,PRETRIAL,Crespo,Pedro,L,Male,Other,09/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/22/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +47089,63697,57795,PRETRIAL,Crespo,Pedro,L,Male,Other,09/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55876,63690,57788,Probation,Rodriguez,Marco,NULL,Male,Hispanic,04/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +55876,63690,57788,Probation,Rodriguez,Marco,NULL,Male,Hispanic,04/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +55876,63690,57788,Probation,Rodriguez,Marco,NULL,Male,Hispanic,04/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54861,63688,56595,Probation,Desiderio,Joseph,NULL,Male,Caucasian,12/10/65,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +54861,63688,56595,Probation,Desiderio,Joseph,NULL,Male,Caucasian,12/10/65,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +54861,63688,56595,Probation,Desiderio,Joseph,NULL,Male,Caucasian,12/10/65,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55886,63707,57803,PRETRIAL,Lamie,Samuel,NULL,Male,Caucasian,11/24/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/22/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +55886,63707,57803,PRETRIAL,Lamie,Samuel,NULL,Male,Caucasian,11/24/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/22/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +55886,63707,57803,PRETRIAL,Lamie,Samuel,NULL,Male,Caucasian,11/24/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55873,63686,57785,Probation,Burton,John,NULL,Male,African-American,07/06/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/22/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +55873,63686,57785,Probation,Burton,John,NULL,Male,African-American,07/06/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/22/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +55873,63686,57785,Probation,Burton,John,NULL,Male,African-American,07/06/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +41221,63694,57792,PRETRIAL,Sullo,John,NULL,Male,Caucasian,07/05/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/22/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +41221,63694,57792,PRETRIAL,Sullo,John,NULL,Male,Caucasian,07/05/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/22/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +41221,63694,57792,PRETRIAL,Sullo,John,NULL,Male,Caucasian,07/05/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55883,63701,57798,PRETRIAL,WECHSLER,LEE,NULL,Male,Caucasian,04/26/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +55883,63701,57798,PRETRIAL,WECHSLER,LEE,NULL,Male,Caucasian,04/26/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-2.62,1,Low,New,1,0 +55883,63701,57798,PRETRIAL,WECHSLER,LEE,NULL,Male,Caucasian,04/26/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55868,63680,57780,Probation,fernandez,jake,NULL,Male,Caucasian,10/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +55868,63680,57780,Probation,fernandez,jake,NULL,Male,Caucasian,10/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +55868,63680,57780,Probation,fernandez,jake,NULL,Male,Caucasian,10/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55878,63691,57789,Probation,Masterson,Jeff,NULL,Male,Caucasian,11/29/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,2,Medium,7,Risk of Violence,-3.08,1,Low,New,1,0 +55878,63691,57789,Probation,Masterson,Jeff,NULL,Male,Caucasian,11/29/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +55878,63691,57789,Probation,Masterson,Jeff,NULL,Male,Caucasian,11/29/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +43246,63704,57800,PRETRIAL,Trotter,Tammy,L,Female,Caucasian,05/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +43246,63704,57800,PRETRIAL,Trotter,Tammy,L,Female,Caucasian,05/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +43246,63704,57800,PRETRIAL,Trotter,Tammy,L,Female,Caucasian,05/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +6768,63696,57794,PRETRIAL,BAUMGRTNER,WILLIAM,B,Male,Caucasian,07/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,New,1,0 +6768,63696,57794,PRETRIAL,BAUMGRTNER,WILLIAM,B,Male,Caucasian,07/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +6768,63696,57794,PRETRIAL,BAUMGRTNER,WILLIAM,B,Male,Caucasian,07/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55864,63677,57777,PRETRIAL,Blankenship,Amanda,NULL,Female,Caucasian,08/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +55864,63677,57777,PRETRIAL,Blankenship,Amanda,NULL,Female,Caucasian,08/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +55864,63677,57777,PRETRIAL,Blankenship,Amanda,NULL,Female,Caucasian,08/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55640,63684,57525,PRETRIAL,LEVY,DANIEL,NULL,Male,African-American,01/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,Copy,1,0 +55640,63684,57525,PRETRIAL,LEVY,DANIEL,NULL,Male,African-American,01/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,Copy,1,0 +55640,63684,57525,PRETRIAL,LEVY,DANIEL,NULL,Male,African-American,01/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +50101,63705,57801,PRETRIAL,Guerra,Luis,NULL,Male,Hispanic,06/15/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/22/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +50101,63705,57801,PRETRIAL,Guerra,Luis,NULL,Male,Hispanic,06/15/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/22/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +50101,63705,57801,PRETRIAL,Guerra,Luis,NULL,Male,Hispanic,06/15/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55879,63693,57791,Probation,beaudoin,patrick,NULL,Male,Caucasian,09/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +55879,63693,57791,Probation,beaudoin,patrick,NULL,Male,Caucasian,09/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +55879,63693,57791,Probation,beaudoin,patrick,NULL,Male,Caucasian,09/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55875,63689,57787,Probation,Sobczak,Janusz,NULL,Male,Caucasian,05/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/22/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +55875,63689,57787,Probation,Sobczak,Janusz,NULL,Male,Caucasian,05/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/22/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +55875,63689,57787,Probation,Sobczak,Janusz,NULL,Male,Caucasian,05/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55874,63687,57786,PRETRIAL,Jones,Brandy,NULL,Female,African-American,07/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +55874,63687,57786,PRETRIAL,Jones,Brandy,NULL,Female,African-American,07/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +55874,63687,57786,PRETRIAL,Jones,Brandy,NULL,Female,African-American,07/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55887,63708,57804,Probation,Blas,Orlanda,NULL,Male,Hispanic,08/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,2,Medium,7,Risk of Violence,-1.33,7,Medium,New,1,0 +55887,63708,57804,Probation,Blas,Orlanda,NULL,Male,Hispanic,08/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +55887,63708,57804,Probation,Blas,Orlanda,NULL,Male,Hispanic,08/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55884,63703,57799,PRETRIAL,Keintz,Cameron,NULL,Male,Caucasian,01/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-1.81,5,Medium,New,1,0 +55884,63703,57799,PRETRIAL,Keintz,Cameron,NULL,Male,Caucasian,01/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +55884,63703,57799,PRETRIAL,Keintz,Cameron,NULL,Male,Caucasian,01/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55870,63682,57782,PRETRIAL,RAMKHELAWAN,CHARMAINE,NULL,Female,Other,04/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/22/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +55870,63682,57782,PRETRIAL,RAMKHELAWAN,CHARMAINE,NULL,Female,Other,04/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/22/13 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +55870,63682,57782,PRETRIAL,RAMKHELAWAN,CHARMAINE,NULL,Female,Other,04/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55880,63695,57793,Probation,WIMBLEY,JASMINE,MARIA,Female,African-American,02/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.17,4,Low,New,1,0 +55880,63695,57793,Probation,WIMBLEY,JASMINE,MARIA,Female,African-American,02/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,9,High,New,1,0 +55880,63695,57793,Probation,WIMBLEY,JASMINE,MARIA,Female,African-American,02/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55882,63700,57797,PRETRIAL,Wiborg,John,NULL,Male,Caucasian,03/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +55882,63700,57797,PRETRIAL,Wiborg,John,NULL,Male,Caucasian,03/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +55882,63700,57797,PRETRIAL,Wiborg,John,NULL,Male,Caucasian,03/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +43286,63721,57817,PRETRIAL,THOMAS,KEVIN,NULL,Male,Caucasian,08/22/71,22,Risk and Prescreen,Intake,English,Post Sentence,Parole,Divorced,7/23/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +43286,63721,57817,PRETRIAL,THOMAS,KEVIN,NULL,Male,Caucasian,08/22/71,22,Risk and Prescreen,Intake,English,Post Sentence,Parole,Divorced,7/23/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +43286,63721,57817,PRETRIAL,THOMAS,KEVIN,NULL,Male,Caucasian,08/22/71,22,Risk and Prescreen,Intake,English,Post Sentence,Parole,Divorced,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51267,63713,57809,Probation,Page,Robert,NULL,Male,African-American,03/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +51267,63713,57809,Probation,Page,Robert,NULL,Male,African-American,03/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +51267,63713,57809,Probation,Page,Robert,NULL,Male,African-American,03/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55895,63716,57812,Probation,balom,daniel,NULL,Male,African-American,04/18/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/23/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +55895,63716,57812,Probation,balom,daniel,NULL,Male,African-American,04/18/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/23/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +55895,63716,57812,Probation,balom,daniel,NULL,Male,African-American,04/18/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55905,63729,57824,Probation,osullivan,victoria,NULL,Female,Caucasian,01/30/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +55905,63729,57824,Probation,osullivan,victoria,NULL,Female,Caucasian,01/30/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +55905,63729,57824,Probation,osullivan,victoria,NULL,Female,Caucasian,01/30/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55901,63724,57819,Probation,Whelpley,James,Glenn,Male,Caucasian,07/29/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/23/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +55901,63724,57819,Probation,Whelpley,James,Glenn,Male,Caucasian,07/29/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/23/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +55901,63724,57819,Probation,Whelpley,James,Glenn,Male,Caucasian,07/29/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55893,63714,57810,Probation,Gould,Deborah,NULL,Female,Caucasian,01/25/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +55893,63714,57810,Probation,Gould,Deborah,NULL,Female,Caucasian,01/25/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +55893,63714,57810,Probation,Gould,Deborah,NULL,Female,Caucasian,01/25/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55889,63710,57806,PRETRIAL,Morales,Elvis,NULL,Male,Hispanic,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +55889,63710,57806,PRETRIAL,Morales,Elvis,NULL,Male,Hispanic,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +55889,63710,57806,PRETRIAL,Morales,Elvis,NULL,Male,Hispanic,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +12688,63728,57823,PRETRIAL,MORSS,RUSSELL,NULL,Male,African-American,07/31/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +12688,63728,57823,PRETRIAL,MORSS,RUSSELL,NULL,Male,African-American,07/31/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +12688,63728,57823,PRETRIAL,MORSS,RUSSELL,NULL,Male,African-American,07/31/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55891,63712,57808,Probation,castaldo,christopher,NULL,Male,Hispanic,04/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +55891,63712,57808,Probation,castaldo,christopher,NULL,Male,Hispanic,04/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +55891,63712,57808,Probation,castaldo,christopher,NULL,Male,Hispanic,04/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55899,63719,57815,DRRD,Forbes,Kyra,NULL,Female,African-American,08/22/84,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +55899,63719,57815,DRRD,Forbes,Kyra,NULL,Female,African-American,08/22/84,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +55899,63719,57815,DRRD,Forbes,Kyra,NULL,Female,African-American,08/22/84,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,2,Medium,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +55903,63726,57821,Probation,GOINS,TYNESHA,NULL,Female,African-American,08/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +55903,63726,57821,Probation,GOINS,TYNESHA,NULL,Female,African-American,08/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,7,Medium,New,1,0 +55903,63726,57821,Probation,GOINS,TYNESHA,NULL,Female,African-American,08/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55896,63717,57813,Probation,CADENAREMAREZ,FERNEY,NULL,Male,Hispanic,05/16/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +55896,63717,57813,Probation,CADENAREMAREZ,FERNEY,NULL,Male,Hispanic,05/16/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +55896,63717,57813,Probation,CADENAREMAREZ,FERNEY,NULL,Male,Hispanic,05/16/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55902,63725,57820,Probation,GREENE,MICHAEL,NULL,Male,African-American,06/24/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +55902,63725,57820,Probation,GREENE,MICHAEL,NULL,Male,African-American,06/24/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +55902,63725,57820,Probation,GREENE,MICHAEL,NULL,Male,African-American,06/24/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55894,63715,57811,Probation,Rosales-Tobias,Karla,Lorena,Female,Hispanic,10/01/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/23/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +55894,63715,57811,Probation,Rosales-Tobias,Karla,Lorena,Female,Hispanic,10/01/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/23/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +55894,63715,57811,Probation,Rosales-Tobias,Karla,Lorena,Female,Hispanic,10/01/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55906,63730,57825,PRETRIAL,bennett,whitney,NULL,Female,African-American,06/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +55906,63730,57825,PRETRIAL,bennett,whitney,NULL,Female,African-American,06/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/13 0:00,4,High,8,Risk of Recidivism,0.03,8,High,New,1,0 +55906,63730,57825,PRETRIAL,bennett,whitney,NULL,Female,African-American,06/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55888,63709,57805,PRETRIAL,mora,luis,miguel,Male,Hispanic,05/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/23/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +55888,63709,57805,PRETRIAL,mora,luis,miguel,Male,Hispanic,05/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/23/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +55888,63709,57805,PRETRIAL,mora,luis,miguel,Male,Hispanic,05/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +45248,63722,57714,PRETRIAL,RAMSAY,KAPIL,MAHENDRA,Male,African-American,04/23/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,7,Risk of Violence,-1.81,5,Medium,New,1,0 +45248,63722,57714,PRETRIAL,RAMSAY,KAPIL,MAHENDRA,Male,African-American,04/23/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,8,Risk of Recidivism,-0.22,5,Medium,New,1,0 +45248,63722,57714,PRETRIAL,RAMSAY,KAPIL,MAHENDRA,Male,African-American,04/23/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,2,Low,New,1,0 +55890,63711,57807,Probation,Yulchevskaya,Julia,NULL,Female,Caucasian,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +55890,63711,57807,Probation,Yulchevskaya,Julia,NULL,Female,Caucasian,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/13 0:00,1,Low,8,Risk of Recidivism,-1.43,2,Low,New,1,0 +55890,63711,57807,Probation,Yulchevskaya,Julia,NULL,Female,Caucasian,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +32013,63718,57814,PRETRIAL,Santiago,Mizraim,NULL,Male,Hispanic,11/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +32013,63718,57814,PRETRIAL,Santiago,Mizraim,NULL,Male,Hispanic,11/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +32013,63718,57814,PRETRIAL,Santiago,Mizraim,NULL,Male,Hispanic,11/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55900,63720,57816,Probation,velez,jacob,NULL,Male,Hispanic,07/23/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +55900,63720,57816,Probation,velez,jacob,NULL,Male,Hispanic,07/23/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +55900,63720,57816,Probation,velez,jacob,NULL,Male,Hispanic,07/23/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +28274,63727,57822,PRETRIAL,Reese,Jeffrey,NULL,Male,African-American,12/03/87,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.91,5,Medium,New,1,0 +28274,63727,57822,PRETRIAL,Reese,Jeffrey,NULL,Male,African-American,12/03/87,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +28274,63727,57822,PRETRIAL,Reese,Jeffrey,NULL,Male,African-American,12/03/87,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +50648,63723,57818,Probation,Riley,William,NULL,Male,Caucasian,03/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.05,8,High,New,1,0 +50648,63723,57818,Probation,Riley,William,NULL,Male,Caucasian,03/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +50648,63723,57818,Probation,Riley,William,NULL,Male,Caucasian,03/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55911,63736,57831,Probation,burkhardt,carl,NULL,Male,Caucasian,12/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/24/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +55911,63736,57831,Probation,burkhardt,carl,NULL,Male,Caucasian,12/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/24/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +55911,63736,57831,Probation,burkhardt,carl,NULL,Male,Caucasian,12/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55908,63732,57827,Probation,Irfan,Ali,NULL,Male,Asian,04/30/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +55908,63732,57827,Probation,Irfan,Ali,NULL,Male,Asian,04/30/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +55908,63732,57827,Probation,Irfan,Ali,NULL,Male,Asian,04/30/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55914,63739,57834,Probation,gibson,shaquilla,NULL,Male,African-American,08/04/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +55914,63739,57834,Probation,gibson,shaquilla,NULL,Male,African-American,08/04/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +55914,63739,57834,Probation,gibson,shaquilla,NULL,Male,African-American,08/04/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55915,63741,57836,Probation,Mohammed,Mark,NULL,Male,African-American,01/24/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/24/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +55915,63741,57836,Probation,Mohammed,Mark,NULL,Male,African-American,01/24/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/24/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +55915,63741,57836,Probation,Mohammed,Mark,NULL,Male,African-American,01/24/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55920,63748,57842,PRETRIAL,Carlo,Michael,NULL,Male,Caucasian,09/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/24/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +55920,63748,57842,PRETRIAL,Carlo,Michael,NULL,Male,Caucasian,09/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/24/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +55920,63748,57842,PRETRIAL,Carlo,Michael,NULL,Male,Caucasian,09/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +53857,63743,55367,PRETRIAL,Bozman,Zarian,NULL,Male,African-American,09/13/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,Copy,1,0 +53857,63743,55367,PRETRIAL,Bozman,Zarian,NULL,Male,African-American,09/13/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,Copy,1,0 +53857,63743,55367,PRETRIAL,Bozman,Zarian,NULL,Male,African-American,09/13/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +55923,63751,57845,Probation,Paredes,Omar,NULL,Male,Hispanic,07/23/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/24/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +55923,63751,57845,Probation,Paredes,Omar,NULL,Male,Hispanic,07/23/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/24/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +55923,63751,57845,Probation,Paredes,Omar,NULL,Male,Hispanic,07/23/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55913,63738,57833,Probation,Demots,Thomas,NULL,Male,Hispanic,10/22/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,7/24/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +55913,63738,57833,Probation,Demots,Thomas,NULL,Male,Hispanic,10/22/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,7/24/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +55913,63738,57833,Probation,Demots,Thomas,NULL,Male,Hispanic,10/22/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50748,63746,57840,PRETRIAL,taylor,TIMOTHY,NULL,Male,Caucasian,03/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +50748,63746,57840,PRETRIAL,taylor,TIMOTHY,NULL,Male,Caucasian,03/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +50748,63746,57840,PRETRIAL,taylor,TIMOTHY,NULL,Male,Caucasian,03/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +14177,63733,57828,Probation,RILEY,WILLIAM,HENRY,Male,Caucasian,04/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +14177,63733,57828,Probation,RILEY,WILLIAM,HENRY,Male,Caucasian,04/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +14177,63733,57828,Probation,RILEY,WILLIAM,HENRY,Male,Caucasian,04/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55919,63747,57841,Probation,macdonald,taylor,NULL,Male,Caucasian,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +55919,63747,57841,Probation,macdonald,taylor,NULL,Male,Caucasian,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +55919,63747,57841,Probation,macdonald,taylor,NULL,Male,Caucasian,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +1169,63735,57830,PRETRIAL,White,Anthony,NULL,Male,African-American,04/30/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +1169,63735,57830,PRETRIAL,White,Anthony,NULL,Male,African-American,04/30/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +1169,63735,57830,PRETRIAL,White,Anthony,NULL,Male,African-American,04/30/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55907,63731,57826,Probation,NEAL,QUINTERRA,T,Female,African-American,05/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +55907,63731,57826,Probation,NEAL,QUINTERRA,T,Female,African-American,05/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +55907,63731,57826,Probation,NEAL,QUINTERRA,T,Female,African-American,05/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55921,63749,57843,Probation,MEZA,LIZANDRO,NULL,Male,Hispanic,08/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +55921,63749,57843,Probation,MEZA,LIZANDRO,NULL,Male,Hispanic,08/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +55921,63749,57843,Probation,MEZA,LIZANDRO,NULL,Male,Hispanic,08/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +11339,63740,57835,PRETRIAL,BRINSON,WILLIE,J,Male,African-American,03/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +11339,63740,57835,PRETRIAL,BRINSON,WILLIE,J,Male,African-American,03/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/13 0:00,4,High,8,Risk of Recidivism,0.41,9,High,New,1,0 +11339,63740,57835,PRETRIAL,BRINSON,WILLIE,J,Male,African-American,03/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55917,63745,57839,Probation,BUITRAGO,LUIS,EDUARDO,Male,Hispanic,02/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/24/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +55917,63745,57839,Probation,BUITRAGO,LUIS,EDUARDO,Male,Hispanic,02/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/24/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +55917,63745,57839,Probation,BUITRAGO,LUIS,EDUARDO,Male,Hispanic,02/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55922,63750,57844,PRETRIAL,rawls,jeffrey,NULL,Male,African-American,12/03/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,2,Medium,7,Risk of Violence,-1.51,6,Medium,New,1,0 +55922,63750,57844,PRETRIAL,rawls,jeffrey,NULL,Male,African-American,12/03/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,6,Medium,New,1,0 +55922,63750,57844,PRETRIAL,rawls,jeffrey,NULL,Male,African-American,12/03/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/24/13 0:00,2,Medium,18,Risk of Failure to Appear,19,2,Low,New,1,0 +55912,63737,57832,Probation,Mendez,Miguel,NULL,Male,Hispanic,09/28/83,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,7/24/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +55912,63737,57832,Probation,Mendez,Miguel,NULL,Male,Hispanic,09/28/83,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,7/24/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +55912,63737,57832,Probation,Mendez,Miguel,NULL,Male,Hispanic,09/28/83,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Single,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55918,63744,57838,PRETRIAL,De Paola,Giovanni,NULL,Male,Caucasian,09/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +55918,63744,57838,PRETRIAL,De Paola,Giovanni,NULL,Male,Caucasian,09/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +55918,63744,57838,PRETRIAL,De Paola,Giovanni,NULL,Male,Caucasian,09/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55910,63734,57829,PRETRIAL,breeden,mathew,NULL,Male,Caucasian,09/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +55910,63734,57829,PRETRIAL,breeden,mathew,NULL,Male,Caucasian,09/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +55910,63734,57829,PRETRIAL,breeden,mathew,NULL,Male,Caucasian,09/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55936,63768,57860,PRETRIAL,Whitley,Kenroy,NULL,Male,Other,01/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/25/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +55936,63768,57860,PRETRIAL,Whitley,Kenroy,NULL,Male,Other,01/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +55936,63768,57860,PRETRIAL,Whitley,Kenroy,NULL,Male,Other,01/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55927,63755,57849,PRETRIAL,delcarpio,alonso,NULL,Male,Hispanic,10/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +55927,63755,57849,PRETRIAL,delcarpio,alonso,NULL,Male,Hispanic,10/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +55927,63755,57849,PRETRIAL,delcarpio,alonso,NULL,Male,Hispanic,10/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +49389,63789,57880,PRETRIAL,Willis,Travis,NULL,Male,African-American,03/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +49389,63789,57880,PRETRIAL,Willis,Travis,NULL,Male,African-American,03/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +49389,63789,57880,PRETRIAL,Willis,Travis,NULL,Male,African-American,03/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55950,63781,57872,Probation,bastien,jeffrey,NULL,Male,African-American,12/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +55950,63781,57872,Probation,bastien,jeffrey,NULL,Male,African-American,12/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +55950,63781,57872,Probation,bastien,jeffrey,NULL,Male,African-American,12/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55955,63787,57878,Probation,Nuckols,Nia,NULL,Female,African-American,01/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +55955,63787,57878,Probation,Nuckols,Nia,NULL,Female,African-American,01/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +55955,63787,57878,Probation,Nuckols,Nia,NULL,Female,African-American,01/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55934,63765,57858,Probation,Camposeco-Mendez,Manuel,NULL,Male,Hispanic,02/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/25/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +55934,63765,57858,Probation,Camposeco-Mendez,Manuel,NULL,Male,Hispanic,02/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +55934,63765,57858,Probation,Camposeco-Mendez,Manuel,NULL,Male,Hispanic,02/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55935,63766,57859,Probation,tebar,vinee,NULL,Female,Caucasian,01/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/13 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +55935,63766,57859,Probation,tebar,vinee,NULL,Female,Caucasian,01/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +55935,63766,57859,Probation,tebar,vinee,NULL,Female,Caucasian,01/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55948,63779,57870,Probation,dorest,hercules,NULL,Male,African-American,11/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +55948,63779,57870,Probation,dorest,hercules,NULL,Male,African-American,11/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +55948,63779,57870,Probation,dorest,hercules,NULL,Male,African-American,11/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55924,63752,57846,PRETRIAL,Martinicorena,Celen,NULL,Female,Caucasian,07/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +55924,63752,57846,PRETRIAL,Martinicorena,Celen,NULL,Female,Caucasian,07/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.03,8,High,New,1,0 +55924,63752,57846,PRETRIAL,Martinicorena,Celen,NULL,Female,Caucasian,07/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +42699,63786,57877,PRETRIAL,Miller,Kelly,NULL,Male,Caucasian,07/22/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,2,Medium,7,Risk of Violence,-2.98,1,Low,New,1,0 +42699,63786,57877,PRETRIAL,Miller,Kelly,NULL,Male,Caucasian,07/22/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +42699,63786,57877,PRETRIAL,Miller,Kelly,NULL,Male,Caucasian,07/22/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55929,63758,57852,Probation,Kozolchyk,Elliot,NULL,Male,Caucasian,07/20/84,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +55929,63758,57852,Probation,Kozolchyk,Elliot,NULL,Male,Caucasian,07/20/84,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +55929,63758,57852,Probation,Kozolchyk,Elliot,NULL,Male,Caucasian,07/20/84,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55941,63771,57863,Probation,Delgado,Gustavo,NULL,Male,Hispanic,11/25/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +55941,63771,57863,Probation,Delgado,Gustavo,NULL,Male,Hispanic,11/25/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +55941,63771,57863,Probation,Delgado,Gustavo,NULL,Male,Hispanic,11/25/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55943,63773,57865,PRETRIAL,whitley,kenroy,NULL,Male,Other,01/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/25/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +55943,63773,57865,PRETRIAL,whitley,kenroy,NULL,Male,Other,01/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +55943,63773,57865,PRETRIAL,whitley,kenroy,NULL,Male,Other,01/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55932,63761,57854,Probation,Diaz,Nelson,NULL,Male,Hispanic,01/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +55932,63761,57854,Probation,Diaz,Nelson,NULL,Male,Hispanic,01/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +55932,63761,57854,Probation,Diaz,Nelson,NULL,Male,Hispanic,01/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55940,63770,57862,Probation,Mireles,Andrew,NULL,Male,Native American,06/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +55940,63770,57862,Probation,Mireles,Andrew,NULL,Male,Native American,06/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +55940,63770,57862,Probation,Mireles,Andrew,NULL,Male,Native American,06/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55951,63782,57873,Probation,Ramos,Noel,NULL,Male,Hispanic,06/16/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/25/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +55951,63782,57873,Probation,Ramos,Noel,NULL,Male,Hispanic,06/16/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/25/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +55951,63782,57873,Probation,Ramos,Noel,NULL,Male,Hispanic,06/16/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55926,63754,57848,Probation,abdelgili,ahmed,NULL,Male,Caucasian,12/06/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +55926,63754,57848,Probation,abdelgili,ahmed,NULL,Male,Caucasian,12/06/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +55926,63754,57848,Probation,abdelgili,ahmed,NULL,Male,Caucasian,12/06/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55945,63775,57867,Probation,Costa,Jose,NULL,Male,Hispanic,01/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +55945,63775,57867,Probation,Costa,Jose,NULL,Male,Hispanic,01/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +55945,63775,57867,Probation,Costa,Jose,NULL,Male,Hispanic,01/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55947,63777,57869,Probation,Hall,Christopher,David,Male,African-American,10/15/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/25/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +55947,63777,57869,Probation,Hall,Christopher,David,Male,African-American,10/15/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +55947,63777,57869,Probation,Hall,Christopher,David,Male,African-American,10/15/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55953,63784,57875,Probation,Ayala,Jorge,NULL,Male,Hispanic,08/16/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +55953,63784,57875,Probation,Ayala,Jorge,NULL,Male,Hispanic,08/16/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +55953,63784,57875,Probation,Ayala,Jorge,NULL,Male,Hispanic,08/16/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +6719,63764,57857,PRETRIAL,ORTIZ,TRAVEON,SARENT,Male,African-American,01/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,New,1,0 +6719,63764,57857,PRETRIAL,ORTIZ,TRAVEON,SARENT,Male,African-American,01/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +6719,63764,57857,PRETRIAL,ORTIZ,TRAVEON,SARENT,Male,African-American,01/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55954,63785,57876,Probation,Leiva,Claudio,NULL,Male,Hispanic,06/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +55954,63785,57876,Probation,Leiva,Claudio,NULL,Male,Hispanic,06/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +55954,63785,57876,Probation,Leiva,Claudio,NULL,Male,Hispanic,06/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55942,63772,57864,Probation,johnson,albert,NULL,Male,African-American,09/01/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +55942,63772,57864,Probation,johnson,albert,NULL,Male,African-American,09/01/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +55942,63772,57864,Probation,johnson,albert,NULL,Male,African-American,09/01/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55949,63780,57871,Probation,Germain,Angelo,NULL,Male,African-American,07/23/87,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/25/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +55949,63780,57871,Probation,Germain,Angelo,NULL,Male,African-American,07/23/87,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +55949,63780,57871,Probation,Germain,Angelo,NULL,Male,African-American,07/23/87,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/25/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55956,63788,57879,Probation,Lebron,Teresa,Ann,Female,Caucasian,03/17/66,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/25/13 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +55956,63788,57879,Probation,Lebron,Teresa,Ann,Female,Caucasian,03/17/66,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +55956,63788,57879,Probation,Lebron,Teresa,Ann,Female,Caucasian,03/17/66,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/25/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55952,63783,57874,Probation,santiago,elizabeth,NULL,Female,Hispanic,11/16/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/13 0:00,1,Low,7,Risk of Violence,-4.32,1,Low,New,1,0 +55952,63783,57874,Probation,santiago,elizabeth,NULL,Female,Hispanic,11/16/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +55952,63783,57874,Probation,santiago,elizabeth,NULL,Female,Hispanic,11/16/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55939,63769,57861,Probation,avila,eduardo,NULL,Male,Hispanic,07/26/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +55939,63769,57861,Probation,avila,eduardo,NULL,Male,Hispanic,07/26/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +55939,63769,57861,Probation,avila,eduardo,NULL,Male,Hispanic,07/26/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55946,63776,57868,Probation,cugno,laura,NULL,Female,Caucasian,09/26/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/25/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +55946,63776,57868,Probation,cugno,laura,NULL,Female,Caucasian,09/26/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/25/13 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +55946,63776,57868,Probation,cugno,laura,NULL,Female,Caucasian,09/26/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55957,63790,57881,Probation,mohorn,john,NULL,Male,African-American,10/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +55957,63790,57881,Probation,mohorn,john,NULL,Male,African-American,10/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +55957,63790,57881,Probation,mohorn,john,NULL,Male,African-American,10/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55925,63753,57847,Probation,Laverde,Adriana,Patricia,Female,Hispanic,02/19/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +55925,63753,57847,Probation,Laverde,Adriana,Patricia,Female,Hispanic,02/19/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +55925,63753,57847,Probation,Laverde,Adriana,Patricia,Female,Hispanic,02/19/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51319,63778,52502,PRETRIAL,Mccloud,Jarvis,NULL,Male,African-American,06/26/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,Copy,1,0 +51319,63778,52502,PRETRIAL,Mccloud,Jarvis,NULL,Male,African-American,06/26/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,Copy,1,0 +51319,63778,52502,PRETRIAL,Mccloud,Jarvis,NULL,Male,African-American,06/26/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +55930,63757,57851,Probation,Guzman,Stephanie,NULL,Female,Caucasian,05/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +55930,63757,57851,Probation,Guzman,Stephanie,NULL,Female,Caucasian,05/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +55930,63757,57851,Probation,Guzman,Stephanie,NULL,Female,Caucasian,05/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55961,63795,57885,PRETRIAL,Franklin,Johnny,NULL,Male,African-American,06/17/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/26/13 0:00,2,Medium,7,Risk of Violence,-3.61,1,Low,New,1,0 +55961,63795,57885,PRETRIAL,Franklin,Johnny,NULL,Male,African-American,06/17/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +55961,63795,57885,PRETRIAL,Franklin,Johnny,NULL,Male,African-American,06/17/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/26/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +55970,63804,57894,Probation,Toussaint,Gina,NULL,Female,African-American,11/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +55970,63804,57894,Probation,Toussaint,Gina,NULL,Female,African-American,11/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +55970,63804,57894,Probation,Toussaint,Gina,NULL,Female,African-American,11/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54881,63792,56627,Probation,Mcrill,Clinton,David,Male,Caucasian,11/29/56,17,All Scales,Intake,English,Other,Probation,Single,7/26/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,Copy,1,0 +54881,63792,56627,Probation,Mcrill,Clinton,David,Male,Caucasian,11/29/56,17,All Scales,Intake,English,Other,Probation,Single,7/26/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,Copy,1,0 +54881,63792,56627,Probation,Mcrill,Clinton,David,Male,Caucasian,11/29/56,17,All Scales,Intake,English,Other,Probation,Single,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +55979,63813,57903,Probation,Kelly,Kapel,NULL,Male,African-American,06/10/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/26/13 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +55979,63813,57903,Probation,Kelly,Kapel,NULL,Male,African-American,06/10/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/26/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +55979,63813,57903,Probation,Kelly,Kapel,NULL,Male,African-American,06/10/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55977,63811,57901,Probation,Tozzi,Angelina,Devette,Female,Hispanic,04/26/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +55977,63811,57901,Probation,Tozzi,Angelina,Devette,Female,Hispanic,04/26/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +55977,63811,57901,Probation,Tozzi,Angelina,Devette,Female,Hispanic,04/26/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +55963,63797,57887,PRETRIAL,craig,taji,NULL,Male,African-American,11/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +55963,63797,57887,PRETRIAL,craig,taji,NULL,Male,African-American,11/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,4,High,8,Risk of Recidivism,0.1,8,High,New,1,0 +55963,63797,57887,PRETRIAL,craig,taji,NULL,Male,African-American,11/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55975,63809,57899,Probation,achille,ezra,NULL,Male,African-American,02/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +55975,63809,57899,Probation,achille,ezra,NULL,Male,African-American,02/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +55975,63809,57899,Probation,achille,ezra,NULL,Male,African-American,02/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55972,63806,57896,Probation,Metayer,Nellie,NULL,Female,African-American,04/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +55972,63806,57896,Probation,Metayer,Nellie,NULL,Female,African-American,04/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +55972,63806,57896,Probation,Metayer,Nellie,NULL,Female,African-American,04/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55959,63793,57883,PRETRIAL,Chavarriacalderon,Edy,NULL,Male,Caucasian,06/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +55959,63793,57883,PRETRIAL,Chavarriacalderon,Edy,NULL,Male,Caucasian,06/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +55959,63793,57883,PRETRIAL,Chavarriacalderon,Edy,NULL,Male,Caucasian,06/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55971,63805,57895,Probation,Pina,Jose,NULL,Male,Hispanic,05/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +55971,63805,57895,Probation,Pina,Jose,NULL,Male,Hispanic,05/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +55971,63805,57895,Probation,Pina,Jose,NULL,Male,Hispanic,05/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55978,63812,57902,PRETRIAL,Guy,Ampella,NULL,Female,African-American,05/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +55978,63812,57902,PRETRIAL,Guy,Ampella,NULL,Female,African-American,05/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +55978,63812,57902,PRETRIAL,Guy,Ampella,NULL,Female,African-American,05/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55962,63796,57886,PRETRIAL,Gonzalez,Giovanny,NULL,Male,Hispanic,01/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +55962,63796,57886,PRETRIAL,Gonzalez,Giovanny,NULL,Male,Hispanic,01/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +55962,63796,57886,PRETRIAL,Gonzalez,Giovanny,NULL,Male,Hispanic,01/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55969,63803,57893,Probation,nolan,sheila,NULL,Female,Caucasian,10/26/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/26/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +55969,63803,57893,Probation,nolan,sheila,NULL,Female,Caucasian,10/26/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/26/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +55969,63803,57893,Probation,nolan,sheila,NULL,Female,Caucasian,10/26/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55966,63800,57890,PRETRIAL,Amico,Joseph,NULL,Male,Caucasian,01/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/26/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +55966,63800,57890,PRETRIAL,Amico,Joseph,NULL,Male,Caucasian,01/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/26/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +55966,63800,57890,PRETRIAL,Amico,Joseph,NULL,Male,Caucasian,01/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55958,63791,57882,PRETRIAL,Korkis,Jean,NULL,Male,Caucasian,06/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +55958,63791,57882,PRETRIAL,Korkis,Jean,NULL,Male,Caucasian,06/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +55958,63791,57882,PRETRIAL,Korkis,Jean,NULL,Male,Caucasian,06/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55973,63807,57897,Probation,vasil,crystal,NULL,Female,Caucasian,04/17/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +55973,63807,57897,Probation,vasil,crystal,NULL,Female,Caucasian,04/17/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +55973,63807,57897,Probation,vasil,crystal,NULL,Female,Caucasian,04/17/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55960,63794,57884,Probation,Bush,Joseph,A,Male,Caucasian,03/07/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/26/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +55960,63794,57884,Probation,Bush,Joseph,A,Male,Caucasian,03/07/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/26/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +55960,63794,57884,Probation,Bush,Joseph,A,Male,Caucasian,03/07/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55976,63810,57900,PRETRIAL,Helvie,James,NULL,Male,Caucasian,07/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +55976,63810,57900,PRETRIAL,Helvie,James,NULL,Male,Caucasian,07/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +55976,63810,57900,PRETRIAL,Helvie,James,NULL,Male,Caucasian,07/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55968,63802,57892,Probation,Morisseau,Gregory,NULL,Male,African-American,09/23/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/26/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +55968,63802,57892,Probation,Morisseau,Gregory,NULL,Male,African-American,09/23/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/26/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +55968,63802,57892,Probation,Morisseau,Gregory,NULL,Male,African-American,09/23/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55987,63823,57911,Probation,ALLEN,LABRINA,NULL,Female,African-American,03/18/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/29/13 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +55987,63823,57911,Probation,ALLEN,LABRINA,NULL,Female,African-American,03/18/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/29/13 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +55987,63823,57911,Probation,ALLEN,LABRINA,NULL,Female,African-American,03/18/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56015,63849,57934,Probation,CADE,KIRK,NULL,Male,African-American,12/11/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,7,Risk of Violence,-2.47,3,Low,New,1,0 +56015,63849,57934,Probation,CADE,KIRK,NULL,Male,African-American,12/11/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +56015,63849,57934,Probation,CADE,KIRK,NULL,Male,African-American,12/11/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +26064,63844,57931,PRETRIAL,TUNDIDOR,SHAWN,BEN,Male,Caucasian,12/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +26064,63844,57931,PRETRIAL,TUNDIDOR,SHAWN,BEN,Male,Caucasian,12/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +26064,63844,57931,PRETRIAL,TUNDIDOR,SHAWN,BEN,Male,Caucasian,12/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55981,63815,57905,PRETRIAL,Forester,William,NULL,Male,Caucasian,09/14/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +55981,63815,57905,PRETRIAL,Forester,William,NULL,Male,Caucasian,09/14/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +55981,63815,57905,PRETRIAL,Forester,William,NULL,Male,Caucasian,09/14/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +55983,63817,57907,PRETRIAL,Matthews,Clifford,Lee,Male,Caucasian,07/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +55983,63817,57907,PRETRIAL,Matthews,Clifford,Lee,Male,Caucasian,07/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +55983,63817,57907,PRETRIAL,Matthews,Clifford,Lee,Male,Caucasian,07/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56008,63842,57929,PRETRIAL,persaud,adesh,NULL,Male,Caucasian,09/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +56008,63842,57929,PRETRIAL,persaud,adesh,NULL,Male,Caucasian,09/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +56008,63842,57929,PRETRIAL,persaud,adesh,NULL,Male,Caucasian,09/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55985,63819,57909,Probation,fowler,sarah,NULL,Female,Caucasian,11/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +55985,63819,57909,Probation,fowler,sarah,NULL,Female,Caucasian,11/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +55985,63819,57909,Probation,fowler,sarah,NULL,Female,Caucasian,11/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +55991,63826,57914,Probation,Saiker,Anthony,NULL,Male,Caucasian,04/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +55991,63826,57914,Probation,Saiker,Anthony,NULL,Male,Caucasian,04/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +55991,63826,57914,Probation,Saiker,Anthony,NULL,Male,Caucasian,04/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56000,63833,57920,Probation,Gill,Kevinne,NULL,Male,Caucasian,03/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +56000,63833,57920,Probation,Gill,Kevinne,NULL,Male,Caucasian,03/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +56000,63833,57920,Probation,Gill,Kevinne,NULL,Male,Caucasian,03/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56020,63854,57939,PRETRIAL,BRYDEN,KAREN,NULL,Male,Caucasian,05/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +56020,63854,57939,PRETRIAL,BRYDEN,KAREN,NULL,Male,Caucasian,05/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +56020,63854,57939,PRETRIAL,BRYDEN,KAREN,NULL,Male,Caucasian,05/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55992,63827,57915,PRETRIAL,schatzberg,anne,NULL,Female,Caucasian,06/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/29/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +55992,63827,57915,PRETRIAL,schatzberg,anne,NULL,Female,Caucasian,06/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/29/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +55992,63827,57915,PRETRIAL,schatzberg,anne,NULL,Female,Caucasian,06/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56006,63840,57927,Probation,sacon,lionel,NULL,Male,Caucasian,08/28/36,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/29/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +56006,63840,57927,Probation,sacon,lionel,NULL,Male,Caucasian,08/28/36,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/29/13 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +56006,63840,57927,Probation,sacon,lionel,NULL,Male,Caucasian,08/28/36,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56002,63835,57922,Probation,williams,oslet,NULL,Male,African-American,01/23/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +56002,63835,57922,Probation,williams,oslet,NULL,Male,African-American,01/23/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +56002,63835,57922,Probation,williams,oslet,NULL,Male,African-American,01/23/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56019,63853,57938,PRETRIAL,Jean,louisette,NULL,Female,Other,12/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/29/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +56019,63853,57938,PRETRIAL,Jean,louisette,NULL,Female,Other,12/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/29/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +56019,63853,57938,PRETRIAL,Jean,louisette,NULL,Female,Other,12/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55999,63832,57919,Probation,Roderick,Timothy,NULL,Male,Caucasian,03/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +55999,63832,57919,Probation,Roderick,Timothy,NULL,Male,Caucasian,03/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +55999,63832,57919,Probation,Roderick,Timothy,NULL,Male,Caucasian,03/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56011,63843,57930,PRETRIAL,Dye,Deanna,J,Female,Caucasian,01/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +56011,63843,57930,PRETRIAL,Dye,Deanna,J,Female,Caucasian,01/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +56011,63843,57930,PRETRIAL,Dye,Deanna,J,Female,Caucasian,01/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56012,63845,57932,PRETRIAL,Sachs,Kevin,NULL,Male,Caucasian,07/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +56012,63845,57932,PRETRIAL,Sachs,Kevin,NULL,Male,Caucasian,07/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +56012,63845,57932,PRETRIAL,Sachs,Kevin,NULL,Male,Caucasian,07/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56016,63850,57935,Probation,Waite,Craig,Anthony,Male,African-American,04/29/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +56016,63850,57935,Probation,Waite,Craig,Anthony,Male,African-American,04/29/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +56016,63850,57935,Probation,Waite,Craig,Anthony,Male,African-American,04/29/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55803,63822,57706,PRETRIAL,WILSON,KENNETH,NULL,Male,African-American,05/21/55,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.24,8,High,Copy,1,0 +55803,63822,57706,PRETRIAL,WILSON,KENNETH,NULL,Male,African-American,05/21/55,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.1,7,Medium,Copy,1,0 +55803,63822,57706,PRETRIAL,WILSON,KENNETH,NULL,Male,African-American,05/21/55,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,48,10,High,Copy,1,0 +55990,63824,57912,Probation,Ibanez,Caroline,NULL,Female,Caucasian,10/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,7,Risk of Violence,-2.27,3,Low,New,1,0 +55990,63824,57912,Probation,Ibanez,Caroline,NULL,Female,Caucasian,10/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +55990,63824,57912,Probation,Ibanez,Caroline,NULL,Female,Caucasian,10/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55982,63816,57906,PRETRIAL,williams,joseph,NULL,Male,Caucasian,08/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +55982,63816,57906,PRETRIAL,williams,joseph,NULL,Male,Caucasian,08/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +55982,63816,57906,PRETRIAL,williams,joseph,NULL,Male,Caucasian,08/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55995,63830,57917,DRRD,Lozandier,Wilnick,NULL,Male,African-American,06/01/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +55995,63830,57917,DRRD,Lozandier,Wilnick,NULL,Male,African-American,06/01/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,8,High,New,1,0 +55995,63830,57917,DRRD,Lozandier,Wilnick,NULL,Male,African-American,06/01/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,2,Low,New,1,0 +5311,63837,57924,PRETRIAL,LEDUC,LINDA,M,Female,African-American,07/20/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.01,4,Low,New,1,0 +5311,63837,57924,PRETRIAL,LEDUC,LINDA,M,Female,African-American,07/20/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,9,High,New,1,0 +5311,63837,57924,PRETRIAL,LEDUC,LINDA,M,Female,African-American,07/20/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +56017,63851,57936,Probation,Douglas,Kemisha,NULL,Female,African-American,12/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/29/13 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +56017,63851,57936,Probation,Douglas,Kemisha,NULL,Female,African-American,12/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +56017,63851,57936,Probation,Douglas,Kemisha,NULL,Female,African-American,12/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/29/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +56014,63848,57933,PRETRIAL,osejo,victor,NULL,Male,Hispanic,06/14/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/29/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +56014,63848,57933,PRETRIAL,osejo,victor,NULL,Male,Hispanic,06/14/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/29/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +56014,63848,57933,PRETRIAL,osejo,victor,NULL,Male,Hispanic,06/14/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +46435,63820,46850,Probation,bernstein,jesse,NULL,Male,Caucasian,04/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,Copy,1,0 +46435,63820,46850,Probation,bernstein,jesse,NULL,Male,Caucasian,04/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,Copy,1,0 +46435,63820,46850,Probation,bernstein,jesse,NULL,Male,Caucasian,04/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +56005,63839,57926,PRETRIAL,Nani,Bianca,NULL,Female,Caucasian,05/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +56005,63839,57926,PRETRIAL,Nani,Bianca,NULL,Female,Caucasian,05/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +56005,63839,57926,PRETRIAL,Nani,Bianca,NULL,Female,Caucasian,05/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56007,63841,57928,Probation,Brooks,Cortney,NULL,Male,African-American,09/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +56007,63841,57928,Probation,Brooks,Cortney,NULL,Male,African-American,09/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +56007,63841,57928,Probation,Brooks,Cortney,NULL,Male,African-American,09/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55989,63825,57913,Probation,lindsay,marquavis,NULL,Male,African-American,08/08/93,17,All Scales,Intake,English,Other,Probation,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +55989,63825,57913,Probation,lindsay,marquavis,NULL,Male,African-American,08/08/93,17,All Scales,Intake,English,Other,Probation,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-0.72,3,Low,New,1,0 +55989,63825,57913,Probation,lindsay,marquavis,NULL,Male,African-American,08/08/93,17,All Scales,Intake,English,Other,Probation,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55996,63829,57916,Probation,busto,sergio,NULL,Male,Caucasian,05/14/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +55996,63829,57916,Probation,busto,sergio,NULL,Male,Caucasian,05/14/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +55996,63829,57916,Probation,busto,sergio,NULL,Male,Caucasian,05/14/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56001,63834,57921,Probation,COATS,SHERMILLA,NULL,Female,African-American,07/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +56001,63834,57921,Probation,COATS,SHERMILLA,NULL,Female,African-American,07/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +56001,63834,57921,Probation,COATS,SHERMILLA,NULL,Female,African-American,07/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56021,63855,57940,PRETRIAL,SIMS,WILLIAM,C,Male,Caucasian,04/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +56021,63855,57940,PRETRIAL,SIMS,WILLIAM,C,Male,Caucasian,04/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +56021,63855,57940,PRETRIAL,SIMS,WILLIAM,C,Male,Caucasian,04/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55267,63864,57089,Probation,Grieco,Justin,NULL,Male,Caucasian,06/08/94,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/30/13 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +55267,63864,57089,Probation,Grieco,Justin,NULL,Male,Caucasian,06/08/94,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/30/13 0:00,4,High,8,Risk of Recidivism,0.67,9,High,New,1,0 +55267,63864,57089,Probation,Grieco,Justin,NULL,Male,Caucasian,06/08/94,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/30/13 0:00,4,High,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +56027,63860,57945,Probation,SCHMIDT,CHRISTINA,NULL,Female,Caucasian,07/04/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +56027,63860,57945,Probation,SCHMIDT,CHRISTINA,NULL,Female,Caucasian,07/04/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +56027,63860,57945,Probation,SCHMIDT,CHRISTINA,NULL,Female,Caucasian,07/04/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56033,63867,57951,Probation,Peterman,Brett,NULL,Male,Caucasian,08/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +56033,63867,57951,Probation,Peterman,Brett,NULL,Male,Caucasian,08/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +56033,63867,57951,Probation,Peterman,Brett,NULL,Male,Caucasian,08/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56029,63862,57947,Probation,Richard,Rhonda,NULL,Female,African-American,01/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +56029,63862,57947,Probation,Richard,Rhonda,NULL,Female,African-American,01/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +56029,63862,57947,Probation,Richard,Rhonda,NULL,Female,African-American,01/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56034,63869,57953,Probation,Francis,Ceon,NULL,Female,African-American,02/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.36,3,Low,New,1,0 +56034,63869,57953,Probation,Francis,Ceon,NULL,Female,African-American,02/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,9,High,New,1,0 +56034,63869,57953,Probation,Francis,Ceon,NULL,Female,African-American,02/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +56032,63866,57950,Probation,Smith,Nikkia,NULL,Female,African-American,09/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +56032,63866,57950,Probation,Smith,Nikkia,NULL,Female,African-American,09/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +56032,63866,57950,Probation,Smith,Nikkia,NULL,Female,African-American,09/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56024,63858,57943,PRETRIAL,Fleischer,Heather,NULL,Female,Caucasian,01/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/30/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +56024,63858,57943,PRETRIAL,Fleischer,Heather,NULL,Female,Caucasian,01/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/30/13 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +56024,63858,57943,PRETRIAL,Fleischer,Heather,NULL,Female,Caucasian,01/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/30/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56036,63871,57955,Probation,Negron,John,NULL,Male,Caucasian,09/20/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +56036,63871,57955,Probation,Negron,John,NULL,Male,Caucasian,09/20/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +56036,63871,57955,Probation,Negron,John,NULL,Male,Caucasian,09/20/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56028,63861,57946,Probation,katchay,ronald,NULL,Male,Native American,06/05/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,7/30/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +56028,63861,57946,Probation,katchay,ronald,NULL,Male,Native American,06/05/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,7/30/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +56028,63861,57946,Probation,katchay,ronald,NULL,Male,Native American,06/05/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,7/30/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56030,63863,57948,Probation,Moses,Robert,NULL,Male,Caucasian,10/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +56030,63863,57948,Probation,Moses,Robert,NULL,Male,Caucasian,10/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +56030,63863,57948,Probation,Moses,Robert,NULL,Male,Caucasian,10/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56026,63859,57944,Probation,Vaca,Myron,NULL,Male,Hispanic,06/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +56026,63859,57944,Probation,Vaca,Myron,NULL,Male,Hispanic,06/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +56026,63859,57944,Probation,Vaca,Myron,NULL,Male,Hispanic,06/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +32188,63868,57952,PRETRIAL,bueler,brian,g,Male,Caucasian,01/24/93,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,7/30/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +32188,63868,57952,PRETRIAL,bueler,brian,g,Male,Caucasian,01/24/93,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,7/30/13 0:00,4,High,8,Risk of Recidivism,0.31,8,High,New,1,0 +32188,63868,57952,PRETRIAL,bueler,brian,g,Male,Caucasian,01/24/93,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,7/30/13 0:00,4,High,18,Risk of Failure to Appear,16,1,Low,New,1,0 +56031,63865,57949,Probation,bay,frank,NULL,Male,Caucasian,02/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +56031,63865,57949,Probation,bay,frank,NULL,Male,Caucasian,02/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +56031,63865,57949,Probation,bay,frank,NULL,Male,Caucasian,02/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56038,63873,57957,Probation,RODRIGUEZ,Eduardo,NULL,Male,Hispanic,11/23/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +56038,63873,57957,Probation,RODRIGUEZ,Eduardo,NULL,Male,Hispanic,11/23/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +56038,63873,57957,Probation,RODRIGUEZ,Eduardo,NULL,Male,Hispanic,11/23/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +20380,63870,57954,PRETRIAL,Libson,Joseph,Denard,Male,African-American,11/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +20380,63870,57954,PRETRIAL,Libson,Joseph,Denard,Male,African-American,11/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +20380,63870,57954,PRETRIAL,Libson,Joseph,Denard,Male,African-American,11/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56065,63904,57984,Probation,osullivan,abina,NULL,Female,Caucasian,04/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +56065,63904,57984,Probation,osullivan,abina,NULL,Female,Caucasian,04/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +56065,63904,57984,Probation,osullivan,abina,NULL,Female,Caucasian,04/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54354,63891,57973,PRETRIAL,Chavarriacarballo,Hecotr,NULL,Male,Hispanic,11/20/86,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,7/31/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +54354,63891,57973,PRETRIAL,Chavarriacarballo,Hecotr,NULL,Male,Hispanic,11/20/86,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,7/31/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +54354,63891,57973,PRETRIAL,Chavarriacarballo,Hecotr,NULL,Male,Hispanic,11/20/86,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Separated,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56057,63896,57976,Probation,Graham,Henry,NULL,Male,African-American,09/02/52,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Widowed,7/31/13 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +56057,63896,57976,Probation,Graham,Henry,NULL,Male,African-American,09/02/52,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Widowed,7/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +56057,63896,57976,Probation,Graham,Henry,NULL,Male,African-American,09/02/52,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Widowed,7/31/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +56060,63899,57979,Probation,Medina,Edgar,NULL,Male,Hispanic,12/27/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/31/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +56060,63899,57979,Probation,Medina,Edgar,NULL,Male,Hispanic,12/27/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/31/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +56060,63899,57979,Probation,Medina,Edgar,NULL,Male,Hispanic,12/27/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55014,63878,56786,Probation,Gomez,Mike,NULL,Male,Hispanic,11/15/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.34,3,Low,Copy,1,0 +55014,63878,56786,Probation,Gomez,Mike,NULL,Male,Hispanic,11/15/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,Copy,1,0 +55014,63878,56786,Probation,Gomez,Mike,NULL,Male,Hispanic,11/15/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +56050,63888,57970,Probation,Andrews,Basil,NULL,Male,Asian,09/13/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,7,Risk of Violence,-4.45,1,Low,New,1,0 +56050,63888,57970,Probation,Andrews,Basil,NULL,Male,Asian,09/13/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +56050,63888,57970,Probation,Andrews,Basil,NULL,Male,Asian,09/13/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56048,63886,57968,Probation,Fox,Regina,Marie,Female,Caucasian,08/23/43,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,7/31/13 0:00,1,Low,7,Risk of Violence,-4.45,1,Low,New,1,0 +56048,63886,57968,Probation,Fox,Regina,Marie,Female,Caucasian,08/23/43,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,7/31/13 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +56048,63886,57968,Probation,Fox,Regina,Marie,Female,Caucasian,08/23/43,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56044,63880,57963,Probation,Vazquez,Alexa,NULL,Female,Hispanic,02/14/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +56044,63880,57963,Probation,Vazquez,Alexa,NULL,Female,Hispanic,02/14/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/13 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +56044,63880,57963,Probation,Vazquez,Alexa,NULL,Female,Hispanic,02/14/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56055,63893,57975,Probation,KING,MITCHELL,H,Male,Caucasian,07/20/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/31/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +56055,63893,57975,Probation,KING,MITCHELL,H,Male,Caucasian,07/20/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/31/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +56055,63893,57975,Probation,KING,MITCHELL,H,Male,Caucasian,07/20/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56052,63889,57971,PRETRIAL,Jewel,Terry,NULL,Male,African-American,02/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/13 0:00,4,High,7,Risk of Violence,-0.38,10,High,New,1,0 +56052,63889,57971,PRETRIAL,Jewel,Terry,NULL,Male,African-American,02/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/13 0:00,4,High,8,Risk of Recidivism,1.04,10,High,New,1,0 +56052,63889,57971,PRETRIAL,Jewel,Terry,NULL,Male,African-American,02/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +56042,63877,57961,Probation,SEAMSTER,SHARICE,NULL,Female,African-American,11/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +56042,63877,57961,Probation,SEAMSTER,SHARICE,NULL,Female,African-American,11/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +56042,63877,57961,Probation,SEAMSTER,SHARICE,NULL,Female,African-American,11/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56047,63884,57966,Probation,Ace,Ebony,NULL,Female,African-American,10/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +56047,63884,57966,Probation,Ace,Ebony,NULL,Female,African-American,10/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +56047,63884,57966,Probation,Ace,Ebony,NULL,Female,African-American,10/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56040,63875,57959,Probation,STEEL,GREGORY,ALLEN,Male,African-American,11/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +56040,63875,57959,Probation,STEEL,GREGORY,ALLEN,Male,African-American,11/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +56040,63875,57959,Probation,STEEL,GREGORY,ALLEN,Male,African-American,11/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56066,63905,57985,PRETRIAL,ELLIS,KEVIN,JAMES,Male,African-American,05/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.01,8,High,New,1,0 +56066,63905,57985,PRETRIAL,ELLIS,KEVIN,JAMES,Male,African-American,05/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +56066,63905,57985,PRETRIAL,ELLIS,KEVIN,JAMES,Male,African-American,05/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56059,63898,57978,Probation,Rivera,Britteny,Jamie,Female,Hispanic,04/19/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +56059,63898,57978,Probation,Rivera,Britteny,Jamie,Female,Hispanic,04/19/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +56059,63898,57978,Probation,Rivera,Britteny,Jamie,Female,Hispanic,04/19/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +8364,63895,7914,PRETRIAL,Smith,Jonathan,NULL,Male,African-American,01/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,Copy,1,0 +8364,63895,7914,PRETRIAL,Smith,Jonathan,NULL,Male,African-American,01/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,Copy,1,0 +8364,63895,7914,PRETRIAL,Smith,Jonathan,NULL,Male,African-American,01/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +56039,63874,57958,Probation,Neal,Terrence,NULL,Male,African-American,09/09/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/13 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +56039,63874,57958,Probation,Neal,Terrence,NULL,Male,African-American,09/09/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +56039,63874,57958,Probation,Neal,Terrence,NULL,Male,African-American,09/09/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56045,63882,57964,PRETRIAL,Joseph,Jean,NULL,Male,African-American,03/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.59,1,Low,New,1,0 +56045,63882,57964,PRETRIAL,Joseph,Jean,NULL,Male,African-American,03/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +56045,63882,57964,PRETRIAL,Joseph,Jean,NULL,Male,African-American,03/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56054,63892,57974,PRETRIAL,samuels,tony,NULL,Male,African-American,10/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +56054,63892,57974,PRETRIAL,samuels,tony,NULL,Male,African-American,10/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.74,10,High,New,1,0 +56054,63892,57974,PRETRIAL,samuels,tony,NULL,Male,African-American,10/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +56064,63903,57983,Probation,Gauntlett,Christopher,Donald,Male,African-American,10/25/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +56064,63903,57983,Probation,Gauntlett,Christopher,Donald,Male,African-American,10/25/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +56064,63903,57983,Probation,Gauntlett,Christopher,Donald,Male,African-American,10/25/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56043,63879,57962,Probation,AVELLANEDA,ANA,MICHELLE,Female,Hispanic,02/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +56043,63879,57962,Probation,AVELLANEDA,ANA,MICHELLE,Female,Hispanic,02/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +56043,63879,57962,Probation,AVELLANEDA,ANA,MICHELLE,Female,Hispanic,02/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +56049,63887,57969,Probation,DUDLEY,CRAIG,NULL,Male,African-American,09/11/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +56049,63887,57969,Probation,DUDLEY,CRAIG,NULL,Male,African-American,09/11/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +56049,63887,57969,Probation,DUDLEY,CRAIG,NULL,Male,African-American,09/11/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56041,63876,57960,Probation,Freelove,Jessica,NULL,Female,African-American,11/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +56041,63876,57960,Probation,Freelove,Jessica,NULL,Female,African-American,11/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,9,High,New,1,0 +56041,63876,57960,Probation,Freelove,Jessica,NULL,Female,African-American,11/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56046,63883,57965,Probation,SIRAGUSA,ALLAN,NULL,Male,Caucasian,08/31/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +56046,63883,57965,Probation,SIRAGUSA,ALLAN,NULL,Male,Caucasian,08/31/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +56046,63883,57965,Probation,SIRAGUSA,ALLAN,NULL,Male,Caucasian,08/31/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +56058,63897,57977,Probation,drushel,matthew,NULL,Male,Caucasian,11/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +56058,63897,57977,Probation,drushel,matthew,NULL,Male,Caucasian,11/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +56058,63897,57977,Probation,drushel,matthew,NULL,Male,Caucasian,11/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56053,63890,57972,Probation,luongo,maria,NULL,Female,Caucasian,07/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/31/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +56053,63890,57972,Probation,luongo,maria,NULL,Female,Caucasian,07/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/31/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +56053,63890,57972,Probation,luongo,maria,NULL,Female,Caucasian,07/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +50750,63885,57967,Probation,Conner,Selena,Danielle,Female,Caucasian,11/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +50750,63885,57967,Probation,Conner,Selena,Danielle,Female,Caucasian,11/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +50750,63885,57967,Probation,Conner,Selena,Danielle,Female,Caucasian,11/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +56101,63953,58031,PRETRIAL,Howard,Augusta,NULL,Male,African-American,02/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +56101,63953,58031,PRETRIAL,Howard,Augusta,NULL,Male,African-American,02/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +56101,63953,58031,PRETRIAL,Howard,Augusta,NULL,Male,African-American,02/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56086,63932,58010,Probation,Jessup,Kevin,Maurice,Male,African-American,03/07/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +56086,63932,58010,Probation,Jessup,Kevin,Maurice,Male,African-American,03/07/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +56086,63932,58010,Probation,Jessup,Kevin,Maurice,Male,African-American,03/07/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +35278,63906,57986,PRETRIAL,COOPER,NORMANDO,NULL,Male,African-American,05/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,4,High,7,Risk of Violence,-0.9,9,High,New,1,0 +35278,63906,57986,PRETRIAL,COOPER,NORMANDO,NULL,Male,African-American,05/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +35278,63906,57986,PRETRIAL,COOPER,NORMANDO,NULL,Male,African-American,05/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56081,63923,58003,PRETRIAL,Haire,Mitchell,NULL,Male,Caucasian,07/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +56081,63923,58003,PRETRIAL,Haire,Mitchell,NULL,Male,Caucasian,07/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +56081,63923,58003,PRETRIAL,Haire,Mitchell,NULL,Male,Caucasian,07/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +56082,63927,58005,Probation,LEON,JASMINE,J,Female,African-American,06/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +56082,63927,58005,Probation,LEON,JASMINE,J,Female,African-American,06/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +56082,63927,58005,Probation,LEON,JASMINE,J,Female,African-American,06/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56090,63936,58014,Probation,GRIFFITH,DAVITA,NULL,Female,Hispanic,02/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +56090,63936,58014,Probation,GRIFFITH,DAVITA,NULL,Female,Hispanic,02/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +56090,63936,58014,Probation,GRIFFITH,DAVITA,NULL,Female,Hispanic,02/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51982,63941,58019,PRETRIAL,Hoover,Edward,Jose,Male,Caucasian,06/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +51982,63941,58019,PRETRIAL,Hoover,Edward,Jose,Male,Caucasian,06/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +51982,63941,58019,PRETRIAL,Hoover,Edward,Jose,Male,Caucasian,06/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +56070,63911,57991,PRETRIAL,BLACKWOOD,CATHERINE,NULL,Female,African-American,03/08/41,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +56070,63911,57991,PRETRIAL,BLACKWOOD,CATHERINE,NULL,Female,African-American,03/08/41,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +56070,63911,57991,PRETRIAL,BLACKWOOD,CATHERINE,NULL,Female,African-American,03/08/41,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56076,63918,57998,PRETRIAL,SPOONEMORE,BRENT,DAVID,Male,Caucasian,12/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +56076,63918,57998,PRETRIAL,SPOONEMORE,BRENT,DAVID,Male,Caucasian,12/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +56076,63918,57998,PRETRIAL,SPOONEMORE,BRENT,DAVID,Male,Caucasian,12/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56079,63920,58000,PRETRIAL,Beneche,Frantz,NULL,Male,Other,07/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/1/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +56079,63920,58000,PRETRIAL,Beneche,Frantz,NULL,Male,Other,07/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/1/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +56079,63920,58000,PRETRIAL,Beneche,Frantz,NULL,Male,Other,07/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56098,63948,58026,Probation,Maraj,Sharmeel,NULL,Male,Asian,02/17/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +56098,63948,58026,Probation,Maraj,Sharmeel,NULL,Male,Asian,02/17/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +56098,63948,58026,Probation,Maraj,Sharmeel,NULL,Male,Asian,02/17/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56091,63937,58015,Probation,Jones,Gail,NULL,Female,Caucasian,11/10/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.24,1,Low,New,1,0 +56091,63937,58015,Probation,Jones,Gail,NULL,Female,Caucasian,11/10/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,9,High,New,1,0 +56091,63937,58015,Probation,Jones,Gail,NULL,Female,Caucasian,11/10/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +48276,63944,58022,PRETRIAL,GUEPSEN,DAREUS,NULL,Male,African-American,07/22/64,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +48276,63944,58022,PRETRIAL,GUEPSEN,DAREUS,NULL,Male,African-American,07/22/64,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +48276,63944,58022,PRETRIAL,GUEPSEN,DAREUS,NULL,Male,African-American,07/22/64,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56075,63916,57996,PRETRIAL,Walker,Danue,Trotwesley,Male,Other,06/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +56075,63916,57996,PRETRIAL,Walker,Danue,Trotwesley,Male,Other,06/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +56075,63916,57996,PRETRIAL,Walker,Danue,Trotwesley,Male,Other,06/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56095,63945,58023,Probation,KALLSTROM,KIMBERLY,ELISE,Female,Caucasian,02/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +56095,63945,58023,Probation,KALLSTROM,KIMBERLY,ELISE,Female,Caucasian,02/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +56095,63945,58023,Probation,KALLSTROM,KIMBERLY,ELISE,Female,Caucasian,02/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56100,63952,58030,Probation,Murray,Jennifer,Andrea,Female,African-American,10/04/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +56100,63952,58030,Probation,Murray,Jennifer,Andrea,Female,African-American,10/04/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,9,High,New,1,0 +56100,63952,58030,Probation,Murray,Jennifer,Andrea,Female,African-American,10/04/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +7532,63921,58001,PRETRIAL,schurman,carl,NULL,Male,African-American,08/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +7532,63921,58001,PRETRIAL,schurman,carl,NULL,Male,African-American,08/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,4,High,8,Risk of Recidivism,0.22,8,High,New,1,0 +7532,63921,58001,PRETRIAL,schurman,carl,NULL,Male,African-American,08/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +41390,63942,58020,PRETRIAL,Mckennie,Jonathan,NULL,Male,African-American,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.11,8,High,New,1,0 +41390,63942,58020,PRETRIAL,Mckennie,Jonathan,NULL,Male,African-American,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +41390,63942,58020,PRETRIAL,Mckennie,Jonathan,NULL,Male,African-American,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56072,63913,57993,PRETRIAL,Noel,Leon,Jude,Male,African-American,08/21/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/1/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +56072,63913,57993,PRETRIAL,Noel,Leon,Jude,Male,African-American,08/21/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +56072,63913,57993,PRETRIAL,Noel,Leon,Jude,Male,African-American,08/21/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +23669,63950,58028,PRETRIAL,AQUIRRE,ADAM,NULL,Male,Hispanic,09/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +23669,63950,58028,PRETRIAL,AQUIRRE,ADAM,NULL,Male,Hispanic,09/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +23669,63950,58028,PRETRIAL,AQUIRRE,ADAM,NULL,Male,Hispanic,09/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56067,63908,57988,PRETRIAL,corey,Steven,L,Male,Caucasian,11/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,4,High,7,Risk of Violence,-0.84,9,High,New,1,0 +56067,63908,57988,PRETRIAL,corey,Steven,L,Male,Caucasian,11/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +56067,63908,57988,PRETRIAL,corey,Steven,L,Male,Caucasian,11/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56083,63929,58007,PRETRIAL,Crew,Delvea,NULL,Female,African-American,02/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/13 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +56083,63929,58007,PRETRIAL,Crew,Delvea,NULL,Female,African-American,02/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +56083,63929,58007,PRETRIAL,Crew,Delvea,NULL,Female,African-American,02/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56088,63934,58012,Probation,Girata,Andres,Eduardoa,Male,Hispanic,12/23/72,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/1/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +56088,63934,58012,Probation,Girata,Andres,Eduardoa,Male,Hispanic,12/23/72,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/1/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +56088,63934,58012,Probation,Girata,Andres,Eduardoa,Male,Hispanic,12/23/72,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56087,63933,58011,Probation,galindo,valeria,NULL,Female,Hispanic,02/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +56087,63933,58011,Probation,galindo,valeria,NULL,Female,Hispanic,02/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +56087,63933,58011,Probation,galindo,valeria,NULL,Female,Hispanic,02/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56071,63912,57992,PRETRIAL,Bromfield,Nicketta,A,Male,African-American,09/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +56071,63912,57992,PRETRIAL,Bromfield,Nicketta,A,Male,African-American,09/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +56071,63912,57992,PRETRIAL,Bromfield,Nicketta,A,Male,African-American,09/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56078,63919,57999,PRETRIAL,TORRES,MIRIAM,NULL,Female,Caucasian,06/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +56078,63919,57999,PRETRIAL,TORRES,MIRIAM,NULL,Female,Caucasian,06/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +56078,63919,57999,PRETRIAL,TORRES,MIRIAM,NULL,Female,Caucasian,06/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +41140,63954,58032,PRETRIAL,Miranda,Daniel,NULL,Male,Hispanic,05/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +41140,63954,58032,PRETRIAL,Miranda,Daniel,NULL,Male,Hispanic,05/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +41140,63954,58032,PRETRIAL,Miranda,Daniel,NULL,Male,Hispanic,05/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +49893,63940,58018,PRETRIAL,Chapman,Anthony,NULL,Male,Caucasian,08/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +49893,63940,58018,PRETRIAL,Chapman,Anthony,NULL,Male,Caucasian,08/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +49893,63940,58018,PRETRIAL,Chapman,Anthony,NULL,Male,Caucasian,08/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56073,63914,57994,PRETRIAL,Asayag,Shlomi,NULL,Male,Caucasian,01/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/1/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +56073,63914,57994,PRETRIAL,Asayag,Shlomi,NULL,Male,Caucasian,01/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/1/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +56073,63914,57994,PRETRIAL,Asayag,Shlomi,NULL,Male,Caucasian,01/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56085,63931,58009,Probation,Elder,Alexander,NULL,Male,Caucasian,08/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +56085,63931,58009,Probation,Elder,Alexander,NULL,Male,Caucasian,08/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +56085,63931,58009,Probation,Elder,Alexander,NULL,Male,Caucasian,08/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56099,63949,58027,PRETRIAL,Sawyer,Stephanie,NULL,Female,Caucasian,12/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/13 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +56099,63949,58027,PRETRIAL,Sawyer,Stephanie,NULL,Female,Caucasian,12/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,6,Medium,New,1,0 +56099,63949,58027,PRETRIAL,Sawyer,Stephanie,NULL,Female,Caucasian,12/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/13 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,New,1,0 +56069,63910,57990,PRETRIAL,Novoa,Fidel,NULL,Male,Caucasian,06/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/1/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +56069,63910,57990,PRETRIAL,Novoa,Fidel,NULL,Male,Caucasian,06/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/1/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +56069,63910,57990,PRETRIAL,Novoa,Fidel,NULL,Male,Caucasian,06/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +42976,63928,58006,PRETRIAL,LINARES,JOHANDER,NULL,Male,Caucasian,10/01/80,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/1/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +42976,63928,58006,PRETRIAL,LINARES,JOHANDER,NULL,Male,Caucasian,10/01/80,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/1/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +42976,63928,58006,PRETRIAL,LINARES,JOHANDER,NULL,Male,Caucasian,10/01/80,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56089,63935,58013,Probation,daniels,TIFFANY,NULL,Female,African-American,11/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.44,3,Low,New,1,0 +56089,63935,58013,Probation,daniels,TIFFANY,NULL,Female,African-American,11/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,8,High,New,1,0 +56089,63935,58013,Probation,daniels,TIFFANY,NULL,Female,African-American,11/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +56074,63915,57995,PRETRIAL,Scott,Jeffrey,NULL,Male,African-American,09/03/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +56074,63915,57995,PRETRIAL,Scott,Jeffrey,NULL,Male,African-American,09/03/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +56074,63915,57995,PRETRIAL,Scott,Jeffrey,NULL,Male,African-American,09/03/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56084,63930,58008,PRETRIAL,Wright,Tyler,Nelson,Male,Caucasian,01/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +56084,63930,58008,PRETRIAL,Wright,Tyler,Nelson,Male,Caucasian,01/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +56084,63930,58008,PRETRIAL,Wright,Tyler,Nelson,Male,Caucasian,01/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55644,63951,58029,Probation,riebe,robert,lee,Male,Caucasian,07/17/70,17,All Scales,Intake,English,Other,Probation,Single,8/1/13 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +55644,63951,58029,Probation,riebe,robert,lee,Male,Caucasian,07/17/70,17,All Scales,Intake,English,Other,Probation,Single,8/1/13 0:00,4,High,8,Risk of Recidivism,0.38,8,High,New,1,0 +55644,63951,58029,Probation,riebe,robert,lee,Male,Caucasian,07/17/70,17,All Scales,Intake,English,Other,Probation,Single,8/1/13 0:00,4,High,18,Risk of Failure to Appear,31,8,High,New,1,0 +56068,63909,57989,PRETRIAL,BROWNLEE,ULYSSES,JAMES,Male,African-American,02/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +56068,63909,57989,PRETRIAL,BROWNLEE,ULYSSES,JAMES,Male,African-American,02/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +56068,63909,57989,PRETRIAL,BROWNLEE,ULYSSES,JAMES,Male,African-American,02/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56094,63943,58021,PRETRIAL,BROWN,DWAYNE,ROY,Male,Other,04/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +56094,63943,58021,PRETRIAL,BROWN,DWAYNE,ROY,Male,Other,04/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +56094,63943,58021,PRETRIAL,BROWN,DWAYNE,ROY,Male,Other,04/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +4164,63907,57987,PRETRIAL,LOSADA,ELIAS,ALBERTO,Male,Caucasian,12/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +4164,63907,57987,PRETRIAL,LOSADA,ELIAS,ALBERTO,Male,Caucasian,12/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +4164,63907,57987,PRETRIAL,LOSADA,ELIAS,ALBERTO,Male,Caucasian,12/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56080,63922,58002,PRETRIAL,Sanchez,Andrienna,A,Female,African-American,09/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +56080,63922,58002,PRETRIAL,Sanchez,Andrienna,A,Female,African-American,09/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +56080,63922,58002,PRETRIAL,Sanchez,Andrienna,A,Female,African-American,09/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56077,63917,57997,PRETRIAL,Cole,Brian,Alan,Male,African-American,01/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +56077,63917,57997,PRETRIAL,Cole,Brian,Alan,Male,African-American,01/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +56077,63917,57997,PRETRIAL,Cole,Brian,Alan,Male,African-American,01/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56096,63946,58024,Probation,Mcclendon,Brian,NULL,Male,African-American,01/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,4,High,7,Risk of Violence,-0.23,10,High,New,1,0 +56096,63946,58024,Probation,Mcclendon,Brian,NULL,Male,African-American,01/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,4,High,8,Risk of Recidivism,0.96,10,High,New,1,0 +56096,63946,58024,Probation,Mcclendon,Brian,NULL,Male,African-American,01/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,4,High,18,Risk of Failure to Appear,42,10,High,New,1,0 +55810,63925,57713,PRETRIAL,LAND,CHARLES,NULL,Male,Caucasian,04/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,Copy,1,0 +55810,63925,57713,PRETRIAL,LAND,CHARLES,NULL,Male,Caucasian,04/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,Copy,1,0 +55810,63925,57713,PRETRIAL,LAND,CHARLES,NULL,Male,Caucasian,04/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +56093,63938,58016,DRRD,Pressley,Mark,Timothy,Male,African-American,07/18/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +56093,63938,58016,DRRD,Pressley,Mark,Timothy,Male,African-American,07/18/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +56093,63938,58016,DRRD,Pressley,Mark,Timothy,Male,African-American,07/18/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/1/13 0:00,4,High,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +47457,63972,49870,Probation,alli,nezam,NULL,Male,Other,09/10/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,Copy,1,0 +47457,63972,49870,Probation,alli,nezam,NULL,Male,Other,09/10/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,Copy,1,0 +47457,63972,49870,Probation,alli,nezam,NULL,Male,Other,09/10/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +56106,63959,58036,PRETRIAL,Willoughby,Brian,Keith,Male,African-American,11/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +56106,63959,58036,PRETRIAL,Willoughby,Brian,Keith,Male,African-American,11/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +56106,63959,58036,PRETRIAL,Willoughby,Brian,Keith,Male,African-American,11/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +48948,63967,58044,PRETRIAL,BRYANT,TRAVIS,A,Male,African-American,01/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +48948,63967,58044,PRETRIAL,BRYANT,TRAVIS,A,Male,African-American,01/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +48948,63967,58044,PRETRIAL,BRYANT,TRAVIS,A,Male,African-American,01/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56124,63985,58061,Probation,Disanto,John,NULL,Male,Caucasian,05/27/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +56124,63985,58061,Probation,Disanto,John,NULL,Male,Caucasian,05/27/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +56124,63985,58061,Probation,Disanto,John,NULL,Male,Caucasian,05/27/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +48900,63964,58041,PRETRIAL,FIELDS,ANTHONY,NULL,Male,Caucasian,02/20/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/2/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +48900,63964,58041,PRETRIAL,FIELDS,ANTHONY,NULL,Male,Caucasian,02/20/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/2/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +48900,63964,58041,PRETRIAL,FIELDS,ANTHONY,NULL,Male,Caucasian,02/20/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56127,63988,58064,Probation,Chiffelle,Patricio,Andres,Male,Hispanic,07/09/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/2/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +56127,63988,58064,Probation,Chiffelle,Patricio,Andres,Male,Hispanic,07/09/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/2/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +56127,63988,58064,Probation,Chiffelle,Patricio,Andres,Male,Hispanic,07/09/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56122,63982,58058,Probation,Whiting,Michael,NULL,Male,Caucasian,10/13/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/2/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +56122,63982,58058,Probation,Whiting,Michael,NULL,Male,Caucasian,10/13/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/2/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +56122,63982,58058,Probation,Whiting,Michael,NULL,Male,Caucasian,10/13/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56107,63961,58038,PRETRIAL,Lopez,Leny,Yesenia,Female,Hispanic,01/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +56107,63961,58038,PRETRIAL,Lopez,Leny,Yesenia,Female,Hispanic,01/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,New,1,0 +56107,63961,58038,PRETRIAL,Lopez,Leny,Yesenia,Female,Hispanic,01/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56112,63970,58047,Probation,Wheeler-Jones,Jeloni,NULL,Male,African-American,03/03/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/2/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +56112,63970,58047,Probation,Wheeler-Jones,Jeloni,NULL,Male,African-American,03/03/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/2/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +56112,63970,58047,Probation,Wheeler-Jones,Jeloni,NULL,Male,African-American,03/03/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/2/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56117,63977,58053,PRETRIAL,CECIL,MARIA,H,Female,Caucasian,06/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +56117,63977,58053,PRETRIAL,CECIL,MARIA,H,Female,Caucasian,06/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +56117,63977,58053,PRETRIAL,CECIL,MARIA,H,Female,Caucasian,06/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50485,63984,58060,Probation,maldonado,ruben,NULL,Male,Hispanic,02/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +50485,63984,58060,Probation,maldonado,ruben,NULL,Male,Hispanic,02/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +50485,63984,58060,Probation,maldonado,ruben,NULL,Male,Hispanic,02/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56102,63956,58033,PRETRIAL,Storey-Broderick,Karen,NULL,Female,African-American,09/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +56102,63956,58033,PRETRIAL,Storey-Broderick,Karen,NULL,Female,African-American,09/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +56102,63956,58033,PRETRIAL,Storey-Broderick,Karen,NULL,Female,African-American,09/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56115,63975,58051,DRRD,Belony,Kymone,J,Male,African-American,07/12/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +56115,63975,58051,DRRD,Belony,Kymone,J,Male,African-American,07/12/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,6,Medium,New,1,0 +56115,63975,58051,DRRD,Belony,Kymone,J,Male,African-American,07/12/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56110,63968,58045,PRETRIAL,Stroud,Joey,Henry,Male,African-American,02/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +56110,63968,58045,PRETRIAL,Stroud,Joey,Henry,Male,African-American,02/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +56110,63968,58045,PRETRIAL,Stroud,Joey,Henry,Male,African-American,02/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53776,63955,55261,PRETRIAL,Jones,Jarvis,NULL,Male,African-American,03/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,Copy,1,0 +53776,63955,55261,PRETRIAL,Jones,Jarvis,NULL,Male,African-American,03/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.8,10,High,Copy,1,0 +53776,63955,55261,PRETRIAL,Jones,Jarvis,NULL,Male,African-American,03/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +56128,63989,58065,Probation,harvard,markevis,NULL,Male,African-American,11/29/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +56128,63989,58065,Probation,harvard,markevis,NULL,Male,African-American,11/29/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +56128,63989,58065,Probation,harvard,markevis,NULL,Male,African-American,11/29/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56109,63963,58040,PRETRIAL,Alcobas,Kyle,James,Male,Caucasian,11/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +56109,63963,58040,PRETRIAL,Alcobas,Kyle,James,Male,Caucasian,11/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +56109,63963,58040,PRETRIAL,Alcobas,Kyle,James,Male,Caucasian,11/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56121,63981,58057,Probation,Coley,Evyan,Celisse,Male,African-American,01/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/2/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +56121,63981,58057,Probation,Coley,Evyan,Celisse,Male,African-American,01/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/2/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +56121,63981,58057,Probation,Coley,Evyan,Celisse,Male,African-American,01/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56105,63960,58037,PRETRIAL,King,Christine,NULL,Female,African-American,11/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +56105,63960,58037,PRETRIAL,King,Christine,NULL,Female,African-American,11/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +56105,63960,58037,PRETRIAL,King,Christine,NULL,Female,African-American,11/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56113,63971,58048,Probation,Hassoun,Ramzey,NULL,Male,Arabic,03/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +56113,63971,58048,Probation,Hassoun,Ramzey,NULL,Male,Arabic,03/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +56113,63971,58048,Probation,Hassoun,Ramzey,NULL,Male,Arabic,03/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56120,63979,58055,PRETRIAL,Harper,Michael,Franklin,Male,Caucasian,02/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +56120,63979,58055,PRETRIAL,Harper,Michael,Franklin,Male,Caucasian,02/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +56120,63979,58055,PRETRIAL,Harper,Michael,Franklin,Male,Caucasian,02/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56104,63958,58035,PRETRIAL,Boone,Demetrice,Antrod,Male,African-American,03/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +56104,63958,58035,PRETRIAL,Boone,Demetrice,Antrod,Male,African-American,03/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +56104,63958,58035,PRETRIAL,Boone,Demetrice,Antrod,Male,African-American,03/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56114,63973,58049,PRETRIAL,terjesen,heather,NULL,Female,Caucasian,09/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +56114,63973,58049,PRETRIAL,terjesen,heather,NULL,Female,Caucasian,09/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/13 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +56114,63973,58049,PRETRIAL,terjesen,heather,NULL,Female,Caucasian,09/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +47062,63966,58043,PRETRIAL,Smith,Shawniel,NULL,Male,African-American,02/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +47062,63966,58043,PRETRIAL,Smith,Shawniel,NULL,Male,African-American,02/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +47062,63966,58043,PRETRIAL,Smith,Shawniel,NULL,Male,African-American,02/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56126,63987,58063,Probation,Jean Pierre Fenelus,Rose Marie,NULL,Female,African-American,09/12/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/2/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +56126,63987,58063,Probation,Jean Pierre Fenelus,Rose Marie,NULL,Female,African-American,09/12/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/2/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +56126,63987,58063,Probation,Jean Pierre Fenelus,Rose Marie,NULL,Female,African-American,09/12/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56123,63983,58059,PRETRIAL,Gayoso,Nancy,NULL,Female,Hispanic,04/23/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/2/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +56123,63983,58059,PRETRIAL,Gayoso,Nancy,NULL,Female,Hispanic,04/23/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/2/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +56123,63983,58059,PRETRIAL,Gayoso,Nancy,NULL,Female,Hispanic,04/23/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56108,63962,58039,PRETRIAL,Warren,Kamal,NULL,Male,African-American,05/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +56108,63962,58039,PRETRIAL,Warren,Kamal,NULL,Male,African-American,05/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +56108,63962,58039,PRETRIAL,Warren,Kamal,NULL,Male,African-American,05/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56116,63976,58052,Probation,PIERRE,FRITZ,G,Male,African-American,10/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +56116,63976,58052,Probation,PIERRE,FRITZ,G,Male,African-American,10/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +56116,63976,58052,Probation,PIERRE,FRITZ,G,Male,African-American,10/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56129,63990,58066,PRETRIAL,VASQUEZ,CARLOS,NULL,Male,Hispanic,01/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +56129,63990,58066,PRETRIAL,VASQUEZ,CARLOS,NULL,Male,Hispanic,01/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +56129,63990,58066,PRETRIAL,VASQUEZ,CARLOS,NULL,Male,Hispanic,01/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56103,63957,58034,PRETRIAL,Johnson,Bruce,Howard,Male,African-American,01/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +56103,63957,58034,PRETRIAL,Johnson,Bruce,Howard,Male,African-American,01/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.77,10,High,New,1,0 +56103,63957,58034,PRETRIAL,Johnson,Bruce,Howard,Male,African-American,01/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +5141,63974,58050,PRETRIAL,HOLSTON,JERRY,JEROME,Male,African-American,08/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/13 0:00,2,Medium,7,Risk of Violence,-1.34,7,Medium,New,1,0 +5141,63974,58050,PRETRIAL,HOLSTON,JERRY,JEROME,Male,African-American,08/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +5141,63974,58050,PRETRIAL,HOLSTON,JERRY,JEROME,Male,African-American,08/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/13 0:00,2,Medium,18,Risk of Failure to Appear,40,10,High,New,1,0 +56118,63978,58054,PRETRIAL,lindsey,herbert,NULL,Male,African-American,12/13/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +56118,63978,58054,PRETRIAL,lindsey,herbert,NULL,Male,African-American,12/13/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +56118,63978,58054,PRETRIAL,lindsey,herbert,NULL,Male,African-American,12/13/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +17347,63995,58070,PRETRIAL,Amity,Christopher,J,Male,Caucasian,02/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/3/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +17347,63995,58070,PRETRIAL,Amity,Christopher,J,Male,Caucasian,02/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/3/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +17347,63995,58070,PRETRIAL,Amity,Christopher,J,Male,Caucasian,02/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +42273,63992,58067,PRETRIAL,Ross,Terry,T,Male,African-American,10/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/3/13 0:00,2,Medium,7,Risk of Violence,-2.66,2,Low,New,1,0 +42273,63992,58067,PRETRIAL,Ross,Terry,T,Male,African-American,10/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +42273,63992,58067,PRETRIAL,Ross,Terry,T,Male,African-American,10/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/3/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56133,63997,58072,PRETRIAL,Newman,Eric,NULL,Male,Caucasian,06/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +56133,63997,58072,PRETRIAL,Newman,Eric,NULL,Male,Caucasian,06/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +56133,63997,58072,PRETRIAL,Newman,Eric,NULL,Male,Caucasian,06/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56131,63994,58069,PRETRIAL,Smith,Jeremy,Bernard,Male,African-American,03/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.14,8,High,New,1,0 +56131,63994,58069,PRETRIAL,Smith,Jeremy,Bernard,Male,African-American,03/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,7,Medium,New,1,0 +56131,63994,58069,PRETRIAL,Smith,Jeremy,Bernard,Male,African-American,03/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +12539,63991,12022,PRETRIAL,metzger,john,joseph,Male,Caucasian,06/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,Copy,1,0 +12539,63991,12022,PRETRIAL,metzger,john,joseph,Male,Caucasian,06/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,Copy,1,0 +12539,63991,12022,PRETRIAL,metzger,john,joseph,Male,Caucasian,06/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +56132,63996,58071,PRETRIAL,GEORGE,BYRAN,NULL,Male,African-American,01/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +56132,63996,58071,PRETRIAL,GEORGE,BYRAN,NULL,Male,African-American,01/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +56132,63996,58071,PRETRIAL,GEORGE,BYRAN,NULL,Male,African-American,01/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56130,63993,58068,PRETRIAL,Tai,Cobie,B,Female,African-American,05/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +56130,63993,58068,PRETRIAL,Tai,Cobie,B,Female,African-American,05/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +56130,63993,58068,PRETRIAL,Tai,Cobie,B,Female,African-American,05/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56140,64006,58080,PRETRIAL,Moriaux,Hannsataky,NULL,Male,Caucasian,01/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +56140,64006,58080,PRETRIAL,Moriaux,Hannsataky,NULL,Male,Caucasian,01/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +56140,64006,58080,PRETRIAL,Moriaux,Hannsataky,NULL,Male,Caucasian,01/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56143,64009,58083,PRETRIAL,Garcia,Franco,NULL,Male,Hispanic,10/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +56143,64009,58083,PRETRIAL,Garcia,Franco,NULL,Male,Hispanic,10/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +56143,64009,58083,PRETRIAL,Garcia,Franco,NULL,Male,Hispanic,10/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56137,64001,58076,PRETRIAL,Manning,Kendarius,NULL,Male,African-American,11/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +56137,64001,58076,PRETRIAL,Manning,Kendarius,NULL,Male,African-American,11/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +56137,64001,58076,PRETRIAL,Manning,Kendarius,NULL,Male,African-American,11/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56138,64003,58078,PRETRIAL,ROSS,JOSHUA,E,Male,African-American,12/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +56138,64003,58078,PRETRIAL,ROSS,JOSHUA,E,Male,African-American,12/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.77,10,High,New,1,0 +56138,64003,58078,PRETRIAL,ROSS,JOSHUA,E,Male,African-American,12/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56136,64000,58075,PRETRIAL,Simms,Saschelle,NULL,Female,African-American,04/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +56136,64000,58075,PRETRIAL,Simms,Saschelle,NULL,Female,African-American,04/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +56136,64000,58075,PRETRIAL,Simms,Saschelle,NULL,Female,African-American,04/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +45590,64005,45868,PRETRIAL,Messina,Alan,Drew,Male,Other,05/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,Copy,1,0 +45590,64005,45868,PRETRIAL,Messina,Alan,Drew,Male,Other,05/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.52,4,Low,Copy,1,0 +45590,64005,45868,PRETRIAL,Messina,Alan,Drew,Male,Other,05/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +56135,63998,58073,PRETRIAL,Price,Precious,NULL,Male,Caucasian,12/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +56135,63998,58073,PRETRIAL,Price,Precious,NULL,Male,Caucasian,12/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +56135,63998,58073,PRETRIAL,Price,Precious,NULL,Male,Caucasian,12/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56141,64007,58081,PRETRIAL,Lindsey,Deandre,Al,Male,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +56141,64007,58081,PRETRIAL,Lindsey,Deandre,Al,Male,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +56141,64007,58081,PRETRIAL,Lindsey,Deandre,Al,Male,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56144,64010,58084,PRETRIAL,deperna,Christina,NULL,Female,Caucasian,10/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +56144,64010,58084,PRETRIAL,deperna,Christina,NULL,Female,Caucasian,10/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,10,High,New,1,0 +56144,64010,58084,PRETRIAL,deperna,Christina,NULL,Female,Caucasian,10/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +45956,64002,58077,PRETRIAL,Colias,Matthew,NULL,Male,Caucasian,11/04/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/4/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +45956,64002,58077,PRETRIAL,Colias,Matthew,NULL,Male,Caucasian,11/04/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/4/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +45956,64002,58077,PRETRIAL,Colias,Matthew,NULL,Male,Caucasian,11/04/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56145,64011,58085,PRETRIAL,buitrago,mauricio,NULL,Male,Hispanic,12/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +56145,64011,58085,PRETRIAL,buitrago,mauricio,NULL,Male,Hispanic,12/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +56145,64011,58085,PRETRIAL,buitrago,mauricio,NULL,Male,Hispanic,12/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56139,64004,58079,PRETRIAL,DERISSE,STEPHANIE,NULL,Female,African-American,11/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +56139,64004,58079,PRETRIAL,DERISSE,STEPHANIE,NULL,Female,African-American,11/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +56139,64004,58079,PRETRIAL,DERISSE,STEPHANIE,NULL,Female,African-American,11/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56142,64008,58082,PRETRIAL,GARCIADICIOCCO,GERMAN,LUIS,Male,Caucasian,08/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +56142,64008,58082,PRETRIAL,GARCIADICIOCCO,GERMAN,LUIS,Male,Caucasian,08/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +56142,64008,58082,PRETRIAL,GARCIADICIOCCO,GERMAN,LUIS,Male,Caucasian,08/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56134,63999,58074,PRETRIAL,JENKINS,JAMES,ALEXANDER,Male,African-American,11/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +56134,63999,58074,PRETRIAL,JENKINS,JAMES,ALEXANDER,Male,African-American,11/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +56134,63999,58074,PRETRIAL,JENKINS,JAMES,ALEXANDER,Male,African-American,11/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56148,64013,58087,PRETRIAL,Patton,Marvardo,NULL,Female,African-American,12/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +56148,64013,58087,PRETRIAL,Patton,Marvardo,NULL,Female,African-American,12/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +56148,64013,58087,PRETRIAL,Patton,Marvardo,NULL,Female,African-American,12/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56179,64050,58122,PRETRIAL,PACE,CHANEKA,NULL,Female,African-American,05/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,2,Medium,7,Risk of Violence,-3.07,1,Low,New,1,0 +56179,64050,58122,PRETRIAL,PACE,CHANEKA,NULL,Female,African-American,05/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +56179,64050,58122,PRETRIAL,PACE,CHANEKA,NULL,Female,African-American,05/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +56174,64046,58118,Probation,NOHARA,JANAINA,NULL,Female,Caucasian,11/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +56174,64046,58118,Probation,NOHARA,JANAINA,NULL,Female,Caucasian,11/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +56174,64046,58118,Probation,NOHARA,JANAINA,NULL,Female,Caucasian,11/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56155,64025,58098,Probation,parker,david,erik,Male,Caucasian,07/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +56155,64025,58098,Probation,parker,david,erik,Male,Caucasian,07/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +56155,64025,58098,Probation,parker,david,erik,Male,Caucasian,07/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +56183,64055,58127,PRETRIAL,Morales,Miguel,NULL,Male,Hispanic,09/29/40,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/5/13 0:00,1,Low,7,Risk of Violence,-4.33,1,Low,New,1,0 +56183,64055,58127,PRETRIAL,Morales,Miguel,NULL,Male,Hispanic,09/29/40,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/5/13 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +56183,64055,58127,PRETRIAL,Morales,Miguel,NULL,Male,Hispanic,09/29/40,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56159,64029,58102,PRETRIAL,Manz,Alexander,NULL,Male,Hispanic,02/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +56159,64029,58102,PRETRIAL,Manz,Alexander,NULL,Male,Hispanic,02/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +56159,64029,58102,PRETRIAL,Manz,Alexander,NULL,Male,Hispanic,02/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56164,64034,58107,Probation,Turkis,Andrew,NULL,Male,Caucasian,02/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +56164,64034,58107,Probation,Turkis,Andrew,NULL,Male,Caucasian,02/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +56164,64034,58107,Probation,Turkis,Andrew,NULL,Male,Caucasian,02/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56151,64018,58092,PRETRIAL,Johnson,Jeniqua,NULL,Female,African-American,10/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +56151,64018,58092,PRETRIAL,Johnson,Jeniqua,NULL,Female,African-American,10/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +56151,64018,58092,PRETRIAL,Johnson,Jeniqua,NULL,Female,African-American,10/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +52554,64020,53879,PRETRIAL,CENTOLELLA,ALLISON,NULL,Female,Caucasian,07/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,Copy,1,0 +52554,64020,53879,PRETRIAL,CENTOLELLA,ALLISON,NULL,Female,Caucasian,07/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,Copy,1,0 +52554,64020,53879,PRETRIAL,CENTOLELLA,ALLISON,NULL,Female,Caucasian,07/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +56169,64039,58112,Probation,CARSON,TACAVEON,NULL,Male,African-American,01/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +56169,64039,58112,Probation,CARSON,TACAVEON,NULL,Male,African-American,01/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +56169,64039,58112,Probation,CARSON,TACAVEON,NULL,Male,African-American,01/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50875,64041,51987,Probation,renz,daniel,NULL,Male,Caucasian,12/20/78,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +50875,64041,51987,Probation,renz,daniel,NULL,Male,Caucasian,12/20/78,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-0.23,5,Medium,New,1,0 +50875,64041,51987,Probation,renz,daniel,NULL,Male,Caucasian,12/20/78,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +56176,64048,58120,PRETRIAL,Becker,Melissa,NULL,Female,Caucasian,04/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/5/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +56176,64048,58120,PRETRIAL,Becker,Melissa,NULL,Female,Caucasian,04/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/5/13 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +56176,64048,58120,PRETRIAL,Becker,Melissa,NULL,Female,Caucasian,04/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +35081,64036,58109,PRETRIAL,Kopins,Sean,NULL,Male,Native American,07/25/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +35081,64036,58109,PRETRIAL,Kopins,Sean,NULL,Male,Native American,07/25/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +35081,64036,58109,PRETRIAL,Kopins,Sean,NULL,Male,Native American,07/25/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +38957,64023,58096,PRETRIAL,PRESSOTTO,DREW,NULL,Male,Caucasian,08/25/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/5/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +38957,64023,58096,PRETRIAL,PRESSOTTO,DREW,NULL,Male,Caucasian,08/25/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/5/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +38957,64023,58096,PRETRIAL,PRESSOTTO,DREW,NULL,Male,Caucasian,08/25/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56185,64057,58129,Probation,MELAND,JASON,GABRIEL,Male,Caucasian,07/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +56185,64057,58129,Probation,MELAND,JASON,GABRIEL,Male,Caucasian,07/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +56185,64057,58129,Probation,MELAND,JASON,GABRIEL,Male,Caucasian,07/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56158,64028,58101,PRETRIAL,Johnson,Latrice,NULL,Female,African-American,11/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +56158,64028,58101,PRETRIAL,Johnson,Latrice,NULL,Female,African-American,11/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +56158,64028,58101,PRETRIAL,Johnson,Latrice,NULL,Female,African-American,11/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +56161,64031,58104,Probation,Roger,Pinckney,NULL,Male,Caucasian,07/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +56161,64031,58104,Probation,Roger,Pinckney,NULL,Male,Caucasian,07/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +56161,64031,58104,Probation,Roger,Pinckney,NULL,Male,Caucasian,07/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56177,64049,58121,PRETRIAL,Lewis,Jeffrey,NULL,Male,African-American,03/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +56177,64049,58121,PRETRIAL,Lewis,Jeffrey,NULL,Male,African-American,03/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +56177,64049,58121,PRETRIAL,Lewis,Jeffrey,NULL,Male,African-American,03/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56172,64044,58116,PRETRIAL,Lopez-Escribano,Luis,Alexis,Male,Hispanic,03/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +56172,64044,58116,PRETRIAL,Lopez-Escribano,Luis,Alexis,Male,Hispanic,03/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +56172,64044,58116,PRETRIAL,Lopez-Escribano,Luis,Alexis,Male,Hispanic,03/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56149,64015,58089,PRETRIAL,RIVERA,LORRAINE,NULL,Female,Caucasian,10/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +56149,64015,58089,PRETRIAL,RIVERA,LORRAINE,NULL,Female,Caucasian,10/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +56149,64015,58089,PRETRIAL,RIVERA,LORRAINE,NULL,Female,Caucasian,10/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56163,64033,58106,Probation,ramirez,benhamin,NULL,Male,Hispanic,11/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/5/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +56163,64033,58106,Probation,ramirez,benhamin,NULL,Male,Hispanic,11/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/5/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +56163,64033,58106,Probation,ramirez,benhamin,NULL,Male,Hispanic,11/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56175,64047,58119,PRETRIAL,Douglas,Travis,J,Male,African-American,03/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,New,1,0 +56175,64047,58119,PRETRIAL,Douglas,Travis,J,Male,African-American,03/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +56175,64047,58119,PRETRIAL,Douglas,Travis,J,Male,African-American,03/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56146,64012,58086,PRETRIAL,DAVIS,ERIC,WAYNE,Male,African-American,02/05/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/5/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +56146,64012,58086,PRETRIAL,DAVIS,ERIC,WAYNE,Male,African-American,02/05/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/5/13 0:00,1,Low,8,Risk of Recidivism,-2.68,1,Low,New,1,0 +56146,64012,58086,PRETRIAL,DAVIS,ERIC,WAYNE,Male,African-American,02/05/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53154,64019,58093,PRETRIAL,LUEYOUNG,LESTER,NULL,Male,African-American,01/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +53154,64019,58093,PRETRIAL,LUEYOUNG,LESTER,NULL,Male,African-American,01/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +53154,64019,58093,PRETRIAL,LUEYOUNG,LESTER,NULL,Male,African-American,01/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56156,64026,58099,PRETRIAL,Ambroise,Maxim,NULL,Male,African-American,03/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +56156,64026,58099,PRETRIAL,Ambroise,Maxim,NULL,Male,African-American,03/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +56156,64026,58099,PRETRIAL,Ambroise,Maxim,NULL,Male,African-American,03/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56182,64054,58126,PRETRIAL,Marlowe,Joshua,NULL,Male,Caucasian,05/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,New,1,0 +56182,64054,58126,PRETRIAL,Marlowe,Joshua,NULL,Male,Caucasian,05/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +56182,64054,58126,PRETRIAL,Marlowe,Joshua,NULL,Male,Caucasian,05/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +9502,64017,58091,PRETRIAL,BROWN,TERRRANCE,D,Male,African-American,06/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +9502,64017,58091,PRETRIAL,BROWN,TERRRANCE,D,Male,African-American,06/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +9502,64017,58091,PRETRIAL,BROWN,TERRRANCE,D,Male,African-American,06/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56152,64021,58094,PRETRIAL,KING,JARAH,NULL,Female,African-American,03/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +56152,64021,58094,PRETRIAL,KING,JARAH,NULL,Female,African-American,03/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +56152,64021,58094,PRETRIAL,KING,JARAH,NULL,Female,African-American,03/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56168,64038,58111,PRETRIAL,Bazard,Christopher,NULL,Male,African-American,01/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +56168,64038,58111,PRETRIAL,Bazard,Christopher,NULL,Male,African-American,01/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +56168,64038,58111,PRETRIAL,Bazard,Christopher,NULL,Male,African-American,01/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56170,64042,58114,PRETRIAL,Micic,David,NULL,Male,Caucasian,04/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +56170,64042,58114,PRETRIAL,Micic,David,NULL,Male,Caucasian,04/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +56170,64042,58114,PRETRIAL,Micic,David,NULL,Male,Caucasian,04/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56167,64037,58110,Probation,Garrison,Brandon,NULL,Male,Caucasian,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +56167,64037,58110,Probation,Garrison,Brandon,NULL,Male,Caucasian,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +56167,64037,58110,Probation,Garrison,Brandon,NULL,Male,Caucasian,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +56178,64051,58123,Probation,Dyer,Roderick,NULL,Male,Caucasian,12/18/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/5/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +56178,64051,58123,Probation,Dyer,Roderick,NULL,Male,Caucasian,12/18/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/5/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +56178,64051,58123,Probation,Dyer,Roderick,NULL,Male,Caucasian,12/18/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56150,64016,58090,PRETRIAL,Patton,Juanita,NULL,Female,Other,07/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +56150,64016,58090,PRETRIAL,Patton,Juanita,NULL,Female,Other,07/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +56150,64016,58090,PRETRIAL,Patton,Juanita,NULL,Female,Other,07/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56160,64030,58103,Probation,GORDON,KEVIN,NULL,Male,African-American,12/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,7,Risk of Violence,-3.31,1,Low,New,1,0 +56160,64030,58103,Probation,GORDON,KEVIN,NULL,Male,African-American,12/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +56160,64030,58103,Probation,GORDON,KEVIN,NULL,Male,African-American,12/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56171,64043,58115,Probation,wilson,franklin,NULL,Male,Hispanic,09/24/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +56171,64043,58115,Probation,wilson,franklin,NULL,Male,Hispanic,09/24/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +56171,64043,58115,Probation,wilson,franklin,NULL,Male,Hispanic,09/24/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56173,64045,58117,PRETRIAL,Davis,Horace,NULL,Male,African-American,12/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +56173,64045,58117,PRETRIAL,Davis,Horace,NULL,Male,African-American,12/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +56173,64045,58117,PRETRIAL,Davis,Horace,NULL,Male,African-American,12/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +56153,64022,58095,PRETRIAL,Gibbons,Francis,NULL,Male,Caucasian,04/01/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/5/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +56153,64022,58095,PRETRIAL,Gibbons,Francis,NULL,Male,Caucasian,04/01/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/5/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +56153,64022,58095,PRETRIAL,Gibbons,Francis,NULL,Male,Caucasian,04/01/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56154,64024,58097,Probation,Smith,Amando,NULL,Female,African-American,03/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +56154,64024,58097,Probation,Smith,Amando,NULL,Female,African-American,03/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +56154,64024,58097,Probation,Smith,Amando,NULL,Female,African-American,03/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,2,Medium,18,Risk of Failure to Appear,30,9,High,New,1,0 +56186,64058,58130,Probation,Byrd,Juliett,NULL,Female,Hispanic,03/14/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-4.55,1,Low,New,1,0 +56186,64058,58130,Probation,Byrd,Juliett,NULL,Female,Hispanic,03/14/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-2.77,1,Low,New,1,0 +56186,64058,58130,Probation,Byrd,Juliett,NULL,Female,Hispanic,03/14/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +31815,64040,58113,PRETRIAL,GILLIS,ANTWAN,D,Male,African-American,10/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +31815,64040,58113,PRETRIAL,GILLIS,ANTWAN,D,Male,African-American,10/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +31815,64040,58113,PRETRIAL,GILLIS,ANTWAN,D,Male,African-American,10/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56157,64027,58100,Probation,Lewis,Carlton,NULL,Male,African-American,05/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/5/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +56157,64027,58100,Probation,Lewis,Carlton,NULL,Male,African-American,05/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/5/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +56157,64027,58100,Probation,Lewis,Carlton,NULL,Male,African-American,05/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56147,64014,58088,PRETRIAL,ROA,JESUS,NULL,Male,Caucasian,07/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +56147,64014,58088,PRETRIAL,ROA,JESUS,NULL,Male,Caucasian,07/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +56147,64014,58088,PRETRIAL,ROA,JESUS,NULL,Male,Caucasian,07/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56162,64032,58105,Probation,GORDON,CHASADEE,I,Female,African-American,12/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.05,8,High,New,1,0 +56162,64032,58105,Probation,GORDON,CHASADEE,I,Female,African-American,12/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.17,7,Medium,New,1,0 +56162,64032,58105,Probation,GORDON,CHASADEE,I,Female,African-American,12/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56165,64035,58108,Probation,Plaisimond,Natasha,NULL,Female,African-American,06/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.53,3,Low,New,1,0 +56165,64035,58108,Probation,Plaisimond,Natasha,NULL,Female,African-American,06/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +56165,64035,58108,Probation,Plaisimond,Natasha,NULL,Female,African-American,06/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56181,64053,58125,Probation,DOMINICK,TERRELL,CHRISTOPHER,Male,Hispanic,09/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,4,High,7,Risk of Violence,-0.29,10,High,New,1,0 +56181,64053,58125,Probation,DOMINICK,TERRELL,CHRISTOPHER,Male,Hispanic,09/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,4,High,8,Risk of Recidivism,1,10,High,New,1,0 +56181,64053,58125,Probation,DOMINICK,TERRELL,CHRISTOPHER,Male,Hispanic,09/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/13 0:00,4,High,18,Risk of Failure to Appear,43,10,High,New,1,0 +56226,64103,58173,PRETRIAL,CLARK,WILLIE,A,Male,African-American,09/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +56226,64103,58173,PRETRIAL,CLARK,WILLIE,A,Male,African-American,09/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +56226,64103,58173,PRETRIAL,CLARK,WILLIE,A,Male,African-American,09/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56205,64082,58153,Probation,MUJICA,TERESITA,VICTORIA,Female,Hispanic,07/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +56205,64082,58153,Probation,MUJICA,TERESITA,VICTORIA,Female,Hispanic,07/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +56205,64082,58153,Probation,MUJICA,TERESITA,VICTORIA,Female,Hispanic,07/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56222,64100,58170,Probation,Passauer,Willard,fredrick,Male,Caucasian,02/27/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +56222,64100,58170,Probation,Passauer,Willard,fredrick,Male,Caucasian,02/27/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +56222,64100,58170,Probation,Passauer,Willard,fredrick,Male,Caucasian,02/27/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56188,64061,58132,PRETRIAL,ARMSTRONG,SHIQUEL,NULL,Male,African-American,10/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +56188,64061,58132,PRETRIAL,ARMSTRONG,SHIQUEL,NULL,Male,African-American,10/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +56188,64061,58132,PRETRIAL,ARMSTRONG,SHIQUEL,NULL,Male,African-American,10/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56216,64095,58165,Probation,Coats,Brandon,NULL,Male,Caucasian,01/31/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +56216,64095,58165,Probation,Coats,Brandon,NULL,Male,Caucasian,01/31/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +56216,64095,58165,Probation,Coats,Brandon,NULL,Male,Caucasian,01/31/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56197,64074,58145,PRETRIAL,Conklin,Michael,NULL,Male,Caucasian,04/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,2,Medium,7,Risk of Violence,-2.96,1,Low,New,1,0 +56197,64074,58145,PRETRIAL,Conklin,Michael,NULL,Male,Caucasian,04/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +56197,64074,58145,PRETRIAL,Conklin,Michael,NULL,Male,Caucasian,04/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +56202,64079,58150,Probation,Khalil,Mohammed,NULL,Male,Caucasian,11/06/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +56202,64079,58150,Probation,Khalil,Mohammed,NULL,Male,Caucasian,11/06/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +56202,64079,58150,Probation,Khalil,Mohammed,NULL,Male,Caucasian,11/06/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56192,64066,58137,PRETRIAL,Tiburcio,Luis,NULL,Male,Hispanic,04/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/6/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +56192,64066,58137,PRETRIAL,Tiburcio,Luis,NULL,Male,Hispanic,04/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +56192,64066,58137,PRETRIAL,Tiburcio,Luis,NULL,Male,Hispanic,04/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56209,64087,58157,Probation,ARCE,RICHARD,NULL,Male,Hispanic,05/16/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +56209,64087,58157,Probation,ARCE,RICHARD,NULL,Male,Hispanic,05/16/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +56209,64087,58157,Probation,ARCE,RICHARD,NULL,Male,Hispanic,05/16/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +25670,64072,58143,PRETRIAL,Navarr0,Joseph,NULL,Male,Caucasian,11/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.1,8,High,New,1,0 +25670,64072,58143,PRETRIAL,Navarr0,Joseph,NULL,Male,Caucasian,11/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +25670,64072,58143,PRETRIAL,Navarr0,Joseph,NULL,Male,Caucasian,11/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +56211,64089,58159,Probation,INGANAMONT,JUDITH,NULL,Female,Caucasian,02/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/6/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +56211,64089,58159,Probation,INGANAMONT,JUDITH,NULL,Female,Caucasian,02/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.62,2,Low,New,1,0 +56211,64089,58159,Probation,INGANAMONT,JUDITH,NULL,Female,Caucasian,02/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56190,64063,58134,PRETRIAL,BROWN,RONIE,WILLIE,Male,African-American,09/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +56190,64063,58134,PRETRIAL,BROWN,RONIE,WILLIE,Male,African-American,09/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +56190,64063,58134,PRETRIAL,BROWN,RONIE,WILLIE,Male,African-American,09/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56194,64068,58139,PRETRIAL,Mitchell,Andrew,Alexander,Male,African-American,10/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +56194,64068,58139,PRETRIAL,Mitchell,Andrew,Alexander,Male,African-American,10/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +56194,64068,58139,PRETRIAL,Mitchell,Andrew,Alexander,Male,African-American,10/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56214,64093,58163,Probation,Diaz,Richard,NULL,Male,Hispanic,04/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/6/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +56214,64093,58163,Probation,Diaz,Richard,NULL,Male,Hispanic,04/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +56214,64093,58163,Probation,Diaz,Richard,NULL,Male,Hispanic,04/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56200,64077,58148,PRETRIAL,etheridge,brian,NULL,Male,Caucasian,05/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,4,High,7,Risk of Violence,-0.67,9,High,New,1,0 +56200,64077,58148,PRETRIAL,etheridge,brian,NULL,Male,Caucasian,05/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,4,High,8,Risk of Recidivism,0.76,10,High,New,1,0 +56200,64077,58148,PRETRIAL,etheridge,brian,NULL,Male,Caucasian,05/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56206,64084,58154,Probation,Richardson,Jamee,NULL,Female,Caucasian,05/20/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +56206,64084,58154,Probation,Richardson,Jamee,NULL,Female,Caucasian,05/20/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +56206,64084,58154,Probation,Richardson,Jamee,NULL,Female,Caucasian,05/20/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56198,64075,58146,Probation,shaw,paulette,NULL,Female,Caucasian,09/09/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/6/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +56198,64075,58146,Probation,shaw,paulette,NULL,Female,Caucasian,09/09/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/6/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +56198,64075,58146,Probation,shaw,paulette,NULL,Female,Caucasian,09/09/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56219,64098,58168,PRETRIAL,Nettles,Roger,D,Male,Caucasian,12/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +56219,64098,58168,PRETRIAL,Nettles,Roger,D,Male,Caucasian,12/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +56219,64098,58168,PRETRIAL,Nettles,Roger,D,Male,Caucasian,12/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +3105,64065,58136,PRETRIAL,HARVARD,DEONTA,RAY,Male,African-American,03/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +3105,64065,58136,PRETRIAL,HARVARD,DEONTA,RAY,Male,African-American,03/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +3105,64065,58136,PRETRIAL,HARVARD,DEONTA,RAY,Male,African-American,03/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +56203,64080,58151,Probation,Garcia,Rueben,NULL,Male,Hispanic,11/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +56203,64080,58151,Probation,Garcia,Rueben,NULL,Male,Hispanic,11/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +56203,64080,58151,Probation,Garcia,Rueben,NULL,Male,Hispanic,11/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56215,64094,58164,PRETRIAL,Alcover,Guillermo,NULL,Male,Caucasian,01/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/6/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +56215,64094,58164,PRETRIAL,Alcover,Guillermo,NULL,Male,Caucasian,01/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +56215,64094,58164,PRETRIAL,Alcover,Guillermo,NULL,Male,Caucasian,01/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/6/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +56223,64101,58171,Probation,Weissbein,Jason,NULL,Male,Caucasian,05/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +56223,64101,58171,Probation,Weissbein,Jason,NULL,Male,Caucasian,05/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +56223,64101,58171,Probation,Weissbein,Jason,NULL,Male,Caucasian,05/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +12180,64073,58144,PRETRIAL,MORALES,JUAN,NULL,Male,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +12180,64073,58144,PRETRIAL,MORALES,JUAN,NULL,Male,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,4,High,8,Risk of Recidivism,0.37,9,High,New,1,0 +12180,64073,58144,PRETRIAL,MORALES,JUAN,NULL,Male,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56208,64086,58156,Probation,Morales,Christopher,NULL,Male,Hispanic,08/22/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +56208,64086,58156,Probation,Morales,Christopher,NULL,Male,Hispanic,08/22/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +56208,64086,58156,Probation,Morales,Christopher,NULL,Male,Hispanic,08/22/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56210,64088,58158,Probation,Francois,Jacky,NULL,Male,African-American,03/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/6/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +56210,64088,58158,Probation,Francois,Jacky,NULL,Male,African-American,03/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +56210,64088,58158,Probation,Francois,Jacky,NULL,Male,African-American,03/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56220,64099,58169,Probation,Stirk,Andrew,NULL,Male,Caucasian,05/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/6/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +56220,64099,58169,Probation,Stirk,Andrew,NULL,Male,Caucasian,05/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/6/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +56220,64099,58169,Probation,Stirk,Andrew,NULL,Male,Caucasian,05/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56201,64078,58149,Probation,GALLARDO,JULIE,NULL,Female,Caucasian,12/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/6/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +56201,64078,58149,Probation,GALLARDO,JULIE,NULL,Female,Caucasian,12/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +56201,64078,58149,Probation,GALLARDO,JULIE,NULL,Female,Caucasian,12/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56212,64091,58161,Probation,McMahon,Sean,Michael,Male,Caucasian,10/13/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/6/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +56212,64091,58161,Probation,McMahon,Sean,Michael,Male,Caucasian,10/13/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/6/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +56212,64091,58161,Probation,McMahon,Sean,Michael,Male,Caucasian,10/13/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56195,64070,58141,PRETRIAL,NICOLAS,NIKENSON,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +56195,64070,58141,PRETRIAL,NICOLAS,NIKENSON,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +56195,64070,58141,PRETRIAL,NICOLAS,NIKENSON,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55877,64083,57790,PRETRIAL,MARCHESSAULT,JAMIE,NULL,Male,Caucasian,02/11/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,Copy,1,0 +55877,64083,57790,PRETRIAL,MARCHESSAULT,JAMIE,NULL,Male,Caucasian,02/11/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,Copy,1,0 +55877,64083,57790,PRETRIAL,MARCHESSAULT,JAMIE,NULL,Male,Caucasian,02/11/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +56218,64097,58167,PRETRIAL,Williams,Tevin,Dave,Male,African-American,08/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +56218,64097,58167,PRETRIAL,Williams,Tevin,Dave,Male,African-American,08/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +56218,64097,58167,PRETRIAL,Williams,Tevin,Dave,Male,African-American,08/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56189,64062,58133,PRETRIAL,bowen,kenyatta,NULL,Male,African-American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +56189,64062,58133,PRETRIAL,bowen,kenyatta,NULL,Male,African-American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +56189,64062,58133,PRETRIAL,bowen,kenyatta,NULL,Male,African-American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50353,64069,58140,PRETRIAL,Holloway,Alicia,NULL,Female,African-American,03/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/13 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +50353,64069,58140,PRETRIAL,Holloway,Alicia,NULL,Female,African-American,03/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/13 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +50353,64069,58140,PRETRIAL,Holloway,Alicia,NULL,Female,African-American,03/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56199,64076,58147,Probation,carter,isiah,NULL,Male,African-American,04/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +56199,64076,58147,Probation,carter,isiah,NULL,Male,African-American,04/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +56199,64076,58147,Probation,carter,isiah,NULL,Male,African-American,04/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +13459,64090,58160,DRRD,Scott,Lauren,NULL,Female,African-American,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,4,High,7,Risk of Violence,-0.95,9,High,New,1,0 +13459,64090,58160,DRRD,Scott,Lauren,NULL,Female,African-American,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +13459,64090,58160,DRRD,Scott,Lauren,NULL,Female,African-American,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +56213,64092,58162,PRETRIAL,Oconnell,Kevin,NULL,Male,Caucasian,07/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +56213,64092,58162,PRETRIAL,Oconnell,Kevin,NULL,Male,Caucasian,07/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +56213,64092,58162,PRETRIAL,Oconnell,Kevin,NULL,Male,Caucasian,07/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +56224,64102,58172,Probation,Serra,John,NULL,Male,Hispanic,11/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +56224,64102,58172,Probation,Serra,John,NULL,Male,Hispanic,11/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +56224,64102,58172,Probation,Serra,John,NULL,Male,Hispanic,11/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +5052,64060,4733,PRETRIAL,WEST,MICHAEL,NULL,Male,African-American,11/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,Copy,1,0 +5052,64060,4733,PRETRIAL,WEST,MICHAEL,NULL,Male,African-American,11/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,Copy,1,0 +5052,64060,4733,PRETRIAL,WEST,MICHAEL,NULL,Male,African-American,11/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +56196,64071,58142,PRETRIAL,TANKSLEY,ALPHONSO,LEE,Male,African-American,07/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +56196,64071,58142,PRETRIAL,TANKSLEY,ALPHONSO,LEE,Male,African-American,07/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +56196,64071,58142,PRETRIAL,TANKSLEY,ALPHONSO,LEE,Male,African-American,07/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56207,64085,58155,PRETRIAL,Yopp,Bryant,F,Male,African-American,06/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +56207,64085,58155,PRETRIAL,Yopp,Bryant,F,Male,African-American,06/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +56207,64085,58155,PRETRIAL,Yopp,Bryant,F,Male,African-American,06/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56191,64064,58135,PRETRIAL,MEZA,APOLINAR,DOMINQUEZ,Male,Caucasian,07/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +56191,64064,58135,PRETRIAL,MEZA,APOLINAR,DOMINQUEZ,Male,Caucasian,07/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +56191,64064,58135,PRETRIAL,MEZA,APOLINAR,DOMINQUEZ,Male,Caucasian,07/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56193,64067,58138,PRETRIAL,Joseph,Daniel,NULL,Male,African-American,09/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,2,Medium,7,Risk of Violence,-2.52,3,Low,New,1,0 +56193,64067,58138,PRETRIAL,Joseph,Daniel,NULL,Male,African-American,09/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +56193,64067,58138,PRETRIAL,Joseph,Daniel,NULL,Male,African-American,09/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56204,64081,58152,PRETRIAL,Cadet,Terry,NULL,Male,African-American,09/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +56204,64081,58152,PRETRIAL,Cadet,Terry,NULL,Male,African-American,09/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +56204,64081,58152,PRETRIAL,Cadet,Terry,NULL,Male,African-American,09/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56254,64132,58199,PRETRIAL,Mann,Jeffery,NULL,Male,Caucasian,11/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +56254,64132,58199,PRETRIAL,Mann,Jeffery,NULL,Male,Caucasian,11/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +56254,64132,58199,PRETRIAL,Mann,Jeffery,NULL,Male,Caucasian,11/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56249,64127,58194,Probation,CLARK,ERIC,C,Male,Caucasian,02/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +56249,64127,58194,Probation,CLARK,ERIC,C,Male,Caucasian,02/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +56249,64127,58194,Probation,CLARK,ERIC,C,Male,Caucasian,02/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56256,64136,58201,PRETRIAL,Spurgin,Brian,James,Male,African-American,05/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +56256,64136,58201,PRETRIAL,Spurgin,Brian,James,Male,African-American,05/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +56256,64136,58201,PRETRIAL,Spurgin,Brian,James,Male,African-American,05/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56229,64106,58176,PRETRIAL,PIERCE,JOEY,R,Male,Caucasian,06/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,4,High,7,Risk of Violence,-0.42,10,High,New,1,0 +56229,64106,58176,PRETRIAL,PIERCE,JOEY,R,Male,Caucasian,06/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,4,High,8,Risk of Recidivism,0.73,10,High,New,1,0 +56229,64106,58176,PRETRIAL,PIERCE,JOEY,R,Male,Caucasian,06/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56246,64123,58190,PRETRIAL,Bowden,Deondre,NULL,Male,African-American,12/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +56246,64123,58190,PRETRIAL,Bowden,Deondre,NULL,Male,African-American,12/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +56246,64123,58190,PRETRIAL,Bowden,Deondre,NULL,Male,African-American,12/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +48714,64139,58204,PRETRIAL,Harnick,Gregory,NULL,Male,Caucasian,04/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +48714,64139,58204,PRETRIAL,Harnick,Gregory,NULL,Male,Caucasian,04/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +48714,64139,58204,PRETRIAL,Harnick,Gregory,NULL,Male,Caucasian,04/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49098,64141,58206,PRETRIAL,Griswell,Jerome,NULL,Male,African-American,09/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,2,Medium,7,Risk of Violence,-2.89,2,Low,New,1,0 +49098,64141,58206,PRETRIAL,Griswell,Jerome,NULL,Male,African-American,09/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +49098,64141,58206,PRETRIAL,Griswell,Jerome,NULL,Male,African-American,09/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56231,64111,58178,PRETRIAL,Williams,Corey,Anthony,Male,African-American,01/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +56231,64111,58178,PRETRIAL,Williams,Corey,Anthony,Male,African-American,01/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +56231,64111,58178,PRETRIAL,Williams,Corey,Anthony,Male,African-American,01/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56233,64113,58180,PRETRIAL,BUTLER,MARVIN,L,Male,African-American,12/30/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +56233,64113,58180,PRETRIAL,BUTLER,MARVIN,L,Male,African-American,12/30/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +56233,64113,58180,PRETRIAL,BUTLER,MARVIN,L,Male,African-American,12/30/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53904,64118,58185,PRETRIAL,Herrera,Justin,NULL,Male,Hispanic,08/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.91,9,High,New,1,0 +53904,64118,58185,PRETRIAL,Herrera,Justin,NULL,Male,Hispanic,08/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +53904,64118,58185,PRETRIAL,Herrera,Justin,NULL,Male,Hispanic,08/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56244,64120,58187,PRETRIAL,HOWARD,MONIQUE,COFFEY,Female,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +56244,64120,58187,PRETRIAL,HOWARD,MONIQUE,COFFEY,Female,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +56244,64120,58187,PRETRIAL,HOWARD,MONIQUE,COFFEY,Female,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56227,64104,58174,PRETRIAL,Louis,Eugenery,NULL,Male,African-American,12/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +56227,64104,58174,PRETRIAL,Louis,Eugenery,NULL,Male,African-American,12/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.63,10,High,New,1,0 +56227,64104,58174,PRETRIAL,Louis,Eugenery,NULL,Male,African-American,12/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56258,64138,58203,PRETRIAL,BENNETT,SAMUEL,NULL,Male,African-American,01/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +56258,64138,58203,PRETRIAL,BENNETT,SAMUEL,NULL,Male,African-American,01/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +56258,64138,58203,PRETRIAL,BENNETT,SAMUEL,NULL,Male,African-American,01/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56247,64125,58192,PRETRIAL,rose,frank,NULL,Male,Caucasian,07/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +56247,64125,58192,PRETRIAL,rose,frank,NULL,Male,Caucasian,07/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +56247,64125,58192,PRETRIAL,rose,frank,NULL,Male,Caucasian,07/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56264,64146,58211,PRETRIAL,Byczkowski,Juliana,NULL,Female,Hispanic,03/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +56264,64146,58211,PRETRIAL,Byczkowski,Juliana,NULL,Female,Hispanic,03/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +56264,64146,58211,PRETRIAL,Byczkowski,Juliana,NULL,Female,Hispanic,03/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56242,64117,58184,PRETRIAL,Espino,Ricauter,NULL,Male,African-American,05/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +56242,64117,58184,PRETRIAL,Espino,Ricauter,NULL,Male,African-American,05/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +56242,64117,58184,PRETRIAL,Espino,Ricauter,NULL,Male,African-American,05/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56261,64143,58208,Probation,ehrlich,thomas,justin,Male,Caucasian,02/12/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/7/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +56261,64143,58208,Probation,ehrlich,thomas,justin,Male,Caucasian,02/12/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/7/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +56261,64143,58208,Probation,ehrlich,thomas,justin,Male,Caucasian,02/12/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +1851,64107,1550,PRETRIAL,SMITH,DAVIE,JERMAIN,Male,African-American,05/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +1851,64107,1550,PRETRIAL,SMITH,DAVIE,JERMAIN,Male,African-American,05/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,Copy,1,0 +1851,64107,1550,PRETRIAL,SMITH,DAVIE,JERMAIN,Male,African-American,05/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +16872,64109,16182,PRETRIAL,KAVALIOU,VITALI,NULL,Female,Caucasian,04/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,Copy,1,0 +16872,64109,16182,PRETRIAL,KAVALIOU,VITALI,NULL,Female,Caucasian,04/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,Copy,1,0 +16872,64109,16182,PRETRIAL,KAVALIOU,VITALI,NULL,Female,Caucasian,04/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +56245,64122,58189,PRETRIAL,Smith,Beverly,NULL,Female,African-American,10/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.37,1,Low,New,1,0 +56245,64122,58189,PRETRIAL,Smith,Beverly,NULL,Female,African-American,10/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +56245,64122,58189,PRETRIAL,Smith,Beverly,NULL,Female,African-American,10/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +2223,64115,58182,PRETRIAL,BARNES,ANTONIO,NULL,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +2223,64115,58182,PRETRIAL,BARNES,ANTONIO,NULL,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +2223,64115,58182,PRETRIAL,BARNES,ANTONIO,NULL,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56252,64130,58197,PRETRIAL,CLARK,JOHNNIE,NULL,Male,African-American,09/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +56252,64130,58197,PRETRIAL,CLARK,JOHNNIE,NULL,Male,African-American,09/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +56252,64130,58197,PRETRIAL,CLARK,JOHNNIE,NULL,Male,African-American,09/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56255,64133,58200,PRETRIAL,Hamilton,Frank,N,Male,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +56255,64133,58200,PRETRIAL,Hamilton,Frank,N,Male,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +56255,64133,58200,PRETRIAL,Hamilton,Frank,N,Male,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +49241,64147,50053,Probation,Arbelaez,Claudia,Cristina,Female,Hispanic,02/09/77,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,8/7/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +49241,64147,50053,Probation,Arbelaez,Claudia,Cristina,Female,Hispanic,02/09/77,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,8/7/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +49241,64147,50053,Probation,Arbelaez,Claudia,Cristina,Female,Hispanic,02/09/77,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +56232,64112,58179,PRETRIAL,McCants,Eddie,L,Male,African-American,12/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +56232,64112,58179,PRETRIAL,McCants,Eddie,L,Male,African-American,12/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +56232,64112,58179,PRETRIAL,McCants,Eddie,L,Male,African-American,12/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56243,64119,58186,PRETRIAL,LUIS,MARIO,H,Male,Hispanic,04/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/7/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +56243,64119,58186,PRETRIAL,LUIS,MARIO,H,Male,Hispanic,04/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/7/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +56243,64119,58186,PRETRIAL,LUIS,MARIO,H,Male,Hispanic,04/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56248,64126,58193,Probation,Luzbel,Frank,NULL,Male,Hispanic,06/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +56248,64126,58193,Probation,Luzbel,Frank,NULL,Male,Hispanic,06/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +56248,64126,58193,Probation,Luzbel,Frank,NULL,Male,Hispanic,06/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56228,64105,58175,PRETRIAL,Prevelhomme,Lance,NULL,Male,African-American,01/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.1,8,High,New,1,0 +56228,64105,58175,PRETRIAL,Prevelhomme,Lance,NULL,Male,African-American,01/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +56228,64105,58175,PRETRIAL,Prevelhomme,Lance,NULL,Male,African-American,01/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56259,64140,58205,Probation,Casseus,Pierre,NULL,Male,African-American,08/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +56259,64140,58205,Probation,Casseus,Pierre,NULL,Male,African-American,08/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +56259,64140,58205,Probation,Casseus,Pierre,NULL,Male,African-American,08/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +33757,64110,32863,PRETRIAL,blount,anthony,NULL,Male,African-American,08/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +33757,64110,32863,PRETRIAL,blount,anthony,NULL,Male,African-American,08/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,Copy,1,0 +33757,64110,32863,PRETRIAL,blount,anthony,NULL,Male,African-American,08/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +56250,64128,58195,Probation,Ortiz,Xocchitl,NULL,Female,Hispanic,04/04/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +56250,64128,58195,Probation,Ortiz,Xocchitl,NULL,Female,Hispanic,04/04/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +56250,64128,58195,Probation,Ortiz,Xocchitl,NULL,Female,Hispanic,04/04/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53105,64135,55265,Probation,fowks,kurt,NULL,Male,Caucasian,02/11/90,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +53105,64135,55265,Probation,fowks,kurt,NULL,Male,Caucasian,02/11/90,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +53105,64135,55265,Probation,fowks,kurt,NULL,Male,Caucasian,02/11/90,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,4,High,18,Risk of Failure to Appear,16,1,Low,New,1,0 +4973,64114,58181,Probation,Whittaker,Ryan,NULL,Male,Other,10/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +4973,64114,58181,Probation,Whittaker,Ryan,NULL,Male,Other,10/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +4973,64114,58181,Probation,Whittaker,Ryan,NULL,Male,Other,10/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56253,64131,58198,Probation,Correa,Jose,NULL,Male,Hispanic,05/21/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.96,5,Medium,New,1,0 +56253,64131,58198,Probation,Correa,Jose,NULL,Male,Hispanic,05/21/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +56253,64131,58198,Probation,Correa,Jose,NULL,Male,Hispanic,05/21/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56257,64137,58202,PRETRIAL,HENLEY,BILLY,RAY,Male,African-American,02/24/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/7/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +56257,64137,58202,PRETRIAL,HENLEY,BILLY,RAY,Male,African-American,02/24/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/7/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +56257,64137,58202,PRETRIAL,HENLEY,BILLY,RAY,Male,African-American,02/24/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56262,64144,58209,Broward County,Rosario,Johnathon,NULL,Male,Hispanic,01/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +56262,64144,58209,Broward County,Rosario,Johnathon,NULL,Male,Hispanic,01/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +56262,64144,58209,Broward County,Rosario,Johnathon,NULL,Male,Hispanic,01/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56241,64116,58183,PRETRIAL,Palen,Alexis,NULL,Male,Caucasian,02/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +56241,64116,58183,PRETRIAL,Palen,Alexis,NULL,Male,Caucasian,02/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +56241,64116,58183,PRETRIAL,Palen,Alexis,NULL,Male,Caucasian,02/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56263,64145,58210,PRETRIAL,Grimes,Carly,NULL,Female,Caucasian,01/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +56263,64145,58210,PRETRIAL,Grimes,Carly,NULL,Female,Caucasian,01/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +56263,64145,58210,PRETRIAL,Grimes,Carly,NULL,Female,Caucasian,01/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50524,64124,58191,PRETRIAL,Thomas,Chauncy,NULL,Male,African-American,08/11/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +50524,64124,58191,PRETRIAL,Thomas,Chauncy,NULL,Male,African-American,08/11/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +50524,64124,58191,PRETRIAL,Thomas,Chauncy,NULL,Male,African-American,08/11/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56230,64108,58177,PRETRIAL,Perry,Aubrey,NULL,Male,African-American,05/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +56230,64108,58177,PRETRIAL,Perry,Aubrey,NULL,Male,African-American,05/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +56230,64108,58177,PRETRIAL,Perry,Aubrey,NULL,Male,African-American,05/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56260,64142,58207,Probation,GIANCOLA,DANIEL,NULL,Male,Hispanic,06/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +56260,64142,58207,Probation,GIANCOLA,DANIEL,NULL,Male,Hispanic,06/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +56260,64142,58207,Probation,GIANCOLA,DANIEL,NULL,Male,Hispanic,06/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56251,64129,58196,PRETRIAL,Whitaker,Alexander,NULL,Male,Caucasian,08/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +56251,64129,58196,PRETRIAL,Whitaker,Alexander,NULL,Male,Caucasian,08/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +56251,64129,58196,PRETRIAL,Whitaker,Alexander,NULL,Male,Caucasian,08/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +24573,64121,58188,DRRD,Hadden,Keric,Justin,Male,African-American,08/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.16,8,High,New,1,0 +24573,64121,58188,DRRD,Hadden,Keric,Justin,Male,African-American,08/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +24573,64121,58188,DRRD,Hadden,Keric,Justin,Male,African-American,08/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56273,64160,58222,PRETRIAL,Cabrices,Raphael,NULL,Male,Caucasian,04/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/8/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +56273,64160,58222,PRETRIAL,Cabrices,Raphael,NULL,Male,Caucasian,04/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/8/13 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +56273,64160,58222,PRETRIAL,Cabrices,Raphael,NULL,Male,Caucasian,04/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +47292,64171,58231,PRETRIAL,SENKBEIL,JESSICA,NULL,Female,Caucasian,05/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +47292,64171,58231,PRETRIAL,SENKBEIL,JESSICA,NULL,Female,Caucasian,05/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.61,2,Low,New,1,0 +47292,64171,58231,PRETRIAL,SENKBEIL,JESSICA,NULL,Female,Caucasian,05/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54165,64150,55735,PRETRIAL,MCGIRT,DERICKY,NULL,Male,African-American,09/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,4,High,7,Risk of Violence,-1,8,High,Copy,1,0 +54165,64150,55735,PRETRIAL,MCGIRT,DERICKY,NULL,Male,African-American,09/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,4,High,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +54165,64150,55735,PRETRIAL,MCGIRT,DERICKY,NULL,Male,African-American,09/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +56291,64181,58240,Probation,laurenfant,cindy,NULL,Female,African-American,01/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +56291,64181,58240,Probation,laurenfant,cindy,NULL,Female,African-American,01/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +56291,64181,58240,Probation,laurenfant,cindy,NULL,Female,African-American,01/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56278,64163,58225,PRETRIAL,Johnson,Deshaud,NULL,Male,African-American,12/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +56278,64163,58225,PRETRIAL,Johnson,Deshaud,NULL,Male,African-American,12/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +56278,64163,58225,PRETRIAL,Johnson,Deshaud,NULL,Male,African-American,12/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56282,64168,58229,Probation,nascimento,MICHAEL,NULL,Male,Hispanic,05/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +56282,64168,58229,Probation,nascimento,MICHAEL,NULL,Male,Hispanic,05/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +56282,64168,58229,Probation,nascimento,MICHAEL,NULL,Male,Hispanic,05/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56270,64155,58217,Probation,RODRIQUEZ,LUIS,NULL,Male,Hispanic,08/30/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +56270,64155,58217,Probation,RODRIQUEZ,LUIS,NULL,Male,Hispanic,08/30/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +56270,64155,58217,Probation,RODRIQUEZ,LUIS,NULL,Male,Hispanic,08/30/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56274,64158,58220,Probation,Rodriguez,Jordan,NULL,Male,Hispanic,05/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/8/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +56274,64158,58220,Probation,Rodriguez,Jordan,NULL,Male,Hispanic,05/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/8/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +56274,64158,58220,Probation,Rodriguez,Jordan,NULL,Male,Hispanic,05/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56285,64173,58233,Probation,Delossantos,Sabino,NULL,Male,Hispanic,01/06/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +56285,64173,58233,Probation,Delossantos,Sabino,NULL,Male,Hispanic,01/06/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +56285,64173,58233,Probation,Delossantos,Sabino,NULL,Male,Hispanic,01/06/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56269,64152,58215,PRETRIAL,Davis,Bruce,NULL,Male,African-American,02/06/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +56269,64152,58215,PRETRIAL,Davis,Bruce,NULL,Male,African-American,02/06/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +56269,64152,58215,PRETRIAL,Davis,Bruce,NULL,Male,African-American,02/06/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56125,64179,58062,PRETRIAL,Davis,Braxton,NULL,Male,African-American,11/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,Copy,1,0 +56125,64179,58062,PRETRIAL,Davis,Braxton,NULL,Male,African-American,11/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,Copy,1,0 +56125,64179,58062,PRETRIAL,Davis,Braxton,NULL,Male,African-American,11/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +56295,64186,58245,PRETRIAL,WILBORN,DARIUS,NULL,Male,African-American,12/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/8/13 0:00,2,Medium,7,Risk of Violence,-2.88,2,Low,New,1,0 +56295,64186,58245,PRETRIAL,WILBORN,DARIUS,NULL,Male,African-American,12/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +56295,64186,58245,PRETRIAL,WILBORN,DARIUS,NULL,Male,African-American,12/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/8/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56280,64166,58227,Probation,Kaiser,Richard,Alan,Male,Caucasian,10/21/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/8/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +56280,64166,58227,Probation,Kaiser,Richard,Alan,Male,Caucasian,10/21/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +56280,64166,58227,Probation,Kaiser,Richard,Alan,Male,Caucasian,10/21/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56267,64149,58213,PRETRIAL,PRATER,VERNON,NULL,Male,Caucasian,03/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +56267,64149,58213,PRETRIAL,PRATER,VERNON,NULL,Male,Caucasian,03/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +56267,64149,58213,PRETRIAL,PRATER,VERNON,NULL,Male,Caucasian,03/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56292,64182,58241,Probation,Salgado,Samantha,NULL,Female,African-American,02/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/8/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +56292,64182,58241,Probation,Salgado,Samantha,NULL,Female,African-American,02/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/8/13 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +56292,64182,58241,Probation,Salgado,Samantha,NULL,Female,African-American,02/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56276,64161,58223,Probation,reano,roberto,NULL,Male,Hispanic,11/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/8/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +56276,64161,58223,Probation,reano,roberto,NULL,Male,Hispanic,11/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +56276,64161,58223,Probation,reano,roberto,NULL,Male,Hispanic,11/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56271,64156,58218,Probation,Jean Gilles,Jean,NULL,Male,African-American,11/23/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +56271,64156,58218,Probation,Jean Gilles,Jean,NULL,Male,African-American,11/23/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +56271,64156,58218,Probation,Jean Gilles,Jean,NULL,Male,African-American,11/23/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56287,64175,58235,Probation,Calico,Chadwick,NULL,Male,Caucasian,07/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +56287,64175,58235,Probation,Calico,Chadwick,NULL,Male,Caucasian,07/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +56287,64175,58235,Probation,Calico,Chadwick,NULL,Male,Caucasian,07/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56289,64177,58237,Probation,Odea,Patrick,NULL,Male,Caucasian,10/26/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +56289,64177,58237,Probation,Odea,Patrick,NULL,Male,Caucasian,10/26/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +56289,64177,58237,Probation,Odea,Patrick,NULL,Male,Caucasian,10/26/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56294,64184,58243,Probation,Santiago,Christian,Santiago,Male,Hispanic,06/19/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/8/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +56294,64184,58243,Probation,Santiago,Christian,Santiago,Male,Hispanic,06/19/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +56294,64184,58243,Probation,Santiago,Christian,Santiago,Male,Hispanic,06/19/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56268,64151,58214,PRETRIAL,McDougle,Terrance,Laquelle,Male,African-American,03/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +56268,64151,58214,PRETRIAL,McDougle,Terrance,Laquelle,Male,African-American,03/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +56268,64151,58214,PRETRIAL,McDougle,Terrance,Laquelle,Male,African-American,03/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56290,64180,58239,DRRD,Sanchez,Jessica,NULL,Female,Hispanic,05/04/90,17,All Scales,Intake,English,Pretrial,Probation,Single,8/8/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +56290,64180,58239,DRRD,Sanchez,Jessica,NULL,Female,Hispanic,05/04/90,17,All Scales,Intake,English,Pretrial,Probation,Single,8/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +56290,64180,58239,DRRD,Sanchez,Jessica,NULL,Female,Hispanic,05/04/90,17,All Scales,Intake,English,Pretrial,Probation,Single,8/8/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56279,64164,58226,PRETRIAL,ORIORDEN,GAEL,NULL,Male,Caucasian,09/24/32,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/8/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +56279,64164,58226,PRETRIAL,ORIORDEN,GAEL,NULL,Male,Caucasian,09/24/32,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/8/13 0:00,1,Low,8,Risk of Recidivism,-2.56,1,Low,New,1,0 +56279,64164,58226,PRETRIAL,ORIORDEN,GAEL,NULL,Male,Caucasian,09/24/32,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56281,64167,58228,PRETRIAL,Stoner,Scott,NULL,Male,Caucasian,08/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +56281,64167,58228,PRETRIAL,Stoner,Scott,NULL,Male,Caucasian,08/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +56281,64167,58228,PRETRIAL,Stoner,Scott,NULL,Male,Caucasian,08/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +27034,64185,58244,Probation,Moratz,Yolani,NULL,Female,Caucasian,11/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/13 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +27034,64185,58244,Probation,Moratz,Yolani,NULL,Female,Caucasian,11/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +27034,64185,58244,Probation,Moratz,Yolani,NULL,Female,Caucasian,11/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56284,64172,58232,Probation,Gonzalez,Edwardo,NULL,Male,Hispanic,09/20/63,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/8/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +56284,64172,58232,Probation,Gonzalez,Edwardo,NULL,Male,Hispanic,09/20/63,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +56284,64172,58232,Probation,Gonzalez,Edwardo,NULL,Male,Hispanic,09/20/63,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56277,64162,58224,PRETRIAL,Nunez,Angel,NULL,Male,Hispanic,10/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +56277,64162,58224,PRETRIAL,Nunez,Angel,NULL,Male,Hispanic,10/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.76,10,High,New,1,0 +56277,64162,58224,PRETRIAL,Nunez,Angel,NULL,Male,Hispanic,10/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +56283,64169,58230,Probation,Lanter,David,NULL,Male,Caucasian,08/11/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/8/13 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +56283,64169,58230,Probation,Lanter,David,NULL,Male,Caucasian,08/11/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/8/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +56283,64169,58230,Probation,Lanter,David,NULL,Male,Caucasian,08/11/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56288,64176,58236,Probation,marxmeyer,bryan,NULL,Male,Caucasian,03/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/8/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +56288,64176,58236,Probation,marxmeyer,bryan,NULL,Male,Caucasian,03/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +56288,64176,58236,Probation,marxmeyer,bryan,NULL,Male,Caucasian,03/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56266,64148,58212,PRETRIAL,Ure,Macauley,Harrison,Male,Caucasian,10/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +56266,64148,58212,PRETRIAL,Ure,Macauley,Harrison,Male,Caucasian,10/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +56266,64148,58212,PRETRIAL,Ure,Macauley,Harrison,Male,Caucasian,10/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56293,64183,58242,Probation,thermidor,fernando,NULL,Male,African-American,11/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +56293,64183,58242,Probation,thermidor,fernando,NULL,Male,African-American,11/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +56293,64183,58242,Probation,thermidor,fernando,NULL,Male,African-American,11/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56272,64157,58219,PRETRIAL,Germaine,Carline,NULL,Female,African-American,03/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/8/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +56272,64157,58219,PRETRIAL,Germaine,Carline,NULL,Female,African-American,03/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +56272,64157,58219,PRETRIAL,Germaine,Carline,NULL,Female,African-American,03/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56286,64174,58234,Probation,arroyo,rojelio,NULL,Male,Hispanic,06/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +56286,64174,58234,Probation,arroyo,rojelio,NULL,Male,Hispanic,06/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +56286,64174,58234,Probation,arroyo,rojelio,NULL,Male,Hispanic,06/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47851,64153,58216,PRETRIAL,Boyd,Jordan,NULL,Male,African-American,01/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +47851,64153,58216,PRETRIAL,Boyd,Jordan,NULL,Male,African-American,01/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +47851,64153,58216,PRETRIAL,Boyd,Jordan,NULL,Male,African-American,01/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +23473,64178,58238,Probation,howlett,edson,NULL,Male,Caucasian,11/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +23473,64178,58238,Probation,howlett,edson,NULL,Male,Caucasian,11/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +23473,64178,58238,Probation,howlett,edson,NULL,Male,Caucasian,11/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +45111,64199,58256,PRETRIAL,Harrison,Chaddie,NULL,Male,African-American,04/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/9/13 0:00,2,Medium,7,Risk of Violence,-2.82,2,Low,New,1,0 +45111,64199,58256,PRETRIAL,Harrison,Chaddie,NULL,Male,African-American,04/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +45111,64199,58256,PRETRIAL,Harrison,Chaddie,NULL,Male,African-American,04/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/9/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56309,64208,58264,PRETRIAL,SYLVAIN,DANTAE,PRINCE,Male,African-American,06/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.11,8,High,New,1,0 +56309,64208,58264,PRETRIAL,SYLVAIN,DANTAE,PRINCE,Male,African-American,06/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +56309,64208,58264,PRETRIAL,SYLVAIN,DANTAE,PRINCE,Male,African-American,06/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56301,64195,58253,PRETRIAL,Glen,Leon,Alphonso,Male,African-American,01/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/9/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +56301,64195,58253,PRETRIAL,Glen,Leon,Alphonso,Male,African-American,01/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/9/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +56301,64195,58253,PRETRIAL,Glen,Leon,Alphonso,Male,African-American,01/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51716,64204,58260,PRETRIAL,Harcum,Bria,NULL,Female,African-American,06/19/92,17,All Scales,Intake,English,Other,Probation,Single,8/9/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +51716,64204,58260,PRETRIAL,Harcum,Bria,NULL,Female,African-American,06/19/92,17,All Scales,Intake,English,Other,Probation,Single,8/9/13 0:00,1,Low,8,Risk of Recidivism,-0.77,4,Low,New,1,0 +51716,64204,58260,PRETRIAL,Harcum,Bria,NULL,Female,African-American,06/19/92,17,All Scales,Intake,English,Other,Probation,Single,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +50127,64197,55770,PRETRIAL,Nunnery,kevin,NULL,Male,African-American,01/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,Copy,1,0 +50127,64197,55770,PRETRIAL,Nunnery,kevin,NULL,Male,African-American,01/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,Copy,1,0 +50127,64197,55770,PRETRIAL,Nunnery,kevin,NULL,Male,African-American,01/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +56312,64211,58267,Probation,Feigin,Corey,Ethan,Male,Caucasian,05/28/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/9/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +56312,64211,58267,Probation,Feigin,Corey,Ethan,Male,Caucasian,05/28/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/9/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +56312,64211,58267,Probation,Feigin,Corey,Ethan,Male,Caucasian,05/28/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +43553,64213,43522,PRETRIAL,Edmond,Jean,Junior,Male,African-American,02/28/82,17,All Scales,Intake,English,Post Sentence,Probation,Significant Other,8/9/13 0:00,4,High,7,Risk of Violence,-0.9,9,High,Copy,1,0 +43553,64213,43522,PRETRIAL,Edmond,Jean,Junior,Male,African-American,02/28/82,17,All Scales,Intake,English,Post Sentence,Probation,Significant Other,8/9/13 0:00,4,High,8,Risk of Recidivism,1.17,10,High,Copy,1,0 +43553,64213,43522,PRETRIAL,Edmond,Jean,Junior,Male,African-American,02/28/82,17,All Scales,Intake,English,Post Sentence,Probation,Significant Other,8/9/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +37741,64218,58273,PRETRIAL,Basile,Michael,NULL,Male,Caucasian,11/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +37741,64218,58273,PRETRIAL,Basile,Michael,NULL,Male,Caucasian,11/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +37741,64218,58273,PRETRIAL,Basile,Michael,NULL,Male,Caucasian,11/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56298,64190,58248,PRETRIAL,Durand,Nicanor,NULL,Male,Caucasian,09/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +56298,64190,58248,PRETRIAL,Durand,Nicanor,NULL,Male,Caucasian,09/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +56298,64190,58248,PRETRIAL,Durand,Nicanor,NULL,Male,Caucasian,09/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56300,64192,58250,PRETRIAL,McBurrows,Zachery,Bernard,Male,African-American,04/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +56300,64192,58250,PRETRIAL,McBurrows,Zachery,Bernard,Male,African-American,04/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +56300,64192,58250,PRETRIAL,McBurrows,Zachery,Bernard,Male,African-American,04/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56307,64206,58262,Probation,Hasan,Rayad,NULL,Male,Arabic,06/16/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +56307,64206,58262,Probation,Hasan,Rayad,NULL,Male,Arabic,06/16/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +56307,64206,58262,Probation,Hasan,Rayad,NULL,Male,Arabic,06/16/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56314,64214,58269,Probation,Sims,Bobby,Lee,Male,African-American,08/28/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/9/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +56314,64214,58269,Probation,Sims,Bobby,Lee,Male,African-American,08/28/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/9/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +56314,64214,58269,Probation,Sims,Bobby,Lee,Male,African-American,08/28/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56304,64201,58257,Probation,Beretta,John,NULL,Male,Caucasian,05/12/36,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,1,Low,7,Risk of Violence,-4.49,1,Low,New,1,0 +56304,64201,58257,Probation,Beretta,John,NULL,Male,Caucasian,05/12/36,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,1,Low,8,Risk of Recidivism,-2.65,1,Low,New,1,0 +56304,64201,58257,Probation,Beretta,John,NULL,Male,Caucasian,05/12/36,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +45818,64216,58271,PRETRIAL,Reilly,Joseph,NULL,Male,Caucasian,06/04/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +45818,64216,58271,PRETRIAL,Reilly,Joseph,NULL,Male,Caucasian,06/04/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +45818,64216,58271,PRETRIAL,Reilly,Joseph,NULL,Male,Caucasian,06/04/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56296,64188,58246,PRETRIAL,Fernandezcueto,Luis,NULL,Male,Caucasian,07/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +56296,64188,58246,PRETRIAL,Fernandezcueto,Luis,NULL,Male,Caucasian,07/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +56296,64188,58246,PRETRIAL,Fernandezcueto,Luis,NULL,Male,Caucasian,07/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56303,64198,58255,PRETRIAL,Browne,Sean,Bandy,Male,Caucasian,01/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +56303,64198,58255,PRETRIAL,Browne,Sean,Bandy,Male,Caucasian,01/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +56303,64198,58255,PRETRIAL,Browne,Sean,Bandy,Male,Caucasian,01/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +37622,64205,58261,PRETRIAL,Short,William,NULL,Male,Caucasian,07/15/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/9/13 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +37622,64205,58261,PRETRIAL,Short,William,NULL,Male,Caucasian,07/15/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/9/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +37622,64205,58261,PRETRIAL,Short,William,NULL,Male,Caucasian,07/15/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56317,64219,58274,Probation,Freeman,Tina,NULL,Female,African-American,09/05/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/9/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +56317,64219,58274,Probation,Freeman,Tina,NULL,Female,African-American,09/05/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +56317,64219,58274,Probation,Freeman,Tina,NULL,Female,African-American,09/05/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/9/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56299,64191,58249,PRETRIAL,Robinson,Ryan,Oneal,Male,African-American,09/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.86,9,High,New,1,0 +56299,64191,58249,PRETRIAL,Robinson,Ryan,Oneal,Male,African-American,09/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,7,Medium,New,1,0 +56299,64191,58249,PRETRIAL,Robinson,Ryan,Oneal,Male,African-American,09/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55916,64200,57837,PRETRIAL,Davis,Nicole,NULL,Female,Caucasian,12/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/9/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,Copy,1,0 +55916,64200,57837,PRETRIAL,Davis,Nicole,NULL,Female,Caucasian,12/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/9/13 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,Copy,1,0 +55916,64200,57837,PRETRIAL,Davis,Nicole,NULL,Female,Caucasian,12/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +56316,64217,58272,Probation,Sheemaz,Sophia,NULL,Female,African-American,12/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +56316,64217,58272,Probation,Sheemaz,Sophia,NULL,Female,African-American,12/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +56316,64217,58272,Probation,Sheemaz,Sophia,NULL,Female,African-American,12/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56302,64196,58254,PRETRIAL,Mcfadden,Michelle,NULL,Male,African-American,10/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +56302,64196,58254,PRETRIAL,Mcfadden,Michelle,NULL,Male,African-American,10/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +56302,64196,58254,PRETRIAL,Mcfadden,Michelle,NULL,Male,African-American,10/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56315,64215,58270,Probation,Becraft,Anthony,NULL,Male,Caucasian,09/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/9/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +56315,64215,58270,Probation,Becraft,Anthony,NULL,Male,Caucasian,09/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/9/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +56315,64215,58270,Probation,Becraft,Anthony,NULL,Male,Caucasian,09/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +36165,64194,58252,PRETRIAL,Martin,Kionte,D,Male,African-American,08/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,New,1,0 +36165,64194,58252,PRETRIAL,Martin,Kionte,D,Male,African-American,08/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +36165,64194,58252,PRETRIAL,Martin,Kionte,D,Male,African-American,08/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56297,64189,58247,PRETRIAL,Wright,James,Earl,Male,Caucasian,06/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/9/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +56297,64189,58247,PRETRIAL,Wright,James,Earl,Male,Caucasian,06/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/9/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +56297,64189,58247,PRETRIAL,Wright,James,Earl,Male,Caucasian,06/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56305,64202,58258,PRETRIAL,viruez,andre,NULL,Male,Hispanic,11/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +56305,64202,58258,PRETRIAL,viruez,andre,NULL,Male,Hispanic,11/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +56305,64202,58258,PRETRIAL,viruez,andre,NULL,Male,Hispanic,11/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56311,64210,58266,PRETRIAL,KINARD,ERNEST,NULL,Male,African-American,08/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +56311,64210,58266,PRETRIAL,KINARD,ERNEST,NULL,Male,African-American,08/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +56311,64210,58266,PRETRIAL,KINARD,ERNEST,NULL,Male,African-American,08/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56324,64228,58282,PRETRIAL,Hyppolite,Florishma,NULL,Male,African-American,10/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +56324,64228,58282,PRETRIAL,Hyppolite,Florishma,NULL,Male,African-American,10/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +56324,64228,58282,PRETRIAL,Hyppolite,Florishma,NULL,Male,African-American,10/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56327,64231,58285,PRETRIAL,Garcia,Alyssa,NULL,Female,Caucasian,11/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +56327,64231,58285,PRETRIAL,Garcia,Alyssa,NULL,Female,Caucasian,11/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +56327,64231,58285,PRETRIAL,Garcia,Alyssa,NULL,Female,Caucasian,11/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56330,64236,58289,PRETRIAL,Hutchinson,Donald,Peart,Male,African-American,06/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.96,9,High,New,1,0 +56330,64236,58289,PRETRIAL,Hutchinson,Donald,Peart,Male,African-American,06/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +56330,64236,58289,PRETRIAL,Hutchinson,Donald,Peart,Male,African-American,06/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56321,64223,58278,PRETRIAL,Carias,Harris,Lee,Male,African-American,05/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,4,High,7,Risk of Violence,-0.65,9,High,New,1,0 +56321,64223,58278,PRETRIAL,Carias,Harris,Lee,Male,African-American,05/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,4,High,8,Risk of Recidivism,0.67,10,High,New,1,0 +56321,64223,58278,PRETRIAL,Carias,Harris,Lee,Male,African-American,05/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56319,64221,58276,PRETRIAL,Lopez,Thelma,NULL,Male,Caucasian,01/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +56319,64221,58276,PRETRIAL,Lopez,Thelma,NULL,Male,Caucasian,01/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +56319,64221,58276,PRETRIAL,Lopez,Thelma,NULL,Male,Caucasian,01/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +16573,64233,58287,PRETRIAL,SHELTON,RONALD,LEE,Male,African-American,08/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +16573,64233,58287,PRETRIAL,SHELTON,RONALD,LEE,Male,African-American,08/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +16573,64233,58287,PRETRIAL,SHELTON,RONALD,LEE,Male,African-American,08/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56323,64226,58281,PRETRIAL,Bochini,Robert,NULL,Male,Caucasian,02/06/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,7,Risk of Violence,-2.27,3,Low,New,1,0 +56323,64226,58281,PRETRIAL,Bochini,Robert,NULL,Male,Caucasian,02/06/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +56323,64226,58281,PRETRIAL,Bochini,Robert,NULL,Male,Caucasian,02/06/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56320,64222,58277,PRETRIAL,BAPTISTE,TYRONE,NULL,Male,African-American,03/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +56320,64222,58277,PRETRIAL,BAPTISTE,TYRONE,NULL,Male,African-American,03/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +56320,64222,58277,PRETRIAL,BAPTISTE,TYRONE,NULL,Male,African-American,03/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +42734,64224,58279,PRETRIAL,Howell,Machell,NULL,Male,African-American,11/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +42734,64224,58279,PRETRIAL,Howell,Machell,NULL,Male,African-American,11/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +42734,64224,58279,PRETRIAL,Howell,Machell,NULL,Male,African-American,11/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56326,64230,58284,PRETRIAL,Hunter,Jamichael,Demittrius,Male,African-American,11/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,4,High,7,Risk of Violence,-1.23,8,High,New,1,0 +56326,64230,58284,PRETRIAL,Hunter,Jamichael,Demittrius,Male,African-American,11/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,4,High,8,Risk of Recidivism,0.87,10,High,New,1,0 +56326,64230,58284,PRETRIAL,Hunter,Jamichael,Demittrius,Male,African-American,11/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56328,64232,58286,PRETRIAL,Rivera,Jose,NULL,Male,Caucasian,06/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +56328,64232,58286,PRETRIAL,Rivera,Jose,NULL,Male,Caucasian,06/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +56328,64232,58286,PRETRIAL,Rivera,Jose,NULL,Male,Caucasian,06/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56329,64235,58288,PRETRIAL,Esteves,Alex,Efrem,Male,Hispanic,01/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +56329,64235,58288,PRETRIAL,Esteves,Alex,Efrem,Male,Hispanic,01/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +56329,64235,58288,PRETRIAL,Esteves,Alex,Efrem,Male,Hispanic,01/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +43504,64227,43465,PRETRIAL,Johnson,Terrence,NULL,Male,African-American,04/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,Copy,1,0 +43504,64227,43465,PRETRIAL,Johnson,Terrence,NULL,Male,African-American,04/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,Copy,1,0 +43504,64227,43465,PRETRIAL,Johnson,Terrence,NULL,Male,African-American,04/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +56318,64220,58275,PRETRIAL,Delacruz,Jerko,NULL,Male,Hispanic,10/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +56318,64220,58275,PRETRIAL,Delacruz,Jerko,NULL,Male,Hispanic,10/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +56318,64220,58275,PRETRIAL,Delacruz,Jerko,NULL,Male,Hispanic,10/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +36582,64234,35875,PRETRIAL,Nelson,Barry,NULL,Male,African-American,02/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,Copy,1,0 +36582,64234,35875,PRETRIAL,Nelson,Barry,NULL,Male,African-American,02/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,Copy,1,0 +36582,64234,35875,PRETRIAL,Nelson,Barry,NULL,Male,African-American,02/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +56325,64229,58283,PRETRIAL,Mcnair,Stephen,NULL,Male,African-American,08/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,New,1,0 +56325,64229,58283,PRETRIAL,Mcnair,Stephen,NULL,Male,African-American,08/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +56325,64229,58283,PRETRIAL,Mcnair,Stephen,NULL,Male,African-American,08/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56322,64225,58280,PRETRIAL,BLOUNT,JATEZ,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +56322,64225,58280,PRETRIAL,BLOUNT,JATEZ,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +56322,64225,58280,PRETRIAL,BLOUNT,JATEZ,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +56340,64246,58299,PRETRIAL,Vidal,Daniella,NULL,Female,Caucasian,03/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/11/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +56340,64246,58299,PRETRIAL,Vidal,Daniella,NULL,Female,Caucasian,03/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/11/13 0:00,1,Low,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +56340,64246,58299,PRETRIAL,Vidal,Daniella,NULL,Female,Caucasian,03/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56342,64248,58301,PRETRIAL,LEWIS,SHANE,NULL,Male,African-American,07/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.06,8,High,New,1,0 +56342,64248,58301,PRETRIAL,LEWIS,SHANE,NULL,Male,African-American,07/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +56342,64248,58301,PRETRIAL,LEWIS,SHANE,NULL,Male,African-American,07/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56333,64239,58292,PRETRIAL,CEDENO,FRANKLIN,AXEL,Male,Caucasian,12/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +56333,64239,58292,PRETRIAL,CEDENO,FRANKLIN,AXEL,Male,Caucasian,12/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +56333,64239,58292,PRETRIAL,CEDENO,FRANKLIN,AXEL,Male,Caucasian,12/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56335,64241,58294,PRETRIAL,Gregory,Heather,A,Female,Caucasian,05/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +56335,64241,58294,PRETRIAL,Gregory,Heather,A,Female,Caucasian,05/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +56335,64241,58294,PRETRIAL,Gregory,Heather,A,Female,Caucasian,05/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +56334,64240,58293,PRETRIAL,WEAVER,CAMERON,NULL,Male,Caucasian,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +56334,64240,58293,PRETRIAL,WEAVER,CAMERON,NULL,Male,Caucasian,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +56334,64240,58293,PRETRIAL,WEAVER,CAMERON,NULL,Male,Caucasian,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56331,64237,58290,PRETRIAL,LOUIMA,CLEVENT,NULL,Male,African-American,10/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.15,8,High,New,1,0 +56331,64237,58290,PRETRIAL,LOUIMA,CLEVENT,NULL,Male,African-American,10/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +56331,64237,58290,PRETRIAL,LOUIMA,CLEVENT,NULL,Male,African-American,10/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56337,64243,58296,PRETRIAL,DIAZ,ADAM,JOHN,Male,Caucasian,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +56337,64243,58296,PRETRIAL,DIAZ,ADAM,JOHN,Male,Caucasian,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +56337,64243,58296,PRETRIAL,DIAZ,ADAM,JOHN,Male,Caucasian,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56339,64245,58298,PRETRIAL,Stillman,Cindy,NULL,Female,Caucasian,01/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +56339,64245,58298,PRETRIAL,Stillman,Cindy,NULL,Female,Caucasian,01/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,8,Risk of Recidivism,-1.61,2,Low,New,1,0 +56339,64245,58298,PRETRIAL,Stillman,Cindy,NULL,Female,Caucasian,01/06/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56341,64247,58300,PRETRIAL,Ragin,Edward,L,Male,African-American,02/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,4,High,7,Risk of Violence,-0.43,10,High,New,1,0 +56341,64247,58300,PRETRIAL,Ragin,Edward,L,Male,African-American,02/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,4,High,8,Risk of Recidivism,1.15,10,High,New,1,0 +56341,64247,58300,PRETRIAL,Ragin,Edward,L,Male,African-American,02/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56336,64242,58295,PRETRIAL,TORRES,JOEL,NULL,Male,Caucasian,06/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +56336,64242,58295,PRETRIAL,TORRES,JOEL,NULL,Male,Caucasian,06/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +56336,64242,58295,PRETRIAL,TORRES,JOEL,NULL,Male,Caucasian,06/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56332,64238,58291,PRETRIAL,LYTLE,ANTONIO,J,Male,African-American,07/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +56332,64238,58291,PRETRIAL,LYTLE,ANTONIO,J,Male,African-American,07/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +56332,64238,58291,PRETRIAL,LYTLE,ANTONIO,J,Male,African-American,07/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56338,64244,58297,PRETRIAL,Montgomery,Scott,NULL,Male,Caucasian,06/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +56338,64244,58297,PRETRIAL,Montgomery,Scott,NULL,Male,Caucasian,06/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +56338,64244,58297,PRETRIAL,Montgomery,Scott,NULL,Male,Caucasian,06/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56375,64294,58341,Probation,Williams,Leticia,NULL,Female,African-American,08/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +56375,64294,58341,Probation,Williams,Leticia,NULL,Female,African-American,08/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +56375,64294,58341,Probation,Williams,Leticia,NULL,Female,African-American,08/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +46822,64265,47271,PRETRIAL,TOWNS,TIMOTHY,NULL,Male,African-American,06/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,Copy,1,0 +46822,64265,47271,PRETRIAL,TOWNS,TIMOTHY,NULL,Male,African-American,06/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.73,4,Low,Copy,1,0 +46822,64265,47271,PRETRIAL,TOWNS,TIMOTHY,NULL,Male,African-American,06/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +3206,64252,58305,PRETRIAL,PAUL,MAXTERSON,NULL,Male,African-American,01/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/12/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +3206,64252,58305,PRETRIAL,PAUL,MAXTERSON,NULL,Male,African-American,01/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +3206,64252,58305,PRETRIAL,PAUL,MAXTERSON,NULL,Male,African-American,01/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56369,64286,58335,Probation,Davis,Dale,NULL,Male,Caucasian,12/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +56369,64286,58335,Probation,Davis,Dale,NULL,Male,Caucasian,12/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +56369,64286,58335,Probation,Davis,Dale,NULL,Male,Caucasian,12/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56371,64288,58337,PRETRIAL,Chambers,Nadine,NULL,Female,Caucasian,08/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/12/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +56371,64288,58337,PRETRIAL,Chambers,Nadine,NULL,Female,Caucasian,08/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/12/13 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +56371,64288,58337,PRETRIAL,Chambers,Nadine,NULL,Female,Caucasian,08/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +32537,64273,58323,Probation,martinez,george,NULL,Male,Hispanic,07/03/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +32537,64273,58323,Probation,martinez,george,NULL,Male,Hispanic,07/03/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +32537,64273,58323,Probation,martinez,george,NULL,Male,Hispanic,07/03/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56348,64257,58310,PRETRIAL,Williams,Branden,NULL,Male,Other,08/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +56348,64257,58310,PRETRIAL,Williams,Branden,NULL,Male,Other,08/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +56348,64257,58310,PRETRIAL,Williams,Branden,NULL,Male,Other,08/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56357,64270,58320,Probation,Gomez,Gustavo,Adolfo,Male,Hispanic,08/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +56357,64270,58320,Probation,Gomez,Gustavo,Adolfo,Male,Hispanic,08/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +56357,64270,58320,Probation,Gomez,Gustavo,Adolfo,Male,Hispanic,08/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56379,64299,58346,Probation,smith,mark,NULL,Male,Caucasian,03/20/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/12/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +56379,64299,58346,Probation,smith,mark,NULL,Male,Caucasian,03/20/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/12/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +56379,64299,58346,Probation,smith,mark,NULL,Male,Caucasian,03/20/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +39415,64278,58328,PRETRIAL,Glass,Herbert,NULL,Male,African-American,06/07/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/12/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +39415,64278,58328,PRETRIAL,Glass,Herbert,NULL,Male,African-American,06/07/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +39415,64278,58328,PRETRIAL,Glass,Herbert,NULL,Male,African-American,06/07/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/12/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56376,64296,58343,Probation,Jenkins,Tyisha,NULL,Female,African-American,01/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +56376,64296,58343,Probation,Jenkins,Tyisha,NULL,Female,African-American,01/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +56376,64296,58343,Probation,Jenkins,Tyisha,NULL,Female,African-American,01/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +56351,64263,58314,Probation,Morris,Patrick,NULL,Male,Caucasian,01/11/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +56351,64263,58314,Probation,Morris,Patrick,NULL,Male,Caucasian,01/11/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +56351,64263,58314,Probation,Morris,Patrick,NULL,Male,Caucasian,01/11/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +7483,64259,7075,PRETRIAL,ADAMS,JAMES,REESE,Male,African-American,10/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,Copy,1,0 +7483,64259,7075,PRETRIAL,ADAMS,JAMES,REESE,Male,African-American,10/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,Copy,1,0 +7483,64259,7075,PRETRIAL,ADAMS,JAMES,REESE,Male,African-American,10/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +56358,64272,58322,Probation,RIERA BLACAZAR,LILIAN,NULL,Female,Hispanic,09/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +56358,64272,58322,Probation,RIERA BLACAZAR,LILIAN,NULL,Female,Hispanic,09/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +56358,64272,58322,Probation,RIERA BLACAZAR,LILIAN,NULL,Female,Hispanic,09/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +56372,64289,58338,Probation,Brown,Michael,NULL,Male,African-American,01/23/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +56372,64289,58338,Probation,Brown,Michael,NULL,Male,African-American,01/23/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +56372,64289,58338,Probation,Brown,Michael,NULL,Male,African-American,01/23/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56367,64284,58333,Probation,Chapman,Kevin,NULL,Male,Caucasian,07/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +56367,64284,58333,Probation,Chapman,Kevin,NULL,Male,Caucasian,07/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +56367,64284,58333,Probation,Chapman,Kevin,NULL,Male,Caucasian,07/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56377,64298,58345,Probation,Ulteus,Jude,NULL,Male,African-American,04/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +56377,64298,58345,Probation,Ulteus,Jude,NULL,Male,African-American,04/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +56377,64298,58345,Probation,Ulteus,Jude,NULL,Male,African-American,04/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56347,64256,58309,PRETRIAL,Margison,Angela,NULL,Female,Caucasian,02/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,8/12/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +56347,64256,58309,PRETRIAL,Margison,Angela,NULL,Female,Caucasian,02/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,8/12/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +56347,64256,58309,PRETRIAL,Margison,Angela,NULL,Female,Caucasian,02/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56345,64254,58307,PRETRIAL,OConnor,Nicole,Marie,Female,Caucasian,05/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,New,1,0 +56345,64254,58307,PRETRIAL,OConnor,Nicole,Marie,Female,Caucasian,05/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +56345,64254,58307,PRETRIAL,OConnor,Nicole,Marie,Female,Caucasian,05/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +56362,64277,58327,PRETRIAL,Foy,Rhoneisha,NULL,Female,African-American,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +56362,64277,58327,PRETRIAL,Foy,Rhoneisha,NULL,Female,African-American,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +56362,64277,58327,PRETRIAL,Foy,Rhoneisha,NULL,Female,African-American,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56363,64279,58329,Probation,Clermond,Wilkens,NULL,Male,African-American,05/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/12/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +56363,64279,58329,Probation,Clermond,Wilkens,NULL,Male,African-American,05/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +56363,64279,58329,Probation,Clermond,Wilkens,NULL,Male,African-American,05/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56349,64258,58311,PRETRIAL,TORRES,CLARA,NULL,Female,Caucasian,08/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/12/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +56349,64258,58311,PRETRIAL,TORRES,CLARA,NULL,Female,Caucasian,08/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/12/13 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +56349,64258,58311,PRETRIAL,TORRES,CLARA,NULL,Female,Caucasian,08/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56370,64287,58336,Probation,Izquierdo,Eduardo,NULL,Male,Hispanic,11/24/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/12/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +56370,64287,58336,Probation,Izquierdo,Eduardo,NULL,Male,Hispanic,11/24/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/12/13 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +56370,64287,58336,Probation,Izquierdo,Eduardo,NULL,Male,Hispanic,11/24/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56343,64251,58304,PRETRIAL,VANTREESE,KAYLA,MARIE,Female,Caucasian,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +56343,64251,58304,PRETRIAL,VANTREESE,KAYLA,MARIE,Female,Caucasian,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,New,1,0 +56343,64251,58304,PRETRIAL,VANTREESE,KAYLA,MARIE,Female,Caucasian,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56352,64266,58316,Probation,FRAZIER,SABRINA,NULL,Female,African-American,11/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +56352,64266,58316,Probation,FRAZIER,SABRINA,NULL,Female,African-American,11/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,New,1,0 +56352,64266,58316,Probation,FRAZIER,SABRINA,NULL,Female,African-American,11/11/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56359,64274,58324,Probation,Hirshorn,Todd,NULL,Male,Caucasian,09/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +56359,64274,58324,Probation,Hirshorn,Todd,NULL,Male,Caucasian,09/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +56359,64274,58324,Probation,Hirshorn,Todd,NULL,Male,Caucasian,09/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51752,64261,58313,PRETRIAL,Vasquez,Sean,NULL,Male,Caucasian,09/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +51752,64261,58313,PRETRIAL,Vasquez,Sean,NULL,Male,Caucasian,09/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +51752,64261,58313,PRETRIAL,Vasquez,Sean,NULL,Male,Caucasian,09/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +40757,64295,58342,Probation,Boyle,Ashley,NULL,Female,Caucasian,07/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +40757,64295,58342,Probation,Boyle,Ashley,NULL,Female,Caucasian,07/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +40757,64295,58342,Probation,Boyle,Ashley,NULL,Female,Caucasian,07/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56344,64253,58306,PRETRIAL,DELISI,CHARLES,NULL,Male,Caucasian,05/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +56344,64253,58306,PRETRIAL,DELISI,CHARLES,NULL,Male,Caucasian,05/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +56344,64253,58306,PRETRIAL,DELISI,CHARLES,NULL,Male,Caucasian,05/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56365,64282,58331,Probation,Thomas Walker,Theresa,NULL,Female,African-American,05/11/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/12/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +56365,64282,58331,Probation,Thomas Walker,Theresa,NULL,Female,African-American,05/11/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/12/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +56365,64282,58331,Probation,Thomas Walker,Theresa,NULL,Female,African-American,05/11/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56380,64300,58347,PRETRIAL,LECHANCE,DEBORAH,NULL,Female,Caucasian,03/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +56380,64300,58347,PRETRIAL,LECHANCE,DEBORAH,NULL,Female,Caucasian,03/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +56380,64300,58347,PRETRIAL,LECHANCE,DEBORAH,NULL,Female,Caucasian,03/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56373,64290,58339,PRETRIAL,barbosa,giovanni,NULL,Male,Hispanic,12/01/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +56373,64290,58339,PRETRIAL,barbosa,giovanni,NULL,Male,Hispanic,12/01/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,4,High,8,Risk of Recidivism,0.26,8,High,New,1,0 +56373,64290,58339,PRETRIAL,barbosa,giovanni,NULL,Male,Hispanic,12/01/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,4,High,18,Risk of Failure to Appear,16,1,Low,New,1,0 +54789,64292,56509,Probation,Hamilton,Telekia,NULL,Female,African-American,05/13/78,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +54789,64292,56509,Probation,Hamilton,Telekia,NULL,Female,African-American,05/13/78,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.78,4,Low,New,1,0 +54789,64292,56509,Probation,Hamilton,Telekia,NULL,Female,African-American,05/13/78,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56366,64283,58332,Probation,Lumpkin,Richard,NULL,Male,Caucasian,01/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +56366,64283,58332,Probation,Lumpkin,Richard,NULL,Male,Caucasian,01/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +56366,64283,58332,Probation,Lumpkin,Richard,NULL,Male,Caucasian,01/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56346,64255,58308,PRETRIAL,Thibeault,Gail,Marie,Female,Caucasian,05/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,4,High,7,Risk of Violence,-0.97,9,High,New,1,0 +56346,64255,58308,PRETRIAL,Thibeault,Gail,Marie,Female,Caucasian,05/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,4,High,8,Risk of Recidivism,0.04,8,High,New,1,0 +56346,64255,58308,PRETRIAL,Thibeault,Gail,Marie,Female,Caucasian,05/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56355,64269,58319,Probation,Sweeney,Stephanie,NULL,Female,Caucasian,02/07/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/12/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +56355,64269,58319,Probation,Sweeney,Stephanie,NULL,Female,Caucasian,02/07/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/12/13 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +56355,64269,58319,Probation,Sweeney,Stephanie,NULL,Female,Caucasian,02/07/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56350,64260,58312,PRETRIAL,HASELEY,COREY,NULL,Male,Caucasian,08/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +56350,64260,58312,PRETRIAL,HASELEY,COREY,NULL,Male,Caucasian,08/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +56350,64260,58312,PRETRIAL,HASELEY,COREY,NULL,Male,Caucasian,08/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56356,64271,58321,PRETRIAL,Gay,Tyler,NULL,Male,Caucasian,08/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.12,8,High,New,1,0 +56356,64271,58321,PRETRIAL,Gay,Tyler,NULL,Male,Caucasian,08/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +56356,64271,58321,PRETRIAL,Gay,Tyler,NULL,Male,Caucasian,08/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56368,64285,58334,Probation,Fischer,Bryan,NULL,Male,Caucasian,06/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +56368,64285,58334,Probation,Fischer,Bryan,NULL,Male,Caucasian,06/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +56368,64285,58334,Probation,Fischer,Bryan,NULL,Male,Caucasian,06/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +1296,64250,58303,PRETRIAL,MIMS,DARREL,NULL,Male,African-American,09/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/12/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +1296,64250,58303,PRETRIAL,MIMS,DARREL,NULL,Male,African-American,09/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +1296,64250,58303,PRETRIAL,MIMS,DARREL,NULL,Male,African-American,09/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +39904,64264,58315,PRETRIAL,LOPEZ,YANCIE,VERNOICA,Female,Hispanic,07/31/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/12/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +39904,64264,58315,PRETRIAL,LOPEZ,YANCIE,VERNOICA,Female,Hispanic,07/31/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +39904,64264,58315,PRETRIAL,LOPEZ,YANCIE,VERNOICA,Female,Hispanic,07/31/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +56353,64267,58317,Probation,Baker,Tashana,NULL,Female,African-American,04/07/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/12/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +56353,64267,58317,Probation,Baker,Tashana,NULL,Female,African-American,04/07/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +56353,64267,58317,Probation,Baker,Tashana,NULL,Female,African-American,04/07/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/12/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56361,64276,58326,Probation,RODAS,ARMANDO,NULL,Male,Hispanic,12/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/12/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +56361,64276,58326,Probation,RODAS,ARMANDO,NULL,Male,Hispanic,12/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/12/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +56361,64276,58326,Probation,RODAS,ARMANDO,NULL,Male,Hispanic,12/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56378,64297,58344,Probation,Gutman,Brandon,NULL,Male,Caucasian,11/29/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +56378,64297,58344,Probation,Gutman,Brandon,NULL,Male,Caucasian,11/29/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +56378,64297,58344,Probation,Gutman,Brandon,NULL,Male,Caucasian,11/29/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56382,64302,58349,PRETRIAL,Jacquette,Athlene,C,Female,Other,10/10/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +56382,64302,58349,PRETRIAL,Jacquette,Athlene,C,Female,Other,10/10/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/13 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +56382,64302,58349,PRETRIAL,Jacquette,Athlene,C,Female,Other,10/10/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +34862,64327,34030,PRETRIAL,Siegrist,Ashley,Marie,Female,Caucasian,02/22/89,17,All Scales,Intake,English,Probation Violator,Probation,Single,8/13/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +34862,64327,34030,PRETRIAL,Siegrist,Ashley,Marie,Female,Caucasian,02/22/89,17,All Scales,Intake,English,Probation Violator,Probation,Single,8/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +34862,64327,34030,PRETRIAL,Siegrist,Ashley,Marie,Female,Caucasian,02/22/89,17,All Scales,Intake,English,Probation Violator,Probation,Single,8/13/13 0:00,2,Medium,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +56407,64336,58381,PRETRIAL,Mange,Blanche,NULL,Female,Caucasian,06/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +56407,64336,58381,PRETRIAL,Mange,Blanche,NULL,Female,Caucasian,06/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +56407,64336,58381,PRETRIAL,Mange,Blanche,NULL,Female,Caucasian,06/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56386,64306,58353,PRETRIAL,Carson,Cedric,Duane,Male,African-American,09/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +56386,64306,58353,PRETRIAL,Carson,Cedric,Duane,Male,African-American,09/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +56386,64306,58353,PRETRIAL,Carson,Cedric,Duane,Male,African-American,09/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +56397,64323,58369,Probation,Bryant,James,NULL,Male,African-American,04/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +56397,64323,58369,Probation,Bryant,James,NULL,Male,African-American,04/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +56397,64323,58369,Probation,Bryant,James,NULL,Male,African-American,04/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56403,64332,58377,PRETRIAL,Holmes,Matthew,NULL,Male,African-American,10/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +56403,64332,58377,PRETRIAL,Holmes,Matthew,NULL,Male,African-American,10/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +56403,64332,58377,PRETRIAL,Holmes,Matthew,NULL,Male,African-American,10/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56405,64334,58379,Probation,ARENAS,ESTEBAN,NULL,Male,Hispanic,08/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +56405,64334,58379,Probation,ARENAS,ESTEBAN,NULL,Male,Hispanic,08/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +56405,64334,58379,Probation,ARENAS,ESTEBAN,NULL,Male,Hispanic,08/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56410,64339,58384,PRETRIAL,Lozada,Victor,NULL,Male,Hispanic,05/12/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/13/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +56410,64339,58384,PRETRIAL,Lozada,Victor,NULL,Male,Hispanic,05/12/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/13/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +56410,64339,58384,PRETRIAL,Lozada,Victor,NULL,Male,Hispanic,05/12/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56411,64341,58385,Probation,AGENOR,DELINIA,S,Female,African-American,08/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +56411,64341,58385,Probation,AGENOR,DELINIA,S,Female,African-American,08/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +56411,64341,58385,Probation,AGENOR,DELINIA,S,Female,African-American,08/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56389,64311,58358,PRETRIAL,Manley,Gerrick,Renard,Male,African-American,10/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +56389,64311,58358,PRETRIAL,Manley,Gerrick,Renard,Male,African-American,10/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +56389,64311,58358,PRETRIAL,Manley,Gerrick,Renard,Male,African-American,10/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +8041,64313,58360,PRETRIAL,MYREE,PATRICK,NULL,Male,African-American,11/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +8041,64313,58360,PRETRIAL,MYREE,PATRICK,NULL,Male,African-American,11/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +8041,64313,58360,PRETRIAL,MYREE,PATRICK,NULL,Male,African-American,11/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +48451,64320,58366,PRETRIAL,Bryant,Harold,Leonard,Male,African-American,07/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/13/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +48451,64320,58366,PRETRIAL,Bryant,Harold,Leonard,Male,African-American,07/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/13/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +48451,64320,58366,PRETRIAL,Bryant,Harold,Leonard,Male,African-American,07/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56383,64303,58350,PRETRIAL,Exantus,Brittany,Nicole,Female,African-American,06/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +56383,64303,58350,PRETRIAL,Exantus,Brittany,Nicole,Female,African-American,06/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +56383,64303,58350,PRETRIAL,Exantus,Brittany,Nicole,Female,African-American,06/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55618,64321,58367,Probation,Gunn,Pamela,Denise,Female,African-American,06/23/79,17,All Scales,Intake,English,Other,Probation,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +55618,64321,58367,Probation,Gunn,Pamela,Denise,Female,African-American,06/23/79,17,All Scales,Intake,English,Other,Probation,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +55618,64321,58367,Probation,Gunn,Pamela,Denise,Female,African-American,06/23/79,17,All Scales,Intake,English,Other,Probation,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56401,64329,58374,Probation,DEMARD,MARCKENSON,NULL,Male,African-American,10/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +56401,64329,58374,Probation,DEMARD,MARCKENSON,NULL,Male,African-American,10/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +56401,64329,58374,Probation,DEMARD,MARCKENSON,NULL,Male,African-American,10/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56387,64308,58355,PRETRIAL,Lokai,Christopher,Burnett,Male,Other,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/13/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +56387,64308,58355,PRETRIAL,Lokai,Christopher,Burnett,Male,Other,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/13/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +56387,64308,58355,PRETRIAL,Lokai,Christopher,Burnett,Male,Other,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +30661,64342,58386,PRETRIAL,SCHELLER,EVANS,NULL,Male,Caucasian,10/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +30661,64342,58386,PRETRIAL,SCHELLER,EVANS,NULL,Male,Caucasian,10/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +30661,64342,58386,PRETRIAL,SCHELLER,EVANS,NULL,Male,Caucasian,10/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56394,64316,58363,Probation,GRIFFITH,RICHARD,NULL,Male,African-American,10/05/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +56394,64316,58363,Probation,GRIFFITH,RICHARD,NULL,Male,African-American,10/05/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +56394,64316,58363,Probation,GRIFFITH,RICHARD,NULL,Male,African-American,10/05/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +23734,63965,58042,PRETRIAL,DIAZ,CHRISTOPER,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,4,High,7,Risk of Violence,-0.4,10,High,New,1,0 +23734,63965,58042,PRETRIAL,DIAZ,CHRISTOPER,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,4,High,8,Risk of Recidivism,0.62,10,High,New,1,0 +23734,63965,58042,PRETRIAL,DIAZ,CHRISTOPER,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56408,64337,58382,Probation,Kirkovich,Gianina,NULL,Female,Caucasian,11/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +56408,64337,58382,Probation,Kirkovich,Gianina,NULL,Female,Caucasian,11/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +56408,64337,58382,Probation,Kirkovich,Gianina,NULL,Female,Caucasian,11/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56413,64344,58388,PRETRIAL,BYRD,BRION,NULL,Male,African-American,12/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/13 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +56413,64344,58388,PRETRIAL,BYRD,BRION,NULL,Male,African-American,12/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +56413,64344,58388,PRETRIAL,BYRD,BRION,NULL,Male,African-American,12/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56398,64324,58370,Probation,BETANCOURT,AUGUSTIN,NULL,Male,Caucasian,03/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,New,1,0 +56398,64324,58370,Probation,BETANCOURT,AUGUSTIN,NULL,Male,Caucasian,03/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +56398,64324,58370,Probation,BETANCOURT,AUGUSTIN,NULL,Male,Caucasian,03/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +56414,64345,58389,Probation,ware,derrick,NULL,Male,African-American,02/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +56414,64345,58389,Probation,ware,derrick,NULL,Male,African-American,02/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +56414,64345,58389,Probation,ware,derrick,NULL,Male,African-American,02/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56404,64333,58378,Probation,Hamilton,Thomas,NULL,Male,Caucasian,02/01/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/13/13 0:00,1,Low,7,Risk of Violence,-4.29,1,Low,New,1,0 +56404,64333,58378,Probation,Hamilton,Thomas,NULL,Male,Caucasian,02/01/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/13/13 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +56404,64333,58378,Probation,Hamilton,Thomas,NULL,Male,Caucasian,02/01/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56385,64305,58352,PRETRIAL,Mason,Joshua,Lynn,Male,Caucasian,06/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +56385,64305,58352,PRETRIAL,Mason,Joshua,Lynn,Male,Caucasian,06/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +56385,64305,58352,PRETRIAL,Mason,Joshua,Lynn,Male,Caucasian,06/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56390,64312,58359,PRETRIAL,DIXON,DONOVAM,NULL,Male,African-American,11/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +56390,64312,58359,PRETRIAL,DIXON,DONOVAM,NULL,Male,African-American,11/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +56390,64312,58359,PRETRIAL,DIXON,DONOVAM,NULL,Male,African-American,11/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56395,64319,58365,Probation,Rancourt,Yvon,NULL,Male,Caucasian,07/04/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +56395,64319,58365,Probation,Rancourt,Yvon,NULL,Male,Caucasian,07/04/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +56395,64319,58365,Probation,Rancourt,Yvon,NULL,Male,Caucasian,07/04/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +56388,64310,58357,PRETRIAL,JACKSON,DERRICK,NULL,Male,African-American,07/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +56388,64310,58357,PRETRIAL,JACKSON,DERRICK,NULL,Male,African-American,07/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +56388,64310,58357,PRETRIAL,JACKSON,DERRICK,NULL,Male,African-American,07/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +43234,64328,58373,PRETRIAL,McCleod,Wilona,NULL,Female,African-American,02/12/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +43234,64328,58373,PRETRIAL,McCleod,Wilona,NULL,Female,African-American,02/12/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +43234,64328,58373,PRETRIAL,McCleod,Wilona,NULL,Female,African-American,02/12/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56406,64335,58380,PRETRIAL,Bynes,Christopher,NULL,Male,African-American,08/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,4,High,7,Risk of Violence,-0.68,9,High,New,1,0 +56406,64335,58380,PRETRIAL,Bynes,Christopher,NULL,Male,African-American,08/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +56406,64335,58380,PRETRIAL,Bynes,Christopher,NULL,Male,African-American,08/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56392,64314,58361,PRETRIAL,gray,alan,NULL,Male,Caucasian,02/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,4,High,7,Risk of Violence,-0.84,9,High,New,1,0 +56392,64314,58361,PRETRIAL,gray,alan,NULL,Male,Caucasian,02/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,4,High,8,Risk of Recidivism,0.47,9,High,New,1,0 +56392,64314,58361,PRETRIAL,gray,alan,NULL,Male,Caucasian,02/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56402,64331,58376,PRETRIAL,Varela,Andres,NULL,Male,Hispanic,01/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +56402,64331,58376,PRETRIAL,Varela,Andres,NULL,Male,Hispanic,01/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +56402,64331,58376,PRETRIAL,Varela,Andres,NULL,Male,Hispanic,01/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56415,64346,58390,Probation,JEANGILLES,kENNSLY,NULL,Male,African-American,09/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,New,1,0 +56415,64346,58390,Probation,JEANGILLES,kENNSLY,NULL,Male,African-American,09/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +56415,64346,58390,Probation,JEANGILLES,kENNSLY,NULL,Male,African-American,09/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55796,64317,57692,PRETRIAL,Pope,Oscar,NULL,Male,African-American,09/20/64,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,New,1,0 +55796,64317,57692,PRETRIAL,Pope,Oscar,NULL,Male,African-American,09/20/64,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,2,Medium,8,Risk of Recidivism,0.15,7,Medium,New,1,0 +55796,64317,57692,PRETRIAL,Pope,Oscar,NULL,Male,African-American,09/20/64,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/13 0:00,2,Medium,18,Risk of Failure to Appear,22,4,Low,New,1,0 +56384,64304,58351,PRETRIAL,Mullen,Euridice,NULL,Female,Hispanic,02/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/13/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +56384,64304,58351,PRETRIAL,Mullen,Euridice,NULL,Female,Hispanic,02/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/13/13 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +56384,64304,58351,PRETRIAL,Mullen,Euridice,NULL,Female,Hispanic,02/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56409,64338,58383,PRETRIAL,lacy,chance,NULL,Male,Caucasian,08/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +56409,64338,58383,PRETRIAL,lacy,chance,NULL,Male,Caucasian,08/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +56409,64338,58383,PRETRIAL,lacy,chance,NULL,Male,Caucasian,08/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +36377,64307,58354,PRETRIAL,Osorio,Kevin,NULL,Male,Caucasian,06/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +36377,64307,58354,PRETRIAL,Osorio,Kevin,NULL,Male,Caucasian,06/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +36377,64307,58354,PRETRIAL,Osorio,Kevin,NULL,Male,Caucasian,06/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50685,64309,58356,PRETRIAL,Anglin,Deamon,Mckenzie,Male,Other,12/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +50685,64309,58356,PRETRIAL,Anglin,Deamon,Mckenzie,Male,Other,12/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +50685,64309,58356,PRETRIAL,Anglin,Deamon,Mckenzie,Male,Other,12/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56396,64322,58368,PRETRIAL,Cyr,Danielle,NULL,Female,Caucasian,05/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/13/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +56396,64322,58368,PRETRIAL,Cyr,Danielle,NULL,Female,Caucasian,05/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/13/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +56396,64322,58368,PRETRIAL,Cyr,Danielle,NULL,Female,Caucasian,05/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56412,64343,58387,Probation,Ware,Dietrick,Omar,Male,African-American,11/27/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/13/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +56412,64343,58387,Probation,Ware,Dietrick,Omar,Male,African-American,11/27/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +56412,64343,58387,Probation,Ware,Dietrick,Omar,Male,African-American,11/27/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/13/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56381,64301,58348,PRETRIAL,ROCHA,DIEGO,EZEQUIEL,Male,Other,09/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +56381,64301,58348,PRETRIAL,ROCHA,DIEGO,EZEQUIEL,Male,Other,09/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +56381,64301,58348,PRETRIAL,ROCHA,DIEGO,EZEQUIEL,Male,Other,09/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56393,64315,58362,Probation,Vansiclen,Peter,NULL,Male,Caucasian,08/04/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +56393,64315,58362,Probation,Vansiclen,Peter,NULL,Male,Caucasian,08/04/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +56393,64315,58362,Probation,Vansiclen,Peter,NULL,Male,Caucasian,08/04/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +39869,64330,58375,PRETRIAL,GONZALEZ,JOSHUA,DANIEL,Male,Caucasian,05/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +39869,64330,58375,PRETRIAL,GONZALEZ,JOSHUA,DANIEL,Male,Caucasian,05/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +39869,64330,58375,PRETRIAL,GONZALEZ,JOSHUA,DANIEL,Male,Caucasian,05/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56437,64380,58418,PRETRIAL,Gilmore,Kevin,NULL,Male,Caucasian,03/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/14/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +56437,64380,58418,PRETRIAL,Gilmore,Kevin,NULL,Male,Caucasian,03/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/14/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +56437,64380,58418,PRETRIAL,Gilmore,Kevin,NULL,Male,Caucasian,03/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51846,64351,53104,PRETRIAL,MORENCY,EVENSON,NULL,Male,African-American,06/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,Copy,1,0 +51846,64351,53104,PRETRIAL,MORENCY,EVENSON,NULL,Male,African-American,06/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,4,High,8,Risk of Recidivism,0.72,10,High,Copy,1,0 +51846,64351,53104,PRETRIAL,MORENCY,EVENSON,NULL,Male,African-American,06/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +56433,64372,58411,PRETRIAL,shaw,William,Ralph,Male,Caucasian,05/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/14/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +56433,64372,58411,PRETRIAL,shaw,William,Ralph,Male,Caucasian,05/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/14/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +56433,64372,58411,PRETRIAL,shaw,William,Ralph,Male,Caucasian,05/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56422,64359,58398,Probation,Musumeci,Richard,NULL,Male,Caucasian,02/26/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/14/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +56422,64359,58398,Probation,Musumeci,Richard,NULL,Male,Caucasian,02/26/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/14/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +56422,64359,58398,Probation,Musumeci,Richard,NULL,Male,Caucasian,02/26/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +56426,64364,58403,PRETRIAL,Young,Nikesha,NULL,Female,African-American,05/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/14/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +56426,64364,58403,PRETRIAL,Young,Nikesha,NULL,Female,African-American,05/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/14/13 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +56426,64364,58403,PRETRIAL,Young,Nikesha,NULL,Female,African-American,05/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56428,64367,58406,PRETRIAL,Maczko,Nicholas,NULL,Male,Caucasian,04/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,8/14/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +56428,64367,58406,PRETRIAL,Maczko,Nicholas,NULL,Male,Caucasian,04/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,8/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +56428,64367,58406,PRETRIAL,Maczko,Nicholas,NULL,Male,Caucasian,04/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,8/14/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56417,64349,58392,PRETRIAL,Dean,Shalaun,NULL,Male,African-American,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.15,8,High,New,1,0 +56417,64349,58392,PRETRIAL,Dean,Shalaun,NULL,Male,African-American,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +56417,64349,58392,PRETRIAL,Dean,Shalaun,NULL,Male,African-American,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56440,64382,58420,Probation,McFadden,Robert,NULL,Male,African-American,03/22/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +56440,64382,58420,Probation,McFadden,Robert,NULL,Male,African-American,03/22/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +56440,64382,58420,Probation,McFadden,Robert,NULL,Male,African-American,03/22/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56423,64361,58400,Probation,Denham,TJ,NULL,Male,Caucasian,09/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +56423,64361,58400,Probation,Denham,TJ,NULL,Male,Caucasian,09/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +56423,64361,58400,Probation,Denham,TJ,NULL,Male,Caucasian,09/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56431,64370,58409,PRETRIAL,Sherman,Ryan,Scott,Male,Caucasian,09/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +56431,64370,58409,PRETRIAL,Sherman,Ryan,Scott,Male,Caucasian,09/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +56431,64370,58409,PRETRIAL,Sherman,Ryan,Scott,Male,Caucasian,09/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56442,64384,58422,Probation,Proctor,Gina,NULL,Female,Caucasian,09/19/66,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,8/14/13 0:00,2,Medium,7,Risk of Violence,-2.82,2,Low,New,1,0 +56442,64384,58422,Probation,Proctor,Gina,NULL,Female,Caucasian,09/19/66,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,8/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,7,Medium,New,1,0 +56442,64384,58422,Probation,Proctor,Gina,NULL,Female,Caucasian,09/19/66,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,8/14/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +56420,64354,58395,PRETRIAL,Dean,Jerel,Charcon,Male,African-American,12/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +56420,64354,58395,PRETRIAL,Dean,Jerel,Charcon,Male,African-American,12/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +56420,64354,58395,PRETRIAL,Dean,Jerel,Charcon,Male,African-American,12/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +43081,64377,58415,PRETRIAL,Harris,Willie,Jerome,Male,African-American,12/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +43081,64377,58415,PRETRIAL,Harris,Willie,Jerome,Male,African-American,12/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +43081,64377,58415,PRETRIAL,Harris,Willie,Jerome,Male,African-American,12/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +48648,64356,58397,PRETRIAL,Jean,Guerry,NULL,Male,African-American,11/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,New,1,0 +48648,64356,58397,PRETRIAL,Jean,Guerry,NULL,Male,African-American,11/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +48648,64356,58397,PRETRIAL,Jean,Guerry,NULL,Male,African-American,11/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56418,64352,58393,PRETRIAL,Hernandez,Miguel,Saba,Male,Other,04/18/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +56418,64352,58393,PRETRIAL,Hernandez,Miguel,Saba,Male,Other,04/18/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,1,Low,8,Risk of Recidivism,-2.78,1,Low,New,1,0 +56418,64352,58393,PRETRIAL,Hernandez,Miguel,Saba,Male,Other,04/18/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56438,64379,58417,Probation,RODRIGUEZ,JOSE,A,Male,Hispanic,03/28/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/14/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +56438,64379,58417,Probation,RODRIGUEZ,JOSE,A,Male,Hispanic,03/28/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/14/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +56438,64379,58417,Probation,RODRIGUEZ,JOSE,A,Male,Hispanic,03/28/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49671,64358,50569,PRETRIAL,HOWARD,NICOLE,NULL,Female,African-American,04/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/13 0:00,2,Medium,7,Risk of Violence,-2.91,2,Low,Copy,1,0 +49671,64358,50569,PRETRIAL,HOWARD,NICOLE,NULL,Female,African-American,04/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,Copy,1,0 +49671,64358,50569,PRETRIAL,HOWARD,NICOLE,NULL,Female,African-American,04/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +56434,64373,58412,Probation,Santiago,Katherine,NULL,Female,Hispanic,12/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/14/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +56434,64373,58412,Probation,Santiago,Katherine,NULL,Female,Hispanic,12/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/14/13 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +56434,64373,58412,Probation,Santiago,Katherine,NULL,Female,Hispanic,12/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +48348,64365,58404,PRETRIAL,Ensley,Nicole,NULL,Female,Caucasian,07/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +48348,64365,58404,PRETRIAL,Ensley,Nicole,NULL,Female,Caucasian,07/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +48348,64365,58404,PRETRIAL,Ensley,Nicole,NULL,Female,Caucasian,07/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56427,64366,58405,Probation,Stiggers,Laurita,NULL,Female,African-American,07/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +56427,64366,58405,Probation,Stiggers,Laurita,NULL,Female,African-American,07/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +56427,64366,58405,Probation,Stiggers,Laurita,NULL,Female,African-American,07/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55743,64376,57630,Probation,hart,kristin,NULL,Female,Caucasian,02/17/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/14/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +55743,64376,57630,Probation,hart,kristin,NULL,Female,Caucasian,02/17/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +55743,64376,57630,Probation,hart,kristin,NULL,Female,Caucasian,02/17/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/14/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56425,64363,58402,Probation,Marinucci,Erika,Lindsey,Female,Caucasian,03/02/77,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/14/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +56425,64363,58402,Probation,Marinucci,Erika,Lindsey,Female,Caucasian,03/02/77,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/14/13 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +56425,64363,58402,Probation,Marinucci,Erika,Lindsey,Female,Caucasian,03/02/77,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +18483,64360,58399,PRETRIAL,SARKO,DONALD,A,Male,Caucasian,10/07/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +18483,64360,58399,PRETRIAL,SARKO,DONALD,A,Male,Caucasian,10/07/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +18483,64360,58399,PRETRIAL,SARKO,DONALD,A,Male,Caucasian,10/07/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56432,64371,58410,Probation,Krall,Kristin,NULL,Female,African-American,01/16/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/14/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +56432,64371,58410,Probation,Krall,Kristin,NULL,Female,African-American,01/16/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/14/13 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +56432,64371,58410,Probation,Krall,Kristin,NULL,Female,African-American,01/16/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +41603,64350,41309,DRRD,Barnes,Willis,NULL,Male,African-American,09/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,4,High,7,Risk of Violence,-0.93,9,High,Copy,1,0 +41603,64350,41309,DRRD,Barnes,Willis,NULL,Male,African-American,09/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,4,High,8,Risk of Recidivism,0.48,9,High,Copy,1,0 +41603,64350,41309,DRRD,Barnes,Willis,NULL,Male,African-American,09/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,4,High,18,Risk of Failure to Appear,16,1,Low,Copy,1,0 +56429,64368,58407,Probation,MORA,EDUARDO,NULL,Male,Hispanic,06/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +56429,64368,58407,Probation,MORA,EDUARDO,NULL,Male,Hispanic,06/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +56429,64368,58407,Probation,MORA,EDUARDO,NULL,Male,Hispanic,06/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56439,64381,58419,PRETRIAL,Dest,Katelyn,NULL,Female,Caucasian,05/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +56439,64381,58419,PRETRIAL,Dest,Katelyn,NULL,Female,Caucasian,05/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +56439,64381,58419,PRETRIAL,Dest,Katelyn,NULL,Female,Caucasian,05/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56416,64348,58391,PRETRIAL,BECKFORD,LEO,NULL,Male,Other,08/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/14/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +56416,64348,58391,PRETRIAL,BECKFORD,LEO,NULL,Male,Other,08/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/14/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +56416,64348,58391,PRETRIAL,BECKFORD,LEO,NULL,Male,Other,08/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56441,64383,58421,Probation,hames,courtney,NULL,Male,Caucasian,01/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +56441,64383,58421,Probation,hames,courtney,NULL,Male,Caucasian,01/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +56441,64383,58421,Probation,hames,courtney,NULL,Male,Caucasian,01/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56424,64362,58401,Probation,Dowd,Jacqueline,NULL,Female,Caucasian,10/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +56424,64362,58401,Probation,Dowd,Jacqueline,NULL,Female,Caucasian,10/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +56424,64362,58401,Probation,Dowd,Jacqueline,NULL,Female,Caucasian,10/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56430,64369,58408,PRETRIAL,Evans,Benny,G,Male,Caucasian,12/19/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +56430,64369,58408,PRETRIAL,Evans,Benny,G,Male,Caucasian,12/19/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +56430,64369,58408,PRETRIAL,Evans,Benny,G,Male,Caucasian,12/19/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56419,64353,58394,PRETRIAL,MENA,MANUEL,NULL,Male,African-American,10/24/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,1,Low,7,Risk of Violence,-4.29,1,Low,New,1,0 +56419,64353,58394,PRETRIAL,MENA,MANUEL,NULL,Male,African-American,10/24/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,1,Low,8,Risk of Recidivism,-2.69,1,Low,New,1,0 +56419,64353,58394,PRETRIAL,MENA,MANUEL,NULL,Male,African-American,10/24/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56436,64378,58416,Probation,GATZKE,CHRISTOPHER,NULL,Male,Caucasian,02/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/14/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +56436,64378,58416,Probation,GATZKE,CHRISTOPHER,NULL,Male,Caucasian,02/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/14/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +56436,64378,58416,Probation,GATZKE,CHRISTOPHER,NULL,Male,Caucasian,02/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +47196,64357,47717,Probation,MALLORY,CHANCY,F,Male,African-American,07/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.17,4,Low,Copy,1,0 +47196,64357,47717,Probation,MALLORY,CHANCY,F,Male,African-American,07/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +47196,64357,47717,Probation,MALLORY,CHANCY,F,Male,African-American,07/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +43089,64374,58413,PRETRIAL,Jordan,Michael,Deon,Male,African-American,09/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +43089,64374,58413,PRETRIAL,Jordan,Michael,Deon,Male,African-American,09/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +43089,64374,58413,PRETRIAL,Jordan,Michael,Deon,Male,African-American,09/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56464,64408,58444,Probation,Lahteenmaki,Markus,Tapani,Male,Caucasian,04/26/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +56464,64408,58444,Probation,Lahteenmaki,Markus,Tapani,Male,Caucasian,04/26/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +56464,64408,58444,Probation,Lahteenmaki,Markus,Tapani,Male,Caucasian,04/26/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56477,64425,58459,Probation,littlejohn,corey,darrell,Male,African-American,10/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +56477,64425,58459,Probation,littlejohn,corey,darrell,Male,African-American,10/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +56477,64425,58459,Probation,littlejohn,corey,darrell,Male,African-American,10/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +48563,64395,58433,PRETRIAL,ELLIOT-BUTTS,ZACH,NULL,Male,African-American,07/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +48563,64395,58433,PRETRIAL,ELLIOT-BUTTS,ZACH,NULL,Male,African-American,07/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +48563,64395,58433,PRETRIAL,ELLIOT-BUTTS,ZACH,NULL,Male,African-American,07/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56460,64404,58440,PRETRIAL,cerniglia,michael,NULL,Male,Caucasian,07/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +56460,64404,58440,PRETRIAL,cerniglia,michael,NULL,Male,Caucasian,07/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +56460,64404,58440,PRETRIAL,cerniglia,michael,NULL,Male,Caucasian,07/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +32448,64429,58463,PRETRIAL,MARCEY,PAUL,S,Male,Caucasian,01/23/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/15/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +32448,64429,58463,PRETRIAL,MARCEY,PAUL,S,Male,Caucasian,01/23/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +32448,64429,58463,PRETRIAL,MARCEY,PAUL,S,Male,Caucasian,01/23/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +56454,64399,58436,Probation,ocasio,amanda,NULL,Female,Caucasian,03/19/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +56454,64399,58436,Probation,ocasio,amanda,NULL,Female,Caucasian,03/19/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +56454,64399,58436,Probation,ocasio,amanda,NULL,Female,Caucasian,03/19/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56466,64411,58446,PRETRIAL,chu,andrew,NULL,Male,Caucasian,01/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +56466,64411,58446,PRETRIAL,chu,andrew,NULL,Male,Caucasian,01/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +56466,64411,58446,PRETRIAL,chu,andrew,NULL,Male,Caucasian,01/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55823,64413,58448,Probation,Jackson,Christina,NULL,Female,African-American,06/24/77,17,All Scales,Intake,English,Probation Violator,Probation,Married,8/15/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +55823,64413,58448,Probation,Jackson,Christina,NULL,Female,African-American,06/24/77,17,All Scales,Intake,English,Probation Violator,Probation,Married,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +55823,64413,58448,Probation,Jackson,Christina,NULL,Female,African-American,06/24/77,17,All Scales,Intake,English,Probation Violator,Probation,Married,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +793,64420,58454,Probation,Hyder,Geoffrey,G,Male,Caucasian,03/18/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/15/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +793,64420,58454,Probation,Hyder,Geoffrey,G,Male,Caucasian,03/18/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +793,64420,58454,Probation,Hyder,Geoffrey,G,Male,Caucasian,03/18/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/15/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56447,64390,58428,PRETRIAL,BarahonaNeira,Nicolas,Ignacio,Male,Hispanic,01/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +56447,64390,58428,PRETRIAL,BarahonaNeira,Nicolas,Ignacio,Male,Hispanic,01/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +56447,64390,58428,PRETRIAL,BarahonaNeira,Nicolas,Ignacio,Male,Hispanic,01/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56449,64392,58430,PRETRIAL,Andrews,Oscar,NULL,Male,African-American,01/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,2,Medium,7,Risk of Violence,-2.95,1,Low,New,1,0 +56449,64392,58430,PRETRIAL,Andrews,Oscar,NULL,Male,African-American,01/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +56449,64392,58430,PRETRIAL,Andrews,Oscar,NULL,Male,African-American,01/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56473,64418,58453,PRETRIAL,DECICCO,MICHAEL,NULL,Male,Caucasian,07/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +56473,64418,58453,PRETRIAL,DECICCO,MICHAEL,NULL,Male,Caucasian,07/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +56473,64418,58453,PRETRIAL,DECICCO,MICHAEL,NULL,Male,Caucasian,07/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56480,64431,58465,Probation,Butler,Robert,NULL,Male,African-American,02/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.6,2,Low,New,1,0 +56480,64431,58465,Probation,Butler,Robert,NULL,Male,African-American,02/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +56480,64431,58465,Probation,Butler,Robert,NULL,Male,African-American,02/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +56465,64410,58445,Probation,matthews,christian,NULL,Male,African-American,04/29/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +56465,64410,58445,Probation,matthews,christian,NULL,Male,African-American,04/29/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +56465,64410,58445,Probation,matthews,christian,NULL,Male,African-American,04/29/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56479,64428,58462,Probation,martinez,jessica,NULL,Female,Caucasian,04/26/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/15/13 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +56479,64428,58462,Probation,martinez,jessica,NULL,Female,Caucasian,04/26/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +56479,64428,58462,Probation,martinez,jessica,NULL,Female,Caucasian,04/26/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/15/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56452,64397,58434,PRETRIAL,Thomas,Tremane,NULL,Male,African-American,02/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +56452,64397,58434,PRETRIAL,Thomas,Tremane,NULL,Male,African-American,02/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +56452,64397,58434,PRETRIAL,Thomas,Tremane,NULL,Male,African-American,02/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56457,64402,58439,PRETRIAL,Jackson,Demetri,NULL,Female,African-American,04/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +56457,64402,58439,PRETRIAL,Jackson,Demetri,NULL,Female,African-American,04/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +56457,64402,58439,PRETRIAL,Jackson,Demetri,NULL,Female,African-American,04/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56446,64389,58427,PRETRIAL,Quirama,Brian,A,Male,Hispanic,10/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +56446,64389,58427,PRETRIAL,Quirama,Brian,A,Male,Hispanic,10/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,4,High,8,Risk of Recidivism,1.09,10,High,New,1,0 +56446,64389,58427,PRETRIAL,Quirama,Brian,A,Male,Hispanic,10/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56476,64423,58457,Probation,Walker,Andrew,Anthony,Male,African-American,01/10/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +56476,64423,58457,Probation,Walker,Andrew,Anthony,Male,African-American,01/10/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +56476,64423,58457,Probation,Walker,Andrew,Anthony,Male,African-American,01/10/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56468,64415,58450,PRETRIAL,Daniels,Cleveland,NULL,Male,African-American,07/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/15/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +56468,64415,58450,PRETRIAL,Daniels,Cleveland,NULL,Male,African-American,07/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +56468,64415,58450,PRETRIAL,Daniels,Cleveland,NULL,Male,African-American,07/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/15/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56444,64387,58425,PRETRIAL,Davis,Marvin,NULL,Male,Other,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +56444,64387,58425,PRETRIAL,Davis,Marvin,NULL,Male,Other,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +56444,64387,58425,PRETRIAL,Davis,Marvin,NULL,Male,Other,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56451,64394,58432,PRETRIAL,RAMOS,DELVIN,NULL,Male,African-American,08/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +56451,64394,58432,PRETRIAL,RAMOS,DELVIN,NULL,Male,African-American,08/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,4,High,8,Risk of Recidivism,0.47,9,High,New,1,0 +56451,64394,58432,PRETRIAL,RAMOS,DELVIN,NULL,Male,African-American,08/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56463,64407,58443,Probation,Brown,Orpheus,NULL,Male,African-American,02/09/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +56463,64407,58443,Probation,Brown,Orpheus,NULL,Male,African-American,02/09/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +56463,64407,58443,Probation,Brown,Orpheus,NULL,Male,African-American,02/09/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +33269,64386,58424,PRETRIAL,kerr,javaughn,NULL,Male,Other,03/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,4,High,7,Risk of Violence,-0.38,10,High,New,1,0 +33269,64386,58424,PRETRIAL,kerr,javaughn,NULL,Male,Other,03/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,4,High,8,Risk of Recidivism,0.62,10,High,New,1,0 +33269,64386,58424,PRETRIAL,kerr,javaughn,NULL,Male,Other,03/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56478,64426,58460,Probation,McHugh,William,NULL,Male,Caucasian,05/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +56478,64426,58460,Probation,McHugh,William,NULL,Male,Caucasian,05/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +56478,64426,58460,Probation,McHugh,William,NULL,Male,Caucasian,05/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56453,64398,58435,Probation,sarmiento,maria,NULL,Female,Hispanic,12/03/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/15/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +56453,64398,58435,Probation,sarmiento,maria,NULL,Female,Hispanic,12/03/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +56453,64398,58435,Probation,sarmiento,maria,NULL,Female,Hispanic,12/03/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56461,64405,58441,PRETRIAL,BAXTER,JERAMAIH,LEE,Male,African-American,05/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/15/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +56461,64405,58441,PRETRIAL,BAXTER,JERAMAIH,LEE,Male,African-American,05/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +56461,64405,58441,PRETRIAL,BAXTER,JERAMAIH,LEE,Male,African-American,05/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/15/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56467,64412,58447,Probation,HANSEN,KELSEY,RAE,Male,Caucasian,06/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,New,1,0 +56467,64412,58447,Probation,HANSEN,KELSEY,RAE,Male,Caucasian,06/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +56467,64412,58447,Probation,HANSEN,KELSEY,RAE,Male,Caucasian,06/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +33913,64419,48383,PRETRIAL,PRINCE,JEAN,NULL,Male,African-American,12/02/70,17,All Scales,Intake,English,Pretrial,Jail Inmate,Married,8/15/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +33913,64419,48383,PRETRIAL,PRINCE,JEAN,NULL,Male,African-American,12/02/70,17,All Scales,Intake,English,Pretrial,Jail Inmate,Married,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +33913,64419,48383,PRETRIAL,PRINCE,JEAN,NULL,Male,African-American,12/02/70,17,All Scales,Intake,English,Pretrial,Jail Inmate,Married,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,19,2,Low,New,1,0 +56448,64391,58429,PRETRIAL,McCabe,Sean,NULL,Male,Caucasian,04/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +56448,64391,58429,PRETRIAL,McCabe,Sean,NULL,Male,Caucasian,04/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +56448,64391,58429,PRETRIAL,McCabe,Sean,NULL,Male,Caucasian,04/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56471,64417,58452,Probation,pollas,erica,NULL,Female,African-American,08/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.07,4,Low,New,1,0 +56471,64417,58452,Probation,pollas,erica,NULL,Female,African-American,08/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,8,High,New,1,0 +56471,64417,58452,Probation,pollas,erica,NULL,Female,African-American,08/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +4933,64396,4617,Probation,Tarr,Kevin,Michael,Male,Caucasian,02/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/15/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,Copy,1,0 +4933,64396,4617,Probation,Tarr,Kevin,Michael,Male,Caucasian,02/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,Copy,1,0 +4933,64396,4617,Probation,Tarr,Kevin,Michael,Male,Caucasian,02/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +55693,64403,57572,Probation,FLETCHER,MARK,ANTHONY,Male,African-American,08/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,Copy,1,0 +55693,64403,57572,Probation,FLETCHER,MARK,ANTHONY,Male,African-American,08/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,Copy,1,0 +55693,64403,57572,Probation,FLETCHER,MARK,ANTHONY,Male,African-American,08/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +56474,64421,58455,Probation,Olson,Ronald,NULL,Male,Hispanic,02/27/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +56474,64421,58455,Probation,Olson,Ronald,NULL,Male,Hispanic,02/27/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +56474,64421,58455,Probation,Olson,Ronald,NULL,Male,Hispanic,02/27/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56443,64385,58423,PRETRIAL,Walker,David,NULL,Male,African-American,04/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +56443,64385,58423,PRETRIAL,Walker,David,NULL,Male,African-American,04/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +56443,64385,58423,PRETRIAL,Walker,David,NULL,Male,African-American,04/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56469,64414,58449,Probation,Anthony,Fiorio,NULL,Male,Caucasian,04/30/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/15/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +56469,64414,58449,Probation,Anthony,Fiorio,NULL,Male,Caucasian,04/30/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +56469,64414,58449,Probation,Anthony,Fiorio,NULL,Male,Caucasian,04/30/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56450,64393,58431,PRETRIAL,McNair,Derek,NULL,Male,African-American,03/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/15/13 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +56450,64393,58431,PRETRIAL,McNair,Derek,NULL,Male,African-American,03/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/15/13 0:00,4,High,8,Risk of Recidivism,0.14,8,High,New,1,0 +56450,64393,58431,PRETRIAL,McNair,Derek,NULL,Male,African-American,03/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/15/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56462,64406,58442,Probation,CONSOLINI,ANNITA,F,Female,Hispanic,01/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +56462,64406,58442,Probation,CONSOLINI,ANNITA,F,Female,Hispanic,01/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +56462,64406,58442,Probation,CONSOLINI,ANNITA,F,Female,Hispanic,01/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52090,64427,58461,Probation,Yondolino,Anthony,NULL,Male,Caucasian,05/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.54,3,Low,New,1,0 +52090,64427,58461,Probation,Yondolino,Anthony,NULL,Male,Caucasian,05/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +52090,64427,58461,Probation,Yondolino,Anthony,NULL,Male,Caucasian,05/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56456,64401,58438,PRETRIAL,Penate,Eriam,NULL,Male,Hispanic,06/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/15/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +56456,64401,58438,PRETRIAL,Penate,Eriam,NULL,Male,Hispanic,06/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +56456,64401,58438,PRETRIAL,Penate,Eriam,NULL,Male,Hispanic,06/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56470,64416,58451,Probation,Juliussen,Denise,Maria,Female,Other,10/06/69,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/15/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +56470,64416,58451,Probation,Juliussen,Denise,Maria,Female,Other,10/06/69,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +56470,64416,58451,Probation,Juliussen,Denise,Maria,Female,Other,10/06/69,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56481,64430,58464,PRETRIAL,LUTZ,KEVIN,NULL,Male,Caucasian,08/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/15/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +56481,64430,58464,PRETRIAL,LUTZ,KEVIN,NULL,Male,Caucasian,08/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/15/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +56481,64430,58464,PRETRIAL,LUTZ,KEVIN,NULL,Male,Caucasian,08/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56445,64388,58426,PRETRIAL,DELGADO,ANGEL,V,Male,Hispanic,02/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +56445,64388,58426,PRETRIAL,DELGADO,ANGEL,V,Male,Hispanic,02/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +56445,64388,58426,PRETRIAL,DELGADO,ANGEL,V,Male,Hispanic,02/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56475,64422,58456,Probation,DAMES,LENORA,NULL,Female,African-American,05/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +56475,64422,58456,Probation,DAMES,LENORA,NULL,Female,African-American,05/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,9,High,New,1,0 +56475,64422,58456,Probation,DAMES,LENORA,NULL,Female,African-American,05/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +46534,64424,58458,PRETRIAL,Monestime,Judy,NULL,Female,African-American,04/08/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +46534,64424,58458,PRETRIAL,Monestime,Judy,NULL,Female,African-American,04/08/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +46534,64424,58458,PRETRIAL,Monestime,Judy,NULL,Female,African-American,04/08/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56489,64443,58476,Probation,Stypelkoski,Gary,NULL,Male,Caucasian,09/19/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +56489,64443,58476,Probation,Stypelkoski,Gary,NULL,Male,Caucasian,09/19/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +56489,64443,58476,Probation,Stypelkoski,Gary,NULL,Male,Caucasian,09/19/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56499,64458,58490,Probation,forges,martin,NULL,Male,African-American,02/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/16/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +56499,64458,58490,Probation,forges,martin,NULL,Male,African-American,02/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +56499,64458,58490,Probation,forges,martin,NULL,Male,African-American,02/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56491,64445,58478,Probation,bushing,michael,NULL,Male,Caucasian,12/20/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +56491,64445,58478,Probation,bushing,michael,NULL,Male,Caucasian,12/20/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +56491,64445,58478,Probation,bushing,michael,NULL,Male,Caucasian,12/20/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56483,64437,58470,PRETRIAL,Petit,Adrien,NULL,Male,African-American,04/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +56483,64437,58470,PRETRIAL,Petit,Adrien,NULL,Male,African-American,04/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +56483,64437,58470,PRETRIAL,Petit,Adrien,NULL,Male,African-American,04/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56503,64461,58493,Probation,morales,Justin,NULL,Male,Hispanic,06/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +56503,64461,58493,Probation,morales,Justin,NULL,Male,Hispanic,06/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +56503,64461,58493,Probation,morales,Justin,NULL,Male,Hispanic,06/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56486,64440,58473,PRETRIAL,Tanaka-Bustios,Kiyoshi,Christopher,Male,Caucasian,08/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +56486,64440,58473,PRETRIAL,Tanaka-Bustios,Kiyoshi,Christopher,Male,Caucasian,08/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +56486,64440,58473,PRETRIAL,Tanaka-Bustios,Kiyoshi,Christopher,Male,Caucasian,08/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56514,64474,58505,PRETRIAL,ROBERTSON,AUSTIN,NULL,Male,Caucasian,07/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +56514,64474,58505,PRETRIAL,ROBERTSON,AUSTIN,NULL,Male,Caucasian,07/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +56514,64474,58505,PRETRIAL,ROBERTSON,AUSTIN,NULL,Male,Caucasian,07/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56482,64435,58468,PRETRIAL,Reckley,Tercel,NULL,Male,Other,07/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +56482,64435,58468,PRETRIAL,Reckley,Tercel,NULL,Male,Other,07/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +56482,64435,58468,PRETRIAL,Reckley,Tercel,NULL,Male,Other,07/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +11131,64453,12106,PRETRIAL,nordelus,Whatley/ ronie,NULL,Male,African-American,03/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,Copy,1,0 +11131,64453,12106,PRETRIAL,nordelus,Whatley/ ronie,NULL,Male,African-American,03/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.94,10,High,Copy,1,0 +11131,64453,12106,PRETRIAL,nordelus,Whatley/ ronie,NULL,Male,African-American,03/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +45114,64432,58466,PRETRIAL,Shell,Ronald,NULL,Male,African-American,01/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +45114,64432,58466,PRETRIAL,Shell,Ronald,NULL,Male,African-American,01/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +45114,64432,58466,PRETRIAL,Shell,Ronald,NULL,Male,African-American,01/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56510,64468,58500,Probation,thomas,regina,NULL,Female,African-American,04/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +56510,64468,58500,Probation,thomas,regina,NULL,Female,African-American,04/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +56510,64468,58500,Probation,thomas,regina,NULL,Female,African-American,04/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56488,64442,58475,PRETRIAL,Gerson,Bruce,NULL,Male,Caucasian,04/04/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,7,Risk of Violence,-4.5,1,Low,New,1,0 +56488,64442,58475,PRETRIAL,Gerson,Bruce,NULL,Male,Caucasian,04/04/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,8,Risk of Recidivism,-2.92,1,Low,New,1,0 +56488,64442,58475,PRETRIAL,Gerson,Bruce,NULL,Male,Caucasian,04/04/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56501,64459,58491,PRETRIAL,Thompson,Curtis,NULL,Male,Caucasian,09/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/16/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +56501,64459,58491,PRETRIAL,Thompson,Curtis,NULL,Male,Caucasian,09/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/16/13 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +56501,64459,58491,PRETRIAL,Thompson,Curtis,NULL,Male,Caucasian,09/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56484,64438,58471,PRETRIAL,Belice,Junior,NULL,Male,Other,07/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +56484,64438,58471,PRETRIAL,Belice,Junior,NULL,Male,Other,07/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +56484,64438,58471,PRETRIAL,Belice,Junior,NULL,Male,Other,07/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56505,64463,58495,Probation,Walton,Keith,NULL,Male,Hispanic,07/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +56505,64463,58495,Probation,Walton,Keith,NULL,Male,Hispanic,07/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +56505,64463,58495,Probation,Walton,Keith,NULL,Male,Hispanic,07/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56513,64472,58504,PRETRIAL,Davis,Michael,NULL,Male,Caucasian,04/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/16/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +56513,64472,58504,PRETRIAL,Davis,Michael,NULL,Male,Caucasian,04/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +56513,64472,58504,PRETRIAL,Davis,Michael,NULL,Male,Caucasian,04/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/16/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +43501,64433,57449,PRETRIAL,JOHNSON,JOSHUA,NULL,Male,African-American,08/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,Copy,1,0 +43501,64433,57449,PRETRIAL,JOHNSON,JOSHUA,NULL,Male,African-American,08/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,Copy,1,0 +43501,64433,57449,PRETRIAL,JOHNSON,JOSHUA,NULL,Male,African-American,08/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +56498,64456,58488,Probation,Mendoza,Luis,NULL,Male,Hispanic,06/19/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/16/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +56498,64456,58488,Probation,Mendoza,Luis,NULL,Male,Hispanic,06/19/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +56498,64456,58488,Probation,Mendoza,Luis,NULL,Male,Hispanic,06/19/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +26724,64475,58506,PRETRIAL,DORAN,ASHLEY,NULL,Female,Caucasian,01/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +26724,64475,58506,PRETRIAL,DORAN,ASHLEY,NULL,Female,Caucasian,01/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,10,High,New,1,0 +26724,64475,58506,PRETRIAL,DORAN,ASHLEY,NULL,Female,Caucasian,01/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +46498,64447,58480,PRETRIAL,Bien-Aime,Emelio,NULL,Male,African-American,03/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +46498,64447,58480,PRETRIAL,Bien-Aime,Emelio,NULL,Male,African-American,03/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +46498,64447,58480,PRETRIAL,Bien-Aime,Emelio,NULL,Male,African-American,03/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56496,64454,58486,PRETRIAL,Williams,Brenda,NULL,Female,African-American,12/10/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +56496,64454,58486,PRETRIAL,Williams,Brenda,NULL,Female,African-American,12/10/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +56496,64454,58486,PRETRIAL,Williams,Brenda,NULL,Female,African-American,12/10/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +28953,64477,58508,Probation,Caleb,Robert,NULL,Male,Caucasian,11/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +28953,64477,58508,Probation,Caleb,Robert,NULL,Male,Caucasian,11/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +28953,64477,58508,Probation,Caleb,Robert,NULL,Male,Caucasian,11/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +48501,64452,58485,PRETRIAL,Mccormick,Terry,NULL,Male,Caucasian,04/26/60,17,All Scales,Intake,English,Other,Probation,Divorced,8/16/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +48501,64452,58485,PRETRIAL,Mccormick,Terry,NULL,Male,Caucasian,04/26/60,17,All Scales,Intake,English,Other,Probation,Divorced,8/16/13 0:00,1,Low,8,Risk of Recidivism,-0.39,4,Low,New,1,0 +48501,64452,58485,PRETRIAL,Mccormick,Terry,NULL,Male,Caucasian,04/26/60,17,All Scales,Intake,English,Other,Probation,Divorced,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,43,10,High,New,1,0 +55273,64473,57096,Probation,Watson,Careem,NULL,Male,African-American,09/09/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +55273,64473,57096,Probation,Watson,Careem,NULL,Male,African-American,09/09/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,4,Low,New,1,0 +55273,64473,57096,Probation,Watson,Careem,NULL,Male,African-American,09/09/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,2,Medium,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +56490,64444,58477,Probation,HARRIS,CARMEL,CONRAD,Male,African-American,12/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +56490,64444,58477,Probation,HARRIS,CARMEL,CONRAD,Male,African-American,12/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +56490,64444,58477,Probation,HARRIS,CARMEL,CONRAD,Male,African-American,12/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56507,64465,58497,PRETRIAL,bennett,melissa,NULL,Female,Caucasian,02/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/16/13 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +56507,64465,58497,PRETRIAL,bennett,melissa,NULL,Female,Caucasian,02/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +56507,64465,58497,PRETRIAL,bennett,melissa,NULL,Female,Caucasian,02/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/16/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +56500,64457,58489,PRETRIAL,PRESTON,MICHAEL,NULL,Male,Caucasian,07/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/16/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +56500,64457,58489,PRETRIAL,PRESTON,MICHAEL,NULL,Male,Caucasian,07/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +56500,64457,58489,PRETRIAL,PRESTON,MICHAEL,NULL,Male,Caucasian,07/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +3794,64436,58469,PRETRIAL,Nowell,Justin,NULL,Male,African-American,02/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +3794,64436,58469,PRETRIAL,Nowell,Justin,NULL,Male,African-American,02/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +3794,64436,58469,PRETRIAL,Nowell,Justin,NULL,Male,African-American,02/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +33607,64470,58502,PRETRIAL,Jackson,Laquetta,NULL,Female,African-American,10/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +33607,64470,58502,PRETRIAL,Jackson,Laquetta,NULL,Female,African-American,10/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +33607,64470,58502,PRETRIAL,Jackson,Laquetta,NULL,Female,African-American,10/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +56485,64439,58472,PRETRIAL,Burks,Deon,NULL,Male,African-American,12/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +56485,64439,58472,PRETRIAL,Burks,Deon,NULL,Male,African-American,12/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +56485,64439,58472,PRETRIAL,Burks,Deon,NULL,Male,African-American,12/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56516,64478,58509,PRETRIAL,Zuniga,Guillermo,NULL,Male,Caucasian,06/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/16/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +56516,64478,58509,PRETRIAL,Zuniga,Guillermo,NULL,Male,Caucasian,06/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +56516,64478,58509,PRETRIAL,Zuniga,Guillermo,NULL,Male,Caucasian,06/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56494,64449,58482,Probation,WILSON,CHRISTOPHER,OHARA,Male,Caucasian,08/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/16/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +56494,64449,58482,Probation,WILSON,CHRISTOPHER,OHARA,Male,Caucasian,08/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +56494,64449,58482,Probation,WILSON,CHRISTOPHER,OHARA,Male,Caucasian,08/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56487,64441,58474,PRETRIAL,Rosenbrier,Nicholas,NULL,Male,Caucasian,09/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,New,1,0 +56487,64441,58474,PRETRIAL,Rosenbrier,Nicholas,NULL,Male,Caucasian,09/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +56487,64441,58474,PRETRIAL,Rosenbrier,Nicholas,NULL,Male,Caucasian,09/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56497,64455,58487,Probation,Baker,Michelle,NULL,Female,Caucasian,12/26/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/16/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +56497,64455,58487,Probation,Baker,Michelle,NULL,Female,Caucasian,12/26/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +56497,64455,58487,Probation,Baker,Michelle,NULL,Female,Caucasian,12/26/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56504,64462,58494,PRETRIAL,Rapone,Peter,Anthony,Male,Caucasian,12/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +56504,64462,58494,PRETRIAL,Rapone,Peter,Anthony,Male,Caucasian,12/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +56504,64462,58494,PRETRIAL,Rapone,Peter,Anthony,Male,Caucasian,12/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56511,64469,58501,Probation,Major,Eureka,NULL,Female,African-American,10/04/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,2,Medium,7,Risk of Violence,-2.94,2,Low,New,1,0 +56511,64469,58501,Probation,Major,Eureka,NULL,Female,African-American,10/04/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +56511,64469,58501,Probation,Major,Eureka,NULL,Female,African-American,10/04/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +20971,64434,58467,PRETRIAL,Lindsay,Ruel,NULL,Male,Other,05/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/16/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +20971,64434,58467,PRETRIAL,Lindsay,Ruel,NULL,Male,Other,05/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +20971,64434,58467,PRETRIAL,Lindsay,Ruel,NULL,Male,Other,05/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56493,64448,58481,Probation,Hall,Lindon,NULL,Male,African-American,04/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/16/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +56493,64448,58481,Probation,Hall,Lindon,NULL,Male,African-American,04/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +56493,64448,58481,Probation,Hall,Lindon,NULL,Male,African-American,04/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +56495,64450,58483,Probation,Lombardi,Dane,Christian,Male,Caucasian,12/15/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/16/13 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +56495,64450,58483,Probation,Lombardi,Dane,Christian,Male,Caucasian,12/15/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +56495,64450,58483,Probation,Lombardi,Dane,Christian,Male,Caucasian,12/15/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/16/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56509,64467,58499,Probation,Asendorf,Heather,NULL,Female,Caucasian,03/04/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +56509,64467,58499,Probation,Asendorf,Heather,NULL,Female,Caucasian,03/04/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +56509,64467,58499,Probation,Asendorf,Heather,NULL,Female,Caucasian,03/04/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,29,9,High,New,1,0 +56492,64446,58479,Probation,smith,lakeeta,NULL,Male,African-American,05/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/16/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +56492,64446,58479,Probation,smith,lakeeta,NULL,Male,African-American,05/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/16/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +56492,64446,58479,Probation,smith,lakeeta,NULL,Male,African-American,05/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56506,64464,58496,Probation,thomas,vilma,NULL,Female,African-American,08/21/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,7,Risk of Violence,-4.56,1,Low,New,1,0 +56506,64464,58496,Probation,thomas,vilma,NULL,Female,African-American,08/21/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +56506,64464,58496,Probation,thomas,vilma,NULL,Female,African-American,08/21/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +43397,64481,43336,PRETRIAL,Hay,Brian,NULL,Male,Caucasian,06/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,Copy,1,0 +43397,64481,43336,PRETRIAL,Hay,Brian,NULL,Male,Caucasian,06/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,Copy,1,0 +43397,64481,43336,PRETRIAL,Hay,Brian,NULL,Male,Caucasian,06/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +56522,64485,58515,PRETRIAL,Stringer,Samesha,NULL,Female,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +56522,64485,58515,PRETRIAL,Stringer,Samesha,NULL,Female,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +56522,64485,58515,PRETRIAL,Stringer,Samesha,NULL,Female,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56520,64483,58513,PRETRIAL,Tillman,Latischa,NULL,Male,African-American,10/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +56520,64483,58513,PRETRIAL,Tillman,Latischa,NULL,Male,African-American,10/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +56520,64483,58513,PRETRIAL,Tillman,Latischa,NULL,Male,African-American,10/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +44632,64490,44762,PRETRIAL,Gosnell,Mark,NULL,Male,Caucasian,12/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,Copy,1,0 +44632,64490,44762,PRETRIAL,Gosnell,Mark,NULL,Male,Caucasian,12/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,Copy,1,0 +44632,64490,44762,PRETRIAL,Gosnell,Mark,NULL,Male,Caucasian,12/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +56518,64480,58511,PRETRIAL,HANON,EUGENE,NULL,Male,African-American,12/14/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +56518,64480,58511,PRETRIAL,HANON,EUGENE,NULL,Male,African-American,12/14/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +56518,64480,58511,PRETRIAL,HANON,EUGENE,NULL,Male,African-American,12/14/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56523,64486,58516,PRETRIAL,Parks,Claudette,NULL,Female,Other,10/07/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/17/13 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +56523,64486,58516,PRETRIAL,Parks,Claudette,NULL,Female,Other,10/07/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/17/13 0:00,1,Low,8,Risk of Recidivism,-2.64,1,Low,New,1,0 +56523,64486,58516,PRETRIAL,Parks,Claudette,NULL,Female,Other,10/07/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56525,64488,58518,PRETRIAL,Wells,Barry,NULL,Male,African-American,01/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +56525,64488,58518,PRETRIAL,Wells,Barry,NULL,Male,African-American,01/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +56525,64488,58518,PRETRIAL,Wells,Barry,NULL,Male,African-American,01/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56521,64484,58514,PRETRIAL,Beneby,Taro,NULL,Male,African-American,11/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +56521,64484,58514,PRETRIAL,Beneby,Taro,NULL,Male,African-American,11/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +56521,64484,58514,PRETRIAL,Beneby,Taro,NULL,Male,African-American,11/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56526,64489,58519,PRETRIAL,SANTOS,TYRONE,ANTONIO,Male,African-American,07/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +56526,64489,58519,PRETRIAL,SANTOS,TYRONE,ANTONIO,Male,African-American,07/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +56526,64489,58519,PRETRIAL,SANTOS,TYRONE,ANTONIO,Male,African-American,07/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56519,64482,58512,PRETRIAL,HYMAN,ANTWON,NULL,Male,African-American,09/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +56519,64482,58512,PRETRIAL,HYMAN,ANTWON,NULL,Male,African-American,09/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +56519,64482,58512,PRETRIAL,HYMAN,ANTWON,NULL,Male,African-American,09/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56524,64487,58517,PRETRIAL,DENNIS,LORENE,MARTELY,Male,Other,05/26/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/17/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +56524,64487,58517,PRETRIAL,DENNIS,LORENE,MARTELY,Male,Other,05/26/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/17/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +56524,64487,58517,PRETRIAL,DENNIS,LORENE,MARTELY,Male,Other,05/26/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56517,64479,58510,PRETRIAL,Hyman,Clifford,NULL,Male,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +56517,64479,58510,PRETRIAL,Hyman,Clifford,NULL,Male,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +56517,64479,58510,PRETRIAL,Hyman,Clifford,NULL,Male,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56530,64495,58523,PRETRIAL,Littleton,Phylicia,NULL,Female,African-American,03/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +56530,64495,58523,PRETRIAL,Littleton,Phylicia,NULL,Female,African-American,03/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +56530,64495,58523,PRETRIAL,Littleton,Phylicia,NULL,Female,African-American,03/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56528,64493,58521,PRETRIAL,KOURY,SAMUEL,JUDE,Male,Caucasian,01/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +56528,64493,58521,PRETRIAL,KOURY,SAMUEL,JUDE,Male,Caucasian,01/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +56528,64493,58521,PRETRIAL,KOURY,SAMUEL,JUDE,Male,Caucasian,01/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56532,64498,58526,PRETRIAL,Russell,Trevor,NULL,Male,African-American,02/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/18/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +56532,64498,58526,PRETRIAL,Russell,Trevor,NULL,Male,African-American,02/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/18/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +56532,64498,58526,PRETRIAL,Russell,Trevor,NULL,Male,African-American,02/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56529,64494,58522,PRETRIAL,RAYMOND,EMMANUEL,NULL,Male,African-American,07/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +56529,64494,58522,PRETRIAL,RAYMOND,EMMANUEL,NULL,Male,African-American,07/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +56529,64494,58522,PRETRIAL,RAYMOND,EMMANUEL,NULL,Male,African-American,07/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +9038,64496,58524,PRETRIAL,HINES,JAMES,CARL,Male,Caucasian,05/11/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/18/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +9038,64496,58524,PRETRIAL,HINES,JAMES,CARL,Male,Caucasian,05/11/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/18/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +9038,64496,58524,PRETRIAL,HINES,JAMES,CARL,Male,Caucasian,05/11/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/18/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +29994,64491,50439,Probation,SELLARS,ROBERT,PAUL,Male,Caucasian,04/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,4,High,7,Risk of Violence,-1.11,8,High,Copy,1,0 +29994,64491,50439,Probation,SELLARS,ROBERT,PAUL,Male,Caucasian,04/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,4,High,8,Risk of Recidivism,0.84,10,High,Copy,1,0 +29994,64491,50439,Probation,SELLARS,ROBERT,PAUL,Male,Caucasian,04/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,4,High,18,Risk of Failure to Appear,41,10,High,Copy,1,0 +56527,64492,58520,PRETRIAL,GRANT,JASON,NULL,Male,African-American,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +56527,64492,58520,PRETRIAL,GRANT,JASON,NULL,Male,African-American,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +56527,64492,58520,PRETRIAL,GRANT,JASON,NULL,Male,African-American,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56531,64497,58525,PRETRIAL,REMBERT,WESLEY,CARDELL,Male,African-American,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +56531,64497,58525,PRETRIAL,REMBERT,WESLEY,CARDELL,Male,African-American,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +56531,64497,58525,PRETRIAL,REMBERT,WESLEY,CARDELL,Male,African-American,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +56536,64502,58530,PRETRIAL,MUNOZ,LALO,NULL,Male,Caucasian,10/11/38,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +56536,64502,58530,PRETRIAL,MUNOZ,LALO,NULL,Male,Caucasian,10/11/38,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +56536,64502,58530,PRETRIAL,MUNOZ,LALO,NULL,Male,Caucasian,10/11/38,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +25454,64527,58552,PRETRIAL,BENDE,ALEXANDER,MICHAEL,Male,Caucasian,04/30/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +25454,64527,58552,PRETRIAL,BENDE,ALEXANDER,MICHAEL,Male,Caucasian,04/30/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +25454,64527,58552,PRETRIAL,BENDE,ALEXANDER,MICHAEL,Male,Caucasian,04/30/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56556,64536,58561,PRETRIAL,IAKOVAKES,JIMMY,NULL,Male,Caucasian,10/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +56556,64536,58561,PRETRIAL,IAKOVAKES,JIMMY,NULL,Male,Caucasian,10/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +56556,64536,58561,PRETRIAL,IAKOVAKES,JIMMY,NULL,Male,Caucasian,10/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56539,64506,58534,PRETRIAL,Howard,Kelvin,NULL,Male,African-American,06/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +56539,64506,58534,PRETRIAL,Howard,Kelvin,NULL,Male,African-American,06/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +56539,64506,58534,PRETRIAL,Howard,Kelvin,NULL,Male,African-American,06/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56550,64523,58550,Probation,Romain,Amy,NULL,Female,Caucasian,06/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +56550,64523,58550,Probation,Romain,Amy,NULL,Female,Caucasian,06/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +56550,64523,58550,Probation,Romain,Amy,NULL,Female,Caucasian,06/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56548,64518,58545,Probation,Olive,Marilia,serna,Female,Caucasian,04/14/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +56548,64518,58545,Probation,Olive,Marilia,serna,Female,Caucasian,04/14/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +56548,64518,58545,Probation,Olive,Marilia,serna,Female,Caucasian,04/14/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56553,64532,58557,Probation,carbone,peter,NULL,Male,Caucasian,07/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +56553,64532,58557,Probation,carbone,peter,NULL,Male,Caucasian,07/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +56553,64532,58557,Probation,carbone,peter,NULL,Male,Caucasian,07/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +45079,64539,58564,PRETRIAL,RIVERA,PEDRO,A,Male,Other,04/11/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +45079,64539,58564,PRETRIAL,RIVERA,PEDRO,A,Male,Other,04/11/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +45079,64539,58564,PRETRIAL,RIVERA,PEDRO,A,Male,Other,04/11/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +41750,64553,58577,Probation,davenport,branden,NULL,Male,African-American,02/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +41750,64553,58577,Probation,davenport,branden,NULL,Male,African-American,02/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +41750,64553,58577,Probation,davenport,branden,NULL,Male,African-American,02/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55984,64541,57908,PRETRIAL,Remis,Alejandro,NULL,Male,Caucasian,10/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,Copy,1,0 +55984,64541,57908,PRETRIAL,Remis,Alejandro,NULL,Male,Caucasian,10/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,Copy,1,0 +55984,64541,57908,PRETRIAL,Remis,Alejandro,NULL,Male,Caucasian,10/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +56544,64511,58539,PRETRIAL,Lewis,Jarvis,NULL,Male,African-American,10/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +56544,64511,58539,PRETRIAL,Lewis,Jarvis,NULL,Male,African-American,10/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +56544,64511,58539,PRETRIAL,Lewis,Jarvis,NULL,Male,African-American,10/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +9384,64513,58541,Probation,Cioutier,Kenneth,NULL,Male,Caucasian,03/11/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +9384,64513,58541,Probation,Cioutier,Kenneth,NULL,Male,Caucasian,03/11/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +9384,64513,58541,Probation,Cioutier,Kenneth,NULL,Male,Caucasian,03/11/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +46212,64520,58547,PRETRIAL,JeanBaptiste,Wilbert,NULL,Male,African-American,06/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +46212,64520,58547,PRETRIAL,JeanBaptiste,Wilbert,NULL,Male,African-American,06/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +46212,64520,58547,PRETRIAL,JeanBaptiste,Wilbert,NULL,Male,African-American,06/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47935,64534,58559,PRETRIAL,Gilles,Andson,NULL,Male,African-American,10/02/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/19/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +47935,64534,58559,PRETRIAL,Gilles,Andson,NULL,Male,African-American,10/02/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +47935,64534,58559,PRETRIAL,Gilles,Andson,NULL,Male,African-American,10/02/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56565,64548,58572,Probation,AGUILAR,JIMMY,J,Male,Hispanic,12/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +56565,64548,58572,Probation,AGUILAR,JIMMY,J,Male,Hispanic,12/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +56565,64548,58572,Probation,AGUILAR,JIMMY,J,Male,Hispanic,12/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +36952,64555,58579,PRETRIAL,Sherbondy,John,NULL,Male,African-American,12/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +36952,64555,58579,PRETRIAL,Sherbondy,John,NULL,Male,African-American,12/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +36952,64555,58579,PRETRIAL,Sherbondy,John,NULL,Male,African-American,12/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55928,64525,57850,PRETRIAL,Micoff,Michelle,NULL,Female,Caucasian,06/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,Copy,1,0 +55928,64525,57850,PRETRIAL,Micoff,Michelle,NULL,Female,Caucasian,06/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,Copy,1,0 +55928,64525,57850,PRETRIAL,Micoff,Michelle,NULL,Female,Caucasian,06/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,Copy,1,0 +56538,64504,58532,PRETRIAL,Eubanks,Terrinna,NULL,Female,African-American,02/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +56538,64504,58532,PRETRIAL,Eubanks,Terrinna,NULL,Female,African-American,02/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +56538,64504,58532,PRETRIAL,Eubanks,Terrinna,NULL,Female,African-American,02/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56558,64538,58563,Probation,Slowinski,William,NULL,Male,Caucasian,12/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/19/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +56558,64538,58563,Probation,Slowinski,William,NULL,Male,Caucasian,12/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/19/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +56558,64538,58563,Probation,Slowinski,William,NULL,Male,Caucasian,12/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56563,64546,58570,Probation,Pineda,Fatima,NULL,Female,Hispanic,12/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +56563,64546,58570,Probation,Pineda,Fatima,NULL,Female,Hispanic,12/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +56563,64546,58570,Probation,Pineda,Fatima,NULL,Female,Hispanic,12/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56533,64499,58527,PRETRIAL,Souffrant,Yves,NULL,Male,Other,10/16/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,8/19/13 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +56533,64499,58527,PRETRIAL,Souffrant,Yves,NULL,Male,Other,10/16/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,8/19/13 0:00,1,Low,8,Risk of Recidivism,-2.77,1,Low,New,1,0 +56533,64499,58527,PRETRIAL,Souffrant,Yves,NULL,Male,Other,10/16/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56547,64517,58544,Probation,Holmes,Laqunta,NULL,Female,African-American,05/04/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +56547,64517,58544,Probation,Holmes,Laqunta,NULL,Female,African-American,05/04/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +56547,64517,58544,Probation,Holmes,Laqunta,NULL,Female,African-American,05/04/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +10467,64530,58555,Probation,Brantman,Jason,Michael,Male,Caucasian,02/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +10467,64530,58555,Probation,Brantman,Jason,Michael,Male,Caucasian,02/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +10467,64530,58555,Probation,Brantman,Jason,Michael,Male,Caucasian,02/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56535,64501,58529,PRETRIAL,DAVIS,SECCUNDA,NULL,Male,African-American,05/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +56535,64501,58529,PRETRIAL,DAVIS,SECCUNDA,NULL,Male,African-American,05/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +56535,64501,58529,PRETRIAL,DAVIS,SECCUNDA,NULL,Male,African-American,05/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +24830,64515,58543,Probation,vilme,valerie,NULL,Female,African-American,07/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +24830,64515,58543,Probation,vilme,valerie,NULL,Female,African-American,07/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +24830,64515,58543,Probation,vilme,valerie,NULL,Female,African-American,07/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56568,64551,58575,Probation,meyer,richard,NULL,Male,African-American,10/31/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +56568,64551,58575,Probation,meyer,richard,NULL,Male,African-American,10/31/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +56568,64551,58575,Probation,meyer,richard,NULL,Male,African-American,10/31/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +8505,64522,58549,PRETRIAL,ARCILA,ALEX,NULL,Male,Hispanic,05/04/80,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/19/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +8505,64522,58549,PRETRIAL,ARCILA,ALEX,NULL,Male,Hispanic,05/04/80,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/19/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +8505,64522,58549,PRETRIAL,ARCILA,ALEX,NULL,Male,Hispanic,05/04/80,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56540,64507,58535,PRETRIAL,Cooper,Darriss,Lamar,Male,African-American,10/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +56540,64507,58535,PRETRIAL,Cooper,Darriss,Lamar,Male,African-American,10/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +56540,64507,58535,PRETRIAL,Cooper,Darriss,Lamar,Male,African-American,10/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56542,64509,58537,PRETRIAL,Hill,Jerome,NULL,Male,African-American,01/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +56542,64509,58537,PRETRIAL,Hill,Jerome,NULL,Male,African-American,01/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +56542,64509,58537,PRETRIAL,Hill,Jerome,NULL,Male,African-American,01/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56562,64543,58567,PRETRIAL,Mclaughlin,Leland,NULL,Male,Caucasian,01/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/19/13 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +56562,64543,58567,PRETRIAL,Mclaughlin,Leland,NULL,Male,Caucasian,01/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/19/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +56562,64543,58567,PRETRIAL,Mclaughlin,Leland,NULL,Male,Caucasian,01/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56554,64533,58558,Probation,Harvey,Michael,NULL,Male,Caucasian,10/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +56554,64533,58558,Probation,Harvey,Michael,NULL,Male,Caucasian,10/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +56554,64533,58558,Probation,Harvey,Michael,NULL,Male,Caucasian,10/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +47194,64505,58533,PRETRIAL,Fuentes,Darryl,NULL,Male,African-American,12/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,2,Medium,7,Risk of Violence,-1.26,7,Medium,New,1,0 +47194,64505,58533,PRETRIAL,Fuentes,Darryl,NULL,Male,African-American,12/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +47194,64505,58533,PRETRIAL,Fuentes,Darryl,NULL,Male,African-American,12/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56545,64512,58540,PRETRIAL,Valencia,Jesus,David,Male,Caucasian,07/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +56545,64512,58540,PRETRIAL,Valencia,Jesus,David,Male,Caucasian,07/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +56545,64512,58540,PRETRIAL,Valencia,Jesus,David,Male,Caucasian,07/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +37126,64519,58546,DRRD,Fish,Jonathan,Thomas,Male,Other,12/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +37126,64519,58546,DRRD,Fish,Jonathan,Thomas,Male,Other,12/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +37126,64519,58546,DRRD,Fish,Jonathan,Thomas,Male,Other,12/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56564,64547,58571,Probation,weiss,carmen,NULL,Female,Caucasian,07/23/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +56564,64547,58571,Probation,weiss,carmen,NULL,Female,Caucasian,07/23/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +56564,64547,58571,Probation,weiss,carmen,NULL,Female,Caucasian,07/23/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56570,64554,58578,PRETRIAL,Manasse,Rochilun,NULL,Male,Other,04/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/19/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +56570,64554,58578,PRETRIAL,Manasse,Rochilun,NULL,Male,Other,04/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/19/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +56570,64554,58578,PRETRIAL,Manasse,Rochilun,NULL,Male,Other,04/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55928,64526,57850,PRETRIAL,Micoff,Michelle,NULL,Female,Caucasian,06/27/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,Copy,1,0 +55928,64526,57850,PRETRIAL,Micoff,Michelle,NULL,Female,Caucasian,06/27/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,4,High,8,Risk of Recidivism,0.14,9,High,Copy,1,0 +55928,64526,57850,PRETRIAL,Micoff,Michelle,NULL,Female,Caucasian,06/27/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,4,High,18,Risk of Failure to Appear,27,8,High,Copy,1,0 +56543,64510,58538,PRETRIAL,Gustave,Julietta,NULL,Female,Other,11/04/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +56543,64510,58538,PRETRIAL,Gustave,Julietta,NULL,Female,Other,11/04/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/13 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +56543,64510,58538,PRETRIAL,Gustave,Julietta,NULL,Female,Other,11/04/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56559,64540,58565,Probation,Burns,Jovonna,Nicole,Female,African-American,08/24/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +56559,64540,58565,Probation,Burns,Jovonna,Nicole,Female,African-American,08/24/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +56559,64540,58565,Probation,Burns,Jovonna,Nicole,Female,African-American,08/24/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56552,64531,58556,PRETRIAL,WESLEY,SAMUEL,M,Male,African-American,05/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +56552,64531,58556,PRETRIAL,WESLEY,SAMUEL,M,Male,African-American,05/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +56552,64531,58556,PRETRIAL,WESLEY,SAMUEL,M,Male,African-American,05/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56546,64514,58542,PRETRIAL,GAINES,DENA,NULL,Female,Caucasian,07/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +56546,64514,58542,PRETRIAL,GAINES,DENA,NULL,Female,Caucasian,07/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +56546,64514,58542,PRETRIAL,GAINES,DENA,NULL,Female,Caucasian,07/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +47934,64528,58553,PRETRIAL,Bienaime,Losaire,NULL,Male,African-American,02/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +47934,64528,58553,PRETRIAL,Bienaime,Losaire,NULL,Male,African-American,02/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +47934,64528,58553,PRETRIAL,Bienaime,Losaire,NULL,Male,African-American,02/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +47412,64535,58560,PRETRIAL,Carrie,John,R,Male,Caucasian,12/27/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +47412,64535,58560,PRETRIAL,Carrie,John,R,Male,Caucasian,12/27/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +47412,64535,58560,PRETRIAL,Carrie,John,R,Male,Caucasian,12/27/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56566,64549,58573,Probation,Tome,Henry,NULL,Male,Hispanic,09/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/19/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +56566,64549,58573,Probation,Tome,Henry,NULL,Male,Hispanic,09/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/19/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +56566,64549,58573,Probation,Tome,Henry,NULL,Male,Hispanic,09/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56541,64508,58536,PRETRIAL,SCHMALHAUS,DAGOBRET,NULL,Male,Caucasian,12/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/13 0:00,1,Low,7,Risk of Violence,-4.29,1,Low,New,1,0 +56541,64508,58536,PRETRIAL,SCHMALHAUS,DAGOBRET,NULL,Male,Caucasian,12/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/13 0:00,1,Low,8,Risk of Recidivism,-2.66,1,Low,New,1,0 +56541,64508,58536,PRETRIAL,SCHMALHAUS,DAGOBRET,NULL,Male,Caucasian,12/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56560,64542,58566,Probation,McFadden,Patrick,NULL,Male,Caucasian,03/09/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +56560,64542,58566,Probation,McFadden,Patrick,NULL,Male,Caucasian,03/09/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +56560,64542,58566,Probation,McFadden,Patrick,NULL,Male,Caucasian,03/09/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56534,64500,58528,PRETRIAL,Walling,Nicole,NULL,Female,Caucasian,05/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +56534,64500,58528,PRETRIAL,Walling,Nicole,NULL,Female,Caucasian,05/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +56534,64500,58528,PRETRIAL,Walling,Nicole,NULL,Female,Caucasian,05/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56567,64550,58574,Probation,Escobar deleon,Marlon,NULL,Male,Hispanic,05/11/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/19/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +56567,64550,58574,Probation,Escobar deleon,Marlon,NULL,Male,Hispanic,05/11/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +56567,64550,58574,Probation,Escobar deleon,Marlon,NULL,Male,Hispanic,05/11/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56537,64503,58531,PRETRIAL,Jennings,Jeremiah,NULL,Male,African-American,09/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +56537,64503,58531,PRETRIAL,Jennings,Jeremiah,NULL,Male,African-American,09/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +56537,64503,58531,PRETRIAL,Jennings,Jeremiah,NULL,Male,African-American,09/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56549,64521,58548,PRETRIAL,Mcgrath,Evan,NULL,Male,Caucasian,09/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +56549,64521,58548,PRETRIAL,Mcgrath,Evan,NULL,Male,Caucasian,09/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +56549,64521,58548,PRETRIAL,Mcgrath,Evan,NULL,Male,Caucasian,09/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +15044,64545,58569,Probation,geiger,joseph,NULL,Male,Caucasian,12/26/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +15044,64545,58569,Probation,geiger,joseph,NULL,Male,Caucasian,12/26/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +15044,64545,58569,Probation,geiger,joseph,NULL,Male,Caucasian,12/26/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56569,64552,58576,Probation,JURZYK,ROBERT,P,Male,Caucasian,03/10/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +56569,64552,58576,Probation,JURZYK,ROBERT,P,Male,Caucasian,03/10/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +56569,64552,58576,Probation,JURZYK,ROBERT,P,Male,Caucasian,03/10/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +36838,64524,58551,Probation,Nemet,Thomas,NULL,Male,Caucasian,08/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.77,2,Low,New,1,0 +36838,64524,58551,Probation,Nemet,Thomas,NULL,Male,Caucasian,08/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +36838,64524,58551,Probation,Nemet,Thomas,NULL,Male,Caucasian,08/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +56003,64516,57925,PRETRIAL,ZEPEDA,KEVIN,NULL,Male,Caucasian,05/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,Copy,1,0 +56003,64516,57925,PRETRIAL,ZEPEDA,KEVIN,NULL,Male,Caucasian,05/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,Copy,1,0 +56003,64516,57925,PRETRIAL,ZEPEDA,KEVIN,NULL,Male,Caucasian,05/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +54232,64566,58590,PRETRIAL,Jaramillo,Adiel,NULL,Male,Caucasian,11/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +54232,64566,58590,PRETRIAL,Jaramillo,Adiel,NULL,Male,Caucasian,11/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +54232,64566,58590,PRETRIAL,Jaramillo,Adiel,NULL,Male,Caucasian,11/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56598,64594,58614,Probation,Gonzalez,Eddie,NULL,Male,Hispanic,03/09/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/20/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +56598,64594,58614,Probation,Gonzalez,Eddie,NULL,Male,Hispanic,03/09/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +56598,64594,58614,Probation,Gonzalez,Eddie,NULL,Male,Hispanic,03/09/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56573,64558,58582,PRETRIAL,Natour,Randa,NULL,Female,Caucasian,02/16/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/20/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +56573,64558,58582,PRETRIAL,Natour,Randa,NULL,Female,Caucasian,02/16/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/20/13 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +56573,64558,58582,PRETRIAL,Natour,Randa,NULL,Female,Caucasian,02/16/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +2609,64560,58584,PRETRIAL,MILLA,MICHAEL,LEWIS,Male,Hispanic,05/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +2609,64560,58584,PRETRIAL,MILLA,MICHAEL,LEWIS,Male,Hispanic,05/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +2609,64560,58584,PRETRIAL,MILLA,MICHAEL,LEWIS,Male,Hispanic,05/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56585,64573,58597,Probation,Denihan,Kelly,NULL,Female,Caucasian,11/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +56585,64573,58597,Probation,Denihan,Kelly,NULL,Female,Caucasian,11/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +56585,64573,58597,Probation,Denihan,Kelly,NULL,Female,Caucasian,11/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +56609,64607,58627,PRETRIAL,Lopez,Kathleen,NULL,Female,Hispanic,10/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/20/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +56609,64607,58627,PRETRIAL,Lopez,Kathleen,NULL,Female,Hispanic,10/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +56609,64607,58627,PRETRIAL,Lopez,Kathleen,NULL,Female,Hispanic,10/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +42131,64579,58602,PRETRIAL,RAINES,MARCONI,NULL,Male,Caucasian,12/18/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +42131,64579,58602,PRETRIAL,RAINES,MARCONI,NULL,Male,Caucasian,12/18/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +42131,64579,58602,PRETRIAL,RAINES,MARCONI,NULL,Male,Caucasian,12/18/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56589,64581,58603,PRETRIAL,PLUMMER,ROMAINE,NULL,Male,African-American,06/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,4,High,7,Risk of Violence,-0.61,10,High,New,1,0 +56589,64581,58603,PRETRIAL,PLUMMER,ROMAINE,NULL,Male,African-American,06/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +56589,64581,58603,PRETRIAL,PLUMMER,ROMAINE,NULL,Male,African-American,06/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50660,64586,58607,PRETRIAL,Sharpe,Bernard,NULL,Male,African-American,08/22/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +50660,64586,58607,PRETRIAL,Sharpe,Bernard,NULL,Male,African-American,08/22/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,4,High,8,Risk of Recidivism,0.19,8,High,New,1,0 +50660,64586,58607,PRETRIAL,Sharpe,Bernard,NULL,Male,African-American,08/22/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56583,64571,58595,Probation,Levesque,Rebecca,NULL,Male,Caucasian,07/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/20/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +56583,64571,58595,Probation,Levesque,Rebecca,NULL,Male,Caucasian,07/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +56583,64571,58595,Probation,Levesque,Rebecca,NULL,Male,Caucasian,07/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56594,64589,58609,PRETRIAL,Dawson,Janet,NULL,Female,Caucasian,02/28/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +56594,64589,58609,PRETRIAL,Dawson,Janet,NULL,Female,Caucasian,02/28/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +56594,64589,58609,PRETRIAL,Dawson,Janet,NULL,Female,Caucasian,02/28/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56580,64568,58592,PRETRIAL,chudicek,kristi,NULL,Female,Caucasian,06/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +56580,64568,58592,PRETRIAL,chudicek,kristi,NULL,Female,Caucasian,06/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +56580,64568,58592,PRETRIAL,chudicek,kristi,NULL,Female,Caucasian,06/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56588,64576,58600,PRETRIAL,stanley,kayla,NULL,Female,African-American,03/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +56588,64576,58600,PRETRIAL,stanley,kayla,NULL,Female,African-American,03/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.43,2,Low,New,1,0 +56588,64576,58600,PRETRIAL,stanley,kayla,NULL,Female,African-American,03/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56577,64563,58587,PRETRIAL,Cali,Brian,Gilbert,Male,Caucasian,10/05/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +56577,64563,58587,PRETRIAL,Cali,Brian,Gilbert,Male,Caucasian,10/05/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +56577,64563,58587,PRETRIAL,Cali,Brian,Gilbert,Male,Caucasian,10/05/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56601,64597,58617,Probation,Desravines,James,NULL,Male,African-American,05/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +56601,64597,58617,Probation,Desravines,James,NULL,Male,African-American,05/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +56601,64597,58617,Probation,Desravines,James,NULL,Male,African-American,05/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56590,64582,58604,Probation,Rodriguez,Lorencio,NULL,Male,Hispanic,06/17/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +56590,64582,58604,Probation,Rodriguez,Lorencio,NULL,Male,Hispanic,06/17/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +56590,64582,58604,Probation,Rodriguez,Lorencio,NULL,Male,Hispanic,06/17/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +49938,64600,58620,Probation,Seymoure,David,NULL,Male,African-American,01/24/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +49938,64600,58620,Probation,Seymoure,David,NULL,Male,African-American,01/24/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +49938,64600,58620,Probation,Seymoure,David,NULL,Male,African-American,01/24/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56600,64596,58616,Probation,MANGRU,THEODORE,NULL,Male,Other,05/26/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/20/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +56600,64596,58616,Probation,MANGRU,THEODORE,NULL,Male,Other,05/26/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +56600,64596,58616,Probation,MANGRU,THEODORE,NULL,Male,Other,05/26/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56605,64603,58623,PRETRIAL,Muriente,Sharon,NULL,Female,Hispanic,05/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/20/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +56605,64603,58623,PRETRIAL,Muriente,Sharon,NULL,Female,Hispanic,05/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/20/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +56605,64603,58623,PRETRIAL,Muriente,Sharon,NULL,Female,Hispanic,05/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56576,64561,58585,PRETRIAL,Delrio,Mario,Andres,Male,Caucasian,12/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +56576,64561,58585,PRETRIAL,Delrio,Mario,Andres,Male,Caucasian,12/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +56576,64561,58585,PRETRIAL,Delrio,Mario,Andres,Male,Caucasian,12/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56582,64570,58594,Probation,Black,Tincy,NULL,Female,Other,11/22/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +56582,64570,58594,Probation,Black,Tincy,NULL,Female,Other,11/22/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +56582,64570,58594,Probation,Black,Tincy,NULL,Female,Other,11/22/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +17973,64591,58611,PRETRIAL,Ylomon,Brisnick,NULL,Male,Other,06/10/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +17973,64591,58611,PRETRIAL,Ylomon,Brisnick,NULL,Male,Other,06/10/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +17973,64591,58611,PRETRIAL,Ylomon,Brisnick,NULL,Male,Other,06/10/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56587,64575,58599,Probation,Espinal,Gina,M,Female,Hispanic,07/14/89,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,8/20/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +56587,64575,58599,Probation,Espinal,Gina,M,Female,Hispanic,07/14/89,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +56587,64575,58599,Probation,Espinal,Gina,M,Female,Hispanic,07/14/89,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +56572,64556,58580,PRETRIAL,Gause,Marquis,NULL,Male,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +56572,64556,58580,PRETRIAL,Gause,Marquis,NULL,Male,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +56572,64556,58580,PRETRIAL,Gause,Marquis,NULL,Male,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +49346,64577,57364,PRETRIAL,SLUYTER,WALTER,NULL,Male,Caucasian,05/22/59,17,All Scales,Intake,English,Post Sentence,Probation,Separated,8/20/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +49346,64577,57364,PRETRIAL,SLUYTER,WALTER,NULL,Male,Caucasian,05/22/59,17,All Scales,Intake,English,Post Sentence,Probation,Separated,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.38,1,Low,New,1,0 +49346,64577,57364,PRETRIAL,SLUYTER,WALTER,NULL,Male,Caucasian,05/22/59,17,All Scales,Intake,English,Post Sentence,Probation,Separated,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +56606,64605,58625,Probation,Ranglin,Kisanne,Camelia,Female,African-American,10/16/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +56606,64605,58625,Probation,Ranglin,Kisanne,Camelia,Female,African-American,10/16/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +56606,64605,58625,Probation,Ranglin,Kisanne,Camelia,Female,African-American,10/16/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +45302,64584,45527,PRETRIAL,Nelson,Anthonett,NULL,Female,African-American,01/16/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,Copy,1,0 +45302,64584,45527,PRETRIAL,Nelson,Anthonett,NULL,Female,African-American,01/16/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,Copy,1,0 +45302,64584,45527,PRETRIAL,Nelson,Anthonett,NULL,Female,African-American,01/16/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +56602,64598,58618,Probation,Moralez,Alejandro,NULL,Male,Hispanic,01/10/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +56602,64598,58618,Probation,Moralez,Alejandro,NULL,Male,Hispanic,01/10/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +56602,64598,58618,Probation,Moralez,Alejandro,NULL,Male,Hispanic,01/10/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56611,64609,58629,PRETRIAL,SCOTT,ANDRE,KENILE,Male,African-American,11/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +56611,64609,58629,PRETRIAL,SCOTT,ANDRE,KENILE,Male,African-American,11/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +56611,64609,58629,PRETRIAL,SCOTT,ANDRE,KENILE,Male,African-American,11/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56593,64588,58608,PRETRIAL,Cirrincione,Anthony,NULL,Male,Caucasian,02/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +56593,64588,58608,PRETRIAL,Cirrincione,Anthony,NULL,Male,Caucasian,02/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +56593,64588,58608,PRETRIAL,Cirrincione,Anthony,NULL,Male,Caucasian,02/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56604,64601,58621,Probation,Agudelo,David,NULL,Male,Hispanic,12/08/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/20/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +56604,64601,58621,Probation,Agudelo,David,NULL,Male,Hispanic,12/08/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +56604,64601,58621,Probation,Agudelo,David,NULL,Male,Hispanic,12/08/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +44457,64580,44560,PRETRIAL,Neal,Robert,NULL,Male,African-American,09/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,Copy,1,0 +44457,64580,44560,PRETRIAL,Neal,Robert,NULL,Male,African-American,09/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,Copy,1,0 +44457,64580,44560,PRETRIAL,Neal,Robert,NULL,Male,African-American,09/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +56579,64567,58591,PRETRIAL,Peterson,Shameka,Delise,Female,African-American,11/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +56579,64567,58591,PRETRIAL,Peterson,Shameka,Delise,Female,African-American,11/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +56579,64567,58591,PRETRIAL,Peterson,Shameka,Delise,Female,African-American,11/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56578,64564,58588,PRETRIAL,TIENTN,CHARLES,L,Male,Asian,10/07/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-4.19,1,Low,New,1,0 +56578,64564,58588,PRETRIAL,TIENTN,CHARLES,L,Male,Asian,10/07/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +56578,64564,58588,PRETRIAL,TIENTN,CHARLES,L,Male,Asian,10/07/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56584,64572,58596,Probation,Coombs,Avia,NULL,Female,African-American,08/18/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +56584,64572,58596,Probation,Coombs,Avia,NULL,Female,African-American,08/18/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +56584,64572,58596,Probation,Coombs,Avia,NULL,Female,African-American,08/18/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56607,64606,58626,Probation,Campbell,Shawn,NULL,Male,African-American,11/17/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +56607,64606,58626,Probation,Campbell,Shawn,NULL,Male,African-American,11/17/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +56607,64606,58626,Probation,Campbell,Shawn,NULL,Male,African-American,11/17/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56574,64559,58583,PRETRIAL,Santiago,Giovanni,NULL,Male,Caucasian,06/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +56574,64559,58583,PRETRIAL,Santiago,Giovanni,NULL,Male,Caucasian,06/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +56574,64559,58583,PRETRIAL,Santiago,Giovanni,NULL,Male,Caucasian,06/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56597,64593,58613,Probation,Pomareda,David,NULL,Male,Hispanic,06/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +56597,64593,58613,Probation,Pomareda,David,NULL,Male,Hispanic,06/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +56597,64593,58613,Probation,Pomareda,David,NULL,Male,Hispanic,06/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +44457,48864,44560,PRETRIAL,Neal,Robert,NULL,Male,African-American,09/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,2,Medium,7,Risk of Violence,-2.72,2,Low,New,1,0 +44457,48864,44560,PRETRIAL,Neal,Robert,NULL,Male,African-American,09/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +44457,48864,44560,PRETRIAL,Neal,Robert,NULL,Male,African-American,09/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56575,64562,58586,PRETRIAL,FRANCIS,TRISTYNN,NICOLE,Female,Caucasian,11/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +56575,64562,58586,PRETRIAL,FRANCIS,TRISTYNN,NICOLE,Female,Caucasian,11/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +56575,64562,58586,PRETRIAL,FRANCIS,TRISTYNN,NICOLE,Female,Caucasian,11/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56591,64583,58605,Probation,Jonesallen,Rachel,NULL,Female,African-American,07/07/84,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/20/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +56591,64583,58605,Probation,Jonesallen,Rachel,NULL,Female,African-American,07/07/84,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +56591,64583,58605,Probation,Jonesallen,Rachel,NULL,Female,African-American,07/07/84,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56595,64590,58610,Probation,Martin,Lenoz,NULL,Male,African-American,05/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +56595,64590,58610,Probation,Martin,Lenoz,NULL,Male,African-American,05/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +56595,64590,58610,Probation,Martin,Lenoz,NULL,Male,African-American,05/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56596,64592,58612,Probation,STRICKLAND,JAMES,NULL,Male,Caucasian,04/28/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +56596,64592,58612,Probation,STRICKLAND,JAMES,NULL,Male,Caucasian,04/28/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +56596,64592,58612,Probation,STRICKLAND,JAMES,NULL,Male,Caucasian,04/28/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +48803,64578,58601,PRETRIAL,PINEDA,REINALDO,DEJESUS,Male,Hispanic,06/25/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/20/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +48803,64578,58601,PRETRIAL,PINEDA,REINALDO,DEJESUS,Male,Hispanic,06/25/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/20/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +48803,64578,58601,PRETRIAL,PINEDA,REINALDO,DEJESUS,Male,Hispanic,06/25/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56603,64599,58619,Probation,roa,jaime,NULL,Male,Hispanic,12/09/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +56603,64599,58619,Probation,roa,jaime,NULL,Male,Hispanic,12/09/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +56603,64599,58619,Probation,roa,jaime,NULL,Male,Hispanic,12/09/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44126,64557,58581,PRETRIAL,BARNETT,ANDREW,DAVID,Male,Caucasian,09/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/20/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +44126,64557,58581,PRETRIAL,BARNETT,ANDREW,DAVID,Male,Caucasian,09/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +44126,64557,58581,PRETRIAL,BARNETT,ANDREW,DAVID,Male,Caucasian,09/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56586,64574,58598,Probation,hall,robert,NULL,Male,Caucasian,03/05/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/20/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +56586,64574,58598,Probation,hall,robert,NULL,Male,Caucasian,03/05/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +56586,64574,58598,Probation,hall,robert,NULL,Male,Caucasian,03/05/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56610,64608,58628,Probation,JONES,CHRISTOPHER,NULL,Male,Caucasian,12/20/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +56610,64608,58628,Probation,JONES,CHRISTOPHER,NULL,Male,Caucasian,12/20/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +56610,64608,58628,Probation,JONES,CHRISTOPHER,NULL,Male,Caucasian,12/20/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56599,64595,58615,Probation,Burke,Nakeysha,NULL,Female,African-American,02/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/20/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +56599,64595,58615,Probation,Burke,Nakeysha,NULL,Female,African-American,02/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/20/13 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +56599,64595,58615,Probation,Burke,Nakeysha,NULL,Female,African-American,02/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +47371,64604,58624,PRETRIAL,HAYNIE,ANTHONY,LEE,Male,Caucasian,05/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +47371,64604,58624,PRETRIAL,HAYNIE,ANTHONY,LEE,Male,Caucasian,05/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +47371,64604,58624,PRETRIAL,HAYNIE,ANTHONY,LEE,Male,Caucasian,05/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,38,10,High,New,1,0 +11216,64629,58647,Probation,Price,Kevin,A,Male,Caucasian,06/08/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/21/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +11216,64629,58647,Probation,Price,Kevin,A,Male,Caucasian,06/08/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +11216,64629,58647,Probation,Price,Kevin,A,Male,Caucasian,06/08/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56624,64625,58643,Probation,BROWN,TATYANA,L,Female,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +56624,64625,58643,Probation,BROWN,TATYANA,L,Female,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +56624,64625,58643,Probation,BROWN,TATYANA,L,Female,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56638,64641,58659,Probation,fuls,jason,NULL,Male,Caucasian,05/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +56638,64641,58659,Probation,fuls,jason,NULL,Male,Caucasian,05/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +56638,64641,58659,Probation,fuls,jason,NULL,Male,Caucasian,05/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56613,64611,58631,PRETRIAL,SPELMAN,GERARD,NULL,Male,Caucasian,04/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +56613,64611,58631,PRETRIAL,SPELMAN,GERARD,NULL,Male,Caucasian,04/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +56613,64611,58631,PRETRIAL,SPELMAN,GERARD,NULL,Male,Caucasian,04/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56614,64613,58632,PRETRIAL,Fong-Aguilar,Leung,NULL,Male,Caucasian,09/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +56614,64613,58632,PRETRIAL,Fong-Aguilar,Leung,NULL,Male,Caucasian,09/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +56614,64613,58632,PRETRIAL,Fong-Aguilar,Leung,NULL,Male,Caucasian,09/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56620,64620,58639,PRETRIAL,Williams,Dwaine,NULL,Male,African-American,02/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +56620,64620,58639,PRETRIAL,Williams,Dwaine,NULL,Male,African-American,02/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +56620,64620,58639,PRETRIAL,Williams,Dwaine,NULL,Male,African-American,02/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56631,64634,58652,PRETRIAL,SAPP,RYAN,NULL,Male,African-American,03/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +56631,64634,58652,PRETRIAL,SAPP,RYAN,NULL,Male,African-American,03/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +56631,64634,58652,PRETRIAL,SAPP,RYAN,NULL,Male,African-American,03/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55698,63448,57578,PRETRIAL,Farmer,Danny,NULL,Male,Caucasian,06/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/21/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +55698,63448,57578,PRETRIAL,Farmer,Danny,NULL,Male,Caucasian,06/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +55698,63448,57578,PRETRIAL,Farmer,Danny,NULL,Male,Caucasian,06/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +46268,64648,58665,PRETRIAL,herreros,sebastian,NULL,Male,Hispanic,05/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.24,8,High,New,1,0 +46268,64648,58665,PRETRIAL,herreros,sebastian,NULL,Male,Hispanic,05/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +46268,64648,58665,PRETRIAL,herreros,sebastian,NULL,Male,Hispanic,05/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56646,64655,58669,PRETRIAL,Torresrodrigues,Maria,NULL,Female,Hispanic,02/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/21/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +56646,64655,58669,PRETRIAL,Torresrodrigues,Maria,NULL,Female,Hispanic,02/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/21/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +56646,64655,58669,PRETRIAL,Torresrodrigues,Maria,NULL,Female,Hispanic,02/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56626,64627,58645,Probation,ASTRALAGA,BIANCA,NULL,Female,Hispanic,04/30/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +56626,64627,58645,Probation,ASTRALAGA,BIANCA,NULL,Female,Hispanic,04/30/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +56626,64627,58645,Probation,ASTRALAGA,BIANCA,NULL,Female,Hispanic,04/30/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56637,64640,58658,Probation,Ott,Charles,NULL,Male,African-American,01/17/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +56637,64640,58658,Probation,Ott,Charles,NULL,Male,African-American,01/17/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +56637,64640,58658,Probation,Ott,Charles,NULL,Male,African-American,01/17/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +43197,64661,58675,PRETRIAL,Gary,Eric,D,Male,African-American,02/21/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,4,High,7,Risk of Violence,-0.64,9,High,New,1,0 +43197,64661,58675,PRETRIAL,Gary,Eric,D,Male,African-American,02/21/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,4,High,8,Risk of Recidivism,0.16,8,High,New,1,0 +43197,64661,58675,PRETRIAL,Gary,Eric,D,Male,African-American,02/21/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +40670,64614,58633,PRETRIAL,ARRIETAROSALES,MIGUEL,NULL,Male,Hispanic,01/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +40670,64614,58633,PRETRIAL,ARRIETAROSALES,MIGUEL,NULL,Male,Hispanic,01/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +40670,64614,58633,PRETRIAL,ARRIETAROSALES,MIGUEL,NULL,Male,Hispanic,01/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49246,64653,58667,PRETRIAL,Cabrera,Aaron,Amado,Male,Caucasian,03/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +49246,64653,58667,PRETRIAL,Cabrera,Aaron,Amado,Male,Caucasian,03/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +49246,64653,58667,PRETRIAL,Cabrera,Aaron,Amado,Male,Caucasian,03/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +48324,64632,58650,PRETRIAL,Douglas,Carnellie,NULL,Male,African-American,09/13/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +48324,64632,58650,PRETRIAL,Douglas,Carnellie,NULL,Male,African-American,09/13/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +48324,64632,58650,PRETRIAL,Douglas,Carnellie,NULL,Male,African-American,09/13/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56632,64635,58653,PRETRIAL,Chebaux-Mcginty,Ivan,NULL,Male,Caucasian,09/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +56632,64635,58653,PRETRIAL,Chebaux-Mcginty,Ivan,NULL,Male,Caucasian,09/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +56632,64635,58653,PRETRIAL,Chebaux-Mcginty,Ivan,NULL,Male,Caucasian,09/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56628,64630,58648,Probation,STEWART-BUTLER,SONIA,E,Female,African-American,12/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +56628,64630,58648,Probation,STEWART-BUTLER,SONIA,E,Female,African-American,12/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +56628,64630,58648,Probation,STEWART-BUTLER,SONIA,E,Female,African-American,12/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56634,64637,58655,Probation,Nguyen,John,NULL,Male,Asian,06/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/21/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +56634,64637,58655,Probation,Nguyen,John,NULL,Male,Asian,06/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +56634,64637,58655,Probation,Nguyen,John,NULL,Male,Asian,06/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56616,64616,58635,PRETRIAL,Valencia,Adriana,NULL,Female,Caucasian,08/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/21/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +56616,64616,58635,PRETRIAL,Valencia,Adriana,NULL,Female,Caucasian,08/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +56616,64616,58635,PRETRIAL,Valencia,Adriana,NULL,Female,Caucasian,08/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56643,64651,58664,Probation,ZIKIRA,ZEKE,NULL,Male,Caucasian,11/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,Copy,1,0 +56643,64651,58664,Probation,ZIKIRA,ZEKE,NULL,Male,Caucasian,11/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,Copy,1,0 +56643,64651,58664,Probation,ZIKIRA,ZEKE,NULL,Male,Caucasian,11/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +56621,64622,58640,Probation,DUBOIS,RICHARD,NULL,Male,Caucasian,08/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +56621,64622,58640,Probation,DUBOIS,RICHARD,NULL,Male,Caucasian,08/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +56621,64622,58640,Probation,DUBOIS,RICHARD,NULL,Male,Caucasian,08/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56642,64645,58663,Probation,CANDELARIA,JOSE,R,Male,Hispanic,07/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +56642,64645,58663,Probation,CANDELARIA,JOSE,R,Male,Hispanic,07/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +56642,64645,58663,Probation,CANDELARIA,JOSE,R,Male,Hispanic,07/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +56623,64624,58642,Probation,Byrd,Charles,NULL,Male,Caucasian,12/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,7,Risk of Violence,-2.74,2,Low,New,1,0 +56623,64624,58642,Probation,Byrd,Charles,NULL,Male,Caucasian,12/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +56623,64624,58642,Probation,Byrd,Charles,NULL,Male,Caucasian,12/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,18,Risk of Failure to Appear,42,10,High,New,1,0 +56640,64643,58661,Probation,medina,lisette,NULL,Male,Hispanic,02/19/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +56640,64643,58661,Probation,medina,lisette,NULL,Male,Hispanic,02/19/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +56640,64643,58661,Probation,medina,lisette,NULL,Male,Hispanic,02/19/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56649,64658,58672,Probation,Solorio,Alberto,NULL,Male,Hispanic,11/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +56649,64658,58672,Probation,Solorio,Alberto,NULL,Male,Hispanic,11/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +56649,64658,58672,Probation,Solorio,Alberto,NULL,Male,Hispanic,11/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +5110,64612,4788,PRETRIAL,SIMMONS,JAMES,GARLIN,Male,African-American,01/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,Copy,1,0 +5110,64612,4788,PRETRIAL,SIMMONS,JAMES,GARLIN,Male,African-American,01/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,Copy,1,0 +5110,64612,4788,PRETRIAL,SIMMONS,JAMES,GARLIN,Male,African-American,01/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,Copy,1,0 +56619,64619,58638,PRETRIAL,WALKER,JOVAUGHN,NULL,Male,African-American,02/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +56619,64619,58638,PRETRIAL,WALKER,JOVAUGHN,NULL,Male,African-American,02/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +56619,64619,58638,PRETRIAL,WALKER,JOVAUGHN,NULL,Male,African-American,02/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56645,64654,58668,Probation,Fernandez,Arthur,NULL,Male,Hispanic,10/14/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/21/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +56645,64654,58668,Probation,Fernandez,Arthur,NULL,Male,Hispanic,10/14/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +56645,64654,58668,Probation,Fernandez,Arthur,NULL,Male,Hispanic,10/14/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56647,64656,58670,Probation,Guzmanoran,Hanghelis,NULL,Female,Hispanic,12/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +56647,64656,58670,Probation,Guzmanoran,Hanghelis,NULL,Female,Hispanic,12/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +56647,64656,58670,Probation,Guzmanoran,Hanghelis,NULL,Female,Hispanic,12/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56625,64626,58644,PRETRIAL,Kahok,Ammar,NULL,Male,Arabic,07/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/21/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +56625,64626,58644,PRETRIAL,Kahok,Ammar,NULL,Male,Arabic,07/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +56625,64626,58644,PRETRIAL,Kahok,Ammar,NULL,Male,Arabic,07/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56639,64642,58660,Probation,Sherwood,Stephanie,NULL,Female,Hispanic,10/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +56639,64642,58660,Probation,Sherwood,Stephanie,NULL,Female,Hispanic,10/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,7,Medium,New,1,0 +56639,64642,58660,Probation,Sherwood,Stephanie,NULL,Female,Hispanic,10/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56650,64659,58673,Probation,Gray,Jeffrey,NULL,Male,African-American,02/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/21/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +56650,64659,58673,Probation,Gray,Jeffrey,NULL,Male,African-American,02/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +56650,64659,58673,Probation,Gray,Jeffrey,NULL,Male,African-American,02/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56635,64638,58656,PRETRIAL,GONZALEZ,KERRY,NULL,Female,African-American,04/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +56635,64638,58656,PRETRIAL,GONZALEZ,KERRY,NULL,Female,African-American,04/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +56635,64638,58656,PRETRIAL,GONZALEZ,KERRY,NULL,Female,African-American,04/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54779,64621,56495,Probation,Myers,Eric,NULL,Male,Caucasian,04/15/75,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +54779,64621,56495,Probation,Myers,Eric,NULL,Male,Caucasian,04/15/75,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-0.62,3,Low,New,1,0 +54779,64621,56495,Probation,Myers,Eric,NULL,Male,Caucasian,04/15/75,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,2,Low,New,1,0 +56617,64617,58636,PRETRIAL,Huings,Daren,NULL,Male,Other,07/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,4,High,7,Risk of Violence,-0.5,10,High,New,1,0 +56617,64617,58636,PRETRIAL,Huings,Daren,NULL,Male,Other,07/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,4,High,8,Risk of Recidivism,0.71,10,High,New,1,0 +56617,64617,58636,PRETRIAL,Huings,Daren,NULL,Male,Other,07/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56633,64636,58654,Probation,stunneck,joseph,NULL,Male,Caucasian,07/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +56633,64636,58654,Probation,stunneck,joseph,NULL,Male,Caucasian,07/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +56633,64636,58654,Probation,stunneck,joseph,NULL,Male,Caucasian,07/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56612,64610,58630,PRETRIAL,PHILOGENE,EMMANUEL,NULL,Male,Other,12/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +56612,64610,58630,PRETRIAL,PHILOGENE,EMMANUEL,NULL,Male,Other,12/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +56612,64610,58630,PRETRIAL,PHILOGENE,EMMANUEL,NULL,Male,Other,12/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56622,64623,58641,Probation,Meus,Beliard,NULL,Male,Other,02/12/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +56622,64623,58641,Probation,Meus,Beliard,NULL,Male,Other,02/12/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +56622,64623,58641,Probation,Meus,Beliard,NULL,Male,Other,02/12/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +47135,64657,58671,PRETRIAL,Bowens,Reshaud,NULL,Male,African-American,12/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,New,1,0 +47135,64657,58671,PRETRIAL,Bowens,Reshaud,NULL,Male,African-American,12/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +47135,64657,58671,PRETRIAL,Bowens,Reshaud,NULL,Male,African-American,12/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56618,64618,58637,PRETRIAL,Clark,Shannon,NULL,Female,Caucasian,11/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +56618,64618,58637,PRETRIAL,Clark,Shannon,NULL,Female,Caucasian,11/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/13 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +56618,64618,58637,PRETRIAL,Clark,Shannon,NULL,Female,Caucasian,11/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +56627,64628,58646,Probation,butler,darius,NULL,Male,African-American,04/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +56627,64628,58646,Probation,butler,darius,NULL,Male,African-American,04/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +56627,64628,58646,Probation,butler,darius,NULL,Male,African-American,04/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56636,64639,58657,PRETRIAL,Neil,Bobby,NULL,Male,African-American,07/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +56636,64639,58657,PRETRIAL,Neil,Bobby,NULL,Male,African-American,07/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,New,1,0 +56636,64639,58657,PRETRIAL,Neil,Bobby,NULL,Male,African-American,07/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +11720,64660,58674,PRETRIAL,ROLAX,RONNIE,LEE,Male,African-American,12/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,4,High,7,Risk of Violence,-0.07,10,High,New,1,0 +11720,64660,58674,PRETRIAL,ROLAX,RONNIE,LEE,Male,African-American,12/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,4,High,8,Risk of Recidivism,0.37,9,High,New,1,0 +11720,64660,58674,PRETRIAL,ROLAX,RONNIE,LEE,Male,African-American,12/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,4,High,18,Risk of Failure to Appear,40,10,High,New,1,0 +56641,64644,58662,Probation,Nunez-Cardenas,Walter,NULL,Male,Hispanic,04/22/75,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/21/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +56641,64644,58662,Probation,Nunez-Cardenas,Walter,NULL,Male,Hispanic,04/22/75,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/21/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +56641,64644,58662,Probation,Nunez-Cardenas,Walter,NULL,Male,Hispanic,04/22/75,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56615,64615,58634,PRETRIAL,Shakespeare,Shaun,Andre,Male,Other,03/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +56615,64615,58634,PRETRIAL,Shakespeare,Shaun,Andre,Male,Other,03/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +56615,64615,58634,PRETRIAL,Shakespeare,Shaun,Andre,Male,Other,03/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56644,64652,58666,DRRD,Hinds,Anthony,NULL,Male,African-American,05/21/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +56644,64652,58666,DRRD,Hinds,Anthony,NULL,Male,African-American,05/21/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +56644,64652,58666,DRRD,Hinds,Anthony,NULL,Male,African-American,05/21/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/21/13 0:00,2,Medium,18,Risk of Failure to Appear,21,3,Low,New,1,0 +4721,64665,58679,PRETRIAL,SWEETING,DEMETRIUS,JARROD,Male,African-American,04/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +4721,64665,58679,PRETRIAL,SWEETING,DEMETRIUS,JARROD,Male,African-American,04/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +4721,64665,58679,PRETRIAL,SWEETING,DEMETRIUS,JARROD,Male,African-American,04/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56676,64701,58714,Probation,Williams,Walter,NULL,Male,African-American,01/27/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/13 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +56676,64701,58714,Probation,Williams,Walter,NULL,Male,African-American,01/27/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/13 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +56676,64701,58714,Probation,Williams,Walter,NULL,Male,African-American,01/27/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56677,64702,58715,PRETRIAL,WELLS,VENORRICE,NULL,Male,African-American,10/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +56677,64702,58715,PRETRIAL,WELLS,VENORRICE,NULL,Male,African-American,10/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +56677,64702,58715,PRETRIAL,WELLS,VENORRICE,NULL,Male,African-American,10/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56658,64673,58687,PRETRIAL,MARTIN,JANEY,NULL,Female,African-American,05/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +56658,64673,58687,PRETRIAL,MARTIN,JANEY,NULL,Female,African-American,05/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +56658,64673,58687,PRETRIAL,MARTIN,JANEY,NULL,Female,African-American,05/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56660,64680,58694,Probation,espinosa,hansel,NULL,Male,Hispanic,06/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +56660,64680,58694,Probation,espinosa,hansel,NULL,Male,Hispanic,06/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +56660,64680,58694,Probation,espinosa,hansel,NULL,Male,Hispanic,06/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56670,64694,58707,PRETRIAL,Weber,Willis,NULL,Male,Caucasian,10/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +56670,64694,58707,PRETRIAL,Weber,Willis,NULL,Male,Caucasian,10/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +56670,64694,58707,PRETRIAL,Weber,Willis,NULL,Male,Caucasian,10/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +28374,64707,37664,PRETRIAL,KINDER,PERCEL,C,Male,African-American,07/22/76,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,Copy,1,0 +28374,64707,37664,PRETRIAL,KINDER,PERCEL,C,Male,African-American,07/22/76,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,4,High,8,Risk of Recidivism,0.67,10,High,Copy,1,0 +28374,64707,37664,PRETRIAL,KINDER,PERCEL,C,Male,African-American,07/22/76,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +56681,64709,58721,Probation,HURTADO,JULIO,NULL,Male,Hispanic,10/13/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +56681,64709,58721,Probation,HURTADO,JULIO,NULL,Male,Hispanic,10/13/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +56681,64709,58721,Probation,HURTADO,JULIO,NULL,Male,Hispanic,10/13/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56666,64686,58700,Probation,Alarcon,Marco,NULL,Male,Hispanic,10/24/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/22/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +56666,64686,58700,Probation,Alarcon,Marco,NULL,Male,Hispanic,10/24/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/22/13 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +56666,64686,58700,Probation,Alarcon,Marco,NULL,Male,Hispanic,10/24/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +47327,64688,58702,PRETRIAL,Gordon,Jeremy,NULL,Male,African-American,08/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +47327,64688,58702,PRETRIAL,Gordon,Jeremy,NULL,Male,African-American,08/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +47327,64688,58702,PRETRIAL,Gordon,Jeremy,NULL,Male,African-American,08/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +8892,64678,58692,PRETRIAL,LENNON,DENNIS,W,Male,Caucasian,04/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/22/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +8892,64678,58692,PRETRIAL,LENNON,DENNIS,W,Male,Caucasian,04/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +8892,64678,58692,PRETRIAL,LENNON,DENNIS,W,Male,Caucasian,04/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56671,64696,58709,Probation,Lamour Jr.,Frantz,NULL,Male,African-American,01/31/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +56671,64696,58709,Probation,Lamour Jr.,Frantz,NULL,Male,African-American,01/31/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +56671,64696,58709,Probation,Lamour Jr.,Frantz,NULL,Male,African-American,01/31/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +56674,64699,58712,Probation,Covar,Nicholas,NULL,Male,Caucasian,03/20/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +56674,64699,58712,Probation,Covar,Nicholas,NULL,Male,Caucasian,03/20/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +56674,64699,58712,Probation,Covar,Nicholas,NULL,Male,Caucasian,03/20/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +39434,64691,58705,PRETRIAL,DYER,CLIFTON,W,Male,Caucasian,10/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +39434,64691,58705,PRETRIAL,DYER,CLIFTON,W,Male,Caucasian,10/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,4,High,8,Risk of Recidivism,0.63,10,High,New,1,0 +39434,64691,58705,PRETRIAL,DYER,CLIFTON,W,Male,Caucasian,10/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56656,64670,58684,PRETRIAL,Daly,Brian,Michael,Male,Caucasian,05/30/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +56656,64670,58684,PRETRIAL,Daly,Brian,Michael,Male,Caucasian,05/30/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +56656,64670,58684,PRETRIAL,Daly,Brian,Michael,Male,Caucasian,05/30/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50148,64704,58717,Probation,MUCKLOW,ANDREA,NULL,Female,Caucasian,12/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +50148,64704,58717,Probation,MUCKLOW,ANDREA,NULL,Female,Caucasian,12/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +50148,64704,58717,Probation,MUCKLOW,ANDREA,NULL,Female,Caucasian,12/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56654,64668,58682,PRETRIAL,CUNNINGHAM,PETER,A,Male,African-American,03/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +56654,64668,58682,PRETRIAL,CUNNINGHAM,PETER,A,Male,African-American,03/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +56654,64668,58682,PRETRIAL,CUNNINGHAM,PETER,A,Male,African-American,03/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56668,64689,58703,Probation,thomas,thomas,NULL,Male,Caucasian,10/03/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +56668,64689,58703,Probation,thomas,thomas,NULL,Male,Caucasian,10/03/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +56668,64689,58703,Probation,thomas,thomas,NULL,Male,Caucasian,10/03/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56652,64663,58677,PRETRIAL,GORDON,TIMOTHY,NULL,Male,African-American,07/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +56652,64663,58677,PRETRIAL,GORDON,TIMOTHY,NULL,Male,African-American,07/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +56652,64663,58677,PRETRIAL,GORDON,TIMOTHY,NULL,Male,African-American,07/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +36939,64672,58686,PRETRIAL,KHAN,STEVEN,NULL,Male,African-American,09/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +36939,64672,58686,PRETRIAL,KHAN,STEVEN,NULL,Male,African-American,09/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +36939,64672,58686,PRETRIAL,KHAN,STEVEN,NULL,Male,African-American,09/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +48922,64693,49676,PRETRIAL,Johnson,Geovani,NULL,Male,African-American,05/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,Copy,1,0 +48922,64693,49676,PRETRIAL,Johnson,Geovani,NULL,Male,African-American,05/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,Copy,1,0 +48922,64693,49676,PRETRIAL,Johnson,Geovani,NULL,Male,African-American,05/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +56682,64710,58722,Probation,Defreitas,Javon,NULL,Male,African-American,07/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +56682,64710,58722,Probation,Defreitas,Javon,NULL,Male,African-American,07/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +56682,64710,58722,Probation,Defreitas,Javon,NULL,Male,African-American,07/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +9659,64675,58689,PRETRIAL,MURRAY,ANTONIO,JARROD,Male,African-American,05/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +9659,64675,58689,PRETRIAL,MURRAY,ANTONIO,JARROD,Male,African-American,05/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +9659,64675,58689,PRETRIAL,MURRAY,ANTONIO,JARROD,Male,African-American,05/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56659,64677,58691,PRETRIAL,Wardlaw,Eric,NULL,Male,African-American,01/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +56659,64677,58691,PRETRIAL,Wardlaw,Eric,NULL,Male,African-American,01/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +56659,64677,58691,PRETRIAL,Wardlaw,Eric,NULL,Male,African-American,01/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56673,64698,58711,PRETRIAL,Metellus,Fredline,NULL,Male,African-American,05/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +56673,64698,58711,PRETRIAL,Metellus,Fredline,NULL,Male,African-American,05/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +56673,64698,58711,PRETRIAL,Metellus,Fredline,NULL,Male,African-American,05/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56678,64705,58718,Probation,HILTON,JAMAAL,S,Male,African-American,03/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +56678,64705,58718,Probation,HILTON,JAMAAL,S,Male,African-American,03/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +56678,64705,58718,Probation,HILTON,JAMAAL,S,Male,African-American,03/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56683,64712,58723,Probation,Modesto,Gilberto,NULL,Male,Hispanic,12/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +56683,64712,58723,Probation,Modesto,Gilberto,NULL,Male,Hispanic,12/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +56683,64712,58723,Probation,Modesto,Gilberto,NULL,Male,Hispanic,12/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56664,64684,58698,Probation,Gutierrez,Karol,Andrea,Female,Hispanic,02/20/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +56664,64684,58698,Probation,Gutierrez,Karol,Andrea,Female,Hispanic,02/20/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +56664,64684,58698,Probation,Gutierrez,Karol,Andrea,Female,Hispanic,02/20/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +22577,64666,58680,PRETRIAL,Harvey,Marcus,Allen,Male,African-American,03/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +22577,64666,58680,PRETRIAL,Harvey,Marcus,Allen,Male,African-American,03/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +22577,64666,58680,PRETRIAL,Harvey,Marcus,Allen,Male,African-American,03/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56667,64687,58701,Probation,Sandrin,Ryan,NULL,Male,Caucasian,06/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-2.74,2,Low,New,1,0 +56667,64687,58701,Probation,Sandrin,Ryan,NULL,Male,Caucasian,06/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +56667,64687,58701,Probation,Sandrin,Ryan,NULL,Male,Caucasian,06/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56662,64682,58696,Probation,Stuart,Maritza,NULL,Female,Hispanic,07/28/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +56662,64682,58696,Probation,Stuart,Maritza,NULL,Female,Hispanic,07/28/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.61,2,Low,New,1,0 +56662,64682,58696,Probation,Stuart,Maritza,NULL,Female,Hispanic,07/28/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56675,64700,58713,Probation,turner,laqaunta,NULL,Female,African-American,07/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +56675,64700,58713,Probation,turner,laqaunta,NULL,Female,African-American,07/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +56675,64700,58713,Probation,turner,laqaunta,NULL,Female,African-American,07/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +2766,64703,58716,PRETRIAL,Dixon,Donte,Antan,Male,African-American,01/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +2766,64703,58716,PRETRIAL,Dixon,Donte,Antan,Male,African-American,01/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +2766,64703,58716,PRETRIAL,Dixon,Donte,Antan,Male,African-American,01/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +38182,64695,58708,PRETRIAL,ROMERO,JAVIER,NULL,Male,Hispanic,07/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +38182,64695,58708,PRETRIAL,ROMERO,JAVIER,NULL,Male,Hispanic,07/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +38182,64695,58708,PRETRIAL,ROMERO,JAVIER,NULL,Male,Hispanic,07/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +39651,64674,58688,Probation,RAMIREZ,EDWIN,NULL,Male,Hispanic,08/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-3.15,1,Low,New,1,0 +39651,64674,58688,Probation,RAMIREZ,EDWIN,NULL,Male,Hispanic,08/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +39651,64674,58688,Probation,RAMIREZ,EDWIN,NULL,Male,Hispanic,08/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +45355,64708,58720,PRETRIAL,Lamarche,Michael,NULL,Male,Caucasian,09/01/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +45355,64708,58720,PRETRIAL,Lamarche,Michael,NULL,Male,Caucasian,09/01/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +45355,64708,58720,PRETRIAL,Lamarche,Michael,NULL,Male,Caucasian,09/01/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56651,64662,58676,PRETRIAL,Dubois,Elie,NULL,Male,Other,12/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +56651,64662,58676,PRETRIAL,Dubois,Elie,NULL,Male,Other,12/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +56651,64662,58676,PRETRIAL,Dubois,Elie,NULL,Male,Other,12/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56655,64669,58683,PRETRIAL,Kroboth,Andres,NULL,Male,Hispanic,10/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +56655,64669,58683,PRETRIAL,Kroboth,Andres,NULL,Male,Hispanic,10/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +56655,64669,58683,PRETRIAL,Kroboth,Andres,NULL,Male,Hispanic,10/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56663,64683,58697,Probation,WELDON,VICKIANN,NULL,Female,Caucasian,11/05/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +56663,64683,58697,Probation,WELDON,VICKIANN,NULL,Female,Caucasian,11/05/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +56663,64683,58697,Probation,WELDON,VICKIANN,NULL,Female,Caucasian,11/05/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +29582,64711,28585,PRETRIAL,Balmer,Gary,NULL,Male,Caucasian,07/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/22/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,Copy,1,0 +29582,64711,28585,PRETRIAL,Balmer,Gary,NULL,Male,Caucasian,07/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/22/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,Copy,1,0 +29582,64711,28585,PRETRIAL,Balmer,Gary,NULL,Male,Caucasian,07/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +56669,64690,58704,PRETRIAL,CABRERA,JULIA,NULL,Female,Hispanic,10/18/65,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +56669,64690,58704,PRETRIAL,CABRERA,JULIA,NULL,Female,Hispanic,10/18/65,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +56669,64690,58704,PRETRIAL,CABRERA,JULIA,NULL,Female,Hispanic,10/18/65,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +47753,64692,58706,PRETRIAL,saldana,Daniel,Antonio,Male,Caucasian,09/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +47753,64692,58706,PRETRIAL,saldana,Daniel,Antonio,Male,Caucasian,09/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +47753,64692,58706,PRETRIAL,saldana,Daniel,Antonio,Male,Caucasian,09/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +43236,64676,58690,PRETRIAL,DELEGAL,SEAN,NULL,Male,Caucasian,09/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +43236,64676,58690,PRETRIAL,DELEGAL,SEAN,NULL,Male,Caucasian,09/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +43236,64676,58690,PRETRIAL,DELEGAL,SEAN,NULL,Male,Caucasian,09/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56672,64697,58710,PRETRIAL,Eliacin,Romario,Scott,Male,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +56672,64697,58710,PRETRIAL,Eliacin,Romario,Scott,Male,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.8,10,High,New,1,0 +56672,64697,58710,PRETRIAL,Eliacin,Romario,Scott,Male,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56679,64706,58719,Probation,Bille,Austin,NULL,Male,Native American,02/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +56679,64706,58719,Probation,Bille,Austin,NULL,Male,Native American,02/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +56679,64706,58719,Probation,Bille,Austin,NULL,Male,Native American,02/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56653,64667,58681,PRETRIAL,Kennedy,David,M,Male,African-American,01/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +56653,64667,58681,PRETRIAL,Kennedy,David,M,Male,African-American,01/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +56653,64667,58681,PRETRIAL,Kennedy,David,M,Male,African-American,01/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56665,64685,58699,Probation,MALLORY,WAYNE,NULL,Male,Caucasian,05/13/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +56665,64685,58699,Probation,MALLORY,WAYNE,NULL,Male,Caucasian,05/13/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +56665,64685,58699,Probation,MALLORY,WAYNE,NULL,Male,Caucasian,05/13/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +32312,64664,58678,PRETRIAL,LEWIS,LAVONTE,NULL,Male,African-American,12/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,4,High,7,Risk of Violence,-0.7,9,High,New,1,0 +32312,64664,58678,PRETRIAL,LEWIS,LAVONTE,NULL,Male,African-American,12/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,4,High,8,Risk of Recidivism,0.71,10,High,New,1,0 +32312,64664,58678,PRETRIAL,LEWIS,LAVONTE,NULL,Male,African-American,12/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56657,64671,58685,PRETRIAL,Derenoncourt,Zachery,Henry,Male,African-American,01/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +56657,64671,58685,PRETRIAL,Derenoncourt,Zachery,Henry,Male,African-American,01/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +56657,64671,58685,PRETRIAL,Derenoncourt,Zachery,Henry,Male,African-American,01/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56699,64739,58745,DRRD,Brown,Adrian,Devon,Male,African-American,09/21/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +56699,64739,58745,DRRD,Brown,Adrian,Devon,Male,African-American,09/21/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,8,High,New,1,0 +56699,64739,58745,DRRD,Brown,Adrian,Devon,Male,African-American,09/21/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +28197,64753,27264,PRETRIAL,Bullard,Armand,NULL,Male,African-American,11/19/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,Copy,1,0 +28197,64753,27264,PRETRIAL,Bullard,Armand,NULL,Male,African-American,11/19/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,Copy,1,0 +28197,64753,27264,PRETRIAL,Bullard,Armand,NULL,Male,African-American,11/19/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +56686,64718,58729,PRETRIAL,Humphrey,Tinikka,NULL,Female,African-American,10/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/23/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +56686,64718,58729,PRETRIAL,Humphrey,Tinikka,NULL,Female,African-American,10/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/23/13 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +56686,64718,58729,PRETRIAL,Humphrey,Tinikka,NULL,Female,African-American,10/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56694,64736,58742,Probation,GRAHAM,ALEX,O,Male,African-American,11/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +56694,64736,58742,Probation,GRAHAM,ALEX,O,Male,African-American,11/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +56694,64736,58742,Probation,GRAHAM,ALEX,O,Male,African-American,11/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +37045,54444,36389,PRETRIAL,Casanova,Hernan,NULL,Male,Hispanic,03/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/23/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,Copy,1,0 +37045,54444,36389,PRETRIAL,Casanova,Hernan,NULL,Male,Hispanic,03/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,Copy,1,0 +37045,54444,36389,PRETRIAL,Casanova,Hernan,NULL,Male,Hispanic,03/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +56551,64727,58554,PRETRIAL,Baptista,Christopher,Andrew,Male,Hispanic,09/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,Copy,1,0 +56551,64727,58554,PRETRIAL,Baptista,Christopher,Andrew,Male,Hispanic,09/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,Copy,1,0 +56551,64727,58554,PRETRIAL,Baptista,Christopher,Andrew,Male,Hispanic,09/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +56709,64757,58759,Probation,Scott,Claudette,NULL,Female,African-American,11/21/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/23/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +56709,64757,58759,Probation,Scott,Claudette,NULL,Female,African-American,11/21/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/23/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +56709,64757,58759,Probation,Scott,Claudette,NULL,Female,African-American,11/21/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56700,64741,58747,Probation,SPICER,MICHAELE,J,Male,African-American,04/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/23/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +56700,64741,58747,Probation,SPICER,MICHAELE,J,Male,African-American,04/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/23/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +56700,64741,58747,Probation,SPICER,MICHAELE,J,Male,African-American,04/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52384,64713,58724,PRETRIAL,Bryan,Wilfred,NULL,Male,Other,08/19/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +52384,64713,58724,PRETRIAL,Bryan,Wilfred,NULL,Male,Other,08/19/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +52384,64713,58724,PRETRIAL,Bryan,Wilfred,NULL,Male,Other,08/19/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56687,64720,58730,PRETRIAL,Henry,Akeem,NULL,Male,African-American,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +56687,64720,58730,PRETRIAL,Henry,Akeem,NULL,Male,African-American,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +56687,64720,58730,PRETRIAL,Henry,Akeem,NULL,Male,African-American,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +26839,64734,58740,PRETRIAL,Gethers,Antonio,NULL,Male,African-American,06/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +26839,64734,58740,PRETRIAL,Gethers,Antonio,NULL,Male,African-American,06/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +26839,64734,58740,PRETRIAL,Gethers,Antonio,NULL,Male,African-American,06/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56705,64748,58753,PRETRIAL,MARINEAU,MARIA,NULL,Female,Caucasian,02/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/23/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +56705,64748,58753,PRETRIAL,MARINEAU,MARIA,NULL,Female,Caucasian,02/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/23/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +56705,64748,58753,PRETRIAL,MARINEAU,MARIA,NULL,Female,Caucasian,02/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +51301,64755,52487,Probation,farias,roberto,NULL,Male,Caucasian,01/26/72,17,All Scales,Intake,English,Post Sentence,Probation,Separated,8/23/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +51301,64755,52487,Probation,farias,roberto,NULL,Male,Caucasian,01/26/72,17,All Scales,Intake,English,Post Sentence,Probation,Separated,8/23/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +51301,64755,52487,Probation,farias,roberto,NULL,Male,Caucasian,01/26/72,17,All Scales,Intake,English,Post Sentence,Probation,Separated,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +48828,64762,58764,PRETRIAL,wolcott,delbert,NULL,Male,Caucasian,06/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/23/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +48828,64762,58764,PRETRIAL,wolcott,delbert,NULL,Male,Caucasian,06/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/23/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +48828,64762,58764,PRETRIAL,wolcott,delbert,NULL,Male,Caucasian,06/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55887,64742,57804,Probation,Blas,Orlanda,NULL,Male,Hispanic,08/11/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +55887,64742,57804,Probation,Blas,Orlanda,NULL,Male,Hispanic,08/11/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,6,Medium,New,1,0 +55887,64742,57804,Probation,Blas,Orlanda,NULL,Male,Hispanic,08/11/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,18,2,Low,New,1,0 +56690,64729,58737,PRETRIAL,Johnson,Tommie,NULL,Male,African-American,09/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +56690,64729,58737,PRETRIAL,Johnson,Tommie,NULL,Male,African-American,09/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +56690,64729,58737,PRETRIAL,Johnson,Tommie,NULL,Male,African-American,09/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +56712,64763,58765,Probation,cheeley,mark,o,Male,Caucasian,02/08/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +56712,64763,58765,Probation,cheeley,mark,o,Male,Caucasian,02/08/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +56712,64763,58765,Probation,cheeley,mark,o,Male,Caucasian,02/08/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +2753,64721,58731,PRETRIAL,SMITH,JOHN,DAVID,Male,Caucasian,11/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +2753,64721,58731,PRETRIAL,SMITH,JOHN,DAVID,Male,Caucasian,11/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +2753,64721,58731,PRETRIAL,SMITH,JOHN,DAVID,Male,Caucasian,11/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +21479,64750,58754,PRETRIAL,caminocasanova,christian,NULL,Male,Caucasian,09/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +21479,64750,58754,PRETRIAL,caminocasanova,christian,NULL,Male,Caucasian,09/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +21479,64750,58754,PRETRIAL,caminocasanova,christian,NULL,Male,Caucasian,09/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56695,64737,58743,Probation,Glover,Roynesto,NULL,Male,African-American,08/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +56695,64737,58743,Probation,Glover,Roynesto,NULL,Male,African-American,08/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +56695,64737,58743,Probation,Glover,Roynesto,NULL,Male,African-American,08/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +12368,64716,58727,PRETRIAL,SIMMON,TERRON,NULL,Male,African-American,01/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,4,High,7,Risk of Violence,-0.73,9,High,New,1,0 +12368,64716,58727,PRETRIAL,SIMMON,TERRON,NULL,Male,African-American,01/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,4,High,8,Risk of Recidivism,1.07,10,High,New,1,0 +12368,64716,58727,PRETRIAL,SIMMON,TERRON,NULL,Male,African-American,01/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +35928,64752,58756,PRETRIAL,RUBIN,WESLEY,NULL,Male,Caucasian,12/21/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +35928,64752,58756,PRETRIAL,RUBIN,WESLEY,NULL,Male,Caucasian,12/21/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +35928,64752,58756,PRETRIAL,RUBIN,WESLEY,NULL,Male,Caucasian,12/21/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53108,64724,58734,Probation,Newson,Timothy,NULL,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +53108,64724,58734,Probation,Newson,Timothy,NULL,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +53108,64724,58734,Probation,Newson,Timothy,NULL,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56710,64758,58760,PRETRIAL,LAMONS,DEREC,NULL,Male,Caucasian,10/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +56710,64758,58760,PRETRIAL,LAMONS,DEREC,NULL,Male,Caucasian,10/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +56710,64758,58760,PRETRIAL,LAMONS,DEREC,NULL,Male,Caucasian,10/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56711,64760,58762,Probation,Lazar,Mircea,NULL,Male,Caucasian,06/06/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/23/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +56711,64760,58762,Probation,Lazar,Mircea,NULL,Male,Caucasian,06/06/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +56711,64760,58762,Probation,Lazar,Mircea,NULL,Male,Caucasian,06/06/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56703,64745,58750,Probation,Washington,Alexandra,Beth,Female,Caucasian,09/15/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/23/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +56703,64745,58750,Probation,Washington,Alexandra,Beth,Female,Caucasian,09/15/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,7,Medium,New,1,0 +56703,64745,58750,Probation,Washington,Alexandra,Beth,Female,Caucasian,09/15/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +8041,64719,58360,PRETRIAL,MYREE,PATRICK,NULL,Male,African-American,11/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,4,High,7,Risk of Violence,-1.24,8,High,Copy,1,0 +8041,64719,58360,PRETRIAL,MYREE,PATRICK,NULL,Male,African-American,11/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,4,High,8,Risk of Recidivism,0.51,9,High,Copy,1,0 +8041,64719,58360,PRETRIAL,MYREE,PATRICK,NULL,Male,African-American,11/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +55964,64733,57888,PRETRIAL,McCloud,Ronald,NULL,Male,African-American,10/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,Copy,1,0 +55964,64733,57888,PRETRIAL,McCloud,Ronald,NULL,Male,African-American,10/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,Copy,1,0 +55964,64733,57888,PRETRIAL,McCloud,Ronald,NULL,Male,African-American,10/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +56704,64747,58752,Probation,Garcia,Jessica,NULL,Female,Hispanic,12/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +56704,64747,58752,Probation,Garcia,Jessica,NULL,Female,Hispanic,12/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,4,High,8,Risk of Recidivism,-0.06,8,High,New,1,0 +56704,64747,58752,Probation,Garcia,Jessica,NULL,Female,Hispanic,12/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56707,64754,58757,PRETRIAL,Dargan,David,M,Male,Caucasian,02/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +56707,64754,58757,PRETRIAL,Dargan,David,M,Male,Caucasian,02/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +56707,64754,58757,PRETRIAL,Dargan,David,M,Male,Caucasian,02/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56708,64756,58758,Probation,CIOPPA,SUZANNE,F,Female,Caucasian,08/01/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/23/13 0:00,1,Low,7,Risk of Violence,-4.38,1,Low,New,1,0 +56708,64756,58758,Probation,CIOPPA,SUZANNE,F,Female,Caucasian,08/01/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/23/13 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +56708,64756,58758,Probation,CIOPPA,SUZANNE,F,Female,Caucasian,08/01/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56697,64740,58746,Probation,Odonnell,Melody,Lee,Female,Caucasian,04/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/23/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +56697,64740,58746,Probation,Odonnell,Melody,Lee,Female,Caucasian,04/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/23/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +56697,64740,58746,Probation,Odonnell,Melody,Lee,Female,Caucasian,04/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56702,64744,58749,Probation,Roberts,Sean,NULL,Male,African-American,08/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/23/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +56702,64744,58749,Probation,Roberts,Sean,NULL,Male,African-American,08/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/23/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +56702,64744,58749,Probation,Roberts,Sean,NULL,Male,African-American,08/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56692,64731,58739,Probation,Ward,Tekeila,NULL,Female,African-American,11/27/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +56692,64731,58739,Probation,Ward,Tekeila,NULL,Female,African-American,11/27/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +56692,64731,58739,Probation,Ward,Tekeila,NULL,Female,African-American,11/27/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +48557,64761,58763,PRETRIAL,Greene,Stephen,NULL,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,New,1,0 +48557,64761,58763,PRETRIAL,Greene,Stephen,NULL,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +48557,64761,58763,PRETRIAL,Greene,Stephen,NULL,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +47225,64714,58725,Probation,harris,alrick,NULL,Male,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +47225,64714,58725,Probation,harris,alrick,NULL,Male,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +47225,64714,58725,Probation,harris,alrick,NULL,Male,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54438,64728,56090,PRETRIAL,Bigger,Clayton,NULL,Male,Caucasian,11/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,Copy,1,0 +54438,64728,56090,PRETRIAL,Bigger,Clayton,NULL,Male,Caucasian,11/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,Copy,1,0 +54438,64728,56090,PRETRIAL,Bigger,Clayton,NULL,Male,Caucasian,11/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +8676,64749,8210,PRETRIAL,JAMES,JAVON,NULL,Male,African-American,11/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,Copy,1,0 +8676,64749,8210,PRETRIAL,JAMES,JAVON,NULL,Male,African-American,11/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,Copy,1,0 +8676,64749,8210,PRETRIAL,JAMES,JAVON,NULL,Male,African-American,11/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +43265,64738,58744,PRETRIAL,AIKEN,BILLY,NULL,Male,African-American,09/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +43265,64738,58744,PRETRIAL,AIKEN,BILLY,NULL,Male,African-American,09/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +43265,64738,58744,PRETRIAL,AIKEN,BILLY,NULL,Male,African-American,09/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52082,64725,58735,PRETRIAL,ESTELHOMME,RALPH,NULL,Male,African-American,09/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +52082,64725,58735,PRETRIAL,ESTELHOMME,RALPH,NULL,Male,African-American,09/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +52082,64725,58735,PRETRIAL,ESTELHOMME,RALPH,NULL,Male,African-American,09/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +50410,64759,58761,PRETRIAL,Evans,Sean,NULL,Male,African-American,12/15/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +50410,64759,58761,PRETRIAL,Evans,Sean,NULL,Male,African-American,12/15/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +50410,64759,58761,PRETRIAL,Evans,Sean,NULL,Male,African-American,12/15/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56685,64717,58728,PRETRIAL,Perez-Betancur,Henry,NULL,Male,Hispanic,08/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +56685,64717,58728,PRETRIAL,Perez-Betancur,Henry,NULL,Male,Hispanic,08/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +56685,64717,58728,PRETRIAL,Perez-Betancur,Henry,NULL,Male,Hispanic,08/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +30915,64746,58751,PRETRIAL,Batista,Jose,NULL,Male,Hispanic,11/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/23/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +30915,64746,58751,PRETRIAL,Batista,Jose,NULL,Male,Hispanic,11/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +30915,64746,58751,PRETRIAL,Batista,Jose,NULL,Male,Hispanic,11/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +13884,64722,58732,PRETRIAL,Daley,Kendrick,NULL,Male,African-American,01/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +13884,64722,58732,PRETRIAL,Daley,Kendrick,NULL,Male,African-American,01/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +13884,64722,58732,PRETRIAL,Daley,Kendrick,NULL,Male,African-American,01/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56701,64743,58748,Probation,Tappenden,Sean,NULL,Male,Caucasian,11/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +56701,64743,58748,Probation,Tappenden,Sean,NULL,Male,Caucasian,11/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +56701,64743,58748,Probation,Tappenden,Sean,NULL,Male,Caucasian,11/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56688,64723,58733,PRETRIAL,Vallejo,Laque,NULL,Female,African-American,02/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +56688,64723,58733,PRETRIAL,Vallejo,Laque,NULL,Female,African-American,02/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +56688,64723,58733,PRETRIAL,Vallejo,Laque,NULL,Female,African-American,02/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56691,64730,58738,PRETRIAL,THORNTON,HELENA,NULL,Female,African-American,03/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +56691,64730,58738,PRETRIAL,THORNTON,HELENA,NULL,Female,African-American,03/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +56691,64730,58738,PRETRIAL,THORNTON,HELENA,NULL,Female,African-American,03/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56684,64715,58726,PRETRIAL,Robinson,David,O,Male,African-American,02/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +56684,64715,58726,PRETRIAL,Robinson,David,O,Male,African-American,02/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +56684,64715,58726,PRETRIAL,Robinson,David,O,Male,African-American,02/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56706,64751,58755,Probation,Hernandez,Katherine,NULL,Female,Hispanic,06/20/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/23/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +56706,64751,58755,Probation,Hernandez,Katherine,NULL,Female,Hispanic,06/20/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/23/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +56706,64751,58755,Probation,Hernandez,Katherine,NULL,Female,Hispanic,06/20/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56713,64764,58766,PRETRIAL,Johnson,Shawanda,Shevel,Female,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/24/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +56713,64764,58766,PRETRIAL,Johnson,Shawanda,Shevel,Female,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/24/13 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +56713,64764,58766,PRETRIAL,Johnson,Shawanda,Shevel,Female,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56716,64767,58769,PRETRIAL,MAYS,LAVENA,YVONNE,Female,Caucasian,04/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +56716,64767,58769,PRETRIAL,MAYS,LAVENA,YVONNE,Female,Caucasian,04/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +56716,64767,58769,PRETRIAL,MAYS,LAVENA,YVONNE,Female,Caucasian,04/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56719,64772,58773,PRETRIAL,Capezzuto,Dante,NULL,Male,Caucasian,04/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.19,4,Low,New,1,0 +56719,64772,58773,PRETRIAL,Capezzuto,Dante,NULL,Male,Caucasian,04/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +56719,64772,58773,PRETRIAL,Capezzuto,Dante,NULL,Male,Caucasian,04/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56718,64770,58771,PRETRIAL,Lherisse,Taketha,Eureka,Female,African-American,05/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +56718,64770,58771,PRETRIAL,Lherisse,Taketha,Eureka,Female,African-American,05/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +56718,64770,58771,PRETRIAL,Lherisse,Taketha,Eureka,Female,African-American,05/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56722,64775,58776,PRETRIAL,Gomez,Justin,Rafael,Male,Hispanic,11/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.97,9,High,New,1,0 +56722,64775,58776,PRETRIAL,Gomez,Justin,Rafael,Male,Hispanic,11/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +56722,64775,58776,PRETRIAL,Gomez,Justin,Rafael,Male,Hispanic,11/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56724,64777,58778,PRETRIAL,Metayer,Kandice,NULL,Female,African-American,12/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +56724,64777,58778,PRETRIAL,Metayer,Kandice,NULL,Female,African-American,12/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +56724,64777,58778,PRETRIAL,Metayer,Kandice,NULL,Female,African-American,12/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56726,64779,58780,PRETRIAL,Rose,Robert,NULL,Male,Caucasian,07/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +56726,64779,58780,PRETRIAL,Rose,Robert,NULL,Male,Caucasian,07/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +56726,64779,58780,PRETRIAL,Rose,Robert,NULL,Male,Caucasian,07/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56714,64765,58767,PRETRIAL,Roman,Epifania,NULL,Male,African-American,10/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +56714,64765,58767,PRETRIAL,Roman,Epifania,NULL,Male,African-American,10/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +56714,64765,58767,PRETRIAL,Roman,Epifania,NULL,Male,African-American,10/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56715,64766,58768,PRETRIAL,GOMEZMARTINEZ,JOANA,NULL,Female,Hispanic,06/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/24/13 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +56715,64766,58768,PRETRIAL,GOMEZMARTINEZ,JOANA,NULL,Female,Hispanic,06/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/24/13 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +56715,64766,58768,PRETRIAL,GOMEZMARTINEZ,JOANA,NULL,Female,Hispanic,06/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56720,64773,58774,PRETRIAL,LEON,ROBERT,ANTHONY,Male,Hispanic,10/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +56720,64773,58774,PRETRIAL,LEON,ROBERT,ANTHONY,Male,Hispanic,10/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +56720,64773,58774,PRETRIAL,LEON,ROBERT,ANTHONY,Male,Hispanic,10/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +49449,64768,50297,PRETRIAL,Slocum,Kiante,NULL,Female,African-American,08/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/24/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,Copy,1,0 +49449,64768,50297,PRETRIAL,Slocum,Kiante,NULL,Female,African-American,08/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/24/13 0:00,4,High,8,Risk of Recidivism,0.03,8,High,Copy,1,0 +49449,64768,50297,PRETRIAL,Slocum,Kiante,NULL,Female,African-American,08/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/24/13 0:00,4,High,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +11494,64771,58772,PRETRIAL,davis,derrius,NULL,Male,African-American,08/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +11494,64771,58772,PRETRIAL,davis,derrius,NULL,Male,African-American,08/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +11494,64771,58772,PRETRIAL,davis,derrius,NULL,Male,African-American,08/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56723,64776,58777,PRETRIAL,McGarth,Brandi,Lynn,Female,Caucasian,08/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +56723,64776,58777,PRETRIAL,McGarth,Brandi,Lynn,Female,Caucasian,08/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +56723,64776,58777,PRETRIAL,McGarth,Brandi,Lynn,Female,Caucasian,08/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56717,64769,58770,PRETRIAL,Sterling,Lloyd,Luther,Male,African-American,05/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +56717,64769,58770,PRETRIAL,Sterling,Lloyd,Luther,Male,African-American,05/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +56717,64769,58770,PRETRIAL,Sterling,Lloyd,Luther,Male,African-American,05/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56721,64774,58775,PRETRIAL,Romero,Roberto,NULL,Male,Hispanic,09/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/24/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +56721,64774,58775,PRETRIAL,Romero,Roberto,NULL,Male,Hispanic,09/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/24/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +56721,64774,58775,PRETRIAL,Romero,Roberto,NULL,Male,Hispanic,09/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/24/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56725,64778,58779,PRETRIAL,Cesar,Riccardo,NULL,Male,African-American,09/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +56725,64778,58779,PRETRIAL,Cesar,Riccardo,NULL,Male,African-American,09/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +56725,64778,58779,PRETRIAL,Cesar,Riccardo,NULL,Male,African-American,09/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +32528,64783,58784,PRETRIAL,CURTISS,JOEL,NULL,Male,African-American,11/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +32528,64783,58784,PRETRIAL,CURTISS,JOEL,NULL,Male,African-American,11/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +32528,64783,58784,PRETRIAL,CURTISS,JOEL,NULL,Male,African-American,11/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +42656,64790,58791,PRETRIAL,Quimbley,Bradley,NULL,Male,African-American,05/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +42656,64790,58791,PRETRIAL,Quimbley,Bradley,NULL,Male,African-American,05/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +42656,64790,58791,PRETRIAL,Quimbley,Bradley,NULL,Male,African-American,05/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56738,64792,58793,PRETRIAL,oliphant,anisha,NULL,Female,African-American,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +56738,64792,58793,PRETRIAL,oliphant,anisha,NULL,Female,African-American,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +56738,64792,58793,PRETRIAL,oliphant,anisha,NULL,Female,African-American,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +43642,47814,43628,PRETRIAL,POWER,TRAVIS,MAURICE,Male,African-American,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,4,High,7,Risk of Violence,-0.31,10,High,New,1,0 +43642,47814,43628,PRETRIAL,POWER,TRAVIS,MAURICE,Male,African-American,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,4,High,8,Risk of Recidivism,0.96,10,High,New,1,0 +43642,47814,43628,PRETRIAL,POWER,TRAVIS,MAURICE,Male,African-American,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56735,64789,58790,PRETRIAL,Ballate,Ulises,NULL,Male,Caucasian,11/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,New,1,0 +56735,64789,58790,PRETRIAL,Ballate,Ulises,NULL,Male,Caucasian,11/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +56735,64789,58790,PRETRIAL,Ballate,Ulises,NULL,Male,Caucasian,11/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56733,64787,58788,PRETRIAL,AUGUSTE,ERWIN,C,Male,African-American,11/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +56733,64787,58788,PRETRIAL,AUGUSTE,ERWIN,C,Male,African-American,11/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +56733,64787,58788,PRETRIAL,AUGUSTE,ERWIN,C,Male,African-American,11/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56728,64781,58782,PRETRIAL,DEMETRIUS,SHAWN,ANTHONY,Male,African-American,06/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +56728,64781,58782,PRETRIAL,DEMETRIUS,SHAWN,ANTHONY,Male,African-American,06/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +56728,64781,58782,PRETRIAL,DEMETRIUS,SHAWN,ANTHONY,Male,African-American,06/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56730,64784,58785,PRETRIAL,Espinosa,Massiel,NULL,Male,Caucasian,03/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +56730,64784,58785,PRETRIAL,Espinosa,Massiel,NULL,Male,Caucasian,03/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +56730,64784,58785,PRETRIAL,Espinosa,Massiel,NULL,Male,Caucasian,03/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56736,64791,58792,PRETRIAL,Abreu,Lucia,NULL,Female,Hispanic,07/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +56736,64791,58792,PRETRIAL,Abreu,Lucia,NULL,Female,Hispanic,07/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +56736,64791,58792,PRETRIAL,Abreu,Lucia,NULL,Female,Hispanic,07/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56729,64782,58783,PRETRIAL,CREIGHTNEY,MICHAEL,GARTH,Male,African-American,05/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +56729,64782,58783,PRETRIAL,CREIGHTNEY,MICHAEL,GARTH,Male,African-American,05/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +56729,64782,58783,PRETRIAL,CREIGHTNEY,MICHAEL,GARTH,Male,African-American,05/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +26082,64793,58794,PRETRIAL,PEAT,ANTHONY,NULL,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +26082,64793,58794,PRETRIAL,PEAT,ANTHONY,NULL,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +26082,64793,58794,PRETRIAL,PEAT,ANTHONY,NULL,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +56731,64785,58786,PRETRIAL,SMITH,ALEXANDRIA,RENEE,Female,African-American,04/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.04,8,High,New,1,0 +56731,64785,58786,PRETRIAL,SMITH,ALEXANDRIA,RENEE,Female,African-American,04/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +56731,64785,58786,PRETRIAL,SMITH,ALEXANDRIA,RENEE,Female,African-American,04/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56727,64780,58781,PRETRIAL,FONTAINE,VLADIMIR,ANDRE,Male,African-American,12/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +56727,64780,58781,PRETRIAL,FONTAINE,VLADIMIR,ANDRE,Male,African-American,12/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +56727,64780,58781,PRETRIAL,FONTAINE,VLADIMIR,ANDRE,Male,African-American,12/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56734,64788,58789,PRETRIAL,SMITH,TROY,RYAN,Male,African-American,09/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +56734,64788,58789,PRETRIAL,SMITH,TROY,RYAN,Male,African-American,09/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +56734,64788,58789,PRETRIAL,SMITH,TROY,RYAN,Male,African-American,09/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +46784,64822,58818,PRETRIAL,gatchair,Kareem,Delroy,Male,African-American,03/18/85,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/26/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +46784,64822,58818,PRETRIAL,gatchair,Kareem,Delroy,Male,African-American,03/18/85,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +46784,64822,58818,PRETRIAL,gatchair,Kareem,Delroy,Male,African-American,03/18/85,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44615,64809,52898,PRETRIAL,GLASCO,AARON,CHRISTOPHE,Male,African-American,09/29/91,17,All Scales,Intake,English,Post Sentence,Probation,Significant Other,8/26/13 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +44615,64809,52898,PRETRIAL,GLASCO,AARON,CHRISTOPHE,Male,African-American,09/29/91,17,All Scales,Intake,English,Post Sentence,Probation,Significant Other,8/26/13 0:00,4,High,8,Risk of Recidivism,0.32,8,High,New,1,0 +44615,64809,52898,PRETRIAL,GLASCO,AARON,CHRISTOPHE,Male,African-American,09/29/91,17,All Scales,Intake,English,Post Sentence,Probation,Significant Other,8/26/13 0:00,4,High,18,Risk of Failure to Appear,16,1,Low,New,1,0 +56759,64824,58820,PRETRIAL,BAPTISTE,MARIO,NULL,Male,African-American,02/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +56759,64824,58820,PRETRIAL,BAPTISTE,MARIO,NULL,Male,African-American,02/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +56759,64824,58820,PRETRIAL,BAPTISTE,MARIO,NULL,Male,African-American,02/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56764,64830,58826,Probation,segal,derek,NULL,Male,Caucasian,05/07/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +56764,64830,58826,Probation,segal,derek,NULL,Male,Caucasian,05/07/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +56764,64830,58826,Probation,segal,derek,NULL,Male,Caucasian,05/07/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56770,64837,58833,Probation,Watson,Tahesha,NULL,Female,African-American,05/02/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.19,4,Low,New,1,0 +56770,64837,58833,Probation,Watson,Tahesha,NULL,Female,African-American,05/02/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,8,High,New,1,0 +56770,64837,58833,Probation,Watson,Tahesha,NULL,Female,African-American,05/02/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56745,64801,58802,PRETRIAL,McKenzie,Eric,NULL,Male,African-American,03/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,4,High,7,Risk of Violence,-0.45,10,High,New,1,0 +56745,64801,58802,PRETRIAL,McKenzie,Eric,NULL,Male,African-American,03/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,4,High,8,Risk of Recidivism,0.44,9,High,New,1,0 +56745,64801,58802,PRETRIAL,McKenzie,Eric,NULL,Male,African-American,03/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56754,64816,58812,Probation,carrillo,norlan,NULL,Male,Hispanic,04/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +56754,64816,58812,Probation,carrillo,norlan,NULL,Male,Hispanic,04/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +56754,64816,58812,Probation,carrillo,norlan,NULL,Male,Hispanic,04/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +45266,64832,58828,PRETRIAL,ORTIZ,JULIAN,NULL,Male,Hispanic,09/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +45266,64832,58828,PRETRIAL,ORTIZ,JULIAN,NULL,Male,Hispanic,09/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +45266,64832,58828,PRETRIAL,ORTIZ,JULIAN,NULL,Male,Hispanic,09/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56768,64835,58831,Probation,Zabilski,Wayne,NULL,Male,Caucasian,10/09/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.99,4,Low,New,1,0 +56768,64835,58831,Probation,Zabilski,Wayne,NULL,Male,Caucasian,10/09/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +56768,64835,58831,Probation,Zabilski,Wayne,NULL,Male,Caucasian,10/09/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +49427,64814,50269,PRETRIAL,Morris,Antoine,Kendrick,Male,African-American,11/24/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,Copy,1,0 +49427,64814,50269,PRETRIAL,Morris,Antoine,Kendrick,Male,African-American,11/24/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,Copy,1,0 +49427,64814,50269,PRETRIAL,Morris,Antoine,Kendrick,Male,African-American,11/24/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +56761,64827,58823,Probation,Cooper,Devin,NULL,Male,African-American,11/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +56761,64827,58823,Probation,Cooper,Devin,NULL,Male,African-American,11/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +56761,64827,58823,Probation,Cooper,Devin,NULL,Male,African-American,11/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +46271,64806,58807,PRETRIAL,Barry,Brian,Mclane,Male,Caucasian,11/15/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +46271,64806,58807,PRETRIAL,Barry,Brian,Mclane,Male,Caucasian,11/15/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +46271,64806,58807,PRETRIAL,Barry,Brian,Mclane,Male,Caucasian,11/15/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +33017,64840,58835,PRETRIAL,Patnaude,Philip,NULL,Male,Caucasian,06/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,2,Medium,7,Risk of Violence,-2.57,2,Low,New,1,0 +33017,64840,58835,PRETRIAL,Patnaude,Philip,NULL,Male,Caucasian,06/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +33017,64840,58835,PRETRIAL,Patnaude,Philip,NULL,Male,Caucasian,06/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56744,64800,58801,PRETRIAL,Miller,Barnabas,William,Male,Caucasian,07/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +56744,64800,58801,PRETRIAL,Miller,Barnabas,William,Male,Caucasian,07/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +56744,64800,58801,PRETRIAL,Miller,Barnabas,William,Male,Caucasian,07/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +48935,64817,58813,PRETRIAL,FLOREZ,JOBANY,NULL,Male,Caucasian,10/19/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +48935,64817,58813,PRETRIAL,FLOREZ,JOBANY,NULL,Male,Caucasian,10/19/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +48935,64817,58813,PRETRIAL,FLOREZ,JOBANY,NULL,Male,Caucasian,10/19/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +1126,64796,58797,PRETRIAL,GIPSON,JAVIER,JAVON,Male,African-American,07/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.47,3,Low,New,1,0 +1126,64796,58797,PRETRIAL,GIPSON,JAVIER,JAVON,Male,African-American,07/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +1126,64796,58797,PRETRIAL,GIPSON,JAVIER,JAVON,Male,African-American,07/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +56747,64803,58804,PRETRIAL,JENSEN,WAYNE,NULL,Male,Caucasian,07/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +56747,64803,58804,PRETRIAL,JENSEN,WAYNE,NULL,Male,Caucasian,07/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +56747,64803,58804,PRETRIAL,JENSEN,WAYNE,NULL,Male,Caucasian,07/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56758,64821,58817,PRETRIAL,Hartsock,John,R,Male,Caucasian,03/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +56758,64821,58817,PRETRIAL,Hartsock,John,R,Male,Caucasian,03/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +56758,64821,58817,PRETRIAL,Hartsock,John,R,Male,Caucasian,03/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56756,64819,58815,Probation,Abdel-Rahman,Mohamad,NULL,Male,African-American,11/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +56756,64819,58815,Probation,Abdel-Rahman,Mohamad,NULL,Male,African-American,11/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +56756,64819,58815,Probation,Abdel-Rahman,Mohamad,NULL,Male,African-American,11/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56766,64833,58829,Probation,Pierre Charles,Wilny,NULL,Male,African-American,07/30/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +56766,64833,58829,Probation,Pierre Charles,Wilny,NULL,Male,African-American,07/30/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +56766,64833,58829,Probation,Pierre Charles,Wilny,NULL,Male,African-American,07/30/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56742,64798,58799,PRETRIAL,Rijos,Gino,NULL,Male,Caucasian,06/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +56742,64798,58799,PRETRIAL,Rijos,Gino,NULL,Male,Caucasian,06/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +56742,64798,58799,PRETRIAL,Rijos,Gino,NULL,Male,Caucasian,06/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56749,64805,58806,Probation,Reed,David,Lee,Male,African-American,02/17/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +56749,64805,58806,Probation,Reed,David,Lee,Male,African-American,02/17/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +56749,64805,58806,Probation,Reed,David,Lee,Male,African-American,02/17/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56752,64812,58810,Probation,Carrio,Alex,NULL,Male,Caucasian,03/31/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +56752,64812,58810,Probation,Carrio,Alex,NULL,Male,Caucasian,03/31/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +56752,64812,58810,Probation,Carrio,Alex,NULL,Male,Caucasian,03/31/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56760,64826,58822,Probation,meneses,estefania,NULL,Female,Hispanic,05/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +56760,64826,58822,Probation,meneses,estefania,NULL,Female,Hispanic,05/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,New,1,0 +56760,64826,58822,Probation,meneses,estefania,NULL,Female,Hispanic,05/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56753,64815,58811,Probation,Stubbs,James,NULL,Male,African-American,02/02/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +56753,64815,58811,Probation,Stubbs,James,NULL,Male,African-American,02/02/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +56753,64815,58811,Probation,Stubbs,James,NULL,Male,African-American,02/02/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56739,64794,58795,PRETRIAL,KONIJA,SCOTT,NULL,Male,Caucasian,11/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +56739,64794,58795,PRETRIAL,KONIJA,SCOTT,NULL,Male,Caucasian,11/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +56739,64794,58795,PRETRIAL,KONIJA,SCOTT,NULL,Male,Caucasian,11/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56750,64807,58808,Probation,Infante,Marc,NULL,Male,Caucasian,09/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +56750,64807,58808,Probation,Infante,Marc,NULL,Male,Caucasian,09/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +56750,64807,58808,Probation,Infante,Marc,NULL,Male,Caucasian,09/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +8061,64823,58819,PRETRIAL,Hodge,Kerry,NULL,Male,African-American,10/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +8061,64823,58819,PRETRIAL,Hodge,Kerry,NULL,Male,African-American,10/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +8061,64823,58819,PRETRIAL,Hodge,Kerry,NULL,Male,African-American,10/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56746,64802,58803,PRETRIAL,Afu,Semisi,NULL,Male,Other,04/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +56746,64802,58803,PRETRIAL,Afu,Semisi,NULL,Male,Other,04/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +56746,64802,58803,PRETRIAL,Afu,Semisi,NULL,Male,Other,04/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56771,64839,58834,Probation,Zukowski,Alycia,NULL,Female,Caucasian,12/29/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +56771,64839,58834,Probation,Zukowski,Alycia,NULL,Female,Caucasian,12/29/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +56771,64839,58834,Probation,Zukowski,Alycia,NULL,Female,Caucasian,12/29/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56755,64818,58814,Probation,freije,christopher,NULL,Male,Caucasian,05/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +56755,64818,58814,Probation,freije,christopher,NULL,Male,Caucasian,05/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +56755,64818,58814,Probation,freije,christopher,NULL,Male,Caucasian,05/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55971,64810,57895,Probation,Pina,Jose,NULL,Male,Hispanic,05/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +55971,64810,57895,Probation,Pina,Jose,NULL,Male,Hispanic,05/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +55971,64810,57895,Probation,Pina,Jose,NULL,Male,Hispanic,05/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56741,64797,58798,PRETRIAL,Gaston,Lawrence,NULL,Male,African-American,04/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +56741,64797,58798,PRETRIAL,Gaston,Lawrence,NULL,Male,African-American,04/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +56741,64797,58798,PRETRIAL,Gaston,Lawrence,NULL,Male,African-American,04/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56765,64831,58827,PRETRIAL,MARTINEZ,ARTURO,NULL,Male,Hispanic,10/23/87,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +56765,64831,58827,PRETRIAL,MARTINEZ,ARTURO,NULL,Male,Hispanic,10/23/87,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +56765,64831,58827,PRETRIAL,MARTINEZ,ARTURO,NULL,Male,Hispanic,10/23/87,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56772,64841,58836,PRETRIAL,HANNER,LUKE,NULL,Male,Caucasian,04/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.88,9,High,New,1,0 +56772,64841,58836,PRETRIAL,HANNER,LUKE,NULL,Male,Caucasian,04/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +56772,64841,58836,PRETRIAL,HANNER,LUKE,NULL,Male,Caucasian,04/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54708,64811,56414,PRETRIAL,Sisco,Jenice,NULL,Female,Caucasian,03/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,Copy,1,0 +54708,64811,56414,PRETRIAL,Sisco,Jenice,NULL,Female,Caucasian,03/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,Copy,1,0 +54708,64811,56414,PRETRIAL,Sisco,Jenice,NULL,Female,Caucasian,03/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +55971,64813,57895,Probation,Pina,Jose,NULL,Male,Hispanic,05/03/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +55971,64813,57895,Probation,Pina,Jose,NULL,Male,Hispanic,05/03/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +55971,64813,57895,Probation,Pina,Jose,NULL,Male,Hispanic,05/03/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56757,64820,58816,Probation,barnett,larry,jerome,Male,African-American,05/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +56757,64820,58816,Probation,barnett,larry,jerome,Male,African-American,05/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +56757,64820,58816,Probation,barnett,larry,jerome,Male,African-American,05/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56767,64834,58830,PRETRIAL,OLIVACONSUEGRA,ANA,NULL,Male,Hispanic,03/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +56767,64834,58830,PRETRIAL,OLIVACONSUEGRA,ANA,NULL,Male,Hispanic,03/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +56767,64834,58830,PRETRIAL,OLIVACONSUEGRA,ANA,NULL,Male,Hispanic,03/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56743,64799,58800,PRETRIAL,MELTON,XAVIER,NULL,Male,African-American,02/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +56743,64799,58800,PRETRIAL,MELTON,XAVIER,NULL,Male,African-American,02/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +56743,64799,58800,PRETRIAL,MELTON,XAVIER,NULL,Male,African-American,02/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +49911,64808,58809,PRETRIAL,Delgado,Mike,NULL,Male,Caucasian,08/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +49911,64808,58809,PRETRIAL,Delgado,Mike,NULL,Male,Caucasian,08/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +49911,64808,58809,PRETRIAL,Delgado,Mike,NULL,Male,Caucasian,08/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +37826,64825,58821,PRETRIAL,horna,joseph,NULL,Male,Caucasian,06/01/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +37826,64825,58821,PRETRIAL,horna,joseph,NULL,Male,Caucasian,06/01/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +37826,64825,58821,PRETRIAL,horna,joseph,NULL,Male,Caucasian,06/01/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56740,64795,58796,PRETRIAL,Bumpers,Matthew,NULL,Male,African-American,11/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +56740,64795,58796,PRETRIAL,Bumpers,Matthew,NULL,Male,African-American,11/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +56740,64795,58796,PRETRIAL,Bumpers,Matthew,NULL,Male,African-American,11/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56748,64804,58805,Probation,busch,keith,NULL,Male,Caucasian,01/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +56748,64804,58805,Probation,busch,keith,NULL,Male,Caucasian,01/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +56748,64804,58805,Probation,busch,keith,NULL,Male,Caucasian,01/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56763,64829,58825,Probation,DeLevy,Lorena,Patricia,Female,Hispanic,04/04/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/26/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +56763,64829,58825,Probation,DeLevy,Lorena,Patricia,Female,Hispanic,04/04/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/26/13 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +56763,64829,58825,Probation,DeLevy,Lorena,Patricia,Female,Hispanic,04/04/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51675,64897,58882,Probation,Salerno,John,NULL,Male,Caucasian,09/29/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +51675,64897,58882,Probation,Salerno,John,NULL,Male,Caucasian,09/29/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +51675,64897,58882,Probation,Salerno,John,NULL,Male,Caucasian,09/29/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56797,64876,58862,PRETRIAL,Miller,Marlon,m,Male,African-American,10/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +56797,64876,58862,PRETRIAL,Miller,Marlon,m,Male,African-American,10/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +56797,64876,58862,PRETRIAL,Miller,Marlon,m,Male,African-American,10/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56778,64850,58844,PRETRIAL,Barnes,Breon,Donte,Male,African-American,01/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +56778,64850,58844,PRETRIAL,Barnes,Breon,Donte,Male,African-American,01/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +56778,64850,58844,PRETRIAL,Barnes,Breon,Donte,Male,African-American,01/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +49739,64867,53723,PRETRIAL,Wallace,Taquan,NULL,Male,African-American,10/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,Copy,1,0 +49739,64867,53723,PRETRIAL,Wallace,Taquan,NULL,Male,African-American,10/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,Copy,1,0 +49739,64867,53723,PRETRIAL,Wallace,Taquan,NULL,Male,African-American,10/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +31068,64885,58870,PRETRIAL,cooper,tarike,NULL,Male,African-American,09/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +31068,64885,58870,PRETRIAL,cooper,tarike,NULL,Male,African-American,09/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +31068,64885,58870,PRETRIAL,cooper,tarike,NULL,Male,African-American,09/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56775,64846,58841,PRETRIAL,Garcia,Sammy,NULL,Male,Hispanic,11/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/27/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +56775,64846,58841,PRETRIAL,Garcia,Sammy,NULL,Male,Hispanic,11/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +56775,64846,58841,PRETRIAL,Garcia,Sammy,NULL,Male,Hispanic,11/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55394,64864,57244,Probation,thomas,fernanda,NULL,Female,Caucasian,11/05/87,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,8/27/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +55394,64864,57244,Probation,thomas,fernanda,NULL,Female,Caucasian,11/05/87,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.54,5,Medium,New,1,0 +55394,64864,57244,Probation,thomas,fernanda,NULL,Female,Caucasian,11/05/87,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56792,64871,58857,Probation,rodriguez,raymond,NULL,Male,Hispanic,03/10/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/27/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +56792,64871,58857,Probation,rodriguez,raymond,NULL,Male,Hispanic,03/10/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +56792,64871,58857,Probation,rodriguez,raymond,NULL,Male,Hispanic,03/10/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56791,64869,58855,PRETRIAL,KANEFSKY,AUSTIN,NULL,Male,Caucasian,02/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +56791,64869,58855,PRETRIAL,KANEFSKY,AUSTIN,NULL,Male,Caucasian,02/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +56791,64869,58855,PRETRIAL,KANEFSKY,AUSTIN,NULL,Male,Caucasian,02/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +28827,64883,58868,PRETRIAL,Piens,Edward,NULL,Male,Caucasian,12/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +28827,64883,58868,PRETRIAL,Piens,Edward,NULL,Male,Caucasian,12/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +28827,64883,58868,PRETRIAL,Piens,Edward,NULL,Male,Caucasian,12/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56776,64848,58842,PRETRIAL,LIZIBELL,AVILES,STEPHANIE,Female,Caucasian,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +56776,64848,58842,PRETRIAL,LIZIBELL,AVILES,STEPHANIE,Female,Caucasian,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +56776,64848,58842,PRETRIAL,LIZIBELL,AVILES,STEPHANIE,Female,Caucasian,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +35842,64855,58848,PRETRIAL,Cabrera,Pablo,NULL,Male,Caucasian,09/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +35842,64855,58848,PRETRIAL,Cabrera,Pablo,NULL,Male,Caucasian,09/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +35842,64855,58848,PRETRIAL,Cabrera,Pablo,NULL,Male,Caucasian,09/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +4436,64862,45431,PRETRIAL,PINA,RAUL,NULL,Male,Hispanic,04/21/69,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +4436,64862,45431,PRETRIAL,PINA,RAUL,NULL,Male,Hispanic,04/21/69,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,6,Medium,New,1,0 +4436,64862,45431,PRETRIAL,PINA,RAUL,NULL,Male,Hispanic,04/21/69,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,2,Medium,18,Risk of Failure to Appear,31,8,High,New,1,0 +49739,59132,53723,PRETRIAL,Wallace,Taquan,NULL,Male,African-American,10/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +49739,59132,53723,PRETRIAL,Wallace,Taquan,NULL,Male,African-American,10/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +49739,59132,53723,PRETRIAL,Wallace,Taquan,NULL,Male,African-American,10/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56808,64890,58875,Probation,Thomas,Yadira,NULL,Female,Hispanic,12/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +56808,64890,58875,Probation,Thomas,Yadira,NULL,Female,Hispanic,12/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +56808,64890,58875,Probation,Thomas,Yadira,NULL,Female,Hispanic,12/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56810,64892,58877,PRETRIAL,Dukes,Diamond,NULL,Female,African-American,04/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +56810,64892,58877,PRETRIAL,Dukes,Diamond,NULL,Female,African-American,04/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,9,High,New,1,0 +56810,64892,58877,PRETRIAL,Dukes,Diamond,NULL,Female,African-American,04/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56788,64865,58853,PRETRIAL,MCINTYRE,TANESHA,MARIE,Female,African-American,02/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +56788,64865,58853,PRETRIAL,MCINTYRE,TANESHA,MARIE,Female,African-American,02/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +56788,64865,58853,PRETRIAL,MCINTYRE,TANESHA,MARIE,Female,African-American,02/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56793,64870,58856,PRETRIAL,Rodriquez,Osvaldo,NULL,Male,Hispanic,03/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/27/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +56793,64870,58856,PRETRIAL,Rodriquez,Osvaldo,NULL,Male,Hispanic,03/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/27/13 0:00,1,Low,8,Risk of Recidivism,-2.7,1,Low,New,1,0 +56793,64870,58856,PRETRIAL,Rodriquez,Osvaldo,NULL,Male,Hispanic,03/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56774,64844,58839,PRETRIAL,Dieujuste,Dalphley,NULL,Male,Other,08/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +56774,64844,58839,PRETRIAL,Dieujuste,Dalphley,NULL,Male,Other,08/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +56774,64844,58839,PRETRIAL,Dieujuste,Dalphley,NULL,Male,Other,08/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +13306,64857,12711,Probation,mompremier,john,NULL,Male,African-American,11/12/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,Copy,1,0 +13306,64857,12711,Probation,mompremier,john,NULL,Male,African-American,11/12/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,Copy,1,0 +13306,64857,12711,Probation,mompremier,john,NULL,Male,African-American,11/12/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +56809,64891,58876,Probation,WILLIAMS,DANIEL,J,Male,African-American,06/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +56809,64891,58876,Probation,WILLIAMS,DANIEL,J,Male,African-American,06/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +56809,64891,58876,Probation,WILLIAMS,DANIEL,J,Male,African-American,06/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56777,64849,58843,PRETRIAL,Daniels,Rodney,John,Male,African-American,01/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/27/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +56777,64849,58843,PRETRIAL,Daniels,Rodney,John,Male,African-American,01/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/27/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +56777,64849,58843,PRETRIAL,Daniels,Rodney,John,Male,African-American,01/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56805,64886,58871,Probation,CASTRILLO,ORLANDO,J,Male,Hispanic,04/06/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +56805,64886,58871,Probation,CASTRILLO,ORLANDO,J,Male,Hispanic,04/06/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +56805,64886,58871,Probation,CASTRILLO,ORLANDO,J,Male,Hispanic,04/06/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56817,64899,58884,Probation,thomas,kenton,NULL,Male,African-American,07/07/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +56817,64899,58884,Probation,thomas,kenton,NULL,Male,African-American,07/07/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +56817,64899,58884,Probation,thomas,kenton,NULL,Male,African-American,07/07/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56798,64878,58863,Probation,Perez,Angel,NULL,Male,Hispanic,11/13/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +56798,64878,58863,Probation,Perez,Angel,NULL,Male,Hispanic,11/13/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +56798,64878,58863,Probation,Perez,Angel,NULL,Male,Hispanic,11/13/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56813,64896,58881,Probation,Santos,Jose,Rafael,Male,Hispanic,12/31/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/27/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +56813,64896,58881,Probation,Santos,Jose,Rafael,Male,Hispanic,12/31/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +56813,64896,58881,Probation,Santos,Jose,Rafael,Male,Hispanic,12/31/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51502,64852,58846,PRETRIAL,Gray,Dwight,NULL,Male,African-American,06/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +51502,64852,58846,PRETRIAL,Gray,Dwight,NULL,Male,African-American,06/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +51502,64852,58846,PRETRIAL,Gray,Dwight,NULL,Male,African-American,06/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56819,64901,58886,Probation,ROBLES,ROBERTO,NULL,Male,Hispanic,02/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +56819,64901,58886,Probation,ROBLES,ROBERTO,NULL,Male,Hispanic,02/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +56819,64901,58886,Probation,ROBLES,ROBERTO,NULL,Male,Hispanic,02/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56820,64902,58887,PRETRIAL,QUINN,ALBERT,C,Male,African-American,04/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +56820,64902,58887,PRETRIAL,QUINN,ALBERT,C,Male,African-American,04/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +56820,64902,58887,PRETRIAL,QUINN,ALBERT,C,Male,African-American,04/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +56795,64873,58859,PRETRIAL,shivers,Eric,NULL,Male,African-American,01/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +56795,64873,58859,PRETRIAL,shivers,Eric,NULL,Male,African-American,01/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +56795,64873,58859,PRETRIAL,shivers,Eric,NULL,Male,African-American,01/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56800,64880,58865,Probation,smallberger,christoffel,NULL,Male,Caucasian,05/11/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +56800,64880,58865,Probation,smallberger,christoffel,NULL,Male,Caucasian,05/11/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +56800,64880,58865,Probation,smallberger,christoffel,NULL,Male,Caucasian,05/11/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55750,64860,57636,PRETRIAL,Harper,Daniel,NULL,Male,Caucasian,06/01/71,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +55750,64860,57636,PRETRIAL,Harper,Daniel,NULL,Male,Caucasian,06/01/71,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,6,Medium,New,1,0 +55750,64860,57636,PRETRIAL,Harper,Daniel,NULL,Male,Caucasian,06/01/71,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +56812,64894,58879,PRETRIAL,PEREZ,ANDRES,NULL,Male,Other,01/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/27/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +56812,64894,58879,PRETRIAL,PEREZ,ANDRES,NULL,Male,Other,01/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +56812,64894,58879,PRETRIAL,PEREZ,ANDRES,NULL,Male,Other,01/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56801,64881,58866,PRETRIAL,Tiahrt,Philip,NULL,Male,Caucasian,07/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +56801,64881,58866,PRETRIAL,Tiahrt,Philip,NULL,Male,Caucasian,07/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +56801,64881,58866,PRETRIAL,Tiahrt,Philip,NULL,Male,Caucasian,07/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +2462,64875,58861,PRETRIAL,PERRONE,VICTORINO,NULL,Male,Caucasian,03/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +2462,64875,58861,PRETRIAL,PERRONE,VICTORINO,NULL,Male,Caucasian,03/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +2462,64875,58861,PRETRIAL,PERRONE,VICTORINO,NULL,Male,Caucasian,03/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +40810,64877,56813,PRETRIAL,Ellis,Robert,NULL,Male,African-American,09/14/87,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +40810,64877,56813,PRETRIAL,Ellis,Robert,NULL,Male,African-American,09/14/87,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +40810,64877,56813,PRETRIAL,Ellis,Robert,NULL,Male,African-American,09/14/87,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +40374,64847,39979,PRETRIAL,Garland,Jermaine,NULL,Male,Caucasian,10/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,Copy,1,0 +40374,64847,39979,PRETRIAL,Garland,Jermaine,NULL,Male,Caucasian,10/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,Copy,1,0 +40374,64847,39979,PRETRIAL,Garland,Jermaine,NULL,Male,Caucasian,10/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +56784,64856,58849,PRETRIAL,Clare,Norman,NULL,Male,African-American,03/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +56784,64856,58849,PRETRIAL,Clare,Norman,NULL,Male,African-American,03/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +56784,64856,58849,PRETRIAL,Clare,Norman,NULL,Male,African-American,03/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56816,64898,58883,PRETRIAL,Galarza,Ronald,NULL,Male,Hispanic,04/02/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,New,1,0 +56816,64898,58883,PRETRIAL,Galarza,Ronald,NULL,Male,Hispanic,04/02/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +56816,64898,58883,PRETRIAL,Galarza,Ronald,NULL,Male,Hispanic,04/02/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56803,64884,58869,Probation,Meran,Wilkins,NULL,Male,Hispanic,01/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +56803,64884,58869,Probation,Meran,Wilkins,NULL,Male,Hispanic,01/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +56803,64884,58869,Probation,Meran,Wilkins,NULL,Male,Hispanic,01/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55566,64889,58874,Probation,Givens,Caroline,NULL,Female,Caucasian,01/16/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,2,Medium,7,Risk of Violence,-2.27,3,Low,New,1,0 +55566,64889,58874,Probation,Givens,Caroline,NULL,Female,Caucasian,01/16/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +55566,64889,58874,Probation,Givens,Caroline,NULL,Female,Caucasian,01/16/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56789,64868,58854,Probation,Ervin,Danielle,NULL,Female,African-American,05/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +56789,64868,58854,Probation,Ervin,Danielle,NULL,Female,African-American,05/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,8,High,New,1,0 +56789,64868,58854,Probation,Ervin,Danielle,NULL,Female,African-American,05/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56785,64859,58851,Probation,SMILEY,ANTOINE,T,Male,African-American,07/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +56785,64859,58851,Probation,SMILEY,ANTOINE,T,Male,African-American,07/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +56785,64859,58851,Probation,SMILEY,ANTOINE,T,Male,African-American,07/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56811,64893,58878,Probation,saintjean,luckner,NULL,Male,African-American,11/09/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/27/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +56811,64893,58878,Probation,saintjean,luckner,NULL,Male,African-American,11/09/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +56811,64893,58878,Probation,saintjean,luckner,NULL,Male,African-American,11/09/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +8772,64863,56602,PRETRIAL,Walker,Marcus,NULL,Male,African-American,11/26/90,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,4,High,7,Risk of Violence,-0.64,9,High,New,1,0 +8772,64863,56602,PRETRIAL,Walker,Marcus,NULL,Male,African-American,11/26/90,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,4,High,8,Risk of Recidivism,0.64,9,High,New,1,0 +8772,64863,56602,PRETRIAL,Walker,Marcus,NULL,Male,African-American,11/26/90,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56794,64872,58858,Probation,Fiorenza,Christian,Joseph,Male,Caucasian,02/20/64,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/27/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +56794,64872,58858,Probation,Fiorenza,Christian,Joseph,Male,Caucasian,02/20/64,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +56794,64872,58858,Probation,Fiorenza,Christian,Joseph,Male,Caucasian,02/20/64,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +56814,64895,58880,PRETRIAL,HOYOS,MARCELA,NULL,Female,Hispanic,10/13/79,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +56814,64895,58880,PRETRIAL,HOYOS,MARCELA,NULL,Female,Hispanic,10/13/79,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +56814,64895,58880,PRETRIAL,HOYOS,MARCELA,NULL,Female,Hispanic,10/13/79,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56787,64861,58852,PRETRIAL,MONROE,DARWIN,NULL,Male,African-American,09/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +56787,64861,58852,PRETRIAL,MONROE,DARWIN,NULL,Male,African-American,09/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +56787,64861,58852,PRETRIAL,MONROE,DARWIN,NULL,Male,African-American,09/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56796,64874,58860,Probation,Johnson,Braden,NULL,Male,Caucasian,10/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +56796,64874,58860,Probation,Johnson,Braden,NULL,Male,Caucasian,10/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +56796,64874,58860,Probation,Johnson,Braden,NULL,Male,Caucasian,10/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56780,64853,58847,PRETRIAL,Manson,Leon,NULL,Male,African-American,11/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +56780,64853,58847,PRETRIAL,Manson,Leon,NULL,Male,African-American,11/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +56780,64853,58847,PRETRIAL,Manson,Leon,NULL,Male,African-American,11/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56802,64882,58867,PRETRIAL,Tuff,Alton,NULL,Male,African-American,07/29/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +56802,64882,58867,PRETRIAL,Tuff,Alton,NULL,Male,African-American,07/29/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +56802,64882,58867,PRETRIAL,Tuff,Alton,NULL,Male,African-American,07/29/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56818,64900,58885,PRETRIAL,Briceno,Michelle,NULL,Female,Caucasian,02/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/27/13 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +56818,64900,58885,PRETRIAL,Briceno,Michelle,NULL,Female,Caucasian,02/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +56818,64900,58885,PRETRIAL,Briceno,Michelle,NULL,Female,Caucasian,02/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/27/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56779,64851,58845,PRETRIAL,Tarver,Ruthie,Rumph,Female,African-American,06/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +56779,64851,58845,PRETRIAL,Tarver,Ruthie,Rumph,Female,African-American,06/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +56779,64851,58845,PRETRIAL,Tarver,Ruthie,Rumph,Female,African-American,06/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56773,64843,58838,PRETRIAL,BLUE,SHAWANNA,NULL,Female,African-American,02/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +56773,64843,58838,PRETRIAL,BLUE,SHAWANNA,NULL,Female,African-American,02/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +56773,64843,58838,PRETRIAL,BLUE,SHAWANNA,NULL,Female,African-American,02/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56786,64858,58850,PRETRIAL,Hostios,Mauricio,NULL,Male,Hispanic,05/29/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/27/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +56786,64858,58850,PRETRIAL,Hostios,Mauricio,NULL,Male,Hispanic,05/29/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/27/13 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +56786,64858,58850,PRETRIAL,Hostios,Mauricio,NULL,Male,Hispanic,05/29/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +46884,64845,58840,PRETRIAL,Ruiz,Rayman,NULL,Male,Hispanic,05/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +46884,64845,58840,PRETRIAL,Ruiz,Rayman,NULL,Male,Hispanic,05/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +46884,64845,58840,PRETRIAL,Ruiz,Rayman,NULL,Male,Hispanic,05/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56799,64879,58864,PRETRIAL,teruggi,roberto,NULL,Male,Caucasian,07/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +56799,64879,58864,PRETRIAL,teruggi,roberto,NULL,Male,Caucasian,07/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +56799,64879,58864,PRETRIAL,teruggi,roberto,NULL,Male,Caucasian,07/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56837,64924,58905,PRETRIAL,MASOOD,HARIS,NULL,Male,Native American,01/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +56837,64924,58905,PRETRIAL,MASOOD,HARIS,NULL,Male,Native American,01/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +56837,64924,58905,PRETRIAL,MASOOD,HARIS,NULL,Male,Native American,01/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56832,64916,58900,PRETRIAL,Golston,Whitney,NULL,Female,African-American,05/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/28/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +56832,64916,58900,PRETRIAL,Golston,Whitney,NULL,Female,African-American,05/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/28/13 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +56832,64916,58900,PRETRIAL,Golston,Whitney,NULL,Female,African-American,05/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56847,64937,58917,Probation,Broder,Christina,NULL,Female,Caucasian,01/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/28/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +56847,64937,58917,Probation,Broder,Christina,NULL,Female,Caucasian,01/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +56847,64937,58917,Probation,Broder,Christina,NULL,Female,Caucasian,01/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56821,64903,58888,PRETRIAL,Keltner,Donald,Andrew,Male,Caucasian,06/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +56821,64903,58888,PRETRIAL,Keltner,Donald,Andrew,Male,Caucasian,06/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +56821,64903,58888,PRETRIAL,Keltner,Donald,Andrew,Male,Caucasian,06/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56825,64908,58892,PRETRIAL,Funez,Mauro,Roger,Male,Caucasian,10/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +56825,64908,58892,PRETRIAL,Funez,Mauro,Roger,Male,Caucasian,10/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +56825,64908,58892,PRETRIAL,Funez,Mauro,Roger,Male,Caucasian,10/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56849,64942,58922,Probation,abreu,flaviano,o,Male,Caucasian,02/17/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +56849,64942,58922,Probation,abreu,flaviano,o,Male,Caucasian,02/17/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +56849,64942,58922,Probation,abreu,flaviano,o,Male,Caucasian,02/17/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56841,64929,58909,Probation,Haynes,Jeffrey,NULL,Male,African-American,08/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +56841,64929,58909,Probation,Haynes,Jeffrey,NULL,Male,African-American,08/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +56841,64929,58909,Probation,Haynes,Jeffrey,NULL,Male,African-American,08/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +32363,64931,58911,PRETRIAL,Mendez,Jesus,NULL,Male,Caucasian,10/03/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +32363,64931,58911,PRETRIAL,Mendez,Jesus,NULL,Male,Caucasian,10/03/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +32363,64931,58911,PRETRIAL,Mendez,Jesus,NULL,Male,Caucasian,10/03/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +47172,64940,58920,PRETRIAL,Hassan,Gregory,NULL,Male,Caucasian,04/19/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +47172,64940,58920,PRETRIAL,Hassan,Gregory,NULL,Male,Caucasian,04/19/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +47172,64940,58920,PRETRIAL,Hassan,Gregory,NULL,Male,Caucasian,04/19/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56827,64910,58894,PRETRIAL,Whitehead,Eddie,NULL,Male,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +56827,64910,58894,PRETRIAL,Whitehead,Eddie,NULL,Male,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +56827,64910,58894,PRETRIAL,Whitehead,Eddie,NULL,Male,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +46814,64944,58924,Probation,OWENS,SHANTRELL,NULL,Female,African-American,05/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +46814,64944,58924,Probation,OWENS,SHANTRELL,NULL,Female,African-American,05/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,7,Medium,New,1,0 +46814,64944,58924,Probation,OWENS,SHANTRELL,NULL,Female,African-American,05/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +34902,64935,58915,PRETRIAL,Cahill,Holli,NULL,Female,Caucasian,11/05/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/28/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +34902,64935,58915,PRETRIAL,Cahill,Holli,NULL,Female,Caucasian,11/05/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +34902,64935,58915,PRETRIAL,Cahill,Holli,NULL,Female,Caucasian,11/05/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56830,64914,58898,PRETRIAL,Carvajalguzman,Kendrick,NULL,Male,Caucasian,07/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +56830,64914,58898,PRETRIAL,Carvajalguzman,Kendrick,NULL,Male,Caucasian,07/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +56830,64914,58898,PRETRIAL,Carvajalguzman,Kendrick,NULL,Male,Caucasian,07/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55726,64928,57612,Probation,Loy,Melanie,NULL,Female,Caucasian,09/02/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +55726,64928,57612,Probation,Loy,Melanie,NULL,Female,Caucasian,09/02/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +55726,64928,57612,Probation,Loy,Melanie,NULL,Female,Caucasian,09/02/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +56833,64919,58901,PRETRIAL,Mortenson,Joseph,NULL,Male,Hispanic,08/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/28/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +56833,64919,58901,PRETRIAL,Mortenson,Joseph,NULL,Male,Hispanic,08/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +56833,64919,58901,PRETRIAL,Mortenson,Joseph,NULL,Male,Hispanic,08/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/28/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +56844,64933,58913,Probation,Godinez,Miguel,NULL,Male,Hispanic,09/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/28/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +56844,64933,58913,Probation,Godinez,Miguel,NULL,Male,Hispanic,09/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +56844,64933,58913,Probation,Godinez,Miguel,NULL,Male,Hispanic,09/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +30751,64905,29738,PRETRIAL,johnson,braxton,magic,Male,African-American,05/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,Copy,1,0 +30751,64905,29738,PRETRIAL,johnson,braxton,magic,Male,African-American,05/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,Copy,1,0 +30751,64905,29738,PRETRIAL,johnson,braxton,magic,Male,African-American,05/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +56828,64912,58896,PRETRIAL,Christman,Jonathan,NULL,Male,Caucasian,03/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,New,1,0 +56828,64912,58896,PRETRIAL,Christman,Jonathan,NULL,Male,Caucasian,03/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +56828,64912,58896,PRETRIAL,Christman,Jonathan,NULL,Male,Caucasian,03/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56831,64915,58899,PRETRIAL,Mills,Latasha,NULL,Female,African-American,08/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/28/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +56831,64915,58899,PRETRIAL,Mills,Latasha,NULL,Female,African-American,08/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/28/13 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +56831,64915,58899,PRETRIAL,Mills,Latasha,NULL,Female,African-American,08/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56835,64922,58903,Broward County,Visconti,Michael,NULL,Male,Hispanic,04/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +56835,64922,58903,Broward County,Visconti,Michael,NULL,Male,Hispanic,04/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +56835,64922,58903,Broward County,Visconti,Michael,NULL,Male,Hispanic,04/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56826,64909,58893,PRETRIAL,MODIA,DEREK,NULL,Male,Hispanic,02/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/28/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +56826,64909,58893,PRETRIAL,MODIA,DEREK,NULL,Male,Hispanic,02/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/28/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +56826,64909,58893,PRETRIAL,MODIA,DEREK,NULL,Male,Hispanic,02/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56850,64943,58923,Probation,mckenize,Kashi,NULL,Male,African-American,05/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/28/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +56850,64943,58923,Probation,mckenize,Kashi,NULL,Male,African-American,05/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/28/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +56850,64943,58923,Probation,mckenize,Kashi,NULL,Male,African-American,05/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49204,54964,50009,PRETRIAL,BAYNHAM,TILFORD,NULL,Male,African-American,06/24/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/28/13 0:00,2,Medium,7,Risk of Violence,-3.59,1,Low,New,1,0 +49204,54964,50009,PRETRIAL,BAYNHAM,TILFORD,NULL,Male,African-American,06/24/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +49204,54964,50009,PRETRIAL,BAYNHAM,TILFORD,NULL,Male,African-American,06/24/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/28/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +56836,64923,58904,Probation,inglis,barbara,NULL,Female,Caucasian,06/21/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +56836,64923,58904,Probation,inglis,barbara,NULL,Female,Caucasian,06/21/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +56836,64923,58904,Probation,inglis,barbara,NULL,Female,Caucasian,06/21/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56842,64930,58910,Probation,Megee,Robert,NULL,Male,Caucasian,07/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +56842,64930,58910,Probation,Megee,Robert,NULL,Male,Caucasian,07/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +56842,64930,58910,Probation,Megee,Robert,NULL,Male,Caucasian,07/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56824,64907,58891,PRETRIAL,PELL,LEONARD,NULL,Male,African-American,03/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +56824,64907,58891,PRETRIAL,PELL,LEONARD,NULL,Male,African-American,03/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,4,High,8,Risk of Recidivism,0.44,9,High,New,1,0 +56824,64907,58891,PRETRIAL,PELL,LEONARD,NULL,Male,African-American,03/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55865,64917,57778,PRETRIAL,CARDULLO,ANTHONY,NULL,Male,Caucasian,06/15/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,Copy,1,0 +55865,64917,57778,PRETRIAL,CARDULLO,ANTHONY,NULL,Male,Caucasian,06/15/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,Copy,1,0 +55865,64917,57778,PRETRIAL,CARDULLO,ANTHONY,NULL,Male,Caucasian,06/15/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +56838,64925,58906,Probation,Cruz,Eliseo,NULL,Male,Hispanic,10/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +56838,64925,58906,Probation,Cruz,Eliseo,NULL,Male,Hispanic,10/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +56838,64925,58906,Probation,Cruz,Eliseo,NULL,Male,Hispanic,10/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56822,64904,58889,PRETRIAL,Lafferriere,Jeff,NULL,Male,African-American,08/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,4,High,7,Risk of Violence,-0.7,9,High,New,1,0 +56822,64904,58889,PRETRIAL,Lafferriere,Jeff,NULL,Male,African-American,08/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,4,High,8,Risk of Recidivism,0.44,9,High,New,1,0 +56822,64904,58889,PRETRIAL,Lafferriere,Jeff,NULL,Male,African-American,08/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56848,64938,58918,Probation,Pozo,Elizabeth,B,Female,Caucasian,01/23/87,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/28/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +56848,64938,58918,Probation,Pozo,Elizabeth,B,Female,Caucasian,01/23/87,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/28/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +56848,64938,58918,Probation,Pozo,Elizabeth,B,Female,Caucasian,01/23/87,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53005,64911,58895,PRETRIAL,JEANBAPTISTE,CHANDLER,NULL,Male,African-American,11/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +53005,64911,58895,PRETRIAL,JEANBAPTISTE,CHANDLER,NULL,Male,African-American,11/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,4,High,8,Risk of Recidivism,0.75,10,High,New,1,0 +53005,64911,58895,PRETRIAL,JEANBAPTISTE,CHANDLER,NULL,Male,African-American,11/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +31415,64941,58921,Probation,Carpio,Peter,NULL,Male,Caucasian,11/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +31415,64941,58921,Probation,Carpio,Peter,NULL,Male,Caucasian,11/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +31415,64941,58921,Probation,Carpio,Peter,NULL,Male,Caucasian,11/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56829,64913,58897,PRETRIAL,GORE,OCATVIOUS,NULL,Male,African-American,12/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +56829,64913,58897,PRETRIAL,GORE,OCATVIOUS,NULL,Male,African-American,12/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,10,High,New,1,0 +56829,64913,58897,PRETRIAL,GORE,OCATVIOUS,NULL,Male,African-American,12/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56843,64932,58912,PRETRIAL,Soto,Yanderi,NULL,Female,Hispanic,02/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +56843,64932,58912,PRETRIAL,Soto,Yanderi,NULL,Female,Hispanic,02/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +56843,64932,58912,PRETRIAL,Soto,Yanderi,NULL,Female,Hispanic,02/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56846,64939,58919,Probation,Louth,Emmanual,NULL,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +56846,64939,58919,Probation,Louth,Emmanual,NULL,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +56846,64939,58919,Probation,Louth,Emmanual,NULL,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55539,64918,57401,Probation,King,Charlie,NULL,Male,African-American,05/17/55,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,8/28/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +55539,64918,57401,Probation,King,Charlie,NULL,Male,African-American,05/17/55,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,8/28/13 0:00,1,Low,8,Risk of Recidivism,-0.95,2,Low,New,1,0 +55539,64918,57401,Probation,King,Charlie,NULL,Male,African-American,05/17/55,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,29,7,Medium,New,1,0 +56823,64906,58890,PRETRIAL,Farley,Devonte,Lorenzo,Male,African-American,09/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +56823,64906,58890,PRETRIAL,Farley,Devonte,Lorenzo,Male,African-American,09/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +56823,64906,58890,PRETRIAL,Farley,Devonte,Lorenzo,Male,African-American,09/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +18100,64995,53147,PRETRIAL,CRESPO,FREDDY,ANTONIO,Male,African-American,11/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,7,Risk of Violence,-0.66,9,High,Copy,1,0 +18100,64995,53147,PRETRIAL,CRESPO,FREDDY,ANTONIO,Male,African-American,11/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,8,Risk of Recidivism,0.96,10,High,Copy,1,0 +18100,64995,53147,PRETRIAL,CRESPO,FREDDY,ANTONIO,Male,African-American,11/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +56872,64974,58951,PRETRIAL,Sukhlall,Ritesh,NULL,Male,Caucasian,05/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +56872,64974,58951,PRETRIAL,Sukhlall,Ritesh,NULL,Male,Caucasian,05/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +56872,64974,58951,PRETRIAL,Sukhlall,Ritesh,NULL,Male,Caucasian,05/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56856,64953,58933,PRETRIAL,Lewis,Keithdrain,NULL,Male,African-American,09/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,7,Risk of Violence,-0.84,9,High,New,1,0 +56856,64953,58933,PRETRIAL,Lewis,Keithdrain,NULL,Male,African-American,09/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,8,Risk of Recidivism,0.2,8,High,New,1,0 +56856,64953,58933,PRETRIAL,Lewis,Keithdrain,NULL,Male,African-American,09/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51670,64957,52874,PRETRIAL,Salnave,Fidel,NULL,Male,Caucasian,07/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,Copy,1,0 +51670,64957,52874,PRETRIAL,Salnave,Fidel,NULL,Male,Caucasian,07/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,Copy,1,0 +51670,64957,52874,PRETRIAL,Salnave,Fidel,NULL,Male,Caucasian,07/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +56884,64992,58968,Probation,ALFONSO,JOSE,NULL,Male,Hispanic,01/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/29/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +56884,64992,58968,Probation,ALFONSO,JOSE,NULL,Male,Hispanic,01/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/29/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +56884,64992,58968,Probation,ALFONSO,JOSE,NULL,Male,Hispanic,01/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +39363,64948,58928,PRETRIAL,Blackshure,Alexander,NULL,Male,African-American,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +39363,64948,58928,PRETRIAL,Blackshure,Alexander,NULL,Male,African-American,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +39363,64948,58928,PRETRIAL,Blackshure,Alexander,NULL,Male,African-American,03/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56858,64955,58935,PRETRIAL,Bladd,Marc,Lewis,Male,Caucasian,11/13/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-4.46,1,Low,New,1,0 +56858,64955,58935,PRETRIAL,Bladd,Marc,Lewis,Male,Caucasian,11/13/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-2.85,1,Low,New,1,0 +56858,64955,58935,PRETRIAL,Bladd,Marc,Lewis,Male,Caucasian,11/13/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56862,64962,58940,Probation,Rosas,Javier,NULL,Male,Hispanic,07/12/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +56862,64962,58940,Probation,Rosas,Javier,NULL,Male,Hispanic,07/12/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +56862,64962,58940,Probation,Rosas,Javier,NULL,Male,Hispanic,07/12/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +47316,64983,58960,PRETRIAL,Gibson,Laron,NULL,Male,African-American,02/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +47316,64983,58960,PRETRIAL,Gibson,Laron,NULL,Male,African-American,02/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +47316,64983,58960,PRETRIAL,Gibson,Laron,NULL,Male,African-American,02/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56870,64972,58949,Probation,Marte,Ashley,NULL,Female,Hispanic,08/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +56870,64972,58949,Probation,Marte,Ashley,NULL,Female,Hispanic,08/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +56870,64972,58949,Probation,Marte,Ashley,NULL,Female,Hispanic,08/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56861,64959,58938,Probation,kolsky,daniel,NULL,Male,Caucasian,12/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +56861,64959,58938,Probation,kolsky,daniel,NULL,Male,Caucasian,12/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +56861,64959,58938,Probation,kolsky,daniel,NULL,Male,Caucasian,12/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56885,64993,58969,PRETRIAL,JARRETT,SHELDON,NULL,Male,African-American,09/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +56885,64993,58969,PRETRIAL,JARRETT,SHELDON,NULL,Male,African-American,09/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +56885,64993,58969,PRETRIAL,JARRETT,SHELDON,NULL,Male,African-American,09/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56865,64967,58944,Probation,Schmid,Karen,Rose,Female,Caucasian,02/27/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/13 0:00,2,Medium,7,Risk of Violence,-2.47,3,Low,New,1,0 +56865,64967,58944,Probation,Schmid,Karen,Rose,Female,Caucasian,02/27/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +56865,64967,58944,Probation,Schmid,Karen,Rose,Female,Caucasian,02/27/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53655,64985,55117,Probation,Saunders,Marquis,NULL,Male,African-American,03/23/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,Copy,1,0 +53655,64985,55117,Probation,Saunders,Marquis,NULL,Male,African-American,03/23/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,Copy,1,0 +53655,64985,55117,Probation,Saunders,Marquis,NULL,Male,African-American,03/23/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +56852,64946,58926,PRETRIAL,Brown,David,NULL,Male,African-American,01/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +56852,64946,58926,PRETRIAL,Brown,David,NULL,Male,African-American,01/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +56852,64946,58926,PRETRIAL,Brown,David,NULL,Male,African-American,01/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +10617,64964,58941,PRETRIAL,VEGA,MIGUEL,NULL,Male,African-American,06/06/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +10617,64964,58941,PRETRIAL,VEGA,MIGUEL,NULL,Male,African-American,06/06/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +10617,64964,58941,PRETRIAL,VEGA,MIGUEL,NULL,Male,African-American,06/06/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56876,64980,58957,PRETRIAL,Fowler,Owen,Fitz,Male,African-American,09/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +56876,64980,58957,PRETRIAL,Fowler,Owen,Fitz,Male,African-American,09/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +56876,64980,58957,PRETRIAL,Fowler,Owen,Fitz,Male,African-American,09/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +22564,64951,58931,PRETRIAL,Lloranzo,Oscar,NULL,Male,Hispanic,06/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +22564,64951,58931,PRETRIAL,Lloranzo,Oscar,NULL,Male,Hispanic,06/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +22564,64951,58931,PRETRIAL,Lloranzo,Oscar,NULL,Male,Hispanic,06/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56881,64988,58964,Probation,Owens,Denisha,NULL,Female,African-American,12/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +56881,64988,58964,Probation,Owens,Denisha,NULL,Female,African-American,12/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +56881,64988,58964,Probation,Owens,Denisha,NULL,Female,African-American,12/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51985,58596,53242,PRETRIAL,Birkley,George,NULL,Male,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +51985,58596,53242,PRETRIAL,Birkley,George,NULL,Male,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +51985,58596,53242,PRETRIAL,Birkley,George,NULL,Male,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56879,64984,58961,Probation,WHITEMAN,MICHAEL,NULL,Male,Caucasian,08/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +56879,64984,58961,Probation,WHITEMAN,MICHAEL,NULL,Male,Caucasian,08/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +56879,64984,58961,Probation,WHITEMAN,MICHAEL,NULL,Male,Caucasian,08/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +17505,64947,58927,PRETRIAL,Soto,Kevin,NULL,Male,African-American,07/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,7,Risk of Violence,-0.64,9,High,New,1,0 +17505,64947,58927,PRETRIAL,Soto,Kevin,NULL,Male,African-American,07/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,8,Risk of Recidivism,1.04,10,High,New,1,0 +17505,64947,58927,PRETRIAL,Soto,Kevin,NULL,Male,African-American,07/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56857,64954,58934,PRETRIAL,Paulino,Silvio,NULL,Male,Caucasian,10/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +56857,64954,58934,PRETRIAL,Paulino,Silvio,NULL,Male,Caucasian,10/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +56857,64954,58934,PRETRIAL,Paulino,Silvio,NULL,Male,Caucasian,10/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56859,64956,58936,PRETRIAL,JOSEPH,AMARI,NULL,Female,African-American,02/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/29/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +56859,64956,58936,PRETRIAL,JOSEPH,AMARI,NULL,Female,African-American,02/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/29/13 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +56859,64956,58936,PRETRIAL,JOSEPH,AMARI,NULL,Female,African-American,02/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56874,64977,58954,PRETRIAL,Remekie,Linell,Gayle,Female,African-American,06/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/29/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +56874,64977,58954,PRETRIAL,Remekie,Linell,Gayle,Female,African-American,06/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/29/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +56874,64977,58954,PRETRIAL,Remekie,Linell,Gayle,Female,African-American,06/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51985,64982,58959,PRETRIAL,Birkley,George,NULL,Male,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +51985,64982,58959,PRETRIAL,Birkley,George,NULL,Male,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,8,Risk of Recidivism,0.17,8,High,New,1,0 +51985,64982,58959,PRETRIAL,Birkley,George,NULL,Male,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +56853,64949,58929,PRETRIAL,STOKES,JOEL,NULL,Male,African-American,10/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,7,Risk of Violence,-0.33,10,High,New,1,0 +56853,64949,58929,PRETRIAL,STOKES,JOEL,NULL,Male,African-American,10/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,8,Risk of Recidivism,0.95,10,High,New,1,0 +56853,64949,58929,PRETRIAL,STOKES,JOEL,NULL,Male,African-American,10/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56878,64986,58962,PRETRIAL,Taylor,Clifford,NULL,Male,Caucasian,09/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/29/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +56878,64986,58962,PRETRIAL,Taylor,Clifford,NULL,Male,Caucasian,09/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/29/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +56878,64986,58962,PRETRIAL,Taylor,Clifford,NULL,Male,Caucasian,09/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +43957,64961,58939,PRETRIAL,harper,tyson,NULL,Male,Caucasian,10/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +43957,64961,58939,PRETRIAL,harper,tyson,NULL,Male,Caucasian,10/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +43957,64961,58939,PRETRIAL,harper,tyson,NULL,Male,Caucasian,10/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +46627,64991,58967,PRETRIAL,Lawrence,Delano,NULL,Male,African-American,10/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +46627,64991,58967,PRETRIAL,Lawrence,Delano,NULL,Male,African-American,10/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,4,High,8,Risk of Recidivism,0.19,8,High,New,1,0 +46627,64991,58967,PRETRIAL,Lawrence,Delano,NULL,Male,African-American,10/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56863,64965,58942,PRETRIAL,KERR,JORDANE,NULL,Male,African-American,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/13 0:00,4,High,7,Risk of Violence,-0.49,10,High,New,1,0 +56863,64965,58942,PRETRIAL,KERR,JORDANE,NULL,Male,African-American,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +56863,64965,58942,PRETRIAL,KERR,JORDANE,NULL,Male,African-American,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56868,64970,58947,Probation,smith,lamar,NULL,Male,Caucasian,04/17/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/29/13 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +56868,64970,58947,Probation,smith,lamar,NULL,Male,Caucasian,04/17/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/29/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +56868,64970,58947,Probation,smith,lamar,NULL,Male,Caucasian,04/17/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50426,64963,57194,PRETRIAL,Dawkins,Elroy,Reckville,Male,African-American,08/14/78,17,All Scales,Intake,English,Conditional Release,Probation,Separated,8/29/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +50426,64963,57194,PRETRIAL,Dawkins,Elroy,Reckville,Male,African-American,08/14/78,17,All Scales,Intake,English,Conditional Release,Probation,Separated,8/29/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +50426,64963,57194,PRETRIAL,Dawkins,Elroy,Reckville,Male,African-American,08/14/78,17,All Scales,Intake,English,Conditional Release,Probation,Separated,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +45532,64976,58953,PRETRIAL,Middlemiss,John,NULL,Male,Caucasian,09/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +45532,64976,58953,PRETRIAL,Middlemiss,John,NULL,Male,Caucasian,09/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +45532,64976,58953,PRETRIAL,Middlemiss,John,NULL,Male,Caucasian,09/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56869,64971,58948,Probation,MARKHAM,STEFANIE,D,Female,Caucasian,07/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +56869,64971,58948,Probation,MARKHAM,STEFANIE,D,Female,Caucasian,07/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +56869,64971,58948,Probation,MARKHAM,STEFANIE,D,Female,Caucasian,07/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56882,64989,58965,Probation,Baca,Carlos,Andres,Male,Hispanic,02/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/13 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +56882,64989,58965,Probation,Baca,Carlos,Andres,Male,Hispanic,02/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +56882,64989,58965,Probation,Baca,Carlos,Andres,Male,Hispanic,02/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56854,64950,58930,PRETRIAL,FREDERICK,PARKER,NULL,Male,Caucasian,10/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +56854,64950,58930,PRETRIAL,FREDERICK,PARKER,NULL,Male,Caucasian,10/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +56854,64950,58930,PRETRIAL,FREDERICK,PARKER,NULL,Male,Caucasian,10/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56866,64968,58945,Probation,Ross,Paul,NULL,Male,Caucasian,05/03/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +56866,64968,58945,Probation,Ross,Paul,NULL,Male,Caucasian,05/03/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +56866,64968,58945,Probation,Ross,Paul,NULL,Male,Caucasian,05/03/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56871,64973,58950,Probation,Portoluri,Jean,Elizabeth,Female,Caucasian,08/18/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +56871,64973,58950,Probation,Portoluri,Jean,Elizabeth,Female,Caucasian,08/18/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +56871,64973,58950,Probation,Portoluri,Jean,Elizabeth,Female,Caucasian,08/18/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +56880,64987,58963,Probation,ganrude,jean,NULL,Female,Caucasian,10/23/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/29/13 0:00,1,Low,7,Risk of Violence,-4.32,1,Low,New,1,0 +56880,64987,58963,Probation,ganrude,jean,NULL,Female,Caucasian,10/23/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/29/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +56880,64987,58963,Probation,ganrude,jean,NULL,Female,Caucasian,10/23/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56855,64952,58932,PRETRIAL,Jones,Claude,NULL,Male,African-American,09/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +56855,64952,58932,PRETRIAL,Jones,Claude,NULL,Male,African-American,09/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +56855,64952,58932,PRETRIAL,Jones,Claude,NULL,Male,African-American,09/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56864,64966,58943,Probation,ARVANITIS,NICHOLAS,NULL,Male,Caucasian,06/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +56864,64966,58943,Probation,ARVANITIS,NICHOLAS,NULL,Male,Caucasian,06/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.7,10,High,New,1,0 +56864,64966,58943,Probation,ARVANITIS,NICHOLAS,NULL,Male,Caucasian,06/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +56860,64958,58937,PRETRIAL,Newsome,Bravon,NULL,Male,Caucasian,04/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,8/29/13 0:00,4,High,7,Risk of Violence,0.01,10,High,New,1,0 +56860,64958,58937,PRETRIAL,Newsome,Bravon,NULL,Male,Caucasian,04/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,8/29/13 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +56860,64958,58937,PRETRIAL,Newsome,Bravon,NULL,Male,Caucasian,04/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,8/29/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +6066,64960,5675,PRETRIAL,DEHAM,GREGORY,NULL,Male,African-American,08/31/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/29/13 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,Copy,1,0 +6066,64960,5675,PRETRIAL,DEHAM,GREGORY,NULL,Male,African-American,08/31/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,Copy,1,0 +6066,64960,5675,PRETRIAL,DEHAM,GREGORY,NULL,Male,African-American,08/31/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/29/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +56886,64994,58970,PRETRIAL,Kenon,Avery,NULL,Male,African-American,03/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,New,1,0 +56886,64994,58970,PRETRIAL,Kenon,Avery,NULL,Male,African-American,03/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +56886,64994,58970,PRETRIAL,Kenon,Avery,NULL,Male,African-American,03/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56875,64979,58956,Probation,ALLEN,JAYNE,WESLEY,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +56875,64979,58956,Probation,ALLEN,JAYNE,WESLEY,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +56875,64979,58956,Probation,ALLEN,JAYNE,WESLEY,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56877,64981,58958,PRETRIAL,PUGLIESE,FACUNDO,E,Male,Caucasian,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +56877,64981,58958,PRETRIAL,PUGLIESE,FACUNDO,E,Male,Caucasian,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +56877,64981,58958,PRETRIAL,PUGLIESE,FACUNDO,E,Male,Caucasian,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +18891,65015,18143,PRETRIAL,PREVAL,SAMMUEL,NULL,Male,African-American,09/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/30/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,Copy,1,0 +18891,65015,18143,PRETRIAL,PREVAL,SAMMUEL,NULL,Male,African-American,09/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,Copy,1,0 +18891,65015,18143,PRETRIAL,PREVAL,SAMMUEL,NULL,Male,African-American,09/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/30/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +52153,65002,53412,PRETRIAL,SANCHEZ,KENNETH,NULL,Male,Hispanic,02/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,Copy,1,0 +52153,65002,53412,PRETRIAL,SANCHEZ,KENNETH,NULL,Male,Hispanic,02/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,Copy,1,0 +52153,65002,53412,PRETRIAL,SANCHEZ,KENNETH,NULL,Male,Hispanic,02/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +56902,65023,58994,Probation,hanley,mary,NULL,Female,Caucasian,10/05/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +56902,65023,58994,Probation,hanley,mary,NULL,Female,Caucasian,10/05/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +56902,65023,58994,Probation,hanley,mary,NULL,Female,Caucasian,10/05/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56898,65018,58990,PRETRIAL,Valente,Michael,NULL,Male,Caucasian,10/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +56898,65018,58990,PRETRIAL,Valente,Michael,NULL,Male,Caucasian,10/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +56898,65018,58990,PRETRIAL,Valente,Michael,NULL,Male,Caucasian,10/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +37357,65010,58983,Probation,francis,opal,NULL,Female,African-American,05/11/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,2,Medium,7,Risk of Violence,-2.82,2,Low,New,1,0 +37357,65010,58983,Probation,francis,opal,NULL,Female,African-American,05/11/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +37357,65010,58983,Probation,francis,opal,NULL,Female,African-American,05/11/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,2,Medium,18,Risk of Failure to Appear,35,10,High,New,1,0 +56887,64997,58972,PRETRIAL,Hines,Benjamin,NULL,Male,African-American,11/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +56887,64997,58972,PRETRIAL,Hines,Benjamin,NULL,Male,African-American,11/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +56887,64997,58972,PRETRIAL,Hines,Benjamin,NULL,Male,African-American,11/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +11279,65031,59002,Probation,Williams,Gary,Sentell,Male,African-American,01/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +11279,65031,59002,Probation,Williams,Gary,Sentell,Male,African-American,01/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +11279,65031,59002,Probation,Williams,Gary,Sentell,Male,African-American,01/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56913,65038,59007,PRETRIAL,Barraza,Melvin,NULL,Male,Hispanic,10/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +56913,65038,59007,PRETRIAL,Barraza,Melvin,NULL,Male,Hispanic,10/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +56913,65038,59007,PRETRIAL,Barraza,Melvin,NULL,Male,Hispanic,10/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +22759,65000,58975,Probation,mosely,nathan,NULL,Male,African-American,06/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +22759,65000,58975,Probation,mosely,nathan,NULL,Male,African-American,06/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +22759,65000,58975,Probation,mosely,nathan,NULL,Male,African-American,06/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56888,65003,58976,PRETRIAL,Telfort,Catrice,NULL,Female,Other,10/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +56888,65003,58976,PRETRIAL,Telfort,Catrice,NULL,Female,Other,10/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +56888,65003,58976,PRETRIAL,Telfort,Catrice,NULL,Female,Other,10/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +32615,64996,58971,PRETRIAL,WASHINGTON,CALODIUS,NULL,Male,African-American,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +32615,64996,58971,PRETRIAL,WASHINGTON,CALODIUS,NULL,Male,African-American,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +32615,64996,58971,PRETRIAL,WASHINGTON,CALODIUS,NULL,Male,African-American,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +34398,65007,58980,PRETRIAL,Riley,Jamal,NULL,Male,African-American,03/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +34398,65007,58980,PRETRIAL,Riley,Jamal,NULL,Male,African-American,03/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +34398,65007,58980,PRETRIAL,Riley,Jamal,NULL,Male,African-American,03/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56900,65021,58992,Probation,FULTON,DAVID,NULL,Male,African-American,09/14/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +56900,65021,58992,Probation,FULTON,DAVID,NULL,Male,African-American,09/14/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +56900,65021,58992,Probation,FULTON,DAVID,NULL,Male,African-American,09/14/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56904,65026,58997,Probation,Rodriguezvillamil,Cesar,NULL,Male,Hispanic,05/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +56904,65026,58997,Probation,Rodriguezvillamil,Cesar,NULL,Male,Hispanic,05/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +56904,65026,58997,Probation,Rodriguezvillamil,Cesar,NULL,Male,Hispanic,05/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56906,65028,58999,Probation,REMEDIOSSANCHEZ,JUAN,RODOLFO,Male,Hispanic,07/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +56906,65028,58999,Probation,REMEDIOSSANCHEZ,JUAN,RODOLFO,Male,Hispanic,07/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +56906,65028,58999,Probation,REMEDIOSSANCHEZ,JUAN,RODOLFO,Male,Hispanic,07/02/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56899,65019,58991,Probation,fleary,jamel,NULL,Male,African-American,12/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +56899,65019,58991,Probation,fleary,jamel,NULL,Male,African-American,12/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +56899,65019,58991,Probation,fleary,jamel,NULL,Male,African-American,12/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56910,65033,59004,PRETRIAL,VAUGHN,AVEN,NULL,Male,African-American,03/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +56910,65033,59004,PRETRIAL,VAUGHN,AVEN,NULL,Male,African-American,03/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +56910,65033,59004,PRETRIAL,VAUGHN,AVEN,NULL,Male,African-American,03/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +9320,64998,58973,DRRD,Maas,Brandon,NULL,Male,African-American,02/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +9320,64998,58973,DRRD,Maas,Brandon,NULL,Male,African-American,02/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +9320,64998,58973,DRRD,Maas,Brandon,NULL,Male,African-American,02/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +29601,65005,58978,PRETRIAL,DANIELS,TONY,DWAYNE,Male,African-American,09/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +29601,65005,58978,PRETRIAL,DANIELS,TONY,DWAYNE,Male,African-American,09/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +29601,65005,58978,PRETRIAL,DANIELS,TONY,DWAYNE,Male,African-American,09/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +22258,65012,58985,Probation,Grande,Faustino,MR,Male,Hispanic,06/24/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +22258,65012,58985,Probation,Grande,Faustino,MR,Male,Hispanic,06/24/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +22258,65012,58985,Probation,Grande,Faustino,MR,Male,Hispanic,06/24/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56901,65022,58993,Probation,Clark,Elijah,NULL,Male,African-American,12/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +56901,65022,58993,Probation,Clark,Elijah,NULL,Male,African-American,12/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.84,10,High,New,1,0 +56901,65022,58993,Probation,Clark,Elijah,NULL,Male,African-American,12/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +56903,65024,58995,PRETRIAL,NORALUS,WINDLEY,NULL,Male,African-American,06/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +56903,65024,58995,PRETRIAL,NORALUS,WINDLEY,NULL,Male,African-American,06/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +56903,65024,58995,PRETRIAL,NORALUS,WINDLEY,NULL,Male,African-American,06/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +25001,65001,37548,Probation,STANLEY,VINCENT,RENARD,Male,African-American,06/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,Copy,1,0 +25001,65001,37548,Probation,STANLEY,VINCENT,RENARD,Male,African-American,06/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,Copy,1,0 +25001,65001,37548,Probation,STANLEY,VINCENT,RENARD,Male,African-American,06/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +56896,65016,58988,Probation,Harrold,Alan,NULL,Male,Caucasian,12/11/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/30/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +56896,65016,58988,Probation,Harrold,Alan,NULL,Male,Caucasian,12/11/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/30/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +56896,65016,58988,Probation,Harrold,Alan,NULL,Male,Caucasian,12/11/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +56912,65037,59006,PRETRIAL,ALDOROTY,JARED,NULL,Male,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,Copy,1,0 +56912,65037,59006,PRETRIAL,ALDOROTY,JARED,NULL,Male,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,Copy,1,0 +56912,65037,59006,PRETRIAL,ALDOROTY,JARED,NULL,Male,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +56895,65014,58987,Probation,Reyes,Jose,NULL,Male,Hispanic,12/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +56895,65014,58987,Probation,Reyes,Jose,NULL,Male,Hispanic,12/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +56895,65014,58987,Probation,Reyes,Jose,NULL,Male,Hispanic,12/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56911,65035,59005,PRETRIAL,MOSSSOLOMON,LYDIA,KAYE,Female,African-American,04/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/30/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +56911,65035,59005,PRETRIAL,MOSSSOLOMON,LYDIA,KAYE,Female,African-American,04/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/30/13 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +56911,65035,59005,PRETRIAL,MOSSSOLOMON,LYDIA,KAYE,Female,African-American,04/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56905,65027,58998,Probation,klemple,brian,NULL,Male,Caucasian,06/01/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +56905,65027,58998,Probation,klemple,brian,NULL,Male,Caucasian,06/01/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +56905,65027,58998,Probation,klemple,brian,NULL,Male,Caucasian,06/01/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56890,65006,58979,PRETRIAL,Stewart,Steven,NULL,Male,Other,02/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/30/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +56890,65006,58979,PRETRIAL,Stewart,Steven,NULL,Male,Other,02/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/30/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +56890,65006,58979,PRETRIAL,Stewart,Steven,NULL,Male,Other,02/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +43819,65034,53967,PRETRIAL,Barros,Jalen,NULL,Male,African-American,04/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,4,High,7,Risk of Violence,-1.01,8,High,Copy,1,0 +43819,65034,53967,PRETRIAL,Barros,Jalen,NULL,Male,African-American,04/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,4,High,8,Risk of Recidivism,0.09,8,High,Copy,1,0 +43819,65034,53967,PRETRIAL,Barros,Jalen,NULL,Male,African-American,04/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +56893,65011,58984,Probation,sonnie,sean,NULL,Male,Caucasian,06/24/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +56893,65011,58984,Probation,sonnie,sean,NULL,Male,Caucasian,06/24/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +56893,65011,58984,Probation,sonnie,sean,NULL,Male,Caucasian,06/24/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55548,65020,57410,Probation,Silva,Igor,NULL,Male,Hispanic,11/04/90,17,All Scales,Intake,English,Other,Probation,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +55548,65020,57410,Probation,Silva,Igor,NULL,Male,Hispanic,11/04/90,17,All Scales,Intake,English,Other,Probation,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-0.74,3,Low,New,1,0 +55548,65020,57410,Probation,Silva,Igor,NULL,Male,Hispanic,11/04/90,17,All Scales,Intake,English,Other,Probation,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +33404,64999,58974,PRETRIAL,Williams,Max,NULL,Male,Caucasian,05/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +33404,64999,58974,PRETRIAL,Williams,Max,NULL,Male,Caucasian,05/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +33404,64999,58974,PRETRIAL,Williams,Max,NULL,Male,Caucasian,05/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +46122,65025,58996,PRETRIAL,Clark,Daniel,NULL,Male,Caucasian,01/05/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +46122,65025,58996,PRETRIAL,Clark,Daniel,NULL,Male,Caucasian,01/05/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +46122,65025,58996,PRETRIAL,Clark,Daniel,NULL,Male,Caucasian,01/05/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56889,65004,58977,PRETRIAL,Parrish,Ernestine,Marie,Female,African-American,11/17/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +56889,65004,58977,PRETRIAL,Parrish,Ernestine,Marie,Female,African-American,11/17/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +56889,65004,58977,PRETRIAL,Parrish,Ernestine,Marie,Female,African-American,11/17/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56907,65029,59000,Probation,Farina,Jose,NULL,Male,Hispanic,05/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +56907,65029,59000,Probation,Farina,Jose,NULL,Male,Hispanic,05/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +56907,65029,59000,Probation,Farina,Jose,NULL,Male,Hispanic,05/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +15668,65174,59125,PRETRIAL,OWENS,ALBERT,NULL,Male,African-American,08/14/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +15668,65174,59125,PRETRIAL,OWENS,ALBERT,NULL,Male,African-American,08/14/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +15668,65174,59125,PRETRIAL,OWENS,ALBERT,NULL,Male,African-American,08/14/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56951,65067,59035,Probation,Marrero,Jorge,NULL,Male,Hispanic,05/20/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +56951,65067,59035,Probation,Marrero,Jorge,NULL,Male,Hispanic,05/20/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +56951,65067,59035,Probation,Marrero,Jorge,NULL,Male,Hispanic,05/20/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +29364,65046,59014,Probation,EVANS,FREDERICK,NULL,Male,African-Am,09/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,4,High,7,Risk of Violence,-0.43,10,High,New,1,0 +29364,65046,59014,Probation,EVANS,FREDERICK,NULL,Male,African-Am,09/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,4,High,8,Risk of Recidivism,0.54,9,High,New,1,0 +29364,65046,59014,Probation,EVANS,FREDERICK,NULL,Male,African-Am,09/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,4,High,18,Risk of Failure to Appear,41,10,High,New,1,0 +56947,65064,59032,PRETRIAL,Suffrin,Nikson,NULL,Male,Other,10/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +56947,65064,59032,PRETRIAL,Suffrin,Nikson,NULL,Male,Other,10/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +56947,65064,59032,PRETRIAL,Suffrin,Nikson,NULL,Male,Other,10/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56953,65069,59037,Probation,MIRANDA,JOSE,LUIS,Male,Hispanic,10/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +56953,65069,59037,Probation,MIRANDA,JOSE,LUIS,Male,Hispanic,10/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +56953,65069,59037,Probation,MIRANDA,JOSE,LUIS,Male,Hispanic,10/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56936,65055,59023,Probation,Morris,Tonia,Roxan,Female,African-American,05/13/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/3/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +56936,65055,59023,Probation,Morris,Tonia,Roxan,Female,African-American,05/13/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/3/13 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +56936,65055,59023,Probation,Morris,Tonia,Roxan,Female,African-American,05/13/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56945,65062,59030,Probation,Hoffman,Robert,NULL,Male,Caucasian,04/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.84,2,Low,New,1,0 +56945,65062,59030,Probation,Hoffman,Robert,NULL,Male,Caucasian,04/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +56945,65062,59030,Probation,Hoffman,Robert,NULL,Male,Caucasian,04/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +56925,65040,59009,PRETRIAL,Badal,Ameer,NULL,Male,Caucasian,05/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +56925,65040,59009,PRETRIAL,Badal,Ameer,NULL,Male,Caucasian,05/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +56925,65040,59009,PRETRIAL,Badal,Ameer,NULL,Male,Caucasian,05/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56944,65061,59029,Probation,Fouche,Natalie,NULL,Female,African-American,08/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +56944,65061,59029,Probation,Fouche,Natalie,NULL,Female,African-American,08/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,New,1,0 +56944,65061,59029,Probation,Fouche,Natalie,NULL,Female,African-American,08/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56934,65053,59021,Probation,RAYMOND,LEGITIME,NULL,Male,African-American,06/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/3/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +56934,65053,59021,Probation,RAYMOND,LEGITIME,NULL,Male,African-American,06/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/3/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +56934,65053,59021,Probation,RAYMOND,LEGITIME,NULL,Male,African-American,06/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56932,65051,59019,PRETRIAL,CONNORS,KEVIN,NULL,Male,Caucasian,05/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +56932,65051,59019,PRETRIAL,CONNORS,KEVIN,NULL,Male,Caucasian,05/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +56932,65051,59019,PRETRIAL,CONNORS,KEVIN,NULL,Male,Caucasian,05/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56950,65066,59034,Probation,RAMOS,BLAKE,NULL,Male,Hispanic,12/22/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +56950,65066,59034,Probation,RAMOS,BLAKE,NULL,Male,Hispanic,12/22/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +56950,65066,59034,Probation,RAMOS,BLAKE,NULL,Male,Hispanic,12/22/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56927,65045,59013,Probation,Luce,Marek,NULL,Male,Caucasian,11/03/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/3/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +56927,65045,59013,Probation,Luce,Marek,NULL,Male,Caucasian,11/03/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/3/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +56927,65045,59013,Probation,Luce,Marek,NULL,Male,Caucasian,11/03/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +24318,65043,59011,PRETRIAL,Lodenquai,Eric,Charlee,Male,African-American,10/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,2,Medium,7,Risk of Violence,-2.47,3,Low,New,1,0 +24318,65043,59011,PRETRIAL,Lodenquai,Eric,Charlee,Male,African-American,10/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +24318,65043,59011,PRETRIAL,Lodenquai,Eric,Charlee,Male,African-American,10/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56941,65058,59026,Probation,gary,jonathan,NULL,Male,African-American,04/07/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/3/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +56941,65058,59026,Probation,gary,jonathan,NULL,Male,African-American,04/07/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/3/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +56941,65058,59026,Probation,gary,jonathan,NULL,Male,African-American,04/07/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56929,65047,59015,PRETRIAL,Walker,Tylicia,NULL,Female,African-American,06/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +56929,65047,59015,PRETRIAL,Walker,Tylicia,NULL,Female,African-American,06/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +56929,65047,59015,PRETRIAL,Walker,Tylicia,NULL,Female,African-American,06/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56931,65049,59017,Probation,rosales,manuel,NULL,Male,Hispanic,01/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +56931,65049,59017,Probation,rosales,manuel,NULL,Male,Hispanic,01/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +56931,65049,59017,Probation,rosales,manuel,NULL,Male,Hispanic,01/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56926,65042,59010,PRETRIAL,Renta,Leonard,NULL,Male,Caucasian,06/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +56926,65042,59010,PRETRIAL,Renta,Leonard,NULL,Male,Caucasian,06/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +56926,65042,59010,PRETRIAL,Renta,Leonard,NULL,Male,Caucasian,06/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56942,65059,59027,Probation,Wells,Dane,NULL,Female,Caucasian,10/04/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/3/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +56942,65059,59027,Probation,Wells,Dane,NULL,Female,Caucasian,10/04/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/3/13 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +56942,65059,59027,Probation,Wells,Dane,NULL,Female,Caucasian,10/04/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56948,65065,59033,PRETRIAL,Miller,Derrico,NULL,Male,African-American,06/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +56948,65065,59033,PRETRIAL,Miller,Derrico,NULL,Male,African-American,06/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +56948,65065,59033,PRETRIAL,Miller,Derrico,NULL,Male,African-American,06/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56928,65044,59012,PRETRIAL,Julien,Kadijah,NULL,Male,African-American,10/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +56928,65044,59012,PRETRIAL,Julien,Kadijah,NULL,Male,African-American,10/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +56928,65044,59012,PRETRIAL,Julien,Kadijah,NULL,Male,African-American,10/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56940,65057,59025,Probation,stevens,kyle,NULL,Male,Caucasian,08/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +56940,65057,59025,Probation,stevens,kyle,NULL,Male,Caucasian,08/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +56940,65057,59025,Probation,stevens,kyle,NULL,Male,Caucasian,08/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56933,65052,59020,Probation,Dow,Cheyenne,NULL,Female,Hispanic,10/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +56933,65052,59020,Probation,Dow,Cheyenne,NULL,Female,Hispanic,10/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,9,High,New,1,0 +56933,65052,59020,Probation,Dow,Cheyenne,NULL,Female,Hispanic,10/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56943,65060,59028,Probation,stach,Philip,NULL,Male,Caucasian,12/17/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/3/13 0:00,2,Medium,7,Risk of Violence,-3.07,1,Low,New,1,0 +56943,65060,59028,Probation,stach,Philip,NULL,Male,Caucasian,12/17/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +56943,65060,59028,Probation,stach,Philip,NULL,Male,Caucasian,12/17/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/3/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56968,65094,59057,PRETRIAL,JOSEPH,IAN,NULL,Male,Caucasian,04/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +56968,65094,59057,PRETRIAL,JOSEPH,IAN,NULL,Male,Caucasian,04/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +56968,65094,59057,PRETRIAL,JOSEPH,IAN,NULL,Male,Caucasian,04/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56979,65109,59070,PRETRIAL,Delacruz,Ramon,NULL,Male,Hispanic,06/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/4/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +56979,65109,59070,PRETRIAL,Delacruz,Ramon,NULL,Male,Hispanic,06/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +56979,65109,59070,PRETRIAL,Delacruz,Ramon,NULL,Male,Hispanic,06/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56959,65081,59045,PRETRIAL,Raja,Amer,Shaker,Male,Caucasian,04/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +56959,65081,59045,PRETRIAL,Raja,Amer,Shaker,Male,Caucasian,04/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +56959,65081,59045,PRETRIAL,Raja,Amer,Shaker,Male,Caucasian,04/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56986,65115,59075,Probation,McCarthy,Dana,NULL,Female,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +56986,65115,59075,Probation,McCarthy,Dana,NULL,Female,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +56986,65115,59075,Probation,McCarthy,Dana,NULL,Female,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56973,65101,59063,Probation,Pham,Lam,NULL,Male,Other,11/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/4/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +56973,65101,59063,Probation,Pham,Lam,NULL,Male,Other,11/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/4/13 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +56973,65101,59063,Probation,Pham,Lam,NULL,Male,Other,11/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56974,65102,59064,Probation,TABARES,RODOLFO,NULL,Male,Hispanic,12/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +56974,65102,59064,Probation,TABARES,RODOLFO,NULL,Male,Hispanic,12/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +56974,65102,59064,Probation,TABARES,RODOLFO,NULL,Male,Hispanic,12/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55454,65073,59038,PRETRIAL,WARD,TAVECA,NULL,Female,African-American,07/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +55454,65073,59038,PRETRIAL,WARD,TAVECA,NULL,Female,African-American,07/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +55454,65073,59038,PRETRIAL,WARD,TAVECA,NULL,Female,African-American,07/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,4,High,18,Risk of Failure to Appear,27,8,High,New,1,0 +56958,65080,59044,PRETRIAL,Garcia,Arturo,NULL,Male,Caucasian,03/30/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/4/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +56958,65080,59044,PRETRIAL,Garcia,Arturo,NULL,Male,Caucasian,03/30/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/4/13 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +56958,65080,59044,PRETRIAL,Garcia,Arturo,NULL,Male,Caucasian,03/30/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56806,64887,58872,PRETRIAL,Kalichman,Shila,NULL,Female,Other,10/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,9/4/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +56806,64887,58872,PRETRIAL,Kalichman,Shila,NULL,Female,Other,10/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +56806,64887,58872,PRETRIAL,Kalichman,Shila,NULL,Female,Other,10/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +56969,65096,59059,PRETRIAL,Mcdade,Jerod,J,Male,Caucasian,03/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +56969,65096,59059,PRETRIAL,Mcdade,Jerod,J,Male,Caucasian,03/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +56969,65096,59059,PRETRIAL,Mcdade,Jerod,J,Male,Caucasian,03/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56977,65107,59068,Probation,GOLDMAN,CHRISTOPHER,L,Male,Caucasian,10/12/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +56977,65107,59068,Probation,GOLDMAN,CHRISTOPHER,L,Male,Caucasian,10/12/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +56977,65107,59068,Probation,GOLDMAN,CHRISTOPHER,L,Male,Caucasian,10/12/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56962,65086,59050,PRETRIAL,Burns,Melonie,NULL,Female,African-American,07/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +56962,65086,59050,PRETRIAL,Burns,Melonie,NULL,Female,African-American,07/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +56962,65086,59050,PRETRIAL,Burns,Melonie,NULL,Female,African-American,07/28/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +46723,65117,59077,PRETRIAL,Velez,Christian,NULL,Male,Hispanic,08/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.71,9,High,New,1,0 +46723,65117,59077,PRETRIAL,Velez,Christian,NULL,Male,Hispanic,08/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +46723,65117,59077,PRETRIAL,Velez,Christian,NULL,Male,Hispanic,08/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +5025,65078,4708,PRETRIAL,MARTON,MIRCEA,NULL,Male,Caucasian,06/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,Copy,1,0 +5025,65078,4708,PRETRIAL,MARTON,MIRCEA,NULL,Male,Caucasian,06/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,Copy,1,0 +5025,65078,4708,PRETRIAL,MARTON,MIRCEA,NULL,Male,Caucasian,06/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +56966,65091,59055,Probation,Wallace,Christopher,NULL,Male,Caucasian,06/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +56966,65091,59055,Probation,Wallace,Christopher,NULL,Male,Caucasian,06/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +56966,65091,59055,Probation,Wallace,Christopher,NULL,Male,Caucasian,06/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +40942,65070,40592,PRETRIAL,Wilson,Johnie,NULL,Male,African-American,07/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,Copy,1,0 +40942,65070,40592,PRETRIAL,Wilson,Johnie,NULL,Male,African-American,07/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +40942,65070,40592,PRETRIAL,Wilson,Johnie,NULL,Male,African-American,07/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +41174,65104,59066,PRETRIAL,Hernandez,Alberlin,NULL,Male,Hispanic,01/29/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +41174,65104,59066,PRETRIAL,Hernandez,Alberlin,NULL,Male,Hispanic,01/29/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +41174,65104,59066,PRETRIAL,Hernandez,Alberlin,NULL,Male,Hispanic,01/29/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56863,65093,58942,PRETRIAL,KERR,JORDANE,NULL,Male,African-American,03/28/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,4,High,7,Risk of Violence,-0.49,10,High,Copy,1,0 +56863,65093,58942,PRETRIAL,KERR,JORDANE,NULL,Male,African-American,03/28/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,Copy,1,0 +56863,65093,58942,PRETRIAL,KERR,JORDANE,NULL,Male,African-American,03/28/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +21368,65072,20522,PRETRIAL,Kesler,Jason,Nthaniel,Male,African-American,01/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,9/4/13 0:00,2,Medium,7,Risk of Violence,-2.99,1,Low,Copy,1,0 +21368,65072,20522,PRETRIAL,Kesler,Jason,Nthaniel,Male,African-American,01/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,9/4/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,Copy,1,0 +21368,65072,20522,PRETRIAL,Kesler,Jason,Nthaniel,Male,African-American,01/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,9/4/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +56985,65114,59074,PRETRIAL,GODFREY,SHANTEGRA,NULL,Female,African-American,08/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +56985,65114,59074,PRETRIAL,GODFREY,SHANTEGRA,NULL,Female,African-American,08/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +56985,65114,59074,PRETRIAL,GODFREY,SHANTEGRA,NULL,Female,African-American,08/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56954,65075,59040,PRETRIAL,Herring,Antwjaun,NULL,Male,African-American,10/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.37,3,Low,New,1,0 +56954,65075,59040,PRETRIAL,Herring,Antwjaun,NULL,Male,African-American,10/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,New,1,0 +56954,65075,59040,PRETRIAL,Herring,Antwjaun,NULL,Male,African-American,10/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +56956,65077,59042,PRETRIAL,Elysee,Francis,NULL,Male,African-American,11/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2,4,Low,New,1,0 +56956,65077,59042,PRETRIAL,Elysee,Francis,NULL,Male,African-American,11/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +56956,65077,59042,PRETRIAL,Elysee,Francis,NULL,Male,African-American,11/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56970,65098,59061,Probation,Amores,Manuel,NULL,Male,Hispanic,11/24/58,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/4/13 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +56970,65098,59061,Probation,Amores,Manuel,NULL,Male,Hispanic,11/24/58,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/4/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +56970,65098,59061,Probation,Amores,Manuel,NULL,Male,Hispanic,11/24/58,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56972,65105,59062,PRETRIAL,Stevenson,Johnnie,NULL,Male,Caucasian,12/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,Copy,1,0 +56972,65105,59062,PRETRIAL,Stevenson,Johnnie,NULL,Male,Caucasian,12/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,Copy,1,0 +56972,65105,59062,PRETRIAL,Stevenson,Johnnie,NULL,Male,Caucasian,12/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +56983,65112,59072,PRETRIAL,Sims,Jeffrey,Donald,Male,African-American,02/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,2,Medium,7,Risk of Violence,-3.31,1,Low,New,1,0 +56983,65112,59072,PRETRIAL,Sims,Jeffrey,Donald,Male,African-American,02/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +56983,65112,59072,PRETRIAL,Sims,Jeffrey,Donald,Male,African-American,02/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,2,Medium,18,Risk of Failure to Appear,44,10,High,New,1,0 +56961,65084,59048,PRETRIAL,Zackery,Kenneth,NULL,Male,African-American,01/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,2,Medium,7,Risk of Violence,-3.11,1,Low,New,1,0 +56961,65084,59048,PRETRIAL,Zackery,Kenneth,NULL,Male,African-American,01/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +56961,65084,59048,PRETRIAL,Zackery,Kenneth,NULL,Male,African-American,01/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56987,65116,59076,PRETRIAL,Benjamin,Robinson,NULL,Male,African-American,08/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +56987,65116,59076,PRETRIAL,Benjamin,Robinson,NULL,Male,African-American,08/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +56987,65116,59076,PRETRIAL,Benjamin,Robinson,NULL,Male,African-American,08/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +11131,65100,12106,PRETRIAL,nordelus,Whatley/ ronie,NULL,Male,African-American,03/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,Copy,1,0 +11131,65100,12106,PRETRIAL,nordelus,Whatley/ ronie,NULL,Male,African-American,03/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.94,10,High,Copy,1,0 +11131,65100,12106,PRETRIAL,nordelus,Whatley/ ronie,NULL,Male,African-American,03/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +56975,65103,59065,Probation,Burleigh,Jorge,NULL,Male,African-American,04/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +56975,65103,59065,Probation,Burleigh,Jorge,NULL,Male,African-American,04/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,4,High,8,Risk of Recidivism,1.2,10,High,New,1,0 +56975,65103,59065,Probation,Burleigh,Jorge,NULL,Male,African-American,04/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +26591,65082,59046,PRETRIAL,Brown,Carlton,Lewis,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,4,High,7,Risk of Violence,-1.17,8,High,New,1,0 +26591,65082,59046,PRETRIAL,Brown,Carlton,Lewis,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,4,High,8,Risk of Recidivism,0.22,8,High,New,1,0 +26591,65082,59046,PRETRIAL,Brown,Carlton,Lewis,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +34416,65095,59058,PRETRIAL,DEVALLE,CHRISTOPHER,NULL,Male,Caucasian,12/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +34416,65095,59058,PRETRIAL,DEVALLE,CHRISTOPHER,NULL,Male,Caucasian,12/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +34416,65095,59058,PRETRIAL,DEVALLE,CHRISTOPHER,NULL,Male,Caucasian,12/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +56978,65108,59069,PRETRIAL,CERON,EDGAR,STEVE,Male,Caucasian,08/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +56978,65108,59069,PRETRIAL,CERON,EDGAR,STEVE,Male,Caucasian,08/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +56978,65108,59069,PRETRIAL,CERON,EDGAR,STEVE,Male,Caucasian,08/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +29822,65074,59039,PRETRIAL,Williams,Terris,NULL,Male,African-American,09/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +29822,65074,59039,PRETRIAL,Williams,Terris,NULL,Male,African-American,09/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +29822,65074,59039,PRETRIAL,Williams,Terris,NULL,Male,African-American,09/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56960,65083,59047,PRETRIAL,Licona,Julissa,Ferrera,Female,Hispanic,07/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/4/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +56960,65083,59047,PRETRIAL,Licona,Julissa,Ferrera,Female,Hispanic,07/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +56960,65083,59047,PRETRIAL,Licona,Julissa,Ferrera,Female,Hispanic,07/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56965,65090,59054,PRETRIAL,Harris,Allan,NULL,Male,African-American,07/21/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +56965,65090,59054,PRETRIAL,Harris,Allan,NULL,Male,African-American,07/21/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +56965,65090,59054,PRETRIAL,Harris,Allan,NULL,Male,African-American,07/21/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56967,65092,59056,Probation,nguyen,sau,van,Male,Asian,03/09/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/13 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +56967,65092,59056,Probation,nguyen,sau,van,Male,Asian,03/09/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/13 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +56967,65092,59056,Probation,nguyen,sau,van,Male,Asian,03/09/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56982,65111,59071,PRETRIAL,SARAVIACIUDADREAL,ALVARO,NULL,Male,Other,10/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +56982,65111,59071,PRETRIAL,SARAVIACIUDADREAL,ALVARO,NULL,Male,Other,10/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +56982,65111,59071,PRETRIAL,SARAVIACIUDADREAL,ALVARO,NULL,Male,Other,10/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56773,65071,58838,PRETRIAL,BLUE,SHAWANNA,NULL,Female,African-American,02/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,Copy,1,0 +56773,65071,58838,PRETRIAL,BLUE,SHAWANNA,NULL,Female,African-American,02/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,Copy,1,0 +56773,65071,58838,PRETRIAL,BLUE,SHAWANNA,NULL,Female,African-American,02/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +7606,65085,59049,PRETRIAL,sciorilli,leonard,NULL,Male,Caucasian,08/09/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +7606,65085,59049,PRETRIAL,sciorilli,leonard,NULL,Male,Caucasian,08/09/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +7606,65085,59049,PRETRIAL,sciorilli,leonard,NULL,Male,Caucasian,08/09/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56971,65097,59060,Probation,Sesler,Christopher,NULL,Male,African-American,06/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +56971,65097,59060,Probation,Sesler,Christopher,NULL,Male,African-American,06/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +56971,65097,59060,Probation,Sesler,Christopher,NULL,Male,African-American,06/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56976,65106,59067,Probation,Woollett,Steven,NULL,Male,Caucasian,04/12/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +56976,65106,59067,Probation,Woollett,Steven,NULL,Male,Caucasian,04/12/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +56976,65106,59067,Probation,Woollett,Steven,NULL,Male,Caucasian,04/12/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56955,65076,59041,PRETRIAL,McDougle,Bryan,NULL,Male,African-American,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +56955,65076,59041,PRETRIAL,McDougle,Bryan,NULL,Male,African-American,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +56955,65076,59041,PRETRIAL,McDougle,Bryan,NULL,Male,African-American,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56993,65127,59087,PRETRIAL,Garcia,Jelissa,NULL,Male,Hispanic,04/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +56993,65127,59087,PRETRIAL,Garcia,Jelissa,NULL,Male,Hispanic,04/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +56993,65127,59087,PRETRIAL,Garcia,Jelissa,NULL,Male,Hispanic,04/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +9981,65118,59078,PRETRIAL,Harris,Curtis,NULL,Male,Caucasian,03/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +9981,65118,59078,PRETRIAL,Harris,Curtis,NULL,Male,Caucasian,03/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +9981,65118,59078,PRETRIAL,Harris,Curtis,NULL,Male,Caucasian,03/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +26552,65136,59094,PRETRIAL,Mcclain,Fred,NULL,Male,African-American,06/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +26552,65136,59094,PRETRIAL,Mcclain,Fred,NULL,Male,African-American,06/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +26552,65136,59094,PRETRIAL,Mcclain,Fred,NULL,Male,African-American,06/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +57019,65153,59106,PRETRIAL,Gitta,Cecelia,NULL,Female,Caucasian,06/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,7,Risk of Violence,-2.94,2,Low,New,1,0 +57019,65153,59106,PRETRIAL,Gitta,Cecelia,NULL,Female,Caucasian,06/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +57019,65153,59106,PRETRIAL,Gitta,Cecelia,NULL,Female,Caucasian,06/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56998,65132,59092,PRETRIAL,Trump,Jasmine,NULL,Female,African-American,01/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +56998,65132,59092,PRETRIAL,Trump,Jasmine,NULL,Female,African-American,01/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +56998,65132,59092,PRETRIAL,Trump,Jasmine,NULL,Female,African-American,01/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57008,65139,59096,Probation,Hoeft,Thomas,NULL,Male,Caucasian,06/29/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/13 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +57008,65139,59096,Probation,Hoeft,Thomas,NULL,Male,Caucasian,06/29/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/13 0:00,4,High,8,Risk of Recidivism,0.31,9,High,New,1,0 +57008,65139,59096,Probation,Hoeft,Thomas,NULL,Male,Caucasian,06/29/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56989,65120,59080,PRETRIAL,DISALVO,DOMINIC,FERNANDO,Male,Caucasian,07/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +56989,65120,59080,PRETRIAL,DISALVO,DOMINIC,FERNANDO,Male,Caucasian,07/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +56989,65120,59080,PRETRIAL,DISALVO,DOMINIC,FERNANDO,Male,Caucasian,07/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56181,65134,58125,Probation,DOMINICK,TERRELL,CHRISTOPHER,Male,Hispanic,09/22/83,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/5/13 0:00,4,High,7,Risk of Violence,-0.33,10,High,New,1,0 +56181,65134,58125,Probation,DOMINICK,TERRELL,CHRISTOPHER,Male,Hispanic,09/22/83,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/5/13 0:00,4,High,8,Risk of Recidivism,0.95,10,High,New,1,0 +56181,65134,58125,Probation,DOMINICK,TERRELL,CHRISTOPHER,Male,Hispanic,09/22/83,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/5/13 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +57010,65141,59098,PRETRIAL,Maxime,Jean,Claude,Male,African-American,11/07/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/5/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +57010,65141,59098,PRETRIAL,Maxime,Jean,Claude,Male,African-American,11/07/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/5/13 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +57010,65141,59098,PRETRIAL,Maxime,Jean,Claude,Male,African-American,11/07/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45316,65148,45541,PRETRIAL,Beggs,Kenneth,NULL,Male,Caucasian,08/18/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,Copy,1,0 +45316,65148,45541,PRETRIAL,Beggs,Kenneth,NULL,Male,Caucasian,08/18/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,Copy,1,0 +45316,65148,45541,PRETRIAL,Beggs,Kenneth,NULL,Male,Caucasian,08/18/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +56995,65129,59089,PRETRIAL,Lane,Marcus,NULL,Male,African-American,03/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +56995,65129,59089,PRETRIAL,Lane,Marcus,NULL,Male,African-American,03/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +56995,65129,59089,PRETRIAL,Lane,Marcus,NULL,Male,African-American,03/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57012,65142,59099,PRETRIAL,Balentine,Bowie,NULL,Male,Caucasian,01/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +57012,65142,59099,PRETRIAL,Balentine,Bowie,NULL,Male,Caucasian,01/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +57012,65142,59099,PRETRIAL,Balentine,Bowie,NULL,Male,Caucasian,01/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +16568,65121,59081,PRETRIAL,Louiseron,Steve,NULL,Male,African-American,07/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +16568,65121,59081,PRETRIAL,Louiseron,Steve,NULL,Male,African-American,07/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +16568,65121,59081,PRETRIAL,Louiseron,Steve,NULL,Male,African-American,07/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +44952,65150,45113,PRETRIAL,blevins,ronaldo,NULL,Male,Caucasian,11/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/5/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,Copy,1,0 +44952,65150,45113,PRETRIAL,blevins,ronaldo,NULL,Male,Caucasian,11/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/5/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,Copy,1,0 +44952,65150,45113,PRETRIAL,blevins,ronaldo,NULL,Male,Caucasian,11/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +57018,65152,59105,Probation,Moorer,Clinton,Xavier,Male,African-American,02/18/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/5/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +57018,65152,59105,Probation,Moorer,Clinton,Xavier,Male,African-American,02/18/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/5/13 0:00,4,High,8,Risk of Recidivism,0.39,8,High,New,1,0 +57018,65152,59105,Probation,Moorer,Clinton,Xavier,Male,African-American,02/18/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/5/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +12856,65137,12340,PRETRIAL,Mullins,Theodore,Marcus,Male,African-American,08/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,Copy,1,0 +12856,65137,12340,PRETRIAL,Mullins,Theodore,Marcus,Male,African-American,08/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,Copy,1,0 +12856,65137,12340,PRETRIAL,Mullins,Theodore,Marcus,Male,African-American,08/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +57014,65145,59101,Probation,WIGGINS,TERRENCE,NULL,Male,African-American,03/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +57014,65145,59101,Probation,WIGGINS,TERRENCE,NULL,Male,African-American,03/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +57014,65145,59101,Probation,WIGGINS,TERRENCE,NULL,Male,African-American,03/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56991,65124,59084,PRETRIAL,Raj,Karan,NULL,Male,Native American,12/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +56991,65124,59084,PRETRIAL,Raj,Karan,NULL,Male,Native American,12/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +56991,65124,59084,PRETRIAL,Raj,Karan,NULL,Male,Native American,12/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56988,65119,59079,PRETRIAL,Roberts,Hope,NULL,Male,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +56988,65119,59079,PRETRIAL,Roberts,Hope,NULL,Male,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +56988,65119,59079,PRETRIAL,Roberts,Hope,NULL,Male,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56999,65133,59093,PRETRIAL,KELLY,DARRELL,B,Male,African-American,01/19/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,2,Medium,7,Risk of Violence,-2.47,3,Low,New,1,0 +56999,65133,59093,PRETRIAL,KELLY,DARRELL,B,Male,African-American,01/19/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +56999,65133,59093,PRETRIAL,KELLY,DARRELL,B,Male,African-American,01/19/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +56992,65126,59086,PRETRIAL,Jacquely,Deana,NULL,Female,African-American,10/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +56992,65126,59086,PRETRIAL,Jacquely,Deana,NULL,Female,African-American,10/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +56992,65126,59086,PRETRIAL,Jacquely,Deana,NULL,Female,African-American,10/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56994,65128,59088,PRETRIAL,Quinones,Sandra,Monica,Female,Caucasian,04/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/5/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +56994,65128,59088,PRETRIAL,Quinones,Sandra,Monica,Female,Caucasian,04/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/5/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +56994,65128,59088,PRETRIAL,Quinones,Sandra,Monica,Female,Caucasian,04/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57016,65147,59103,Probation,Blake,Frank,NULL,Male,African-American,11/17/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/5/13 0:00,2,Medium,7,Risk of Violence,-3.46,1,Low,New,1,0 +57016,65147,59103,Probation,Blake,Frank,NULL,Male,African-American,11/17/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +57016,65147,59103,Probation,Blake,Frank,NULL,Male,African-American,11/17/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/5/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +26662,65149,42043,PRETRIAL,Blake,Patrick,NULL,Male,African-American,12/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,Copy,1,0 +26662,65149,42043,PRETRIAL,Blake,Patrick,NULL,Male,African-American,12/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,Copy,1,0 +26662,65149,42043,PRETRIAL,Blake,Patrick,NULL,Male,African-American,12/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +56834,65135,58902,PRETRIAL,LEVY,DAMIAN,NULL,Male,African-American,04/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,Copy,1,0 +56834,65135,58902,PRETRIAL,LEVY,DAMIAN,NULL,Male,African-American,04/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,Copy,1,0 +56834,65135,58902,PRETRIAL,LEVY,DAMIAN,NULL,Male,African-American,04/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +56997,65131,59091,PRETRIAL,DABREZIL,JOHNY,NULL,Male,African-American,12/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,4,High,7,Risk of Violence,-0.12,10,High,New,1,0 +56997,65131,59091,PRETRIAL,DABREZIL,JOHNY,NULL,Male,African-American,12/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,4,High,8,Risk of Recidivism,0.92,10,High,New,1,0 +56997,65131,59091,PRETRIAL,DABREZIL,JOHNY,NULL,Male,African-American,12/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57009,65140,59097,Probation,noel,blaine,NULL,Male,Caucasian,01/11/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/5/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +57009,65140,59097,Probation,noel,blaine,NULL,Male,Caucasian,01/11/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/5/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +57009,65140,59097,Probation,noel,blaine,NULL,Male,Caucasian,01/11/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50393,65144,51408,PRETRIAL,CROWDER,DANIEL,NULL,Male,Caucasian,11/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,Copy,1,0 +50393,65144,51408,PRETRIAL,CROWDER,DANIEL,NULL,Male,Caucasian,11/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,Copy,1,0 +50393,65144,51408,PRETRIAL,CROWDER,DANIEL,NULL,Male,Caucasian,11/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +57002,65138,59095,DRRD,Brown,Breon,Dontrez,Male,African-American,11/06/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/5/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +57002,65138,59095,DRRD,Brown,Breon,Dontrez,Male,African-American,11/06/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/5/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +57002,65138,59095,DRRD,Brown,Breon,Dontrez,Male,African-American,11/06/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,1,Low,New,1,0 +32493,65125,59085,PRETRIAL,Sandholzer,Robert,NULL,Male,Caucasian,07/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +32493,65125,59085,PRETRIAL,Sandholzer,Robert,NULL,Male,Caucasian,07/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +32493,65125,59085,PRETRIAL,Sandholzer,Robert,NULL,Male,Caucasian,07/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57015,65146,59102,PRETRIAL,Aiken,Warren,NULL,Male,African-American,09/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +57015,65146,59102,PRETRIAL,Aiken,Warren,NULL,Male,African-American,09/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +57015,65146,59102,PRETRIAL,Aiken,Warren,NULL,Male,African-American,09/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +49819,65123,59083,PRETRIAL,Williams,Charleston,NULL,Male,African-American,12/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +49819,65123,59083,PRETRIAL,Williams,Charleston,NULL,Male,African-American,12/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +49819,65123,59083,PRETRIAL,Williams,Charleston,NULL,Male,African-American,12/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56996,65130,59090,PRETRIAL,MARIANI,MICHAEL,NULL,Male,Caucasian,04/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +56996,65130,59090,PRETRIAL,MARIANI,MICHAEL,NULL,Male,Caucasian,04/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +56996,65130,59090,PRETRIAL,MARIANI,MICHAEL,NULL,Male,Caucasian,04/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56990,65122,59082,PRETRIAL,Martin,Dalvis,G,Male,African-American,12/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +56990,65122,59082,PRETRIAL,Martin,Dalvis,G,Male,African-American,12/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +56990,65122,59082,PRETRIAL,Martin,Dalvis,G,Male,African-American,12/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +16861,65188,59136,PRETRIAL,Jones,Elton,A,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/13 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,New,1,0 +16861,65188,59136,PRETRIAL,Jones,Elton,A,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +16861,65188,59136,PRETRIAL,Jones,Elton,A,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57043,65180,59129,Probation,Mejia,Mario,NULL,Male,Hispanic,12/28/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +57043,65180,59129,Probation,Mejia,Mario,NULL,Male,Hispanic,12/28/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +57043,65180,59129,Probation,Mejia,Mario,NULL,Male,Hispanic,12/28/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57027,65164,59115,PRETRIAL,Beausejour,Jim,NULL,Male,African-American,03/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.07,4,Low,New,1,0 +57027,65164,59115,PRETRIAL,Beausejour,Jim,NULL,Male,African-American,03/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +57027,65164,59115,PRETRIAL,Beausejour,Jim,NULL,Male,African-American,03/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57035,65167,59118,PRETRIAL,Hill,Darrin,Michael,Male,Caucasian,11/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/6/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +57035,65167,59118,PRETRIAL,Hill,Darrin,Michael,Male,Caucasian,11/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/6/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +57035,65167,59118,PRETRIAL,Hill,Darrin,Michael,Male,Caucasian,11/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56057,65185,57976,Probation,Graham,Henry,NULL,Male,African-American,09/02/52,17,All Scales,Intake,English,Other,Probation,Widowed,9/6/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +56057,65185,57976,Probation,Graham,Henry,NULL,Male,African-American,09/02/52,17,All Scales,Intake,English,Other,Probation,Widowed,9/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +56057,65185,57976,Probation,Graham,Henry,NULL,Male,African-American,09/02/52,17,All Scales,Intake,English,Other,Probation,Widowed,9/6/13 0:00,2,Medium,18,Risk of Failure to Appear,31,8,High,New,1,0 +57022,65159,59110,PRETRIAL,Wright,Zezelda,NULL,Female,African-American,05/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +57022,65159,59110,PRETRIAL,Wright,Zezelda,NULL,Female,African-American,05/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,9,High,New,1,0 +57022,65159,59110,PRETRIAL,Wright,Zezelda,NULL,Female,African-American,05/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +57054,65193,59140,PRETRIAL,Elliot,Nesta,NULL,Male,African-American,06/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +57054,65193,59140,PRETRIAL,Elliot,Nesta,NULL,Male,African-American,06/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +57054,65193,59140,PRETRIAL,Elliot,Nesta,NULL,Male,African-American,06/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57040,65172,59123,PRETRIAL,Uter,Andre,NULL,Male,African-American,05/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +57040,65172,59123,PRETRIAL,Uter,Andre,NULL,Male,African-American,05/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +57040,65172,59123,PRETRIAL,Uter,Andre,NULL,Male,African-American,05/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57024,65161,59112,PRETRIAL,Cooper,Portia,NULL,Female,African-American,01/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +57024,65161,59112,PRETRIAL,Cooper,Portia,NULL,Female,African-American,01/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +57024,65161,59112,PRETRIAL,Cooper,Portia,NULL,Female,African-American,01/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57047,65186,59134,PRETRIAL,LIVINGSTON,TODD,ALAN,Female,Caucasian,05/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +57047,65186,59134,PRETRIAL,LIVINGSTON,TODD,ALAN,Female,Caucasian,05/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +57047,65186,59134,PRETRIAL,LIVINGSTON,TODD,ALAN,Female,Caucasian,05/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +57060,65200,59145,PRETRIAL,Pena,Rolando,NULL,Male,Hispanic,12/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +57060,65200,59145,PRETRIAL,Pena,Rolando,NULL,Male,Hispanic,12/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +57060,65200,59145,PRETRIAL,Pena,Rolando,NULL,Male,Hispanic,12/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57045,65182,59131,Probation,Wade,Joey,NULL,Male,African-American,12/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +57045,65182,59131,Probation,Wade,Joey,NULL,Male,African-American,12/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +57045,65182,59131,Probation,Wade,Joey,NULL,Male,African-American,12/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57057,65196,59143,PRETRIAL,Daniels,Gary,NULL,Male,African-American,03/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +57057,65196,59143,PRETRIAL,Daniels,Gary,NULL,Male,African-American,03/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,4,High,8,Risk of Recidivism,0.26,8,High,New,1,0 +57057,65196,59143,PRETRIAL,Daniels,Gary,NULL,Male,African-American,03/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56268,65154,58214,PRETRIAL,McDougle,Terrance,Laquelle,Male,African-American,03/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,Copy,1,0 +56268,65154,58214,PRETRIAL,McDougle,Terrance,Laquelle,Male,African-American,03/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,Copy,1,0 +56268,65154,58214,PRETRIAL,McDougle,Terrance,Laquelle,Male,African-American,03/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +32728,65156,59107,PRETRIAL,BAKER,NORENCE,NULL,Male,African-American,09/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +32728,65156,59107,PRETRIAL,BAKER,NORENCE,NULL,Male,African-American,09/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +32728,65156,59107,PRETRIAL,BAKER,NORENCE,NULL,Male,African-American,09/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53799,65175,55293,PRETRIAL,Telfair,Travis,NULL,Male,African-American,03/06/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,4,High,7,Risk of Violence,-0.94,9,High,Copy,1,0 +53799,65175,55293,PRETRIAL,Telfair,Travis,NULL,Male,African-American,03/06/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,4,High,8,Risk of Recidivism,0.35,9,High,Copy,1,0 +53799,65175,55293,PRETRIAL,Telfair,Travis,NULL,Male,African-American,03/06/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +56916,65177,59126,PRETRIAL,Gomez,Ivan,NULL,Male,Hispanic,02/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +56916,65177,59126,PRETRIAL,Gomez,Ivan,NULL,Male,Hispanic,02/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +56916,65177,59126,PRETRIAL,Gomez,Ivan,NULL,Male,Hispanic,02/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57038,65170,59121,PRETRIAL,Bosi-Godomar,Remo,NULL,Male,Caucasian,11/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +57038,65170,59121,PRETRIAL,Bosi-Godomar,Remo,NULL,Male,Caucasian,11/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +57038,65170,59121,PRETRIAL,Bosi-Godomar,Remo,NULL,Male,Caucasian,11/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57046,65184,59133,PRETRIAL,Little,Elliott,NULL,Male,African-American,02/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +57046,65184,59133,PRETRIAL,Little,Elliott,NULL,Male,African-American,02/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +57046,65184,59133,PRETRIAL,Little,Elliott,NULL,Male,African-American,02/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +20025,65191,51863,PRETRIAL,daniels,coy,samuel,Male,African-American,12/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,Copy,1,0 +20025,65191,51863,PRETRIAL,daniels,coy,samuel,Male,African-American,12/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,9,High,Copy,1,0 +20025,65191,51863,PRETRIAL,daniels,coy,samuel,Male,African-American,12/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +43541,65198,43508,PRETRIAL,Forte,Jaime,NULL,Female,African-American,03/04/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,New,1,0 +43541,65198,43508,PRETRIAL,Forte,Jaime,NULL,Female,African-American,03/04/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +43541,65198,43508,PRETRIAL,Forte,Jaime,NULL,Female,African-American,03/04/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +37927,65179,59128,PRETRIAL,Guaqueta,Santiago,NULL,Male,Caucasian,04/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +37927,65179,59128,PRETRIAL,Guaqueta,Santiago,NULL,Male,Caucasian,04/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +37927,65179,59128,PRETRIAL,Guaqueta,Santiago,NULL,Male,Caucasian,04/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57044,65181,59130,PRETRIAL,Provenzano,John,NULL,Male,Caucasian,04/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +57044,65181,59130,PRETRIAL,Provenzano,John,NULL,Male,Caucasian,04/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +57044,65181,59130,PRETRIAL,Provenzano,John,NULL,Male,Caucasian,04/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57021,65158,59109,PRETRIAL,Darby,Javon,NULL,Male,Other,09/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +57021,65158,59109,PRETRIAL,Darby,Javon,NULL,Male,Other,09/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +57021,65158,59109,PRETRIAL,Darby,Javon,NULL,Male,Other,09/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57023,65160,59111,PRETRIAL,Ortiz,Joshua,NULL,Male,Hispanic,08/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +57023,65160,59111,PRETRIAL,Ortiz,Joshua,NULL,Male,Hispanic,08/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +57023,65160,59111,PRETRIAL,Ortiz,Joshua,NULL,Male,Hispanic,08/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57055,65194,59141,Probation,CROWLEY,SHAUN,J,Male,Caucasian,11/10/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +57055,65194,59141,Probation,CROWLEY,SHAUN,J,Male,Caucasian,11/10/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +57055,65194,59141,Probation,CROWLEY,SHAUN,J,Male,Caucasian,11/10/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57028,65166,59117,PRETRIAL,Louis,Jose,NULL,Male,African-American,09/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +57028,65166,59117,PRETRIAL,Louis,Jose,NULL,Male,African-American,09/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +57028,65166,59117,PRETRIAL,Louis,Jose,NULL,Male,African-American,09/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57041,65173,59124,PRETRIAL,GOMEZDIBENEDETTO,JENNY,NULL,Female,Caucasian,09/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +57041,65173,59124,PRETRIAL,GOMEZDIBENEDETTO,JENNY,NULL,Female,Caucasian,09/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +57041,65173,59124,PRETRIAL,GOMEZDIBENEDETTO,JENNY,NULL,Female,Caucasian,09/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57048,65187,59135,Probation,Nassarpineda,Rafael,NULL,Male,Hispanic,06/02/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/6/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +57048,65187,59135,Probation,Nassarpineda,Rafael,NULL,Male,Hispanic,06/02/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +57048,65187,59135,Probation,Nassarpineda,Rafael,NULL,Male,Hispanic,06/02/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57036,65168,59119,PRETRIAL,Morgan,Tiffany,Denise,Female,African-American,07/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +57036,65168,59119,PRETRIAL,Morgan,Tiffany,Denise,Female,African-American,07/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +57036,65168,59119,PRETRIAL,Morgan,Tiffany,Denise,Female,African-American,07/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57039,65171,59122,PRETRIAL,Andujar,Jessica,NULL,Female,Caucasian,12/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +57039,65171,59122,PRETRIAL,Andujar,Jessica,NULL,Female,Caucasian,12/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +57039,65171,59122,PRETRIAL,Andujar,Jessica,NULL,Female,Caucasian,12/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +30141,65189,59137,Probation,Blanchette,Mark,NULL,Male,Caucasian,10/16/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/6/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +30141,65189,59137,Probation,Blanchette,Mark,NULL,Male,Caucasian,10/16/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/6/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +30141,65189,59137,Probation,Blanchette,Mark,NULL,Male,Caucasian,10/16/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,38,10,High,New,1,0 +41192,65176,40863,PRETRIAL,WILLIAMS,DEREK,KENYARDA,Male,African-American,08/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,Copy,1,0 +41192,65176,40863,PRETRIAL,WILLIAMS,DEREK,KENYARDA,Male,African-American,08/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,Copy,1,0 +41192,65176,40863,PRETRIAL,WILLIAMS,DEREK,KENYARDA,Male,African-American,08/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +57026,65163,59114,PRETRIAL,Richardson,Christopher,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +57026,65163,59114,PRETRIAL,Richardson,Christopher,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +57026,65163,59114,PRETRIAL,Richardson,Christopher,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57059,65197,59144,Probation,Molina,Jimy,NULL,Male,Hispanic,04/25/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/6/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +57059,65197,59144,Probation,Molina,Jimy,NULL,Male,Hispanic,04/25/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/6/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +57059,65197,59144,Probation,Molina,Jimy,NULL,Male,Hispanic,04/25/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +43223,65155,43139,Probation,Beasley,Kenneth,NULL,Male,African-American,01/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,Copy,1,0 +43223,65155,43139,Probation,Beasley,Kenneth,NULL,Male,African-American,01/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,Copy,1,0 +43223,65155,43139,Probation,Beasley,Kenneth,NULL,Male,African-American,01/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +57025,65162,59113,PRETRIAL,Diaz,Angelita,NULL,Male,African-American,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +57025,65162,59113,PRETRIAL,Diaz,Angelita,NULL,Male,African-American,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +57025,65162,59113,PRETRIAL,Diaz,Angelita,NULL,Male,African-American,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +16861,17441,16171,PRETRIAL,Jones,Elton,A,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/13 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +16861,17441,16171,PRETRIAL,Jones,Elton,A,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +16861,17441,16171,PRETRIAL,Jones,Elton,A,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57037,65169,59120,PRETRIAL,Dumera,Nesler,NULL,Male,Other,08/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +57037,65169,59120,PRETRIAL,Dumera,Nesler,NULL,Male,Other,08/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +57037,65169,59120,PRETRIAL,Dumera,Nesler,NULL,Male,Other,08/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +38525,65183,59132,PRETRIAL,Gubert,Timothy,NULL,Male,Caucasian,06/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +38525,65183,59132,PRETRIAL,Gubert,Timothy,NULL,Male,Caucasian,06/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +38525,65183,59132,PRETRIAL,Gubert,Timothy,NULL,Male,Caucasian,06/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57050,65192,59139,Probation,cooper,latif,NULL,Male,Caucasian,10/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.15,4,Low,New,1,0 +57050,65192,59139,Probation,cooper,latif,NULL,Male,Caucasian,10/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +57050,65192,59139,Probation,cooper,latif,NULL,Male,Caucasian,10/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57049,65190,59138,Probation,Gordon,Deron,NULL,Male,African-American,05/31/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +57049,65190,59138,Probation,Gordon,Deron,NULL,Male,African-American,05/31/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-2.73,1,Low,New,1,0 +57049,65190,59138,Probation,Gordon,Deron,NULL,Male,African-American,05/31/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57020,65157,59108,PRETRIAL,Hernandez,Carlos,Daniel,Male,Hispanic,07/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +57020,65157,59108,PRETRIAL,Hernandez,Carlos,Daniel,Male,Hispanic,07/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +57020,65157,59108,PRETRIAL,Hernandez,Carlos,Daniel,Male,Hispanic,07/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57042,65178,59127,Probation,Santos,Fabio,NULL,Male,Hispanic,01/01/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/6/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +57042,65178,59127,Probation,Santos,Fabio,NULL,Male,Hispanic,01/01/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +57042,65178,59127,Probation,Santos,Fabio,NULL,Male,Hispanic,01/01/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57056,65195,59142,PRETRIAL,Santiago,Patrick,NULL,Male,African-American,05/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +57056,65195,59142,PRETRIAL,Santiago,Patrick,NULL,Male,African-American,05/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +57056,65195,59142,PRETRIAL,Santiago,Patrick,NULL,Male,African-American,05/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +49669,65199,50567,Probation,nicholas,charlotte,NULL,Female,Caucasian,09/19/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,Copy,1,0 +49669,65199,50567,Probation,nicholas,charlotte,NULL,Female,Caucasian,09/19/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,Copy,1,0 +49669,65199,50567,Probation,nicholas,charlotte,NULL,Female,Caucasian,09/19/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +57063,65204,59148,PRETRIAL,Brown,Jessica,NULL,Female,African-American,05/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +57063,65204,59148,PRETRIAL,Brown,Jessica,NULL,Female,African-American,05/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +57063,65204,59148,PRETRIAL,Brown,Jessica,NULL,Female,African-American,05/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +48489,65208,59152,PRETRIAL,SPILLANE,BRUCE,NULL,Male,Caucasian,11/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/7/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +48489,65208,59152,PRETRIAL,SPILLANE,BRUCE,NULL,Male,Caucasian,11/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/7/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +48489,65208,59152,PRETRIAL,SPILLANE,BRUCE,NULL,Male,Caucasian,11/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/7/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57068,65210,59154,PRETRIAL,Rawiszer,Mark,NULL,Male,Caucasian,09/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +57068,65210,59154,PRETRIAL,Rawiszer,Mark,NULL,Male,Caucasian,09/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +57068,65210,59154,PRETRIAL,Rawiszer,Mark,NULL,Male,Caucasian,09/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57061,65202,59146,PRETRIAL,Fields,James,Samuel,Male,Caucasian,03/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/7/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +57061,65202,59146,PRETRIAL,Fields,James,Samuel,Male,Caucasian,03/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/7/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +57061,65202,59146,PRETRIAL,Fields,James,Samuel,Male,Caucasian,03/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57065,65205,59149,PRETRIAL,CERENZIA,GABRIEL,NULL,Male,Caucasian,11/21/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +57065,65205,59149,PRETRIAL,CERENZIA,GABRIEL,NULL,Male,Caucasian,11/21/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +57065,65205,59149,PRETRIAL,CERENZIA,GABRIEL,NULL,Male,Caucasian,11/21/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57066,65207,59151,PRETRIAL,Waller,Angela,Dawn,Female,Caucasian,07/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +57066,65207,59151,PRETRIAL,Waller,Angela,Dawn,Female,Caucasian,07/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +57066,65207,59151,PRETRIAL,Waller,Angela,Dawn,Female,Caucasian,07/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57062,65203,59147,PRETRIAL,MODROK,DEREK,A,Male,Caucasian,11/16/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +57062,65203,59147,PRETRIAL,MODROK,DEREK,A,Male,Caucasian,11/16/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +57062,65203,59147,PRETRIAL,MODROK,DEREK,A,Male,Caucasian,11/16/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57064,65206,59150,PRETRIAL,Eady,Carlos,S,Male,African-American,12/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +57064,65206,59150,PRETRIAL,Eady,Carlos,S,Male,African-American,12/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +57064,65206,59150,PRETRIAL,Eady,Carlos,S,Male,African-American,12/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +7805,65201,53767,PRETRIAL,Roberts,Samuel,NULL,Male,African-American,01/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,4,High,7,Risk of Violence,-1.25,8,High,Copy,1,0 +7805,65201,53767,PRETRIAL,Roberts,Samuel,NULL,Male,African-American,01/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,Copy,1,0 +7805,65201,53767,PRETRIAL,Roberts,Samuel,NULL,Male,African-American,01/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +57067,65209,59153,PRETRIAL,Morris,Glenn,NULL,Male,Caucasian,12/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/7/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +57067,65209,59153,PRETRIAL,Morris,Glenn,NULL,Male,Caucasian,12/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/7/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +57067,65209,59153,PRETRIAL,Morris,Glenn,NULL,Male,Caucasian,12/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/7/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57075,65222,59164,PRETRIAL,CALIXTE,VLADIMIR,F,Male,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +57075,65222,59164,PRETRIAL,CALIXTE,VLADIMIR,F,Male,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +57075,65222,59164,PRETRIAL,CALIXTE,VLADIMIR,F,Male,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57077,65224,59166,PRETRIAL,fanfan,jonathan,NULL,Male,African-American,08/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +57077,65224,59166,PRETRIAL,fanfan,jonathan,NULL,Male,African-American,08/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +57077,65224,59166,PRETRIAL,fanfan,jonathan,NULL,Male,African-American,08/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57072,65216,59159,PRETRIAL,Beldunord,Jean,NULL,Male,Other,06/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/8/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +57072,65216,59159,PRETRIAL,Beldunord,Jean,NULL,Male,Other,06/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/8/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +57072,65216,59159,PRETRIAL,Beldunord,Jean,NULL,Male,Other,06/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +13032,13428,12471,PRETRIAL,Bryant,Christopher,S,Male,African-American,09/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +13032,13428,12471,PRETRIAL,Bryant,Christopher,S,Male,African-American,09/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +13032,13428,12471,PRETRIAL,Bryant,Christopher,S,Male,African-American,09/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57070,65214,59157,PRETRIAL,DUBICKI,PHILIP,JOSEPH,Male,Caucasian,10/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/8/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +57070,65214,59157,PRETRIAL,DUBICKI,PHILIP,JOSEPH,Male,Caucasian,10/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/8/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +57070,65214,59157,PRETRIAL,DUBICKI,PHILIP,JOSEPH,Male,Caucasian,10/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/8/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +38031,65217,59160,PRETRIAL,Morgan,Wilford,NULL,Male,African-American,03/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +38031,65217,59160,PRETRIAL,Morgan,Wilford,NULL,Male,African-American,03/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,4,High,8,Risk of Recidivism,0.26,8,High,New,1,0 +38031,65217,59160,PRETRIAL,Morgan,Wilford,NULL,Male,African-American,03/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +11150,65221,10668,PRETRIAL,SMITH,MARKEI,YALE,Male,African-American,11/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.25,3,Low,Copy,1,0 +11150,65221,10668,PRETRIAL,SMITH,MARKEI,YALE,Male,African-American,11/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +11150,65221,10668,PRETRIAL,SMITH,MARKEI,YALE,Male,African-American,11/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +57069,65212,59156,PRETRIAL,CURIEL,NIKOLE,FRANCINE,Female,Caucasian,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/8/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +57069,65212,59156,PRETRIAL,CURIEL,NIKOLE,FRANCINE,Female,Caucasian,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +57069,65212,59156,PRETRIAL,CURIEL,NIKOLE,FRANCINE,Female,Caucasian,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/8/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57073,65219,59162,PRETRIAL,BRUNA,DIEGO,PABLO,Male,Hispanic,07/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +57073,65219,59162,PRETRIAL,BRUNA,DIEGO,PABLO,Male,Hispanic,07/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +57073,65219,59162,PRETRIAL,BRUNA,DIEGO,PABLO,Male,Hispanic,07/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57076,65223,59165,PRETRIAL,Letsky,Garry,Franklin,Male,Caucasian,03/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/8/13 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,New,1,0 +57076,65223,59165,PRETRIAL,Letsky,Garry,Franklin,Male,Caucasian,03/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +57076,65223,59165,PRETRIAL,Letsky,Garry,Franklin,Male,Caucasian,03/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/8/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57071,65215,59158,PRETRIAL,Hawkins,Tawanna,NULL,Female,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +57071,65215,59158,PRETRIAL,Hawkins,Tawanna,NULL,Female,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +57071,65215,59158,PRETRIAL,Hawkins,Tawanna,NULL,Female,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +8206,65218,59161,PRETRIAL,MCCLOUD,RENARD,NULL,Male,African-American,01/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.01,4,Low,New,1,0 +8206,65218,59161,PRETRIAL,MCCLOUD,RENARD,NULL,Male,African-American,01/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +8206,65218,59161,PRETRIAL,MCCLOUD,RENARD,NULL,Male,African-American,01/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +13032,65225,12471,PRETRIAL,Bryant,Christopher,S,Male,African-American,09/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,Copy,1,0 +13032,65225,12471,PRETRIAL,Bryant,Christopher,S,Male,African-American,09/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,Copy,1,0 +13032,65225,12471,PRETRIAL,Bryant,Christopher,S,Male,African-American,09/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +37721,65213,54976,PRETRIAL,Westbrook,Broderick,D,Male,African-American,05/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,4,High,7,Risk of Violence,-1.07,8,High,Copy,1,0 +37721,65213,54976,PRETRIAL,Westbrook,Broderick,D,Male,African-American,05/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,4,High,8,Risk of Recidivism,0.35,9,High,Copy,1,0 +37721,65213,54976,PRETRIAL,Westbrook,Broderick,D,Male,African-American,05/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +42846,65211,59155,PRETRIAL,Owens,Velon,NULL,Male,African-American,01/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,New,1,0 +42846,65211,59155,PRETRIAL,Owens,Velon,NULL,Male,African-American,01/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +42846,65211,59155,PRETRIAL,Owens,Velon,NULL,Male,African-American,01/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57074,65220,59163,PRETRIAL,COOKE,HARATIO,NULL,Male,African-American,07/31/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +57074,65220,59163,PRETRIAL,COOKE,HARATIO,NULL,Male,African-American,07/31/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +57074,65220,59163,PRETRIAL,COOKE,HARATIO,NULL,Male,African-American,07/31/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +25399,65269,59207,Probation,CARBAJAL,JOSE,A,Male,Hispanic,05/13/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/9/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +25399,65269,59207,Probation,CARBAJAL,JOSE,A,Male,Hispanic,05/13/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +25399,65269,59207,Probation,CARBAJAL,JOSE,A,Male,Hispanic,05/13/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +33818,65241,59181,PRETRIAL,marino,Alexander,NULL,Male,Caucasian,07/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +33818,65241,59181,PRETRIAL,marino,Alexander,NULL,Male,Caucasian,07/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +33818,65241,59181,PRETRIAL,marino,Alexander,NULL,Male,Caucasian,07/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +45570,65248,59187,PRETRIAL,MURRAY,JAMES,LEE,Male,Caucasian,01/31/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/9/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +45570,65248,59187,PRETRIAL,MURRAY,JAMES,LEE,Male,Caucasian,01/31/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/9/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +45570,65248,59187,PRETRIAL,MURRAY,JAMES,LEE,Male,Caucasian,01/31/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57102,65255,59194,Probation,Chilel,Audencio,NULL,Male,Hispanic,03/30/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +57102,65255,59194,Probation,Chilel,Audencio,NULL,Male,Hispanic,03/30/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +57102,65255,59194,Probation,Chilel,Audencio,NULL,Male,Hispanic,03/30/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57107,65262,59200,Probation,Rivera Ruiz,Joseph,NULL,Male,Hispanic,07/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +57107,65262,59200,Probation,Rivera Ruiz,Joseph,NULL,Male,Hispanic,07/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +57107,65262,59200,Probation,Rivera Ruiz,Joseph,NULL,Male,Hispanic,07/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57114,65276,59214,PRETRIAL,JOHNSON,WILLIE,NULL,Male,African-American,11/02/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +57114,65276,59214,PRETRIAL,JOHNSON,WILLIE,NULL,Male,African-American,11/02/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +57114,65276,59214,PRETRIAL,JOHNSON,WILLIE,NULL,Male,African-American,11/02/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +57081,65229,59170,PRETRIAL,Yearby,Darryl,Hilton,Male,African-American,07/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +57081,65229,59170,PRETRIAL,Yearby,Darryl,Hilton,Male,African-American,07/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +57081,65229,59170,PRETRIAL,Yearby,Darryl,Hilton,Male,African-American,07/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +55766,65246,57656,Probation,Fields,Monyca,NULL,Female,African-American,02/14/82,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +55766,65246,57656,Probation,Fields,Monyca,NULL,Female,African-American,02/14/82,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +55766,65246,57656,Probation,Fields,Monyca,NULL,Female,African-American,02/14/82,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57108,65264,59202,PRETRIAL,Irby,Anthony,NULL,Male,African-American,01/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +57108,65264,59202,PRETRIAL,Irby,Anthony,NULL,Male,African-American,01/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +57108,65264,59202,PRETRIAL,Irby,Anthony,NULL,Male,African-American,01/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +45269,65271,59209,PRETRIAL,Rutledge,Mark,NULL,Male,African-American,11/17/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,4,High,7,Risk of Violence,-0.49,10,High,New,1,0 +45269,65271,59209,PRETRIAL,Rutledge,Mark,NULL,Male,African-American,11/17/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,4,High,8,Risk of Recidivism,0.44,9,High,New,1,0 +45269,65271,59209,PRETRIAL,Rutledge,Mark,NULL,Male,African-American,11/17/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,4,High,18,Risk of Failure to Appear,19,2,Low,New,1,0 +57097,65250,59189,PRETRIAL,Pagan,Felipe,NULL,Male,African-American,12/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/9/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +57097,65250,59189,PRETRIAL,Pagan,Felipe,NULL,Male,African-American,12/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +57097,65250,59189,PRETRIAL,Pagan,Felipe,NULL,Male,African-American,12/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57111,65267,59205,Probation,obsaint,jerry,NULL,Male,African-American,08/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,New,1,0 +57111,65267,59205,Probation,obsaint,jerry,NULL,Male,African-American,08/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +57111,65267,59205,Probation,obsaint,jerry,NULL,Male,African-American,08/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57087,65236,59176,PRETRIAL,Shuman,Christopher,NULL,Male,African-American,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +57087,65236,59176,PRETRIAL,Shuman,Christopher,NULL,Male,African-American,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +57087,65236,59176,PRETRIAL,Shuman,Christopher,NULL,Male,African-American,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57090,65239,59179,PRETRIAL,BRYANT,DARREN,JOSEPH,Male,African-American,04/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +57090,65239,59179,PRETRIAL,BRYANT,DARREN,JOSEPH,Male,African-American,04/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +57090,65239,59179,PRETRIAL,BRYANT,DARREN,JOSEPH,Male,African-American,04/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57103,65257,59196,PRETRIAL,RODRIGUEZ,ROBELLO,NULL,Male,Hispanic,09/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +57103,65257,59196,PRETRIAL,RODRIGUEZ,ROBELLO,NULL,Male,Hispanic,09/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +57103,65257,59196,PRETRIAL,RODRIGUEZ,ROBELLO,NULL,Male,Hispanic,09/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57094,65244,59184,PRETRIAL,Williams,Joe,NULL,Male,African-American,10/20/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.16,8,High,New,1,0 +57094,65244,59184,PRETRIAL,Williams,Joe,NULL,Male,African-American,10/20/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +57094,65244,59184,PRETRIAL,Williams,Joe,NULL,Male,African-American,10/20/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,2,Low,New,1,0 +57083,65231,59172,PRETRIAL,BANKSTON,DAMANI,MARKEL,Male,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +57083,65231,59172,PRETRIAL,BANKSTON,DAMANI,MARKEL,Male,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +57083,65231,59172,PRETRIAL,BANKSTON,DAMANI,MARKEL,Male,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53913,65260,55437,PRETRIAL,Running,Rodger,Hall,Male,Caucasian,12/08/62,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,9/9/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +53913,65260,55437,PRETRIAL,Running,Rodger,Hall,Male,Caucasian,12/08/62,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +53913,65260,55437,PRETRIAL,Running,Rodger,Hall,Male,Caucasian,12/08/62,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,23,4,Low,New,1,0 +33606,65273,59211,PRETRIAL,boone,kena,NULL,Male,African-American,07/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +33606,65273,59211,PRETRIAL,boone,kena,NULL,Male,African-American,07/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,4,High,8,Risk of Recidivism,0.42,9,High,New,1,0 +33606,65273,59211,PRETRIAL,boone,kena,NULL,Male,African-American,07/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57098,65252,59191,PRETRIAL,Pinales,Jordan,NULL,Male,African-American,05/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +57098,65252,59191,PRETRIAL,Pinales,Jordan,NULL,Male,African-American,05/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +57098,65252,59191,PRETRIAL,Pinales,Jordan,NULL,Male,African-American,05/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57085,65233,59174,PRETRIAL,BAILEY,JAMAL,NULL,Male,African-American,06/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +57085,65233,59174,PRETRIAL,BAILEY,JAMAL,NULL,Male,African-American,06/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +57085,65233,59174,PRETRIAL,BAILEY,JAMAL,NULL,Male,African-American,06/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +36989,65270,59208,PRETRIAL,White,Kelvin,NULL,Male,African-American,12/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +36989,65270,59208,PRETRIAL,White,Kelvin,NULL,Male,African-American,12/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +36989,65270,59208,PRETRIAL,White,Kelvin,NULL,Male,African-American,12/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57078,65226,59167,PRETRIAL,ANKNEY,JASON,PHILIP,Male,Caucasian,02/06/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +57078,65226,59167,PRETRIAL,ANKNEY,JASON,PHILIP,Male,Caucasian,02/06/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +57078,65226,59167,PRETRIAL,ANKNEY,JASON,PHILIP,Male,Caucasian,02/06/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57080,65228,59169,PRETRIAL,KETOLA,TARA,LEANNE,Female,Caucasian,03/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +57080,65228,59169,PRETRIAL,KETOLA,TARA,LEANNE,Female,Caucasian,03/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +57080,65228,59169,PRETRIAL,KETOLA,TARA,LEANNE,Female,Caucasian,03/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57113,65275,59213,PRETRIAL,Quiruz,Tatiana,NULL,Female,Hispanic,03/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/9/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +57113,65275,59213,PRETRIAL,Quiruz,Tatiana,NULL,Female,Hispanic,03/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +57113,65275,59213,PRETRIAL,Quiruz,Tatiana,NULL,Female,Hispanic,03/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55840,65247,59186,PRETRIAL,Oberman,Bridgette,NULL,Female,Caucasian,12/11/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +55840,65247,59186,PRETRIAL,Oberman,Bridgette,NULL,Female,Caucasian,12/11/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +55840,65247,59186,PRETRIAL,Oberman,Bridgette,NULL,Female,Caucasian,12/11/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,18,2,Low,New,1,0 +57096,65249,59188,Probation,MERTZ,THOMAS,T,Male,Caucasian,12/01/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/9/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +57096,65249,59188,Probation,MERTZ,THOMAS,T,Male,Caucasian,12/01/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +57096,65249,59188,Probation,MERTZ,THOMAS,T,Male,Caucasian,12/01/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +16235,65254,59193,PRETRIAL,SMITH,LEVAR,NULL,Male,African-American,09/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +16235,65254,59193,PRETRIAL,SMITH,LEVAR,NULL,Male,African-American,09/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +16235,65254,59193,PRETRIAL,SMITH,LEVAR,NULL,Male,African-American,09/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +57101,65256,59195,Probation,Casciola,Thomas,NULL,Male,Caucasian,06/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +57101,65256,59195,Probation,Casciola,Thomas,NULL,Male,Caucasian,06/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +57101,65256,59195,Probation,Casciola,Thomas,NULL,Male,Caucasian,06/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56922,65242,59182,PRETRIAL,Davis,Heidemarie,NULL,Female,Caucasian,08/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +56922,65242,59182,PRETRIAL,Davis,Heidemarie,NULL,Female,Caucasian,08/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,8,High,New,1,0 +56922,65242,59182,PRETRIAL,Davis,Heidemarie,NULL,Female,Caucasian,08/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +57105,65259,59198,PRETRIAL,Peters,Stephen,NULL,Male,Caucasian,08/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/9/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +57105,65259,59198,PRETRIAL,Peters,Stephen,NULL,Male,Caucasian,08/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +57105,65259,59198,PRETRIAL,Peters,Stephen,NULL,Male,Caucasian,08/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57088,65238,59178,PRETRIAL,CRUZ-MOLINA,WESSLEY,T,Male,Caucasian,07/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +57088,65238,59178,PRETRIAL,CRUZ-MOLINA,WESSLEY,T,Male,Caucasian,07/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +57088,65238,59178,PRETRIAL,CRUZ-MOLINA,WESSLEY,T,Male,Caucasian,07/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +36931,65263,59201,PRETRIAL,Bedford,Terrace,NULL,Male,African-American,12/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +36931,65263,59201,PRETRIAL,Bedford,Terrace,NULL,Male,African-American,12/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +36931,65263,59201,PRETRIAL,Bedford,Terrace,NULL,Male,African-American,12/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57112,65272,59210,Probation,Moore,Keith,Jerome,Male,African-American,06/13/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +57112,65272,59210,Probation,Moore,Keith,Jerome,Male,African-American,06/13/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +57112,65272,59210,Probation,Moore,Keith,Jerome,Male,African-American,06/13/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +45766,65268,59206,PRETRIAL,Tindall,Christopher,NULL,Male,African-American,12/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +45766,65268,59206,PRETRIAL,Tindall,Christopher,NULL,Male,African-American,12/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +45766,65268,59206,PRETRIAL,Tindall,Christopher,NULL,Male,African-American,12/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57084,65232,59173,PRETRIAL,Sweeting,Travis,NULL,Male,African-American,11/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +57084,65232,59173,PRETRIAL,Sweeting,Travis,NULL,Male,African-American,11/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +57084,65232,59173,PRETRIAL,Sweeting,Travis,NULL,Male,African-American,11/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57086,65235,59175,PRETRIAL,Bishop,Dylan,P,Male,Caucasian,02/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +57086,65235,59175,PRETRIAL,Bishop,Dylan,P,Male,Caucasian,02/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +57086,65235,59175,PRETRIAL,Bishop,Dylan,P,Male,Caucasian,02/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57100,65253,59192,PRETRIAL,Boubacar,Zida,NULL,Male,Other,04/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/9/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +57100,65253,59192,PRETRIAL,Boubacar,Zida,NULL,Male,Other,04/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +57100,65253,59192,PRETRIAL,Boubacar,Zida,NULL,Male,Other,04/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +18233,65240,59180,PRETRIAL,Evans,Thomas,NULL,Male,African-American,08/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/9/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +18233,65240,59180,PRETRIAL,Evans,Thomas,NULL,Male,African-American,08/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +18233,65240,59180,PRETRIAL,Evans,Thomas,NULL,Male,African-American,08/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +5911,65274,59212,PRETRIAL,POPLIN,BELINDA,FAYE,Female,Caucasian,09/26/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.46,3,Low,New,1,0 +5911,65274,59212,PRETRIAL,POPLIN,BELINDA,FAYE,Female,Caucasian,09/26/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,9,High,New,1,0 +5911,65274,59212,PRETRIAL,POPLIN,BELINDA,FAYE,Female,Caucasian,09/26/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +57079,65227,59168,PRETRIAL,Gonzalez,Christopher,NULL,Male,Hispanic,01/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/9/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +57079,65227,59168,PRETRIAL,Gonzalez,Christopher,NULL,Male,Hispanic,01/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +57079,65227,59168,PRETRIAL,Gonzalez,Christopher,NULL,Male,Hispanic,01/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57082,65230,59171,PRETRIAL,Coleman,Dyesha,NULL,Female,African-American,09/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +57082,65230,59171,PRETRIAL,Coleman,Dyesha,NULL,Female,African-American,09/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +57082,65230,59171,PRETRIAL,Coleman,Dyesha,NULL,Female,African-American,09/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57110,65266,59204,Probation,Otano,Idael,NULL,Male,Hispanic,12/24/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/9/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +57110,65266,59204,Probation,Otano,Idael,NULL,Male,Hispanic,12/24/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +57110,65266,59204,Probation,Otano,Idael,NULL,Male,Hispanic,12/24/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57089,65237,59177,PRETRIAL,GRANT,MATTHEW,G,Male,African-American,07/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +57089,65237,59177,PRETRIAL,GRANT,MATTHEW,G,Male,African-American,07/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +57089,65237,59177,PRETRIAL,GRANT,MATTHEW,G,Male,African-American,07/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57099,65251,59190,PRETRIAL,ANTOINE,ORNAN,NULL,Male,African-American,06/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +57099,65251,59190,PRETRIAL,ANTOINE,ORNAN,NULL,Male,African-American,06/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +57099,65251,59190,PRETRIAL,ANTOINE,ORNAN,NULL,Male,African-American,06/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57104,65258,59197,PRETRIAL,Logiudice,Matthew,NULL,Male,Caucasian,09/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/9/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +57104,65258,59197,PRETRIAL,Logiudice,Matthew,NULL,Male,Caucasian,09/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +57104,65258,59197,PRETRIAL,Logiudice,Matthew,NULL,Male,Caucasian,09/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57093,65243,59183,Probation,MCMILLIAN,LEMANUEL,L,Male,African-American,12/10/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +57093,65243,59183,Probation,MCMILLIAN,LEMANUEL,L,Male,African-American,12/10/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +57093,65243,59183,Probation,MCMILLIAN,LEMANUEL,L,Male,African-American,12/10/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57095,65245,59185,Probation,Brown,Cameron,NULL,Male,African-American,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/9/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +57095,65245,59185,Probation,Brown,Cameron,NULL,Male,African-American,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/9/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +57095,65245,59185,Probation,Brown,Cameron,NULL,Male,African-American,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/9/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +57117,65279,59217,PRETRIAL,COLLINS,kENYATTI,NULL,Male,African-American,01/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +57117,65279,59217,PRETRIAL,COLLINS,kENYATTI,NULL,Male,African-American,01/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +57117,65279,59217,PRETRIAL,COLLINS,kENYATTI,NULL,Male,African-American,01/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57125,65287,59223,PRETRIAL,Foerster,Lori,NULL,Female,Caucasian,03/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +57125,65287,59223,PRETRIAL,Foerster,Lori,NULL,Female,Caucasian,03/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +57125,65287,59223,PRETRIAL,Foerster,Lori,NULL,Female,Caucasian,03/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +45325,65295,59230,PRETRIAL,McMillon,Joshua,NULL,Male,African-American,04/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/10/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +45325,65295,59230,PRETRIAL,McMillon,Joshua,NULL,Male,African-American,04/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/10/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +45325,65295,59230,PRETRIAL,McMillon,Joshua,NULL,Male,African-American,04/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57137,65308,59242,Probation,bryant,antonio,NULL,Male,African-American,03/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +57137,65308,59242,Probation,bryant,antonio,NULL,Male,African-American,03/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +57137,65308,59242,Probation,bryant,antonio,NULL,Male,African-American,03/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57134,65303,59237,Probation,gomez,enrique,NULL,Male,Caucasian,10/26/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/10/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +57134,65303,59237,Probation,gomez,enrique,NULL,Male,Caucasian,10/26/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/10/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +57134,65303,59237,Probation,gomez,enrique,NULL,Male,Caucasian,10/26/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57123,65282,59219,PRETRIAL,Munoz,Jaircinio,NULL,Male,Hispanic,05/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +57123,65282,59219,PRETRIAL,Munoz,Jaircinio,NULL,Male,Hispanic,05/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +57123,65282,59219,PRETRIAL,Munoz,Jaircinio,NULL,Male,Hispanic,05/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57126,65289,59224,Probation,Rubiovalesquez,Luis,NULL,Male,Hispanic,08/20/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/10/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +57126,65289,59224,Probation,Rubiovalesquez,Luis,NULL,Male,Hispanic,08/20/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/10/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +57126,65289,59224,Probation,Rubiovalesquez,Luis,NULL,Male,Hispanic,08/20/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +31285,65314,59248,PRETRIAL,deutsch,zackery,NULL,Male,Caucasian,12/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +31285,65314,59248,PRETRIAL,deutsch,zackery,NULL,Male,Caucasian,12/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +31285,65314,59248,PRETRIAL,deutsch,zackery,NULL,Male,Caucasian,12/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57139,65310,59244,PRETRIAL,Giarraputo,Toni,NULL,Female,Caucasian,10/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +57139,65310,59244,PRETRIAL,Giarraputo,Toni,NULL,Female,Caucasian,10/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +57139,65310,59244,PRETRIAL,Giarraputo,Toni,NULL,Female,Caucasian,10/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57115,65277,59215,PRETRIAL,Junior,Foufoune,NULL,Female,Other,10/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +57115,65277,59215,PRETRIAL,Junior,Foufoune,NULL,Female,Other,10/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +57115,65277,59215,PRETRIAL,Junior,Foufoune,NULL,Female,Other,10/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57124,65284,59220,PRETRIAL,KEMP,JOHN,NULL,Male,African-American,02/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +57124,65284,59220,PRETRIAL,KEMP,JOHN,NULL,Male,African-American,02/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/13 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +57124,65284,59220,PRETRIAL,KEMP,JOHN,NULL,Male,African-American,02/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57128,65291,59226,PRETRIAL,LOUGHRAN,MICHAEL,OATRICK,Male,Caucasian,08/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +57128,65291,59226,PRETRIAL,LOUGHRAN,MICHAEL,OATRICK,Male,Caucasian,08/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +57128,65291,59226,PRETRIAL,LOUGHRAN,MICHAEL,OATRICK,Male,Caucasian,08/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +48962,65298,59233,PRETRIAL,HOFER,DONNA,RICE,Female,Caucasian,01/27/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/10/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +48962,65298,59233,PRETRIAL,HOFER,DONNA,RICE,Female,Caucasian,01/27/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/10/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +48962,65298,59233,PRETRIAL,HOFER,DONNA,RICE,Female,Caucasian,01/27/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +48661,65305,59239,PRETRIAL,Foutz,Frederick,NULL,Male,Caucasian,09/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/10/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +48661,65305,59239,PRETRIAL,Foutz,Frederick,NULL,Male,Caucasian,09/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/10/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +48661,65305,59239,PRETRIAL,Foutz,Frederick,NULL,Male,Caucasian,09/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57133,65301,59235,Probation,Motta,Bruna,NULL,Female,Caucasian,02/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +57133,65301,59235,Probation,Motta,Bruna,NULL,Female,Caucasian,02/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +57133,65301,59235,Probation,Motta,Bruna,NULL,Female,Caucasian,02/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +52274,65302,59236,PRETRIAL,MOSLEY,DEON,MAURRICE,Male,African-American,10/09/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +52274,65302,59236,PRETRIAL,MOSLEY,DEON,MAURRICE,Male,African-American,10/09/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +52274,65302,59236,PRETRIAL,MOSLEY,DEON,MAURRICE,Male,African-American,10/09/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57122,65280,59218,PRETRIAL,Brown,Jamal,NULL,Male,African-American,01/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +57122,65280,59218,PRETRIAL,Brown,Jamal,NULL,Male,African-American,01/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +57122,65280,59218,PRETRIAL,Brown,Jamal,NULL,Male,African-American,01/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57130,65294,59229,PRETRIAL,Hylton,Ricardo,NULL,Male,African-American,02/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +57130,65294,59229,PRETRIAL,Hylton,Ricardo,NULL,Male,African-American,02/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +57130,65294,59229,PRETRIAL,Hylton,Ricardo,NULL,Male,African-American,02/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57138,65309,59243,Probation,CARLUCCI,ANTHONY,P,Male,Caucasian,10/05/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +57138,65309,59243,Probation,CARLUCCI,ANTHONY,P,Male,Caucasian,10/05/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +57138,65309,59243,Probation,CARLUCCI,ANTHONY,P,Male,Caucasian,10/05/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +37089,65281,36443,Probation,Stanley,Winston,A,Male,African-American,12/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,Copy,1,0 +37089,65281,36443,Probation,Stanley,Winston,A,Male,African-American,12/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,Copy,1,0 +37089,65281,36443,Probation,Stanley,Winston,A,Male,African-American,12/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +49384,65288,50221,PRETRIAL,BATTLE,FRANK,NULL,Male,African-American,09/10/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2,4,Low,Copy,1,0 +49384,65288,50221,PRETRIAL,BATTLE,FRANK,NULL,Male,African-American,09/10/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,Copy,1,0 +49384,65288,50221,PRETRIAL,BATTLE,FRANK,NULL,Male,African-American,09/10/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,Copy,1,0 +57143,65315,59249,PRETRIAL,COLEMAN,EDWIN,PIERRE,Male,African-American,10/10/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +57143,65315,59249,PRETRIAL,COLEMAN,EDWIN,PIERRE,Male,African-American,10/10/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +57143,65315,59249,PRETRIAL,COLEMAN,EDWIN,PIERRE,Male,African-American,10/10/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,2,Medium,18,Risk of Failure to Appear,40,10,High,New,1,0 +36034,65299,35278,PRETRIAL,Rozier,Demetrius,Levon,Male,African-American,12/31/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,Copy,1,0 +36034,65299,35278,PRETRIAL,Rozier,Demetrius,Levon,Male,African-American,12/31/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,Copy,1,0 +36034,65299,35278,PRETRIAL,Rozier,Demetrius,Levon,Male,African-American,12/31/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +57116,65278,59216,PRETRIAL,SIMMS,ASHANNA,A,Female,African-American,06/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +57116,65278,59216,PRETRIAL,SIMMS,ASHANNA,A,Female,African-American,06/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +57116,65278,59216,PRETRIAL,SIMMS,ASHANNA,A,Female,African-American,06/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57140,65312,59246,Probation,King,Grerory,NULL,Male,Caucasian,10/29/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/10/13 0:00,2,Medium,7,Risk of Violence,-2.64,2,Low,New,1,0 +57140,65312,59246,Probation,King,Grerory,NULL,Male,Caucasian,10/29/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +57140,65312,59246,Probation,King,Grerory,NULL,Male,Caucasian,10/29/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/10/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +32569,65296,59231,Probation,Georgio,John,J,Male,Caucasian,02/01/49,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-4.38,1,Low,New,1,0 +32569,65296,59231,Probation,Georgio,John,J,Male,Caucasian,02/01/49,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-2.6,1,Low,New,1,0 +32569,65296,59231,Probation,Georgio,John,J,Male,Caucasian,02/01/49,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57136,65307,59241,Probation,Valero,Javier,NULL,Male,Hispanic,10/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +57136,65307,59241,Probation,Valero,Javier,NULL,Male,Hispanic,10/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +57136,65307,59241,Probation,Valero,Javier,NULL,Male,Hispanic,10/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +31989,65286,59222,PRETRIAL,Reed,Moeshae,M,Female,African-American,09/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,4,High,7,Risk of Violence,-1.07,8,High,New,1,0 +31989,65286,59222,PRETRIAL,Reed,Moeshae,M,Female,African-American,09/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,4,High,8,Risk of Recidivism,0.21,9,High,New,1,0 +31989,65286,59222,PRETRIAL,Reed,Moeshae,M,Female,African-American,09/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,4,High,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +7602,65285,59221,PRETRIAL,CARTER,JOSE,NULL,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +7602,65285,59221,PRETRIAL,CARTER,JOSE,NULL,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +7602,65285,59221,PRETRIAL,CARTER,JOSE,NULL,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +57131,65297,59232,Probation,smith,Erik,NULL,Female,African-American,09/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,2,Medium,7,Risk of Violence,-2.77,2,Low,New,1,0 +57131,65297,59232,Probation,smith,Erik,NULL,Female,African-American,09/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +57131,65297,59232,Probation,smith,Erik,NULL,Female,African-American,09/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57135,65306,59240,PRETRIAL,Holmes,Kathy,NULL,Female,Caucasian,11/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +57135,65306,59240,PRETRIAL,Holmes,Kathy,NULL,Female,Caucasian,11/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +57135,65306,59240,PRETRIAL,Holmes,Kathy,NULL,Female,Caucasian,11/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57129,65292,59227,Probation,marmolejo,victor,NULL,Male,Hispanic,05/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/10/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +57129,65292,59227,Probation,marmolejo,victor,NULL,Male,Hispanic,05/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/10/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +57129,65292,59227,Probation,marmolejo,victor,NULL,Male,Hispanic,05/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49884,65283,50818,PRETRIAL,Rosario,Eliezer,NULL,Male,Hispanic,05/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,Copy,1,0 +49884,65283,50818,PRETRIAL,Rosario,Eliezer,NULL,Male,Hispanic,05/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,7,Medium,Copy,1,0 +49884,65283,50818,PRETRIAL,Rosario,Eliezer,NULL,Male,Hispanic,05/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +57127,65290,59225,Probation,cruz,srephen,NULL,Male,Hispanic,04/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +57127,65290,59225,Probation,cruz,srephen,NULL,Male,Hispanic,04/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +57127,65290,59225,Probation,cruz,srephen,NULL,Male,Hispanic,04/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57162,65341,59272,PRETRIAL,Denonno,Michael,NULL,Male,Caucasian,05/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +57162,65341,59272,PRETRIAL,Denonno,Michael,NULL,Male,Caucasian,05/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +57162,65341,59272,PRETRIAL,Denonno,Michael,NULL,Male,Caucasian,05/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55700,65348,57580,Probation,Erb,Dylan,NULL,Male,Caucasian,06/09/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,4,High,7,Risk of Violence,-0.85,9,High,New,1,0 +55700,65348,57580,Probation,Erb,Dylan,NULL,Male,Caucasian,06/09/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,4,High,8,Risk of Recidivism,0.7,10,High,New,1,0 +55700,65348,57580,Probation,Erb,Dylan,NULL,Male,Caucasian,06/09/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,4,High,18,Risk of Failure to Appear,19,2,Low,New,1,0 +57171,65355,59284,Probation,Hall,Heather,NULL,Female,Caucasian,03/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +57171,65355,59284,Probation,Hall,Heather,NULL,Female,Caucasian,03/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +57171,65355,59284,Probation,Hall,Heather,NULL,Female,Caucasian,03/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57146,65320,59254,PRETRIAL,Harris,Viccas,Calvert,Male,Other,11/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/11/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +57146,65320,59254,PRETRIAL,Harris,Viccas,Calvert,Male,Other,11/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/11/13 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +57146,65320,59254,PRETRIAL,Harris,Viccas,Calvert,Male,Other,11/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57157,65334,59265,Probation,Daubar,Daniel,NULL,Male,Hispanic,08/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +57157,65334,59265,Probation,Daubar,Daniel,NULL,Male,Hispanic,08/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +57157,65334,59265,Probation,Daubar,Daniel,NULL,Male,Hispanic,08/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57153,65327,59261,Probation,Rivera,Claudette,NULL,Female,Hispanic,08/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +57153,65327,59261,Probation,Rivera,Claudette,NULL,Female,Hispanic,08/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +57153,65327,59261,Probation,Rivera,Claudette,NULL,Female,Hispanic,08/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +57145,65318,59252,PRETRIAL,KEMP,MILES,NULL,Male,African-American,04/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +57145,65318,59252,PRETRIAL,KEMP,MILES,NULL,Male,African-American,04/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +57145,65318,59252,PRETRIAL,KEMP,MILES,NULL,Male,African-American,04/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +45074,65353,59282,PRETRIAL,Taylor,Morgan,leigh,Female,Caucasian,03/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +45074,65353,59282,PRETRIAL,Taylor,Morgan,leigh,Female,Caucasian,03/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +45074,65353,59282,PRETRIAL,Taylor,Morgan,leigh,Female,Caucasian,03/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +57160,65339,59270,PRETRIAL,Reid-Cooks,Kerri,NULL,Female,African-American,07/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/11/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +57160,65339,59270,PRETRIAL,Reid-Cooks,Kerri,NULL,Female,African-American,07/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/11/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +57160,65339,59270,PRETRIAL,Reid-Cooks,Kerri,NULL,Female,African-American,07/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57172,65357,59285,PRETRIAL,FERNANDEZ,TRISTAN,NULL,Male,Caucasian,08/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +57172,65357,59285,PRETRIAL,FERNANDEZ,TRISTAN,NULL,Male,Caucasian,08/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +57172,65357,59285,PRETRIAL,FERNANDEZ,TRISTAN,NULL,Male,Caucasian,08/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +8489,65317,59251,PRETRIAL,McClemore,Yarvis,NULL,Male,African-American,01/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,4,High,7,Risk of Violence,0.09,10,High,New,1,0 +8489,65317,59251,PRETRIAL,McClemore,Yarvis,NULL,Male,African-American,01/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,4,High,8,Risk of Recidivism,1.14,10,High,New,1,0 +8489,65317,59251,PRETRIAL,McClemore,Yarvis,NULL,Male,African-American,01/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57170,65354,59283,Probation,Joel,Siegrist,NULL,Male,Caucasian,07/25/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +57170,65354,59283,Probation,Joel,Siegrist,NULL,Male,Caucasian,07/25/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +57170,65354,59283,Probation,Joel,Siegrist,NULL,Male,Caucasian,07/25/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57166,65346,59276,Probation,Bray,Tyler,NULL,Male,Caucasian,05/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +57166,65346,59276,Probation,Bray,Tyler,NULL,Male,Caucasian,05/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +57166,65346,59276,Probation,Bray,Tyler,NULL,Male,Caucasian,05/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57151,65325,59259,PRETRIAL,Wright,Bryon,QJ,Male,African-American,02/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,New,1,0 +57151,65325,59259,PRETRIAL,Wright,Bryon,QJ,Male,African-American,02/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +57151,65325,59259,PRETRIAL,Wright,Bryon,QJ,Male,African-American,02/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57156,65333,59264,Probation,Walker,Jazzlin,NULL,Female,African-American,12/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +57156,65333,59264,Probation,Walker,Jazzlin,NULL,Female,African-American,12/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +57156,65333,59264,Probation,Walker,Jazzlin,NULL,Female,African-American,12/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57161,65338,59269,Probation,Gray,Robert,NULL,Male,Caucasian,07/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/11/13 0:00,2,Medium,7,Risk of Violence,-2.72,2,Low,New,1,0 +57161,65338,59269,Probation,Gray,Robert,NULL,Male,Caucasian,07/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +57161,65338,59269,Probation,Gray,Robert,NULL,Male,Caucasian,07/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/11/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57148,65322,59256,PRETRIAL,LAMORE,JON,CARLO,Male,Caucasian,03/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.11,8,High,New,1,0 +57148,65322,59256,PRETRIAL,LAMORE,JON,CARLO,Male,Caucasian,03/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +57148,65322,59256,PRETRIAL,LAMORE,JON,CARLO,Male,Caucasian,03/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +57163,65343,59273,PRETRIAL,PIERRE-LOUIS,JACK,NULL,Male,Other,01/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/11/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +57163,65343,59273,PRETRIAL,PIERRE-LOUIS,JACK,NULL,Male,Other,01/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/11/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +57163,65343,59273,PRETRIAL,PIERRE-LOUIS,JACK,NULL,Male,Other,01/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57149,65323,59257,PRETRIAL,CRUZ,MIGUEL,NULL,Female,Caucasian,12/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +57149,65323,59257,PRETRIAL,CRUZ,MIGUEL,NULL,Female,Caucasian,12/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +57149,65323,59257,PRETRIAL,CRUZ,MIGUEL,NULL,Female,Caucasian,12/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +57155,65330,59263,PRETRIAL,Yate,Richard,NULL,Male,Hispanic,06/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +57155,65330,59263,PRETRIAL,Yate,Richard,NULL,Male,Hispanic,06/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +57155,65330,59263,PRETRIAL,Yate,Richard,NULL,Male,Hispanic,06/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +6719,65351,59280,PRETRIAL,ORTIZ,TRAVEON,SARENT,Male,African-American,01/09/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,New,1,0 +6719,65351,59280,PRETRIAL,ORTIZ,TRAVEON,SARENT,Male,African-American,01/09/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.31,5,Medium,New,1,0 +6719,65351,59280,PRETRIAL,ORTIZ,TRAVEON,SARENT,Male,African-American,01/09/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +58028,66387,60209,Probation,MCMILLIAN,larhonda,NULL,Female,African-American,10/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +58028,66387,60209,Probation,MCMILLIAN,larhonda,NULL,Female,African-American,10/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +58028,66387,60209,Probation,MCMILLIAN,larhonda,NULL,Female,African-American,10/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +3818,65319,59253,PRETRIAL,SINGLETARY,DEVONN,R,Male,African-American,08/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +3818,65319,59253,PRETRIAL,SINGLETARY,DEVONN,R,Male,African-American,08/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +3818,65319,59253,PRETRIAL,SINGLETARY,DEVONN,R,Male,African-American,08/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57152,65326,59260,PRETRIAL,BALBI,BRUNO,NULL,Male,Hispanic,12/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +57152,65326,59260,PRETRIAL,BALBI,BRUNO,NULL,Male,Hispanic,12/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +57152,65326,59260,PRETRIAL,BALBI,BRUNO,NULL,Male,Hispanic,12/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57013,65328,59100,PRETRIAL,KIFFIN,ANTHONY,NULL,Male,African-American,09/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,Copy,1,0 +57013,65328,59100,PRETRIAL,KIFFIN,ANTHONY,NULL,Male,African-American,09/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,Copy,1,0 +57013,65328,59100,PRETRIAL,KIFFIN,ANTHONY,NULL,Male,African-American,09/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +57167,65347,59277,Probation,Lucas,Lester,NULL,Male,African-American,12/25/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +57167,65347,59277,Probation,Lucas,Lester,NULL,Male,African-American,12/25/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +57167,65347,59277,Probation,Lucas,Lester,NULL,Male,African-American,12/25/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57168,65349,59278,Probation,Borghese,Ralph,NULL,Male,Caucasian,10/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +57168,65349,59278,Probation,Borghese,Ralph,NULL,Male,Caucasian,10/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +57168,65349,59278,Probation,Borghese,Ralph,NULL,Male,Caucasian,10/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +6999,65356,50790,PRETRIAL,STROMAN,IRA,C,Male,African-American,10/28/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +6999,65356,50790,PRETRIAL,STROMAN,IRA,C,Male,African-American,10/28/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-0.63,3,Low,New,1,0 +6999,65356,50790,PRETRIAL,STROMAN,IRA,C,Male,African-American,10/28/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,23,4,Low,New,1,0 +57164,65344,59274,PRETRIAL,MACKEY,GERALD,NULL,Female,African-American,04/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +57164,65344,59274,PRETRIAL,MACKEY,GERALD,NULL,Female,African-American,04/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +57164,65344,59274,PRETRIAL,MACKEY,GERALD,NULL,Female,African-American,04/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56630,65331,58651,PRETRIAL,Bohl,Matthew,NULL,Male,Caucasian,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,Copy,1,0 +56630,65331,58651,PRETRIAL,Bohl,Matthew,NULL,Male,Caucasian,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,Copy,1,0 +56630,65331,58651,PRETRIAL,Bohl,Matthew,NULL,Male,Caucasian,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +38809,65340,59271,PRETRIAL,SEVERINO,MARCELO,NULL,Male,African-American,03/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +38809,65340,59271,PRETRIAL,SEVERINO,MARCELO,NULL,Male,African-American,03/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +38809,65340,59271,PRETRIAL,SEVERINO,MARCELO,NULL,Male,African-American,03/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +36834,39485,36137,PRETRIAL,Dieudonne,Gerald,NULL,Male,African-American,02/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +36834,39485,36137,PRETRIAL,Dieudonne,Gerald,NULL,Male,African-American,02/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +36834,39485,36137,PRETRIAL,Dieudonne,Gerald,NULL,Male,African-American,02/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57147,65321,59255,PRETRIAL,Wilson,Steven,Bernard,Male,African-American,06/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +57147,65321,59255,PRETRIAL,Wilson,Steven,Bernard,Male,African-American,06/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +57147,65321,59255,PRETRIAL,Wilson,Steven,Bernard,Male,African-American,06/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57169,65350,59279,Probation,feliz,uritzky,NULL,Male,Hispanic,12/03/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/11/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +57169,65350,59279,Probation,feliz,uritzky,NULL,Male,Hispanic,12/03/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/11/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +57169,65350,59279,Probation,feliz,uritzky,NULL,Male,Hispanic,12/03/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57154,65329,59262,PRETRIAL,Hopkins,Kim,NULL,Female,African-American,05/04/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +57154,65329,59262,PRETRIAL,Hopkins,Kim,NULL,Female,African-American,05/04/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +57154,65329,59262,PRETRIAL,Hopkins,Kim,NULL,Female,African-American,05/04/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +36834,65342,36137,PRETRIAL,Dieudonne,Gerald,NULL,Male,African-American,02/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,Copy,1,0 +36834,65342,36137,PRETRIAL,Dieudonne,Gerald,NULL,Male,African-American,02/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,Copy,1,0 +36834,65342,36137,PRETRIAL,Dieudonne,Gerald,NULL,Male,African-American,02/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +20006,65352,59281,Probation,scarr,jill,NULL,Female,Caucasian,09/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/11/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +20006,65352,59281,Probation,scarr,jill,NULL,Female,Caucasian,09/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/11/13 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +20006,65352,59281,Probation,scarr,jill,NULL,Female,Caucasian,09/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57144,65316,59250,PRETRIAL,MOSLEY,EDDIE,SEBASTIAN,Male,African-American,08/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,4,High,7,Risk of Violence,-0.5,10,High,New,1,0 +57144,65316,59250,PRETRIAL,MOSLEY,EDDIE,SEBASTIAN,Male,African-American,08/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,4,High,8,Risk of Recidivism,0.66,10,High,New,1,0 +57144,65316,59250,PRETRIAL,MOSLEY,EDDIE,SEBASTIAN,Male,African-American,08/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57150,65324,59258,PRETRIAL,WILLIAMS,DORJAN,NULL,Male,African-American,12/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +57150,65324,59258,PRETRIAL,WILLIAMS,DORJAN,NULL,Male,African-American,12/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +57150,65324,59258,PRETRIAL,WILLIAMS,DORJAN,NULL,Male,African-American,12/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57173,65358,59286,PRETRIAL,Xiomara,Rivera,Isabelle,Female,Hispanic,12/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +57173,65358,59286,PRETRIAL,Xiomara,Rivera,Isabelle,Female,Hispanic,12/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +57173,65358,59286,PRETRIAL,Xiomara,Rivera,Isabelle,Female,Hispanic,12/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57165,65345,59275,PRETRIAL,PIERRE,KHENJA,NULL,Female,African-American,10/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +57165,65345,59275,PRETRIAL,PIERRE,KHENJA,NULL,Female,African-American,10/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +57165,65345,59275,PRETRIAL,PIERRE,KHENJA,NULL,Female,African-American,10/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57174,65360,59288,PRETRIAL,ANDREWS,JASON,ALLEN,Male,Caucasian,11/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +57174,65360,59288,PRETRIAL,ANDREWS,JASON,ALLEN,Male,Caucasian,11/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +57174,65360,59288,PRETRIAL,ANDREWS,JASON,ALLEN,Male,Caucasian,11/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57202,65379,59307,PRETRIAL,DURRANT,AL,NULL,Male,African-American,10/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +57202,65379,59307,PRETRIAL,DURRANT,AL,NULL,Male,African-American,10/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +57202,65379,59307,PRETRIAL,DURRANT,AL,NULL,Male,African-American,10/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57227,65394,59322,PRETRIAL,OEFELEIN,SCOTT,NULL,Male,Caucasian,10/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +57227,65394,59322,PRETRIAL,OEFELEIN,SCOTT,NULL,Male,Caucasian,10/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +57227,65394,59322,PRETRIAL,OEFELEIN,SCOTT,NULL,Male,Caucasian,10/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57204,65381,59309,Probation,STEWARD,BRUCE,ALLEN,Male,Caucasian,11/12/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/12/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +57204,65381,59309,Probation,STEWARD,BRUCE,ALLEN,Male,Caucasian,11/12/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +57204,65381,59309,Probation,STEWARD,BRUCE,ALLEN,Male,Caucasian,11/12/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57189,65366,59294,PRETRIAL,Agapay,Christopher,NULL,Male,Caucasian,10/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +57189,65366,59294,PRETRIAL,Agapay,Christopher,NULL,Male,Caucasian,10/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +57189,65366,59294,PRETRIAL,Agapay,Christopher,NULL,Male,Caucasian,10/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57195,65373,59301,PRETRIAL,HUNTER,MICHELLE,NULL,Female,Caucasian,08/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +57195,65373,59301,PRETRIAL,HUNTER,MICHELLE,NULL,Female,Caucasian,08/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +57195,65373,59301,PRETRIAL,HUNTER,MICHELLE,NULL,Female,Caucasian,08/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57211,65387,59315,PRETRIAL,Scott,James,NULL,Male,African-American,09/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.14,8,High,New,1,0 +57211,65387,59315,PRETRIAL,Scott,James,NULL,Male,African-American,09/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +57211,65387,59315,PRETRIAL,Scott,James,NULL,Male,African-American,09/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +57199,65376,59304,Probation,mcford,brian,NULL,Male,Caucasian,06/15/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/12/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +57199,65376,59304,Probation,mcford,brian,NULL,Male,Caucasian,06/15/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +57199,65376,59304,Probation,mcford,brian,NULL,Male,Caucasian,06/15/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57186,65363,59291,PRETRIAL,Lanier,Shantrill,R,Male,African-American,10/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,New,1,0 +57186,65363,59291,PRETRIAL,Lanier,Shantrill,R,Male,African-American,10/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +57186,65363,59291,PRETRIAL,Lanier,Shantrill,R,Male,African-American,10/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57229,65397,59325,PRETRIAL,Nesbitt,Ruthie,NULL,Female,African-American,09/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +57229,65397,59325,PRETRIAL,Nesbitt,Ruthie,NULL,Female,African-American,09/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +57229,65397,59325,PRETRIAL,Nesbitt,Ruthie,NULL,Female,African-American,09/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57191,65368,59296,PRETRIAL,Burnett,Ponda,NULL,Male,African-American,12/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +57191,65368,59296,PRETRIAL,Burnett,Ponda,NULL,Male,African-American,12/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +57191,65368,59296,PRETRIAL,Burnett,Ponda,NULL,Male,African-American,12/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57194,65371,59299,PRETRIAL,Munoz,Matt,Steve,Male,Caucasian,03/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +57194,65371,59299,PRETRIAL,Munoz,Matt,Steve,Male,Caucasian,03/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +57194,65371,59299,PRETRIAL,Munoz,Matt,Steve,Male,Caucasian,03/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30878,65389,59317,PRETRIAL,LOGAN,BELAL,NULL,Male,Other,09/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +30878,65389,59317,PRETRIAL,LOGAN,BELAL,NULL,Male,Other,09/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +30878,65389,59317,PRETRIAL,LOGAN,BELAL,NULL,Male,Other,09/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +41684,65382,59310,PRETRIAL,CABREJA,JOEL,A,Male,Hispanic,04/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +41684,65382,59310,PRETRIAL,CABREJA,JOEL,A,Male,Hispanic,04/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +41684,65382,59310,PRETRIAL,CABREJA,JOEL,A,Male,Hispanic,04/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57228,65396,59324,Probation,Proenzamartinez,Michel,NULL,Male,Hispanic,09/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +57228,65396,59324,Probation,Proenzamartinez,Michel,NULL,Male,Hispanic,09/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +57228,65396,59324,Probation,Proenzamartinez,Michel,NULL,Male,Hispanic,09/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57210,65386,59314,Probation,lauria,marc,NULL,Male,Caucasian,07/25/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +57210,65386,59314,Probation,lauria,marc,NULL,Male,Caucasian,07/25/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +57210,65386,59314,Probation,lauria,marc,NULL,Male,Caucasian,07/25/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57188,65365,59293,PRETRIAL,Telon,Lafrance,NULL,Male,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +57188,65365,59293,PRETRIAL,Telon,Lafrance,NULL,Male,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.74,10,High,New,1,0 +57188,65365,59293,PRETRIAL,Telon,Lafrance,NULL,Male,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57182,65361,59289,PRETRIAL,suarez,derek,NULL,Male,Caucasian,03/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +57182,65361,59289,PRETRIAL,suarez,derek,NULL,Male,Caucasian,03/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +57182,65361,59289,PRETRIAL,suarez,derek,NULL,Male,Caucasian,03/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57198,65375,59303,PRETRIAL,Cerra,Patricia,NULL,Female,Caucasian,03/07/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +57198,65375,59303,PRETRIAL,Cerra,Patricia,NULL,Female,Caucasian,03/07/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +57198,65375,59303,PRETRIAL,Cerra,Patricia,NULL,Female,Caucasian,03/07/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57200,65377,59305,PRETRIAL,Nichols,Becky,NULL,Female,Caucasian,12/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +57200,65377,59305,PRETRIAL,Nichols,Becky,NULL,Female,Caucasian,12/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +57200,65377,59305,PRETRIAL,Nichols,Becky,NULL,Female,Caucasian,12/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57193,65370,59298,PRETRIAL,Vanburen,Christopher,NULL,Male,Caucasian,09/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +57193,65370,59298,PRETRIAL,Vanburen,Christopher,NULL,Male,Caucasian,09/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +57193,65370,59298,PRETRIAL,Vanburen,Christopher,NULL,Male,Caucasian,09/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57208,65384,59312,Probation,VELARDI,LESLIEANN,NULL,Female,Caucasian,06/21/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/12/13 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +57208,65384,59312,Probation,VELARDI,LESLIEANN,NULL,Female,Caucasian,06/21/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/12/13 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +57208,65384,59312,Probation,VELARDI,LESLIEANN,NULL,Female,Caucasian,06/21/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57215,65391,59319,Probation,hoepker,jessica,NULL,Female,Caucasian,04/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +57215,65391,59319,Probation,hoepker,jessica,NULL,Female,Caucasian,04/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +57215,65391,59319,Probation,hoepker,jessica,NULL,Female,Caucasian,04/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57230,65398,59326,Probation,rivero,eliodoro,NULL,Male,Hispanic,12/08/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/12/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +57230,65398,59326,Probation,rivero,eliodoro,NULL,Male,Hispanic,12/08/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +57230,65398,59326,Probation,rivero,eliodoro,NULL,Male,Hispanic,12/08/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57203,65380,59308,Probation,mota,paulo,NULL,Male,Other,04/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +57203,65380,59308,Probation,mota,paulo,NULL,Male,Other,04/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +57203,65380,59308,Probation,mota,paulo,NULL,Male,Other,04/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57213,65388,59316,Probation,FASSI,ISABEL,NULL,Female,Hispanic,12/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +57213,65388,59316,Probation,FASSI,ISABEL,NULL,Female,Hispanic,12/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +57213,65388,59316,Probation,FASSI,ISABEL,NULL,Female,Hispanic,12/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +33855,65372,59300,PRETRIAL,Maccall,Patricia,NULL,Female,African-American,04/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +33855,65372,59300,PRETRIAL,Maccall,Patricia,NULL,Female,African-American,04/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +33855,65372,59300,PRETRIAL,Maccall,Patricia,NULL,Female,African-American,04/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +13268,65359,59287,PRETRIAL,Laravalasquez,Dennis,Alberto,Male,Caucasian,05/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +13268,65359,59287,PRETRIAL,Laravalasquez,Dennis,Alberto,Male,Caucasian,05/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +13268,65359,59287,PRETRIAL,Laravalasquez,Dennis,Alberto,Male,Caucasian,05/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57226,65393,59321,Probation,Montalvan,Oscar,NULL,Male,Hispanic,06/29/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/12/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +57226,65393,59321,Probation,Montalvan,Oscar,NULL,Male,Hispanic,06/29/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +57226,65393,59321,Probation,Montalvan,Oscar,NULL,Male,Hispanic,06/29/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57187,65364,59292,PRETRIAL,Harnarrine,Tulsiram,NULL,Male,Asian,05/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +57187,65364,59292,PRETRIAL,Harnarrine,Tulsiram,NULL,Male,Asian,05/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +57187,65364,59292,PRETRIAL,Harnarrine,Tulsiram,NULL,Male,Asian,05/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57190,65367,59295,PRETRIAL,GOMEZ,LEON,NULL,Male,Caucasian,09/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +57190,65367,59295,PRETRIAL,GOMEZ,LEON,NULL,Male,Caucasian,09/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +57190,65367,59295,PRETRIAL,GOMEZ,LEON,NULL,Male,Caucasian,09/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57209,65385,59313,Probation,Falzarro,Laura,NULL,Female,Caucasian,01/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +57209,65385,59313,Probation,Falzarro,Laura,NULL,Female,Caucasian,01/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +57209,65385,59313,Probation,Falzarro,Laura,NULL,Female,Caucasian,01/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57201,65378,59306,Probation,Schneider,Walter,NULL,Male,Caucasian,09/05/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +57201,65378,59306,Probation,Schneider,Walter,NULL,Male,Caucasian,09/05/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +57201,65378,59306,Probation,Schneider,Walter,NULL,Male,Caucasian,09/05/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +17560,65395,59323,Probation,Hall,Antuan,NULL,Male,African-American,03/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.99,4,Low,New,1,0 +17560,65395,59323,Probation,Hall,Antuan,NULL,Male,African-American,03/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +17560,65395,59323,Probation,Hall,Antuan,NULL,Male,African-American,03/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57197,65374,59302,Probation,barrios,edward,NULL,Male,Hispanic,11/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +57197,65374,59302,Probation,barrios,edward,NULL,Male,Hispanic,11/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +57197,65374,59302,Probation,barrios,edward,NULL,Male,Hispanic,11/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57192,65369,59297,PRETRIAL,Arabitg,Adrian,NULL,Male,Caucasian,07/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +57192,65369,59297,PRETRIAL,Arabitg,Adrian,NULL,Male,Caucasian,07/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +57192,65369,59297,PRETRIAL,Arabitg,Adrian,NULL,Male,Caucasian,07/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57205,65383,59311,Probation,saraceno-taglione,john,NULL,Male,Caucasian,11/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +57205,65383,59311,Probation,saraceno-taglione,john,NULL,Male,Caucasian,11/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +57205,65383,59311,Probation,saraceno-taglione,john,NULL,Male,Caucasian,11/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57214,65390,59318,Probation,roberts,antoinette,NULL,Female,African-American,01/23/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.95,1,Low,New,1,0 +57214,65390,59318,Probation,roberts,antoinette,NULL,Female,African-American,01/23/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,8,High,New,1,0 +57214,65390,59318,Probation,roberts,antoinette,NULL,Female,African-American,01/23/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57185,65362,59290,PRETRIAL,PRIGEON,TERMELL,NULL,Male,African-American,08/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +57185,65362,59290,PRETRIAL,PRIGEON,TERMELL,NULL,Male,African-American,08/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +57185,65362,59290,PRETRIAL,PRIGEON,TERMELL,NULL,Male,African-American,08/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57216,65392,59320,Probation,ARMOOGAN,JOANN,R,Female,Asian,02/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +57216,65392,59320,Probation,ARMOOGAN,JOANN,R,Female,Asian,02/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +57216,65392,59320,Probation,ARMOOGAN,JOANN,R,Female,Asian,02/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57246,65411,59338,Probation,Mundy,Howard,NULL,Male,African-American,04/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +57246,65411,59338,Probation,Mundy,Howard,NULL,Male,African-American,04/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +57246,65411,59338,Probation,Mundy,Howard,NULL,Male,African-American,04/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +57254,65420,59347,PRETRIAL,ORTIZ,JULIAN,EDUARDO,Male,Other,04/18/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/13/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +57254,65420,59347,PRETRIAL,ORTIZ,JULIAN,EDUARDO,Male,Other,04/18/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/13/13 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +57254,65420,59347,PRETRIAL,ORTIZ,JULIAN,EDUARDO,Male,Other,04/18/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57265,65434,59361,Probation,KRUPIT,DOUGLAS,PAUL,Male,Caucasian,03/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/13/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +57265,65434,59361,Probation,KRUPIT,DOUGLAS,PAUL,Male,Caucasian,03/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/13/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +57265,65434,59361,Probation,KRUPIT,DOUGLAS,PAUL,Male,Caucasian,03/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57231,65399,59327,PRETRIAL,Denney,Marcie,NULL,Female,Caucasian,10/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/13/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +57231,65399,59327,PRETRIAL,Denney,Marcie,NULL,Female,Caucasian,10/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,7,Medium,New,1,0 +57231,65399,59327,PRETRIAL,Denney,Marcie,NULL,Female,Caucasian,10/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/13/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53047,65408,54464,Probation,Rogers,Charles,NULL,Male,Caucasian,12/13/54,17,All Scales,Intake,English,Post Sentence,Probation,Separated,9/13/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +53047,65408,54464,Probation,Rogers,Charles,NULL,Male,Caucasian,12/13/54,17,All Scales,Intake,English,Post Sentence,Probation,Separated,9/13/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +53047,65408,54464,Probation,Rogers,Charles,NULL,Male,Caucasian,12/13/54,17,All Scales,Intake,English,Post Sentence,Probation,Separated,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,23,4,Low,New,1,0 +57261,65429,59356,Probation,jules,charles,NULL,Male,African-American,10/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/13/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +57261,65429,59356,Probation,jules,charles,NULL,Male,African-American,10/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/13/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +57261,65429,59356,Probation,jules,charles,NULL,Male,African-American,10/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50846,65425,59352,PRETRIAL,WILLIAMS,TETHINE,AMIR,Male,African-American,10/26/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +50846,65425,59352,PRETRIAL,WILLIAMS,TETHINE,AMIR,Male,African-American,10/26/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +50846,65425,59352,PRETRIAL,WILLIAMS,TETHINE,AMIR,Male,African-American,10/26/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57242,65404,59332,PRETRIAL,Curry,Dewayne,NULL,Male,African-American,02/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +57242,65404,59332,PRETRIAL,Curry,Dewayne,NULL,Male,African-American,02/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.9,10,High,New,1,0 +57242,65404,59332,PRETRIAL,Curry,Dewayne,NULL,Male,African-American,02/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57266,65435,59362,Probation,Cazzaniga,Karen,NULL,Female,Caucasian,06/01/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +57266,65435,59362,Probation,Cazzaniga,Karen,NULL,Female,Caucasian,06/01/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +57266,65435,59362,Probation,Cazzaniga,Karen,NULL,Female,Caucasian,06/01/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57264,65432,59359,DRRD,Sanchez,Sebastian,None,Male,Hispanic,03/07/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +57264,65432,59359,DRRD,Sanchez,Sebastian,None,Male,Hispanic,03/07/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-0.7,3,Low,New,1,0 +57264,65432,59359,DRRD,Sanchez,Sebastian,None,Male,Hispanic,03/07/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +15866,65427,59354,Probation,robbins,david,NULL,Male,Hispanic,04/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +15866,65427,59354,Probation,robbins,david,NULL,Male,Hispanic,04/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +15866,65427,59354,Probation,robbins,david,NULL,Male,Hispanic,04/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57244,65406,59334,PRETRIAL,Johnson,Kurveen,NULL,Male,African-American,06/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/13/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +57244,65406,59334,PRETRIAL,Johnson,Kurveen,NULL,Male,African-American,06/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/13/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +57244,65406,59334,PRETRIAL,Johnson,Kurveen,NULL,Male,African-American,06/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57256,65422,59349,PRETRIAL,MCKINLEY,SHAUN,E,Male,African-American,02/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.78,9,High,New,1,0 +57256,65422,59349,PRETRIAL,MCKINLEY,SHAUN,E,Male,African-American,02/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +57256,65422,59349,PRETRIAL,MCKINLEY,SHAUN,E,Male,African-American,02/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +57258,65424,59351,PRETRIAL,Blackwood,Britton,NULL,Male,African-American,05/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,4,High,7,Risk of Violence,-0.52,10,High,New,1,0 +57258,65424,59351,PRETRIAL,Blackwood,Britton,NULL,Male,African-American,05/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,4,High,8,Risk of Recidivism,1.07,10,High,New,1,0 +57258,65424,59351,PRETRIAL,Blackwood,Britton,NULL,Male,African-American,05/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57245,65409,59336,PRETRIAL,WIEDERIN,STACEY,NULL,Female,Caucasian,04/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +57245,65409,59336,PRETRIAL,WIEDERIN,STACEY,NULL,Female,Caucasian,04/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +57245,65409,59336,PRETRIAL,WIEDERIN,STACEY,NULL,Female,Caucasian,04/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57262,65430,59357,Probation,Amelio,James,NULL,Male,Caucasian,06/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +57262,65430,59357,Probation,Amelio,James,NULL,Male,Caucasian,06/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +57262,65430,59357,Probation,Amelio,James,NULL,Male,Caucasian,06/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57233,65401,59329,PRETRIAL,Porter,Krystal,NULL,Female,African-American,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +57233,65401,59329,PRETRIAL,Porter,Krystal,NULL,Female,African-American,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +57233,65401,59329,PRETRIAL,Porter,Krystal,NULL,Female,African-American,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57243,65405,59333,PRETRIAL,Robinson,Leon,NULL,Male,African-American,01/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +57243,65405,59333,PRETRIAL,Robinson,Leon,NULL,Male,African-American,01/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.78,10,High,New,1,0 +57243,65405,59333,PRETRIAL,Robinson,Leon,NULL,Male,African-American,01/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57253,65419,59346,PRETRIAL,ali,nadeem,NULL,Male,Asian,09/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +57253,65419,59346,PRETRIAL,ali,nadeem,NULL,Male,Asian,09/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +57253,65419,59346,PRETRIAL,ali,nadeem,NULL,Male,Asian,09/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57247,65412,59339,PRETRIAL,TRAMUN,JERMAINE,NULL,Male,African-American,01/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +57247,65412,59339,PRETRIAL,TRAMUN,JERMAINE,NULL,Male,African-American,01/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +57247,65412,59339,PRETRIAL,TRAMUN,JERMAINE,NULL,Male,African-American,01/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +49557,65433,59360,PRETRIAL,LEWIS,DESMON,DEMETRIUS,Male,African-American,06/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,New,1,0 +49557,65433,59360,PRETRIAL,LEWIS,DESMON,DEMETRIUS,Male,African-American,06/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +49557,65433,59360,PRETRIAL,LEWIS,DESMON,DEMETRIUS,Male,African-American,06/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57241,65403,59331,PRETRIAL,Therlonge,Roody,NULL,Male,African-American,11/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +57241,65403,59331,PRETRIAL,Therlonge,Roody,NULL,Male,African-American,11/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +57241,65403,59331,PRETRIAL,Therlonge,Roody,NULL,Male,African-American,11/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57252,65417,59344,Probation,Miranda,Carlos,NULL,Male,Hispanic,05/14/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +57252,65417,59344,Probation,Miranda,Carlos,NULL,Male,Hispanic,05/14/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +57252,65417,59344,Probation,Miranda,Carlos,NULL,Male,Hispanic,05/14/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57232,65400,59328,PRETRIAL,Rivero,Yahandry,A,Male,Caucasian,03/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,New,1,0 +57232,65400,59328,PRETRIAL,Rivero,Yahandry,A,Male,Caucasian,03/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +57232,65400,59328,PRETRIAL,Rivero,Yahandry,A,Male,Caucasian,03/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +30929,65407,59335,PRETRIAL,Williams,Rickie,NULL,Male,African-American,03/08/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +30929,65407,59335,PRETRIAL,Williams,Rickie,NULL,Male,African-American,03/08/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +30929,65407,59335,PRETRIAL,Williams,Rickie,NULL,Male,African-American,03/08/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +57255,65421,59348,PRETRIAL,Austin,Gloria,NULL,Female,African-American,06/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +57255,65421,59348,PRETRIAL,Austin,Gloria,NULL,Female,African-American,06/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,New,1,0 +57255,65421,59348,PRETRIAL,Austin,Gloria,NULL,Female,African-American,06/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +19364,65418,59345,PRETRIAL,PINTO,ARTURO,NULL,Male,Hispanic,10/21/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/13/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +19364,65418,59345,PRETRIAL,PINTO,ARTURO,NULL,Male,Hispanic,10/21/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/13/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +19364,65418,59345,PRETRIAL,PINTO,ARTURO,NULL,Male,Hispanic,10/21/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57267,65436,59363,Probation,Woodward,Fred,NULL,Male,Caucasian,12/22/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +57267,65436,59363,Probation,Woodward,Fred,NULL,Male,Caucasian,12/22/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.74,10,High,New,1,0 +57267,65436,59363,Probation,Woodward,Fred,NULL,Male,Caucasian,12/22/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +57263,65431,59358,Probation,CIRIGLIANO,TIMOTHY,W,Male,Caucasian,12/14/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +57263,65431,59358,Probation,CIRIGLIANO,TIMOTHY,W,Male,Caucasian,12/14/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +57263,65431,59358,Probation,CIRIGLIANO,TIMOTHY,W,Male,Caucasian,12/14/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57196,65410,59337,PRETRIAL,Laganella,Stephen,NULL,Male,Caucasian,06/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/13/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +57196,65410,59337,PRETRIAL,Laganella,Stephen,NULL,Male,Caucasian,06/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/13/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +57196,65410,59337,PRETRIAL,Laganella,Stephen,NULL,Male,Caucasian,06/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57240,65402,59330,PRETRIAL,Johnson,Miah,NULL,Female,African-American,11/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.19,4,Low,New,1,0 +57240,65402,59330,PRETRIAL,Johnson,Miah,NULL,Female,African-American,11/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,8,High,New,1,0 +57240,65402,59330,PRETRIAL,Johnson,Miah,NULL,Female,African-American,11/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57257,65423,59350,Probation,Watson,Corey,NULL,Male,African-American,06/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +57257,65423,59350,Probation,Watson,Corey,NULL,Male,African-American,06/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +57257,65423,59350,Probation,Watson,Corey,NULL,Male,African-American,06/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57250,65415,59342,Probation,Hinds,Jazmin,NULL,Female,African-American,08/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +57250,65415,59342,Probation,Hinds,Jazmin,NULL,Female,African-American,08/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +57250,65415,59342,Probation,Hinds,Jazmin,NULL,Female,African-American,08/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57273,65444,59369,PRETRIAL,Schnoor,Dougles,NULL,Male,Caucasian,08/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +57273,65444,59369,PRETRIAL,Schnoor,Dougles,NULL,Male,Caucasian,08/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +57273,65444,59369,PRETRIAL,Schnoor,Dougles,NULL,Male,Caucasian,08/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57270,65439,59366,PRETRIAL,Afonso,Josalina,NULL,Female,African-American,05/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +57270,65439,59366,PRETRIAL,Afonso,Josalina,NULL,Female,African-American,05/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +57270,65439,59366,PRETRIAL,Afonso,Josalina,NULL,Female,African-American,05/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57269,65438,59365,PRETRIAL,Goodroad,Korbin,NULL,Male,Caucasian,04/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,4,High,7,Risk of Violence,-0.63,9,High,New,1,0 +57269,65438,59365,PRETRIAL,Goodroad,Korbin,NULL,Male,Caucasian,04/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,4,High,8,Risk of Recidivism,0.76,10,High,New,1,0 +57269,65438,59365,PRETRIAL,Goodroad,Korbin,NULL,Male,Caucasian,04/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53910,65442,55434,PRETRIAL,wilson,Brian,NULL,Male,Caucasian,01/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/14/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,Copy,1,0 +53910,65442,55434,PRETRIAL,wilson,Brian,NULL,Male,Caucasian,01/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/14/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,Copy,1,0 +53910,65442,55434,PRETRIAL,wilson,Brian,NULL,Male,Caucasian,01/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +57276,65447,59372,PRETRIAL,Phillip,Jamaal,Sterlin,Male,African-American,12/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,2,Medium,7,Risk of Violence,-2.73,2,Low,New,1,0 +57276,65447,59372,PRETRIAL,Phillip,Jamaal,Sterlin,Male,African-American,12/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +57276,65447,59372,PRETRIAL,Phillip,Jamaal,Sterlin,Male,African-American,12/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57278,65449,59374,PRETRIAL,Uman,Jose,NULL,Male,Caucasian,08/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +57278,65449,59374,PRETRIAL,Uman,Jose,NULL,Male,Caucasian,08/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +57278,65449,59374,PRETRIAL,Uman,Jose,NULL,Male,Caucasian,08/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57268,65437,59364,PRETRIAL,COCUZZA,CHARLES,NULL,Male,Caucasian,05/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.92,9,High,New,1,0 +57268,65437,59364,PRETRIAL,COCUZZA,CHARLES,NULL,Male,Caucasian,05/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +57268,65437,59364,PRETRIAL,COCUZZA,CHARLES,NULL,Male,Caucasian,05/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57272,65443,59368,PRETRIAL,Douse,Jeremiah,NULL,Male,African-American,08/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +57272,65443,59368,PRETRIAL,Douse,Jeremiah,NULL,Male,African-American,08/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +57272,65443,59368,PRETRIAL,Douse,Jeremiah,NULL,Male,African-American,08/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57274,65445,59370,PRETRIAL,Kuse,Ryan,NULL,Male,Caucasian,06/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +57274,65445,59370,PRETRIAL,Kuse,Ryan,NULL,Male,Caucasian,06/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +57274,65445,59370,PRETRIAL,Kuse,Ryan,NULL,Male,Caucasian,06/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57271,65440,59367,PRETRIAL,Whyte,Dane,O,Male,Other,08/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +57271,65440,59367,PRETRIAL,Whyte,Dane,O,Male,Other,08/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +57271,65440,59367,PRETRIAL,Whyte,Dane,O,Male,Other,08/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +14432,65450,13815,Probation,barnes,timothy,NULL,Male,African-American,06/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,9/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.28,3,Low,Copy,1,0 +14432,65450,13815,Probation,barnes,timothy,NULL,Male,African-American,06/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,9/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,Copy,1,0 +14432,65450,13815,Probation,barnes,timothy,NULL,Male,African-American,06/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,9/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +57275,65446,59371,PRETRIAL,Allen,Eldrich,NULL,Male,African-American,12/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.25,3,Low,New,1,0 +57275,65446,59371,PRETRIAL,Allen,Eldrich,NULL,Male,African-American,12/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +57275,65446,59371,PRETRIAL,Allen,Eldrich,NULL,Male,African-American,12/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +1172,65441,862,PRETRIAL,SHELL,DENARD,R,Male,African-American,06/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,Copy,1,0 +1172,65441,862,PRETRIAL,SHELL,DENARD,R,Male,African-American,06/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,Copy,1,0 +1172,65441,862,PRETRIAL,SHELL,DENARD,R,Male,African-American,06/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +57277,65448,59373,PRETRIAL,JoynerJordan,Demeitric,NULL,Male,African-American,12/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +57277,65448,59373,PRETRIAL,JoynerJordan,Demeitric,NULL,Male,African-American,12/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +57277,65448,59373,PRETRIAL,JoynerJordan,Demeitric,NULL,Male,African-American,12/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57287,65455,59378,PRETRIAL,Stark,Ronelson,NULL,Male,Other,10/04/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +57287,65455,59378,PRETRIAL,Stark,Ronelson,NULL,Male,Other,10/04/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +57287,65455,59378,PRETRIAL,Stark,Ronelson,NULL,Male,Other,10/04/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57293,65462,59384,PRETRIAL,Stott,Jerry,R,Male,Caucasian,10/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/15/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +57293,65462,59384,PRETRIAL,Stott,Jerry,R,Male,Caucasian,10/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/15/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +57293,65462,59384,PRETRIAL,Stott,Jerry,R,Male,Caucasian,10/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57292,65461,59383,PRETRIAL,Metcalf,Christopher,NULL,Male,Caucasian,03/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +57292,65461,59383,PRETRIAL,Metcalf,Christopher,NULL,Male,Caucasian,03/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +57292,65461,59383,PRETRIAL,Metcalf,Christopher,NULL,Male,Caucasian,03/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57290,65458,59381,PRETRIAL,Latimore,Charleton,NULL,Male,African-American,11/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +57290,65458,59381,PRETRIAL,Latimore,Charleton,NULL,Male,African-American,11/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +57290,65458,59381,PRETRIAL,Latimore,Charleton,NULL,Male,African-American,11/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57279,65451,59375,PRETRIAL,Gebar,Jeremy,John,Male,Hispanic,11/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/15/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +57279,65451,59375,PRETRIAL,Gebar,Jeremy,John,Male,Hispanic,11/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/15/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +57279,65451,59375,PRETRIAL,Gebar,Jeremy,John,Male,Hispanic,11/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/15/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57288,65456,59379,PRETRIAL,Lewis,Tereatha,NULL,Male,African-American,02/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +57288,65456,59379,PRETRIAL,Lewis,Tereatha,NULL,Male,African-American,02/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +57288,65456,59379,PRETRIAL,Lewis,Tereatha,NULL,Male,African-American,02/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +37722,65459,37113,PRETRIAL,HARGRETT,ISIAH,NULL,Female,African-American,11/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +37722,65459,37113,PRETRIAL,HARGRETT,ISIAH,NULL,Female,African-American,11/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,Copy,1,0 +37722,65459,37113,PRETRIAL,HARGRETT,ISIAH,NULL,Female,African-American,11/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +57294,65463,59385,PRETRIAL,NUNEZ,BROOKS,LAURENCE,Male,Caucasian,05/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/15/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +57294,65463,59385,PRETRIAL,NUNEZ,BROOKS,LAURENCE,Male,Caucasian,05/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/15/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +57294,65463,59385,PRETRIAL,NUNEZ,BROOKS,LAURENCE,Male,Caucasian,05/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57281,65454,59377,PRETRIAL,KELLINGBECK,VAUGHN,ALBERT,Male,African-American,07/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +57281,65454,59377,PRETRIAL,KELLINGBECK,VAUGHN,ALBERT,Male,African-American,07/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +57281,65454,59377,PRETRIAL,KELLINGBECK,VAUGHN,ALBERT,Male,African-American,07/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57289,65457,59380,PRETRIAL,DALESSANDRO,CHRISTOPHER,PAUL,Male,Caucasian,04/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/15/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +57289,65457,59380,PRETRIAL,DALESSANDRO,CHRISTOPHER,PAUL,Male,Caucasian,04/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/15/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +57289,65457,59380,PRETRIAL,DALESSANDRO,CHRISTOPHER,PAUL,Male,Caucasian,04/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57291,65460,59382,PRETRIAL,Wilkinson,David,NULL,Male,Caucasian,12/12/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +57291,65460,59382,PRETRIAL,Wilkinson,David,NULL,Male,Caucasian,12/12/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +57291,65460,59382,PRETRIAL,Wilkinson,David,NULL,Male,Caucasian,12/12/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57280,65452,59376,PRETRIAL,YERKOVICH,PATRICK,THOMAS,Male,Caucasian,04/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +57280,65452,59376,PRETRIAL,YERKOVICH,PATRICK,THOMAS,Male,Caucasian,04/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +57280,65452,59376,PRETRIAL,YERKOVICH,PATRICK,THOMAS,Male,Caucasian,04/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +57322,65501,59420,Probation,chin,dwayne,NULL,Male,African-American,10/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +57322,65501,59420,Probation,chin,dwayne,NULL,Male,African-American,10/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +57322,65501,59420,Probation,chin,dwayne,NULL,Male,African-American,10/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57323,65502,59421,PRETRIAL,Eaton,Douglas,NULL,Male,Caucasian,05/28/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +57323,65502,59421,PRETRIAL,Eaton,Douglas,NULL,Male,Caucasian,05/28/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +57323,65502,59421,PRETRIAL,Eaton,Douglas,NULL,Male,Caucasian,05/28/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57302,65473,59393,Probation,Cooper,Fatimah,NULL,Female,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,New,1,0 +57302,65473,59393,Probation,Cooper,Fatimah,NULL,Female,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.07,8,High,New,1,0 +57302,65473,59393,Probation,Cooper,Fatimah,NULL,Female,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57308,65480,59400,Probation,Sanchez,Wascar,NULL,Male,Hispanic,08/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +57308,65480,59400,Probation,Sanchez,Wascar,NULL,Male,Hispanic,08/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +57308,65480,59400,Probation,Sanchez,Wascar,NULL,Male,Hispanic,08/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +57316,65494,59413,PRETRIAL,harris,john,NULL,Male,African-American,10/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/16/13 0:00,2,Medium,7,Risk of Violence,-3.06,1,Low,New,1,0 +57316,65494,59413,PRETRIAL,harris,john,NULL,Male,African-American,10/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +57316,65494,59413,PRETRIAL,harris,john,NULL,Male,African-American,10/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/16/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57318,65496,59415,Probation,MARTIN,MILTON,NULL,Male,Hispanic,12/12/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +57318,65496,59415,Probation,MARTIN,MILTON,NULL,Male,Hispanic,12/12/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +57318,65496,59415,Probation,MARTIN,MILTON,NULL,Male,Hispanic,12/12/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57331,65509,59427,Probation,BAKER,LATRISHA,NULL,Female,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +57331,65509,59427,Probation,BAKER,LATRISHA,NULL,Female,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +57331,65509,59427,Probation,BAKER,LATRISHA,NULL,Female,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +57309,65481,59401,Probation,POLLATRONE,DEANNA,RUTH,Female,Caucasian,06/11/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +57309,65481,59401,Probation,POLLATRONE,DEANNA,RUTH,Female,Caucasian,06/11/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +57309,65481,59401,Probation,POLLATRONE,DEANNA,RUTH,Female,Caucasian,06/11/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +39489,65488,59407,Probation,Aiello,John,NULL,Male,Caucasian,08/18/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/13 0:00,2,Medium,7,Risk of Violence,-2.77,2,Low,New,1,0 +39489,65488,59407,Probation,Aiello,John,NULL,Male,Caucasian,08/18/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +39489,65488,59407,Probation,Aiello,John,NULL,Male,Caucasian,08/18/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57330,65507,59425,PRETRIAL,Bouma,Chad,NULL,Male,Caucasian,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +57330,65507,59425,PRETRIAL,Bouma,Chad,NULL,Male,Caucasian,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +57330,65507,59425,PRETRIAL,Bouma,Chad,NULL,Male,Caucasian,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +46711,65486,47151,PRETRIAL,Morsillo,Shannon,NULL,Female,Caucasian,05/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,Copy,1,0 +46711,65486,47151,PRETRIAL,Morsillo,Shannon,NULL,Female,Caucasian,05/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,Copy,1,0 +46711,65486,47151,PRETRIAL,Morsillo,Shannon,NULL,Female,Caucasian,05/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +47650,65504,48223,PRETRIAL,Hawes,Brice,NULL,Male,African-American,09/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/16/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,Copy,1,0 +47650,65504,48223,PRETRIAL,Hawes,Brice,NULL,Male,African-American,09/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,Copy,1,0 +47650,65504,48223,PRETRIAL,Hawes,Brice,NULL,Male,African-American,09/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/16/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +57306,65478,59398,Probation,Badaracco,Jonah,NULL,Male,Caucasian,06/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +57306,65478,59398,Probation,Badaracco,Jonah,NULL,Male,Caucasian,06/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +57306,65478,59398,Probation,Badaracco,Jonah,NULL,Male,Caucasian,06/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57296,65465,59387,PRETRIAL,BOYD,BRYAN,NULL,Male,African-American,11/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +57296,65465,59387,PRETRIAL,BOYD,BRYAN,NULL,Male,African-American,11/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +57296,65465,59387,PRETRIAL,BOYD,BRYAN,NULL,Male,African-American,11/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57321,65499,59418,Probation,Humphrey,Louis,NULL,Male,Caucasian,06/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +57321,65499,59418,Probation,Humphrey,Louis,NULL,Male,Caucasian,06/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +57321,65499,59418,Probation,Humphrey,Louis,NULL,Male,Caucasian,06/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +57299,65468,59390,PRETRIAL,Allen,Jeanne,NULL,Female,Other,05/15/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +57299,65468,59390,PRETRIAL,Allen,Jeanne,NULL,Female,Other,05/15/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +57299,65468,59390,PRETRIAL,Allen,Jeanne,NULL,Female,Other,05/15/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52979,65475,59395,Probation,Perez,Gerardo,NULL,Male,Hispanic,03/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +52979,65475,59395,Probation,Perez,Gerardo,NULL,Male,Hispanic,03/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +52979,65475,59395,Probation,Perez,Gerardo,NULL,Male,Hispanic,03/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57313,65489,59408,Probation,BARTRA,ROSARIO,V,Female,Hispanic,02/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +57313,65489,59408,Probation,BARTRA,ROSARIO,V,Female,Hispanic,02/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +57313,65489,59408,Probation,BARTRA,ROSARIO,V,Female,Hispanic,02/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57315,65493,59412,Probation,Spungin,Charme,NULL,Female,Hispanic,03/27/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +57315,65493,59412,Probation,Spungin,Charme,NULL,Female,Hispanic,03/27/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +57315,65493,59412,Probation,Spungin,Charme,NULL,Female,Hispanic,03/27/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +57332,65510,59428,PRETRIAL,MURDOCK,JOSEPH,NULL,Male,African-American,05/02/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +57332,65510,59428,PRETRIAL,MURDOCK,JOSEPH,NULL,Male,African-American,05/02/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +57332,65510,59428,PRETRIAL,MURDOCK,JOSEPH,NULL,Male,African-American,05/02/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57305,65477,59397,PRETRIAL,Leon,Flaviano,NULL,Male,Hispanic,01/28/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/16/13 0:00,1,Low,7,Risk of Violence,-4.42,1,Low,New,1,0 +57305,65477,59397,PRETRIAL,Leon,Flaviano,NULL,Male,Hispanic,01/28/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/16/13 0:00,1,Low,8,Risk of Recidivism,-2.8,1,Low,New,1,0 +57305,65477,59397,PRETRIAL,Leon,Flaviano,NULL,Male,Hispanic,01/28/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57300,65470,59391,PRETRIAL,Ferguson,Jameka,Omoro,Male,Other,11/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +57300,65470,59391,PRETRIAL,Ferguson,Jameka,Omoro,Male,Other,11/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +57300,65470,59391,PRETRIAL,Ferguson,Jameka,Omoro,Male,Other,11/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57311,65484,59404,PRETRIAL,Posada,Carlos,NULL,Male,Hispanic,05/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/16/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +57311,65484,59404,PRETRIAL,Posada,Carlos,NULL,Male,Hispanic,05/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/16/13 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +57311,65484,59404,PRETRIAL,Posada,Carlos,NULL,Male,Hispanic,05/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +46711,51780,47151,PRETRIAL,Morsillo,Shannon,NULL,Female,Caucasian,05/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +46711,51780,47151,PRETRIAL,Morsillo,Shannon,NULL,Female,Caucasian,05/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +46711,51780,47151,PRETRIAL,Morsillo,Shannon,NULL,Female,Caucasian,05/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +29315,65491,59410,PRETRIAL,Smith,Terry,Daniel,Male,Caucasian,08/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.85,9,High,New,1,0 +29315,65491,59410,PRETRIAL,Smith,Terry,Daniel,Male,Caucasian,08/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +29315,65491,59410,PRETRIAL,Smith,Terry,Daniel,Male,Caucasian,08/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +45984,65498,59417,PRETRIAL,Hernandez,Joseph,NULL,Male,Caucasian,08/22/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +45984,65498,59417,PRETRIAL,Hernandez,Joseph,NULL,Male,Caucasian,08/22/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +45984,65498,59417,PRETRIAL,Hernandez,Joseph,NULL,Male,Caucasian,08/22/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57327,65505,59423,Probation,Sherrill,travis,NULL,Male,African-American,08/31/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,New,1,0 +57327,65505,59423,Probation,Sherrill,travis,NULL,Male,African-American,08/31/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +57327,65505,59423,Probation,Sherrill,travis,NULL,Male,African-American,08/31/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +43610,65602,59507,Probation,Medina,Mario,NULL,Male,Caucasian,09/06/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +43610,65602,59507,Probation,Medina,Mario,NULL,Male,Caucasian,09/06/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +43610,65602,59507,Probation,Medina,Mario,NULL,Male,Caucasian,09/06/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57297,65466,59388,PRETRIAL,HOHLE,CHAD,C,Male,Caucasian,05/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +57297,65466,59388,PRETRIAL,HOHLE,CHAD,C,Male,Caucasian,05/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +57297,65466,59388,PRETRIAL,HOHLE,CHAD,C,Male,Caucasian,05/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57307,65479,59399,Probation,quesada,jacquelyn,NULL,Female,Caucasian,06/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +57307,65479,59399,Probation,quesada,jacquelyn,NULL,Female,Caucasian,06/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +57307,65479,59399,Probation,quesada,jacquelyn,NULL,Female,Caucasian,06/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57317,65495,59414,Probation,SOUCY,LAURENCE,NULL,Female,Caucasian,03/20/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +57317,65495,59414,Probation,SOUCY,LAURENCE,NULL,Female,Caucasian,03/20/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +57317,65495,59414,Probation,SOUCY,LAURENCE,NULL,Female,Caucasian,03/20/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +57303,65474,59394,PRETRIAL,Ramirez-Ramirez,Trinidad,NULL,Male,Hispanic,11/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +57303,65474,59394,PRETRIAL,Ramirez-Ramirez,Trinidad,NULL,Male,Hispanic,11/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +57303,65474,59394,PRETRIAL,Ramirez-Ramirez,Trinidad,NULL,Male,Hispanic,11/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57329,65508,59426,Probation,Lymon,Marquis,NULL,Male,African-American,09/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +57329,65508,59426,Probation,Lymon,Marquis,NULL,Male,African-American,09/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +57329,65508,59426,Probation,Lymon,Marquis,NULL,Male,African-American,09/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57390,65597,59502,Probation,mojica-barbosa,jose,NULL,Male,Hispanic,02/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +57390,65597,59502,Probation,mojica-barbosa,jose,NULL,Male,Hispanic,02/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +57390,65597,59502,Probation,mojica-barbosa,jose,NULL,Male,Hispanic,02/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +33403,65482,59402,PRETRIAL,Bayliss,Joshua,NULL,Male,Caucasian,12/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +33403,65482,59402,PRETRIAL,Bayliss,Joshua,NULL,Male,Caucasian,12/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +33403,65482,59402,PRETRIAL,Bayliss,Joshua,NULL,Male,Caucasian,12/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +48727,65500,59419,PRETRIAL,ROSEN,ROMINA,NULL,Female,Caucasian,05/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +48727,65500,59419,PRETRIAL,ROSEN,ROMINA,NULL,Female,Caucasian,05/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +48727,65500,59419,PRETRIAL,ROSEN,ROMINA,NULL,Female,Caucasian,05/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57314,65492,59411,PRETRIAL,Jackson,Levert,NULL,Male,African-American,07/23/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,2,Medium,7,Risk of Violence,-3.32,1,Low,New,1,0 +57314,65492,59411,PRETRIAL,Jackson,Levert,NULL,Male,African-American,07/23/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +57314,65492,59411,PRETRIAL,Jackson,Levert,NULL,Male,African-American,07/23/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57333,65511,59429,PRETRIAL,JUMPP,LEON,D,Male,African-American,08/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +57333,65511,59429,PRETRIAL,JUMPP,LEON,D,Male,African-American,08/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,4,High,8,Risk of Recidivism,0.7,10,High,New,1,0 +57333,65511,59429,PRETRIAL,JUMPP,LEON,D,Male,African-American,08/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,4,High,18,Risk of Failure to Appear,40,10,High,New,1,0 +54097,65469,55651,PRETRIAL,May,Jason,NULL,Male,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/16/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,Copy,1,0 +54097,65469,55651,PRETRIAL,May,Jason,NULL,Male,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,Copy,1,0 +54097,65469,55651,PRETRIAL,May,Jason,NULL,Male,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +57304,65476,59396,PRETRIAL,turnquest,james,NULL,Male,African-American,09/25/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +57304,65476,59396,PRETRIAL,turnquest,james,NULL,Male,African-American,09/25/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +57304,65476,59396,PRETRIAL,turnquest,james,NULL,Male,African-American,09/25/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +57320,65497,59416,PRETRIAL,Lozano,Cristino,NULL,Male,Hispanic,03/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/16/13 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +57320,65497,59416,PRETRIAL,Lozano,Cristino,NULL,Male,Hispanic,03/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/16/13 0:00,1,Low,8,Risk of Recidivism,-2.95,1,Low,New,1,0 +57320,65497,59416,PRETRIAL,Lozano,Cristino,NULL,Male,Hispanic,03/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57328,65506,59424,Probation,mora,luis,NULL,Male,Hispanic,08/25/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/13 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +57328,65506,59424,Probation,mora,luis,NULL,Male,Hispanic,08/25/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/13 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +57328,65506,59424,Probation,mora,luis,NULL,Male,Hispanic,08/25/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57295,65464,59386,PRETRIAL,Scott,Emanuel,NULL,Male,African-American,01/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +57295,65464,59386,PRETRIAL,Scott,Emanuel,NULL,Male,African-American,01/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +57295,65464,59386,PRETRIAL,Scott,Emanuel,NULL,Male,African-American,01/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57298,65467,59389,PRETRIAL,Alcius,Fred,NULL,Male,Other,04/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +57298,65467,59389,PRETRIAL,Alcius,Fred,NULL,Male,Other,04/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +57298,65467,59389,PRETRIAL,Alcius,Fred,NULL,Male,Other,04/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57301,65471,59392,PRETRIAL,Hernandez,Jesus,NULL,Male,Hispanic,11/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +57301,65471,59392,PRETRIAL,Hernandez,Jesus,NULL,Male,Hispanic,11/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +57301,65471,59392,PRETRIAL,Hernandez,Jesus,NULL,Male,Hispanic,11/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57312,65485,59405,Probation,Crowe,Kane,NULL,Male,Caucasian,12/01/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +57312,65485,59405,Probation,Crowe,Kane,NULL,Male,Caucasian,12/01/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +57312,65485,59405,Probation,Crowe,Kane,NULL,Male,Caucasian,12/01/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +57339,65518,59435,PRETRIAL,Arnold,Deandre,Dwayne,Male,African-American,09/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +57339,65518,59435,PRETRIAL,Arnold,Deandre,Dwayne,Male,African-American,09/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +57339,65518,59435,PRETRIAL,Arnold,Deandre,Dwayne,Male,African-American,09/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57351,65532,59447,Probation,Rodriguez,Julio,NULL,Male,Hispanic,08/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +57351,65532,59447,Probation,Rodriguez,Julio,NULL,Male,Hispanic,08/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +57351,65532,59447,Probation,Rodriguez,Julio,NULL,Male,Hispanic,08/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57354,65539,59453,Probation,Watson,Angela,NULL,Female,Caucasian,03/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +57354,65539,59453,Probation,Watson,Angela,NULL,Female,Caucasian,03/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,New,1,0 +57354,65539,59453,Probation,Watson,Angela,NULL,Female,Caucasian,03/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +11694,65527,58693,PRETRIAL,Kittles,Jackie,Lee,Male,African-American,08/31/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/13 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,Copy,1,0 +11694,65527,58693,PRETRIAL,Kittles,Jackie,Lee,Male,African-American,08/31/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,Copy,1,0 +11694,65527,58693,PRETRIAL,Kittles,Jackie,Lee,Male,African-American,08/31/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +57341,65520,59437,PRETRIAL,Llauro,Lisset,NULL,Female,Caucasian,01/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +57341,65520,59437,PRETRIAL,Llauro,Lisset,NULL,Female,Caucasian,01/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +57341,65520,59437,PRETRIAL,Llauro,Lisset,NULL,Female,Caucasian,01/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57352,65534,59449,Probation,Rijo,Richard,NULL,Male,Caucasian,03/08/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +57352,65534,59449,Probation,Rijo,Richard,NULL,Male,Caucasian,03/08/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +57352,65534,59449,Probation,Rijo,Richard,NULL,Male,Caucasian,03/08/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57356,65541,59455,PRETRIAL,POTTLE,RYAN,NULL,Male,Caucasian,03/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +57356,65541,59455,PRETRIAL,POTTLE,RYAN,NULL,Male,Caucasian,03/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +57356,65541,59455,PRETRIAL,POTTLE,RYAN,NULL,Male,Caucasian,03/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55545,65548,57406,Probation,Williams,Robert,Dean,Male,Caucasian,02/24/64,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +55545,65548,57406,Probation,Williams,Robert,Dean,Male,Caucasian,02/24/64,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-0.44,4,Low,New,1,0 +55545,65548,57406,Probation,Williams,Robert,Dean,Male,Caucasian,02/24/64,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,23,4,Low,New,1,0 +56651,65513,58676,PRETRIAL,Dubois,Elie,NULL,Male,Other,12/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,Copy,1,0 +56651,65513,58676,PRETRIAL,Dubois,Elie,NULL,Male,Other,12/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,Copy,1,0 +56651,65513,58676,PRETRIAL,Dubois,Elie,NULL,Male,Other,12/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +57342,65521,59438,PRETRIAL,Epstein,Aaron,NULL,Male,Caucasian,12/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +57342,65521,59438,PRETRIAL,Epstein,Aaron,NULL,Male,Caucasian,12/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +57342,65521,59438,PRETRIAL,Epstein,Aaron,NULL,Male,Caucasian,12/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57357,65542,59456,Probation,Molly,Patrick,NULL,Male,Caucasian,08/24/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +57357,65542,59456,Probation,Molly,Patrick,NULL,Male,Caucasian,08/24/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +57357,65542,59456,Probation,Molly,Patrick,NULL,Male,Caucasian,08/24/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57347,65529,59444,Probation,Delcarpio,Paolo,NULL,Male,Hispanic,06/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +57347,65529,59444,Probation,Delcarpio,Paolo,NULL,Male,Hispanic,06/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +57347,65529,59444,Probation,Delcarpio,Paolo,NULL,Male,Hispanic,06/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51462,65545,59459,PRETRIAL,Ramsook,Dechand,NULL,Male,Other,08/15/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/17/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +51462,65545,59459,PRETRIAL,Ramsook,Dechand,NULL,Male,Other,08/15/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/17/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +51462,65545,59459,PRETRIAL,Ramsook,Dechand,NULL,Male,Other,08/15/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57345,65524,59441,PRETRIAL,Santiago,Angel,Manuel,Male,African-American,07/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.22,4,Low,New,1,0 +57345,65524,59441,PRETRIAL,Santiago,Angel,Manuel,Male,African-American,07/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +57345,65524,59441,PRETRIAL,Santiago,Angel,Manuel,Male,African-American,07/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57337,65516,59433,PRETRIAL,Dunlop,Marlon,NULL,Male,African-American,10/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +57337,65516,59433,PRETRIAL,Dunlop,Marlon,NULL,Male,African-American,10/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +57337,65516,59433,PRETRIAL,Dunlop,Marlon,NULL,Male,African-American,10/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57353,65537,59451,Probation,adrian,marquita,NULL,Female,Caucasian,02/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +57353,65537,59451,Probation,adrian,marquita,NULL,Female,Caucasian,02/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +57353,65537,59451,Probation,adrian,marquita,NULL,Female,Caucasian,02/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57340,65519,59436,PRETRIAL,PARKER,TRACY,NULL,Male,African-American,11/07/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +57340,65519,59436,PRETRIAL,PARKER,TRACY,NULL,Male,African-American,11/07/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +57340,65519,59436,PRETRIAL,PARKER,TRACY,NULL,Male,African-American,11/07/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +55441,65526,57298,Probation,Brown,Carnell,NULL,Male,African-American,02/07/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,Copy,1,0 +55441,65526,57298,Probation,Brown,Carnell,NULL,Male,African-American,02/07/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,7,Medium,Copy,1,0 +55441,65526,57298,Probation,Brown,Carnell,NULL,Male,African-American,02/07/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +56923,65528,59443,PRETRIAL,Cintron,Melanie,NULL,Female,Caucasian,08/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +56923,65528,59443,PRETRIAL,Cintron,Melanie,NULL,Female,Caucasian,08/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +56923,65528,59443,PRETRIAL,Cintron,Melanie,NULL,Female,Caucasian,08/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57350,65531,59446,Probation,CEASAR,JULIS,NULL,Male,African-American,08/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +57350,65531,59446,Probation,CEASAR,JULIS,NULL,Male,African-American,08/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +57350,65531,59446,Probation,CEASAR,JULIS,NULL,Male,African-American,08/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +8556,65540,59454,PRETRIAL,MONSALVE,JOSE,L,Male,Caucasian,09/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +8556,65540,59454,PRETRIAL,MONSALVE,JOSE,L,Male,Caucasian,09/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +8556,65540,59454,PRETRIAL,MONSALVE,JOSE,L,Male,Caucasian,09/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +57335,65514,59431,PRETRIAL,Drew,Joshua,NULL,Male,Caucasian,04/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +57335,65514,59431,PRETRIAL,Drew,Joshua,NULL,Male,Caucasian,04/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +57335,65514,59431,PRETRIAL,Drew,Joshua,NULL,Male,Caucasian,04/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +29911,65535,59450,Probation,brinkley,mushirley,NULL,Female,African-American,01/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +29911,65535,59450,Probation,brinkley,mushirley,NULL,Female,African-American,01/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +29911,65535,59450,Probation,brinkley,mushirley,NULL,Female,African-American,01/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57349,65533,59448,PRETRIAL,BAPTIST-MURILLO,HAZEL,NULL,Female,Caucasian,02/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +57349,65533,59448,PRETRIAL,BAPTIST-MURILLO,HAZEL,NULL,Female,Caucasian,02/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +57349,65533,59448,PRETRIAL,BAPTIST-MURILLO,HAZEL,NULL,Female,Caucasian,02/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +47977,65538,59452,PRETRIAL,Joseph,Jeff,NULL,Male,African-American,01/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +47977,65538,59452,PRETRIAL,Joseph,Jeff,NULL,Male,African-American,01/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +47977,65538,59452,PRETRIAL,Joseph,Jeff,NULL,Male,African-American,01/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57334,65512,59430,PRETRIAL,GREY,ADRIAN,NULL,Male,African-American,05/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +57334,65512,59430,PRETRIAL,GREY,ADRIAN,NULL,Male,African-American,05/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +57334,65512,59430,PRETRIAL,GREY,ADRIAN,NULL,Male,African-American,05/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57358,65546,59460,Probation,toski,bruce,NULL,Male,Caucasian,01/17/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/17/13 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +57358,65546,59460,Probation,toski,bruce,NULL,Male,Caucasian,01/17/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/17/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +57358,65546,59460,Probation,toski,bruce,NULL,Male,Caucasian,01/17/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57336,65515,59432,PRETRIAL,Colon,Benjamin,NULL,Male,Hispanic,12/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/13 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +57336,65515,59432,PRETRIAL,Colon,Benjamin,NULL,Male,Hispanic,12/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/13 0:00,1,Low,8,Risk of Recidivism,-2.62,1,Low,New,1,0 +57336,65515,59432,PRETRIAL,Colon,Benjamin,NULL,Male,Hispanic,12/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57338,65517,59434,PRETRIAL,ROPERTO,FARIS,NULL,Female,African-American,09/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,New,1,0 +57338,65517,59434,PRETRIAL,ROPERTO,FARIS,NULL,Female,African-American,09/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,8,High,New,1,0 +57338,65517,59434,PRETRIAL,ROPERTO,FARIS,NULL,Female,African-American,09/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57343,65522,59439,PRETRIAL,Blocker,Desmond,Rashard,Male,African-American,11/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +57343,65522,59439,PRETRIAL,Blocker,Desmond,Rashard,Male,African-American,11/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +57343,65522,59439,PRETRIAL,Blocker,Desmond,Rashard,Male,African-American,11/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50660,65543,59457,PRETRIAL,Sharpe,Bernard,NULL,Male,African-American,08/22/94,17,All Scales,Intake,English,Other,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.95,9,High,New,1,0 +50660,65543,59457,PRETRIAL,Sharpe,Bernard,NULL,Male,African-American,08/22/94,17,All Scales,Intake,English,Other,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,7,Medium,New,1,0 +50660,65543,59457,PRETRIAL,Sharpe,Bernard,NULL,Male,African-American,08/22/94,17,All Scales,Intake,English,Other,Probation,Single,9/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,1,Low,New,1,0 +57344,65523,59440,PRETRIAL,RICHARDSON,MACK,CLYDE,Male,African-American,04/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +57344,65523,59440,PRETRIAL,RICHARDSON,MACK,CLYDE,Male,African-American,04/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +57344,65523,59440,PRETRIAL,RICHARDSON,MACK,CLYDE,Male,African-American,04/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +57348,65530,59445,Probation,RYAN,SEAN,PATRICK,Male,Caucasian,12/30/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/17/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +57348,65530,59445,Probation,RYAN,SEAN,PATRICK,Male,Caucasian,12/30/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/17/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +57348,65530,59445,Probation,RYAN,SEAN,PATRICK,Male,Caucasian,12/30/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57378,65580,59489,Probation,Oshea,Brian,NULL,Male,Caucasian,03/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +57378,65580,59489,Probation,Oshea,Brian,NULL,Male,Caucasian,03/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,4,High,8,Risk of Recidivism,0.98,10,High,New,1,0 +57378,65580,59489,Probation,Oshea,Brian,NULL,Male,Caucasian,03/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +57361,65551,59464,PRETRIAL,Traverso,Jerome,NULL,Male,African-American,04/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +57361,65551,59464,PRETRIAL,Traverso,Jerome,NULL,Male,African-American,04/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +57361,65551,59464,PRETRIAL,Traverso,Jerome,NULL,Male,African-American,04/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57364,65559,59471,Probation,Mott,Victor,NULL,Male,African-American,01/21/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.35,3,Low,New,1,0 +57364,65559,59471,Probation,Mott,Victor,NULL,Male,African-American,01/21/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +57364,65559,59471,Probation,Mott,Victor,NULL,Male,African-American,01/21/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57374,65572,59483,Probation,montenegro,oscar,NULL,Male,Hispanic,03/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +57374,65572,59483,Probation,montenegro,oscar,NULL,Male,Hispanic,03/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +57374,65572,59483,Probation,montenegro,oscar,NULL,Male,Hispanic,03/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50975,65554,59466,PRETRIAL,Placil,Kennol,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +50975,65554,59466,PRETRIAL,Placil,Kennol,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +50975,65554,59466,PRETRIAL,Placil,Kennol,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57368,65564,59475,PRETRIAL,CHEATON,DERRICK,NULL,Male,African-American,02/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.22,8,High,New,1,0 +57368,65564,59475,PRETRIAL,CHEATON,DERRICK,NULL,Male,African-American,02/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +57368,65564,59475,PRETRIAL,CHEATON,DERRICK,NULL,Male,African-American,02/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57376,65575,59486,Probation,Pool,Crystal,NULL,Female,Caucasian,01/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +57376,65575,59486,Probation,Pool,Crystal,NULL,Female,Caucasian,01/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +57376,65575,59486,Probation,Pool,Crystal,NULL,Female,Caucasian,01/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57369,65565,59476,Probation,Logue,James,NULL,Male,Caucasian,11/21/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +57369,65565,59476,Probation,Logue,James,NULL,Male,Caucasian,11/21/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +57369,65565,59476,Probation,Logue,James,NULL,Male,Caucasian,11/21/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57159,65561,59267,PRETRIAL,Butler,Tabria,NULL,Female,African-American,06/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.44,3,Low,Copy,1,0 +57159,65561,59267,PRETRIAL,Butler,Tabria,NULL,Female,African-American,06/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,8,High,Copy,1,0 +57159,65561,59267,PRETRIAL,Butler,Tabria,NULL,Female,African-American,06/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +53108,65577,58734,Probation,Newson,Timothy,NULL,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,Copy,1,0 +53108,65577,58734,Probation,Newson,Timothy,NULL,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,Copy,1,0 +53108,65577,58734,Probation,Newson,Timothy,NULL,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +57360,65549,59462,PRETRIAL,WALDMAN,MONTE,CHARLES,Male,Caucasian,06/21/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +57360,65549,59462,PRETRIAL,WALDMAN,MONTE,CHARLES,Male,Caucasian,06/21/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +57360,65549,59462,PRETRIAL,WALDMAN,MONTE,CHARLES,Male,Caucasian,06/21/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +32763,65556,59468,PRETRIAL,kelly,tramail,NULL,Male,African-American,03/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,4,High,7,Risk of Violence,-1.17,8,High,New,1,0 +32763,65556,59468,PRETRIAL,kelly,tramail,NULL,Male,African-American,03/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,4,High,8,Risk of Recidivism,1.01,10,High,New,1,0 +32763,65556,59468,PRETRIAL,kelly,tramail,NULL,Male,African-American,03/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +49178,65570,59481,PRETRIAL,Watson,Qiana,Tahnee,Female,African-American,12/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +49178,65570,59481,PRETRIAL,Watson,Qiana,Tahnee,Female,African-American,12/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +49178,65570,59481,PRETRIAL,Watson,Qiana,Tahnee,Female,African-American,12/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +25709,65584,24879,PRETRIAL,Williams,Adrian,Lavon,Male,African-American,03/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,Copy,1,0 +25709,65584,24879,PRETRIAL,Williams,Adrian,Lavon,Male,African-American,03/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,Copy,1,0 +25709,65584,24879,PRETRIAL,Williams,Adrian,Lavon,Male,African-American,03/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +57362,65552,59465,PRETRIAL,Goldston,Treton,NULL,Male,African-American,10/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +57362,65552,59465,PRETRIAL,Goldston,Treton,NULL,Male,African-American,10/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +57362,65552,59465,PRETRIAL,Goldston,Treton,NULL,Male,African-American,10/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57370,65566,59477,PRETRIAL,durmeus,daniel,NULL,Male,African-American,02/06/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +57370,65566,59477,PRETRIAL,durmeus,daniel,NULL,Male,African-American,02/06/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +57370,65566,59477,PRETRIAL,durmeus,daniel,NULL,Male,African-American,02/06/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +36615,65573,59484,PRETRIAL,FRANCOIS,JAMES,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,New,1,0 +36615,65573,59484,PRETRIAL,FRANCOIS,JAMES,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +36615,65573,59484,PRETRIAL,FRANCOIS,JAMES,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57363,65558,59470,PRETRIAL,kimball,joseph,NULL,Male,Caucasian,09/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +57363,65558,59470,PRETRIAL,kimball,joseph,NULL,Male,Caucasian,09/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +57363,65558,59470,PRETRIAL,kimball,joseph,NULL,Male,Caucasian,09/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +6071,65581,59490,PRETRIAL,Farrell,Siegel,NULL,Male,African-American,06/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +6071,65581,59490,PRETRIAL,Farrell,Siegel,NULL,Male,African-American,06/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +6071,65581,59490,PRETRIAL,Farrell,Siegel,NULL,Male,African-American,06/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +57365,65560,59472,Probation,Belisario,Russell,NULL,Male,Caucasian,10/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,2,Medium,7,Risk of Violence,-3.17,1,Low,New,1,0 +57365,65560,59472,Probation,Belisario,Russell,NULL,Male,Caucasian,10/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +57365,65560,59472,Probation,Belisario,Russell,NULL,Male,Caucasian,10/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +57367,65563,59474,PRETRIAL,RUSHTON,CRYSTAL,NULL,Female,Caucasian,12/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +57367,65563,59474,PRETRIAL,RUSHTON,CRYSTAL,NULL,Female,Caucasian,12/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,4,High,8,Risk of Recidivism,0.06,8,High,New,1,0 +57367,65563,59474,PRETRIAL,RUSHTON,CRYSTAL,NULL,Female,Caucasian,12/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +30162,65576,59487,PRETRIAL,Yilmaz,Ibrahim,NULL,Male,Other,02/13/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +30162,65576,59487,PRETRIAL,Yilmaz,Ibrahim,NULL,Male,Other,02/13/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +30162,65576,59487,PRETRIAL,Yilmaz,Ibrahim,NULL,Male,Other,02/13/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57372,65568,59479,Probation,Pitter,Derrick,NULL,Male,African-American,06/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +57372,65568,59479,Probation,Pitter,Derrick,NULL,Male,African-American,06/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +57372,65568,59479,Probation,Pitter,Derrick,NULL,Male,African-American,06/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51704,65571,59482,PRETRIAL,WIESS,ELIZABETH,NULL,Female,Caucasian,04/05/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +51704,65571,59482,PRETRIAL,WIESS,ELIZABETH,NULL,Female,Caucasian,04/05/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +51704,65571,59482,PRETRIAL,WIESS,ELIZABETH,NULL,Female,Caucasian,04/05/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +1834,65550,59463,PRETRIAL,lapoint,joseph,j,Male,Caucasian,02/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +1834,65550,59463,PRETRIAL,lapoint,joseph,j,Male,Caucasian,02/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +1834,65550,59463,PRETRIAL,lapoint,joseph,j,Male,Caucasian,02/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55732,65583,57617,Probation,noel,Franquaill,NULL,Female,African-American,11/20/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,Copy,1,0 +55732,65583,57617,Probation,noel,Franquaill,NULL,Female,African-American,11/20/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,8,High,Copy,1,0 +55732,65583,57617,Probation,noel,Franquaill,NULL,Female,African-American,11/20/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +10580,65490,59409,Probation,Weise,Richard,NULL,Male,African-American,03/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +10580,65490,59409,Probation,Weise,Richard,NULL,Male,African-American,03/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +10580,65490,59409,Probation,Weise,Richard,NULL,Male,African-American,03/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57366,65562,59473,Probation,Mangones,Paolo,NULL,Male,Hispanic,07/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +57366,65562,59473,Probation,Mangones,Paolo,NULL,Male,Hispanic,07/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +57366,65562,59473,Probation,Mangones,Paolo,NULL,Male,Hispanic,07/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +52591,65555,59467,PRETRIAL,Felinor,Jean,Clotaireso,Male,Other,02/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +52591,65555,59467,PRETRIAL,Felinor,Jean,Clotaireso,Male,Other,02/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +52591,65555,59467,PRETRIAL,Felinor,Jean,Clotaireso,Male,Other,02/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57373,65569,59480,Probation,oneill,terence,NULL,Male,Caucasian,12/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +57373,65569,59480,Probation,oneill,terence,NULL,Male,Caucasian,12/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +57373,65569,59480,Probation,oneill,terence,NULL,Male,Caucasian,12/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57377,65578,59488,Probation,lopez,jesus,NULL,Male,Hispanic,10/03/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +57377,65578,59488,Probation,lopez,jesus,NULL,Male,Hispanic,10/03/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +57377,65578,59488,Probation,lopez,jesus,NULL,Male,Hispanic,10/03/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57375,65574,59485,Probation,Jean,Smith,NULL,Male,African-American,11/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +57375,65574,59485,Probation,Jean,Smith,NULL,Male,African-American,11/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +57375,65574,59485,Probation,Jean,Smith,NULL,Male,African-American,11/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +7845,65557,59469,PRETRIAL,JONES,JOSE,C,Male,African-American,01/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,4,High,7,Risk of Violence,-0.71,9,High,New,1,0 +7845,65557,59469,PRETRIAL,JONES,JOSE,C,Male,African-American,01/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,4,High,8,Risk of Recidivism,0.93,10,High,New,1,0 +7845,65557,59469,PRETRIAL,JONES,JOSE,C,Male,African-American,01/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,4,High,18,Risk of Failure to Appear,35,10,High,New,1,0 +24318,65553,59011,PRETRIAL,Lodenquai,Eric,Charlee,Male,African-American,10/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.17,4,Low,Copy,1,0 +24318,65553,59011,PRETRIAL,Lodenquai,Eric,Charlee,Male,African-American,10/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,Copy,1,0 +24318,65553,59011,PRETRIAL,Lodenquai,Eric,Charlee,Male,African-American,10/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +57395,65604,59508,Probation,Fedderwitz,warren,NULL,Male,Caucasian,11/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/19/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +57395,65604,59508,Probation,Fedderwitz,warren,NULL,Male,Caucasian,11/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/19/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +57395,65604,59508,Probation,Fedderwitz,warren,NULL,Male,Caucasian,11/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49810,65608,59512,PRETRIAL,Sills,norma-jean,NULL,Female,Caucasian,09/22/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/13 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +49810,65608,59512,PRETRIAL,Sills,norma-jean,NULL,Female,Caucasian,09/22/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +49810,65608,59512,PRETRIAL,Sills,norma-jean,NULL,Female,Caucasian,09/22/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53267,65595,59500,PRETRIAL,Davis,Jessie,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,2,Medium,7,Risk of Violence,-1.87,5,Medium,New,1,0 +53267,65595,59500,PRETRIAL,Davis,Jessie,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +53267,65595,59500,PRETRIAL,Davis,Jessie,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57407,65620,59523,DRRD,Marion,Antonio,NULL,Male,African-American,11/02/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +57407,65620,59523,DRRD,Marion,Antonio,NULL,Male,African-American,11/02/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +57407,65620,59523,DRRD,Marion,Antonio,NULL,Male,African-American,11/02/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57400,65611,59515,PRETRIAL,Woodard,Vinquisha,NULL,Female,African-American,09/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +57400,65611,59515,PRETRIAL,Woodard,Vinquisha,NULL,Female,African-American,09/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +57400,65611,59515,PRETRIAL,Woodard,Vinquisha,NULL,Female,African-American,09/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57402,65613,59517,Probation,CHADHA,AMBEK,NULL,Male,Asian,04/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +57402,65613,59517,Probation,CHADHA,AMBEK,NULL,Male,Asian,04/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +57402,65613,59517,Probation,CHADHA,AMBEK,NULL,Male,Asian,04/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57385,65590,59496,PRETRIAL,Tieso,Louise,NULL,Male,Caucasian,04/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +57385,65590,59496,PRETRIAL,Tieso,Louise,NULL,Male,Caucasian,04/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +57385,65590,59496,PRETRIAL,Tieso,Louise,NULL,Male,Caucasian,04/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57386,65592,59497,PRETRIAL,Daniels,Kevin,NULL,Male,African-American,03/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +57386,65592,59497,PRETRIAL,Daniels,Kevin,NULL,Male,African-American,03/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +57386,65592,59497,PRETRIAL,Daniels,Kevin,NULL,Male,African-American,03/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57384,65589,59495,PRETRIAL,Alcy,Kendy,NULL,Male,African-American,08/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +57384,65589,59495,PRETRIAL,Alcy,Kendy,NULL,Male,African-American,08/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +57384,65589,59495,PRETRIAL,Alcy,Kendy,NULL,Male,African-American,08/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +41629,65618,59521,PRETRIAL,Tetreault,Jonathan,NULL,Male,Caucasian,12/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +41629,65618,59521,PRETRIAL,Tetreault,Jonathan,NULL,Male,Caucasian,12/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +41629,65618,59521,PRETRIAL,Tetreault,Jonathan,NULL,Male,Caucasian,12/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +40103,65610,59514,PRETRIAL,Ham,Nelson,David,Male,Caucasian,06/06/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +40103,65610,59514,PRETRIAL,Ham,Nelson,David,Male,Caucasian,06/06/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +40103,65610,59514,PRETRIAL,Ham,Nelson,David,Male,Caucasian,06/06/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57388,65594,59499,PRETRIAL,Orr,Tony,NULL,Male,African-American,06/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +57388,65594,59499,PRETRIAL,Orr,Tony,NULL,Male,African-American,06/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +57388,65594,59499,PRETRIAL,Orr,Tony,NULL,Male,African-American,06/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57404,65615,59519,Probation,VILLARREAL,FLAVIO,NULL,Male,Hispanic,05/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +57404,65615,59519,Probation,VILLARREAL,FLAVIO,NULL,Male,Hispanic,05/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +57404,65615,59519,Probation,VILLARREAL,FLAVIO,NULL,Male,Hispanic,05/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57382,65587,59493,PRETRIAL,Cardona,Adriana,Yvette,Female,Caucasian,08/31/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/19/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +57382,65587,59493,PRETRIAL,Cardona,Adriana,Yvette,Female,Caucasian,08/31/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +57382,65587,59493,PRETRIAL,Cardona,Adriana,Yvette,Female,Caucasian,08/31/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57406,65619,59522,PRETRIAL,fulton,jeffrey,NULL,Male,African-American,02/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +57406,65619,59522,PRETRIAL,fulton,jeffrey,NULL,Male,African-American,02/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +57406,65619,59522,PRETRIAL,fulton,jeffrey,NULL,Male,African-American,02/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +18644,65591,52040,PRETRIAL,WATSON,CHRISTOPHER,NULL,Male,African-American,07/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,Copy,1,0 +18644,65591,52040,PRETRIAL,WATSON,CHRISTOPHER,NULL,Male,African-American,07/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,4,High,8,Risk of Recidivism,0.79,10,High,Copy,1,0 +18644,65591,52040,PRETRIAL,WATSON,CHRISTOPHER,NULL,Male,African-American,07/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +57392,65598,59503,Probation,Speedman,Richard,NULL,Male,Caucasian,08/27/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +57392,65598,59503,Probation,Speedman,Richard,NULL,Male,Caucasian,08/27/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +57392,65598,59503,Probation,Speedman,Richard,NULL,Male,Caucasian,08/27/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57397,65605,59509,Probation,VAZQUEZ,ROY,NULL,Male,Hispanic,10/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +57397,65605,59509,Probation,VAZQUEZ,ROY,NULL,Male,Hispanic,10/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +57397,65605,59509,Probation,VAZQUEZ,ROY,NULL,Male,Hispanic,10/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57412,65626,59528,Probation,Garcia Guzman,ligo,NULL,Male,Hispanic,05/28/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +57412,65626,59528,Probation,Garcia Guzman,ligo,NULL,Male,Hispanic,05/28/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +57412,65626,59528,Probation,Garcia Guzman,ligo,NULL,Male,Hispanic,05/28/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57401,65612,59516,Probation,Valenciacano,juan,Carlos,Male,Hispanic,09/21/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +57401,65612,59516,Probation,Valenciacano,juan,Carlos,Male,Hispanic,09/21/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +57401,65612,59516,Probation,Valenciacano,juan,Carlos,Male,Hispanic,09/21/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57381,65586,59492,PRETRIAL,Jones,Thurman,NULL,Male,African-American,11/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/19/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +57381,65586,59492,PRETRIAL,Jones,Thurman,NULL,Male,African-American,11/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +57381,65586,59492,PRETRIAL,Jones,Thurman,NULL,Male,African-American,11/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57408,65621,59524,Probation,Alvarez-Duque,Jaime,NULL,Male,Hispanic,04/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +57408,65621,59524,Probation,Alvarez-Duque,Jaime,NULL,Male,Hispanic,04/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +57408,65621,59524,Probation,Alvarez-Duque,Jaime,NULL,Male,Hispanic,04/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57393,65600,59505,Probation,Gonzalez,Eduardo,NULL,Male,Hispanic,05/04/51,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/19/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +57393,65600,59505,Probation,Gonzalez,Eduardo,NULL,Male,Hispanic,05/04/51,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/19/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +57393,65600,59505,Probation,Gonzalez,Eduardo,NULL,Male,Hispanic,05/04/51,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57399,65607,59511,Probation,rios,Sandra,Josephina,Female,Hispanic,08/07/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/19/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +57399,65607,59511,Probation,rios,Sandra,Josephina,Female,Hispanic,08/07/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1.62,2,Low,New,1,0 +57399,65607,59511,Probation,rios,Sandra,Josephina,Female,Hispanic,08/07/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +57380,65585,59491,PRETRIAL,Rivero,Amber,NULL,Male,African-American,12/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +57380,65585,59491,PRETRIAL,Rivero,Amber,NULL,Male,African-American,12/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +57380,65585,59491,PRETRIAL,Rivero,Amber,NULL,Male,African-American,12/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57398,65606,59510,PRETRIAL,Robinson,Daphne,NULL,Female,African-American,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +57398,65606,59510,PRETRIAL,Robinson,Daphne,NULL,Female,African-American,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,9,High,New,1,0 +57398,65606,59510,PRETRIAL,Robinson,Daphne,NULL,Female,African-American,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57387,65593,59498,PRETRIAL,Joseph,Ramainson,NULL,Male,African-American,01/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +57387,65593,59498,PRETRIAL,Joseph,Ramainson,NULL,Male,African-American,01/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +57387,65593,59498,PRETRIAL,Joseph,Ramainson,NULL,Male,African-American,01/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57413,65627,59529,PRETRIAL,Joseph,Jeffrey,NULL,Male,African-American,09/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +57413,65627,59529,PRETRIAL,Joseph,Jeffrey,NULL,Male,African-American,09/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +57413,65627,59529,PRETRIAL,Joseph,Jeffrey,NULL,Male,African-American,09/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57383,65588,59494,PRETRIAL,Shehadeh,Karam,NULL,Male,Caucasian,03/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +57383,65588,59494,PRETRIAL,Shehadeh,Karam,NULL,Male,Caucasian,03/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +57383,65588,59494,PRETRIAL,Shehadeh,Karam,NULL,Male,Caucasian,03/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57405,65616,59520,Probation,Sanford,Lance,NULL,Male,Caucasian,11/05/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +57405,65616,59520,Probation,Sanford,Lance,NULL,Male,Caucasian,11/05/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +57405,65616,59520,Probation,Sanford,Lance,NULL,Male,Caucasian,11/05/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57389,65596,59501,PRETRIAL,Cardona,Ivan,NULL,Male,Hispanic,07/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/19/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +57389,65596,59501,PRETRIAL,Cardona,Ivan,NULL,Male,Hispanic,07/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +57389,65596,59501,PRETRIAL,Cardona,Ivan,NULL,Male,Hispanic,07/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +27573,65609,59513,PRETRIAL,Thomas,Laurence,NULL,Male,African-American,03/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +27573,65609,59513,PRETRIAL,Thomas,Laurence,NULL,Male,African-American,03/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,4,High,8,Risk of Recidivism,0.19,8,High,New,1,0 +27573,65609,59513,PRETRIAL,Thomas,Laurence,NULL,Male,African-American,03/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +29160,65617,28184,PRETRIAL,Clay,Thomas,NULL,Male,African-American,06/25/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,Copy,1,0 +29160,65617,28184,PRETRIAL,Clay,Thomas,NULL,Male,African-American,06/25/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,Copy,1,0 +29160,65617,28184,PRETRIAL,Clay,Thomas,NULL,Male,African-American,06/25/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +57409,65622,59525,Probation,Di9az,Rosario,Jesus,Female,Hispanic,09/05/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/19/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +57409,65622,59525,Probation,Di9az,Rosario,Jesus,Female,Hispanic,09/05/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/19/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +57409,65622,59525,Probation,Di9az,Rosario,Jesus,Female,Hispanic,09/05/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57410,65624,59526,PRETRIAL,MACKEY,TIMOTHY,NULL,Male,Caucasian,12/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +57410,65624,59526,PRETRIAL,MACKEY,TIMOTHY,NULL,Male,Caucasian,12/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +57410,65624,59526,PRETRIAL,MACKEY,TIMOTHY,NULL,Male,Caucasian,12/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55792,65658,57688,Probation,SHERRELL,AMBROSIA,NULL,Female,African-American,01/24/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,4,High,7,Risk of Violence,-0.85,9,High,Copy,1,0 +55792,65658,57688,Probation,SHERRELL,AMBROSIA,NULL,Female,African-American,01/24/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,4,High,8,Risk of Recidivism,0.72,10,High,Copy,1,0 +55792,65658,57688,Probation,SHERRELL,AMBROSIA,NULL,Female,African-American,01/24/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +57426,65643,59544,Probation,sabb,harvey,NULL,Male,African-American,09/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +57426,65643,59544,Probation,sabb,harvey,NULL,Male,African-American,09/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +57426,65643,59544,Probation,sabb,harvey,NULL,Male,African-American,09/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +49624,65645,50508,PRETRIAL,Terrell,Roger,NULL,Male,African-American,10/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,9/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,Copy,1,0 +49624,65645,50508,PRETRIAL,Terrell,Roger,NULL,Male,African-American,10/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,9/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,Copy,1,0 +49624,65645,50508,PRETRIAL,Terrell,Roger,NULL,Male,African-American,10/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,9/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +10630,65630,59531,PRETRIAL,JOHNSON,SHIMEKO,NICOLE,Female,African-American,02/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +10630,65630,59531,PRETRIAL,JOHNSON,SHIMEKO,NICOLE,Female,African-American,02/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +10630,65630,59531,PRETRIAL,JOHNSON,SHIMEKO,NICOLE,Female,African-American,02/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57419,65637,59538,PRETRIAL,Pharicien,Walter,NULL,Male,Other,02/18/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +57419,65637,59538,PRETRIAL,Pharicien,Walter,NULL,Male,Other,02/18/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/13 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +57419,65637,59538,PRETRIAL,Pharicien,Walter,NULL,Male,Other,02/18/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57420,65638,59539,PRETRIAL,Watson,Mary,Thomas,Female,Caucasian,07/28/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/20/13 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +57420,65638,59539,PRETRIAL,Watson,Mary,Thomas,Female,Caucasian,07/28/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/20/13 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +57420,65638,59539,PRETRIAL,Watson,Mary,Thomas,Female,Caucasian,07/28/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56908,65651,59001,PRETRIAL,Bretti,Dino,NULL,Male,Caucasian,03/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,Copy,1,0 +56908,65651,59001,PRETRIAL,Bretti,Dino,NULL,Male,Caucasian,03/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,Copy,1,0 +56908,65651,59001,PRETRIAL,Bretti,Dino,NULL,Male,Caucasian,03/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +57417,65635,59536,PRETRIAL,Delarosa,Douglas,NULL,Male,Caucasian,01/31/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +57417,65635,59536,PRETRIAL,Delarosa,Douglas,NULL,Male,Caucasian,01/31/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +57417,65635,59536,PRETRIAL,Delarosa,Douglas,NULL,Male,Caucasian,01/31/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57415,65632,59533,PRETRIAL,Isme,Wisler,NULL,Male,African-American,02/21/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +57415,65632,59533,PRETRIAL,Isme,Wisler,NULL,Male,African-American,02/21/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +57415,65632,59533,PRETRIAL,Isme,Wisler,NULL,Male,African-American,02/21/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57436,65654,59552,PRETRIAL,TUCKER,ALFRED,NULL,Male,Native American,09/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.72,9,High,New,1,0 +57436,65654,59552,PRETRIAL,TUCKER,ALFRED,NULL,Male,Native American,09/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +57436,65654,59552,PRETRIAL,TUCKER,ALFRED,NULL,Male,Native American,09/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57858,66161,60007,Broward County,Bird,Mark,NULL,Male,Caucasian,06/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +57858,66161,60007,Broward County,Bird,Mark,NULL,Male,Caucasian,06/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +57858,66161,60007,Broward County,Bird,Mark,NULL,Male,Caucasian,06/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +21372,65633,59534,PRETRIAL,lewis,lorenzo,NULL,Male,African-American,12/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +21372,65633,59534,PRETRIAL,lewis,lorenzo,NULL,Male,African-American,12/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,4,High,8,Risk of Recidivism,1.25,10,High,New,1,0 +21372,65633,59534,PRETRIAL,lewis,lorenzo,NULL,Male,African-American,12/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +33922,65628,33039,PRETRIAL,Bele,Joshua,NULL,Male,African-American,06/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,4,High,7,Risk of Violence,-1.11,8,High,Copy,1,0 +33922,65628,33039,PRETRIAL,Bele,Joshua,NULL,Male,African-American,06/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,4,High,8,Risk of Recidivism,0.2,8,High,Copy,1,0 +33922,65628,33039,PRETRIAL,Bele,Joshua,NULL,Male,African-American,06/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +57430,65647,59547,PRETRIAL,Stewart,Tyler,NULL,Male,African-American,06/01/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +57430,65647,59547,PRETRIAL,Stewart,Tyler,NULL,Male,African-American,06/01/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,4,Low,New,1,0 +57430,65647,59547,PRETRIAL,Stewart,Tyler,NULL,Male,African-American,06/01/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57432,65649,59549,PRETRIAL,GARCIA,MARIO,NULL,Male,Hispanic,09/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +57432,65649,59549,PRETRIAL,GARCIA,MARIO,NULL,Male,Hispanic,09/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +57432,65649,59549,PRETRIAL,GARCIA,MARIO,NULL,Male,Hispanic,09/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57435,65652,59551,PRETRIAL,Dejesus,Ivan,NULL,Male,Hispanic,04/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +57435,65652,59551,PRETRIAL,Dejesus,Ivan,NULL,Male,Hispanic,04/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +57435,65652,59551,PRETRIAL,Dejesus,Ivan,NULL,Male,Hispanic,04/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57428,65644,59545,Probation,Daoust,Lucien,NULL,Male,Caucasian,12/20/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/20/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +57428,65644,59545,Probation,Daoust,Lucien,NULL,Male,Caucasian,12/20/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/20/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +57428,65644,59545,Probation,Daoust,Lucien,NULL,Male,Caucasian,12/20/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57414,65631,59532,PRETRIAL,Alvarado,Grace,Yessenia,Female,Hispanic,06/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +57414,65631,59532,PRETRIAL,Alvarado,Grace,Yessenia,Female,Hispanic,06/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +57414,65631,59532,PRETRIAL,Alvarado,Grace,Yessenia,Female,Hispanic,06/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57418,65636,59537,PRETRIAL,Brown,Courtney,NULL,Male,African-American,07/06/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/20/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +57418,65636,59537,PRETRIAL,Brown,Courtney,NULL,Male,African-American,07/06/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/20/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +57418,65636,59537,PRETRIAL,Brown,Courtney,NULL,Male,African-American,07/06/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57421,65639,59540,PRETRIAL,Washington,Travis,NULL,Male,African-American,05/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +57421,65639,59540,PRETRIAL,Washington,Travis,NULL,Male,African-American,05/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +57421,65639,59540,PRETRIAL,Washington,Travis,NULL,Male,African-American,05/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +57416,65634,59535,PRETRIAL,Ahmed,Mohammad,NULL,Male,Other,11/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +57416,65634,59535,PRETRIAL,Ahmed,Mohammad,NULL,Male,Other,11/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +57416,65634,59535,PRETRIAL,Ahmed,Mohammad,NULL,Male,Other,11/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57424,65641,59542,Probation,Deltoro,Keely,NULL,Female,Hispanic,12/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +57424,65641,59542,Probation,Deltoro,Keely,NULL,Female,Hispanic,12/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +57424,65641,59542,Probation,Deltoro,Keely,NULL,Female,Hispanic,12/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57431,65648,59548,Probation,Hyde,Stephen,NULL,Male,Caucasian,09/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +57431,65648,59548,Probation,Hyde,Stephen,NULL,Male,Caucasian,09/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +57431,65648,59548,Probation,Hyde,Stephen,NULL,Male,Caucasian,09/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57437,65655,59553,Probation,Zurita,Fernando,NULL,Male,Hispanic,12/11/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,2,Medium,7,Risk of Violence,-2.85,2,Low,New,1,0 +57437,65655,59553,Probation,Zurita,Fernando,NULL,Male,Hispanic,12/11/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +57437,65655,59553,Probation,Zurita,Fernando,NULL,Male,Hispanic,12/11/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +21599,65629,59530,PRETRIAL,Siggins,Raymond,NULL,Male,Caucasian,09/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +21599,65629,59530,PRETRIAL,Siggins,Raymond,NULL,Male,Caucasian,09/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,4,High,8,Risk of Recidivism,0.92,10,High,New,1,0 +21599,65629,59530,PRETRIAL,Siggins,Raymond,NULL,Male,Caucasian,09/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,4,High,18,Risk of Failure to Appear,38,10,High,New,1,0 +57429,65646,59546,Probation,Fludd,Cedrick,NULL,Male,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +57429,65646,59546,Probation,Fludd,Cedrick,NULL,Male,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +57429,65646,59546,Probation,Fludd,Cedrick,NULL,Male,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57434,65650,59550,PRETRIAL,CUNNINGHAM,JON,DAVID,Male,African-American,09/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +57434,65650,59550,PRETRIAL,CUNNINGHAM,JON,DAVID,Male,African-American,09/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +57434,65650,59550,PRETRIAL,CUNNINGHAM,JON,DAVID,Male,African-American,09/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57444,65664,59559,PRETRIAL,Bienamie,Joubert,NULL,Male,African-American,09/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +57444,65664,59559,PRETRIAL,Bienamie,Joubert,NULL,Male,African-American,09/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +57444,65664,59559,PRETRIAL,Bienamie,Joubert,NULL,Male,African-American,09/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57456,65671,59566,PRETRIAL,Hayes,Todd,E,Male,Caucasian,07/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +57456,65671,59566,PRETRIAL,Hayes,Todd,E,Male,Caucasian,07/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/13 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +57456,65671,59566,PRETRIAL,Hayes,Todd,E,Male,Caucasian,07/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57462,65676,59570,PRETRIAL,SMART,BASIL,NULL,Male,Other,04/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +57462,65676,59570,PRETRIAL,SMART,BASIL,NULL,Male,Other,04/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +57462,65676,59570,PRETRIAL,SMART,BASIL,NULL,Male,Other,04/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57452,65667,59562,PRETRIAL,Hayden,Romario,NULL,Male,African-American,11/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +57452,65667,59562,PRETRIAL,Hayden,Romario,NULL,Male,African-American,11/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +57452,65667,59562,PRETRIAL,Hayden,Romario,NULL,Male,African-American,11/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57454,65669,59564,PRETRIAL,Johnson,Tremaine,NULL,Male,African-American,05/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.05,8,High,New,1,0 +57454,65669,59564,PRETRIAL,Johnson,Tremaine,NULL,Male,African-American,05/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +57454,65669,59564,PRETRIAL,Johnson,Tremaine,NULL,Male,African-American,05/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57442,65662,59557,PRETRIAL,Wright,Maceo,Parker,Male,African-American,11/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +57442,65662,59557,PRETRIAL,Wright,Maceo,Parker,Male,African-American,11/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +57442,65662,59557,PRETRIAL,Wright,Maceo,Parker,Male,African-American,11/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57445,65665,59560,PRETRIAL,Philibert,Ricardo,NULL,Male,African-American,07/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +57445,65665,59560,PRETRIAL,Philibert,Ricardo,NULL,Male,African-American,07/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +57445,65665,59560,PRETRIAL,Philibert,Ricardo,NULL,Male,African-American,07/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57460,65673,59568,PRETRIAL,francis,andre,NULL,Male,African-American,05/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,New,1,0 +57460,65673,59568,PRETRIAL,francis,andre,NULL,Male,African-American,05/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +57460,65673,59568,PRETRIAL,francis,andre,NULL,Male,African-American,05/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57440,65660,59555,PRETRIAL,Lankford,Alton,NULL,Male,Caucasian,01/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,2,Medium,7,Risk of Violence,-2.72,2,Low,New,1,0 +57440,65660,59555,PRETRIAL,Lankford,Alton,NULL,Male,Caucasian,01/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +57440,65660,59555,PRETRIAL,Lankford,Alton,NULL,Male,Caucasian,01/31/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +57463,65677,59571,PRETRIAL,Hurlock,Shane,NULL,Male,African-American,09/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +57463,65677,59571,PRETRIAL,Hurlock,Shane,NULL,Male,African-American,09/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +57463,65677,59571,PRETRIAL,Hurlock,Shane,NULL,Male,African-American,09/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57455,65670,59565,PRETRIAL,Singletary,Markee,NULL,Female,African-American,04/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +57455,65670,59565,PRETRIAL,Singletary,Markee,NULL,Female,African-American,04/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +57455,65670,59565,PRETRIAL,Singletary,Markee,NULL,Female,African-American,04/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57459,65672,59567,PRETRIAL,Toledo,David,NULL,Male,Caucasian,09/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +57459,65672,59567,PRETRIAL,Toledo,David,NULL,Male,Caucasian,09/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +57459,65672,59567,PRETRIAL,Toledo,David,NULL,Male,Caucasian,09/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57443,65663,59558,PRETRIAL,Evans,Aaron,Xavier,Male,African-American,02/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +57443,65663,59558,PRETRIAL,Evans,Aaron,Xavier,Male,African-American,02/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +57443,65663,59558,PRETRIAL,Evans,Aaron,Xavier,Male,African-American,02/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57453,65668,59563,PRETRIAL,Dormeus,Marceaux,NULL,Male,African-American,07/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +57453,65668,59563,PRETRIAL,Dormeus,Marceaux,NULL,Male,African-American,07/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +57453,65668,59563,PRETRIAL,Dormeus,Marceaux,NULL,Male,African-American,07/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +23645,65675,22844,PRETRIAL,JONES,CLINTON,NULL,Male,African-American,05/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,4,High,7,Risk of Violence,-0.7,9,High,Copy,1,0 +23645,65675,22844,PRETRIAL,JONES,CLINTON,NULL,Male,African-American,05/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,4,High,8,Risk of Recidivism,0.54,9,High,Copy,1,0 +23645,65675,22844,PRETRIAL,JONES,CLINTON,NULL,Male,African-American,05/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +57441,65661,59556,PRETRIAL,Frias,Armando,NULL,Male,Hispanic,04/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +57441,65661,59556,PRETRIAL,Frias,Armando,NULL,Male,Hispanic,04/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/13 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +57441,65661,59556,PRETRIAL,Frias,Armando,NULL,Male,Hispanic,04/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57461,65674,59569,PRETRIAL,Wilson,Darril,NULL,Male,African-American,10/06/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +57461,65674,59569,PRETRIAL,Wilson,Darril,NULL,Male,African-American,10/06/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +57461,65674,59569,PRETRIAL,Wilson,Darril,NULL,Male,African-American,10/06/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57467,65682,59575,PRETRIAL,Delatorre,Carlos,Ernesto,Male,Hispanic,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +57467,65682,59575,PRETRIAL,Delatorre,Carlos,Ernesto,Male,Hispanic,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +57467,65682,59575,PRETRIAL,Delatorre,Carlos,Ernesto,Male,Hispanic,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57464,65679,59572,PRETRIAL,Van Kanten,Sergio,NULL,Male,African-American,07/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/22/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +57464,65679,59572,PRETRIAL,Van Kanten,Sergio,NULL,Male,African-American,07/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/22/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +57464,65679,59572,PRETRIAL,Van Kanten,Sergio,NULL,Male,African-American,07/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57473,65689,59581,PRETRIAL,MCNULTY,MEGAN,NULL,Female,Caucasian,07/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +57473,65689,59581,PRETRIAL,MCNULTY,MEGAN,NULL,Female,Caucasian,07/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +57473,65689,59581,PRETRIAL,MCNULTY,MEGAN,NULL,Female,Caucasian,07/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +9042,9171,8574,PRETRIAL,SPICY,JASON,NULL,Male,African-American,09/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/22/13 0:00,4,High,7,Risk of Violence,0.5,10,High,New,1,0 +9042,9171,8574,PRETRIAL,SPICY,JASON,NULL,Male,African-American,09/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/22/13 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +9042,9171,8574,PRETRIAL,SPICY,JASON,NULL,Male,African-American,09/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/22/13 0:00,4,High,18,Risk of Failure to Appear,35,10,High,New,1,0 +57469,65684,59577,PRETRIAL,Francois,Kerry,NULL,Male,African-American,12/18/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +57469,65684,59577,PRETRIAL,Francois,Kerry,NULL,Male,African-American,12/18/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +57469,65684,59577,PRETRIAL,Francois,Kerry,NULL,Male,African-American,12/18/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57466,65681,59574,PRETRIAL,GRANT,AVIAN,DEGNO,Male,Other,01/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +57466,65681,59574,PRETRIAL,GRANT,AVIAN,DEGNO,Male,Other,01/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +57466,65681,59574,PRETRIAL,GRANT,AVIAN,DEGNO,Male,Other,01/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57465,65680,59573,PRETRIAL,McKennie,Glenn,Edward,Male,African-American,08/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +57465,65680,59573,PRETRIAL,McKennie,Glenn,Edward,Male,African-American,08/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.1,10,High,New,1,0 +57465,65680,59573,PRETRIAL,McKennie,Glenn,Edward,Male,African-American,08/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57472,65688,59580,PRETRIAL,Penalopez,Andres,f,Male,Hispanic,06/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,9/22/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +57472,65688,59580,PRETRIAL,Penalopez,Andres,f,Male,Hispanic,06/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,9/22/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +57472,65688,59580,PRETRIAL,Penalopez,Andres,f,Male,Hispanic,06/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,9/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55217,65678,57022,Probation,Nieves,Norberto,NULL,Male,Hispanic,01/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,Copy,1,0 +55217,65678,57022,Probation,Nieves,Norberto,NULL,Male,Hispanic,01/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,Copy,1,0 +55217,65678,57022,Probation,Nieves,Norberto,NULL,Male,Hispanic,01/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +57471,65686,59579,PRETRIAL,Leslie,Michael,A,Male,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/22/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +57471,65686,59579,PRETRIAL,Leslie,Michael,A,Male,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +57471,65686,59579,PRETRIAL,Leslie,Michael,A,Male,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/22/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57468,65683,59576,PRETRIAL,HAMILTON,PATRICK,ANTHONY,Male,Other,05/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/22/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +57468,65683,59576,PRETRIAL,HAMILTON,PATRICK,ANTHONY,Male,Other,05/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/22/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +57468,65683,59576,PRETRIAL,HAMILTON,PATRICK,ANTHONY,Male,Other,05/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57470,65685,59578,PRETRIAL,Jimenezpagan,Francisco,NULL,Male,Hispanic,03/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,9/22/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +57470,65685,59578,PRETRIAL,Jimenezpagan,Francisco,NULL,Male,Hispanic,03/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,9/22/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +57470,65685,59578,PRETRIAL,Jimenezpagan,Francisco,NULL,Male,Hispanic,03/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,9/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57497,65718,59608,PRETRIAL,Mohammadnejad,Farroka,NULL,Male,Arabic,06/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/23/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +57497,65718,59608,PRETRIAL,Mohammadnejad,Farroka,NULL,Male,Arabic,06/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/23/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +57497,65718,59608,PRETRIAL,Mohammadnejad,Farroka,NULL,Male,Arabic,06/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57515,65736,59626,PRETRIAL,Silva,Carla,NULL,Female,Other,03/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +57515,65736,59626,PRETRIAL,Silva,Carla,NULL,Female,Other,03/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +57515,65736,59626,PRETRIAL,Silva,Carla,NULL,Female,Other,03/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57510,65732,59622,Probation,Torres,Jorge,NULL,Male,Hispanic,01/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/23/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +57510,65732,59622,Probation,Torres,Jorge,NULL,Male,Hispanic,01/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/23/13 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +57510,65732,59622,Probation,Torres,Jorge,NULL,Male,Hispanic,01/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57519,65739,59629,PRETRIAL,Ulpiano,Gabriella,NULL,Female,Caucasian,06/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +57519,65739,59629,PRETRIAL,Ulpiano,Gabriella,NULL,Female,Caucasian,06/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +57519,65739,59629,PRETRIAL,Ulpiano,Gabriella,NULL,Female,Caucasian,06/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +31931,65697,59588,PRETRIAL,RANDELL,WILLIAMS,CHONSHI,Male,Caucasian,01/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +31931,65697,59588,PRETRIAL,RANDELL,WILLIAMS,CHONSHI,Male,Caucasian,01/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,4,High,8,Risk of Recidivism,0.39,9,High,New,1,0 +31931,65697,59588,PRETRIAL,RANDELL,WILLIAMS,CHONSHI,Male,Caucasian,01/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57489,65706,59596,Probation,Hall,Hailey,NULL,Female,Caucasian,10/21/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +57489,65706,59596,Probation,Hall,Hailey,NULL,Female,Caucasian,10/21/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +57489,65706,59596,Probation,Hall,Hailey,NULL,Female,Caucasian,10/21/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57505,65727,59617,PRETRIAL,Jasmine,Angelo,NULL,Male,African-American,10/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +57505,65727,59617,PRETRIAL,Jasmine,Angelo,NULL,Male,African-American,10/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +57505,65727,59617,PRETRIAL,Jasmine,Angelo,NULL,Male,African-American,10/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58022,66378,60201,Broward County,Wofford,Austin,NULL,Male,Caucasian,01/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +58022,66378,60201,Broward County,Wofford,Austin,NULL,Male,Caucasian,01/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +58022,66378,60201,Broward County,Wofford,Austin,NULL,Male,Caucasian,01/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57474,65690,59582,PRETRIAL,West,Shamroy,Addonnis,Male,Other,03/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +57474,65690,59582,PRETRIAL,West,Shamroy,Addonnis,Male,Other,03/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +57474,65690,59582,PRETRIAL,West,Shamroy,Addonnis,Male,Other,03/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57476,65692,59584,PRETRIAL,Voltaire,Roland,NULL,Male,Other,10/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +57476,65692,59584,PRETRIAL,Voltaire,Roland,NULL,Male,Other,10/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +57476,65692,59584,PRETRIAL,Voltaire,Roland,NULL,Male,Other,10/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57494,65713,59603,Probation,PHARR,LATASHA,YVONNE,Female,African-American,06/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +57494,65713,59603,Probation,PHARR,LATASHA,YVONNE,Female,African-American,06/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +57494,65713,59603,Probation,PHARR,LATASHA,YVONNE,Female,African-American,06/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57511,65734,59624,PRETRIAL,Click,Savannah,NULL,Female,Caucasian,05/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +57511,65734,59624,PRETRIAL,Click,Savannah,NULL,Female,Caucasian,05/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +57511,65734,59624,PRETRIAL,Click,Savannah,NULL,Female,Caucasian,05/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57521,65741,59631,Probation,Royster,Don,NULL,Male,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +57521,65741,59631,Probation,Royster,Don,NULL,Male,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +57521,65741,59631,Probation,Royster,Don,NULL,Male,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57527,65748,59637,PRETRIAL,Brown,John,Raven,Male,African-American,12/01/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +57527,65748,59637,PRETRIAL,Brown,John,Raven,Male,African-American,12/01/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +57527,65748,59637,PRETRIAL,Brown,John,Raven,Male,African-American,12/01/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57487,65704,59594,PRETRIAL,Delcid,Carlos,NULL,Male,Hispanic,05/11/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,4,High,7,Risk of Violence,-0.25,10,High,New,1,0 +57487,65704,59594,PRETRIAL,Delcid,Carlos,NULL,Male,Hispanic,05/11/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +57487,65704,59594,PRETRIAL,Delcid,Carlos,NULL,Male,Hispanic,05/11/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,4,High,18,Risk of Failure to Appear,19,2,Low,New,1,0 +57490,65707,59597,PRETRIAL,Mena,Guillermo,NULL,Male,Hispanic,02/10/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +57490,65707,59597,PRETRIAL,Mena,Guillermo,NULL,Male,Hispanic,02/10/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +57490,65707,59597,PRETRIAL,Mena,Guillermo,NULL,Male,Hispanic,02/10/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57503,65725,59615,PRETRIAL,LAMOTTA,ELISA,NULL,Female,Caucasian,10/06/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +57503,65725,59615,PRETRIAL,LAMOTTA,ELISA,NULL,Female,Caucasian,10/06/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +57503,65725,59615,PRETRIAL,LAMOTTA,ELISA,NULL,Female,Caucasian,10/06/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57493,65712,59602,PRETRIAL,SOTO,ELVIN,NULL,Male,Hispanic,03/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +57493,65712,59602,PRETRIAL,SOTO,ELVIN,NULL,Male,Hispanic,03/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +57493,65712,59602,PRETRIAL,SOTO,ELVIN,NULL,Male,Hispanic,03/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57526,65746,59635,Probation,Plaza,Joycee,NULL,Female,Hispanic,12/20/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/23/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +57526,65746,59635,Probation,Plaza,Joycee,NULL,Female,Hispanic,12/20/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +57526,65746,59635,Probation,Plaza,Joycee,NULL,Female,Hispanic,12/20/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57483,65699,59590,PRETRIAL,CARTRIGHT,KIMBERLY,NULL,Male,Other,09/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +57483,65699,59590,PRETRIAL,CARTRIGHT,KIMBERLY,NULL,Male,Other,09/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +57483,65699,59590,PRETRIAL,CARTRIGHT,KIMBERLY,NULL,Male,Other,09/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57512,65733,59623,PRETRIAL,jovelton,joseph,NULL,Male,African-American,10/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +57512,65733,59623,PRETRIAL,jovelton,joseph,NULL,Male,African-American,10/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +57512,65733,59623,PRETRIAL,jovelton,joseph,NULL,Male,African-American,10/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57485,65701,59592,PRETRIAL,ELLIOT,VERON,R,Male,Caucasian,05/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +57485,65701,59592,PRETRIAL,ELLIOT,VERON,R,Male,Caucasian,05/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +57485,65701,59592,PRETRIAL,ELLIOT,VERON,R,Male,Caucasian,05/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57486,65702,59593,PRETRIAL,Plummer,Kory,Omar,Male,Other,03/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/23/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +57486,65702,59593,PRETRIAL,Plummer,Kory,Omar,Male,Other,03/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +57486,65702,59593,PRETRIAL,Plummer,Kory,Omar,Male,Other,03/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57518,65738,59628,Probation,Carmona,Giovanni,NULL,Male,Hispanic,02/16/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +57518,65738,59628,Probation,Carmona,Giovanni,NULL,Male,Hispanic,02/16/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +57518,65738,59628,Probation,Carmona,Giovanni,NULL,Male,Hispanic,02/16/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57491,65709,59599,Probation,WILLIAMS,YOLANDA,NULL,Female,African-American,11/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +57491,65709,59599,Probation,WILLIAMS,YOLANDA,NULL,Female,African-American,11/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +57491,65709,59599,Probation,WILLIAMS,YOLANDA,NULL,Female,African-American,11/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +57502,65723,59613,Probation,Green,Tehsia,NULL,Female,African-American,08/22/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +57502,65723,59613,Probation,Green,Tehsia,NULL,Female,African-American,08/22/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +57502,65723,59613,Probation,Green,Tehsia,NULL,Female,African-American,08/22/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57495,65715,59605,Probation,Merrill,Michael,NULL,Male,Caucasian,07/01/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +57495,65715,59605,Probation,Merrill,Michael,NULL,Male,Caucasian,07/01/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +57495,65715,59605,Probation,Merrill,Michael,NULL,Male,Caucasian,07/01/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +42194,65717,59607,PRETRIAL,Mclaughlin,Dominica,Lucille,Female,Caucasian,10/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +42194,65717,59607,PRETRIAL,Mclaughlin,Dominica,Lucille,Female,Caucasian,10/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +42194,65717,59607,PRETRIAL,Mclaughlin,Dominica,Lucille,Female,Caucasian,10/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57501,65722,59612,PRETRIAL,Martinez,Jorge,NULL,Male,Hispanic,07/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +57501,65722,59612,PRETRIAL,Martinez,Jorge,NULL,Male,Hispanic,07/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +57501,65722,59612,PRETRIAL,Martinez,Jorge,NULL,Male,Hispanic,07/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +57480,65694,59586,PRETRIAL,CAJETE,JESSICA,NULL,Female,Hispanic,08/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +57480,65694,59586,PRETRIAL,CAJETE,JESSICA,NULL,Female,Hispanic,08/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +57480,65694,59586,PRETRIAL,CAJETE,JESSICA,NULL,Female,Hispanic,08/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +16248,65696,15576,PRETRIAL,GARAFOLO,JOSEPH,JAMES,Male,Caucasian,10/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +16248,65696,15576,PRETRIAL,GARAFOLO,JOSEPH,JAMES,Male,Caucasian,10/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,Copy,1,0 +16248,65696,15576,PRETRIAL,GARAFOLO,JOSEPH,JAMES,Male,Caucasian,10/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +57508,65730,59620,PRETRIAL,harris,zavier,NULL,Male,African-American,12/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,4,High,7,Risk of Violence,-0.09,10,High,New,1,0 +57508,65730,59620,PRETRIAL,harris,zavier,NULL,Male,African-American,12/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,4,High,8,Risk of Recidivism,1.37,10,High,New,1,0 +57508,65730,59620,PRETRIAL,harris,zavier,NULL,Male,African-American,12/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57522,65743,59633,PRETRIAL,SALOW,ALEXANDER,NULL,Male,Caucasian,10/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +57522,65743,59633,PRETRIAL,SALOW,ALEXANDER,NULL,Male,Caucasian,10/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +57522,65743,59633,PRETRIAL,SALOW,ALEXANDER,NULL,Male,Caucasian,10/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57475,65691,59583,PRETRIAL,Lopez,Rafael,NULL,Male,Hispanic,03/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +57475,65691,59583,PRETRIAL,Lopez,Rafael,NULL,Male,Hispanic,03/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +57475,65691,59583,PRETRIAL,Lopez,Rafael,NULL,Male,Hispanic,03/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57482,65698,59589,PRETRIAL,Holmes,Evan,Christopher,Male,Caucasian,06/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +57482,65698,59589,PRETRIAL,Holmes,Evan,Christopher,Male,Caucasian,06/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +57482,65698,59589,PRETRIAL,Holmes,Evan,Christopher,Male,Caucasian,06/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57488,65705,59595,Probation,Mounds,Otis,Devante-Henry,Male,African-American,06/21/97,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +57488,65705,59595,Probation,Mounds,Otis,Devante-Henry,Male,African-American,06/21/97,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/13 0:00,4,High,8,Risk of Recidivism,1.13,10,High,New,1,0 +57488,65705,59595,Probation,Mounds,Otis,Devante-Henry,Male,African-American,06/21/97,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57498,65719,59609,PRETRIAL,Merisier,Mary,NULL,Female,African-American,10/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/23/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +57498,65719,59609,PRETRIAL,Merisier,Mary,NULL,Female,African-American,10/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +57498,65719,59609,PRETRIAL,Merisier,Mary,NULL,Female,African-American,10/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57504,65726,59616,Probation,VALENTINE,ZACHARY,N,Male,Caucasian,03/24/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +57504,65726,59616,Probation,VALENTINE,ZACHARY,N,Male,Caucasian,03/24/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +57504,65726,59616,Probation,VALENTINE,ZACHARY,N,Male,Caucasian,03/24/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57528,65749,59638,PRETRIAL,CABRERA,ALEJANDRO,JOSE,Male,Caucasian,03/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/23/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +57528,65749,59638,PRETRIAL,CABRERA,ALEJANDRO,JOSE,Male,Caucasian,03/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/23/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +57528,65749,59638,PRETRIAL,CABRERA,ALEJANDRO,JOSE,Male,Caucasian,03/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57479,65693,59585,PRETRIAL,Brutus,Irvans,NULL,Male,Other,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +57479,65693,59585,PRETRIAL,Brutus,Irvans,NULL,Male,Other,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +57479,65693,59585,PRETRIAL,Brutus,Irvans,NULL,Male,Other,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57492,65710,59600,PRETRIAL,Marshall,Lyntina,Marilyn,Female,African-American,06/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,9/23/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +57492,65710,59600,PRETRIAL,Marshall,Lyntina,Marilyn,Female,African-American,06/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +57492,65710,59600,PRETRIAL,Marshall,Lyntina,Marilyn,Female,African-American,06/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +37817,65744,57417,PRETRIAL,Singh,Navin,NULL,Male,Caucasian,01/17/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/23/13 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +37817,65744,57417,PRETRIAL,Singh,Navin,NULL,Male,Caucasian,01/17/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,6,Medium,New,1,0 +37817,65744,57417,PRETRIAL,Singh,Navin,NULL,Male,Caucasian,01/17/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/23/13 0:00,2,Medium,18,Risk of Failure to Appear,18,2,Low,New,1,0 +57509,65731,59621,PRETRIAL,Dundis,Joshua,NULL,Male,Caucasian,01/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +57509,65731,59621,PRETRIAL,Dundis,Joshua,NULL,Male,Caucasian,01/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +57509,65731,59621,PRETRIAL,Dundis,Joshua,NULL,Male,Caucasian,01/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57520,65740,59630,Probation,De Leon Jimenez,Jose,NULL,Male,Hispanic,01/28/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/23/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +57520,65740,59630,Probation,De Leon Jimenez,Jose,NULL,Male,Hispanic,01/28/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +57520,65740,59630,Probation,De Leon Jimenez,Jose,NULL,Male,Hispanic,01/28/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +30520,65714,59604,PRETRIAL,Law,Timothy,J,Male,African-American,08/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,4,High,7,Risk of Violence,-0.53,10,High,New,1,0 +30520,65714,59604,PRETRIAL,Law,Timothy,J,Male,African-American,08/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,4,High,8,Risk of Recidivism,1.59,10,High,New,1,0 +30520,65714,59604,PRETRIAL,Law,Timothy,J,Male,African-American,08/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57514,65735,59625,Probation,Brownlee,Brian,NULL,Male,African-American,05/05/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +57514,65735,59625,Probation,Brownlee,Brian,NULL,Male,African-American,05/05/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +57514,65735,59625,Probation,Brownlee,Brian,NULL,Male,African-American,05/05/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +9585,65724,59614,PRETRIAL,terrell,travers,NULL,Male,African-American,10/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +9585,65724,59614,PRETRIAL,terrell,travers,NULL,Male,African-American,10/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +9585,65724,59614,PRETRIAL,terrell,travers,NULL,Male,African-American,10/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57517,65737,59627,DRRD,Smith,Tariq,Naim,Male,African-American,02/19/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +57517,65737,59627,DRRD,Smith,Tariq,Naim,Male,African-American,02/19/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,8,High,New,1,0 +57517,65737,59627,DRRD,Smith,Tariq,Naim,Male,African-American,02/19/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +57496,65716,59606,Probation,Gregory,Francesca,Cristina,Female,Hispanic,04/30/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.71,2,Low,New,1,0 +57496,65716,59606,Probation,Gregory,Francesca,Cristina,Female,Hispanic,04/30/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.07,8,High,New,1,0 +57496,65716,59606,Probation,Gregory,Francesca,Cristina,Female,Hispanic,04/30/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57484,65700,59591,PRETRIAL,Saunders,Bari,Alexander,Male,African-American,09/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +57484,65700,59591,PRETRIAL,Saunders,Bari,Alexander,Male,African-American,09/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +57484,65700,59591,PRETRIAL,Saunders,Bari,Alexander,Male,African-American,09/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57487,65703,59594,PRETRIAL,Delcid,Carlos,NULL,Male,Hispanic,05/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,4,High,7,Risk of Violence,-0.25,10,High,New,1,0 +57487,65703,59594,PRETRIAL,Delcid,Carlos,NULL,Male,Hispanic,05/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +57487,65703,59594,PRETRIAL,Delcid,Carlos,NULL,Male,Hispanic,05/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57500,65721,59611,PRETRIAL,Morenovasquez,Carlos,Francisco,Male,Hispanic,06/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/23/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +57500,65721,59611,PRETRIAL,Morenovasquez,Carlos,Francisco,Male,Hispanic,06/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +57500,65721,59611,PRETRIAL,Morenovasquez,Carlos,Francisco,Male,Hispanic,06/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57523,65742,59632,PRETRIAL,Boyance,William,NULL,Male,Caucasian,11/12/43,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +57523,65742,59632,PRETRIAL,Boyance,William,NULL,Male,Caucasian,11/12/43,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +57523,65742,59632,PRETRIAL,Boyance,William,NULL,Male,Caucasian,11/12/43,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +57481,65695,59587,PRETRIAL,Jean Jacques,Moise,NULL,Male,Other,11/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +57481,65695,59587,PRETRIAL,Jean Jacques,Moise,NULL,Male,Other,11/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +57481,65695,59587,PRETRIAL,Jean Jacques,Moise,NULL,Male,Other,11/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57506,65729,59619,PRETRIAL,TOWNSEND,ROSALIND,NULL,Female,African-American,03/28/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +57506,65729,59619,PRETRIAL,TOWNSEND,ROSALIND,NULL,Female,African-American,03/28/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +57506,65729,59619,PRETRIAL,TOWNSEND,ROSALIND,NULL,Female,African-American,03/28/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57539,65763,59652,PRETRIAL,COBB,HAVEARD,NULL,Male,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/24/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +57539,65763,59652,PRETRIAL,COBB,HAVEARD,NULL,Male,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/24/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +57539,65763,59652,PRETRIAL,COBB,HAVEARD,NULL,Male,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57550,65776,59663,Probation,Harris,Robert,NULL,Male,African-American,12/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/13 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +57550,65776,59663,Probation,Harris,Robert,NULL,Male,African-American,12/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +57550,65776,59663,Probation,Harris,Robert,NULL,Male,African-American,12/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57544,65768,59656,Probation,Montano,Jorge,Alberto,Male,Hispanic,09/16/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +57544,65768,59656,Probation,Montano,Jorge,Alberto,Male,Hispanic,09/16/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +57544,65768,59656,Probation,Montano,Jorge,Alberto,Male,Hispanic,09/16/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57546,65771,59659,Probation,Mendezbernal,Javier,NULL,Male,Hispanic,04/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +57546,65771,59659,Probation,Mendezbernal,Javier,NULL,Male,Hispanic,04/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +57546,65771,59659,Probation,Mendezbernal,Javier,NULL,Male,Hispanic,04/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57529,65750,59639,PRETRIAL,URREA,HELBERT,ANDREAS,Male,Hispanic,07/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +57529,65750,59639,PRETRIAL,URREA,HELBERT,ANDREAS,Male,Hispanic,07/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,4,High,8,Risk of Recidivism,0.18,8,High,New,1,0 +57529,65750,59639,PRETRIAL,URREA,HELBERT,ANDREAS,Male,Hispanic,07/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56937,65766,59024,PRETRIAL,Thompson,Raymond,NULL,Male,Caucasian,07/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,Copy,1,0 +56937,65766,59024,PRETRIAL,Thompson,Raymond,NULL,Male,Caucasian,07/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,Copy,1,0 +56937,65766,59024,PRETRIAL,Thompson,Raymond,NULL,Male,Caucasian,07/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +6768,65773,57794,PRETRIAL,BAUMGRTNER,WILLIAM,B,Male,Caucasian,07/27/87,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +6768,65773,57794,PRETRIAL,BAUMGRTNER,WILLIAM,B,Male,Caucasian,07/27/87,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +6768,65773,57794,PRETRIAL,BAUMGRTNER,WILLIAM,B,Male,Caucasian,07/27/87,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +57531,65752,59641,PRETRIAL,Roldan,Jose,Francisco,Male,Caucasian,01/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +57531,65752,59641,PRETRIAL,Roldan,Jose,Francisco,Male,Caucasian,01/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +57531,65752,59641,PRETRIAL,Roldan,Jose,Francisco,Male,Caucasian,01/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57536,65758,59647,PRETRIAL,Turner,Tamika,NULL,Female,African-American,07/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +57536,65758,59647,PRETRIAL,Turner,Tamika,NULL,Female,African-American,07/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +57536,65758,59647,PRETRIAL,Turner,Tamika,NULL,Female,African-American,07/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57554,65781,59667,Probation,gonzalez,ricardo,NULL,Male,Hispanic,09/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/24/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +57554,65781,59667,Probation,gonzalez,ricardo,NULL,Male,Hispanic,09/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/24/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +57554,65781,59667,Probation,gonzalez,ricardo,NULL,Male,Hispanic,09/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +24652,65760,59649,PRETRIAL,Archibald,James,NULL,Male,African-American,11/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +24652,65760,59649,PRETRIAL,Archibald,James,NULL,Male,African-American,11/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +24652,65760,59649,PRETRIAL,Archibald,James,NULL,Male,African-American,11/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57552,65779,59665,PRETRIAL,Fiora,Richard,NULL,Male,Caucasian,12/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +57552,65779,59665,PRETRIAL,Fiora,Richard,NULL,Male,Caucasian,12/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +57552,65779,59665,PRETRIAL,Fiora,Richard,NULL,Male,Caucasian,12/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +57558,65786,59672,PRETRIAL,Hall,Shane,NULL,Male,Caucasian,09/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +57558,65786,59672,PRETRIAL,Hall,Shane,NULL,Male,Caucasian,09/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +57558,65786,59672,PRETRIAL,Hall,Shane,NULL,Male,Caucasian,09/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +57555,65782,59668,PRETRIAL,Haberstroh,Carl,NULL,Male,Caucasian,07/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +57555,65782,59668,PRETRIAL,Haberstroh,Carl,NULL,Male,Caucasian,07/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +57555,65782,59668,PRETRIAL,Haberstroh,Carl,NULL,Male,Caucasian,07/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +57538,65761,59650,PRETRIAL,Feldman,Golan,NULL,Male,Caucasian,04/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/24/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +57538,65761,59650,PRETRIAL,Feldman,Golan,NULL,Male,Caucasian,04/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/24/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +57538,65761,59650,PRETRIAL,Feldman,Golan,NULL,Male,Caucasian,04/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57534,65756,59645,PRETRIAL,Goodwin,James,NULL,Male,African-American,12/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +57534,65756,59645,PRETRIAL,Goodwin,James,NULL,Male,African-American,12/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +57534,65756,59645,PRETRIAL,Goodwin,James,NULL,Male,African-American,12/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57551,65777,59664,Probation,Calvino,Oscar,NULL,Male,Hispanic,08/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +57551,65777,59664,Probation,Calvino,Oscar,NULL,Male,Hispanic,08/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +57551,65777,59664,Probation,Calvino,Oscar,NULL,Male,Hispanic,08/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +38397,65770,59658,PRETRIAL,BONNER,SCOTT,ROBERT,Female,Caucasian,10/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/24/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +38397,65770,59658,PRETRIAL,BONNER,SCOTT,ROBERT,Female,Caucasian,10/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/24/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +38397,65770,59658,PRETRIAL,BONNER,SCOTT,ROBERT,Female,Caucasian,10/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57556,65784,59670,PRETRIAL,Hinsch,Michael,NULL,Male,Caucasian,12/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +57556,65784,59670,PRETRIAL,Hinsch,Michael,NULL,Male,Caucasian,12/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +57556,65784,59670,PRETRIAL,Hinsch,Michael,NULL,Male,Caucasian,12/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,36,10,High,New,1,0 +57530,65751,59640,PRETRIAL,Sanchez,Javier,NULL,Male,Caucasian,05/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +57530,65751,59640,PRETRIAL,Sanchez,Javier,NULL,Male,Caucasian,05/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +57530,65751,59640,PRETRIAL,Sanchez,Javier,NULL,Male,Caucasian,05/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57537,65759,59648,PRETRIAL,ORTIZ,RICHARD,NULL,Male,Hispanic,07/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +57537,65759,59648,PRETRIAL,ORTIZ,RICHARD,NULL,Male,Hispanic,07/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +57537,65759,59648,PRETRIAL,ORTIZ,RICHARD,NULL,Male,Hispanic,07/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57543,65767,59655,PRETRIAL,DRAIN,ROGER,NULL,Male,African-American,06/18/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.19,4,Low,New,1,0 +57543,65767,59655,PRETRIAL,DRAIN,ROGER,NULL,Male,African-American,06/18/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +57543,65767,59655,PRETRIAL,DRAIN,ROGER,NULL,Male,African-American,06/18/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +57547,65772,59660,Probation,Babitz,Alan,Lee,Male,Caucasian,09/22/57,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/24/13 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +57547,65772,59660,Probation,Babitz,Alan,Lee,Male,Caucasian,09/22/57,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/24/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +57547,65772,59660,Probation,Babitz,Alan,Lee,Male,Caucasian,09/22/57,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57553,65780,59666,PRETRIAL,Jones,ervin,NULL,Male,African-American,10/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +57553,65780,59666,PRETRIAL,Jones,ervin,NULL,Male,African-American,10/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +57553,65780,59666,PRETRIAL,Jones,ervin,NULL,Male,African-American,10/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57540,65764,59653,PRETRIAL,Rodriguez,Matthew,NULL,Male,Hispanic,12/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/24/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +57540,65764,59653,PRETRIAL,Rodriguez,Matthew,NULL,Male,Hispanic,12/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/24/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +57540,65764,59653,PRETRIAL,Rodriguez,Matthew,NULL,Male,Hispanic,12/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57549,65775,59662,PRETRIAL,Jasmin,Joel,NULL,Male,African-American,02/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +57549,65775,59662,PRETRIAL,Jasmin,Joel,NULL,Male,African-American,02/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +57549,65775,59662,PRETRIAL,Jasmin,Joel,NULL,Male,African-American,02/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +39058,65754,59643,PRETRIAL,Moore,Emmett,NULL,Male,Caucasian,07/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +39058,65754,59643,PRETRIAL,Moore,Emmett,NULL,Male,Caucasian,07/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +39058,65754,59643,PRETRIAL,Moore,Emmett,NULL,Male,Caucasian,07/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +57557,65785,59671,PRETRIAL,CRAMER,RUSSELL,NULL,Male,Caucasian,01/17/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +57557,65785,59671,PRETRIAL,CRAMER,RUSSELL,NULL,Male,Caucasian,01/17/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +57557,65785,59671,PRETRIAL,CRAMER,RUSSELL,NULL,Male,Caucasian,01/17/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +57533,65755,59644,PRETRIAL,Carter,Bobbie,NULL,Male,African-American,01/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +57533,65755,59644,PRETRIAL,Carter,Bobbie,NULL,Male,African-American,01/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +57533,65755,59644,PRETRIAL,Carter,Bobbie,NULL,Male,African-American,01/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57545,65769,59657,Probation,ramnauth,pooranchand,NULL,Male,Other,04/23/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/24/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +57545,65769,59657,Probation,ramnauth,pooranchand,NULL,Male,Other,04/23/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/24/13 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +57545,65769,59657,Probation,ramnauth,pooranchand,NULL,Male,Other,04/23/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +44424,65762,59651,PRETRIAL,CLARK,ZAMOTH,WILLIAM,Male,African-American,08/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +44424,65762,59651,PRETRIAL,CLARK,ZAMOTH,WILLIAM,Male,African-American,08/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +44424,65762,59651,PRETRIAL,CLARK,ZAMOTH,WILLIAM,Male,African-American,08/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +2047,65783,59669,PRETRIAL,BROWN,VICTOR,NULL,Male,African-American,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,4,High,7,Risk of Violence,0,10,High,New,1,0 +2047,65783,59669,PRETRIAL,BROWN,VICTOR,NULL,Male,African-American,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,4,High,8,Risk of Recidivism,1.13,10,High,New,1,0 +2047,65783,59669,PRETRIAL,BROWN,VICTOR,NULL,Male,African-American,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57548,65774,59661,PRETRIAL,DONELSON,QWINTA,NULL,Male,African-American,06/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +57548,65774,59661,PRETRIAL,DONELSON,QWINTA,NULL,Male,African-American,06/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,9,High,New,1,0 +57548,65774,59661,PRETRIAL,DONELSON,QWINTA,NULL,Male,African-American,06/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +57535,65757,59646,PRETRIAL,Staggewise,Nicholas,NULL,Male,Caucasian,02/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-1.77,5,Medium,New,1,0 +57535,65757,59646,PRETRIAL,Staggewise,Nicholas,NULL,Male,Caucasian,02/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +57535,65757,59646,PRETRIAL,Staggewise,Nicholas,NULL,Male,Caucasian,02/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57532,65753,59642,PRETRIAL,Dickens,Janez,Shanice,Female,African-American,02/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +57532,65753,59642,PRETRIAL,Dickens,Janez,Shanice,Female,African-American,02/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +57532,65753,59642,PRETRIAL,Dickens,Janez,Shanice,Female,African-American,02/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57569,65804,59685,Probation,Taype,julio,NULL,Male,Hispanic,07/29/44,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/25/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +57569,65804,59685,Probation,Taype,julio,NULL,Male,Hispanic,07/29/44,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/25/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +57569,65804,59685,Probation,Taype,julio,NULL,Male,Hispanic,07/29/44,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56963,65799,59051,PRETRIAL,Campanile,Michael,NULL,Male,Caucasian,08/03/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,Copy,1,0 +56963,65799,59051,PRETRIAL,Campanile,Michael,NULL,Male,Caucasian,08/03/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,Copy,1,0 +56963,65799,59051,PRETRIAL,Campanile,Michael,NULL,Male,Caucasian,08/03/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +57573,65808,59689,Probation,couch,lawrence,NULL,Male,Caucasian,09/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +57573,65808,59689,Probation,couch,lawrence,NULL,Male,Caucasian,09/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +57573,65808,59689,Probation,couch,lawrence,NULL,Male,Caucasian,09/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +24330,65795,33696,PRETRIAL,MONDELUS,RAFAEL,NULL,Male,African-American,08/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,2,Medium,7,Risk of Violence,-2.85,2,Low,Copy,1,0 +24330,65795,33696,PRETRIAL,MONDELUS,RAFAEL,NULL,Male,African-American,08/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,Copy,1,0 +24330,65795,33696,PRETRIAL,MONDELUS,RAFAEL,NULL,Male,African-American,08/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +3857,65790,59675,PRETRIAL,TATE,DORRON,NULL,Male,African-American,04/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,4,High,7,Risk of Violence,-0.62,10,High,New,1,0 +3857,65790,59675,PRETRIAL,TATE,DORRON,NULL,Male,African-American,04/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,4,High,8,Risk of Recidivism,0.67,10,High,New,1,0 +3857,65790,59675,PRETRIAL,TATE,DORRON,NULL,Male,African-American,04/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57561,65792,59677,PRETRIAL,Kennon,Tatiana,NULL,Female,African-American,03/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +57561,65792,59677,PRETRIAL,Kennon,Tatiana,NULL,Female,African-American,03/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +57561,65792,59677,PRETRIAL,Kennon,Tatiana,NULL,Female,African-American,03/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +49349,65811,59692,PRETRIAL,BROWN,TAJ,NULL,Male,African-American,07/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +49349,65811,59692,PRETRIAL,BROWN,TAJ,NULL,Male,African-American,07/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +49349,65811,59692,PRETRIAL,BROWN,TAJ,NULL,Male,African-American,07/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57577,65814,59694,Probation,Harrell,OC,NULL,Male,African-American,01/07/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +57577,65814,59694,Probation,Harrell,OC,NULL,Male,African-American,01/07/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +57577,65814,59694,Probation,Harrell,OC,NULL,Male,African-American,01/07/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57562,65793,59678,PRETRIAL,LAMPARTER,JASSEN,LEE,Male,Caucasian,07/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +57562,65793,59678,PRETRIAL,LAMPARTER,JASSEN,LEE,Male,Caucasian,07/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +57562,65793,59678,PRETRIAL,LAMPARTER,JASSEN,LEE,Male,Caucasian,07/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57394,65801,59506,PRETRIAL,SCOTT,CHARLES,NULL,Male,African-American,10/01/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/25/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,Copy,1,0 +57394,65801,59506,PRETRIAL,SCOTT,CHARLES,NULL,Male,African-American,10/01/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/25/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,Copy,1,0 +57394,65801,59506,PRETRIAL,SCOTT,CHARLES,NULL,Male,African-American,10/01/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +57571,65806,59687,Probation,TYSON,MICHAEL,V,Male,African-American,01/04/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +57571,65806,59687,Probation,TYSON,MICHAEL,V,Male,African-American,01/04/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +57571,65806,59687,Probation,TYSON,MICHAEL,V,Male,African-American,01/04/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +57574,65809,59690,PRETRIAL,Swanson,Justin,NULL,Male,Caucasian,10/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +57574,65809,59690,PRETRIAL,Swanson,Justin,NULL,Male,Caucasian,10/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +57574,65809,59690,PRETRIAL,Swanson,Justin,NULL,Male,Caucasian,10/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57559,65788,59673,PRETRIAL,ELLIS,ANDREW,NULL,Male,African-American,06/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +57559,65788,59673,PRETRIAL,ELLIS,ANDREW,NULL,Male,African-American,06/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +57559,65788,59673,PRETRIAL,ELLIS,ANDREW,NULL,Male,African-American,06/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57564,65796,59680,PRETRIAL,roser,robert,NULL,Male,Caucasian,08/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +57564,65796,59680,PRETRIAL,roser,robert,NULL,Male,Caucasian,08/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +57564,65796,59680,PRETRIAL,roser,robert,NULL,Male,Caucasian,08/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57560,65791,59676,PRETRIAL,WILLIS,ANGEL,NULL,Female,African-American,05/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/25/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +57560,65791,59676,PRETRIAL,WILLIS,ANGEL,NULL,Female,African-American,05/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/25/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +57560,65791,59676,PRETRIAL,WILLIS,ANGEL,NULL,Female,African-American,05/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +32654,65798,45137,PRETRIAL,mccall,nicholas,NULL,Male,African-American,03/30/86,17,All Scales,Intake,English,Probation Violator,Probation,Single,9/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +32654,65798,45137,PRETRIAL,mccall,nicholas,NULL,Male,African-American,03/30/86,17,All Scales,Intake,English,Probation Violator,Probation,Single,9/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.11,10,High,New,1,0 +32654,65798,45137,PRETRIAL,mccall,nicholas,NULL,Male,African-American,03/30/86,17,All Scales,Intake,English,Probation Violator,Probation,Single,9/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57570,65805,59686,PRETRIAL,Blue,Eric,NULL,Male,Caucasian,01/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +57570,65805,59686,PRETRIAL,Blue,Eric,NULL,Male,Caucasian,01/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +57570,65805,59686,PRETRIAL,Blue,Eric,NULL,Male,Caucasian,01/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57566,65800,59682,Probation,Mora,Moises,Joel,Male,Hispanic,03/01/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/25/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +57566,65800,59682,Probation,Mora,Moises,Joel,Male,Hispanic,03/01/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/25/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +57566,65800,59682,Probation,Mora,Moises,Joel,Male,Hispanic,03/01/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57572,65807,59688,Probation,Marlow,Jeffrey,NULL,Male,Asian,09/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/25/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +57572,65807,59688,Probation,Marlow,Jeffrey,NULL,Male,Asian,09/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/25/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +57572,65807,59688,Probation,Marlow,Jeffrey,NULL,Male,Asian,09/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57568,65803,59684,Probation,Uriarte,Lester,NULL,Male,Caucasian,10/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +57568,65803,59684,Probation,Uriarte,Lester,NULL,Male,Caucasian,10/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +57568,65803,59684,Probation,Uriarte,Lester,NULL,Male,Caucasian,10/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57563,65794,59679,PRETRIAL,Williams,Anthony,NULL,Male,African-American,08/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.55,3,Low,New,1,0 +57563,65794,59679,PRETRIAL,Williams,Anthony,NULL,Male,African-American,08/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +57563,65794,59679,PRETRIAL,Williams,Anthony,NULL,Male,African-American,08/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57578,65815,59695,PRETRIAL,Gory,Nicholas,NULL,Male,Caucasian,02/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/13 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +57578,65815,59695,PRETRIAL,Gory,Nicholas,NULL,Male,Caucasian,02/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +57578,65815,59695,PRETRIAL,Gory,Nicholas,NULL,Male,Caucasian,02/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57567,65802,59683,Probation,RODRIGUEZ,STEVEN,NULL,Male,Hispanic,01/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/25/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +57567,65802,59683,Probation,RODRIGUEZ,STEVEN,NULL,Male,Hispanic,01/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/25/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +57567,65802,59683,Probation,RODRIGUEZ,STEVEN,NULL,Male,Hispanic,01/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +15379,65789,59674,PRETRIAL,COLLIER,RASEAN,LENORRIS,Male,African-American,08/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +15379,65789,59674,PRETRIAL,COLLIER,RASEAN,LENORRIS,Male,African-American,08/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +15379,65789,59674,PRETRIAL,COLLIER,RASEAN,LENORRIS,Male,African-American,08/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +57595,65839,59717,PRETRIAL,YUDER,VINCENTE,NULL,Male,Hispanic,03/22/74,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +57595,65839,59717,PRETRIAL,YUDER,VINCENTE,NULL,Male,Hispanic,03/22/74,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +57595,65839,59717,PRETRIAL,YUDER,VINCENTE,NULL,Male,Hispanic,03/22/74,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57606,65857,59732,Probation,puchalsky,william,NULL,Male,Caucasian,09/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +57606,65857,59732,Probation,puchalsky,william,NULL,Male,Caucasian,09/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +57606,65857,59732,Probation,puchalsky,william,NULL,Male,Caucasian,09/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57580,65818,59697,PRETRIAL,Guillen,Brian,james,Male,Caucasian,08/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +57580,65818,59697,PRETRIAL,Guillen,Brian,james,Male,Caucasian,08/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +57580,65818,59697,PRETRIAL,Guillen,Brian,james,Male,Caucasian,08/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57592,65836,59714,Probation,TOLTIN,SEAN,NULL,Female,African-American,02/23/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/26/13 0:00,2,Medium,7,Risk of Violence,-2.97,1,Low,New,1,0 +57592,65836,59714,Probation,TOLTIN,SEAN,NULL,Female,African-American,02/23/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +57592,65836,59714,Probation,TOLTIN,SEAN,NULL,Female,African-American,02/23/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57588,65831,59709,PRETRIAL,Jean,Rony,NULL,Male,Other,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +57588,65831,59709,PRETRIAL,Jean,Rony,NULL,Male,Other,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +57588,65831,59709,PRETRIAL,Jean,Rony,NULL,Male,Other,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57614,65865,59740,Probation,Gardner,Keon,Kevon,Male,African-American,10/08/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/26/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +57614,65865,59740,Probation,Gardner,Keon,Kevon,Male,African-American,10/08/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +57614,65865,59740,Probation,Gardner,Keon,Kevon,Male,African-American,10/08/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +45343,65844,59720,PRETRIAL,Ogden,Ezra,Christophe,Male,Caucasian,07/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +45343,65844,59720,PRETRIAL,Ogden,Ezra,Christophe,Male,Caucasian,07/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +45343,65844,59720,PRETRIAL,Ogden,Ezra,Christophe,Male,Caucasian,07/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +40687,65878,40310,PRETRIAL,Scott,Mcken,NULL,Male,African-American,04/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,4,High,7,Risk of Violence,-0.75,9,High,Copy,1,0 +40687,65878,40310,PRETRIAL,Scott,Mcken,NULL,Male,African-American,04/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,Copy,1,0 +40687,65878,40310,PRETRIAL,Scott,Mcken,NULL,Male,African-American,04/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +57601,65852,59727,Probation,veliky,brandon,NULL,Male,Caucasian,12/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +57601,65852,59727,Probation,veliky,brandon,NULL,Male,Caucasian,12/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +57601,65852,59727,Probation,veliky,brandon,NULL,Male,Caucasian,12/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57583,65823,59702,PRETRIAL,Graneau,Shaquile,NULL,Male,African-American,08/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,7,Risk of Violence,-1.34,7,Medium,New,1,0 +57583,65823,59702,PRETRIAL,Graneau,Shaquile,NULL,Male,African-American,08/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +57583,65823,59702,PRETRIAL,Graneau,Shaquile,NULL,Male,African-American,08/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57620,65873,59748,Probation,Ochart,john,NULL,Male,Hispanic,07/09/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/26/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +57620,65873,59748,Probation,Ochart,john,NULL,Male,Hispanic,07/09/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +57620,65873,59748,Probation,Ochart,john,NULL,Male,Hispanic,07/09/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57609,65860,59735,Probation,PITTS,RILEY,CORBIN,Male,Caucasian,07/02/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +57609,65860,59735,Probation,PITTS,RILEY,CORBIN,Male,Caucasian,07/02/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +57609,65860,59735,Probation,PITTS,RILEY,CORBIN,Male,Caucasian,07/02/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57021,65821,59700,PRETRIAL,Darby,Javon,NULL,Male,Other,09/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +57021,65821,59700,PRETRIAL,Darby,Javon,NULL,Male,Other,09/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +57021,65821,59700,PRETRIAL,Darby,Javon,NULL,Male,Other,09/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57603,65854,59729,Probation,Hernandez,Michael,NULL,Male,Hispanic,06/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +57603,65854,59729,Probation,Hernandez,Michael,NULL,Male,Hispanic,06/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +57603,65854,59729,Probation,Hernandez,Michael,NULL,Male,Hispanic,06/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +46676,65872,59747,PRETRIAL,Hopper,Daryle,NULL,Male,African-American,04/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,New,1,0 +46676,65872,59747,PRETRIAL,Hopper,Daryle,NULL,Male,African-American,04/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +46676,65872,59747,PRETRIAL,Hopper,Daryle,NULL,Male,African-American,04/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57617,65868,59743,Probation,Jackson,Jada,NULL,Female,African-American,03/17/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/26/13 0:00,2,Medium,7,Risk of Violence,-2.87,2,Low,New,1,0 +57617,65868,59743,Probation,Jackson,Jada,NULL,Female,African-American,03/17/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +57617,65868,59743,Probation,Jackson,Jada,NULL,Female,African-American,03/17/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +57622,65875,59750,PRETRIAL,FULLER,ANGELA,NULL,Female,Hispanic,12/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +57622,65875,59750,PRETRIAL,FULLER,ANGELA,NULL,Female,Hispanic,12/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +57622,65875,59750,PRETRIAL,FULLER,ANGELA,NULL,Female,Hispanic,12/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +14639,15110,14009,PRETRIAL,PERRY,SHAWANDA,LOVELLA,Female,African-American,06/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +14639,15110,14009,PRETRIAL,PERRY,SHAWANDA,LOVELLA,Female,African-American,06/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.1,8,High,New,1,0 +14639,15110,14009,PRETRIAL,PERRY,SHAWANDA,LOVELLA,Female,African-American,06/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57612,65863,59738,PRETRIAL,KURUVILLA,MICHAEL,NULL,Male,Other,06/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +57612,65863,59738,PRETRIAL,KURUVILLA,MICHAEL,NULL,Male,Other,06/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/13 0:00,1,Low,8,Risk of Recidivism,-2.62,1,Low,New,1,0 +57612,65863,59738,PRETRIAL,KURUVILLA,MICHAEL,NULL,Male,Other,06/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57589,65833,59711,PRETRIAL,Adler,Hilary,J,Male,Caucasian,11/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +57589,65833,59711,PRETRIAL,Adler,Hilary,J,Male,Caucasian,11/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +57589,65833,59711,PRETRIAL,Adler,Hilary,J,Male,Caucasian,11/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +33754,65842,32860,PRETRIAL,LEE,GREGORY,WAYNE,Male,African-American,10/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +33754,65842,32860,PRETRIAL,LEE,GREGORY,WAYNE,Male,African-American,10/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,Copy,1,0 +33754,65842,32860,PRETRIAL,LEE,GREGORY,WAYNE,Male,African-American,10/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +57581,65819,59698,PRETRIAL,Johnson,Tarell,NULL,Male,African-American,09/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +57581,65819,59698,PRETRIAL,Johnson,Tarell,NULL,Male,African-American,09/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +57581,65819,59698,PRETRIAL,Johnson,Tarell,NULL,Male,African-American,09/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57619,65870,59745,PRETRIAL,JOSEPH,HENRY,NULL,Male,African-American,12/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +57619,65870,59745,PRETRIAL,JOSEPH,HENRY,NULL,Male,African-American,12/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +57619,65870,59745,PRETRIAL,JOSEPH,HENRY,NULL,Male,African-American,12/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +49787,65828,59707,PRETRIAL,Thibault,Cody,William,Male,Caucasian,04/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.07,8,High,New,1,0 +49787,65828,59707,PRETRIAL,Thibault,Cody,William,Male,Caucasian,04/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +49787,65828,59707,PRETRIAL,Thibault,Cody,William,Male,Caucasian,04/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57598,65847,59723,PRETRIAL,Mompremier,Maxwell,NULL,Male,African-American,11/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/26/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +57598,65847,59723,PRETRIAL,Mompremier,Maxwell,NULL,Male,African-American,11/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/26/13 0:00,2,Medium,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +57598,65847,59723,PRETRIAL,Mompremier,Maxwell,NULL,Male,African-American,11/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +48067,65877,48736,Probation,Vause,Michael,NULL,Male,Caucasian,11/08/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,Copy,1,0 +48067,65877,48736,Probation,Vause,Michael,NULL,Male,Caucasian,11/08/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,Copy,1,0 +48067,65877,48736,Probation,Vause,Michael,NULL,Male,Caucasian,11/08/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +57585,65826,59705,PRETRIAL,Saver,Laura,NULL,Female,Caucasian,04/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +57585,65826,59705,PRETRIAL,Saver,Laura,NULL,Female,Caucasian,04/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +57585,65826,59705,PRETRIAL,Saver,Laura,NULL,Female,Caucasian,04/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57599,65849,59725,PRETRIAL,Hills,Rakesha,NULL,Female,African-American,04/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +57599,65849,59725,PRETRIAL,Hills,Rakesha,NULL,Female,African-American,04/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +57599,65849,59725,PRETRIAL,Hills,Rakesha,NULL,Female,African-American,04/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57605,65856,59731,Probation,Allen,Nance,NULL,Female,African-American,09/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +57605,65856,59731,Probation,Allen,Nance,NULL,Female,African-American,09/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +57605,65856,59731,Probation,Allen,Nance,NULL,Female,African-American,09/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +1476,65830,15127,PRETRIAL,LOVINSKY,AUDWIN,NULL,Male,African-American,06/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,Copy,1,0 +1476,65830,15127,PRETRIAL,LOVINSKY,AUDWIN,NULL,Male,African-American,06/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,Copy,1,0 +1476,65830,15127,PRETRIAL,LOVINSKY,AUDWIN,NULL,Male,African-American,06/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +56952,65843,59036,PRETRIAL,Benjamin,Anthony,NULL,Male,African-American,12/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/26/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,Copy,1,0 +56952,65843,59036,PRETRIAL,Benjamin,Anthony,NULL,Male,African-American,12/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,Copy,1,0 +56952,65843,59036,PRETRIAL,Benjamin,Anthony,NULL,Male,African-American,12/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +45848,65845,59721,PRETRIAL,MANNINO,MARK,A,Male,Caucasian,08/13/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/26/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +45848,65845,59721,PRETRIAL,MANNINO,MARK,A,Male,Caucasian,08/13/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +45848,65845,59721,PRETRIAL,MANNINO,MARK,A,Male,Caucasian,08/13/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57579,65817,59696,PRETRIAL,Durrant,Lindroy,NULL,Male,African-American,08/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +57579,65817,59696,PRETRIAL,Durrant,Lindroy,NULL,Male,African-American,08/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +57579,65817,59696,PRETRIAL,Durrant,Lindroy,NULL,Male,African-American,08/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57584,65824,59703,PRETRIAL,Cormier,Michael,NULL,Male,Caucasian,08/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +57584,65824,59703,PRETRIAL,Cormier,Michael,NULL,Male,Caucasian,08/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +57584,65824,59703,PRETRIAL,Cormier,Michael,NULL,Male,Caucasian,08/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +14639,65851,14009,PRETRIAL,PERRY,SHAWANDA,LOVELLA,Female,African-American,06/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,Copy,1,0 +14639,65851,14009,PRETRIAL,PERRY,SHAWANDA,LOVELLA,Female,African-American,06/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,Copy,1,0 +14639,65851,14009,PRETRIAL,PERRY,SHAWANDA,LOVELLA,Female,African-American,06/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +57607,65858,59733,PRETRIAL,Mascary,Wilner,NULL,Male,African-American,06/12/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +57607,65858,59733,PRETRIAL,Mascary,Wilner,NULL,Male,African-American,06/12/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +57607,65858,59733,PRETRIAL,Mascary,Wilner,NULL,Male,African-American,06/12/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57594,65838,59716,PRETRIAL,Smith,Louis,NULL,Male,African-American,11/24/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +57594,65838,59716,PRETRIAL,Smith,Louis,NULL,Male,African-American,11/24/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +57594,65838,59716,PRETRIAL,Smith,Louis,NULL,Male,African-American,11/24/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +782,65816,472,PRETRIAL,Adams,Kristen,NULL,Female,Caucasian,07/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,4,High,7,Risk of Violence,-0.91,9,High,Copy,1,0 +782,65816,472,PRETRIAL,Adams,Kristen,NULL,Female,Caucasian,07/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,4,High,8,Risk of Recidivism,0.48,10,High,Copy,1,0 +782,65816,472,PRETRIAL,Adams,Kristen,NULL,Female,Caucasian,07/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +57615,65866,59741,Probation,Reaves,Willie,NULL,Male,African-American,05/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +57615,65866,59741,Probation,Reaves,Willie,NULL,Male,African-American,05/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.9,10,High,New,1,0 +57615,65866,59741,Probation,Reaves,Willie,NULL,Male,African-American,05/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57596,65840,59718,Probation,Coleman,Cashani,NULL,Male,African-American,10/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,New,1,0 +57596,65840,59718,Probation,Coleman,Cashani,NULL,Male,African-American,10/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +57596,65840,59718,Probation,Coleman,Cashani,NULL,Male,African-American,10/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57621,65874,59749,Probation,Crespo,Ayinde,NULL,Male,African-American,07/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +57621,65874,59749,Probation,Crespo,Ayinde,NULL,Male,African-American,07/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +57621,65874,59749,Probation,Crespo,Ayinde,NULL,Male,African-American,07/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +57586,65827,59706,PRETRIAL,Eberhart,Melvin,NULL,Male,African-American,06/07/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +57586,65827,59706,PRETRIAL,Eberhart,Melvin,NULL,Male,African-American,06/07/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +57586,65827,59706,PRETRIAL,Eberhart,Melvin,NULL,Male,African-American,06/07/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57610,65861,59736,Probation,zapata,silvio,NULL,Male,Hispanic,11/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +57610,65861,59736,Probation,zapata,silvio,NULL,Male,Hispanic,11/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +57610,65861,59736,Probation,zapata,silvio,NULL,Male,Hispanic,11/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +11374,65832,59710,Probation,Woodard,Bianca,L,Female,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +11374,65832,59710,Probation,Woodard,Bianca,L,Female,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +11374,65832,59710,Probation,Woodard,Bianca,L,Female,African-American,02/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +5705,65822,59701,Probation,Irvin,Antwaun,Devon,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +5705,65822,59701,Probation,Irvin,Antwaun,Devon,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +5705,65822,59701,Probation,Irvin,Antwaun,Devon,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57591,65835,59713,PRETRIAL,Cooper,Demetrius,NULL,Male,African-American,03/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,9/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.05,8,High,New,1,0 +57591,65835,59713,PRETRIAL,Cooper,Demetrius,NULL,Male,African-American,03/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,9/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +57591,65835,59713,PRETRIAL,Cooper,Demetrius,NULL,Male,African-American,03/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,9/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +57602,65853,59728,Probation,Yarbrough,Neil,NULL,Male,Caucasian,01/03/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +57602,65853,59728,Probation,Yarbrough,Neil,NULL,Male,Caucasian,01/03/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +57602,65853,59728,Probation,Yarbrough,Neil,NULL,Male,Caucasian,01/03/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57611,65862,59737,Probation,Martinez Reyes,Rafael,NULL,Male,Hispanic,08/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +57611,65862,59737,Probation,Martinez Reyes,Rafael,NULL,Male,Hispanic,08/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +57611,65862,59737,Probation,Martinez Reyes,Rafael,NULL,Male,Hispanic,08/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57582,65820,59699,PRETRIAL,Camel,Lemariani,NULL,Male,African-American,09/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +57582,65820,59699,PRETRIAL,Camel,Lemariani,NULL,Male,African-American,09/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +57582,65820,59699,PRETRIAL,Camel,Lemariani,NULL,Male,African-American,09/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57604,65855,59730,Probation,JOHN,MICHAEL,NULL,Male,Caucasian,05/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +57604,65855,59730,Probation,JOHN,MICHAEL,NULL,Male,Caucasian,05/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +57604,65855,59730,Probation,JOHN,MICHAEL,NULL,Male,Caucasian,05/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +49092,65841,59719,Probation,Rivera,Joshua,NULL,Male,Hispanic,05/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +49092,65841,59719,Probation,Rivera,Joshua,NULL,Male,Hispanic,05/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +49092,65841,59719,Probation,Rivera,Joshua,NULL,Male,Hispanic,05/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +18144,65848,59724,PRETRIAL,young,henry,NULL,Male,African-American,12/08/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +18144,65848,59724,PRETRIAL,young,henry,NULL,Male,African-American,12/08/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +18144,65848,59724,PRETRIAL,young,henry,NULL,Male,African-American,12/08/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57587,65829,59708,PRETRIAL,Sheng,Bei,NULL,Female,Asian,09/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +57587,65829,59708,PRETRIAL,Sheng,Bei,NULL,Female,Asian,09/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +57587,65829,59708,PRETRIAL,Sheng,Bei,NULL,Female,Asian,09/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57597,65846,59722,Probation,Calinao,Matthew,NULL,Male,Caucasian,11/06/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/26/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +57597,65846,59722,Probation,Calinao,Matthew,NULL,Male,Caucasian,11/06/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +57597,65846,59722,Probation,Calinao,Matthew,NULL,Male,Caucasian,11/06/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57616,65867,59742,Probation,Giron,Nelson,NULL,Male,Hispanic,11/10/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +57616,65867,59742,Probation,Giron,Nelson,NULL,Male,Hispanic,11/10/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +57616,65867,59742,Probation,Giron,Nelson,NULL,Male,Hispanic,11/10/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +46482,65876,59751,PRETRIAL,Smith,Simon,NULL,Male,African-American,09/07/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +46482,65876,59751,PRETRIAL,Smith,Simon,NULL,Male,African-American,09/07/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +46482,65876,59751,PRETRIAL,Smith,Simon,NULL,Male,African-American,09/07/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +14962,65871,59746,PRETRIAL,PHILLIPS,JEREMY,NULL,Male,African-American,11/19/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,4,High,7,Risk of Violence,-0.46,10,High,New,1,0 +14962,65871,59746,PRETRIAL,PHILLIPS,JEREMY,NULL,Male,African-American,11/19/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +14962,65871,59746,PRETRIAL,PHILLIPS,JEREMY,NULL,Male,African-American,11/19/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +8293,65825,59704,PRETRIAL,WHITFIELD,BRANDON,NULL,Male,African-American,12/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +8293,65825,59704,PRETRIAL,WHITFIELD,BRANDON,NULL,Male,African-American,12/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +8293,65825,59704,PRETRIAL,WHITFIELD,BRANDON,NULL,Male,African-American,12/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57600,65850,59726,PRETRIAL,Monestime,Kenyardis,Vendrell,Male,African-American,01/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +57600,65850,59726,PRETRIAL,Monestime,Kenyardis,Vendrell,Male,African-American,01/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +57600,65850,59726,PRETRIAL,Monestime,Kenyardis,Vendrell,Male,African-American,01/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57613,65864,59739,Probation,KETTWIG,REINHOLD,JOSEPF,Male,Caucasian,11/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/26/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +57613,65864,59739,Probation,KETTWIG,REINHOLD,JOSEPF,Male,Caucasian,11/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/26/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +57613,65864,59739,Probation,KETTWIG,REINHOLD,JOSEPF,Male,Caucasian,11/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +29432,65918,59790,PRETRIAL,Soto,Jessica,Luisa,Female,Caucasian,12/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/27/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +29432,65918,59790,PRETRIAL,Soto,Jessica,Luisa,Female,Caucasian,12/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +29432,65918,59790,PRETRIAL,Soto,Jessica,Luisa,Female,Caucasian,12/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57628,65885,59757,PRETRIAL,Pintobarros,Cludio,Marcio,Male,Hispanic,05/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/27/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +57628,65885,59757,PRETRIAL,Pintobarros,Cludio,Marcio,Male,Hispanic,05/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +57628,65885,59757,PRETRIAL,Pintobarros,Cludio,Marcio,Male,Hispanic,05/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57665,65922,59794,PRETRIAL,Russell,Travis,NULL,Male,African-American,03/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +57665,65922,59794,PRETRIAL,Russell,Travis,NULL,Male,African-American,03/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +57665,65922,59794,PRETRIAL,Russell,Travis,NULL,Male,African-American,03/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57649,65901,59773,Probation,RAMOS,WILSON,NULL,Male,Hispanic,12/18/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/27/13 0:00,1,Low,7,Risk of Violence,-4.36,1,Low,New,1,0 +57649,65901,59773,Probation,RAMOS,WILSON,NULL,Male,Hispanic,12/18/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/27/13 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +57649,65901,59773,Probation,RAMOS,WILSON,NULL,Male,Hispanic,12/18/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57653,65906,59778,PRETRIAL,Lara,Scott,Fitzgerald,Male,Caucasian,03/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +57653,65906,59778,PRETRIAL,Lara,Scott,Fitzgerald,Male,Caucasian,03/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +57653,65906,59778,PRETRIAL,Lara,Scott,Fitzgerald,Male,Caucasian,03/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57624,65880,59753,PRETRIAL,Harris,Tiffany,NULL,Male,African-American,11/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +57624,65880,59753,PRETRIAL,Harris,Tiffany,NULL,Male,African-American,11/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +57624,65880,59753,PRETRIAL,Harris,Tiffany,NULL,Male,African-American,11/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57664,65920,59792,Probation,Walker,Adrumica,NULL,Female,African-American,12/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +57664,65920,59792,Probation,Walker,Adrumica,NULL,Female,African-American,12/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +57664,65920,59792,Probation,Walker,Adrumica,NULL,Female,African-American,12/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57656,65911,59783,PRETRIAL,Sasnett,Kevin,NULL,Male,Caucasian,01/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +57656,65911,59783,PRETRIAL,Sasnett,Kevin,NULL,Male,Caucasian,01/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +57656,65911,59783,PRETRIAL,Sasnett,Kevin,NULL,Male,Caucasian,01/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57659,65913,59785,Probation,doctor,patrick,NULL,Male,Native American,01/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +57659,65913,59785,Probation,doctor,patrick,NULL,Male,Native American,01/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,New,1,0 +57659,65913,59785,Probation,doctor,patrick,NULL,Male,Native American,01/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +53655,65883,55117,Probation,Saunders,Marquis,NULL,Male,African-American,03/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +53655,65883,55117,Probation,Saunders,Marquis,NULL,Male,African-American,03/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,Copy,1,0 +53655,65883,55117,Probation,Saunders,Marquis,NULL,Male,African-American,03/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +57635,65890,59762,Probation,Zalcberg,Tristan,David,Male,Caucasian,12/24/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +57635,65890,59762,Probation,Zalcberg,Tristan,David,Male,Caucasian,12/24/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +57635,65890,59762,Probation,Zalcberg,Tristan,David,Male,Caucasian,12/24/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57638,65892,59764,Probation,CAMPUZANO,TONY,NULL,Male,Hispanic,05/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +57638,65892,59764,Probation,CAMPUZANO,TONY,NULL,Male,Hispanic,05/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +57638,65892,59764,Probation,CAMPUZANO,TONY,NULL,Male,Hispanic,05/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57651,65903,59775,Probation,Cohen,Felipe,NULL,Male,Caucasian,08/30/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +57651,65903,59775,Probation,Cohen,Felipe,NULL,Male,Caucasian,08/30/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +57651,65903,59775,Probation,Cohen,Felipe,NULL,Male,Caucasian,08/30/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +47435,65921,59793,PRETRIAL,Munoz,Jessie,NULL,Male,African-American,11/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +47435,65921,59793,PRETRIAL,Munoz,Jessie,NULL,Male,African-American,11/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +47435,65921,59793,PRETRIAL,Munoz,Jessie,NULL,Male,African-American,11/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57626,65882,59755,PRETRIAL,Castillo,Alonso,NULL,Male,Caucasian,10/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +57626,65882,59755,PRETRIAL,Castillo,Alonso,NULL,Male,Caucasian,10/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +57626,65882,59755,PRETRIAL,Castillo,Alonso,NULL,Male,Caucasian,10/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57648,65900,59772,Probation,Eisenberg,gail,Lee,Female,Caucasian,11/18/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/27/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +57648,65900,59772,Probation,Eisenberg,gail,Lee,Female,Caucasian,11/18/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +57648,65900,59772,Probation,Eisenberg,gail,Lee,Female,Caucasian,11/18/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57641,65895,59767,PRETRIAL,Grice,Theo,NULL,Male,African-American,09/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +57641,65895,59767,PRETRIAL,Grice,Theo,NULL,Male,African-American,09/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +57641,65895,59767,PRETRIAL,Grice,Theo,NULL,Male,African-American,09/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57661,65916,59788,Probation,colbeck,jamilya,NULL,Male,Asian,07/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/27/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +57661,65916,59788,Probation,colbeck,jamilya,NULL,Male,Asian,07/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +57661,65916,59788,Probation,colbeck,jamilya,NULL,Male,Asian,07/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57630,65887,59759,PRETRIAL,Franklin,Jamar,NULL,Male,African-American,11/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +57630,65887,59759,PRETRIAL,Franklin,Jamar,NULL,Male,African-American,11/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +57630,65887,59759,PRETRIAL,Franklin,Jamar,NULL,Male,African-American,11/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57667,65924,59796,PRETRIAL,Long,Alonzo,NULL,Male,African-American,07/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +57667,65924,59796,PRETRIAL,Long,Alonzo,NULL,Male,African-American,07/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +57667,65924,59796,PRETRIAL,Long,Alonzo,NULL,Male,African-American,07/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57623,65879,59752,PRETRIAL,Dellinger,Sabrina,NULL,Female,African-American,12/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,2,Medium,7,Risk of Violence,-3.2,1,Low,New,1,0 +57623,65879,59752,PRETRIAL,Dellinger,Sabrina,NULL,Female,African-American,12/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +57623,65879,59752,PRETRIAL,Dellinger,Sabrina,NULL,Female,African-American,12/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57654,65905,59777,PRETRIAL,basham,jeffrey,NULL,Male,Caucasian,02/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/27/13 0:00,2,Medium,7,Risk of Violence,-2.77,2,Low,New,1,0 +57654,65905,59777,PRETRIAL,basham,jeffrey,NULL,Male,Caucasian,02/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +57654,65905,59777,PRETRIAL,basham,jeffrey,NULL,Male,Caucasian,02/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/27/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +57663,65919,59791,Probation,Hartness,Brian,Christopher,Male,Caucasian,09/16/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +57663,65919,59791,Probation,Hartness,Brian,Christopher,Male,Caucasian,09/16/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +57663,65919,59791,Probation,Hartness,Brian,Christopher,Male,Caucasian,09/16/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57627,65884,59756,PRETRIAL,Robinson,Jamil,NULL,Male,African-American,01/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +57627,65884,59756,PRETRIAL,Robinson,Jamil,NULL,Male,African-American,01/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +57627,65884,59756,PRETRIAL,Robinson,Jamil,NULL,Male,African-American,01/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57637,65891,59763,Probation,Hatch,Mary Ann,NULL,Female,Caucasian,08/30/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/27/13 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +57637,65891,59763,Probation,Hatch,Mary Ann,NULL,Female,Caucasian,08/30/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/27/13 0:00,1,Low,8,Risk of Recidivism,-2.64,1,Low,New,1,0 +57637,65891,59763,Probation,Hatch,Mary Ann,NULL,Female,Caucasian,08/30/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57657,65910,59782,Probation,Grandosgomez,Guadalupe,NULL,Female,Hispanic,07/25/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/27/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +57657,65910,59782,Probation,Grandosgomez,Guadalupe,NULL,Female,Hispanic,07/25/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +57657,65910,59782,Probation,Grandosgomez,Guadalupe,NULL,Female,Hispanic,07/25/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57634,65889,59761,Probation,EDGECOMBE,TARVEL,NULL,Male,African-American,10/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +57634,65889,59761,Probation,EDGECOMBE,TARVEL,NULL,Male,African-American,10/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +57634,65889,59761,Probation,EDGECOMBE,TARVEL,NULL,Male,African-American,10/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57639,65893,59765,Probation,Rodriguez,Roberto,NULL,Male,Hispanic,03/11/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +57639,65893,59765,Probation,Rodriguez,Roberto,NULL,Male,Hispanic,03/11/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +57639,65893,59765,Probation,Rodriguez,Roberto,NULL,Male,Hispanic,03/11/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +49306,65914,59786,Probation,Cornell,Jamie,Rodriguez,Male,Hispanic,04/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +49306,65914,59786,Probation,Cornell,Jamie,Rodriguez,Male,Hispanic,04/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +49306,65914,59786,Probation,Cornell,Jamie,Rodriguez,Male,Hispanic,04/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57640,65894,59766,Probation,Stealy,Roberta,NULL,Female,Caucasian,01/08/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/27/13 0:00,1,Low,7,Risk of Violence,-4.19,1,Low,New,1,0 +57640,65894,59766,Probation,Stealy,Roberta,NULL,Female,Caucasian,01/08/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/27/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +57640,65894,59766,Probation,Stealy,Roberta,NULL,Female,Caucasian,01/08/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57642,65896,59768,PRETRIAL,Nazaire,David,NULL,Male,African-American,02/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/27/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +57642,65896,59768,PRETRIAL,Nazaire,David,NULL,Male,African-American,02/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +57642,65896,59768,PRETRIAL,Nazaire,David,NULL,Male,African-American,02/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57625,65881,59754,PRETRIAL,Benites,Jose,Francisco,Male,Caucasian,09/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/27/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +57625,65881,59754,PRETRIAL,Benites,Jose,Francisco,Male,Caucasian,09/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +57625,65881,59754,PRETRIAL,Benites,Jose,Francisco,Male,Caucasian,09/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57660,65915,59787,Probation,Darling,Jeremiah,NULL,Male,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +57660,65915,59787,Probation,Darling,Jeremiah,NULL,Male,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +57660,65915,59787,Probation,Darling,Jeremiah,NULL,Male,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +27253,65909,59781,Probation,DEBEVITS,JOHN,NULL,Male,Caucasian,09/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/27/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +27253,65909,59781,Probation,DEBEVITS,JOHN,NULL,Male,Caucasian,09/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +27253,65909,59781,Probation,DEBEVITS,JOHN,NULL,Male,Caucasian,09/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57666,65923,59795,PRETRIAL,DEPALMA,MARK,NULL,Male,Caucasian,07/24/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +57666,65923,59795,PRETRIAL,DEPALMA,MARK,NULL,Male,Caucasian,07/24/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +57666,65923,59795,PRETRIAL,DEPALMA,MARK,NULL,Male,Caucasian,07/24/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57631,65888,59760,PRETRIAL,Mathis,Aubray,NULL,Male,African-American,08/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +57631,65888,59760,PRETRIAL,Mathis,Aubray,NULL,Male,African-American,08/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.82,10,High,New,1,0 +57631,65888,59760,PRETRIAL,Mathis,Aubray,NULL,Male,African-American,08/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57650,65902,59774,Probation,wilson-Santos,kathleen,NULL,Female,Caucasian,06/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/27/13 0:00,1,Low,7,Risk of Violence,-4.19,1,Low,New,1,0 +57650,65902,59774,Probation,wilson-Santos,kathleen,NULL,Female,Caucasian,06/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/27/13 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +57650,65902,59774,Probation,wilson-Santos,kathleen,NULL,Female,Caucasian,06/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57658,65912,59784,Probation,Montalvo,Ariel,NULL,Male,African-American,07/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +57658,65912,59784,Probation,Montalvo,Ariel,NULL,Male,African-American,07/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +57658,65912,59784,Probation,Montalvo,Ariel,NULL,Male,African-American,07/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57647,65899,59771,PRETRIAL,amos,antonio,NULL,Male,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.23,8,High,New,1,0 +57647,65899,59771,PRETRIAL,amos,antonio,NULL,Male,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +57647,65899,59771,PRETRIAL,amos,antonio,NULL,Male,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57629,65886,59758,PRETRIAL,Delinois,Herold,NULL,Male,Other,04/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +57629,65886,59758,PRETRIAL,Delinois,Herold,NULL,Male,Other,04/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +57629,65886,59758,PRETRIAL,Delinois,Herold,NULL,Male,Other,04/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57652,65904,59776,Probation,Mclandsborough,Donald,NULL,Male,Caucasian,08/23/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/27/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +57652,65904,59776,Probation,Mclandsborough,Donald,NULL,Male,Caucasian,08/23/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/27/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +57652,65904,59776,Probation,Mclandsborough,Donald,NULL,Male,Caucasian,08/23/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57655,65907,59779,PRETRIAL,PETIT,BRET,NULL,Male,Caucasian,05/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +57655,65907,59779,PRETRIAL,PETIT,BRET,NULL,Male,Caucasian,05/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +57655,65907,59779,PRETRIAL,PETIT,BRET,NULL,Male,Caucasian,05/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57668,65925,59797,PRETRIAL,Pagano,Franciso,NULL,Male,Caucasian,01/12/39,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +57668,65925,59797,PRETRIAL,Pagano,Franciso,NULL,Male,Caucasian,01/12/39,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +57668,65925,59797,PRETRIAL,Pagano,Franciso,NULL,Male,Caucasian,01/12/39,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57673,65933,59804,PRETRIAL,Abernath,Kelly,NULL,Female,Caucasian,11/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/28/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +57673,65933,59804,PRETRIAL,Abernath,Kelly,NULL,Female,Caucasian,11/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/28/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +57673,65933,59804,PRETRIAL,Abernath,Kelly,NULL,Female,Caucasian,11/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57671,65930,59801,PRETRIAL,Lundy,Sony,NULL,Male,Other,11/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/28/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +57671,65930,59801,PRETRIAL,Lundy,Sony,NULL,Male,Other,11/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/28/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +57671,65930,59801,PRETRIAL,Lundy,Sony,NULL,Male,Other,11/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57675,65935,59806,PRETRIAL,GOMEZ,ERIK,NULL,Male,Hispanic,08/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +57675,65935,59806,PRETRIAL,GOMEZ,ERIK,NULL,Male,Hispanic,08/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +57675,65935,59806,PRETRIAL,GOMEZ,ERIK,NULL,Male,Hispanic,08/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +17337,65931,59802,PRETRIAL,KNIGHTON,TOMMY,LEE,Male,African-Am,01/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,4,High,7,Risk of Violence,-0.69,9,High,New,1,0 +17337,65931,59802,PRETRIAL,KNIGHTON,TOMMY,LEE,Male,African-Am,01/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,4,High,8,Risk of Recidivism,0.86,10,High,New,1,0 +17337,65931,59802,PRETRIAL,KNIGHTON,TOMMY,LEE,Male,African-Am,01/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +57669,65926,59798,PRETRIAL,Flores,Luis,NULL,Male,Hispanic,09/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,4,High,7,Risk of Violence,-0.57,10,High,New,1,0 +57669,65926,59798,PRETRIAL,Flores,Luis,NULL,Male,Hispanic,09/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,New,1,0 +57669,65926,59798,PRETRIAL,Flores,Luis,NULL,Male,Hispanic,09/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57670,65928,59800,PRETRIAL,NORMAN,RUSSELL,JEROME,Male,Caucasian,06/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +57670,65928,59800,PRETRIAL,NORMAN,RUSSELL,JEROME,Male,Caucasian,06/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +57670,65928,59800,PRETRIAL,NORMAN,RUSSELL,JEROME,Male,Caucasian,06/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +42846,65929,59155,PRETRIAL,Owens,Velon,NULL,Male,African-American,01/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +42846,65929,59155,PRETRIAL,Owens,Velon,NULL,Male,African-American,01/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,Copy,1,0 +42846,65929,59155,PRETRIAL,Owens,Velon,NULL,Male,African-American,01/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +57674,65934,59805,PRETRIAL,HANSON,MERLITA,NULL,Female,African-American,01/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/28/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +57674,65934,59805,PRETRIAL,HANSON,MERLITA,NULL,Female,African-American,01/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/28/13 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +57674,65934,59805,PRETRIAL,HANSON,MERLITA,NULL,Female,African-American,01/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +18793,65927,59799,PRETRIAL,MONTANEZ,JHONNY,NULL,Male,Hispanic,11/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +18793,65927,59799,PRETRIAL,MONTANEZ,JHONNY,NULL,Male,Hispanic,11/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +18793,65927,59799,PRETRIAL,MONTANEZ,JHONNY,NULL,Male,Hispanic,11/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57672,65932,59803,PRETRIAL,Fairclough,Tyrel,NULL,Male,African-American,09/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,New,1,0 +57672,65932,59803,PRETRIAL,Fairclough,Tyrel,NULL,Male,African-American,09/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +57672,65932,59803,PRETRIAL,Fairclough,Tyrel,NULL,Male,African-American,09/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +8884,65943,8417,PRETRIAL,Waldrep,Chad,NULL,Male,Caucasian,05/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,Copy,1,0 +8884,65943,8417,PRETRIAL,Waldrep,Chad,NULL,Male,Caucasian,05/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,Copy,1,0 +8884,65943,8417,PRETRIAL,Waldrep,Chad,NULL,Male,Caucasian,05/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +8639,65936,59807,PRETRIAL,Sydnor,Michael,Trent,Male,African-American,08/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.65,9,High,New,1,0 +8639,65936,59807,PRETRIAL,Sydnor,Michael,Trent,Male,African-American,08/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +8639,65936,59807,PRETRIAL,Sydnor,Michael,Trent,Male,African-American,08/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57677,65939,59810,PRETRIAL,RODMAN,WILLIAM,GAGE,Male,Caucasian,09/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +57677,65939,59810,PRETRIAL,RODMAN,WILLIAM,GAGE,Male,Caucasian,09/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +57677,65939,59810,PRETRIAL,RODMAN,WILLIAM,GAGE,Male,Caucasian,09/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57678,65941,59811,PRETRIAL,STERNAL,WILLIAM,NULL,Male,Caucasian,07/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/29/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +57678,65941,59811,PRETRIAL,STERNAL,WILLIAM,NULL,Male,Caucasian,07/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/29/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +57678,65941,59811,PRETRIAL,STERNAL,WILLIAM,NULL,Male,Caucasian,07/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57679,65942,59812,PRETRIAL,SALTERS,CHRISTOPHER,NULL,Male,African-American,08/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/29/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +57679,65942,59812,PRETRIAL,SALTERS,CHRISTOPHER,NULL,Male,African-American,08/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/29/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +57679,65942,59812,PRETRIAL,SALTERS,CHRISTOPHER,NULL,Male,African-American,08/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57682,65945,59815,PRETRIAL,SALCEDO,PATRICK,NULL,Male,Caucasian,07/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +57682,65945,59815,PRETRIAL,SALCEDO,PATRICK,NULL,Male,Caucasian,07/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +57682,65945,59815,PRETRIAL,SALCEDO,PATRICK,NULL,Male,Caucasian,07/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +23992,65937,59808,PRETRIAL,Foster,Eddie,NULL,Male,African-American,04/08/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +23992,65937,59808,PRETRIAL,Foster,Eddie,NULL,Male,African-American,04/08/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +23992,65937,59808,PRETRIAL,Foster,Eddie,NULL,Male,African-American,04/08/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +57676,65938,59809,PRETRIAL,Saa,Christhian,NULL,Male,Hispanic,12/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +57676,65938,59809,PRETRIAL,Saa,Christhian,NULL,Male,Hispanic,12/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +57676,65938,59809,PRETRIAL,Saa,Christhian,NULL,Male,Hispanic,12/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57683,65946,59816,PRETRIAL,Jones,Antwane,D,Male,African-American,01/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,4,High,7,Risk of Violence,-0.55,10,High,New,1,0 +57683,65946,59816,PRETRIAL,Jones,Antwane,D,Male,African-American,01/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +57683,65946,59816,PRETRIAL,Jones,Antwane,D,Male,African-American,01/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +39434,65980,59844,PRETRIAL,DYER,CLIFTON,W,Male,Caucasian,10/27/89,17,All Scales,Intake,English,Other,Probation,Single,9/30/13 0:00,4,High,7,Risk of Violence,-0.56,10,High,Copy,1,0 +39434,65980,59844,PRETRIAL,DYER,CLIFTON,W,Male,Caucasian,10/27/89,17,All Scales,Intake,English,Other,Probation,Single,9/30/13 0:00,4,High,8,Risk of Recidivism,0.79,10,High,Copy,1,0 +39434,65980,59844,PRETRIAL,DYER,CLIFTON,W,Male,Caucasian,10/27/89,17,All Scales,Intake,English,Other,Probation,Single,9/30/13 0:00,4,High,18,Risk of Failure to Appear,25,5,Medium,Copy,1,0 +57701,65967,59836,Probation,Clark,Jimmie,Lee,Male,African-American,05/18/72,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/30/13 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +57701,65967,59836,Probation,Clark,Jimmie,Lee,Male,African-American,05/18/72,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +57701,65967,59836,Probation,Clark,Jimmie,Lee,Male,African-American,05/18/72,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/30/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +49873,66001,59866,PRETRIAL,Duncan,Almond,Rashas,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +49873,66001,59866,PRETRIAL,Duncan,Almond,Rashas,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +49873,66001,59866,PRETRIAL,Duncan,Almond,Rashas,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57731,66006,59870,Probation,Mccahera,rita,NULL,Female,Caucasian,02/02/68,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +57731,66006,59870,Probation,Mccahera,rita,NULL,Female,Caucasian,02/02/68,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +57731,66006,59870,Probation,Mccahera,rita,NULL,Female,Caucasian,02/02/68,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +56395,65993,58365,Probation,Rancourt,Yvon,NULL,Male,Caucasian,07/04/81,17,All Scales,Intake,English,Other,Probation,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +56395,65993,58365,Probation,Rancourt,Yvon,NULL,Male,Caucasian,07/04/81,17,All Scales,Intake,English,Other,Probation,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.27,5,Medium,New,1,0 +56395,65993,58365,Probation,Rancourt,Yvon,NULL,Male,Caucasian,07/04/81,17,All Scales,Intake,English,Other,Probation,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +57690,65954,59823,PRETRIAL,Taylor,Robert,NULL,Male,African-American,06/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +57690,65954,59823,PRETRIAL,Taylor,Robert,NULL,Male,African-American,06/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.01,10,High,New,1,0 +57690,65954,59823,PRETRIAL,Taylor,Robert,NULL,Male,African-American,06/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57704,65972,59841,PRETRIAL,picard,david,NULL,Male,Caucasian,03/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +57704,65972,59841,PRETRIAL,picard,david,NULL,Male,Caucasian,03/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +57704,65972,59841,PRETRIAL,picard,david,NULL,Male,Caucasian,03/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57714,65985,59851,Probation,Tafur,Ricardo,NULL,Male,Hispanic,06/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +57714,65985,59851,Probation,Tafur,Ricardo,NULL,Male,Hispanic,06/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +57714,65985,59851,Probation,Tafur,Ricardo,NULL,Male,Hispanic,06/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +49647,65988,59854,PRETRIAL,Dorsey,Trevor,NULL,Male,African-American,11/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/30/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +49647,65988,59854,PRETRIAL,Dorsey,Trevor,NULL,Male,African-American,11/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +49647,65988,59854,PRETRIAL,Dorsey,Trevor,NULL,Male,African-American,11/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57695,65959,59828,PRETRIAL,JOHNSON,ERICA,ERICA,Female,Caucasian,06/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +57695,65959,59828,PRETRIAL,JOHNSON,ERICA,ERICA,Female,Caucasian,06/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +57695,65959,59828,PRETRIAL,JOHNSON,ERICA,ERICA,Female,Caucasian,06/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57734,66009,59873,Probation,Richards,Damian,Leroy,Male,African-American,06/20/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +57734,66009,59873,Probation,Richards,Damian,Leroy,Male,African-American,06/20/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +57734,66009,59873,Probation,Richards,Damian,Leroy,Male,African-American,06/20/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57721,65996,59861,PRETRIAL,Alexander,Laute,NULL,Male,Caucasian,06/10/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +57721,65996,59861,PRETRIAL,Alexander,Laute,NULL,Male,Caucasian,06/10/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.19,5,Medium,New,1,0 +57721,65996,59861,PRETRIAL,Alexander,Laute,NULL,Male,Caucasian,06/10/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57687,65951,59820,PRETRIAL,MCPHERSON,ROBERT,NULL,Male,African-American,04/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +57687,65951,59820,PRETRIAL,MCPHERSON,ROBERT,NULL,Male,African-American,04/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +57687,65951,59820,PRETRIAL,MCPHERSON,ROBERT,NULL,Male,African-American,04/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57684,65947,59817,PRETRIAL,Lamons,Keylin,NULL,Male,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.99,9,High,New,1,0 +57684,65947,59817,PRETRIAL,Lamons,Keylin,NULL,Male,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +57684,65947,59817,PRETRIAL,Lamons,Keylin,NULL,Male,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57707,65977,59846,Probation,Johnson,Toriano,NULL,Male,African-American,02/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.88,2,Low,New,1,0 +57707,65977,59846,Probation,Johnson,Toriano,NULL,Male,African-American,02/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +57707,65977,59846,Probation,Johnson,Toriano,NULL,Male,African-American,02/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57686,65949,59819,PRETRIAL,REGG,NORMAN,NULL,Male,Caucasian,06/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +57686,65949,59819,PRETRIAL,REGG,NORMAN,NULL,Male,Caucasian,06/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +57686,65949,59819,PRETRIAL,REGG,NORMAN,NULL,Male,Caucasian,06/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57692,65956,59825,PRETRIAL,Salters,Valarie,NULL,Female,African-American,11/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/30/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +57692,65956,59825,PRETRIAL,Salters,Valarie,NULL,Female,African-American,11/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +57692,65956,59825,PRETRIAL,Salters,Valarie,NULL,Female,African-American,11/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57722,65998,59863,Probation,Box,Mitchell,NULL,Male,Caucasian,05/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +57722,65998,59863,Probation,Box,Mitchell,NULL,Male,Caucasian,05/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +57722,65998,59863,Probation,Box,Mitchell,NULL,Male,Caucasian,05/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57730,66005,59869,Probation,Gayeski,Jennifer,NULL,Female,Caucasian,01/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +57730,66005,59869,Probation,Gayeski,Jennifer,NULL,Female,Caucasian,01/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +57730,66005,59869,Probation,Gayeski,Jennifer,NULL,Female,Caucasian,01/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57700,65965,59834,Probation,blaNCO,PEDRO,NULL,Male,Caucasian,07/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/30/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +57700,65965,59834,Probation,blaNCO,PEDRO,NULL,Male,Caucasian,07/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +57700,65965,59834,Probation,blaNCO,PEDRO,NULL,Male,Caucasian,07/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57697,65961,59830,PRETRIAL,Holston,Andre,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +57697,65961,59830,PRETRIAL,Holston,Andre,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +57697,65961,59830,PRETRIAL,Holston,Andre,NULL,Male,African-American,03/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57713,65986,59852,PRETRIAL,owen,justin,NULL,Male,Caucasian,07/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +57713,65986,59852,PRETRIAL,owen,justin,NULL,Male,Caucasian,07/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +57713,65986,59852,PRETRIAL,owen,justin,NULL,Male,Caucasian,07/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57710,65982,59848,PRETRIAL,GIRALDO,CHRISTIAN,NULL,Male,Caucasian,11/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +57710,65982,59848,PRETRIAL,GIRALDO,CHRISTIAN,NULL,Male,Caucasian,11/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +57710,65982,59848,PRETRIAL,GIRALDO,CHRISTIAN,NULL,Male,Caucasian,11/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57726,66000,59865,Probation,Louissaint,Junior,NULL,Male,African-American,11/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +57726,66000,59865,Probation,Louissaint,Junior,NULL,Male,African-American,11/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +57726,66000,59865,Probation,Louissaint,Junior,NULL,Male,African-American,11/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57733,66007,59871,Probation,Oconnor,Kyle,NULL,Male,Caucasian,07/19/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +57733,66007,59871,Probation,Oconnor,Kyle,NULL,Male,Caucasian,07/19/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +57733,66007,59871,Probation,Oconnor,Kyle,NULL,Male,Caucasian,07/19/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57688,65952,59821,PRETRIAL,SIMPSON,ANPHERNY,MYCHEAL,Male,African-American,10/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +57688,65952,59821,PRETRIAL,SIMPSON,ANPHERNY,MYCHEAL,Male,African-American,10/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +57688,65952,59821,PRETRIAL,SIMPSON,ANPHERNY,MYCHEAL,Male,African-American,10/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57715,65987,59853,Probation,Blanco,Nery,NULL,Male,Hispanic,01/02/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/30/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +57715,65987,59853,Probation,Blanco,Nery,NULL,Male,Hispanic,01/02/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +57715,65987,59853,Probation,Blanco,Nery,NULL,Male,Hispanic,01/02/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +40963,65966,59835,PRETRIAL,brown,tevin,NULL,Male,African-American,12/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,4,High,7,Risk of Violence,-0.33,10,High,New,1,0 +40963,65966,59835,PRETRIAL,brown,tevin,NULL,Male,African-American,12/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,4,High,8,Risk of Recidivism,1.01,10,High,New,1,0 +40963,65966,59835,PRETRIAL,brown,tevin,NULL,Male,African-American,12/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57705,65973,59842,Probation,GODINEZ,MANUEL,NULL,Male,Hispanic,04/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +57705,65973,59842,Probation,GODINEZ,MANUEL,NULL,Male,Hispanic,04/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +57705,65973,59842,Probation,GODINEZ,MANUEL,NULL,Male,Hispanic,04/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57696,65960,59829,PRETRIAL,BUTING,WESTGARD,NULL,Male,Other,09/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +57696,65960,59829,PRETRIAL,BUTING,WESTGARD,NULL,Male,Other,09/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +57696,65960,59829,PRETRIAL,BUTING,WESTGARD,NULL,Male,Other,09/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57720,65994,59859,PRETRIAL,Ramos,Zulma,NULL,Female,Hispanic,04/29/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +57720,65994,59859,PRETRIAL,Ramos,Zulma,NULL,Female,Hispanic,04/29/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,New,1,0 +57720,65994,59859,PRETRIAL,Ramos,Zulma,NULL,Female,Hispanic,04/29/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57694,65958,59827,PRETRIAL,VARELA,LINA,NULL,Female,Caucasian,09/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +57694,65958,59827,PRETRIAL,VARELA,LINA,NULL,Female,Caucasian,09/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +57694,65958,59827,PRETRIAL,VARELA,LINA,NULL,Female,Caucasian,09/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57709,65981,59847,Probation,donlon,gary,NULL,Male,Caucasian,08/05/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +57709,65981,59847,Probation,donlon,gary,NULL,Male,Caucasian,08/05/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +57709,65981,59847,Probation,donlon,gary,NULL,Male,Caucasian,08/05/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56957,65079,59043,PRETRIAL,White,Dominque,NULL,Male,African-American,08/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +56957,65079,59043,PRETRIAL,White,Dominque,NULL,Male,African-American,08/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +56957,65079,59043,PRETRIAL,White,Dominque,NULL,Male,African-American,08/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57708,65976,59845,Probation,Grant,Fredrick,NULL,Male,Caucasian,03/06/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/30/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +57708,65976,59845,Probation,Grant,Fredrick,NULL,Male,Caucasian,03/06/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +57708,65976,59845,Probation,Grant,Fredrick,NULL,Male,Caucasian,03/06/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +39354,66010,59874,Probation,lathrop,thomas,NULL,Male,Caucasian,01/25/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/30/13 0:00,1,Low,7,Risk of Violence,-4.27,1,Low,New,1,0 +39354,66010,59874,Probation,lathrop,thomas,NULL,Male,Caucasian,01/25/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/30/13 0:00,1,Low,8,Risk of Recidivism,-2.61,1,Low,New,1,0 +39354,66010,59874,Probation,lathrop,thomas,NULL,Male,Caucasian,01/25/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57680,65963,59832,PRETRIAL,Blackwood,Lansberth,NULL,Male,Other,07/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +57680,65963,59832,PRETRIAL,Blackwood,Lansberth,NULL,Male,Other,07/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +57680,65963,59832,PRETRIAL,Blackwood,Lansberth,NULL,Male,Other,07/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57723,65997,59862,PRETRIAL,Emond,Ashley,NULL,Female,Caucasian,05/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +57723,65997,59862,PRETRIAL,Emond,Ashley,NULL,Female,Caucasian,05/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +57723,65997,59862,PRETRIAL,Emond,Ashley,NULL,Female,Caucasian,05/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +20922,65950,56894,PRETRIAL,Coney,Steven,James,Male,African-American,08/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,4,High,7,Risk of Violence,-1.07,8,High,Copy,1,0 +20922,65950,56894,PRETRIAL,Coney,Steven,James,Male,African-American,08/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,4,High,8,Risk of Recidivism,0.12,8,High,Copy,1,0 +20922,65950,56894,PRETRIAL,Coney,Steven,James,Male,African-American,08/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +57702,65968,59837,Probation,Smith,Shakela,NULL,Female,African-American,01/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +57702,65968,59837,Probation,Smith,Shakela,NULL,Female,African-American,01/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +57702,65968,59837,Probation,Smith,Shakela,NULL,Female,African-American,01/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57703,65971,59840,Probation,catano,hector,NULL,Male,Hispanic,03/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +57703,65971,59840,Probation,catano,hector,NULL,Male,Hispanic,03/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +57703,65971,59840,Probation,catano,hector,NULL,Male,Hispanic,03/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57717,65989,59855,PRETRIAL,Molino,Lenee,NULL,Female,Caucasian,05/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +57717,65989,59855,PRETRIAL,Molino,Lenee,NULL,Female,Caucasian,05/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +57717,65989,59855,PRETRIAL,Molino,Lenee,NULL,Female,Caucasian,05/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57685,65948,59818,PRETRIAL,Polimice,Junior,NULL,Male,African-American,09/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +57685,65948,59818,PRETRIAL,Polimice,Junior,NULL,Male,African-American,09/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +57685,65948,59818,PRETRIAL,Polimice,Junior,NULL,Male,African-American,09/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57691,65955,59824,PRETRIAL,DAVIDSON,ANDREA,MARIE,Female,African-American,10/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +57691,65955,59824,PRETRIAL,DAVIDSON,ANDREA,MARIE,Female,African-American,10/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,7,Medium,New,1,0 +57691,65955,59824,PRETRIAL,DAVIDSON,ANDREA,MARIE,Female,African-American,10/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +11206,65969,59838,PRETRIAL,MARTIN,ALLEN,JAMES,Male,Caucasian,03/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +11206,65969,59838,PRETRIAL,MARTIN,ALLEN,JAMES,Male,Caucasian,03/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +11206,65969,59838,PRETRIAL,MARTIN,ALLEN,JAMES,Male,Caucasian,03/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57711,65983,59849,PRETRIAL,COBY,JONATHAN,NULL,Male,African-American,05/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +57711,65983,59849,PRETRIAL,COBY,JONATHAN,NULL,Male,African-American,05/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +57711,65983,59849,PRETRIAL,COBY,JONATHAN,NULL,Male,African-American,05/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57718,65990,59856,PRETRIAL,Jones,Christopher,NULL,Male,African-American,08/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/30/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +57718,65990,59856,PRETRIAL,Jones,Christopher,NULL,Male,African-American,08/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +57718,65990,59856,PRETRIAL,Jones,Christopher,NULL,Male,African-American,08/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57719,65992,59858,Probation,diefenderfer,glen,NULL,Male,Caucasian,04/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +57719,65992,59858,Probation,diefenderfer,glen,NULL,Male,Caucasian,04/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +57719,65992,59858,Probation,diefenderfer,glen,NULL,Male,Caucasian,04/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57698,65962,59831,PRETRIAL,Rubin-Furtado,Michelle,NULL,Female,Caucasian,09/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,9/30/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +57698,65962,59831,PRETRIAL,Rubin-Furtado,Michelle,NULL,Female,Caucasian,09/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,9/30/13 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +57698,65962,59831,PRETRIAL,Rubin-Furtado,Michelle,NULL,Female,Caucasian,09/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57699,65964,59833,Probation,Martinez,Cesar,Julio,Male,Hispanic,07/30/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +57699,65964,59833,Probation,Martinez,Cesar,Julio,Male,Hispanic,07/30/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +57699,65964,59833,Probation,Martinez,Cesar,Julio,Male,Hispanic,07/30/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57735,66011,59875,PRETRIAL,Williams,Finest,NULL,Male,African-American,03/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/30/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +57735,66011,59875,PRETRIAL,Williams,Finest,NULL,Male,African-American,03/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +57735,66011,59875,PRETRIAL,Williams,Finest,NULL,Male,African-American,03/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57737,66013,59877,PRETRIAL,KHAN,SHOAIB,ZAMAN,Male,Other,08/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +57737,66013,59877,PRETRIAL,KHAN,SHOAIB,ZAMAN,Male,Other,08/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +57737,66013,59877,PRETRIAL,KHAN,SHOAIB,ZAMAN,Male,Other,08/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57689,65953,59822,PRETRIAL,Walls,Joseph,NULL,Male,Caucasian,09/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +57689,65953,59822,PRETRIAL,Walls,Joseph,NULL,Male,Caucasian,09/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +57689,65953,59822,PRETRIAL,Walls,Joseph,NULL,Male,Caucasian,09/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57729,66004,59868,Probation,Lopez,Carlos,NULL,Male,Hispanic,03/03/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/30/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +57729,66004,59868,Probation,Lopez,Carlos,NULL,Male,Hispanic,03/03/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/30/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +57729,66004,59868,Probation,Lopez,Carlos,NULL,Male,Hispanic,03/03/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57693,65957,59826,PRETRIAL,BRADLEY,BRIAN,NULL,Male,African-American,05/11/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +57693,65957,59826,PRETRIAL,BRADLEY,BRIAN,NULL,Male,African-American,05/11/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +57693,65957,59826,PRETRIAL,BRADLEY,BRIAN,NULL,Male,African-American,05/11/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +48786,65995,59860,PRETRIAL,SOSA,MICHAEL,ALEXANDER,Male,Caucasian,07/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +48786,65995,59860,PRETRIAL,SOSA,MICHAEL,ALEXANDER,Male,Caucasian,07/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +48786,65995,59860,PRETRIAL,SOSA,MICHAEL,ALEXANDER,Male,Caucasian,07/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57706,65974,59843,PRETRIAL,Patterson,Therese,V,Male,Caucasian,08/20/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/30/13 0:00,1,Low,7,Risk of Violence,-4.53,1,Low,New,1,0 +57706,65974,59843,PRETRIAL,Patterson,Therese,V,Male,Caucasian,08/20/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/30/13 0:00,1,Low,8,Risk of Recidivism,-2.83,1,Low,New,1,0 +57706,65974,59843,PRETRIAL,Patterson,Therese,V,Male,Caucasian,08/20/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57732,66008,59872,PRETRIAL,JONES,CASEY,NULL,Male,African-American,10/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/30/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +57732,66008,59872,PRETRIAL,JONES,CASEY,NULL,Male,African-American,10/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/30/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +57732,66008,59872,PRETRIAL,JONES,CASEY,NULL,Male,African-American,10/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/30/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57749,66029,59890,Probation,FASULO,ANTHONY,NULL,Male,Hispanic,05/06/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +57749,66029,59890,Probation,FASULO,ANTHONY,NULL,Male,Hispanic,05/06/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +57749,66029,59890,Probation,FASULO,ANTHONY,NULL,Male,Hispanic,05/06/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +28538,66046,59904,PRETRIAL,Crespo,Samuel,F,Male,Caucasian,06/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/1/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +28538,66046,59904,PRETRIAL,Crespo,Samuel,F,Male,Caucasian,06/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/1/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +28538,66046,59904,PRETRIAL,Crespo,Samuel,F,Male,Caucasian,06/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +9264,42731,39091,PRETRIAL,WHIPPLE,ADRIAN,MARNEL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/1/13 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +9264,42731,39091,PRETRIAL,WHIPPLE,ADRIAN,MARNEL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/1/13 0:00,4,High,8,Risk of Recidivism,0.54,9,High,New,1,0 +9264,42731,39091,PRETRIAL,WHIPPLE,ADRIAN,MARNEL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/1/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +57132,66025,59234,PRETRIAL,FRANCOIS,KELOS,NULL,Male,African-American,02/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,Copy,1,0 +57132,66025,59234,PRETRIAL,FRANCOIS,KELOS,NULL,Male,African-American,02/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,Copy,1,0 +57132,66025,59234,PRETRIAL,FRANCOIS,KELOS,NULL,Male,African-American,02/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +23661,66050,59780,PRETRIAL,Cotilla,Reben,E,Male,Caucasian,05/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,4,High,7,Risk of Violence,-1.22,8,High,Copy,1,0 +23661,66050,59780,PRETRIAL,Cotilla,Reben,E,Male,Caucasian,05/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,4,High,8,Risk of Recidivism,0.37,9,High,Copy,1,0 +23661,66050,59780,PRETRIAL,Cotilla,Reben,E,Male,Caucasian,05/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +57742,66020,59883,PRETRIAL,Corbin,Everett,Messiah,Male,African-American,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,4,High,7,Risk of Violence,-1.23,8,High,New,1,0 +57742,66020,59883,PRETRIAL,Corbin,Everett,Messiah,Male,African-American,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,4,High,8,Risk of Recidivism,0.71,10,High,New,1,0 +57742,66020,59883,PRETRIAL,Corbin,Everett,Messiah,Male,African-American,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +46285,66055,46675,PRETRIAL,Johnson,Keith,NULL,Male,African-American,10/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,Copy,1,0 +46285,66055,46675,PRETRIAL,Johnson,Keith,NULL,Male,African-American,10/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,Copy,1,0 +46285,66055,46675,PRETRIAL,Johnson,Keith,NULL,Male,African-American,10/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +57752,66034,59895,Probation,ross,amanda,NULL,Female,Caucasian,02/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +57752,66034,59895,Probation,ross,amanda,NULL,Female,Caucasian,02/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +57752,66034,59895,Probation,ross,amanda,NULL,Female,Caucasian,02/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57761,66041,59899,DRRD,Peatenlane,Teias,Treyvier,Male,African-American,07/02/93,17,All Scales,Intake,English,Post Sentence,Parole,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +57761,66041,59899,DRRD,Peatenlane,Teias,Treyvier,Male,African-American,07/02/93,17,All Scales,Intake,English,Post Sentence,Parole,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-0.31,5,Medium,New,1,0 +57761,66041,59899,DRRD,Peatenlane,Teias,Treyvier,Male,African-American,07/02/93,17,All Scales,Intake,English,Post Sentence,Parole,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57765,66048,59906,PRETRIAL,vanessa,Cardellaadams,NULL,Female,Caucasian,06/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +57765,66048,59906,PRETRIAL,vanessa,Cardellaadams,NULL,Female,Caucasian,06/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +57765,66048,59906,PRETRIAL,vanessa,Cardellaadams,NULL,Female,Caucasian,06/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51620,66036,52814,PRETRIAL,ONEAL,JENNIFER,NULL,Female,African-American,11/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,Copy,1,0 +51620,66036,52814,PRETRIAL,ONEAL,JENNIFER,NULL,Female,African-American,11/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,Copy,1,0 +51620,66036,52814,PRETRIAL,ONEAL,JENNIFER,NULL,Female,African-American,11/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +57758,66039,59898,PRETRIAL,LATHAM,JUDY,NULL,Female,Caucasian,11/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +57758,66039,59898,PRETRIAL,LATHAM,JUDY,NULL,Female,Caucasian,11/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +57758,66039,59898,PRETRIAL,LATHAM,JUDY,NULL,Female,Caucasian,11/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57741,66018,59881,PRETRIAL,Harris,Austin,NULL,Male,Caucasian,07/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +57741,66018,59881,PRETRIAL,Harris,Austin,NULL,Male,Caucasian,07/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +57741,66018,59881,PRETRIAL,Harris,Austin,NULL,Male,Caucasian,07/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50299,66044,59902,PRETRIAL,atkinson,andrew,NULL,Male,Caucasian,09/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +50299,66044,59902,PRETRIAL,atkinson,andrew,NULL,Male,Caucasian,09/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +50299,66044,59902,PRETRIAL,atkinson,andrew,NULL,Male,Caucasian,09/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51620,58122,52814,PRETRIAL,ONEAL,JENNIFER,NULL,Female,African-American,11/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +51620,58122,52814,PRETRIAL,ONEAL,JENNIFER,NULL,Female,African-American,11/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +51620,58122,52814,PRETRIAL,ONEAL,JENNIFER,NULL,Female,African-American,11/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57739,66015,59879,PRETRIAL,Harrigan,Crystal,Colette,Female,African-American,01/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +57739,66015,59879,PRETRIAL,Harrigan,Crystal,Colette,Female,African-American,01/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +57739,66015,59879,PRETRIAL,Harrigan,Crystal,Colette,Female,African-American,01/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57744,66023,59886,PRETRIAL,Philus,Johnny,NULL,Male,African-American,11/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +57744,66023,59886,PRETRIAL,Philus,Johnny,NULL,Male,African-American,11/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +57744,66023,59886,PRETRIAL,Philus,Johnny,NULL,Male,African-American,11/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57767,66052,59908,Probation,Gordillo,Etna,NULL,Female,Hispanic,09/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +57767,66052,59908,Probation,Gordillo,Etna,NULL,Female,Hispanic,09/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +57767,66052,59908,Probation,Gordillo,Etna,NULL,Female,Hispanic,09/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57743,66021,59884,PRETRIAL,StHubert,Wadsen,NULL,Male,African-American,07/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +57743,66021,59884,PRETRIAL,StHubert,Wadsen,NULL,Male,African-American,07/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +57743,66021,59884,PRETRIAL,StHubert,Wadsen,NULL,Male,African-American,07/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +45582,66054,59910,PRETRIAL,CID,VARINIA,NULL,Female,Caucasian,06/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +45582,66054,59910,PRETRIAL,CID,VARINIA,NULL,Female,Caucasian,06/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +45582,66054,59910,PRETRIAL,CID,VARINIA,NULL,Female,Caucasian,06/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +9264,66033,59894,PRETRIAL,WHIPPLE,ADRIAN,MARNEL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +9264,66033,59894,PRETRIAL,WHIPPLE,ADRIAN,MARNEL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,4,High,8,Risk of Recidivism,0.48,9,High,New,1,0 +9264,66033,59894,PRETRIAL,WHIPPLE,ADRIAN,MARNEL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +57762,66042,59900,PRETRIAL,WRIGHT,SHERISE,NULL,Female,African-American,01/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +57762,66042,59900,PRETRIAL,WRIGHT,SHERISE,NULL,Female,African-American,01/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +57762,66042,59900,PRETRIAL,WRIGHT,SHERISE,NULL,Female,African-American,01/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57738,66019,59882,PRETRIAL,MCCANN,TIMOTHY,NULL,Male,Caucasian,05/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +57738,66019,59882,PRETRIAL,MCCANN,TIMOTHY,NULL,Male,Caucasian,05/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +57738,66019,59882,PRETRIAL,MCCANN,TIMOTHY,NULL,Male,Caucasian,05/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57590,66056,59712,PRETRIAL,Gross,Dale,NULL,Male,Caucasian,12/21/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,Copy,1,0 +57590,66056,59712,PRETRIAL,Gross,Dale,NULL,Male,Caucasian,12/21/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,Copy,1,0 +57590,66056,59712,PRETRIAL,Gross,Dale,NULL,Male,Caucasian,12/21/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +45342,49994,45574,PRETRIAL,Valcourt,Jean,NULL,Male,African-American,03/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +45342,49994,45574,PRETRIAL,Valcourt,Jean,NULL,Male,African-American,03/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +45342,49994,45574,PRETRIAL,Valcourt,Jean,NULL,Male,African-American,03/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57645,66028,59770,PRETRIAL,BURKLAND,MICHAEL,NULL,Male,Caucasian,09/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,Copy,1,0 +57645,66028,59770,PRETRIAL,BURKLAND,MICHAEL,NULL,Male,Caucasian,09/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,Copy,1,0 +57645,66028,59770,PRETRIAL,BURKLAND,MICHAEL,NULL,Male,Caucasian,09/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +57764,66047,59905,PRETRIAL,Zepeda,Fausto,Gerardo,Male,Hispanic,06/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/1/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +57764,66047,59905,PRETRIAL,Zepeda,Fausto,Gerardo,Male,Hispanic,06/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +57764,66047,59905,PRETRIAL,Zepeda,Fausto,Gerardo,Male,Hispanic,06/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +49532,66017,50394,PRETRIAL,Blagman,Latif,NULL,Male,African-American,04/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,Copy,1,0 +49532,66017,50394,PRETRIAL,Blagman,Latif,NULL,Male,African-American,04/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,Copy,1,0 +49532,66017,50394,PRETRIAL,Blagman,Latif,NULL,Male,African-American,04/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +57745,66024,59887,PRETRIAL,WATKINS,JANICE,NULL,Female,African-American,10/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,7,Risk of Violence,-1.39,7,Medium,New,1,0 +57745,66024,59887,PRETRIAL,WATKINS,JANICE,NULL,Female,African-American,10/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +57745,66024,59887,PRETRIAL,WATKINS,JANICE,NULL,Female,African-American,10/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51273,66051,59907,PRETRIAL,Fletcher,Kalif,NULL,Male,African-American,06/07/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/1/13 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +51273,66051,59907,PRETRIAL,Fletcher,Kalif,NULL,Male,African-American,06/07/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/1/13 0:00,4,High,8,Risk of Recidivism,0.63,10,High,New,1,0 +51273,66051,59907,PRETRIAL,Fletcher,Kalif,NULL,Male,African-American,06/07/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/1/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57750,66030,59891,Probation,Jochim,Eric,NULL,Male,Caucasian,06/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +57750,66030,59891,Probation,Jochim,Eric,NULL,Male,Caucasian,06/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +57750,66030,59891,Probation,Jochim,Eric,NULL,Male,Caucasian,06/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57763,66045,59903,Probation,brownlee,daphne,NULL,Female,African-American,12/06/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +57763,66045,59903,Probation,brownlee,daphne,NULL,Female,African-American,12/06/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.92,10,High,New,1,0 +57763,66045,59903,Probation,brownlee,daphne,NULL,Female,African-American,12/06/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +57740,66016,59880,PRETRIAL,Hernandez,Angel,NULL,Male,Hispanic,09/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +57740,66016,59880,PRETRIAL,Hernandez,Angel,NULL,Male,Hispanic,09/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +57740,66016,59880,PRETRIAL,Hernandez,Angel,NULL,Male,Hispanic,09/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57756,66037,59896,Probation,Govern,Jacob,NULL,Male,Caucasian,12/08/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +57756,66037,59896,Probation,Govern,Jacob,NULL,Male,Caucasian,12/08/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +57756,66037,59896,Probation,Govern,Jacob,NULL,Male,Caucasian,12/08/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57757,66038,59897,Probation,ROFFE,RAPHAEL,NULL,Male,Caucasian,01/12/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/1/13 0:00,1,Low,7,Risk of Violence,-4.34,1,Low,New,1,0 +57757,66038,59897,Probation,ROFFE,RAPHAEL,NULL,Male,Caucasian,01/12/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/1/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +57757,66038,59897,Probation,ROFFE,RAPHAEL,NULL,Male,Caucasian,01/12/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +27249,66022,59885,PRETRIAL,BLISS,TYRONE,NULL,Male,African-American,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +27249,66022,59885,PRETRIAL,BLISS,TYRONE,NULL,Male,African-American,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +27249,66022,59885,PRETRIAL,BLISS,TYRONE,NULL,Male,African-American,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57768,66053,59909,Probation,Margri,Grace,Margaret,Female,Caucasian,07/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/1/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +57768,66053,59909,Probation,Margri,Grace,Margaret,Female,Caucasian,07/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +57768,66053,59909,Probation,Margri,Grace,Margaret,Female,Caucasian,07/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57751,66032,59893,Probation,Suarezmartinez,Angel,NULL,Male,Hispanic,06/26/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +57751,66032,59893,Probation,Suarezmartinez,Angel,NULL,Male,Hispanic,06/26/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +57751,66032,59893,Probation,Suarezmartinez,Angel,NULL,Male,Hispanic,06/26/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +37772,66043,59901,PRETRIAL,Thompson,Keon,NULL,Male,African-American,07/03/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/1/13 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +37772,66043,59901,PRETRIAL,Thompson,Keon,NULL,Male,African-American,07/03/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/1/13 0:00,4,High,8,Risk of Recidivism,0.55,9,High,New,1,0 +37772,66043,59901,PRETRIAL,Thompson,Keon,NULL,Male,African-American,07/03/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/1/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51620,66035,52814,PRETRIAL,ONEAL,JENNIFER,NULL,Female,African-American,11/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,Copy,1,0 +51620,66035,52814,PRETRIAL,ONEAL,JENNIFER,NULL,Female,African-American,11/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,Copy,1,0 +51620,66035,52814,PRETRIAL,ONEAL,JENNIFER,NULL,Female,African-American,11/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +57507,66040,59618,PRETRIAL,Evenson,Eric,NULL,Male,Caucasian,07/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,Copy,1,0 +57507,66040,59618,PRETRIAL,Evenson,Eric,NULL,Male,Caucasian,07/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +57507,66040,59618,PRETRIAL,Evenson,Eric,NULL,Male,Caucasian,07/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +57738,66014,59878,PRETRIAL,MCCANN,TIMOTHY,NULL,Male,Caucasian,05/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +57738,66014,59878,PRETRIAL,MCCANN,TIMOTHY,NULL,Male,Caucasian,05/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +57738,66014,59878,PRETRIAL,MCCANN,TIMOTHY,NULL,Male,Caucasian,05/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57747,66027,59889,PRETRIAL,castillo,vicky,NULL,Female,Caucasian,10/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/1/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +57747,66027,59889,PRETRIAL,castillo,vicky,NULL,Female,Caucasian,10/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/1/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +57747,66027,59889,PRETRIAL,castillo,vicky,NULL,Female,Caucasian,10/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57773,66061,59915,PRETRIAL,Jones,Jamal,Tarrell,Male,African-American,03/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +57773,66061,59915,PRETRIAL,Jones,Jamal,Tarrell,Male,African-American,03/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +57773,66061,59915,PRETRIAL,Jones,Jamal,Tarrell,Male,African-American,03/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57788,66074,59925,PRETRIAL,Wilson,Steven,Derrick,Male,African-American,03/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/2/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +57788,66074,59925,PRETRIAL,Wilson,Steven,Derrick,Male,African-American,03/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/2/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +57788,66074,59925,PRETRIAL,Wilson,Steven,Derrick,Male,African-American,03/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57793,66082,59932,Probation,Hernandez,Mauricio,NULL,Male,Hispanic,07/04/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/2/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +57793,66082,59932,Probation,Hernandez,Mauricio,NULL,Male,Hispanic,07/04/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/2/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +57793,66082,59932,Probation,Hernandez,Mauricio,NULL,Male,Hispanic,07/04/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57796,66087,59937,PRETRIAL,Green,Tammy,NULL,Female,Caucasian,07/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +57796,66087,59937,PRETRIAL,Green,Tammy,NULL,Female,Caucasian,07/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +57796,66087,59937,PRETRIAL,Green,Tammy,NULL,Female,Caucasian,07/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57771,66059,59913,PRETRIAL,KOLISKE,STEVEN,NULL,Male,Caucasian,05/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +57771,66059,59913,PRETRIAL,KOLISKE,STEVEN,NULL,Male,Caucasian,05/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +57771,66059,59913,PRETRIAL,KOLISKE,STEVEN,NULL,Male,Caucasian,05/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57783,66066,59920,PRETRIAL,TUCKER,LATAVYIA,JAQUEL,Female,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +57783,66066,59920,PRETRIAL,TUCKER,LATAVYIA,JAQUEL,Female,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +57783,66066,59920,PRETRIAL,TUCKER,LATAVYIA,JAQUEL,Female,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +49909,66079,59929,PRETRIAL,SCREEN,PATRICK,EDWARD LEE,Male,African-American,04/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +49909,66079,59929,PRETRIAL,SCREEN,PATRICK,EDWARD LEE,Male,African-American,04/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +49909,66079,59929,PRETRIAL,SCREEN,PATRICK,EDWARD LEE,Male,African-American,04/19/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57770,66058,59912,PRETRIAL,Honewell,Timar,Udell,Male,African-American,11/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +57770,66058,59912,PRETRIAL,Honewell,Timar,Udell,Male,African-American,11/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +57770,66058,59912,PRETRIAL,Honewell,Timar,Udell,Male,African-American,11/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57790,66077,59927,Probation,ALTIMAR,JOSEPH,M,Male,Caucasian,03/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +57790,66077,59927,Probation,ALTIMAR,JOSEPH,M,Male,Caucasian,03/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +57790,66077,59927,Probation,ALTIMAR,JOSEPH,M,Male,Caucasian,03/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57260,66070,59355,PRETRIAL,Sapp,Benjamin,NULL,Male,African-American,01/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/2/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,Copy,1,0 +57260,66070,59355,PRETRIAL,Sapp,Benjamin,NULL,Male,African-American,01/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/2/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,Copy,1,0 +57260,66070,59355,PRETRIAL,Sapp,Benjamin,NULL,Male,African-American,01/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +23381,66084,59934,PRETRIAL,Colas,Daniel,NULL,Male,African-American,09/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.38,3,Low,New,1,0 +23381,66084,59934,PRETRIAL,Colas,Daniel,NULL,Male,African-American,09/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +23381,66084,59934,PRETRIAL,Colas,Daniel,NULL,Male,African-American,09/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57800,66091,59941,Probation,Allen,Christina,NULL,Male,African-American,11/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +57800,66091,59941,Probation,Allen,Christina,NULL,Male,African-American,11/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +57800,66091,59941,Probation,Allen,Christina,NULL,Male,African-American,11/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57775,66063,59917,PRETRIAL,Dilullo,Vincenzo,NULL,Male,Caucasian,04/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +57775,66063,59917,PRETRIAL,Dilullo,Vincenzo,NULL,Male,Caucasian,04/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +57775,66063,59917,PRETRIAL,Dilullo,Vincenzo,NULL,Male,Caucasian,04/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57786,66072,59923,PRETRIAL,Clarke,Paulette,NULL,Male,African-American,06/24/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +57786,66072,59923,PRETRIAL,Clarke,Paulette,NULL,Male,African-American,06/24/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +57786,66072,59923,PRETRIAL,Clarke,Paulette,NULL,Male,African-American,06/24/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57798,66089,59939,PRETRIAL,Detres,Cynthia,NULL,Female,Caucasian,08/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +57798,66089,59939,PRETRIAL,Detres,Cynthia,NULL,Female,Caucasian,08/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +57798,66089,59939,PRETRIAL,Detres,Cynthia,NULL,Female,Caucasian,08/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +39898,66068,39486,PRETRIAL,Quintal,Beville,NULL,Male,Other,08/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +39898,66068,39486,PRETRIAL,Quintal,Beville,NULL,Male,Other,08/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,Copy,1,0 +39898,66068,39486,PRETRIAL,Quintal,Beville,NULL,Male,Other,08/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +57789,66075,59926,Probation,White,Brian,NULL,Male,African-American,06/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,New,1,0 +57789,66075,59926,Probation,White,Brian,NULL,Male,African-American,06/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +57789,66075,59926,Probation,White,Brian,NULL,Male,African-American,06/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57797,66088,59938,Probation,Ramirez,Jose,NULL,Male,Hispanic,06/10/79,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/2/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +57797,66088,59938,Probation,Ramirez,Jose,NULL,Male,Hispanic,06/10/79,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/2/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +57797,66088,59938,Probation,Ramirez,Jose,NULL,Male,Hispanic,06/10/79,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +29985,31692,28957,PRETRIAL,LANGLOIRE,ISRAEL,NULL,Male,African-American,05/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +29985,31692,28957,PRETRIAL,LANGLOIRE,ISRAEL,NULL,Male,African-American,05/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +29985,31692,28957,PRETRIAL,LANGLOIRE,ISRAEL,NULL,Male,African-American,05/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57787,66073,59924,Probation,Ullysse,Carlo,NULL,Male,African-American,05/22/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/2/13 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +57787,66073,59924,Probation,Ullysse,Carlo,NULL,Male,African-American,05/22/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +57787,66073,59924,Probation,Ullysse,Carlo,NULL,Male,African-American,05/22/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/2/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57772,66060,59914,PRETRIAL,BASSEY,ABIA,NULL,Male,African-American,12/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +57772,66060,59914,PRETRIAL,BASSEY,ABIA,NULL,Male,African-American,12/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +57772,66060,59914,PRETRIAL,BASSEY,ABIA,NULL,Male,African-American,12/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +17055,66081,59931,Probation,kabistan,joel,NULL,Male,Hispanic,10/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +17055,66081,59931,Probation,kabistan,joel,NULL,Male,Hispanic,10/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +17055,66081,59931,Probation,kabistan,joel,NULL,Male,Hispanic,10/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57791,66078,59928,Probation,waddell,michael,NULL,Male,Caucasian,03/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +57791,66078,59928,Probation,waddell,michael,NULL,Male,Caucasian,03/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.86,10,High,New,1,0 +57791,66078,59928,Probation,waddell,michael,NULL,Male,Caucasian,03/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57777,66065,59919,PRETRIAL,Ruiz,Rut,NULL,Female,African-American,11/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +57777,66065,59919,PRETRIAL,Ruiz,Rut,NULL,Female,African-American,11/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +57777,66065,59919,PRETRIAL,Ruiz,Rut,NULL,Female,African-American,11/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57769,66057,59911,PRETRIAL,Walters,Stefan,NULL,Male,African-American,07/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +57769,66057,59911,PRETRIAL,Walters,Stefan,NULL,Male,African-American,07/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +57769,66057,59911,PRETRIAL,Walters,Stefan,NULL,Male,African-American,07/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +29985,66086,59936,PRETRIAL,LANGLOIRE,ISRAEL,NULL,Male,African-American,05/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +29985,66086,59936,PRETRIAL,LANGLOIRE,ISRAEL,NULL,Male,African-American,05/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +29985,66086,59936,PRETRIAL,LANGLOIRE,ISRAEL,NULL,Male,African-American,05/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +57774,66062,59916,PRETRIAL,Carlson,Elizabeth,NULL,Female,Caucasian,03/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/2/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +57774,66062,59916,PRETRIAL,Carlson,Elizabeth,NULL,Female,Caucasian,03/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/2/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +57774,66062,59916,PRETRIAL,Carlson,Elizabeth,NULL,Female,Caucasian,03/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57776,66064,59918,PRETRIAL,Bocanegra,Sebastian,NULL,Male,Caucasian,05/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +57776,66064,59918,PRETRIAL,Bocanegra,Sebastian,NULL,Male,Caucasian,05/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +57776,66064,59918,PRETRIAL,Bocanegra,Sebastian,NULL,Male,Caucasian,05/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57794,66083,59933,PRETRIAL,Cameron,Artis,NULL,Male,African-American,04/24/38,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/2/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +57794,66083,59933,PRETRIAL,Cameron,Artis,NULL,Male,African-American,04/24/38,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/2/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +57794,66083,59933,PRETRIAL,Cameron,Artis,NULL,Male,African-American,04/24/38,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57795,66085,59935,Probation,jean-baptiste,jeannedy,NULL,Male,African-American,02/16/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/2/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +57795,66085,59935,Probation,jean-baptiste,jeannedy,NULL,Male,African-American,02/16/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/2/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +57795,66085,59935,Probation,jean-baptiste,jeannedy,NULL,Male,African-American,02/16/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57799,66090,59940,Probation,LEE,TERRENCE,R,Male,African-American,08/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +57799,66090,59940,Probation,LEE,TERRENCE,R,Male,African-American,08/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +57799,66090,59940,Probation,LEE,TERRENCE,R,Male,African-American,08/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +21458,66092,20612,PRETRIAL,walker,john,NULL,Male,African-American,08/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,Copy,1,0 +21458,66092,20612,PRETRIAL,walker,john,NULL,Male,African-American,08/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-0.92,2,Low,Copy,1,0 +21458,66092,20612,PRETRIAL,walker,john,NULL,Male,African-American,08/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,23,4,Low,Copy,1,0 +57792,66080,59930,PRETRIAL,mion,amanda,NULL,Female,Caucasian,10/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +57792,66080,59930,PRETRIAL,mion,amanda,NULL,Female,Caucasian,10/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +57792,66080,59930,PRETRIAL,mion,amanda,NULL,Female,Caucasian,10/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57784,66067,59921,PRETRIAL,Goode,Donovan,NULL,Male,African-American,11/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +57784,66067,59921,PRETRIAL,Goode,Donovan,NULL,Male,African-American,11/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,8,Risk of Recidivism,-2.58,1,Low,New,1,0 +57784,66067,59921,PRETRIAL,Goode,Donovan,NULL,Male,African-American,11/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57809,66101,59950,PRETRIAL,Figueroalopez,Dennis,Rafael,Male,Caucasian,06/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +57809,66101,59950,PRETRIAL,Figueroalopez,Dennis,Rafael,Male,Caucasian,06/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +57809,66101,59950,PRETRIAL,Figueroalopez,Dennis,Rafael,Male,Caucasian,06/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57805,66097,59946,PRETRIAL,Kaplan,Scott,NULL,Male,Caucasian,09/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +57805,66097,59946,PRETRIAL,Kaplan,Scott,NULL,Male,Caucasian,09/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +57805,66097,59946,PRETRIAL,Kaplan,Scott,NULL,Male,Caucasian,09/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57823,66118,59965,PRETRIAL,GREEN,JAMES,ALAN,Male,Caucasian,09/25/25,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +57823,66118,59965,PRETRIAL,GREEN,JAMES,ALAN,Male,Caucasian,09/25/25,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +57823,66118,59965,PRETRIAL,GREEN,JAMES,ALAN,Male,Caucasian,09/25/25,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57833,66132,59979,Probation,STERN,DAVID,HENRY,Male,Caucasian,06/12/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +57833,66132,59979,Probation,STERN,DAVID,HENRY,Male,Caucasian,06/12/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +57833,66132,59979,Probation,STERN,DAVID,HENRY,Male,Caucasian,06/12/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57836,66136,59983,Probation,Rodriguez,Grace,NULL,Female,Hispanic,09/13/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +57836,66136,59983,Probation,Rodriguez,Grace,NULL,Female,Hispanic,09/13/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +57836,66136,59983,Probation,Rodriguez,Grace,NULL,Female,Hispanic,09/13/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57817,66111,59959,Probation,Armeno,Jeffrey,NULL,Male,Hispanic,06/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.87,2,Low,New,1,0 +57817,66111,59959,Probation,Armeno,Jeffrey,NULL,Male,Hispanic,06/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +57817,66111,59959,Probation,Armeno,Jeffrey,NULL,Male,Hispanic,06/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57818,66113,59960,Probation,willie,joseph,NULL,Male,African-American,12/06/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,New,1,0 +57818,66113,59960,Probation,willie,joseph,NULL,Male,African-American,12/06/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.75,10,High,New,1,0 +57818,66113,59960,Probation,willie,joseph,NULL,Male,African-American,12/06/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +57835,66134,59981,Probation,jacques,wisler,NULL,Male,African-American,02/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +57835,66134,59981,Probation,jacques,wisler,NULL,Male,African-American,02/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +57835,66134,59981,Probation,jacques,wisler,NULL,Male,African-American,02/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57813,66106,59954,Probation,Romeroarroyo,Jose,NULL,Male,Hispanic,05/07/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +57813,66106,59954,Probation,Romeroarroyo,Jose,NULL,Male,Hispanic,05/07/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +57813,66106,59954,Probation,Romeroarroyo,Jose,NULL,Male,Hispanic,05/07/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57825,66120,59967,Probation,Perry,Cristiane,NULL,Female,Caucasian,12/03/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/3/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +57825,66120,59967,Probation,Perry,Cristiane,NULL,Female,Caucasian,12/03/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.43,2,Low,New,1,0 +57825,66120,59967,Probation,Perry,Cristiane,NULL,Female,Caucasian,12/03/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57811,66104,59952,PRETRIAL,DAFFRON,DAVID,NULL,Male,Caucasian,02/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +57811,66104,59952,PRETRIAL,DAFFRON,DAVID,NULL,Male,Caucasian,02/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +57811,66104,59952,PRETRIAL,DAFFRON,DAVID,NULL,Male,Caucasian,02/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57828,66125,59972,PRETRIAL,Mascarenhas,Vivaldo,NULL,Male,African-American,08/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +57828,66125,59972,PRETRIAL,Mascarenhas,Vivaldo,NULL,Male,African-American,08/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +57828,66125,59972,PRETRIAL,Mascarenhas,Vivaldo,NULL,Male,African-American,08/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57807,66099,59948,PRETRIAL,CASH,vVINCENT,NULL,Male,African-American,12/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +57807,66099,59948,PRETRIAL,CASH,vVINCENT,NULL,Male,African-American,12/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +57807,66099,59948,PRETRIAL,CASH,vVINCENT,NULL,Male,African-American,12/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57834,66133,59980,Probation,Smith,Jpon,B,Male,Caucasian,08/10/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +57834,66133,59980,Probation,Smith,Jpon,B,Male,Caucasian,08/10/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +57834,66133,59980,Probation,Smith,Jpon,B,Male,Caucasian,08/10/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +11871,66112,57435,Probation,Vanhorne,Courtney,R,Male,African-American,10/07/83,17,All Scales,Intake,English,Other,Probation,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +11871,66112,57435,Probation,Vanhorne,Courtney,R,Male,African-American,10/07/83,17,All Scales,Intake,English,Other,Probation,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +11871,66112,57435,Probation,Vanhorne,Courtney,R,Male,African-American,10/07/83,17,All Scales,Intake,English,Other,Probation,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +57802,66094,59943,PRETRIAL,Harding,Richard,NULL,Male,African-American,09/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +57802,66094,59943,PRETRIAL,Harding,Richard,NULL,Male,African-American,09/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +57802,66094,59943,PRETRIAL,Harding,Richard,NULL,Male,African-American,09/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57804,66096,59945,PRETRIAL,Langley,Denzle,D,Male,Other,04/04/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/13 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +57804,66096,59945,PRETRIAL,Langley,Denzle,D,Male,Other,04/04/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/13 0:00,1,Low,8,Risk of Recidivism,-2.63,1,Low,New,1,0 +57804,66096,59945,PRETRIAL,Langley,Denzle,D,Male,Other,04/04/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +52342,66130,59977,PRETRIAL,Larosa,Francesca,NULL,Female,Caucasian,05/27/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/3/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +52342,66130,59977,PRETRIAL,Larosa,Francesca,NULL,Female,Caucasian,05/27/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +52342,66130,59977,PRETRIAL,Larosa,Francesca,NULL,Female,Caucasian,05/27/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57820,66115,59962,Probation,GARCIA,MARIO,E,Male,Caucasian,06/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +57820,66115,59962,Probation,GARCIA,MARIO,E,Male,Caucasian,06/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +57820,66115,59962,Probation,GARCIA,MARIO,E,Male,Caucasian,06/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57822,66117,59964,PRETRIAL,HANDY,THOMAS,REED,Male,Caucasian,09/17/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +57822,66117,59964,PRETRIAL,HANDY,THOMAS,REED,Male,Caucasian,09/17/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/13 0:00,1,Low,8,Risk of Recidivism,-2.63,1,Low,New,1,0 +57822,66117,59964,PRETRIAL,HANDY,THOMAS,REED,Male,Caucasian,09/17/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +43623,66109,59957,PRETRIAL,Bond,Shari,NULL,Male,Caucasian,10/20/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/3/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +43623,66109,59957,PRETRIAL,Bond,Shari,NULL,Male,Caucasian,10/20/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/3/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +43623,66109,59957,PRETRIAL,Bond,Shari,NULL,Male,Caucasian,10/20/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +27739,66123,59970,Probation,parrish,craig,NULL,Male,African-American,10/08/80,17,All Scales,Intake,English,Other,Jail Inmate,Single,10/3/13 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +27739,66123,59970,Probation,parrish,craig,NULL,Male,African-American,10/08/80,17,All Scales,Intake,English,Other,Jail Inmate,Single,10/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,5,Medium,New,1,0 +27739,66123,59970,Probation,parrish,craig,NULL,Male,African-American,10/08/80,17,All Scales,Intake,English,Other,Jail Inmate,Single,10/3/13 0:00,2,Medium,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +57810,66102,59951,Probation,Wolfe,Theodore,Lee,Male,Caucasian,06/18/76,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,10/3/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +57810,66102,59951,Probation,Wolfe,Theodore,Lee,Male,Caucasian,06/18/76,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,10/3/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +57810,66102,59951,Probation,Wolfe,Theodore,Lee,Male,Caucasian,06/18/76,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +57838,66138,59985,PRETRIAL,Newton,Robert,Joseph,Male,Caucasian,01/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/3/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +57838,66138,59985,PRETRIAL,Newton,Robert,Joseph,Male,Caucasian,01/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +57838,66138,59985,PRETRIAL,Newton,Robert,Joseph,Male,Caucasian,01/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57801,66093,59942,PRETRIAL,Thurston,Don,K,Male,African-American,09/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +57801,66093,59942,PRETRIAL,Thurston,Don,K,Male,African-American,09/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +57801,66093,59942,PRETRIAL,Thurston,Don,K,Male,African-American,09/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57819,66114,59961,Probation,Gilbert,Giles,NULL,Male,African-American,04/10/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +57819,66114,59961,Probation,Gilbert,Giles,NULL,Male,African-American,04/10/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +57819,66114,59961,Probation,Gilbert,Giles,NULL,Male,African-American,04/10/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57832,66131,59978,Probation,Pimental,Lisbeth,NULL,Female,Hispanic,12/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +57832,66131,59978,Probation,Pimental,Lisbeth,NULL,Female,Hispanic,12/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +57832,66131,59978,Probation,Pimental,Lisbeth,NULL,Female,Hispanic,12/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +57816,66110,59958,PRETRIAL,Robinson,Demetrius,A,Male,African-American,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/13 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +57816,66110,59958,PRETRIAL,Robinson,Demetrius,A,Male,African-American,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/13 0:00,4,High,8,Risk of Recidivism,1.14,10,High,New,1,0 +57816,66110,59958,PRETRIAL,Robinson,Demetrius,A,Male,African-American,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +57806,66098,59947,PRETRIAL,Philippe,Juster,NULL,Male,Other,05/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +57806,66098,59947,PRETRIAL,Philippe,Juster,NULL,Male,Other,05/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +57806,66098,59947,PRETRIAL,Philippe,Juster,NULL,Male,Other,05/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57812,66105,59953,Probation,cote,deborah,lynn,Female,Caucasian,05/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/3/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +57812,66105,59953,Probation,cote,deborah,lynn,Female,Caucasian,05/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/3/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +57812,66105,59953,Probation,cote,deborah,lynn,Female,Caucasian,05/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57824,66119,59966,PRETRIAL,LANZA,ELLAYHER,NULL,Male,African-American,08/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +57824,66119,59966,PRETRIAL,LANZA,ELLAYHER,NULL,Male,African-American,08/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +57824,66119,59966,PRETRIAL,LANZA,ELLAYHER,NULL,Male,African-American,08/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57831,66128,59975,Probation,Baggiero,Steven,NULL,Male,Caucasian,03/28/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/3/13 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +57831,66128,59975,Probation,Baggiero,Steven,NULL,Male,Caucasian,03/28/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/3/13 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +57831,66128,59975,Probation,Baggiero,Steven,NULL,Male,Caucasian,03/28/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57827,66124,59971,PRETRIAL,Brown,Willie,NULL,Male,African-American,04/27/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/3/13 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +57827,66124,59971,PRETRIAL,Brown,Willie,NULL,Male,African-American,04/27/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/3/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +57827,66124,59971,PRETRIAL,Brown,Willie,NULL,Male,African-American,04/27/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/3/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +57821,66116,59963,PRETRIAL,Trovato,Sheila,Diane,Female,Caucasian,10/02/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +57821,66116,59963,PRETRIAL,Trovato,Sheila,Diane,Female,Caucasian,10/02/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +57821,66116,59963,PRETRIAL,Trovato,Sheila,Diane,Female,Caucasian,10/02/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57837,66137,59984,PRETRIAL,Griffin,Robert,NULL,Male,Caucasian,03/06/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +57837,66137,59984,PRETRIAL,Griffin,Robert,NULL,Male,Caucasian,03/06/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +57837,66137,59984,PRETRIAL,Griffin,Robert,NULL,Male,Caucasian,03/06/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57808,66100,59949,PRETRIAL,Valerio,German,NULL,Male,African-American,09/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +57808,66100,59949,PRETRIAL,Valerio,German,NULL,Male,African-American,09/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +57808,66100,59949,PRETRIAL,Valerio,German,NULL,Male,African-American,09/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57370,66103,59477,PRETRIAL,durmeus,daniel,NULL,Male,African-American,02/06/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +57370,66103,59477,PRETRIAL,durmeus,daniel,NULL,Male,African-American,02/06/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +57370,66103,59477,PRETRIAL,durmeus,daniel,NULL,Male,African-American,02/06/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +46306,66121,59968,PRETRIAL,CROSS,STEPHEN,EVERETT,Male,Caucasian,09/04/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +46306,66121,59968,PRETRIAL,CROSS,STEPHEN,EVERETT,Male,Caucasian,09/04/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +46306,66121,59968,PRETRIAL,CROSS,STEPHEN,EVERETT,Male,Caucasian,09/04/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57815,66108,59956,Probation,Accardi,Joseph,NULL,Male,Caucasian,01/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +57815,66108,59956,Probation,Accardi,Joseph,NULL,Male,Caucasian,01/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +57815,66108,59956,Probation,Accardi,Joseph,NULL,Male,Caucasian,01/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57803,66095,59944,PRETRIAL,Zucker,Randall,J,Male,Caucasian,01/05/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +57803,66095,59944,PRETRIAL,Zucker,Randall,J,Male,Caucasian,01/05/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +57803,66095,59944,PRETRIAL,Zucker,Randall,J,Male,Caucasian,01/05/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +13053,66129,59976,PRETRIAL,KETCHUM,JOHN,NULL,Male,Caucasian,08/08/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +13053,66129,59976,PRETRIAL,KETCHUM,JOHN,NULL,Male,Caucasian,08/08/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +13053,66129,59976,PRETRIAL,KETCHUM,JOHN,NULL,Male,Caucasian,08/08/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57861,66163,60009,PRETRIAL,ALSTON,ERIC,NULL,Male,African-American,05/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +57861,66163,60009,PRETRIAL,ALSTON,ERIC,NULL,Male,African-American,05/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +57861,66163,60009,PRETRIAL,ALSTON,ERIC,NULL,Male,African-American,05/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57842,66142,59989,PRETRIAL,Hedges,Jason,Warren,Male,Caucasian,01/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +57842,66142,59989,PRETRIAL,Hedges,Jason,Warren,Male,Caucasian,01/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +57842,66142,59989,PRETRIAL,Hedges,Jason,Warren,Male,Caucasian,01/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57868,66176,60018,Probation,Barber,James,NULL,Male,Caucasian,09/07/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/4/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +57868,66176,60018,Probation,Barber,James,NULL,Male,Caucasian,09/07/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/4/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +57868,66176,60018,Probation,Barber,James,NULL,Male,Caucasian,09/07/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +18290,66171,60013,PRETRIAL,LLOYD,CHRISTOPHER,NULL,Male,African-American,02/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +18290,66171,60013,PRETRIAL,LLOYD,CHRISTOPHER,NULL,Male,African-American,02/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +18290,66171,60013,PRETRIAL,LLOYD,CHRISTOPHER,NULL,Male,African-American,02/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +45819,66150,59997,PRETRIAL,Siuki,Luis,NULL,Male,Hispanic,01/14/35,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/4/13 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +45819,66150,59997,PRETRIAL,Siuki,Luis,NULL,Male,Hispanic,01/14/35,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/4/13 0:00,1,Low,8,Risk of Recidivism,-2.74,1,Low,New,1,0 +45819,66150,59997,PRETRIAL,Siuki,Luis,NULL,Male,Hispanic,01/14/35,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57865,66173,60015,Probation,Smith,Marcus,NULL,Male,African-American,05/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +57865,66173,60015,Probation,Smith,Marcus,NULL,Male,African-American,05/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +57865,66173,60015,Probation,Smith,Marcus,NULL,Male,African-American,05/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57877,66187,60029,PRETRIAL,Duffy,Thomas,NULL,Male,Caucasian,12/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +57877,66187,60029,PRETRIAL,Duffy,Thomas,NULL,Male,Caucasian,12/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +57877,66187,60029,PRETRIAL,Duffy,Thomas,NULL,Male,Caucasian,12/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57848,66152,59999,Probation,Bruno,Tara,NULL,Female,Caucasian,02/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +57848,66152,59999,Probation,Bruno,Tara,NULL,Female,Caucasian,02/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +57848,66152,59999,Probation,Bruno,Tara,NULL,Female,Caucasian,02/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57857,66158,60004,Probation,PASQUALE,AMBER,NICOLE,Female,Caucasian,08/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +57857,66158,60004,Probation,PASQUALE,AMBER,NICOLE,Female,Caucasian,08/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +57857,66158,60004,Probation,PASQUALE,AMBER,NICOLE,Female,Caucasian,08/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57859,66160,60006,Probation,Rivera-Vasquez,Alfonso,NULL,Male,Hispanic,02/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +57859,66160,60006,Probation,Rivera-Vasquez,Alfonso,NULL,Male,Hispanic,02/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +57859,66160,60006,Probation,Rivera-Vasquez,Alfonso,NULL,Male,Hispanic,02/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +48419,66179,60021,Probation,kickbush,brian,NULL,Male,Caucasian,01/07/54,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +48419,66179,60021,Probation,kickbush,brian,NULL,Male,Caucasian,01/07/54,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +48419,66179,60021,Probation,kickbush,brian,NULL,Male,Caucasian,01/07/54,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +49347,66147,59994,PRETRIAL,Samper,German,NULL,Male,Asian,07/11/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/4/13 0:00,1,Low,7,Risk of Violence,-4.34,1,Low,New,1,0 +49347,66147,59994,PRETRIAL,Samper,German,NULL,Male,Asian,07/11/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/4/13 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +49347,66147,59994,PRETRIAL,Samper,German,NULL,Male,Asian,07/11/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57847,66149,59996,PRETRIAL,SHEEHAN,CHRISTOPHER,NULL,Male,Arabic,09/27/39,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-4.47,1,Low,New,1,0 +57847,66149,59996,PRETRIAL,SHEEHAN,CHRISTOPHER,NULL,Male,Arabic,09/27/39,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-2.83,1,Low,New,1,0 +57847,66149,59996,PRETRIAL,SHEEHAN,CHRISTOPHER,NULL,Male,Arabic,09/27/39,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57851,66156,60002,PRETRIAL,Mueller,Zachary,William,Male,Caucasian,12/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +57851,66156,60002,PRETRIAL,Mueller,Zachary,William,Male,Caucasian,12/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +57851,66156,60002,PRETRIAL,Mueller,Zachary,William,Male,Caucasian,12/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +47525,66170,60012,PRETRIAL,Gardner,Michael,NULL,Male,African-American,08/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +47525,66170,60012,PRETRIAL,Gardner,Michael,NULL,Male,African-American,08/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +47525,66170,60012,PRETRIAL,Gardner,Michael,NULL,Male,African-American,08/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57869,66177,60019,PRETRIAL,Leigh,Michael,NULL,Male,Caucasian,10/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +57869,66177,60019,PRETRIAL,Leigh,Michael,NULL,Male,Caucasian,10/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +57869,66177,60019,PRETRIAL,Leigh,Michael,NULL,Male,Caucasian,10/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57874,66184,60026,Probation,saudi,samid,NULL,Male,Hispanic,11/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/4/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +57874,66184,60026,Probation,saudi,samid,NULL,Male,Hispanic,11/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +57874,66184,60026,Probation,saudi,samid,NULL,Male,Hispanic,11/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +38460,66135,59982,PRETRIAL,Flynn,Joseph,Daniel,Male,Caucasian,08/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +38460,66135,59982,PRETRIAL,Flynn,Joseph,Daniel,Male,Caucasian,08/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +38460,66135,59982,PRETRIAL,Flynn,Joseph,Daniel,Male,Caucasian,08/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57840,66140,59987,PRETRIAL,Flewellyn,Joshua,Michael,Male,Caucasian,04/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +57840,66140,59987,PRETRIAL,Flewellyn,Joshua,Michael,Male,Caucasian,04/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +57840,66140,59987,PRETRIAL,Flewellyn,Joshua,Michael,Male,Caucasian,04/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57862,66165,60010,PRETRIAL,Fernand,Romell,Henry,Male,African-American,05/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +57862,66165,60010,PRETRIAL,Fernand,Romell,Henry,Male,African-American,05/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +57862,66165,60010,PRETRIAL,Fernand,Romell,Henry,Male,African-American,05/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57844,66144,59991,PRETRIAL,Stringer,Darryl,NULL,Male,African-American,11/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +57844,66144,59991,PRETRIAL,Stringer,Darryl,NULL,Male,African-American,11/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +57844,66144,59991,PRETRIAL,Stringer,Darryl,NULL,Male,African-American,11/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57873,66182,60024,Probation,MOOTOO,ALEX,E,Male,Hispanic,09/19/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/4/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +57873,66182,60024,Probation,MOOTOO,ALEX,E,Male,Hispanic,09/19/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +57873,66182,60024,Probation,MOOTOO,ALEX,E,Male,Hispanic,09/19/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57876,66186,60028,Probation,Blum,Michael,NULL,Male,Caucasian,01/02/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.84,2,Low,New,1,0 +57876,66186,60028,Probation,Blum,Michael,NULL,Male,Caucasian,01/02/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +57876,66186,60028,Probation,Blum,Michael,NULL,Male,Caucasian,01/02/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +14951,66159,60005,Probation,MILLEVOIX,DAVE,NULL,Male,African-American,01/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.11,8,High,New,1,0 +14951,66159,60005,Probation,MILLEVOIX,DAVE,NULL,Male,African-American,01/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +14951,66159,60005,Probation,MILLEVOIX,DAVE,NULL,Male,African-American,01/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52478,66151,59998,PRETRIAL,TAYLOR,DANIEL,NULL,Male,African-American,11/05/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,4,High,7,Risk of Violence,-0.55,10,High,New,1,0 +52478,66151,59998,PRETRIAL,TAYLOR,DANIEL,NULL,Male,African-American,11/05/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +52478,66151,59998,PRETRIAL,TAYLOR,DANIEL,NULL,Male,African-American,11/05/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,4,High,18,Risk of Failure to Appear,29,7,Medium,New,1,0 +42277,66146,59993,DRRD,Previlus,Pedro,None,Male,African-American,04/02/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +42277,66146,59993,DRRD,Previlus,Pedro,None,Male,African-American,04/02/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,5,Medium,New,1,0 +42277,66146,59993,DRRD,Previlus,Pedro,None,Male,African-American,04/02/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,2,Medium,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +57871,66180,60022,PRETRIAL,Jaggon,Phillip,NULL,Male,African-American,08/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +57871,66180,60022,PRETRIAL,Jaggon,Phillip,NULL,Male,African-American,08/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +57871,66180,60022,PRETRIAL,Jaggon,Phillip,NULL,Male,African-American,08/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57863,66167,60011,PRETRIAL,ASBELL,MARK,NULL,Male,Caucasian,11/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +57863,66167,60011,PRETRIAL,ASBELL,MARK,NULL,Male,Caucasian,11/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +57863,66167,60011,PRETRIAL,ASBELL,MARK,NULL,Male,Caucasian,11/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57866,66175,60017,Probation,ramirez,alex,NULL,Male,Hispanic,03/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/4/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +57866,66175,60017,Probation,ramirez,alex,NULL,Male,Hispanic,03/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +57866,66175,60017,Probation,ramirez,alex,NULL,Male,Hispanic,03/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57841,66141,59988,PRETRIAL,Iglesias,Giovanni,A,Male,Caucasian,10/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +57841,66141,59988,PRETRIAL,Iglesias,Giovanni,A,Male,Caucasian,10/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +57841,66141,59988,PRETRIAL,Iglesias,Giovanni,A,Male,Caucasian,10/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57846,66148,59995,Probation,perez,bianca,NULL,Female,Caucasian,09/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +57846,66148,59995,Probation,perez,bianca,NULL,Female,Caucasian,09/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +57846,66148,59995,Probation,perez,bianca,NULL,Female,Caucasian,09/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57860,66162,60008,PRETRIAL,Rosa,Michael,NULL,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/4/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +57860,66162,60008,PRETRIAL,Rosa,Michael,NULL,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +57860,66162,60008,PRETRIAL,Rosa,Michael,NULL,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +38957,66164,58096,PRETRIAL,PRESSOTTO,DREW,NULL,Male,Caucasian,08/25/69,17,All Scales,Intake,English,Pretrial,Jail Inmate,Separated,10/4/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +38957,66164,58096,PRETRIAL,PRESSOTTO,DREW,NULL,Male,Caucasian,08/25/69,17,All Scales,Intake,English,Pretrial,Jail Inmate,Separated,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +38957,66164,58096,PRETRIAL,PRESSOTTO,DREW,NULL,Male,Caucasian,08/25/69,17,All Scales,Intake,English,Pretrial,Jail Inmate,Separated,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +18290,18934,17557,PRETRIAL,LLOYD,CHRISTOPHER,NULL,Male,African-American,02/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +18290,18934,17557,PRETRIAL,LLOYD,CHRISTOPHER,NULL,Male,African-American,02/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +18290,18934,17557,PRETRIAL,LLOYD,CHRISTOPHER,NULL,Male,African-American,02/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44967,66183,60025,PRETRIAL,Valderrama,Juan,NULL,Male,Caucasian,02/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +44967,66183,60025,PRETRIAL,Valderrama,Juan,NULL,Male,Caucasian,02/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,New,1,0 +44967,66183,60025,PRETRIAL,Valderrama,Juan,NULL,Male,Caucasian,02/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57875,66185,60027,PRETRIAL,TRUJULLO,NARJAN,NULL,Male,Other,10/31/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +57875,66185,60027,PRETRIAL,TRUJULLO,NARJAN,NULL,Male,Other,10/31/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +57875,66185,60027,PRETRIAL,TRUJULLO,NARJAN,NULL,Male,Other,10/31/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57839,66139,59986,PRETRIAL,Walker,Fernando,NULL,Male,African-American,09/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +57839,66139,59986,PRETRIAL,Walker,Fernando,NULL,Male,African-American,09/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +57839,66139,59986,PRETRIAL,Walker,Fernando,NULL,Male,African-American,09/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57849,66153,60000,Probation,OBRIEN,LAURA,BETH,Female,Caucasian,02/02/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +57849,66153,60000,Probation,OBRIEN,LAURA,BETH,Female,Caucasian,02/02/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +57849,66153,60000,Probation,OBRIEN,LAURA,BETH,Female,Caucasian,02/02/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57843,66143,59990,PRETRIAL,Bruguier,Edmund,NULL,Male,Caucasian,06/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +57843,66143,59990,PRETRIAL,Bruguier,Edmund,NULL,Male,Caucasian,06/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +57843,66143,59990,PRETRIAL,Bruguier,Edmund,NULL,Male,Caucasian,06/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +47290,66157,60003,Probation,giordano,todd,NULL,Male,Caucasian,05/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +47290,66157,60003,Probation,giordano,todd,NULL,Male,Caucasian,05/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +47290,66157,60003,Probation,giordano,todd,NULL,Male,Caucasian,05/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57870,66178,60020,Probation,smith,stephen,NULL,Male,African-American,04/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +57870,66178,60020,Probation,smith,stephen,NULL,Male,African-American,04/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +57870,66178,60020,Probation,smith,stephen,NULL,Male,African-American,04/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57867,66174,60016,Probation,WESLEY,LANCE,TYREE,Male,African-American,10/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +57867,66174,60016,Probation,WESLEY,LANCE,TYREE,Male,African-American,10/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +57867,66174,60016,Probation,WESLEY,LANCE,TYREE,Male,African-American,10/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57883,66195,60036,PRETRIAL,Feest,Carl,NULL,Male,Caucasian,01/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +57883,66195,60036,PRETRIAL,Feest,Carl,NULL,Male,Caucasian,01/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +57883,66195,60036,PRETRIAL,Feest,Carl,NULL,Male,Caucasian,01/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +7642,66190,60032,PRETRIAL,CARTER,TAVARIS,NULL,Male,African-American,08/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,4,High,7,Risk of Violence,-0.9,9,High,New,1,0 +7642,66190,60032,PRETRIAL,CARTER,TAVARIS,NULL,Male,African-American,08/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,4,High,8,Risk of Recidivism,1.14,10,High,New,1,0 +7642,66190,60032,PRETRIAL,CARTER,TAVARIS,NULL,Male,African-American,08/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +34331,66192,33475,PRETRIAL,Brown,Robie,NULL,Male,African-American,11/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,4,High,7,Risk of Violence,-0.71,9,High,Copy,1,0 +34331,66192,33475,PRETRIAL,Brown,Robie,NULL,Male,African-American,11/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,Copy,1,0 +34331,66192,33475,PRETRIAL,Brown,Robie,NULL,Male,African-American,11/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,4,High,18,Risk of Failure to Appear,35,10,High,Copy,1,0 +57881,66193,60034,PRETRIAL,MUNIZ,JONATHAN,NULL,Male,Hispanic,09/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +57881,66193,60034,PRETRIAL,MUNIZ,JONATHAN,NULL,Male,Hispanic,09/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +57881,66193,60034,PRETRIAL,MUNIZ,JONATHAN,NULL,Male,Hispanic,09/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57878,66188,60030,PRETRIAL,Villalta,Jose,NULL,Male,Hispanic,03/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +57878,66188,60030,PRETRIAL,Villalta,Jose,NULL,Male,Hispanic,03/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +57878,66188,60030,PRETRIAL,Villalta,Jose,NULL,Male,Hispanic,03/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57880,66191,60033,PRETRIAL,Jeanpierre,Kenson,NULL,Male,African-American,10/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +57880,66191,60033,PRETRIAL,Jeanpierre,Kenson,NULL,Male,African-American,10/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +57880,66191,60033,PRETRIAL,Jeanpierre,Kenson,NULL,Male,African-American,10/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57882,66194,60035,PRETRIAL,King,Tereese,NULL,Female,African-American,08/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +57882,66194,60035,PRETRIAL,King,Tereese,NULL,Female,African-American,08/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +57882,66194,60035,PRETRIAL,King,Tereese,NULL,Female,African-American,08/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57879,66189,60031,PRETRIAL,Margadonna,David,NULL,Male,Caucasian,01/18/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/13 0:00,1,Low,7,Risk of Violence,-4.27,1,Low,New,1,0 +57879,66189,60031,PRETRIAL,Margadonna,David,NULL,Male,Caucasian,01/18/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/13 0:00,1,Low,8,Risk of Recidivism,-2.67,1,Low,New,1,0 +57879,66189,60031,PRETRIAL,Margadonna,David,NULL,Male,Caucasian,01/18/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57885,66197,60038,PRETRIAL,Medina,Noel,NULL,Male,Caucasian,03/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +57885,66197,60038,PRETRIAL,Medina,Noel,NULL,Male,Caucasian,03/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +57885,66197,60038,PRETRIAL,Medina,Noel,NULL,Male,Caucasian,03/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57886,66198,60039,PRETRIAL,Wang,Hanyu,NULL,Male,Caucasian,12/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +57886,66198,60039,PRETRIAL,Wang,Hanyu,NULL,Male,Caucasian,12/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +57886,66198,60039,PRETRIAL,Wang,Hanyu,NULL,Male,Caucasian,12/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +18900,66200,18152,PRETRIAL,williams,donald,NULL,Male,Caucasian,08/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,Copy,1,0 +18900,66200,18152,PRETRIAL,williams,donald,NULL,Male,Caucasian,08/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/13 0:00,1,Low,8,Risk of Recidivism,-0.63,3,Low,Copy,1,0 +18900,66200,18152,PRETRIAL,williams,donald,NULL,Male,Caucasian,08/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +57884,66196,60037,PRETRIAL,Morales,Kelvin,NULL,Male,Hispanic,12/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +57884,66196,60037,PRETRIAL,Morales,Kelvin,NULL,Male,Hispanic,12/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +57884,66196,60037,PRETRIAL,Morales,Kelvin,NULL,Male,Hispanic,12/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57889,66201,60041,PRETRIAL,Kitt,Steven,NULL,Male,Caucasian,07/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/6/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +57889,66201,60041,PRETRIAL,Kitt,Steven,NULL,Male,Caucasian,07/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/6/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +57889,66201,60041,PRETRIAL,Kitt,Steven,NULL,Male,Caucasian,07/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57887,66199,60040,PRETRIAL,Alcocer,David,NULL,Male,African-American,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +57887,66199,60040,PRETRIAL,Alcocer,David,NULL,Male,African-American,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +57887,66199,60040,PRETRIAL,Alcocer,David,NULL,Male,African-American,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57895,66208,60048,PRETRIAL,Eugene,Joanne,NULL,Female,African-American,12/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +57895,66208,60048,PRETRIAL,Eugene,Joanne,NULL,Female,African-American,12/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +57895,66208,60048,PRETRIAL,Eugene,Joanne,NULL,Female,African-American,12/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57917,66229,60069,PRETRIAL,lewis,kevin,NULL,Male,African-American,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +57917,66229,60069,PRETRIAL,lewis,kevin,NULL,Male,African-American,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,4,High,8,Risk of Recidivism,0.26,8,High,New,1,0 +57917,66229,60069,PRETRIAL,lewis,kevin,NULL,Male,African-American,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57930,66246,60083,Probation,Florence,Norman,NULL,Male,Hispanic,04/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +57930,66246,60083,Probation,Florence,Norman,NULL,Male,Hispanic,04/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +57930,66246,60083,Probation,Florence,Norman,NULL,Male,Hispanic,04/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57912,66225,60065,Probation,Chavarria,Jeffrey,NULL,Male,Hispanic,06/07/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +57912,66225,60065,Probation,Chavarria,Jeffrey,NULL,Male,Hispanic,06/07/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +57912,66225,60065,Probation,Chavarria,Jeffrey,NULL,Male,Hispanic,06/07/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +57933,66250,60087,Probation,Bethancourt,Julio,NULL,Male,Hispanic,03/26/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +57933,66250,60087,Probation,Bethancourt,Julio,NULL,Male,Hispanic,03/26/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +57933,66250,60087,Probation,Bethancourt,Julio,NULL,Male,Hispanic,03/26/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +19078,66204,60044,PRETRIAL,Walquer,Eyzzaquirre,NULL,Male,African-American,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,2,Medium,7,Risk of Violence,-1.27,7,Medium,New,1,0 +19078,66204,60044,PRETRIAL,Walquer,Eyzzaquirre,NULL,Male,African-American,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +19078,66204,60044,PRETRIAL,Walquer,Eyzzaquirre,NULL,Male,African-American,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57898,66211,60051,PRETRIAL,Hughes,Devonte,NULL,Male,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +57898,66211,60051,PRETRIAL,Hughes,Devonte,NULL,Male,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +57898,66211,60051,PRETRIAL,Hughes,Devonte,NULL,Male,African-American,07/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57900,66213,60053,PRETRIAL,adams,sharkiem,NULL,Male,African-American,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +57900,66213,60053,PRETRIAL,adams,sharkiem,NULL,Male,African-American,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +57900,66213,60053,PRETRIAL,adams,sharkiem,NULL,Male,African-American,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57941,66262,60098,PRETRIAL,JACQUES,JUVINCE,NULL,Male,African-American,12/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +57941,66262,60098,PRETRIAL,JACQUES,JUVINCE,NULL,Male,African-American,12/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +57941,66262,60098,PRETRIAL,JACQUES,JUVINCE,NULL,Male,African-American,12/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57943,66264,60100,PRETRIAL,FRAZIER,DIJOHN,NULL,Male,African-American,02/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,4,High,7,Risk of Violence,-0.45,10,High,New,1,0 +57943,66264,60100,PRETRIAL,FRAZIER,DIJOHN,NULL,Male,African-American,02/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,4,High,8,Risk of Recidivism,0.62,10,High,New,1,0 +57943,66264,60100,PRETRIAL,FRAZIER,DIJOHN,NULL,Male,African-American,02/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57914,66227,60067,PRETRIAL,Cadet,Marie,NULL,Female,African-American,02/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +57914,66227,60067,PRETRIAL,Cadet,Marie,NULL,Female,African-American,02/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +57914,66227,60067,PRETRIAL,Cadet,Marie,NULL,Female,African-American,02/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57919,66234,60073,Probation,Florez,Jonathan,NULL,Male,Hispanic,02/09/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +57919,66234,60073,Probation,Florez,Jonathan,NULL,Male,Hispanic,02/09/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +57919,66234,60073,Probation,Florez,Jonathan,NULL,Male,Hispanic,02/09/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57924,66241,60078,Probation,MAYWEATHER,MICHAEL,NULL,Male,African-American,05/15/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/7/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +57924,66241,60078,Probation,MAYWEATHER,MICHAEL,NULL,Male,African-American,05/15/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/7/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +57924,66241,60078,Probation,MAYWEATHER,MICHAEL,NULL,Male,African-American,05/15/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57893,66206,60046,PRETRIAL,LOPEZ,JOHN,CARLOS,Male,Hispanic,11/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +57893,66206,60046,PRETRIAL,LOPEZ,JOHN,CARLOS,Male,Hispanic,11/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +57893,66206,60046,PRETRIAL,LOPEZ,JOHN,CARLOS,Male,Hispanic,11/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57907,66220,60060,Probation,Scunziano,Michael,Thomas,Male,Caucasian,10/30/54,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/7/13 0:00,1,Low,7,Risk of Violence,-4.29,1,Low,New,1,0 +57907,66220,60060,Probation,Scunziano,Michael,Thomas,Male,Caucasian,10/30/54,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/7/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +57907,66220,60060,Probation,Scunziano,Michael,Thomas,Male,Caucasian,10/30/54,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57937,66255,60092,Probation,LAPETER,MARY,NULL,Female,Caucasian,05/05/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/7/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +57937,66255,60092,Probation,LAPETER,MARY,NULL,Female,Caucasian,05/05/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/7/13 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +57937,66255,60092,Probation,LAPETER,MARY,NULL,Female,Caucasian,05/05/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +41977,45700,41734,PRETRIAL,LINDO,RICHARD,NULL,Male,African-American,02/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +41977,45700,41734,PRETRIAL,LINDO,RICHARD,NULL,Male,African-American,02/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +41977,45700,41734,PRETRIAL,LINDO,RICHARD,NULL,Male,African-American,02/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +48206,66235,48883,PRETRIAL,Gause,Vanessa,NULL,Male,African-American,02/25/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,2,Medium,7,Risk of Violence,-2.74,2,Low,Copy,1,0 +48206,66235,48883,PRETRIAL,Gause,Vanessa,NULL,Male,African-American,02/25/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,Copy,1,0 +48206,66235,48883,PRETRIAL,Gause,Vanessa,NULL,Male,African-American,02/25/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +57923,66240,60077,PRETRIAL,Zacariasreyes,Rosa,Abelino,Male,Hispanic,02/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +57923,66240,60077,PRETRIAL,Zacariasreyes,Rosa,Abelino,Male,Hispanic,02/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +57923,66240,60077,PRETRIAL,Zacariasreyes,Rosa,Abelino,Male,Hispanic,02/22/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57901,66214,60054,PRETRIAL,Mitchell,Maura,NULL,Female,Caucasian,01/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/13 0:00,1,Low,7,Risk of Violence,-4.39,1,Low,New,1,0 +57901,66214,60054,PRETRIAL,Mitchell,Maura,NULL,Female,Caucasian,01/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/13 0:00,1,Low,8,Risk of Recidivism,-2.78,1,Low,New,1,0 +57901,66214,60054,PRETRIAL,Mitchell,Maura,NULL,Female,Caucasian,01/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +57932,66248,60085,PRETRIAL,McDonald,Davel,NULL,Male,African-American,05/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/7/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +57932,66248,60085,PRETRIAL,McDonald,Davel,NULL,Male,African-American,05/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +57932,66248,60085,PRETRIAL,McDonald,Davel,NULL,Male,African-American,05/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +39731,66261,60097,PRETRIAL,FOLWER,MICHAEL,NULL,Male,African-American,11/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +39731,66261,60097,PRETRIAL,FOLWER,MICHAEL,NULL,Male,African-American,11/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +39731,66261,60097,PRETRIAL,FOLWER,MICHAEL,NULL,Male,African-American,11/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +19449,66232,60071,Probation,Brock,Martha,NULL,Female,Caucasian,10/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +19449,66232,60071,Probation,Brock,Martha,NULL,Female,Caucasian,10/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +19449,66232,60071,Probation,Brock,Martha,NULL,Female,Caucasian,10/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57926,66243,60080,Probation,Rios,Angel,NULL,Male,Hispanic,10/17/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +57926,66243,60080,Probation,Rios,Angel,NULL,Male,Hispanic,10/17/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +57926,66243,60080,Probation,Rios,Angel,NULL,Male,Hispanic,10/17/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57909,66222,60062,Probation,WESSLING,ALAN,NULL,Male,Caucasian,12/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +57909,66222,60062,Probation,WESSLING,ALAN,NULL,Male,Caucasian,12/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +57909,66222,60062,Probation,WESSLING,ALAN,NULL,Male,Caucasian,12/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +57935,66253,60090,Probation,Rivera,Magdelina,NULL,Female,Hispanic,12/04/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +57935,66253,60090,Probation,Rivera,Magdelina,NULL,Female,Hispanic,12/04/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +57935,66253,60090,Probation,Rivera,Magdelina,NULL,Female,Hispanic,12/04/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +12802,66245,60082,PRETRIAL,CUNNINGHAM,TONI,DEMITRI,Male,African-American,11/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/7/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +12802,66245,60082,PRETRIAL,CUNNINGHAM,TONI,DEMITRI,Male,African-American,11/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +12802,66245,60082,PRETRIAL,CUNNINGHAM,TONI,DEMITRI,Male,African-American,11/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57904,66217,60057,Probation,Pilgrim,Cerise,NULL,Female,African-American,01/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +57904,66217,60057,Probation,Pilgrim,Cerise,NULL,Female,African-American,01/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +57904,66217,60057,Probation,Pilgrim,Cerise,NULL,Female,African-American,01/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +57911,66224,60064,Probation,Marrero,Jose,NULL,Male,Hispanic,02/07/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,2,Medium,7,Risk of Violence,-3.01,1,Low,New,1,0 +57911,66224,60064,Probation,Marrero,Jose,NULL,Male,Hispanic,02/07/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +57911,66224,60064,Probation,Marrero,Jose,NULL,Male,Hispanic,02/07/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +2557,66251,60088,Probation,Rodriguez,Geovanni,Jesus,Male,Caucasian,08/08/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +2557,66251,60088,Probation,Rodriguez,Geovanni,Jesus,Male,Caucasian,08/08/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +2557,66251,60088,Probation,Rodriguez,Geovanni,Jesus,Male,Caucasian,08/08/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +57939,66258,60094,Probation,Bray,Tyler,NULL,Male,Caucasian,05/08/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +57939,66258,60094,Probation,Bray,Tyler,NULL,Male,Caucasian,05/08/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +57939,66258,60094,Probation,Bray,Tyler,NULL,Male,Caucasian,05/08/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +41977,66237,41734,PRETRIAL,LINDO,RICHARD,NULL,Male,African-American,02/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,Copy,1,0 +41977,66237,41734,PRETRIAL,LINDO,RICHARD,NULL,Male,African-American,02/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,Copy,1,0 +41977,66237,41734,PRETRIAL,LINDO,RICHARD,NULL,Male,African-American,02/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +57922,66238,60075,PRETRIAL,SANTIAGO,OMAR,NULL,Male,Caucasian,05/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/7/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +57922,66238,60075,PRETRIAL,SANTIAGO,OMAR,NULL,Male,Caucasian,05/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/7/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +57922,66238,60075,PRETRIAL,SANTIAGO,OMAR,NULL,Male,Caucasian,05/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +57903,66216,60056,PRETRIAL,MARTIN,DANIEL,NULL,Male,African-American,11/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +57903,66216,60056,PRETRIAL,MARTIN,DANIEL,NULL,Male,African-American,11/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +57903,66216,60056,PRETRIAL,MARTIN,DANIEL,NULL,Male,African-American,11/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57940,66259,60095,PRETRIAL,Sippin,Barry,NULL,Male,Caucasian,11/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +57940,66259,60095,PRETRIAL,Sippin,Barry,NULL,Male,Caucasian,11/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +57940,66259,60095,PRETRIAL,Sippin,Barry,NULL,Male,Caucasian,11/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57894,66207,60047,PRETRIAL,CARTY,ALEXIS,NULL,Female,African-American,01/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +57894,66207,60047,PRETRIAL,CARTY,ALEXIS,NULL,Female,African-American,01/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +57894,66207,60047,PRETRIAL,CARTY,ALEXIS,NULL,Female,African-American,01/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57892,66203,60043,PRETRIAL,BENITO,ANDREW,JOSEPH,Male,Caucasian,09/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,4,High,7,Risk of Violence,-0.5,10,High,New,1,0 +57892,66203,60043,PRETRIAL,BENITO,ANDREW,JOSEPH,Male,Caucasian,09/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +57892,66203,60043,PRETRIAL,BENITO,ANDREW,JOSEPH,Male,Caucasian,09/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57908,66221,60061,PRETRIAL,younger,patricia,NULL,Female,African-American,05/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +57908,66221,60061,PRETRIAL,younger,patricia,NULL,Female,African-American,05/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +57908,66221,60061,PRETRIAL,younger,patricia,NULL,Female,African-American,05/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57899,66212,60052,PRETRIAL,Carter,Samyrah,Janay,Female,African-American,05/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +57899,66212,60052,PRETRIAL,Carter,Samyrah,Janay,Female,African-American,05/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +57899,66212,60052,PRETRIAL,Carter,Samyrah,Janay,Female,African-American,05/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57942,66263,60099,PRETRIAL,Cummings,Lamont,Jamarcus,Male,African-American,07/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +57942,66263,60099,PRETRIAL,Cummings,Lamont,Jamarcus,Male,African-American,07/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +57942,66263,60099,PRETRIAL,Cummings,Lamont,Jamarcus,Male,African-American,07/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +27791,66233,60072,PRETRIAL,martinez,mario,NULL,Male,Hispanic,07/20/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +27791,66233,60072,PRETRIAL,martinez,mario,NULL,Male,Hispanic,07/20/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +27791,66233,60072,PRETRIAL,martinez,mario,NULL,Male,Hispanic,07/20/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57925,66242,60079,Probation,SALAZARQUINONES,LUIS,EDUARDO,Male,Hispanic,01/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/7/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +57925,66242,60079,Probation,SALAZARQUINONES,LUIS,EDUARDO,Male,Hispanic,01/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +57925,66242,60079,Probation,SALAZARQUINONES,LUIS,EDUARDO,Male,Hispanic,01/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57915,66228,60068,PRETRIAL,Adger,Fredrick,Sotusai,Male,African-American,09/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +57915,66228,60068,PRETRIAL,Adger,Fredrick,Sotusai,Male,African-American,09/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +57915,66228,60068,PRETRIAL,Adger,Fredrick,Sotusai,Male,African-American,09/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57931,66247,60084,Probation,GULINO,LARRY,NULL,Male,Caucasian,05/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,2,Medium,7,Risk of Violence,-2.89,2,Low,New,1,0 +57931,66247,60084,Probation,GULINO,LARRY,NULL,Male,Caucasian,05/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +57931,66247,60084,Probation,GULINO,LARRY,NULL,Male,Caucasian,05/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +57913,66226,60066,Probation,Kidd,Tonya,NULL,Female,Caucasian,12/29/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +57913,66226,60066,Probation,Kidd,Tonya,NULL,Female,Caucasian,12/29/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +57913,66226,60066,Probation,Kidd,Tonya,NULL,Female,Caucasian,12/29/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57929,66249,60086,PRETRIAL,mejia,carlos,NULL,Male,Hispanic,01/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +57929,66249,60086,PRETRIAL,mejia,carlos,NULL,Male,Hispanic,01/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +57929,66249,60086,PRETRIAL,mejia,carlos,NULL,Male,Hispanic,01/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +19078,66205,60045,PRETRIAL,Walquer,Eyzzaquirre,NULL,Male,African-American,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +19078,66205,60045,PRETRIAL,Walquer,Eyzzaquirre,NULL,Male,African-American,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +19078,66205,60045,PRETRIAL,Walquer,Eyzzaquirre,NULL,Male,African-American,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57906,66219,60059,PRETRIAL,Madison,Trevon,NULL,Male,African-American,09/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,New,1,0 +57906,66219,60059,PRETRIAL,Madison,Trevon,NULL,Male,African-American,09/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +57906,66219,60059,PRETRIAL,Madison,Trevon,NULL,Male,African-American,09/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57918,66231,60070,Probation,Heinrich,David,NULL,Male,Caucasian,03/22/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/7/13 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +57918,66231,60070,Probation,Heinrich,David,NULL,Male,Caucasian,03/22/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/7/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +57918,66231,60070,Probation,Heinrich,David,NULL,Male,Caucasian,03/22/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57897,66210,60050,PRETRIAL,COHEN,MERVIN,ELLIS,Male,African-American,05/24/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/7/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +57897,66210,60050,PRETRIAL,COHEN,MERVIN,ELLIS,Male,African-American,05/24/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/7/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +57897,66210,60050,PRETRIAL,COHEN,MERVIN,ELLIS,Male,African-American,05/24/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57927,66244,60081,Probation,Keegan,Peter,NULL,Male,Caucasian,02/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/7/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +57927,66244,60081,Probation,Keegan,Peter,NULL,Male,Caucasian,02/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +57927,66244,60081,Probation,Keegan,Peter,NULL,Male,Caucasian,02/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57920,66236,60074,PRETRIAL,Santos,Jose,Luis,Male,Hispanic,12/02/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +57920,66236,60074,PRETRIAL,Santos,Jose,Luis,Male,Hispanic,12/02/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/13 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +57920,66236,60074,PRETRIAL,Santos,Jose,Luis,Male,Hispanic,12/02/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57921,66239,60076,Probation,Owens,Kennard,NULL,Male,African-American,11/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +57921,66239,60076,Probation,Owens,Kennard,NULL,Male,African-American,11/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +57921,66239,60076,Probation,Owens,Kennard,NULL,Male,African-American,11/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57902,66215,60055,PRETRIAL,Russell,Alyza,Rachel,Female,Caucasian,04/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +57902,66215,60055,PRETRIAL,Russell,Alyza,Rachel,Female,Caucasian,04/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +57902,66215,60055,PRETRIAL,Russell,Alyza,Rachel,Female,Caucasian,04/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57891,66202,60042,PRETRIAL,Cabrera,Alejandro,Jose,Male,Hispanic,03/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +57891,66202,60042,PRETRIAL,Cabrera,Alejandro,Jose,Male,Hispanic,03/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +57891,66202,60042,PRETRIAL,Cabrera,Alejandro,Jose,Male,Hispanic,03/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57934,66252,60089,Probation,ROMAN,ASHLEY,NICOLE,Female,Hispanic,11/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +57934,66252,60089,Probation,ROMAN,ASHLEY,NICOLE,Female,Hispanic,11/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +57934,66252,60089,Probation,ROMAN,ASHLEY,NICOLE,Female,Hispanic,11/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57910,66223,60063,PRETRIAL,JOHNSON,TAMEKA,NULL,Male,African-American,01/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,4,High,7,Risk of Violence,0.08,10,High,New,1,0 +57910,66223,60063,PRETRIAL,JOHNSON,TAMEKA,NULL,Male,African-American,01/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +57910,66223,60063,PRETRIAL,JOHNSON,TAMEKA,NULL,Male,African-American,01/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/13 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52906,66273,60108,PRETRIAL,brown,jermaine,NULL,Male,African-American,12/15/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.71,9,High,New,1,0 +52906,66273,60108,PRETRIAL,brown,jermaine,NULL,Male,African-American,12/15/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,7,Medium,New,1,0 +52906,66273,60108,PRETRIAL,brown,jermaine,NULL,Male,African-American,12/15/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57960,66288,60119,Probation,arthurton,leanda,NULL,Female,African-American,09/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +57960,66288,60119,Probation,arthurton,leanda,NULL,Female,African-American,09/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +57960,66288,60119,Probation,arthurton,leanda,NULL,Female,African-American,09/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +46679,66294,60125,PRETRIAL,Brayboy,Maquia,NULL,Female,African-American,01/16/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +46679,66294,60125,PRETRIAL,Brayboy,Maquia,NULL,Female,African-American,01/16/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +46679,66294,60125,PRETRIAL,Brayboy,Maquia,NULL,Female,African-American,01/16/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57954,66281,60113,PRETRIAL,Johnson,Brenley,K,Male,African-American,08/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/8/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +57954,66281,60113,PRETRIAL,Johnson,Brenley,K,Male,African-American,08/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/8/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +57954,66281,60113,PRETRIAL,Johnson,Brenley,K,Male,African-American,08/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57966,66296,60127,Probation,acevedo,charles,NULL,Male,Hispanic,07/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/8/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +57966,66296,60127,Probation,acevedo,charles,NULL,Male,Hispanic,07/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/8/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +57966,66296,60127,Probation,acevedo,charles,NULL,Male,Hispanic,07/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57958,66286,60117,PRETRIAL,Kopf,Thomas,NULL,Male,Caucasian,11/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/8/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +57958,66286,60117,PRETRIAL,Kopf,Thomas,NULL,Male,Caucasian,11/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/8/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +57958,66286,60117,PRETRIAL,Kopf,Thomas,NULL,Male,Caucasian,11/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57944,66265,60101,PRETRIAL,HOOPER,CHANEL,NULL,Female,African-American,09/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +57944,66265,60101,PRETRIAL,HOOPER,CHANEL,NULL,Female,African-American,09/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +57944,66265,60101,PRETRIAL,HOOPER,CHANEL,NULL,Female,African-American,09/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +27745,66299,26845,DRRD,Johnson,Reginald,NULL,Male,African-American,07/14/72,22,Risk and Prescreen,Intake,English,Conditional Release,Pretrial Defendant,Single,10/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,Copy,1,0 +27745,66299,26845,DRRD,Johnson,Reginald,NULL,Male,African-American,07/14/72,22,Risk and Prescreen,Intake,English,Conditional Release,Pretrial Defendant,Single,10/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.8,10,High,Copy,1,0 +27745,66299,26845,DRRD,Johnson,Reginald,NULL,Male,African-American,07/14/72,22,Risk and Prescreen,Intake,English,Conditional Release,Pretrial Defendant,Single,10/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,7,Medium,Copy,1,0 +57950,66278,60110,Probation,Niesen,Michelle,Lynn,Female,Caucasian,10/11/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +57950,66278,60110,Probation,Niesen,Michelle,Lynn,Female,Caucasian,10/11/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +57950,66278,60110,Probation,Niesen,Michelle,Lynn,Female,Caucasian,10/11/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +38662,66270,60106,PRETRIAL,RAKOSKI,RAYMOND,NULL,Male,Caucasian,06/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +38662,66270,60106,PRETRIAL,RAKOSKI,RAYMOND,NULL,Male,Caucasian,06/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +38662,66270,60106,PRETRIAL,RAKOSKI,RAYMOND,NULL,Male,Caucasian,06/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57748,66277,59892,PRETRIAL,daley,ricardo,NULL,Male,African-American,11/12/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,Copy,1,0 +57748,66277,59892,PRETRIAL,daley,ricardo,NULL,Male,African-American,11/12/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,Copy,1,0 +57748,66277,59892,PRETRIAL,daley,ricardo,NULL,Male,African-American,11/12/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +57955,66284,60115,Probation,Gatto,Kimberly,NULL,Female,Caucasian,11/30/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/8/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +57955,66284,60115,Probation,Gatto,Kimberly,NULL,Female,Caucasian,11/30/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/8/13 0:00,1,Low,8,Risk of Recidivism,-1.43,2,Low,New,1,0 +57955,66284,60115,Probation,Gatto,Kimberly,NULL,Female,Caucasian,11/30/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +47178,66291,60122,PRETRIAL,Rai,Justin,NULL,Male,Hispanic,08/22/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +47178,66291,60122,PRETRIAL,Rai,Justin,NULL,Male,Hispanic,08/22/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,4,High,8,Risk of Recidivism,0.28,8,High,New,1,0 +47178,66291,60122,PRETRIAL,Rai,Justin,NULL,Male,Hispanic,08/22/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57968,66298,60129,Probation,PROPHETE,BOB,NULL,Male,African-American,08/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +57968,66298,60129,Probation,PROPHETE,BOB,NULL,Male,African-American,08/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +57968,66298,60129,Probation,PROPHETE,BOB,NULL,Male,African-American,08/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57095,66272,59185,Probation,Brown,Cameron,NULL,Male,African-American,06/10/83,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +57095,66272,59185,Probation,Brown,Cameron,NULL,Male,African-American,06/10/83,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-0.49,4,Low,New,1,0 +57095,66272,59185,Probation,Brown,Cameron,NULL,Male,African-American,06/10/83,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +57961,66289,60120,Probation,Pierre,Jean,NULL,Male,Hispanic,07/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +57961,66289,60120,Probation,Pierre,Jean,NULL,Male,Hispanic,07/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +57961,66289,60120,Probation,Pierre,Jean,NULL,Male,Hispanic,07/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +46908,66268,60104,PRETRIAL,Mcbride,Oswald,NULL,Male,African-American,02/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +46908,66268,60104,PRETRIAL,Mcbride,Oswald,NULL,Male,African-American,02/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +46908,66268,60104,PRETRIAL,Mcbride,Oswald,NULL,Male,African-American,02/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57949,66275,60109,Probation,mazyck,nekarah,NULL,Female,African-American,02/05/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +57949,66275,60109,Probation,mazyck,nekarah,NULL,Female,African-American,02/05/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +57949,66275,60109,Probation,mazyck,nekarah,NULL,Female,African-American,02/05/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57945,66266,60102,PRETRIAL,Taveras,Luis,Miguel,Male,Hispanic,09/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +57945,66266,60102,PRETRIAL,Taveras,Luis,Miguel,Male,Hispanic,09/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +57945,66266,60102,PRETRIAL,Taveras,Luis,Miguel,Male,Hispanic,09/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57959,66287,60118,Probation,Reid,Shanek,NULL,Female,African-American,04/07/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +57959,66287,60118,Probation,Reid,Shanek,NULL,Female,African-American,04/07/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +57959,66287,60118,Probation,Reid,Shanek,NULL,Female,African-American,04/07/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57525,66282,59634,PRETRIAL,Holloway,Shannon,NULL,Male,African-American,08/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,Copy,1,0 +57525,66282,59634,PRETRIAL,Holloway,Shannon,NULL,Male,African-American,08/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,Copy,1,0 +57525,66282,59634,PRETRIAL,Holloway,Shannon,NULL,Male,African-American,08/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +57969,66300,60130,PRETRIAL,LITTLE,ELLIOT,F,Male,African-American,02/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +57969,66300,60130,PRETRIAL,LITTLE,ELLIOT,F,Male,African-American,02/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +57969,66300,60130,PRETRIAL,LITTLE,ELLIOT,F,Male,African-American,02/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57947,66269,60105,PRETRIAL,Hopkins,Jabari,NULL,Male,African-American,12/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +57947,66269,60105,PRETRIAL,Hopkins,Jabari,NULL,Male,African-American,12/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +57947,66269,60105,PRETRIAL,Hopkins,Jabari,NULL,Male,African-American,12/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57956,66283,60114,Probation,heinemann,taryn,NULL,Female,Caucasian,12/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +57956,66283,60114,Probation,heinemann,taryn,NULL,Female,Caucasian,12/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +57956,66283,60114,Probation,heinemann,taryn,NULL,Female,Caucasian,12/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57957,66285,60116,Probation,BARONA,JAMES,ALBERTO,Male,Hispanic,07/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +57957,66285,60116,Probation,BARONA,JAMES,ALBERTO,Male,Hispanic,07/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +57957,66285,60116,Probation,BARONA,JAMES,ALBERTO,Male,Hispanic,07/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57962,66290,60121,Probation,JOHNSON,LATASHA,S,Female,African-American,12/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.19,4,Low,New,1,0 +57962,66290,60121,Probation,JOHNSON,LATASHA,S,Female,African-American,12/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.1,8,High,New,1,0 +57962,66290,60121,Probation,JOHNSON,LATASHA,S,Female,African-American,12/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57963,66292,60123,Probation,rodriguez,MAURICIO,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/8/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +57963,66292,60123,Probation,rodriguez,MAURICIO,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/8/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +57963,66292,60123,Probation,rodriguez,MAURICIO,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57948,66271,60107,Probation,Carroll,Marianne,NULL,Female,Caucasian,10/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +57948,66271,60107,Probation,Carroll,Marianne,NULL,Female,Caucasian,10/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +57948,66271,60107,Probation,Carroll,Marianne,NULL,Female,Caucasian,10/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57953,66280,60112,Probation,POLO,AHMED,M,Male,Hispanic,03/12/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +57953,66280,60112,Probation,POLO,AHMED,M,Male,Hispanic,03/12/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/13 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +57953,66280,60112,Probation,POLO,AHMED,M,Male,Hispanic,03/12/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57967,66297,60128,PRETRIAL,KELLY,RICHARD,NULL,Male,Caucasian,10/19/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/8/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +57967,66297,60128,PRETRIAL,KELLY,RICHARD,NULL,Male,Caucasian,10/19/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/8/13 0:00,1,Low,8,Risk of Recidivism,-2.58,1,Low,New,1,0 +57967,66297,60128,PRETRIAL,KELLY,RICHARD,NULL,Male,Caucasian,10/19/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57946,66267,60103,PRETRIAL,Hawkins,Angelika,NULL,Female,African-American,06/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +57946,66267,60103,PRETRIAL,Hawkins,Angelika,NULL,Female,African-American,06/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +57946,66267,60103,PRETRIAL,Hawkins,Angelika,NULL,Female,African-American,06/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57905,66276,60058,PRETRIAL,Sternberg,Christopher,NULL,Male,Caucasian,09/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/8/13 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,Copy,1,0 +57905,66276,60058,PRETRIAL,Sternberg,Christopher,NULL,Male,Caucasian,09/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/8/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,Copy,1,0 +57905,66276,60058,PRETRIAL,Sternberg,Christopher,NULL,Male,Caucasian,09/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/8/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +14837,66301,14186,Probation,leslie,nicholas,NULL,Male,Caucasian,03/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.68,2,Low,Copy,1,0 +14837,66301,14186,Probation,leslie,nicholas,NULL,Male,Caucasian,03/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,Copy,1,0 +14837,66301,14186,Probation,leslie,nicholas,NULL,Male,Caucasian,03/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +57983,66322,60148,PRETRIAL,LAMBKE,CINDY,NULL,Female,Caucasian,05/13/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/9/13 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +57983,66322,60148,PRETRIAL,LAMBKE,CINDY,NULL,Female,Caucasian,05/13/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/9/13 0:00,1,Low,8,Risk of Recidivism,-2.61,1,Low,New,1,0 +57983,66322,60148,PRETRIAL,LAMBKE,CINDY,NULL,Female,Caucasian,05/13/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57864,66318,60014,PRETRIAL,RABER,WILLIAM,NULL,Male,Caucasian,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/9/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,Copy,1,0 +57864,66318,60014,PRETRIAL,RABER,WILLIAM,NULL,Male,Caucasian,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/9/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,Copy,1,0 +57864,66318,60014,PRETRIAL,RABER,WILLIAM,NULL,Male,Caucasian,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +57991,66332,60157,Probation,Leon,Yenesis,NULL,Female,Hispanic,07/17/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/9/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +57991,66332,60157,Probation,Leon,Yenesis,NULL,Female,Hispanic,07/17/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/9/13 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +57991,66332,60157,Probation,Leon,Yenesis,NULL,Female,Hispanic,07/17/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57978,66311,60140,Probation,Garcia,Giovanni,NULL,Male,Hispanic,03/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,4,High,7,Risk of Violence,-1.07,8,High,New,1,0 +57978,66311,60140,Probation,Garcia,Giovanni,NULL,Male,Hispanic,03/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +57978,66311,60140,Probation,Garcia,Giovanni,NULL,Male,Hispanic,03/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57979,66313,60142,PRETRIAL,Santoni,Patrick,NULL,Male,Caucasian,05/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +57979,66313,60142,PRETRIAL,Santoni,Patrick,NULL,Male,Caucasian,05/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +57979,66313,60142,PRETRIAL,Santoni,Patrick,NULL,Male,Caucasian,05/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57974,66306,60135,PRETRIAL,Glasgow,Shawn,NULL,Male,African-American,08/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +57974,66306,60135,PRETRIAL,Glasgow,Shawn,NULL,Male,African-American,08/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +57974,66306,60135,PRETRIAL,Glasgow,Shawn,NULL,Male,African-American,08/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57981,66320,60146,PRETRIAL,Leconte,Tara,NULL,Female,African-American,01/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +57981,66320,60146,PRETRIAL,Leconte,Tara,NULL,Female,African-American,01/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +57981,66320,60146,PRETRIAL,Leconte,Tara,NULL,Female,African-American,01/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57986,66327,60152,PRETRIAL,Williamson,Derrick,NULL,Male,African-American,07/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/9/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +57986,66327,60152,PRETRIAL,Williamson,Derrick,NULL,Male,African-American,07/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/9/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +57986,66327,60152,PRETRIAL,Williamson,Derrick,NULL,Male,African-American,07/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57992,66334,60159,PRETRIAL,MASSARO,STACY,NULL,Female,Caucasian,03/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +57992,66334,60159,PRETRIAL,MASSARO,STACY,NULL,Female,Caucasian,03/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +57992,66334,60159,PRETRIAL,MASSARO,STACY,NULL,Female,Caucasian,03/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57976,66308,60137,PRETRIAL,Turbe,Jarrod,NULL,Male,African-American,12/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +57976,66308,60137,PRETRIAL,Turbe,Jarrod,NULL,Male,African-American,12/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +57976,66308,60137,PRETRIAL,Turbe,Jarrod,NULL,Male,African-American,12/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57988,66329,60154,PRETRIAL,Johnson,Reginald,NULL,Male,African-American,07/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +57988,66329,60154,PRETRIAL,Johnson,Reginald,NULL,Male,African-American,07/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +57988,66329,60154,PRETRIAL,Johnson,Reginald,NULL,Male,African-American,07/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57971,66303,60132,PRETRIAL,Desvergers,Russell,Neal,Male,Caucasian,05/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +57971,66303,60132,PRETRIAL,Desvergers,Russell,Neal,Male,Caucasian,05/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +57971,66303,60132,PRETRIAL,Desvergers,Russell,Neal,Male,Caucasian,05/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57982,66321,60147,Probation,stewart,tishawna,NULL,Female,African-American,05/11/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,4,High,7,Risk of Violence,-0.6,10,High,New,1,0 +57982,66321,60147,Probation,stewart,tishawna,NULL,Female,African-American,05/11/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,4,High,8,Risk of Recidivism,1.04,10,High,New,1,0 +57982,66321,60147,Probation,stewart,tishawna,NULL,Female,African-American,05/11/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +26222,66324,60150,PRETRIAL,salters,alan,NULL,Male,African-American,03/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +26222,66324,60150,PRETRIAL,salters,alan,NULL,Male,African-American,03/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +26222,66324,60150,PRETRIAL,salters,alan,NULL,Male,African-American,03/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +43205,66310,60139,PRETRIAL,KENDIRCK,SADE,NULL,Female,African-American,08/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +43205,66310,60139,PRETRIAL,KENDIRCK,SADE,NULL,Female,African-American,08/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +43205,66310,60139,PRETRIAL,KENDIRCK,SADE,NULL,Female,African-American,08/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +5911,66314,59212,PRETRIAL,POPLIN,BELINDA,FAYE,Female,Caucasian,09/26/69,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.38,3,Low,New,1,0 +5911,66314,59212,PRETRIAL,POPLIN,BELINDA,FAYE,Female,Caucasian,09/26/69,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +5911,66314,59212,PRETRIAL,POPLIN,BELINDA,FAYE,Female,Caucasian,09/26/69,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,9,High,New,1,0 +57990,66331,60156,Probation,clarke,steven,NULL,Male,African-American,01/25/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +57990,66331,60156,Probation,clarke,steven,NULL,Male,African-American,01/25/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +57990,66331,60156,Probation,clarke,steven,NULL,Male,African-American,01/25/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57987,66328,60153,PRETRIAL,Oneal,Mary,NULL,Female,African-American,12/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/9/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +57987,66328,60153,PRETRIAL,Oneal,Mary,NULL,Female,African-American,12/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/9/13 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +57987,66328,60153,PRETRIAL,Oneal,Mary,NULL,Female,African-American,12/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57980,66319,60145,Probation,Jones,Thomas,NULL,Male,Caucasian,09/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +57980,66319,60145,Probation,Jones,Thomas,NULL,Male,Caucasian,09/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +57980,66319,60145,Probation,Jones,Thomas,NULL,Male,Caucasian,09/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57985,66326,60151,PRETRIAL,Thomas,Jaron,NULL,Male,African-American,07/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +57985,66326,60151,PRETRIAL,Thomas,Jaron,NULL,Male,African-American,07/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +57985,66326,60151,PRETRIAL,Thomas,Jaron,NULL,Male,African-American,07/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57973,66305,60134,PRETRIAL,Hendricks,Cassandra,NULL,Female,Caucasian,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +57973,66305,60134,PRETRIAL,Hendricks,Cassandra,NULL,Female,Caucasian,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,New,1,0 +57973,66305,60134,PRETRIAL,Hendricks,Cassandra,NULL,Female,Caucasian,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,9,High,New,1,0 +33123,66312,60141,PRETRIAL,Roaches,Krista,NULL,Female,African-American,03/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/9/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +33123,66312,60141,PRETRIAL,Roaches,Krista,NULL,Female,African-American,03/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/9/13 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +33123,66312,60141,PRETRIAL,Roaches,Krista,NULL,Female,African-American,03/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +34434,66333,60158,PRETRIAL,Stewart,Dave,NULL,Male,African-American,05/27/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/9/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +34434,66333,60158,PRETRIAL,Stewart,Dave,NULL,Male,African-American,05/27/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/9/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +34434,66333,60158,PRETRIAL,Stewart,Dave,NULL,Male,African-American,05/27/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57972,66304,60133,PRETRIAL,Hecht,Robert,NULL,Male,Caucasian,07/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +57972,66304,60133,PRETRIAL,Hecht,Robert,NULL,Male,Caucasian,07/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +57972,66304,60133,PRETRIAL,Hecht,Robert,NULL,Male,Caucasian,07/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57975,66307,60136,PRETRIAL,ISCARO,RITA,NULL,Male,Caucasian,10/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/9/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +57975,66307,60136,PRETRIAL,ISCARO,RITA,NULL,Male,Caucasian,10/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/9/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +57975,66307,60136,PRETRIAL,ISCARO,RITA,NULL,Male,Caucasian,10/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57263,66325,59358,Probation,CIRIGLIANO,TIMOTHY,W,Male,Caucasian,12/14/75,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/9/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +57263,66325,59358,Probation,CIRIGLIANO,TIMOTHY,W,Male,Caucasian,12/14/75,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/9/13 0:00,1,Low,8,Risk of Recidivism,-0.48,4,Low,New,1,0 +57263,66325,59358,Probation,CIRIGLIANO,TIMOTHY,W,Male,Caucasian,12/14/75,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,23,4,Low,New,1,0 +45813,66315,60143,PRETRIAL,POZIT,FELICIA,NULL,Female,Caucasian,11/01/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +45813,66315,60143,PRETRIAL,POZIT,FELICIA,NULL,Female,Caucasian,11/01/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +45813,66315,60143,PRETRIAL,POZIT,FELICIA,NULL,Female,Caucasian,11/01/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57989,66330,60155,PRETRIAL,JACKSON,ALICIA,NULL,Female,African-American,09/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +57989,66330,60155,PRETRIAL,JACKSON,ALICIA,NULL,Female,African-American,09/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +57989,66330,60155,PRETRIAL,JACKSON,ALICIA,NULL,Female,African-American,09/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +34113,66317,60144,PRETRIAL,Howitt,Venessa,NULL,Female,African-American,09/17/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/9/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +34113,66317,60144,PRETRIAL,Howitt,Venessa,NULL,Female,African-American,09/17/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +34113,66317,60144,PRETRIAL,Howitt,Venessa,NULL,Female,African-American,09/17/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/9/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57984,66323,60149,Probation,Jackson,Sirron,NULL,Male,African-American,10/06/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +57984,66323,60149,Probation,Jackson,Sirron,NULL,Male,African-American,10/06/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.78,10,High,New,1,0 +57984,66323,60149,Probation,Jackson,Sirron,NULL,Male,African-American,10/06/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +57970,66302,60131,PRETRIAL,DANIELS,WANDA,NULL,Female,African-American,12/18/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.85,2,Low,New,1,0 +57970,66302,60131,PRETRIAL,DANIELS,WANDA,NULL,Female,African-American,12/18/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,10,High,New,1,0 +57970,66302,60131,PRETRIAL,DANIELS,WANDA,NULL,Female,African-American,12/18/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,39,10,High,New,1,0 +57977,66309,60138,PRETRIAL,ALFORD,DANNY,DEVON,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,4,High,7,Risk of Violence,-0.73,9,High,New,1,0 +57977,66309,60138,PRETRIAL,ALFORD,DANNY,DEVON,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,New,1,0 +57977,66309,60138,PRETRIAL,ALFORD,DANNY,DEVON,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57995,66338,60163,PRETRIAL,Herring,Jason,NULL,Male,Caucasian,11/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +57995,66338,60163,PRETRIAL,Herring,Jason,NULL,Male,Caucasian,11/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +57995,66338,60163,PRETRIAL,Herring,Jason,NULL,Male,Caucasian,11/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58004,66351,60175,Probation,Carrion,Saul,NULL,Male,Hispanic,11/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +58004,66351,60175,Probation,Carrion,Saul,NULL,Male,Hispanic,11/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +58004,66351,60175,Probation,Carrion,Saul,NULL,Male,Hispanic,11/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58019,66375,60198,Probation,rodriguez,javier,NULL,Male,Hispanic,12/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +58019,66375,60198,Probation,rodriguez,javier,NULL,Male,Hispanic,12/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +58019,66375,60198,Probation,rodriguez,javier,NULL,Male,Hispanic,12/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58007,66354,60178,PRETRIAL,Ocio,virgini,NULL,Female,Caucasian,03/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +58007,66354,60178,PRETRIAL,Ocio,virgini,NULL,Female,Caucasian,03/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +58007,66354,60178,PRETRIAL,Ocio,virgini,NULL,Female,Caucasian,03/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58017,66372,60195,Probation,COX,NOEL,NULL,Male,African-American,01/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +58017,66372,60195,Probation,COX,NOEL,NULL,Male,African-American,01/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +58017,66372,60195,Probation,COX,NOEL,NULL,Male,African-American,01/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +57965,66346,60171,DRRD,Taylor,Harry,Leonard,Male,African-American,08/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,4,High,7,Risk of Violence,-0.16,10,High,New,1,0 +57965,66346,60171,DRRD,Taylor,Harry,Leonard,Male,African-American,08/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,4,High,8,Risk of Recidivism,1.33,10,High,New,1,0 +57965,66346,60171,DRRD,Taylor,Harry,Leonard,Male,African-American,08/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58023,66380,60202,Probation,Santana Romero,William,NULL,Male,Hispanic,05/30/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +58023,66380,60202,Probation,Santana Romero,William,NULL,Male,Hispanic,05/30/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +58023,66380,60202,Probation,Santana Romero,William,NULL,Male,Hispanic,05/30/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +33659,66356,60180,PRETRIAL,Skovron,Keely,NULL,Female,Caucasian,11/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +33659,66356,60180,PRETRIAL,Skovron,Keely,NULL,Female,Caucasian,11/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +33659,66356,60180,PRETRIAL,Skovron,Keely,NULL,Female,Caucasian,11/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +16722,66370,60193,PRETRIAL,McCreath,Mikhail,Che,Male,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +16722,66370,60193,PRETRIAL,McCreath,Mikhail,Che,Male,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +16722,66370,60193,PRETRIAL,McCreath,Mikhail,Che,Male,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58021,66377,60200,Probation,jones,chiquita,NULL,Female,African-American,12/20/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +58021,66377,60200,Probation,jones,chiquita,NULL,Female,African-American,12/20/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +58021,66377,60200,Probation,jones,chiquita,NULL,Female,African-American,12/20/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50622,66384,60206,PRETRIAL,Little,Stephanie,NULL,Female,African-American,10/20/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +50622,66384,60206,PRETRIAL,Little,Stephanie,NULL,Female,African-American,10/20/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +50622,66384,60206,PRETRIAL,Little,Stephanie,NULL,Female,African-American,10/20/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +6227,66349,60174,PRETRIAL,Singletary,Shelly,NULL,Male,African-American,09/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.61,2,Low,New,1,0 +6227,66349,60174,PRETRIAL,Singletary,Shelly,NULL,Male,African-American,09/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +6227,66349,60174,PRETRIAL,Singletary,Shelly,NULL,Male,African-American,09/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58002,66347,60172,PRETRIAL,OTTO,MICHELLE,NULL,Female,Caucasian,03/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +58002,66347,60172,PRETRIAL,OTTO,MICHELLE,NULL,Female,Caucasian,03/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +58002,66347,60172,PRETRIAL,OTTO,MICHELLE,NULL,Female,Caucasian,03/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58013,66365,60188,PRETRIAL,meneses,reynaldo,NULL,Male,Hispanic,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +58013,66365,60188,PRETRIAL,meneses,reynaldo,NULL,Male,Hispanic,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +58013,66365,60188,PRETRIAL,meneses,reynaldo,NULL,Male,Hispanic,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57993,66335,60160,PRETRIAL,Metellus,Richllen,NULL,Male,African-American,05/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +57993,66335,60160,PRETRIAL,Metellus,Richllen,NULL,Male,African-American,05/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +57993,66335,60160,PRETRIAL,Metellus,Richllen,NULL,Male,African-American,05/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58000,66344,60169,PRETRIAL,Quaknine,Tania,NULL,Female,Caucasian,07/21/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +58000,66344,60169,PRETRIAL,Quaknine,Tania,NULL,Female,Caucasian,07/21/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +58000,66344,60169,PRETRIAL,Quaknine,Tania,NULL,Female,Caucasian,07/21/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58011,66361,60185,Probation,Mendozadiaz,Francisco,NULL,Male,Hispanic,05/01/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +58011,66361,60185,Probation,Mendozadiaz,Francisco,NULL,Male,Hispanic,05/01/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +58011,66361,60185,Probation,Mendozadiaz,Francisco,NULL,Male,Hispanic,05/01/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58025,66382,60204,Probation,GIRARD,NESTER,NULL,Male,African-American,03/01/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +58025,66382,60204,Probation,GIRARD,NESTER,NULL,Male,African-American,03/01/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +58025,66382,60204,Probation,GIRARD,NESTER,NULL,Male,African-American,03/01/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58027,66386,60208,Probation,Grozdanov,hristo,NULL,Male,Other,09/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +58027,66386,60208,Probation,Grozdanov,hristo,NULL,Male,Other,09/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +58027,66386,60208,Probation,Grozdanov,hristo,NULL,Male,Other,09/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57997,66340,60165,PRETRIAL,Burns,Kevin,NULL,Male,Caucasian,04/16/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +57997,66340,60165,PRETRIAL,Burns,Kevin,NULL,Male,Caucasian,04/16/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +57997,66340,60165,PRETRIAL,Burns,Kevin,NULL,Male,Caucasian,04/16/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58009,66358,60182,Probation,Schunk,Brian,NULL,Male,Caucasian,04/13/87,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +58009,66358,60182,Probation,Schunk,Brian,NULL,Male,Caucasian,04/13/87,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +58009,66358,60182,Probation,Schunk,Brian,NULL,Male,Caucasian,04/13/87,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58001,66345,60170,PRETRIAL,Jefferson,Shawntoria,NULL,Female,African-American,06/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +58001,66345,60170,PRETRIAL,Jefferson,Shawntoria,NULL,Female,African-American,06/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +58001,66345,60170,PRETRIAL,Jefferson,Shawntoria,NULL,Female,African-American,06/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58024,66381,60203,Probation,Kent,Jill,NULL,Female,Caucasian,01/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +58024,66381,60203,Probation,Kent,Jill,NULL,Female,Caucasian,01/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,New,1,0 +58024,66381,60203,Probation,Kent,Jill,NULL,Female,Caucasian,01/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57994,66337,60162,PRETRIAL,Clark,Timothy,NULL,Male,African-American,01/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.15,4,Low,New,1,0 +57994,66337,60162,PRETRIAL,Clark,Timothy,NULL,Male,African-American,01/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +57994,66337,60162,PRETRIAL,Clark,Timothy,NULL,Male,African-American,01/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58018,66373,60196,Probation,Spangler,Sierra,NULL,Female,Caucasian,01/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,New,1,0 +58018,66373,60196,Probation,Spangler,Sierra,NULL,Female,Caucasian,01/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +58018,66373,60196,Probation,Spangler,Sierra,NULL,Female,Caucasian,01/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58005,66352,60176,Probation,Soto,Francisco,NULL,Male,Hispanic,06/27/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +58005,66352,60176,Probation,Soto,Francisco,NULL,Male,Hispanic,06/27/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +58005,66352,60176,Probation,Soto,Francisco,NULL,Male,Hispanic,06/27/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50591,66366,60189,PRETRIAL,YANEZ,FELIX,NULL,Male,Caucasian,04/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +50591,66366,60189,PRETRIAL,YANEZ,FELIX,NULL,Male,Caucasian,04/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +50591,66366,60189,PRETRIAL,YANEZ,FELIX,NULL,Male,Caucasian,04/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +11577,66371,60194,PRETRIAL,MARION,NATHANEL,NULL,Male,African-American,05/31/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +11577,66371,60194,PRETRIAL,MARION,NATHANEL,NULL,Male,African-American,05/31/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +11577,66371,60194,PRETRIAL,MARION,NATHANEL,NULL,Male,African-American,05/31/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58015,66368,60191,PRETRIAL,JONES,LLEWELLYN,ANTHONY,Male,African-American,11/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +58015,66368,60191,PRETRIAL,JONES,LLEWELLYN,ANTHONY,Male,African-American,11/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +58015,66368,60191,PRETRIAL,JONES,LLEWELLYN,ANTHONY,Male,African-American,11/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +7034,66363,6624,PRETRIAL,Wongwon,roderick,lamout,Male,African-American,09/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,Copy,1,0 +7034,66363,6624,PRETRIAL,Wongwon,roderick,lamout,Male,African-American,09/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,Copy,1,0 +7034,66363,6624,PRETRIAL,Wongwon,roderick,lamout,Male,African-American,09/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +57998,66342,60167,PRETRIAL,JONES,JARVIS,NULL,Male,African-American,03/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +57998,66342,60167,PRETRIAL,JONES,JARVIS,NULL,Male,African-American,03/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +57998,66342,60167,PRETRIAL,JONES,JARVIS,NULL,Male,African-American,03/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58020,66376,60199,Probation,collins,kiandra,NULL,Female,African-American,10/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +58020,66376,60199,Probation,collins,kiandra,NULL,Female,African-American,10/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.81,10,High,New,1,0 +58020,66376,60199,Probation,collins,kiandra,NULL,Female,African-American,10/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +22874,66355,60179,DRRD,Harris,Richard,Andrew,Male,African-American,12/06/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +22874,66355,60179,DRRD,Harris,Richard,Andrew,Male,African-American,12/06/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +22874,66355,60179,DRRD,Harris,Richard,Andrew,Male,African-American,12/06/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +39337,66362,60186,Probation,softy,charles,NULL,Male,Caucasian,04/14/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +39337,66362,60186,Probation,softy,charles,NULL,Male,Caucasian,04/14/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +39337,66362,60186,Probation,softy,charles,NULL,Male,Caucasian,04/14/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,40,10,High,New,1,0 +39725,66364,60187,PRETRIAL,Benjamin,Louinie,NULL,Female,African-American,08/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +39725,66364,60187,PRETRIAL,Benjamin,Louinie,NULL,Female,African-American,08/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +39725,66364,60187,PRETRIAL,Benjamin,Louinie,NULL,Female,African-American,08/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +47567,66383,60205,PRETRIAL,MASSEY,HAMILTON,W,Male,African-American,05/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +47567,66383,60205,PRETRIAL,MASSEY,HAMILTON,W,Male,African-American,05/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +47567,66383,60205,PRETRIAL,MASSEY,HAMILTON,W,Male,African-American,05/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58026,66385,60207,Probation,Davilla,Josue,NULL,Male,Hispanic,07/19/78,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/10/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +58026,66385,60207,Probation,Davilla,Josue,NULL,Male,Hispanic,07/19/78,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/10/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +58026,66385,60207,Probation,Davilla,Josue,NULL,Male,Hispanic,07/19/78,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57999,66343,60168,PRETRIAL,Howard,Torrence,NULL,Male,African-American,07/31/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +57999,66343,60168,PRETRIAL,Howard,Torrence,NULL,Male,African-American,07/31/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +57999,66343,60168,PRETRIAL,Howard,Torrence,NULL,Male,African-American,07/31/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +10984,66336,60161,PRETRIAL,Ali,Ben,NULL,Male,African-American,07/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +10984,66336,60161,PRETRIAL,Ali,Ben,NULL,Male,African-American,07/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +10984,66336,60161,PRETRIAL,Ali,Ben,NULL,Male,African-American,07/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57996,66339,60164,PRETRIAL,Pierre,Ronald,NULL,Male,African-American,09/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +57996,66339,60164,PRETRIAL,Pierre,Ronald,NULL,Male,African-American,09/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +57996,66339,60164,PRETRIAL,Pierre,Ronald,NULL,Male,African-American,09/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58012,66369,60192,PRETRIAL,Campos,Timothy,NULL,Male,Caucasian,07/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +58012,66369,60192,PRETRIAL,Campos,Timothy,NULL,Male,Caucasian,07/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +58012,66369,60192,PRETRIAL,Campos,Timothy,NULL,Male,Caucasian,07/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +37115,66374,60197,Probation,drew,ronald,NULL,Male,African-American,11/16/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/10/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +37115,66374,60197,Probation,drew,ronald,NULL,Male,African-American,11/16/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/10/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +37115,66374,60197,Probation,drew,ronald,NULL,Male,African-American,11/16/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/10/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58003,66348,60173,PRETRIAL,WILLIAMS,BRITENY,NULL,Female,Caucasian,01/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +58003,66348,60173,PRETRIAL,WILLIAMS,BRITENY,NULL,Female,Caucasian,01/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,9,High,New,1,0 +58003,66348,60173,PRETRIAL,WILLIAMS,BRITENY,NULL,Female,Caucasian,01/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58040,66399,60221,Probation,Whitehead,Nickia,NULL,Male,African-American,08/11/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +58040,66399,60221,Probation,Whitehead,Nickia,NULL,Male,African-American,08/11/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.15,10,High,New,1,0 +58040,66399,60221,Probation,Whitehead,Nickia,NULL,Male,African-American,08/11/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +10419,66408,60230,PRETRIAL,THOMPSON,LEONARDO,D,Male,African-American,01/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +10419,66408,60230,PRETRIAL,THOMPSON,LEONARDO,D,Male,African-American,01/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +10419,66408,60230,PRETRIAL,THOMPSON,LEONARDO,D,Male,African-American,01/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +58031,66390,60212,PRETRIAL,Pierre,Carlos,NULL,Male,African-American,06/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,4,High,7,Risk of Violence,-0.16,10,High,New,1,0 +58031,66390,60212,PRETRIAL,Pierre,Carlos,NULL,Male,African-American,06/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,4,High,8,Risk of Recidivism,0.96,10,High,New,1,0 +58031,66390,60212,PRETRIAL,Pierre,Carlos,NULL,Male,African-American,06/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58045,66404,60226,Probation,selzer,david,NULL,Male,Caucasian,01/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.96,1,Low,New,1,0 +58045,66404,60226,Probation,selzer,david,NULL,Male,Caucasian,01/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,New,1,0 +58045,66404,60226,Probation,selzer,david,NULL,Male,Caucasian,01/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +50114,66411,60233,PRETRIAL,Carter,Christopher,NULL,Male,Caucasian,09/28/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/11/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +50114,66411,60233,PRETRIAL,Carter,Christopher,NULL,Male,Caucasian,09/28/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/11/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +50114,66411,60233,PRETRIAL,Carter,Christopher,NULL,Male,Caucasian,09/28/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58033,66392,60214,PRETRIAL,Flynn,Jamie,NULL,Male,Caucasian,04/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +58033,66392,60214,PRETRIAL,Flynn,Jamie,NULL,Male,Caucasian,04/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +58033,66392,60214,PRETRIAL,Flynn,Jamie,NULL,Male,Caucasian,04/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58052,66413,60235,PRETRIAL,Bauman,Lawrence,NULL,Male,Caucasian,06/28/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/11/13 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +58052,66413,60235,PRETRIAL,Bauman,Lawrence,NULL,Male,Caucasian,06/28/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/11/13 0:00,1,Low,8,Risk of Recidivism,-2.73,1,Low,New,1,0 +58052,66413,60235,PRETRIAL,Bauman,Lawrence,NULL,Male,Caucasian,06/28/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58047,66406,60228,Probation,Futo,Andrew,NULL,Male,Hispanic,01/25/65,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/11/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +58047,66406,60228,Probation,Futo,Andrew,NULL,Male,Hispanic,01/25/65,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/11/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +58047,66406,60228,Probation,Futo,Andrew,NULL,Male,Hispanic,01/25/65,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +58058,66420,60242,PRETRIAL,Zachary,Deborah,NULL,Female,Caucasian,08/18/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,10/11/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +58058,66420,60242,PRETRIAL,Zachary,Deborah,NULL,Female,Caucasian,08/18/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,10/11/13 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +58058,66420,60242,PRETRIAL,Zachary,Deborah,NULL,Female,Caucasian,08/18/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +16521,66397,60219,Probation,WASHINGTON,KEISHA,NICHOLE,Female,African-American,09/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +16521,66397,60219,Probation,WASHINGTON,KEISHA,NICHOLE,Female,African-American,09/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +16521,66397,60219,Probation,WASHINGTON,KEISHA,NICHOLE,Female,African-American,09/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58030,66389,60211,PRETRIAL,Smith,David,NULL,Male,African-American,01/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +58030,66389,60211,PRETRIAL,Smith,David,NULL,Male,African-American,01/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +58030,66389,60211,PRETRIAL,Smith,David,NULL,Male,African-American,01/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +58043,66402,60224,Probation,SWIFT,MICHAEL,JOSEPH,Male,Caucasian,10/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +58043,66402,60224,Probation,SWIFT,MICHAEL,JOSEPH,Male,Caucasian,10/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +58043,66402,60224,Probation,SWIFT,MICHAEL,JOSEPH,Male,Caucasian,10/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +31727,66423,47680,PRETRIAL,GRAYHEART,CHRISTOPHER,NULL,Male,African-American,01/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,4,High,7,Risk of Violence,-1.07,8,High,Copy,1,0 +31727,66423,47680,PRETRIAL,GRAYHEART,CHRISTOPHER,NULL,Male,African-American,01/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,4,High,8,Risk of Recidivism,0.45,9,High,Copy,1,0 +31727,66423,47680,PRETRIAL,GRAYHEART,CHRISTOPHER,NULL,Male,African-American,01/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +58054,66415,60237,PRETRIAL,Foy,Patrick,NULL,Male,African-American,02/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,4,High,7,Risk of Violence,-1.17,8,High,New,1,0 +58054,66415,60237,PRETRIAL,Foy,Patrick,NULL,Male,African-American,02/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,4,High,8,Risk of Recidivism,0.67,10,High,New,1,0 +58054,66415,60237,PRETRIAL,Foy,Patrick,NULL,Male,African-American,02/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58035,66394,60216,PRETRIAL,Jacques,Joyce,NULL,Female,Other,11/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/11/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +58035,66394,60216,PRETRIAL,Jacques,Joyce,NULL,Female,Other,11/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/11/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +58035,66394,60216,PRETRIAL,Jacques,Joyce,NULL,Female,Other,11/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58044,66403,60225,Probation,Wolfe,James,NULL,Male,Caucasian,11/28/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,7,Risk of Violence,-4.34,1,Low,New,1,0 +58044,66403,60225,Probation,Wolfe,James,NULL,Male,Caucasian,11/28/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +58044,66403,60225,Probation,Wolfe,James,NULL,Male,Caucasian,11/28/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58059,66421,60243,Probation,perry,Lakesha,NULL,Female,African-American,05/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +58059,66421,60243,Probation,perry,Lakesha,NULL,Female,African-American,05/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +58059,66421,60243,Probation,perry,Lakesha,NULL,Female,African-American,05/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58041,66400,60222,Probation,STANLEY,THERESA,M,Female,African-American,06/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +58041,66400,60222,Probation,STANLEY,THERESA,M,Female,African-American,06/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +58041,66400,60222,Probation,STANLEY,THERESA,M,Female,African-American,06/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +46183,66407,60229,PRETRIAL,Couch,Laurence,Gregory,Male,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +46183,66407,60229,PRETRIAL,Couch,Laurence,Gregory,Male,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +46183,66407,60229,PRETRIAL,Couch,Laurence,Gregory,Male,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58051,66412,60234,PRETRIAL,Thirsty,Melvin,NULL,Male,African-American,10/15/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,4,High,7,Risk of Violence,-0.43,10,High,New,1,0 +58051,66412,60234,PRETRIAL,Thirsty,Melvin,NULL,Male,African-American,10/15/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,4,High,8,Risk of Recidivism,0.11,8,High,New,1,0 +58051,66412,60234,PRETRIAL,Thirsty,Melvin,NULL,Male,African-American,10/15/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +58039,66398,60220,Probation,malave,jose,NULL,Male,Hispanic,05/21/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +58039,66398,60220,Probation,malave,jose,NULL,Male,Hispanic,05/21/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +58039,66398,60220,Probation,malave,jose,NULL,Male,Hispanic,05/21/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +6580,66419,60241,PRETRIAL,GONZALES,ALBERTO,NULL,Male,Hispanic,06/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +6580,66419,60241,PRETRIAL,GONZALES,ALBERTO,NULL,Male,Hispanic,06/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +6580,66419,60241,PRETRIAL,GONZALES,ALBERTO,NULL,Male,Hispanic,06/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58032,66391,60213,PRETRIAL,Roberts,Joseph,NULL,Male,African-American,02/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +58032,66391,60213,PRETRIAL,Roberts,Joseph,NULL,Male,African-American,02/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +58032,66391,60213,PRETRIAL,Roberts,Joseph,NULL,Male,African-American,02/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,2,Medium,18,Risk of Failure to Appear,35,10,High,New,1,0 +58046,66405,60227,Probation,BRYANT,JOQUIAL,C,Female,African-American,12/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +58046,66405,60227,Probation,BRYANT,JOQUIAL,C,Female,African-American,12/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +58046,66405,60227,Probation,BRYANT,JOQUIAL,C,Female,African-American,12/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58053,66414,60236,PRETRIAL,COUSINO,JASON,NULL,Male,Caucasian,12/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/11/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +58053,66414,60236,PRETRIAL,COUSINO,JASON,NULL,Male,Caucasian,12/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/11/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +58053,66414,60236,PRETRIAL,COUSINO,JASON,NULL,Male,Caucasian,12/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58034,66393,60215,PRETRIAL,innocent,Jean,NULL,Male,African-American,01/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +58034,66393,60215,PRETRIAL,innocent,Jean,NULL,Male,African-American,01/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +58034,66393,60215,PRETRIAL,innocent,Jean,NULL,Male,African-American,01/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58056,66417,60239,Probation,Banihashemi,Seyed,NULL,Male,Other,04/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +58056,66417,60239,Probation,Banihashemi,Seyed,NULL,Male,Other,04/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +58056,66417,60239,Probation,Banihashemi,Seyed,NULL,Male,Other,04/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58037,66396,60218,Probation,Mtchell,John,NULL,Male,Caucasian,11/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/11/13 0:00,2,Medium,7,Risk of Violence,-2.95,1,Low,New,1,0 +58037,66396,60218,Probation,Mtchell,John,NULL,Male,Caucasian,11/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +58037,66396,60218,Probation,Mtchell,John,NULL,Male,Caucasian,11/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/11/13 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +58029,66388,60210,PRETRIAL,Kersey,Sandra,NULL,Female,Other,12/31/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +58029,66388,60210,PRETRIAL,Kersey,Sandra,NULL,Female,Other,12/31/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +58029,66388,60210,PRETRIAL,Kersey,Sandra,NULL,Female,Other,12/31/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58048,66409,60231,Probation,deroseau,ben,NULL,Male,African-American,06/25/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +58048,66409,60231,Probation,deroseau,ben,NULL,Male,African-American,06/25/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +58048,66409,60231,Probation,deroseau,ben,NULL,Male,African-American,06/25/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54122,66430,55683,PRETRIAL,CASH,LEROY,JOSE,Male,Caucasian,04/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,Copy,1,0 +54122,66430,55683,PRETRIAL,CASH,LEROY,JOSE,Male,Caucasian,04/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,Copy,1,0 +54122,66430,55683,PRETRIAL,CASH,LEROY,JOSE,Male,Caucasian,04/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +58070,66432,60252,PRETRIAL,BANSIE,STEVEN,NULL,Male,Other,09/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +58070,66432,60252,PRETRIAL,BANSIE,STEVEN,NULL,Male,Other,09/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +58070,66432,60252,PRETRIAL,BANSIE,STEVEN,NULL,Male,Other,09/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58060,66424,60245,PRETRIAL,Irvin,Terrance,NULL,Male,African-American,04/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +58060,66424,60245,PRETRIAL,Irvin,Terrance,NULL,Male,African-American,04/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +58060,66424,60245,PRETRIAL,Irvin,Terrance,NULL,Male,African-American,04/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58065,66426,60247,PRETRIAL,Addeo,Brian,NULL,Male,Caucasian,01/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +58065,66426,60247,PRETRIAL,Addeo,Brian,NULL,Male,Caucasian,01/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +58065,66426,60247,PRETRIAL,Addeo,Brian,NULL,Male,Caucasian,01/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58067,66428,60249,PRETRIAL,Funchess,Tim,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +58067,66428,60249,PRETRIAL,Funchess,Tim,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +58067,66428,60249,PRETRIAL,Funchess,Tim,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56195,66433,60253,PRETRIAL,NICOLAS,NIKENSON,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +56195,66433,60253,PRETRIAL,NICOLAS,NIKENSON,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +56195,66433,60253,PRETRIAL,NICOLAS,NIKENSON,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58069,66431,60251,PRETRIAL,Lang,Ronald,NULL,Male,African-American,02/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,7,Risk of Violence,-2.76,2,Low,New,1,0 +58069,66431,60251,PRETRIAL,Lang,Ronald,NULL,Male,African-American,02/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +58069,66431,60251,PRETRIAL,Lang,Ronald,NULL,Male,African-American,02/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58066,66427,60248,PRETRIAL,CLEOPHAR,VILARDIN,NULL,Male,African-American,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +58066,66427,60248,PRETRIAL,CLEOPHAR,VILARDIN,NULL,Male,African-American,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +58066,66427,60248,PRETRIAL,CLEOPHAR,VILARDIN,NULL,Male,African-American,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58071,66434,60254,PRETRIAL,Williams,Dersshawn,NULL,Male,African-American,04/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +58071,66434,60254,PRETRIAL,Williams,Dersshawn,NULL,Male,African-American,04/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +58071,66434,60254,PRETRIAL,Williams,Dersshawn,NULL,Male,African-American,04/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +43011,66425,60246,PRETRIAL,PARRIS,CHRISTOPHER,A,Male,African-American,12/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +43011,66425,60246,PRETRIAL,PARRIS,CHRISTOPHER,A,Male,African-American,12/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +43011,66425,60246,PRETRIAL,PARRIS,CHRISTOPHER,A,Male,African-American,12/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58068,66429,60250,PRETRIAL,DOCTOR,TERRTRIC,NULL,Male,African-American,02/28/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/12/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +58068,66429,60250,PRETRIAL,DOCTOR,TERRTRIC,NULL,Male,African-American,02/28/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/12/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +58068,66429,60250,PRETRIAL,DOCTOR,TERRTRIC,NULL,Male,African-American,02/28/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58081,66446,60264,PRETRIAL,MCCrea,Irish,Nicole,Female,African-American,11/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/13/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +58081,66446,60264,PRETRIAL,MCCrea,Irish,Nicole,Female,African-American,11/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/13/13 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +58081,66446,60264,PRETRIAL,MCCrea,Irish,Nicole,Female,African-American,11/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +11134,66441,10652,Probation,Ace,Stanley,NULL,Male,African-American,07/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,Copy,1,0 +11134,66441,10652,Probation,Ace,Stanley,NULL,Male,African-American,07/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,Copy,1,0 +11134,66441,10652,Probation,Ace,Stanley,NULL,Male,African-American,07/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +58079,66444,60262,PRETRIAL,Pirolo,Anthony,NULL,Male,Caucasian,04/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +58079,66444,60262,PRETRIAL,Pirolo,Anthony,NULL,Male,Caucasian,04/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +58079,66444,60262,PRETRIAL,Pirolo,Anthony,NULL,Male,Caucasian,04/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58076,66439,60259,PRETRIAL,BEACH,JOSHUA,NULL,Male,African-American,04/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +58076,66439,60259,PRETRIAL,BEACH,JOSHUA,NULL,Male,African-American,04/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +58076,66439,60259,PRETRIAL,BEACH,JOSHUA,NULL,Male,African-American,04/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58073,66436,60256,PRETRIAL,MEJIAS,MARILYN,NULL,Female,Hispanic,11/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +58073,66436,60256,PRETRIAL,MEJIAS,MARILYN,NULL,Female,Hispanic,11/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,New,1,0 +58073,66436,60256,PRETRIAL,MEJIAS,MARILYN,NULL,Female,Hispanic,11/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54190,66442,55771,PRETRIAL,seymore,john,NULL,Male,African-American,11/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.5,3,Low,Copy,1,0 +54190,66442,55771,PRETRIAL,seymore,john,NULL,Male,African-American,11/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,Copy,1,0 +54190,66442,55771,PRETRIAL,seymore,john,NULL,Male,African-American,11/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +4973,66447,58181,Probation,Whittaker,Ryan,NULL,Male,Other,10/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,Copy,1,0 +4973,66447,58181,Probation,Whittaker,Ryan,NULL,Male,Other,10/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,Copy,1,0 +4973,66447,58181,Probation,Whittaker,Ryan,NULL,Male,Other,10/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +58083,66449,60266,PRETRIAL,Altagrace,Augustin,NULL,Female,African-American,11/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/13/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +58083,66449,60266,PRETRIAL,Altagrace,Augustin,NULL,Female,African-American,11/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/13/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +58083,66449,60266,PRETRIAL,Altagrace,Augustin,NULL,Female,African-American,11/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58080,66445,60263,PRETRIAL,Kazi,Rehan,Rajabali,Male,Asian,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/13/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +58080,66445,60263,PRETRIAL,Kazi,Rehan,Rajabali,Male,Asian,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/13/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +58080,66445,60263,PRETRIAL,Kazi,Rehan,Rajabali,Male,Asian,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58074,66437,60257,PRETRIAL,RAYONI,DOMINIC,EUGENE,Male,Caucasian,03/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +58074,66437,60257,PRETRIAL,RAYONI,DOMINIC,EUGENE,Male,Caucasian,03/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +58074,66437,60257,PRETRIAL,RAYONI,DOMINIC,EUGENE,Male,Caucasian,03/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58075,66438,60258,PRETRIAL,SINGLETARY,Myquavis,SINCLAIRE,Male,African-American,05/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +58075,66438,60258,PRETRIAL,SINGLETARY,Myquavis,SINCLAIRE,Male,African-American,05/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,4,High,8,Risk of Recidivism,0.17,8,High,New,1,0 +58075,66438,60258,PRETRIAL,SINGLETARY,Myquavis,SINCLAIRE,Male,African-American,05/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58078,66443,60261,PRETRIAL,Colosimo,Christopher,NULL,Male,Caucasian,02/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +58078,66443,60261,PRETRIAL,Colosimo,Christopher,NULL,Male,Caucasian,02/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +58078,66443,60261,PRETRIAL,Colosimo,Christopher,NULL,Male,Caucasian,02/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58077,66440,60260,PRETRIAL,STILWELL,ANTHONY,CHARLES,Male,Caucasian,01/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +58077,66440,60260,PRETRIAL,STILWELL,ANTHONY,CHARLES,Male,Caucasian,01/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +58077,66440,60260,PRETRIAL,STILWELL,ANTHONY,CHARLES,Male,Caucasian,01/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58082,66448,60265,PRETRIAL,Seraphin,Edy,NULL,Male,African-American,04/12/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/13/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +58082,66448,60265,PRETRIAL,Seraphin,Edy,NULL,Male,African-American,04/12/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/13/13 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +58082,66448,60265,PRETRIAL,Seraphin,Edy,NULL,Male,African-American,04/12/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58072,66435,60255,PRETRIAL,ARCIA,ELIOTT,NULL,Male,African-American,10/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +58072,66435,60255,PRETRIAL,ARCIA,ELIOTT,NULL,Male,African-American,10/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +58072,66435,60255,PRETRIAL,ARCIA,ELIOTT,NULL,Male,African-American,10/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58102,66474,60290,Probation,levy,richard,NULL,Male,African-American,08/16/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +58102,66474,60290,Probation,levy,richard,NULL,Male,African-American,08/16/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +58102,66474,60290,Probation,levy,richard,NULL,Male,African-American,08/16/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +6782,66482,60297,PRETRIAL,LUBIN,HOWARD,NULL,Male,Other,11/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +6782,66482,60297,PRETRIAL,LUBIN,HOWARD,NULL,Male,Other,11/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +6782,66482,60297,PRETRIAL,LUBIN,HOWARD,NULL,Male,Other,11/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58116,66495,60306,Probation,STONE,KENNETH,NULL,Male,Caucasian,07/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/13 0:00,2,Medium,7,Risk of Violence,-2.94,2,Low,New,1,0 +58116,66495,60306,Probation,STONE,KENNETH,NULL,Male,Caucasian,07/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +58116,66495,60306,Probation,STONE,KENNETH,NULL,Male,Caucasian,07/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +47287,66453,47818,PRETRIAL,Jean-Francois,Jermaine,NULL,Male,Other,10/15/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,Copy,1,0 +47287,66453,47818,PRETRIAL,Jean-Francois,Jermaine,NULL,Male,Other,10/15/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,Copy,1,0 +47287,66453,47818,PRETRIAL,Jean-Francois,Jermaine,NULL,Male,Other,10/15/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +58114,66490,60303,PRETRIAL,Palazuelos,Miguel,Angel,Male,Hispanic,03/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +58114,66490,60303,PRETRIAL,Palazuelos,Miguel,Angel,Male,Hispanic,03/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +58114,66490,60303,PRETRIAL,Palazuelos,Miguel,Angel,Male,Hispanic,03/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58093,66461,60277,PRETRIAL,Wright,Lee,NULL,Male,African-American,08/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +58093,66461,60277,PRETRIAL,Wright,Lee,NULL,Male,African-American,08/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +58093,66461,60277,PRETRIAL,Wright,Lee,NULL,Male,African-American,08/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58111,66487,60300,PRETRIAL,pardo,raekwon,NULL,Male,African-American,02/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +58111,66487,60300,PRETRIAL,pardo,raekwon,NULL,Male,African-American,02/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +58111,66487,60300,PRETRIAL,pardo,raekwon,NULL,Male,African-American,02/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58092,66459,60275,PRETRIAL,COOPER,JOHN,NULL,Female,Caucasian,09/14/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +58092,66459,60275,PRETRIAL,COOPER,JOHN,NULL,Female,Caucasian,09/14/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +58092,66459,60275,PRETRIAL,COOPER,JOHN,NULL,Female,Caucasian,09/14/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +58095,66466,60282,Probation,Myers,Shawn,NULL,Male,African-American,04/04/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +58095,66466,60282,Probation,Myers,Shawn,NULL,Male,African-American,04/04/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +58095,66466,60282,Probation,Myers,Shawn,NULL,Male,African-American,04/04/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58107,66479,60294,Probation,Simmons,Loreva,NULL,Female,African-American,01/17/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +58107,66479,60294,Probation,Simmons,Loreva,NULL,Female,African-American,01/17/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +58107,66479,60294,Probation,Simmons,Loreva,NULL,Female,African-American,01/17/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58085,66451,60268,PRETRIAL,STINSON,KEENEN,DEVAUGHN,Male,African-American,03/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +58085,66451,60268,PRETRIAL,STINSON,KEENEN,DEVAUGHN,Male,African-American,03/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +58085,66451,60268,PRETRIAL,STINSON,KEENEN,DEVAUGHN,Male,African-American,03/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58091,66458,60274,PRETRIAL,Lane,Dathmus,Dakkar,Male,African-American,01/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +58091,66458,60274,PRETRIAL,Lane,Dathmus,Dakkar,Male,African-American,01/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +58091,66458,60274,PRETRIAL,Lane,Dathmus,Dakkar,Male,African-American,01/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58089,66456,60272,PRETRIAL,ALSTON,GUYSHANA,NULL,Female,African-American,06/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +58089,66456,60272,PRETRIAL,ALSTON,GUYSHANA,NULL,Female,African-American,06/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +58089,66456,60272,PRETRIAL,ALSTON,GUYSHANA,NULL,Female,African-American,06/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +17287,66470,60286,PRETRIAL,EDDINS,TERRI,LEVETTE,Female,African-American,08/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +17287,66470,60286,PRETRIAL,EDDINS,TERRI,LEVETTE,Female,African-American,08/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +17287,66470,60286,PRETRIAL,EDDINS,TERRI,LEVETTE,Female,African-American,08/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +58104,66477,60292,PRETRIAL,Moore,Quavon,Jarrell,Male,African-American,03/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,New,1,0 +58104,66477,60292,PRETRIAL,Moore,Quavon,Jarrell,Male,African-American,03/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +58104,66477,60292,PRETRIAL,Moore,Quavon,Jarrell,Male,African-American,03/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +38239,66491,57187,PRETRIAL,Stevenson,Lance,Michael,Male,Caucasian,04/15/56,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,Copy,1,0 +38239,66491,57187,PRETRIAL,Stevenson,Lance,Michael,Male,Caucasian,04/15/56,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,Copy,1,0 +38239,66491,57187,PRETRIAL,Stevenson,Lance,Michael,Male,Caucasian,04/15/56,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,41,10,High,Copy,1,0 +58094,66463,60279,PRETRIAL,AMEDA,EUGENE,NULL,Male,African-American,01/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,4,High,7,Risk of Violence,-1.19,8,High,New,1,0 +58094,66463,60279,PRETRIAL,AMEDA,EUGENE,NULL,Male,African-American,01/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,4,High,8,Risk of Recidivism,0.7,10,High,New,1,0 +58094,66463,60279,PRETRIAL,AMEDA,EUGENE,NULL,Male,African-American,01/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58097,66468,60284,Probation,Martinez,diego,Alfonso,Male,Hispanic,10/18/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/14/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +58097,66468,60284,Probation,Martinez,diego,Alfonso,Male,Hispanic,10/18/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/14/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +58097,66468,60284,Probation,Martinez,diego,Alfonso,Male,Hispanic,10/18/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58103,66475,60291,Probation,monier,jose,NULL,Male,Hispanic,02/18/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +58103,66475,60291,Probation,monier,jose,NULL,Male,Hispanic,02/18/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +58103,66475,60291,Probation,monier,jose,NULL,Male,Hispanic,02/18/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54379,66493,60304,PRETRIAL,SOHIT,CHRISTOPHER,NULL,Male,Other,08/12/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +54379,66493,60304,PRETRIAL,SOHIT,CHRISTOPHER,NULL,Male,Other,08/12/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +54379,66493,60304,PRETRIAL,SOHIT,CHRISTOPHER,NULL,Male,Other,08/12/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +4411,66454,60270,PRETRIAL,PICOU,NAFISA,NULL,Female,African-American,04/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +4411,66454,60270,PRETRIAL,PICOU,NAFISA,NULL,Female,African-American,04/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,4,High,8,Risk of Recidivism,0.51,10,High,New,1,0 +4411,66454,60270,PRETRIAL,PICOU,NAFISA,NULL,Female,African-American,04/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,4,High,18,Risk of Failure to Appear,30,9,High,New,1,0 +52808,66472,60288,PRETRIAL,Hilaire,Gregory,NULL,Male,Other,04/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +52808,66472,60288,PRETRIAL,Hilaire,Gregory,NULL,Male,Other,04/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +52808,66472,60288,PRETRIAL,Hilaire,Gregory,NULL,Male,Other,04/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58113,66489,60302,Probation,glenn,voxakeveia,NULL,Female,African-American,09/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +58113,66489,60302,Probation,glenn,voxakeveia,NULL,Female,African-American,09/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +58113,66489,60302,Probation,glenn,voxakeveia,NULL,Female,African-American,09/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58090,66457,60273,PRETRIAL,Kittendorf,Brandon,Von,Male,Caucasian,05/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/14/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +58090,66457,60273,PRETRIAL,Kittendorf,Brandon,Von,Male,Caucasian,05/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/14/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +58090,66457,60273,PRETRIAL,Kittendorf,Brandon,Von,Male,Caucasian,05/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58106,66478,60293,Probation,Perlmutter,Rosalind,NULL,Female,Caucasian,11/16/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/13 0:00,1,Low,7,Risk of Violence,-4.5,1,Low,New,1,0 +58106,66478,60293,Probation,Perlmutter,Rosalind,NULL,Female,Caucasian,11/16/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/13 0:00,1,Low,8,Risk of Recidivism,-2.71,1,Low,New,1,0 +58106,66478,60293,Probation,Perlmutter,Rosalind,NULL,Female,Caucasian,11/16/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +12630,66465,60281,DRRD,JONES,MICHAEL,NULL,Male,African-American,03/04/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +12630,66465,60281,DRRD,JONES,MICHAEL,NULL,Male,African-American,03/04/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +12630,66465,60281,DRRD,JONES,MICHAEL,NULL,Male,African-American,03/04/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58087,66460,60276,PRETRIAL,CRESPO,ADALBERTO,NULL,Male,Caucasian,09/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +58087,66460,60276,PRETRIAL,CRESPO,ADALBERTO,NULL,Male,Caucasian,09/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +58087,66460,60276,PRETRIAL,CRESPO,ADALBERTO,NULL,Male,Caucasian,09/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58115,66494,60305,Probation,MINO,GRACIELA,NULL,Female,Hispanic,02/28/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +58115,66494,60305,Probation,MINO,GRACIELA,NULL,Female,Hispanic,02/28/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +58115,66494,60305,Probation,MINO,GRACIELA,NULL,Female,Hispanic,02/28/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +40936,66481,60296,PRETRIAL,Sinclair,Roger,NULL,Male,African-American,12/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/13 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +40936,66481,60296,PRETRIAL,Sinclair,Roger,NULL,Male,African-American,12/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +40936,66481,60296,PRETRIAL,Sinclair,Roger,NULL,Male,African-American,12/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58117,66496,60307,PRETRIAL,mosier,dallas,NULL,Male,Caucasian,03/14/94,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,10/14/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +58117,66496,60307,PRETRIAL,mosier,dallas,NULL,Male,Caucasian,03/14/94,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,10/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,4,Low,New,1,0 +58117,66496,60307,PRETRIAL,mosier,dallas,NULL,Male,Caucasian,03/14/94,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,10/14/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58101,66473,60289,Probation,Colorio,Thomas,NULL,Male,Caucasian,12/21/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/13 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +58101,66473,60289,Probation,Colorio,Thomas,NULL,Male,Caucasian,12/21/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +58101,66473,60289,Probation,Colorio,Thomas,NULL,Male,Caucasian,12/21/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +58112,66488,60301,Probation,Baloco,Fernando,NULL,Male,Hispanic,05/03/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +58112,66488,60301,Probation,Baloco,Fernando,NULL,Male,Hispanic,05/03/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +58112,66488,60301,Probation,Baloco,Fernando,NULL,Male,Hispanic,05/03/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58086,66452,60269,PRETRIAL,PEREZ,OMAR,CHAVEZ,Male,Hispanic,07/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +58086,66452,60269,PRETRIAL,PEREZ,OMAR,CHAVEZ,Male,Hispanic,07/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +58086,66452,60269,PRETRIAL,PEREZ,OMAR,CHAVEZ,Male,Hispanic,07/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58088,66455,60271,PRETRIAL,Brown,Jarvarris,NULL,Male,African-American,09/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/13 0:00,2,Medium,7,Risk of Violence,-2.74,2,Low,New,1,0 +58088,66455,60271,PRETRIAL,Brown,Jarvarris,NULL,Male,African-American,09/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +58088,66455,60271,PRETRIAL,Brown,Jarvarris,NULL,Male,African-American,09/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +27065,66462,60278,Probation,Insua,Jeffrey,NULL,Male,Hispanic,06/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +27065,66462,60278,Probation,Insua,Jeffrey,NULL,Male,Hispanic,06/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +27065,66462,60278,Probation,Insua,Jeffrey,NULL,Male,Hispanic,06/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52996,66464,60280,PRETRIAL,Zackery,Dominic,NULL,Male,African-American,09/12/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +52996,66464,60280,PRETRIAL,Zackery,Dominic,NULL,Male,African-American,09/12/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +52996,66464,60280,PRETRIAL,Zackery,Dominic,NULL,Male,African-American,09/12/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +47311,66483,57212,PRETRIAL,Davila,Ralph,Justin,Male,Caucasian,10/22/71,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +47311,66483,57212,PRETRIAL,Davila,Ralph,Justin,Male,Caucasian,10/22/71,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-1.32,1,Low,New,1,0 +47311,66483,57212,PRETRIAL,Davila,Ralph,Justin,Male,Caucasian,10/22/71,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +58108,66480,60295,PRETRIAL,Maloney,Shayne,NULL,Male,Caucasian,08/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +58108,66480,60295,PRETRIAL,Maloney,Shayne,NULL,Male,Caucasian,08/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +58108,66480,60295,PRETRIAL,Maloney,Shayne,NULL,Male,Caucasian,08/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58096,66467,60283,PRETRIAL,ulpiano,gabriela,NULL,Female,Caucasian,06/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +58096,66467,60283,PRETRIAL,ulpiano,gabriela,NULL,Female,Caucasian,06/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +58096,66467,60283,PRETRIAL,ulpiano,gabriela,NULL,Female,Caucasian,06/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +46058,66476,46412,PRETRIAL,Cruz,Enrique,NULL,Male,Hispanic,02/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/14/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,Copy,1,0 +46058,66476,46412,PRETRIAL,Cruz,Enrique,NULL,Male,Hispanic,02/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/14/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,Copy,1,0 +46058,66476,46412,PRETRIAL,Cruz,Enrique,NULL,Male,Hispanic,02/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +58084,66450,60267,PRETRIAL,BROWN,NATASHA,NULL,Female,African-American,05/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +58084,66450,60267,PRETRIAL,BROWN,NATASHA,NULL,Female,African-American,05/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +58084,66450,60267,PRETRIAL,BROWN,NATASHA,NULL,Female,African-American,05/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58099,66471,60287,Probation,mitchison,blake,NULL,Male,Caucasian,06/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +58099,66471,60287,Probation,mitchison,blake,NULL,Male,Caucasian,06/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +58099,66471,60287,Probation,mitchison,blake,NULL,Male,Caucasian,06/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58136,66522,60329,Probation,Durante,Jean,NULL,Male,Caucasian,03/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/15/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +58136,66522,60329,Probation,Durante,Jean,NULL,Male,Caucasian,03/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/15/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +58136,66522,60329,Probation,Durante,Jean,NULL,Male,Caucasian,03/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +46277,66539,60346,Probation,henaghanan,william,NULL,Male,Caucasian,06/15/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +46277,66539,60346,Probation,henaghanan,william,NULL,Male,Caucasian,06/15/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +46277,66539,60346,Probation,henaghanan,william,NULL,Male,Caucasian,06/15/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +58133,66518,60326,PRETRIAL,Gutierrez,Jonathan,NULL,Male,Hispanic,04/04/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +58133,66518,60326,PRETRIAL,Gutierrez,Jonathan,NULL,Male,Hispanic,04/04/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,4,High,8,Risk of Recidivism,0.55,9,High,New,1,0 +58133,66518,60326,PRETRIAL,Gutierrez,Jonathan,NULL,Male,Hispanic,04/04/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,4,High,18,Risk of Failure to Appear,18,2,Low,New,1,0 +47893,66501,48514,PRETRIAL,Taulbert,Moses,NULL,Male,African-American,06/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.31,3,Low,Copy,1,0 +47893,66501,48514,PRETRIAL,Taulbert,Moses,NULL,Male,African-American,06/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,Copy,1,0 +47893,66501,48514,PRETRIAL,Taulbert,Moses,NULL,Male,African-American,06/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +58118,66497,60308,PRETRIAL,Barr,Jordan,NULL,Male,African-American,07/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +58118,66497,60308,PRETRIAL,Barr,Jordan,NULL,Male,African-American,07/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +58118,66497,60308,PRETRIAL,Barr,Jordan,NULL,Male,African-American,07/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58130,66513,60322,PRETRIAL,bellidodeluna,alvaro,NULL,Male,Hispanic,05/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +58130,66513,60322,PRETRIAL,bellidodeluna,alvaro,NULL,Male,Hispanic,05/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +58130,66513,60322,PRETRIAL,bellidodeluna,alvaro,NULL,Male,Hispanic,05/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58124,66506,60315,PRETRIAL,Noronha,Emily,NULL,Female,Other,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +58124,66506,60315,PRETRIAL,Noronha,Emily,NULL,Female,Other,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +58124,66506,60315,PRETRIAL,Noronha,Emily,NULL,Female,Other,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58135,66520,60328,Probation,Kilar,Seyfettin,NULL,Male,Caucasian,10/06/76,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/15/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +58135,66520,60328,Probation,Kilar,Seyfettin,NULL,Male,Caucasian,10/06/76,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/15/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +58135,66520,60328,Probation,Kilar,Seyfettin,NULL,Male,Caucasian,10/06/76,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53480,66534,60341,Probation,LopesP,Carlos,NULL,Male,Hispanic,03/21/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +53480,66534,60341,Probation,LopesP,Carlos,NULL,Male,Hispanic,03/21/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +53480,66534,60341,Probation,LopesP,Carlos,NULL,Male,Hispanic,03/21/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +48516,66541,49211,PRETRIAL,wiggins,blaine,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,Copy,1,0 +48516,66541,49211,PRETRIAL,wiggins,blaine,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,8,Risk of Recidivism,0.15,7,Medium,Copy,1,0 +48516,66541,49211,PRETRIAL,wiggins,blaine,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,18,Risk of Failure to Appear,21,3,Low,Copy,1,0 +58122,66502,60312,PRETRIAL,Jeanbaptiste,Emmanuel,NULL,Male,Other,10/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +58122,66502,60312,PRETRIAL,Jeanbaptiste,Emmanuel,NULL,Male,Other,10/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +58122,66502,60312,PRETRIAL,Jeanbaptiste,Emmanuel,NULL,Male,Other,10/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58127,66509,60318,PRETRIAL,Martinez,Andrew,NULL,Male,Caucasian,05/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +58127,66509,60318,PRETRIAL,Martinez,Andrew,NULL,Male,Caucasian,05/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +58127,66509,60318,PRETRIAL,Martinez,Andrew,NULL,Male,Caucasian,05/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58137,66523,60330,Probation,Johnson,Will,NULL,Male,African-American,08/30/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/15/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +58137,66523,60330,Probation,Johnson,Will,NULL,Male,African-American,08/30/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/15/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +58137,66523,60330,Probation,Johnson,Will,NULL,Male,African-American,08/30/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58148,66538,60345,PRETRIAL,Sisson,Stephen,NULL,Male,Caucasian,06/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +58148,66538,60345,PRETRIAL,Sisson,Stephen,NULL,Male,Caucasian,06/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +58148,66538,60345,PRETRIAL,Sisson,Stephen,NULL,Male,Caucasian,06/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +46012,66515,60323,PRETRIAL,Chacon,Theodore,NULL,Male,Caucasian,11/20/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/15/13 0:00,2,Medium,7,Risk of Violence,-2.82,2,Low,New,1,0 +46012,66515,60323,PRETRIAL,Chacon,Theodore,NULL,Male,Caucasian,11/20/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +46012,66515,60323,PRETRIAL,Chacon,Theodore,NULL,Male,Caucasian,11/20/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/15/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58142,66530,60337,PRETRIAL,Jones,Lonnie,NULL,Male,African-American,06/21/45,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,10/15/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +58142,66530,60337,PRETRIAL,Jones,Lonnie,NULL,Male,African-American,06/21/45,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,10/15/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +58142,66530,60337,PRETRIAL,Jones,Lonnie,NULL,Male,African-American,06/21/45,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58132,66517,60325,PRETRIAL,Martinez-Salas,Fernando,NULL,Male,Hispanic,05/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/15/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +58132,66517,60325,PRETRIAL,Martinez-Salas,Fernando,NULL,Male,Hispanic,05/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/15/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +58132,66517,60325,PRETRIAL,Martinez-Salas,Fernando,NULL,Male,Hispanic,05/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58129,66512,60321,PRETRIAL,Thomson,Jessica,Lee,Female,Caucasian,12/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/15/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +58129,66512,60321,PRETRIAL,Thomson,Jessica,Lee,Female,Caucasian,12/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/15/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +58129,66512,60321,PRETRIAL,Thomson,Jessica,Lee,Female,Caucasian,12/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58120,66499,60310,PRETRIAL,Rosario,Carlos,NULL,Male,Caucasian,04/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +58120,66499,60310,PRETRIAL,Rosario,Carlos,NULL,Male,Caucasian,04/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +58120,66499,60310,PRETRIAL,Rosario,Carlos,NULL,Male,Caucasian,04/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +7303,66533,60340,PRETRIAL,PINDER,SHANKERA,NULL,Male,African-American,07/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +7303,66533,60340,PRETRIAL,PINDER,SHANKERA,NULL,Male,African-American,07/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +7303,66533,60340,PRETRIAL,PINDER,SHANKERA,NULL,Male,African-American,07/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +35029,66504,60314,PRETRIAL,Butler,Earl,NULL,Male,African-American,12/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +35029,66504,60314,PRETRIAL,Butler,Earl,NULL,Male,African-American,12/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +35029,66504,60314,PRETRIAL,Butler,Earl,NULL,Male,African-American,12/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58126,66507,60316,PRETRIAL,Flores,Travoy,I,Male,African-American,07/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +58126,66507,60316,PRETRIAL,Flores,Travoy,I,Male,African-American,07/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +58126,66507,60316,PRETRIAL,Flores,Travoy,I,Male,African-American,07/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58139,66525,60332,Probation,JACKSON,TESHEYRA,NULL,Male,African-American,08/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +58139,66525,60332,Probation,JACKSON,TESHEYRA,NULL,Male,African-American,08/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +58139,66525,60332,Probation,JACKSON,TESHEYRA,NULL,Male,African-American,08/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58149,66540,60347,PRETRIAL,Baylor,Keith,NULL,Male,Caucasian,10/19/71,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +58149,66540,60347,PRETRIAL,Baylor,Keith,NULL,Male,Caucasian,10/19/71,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,6,Medium,New,1,0 +58149,66540,60347,PRETRIAL,Baylor,Keith,NULL,Male,Caucasian,10/19/71,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,2,Medium,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +8339,66514,7891,Probation,wood,morgan,NULL,Male,Caucasian,12/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,Copy,1,0 +8339,66514,7891,Probation,wood,morgan,NULL,Male,Caucasian,12/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,Copy,1,0 +8339,66514,7891,Probation,wood,morgan,NULL,Male,Caucasian,12/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +52133,66531,60338,PRETRIAL,DAVID,LAKEINYAS,S,Female,African-American,01/17/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +52133,66531,60338,PRETRIAL,DAVID,LAKEINYAS,S,Female,African-American,01/17/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +52133,66531,60338,PRETRIAL,DAVID,LAKEINYAS,S,Female,African-American,01/17/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +21533,66510,60319,PRETRIAL,Kerone,Oneil,NULL,Male,African-American,02/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +21533,66510,60319,PRETRIAL,Kerone,Oneil,NULL,Male,African-American,02/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,4,High,8,Risk of Recidivism,1.04,10,High,New,1,0 +21533,66510,60319,PRETRIAL,Kerone,Oneil,NULL,Male,African-American,02/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58145,66535,60342,Probation,KATZMAN,BRADLEY,ADAM,Male,Caucasian,07/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.07,8,High,New,1,0 +58145,66535,60342,Probation,KATZMAN,BRADLEY,ADAM,Male,Caucasian,07/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +58145,66535,60342,Probation,KATZMAN,BRADLEY,ADAM,Male,Caucasian,07/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +16814,66505,54746,PRETRIAL,Torres,Rafael,Ernesto,Male,Caucasian,02/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,Copy,1,0 +16814,66505,54746,PRETRIAL,Torres,Rafael,Ernesto,Male,Caucasian,02/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,Copy,1,0 +16814,66505,54746,PRETRIAL,Torres,Rafael,Ernesto,Male,Caucasian,02/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +58134,66519,60327,Probation,wilder,sean,NULL,Male,Caucasian,05/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +58134,66519,60327,Probation,wilder,sean,NULL,Male,Caucasian,05/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +58134,66519,60327,Probation,wilder,sean,NULL,Male,Caucasian,05/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58140,66526,60333,PRETRIAL,Massucco,Joseph,NULL,Male,Caucasian,04/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +58140,66526,60333,PRETRIAL,Massucco,Joseph,NULL,Male,Caucasian,04/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +58140,66526,60333,PRETRIAL,Massucco,Joseph,NULL,Male,Caucasian,04/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58141,66528,60335,Probation,Thornton,Robert,NULL,Male,African-American,04/28/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +58141,66528,60335,Probation,Thornton,Robert,NULL,Male,African-American,04/28/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.95,10,High,New,1,0 +58141,66528,60335,Probation,Thornton,Robert,NULL,Male,African-American,04/28/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +58119,66498,60309,PRETRIAL,Belhomme,Patrick,NULL,Male,African-American,03/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +58119,66498,60309,PRETRIAL,Belhomme,Patrick,NULL,Male,African-American,03/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +58119,66498,60309,PRETRIAL,Belhomme,Patrick,NULL,Male,African-American,03/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58138,66524,60331,Probation,Rahim,Reza,NULL,Male,Caucasian,03/31/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/15/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +58138,66524,60331,Probation,Rahim,Reza,NULL,Male,Caucasian,03/31/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/15/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +58138,66524,60331,Probation,Rahim,Reza,NULL,Male,Caucasian,03/31/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58144,66532,60339,Probation,Sutton,Michael,NULL,Male,Caucasian,05/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +58144,66532,60339,Probation,Sutton,Michael,NULL,Male,Caucasian,05/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +58144,66532,60339,Probation,Sutton,Michael,NULL,Male,Caucasian,05/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58131,66516,60324,Probation,Balboa,Joseph,NULL,Male,Hispanic,04/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +58131,66516,60324,Probation,Balboa,Joseph,NULL,Male,Hispanic,04/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +58131,66516,60324,Probation,Balboa,Joseph,NULL,Male,Hispanic,04/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58147,66537,60344,Probation,Lockwood,Reginald,Anton,Male,African-American,11/23/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/15/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +58147,66537,60344,Probation,Lockwood,Reginald,Anton,Male,African-American,11/23/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/15/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +58147,66537,60344,Probation,Lockwood,Reginald,Anton,Male,African-American,11/23/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58121,66500,60311,PRETRIAL,Bellamy,Bernard,NULL,Male,African-American,11/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +58121,66500,60311,PRETRIAL,Bellamy,Bernard,NULL,Male,African-American,11/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +58121,66500,60311,PRETRIAL,Bellamy,Bernard,NULL,Male,African-American,11/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58128,66511,60320,PRETRIAL,LATERIA,GREEN,NULL,Female,African-American,12/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +58128,66511,60320,PRETRIAL,LATERIA,GREEN,NULL,Female,African-American,12/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,4,High,8,Risk of Recidivism,0.25,9,High,New,1,0 +58128,66511,60320,PRETRIAL,LATERIA,GREEN,NULL,Female,African-American,12/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58143,66529,60336,Probation,kaplan,louis,joel,Male,Caucasian,06/10/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/15/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +58143,66529,60336,Probation,kaplan,louis,joel,Male,Caucasian,06/10/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/15/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +58143,66529,60336,Probation,kaplan,louis,joel,Male,Caucasian,06/10/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58123,66503,60313,PRETRIAL,BERLANGA,MITCHELL,NULL,Male,Caucasian,12/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +58123,66503,60313,PRETRIAL,BERLANGA,MITCHELL,NULL,Male,Caucasian,12/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +58123,66503,60313,PRETRIAL,BERLANGA,MITCHELL,NULL,Male,Caucasian,12/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58125,66508,60317,PRETRIAL,MILLER,MITCHELL,GENE,Male,African-American,08/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +58125,66508,60317,PRETRIAL,MILLER,MITCHELL,GENE,Male,African-American,08/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +58125,66508,60317,PRETRIAL,MILLER,MITCHELL,GENE,Male,African-American,08/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58150,66542,60348,PRETRIAL,Turner,Marlon,NULL,Male,African-American,10/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +58150,66542,60348,PRETRIAL,Turner,Marlon,NULL,Male,African-American,10/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +58150,66542,60348,PRETRIAL,Turner,Marlon,NULL,Male,African-American,10/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58156,66550,60356,PRETRIAL,PINKSTON,MICHAEL,NULL,Male,African-American,11/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.65,2,Low,New,1,0 +58156,66550,60356,PRETRIAL,PINKSTON,MICHAEL,NULL,Male,African-American,11/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +58156,66550,60356,PRETRIAL,PINKSTON,MICHAEL,NULL,Male,African-American,11/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58171,66568,60372,Probation,brown,kristen,NULL,Female,Caucasian,10/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.6,2,Low,New,1,0 +58171,66568,60372,Probation,brown,kristen,NULL,Female,Caucasian,10/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +58171,66568,60372,Probation,brown,kristen,NULL,Female,Caucasian,10/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58173,66571,60375,Probation,dearmas,Javier,NULL,Male,Caucasian,10/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +58173,66571,60375,Probation,dearmas,Javier,NULL,Male,Caucasian,10/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +58173,66571,60375,Probation,dearmas,Javier,NULL,Male,Caucasian,10/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55722,66573,57607,Probation,Cesar,Johnny,NULL,Male,African-American,10/30/87,17,All Scales,Intake,English,Conditional Release,Probation,Significant Other,10/16/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +55722,66573,57607,Probation,Cesar,Johnny,NULL,Male,African-American,10/30/87,17,All Scales,Intake,English,Conditional Release,Probation,Significant Other,10/16/13 0:00,1,Low,8,Risk of Recidivism,-0.74,3,Low,New,1,0 +55722,66573,57607,Probation,Cesar,Johnny,NULL,Male,African-American,10/30/87,17,All Scales,Intake,English,Conditional Release,Probation,Significant Other,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +47214,66574,60377,PRETRIAL,FERNANDEZ,DAMIAN,ALEXANDER,Male,Caucasian,11/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +47214,66574,60377,PRETRIAL,FERNANDEZ,DAMIAN,ALEXANDER,Male,Caucasian,11/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +47214,66574,60377,PRETRIAL,FERNANDEZ,DAMIAN,ALEXANDER,Male,Caucasian,11/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58169,66566,60370,PRETRIAL,BROOKS,TRAVIS,NULL,Male,African-American,11/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/16/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +58169,66566,60370,PRETRIAL,BROOKS,TRAVIS,NULL,Male,African-American,11/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/16/13 0:00,4,High,8,Risk of Recidivism,0.31,9,High,New,1,0 +58169,66566,60370,PRETRIAL,BROOKS,TRAVIS,NULL,Male,African-American,11/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/16/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58153,66545,60351,PRETRIAL,Baptiste,Omar,NULL,Male,Other,06/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +58153,66545,60351,PRETRIAL,Baptiste,Omar,NULL,Male,Other,06/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +58153,66545,60351,PRETRIAL,Baptiste,Omar,NULL,Male,Other,06/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58158,66553,60359,Probation,bowe,preston,NULL,Male,African-American,06/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +58158,66553,60359,Probation,bowe,preston,NULL,Male,African-American,06/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +58158,66553,60359,Probation,bowe,preston,NULL,Male,African-American,06/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57618,66558,59744,PRETRIAL,moreland,Jamaree,NULL,Male,African-American,08/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,Copy,1,0 +57618,66558,59744,PRETRIAL,moreland,Jamaree,NULL,Male,African-American,08/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.38,5,Medium,Copy,1,0 +57618,66558,59744,PRETRIAL,moreland,Jamaree,NULL,Male,African-American,08/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +58163,66560,60364,Probation,FERNANDEZPEREZ,FRANCISCO,JAVIER,Male,Hispanic,12/12/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +58163,66560,60364,Probation,FERNANDEZPEREZ,FRANCISCO,JAVIER,Male,Hispanic,12/12/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +58163,66560,60364,Probation,FERNANDEZPEREZ,FRANCISCO,JAVIER,Male,Hispanic,12/12/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58155,66547,60353,PRETRIAL,GARCIA,SERGIO,NULL,Male,Caucasian,02/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/16/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +58155,66547,60353,PRETRIAL,GARCIA,SERGIO,NULL,Male,Caucasian,02/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/16/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +58155,66547,60353,PRETRIAL,GARCIA,SERGIO,NULL,Male,Caucasian,02/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +26934,66549,60355,PRETRIAL,sanchez,stacey,lynne,Female,Native American,09/17/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,4,High,7,Risk of Violence,-0.95,9,High,New,1,0 +26934,66549,60355,PRETRIAL,sanchez,stacey,lynne,Female,Native American,09/17/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,4,High,8,Risk of Recidivism,0.76,10,High,New,1,0 +26934,66549,60355,PRETRIAL,sanchez,stacey,lynne,Female,Native American,09/17/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +58159,66556,60361,DRRD,Burch,Jonathan,None,Male,African-American,03/22/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +58159,66556,60361,DRRD,Burch,Jonathan,None,Male,African-American,03/22/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +58159,66556,60361,DRRD,Burch,Jonathan,None,Male,African-American,03/22/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,2,Medium,18,Risk of Failure to Appear,18,2,Low,New,1,0 +58172,66570,60374,Probation,SHEETS,ROBERT,C,Male,Caucasian,08/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +58172,66570,60374,Probation,SHEETS,ROBERT,C,Male,Caucasian,08/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +58172,66570,60374,Probation,SHEETS,ROBERT,C,Male,Caucasian,08/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58152,66544,60350,PRETRIAL,GUACANEME,JUAN,NULL,Male,Caucasian,10/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +58152,66544,60350,PRETRIAL,GUACANEME,JUAN,NULL,Male,Caucasian,10/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +58152,66544,60350,PRETRIAL,GUACANEME,JUAN,NULL,Male,Caucasian,10/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58168,66565,60369,Probation,MOREAU,ELSIE,C,Female,African-American,02/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +58168,66565,60369,Probation,MOREAU,ELSIE,C,Female,African-American,02/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +58168,66565,60369,Probation,MOREAU,ELSIE,C,Female,African-American,02/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +58162,66561,60365,PRETRIAL,Mahoney,Elizabeth,NULL,Female,Caucasian,05/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/13 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +58162,66561,60365,PRETRIAL,Mahoney,Elizabeth,NULL,Female,Caucasian,05/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +58162,66561,60365,PRETRIAL,Mahoney,Elizabeth,NULL,Female,Caucasian,05/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58176,66575,60378,PRETRIAL,Bryant,Lattee,NULL,Male,African-American,09/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/16/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +58176,66575,60378,PRETRIAL,Bryant,Lattee,NULL,Male,African-American,09/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/16/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +58176,66575,60378,PRETRIAL,Bryant,Lattee,NULL,Male,African-American,09/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57576,66554,59693,PRETRIAL,JOHNSON,GREGORY,NULL,Male,African-American,11/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,Copy,1,0 +57576,66554,59693,PRETRIAL,JOHNSON,GREGORY,NULL,Male,African-American,11/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,Copy,1,0 +57576,66554,59693,PRETRIAL,JOHNSON,GREGORY,NULL,Male,African-American,11/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +58175,66572,60376,DRRD,Shirey,Shaun,Hunter,Male,Caucasian,04/12/88,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +58175,66572,60376,DRRD,Shirey,Shaun,Hunter,Male,Caucasian,04/12/88,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,8,High,New,1,0 +58175,66572,60376,DRRD,Shirey,Shaun,Hunter,Male,Caucasian,04/12/88,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,9,High,New,1,0 +58154,66546,60352,PRETRIAL,Myers,Carla,M,Female,Caucasian,12/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/16/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +58154,66546,60352,PRETRIAL,Myers,Carla,M,Female,Caucasian,12/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/16/13 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +58154,66546,60352,PRETRIAL,Myers,Carla,M,Female,Caucasian,12/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58157,66551,60357,Probation,Demichelle,Hugo,NULL,Male,Hispanic,06/27/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +58157,66551,60357,Probation,Demichelle,Hugo,NULL,Male,Hispanic,06/27/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,8,Risk of Recidivism,-2.62,1,Low,New,1,0 +58157,66551,60357,Probation,Demichelle,Hugo,NULL,Male,Hispanic,06/27/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58161,66559,60363,PRETRIAL,Mohns,Bryant,NULL,Male,Caucasian,06/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +58161,66559,60363,PRETRIAL,Mohns,Bryant,NULL,Male,Caucasian,06/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +58161,66559,60363,PRETRIAL,Mohns,Bryant,NULL,Male,Caucasian,06/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50767,66555,60360,PRETRIAL,ROSEN,JUSTIN,RORY,Male,Caucasian,06/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +50767,66555,60360,PRETRIAL,ROSEN,JUSTIN,RORY,Male,Caucasian,06/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +50767,66555,60360,PRETRIAL,ROSEN,JUSTIN,RORY,Male,Caucasian,06/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58164,66562,60366,Probation,Pollard,Derik,NULL,Male,Caucasian,06/13/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +58164,66562,60366,Probation,Pollard,Derik,NULL,Male,Caucasian,06/13/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +58164,66562,60366,Probation,Pollard,Derik,NULL,Male,Caucasian,06/13/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58166,66564,60368,PRETRIAL,Ledbetter,Mary,NULL,Female,Caucasian,03/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/16/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +58166,66564,60368,PRETRIAL,Ledbetter,Mary,NULL,Female,Caucasian,03/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/16/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +58166,66564,60368,PRETRIAL,Ledbetter,Mary,NULL,Female,Caucasian,03/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56546,66548,60354,PRETRIAL,GAINES,DENA,NULL,Female,Caucasian,07/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +56546,66548,60354,PRETRIAL,GAINES,DENA,NULL,Female,Caucasian,07/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +56546,66548,60354,PRETRIAL,GAINES,DENA,NULL,Female,Caucasian,07/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +43581,66569,60373,PRETRIAL,Lubin,Thursby,NULL,Male,African-American,08/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +43581,66569,60373,PRETRIAL,Lubin,Thursby,NULL,Male,African-American,08/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +43581,66569,60373,PRETRIAL,Lubin,Thursby,NULL,Male,African-American,08/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58151,66543,60349,PRETRIAL,MARCUS,DORIO,NULL,Male,Caucasian,05/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +58151,66543,60349,PRETRIAL,MARCUS,DORIO,NULL,Male,Caucasian,05/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +58151,66543,60349,PRETRIAL,MARCUS,DORIO,NULL,Male,Caucasian,05/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58160,66557,60362,Probation,Mckenzie,William,NULL,Male,African-American,05/04/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +58160,66557,60362,Probation,Mckenzie,William,NULL,Male,African-American,05/04/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +58160,66557,60362,Probation,Mckenzie,William,NULL,Male,African-American,05/04/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58186,66590,60390,Probation,Osceola,Melody,Jean,Female,Caucasian,05/08/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/17/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +58186,66590,60390,Probation,Osceola,Melody,Jean,Female,Caucasian,05/08/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/17/13 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,New,1,0 +58186,66590,60390,Probation,Osceola,Melody,Jean,Female,Caucasian,05/08/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58194,66604,60402,Probation,Chick,Christene,NULL,Female,Caucasian,09/13/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +58194,66604,60402,Probation,Chick,Christene,NULL,Female,Caucasian,09/13/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +58194,66604,60402,Probation,Chick,Christene,NULL,Female,Caucasian,09/13/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58200,66611,60409,Probation,Osa,Thomas,NULL,Male,Caucasian,04/22/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +58200,66611,60409,Probation,Osa,Thomas,NULL,Male,Caucasian,04/22/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +58200,66611,60409,Probation,Osa,Thomas,NULL,Male,Caucasian,04/22/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58177,66578,60380,PRETRIAL,Frazier,Clyde,A,Male,African-American,07/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,4,High,7,Risk of Violence,-1.17,8,High,New,1,0 +58177,66578,60380,PRETRIAL,Frazier,Clyde,A,Male,African-American,07/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,4,High,8,Risk of Recidivism,0.86,10,High,New,1,0 +58177,66578,60380,PRETRIAL,Frazier,Clyde,A,Male,African-American,07/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58195,66608,60406,Probation,Moss,Todd,NULL,Male,African-American,04/06/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.76,2,Low,New,1,0 +58195,66608,60406,Probation,Moss,Todd,NULL,Male,African-American,04/06/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +58195,66608,60406,Probation,Moss,Todd,NULL,Male,African-American,04/06/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +4619,66613,60411,PRETRIAL,BURLEY,CHAYLA,LANEICE,Female,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +4619,66613,60411,PRETRIAL,BURLEY,CHAYLA,LANEICE,Female,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +4619,66613,60411,PRETRIAL,BURLEY,CHAYLA,LANEICE,Female,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58182,66583,60385,PRETRIAL,Hanna,Jamal,NULL,Male,African-American,01/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/17/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +58182,66583,60385,PRETRIAL,Hanna,Jamal,NULL,Male,African-American,01/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/17/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +58182,66583,60385,PRETRIAL,Hanna,Jamal,NULL,Male,African-American,01/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +5745,66585,5372,PRETRIAL,Charles,Marce,NULL,Male,African-American,03/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,Copy,1,0 +5745,66585,5372,PRETRIAL,Charles,Marce,NULL,Male,African-American,03/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,Copy,1,0 +5745,66585,5372,PRETRIAL,Charles,Marce,NULL,Male,African-American,03/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +54427,66592,56076,PRETRIAL,Smith,Erica,NULL,Female,African-American,10/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/13 0:00,4,High,7,Risk of Violence,-0.69,9,High,Copy,1,0 +54427,66592,56076,PRETRIAL,Smith,Erica,NULL,Female,African-American,10/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/13 0:00,4,High,8,Risk of Recidivism,0.94,10,High,Copy,1,0 +54427,66592,56076,PRETRIAL,Smith,Erica,NULL,Female,African-American,10/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +46610,66606,60404,Probation,perez,luis,NULL,Male,Other,03/03/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/17/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +46610,66606,60404,Probation,perez,luis,NULL,Male,Other,03/03/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/17/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +46610,66606,60404,Probation,perez,luis,NULL,Male,Other,03/03/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +41191,66609,60407,PRETRIAL,EDDY,VANESSA,DYANE,Female,African-American,04/26/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +41191,66609,60407,PRETRIAL,EDDY,VANESSA,DYANE,Female,African-American,04/26/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +41191,66609,60407,PRETRIAL,EDDY,VANESSA,DYANE,Female,African-American,04/26/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58203,66616,60414,Probation,ADDERLEY,VONTISKA,NULL,Female,African-American,05/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,2,Medium,7,Risk of Violence,-2.47,3,Low,New,1,0 +58203,66616,60414,Probation,ADDERLEY,VONTISKA,NULL,Female,African-American,05/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +58203,66616,60414,Probation,ADDERLEY,VONTISKA,NULL,Female,African-American,05/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58185,66588,60389,PRETRIAL,Mitchell,Barbara,NULL,Female,Caucasian,08/02/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/17/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +58185,66588,60389,PRETRIAL,Mitchell,Barbara,NULL,Female,Caucasian,08/02/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/17/13 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +58185,66588,60389,PRETRIAL,Mitchell,Barbara,NULL,Female,Caucasian,08/02/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58179,66580,60382,PRETRIAL,Wonser,Jonathon,NULL,Male,Caucasian,09/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +58179,66580,60382,PRETRIAL,Wonser,Jonathon,NULL,Male,Caucasian,09/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +58179,66580,60382,PRETRIAL,Wonser,Jonathon,NULL,Male,Caucasian,09/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58202,66614,60412,Probation,Riche,Marc,NULL,Male,African-American,08/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +58202,66614,60412,Probation,Riche,Marc,NULL,Male,African-American,08/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +58202,66614,60412,Probation,Riche,Marc,NULL,Male,African-American,08/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58193,66601,60399,PRETRIAL,CATO,ZACHARY,NULL,Male,Caucasian,10/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +58193,66601,60399,PRETRIAL,CATO,ZACHARY,NULL,Male,Caucasian,10/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +58193,66601,60399,PRETRIAL,CATO,ZACHARY,NULL,Male,Caucasian,10/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54427,66593,56076,PRETRIAL,Smith,Erica,NULL,Female,African-American,10/04/80,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,Copy,1,0 +54427,66593,56076,PRETRIAL,Smith,Erica,NULL,Female,African-American,10/04/80,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/13 0:00,4,High,8,Risk of Recidivism,1.26,10,High,Copy,1,0 +54427,66593,56076,PRETRIAL,Smith,Erica,NULL,Female,African-American,10/04/80,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/13 0:00,4,High,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +58183,66586,60387,PRETRIAL,lee,jonathan,NULL,Male,African-American,10/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.02,8,High,New,1,0 +58183,66586,60387,PRETRIAL,lee,jonathan,NULL,Male,African-American,10/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +58183,66586,60387,PRETRIAL,lee,jonathan,NULL,Male,African-American,10/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58196,66607,60405,Probation,sacramone,mario,NULL,Male,Caucasian,04/08/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/17/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +58196,66607,60405,Probation,sacramone,mario,NULL,Male,Caucasian,04/08/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/17/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +58196,66607,60405,Probation,sacramone,mario,NULL,Male,Caucasian,04/08/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58181,66582,60384,PRETRIAL,Walker,Jerry,NULL,Male,Caucasian,04/06/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +58181,66582,60384,PRETRIAL,Walker,Jerry,NULL,Male,Caucasian,04/06/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +58181,66582,60384,PRETRIAL,Walker,Jerry,NULL,Male,Caucasian,04/06/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58201,66612,60410,Probation,mann,benjamin,NULL,Male,Caucasian,08/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +58201,66612,60410,Probation,mann,benjamin,NULL,Male,Caucasian,08/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +58201,66612,60410,Probation,mann,benjamin,NULL,Male,Caucasian,08/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +47666,66603,60401,PRETRIAL,Walker,Veronica,NULL,Female,African-American,01/29/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/17/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +47666,66603,60401,PRETRIAL,Walker,Veronica,NULL,Female,African-American,01/29/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/17/13 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +47666,66603,60401,PRETRIAL,Walker,Veronica,NULL,Female,African-American,01/29/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47734,66605,60403,PRETRIAL,StHilaire,Berry,NULL,Male,African-American,04/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +47734,66605,60403,PRETRIAL,StHilaire,Berry,NULL,Male,African-American,04/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +47734,66605,60403,PRETRIAL,StHilaire,Berry,NULL,Male,African-American,04/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +50493,66577,60379,PRETRIAL,Edwards,Devorn,NULL,Male,African-American,06/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +50493,66577,60379,PRETRIAL,Edwards,Devorn,NULL,Male,African-American,06/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,4,High,8,Risk of Recidivism,0.39,9,High,New,1,0 +50493,66577,60379,PRETRIAL,Edwards,Devorn,NULL,Male,African-American,06/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +35934,66584,60386,PRETRIAL,Bynes,Sherman,NULL,Male,African-American,10/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +35934,66584,60386,PRETRIAL,Bynes,Sherman,NULL,Male,African-American,10/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +35934,66584,60386,PRETRIAL,Bynes,Sherman,NULL,Male,African-American,10/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +58187,66591,60391,Probation,Bardales,Prescott,NULL,Male,African-American,04/16/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +58187,66591,60391,Probation,Bardales,Prescott,NULL,Male,African-American,04/16/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +58187,66591,60391,Probation,Bardales,Prescott,NULL,Male,African-American,04/16/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58191,66598,60396,Probation,Labarca,Angeline,NULL,Female,Hispanic,10/07/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/17/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +58191,66598,60396,Probation,Labarca,Angeline,NULL,Female,Hispanic,10/07/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/17/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +58191,66598,60396,Probation,Labarca,Angeline,NULL,Female,Hispanic,10/07/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58178,66579,60381,PRETRIAL,Seay,Keandra,NULL,Female,African-American,04/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +58178,66579,60381,PRETRIAL,Seay,Keandra,NULL,Female,African-American,04/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +58178,66579,60381,PRETRIAL,Seay,Keandra,NULL,Female,African-American,04/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58180,66581,60383,PRETRIAL,Adams,James,NULL,Male,African-American,10/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +58180,66581,60383,PRETRIAL,Adams,James,NULL,Male,African-American,10/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +58180,66581,60383,PRETRIAL,Adams,James,NULL,Male,African-American,10/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +58189,66595,60393,Probation,Jackson,Casey,NULL,Male,African-American,12/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/17/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +58189,66595,60393,Probation,Jackson,Casey,NULL,Male,African-American,12/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/17/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +58189,66595,60393,Probation,Jackson,Casey,NULL,Male,African-American,12/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +30995,66602,60400,PRETRIAL,Gathers,Izetta,NULL,Female,African-American,02/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +30995,66602,60400,PRETRIAL,Gathers,Izetta,NULL,Female,African-American,02/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,7,Medium,New,1,0 +30995,66602,60400,PRETRIAL,Gathers,Izetta,NULL,Female,African-American,02/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +58184,66587,60388,Probation,Davidoff,Eric,NULL,Male,Caucasian,09/11/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +58184,66587,60388,Probation,Davidoff,Eric,NULL,Male,Caucasian,09/11/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +58184,66587,60388,Probation,Davidoff,Eric,NULL,Male,Caucasian,09/11/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +53488,66576,54994,PRETRIAL,COLLINS,ASHLEY,NICOLE,Female,African-American,10/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +53488,66576,54994,PRETRIAL,COLLINS,ASHLEY,NICOLE,Female,African-American,10/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,Copy,1,0 +53488,66576,54994,PRETRIAL,COLLINS,ASHLEY,NICOLE,Female,African-American,10/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +58190,66597,60395,Probation,EUTSEY,KEVIN,M,Male,African-American,05/19/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/17/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +58190,66597,60395,Probation,EUTSEY,KEVIN,M,Male,African-American,05/19/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/17/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +58190,66597,60395,Probation,EUTSEY,KEVIN,M,Male,African-American,05/19/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58214,66631,60428,PRETRIAL,Brown,Lorenzo,NULL,Male,African-American,01/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/18/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +58214,66631,60428,PRETRIAL,Brown,Lorenzo,NULL,Male,African-American,01/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/18/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +58214,66631,60428,PRETRIAL,Brown,Lorenzo,NULL,Male,African-American,01/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +27533,66639,26638,Probation,duplessy,michael,NULL,Male,African-American,09/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +27533,66639,26638,Probation,duplessy,michael,NULL,Male,African-American,09/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +27533,66639,26638,Probation,duplessy,michael,NULL,Male,African-American,09/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58205,66618,60416,PRETRIAL,Defazio,Vincent,NULL,Male,Caucasian,01/12/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +58205,66618,60416,PRETRIAL,Defazio,Vincent,NULL,Male,Caucasian,01/12/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +58205,66618,60416,PRETRIAL,Defazio,Vincent,NULL,Male,Caucasian,01/12/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,New,1,0 +58209,66623,60421,PRETRIAL,PHANORD,JEAN,NULL,Male,Other,08/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +58209,66623,60421,PRETRIAL,PHANORD,JEAN,NULL,Male,Other,08/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +58209,66623,60421,PRETRIAL,PHANORD,JEAN,NULL,Male,Other,08/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58206,66619,60417,PRETRIAL,Yoder,Christian,NULL,Male,Hispanic,09/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,4,High,7,Risk of Violence,-0.82,9,High,New,1,0 +58206,66619,60417,PRETRIAL,Yoder,Christian,NULL,Male,Hispanic,09/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +58206,66619,60417,PRETRIAL,Yoder,Christian,NULL,Male,Hispanic,09/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +13010,66626,60424,PRETRIAL,CORTES,ROBERT,DARIO,Male,Caucasian,04/25/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/18/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +13010,66626,60424,PRETRIAL,CORTES,ROBERT,DARIO,Male,Caucasian,04/25/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +13010,66626,60424,PRETRIAL,CORTES,ROBERT,DARIO,Male,Caucasian,04/25/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/18/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +58212,66628,60425,Probation,COTILUS,ANTHONY,W,Male,Caucasian,10/26/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/18/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +58212,66628,60425,Probation,COTILUS,ANTHONY,W,Male,Caucasian,10/26/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/18/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +58212,66628,60425,Probation,COTILUS,ANTHONY,W,Male,Caucasian,10/26/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +27573,66633,60430,PRETRIAL,Thomas,Laurence,NULL,Male,African-American,03/31/90,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +27573,66633,60430,PRETRIAL,Thomas,Laurence,NULL,Male,African-American,03/31/90,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +27573,66633,60430,PRETRIAL,Thomas,Laurence,NULL,Male,African-American,03/31/90,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,4,High,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +14531,66621,60419,PRETRIAL,Jackson,Trenard,Lavar,Male,African-American,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +14531,66621,60419,PRETRIAL,Jackson,Trenard,Lavar,Male,African-American,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,9,High,New,1,0 +14531,66621,60419,PRETRIAL,Jackson,Trenard,Lavar,Male,African-American,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +58222,66643,60438,PRETRIAL,Grella,Michael,NULL,Male,Caucasian,09/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/18/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +58222,66643,60438,PRETRIAL,Grella,Michael,NULL,Male,Caucasian,09/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/18/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +58222,66643,60438,PRETRIAL,Grella,Michael,NULL,Male,Caucasian,09/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58208,66622,60420,PRETRIAL,CINEUS,THERY,NULL,Male,Other,05/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/18/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +58208,66622,60420,PRETRIAL,CINEUS,THERY,NULL,Male,Other,05/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/18/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +58208,66622,60420,PRETRIAL,CINEUS,THERY,NULL,Male,Other,05/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58219,66640,60435,PRETRIAL,Castro,Allan,NULL,Male,Hispanic,10/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/18/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +58219,66640,60435,PRETRIAL,Castro,Allan,NULL,Male,Hispanic,10/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/18/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +58219,66640,60435,PRETRIAL,Castro,Allan,NULL,Male,Hispanic,10/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58210,66624,60422,PRETRIAL,Sabino,Kenneth,Fredrick,Male,Caucasian,04/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +58210,66624,60422,PRETRIAL,Sabino,Kenneth,Fredrick,Male,Caucasian,04/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +58210,66624,60422,PRETRIAL,Sabino,Kenneth,Fredrick,Male,Caucasian,04/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58218,66638,60434,PRETRIAL,Alen,Michael,NULL,Male,Caucasian,01/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/18/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +58218,66638,60434,PRETRIAL,Alen,Michael,NULL,Male,Caucasian,01/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/18/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +58218,66638,60434,PRETRIAL,Alen,Michael,NULL,Male,Caucasian,01/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58204,66617,60415,PRETRIAL,Mutti,Robert,NULL,Male,Caucasian,01/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +58204,66617,60415,PRETRIAL,Mutti,Robert,NULL,Male,Caucasian,01/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +58204,66617,60415,PRETRIAL,Mutti,Robert,NULL,Male,Caucasian,01/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58213,66630,60427,PRETRIAL,Peterson,Christopher,NULL,Male,African-American,06/30/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/18/13 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,New,1,0 +58213,66630,60427,PRETRIAL,Peterson,Christopher,NULL,Male,African-American,06/30/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,5,Medium,New,1,0 +58213,66630,60427,PRETRIAL,Peterson,Christopher,NULL,Male,African-American,06/30/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/18/13 0:00,2,Medium,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +58215,66632,60429,Probation,FIORELLO,JOSEPH,NULL,Male,Caucasian,10/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/18/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +58215,66632,60429,Probation,FIORELLO,JOSEPH,NULL,Male,Caucasian,10/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/18/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +58215,66632,60429,Probation,FIORELLO,JOSEPH,NULL,Male,Caucasian,10/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58207,66620,60418,PRETRIAL,Martin,Daquan,Imani,Male,African-American,11/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,New,1,0 +58207,66620,60418,PRETRIAL,Martin,Daquan,Imani,Male,African-American,11/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +58207,66620,60418,PRETRIAL,Martin,Daquan,Imani,Male,African-American,11/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +6746,66627,6339,PRETRIAL,JONES,KEISHA,NULL,Female,African-American,12/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/18/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,Copy,1,0 +6746,66627,6339,PRETRIAL,JONES,KEISHA,NULL,Female,African-American,12/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/18/13 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,Copy,1,0 +6746,66627,6339,PRETRIAL,JONES,KEISHA,NULL,Female,African-American,12/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +58216,66634,60431,Probation,Remedios,Juan,NULL,Male,Hispanic,10/15/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/18/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +58216,66634,60431,Probation,Remedios,Juan,NULL,Male,Hispanic,10/15/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/18/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +58216,66634,60431,Probation,Remedios,Juan,NULL,Male,Hispanic,10/15/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +19465,66629,60426,PRETRIAL,TORRES,ARCADIO,NULL,Male,Hispanic,05/07/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/18/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +19465,66629,60426,PRETRIAL,TORRES,ARCADIO,NULL,Male,Hispanic,05/07/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/18/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +19465,66629,60426,PRETRIAL,TORRES,ARCADIO,NULL,Male,Hispanic,05/07/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +58211,66625,60423,PRETRIAL,Pena,Jorge,Alberto,Male,Hispanic,10/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/18/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +58211,66625,60423,PRETRIAL,Pena,Jorge,Alberto,Male,Hispanic,10/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/18/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +58211,66625,60423,PRETRIAL,Pena,Jorge,Alberto,Male,Hispanic,10/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58228,66650,60444,PRETRIAL,MARROQUINCAMACHO,RUPERTO,NULL,Male,Caucasian,01/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/19/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +58228,66650,60444,PRETRIAL,MARROQUINCAMACHO,RUPERTO,NULL,Male,Caucasian,01/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/19/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +58228,66650,60444,PRETRIAL,MARROQUINCAMACHO,RUPERTO,NULL,Male,Caucasian,01/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58224,66646,60440,PRETRIAL,Pierre,Johnson,NULL,Male,African-American,06/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +58224,66646,60440,PRETRIAL,Pierre,Johnson,NULL,Male,African-American,06/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +58224,66646,60440,PRETRIAL,Pierre,Johnson,NULL,Male,African-American,06/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58230,66655,60446,PRETRIAL,Abrames,Susan,NULL,Female,Caucasian,02/21/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/19/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +58230,66655,60446,PRETRIAL,Abrames,Susan,NULL,Female,Caucasian,02/21/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/19/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +58230,66655,60446,PRETRIAL,Abrames,Susan,NULL,Female,Caucasian,02/21/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +13602,66651,12997,Probation,SAMUEL,SHERWIN,NULL,Male,African-American,09/22/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,Copy,1,0 +13602,66651,12997,Probation,SAMUEL,SHERWIN,NULL,Male,African-American,09/22/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,Copy,1,0 +13602,66651,12997,Probation,SAMUEL,SHERWIN,NULL,Male,African-American,09/22/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +36268,66653,35530,PRETRIAL,Kendrick,Jeremiah,NULL,Male,African-American,11/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +36268,66653,35530,PRETRIAL,Kendrick,Jeremiah,NULL,Male,African-American,11/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,Copy,1,0 +36268,66653,35530,PRETRIAL,Kendrick,Jeremiah,NULL,Male,African-American,11/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +58223,66645,60439,PRETRIAL,HERBERT,ROZIER,NULL,Male,African-American,08/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/19/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +58223,66645,60439,PRETRIAL,HERBERT,ROZIER,NULL,Male,African-American,08/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/19/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +58223,66645,60439,PRETRIAL,HERBERT,ROZIER,NULL,Male,African-American,08/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58226,66648,60442,PRETRIAL,Haynes,Brian,Cornelius,Male,African-American,12/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +58226,66648,60442,PRETRIAL,Haynes,Brian,Cornelius,Male,African-American,12/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +58226,66648,60442,PRETRIAL,Haynes,Brian,Cornelius,Male,African-American,12/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58229,66654,60445,PRETRIAL,SOMARRIBA-BARRERA,JOSE,S,Male,Caucasian,12/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/19/13 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +58229,66654,60445,PRETRIAL,SOMARRIBA-BARRERA,JOSE,S,Male,Caucasian,12/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/19/13 0:00,1,Low,8,Risk of Recidivism,-2.76,1,Low,New,1,0 +58229,66654,60445,PRETRIAL,SOMARRIBA-BARRERA,JOSE,S,Male,Caucasian,12/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58225,66647,60441,PRETRIAL,Thomas,Andrew,David,Male,Caucasian,05/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +58225,66647,60441,PRETRIAL,Thomas,Andrew,David,Male,Caucasian,05/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +58225,66647,60441,PRETRIAL,Thomas,Andrew,David,Male,Caucasian,05/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58227,66649,60443,PRETRIAL,SERFIS,DEAN,NULL,Male,Caucasian,05/23/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +58227,66649,60443,PRETRIAL,SERFIS,DEAN,NULL,Male,Caucasian,05/23/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,8,Risk of Recidivism,-2.64,1,Low,New,1,0 +58227,66649,60443,PRETRIAL,SERFIS,DEAN,NULL,Male,Caucasian,05/23/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +40560,66644,40174,PRETRIAL,Austin,Freddie,NULL,Male,African-American,01/25/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,Copy,1,0 +40560,66644,40174,PRETRIAL,Austin,Freddie,NULL,Male,African-American,01/25/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,Copy,1,0 +40560,66644,40174,PRETRIAL,Austin,Freddie,NULL,Male,African-American,01/25/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +58240,66665,60456,PRETRIAL,ROMINES,JERRY,NULL,Male,Caucasian,12/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +58240,66665,60456,PRETRIAL,ROMINES,JERRY,NULL,Male,Caucasian,12/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +58240,66665,60456,PRETRIAL,ROMINES,JERRY,NULL,Male,Caucasian,12/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58232,66657,60448,PRETRIAL,Latimore,Anthony,NULL,Male,African-American,04/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +58232,66657,60448,PRETRIAL,Latimore,Anthony,NULL,Male,African-American,04/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +58232,66657,60448,PRETRIAL,Latimore,Anthony,NULL,Male,African-American,04/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58235,66660,60451,PRETRIAL,ROLLE,DESMOND,NULL,Male,African-American,03/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/20/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +58235,66660,60451,PRETRIAL,ROLLE,DESMOND,NULL,Male,African-American,03/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/20/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +58235,66660,60451,PRETRIAL,ROLLE,DESMOND,NULL,Male,African-American,03/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58244,66670,60461,PRETRIAL,SIMPSON,GAVIN,NULL,Male,Other,02/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/20/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +58244,66670,60461,PRETRIAL,SIMPSON,GAVIN,NULL,Male,Other,02/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/20/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +58244,66670,60461,PRETRIAL,SIMPSON,GAVIN,NULL,Male,Other,02/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58231,66656,60447,PRETRIAL,WALKER,PRINCESS,D,Female,African-American,10/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +58231,66656,60447,PRETRIAL,WALKER,PRINCESS,D,Female,African-American,10/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +58231,66656,60447,PRETRIAL,WALKER,PRINCESS,D,Female,African-American,10/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58249,66672,60463,PRETRIAL,Reilly,Peter,James,Male,Caucasian,02/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +58249,66672,60463,PRETRIAL,Reilly,Peter,James,Male,Caucasian,02/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +58249,66672,60463,PRETRIAL,Reilly,Peter,James,Male,Caucasian,02/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58242,66668,60459,PRETRIAL,SMITH,RAHEEM,NULL,Male,African-American,06/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,4,High,7,Risk of Violence,-0.76,9,High,New,1,0 +58242,66668,60459,PRETRIAL,SMITH,RAHEEM,NULL,Male,African-American,06/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +58242,66668,60459,PRETRIAL,SMITH,RAHEEM,NULL,Male,African-American,06/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58238,66663,60454,PRETRIAL,WILLIAMS,NIKKI,NULL,Female,African-American,11/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +58238,66663,60454,PRETRIAL,WILLIAMS,NIKKI,NULL,Female,African-American,11/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +58238,66663,60454,PRETRIAL,WILLIAMS,NIKKI,NULL,Female,African-American,11/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58243,66669,60460,PRETRIAL,Reffner,Sire,NULL,Male,Caucasian,09/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +58243,66669,60460,PRETRIAL,Reffner,Sire,NULL,Male,Caucasian,09/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +58243,66669,60460,PRETRIAL,Reffner,Sire,NULL,Male,Caucasian,09/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58236,66661,60452,PRETRIAL,Williams,Leontae,NULL,Female,African-American,11/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +58236,66661,60452,PRETRIAL,Williams,Leontae,NULL,Female,African-American,11/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,9,High,New,1,0 +58236,66661,60452,PRETRIAL,Williams,Leontae,NULL,Female,African-American,11/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58234,66659,60450,PRETRIAL,DEAN,EDDIE,NULL,Male,African-American,04/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/20/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +58234,66659,60450,PRETRIAL,DEAN,EDDIE,NULL,Male,African-American,04/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/20/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +58234,66659,60450,PRETRIAL,DEAN,EDDIE,NULL,Male,African-American,04/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58233,66658,60449,PRETRIAL,SORRELL,DERRIK,NULL,Male,Caucasian,10/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +58233,66658,60449,PRETRIAL,SORRELL,DERRIK,NULL,Male,Caucasian,10/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +58233,66658,60449,PRETRIAL,SORRELL,DERRIK,NULL,Male,Caucasian,10/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58241,66666,60457,PRETRIAL,Pomales,Abigail,NULL,Female,Caucasian,10/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +58241,66666,60457,PRETRIAL,Pomales,Abigail,NULL,Female,Caucasian,10/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +58241,66666,60457,PRETRIAL,Pomales,Abigail,NULL,Female,Caucasian,10/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58237,66662,60453,PRETRIAL,Thetais,Joe,NULL,Male,African-American,04/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +58237,66662,60453,PRETRIAL,Thetais,Joe,NULL,Male,African-American,04/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +58237,66662,60453,PRETRIAL,Thetais,Joe,NULL,Male,African-American,04/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58239,66664,60455,PRETRIAL,MILLER,BERNARD,ANDREW,Male,Other,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +58239,66664,60455,PRETRIAL,MILLER,BERNARD,ANDREW,Male,Other,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +58239,66664,60455,PRETRIAL,MILLER,BERNARD,ANDREW,Male,Other,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +8371,66667,60458,PRETRIAL,PATTERSON,CHRISTOPHER,ANTHONY,Male,African-American,06/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +8371,66667,60458,PRETRIAL,PATTERSON,CHRISTOPHER,ANTHONY,Male,African-American,06/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,4,High,8,Risk of Recidivism,0.36,9,High,New,1,0 +8371,66667,60458,PRETRIAL,PATTERSON,CHRISTOPHER,ANTHONY,Male,African-American,06/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58245,66671,60462,PRETRIAL,Velez-cupeles,Ramon,NULL,Male,Caucasian,04/07/42,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +58245,66671,60462,PRETRIAL,Velez-cupeles,Ramon,NULL,Male,Caucasian,04/07/42,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +58245,66671,60462,PRETRIAL,Velez-cupeles,Ramon,NULL,Male,Caucasian,04/07/42,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +44470,66718,60504,PRETRIAL,ARMSTRONG,MARK,NULL,Male,Caucasian,06/27/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/21/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +44470,66718,60504,PRETRIAL,ARMSTRONG,MARK,NULL,Male,Caucasian,06/27/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +44470,66718,60504,PRETRIAL,ARMSTRONG,MARK,NULL,Male,Caucasian,06/27/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58253,66676,60467,PRETRIAL,Georges,Romeld,NULL,Male,Other,10/07/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +58253,66676,60467,PRETRIAL,Georges,Romeld,NULL,Male,Other,10/07/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-2.91,1,Low,New,1,0 +58253,66676,60467,PRETRIAL,Georges,Romeld,NULL,Male,Other,10/07/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58273,66701,60491,Probation,julesaint,amonise,NULL,Female,African-American,04/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/21/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +58273,66701,60491,Probation,julesaint,amonise,NULL,Female,African-American,04/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +58273,66701,60491,Probation,julesaint,amonise,NULL,Female,African-American,04/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +21361,66680,60470,PRETRIAL,Toussaint,Rodney,NULL,Male,African-American,09/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,4,High,7,Risk of Violence,-0.72,9,High,New,1,0 +21361,66680,60470,PRETRIAL,Toussaint,Rodney,NULL,Male,African-American,09/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,4,High,8,Risk of Recidivism,0.86,10,High,New,1,0 +21361,66680,60470,PRETRIAL,Toussaint,Rodney,NULL,Male,African-American,09/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +33964,66713,33088,PRETRIAL,sheely,willie,NULL,Male,African-American,09/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/21/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,Copy,1,0 +33964,66713,33088,PRETRIAL,sheely,willie,NULL,Male,African-American,09/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,Copy,1,0 +33964,66713,33088,PRETRIAL,sheely,willie,NULL,Male,African-American,09/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/21/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +58257,66683,60473,PRETRIAL,Moscatiello,Anthony,NULL,Male,Caucasian,04/18/39,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/21/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +58257,66683,60473,PRETRIAL,Moscatiello,Anthony,NULL,Male,Caucasian,04/18/39,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +58257,66683,60473,PRETRIAL,Moscatiello,Anthony,NULL,Male,Caucasian,04/18/39,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58259,66685,60475,PRETRIAL,Maloy,William,NULL,Male,Caucasian,08/03/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/21/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +58259,66685,60475,PRETRIAL,Maloy,William,NULL,Male,Caucasian,08/03/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +58259,66685,60475,PRETRIAL,Maloy,William,NULL,Male,Caucasian,08/03/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58265,66692,60482,Probation,buchanan,deion,NULL,Male,African-American,03/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +58265,66692,60482,Probation,buchanan,deion,NULL,Male,African-American,03/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +58265,66692,60482,Probation,buchanan,deion,NULL,Male,African-American,03/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58277,66706,60495,PRETRIAL,BOYD,ROBERT,NULL,Male,African-American,08/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +58277,66706,60495,PRETRIAL,BOYD,ROBERT,NULL,Male,African-American,08/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +58277,66706,60495,PRETRIAL,BOYD,ROBERT,NULL,Male,African-American,08/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +12038,66720,45559,PRETRIAL,BANNING,KEVIN,PAUL,Male,Caucasian,01/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,Copy,1,0 +12038,66720,45559,PRETRIAL,BANNING,KEVIN,PAUL,Male,Caucasian,01/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,Copy,1,0 +12038,66720,45559,PRETRIAL,BANNING,KEVIN,PAUL,Male,Caucasian,01/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +58255,66679,60469,PRETRIAL,Marakin,Siarhei,Anatolievi,Male,Caucasian,08/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +58255,66679,60469,PRETRIAL,Marakin,Siarhei,Anatolievi,Male,Caucasian,08/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +58255,66679,60469,PRETRIAL,Marakin,Siarhei,Anatolievi,Male,Caucasian,08/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57499,66695,60485,PRETRIAL,Alonso,Jenny,NULL,Female,Hispanic,12/09/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +57499,66695,60485,PRETRIAL,Alonso,Jenny,NULL,Female,Hispanic,12/09/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +57499,66695,60485,PRETRIAL,Alonso,Jenny,NULL,Female,Hispanic,12/09/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58251,66674,60465,PRETRIAL,EXUMAT,ISACC,NULL,Male,Other,08/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +58251,66674,60465,PRETRIAL,EXUMAT,ISACC,NULL,Male,Other,08/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +58251,66674,60465,PRETRIAL,EXUMAT,ISACC,NULL,Male,Other,08/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +34006,66687,60477,PRETRIAL,Garciamarino,Jessica,NULL,Female,Caucasian,08/18/92,17,All Scales,Intake,English,Other,Jail Inmate,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +34006,66687,60477,PRETRIAL,Garciamarino,Jessica,NULL,Female,Caucasian,08/18/92,17,All Scales,Intake,English,Other,Jail Inmate,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +34006,66687,60477,PRETRIAL,Garciamarino,Jessica,NULL,Female,Caucasian,08/18/92,17,All Scales,Intake,English,Other,Jail Inmate,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +47840,66700,60490,PRETRIAL,SAINTHELHOMME,MILAND,NULL,Male,African-American,12/01/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-4.33,1,Low,New,1,0 +47840,66700,60490,PRETRIAL,SAINTHELHOMME,MILAND,NULL,Male,African-American,12/01/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +47840,66700,60490,PRETRIAL,SAINTHELHOMME,MILAND,NULL,Male,African-American,12/01/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58279,66711,60498,PRETRIAL,DUVAL,CHERNARD,NULL,Male,African-American,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +58279,66711,60498,PRETRIAL,DUVAL,CHERNARD,NULL,Male,African-American,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +58279,66711,60498,PRETRIAL,DUVAL,CHERNARD,NULL,Male,African-American,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58264,66690,60480,PRETRIAL,Hepburn,Joseph,NULL,Female,African-American,06/27/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/21/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +58264,66690,60480,PRETRIAL,Hepburn,Joseph,NULL,Female,African-American,06/27/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +58264,66690,60480,PRETRIAL,Hepburn,Joseph,NULL,Female,African-American,06/27/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +35545,66703,60493,PRETRIAL,JUNE,CURTIS,NULL,Male,African-American,08/22/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/21/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +35545,66703,60493,PRETRIAL,JUNE,CURTIS,NULL,Male,African-American,08/22/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/21/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +35545,66703,60493,PRETRIAL,JUNE,CURTIS,NULL,Male,African-American,08/22/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +45913,66708,60497,PRETRIAL,Hughes,Richard,NULL,Male,Caucasian,01/15/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +45913,66708,60497,PRETRIAL,Hughes,Richard,NULL,Male,Caucasian,01/15/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +45913,66708,60497,PRETRIAL,Hughes,Richard,NULL,Male,Caucasian,01/15/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +48654,66682,60472,PRETRIAL,Hamilton,Christopher,NULL,Male,African-American,08/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +48654,66682,60472,PRETRIAL,Hamilton,Christopher,NULL,Male,African-American,08/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +48654,66682,60472,PRETRIAL,Hamilton,Christopher,NULL,Male,African-American,08/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58281,66714,60500,PRETRIAL,SMITH,ANTWAIN,NULL,Male,African-American,12/27/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +58281,66714,60500,PRETRIAL,SMITH,ANTWAIN,NULL,Male,African-American,12/27/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +58281,66714,60500,PRETRIAL,SMITH,ANTWAIN,NULL,Male,African-American,12/27/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58252,66675,60466,PRETRIAL,TORRES,BRYAN,NULL,Male,Hispanic,02/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +58252,66675,60466,PRETRIAL,TORRES,BRYAN,NULL,Male,Hispanic,02/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +58252,66675,60466,PRETRIAL,TORRES,BRYAN,NULL,Male,Hispanic,02/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +48506,66693,60483,PRETRIAL,Lutterodt,Gabrielle,NULL,Female,African-American,02/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +48506,66693,60483,PRETRIAL,Lutterodt,Gabrielle,NULL,Female,African-American,02/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,7,Medium,New,1,0 +48506,66693,60483,PRETRIAL,Lutterodt,Gabrielle,NULL,Female,African-American,02/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +7192,66691,60481,PRETRIAL,ANDERSON,ZACHERY,RANDALL,Male,Caucasian,01/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +7192,66691,60481,PRETRIAL,ANDERSON,ZACHERY,RANDALL,Male,Caucasian,01/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +7192,66691,60481,PRETRIAL,ANDERSON,ZACHERY,RANDALL,Male,Caucasian,01/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57727,66705,59864,PRETRIAL,Joseph,Robens,NULL,Male,African-American,09/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,Copy,1,0 +57727,66705,59864,PRETRIAL,Joseph,Robens,NULL,Male,African-American,09/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,Copy,1,0 +57727,66705,59864,PRETRIAL,Joseph,Robens,NULL,Male,African-American,09/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +7109,66677,6700,PRETRIAL,BARTHER,BRANDON,NULL,Male,African-American,09/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,Copy,1,0 +7109,66677,6700,PRETRIAL,BARTHER,BRANDON,NULL,Male,African-American,09/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,Copy,1,0 +7109,66677,6700,PRETRIAL,BARTHER,BRANDON,NULL,Male,African-American,09/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +58258,66684,60474,PRETRIAL,Brown,Laneatra,NULL,Female,African-American,01/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +58258,66684,60474,PRETRIAL,Brown,Laneatra,NULL,Female,African-American,01/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +58258,66684,60474,PRETRIAL,Brown,Laneatra,NULL,Female,African-American,01/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58271,66698,60488,PRETRIAL,Rodriguez,David,NULL,Male,Hispanic,08/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +58271,66698,60488,PRETRIAL,Rodriguez,David,NULL,Male,Hispanic,08/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +58271,66698,60488,PRETRIAL,Rodriguez,David,NULL,Male,Hispanic,08/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58285,66719,60505,PRETRIAL,Blake,Evan,NULL,Male,Caucasian,02/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,4,High,7,Risk of Violence,-0.7,9,High,New,1,0 +58285,66719,60505,PRETRIAL,Blake,Evan,NULL,Male,Caucasian,02/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +58285,66719,60505,PRETRIAL,Blake,Evan,NULL,Male,Caucasian,02/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58267,66694,60484,PRETRIAL,Hammond,Aaron,NULL,Male,Caucasian,05/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +58267,66694,60484,PRETRIAL,Hammond,Aaron,NULL,Male,Caucasian,05/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +58267,66694,60484,PRETRIAL,Hammond,Aaron,NULL,Male,Caucasian,05/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58284,66717,60503,PRETRIAL,Goldfinger,Rachael,NULL,Female,Caucasian,12/19/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +58284,66717,60503,PRETRIAL,Goldfinger,Rachael,NULL,Female,Caucasian,12/19/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-0.57,5,Medium,New,1,0 +58284,66717,60503,PRETRIAL,Goldfinger,Rachael,NULL,Female,Caucasian,12/19/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58256,66681,60471,PRETRIAL,Scott,Shadae,NULL,Female,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +58256,66681,60471,PRETRIAL,Scott,Shadae,NULL,Female,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +58256,66681,60471,PRETRIAL,Scott,Shadae,NULL,Female,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58268,66696,60486,Probation,Brown,Brendan,NULL,Male,African-American,12/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +58268,66696,60486,Probation,Brown,Brendan,NULL,Male,African-American,12/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +58268,66696,60486,Probation,Brown,Brendan,NULL,Male,African-American,12/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58282,66715,60501,Probation,demarco,joseph,NULL,Male,Caucasian,06/12/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/21/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +58282,66715,60501,Probation,demarco,joseph,NULL,Male,Caucasian,06/12/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +58282,66715,60501,Probation,demarco,joseph,NULL,Male,Caucasian,06/12/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58250,66673,60464,PRETRIAL,Renteria,Meyer,Francisco,Male,Hispanic,04/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +58250,66673,60464,PRETRIAL,Renteria,Meyer,Francisco,Male,Hispanic,04/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +58250,66673,60464,PRETRIAL,Renteria,Meyer,Francisco,Male,Hispanic,04/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58262,66688,60478,Probation,SCHEMER,ASHLEY,MICHELE,Female,Caucasian,01/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +58262,66688,60478,Probation,SCHEMER,ASHLEY,MICHELE,Female,Caucasian,01/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +58262,66688,60478,Probation,SCHEMER,ASHLEY,MICHELE,Female,Caucasian,01/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58275,66702,60492,Probation,Mcfadden,Jennie,NULL,Female,African-American,02/13/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +58275,66702,60492,Probation,Mcfadden,Jennie,NULL,Female,African-American,02/13/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +58275,66702,60492,Probation,Mcfadden,Jennie,NULL,Female,African-American,02/13/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58276,66704,60494,Probation,Basri,Rabia,NULL,Female,Arabic,07/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +58276,66704,60494,Probation,Basri,Rabia,NULL,Female,Arabic,07/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +58276,66704,60494,Probation,Basri,Rabia,NULL,Female,Arabic,07/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58278,66707,60496,Probation,OVADIA,ADRIEL,ABRAHAM,Male,Hispanic,12/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +58278,66707,60496,Probation,OVADIA,ADRIEL,ABRAHAM,Male,Hispanic,12/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +58278,66707,60496,Probation,OVADIA,ADRIEL,ABRAHAM,Male,Hispanic,12/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58261,66686,60476,PRETRIAL,Mouzon,Kevin,NULL,Male,African-American,04/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +58261,66686,60476,PRETRIAL,Mouzon,Kevin,NULL,Male,African-American,04/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +58261,66686,60476,PRETRIAL,Mouzon,Kevin,NULL,Male,African-American,04/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58272,66699,60489,PRETRIAL,Quesada,Alfonso,NULL,Male,Hispanic,05/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/21/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +58272,66699,60489,PRETRIAL,Quesada,Alfonso,NULL,Male,Hispanic,05/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/21/13 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +58272,66699,60489,PRETRIAL,Quesada,Alfonso,NULL,Male,Hispanic,05/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58280,66712,60499,Probation,gault,kylee,NULL,Female,Caucasian,09/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +58280,66712,60499,Probation,gault,kylee,NULL,Female,Caucasian,09/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +58280,66712,60499,Probation,gault,kylee,NULL,Female,Caucasian,09/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58254,66678,60468,PRETRIAL,TORRES,TIFFANY,NULL,Female,Hispanic,05/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +58254,66678,60468,PRETRIAL,TORRES,TIFFANY,NULL,Female,Hispanic,05/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +58254,66678,60468,PRETRIAL,TORRES,TIFFANY,NULL,Female,Hispanic,05/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58308,66746,60529,Probation,gomez,heriberto,NULL,Male,Hispanic,02/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +58308,66746,60529,Probation,gomez,heriberto,NULL,Male,Hispanic,02/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +58308,66746,60529,Probation,gomez,heriberto,NULL,Male,Hispanic,02/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58288,66725,60510,PRETRIAL,JOHNSON,EDWARD,NATHANIEL,Male,African-American,10/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/22/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +58288,66725,60510,PRETRIAL,JOHNSON,EDWARD,NATHANIEL,Male,African-American,10/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +58288,66725,60510,PRETRIAL,JOHNSON,EDWARD,NATHANIEL,Male,African-American,10/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/22/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58315,66754,60536,Probation,richards,lisa,NULL,Female,Caucasian,08/04/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/22/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +58315,66754,60536,Probation,richards,lisa,NULL,Female,Caucasian,08/04/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/22/13 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +58315,66754,60536,Probation,richards,lisa,NULL,Female,Caucasian,08/04/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +58289,66723,60508,PRETRIAL,Bailey,Leroy,NULL,Male,Other,05/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +58289,66723,60508,PRETRIAL,Bailey,Leroy,NULL,Male,Other,05/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +58289,66723,60508,PRETRIAL,Bailey,Leroy,NULL,Male,Other,05/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58301,66738,60522,Probation,Lanauze,Anthony,NULL,Male,Hispanic,01/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +58301,66738,60522,Probation,Lanauze,Anthony,NULL,Male,Hispanic,01/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +58301,66738,60522,Probation,Lanauze,Anthony,NULL,Male,Hispanic,01/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58294,66730,60515,PRETRIAL,GRIFFIN,LATONYA,YVETTE,Female,African-American,11/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +58294,66730,60515,PRETRIAL,GRIFFIN,LATONYA,YVETTE,Female,African-American,11/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +58294,66730,60515,PRETRIAL,GRIFFIN,LATONYA,YVETTE,Female,African-American,11/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58313,66751,60534,Probation,Johnson,Ronald,NULL,Male,African-American,04/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/22/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +58313,66751,60534,Probation,Johnson,Ronald,NULL,Male,African-American,04/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +58313,66751,60534,Probation,Johnson,Ronald,NULL,Male,African-American,04/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +48153,66726,60511,PRETRIAL,Washington,Marqus,NULL,Male,African-American,03/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +48153,66726,60511,PRETRIAL,Washington,Marqus,NULL,Male,African-American,03/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,4,High,8,Risk of Recidivism,0.1,8,High,New,1,0 +48153,66726,60511,PRETRIAL,Washington,Marqus,NULL,Male,African-American,03/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +58292,66728,60513,PRETRIAL,McKenzie,Tremaine,Alex,Male,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +58292,66728,60513,PRETRIAL,McKenzie,Tremaine,Alex,Male,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,4,High,8,Risk of Recidivism,0.58,9,High,New,1,0 +58292,66728,60513,PRETRIAL,McKenzie,Tremaine,Alex,Male,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58309,66747,60530,Probation,STANLEY,MICHAEL,NULL,Male,Caucasian,12/25/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +58309,66747,60530,Probation,STANLEY,MICHAEL,NULL,Male,Caucasian,12/25/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +58309,66747,60530,Probation,STANLEY,MICHAEL,NULL,Male,Caucasian,12/25/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58311,66749,60532,PRETRIAL,Sarlo,Domimick,C,Male,Caucasian,08/10/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/22/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +58311,66749,60532,PRETRIAL,Sarlo,Domimick,C,Male,Caucasian,08/10/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +58311,66749,60532,PRETRIAL,Sarlo,Domimick,C,Male,Caucasian,08/10/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +23392,66756,22584,PRETRIAL,copeland,xavier,NULL,Male,African-American,11/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,Copy,1,0 +23392,66756,22584,PRETRIAL,copeland,xavier,NULL,Male,African-American,11/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,Copy,1,0 +23392,66756,22584,PRETRIAL,copeland,xavier,NULL,Male,African-American,11/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +58303,66740,60524,Probation,Kamoo,Mohamed,NULL,Male,Other,07/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/22/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +58303,66740,60524,Probation,Kamoo,Mohamed,NULL,Male,Other,07/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +58303,66740,60524,Probation,Kamoo,Mohamed,NULL,Male,Other,07/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58295,66731,60516,PRETRIAL,Ravino,James,NULL,Male,Caucasian,09/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +58295,66731,60516,PRETRIAL,Ravino,James,NULL,Male,Caucasian,09/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +58295,66731,60516,PRETRIAL,Ravino,James,NULL,Male,Caucasian,09/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58298,66735,60519,Probation,way,gwendolyn,NULL,Female,African-American,04/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/22/13 0:00,2,Medium,7,Risk of Violence,-2.99,1,Low,New,1,0 +58298,66735,60519,Probation,way,gwendolyn,NULL,Female,African-American,04/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +58298,66735,60519,Probation,way,gwendolyn,NULL,Female,African-American,04/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/22/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56497,66744,58487,Probation,Baker,Michelle,NULL,Female,Caucasian,12/26/77,17,All Scales,Intake,English,Conditional Release,Probation,Separated,10/22/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +56497,66744,58487,Probation,Baker,Michelle,NULL,Female,Caucasian,12/26/77,17,All Scales,Intake,English,Conditional Release,Probation,Separated,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +56497,66744,58487,Probation,Baker,Michelle,NULL,Female,Caucasian,12/26/77,17,All Scales,Intake,English,Conditional Release,Probation,Separated,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58293,66729,60514,PRETRIAL,Thach,Ngoc,Cuong,Male,Other,05/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +58293,66729,60514,PRETRIAL,Thach,Ngoc,Cuong,Male,Other,05/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +58293,66729,60514,PRETRIAL,Thach,Ngoc,Cuong,Male,Other,05/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58300,66737,60521,Probation,Roche,Michael,NULL,Male,Caucasian,08/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +58300,66737,60521,Probation,Roche,Michael,NULL,Male,Caucasian,08/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +58300,66737,60521,Probation,Roche,Michael,NULL,Male,Caucasian,08/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58305,66742,60526,PRETRIAL,Louissaint,Alex,Antoine,Male,African-American,01/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.09,8,High,New,1,0 +58305,66742,60526,PRETRIAL,Louissaint,Alex,Antoine,Male,African-American,01/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +58305,66742,60526,PRETRIAL,Louissaint,Alex,Antoine,Male,African-American,01/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58286,66721,60506,PRETRIAL,Rolle,Tarell,NULL,Male,African-American,04/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +58286,66721,60506,PRETRIAL,Rolle,Tarell,NULL,Male,African-American,04/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,New,1,0 +58286,66721,60506,PRETRIAL,Rolle,Tarell,NULL,Male,African-American,04/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58290,66724,60509,PRETRIAL,Maharajh,Rajdaye,NULL,Female,Other,05/12/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/22/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +58290,66724,60509,PRETRIAL,Maharajh,Rajdaye,NULL,Female,Other,05/12/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/22/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +58290,66724,60509,PRETRIAL,Maharajh,Rajdaye,NULL,Female,Other,05/12/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58307,66745,60528,PRETRIAL,spencer,daniel,NULL,Male,African-American,10/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +58307,66745,60528,PRETRIAL,spencer,daniel,NULL,Male,African-American,10/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +58307,66745,60528,PRETRIAL,spencer,daniel,NULL,Male,African-American,10/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58314,66752,60535,Probation,nappi,robert,NULL,Male,Caucasian,06/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/22/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +58314,66752,60535,Probation,nappi,robert,NULL,Male,Caucasian,06/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +58314,66752,60535,Probation,nappi,robert,NULL,Male,Caucasian,06/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58296,66732,60517,PRETRIAL,Forrest,Orville,NULL,Male,Other,08/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +58296,66732,60517,PRETRIAL,Forrest,Orville,NULL,Male,Other,08/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +58296,66732,60517,PRETRIAL,Forrest,Orville,NULL,Male,Other,08/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +48566,66753,49266,PRETRIAL,FRANCIS,DAMIAN,NULL,Male,African-American,01/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,Copy,1,0 +48566,66753,49266,PRETRIAL,FRANCIS,DAMIAN,NULL,Male,African-American,01/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,Copy,1,0 +48566,66753,49266,PRETRIAL,FRANCIS,DAMIAN,NULL,Male,African-American,01/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +58291,66727,60512,PRETRIAL,GRANT,DEVONTA,D,Male,African-American,09/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +58291,66727,60512,PRETRIAL,GRANT,DEVONTA,D,Male,African-American,09/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +58291,66727,60512,PRETRIAL,GRANT,DEVONTA,D,Male,African-American,09/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58297,66734,60518,PRETRIAL,PEREZ-GODINEZ,OSCAR,NULL,Male,Hispanic,10/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/22/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +58297,66734,60518,PRETRIAL,PEREZ-GODINEZ,OSCAR,NULL,Male,Hispanic,10/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +58297,66734,60518,PRETRIAL,PEREZ-GODINEZ,OSCAR,NULL,Male,Hispanic,10/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58304,66741,60525,PRETRIAL,PANICCIA,JOHN,NULL,Male,Caucasian,05/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/22/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +58304,66741,60525,PRETRIAL,PANICCIA,JOHN,NULL,Male,Caucasian,05/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/22/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +58304,66741,60525,PRETRIAL,PANICCIA,JOHN,NULL,Male,Caucasian,05/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +18440,66755,60537,PRETRIAL,TRIBBLE,PATRICIA,NULL,Female,Caucasian,05/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/22/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +18440,66755,60537,PRETRIAL,TRIBBLE,PATRICIA,NULL,Female,Caucasian,05/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/22/13 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +18440,66755,60537,PRETRIAL,TRIBBLE,PATRICIA,NULL,Female,Caucasian,05/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,30,9,High,New,1,0 +34174,54388,49492,PRETRIAL,MASSINGILL,RUSSELL,NULL,Male,African-American,05/12/73,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Separated,10/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +34174,54388,49492,PRETRIAL,MASSINGILL,RUSSELL,NULL,Male,African-American,05/12/73,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Separated,10/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +34174,54388,49492,PRETRIAL,MASSINGILL,RUSSELL,NULL,Male,African-American,05/12/73,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Separated,10/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58310,66748,60531,PRETRIAL,IDOWU,MARGARET,NULL,Female,African-American,03/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +58310,66748,60531,PRETRIAL,IDOWU,MARGARET,NULL,Female,African-American,03/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +58310,66748,60531,PRETRIAL,IDOWU,MARGARET,NULL,Female,African-American,03/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58299,66736,60520,Probation,RASTELLI,SERGIO,NULL,Male,Caucasian,06/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +58299,66736,60520,Probation,RASTELLI,SERGIO,NULL,Male,Caucasian,06/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +58299,66736,60520,Probation,RASTELLI,SERGIO,NULL,Male,Caucasian,06/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58306,66743,60527,PRETRIAL,Pereyra,Osvaldo,NULL,Male,Caucasian,06/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/22/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +58306,66743,60527,PRETRIAL,Pereyra,Osvaldo,NULL,Male,Caucasian,06/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +58306,66743,60527,PRETRIAL,Pereyra,Osvaldo,NULL,Male,Caucasian,06/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/22/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58287,66722,60507,PRETRIAL,Reinosolopez,Franklin,NULL,Male,Other,02/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +58287,66722,60507,PRETRIAL,Reinosolopez,Franklin,NULL,Male,Other,02/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/13 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +58287,66722,60507,PRETRIAL,Reinosolopez,Franklin,NULL,Male,Other,02/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58302,66739,60523,Probation,Ciaramello,Thomas,NULL,Male,Caucasian,10/24/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/22/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +58302,66739,60523,Probation,Ciaramello,Thomas,NULL,Male,Caucasian,10/24/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/22/13 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +58302,66739,60523,Probation,Ciaramello,Thomas,NULL,Male,Caucasian,10/24/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58316,66757,60538,PRETRIAL,Adderly,Terrence,NULL,Male,Other,12/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/23/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +58316,66757,60538,PRETRIAL,Adderly,Terrence,NULL,Male,Other,12/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/23/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +58316,66757,60538,PRETRIAL,Adderly,Terrence,NULL,Male,Other,12/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58325,66769,60549,PRETRIAL,Jimison,Scott,NULL,Male,Caucasian,08/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +58325,66769,60549,PRETRIAL,Jimison,Scott,NULL,Male,Caucasian,08/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +58325,66769,60549,PRETRIAL,Jimison,Scott,NULL,Male,Caucasian,08/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58333,66778,60558,PRETRIAL,Indik,Jarrod,NULL,Male,Caucasian,04/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/23/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +58333,66778,60558,PRETRIAL,Indik,Jarrod,NULL,Male,Caucasian,04/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/23/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +58333,66778,60558,PRETRIAL,Indik,Jarrod,NULL,Male,Caucasian,04/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58319,66762,60543,PRETRIAL,MATTHEW,BRANDON,WALKER,Male,Caucasian,07/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +58319,66762,60543,PRETRIAL,MATTHEW,BRANDON,WALKER,Male,Caucasian,07/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +58319,66762,60543,PRETRIAL,MATTHEW,BRANDON,WALKER,Male,Caucasian,07/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58338,66785,60565,Probation,Sanchez,Victor,NULL,Male,Hispanic,04/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +58338,66785,60565,Probation,Sanchez,Victor,NULL,Male,Hispanic,04/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +58338,66785,60565,Probation,Sanchez,Victor,NULL,Male,Hispanic,04/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +38968,66764,38437,PRETRIAL,Cray,Andrae,NULL,Male,African-American,03/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,Copy,1,0 +38968,66764,38437,PRETRIAL,Cray,Andrae,NULL,Male,African-American,03/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,Copy,1,0 +38968,66764,38437,PRETRIAL,Cray,Andrae,NULL,Male,African-American,03/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +7958,66783,60563,Probation,Narine,Parmanand,NULL,Male,Other,10/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/23/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +7958,66783,60563,Probation,Narine,Parmanand,NULL,Male,Other,10/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/23/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +7958,66783,60563,Probation,Narine,Parmanand,NULL,Male,Other,10/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58317,66758,60539,PRETRIAL,Miller,Robert,NULL,Male,Caucasian,06/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/23/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +58317,66758,60539,PRETRIAL,Miller,Robert,NULL,Male,Caucasian,06/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/23/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +58317,66758,60539,PRETRIAL,Miller,Robert,NULL,Male,Caucasian,06/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +15114,66760,60541,PRETRIAL,PARKER,ROBERT,NULL,Male,African-American,01/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/23/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +15114,66760,60541,PRETRIAL,PARKER,ROBERT,NULL,Male,African-American,01/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/23/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +15114,66760,60541,PRETRIAL,PARKER,ROBERT,NULL,Male,African-American,01/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58340,66787,60567,Probation,Woodrum,Ronald,NULL,Male,Caucasian,11/12/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.19,1,Low,New,1,0 +58340,66787,60567,Probation,Woodrum,Ronald,NULL,Male,Caucasian,11/12/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +58340,66787,60567,Probation,Woodrum,Ronald,NULL,Male,Caucasian,11/12/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58322,66766,60546,PRETRIAL,Aspelly,Claire,P,Female,Other,06/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +58322,66766,60546,PRETRIAL,Aspelly,Claire,P,Female,Other,06/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +58322,66766,60546,PRETRIAL,Aspelly,Claire,P,Female,Other,06/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58334,66779,60559,Probation,Lemons,Jeremy,NULL,Male,Caucasian,01/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +58334,66779,60559,Probation,Lemons,Jeremy,NULL,Male,Caucasian,01/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +58334,66779,60559,Probation,Lemons,Jeremy,NULL,Male,Caucasian,01/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58336,66781,60561,PRETRIAL,Curtis,Edward,NULL,Male,African-American,01/30/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.65,2,Low,New,1,0 +58336,66781,60561,PRETRIAL,Curtis,Edward,NULL,Male,African-American,01/30/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +58336,66781,60561,PRETRIAL,Curtis,Edward,NULL,Male,African-American,01/30/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +58329,66773,60553,Probation,Romero,Cesar,NULL,Male,Hispanic,06/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +58329,66773,60553,Probation,Romero,Cesar,NULL,Male,Hispanic,06/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +58329,66773,60553,Probation,Romero,Cesar,NULL,Male,Hispanic,06/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58330,66774,60554,Probation,CARROLL,KEVIN,PETER,Male,Caucasian,07/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +58330,66774,60554,Probation,CARROLL,KEVIN,PETER,Male,Caucasian,07/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +58330,66774,60554,Probation,CARROLL,KEVIN,PETER,Male,Caucasian,07/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +40371,66789,39976,PRETRIAL,GADSON,BRUCE,NULL,Male,African-American,02/04/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/23/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,Copy,1,0 +40371,66789,39976,PRETRIAL,GADSON,BRUCE,NULL,Male,African-American,02/04/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/23/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,Copy,1,0 +40371,66789,39976,PRETRIAL,GADSON,BRUCE,NULL,Male,African-American,02/04/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +58324,66768,60548,PRETRIAL,TRAPP,EARL,NULL,Male,Caucasian,04/23/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/23/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +58324,66768,60548,PRETRIAL,TRAPP,EARL,NULL,Male,Caucasian,04/23/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/23/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +58324,66768,60548,PRETRIAL,TRAPP,EARL,NULL,Male,Caucasian,04/23/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58332,66776,60556,Probation,HUMLICK,JOSEPH,EUGENE,Male,Caucasian,09/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +58332,66776,60556,Probation,HUMLICK,JOSEPH,EUGENE,Male,Caucasian,09/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +58332,66776,60556,Probation,HUMLICK,JOSEPH,EUGENE,Male,Caucasian,09/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58320,66763,60544,PRETRIAL,WILLIS,ROHAN,NULL,Male,African-American,10/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +58320,66763,60544,PRETRIAL,WILLIS,ROHAN,NULL,Male,African-American,10/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +58320,66763,60544,PRETRIAL,WILLIS,ROHAN,NULL,Male,African-American,10/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +58321,66765,60545,PRETRIAL,SMITH,RUEBEN,NULL,Male,African-American,07/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,7,Risk of Violence,-3.16,1,Low,New,1,0 +58321,66765,60545,PRETRIAL,SMITH,RUEBEN,NULL,Male,African-American,07/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +58321,66765,60545,PRETRIAL,SMITH,RUEBEN,NULL,Male,African-American,07/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58337,66782,60562,Probation,Inman,Melissa,NULL,Female,African-American,09/06/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +58337,66782,60562,Probation,Inman,Melissa,NULL,Female,African-American,09/06/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +58337,66782,60562,Probation,Inman,Melissa,NULL,Female,African-American,09/06/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58318,66761,60542,PRETRIAL,Seavey,Carson,Trafton,Male,Caucasian,04/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +58318,66761,60542,PRETRIAL,Seavey,Carson,Trafton,Male,Caucasian,04/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +58318,66761,60542,PRETRIAL,Seavey,Carson,Trafton,Male,Caucasian,04/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58339,66786,60566,Probation,bridges,alan,NULL,Male,Caucasian,08/30/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/23/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +58339,66786,60566,Probation,bridges,alan,NULL,Male,Caucasian,08/30/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/23/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +58339,66786,60566,Probation,bridges,alan,NULL,Male,Caucasian,08/30/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58326,66770,60550,PRETRIAL,Lizano,Oscar,A,Male,Caucasian,12/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +58326,66770,60550,PRETRIAL,Lizano,Oscar,A,Male,Caucasian,12/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +58326,66770,60550,PRETRIAL,Lizano,Oscar,A,Male,Caucasian,12/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +40189,66777,60557,PRETRIAL,JONES,STACEY,NULL,Female,African-American,05/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.79,2,Low,New,1,0 +40189,66777,60557,PRETRIAL,JONES,STACEY,NULL,Female,African-American,05/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +40189,66777,60557,PRETRIAL,JONES,STACEY,NULL,Female,African-American,05/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53411,66784,60564,PRETRIAL,Terri,Justin,NULL,Male,Caucasian,07/31/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +53411,66784,60564,PRETRIAL,Terri,Justin,NULL,Male,Caucasian,07/31/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +53411,66784,60564,PRETRIAL,Terri,Justin,NULL,Male,Caucasian,07/31/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52854,66788,60568,PRETRIAL,Molina,Mauricio,R,Male,Caucasian,01/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +52854,66788,60568,PRETRIAL,Molina,Mauricio,R,Male,Caucasian,01/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +52854,66788,60568,PRETRIAL,Molina,Mauricio,R,Male,Caucasian,01/03/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +13699,66759,60540,PRETRIAL,Hampton,Braden,NULL,Male,Caucasian,08/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +13699,66759,60540,PRETRIAL,Hampton,Braden,NULL,Male,Caucasian,08/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +13699,66759,60540,PRETRIAL,Hampton,Braden,NULL,Male,Caucasian,08/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +58328,66772,60552,Probation,Marshall,Brandon,NULL,Male,African-American,04/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,4,High,7,Risk of Violence,-0.68,9,High,New,1,0 +58328,66772,60552,Probation,Marshall,Brandon,NULL,Male,African-American,04/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,New,1,0 +58328,66772,60552,Probation,Marshall,Brandon,NULL,Male,African-American,04/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/13 0:00,4,High,18,Risk of Failure to Appear,38,10,High,New,1,0 +58331,66775,60555,PRETRIAL,Jackson,Rufus,Valantino,Male,African-American,11/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/23/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +58331,66775,60555,PRETRIAL,Jackson,Rufus,Valantino,Male,African-American,11/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/23/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +58331,66775,60555,PRETRIAL,Jackson,Rufus,Valantino,Male,African-American,11/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58335,66780,60560,PRETRIAL,CALLAHAN,EDMUND,NULL,Female,Caucasian,03/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +58335,66780,60560,PRETRIAL,CALLAHAN,EDMUND,NULL,Female,Caucasian,03/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +58335,66780,60560,PRETRIAL,CALLAHAN,EDMUND,NULL,Female,Caucasian,03/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58323,66767,60547,PRETRIAL,COLEY,STACY,NULL,Male,African-American,10/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,7,Risk of Violence,-2.76,2,Low,New,1,0 +58323,66767,60547,PRETRIAL,COLEY,STACY,NULL,Male,African-American,10/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +58323,66767,60547,PRETRIAL,COLEY,STACY,NULL,Male,African-American,10/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +58353,66801,60579,PRETRIAL,BRAWLEY,STEVEN,RAY,Male,Caucasian,09/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +58353,66801,60579,PRETRIAL,BRAWLEY,STEVEN,RAY,Male,Caucasian,09/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +58353,66801,60579,PRETRIAL,BRAWLEY,STEVEN,RAY,Male,Caucasian,09/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58366,66814,60592,PRETRIAL,Richardson,Tyrell,NULL,Male,African-American,12/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +58366,66814,60592,PRETRIAL,Richardson,Tyrell,NULL,Male,African-American,12/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +58366,66814,60592,PRETRIAL,Richardson,Tyrell,NULL,Male,African-American,12/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58346,66793,60572,PRETRIAL,Robertshudson,Amos,NULL,Male,African-American,07/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +58346,66793,60572,PRETRIAL,Robertshudson,Amos,NULL,Male,African-American,07/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +58346,66793,60572,PRETRIAL,Robertshudson,Amos,NULL,Male,African-American,07/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58374,66822,60599,PRETRIAL,Hines,Olivia,NULL,Female,African-American,09/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +58374,66822,60599,PRETRIAL,Hines,Olivia,NULL,Female,African-American,09/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +58374,66822,60599,PRETRIAL,Hines,Olivia,NULL,Female,African-American,09/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58362,66809,60587,Probation,LINDSEY,TOBE,NULL,Male,African-American,09/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +58362,66809,60587,Probation,LINDSEY,TOBE,NULL,Male,African-American,09/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +58362,66809,60587,Probation,LINDSEY,TOBE,NULL,Male,African-American,09/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58373,66824,60600,DRRD,Lopez,Isreal,Paul,Male,Hispanic,07/20/89,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/24/13 0:00,4,High,7,Risk of Violence,-0.31,10,High,New,1,0 +58373,66824,60600,DRRD,Lopez,Isreal,Paul,Male,Hispanic,07/20/89,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/24/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +58373,66824,60600,DRRD,Lopez,Isreal,Paul,Male,Hispanic,07/20/89,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/24/13 0:00,4,High,18,Risk of Failure to Appear,29,7,Medium,New,1,0 +58367,66817,60594,PRETRIAL,COSTA,ANDERSON,N,Male,Caucasian,08/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +58367,66817,60594,PRETRIAL,COSTA,ANDERSON,N,Male,Caucasian,08/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,New,1,0 +58367,66817,60594,PRETRIAL,COSTA,ANDERSON,N,Male,Caucasian,08/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58348,66796,60574,PRETRIAL,GUILLAUME,JOHN,JONERCE,Male,African-American,05/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +58348,66796,60574,PRETRIAL,GUILLAUME,JOHN,JONERCE,Male,African-American,05/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +58348,66796,60574,PRETRIAL,GUILLAUME,JOHN,JONERCE,Male,African-American,05/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58379,66830,60605,Probation,SANCHEZ,EDWIN,NULL,Male,Caucasian,10/12/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +58379,66830,60605,Probation,SANCHEZ,EDWIN,NULL,Male,Caucasian,10/12/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +58379,66830,60605,Probation,SANCHEZ,EDWIN,NULL,Male,Caucasian,10/12/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50963,66832,60607,PRETRIAL,EDWARDS,KERON,ORLANDO,Male,Other,05/18/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +50963,66832,60607,PRETRIAL,EDWARDS,KERON,ORLANDO,Male,Other,05/18/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +50963,66832,60607,PRETRIAL,EDWARDS,KERON,ORLANDO,Male,Other,05/18/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58344,66791,60570,PRETRIAL,Morgan,Jeffrey,NULL,Male,African-American,02/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +58344,66791,60570,PRETRIAL,Morgan,Jeffrey,NULL,Male,African-American,02/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +58344,66791,60570,PRETRIAL,Morgan,Jeffrey,NULL,Male,African-American,02/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58357,66805,60583,Probation,Jackson,Brion,NULL,Male,African-American,11/17/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +58357,66805,60583,Probation,Jackson,Brion,NULL,Male,African-American,11/17/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +58357,66805,60583,Probation,Jackson,Brion,NULL,Male,African-American,11/17/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58350,66798,60576,PRETRIAL,Oliva,Edwin,Anthony,Male,Caucasian,08/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +58350,66798,60576,PRETRIAL,Oliva,Edwin,Anthony,Male,Caucasian,08/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +58350,66798,60576,PRETRIAL,Oliva,Edwin,Anthony,Male,Caucasian,08/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58369,66819,60596,Probation,smith,clifford,NULL,Male,African-American,10/24/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,New,1,0 +58369,66819,60596,Probation,smith,clifford,NULL,Male,African-American,10/24/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +58369,66819,60596,Probation,smith,clifford,NULL,Male,African-American,10/24/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58375,66826,60601,Probation,Shennett,cornelius,NULL,Male,African-American,07/02/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +58375,66826,60601,Probation,Shennett,cornelius,NULL,Male,African-American,07/02/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +58375,66826,60601,Probation,Shennett,cornelius,NULL,Male,African-American,07/02/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58377,66828,60603,PRETRIAL,RAMO,LOUIS,NULL,Male,Other,01/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/24/13 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +58377,66828,60603,PRETRIAL,RAMO,LOUIS,NULL,Male,Other,01/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/24/13 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +58377,66828,60603,PRETRIAL,RAMO,LOUIS,NULL,Male,Other,01/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58352,66800,60578,PRETRIAL,Kearney,Christopher,J,Male,African-American,06/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +58352,66800,60578,PRETRIAL,Kearney,Christopher,J,Male,African-American,06/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +58352,66800,60578,PRETRIAL,Kearney,Christopher,J,Male,African-American,06/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58360,66807,60585,Probation,Edwards,Kevin,NULL,Male,Caucasian,07/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +58360,66807,60585,Probation,Edwards,Kevin,NULL,Male,Caucasian,07/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +58360,66807,60585,Probation,Edwards,Kevin,NULL,Male,Caucasian,07/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58372,66821,60598,Probation,Ramkhelawan,Charmaine,NULL,Female,Other,04/16/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +58372,66821,60598,Probation,Ramkhelawan,Charmaine,NULL,Female,Other,04/16/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +58372,66821,60598,Probation,Ramkhelawan,Charmaine,NULL,Female,Other,04/16/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52570,66816,60593,PRETRIAL,Peeples,Sharonada,Redding,Female,African-American,06/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/24/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +52570,66816,60593,PRETRIAL,Peeples,Sharonada,Redding,Female,African-American,06/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/24/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +52570,66816,60593,PRETRIAL,Peeples,Sharonada,Redding,Female,African-American,06/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58380,66833,60608,Probation,Carranza,Gilbert,NULL,Male,Hispanic,09/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +58380,66833,60608,Probation,Carranza,Gilbert,NULL,Male,Hispanic,09/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +58380,66833,60608,Probation,Carranza,Gilbert,NULL,Male,Hispanic,09/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58355,66803,60581,PRETRIAL,BROWN,NATHAN,NULL,Male,African-American,05/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +58355,66803,60581,PRETRIAL,BROWN,NATHAN,NULL,Male,African-American,05/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +58355,66803,60581,PRETRIAL,BROWN,NATHAN,NULL,Male,African-American,05/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58365,66812,60590,Probation,Cabrera,Dennis,NULL,Male,Hispanic,04/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/24/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +58365,66812,60590,Probation,Cabrera,Dennis,NULL,Male,Hispanic,04/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/24/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +58365,66812,60590,Probation,Cabrera,Dennis,NULL,Male,Hispanic,04/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58349,66797,60575,PRETRIAL,Rumph,Henry,NULL,Male,African-American,11/16/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +58349,66797,60575,PRETRIAL,Rumph,Henry,NULL,Male,African-American,11/16/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +58349,66797,60575,PRETRIAL,Rumph,Henry,NULL,Male,African-American,11/16/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +1307,66831,60606,PRETRIAL,MARROQUINPASCACIO,JUAN,NULL,Male,Hispanic,06/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +1307,66831,60606,PRETRIAL,MARROQUINPASCACIO,JUAN,NULL,Male,Hispanic,06/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +1307,66831,60606,PRETRIAL,MARROQUINPASCACIO,JUAN,NULL,Male,Hispanic,06/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58363,66810,60588,PRETRIAL,Yearby,Dustin,NULL,Male,African-American,06/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/24/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +58363,66810,60588,PRETRIAL,Yearby,Dustin,NULL,Male,African-American,06/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/24/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +58363,66810,60588,PRETRIAL,Yearby,Dustin,NULL,Male,African-American,06/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58368,66818,60595,Probation,Morlaperez,Leonel,NULL,Male,Hispanic,06/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +58368,66818,60595,Probation,Morlaperez,Leonel,NULL,Male,Hispanic,06/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +58368,66818,60595,Probation,Morlaperez,Leonel,NULL,Male,Hispanic,06/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57329,66823,59426,Probation,Lymon,Marquis,NULL,Male,African-American,09/21/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +57329,66823,59426,Probation,Lymon,Marquis,NULL,Male,African-American,09/21/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,2,Medium,8,Risk of Recidivism,0.18,7,Medium,New,1,0 +57329,66823,59426,Probation,Lymon,Marquis,NULL,Male,African-American,09/21/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,2,Medium,18,Risk of Failure to Appear,23,4,Low,New,1,0 +58347,66795,60573,PRETRIAL,Garcon,Jonas,NULL,Male,African-American,10/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +58347,66795,60573,PRETRIAL,Garcon,Jonas,NULL,Male,African-American,10/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +58347,66795,60573,PRETRIAL,Garcon,Jonas,NULL,Male,African-American,10/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58354,66802,60580,PRETRIAL,Eggers,Edward,H,Male,Caucasian,05/01/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +58354,66802,60580,PRETRIAL,Eggers,Edward,H,Male,Caucasian,05/01/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +58354,66802,60580,PRETRIAL,Eggers,Edward,H,Male,Caucasian,05/01/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +30000,66815,28972,PRETRIAL,Binion,Tommy,NULL,Male,African-American,07/23/68,17,All Scales,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,Copy,1,0 +30000,66815,28972,PRETRIAL,Binion,Tommy,NULL,Male,African-American,07/23/68,17,All Scales,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,Copy,1,0 +30000,66815,28972,PRETRIAL,Binion,Tommy,NULL,Male,African-American,07/23/68,17,All Scales,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +54690,66794,56390,PRETRIAL,DAVIS,ANTWAN,NULL,Male,Caucasian,03/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,4,High,7,Risk of Violence,-0.61,10,High,New,1,0 +54690,66794,56390,PRETRIAL,DAVIS,ANTWAN,NULL,Male,Caucasian,03/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,4,High,8,Risk of Recidivism,0.38,9,High,New,1,0 +54690,66794,56390,PRETRIAL,DAVIS,ANTWAN,NULL,Male,Caucasian,03/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58345,66792,60571,PRETRIAL,Edwards,Torrone,NULL,Male,African-American,08/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +58345,66792,60571,PRETRIAL,Edwards,Torrone,NULL,Male,African-American,08/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +58345,66792,60571,PRETRIAL,Edwards,Torrone,NULL,Male,African-American,08/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58358,66806,60584,Probation,simmons,edward,NULL,Male,African-American,07/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +58358,66806,60584,Probation,simmons,edward,NULL,Male,African-American,07/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +58358,66806,60584,Probation,simmons,edward,NULL,Male,African-American,07/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58370,66820,60597,PRETRIAL,bynum,nicholas,NULL,Male,African-American,05/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +58370,66820,60597,PRETRIAL,bynum,nicholas,NULL,Male,African-American,05/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +58370,66820,60597,PRETRIAL,bynum,nicholas,NULL,Male,African-American,05/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58376,66827,60602,Probation,tran,bihn,NULL,Male,Other,07/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +58376,66827,60602,Probation,tran,bihn,NULL,Male,Other,07/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +58376,66827,60602,Probation,tran,bihn,NULL,Male,Other,07/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58382,66834,60609,PRETRIAL,Taddeo,John,NULL,Male,Caucasian,12/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +58382,66834,60609,PRETRIAL,Taddeo,John,NULL,Male,Caucasian,12/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +58382,66834,60609,PRETRIAL,Taddeo,John,NULL,Male,Caucasian,12/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58351,66799,60577,PRETRIAL,Campbell,Richard,NULL,Male,African-American,10/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +58351,66799,60577,PRETRIAL,Campbell,Richard,NULL,Male,African-American,10/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +58351,66799,60577,PRETRIAL,Campbell,Richard,NULL,Male,African-American,10/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58378,66829,60604,Probation,Diazgonzalez,Rafael,NULL,Male,Hispanic,11/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/24/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +58378,66829,60604,Probation,Diazgonzalez,Rafael,NULL,Male,Hispanic,11/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/24/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +58378,66829,60604,Probation,Diazgonzalez,Rafael,NULL,Male,Hispanic,11/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58343,66790,60569,PRETRIAL,Butler,Ira,NULL,Male,African-American,09/20/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,7,Risk of Violence,-4.19,1,Low,New,1,0 +58343,66790,60569,PRETRIAL,Butler,Ira,NULL,Male,African-American,09/20/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +58343,66790,60569,PRETRIAL,Butler,Ira,NULL,Male,African-American,09/20/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58356,66804,60582,PRETRIAL,Jean,Kenold,NULL,Male,Other,08/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +58356,66804,60582,PRETRIAL,Jean,Kenold,NULL,Male,Other,08/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +58356,66804,60582,PRETRIAL,Jean,Kenold,NULL,Male,Other,08/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58361,66808,60586,Probation,Quick,Kara,NULL,Female,Caucasian,09/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.57,2,Low,New,1,0 +58361,66808,60586,Probation,Quick,Kara,NULL,Female,Caucasian,09/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,8,High,New,1,0 +58361,66808,60586,Probation,Quick,Kara,NULL,Female,Caucasian,09/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +58364,66811,60589,PRETRIAL,Tommie,Kenneth,NULL,Male,Other,01/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +58364,66811,60589,PRETRIAL,Tommie,Kenneth,NULL,Male,Other,01/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +58364,66811,60589,PRETRIAL,Tommie,Kenneth,NULL,Male,Other,01/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/24/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +38097,66825,37513,PRETRIAL,Smith,Lucius,Bernard,Male,African-American,11/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/24/13 0:00,4,High,7,Risk of Violence,-1.04,8,High,Copy,1,0 +38097,66825,37513,PRETRIAL,Smith,Lucius,Bernard,Male,African-American,11/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/24/13 0:00,4,High,8,Risk of Recidivism,0.84,10,High,Copy,1,0 +38097,66825,37513,PRETRIAL,Smith,Lucius,Bernard,Male,African-American,11/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/24/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +58393,66850,60622,Probation,kenrick,Ridge,NULL,Male,African-American,01/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/25/13 0:00,4,High,7,Risk of Violence,-1.03,8,High,New,1,0 +58393,66850,60622,Probation,kenrick,Ridge,NULL,Male,African-American,01/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/25/13 0:00,4,High,8,Risk of Recidivism,1.56,10,High,New,1,0 +58393,66850,60622,Probation,kenrick,Ridge,NULL,Male,African-American,01/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/25/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58403,66871,60639,PRETRIAL,PARRISH,VALENTINA,NULL,Female,Caucasian,01/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +58403,66871,60639,PRETRIAL,PARRISH,VALENTINA,NULL,Female,Caucasian,01/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,10,High,New,1,0 +58403,66871,60639,PRETRIAL,PARRISH,VALENTINA,NULL,Female,Caucasian,01/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58390,66846,60618,PRETRIAL,King,Rodney,Leon,Male,African-American,10/13/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/25/13 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +58390,66846,60618,PRETRIAL,King,Rodney,Leon,Male,African-American,10/13/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/25/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +58390,66846,60618,PRETRIAL,King,Rodney,Leon,Male,African-American,10/13/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58401,66867,60636,PRETRIAL,Chapin,Constance,NULL,Female,Caucasian,12/13/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +58401,66867,60636,PRETRIAL,Chapin,Constance,NULL,Female,Caucasian,12/13/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +58401,66867,60636,PRETRIAL,Chapin,Constance,NULL,Female,Caucasian,12/13/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58407,66876,60642,PRETRIAL,Anderson,Geoffrey,NULL,Male,Caucasian,08/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +58407,66876,60642,PRETRIAL,Anderson,Geoffrey,NULL,Male,Caucasian,08/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +58407,66876,60642,PRETRIAL,Anderson,Geoffrey,NULL,Male,Caucasian,08/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58386,66841,60614,PRETRIAL,Owen,Shamar,Lloyd,Male,African-American,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +58386,66841,60614,PRETRIAL,Owen,Shamar,Lloyd,Male,African-American,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +58386,66841,60614,PRETRIAL,Owen,Shamar,Lloyd,Male,African-American,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +21450,66855,60626,Probation,butler,christopher,NULL,Male,African-American,08/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +21450,66855,60626,Probation,butler,christopher,NULL,Male,African-American,08/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +21450,66855,60626,Probation,butler,christopher,NULL,Male,African-American,08/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58399,66862,60631,Probation,Hill,Nimroy,NULL,Male,African-American,08/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/25/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +58399,66862,60631,Probation,Hill,Nimroy,NULL,Male,African-American,08/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/25/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +58399,66862,60631,Probation,Hill,Nimroy,NULL,Male,African-American,08/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58400,66864,60633,Probation,Hudson,Jason,NULL,Male,Caucasian,12/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +58400,66864,60633,Probation,Hudson,Jason,NULL,Male,Caucasian,12/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +58400,66864,60633,Probation,Hudson,Jason,NULL,Male,Caucasian,12/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58397,66860,60629,PRETRIAL,Smith,Ty-Shawn,NULL,Male,African-American,12/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +58397,66860,60629,PRETRIAL,Smith,Ty-Shawn,NULL,Male,African-American,12/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +58397,66860,60629,PRETRIAL,Smith,Ty-Shawn,NULL,Male,African-American,12/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58394,66852,60623,Probation,Dutke,Jean-Pierre,NULL,Male,Caucasian,03/03/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/25/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +58394,66852,60623,Probation,Dutke,Jean-Pierre,NULL,Male,Caucasian,03/03/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/25/13 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +58394,66852,60623,Probation,Dutke,Jean-Pierre,NULL,Male,Caucasian,03/03/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58383,66836,60610,PRETRIAL,Rodriguez,Nathaniel,NULL,Male,Caucasian,06/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +58383,66836,60610,PRETRIAL,Rodriguez,Nathaniel,NULL,Male,Caucasian,06/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +58383,66836,60610,PRETRIAL,Rodriguez,Nathaniel,NULL,Male,Caucasian,06/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58384,66839,60612,PRETRIAL,Santamaria,Shannon,Mae,Female,Caucasian,10/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +58384,66839,60612,PRETRIAL,Santamaria,Shannon,Mae,Female,Caucasian,10/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +58384,66839,60612,PRETRIAL,Santamaria,Shannon,Mae,Female,Caucasian,10/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51670,66857,52874,PRETRIAL,Salnave,Fidel,NULL,Male,Caucasian,07/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,Copy,1,0 +51670,66857,52874,PRETRIAL,Salnave,Fidel,NULL,Male,Caucasian,07/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,Copy,1,0 +51670,66857,52874,PRETRIAL,Salnave,Fidel,NULL,Male,Caucasian,07/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +58389,66844,60617,PRETRIAL,Stanley,Steve,NULL,Male,Caucasian,03/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/25/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +58389,66844,60617,PRETRIAL,Stanley,Steve,NULL,Male,Caucasian,03/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/25/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +58389,66844,60617,PRETRIAL,Stanley,Steve,NULL,Male,Caucasian,03/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +11711,66837,11215,PRETRIAL,Joseph,Jean,NULL,Male,Other,02/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,Copy,1,0 +11711,66837,11215,PRETRIAL,Joseph,Jean,NULL,Male,Other,02/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,Copy,1,0 +11711,66837,11215,PRETRIAL,Joseph,Jean,NULL,Male,Other,02/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +58387,66842,60615,PRETRIAL,Infante,Alfred,NULL,Male,African-American,12/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +58387,66842,60615,PRETRIAL,Infante,Alfred,NULL,Male,African-American,12/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +58387,66842,60615,PRETRIAL,Infante,Alfred,NULL,Male,African-American,12/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58402,66868,60637,PRETRIAL,Campbell,Kwatavis,NULL,Male,African-American,04/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +58402,66868,60637,PRETRIAL,Campbell,Kwatavis,NULL,Male,African-American,04/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +58402,66868,60637,PRETRIAL,Campbell,Kwatavis,NULL,Male,African-American,04/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45869,50699,46202,PRETRIAL,Weaver,Darryl,NULL,Male,African-American,11/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +45869,50699,46202,PRETRIAL,Weaver,Darryl,NULL,Male,African-American,11/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,4,High,8,Risk of Recidivism,0.76,10,High,New,1,0 +45869,50699,46202,PRETRIAL,Weaver,Darryl,NULL,Male,African-American,11/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58391,66847,60619,PRETRIAL,FRANCOIS,WIDNER,NULL,Male,African-American,11/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +58391,66847,60619,PRETRIAL,FRANCOIS,WIDNER,NULL,Male,African-American,11/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +58391,66847,60619,PRETRIAL,FRANCOIS,WIDNER,NULL,Male,African-American,11/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +30529,66849,60621,PRETRIAL,Bartlett,Roper,NULL,Male,Caucasian,06/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +30529,66849,60621,PRETRIAL,Bartlett,Roper,NULL,Male,Caucasian,06/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +30529,66849,60621,PRETRIAL,Bartlett,Roper,NULL,Male,Caucasian,06/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +58395,66856,60627,Probation,Galarza,Luis,NULL,Male,Hispanic,03/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +58395,66856,60627,Probation,Galarza,Luis,NULL,Male,Hispanic,03/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +58395,66856,60627,Probation,Galarza,Luis,NULL,Male,Hispanic,03/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +2105,66870,60638,PRETRIAL,Rodriguez,Alexander,M,Male,Caucasian,03/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +2105,66870,60638,PRETRIAL,Rodriguez,Alexander,M,Male,Caucasian,03/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +2105,66870,60638,PRETRIAL,Rodriguez,Alexander,M,Male,Caucasian,03/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58408,66877,60643,PRETRIAL,Castaneda,Ronald,NULL,Male,Hispanic,05/31/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/25/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +58408,66877,60643,PRETRIAL,Castaneda,Ronald,NULL,Male,Hispanic,05/31/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/25/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +58408,66877,60643,PRETRIAL,Castaneda,Ronald,NULL,Male,Hispanic,05/31/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57621,66866,60635,Probation,Crespo,Ayinde,NULL,Male,African-American,07/23/80,17,All Scales,Intake,English,Pretrial,Probation,Single,10/25/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +57621,66866,60635,Probation,Crespo,Ayinde,NULL,Male,African-American,07/23/80,17,All Scales,Intake,English,Pretrial,Probation,Single,10/25/13 0:00,1,Low,8,Risk of Recidivism,-0.26,5,Medium,New,1,0 +57621,66866,60635,Probation,Crespo,Ayinde,NULL,Male,African-American,07/23/80,17,All Scales,Intake,English,Pretrial,Probation,Single,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,35,9,High,New,1,0 +56621,66851,58640,Probation,DUBOIS,RICHARD,NULL,Male,Caucasian,08/14/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/25/13 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +56621,66851,58640,Probation,DUBOIS,RICHARD,NULL,Male,Caucasian,08/14/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,6,Medium,New,1,0 +56621,66851,58640,Probation,DUBOIS,RICHARD,NULL,Male,Caucasian,08/14/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/25/13 0:00,2,Medium,18,Risk of Failure to Appear,16,1,Low,New,1,0 +57659,66853,60624,Probation,doctor,patrick,NULL,Male,Native American,01/17/78,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +57659,66853,60624,Probation,doctor,patrick,NULL,Male,Native American,01/17/78,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.77,10,High,New,1,0 +57659,66853,60624,Probation,doctor,patrick,NULL,Male,Native American,01/17/78,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +42015,66838,60611,PRETRIAL,ALEXIS,WARDSON,NULL,Male,African-American,04/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +42015,66838,60611,PRETRIAL,ALEXIS,WARDSON,NULL,Male,African-American,04/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.76,10,High,New,1,0 +42015,66838,60611,PRETRIAL,ALEXIS,WARDSON,NULL,Male,African-American,04/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +20380,66874,57954,PRETRIAL,Libson,Joseph,Denard,Male,African-American,11/30/79,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,New,1,0 +20380,66874,57954,PRETRIAL,Libson,Joseph,Denard,Male,African-American,11/30/79,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,8,High,New,1,0 +20380,66874,57954,PRETRIAL,Libson,Joseph,Denard,Male,African-American,11/30/79,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +52569,66845,53897,PRETRIAL,Lewis,Darryl,NULL,Male,African-American,08/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,Copy,1,0 +52569,66845,53897,PRETRIAL,Lewis,Darryl,NULL,Male,African-American,08/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,Copy,1,0 +52569,66845,53897,PRETRIAL,Lewis,Darryl,NULL,Male,African-American,08/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/25/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +48838,66859,49586,PRETRIAL,Grant,Nadia,NULL,Female,African-American,02/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/25/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,Copy,1,0 +48838,66859,49586,PRETRIAL,Grant,Nadia,NULL,Female,African-American,02/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/25/13 0:00,1,Low,8,Risk of Recidivism,-0.6,5,Medium,Copy,1,0 +48838,66859,49586,PRETRIAL,Grant,Nadia,NULL,Female,African-American,02/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +58385,66840,60613,PRETRIAL,Burgess,Justin,P,Male,African-American,09/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +58385,66840,60613,PRETRIAL,Burgess,Justin,P,Male,African-American,09/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +58385,66840,60613,PRETRIAL,Burgess,Justin,P,Male,African-American,09/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58388,66843,60616,PRETRIAL,Cooper,Martez,keith,Male,African-American,05/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +58388,66843,60616,PRETRIAL,Cooper,Martez,keith,Male,African-American,05/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +58388,66843,60616,PRETRIAL,Cooper,Martez,keith,Male,African-American,05/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58398,66861,60630,Probation,PHILLIPS,SHERMANDA,NULL,Female,African-American,09/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +58398,66861,60630,Probation,PHILLIPS,SHERMANDA,NULL,Female,African-American,09/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +58398,66861,60630,Probation,PHILLIPS,SHERMANDA,NULL,Female,African-American,09/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58392,66848,60620,Probation,Chmielewski,Lisa,NULL,Female,Caucasian,03/20/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +58392,66848,60620,Probation,Chmielewski,Lisa,NULL,Female,Caucasian,03/20/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +58392,66848,60620,Probation,Chmielewski,Lisa,NULL,Female,Caucasian,03/20/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/25/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +19512,66835,18747,PRETRIAL,Prosper,Victor,NULL,Male,African-American,07/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,Copy,1,0 +19512,66835,18747,PRETRIAL,Prosper,Victor,NULL,Male,African-American,07/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,Copy,1,0 +19512,66835,18747,PRETRIAL,Prosper,Victor,NULL,Male,African-American,07/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +58411,66882,60647,PRETRIAL,Clark,Nicholas,James,Male,Caucasian,09/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/13 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +58411,66882,60647,PRETRIAL,Clark,Nicholas,James,Male,Caucasian,09/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +58411,66882,60647,PRETRIAL,Clark,Nicholas,James,Male,Caucasian,09/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58413,66884,60649,PRETRIAL,NIEVES,VICTOR,NULL,Male,Hispanic,11/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/26/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +58413,66884,60649,PRETRIAL,NIEVES,VICTOR,NULL,Male,Hispanic,11/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/26/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +58413,66884,60649,PRETRIAL,NIEVES,VICTOR,NULL,Male,Hispanic,11/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58409,66879,60645,PRETRIAL,Battiste,Ruth,NULL,Female,African-American,01/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +58409,66879,60645,PRETRIAL,Battiste,Ruth,NULL,Female,African-American,01/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +58409,66879,60645,PRETRIAL,Battiste,Ruth,NULL,Female,African-American,01/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50780,66878,60644,PRETRIAL,Taylor,Lisa,D,Female,Caucasian,07/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.74,2,Low,New,1,0 +50780,66878,60644,PRETRIAL,Taylor,Lisa,D,Female,Caucasian,07/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,New,1,0 +50780,66878,60644,PRETRIAL,Taylor,Lisa,D,Female,Caucasian,07/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58410,66881,60646,PRETRIAL,Lizcano,Zulimay,NULL,Female,Caucasian,02/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/26/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +58410,66881,60646,PRETRIAL,Lizcano,Zulimay,NULL,Female,Caucasian,02/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/26/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +58410,66881,60646,PRETRIAL,Lizcano,Zulimay,NULL,Female,Caucasian,02/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/26/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58412,66883,60648,PRETRIAL,Gayle,Sean,Michael,Male,Caucasian,04/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +58412,66883,60648,PRETRIAL,Gayle,Sean,Michael,Male,Caucasian,04/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +58412,66883,60648,PRETRIAL,Gayle,Sean,Michael,Male,Caucasian,04/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +16861,66880,59136,PRETRIAL,Jones,Elton,A,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/26/13 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,Copy,1,0 +16861,66880,59136,PRETRIAL,Jones,Elton,A,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,Copy,1,0 +16861,66880,59136,PRETRIAL,Jones,Elton,A,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/26/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +58414,66885,60650,PRETRIAL,Etienne,Addlin,NULL,Male,African-American,09/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +58414,66885,60650,PRETRIAL,Etienne,Addlin,NULL,Male,African-American,09/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +58414,66885,60650,PRETRIAL,Etienne,Addlin,NULL,Male,African-American,09/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58420,66892,60656,PRETRIAL,Fernandez,Luis,NULL,Male,Hispanic,09/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/27/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +58420,66892,60656,PRETRIAL,Fernandez,Luis,NULL,Male,Hispanic,09/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/27/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +58420,66892,60656,PRETRIAL,Fernandez,Luis,NULL,Male,Hispanic,09/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58425,66894,60658,PRETRIAL,campo,carlos,NULL,Male,Hispanic,12/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +58425,66894,60658,PRETRIAL,campo,carlos,NULL,Male,Hispanic,12/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +58425,66894,60658,PRETRIAL,campo,carlos,NULL,Male,Hispanic,12/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58417,66888,60653,PRETRIAL,LANDSGARD,CHRISTOPHER,LEE,Male,Caucasian,10/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +58417,66888,60653,PRETRIAL,LANDSGARD,CHRISTOPHER,LEE,Male,Caucasian,10/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +58417,66888,60653,PRETRIAL,LANDSGARD,CHRISTOPHER,LEE,Male,Caucasian,10/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58415,66886,60651,PRETRIAL,AVILES,SAMIA,NULL,Female,Caucasian,03/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +58415,66886,60651,PRETRIAL,AVILES,SAMIA,NULL,Female,Caucasian,03/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +58415,66886,60651,PRETRIAL,AVILES,SAMIA,NULL,Female,Caucasian,03/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58424,66893,60657,PRETRIAL,Fernandez,Michael,Anthony,Male,Hispanic,11/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +58424,66893,60657,PRETRIAL,Fernandez,Michael,Anthony,Male,Hispanic,11/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +58424,66893,60657,PRETRIAL,Fernandez,Michael,Anthony,Male,Hispanic,11/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58418,66889,60654,PRETRIAL,Penaloza,Ebrain,NULL,Male,Hispanic,01/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +58418,66889,60654,PRETRIAL,Penaloza,Ebrain,NULL,Male,Hispanic,01/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +58418,66889,60654,PRETRIAL,Penaloza,Ebrain,NULL,Male,Hispanic,01/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50808,66891,51908,PRETRIAL,James,Tawanna,NULL,Female,African-American,09/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,Copy,1,0 +50808,66891,51908,PRETRIAL,James,Tawanna,NULL,Female,African-American,09/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,Copy,1,0 +50808,66891,51908,PRETRIAL,James,Tawanna,NULL,Female,African-American,09/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +58419,66890,60655,PRETRIAL,KING,STEVEN,OMAR,Male,African-American,12/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +58419,66890,60655,PRETRIAL,KING,STEVEN,OMAR,Male,African-American,12/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +58419,66890,60655,PRETRIAL,KING,STEVEN,OMAR,Male,African-American,12/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58416,66887,60652,PRETRIAL,ANGLIN,CHAQUIAY,MARCIA,Female,African-American,09/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +58416,66887,60652,PRETRIAL,ANGLIN,CHAQUIAY,MARCIA,Female,African-American,09/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +58416,66887,60652,PRETRIAL,ANGLIN,CHAQUIAY,MARCIA,Female,African-American,09/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58426,66895,60659,PRETRIAL,Almansour,Thamer,Nasser,Male,Caucasian,03/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/28/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +58426,66895,60659,PRETRIAL,Almansour,Thamer,Nasser,Male,Caucasian,03/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +58426,66895,60659,PRETRIAL,Almansour,Thamer,Nasser,Male,Caucasian,03/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58465,66924,60687,Probation,MYERS,LESSIE,A,Female,African-American,08/05/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +58465,66924,60687,Probation,MYERS,LESSIE,A,Female,African-American,08/05/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +58465,66924,60687,Probation,MYERS,LESSIE,A,Female,African-American,08/05/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58442,66908,60672,Probation,mckeehan,steven,NULL,Male,Caucasian,10/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +58442,66908,60672,Probation,mckeehan,steven,NULL,Male,Caucasian,10/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +58442,66908,60672,Probation,mckeehan,steven,NULL,Male,Caucasian,10/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58464,66921,60685,PRETRIAL,Pantaleon,Carlos,NULL,Male,Hispanic,06/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/28/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +58464,66921,60685,PRETRIAL,Pantaleon,Carlos,NULL,Male,Hispanic,06/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/28/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +58464,66921,60685,PRETRIAL,Pantaleon,Carlos,NULL,Male,Hispanic,06/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58454,66911,60675,Probation,McKenley,Shanique,NULL,Female,African-American,10/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +58454,66911,60675,Probation,McKenley,Shanique,NULL,Female,African-American,10/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +58454,66911,60675,Probation,McKenley,Shanique,NULL,Female,African-American,10/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58468,66929,60691,Probation,VIERA,AILEEN,NULL,Female,Hispanic,10/07/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +58468,66929,60691,Probation,VIERA,AILEEN,NULL,Female,Hispanic,10/07/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +58468,66929,60691,Probation,VIERA,AILEEN,NULL,Female,Hispanic,10/07/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58437,66903,60667,PRETRIAL,Quinones,Victor,NULL,Male,Hispanic,09/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/28/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +58437,66903,60667,PRETRIAL,Quinones,Victor,NULL,Male,Hispanic,09/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/28/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +58437,66903,60667,PRETRIAL,Quinones,Victor,NULL,Male,Hispanic,09/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58439,66905,60669,PRETRIAL,heron,nathaniel,NULL,Male,African-American,08/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +58439,66905,60669,PRETRIAL,heron,nathaniel,NULL,Male,African-American,08/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +58439,66905,60669,PRETRIAL,heron,nathaniel,NULL,Male,African-American,08/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58429,66898,60662,PRETRIAL,GONZALEZ,MICHELLE,NULL,Female,Caucasian,07/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +58429,66898,60662,PRETRIAL,GONZALEZ,MICHELLE,NULL,Female,Caucasian,07/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +58429,66898,60662,PRETRIAL,GONZALEZ,MICHELLE,NULL,Female,Caucasian,07/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58434,66900,60664,PRETRIAL,MARSH,BENJAMIN,NELSON,Male,African-American,01/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +58434,66900,60664,PRETRIAL,MARSH,BENJAMIN,NELSON,Male,African-American,01/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +58434,66900,60664,PRETRIAL,MARSH,BENJAMIN,NELSON,Male,African-American,01/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58462,66919,60683,Probation,watson,jarkee,NULL,Male,African-American,08/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +58462,66919,60683,Probation,watson,jarkee,NULL,Male,African-American,08/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +58462,66919,60683,Probation,watson,jarkee,NULL,Male,African-American,08/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +42900,66926,60688,PRETRIAL,JOHNSON,AKIRI,RASHAD,Male,African-American,01/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +42900,66926,60688,PRETRIAL,JOHNSON,AKIRI,RASHAD,Male,African-American,01/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +42900,66926,60688,PRETRIAL,JOHNSON,AKIRI,RASHAD,Male,African-American,01/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58467,66928,60690,Probation,carlos,danny,NULL,Male,Hispanic,11/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +58467,66928,60690,Probation,carlos,danny,NULL,Male,Hispanic,11/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +58467,66928,60690,Probation,carlos,danny,NULL,Male,Hispanic,11/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58444,66910,60674,PRETRIAL,Castillo,Kenny,NULL,Male,Hispanic,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +58444,66910,60674,PRETRIAL,Castillo,Kenny,NULL,Male,Hispanic,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +58444,66910,60674,PRETRIAL,Castillo,Kenny,NULL,Male,Hispanic,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58457,66914,60678,Probation,Zayas,Caz,NULL,Male,Hispanic,09/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +58457,66914,60678,Probation,Zayas,Caz,NULL,Male,Hispanic,09/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +58457,66914,60678,Probation,Zayas,Caz,NULL,Male,Hispanic,09/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58470,66931,60693,Probation,burton,jimmesha,NULL,Female,African-American,06/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +58470,66931,60693,Probation,burton,jimmesha,NULL,Female,African-American,06/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,New,1,0 +58470,66931,60693,Probation,burton,jimmesha,NULL,Female,African-American,06/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58441,66907,60671,PRETRIAL,SMITH,JENNIFER,NULL,Female,Caucasian,12/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +58441,66907,60671,PRETRIAL,SMITH,JENNIFER,NULL,Female,Caucasian,12/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +58441,66907,60671,PRETRIAL,SMITH,JENNIFER,NULL,Female,Caucasian,12/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +48523,66925,49219,PRETRIAL,Timothee,Fred,Junior,Male,African-American,09/29/93,17,All Scales,Intake,English,Post Sentence,Probation,Married,10/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +48523,66925,49219,PRETRIAL,Timothee,Fred,Junior,Male,African-American,09/29/93,17,All Scales,Intake,English,Post Sentence,Probation,Married,10/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,8,High,New,1,0 +48523,66925,49219,PRETRIAL,Timothee,Fred,Junior,Male,African-American,09/29/93,17,All Scales,Intake,English,Post Sentence,Probation,Married,10/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58455,66912,60676,PRETRIAL,FIGUEROA,TONY,NULL,Male,Hispanic,08/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +58455,66912,60676,PRETRIAL,FIGUEROA,TONY,NULL,Male,Hispanic,08/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +58455,66912,60676,PRETRIAL,FIGUEROA,TONY,NULL,Male,Hispanic,08/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58430,66899,60663,PRETRIAL,LAMBERT,RAY,GARNET,Male,African-American,09/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +58430,66899,60663,PRETRIAL,LAMBERT,RAY,GARNET,Male,African-American,09/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +58430,66899,60663,PRETRIAL,LAMBERT,RAY,GARNET,Male,African-American,09/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +44245,66923,60686,PRETRIAL,Hung,Andres,NULL,Male,Hispanic,06/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +44245,66923,60686,PRETRIAL,Hung,Andres,NULL,Male,Hispanic,06/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +44245,66923,60686,PRETRIAL,Hung,Andres,NULL,Male,Hispanic,06/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58436,66902,60666,PRETRIAL,BATES,JUSTIN,NULL,Male,African-American,01/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +58436,66902,60666,PRETRIAL,BATES,JUSTIN,NULL,Male,African-American,01/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +58436,66902,60666,PRETRIAL,BATES,JUSTIN,NULL,Male,African-American,01/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58443,66909,60673,Probation,Flanders,Sammie,NULL,Male,African-American,05/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,New,1,0 +58443,66909,60673,Probation,Flanders,Sammie,NULL,Male,African-American,05/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +58443,66909,60673,Probation,Flanders,Sammie,NULL,Male,African-American,05/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58460,66917,60681,Probation,Johnson,Yasmin,NULL,Female,African-American,05/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/28/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +58460,66917,60681,Probation,Johnson,Yasmin,NULL,Female,African-American,05/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +58460,66917,60681,Probation,Johnson,Yasmin,NULL,Female,African-American,05/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58427,66896,60660,PRETRIAL,RAPHAEL,RAUL,LEON,Male,Caucasian,04/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/28/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +58427,66896,60660,PRETRIAL,RAPHAEL,RAUL,LEON,Male,Caucasian,04/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +58427,66896,60660,PRETRIAL,RAPHAEL,RAUL,LEON,Male,Caucasian,04/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58458,66915,60679,Probation,Sobrino-Sanchez,Victoria,NULL,Female,Hispanic,03/22/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +58458,66915,60679,Probation,Sobrino-Sanchez,Victoria,NULL,Female,Hispanic,03/22/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +58458,66915,60679,Probation,Sobrino-Sanchez,Victoria,NULL,Female,Hispanic,03/22/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58469,66930,60692,Probation,Pryor,Tiara,NULL,Female,African-American,11/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,2,Medium,7,Risk of Violence,-2.94,2,Low,New,1,0 +58469,66930,60692,Probation,Pryor,Tiara,NULL,Female,African-American,11/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +58469,66930,60692,Probation,Pryor,Tiara,NULL,Female,African-American,11/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58456,66913,60677,Probation,rojas,ingrid,NULL,Female,Hispanic,10/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +58456,66913,60677,Probation,rojas,ingrid,NULL,Female,Hispanic,10/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +58456,66913,60677,Probation,rojas,ingrid,NULL,Female,Hispanic,10/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58440,66906,60670,Probation,Gonzalez,Stephanie,NULL,Female,Hispanic,11/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +58440,66906,60670,Probation,Gonzalez,Stephanie,NULL,Female,Hispanic,11/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +58440,66906,60670,Probation,Gonzalez,Stephanie,NULL,Female,Hispanic,11/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58463,66920,60684,Probation,Cameron,Alci,NULL,Male,Caucasian,10/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +58463,66920,60684,Probation,Cameron,Alci,NULL,Male,Caucasian,10/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +58463,66920,60684,Probation,Cameron,Alci,NULL,Male,Caucasian,10/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58466,66927,60689,Probation,Brown,John,NULL,Male,African-American,12/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +58466,66927,60689,Probation,Brown,John,NULL,Male,African-American,12/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +58466,66927,60689,Probation,Brown,John,NULL,Male,African-American,12/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58428,66897,60661,PRETRIAL,FLEURIMOND,JUDY,NULL,Female,African-American,03/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/28/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +58428,66897,60661,PRETRIAL,FLEURIMOND,JUDY,NULL,Female,African-American,03/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +58428,66897,60661,PRETRIAL,FLEURIMOND,JUDY,NULL,Female,African-American,03/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58435,66901,60665,PRETRIAL,FRANCHINO,NICHOLAS,NULL,Male,Caucasian,11/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/28/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +58435,66901,60665,PRETRIAL,FRANCHINO,NICHOLAS,NULL,Male,Caucasian,11/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/28/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +58435,66901,60665,PRETRIAL,FRANCHINO,NICHOLAS,NULL,Male,Caucasian,11/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +33063,66922,32143,PRETRIAL,StLouis,Eugene,NULL,Male,Other,06/23/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.86,9,High,New,1,0 +33063,66922,32143,PRETRIAL,StLouis,Eugene,NULL,Male,Other,06/23/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,7,Medium,New,1,0 +33063,66922,32143,PRETRIAL,StLouis,Eugene,NULL,Male,Other,06/23/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58461,66918,60682,Probation,frybergh,phillip,NULL,Female,Caucasian,11/13/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +58461,66918,60682,Probation,frybergh,phillip,NULL,Female,Caucasian,11/13/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/13 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +58461,66918,60682,Probation,frybergh,phillip,NULL,Female,Caucasian,11/13/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58474,66936,60698,PRETRIAL,DAVID,ANDREW,WISDOM,Male,African-American,10/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/29/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +58474,66936,60698,PRETRIAL,DAVID,ANDREW,WISDOM,Male,African-American,10/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/29/13 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +58474,66936,60698,PRETRIAL,DAVID,ANDREW,WISDOM,Male,African-American,10/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +33932,66943,60705,PRETRIAL,YOUNG,CHERYL,NULL,Female,African-American,03/05/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/29/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +33932,66943,60705,PRETRIAL,YOUNG,CHERYL,NULL,Female,African-American,03/05/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/29/13 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +33932,66943,60705,PRETRIAL,YOUNG,CHERYL,NULL,Female,African-American,03/05/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58477,66939,60701,PRETRIAL,Hemingway,Nashavia,Sharde,Female,African-American,11/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +58477,66939,60701,PRETRIAL,Hemingway,Nashavia,Sharde,Female,African-American,11/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +58477,66939,60701,PRETRIAL,Hemingway,Nashavia,Sharde,Female,African-American,11/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58496,66957,60714,Probation,Gil,Shanna,NULL,Female,Caucasian,06/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/29/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +58496,66957,60714,Probation,Gil,Shanna,NULL,Female,Caucasian,06/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +58496,66957,60714,Probation,Gil,Shanna,NULL,Female,Caucasian,06/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58507,66969,60724,Probation,Campos,Cicero,NULL,Male,Hispanic,06/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +58507,66969,60724,Probation,Campos,Cicero,NULL,Male,Hispanic,06/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +58507,66969,60724,Probation,Campos,Cicero,NULL,Male,Hispanic,06/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +18326,66978,60732,PRETRIAL,SILVERA,DAVION,NULL,Male,African-American,06/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +18326,66978,60732,PRETRIAL,SILVERA,DAVION,NULL,Male,African-American,06/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +18326,66978,60732,PRETRIAL,SILVERA,DAVION,NULL,Male,African-American,06/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58492,66948,60709,Probation,Vonmassenbach,Wendy,NULL,Female,Caucasian,05/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/29/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +58492,66948,60709,Probation,Vonmassenbach,Wendy,NULL,Female,Caucasian,05/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +58492,66948,60709,Probation,Vonmassenbach,Wendy,NULL,Female,Caucasian,05/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58472,66934,60696,PRETRIAL,McKinney,Lorenzo,A,Male,African-American,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +58472,66934,60696,PRETRIAL,McKinney,Lorenzo,A,Male,African-American,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +58472,66934,60696,PRETRIAL,McKinney,Lorenzo,A,Male,African-American,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58480,66941,60703,PRETRIAL,Russomano,Gerald,Wayne,Male,Caucasian,03/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/29/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +58480,66941,60703,PRETRIAL,Russomano,Gerald,Wayne,Male,Caucasian,03/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +58480,66941,60703,PRETRIAL,Russomano,Gerald,Wayne,Male,Caucasian,03/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58495,66955,60713,PRETRIAL,PIERCE,PRISCILLA,NULL,Female,African-American,02/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +58495,66955,60713,PRETRIAL,PIERCE,PRISCILLA,NULL,Female,African-American,02/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +58495,66955,60713,PRETRIAL,PIERCE,PRISCILLA,NULL,Female,African-American,02/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +58500,66962,60719,Probation,Dealmedia-Vaz,Filipe,NULL,Male,Hispanic,08/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +58500,66962,60719,Probation,Dealmedia-Vaz,Filipe,NULL,Male,Hispanic,08/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +58500,66962,60719,Probation,Dealmedia-Vaz,Filipe,NULL,Male,Hispanic,08/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58497,66959,60716,PRETRIAL,Cohen,Jared,Samuel,Male,Caucasian,11/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/29/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +58497,66959,60716,PRETRIAL,Cohen,Jared,Samuel,Male,Caucasian,11/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/29/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +58497,66959,60716,PRETRIAL,Cohen,Jared,Samuel,Male,Caucasian,11/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58476,66938,60700,PRETRIAL,Bellamy,Samuel,David,Male,African-American,08/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +58476,66938,60700,PRETRIAL,Bellamy,Samuel,David,Male,African-American,08/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +58476,66938,60700,PRETRIAL,Bellamy,Samuel,David,Male,African-American,08/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58471,66933,60695,PRETRIAL,HALL,CHRISTOPHER,A,Male,African-American,05/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/29/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +58471,66933,60695,PRETRIAL,HALL,CHRISTOPHER,A,Male,African-American,05/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +58471,66933,60695,PRETRIAL,HALL,CHRISTOPHER,A,Male,African-American,05/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +26341,66980,60734,PRETRIAL,SAWYER,JOHNNY,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,10/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,New,1,0 +26341,66980,60734,PRETRIAL,SAWYER,JOHNNY,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,10/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +26341,66980,60734,PRETRIAL,SAWYER,JOHNNY,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,10/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +58505,66967,60722,PRETRIAL,Hewitt,Nicole,NULL,Female,African-American,04/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +58505,66967,60722,PRETRIAL,Hewitt,Nicole,NULL,Female,African-American,04/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,9,High,New,1,0 +58505,66967,60722,PRETRIAL,Hewitt,Nicole,NULL,Female,African-American,04/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +45853,66975,60730,PRETRIAL,Petrie,Joseph,Bryant,Male,Caucasian,12/13/51,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,10/29/13 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +45853,66975,60730,PRETRIAL,Petrie,Joseph,Bryant,Male,Caucasian,12/13/51,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,10/29/13 0:00,1,Low,8,Risk of Recidivism,-2.61,1,Low,New,1,0 +45853,66975,60730,PRETRIAL,Petrie,Joseph,Bryant,Male,Caucasian,12/13/51,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58503,66965,60720,PRETRIAL,THOMAS,EDWARD,L,Male,African-American,04/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +58503,66965,60720,PRETRIAL,THOMAS,EDWARD,L,Male,African-American,04/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +58503,66965,60720,PRETRIAL,THOMAS,EDWARD,L,Male,African-American,04/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +58473,66935,60697,PRETRIAL,Martin,Margretta,NULL,Female,Other,08/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +58473,66935,60697,PRETRIAL,Martin,Margretta,NULL,Female,Other,08/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,New,1,0 +58473,66935,60697,PRETRIAL,Martin,Margretta,NULL,Female,Other,08/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58490,66944,60706,Probation,Espinoza,Monika,NULL,Female,Hispanic,09/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +58490,66944,60706,Probation,Espinoza,Monika,NULL,Female,Hispanic,09/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +58490,66944,60706,Probation,Espinoza,Monika,NULL,Female,Hispanic,09/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58479,66940,60702,PRETRIAL,Mesadieu,Evans,NULL,Male,African-American,09/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/29/13 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +58479,66940,60702,PRETRIAL,Mesadieu,Evans,NULL,Male,African-American,09/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +58479,66940,60702,PRETRIAL,Mesadieu,Evans,NULL,Male,African-American,09/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58501,66961,60718,PRETRIAL,Williams,Michael,l,Male,African-American,11/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/29/13 0:00,2,Medium,7,Risk of Violence,-3.15,1,Low,New,1,0 +58501,66961,60718,PRETRIAL,Williams,Michael,l,Male,African-American,11/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +58501,66961,60718,PRETRIAL,Williams,Michael,l,Male,African-American,11/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +1810,66947,60708,PRETRIAL,PETITHOMME,JOSUE,NULL,Male,Caucasian,10/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/29/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +1810,66947,60708,PRETRIAL,PETITHOMME,JOSUE,NULL,Male,Caucasian,10/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/29/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +1810,66947,60708,PRETRIAL,PETITHOMME,JOSUE,NULL,Male,Caucasian,10/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58493,66949,60710,PRETRIAL,gildon,amy,NULL,Female,Caucasian,11/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +58493,66949,60710,PRETRIAL,gildon,amy,NULL,Female,Caucasian,11/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,7,Medium,New,1,0 +58493,66949,60710,PRETRIAL,gildon,amy,NULL,Female,Caucasian,11/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57634,66956,59761,Probation,EDGECOMBE,TARVEL,NULL,Male,African-American,10/02/84,17,All Scales,Intake,English,Conditional Release,Probation,Married,10/29/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,Copy,1,0 +57634,66956,59761,Probation,EDGECOMBE,TARVEL,NULL,Male,African-American,10/02/84,17,All Scales,Intake,English,Conditional Release,Probation,Married,10/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,6,Medium,Copy,1,0 +57634,66956,59761,Probation,EDGECOMBE,TARVEL,NULL,Male,African-American,10/02/84,17,All Scales,Intake,English,Conditional Release,Probation,Married,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,22,4,Low,Copy,1,0 +15082,66970,60725,PRETRIAL,Labrador,Dennis,NULL,Male,Caucasian,03/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +15082,66970,60725,PRETRIAL,Labrador,Dennis,NULL,Male,Caucasian,03/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +15082,66970,60725,PRETRIAL,Labrador,Dennis,NULL,Male,Caucasian,03/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +7659,66977,7687,PRETRIAL,Mason,Eldriche,A,Male,African-American,04/05/76,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,10/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,Copy,1,0 +7659,66977,7687,PRETRIAL,Mason,Eldriche,A,Male,African-American,04/05/76,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,10/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,Copy,1,0 +7659,66977,7687,PRETRIAL,Mason,Eldriche,A,Male,African-American,04/05/76,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,10/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +58475,66937,60699,PRETRIAL,walker,willie,NULL,Male,African-American,11/15/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +58475,66937,60699,PRETRIAL,walker,willie,NULL,Male,African-American,11/15/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +58475,66937,60699,PRETRIAL,walker,willie,NULL,Male,African-American,11/15/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58478,66942,60704,PRETRIAL,Chermak,Paul,F,Male,Caucasian,03/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/29/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +58478,66942,60704,PRETRIAL,Chermak,Paul,F,Male,Caucasian,03/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/29/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +58478,66942,60704,PRETRIAL,Chermak,Paul,F,Male,Caucasian,03/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58508,66971,60726,Probation,john,kristin,NULL,Female,African-American,07/15/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +58508,66971,60726,Probation,john,kristin,NULL,Female,African-American,07/15/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +58508,66971,60726,Probation,john,kristin,NULL,Female,African-American,07/15/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +58533,66976,60731,Probation,Allen,Brandon,NULL,Male,Caucasian,02/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +58533,66976,60731,Probation,Allen,Brandon,NULL,Male,Caucasian,02/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +58533,66976,60731,Probation,Allen,Brandon,NULL,Male,Caucasian,02/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +48123,66950,60711,PRETRIAL,Day,Bethany,NULL,Female,Caucasian,01/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +48123,66950,60711,PRETRIAL,Day,Bethany,NULL,Female,Caucasian,01/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +48123,66950,60711,PRETRIAL,Day,Bethany,NULL,Female,Caucasian,01/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +5705,66963,59701,Probation,Irvin,Antwaun,Devon,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,Copy,1,0 +5705,66963,59701,Probation,Irvin,Antwaun,Devon,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,Copy,1,0 +5705,66963,59701,Probation,Irvin,Antwaun,Devon,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +58506,66968,60723,Probation,morris,wayne,NULL,Male,Caucasian,09/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +58506,66968,60723,Probation,morris,wayne,NULL,Male,Caucasian,09/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +58506,66968,60723,Probation,morris,wayne,NULL,Male,Caucasian,09/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58536,66979,60733,Probation,Hylton,Gervaise,NULL,Male,African-American,06/26/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/29/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +58536,66979,60733,Probation,Hylton,Gervaise,NULL,Male,African-American,06/26/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +58536,66979,60733,Probation,Hylton,Gervaise,NULL,Male,African-American,06/26/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58498,66958,60715,PRETRIAL,NERESTANT,WINNIE,NULL,Female,African-American,04/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +58498,66958,60715,PRETRIAL,NERESTANT,WINNIE,NULL,Female,African-American,04/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,8,High,New,1,0 +58498,66958,60715,PRETRIAL,NERESTANT,WINNIE,NULL,Female,African-American,04/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58511,66973,60728,Probation,CRUZ,JOEL,JAIMES,Male,Hispanic,07/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/29/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +58511,66973,60728,Probation,CRUZ,JOEL,JAIMES,Male,Hispanic,07/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/29/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +58511,66973,60728,Probation,CRUZ,JOEL,JAIMES,Male,Hispanic,07/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53004,66974,60729,PRETRIAL,Tisdale,Issac,NULL,Male,African-American,10/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +53004,66974,60729,PRETRIAL,Tisdale,Issac,NULL,Male,African-American,10/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +53004,66974,60729,PRETRIAL,Tisdale,Issac,NULL,Male,African-American,10/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58491,66945,60707,PRETRIAL,LLaguna,Jose,NULL,Male,Caucasian,04/12/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +58491,66945,60707,PRETRIAL,LLaguna,Jose,NULL,Male,Caucasian,04/12/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +58491,66945,60707,PRETRIAL,LLaguna,Jose,NULL,Male,Caucasian,04/12/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52515,66952,53837,Probation,Hayes,Austin,NULL,Male,Caucasian,01/28/95,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +52515,66952,53837,Probation,Hayes,Austin,NULL,Male,Caucasian,01/28/95,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +52515,66952,53837,Probation,Hayes,Austin,NULL,Male,Caucasian,01/28/95,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58494,66953,60712,PRETRIAL,tavarez,elvis,NULL,Male,Hispanic,10/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +58494,66953,60712,PRETRIAL,tavarez,elvis,NULL,Male,Hispanic,10/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +58494,66953,60712,PRETRIAL,tavarez,elvis,NULL,Male,Hispanic,10/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58499,66960,60717,Probation,Ghani,Blal,NULL,Male,Caucasian,12/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +58499,66960,60717,Probation,Ghani,Blal,NULL,Male,Caucasian,12/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +58499,66960,60717,Probation,Ghani,Blal,NULL,Male,Caucasian,12/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +39488,66932,60694,PRETRIAL,THOMPSON,LAVON,NULL,Male,African-American,04/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,7,Risk of Violence,-1.34,7,Medium,New,1,0 +39488,66932,60694,PRETRIAL,THOMPSON,LAVON,NULL,Male,African-American,04/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +39488,66932,60694,PRETRIAL,THOMPSON,LAVON,NULL,Male,African-American,04/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58504,66966,60721,Probation,Blanco,Humberto,NULL,Male,Hispanic,09/27/63,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/29/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +58504,66966,60721,Probation,Blanco,Humberto,NULL,Male,Hispanic,09/27/63,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/29/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +58504,66966,60721,Probation,Blanco,Humberto,NULL,Male,Hispanic,09/27/63,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +28704,66981,60735,PRETRIAL,SOARES,ARMONDO,NULL,Male,African-American,06/03/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +28704,66981,60735,PRETRIAL,SOARES,ARMONDO,NULL,Male,African-American,06/03/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +28704,66981,60735,PRETRIAL,SOARES,ARMONDO,NULL,Male,African-American,06/03/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +58564,67015,60766,PRETRIAL,Zilka,Warren,NULL,Male,Caucasian,07/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/30/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +58564,67015,60766,PRETRIAL,Zilka,Warren,NULL,Male,Caucasian,07/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/30/13 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +58564,67015,60766,PRETRIAL,Zilka,Warren,NULL,Male,Caucasian,07/12/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58542,66987,60740,PRETRIAL,Tripp,Debra,NULL,Female,Caucasian,04/15/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +58542,66987,60740,PRETRIAL,Tripp,Debra,NULL,Female,Caucasian,04/15/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +58542,66987,60740,PRETRIAL,Tripp,Debra,NULL,Female,Caucasian,04/15/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58547,66994,60747,PRETRIAL,Boyd,Haywood,NULL,Male,African-American,05/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +58547,66994,60747,PRETRIAL,Boyd,Haywood,NULL,Male,African-American,05/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +58547,66994,60747,PRETRIAL,Boyd,Haywood,NULL,Male,African-American,05/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58548,66995,60748,PRETRIAL,Sturdivant,Bobby,Fitzgerald,Male,African-American,04/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +58548,66995,60748,PRETRIAL,Sturdivant,Bobby,Fitzgerald,Male,African-American,04/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +58548,66995,60748,PRETRIAL,Sturdivant,Bobby,Fitzgerald,Male,African-American,04/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +6589,67002,60755,PRETRIAL,Armstrong,Vitas,B,Male,Other,03/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,New,1,0 +6589,67002,60755,PRETRIAL,Armstrong,Vitas,B,Male,Other,03/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +6589,67002,60755,PRETRIAL,Armstrong,Vitas,B,Male,Other,03/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58569,67023,60774,Probation,Foster,Kimberley,NULL,Female,Caucasian,05/13/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +58569,67023,60774,Probation,Foster,Kimberley,NULL,Female,Caucasian,05/13/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +58569,67023,60774,Probation,Foster,Kimberley,NULL,Female,Caucasian,05/13/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +36929,66989,60742,PRETRIAL,Terry,Mueller,Joseph,Male,Caucasian,01/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +36929,66989,60742,PRETRIAL,Terry,Mueller,Joseph,Male,Caucasian,01/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +36929,66989,60742,PRETRIAL,Terry,Mueller,Joseph,Male,Caucasian,01/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58565,67018,60769,Probation,Jean,Sony,NULL,Male,African-American,07/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +58565,67018,60769,Probation,Jean,Sony,NULL,Male,African-American,07/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +58565,67018,60769,Probation,Jean,Sony,NULL,Male,African-American,07/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58550,66997,60750,PRETRIAL,MAJOR,MAURICE,LAMOND,Male,African-American,01/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +58550,66997,60750,PRETRIAL,MAJOR,MAURICE,LAMOND,Male,African-American,01/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +58550,66997,60750,PRETRIAL,MAJOR,MAURICE,LAMOND,Male,African-American,01/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58573,67031,60780,Probation,Hart,Willie,NULL,Male,African-American,08/16/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +58573,67031,60780,Probation,Hart,Willie,NULL,Male,African-American,08/16/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +58573,67031,60780,Probation,Hart,Willie,NULL,Male,African-American,08/16/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58560,67010,60761,PRETRIAL,Daley,Nicole,NULL,Female,African-American,01/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +58560,67010,60761,PRETRIAL,Daley,Nicole,NULL,Female,African-American,01/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +58560,67010,60761,PRETRIAL,Daley,Nicole,NULL,Female,African-American,01/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58539,66984,60737,PRETRIAL,RUSS,TANARES,J,Female,African-American,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +58539,66984,60737,PRETRIAL,RUSS,TANARES,J,Female,African-American,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +58539,66984,60737,PRETRIAL,RUSS,TANARES,J,Female,African-American,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58544,66991,60744,PRETRIAL,Diaz,Alex,NULL,Male,African-American,05/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +58544,66991,60744,PRETRIAL,Diaz,Alex,NULL,Male,African-American,05/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +58544,66991,60744,PRETRIAL,Diaz,Alex,NULL,Male,African-American,05/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58556,67005,60757,PRETRIAL,Williams,Dominique,NULL,Male,African-American,08/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +58556,67005,60757,PRETRIAL,Williams,Dominique,NULL,Male,African-American,08/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +58556,67005,60757,PRETRIAL,Williams,Dominique,NULL,Male,African-American,08/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58553,67000,60753,Broward County,Gilbert,Craig,NULL,Female,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +58553,67000,60753,Broward County,Gilbert,Craig,NULL,Female,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +58553,67000,60753,Broward County,Gilbert,Craig,NULL,Female,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58566,67019,60770,Probation,Lloyd,Brandon,NULL,Male,African-American,06/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +58566,67019,60770,Probation,Lloyd,Brandon,NULL,Male,African-American,06/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +58566,67019,60770,Probation,Lloyd,Brandon,NULL,Male,African-American,06/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +863,67021,60772,PRETRIAL,SANTANA,ELPIDIO,A,Male,Hispanic,10/31/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/13 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +863,67021,60772,PRETRIAL,SANTANA,ELPIDIO,A,Male,Hispanic,10/31/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/13 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +863,67021,60772,PRETRIAL,SANTANA,ELPIDIO,A,Male,Hispanic,10/31/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58571,67026,60777,Probation,creach,diamond,NULL,Female,African-American,07/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +58571,67026,60777,Probation,creach,diamond,NULL,Female,African-American,07/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +58571,67026,60777,Probation,creach,diamond,NULL,Female,African-American,07/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +46634,67028,47061,PRETRIAL,RUSSELL,CAMERON,NULL,Male,African-American,05/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.32,3,Low,Copy,1,0 +46634,67028,47061,PRETRIAL,RUSSELL,CAMERON,NULL,Male,African-American,05/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,Copy,1,0 +46634,67028,47061,PRETRIAL,RUSSELL,CAMERON,NULL,Male,African-American,05/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +58541,66986,60739,PRETRIAL,Taylor,Antonio,NULL,Male,African-American,09/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +58541,66986,60739,PRETRIAL,Taylor,Antonio,NULL,Male,African-American,09/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +58541,66986,60739,PRETRIAL,Taylor,Antonio,NULL,Male,African-American,09/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58396,67007,60628,PRETRIAL,LANDERS,MARKEL,S,Male,African-American,12/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/13 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,Copy,1,0 +58396,67007,60628,PRETRIAL,LANDERS,MARKEL,S,Male,African-American,12/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.55,4,Low,Copy,1,0 +58396,67007,60628,PRETRIAL,LANDERS,MARKEL,S,Male,African-American,12/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +3600,67003,3316,PRETRIAL,Williams,Lee,NULL,Male,African-American,12/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/30/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,Copy,1,0 +3600,67003,3316,PRETRIAL,Williams,Lee,NULL,Male,African-American,12/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,Copy,1,0 +3600,67003,3316,PRETRIAL,Williams,Lee,NULL,Male,African-American,12/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +13643,67012,60763,PRETRIAL,SPICER,WALTER,THOMAS,Male,Caucasian,09/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/30/13 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +13643,67012,60763,PRETRIAL,SPICER,WALTER,THOMAS,Male,Caucasian,09/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +13643,67012,60763,PRETRIAL,SPICER,WALTER,THOMAS,Male,Caucasian,09/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/30/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +7620,66982,7212,DRRD,Major,Anthony,Daniel,Male,African-American,10/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/30/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,Copy,1,0 +7620,66982,7212,DRRD,Major,Anthony,Daniel,Male,African-American,10/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.51,4,Low,Copy,1,0 +7620,66982,7212,DRRD,Major,Anthony,Daniel,Male,African-American,10/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,27,6,Medium,Copy,1,0 +47168,67016,60767,PRETRIAL,Doyle,Michael,NULL,Male,Caucasian,09/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +47168,67016,60767,PRETRIAL,Doyle,Michael,NULL,Male,Caucasian,09/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +47168,67016,60767,PRETRIAL,Doyle,Michael,NULL,Male,Caucasian,09/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +23407,67033,22600,Probation,CAMPBELL,DAVID,NULL,Male,African-American,06/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,4,High,7,Risk of Violence,-0.19,10,High,Copy,1,0 +23407,67033,22600,Probation,CAMPBELL,DAVID,NULL,Male,African-American,06/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,4,High,8,Risk of Recidivism,1.21,10,High,Copy,1,0 +23407,67033,22600,Probation,CAMPBELL,DAVID,NULL,Male,African-American,06/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +29728,31435,28729,PRETRIAL,Cajas,Nelson,NULL,Male,Hispanic,01/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,7,Risk of Violence,-1.43,7,Medium,New,1,0 +29728,31435,28729,PRETRIAL,Cajas,Nelson,NULL,Male,Hispanic,01/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +29728,31435,28729,PRETRIAL,Cajas,Nelson,NULL,Male,Hispanic,01/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58568,67022,60773,Probation,VANNIEKERK,JASON,JOHN,Male,Caucasian,01/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +58568,67022,60773,Probation,VANNIEKERK,JASON,JOHN,Male,Caucasian,01/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +58568,67022,60773,Probation,VANNIEKERK,JASON,JOHN,Male,Caucasian,01/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58546,66993,60746,PRETRIAL,Brown,Oceal,NULL,Male,African-American,11/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.43,3,Low,New,1,0 +58546,66993,60746,PRETRIAL,Brown,Oceal,NULL,Male,African-American,11/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +58546,66993,60746,PRETRIAL,Brown,Oceal,NULL,Male,African-American,11/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58563,67014,60765,PRETRIAL,THOMPSON,KYLE,NULL,Male,Caucasian,02/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +58563,67014,60765,PRETRIAL,THOMPSON,KYLE,NULL,Male,Caucasian,02/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +58563,67014,60765,PRETRIAL,THOMPSON,KYLE,NULL,Male,Caucasian,02/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58543,66988,60741,PRETRIAL,Leiba,Abdul,NULL,Male,African-American,09/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +58543,66988,60741,PRETRIAL,Leiba,Abdul,NULL,Male,African-American,09/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +58543,66988,60741,PRETRIAL,Leiba,Abdul,NULL,Male,African-American,09/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58570,67024,60775,Probation,MORRISSEAU,ALBERT,NULL,Male,Caucasian,06/22/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +58570,67024,60775,Probation,MORRISSEAU,ALBERT,NULL,Male,Caucasian,06/22/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +58570,67024,60775,Probation,MORRISSEAU,ALBERT,NULL,Male,Caucasian,06/22/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58559,67009,60760,Probation,Parfait,Lyonel,NULL,Male,African-American,09/28/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/30/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +58559,67009,60760,Probation,Parfait,Lyonel,NULL,Male,African-American,09/28/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/30/13 0:00,1,Low,8,Risk of Recidivism,-2.58,1,Low,New,1,0 +58559,67009,60760,Probation,Parfait,Lyonel,NULL,Male,African-American,09/28/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58572,67030,60779,Probation,Williams,Justin,NULL,Male,African-American,12/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-1.77,5,Medium,New,1,0 +58572,67030,60779,Probation,Williams,Justin,NULL,Male,African-American,12/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +58572,67030,60779,Probation,Williams,Justin,NULL,Male,African-American,12/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58574,67032,60781,PRETRIAL,Daniels,Derick,NULL,Male,African-American,10/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +58574,67032,60781,PRETRIAL,Daniels,Derick,NULL,Male,African-American,10/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +58574,67032,60781,PRETRIAL,Daniels,Derick,NULL,Male,African-American,10/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58549,66996,60749,PRETRIAL,Watrous,Kevin,Keith,Male,Caucasian,03/22/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/30/13 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +58549,66996,60749,PRETRIAL,Watrous,Kevin,Keith,Male,Caucasian,03/22/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/30/13 0:00,1,Low,8,Risk of Recidivism,-2.81,1,Low,New,1,0 +58549,66996,60749,PRETRIAL,Watrous,Kevin,Keith,Male,Caucasian,03/22/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +29728,67017,60768,PRETRIAL,Cajas,Nelson,NULL,Male,Hispanic,01/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +29728,67017,60768,PRETRIAL,Cajas,Nelson,NULL,Male,Hispanic,01/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +29728,67017,60768,PRETRIAL,Cajas,Nelson,NULL,Male,Hispanic,01/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58540,66985,60738,PRETRIAL,Simmons,Manny,NULL,Male,African-American,01/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.76,2,Low,New,1,0 +58540,66985,60738,PRETRIAL,Simmons,Manny,NULL,Male,African-American,01/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.64,10,High,New,1,0 +58540,66985,60738,PRETRIAL,Simmons,Manny,NULL,Male,African-American,01/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58538,66983,60736,PRETRIAL,Reed,Michael,NULL,Male,African-American,04/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +58538,66983,60736,PRETRIAL,Reed,Michael,NULL,Male,African-American,04/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +58538,66983,60736,PRETRIAL,Reed,Michael,NULL,Male,African-American,04/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58562,67013,60764,Probation,MORAGA,KEVIN,NULL,Male,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +58562,67013,60764,Probation,MORAGA,KEVIN,NULL,Male,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +58562,67013,60764,Probation,MORAGA,KEVIN,NULL,Male,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58557,67006,60758,PRETRIAL,Allen,Yolanda,NULL,Female,African-American,09/04/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/30/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +58557,67006,60758,PRETRIAL,Allen,Yolanda,NULL,Female,African-American,09/04/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/30/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +58557,67006,60758,PRETRIAL,Allen,Yolanda,NULL,Female,African-American,09/04/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58567,67020,60771,Probation,Reyes,Angelika,NULL,Female,Hispanic,10/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +58567,67020,60771,Probation,Reyes,Angelika,NULL,Female,Hispanic,10/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +58567,67020,60771,Probation,Reyes,Angelika,NULL,Female,Hispanic,10/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +949,67027,60778,PRETRIAL,MOISE,CHEDLINE,NULL,Female,African-American,05/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +949,67027,60778,PRETRIAL,MOISE,CHEDLINE,NULL,Female,African-American,05/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,10,High,New,1,0 +949,67027,60778,PRETRIAL,MOISE,CHEDLINE,NULL,Female,African-American,05/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +19455,66990,60743,PRETRIAL,BROWN,DELANO,NULL,Male,African-American,09/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +19455,66990,60743,PRETRIAL,BROWN,DELANO,NULL,Male,African-American,09/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,4,High,8,Risk of Recidivism,0.67,10,High,New,1,0 +19455,66990,60743,PRETRIAL,BROWN,DELANO,NULL,Male,African-American,09/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58558,67008,60759,Probation,Yasin,Renaud,NULL,Male,Arabic,04/16/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +58558,67008,60759,Probation,Yasin,Renaud,NULL,Male,Arabic,04/16/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +58558,67008,60759,Probation,Yasin,Renaud,NULL,Male,Arabic,04/16/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +8558,67025,60776,PRETRIAL,BAKER,RONNIE,NULL,Male,African-American,08/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +8558,67025,60776,PRETRIAL,BAKER,RONNIE,NULL,Male,African-American,08/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +8558,67025,60776,PRETRIAL,BAKER,RONNIE,NULL,Male,African-American,08/24/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58555,67004,60756,Probation,Marius,Rodney,NULL,Male,African-American,03/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +58555,67004,60756,Probation,Marius,Rodney,NULL,Male,African-American,03/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +58555,67004,60756,Probation,Marius,Rodney,NULL,Male,African-American,03/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58561,67011,60762,PRETRIAL,Simmons,Charlie,NULL,Male,African-American,11/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +58561,67011,60762,PRETRIAL,Simmons,Charlie,NULL,Male,African-American,11/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +58561,67011,60762,PRETRIAL,Simmons,Charlie,NULL,Male,African-American,11/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58586,67050,60796,PRETRIAL,Ballew,John,NULL,Male,Caucasian,10/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +58586,67050,60796,PRETRIAL,Ballew,John,NULL,Male,Caucasian,10/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +58586,67050,60796,PRETRIAL,Ballew,John,NULL,Male,Caucasian,10/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58603,67067,60813,Probation,Lopez anronio,Jose,NULL,Male,Hispanic,05/09/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +58603,67067,60813,Probation,Lopez anronio,Jose,NULL,Male,Hispanic,05/09/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +58603,67067,60813,Probation,Lopez anronio,Jose,NULL,Male,Hispanic,05/09/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58584,67046,60792,PRETRIAL,Payne,Felix,NULL,Male,African-American,06/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +58584,67046,60792,PRETRIAL,Payne,Felix,NULL,Male,African-American,06/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +58584,67046,60792,PRETRIAL,Payne,Felix,NULL,Male,African-American,06/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +58606,67071,60816,PRETRIAL,Verola,Alyssa,NULL,Female,Caucasian,05/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +58606,67071,60816,PRETRIAL,Verola,Alyssa,NULL,Female,Caucasian,05/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +58606,67071,60816,PRETRIAL,Verola,Alyssa,NULL,Female,Caucasian,05/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58575,67034,60782,PRETRIAL,Williams,Barry,NULL,Male,African-American,04/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +58575,67034,60782,PRETRIAL,Williams,Barry,NULL,Male,African-American,04/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +58575,67034,60782,PRETRIAL,Williams,Barry,NULL,Male,African-American,04/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58581,67041,60789,PRETRIAL,Register,Nyisha,NULL,Female,African-American,06/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +58581,67041,60789,PRETRIAL,Register,Nyisha,NULL,Female,African-American,06/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +58581,67041,60789,PRETRIAL,Register,Nyisha,NULL,Female,African-American,06/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58591,67055,60801,Probation,Morgan,Shantal,NULL,Female,African-American,02/10/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +58591,67055,60801,Probation,Morgan,Shantal,NULL,Female,African-American,02/10/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +58591,67055,60801,Probation,Morgan,Shantal,NULL,Female,African-American,02/10/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58600,67064,60810,Probation,Gomez,Jorge,NULL,Male,Hispanic,08/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +58600,67064,60810,Probation,Gomez,Jorge,NULL,Male,Hispanic,08/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +58600,67064,60810,Probation,Gomez,Jorge,NULL,Male,Hispanic,08/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +49711,67062,60808,PRETRIAL,ricco,michael,NULL,Male,Caucasian,01/04/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/31/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +49711,67062,60808,PRETRIAL,ricco,michael,NULL,Male,Caucasian,01/04/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/31/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +49711,67062,60808,PRETRIAL,ricco,michael,NULL,Male,Caucasian,01/04/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58587,67051,60797,PRETRIAL,Dukes,Matthew,Brian,Male,Caucasian,01/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +58587,67051,60797,PRETRIAL,Dukes,Matthew,Brian,Male,Caucasian,01/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +58587,67051,60797,PRETRIAL,Dukes,Matthew,Brian,Male,Caucasian,01/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58589,67053,60799,PRETRIAL,pereira,john,NULL,Male,Caucasian,08/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/31/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +58589,67053,60799,PRETRIAL,pereira,john,NULL,Male,Caucasian,08/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/31/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +58589,67053,60799,PRETRIAL,pereira,john,NULL,Male,Caucasian,08/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58602,67066,60812,Broward County,Smith,Rodney,NULL,Male,African-American,01/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +58602,67066,60812,Broward County,Smith,Rodney,NULL,Male,African-American,01/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +58602,67066,60812,Broward County,Smith,Rodney,NULL,Male,African-American,01/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +56547,67045,58544,Probation,Holmes,Laqunta,NULL,Female,African-American,05/04/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +56547,67045,58544,Probation,Holmes,Laqunta,NULL,Female,African-American,05/04/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +56547,67045,58544,Probation,Holmes,Laqunta,NULL,Female,African-American,05/04/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58594,67059,60805,Probation,woldman,edward,NULL,Male,Caucasian,03/19/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/31/13 0:00,1,Low,7,Risk of Violence,-4.19,1,Low,New,1,0 +58594,67059,60805,Probation,woldman,edward,NULL,Male,Caucasian,03/19/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/31/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +58594,67059,60805,Probation,woldman,edward,NULL,Male,Caucasian,03/19/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58579,67038,60786,PRETRIAL,Raiche,Marc,NULL,Male,Caucasian,10/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/31/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +58579,67038,60786,PRETRIAL,Raiche,Marc,NULL,Male,Caucasian,10/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/31/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +58579,67038,60786,PRETRIAL,Raiche,Marc,NULL,Male,Caucasian,10/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58576,67035,60783,PRETRIAL,Whyte,Everan,NULL,Male,Other,04/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +58576,67035,60783,PRETRIAL,Whyte,Everan,NULL,Male,Other,04/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +58576,67035,60783,PRETRIAL,Whyte,Everan,NULL,Male,Other,04/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58604,67069,60814,Probation,Shaffer,David,NULL,Male,Caucasian,08/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +58604,67069,60814,Probation,Shaffer,David,NULL,Male,Caucasian,08/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +58604,67069,60814,Probation,Shaffer,David,NULL,Male,Caucasian,08/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58596,67061,60807,Probation,mcdonald,rhonda,NULL,Female,African-American,07/01/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/31/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +58596,67061,60807,Probation,mcdonald,rhonda,NULL,Female,African-American,07/01/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/31/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +58596,67061,60807,Probation,mcdonald,rhonda,NULL,Female,African-American,07/01/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50000,67040,60788,PRETRIAL,Nobles,Bernard,NULL,Male,African-American,07/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +50000,67040,60788,PRETRIAL,Nobles,Bernard,NULL,Male,African-American,07/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +50000,67040,60788,PRETRIAL,Nobles,Bernard,NULL,Male,African-American,07/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58599,67063,60809,Probation,Emrickvalentin,Janet,NULL,Female,Caucasian,10/15/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +58599,67063,60809,Probation,Emrickvalentin,Janet,NULL,Female,Caucasian,10/15/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +58599,67063,60809,Probation,Emrickvalentin,Janet,NULL,Female,Caucasian,10/15/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58578,67037,60785,PRETRIAL,Robinson,Clifton,NULL,Male,African-American,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,2,Medium,7,Risk of Violence,-1.33,7,Medium,New,1,0 +58578,67037,60785,PRETRIAL,Robinson,Clifton,NULL,Male,African-American,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +58578,67037,60785,PRETRIAL,Robinson,Clifton,NULL,Male,African-American,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58593,67058,60804,Probation,jones,brian,NULL,Male,African-American,04/09/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/31/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +58593,67058,60804,Probation,jones,brian,NULL,Male,African-American,04/09/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +58593,67058,60804,Probation,jones,brian,NULL,Male,African-American,04/09/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/31/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +58607,67072,60817,Probation,Martinez,Christopher,NULL,Male,Hispanic,05/18/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +58607,67072,60817,Probation,Martinez,Christopher,NULL,Male,Hispanic,05/18/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +58607,67072,60817,Probation,Martinez,Christopher,NULL,Male,Hispanic,05/18/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58590,67054,60800,Probation,Cameron,Lester,NULL,Male,African-American,12/26/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/31/13 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +58590,67054,60800,Probation,Cameron,Lester,NULL,Male,African-American,12/26/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +58590,67054,60800,Probation,Cameron,Lester,NULL,Male,African-American,12/26/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/31/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51465,67047,60793,PRETRIAL,KENDRICK,TIMOTHY,DRAKE,Male,African-American,01/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +51465,67047,60793,PRETRIAL,KENDRICK,TIMOTHY,DRAKE,Male,African-American,01/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +51465,67047,60793,PRETRIAL,KENDRICK,TIMOTHY,DRAKE,Male,African-American,01/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +27048,67049,60795,Probation,ROBINSON,REGINALD,D,Male,African-American,12/04/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/31/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +27048,67049,60795,Probation,ROBINSON,REGINALD,D,Male,African-American,12/04/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/31/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +27048,67049,60795,Probation,ROBINSON,REGINALD,D,Male,African-American,12/04/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58582,67042,60790,PRETRIAL,Edmond,Joshua,NULL,Male,African-American,10/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +58582,67042,60790,PRETRIAL,Edmond,Joshua,NULL,Male,African-American,10/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +58582,67042,60790,PRETRIAL,Edmond,Joshua,NULL,Male,African-American,10/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58592,67056,60802,PRETRIAL,HOLAWAY,TROY,NULL,Male,African-American,12/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +58592,67056,60802,PRETRIAL,HOLAWAY,TROY,NULL,Male,African-American,12/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +58592,67056,60802,PRETRIAL,HOLAWAY,TROY,NULL,Male,African-American,12/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58583,67044,60791,PRETRIAL,ponder,leroy,NULL,Male,African-American,08/25/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +58583,67044,60791,PRETRIAL,ponder,leroy,NULL,Male,African-American,08/25/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +58583,67044,60791,PRETRIAL,ponder,leroy,NULL,Male,African-American,08/25/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58601,67065,60811,Probation,Novak Jr.,John,Mitchell,Male,Caucasian,06/30/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +58601,67065,60811,Probation,Novak Jr.,John,Mitchell,Male,Caucasian,06/30/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +58601,67065,60811,Probation,Novak Jr.,John,Mitchell,Male,Caucasian,06/30/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58577,67036,60784,PRETRIAL,Fenelon,Marc,NULL,Male,African-American,11/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,New,1,0 +58577,67036,60784,PRETRIAL,Fenelon,Marc,NULL,Male,African-American,11/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.74,10,High,New,1,0 +58577,67036,60784,PRETRIAL,Fenelon,Marc,NULL,Male,African-American,11/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58580,67039,60787,PRETRIAL,Augustin,Luben,NULL,Male,African-American,11/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.1,8,High,New,1,0 +58580,67039,60787,PRETRIAL,Augustin,Luben,NULL,Male,African-American,11/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +58580,67039,60787,PRETRIAL,Augustin,Luben,NULL,Male,African-American,11/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +26329,67057,60803,PRETRIAL,Xavier,Chad,NULL,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +26329,67057,60803,PRETRIAL,Xavier,Chad,NULL,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +26329,67057,60803,PRETRIAL,Xavier,Chad,NULL,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58608,67073,60818,Probation,Weaver,Aaron,NULL,Male,Caucasian,11/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +58608,67073,60818,Probation,Weaver,Aaron,NULL,Male,Caucasian,11/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +58608,67073,60818,Probation,Weaver,Aaron,NULL,Male,Caucasian,11/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58588,67052,60798,Probation,MOJICA,BOBBY,DALE,Male,Hispanic,07/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +58588,67052,60798,Probation,MOJICA,BOBBY,DALE,Male,Hispanic,07/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +58588,67052,60798,Probation,MOJICA,BOBBY,DALE,Male,Hispanic,07/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58595,67060,60806,Probation,KNUDSEN,LUIS,A,Male,Hispanic,09/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +58595,67060,60806,Probation,KNUDSEN,LUIS,A,Male,Hispanic,09/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +58595,67060,60806,Probation,KNUDSEN,LUIS,A,Male,Hispanic,09/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58622,67094,60837,Probation,Mustain,James,NULL,Male,Caucasian,01/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/1/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +58622,67094,60837,Probation,Mustain,James,NULL,Male,Caucasian,01/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +58622,67094,60837,Probation,Mustain,James,NULL,Male,Caucasian,01/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58623,67096,60839,Probation,crapp,arthur,NULL,Male,African-American,11/12/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/1/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +58623,67096,60839,Probation,crapp,arthur,NULL,Male,African-American,11/12/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +58623,67096,60839,Probation,crapp,arthur,NULL,Male,African-American,11/12/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50422,67081,60826,PRETRIAL,Jackson,Marcel,NULL,Male,African-American,12/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/1/13 0:00,4,High,7,Risk of Violence,-1.07,8,High,New,1,0 +50422,67081,60826,PRETRIAL,Jackson,Marcel,NULL,Male,African-American,12/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/1/13 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +50422,67081,60826,PRETRIAL,Jackson,Marcel,NULL,Male,African-American,12/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/1/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58632,67102,60844,Probation,Eisenberg,David,NULL,Male,Caucasian,05/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +58632,67102,60844,Probation,Eisenberg,David,NULL,Male,Caucasian,05/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +58632,67102,60844,Probation,Eisenberg,David,NULL,Male,Caucasian,05/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58648,67123,60862,Probation,REYNOLDS,DWAYNE,D,Male,African-American,09/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/1/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +58648,67123,60862,Probation,REYNOLDS,DWAYNE,D,Male,African-American,09/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +58648,67123,60862,Probation,REYNOLDS,DWAYNE,D,Male,African-American,09/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58633,67107,60848,Probation,Parker,James,NULL,Male,African-American,07/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +58633,67107,60848,Probation,Parker,James,NULL,Male,African-American,07/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +58633,67107,60848,Probation,Parker,James,NULL,Male,African-American,07/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56686,67086,58729,PRETRIAL,Humphrey,Tinikka,NULL,Female,African-American,10/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/1/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,Copy,1,0 +56686,67086,58729,PRETRIAL,Humphrey,Tinikka,NULL,Female,African-American,10/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,Copy,1,0 +56686,67086,58729,PRETRIAL,Humphrey,Tinikka,NULL,Female,African-American,10/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +58055,67104,60238,PRETRIAL,crawford,Calvin,NULL,Male,African-American,10/27/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,Copy,1,0 +58055,67104,60238,PRETRIAL,crawford,Calvin,NULL,Male,African-American,10/27/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.76,10,High,Copy,1,0 +58055,67104,60238,PRETRIAL,crawford,Calvin,NULL,Male,African-American,10/27/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +58626,67099,60842,PRETRIAL,Mckinney,Eric,Donovan,Male,African-American,01/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +58626,67099,60842,PRETRIAL,Mckinney,Eric,Donovan,Male,African-American,01/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +58626,67099,60842,PRETRIAL,Mckinney,Eric,Donovan,Male,African-American,01/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58613,67078,60823,PRETRIAL,Examar,Nadege,NULL,Female,African-American,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +58613,67078,60823,PRETRIAL,Examar,Nadege,NULL,Female,African-American,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.09,10,High,New,1,0 +58613,67078,60823,PRETRIAL,Examar,Nadege,NULL,Female,African-American,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58639,67112,60853,DRRD,Smith,Deandre,Alexander,Male,African-American,03/04/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +58639,67112,60853,DRRD,Smith,Deandre,Alexander,Male,African-American,03/04/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,6,Medium,New,1,0 +58639,67112,60853,DRRD,Smith,Deandre,Alexander,Male,African-American,03/04/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,2,Medium,18,Risk of Failure to Appear,22,4,Low,New,1,0 +27513,67105,60846,Probation,devlieger,justin,NULL,Male,Caucasian,05/02/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +27513,67105,60846,Probation,devlieger,justin,NULL,Male,Caucasian,05/02/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +27513,67105,60846,Probation,devlieger,justin,NULL,Male,Caucasian,05/02/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58612,67077,60822,PRETRIAL,Hamil,Chevroy,Obrian,Male,Other,10/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/1/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +58612,67077,60822,PRETRIAL,Hamil,Chevroy,Obrian,Male,Other,10/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +58612,67077,60822,PRETRIAL,Hamil,Chevroy,Obrian,Male,Other,10/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58617,67084,60829,PRETRIAL,Mathews,Sean,Michael,Male,Caucasian,01/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +58617,67084,60829,PRETRIAL,Mathews,Sean,Michael,Male,Caucasian,01/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +58617,67084,60829,PRETRIAL,Mathews,Sean,Michael,Male,Caucasian,01/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58625,67098,60841,Probation,Vasquez,Claudia,NULL,Female,African-American,07/31/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +58625,67098,60841,Probation,Vasquez,Claudia,NULL,Female,African-American,07/31/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +58625,67098,60841,Probation,Vasquez,Claudia,NULL,Female,African-American,07/31/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +43241,67100,43158,PRETRIAL,Beckwith,Franklin,NULL,Male,African-American,05/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,Copy,1,0 +43241,67100,43158,PRETRIAL,Beckwith,Franklin,NULL,Male,African-American,05/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,Copy,1,0 +43241,67100,43158,PRETRIAL,Beckwith,Franklin,NULL,Male,African-American,05/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +56400,64326,58372,PRETRIAL,Hughes,Gregory,NULL,Male,Caucasian,11/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/1/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +56400,64326,58372,PRETRIAL,Hughes,Gregory,NULL,Male,Caucasian,11/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/1/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +56400,64326,58372,PRETRIAL,Hughes,Gregory,NULL,Male,Caucasian,11/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +58644,67119,60858,Probation,Martinez,Marcus,NULL,Male,Hispanic,06/17/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +58644,67119,60858,Probation,Martinez,Marcus,NULL,Male,Hispanic,06/17/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +58644,67119,60858,Probation,Martinez,Marcus,NULL,Male,Hispanic,06/17/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58646,67121,60860,Probation,Menter,Unique,NULL,Female,African-American,10/05/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +58646,67121,60860,Probation,Menter,Unique,NULL,Female,African-American,10/05/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,8,High,New,1,0 +58646,67121,60860,Probation,Menter,Unique,NULL,Female,African-American,10/05/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +58650,67126,60865,PRETRIAL,Williams,Mallory,Roslyn,Female,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/1/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +58650,67126,60865,PRETRIAL,Williams,Mallory,Roslyn,Female,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +58650,67126,60865,PRETRIAL,Williams,Mallory,Roslyn,Female,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/1/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +58614,67079,60824,PRETRIAL,Lamusique,Marie,NULL,Female,Other,05/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/1/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +58614,67079,60824,PRETRIAL,Lamusique,Marie,NULL,Female,Other,05/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/1/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +58614,67079,60824,PRETRIAL,Lamusique,Marie,NULL,Female,Other,05/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58621,67093,60836,PRETRIAL,MONTALVO,CARLOS,NULL,Male,Caucasian,10/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +58621,67093,60836,PRETRIAL,MONTALVO,CARLOS,NULL,Male,Caucasian,10/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +58621,67093,60836,PRETRIAL,MONTALVO,CARLOS,NULL,Male,Caucasian,10/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58610,67075,60820,PRETRIAL,Loubeau,Henry,NULL,Male,Other,09/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +58610,67075,60820,PRETRIAL,Loubeau,Henry,NULL,Male,Other,09/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +58610,67075,60820,PRETRIAL,Loubeau,Henry,NULL,Male,Other,09/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58636,67110,60851,PRETRIAL,romero,freddy,NULL,Male,Hispanic,01/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,New,1,0 +58636,67110,60851,PRETRIAL,romero,freddy,NULL,Male,Hispanic,01/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.85,10,High,New,1,0 +58636,67110,60851,PRETRIAL,romero,freddy,NULL,Male,Hispanic,01/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +58641,67114,60855,Probation,Andreassen,Richard,NULL,Male,Caucasian,06/19/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +58641,67114,60855,Probation,Andreassen,Richard,NULL,Male,Caucasian,06/19/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +58641,67114,60855,Probation,Andreassen,Richard,NULL,Male,Caucasian,06/19/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58620,67090,60833,Probation,Douthard,Damon,NULL,Male,African-American,08/05/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +58620,67090,60833,Probation,Douthard,Damon,NULL,Male,African-American,08/05/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +58620,67090,60833,Probation,Douthard,Damon,NULL,Male,African-American,08/05/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58634,67108,60849,Probation,Ramirez,Lucas,NULL,Male,Hispanic,01/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +58634,67108,60849,Probation,Ramirez,Lucas,NULL,Male,Hispanic,01/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +58634,67108,60849,Probation,Ramirez,Lucas,NULL,Male,Hispanic,01/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58637,67111,60852,PRETRIAL,Valenzuela,Luis,NULL,Male,Hispanic,06/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +58637,67111,60852,PRETRIAL,Valenzuela,Luis,NULL,Male,Hispanic,06/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +58637,67111,60852,PRETRIAL,Valenzuela,Luis,NULL,Male,Hispanic,06/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58651,67129,60867,Probation,lopez,sergio,NULL,Male,Hispanic,05/12/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +58651,67129,60867,Probation,lopez,sergio,NULL,Male,Hispanic,05/12/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +58651,67129,60867,Probation,lopez,sergio,NULL,Male,Hispanic,05/12/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +44520,67103,60845,PRETRIAL,James,Keith,NULL,Male,Other,07/22/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/1/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +44520,67103,60845,PRETRIAL,James,Keith,NULL,Male,Other,07/22/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/1/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +44520,67103,60845,PRETRIAL,James,Keith,NULL,Male,Other,07/22/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +24479,67082,60827,PRETRIAL,GIBBS,JOSEPH,NULL,Male,Caucasian,08/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +24479,67082,60827,PRETRIAL,GIBBS,JOSEPH,NULL,Male,Caucasian,08/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +24479,67082,60827,PRETRIAL,GIBBS,JOSEPH,NULL,Male,Caucasian,08/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +51789,67124,60863,PRETRIAL,Gonzalez,Pedro,NULL,Male,Hispanic,05/17/67,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/1/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +51789,67124,60863,PRETRIAL,Gonzalez,Pedro,NULL,Male,Hispanic,05/17/67,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/1/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +51789,67124,60863,PRETRIAL,Gonzalez,Pedro,NULL,Male,Hispanic,05/17/67,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58618,67085,60830,PRETRIAL,Mack,Levon,NULL,Male,African-American,02/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +58618,67085,60830,PRETRIAL,Mack,Levon,NULL,Male,African-American,02/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +58618,67085,60830,PRETRIAL,Mack,Levon,NULL,Male,African-American,02/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58616,67083,60828,PRETRIAL,Isaac,Carlos,NULL,Male,Other,04/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +58616,67083,60828,PRETRIAL,Isaac,Carlos,NULL,Male,Other,04/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +58616,67083,60828,PRETRIAL,Isaac,Carlos,NULL,Male,Other,04/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58055,67106,60847,PRETRIAL,crawford,Calvin,NULL,Male,African-American,10/27/51,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Separated,11/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +58055,67106,60847,PRETRIAL,crawford,Calvin,NULL,Male,African-American,10/27/51,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Separated,11/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +58055,67106,60847,PRETRIAL,crawford,Calvin,NULL,Male,African-American,10/27/51,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Separated,11/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +58640,67113,60854,Probation,Bathurst,Benjamin,NULL,Male,Caucasian,09/03/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +58640,67113,60854,Probation,Bathurst,Benjamin,NULL,Male,Caucasian,09/03/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +58640,67113,60854,Probation,Bathurst,Benjamin,NULL,Male,Caucasian,09/03/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +58645,67120,60859,Probation,Samayoa,Jose,NULL,Male,Hispanic,02/10/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +58645,67120,60859,Probation,Samayoa,Jose,NULL,Male,Hispanic,02/10/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +58645,67120,60859,Probation,Samayoa,Jose,NULL,Male,Hispanic,02/10/57,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58649,67127,60866,Probation,Torres,Kathleen,NULL,Female,Hispanic,08/15/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +58649,67127,60866,Probation,Torres,Kathleen,NULL,Female,Hispanic,08/15/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +58649,67127,60866,Probation,Torres,Kathleen,NULL,Female,Hispanic,08/15/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58611,67076,60821,PRETRIAL,Ajayi,Diana,NULL,Female,African-American,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +58611,67076,60821,PRETRIAL,Ajayi,Diana,NULL,Female,African-American,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +58611,67076,60821,PRETRIAL,Ajayi,Diana,NULL,Female,African-American,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58615,67080,60825,PRETRIAL,Weaver,Jarrell,NULL,Male,African-American,12/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +58615,67080,60825,PRETRIAL,Weaver,Jarrell,NULL,Male,African-American,12/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +58615,67080,60825,PRETRIAL,Weaver,Jarrell,NULL,Male,African-American,12/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58624,67097,60840,PRETRIAL,jacques,frantz,NULL,Male,African-American,07/25/82,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,11/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.69,2,Low,New,1,0 +58624,67097,60840,PRETRIAL,jacques,frantz,NULL,Male,African-American,07/25/82,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,11/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,8,High,New,1,0 +58624,67097,60840,PRETRIAL,jacques,frantz,NULL,Male,African-American,07/25/82,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,11/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,New,1,0 +58647,67122,60861,Probation,Hueso,German,NULL,Male,Hispanic,04/12/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +58647,67122,60861,Probation,Hueso,German,NULL,Male,Hispanic,04/12/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +58647,67122,60861,Probation,Hueso,German,NULL,Male,Hispanic,04/12/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58660,67139,60876,PRETRIAL,Whorrie,Yvonne,NULL,Female,Caucasian,09/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +58660,67139,60876,PRETRIAL,Whorrie,Yvonne,NULL,Female,Caucasian,09/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +58660,67139,60876,PRETRIAL,Whorrie,Yvonne,NULL,Female,Caucasian,09/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58657,67136,60873,PRETRIAL,Thompson,Steven,NULL,Male,African-American,06/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +58657,67136,60873,PRETRIAL,Thompson,Steven,NULL,Male,African-American,06/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.91,10,High,New,1,0 +58657,67136,60873,PRETRIAL,Thompson,Steven,NULL,Male,African-American,06/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58655,67134,60871,PRETRIAL,Evans,Mourica,NULL,Female,Other,11/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/2/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +58655,67134,60871,PRETRIAL,Evans,Mourica,NULL,Female,Other,11/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/2/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +58655,67134,60871,PRETRIAL,Evans,Mourica,NULL,Female,Other,11/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58661,67141,60878,PRETRIAL,Robinson,Rebecca,NULL,Female,African-American,09/24/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/2/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +58661,67141,60878,PRETRIAL,Robinson,Rebecca,NULL,Female,African-American,09/24/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/2/13 0:00,1,Low,8,Risk of Recidivism,-2.81,1,Low,New,1,0 +58661,67141,60878,PRETRIAL,Robinson,Rebecca,NULL,Female,African-American,09/24/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/2/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58653,67132,60869,PRETRIAL,Enguita,Raul,NULL,Male,Hispanic,11/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +58653,67132,60869,PRETRIAL,Enguita,Raul,NULL,Male,Hispanic,11/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +58653,67132,60869,PRETRIAL,Enguita,Raul,NULL,Male,Hispanic,11/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58658,67137,60874,PRETRIAL,Walraven,Courtney,NULL,Female,Caucasian,04/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +58658,67137,60874,PRETRIAL,Walraven,Courtney,NULL,Female,Caucasian,04/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,7,Medium,New,1,0 +58658,67137,60874,PRETRIAL,Walraven,Courtney,NULL,Female,Caucasian,04/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +58656,67135,60872,PRETRIAL,Evans,Craig,NULL,Male,Other,05/30/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/2/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +58656,67135,60872,PRETRIAL,Evans,Craig,NULL,Male,Other,05/30/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/2/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +58656,67135,60872,PRETRIAL,Evans,Craig,NULL,Male,Other,05/30/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +17894,67140,60877,PRETRIAL,FARMAN,ANDRE,NULL,Male,Caucasian,06/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +17894,67140,60877,PRETRIAL,FARMAN,ANDRE,NULL,Male,Caucasian,06/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +17894,67140,60877,PRETRIAL,FARMAN,ANDRE,NULL,Male,Caucasian,06/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58654,67133,60870,PRETRIAL,Fitpatrick,Shakeirrah,NULL,Female,African-American,03/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +58654,67133,60870,PRETRIAL,Fitpatrick,Shakeirrah,NULL,Female,African-American,03/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +58654,67133,60870,PRETRIAL,Fitpatrick,Shakeirrah,NULL,Female,African-American,03/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58659,67138,60875,PRETRIAL,Araujo,Gabriel,NULL,Male,Hispanic,08/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +58659,67138,60875,PRETRIAL,Araujo,Gabriel,NULL,Male,Hispanic,08/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +58659,67138,60875,PRETRIAL,Araujo,Gabriel,NULL,Male,Hispanic,08/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58671,67151,60888,PRETRIAL,MELCHOR,ROBERTO,NULL,Male,Caucasian,06/07/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +58671,67151,60888,PRETRIAL,MELCHOR,ROBERTO,NULL,Male,Caucasian,06/07/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +58671,67151,60888,PRETRIAL,MELCHOR,ROBERTO,NULL,Male,Caucasian,06/07/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58673,67154,60890,PRETRIAL,WILLIAMS,GARY,NULL,Male,Other,06/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +58673,67154,60890,PRETRIAL,WILLIAMS,GARY,NULL,Male,Other,06/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/13 0:00,1,Low,8,Risk of Recidivism,-2.61,1,Low,New,1,0 +58673,67154,60890,PRETRIAL,WILLIAMS,GARY,NULL,Male,Other,06/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58664,67144,60881,PRETRIAL,GUTMAN,DAVID,NULL,Male,Caucasian,05/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +58664,67144,60881,PRETRIAL,GUTMAN,DAVID,NULL,Male,Caucasian,05/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +58664,67144,60881,PRETRIAL,GUTMAN,DAVID,NULL,Male,Caucasian,05/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58669,67149,60886,PRETRIAL,Leon,Concepcion,NULL,Female,Hispanic,11/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/3/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +58669,67149,60886,PRETRIAL,Leon,Concepcion,NULL,Female,Hispanic,11/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/3/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +58669,67149,60886,PRETRIAL,Leon,Concepcion,NULL,Female,Hispanic,11/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58662,67142,60879,PRETRIAL,SANNINO,MARK,ANTONIO,Male,Caucasian,04/08/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +58662,67142,60879,PRETRIAL,SANNINO,MARK,ANTONIO,Male,Caucasian,04/08/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +58662,67142,60879,PRETRIAL,SANNINO,MARK,ANTONIO,Male,Caucasian,04/08/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58675,67156,60892,PRETRIAL,POTESTA,GIOVANNI,NULL,Male,Hispanic,06/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +58675,67156,60892,PRETRIAL,POTESTA,GIOVANNI,NULL,Male,Hispanic,06/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +58675,67156,60892,PRETRIAL,POTESTA,GIOVANNI,NULL,Male,Hispanic,06/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58670,67150,60887,PRETRIAL,GonzalezSanchez,Ulises,NULL,Male,Hispanic,07/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +58670,67150,60887,PRETRIAL,GonzalezSanchez,Ulises,NULL,Male,Hispanic,07/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +58670,67150,60887,PRETRIAL,GonzalezSanchez,Ulises,NULL,Male,Hispanic,07/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58672,67152,60889,PRETRIAL,COVINGTON,AERITTA,NULL,Female,African-American,08/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +58672,67152,60889,PRETRIAL,COVINGTON,AERITTA,NULL,Female,African-American,08/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +58672,67152,60889,PRETRIAL,COVINGTON,AERITTA,NULL,Female,African-American,08/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58674,67155,60891,PRETRIAL,DAVIS,GLORISHA,NULL,Female,African-American,11/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +58674,67155,60891,PRETRIAL,DAVIS,GLORISHA,NULL,Female,African-American,11/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,8,High,New,1,0 +58674,67155,60891,PRETRIAL,DAVIS,GLORISHA,NULL,Female,African-American,11/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58663,67143,60880,PRETRIAL,WILLIAMS,KAREEM,RAMON,Male,Other,08/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +58663,67143,60880,PRETRIAL,WILLIAMS,KAREEM,RAMON,Male,Other,08/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +58663,67143,60880,PRETRIAL,WILLIAMS,KAREEM,RAMON,Male,Other,08/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58676,67157,60893,PRETRIAL,Digiulio,Michael,A,Male,Caucasian,01/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +58676,67157,60893,PRETRIAL,Digiulio,Michael,A,Male,Caucasian,01/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +58676,67157,60893,PRETRIAL,Digiulio,Michael,A,Male,Caucasian,01/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58668,67148,60885,PRETRIAL,PRIMOSE,TRACY,NULL,Female,Caucasian,12/12/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/3/13 0:00,2,Medium,7,Risk of Violence,-3.23,1,Low,New,1,0 +58668,67148,60885,PRETRIAL,PRIMOSE,TRACY,NULL,Female,Caucasian,12/12/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +58668,67148,60885,PRETRIAL,PRIMOSE,TRACY,NULL,Female,Caucasian,12/12/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/3/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58702,67178,60914,PRETRIAL,Pericles,Tiffany,NULL,Female,African-American,09/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +58702,67178,60914,PRETRIAL,Pericles,Tiffany,NULL,Female,African-American,09/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +58702,67178,60914,PRETRIAL,Pericles,Tiffany,NULL,Female,African-American,09/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58713,67190,60925,Probation,Urbina,Medardo,NULL,Male,Hispanic,08/08/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +58713,67190,60925,Probation,Urbina,Medardo,NULL,Male,Hispanic,08/08/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +58713,67190,60925,Probation,Urbina,Medardo,NULL,Male,Hispanic,08/08/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +12430,67164,60900,PRETRIAL,EDWARDS,MARCUS,JEROME,Male,African-American,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.88,9,High,New,1,0 +12430,67164,60900,PRETRIAL,EDWARDS,MARCUS,JEROME,Male,African-American,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +12430,67164,60900,PRETRIAL,EDWARDS,MARCUS,JEROME,Male,African-American,01/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +58705,67183,60919,Probation,Richter,Christopher,NULL,Male,Caucasian,08/18/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/4/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +58705,67183,60919,Probation,Richter,Christopher,NULL,Male,Caucasian,08/18/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/4/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +58705,67183,60919,Probation,Richter,Christopher,NULL,Male,Caucasian,08/18/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58679,67162,60898,PRETRIAL,Eppinger,Julius,NULL,Male,African-American,07/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +58679,67162,60898,PRETRIAL,Eppinger,Julius,NULL,Male,African-American,07/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +58679,67162,60898,PRETRIAL,Eppinger,Julius,NULL,Male,African-American,07/31/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58707,67185,60921,PRETRIAL,Milton,Sabrina,NULL,Female,African-American,11/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +58707,67185,60921,PRETRIAL,Milton,Sabrina,NULL,Female,African-American,11/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +58707,67185,60921,PRETRIAL,Milton,Sabrina,NULL,Female,African-American,11/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58716,67195,60930,Probation,Grant,Nicholas,NULL,Male,African-American,11/22/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +58716,67195,60930,Probation,Grant,Nicholas,NULL,Male,African-American,11/22/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +58716,67195,60930,Probation,Grant,Nicholas,NULL,Male,African-American,11/22/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58688,67173,60909,Probation,Pirajan,Peter,NULL,Male,Hispanic,08/15/41,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/13 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +58688,67173,60909,Probation,Pirajan,Peter,NULL,Male,Hispanic,08/15/41,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +58688,67173,60909,Probation,Pirajan,Peter,NULL,Male,Hispanic,08/15/41,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58689,67174,60910,Probation,Lopez,Alberto,NULL,Male,Hispanic,01/24/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +58689,67174,60910,Probation,Lopez,Alberto,NULL,Male,Hispanic,01/24/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +58689,67174,60910,Probation,Lopez,Alberto,NULL,Male,Hispanic,01/24/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58682,67166,60902,Probation,smith,Donald,NULL,Male,Caucasian,10/07/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.45,3,Low,New,1,0 +58682,67166,60902,Probation,smith,Donald,NULL,Male,Caucasian,10/07/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +58682,67166,60902,Probation,smith,Donald,NULL,Male,Caucasian,10/07/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +29581,67160,60896,PRETRIAL,Angelet,Alexander,Steve,Male,Hispanic,06/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +29581,67160,60896,PRETRIAL,Angelet,Alexander,Steve,Male,Hispanic,06/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +29581,67160,60896,PRETRIAL,Angelet,Alexander,Steve,Male,Hispanic,06/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58709,67187,60923,PRETRIAL,WASHINGTON,MARVIS,NULL,Male,African-American,08/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +58709,67187,60923,PRETRIAL,WASHINGTON,MARVIS,NULL,Male,African-American,08/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +58709,67187,60923,PRETRIAL,WASHINGTON,MARVIS,NULL,Male,African-American,08/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58715,67194,60929,Probation,DeJong,Peter,NULL,Male,Caucasian,11/22/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +58715,67194,60929,Probation,DeJong,Peter,NULL,Male,Caucasian,11/22/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +58715,67194,60929,Probation,DeJong,Peter,NULL,Male,Caucasian,11/22/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58706,67184,60920,PRETRIAL,scirghio,jessica,NULL,Female,Caucasian,11/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +58706,67184,60920,PRETRIAL,scirghio,jessica,NULL,Female,Caucasian,11/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +58706,67184,60920,PRETRIAL,scirghio,jessica,NULL,Female,Caucasian,11/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58717,67197,60931,Probation,spenceburrell,nicola,NULL,Female,African-American,06/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/4/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +58717,67197,60931,Probation,spenceburrell,nicola,NULL,Female,African-American,06/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +58717,67197,60931,Probation,spenceburrell,nicola,NULL,Female,African-American,06/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58686,67171,60907,PRETRIAL,DISMUKE,DERRICK,NULL,Male,African-American,06/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +58686,67171,60907,PRETRIAL,DISMUKE,DERRICK,NULL,Male,African-American,06/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +58686,67171,60907,PRETRIAL,DISMUKE,DERRICK,NULL,Male,African-American,06/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58691,67176,60912,Probation,correa,harold,NULL,Male,Caucasian,08/11/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/4/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +58691,67176,60912,Probation,correa,harold,NULL,Male,Caucasian,08/11/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +58691,67176,60912,Probation,correa,harold,NULL,Male,Caucasian,08/11/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58683,67168,60904,PRETRIAL,Hupp,Angie,NULL,Female,Caucasian,04/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/4/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +58683,67168,60904,PRETRIAL,Hupp,Angie,NULL,Female,Caucasian,04/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/4/13 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +58683,67168,60904,PRETRIAL,Hupp,Angie,NULL,Female,Caucasian,04/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +42701,67179,60915,PRETRIAL,Roger,Julia,NULL,Female,Caucasian,06/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/4/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +42701,67179,60915,PRETRIAL,Roger,Julia,NULL,Female,Caucasian,06/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/4/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +42701,67179,60915,PRETRIAL,Roger,Julia,NULL,Female,Caucasian,06/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +18532,67158,60894,PRETRIAL,Thomas,Darius,NULL,Male,African-American,12/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +18532,67158,60894,PRETRIAL,Thomas,Darius,NULL,Male,African-American,12/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.73,10,High,New,1,0 +18532,67158,60894,PRETRIAL,Thomas,Darius,NULL,Male,African-American,12/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +34467,67189,33626,PRETRIAL,Douze,Mike,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,Copy,1,0 +34467,67189,33626,PRETRIAL,Douze,Mike,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,Copy,1,0 +34467,67189,33626,PRETRIAL,Douze,Mike,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +58714,67191,60926,Probation,araya,charlene,NULL,Female,Hispanic,08/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +58714,67191,60926,Probation,araya,charlene,NULL,Female,Hispanic,08/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +58714,67191,60926,Probation,araya,charlene,NULL,Female,Hispanic,08/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +58680,67163,60899,PRETRIAL,Petinaud,Christopher,Troy,Male,Caucasian,09/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/4/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +58680,67163,60899,PRETRIAL,Petinaud,Christopher,Troy,Male,Caucasian,09/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +58680,67163,60899,PRETRIAL,Petinaud,Christopher,Troy,Male,Caucasian,09/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58685,67170,60906,PRETRIAL,LETHBRIDGE,PERRY,NULL,Male,Caucasian,10/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +58685,67170,60906,PRETRIAL,LETHBRIDGE,PERRY,NULL,Male,Caucasian,10/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +58685,67170,60906,PRETRIAL,LETHBRIDGE,PERRY,NULL,Male,Caucasian,10/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58692,67177,60913,PRETRIAL,Bard,Glenn,NULL,Male,Caucasian,02/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/4/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +58692,67177,60913,PRETRIAL,Bard,Glenn,NULL,Male,Caucasian,02/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +58692,67177,60913,PRETRIAL,Bard,Glenn,NULL,Male,Caucasian,02/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58718,67198,60932,Probation,Shin,Hahnan,NULL,Female,Asian,08/30/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +58718,67198,60932,Probation,Shin,Hahnan,NULL,Female,Asian,08/30/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +58718,67198,60932,Probation,Shin,Hahnan,NULL,Female,Asian,08/30/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58720,67200,60934,Probation,Vargas,Yhovanna,NULL,Female,Hispanic,06/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +58720,67200,60934,Probation,Vargas,Yhovanna,NULL,Female,Hispanic,06/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +58720,67200,60934,Probation,Vargas,Yhovanna,NULL,Female,Hispanic,06/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58703,67182,60918,Probation,Axonovitz,Ashley,NULL,Male,Caucasian,08/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +58703,67182,60918,Probation,Axonovitz,Ashley,NULL,Male,Caucasian,08/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +58703,67182,60918,Probation,Axonovitz,Ashley,NULL,Male,Caucasian,08/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +34467,36741,33626,PRETRIAL,Douze,Mike,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +34467,36741,33626,PRETRIAL,Douze,Mike,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +34467,36741,33626,PRETRIAL,Douze,Mike,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58678,67161,60897,PRETRIAL,Lovo,Aaliyah,NULL,Female,Caucasian,11/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +58678,67161,60897,PRETRIAL,Lovo,Aaliyah,NULL,Female,Caucasian,11/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,7,Medium,New,1,0 +58678,67161,60897,PRETRIAL,Lovo,Aaliyah,NULL,Female,Caucasian,11/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51741,67193,60928,Probation,perez,daniel,NULL,Male,Hispanic,03/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/13 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +51741,67193,60928,Probation,perez,daniel,NULL,Male,Hispanic,03/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +51741,67193,60928,Probation,perez,daniel,NULL,Male,Hispanic,03/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58687,67172,60908,Probation,Bradac,Bo,NULL,Male,Caucasian,06/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +58687,67172,60908,Probation,Bradac,Bo,NULL,Male,Caucasian,06/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +58687,67172,60908,Probation,Bradac,Bo,NULL,Male,Caucasian,06/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58690,67175,60911,Probation,Lazaridi,Svetleana,NULL,Female,Caucasian,02/27/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +58690,67175,60911,Probation,Lazaridi,Svetleana,NULL,Female,Caucasian,02/27/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +58690,67175,60911,Probation,Lazaridi,Svetleana,NULL,Female,Caucasian,02/27/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58721,67201,60935,Probation,Osmann,Gary,NULL,Male,African-American,09/20/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +58721,67201,60935,Probation,Osmann,Gary,NULL,Male,African-American,09/20/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +58721,67201,60935,Probation,Osmann,Gary,NULL,Male,African-American,09/20/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58677,67159,60895,PRETRIAL,SOPON,RENEE,JESUS,Male,Other,05/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +58677,67159,60895,PRETRIAL,SOPON,RENEE,JESUS,Male,Other,05/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +58677,67159,60895,PRETRIAL,SOPON,RENEE,JESUS,Male,Other,05/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58728,67209,60943,PRETRIAL,CETOUTE,JARNY,NULL,Male,African-American,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +58728,67209,60943,PRETRIAL,CETOUTE,JARNY,NULL,Male,African-American,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +58728,67209,60943,PRETRIAL,CETOUTE,JARNY,NULL,Male,African-American,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58742,67224,60956,PRETRIAL,JONES,BRIAN,NULL,Male,Caucasian,05/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +58742,67224,60956,PRETRIAL,JONES,BRIAN,NULL,Male,Caucasian,05/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +58742,67224,60956,PRETRIAL,JONES,BRIAN,NULL,Male,Caucasian,05/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58751,67238,60968,Probation,Lawson,Marqueta,NULL,Female,African-American,01/30/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +58751,67238,60968,Probation,Lawson,Marqueta,NULL,Female,African-American,01/30/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +58751,67238,60968,Probation,Lawson,Marqueta,NULL,Female,African-American,01/30/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +30397,67245,60974,PRETRIAL,sartori,daniel,NULL,Male,Caucasian,05/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +30397,67245,60974,PRETRIAL,sartori,daniel,NULL,Male,Caucasian,05/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +30397,67245,60974,PRETRIAL,sartori,daniel,NULL,Male,Caucasian,05/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58054,67230,60237,PRETRIAL,Foy,Patrick,NULL,Male,African-American,02/10/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/13 0:00,4,High,7,Risk of Violence,-1.13,8,High,Copy,1,0 +58054,67230,60237,PRETRIAL,Foy,Patrick,NULL,Male,African-American,02/10/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/13 0:00,4,High,8,Risk of Recidivism,0.71,10,High,Copy,1,0 +58054,67230,60237,PRETRIAL,Foy,Patrick,NULL,Male,African-American,02/10/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +58757,67251,60977,Probation,Tirado,Maria,NULL,Female,Hispanic,01/14/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +58757,67251,60977,Probation,Tirado,Maria,NULL,Female,Hispanic,01/14/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +58757,67251,60977,Probation,Tirado,Maria,NULL,Female,Hispanic,01/14/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +14660,67253,60979,Probation,baldwin,latrice,NULL,Female,African-American,02/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +14660,67253,60979,Probation,baldwin,latrice,NULL,Female,African-American,02/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,9,High,New,1,0 +14660,67253,60979,Probation,baldwin,latrice,NULL,Female,African-American,02/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +58734,67217,60949,PRETRIAL,Agenord,Yvon,NULL,Male,African-American,11/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +58734,67217,60949,PRETRIAL,Agenord,Yvon,NULL,Male,African-American,11/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +58734,67217,60949,PRETRIAL,Agenord,Yvon,NULL,Male,African-American,11/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58747,67235,60965,Probation,Gall,Brook,NULL,Male,Caucasian,11/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +58747,67235,60965,Probation,Gall,Brook,NULL,Male,Caucasian,11/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +58747,67235,60965,Probation,Gall,Brook,NULL,Male,Caucasian,11/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58739,67222,60954,Probation,walcott,devon,l,Male,African-American,05/25/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +58739,67222,60954,Probation,walcott,devon,l,Male,African-American,05/25/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +58739,67222,60954,Probation,walcott,devon,l,Male,African-American,05/25/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58752,67240,60970,Probation,Perez,Alex,NULL,Male,Hispanic,10/28/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +58752,67240,60970,Probation,Perez,Alex,NULL,Male,Hispanic,10/28/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +58752,67240,60970,Probation,Perez,Alex,NULL,Male,Hispanic,10/28/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58754,67243,60972,Probation,Daprix,Peter,NULL,Male,Caucasian,08/09/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,11/5/13 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +58754,67243,60972,Probation,Daprix,Peter,NULL,Male,Caucasian,08/09/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,11/5/13 0:00,1,Low,8,Risk of Recidivism,-2.58,1,Low,New,1,0 +58754,67243,60972,Probation,Daprix,Peter,NULL,Male,Caucasian,08/09/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58759,67254,60980,Probation,Health,Oglathe,NULL,Female,African-American,10/27/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +58759,67254,60980,Probation,Health,Oglathe,NULL,Female,African-American,10/27/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +58759,67254,60980,Probation,Health,Oglathe,NULL,Female,African-American,10/27/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58726,67207,60941,PRETRIAL,Rolle,Deandre,NULL,Male,African-American,09/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +58726,67207,60941,PRETRIAL,Rolle,Deandre,NULL,Male,African-American,09/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +58726,67207,60941,PRETRIAL,Rolle,Deandre,NULL,Male,African-American,09/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58733,67216,60948,PRETRIAL,Jamelle,Tucker,N,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/13 0:00,2,Medium,7,Risk of Violence,-1.39,7,Medium,New,1,0 +58733,67216,60948,PRETRIAL,Jamelle,Tucker,N,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +58733,67216,60948,PRETRIAL,Jamelle,Tucker,N,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +48176,67233,60963,PRETRIAL,HALAN,SHIVRAM,NULL,Male,Other,05/22/66,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +48176,67233,60963,PRETRIAL,HALAN,SHIVRAM,NULL,Male,Other,05/22/66,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +48176,67233,60963,PRETRIAL,HALAN,SHIVRAM,NULL,Male,Other,05/22/66,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58723,67203,60937,PRETRIAL,MARCELLO,JUSTIN,SETH,Male,Caucasian,08/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +58723,67203,60937,PRETRIAL,MARCELLO,JUSTIN,SETH,Male,Caucasian,08/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +58723,67203,60937,PRETRIAL,MARCELLO,JUSTIN,SETH,Male,Caucasian,08/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +56425,67212,58402,Probation,Marinucci,Erika,Lindsey,Female,Caucasian,03/02/77,17,All Scales,Intake,English,Other,Probation,Divorced,11/5/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,Copy,1,0 +56425,67212,58402,Probation,Marinucci,Erika,Lindsey,Female,Caucasian,03/02/77,17,All Scales,Intake,English,Other,Probation,Divorced,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,Copy,1,0 +56425,67212,58402,Probation,Marinucci,Erika,Lindsey,Female,Caucasian,03/02/77,17,All Scales,Intake,English,Other,Probation,Divorced,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +58750,67237,60967,Probation,HARDCASTLE,LUIS,DANIEL,Male,Hispanic,12/24/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +58750,67237,60967,Probation,HARDCASTLE,LUIS,DANIEL,Male,Hispanic,12/24/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +58750,67237,60967,Probation,HARDCASTLE,LUIS,DANIEL,Male,Hispanic,12/24/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58736,67219,60951,PRETRIAL,Evans,Wayne,NULL,Male,African-American,05/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +58736,67219,60951,PRETRIAL,Evans,Wayne,NULL,Male,African-American,05/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +58736,67219,60951,PRETRIAL,Evans,Wayne,NULL,Male,African-American,05/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58738,67221,60953,PRETRIAL,Tiger,James,NULL,Male,Native American,09/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +58738,67221,60953,PRETRIAL,Tiger,James,NULL,Male,Native American,09/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +58738,67221,60953,PRETRIAL,Tiger,James,NULL,Male,Native American,09/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58744,67226,60958,Probation,Araujo,Amin,NULL,Male,Hispanic,01/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +58744,67226,60958,Probation,Araujo,Amin,NULL,Male,Hispanic,01/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +58744,67226,60958,Probation,Araujo,Amin,NULL,Male,Hispanic,01/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58745,67228,60960,Probation,Lexius,Tina,NULL,Female,African-American,01/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +58745,67228,60960,Probation,Lexius,Tina,NULL,Female,African-American,01/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +58745,67228,60960,Probation,Lexius,Tina,NULL,Female,African-American,01/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +22114,67242,21273,PRETRIAL,little,joey,NULL,Male,African-American,06/22/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,Copy,1,0 +22114,67242,21273,PRETRIAL,little,joey,NULL,Male,African-American,06/22/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +22114,67242,21273,PRETRIAL,little,joey,NULL,Male,African-American,06/22/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,2,Low,Copy,1,0 +54345,67239,60969,PRETRIAL,Marciniak,Kristen,NULL,Female,Caucasian,04/06/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +54345,67239,60969,PRETRIAL,Marciniak,Kristen,NULL,Female,Caucasian,04/06/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +54345,67239,60969,PRETRIAL,Marciniak,Kristen,NULL,Female,Caucasian,04/06/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +58735,67218,60950,Probation,Bustillo,Ernesto,NULL,Male,Hispanic,11/29/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +58735,67218,60950,Probation,Bustillo,Ernesto,NULL,Male,Hispanic,11/29/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +58735,67218,60950,Probation,Bustillo,Ernesto,NULL,Male,Hispanic,11/29/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58748,67236,60966,Probation,Hyde,Roy,NULL,Male,Caucasian,12/12/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +58748,67236,60966,Probation,Hyde,Roy,NULL,Male,Caucasian,12/12/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +58748,67236,60966,Probation,Hyde,Roy,NULL,Male,Caucasian,12/12/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58725,67205,60939,PRETRIAL,KENNEDY,DEMEAN,PATRICK,Male,African-American,08/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-1.77,5,Medium,New,1,0 +58725,67205,60939,PRETRIAL,KENNEDY,DEMEAN,PATRICK,Male,African-American,08/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +58725,67205,60939,PRETRIAL,KENNEDY,DEMEAN,PATRICK,Male,African-American,08/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58729,67210,60944,PRETRIAL,StFort,Shantrina,NULL,Female,African-American,06/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +58729,67210,60944,PRETRIAL,StFort,Shantrina,NULL,Female,African-American,06/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +58729,67210,60944,PRETRIAL,StFort,Shantrina,NULL,Female,African-American,06/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58741,67231,60962,PRETRIAL,HARJO,JONATHAN,NULL,Male,Native American,03/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/5/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +58741,67231,60962,PRETRIAL,HARJO,JONATHAN,NULL,Male,Native American,03/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +58741,67231,60962,PRETRIAL,HARJO,JONATHAN,NULL,Male,Native American,03/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58732,67215,60947,Probation,RODRIGUEZ,RYAN,C,Male,Hispanic,07/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,New,1,0 +58732,67215,60947,Probation,RODRIGUEZ,RYAN,C,Male,Hispanic,07/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +58732,67215,60947,Probation,RODRIGUEZ,RYAN,C,Male,Hispanic,07/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58740,67223,60955,Probation,bermudez,HENRY,NULL,Male,Hispanic,03/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/5/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +58740,67223,60955,Probation,bermudez,HENRY,NULL,Male,Hispanic,03/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +58740,67223,60955,Probation,bermudez,HENRY,NULL,Male,Hispanic,03/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58722,67202,60936,PRETRIAL,METAYER,RICHENEL,NULL,Male,Other,04/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/5/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +58722,67202,60936,PRETRIAL,METAYER,RICHENEL,NULL,Male,Other,04/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +58722,67202,60936,PRETRIAL,METAYER,RICHENEL,NULL,Male,Other,04/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58758,67252,60978,Probation,Ramirez,Yraida,NULL,Female,Hispanic,10/11/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +58758,67252,60978,Probation,Ramirez,Yraida,NULL,Female,Hispanic,10/11/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +58758,67252,60978,Probation,Ramirez,Yraida,NULL,Female,Hispanic,10/11/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58760,67255,60981,Probation,Manders,Jake,NULL,Male,Caucasian,05/19/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +58760,67255,60981,Probation,Manders,Jake,NULL,Male,Caucasian,05/19/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +58760,67255,60981,Probation,Manders,Jake,NULL,Male,Caucasian,05/19/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50102,67234,60964,PRETRIAL,Waters,Natalia,NULL,Female,Caucasian,09/19/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +50102,67234,60964,PRETRIAL,Waters,Natalia,NULL,Female,Caucasian,09/19/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +50102,67234,60964,PRETRIAL,Waters,Natalia,NULL,Female,Caucasian,09/19/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55346,67206,60940,Probation,Harris,Shawn,Anthony,Male,African-American,06/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +55346,67206,60940,Probation,Harris,Shawn,Anthony,Male,African-American,06/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +55346,67206,60940,Probation,Harris,Shawn,Anthony,Male,African-American,06/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58753,67241,60971,Probation,PINEDAURREGO,SEBASTIAN,NULL,Male,Hispanic,11/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +58753,67241,60971,Probation,PINEDAURREGO,SEBASTIAN,NULL,Male,Hispanic,11/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +58753,67241,60971,Probation,PINEDAURREGO,SEBASTIAN,NULL,Male,Hispanic,11/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58731,67213,60946,PRETRIAL,Cuellar,Silvio,NULL,Male,Hispanic,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/5/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +58731,67213,60946,PRETRIAL,Cuellar,Silvio,NULL,Male,Hispanic,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +58731,67213,60946,PRETRIAL,Cuellar,Silvio,NULL,Male,Hispanic,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58737,67220,60952,PRETRIAL,WARNER,TUMEKA,NULL,Female,African-American,04/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +58737,67220,60952,PRETRIAL,WARNER,TUMEKA,NULL,Female,African-American,04/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +58737,67220,60952,PRETRIAL,WARNER,TUMEKA,NULL,Female,African-American,04/25/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58727,67208,60942,PRETRIAL,Miller,Trevin,Trammond,Male,African-American,09/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +58727,67208,60942,PRETRIAL,Miller,Trevin,Trammond,Male,African-American,09/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +58727,67208,60942,PRETRIAL,Miller,Trevin,Trammond,Male,African-American,09/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58743,67225,60957,Probation,Vukelich,Theodore,NULL,Male,Caucasian,10/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +58743,67225,60957,Probation,Vukelich,Theodore,NULL,Male,Caucasian,10/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +58743,67225,60957,Probation,Vukelich,Theodore,NULL,Male,Caucasian,10/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58724,67204,60938,PRETRIAL,Vasquezlimas,Rigoberto,NULL,Male,Hispanic,01/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/5/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +58724,67204,60938,PRETRIAL,Vasquezlimas,Rigoberto,NULL,Male,Hispanic,01/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/5/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +58724,67204,60938,PRETRIAL,Vasquezlimas,Rigoberto,NULL,Male,Hispanic,01/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58730,67211,60945,PRETRIAL,torres,arturo,NULL,Male,Hispanic,08/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.43,3,Low,New,1,0 +58730,67211,60945,PRETRIAL,torres,arturo,NULL,Male,Hispanic,08/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +58730,67211,60945,PRETRIAL,torres,arturo,NULL,Male,Hispanic,08/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +43532,67229,60961,Probation,Carr,Elisha,NULL,Female,Caucasian,01/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +43532,67229,60961,Probation,Carr,Elisha,NULL,Female,Caucasian,01/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +43532,67229,60961,Probation,Carr,Elisha,NULL,Female,Caucasian,01/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58755,67246,60975,Probation,Vergara Perez,Jorge,NULL,Male,Hispanic,04/18/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/5/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +58755,67246,60975,Probation,Vergara Perez,Jorge,NULL,Male,Hispanic,04/18/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/5/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +58755,67246,60975,Probation,Vergara Perez,Jorge,NULL,Male,Hispanic,04/18/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58772,67271,60995,Probation,Mody,Anna,NULL,Female,Caucasian,12/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +58772,67271,60995,Probation,Mody,Anna,NULL,Female,Caucasian,12/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +58772,67271,60995,Probation,Mody,Anna,NULL,Female,Caucasian,12/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +58769,67267,60992,Broward County,Neal,Reginald,NULL,Male,African-American,11/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,2,Medium,7,Risk of Violence,-2.77,2,Low,New,1,0 +58769,67267,60992,Broward County,Neal,Reginald,NULL,Male,African-American,11/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +58769,67267,60992,Broward County,Neal,Reginald,NULL,Male,African-American,11/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +14870,67276,61000,PRETRIAL,FABRE,JAMIE,JOHN,Male,Caucasian,07/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +14870,67276,61000,PRETRIAL,FABRE,JAMIE,JOHN,Male,Caucasian,07/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,4,High,8,Risk of Recidivism,0.92,10,High,New,1,0 +14870,67276,61000,PRETRIAL,FABRE,JAMIE,JOHN,Male,Caucasian,07/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58788,67292,61015,Probation,BISHOP,PHILLIP,NULL,Male,Caucasian,05/04/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +58788,67292,61015,Probation,BISHOP,PHILLIP,NULL,Male,Caucasian,05/04/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +58788,67292,61015,Probation,BISHOP,PHILLIP,NULL,Male,Caucasian,05/04/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58169,67264,60370,PRETRIAL,BROOKS,TRAVIS,NULL,Male,African-American,11/21/84,17,All Scales,Intake,English,Pretrial,Residential Program,Single,11/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.08,8,High,New,1,0 +58169,67264,60370,PRETRIAL,BROOKS,TRAVIS,NULL,Male,African-American,11/21/84,17,All Scales,Intake,English,Pretrial,Residential Program,Single,11/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,7,Medium,New,1,0 +58169,67264,60370,PRETRIAL,BROOKS,TRAVIS,NULL,Male,African-American,11/21/84,17,All Scales,Intake,English,Pretrial,Residential Program,Single,11/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,2,Low,New,1,0 +58782,67283,61006,PRETRIAL,Reyna,Tyrone,NULL,Male,Hispanic,06/25/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +58782,67283,61006,PRETRIAL,Reyna,Tyrone,NULL,Male,Hispanic,06/25/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +58782,67283,61006,PRETRIAL,Reyna,Tyrone,NULL,Male,Hispanic,06/25/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58765,67262,60988,PRETRIAL,Wyatt,Paul,NULL,Male,Caucasian,09/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +58765,67262,60988,PRETRIAL,Wyatt,Paul,NULL,Male,Caucasian,09/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +58765,67262,60988,PRETRIAL,Wyatt,Paul,NULL,Male,Caucasian,09/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +20612,67285,61008,PRETRIAL,Assad,Gibran,NULL,Male,African-American,10/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +20612,67285,61008,PRETRIAL,Assad,Gibran,NULL,Male,African-American,10/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +20612,67285,61008,PRETRIAL,Assad,Gibran,NULL,Male,African-American,10/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58785,67288,61011,Probation,McCoy,Charles,NULL,Male,African-American,11/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +58785,67288,61011,Probation,McCoy,Charles,NULL,Male,African-American,11/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +58785,67288,61011,Probation,McCoy,Charles,NULL,Male,African-American,11/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58774,67273,60997,Probation,Cardona,Manuela,NULL,Female,Hispanic,05/25/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +58774,67273,60997,Probation,Cardona,Manuela,NULL,Female,Hispanic,05/25/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +58774,67273,60997,Probation,Cardona,Manuela,NULL,Female,Hispanic,05/25/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58780,67281,61004,Probation,Joseph,Sem,NULL,Male,African-American,12/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/6/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +58780,67281,61004,Probation,Joseph,Sem,NULL,Male,African-American,12/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/6/13 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +58780,67281,61004,Probation,Joseph,Sem,NULL,Male,African-American,12/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56322,67260,60986,PRETRIAL,BLOUNT,JATEZ,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +56322,67260,60986,PRETRIAL,BLOUNT,JATEZ,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +56322,67260,60986,PRETRIAL,BLOUNT,JATEZ,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58767,67265,60990,Probation,white,william,l,Male,Caucasian,06/18/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,2,Medium,7,Risk of Violence,-2.84,2,Low,New,1,0 +58767,67265,60990,Probation,white,william,l,Male,Caucasian,06/18/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +58767,67265,60990,Probation,white,william,l,Male,Caucasian,06/18/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58778,67278,61002,Probation,GABBIDON,KIERA,C,Female,African-American,12/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +58778,67278,61002,Probation,GABBIDON,KIERA,C,Female,African-American,12/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +58778,67278,61002,Probation,GABBIDON,KIERA,C,Female,African-American,12/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +20905,67286,61009,PRETRIAL,Nguyen,Hieu,NULL,Male,Asian,10/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +20905,67286,61009,PRETRIAL,Nguyen,Hieu,NULL,Male,Asian,10/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +20905,67286,61009,PRETRIAL,Nguyen,Hieu,NULL,Male,Asian,10/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58762,67257,60983,PRETRIAL,Rodriguez,Robert,NULL,Male,Hispanic,01/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +58762,67257,60983,PRETRIAL,Rodriguez,Robert,NULL,Male,Hispanic,01/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +58762,67257,60983,PRETRIAL,Rodriguez,Robert,NULL,Male,Hispanic,01/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58761,67256,60982,PRETRIAL,Martinez,Jose,NULL,Male,Hispanic,12/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +58761,67256,60982,PRETRIAL,Martinez,Jose,NULL,Male,Hispanic,12/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +58761,67256,60982,PRETRIAL,Martinez,Jose,NULL,Male,Hispanic,12/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58766,67263,60989,Probation,Pascal,Emmanuella,NULL,Female,African-American,10/31/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +58766,67263,60989,Probation,Pascal,Emmanuella,NULL,Female,African-American,10/31/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +58766,67263,60989,Probation,Pascal,Emmanuella,NULL,Female,African-American,10/31/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58771,67270,60994,Probation,SIMON,CASEY,LYNN,Female,Caucasian,08/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +58771,67270,60994,Probation,SIMON,CASEY,LYNN,Female,Caucasian,08/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +58771,67270,60994,Probation,SIMON,CASEY,LYNN,Female,Caucasian,08/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58777,67277,61001,PRETRIAL,Alvarez,Rodney,NULL,Male,African-American,10/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +58777,67277,61001,PRETRIAL,Alvarez,Rodney,NULL,Male,African-American,10/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +58777,67277,61001,PRETRIAL,Alvarez,Rodney,NULL,Male,African-American,10/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +4334,50173,4037,Probation,Murdough,Michael,John,Male,Caucasian,09/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +4334,50173,4037,Probation,Murdough,Michael,John,Male,Caucasian,09/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +4334,50173,4037,Probation,Murdough,Michael,John,Male,Caucasian,09/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58783,67284,61007,PRETRIAL,guerrier,rick,NULL,Male,African-American,02/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +58783,67284,61007,PRETRIAL,guerrier,rick,NULL,Male,African-American,02/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +58783,67284,61007,PRETRIAL,guerrier,rick,NULL,Male,African-American,02/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +58763,67258,60984,PRETRIAL,Dpugh,Richard,NULL,Male,Caucasian,10/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +58763,67258,60984,PRETRIAL,Dpugh,Richard,NULL,Male,Caucasian,10/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +58763,67258,60984,PRETRIAL,Dpugh,Richard,NULL,Male,Caucasian,10/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +58773,67272,60996,PRETRIAL,Clarke,Samuel,Ray,Male,African-American,09/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +58773,67272,60996,PRETRIAL,Clarke,Samuel,Ray,Male,African-American,09/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +58773,67272,60996,PRETRIAL,Clarke,Samuel,Ray,Male,African-American,09/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58776,67275,60999,PRETRIAL,Shield,Edmond,NULL,Male,African-American,09/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/6/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +58776,67275,60999,PRETRIAL,Shield,Edmond,NULL,Male,African-American,09/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/6/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +58776,67275,60999,PRETRIAL,Shield,Edmond,NULL,Male,African-American,09/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58786,67289,61012,Probation,Singh,Alvin,NULL,Male,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +58786,67289,61012,Probation,Singh,Alvin,NULL,Male,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +58786,67289,61012,Probation,Singh,Alvin,NULL,Male,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58770,67268,60993,Probation,Moscoso,Monica,NULL,Female,Hispanic,09/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +58770,67268,60993,Probation,Moscoso,Monica,NULL,Female,Hispanic,09/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +58770,67268,60993,Probation,Moscoso,Monica,NULL,Female,Hispanic,09/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58779,67279,61003,PRETRIAL,Baker,Shakennea,NULL,Female,African-American,12/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/6/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +58779,67279,61003,PRETRIAL,Baker,Shakennea,NULL,Female,African-American,12/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/6/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +58779,67279,61003,PRETRIAL,Baker,Shakennea,NULL,Female,African-American,12/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58789,67293,61016,PRETRIAL,MILLER,WILLIAM,JAMES,Male,Caucasian,05/17/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +58789,67293,61016,PRETRIAL,MILLER,WILLIAM,JAMES,Male,Caucasian,05/17/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +58789,67293,61016,PRETRIAL,MILLER,WILLIAM,JAMES,Male,Caucasian,05/17/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51678,67261,60987,PRETRIAL,Leal,Justin,NULL,Male,Caucasian,01/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,4,High,7,Risk of Violence,-0.65,9,High,New,1,0 +51678,67261,60987,PRETRIAL,Leal,Justin,NULL,Male,Caucasian,01/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +51678,67261,60987,PRETRIAL,Leal,Justin,NULL,Male,Caucasian,01/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +18129,67290,61013,Probation,Goldshot,Michael,NULL,Male,Caucasian,09/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +18129,67290,61013,Probation,Goldshot,Michael,NULL,Male,Caucasian,09/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +18129,67290,61013,Probation,Goldshot,Michael,NULL,Male,Caucasian,09/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +17178,67269,16472,PRETRIAL,Givens,Tracey,NULL,Male,African-American,08/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,Copy,1,0 +17178,67269,16472,PRETRIAL,Givens,Tracey,NULL,Male,African-American,08/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,Copy,1,0 +17178,67269,16472,PRETRIAL,Givens,Tracey,NULL,Male,African-American,08/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,39,10,High,Copy,1,0 +58768,67266,60991,Probation,Stone,Zachary,NULL,Male,Caucasian,07/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +58768,67266,60991,Probation,Stone,Zachary,NULL,Male,Caucasian,07/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +58768,67266,60991,Probation,Stone,Zachary,NULL,Male,Caucasian,07/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58784,67287,61010,Probation,Fredericks,Lynisha,NULL,Female,African-American,06/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +58784,67287,61010,Probation,Fredericks,Lynisha,NULL,Female,African-American,06/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +58784,67287,61010,Probation,Fredericks,Lynisha,NULL,Female,African-American,06/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58764,67259,60985,PRETRIAL,RAYMONDVIL,OLVINS,MICHAEL,Male,African-American,03/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +58764,67259,60985,PRETRIAL,RAYMONDVIL,OLVINS,MICHAEL,Male,African-American,03/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,4,High,8,Risk of Recidivism,0.14,8,High,New,1,0 +58764,67259,60985,PRETRIAL,RAYMONDVIL,OLVINS,MICHAEL,Male,African-American,03/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58775,67274,60998,Probation,Quince,William,NULL,Male,African-American,06/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +58775,67274,60998,Probation,Quince,William,NULL,Male,African-American,06/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +58775,67274,60998,Probation,Quince,William,NULL,Male,African-American,06/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58815,67324,61045,Probation,Zurbaran,Adriana,Giselle,Female,Hispanic,06/10/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +58815,67324,61045,Probation,Zurbaran,Adriana,Giselle,Female,Hispanic,06/10/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +58815,67324,61045,Probation,Zurbaran,Adriana,Giselle,Female,Hispanic,06/10/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58791,67295,61018,PRETRIAL,Jean,Marsofia,Berline,Female,African-American,04/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +58791,67295,61018,PRETRIAL,Jean,Marsofia,Berline,Female,African-American,04/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +58791,67295,61018,PRETRIAL,Jean,Marsofia,Berline,Female,African-American,04/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58822,67332,61052,Probation,Casey,Christopher,NULL,Male,Caucasian,12/23/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +58822,67332,61052,Probation,Casey,Christopher,NULL,Male,Caucasian,12/23/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +58822,67332,61052,Probation,Casey,Christopher,NULL,Male,Caucasian,12/23/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58797,67303,61025,PRETRIAL,FORTE,ANTHONY,NULL,Male,Caucasian,03/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +58797,67303,61025,PRETRIAL,FORTE,ANTHONY,NULL,Male,Caucasian,03/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +58797,67303,61025,PRETRIAL,FORTE,ANTHONY,NULL,Male,Caucasian,03/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58808,67316,61037,Probation,DIAZ,ROBERTO,NULL,Male,Hispanic,11/11/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +58808,67316,61037,Probation,DIAZ,ROBERTO,NULL,Male,Hispanic,11/11/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +58808,67316,61037,Probation,DIAZ,ROBERTO,NULL,Male,Hispanic,11/11/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58802,67308,61030,Probation,Navarro,Laydel,NULL,Female,Hispanic,10/27/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +58802,67308,61030,Probation,Navarro,Laydel,NULL,Female,Hispanic,10/27/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +58802,67308,61030,Probation,Navarro,Laydel,NULL,Female,Hispanic,10/27/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58805,67311,61033,PRETRIAL,hussain,mansoor,NULL,Male,Caucasian,06/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/7/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +58805,67311,61033,PRETRIAL,hussain,mansoor,NULL,Male,Caucasian,06/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/7/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +58805,67311,61033,PRETRIAL,hussain,mansoor,NULL,Male,Caucasian,06/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58817,67326,61047,PRETRIAL,Mcphee,Ebony,NULL,Female,African-American,10/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +58817,67326,61047,PRETRIAL,Mcphee,Ebony,NULL,Female,African-American,10/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +58817,67326,61047,PRETRIAL,Mcphee,Ebony,NULL,Female,African-American,10/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +29359,67331,61051,Probation,maranon,melissa,NULL,Female,Hispanic,01/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +29359,67331,61051,Probation,maranon,melissa,NULL,Female,Hispanic,01/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +29359,67331,61051,Probation,maranon,melissa,NULL,Female,Hispanic,01/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58799,67305,61027,Probation,Jackson,japhus,NULL,Male,African-American,01/11/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +58799,67305,61027,Probation,Jackson,japhus,NULL,Male,African-American,01/11/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +58799,67305,61027,Probation,Jackson,japhus,NULL,Male,African-American,01/11/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58811,67319,61040,Probation,beckford,lois,NULL,Male,African-American,09/10/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +58811,67319,61040,Probation,beckford,lois,NULL,Male,African-American,09/10/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +58811,67319,61040,Probation,beckford,lois,NULL,Male,African-American,09/10/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58812,67321,61042,Probation,Dahle,Kim,NULL,Female,Caucasian,01/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +58812,67321,61042,Probation,Dahle,Kim,NULL,Female,Caucasian,01/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +58812,67321,61042,Probation,Dahle,Kim,NULL,Female,Caucasian,01/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57921,67328,61049,Probation,Owens,Kennard,NULL,Male,African-American,11/08/83,17,All Scales,Intake,English,Other,Probation,Single,11/7/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +57921,67328,61049,Probation,Owens,Kennard,NULL,Male,African-American,11/08/83,17,All Scales,Intake,English,Other,Probation,Single,11/7/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +57921,67328,61049,Probation,Owens,Kennard,NULL,Male,African-American,11/08/83,17,All Scales,Intake,English,Other,Probation,Single,11/7/13 0:00,2,Medium,18,Risk of Failure to Appear,21,3,Low,New,1,0 +58793,67298,61021,PRETRIAL,WILLIAMS,TWANA,YVETTE,Female,African-American,03/11/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +58793,67298,61021,PRETRIAL,WILLIAMS,TWANA,YVETTE,Female,African-American,03/11/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +58793,67298,61021,PRETRIAL,WILLIAMS,TWANA,YVETTE,Female,African-American,03/11/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +7481,67300,37973,PRETRIAL,SAO,OMAR,LEE,Male,Caucasian,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/7/13 0:00,4,High,7,Risk of Violence,-1.14,8,High,Copy,1,0 +7481,67300,37973,PRETRIAL,SAO,OMAR,LEE,Male,Caucasian,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/7/13 0:00,4,High,8,Risk of Recidivism,0.47,9,High,Copy,1,0 +7481,67300,37973,PRETRIAL,SAO,OMAR,LEE,Male,Caucasian,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/7/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +58801,67307,61029,Probation,Zahariev,Radomir,NULL,Male,Arabic,01/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.91,5,Medium,New,1,0 +58801,67307,61029,Probation,Zahariev,Radomir,NULL,Male,Arabic,01/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +58801,67307,61029,Probation,Zahariev,Radomir,NULL,Male,Arabic,01/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58816,67325,61046,Probation,MOLINA,NANCY,C,Female,Hispanic,09/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +58816,67325,61046,Probation,MOLINA,NANCY,C,Female,Hispanic,09/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +58816,67325,61046,Probation,MOLINA,NANCY,C,Female,Hispanic,09/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58798,67304,61026,Probation,Jagat,Harry,Harpeo,Male,Asian,02/14/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/7/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +58798,67304,61026,Probation,Jagat,Harry,Harpeo,Male,Asian,02/14/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/7/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +58798,67304,61026,Probation,Jagat,Harry,Harpeo,Male,Asian,02/14/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53280,67312,61034,PRETRIAL,Montgomery,Mark,NULL,Male,African-American,11/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.21,4,Low,New,1,0 +53280,67312,61034,PRETRIAL,Montgomery,Mark,NULL,Male,African-American,11/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +53280,67312,61034,PRETRIAL,Montgomery,Mark,NULL,Male,African-American,11/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58794,67299,61022,PRETRIAL,Yamin,Robert,Paul,Male,Caucasian,06/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +58794,67299,61022,PRETRIAL,Yamin,Robert,Paul,Male,Caucasian,06/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +58794,67299,61022,PRETRIAL,Yamin,Robert,Paul,Male,Caucasian,06/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58821,67333,61053,Probation,Negrinaguirre,Juan,NULL,Male,Hispanic,02/13/52,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +58821,67333,61053,Probation,Negrinaguirre,Juan,NULL,Male,Hispanic,02/13/52,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +58821,67333,61053,Probation,Negrinaguirre,Juan,NULL,Male,Hispanic,02/13/52,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58790,67294,61017,PRETRIAL,JOHNSON,MERDIS,NULL,Female,African-American,06/08/41,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +58790,67294,61017,PRETRIAL,JOHNSON,MERDIS,NULL,Female,African-American,06/08/41,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +58790,67294,61017,PRETRIAL,JOHNSON,MERDIS,NULL,Female,African-American,06/08/41,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58792,67296,61019,PRETRIAL,Hansen,Kyle,NULL,Male,Caucasian,04/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +58792,67296,61019,PRETRIAL,Hansen,Kyle,NULL,Male,Caucasian,04/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +58792,67296,61019,PRETRIAL,Hansen,Kyle,NULL,Male,Caucasian,04/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58820,67330,61050,Probation,Barrios,Alexander,NULL,Male,Hispanic,05/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +58820,67330,61050,Probation,Barrios,Alexander,NULL,Male,Hispanic,05/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +58820,67330,61050,Probation,Barrios,Alexander,NULL,Male,Hispanic,05/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58807,67315,61036,Probation,Santos,Amilcar,NULL,Male,Hispanic,12/03/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +58807,67315,61036,Probation,Santos,Amilcar,NULL,Male,Hispanic,12/03/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +58807,67315,61036,Probation,Santos,Amilcar,NULL,Male,Hispanic,12/03/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +46473,67317,61038,PRETRIAL,WILSON,RASHAAD,DWAYNE,Male,African-American,03/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +46473,67317,61038,PRETRIAL,WILSON,RASHAAD,DWAYNE,Male,African-American,03/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +46473,67317,61038,PRETRIAL,WILSON,RASHAAD,DWAYNE,Male,African-American,03/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58803,67309,61031,Probation,Ramautar,Rajindra,NULL,Male,Other,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.47,3,Low,New,1,0 +58803,67309,61031,Probation,Ramautar,Rajindra,NULL,Male,Other,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +58803,67309,61031,Probation,Ramautar,Rajindra,NULL,Male,Other,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58814,67323,61044,Probation,Olmedo,Jorge Santos,NULL,Male,Hispanic,07/29/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +58814,67323,61044,Probation,Olmedo,Jorge Santos,NULL,Male,Hispanic,07/29/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +58814,67323,61044,Probation,Olmedo,Jorge Santos,NULL,Male,Hispanic,07/29/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58796,67302,61024,PRETRIAL,Bowens,Jermaine,Rashard,Male,African-American,04/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +58796,67302,61024,PRETRIAL,Bowens,Jermaine,Rashard,Male,African-American,04/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +58796,67302,61024,PRETRIAL,Bowens,Jermaine,Rashard,Male,African-American,04/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58800,67306,61028,Probation,borrell,jaime,NULL,Male,Caucasian,06/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +58800,67306,61028,Probation,borrell,jaime,NULL,Male,Caucasian,06/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +58800,67306,61028,Probation,borrell,jaime,NULL,Male,Caucasian,06/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58806,67313,61035,PRETRIAL,Darby,Kevin,NULL,Male,Caucasian,09/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +58806,67313,61035,PRETRIAL,Darby,Kevin,NULL,Male,Caucasian,09/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +58806,67313,61035,PRETRIAL,Darby,Kevin,NULL,Male,Caucasian,09/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +30829,67320,61041,Probation,masis,liljana,NULL,Female,Hispanic,06/05/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/7/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +30829,67320,61041,Probation,masis,liljana,NULL,Female,Hispanic,06/05/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/7/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +30829,67320,61041,Probation,masis,liljana,NULL,Female,Hispanic,06/05/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58818,67327,61048,Probation,DAVIS,ALPHEUS,NULL,Male,African-American,08/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +58818,67327,61048,Probation,DAVIS,ALPHEUS,NULL,Male,African-American,08/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +58818,67327,61048,Probation,DAVIS,ALPHEUS,NULL,Male,African-American,08/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58813,67322,61043,Probation,BLANC,JEAN,G,Male,African-American,01/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +58813,67322,61043,Probation,BLANC,JEAN,G,Male,African-American,01/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +58813,67322,61043,Probation,BLANC,JEAN,G,Male,African-American,01/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58810,67318,61039,DRRD,Allen,Onarjai,Oneil,Male,African-American,08/07/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,11/7/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +58810,67318,61039,DRRD,Allen,Onarjai,Oneil,Male,African-American,08/07/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,11/7/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +58810,67318,61039,DRRD,Allen,Onarjai,Oneil,Male,African-American,08/07/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,11/7/13 0:00,2,Medium,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +50027,67297,61020,PRETRIAL,MUNOZ,DIANA,MAE,Female,Caucasian,08/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +50027,67297,61020,PRETRIAL,MUNOZ,DIANA,MAE,Female,Caucasian,08/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +50027,67297,61020,PRETRIAL,MUNOZ,DIANA,MAE,Female,Caucasian,08/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58795,67301,61023,PRETRIAL,Mckennie,Edward,NULL,Male,African-American,09/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +58795,67301,61023,PRETRIAL,Mckennie,Edward,NULL,Male,African-American,09/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +58795,67301,61023,PRETRIAL,Mckennie,Edward,NULL,Male,African-American,09/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +58834,67348,61066,Probation,Rivers,Shakay,NULL,Female,African-American,01/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +58834,67348,61066,Probation,Rivers,Shakay,NULL,Female,African-American,01/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +58834,67348,61066,Probation,Rivers,Shakay,NULL,Female,African-American,01/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58825,67336,61056,PRETRIAL,Shirley,Patrick,Everette,Male,African-American,05/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +58825,67336,61056,PRETRIAL,Shirley,Patrick,Everette,Male,African-American,05/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +58825,67336,61056,PRETRIAL,Shirley,Patrick,Everette,Male,African-American,05/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58831,67343,61063,Probation,RODRIGUEZ,ROBERTO,NULL,Male,African-American,12/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +58831,67343,61063,Probation,RODRIGUEZ,ROBERTO,NULL,Male,African-American,12/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +58831,67343,61063,Probation,RODRIGUEZ,ROBERTO,NULL,Male,African-American,12/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58828,67339,61059,PRETRIAL,Casaberry,Pentara,NULL,Female,African-American,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +58828,67339,61059,PRETRIAL,Casaberry,Pentara,NULL,Female,African-American,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +58828,67339,61059,PRETRIAL,Casaberry,Pentara,NULL,Female,African-American,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58841,67357,61074,Probation,Nicoletti,Gino,NULL,Male,Oriental,01/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +58841,67357,61074,Probation,Nicoletti,Gino,NULL,Male,Oriental,01/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +58841,67357,61074,Probation,Nicoletti,Gino,NULL,Male,Oriental,01/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58829,67341,61061,PRETRIAL,harvey,stephanie,NULL,Female,Caucasian,08/31/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +58829,67341,61061,PRETRIAL,harvey,stephanie,NULL,Female,Caucasian,08/31/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +58829,67341,61061,PRETRIAL,harvey,stephanie,NULL,Female,Caucasian,08/31/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58838,67355,61072,Probation,Dale,Nyasha,NULL,Female,African-American,04/16/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/8/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +58838,67355,61072,Probation,Dale,Nyasha,NULL,Female,African-American,04/16/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,7,Medium,New,1,0 +58838,67355,61072,Probation,Dale,Nyasha,NULL,Female,African-American,04/16/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/8/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58845,67362,61079,PRETRIAL,RUSSELL,MARLENE,NULL,Female,African-American,04/11/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +58845,67362,61079,PRETRIAL,RUSSELL,MARLENE,NULL,Female,African-American,04/11/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +58845,67362,61079,PRETRIAL,RUSSELL,MARLENE,NULL,Female,African-American,04/11/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58823,67334,61054,PRETRIAL,Royer,Amy,NULL,Female,African-American,09/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/8/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +58823,67334,61054,PRETRIAL,Royer,Amy,NULL,Female,African-American,09/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/8/13 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +58823,67334,61054,PRETRIAL,Royer,Amy,NULL,Female,African-American,09/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58847,67364,61081,Probation,Bankston,Kenneth,NULL,Male,African-American,10/04/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/8/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +58847,67364,61081,Probation,Bankston,Kenneth,NULL,Male,African-American,10/04/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/8/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +58847,67364,61081,Probation,Bankston,Kenneth,NULL,Male,African-American,10/04/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58827,67338,61058,PRETRIAL,McCarthy,Janet,NULL,Male,Caucasian,08/19/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +58827,67338,61058,PRETRIAL,McCarthy,Janet,NULL,Male,Caucasian,08/19/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +58827,67338,61058,PRETRIAL,McCarthy,Janet,NULL,Male,Caucasian,08/19/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +47063,67359,61076,PRETRIAL,Alvarez,Dandre,Dantae,Male,African-American,09/25/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +47063,67359,61076,PRETRIAL,Alvarez,Dandre,Dantae,Male,African-American,09/25/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +47063,67359,61076,PRETRIAL,Alvarez,Dandre,Dantae,Male,African-American,09/25/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58020,67351,60199,Probation,collins,kiandra,NULL,Female,African-American,10/18/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,11/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,New,1,0 +58020,67351,60199,Probation,collins,kiandra,NULL,Female,African-American,10/18/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,11/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,10,High,New,1,0 +58020,67351,60199,Probation,collins,kiandra,NULL,Female,African-American,10/18/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,11/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +3288,67367,61084,PRETRIAL,Levy,Steven,Neville,Male,Caucasian,03/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +3288,67367,61084,PRETRIAL,Levy,Steven,Neville,Male,Caucasian,03/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +3288,67367,61084,PRETRIAL,Levy,Steven,Neville,Male,Caucasian,03/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58832,67346,61064,Probation,Turner,Charles,NULL,Male,Caucasian,03/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +58832,67346,61064,Probation,Turner,Charles,NULL,Male,Caucasian,03/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +58832,67346,61064,Probation,Turner,Charles,NULL,Male,Caucasian,03/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58839,67354,61071,Probation,Behari,Donna,NULL,Female,Other,03/19/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/8/13 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +58839,67354,61071,Probation,Behari,Donna,NULL,Female,Other,03/19/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/8/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +58839,67354,61071,Probation,Behari,Donna,NULL,Female,Other,03/19/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58853,67372,61089,PRETRIAL,Gonzales,Rachel,NULL,Male,Caucasian,09/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +58853,67372,61089,PRETRIAL,Gonzales,Rachel,NULL,Male,Caucasian,09/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +58853,67372,61089,PRETRIAL,Gonzales,Rachel,NULL,Male,Caucasian,09/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58835,67349,61067,PRETRIAL,dacosta,darren,NULL,Male,African-American,12/16/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +58835,67349,61067,PRETRIAL,dacosta,darren,NULL,Male,African-American,12/16/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.41,4,Low,New,1,0 +58835,67349,61067,PRETRIAL,dacosta,darren,NULL,Male,African-American,12/16/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58846,67363,61080,PRETRIAL,HANNAH,ASHLEY,NULL,Female,African-American,10/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +58846,67363,61080,PRETRIAL,HANNAH,ASHLEY,NULL,Female,African-American,10/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +58846,67363,61080,PRETRIAL,HANNAH,ASHLEY,NULL,Female,African-American,10/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +32960,67370,61087,PRETRIAL,KLINE,ALEXANDER,GEORGE,Male,African-American,08/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.07,4,Low,New,1,0 +32960,67370,61087,PRETRIAL,KLINE,ALEXANDER,GEORGE,Male,African-American,08/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +32960,67370,61087,PRETRIAL,KLINE,ALEXANDER,GEORGE,Male,African-American,08/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58830,67342,61062,PRETRIAL,LUTI,ANGIE,NULL,Female,Caucasian,04/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/8/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +58830,67342,61062,PRETRIAL,LUTI,ANGIE,NULL,Female,Caucasian,04/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/8/13 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +58830,67342,61062,PRETRIAL,LUTI,ANGIE,NULL,Female,Caucasian,04/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58840,67356,61073,PRETRIAL,koons,lori,NULL,Female,Caucasian,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,2,Medium,7,Risk of Violence,-2.83,2,Low,New,1,0 +58840,67356,61073,PRETRIAL,koons,lori,NULL,Female,Caucasian,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +58840,67356,61073,PRETRIAL,koons,lori,NULL,Female,Caucasian,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,New,1,0 +58824,67335,61055,PRETRIAL,Jones,David,Demetrius,Male,African-American,04/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +58824,67335,61055,PRETRIAL,Jones,David,Demetrius,Male,African-American,04/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +58824,67335,61055,PRETRIAL,Jones,David,Demetrius,Male,African-American,04/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58848,67365,61082,Probation,WILLIAMS,LATOSHA,NULL,Female,African-American,11/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +58848,67365,61082,Probation,WILLIAMS,LATOSHA,NULL,Female,African-American,11/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +58848,67365,61082,Probation,WILLIAMS,LATOSHA,NULL,Female,African-American,11/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +41373,67340,61060,PRETRIAL,Grant,Wade,Nicolas,Male,African-American,03/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/8/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +41373,67340,61060,PRETRIAL,Grant,Wade,Nicolas,Male,African-American,03/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/8/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +41373,67340,61060,PRETRIAL,Grant,Wade,Nicolas,Male,African-American,03/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58833,67347,61065,Probation,Londono,Leonardo,NULL,Male,Hispanic,09/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/8/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +58833,67347,61065,Probation,Londono,Leonardo,NULL,Male,Hispanic,09/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/8/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +58833,67347,61065,Probation,Londono,Leonardo,NULL,Male,Hispanic,09/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58844,67361,61078,Probation,BOLANOS,ROLANDO,ANGEL,Male,Hispanic,09/18/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/8/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +58844,67361,61078,Probation,BOLANOS,ROLANDO,ANGEL,Male,Hispanic,09/18/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +58844,67361,61078,Probation,BOLANOS,ROLANDO,ANGEL,Male,Hispanic,09/18/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/8/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58850,67368,61085,Probation,Buitrago,luis,Eduardo,Male,Hispanic,02/10/67,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/8/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +58850,67368,61085,Probation,Buitrago,luis,Eduardo,Male,Hispanic,02/10/67,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/8/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +58850,67368,61085,Probation,Buitrago,luis,Eduardo,Male,Hispanic,02/10/67,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58842,67358,61075,Probation,Leon,Miriam,NULL,Female,Caucasian,09/22/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/8/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +58842,67358,61075,Probation,Leon,Miriam,NULL,Female,Caucasian,09/22/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/8/13 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +58842,67358,61075,Probation,Leon,Miriam,NULL,Female,Caucasian,09/22/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58826,67337,61057,PRETRIAL,Lyerla,Crystal,Ann,Female,Caucasian,06/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/8/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +58826,67337,61057,PRETRIAL,Lyerla,Crystal,Ann,Female,Caucasian,06/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/8/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +58826,67337,61057,PRETRIAL,Lyerla,Crystal,Ann,Female,Caucasian,06/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58852,67371,61088,PRETRIAL,kingery,robert,NULL,Male,Caucasian,05/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +58852,67371,61088,PRETRIAL,kingery,robert,NULL,Male,Caucasian,05/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +58852,67371,61088,PRETRIAL,kingery,robert,NULL,Male,Caucasian,05/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58849,67366,61083,Probation,Bazelais,Richard,NULL,Male,African-American,11/10/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +58849,67366,61083,Probation,Bazelais,Richard,NULL,Male,African-American,11/10/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +58849,67366,61083,Probation,Bazelais,Richard,NULL,Male,African-American,11/10/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58837,67353,61070,Probation,JEAN,WILSON,NULL,Male,African-American,09/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +58837,67353,61070,Probation,JEAN,WILSON,NULL,Male,African-American,09/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +58837,67353,61070,Probation,JEAN,WILSON,NULL,Male,African-American,09/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58843,67360,61077,Probation,Cantillano,Sobeyda,NULL,Female,Hispanic,11/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/8/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +58843,67360,61077,Probation,Cantillano,Sobeyda,NULL,Female,Hispanic,11/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/8/13 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +58843,67360,61077,Probation,Cantillano,Sobeyda,NULL,Female,Hispanic,11/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +34034,67345,42731,PRETRIAL,Sarner,Sylvia,NULL,Male,Caucasian,01/23/45,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-4.47,1,Low,Copy,1,0 +34034,67345,42731,PRETRIAL,Sarner,Sylvia,NULL,Male,Caucasian,01/23/45,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,Copy,1,0 +34034,67345,42731,PRETRIAL,Sarner,Sylvia,NULL,Male,Caucasian,01/23/45,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +58836,67352,61069,Probation,Bocelli,Mark,NULL,Male,Caucasian,11/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +58836,67352,61069,Probation,Bocelli,Mark,NULL,Male,Caucasian,11/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +58836,67352,61069,Probation,Bocelli,Mark,NULL,Male,Caucasian,11/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/8/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58854,67373,61090,PRETRIAL,Myers,Anthony,NULL,Male,African-American,07/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +58854,67373,61090,PRETRIAL,Myers,Anthony,NULL,Male,African-American,07/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +58854,67373,61090,PRETRIAL,Myers,Anthony,NULL,Male,African-American,07/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58855,67374,61091,PRETRIAL,Higgs,Tiara,NULL,Female,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +58855,67374,61091,PRETRIAL,Higgs,Tiara,NULL,Female,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +58855,67374,61091,PRETRIAL,Higgs,Tiara,NULL,Female,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +42627,67387,49539,PRETRIAL,Smith,Sheri,NULL,Male,African-American,06/23/77,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,11/9/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,Copy,1,0 +42627,67387,49539,PRETRIAL,Smith,Sheri,NULL,Male,African-American,06/23/77,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,11/9/13 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,Copy,1,0 +42627,67387,49539,PRETRIAL,Smith,Sheri,NULL,Male,African-American,06/23/77,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,11/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +58860,67381,61097,PRETRIAL,SHAMARK,DONTRAY,BLACKSHEAR,Male,African-American,10/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.62,2,Low,New,1,0 +58860,67381,61097,PRETRIAL,SHAMARK,DONTRAY,BLACKSHEAR,Male,African-American,10/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +58860,67381,61097,PRETRIAL,SHAMARK,DONTRAY,BLACKSHEAR,Male,African-American,10/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58863,67384,61100,PRETRIAL,Jenkins,Christopher,Jesse,Male,African-American,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +58863,67384,61100,PRETRIAL,Jenkins,Christopher,Jesse,Male,African-American,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,New,1,0 +58863,67384,61100,PRETRIAL,Jenkins,Christopher,Jesse,Male,African-American,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58857,67376,61093,PRETRIAL,Moise,David,Atkins,Male,African-American,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +58857,67376,61093,PRETRIAL,Moise,David,Atkins,Male,African-American,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +58857,67376,61093,PRETRIAL,Moise,David,Atkins,Male,African-American,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +18071,67389,17341,Probation,sweet,samantha,NULL,Female,Caucasian,07/27/90,22,Risk and Prescreen,Intake,English,Conditional Release,Pretrial Defendant,Single,11/9/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,Copy,1,0 +18071,67389,17341,Probation,sweet,samantha,NULL,Female,Caucasian,07/27/90,22,Risk and Prescreen,Intake,English,Conditional Release,Pretrial Defendant,Single,11/9/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,Copy,1,0 +18071,67389,17341,Probation,sweet,samantha,NULL,Female,Caucasian,07/27/90,22,Risk and Prescreen,Intake,English,Conditional Release,Pretrial Defendant,Single,11/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +58859,67379,61096,PRETRIAL,Mais,Tyrone,NULL,Male,African-American,07/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +58859,67379,61096,PRETRIAL,Mais,Tyrone,NULL,Male,African-American,07/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +58859,67379,61096,PRETRIAL,Mais,Tyrone,NULL,Male,African-American,07/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58864,67386,61101,PRETRIAL,BETEZA,SHAWN,M,Male,Caucasian,09/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/9/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +58864,67386,61101,PRETRIAL,BETEZA,SHAWN,M,Male,Caucasian,09/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/9/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +58864,67386,61101,PRETRIAL,BETEZA,SHAWN,M,Male,Caucasian,09/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/9/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58861,67382,61098,PRETRIAL,SWEETING,ARTHUR,LANG,Male,African-American,03/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +58861,67382,61098,PRETRIAL,SWEETING,ARTHUR,LANG,Male,African-American,03/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +58861,67382,61098,PRETRIAL,SWEETING,ARTHUR,LANG,Male,African-American,03/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +32468,67377,61094,PRETRIAL,Nicholson,Rozanna,NULL,Female,Caucasian,07/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,New,1,0 +32468,67377,61094,PRETRIAL,Nicholson,Rozanna,NULL,Female,Caucasian,07/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,9,High,New,1,0 +32468,67377,61094,PRETRIAL,Nicholson,Rozanna,NULL,Female,Caucasian,07/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58856,67375,61092,PRETRIAL,Brown-Cruz,Brandon,NULL,Male,African-American,11/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +58856,67375,61092,PRETRIAL,Brown-Cruz,Brandon,NULL,Male,African-American,11/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +58856,67375,61092,PRETRIAL,Brown-Cruz,Brandon,NULL,Male,African-American,11/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +34057,67380,47961,Probation,wright,eddie,NULL,Male,African-American,12/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,Copy,1,0 +34057,67380,47961,Probation,wright,eddie,NULL,Male,African-American,12/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.68,10,High,Copy,1,0 +34057,67380,47961,Probation,wright,eddie,NULL,Male,African-American,12/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +58865,67388,61102,PRETRIAL,Maitland,Kevin,Leo,Male,Caucasian,04/18/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/9/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +58865,67388,61102,PRETRIAL,Maitland,Kevin,Leo,Male,Caucasian,04/18/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/9/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +58865,67388,61102,PRETRIAL,Maitland,Kevin,Leo,Male,Caucasian,04/18/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58862,67383,61099,PRETRIAL,Huynh,Suong,NULL,Male,Caucasian,10/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +58862,67383,61099,PRETRIAL,Huynh,Suong,NULL,Male,Caucasian,10/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +58862,67383,61099,PRETRIAL,Huynh,Suong,NULL,Male,Caucasian,10/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +45430,67385,45684,PRETRIAL,Darville,Chaves,NULL,Male,African-American,12/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,Copy,1,0 +45430,67385,45684,PRETRIAL,Darville,Chaves,NULL,Male,African-American,12/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,Copy,1,0 +45430,67385,45684,PRETRIAL,Darville,Chaves,NULL,Male,African-American,12/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +42627,54437,49539,PRETRIAL,Smith,Sheri,NULL,Male,African-American,06/23/77,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,11/9/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +42627,54437,49539,PRETRIAL,Smith,Sheri,NULL,Male,African-American,06/23/77,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,11/9/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +42627,54437,49539,PRETRIAL,Smith,Sheri,NULL,Male,African-American,06/23/77,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,11/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58858,67378,61095,PRETRIAL,Geter,Tarus,Bene,Male,African-American,03/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,2,Medium,7,Risk of Violence,-1.28,7,Medium,New,1,0 +58858,67378,61095,PRETRIAL,Geter,Tarus,Bene,Male,African-American,03/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +58858,67378,61095,PRETRIAL,Geter,Tarus,Bene,Male,African-American,03/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58867,67392,61104,PRETRIAL,CISNEROS,EDUARDO,ANTONIO,Male,Caucasian,08/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +58867,67392,61104,PRETRIAL,CISNEROS,EDUARDO,ANTONIO,Male,Caucasian,08/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +58867,67392,61104,PRETRIAL,CISNEROS,EDUARDO,ANTONIO,Male,Caucasian,08/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58871,67396,61108,PRETRIAL,MILLER,DUANE,ANTONIO,Male,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +58871,67396,61108,PRETRIAL,MILLER,DUANE,ANTONIO,Male,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +58871,67396,61108,PRETRIAL,MILLER,DUANE,ANTONIO,Male,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58868,67393,61105,PRETRIAL,DALRYMPLE,DONATO,NULL,Male,Caucasian,03/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/13 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +58868,67393,61105,PRETRIAL,DALRYMPLE,DONATO,NULL,Male,Caucasian,03/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/13 0:00,1,Low,8,Risk of Recidivism,-2.67,1,Low,New,1,0 +58868,67393,61105,PRETRIAL,DALRYMPLE,DONATO,NULL,Male,Caucasian,03/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58232,67391,60448,PRETRIAL,Latimore,Anthony,NULL,Male,African-American,04/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,Copy,1,0 +58232,67391,60448,PRETRIAL,Latimore,Anthony,NULL,Male,African-American,04/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,Copy,1,0 +58232,67391,60448,PRETRIAL,Latimore,Anthony,NULL,Male,African-American,04/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +58873,67398,61110,PRETRIAL,WHALEN,THOMAS,NULL,Male,Caucasian,01/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/13 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +58873,67398,61110,PRETRIAL,WHALEN,THOMAS,NULL,Male,Caucasian,01/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/13 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +58873,67398,61110,PRETRIAL,WHALEN,THOMAS,NULL,Male,Caucasian,01/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58872,67397,61109,PRETRIAL,BAIRD,MARK,NULL,Male,Caucasian,08/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +58872,67397,61109,PRETRIAL,BAIRD,MARK,NULL,Male,Caucasian,08/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +58872,67397,61109,PRETRIAL,BAIRD,MARK,NULL,Male,Caucasian,08/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58869,67394,61106,PRETRIAL,SURACE,JASON,NULL,Male,African-American,07/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,4,High,7,Risk of Violence,-0.72,9,High,New,1,0 +58869,67394,61106,PRETRIAL,SURACE,JASON,NULL,Male,African-American,07/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +58869,67394,61106,PRETRIAL,SURACE,JASON,NULL,Male,African-American,07/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58870,67395,61107,PRETRIAL,GABRIEL,JASON,NULL,Male,African-American,12/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +58870,67395,61107,PRETRIAL,GABRIEL,JASON,NULL,Male,African-American,12/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +58870,67395,61107,PRETRIAL,GABRIEL,JASON,NULL,Male,African-American,12/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58876,67402,61113,PRETRIAL,Dowlings,Eldred,D,Male,African-American,12/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/11/13 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +58876,67402,61113,PRETRIAL,Dowlings,Eldred,D,Male,African-American,12/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +58876,67402,61113,PRETRIAL,Dowlings,Eldred,D,Male,African-American,12/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/11/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +34198,67405,33336,PRETRIAL,CARTER,TODD,NULL,Male,African-American,09/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,Copy,1,0 +34198,67405,33336,PRETRIAL,CARTER,TODD,NULL,Male,African-American,09/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,Copy,1,0 +34198,67405,33336,PRETRIAL,CARTER,TODD,NULL,Male,African-American,09/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +58877,67403,61114,PRETRIAL,WILLIAMS,CRAIG,NULL,Male,African-American,04/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +58877,67403,61114,PRETRIAL,WILLIAMS,CRAIG,NULL,Male,African-American,04/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +58877,67403,61114,PRETRIAL,WILLIAMS,CRAIG,NULL,Male,African-American,04/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58880,67407,61117,PRETRIAL,Clark,Sheldon,NULL,Male,African-American,10/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +58880,67407,61117,PRETRIAL,Clark,Sheldon,NULL,Male,African-American,10/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +58880,67407,61117,PRETRIAL,Clark,Sheldon,NULL,Male,African-American,10/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +58875,67401,61112,PRETRIAL,Kasdorf,Stephen,NULL,Male,Caucasian,05/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/11/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +58875,67401,61112,PRETRIAL,Kasdorf,Stephen,NULL,Male,Caucasian,05/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/11/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +58875,67401,61112,PRETRIAL,Kasdorf,Stephen,NULL,Male,Caucasian,05/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/11/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +58882,67409,61119,PRETRIAL,Derose,Larry,NULL,Male,Caucasian,07/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +58882,67409,61119,PRETRIAL,Derose,Larry,NULL,Male,Caucasian,07/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +58882,67409,61119,PRETRIAL,Derose,Larry,NULL,Male,Caucasian,07/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58879,67406,61116,PRETRIAL,Vitulano,Jennifer,NULL,Female,Caucasian,10/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +58879,67406,61116,PRETRIAL,Vitulano,Jennifer,NULL,Female,Caucasian,10/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,9,High,New,1,0 +58879,67406,61116,PRETRIAL,Vitulano,Jennifer,NULL,Female,Caucasian,10/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +58881,67408,61118,PRETRIAL,LINDO,RACHELLE,NULL,Female,Caucasian,12/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +58881,67408,61118,PRETRIAL,LINDO,RACHELLE,NULL,Female,Caucasian,12/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +58881,67408,61118,PRETRIAL,LINDO,RACHELLE,NULL,Female,Caucasian,12/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58878,67404,61115,PRETRIAL,LEVELL,VICTOR,NULL,Male,African-American,10/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +58878,67404,61115,PRETRIAL,LEVELL,VICTOR,NULL,Male,African-American,10/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +58878,67404,61115,PRETRIAL,LEVELL,VICTOR,NULL,Male,African-American,10/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58884,67411,61121,PRETRIAL,MAGEE,RIANNA,DARLENE,Female,Caucasian,10/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/12/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +58884,67411,61121,PRETRIAL,MAGEE,RIANNA,DARLENE,Female,Caucasian,10/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/12/13 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +58884,67411,61121,PRETRIAL,MAGEE,RIANNA,DARLENE,Female,Caucasian,10/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58898,67429,61138,PRETRIAL,Beder,Gregory,NULL,Male,Caucasian,06/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/12/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +58898,67429,61138,PRETRIAL,Beder,Gregory,NULL,Male,Caucasian,06/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +58898,67429,61138,PRETRIAL,Beder,Gregory,NULL,Male,Caucasian,06/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58915,67446,61153,Probation,SOLIS ROJAS,OSCAR,NULL,Male,Hispanic,07/20/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +58915,67446,61153,Probation,SOLIS ROJAS,OSCAR,NULL,Male,Hispanic,07/20/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +58915,67446,61153,Probation,SOLIS ROJAS,OSCAR,NULL,Male,Hispanic,07/20/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58885,67413,61123,PRETRIAL,MOHAMMED,WESTLEY,SHAZAD,Male,Other,12/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +58885,67413,61123,PRETRIAL,MOHAMMED,WESTLEY,SHAZAD,Male,Other,12/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +58885,67413,61123,PRETRIAL,MOHAMMED,WESTLEY,SHAZAD,Male,Other,12/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +39707,67420,39257,Probation,CORBIN,DAVID,W,Male,African-American,02/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,4,High,7,Risk of Violence,-0.78,9,High,Copy,1,0 +39707,67420,39257,Probation,CORBIN,DAVID,W,Male,African-American,02/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,4,High,8,Risk of Recidivism,0.71,10,High,Copy,1,0 +39707,67420,39257,Probation,CORBIN,DAVID,W,Male,African-American,02/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +58896,67427,61136,PRETRIAL,Mccrea,Malik,NULL,Male,African-American,06/20/97,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,4,High,7,Risk of Violence,-0.01,10,High,New,1,0 +58896,67427,61136,PRETRIAL,Mccrea,Malik,NULL,Male,African-American,06/20/97,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,4,High,8,Risk of Recidivism,0.87,10,High,New,1,0 +58896,67427,61136,PRETRIAL,Mccrea,Malik,NULL,Male,African-American,06/20/97,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58921,67455,61161,Probation,Swaby,Anthony,NULL,Male,African-American,01/04/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +58921,67455,61161,Probation,Swaby,Anthony,NULL,Male,African-American,01/04/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +58921,67455,61161,Probation,Swaby,Anthony,NULL,Male,African-American,01/04/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58904,67434,61143,Probation,Mitchell,Alise,NULL,Female,Caucasian,03/20/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +58904,67434,61143,Probation,Mitchell,Alise,NULL,Female,Caucasian,03/20/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +58904,67434,61143,Probation,Mitchell,Alise,NULL,Female,Caucasian,03/20/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58893,67424,61133,PRETRIAL,LENOIR,JOSPEH,NULL,Male,African-American,06/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +58893,67424,61133,PRETRIAL,LENOIR,JOSPEH,NULL,Male,African-American,06/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +58893,67424,61133,PRETRIAL,LENOIR,JOSPEH,NULL,Male,African-American,06/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +22114,67438,21273,PRETRIAL,little,joey,NULL,Male,African-American,06/22/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,Copy,1,0 +22114,67438,21273,PRETRIAL,little,joey,NULL,Male,African-American,06/22/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +22114,67438,21273,PRETRIAL,little,joey,NULL,Male,African-American,06/22/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,2,Low,Copy,1,0 +58914,67445,61152,Probation,Aristizabal,Luz,Marina,Female,Hispanic,07/18/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/12/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +58914,67445,61152,Probation,Aristizabal,Luz,Marina,Female,Hispanic,07/18/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +58914,67445,61152,Probation,Aristizabal,Luz,Marina,Female,Hispanic,07/18/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +31946,67453,61159,PRETRIAL,Reyes,Ashley,NULL,Female,African-American,08/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +31946,67453,61159,PRETRIAL,Reyes,Ashley,NULL,Female,African-American,08/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,4,High,8,Risk of Recidivism,0.45,10,High,New,1,0 +31946,67453,61159,PRETRIAL,Reyes,Ashley,NULL,Female,African-American,08/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +58887,67417,61127,PRETRIAL,Hernani,Fabio,NULL,Male,Caucasian,06/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +58887,67417,61127,PRETRIAL,Hernani,Fabio,NULL,Male,Caucasian,06/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,4,High,8,Risk of Recidivism,0.98,10,High,New,1,0 +58887,67417,61127,PRETRIAL,Hernani,Fabio,NULL,Male,Caucasian,06/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58901,67432,61141,Probation,Perez,Jean,Paul,Male,Hispanic,05/10/75,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/12/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +58901,67432,61141,Probation,Perez,Jean,Paul,Male,Hispanic,05/10/75,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +58901,67432,61141,Probation,Perez,Jean,Paul,Male,Hispanic,05/10/75,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +52226,67451,61157,Probation,maclaughlin,pamela,NULL,Female,Caucasian,09/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/12/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +52226,67451,61157,Probation,maclaughlin,pamela,NULL,Female,Caucasian,09/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +52226,67451,61157,Probation,maclaughlin,pamela,NULL,Female,Caucasian,09/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +35599,67414,61124,PRETRIAL,Delay,Cato,Michael,Male,African-American,09/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +35599,67414,61124,PRETRIAL,Delay,Cato,Michael,Male,African-American,09/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +35599,67414,61124,PRETRIAL,Delay,Cato,Michael,Male,African-American,09/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58916,67448,61154,Probation,EDWARDS,VINCENT,NULL,Male,African-American,07/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +58916,67448,61154,Probation,EDWARDS,VINCENT,NULL,Male,African-American,07/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +58916,67448,61154,Probation,EDWARDS,VINCENT,NULL,Male,African-American,07/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58905,67435,61144,Probation,PARK,SUNG,NULL,Male,Asian,06/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +58905,67435,61144,Probation,PARK,SUNG,NULL,Male,Asian,06/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +58905,67435,61144,Probation,PARK,SUNG,NULL,Male,Asian,06/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58911,67440,61148,Probation,Garcia-Simmisterra,Beverti,NULL,Male,Hispanic,06/23/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/12/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +58911,67440,61148,Probation,Garcia-Simmisterra,Beverti,NULL,Male,Hispanic,06/23/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/12/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +58911,67440,61148,Probation,Garcia-Simmisterra,Beverti,NULL,Male,Hispanic,06/23/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58891,67422,61131,PRETRIAL,RAMOS,CARLOS,JESUS,Male,Caucasian,02/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +58891,67422,61131,PRETRIAL,RAMOS,CARLOS,JESUS,Male,Caucasian,02/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +58891,67422,61131,PRETRIAL,RAMOS,CARLOS,JESUS,Male,Caucasian,02/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +5446,67412,61122,PRETRIAL,maiani,daniel,NULL,Male,Caucasian,12/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/12/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +5446,67412,61122,PRETRIAL,maiani,daniel,NULL,Male,Caucasian,12/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/12/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +5446,67412,61122,PRETRIAL,maiani,daniel,NULL,Male,Caucasian,12/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58909,67437,61146,DRRD,Edwards,Xavier,Givonte,Male,African-American,12/24/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,4,High,7,Risk of Violence,-0.28,10,High,New,1,0 +58909,67437,61146,DRRD,Edwards,Xavier,Givonte,Male,African-American,12/24/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,4,High,8,Risk of Recidivism,0.26,8,High,New,1,0 +58909,67437,61146,DRRD,Edwards,Xavier,Givonte,Male,African-American,12/24/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,4,High,18,Risk of Failure to Appear,22,4,Low,New,1,0 +58886,67416,61126,PRETRIAL,Fields,Dorian,NULL,Male,African-American,05/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +58886,67416,61126,PRETRIAL,Fields,Dorian,NULL,Male,African-American,05/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +58886,67416,61126,PRETRIAL,Fields,Dorian,NULL,Male,African-American,05/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58903,67433,61142,Probation,robinson,ronneshia,NULL,Female,African-American,04/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +58903,67433,61142,Probation,robinson,ronneshia,NULL,Female,African-American,04/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +58903,67433,61142,Probation,robinson,ronneshia,NULL,Female,African-American,04/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +58917,67449,61155,PRETRIAL,Alonzo,Domingo,NULL,Male,Hispanic,10/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +58917,67449,61155,PRETRIAL,Alonzo,Domingo,NULL,Male,Hispanic,10/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +58917,67449,61155,PRETRIAL,Alonzo,Domingo,NULL,Male,Hispanic,10/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58889,67419,61129,PRETRIAL,Reyes,Gispert,NULL,Male,Hispanic,08/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +58889,67419,61129,PRETRIAL,Reyes,Gispert,NULL,Male,Hispanic,08/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +58889,67419,61129,PRETRIAL,Reyes,Gispert,NULL,Male,Hispanic,08/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58890,67421,61130,PRETRIAL,Edwards,Kalil,NULL,Male,African-American,06/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +58890,67421,61130,PRETRIAL,Edwards,Kalil,NULL,Male,African-American,06/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +58890,67421,61130,PRETRIAL,Edwards,Kalil,NULL,Male,African-American,06/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58913,67442,61150,Probation,Shotwell,Marion,NULL,Male,African-American,07/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +58913,67442,61150,Probation,Shotwell,Marion,NULL,Male,African-American,07/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +58913,67442,61150,Probation,Shotwell,Marion,NULL,Male,African-American,07/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +47076,67456,61162,PRETRIAL,Morfa Lima,William,NULL,Male,Hispanic,08/29/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/12/13 0:00,1,Low,7,Risk of Violence,-1,-1,N/A,New,1,0 +47076,67456,61162,PRETRIAL,Morfa Lima,William,NULL,Male,Hispanic,08/29/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +47076,67456,61162,PRETRIAL,Morfa Lima,William,NULL,Male,Hispanic,08/29/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58883,67410,61120,PRETRIAL,Senior,Michael,Tyron,Male,African-American,10/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +58883,67410,61120,PRETRIAL,Senior,Michael,Tyron,Male,African-American,10/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +58883,67410,61120,PRETRIAL,Senior,Michael,Tyron,Male,African-American,10/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58888,67418,61128,PRETRIAL,Johnson,Boston,NULL,Male,African-American,07/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/12/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +58888,67418,61128,PRETRIAL,Johnson,Boston,NULL,Male,African-American,07/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/12/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +58888,67418,61128,PRETRIAL,Johnson,Boston,NULL,Male,African-American,07/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +58900,67431,61140,Probation,BELL,JOSEPH,WAYNE,Male,Hispanic,12/22/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/12/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +58900,67431,61140,Probation,BELL,JOSEPH,WAYNE,Male,Hispanic,12/22/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/12/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +58900,67431,61140,Probation,BELL,JOSEPH,WAYNE,Male,Hispanic,12/22/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +3832,67436,61145,Probation,Wallace,Joe,Lewis,Male,African-American,05/05/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +3832,67436,61145,Probation,Wallace,Joe,Lewis,Male,African-American,05/05/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +3832,67436,61145,Probation,Wallace,Joe,Lewis,Male,African-American,05/05/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +30731,67447,29716,Probation,GEORGE,KATHRYN,ANN,Male,Caucasian,08/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/13 0:00,4,High,7,Risk of Violence,-0.33,10,High,Copy,1,0 +30731,67447,29716,Probation,GEORGE,KATHRYN,ANN,Male,Caucasian,08/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,Copy,1,0 +30731,67447,29716,Probation,GEORGE,KATHRYN,ANN,Male,Caucasian,08/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/13 0:00,4,High,18,Risk of Failure to Appear,36,10,High,Copy,1,0 +58910,67439,61147,Probation,OLVERA,DAVID,NULL,Male,Hispanic,10/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +58910,67439,61147,Probation,OLVERA,DAVID,NULL,Male,Hispanic,10/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +58910,67439,61147,Probation,OLVERA,DAVID,NULL,Male,Hispanic,10/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58922,67457,61163,Probation,WILLIAMS,TANYA,LATRICE,Female,African-American,12/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +58922,67457,61163,Probation,WILLIAMS,TANYA,LATRICE,Female,African-American,12/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +58922,67457,61163,Probation,WILLIAMS,TANYA,LATRICE,Female,African-American,12/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58919,67452,61158,Probation,MORRIS,ALFRED,JAMES,Male,African-American,08/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +58919,67452,61158,Probation,MORRIS,ALFRED,JAMES,Male,African-American,08/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +58919,67452,61158,Probation,MORRIS,ALFRED,JAMES,Male,African-American,08/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58892,67423,61132,PRETRIAL,Robinson,Sherrod,Jamal,Male,African-American,05/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +58892,67423,61132,PRETRIAL,Robinson,Sherrod,Jamal,Male,African-American,05/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +58892,67423,61132,PRETRIAL,Robinson,Sherrod,Jamal,Male,African-American,05/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +36956,67415,61125,PRETRIAL,Whyte,Delva,NULL,Male,African-American,08/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +36956,67415,61125,PRETRIAL,Whyte,Delva,NULL,Male,African-American,08/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +36956,67415,61125,PRETRIAL,Whyte,Delva,NULL,Male,African-American,08/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58931,67468,61173,PRETRIAL,Cottle,Lawrence,NULL,Male,African-American,11/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +58931,67468,61173,PRETRIAL,Cottle,Lawrence,NULL,Male,African-American,11/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +58931,67468,61173,PRETRIAL,Cottle,Lawrence,NULL,Male,African-American,11/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58942,67481,61185,PRETRIAL,RAMOS,JULIO,CEASAR,Male,Caucasian,10/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,New,1,0 +58942,67481,61185,PRETRIAL,RAMOS,JULIO,CEASAR,Male,Caucasian,10/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +58942,67481,61185,PRETRIAL,RAMOS,JULIO,CEASAR,Male,Caucasian,10/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58925,67460,61166,PRETRIAL,RIZON,KENT,DALMAO,Male,Other,03/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/13/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +58925,67460,61166,PRETRIAL,RIZON,KENT,DALMAO,Male,Other,03/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +58925,67460,61166,PRETRIAL,RIZON,KENT,DALMAO,Male,Other,03/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58948,67489,61193,PRETRIAL,Pitts,Andre,NULL,Male,African-American,08/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +58948,67489,61193,PRETRIAL,Pitts,Andre,NULL,Male,African-American,08/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +58948,67489,61193,PRETRIAL,Pitts,Andre,NULL,Male,African-American,08/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58952,67494,61198,Probation,BRENNAN,EDWARD,NULL,Male,Caucasian,10/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/13/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +58952,67494,61198,Probation,BRENNAN,EDWARD,NULL,Male,Caucasian,10/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/13/13 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +58952,67494,61198,Probation,BRENNAN,EDWARD,NULL,Male,Caucasian,10/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58954,67496,61200,Probation,BENNETT,TIMOTHY,LAMONT,Male,African-American,11/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +58954,67496,61200,Probation,BENNETT,TIMOTHY,LAMONT,Male,African-American,11/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +58954,67496,61200,Probation,BENNETT,TIMOTHY,LAMONT,Male,African-American,11/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58935,67473,61177,PRETRIAL,Hayes,Chari,Eileen,Female,Caucasian,12/08/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +58935,67473,61177,PRETRIAL,Hayes,Chari,Eileen,Female,Caucasian,12/08/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +58935,67473,61177,PRETRIAL,Hayes,Chari,Eileen,Female,Caucasian,12/08/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +58947,67488,61192,Probation,MEJIA,CARLOS,NULL,Male,Hispanic,04/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +58947,67488,61192,Probation,MEJIA,CARLOS,NULL,Male,Hispanic,04/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +58947,67488,61192,Probation,MEJIA,CARLOS,NULL,Male,Hispanic,04/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58945,67486,61190,Probation,riera,yina,NULL,Male,Caucasian,09/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +58945,67486,61190,Probation,riera,yina,NULL,Male,Caucasian,09/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +58945,67486,61190,Probation,riera,yina,NULL,Male,Caucasian,09/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +32907,67504,61208,PRETRIAL,rolle,Howard,NULL,Male,African-American,02/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +32907,67504,61208,PRETRIAL,rolle,Howard,NULL,Male,African-American,02/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +32907,67504,61208,PRETRIAL,rolle,Howard,NULL,Male,African-American,02/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58928,67465,61170,PRETRIAL,Camper,Cedrick,Carnell,Male,African-American,01/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +58928,67465,61170,PRETRIAL,Camper,Cedrick,Carnell,Male,African-American,01/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +58928,67465,61170,PRETRIAL,Camper,Cedrick,Carnell,Male,African-American,01/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58956,67499,61203,Probation,DUME,CHRISTIAN,F,Male,Hispanic,02/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +58956,67499,61203,Probation,DUME,CHRISTIAN,F,Male,Hispanic,02/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +58956,67499,61203,Probation,DUME,CHRISTIAN,F,Male,Hispanic,02/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +46525,67478,61182,PRETRIAL,rega,steven,david,Male,Caucasian,10/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/13 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +46525,67478,61182,PRETRIAL,rega,steven,david,Male,Caucasian,10/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +46525,67478,61182,PRETRIAL,rega,steven,david,Male,Caucasian,10/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58949,67491,61195,Probation,ANOSIKE,TASHIA,NULL,Female,African-American,08/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +58949,67491,61195,Probation,ANOSIKE,TASHIA,NULL,Female,African-American,08/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +58949,67491,61195,Probation,ANOSIKE,TASHIA,NULL,Female,African-American,08/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +18604,67463,61168,PRETRIAL,HAMIN,TAWFIQ,NULL,Male,African-American,01/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +18604,67463,61168,PRETRIAL,HAMIN,TAWFIQ,NULL,Male,African-American,01/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +18604,67463,61168,PRETRIAL,HAMIN,TAWFIQ,NULL,Male,African-American,01/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58933,67470,61175,PRETRIAL,Frsncis,Ezekiel,NULL,Male,Caucasian,09/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +58933,67470,61175,PRETRIAL,Frsncis,Ezekiel,NULL,Male,Caucasian,09/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +58933,67470,61175,PRETRIAL,Frsncis,Ezekiel,NULL,Male,Caucasian,09/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58939,67477,61181,Probation,Medina,John,NULL,Male,Hispanic,07/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +58939,67477,61181,Probation,Medina,John,NULL,Male,Hispanic,07/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +58939,67477,61181,Probation,Medina,John,NULL,Male,Hispanic,07/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58955,67498,61202,Probation,REA,JORGE,A,Male,Hispanic,04/25/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +58955,67498,61202,Probation,REA,JORGE,A,Male,Hispanic,04/25/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +58955,67498,61202,Probation,REA,JORGE,A,Male,Hispanic,04/25/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +33759,67500,61204,PRETRIAL,Beneby,Earl,NULL,Male,African-American,03/22/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +33759,67500,61204,PRETRIAL,Beneby,Earl,NULL,Male,African-American,03/22/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +33759,67500,61204,PRETRIAL,Beneby,Earl,NULL,Male,African-American,03/22/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +21743,67484,61188,Probation,dossantos,marlon,NULL,Male,Hispanic,12/01/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/13/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +21743,67484,61188,Probation,dossantos,marlon,NULL,Male,Hispanic,12/01/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +21743,67484,61188,Probation,dossantos,marlon,NULL,Male,Hispanic,12/01/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +30818,67505,61209,PRETRIAL,MCREED,JONATHAN,NULL,Male,African-American,05/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +30818,67505,61209,PRETRIAL,MCREED,JONATHAN,NULL,Male,African-American,05/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.71,10,High,New,1,0 +30818,67505,61209,PRETRIAL,MCREED,JONATHAN,NULL,Male,African-American,05/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58923,67458,61164,PRETRIAL,GARCIA,JESSICA,NICOLE,Female,Caucasian,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-1.81,5,Medium,New,1,0 +58923,67458,61164,PRETRIAL,GARCIA,JESSICA,NICOLE,Female,Caucasian,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +58923,67458,61164,PRETRIAL,GARCIA,JESSICA,NICOLE,Female,Caucasian,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58937,67475,61179,PRETRIAL,Valdes,Javier,Amado,Male,Caucasian,04/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +58937,67475,61179,PRETRIAL,Valdes,Javier,Amado,Male,Caucasian,04/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +58937,67475,61179,PRETRIAL,Valdes,Javier,Amado,Male,Caucasian,04/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58951,67493,61197,Probation,Dastugue,Kim,Gerard,Male,Caucasian,11/21/56,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/13/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +58951,67493,61197,Probation,Dastugue,Kim,Gerard,Male,Caucasian,11/21/56,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/13/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +58951,67493,61197,Probation,Dastugue,Kim,Gerard,Male,Caucasian,11/21/56,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58940,67479,61183,Probation,brown,william,NULL,Male,Caucasian,05/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +58940,67479,61183,Probation,brown,william,NULL,Male,Caucasian,05/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +58940,67479,61183,Probation,brown,william,NULL,Male,Caucasian,05/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58926,67461,61167,PRETRIAL,Sands,Summer,NULL,Female,Caucasian,03/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +58926,67461,61167,PRETRIAL,Sands,Summer,NULL,Female,Caucasian,03/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +58926,67461,61167,PRETRIAL,Sands,Summer,NULL,Female,Caucasian,03/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +44367,67490,61194,PRETRIAL,ROSE,KEVIN,S,Male,Caucasian,09/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/13/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +44367,67490,61194,PRETRIAL,ROSE,KEVIN,S,Male,Caucasian,09/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +44367,67490,61194,PRETRIAL,ROSE,KEVIN,S,Male,Caucasian,09/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58932,67469,61174,PRETRIAL,SCOTT,ROSELIA,SYLVESTER,Female,African-American,08/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +58932,67469,61174,PRETRIAL,SCOTT,ROSELIA,SYLVESTER,Female,African-American,08/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,New,1,0 +58932,67469,61174,PRETRIAL,SCOTT,ROSELIA,SYLVESTER,Female,African-American,08/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +36318,67503,61207,PRETRIAL,CLARK,THOMAS,E,Male,African-American,12/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +36318,67503,61207,PRETRIAL,CLARK,THOMAS,E,Male,African-American,12/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +36318,67503,61207,PRETRIAL,CLARK,THOMAS,E,Male,African-American,12/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58929,67466,61171,PRETRIAL,Perry,Breon,NULL,Male,African-American,04/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +58929,67466,61171,PRETRIAL,Perry,Breon,NULL,Male,African-American,04/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +58929,67466,61171,PRETRIAL,Perry,Breon,NULL,Male,African-American,04/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58946,67487,61191,Probation,Rodriguez,Juvens,NULL,Male,Hispanic,09/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,2,Medium,7,Risk of Violence,-2.71,2,Low,New,1,0 +58946,67487,61191,Probation,Rodriguez,Juvens,NULL,Male,Hispanic,09/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +58946,67487,61191,Probation,Rodriguez,Juvens,NULL,Male,Hispanic,09/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +58953,67495,61199,Probation,Duncan,Tonquese,NULL,Female,African-American,01/29/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +58953,67495,61199,Probation,Duncan,Tonquese,NULL,Female,African-American,01/29/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +58953,67495,61199,Probation,Duncan,Tonquese,NULL,Female,African-American,01/29/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58924,67459,61165,PRETRIAL,Omana,Francia,NULL,Male,Caucasian,09/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/13/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +58924,67459,61165,PRETRIAL,Omana,Francia,NULL,Male,Caucasian,09/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/13/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +58924,67459,61165,PRETRIAL,Omana,Francia,NULL,Male,Caucasian,09/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58936,67474,61178,PRETRIAL,Mattear,Omara,J,Male,African-American,12/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +58936,67474,61178,PRETRIAL,Mattear,Omara,J,Male,African-American,12/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,4,High,8,Risk of Recidivism,0.48,9,High,New,1,0 +58936,67474,61178,PRETRIAL,Mattear,Omara,J,Male,African-American,12/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58943,67483,61187,Probation,SPEEDY,CHRISTINE,A,Female,Caucasian,06/22/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +58943,67483,61187,Probation,SPEEDY,CHRISTINE,A,Female,Caucasian,06/22/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +58943,67483,61187,Probation,SPEEDY,CHRISTINE,A,Female,Caucasian,06/22/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +6505,67462,6100,DRRD,Anglin,Leroy,NULL,Male,African-American,10/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,Copy,1,0 +6505,67462,6100,DRRD,Anglin,Leroy,NULL,Male,African-American,10/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,4,High,8,Risk of Recidivism,0.43,9,High,Copy,1,0 +6505,67462,6100,DRRD,Anglin,Leroy,NULL,Male,African-American,10/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,4,High,18,Risk of Failure to Appear,28,7,Medium,Copy,1,0 +58927,67464,61169,PRETRIAL,Floyd,Zuberi,A,Male,African-American,06/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +58927,67464,61169,PRETRIAL,Floyd,Zuberi,A,Male,African-American,06/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +58927,67464,61169,PRETRIAL,Floyd,Zuberi,A,Male,African-American,06/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58944,67485,61189,Probation,SINDONE,JOHN,NULL,Male,Caucasian,02/06/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +58944,67485,61189,Probation,SINDONE,JOHN,NULL,Male,Caucasian,02/06/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +58944,67485,61189,Probation,SINDONE,JOHN,NULL,Male,Caucasian,02/06/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58950,67492,61196,Probation,bradley,jeffery,NULL,Male,African-American,08/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.6,2,Low,New,1,0 +58950,67492,61196,Probation,bradley,jeffery,NULL,Male,African-American,08/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +58950,67492,61196,Probation,bradley,jeffery,NULL,Male,African-American,08/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +20792,67471,19965,PRETRIAL,penso,steven,NULL,Male,Caucasian,08/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,Copy,1,0 +20792,67471,19965,PRETRIAL,penso,steven,NULL,Male,Caucasian,08/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,Copy,1,0 +20792,67471,19965,PRETRIAL,penso,steven,NULL,Male,Caucasian,08/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +46043,67480,61184,PRETRIAL,Moyer,Candy,NULL,Female,Caucasian,02/02/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +46043,67480,61184,PRETRIAL,Moyer,Candy,NULL,Female,Caucasian,02/02/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +46043,67480,61184,PRETRIAL,Moyer,Candy,NULL,Female,Caucasian,02/02/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58930,67467,61172,PRETRIAL,Fortin,Elijah,Pierre,Male,Caucasian,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +58930,67467,61172,PRETRIAL,Fortin,Elijah,Pierre,Male,Caucasian,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +58930,67467,61172,PRETRIAL,Fortin,Elijah,Pierre,Male,Caucasian,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +41583,67501,61205,PRETRIAL,LICENCIER,NANCY,NULL,Female,African-American,07/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +41583,67501,61205,PRETRIAL,LICENCIER,NANCY,NULL,Female,African-American,07/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +41583,67501,61205,PRETRIAL,LICENCIER,NANCY,NULL,Female,African-American,07/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +17004,67497,61201,PRETRIAL,farquharson,andrew,NULL,Male,African-American,09/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +17004,67497,61201,PRETRIAL,farquharson,andrew,NULL,Male,African-American,09/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +17004,67497,61201,PRETRIAL,farquharson,andrew,NULL,Male,African-American,09/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58938,67476,61180,PRETRIAL,TEPPER,IRVING,NULL,Male,Caucasian,07/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +58938,67476,61180,PRETRIAL,TEPPER,IRVING,NULL,Male,Caucasian,07/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +58938,67476,61180,PRETRIAL,TEPPER,IRVING,NULL,Male,Caucasian,07/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58985,67543,61245,Probation,clamaco,jose,NULL,Male,Hispanic,04/30/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/14/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +58985,67543,61245,Probation,clamaco,jose,NULL,Male,Hispanic,04/30/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/14/13 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +58985,67543,61245,Probation,clamaco,jose,NULL,Male,Hispanic,04/30/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58970,67522,61224,Probation,Ocampo,Alexandra,NULL,Female,Hispanic,07/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/14/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +58970,67522,61224,Probation,Ocampo,Alexandra,NULL,Female,Hispanic,07/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/14/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +58970,67522,61224,Probation,Ocampo,Alexandra,NULL,Female,Hispanic,07/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58980,67536,61238,Probation,bencomo,amy,NULL,Female,Hispanic,03/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +58980,67536,61238,Probation,bencomo,amy,NULL,Female,Hispanic,03/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +58980,67536,61238,Probation,bencomo,amy,NULL,Female,Hispanic,03/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45960,67518,46305,PRETRIAL,Rodriguez,Raymond,NULL,Male,Hispanic,12/18/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +45960,67518,46305,PRETRIAL,Rodriguez,Raymond,NULL,Male,Hispanic,12/18/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.66,9,High,New,1,0 +45960,67518,46305,PRETRIAL,Rodriguez,Raymond,NULL,Male,Hispanic,12/18/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,2,Low,New,1,0 +58988,67548,61249,Probation,Hall,Andre,NULL,Male,African-American,11/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +58988,67548,61249,Probation,Hall,Andre,NULL,Male,African-American,11/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +58988,67548,61249,Probation,Hall,Andre,NULL,Male,African-American,11/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58983,67539,61241,Probation,Dunn,Raven,NULL,Female,African-American,06/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +58983,67539,61241,Probation,Dunn,Raven,NULL,Female,African-American,06/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +58983,67539,61241,Probation,Dunn,Raven,NULL,Female,African-American,06/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58957,67506,61210,PRETRIAL,Jackson Jr,Deaunta,Garcia,Male,African-American,08/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +58957,67506,61210,PRETRIAL,Jackson Jr,Deaunta,Garcia,Male,African-American,08/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +58957,67506,61210,PRETRIAL,Jackson Jr,Deaunta,Garcia,Male,African-American,08/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +17106,67541,61243,PRETRIAL,SHALLEY,STEVEN,NULL,Male,Caucasian,12/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +17106,67541,61243,PRETRIAL,SHALLEY,STEVEN,NULL,Male,Caucasian,12/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +17106,67541,61243,PRETRIAL,SHALLEY,STEVEN,NULL,Male,Caucasian,12/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58968,67520,61222,Probation,johnson,andre,NULL,Male,African-American,01/13/75,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-1,-1,N/A,New,1,0 +58968,67520,61222,Probation,johnson,andre,NULL,Male,African-American,01/13/75,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +58968,67520,61222,Probation,johnson,andre,NULL,Male,African-American,01/13/75,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58974,67527,61229,Probation,colditz,patricia,NULL,Female,African-American,07/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/14/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +58974,67527,61229,Probation,colditz,patricia,NULL,Female,African-American,07/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/14/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +58974,67527,61229,Probation,colditz,patricia,NULL,Female,African-American,07/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58978,67534,61236,PRETRIAL,perez-zambrano,carlos,NULL,Male,Hispanic,10/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/14/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +58978,67534,61236,PRETRIAL,perez-zambrano,carlos,NULL,Male,Hispanic,10/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/14/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +58978,67534,61236,PRETRIAL,perez-zambrano,carlos,NULL,Male,Hispanic,10/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +1279,67524,61226,PRETRIAL,ROBICHAUD,COURTNEY,L,Female,Caucasian,04/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +1279,67524,61226,PRETRIAL,ROBICHAUD,COURTNEY,L,Female,Caucasian,04/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +1279,67524,61226,PRETRIAL,ROBICHAUD,COURTNEY,L,Female,Caucasian,04/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +58987,67545,61246,Probation,sutton,noah,NULL,Male,African-American,10/28/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +58987,67545,61246,Probation,sutton,noah,NULL,Male,African-American,10/28/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +58987,67545,61246,Probation,sutton,noah,NULL,Male,African-American,10/28/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +44683,67552,61253,Probation,GULLO,JASON,J,Male,Hispanic,06/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +44683,67552,61253,Probation,GULLO,JASON,J,Male,Hispanic,06/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +44683,67552,61253,Probation,GULLO,JASON,J,Male,Hispanic,06/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58977,67532,61234,Probation,Buhot,Danielle,Bonita,Female,Caucasian,03/19/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +58977,67532,61234,Probation,Buhot,Danielle,Bonita,Female,Caucasian,03/19/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +58977,67532,61234,Probation,Buhot,Danielle,Bonita,Female,Caucasian,03/19/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +58981,67537,61239,PRETRIAL,Berry,Bryan,Edward,Male,Caucasian,09/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/14/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +58981,67537,61239,PRETRIAL,Berry,Bryan,Edward,Male,Caucasian,09/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/14/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +58981,67537,61239,PRETRIAL,Berry,Bryan,Edward,Male,Caucasian,09/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58966,67516,61219,Probation,bradshaw,orayne,NULL,Male,African-American,12/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +58966,67516,61219,Probation,bradshaw,orayne,NULL,Male,African-American,12/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +58966,67516,61219,Probation,bradshaw,orayne,NULL,Male,African-American,12/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58990,67550,61251,Probation,Casey,Justin,NULL,Male,Hispanic,06/05/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +58990,67550,61251,Probation,Casey,Justin,NULL,Male,Hispanic,06/05/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +58990,67550,61251,Probation,Casey,Justin,NULL,Male,Hispanic,06/05/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58959,67508,61212,PRETRIAL,Williams,Tavares,NULL,Male,African-American,01/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/14/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +58959,67508,61212,PRETRIAL,Williams,Tavares,NULL,Male,African-American,01/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/14/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +58959,67508,61212,PRETRIAL,Williams,Tavares,NULL,Male,African-American,01/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58962,67511,61215,PRETRIAL,BRADLEY,CHERIZ,NULL,Female,African-American,07/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +58962,67511,61215,PRETRIAL,BRADLEY,CHERIZ,NULL,Female,African-American,07/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +58962,67511,61215,PRETRIAL,BRADLEY,CHERIZ,NULL,Female,African-American,07/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +12962,67529,61231,Probation,james,dartanyun,NULL,Male,African-American,08/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,New,1,0 +12962,67529,61231,Probation,james,dartanyun,NULL,Male,African-American,08/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +12962,67529,61231,Probation,james,dartanyun,NULL,Male,African-American,08/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +15734,67547,61248,PRETRIAL,Looper,Brandon,M,Male,Caucasian,09/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +15734,67547,61248,PRETRIAL,Looper,Brandon,M,Male,Caucasian,09/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +15734,67547,61248,PRETRIAL,Looper,Brandon,M,Male,Caucasian,09/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58973,67526,61228,Probation,Voltaire,Anterio,NULL,Male,African-American,12/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/14/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +58973,67526,61228,Probation,Voltaire,Anterio,NULL,Male,African-American,12/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +58973,67526,61228,Probation,Voltaire,Anterio,NULL,Male,African-American,12/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +18546,67540,61242,PRETRIAL,CARTER,TARIK,DEMTRIUS,Male,African-American,08/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +18546,67540,61242,PRETRIAL,CARTER,TARIK,DEMTRIUS,Male,African-American,08/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +18546,67540,61242,PRETRIAL,CARTER,TARIK,DEMTRIUS,Male,African-American,08/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +58964,67514,61217,Probation,Major,Charles,NULL,Male,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/14/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +58964,67514,61217,Probation,Major,Charles,NULL,Male,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +58964,67514,61217,Probation,Major,Charles,NULL,Male,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56091,67544,58015,Probation,Jones,Gail,NULL,Female,Caucasian,11/10/63,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.24,1,Low,Copy,1,0 +56091,67544,58015,Probation,Jones,Gail,NULL,Female,Caucasian,11/10/63,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,Copy,1,0 +56091,67544,58015,Probation,Jones,Gail,NULL,Female,Caucasian,11/10/63,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +58285,67531,61233,PRETRIAL,Blake,Evan,NULL,Male,Caucasian,02/27/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/13 0:00,4,High,7,Risk of Violence,-0.7,9,High,New,1,0 +58285,67531,61233,PRETRIAL,Blake,Evan,NULL,Male,Caucasian,02/27/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +58285,67531,61233,PRETRIAL,Blake,Evan,NULL,Male,Caucasian,02/27/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/13 0:00,4,High,18,Risk of Failure to Appear,22,4,Low,New,1,0 +58979,67535,61237,PRETRIAL,benitez-morales,angelica,NULL,Female,Hispanic,11/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +58979,67535,61237,PRETRIAL,benitez-morales,angelica,NULL,Female,Hispanic,11/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +58979,67535,61237,PRETRIAL,benitez-morales,angelica,NULL,Female,Hispanic,11/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58989,67549,61250,Probation,Soberon,Leonel,NULL,Male,Hispanic,12/23/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +58989,67549,61250,Probation,Soberon,Leonel,NULL,Male,Hispanic,12/23/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +58989,67549,61250,Probation,Soberon,Leonel,NULL,Male,Hispanic,12/23/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58967,67519,61221,Probation,Banhossenhireti,Rodnei,NULL,Male,Caucasian,09/19/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/14/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +58967,67519,61221,Probation,Banhossenhireti,Rodnei,NULL,Male,Caucasian,09/19/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/14/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +58967,67519,61221,Probation,Banhossenhireti,Rodnei,NULL,Male,Caucasian,09/19/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58969,67521,61223,Probation,Macelroy,Katheryn,Elizabeth,Female,Native American,08/26/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,New,1,0 +58969,67521,61223,Probation,Macelroy,Katheryn,Elizabeth,Female,Native American,08/26/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,10,High,New,1,0 +58969,67521,61223,Probation,Macelroy,Katheryn,Elizabeth,Female,Native American,08/26/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +58975,67528,61230,Probation,felicjano,zulika,NULL,Female,Hispanic,01/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +58975,67528,61230,Probation,felicjano,zulika,NULL,Female,Hispanic,01/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +58975,67528,61230,Probation,felicjano,zulika,NULL,Female,Hispanic,01/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58984,67542,61244,Probation,canderlario,samantha,NULL,Female,Caucasian,02/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +58984,67542,61244,Probation,canderlario,samantha,NULL,Female,Caucasian,02/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +58984,67542,61244,Probation,canderlario,samantha,NULL,Female,Caucasian,02/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58963,67512,61216,Probation,Jean,Jhamson,NULL,Male,African-American,10/11/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.14,4,Low,New,1,0 +58963,67512,61216,Probation,Jean,Jhamson,NULL,Male,African-American,10/11/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +58963,67512,61216,Probation,Jean,Jhamson,NULL,Male,African-American,10/11/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58958,67507,61211,PRETRIAL,Ho,Kiet,NULL,Male,Asian,11/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/14/13 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +58958,67507,61211,PRETRIAL,Ho,Kiet,NULL,Male,Asian,11/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/14/13 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +58958,67507,61211,PRETRIAL,Ho,Kiet,NULL,Male,Asian,11/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58972,67525,61227,PRETRIAL,Paul,Roberto,NULL,Male,African-American,05/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +58972,67525,61227,PRETRIAL,Paul,Roberto,NULL,Male,African-American,05/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +58972,67525,61227,PRETRIAL,Paul,Roberto,NULL,Male,African-American,05/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +58982,67538,61240,Probation,Scott,Devonte,NULL,Male,African-American,09/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +58982,67538,61240,Probation,Scott,Devonte,NULL,Male,African-American,09/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +58982,67538,61240,Probation,Scott,Devonte,NULL,Male,African-American,09/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58960,67509,61213,PRETRIAL,NEGRON,JASMIN,NULL,Female,Caucasian,09/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.22,8,High,New,1,0 +58960,67509,61213,PRETRIAL,NEGRON,JASMIN,NULL,Female,Caucasian,09/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.23,7,Medium,New,1,0 +58960,67509,61213,PRETRIAL,NEGRON,JASMIN,NULL,Female,Caucasian,09/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58961,67510,61214,PRETRIAL,CORKER,BRIAN,MAURICE,Male,African-American,07/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-1.77,5,Medium,New,1,0 +58961,67510,61214,PRETRIAL,CORKER,BRIAN,MAURICE,Male,African-American,07/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +58961,67510,61214,PRETRIAL,CORKER,BRIAN,MAURICE,Male,African-American,07/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58971,67523,61225,PRETRIAL,DICICCO,MICHAEL,NULL,Male,Caucasian,04/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +58971,67523,61225,PRETRIAL,DICICCO,MICHAEL,NULL,Male,Caucasian,04/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +58971,67523,61225,PRETRIAL,DICICCO,MICHAEL,NULL,Male,Caucasian,04/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58965,67515,61218,PRETRIAL,Rangoowala,Shella,NULL,Female,Asian,05/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/14/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +58965,67515,61218,PRETRIAL,Rangoowala,Shella,NULL,Female,Asian,05/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/14/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +58965,67515,61218,PRETRIAL,Rangoowala,Shella,NULL,Female,Asian,05/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +5956,67517,61220,PRETRIAL,reid,ricardo,NULL,Male,Other,01/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +5956,67517,61220,PRETRIAL,reid,ricardo,NULL,Male,Other,01/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +5956,67517,61220,PRETRIAL,reid,ricardo,NULL,Male,Other,01/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58998,67559,61260,PRETRIAL,Smith,Dyneisha,Sharelle,Female,African-American,01/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +58998,67559,61260,PRETRIAL,Smith,Dyneisha,Sharelle,Female,African-American,01/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +58998,67559,61260,PRETRIAL,Smith,Dyneisha,Sharelle,Female,African-American,01/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59024,67588,61286,PRETRIAL,Dunn,Eileen,NULL,Female,Caucasian,08/07/41,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/15/13 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +59024,67588,61286,PRETRIAL,Dunn,Eileen,NULL,Female,Caucasian,08/07/41,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/15/13 0:00,1,Low,8,Risk of Recidivism,-2.68,1,Low,New,1,0 +59024,67588,61286,PRETRIAL,Dunn,Eileen,NULL,Female,Caucasian,08/07/41,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59014,67575,61275,Probation,Klem,Donna,NULL,Female,Caucasian,02/17/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +59014,67575,61275,Probation,Klem,Donna,NULL,Female,Caucasian,02/17/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +59014,67575,61275,Probation,Klem,Donna,NULL,Female,Caucasian,02/17/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +5167,67593,61289,PRETRIAL,Payne,Allen,Kennard,Male,African-American,01/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,11/15/13 0:00,4,High,7,Risk of Violence,-0.16,10,High,New,1,0 +5167,67593,61289,PRETRIAL,Payne,Allen,Kennard,Male,African-American,01/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,11/15/13 0:00,4,High,8,Risk of Recidivism,0.95,10,High,New,1,0 +5167,67593,61289,PRETRIAL,Payne,Allen,Kennard,Male,African-American,01/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,11/15/13 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +58993,67554,61255,PRETRIAL,Cisneros,Edgar,Michael,Male,Caucasian,08/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +58993,67554,61255,PRETRIAL,Cisneros,Edgar,Michael,Male,Caucasian,08/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +58993,67554,61255,PRETRIAL,Cisneros,Edgar,Michael,Male,Caucasian,08/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59011,67572,61272,Probation,MAHONES,VERONICA,NULL,Female,African-American,01/27/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +59011,67572,61272,Probation,MAHONES,VERONICA,NULL,Female,African-American,01/27/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +59011,67572,61272,Probation,MAHONES,VERONICA,NULL,Female,African-American,01/27/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59017,67580,61279,Probation,Cypress,Charley,NULL,Male,Native American,02/23/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,New,1,0 +59017,67580,61279,Probation,Cypress,Charley,NULL,Male,Native American,02/23/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +59017,67580,61279,Probation,Cypress,Charley,NULL,Male,Native American,02/23/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58995,67556,61257,PRETRIAL,Golding,Christine,NULL,Female,African-American,09/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +58995,67556,61257,PRETRIAL,Golding,Christine,NULL,Female,African-American,09/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +58995,67556,61257,PRETRIAL,Golding,Christine,NULL,Female,African-American,09/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +12328,67591,11821,PRETRIAL,Howell,Jerome,NULL,Male,African-American,03/12/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,Copy,1,0 +12328,67591,11821,PRETRIAL,Howell,Jerome,NULL,Male,African-American,03/12/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,Copy,1,0 +12328,67591,11821,PRETRIAL,Howell,Jerome,NULL,Male,African-American,03/12/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +59002,67563,61264,PRETRIAL,Flores,Lonnie,NULL,Male,Caucasian,12/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +59002,67563,61264,PRETRIAL,Flores,Lonnie,NULL,Male,Caucasian,12/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +59002,67563,61264,PRETRIAL,Flores,Lonnie,NULL,Male,Caucasian,12/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59008,67570,61270,PRETRIAL,Darren,Houston,Lee,Male,African-American,04/13/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/15/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,Copy,1,0 +59008,67570,61270,PRETRIAL,Darren,Houston,Lee,Male,African-American,04/13/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/15/13 0:00,4,High,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +59008,67570,61270,PRETRIAL,Darren,Houston,Lee,Male,African-American,04/13/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/15/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +59015,67577,61276,Probation,smith,charles,NULL,Male,Caucasian,08/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +59015,67577,61276,Probation,smith,charles,NULL,Male,Caucasian,08/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +59015,67577,61276,Probation,smith,charles,NULL,Male,Caucasian,08/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59004,67565,61266,PRETRIAL,Hill,James,NULL,Male,African-American,07/31/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/15/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +59004,67565,61266,PRETRIAL,Hill,James,NULL,Male,African-American,07/31/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +59004,67565,61266,PRETRIAL,Hill,James,NULL,Male,African-American,07/31/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59018,67582,61280,PRETRIAL,ulloa,leonard,NULL,Male,Caucasian,01/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/15/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +59018,67582,61280,PRETRIAL,ulloa,leonard,NULL,Male,Caucasian,01/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +59018,67582,61280,PRETRIAL,ulloa,leonard,NULL,Male,Caucasian,01/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59000,67561,61262,PRETRIAL,Ospina,Johan,NULL,Male,Caucasian,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/15/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +59000,67561,61262,PRETRIAL,Ospina,Johan,NULL,Male,Caucasian,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +59000,67561,61262,PRETRIAL,Ospina,Johan,NULL,Male,Caucasian,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59022,67586,61284,Probation,mendonca,priscilla,NULL,Female,Caucasian,01/30/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +59022,67586,61284,Probation,mendonca,priscilla,NULL,Female,Caucasian,01/30/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +59022,67586,61284,Probation,mendonca,priscilla,NULL,Female,Caucasian,01/30/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58997,67558,61259,PRETRIAL,Cedieu,Michael,NULL,Male,African-American,10/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +58997,67558,61259,PRETRIAL,Cedieu,Michael,NULL,Male,African-American,10/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +58997,67558,61259,PRETRIAL,Cedieu,Michael,NULL,Male,African-American,10/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57845,67576,59992,PRETRIAL,Obasogie,Shawnita,NULL,Female,African-American,02/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,Copy,1,0 +57845,67576,59992,PRETRIAL,Obasogie,Shawnita,NULL,Female,African-American,02/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,Copy,1,0 +57845,67576,59992,PRETRIAL,Obasogie,Shawnita,NULL,Female,African-American,02/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +59020,67584,61282,Probation,MCKINNEY,GARRY,NULL,Male,Caucasian,05/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/15/13 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +59020,67584,61282,Probation,MCKINNEY,GARRY,NULL,Male,Caucasian,05/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/15/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +59020,67584,61282,Probation,MCKINNEY,GARRY,NULL,Male,Caucasian,05/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53802,67571,61271,PRETRIAL,ALONSO,LINETTE,MARIA,Female,Caucasian,08/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +53802,67571,61271,PRETRIAL,ALONSO,LINETTE,MARIA,Female,Caucasian,08/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +53802,67571,61271,PRETRIAL,ALONSO,LINETTE,MARIA,Female,Caucasian,08/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59005,67566,61267,PRETRIAL,hughes,alan,NULL,Male,Caucasian,10/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +59005,67566,61267,PRETRIAL,hughes,alan,NULL,Male,Caucasian,10/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +59005,67566,61267,PRETRIAL,hughes,alan,NULL,Male,Caucasian,10/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58992,67553,61254,PRETRIAL,Wright,Travis,NULL,Male,African-American,01/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +58992,67553,61254,PRETRIAL,Wright,Travis,NULL,Male,African-American,01/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,4,High,8,Risk of Recidivism,0.58,9,High,New,1,0 +58992,67553,61254,PRETRIAL,Wright,Travis,NULL,Male,African-American,01/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59023,67587,61285,Probation,Mendez,Michael,Rene,Male,Hispanic,03/31/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +59023,67587,61285,Probation,Mendez,Michael,Rene,Male,Hispanic,03/31/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +59023,67587,61285,Probation,Mendez,Michael,Rene,Male,Hispanic,03/31/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57719,67581,59858,Probation,diefenderfer,glen,NULL,Male,Caucasian,04/08/69,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,11/15/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +57719,67581,59858,Probation,diefenderfer,glen,NULL,Male,Caucasian,04/08/69,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +57719,67581,59858,Probation,diefenderfer,glen,NULL,Male,Caucasian,04/08/69,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +58999,67560,61261,PRETRIAL,Marino,Gina,NULL,Female,Hispanic,12/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +58999,67560,61261,PRETRIAL,Marino,Gina,NULL,Female,Hispanic,12/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +58999,67560,61261,PRETRIAL,Marino,Gina,NULL,Female,Hispanic,12/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59012,67573,61273,Probation,Garcia,Carlos,NULL,Male,Hispanic,04/14/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/15/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +59012,67573,61273,Probation,Garcia,Carlos,NULL,Male,Hispanic,04/14/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/15/13 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +59012,67573,61273,Probation,Garcia,Carlos,NULL,Male,Hispanic,04/14/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59013,67574,61274,Probation,chery,ronald,NULL,Male,African-American,01/09/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/15/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +59013,67574,61274,Probation,chery,ronald,NULL,Male,African-American,01/09/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +59013,67574,61274,Probation,chery,ronald,NULL,Male,African-American,01/09/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59019,67583,61281,Probation,Davis,Reginald,NULL,Male,African-American,08/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +59019,67583,61281,Probation,Davis,Reginald,NULL,Male,African-American,08/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +59019,67583,61281,Probation,Davis,Reginald,NULL,Male,African-American,08/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59021,67585,61283,Probation,Moreau,Brielle,NULL,Female,Caucasian,02/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +59021,67585,61283,Probation,Moreau,Brielle,NULL,Female,Caucasian,02/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +59021,67585,61283,Probation,Moreau,Brielle,NULL,Female,Caucasian,02/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58994,67555,61256,PRETRIAL,Barthelemy,Geranie,L,Male,Other,12/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/15/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +58994,67555,61256,PRETRIAL,Barthelemy,Geranie,L,Male,Other,12/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +58994,67555,61256,PRETRIAL,Barthelemy,Geranie,L,Male,Other,12/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59001,67562,61263,PRETRIAL,Dunn,Erin,Christine,Female,Caucasian,02/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +59001,67562,61263,PRETRIAL,Dunn,Erin,Christine,Female,Caucasian,02/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +59001,67562,61263,PRETRIAL,Dunn,Erin,Christine,Female,Caucasian,02/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59003,67564,61265,PRETRIAL,Fontanez,Edwin,NULL,Male,Caucasian,08/06/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/15/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +59003,67564,61265,PRETRIAL,Fontanez,Edwin,NULL,Male,Caucasian,08/06/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/15/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +59003,67564,61265,PRETRIAL,Fontanez,Edwin,NULL,Male,Caucasian,08/06/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/15/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59008,67569,61270,PRETRIAL,Darren,Houston,Lee,Male,African-American,04/13/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/15/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +59008,67569,61270,PRETRIAL,Darren,Houston,Lee,Male,African-American,04/13/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/15/13 0:00,4,High,8,Risk of Recidivism,0.27,8,High,New,1,0 +59008,67569,61270,PRETRIAL,Darren,Houston,Lee,Male,African-American,04/13/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/15/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +24325,67578,61277,PRETRIAL,Rifkind,Robert,NULL,Male,Caucasian,09/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +24325,67578,61277,PRETRIAL,Rifkind,Robert,NULL,Male,Caucasian,09/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +24325,67578,61277,PRETRIAL,Rifkind,Robert,NULL,Male,Caucasian,09/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58996,67557,61258,PRETRIAL,Al-Matteen,Zakiyyah,NULL,Female,African-American,05/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +58996,67557,61258,PRETRIAL,Al-Matteen,Zakiyyah,NULL,Female,African-American,05/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +58996,67557,61258,PRETRIAL,Al-Matteen,Zakiyyah,NULL,Female,African-American,05/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +59031,67604,61298,PRETRIAL,Adderly,Gerod,NULL,Male,African-American,02/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +59031,67604,61298,PRETRIAL,Adderly,Gerod,NULL,Male,African-American,02/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +59031,67604,61298,PRETRIAL,Adderly,Gerod,NULL,Male,African-American,02/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59028,67599,61294,PRETRIAL,Thompson,Jeremy,NULL,Male,African-American,06/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +59028,67599,61294,PRETRIAL,Thompson,Jeremy,NULL,Male,African-American,06/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +59028,67599,61294,PRETRIAL,Thompson,Jeremy,NULL,Male,African-American,06/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59033,67606,61300,PRETRIAL,LALLIER,ROBERT,NULL,Male,Caucasian,12/13/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +59033,67606,61300,PRETRIAL,LALLIER,ROBERT,NULL,Male,Caucasian,12/13/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +59033,67606,61300,PRETRIAL,LALLIER,ROBERT,NULL,Male,Caucasian,12/13/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +59025,67595,61290,PRETRIAL,McDougle,Calvin,NULL,Male,African-American,01/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/16/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +59025,67595,61290,PRETRIAL,McDougle,Calvin,NULL,Male,African-American,01/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/16/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +59025,67595,61290,PRETRIAL,McDougle,Calvin,NULL,Male,African-American,01/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +38194,67602,61296,PRETRIAL,Wilson,Omar,NULL,Male,African-American,06/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +38194,67602,61296,PRETRIAL,Wilson,Omar,NULL,Male,African-American,06/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +38194,67602,61296,PRETRIAL,Wilson,Omar,NULL,Male,African-American,06/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +34921,67594,34094,PRETRIAL,jasmin,jamil,travis,Male,African-American,10/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +34921,67594,34094,PRETRIAL,jasmin,jamil,travis,Male,African-American,10/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,Copy,1,0 +34921,67594,34094,PRETRIAL,jasmin,jamil,travis,Male,African-American,10/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +59032,67605,61299,PRETRIAL,Rodney,Odainey,NULL,Male,African-American,09/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +59032,67605,61299,PRETRIAL,Rodney,Odainey,NULL,Male,African-American,09/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +59032,67605,61299,PRETRIAL,Rodney,Odainey,NULL,Male,African-American,09/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59027,67597,61292,PRETRIAL,Filius,Christopher,Allen,Male,African-American,11/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +59027,67597,61292,PRETRIAL,Filius,Christopher,Allen,Male,African-American,11/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +59027,67597,61292,PRETRIAL,Filius,Christopher,Allen,Male,African-American,11/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59030,67603,61297,PRETRIAL,Paul,Lonny,Rawn,Male,Caucasian,12/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +59030,67603,61297,PRETRIAL,Paul,Lonny,Rawn,Male,Caucasian,12/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +59030,67603,61297,PRETRIAL,Paul,Lonny,Rawn,Male,Caucasian,12/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58728,67598,61293,PRETRIAL,CETOUTE,JARNY,NULL,Male,African-American,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +58728,67598,61293,PRETRIAL,CETOUTE,JARNY,NULL,Male,African-American,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +58728,67598,61293,PRETRIAL,CETOUTE,JARNY,NULL,Male,African-American,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +46610,67600,60404,Probation,perez,luis,NULL,Male,Other,03/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/16/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,Copy,1,0 +46610,67600,60404,Probation,perez,luis,NULL,Male,Other,03/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/16/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,Copy,1,0 +46610,67600,60404,Probation,perez,luis,NULL,Male,Other,03/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/16/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +59029,67601,61295,PRETRIAL,Degiovanni,Paul,NULL,Male,Caucasian,08/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +59029,67601,61295,PRETRIAL,Degiovanni,Paul,NULL,Male,Caucasian,08/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +59029,67601,61295,PRETRIAL,Degiovanni,Paul,NULL,Male,Caucasian,08/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59026,67596,61291,PRETRIAL,Santiago,Anthony,NULL,Male,Caucasian,06/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +59026,67596,61291,PRETRIAL,Santiago,Anthony,NULL,Male,Caucasian,06/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +59026,67596,61291,PRETRIAL,Santiago,Anthony,NULL,Male,Caucasian,06/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59045,67617,61310,PRETRIAL,Dor,Harold,Kareem,Male,African-American,06/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/17/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +59045,67617,61310,PRETRIAL,Dor,Harold,Kareem,Male,African-American,06/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/17/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +59045,67617,61310,PRETRIAL,Dor,Harold,Kareem,Male,African-American,06/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +34284,67609,33427,Probation,graham,tavarus,NULL,Male,African-American,07/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,Copy,1,0 +34284,67609,33427,Probation,graham,tavarus,NULL,Male,African-American,07/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,Copy,1,0 +34284,67609,33427,Probation,graham,tavarus,NULL,Male,African-American,07/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +59041,67614,61307,PRETRIAL,Heckart,Neil,NULL,Male,Caucasian,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +59041,67614,61307,PRETRIAL,Heckart,Neil,NULL,Male,Caucasian,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +59041,67614,61307,PRETRIAL,Heckart,Neil,NULL,Male,Caucasian,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +36613,67619,35907,Probation,Gibson,Charles,NULL,Male,Caucasian,02/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,Copy,1,0 +36613,67619,35907,Probation,Gibson,Charles,NULL,Male,Caucasian,02/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,Copy,1,0 +36613,67619,35907,Probation,Gibson,Charles,NULL,Male,Caucasian,02/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +59040,67612,61305,PRETRIAL,Jenkins,Antwon,T,Male,African-American,01/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,New,1,0 +59040,67612,61305,PRETRIAL,Jenkins,Antwon,T,Male,African-American,01/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +59040,67612,61305,PRETRIAL,Jenkins,Antwon,T,Male,African-American,01/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59044,67616,61309,PRETRIAL,DAVIS,ERNEST,JOVAN,Male,African-American,07/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/17/13 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +59044,67616,61309,PRETRIAL,DAVIS,ERNEST,JOVAN,Male,African-American,07/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +59044,67616,61309,PRETRIAL,DAVIS,ERNEST,JOVAN,Male,African-American,07/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/17/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59034,67607,61301,PRETRIAL,Williams,Sheron,NULL,Female,African-American,08/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/17/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +59034,67607,61301,PRETRIAL,Williams,Sheron,NULL,Female,African-American,08/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/17/13 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +59034,67607,61301,PRETRIAL,Williams,Sheron,NULL,Female,African-American,08/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/17/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59043,67615,61308,PRETRIAL,LIETZAU,DEAN,DONALD,Male,Caucasian,06/10/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/17/13 0:00,2,Medium,7,Risk of Violence,-3.45,1,Low,New,1,0 +59043,67615,61308,PRETRIAL,LIETZAU,DEAN,DONALD,Male,Caucasian,06/10/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +59043,67615,61308,PRETRIAL,LIETZAU,DEAN,DONALD,Male,Caucasian,06/10/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/17/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59036,67610,61303,PRETRIAL,SOUFFERANC,TEVIN,SHANE,Male,African-American,08/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,2,Medium,7,Risk of Violence,-1.39,7,Medium,New,1,0 +59036,67610,61303,PRETRIAL,SOUFFERANC,TEVIN,SHANE,Male,African-American,08/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +59036,67610,61303,PRETRIAL,SOUFFERANC,TEVIN,SHANE,Male,African-American,08/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59042,67613,61306,PRETRIAL,Suarez,Adriano,NULL,Male,Hispanic,01/02/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +59042,67613,61306,PRETRIAL,Suarez,Adriano,NULL,Male,Hispanic,01/02/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +59042,67613,61306,PRETRIAL,Suarez,Adriano,NULL,Male,Hispanic,01/02/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59049,67620,61312,PRETRIAL,CLAY,BRANDI,NULL,Female,Caucasian,08/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +59049,67620,61312,PRETRIAL,CLAY,BRANDI,NULL,Female,Caucasian,08/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,New,1,0 +59049,67620,61312,PRETRIAL,CLAY,BRANDI,NULL,Female,Caucasian,08/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +10497,67611,61304,PRETRIAL,BERMAN,BRIAN,VINCENT,Male,Caucasian,02/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +10497,67611,61304,PRETRIAL,BERMAN,BRIAN,VINCENT,Male,Caucasian,02/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +10497,67611,61304,PRETRIAL,BERMAN,BRIAN,VINCENT,Male,Caucasian,02/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59035,67608,61302,PRETRIAL,PEREZ,HERMES,NULL,Male,Caucasian,05/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +59035,67608,61302,PRETRIAL,PEREZ,HERMES,NULL,Male,Caucasian,05/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +59035,67608,61302,PRETRIAL,PEREZ,HERMES,NULL,Male,Caucasian,05/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58146,67625,61317,PRETRIAL,Tenney,Tyler,NULL,Male,African-American,07/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +58146,67625,61317,PRETRIAL,Tenney,Tyler,NULL,Male,African-American,07/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +58146,67625,61317,PRETRIAL,Tenney,Tyler,NULL,Male,African-American,07/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59057,67629,61321,PRETRIAL,Dewar,Vanessa,NULL,Female,Other,03/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +59057,67629,61321,PRETRIAL,Dewar,Vanessa,NULL,Female,Other,03/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +59057,67629,61321,PRETRIAL,Dewar,Vanessa,NULL,Female,Other,03/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59069,67646,61338,PRETRIAL,Joseph,Gonzales,NULL,Male,African-American,09/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/18/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +59069,67646,61338,PRETRIAL,Joseph,Gonzales,NULL,Male,African-American,09/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +59069,67646,61338,PRETRIAL,Joseph,Gonzales,NULL,Male,African-American,09/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59056,67627,61319,PRETRIAL,SCHROEDER,BARTON,JAMES,Male,Caucasian,08/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +59056,67627,61319,PRETRIAL,SCHROEDER,BARTON,JAMES,Male,Caucasian,08/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +59056,67627,61319,PRETRIAL,SCHROEDER,BARTON,JAMES,Male,Caucasian,08/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +46196,67641,61333,PRETRIAL,GALGANO,ANTHONY,NULL,Male,Caucasian,11/23/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +46196,67641,61333,PRETRIAL,GALGANO,ANTHONY,NULL,Male,Caucasian,11/23/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,8,Risk of Recidivism,-2.65,1,Low,New,1,0 +46196,67641,61333,PRETRIAL,GALGANO,ANTHONY,NULL,Male,Caucasian,11/23/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59060,67634,61326,Probation,Mataccchiera,Angela,NULL,Female,Caucasian,03/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +59060,67634,61326,Probation,Mataccchiera,Angela,NULL,Female,Caucasian,03/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +59060,67634,61326,Probation,Mataccchiera,Angela,NULL,Female,Caucasian,03/22/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59052,67623,61315,PRETRIAL,Delgado,Moises,NULL,Male,Caucasian,11/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +59052,67623,61315,PRETRIAL,Delgado,Moises,NULL,Male,Caucasian,11/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +59052,67623,61315,PRETRIAL,Delgado,Moises,NULL,Male,Caucasian,11/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59079,67660,61352,Probation,Defee,Teresa,NULL,Female,Caucasian,07/10/69,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Married,11/18/13 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +59079,67660,61352,Probation,Defee,Teresa,NULL,Female,Caucasian,07/10/69,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Married,11/18/13 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +59079,67660,61352,Probation,Defee,Teresa,NULL,Female,Caucasian,07/10/69,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Married,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +59058,67631,61323,PRETRIAL,Heagle,Robert,Lydell,Male,African-American,01/23/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +59058,67631,61323,PRETRIAL,Heagle,Robert,Lydell,Male,African-American,01/23/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +59058,67631,61323,PRETRIAL,Heagle,Robert,Lydell,Male,African-American,01/23/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51562,67636,61328,Probation,Lee,Kimberly,E,Female,African-American,09/06/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +51562,67636,61328,Probation,Lee,Kimberly,E,Female,African-American,09/06/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +51562,67636,61328,Probation,Lee,Kimberly,E,Female,African-American,09/06/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59070,67647,61339,PRETRIAL,Palacios,Tyrone,NULL,Male,Caucasian,04/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/18/13 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +59070,67647,61339,PRETRIAL,Palacios,Tyrone,NULL,Male,Caucasian,04/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/18/13 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +59070,67647,61339,PRETRIAL,Palacios,Tyrone,NULL,Male,Caucasian,04/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59054,67626,61318,PRETRIAL,WEGLARZ,CRISTINA,NULL,Female,Caucasian,10/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +59054,67626,61318,PRETRIAL,WEGLARZ,CRISTINA,NULL,Female,Caucasian,10/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/13 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +59054,67626,61318,PRETRIAL,WEGLARZ,CRISTINA,NULL,Female,Caucasian,10/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,29,9,High,New,1,0 +59078,67657,61349,Probation,Williams,Wilfred,NULL,Male,African-American,03/05/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +59078,67657,61349,Probation,Williams,Wilfred,NULL,Male,African-American,03/05/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +59078,67657,61349,Probation,Williams,Wilfred,NULL,Male,African-American,03/05/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55667,67644,61336,PRETRIAL,Palma,Dolres,NULL,Female,Caucasian,08/23/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +55667,67644,61336,PRETRIAL,Palma,Dolres,NULL,Female,Caucasian,08/23/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +55667,67644,61336,PRETRIAL,Palma,Dolres,NULL,Female,Caucasian,08/23/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59074,67652,61344,Probation,khosla,mohit,NULL,Male,Other,06/11/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +59074,67652,61344,Probation,khosla,mohit,NULL,Male,Other,06/11/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +59074,67652,61344,Probation,khosla,mohit,NULL,Male,Other,06/11/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45497,67654,61346,Probation,garcia,maria,NULL,Female,Hispanic,09/11/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +45497,67654,61346,Probation,garcia,maria,NULL,Female,Hispanic,09/11/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +45497,67654,61346,Probation,garcia,maria,NULL,Female,Hispanic,09/11/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +34134,67633,61325,PRETRIAL,Prenelus,Denny,NULL,Male,African-American,08/01/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +34134,67633,61325,PRETRIAL,Prenelus,Denny,NULL,Male,African-American,08/01/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +34134,67633,61325,PRETRIAL,Prenelus,Denny,NULL,Male,African-American,08/01/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52514,67782,61463,Probation,BRUCE,NATALIE,D,Female,Caucasian,12/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +52514,67782,61463,Probation,BRUCE,NATALIE,D,Female,Caucasian,12/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +52514,67782,61463,Probation,BRUCE,NATALIE,D,Female,Caucasian,12/09/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59064,67637,61329,Probation,Johnson,Sharissa,NULL,Female,African-American,09/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +59064,67637,61329,Probation,Johnson,Sharissa,NULL,Female,African-American,09/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +59064,67637,61329,Probation,Johnson,Sharissa,NULL,Female,African-American,09/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59050,67621,61313,PRETRIAL,HOSSAIN,AKHTER,NULL,Male,Other,09/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +59050,67621,61313,PRETRIAL,HOSSAIN,AKHTER,NULL,Male,Other,09/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +59050,67621,61313,PRETRIAL,HOSSAIN,AKHTER,NULL,Male,Other,09/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +6380,67628,61320,PRETRIAL,QUINTANILLA,RICARDO,NULL,Male,Hispanic,05/13/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +6380,67628,61320,PRETRIAL,QUINTANILLA,RICARDO,NULL,Male,Hispanic,05/13/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +6380,67628,61320,PRETRIAL,QUINTANILLA,RICARDO,NULL,Male,Hispanic,05/13/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59071,67649,61341,Probation,Vargas,Enancel,NULL,Male,Hispanic,05/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +59071,67649,61341,Probation,Vargas,Enancel,NULL,Male,Hispanic,05/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +59071,67649,61341,Probation,Vargas,Enancel,NULL,Male,Hispanic,05/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59077,67656,61348,Probation,CRISPINO,JOHN,NULL,Male,Caucasian,11/25/63,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,11/18/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +59077,67656,61348,Probation,CRISPINO,JOHN,NULL,Male,Caucasian,11/25/63,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +59077,67656,61348,Probation,CRISPINO,JOHN,NULL,Male,Caucasian,11/25/63,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53442,67642,61334,PRETRIAL,Cockroft,Enrico,NULL,Male,African-American,07/23/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/13 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,New,1,0 +53442,67642,61334,PRETRIAL,Cockroft,Enrico,NULL,Male,African-American,07/23/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +53442,67642,61334,PRETRIAL,Cockroft,Enrico,NULL,Male,African-American,07/23/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59061,67635,61327,PRETRIAL,WRIGHT,BLAIR,NULL,Male,Caucasian,08/21/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/18/13 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +59061,67635,61327,PRETRIAL,WRIGHT,BLAIR,NULL,Male,Caucasian,08/21/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/18/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +59061,67635,61327,PRETRIAL,WRIGHT,BLAIR,NULL,Male,Caucasian,08/21/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59072,67648,61340,PRETRIAL,Jones,Evon,Allan,Male,African-American,10/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +59072,67648,61340,PRETRIAL,Jones,Evon,Allan,Male,African-American,10/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +59072,67648,61340,PRETRIAL,Jones,Evon,Allan,Male,African-American,10/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59051,67622,61314,PRETRIAL,GUEDES,MARISSA,ALTAGRACIA,Female,Caucasian,07/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +59051,67622,61314,PRETRIAL,GUEDES,MARISSA,ALTAGRACIA,Female,Caucasian,07/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +59051,67622,61314,PRETRIAL,GUEDES,MARISSA,ALTAGRACIA,Female,Caucasian,07/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59066,67640,61332,PRETRIAL,slone,jillian,NULL,Female,Caucasian,07/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +59066,67640,61332,PRETRIAL,slone,jillian,NULL,Female,Caucasian,07/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +59066,67640,61332,PRETRIAL,slone,jillian,NULL,Female,Caucasian,07/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59067,67643,61335,PRETRIAL,TORRES,JEREMY,NULL,Male,Hispanic,03/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +59067,67643,61335,PRETRIAL,TORRES,JEREMY,NULL,Male,Hispanic,03/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +59067,67643,61335,PRETRIAL,TORRES,JEREMY,NULL,Male,Hispanic,03/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59053,67624,61316,PRETRIAL,MIXON,DON,CORNILIA,Male,African-American,10/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +59053,67624,61316,PRETRIAL,MIXON,DON,CORNILIA,Male,African-American,10/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/13 0:00,4,High,8,Risk of Recidivism,0.36,9,High,New,1,0 +59053,67624,61316,PRETRIAL,MIXON,DON,CORNILIA,Male,African-American,10/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +51740,67659,61351,PRETRIAL,allen,carlos,NULL,Male,Hispanic,01/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +51740,67659,61351,PRETRIAL,allen,carlos,NULL,Male,Hispanic,01/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +51740,67659,61351,PRETRIAL,allen,carlos,NULL,Male,Hispanic,01/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59065,67638,61330,Probation,SCOTTJOHNSON,LASHANNA,NULL,Female,African-American,09/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +59065,67638,61330,Probation,SCOTTJOHNSON,LASHANNA,NULL,Female,African-American,09/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +59065,67638,61330,Probation,SCOTTJOHNSON,LASHANNA,NULL,Female,African-American,09/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59068,67645,61337,PRETRIAL,carter,tyrone,NULL,Male,African-American,11/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/13 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +59068,67645,61337,PRETRIAL,carter,tyrone,NULL,Male,African-American,11/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/13 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +59068,67645,61337,PRETRIAL,carter,tyrone,NULL,Male,African-American,11/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59059,67632,61324,PRETRIAL,Morgan,Mariana,NULL,Female,Caucasian,11/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/18/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +59059,67632,61324,PRETRIAL,Morgan,Mariana,NULL,Female,Caucasian,11/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +59059,67632,61324,PRETRIAL,Morgan,Mariana,NULL,Female,Caucasian,11/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/18/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +43778,67651,61343,PRETRIAL,COSYN,JOHN,NULL,Male,Caucasian,08/15/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,11/18/13 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +43778,67651,61343,PRETRIAL,COSYN,JOHN,NULL,Male,Caucasian,08/15/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,11/18/13 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +43778,67651,61343,PRETRIAL,COSYN,JOHN,NULL,Male,Caucasian,08/15/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59055,67630,61322,PRETRIAL,Baxterskeffrey,Shinell,NULL,Female,Other,09/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +59055,67630,61322,PRETRIAL,Baxterskeffrey,Shinell,NULL,Female,Other,09/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +59055,67630,61322,PRETRIAL,Baxterskeffrey,Shinell,NULL,Female,Other,09/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59075,67653,61345,Probation,Luna,Alberto,NULL,Male,Hispanic,07/26/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +59075,67653,61345,Probation,Luna,Alberto,NULL,Male,Hispanic,07/26/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +59075,67653,61345,Probation,Luna,Alberto,NULL,Male,Hispanic,07/26/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59101,67687,61375,PRETRIAL,CEMELUS,CELOUES,NULL,Male,African-American,01/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +59101,67687,61375,PRETRIAL,CEMELUS,CELOUES,NULL,Male,African-American,01/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,4,High,8,Risk of Recidivism,0.2,8,High,New,1,0 +59101,67687,61375,PRETRIAL,CEMELUS,CELOUES,NULL,Male,African-American,01/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59086,67666,61358,PRETRIAL,CALIX,GREGORY,NULL,Male,African-American,10/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +59086,67666,61358,PRETRIAL,CALIX,GREGORY,NULL,Male,African-American,10/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,4,High,8,Risk of Recidivism,0.12,8,High,New,1,0 +59086,67666,61358,PRETRIAL,CALIX,GREGORY,NULL,Male,African-American,10/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59105,67695,61382,Probation,York,Taj,NULL,Male,African-American,08/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +59105,67695,61382,Probation,York,Taj,NULL,Male,African-American,08/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,New,1,0 +59105,67695,61382,Probation,York,Taj,NULL,Male,African-American,08/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +25062,67674,56391,PRETRIAL,Overby,Christopher,NULL,Male,Caucasian,04/07/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,Copy,1,0 +25062,67674,56391,PRETRIAL,Overby,Christopher,NULL,Male,Caucasian,04/07/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.63,10,High,Copy,1,0 +25062,67674,56391,PRETRIAL,Overby,Christopher,NULL,Male,Caucasian,04/07/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +59103,67690,61377,PRETRIAL,Gutirrez,Jose,NULL,Male,Hispanic,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,Copy,1,0 +59103,67690,61377,PRETRIAL,Gutirrez,Jose,NULL,Male,Hispanic,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,Copy,1,0 +59103,67690,61377,PRETRIAL,Gutirrez,Jose,NULL,Male,Hispanic,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +59082,67661,61353,PRETRIAL,FRAZIER,RAFAEL,ZORAN,Male,African-American,08/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +59082,67661,61353,PRETRIAL,FRAZIER,RAFAEL,ZORAN,Male,African-American,08/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +59082,67661,61353,PRETRIAL,FRAZIER,RAFAEL,ZORAN,Male,African-American,08/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59097,67682,61371,PRETRIAL,DEMMERT,NORA,NULL,Female,Caucasian,10/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +59097,67682,61371,PRETRIAL,DEMMERT,NORA,NULL,Female,Caucasian,10/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +59097,67682,61371,PRETRIAL,DEMMERT,NORA,NULL,Female,Caucasian,10/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +23292,67669,61361,PRETRIAL,Young,Adam,G,Male,Caucasian,04/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +23292,67669,61361,PRETRIAL,Young,Adam,G,Male,Caucasian,04/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +23292,67669,61361,PRETRIAL,Young,Adam,G,Male,Caucasian,04/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59093,67677,61366,Probation,Nisall,Jared,Isadore,Male,Caucasian,12/22/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/19/13 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +59093,67677,61366,Probation,Nisall,Jared,Isadore,Male,Caucasian,12/22/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +59093,67677,61366,Probation,Nisall,Jared,Isadore,Male,Caucasian,12/22/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/19/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +30171,67691,61378,PRETRIAL,Kuzmickie,Nicholas,Vincent,Male,Caucasian,09/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +30171,67691,61378,PRETRIAL,Kuzmickie,Nicholas,Vincent,Male,Caucasian,09/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +30171,67691,61378,PRETRIAL,Kuzmickie,Nicholas,Vincent,Male,Caucasian,09/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +22711,67663,61355,PRETRIAL,ORISME,MICHELET,NULL,Male,African-American,07/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +22711,67663,61355,PRETRIAL,ORISME,MICHELET,NULL,Male,African-American,07/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +22711,67663,61355,PRETRIAL,ORISME,MICHELET,NULL,Male,African-American,07/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59089,67670,61362,PRETRIAL,Bentley,Travon,NULL,Male,African-American,11/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +59089,67670,61362,PRETRIAL,Bentley,Travon,NULL,Male,African-American,11/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +59089,67670,61362,PRETRIAL,Bentley,Travon,NULL,Male,African-American,11/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59098,67684,61372,PRETRIAL,Davis,Ulysses,NULL,Male,African-American,05/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +59098,67684,61372,PRETRIAL,Davis,Ulysses,NULL,Male,African-American,05/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +59098,67684,61372,PRETRIAL,Davis,Ulysses,NULL,Male,African-American,05/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59094,67679,61368,Probation,Maria,Brant,NULL,Female,African-American,11/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +59094,67679,61368,Probation,Maria,Brant,NULL,Female,African-American,11/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +59094,67679,61368,Probation,Maria,Brant,NULL,Female,African-American,11/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +31415,67675,58921,Probation,Carpio,Peter,NULL,Male,Caucasian,11/13/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,Copy,1,0 +31415,67675,58921,Probation,Carpio,Peter,NULL,Male,Caucasian,11/13/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,Copy,1,0 +31415,67675,58921,Probation,Carpio,Peter,NULL,Male,Caucasian,11/13/75,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +21777,67693,61380,Probation,SANTIAGOGRIER,JOSEPH,NULL,Male,Hispanic,10/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +21777,67693,61380,Probation,SANTIAGOGRIER,JOSEPH,NULL,Male,Hispanic,10/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +21777,67693,61380,Probation,SANTIAGOGRIER,JOSEPH,NULL,Male,Hispanic,10/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59085,67665,61357,PRETRIAL,SAINTJUSTE,WENDY,NULL,Female,Other,11/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +59085,67665,61357,PRETRIAL,SAINTJUSTE,WENDY,NULL,Female,Other,11/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +59085,67665,61357,PRETRIAL,SAINTJUSTE,WENDY,NULL,Female,Other,11/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +30929,67678,61367,PRETRIAL,Williams,Rickie,NULL,Male,African-American,03/08/68,17,All Scales,Intake,English,Other,Jail Inmate,Single,11/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +30929,67678,61367,PRETRIAL,Williams,Rickie,NULL,Male,African-American,03/08/68,17,All Scales,Intake,English,Other,Jail Inmate,Single,11/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,New,1,0 +30929,67678,61367,PRETRIAL,Williams,Rickie,NULL,Male,African-American,03/08/68,17,All Scales,Intake,English,Other,Jail Inmate,Single,11/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,39,10,High,New,1,0 +45843,67686,61374,PRETRIAL,REIBOLD,PETER,NULL,Male,Caucasian,06/09/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/19/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +45843,67686,61374,PRETRIAL,REIBOLD,PETER,NULL,Male,Caucasian,06/09/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/19/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +45843,67686,61374,PRETRIAL,REIBOLD,PETER,NULL,Male,Caucasian,06/09/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59102,67688,61376,PRETRIAL,Georges,Jamsly,NULL,Male,African-American,06/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/19/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +59102,67688,61376,PRETRIAL,Georges,Jamsly,NULL,Male,African-American,06/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/19/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +59102,67688,61376,PRETRIAL,Georges,Jamsly,NULL,Male,African-American,06/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59091,67673,61364,PRETRIAL,RENDER,JAMES,NULL,Male,African-American,04/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +59091,67673,61364,PRETRIAL,RENDER,JAMES,NULL,Male,African-American,04/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +59091,67673,61364,PRETRIAL,RENDER,JAMES,NULL,Male,African-American,04/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59088,67668,61360,PRETRIAL,Session,Tavon,Jauwan,Male,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,4,High,7,Risk of Violence,-0.24,10,High,New,1,0 +59088,67668,61360,PRETRIAL,Session,Tavon,Jauwan,Male,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,4,High,8,Risk of Recidivism,1.01,10,High,New,1,0 +59088,67668,61360,PRETRIAL,Session,Tavon,Jauwan,Male,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59104,67694,61381,Probation,Montalvo,Louise,NULL,Female,Hispanic,12/18/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +59104,67694,61381,Probation,Montalvo,Louise,NULL,Female,Hispanic,12/18/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +59104,67694,61381,Probation,Montalvo,Louise,NULL,Female,Hispanic,12/18/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59099,67685,61373,Probation,Troxell,Paul,NULL,Male,Caucasian,09/15/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +59099,67685,61373,Probation,Troxell,Paul,NULL,Male,Caucasian,09/15/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +59099,67685,61373,Probation,Troxell,Paul,NULL,Male,Caucasian,09/15/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59083,67662,61354,PRETRIAL,HARRIS,TROY,J,Male,African-American,09/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +59083,67662,61354,PRETRIAL,HARRIS,TROY,J,Male,African-American,09/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +59083,67662,61354,PRETRIAL,HARRIS,TROY,J,Male,African-American,09/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59084,67664,61356,PRETRIAL,Brown,Alando,D,Male,African-American,05/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +59084,67664,61356,PRETRIAL,Brown,Alando,D,Male,African-American,05/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +59084,67664,61356,PRETRIAL,Brown,Alando,D,Male,African-American,05/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +47808,67692,61379,PRETRIAL,Ladin,Aharon,NULL,Male,Caucasian,07/17/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +47808,67692,61379,PRETRIAL,Ladin,Aharon,NULL,Male,Caucasian,07/17/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +47808,67692,61379,PRETRIAL,Ladin,Aharon,NULL,Male,Caucasian,07/17/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59090,67671,61363,PRETRIAL,Smith,Jerome,NULL,Male,African-American,12/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +59090,67671,61363,PRETRIAL,Smith,Jerome,NULL,Male,African-American,12/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +59090,67671,61363,PRETRIAL,Smith,Jerome,NULL,Male,African-American,12/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59095,67680,61369,PRETRIAL,Hoyt,Kyle,NULL,Male,Caucasian,05/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +59095,67680,61369,PRETRIAL,Hoyt,Kyle,NULL,Male,Caucasian,05/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +59095,67680,61369,PRETRIAL,Hoyt,Kyle,NULL,Male,Caucasian,05/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59087,67667,61359,PRETRIAL,ARNESON,RICKY,NULL,Male,Caucasian,01/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/13 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +59087,67667,61359,PRETRIAL,ARNESON,RICKY,NULL,Male,Caucasian,01/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +59087,67667,61359,PRETRIAL,ARNESON,RICKY,NULL,Male,Caucasian,01/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59092,67676,61365,Probation,ESTES,COREY,NULL,Male,Caucasian,05/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +59092,67676,61365,Probation,ESTES,COREY,NULL,Male,Caucasian,05/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +59092,67676,61365,Probation,ESTES,COREY,NULL,Male,Caucasian,05/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +8538,67697,61384,DRRD,Harrell,Sandy,None,Male,African-American,04/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +8538,67697,61384,DRRD,Harrell,Sandy,None,Male,African-American,04/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +8538,67697,61384,DRRD,Harrell,Sandy,None,Male,African-American,04/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52706,67722,61406,PRETRIAL,HYNES,CEDRIC,LEE,Male,African-American,05/04/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +52706,67722,61406,PRETRIAL,HYNES,CEDRIC,LEE,Male,African-American,05/04/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +52706,67722,61406,PRETRIAL,HYNES,CEDRIC,LEE,Male,African-American,05/04/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51061,67736,61419,PRETRIAL,MAROLD,MICHAEL,ROBERT,Male,Caucasian,05/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +51061,67736,61419,PRETRIAL,MAROLD,MICHAEL,ROBERT,Male,Caucasian,05/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,9,High,New,1,0 +51061,67736,61419,PRETRIAL,MAROLD,MICHAEL,ROBERT,Male,Caucasian,05/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59109,67701,61388,PRETRIAL,Willoughby,Calvin,NULL,Male,African-American,09/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +59109,67701,61388,PRETRIAL,Willoughby,Calvin,NULL,Male,African-American,09/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +59109,67701,61388,PRETRIAL,Willoughby,Calvin,NULL,Male,African-American,09/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58665,67718,60882,PRETRIAL,Knight,Mitchell,NULL,Male,African-American,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,Copy,1,0 +58665,67718,60882,PRETRIAL,Knight,Mitchell,NULL,Male,African-American,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,Copy,1,0 +58665,67718,60882,PRETRIAL,Knight,Mitchell,NULL,Male,African-American,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +52635,67727,61411,PRETRIAL,Brown,Daniel,Kendrick,Male,Caucasian,12/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/20/13 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +52635,67727,61411,PRETRIAL,Brown,Daniel,Kendrick,Male,Caucasian,12/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/20/13 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +52635,67727,61411,PRETRIAL,Brown,Daniel,Kendrick,Male,Caucasian,12/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +17894,67706,61393,PRETRIAL,FARMAN,ANDRE,NULL,Male,Caucasian,06/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +17894,67706,61393,PRETRIAL,FARMAN,ANDRE,NULL,Male,Caucasian,06/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +17894,67706,61393,PRETRIAL,FARMAN,ANDRE,NULL,Male,Caucasian,06/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +59123,67713,61399,PRETRIAL,Armstrong,Dominic,NULL,Male,African-American,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.37,3,Low,New,1,0 +59123,67713,61399,PRETRIAL,Armstrong,Dominic,NULL,Male,African-American,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +59123,67713,61399,PRETRIAL,Armstrong,Dominic,NULL,Male,African-American,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +59127,67720,61404,PRETRIAL,LATOURCLARKE,SIBTHORPE,NULL,Male,African-American,06/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +59127,67720,61404,PRETRIAL,LATOURCLARKE,SIBTHORPE,NULL,Male,African-American,06/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +59127,67720,61404,PRETRIAL,LATOURCLARKE,SIBTHORPE,NULL,Male,African-American,06/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59106,67696,61383,PRETRIAL,ADDIS,STEVEN,NULL,Male,Caucasian,12/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +59106,67696,61383,PRETRIAL,ADDIS,STEVEN,NULL,Male,Caucasian,12/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +59106,67696,61383,PRETRIAL,ADDIS,STEVEN,NULL,Male,Caucasian,12/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59128,67723,61407,Probation,PIZZA,ALEXANDER,NULL,Male,Caucasian,05/24/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +59128,67723,61407,Probation,PIZZA,ALEXANDER,NULL,Male,Caucasian,05/24/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +59128,67723,61407,Probation,PIZZA,ALEXANDER,NULL,Male,Caucasian,05/24/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59133,67730,61414,Probation,JONES,MICHAEL,P,Male,African-American,12/20/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +59133,67730,61414,Probation,JONES,MICHAEL,P,Male,African-American,12/20/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +59133,67730,61414,Probation,JONES,MICHAEL,P,Male,African-American,12/20/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59110,67702,61389,PRETRIAL,Fluker,Eddie,James,Male,African-American,12/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +59110,67702,61389,PRETRIAL,Fluker,Eddie,James,Male,African-American,12/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +59110,67702,61389,PRETRIAL,Fluker,Eddie,James,Male,African-American,12/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59125,67715,61401,Probation,Davis,Samuel,NULL,Male,Caucasian,04/10/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +59125,67715,61401,Probation,Davis,Samuel,NULL,Male,Caucasian,04/10/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +59125,67715,61401,Probation,Davis,Samuel,NULL,Male,Caucasian,04/10/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59116,67709,61396,PRETRIAL,Harris,Christopher,NULL,Male,African-American,03/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +59116,67709,61396,PRETRIAL,Harris,Christopher,NULL,Male,African-American,03/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +59116,67709,61396,PRETRIAL,Harris,Christopher,NULL,Male,African-American,03/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59117,67710,61397,PRETRIAL,CONNELLY,CHRISTOPHER,NULL,Male,Caucasian,06/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +59117,67710,61397,PRETRIAL,CONNELLY,CHRISTOPHER,NULL,Male,Caucasian,06/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +59117,67710,61397,PRETRIAL,CONNELLY,CHRISTOPHER,NULL,Male,Caucasian,06/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59134,67731,61415,Probation,Georges,James,NULL,Male,African-American,04/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +59134,67731,61415,Probation,Georges,James,NULL,Male,African-American,04/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +59134,67731,61415,Probation,Georges,James,NULL,Male,African-American,04/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59138,67738,61421,PRETRIAL,Livingston,Taveunshae,NULL,Female,African-American,09/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,4,High,7,Risk of Violence,-0.61,10,High,New,1,0 +59138,67738,61421,PRETRIAL,Livingston,Taveunshae,NULL,Female,African-American,09/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,4,High,8,Risk of Recidivism,0.91,10,High,New,1,0 +59138,67738,61421,PRETRIAL,Livingston,Taveunshae,NULL,Female,African-American,09/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59112,67704,61391,PRETRIAL,BROWN,MARIO,LETROY,Male,Caucasian,11/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +59112,67704,61391,PRETRIAL,BROWN,MARIO,LETROY,Male,Caucasian,11/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +59112,67704,61391,PRETRIAL,BROWN,MARIO,LETROY,Male,Caucasian,11/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59114,67707,61394,PRETRIAL,Bedoya,Jaime,Ricardo,Male,Caucasian,09/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +59114,67707,61394,PRETRIAL,Bedoya,Jaime,Ricardo,Male,Caucasian,09/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +59114,67707,61394,PRETRIAL,Bedoya,Jaime,Ricardo,Male,Caucasian,09/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59129,67725,61409,Probation,pollock,ray,NULL,Male,African-American,07/14/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/20/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +59129,67725,61409,Probation,pollock,ray,NULL,Male,African-American,07/14/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/20/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +59129,67725,61409,Probation,pollock,ray,NULL,Male,African-American,07/14/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59119,67712,61398,Probation,spence,andrew,NULL,Male,African-American,03/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +59119,67712,61398,Probation,spence,andrew,NULL,Male,African-American,03/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +59119,67712,61398,Probation,spence,andrew,NULL,Male,African-American,03/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59108,67699,61386,PRETRIAL,BATSON,TIFFANEY,ANNETE,Female,African-American,05/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +59108,67699,61386,PRETRIAL,BATSON,TIFFANEY,ANNETE,Female,African-American,05/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +59108,67699,61386,PRETRIAL,BATSON,TIFFANEY,ANNETE,Female,African-American,05/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +45465,67733,61417,PRETRIAL,Augustinparks,Christopher,NULL,Male,Other,07/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +45465,67733,61417,PRETRIAL,Augustinparks,Christopher,NULL,Male,Other,07/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +45465,67733,61417,PRETRIAL,Augustinparks,Christopher,NULL,Male,Other,07/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59131,67726,61410,Probation,HEALD,GUISELL,C,Female,Hispanic,07/31/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/20/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +59131,67726,61410,Probation,HEALD,GUISELL,C,Female,Hispanic,07/31/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/20/13 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +59131,67726,61410,Probation,HEALD,GUISELL,C,Female,Hispanic,07/31/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59113,67705,61392,PRETRIAL,ONUFER,MARK,NULL,Male,Caucasian,11/02/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/13 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +59113,67705,61392,PRETRIAL,ONUFER,MARK,NULL,Male,Caucasian,11/02/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/13 0:00,1,Low,8,Risk of Recidivism,-2.69,1,Low,New,1,0 +59113,67705,61392,PRETRIAL,ONUFER,MARK,NULL,Male,Caucasian,11/02/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59124,67714,61400,Probation,JAMES,DARIUS,R,Male,African-American,08/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/20/13 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +59124,67714,61400,Probation,JAMES,DARIUS,R,Male,African-American,08/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/20/13 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +59124,67714,61400,Probation,JAMES,DARIUS,R,Male,African-American,08/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/20/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59088,67700,61387,PRETRIAL,Session,Tavon,Jauwan,Male,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,4,High,7,Risk of Violence,-0.24,10,High,New,1,0 +59088,67700,61387,PRETRIAL,Session,Tavon,Jauwan,Male,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,4,High,8,Risk of Recidivism,1.05,10,High,New,1,0 +59088,67700,61387,PRETRIAL,Session,Tavon,Jauwan,Male,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59107,67698,61385,PRETRIAL,DOE,LATARA,S,Female,African-American,02/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +59107,67698,61385,PRETRIAL,DOE,LATARA,S,Female,African-American,02/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +59107,67698,61385,PRETRIAL,DOE,LATARA,S,Female,African-American,02/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59126,67719,61403,PRETRIAL,Gilbert,Xavier,Alenander,Male,African-American,11/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +59126,67719,61403,PRETRIAL,Gilbert,Xavier,Alenander,Male,African-American,11/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +59126,67719,61403,PRETRIAL,Gilbert,Xavier,Alenander,Male,African-American,11/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +24065,67721,61405,PRETRIAL,KROLL,DAVID,NULL,Male,Caucasian,07/19/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +24065,67721,61405,PRETRIAL,KROLL,DAVID,NULL,Male,Caucasian,07/19/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +24065,67721,61405,PRETRIAL,KROLL,DAVID,NULL,Male,Caucasian,07/19/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51521,67728,61412,PRETRIAL,Burgos,David,Anthony,Male,Caucasian,06/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +51521,67728,61412,PRETRIAL,Burgos,David,Anthony,Male,Caucasian,06/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +51521,67728,61412,PRETRIAL,Burgos,David,Anthony,Male,Caucasian,06/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59111,67703,61390,PRETRIAL,Quarrie,Leighton,NULL,Male,African-American,04/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +59111,67703,61390,PRETRIAL,Quarrie,Leighton,NULL,Male,African-American,04/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +59111,67703,61390,PRETRIAL,Quarrie,Leighton,NULL,Male,African-American,04/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59137,67737,61420,PRETRIAL,Hand,Eric,NULL,Male,Caucasian,11/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +59137,67737,61420,PRETRIAL,Hand,Eric,NULL,Male,Caucasian,11/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +59137,67737,61420,PRETRIAL,Hand,Eric,NULL,Male,Caucasian,11/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +35807,67716,61402,PRETRIAL,Martin,Xavier,NULL,Male,African-American,09/28/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/20/13 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +35807,67716,61402,PRETRIAL,Martin,Xavier,NULL,Male,African-American,09/28/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/20/13 0:00,4,High,8,Risk of Recidivism,0.32,9,High,New,1,0 +35807,67716,61402,PRETRIAL,Martin,Xavier,NULL,Male,African-American,09/28/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/20/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58643,67711,60857,PRETRIAL,Nioka,Myrie,NULL,Female,African-American,04/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,Copy,1,0 +58643,67711,60857,PRETRIAL,Nioka,Myrie,NULL,Female,African-American,04/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,Copy,1,0 +58643,67711,60857,PRETRIAL,Nioka,Myrie,NULL,Female,African-American,04/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +59132,67729,61413,Probation,persuad,Nicholas,NULL,Male,Other,01/01/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/20/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +59132,67729,61413,Probation,persuad,Nicholas,NULL,Male,Other,01/01/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/20/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +59132,67729,61413,Probation,persuad,Nicholas,NULL,Male,Other,01/01/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59115,67708,61395,PRETRIAL,Spencer,Randail,NULL,Male,African-American,02/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +59115,67708,61395,PRETRIAL,Spencer,Randail,NULL,Male,African-American,02/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +59115,67708,61395,PRETRIAL,Spencer,Randail,NULL,Male,African-American,02/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59130,67724,61408,Probation,Sedmak,Timothy,NULL,Male,Caucasian,07/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +59130,67724,61408,Probation,Sedmak,Timothy,NULL,Male,Caucasian,07/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +59130,67724,61408,Probation,Sedmak,Timothy,NULL,Male,Caucasian,07/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59156,67760,61441,Probation,estrada,pedro,NULL,Male,Hispanic,10/05/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +59156,67760,61441,Probation,estrada,pedro,NULL,Male,Hispanic,10/05/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +59156,67760,61441,Probation,estrada,pedro,NULL,Male,Hispanic,10/05/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59143,67745,61428,Probation,Greggs,VINCENT,NULL,Male,African-American,01/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +59143,67745,61428,Probation,Greggs,VINCENT,NULL,Male,African-American,01/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +59143,67745,61428,Probation,Greggs,VINCENT,NULL,Male,African-American,01/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59160,67766,61447,PRETRIAL,Butler,Marvin,NULL,Male,African-American,10/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.79,9,High,New,1,0 +59160,67766,61447,PRETRIAL,Butler,Marvin,NULL,Male,African-American,10/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +59160,67766,61447,PRETRIAL,Butler,Marvin,NULL,Male,African-American,10/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59146,67753,61435,PRETRIAL,Fairchild,Quanana`,NULL,Female,African-American,12/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/21/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +59146,67753,61435,PRETRIAL,Fairchild,Quanana`,NULL,Female,African-American,12/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/21/13 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +59146,67753,61435,PRETRIAL,Fairchild,Quanana`,NULL,Female,African-American,12/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59153,67758,61439,PRETRIAL,sluder,christi,NULL,Female,Caucasian,03/16/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/21/13 0:00,2,Medium,7,Risk of Violence,-2.64,2,Low,New,1,0 +59153,67758,61439,PRETRIAL,sluder,christi,NULL,Female,Caucasian,03/16/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +59153,67758,61439,PRETRIAL,sluder,christi,NULL,Female,Caucasian,03/16/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/21/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +59147,67750,61432,Probation,Turner,Marilyn,NULL,Female,African-American,10/28/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/13 0:00,2,Medium,7,Risk of Violence,-2.61,2,Low,New,1,0 +59147,67750,61432,Probation,Turner,Marilyn,NULL,Female,African-American,10/28/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +59147,67750,61432,Probation,Turner,Marilyn,NULL,Female,African-American,10/28/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +1636,67749,61431,PRETRIAL,Bates,Wesley,Ryan,Male,Caucasian,08/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/21/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +1636,67749,61431,PRETRIAL,Bates,Wesley,Ryan,Male,Caucasian,08/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/21/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +1636,67749,61431,PRETRIAL,Bates,Wesley,Ryan,Male,Caucasian,08/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/21/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58642,67756,60856,DRRD,Strayhorn,Saphoria,NULL,Female,African-American,12/04/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +58642,67756,60856,DRRD,Strayhorn,Saphoria,NULL,Female,African-American,12/04/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +58642,67756,60856,DRRD,Strayhorn,Saphoria,NULL,Female,African-American,12/04/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,2,Medium,18,Risk of Failure to Appear,18,2,Low,New,1,0 +7355,67763,61444,Probation,Smith,Xavier,NULL,Male,African-American,11/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +7355,67763,61444,Probation,Smith,Xavier,NULL,Male,African-American,11/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.68,10,High,New,1,0 +7355,67763,61444,Probation,Smith,Xavier,NULL,Male,African-American,11/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +59141,67742,61425,PRETRIAL,jones,sidney,NULL,Male,African-American,02/20/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +59141,67742,61425,PRETRIAL,jones,sidney,NULL,Male,African-American,02/20/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,9,High,New,1,0 +59141,67742,61425,PRETRIAL,jones,sidney,NULL,Male,African-American,02/20/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59142,67744,61427,Probation,Thomas,Mark,Alan,Male,Caucasian,08/05/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/21/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +59142,67744,61427,Probation,Thomas,Mark,Alan,Male,Caucasian,08/05/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/21/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +59142,67744,61427,Probation,Thomas,Mark,Alan,Male,Caucasian,08/05/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +25568,67765,61446,Probation,malisani,mauricio,NULL,Male,Hispanic,09/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/13 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +25568,67765,61446,Probation,malisani,mauricio,NULL,Male,Hispanic,09/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +25568,67765,61446,Probation,malisani,mauricio,NULL,Male,Hispanic,09/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59139,67740,61423,PRETRIAL,VEGA,JORGE,NULL,Male,Caucasian,07/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/13 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +59139,67740,61423,PRETRIAL,VEGA,JORGE,NULL,Male,Caucasian,07/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/13 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +59139,67740,61423,PRETRIAL,VEGA,JORGE,NULL,Male,Caucasian,07/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +32776,67747,31828,PRETRIAL,Mercado,Luis,NULL,Male,Caucasian,06/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,Copy,1,0 +32776,67747,31828,PRETRIAL,Mercado,Luis,NULL,Male,Caucasian,06/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,Copy,1,0 +32776,67747,31828,PRETRIAL,Mercado,Luis,NULL,Male,Caucasian,06/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +49194,67761,61442,PRETRIAL,Cacopedro,Peter,NULL,Male,Caucasian,09/20/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/13 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +49194,67761,61442,PRETRIAL,Cacopedro,Peter,NULL,Male,Caucasian,09/20/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/13 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +49194,67761,61442,PRETRIAL,Cacopedro,Peter,NULL,Male,Caucasian,09/20/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59161,67767,61448,Probation,Granthon,Hugo,NULL,Male,Hispanic,04/02/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +59161,67767,61448,Probation,Granthon,Hugo,NULL,Male,Hispanic,04/02/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +59161,67767,61448,Probation,Granthon,Hugo,NULL,Male,Hispanic,04/02/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59144,67746,61429,Probation,Pereira,Denver,NULL,Male,Asian,09/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/21/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +59144,67746,61429,Probation,Pereira,Denver,NULL,Male,Asian,09/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/21/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +59144,67746,61429,Probation,Pereira,Denver,NULL,Male,Asian,09/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +3348,67754,61436,Probation,Taylor,Kelvin,NULL,Male,African-American,10/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +3348,67754,61436,Probation,Taylor,Kelvin,NULL,Male,African-American,10/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +3348,67754,61436,Probation,Taylor,Kelvin,NULL,Male,African-American,10/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +59154,67759,61440,Probation,Garcia,Roger,NULL,Male,Hispanic,02/11/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +59154,67759,61440,Probation,Garcia,Roger,NULL,Male,Hispanic,02/11/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +59154,67759,61440,Probation,Garcia,Roger,NULL,Male,Hispanic,02/11/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59140,67741,61424,PRETRIAL,Shaver,Nicole,Ashley,Female,Caucasian,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +59140,67741,61424,PRETRIAL,Shaver,Nicole,Ashley,Female,Caucasian,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/13 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +59140,67741,61424,PRETRIAL,Shaver,Nicole,Ashley,Female,Caucasian,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59150,67755,61437,Probation,HERNANDEZ,ABEL,NULL,Male,Hispanic,01/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/21/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +59150,67755,61437,Probation,HERNANDEZ,ABEL,NULL,Male,Hispanic,01/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/21/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +59150,67755,61437,Probation,HERNANDEZ,ABEL,NULL,Male,Hispanic,01/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59158,67762,61443,Probation,petitfrefe,brunel,NULL,Male,African-American,02/09/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/21/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +59158,67762,61443,Probation,petitfrefe,brunel,NULL,Male,African-American,02/09/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/21/13 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +59158,67762,61443,Probation,petitfrefe,brunel,NULL,Male,African-American,02/09/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59159,67764,61445,Probation,Hincapie,John,NULL,Male,Hispanic,12/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/21/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +59159,67764,61445,Probation,Hincapie,John,NULL,Male,Hispanic,12/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/21/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +59159,67764,61445,Probation,Hincapie,John,NULL,Male,Hispanic,12/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59149,67752,61434,Probation,TUMBLIN,BARBARA,ANN,Female,African-American,08/19/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +59149,67752,61434,Probation,TUMBLIN,BARBARA,ANN,Female,African-American,08/19/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +59149,67752,61434,Probation,TUMBLIN,BARBARA,ANN,Female,African-American,08/19/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54759,67769,61450,PRETRIAL,Gourdet,Sindy,NULL,Male,African-American,10/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +54759,67769,61450,PRETRIAL,Gourdet,Sindy,NULL,Male,African-American,10/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +54759,67769,61450,PRETRIAL,Gourdet,Sindy,NULL,Male,African-American,10/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53792,67739,61422,Probation,HARBISON,COURTNEY,NULL,Male,Caucasian,12/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/21/13 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +53792,67739,61422,Probation,HARBISON,COURTNEY,NULL,Male,Caucasian,12/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +53792,67739,61422,Probation,HARBISON,COURTNEY,NULL,Male,Caucasian,12/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/21/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59145,67748,61430,Probation,BEJA,JOSEPH,ROBERT,Male,Caucasian,02/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +59145,67748,61430,Probation,BEJA,JOSEPH,ROBERT,Male,Caucasian,02/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +59145,67748,61430,Probation,BEJA,JOSEPH,ROBERT,Male,Caucasian,02/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +32776,34805,31828,PRETRIAL,Mercado,Luis,NULL,Male,Caucasian,06/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +32776,34805,31828,PRETRIAL,Mercado,Luis,NULL,Male,Caucasian,06/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +32776,34805,31828,PRETRIAL,Mercado,Luis,NULL,Male,Caucasian,06/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +10347,67743,61426,PRETRIAL,woessner,william,NULL,Male,Caucasian,04/20/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/21/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +10347,67743,61426,PRETRIAL,woessner,william,NULL,Male,Caucasian,04/20/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/21/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +10347,67743,61426,PRETRIAL,woessner,william,NULL,Male,Caucasian,04/20/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59181,67790,61470,Probation,McCutcheon,Krystal,NULL,Female,African-American,08/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +59181,67790,61470,Probation,McCutcheon,Krystal,NULL,Female,African-American,08/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +59181,67790,61470,Probation,McCutcheon,Krystal,NULL,Female,African-American,08/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +59184,67794,61473,PRETRIAL,Williams,Joevel,NULL,Male,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/13 0:00,2,Medium,7,Risk of Violence,-1.51,6,Medium,New,1,0 +59184,67794,61473,PRETRIAL,Williams,Joevel,NULL,Male,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +59184,67794,61473,PRETRIAL,Williams,Joevel,NULL,Male,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59168,67773,61454,PRETRIAL,Westcott,Lyndsay,NULL,Female,Caucasian,09/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +59168,67773,61454,PRETRIAL,Westcott,Lyndsay,NULL,Female,Caucasian,09/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +59168,67773,61454,PRETRIAL,Westcott,Lyndsay,NULL,Female,Caucasian,09/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59172,67778,61459,PRETRIAL,Hoff,Yolanda,L,Female,African-American,10/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +59172,67778,61459,PRETRIAL,Hoff,Yolanda,L,Female,African-American,10/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +59172,67778,61459,PRETRIAL,Hoff,Yolanda,L,Female,African-American,10/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59176,67785,61465,PRETRIAL,Hughes,Christian,NULL,Male,Caucasian,12/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +59176,67785,61465,PRETRIAL,Hughes,Christian,NULL,Male,Caucasian,12/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +59176,67785,61465,PRETRIAL,Hughes,Christian,NULL,Male,Caucasian,12/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59179,67788,61468,PRETRIAL,Emigh,Lauren,NULL,Female,Caucasian,07/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +59179,67788,61468,PRETRIAL,Emigh,Lauren,NULL,Female,Caucasian,07/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +59179,67788,61468,PRETRIAL,Emigh,Lauren,NULL,Female,Caucasian,07/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59186,67796,61475,Probation,raymond,tiffany,NULL,Female,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +59186,67796,61475,Probation,raymond,tiffany,NULL,Female,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +59186,67796,61475,Probation,raymond,tiffany,NULL,Female,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59167,67772,61453,PRETRIAL,Ungerland,Joseph,NULL,Male,Caucasian,11/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +59167,67772,61453,PRETRIAL,Ungerland,Joseph,NULL,Male,Caucasian,11/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +59167,67772,61453,PRETRIAL,Ungerland,Joseph,NULL,Male,Caucasian,11/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56008,67775,61456,PRETRIAL,persaud,adesh,NULL,Male,Caucasian,09/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +56008,67775,61456,PRETRIAL,persaud,adesh,NULL,Male,Caucasian,09/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,4,High,8,Risk of Recidivism,0.26,8,High,New,1,0 +56008,67775,61456,PRETRIAL,persaud,adesh,NULL,Male,Caucasian,09/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59183,67793,61472,PRETRIAL,dambra,barry,NULL,Male,Caucasian,08/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +59183,67793,61472,PRETRIAL,dambra,barry,NULL,Male,Caucasian,08/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +59183,67793,61472,PRETRIAL,dambra,barry,NULL,Male,Caucasian,08/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59174,67780,61461,Probation,Irvin,Beau,NULL,Male,African-American,08/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +59174,67780,61461,Probation,Irvin,Beau,NULL,Male,African-American,08/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +59174,67780,61461,Probation,Irvin,Beau,NULL,Male,African-American,08/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,39,10,High,New,1,0 +59177,67786,61466,Probation,Cruz,Ricardo,NULL,Male,Hispanic,06/06/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +59177,67786,61466,Probation,Cruz,Ricardo,NULL,Male,Hispanic,06/06/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +59177,67786,61466,Probation,Cruz,Ricardo,NULL,Male,Hispanic,06/06/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59171,67777,61458,PRETRIAL,Sayers,Keith,NULL,Male,Caucasian,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +59171,67777,61458,PRETRIAL,Sayers,Keith,NULL,Male,Caucasian,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +59171,67777,61458,PRETRIAL,Sayers,Keith,NULL,Male,Caucasian,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +59162,67770,61451,PRETRIAL,Turner,Rosco,NULL,Male,African-American,12/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,2,Medium,7,Risk of Violence,-2.97,1,Low,New,1,0 +59162,67770,61451,PRETRIAL,Turner,Rosco,NULL,Male,African-American,12/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +59162,67770,61451,PRETRIAL,Turner,Rosco,NULL,Male,African-American,12/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55315,67784,57151,Probation,Johnson,Lucious,NULL,Male,African-American,03/09/56,17,All Scales,Intake,English,Other,Probation,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +55315,67784,57151,Probation,Johnson,Lucious,NULL,Male,African-American,03/09/56,17,All Scales,Intake,English,Other,Probation,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-0.4,4,Low,New,1,0 +55315,67784,57151,Probation,Johnson,Lucious,NULL,Male,African-American,03/09/56,17,All Scales,Intake,English,Other,Probation,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +59163,67771,61452,PRETRIAL,Durand,Eduardo,NULL,Male,Hispanic,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +59163,67771,61452,PRETRIAL,Durand,Eduardo,NULL,Male,Hispanic,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +59163,67771,61452,PRETRIAL,Durand,Eduardo,NULL,Male,Hispanic,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59170,67776,61457,PRETRIAL,Villa,Juan,Pablo,Male,Caucasian,01/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +59170,67776,61457,PRETRIAL,Villa,Juan,Pablo,Male,Caucasian,01/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +59170,67776,61457,PRETRIAL,Villa,Juan,Pablo,Male,Caucasian,01/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59173,67779,61460,PRETRIAL,Denicola,Janel,NULL,Female,Caucasian,03/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +59173,67779,61460,PRETRIAL,Denicola,Janel,NULL,Female,Caucasian,03/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +59173,67779,61460,PRETRIAL,Denicola,Janel,NULL,Female,Caucasian,03/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59178,67787,61467,Probation,sama,felix,NULL,Male,Hispanic,07/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +59178,67787,61467,Probation,sama,felix,NULL,Male,Hispanic,07/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +59178,67787,61467,Probation,sama,felix,NULL,Male,Hispanic,07/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59180,67789,61469,Probation,vandenbosch,shannon,NULL,Female,Caucasian,04/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +59180,67789,61469,Probation,vandenbosch,shannon,NULL,Female,Caucasian,04/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +59180,67789,61469,Probation,vandenbosch,shannon,NULL,Female,Caucasian,04/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59175,67781,61462,Probation,SWAIN,PATRICIA,ANN,Female,Caucasian,06/06/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/22/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +59175,67781,61462,Probation,SWAIN,PATRICIA,ANN,Female,Caucasian,06/06/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/22/13 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +59175,67781,61462,Probation,SWAIN,PATRICIA,ANN,Female,Caucasian,06/06/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +59185,67795,61474,Probation,LAVIGNE,SHAUN,NULL,Male,Caucasian,10/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/22/13 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +59185,67795,61474,Probation,LAVIGNE,SHAUN,NULL,Male,Caucasian,10/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/22/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +59185,67795,61474,Probation,LAVIGNE,SHAUN,NULL,Male,Caucasian,10/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/22/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59169,67774,61455,PRETRIAL,Pichonot,Ruth,NULL,Female,Other,05/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +59169,67774,61455,PRETRIAL,Pichonot,Ruth,NULL,Female,Other,05/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +59169,67774,61455,PRETRIAL,Pichonot,Ruth,NULL,Female,Other,05/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +12045,67810,11562,PRETRIAL,CRISCIONE,JOSEPH,EUGENE,Male,Caucasian,11/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,Copy,1,0 +12045,67810,11562,PRETRIAL,CRISCIONE,JOSEPH,EUGENE,Male,Caucasian,11/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,Copy,1,0 +12045,67810,11562,PRETRIAL,CRISCIONE,JOSEPH,EUGENE,Male,Caucasian,11/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +59189,67802,61478,PRETRIAL,Cleare,Jonathan,NULL,Male,African-American,12/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +59189,67802,61478,PRETRIAL,Cleare,Jonathan,NULL,Male,African-American,12/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +59189,67802,61478,PRETRIAL,Cleare,Jonathan,NULL,Male,African-American,12/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59187,67797,61476,PRETRIAL,Ross,Destin,NULL,Male,African-American,02/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +59187,67797,61476,PRETRIAL,Ross,Destin,NULL,Male,African-American,02/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +59187,67797,61476,PRETRIAL,Ross,Destin,NULL,Male,African-American,02/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59192,67805,61481,PRETRIAL,Holmes,Jody,NULL,Male,African-American,10/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,7,Risk of Violence,-2.63,2,Low,New,1,0 +59192,67805,61481,PRETRIAL,Holmes,Jody,NULL,Male,African-American,10/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +59192,67805,61481,PRETRIAL,Holmes,Jody,NULL,Male,African-American,10/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59204,67818,61493,PRETRIAL,Jeanbaptiste,Evens,NULL,Male,African-American,02/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/23/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +59204,67818,61493,PRETRIAL,Jeanbaptiste,Evens,NULL,Male,African-American,02/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/23/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +59204,67818,61493,PRETRIAL,Jeanbaptiste,Evens,NULL,Male,African-American,02/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59188,67798,61477,PRETRIAL,Bruns,Shelby,NULL,Male,Caucasian,09/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +59188,67798,61477,PRETRIAL,Bruns,Shelby,NULL,Male,Caucasian,09/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +59188,67798,61477,PRETRIAL,Bruns,Shelby,NULL,Male,Caucasian,09/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59194,67807,61483,PRETRIAL,Fountain,Troy,NULL,Male,African-American,08/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +59194,67807,61483,PRETRIAL,Fountain,Troy,NULL,Male,African-American,08/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +59194,67807,61483,PRETRIAL,Fountain,Troy,NULL,Male,African-American,08/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59202,67816,61491,PRETRIAL,Ferguson,Roderick,G,Male,African-American,06/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/23/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +59202,67816,61491,PRETRIAL,Ferguson,Roderick,G,Male,African-American,06/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +59202,67816,61491,PRETRIAL,Ferguson,Roderick,G,Male,African-American,06/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/23/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59190,67803,61479,PRETRIAL,Butler,Steven,NULL,Male,African-American,07/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +59190,67803,61479,PRETRIAL,Butler,Steven,NULL,Male,African-American,07/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +59190,67803,61479,PRETRIAL,Butler,Steven,NULL,Male,African-American,07/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59198,67812,61487,PRETRIAL,HODGE,FRANTESSA,ELIZABETH,Female,African-American,05/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +59198,67812,61487,PRETRIAL,HODGE,FRANTESSA,ELIZABETH,Female,African-American,05/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +59198,67812,61487,PRETRIAL,HODGE,FRANTESSA,ELIZABETH,Female,African-American,05/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30502,67801,29460,PRETRIAL,JONES,LINDA,A,Female,African-American,05/03/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,Copy,1,0 +30502,67801,29460,PRETRIAL,JONES,LINDA,A,Female,African-American,05/03/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,Copy,1,0 +30502,67801,29460,PRETRIAL,JONES,LINDA,A,Female,African-American,05/03/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +59203,67817,61492,PRETRIAL,Flores,Giovanna,Mariaella,Male,Hispanic,07/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +59203,67817,61492,PRETRIAL,Flores,Giovanna,Mariaella,Male,Hispanic,07/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +59203,67817,61492,PRETRIAL,Flores,Giovanna,Mariaella,Male,Hispanic,07/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59196,67809,61485,PRETRIAL,Woodard,Kevis,NULL,Male,African-American,09/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +59196,67809,61485,PRETRIAL,Woodard,Kevis,NULL,Male,African-American,09/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +59196,67809,61485,PRETRIAL,Woodard,Kevis,NULL,Male,African-American,09/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59193,67806,61482,PRETRIAL,MARTIN,DEVINTE,LAMAR,Male,African-American,05/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +59193,67806,61482,PRETRIAL,MARTIN,DEVINTE,LAMAR,Male,African-American,05/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +59193,67806,61482,PRETRIAL,MARTIN,DEVINTE,LAMAR,Male,African-American,05/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59199,67813,61488,PRETRIAL,BENJILALI,HOUSSAIN,NULL,Male,Caucasian,11/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +59199,67813,61488,PRETRIAL,BENJILALI,HOUSSAIN,NULL,Male,Caucasian,11/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +59199,67813,61488,PRETRIAL,BENJILALI,HOUSSAIN,NULL,Male,Caucasian,11/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59195,67808,61484,PRETRIAL,GAMBOA,JORGE,HERNANDO,Male,Caucasian,08/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +59195,67808,61484,PRETRIAL,GAMBOA,JORGE,HERNANDO,Male,Caucasian,08/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +59195,67808,61484,PRETRIAL,GAMBOA,JORGE,HERNANDO,Male,Caucasian,08/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59191,67804,61480,PRETRIAL,HERBERT,RANDALL,WERNSING,Male,Caucasian,08/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +59191,67804,61480,PRETRIAL,HERBERT,RANDALL,WERNSING,Male,Caucasian,08/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +59191,67804,61480,PRETRIAL,HERBERT,RANDALL,WERNSING,Male,Caucasian,08/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +59197,67811,61486,PRETRIAL,Gonzalez,Carlos,NULL,Male,Hispanic,11/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/23/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +59197,67811,61486,PRETRIAL,Gonzalez,Carlos,NULL,Male,Hispanic,11/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/23/13 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +59197,67811,61486,PRETRIAL,Gonzalez,Carlos,NULL,Male,Hispanic,11/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/23/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59201,67815,61490,PRETRIAL,Dowds,Melissa,NULL,Female,Caucasian,06/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +59201,67815,61490,PRETRIAL,Dowds,Melissa,NULL,Female,Caucasian,06/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +59201,67815,61490,PRETRIAL,Dowds,Melissa,NULL,Female,Caucasian,06/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +866,67825,559,PRETRIAL,Boles,Lashawn,Nicole,Female,African-American,01/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,Copy,1,0 +866,67825,559,PRETRIAL,Boles,Lashawn,Nicole,Female,African-American,01/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,1,Low,8,Risk of Recidivism,-1.61,2,Low,Copy,1,0 +866,67825,559,PRETRIAL,Boles,Lashawn,Nicole,Female,African-American,01/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +866,649,559,PRETRIAL,Boles,Lashawn,Nicole,Female,African-American,01/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +866,649,559,PRETRIAL,Boles,Lashawn,Nicole,Female,African-American,01/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +866,649,559,PRETRIAL,Boles,Lashawn,Nicole,Female,African-American,01/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59206,67820,61495,PRETRIAL,Toney,Cornelius,NULL,Male,African-American,03/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/24/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +59206,67820,61495,PRETRIAL,Toney,Cornelius,NULL,Male,African-American,03/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/24/13 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +59206,67820,61495,PRETRIAL,Toney,Cornelius,NULL,Male,African-American,03/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/24/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59210,67824,61499,PRETRIAL,Brown,Temisa,NULL,Female,African-American,09/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,2,Medium,7,Risk of Violence,-3,1,Low,New,1,0 +59210,67824,61499,PRETRIAL,Brown,Temisa,NULL,Female,African-American,09/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +59210,67824,61499,PRETRIAL,Brown,Temisa,NULL,Female,African-American,09/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59208,67822,61497,PRETRIAL,WALTERS,DAVID,NULL,Male,African-American,10/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +59208,67822,61497,PRETRIAL,WALTERS,DAVID,NULL,Male,African-American,10/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +59208,67822,61497,PRETRIAL,WALTERS,DAVID,NULL,Male,African-American,10/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59207,67821,61496,PRETRIAL,MCCARTER,SOLOMON,NULL,Male,African-American,09/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/24/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +59207,67821,61496,PRETRIAL,MCCARTER,SOLOMON,NULL,Male,African-American,09/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/24/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +59207,67821,61496,PRETRIAL,MCCARTER,SOLOMON,NULL,Male,African-American,09/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59205,67819,61494,PRETRIAL,Canas-Rodriguez,Victor,NULL,Male,Hispanic,03/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +59205,67819,61494,PRETRIAL,Canas-Rodriguez,Victor,NULL,Male,Hispanic,03/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +59205,67819,61494,PRETRIAL,Canas-Rodriguez,Victor,NULL,Male,Hispanic,03/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59209,67823,61498,PRETRIAL,Williams,Dennis,NULL,Male,African-American,02/26/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +59209,67823,61498,PRETRIAL,Williams,Dennis,NULL,Male,African-American,02/26/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +59209,67823,61498,PRETRIAL,Williams,Dennis,NULL,Male,African-American,02/26/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59244,67860,61533,Probation,tobon,henry,NULL,Male,Hispanic,01/21/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/25/13 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +59244,67860,61533,Probation,tobon,henry,NULL,Male,Hispanic,01/21/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/25/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +59244,67860,61533,Probation,tobon,henry,NULL,Male,Hispanic,01/21/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59218,67831,61505,PRETRIAL,TAYLOR,WILLIAM,FRANCIS,Male,African-American,11/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +59218,67831,61505,PRETRIAL,TAYLOR,WILLIAM,FRANCIS,Male,African-American,11/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +59218,67831,61505,PRETRIAL,TAYLOR,WILLIAM,FRANCIS,Male,African-American,11/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59236,67852,61525,PRETRIAL,Mallen,Michael,NULL,Male,Caucasian,11/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +59236,67852,61525,PRETRIAL,Mallen,Michael,NULL,Male,Caucasian,11/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +59236,67852,61525,PRETRIAL,Mallen,Michael,NULL,Male,Caucasian,11/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59222,67836,61510,PRETRIAL,HARRELL,LEONARD,NULL,Male,Caucasian,08/20/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/25/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +59222,67836,61510,PRETRIAL,HARRELL,LEONARD,NULL,Male,Caucasian,08/20/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +59222,67836,61510,PRETRIAL,HARRELL,LEONARD,NULL,Male,Caucasian,08/20/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59232,67847,61520,PRETRIAL,SHELLY,OTIS,NULL,Male,African-American,02/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +59232,67847,61520,PRETRIAL,SHELLY,OTIS,NULL,Male,African-American,02/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +59232,67847,61520,PRETRIAL,SHELLY,OTIS,NULL,Male,African-American,02/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59211,67826,61500,PRETRIAL,BIANCO,ROBERT,WILSON,Male,Caucasian,09/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/25/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +59211,67826,61500,PRETRIAL,BIANCO,ROBERT,WILSON,Male,Caucasian,09/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +59211,67826,61500,PRETRIAL,BIANCO,ROBERT,WILSON,Male,Caucasian,09/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59229,67844,61517,PRETRIAL,Devonow,Karen,NULL,Female,Caucasian,11/26/55,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-1,-1,N/A,New,1,0 +59229,67844,61517,PRETRIAL,Devonow,Karen,NULL,Female,Caucasian,11/26/55,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +59229,67844,61517,PRETRIAL,Devonow,Karen,NULL,Female,Caucasian,11/26/55,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59241,67857,61530,DRRD,Lacey,Lenna,NULL,Female,African-American,02/02/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/25/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +59241,67857,61530,DRRD,Lacey,Lenna,NULL,Female,African-American,02/02/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/25/13 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +59241,67857,61530,DRRD,Lacey,Lenna,NULL,Female,African-American,02/02/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59215,67828,61502,PRETRIAL,Smith,Ladarious,NULL,Male,African-American,04/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +59215,67828,61502,PRETRIAL,Smith,Ladarious,NULL,Male,African-American,04/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +59215,67828,61502,PRETRIAL,Smith,Ladarious,NULL,Male,African-American,04/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59240,67856,61529,Probation,Dunbar,Taiwo,NULL,Male,African-American,09/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,2,Medium,7,Risk of Violence,-2.81,2,Low,New,1,0 +59240,67856,61529,Probation,Dunbar,Taiwo,NULL,Male,African-American,09/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +59240,67856,61529,Probation,Dunbar,Taiwo,NULL,Male,African-American,09/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59228,67842,61516,Probation,Domkoski,Taylor,NULL,Female,Caucasian,04/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +59228,67842,61516,Probation,Domkoski,Taylor,NULL,Female,Caucasian,04/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +59228,67842,61516,Probation,Domkoski,Taylor,NULL,Female,Caucasian,04/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59223,67837,61511,PRETRIAL,COXIE,CRYSTAL,NULL,Female,Caucasian,04/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +59223,67837,61511,PRETRIAL,COXIE,CRYSTAL,NULL,Female,Caucasian,04/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +59223,67837,61511,PRETRIAL,COXIE,CRYSTAL,NULL,Female,Caucasian,04/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59220,67833,61507,PRETRIAL,Mcfield,Peter,O,Male,Other,02/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/25/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +59220,67833,61507,PRETRIAL,Mcfield,Peter,O,Male,Other,02/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +59220,67833,61507,PRETRIAL,Mcfield,Peter,O,Male,Other,02/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59242,67858,61531,Probation,Peeples,Heather,NULL,Female,Caucasian,09/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +59242,67858,61531,Probation,Peeples,Heather,NULL,Female,Caucasian,09/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +59242,67858,61531,Probation,Peeples,Heather,NULL,Female,Caucasian,09/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +6210,67854,61527,PRETRIAL,HENRY,FRITZNER,NULL,Male,African-American,05/16/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/25/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +6210,67854,61527,PRETRIAL,HENRY,FRITZNER,NULL,Male,African-American,05/16/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +6210,67854,61527,PRETRIAL,HENRY,FRITZNER,NULL,Male,African-American,05/16/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +8687,67861,61534,PRETRIAL,HIGGS,MARSHALL,E,Male,African-American,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +8687,67861,61534,PRETRIAL,HIGGS,MARSHALL,E,Male,African-American,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.02,10,High,New,1,0 +8687,67861,61534,PRETRIAL,HIGGS,MARSHALL,E,Male,African-American,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55725,67843,57621,PRETRIAL,alonso,waldo,NULL,Male,Caucasian,11/12/71,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,11/25/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +55725,67843,57621,PRETRIAL,alonso,waldo,NULL,Male,Caucasian,11/12/71,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +55725,67843,57621,PRETRIAL,alonso,waldo,NULL,Male,Caucasian,11/12/71,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +59221,67835,61509,PRETRIAL,ROZIER,VICTOR,NULL,Male,African-American,03/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +59221,67835,61509,PRETRIAL,ROZIER,VICTOR,NULL,Male,African-American,03/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +59221,67835,61509,PRETRIAL,ROZIER,VICTOR,NULL,Male,African-American,03/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +59233,67848,61521,Probation,Grant,Craig,Jones,Male,Caucasian,08/02/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +59233,67848,61521,Probation,Grant,Craig,Jones,Male,Caucasian,08/02/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +59233,67848,61521,Probation,Grant,Craig,Jones,Male,Caucasian,08/02/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59243,67859,61532,PRETRIAL,Burleigh,Scott,NULL,Male,African-American,09/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/25/13 0:00,4,High,7,Risk of Violence,-0.92,9,High,New,1,0 +59243,67859,61532,PRETRIAL,Burleigh,Scott,NULL,Male,African-American,09/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/25/13 0:00,4,High,8,Risk of Recidivism,1.03,10,High,New,1,0 +59243,67859,61532,PRETRIAL,Burleigh,Scott,NULL,Male,African-American,09/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/25/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59224,67838,61512,PRETRIAL,deas,charles,NULL,Male,African-American,08/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +59224,67838,61512,PRETRIAL,deas,charles,NULL,Male,African-American,08/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +59224,67838,61512,PRETRIAL,deas,charles,NULL,Male,African-American,08/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59230,67845,61518,Probation,Scott,Mindy,NULL,Female,Caucasian,01/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +59230,67845,61518,Probation,Scott,Mindy,NULL,Female,Caucasian,01/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +59230,67845,61518,Probation,Scott,Mindy,NULL,Female,Caucasian,01/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59219,67832,61506,PRETRIAL,Huffman,Melinda,NULL,Female,Caucasian,04/28/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/25/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +59219,67832,61506,PRETRIAL,Huffman,Melinda,NULL,Female,Caucasian,04/28/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/25/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +59219,67832,61506,PRETRIAL,Huffman,Melinda,NULL,Female,Caucasian,04/28/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59235,67851,61524,Probation,Bernstein,Jonathan,NULL,Male,Caucasian,04/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +59235,67851,61524,Probation,Bernstein,Jonathan,NULL,Male,Caucasian,04/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +59235,67851,61524,Probation,Bernstein,Jonathan,NULL,Male,Caucasian,04/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59216,67830,61504,PRETRIAL,LOTIERZO,ZACHARY,JOSEPH,Male,African-American,02/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.71,9,High,New,1,0 +59216,67830,61504,PRETRIAL,LOTIERZO,ZACHARY,JOSEPH,Male,African-American,02/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +59216,67830,61504,PRETRIAL,LOTIERZO,ZACHARY,JOSEPH,Male,African-American,02/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59237,67853,61526,Probation,Gerhardt,Kristina,Marie,Female,Caucasian,08/20/85,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/25/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +59237,67853,61526,Probation,Gerhardt,Kristina,Marie,Female,Caucasian,08/20/85,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +59237,67853,61526,Probation,Gerhardt,Kristina,Marie,Female,Caucasian,08/20/85,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51134,67827,61501,PRETRIAL,Papacosmas,Thomas,NULL,Male,Caucasian,04/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +51134,67827,61501,PRETRIAL,Papacosmas,Thomas,NULL,Male,Caucasian,04/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +51134,67827,61501,PRETRIAL,Papacosmas,Thomas,NULL,Male,Caucasian,04/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59227,67841,61515,Probation,MARTINEZ-ARAYA,GRETTEL,C,Female,Hispanic,05/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +59227,67841,61515,Probation,MARTINEZ-ARAYA,GRETTEL,C,Female,Hispanic,05/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +59227,67841,61515,Probation,MARTINEZ-ARAYA,GRETTEL,C,Female,Hispanic,05/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +37543,67834,61508,PRETRIAL,Miranda,Michael,NULL,Male,Hispanic,11/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +37543,67834,61508,PRETRIAL,Miranda,Michael,NULL,Male,Hispanic,11/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +37543,67834,61508,PRETRIAL,Miranda,Michael,NULL,Male,Hispanic,11/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59238,67855,61528,Probation,rubio,jose,NULL,Male,Hispanic,01/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +59238,67855,61528,Probation,rubio,jose,NULL,Male,Hispanic,01/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +59238,67855,61528,Probation,rubio,jose,NULL,Male,Hispanic,01/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +47036,67862,61535,Probation,innocent,james,NULL,Male,African-American,12/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,2,Medium,7,Risk of Violence,-2.76,2,Low,New,1,0 +47036,67862,61535,Probation,innocent,james,NULL,Male,African-American,12/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +47036,67862,61535,Probation,innocent,james,NULL,Male,African-American,12/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59231,67846,61519,Probation,Taylor,Gregory,Montell,Male,African-American,02/08/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +59231,67846,61519,Probation,Taylor,Gregory,Montell,Male,African-American,02/08/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +59231,67846,61519,Probation,Taylor,Gregory,Montell,Male,African-American,02/08/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59217,67829,61503,PRETRIAL,Pantaleon,Jose,NULL,Male,Hispanic,07/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +59217,67829,61503,PRETRIAL,Pantaleon,Jose,NULL,Male,Hispanic,07/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +59217,67829,61503,PRETRIAL,Pantaleon,Jose,NULL,Male,Hispanic,07/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +32180,67897,61564,PRETRIAL,lantigua,luis,NULL,Male,African-American,04/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +32180,67897,61564,PRETRIAL,lantigua,luis,NULL,Male,African-American,04/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +32180,67897,61564,PRETRIAL,lantigua,luis,NULL,Male,African-American,04/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59253,67876,61548,PRETRIAL,Sutton,Cindy,C,Female,Caucasian,09/19/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/26/13 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +59253,67876,61548,PRETRIAL,Sutton,Cindy,C,Female,Caucasian,09/19/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/26/13 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +59253,67876,61548,PRETRIAL,Sutton,Cindy,C,Female,Caucasian,09/19/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59248,67871,61543,PRETRIAL,Porter,Nikeisha,NULL,Female,African-American,01/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +59248,67871,61543,PRETRIAL,Porter,Nikeisha,NULL,Female,African-American,01/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +59248,67871,61543,PRETRIAL,Porter,Nikeisha,NULL,Female,African-American,01/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59016,67880,61278,PRETRIAL,Turner,Daniel,NULL,Male,Caucasian,10/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/26/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,Copy,1,0 +59016,67880,61278,PRETRIAL,Turner,Daniel,NULL,Male,Caucasian,10/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,Copy,1,0 +59016,67880,61278,PRETRIAL,Turner,Daniel,NULL,Male,Caucasian,10/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +59246,67867,61539,PRETRIAL,WISDOM,RYAN,LATHIO,Male,African-American,07/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +59246,67867,61539,PRETRIAL,WISDOM,RYAN,LATHIO,Male,African-American,07/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +59246,67867,61539,PRETRIAL,WISDOM,RYAN,LATHIO,Male,African-American,07/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59265,67901,61568,Probation,Avila,Sandra,NULL,Female,Hispanic,07/31/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/26/13 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +59265,67901,61568,Probation,Avila,Sandra,NULL,Female,Hispanic,07/31/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +59265,67901,61568,Probation,Avila,Sandra,NULL,Female,Hispanic,07/31/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +1074,67864,61536,PRETRIAL,edwards,nathan,NULL,Male,African-American,12/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +1074,67864,61536,PRETRIAL,edwards,nathan,NULL,Male,African-American,12/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +1074,67864,61536,PRETRIAL,edwards,nathan,NULL,Male,African-American,12/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +46729,67883,61552,Probation,BAMBERRY,TIFFANY,NULL,Female,African-Am,12/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +46729,67883,61552,Probation,BAMBERRY,TIFFANY,NULL,Female,African-Am,12/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +46729,67883,61552,Probation,BAMBERRY,TIFFANY,NULL,Female,African-Am,12/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +46481,67885,61554,PRETRIAL,Toro,Juan,NULL,Male,Hispanic,09/21/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +46481,67885,61554,PRETRIAL,Toro,Juan,NULL,Male,Hispanic,09/21/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +46481,67885,61554,PRETRIAL,Toro,Juan,NULL,Male,Hispanic,09/21/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59260,67892,61559,Probation,Davis,Bobby,Phill,Male,African-American,11/19/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +59260,67892,61559,Probation,Davis,Bobby,Phill,Male,African-American,11/19/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +59260,67892,61559,Probation,Davis,Bobby,Phill,Male,African-American,11/19/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +59268,67906,61571,Probation,Natasha,Striggles,NULL,Female,African-American,09/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.37,3,Low,New,1,0 +59268,67906,61571,Probation,Natasha,Striggles,NULL,Female,African-American,09/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,9,High,New,1,0 +59268,67906,61571,Probation,Natasha,Striggles,NULL,Female,African-American,09/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +19575,67866,61538,PRETRIAL,Jones,Kenneth,NULL,Male,African-American,11/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +19575,67866,61538,PRETRIAL,Jones,Kenneth,NULL,Male,African-American,11/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +19575,67866,61538,PRETRIAL,Jones,Kenneth,NULL,Male,African-American,11/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59262,67895,61562,Probation,Johnson,Kenneth,NULL,Male,African-American,05/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/26/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +59262,67895,61562,Probation,Johnson,Kenneth,NULL,Male,African-American,05/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +59262,67895,61562,Probation,Johnson,Kenneth,NULL,Male,African-American,05/19/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59251,67874,61546,PRETRIAL,FRANC,BENJAMIN,DAVID,Male,Caucasian,06/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +59251,67874,61546,PRETRIAL,FRANC,BENJAMIN,DAVID,Male,Caucasian,06/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +59251,67874,61546,PRETRIAL,FRANC,BENJAMIN,DAVID,Male,Caucasian,06/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53215,67869,61541,PRETRIAL,Fields,Lamondrio,NULL,Male,African-American,03/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +53215,67869,61541,PRETRIAL,Fields,Lamondrio,NULL,Male,African-American,03/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +53215,67869,61541,PRETRIAL,Fields,Lamondrio,NULL,Male,African-American,03/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58708,67882,60922,PRETRIAL,Kaye,Lisa,NULL,Female,Caucasian,10/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/26/13 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,Copy,1,0 +58708,67882,60922,PRETRIAL,Kaye,Lisa,NULL,Female,Caucasian,10/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/26/13 0:00,1,Low,8,Risk of Recidivism,-2.56,1,Low,Copy,1,0 +58708,67882,60922,PRETRIAL,Kaye,Lisa,NULL,Female,Caucasian,10/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +59270,67908,61573,PRETRIAL,Brown,John,NULL,Male,Caucasian,04/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +59270,67908,61573,PRETRIAL,Brown,John,NULL,Male,Caucasian,04/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +59270,67908,61573,PRETRIAL,Brown,John,NULL,Male,Caucasian,04/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57876,67890,61553,Probation,Blum,Michael,NULL,Male,Caucasian,01/02/70,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,11/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.84,2,Low,Copy,1,0 +57876,67890,61553,Probation,Blum,Michael,NULL,Male,Caucasian,01/02/70,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,11/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,Copy,1,0 +57876,67890,61553,Probation,Blum,Michael,NULL,Male,Caucasian,01/02/70,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,11/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +59249,67872,61544,PRETRIAL,Lumene,Jean,NULL,Male,Other,07/16/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +59249,67872,61544,PRETRIAL,Lumene,Jean,NULL,Male,Other,07/16/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +59249,67872,61544,PRETRIAL,Lumene,Jean,NULL,Male,Other,07/16/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59252,67875,61547,PRETRIAL,Davis,Anthony,NULL,Male,African-American,07/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +59252,67875,61547,PRETRIAL,Davis,Anthony,NULL,Male,African-American,07/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +59252,67875,61547,PRETRIAL,Davis,Anthony,NULL,Male,African-American,07/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59261,67893,61560,PRETRIAL,BARRETT,DAVAHU,NULL,Female,African-American,07/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/26/13 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +59261,67893,61560,PRETRIAL,BARRETT,DAVAHU,NULL,Female,African-American,07/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +59261,67893,61560,PRETRIAL,BARRETT,DAVAHU,NULL,Female,African-American,07/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/26/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59254,67877,61549,PRETRIAL,Randall,Henry,J,Male,African-American,09/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +59254,67877,61549,PRETRIAL,Randall,Henry,J,Male,African-American,09/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +59254,67877,61549,PRETRIAL,Randall,Henry,J,Male,African-American,09/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59259,67891,61558,Probation,Turner,Sabrina,NULL,Female,African-American,10/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +59259,67891,61558,Probation,Turner,Sabrina,NULL,Female,African-American,10/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +59259,67891,61558,Probation,Turner,Sabrina,NULL,Female,African-American,10/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59247,67870,61542,PRETRIAL,Darlington,Marvin,Erwin,Male,African-American,09/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +59247,67870,61542,PRETRIAL,Darlington,Marvin,Erwin,Male,African-American,09/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +59247,67870,61542,PRETRIAL,Darlington,Marvin,Erwin,Male,African-American,09/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59263,67898,61565,Probation,Brooks,Clara,NULL,Female,Caucasian,08/31/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,11/26/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +59263,67898,61565,Probation,Brooks,Clara,NULL,Female,Caucasian,08/31/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +59263,67898,61565,Probation,Brooks,Clara,NULL,Female,Caucasian,08/31/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50236,67900,61567,PRETRIAL,Gilbert,Myrticea,NULL,Female,African-American,06/03/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +50236,67900,61567,PRETRIAL,Gilbert,Myrticea,NULL,Female,African-American,06/03/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,4,High,8,Risk of Recidivism,0.67,10,High,New,1,0 +50236,67900,61567,PRETRIAL,Gilbert,Myrticea,NULL,Female,African-American,06/03/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,4,High,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +12649,67894,61561,PRETRIAL,Espinoza,Germayn,NULL,Male,Native American,05/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +12649,67894,61561,PRETRIAL,Espinoza,Germayn,NULL,Male,Native American,05/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +12649,67894,61561,PRETRIAL,Espinoza,Germayn,NULL,Male,Native American,05/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59269,67907,61572,Probation,Norman,Tyler,NULL,Male,Caucasian,05/16/84,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/26/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +59269,67907,61572,Probation,Norman,Tyler,NULL,Male,Caucasian,05/16/84,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +59269,67907,61572,Probation,Norman,Tyler,NULL,Male,Caucasian,05/16/84,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59245,67865,61537,PRETRIAL,MARTIN,FREDDERICK,NULL,Male,African-American,08/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.07,8,High,New,1,0 +59245,67865,61537,PRETRIAL,MARTIN,FREDDERICK,NULL,Male,African-American,08/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +59245,67865,61537,PRETRIAL,MARTIN,FREDDERICK,NULL,Male,African-American,08/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59267,67904,61570,PRETRIAL,NANCE,DAMIAN,NULL,Male,African-American,11/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +59267,67904,61570,PRETRIAL,NANCE,DAMIAN,NULL,Male,African-American,11/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +59267,67904,61570,PRETRIAL,NANCE,DAMIAN,NULL,Male,African-American,11/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59264,67899,61566,Probation,Herlinger,Gregory,Matthew,Male,Caucasian,01/04/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +59264,67899,61566,Probation,Herlinger,Gregory,Matthew,Male,Caucasian,01/04/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +59264,67899,61566,Probation,Herlinger,Gregory,Matthew,Male,Caucasian,01/04/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59250,67873,61545,PRETRIAL,MARCHANT,MARK,ANDREW,Male,Caucasian,03/29/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +59250,67873,61545,PRETRIAL,MARCHANT,MARK,ANDREW,Male,Caucasian,03/29/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +59250,67873,61545,PRETRIAL,MARCHANT,MARK,ANDREW,Male,Caucasian,03/29/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59255,67878,61550,PRETRIAL,FORD,JOSEPH,EDWARD,Male,African-American,02/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +59255,67878,61550,PRETRIAL,FORD,JOSEPH,EDWARD,Male,African-American,02/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +59255,67878,61550,PRETRIAL,FORD,JOSEPH,EDWARD,Male,African-American,02/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58406,67881,60641,PRETRIAL,DOVOLIS,ALEXANDRA,NULL,Female,Caucasian,05/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,Copy,1,0 +58406,67881,60641,PRETRIAL,DOVOLIS,ALEXANDRA,NULL,Female,Caucasian,05/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,Copy,1,0 +58406,67881,60641,PRETRIAL,DOVOLIS,ALEXANDRA,NULL,Female,Caucasian,05/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +59257,67888,61556,Probation,sebastian,osbin,NULL,Male,Hispanic,04/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +59257,67888,61556,Probation,sebastian,osbin,NULL,Male,Hispanic,04/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +59257,67888,61556,Probation,sebastian,osbin,NULL,Male,Hispanic,04/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59258,67889,61557,Probation,Oneil,Sindy,NULL,Female,Hispanic,05/07/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/26/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +59258,67889,61557,Probation,Oneil,Sindy,NULL,Female,Hispanic,05/07/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/26/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +59258,67889,61557,Probation,Oneil,Sindy,NULL,Female,Hispanic,05/07/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/26/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +20581,67896,61563,PRETRIAL,Sheppard,Jereme,NULL,Male,African-American,05/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +20581,67896,61563,PRETRIAL,Sheppard,Jereme,NULL,Male,African-American,05/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +20581,67896,61563,PRETRIAL,Sheppard,Jereme,NULL,Male,African-American,05/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +32442,67868,61540,PRETRIAL,Roberson,Lagary,NULL,Male,African-American,08/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +32442,67868,61540,PRETRIAL,Roberson,Lagary,NULL,Male,African-American,08/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +32442,67868,61540,PRETRIAL,Roberson,Lagary,NULL,Male,African-American,08/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59266,67902,61569,PRETRIAL,thorpe,keith,NULL,Male,African-American,07/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.04,8,High,New,1,0 +59266,67902,61569,PRETRIAL,thorpe,keith,NULL,Male,African-American,07/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +59266,67902,61569,PRETRIAL,thorpe,keith,NULL,Male,African-American,07/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59279,67917,61581,PRETRIAL,MITTAPALLI,SARADA,NULL,Male,Other,07/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +59279,67917,61581,PRETRIAL,MITTAPALLI,SARADA,NULL,Male,Other,07/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +59279,67917,61581,PRETRIAL,MITTAPALLI,SARADA,NULL,Male,Other,07/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59283,67923,61586,Probation,Tsiartas,Nicole,NULL,Female,Caucasian,01/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/27/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +59283,67923,61586,Probation,Tsiartas,Nicole,NULL,Female,Caucasian,01/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/27/13 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +59283,67923,61586,Probation,Tsiartas,Nicole,NULL,Female,Caucasian,01/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59286,67930,61592,PRETRIAL,Shakir,Sultan,NULL,Male,African-American,10/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/27/13 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +59286,67930,61592,PRETRIAL,Shakir,Sultan,NULL,Male,African-American,10/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +59286,67930,61592,PRETRIAL,Shakir,Sultan,NULL,Male,African-American,10/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/27/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58393,67931,60622,Probation,kenrick,Ridge,NULL,Male,African-American,01/04/88,17,All Scales,Intake,English,Post Sentence,Probation,Married,11/27/13 0:00,4,High,7,Risk of Violence,-1.19,8,High,New,1,0 +58393,67931,60622,Probation,kenrick,Ridge,NULL,Male,African-American,01/04/88,17,All Scales,Intake,English,Post Sentence,Probation,Married,11/27/13 0:00,4,High,8,Risk of Recidivism,1.26,10,High,New,1,0 +58393,67931,60622,Probation,kenrick,Ridge,NULL,Male,African-American,01/04/88,17,All Scales,Intake,English,Post Sentence,Probation,Married,11/27/13 0:00,4,High,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +59274,67912,61576,PRETRIAL,FLETCHER,DAMIAN,ANTHONY,Male,African-American,10/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +59274,67912,61576,PRETRIAL,FLETCHER,DAMIAN,ANTHONY,Male,African-American,10/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +59274,67912,61576,PRETRIAL,FLETCHER,DAMIAN,ANTHONY,Male,African-American,10/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +59287,67933,61593,Probation,olson,stephanie,NULL,Female,Caucasian,12/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/27/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +59287,67933,61593,Probation,olson,stephanie,NULL,Female,Caucasian,12/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +59287,67933,61593,Probation,olson,stephanie,NULL,Female,Caucasian,12/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/27/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59277,67915,61579,PRETRIAL,TOLENTINO,KELVIN,RAFAEL,Male,Caucasian,02/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +59277,67915,61579,PRETRIAL,TOLENTINO,KELVIN,RAFAEL,Male,Caucasian,02/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +59277,67915,61579,PRETRIAL,TOLENTINO,KELVIN,RAFAEL,Male,Caucasian,02/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +30369,67925,61588,PRETRIAL,Francois,Odrin,NULL,Male,African-American,05/15/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/27/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +30369,67925,61588,PRETRIAL,Francois,Odrin,NULL,Male,African-American,05/15/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/27/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +30369,67925,61588,PRETRIAL,Francois,Odrin,NULL,Male,African-American,05/15/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59280,67919,61583,PRETRIAL,Watelski,Sean,NULL,Male,Caucasian,02/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/27/13 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +59280,67919,61583,PRETRIAL,Watelski,Sean,NULL,Male,Caucasian,02/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/27/13 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +59280,67919,61583,PRETRIAL,Watelski,Sean,NULL,Male,Caucasian,02/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59281,67921,61584,PRETRIAL,Miranda,Yoan,NULL,Male,Caucasian,03/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +59281,67921,61584,PRETRIAL,Miranda,Yoan,NULL,Male,Caucasian,03/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +59281,67921,61584,PRETRIAL,Miranda,Yoan,NULL,Male,Caucasian,03/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59285,67928,61590,PRETRIAL,CHERIF,IMAD,NULL,Male,Other,07/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +59285,67928,61590,PRETRIAL,CHERIF,IMAD,NULL,Male,Other,07/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +59285,67928,61590,PRETRIAL,CHERIF,IMAD,NULL,Male,Other,07/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59284,67926,61589,PRETRIAL,VERGARA,TEOBALDO,NULL,Male,Caucasian,10/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,4,High,7,Risk of Violence,-1.23,8,High,New,1,0 +59284,67926,61589,PRETRIAL,VERGARA,TEOBALDO,NULL,Male,Caucasian,10/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,4,High,8,Risk of Recidivism,0.37,9,High,New,1,0 +59284,67926,61589,PRETRIAL,VERGARA,TEOBALDO,NULL,Male,Caucasian,10/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59276,67914,61578,PRETRIAL,Polynice,Jamarc,Anthony,Male,African-American,08/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +59276,67914,61578,PRETRIAL,Polynice,Jamarc,Anthony,Male,African-American,08/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +59276,67914,61578,PRETRIAL,Polynice,Jamarc,Anthony,Male,African-American,08/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +47251,67929,61591,PRETRIAL,gachette,chris,NULL,Male,Caucasian,08/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/27/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +47251,67929,61591,PRETRIAL,gachette,chris,NULL,Male,Caucasian,08/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/27/13 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +47251,67929,61591,PRETRIAL,gachette,chris,NULL,Male,Caucasian,08/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59273,67911,61575,PRETRIAL,Watts,John,Fitzgerald,Male,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +59273,67911,61575,PRETRIAL,Watts,John,Fitzgerald,Male,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +59273,67911,61575,PRETRIAL,Watts,John,Fitzgerald,Male,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59278,67916,61580,PRETRIAL,Graham,Roshod,NULL,Male,African-American,12/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +59278,67916,61580,PRETRIAL,Graham,Roshod,NULL,Male,African-American,12/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +59278,67916,61580,PRETRIAL,Graham,Roshod,NULL,Male,African-American,12/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54187,67924,61587,Probation,LOISY,BRANDON,MORGAN,Male,African-American,02/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +54187,67924,61587,Probation,LOISY,BRANDON,MORGAN,Male,African-American,02/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +54187,67924,61587,Probation,LOISY,BRANDON,MORGAN,Male,African-American,02/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52231,67932,53502,PRETRIAL,Louis,Cassandra,NULL,Female,Other,02/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/27/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,Copy,1,0 +52231,67932,53502,PRETRIAL,Louis,Cassandra,NULL,Female,Other,02/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/27/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,Copy,1,0 +52231,67932,53502,PRETRIAL,Louis,Cassandra,NULL,Female,Other,02/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +59275,67913,61577,PRETRIAL,PINNOCK,WAYNE,ROHAN,Male,African-American,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +59275,67913,61577,PRETRIAL,PINNOCK,WAYNE,ROHAN,Male,African-American,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,4,High,8,Risk of Recidivism,0.36,9,High,New,1,0 +59275,67913,61577,PRETRIAL,PINNOCK,WAYNE,ROHAN,Male,African-American,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +869,67920,562,PRETRIAL,Eaton,Andre,A,Male,Other,07/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,Copy,1,0 +869,67920,562,PRETRIAL,Eaton,Andre,A,Male,Other,07/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,Copy,1,0 +869,67920,562,PRETRIAL,Eaton,Andre,A,Male,Other,07/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +42409,67927,55319,PRETRIAL,Minor,Herman,NULL,Male,African-American,06/29/84,17,All Scales,Intake,English,Other,Probation,Single,11/27/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,Copy,1,0 +42409,67927,55319,PRETRIAL,Minor,Herman,NULL,Male,African-American,06/29/84,17,All Scales,Intake,English,Other,Probation,Single,11/27/13 0:00,4,High,8,Risk of Recidivism,0.11,8,High,Copy,1,0 +42409,67927,55319,PRETRIAL,Minor,Herman,NULL,Male,African-American,06/29/84,17,All Scales,Intake,English,Other,Probation,Single,11/27/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +15247,67918,61582,DRRD,Geraldine,Hughes,NULL,Female,African-American,06/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +15247,67918,61582,DRRD,Geraldine,Hughes,NULL,Female,African-American,06/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +15247,67918,61582,DRRD,Geraldine,Hughes,NULL,Female,African-American,06/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59282,67922,61585,PRETRIAL,HAHN,DANIELLE,L,Female,Caucasian,05/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +59282,67922,61585,PRETRIAL,HAHN,DANIELLE,L,Female,Caucasian,05/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +59282,67922,61585,PRETRIAL,HAHN,DANIELLE,L,Female,Caucasian,05/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59295,67943,61603,PRETRIAL,Fairbrother,Thomas,Roy,Male,Caucasian,01/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +59295,67943,61603,PRETRIAL,Fairbrother,Thomas,Roy,Male,Caucasian,01/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +59295,67943,61603,PRETRIAL,Fairbrother,Thomas,Roy,Male,Caucasian,01/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59292,67939,61599,PRETRIAL,LEE,DERRICK,NULL,Male,African-American,11/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,New,1,0 +59292,67939,61599,PRETRIAL,LEE,DERRICK,NULL,Male,African-American,11/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +59292,67939,61599,PRETRIAL,LEE,DERRICK,NULL,Male,African-American,11/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50037,67941,61601,PRETRIAL,Hough,Paul,NULL,Male,African-American,10/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,4,High,7,Risk of Violence,-0.73,9,High,New,1,0 +50037,67941,61601,PRETRIAL,Hough,Paul,NULL,Male,African-American,10/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,4,High,8,Risk of Recidivism,0.88,10,High,New,1,0 +50037,67941,61601,PRETRIAL,Hough,Paul,NULL,Male,African-American,10/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59290,67936,61596,PRETRIAL,Frongello,Jake,Daniel,Male,Caucasian,06/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,4,High,7,Risk of Violence,-0.97,9,High,New,1,0 +59290,67936,61596,PRETRIAL,Frongello,Jake,Daniel,Male,Caucasian,06/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +59290,67936,61596,PRETRIAL,Frongello,Jake,Daniel,Male,Caucasian,06/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59289,67937,61597,PRETRIAL,HARRIS,ASHANTAE,PATRICIA,Female,African-American,01/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +59289,67937,61597,PRETRIAL,HARRIS,ASHANTAE,PATRICIA,Female,African-American,01/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +59289,67937,61597,PRETRIAL,HARRIS,ASHANTAE,PATRICIA,Female,African-American,01/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59288,67935,61595,PRETRIAL,Harriton,Charles,NULL,Male,Caucasian,05/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +59288,67935,61595,PRETRIAL,Harriton,Charles,NULL,Male,Caucasian,05/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +59288,67935,61595,PRETRIAL,Harriton,Charles,NULL,Male,Caucasian,05/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59296,67944,61604,PRETRIAL,Hossain,Rabbir,NULL,Male,African-American,01/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +59296,67944,61604,PRETRIAL,Hossain,Rabbir,NULL,Male,African-American,01/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +59296,67944,61604,PRETRIAL,Hossain,Rabbir,NULL,Male,African-American,01/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59293,67940,61600,PRETRIAL,CLARKE,MICHAEL,NULL,Male,African-American,05/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +59293,67940,61600,PRETRIAL,CLARKE,MICHAEL,NULL,Male,African-American,05/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +59293,67940,61600,PRETRIAL,CLARKE,MICHAEL,NULL,Male,African-American,05/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59294,67942,61602,PRETRIAL,Dejesus,Angel,David,Male,Hispanic,04/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/28/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +59294,67942,61602,PRETRIAL,Dejesus,Angel,David,Male,Hispanic,04/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/28/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +59294,67942,61602,PRETRIAL,Dejesus,Angel,David,Male,Hispanic,04/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59291,67938,61598,PRETRIAL,Benn,Patrick,Sylvester,Male,African-American,04/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +59291,67938,61598,PRETRIAL,Benn,Patrick,Sylvester,Male,African-American,04/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +59291,67938,61598,PRETRIAL,Benn,Patrick,Sylvester,Male,African-American,04/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59298,67946,61606,PRETRIAL,Bocanegra-Garcia,Romy,Carolina,Female,Hispanic,01/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +59298,67946,61606,PRETRIAL,Bocanegra-Garcia,Romy,Carolina,Female,Hispanic,01/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/13 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +59298,67946,61606,PRETRIAL,Bocanegra-Garcia,Romy,Carolina,Female,Hispanic,01/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +15718,67947,61607,PRETRIAL,Garciagarcia,randy,NULL,Male,Hispanic,06/08/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/29/13 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +15718,67947,61607,PRETRIAL,Garciagarcia,randy,NULL,Male,Hispanic,06/08/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/29/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +15718,67947,61607,PRETRIAL,Garciagarcia,randy,NULL,Male,Hispanic,06/08/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/29/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59297,67945,61605,PRETRIAL,Alancastro,Jose,NULL,Male,Hispanic,08/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +59297,67945,61605,PRETRIAL,Alancastro,Jose,NULL,Male,Hispanic,08/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +59297,67945,61605,PRETRIAL,Alancastro,Jose,NULL,Male,Hispanic,08/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59299,67948,61608,PRETRIAL,Fisher,Jay,NULL,Male,Caucasian,02/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +59299,67948,61608,PRETRIAL,Fisher,Jay,NULL,Male,Caucasian,02/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +59299,67948,61608,PRETRIAL,Fisher,Jay,NULL,Male,Caucasian,02/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59301,67952,61612,PRETRIAL,MILES,MARSHA,NULL,Male,Other,08/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/30/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +59301,67952,61612,PRETRIAL,MILES,MARSHA,NULL,Male,Other,08/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/30/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +59301,67952,61612,PRETRIAL,MILES,MARSHA,NULL,Male,Other,08/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59302,67953,61613,PRETRIAL,george,audray,leray,Male,African-American,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.85,9,High,New,1,0 +59302,67953,61613,PRETRIAL,george,audray,leray,Male,African-American,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +59302,67953,61613,PRETRIAL,george,audray,leray,Male,African-American,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +59300,67950,61610,PRETRIAL,Ettinger,Phylis,NULL,Female,Caucasian,11/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/30/13 0:00,2,Medium,7,Risk of Violence,-3,1,Low,New,1,0 +59300,67950,61610,PRETRIAL,Ettinger,Phylis,NULL,Female,Caucasian,11/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,7,Medium,New,1,0 +59300,67950,61610,PRETRIAL,Ettinger,Phylis,NULL,Female,Caucasian,11/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/30/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +4204,67949,61609,PRETRIAL,ALSTON,BRODERICK,L,Male,African-American,09/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/30/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +4204,67949,61609,PRETRIAL,ALSTON,BRODERICK,L,Male,African-American,09/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/30/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +4204,67949,61609,PRETRIAL,ALSTON,BRODERICK,L,Male,African-American,09/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59303,67954,61614,PRETRIAL,Prebal,Juan,NULL,Male,Hispanic,02/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/30/13 0:00,4,High,7,Risk of Violence,-0.85,9,High,New,1,0 +59303,67954,61614,PRETRIAL,Prebal,Juan,NULL,Male,Hispanic,02/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/30/13 0:00,4,High,8,Risk of Recidivism,0.98,10,High,New,1,0 +59303,67954,61614,PRETRIAL,Prebal,Juan,NULL,Male,Hispanic,02/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/30/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +2005,67951,61611,PRETRIAL,R,BYRON,HILL,Male,African-American,12/08/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/30/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +2005,67951,61611,PRETRIAL,R,BYRON,HILL,Male,African-American,12/08/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/30/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +2005,67951,61611,PRETRIAL,R,BYRON,HILL,Male,African-American,12/08/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +1013,67959,61619,PRETRIAL,KING,RASHON,NULL,Male,African-American,05/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,12/1/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +1013,67959,61619,PRETRIAL,KING,RASHON,NULL,Male,African-American,05/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,12/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +1013,67959,61619,PRETRIAL,KING,RASHON,NULL,Male,African-American,05/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,12/1/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +47855,67956,61616,PRETRIAL,Rhoomes,Brian,NULL,Male,African-American,08/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +47855,67956,61616,PRETRIAL,Rhoomes,Brian,NULL,Male,African-American,08/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +47855,67956,61616,PRETRIAL,Rhoomes,Brian,NULL,Male,African-American,08/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +32762,67963,61623,PRETRIAL,KELLY,TAMORRIS,NULL,Male,Caucasian,02/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,4,High,7,Risk of Violence,-0.72,9,High,New,1,0 +32762,67963,61623,PRETRIAL,KELLY,TAMORRIS,NULL,Male,Caucasian,02/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,4,High,8,Risk of Recidivism,0.89,10,High,New,1,0 +32762,67963,61623,PRETRIAL,KELLY,TAMORRIS,NULL,Male,Caucasian,02/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59308,67961,61621,PRETRIAL,AQUINO,CARMELO,NULL,Male,Caucasian,05/31/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/1/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +59308,67961,61621,PRETRIAL,AQUINO,CARMELO,NULL,Male,Caucasian,05/31/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/1/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +59308,67961,61621,PRETRIAL,AQUINO,CARMELO,NULL,Male,Caucasian,05/31/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/1/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59306,67958,61618,PRETRIAL,JASMIN,LEVERDIEU,NULL,Male,African-American,07/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/1/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +59306,67958,61618,PRETRIAL,JASMIN,LEVERDIEU,NULL,Male,African-American,07/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/1/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +59306,67958,61618,PRETRIAL,JASMIN,LEVERDIEU,NULL,Male,African-American,07/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/1/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59307,67960,61620,PRETRIAL,DULOM,edward,NULL,Male,Caucasian,09/30/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/1/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +59307,67960,61620,PRETRIAL,DULOM,edward,NULL,Male,Caucasian,09/30/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/1/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +59307,67960,61620,PRETRIAL,DULOM,edward,NULL,Male,Caucasian,09/30/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/1/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59304,67955,61615,PRETRIAL,Carrascoe,Jose,NULL,Male,Hispanic,08/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/1/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +59304,67955,61615,PRETRIAL,Carrascoe,Jose,NULL,Male,Hispanic,08/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/1/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +59304,67955,61615,PRETRIAL,Carrascoe,Jose,NULL,Male,Hispanic,08/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/1/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59305,67957,61617,PRETRIAL,Williams,Enrick,NULL,Male,African-American,02/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +59305,67957,61617,PRETRIAL,Williams,Enrick,NULL,Male,African-American,02/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +59305,67957,61617,PRETRIAL,Williams,Enrick,NULL,Male,African-American,02/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59309,67962,61622,PRETRIAL,Mathurin,Lunie,NULL,Female,African-American,05/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +59309,67962,61622,PRETRIAL,Mathurin,Lunie,NULL,Female,African-American,05/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +59309,67962,61622,PRETRIAL,Mathurin,Lunie,NULL,Female,African-American,05/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59310,67964,61624,PRETRIAL,strowbridge,rebecca,NULL,Female,African-American,07/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +59310,67964,61624,PRETRIAL,strowbridge,rebecca,NULL,Female,African-American,07/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,7,Medium,New,1,0 +59310,67964,61624,PRETRIAL,strowbridge,rebecca,NULL,Female,African-American,07/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/13 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,New,1,0 +59326,67983,61642,Probation,Mladjenovic,Radovan,NULL,Male,Caucasian,03/11/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/2/13 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +59326,67983,61642,Probation,Mladjenovic,Radovan,NULL,Male,Caucasian,03/11/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/2/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +59326,67983,61642,Probation,Mladjenovic,Radovan,NULL,Male,Caucasian,03/11/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59329,67985,61643,PRETRIAL,Septak,Michael,NULL,Male,Caucasian,12/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.77,2,Low,New,1,0 +59329,67985,61643,PRETRIAL,Septak,Michael,NULL,Male,Caucasian,12/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +59329,67985,61643,PRETRIAL,Septak,Michael,NULL,Male,Caucasian,12/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +51888,67992,61649,PRETRIAL,Garland,Elijah,NULL,Male,African-American,01/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +51888,67992,61649,PRETRIAL,Garland,Elijah,NULL,Male,African-American,01/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +51888,67992,61649,PRETRIAL,Garland,Elijah,NULL,Male,African-American,01/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59315,67969,61629,PRETRIAL,Jackson,Annette,NULL,Female,African-American,08/13/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,12/2/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +59315,67969,61629,PRETRIAL,Jackson,Annette,NULL,Female,African-American,08/13/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,12/2/13 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +59315,67969,61629,PRETRIAL,Jackson,Annette,NULL,Female,African-American,08/13/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59338,67999,61656,Probation,Saunders,Michael,NULL,Male,Caucasian,05/06/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/2/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +59338,67999,61656,Probation,Saunders,Michael,NULL,Male,Caucasian,05/06/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/2/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +59338,67999,61656,Probation,Saunders,Michael,NULL,Male,Caucasian,05/06/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/2/13 0:00,2,Medium,18,Risk of Failure to Appear,40,10,High,New,1,0 +59319,67973,61633,PRETRIAL,Kuntz,Cristina,NULL,Female,Hispanic,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/2/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +59319,67973,61633,PRETRIAL,Kuntz,Cristina,NULL,Female,Hispanic,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/2/13 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +59319,67973,61633,PRETRIAL,Kuntz,Cristina,NULL,Female,Hispanic,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59324,67978,61638,Probation,teruggi,roberto,NULL,Male,Caucasian,07/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +59324,67978,61638,Probation,teruggi,roberto,NULL,Male,Caucasian,07/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +59324,67978,61638,Probation,teruggi,roberto,NULL,Male,Caucasian,07/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +38111,67994,61651,PRETRIAL,Dean,Anthony,NULL,Male,African-American,02/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +38111,67994,61651,PRETRIAL,Dean,Anthony,NULL,Male,African-American,02/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +38111,67994,61651,PRETRIAL,Dean,Anthony,NULL,Male,African-American,02/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59332,67990,61647,PRETRIAL,Sampaio,Sando,NULL,Male,Caucasian,02/11/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/2/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +59332,67990,61647,PRETRIAL,Sampaio,Sando,NULL,Male,Caucasian,02/11/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/2/13 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +59332,67990,61647,PRETRIAL,Sampaio,Sando,NULL,Male,Caucasian,02/11/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59320,67974,61634,PRETRIAL,Slyvain,Claude,NULL,Male,African-American,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,2,Medium,7,Risk of Violence,-1.26,7,Medium,New,1,0 +59320,67974,61634,PRETRIAL,Slyvain,Claude,NULL,Male,African-American,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +59320,67974,61634,PRETRIAL,Slyvain,Claude,NULL,Male,African-American,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +35360,37758,34574,PRETRIAL,Battle,Courtney,NULL,Male,African-American,04/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +35360,37758,34574,PRETRIAL,Battle,Courtney,NULL,Male,African-American,04/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,4,High,8,Risk of Recidivism,0.95,10,High,New,1,0 +35360,37758,34574,PRETRIAL,Battle,Courtney,NULL,Male,African-American,04/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59327,67981,61640,Probation,SEMINARIO,JOHN,CARLOS,Male,Hispanic,06/14/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/2/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +59327,67981,61640,Probation,SEMINARIO,JOHN,CARLOS,Male,Hispanic,06/14/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/2/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +59327,67981,61640,Probation,SEMINARIO,JOHN,CARLOS,Male,Hispanic,06/14/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59334,67995,61652,Probation,Sandoval,Fatima,NULL,Female,Native American,05/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +59334,67995,61652,Probation,Sandoval,Fatima,NULL,Female,Native American,05/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +59334,67995,61652,Probation,Sandoval,Fatima,NULL,Female,Native American,05/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +35360,67987,34574,PRETRIAL,Battle,Courtney,NULL,Male,African-American,04/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,4,High,7,Risk of Violence,-0.96,9,High,Copy,1,0 +35360,67987,34574,PRETRIAL,Battle,Courtney,NULL,Male,African-American,04/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,4,High,8,Risk of Recidivism,1.33,10,High,Copy,1,0 +35360,67987,34574,PRETRIAL,Battle,Courtney,NULL,Male,African-American,04/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +59331,67989,61646,Probation,Bulford,Patrick,NULL,Male,Caucasian,05/04/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/2/13 0:00,1,Low,7,Risk of Violence,-4.37,1,Low,New,1,0 +59331,67989,61646,Probation,Bulford,Patrick,NULL,Male,Caucasian,05/04/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/2/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +59331,67989,61646,Probation,Bulford,Patrick,NULL,Male,Caucasian,05/04/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59312,67966,61626,PRETRIAL,HINTZ,CHANDRA,NULL,Male,Caucasian,03/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +59312,67966,61626,PRETRIAL,HINTZ,CHANDRA,NULL,Male,Caucasian,03/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +59312,67966,61626,PRETRIAL,HINTZ,CHANDRA,NULL,Male,Caucasian,03/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59314,67968,61628,PRETRIAL,Lewis,Britanya,Ranita,Female,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +59314,67968,61628,PRETRIAL,Lewis,Britanya,Ranita,Female,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +59314,67968,61628,PRETRIAL,Lewis,Britanya,Ranita,Female,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +59341,68002,61659,Probation,LUBIN,ALIX,NULL,Male,African-American,11/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +59341,68002,61659,Probation,LUBIN,ALIX,NULL,Male,African-American,11/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +59341,68002,61659,Probation,LUBIN,ALIX,NULL,Male,African-American,11/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59322,67976,61636,PRETRIAL,DARWISH,ABRAHIEM,NULL,Male,Caucasian,02/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,New,1,0 +59322,67976,61636,PRETRIAL,DARWISH,ABRAHIEM,NULL,Male,Caucasian,02/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +59322,67976,61636,PRETRIAL,DARWISH,ABRAHIEM,NULL,Male,Caucasian,02/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57813,67979,59954,Probation,Romeroarroyo,Jose,NULL,Male,Hispanic,05/07/63,17,All Scales,Intake,English,Conditional Release,Probation,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +57813,67979,59954,Probation,Romeroarroyo,Jose,NULL,Male,Hispanic,05/07/63,17,All Scales,Intake,English,Conditional Release,Probation,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +57813,67979,59954,Probation,Romeroarroyo,Jose,NULL,Male,Hispanic,05/07/63,17,All Scales,Intake,English,Conditional Release,Probation,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,19,2,Low,New,1,0 +59336,67997,61654,Probation,stepper,sheri,NULL,Female,Caucasian,08/07/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +59336,67997,61654,Probation,stepper,sheri,NULL,Female,Caucasian,08/07/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +59336,67997,61654,Probation,stepper,sheri,NULL,Female,Caucasian,08/07/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58894,67984,61134,PRETRIAL,Moran,Robert,NULL,Male,Caucasian,08/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,Copy,1,0 +58894,67984,61134,PRETRIAL,Moran,Robert,NULL,Male,Caucasian,08/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,Copy,1,0 +58894,67984,61134,PRETRIAL,Moran,Robert,NULL,Male,Caucasian,08/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +59317,67971,61631,PRETRIAL,JURADO,ADRIANA,NULL,Male,Caucasian,04/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/2/13 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +59317,67971,61631,PRETRIAL,JURADO,ADRIANA,NULL,Male,Caucasian,04/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/2/13 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +59317,67971,61631,PRETRIAL,JURADO,ADRIANA,NULL,Male,Caucasian,04/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59311,67965,61625,PRETRIAL,BROWN,LEVERRON,NULL,Male,African-American,10/29/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,2,Medium,7,Risk of Violence,-2.66,2,Low,New,1,0 +59311,67965,61625,PRETRIAL,BROWN,LEVERRON,NULL,Male,African-American,10/29/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +59311,67965,61625,PRETRIAL,BROWN,LEVERRON,NULL,Male,African-American,10/29/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +53962,67986,61644,PRETRIAL,Wyngaarde,Johan,Anson,Male,African-American,07/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +53962,67986,61644,PRETRIAL,Wyngaarde,Johan,Anson,Male,African-American,07/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +53962,67986,61644,PRETRIAL,Wyngaarde,Johan,Anson,Male,African-American,07/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59342,68003,61660,Probation,Fournier,Antonio,NULL,Male,Hispanic,03/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/2/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +59342,68003,61660,Probation,Fournier,Antonio,NULL,Male,Hispanic,03/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/2/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +59342,68003,61660,Probation,Fournier,Antonio,NULL,Male,Hispanic,03/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59328,67982,61641,Probation,Cuff,Robert,NULL,Male,African-American,12/08/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +59328,67982,61641,Probation,Cuff,Robert,NULL,Male,African-American,12/08/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +59328,67982,61641,Probation,Cuff,Robert,NULL,Male,African-American,12/08/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59316,67970,61630,PRETRIAL,Briones,Jose,Vielma,Male,Caucasian,03/07/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +59316,67970,61630,PRETRIAL,Briones,Jose,Vielma,Male,Caucasian,03/07/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +59316,67970,61630,PRETRIAL,Briones,Jose,Vielma,Male,Caucasian,03/07/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59323,67977,61637,PRETRIAL,Hamilton,Jamie,Lynne,Female,Caucasian,09/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +59323,67977,61637,PRETRIAL,Hamilton,Jamie,Lynne,Female,Caucasian,09/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +59323,67977,61637,PRETRIAL,Hamilton,Jamie,Lynne,Female,Caucasian,09/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59339,68000,61657,Probation,arancibia,Eduardo,NULL,Male,Hispanic,08/17/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/2/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +59339,68000,61657,Probation,arancibia,Eduardo,NULL,Male,Hispanic,08/17/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/2/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +59339,68000,61657,Probation,arancibia,Eduardo,NULL,Male,Hispanic,08/17/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59337,67998,61655,Probation,UPSHAW,OSCAR,NULL,Male,African-American,12/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +59337,67998,61655,Probation,UPSHAW,OSCAR,NULL,Male,African-American,12/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +59337,67998,61655,Probation,UPSHAW,OSCAR,NULL,Male,African-American,12/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59330,67988,61645,PRETRIAL,VEGA,CORY,NULL,Male,Caucasian,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +59330,67988,61645,PRETRIAL,VEGA,CORY,NULL,Male,Caucasian,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +59330,67988,61645,PRETRIAL,VEGA,CORY,NULL,Male,Caucasian,11/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59318,67972,61632,PRETRIAL,Wilson,David,NULL,Male,Caucasian,10/21/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/2/13 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +59318,67972,61632,PRETRIAL,Wilson,David,NULL,Male,Caucasian,10/21/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/2/13 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +59318,67972,61632,PRETRIAL,Wilson,David,NULL,Male,Caucasian,10/21/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59321,67975,61635,PRETRIAL,Alvarez,Kenneth,Eric,Male,Caucasian,08/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/2/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +59321,67975,61635,PRETRIAL,Alvarez,Kenneth,Eric,Male,Caucasian,08/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/2/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +59321,67975,61635,PRETRIAL,Alvarez,Kenneth,Eric,Male,Caucasian,08/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59333,67993,61650,Probation,Martinez,J-Isaac,NULL,Male,Hispanic,09/03/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/2/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +59333,67993,61650,Probation,Martinez,J-Isaac,NULL,Male,Hispanic,09/03/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/2/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +59333,67993,61650,Probation,Martinez,J-Isaac,NULL,Male,Hispanic,09/03/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +47519,67980,61639,Probation,colato,karen,NULL,Female,Hispanic,11/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +47519,67980,61639,Probation,colato,karen,NULL,Female,Hispanic,11/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,8,High,New,1,0 +47519,67980,61639,Probation,colato,karen,NULL,Female,Hispanic,11/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +59313,67967,61627,PRETRIAL,TORRES,WILFREDO,NULL,Male,Caucasian,07/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/2/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +59313,67967,61627,PRETRIAL,TORRES,WILFREDO,NULL,Male,Caucasian,07/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/2/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +59313,67967,61627,PRETRIAL,TORRES,WILFREDO,NULL,Male,Caucasian,07/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/2/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59340,68001,61658,Probation,CARDOSO,stephanie,NULL,Female,Caucasian,09/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,New,1,0 +59340,68001,61658,Probation,CARDOSO,stephanie,NULL,Female,Caucasian,09/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,9,High,New,1,0 +59340,68001,61658,Probation,CARDOSO,stephanie,NULL,Female,Caucasian,09/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/2/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +20314,68035,61688,PRETRIAL,SWINT,ANTHONY,L,Male,African-American,09/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.31,3,Low,New,1,0 +20314,68035,61688,PRETRIAL,SWINT,ANTHONY,L,Male,African-American,09/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +20314,68035,61688,PRETRIAL,SWINT,ANTHONY,L,Male,African-American,09/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59350,68014,61670,PRETRIAL,Jones,Edith,NULL,Female,Caucasian,02/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +59350,68014,61670,PRETRIAL,Jones,Edith,NULL,Female,Caucasian,02/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +59350,68014,61670,PRETRIAL,Jones,Edith,NULL,Female,Caucasian,02/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59358,68022,61676,Probation,Belnavis,Robert,NULL,Male,African-American,10/05/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/3/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +59358,68022,61676,Probation,Belnavis,Robert,NULL,Male,African-American,10/05/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/3/13 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +59358,68022,61676,Probation,Belnavis,Robert,NULL,Male,African-American,10/05/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50005,68040,61693,PRETRIAL,JEAN-FELIX,STEPHEN,ALEXANDRE,Male,African-American,08/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +50005,68040,61693,PRETRIAL,JEAN-FELIX,STEPHEN,ALEXANDRE,Male,African-American,08/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +50005,68040,61693,PRETRIAL,JEAN-FELIX,STEPHEN,ALEXANDRE,Male,African-American,08/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59370,68038,61691,Probation,velentzas,susan,NULL,Male,Caucasian,07/27/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/3/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +59370,68038,61691,Probation,velentzas,susan,NULL,Male,Caucasian,07/27/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/3/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +59370,68038,61691,Probation,velentzas,susan,NULL,Male,Caucasian,07/27/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59346,68009,61665,PRETRIAL,CHASTEEN,BRANDON,SHANE,Male,Caucasian,03/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +59346,68009,61665,PRETRIAL,CHASTEEN,BRANDON,SHANE,Male,Caucasian,03/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +59346,68009,61665,PRETRIAL,CHASTEEN,BRANDON,SHANE,Male,Caucasian,03/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59359,68024,61678,Probation,Philo,Ed,NULL,Male,African-American,05/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +59359,68024,61678,Probation,Philo,Ed,NULL,Male,African-American,05/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +59359,68024,61678,Probation,Philo,Ed,NULL,Male,African-American,05/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +59352,68017,61672,PRETRIAL,diprima,gregg,NULL,Male,Caucasian,02/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +59352,68017,61672,PRETRIAL,diprima,gregg,NULL,Male,Caucasian,02/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +59352,68017,61672,PRETRIAL,diprima,gregg,NULL,Male,Caucasian,02/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +46373,68030,61683,Probation,Horvath,Levente,NULL,Male,Caucasian,08/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/3/13 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +46373,68030,61683,Probation,Horvath,Levente,NULL,Male,Caucasian,08/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/3/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +46373,68030,61683,Probation,Horvath,Levente,NULL,Male,Caucasian,08/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +39386,68032,61685,PRETRIAL,ARMISTEAD,ROBERT,G,Male,Caucasian,02/26/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +39386,68032,61685,PRETRIAL,ARMISTEAD,ROBERT,G,Male,Caucasian,02/26/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +39386,68032,61685,PRETRIAL,ARMISTEAD,ROBERT,G,Male,Caucasian,02/26/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59357,68021,61675,PRETRIAL,Ibanez,Marco,NULL,Male,Hispanic,04/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +59357,68021,61675,PRETRIAL,Ibanez,Marco,NULL,Male,Hispanic,04/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +59357,68021,61675,PRETRIAL,Ibanez,Marco,NULL,Male,Hispanic,04/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58912,68019,61149,PRETRIAL,LOMAGISTRO,SCOTT,NULL,Male,Caucasian,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,Copy,1,0 +58912,68019,61149,PRETRIAL,LOMAGISTRO,SCOTT,NULL,Male,Caucasian,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,Copy,1,0 +58912,68019,61149,PRETRIAL,LOMAGISTRO,SCOTT,NULL,Male,Caucasian,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +59344,68007,61663,PRETRIAL,Ramsey,Eric,NULL,Male,African-American,03/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +59344,68007,61663,PRETRIAL,Ramsey,Eric,NULL,Male,African-American,03/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +59344,68007,61663,PRETRIAL,Ramsey,Eric,NULL,Male,African-American,03/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +49147,68012,61668,PRETRIAL,OCONNOR,MICHAEL,NULL,Male,Caucasian,04/06/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +49147,68012,61668,PRETRIAL,OCONNOR,MICHAEL,NULL,Male,Caucasian,04/06/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +49147,68012,61668,PRETRIAL,OCONNOR,MICHAEL,NULL,Male,Caucasian,04/06/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59369,68037,61690,Probation,Kerolle,Daniel,NULL,Male,African-American,04/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +59369,68037,61690,Probation,Kerolle,Daniel,NULL,Male,African-American,04/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +59369,68037,61690,Probation,Kerolle,Daniel,NULL,Male,African-American,04/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58991,68016,61252,PRETRIAL,DAY,CLETUS,NULL,Male,Caucasian,11/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,Copy,1,0 +58991,68016,61252,PRETRIAL,DAY,CLETUS,NULL,Male,Caucasian,11/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,Copy,1,0 +58991,68016,61252,PRETRIAL,DAY,CLETUS,NULL,Male,Caucasian,11/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +59367,68033,61686,PRETRIAL,hudson,fernando,NULL,Male,African-American,09/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +59367,68033,61686,PRETRIAL,hudson,fernando,NULL,Male,African-American,09/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +59367,68033,61686,PRETRIAL,hudson,fernando,NULL,Male,African-American,09/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +2715,68005,61661,PRETRIAL,WILLIAMS,JERMAINE,NULL,Male,African-American,02/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +2715,68005,61661,PRETRIAL,WILLIAMS,JERMAINE,NULL,Male,African-American,02/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +2715,68005,61661,PRETRIAL,WILLIAMS,JERMAINE,NULL,Male,African-American,02/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54453,68018,61673,Probation,DEJESUS,ANGEL,LUIS,Male,Hispanic,09/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +54453,68018,61673,Probation,DEJESUS,ANGEL,LUIS,Male,Hispanic,09/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +54453,68018,61673,Probation,DEJESUS,ANGEL,LUIS,Male,Hispanic,09/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59361,68026,61679,PRETRIAL,Cloninger,William,Elzia,Male,Caucasian,08/01/86,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,4,High,7,Risk of Violence,-0.48,10,High,Copy,1,0 +59361,68026,61679,PRETRIAL,Cloninger,William,Elzia,Male,Caucasian,08/01/86,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,4,High,8,Risk of Recidivism,0.84,10,High,Copy,1,0 +59361,68026,61679,PRETRIAL,Cloninger,William,Elzia,Male,Caucasian,08/01/86,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,4,High,18,Risk of Failure to Appear,35,10,High,Copy,1,0 +59360,68023,61677,PRETRIAL,ETIENNE,RUTH,NULL,Female,African-American,08/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +59360,68023,61677,PRETRIAL,ETIENNE,RUTH,NULL,Female,African-American,08/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +59360,68023,61677,PRETRIAL,ETIENNE,RUTH,NULL,Female,African-American,08/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59366,68031,61684,Probation,Williams,Christopher,NULL,Male,African-American,03/04/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +59366,68031,61684,Probation,Williams,Christopher,NULL,Male,African-American,03/04/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +59366,68031,61684,Probation,Williams,Christopher,NULL,Male,African-American,03/04/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59347,68010,61666,PRETRIAL,Davis,Lawrence,Kelvin,Male,African-American,08/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +59347,68010,61666,PRETRIAL,Davis,Lawrence,Kelvin,Male,African-American,08/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +59347,68010,61666,PRETRIAL,Davis,Lawrence,Kelvin,Male,African-American,08/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +34724,68004,33888,Probation,Harris,Roy,Bee,Male,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,Copy,1,0 +34724,68004,33888,Probation,Harris,Roy,Bee,Male,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,Copy,1,0 +34724,68004,33888,Probation,Harris,Roy,Bee,Male,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +59351,68015,61671,PRETRIAL,BEACHEM,MARCUS,YALE,Male,African-American,11/04/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.15,4,Low,New,1,0 +59351,68015,61671,PRETRIAL,BEACHEM,MARCUS,YALE,Male,African-American,11/04/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +59351,68015,61671,PRETRIAL,BEACHEM,MARCUS,YALE,Male,African-American,11/04/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59365,68029,61682,Probation,Glaze,Joshua,Steven,Male,Caucasian,10/26/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/3/13 0:00,4,High,7,Risk of Violence,-0.54,10,High,New,1,0 +59365,68029,61682,Probation,Glaze,Joshua,Steven,Male,Caucasian,10/26/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/3/13 0:00,4,High,8,Risk of Recidivism,1.19,10,High,New,1,0 +59365,68029,61682,Probation,Glaze,Joshua,Steven,Male,Caucasian,10/26/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/3/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59345,68008,61664,PRETRIAL,Pena,Rodolfo,M,Male,Hispanic,03/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +59345,68008,61664,PRETRIAL,Pena,Rodolfo,M,Male,Hispanic,03/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +59345,68008,61664,PRETRIAL,Pena,Rodolfo,M,Male,Hispanic,03/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +59348,68011,61667,PRETRIAL,Tritsch,Michael,J,Female,Caucasian,02/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +59348,68011,61667,PRETRIAL,Tritsch,Michael,J,Female,Caucasian,02/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +59348,68011,61667,PRETRIAL,Tritsch,Michael,J,Female,Caucasian,02/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59361,68025,61679,PRETRIAL,Cloninger,William,Elzia,Male,Caucasian,08/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,4,High,7,Risk of Violence,-0.48,10,High,New,1,0 +59361,68025,61679,PRETRIAL,Cloninger,William,Elzia,Male,Caucasian,08/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,4,High,8,Risk of Recidivism,0.84,10,High,New,1,0 +59361,68025,61679,PRETRIAL,Cloninger,William,Elzia,Male,Caucasian,08/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,4,High,18,Risk of Failure to Appear,35,10,High,New,1,0 +59362,68027,61680,PRETRIAL,Nguyen,Kelvin,NULL,Male,Asian,02/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +59362,68027,61680,PRETRIAL,Nguyen,Kelvin,NULL,Male,Asian,02/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +59362,68027,61680,PRETRIAL,Nguyen,Kelvin,NULL,Male,Asian,02/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54876,68041,61694,PRETRIAL,HERNANDEZ,RAYMOND,NULL,Male,Caucasian,06/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +54876,68041,61694,PRETRIAL,HERNANDEZ,RAYMOND,NULL,Male,Caucasian,06/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +54876,68041,61694,PRETRIAL,HERNANDEZ,RAYMOND,NULL,Male,Caucasian,06/24/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59343,68006,61662,PRETRIAL,AMATO,JOSEPH,M,Male,Caucasian,01/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +59343,68006,61662,PRETRIAL,AMATO,JOSEPH,M,Male,Caucasian,01/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +59343,68006,61662,PRETRIAL,AMATO,JOSEPH,M,Male,Caucasian,01/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59349,68013,61669,PRETRIAL,BEGUIRISTAIN,IGNACIO,NULL,Male,Caucasian,03/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +59349,68013,61669,PRETRIAL,BEGUIRISTAIN,IGNACIO,NULL,Male,Caucasian,03/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +59349,68013,61669,PRETRIAL,BEGUIRISTAIN,IGNACIO,NULL,Male,Caucasian,03/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59356,68020,61674,PRETRIAL,Rocha,Jedidiah,NULL,Male,Caucasian,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +59356,68020,61674,PRETRIAL,Rocha,Jedidiah,NULL,Male,Caucasian,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +59356,68020,61674,PRETRIAL,Rocha,Jedidiah,NULL,Male,Caucasian,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +23656,68034,61687,PRETRIAL,PEIKES,ASHLEY,NULL,Female,Caucasian,03/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/3/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +23656,68034,61687,PRETRIAL,PEIKES,ASHLEY,NULL,Female,Caucasian,03/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/3/13 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +23656,68034,61687,PRETRIAL,PEIKES,ASHLEY,NULL,Female,Caucasian,03/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59368,68036,61689,Probation,langan,matthew,NULL,Male,Caucasian,11/11/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +59368,68036,61689,Probation,langan,matthew,NULL,Male,Caucasian,11/11/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +59368,68036,61689,Probation,langan,matthew,NULL,Male,Caucasian,11/11/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/3/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50569,68055,57429,PRETRIAL,Terrero,Raul,E.,Male,Hispanic,11/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/4/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +50569,68055,57429,PRETRIAL,Terrero,Raul,E.,Male,Hispanic,11/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +50569,68055,57429,PRETRIAL,Terrero,Raul,E.,Male,Hispanic,11/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59382,68057,61707,Probation,johnson,alfreddie,NULL,Male,African-American,09/25/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/4/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +59382,68057,61707,Probation,johnson,alfreddie,NULL,Male,African-American,09/25/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +59382,68057,61707,Probation,johnson,alfreddie,NULL,Male,African-American,09/25/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59386,68062,61710,Probation,Bauman,Sean,NULL,Male,Caucasian,10/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +59386,68062,61710,Probation,Bauman,Sean,NULL,Male,Caucasian,10/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +59386,68062,61710,Probation,Bauman,Sean,NULL,Male,Caucasian,10/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59388,68064,61711,PRETRIAL,Simon,Louis,B,Male,Caucasian,12/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.26,1,Low,Copy,1,0 +59388,68064,61711,PRETRIAL,Simon,Louis,B,Male,Caucasian,12/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,Copy,1,0 +59388,68064,61711,PRETRIAL,Simon,Louis,B,Male,Caucasian,12/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,Copy,1,0 +58864,68078,61101,PRETRIAL,BETEZA,SHAWN,M,Male,Caucasian,09/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/4/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +58864,68078,61101,PRETRIAL,BETEZA,SHAWN,M,Male,Caucasian,09/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +58864,68078,61101,PRETRIAL,BETEZA,SHAWN,M,Male,Caucasian,09/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59396,68076,61721,Probation,HELTON,JAMES,E,Male,Caucasian,08/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/4/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +59396,68076,61721,Probation,HELTON,JAMES,E,Male,Caucasian,08/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +59396,68076,61721,Probation,HELTON,JAMES,E,Male,Caucasian,08/27/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57479,68046,61698,PRETRIAL,Brutus,Irvans,NULL,Male,Other,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +57479,68046,61698,PRETRIAL,Brutus,Irvans,NULL,Male,Other,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +57479,68046,61698,PRETRIAL,Brutus,Irvans,NULL,Male,Other,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +44587,68071,61718,PRETRIAL,GASKINS,LATONYA,YVONNE,Female,African-American,08/02/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +44587,68071,61718,PRETRIAL,GASKINS,LATONYA,YVONNE,Female,African-American,08/02/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +44587,68071,61718,PRETRIAL,GASKINS,LATONYA,YVONNE,Female,African-American,08/02/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +58732,68080,60947,Probation,RODRIGUEZ,RYAN,C,Male,Hispanic,07/06/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +58732,68080,60947,Probation,RODRIGUEZ,RYAN,C,Male,Hispanic,07/06/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,5,Medium,New,1,0 +58732,68080,60947,Probation,RODRIGUEZ,RYAN,C,Male,Hispanic,07/06/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,2,Medium,18,Risk of Failure to Appear,21,3,Low,New,1,0 +59378,68050,61702,PRETRIAL,JENKINS,BRANDON,NULL,Male,African-American,10/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +59378,68050,61702,PRETRIAL,JENKINS,BRANDON,NULL,Male,African-American,10/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +59378,68050,61702,PRETRIAL,JENKINS,BRANDON,NULL,Male,African-American,10/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59391,68067,61714,PRETRIAL,Zaharis,Ellena,NULL,Female,Caucasian,03/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/4/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +59391,68067,61714,PRETRIAL,Zaharis,Ellena,NULL,Female,Caucasian,03/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/4/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +59391,68067,61714,PRETRIAL,Zaharis,Ellena,NULL,Female,Caucasian,03/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59384,68060,61709,DRRD,Lopez,Fernando,NULL,Male,African-American,07/17/91,17,All Scales,Intake,English,Pretrial,Probation,Married,12/4/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +59384,68060,61709,DRRD,Lopez,Fernando,NULL,Male,African-American,07/17/91,17,All Scales,Intake,English,Pretrial,Probation,Married,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.5,4,Low,New,1,0 +59384,68060,61709,DRRD,Lopez,Fernando,NULL,Male,African-American,07/17/91,17,All Scales,Intake,English,Pretrial,Probation,Married,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +59399,68081,61724,PRETRIAL,daniel,odonoghue,NULL,Male,Caucasian,08/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +59399,68081,61724,PRETRIAL,daniel,odonoghue,NULL,Male,Caucasian,08/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +59399,68081,61724,PRETRIAL,daniel,odonoghue,NULL,Male,Caucasian,08/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59392,68068,61715,Probation,palenzuela,mariano,NULL,Male,Hispanic,05/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +59392,68068,61715,Probation,palenzuela,mariano,NULL,Male,Hispanic,05/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +59392,68068,61715,Probation,palenzuela,mariano,NULL,Male,Hispanic,05/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +22888,68044,56440,PRETRIAL,Glinton,Afred,NULL,Male,African-American,04/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,Copy,1,0 +22888,68044,56440,PRETRIAL,Glinton,Afred,NULL,Male,African-American,04/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,Copy,1,0 +22888,68044,56440,PRETRIAL,Glinton,Afred,NULL,Male,African-American,04/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +59375,68047,61699,PRETRIAL,Holmes,Robert,NULL,Male,Caucasian,09/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +59375,68047,61699,PRETRIAL,Holmes,Robert,NULL,Male,Caucasian,09/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +59375,68047,61699,PRETRIAL,Holmes,Robert,NULL,Male,Caucasian,09/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59387,68065,61712,Probation,Orellana,Oscar,NULL,Male,Hispanic,06/23/62,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,12/4/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +59387,68065,61712,Probation,Orellana,Oscar,NULL,Male,Hispanic,06/23/62,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,12/4/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +59387,68065,61712,Probation,Orellana,Oscar,NULL,Male,Hispanic,06/23/62,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59380,68052,61704,PRETRIAL,Sweeting,Roderica,NULL,Female,African-American,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +59380,68052,61704,PRETRIAL,Sweeting,Roderica,NULL,Female,African-American,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +59380,68052,61704,PRETRIAL,Sweeting,Roderica,NULL,Female,African-American,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +48884,68073,49638,PRETRIAL,Bensinger,Arnold,NULL,Male,Caucasian,05/23/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,Copy,1,0 +48884,68073,49638,PRETRIAL,Bensinger,Arnold,NULL,Male,Caucasian,05/23/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,Copy,1,0 +48884,68073,49638,PRETRIAL,Bensinger,Arnold,NULL,Male,Caucasian,05/23/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +56551,68054,58554,PRETRIAL,Baptista,Christopher,Andrew,Male,Hispanic,09/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,Copy,1,0 +56551,68054,58554,PRETRIAL,Baptista,Christopher,Andrew,Male,Hispanic,09/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,Copy,1,0 +56551,68054,58554,PRETRIAL,Baptista,Christopher,Andrew,Male,Hispanic,09/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +59398,68079,61723,PRETRIAL,Khoury,Albert,NULL,Male,Caucasian,12/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/4/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +59398,68079,61723,PRETRIAL,Khoury,Albert,NULL,Male,Caucasian,12/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/4/13 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +59398,68079,61723,PRETRIAL,Khoury,Albert,NULL,Male,Caucasian,12/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53894,68058,55416,PRETRIAL,Clarke,Keontrae,NULL,Female,African-American,08/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +53894,68058,55416,PRETRIAL,Clarke,Keontrae,NULL,Female,African-American,08/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,4,High,8,Risk of Recidivism,0.66,10,High,New,1,0 +53894,68058,55416,PRETRIAL,Clarke,Keontrae,NULL,Female,African-American,08/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +35290,68075,61720,PRETRIAL,ALEBA,DAVI,NULL,Female,Caucasian,10/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/4/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +35290,68075,61720,PRETRIAL,ALEBA,DAVI,NULL,Female,Caucasian,10/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +35290,68075,61720,PRETRIAL,ALEBA,DAVI,NULL,Female,Caucasian,10/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59377,68049,61701,PRETRIAL,Ducard,Vladimir,NULL,Male,African-American,12/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +59377,68049,61701,PRETRIAL,Ducard,Vladimir,NULL,Male,African-American,12/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +59377,68049,61701,PRETRIAL,Ducard,Vladimir,NULL,Male,African-American,12/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59372,68042,61695,PRETRIAL,Taylor,Kedric,NULL,Male,African-American,12/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +59372,68042,61695,PRETRIAL,Taylor,Kedric,NULL,Male,African-American,12/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +59372,68042,61695,PRETRIAL,Taylor,Kedric,NULL,Male,African-American,12/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +33118,68056,61706,PRETRIAL,DUMASSAIS,JUNIOR,NULL,Male,African-American,06/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +33118,68056,61706,PRETRIAL,DUMASSAIS,JUNIOR,NULL,Male,African-American,06/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +33118,68056,61706,PRETRIAL,DUMASSAIS,JUNIOR,NULL,Male,African-American,06/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +3363,68070,61717,PRETRIAL,Coninsby,Alfred,Alfred,Male,Caucasian,09/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,New,1,0 +3363,68070,61717,PRETRIAL,Coninsby,Alfred,Alfred,Male,Caucasian,09/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +3363,68070,61717,PRETRIAL,Coninsby,Alfred,Alfred,Male,Caucasian,09/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59379,68051,61703,PRETRIAL,HARRIS,MAURICE,J,Male,African-American,12/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,New,1,0 +59379,68051,61703,PRETRIAL,HARRIS,MAURICE,J,Male,African-American,12/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +59379,68051,61703,PRETRIAL,HARRIS,MAURICE,J,Male,African-American,12/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59381,68053,61705,PRETRIAL,INSUA,JORGE,NULL,Male,Caucasian,05/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +59381,68053,61705,PRETRIAL,INSUA,JORGE,NULL,Male,Caucasian,05/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +59381,68053,61705,PRETRIAL,INSUA,JORGE,NULL,Male,Caucasian,05/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59389,68066,61713,PRETRIAL,Mosleyjr,Eddie,Lee,Male,African-American,11/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.52,3,Low,New,1,0 +59389,68066,61713,PRETRIAL,Mosleyjr,Eddie,Lee,Male,African-American,11/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +59389,68066,61713,PRETRIAL,Mosleyjr,Eddie,Lee,Male,African-American,11/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59383,68059,61708,Probation,WILSON,BRIAN,A,Male,Hispanic,10/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/4/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +59383,68059,61708,Probation,WILSON,BRIAN,A,Male,Hispanic,10/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/4/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +59383,68059,61708,Probation,WILSON,BRIAN,A,Male,Hispanic,10/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59374,68045,61697,PRETRIAL,MURRAY,ANNE,MERYL,Female,Caucasian,02/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/4/13 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +59374,68045,61697,PRETRIAL,MURRAY,ANNE,MERYL,Female,Caucasian,02/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/4/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +59374,68045,61697,PRETRIAL,MURRAY,ANNE,MERYL,Female,Caucasian,02/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59395,68074,61719,Probation,PERRI,JOSEPH,G,Male,Caucasian,01/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +59395,68074,61719,Probation,PERRI,JOSEPH,G,Male,Caucasian,01/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +59395,68074,61719,Probation,PERRI,JOSEPH,G,Male,Caucasian,01/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +8157,62542,56752,PRETRIAL,wilcher,devondrea,NULL,Male,African-American,06/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +8157,62542,56752,PRETRIAL,wilcher,devondrea,NULL,Male,African-American,06/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,4,High,8,Risk of Recidivism,0.47,9,High,New,1,0 +8157,62542,56752,PRETRIAL,wilcher,devondrea,NULL,Male,African-American,06/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59373,68043,61696,PRETRIAL,FERGUSON,DYONTAE,MARQUIS,Male,African-American,05/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +59373,68043,61696,PRETRIAL,FERGUSON,DYONTAE,MARQUIS,Male,African-American,05/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +59373,68043,61696,PRETRIAL,FERGUSON,DYONTAE,MARQUIS,Male,African-American,05/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30731,68061,29716,Probation,GEORGE,KATHRYN,ANN,Male,Caucasian,08/20/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,4,High,7,Risk of Violence,-0.33,10,High,New,1,0 +30731,68061,29716,Probation,GEORGE,KATHRYN,ANN,Male,Caucasian,08/20/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +30731,68061,29716,Probation,GEORGE,KATHRYN,ANN,Male,Caucasian,08/20/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/13 0:00,4,High,18,Risk of Failure to Appear,31,8,High,New,1,0 +59376,68048,61700,PRETRIAL,Fennell,Kenneth,NULL,Male,African-American,08/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +59376,68048,61700,PRETRIAL,Fennell,Kenneth,NULL,Male,African-American,08/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +59376,68048,61700,PRETRIAL,Fennell,Kenneth,NULL,Male,African-American,08/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +32922,68082,61725,PRETRIAL,Keefer,Gary,NULL,Male,Caucasian,01/03/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/4/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +32922,68082,61725,PRETRIAL,Keefer,Gary,NULL,Male,Caucasian,01/03/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/4/13 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +32922,68082,61725,PRETRIAL,Keefer,Gary,NULL,Male,Caucasian,01/03/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/4/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +42890,68069,61716,PRETRIAL,Joseph,Shaderson,NULL,Male,African-American,01/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +42890,68069,61716,PRETRIAL,Joseph,Shaderson,NULL,Male,African-American,01/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.73,10,High,New,1,0 +42890,68069,61716,PRETRIAL,Joseph,Shaderson,NULL,Male,African-American,01/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/4/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +59417,68103,61744,PRETRIAL,marino,terance,NULL,Male,Caucasian,08/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +59417,68103,61744,PRETRIAL,marino,terance,NULL,Male,Caucasian,08/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +59417,68103,61744,PRETRIAL,marino,terance,NULL,Male,Caucasian,08/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59428,68116,61756,Probation,Griggs,Rebecca,Anne,Female,Caucasian,09/30/51,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,12/5/13 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +59428,68116,61756,Probation,Griggs,Rebecca,Anne,Female,Caucasian,09/30/51,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +59428,68116,61756,Probation,Griggs,Rebecca,Anne,Female,Caucasian,09/30/51,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59420,68108,61748,Probation,Santiago,Jose,NULL,Male,Hispanic,09/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +59420,68108,61748,Probation,Santiago,Jose,NULL,Male,Hispanic,09/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +59420,68108,61748,Probation,Santiago,Jose,NULL,Male,Hispanic,09/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59423,68111,61751,Probation,Petrillo,David,NULL,Male,Caucasian,05/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +59423,68111,61751,Probation,Petrillo,David,NULL,Male,Caucasian,05/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +59423,68111,61751,Probation,Petrillo,David,NULL,Male,Caucasian,05/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59407,68090,61733,PRETRIAL,Latson,Katavia,NULL,Female,African-American,03/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +59407,68090,61733,PRETRIAL,Latson,Katavia,NULL,Female,African-American,03/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,New,1,0 +59407,68090,61733,PRETRIAL,Latson,Katavia,NULL,Female,African-American,03/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59440,68129,61769,PRETRIAL,VALLMYR,JASON,NULL,Male,African-American,03/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +59440,68129,61769,PRETRIAL,VALLMYR,JASON,NULL,Male,African-American,03/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +59440,68129,61769,PRETRIAL,VALLMYR,JASON,NULL,Male,African-American,03/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59411,68095,61737,Probation,CELENTANO,WILLIAM,D,Male,Caucasian,06/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/5/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +59411,68095,61737,Probation,CELENTANO,WILLIAM,D,Male,Caucasian,06/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +59411,68095,61737,Probation,CELENTANO,WILLIAM,D,Male,Caucasian,06/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59435,68124,61764,Probation,Matthias,Katherina,NULL,Female,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/5/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +59435,68124,61764,Probation,Matthias,Katherina,NULL,Female,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +59435,68124,61764,Probation,Matthias,Katherina,NULL,Female,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59404,68087,61730,PRETRIAL,Quinterri,Taryn,Elizabeth,Female,Caucasian,12/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +59404,68087,61730,PRETRIAL,Quinterri,Taryn,Elizabeth,Female,Caucasian,12/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +59404,68087,61730,PRETRIAL,Quinterri,Taryn,Elizabeth,Female,Caucasian,12/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59444,68132,61772,Probation,ROSA,MISHELL,NULL,Female,Hispanic,08/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +59444,68132,61772,Probation,ROSA,MISHELL,NULL,Female,Hispanic,08/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +59444,68132,61772,Probation,ROSA,MISHELL,NULL,Female,Hispanic,08/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +59431,68119,61759,Probation,ellis,ricardo,NULL,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +59431,68119,61759,Probation,ellis,ricardo,NULL,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +59431,68119,61759,Probation,ellis,ricardo,NULL,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59414,68098,61740,PRETRIAL,Silva,Hudson,NULL,Male,Other,03/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/5/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +59414,68098,61740,PRETRIAL,Silva,Hudson,NULL,Male,Other,03/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +59414,68098,61740,PRETRIAL,Silva,Hudson,NULL,Male,Other,03/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59433,68121,61761,Probation,Geldres,Carlos,NULL,Male,Hispanic,07/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/5/13 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +59433,68121,61761,Probation,Geldres,Carlos,NULL,Male,Hispanic,07/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +59433,68121,61761,Probation,Geldres,Carlos,NULL,Male,Hispanic,07/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59437,68126,61766,Probation,hirsch,steven,NULL,Male,Other,06/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +59437,68126,61766,Probation,hirsch,steven,NULL,Male,Other,06/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +59437,68126,61766,Probation,hirsch,steven,NULL,Male,Other,06/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59401,68084,61727,PRETRIAL,JHAMSON,JEAN,NULL,Male,African-American,10/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +59401,68084,61727,PRETRIAL,JHAMSON,JEAN,NULL,Male,African-American,10/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +59401,68084,61727,PRETRIAL,JHAMSON,JEAN,NULL,Male,African-American,10/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +13383,68105,61745,PRETRIAL,LOGATTI,MARCO,ANTONIO,Male,Hispanic,11/15/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +13383,68105,61745,PRETRIAL,LOGATTI,MARCO,ANTONIO,Male,Hispanic,11/15/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +13383,68105,61745,PRETRIAL,LOGATTI,MARCO,ANTONIO,Male,Hispanic,11/15/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59426,68114,61754,PRETRIAL,Miller,Tiffany,Denise,Female,Caucasian,03/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +59426,68114,61754,PRETRIAL,Miller,Tiffany,Denise,Female,Caucasian,03/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +59426,68114,61754,PRETRIAL,Miller,Tiffany,Denise,Female,Caucasian,03/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59419,68107,61747,Probation,major,daniel,NULL,Male,African-American,01/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +59419,68107,61747,Probation,major,daniel,NULL,Male,African-American,01/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +59419,68107,61747,Probation,major,daniel,NULL,Male,African-American,01/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59425,68112,61752,PRETRIAL,Allen,Thajuana,NULL,Female,African-American,05/25/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +59425,68112,61752,PRETRIAL,Allen,Thajuana,NULL,Female,African-American,05/25/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,New,1,0 +59425,68112,61752,PRETRIAL,Allen,Thajuana,NULL,Female,African-American,05/25/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59403,68086,61729,PRETRIAL,DELIONS,MELINDA,JANE,Female,African-American,12/05/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +59403,68086,61729,PRETRIAL,DELIONS,MELINDA,JANE,Female,African-American,12/05/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +59403,68086,61729,PRETRIAL,DELIONS,MELINDA,JANE,Female,African-American,12/05/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59432,68120,61760,Probation,Perrier,Justina,NULL,Female,Caucasian,09/26/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +59432,68120,61760,Probation,Perrier,Justina,NULL,Female,Caucasian,09/26/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +59432,68120,61760,Probation,Perrier,Justina,NULL,Female,Caucasian,09/26/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +7942,68104,7524,PRETRIAL,GOMEZ,JASON,NULL,Male,Caucasian,10/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,Copy,1,0 +7942,68104,7524,PRETRIAL,GOMEZ,JASON,NULL,Male,Caucasian,10/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,Copy,1,0 +7942,68104,7524,PRETRIAL,GOMEZ,JASON,NULL,Male,Caucasian,10/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +59427,68115,61755,PRETRIAL,MANNING,ERIK,NULL,Male,Caucasian,12/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +59427,68115,61755,PRETRIAL,MANNING,ERIK,NULL,Male,Caucasian,12/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +59427,68115,61755,PRETRIAL,MANNING,ERIK,NULL,Male,Caucasian,12/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59436,68125,61765,Probation,ESQUENAZI,MICHELLE,NULL,Female,Hispanic,04/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +59436,68125,61765,Probation,ESQUENAZI,MICHELLE,NULL,Female,Hispanic,04/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +59436,68125,61765,Probation,ESQUENAZI,MICHELLE,NULL,Female,Hispanic,04/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +51415,68102,61743,PRETRIAL,Hamilton,Alfonso,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +51415,68102,61743,PRETRIAL,Hamilton,Alfonso,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +51415,68102,61743,PRETRIAL,Hamilton,Alfonso,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59429,68117,61757,PRETRIAL,MUHAMMED,JODDER,SHAHARIAR,Male,Caucasian,01/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/5/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +59429,68117,61757,PRETRIAL,MUHAMMED,JODDER,SHAHARIAR,Male,Caucasian,01/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +59429,68117,61757,PRETRIAL,MUHAMMED,JODDER,SHAHARIAR,Male,Caucasian,01/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59406,68089,61732,PRETRIAL,BROWN,BENJAMIN,NULL,Male,African-American,10/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +59406,68089,61732,PRETRIAL,BROWN,BENJAMIN,NULL,Male,African-American,10/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +59406,68089,61732,PRETRIAL,BROWN,BENJAMIN,NULL,Male,African-American,10/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59412,68096,61738,PRETRIAL,Lupo,Anthony,NULL,Male,Caucasian,07/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +59412,68096,61738,PRETRIAL,Lupo,Anthony,NULL,Male,Caucasian,07/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +59412,68096,61738,PRETRIAL,Lupo,Anthony,NULL,Male,Caucasian,07/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59441,68130,61770,Probation,Goodwin,Alvin,Lewis,Male,African-American,07/18/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/5/13 0:00,2,Medium,7,Risk of Violence,-2.65,2,Low,New,1,0 +59441,68130,61770,Probation,Goodwin,Alvin,Lewis,Male,African-American,07/18/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +59441,68130,61770,Probation,Goodwin,Alvin,Lewis,Male,African-American,07/18/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/5/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59405,68088,61731,PRETRIAL,Ortiz,Raymond,NULL,Male,Caucasian,03/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/5/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +59405,68088,61731,PRETRIAL,Ortiz,Raymond,NULL,Male,Caucasian,03/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/5/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +59405,68088,61731,PRETRIAL,Ortiz,Raymond,NULL,Male,Caucasian,03/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59442,68131,61771,Probation,CALIXTE,ALAND,NULL,Male,African-American,06/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +59442,68131,61771,Probation,CALIXTE,ALAND,NULL,Male,African-American,06/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +59442,68131,61771,Probation,CALIXTE,ALAND,NULL,Male,African-American,06/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59421,68109,61749,PRETRIAL,Bellidio-Deluna,Alvaro,NULL,Male,Caucasian,05/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +59421,68109,61749,PRETRIAL,Bellidio-Deluna,Alvaro,NULL,Male,Caucasian,05/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +59421,68109,61749,PRETRIAL,Bellidio-Deluna,Alvaro,NULL,Male,Caucasian,05/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59422,68110,61750,PRETRIAL,Ferguson,Regina,NULL,Female,Caucasian,01/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/5/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +59422,68110,61750,PRETRIAL,Ferguson,Regina,NULL,Female,Caucasian,01/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +59422,68110,61750,PRETRIAL,Ferguson,Regina,NULL,Female,Caucasian,01/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59416,68101,61742,Probation,Rodriguez,David,NULL,Male,Hispanic,05/24/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/5/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +59416,68101,61742,Probation,Rodriguez,David,NULL,Male,Hispanic,05/24/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +59416,68101,61742,Probation,Rodriguez,David,NULL,Male,Hispanic,05/24/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59430,68118,61758,PRETRIAL,SHERMAN,CHARLES,DEON,Male,African-American,03/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/5/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +59430,68118,61758,PRETRIAL,SHERMAN,CHARLES,DEON,Male,African-American,03/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +59430,68118,61758,PRETRIAL,SHERMAN,CHARLES,DEON,Male,African-American,03/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59413,68097,61739,Probation,Gondek,Gregg,Douglas,Male,Caucasian,02/07/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +59413,68097,61739,Probation,Gondek,Gregg,Douglas,Male,Caucasian,02/07/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +59413,68097,61739,Probation,Gondek,Gregg,Douglas,Male,Caucasian,02/07/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +19089,68122,61762,PRETRIAL,MENDEZ,RAUL,NULL,Male,Caucasian,10/26/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/5/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +19089,68122,61762,PRETRIAL,MENDEZ,RAUL,NULL,Male,Caucasian,10/26/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/5/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +19089,68122,61762,PRETRIAL,MENDEZ,RAUL,NULL,Male,Caucasian,10/26/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +20209,21076,19431,PRETRIAL,MONTGOMERY,BRANDON,NULL,Male,African-American,05/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/5/13 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +20209,21076,19431,PRETRIAL,MONTGOMERY,BRANDON,NULL,Male,African-American,05/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/5/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +20209,21076,19431,PRETRIAL,MONTGOMERY,BRANDON,NULL,Male,African-American,05/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/5/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58388,68092,60616,PRETRIAL,Cooper,Martez,keith,Male,African-American,05/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,Copy,1,0 +58388,68092,60616,PRETRIAL,Cooper,Martez,keith,Male,African-American,05/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,Copy,1,0 +58388,68092,60616,PRETRIAL,Cooper,Martez,keith,Male,African-American,05/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +59438,68127,61767,Probation,Spence,Camile,NULL,Female,African-American,10/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +59438,68127,61767,Probation,Spence,Camile,NULL,Female,African-American,10/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +59438,68127,61767,Probation,Spence,Camile,NULL,Female,African-American,10/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59418,68106,61746,Probation,norman,joseph,NULL,Male,Caucasian,03/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +59418,68106,61746,Probation,norman,joseph,NULL,Male,Caucasian,03/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +59418,68106,61746,Probation,norman,joseph,NULL,Male,Caucasian,03/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59424,68113,61753,PRETRIAL,Paisley,Kerome,NULL,Male,African-American,07/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +59424,68113,61753,PRETRIAL,Paisley,Kerome,NULL,Male,African-American,07/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.74,10,High,New,1,0 +59424,68113,61753,PRETRIAL,Paisley,Kerome,NULL,Male,African-American,07/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59400,68083,61726,PRETRIAL,Serrano,Xavier,NULL,Male,Caucasian,09/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +59400,68083,61726,PRETRIAL,Serrano,Xavier,NULL,Male,Caucasian,09/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +59400,68083,61726,PRETRIAL,Serrano,Xavier,NULL,Male,Caucasian,09/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59402,68085,61728,PRETRIAL,Felder,James,NULL,Male,African-American,08/11/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +59402,68085,61728,PRETRIAL,Felder,James,NULL,Male,African-American,08/11/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +59402,68085,61728,PRETRIAL,Felder,James,NULL,Male,African-American,08/11/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59446,68134,61774,PRETRIAL,Charlton,Zachary,NULL,Male,Caucasian,02/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +59446,68134,61774,PRETRIAL,Charlton,Zachary,NULL,Male,Caucasian,02/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +59446,68134,61774,PRETRIAL,Charlton,Zachary,NULL,Male,Caucasian,02/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59448,68136,61776,PRETRIAL,Gray,Vinessa,NULL,Male,African-American,10/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +59448,68136,61776,PRETRIAL,Gray,Vinessa,NULL,Male,African-American,10/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +59448,68136,61776,PRETRIAL,Gray,Vinessa,NULL,Male,African-American,10/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +27148,68155,61789,PRETRIAL,Lopez,Caelos,NULL,Male,Caucasian,07/01/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/6/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +27148,68155,61789,PRETRIAL,Lopez,Caelos,NULL,Male,Caucasian,07/01/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/6/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +27148,68155,61789,PRETRIAL,Lopez,Caelos,NULL,Male,Caucasian,07/01/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59459,68157,61791,PRETRIAL,GOTIEAR,TONY,MAURICE,Male,African-American,06/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +59459,68157,61791,PRETRIAL,GOTIEAR,TONY,MAURICE,Male,African-American,06/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +59459,68157,61791,PRETRIAL,GOTIEAR,TONY,MAURICE,Male,African-American,06/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59461,68162,61796,PRETRIAL,Sullivan,ROBERTO,NULL,Male,Caucasian,02/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2,4,Low,New,1,0 +59461,68162,61796,PRETRIAL,Sullivan,ROBERTO,NULL,Male,Caucasian,02/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +59461,68162,61796,PRETRIAL,Sullivan,ROBERTO,NULL,Male,Caucasian,02/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +28633,68164,27678,Probation,Jean,Wiky,NULL,Male,African-American,06/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,Copy,1,0 +28633,68164,27678,Probation,Jean,Wiky,NULL,Male,African-American,06/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,Copy,1,0 +28633,68164,27678,Probation,Jean,Wiky,NULL,Male,African-American,06/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +45149,68143,61782,Probation,fonseca,HUMBERTO,NULL,Male,Hispanic,06/22/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +45149,68143,61782,Probation,fonseca,HUMBERTO,NULL,Male,Hispanic,06/22/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +45149,68143,61782,Probation,fonseca,HUMBERTO,NULL,Male,Hispanic,06/22/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51399,68152,61788,PRETRIAL,McManus,Kevin,NULL,Male,Caucasian,08/03/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +51399,68152,61788,PRETRIAL,McManus,Kevin,NULL,Male,Caucasian,08/03/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +51399,68152,61788,PRETRIAL,McManus,Kevin,NULL,Male,Caucasian,08/03/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +59467,68169,61802,PRETRIAL,Jason,Altron,NULL,Male,African-American,08/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +59467,68169,61802,PRETRIAL,Jason,Altron,NULL,Male,African-American,08/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +59467,68169,61802,PRETRIAL,Jason,Altron,NULL,Male,African-American,08/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59451,68139,61779,PRETRIAL,Zorilla,Juan,NULL,Male,Hispanic,06/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +59451,68139,61779,PRETRIAL,Zorilla,Juan,NULL,Male,Hispanic,06/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +59451,68139,61779,PRETRIAL,Zorilla,Juan,NULL,Male,Hispanic,06/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +34487,68148,33648,PRETRIAL,JOHNSON,ISAAC,LEE,Male,African-American,02/11/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,Copy,1,0 +34487,68148,33648,PRETRIAL,JOHNSON,ISAAC,LEE,Male,African-American,02/11/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,Copy,1,0 +34487,68148,33648,PRETRIAL,JOHNSON,ISAAC,LEE,Male,African-American,02/11/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +59469,68173,61804,PRETRIAL,Baptiste-Gilmore,Cecelia,NULL,Female,Caucasian,04/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/6/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +59469,68173,61804,PRETRIAL,Baptiste-Gilmore,Cecelia,NULL,Female,Caucasian,04/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/6/13 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +59469,68173,61804,PRETRIAL,Baptiste-Gilmore,Cecelia,NULL,Female,Caucasian,04/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59460,68159,61793,PRETRIAL,HATCHER,LEON,AJ,Male,African-American,03/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +59460,68159,61793,PRETRIAL,HATCHER,LEON,AJ,Male,African-American,03/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +59460,68159,61793,PRETRIAL,HATCHER,LEON,AJ,Male,African-American,03/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59450,68138,61778,PRETRIAL,Bonner,Matthew,NULL,Male,Caucasian,11/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +59450,68138,61778,PRETRIAL,Bonner,Matthew,NULL,Male,Caucasian,11/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,2,Medium,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +59450,68138,61778,PRETRIAL,Bonner,Matthew,NULL,Male,Caucasian,11/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59457,68151,61787,Probation,Almeida,Pedro,NULL,Male,Hispanic,03/05/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/6/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +59457,68151,61787,Probation,Almeida,Pedro,NULL,Male,Hispanic,03/05/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/6/13 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +59457,68151,61787,Probation,Almeida,Pedro,NULL,Male,Hispanic,03/05/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +33563,68154,32666,PRETRIAL,NICOLETTI,RENZO,NULL,Male,Caucasian,06/15/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +33563,68154,32666,PRETRIAL,NICOLETTI,RENZO,NULL,Male,Caucasian,06/15/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +33563,68154,32666,PRETRIAL,NICOLETTI,RENZO,NULL,Male,Caucasian,06/15/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +42317,68172,42133,PRETRIAL,WHYTE,FANNIE,NULL,Female,Caucasian,06/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,2,Medium,7,Risk of Violence,-2.94,2,Low,Copy,1,0 +42317,68172,42133,PRETRIAL,WHYTE,FANNIE,NULL,Female,Caucasian,06/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,Copy,1,0 +42317,68172,42133,PRETRIAL,WHYTE,FANNIE,NULL,Female,Caucasian,06/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +59445,68133,61773,PRETRIAL,Hardy,Stephanie,NULL,Female,African-American,07/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/6/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +59445,68133,61773,PRETRIAL,Hardy,Stephanie,NULL,Female,African-American,07/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/6/13 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +59445,68133,61773,PRETRIAL,Hardy,Stephanie,NULL,Female,African-American,07/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59465,68167,61800,PRETRIAL,JEAN,PATRICK,NULL,Male,African-American,04/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +59465,68167,61800,PRETRIAL,JEAN,PATRICK,NULL,Male,African-American,04/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.87,10,High,New,1,0 +59465,68167,61800,PRETRIAL,JEAN,PATRICK,NULL,Male,African-American,04/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +48049,68146,61783,PRETRIAL,Ozbeyler,Mahmut,NULL,Male,Caucasian,07/15/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/6/13 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +48049,68146,61783,PRETRIAL,Ozbeyler,Mahmut,NULL,Male,Caucasian,07/15/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/6/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +48049,68146,61783,PRETRIAL,Ozbeyler,Mahmut,NULL,Male,Caucasian,07/15/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59447,68135,61775,PRETRIAL,Sosa,Yajaira,NULL,Female,Caucasian,08/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +59447,68135,61775,PRETRIAL,Sosa,Yajaira,NULL,Female,Caucasian,08/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +59447,68135,61775,PRETRIAL,Sosa,Yajaira,NULL,Female,Caucasian,08/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +32312,68144,58678,PRETRIAL,LEWIS,LAVONTE,NULL,Male,African-American,12/16/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +32312,68144,58678,PRETRIAL,LEWIS,LAVONTE,NULL,Male,African-American,12/16/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +32312,68144,58678,PRETRIAL,LEWIS,LAVONTE,NULL,Male,African-American,12/16/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,4,High,18,Risk of Failure to Appear,18,2,Low,New,1,0 +50457,68161,61795,Probation,CASIGLIO,MICHAEL,DAVID,Male,Caucasian,05/03/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +50457,68161,61795,Probation,CASIGLIO,MICHAEL,DAVID,Male,Caucasian,05/03/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +50457,68161,61795,Probation,CASIGLIO,MICHAEL,DAVID,Male,Caucasian,05/03/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59452,68140,61780,PRETRIAL,Maynard,Christopher,NULL,Male,Caucasian,08/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/6/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +59452,68140,61780,PRETRIAL,Maynard,Christopher,NULL,Male,Caucasian,08/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/6/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +59452,68140,61780,PRETRIAL,Maynard,Christopher,NULL,Male,Caucasian,08/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59454,68147,61784,Probation,Samuels,Vernal,NULL,Male,African-American,09/30/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.52,3,Low,New,1,0 +59454,68147,61784,Probation,Samuels,Vernal,NULL,Male,African-American,09/30/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +59454,68147,61784,Probation,Samuels,Vernal,NULL,Male,African-American,09/30/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59463,68165,61798,Probation,Holguin,Yaira,NULL,Female,Hispanic,10/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +59463,68165,61798,Probation,Holguin,Yaira,NULL,Female,Hispanic,10/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +59463,68165,61798,Probation,Holguin,Yaira,NULL,Female,Hispanic,10/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59455,68149,61785,PRETRIAL,Rasbin,Reginald,NULL,Male,African-American,02/17/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,12/6/13 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +59455,68149,61785,PRETRIAL,Rasbin,Reginald,NULL,Male,African-American,02/17/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,12/6/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +59455,68149,61785,PRETRIAL,Rasbin,Reginald,NULL,Male,African-American,02/17/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +59458,68156,61790,Probation,Acevedo,Jonathan,NULL,Male,Hispanic,03/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +59458,68156,61790,Probation,Acevedo,Jonathan,NULL,Male,Hispanic,03/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +59458,68156,61790,Probation,Acevedo,Jonathan,NULL,Male,Hispanic,03/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +59462,68163,61797,Probation,LOLL,MICHAEL,S,Male,Caucasian,10/24/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +59462,68163,61797,Probation,LOLL,MICHAEL,S,Male,Caucasian,10/24/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +59462,68163,61797,Probation,LOLL,MICHAEL,S,Male,Caucasian,10/24/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +59453,68142,61781,PRETRIAL,WIMBERLY,OTIS,NULL,Male,African-American,03/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +59453,68142,61781,PRETRIAL,WIMBERLY,OTIS,NULL,Male,African-American,03/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +59453,68142,61781,PRETRIAL,WIMBERLY,OTIS,NULL,Male,African-American,03/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56406,68153,58380,PRETRIAL,Bynes,Christopher,NULL,Male,African-American,08/07/77,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,4,High,7,Risk of Violence,-0.68,9,High,New,1,0 +56406,68153,58380,PRETRIAL,Bynes,Christopher,NULL,Male,African-American,08/07/77,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +56406,68153,58380,PRETRIAL,Bynes,Christopher,NULL,Male,African-American,08/07/77,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,4,High,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +59464,68166,61799,PRETRIAL,NELSON,CYNTHIA,NULL,Female,Caucasian,08/30/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +59464,68166,61799,PRETRIAL,NELSON,CYNTHIA,NULL,Female,Caucasian,08/30/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +59464,68166,61799,PRETRIAL,NELSON,CYNTHIA,NULL,Female,Caucasian,08/30/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59466,68168,61801,PRETRIAL,Bloodsaw,Matthew,NULL,Male,African-American,10/01/89,17,All Scales,Intake,English,Post Sentence,Probation,Married,12/6/13 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +59466,68168,61801,PRETRIAL,Bloodsaw,Matthew,NULL,Male,African-American,10/01/89,17,All Scales,Intake,English,Post Sentence,Probation,Married,12/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +59466,68168,61801,PRETRIAL,Bloodsaw,Matthew,NULL,Male,African-American,10/01/89,17,All Scales,Intake,English,Post Sentence,Probation,Married,12/6/13 0:00,2,Medium,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +48433,68145,55298,PRETRIAL,Stewart,Christopher,NULL,Male,African-American,09/21/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,Copy,1,0 +48433,68145,55298,PRETRIAL,Stewart,Christopher,NULL,Male,African-American,09/21/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,Copy,1,0 +48433,68145,55298,PRETRIAL,Stewart,Christopher,NULL,Male,African-American,09/21/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +6363,68160,61794,PRETRIAL,RIERA,DANNY,NMN,Male,Hispanic,08/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/6/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +6363,68160,61794,PRETRIAL,RIERA,DANNY,NMN,Male,Hispanic,08/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/6/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +6363,68160,61794,PRETRIAL,RIERA,DANNY,NMN,Male,Hispanic,08/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/6/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +52029,68158,61792,PRETRIAL,Baldocchi,Albert,NULL,Male,Caucasian,01/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +52029,68158,61792,PRETRIAL,Baldocchi,Albert,NULL,Male,Caucasian,01/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +52029,68158,61792,PRETRIAL,Baldocchi,Albert,NULL,Male,Caucasian,01/11/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59456,68150,61786,PRETRIAL,Blake,Harriet,Sarah,Female,Caucasian,04/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +59456,68150,61786,PRETRIAL,Blake,Harriet,Sarah,Female,Caucasian,04/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +59456,68150,61786,PRETRIAL,Blake,Harriet,Sarah,Female,Caucasian,04/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59449,68137,61777,PRETRIAL,Barnes,Sean,NULL,Male,Caucasian,08/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/6/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +59449,68137,61777,PRETRIAL,Barnes,Sean,NULL,Male,Caucasian,08/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/6/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +59449,68137,61777,PRETRIAL,Barnes,Sean,NULL,Male,Caucasian,08/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/6/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59468,68171,61803,PRETRIAL,ORTON,STEVEN,H,Male,Caucasian,02/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +59468,68171,61803,PRETRIAL,ORTON,STEVEN,H,Male,Caucasian,02/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,4,High,8,Risk of Recidivism,0.67,10,High,New,1,0 +59468,68171,61803,PRETRIAL,ORTON,STEVEN,H,Male,Caucasian,02/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/13 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +59478,68184,61815,PRETRIAL,LLerena,Jose,NULL,Male,Hispanic,09/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +59478,68184,61815,PRETRIAL,LLerena,Jose,NULL,Male,Hispanic,09/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +59478,68184,61815,PRETRIAL,LLerena,Jose,NULL,Male,Hispanic,09/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59471,68176,61807,PRETRIAL,Aponte,Christophe,NULL,Male,Hispanic,08/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +59471,68176,61807,PRETRIAL,Aponte,Christophe,NULL,Male,Hispanic,08/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +59471,68176,61807,PRETRIAL,Aponte,Christophe,NULL,Male,Hispanic,08/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59474,68179,61810,PRETRIAL,Vilcant,Wisler,NULL,Male,Other,08/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +59474,68179,61810,PRETRIAL,Vilcant,Wisler,NULL,Male,Other,08/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +59474,68179,61810,PRETRIAL,Vilcant,Wisler,NULL,Male,Other,08/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +45429,68174,61805,PRETRIAL,Reddie,Colin,NULL,Male,African-American,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +45429,68174,61805,PRETRIAL,Reddie,Colin,NULL,Male,African-American,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +45429,68174,61805,PRETRIAL,Reddie,Colin,NULL,Male,African-American,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +44233,68181,61812,PRETRIAL,Simon,Onel,NULL,Male,African-American,06/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +44233,68181,61812,PRETRIAL,Simon,Onel,NULL,Male,African-American,06/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +44233,68181,61812,PRETRIAL,Simon,Onel,NULL,Male,African-American,06/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +59481,68187,61818,PRETRIAL,Newbold,Donovan,L,Male,Other,11/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +59481,68187,61818,PRETRIAL,Newbold,Donovan,L,Male,Other,11/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +59481,68187,61818,PRETRIAL,Newbold,Donovan,L,Male,Other,11/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59483,68189,61820,PRETRIAL,HYPPOLITE,JONADIA,NULL,Female,African-American,11/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +59483,68189,61820,PRETRIAL,HYPPOLITE,JONADIA,NULL,Female,African-American,11/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +59483,68189,61820,PRETRIAL,HYPPOLITE,JONADIA,NULL,Female,African-American,11/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59472,68177,61808,PRETRIAL,Georges,Annonce,NULL,Male,Other,11/11/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +59472,68177,61808,PRETRIAL,Georges,Annonce,NULL,Male,Other,11/11/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +59472,68177,61808,PRETRIAL,Georges,Annonce,NULL,Male,Other,11/11/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59485,68191,61822,PRETRIAL,Carr,Tichina,artaavia,Female,African-American,07/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +59485,68191,61822,PRETRIAL,Carr,Tichina,artaavia,Female,African-American,07/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +59485,68191,61822,PRETRIAL,Carr,Tichina,artaavia,Female,African-American,07/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59480,68186,61817,PRETRIAL,Alexander,Romero,Joseph,Male,Other,03/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +59480,68186,61817,PRETRIAL,Alexander,Romero,Joseph,Male,Other,03/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +59480,68186,61817,PRETRIAL,Alexander,Romero,Joseph,Male,Other,03/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59476,68182,61813,PRETRIAL,AVERY,CAMERON,WHITNEY,Male,African-American,07/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +59476,68182,61813,PRETRIAL,AVERY,CAMERON,WHITNEY,Male,African-American,07/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +59476,68182,61813,PRETRIAL,AVERY,CAMERON,WHITNEY,Male,African-American,07/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59475,68180,61811,PRETRIAL,BRUNDAGE,BRUCE,LAROSE,Male,African-American,06/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +59475,68180,61811,PRETRIAL,BRUNDAGE,BRUCE,LAROSE,Male,African-American,06/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +59475,68180,61811,PRETRIAL,BRUNDAGE,BRUCE,LAROSE,Male,African-American,06/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +59470,68175,61806,PRETRIAL,Arenas,William,NULL,Male,Hispanic,09/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +59470,68175,61806,PRETRIAL,Arenas,William,NULL,Male,Hispanic,09/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +59470,68175,61806,PRETRIAL,Arenas,William,NULL,Male,Hispanic,09/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59482,68188,61819,PRETRIAL,Rogers,James,NULL,Male,African-American,12/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +59482,68188,61819,PRETRIAL,Rogers,James,NULL,Male,African-American,12/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +59482,68188,61819,PRETRIAL,Rogers,James,NULL,Male,African-American,12/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59484,68190,61821,PRETRIAL,Mincey,Lawrence,NULL,Male,African-American,08/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +59484,68190,61821,PRETRIAL,Mincey,Lawrence,NULL,Male,African-American,08/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +59484,68190,61821,PRETRIAL,Mincey,Lawrence,NULL,Male,African-American,08/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59477,68183,61814,PRETRIAL,Brien,Ginge,NULL,Male,Caucasian,06/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +59477,68183,61814,PRETRIAL,Brien,Ginge,NULL,Male,Caucasian,06/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/13 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +59477,68183,61814,PRETRIAL,Brien,Ginge,NULL,Male,Caucasian,06/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59479,68185,61816,PRETRIAL,BRUSCHETTI,JAMES,NULL,Male,Caucasian,01/21/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/7/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +59479,68185,61816,PRETRIAL,BRUSCHETTI,JAMES,NULL,Male,Caucasian,01/21/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/7/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +59479,68185,61816,PRETRIAL,BRUSCHETTI,JAMES,NULL,Male,Caucasian,01/21/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/7/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59473,68178,61809,PRETRIAL,George,Dywanda,NULL,Female,African-American,11/25/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +59473,68178,61809,PRETRIAL,George,Dywanda,NULL,Female,African-American,11/25/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,9,High,New,1,0 +59473,68178,61809,PRETRIAL,George,Dywanda,NULL,Female,African-American,11/25/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59486,68192,61823,PRETRIAL,PRICE,DANIEL,NULL,Male,Caucasian,07/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +59486,68192,61823,PRETRIAL,PRICE,DANIEL,NULL,Male,Caucasian,07/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +59486,68192,61823,PRETRIAL,PRICE,DANIEL,NULL,Male,Caucasian,07/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59492,68199,61828,PRETRIAL,Walker,Chasidy,NULL,Female,African-American,05/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +59492,68199,61828,PRETRIAL,Walker,Chasidy,NULL,Female,African-American,05/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +59492,68199,61828,PRETRIAL,Walker,Chasidy,NULL,Female,African-American,05/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +7342,68194,61825,PRETRIAL,LAPAIX,JAMES,NULL,Male,African-American,10/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/8/13 0:00,4,High,7,Risk of Violence,-0.57,10,High,New,1,0 +7342,68194,61825,PRETRIAL,LAPAIX,JAMES,NULL,Male,African-American,10/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/8/13 0:00,4,High,8,Risk of Recidivism,0.65,10,High,New,1,0 +7342,68194,61825,PRETRIAL,LAPAIX,JAMES,NULL,Male,African-American,10/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/8/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +51225,68196,52391,PRETRIAL,Lewis,Shavoria,NULL,Female,African-American,07/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,Copy,1,0 +51225,68196,52391,PRETRIAL,Lewis,Shavoria,NULL,Female,African-American,07/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,Copy,1,0 +51225,68196,52391,PRETRIAL,Lewis,Shavoria,NULL,Female,African-American,07/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +59487,68193,61824,PRETRIAL,kelly,Kelsian,NULL,Male,African-American,02/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.48,3,Low,New,1,0 +59487,68193,61824,PRETRIAL,kelly,Kelsian,NULL,Male,African-American,02/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +59487,68193,61824,PRETRIAL,kelly,Kelsian,NULL,Male,African-American,02/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +59489,68198,61827,PRETRIAL,ALI,ANTHONY,NULL,Male,Caucasian,04/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +59489,68198,61827,PRETRIAL,ALI,ANTHONY,NULL,Male,Caucasian,04/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +59489,68198,61827,PRETRIAL,ALI,ANTHONY,NULL,Male,Caucasian,04/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59491,68200,61829,PRETRIAL,MERSIER,FRANTZ,NULL,Male,Caucasian,06/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +59491,68200,61829,PRETRIAL,MERSIER,FRANTZ,NULL,Male,Caucasian,06/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +59491,68200,61829,PRETRIAL,MERSIER,FRANTZ,NULL,Male,Caucasian,06/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59490,68197,61826,PRETRIAL,DANIELS,NATASHA,MERCEDES,Female,African-American,07/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +59490,68197,61826,PRETRIAL,DANIELS,NATASHA,MERCEDES,Female,African-American,07/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +59490,68197,61826,PRETRIAL,DANIELS,NATASHA,MERCEDES,Female,African-American,07/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59514,68226,61854,Probation,Jensen,Greg,NULL,Male,Caucasian,07/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +59514,68226,61854,Probation,Jensen,Greg,NULL,Male,Caucasian,07/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +59514,68226,61854,Probation,Jensen,Greg,NULL,Male,Caucasian,07/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59526,68244,61871,Probation,bradshaw,michael,NULL,Male,Caucasian,06/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +59526,68244,61871,Probation,bradshaw,michael,NULL,Male,Caucasian,06/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +59526,68244,61871,Probation,bradshaw,michael,NULL,Male,Caucasian,06/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59496,68205,61834,PRETRIAL,Blackburn,Darrell,Anthony,Male,Caucasian,11/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +59496,68205,61834,PRETRIAL,Blackburn,Darrell,Anthony,Male,Caucasian,11/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +59496,68205,61834,PRETRIAL,Blackburn,Darrell,Anthony,Male,Caucasian,11/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58369,68239,60596,Probation,smith,clifford,NULL,Male,African-American,10/24/72,17,All Scales,Intake,English,Conditional Release,Probation,Single,12/9/13 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +58369,68239,60596,Probation,smith,clifford,NULL,Male,African-American,10/24/72,17,All Scales,Intake,English,Conditional Release,Probation,Single,12/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,6,Medium,New,1,0 +58369,68239,60596,Probation,smith,clifford,NULL,Male,African-American,10/24/72,17,All Scales,Intake,English,Conditional Release,Probation,Single,12/9/13 0:00,2,Medium,18,Risk of Failure to Appear,22,4,Low,New,1,0 +59511,68223,61851,PRETRIAL,Heim,Daniel,NULL,Male,Caucasian,10/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +59511,68223,61851,PRETRIAL,Heim,Daniel,NULL,Male,Caucasian,10/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +59511,68223,61851,PRETRIAL,Heim,Daniel,NULL,Male,Caucasian,10/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59517,68231,61859,Probation,Drinkwine,Cory,NULL,Male,Caucasian,12/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +59517,68231,61859,Probation,Drinkwine,Cory,NULL,Male,Caucasian,12/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +59517,68231,61859,Probation,Drinkwine,Cory,NULL,Male,Caucasian,12/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59500,68210,61839,PRETRIAL,Deus,Moriach,NULL,Male,African-American,08/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +59500,68210,61839,PRETRIAL,Deus,Moriach,NULL,Male,African-American,08/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +59500,68210,61839,PRETRIAL,Deus,Moriach,NULL,Male,African-American,08/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59507,68219,61847,PRETRIAL,Carr,Ryan,NULL,Male,Caucasian,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +59507,68219,61847,PRETRIAL,Carr,Ryan,NULL,Male,Caucasian,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +59507,68219,61847,PRETRIAL,Carr,Ryan,NULL,Male,Caucasian,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59509,68221,61849,Probation,Tippett,Christopher,NULL,Male,Caucasian,07/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +59509,68221,61849,Probation,Tippett,Christopher,NULL,Male,Caucasian,07/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +59509,68221,61849,Probation,Tippett,Christopher,NULL,Male,Caucasian,07/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +45759,68228,61856,PRETRIAL,Archer,Susan,Rose,Female,African-American,09/24/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/9/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +45759,68228,61856,PRETRIAL,Archer,Susan,Rose,Female,African-American,09/24/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +45759,68228,61856,PRETRIAL,Archer,Susan,Rose,Female,African-American,09/24/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59524,68242,61869,Probation,Sajdak,Rachel,NULL,Female,Caucasian,12/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +59524,68242,61869,Probation,Sajdak,Rachel,NULL,Female,Caucasian,12/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +59524,68242,61869,Probation,Sajdak,Rachel,NULL,Female,Caucasian,12/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59498,68207,61836,PRETRIAL,HULLANDER,AARON,NULL,Male,Caucasian,02/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/9/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +59498,68207,61836,PRETRIAL,HULLANDER,AARON,NULL,Male,Caucasian,02/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +59498,68207,61836,PRETRIAL,HULLANDER,AARON,NULL,Male,Caucasian,02/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51639,68212,61841,Probation,Herrington,Levert,NULL,Male,African-American,01/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,2,Medium,7,Risk of Violence,-3.2,1,Low,New,1,0 +51639,68212,61841,Probation,Herrington,Levert,NULL,Male,African-American,01/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +51639,68212,61841,Probation,Herrington,Levert,NULL,Male,African-American,01/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +59495,68203,61832,PRETRIAL,Barnes,Patria,Theresa,Female,Other,06/06/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +59495,68203,61832,PRETRIAL,Barnes,Patria,Theresa,Female,Other,06/06/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +59495,68203,61832,PRETRIAL,Barnes,Patria,Theresa,Female,Other,06/06/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +34636,68233,61861,PRETRIAL,polakoff,joshua,k,Male,African-American,12/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +34636,68233,61861,PRETRIAL,polakoff,joshua,k,Male,African-American,12/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,4,High,8,Risk of Recidivism,1.1,10,High,New,1,0 +34636,68233,61861,PRETRIAL,polakoff,joshua,k,Male,African-American,12/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52333,68237,61865,PRETRIAL,Dawson,Demarquize,NULL,Male,African-American,11/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +52333,68237,61865,PRETRIAL,Dawson,Demarquize,NULL,Male,African-American,11/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +52333,68237,61865,PRETRIAL,Dawson,Demarquize,NULL,Male,African-American,11/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +59525,68243,61870,Probation,Guan,Xia,NULL,Female,Oriental,05/30/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +59525,68243,61870,Probation,Guan,Xia,NULL,Female,Oriental,05/30/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +59525,68243,61870,Probation,Guan,Xia,NULL,Female,Oriental,05/30/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +18119,68240,61867,Probation,Campbell,Joey,Scott,Male,Caucasian,08/16/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +18119,68240,61867,Probation,Campbell,Joey,Scott,Male,Caucasian,08/16/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +18119,68240,61867,Probation,Campbell,Joey,Scott,Male,Caucasian,08/16/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59503,68214,61843,Probation,Ritter,Michael,NULL,Male,African-American,10/31/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +59503,68214,61843,Probation,Ritter,Michael,NULL,Male,African-American,10/31/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +59503,68214,61843,Probation,Ritter,Michael,NULL,Male,African-American,10/31/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59493,68201,61830,PRETRIAL,BROOKS,THERESA,RENEE,Female,Caucasian,01/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +59493,68201,61830,PRETRIAL,BROOKS,THERESA,RENEE,Female,Caucasian,01/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +59493,68201,61830,PRETRIAL,BROOKS,THERESA,RENEE,Female,Caucasian,01/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +38137,68230,61858,PRETRIAL,SACHTOURAS,ILIAS,NULL,Male,Caucasian,09/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/9/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +38137,68230,61858,PRETRIAL,SACHTOURAS,ILIAS,NULL,Male,Caucasian,09/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +38137,68230,61858,PRETRIAL,SACHTOURAS,ILIAS,NULL,Male,Caucasian,09/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59518,68232,61860,Probation,sainmelus,alnorius,NULL,Male,African-American,12/15/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/9/13 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +59518,68232,61860,Probation,sainmelus,alnorius,NULL,Male,African-American,12/15/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/9/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +59518,68232,61860,Probation,sainmelus,alnorius,NULL,Male,African-American,12/15/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59505,68217,61845,Probation,Regulus,christian,NULL,Male,African-American,04/13/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/9/13 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +59505,68217,61845,Probation,Regulus,christian,NULL,Male,African-American,04/13/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +59505,68217,61845,Probation,Regulus,christian,NULL,Male,African-American,04/13/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/9/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59513,68224,61852,Probation,Barkley,Richard,NULL,Male,Caucasian,06/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +59513,68224,61852,Probation,Barkley,Richard,NULL,Male,Caucasian,06/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +59513,68224,61852,Probation,Barkley,Richard,NULL,Male,Caucasian,06/25/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59522,68238,61866,PRETRIAL,POSEY,CHANDRA,NULL,Female,African-American,11/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,New,1,0 +59522,68238,61866,PRETRIAL,POSEY,CHANDRA,NULL,Female,African-American,11/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,7,Medium,New,1,0 +59522,68238,61866,PRETRIAL,POSEY,CHANDRA,NULL,Female,African-American,11/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +7601,68209,61838,PRETRIAL,HARRIS,KENNETH,J,Male,Caucasian,03/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,4,High,7,Risk of Violence,-1.05,8,High,New,1,0 +7601,68209,61838,PRETRIAL,HARRIS,KENNETH,J,Male,Caucasian,03/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,4,High,8,Risk of Recidivism,0.17,8,High,New,1,0 +7601,68209,61838,PRETRIAL,HARRIS,KENNETH,J,Male,Caucasian,03/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59527,68245,61872,PRETRIAL,SINCLAIR,RICARDO,NULL,Male,African-American,12/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +59527,68245,61872,PRETRIAL,SINCLAIR,RICARDO,NULL,Male,African-American,12/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +59527,68245,61872,PRETRIAL,SINCLAIR,RICARDO,NULL,Male,African-American,12/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59499,68208,61837,PRETRIAL,RIVAS,ANTONIO,NULL,Male,Caucasian,07/14/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/9/13 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +59499,68208,61837,PRETRIAL,RIVAS,ANTONIO,NULL,Male,Caucasian,07/14/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/9/13 0:00,1,Low,8,Risk of Recidivism,-2.67,1,Low,New,1,0 +59499,68208,61837,PRETRIAL,RIVAS,ANTONIO,NULL,Male,Caucasian,07/14/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59501,68211,61840,Probation,Brown,Al,NULL,Male,African-American,10/04/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +59501,68211,61840,Probation,Brown,Al,NULL,Male,African-American,10/04/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +59501,68211,61840,Probation,Brown,Al,NULL,Male,African-American,10/04/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59512,68225,61853,PRETRIAL,Holness,Kaeron,Ricardo,Male,Other,10/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +59512,68225,61853,PRETRIAL,Holness,Kaeron,Ricardo,Male,Other,10/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +59512,68225,61853,PRETRIAL,Holness,Kaeron,Ricardo,Male,Other,10/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59497,68204,61833,PRETRIAL,ARMSTRONG,JUSTIN,NULL,Male,Caucasian,02/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +59497,68204,61833,PRETRIAL,ARMSTRONG,JUSTIN,NULL,Male,Caucasian,02/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +59497,68204,61833,PRETRIAL,ARMSTRONG,JUSTIN,NULL,Male,Caucasian,02/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59504,68215,61844,Probation,Lopezvaxzquez,Antonio,NULL,Male,Hispanic,08/13/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/9/13 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +59504,68215,61844,Probation,Lopezvaxzquez,Antonio,NULL,Male,Hispanic,08/13/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/9/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +59504,68215,61844,Probation,Lopezvaxzquez,Antonio,NULL,Male,Hispanic,08/13/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59516,68229,61857,Probation,mirabile,jean,NULL,Female,Caucasian,10/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/9/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +59516,68229,61857,Probation,mirabile,jean,NULL,Female,Caucasian,10/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +59516,68229,61857,Probation,mirabile,jean,NULL,Female,Caucasian,10/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59523,68241,61868,Probation,demps,shellrick,NULL,Male,African-American,11/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,New,1,0 +59523,68241,61868,Probation,demps,shellrick,NULL,Male,African-American,11/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.89,10,High,New,1,0 +59523,68241,61868,Probation,demps,shellrick,NULL,Male,African-American,11/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +59508,68220,61848,Probation,Brown,James,NULL,Male,African-American,01/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/9/13 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +59508,68220,61848,Probation,Brown,James,NULL,Male,African-American,01/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/9/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +59508,68220,61848,Probation,Brown,James,NULL,Male,African-American,01/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +4074,68206,61835,PRETRIAL,pratt,michael,NULL,Male,African-Am,03/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,4,High,7,Risk of Violence,-1.19,8,High,New,1,0 +4074,68206,61835,PRETRIAL,pratt,michael,NULL,Male,African-Am,03/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,4,High,8,Risk of Recidivism,0.45,9,High,New,1,0 +4074,68206,61835,PRETRIAL,pratt,michael,NULL,Male,African-Am,03/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/13 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59502,68213,61842,PRETRIAL,Miller,Sean,NULL,Male,Caucasian,01/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +59502,68213,61842,PRETRIAL,Miller,Sean,NULL,Male,Caucasian,01/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +59502,68213,61842,PRETRIAL,Miller,Sean,NULL,Male,Caucasian,01/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59515,68227,61855,Probation,Barthelus,Kenley,NULL,Male,African-American,09/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +59515,68227,61855,Probation,Barthelus,Kenley,NULL,Male,African-American,09/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +59515,68227,61855,Probation,Barthelus,Kenley,NULL,Male,African-American,09/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55075,68236,61864,PRETRIAL,POPE,LENARIS,MARQUI,Male,African-American,12/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +55075,68236,61864,PRETRIAL,POPE,LENARIS,MARQUI,Male,African-American,12/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +55075,68236,61864,PRETRIAL,POPE,LENARIS,MARQUI,Male,African-American,12/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/9/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59558,68285,61910,Probation,BUCKELY,PATRICK,NULL,Male,African-American,04/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +59558,68285,61910,Probation,BUCKELY,PATRICK,NULL,Male,African-American,04/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +59558,68285,61910,Probation,BUCKELY,PATRICK,NULL,Male,African-American,04/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +29302,68255,61882,PRETRIAL,Cole,Joseph,NULL,Male,African-American,07/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +29302,68255,61882,PRETRIAL,Cole,Joseph,NULL,Male,African-American,07/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +29302,68255,61882,PRETRIAL,Cole,Joseph,NULL,Male,African-American,07/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,4,High,18,Risk of Failure to Appear,40,10,High,New,1,0 +59537,68257,61884,PRETRIAL,Londono,Jaime,NULL,Male,Caucasian,08/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/10/13 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +59537,68257,61884,PRETRIAL,Londono,Jaime,NULL,Male,Caucasian,08/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/10/13 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +59537,68257,61884,PRETRIAL,Londono,Jaime,NULL,Male,Caucasian,08/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59554,68278,61903,Probation,Beckwer,Melissa,NULL,Female,Hispanic,04/23/80,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,12/10/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +59554,68278,61903,Probation,Beckwer,Melissa,NULL,Female,Hispanic,04/23/80,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +59554,68278,61903,Probation,Beckwer,Melissa,NULL,Female,Hispanic,04/23/80,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49136,68292,61917,PRETRIAL,Potts,Sean,NULL,Male,Caucasian,02/24/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/10/13 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +49136,68292,61917,PRETRIAL,Potts,Sean,NULL,Male,Caucasian,02/24/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +49136,68292,61917,PRETRIAL,Potts,Sean,NULL,Male,Caucasian,02/24/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +38982,56746,50382,PRETRIAL,MAHER,STEPHEN,M,Male,Caucasian,09/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.51,3,Low,Copy,1,0 +38982,56746,50382,PRETRIAL,MAHER,STEPHEN,M,Male,Caucasian,09/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,Copy,1,0 +38982,56746,50382,PRETRIAL,MAHER,STEPHEN,M,Male,Caucasian,09/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +59571,68299,61923,PRETRIAL,Rowe,Glenn,NULL,Male,Caucasian,10/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +59571,68299,61923,PRETRIAL,Rowe,Glenn,NULL,Male,Caucasian,10/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +59571,68299,61923,PRETRIAL,Rowe,Glenn,NULL,Male,Caucasian,10/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59531,68250,61877,PRETRIAL,Cohn,Sebastian,NULL,Male,Caucasian,08/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/10/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +59531,68250,61877,PRETRIAL,Cohn,Sebastian,NULL,Male,Caucasian,08/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +59531,68250,61877,PRETRIAL,Cohn,Sebastian,NULL,Male,Caucasian,08/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +8687,68267,61534,PRETRIAL,HIGGS,MARSHALL,E,Male,African-American,11/26/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +8687,68267,61534,PRETRIAL,HIGGS,MARSHALL,E,Male,African-American,11/26/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.76,10,High,New,1,0 +8687,68267,61534,PRETRIAL,HIGGS,MARSHALL,E,Male,African-American,11/26/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,3,Low,New,1,0 +56195,68246,61873,PRETRIAL,NICOLAS,NIKENSON,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +56195,68246,61873,PRETRIAL,NICOLAS,NIKENSON,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +56195,68246,61873,PRETRIAL,NICOLAS,NIKENSON,NULL,Male,African-American,05/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59547,68271,61896,DRRD,Lucas,Altaneca,Lashay,Female,African-American,04/18/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +59547,68271,61896,DRRD,Lucas,Altaneca,Lashay,Female,African-American,04/18/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.35,6,Medium,New,1,0 +59547,68271,61896,DRRD,Lucas,Altaneca,Lashay,Female,African-American,04/18/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,2,Medium,18,Risk of Failure to Appear,16,1,Low,New,1,0 +59562,68297,61914,PRETRIAL,Elisias,Tyvon,Marquis,Male,African-American,03/12/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,4,High,7,Risk of Violence,-0.65,9,High,New,1,0 +59562,68297,61914,PRETRIAL,Elisias,Tyvon,Marquis,Male,African-American,03/12/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +59562,68297,61914,PRETRIAL,Elisias,Tyvon,Marquis,Male,African-American,03/12/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,4,High,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +59542,68262,61889,PRETRIAL,Smaglik,Corey,Lee,Male,Caucasian,08/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +59542,68262,61889,PRETRIAL,Smaglik,Corey,Lee,Male,Caucasian,08/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +59542,68262,61889,PRETRIAL,Smaglik,Corey,Lee,Male,Caucasian,08/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59552,68276,61901,PRETRIAL,Perez-Cuyuch,Eugenio,Jehu,Male,Hispanic,02/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +59552,68276,61901,PRETRIAL,Perez-Cuyuch,Eugenio,Jehu,Male,Hispanic,02/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +59552,68276,61901,PRETRIAL,Perez-Cuyuch,Eugenio,Jehu,Male,Hispanic,02/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59567,68295,61920,Probation,Perry,Jerald,NULL,Male,African-American,06/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +59567,68295,61920,Probation,Perry,Jerald,NULL,Male,African-American,06/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +59567,68295,61920,Probation,Perry,Jerald,NULL,Male,African-American,06/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59550,68274,61899,PRETRIAL,Briceno,Michelle,NULL,Female,Caucasian,11/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +59550,68274,61899,PRETRIAL,Briceno,Michelle,NULL,Female,Caucasian,11/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +59550,68274,61899,PRETRIAL,Briceno,Michelle,NULL,Female,Caucasian,11/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59532,68251,61878,PRETRIAL,Foulks,Andre,NULL,Male,Other,10/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/10/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +59532,68251,61878,PRETRIAL,Foulks,Andre,NULL,Male,Other,10/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +59532,68251,61878,PRETRIAL,Foulks,Andre,NULL,Male,Other,10/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59534,68253,61880,PRETRIAL,MILLER,TERRY,NULL,Male,African-American,07/14/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +59534,68253,61880,PRETRIAL,MILLER,TERRY,NULL,Male,African-American,07/14/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +59534,68253,61880,PRETRIAL,MILLER,TERRY,NULL,Male,African-American,07/14/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +20295,68287,61912,PRETRIAL,Delprado,Jorge,NULL,Male,Caucasian,10/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.47,3,Low,New,1,0 +20295,68287,61912,PRETRIAL,Delprado,Jorge,NULL,Male,Caucasian,10/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +20295,68287,61912,PRETRIAL,Delprado,Jorge,NULL,Male,Caucasian,10/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58976,68266,61232,PRETRIAL,Camargo,Danielle,NULL,Female,Caucasian,03/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,Copy,1,0 +58976,68266,61232,PRETRIAL,Camargo,Danielle,NULL,Female,Caucasian,03/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,Copy,1,0 +58976,68266,61232,PRETRIAL,Camargo,Danielle,NULL,Female,Caucasian,03/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +59546,68269,61894,Probation,Strowbridge,Nathaniel,NULL,Male,African-American,11/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +59546,68269,61894,Probation,Strowbridge,Nathaniel,NULL,Male,African-American,11/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +59546,68269,61894,Probation,Strowbridge,Nathaniel,NULL,Male,African-American,11/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59529,68248,61875,PRETRIAL,KLEINHENZ,RICHARD,DANIEL,Male,Caucasian,08/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,4,High,7,Risk of Violence,-0.56,10,High,New,1,0 +59529,68248,61875,PRETRIAL,KLEINHENZ,RICHARD,DANIEL,Male,Caucasian,08/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,4,High,8,Risk of Recidivism,1.15,10,High,New,1,0 +59529,68248,61875,PRETRIAL,KLEINHENZ,RICHARD,DANIEL,Male,Caucasian,08/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59557,68282,61907,PRETRIAL,slade,paul,NULL,Male,Caucasian,12/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +59557,68282,61907,PRETRIAL,slade,paul,NULL,Male,Caucasian,12/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +59557,68282,61907,PRETRIAL,slade,paul,NULL,Male,Caucasian,12/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59563,68290,61915,Probation,miller,kenneth,NULL,Male,African-American,02/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.09,4,Low,New,1,0 +59563,68290,61915,Probation,miller,kenneth,NULL,Male,African-American,02/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.77,10,High,New,1,0 +59563,68290,61915,Probation,miller,kenneth,NULL,Male,African-American,02/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59541,68261,61888,PRETRIAL,Young,Jahreal,D,Male,African-American,06/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +59541,68261,61888,PRETRIAL,Young,Jahreal,D,Male,African-American,06/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +59541,68261,61888,PRETRIAL,Young,Jahreal,D,Male,African-American,06/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59560,68284,61909,Probation,WORRELL,LIONEL,M,Male,African-American,01/07/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,12/10/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +59560,68284,61909,Probation,WORRELL,LIONEL,M,Male,African-American,01/07/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,12/10/13 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +59560,68284,61909,Probation,WORRELL,LIONEL,M,Male,African-American,01/07/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59535,68254,61881,PRETRIAL,Petit,Toshiko,NULL,Female,Other,07/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +59535,68254,61881,PRETRIAL,Petit,Toshiko,NULL,Female,Other,07/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +59535,68254,61881,PRETRIAL,Petit,Toshiko,NULL,Female,Other,07/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +49153,68272,61897,PRETRIAL,Genhold,Brian,NULL,Male,Caucasian,02/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,12/10/13 0:00,2,Medium,7,Risk of Violence,-2.65,2,Low,New,1,0 +49153,68272,61897,PRETRIAL,Genhold,Brian,NULL,Male,Caucasian,02/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,12/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +49153,68272,61897,PRETRIAL,Genhold,Brian,NULL,Male,Caucasian,02/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,12/10/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +29710,68279,61904,PRETRIAL,CORTES,DANIEL,NULL,Male,Caucasian,04/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/10/13 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +29710,68279,61904,PRETRIAL,CORTES,DANIEL,NULL,Male,Caucasian,04/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/10/13 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +29710,68279,61904,PRETRIAL,CORTES,DANIEL,NULL,Male,Caucasian,04/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/10/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59538,68258,61885,PRETRIAL,JONES,JASMINE,NULL,Female,African-American,11/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +59538,68258,61885,PRETRIAL,JONES,JASMINE,NULL,Female,African-American,11/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +59538,68258,61885,PRETRIAL,JONES,JASMINE,NULL,Female,African-American,11/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59551,68275,61900,PRETRIAL,Mora,Raul,Fernandez,Male,Hispanic,11/12/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/10/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +59551,68275,61900,PRETRIAL,Mora,Raul,Fernandez,Male,Hispanic,11/12/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +59551,68275,61900,PRETRIAL,Mora,Raul,Fernandez,Male,Hispanic,11/12/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59565,68293,61918,PRETRIAL,kalbkauf,kevin,NULL,Male,Caucasian,12/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/10/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +59565,68293,61918,PRETRIAL,kalbkauf,kevin,NULL,Male,Caucasian,12/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/10/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +59565,68293,61918,PRETRIAL,kalbkauf,kevin,NULL,Male,Caucasian,12/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59553,68277,61902,Probation,Jackson,Carol,NULL,Female,African-American,11/09/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,2,Medium,7,Risk of Violence,-3.62,1,Low,New,1,0 +59553,68277,61902,Probation,Jackson,Carol,NULL,Female,African-American,11/09/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +59553,68277,61902,Probation,Jackson,Carol,NULL,Female,African-American,11/09/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59530,68249,61876,PRETRIAL,MOSIMAN,THOMAS,NULL,Male,Caucasian,07/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +59530,68249,61876,PRETRIAL,MOSIMAN,THOMAS,NULL,Male,Caucasian,07/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +59530,68249,61876,PRETRIAL,MOSIMAN,THOMAS,NULL,Male,Caucasian,07/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59536,68256,61883,PRETRIAL,Miranda,Mathew,T,Male,Caucasian,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +59536,68256,61883,PRETRIAL,Miranda,Mathew,T,Male,Caucasian,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +59536,68256,61883,PRETRIAL,Miranda,Mathew,T,Male,Caucasian,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59543,68263,61890,PRETRIAL,LOWRY,JAMES,NULL,Male,Caucasian,02/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +59543,68263,61890,PRETRIAL,LOWRY,JAMES,NULL,Male,Caucasian,02/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +59543,68263,61890,PRETRIAL,LOWRY,JAMES,NULL,Male,Caucasian,02/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +52701,68298,61922,PRETRIAL,Baquedano-Rivera,Ronald,NULL,Male,Hispanic,12/09/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +52701,68298,61922,PRETRIAL,Baquedano-Rivera,Ronald,NULL,Male,Hispanic,12/09/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +52701,68298,61922,PRETRIAL,Baquedano-Rivera,Ronald,NULL,Male,Hispanic,12/09/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59548,68270,61895,Probation,Walker,Steven,Neil,Male,African-American,01/14/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +59548,68270,61895,Probation,Walker,Steven,Neil,Male,African-American,01/14/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +59548,68270,61895,Probation,Walker,Steven,Neil,Male,African-American,01/14/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59572,68300,61924,Probation,swersky,andrew,NULL,Male,Caucasian,03/31/62,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +59572,68300,61924,Probation,swersky,andrew,NULL,Male,Caucasian,03/31/62,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +59572,68300,61924,Probation,swersky,andrew,NULL,Male,Caucasian,03/31/62,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59540,68260,61887,PRETRIAL,Campbell,Errol,NULL,Male,Other,09/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +59540,68260,61887,PRETRIAL,Campbell,Errol,NULL,Male,Other,09/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +59540,68260,61887,PRETRIAL,Campbell,Errol,NULL,Male,Other,09/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59556,68281,61906,Probation,SHAHZAD,MOHAMMAD,NULL,Male,Asian,11/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +59556,68281,61906,Probation,SHAHZAD,MOHAMMAD,NULL,Male,Asian,11/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +59556,68281,61906,Probation,SHAHZAD,MOHAMMAD,NULL,Male,Asian,11/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +47630,68288,61913,PRETRIAL,Jiminez,John,NULL,Male,Hispanic,06/22/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/10/13 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +47630,68288,61913,PRETRIAL,Jiminez,John,NULL,Male,Hispanic,06/22/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/10/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +47630,68288,61913,PRETRIAL,Jiminez,John,NULL,Male,Hispanic,06/22/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59562,68289,61914,PRETRIAL,Elisias,Tyvon,Marquis,Male,African-American,03/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,4,High,7,Risk of Violence,-0.61,10,High,New,1,0 +59562,68289,61914,PRETRIAL,Elisias,Tyvon,Marquis,Male,African-American,03/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,4,High,8,Risk of Recidivism,0.28,8,High,New,1,0 +59562,68289,61914,PRETRIAL,Elisias,Tyvon,Marquis,Male,African-American,03/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +59568,68296,61921,PRETRIAL,Freeze,Williams,Brian,Male,Caucasian,10/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +59568,68296,61921,PRETRIAL,Freeze,Williams,Brian,Male,Caucasian,10/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +59568,68296,61921,PRETRIAL,Freeze,Williams,Brian,Male,Caucasian,10/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +36277,68268,61893,PRETRIAL,GRAY,COURTNEY,NULL,Male,African-American,02/08/91,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,12/10/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +36277,68268,61893,PRETRIAL,GRAY,COURTNEY,NULL,Male,African-American,02/08/91,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,12/10/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +36277,68268,61893,PRETRIAL,GRAY,COURTNEY,NULL,Male,African-American,02/08/91,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,12/10/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59549,68273,61898,Probation,BUTRIM,JOHN,MARTIN,Male,Caucasian,11/11/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +59549,68273,61898,Probation,BUTRIM,JOHN,MARTIN,Male,Caucasian,11/11/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +59549,68273,61898,Probation,BUTRIM,JOHN,MARTIN,Male,Caucasian,11/11/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59533,68252,61879,PRETRIAL,HAGINS,LEON,MONTAWALLY,Male,African-American,12/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +59533,68252,61879,PRETRIAL,HAGINS,LEON,MONTAWALLY,Male,African-American,12/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +59533,68252,61879,PRETRIAL,HAGINS,LEON,MONTAWALLY,Male,African-American,12/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59561,68286,61911,Probation,Perez,Juan,NULL,Male,Hispanic,10/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/10/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +59561,68286,61911,Probation,Perez,Juan,NULL,Male,Hispanic,10/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/10/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +59561,68286,61911,Probation,Perez,Juan,NULL,Male,Hispanic,10/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59566,68294,61919,Probation,vigon,robert,NULL,Male,Hispanic,06/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/10/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +59566,68294,61919,Probation,vigon,robert,NULL,Male,Hispanic,06/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/10/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +59566,68294,61919,Probation,vigon,robert,NULL,Male,Hispanic,06/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59528,68247,61874,PRETRIAL,CASTANON,PETER,NULL,Male,Caucasian,04/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/10/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +59528,68247,61874,PRETRIAL,CASTANON,PETER,NULL,Male,Caucasian,04/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/10/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +59528,68247,61874,PRETRIAL,CASTANON,PETER,NULL,Male,Caucasian,04/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/10/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59545,68265,61892,PRETRIAL,Lucas,Avious,NULL,Female,African-American,07/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +59545,68265,61892,PRETRIAL,Lucas,Avious,NULL,Female,African-American,07/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,9,High,New,1,0 +59545,68265,61892,PRETRIAL,Lucas,Avious,NULL,Female,African-American,07/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +39806,68304,61928,PRETRIAL,Williams,Diante,NULL,Male,African-American,12/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.05,8,High,New,1,0 +39806,68304,61928,PRETRIAL,Williams,Diante,NULL,Male,African-American,12/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +39806,68304,61928,PRETRIAL,Williams,Diante,NULL,Male,African-American,12/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53843,68315,61938,Probation,ARISTIZABAL,LORENA,NULL,Female,Hispanic,06/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +53843,68315,61938,Probation,ARISTIZABAL,LORENA,NULL,Female,Hispanic,06/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +53843,68315,61938,Probation,ARISTIZABAL,LORENA,NULL,Female,Hispanic,06/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59580,68312,61935,PRETRIAL,Chaves,Priscilla,NULL,Female,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +59580,68312,61935,PRETRIAL,Chaves,Priscilla,NULL,Female,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +59580,68312,61935,PRETRIAL,Chaves,Priscilla,NULL,Female,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59594,68325,61948,PRETRIAL,Jones,Justin,NULL,Male,African-American,11/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +59594,68325,61948,PRETRIAL,Jones,Justin,NULL,Male,African-American,11/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +59594,68325,61948,PRETRIAL,Jones,Justin,NULL,Male,African-American,11/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59589,68320,61943,Probation,Burbick,Shane,NULL,Male,Caucasian,04/11/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/11/13 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +59589,68320,61943,Probation,Burbick,Shane,NULL,Male,Caucasian,04/11/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/11/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +59589,68320,61943,Probation,Burbick,Shane,NULL,Male,Caucasian,04/11/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59576,68307,61931,PRETRIAL,Cooper,Steven,NULL,Male,Caucasian,11/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +59576,68307,61931,PRETRIAL,Cooper,Steven,NULL,Male,Caucasian,11/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +59576,68307,61931,PRETRIAL,Cooper,Steven,NULL,Male,Caucasian,11/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58363,68302,61926,PRETRIAL,Yearby,Dustin,NULL,Male,African-American,06/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/13 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +58363,68302,61926,PRETRIAL,Yearby,Dustin,NULL,Male,African-American,06/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +58363,68302,61926,PRETRIAL,Yearby,Dustin,NULL,Male,African-American,06/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59587,68317,61940,Probation,WILLIE,KIMBERLY,NULL,Female,Caucasian,12/25/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +59587,68317,61940,Probation,WILLIE,KIMBERLY,NULL,Female,Caucasian,12/25/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +59587,68317,61940,Probation,WILLIE,KIMBERLY,NULL,Female,Caucasian,12/25/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59593,68323,61946,PRETRIAL,KUSHNER,STEPHEN,P,Male,Caucasian,11/10/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +59593,68323,61946,PRETRIAL,KUSHNER,STEPHEN,P,Male,Caucasian,11/10/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,1,Low,8,Risk of Recidivism,-2.64,1,Low,New,1,0 +59593,68323,61946,PRETRIAL,KUSHNER,STEPHEN,P,Male,Caucasian,11/10/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59600,68330,61953,PRETRIAL,Jarnagin,Randy,NULL,Male,Caucasian,07/26/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +59600,68330,61953,PRETRIAL,Jarnagin,Randy,NULL,Male,Caucasian,07/26/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +59600,68330,61953,PRETRIAL,Jarnagin,Randy,NULL,Male,Caucasian,07/26/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +7162,68331,6751,PRETRIAL,CLARK,RENARDO,C,Male,African-American,10/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/13 0:00,4,High,7,Risk of Violence,-1.14,8,High,Copy,1,0 +7162,68331,6751,PRETRIAL,CLARK,RENARDO,C,Male,African-American,10/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/13 0:00,4,High,8,Risk of Recidivism,0.71,10,High,Copy,1,0 +7162,68331,6751,PRETRIAL,CLARK,RENARDO,C,Male,African-American,10/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/13 0:00,4,High,18,Risk of Failure to Appear,35,10,High,Copy,1,0 +59578,68309,61933,PRETRIAL,Milfort,Theova,NULL,Male,Other,10/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/13 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +59578,68309,61933,PRETRIAL,Milfort,Theova,NULL,Male,Other,10/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/13 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +59578,68309,61933,PRETRIAL,Milfort,Theova,NULL,Male,Other,10/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59579,68310,61934,PRETRIAL,Lewis,Demetris,Devon,Male,African-American,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +59579,68310,61934,PRETRIAL,Lewis,Demetris,Devon,Male,African-American,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +59579,68310,61934,PRETRIAL,Lewis,Demetris,Devon,Male,African-American,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +59588,68319,61942,PRETRIAL,Carlson,Raymond,NULL,Male,Caucasian,01/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/11/13 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +59588,68319,61942,PRETRIAL,Carlson,Raymond,NULL,Male,Caucasian,01/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/11/13 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +59588,68319,61942,PRETRIAL,Carlson,Raymond,NULL,Male,Caucasian,01/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59590,68321,61944,PRETRIAL,Seal,Jerry,NULL,Male,Caucasian,09/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/11/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +59590,68321,61944,PRETRIAL,Seal,Jerry,NULL,Male,Caucasian,09/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/11/13 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +59590,68321,61944,PRETRIAL,Seal,Jerry,NULL,Male,Caucasian,09/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59597,68328,61951,Probation,Kessler,Anthony,NULL,Male,Caucasian,02/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/11/13 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +59597,68328,61951,Probation,Kessler,Anthony,NULL,Male,Caucasian,02/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +59597,68328,61951,Probation,Kessler,Anthony,NULL,Male,Caucasian,02/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/11/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59595,68326,61949,PRETRIAL,Babecki,Christopher,NULL,Male,Caucasian,05/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +59595,68326,61949,PRETRIAL,Babecki,Christopher,NULL,Male,Caucasian,05/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +59595,68326,61949,PRETRIAL,Babecki,Christopher,NULL,Male,Caucasian,05/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57083,68305,61929,PRETRIAL,BANKSTON,DAMANI,MARKEL,Male,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +57083,68305,61929,PRETRIAL,BANKSTON,DAMANI,MARKEL,Male,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +57083,68305,61929,PRETRIAL,BANKSTON,DAMANI,MARKEL,Male,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59582,68314,61937,PRETRIAL,Hitzemankhan,Lisa,NULL,Female,Caucasian,11/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/11/13 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +59582,68314,61937,PRETRIAL,Hitzemankhan,Lisa,NULL,Female,Caucasian,11/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/11/13 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +59582,68314,61937,PRETRIAL,Hitzemankhan,Lisa,NULL,Female,Caucasian,11/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +59510,68311,61850,PRETRIAL,Mashaw,Lnida,NULL,Female,Caucasian,06/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,Copy,1,0 +59510,68311,61850,PRETRIAL,Mashaw,Lnida,NULL,Female,Caucasian,06/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,Copy,1,0 +59510,68311,61850,PRETRIAL,Mashaw,Lnida,NULL,Female,Caucasian,06/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +59577,68308,61932,PRETRIAL,May,Tiffany,Noel,Female,Caucasian,05/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +59577,68308,61932,PRETRIAL,May,Tiffany,Noel,Female,Caucasian,05/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +59577,68308,61932,PRETRIAL,May,Tiffany,Noel,Female,Caucasian,05/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59598,68329,61952,PRETRIAL,Stroman,Xavier,NULL,Male,African-American,07/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +59598,68329,61952,PRETRIAL,Stroman,Xavier,NULL,Male,African-American,07/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +59598,68329,61952,PRETRIAL,Stroman,Xavier,NULL,Male,African-American,07/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59586,68316,61939,PRETRIAL,Baladi,Roger,NULL,Male,Hispanic,07/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +59586,68316,61939,PRETRIAL,Baladi,Roger,NULL,Male,Hispanic,07/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +59586,68316,61939,PRETRIAL,Baladi,Roger,NULL,Male,Hispanic,07/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59574,68303,61927,PRETRIAL,WOODRUFF,TENETTA,NULL,Female,Native American,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +59574,68303,61927,PRETRIAL,WOODRUFF,TENETTA,NULL,Female,Native American,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,7,Medium,New,1,0 +59574,68303,61927,PRETRIAL,WOODRUFF,TENETTA,NULL,Female,Native American,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +24047,39007,35719,PRETRIAL,FASANO,FRANK,NULL,Male,Caucasian,02/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +24047,39007,35719,PRETRIAL,FASANO,FRANK,NULL,Male,Caucasian,02/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +24047,39007,35719,PRETRIAL,FASANO,FRANK,NULL,Male,Caucasian,02/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54490,68324,61947,PRETRIAL,Bienaime,Mckenzy,NULL,Male,Caucasian,05/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +54490,68324,61947,PRETRIAL,Bienaime,Mckenzy,NULL,Male,Caucasian,05/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +54490,68324,61947,PRETRIAL,Bienaime,Mckenzy,NULL,Male,Caucasian,05/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59591,68322,61945,Probation,Vargas,Hugo,NULL,Male,Hispanic,03/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/11/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +59591,68322,61945,Probation,Vargas,Hugo,NULL,Male,Hispanic,03/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/11/13 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +59591,68322,61945,Probation,Vargas,Hugo,NULL,Male,Hispanic,03/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59573,68301,61925,PRETRIAL,MCMULLEN,NATHAN,CHARLES,Male,Caucasian,03/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +59573,68301,61925,PRETRIAL,MCMULLEN,NATHAN,CHARLES,Male,Caucasian,03/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +59573,68301,61925,PRETRIAL,MCMULLEN,NATHAN,CHARLES,Male,Caucasian,03/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +38601,68318,61941,PRETRIAL,Williams,Cassandra,NULL,Female,Caucasian,12/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/11/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +38601,68318,61941,PRETRIAL,Williams,Cassandra,NULL,Female,Caucasian,12/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/11/13 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +38601,68318,61941,PRETRIAL,Williams,Cassandra,NULL,Female,Caucasian,12/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59575,68306,61930,PRETRIAL,GARDNER,JASON,MITCHELL,Male,Caucasian,03/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/11/13 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +59575,68306,61930,PRETRIAL,GARDNER,JASON,MITCHELL,Male,Caucasian,03/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/11/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +59575,68306,61930,PRETRIAL,GARDNER,JASON,MITCHELL,Male,Caucasian,03/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/11/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59581,68313,61936,PRETRIAL,Zambrano,Stephen,NULL,Male,Hispanic,09/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +59581,68313,61936,PRETRIAL,Zambrano,Stephen,NULL,Male,Hispanic,09/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +59581,68313,61936,PRETRIAL,Zambrano,Stephen,NULL,Male,Hispanic,09/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59596,68327,61950,PRETRIAL,Valcy,Sebastian,NULL,Male,African-American,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +59596,68327,61950,PRETRIAL,Valcy,Sebastian,NULL,Male,African-American,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +59596,68327,61950,PRETRIAL,Valcy,Sebastian,NULL,Male,African-American,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59601,68334,61956,Probation,Nyson,Andre,NULL,Male,African-American,08/23/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/11/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +59601,68334,61956,Probation,Nyson,Andre,NULL,Male,African-American,08/23/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/11/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +59601,68334,61956,Probation,Nyson,Andre,NULL,Male,African-American,08/23/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/11/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59603,68336,61957,PRETRIAL,Lee,David,NULL,Male,African-American,10/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,New,1,0 +59603,68336,61957,PRETRIAL,Lee,David,NULL,Male,African-American,10/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +59603,68336,61957,PRETRIAL,Lee,David,NULL,Male,African-American,10/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59619,68355,61976,Probation,Lavergne,Emily,NULL,Female,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +59619,68355,61976,Probation,Lavergne,Emily,NULL,Female,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,9,High,New,1,0 +59619,68355,61976,Probation,Lavergne,Emily,NULL,Female,Caucasian,09/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +49200,68357,61978,PRETRIAL,BICKLE,ASHLEY,LYNN,Female,Caucasian,09/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +49200,68357,61978,PRETRIAL,BICKLE,ASHLEY,LYNN,Female,Caucasian,09/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +49200,68357,61978,PRETRIAL,BICKLE,ASHLEY,LYNN,Female,Caucasian,09/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +28116,68364,61984,PRETRIAL,Fleming,Markayle,NULL,Male,African-American,12/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,New,1,0 +28116,68364,61984,PRETRIAL,Fleming,Markayle,NULL,Male,African-American,12/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +28116,68364,61984,PRETRIAL,Fleming,Markayle,NULL,Male,African-American,12/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +42166,68352,61973,PRETRIAL,Calixte,Denley,Snider,Male,Other,08/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +42166,68352,61973,PRETRIAL,Calixte,Denley,Snider,Male,Other,08/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +42166,68352,61973,PRETRIAL,Calixte,Denley,Snider,Male,Other,08/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59630,68369,61989,Probation,Jordan,Joey,NULL,Male,Caucasian,04/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +59630,68369,61989,Probation,Jordan,Joey,NULL,Male,Caucasian,04/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +59630,68369,61989,Probation,Jordan,Joey,NULL,Male,Caucasian,04/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +35674,68339,61960,PRETRIAL,Olivio,Nelson,NULL,Male,African-American,06/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/12/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +35674,68339,61960,PRETRIAL,Olivio,Nelson,NULL,Male,African-American,06/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/12/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +35674,68339,61960,PRETRIAL,Olivio,Nelson,NULL,Male,African-American,06/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +44189,68348,61969,Probation,payne,miranda,NULL,Female,Caucasian,10/17/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +44189,68348,61969,Probation,payne,miranda,NULL,Female,Caucasian,10/17/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,8,High,New,1,0 +44189,68348,61969,Probation,payne,miranda,NULL,Female,Caucasian,10/17/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59610,68343,61964,Probation,Motley,Christopher,NULL,Male,African-American,01/08/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/12/13 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +59610,68343,61964,Probation,Motley,Christopher,NULL,Male,African-American,01/08/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/12/13 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +59610,68343,61964,Probation,Motley,Christopher,NULL,Male,African-American,01/08/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +37973,40817,37375,PRETRIAL,Bolden,Keyon,NULL,Male,African-American,04/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +37973,40817,37375,PRETRIAL,Bolden,Keyon,NULL,Male,African-American,04/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,4,High,8,Risk of Recidivism,0.26,8,High,New,1,0 +37973,40817,37375,PRETRIAL,Bolden,Keyon,NULL,Male,African-American,04/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +8300,68345,61966,PRETRIAL,Deanda,Brandon,Reed,Male,Caucasian,04/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/12/13 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +8300,68345,61966,PRETRIAL,Deanda,Brandon,Reed,Male,Caucasian,04/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +8300,68345,61966,PRETRIAL,Deanda,Brandon,Reed,Male,Caucasian,04/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/12/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +59622,68360,61980,PRETRIAL,Mcduffie,Nijah,NULL,Male,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +59622,68360,61980,PRETRIAL,Mcduffie,Nijah,NULL,Male,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +59622,68360,61980,PRETRIAL,Mcduffie,Nijah,NULL,Male,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59627,68366,61986,Probation,FONSECA,SARA,L,Female,Caucasian,08/31/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +59627,68366,61986,Probation,FONSECA,SARA,L,Female,Caucasian,08/31/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +59627,68366,61986,Probation,FONSECA,SARA,L,Female,Caucasian,08/31/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59617,68353,61974,PRETRIAL,Zinser,Robert,NULL,Male,Caucasian,03/17/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/12/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +59617,68353,61974,PRETRIAL,Zinser,Robert,NULL,Male,Caucasian,03/17/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/12/13 0:00,1,Low,8,Risk of Recidivism,-2.62,1,Low,New,1,0 +59617,68353,61974,PRETRIAL,Zinser,Robert,NULL,Male,Caucasian,03/17/53,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59629,68368,61988,Probation,mclaughlin,brian,NULL,Male,Caucasian,08/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,2,Medium,7,Risk of Violence,-2.65,2,Low,New,1,0 +59629,68368,61988,Probation,mclaughlin,brian,NULL,Male,Caucasian,08/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +59629,68368,61988,Probation,mclaughlin,brian,NULL,Male,Caucasian,08/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59604,68337,61958,PRETRIAL,Drake,Chance,Alexander,Male,Caucasian,11/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +59604,68337,61958,PRETRIAL,Drake,Chance,Alexander,Male,Caucasian,11/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +59604,68337,61958,PRETRIAL,Drake,Chance,Alexander,Male,Caucasian,11/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59615,68350,61971,Probation,McKnight,Dynesha,NULL,Female,African-American,11/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +59615,68350,61971,Probation,McKnight,Dynesha,NULL,Female,African-American,11/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +59615,68350,61971,Probation,McKnight,Dynesha,NULL,Female,African-American,11/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59611,68344,61965,DRRD,Lucas,Markell,Javon,Male,African-American,07/31/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +59611,68344,61965,DRRD,Lucas,Markell,Javon,Male,African-American,07/31/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,5,Medium,New,1,0 +59611,68344,61965,DRRD,Lucas,Markell,Javon,Male,African-American,07/31/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59623,68361,61981,Probation,Hollander,Shawn,NULL,Male,Caucasian,02/20/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/12/13 0:00,2,Medium,7,Risk of Violence,-3.43,1,Low,New,1,0 +59623,68361,61981,Probation,Hollander,Shawn,NULL,Male,Caucasian,02/20/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +59623,68361,61981,Probation,Hollander,Shawn,NULL,Male,Caucasian,02/20/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/12/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59606,68340,61961,PRETRIAL,Bordones,Kalim,NULL,Male,Caucasian,06/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +59606,68340,61961,PRETRIAL,Bordones,Kalim,NULL,Male,Caucasian,06/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +59606,68340,61961,PRETRIAL,Bordones,Kalim,NULL,Male,Caucasian,06/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59613,68347,61968,Broward County,Soto,Randolph,NULL,Male,African-American,04/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/13 0:00,4,High,7,Risk of Violence,-0.21,10,High,New,1,0 +59613,68347,61968,Broward County,Soto,Randolph,NULL,Male,African-American,04/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/13 0:00,4,High,8,Risk of Recidivism,0.95,10,High,New,1,0 +59613,68347,61968,Broward County,Soto,Randolph,NULL,Male,African-American,04/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/13 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +59626,68365,61985,PRETRIAL,Archibald,Ralante,NULL,Male,African-American,08/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/13 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +59626,68365,61985,PRETRIAL,Archibald,Ralante,NULL,Male,African-American,08/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +59626,68365,61985,PRETRIAL,Archibald,Ralante,NULL,Male,African-American,08/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59608,68342,61963,PRETRIAL,Vasquez,Sergio,NULL,Male,Hispanic,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.14,8,High,New,1,0 +59608,68342,61963,PRETRIAL,Vasquez,Sergio,NULL,Male,Hispanic,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +59608,68342,61963,PRETRIAL,Vasquez,Sergio,NULL,Male,Hispanic,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59614,68349,61970,Probation,Padilla,Nelson,NULL,Male,Hispanic,03/05/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/12/13 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +59614,68349,61970,Probation,Padilla,Nelson,NULL,Male,Hispanic,03/05/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/12/13 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +59614,68349,61970,Probation,Padilla,Nelson,NULL,Male,Hispanic,03/05/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59620,68356,61977,Probation,bulnes,robert,NULL,Male,Caucasian,01/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +59620,68356,61977,Probation,bulnes,robert,NULL,Male,Caucasian,01/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +59620,68356,61977,Probation,bulnes,robert,NULL,Male,Caucasian,01/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59625,68363,61983,PRETRIAL,Harris,Sony,NULL,Male,African-American,01/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +59625,68363,61983,PRETRIAL,Harris,Sony,NULL,Male,African-American,01/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +59625,68363,61983,PRETRIAL,Harris,Sony,NULL,Male,African-American,01/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +36040,68370,61990,PRETRIAL,wokral,brittany,NULL,Female,Caucasian,03/23/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +36040,68370,61990,PRETRIAL,wokral,brittany,NULL,Female,Caucasian,03/23/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +36040,68370,61990,PRETRIAL,wokral,brittany,NULL,Female,Caucasian,03/23/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59621,68359,61979,Probation,SGAMBATI-SHEIL,LISA,MARIE,Female,Caucasian,05/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,12/12/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.37,3,Low,New,1,0 +59621,68359,61979,Probation,SGAMBATI-SHEIL,LISA,MARIE,Female,Caucasian,05/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,12/12/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,8,High,New,1,0 +59621,68359,61979,Probation,SGAMBATI-SHEIL,LISA,MARIE,Female,Caucasian,05/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,12/12/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59605,68338,61959,PRETRIAL,WILLIAMS,TERRANCE,NULL,Male,African-American,09/16/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +59605,68338,61959,PRETRIAL,WILLIAMS,TERRANCE,NULL,Male,African-American,09/16/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +59605,68338,61959,PRETRIAL,WILLIAMS,TERRANCE,NULL,Male,African-American,09/16/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +59616,68351,61972,Probation,GATES,KAREN,LOUISE,Female,Caucasian,05/12/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +59616,68351,61972,Probation,GATES,KAREN,LOUISE,Female,Caucasian,05/12/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +59616,68351,61972,Probation,GATES,KAREN,LOUISE,Female,Caucasian,05/12/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59607,68341,61962,PRETRIAL,YOUNG,YOLANDA,YVETTE,Female,African-American,03/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +59607,68341,61962,PRETRIAL,YOUNG,YOLANDA,YVETTE,Female,African-American,03/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +59607,68341,61962,PRETRIAL,YOUNG,YOLANDA,YVETTE,Female,African-American,03/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59612,68346,61967,Probation,BANCROFT,MINDY,NULL,Female,Caucasian,11/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/12/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +59612,68346,61967,Probation,BANCROFT,MINDY,NULL,Female,Caucasian,11/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/12/13 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +59612,68346,61967,Probation,BANCROFT,MINDY,NULL,Female,Caucasian,11/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59628,68367,61987,Probation,dennis,sophia,NULL,Female,African-American,03/12/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +59628,68367,61987,Probation,dennis,sophia,NULL,Female,African-American,03/12/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +59628,68367,61987,Probation,dennis,sophia,NULL,Female,African-American,03/12/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59624,68362,61982,PRETRIAL,HARRIS,OCTAVIOUS,NULL,Male,African-American,06/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +59624,68362,61982,PRETRIAL,HARRIS,OCTAVIOUS,NULL,Male,African-American,06/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +59624,68362,61982,PRETRIAL,HARRIS,OCTAVIOUS,NULL,Male,African-American,06/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59618,68354,61975,Probation,Castellanos,Efrain,NULL,Male,Hispanic,01/11/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/12/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +59618,68354,61975,Probation,Castellanos,Efrain,NULL,Male,Hispanic,01/11/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/12/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +59618,68354,61975,Probation,Castellanos,Efrain,NULL,Male,Hispanic,01/11/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/12/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59639,68383,62001,PRETRIAL,Ramos,Xavier,A,Male,Hispanic,02/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.91,9,High,New,1,0 +59639,68383,62001,PRETRIAL,Ramos,Xavier,A,Male,Hispanic,02/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +59639,68383,62001,PRETRIAL,Ramos,Xavier,A,Male,Hispanic,02/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53001,68375,54411,PRETRIAL,Smith,Anthony,NULL,Male,African-American,07/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.56,2,Low,Copy,1,0 +53001,68375,54411,PRETRIAL,Smith,Anthony,NULL,Male,African-American,07/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.67,10,High,Copy,1,0 +53001,68375,54411,PRETRIAL,Smith,Anthony,NULL,Male,African-American,07/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +59649,68393,62010,Probation,underhill,william,charles,Male,Caucasian,11/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +59649,68393,62010,Probation,underhill,william,charles,Male,Caucasian,11/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +59649,68393,62010,Probation,underhill,william,charles,Male,Caucasian,11/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59656,68401,62018,PRETRIAL,HAWKINS,PAUL,ROBERT,Male,Caucasian,12/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/13/13 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +59656,68401,62018,PRETRIAL,HAWKINS,PAUL,ROBERT,Male,Caucasian,12/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +59656,68401,62018,PRETRIAL,HAWKINS,PAUL,ROBERT,Male,Caucasian,12/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59637,68380,61998,PRETRIAL,Coronado-Cruz,Harold,NULL,Male,Hispanic,08/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/13/13 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +59637,68380,61998,PRETRIAL,Coronado-Cruz,Harold,NULL,Male,Hispanic,08/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/13/13 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +59637,68380,61998,PRETRIAL,Coronado-Cruz,Harold,NULL,Male,Hispanic,08/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59660,68404,62021,Probation,Garth,Jimmy,NULL,Male,Hispanic,02/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +59660,68404,62021,Probation,Garth,Jimmy,NULL,Male,Hispanic,02/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +59660,68404,62021,Probation,Garth,Jimmy,NULL,Male,Hispanic,02/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59651,68396,62013,PRETRIAL,Small,Doyen,NULL,Male,African-American,01/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,New,1,0 +59651,68396,62013,PRETRIAL,Small,Doyen,NULL,Male,African-American,01/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +59651,68396,62013,PRETRIAL,Small,Doyen,NULL,Male,African-American,01/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59644,68388,62005,PRETRIAL,Pedraza,Cesar,NULL,Male,Caucasian,03/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +59644,68388,62005,PRETRIAL,Pedraza,Cesar,NULL,Male,Caucasian,03/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +59644,68388,62005,PRETRIAL,Pedraza,Cesar,NULL,Male,Caucasian,03/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59663,68409,62025,PRETRIAL,SCHWARTZBACH,ALONA,NULL,Female,Caucasian,08/16/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +59663,68409,62025,PRETRIAL,SCHWARTZBACH,ALONA,NULL,Female,Caucasian,08/16/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +59663,68409,62025,PRETRIAL,SCHWARTZBACH,ALONA,NULL,Female,Caucasian,08/16/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +59655,68400,62017,Probation,Gaspard,Kaycy,NULL,Male,African-American,11/09/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +59655,68400,62017,Probation,Gaspard,Kaycy,NULL,Male,African-American,11/09/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +59655,68400,62017,Probation,Gaspard,Kaycy,NULL,Male,African-American,11/09/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59647,68391,62008,Probation,Teufel,Dawn,NULL,Female,Caucasian,07/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +59647,68391,62008,Probation,Teufel,Dawn,NULL,Female,Caucasian,07/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +59647,68391,62008,Probation,Teufel,Dawn,NULL,Female,Caucasian,07/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59653,68398,62015,PRETRIAL,Colon,Emilio,NULL,Male,Hispanic,03/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/13/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +59653,68398,62015,PRETRIAL,Colon,Emilio,NULL,Male,Hispanic,03/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +59653,68398,62015,PRETRIAL,Colon,Emilio,NULL,Male,Hispanic,03/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59634,68377,61995,PRETRIAL,Kasten,Christopher,NULL,Male,Caucasian,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/13/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +59634,68377,61995,PRETRIAL,Kasten,Christopher,NULL,Male,Caucasian,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +59634,68377,61995,PRETRIAL,Kasten,Christopher,NULL,Male,Caucasian,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +19617,68412,62028,PRETRIAL,DELVA,TRACY,NULL,Female,African-American,07/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +19617,68412,62028,PRETRIAL,DELVA,TRACY,NULL,Female,African-American,07/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,10,High,New,1,0 +19617,68412,62028,PRETRIAL,DELVA,TRACY,NULL,Female,African-American,07/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59640,68382,62000,PRETRIAL,Torres,Christian,NULL,Male,Caucasian,10/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +59640,68382,62000,PRETRIAL,Torres,Christian,NULL,Male,Caucasian,10/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +59640,68382,62000,PRETRIAL,Torres,Christian,NULL,Male,Caucasian,10/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59662,68407,62024,Probation,VARGAS,LOUIS,NULL,Male,Hispanic,02/06/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +59662,68407,62024,Probation,VARGAS,LOUIS,NULL,Male,Hispanic,02/06/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +59662,68407,62024,Probation,VARGAS,LOUIS,NULL,Male,Hispanic,02/06/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +27054,68386,44201,PRETRIAL,VINCENT,GORDON,NULL,Male,African-American,07/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,Copy,1,0 +27054,68386,44201,PRETRIAL,VINCENT,GORDON,NULL,Male,African-American,07/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,Copy,1,0 +27054,68386,44201,PRETRIAL,VINCENT,GORDON,NULL,Male,African-American,07/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +59659,68403,62020,Probation,Akers,Sherman,NULL,Male,African-American,09/14/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +59659,68403,62020,Probation,Akers,Sherman,NULL,Male,African-American,09/14/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +59659,68403,62020,Probation,Akers,Sherman,NULL,Male,African-American,09/14/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59641,68384,62002,PRETRIAL,Marc,Wilny,NULL,Male,African-American,09/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +59641,68384,62002,PRETRIAL,Marc,Wilny,NULL,Male,African-American,09/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +59641,68384,62002,PRETRIAL,Marc,Wilny,NULL,Male,African-American,09/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59661,68405,62022,Probation,Palacio,Diego,NULL,Male,Hispanic,07/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +59661,68405,62022,Probation,Palacio,Diego,NULL,Male,Hispanic,07/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +59661,68405,62022,Probation,Palacio,Diego,NULL,Male,Hispanic,07/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59652,68397,62014,PRETRIAL,jones,christopher,NULL,Male,African-American,08/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/13/13 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +59652,68397,62014,PRETRIAL,jones,christopher,NULL,Male,African-American,08/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/13/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +59652,68397,62014,PRETRIAL,jones,christopher,NULL,Male,African-American,08/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59633,68376,61994,PRETRIAL,Velazquezlugo,Elizabeth,NULL,Female,Caucasian,05/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +59633,68376,61994,PRETRIAL,Velazquezlugo,Elizabeth,NULL,Female,Caucasian,05/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +59633,68376,61994,PRETRIAL,Velazquezlugo,Elizabeth,NULL,Female,Caucasian,05/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59636,68379,61997,PRETRIAL,Jenkins,Dominick,NULL,Male,African-American,10/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +59636,68379,61997,PRETRIAL,Jenkins,Dominick,NULL,Male,African-American,10/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +59636,68379,61997,PRETRIAL,Jenkins,Dominick,NULL,Male,African-American,10/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59643,68387,62004,PRETRIAL,Cruz,Andy,NULL,Male,Caucasian,02/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +59643,68387,62004,PRETRIAL,Cruz,Andy,NULL,Male,Caucasian,02/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +59643,68387,62004,PRETRIAL,Cruz,Andy,NULL,Male,Caucasian,02/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59658,68402,62019,Probation,EHRLICK,GARY,NULL,Male,Caucasian,08/09/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +59658,68402,62019,Probation,EHRLICK,GARY,NULL,Male,Caucasian,08/09/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +59658,68402,62019,Probation,EHRLICK,GARY,NULL,Male,Caucasian,08/09/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53789,68395,62012,PRETRIAL,MIONE,HEIDI,NULL,Female,Caucasian,01/28/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +53789,68395,62012,PRETRIAL,MIONE,HEIDI,NULL,Female,Caucasian,01/28/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +53789,68395,62012,PRETRIAL,MIONE,HEIDI,NULL,Female,Caucasian,01/28/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +59664,68410,62026,PRETRIAL,mcnaughton,gail,NULL,Female,Caucasian,06/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/13/13 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +59664,68410,62026,PRETRIAL,mcnaughton,gail,NULL,Female,Caucasian,06/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +59664,68410,62026,PRETRIAL,mcnaughton,gail,NULL,Female,Caucasian,06/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +31140,68374,61993,PRETRIAL,Peschard,Eugenio,NULL,Male,Hispanic,03/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +31140,68374,61993,PRETRIAL,Peschard,Eugenio,NULL,Male,Hispanic,03/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +31140,68374,61993,PRETRIAL,Peschard,Eugenio,NULL,Male,Hispanic,03/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59638,68381,61999,PRETRIAL,Jarrett,Antonio,NULL,Male,African-American,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +59638,68381,61999,PRETRIAL,Jarrett,Antonio,NULL,Male,African-American,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +59638,68381,61999,PRETRIAL,Jarrett,Antonio,NULL,Male,African-American,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59650,68394,62011,PRETRIAL,CORKER,LIAS,NULL,Male,African-American,11/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.22,8,High,New,1,0 +59650,68394,62011,PRETRIAL,CORKER,LIAS,NULL,Male,African-American,11/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +59650,68394,62011,PRETRIAL,CORKER,LIAS,NULL,Male,African-American,11/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59665,68411,62027,Probation,ECHEVERRY,JEFFREY,NULL,Male,Hispanic,07/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/13/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +59665,68411,62027,Probation,ECHEVERRY,JEFFREY,NULL,Male,Hispanic,07/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +59665,68411,62027,Probation,ECHEVERRY,JEFFREY,NULL,Male,Hispanic,07/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59646,68390,62007,PRETRIAL,Steffen,Anthony,NULL,Male,Caucasian,03/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.82,9,High,New,1,0 +59646,68390,62007,PRETRIAL,Steffen,Anthony,NULL,Male,Caucasian,03/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +59646,68390,62007,PRETRIAL,Steffen,Anthony,NULL,Male,Caucasian,03/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +34331,68408,33475,PRETRIAL,Brown,Robie,NULL,Male,African-American,11/28/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +34331,68408,33475,PRETRIAL,Brown,Robie,NULL,Male,African-American,11/28/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,4,High,8,Risk of Recidivism,0.55,9,High,New,1,0 +34331,68408,33475,PRETRIAL,Brown,Robie,NULL,Male,African-American,11/28/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/13/13 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +59642,68385,62003,PRETRIAL,Bowen-Dixon,Hannahlelh,NULL,Female,African-American,01/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/13/13 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +59642,68385,62003,PRETRIAL,Bowen-Dixon,Hannahlelh,NULL,Female,African-American,01/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +59642,68385,62003,PRETRIAL,Bowen-Dixon,Hannahlelh,NULL,Female,African-American,01/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59635,68378,61996,PRETRIAL,Dillon,Michael,NULL,Male,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +59635,68378,61996,PRETRIAL,Dillon,Michael,NULL,Male,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +59635,68378,61996,PRETRIAL,Dillon,Michael,NULL,Male,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59648,68392,62009,Probation,COBB,CYNTHIA,NULL,Female,Caucasian,08/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +59648,68392,62009,Probation,COBB,CYNTHIA,NULL,Female,Caucasian,08/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +59648,68392,62009,Probation,COBB,CYNTHIA,NULL,Female,Caucasian,08/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59654,68399,62016,Probation,Lozea,Lori,NULL,Female,Caucasian,06/06/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/13/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +59654,68399,62016,Probation,Lozea,Lori,NULL,Female,Caucasian,06/06/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +59654,68399,62016,Probation,Lozea,Lori,NULL,Female,Caucasian,06/06/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53312,68406,62023,PRETRIAL,Gonzalez-Estrella,Carlos,J,Male,Hispanic,09/08/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/13/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +53312,68406,62023,PRETRIAL,Gonzalez-Estrella,Carlos,J,Male,Hispanic,09/08/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/13/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +53312,68406,62023,PRETRIAL,Gonzalez-Estrella,Carlos,J,Male,Hispanic,09/08/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/13/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59667,68413,62029,PRETRIAL,TURBAY,DANIEL,NULL,Male,Caucasian,05/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +59667,68413,62029,PRETRIAL,TURBAY,DANIEL,NULL,Male,Caucasian,05/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +59667,68413,62029,PRETRIAL,TURBAY,DANIEL,NULL,Male,Caucasian,05/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59668,68415,62030,PRETRIAL,SMITH,KENNETH,NULL,Female,African-American,12/01/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.63,2,Low,New,1,0 +59668,68415,62030,PRETRIAL,SMITH,KENNETH,NULL,Female,African-American,12/01/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +59668,68415,62030,PRETRIAL,SMITH,KENNETH,NULL,Female,African-American,12/01/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +59678,68423,62038,PRETRIAL,Simpson,Michael,NULL,Male,African-American,08/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +59678,68423,62038,PRETRIAL,Simpson,Michael,NULL,Male,African-American,08/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +59678,68423,62038,PRETRIAL,Simpson,Michael,NULL,Male,African-American,08/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59671,68418,62033,PRETRIAL,Williams,Stephanie,NULL,Female,African-American,10/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +59671,68418,62033,PRETRIAL,Williams,Stephanie,NULL,Female,African-American,10/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +59671,68418,62033,PRETRIAL,Williams,Stephanie,NULL,Female,African-American,10/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59669,68416,62031,PRETRIAL,Sinclair,Christopher,W,Male,Other,02/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +59669,68416,62031,PRETRIAL,Sinclair,Christopher,W,Male,Other,02/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +59669,68416,62031,PRETRIAL,Sinclair,Christopher,W,Male,Other,02/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59672,68421,62036,PRETRIAL,Santiago-Ortiz,Carlos,NULL,Male,Hispanic,08/21/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/14/13 0:00,1,Low,7,Risk of Violence,-4.43,1,Low,New,1,0 +59672,68421,62036,PRETRIAL,Santiago-Ortiz,Carlos,NULL,Male,Hispanic,08/21/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/14/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +59672,68421,62036,PRETRIAL,Santiago-Ortiz,Carlos,NULL,Male,Hispanic,08/21/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/14/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59679,68424,62039,PRETRIAL,Bractley,Trenton,Devon,Male,African-American,09/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +59679,68424,62039,PRETRIAL,Bractley,Trenton,Devon,Male,African-American,09/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +59679,68424,62039,PRETRIAL,Bractley,Trenton,Devon,Male,African-American,09/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59680,68425,62040,PRETRIAL,Angulo,Alvaro,Enrique,Male,Caucasian,09/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +59680,68425,62040,PRETRIAL,Angulo,Alvaro,Enrique,Male,Caucasian,09/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +59680,68425,62040,PRETRIAL,Angulo,Alvaro,Enrique,Male,Caucasian,09/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59670,68417,62032,PRETRIAL,Jemmott,Marvon,NULL,Male,African-American,01/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +59670,68417,62032,PRETRIAL,Jemmott,Marvon,NULL,Male,African-American,01/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +59670,68417,62032,PRETRIAL,Jemmott,Marvon,NULL,Male,African-American,01/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58054,68414,60237,PRETRIAL,Foy,Patrick,NULL,Male,African-American,02/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,4,High,7,Risk of Violence,-0.94,9,High,Copy,1,0 +58054,68414,60237,PRETRIAL,Foy,Patrick,NULL,Male,African-American,02/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,4,High,8,Risk of Recidivism,0.85,10,High,Copy,1,0 +58054,68414,60237,PRETRIAL,Foy,Patrick,NULL,Male,African-American,02/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +59677,68422,62037,PRETRIAL,Lampert,Danyelle,NULL,Female,Caucasian,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +59677,68422,62037,PRETRIAL,Lampert,Danyelle,NULL,Female,Caucasian,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +59677,68422,62037,PRETRIAL,Lampert,Danyelle,NULL,Female,Caucasian,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59689,68435,62049,PRETRIAL,Rolle,Leroy,John,Male,African-American,02/08/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/15/13 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +59689,68435,62049,PRETRIAL,Rolle,Leroy,John,Male,African-American,02/08/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/15/13 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +59689,68435,62049,PRETRIAL,Rolle,Leroy,John,Male,African-American,02/08/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59683,68430,62044,PRETRIAL,RAPISARDA,TIBERIO,NULL,Male,Caucasian,08/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/15/13 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +59683,68430,62044,PRETRIAL,RAPISARDA,TIBERIO,NULL,Male,Caucasian,08/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/15/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +59683,68430,62044,PRETRIAL,RAPISARDA,TIBERIO,NULL,Male,Caucasian,08/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59685,68432,62046,PRETRIAL,PALACIOS,ALEJANDRA,LEONORE,Female,Caucasian,08/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +59685,68432,62046,PRETRIAL,PALACIOS,ALEJANDRA,LEONORE,Female,Caucasian,08/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +59685,68432,62046,PRETRIAL,PALACIOS,ALEJANDRA,LEONORE,Female,Caucasian,08/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59692,68438,62052,PRETRIAL,Urrea,Daniel,NULL,Male,Caucasian,11/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/15/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +59692,68438,62052,PRETRIAL,Urrea,Daniel,NULL,Male,Caucasian,11/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/15/13 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +59692,68438,62052,PRETRIAL,Urrea,Daniel,NULL,Male,Caucasian,11/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +32144,68428,62042,PRETRIAL,Collins,Andre,Tremael,Male,African-American,03/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +32144,68428,62042,PRETRIAL,Collins,Andre,Tremael,Male,African-American,03/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +32144,68428,62042,PRETRIAL,Collins,Andre,Tremael,Male,African-American,03/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +59694,68442,62054,PRETRIAL,Crawford,Garrick,Allen,Male,Caucasian,11/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +59694,68442,62054,PRETRIAL,Crawford,Garrick,Allen,Male,Caucasian,11/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,4,High,8,Risk of Recidivism,0.18,8,High,New,1,0 +59694,68442,62054,PRETRIAL,Crawford,Garrick,Allen,Male,Caucasian,11/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59691,68437,62051,PRETRIAL,Muselaire,Ghislene,NULL,Female,African-American,07/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +59691,68437,62051,PRETRIAL,Muselaire,Ghislene,NULL,Female,African-American,07/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +59691,68437,62051,PRETRIAL,Muselaire,Ghislene,NULL,Female,African-American,07/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +10438,68426,37333,PRETRIAL,Sims,Calvin,NULL,Male,African-American,01/31/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/15/13 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,Copy,1,0 +10438,68426,37333,PRETRIAL,Sims,Calvin,NULL,Male,African-American,01/31/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/15/13 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,Copy,1,0 +10438,68426,37333,PRETRIAL,Sims,Calvin,NULL,Male,African-American,01/31/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/15/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +59684,68431,62045,PRETRIAL,ALTENOR,MARIE,NULL,Female,Other,09/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/15/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +59684,68431,62045,PRETRIAL,ALTENOR,MARIE,NULL,Female,Other,09/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/15/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +59684,68431,62045,PRETRIAL,ALTENOR,MARIE,NULL,Female,Other,09/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/15/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59682,68429,62043,PRETRIAL,Bowen,Cynthia,NULL,Female,African-American,09/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +59682,68429,62043,PRETRIAL,Bowen,Cynthia,NULL,Female,African-American,09/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,10,High,New,1,0 +59682,68429,62043,PRETRIAL,Bowen,Cynthia,NULL,Female,African-American,09/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +59693,68441,62053,PRETRIAL,Miller,Jeremy,NULL,Male,Caucasian,06/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/15/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,Copy,1,0 +59693,68441,62053,PRETRIAL,Miller,Jeremy,NULL,Male,Caucasian,06/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/15/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,Copy,1,0 +59693,68441,62053,PRETRIAL,Miller,Jeremy,NULL,Male,Caucasian,06/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/15/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +59681,68427,62041,PRETRIAL,Jacobs,Marshall,NULL,Male,Caucasian,04/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +59681,68427,62041,PRETRIAL,Jacobs,Marshall,NULL,Male,Caucasian,04/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +59681,68427,62041,PRETRIAL,Jacobs,Marshall,NULL,Male,Caucasian,04/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59686,68434,62048,PRETRIAL,DIAZ,KELVIN,NULL,Male,Caucasian,08/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +59686,68434,62048,PRETRIAL,DIAZ,KELVIN,NULL,Male,Caucasian,08/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +59686,68434,62048,PRETRIAL,DIAZ,KELVIN,NULL,Male,Caucasian,08/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59690,68436,62050,PRETRIAL,Jones,Arrow,NULL,Male,African-American,08/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +59690,68436,62050,PRETRIAL,Jones,Arrow,NULL,Male,African-American,08/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +59690,68436,62050,PRETRIAL,Jones,Arrow,NULL,Male,African-American,08/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +47446,68485,62092,Probation,saunder,danielle,NULL,Female,African-American,05/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +47446,68485,62092,Probation,saunder,danielle,NULL,Female,African-American,05/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +47446,68485,62092,Probation,saunder,danielle,NULL,Female,African-American,05/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59706,68455,62067,PRETRIAL,ALMENDARES,LUIS,NULL,Male,Caucasian,10/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +59706,68455,62067,PRETRIAL,ALMENDARES,LUIS,NULL,Male,Caucasian,10/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +59706,68455,62067,PRETRIAL,ALMENDARES,LUIS,NULL,Male,Caucasian,10/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59707,68457,62069,PRETRIAL,Suarezmesa,Alan,NULL,Male,Caucasian,01/22/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +59707,68457,62069,PRETRIAL,Suarezmesa,Alan,NULL,Male,Caucasian,01/22/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +59707,68457,62069,PRETRIAL,Suarezmesa,Alan,NULL,Male,Caucasian,01/22/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +35031,68464,62076,PRETRIAL,Smith,Nicole,NULL,Female,African-American,12/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +35031,68464,62076,PRETRIAL,Smith,Nicole,NULL,Female,African-American,12/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +35031,68464,62076,PRETRIAL,Smith,Nicole,NULL,Female,African-American,12/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59697,68446,62058,PRETRIAL,PARSONS,STEPHEN,NULL,Male,Caucasian,01/21/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +59697,68446,62058,PRETRIAL,PARSONS,STEPHEN,NULL,Male,Caucasian,01/21/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +59697,68446,62058,PRETRIAL,PARSONS,STEPHEN,NULL,Male,Caucasian,01/21/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +59701,68450,62062,PRETRIAL,Stewart,Raquel,NULL,Female,African-American,10/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/16/13 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +59701,68450,62062,PRETRIAL,Stewart,Raquel,NULL,Female,African-American,10/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +59701,68450,62062,PRETRIAL,Stewart,Raquel,NULL,Female,African-American,10/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/16/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59717,68467,62078,PRETRIAL,Bassininsky,Brooke,NULL,Female,Caucasian,11/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/16/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +59717,68467,62078,PRETRIAL,Bassininsky,Brooke,NULL,Female,Caucasian,11/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/16/13 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +59717,68467,62078,PRETRIAL,Bassininsky,Brooke,NULL,Female,Caucasian,11/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +59712,68462,62074,Probation,kiss,pal,NULL,Male,African-American,06/17/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/16/13 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +59712,68462,62074,Probation,kiss,pal,NULL,Male,African-American,06/17/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/16/13 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +59712,68462,62074,Probation,kiss,pal,NULL,Male,African-American,06/17/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59720,68476,62083,Probation,scott,bowen,NULL,Male,Caucasian,05/21/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/16/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +59720,68476,62083,Probation,scott,bowen,NULL,Male,Caucasian,05/21/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/16/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +59720,68476,62083,Probation,scott,bowen,NULL,Male,Caucasian,05/21/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45861,68483,62090,Probation,Laberge,Chad,Michael,Male,Caucasian,02/27/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +45861,68483,62090,Probation,Laberge,Chad,Michael,Male,Caucasian,02/27/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +45861,68483,62090,Probation,Laberge,Chad,Michael,Male,Caucasian,02/27/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59725,68481,62088,PRETRIAL,riffle,david,NULL,Male,Caucasian,08/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +59725,68481,62088,PRETRIAL,riffle,david,NULL,Male,Caucasian,08/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +59725,68481,62088,PRETRIAL,riffle,david,NULL,Male,Caucasian,08/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +32788,68488,31840,PRETRIAL,Jones,Kewuana,NULL,Female,African-American,04/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,Copy,1,0 +32788,68488,31840,PRETRIAL,Jones,Kewuana,NULL,Female,African-American,04/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,Copy,1,0 +32788,68488,31840,PRETRIAL,Jones,Kewuana,NULL,Female,African-American,04/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +59711,68460,62072,Probation,Laboy,Abraham,NULL,Male,Caucasian,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.19,4,Low,New,1,0 +59711,68460,62072,Probation,Laboy,Abraham,NULL,Male,Caucasian,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +59711,68460,62072,Probation,Laboy,Abraham,NULL,Male,Caucasian,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +59716,68468,62077,PRETRIAL,CANNON,ROBERT,NULL,Male,African-American,01/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,Copy,1,0 +59716,68468,62077,PRETRIAL,CANNON,ROBERT,NULL,Male,African-American,01/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +59716,68468,62077,PRETRIAL,CANNON,ROBERT,NULL,Male,African-American,01/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +59695,68444,62056,PRETRIAL,ASHEN,STELLA,NULL,Female,Caucasian,01/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +59695,68444,62056,PRETRIAL,ASHEN,STELLA,NULL,Female,Caucasian,01/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +59695,68444,62056,PRETRIAL,ASHEN,STELLA,NULL,Female,Caucasian,01/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59698,68447,62059,PRETRIAL,CHU,KOLSON,NULL,Male,Asian,03/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +59698,68447,62059,PRETRIAL,CHU,KOLSON,NULL,Male,Asian,03/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +59698,68447,62059,PRETRIAL,CHU,KOLSON,NULL,Male,Asian,03/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59704,68452,62064,PRETRIAL,Stfleur,Nickles,NULL,Male,African-American,09/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.15,8,High,New,1,0 +59704,68452,62064,PRETRIAL,Stfleur,Nickles,NULL,Male,African-American,09/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +59704,68452,62064,PRETRIAL,Stfleur,Nickles,NULL,Male,African-American,09/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59727,68486,62093,Probation,MATHIS,KAMARON,D,Male,African-American,11/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +59727,68486,62093,Probation,MATHIS,KAMARON,D,Male,African-American,11/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +59727,68486,62093,Probation,MATHIS,KAMARON,D,Male,African-American,11/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59719,68473,62081,Probation,morris,kortney,NULL,Female,African-American,09/01/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +59719,68473,62081,Probation,morris,kortney,NULL,Female,African-American,09/01/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,9,High,New,1,0 +59719,68473,62081,Probation,morris,kortney,NULL,Female,African-American,09/01/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59705,68454,62066,PRETRIAL,Bligen,Saleem,NULL,Male,African-American,12/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +59705,68454,62066,PRETRIAL,Bligen,Saleem,NULL,Male,African-American,12/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +59705,68454,62066,PRETRIAL,Bligen,Saleem,NULL,Male,African-American,12/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +59726,68484,62091,Probation,Delgado,Vincent,NULL,Male,Hispanic,11/26/46,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,12/16/13 0:00,2,Medium,7,Risk of Violence,-3.13,1,Low,New,1,0 +59726,68484,62091,Probation,Delgado,Vincent,NULL,Male,Hispanic,11/26/46,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,12/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +59726,68484,62091,Probation,Delgado,Vincent,NULL,Male,Hispanic,11/26/46,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,12/16/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59723,68479,62086,Probation,jackson,marshall,NULL,Male,African-American,11/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/16/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +59723,68479,62086,Probation,jackson,marshall,NULL,Male,African-American,11/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/16/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +59723,68479,62086,Probation,jackson,marshall,NULL,Male,African-American,11/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +19319,68472,18560,PRETRIAL,PEREZ,LAZARO,NULL,Male,Hispanic,12/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.09,8,High,Copy,1,0 +19319,68472,18560,PRETRIAL,PEREZ,LAZARO,NULL,Male,Hispanic,12/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +19319,68472,18560,PRETRIAL,PEREZ,LAZARO,NULL,Male,Hispanic,12/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +59721,68477,62084,PRETRIAL,Mckinley,Joseph,NULL,Male,African-American,11/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +59721,68477,62084,PRETRIAL,Mckinley,Joseph,NULL,Male,African-American,11/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +59721,68477,62084,PRETRIAL,Mckinley,Joseph,NULL,Male,African-American,11/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59700,68449,62061,PRETRIAL,Phillips,Victoria,Elaine,Female,African-American,05/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +59700,68449,62061,PRETRIAL,Phillips,Victoria,Elaine,Female,African-American,05/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +59700,68449,62061,PRETRIAL,Phillips,Victoria,Elaine,Female,African-American,05/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +48793,68456,62068,Probation,Rivera,Adam,NULL,Male,Hispanic,07/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +48793,68456,62068,Probation,Rivera,Adam,NULL,Male,Hispanic,07/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +48793,68456,62068,Probation,Rivera,Adam,NULL,Male,Hispanic,07/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55439,68470,62080,PRETRIAL,ALINSTANT,JACQUES,NULL,Male,Other,08/20/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/16/13 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +55439,68470,62080,PRETRIAL,ALINSTANT,JACQUES,NULL,Male,Other,08/20/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/16/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +55439,68470,62080,PRETRIAL,ALINSTANT,JACQUES,NULL,Male,Other,08/20/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +45475,68474,62082,PRETRIAL,Barrientos,Henry,NULL,Male,Caucasian,02/26/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/16/13 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +45475,68474,62082,PRETRIAL,Barrientos,Henry,NULL,Male,Caucasian,02/26/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/16/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +45475,68474,62082,PRETRIAL,Barrientos,Henry,NULL,Male,Caucasian,02/26/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/16/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59696,68445,62057,PRETRIAL,JAMES,NAITA,NULL,Female,African-American,09/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +59696,68445,62057,PRETRIAL,JAMES,NAITA,NULL,Female,African-American,09/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +59696,68445,62057,PRETRIAL,JAMES,NAITA,NULL,Female,African-American,09/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +36957,68459,62071,PRETRIAL,Walker,Meshack,NULL,Male,African-American,09/01/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/16/13 0:00,4,High,7,Risk of Violence,-0.97,9,High,New,1,0 +36957,68459,62071,PRETRIAL,Walker,Meshack,NULL,Male,African-American,09/01/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/16/13 0:00,4,High,8,Risk of Recidivism,0.33,9,High,New,1,0 +36957,68459,62071,PRETRIAL,Walker,Meshack,NULL,Male,African-American,09/01/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/16/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59272,68466,61574,PRETRIAL,Slovinski,Mateus,NULL,Male,Caucasian,10/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.1,8,High,Copy,1,0 +59272,68466,61574,PRETRIAL,Slovinski,Mateus,NULL,Male,Caucasian,10/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.15,6,Medium,Copy,1,0 +59272,68466,61574,PRETRIAL,Slovinski,Mateus,NULL,Male,Caucasian,10/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +59702,68451,62063,PRETRIAL,Holness,Kimberly,NULL,Female,African-American,11/05/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +59702,68451,62063,PRETRIAL,Holness,Kimberly,NULL,Female,African-American,11/05/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +59702,68451,62063,PRETRIAL,Holness,Kimberly,NULL,Female,African-American,11/05/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59703,68453,62065,PRETRIAL,Mozart,Samuel,NULL,Male,African-American,07/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/16/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +59703,68453,62065,PRETRIAL,Mozart,Samuel,NULL,Male,African-American,07/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/16/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +59703,68453,62065,PRETRIAL,Mozart,Samuel,NULL,Male,African-American,07/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59728,68487,62094,Probation,golovina,tatyana,NULL,Female,Caucasian,03/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,2,Medium,7,Risk of Violence,-2.73,2,Low,New,1,0 +59728,68487,62094,Probation,golovina,tatyana,NULL,Female,Caucasian,03/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +59728,68487,62094,Probation,golovina,tatyana,NULL,Female,Caucasian,03/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/16/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59718,68469,62079,PRETRIAL,STARKEY,WILLIE,NULL,Male,African-American,03/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +59718,68469,62079,PRETRIAL,STARKEY,WILLIE,NULL,Male,African-American,03/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +59718,68469,62079,PRETRIAL,STARKEY,WILLIE,NULL,Male,African-American,03/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59699,68448,62060,PRETRIAL,DENNIS,GREGORY,NULL,Male,African-American,08/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/16/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +59699,68448,62060,PRETRIAL,DENNIS,GREGORY,NULL,Male,African-American,08/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/16/13 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +59699,68448,62060,PRETRIAL,DENNIS,GREGORY,NULL,Male,African-American,08/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54836,68443,62055,PRETRIAL,ACEVEDO,CHASITY,JASALENE,Female,Caucasian,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +54836,68443,62055,PRETRIAL,ACEVEDO,CHASITY,JASALENE,Female,Caucasian,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +54836,68443,62055,PRETRIAL,ACEVEDO,CHASITY,JASALENE,Female,Caucasian,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59710,68461,62073,PRETRIAL,GRIFFITH,QUITA,NULL,Female,African-American,12/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +59710,68461,62073,PRETRIAL,GRIFFITH,QUITA,NULL,Female,African-American,12/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +59710,68461,62073,PRETRIAL,GRIFFITH,QUITA,NULL,Female,African-American,12/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59762,68511,62115,Probation,gil,david,NULL,Male,Caucasian,07/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/17/13 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +59762,68511,62115,Probation,gil,david,NULL,Male,Caucasian,07/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +59762,68511,62115,Probation,gil,david,NULL,Male,Caucasian,07/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59777,68529,62131,Probation,michael,david,NULL,Male,Caucasian,12/28/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +59777,68529,62131,Probation,michael,david,NULL,Male,Caucasian,12/28/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +59777,68529,62131,Probation,michael,david,NULL,Male,Caucasian,12/28/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59729,68490,62095,PRETRIAL,Morales,Miguel,NULL,Male,Caucasian,05/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +59729,68490,62095,PRETRIAL,Morales,Miguel,NULL,Male,Caucasian,05/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +59729,68490,62095,PRETRIAL,Morales,Miguel,NULL,Male,Caucasian,05/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +34335,68508,62112,PRETRIAL,rosario,victor,NULL,Male,Caucasian,05/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +34335,68508,62112,PRETRIAL,rosario,victor,NULL,Male,Caucasian,05/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +34335,68508,62112,PRETRIAL,rosario,victor,NULL,Male,Caucasian,05/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59766,68516,62119,PRETRIAL,FARLOW,RICKY,NULL,Male,African-American,06/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.23,8,High,New,1,0 +59766,68516,62119,PRETRIAL,FARLOW,RICKY,NULL,Male,African-American,06/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +59766,68516,62119,PRETRIAL,FARLOW,RICKY,NULL,Male,African-American,06/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59740,68503,62108,PRETRIAL,Woodson,Michael,Melvin,Male,Caucasian,12/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +59740,68503,62108,PRETRIAL,Woodson,Michael,Melvin,Male,Caucasian,12/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +59740,68503,62108,PRETRIAL,Woodson,Michael,Melvin,Male,Caucasian,12/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59780,68532,62134,Probation,Antoine,Rachel,NULL,Female,African-American,01/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +59780,68532,62134,Probation,Antoine,Rachel,NULL,Female,African-American,01/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +59780,68532,62134,Probation,Antoine,Rachel,NULL,Female,African-American,01/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59734,68495,62100,PRETRIAL,Porter,Anton,NULL,Male,Other,11/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.36,3,Low,New,1,0 +59734,68495,62100,PRETRIAL,Porter,Anton,NULL,Male,Other,11/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +59734,68495,62100,PRETRIAL,Porter,Anton,NULL,Male,Other,11/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59770,68521,62123,Probation,Wright,Ronald,NULL,Male,African-American,05/10/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +59770,68521,62123,Probation,Wright,Ronald,NULL,Male,African-American,05/10/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +59770,68521,62123,Probation,Wright,Ronald,NULL,Male,African-American,05/10/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59730,68491,62096,PRETRIAL,MAGNUS,GERALD,GERROD,Male,African-American,05/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +59730,68491,62096,PRETRIAL,MAGNUS,GERALD,GERROD,Male,African-American,05/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +59730,68491,62096,PRETRIAL,MAGNUS,GERALD,GERROD,Male,African-American,05/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +59736,68498,62103,PRETRIAL,Benzing,Gina,May,Female,Caucasian,06/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +59736,68498,62103,PRETRIAL,Benzing,Gina,May,Female,Caucasian,06/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +59736,68498,62103,PRETRIAL,Benzing,Gina,May,Female,Caucasian,06/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59737,68500,62105,PRETRIAL,White,Phillipe,NULL,Male,Other,06/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/17/13 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +59737,68500,62105,PRETRIAL,White,Phillipe,NULL,Male,Other,06/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +59737,68500,62105,PRETRIAL,White,Phillipe,NULL,Male,Other,06/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +17688,68528,62130,PRETRIAL,PAVONE,MICHAEL,T,Male,Caucasian,01/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,7,Risk of Violence,-2.78,2,Low,New,1,0 +17688,68528,62130,PRETRIAL,PAVONE,MICHAEL,T,Male,Caucasian,01/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +17688,68528,62130,PRETRIAL,PAVONE,MICHAEL,T,Male,Caucasian,01/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +42945,68540,62141,PRETRIAL,BLAIR,GEORGE,VERCILE,Male,Caucasian,12/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +42945,68540,62141,PRETRIAL,BLAIR,GEORGE,VERCILE,Male,Caucasian,12/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +42945,68540,62141,PRETRIAL,BLAIR,GEORGE,VERCILE,Male,Caucasian,12/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59732,68493,62098,PRETRIAL,Gilner,Dominique,NULL,Male,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/17/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +59732,68493,62098,PRETRIAL,Gilner,Dominique,NULL,Male,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +59732,68493,62098,PRETRIAL,Gilner,Dominique,NULL,Male,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59783,68535,62137,Probation,wise,ryan,NULL,Male,African-American,01/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +59783,68535,62137,Probation,wise,ryan,NULL,Male,African-American,01/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +59783,68535,62137,Probation,wise,ryan,NULL,Male,African-American,01/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59741,68505,62110,PRETRIAL,Whittaker,Jamielle,NULL,Female,Other,02/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +59741,68505,62110,PRETRIAL,Whittaker,Jamielle,NULL,Female,Other,02/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +59741,68505,62110,PRETRIAL,Whittaker,Jamielle,NULL,Female,Other,02/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59764,68514,62117,Probation,Eslahi,Shahram,NULL,Male,Other,07/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +59764,68514,62117,Probation,Eslahi,Shahram,NULL,Male,Other,07/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +59764,68514,62117,Probation,Eslahi,Shahram,NULL,Male,Other,07/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59756,68507,62111,PRETRIAL,SMITH,LEROME,NULL,Male,African-American,12/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/17/13 0:00,2,Medium,7,Risk of Violence,-1.27,7,Medium,New,1,0 +59756,68507,62111,PRETRIAL,SMITH,LEROME,NULL,Male,African-American,12/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +59756,68507,62111,PRETRIAL,SMITH,LEROME,NULL,Male,African-American,12/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/17/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59786,68541,62142,PRETRIAL,Magnum,Brabara,NULL,Female,Caucasian,11/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/17/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +59786,68541,62142,PRETRIAL,Magnum,Brabara,NULL,Female,Caucasian,11/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +59786,68541,62142,PRETRIAL,Magnum,Brabara,NULL,Female,Caucasian,11/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59769,68520,62122,Probation,Galan,Jairo,NULL,Male,Hispanic,09/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +59769,68520,62122,Probation,Galan,Jairo,NULL,Male,Hispanic,09/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +59769,68520,62122,Probation,Galan,Jairo,NULL,Male,Hispanic,09/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59765,68515,62118,Probation,White,Phillip,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +59765,68515,62118,Probation,White,Phillip,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +59765,68515,62118,Probation,White,Phillip,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59781,68533,62135,Probation,BROWN,SAMANTHA,BERNITA,Female,African-American,04/12/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +59781,68533,62135,Probation,BROWN,SAMANTHA,BERNITA,Female,African-American,04/12/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +59781,68533,62135,Probation,BROWN,SAMANTHA,BERNITA,Female,African-American,04/12/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59733,68494,62099,PRETRIAL,TANAKA,KEN,NULL,Male,Other,10/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/17/13 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +59733,68494,62099,PRETRIAL,TANAKA,KEN,NULL,Male,Other,10/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/17/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +59733,68494,62099,PRETRIAL,TANAKA,KEN,NULL,Male,Other,10/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59763,68512,62116,PRETRIAL,Haynes,James,Richard,Male,Caucasian,09/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/17/13 0:00,4,High,7,Risk of Violence,-0.61,10,High,New,1,0 +59763,68512,62116,PRETRIAL,Haynes,James,Richard,Male,Caucasian,09/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/17/13 0:00,4,High,8,Risk of Recidivism,0.71,10,High,New,1,0 +59763,68512,62116,PRETRIAL,Haynes,James,Richard,Male,Caucasian,09/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/17/13 0:00,4,High,18,Risk of Failure to Appear,35,10,High,New,1,0 +59739,68502,62107,PRETRIAL,Hafford,Michael,Phillip,Male,Caucasian,12/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +59739,68502,62107,PRETRIAL,Hafford,Michael,Phillip,Male,Caucasian,12/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +59739,68502,62107,PRETRIAL,Hafford,Michael,Phillip,Male,Caucasian,12/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +23464,68504,62109,PRETRIAL,POWELL,PHILLIP,NULL,Male,African-American,03/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +23464,68504,62109,PRETRIAL,POWELL,PHILLIP,NULL,Male,African-American,03/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +23464,68504,62109,PRETRIAL,POWELL,PHILLIP,NULL,Male,African-American,03/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59767,68517,62120,Probation,Vassell,Kareen,NULL,Male,African-American,03/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +59767,68517,62120,Probation,Vassell,Kareen,NULL,Male,African-American,03/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +59767,68517,62120,Probation,Vassell,Kareen,NULL,Male,African-American,03/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +27125,68489,53499,PRETRIAL,Johnson,Ernest,J,Male,African-American,10/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,Copy,1,0 +27125,68489,53499,PRETRIAL,Johnson,Ernest,J,Male,African-American,10/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,Copy,1,0 +27125,68489,53499,PRETRIAL,Johnson,Ernest,J,Male,African-American,10/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +59774,68525,62127,Probation,Jaquez,Awilda,NULL,Female,Hispanic,08/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,12/17/13 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +59774,68525,62127,Probation,Jaquez,Awilda,NULL,Female,Hispanic,08/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +59774,68525,62127,Probation,Jaquez,Awilda,NULL,Female,Hispanic,08/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59778,68530,62132,Probation,OBERDE,AURELUS,NULL,Male,African-American,11/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +59778,68530,62132,Probation,OBERDE,AURELUS,NULL,Male,African-American,11/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +59778,68530,62132,Probation,OBERDE,AURELUS,NULL,Male,African-American,11/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59735,68496,62101,PRETRIAL,Jarrett,Donald,Jehmalla,Male,African-American,11/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +59735,68496,62101,PRETRIAL,Jarrett,Donald,Jehmalla,Male,African-American,11/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +59735,68496,62101,PRETRIAL,Jarrett,Donald,Jehmalla,Male,African-American,11/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59760,68509,62113,PRETRIAL,GABRIELE,CARLOS,NULL,Male,Hispanic,02/27/86,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +59760,68509,62113,PRETRIAL,GABRIELE,CARLOS,NULL,Male,Hispanic,02/27/86,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +59760,68509,62113,PRETRIAL,GABRIELE,CARLOS,NULL,Male,Hispanic,02/27/86,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59761,68510,62114,Probation,Cruz,Carlos,NULL,Male,Hispanic,09/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +59761,68510,62114,Probation,Cruz,Carlos,NULL,Male,Hispanic,09/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +59761,68510,62114,Probation,Cruz,Carlos,NULL,Male,Hispanic,09/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59779,68531,62133,Probation,brown,bartholomew,NULL,Male,African-American,07/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +59779,68531,62133,Probation,brown,bartholomew,NULL,Male,African-American,07/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +59779,68531,62133,Probation,brown,bartholomew,NULL,Male,African-American,07/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59771,68522,62124,PRETRIAL,Kiester,Kenneth,NULL,Male,Caucasian,01/13/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/17/13 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +59771,68522,62124,PRETRIAL,Kiester,Kenneth,NULL,Male,Caucasian,01/13/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/17/13 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +59771,68522,62124,PRETRIAL,Kiester,Kenneth,NULL,Male,Caucasian,01/13/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59738,68501,62106,PRETRIAL,HENDRICKS,CHRISTOPHER,NULL,Male,Caucasian,07/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,New,1,0 +59738,68501,62106,PRETRIAL,HENDRICKS,CHRISTOPHER,NULL,Male,Caucasian,07/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +59738,68501,62106,PRETRIAL,HENDRICKS,CHRISTOPHER,NULL,Male,Caucasian,07/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59768,68518,62121,Probation,Antimucci,Franco,NULL,Male,Hispanic,10/03/42,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,7,Risk of Violence,-4.5,1,Low,New,1,0 +59768,68518,62121,Probation,Antimucci,Franco,NULL,Male,Hispanic,10/03/42,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +59768,68518,62121,Probation,Antimucci,Franco,NULL,Male,Hispanic,10/03/42,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +25542,68539,62140,PRETRIAL,BRENNEMAN,RICHARD,MATTHEW,Male,Caucasian,06/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +25542,68539,62140,PRETRIAL,BRENNEMAN,RICHARD,MATTHEW,Male,Caucasian,06/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +25542,68539,62140,PRETRIAL,BRENNEMAN,RICHARD,MATTHEW,Male,Caucasian,06/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +59782,68534,62136,Probation,MCDOUGLE,TIMOTHY,NULL,Male,African-American,11/03/79,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +59782,68534,62136,Probation,MCDOUGLE,TIMOTHY,NULL,Male,African-American,11/03/79,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +59782,68534,62136,Probation,MCDOUGLE,TIMOTHY,NULL,Male,African-American,11/03/79,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,8,High,New,1,0 +53880,68536,62138,PRETRIAL,SHARPE,TASHESHIA,NULL,Female,African-American,07/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +53880,68536,62138,PRETRIAL,SHARPE,TASHESHIA,NULL,Female,African-American,07/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +53880,68536,62138,PRETRIAL,SHARPE,TASHESHIA,NULL,Female,African-American,07/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59731,68492,62097,PRETRIAL,SANDERS,CURTIS,LEON,Male,African-American,03/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +59731,68492,62097,PRETRIAL,SANDERS,CURTIS,LEON,Male,African-American,03/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +59731,68492,62097,PRETRIAL,SANDERS,CURTIS,LEON,Male,African-American,03/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +59775,68527,62129,Probation,hernandez,ramona,NULL,Male,Hispanic,06/19/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/17/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +59775,68527,62129,Probation,hernandez,ramona,NULL,Male,Hispanic,06/19/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/17/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +59775,68527,62129,Probation,hernandez,ramona,NULL,Male,Hispanic,06/19/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +8012,68499,62104,PRETRIAL,KENT,RAYNARD,NULL,Male,African-American,10/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +8012,68499,62104,PRETRIAL,KENT,RAYNARD,NULL,Male,African-American,10/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +8012,68499,62104,PRETRIAL,KENT,RAYNARD,NULL,Male,African-American,10/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59350,68506,61670,PRETRIAL,Jones,Edith,NULL,Female,Caucasian,02/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,Copy,1,0 +59350,68506,61670,PRETRIAL,Jones,Edith,NULL,Female,Caucasian,02/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,Copy,1,0 +59350,68506,61670,PRETRIAL,Jones,Edith,NULL,Female,Caucasian,02/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +59812,68578,62176,Probation,Archon,Nicole,NULL,Female,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/18/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +59812,68578,62176,Probation,Archon,Nicole,NULL,Female,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/18/13 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +59812,68578,62176,Probation,Archon,Nicole,NULL,Female,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59795,68555,62154,PRETRIAL,Taylor,Zebedee,NULL,Male,African-American,11/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/18/13 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +59795,68555,62154,PRETRIAL,Taylor,Zebedee,NULL,Male,African-American,11/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/18/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +59795,68555,62154,PRETRIAL,Taylor,Zebedee,NULL,Male,African-American,11/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +36477,68557,62156,PRETRIAL,Lindo,Leon,NULL,Male,African-American,03/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +36477,68557,62156,PRETRIAL,Lindo,Leon,NULL,Male,African-American,03/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,4,High,8,Risk of Recidivism,1.13,10,High,New,1,0 +36477,68557,62156,PRETRIAL,Lindo,Leon,NULL,Male,African-American,03/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59802,68564,62163,PRETRIAL,Hanna,Albert,NULL,Male,African-American,03/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +59802,68564,62163,PRETRIAL,Hanna,Albert,NULL,Male,African-American,03/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +59802,68564,62163,PRETRIAL,Hanna,Albert,NULL,Male,African-American,03/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +23545,68548,62149,PRETRIAL,Bradley,Terry,NULL,Male,African-American,08/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +23545,68548,62149,PRETRIAL,Bradley,Terry,NULL,Male,African-American,08/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +23545,68548,62149,PRETRIAL,Bradley,Terry,NULL,Male,African-American,08/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51087,68552,62151,PRETRIAL,Metayer,Markendy,NULL,Male,African-American,12/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +51087,68552,62151,PRETRIAL,Metayer,Markendy,NULL,Male,African-American,12/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,4,High,8,Risk of Recidivism,0.81,10,High,New,1,0 +51087,68552,62151,PRETRIAL,Metayer,Markendy,NULL,Male,African-American,12/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +33232,68569,62168,Probation,francois,sandy,NULL,Female,African-American,09/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +33232,68569,62168,Probation,francois,sandy,NULL,Female,African-American,09/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.17,7,Medium,New,1,0 +33232,68569,62168,Probation,francois,sandy,NULL,Female,African-American,09/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59805,68567,62166,Probation,Garcia,Felix,NULL,Male,Hispanic,11/14/77,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,12/18/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +59805,68567,62166,Probation,Garcia,Felix,NULL,Male,Hispanic,11/14/77,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,12/18/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +59805,68567,62166,Probation,Garcia,Felix,NULL,Male,Hispanic,11/14/77,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59791,68546,62147,PRETRIAL,Stremy,Jonathan,NULL,Male,African-American,08/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +59791,68546,62147,PRETRIAL,Stremy,Jonathan,NULL,Male,African-American,08/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +59791,68546,62147,PRETRIAL,Stremy,Jonathan,NULL,Male,African-American,08/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54469,68559,62158,PRETRIAL,Yount,Malcolm,John,Male,Caucasian,02/21/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/18/13 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +54469,68559,62158,PRETRIAL,Yount,Malcolm,John,Male,Caucasian,02/21/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/18/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +54469,68559,62158,PRETRIAL,Yount,Malcolm,John,Male,Caucasian,02/21/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56337,68551,58296,PRETRIAL,DIAZ,ADAM,JOHN,Male,Caucasian,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,Copy,1,0 +56337,68551,58296,PRETRIAL,DIAZ,ADAM,JOHN,Male,Caucasian,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,Copy,1,0 +56337,68551,58296,PRETRIAL,DIAZ,ADAM,JOHN,Male,Caucasian,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +59800,68562,62161,PRETRIAL,CHAJ,EDWIN,NULL,Male,Hispanic,09/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.33,3,Low,New,1,0 +59800,68562,62161,PRETRIAL,CHAJ,EDWIN,NULL,Male,Hispanic,09/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +59800,68562,62161,PRETRIAL,CHAJ,EDWIN,NULL,Male,Hispanic,09/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59808,68572,62171,Probation,Penichet,Darcy,NULL,Male,Caucasian,08/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/18/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +59808,68572,62171,Probation,Penichet,Darcy,NULL,Male,Caucasian,08/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/18/13 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +59808,68572,62171,Probation,Penichet,Darcy,NULL,Male,Caucasian,08/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53081,68554,62153,PRETRIAL,Soto,Ruben,NULL,Male,Caucasian,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.05,8,High,New,1,0 +53081,68554,62153,PRETRIAL,Soto,Ruben,NULL,Male,Caucasian,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +53081,68554,62153,PRETRIAL,Soto,Ruben,NULL,Male,Caucasian,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59811,68575,62174,PRETRIAL,Chamberlain,Rachel,NULL,Female,Caucasian,05/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +59811,68575,62174,PRETRIAL,Chamberlain,Rachel,NULL,Female,Caucasian,05/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +59811,68575,62174,PRETRIAL,Chamberlain,Rachel,NULL,Female,Caucasian,05/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59814,68580,62178,PRETRIAL,Jicka,Laura,NULL,Male,Caucasian,05/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +59814,68580,62178,PRETRIAL,Jicka,Laura,NULL,Male,Caucasian,05/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +59814,68580,62178,PRETRIAL,Jicka,Laura,NULL,Male,Caucasian,05/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54796,68582,62180,PRETRIAL,Rosewell,Steve,NULL,Male,Other,11/02/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/18/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +54796,68582,62180,PRETRIAL,Rosewell,Steve,NULL,Male,Other,11/02/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/18/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +54796,68582,62180,PRETRIAL,Rosewell,Steve,NULL,Male,Other,11/02/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59799,68561,62160,PRETRIAL,valeus,jean,NULL,Male,African-American,11/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +59799,68561,62160,PRETRIAL,valeus,jean,NULL,Male,African-American,11/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +59799,68561,62160,PRETRIAL,valeus,jean,NULL,Male,African-American,11/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59792,68547,62148,PRETRIAL,HERMAN,REGINALD,NULL,Male,African-American,09/22/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/18/13 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +59792,68547,62148,PRETRIAL,HERMAN,REGINALD,NULL,Male,African-American,09/22/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/18/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +59792,68547,62148,PRETRIAL,HERMAN,REGINALD,NULL,Male,African-American,09/22/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59803,68565,62164,PRETRIAL,Gillis,Anderia,NULL,Female,African-American,09/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.26,3,Low,New,1,0 +59803,68565,62164,PRETRIAL,Gillis,Anderia,NULL,Female,African-American,09/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,9,High,New,1,0 +59803,68565,62164,PRETRIAL,Gillis,Anderia,NULL,Female,African-American,09/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +59793,68549,62150,PRETRIAL,Guzman,Maribell,NULL,Female,Hispanic,05/31/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +59793,68549,62150,PRETRIAL,Guzman,Maribell,NULL,Female,Hispanic,05/31/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +59793,68549,62150,PRETRIAL,Guzman,Maribell,NULL,Female,Hispanic,05/31/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59796,68556,62155,PRETRIAL,DEHART,LOUIE,NULL,Male,Caucasian,10/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +59796,68556,62155,PRETRIAL,DEHART,LOUIE,NULL,Male,Caucasian,10/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +59796,68556,62155,PRETRIAL,DEHART,LOUIE,NULL,Male,Caucasian,10/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59801,68563,62162,Probation,LEE,DEVUAN,ANTHONY,Male,African-American,08/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/18/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +59801,68563,62162,Probation,LEE,DEVUAN,ANTHONY,Male,African-American,08/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/18/13 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +59801,68563,62162,Probation,LEE,DEVUAN,ANTHONY,Male,African-American,08/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +32702,68545,62146,PRETRIAL,Delhomme,Dekorian,M,Male,African-American,03/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +32702,68545,62146,PRETRIAL,Delhomme,Dekorian,M,Male,African-American,03/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,4,High,8,Risk of Recidivism,0.9,10,High,New,1,0 +32702,68545,62146,PRETRIAL,Delhomme,Dekorian,M,Male,African-American,03/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59798,68560,62159,Probation,Wallace Jr.,Nixton,NULL,Male,African-American,03/10/85,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,12/18/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +59798,68560,62159,Probation,Wallace Jr.,Nixton,NULL,Male,African-American,03/10/85,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,12/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +59798,68560,62159,Probation,Wallace Jr.,Nixton,NULL,Male,African-American,03/10/85,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,12/18/13 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +59810,68574,62173,PRETRIAL,Walker,Jonathan,NULL,Male,African-American,11/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +59810,68574,62173,PRETRIAL,Walker,Jonathan,NULL,Male,African-American,11/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +59810,68574,62173,PRETRIAL,Walker,Jonathan,NULL,Male,African-American,11/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +59815,68581,62179,Probation,Roman,Yissenia,NULL,Female,Hispanic,03/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/18/13 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +59815,68581,62179,Probation,Roman,Yissenia,NULL,Female,Hispanic,03/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/18/13 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +59815,68581,62179,Probation,Roman,Yissenia,NULL,Female,Hispanic,03/03/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59804,68566,62165,PRETRIAL,Brown,Samantha,NULL,Female,African-American,08/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +59804,68566,62165,PRETRIAL,Brown,Samantha,NULL,Female,African-American,08/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +59804,68566,62165,PRETRIAL,Brown,Samantha,NULL,Female,African-American,08/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59794,68553,62152,PRETRIAL,KILIC,MUZAFFER,NULL,Male,Other,01/01/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/18/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +59794,68553,62152,PRETRIAL,KILIC,MUZAFFER,NULL,Male,Other,01/01/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/18/13 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +59794,68553,62152,PRETRIAL,KILIC,MUZAFFER,NULL,Male,Other,01/01/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54022,68568,62167,PRETRIAL,Rowe,Danny,Dayton,Male,African-American,02/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/18/13 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +54022,68568,62167,PRETRIAL,Rowe,Danny,Dayton,Male,African-American,02/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/18/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +54022,68568,62167,PRETRIAL,Rowe,Danny,Dayton,Male,African-American,02/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/18/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59807,68571,62170,Probation,LEE,PHILLIP,A,Male,African-American,03/04/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,12/18/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +59807,68571,62170,Probation,LEE,PHILLIP,A,Male,African-American,03/04/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,12/18/13 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +59807,68571,62170,Probation,LEE,PHILLIP,A,Male,African-American,03/04/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +9377,68550,8910,Probation,Cure,Jarvis,NULL,Male,African-American,11/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,7,Risk of Violence,-1.34,7,Medium,Copy,1,0 +9377,68550,8910,Probation,Cure,Jarvis,NULL,Male,African-American,11/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,Copy,1,0 +9377,68550,8910,Probation,Cure,Jarvis,NULL,Male,African-American,11/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +59813,68579,62177,PRETRIAL,ORTIZ,KATICIA,NULL,Female,Hispanic,01/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +59813,68579,62177,PRETRIAL,ORTIZ,KATICIA,NULL,Female,Hispanic,01/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +59813,68579,62177,PRETRIAL,ORTIZ,KATICIA,NULL,Female,Hispanic,01/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51650,68597,62195,PRETRIAL,GISPERT,ANGELA,NULL,Female,Caucasian,03/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/19/13 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +51650,68597,62195,PRETRIAL,GISPERT,ANGELA,NULL,Female,Caucasian,03/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +51650,68597,62195,PRETRIAL,GISPERT,ANGELA,NULL,Female,Caucasian,03/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59817,68584,62182,PRETRIAL,Laurie,Charles,NULL,Male,Caucasian,09/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/19/13 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +59817,68584,62182,PRETRIAL,Laurie,Charles,NULL,Male,Caucasian,09/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +59817,68584,62182,PRETRIAL,Laurie,Charles,NULL,Male,Caucasian,09/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59847,68618,62215,Probation,Turino,Sergio,NULL,Male,Hispanic,02/27/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,12/19/13 0:00,2,Medium,7,Risk of Violence,-3.13,1,Low,New,1,0 +59847,68618,62215,Probation,Turino,Sergio,NULL,Male,Hispanic,02/27/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,12/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +59847,68618,62215,Probation,Turino,Sergio,NULL,Male,Hispanic,02/27/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,12/19/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59819,68587,62185,PRETRIAL,DANIELS,DENSMORE,NULL,Male,African-American,10/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +59819,68587,62185,PRETRIAL,DANIELS,DENSMORE,NULL,Male,African-American,10/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +59819,68587,62185,PRETRIAL,DANIELS,DENSMORE,NULL,Male,African-American,10/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59832,68602,62200,Probation,FISHER,ASHLYN,NULL,Female,African-American,12/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +59832,68602,62200,Probation,FISHER,ASHLYN,NULL,Female,African-American,12/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +59832,68602,62200,Probation,FISHER,ASHLYN,NULL,Female,African-American,12/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +42341,68589,62187,PRETRIAL,BEST,CLEON,ODONELL,Male,African-American,10/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +42341,68589,62187,PRETRIAL,BEST,CLEON,ODONELL,Male,African-American,10/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +42341,68589,62187,PRETRIAL,BEST,CLEON,ODONELL,Male,African-American,10/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +33889,68623,62220,PRETRIAL,Dieguez,Ruben,NULL,Male,Hispanic,11/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +33889,68623,62220,PRETRIAL,Dieguez,Ruben,NULL,Male,Hispanic,11/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +33889,68623,62220,PRETRIAL,Dieguez,Ruben,NULL,Male,Hispanic,11/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59857,68631,62228,Probation,Knowles,Jessica,NULL,Female,Caucasian,03/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/19/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +59857,68631,62228,Probation,Knowles,Jessica,NULL,Female,Caucasian,03/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +59857,68631,62228,Probation,Knowles,Jessica,NULL,Female,Caucasian,03/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59826,68595,62193,Probation,Toche,Danny,NULL,Male,Caucasian,06/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/19/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +59826,68595,62193,Probation,Toche,Danny,NULL,Male,Caucasian,06/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +59826,68595,62193,Probation,Toche,Danny,NULL,Male,Caucasian,06/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +6954,68610,62208,PRETRIAL,Thorpe,Ann,NULL,Female,Caucasian,10/16/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,New,1,0 +6954,68610,62208,PRETRIAL,Thorpe,Ann,NULL,Female,Caucasian,10/16/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,10,High,New,1,0 +6954,68610,62208,PRETRIAL,Thorpe,Ann,NULL,Female,Caucasian,10/16/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +59855,68628,62225,Probation,peev,Ivan,NULL,Male,Caucasian,08/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +59855,68628,62225,Probation,peev,Ivan,NULL,Male,Caucasian,08/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +59855,68628,62225,Probation,peev,Ivan,NULL,Male,Caucasian,08/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +59822,68591,62189,PRETRIAL,Valverde-Harrison,Elisa,NULL,Female,Caucasian,12/02/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/19/13 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +59822,68591,62189,PRETRIAL,Valverde-Harrison,Elisa,NULL,Female,Caucasian,12/02/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/19/13 0:00,1,Low,8,Risk of Recidivism,-2.6,1,Low,New,1,0 +59822,68591,62189,PRETRIAL,Valverde-Harrison,Elisa,NULL,Female,Caucasian,12/02/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59828,68598,62196,PRETRIAL,wert,ryan,NULL,Male,Caucasian,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +59828,68598,62196,PRETRIAL,wert,ryan,NULL,Male,Caucasian,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +59828,68598,62196,PRETRIAL,wert,ryan,NULL,Male,Caucasian,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59830,68600,62198,Probation,Robinson,Sharon,NULL,Female,African-American,09/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +59830,68600,62198,Probation,Robinson,Sharon,NULL,Female,African-American,09/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +59830,68600,62198,Probation,Robinson,Sharon,NULL,Female,African-American,09/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +49017,68619,62216,Probation,Lovesmith,Erica,NULL,Female,Caucasian,03/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +49017,68619,62216,Probation,Lovesmith,Erica,NULL,Female,Caucasian,03/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +49017,68619,62216,Probation,Lovesmith,Erica,NULL,Female,Caucasian,03/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59849,68621,62218,Probation,Carnet,Elisabel,NULL,Female,Hispanic,07/25/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +59849,68621,62218,Probation,Carnet,Elisabel,NULL,Female,Hispanic,07/25/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +59849,68621,62218,Probation,Carnet,Elisabel,NULL,Female,Hispanic,07/25/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +59842,68612,62210,Probation,OCONNOR,JOSHUA,ANTHONY,Male,African-American,01/30/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +59842,68612,62210,Probation,OCONNOR,JOSHUA,ANTHONY,Male,African-American,01/30/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +59842,68612,62210,Probation,OCONNOR,JOSHUA,ANTHONY,Male,African-American,01/30/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59837,68607,62205,PRETRIAL,Murphy,Kerryann,NULL,Female,African-American,04/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/19/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +59837,68607,62205,PRETRIAL,Murphy,Kerryann,NULL,Female,African-American,04/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +59837,68607,62205,PRETRIAL,Murphy,Kerryann,NULL,Female,African-American,04/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59845,68616,62213,Probation,padron,michael,NULL,Male,Hispanic,09/06/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.85,2,Low,New,1,0 +59845,68616,62213,Probation,padron,michael,NULL,Male,Hispanic,09/06/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +59845,68616,62213,Probation,padron,michael,NULL,Male,Hispanic,09/06/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +45573,68586,62184,PRETRIAL,Jackson,Seth,Aubray,Male,African-American,01/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +45573,68586,62184,PRETRIAL,Jackson,Seth,Aubray,Male,African-American,01/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +45573,68586,62184,PRETRIAL,Jackson,Seth,Aubray,Male,African-American,01/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +59833,68603,62201,Probation,ward,Willie,NULL,Male,African-American,05/25/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/19/13 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +59833,68603,62201,Probation,ward,Willie,NULL,Male,African-American,05/25/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +59833,68603,62201,Probation,ward,Willie,NULL,Male,African-American,05/25/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/19/13 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59843,68614,62211,Probation,Hicks,Kevin,NULL,Male,Caucasian,11/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +59843,68614,62211,Probation,Hicks,Kevin,NULL,Male,Caucasian,11/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +59843,68614,62211,Probation,Hicks,Kevin,NULL,Male,Caucasian,11/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59831,68601,62199,Probation,Emanual,Michael,NULL,Male,African-American,01/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.33,3,Low,New,1,0 +59831,68601,62199,Probation,Emanual,Michael,NULL,Male,African-American,01/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +59831,68601,62199,Probation,Emanual,Michael,NULL,Male,African-American,01/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59861,68635,62232,PRETRIAL,Watkins,Brian,NULL,Male,Caucasian,05/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/19/13 0:00,2,Medium,7,Risk of Violence,-3.1,1,Low,New,1,0 +59861,68635,62232,PRETRIAL,Watkins,Brian,NULL,Male,Caucasian,05/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/19/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +59861,68635,62232,PRETRIAL,Watkins,Brian,NULL,Male,Caucasian,05/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/19/13 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +59816,68583,62181,PRETRIAL,Jarrett,Jervon,NULL,Male,African-American,06/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +59816,68583,62181,PRETRIAL,Jarrett,Jervon,NULL,Male,African-American,06/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,4,High,8,Risk of Recidivism,0.33,9,High,New,1,0 +59816,68583,62181,PRETRIAL,Jarrett,Jervon,NULL,Male,African-American,06/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59850,68622,62219,Probation,Fowler,James,NULL,Male,African-American,04/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +59850,68622,62219,Probation,Fowler,James,NULL,Male,African-American,04/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +59850,68622,62219,Probation,Fowler,James,NULL,Male,African-American,04/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59824,68593,62191,PRETRIAL,Scott,Jake,NULL,Male,Caucasian,01/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/19/13 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +59824,68593,62191,PRETRIAL,Scott,Jake,NULL,Male,Caucasian,01/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +59824,68593,62191,PRETRIAL,Scott,Jake,NULL,Male,Caucasian,01/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/19/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59834,68604,62202,Probation,OSCEOLA,GREGORY,ALLEN,Male,Native American,02/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +59834,68604,62202,Probation,OSCEOLA,GREGORY,ALLEN,Male,Native American,02/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +59834,68604,62202,Probation,OSCEOLA,GREGORY,ALLEN,Male,Native American,02/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59853,68625,62222,Probation,Oviedo,Adriana,Mercedes,Female,Hispanic,04/24/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,New,1,0 +59853,68625,62222,Probation,Oviedo,Adriana,Mercedes,Female,Hispanic,04/24/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +59853,68625,62222,Probation,Oviedo,Adriana,Mercedes,Female,Hispanic,04/24/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59858,68632,62229,Probation,saxton,kerrie,NULL,Female,Caucasian,07/07/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +59858,68632,62229,Probation,saxton,kerrie,NULL,Female,Caucasian,07/07/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +59858,68632,62229,Probation,saxton,kerrie,NULL,Female,Caucasian,07/07/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59827,68596,62194,PRETRIAL,Wick,Daniel,D,Male,Caucasian,03/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/19/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +59827,68596,62194,PRETRIAL,Wick,Daniel,D,Male,Caucasian,03/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +59827,68596,62194,PRETRIAL,Wick,Daniel,D,Male,Caucasian,03/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59840,68609,62207,Probation,MATTHEWS,TAFOLIA,D,Female,African-American,04/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,New,1,0 +59840,68609,62207,Probation,MATTHEWS,TAFOLIA,D,Female,African-American,04/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +59840,68609,62207,Probation,MATTHEWS,TAFOLIA,D,Female,African-American,04/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59820,68588,62186,PRETRIAL,Santiago,Resendiz,NULL,Male,Caucasian,08/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/19/13 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +59820,68588,62186,PRETRIAL,Santiago,Resendiz,NULL,Male,Caucasian,08/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/19/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +59820,68588,62186,PRETRIAL,Santiago,Resendiz,NULL,Male,Caucasian,08/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59846,68617,62214,Probation,FINZI,DAN,NULL,Male,Hispanic,01/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +59846,68617,62214,Probation,FINZI,DAN,NULL,Male,Hispanic,01/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +59846,68617,62214,Probation,FINZI,DAN,NULL,Male,Hispanic,01/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59852,68624,62221,DRRD,Owens,Keandre,lAMAR,Male,African-American,10/27/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +59852,68624,62221,DRRD,Owens,Keandre,lAMAR,Male,African-American,10/27/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +59852,68624,62221,DRRD,Owens,Keandre,lAMAR,Male,African-American,10/27/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59848,68620,62217,PRETRIAL,Brown,Travis,NULL,Male,African-American,05/30/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,New,1,0 +59848,68620,62217,PRETRIAL,Brown,Travis,NULL,Male,African-American,05/30/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.4,4,Low,New,1,0 +59848,68620,62217,PRETRIAL,Brown,Travis,NULL,Male,African-American,05/30/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59821,68590,62188,PRETRIAL,Kastner,Michelle,NULL,Female,Caucasian,05/22/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +59821,68590,62188,PRETRIAL,Kastner,Michelle,NULL,Female,Caucasian,05/22/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.62,2,Low,New,1,0 +59821,68590,62188,PRETRIAL,Kastner,Michelle,NULL,Female,Caucasian,05/22/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59839,68608,62206,PRETRIAL,BYRUM,ROGER,DWAYNE,Female,African-American,06/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +59839,68608,62206,PRETRIAL,BYRUM,ROGER,DWAYNE,Female,African-American,06/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +59839,68608,62206,PRETRIAL,BYRUM,ROGER,DWAYNE,Female,African-American,06/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59844,68615,62212,Probation,Jean,Yves,Mary,Male,African-American,12/02/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/19/13 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +59844,68615,62212,Probation,Jean,Yves,Mary,Male,African-American,12/02/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +59844,68615,62212,Probation,Jean,Yves,Mary,Male,African-American,12/02/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59825,68594,62192,Probation,Jackson,Vendale,NULL,Male,African-American,09/14/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/19/13 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +59825,68594,62192,Probation,Jackson,Vendale,NULL,Male,African-American,09/14/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +59825,68594,62192,Probation,Jackson,Vendale,NULL,Male,African-American,09/14/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59841,68611,62209,Probation,Jamieson,Scott,NULL,Male,Caucasian,03/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +59841,68611,62209,Probation,Jamieson,Scott,NULL,Male,Caucasian,03/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +59841,68611,62209,Probation,Jamieson,Scott,NULL,Male,Caucasian,03/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59856,68629,62226,Probation,Cascio,Michael,Anthony,Male,Caucasian,07/15/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/19/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +59856,68629,62226,Probation,Cascio,Michael,Anthony,Male,Caucasian,07/15/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/19/13 0:00,2,Medium,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +59856,68629,62226,Probation,Cascio,Michael,Anthony,Male,Caucasian,07/15/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/19/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59818,68585,62183,PRETRIAL,CIVIL,MARIE,NULL,Female,African-American,09/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +59818,68585,62183,PRETRIAL,CIVIL,MARIE,NULL,Female,African-American,09/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +59818,68585,62183,PRETRIAL,CIVIL,MARIE,NULL,Female,African-American,09/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +59860,68634,62231,Probation,STEWART,JAMES,NULL,Male,Hispanic,05/26/87,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +59860,68634,62231,Probation,STEWART,JAMES,NULL,Male,Hispanic,05/26/87,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +59860,68634,62231,Probation,STEWART,JAMES,NULL,Male,Hispanic,05/26/87,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +44267,68627,62224,Probation,buresh,fredric,NULL,Male,Caucasian,02/04/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +44267,68627,62224,Probation,buresh,fredric,NULL,Male,Caucasian,02/04/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +44267,68627,62224,Probation,buresh,fredric,NULL,Male,Caucasian,02/04/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59823,68592,62190,PRETRIAL,Karlson,William,Tyrone,Male,African-American,09/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +59823,68592,62190,PRETRIAL,Karlson,William,Tyrone,Male,African-American,09/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +59823,68592,62190,PRETRIAL,Karlson,William,Tyrone,Male,African-American,09/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59829,68599,62197,Probation,Maldonado,Jose,Orlando,Male,Hispanic,08/30/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.47,3,Low,New,1,0 +59829,68599,62197,Probation,Maldonado,Jose,Orlando,Male,Hispanic,08/30/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +59829,68599,62197,Probation,Maldonado,Jose,Orlando,Male,Hispanic,08/30/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/19/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59836,68606,62204,Probation,Romero,Edward,NULL,Male,Hispanic,10/03/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +59836,68606,62204,Probation,Romero,Edward,NULL,Male,Hispanic,10/03/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +59836,68606,62204,Probation,Romero,Edward,NULL,Male,Hispanic,10/03/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/19/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59862,68636,62233,PRETRIAL,Quinones,Ricardo,NULL,Male,African-American,08/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +59862,68636,62233,PRETRIAL,Quinones,Ricardo,NULL,Male,African-American,08/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +59862,68636,62233,PRETRIAL,Quinones,Ricardo,NULL,Male,African-American,08/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +9358,68657,8889,PRETRIAL,ramdeen,romoy,NULL,Male,Other,07/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,Copy,1,0 +9358,68657,8889,PRETRIAL,ramdeen,romoy,NULL,Male,Other,07/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,Copy,1,0 +9358,68657,8889,PRETRIAL,ramdeen,romoy,NULL,Male,Other,07/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +59883,68664,62258,Probation,JARQUIN-ESQUIVEL,MICHAEL,NULL,Male,Hispanic,09/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +59883,68664,62258,Probation,JARQUIN-ESQUIVEL,MICHAEL,NULL,Male,Hispanic,09/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +59883,68664,62258,Probation,JARQUIN-ESQUIVEL,MICHAEL,NULL,Male,Hispanic,09/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51927,68662,62256,Probation,MORONY,JEFFREY,SCOTT,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +51927,68662,62256,Probation,MORONY,JEFFREY,SCOTT,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +51927,68662,62256,Probation,MORONY,JEFFREY,SCOTT,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59053,68641,61316,PRETRIAL,MIXON,DON,CORNILIA,Male,African-American,10/18/81,17,All Scales,Intake,English,Pretrial,Jail Inmate,Married,12/20/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,Copy,1,0 +59053,68641,61316,PRETRIAL,MIXON,DON,CORNILIA,Male,African-American,10/18/81,17,All Scales,Intake,English,Pretrial,Jail Inmate,Married,12/20/13 0:00,4,High,8,Risk of Recidivism,0.36,9,High,Copy,1,0 +59053,68641,61316,PRETRIAL,MIXON,DON,CORNILIA,Male,African-American,10/18/81,17,All Scales,Intake,English,Pretrial,Jail Inmate,Married,12/20/13 0:00,4,High,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +59873,68650,62246,Probation,Purcell,Richard,NULL,Male,African-American,06/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +59873,68650,62246,Probation,Purcell,Richard,NULL,Male,African-American,06/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +59873,68650,62246,Probation,Purcell,Richard,NULL,Male,African-American,06/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +31312,68645,62241,PRETRIAL,Gorczyca,John,NULL,Male,Caucasian,02/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +31312,68645,62241,PRETRIAL,Gorczyca,John,NULL,Male,Caucasian,02/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +31312,68645,62241,PRETRIAL,Gorczyca,John,NULL,Male,Caucasian,02/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59880,68659,62253,Probation,MOHAMMAD,HAKEEM,NULL,Male,African-American,11/07/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +59880,68659,62253,Probation,MOHAMMAD,HAKEEM,NULL,Male,African-American,11/07/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +59880,68659,62253,Probation,MOHAMMAD,HAKEEM,NULL,Male,African-American,11/07/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59864,68638,62235,PRETRIAL,McKenzieWallace,Shanairj,Eurohn,Male,Other,11/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +59864,68638,62235,PRETRIAL,McKenzieWallace,Shanairj,Eurohn,Male,Other,11/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +59864,68638,62235,PRETRIAL,McKenzieWallace,Shanairj,Eurohn,Male,Other,11/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59876,68653,62249,Probation,Gutierrez,Eswin,NULL,Male,Hispanic,01/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/20/13 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +59876,68653,62249,Probation,Gutierrez,Eswin,NULL,Male,Hispanic,01/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/20/13 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +59876,68653,62249,Probation,Gutierrez,Eswin,NULL,Male,Hispanic,01/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59868,68643,62239,Probation,SULTZER,KRISTIE,MARIE,Female,Hispanic,04/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +59868,68643,62239,Probation,SULTZER,KRISTIE,MARIE,Female,Hispanic,04/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +59868,68643,62239,Probation,SULTZER,KRISTIE,MARIE,Female,Hispanic,04/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59871,68648,62244,Probation,TUDERS,ROBERT,LEE,Male,Caucasian,10/28/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/20/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +59871,68648,62244,Probation,TUDERS,ROBERT,LEE,Male,Caucasian,10/28/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/20/13 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +59871,68648,62244,Probation,TUDERS,ROBERT,LEE,Male,Caucasian,10/28/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59863,68637,62234,PRETRIAL,Angelini,Briana,NULL,Female,Caucasian,03/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +59863,68637,62234,PRETRIAL,Angelini,Briana,NULL,Female,Caucasian,03/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +59863,68637,62234,PRETRIAL,Angelini,Briana,NULL,Female,Caucasian,03/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59877,68654,62250,Probation,CIOE,ANNEMARIE,NULL,Female,Caucasian,07/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +59877,68654,62250,Probation,CIOE,ANNEMARIE,NULL,Female,Caucasian,07/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +59877,68654,62250,Probation,CIOE,ANNEMARIE,NULL,Female,Caucasian,07/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59879,68658,62252,PRETRIAL,Webber,Kennyal,NULL,Male,African-American,06/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +59879,68658,62252,PRETRIAL,Webber,Kennyal,NULL,Male,African-American,06/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +59879,68658,62252,PRETRIAL,Webber,Kennyal,NULL,Male,African-American,06/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59882,68663,62257,PRETRIAL,Abhilash,Sastri,NULL,Male,Other,01/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +59882,68663,62257,PRETRIAL,Abhilash,Sastri,NULL,Male,Other,01/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +59882,68663,62257,PRETRIAL,Abhilash,Sastri,NULL,Male,Other,01/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59867,68642,62238,Probation,pierre,didelin,NULL,Male,African-American,07/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +59867,68642,62238,Probation,pierre,didelin,NULL,Male,African-American,07/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +59867,68642,62238,Probation,pierre,didelin,NULL,Male,African-American,07/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59872,68649,62245,Probation,Shar,Jeffrey,NULL,Male,Caucasian,02/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/20/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +59872,68649,62245,Probation,Shar,Jeffrey,NULL,Male,Caucasian,02/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/20/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +59872,68649,62245,Probation,Shar,Jeffrey,NULL,Male,Caucasian,02/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59878,68656,62251,PRETRIAL,Knight,Ronald,Quincy,Male,African-American,05/31/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +59878,68656,62251,PRETRIAL,Knight,Ronald,Quincy,Male,African-American,05/31/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +59878,68656,62251,PRETRIAL,Knight,Ronald,Quincy,Male,African-American,05/31/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59881,68660,62254,Probation,MACHADO,ERIKA,NULL,Female,Hispanic,03/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/20/13 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +59881,68660,62254,Probation,MACHADO,ERIKA,NULL,Female,Hispanic,03/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +59881,68660,62254,Probation,MACHADO,ERIKA,NULL,Female,Hispanic,03/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/20/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59875,68652,62248,Probation,vives,patrick,NULL,Male,Hispanic,09/17/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.28,3,Low,New,1,0 +59875,68652,62248,Probation,vives,patrick,NULL,Male,Hispanic,09/17/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.91,10,High,New,1,0 +59875,68652,62248,Probation,vives,patrick,NULL,Male,Hispanic,09/17/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59865,68639,62236,PRETRIAL,ali,masoom,NULL,Male,Caucasian,07/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/20/13 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +59865,68639,62236,PRETRIAL,ali,masoom,NULL,Male,Caucasian,07/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/20/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +59865,68639,62236,PRETRIAL,ali,masoom,NULL,Male,Caucasian,07/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +36972,68647,62243,PRETRIAL,Atkins,Anthony,NULL,Male,Caucasian,09/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +36972,68647,62243,PRETRIAL,Atkins,Anthony,NULL,Male,Caucasian,09/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +36972,68647,62243,PRETRIAL,Atkins,Anthony,NULL,Male,Caucasian,09/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/20/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59869,68644,62240,PRETRIAL,Finder,Brittany,Nicole,Female,Caucasian,12/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/20/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +59869,68644,62240,PRETRIAL,Finder,Brittany,Nicole,Female,Caucasian,12/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/20/13 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +59869,68644,62240,PRETRIAL,Finder,Brittany,Nicole,Female,Caucasian,12/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/20/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59886,68665,62259,PRETRIAL,Hall,Timothy,NULL,Male,African-American,07/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +59886,68665,62259,PRETRIAL,Hall,Timothy,NULL,Male,African-American,07/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +59886,68665,62259,PRETRIAL,Hall,Timothy,NULL,Male,African-American,07/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59891,68673,62266,PRETRIAL,Francis,Richard,Jordan,Male,African-American,03/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +59891,68673,62266,PRETRIAL,Francis,Richard,Jordan,Male,African-American,03/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +59891,68673,62266,PRETRIAL,Francis,Richard,Jordan,Male,African-American,03/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59889,68668,62262,PRETRIAL,Hernandez,Martin,NULL,Male,Hispanic,01/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +59889,68668,62262,PRETRIAL,Hernandez,Martin,NULL,Male,Hispanic,01/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +59889,68668,62262,PRETRIAL,Hernandez,Martin,NULL,Male,Hispanic,01/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59890,68670,62264,PRETRIAL,Stafford,Dominick,NULL,Male,African-American,04/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +59890,68670,62264,PRETRIAL,Stafford,Dominick,NULL,Male,African-American,04/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +59890,68670,62264,PRETRIAL,Stafford,Dominick,NULL,Male,African-American,04/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +39483,68672,39003,PRETRIAL,MADEIRA,ANTHONY,NULL,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,Copy,1,0 +39483,68672,39003,PRETRIAL,MADEIRA,ANTHONY,NULL,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,Copy,1,0 +39483,68672,39003,PRETRIAL,MADEIRA,ANTHONY,NULL,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +56348,68669,62263,PRETRIAL,Williams,Branden,NULL,Male,Other,08/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +56348,68669,62263,PRETRIAL,Williams,Branden,NULL,Male,Other,08/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/13 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +56348,68669,62263,PRETRIAL,Williams,Branden,NULL,Male,Other,08/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59887,68666,62260,PRETRIAL,Campos,Ailton,NULL,Male,Hispanic,04/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +59887,68666,62260,PRETRIAL,Campos,Ailton,NULL,Male,Hispanic,04/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +59887,68666,62260,PRETRIAL,Campos,Ailton,NULL,Male,Hispanic,04/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59888,68667,62261,PRETRIAL,Howell,Amber,NULL,Female,African-American,01/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +59888,68667,62261,PRETRIAL,Howell,Amber,NULL,Female,African-American,01/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +59888,68667,62261,PRETRIAL,Howell,Amber,NULL,Female,African-American,01/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +41026,68671,62265,PRETRIAL,Williams,Henry,NULL,Male,African-American,09/19/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,2,Medium,7,Risk of Violence,-2.7,2,Low,New,1,0 +41026,68671,62265,PRETRIAL,Williams,Henry,NULL,Male,African-American,09/19/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +41026,68671,62265,PRETRIAL,Williams,Henry,NULL,Male,African-American,09/19/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/13 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +41426,68680,41126,PRETRIAL,JeanPhilippe,Kenson,NULL,Male,African-American,07/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.96,9,High,Copy,1,0 +41426,68680,41126,PRETRIAL,JeanPhilippe,Kenson,NULL,Male,African-American,07/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,Copy,1,0 +41426,68680,41126,PRETRIAL,JeanPhilippe,Kenson,NULL,Male,African-American,07/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +32689,68676,62269,PRETRIAL,Hope,Barry,NULL,Male,African-American,01/05/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.81,9,High,New,1,0 +32689,68676,62269,PRETRIAL,Hope,Barry,NULL,Male,African-American,01/05/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +32689,68676,62269,PRETRIAL,Hope,Barry,NULL,Male,African-American,01/05/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59898,68683,62274,PRETRIAL,Muller,Daniel,NULL,Male,Caucasian,03/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +59898,68683,62274,PRETRIAL,Muller,Daniel,NULL,Male,Caucasian,03/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +59898,68683,62274,PRETRIAL,Muller,Daniel,NULL,Male,Caucasian,03/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59900,68685,62276,PRETRIAL,Peterson,Ashley,NULL,Female,African-American,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +59900,68685,62276,PRETRIAL,Peterson,Ashley,NULL,Female,African-American,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,4,High,8,Risk of Recidivism,0.05,8,High,New,1,0 +59900,68685,62276,PRETRIAL,Peterson,Ashley,NULL,Female,African-American,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59905,68692,62281,PRETRIAL,Evans,Joanne,NULL,Female,Caucasian,02/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +59905,68692,62281,PRETRIAL,Evans,Joanne,NULL,Female,Caucasian,02/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,7,Medium,New,1,0 +59905,68692,62281,PRETRIAL,Evans,Joanne,NULL,Female,Caucasian,02/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +11417,68678,10941,PRETRIAL,DAVIS,DARRIOUS,NULL,Male,African-American,06/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,4,High,7,Risk of Violence,-0.84,9,High,Copy,1,0 +11417,68678,10941,PRETRIAL,DAVIS,DARRIOUS,NULL,Male,African-American,06/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,4,High,8,Risk of Recidivism,0.89,10,High,Copy,1,0 +11417,68678,10941,PRETRIAL,DAVIS,DARRIOUS,NULL,Male,African-American,06/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +37171,68674,62267,PRETRIAL,Beckford,Rajiv,NULL,Male,African-American,05/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +37171,68674,62267,PRETRIAL,Beckford,Rajiv,NULL,Male,African-American,05/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +37171,68674,62267,PRETRIAL,Beckford,Rajiv,NULL,Male,African-American,05/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59902,68687,62278,PRETRIAL,WAY,WILLIE,NULL,Male,African-American,07/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/22/13 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +59902,68687,62278,PRETRIAL,WAY,WILLIE,NULL,Male,African-American,07/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/22/13 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +59902,68687,62278,PRETRIAL,WAY,WILLIE,NULL,Male,African-American,07/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/22/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59897,68682,62273,PRETRIAL,DOREUS,DEROSLYN,NULL,Male,African-American,01/02/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +59897,68682,62273,PRETRIAL,DOREUS,DEROSLYN,NULL,Male,African-American,01/02/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +59897,68682,62273,PRETRIAL,DOREUS,DEROSLYN,NULL,Male,African-American,01/02/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59904,68690,62280,PRETRIAL,Scher,Catherine,NULL,Female,Caucasian,05/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,Copy,1,0 +59904,68690,62280,PRETRIAL,Scher,Catherine,NULL,Female,Caucasian,05/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,Copy,1,0 +59904,68690,62280,PRETRIAL,Scher,Catherine,NULL,Female,Caucasian,05/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +59894,68679,62271,PRETRIAL,WILLIAMS,BRYON,URIUS,Male,African-American,08/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +59894,68679,62271,PRETRIAL,WILLIAMS,BRYON,URIUS,Male,African-American,08/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +59894,68679,62271,PRETRIAL,WILLIAMS,BRYON,URIUS,Male,African-American,08/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59903,68688,62279,PRETRIAL,SHOULTZ,DEIRDRE,NULL,Female,African-American,04/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +59903,68688,62279,PRETRIAL,SHOULTZ,DEIRDRE,NULL,Female,African-American,04/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,9,High,New,1,0 +59903,68688,62279,PRETRIAL,SHOULTZ,DEIRDRE,NULL,Female,African-American,04/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +59892,68675,62268,PRETRIAL,Fox,Richard,NULL,Male,Other,04/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/22/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +59892,68675,62268,PRETRIAL,Fox,Richard,NULL,Male,Other,04/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/22/13 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +59892,68675,62268,PRETRIAL,Fox,Richard,NULL,Male,Other,04/08/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59899,68684,62275,PRETRIAL,CAMPOS,DANIEL,ANDRES,Male,Caucasian,07/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/22/13 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +59899,68684,62275,PRETRIAL,CAMPOS,DANIEL,ANDRES,Male,Caucasian,07/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/22/13 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +59899,68684,62275,PRETRIAL,CAMPOS,DANIEL,ANDRES,Male,Caucasian,07/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/22/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +903,68691,595,Probation,Garner,Timothy,M,Male,African-American,12/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.91,9,High,Copy,1,0 +903,68691,595,Probation,Garner,Timothy,M,Male,African-American,12/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.54,4,Low,Copy,1,0 +903,68691,595,Probation,Garner,Timothy,M,Male,African-American,12/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +59893,68677,62270,PRETRIAL,DEMARINIS,DARIA,NULL,Female,Caucasian,11/08/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +59893,68677,62270,PRETRIAL,DEMARINIS,DARIA,NULL,Female,Caucasian,11/08/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +59893,68677,62270,PRETRIAL,DEMARINIS,DARIA,NULL,Female,Caucasian,11/08/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59896,68681,62272,PRETRIAL,KENON,AVERY,MAURICE,Male,African-American,03/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +59896,68681,62272,PRETRIAL,KENON,AVERY,MAURICE,Male,African-American,03/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +59896,68681,62272,PRETRIAL,KENON,AVERY,MAURICE,Male,African-American,03/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59901,68686,62277,PRETRIAL,DEFROSCIA,MARIA,NULL,Female,Caucasian,11/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/22/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +59901,68686,62277,PRETRIAL,DEFROSCIA,MARIA,NULL,Female,Caucasian,11/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/22/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +59901,68686,62277,PRETRIAL,DEFROSCIA,MARIA,NULL,Female,Caucasian,11/04/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/22/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59935,68720,62307,PRETRIAL,Nielsen,shan,NULL,Male,African-American,10/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +59935,68720,62307,PRETRIAL,Nielsen,shan,NULL,Male,African-American,10/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +59935,68720,62307,PRETRIAL,Nielsen,shan,NULL,Male,African-American,10/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59924,68707,62295,PRETRIAL,HOPKINS,JEFFREY,NULL,Male,Caucasian,11/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +59924,68707,62295,PRETRIAL,HOPKINS,JEFFREY,NULL,Male,Caucasian,11/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +59924,68707,62295,PRETRIAL,HOPKINS,JEFFREY,NULL,Male,Caucasian,11/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59946,68733,62318,PRETRIAL,Walker,William,NULL,Male,Caucasian,05/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +59946,68733,62318,PRETRIAL,Walker,William,NULL,Male,Caucasian,05/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +59946,68733,62318,PRETRIAL,Walker,William,NULL,Male,Caucasian,05/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +21308,68694,20485,Probation,zachary,jordan,NULL,Male,Caucasian,05/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,Copy,1,0 +21308,68694,20485,Probation,zachary,jordan,NULL,Male,Caucasian,05/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,Copy,1,0 +21308,68694,20485,Probation,zachary,jordan,NULL,Male,Caucasian,05/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +59929,68712,62300,PRETRIAL,NAVARRO,john,NULL,Male,Caucasian,10/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/23/13 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +59929,68712,62300,PRETRIAL,NAVARRO,john,NULL,Male,Caucasian,10/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +59929,68712,62300,PRETRIAL,NAVARRO,john,NULL,Male,Caucasian,10/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59933,68717,62304,Probation,Reyes Rivera,Eli,Samuel,Male,Hispanic,09/12/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +59933,68717,62304,Probation,Reyes Rivera,Eli,Samuel,Male,Hispanic,09/12/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +59933,68717,62304,Probation,Reyes Rivera,Eli,Samuel,Male,Hispanic,09/12/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59945,68731,62316,PRETRIAL,Lama,Mahmud,NULL,Male,Arabic,04/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +59945,68731,62316,PRETRIAL,Lama,Mahmud,NULL,Male,Arabic,04/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +59945,68731,62316,PRETRIAL,Lama,Mahmud,NULL,Male,Arabic,04/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59907,68696,62284,PRETRIAL,HUFFMAN,DEREK,LYLE,Male,Caucasian,05/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/13 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +59907,68696,62284,PRETRIAL,HUFFMAN,DEREK,LYLE,Male,Caucasian,05/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/13 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +59907,68696,62284,PRETRIAL,HUFFMAN,DEREK,LYLE,Male,Caucasian,05/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59927,68710,62298,PRETRIAL,Inman,Donna,NULL,Female,Caucasian,08/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/23/13 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +59927,68710,62298,PRETRIAL,Inman,Donna,NULL,Female,Caucasian,08/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +59927,68710,62298,PRETRIAL,Inman,Donna,NULL,Female,Caucasian,08/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59912,68702,62290,PRETRIAL,DALEY,PAUL,V,Male,African-American,12/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +59912,68702,62290,PRETRIAL,DALEY,PAUL,V,Male,African-American,12/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +59912,68702,62290,PRETRIAL,DALEY,PAUL,V,Male,African-American,12/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59914,68704,62292,PRETRIAL,Skolnick,Kevin,NULL,Male,Caucasian,07/11/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +59914,68704,62292,PRETRIAL,Skolnick,Kevin,NULL,Male,Caucasian,07/11/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +59914,68704,62292,PRETRIAL,Skolnick,Kevin,NULL,Male,Caucasian,07/11/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59939,68725,62310,PRETRIAL,santos,kirsty,NULL,Female,Hispanic,09/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +59939,68725,62310,PRETRIAL,santos,kirsty,NULL,Female,Hispanic,09/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +59939,68725,62310,PRETRIAL,santos,kirsty,NULL,Female,Hispanic,09/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59942,68728,62313,PRETRIAL,Jackson,Dennis,NULL,Male,Other,04/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +59942,68728,62313,PRETRIAL,Jackson,Dennis,NULL,Male,Other,04/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +59942,68728,62313,PRETRIAL,Jackson,Dennis,NULL,Male,Other,04/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59909,68698,62286,PRETRIAL,POTENZIANI,ROBERT,ANTHONY,Male,Caucasian,02/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +59909,68698,62286,PRETRIAL,POTENZIANI,ROBERT,ANTHONY,Male,Caucasian,02/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +59909,68698,62286,PRETRIAL,POTENZIANI,ROBERT,ANTHONY,Male,Caucasian,02/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59910,68700,62288,PRETRIAL,SHORT,MICHAEL,JOSEPH,Male,Caucasian,12/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +59910,68700,62288,PRETRIAL,SHORT,MICHAEL,JOSEPH,Male,Caucasian,12/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +59910,68700,62288,PRETRIAL,SHORT,MICHAEL,JOSEPH,Male,Caucasian,12/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59934,68719,62306,PRETRIAL,Delva,Nadjeda,NULL,Female,African-American,11/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +59934,68719,62306,PRETRIAL,Delva,Nadjeda,NULL,Female,African-American,11/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +59934,68719,62306,PRETRIAL,Delva,Nadjeda,NULL,Female,African-American,11/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59922,68705,62293,PRETRIAL,FILIZZOLA,STEVEN,MICHAEL,Male,Caucasian,03/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +59922,68705,62293,PRETRIAL,FILIZZOLA,STEVEN,MICHAEL,Male,Caucasian,03/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +59922,68705,62293,PRETRIAL,FILIZZOLA,STEVEN,MICHAEL,Male,Caucasian,03/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59926,68709,62297,Probation,turk,anthony,NULL,Male,Caucasian,07/19/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/23/13 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +59926,68709,62297,Probation,turk,anthony,NULL,Male,Caucasian,07/19/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +59926,68709,62297,Probation,turk,anthony,NULL,Male,Caucasian,07/19/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59930,68714,62301,PRETRIAL,Vassell,Aron,NULL,Male,Other,06/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +59930,68714,62301,PRETRIAL,Vassell,Aron,NULL,Male,Other,06/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,2,Medium,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +59930,68714,62301,PRETRIAL,Vassell,Aron,NULL,Male,Other,06/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +44324,68693,62282,PRETRIAL,METAYER,JOHNIOR,NULL,Male,African-American,09/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/13 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,New,1,0 +44324,68693,62282,PRETRIAL,METAYER,JOHNIOR,NULL,Male,African-American,09/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/13 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +44324,68693,62282,PRETRIAL,METAYER,JOHNIOR,NULL,Male,African-American,09/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/13 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59944,68730,62315,PRETRIAL,CELESTIN,SHELIA,NULL,Female,African-American,11/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +59944,68730,62315,PRETRIAL,CELESTIN,SHELIA,NULL,Female,African-American,11/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,9,High,New,1,0 +59944,68730,62315,PRETRIAL,CELESTIN,SHELIA,NULL,Female,African-American,11/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59925,68708,62296,PRETRIAL,BURNSIDE,CHAD,NULL,Male,Caucasian,12/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +59925,68708,62296,PRETRIAL,BURNSIDE,CHAD,NULL,Male,Caucasian,12/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +59925,68708,62296,PRETRIAL,BURNSIDE,CHAD,NULL,Male,Caucasian,12/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59928,68711,62299,Probation,KULIC,ROBERT,MICHAEL,Male,Hispanic,05/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +59928,68711,62299,Probation,KULIC,ROBERT,MICHAEL,Male,Hispanic,05/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +59928,68711,62299,Probation,KULIC,ROBERT,MICHAEL,Male,Hispanic,05/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59943,68729,62314,PRETRIAL,DAY,SABRINA,NULL,Female,African-American,10/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +59943,68729,62314,PRETRIAL,DAY,SABRINA,NULL,Female,African-American,10/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +59943,68729,62314,PRETRIAL,DAY,SABRINA,NULL,Female,African-American,10/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59932,68716,62303,Probation,BELLOT,RENOT,NULL,Male,African-American,09/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +59932,68716,62303,Probation,BELLOT,RENOT,NULL,Male,African-American,09/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +59932,68716,62303,Probation,BELLOT,RENOT,NULL,Male,African-American,09/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59913,68703,62291,PRETRIAL,Mars,Nia-Tarin,NULL,Female,African-American,04/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +59913,68703,62291,PRETRIAL,Mars,Nia-Tarin,NULL,Female,African-American,04/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +59913,68703,62291,PRETRIAL,Mars,Nia-Tarin,NULL,Female,African-American,04/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +43114,68732,62317,PRETRIAL,weller,michael,NULL,Male,Caucasian,11/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/23/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.63,2,Low,New,1,0 +43114,68732,62317,PRETRIAL,weller,michael,NULL,Male,Caucasian,11/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/23/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +43114,68732,62317,PRETRIAL,weller,michael,NULL,Male,Caucasian,11/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/23/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59938,68724,62309,PRETRIAL,Noonan,John,David,Male,Caucasian,06/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/23/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,Copy,1,0 +59938,68724,62309,PRETRIAL,Noonan,John,David,Male,Caucasian,06/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,Copy,1,0 +59938,68724,62309,PRETRIAL,Noonan,John,David,Male,Caucasian,06/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +59906,68695,62283,PRETRIAL,FERRELL,BROOKE,CAROLYN,Female,Caucasian,01/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +59906,68695,62283,PRETRIAL,FERRELL,BROOKE,CAROLYN,Female,Caucasian,01/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +59906,68695,62283,PRETRIAL,FERRELL,BROOKE,CAROLYN,Female,Caucasian,01/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +13884,68713,58732,PRETRIAL,Daley,Kendrick,NULL,Male,African-American,01/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,Copy,1,0 +13884,68713,58732,PRETRIAL,Daley,Kendrick,NULL,Male,African-American,01/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,Copy,1,0 +13884,68713,58732,PRETRIAL,Daley,Kendrick,NULL,Male,African-American,01/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +41688,68699,62287,PRETRIAL,McNair,Jessie,NULL,Male,African-American,07/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +41688,68699,62287,PRETRIAL,McNair,Jessie,NULL,Male,African-American,07/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +41688,68699,62287,PRETRIAL,McNair,Jessie,NULL,Male,African-American,07/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59923,68706,62294,PRETRIAL,BANKS,EMONTE,MAURICE,Male,African-American,01/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/13 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +59923,68706,62294,PRETRIAL,BANKS,EMONTE,MAURICE,Male,African-American,01/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +59923,68706,62294,PRETRIAL,BANKS,EMONTE,MAURICE,Male,African-American,01/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59908,68697,62285,PRETRIAL,Padilla,Jason,NULL,Male,Hispanic,12/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +59908,68697,62285,PRETRIAL,Padilla,Jason,NULL,Male,Hispanic,12/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +59908,68697,62285,PRETRIAL,Padilla,Jason,NULL,Male,Hispanic,12/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59937,68722,62308,PRETRIAL,Cam,Sheldon,G,Male,African-American,09/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/23/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +59937,68722,62308,PRETRIAL,Cam,Sheldon,G,Male,African-American,09/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/23/13 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +59937,68722,62308,PRETRIAL,Cam,Sheldon,G,Male,African-American,09/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59911,68701,62289,PRETRIAL,ALTAF,MUHAMMAD,NULL,Male,Caucasian,04/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +59911,68701,62289,PRETRIAL,ALTAF,MUHAMMAD,NULL,Male,Caucasian,04/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/13 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +59911,68701,62289,PRETRIAL,ALTAF,MUHAMMAD,NULL,Male,Caucasian,04/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +36486,68752,35764,PRETRIAL,Eddins,Aaron,T,Male,African-American,12/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,4,High,7,Risk of Violence,-1.09,8,High,Copy,1,0 +36486,68752,35764,PRETRIAL,Eddins,Aaron,T,Male,African-American,12/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,4,High,8,Risk of Recidivism,0.46,9,High,Copy,1,0 +36486,68752,35764,PRETRIAL,Eddins,Aaron,T,Male,African-American,12/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,4,High,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +59952,68739,62324,PRETRIAL,Severe,Alescynor,B,Male,African-American,01/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +59952,68739,62324,PRETRIAL,Severe,Alescynor,B,Male,African-American,01/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +59952,68739,62324,PRETRIAL,Severe,Alescynor,B,Male,African-American,01/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59958,68748,62331,PRETRIAL,Humes,Delroy,NULL,Male,African-American,12/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/24/13 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +59958,68748,62331,PRETRIAL,Humes,Delroy,NULL,Male,African-American,12/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/24/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +59958,68748,62331,PRETRIAL,Humes,Delroy,NULL,Male,African-American,12/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/24/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58851,68743,61086,PRETRIAL,Jones,Christian,NULL,Male,African-American,06/22/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/24/13 0:00,4,High,7,Risk of Violence,-0.49,10,High,Copy,1,0 +58851,68743,61086,PRETRIAL,Jones,Christian,NULL,Male,African-American,06/22/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/24/13 0:00,4,High,8,Risk of Recidivism,0.53,9,High,Copy,1,0 +58851,68743,61086,PRETRIAL,Jones,Christian,NULL,Male,African-American,06/22/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/24/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +59949,68736,62321,PRETRIAL,Daniel,Miesha,NULL,Female,African-American,02/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +59949,68736,62321,PRETRIAL,Daniel,Miesha,NULL,Female,African-American,02/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.36,7,Medium,New,1,0 +59949,68736,62321,PRETRIAL,Daniel,Miesha,NULL,Female,African-American,02/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59947,68734,62319,PRETRIAL,WOODCOCK,QUAVON,ANTONIO,Male,African-American,03/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +59947,68734,62319,PRETRIAL,WOODCOCK,QUAVON,ANTONIO,Male,African-American,03/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,4,High,8,Risk of Recidivism,0.09,8,High,New,1,0 +59947,68734,62319,PRETRIAL,WOODCOCK,QUAVON,ANTONIO,Male,African-American,03/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54066,68745,62328,PRETRIAL,PARKER,KEVIN,NULL,Male,Caucasian,01/24/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/24/13 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +54066,68745,62328,PRETRIAL,PARKER,KEVIN,NULL,Male,Caucasian,01/24/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/24/13 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +54066,68745,62328,PRETRIAL,PARKER,KEVIN,NULL,Male,Caucasian,01/24/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/24/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59950,68737,62322,PRETRIAL,Nickel,Irina,NULL,Female,Caucasian,05/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +59950,68737,62322,PRETRIAL,Nickel,Irina,NULL,Female,Caucasian,05/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +59950,68737,62322,PRETRIAL,Nickel,Irina,NULL,Female,Caucasian,05/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59960,68750,62333,PRETRIAL,Valliere,Flora,NULL,Female,Caucasian,12/04/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/24/13 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +59960,68750,62333,PRETRIAL,Valliere,Flora,NULL,Female,Caucasian,12/04/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/24/13 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +59960,68750,62333,PRETRIAL,Valliere,Flora,NULL,Female,Caucasian,12/04/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/24/13 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +59955,68744,62327,PRETRIAL,Tarver,Charles,NULL,Male,African-American,11/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,New,1,0 +59955,68744,62327,PRETRIAL,Tarver,Charles,NULL,Male,African-American,11/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +59955,68744,62327,PRETRIAL,Tarver,Charles,NULL,Male,African-American,11/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59953,68740,62325,PRETRIAL,Hoggins,Jeremy,B,Male,African-American,08/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +59953,68740,62325,PRETRIAL,Hoggins,Jeremy,B,Male,African-American,08/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +59953,68740,62325,PRETRIAL,Hoggins,Jeremy,B,Male,African-American,08/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59957,68747,62330,PRETRIAL,OLAZABAL,JONATHAN,NULL,Male,Caucasian,07/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +59957,68747,62330,PRETRIAL,OLAZABAL,JONATHAN,NULL,Male,Caucasian,07/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +59957,68747,62330,PRETRIAL,OLAZABAL,JONATHAN,NULL,Male,Caucasian,07/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59948,68735,62320,PRETRIAL,ANTHONY,MICHAEL,MATTHEWS,Male,African-American,06/08/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +59948,68735,62320,PRETRIAL,ANTHONY,MICHAEL,MATTHEWS,Male,African-American,06/08/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +59948,68735,62320,PRETRIAL,ANTHONY,MICHAEL,MATTHEWS,Male,African-American,06/08/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58851,68742,61086,PRETRIAL,Jones,Christian,NULL,Male,African-American,06/22/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/24/13 0:00,4,High,7,Risk of Violence,-0.49,10,High,Copy,1,0 +58851,68742,61086,PRETRIAL,Jones,Christian,NULL,Male,African-American,06/22/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/24/13 0:00,4,High,8,Risk of Recidivism,0.53,9,High,Copy,1,0 +58851,68742,61086,PRETRIAL,Jones,Christian,NULL,Male,African-American,06/22/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/24/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +59951,68738,62323,PRETRIAL,ANDERSON,ALLIYAH,LATONIA,Male,African-American,04/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +59951,68738,62323,PRETRIAL,ANDERSON,ALLIYAH,LATONIA,Male,African-American,04/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,2,Medium,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +59951,68738,62323,PRETRIAL,ANDERSON,ALLIYAH,LATONIA,Male,African-American,04/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59148,68751,61433,PRETRIAL,SIMMONS,SANDRINNA,NULL,Female,African-American,09/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/24/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.89,2,Low,Copy,1,0 +59148,68751,61433,PRETRIAL,SIMMONS,SANDRINNA,NULL,Female,African-American,09/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/24/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,9,High,Copy,1,0 +59148,68751,61433,PRETRIAL,SIMMONS,SANDRINNA,NULL,Female,African-American,09/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/24/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +59956,68746,62329,PRETRIAL,MCGINNIS,JOHN,NULL,Male,Caucasian,04/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/24/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +59956,68746,62329,PRETRIAL,MCGINNIS,JOHN,NULL,Male,Caucasian,04/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/24/13 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +59956,68746,62329,PRETRIAL,MCGINNIS,JOHN,NULL,Male,Caucasian,04/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/24/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59954,68741,62326,PRETRIAL,CONNOLLY,MAX,DAVID,Male,Caucasian,03/04/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +59954,68741,62326,PRETRIAL,CONNOLLY,MAX,DAVID,Male,Caucasian,03/04/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +59954,68741,62326,PRETRIAL,CONNOLLY,MAX,DAVID,Male,Caucasian,03/04/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/13 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +59962,68754,62335,PRETRIAL,Evans,Theodore,NULL,Female,African-American,02/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +59962,68754,62335,PRETRIAL,Evans,Theodore,NULL,Female,African-American,02/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +59962,68754,62335,PRETRIAL,Evans,Theodore,NULL,Female,African-American,02/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59969,68762,62342,PRETRIAL,Wisniewski,Kimberly,M,Female,Caucasian,05/27/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +59969,68762,62342,PRETRIAL,Wisniewski,Kimberly,M,Female,Caucasian,05/27/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +59969,68762,62342,PRETRIAL,Wisniewski,Kimberly,M,Female,Caucasian,05/27/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59966,68759,62339,PRETRIAL,Marcus,Samuel,NULL,Male,African-American,11/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +59966,68759,62339,PRETRIAL,Marcus,Samuel,NULL,Male,African-American,11/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +59966,68759,62339,PRETRIAL,Marcus,Samuel,NULL,Male,African-American,11/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59964,68756,62337,PRETRIAL,MONTALBANO,GIUSEPPE,ANTHONY,Male,Caucasian,04/26/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +59964,68756,62337,PRETRIAL,MONTALBANO,GIUSEPPE,ANTHONY,Male,Caucasian,04/26/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +59964,68756,62337,PRETRIAL,MONTALBANO,GIUSEPPE,ANTHONY,Male,Caucasian,04/26/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +2854,68763,62343,PRETRIAL,harrison,orett,p,Male,African-American,03/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +2854,68763,62343,PRETRIAL,harrison,orett,p,Male,African-American,03/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +2854,68763,62343,PRETRIAL,harrison,orett,p,Male,African-American,03/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59968,68761,62341,PRETRIAL,Guerrero,Rafael,NULL,Male,Caucasian,05/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +59968,68761,62341,PRETRIAL,Guerrero,Rafael,NULL,Male,Caucasian,05/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,2,Medium,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +59968,68761,62341,PRETRIAL,Guerrero,Rafael,NULL,Male,Caucasian,05/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59965,68758,62338,PRETRIAL,ROMERO,DOUGLAS,R,Male,Caucasian,05/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +59965,68758,62338,PRETRIAL,ROMERO,DOUGLAS,R,Male,Caucasian,05/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +59965,68758,62338,PRETRIAL,ROMERO,DOUGLAS,R,Male,Caucasian,05/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +59967,68760,62340,PRETRIAL,COELLO,STEPHANIE,NULL,Male,Caucasian,10/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +59967,68760,62340,PRETRIAL,COELLO,STEPHANIE,NULL,Male,Caucasian,10/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +59967,68760,62340,PRETRIAL,COELLO,STEPHANIE,NULL,Male,Caucasian,10/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +9299,68757,49137,PRETRIAL,Ullda,Johell,Enrique,Male,Hispanic,02/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,Copy,1,0 +9299,68757,49137,PRETRIAL,Ullda,Johell,Enrique,Male,Hispanic,02/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,Copy,1,0 +9299,68757,49137,PRETRIAL,Ullda,Johell,Enrique,Male,Hispanic,02/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +59970,68764,62344,PRETRIAL,MILLER,GLENN,ALLAN,Male,Caucasian,03/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +59970,68764,62344,PRETRIAL,MILLER,GLENN,ALLAN,Male,Caucasian,03/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,8,Risk of Recidivism,-2.73,1,Low,New,1,0 +59970,68764,62344,PRETRIAL,MILLER,GLENN,ALLAN,Male,Caucasian,03/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59963,68755,62336,PRETRIAL,DAMEUS,JAMES,SMITH,Male,African-American,06/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +59963,68755,62336,PRETRIAL,DAMEUS,JAMES,SMITH,Male,African-American,06/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +59963,68755,62336,PRETRIAL,DAMEUS,JAMES,SMITH,Male,African-American,06/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59981,68778,62356,Broward County,Boyd,Velarry,NULL,Male,African-American,09/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +59981,68778,62356,Broward County,Boyd,Velarry,NULL,Male,African-American,09/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +59981,68778,62356,Broward County,Boyd,Velarry,NULL,Male,African-American,09/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +59976,68773,62351,PRETRIAL,Murphy,Kristen,NULL,Female,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +59976,68773,62351,PRETRIAL,Murphy,Kristen,NULL,Female,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +59976,68773,62351,PRETRIAL,Murphy,Kristen,NULL,Female,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59973,68769,62347,PRETRIAL,Parchment,Owen,NULL,Male,African-American,04/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/26/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +59973,68769,62347,PRETRIAL,Parchment,Owen,NULL,Male,African-American,04/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/26/13 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +59973,68769,62347,PRETRIAL,Parchment,Owen,NULL,Male,African-American,04/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59977,68774,62352,PRETRIAL,Robinson,Rod,NULL,Male,African-American,10/08/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/26/13 0:00,2,Medium,7,Risk of Violence,-3.16,1,Low,New,1,0 +59977,68774,62352,PRETRIAL,Robinson,Rod,NULL,Male,African-American,10/08/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +59977,68774,62352,PRETRIAL,Robinson,Rod,NULL,Male,African-American,10/08/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/26/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59982,68781,62358,PRETRIAL,Lamons,Racquel,NULL,Female,African-American,01/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +59982,68781,62358,PRETRIAL,Lamons,Racquel,NULL,Female,African-American,01/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,4,High,8,Risk of Recidivism,0.3,9,High,New,1,0 +59982,68781,62358,PRETRIAL,Lamons,Racquel,NULL,Female,African-American,01/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +28532,68766,27577,PRETRIAL,POUX,JUSTIN,NULL,Male,African-American,08/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,Copy,1,0 +28532,68766,27577,PRETRIAL,POUX,JUSTIN,NULL,Male,African-American,08/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,Copy,1,0 +28532,68766,27577,PRETRIAL,POUX,JUSTIN,NULL,Male,African-American,08/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +59972,68768,62346,PRETRIAL,Lall,Haryidial,NULL,Male,Oriental,01/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/26/13 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +59972,68768,62346,PRETRIAL,Lall,Haryidial,NULL,Male,Oriental,01/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/26/13 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +59972,68768,62346,PRETRIAL,Lall,Haryidial,NULL,Male,Oriental,01/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +33700,68787,62363,PRETRIAL,Hughes,Stephanie,Ann,Male,Caucasian,09/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +33700,68787,62363,PRETRIAL,Hughes,Stephanie,Ann,Male,Caucasian,09/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +33700,68787,62363,PRETRIAL,Hughes,Stephanie,Ann,Male,Caucasian,09/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,39,10,High,New,1,0 +59979,68776,62354,PRETRIAL,Hourruitiner,Jorge,NULL,Male,Hispanic,03/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +59979,68776,62354,PRETRIAL,Hourruitiner,Jorge,NULL,Male,Hispanic,03/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +59979,68776,62354,PRETRIAL,Hourruitiner,Jorge,NULL,Male,Hispanic,03/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59974,68771,62349,PRETRIAL,Marrero,Corey,Jacob,Male,Caucasian,11/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,2,Medium,7,Risk of Violence,-1.51,6,Medium,New,1,0 +59974,68771,62349,PRETRIAL,Marrero,Corey,Jacob,Male,Caucasian,11/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +59974,68771,62349,PRETRIAL,Marrero,Corey,Jacob,Male,Caucasian,11/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +45924,68765,54400,PRETRIAL,Salamanca,Avisay,NULL,Male,Hispanic,08/09/65,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,12/26/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,Copy,1,0 +45924,68765,54400,PRETRIAL,Salamanca,Avisay,NULL,Male,Hispanic,08/09/65,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,12/26/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,Copy,1,0 +45924,68765,54400,PRETRIAL,Salamanca,Avisay,NULL,Male,Hispanic,08/09/65,22,Risk and Prescreen,Intake,Spanish,Other,Probation,Married,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +51560,68786,62362,PRETRIAL,pierre,majorie,NULL,Female,African-American,10/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,New,1,0 +51560,68786,62362,PRETRIAL,pierre,majorie,NULL,Female,African-American,10/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.2,7,Medium,New,1,0 +51560,68786,62362,PRETRIAL,pierre,majorie,NULL,Female,African-American,10/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59797,68782,62157,PRETRIAL,Inostroza,Axel,NULL,Male,Hispanic,10/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,Copy,1,0 +59797,68782,62157,PRETRIAL,Inostroza,Axel,NULL,Male,Hispanic,10/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,Copy,1,0 +59797,68782,62157,PRETRIAL,Inostroza,Axel,NULL,Male,Hispanic,10/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +59980,68777,62355,PRETRIAL,Mauro,John,NULL,Male,Caucasian,03/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +59980,68777,62355,PRETRIAL,Mauro,John,NULL,Male,Caucasian,03/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +59980,68777,62355,PRETRIAL,Mauro,John,NULL,Male,Caucasian,03/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +12858,68770,62348,PRETRIAL,SOLVAN,ENRIQUE,NULL,Male,Hispanic,04/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +12858,68770,62348,PRETRIAL,SOLVAN,ENRIQUE,NULL,Male,Hispanic,04/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +12858,68770,62348,PRETRIAL,SOLVAN,ENRIQUE,NULL,Male,Hispanic,04/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59971,68767,62345,PRETRIAL,Franklin,Antron,NULL,Male,African-American,12/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,4,High,7,Risk of Violence,-0.61,10,High,New,1,0 +59971,68767,62345,PRETRIAL,Franklin,Antron,NULL,Male,African-American,12/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,4,High,8,Risk of Recidivism,0.81,10,High,New,1,0 +59971,68767,62345,PRETRIAL,Franklin,Antron,NULL,Male,African-American,12/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59650,68780,62011,PRETRIAL,CORKER,LIAS,NULL,Male,African-American,11/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.22,8,High,Copy,1,0 +59650,68780,62011,PRETRIAL,CORKER,LIAS,NULL,Male,African-American,11/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,7,Medium,Copy,1,0 +59650,68780,62011,PRETRIAL,CORKER,LIAS,NULL,Male,African-American,11/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +59975,68772,62350,PRETRIAL,Gonzalez,Luis,A,Male,Caucasian,05/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +59975,68772,62350,PRETRIAL,Gonzalez,Luis,A,Male,Caucasian,05/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +59975,68772,62350,PRETRIAL,Gonzalez,Luis,A,Male,Caucasian,05/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59983,68783,62359,PRETRIAL,McKinney,Darryl,NULL,Male,African-American,06/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/26/13 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +59983,68783,62359,PRETRIAL,McKinney,Darryl,NULL,Male,African-American,06/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/26/13 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +59983,68783,62359,PRETRIAL,McKinney,Darryl,NULL,Male,African-American,06/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +59978,68775,62353,PRETRIAL,Firmin,Daniel,C,Male,African-American,05/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +59978,68775,62353,PRETRIAL,Firmin,Daniel,C,Male,African-American,05/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +59978,68775,62353,PRETRIAL,Firmin,Daniel,C,Male,African-American,05/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60004,68809,62384,PRETRIAL,SINGH,RADICA,DEVI,Female,Caucasian,03/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +60004,68809,62384,PRETRIAL,SINGH,RADICA,DEVI,Female,Caucasian,03/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +60004,68809,62384,PRETRIAL,SINGH,RADICA,DEVI,Female,Caucasian,03/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59985,68788,62364,PRETRIAL,Zachary,Samantha,NULL,Female,Caucasian,11/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +59985,68788,62364,PRETRIAL,Zachary,Samantha,NULL,Female,Caucasian,11/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +59985,68788,62364,PRETRIAL,Zachary,Samantha,NULL,Female,Caucasian,11/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59997,68801,62377,PRETRIAL,Adhemar,Bianca,NULL,Female,African-American,07/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +59997,68801,62377,PRETRIAL,Adhemar,Bianca,NULL,Female,African-American,07/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +59997,68801,62377,PRETRIAL,Adhemar,Bianca,NULL,Female,African-American,07/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59989,68793,62369,PRETRIAL,Rowe,Derrick,NULL,Male,Other,08/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +59989,68793,62369,PRETRIAL,Rowe,Derrick,NULL,Male,Other,08/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +59989,68793,62369,PRETRIAL,Rowe,Derrick,NULL,Male,Other,08/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59992,68796,62372,PRETRIAL,Etienne,Edwin,NULL,Male,African-American,11/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +59992,68796,62372,PRETRIAL,Etienne,Edwin,NULL,Male,African-American,11/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +59992,68796,62372,PRETRIAL,Etienne,Edwin,NULL,Male,African-American,11/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60000,68804,62380,PRETRIAL,Magana,Rafael,NULL,Male,Hispanic,05/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +60000,68804,62380,PRETRIAL,Magana,Rafael,NULL,Male,Hispanic,05/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +60000,68804,62380,PRETRIAL,Magana,Rafael,NULL,Male,Hispanic,05/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59987,68791,62367,PRETRIAL,Batifora,Tomas,NULL,Male,Hispanic,09/20/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +59987,68791,62367,PRETRIAL,Batifora,Tomas,NULL,Male,Hispanic,09/20/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +59987,68791,62367,PRETRIAL,Batifora,Tomas,NULL,Male,Hispanic,09/20/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59994,68798,62374,PRETRIAL,Louis,Willins,NULL,Male,Other,05/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +59994,68798,62374,PRETRIAL,Louis,Willins,NULL,Male,Other,05/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +59994,68798,62374,PRETRIAL,Louis,Willins,NULL,Male,Other,05/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59996,68800,62376,PRETRIAL,McKinley,Mary,Ada,Female,African-American,10/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +59996,68800,62376,PRETRIAL,McKinley,Mary,Ada,Female,African-American,10/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +59996,68800,62376,PRETRIAL,McKinley,Mary,Ada,Female,African-American,10/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60003,68807,62383,PRETRIAL,Wilson,Tony,NULL,Male,African-American,10/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/27/13 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +60003,68807,62383,PRETRIAL,Wilson,Tony,NULL,Male,African-American,10/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +60003,68807,62383,PRETRIAL,Wilson,Tony,NULL,Male,African-American,10/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/27/13 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +59999,68803,62379,PRETRIAL,Miscavage,Alan,R,Male,Caucasian,03/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +59999,68803,62379,PRETRIAL,Miscavage,Alan,R,Male,Caucasian,03/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,10,High,New,1,0 +59999,68803,62379,PRETRIAL,Miscavage,Alan,R,Male,Caucasian,03/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,41,10,High,New,1,0 +60001,68805,62381,Probation,REINIGER,LAVANDA,L,Female,African-American,07/31/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/27/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +60001,68805,62381,Probation,REINIGER,LAVANDA,L,Female,African-American,07/31/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/27/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,9,High,New,1,0 +60001,68805,62381,Probation,REINIGER,LAVANDA,L,Female,African-American,07/31/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/27/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59993,68797,62373,PRETRIAL,Cooper,Cassius,NULL,Male,African-American,02/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +59993,68797,62373,PRETRIAL,Cooper,Cassius,NULL,Male,African-American,02/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +59993,68797,62373,PRETRIAL,Cooper,Cassius,NULL,Male,African-American,02/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59998,68802,62378,PRETRIAL,Butts,David,Lee,Male,African-American,05/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +59998,68802,62378,PRETRIAL,Butts,David,Lee,Male,African-American,05/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +59998,68802,62378,PRETRIAL,Butts,David,Lee,Male,African-American,05/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +59986,68789,62365,PRETRIAL,Larrieux,Jovan,NULL,Male,African-American,01/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +59986,68789,62365,PRETRIAL,Larrieux,Jovan,NULL,Male,African-American,01/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +59986,68789,62365,PRETRIAL,Larrieux,Jovan,NULL,Male,African-American,01/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59991,68795,62371,PRETRIAL,Rombardo,Rocco,NULL,Male,Caucasian,02/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +59991,68795,62371,PRETRIAL,Rombardo,Rocco,NULL,Male,Caucasian,02/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +59991,68795,62371,PRETRIAL,Rombardo,Rocco,NULL,Male,Caucasian,02/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60005,68810,62385,PRETRIAL,CARLO,DONALD,A,Male,Caucasian,12/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/27/13 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +60005,68810,62385,PRETRIAL,CARLO,DONALD,A,Male,Caucasian,12/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/27/13 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +60005,68810,62385,PRETRIAL,CARLO,DONALD,A,Male,Caucasian,12/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59990,68794,62370,PRETRIAL,Adhemar,Briana,NULL,Female,African-American,07/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +59990,68794,62370,PRETRIAL,Adhemar,Briana,NULL,Female,African-American,07/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +59990,68794,62370,PRETRIAL,Adhemar,Briana,NULL,Female,African-American,07/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57454,68790,62366,PRETRIAL,Johnson,Tremaine,NULL,Male,African-American,05/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +57454,68790,62366,PRETRIAL,Johnson,Tremaine,NULL,Male,African-American,05/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,4,High,8,Risk of Recidivism,0.1,8,High,New,1,0 +57454,68790,62366,PRETRIAL,Johnson,Tremaine,NULL,Male,African-American,05/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59988,68792,62368,PRETRIAL,Ebanks,Oneil,NULL,Male,Other,01/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +59988,68792,62368,PRETRIAL,Ebanks,Oneil,NULL,Male,Other,01/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +59988,68792,62368,PRETRIAL,Ebanks,Oneil,NULL,Male,Other,01/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59995,68799,62375,PRETRIAL,Joseph,Kadeem,A,Male,African-American,07/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +59995,68799,62375,PRETRIAL,Joseph,Kadeem,A,Male,African-American,07/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +59995,68799,62375,PRETRIAL,Joseph,Kadeem,A,Male,African-American,07/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60002,68806,62382,PRETRIAL,Prevelhomme,Lance,NULL,Male,African-American,01/22/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/27/13 0:00,4,High,7,Risk of Violence,-0.55,10,High,New,1,0 +60002,68806,62382,PRETRIAL,Prevelhomme,Lance,NULL,Male,African-American,01/22/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/27/13 0:00,4,High,8,Risk of Recidivism,0.36,8,High,New,1,0 +60002,68806,62382,PRETRIAL,Prevelhomme,Lance,NULL,Male,African-American,01/22/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/27/13 0:00,4,High,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +60008,68813,62388,PRETRIAL,JOHNSON,STEVIE,LAMAR,Male,African-American,07/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/28/13 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +60008,68813,62388,PRETRIAL,JOHNSON,STEVIE,LAMAR,Male,African-American,07/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +60008,68813,62388,PRETRIAL,JOHNSON,STEVIE,LAMAR,Male,African-American,07/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/28/13 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60018,68827,62401,PRETRIAL,wilkins,darius,NULL,Male,African-American,02/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +60018,68827,62401,PRETRIAL,wilkins,darius,NULL,Male,African-American,02/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +60018,68827,62401,PRETRIAL,wilkins,darius,NULL,Male,African-American,02/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +7022,68815,52282,PRETRIAL,mickles,keion,NULL,Male,African-American,10/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,Copy,1,0 +7022,68815,52282,PRETRIAL,mickles,keion,NULL,Male,African-American,10/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.67,10,High,Copy,1,0 +7022,68815,52282,PRETRIAL,mickles,keion,NULL,Male,African-American,10/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +60020,68829,62403,PRETRIAL,juma,ali,NULL,Male,Caucasian,05/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +60020,68829,62403,PRETRIAL,juma,ali,NULL,Male,Caucasian,05/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +60020,68829,62403,PRETRIAL,juma,ali,NULL,Male,Caucasian,05/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60012,68820,62394,PRETRIAL,Valentin,Joel,NULL,Male,Hispanic,01/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +60012,68820,62394,PRETRIAL,Valentin,Joel,NULL,Male,Hispanic,01/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +60012,68820,62394,PRETRIAL,Valentin,Joel,NULL,Male,Hispanic,01/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60022,68831,62405,PRETRIAL,ARTZE,LISETTE,STEPHANIE,Female,Caucasian,09/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +60022,68831,62405,PRETRIAL,ARTZE,LISETTE,STEPHANIE,Female,Caucasian,09/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +60022,68831,62405,PRETRIAL,ARTZE,LISETTE,STEPHANIE,Female,Caucasian,09/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50834,68823,62397,PRETRIAL,Lewis,Dalton,NULL,Male,Caucasian,06/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +50834,68823,62397,PRETRIAL,Lewis,Dalton,NULL,Male,Caucasian,06/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +50834,68823,62397,PRETRIAL,Lewis,Dalton,NULL,Male,Caucasian,06/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60017,68826,62400,PRETRIAL,jackson,anthony,NULL,Male,African-American,06/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +60017,68826,62400,PRETRIAL,jackson,anthony,NULL,Male,African-American,06/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +60017,68826,62400,PRETRIAL,jackson,anthony,NULL,Male,African-American,06/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50289,68818,62392,PRETRIAL,Bacafunes,Yeliza,NULL,Female,Hispanic,02/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +50289,68818,62392,PRETRIAL,Bacafunes,Yeliza,NULL,Female,Hispanic,02/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +50289,68818,62392,PRETRIAL,Bacafunes,Yeliza,NULL,Female,Hispanic,02/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +12806,68816,62390,PRETRIAL,Bocanegra,George,NULL,Male,Hispanic,04/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +12806,68816,62390,PRETRIAL,Bocanegra,George,NULL,Male,Hispanic,04/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,4,High,8,Risk of Recidivism,0.22,8,High,New,1,0 +12806,68816,62390,PRETRIAL,Bocanegra,George,NULL,Male,Hispanic,04/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60007,68812,62387,PRETRIAL,Hinzey,Jameson,NULL,Male,African-American,08/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +60007,68812,62387,PRETRIAL,Hinzey,Jameson,NULL,Male,African-American,08/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +60007,68812,62387,PRETRIAL,Hinzey,Jameson,NULL,Male,African-American,08/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60011,68819,62393,PRETRIAL,Pierrelouis,Kevin,Leroy,Male,African-American,10/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +60011,68819,62393,PRETRIAL,Pierrelouis,Kevin,Leroy,Male,African-American,10/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +60011,68819,62393,PRETRIAL,Pierrelouis,Kevin,Leroy,Male,African-American,10/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60013,68821,62395,PRETRIAL,MONTGOMERY,RODNEY,JOEL,Male,African-American,09/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +60013,68821,62395,PRETRIAL,MONTGOMERY,RODNEY,JOEL,Male,African-American,09/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +60013,68821,62395,PRETRIAL,MONTGOMERY,RODNEY,JOEL,Male,African-American,09/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60019,68828,62402,PRETRIAL,henry,sidney,NULL,Male,African-American,04/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +60019,68828,62402,PRETRIAL,henry,sidney,NULL,Male,African-American,04/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +60019,68828,62402,PRETRIAL,henry,sidney,NULL,Male,African-American,04/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60016,68825,62399,PRETRIAL,Jorgensen,Lindsey,NULL,Male,Caucasian,06/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +60016,68825,62399,PRETRIAL,Jorgensen,Lindsey,NULL,Male,Caucasian,06/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +60016,68825,62399,PRETRIAL,Jorgensen,Lindsey,NULL,Male,Caucasian,06/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60010,68817,62391,PRETRIAL,Perkins,Alexsis,Glenndena,Male,Caucasian,12/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +60010,68817,62391,PRETRIAL,Perkins,Alexsis,Glenndena,Male,Caucasian,12/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +60010,68817,62391,PRETRIAL,Perkins,Alexsis,Glenndena,Male,Caucasian,12/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60015,68824,62398,PRETRIAL,Rodriguez-Bustios,Nicholas,NULL,Male,Caucasian,09/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +60015,68824,62398,PRETRIAL,Rodriguez-Bustios,Nicholas,NULL,Male,Caucasian,09/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,2,Medium,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +60015,68824,62398,PRETRIAL,Rodriguez-Bustios,Nicholas,NULL,Male,Caucasian,09/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60014,68822,62396,PRETRIAL,FLOYD,ERIC,NULL,Male,African-American,07/12/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +60014,68822,62396,PRETRIAL,FLOYD,ERIC,NULL,Male,African-American,07/12/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +60014,68822,62396,PRETRIAL,FLOYD,ERIC,NULL,Male,African-American,07/12/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60009,68814,62389,PRETRIAL,Heidegger,Kevin,NULL,Male,Caucasian,02/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +60009,68814,62389,PRETRIAL,Heidegger,Kevin,NULL,Male,Caucasian,02/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +60009,68814,62389,PRETRIAL,Heidegger,Kevin,NULL,Male,Caucasian,02/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57479,68835,62409,PRETRIAL,Brutus,Irvans,NULL,Male,Other,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +57479,68835,62409,PRETRIAL,Brutus,Irvans,NULL,Male,Other,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +57479,68835,62409,PRETRIAL,Brutus,Irvans,NULL,Male,Other,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +18271,68840,62411,PRETRIAL,Dixon,Jamar,Dwayne,Male,African-American,07/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +18271,68840,62411,PRETRIAL,Dixon,Jamar,Dwayne,Male,African-American,07/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.08,10,High,New,1,0 +18271,68840,62411,PRETRIAL,Dixon,Jamar,Dwayne,Male,African-American,07/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60023,68832,62406,PRETRIAL,Diaz,Lazaro,NULL,Male,Hispanic,05/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +60023,68832,62406,PRETRIAL,Diaz,Lazaro,NULL,Male,Hispanic,05/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +60023,68832,62406,PRETRIAL,Diaz,Lazaro,NULL,Male,Hispanic,05/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +20972,68838,30644,PRETRIAL,BLACK,DANNY,NULL,Male,African-American,12/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,4,High,7,Risk of Violence,-1.17,8,High,Copy,1,0 +20972,68838,30644,PRETRIAL,BLACK,DANNY,NULL,Male,African-American,12/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,4,High,8,Risk of Recidivism,0.24,8,High,Copy,1,0 +20972,68838,30644,PRETRIAL,BLACK,DANNY,NULL,Male,African-American,12/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +60025,68833,62407,PRETRIAL,Parker,Khadijha,NULL,Female,African-American,03/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +60025,68833,62407,PRETRIAL,Parker,Khadijha,NULL,Female,African-American,03/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,7,Medium,New,1,0 +60025,68833,62407,PRETRIAL,Parker,Khadijha,NULL,Female,African-American,03/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +43296,68837,43222,Probation,Henderson,Kevin,NULL,Male,African-American,08/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/29/13 0:00,2,Medium,7,Risk of Violence,-2.93,2,Low,Copy,1,0 +43296,68837,43222,Probation,Henderson,Kevin,NULL,Male,African-American,08/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/29/13 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,Copy,1,0 +43296,68837,43222,Probation,Henderson,Kevin,NULL,Male,African-American,08/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/29/13 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +24763,68839,45899,PRETRIAL,MOXIE,BRANDON,NULL,Male,African-American,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,Copy,1,0 +24763,68839,45899,PRETRIAL,MOXIE,BRANDON,NULL,Male,African-American,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,Copy,1,0 +24763,68839,45899,PRETRIAL,MOXIE,BRANDON,NULL,Male,African-American,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +60027,68841,62412,PRETRIAL,burns,Ronald,NULL,Male,African-American,07/16/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/29/13 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +60027,68841,62412,PRETRIAL,burns,Ronald,NULL,Male,African-American,07/16/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/29/13 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +60027,68841,62412,PRETRIAL,burns,Ronald,NULL,Male,African-American,07/16/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/29/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60024,68836,62410,PRETRIAL,RIVERA,MICHAEL,NULL,Male,Other,11/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +60024,68836,62410,PRETRIAL,RIVERA,MICHAEL,NULL,Male,Other,11/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +60024,68836,62410,PRETRIAL,RIVERA,MICHAEL,NULL,Male,Other,11/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +26033,68834,62408,PRETRIAL,GUAGLUARDI,DOMINIC,NULL,Male,Caucasian,10/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/29/13 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +26033,68834,62408,PRETRIAL,GUAGLUARDI,DOMINIC,NULL,Male,Caucasian,10/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/29/13 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +26033,68834,62408,PRETRIAL,GUAGLUARDI,DOMINIC,NULL,Male,Caucasian,10/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/29/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60040,68857,62427,PRETRIAL,KING,BRIANNA,NULL,Female,African-American,08/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +60040,68857,62427,PRETRIAL,KING,BRIANNA,NULL,Female,African-American,08/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +60040,68857,62427,PRETRIAL,KING,BRIANNA,NULL,Female,African-American,08/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60038,68855,62425,PRETRIAL,SMILEY,ALLEN,NULL,Male,African-American,03/09/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +60038,68855,62425,PRETRIAL,SMILEY,ALLEN,NULL,Male,African-American,03/09/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +60038,68855,62425,PRETRIAL,SMILEY,ALLEN,NULL,Male,African-American,03/09/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60034,68850,62421,PRETRIAL,SPENCEBURRELL,NICOLA,LATOYA,Female,Other,06/30/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +60034,68850,62421,PRETRIAL,SPENCEBURRELL,NICOLA,LATOYA,Female,Other,06/30/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +60034,68850,62421,PRETRIAL,SPENCEBURRELL,NICOLA,LATOYA,Female,Other,06/30/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60051,68871,62438,PRETRIAL,HENDERSON,CHRISTOPHER,NULL,Male,Caucasian,11/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +60051,68871,62438,PRETRIAL,HENDERSON,CHRISTOPHER,NULL,Male,Caucasian,11/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +60051,68871,62438,PRETRIAL,HENDERSON,CHRISTOPHER,NULL,Male,Caucasian,11/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60045,68862,62432,Probation,Curry,Jawaun,NULL,Male,African-American,08/06/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/30/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.79,9,High,New,1,0 +60045,68862,62432,Probation,Curry,Jawaun,NULL,Male,African-American,08/06/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/30/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +60045,68862,62432,Probation,Curry,Jawaun,NULL,Male,African-American,08/06/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/30/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60052,68873,62440,PRETRIAL,Brown,Clive,NULL,Male,African-American,06/16/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +60052,68873,62440,PRETRIAL,Brown,Clive,NULL,Male,African-American,06/16/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +60052,68873,62440,PRETRIAL,Brown,Clive,NULL,Male,African-American,06/16/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60035,68852,62422,PRETRIAL,Lopez,Carlos,NULL,Male,Hispanic,06/01/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +60035,68852,62422,PRETRIAL,Lopez,Carlos,NULL,Male,Hispanic,06/01/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +60035,68852,62422,PRETRIAL,Lopez,Carlos,NULL,Male,Hispanic,06/01/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60030,68844,62415,PRETRIAL,TIMES,MICHAEL,NULL,Male,African-American,06/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +60030,68844,62415,PRETRIAL,TIMES,MICHAEL,NULL,Male,African-American,06/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +60030,68844,62415,PRETRIAL,TIMES,MICHAEL,NULL,Male,African-American,06/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60043,68860,62430,PRETRIAL,Gilbert,Robert,NULL,Male,Caucasian,02/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/30/13 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +60043,68860,62430,PRETRIAL,Gilbert,Robert,NULL,Male,Caucasian,02/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/30/13 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +60043,68860,62430,PRETRIAL,Gilbert,Robert,NULL,Male,Caucasian,02/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60037,68854,62424,PRETRIAL,Kaiyal,Darwish,NULL,Male,Caucasian,10/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +60037,68854,62424,PRETRIAL,Kaiyal,Darwish,NULL,Male,Caucasian,10/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +60037,68854,62424,PRETRIAL,Kaiyal,Darwish,NULL,Male,Caucasian,10/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60046,68863,62433,Probation,CLARKE,KRISTOPHER,J,Male,Caucasian,10/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/30/13 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +60046,68863,62433,Probation,CLARKE,KRISTOPHER,J,Male,Caucasian,10/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/30/13 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +60046,68863,62433,Probation,CLARKE,KRISTOPHER,J,Male,Caucasian,10/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60028,68842,62413,PRETRIAL,Baczewski,Lester,NULL,Male,Caucasian,08/31/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/30/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +60028,68842,62413,PRETRIAL,Baczewski,Lester,NULL,Male,Caucasian,08/31/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/30/13 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +60028,68842,62413,PRETRIAL,Baczewski,Lester,NULL,Male,Caucasian,08/31/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60033,68849,62420,PRETRIAL,JIRKA,DAVIS,NULL,Male,Caucasian,02/05/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +60033,68849,62420,PRETRIAL,JIRKA,DAVIS,NULL,Male,Caucasian,02/05/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +60033,68849,62420,PRETRIAL,JIRKA,DAVIS,NULL,Male,Caucasian,02/05/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60039,68856,62426,PRETRIAL,Haffner,Matthew,NULL,Male,Caucasian,12/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/13 0:00,2,Medium,7,Risk of Violence,-1.33,7,Medium,New,1,0 +60039,68856,62426,PRETRIAL,Haffner,Matthew,NULL,Male,Caucasian,12/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +60039,68856,62426,PRETRIAL,Haffner,Matthew,NULL,Male,Caucasian,12/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/13 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60050,68870,62437,Probation,fewcett,forrest,NULL,Male,Caucasian,09/13/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/30/13 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +60050,68870,62437,Probation,fewcett,forrest,NULL,Male,Caucasian,09/13/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/30/13 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +60050,68870,62437,Probation,fewcett,forrest,NULL,Male,Caucasian,09/13/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60053,68872,62439,PRETRIAL,Quiles,Kelvin,NULL,Male,Caucasian,07/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/30/13 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +60053,68872,62439,PRETRIAL,Quiles,Kelvin,NULL,Male,Caucasian,07/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/30/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +60053,68872,62439,PRETRIAL,Quiles,Kelvin,NULL,Male,Caucasian,07/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60036,68853,62423,PRETRIAL,PETRI,DARREN,NULL,Male,Caucasian,01/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +60036,68853,62423,PRETRIAL,PETRI,DARREN,NULL,Male,Caucasian,01/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +60036,68853,62423,PRETRIAL,PETRI,DARREN,NULL,Male,Caucasian,01/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60042,68859,62429,PRETRIAL,Britton,Raymond,NULL,Male,African-American,05/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +60042,68859,62429,PRETRIAL,Britton,Raymond,NULL,Male,African-American,05/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +60042,68859,62429,PRETRIAL,Britton,Raymond,NULL,Male,African-American,05/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60049,68866,62436,Probation,HOLTON,DONALD,NULL,Male,African-American,09/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +60049,68866,62436,Probation,HOLTON,DONALD,NULL,Male,African-American,09/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +60049,68866,62436,Probation,HOLTON,DONALD,NULL,Male,African-American,09/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60017,68867,62400,PRETRIAL,jackson,anthony,NULL,Male,African-American,06/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,Copy,1,0 +60017,68867,62400,PRETRIAL,jackson,anthony,NULL,Male,African-American,06/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,Copy,1,0 +60017,68867,62400,PRETRIAL,jackson,anthony,NULL,Male,African-American,06/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +60054,68874,62441,Probation,Licata,Anthony,NULL,Male,Hispanic,09/27/85,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +60054,68874,62441,Probation,Licata,Anthony,NULL,Male,Hispanic,09/27/85,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +60054,68874,62441,Probation,Licata,Anthony,NULL,Male,Hispanic,09/27/85,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60031,68845,62416,PRETRIAL,FRIEDLAND,MARK,ABRAHAM,Male,Caucasian,07/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +60031,68845,62416,PRETRIAL,FRIEDLAND,MARK,ABRAHAM,Male,Caucasian,07/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-2.56,1,Low,New,1,0 +60031,68845,62416,PRETRIAL,FRIEDLAND,MARK,ABRAHAM,Male,Caucasian,07/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60032,68846,62417,PRETRIAL,Walls,Taneka,NULL,Female,African-American,04/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +60032,68846,62417,PRETRIAL,Walls,Taneka,NULL,Female,African-American,04/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +60032,68846,62417,PRETRIAL,Walls,Taneka,NULL,Female,African-American,04/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50014,68851,50954,PRETRIAL,JIMENEZ,Marius,NULL,Male,Caucasian,10/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,Copy,1,0 +50014,68851,50954,PRETRIAL,JIMENEZ,Marius,NULL,Male,Caucasian,10/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,Copy,1,0 +50014,68851,50954,PRETRIAL,JIMENEZ,Marius,NULL,Male,Caucasian,10/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +60029,68843,62414,PRETRIAL,MCDONALD,JASON,NULL,Male,African-American,10/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +60029,68843,62414,PRETRIAL,MCDONALD,JASON,NULL,Male,African-American,10/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +60029,68843,62414,PRETRIAL,MCDONALD,JASON,NULL,Male,African-American,10/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60044,68861,62431,Probation,MEYERS,RAYMOND,NULL,Male,African-American,06/18/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/13 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +60044,68861,62431,Probation,MEYERS,RAYMOND,NULL,Male,African-American,06/18/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/13 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +60044,68861,62431,Probation,MEYERS,RAYMOND,NULL,Male,African-American,06/18/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58973,68869,61228,Probation,Voltaire,Anterio,NULL,Male,African-American,12/15/92,17,All Scales,Intake,English,Other,Probation,Married,12/30/13 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,Copy,1,0 +58973,68869,61228,Probation,Voltaire,Anterio,NULL,Male,African-American,12/15/92,17,All Scales,Intake,English,Other,Probation,Married,12/30/13 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,Copy,1,0 +58973,68869,61228,Probation,Voltaire,Anterio,NULL,Male,African-American,12/15/92,17,All Scales,Intake,English,Other,Probation,Married,12/30/13 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +28536,68848,62419,PRETRIAL,Reed,Dana,NULL,Female,African-American,05/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +28536,68848,62419,PRETRIAL,Reed,Dana,NULL,Female,African-American,05/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +28536,68848,62419,PRETRIAL,Reed,Dana,NULL,Female,African-American,05/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/13 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +60060,68882,62448,PRETRIAL,Resiles,Davonte,Omar,Male,African-American,09/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,4,High,7,Risk of Violence,-0.68,9,High,New,1,0 +60060,68882,62448,PRETRIAL,Resiles,Davonte,Omar,Male,African-American,09/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +60060,68882,62448,PRETRIAL,Resiles,Davonte,Omar,Male,African-American,09/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60068,68890,62456,PRETRIAL,THOMAS,HEATHER,NULL,Female,Caucasian,05/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +60068,68890,62456,PRETRIAL,THOMAS,HEATHER,NULL,Female,Caucasian,05/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +60068,68890,62456,PRETRIAL,THOMAS,HEATHER,NULL,Female,Caucasian,05/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +60071,68895,62460,Probation,brantley,lamont,NULL,Male,African-American,02/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,12/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +60071,68895,62460,Probation,brantley,lamont,NULL,Male,African-American,02/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,12/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +60071,68895,62460,Probation,brantley,lamont,NULL,Male,African-American,02/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,12/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +60065,68887,62453,PRETRIAL,Robbins,Genny,NULL,Female,Caucasian,05/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +60065,68887,62453,PRETRIAL,Robbins,Genny,NULL,Female,Caucasian,05/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +60065,68887,62453,PRETRIAL,Robbins,Genny,NULL,Female,Caucasian,05/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60075,68898,62463,PRETRIAL,Walsh,Dawn,Christina,Female,Caucasian,09/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/13 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +60075,68898,62463,PRETRIAL,Walsh,Dawn,Christina,Female,Caucasian,09/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +60075,68898,62463,PRETRIAL,Walsh,Dawn,Christina,Female,Caucasian,09/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/13 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,New,1,0 +60076,68900,62464,Probation,JnCharles,Gordon,NULL,Male,African-American,01/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +60076,68900,62464,Probation,JnCharles,Gordon,NULL,Male,African-American,01/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.7,10,High,New,1,0 +60076,68900,62464,Probation,JnCharles,Gordon,NULL,Male,African-American,01/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60057,68877,62444,PRETRIAL,MOODY,SIDNEY,MAURICE,Male,African-American,10/27/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/31/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +60057,68877,62444,PRETRIAL,MOODY,SIDNEY,MAURICE,Male,African-American,10/27/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/31/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +60057,68877,62444,PRETRIAL,MOODY,SIDNEY,MAURICE,Male,African-American,10/27/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60067,68888,62454,PRETRIAL,Hadler,Alison,Marie,Female,Caucasian,03/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +60067,68888,62454,PRETRIAL,Hadler,Alison,Marie,Female,Caucasian,03/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +60067,68888,62454,PRETRIAL,Hadler,Alison,Marie,Female,Caucasian,03/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60055,68875,62442,PRETRIAL,Raoui,Tariq,NULL,Male,Caucasian,03/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/31/13 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +60055,68875,62442,PRETRIAL,Raoui,Tariq,NULL,Male,Caucasian,03/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/31/13 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +60055,68875,62442,PRETRIAL,Raoui,Tariq,NULL,Male,Caucasian,03/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60062,68884,62450,PRETRIAL,CACA,AGLI,NULL,Male,Caucasian,07/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +60062,68884,62450,PRETRIAL,CACA,AGLI,NULL,Male,Caucasian,07/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +60062,68884,62450,PRETRIAL,CACA,AGLI,NULL,Male,Caucasian,07/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +33217,68879,32298,PRETRIAL,Hare,Brandon,NULL,Male,Caucasian,09/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.53,3,Low,Copy,1,0 +33217,68879,32298,PRETRIAL,Hare,Brandon,NULL,Male,Caucasian,09/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,Copy,1,0 +33217,68879,32298,PRETRIAL,Hare,Brandon,NULL,Male,Caucasian,09/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +60059,68881,62447,PRETRIAL,Alayo,Oscar,Edward,Male,Caucasian,05/06/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/31/13 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +60059,68881,62447,PRETRIAL,Alayo,Oscar,Edward,Male,Caucasian,05/06/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/31/13 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +60059,68881,62447,PRETRIAL,Alayo,Oscar,Edward,Male,Caucasian,05/06/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60066,68889,62455,PRETRIAL,FONTES,CARMEN,NULL,Female,Caucasian,09/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +60066,68889,62455,PRETRIAL,FONTES,CARMEN,NULL,Female,Caucasian,09/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +60066,68889,62455,PRETRIAL,FONTES,CARMEN,NULL,Female,Caucasian,09/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60070,68894,62459,Probation,Mitchell,Malissa,Maria,Female,Caucasian,05/11/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/31/13 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +60070,68894,62459,Probation,Mitchell,Malissa,Maria,Female,Caucasian,05/11/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/31/13 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +60070,68894,62459,Probation,Mitchell,Malissa,Maria,Female,Caucasian,05/11/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60064,68886,62452,PRETRIAL,FEDERICK,EBONEY,TIYASHA,Female,African-American,06/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +60064,68886,62452,PRETRIAL,FEDERICK,EBONEY,TIYASHA,Female,African-American,06/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +60064,68886,62452,PRETRIAL,FEDERICK,EBONEY,TIYASHA,Female,African-American,06/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +25209,68880,62446,PRETRIAL,Williams,Delvin,NULL,Male,African-American,05/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +25209,68880,62446,PRETRIAL,Williams,Delvin,NULL,Male,African-American,05/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.84,10,High,New,1,0 +25209,68880,62446,PRETRIAL,Williams,Delvin,NULL,Male,African-American,05/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60074,68897,62462,PRETRIAL,Clark,Adam,NULL,Male,Caucasian,01/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +60074,68897,62462,PRETRIAL,Clark,Adam,NULL,Male,Caucasian,01/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +60074,68897,62462,PRETRIAL,Clark,Adam,NULL,Male,Caucasian,01/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60056,68876,62443,PRETRIAL,Reyes,Juan,Luis,Male,Hispanic,09/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +60056,68876,62443,PRETRIAL,Reyes,Juan,Luis,Male,Hispanic,09/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +60056,68876,62443,PRETRIAL,Reyes,Juan,Luis,Male,Hispanic,09/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60061,68883,62449,PRETRIAL,GROSHOLZ,TREVOR,NULL,Male,Caucasian,12/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/31/13 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +60061,68883,62449,PRETRIAL,GROSHOLZ,TREVOR,NULL,Male,Caucasian,12/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/31/13 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +60061,68883,62449,PRETRIAL,GROSHOLZ,TREVOR,NULL,Male,Caucasian,12/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60063,68885,62451,PRETRIAL,Guerra,Brandon,NULL,Male,Caucasian,11/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +60063,68885,62451,PRETRIAL,Guerra,Brandon,NULL,Male,Caucasian,11/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +60063,68885,62451,PRETRIAL,Guerra,Brandon,NULL,Male,Caucasian,11/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60058,68878,62445,PRETRIAL,Diaz,Michael,Thomas,Male,Hispanic,02/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +60058,68878,62445,PRETRIAL,Diaz,Michael,Thomas,Male,Hispanic,02/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +60058,68878,62445,PRETRIAL,Diaz,Michael,Thomas,Male,Hispanic,02/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/13 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60069,68892,62457,Probation,sheppard,jacobbi,NULL,Female,African-American,04/30/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/31/13 0:00,2,Medium,7,Risk of Violence,-1.43,7,Medium,New,1,0 +60069,68892,62457,Probation,sheppard,jacobbi,NULL,Female,African-American,04/30/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/31/13 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +60069,68892,62457,Probation,sheppard,jacobbi,NULL,Female,African-American,04/30/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/31/13 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60080,68906,62468,PRETRIAL,AUSTIN,STEVEN,LEONARD,Male,African-American,11/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +60080,68906,62468,PRETRIAL,AUSTIN,STEVEN,LEONARD,Male,African-American,11/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +60080,68906,62468,PRETRIAL,AUSTIN,STEVEN,LEONARD,Male,African-American,11/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60086,68913,62475,PRETRIAL,MATOS,AMY,NULL,Female,Hispanic,02/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +60086,68913,62475,PRETRIAL,MATOS,AMY,NULL,Female,Hispanic,02/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +60086,68913,62475,PRETRIAL,MATOS,AMY,NULL,Female,Hispanic,02/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +17011,68907,62469,PRETRIAL,CLERVIUS,JEHIEL,NULL,Male,African-American,12/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +17011,68907,62469,PRETRIAL,CLERVIUS,JEHIEL,NULL,Male,African-American,12/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +17011,68907,62469,PRETRIAL,CLERVIUS,JEHIEL,NULL,Male,African-American,12/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60085,68912,62474,PRETRIAL,Long,Jamal,NULL,Male,African-American,08/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +60085,68912,62474,PRETRIAL,Long,Jamal,NULL,Male,African-American,08/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +60085,68912,62474,PRETRIAL,Long,Jamal,NULL,Male,African-American,08/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +47478,68902,48044,PRETRIAL,Rodriguez,Jose,I,Male,Caucasian,05/28/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,Copy,1,0 +47478,68902,48044,PRETRIAL,Rodriguez,Jose,I,Male,Caucasian,05/28/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,Copy,1,0 +47478,68902,48044,PRETRIAL,Rodriguez,Jose,I,Male,Caucasian,05/28/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +60078,68904,62466,PRETRIAL,Schmiedeknecht,Cassi,K,Female,Caucasian,11/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +60078,68904,62466,PRETRIAL,Schmiedeknecht,Cassi,K,Female,Caucasian,11/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.1,8,High,New,1,0 +60078,68904,62466,PRETRIAL,Schmiedeknecht,Cassi,K,Female,Caucasian,11/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60083,68910,62472,PRETRIAL,Betsy,Lester,NULL,Male,African-American,10/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.07,4,Low,New,1,0 +60083,68910,62472,PRETRIAL,Betsy,Lester,NULL,Male,African-American,10/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +60083,68910,62472,PRETRIAL,Betsy,Lester,NULL,Male,African-American,10/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60082,68909,62471,PRETRIAL,MCFADDEN,RODNEY,NULL,Male,Caucasian,05/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/14 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +60082,68909,62471,PRETRIAL,MCFADDEN,RODNEY,NULL,Male,Caucasian,05/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/14 0:00,1,Low,8,Risk of Recidivism,-2.87,1,Low,New,1,0 +60082,68909,62471,PRETRIAL,MCFADDEN,RODNEY,NULL,Male,Caucasian,05/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +40508,68914,62476,Probation,satterfield,NICHOLAS,NULL,Male,Caucasian,06/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/1/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +40508,68914,62476,Probation,satterfield,NICHOLAS,NULL,Male,Caucasian,06/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/1/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +40508,68914,62476,Probation,satterfield,NICHOLAS,NULL,Male,Caucasian,06/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/1/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60079,68905,62467,PRETRIAL,Anderson,Michael,Patrick,Male,Caucasian,10/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +60079,68905,62467,PRETRIAL,Anderson,Michael,Patrick,Male,Caucasian,10/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,4,High,8,Risk of Recidivism,0.09,8,High,New,1,0 +60079,68905,62467,PRETRIAL,Anderson,Michael,Patrick,Male,Caucasian,10/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +40508,43895,40122,Probation,satterfield,NICHOLAS,NULL,Male,Caucasian,06/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Divorced,1/1/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +40508,43895,40122,Probation,satterfield,NICHOLAS,NULL,Male,Caucasian,06/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Divorced,1/1/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +40508,43895,40122,Probation,satterfield,NICHOLAS,NULL,Male,Caucasian,06/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Divorced,1/1/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60081,68908,62470,PRETRIAL,KIRBY,CHRISTOPHER,NULL,Male,Caucasian,03/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +60081,68908,62470,PRETRIAL,KIRBY,CHRISTOPHER,NULL,Male,Caucasian,03/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +60081,68908,62470,PRETRIAL,KIRBY,CHRISTOPHER,NULL,Male,Caucasian,03/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60084,68911,62473,PRETRIAL,Fogel,Arthur,Robert,Male,Caucasian,01/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +60084,68911,62473,PRETRIAL,Fogel,Arthur,Robert,Male,Caucasian,01/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +60084,68911,62473,PRETRIAL,Fogel,Arthur,Robert,Male,Caucasian,01/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60077,68903,62465,PRETRIAL,Garzon,Yaneia,NULL,Female,Caucasian,08/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +60077,68903,62465,PRETRIAL,Garzon,Yaneia,NULL,Female,Caucasian,08/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,8,High,New,1,0 +60077,68903,62465,PRETRIAL,Garzon,Yaneia,NULL,Female,Caucasian,08/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +35374,68937,34590,PRETRIAL,berry,don,NULL,Male,African-American,10/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,Copy,1,0 +35374,68937,34590,PRETRIAL,berry,don,NULL,Male,African-American,10/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,Copy,1,0 +35374,68937,34590,PRETRIAL,berry,don,NULL,Male,African-American,10/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +60090,68916,62478,PRETRIAL,Waskiw,Jonathan,NULL,Male,Caucasian,04/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +60090,68916,62478,PRETRIAL,Waskiw,Jonathan,NULL,Male,Caucasian,04/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +60090,68916,62478,PRETRIAL,Waskiw,Jonathan,NULL,Male,Caucasian,04/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60100,68929,62490,PRETRIAL,Cooper,Jonathan,NULL,Male,Caucasian,01/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +60100,68929,62490,PRETRIAL,Cooper,Jonathan,NULL,Male,Caucasian,01/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +60100,68929,62490,PRETRIAL,Cooper,Jonathan,NULL,Male,Caucasian,01/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60096,68924,62486,PRETRIAL,walker,rosetta,NULL,Female,African-American,02/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +60096,68924,62486,PRETRIAL,walker,rosetta,NULL,Female,African-American,02/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +60096,68924,62486,PRETRIAL,walker,rosetta,NULL,Female,African-American,02/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60102,68932,62493,Probation,richardson,cordy,NULL,Male,African-American,11/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +60102,68932,62493,Probation,richardson,cordy,NULL,Male,African-American,11/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +60102,68932,62493,Probation,richardson,cordy,NULL,Male,African-American,11/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60104,68935,62496,PRETRIAL,NICOLAS,JOHN,NULL,Male,African-American,10/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +60104,68935,62496,PRETRIAL,NICOLAS,JOHN,NULL,Male,African-American,10/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +60104,68935,62496,PRETRIAL,NICOLAS,JOHN,NULL,Male,African-American,10/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60101,68930,62491,PRETRIAL,FLEURY,BERNADETTE,NULL,Female,African-American,04/28/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/2/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +60101,68930,62491,PRETRIAL,FLEURY,BERNADETTE,NULL,Female,African-American,04/28/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/2/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +60101,68930,62491,PRETRIAL,FLEURY,BERNADETTE,NULL,Female,African-American,04/28/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58333,68926,60558,PRETRIAL,Indik,Jarrod,NULL,Male,Caucasian,04/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/2/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,Copy,1,0 +58333,68926,60558,PRETRIAL,Indik,Jarrod,NULL,Male,Caucasian,04/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/2/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,Copy,1,0 +58333,68926,60558,PRETRIAL,Indik,Jarrod,NULL,Male,Caucasian,04/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +57775,68940,59917,PRETRIAL,Dilullo,Vincenzo,NULL,Male,Caucasian,04/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,Copy,1,0 +57775,68940,59917,PRETRIAL,Dilullo,Vincenzo,NULL,Male,Caucasian,04/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,Copy,1,0 +57775,68940,59917,PRETRIAL,Dilullo,Vincenzo,NULL,Male,Caucasian,04/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +60099,68928,62489,Probation,Batson,Devon,NULL,Female,Caucasian,11/22/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/2/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +60099,68928,62489,Probation,Batson,Devon,NULL,Female,Caucasian,11/22/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/2/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +60099,68928,62489,Probation,Batson,Devon,NULL,Female,Caucasian,11/22/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +35374,37776,34590,PRETRIAL,berry,don,NULL,Male,African-American,10/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +35374,37776,34590,PRETRIAL,berry,don,NULL,Male,African-American,10/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +35374,37776,34590,PRETRIAL,berry,don,NULL,Male,African-American,10/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +13663,68942,62501,PRETRIAL,RICHARDS,MAX,NULL,Male,African-American,09/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +13663,68942,62501,PRETRIAL,RICHARDS,MAX,NULL,Male,African-American,09/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +13663,68942,62501,PRETRIAL,RICHARDS,MAX,NULL,Male,African-American,09/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60093,68919,62481,PRETRIAL,Clermontvl,Medius,NULL,Male,African-American,06/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/2/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +60093,68919,62481,PRETRIAL,Clermontvl,Medius,NULL,Male,African-American,06/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/2/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +60093,68919,62481,PRETRIAL,Clermontvl,Medius,NULL,Male,African-American,06/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60095,68921,62483,PRETRIAL,Statia,Brian,NULL,Male,African-American,09/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,4,High,7,Risk of Violence,-0.34,10,High,New,1,0 +60095,68921,62483,PRETRIAL,Statia,Brian,NULL,Male,African-American,09/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +60095,68921,62483,PRETRIAL,Statia,Brian,NULL,Male,African-American,09/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60091,68917,62479,PRETRIAL,Huggins,Clifton,E,Female,Caucasian,11/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +60091,68917,62479,PRETRIAL,Huggins,Clifton,E,Female,Caucasian,11/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +60091,68917,62479,PRETRIAL,Huggins,Clifton,E,Female,Caucasian,11/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +44584,68931,62492,PRETRIAL,Esteves,George,NULL,Male,Caucasian,09/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +44584,68931,62492,PRETRIAL,Esteves,George,NULL,Male,Caucasian,09/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +44584,68931,62492,PRETRIAL,Esteves,George,NULL,Male,Caucasian,09/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60110,68938,62498,PRETRIAL,KASALI,KAYODE,NULL,Male,African-American,10/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +60110,68938,62498,PRETRIAL,KASALI,KAYODE,NULL,Male,African-American,10/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +60110,68938,62498,PRETRIAL,KASALI,KAYODE,NULL,Male,African-American,10/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +13532,68923,62485,PRETRIAL,Smith,Denise,Lashawn,Female,African-American,05/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +13532,68923,62485,PRETRIAL,Smith,Denise,Lashawn,Female,African-American,05/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,9,High,New,1,0 +13532,68923,62485,PRETRIAL,Smith,Denise,Lashawn,Female,African-American,05/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60097,68925,62487,PRETRIAL,Tapia,Jeffrey,NULL,Male,Caucasian,02/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +60097,68925,62487,PRETRIAL,Tapia,Jeffrey,NULL,Male,Caucasian,02/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +60097,68925,62487,PRETRIAL,Tapia,Jeffrey,NULL,Male,Caucasian,02/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/2/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60089,68915,62477,PRETRIAL,Anderson,Jeffrey,NULL,Male,Caucasian,08/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +60089,68915,62477,PRETRIAL,Anderson,Jeffrey,NULL,Male,Caucasian,08/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +60089,68915,62477,PRETRIAL,Anderson,Jeffrey,NULL,Male,Caucasian,08/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60103,68933,62494,PRETRIAL,SNELLTURNER,GEORGE,NULL,Male,African-American,09/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +60103,68933,62494,PRETRIAL,SNELLTURNER,GEORGE,NULL,Male,African-American,09/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +60103,68933,62494,PRETRIAL,SNELLTURNER,GEORGE,NULL,Male,African-American,09/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60094,68920,62482,PRETRIAL,Sherrell,Jasmine,NULL,Female,African-American,08/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.12,8,High,New,1,0 +60094,68920,62482,PRETRIAL,Sherrell,Jasmine,NULL,Female,African-American,08/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +60094,68920,62482,PRETRIAL,Sherrell,Jasmine,NULL,Female,African-American,08/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60105,68936,62497,PRETRIAL,Saintil,Wilensky,NULL,Male,African-American,04/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,2,Medium,7,Risk of Violence,-2.45,3,Low,New,1,0 +60105,68936,62497,PRETRIAL,Saintil,Wilensky,NULL,Male,African-American,04/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +60105,68936,62497,PRETRIAL,Saintil,Wilensky,NULL,Male,African-American,04/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +45707,68934,62495,Probation,ELISIAS,KINDSON,NULL,Male,African-American,05/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/14 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,New,1,0 +45707,68934,62495,Probation,ELISIAS,KINDSON,NULL,Male,African-American,05/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +45707,68934,62495,Probation,ELISIAS,KINDSON,NULL,Male,African-American,05/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +44584,58795,53420,PRETRIAL,Esteves,George,NULL,Male,Caucasian,09/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +44584,58795,53420,PRETRIAL,Esteves,George,NULL,Male,Caucasian,09/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +44584,58795,53420,PRETRIAL,Esteves,George,NULL,Male,Caucasian,09/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +28478,68922,62484,PRETRIAL,LEAL,CHRISTOPHER,ANDREW,Male,Caucasian,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.88,9,High,New,1,0 +28478,68922,62484,PRETRIAL,LEAL,CHRISTOPHER,ANDREW,Male,Caucasian,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +28478,68922,62484,PRETRIAL,LEAL,CHRISTOPHER,ANDREW,Male,Caucasian,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60092,68918,62480,PRETRIAL,Parish,Nadja,Nadira,Female,Other,07/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +60092,68918,62480,PRETRIAL,Parish,Nadja,Nadira,Female,Other,07/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +60092,68918,62480,PRETRIAL,Parish,Nadja,Nadira,Female,Other,07/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +20238,68939,62499,PRETRIAL,TAYLOR,ROBERT,NULL,Male,African-American,08/09/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/14 0:00,4,High,7,Risk of Violence,-0.67,9,High,New,1,0 +20238,68939,62499,PRETRIAL,TAYLOR,ROBERT,NULL,Male,African-American,08/09/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/14 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +20238,68939,62499,PRETRIAL,TAYLOR,ROBERT,NULL,Male,African-American,08/09/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/2/14 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +60112,68943,62502,PRETRIAL,Mitchell,Clayton,NULL,Male,African-American,10/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,1/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.89,9,High,New,1,0 +60112,68943,62502,PRETRIAL,Mitchell,Clayton,NULL,Male,African-American,10/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,1/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +60112,68943,62502,PRETRIAL,Mitchell,Clayton,NULL,Male,African-American,10/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,1/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60116,68948,62506,PRETRIAL,Coletto,Shaun,Jon,Male,Caucasian,10/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +60116,68948,62506,PRETRIAL,Coletto,Shaun,Jon,Male,Caucasian,10/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +60116,68948,62506,PRETRIAL,Coletto,Shaun,Jon,Male,Caucasian,10/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60119,68952,62510,PRETRIAL,Bowers,Christopher,NULL,Male,African-American,09/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,7,Risk of Violence,-1.77,5,Medium,New,1,0 +60119,68952,62510,PRETRIAL,Bowers,Christopher,NULL,Male,African-American,09/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +60119,68952,62510,PRETRIAL,Bowers,Christopher,NULL,Male,African-American,09/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54350,68957,62515,Probation,hankins,stephen,NULL,Male,Caucasian,06/25/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/3/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +54350,68957,62515,Probation,hankins,stephen,NULL,Male,Caucasian,06/25/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/3/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +54350,68957,62515,Probation,hankins,stephen,NULL,Male,Caucasian,06/25/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60129,68964,62522,Probation,Robinson,Herman,NULL,Male,African-American,08/25/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,New,1,0 +60129,68964,62522,Probation,Robinson,Herman,NULL,Male,African-American,08/25/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +60129,68964,62522,Probation,Robinson,Herman,NULL,Male,African-American,08/25/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +60122,68955,62513,Probation,Hindi,Jibrael,NULL,Male,Other,04/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +60122,68955,62513,Probation,Hindi,Jibrael,NULL,Male,Other,04/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +60122,68955,62513,Probation,Hindi,Jibrael,NULL,Male,Other,04/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60121,68954,62512,Probation,Shapiro,Tara,NULL,Female,Caucasian,08/06/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/3/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +60121,68954,62512,Probation,Shapiro,Tara,NULL,Female,Caucasian,08/06/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/3/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +60121,68954,62512,Probation,Shapiro,Tara,NULL,Female,Caucasian,08/06/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60127,68962,62520,PRETRIAL,OTTEY,MICHAEL,ANDREW,Male,African-American,04/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +60127,68962,62520,PRETRIAL,OTTEY,MICHAEL,ANDREW,Male,African-American,04/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +60127,68962,62520,PRETRIAL,OTTEY,MICHAEL,ANDREW,Male,African-American,04/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60124,68959,62517,Probation,MCREA,OSVALDO,NULL,Male,Hispanic,07/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/3/14 0:00,2,Medium,7,Risk of Violence,-2.9,2,Low,New,1,0 +60124,68959,62517,Probation,MCREA,OSVALDO,NULL,Male,Hispanic,07/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +60124,68959,62517,Probation,MCREA,OSVALDO,NULL,Male,Hispanic,07/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/3/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60114,68946,62504,PRETRIAL,Nguyen,Tina,NULL,Female,Asian,12/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +60114,68946,62504,PRETRIAL,Nguyen,Tina,NULL,Female,Asian,12/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +60114,68946,62504,PRETRIAL,Nguyen,Tina,NULL,Female,Asian,12/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +18232,68949,62507,PRETRIAL,Sealy,Patrick,NULL,Male,African-American,09/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +18232,68949,62507,PRETRIAL,Sealy,Patrick,NULL,Male,African-American,09/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +18232,68949,62507,PRETRIAL,Sealy,Patrick,NULL,Male,African-American,09/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +33282,68956,62514,PRETRIAL,Rogers,Jamere,NULL,Female,African-American,03/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +33282,68956,62514,PRETRIAL,Rogers,Jamere,NULL,Female,African-American,03/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/14 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +33282,68956,62514,PRETRIAL,Rogers,Jamere,NULL,Female,African-American,03/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60128,68963,62521,PRETRIAL,JEANJOSEPH,MARSHA,CHELSIE,Female,African-American,06/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,New,1,0 +60128,68963,62521,PRETRIAL,JEANJOSEPH,MARSHA,CHELSIE,Female,African-American,06/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +60128,68963,62521,PRETRIAL,JEANJOSEPH,MARSHA,CHELSIE,Female,African-American,06/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60118,68951,62509,PRETRIAL,Graham,Livingston,NULL,Male,African-American,07/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +60118,68951,62509,PRETRIAL,Graham,Livingston,NULL,Male,African-American,07/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +60118,68951,62509,PRETRIAL,Graham,Livingston,NULL,Male,African-American,07/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60130,68965,62523,PRETRIAL,Luzon,Harold,NULL,Male,Hispanic,02/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +60130,68965,62523,PRETRIAL,Luzon,Harold,NULL,Male,Hispanic,02/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +60130,68965,62523,PRETRIAL,Luzon,Harold,NULL,Male,Hispanic,02/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +14476,68944,13851,Probation,WIGGINS,JEREMY,NULL,Male,African-American,12/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,4,High,7,Risk of Violence,-0.59,10,High,Copy,1,0 +14476,68944,13851,Probation,WIGGINS,JEREMY,NULL,Male,African-American,12/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,4,High,8,Risk of Recidivism,0.76,10,High,Copy,1,0 +14476,68944,13851,Probation,WIGGINS,JEREMY,NULL,Male,African-American,12/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +60115,68947,62505,PRETRIAL,Matamoros,Julio,NULL,Male,Hispanic,06/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +60115,68947,62505,PRETRIAL,Matamoros,Julio,NULL,Male,Hispanic,06/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +60115,68947,62505,PRETRIAL,Matamoros,Julio,NULL,Male,Hispanic,06/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60126,68961,62519,PRETRIAL,APOLLO,KENNETH,F,Male,Caucasian,08/02/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +60126,68961,62519,PRETRIAL,APOLLO,KENNETH,F,Male,Caucasian,08/02/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +60126,68961,62519,PRETRIAL,APOLLO,KENNETH,F,Male,Caucasian,08/02/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55265,68968,62526,PRETRIAL,Fetters,Jeffery,NULL,Male,Caucasian,07/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/3/14 0:00,2,Medium,7,Risk of Violence,-2.76,2,Low,New,1,0 +55265,68968,62526,PRETRIAL,Fetters,Jeffery,NULL,Male,Caucasian,07/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +55265,68968,62526,PRETRIAL,Fetters,Jeffery,NULL,Male,Caucasian,07/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/3/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60120,68953,62511,PRETRIAL,Leon,Mariorly,NULL,Female,Caucasian,03/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +60120,68953,62511,PRETRIAL,Leon,Mariorly,NULL,Female,Caucasian,03/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +60120,68953,62511,PRETRIAL,Leon,Mariorly,NULL,Female,Caucasian,03/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60113,68945,62503,PRETRIAL,Bitz,Lourdes,NULL,Female,Caucasian,08/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +60113,68945,62503,PRETRIAL,Bitz,Lourdes,NULL,Female,Caucasian,08/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +60113,68945,62503,PRETRIAL,Bitz,Lourdes,NULL,Female,Caucasian,08/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +48304,68960,62518,Probation,Faulk,Zechariah,NULL,Male,African-Am,10/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +48304,68960,62518,Probation,Faulk,Zechariah,NULL,Male,African-Am,10/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +48304,68960,62518,Probation,Faulk,Zechariah,NULL,Male,African-Am,10/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60123,68958,62516,Probation,hawkinson,brent,NULL,Male,Caucasian,05/26/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/3/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +60123,68958,62516,Probation,hawkinson,brent,NULL,Male,Caucasian,05/26/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/3/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +60123,68958,62516,Probation,hawkinson,brent,NULL,Male,Caucasian,05/26/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60117,68950,62508,PRETRIAL,Baker,Tiffany,NULL,Female,African-American,08/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,2,Medium,7,Risk of Violence,-1.33,7,Medium,New,1,0 +60117,68950,62508,PRETRIAL,Baker,Tiffany,NULL,Female,African-American,08/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +60117,68950,62508,PRETRIAL,Baker,Tiffany,NULL,Female,African-American,08/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/3/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60141,68984,62540,PRETRIAL,TAYLOR,BRYAN,JEFFREY,Female,African-American,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +60141,68984,62540,PRETRIAL,TAYLOR,BRYAN,JEFFREY,Female,African-American,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,4,High,8,Risk of Recidivism,1.06,10,High,New,1,0 +60141,68984,62540,PRETRIAL,TAYLOR,BRYAN,JEFFREY,Female,African-American,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,4,High,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +51800,68971,53045,PRETRIAL,Jones,Douglas,NULL,Male,African-American,05/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,2,Medium,7,Risk of Violence,-3.23,1,Low,Copy,1,0 +51800,68971,53045,PRETRIAL,Jones,Douglas,NULL,Male,African-American,05/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,Copy,1,0 +51800,68971,53045,PRETRIAL,Jones,Douglas,NULL,Male,African-American,05/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +3574,68976,3289,PRETRIAL,steele,jeffrey,j,Male,African-American,01/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,Copy,1,0 +3574,68976,3289,PRETRIAL,steele,jeffrey,j,Male,African-American,01/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,Copy,1,0 +3574,68976,3289,PRETRIAL,steele,jeffrey,j,Male,African-American,01/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +51525,68979,62535,PRETRIAL,Brady,Parris,A,Male,African-American,01/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +51525,68979,62535,PRETRIAL,Brady,Parris,A,Male,African-American,01/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +51525,68979,62535,PRETRIAL,Brady,Parris,A,Male,African-American,01/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60134,68974,62531,PRETRIAL,Heath,Sharell,NULL,Female,African-American,11/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +60134,68974,62531,PRETRIAL,Heath,Sharell,NULL,Female,African-American,11/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +60134,68974,62531,PRETRIAL,Heath,Sharell,NULL,Female,African-American,11/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60139,68981,62537,PRETRIAL,Rodriguez,Reynaldo,NULL,Male,Caucasian,09/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +60139,68981,62537,PRETRIAL,Rodriguez,Reynaldo,NULL,Male,Caucasian,09/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +60139,68981,62537,PRETRIAL,Rodriguez,Reynaldo,NULL,Male,Caucasian,09/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60144,68987,62543,PRETRIAL,Ortiz,Carmen,NULL,Female,Hispanic,04/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +60144,68987,62543,PRETRIAL,Ortiz,Carmen,NULL,Female,Hispanic,04/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +60144,68987,62543,PRETRIAL,Ortiz,Carmen,NULL,Female,Hispanic,04/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60143,68986,62542,PRETRIAL,White,Hassheim,NULL,Male,African-American,10/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,4,High,7,Risk of Violence,-0.42,10,High,New,1,0 +60143,68986,62542,PRETRIAL,White,Hassheim,NULL,Male,African-American,10/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,4,High,8,Risk of Recidivism,0.16,8,High,New,1,0 +60143,68986,62542,PRETRIAL,White,Hassheim,NULL,Male,African-American,10/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +28801,68982,62538,PRETRIAL,rodriguez,george,NULL,Male,Hispanic,05/14/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +28801,68982,62538,PRETRIAL,rodriguez,george,NULL,Male,Hispanic,05/14/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +28801,68982,62538,PRETRIAL,rodriguez,george,NULL,Male,Hispanic,05/14/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60136,68977,62533,PRETRIAL,Jones,Maurice,NULL,Male,African-American,12/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +60136,68977,62533,PRETRIAL,Jones,Maurice,NULL,Male,African-American,12/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +60136,68977,62533,PRETRIAL,Jones,Maurice,NULL,Male,African-American,12/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +8814,68970,62528,PRETRIAL,Bartlett,Matthew,William,Male,Caucasian,08/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +8814,68970,62528,PRETRIAL,Bartlett,Matthew,William,Male,Caucasian,08/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +8814,68970,62528,PRETRIAL,Bartlett,Matthew,William,Male,Caucasian,08/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +60133,68972,62529,PRETRIAL,Louis,Colleen,D,Female,African-American,04/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/4/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +60133,68972,62529,PRETRIAL,Louis,Colleen,D,Female,African-American,04/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/4/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +60133,68972,62529,PRETRIAL,Louis,Colleen,D,Female,African-American,04/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60138,68980,62536,PRETRIAL,Deleon,Ahmed,Abdel,Male,Caucasian,06/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +60138,68980,62536,PRETRIAL,Deleon,Ahmed,Abdel,Male,Caucasian,06/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +60138,68980,62536,PRETRIAL,Deleon,Ahmed,Abdel,Male,Caucasian,06/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60140,68983,62539,PRETRIAL,GARNER,SHAWN,PATRICK,Male,Caucasian,11/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +60140,68983,62539,PRETRIAL,GARNER,SHAWN,PATRICK,Male,Caucasian,11/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +60140,68983,62539,PRETRIAL,GARNER,SHAWN,PATRICK,Male,Caucasian,11/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60135,68975,62532,PRETRIAL,Comisky,Michael,NULL,Male,Caucasian,10/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +60135,68975,62532,PRETRIAL,Comisky,Michael,NULL,Male,Caucasian,10/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +60135,68975,62532,PRETRIAL,Comisky,Michael,NULL,Male,Caucasian,10/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60142,68985,62541,PRETRIAL,Brown,Prince,NULL,Male,African-American,09/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +60142,68985,62541,PRETRIAL,Brown,Prince,NULL,Male,African-American,09/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +60142,68985,62541,PRETRIAL,Brown,Prince,NULL,Male,African-American,09/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60137,68978,62534,PRETRIAL,Ramnarine,Goonwatty,NULL,Female,Other,05/04/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/14 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +60137,68978,62534,PRETRIAL,Ramnarine,Goonwatty,NULL,Female,Other,05/04/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/14 0:00,1,Low,8,Risk of Recidivism,-2.67,1,Low,New,1,0 +60137,68978,62534,PRETRIAL,Ramnarine,Goonwatty,NULL,Female,Other,05/04/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/4/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +22510,68973,62530,PRETRIAL,Lofton,Willie,NULL,Male,African-American,06/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +22510,68973,62530,PRETRIAL,Lofton,Willie,NULL,Male,African-American,06/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.76,10,High,New,1,0 +22510,68973,62530,PRETRIAL,Lofton,Willie,NULL,Male,African-American,06/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60147,68990,62546,PRETRIAL,WILLIAMSON,DYLAN,JAMES,Male,Caucasian,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +60147,68990,62546,PRETRIAL,WILLIAMSON,DYLAN,JAMES,Male,Caucasian,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,4,High,8,Risk of Recidivism,0.54,9,High,New,1,0 +60147,68990,62546,PRETRIAL,WILLIAMSON,DYLAN,JAMES,Male,Caucasian,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60151,68994,62551,PRETRIAL,YOUNG,MARQUITA,NULL,Female,African-American,07/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +60151,68994,62551,PRETRIAL,YOUNG,MARQUITA,NULL,Female,African-American,07/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +60151,68994,62551,PRETRIAL,YOUNG,MARQUITA,NULL,Female,African-American,07/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60149,68992,62548,PRETRIAL,Taylor,Cynthia,NULL,Male,African-American,12/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/5/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +60149,68992,62548,PRETRIAL,Taylor,Cynthia,NULL,Male,African-American,12/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/5/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +60149,68992,62548,PRETRIAL,Taylor,Cynthia,NULL,Male,African-American,12/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60155,68999,62555,PRETRIAL,MILES,ALEXANDREA,NULL,Male,African-American,12/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +60155,68999,62555,PRETRIAL,MILES,ALEXANDREA,NULL,Male,African-American,12/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +60155,68999,62555,PRETRIAL,MILES,ALEXANDREA,NULL,Male,African-American,12/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60145,68988,62544,PRETRIAL,BEDFORD,TIMOTHY,NULL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +60145,68988,62544,PRETRIAL,BEDFORD,TIMOTHY,NULL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +60145,68988,62544,PRETRIAL,BEDFORD,TIMOTHY,NULL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60152,68996,62552,PRETRIAL,ABBOTT,ANDREW,NULL,Male,Caucasian,12/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +60152,68996,62552,PRETRIAL,ABBOTT,ANDREW,NULL,Male,Caucasian,12/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +60152,68996,62552,PRETRIAL,ABBOTT,ANDREW,NULL,Male,Caucasian,12/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60148,68991,62547,PRETRIAL,FERNANDEZ,RANDY,NULL,Male,Caucasian,11/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +60148,68991,62547,PRETRIAL,FERNANDEZ,RANDY,NULL,Male,Caucasian,11/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +60148,68991,62547,PRETRIAL,FERNANDEZ,RANDY,NULL,Male,Caucasian,11/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60150,68993,62549,PRETRIAL,Milan,Jasmine,NULL,Male,Caucasian,06/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +60150,68993,62549,PRETRIAL,Milan,Jasmine,NULL,Male,Caucasian,06/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +60150,68993,62549,PRETRIAL,Milan,Jasmine,NULL,Male,Caucasian,06/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60154,68998,62554,PRETRIAL,Grant,Ativia,NULL,Female,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +60154,68998,62554,PRETRIAL,Grant,Ativia,NULL,Female,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +60154,68998,62554,PRETRIAL,Grant,Ativia,NULL,Female,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60146,68989,62545,PRETRIAL,DOE,TAKEYMA,NULL,Female,African-American,09/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +60146,68989,62545,PRETRIAL,DOE,TAKEYMA,NULL,Female,African-American,09/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +60146,68989,62545,PRETRIAL,DOE,TAKEYMA,NULL,Female,African-American,09/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +46588,68995,47012,Probation,LANDERS,BERNARD,L,Male,African-American,08/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,Copy,1,0 +46588,68995,47012,Probation,LANDERS,BERNARD,L,Male,African-American,08/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,Copy,1,0 +46588,68995,47012,Probation,LANDERS,BERNARD,L,Male,African-American,08/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +60153,68997,62553,PRETRIAL,BILLION,STEPHON,NULL,Male,African-American,07/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +60153,68997,62553,PRETRIAL,BILLION,STEPHON,NULL,Male,African-American,07/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +60153,68997,62553,PRETRIAL,BILLION,STEPHON,NULL,Male,African-American,07/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60190,69044,62597,Probation,Rodriguezcuellar,Sandra,NULL,Female,Hispanic,07/20/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/6/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +60190,69044,62597,Probation,Rodriguezcuellar,Sandra,NULL,Female,Hispanic,07/20/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +60190,69044,62597,Probation,Rodriguezcuellar,Sandra,NULL,Female,Hispanic,07/20/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/6/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60193,69047,62600,PRETRIAL,Ferreiriradeoliveira,Gilmar,NULL,Male,Hispanic,01/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +60193,69047,62600,PRETRIAL,Ferreiriradeoliveira,Gilmar,NULL,Male,Hispanic,01/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +60193,69047,62600,PRETRIAL,Ferreiriradeoliveira,Gilmar,NULL,Male,Hispanic,01/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60176,69026,62580,Probation,KANE,CHELSI,N,Female,Caucasian,04/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +60176,69026,62580,Probation,KANE,CHELSI,N,Female,Caucasian,04/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +60176,69026,62580,Probation,KANE,CHELSI,N,Female,Caucasian,04/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60160,69005,62561,PRETRIAL,Asdot,Daniel,NULL,Male,Caucasian,12/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +60160,69005,62561,PRETRIAL,Asdot,Daniel,NULL,Male,Caucasian,12/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +60160,69005,62561,PRETRIAL,Asdot,Daniel,NULL,Male,Caucasian,12/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60187,69039,62593,PRETRIAL,Lorenzo-Luaces,Alberto,NULL,Male,Hispanic,08/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +60187,69039,62593,PRETRIAL,Lorenzo-Luaces,Alberto,NULL,Male,Hispanic,08/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +60187,69039,62593,PRETRIAL,Lorenzo-Luaces,Alberto,NULL,Male,Hispanic,08/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60170,69018,62573,Probation,ROBINSON,TIMOTHY,ELIJAH,Male,African-American,08/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +60170,69018,62573,Probation,ROBINSON,TIMOTHY,ELIJAH,Male,African-American,08/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +60170,69018,62573,Probation,ROBINSON,TIMOTHY,ELIJAH,Male,African-American,08/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60165,69010,62566,PRETRIAL,JONES,BRENZINA,NULL,Female,African-American,02/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +60165,69010,62566,PRETRIAL,JONES,BRENZINA,NULL,Female,African-American,02/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +60165,69010,62566,PRETRIAL,JONES,BRENZINA,NULL,Female,African-American,02/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60180,69031,62585,PRETRIAL,Myers,Staci,NULL,Female,African-American,09/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +60180,69031,62585,PRETRIAL,Myers,Staci,NULL,Female,African-American,09/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +60180,69031,62585,PRETRIAL,Myers,Staci,NULL,Female,African-American,09/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +42796,69002,62558,PRETRIAL,Ortiz,Jose,Omi,Male,Caucasian,11/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/6/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +42796,69002,62558,PRETRIAL,Ortiz,Jose,Omi,Male,Caucasian,11/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/6/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +42796,69002,62558,PRETRIAL,Ortiz,Jose,Omi,Male,Caucasian,11/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60173,69023,62577,PRETRIAL,Morales,Angel,NULL,Male,Hispanic,03/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +60173,69023,62577,PRETRIAL,Morales,Angel,NULL,Male,Hispanic,03/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +60173,69023,62577,PRETRIAL,Morales,Angel,NULL,Male,Hispanic,03/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60172,69021,62575,PRETRIAL,CHAO,ERNESTO,NULL,Male,Caucasian,09/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +60172,69021,62575,PRETRIAL,CHAO,ERNESTO,NULL,Male,Caucasian,09/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +60172,69021,62575,PRETRIAL,CHAO,ERNESTO,NULL,Male,Caucasian,09/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60167,69014,62569,Probation,Jackson,Rufus,Valantino,Male,African-American,11/14/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/6/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +60167,69014,62569,Probation,Jackson,Rufus,Valantino,Male,African-American,11/14/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/6/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +60167,69014,62569,Probation,Jackson,Rufus,Valantino,Male,African-American,11/14/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +9982,69028,62582,PRETRIAL,PARKS,DEAN,NULL,Male,African-American,06/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +9982,69028,62582,PRETRIAL,PARKS,DEAN,NULL,Male,African-American,06/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +9982,69028,62582,PRETRIAL,PARKS,DEAN,NULL,Male,African-American,06/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60184,69035,62589,Probation,CHRISTLIEB,SUMMER,K,Female,Caucasian,10/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/6/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +60184,69035,62589,Probation,CHRISTLIEB,SUMMER,K,Female,Caucasian,10/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +60184,69035,62589,Probation,CHRISTLIEB,SUMMER,K,Female,Caucasian,10/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60189,69042,62595,Probation,vanterpool,erol,NULL,Male,African-American,09/19/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +60189,69042,62595,Probation,vanterpool,erol,NULL,Male,African-American,09/19/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +60189,69042,62595,Probation,vanterpool,erol,NULL,Male,African-American,09/19/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60162,69007,62563,PRETRIAL,RAGIN,ISAIAH,JERMAINE,Male,African-American,05/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +60162,69007,62563,PRETRIAL,RAGIN,ISAIAH,JERMAINE,Male,African-American,05/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,4,High,8,Risk of Recidivism,0.22,8,High,New,1,0 +60162,69007,62563,PRETRIAL,RAGIN,ISAIAH,JERMAINE,Male,African-American,05/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60169,69016,62571,Probation,monahan,david,NULL,Male,Caucasian,11/30/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/6/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +60169,69016,62571,Probation,monahan,david,NULL,Male,Caucasian,11/30/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +60169,69016,62571,Probation,monahan,david,NULL,Male,Caucasian,11/30/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60158,69003,62559,PRETRIAL,FREEMAN,CHRISTOOPHER,MICHAEL,Male,Caucasian,09/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +60158,69003,62559,PRETRIAL,FREEMAN,CHRISTOOPHER,MICHAEL,Male,Caucasian,09/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +60158,69003,62559,PRETRIAL,FREEMAN,CHRISTOOPHER,MICHAEL,Male,Caucasian,09/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60186,69037,62591,Probation,Maretinez,Gisela,NULL,Female,Hispanic,03/14/71,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/6/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +60186,69037,62591,Probation,Maretinez,Gisela,NULL,Female,Hispanic,03/14/71,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +60186,69037,62591,Probation,Maretinez,Gisela,NULL,Female,Hispanic,03/14/71,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60182,69033,62587,PRETRIAL,BOUCHARD,DUSTIN,NULL,Male,Caucasian,07/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +60182,69033,62587,PRETRIAL,BOUCHARD,DUSTIN,NULL,Male,Caucasian,07/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +60182,69033,62587,PRETRIAL,BOUCHARD,DUSTIN,NULL,Male,Caucasian,07/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60191,69045,62598,PRETRIAL,Morales,Efrain,NULL,Male,Hispanic,03/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +60191,69045,62598,PRETRIAL,Morales,Efrain,NULL,Male,Hispanic,03/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +60191,69045,62598,PRETRIAL,Morales,Efrain,NULL,Male,Hispanic,03/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60192,69046,62599,PRETRIAL,Higgins,Michael,NULL,Male,Caucasian,01/27/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +60192,69046,62599,PRETRIAL,Higgins,Michael,NULL,Male,Caucasian,01/27/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +60192,69046,62599,PRETRIAL,Higgins,Michael,NULL,Male,Caucasian,01/27/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +15663,69017,62572,PRETRIAL,REYES,CHARLIE,NULL,Male,Hispanic,02/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +15663,69017,62572,PRETRIAL,REYES,CHARLIE,NULL,Male,Hispanic,02/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +15663,69017,62572,PRETRIAL,REYES,CHARLIE,NULL,Male,Hispanic,02/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60174,69024,62578,Probation,Paez,ana,NULL,Female,Hispanic,07/26/53,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/6/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +60174,69024,62578,Probation,Paez,ana,NULL,Female,Hispanic,07/26/53,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/6/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +60174,69024,62578,Probation,Paez,ana,NULL,Female,Hispanic,07/26/53,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60175,69025,62579,Probation,Deodat,Virendra,NULL,Male,Other,08/31/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,2,Medium,7,Risk of Violence,-2.23,4,Low,New,1,0 +60175,69025,62579,Probation,Deodat,Virendra,NULL,Male,Other,08/31/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +60175,69025,62579,Probation,Deodat,Virendra,NULL,Male,Other,08/31/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60181,69032,62586,Probation,calderon,isaac,NULL,Male,Hispanic,05/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/6/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +60181,69032,62586,Probation,calderon,isaac,NULL,Male,Hispanic,05/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/6/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +60181,69032,62586,Probation,calderon,isaac,NULL,Male,Hispanic,05/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60159,69004,62560,PRETRIAL,TEAGUE,KARLIJO,NULL,Female,Caucasian,12/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +60159,69004,62560,PRETRIAL,TEAGUE,KARLIJO,NULL,Female,Caucasian,12/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +60159,69004,62560,PRETRIAL,TEAGUE,KARLIJO,NULL,Female,Caucasian,12/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,2,Medium,18,Risk of Failure to Appear,29,9,High,New,1,0 +50633,69038,62592,PRETRIAL,MATOS,DAVID,PAUL,Male,Caucasian,01/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/6/14 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +50633,69038,62592,PRETRIAL,MATOS,DAVID,PAUL,Male,Caucasian,01/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/6/14 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +50633,69038,62592,PRETRIAL,MATOS,DAVID,PAUL,Male,Caucasian,01/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/6/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60198,69053,62606,PRETRIAL,MARTIN,TREVIS,C,Male,Caucasian,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +60198,69053,62606,PRETRIAL,MARTIN,TREVIS,C,Male,Caucasian,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +60198,69053,62606,PRETRIAL,MARTIN,TREVIS,C,Male,Caucasian,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +41905,69022,62576,PRETRIAL,hernandez,MORRIS,OCTAVIO,Male,Caucasian,03/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/6/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +41905,69022,62576,PRETRIAL,hernandez,MORRIS,OCTAVIO,Male,Caucasian,03/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +41905,69022,62576,PRETRIAL,hernandez,MORRIS,OCTAVIO,Male,Caucasian,03/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60164,69009,62565,PRETRIAL,WATSON,KEESHA,NULL,Female,African-American,09/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +60164,69009,62565,PRETRIAL,WATSON,KEESHA,NULL,Female,African-American,09/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +60164,69009,62565,PRETRIAL,WATSON,KEESHA,NULL,Female,African-American,09/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +33539,69043,62596,Probation,Boxer,Mitchell,NULL,Male,Caucasian,05/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/6/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +33539,69043,62596,Probation,Boxer,Mitchell,NULL,Male,Caucasian,05/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +33539,69043,62596,Probation,Boxer,Mitchell,NULL,Male,Caucasian,05/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60194,69048,62601,Probation,rubin,harold,NULL,Male,Caucasian,09/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/6/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +60194,69048,62601,Probation,rubin,harold,NULL,Male,Caucasian,09/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/6/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +60194,69048,62601,Probation,rubin,harold,NULL,Male,Caucasian,09/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60157,69001,62557,PRETRIAL,Espinoza,Martin,NULL,Male,Caucasian,02/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +60157,69001,62557,PRETRIAL,Espinoza,Martin,NULL,Male,Caucasian,02/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +60157,69001,62557,PRETRIAL,Espinoza,Martin,NULL,Male,Caucasian,02/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53968,69051,62604,PRETRIAL,Mckenzie,Vernee,Alena,Female,African-American,09/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +53968,69051,62604,PRETRIAL,Mckenzie,Vernee,Alena,Female,African-American,09/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +53968,69051,62604,PRETRIAL,Mckenzie,Vernee,Alena,Female,African-American,09/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60179,69030,62584,Probation,Rodriguez,Carlos,NULL,Male,Hispanic,10/29/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/6/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +60179,69030,62584,Probation,Rodriguez,Carlos,NULL,Male,Hispanic,10/29/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/6/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +60179,69030,62584,Probation,Rodriguez,Carlos,NULL,Male,Hispanic,10/29/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60161,69006,62562,PRETRIAL,Altman,Linda,Gail,Female,Caucasian,11/30/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/6/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +60161,69006,62562,PRETRIAL,Altman,Linda,Gail,Female,Caucasian,11/30/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/6/14 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +60161,69006,62562,PRETRIAL,Altman,Linda,Gail,Female,Caucasian,11/30/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +45854,69013,62568,Probation,Adams,Gerard,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/6/14 0:00,2,Medium,7,Risk of Violence,-2.27,3,Low,New,1,0 +45854,69013,62568,Probation,Adams,Gerard,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/6/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +45854,69013,62568,Probation,Adams,Gerard,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/6/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60177,69027,62581,PRETRIAL,Thomas,Thaddeus,Claude,Male,African-American,06/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/6/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +60177,69027,62581,PRETRIAL,Thomas,Thaddeus,Claude,Male,African-American,06/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +60177,69027,62581,PRETRIAL,Thomas,Thaddeus,Claude,Male,African-American,06/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60185,69036,62590,PRETRIAL,Thomas,Chantel,NULL,Female,African-American,08/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +60185,69036,62590,PRETRIAL,Thomas,Chantel,NULL,Female,African-American,08/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +60185,69036,62590,PRETRIAL,Thomas,Chantel,NULL,Female,African-American,08/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60183,69034,62588,Probation,Tourigny,Adam,NULL,Male,Caucasian,08/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +60183,69034,62588,Probation,Tourigny,Adam,NULL,Male,Caucasian,08/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +60183,69034,62588,Probation,Tourigny,Adam,NULL,Male,Caucasian,08/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60178,69029,62583,PRETRIAL,Robinson,Chevane,NULL,Male,African-American,04/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +60178,69029,62583,PRETRIAL,Robinson,Chevane,NULL,Male,African-American,04/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +60178,69029,62583,PRETRIAL,Robinson,Chevane,NULL,Male,African-American,04/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60163,69008,62564,PRETRIAL,JONES,COLIN,NULL,Male,African-American,08/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +60163,69008,62564,PRETRIAL,JONES,COLIN,NULL,Male,African-American,08/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +60163,69008,62564,PRETRIAL,JONES,COLIN,NULL,Male,African-American,08/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60188,69041,62594,Probation,Lafrance,Mario,NULL,Male,African-American,01/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +60188,69041,62594,Probation,Lafrance,Mario,NULL,Male,African-American,01/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +60188,69041,62594,Probation,Lafrance,Mario,NULL,Male,African-American,01/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60196,69050,62603,Probation,Lynch,Danielle,NULL,Female,African-American,07/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +60196,69050,62603,Probation,Lynch,Danielle,NULL,Female,African-American,07/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,10,High,New,1,0 +60196,69050,62603,Probation,Lynch,Danielle,NULL,Female,African-American,07/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60171,69020,62574,PRETRIAL,Parisi,Joseph,NULL,Male,Caucasian,06/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +60171,69020,62574,PRETRIAL,Parisi,Joseph,NULL,Male,Caucasian,06/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +60171,69020,62574,PRETRIAL,Parisi,Joseph,NULL,Male,Caucasian,06/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/6/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60219,69071,62623,Probation,Vaitoska,Justinas,NULL,Male,Caucasian,07/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/7/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +60219,69071,62623,Probation,Vaitoska,Justinas,NULL,Male,Caucasian,07/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/7/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +60219,69071,62623,Probation,Vaitoska,Justinas,NULL,Male,Caucasian,07/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,37,10,High,New,1,0 +60228,69083,62633,PRETRIAL,Garrison,Christina,NULL,Female,Caucasian,01/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/7/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +60228,69083,62633,PRETRIAL,Garrison,Christina,NULL,Female,Caucasian,01/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +60228,69083,62633,PRETRIAL,Garrison,Christina,NULL,Female,Caucasian,01/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52425,69062,62615,PRETRIAL,Edwards,Linda,NULL,Male,African-American,07/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +52425,69062,62615,PRETRIAL,Edwards,Linda,NULL,Male,African-American,07/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +52425,69062,62615,PRETRIAL,Edwards,Linda,NULL,Male,African-American,07/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60225,69080,62630,PRETRIAL,ROSS,WILLIE,NULL,Male,African-American,02/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +60225,69080,62630,PRETRIAL,ROSS,WILLIE,NULL,Male,African-American,02/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +60225,69080,62630,PRETRIAL,ROSS,WILLIE,NULL,Male,African-American,02/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +60202,69057,62610,PRETRIAL,WALKERGREAVES,DANIEL,MICHAEL,Male,Native American,08/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +60202,69057,62610,PRETRIAL,WALKERGREAVES,DANIEL,MICHAEL,Male,Native American,08/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +60202,69057,62610,PRETRIAL,WALKERGREAVES,DANIEL,MICHAEL,Male,Native American,08/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60200,69055,62608,PRETRIAL,Everhardt,Christopher,Charles,Male,Caucasian,04/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +60200,69055,62608,PRETRIAL,Everhardt,Christopher,Charles,Male,Caucasian,04/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +60200,69055,62608,PRETRIAL,Everhardt,Christopher,Charles,Male,Caucasian,04/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60214,69064,62617,Probation,spence,kristina,NULL,Female,Caucasian,09/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/14 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +60214,69064,62617,Probation,spence,kristina,NULL,Female,Caucasian,09/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,New,1,0 +60214,69064,62617,Probation,spence,kristina,NULL,Female,Caucasian,09/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60223,69078,62628,Probation,jones,horace,NULL,Male,African-American,08/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/7/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +60223,69078,62628,Probation,jones,horace,NULL,Male,African-American,08/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/7/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +60223,69078,62628,Probation,jones,horace,NULL,Male,African-American,08/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60230,69085,62635,PRETRIAL,TRUE,james,NULL,Male,Caucasian,09/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +60230,69085,62635,PRETRIAL,TRUE,james,NULL,Male,Caucasian,09/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +60230,69085,62635,PRETRIAL,TRUE,james,NULL,Male,Caucasian,09/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60205,69061,62614,PRETRIAL,GARCIA,JACQUELINE,NULL,Female,Caucasian,01/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/7/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +60205,69061,62614,PRETRIAL,GARCIA,JACQUELINE,NULL,Female,Caucasian,01/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/7/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +60205,69061,62614,PRETRIAL,GARCIA,JACQUELINE,NULL,Female,Caucasian,01/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60235,69090,62640,PRETRIAL,Drogus,Eugene,NULL,Male,Caucasian,10/17/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +60235,69090,62640,PRETRIAL,Drogus,Eugene,NULL,Male,Caucasian,10/17/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +60235,69090,62640,PRETRIAL,Drogus,Eugene,NULL,Male,Caucasian,10/17/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +60227,69082,62632,PRETRIAL,Outar,Donette,NULL,Female,Other,01/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +60227,69082,62632,PRETRIAL,Outar,Donette,NULL,Female,Other,01/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +60227,69082,62632,PRETRIAL,Outar,Donette,NULL,Female,Other,01/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60218,69069,62621,PRETRIAL,COLEMAN,CRAIG,NULL,Male,African-American,10/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/7/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +60218,69069,62621,PRETRIAL,COLEMAN,CRAIG,NULL,Male,African-American,10/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +60218,69069,62621,PRETRIAL,COLEMAN,CRAIG,NULL,Male,African-American,10/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60232,69087,62637,PRETRIAL,Witkowski,Edmund,NULL,Male,Caucasian,06/07/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/7/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +60232,69087,62637,PRETRIAL,Witkowski,Edmund,NULL,Male,Caucasian,06/07/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/7/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +60232,69087,62637,PRETRIAL,Witkowski,Edmund,NULL,Male,Caucasian,06/07/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +45108,69059,62612,PRETRIAL,Smith,Stephanie,NULL,Female,African-American,11/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/7/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +45108,69059,62612,PRETRIAL,Smith,Stephanie,NULL,Female,African-American,11/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/7/14 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +45108,69059,62612,PRETRIAL,Smith,Stephanie,NULL,Female,African-American,11/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60215,69066,62618,Probation,Kilpatrick,Kenneth,NULL,Male,Caucasian,11/25/50,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/7/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +60215,69066,62618,Probation,Kilpatrick,Kenneth,NULL,Male,Caucasian,11/25/50,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +60215,69066,62618,Probation,Kilpatrick,Kenneth,NULL,Male,Caucasian,11/25/50,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60216,69067,62619,PRETRIAL,weston,alicia,NULL,Female,Caucasian,12/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/7/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +60216,69067,62619,PRETRIAL,weston,alicia,NULL,Female,Caucasian,12/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +60216,69067,62619,PRETRIAL,weston,alicia,NULL,Female,Caucasian,12/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,29,9,High,New,1,0 +60203,69058,62611,PRETRIAL,JONES,KEJAN,NULL,Male,African-American,04/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +60203,69058,62611,PRETRIAL,JONES,KEJAN,NULL,Male,African-American,04/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +60203,69058,62611,PRETRIAL,JONES,KEJAN,NULL,Male,African-American,04/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60224,69079,62629,Probation,Zorrilla,Fernando,NULL,Male,Hispanic,10/01/65,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/7/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +60224,69079,62629,Probation,Zorrilla,Fernando,NULL,Male,Hispanic,10/01/65,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +60224,69079,62629,Probation,Zorrilla,Fernando,NULL,Male,Hispanic,10/01/65,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60199,69054,62607,PRETRIAL,HEPBURN,ALONZO,ROMELO,Male,African-American,11/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,4,High,7,Risk of Violence,-0.4,10,High,New,1,0 +60199,69054,62607,PRETRIAL,HEPBURN,ALONZO,ROMELO,Male,African-American,11/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +60199,69054,62607,PRETRIAL,HEPBURN,ALONZO,ROMELO,Male,African-American,11/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60233,69088,62638,PRETRIAL,HARROLD,JESSICA,NULL,Female,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +60233,69088,62638,PRETRIAL,HARROLD,JESSICA,NULL,Female,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +60233,69088,62638,PRETRIAL,HARROLD,JESSICA,NULL,Female,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60222,69075,62626,PRETRIAL,Jaramillo,Eyxnor,NULL,Male,Hispanic,11/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +60222,69075,62626,PRETRIAL,Jaramillo,Eyxnor,NULL,Male,Hispanic,11/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +60222,69075,62626,PRETRIAL,Jaramillo,Eyxnor,NULL,Male,Hispanic,11/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60229,69084,62634,Probation,aguilar,nelson,NULL,Male,Hispanic,05/04/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/7/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +60229,69084,62634,Probation,aguilar,nelson,NULL,Male,Hispanic,05/04/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +60229,69084,62634,Probation,aguilar,nelson,NULL,Male,Hispanic,05/04/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60201,69056,62609,PRETRIAL,LOUIDOR,JEAN,ROBERT,Male,African-American,03/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +60201,69056,62609,PRETRIAL,LOUIDOR,JEAN,ROBERT,Male,African-American,03/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +60201,69056,62609,PRETRIAL,LOUIDOR,JEAN,ROBERT,Male,African-American,03/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60206,69063,62616,PRETRIAL,Shaquella,Pines,Lesabre,Female,African-American,04/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +60206,69063,62616,PRETRIAL,Shaquella,Pines,Lesabre,Female,African-American,04/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,4,High,8,Risk of Recidivism,0.02,8,High,New,1,0 +60206,69063,62616,PRETRIAL,Shaquella,Pines,Lesabre,Female,African-American,04/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59982,69077,62358,PRETRIAL,Lamons,Racquel,NULL,Female,African-American,01/27/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,4,High,7,Risk of Violence,-1.18,8,High,Copy,1,0 +59982,69077,62358,PRETRIAL,Lamons,Racquel,NULL,Female,African-American,01/27/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,4,High,8,Risk of Recidivism,0.3,9,High,Copy,1,0 +59982,69077,62358,PRETRIAL,Lamons,Racquel,NULL,Female,African-American,01/27/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/7/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +54714,69070,62622,PRETRIAL,ONIQUE,WILLIAMS,NULL,Male,African-American,01/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +54714,69070,62622,PRETRIAL,ONIQUE,WILLIAMS,NULL,Male,African-American,01/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +54714,69070,62622,PRETRIAL,ONIQUE,WILLIAMS,NULL,Male,African-American,01/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60220,69072,62624,Probation,Sorondotamayo,Irving,Jorge,Male,Hispanic,08/19/76,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/7/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +60220,69072,62624,Probation,Sorondotamayo,Irving,Jorge,Male,Hispanic,08/19/76,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +60220,69072,62624,Probation,Sorondotamayo,Irving,Jorge,Male,Hispanic,08/19/76,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60204,69060,62613,PRETRIAL,McFadden,Shanta,NULL,Female,African-American,07/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +60204,69060,62613,PRETRIAL,McFadden,Shanta,NULL,Female,African-American,07/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +60204,69060,62613,PRETRIAL,McFadden,Shanta,NULL,Female,African-American,07/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/7/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60226,69081,62631,Probation,DAVIS,PAUL,NULL,Male,Hispanic,08/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +60226,69081,62631,Probation,DAVIS,PAUL,NULL,Male,Hispanic,08/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +60226,69081,62631,Probation,DAVIS,PAUL,NULL,Male,Hispanic,08/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60221,69073,62625,Probation,Lestrade,Royette,NULL,Female,African-American,07/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/7/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +60221,69073,62625,Probation,Lestrade,Royette,NULL,Female,African-American,07/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/7/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +60221,69073,62625,Probation,Lestrade,Royette,NULL,Female,African-American,07/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60231,69086,62636,PRETRIAL,Fleming,Sean,NULL,Male,African-American,03/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/7/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +60231,69086,62636,PRETRIAL,Fleming,Sean,NULL,Male,African-American,03/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/7/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +60231,69086,62636,PRETRIAL,Fleming,Sean,NULL,Male,African-American,03/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/7/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60259,69120,62666,Probation,DiCarlo,Hector,Oscar,Male,Hispanic,07/25/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/8/14 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +60259,69120,62666,Probation,DiCarlo,Hector,Oscar,Male,Hispanic,07/25/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/8/14 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +60259,69120,62666,Probation,DiCarlo,Hector,Oscar,Male,Hispanic,07/25/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60254,69115,62661,Probation,ramirez,jorge,NULL,Male,Hispanic,12/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +60254,69115,62661,Probation,ramirez,jorge,NULL,Male,Hispanic,12/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +60254,69115,62661,Probation,ramirez,jorge,NULL,Male,Hispanic,12/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +46242,69133,62679,PRETRIAL,PHENGKHAMPHATH,PHOUTHALA,NULL,Male,Caucasian,06/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +46242,69133,62679,PRETRIAL,PHENGKHAMPHATH,PHOUTHALA,NULL,Male,Caucasian,06/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +46242,69133,62679,PRETRIAL,PHENGKHAMPHATH,PHOUTHALA,NULL,Male,Caucasian,06/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60239,69094,62644,PRETRIAL,Roundtree,Derrick,Terron,Male,African-American,10/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +60239,69094,62644,PRETRIAL,Roundtree,Derrick,Terron,Male,African-American,10/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +60239,69094,62644,PRETRIAL,Roundtree,Derrick,Terron,Male,African-American,10/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60252,69112,62659,Probation,diaz,erik,NULL,Male,African-American,03/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +60252,69112,62659,Probation,diaz,erik,NULL,Male,African-American,03/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +60252,69112,62659,Probation,diaz,erik,NULL,Male,African-American,03/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60249,69110,62657,Probation,Nelson,Floyd,NULL,Male,African-American,04/10/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +60249,69110,62657,Probation,Nelson,Floyd,NULL,Male,African-American,04/10/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +60249,69110,62657,Probation,Nelson,Floyd,NULL,Male,African-American,04/10/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60256,69117,62663,Probation,RODRIGUEZ,VALARIE,NULL,Female,Caucasian,03/01/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +60256,69117,62663,Probation,RODRIGUEZ,VALARIE,NULL,Female,Caucasian,03/01/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +60256,69117,62663,Probation,RODRIGUEZ,VALARIE,NULL,Female,Caucasian,03/01/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60241,69096,62646,PRETRIAL,Sessa,Joseph,NULL,Male,Caucasian,01/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +60241,69096,62646,PRETRIAL,Sessa,Joseph,NULL,Male,Caucasian,01/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +60241,69096,62646,PRETRIAL,Sessa,Joseph,NULL,Male,Caucasian,01/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60267,69131,62677,PRETRIAL,schmidt,robert,NULL,Male,Caucasian,08/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +60267,69131,62677,PRETRIAL,schmidt,robert,NULL,Male,Caucasian,08/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +60267,69131,62677,PRETRIAL,schmidt,robert,NULL,Male,Caucasian,08/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60261,69123,62669,Probation,crowley,andrew,NULL,Male,Caucasian,06/27/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +60261,69123,62669,Probation,crowley,andrew,NULL,Male,Caucasian,06/27/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +60261,69123,62669,Probation,crowley,andrew,NULL,Male,Caucasian,06/27/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60262,69125,62671,PRETRIAL,Principe,Anthony,NULL,Male,Caucasian,12/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +60262,69125,62671,PRETRIAL,Principe,Anthony,NULL,Male,Caucasian,12/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +60262,69125,62671,PRETRIAL,Principe,Anthony,NULL,Male,Caucasian,12/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60247,69102,62652,Probation,perkins,janice,NULL,Female,Caucasian,04/17/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +60247,69102,62652,Probation,perkins,janice,NULL,Female,Caucasian,04/17/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +60247,69102,62652,Probation,perkins,janice,NULL,Female,Caucasian,04/17/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51895,69104,62653,PRETRIAL,Sloan,Aurora,NULL,Female,Caucasian,06/14/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +51895,69104,62653,PRETRIAL,Sloan,Aurora,NULL,Female,Caucasian,06/14/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +51895,69104,62653,PRETRIAL,Sloan,Aurora,NULL,Female,Caucasian,06/14/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60258,69119,62665,Probation,EKER,JASON,JONATHAN,Male,Caucasian,01/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +60258,69119,62665,Probation,EKER,JASON,JONATHAN,Male,Caucasian,01/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +60258,69119,62665,Probation,EKER,JASON,JONATHAN,Male,Caucasian,01/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60238,69093,62643,PRETRIAL,Chance,Dvraj,Singh,Male,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +60238,69093,62643,PRETRIAL,Chance,Dvraj,Singh,Male,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +60238,69093,62643,PRETRIAL,Chance,Dvraj,Singh,Male,African-American,09/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60243,69098,62648,PRETRIAL,NIESTERCZUK,PATRICK,NULL,Male,Caucasian,06/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +60243,69098,62648,PRETRIAL,NIESTERCZUK,PATRICK,NULL,Male,Caucasian,06/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +60243,69098,62648,PRETRIAL,NIESTERCZUK,PATRICK,NULL,Male,Caucasian,06/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60245,69100,62650,PRETRIAL,JOHNSON,PAUL,NULL,Male,African-American,06/25/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +60245,69100,62650,PRETRIAL,JOHNSON,PAUL,NULL,Male,African-American,06/25/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +60245,69100,62650,PRETRIAL,JOHNSON,PAUL,NULL,Male,African-American,06/25/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +60253,69114,62660,PRETRIAL,Johnson,Jewel,NULL,Male,African-American,04/08/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +60253,69114,62660,PRETRIAL,Johnson,Jewel,NULL,Male,African-American,04/08/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,4,High,8,Risk of Recidivism,1.18,10,High,New,1,0 +60253,69114,62660,PRETRIAL,Johnson,Jewel,NULL,Male,African-American,04/08/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +60265,69128,62674,Probation,Solz,Colette,NULL,Female,Caucasian,06/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +60265,69128,62674,Probation,Solz,Colette,NULL,Female,Caucasian,06/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +60265,69128,62674,Probation,Solz,Colette,NULL,Female,Caucasian,06/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60269,69135,62680,Probation,Bender,Jeanne,Boyce,Female,Caucasian,06/30/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/8/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +60269,69135,62680,Probation,Bender,Jeanne,Boyce,Female,Caucasian,06/30/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/8/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +60269,69135,62680,Probation,Bender,Jeanne,Boyce,Female,Caucasian,06/30/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60250,69109,62656,PRETRIAL,regis,Felix,NULL,Male,African-American,10/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +60250,69109,62656,PRETRIAL,regis,Felix,NULL,Male,African-American,10/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +60250,69109,62656,PRETRIAL,regis,Felix,NULL,Male,African-American,10/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60248,69105,62654,Probation,Pincus,Joseph,NULL,Male,Caucasian,03/29/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +60248,69105,62654,Probation,Pincus,Joseph,NULL,Male,Caucasian,03/29/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +60248,69105,62654,Probation,Pincus,Joseph,NULL,Male,Caucasian,03/29/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60266,69130,62676,Probation,Restrepo,Milena,NULL,Female,Hispanic,03/07/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +60266,69130,62676,Probation,Restrepo,Milena,NULL,Female,Hispanic,03/07/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +60266,69130,62676,Probation,Restrepo,Milena,NULL,Female,Hispanic,03/07/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60263,69126,62672,Probation,Alders,Paul,NULL,Male,Caucasian,01/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +60263,69126,62672,Probation,Alders,Paul,NULL,Male,Caucasian,01/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +60263,69126,62672,Probation,Alders,Paul,NULL,Male,Caucasian,01/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55241,69124,62670,PRETRIAL,Silva,Flavio,NULL,Male,Hispanic,08/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +55241,69124,62670,PRETRIAL,Silva,Flavio,NULL,Male,Hispanic,08/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +55241,69124,62670,PRETRIAL,Silva,Flavio,NULL,Male,Hispanic,08/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60240,69095,62645,PRETRIAL,BROWNE,OMAR,QUINCY,Male,African-American,09/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +60240,69095,62645,PRETRIAL,BROWNE,OMAR,QUINCY,Male,African-American,09/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +60240,69095,62645,PRETRIAL,BROWNE,OMAR,QUINCY,Male,African-American,09/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60268,69132,62678,Probation,thibodeau,dale,NULL,Male,Caucasian,07/10/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +60268,69132,62678,Probation,thibodeau,dale,NULL,Male,Caucasian,07/10/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +60268,69132,62678,Probation,thibodeau,dale,NULL,Male,Caucasian,07/10/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59175,69103,61462,Probation,SWAIN,PATRICIA,ANN,Female,Caucasian,06/06/63,17,All Scales,Intake,English,Conditional Release,Probation,Married,1/8/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +59175,69103,61462,Probation,SWAIN,PATRICIA,ANN,Female,Caucasian,06/06/63,17,All Scales,Intake,English,Conditional Release,Probation,Married,1/8/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +59175,69103,61462,Probation,SWAIN,PATRICIA,ANN,Female,Caucasian,06/06/63,17,All Scales,Intake,English,Conditional Release,Probation,Married,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +59365,69137,61682,Probation,Glaze,Joshua,Steven,Male,Caucasian,10/26/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,4,High,7,Risk of Violence,-0.58,10,High,Copy,1,0 +59365,69137,61682,Probation,Glaze,Joshua,Steven,Male,Caucasian,10/26/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,4,High,8,Risk of Recidivism,1.14,10,High,Copy,1,0 +59365,69137,61682,Probation,Glaze,Joshua,Steven,Male,Caucasian,10/26/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,4,High,18,Risk of Failure to Appear,29,7,Medium,Copy,1,0 +60255,69116,62662,Probation,Nabridge,Robert,NULL,Male,Caucasian,11/19/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +60255,69116,62662,Probation,Nabridge,Robert,NULL,Male,Caucasian,11/19/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +60255,69116,62662,Probation,Nabridge,Robert,NULL,Male,Caucasian,11/19/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60251,69111,62658,PRETRIAL,Pierre,Esther,NULL,Female,African-American,05/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/8/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +60251,69111,62658,PRETRIAL,Pierre,Esther,NULL,Female,African-American,05/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +60251,69111,62658,PRETRIAL,Pierre,Esther,NULL,Female,African-American,05/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +15603,69129,62675,PRETRIAL,dorso,doreen,NULL,Female,Caucasian,03/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +15603,69129,62675,PRETRIAL,dorso,doreen,NULL,Female,Caucasian,03/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +15603,69129,62675,PRETRIAL,dorso,doreen,NULL,Female,Caucasian,03/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60237,69092,62642,PRETRIAL,LIMA,LUIS,A,Male,Hispanic,03/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +60237,69092,62642,PRETRIAL,LIMA,LUIS,A,Male,Hispanic,03/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +60237,69092,62642,PRETRIAL,LIMA,LUIS,A,Male,Hispanic,03/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60244,69099,62649,PRETRIAL,CIMELUS,KASENET,NULL,Male,African-American,04/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +60244,69099,62649,PRETRIAL,CIMELUS,KASENET,NULL,Male,African-American,04/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +60244,69099,62649,PRETRIAL,CIMELUS,KASENET,NULL,Male,African-American,04/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59870,69113,62242,PRETRIAL,Siegel,Andrew,NULL,Male,Caucasian,06/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,Copy,1,0 +59870,69113,62242,PRETRIAL,Siegel,Andrew,NULL,Male,Caucasian,06/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,Copy,1,0 +59870,69113,62242,PRETRIAL,Siegel,Andrew,NULL,Male,Caucasian,06/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +60264,69127,62673,PRETRIAL,Brasher,Amon,NULL,Male,Caucasian,10/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +60264,69127,62673,PRETRIAL,Brasher,Amon,NULL,Male,Caucasian,10/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +60264,69127,62673,PRETRIAL,Brasher,Amon,NULL,Male,Caucasian,10/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +41767,69136,62681,PRETRIAL,BUTLER,LEQUENTIN,TERRILL,Male,African-American,07/31/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,2,Medium,7,Risk of Violence,-3.2,1,Low,New,1,0 +41767,69136,62681,PRETRIAL,BUTLER,LEQUENTIN,TERRILL,Male,African-American,07/31/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +41767,69136,62681,PRETRIAL,BUTLER,LEQUENTIN,TERRILL,Male,African-American,07/31/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +49263,69134,50080,Probation,Bullock,Quintis,NULL,Male,African-American,10/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/8/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,Copy,1,0 +49263,69134,50080,Probation,Bullock,Quintis,NULL,Male,African-American,10/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/8/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,Copy,1,0 +49263,69134,50080,Probation,Bullock,Quintis,NULL,Male,African-American,10/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +60242,69097,62647,PRETRIAL,PIERRE,PATRICIA,NULL,Female,African-American,07/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +60242,69097,62647,PRETRIAL,PIERRE,PATRICIA,NULL,Female,African-American,07/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +60242,69097,62647,PRETRIAL,PIERRE,PATRICIA,NULL,Female,African-American,07/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60246,69101,62651,Probation,Smith,Keosha,NULL,Female,African-American,03/20/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +60246,69101,62651,Probation,Smith,Keosha,NULL,Female,African-American,03/20/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,10,High,New,1,0 +60246,69101,62651,Probation,Smith,Keosha,NULL,Female,African-American,03/20/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55300,69122,62668,Probation,Standifer,Roosevelt,NULL,Male,African-American,01/07/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,2,Medium,7,Risk of Violence,-3.01,1,Low,New,1,0 +55300,69122,62668,Probation,Standifer,Roosevelt,NULL,Male,African-American,01/07/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +55300,69122,62668,Probation,Standifer,Roosevelt,NULL,Male,African-American,01/07/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/8/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +32924,69139,31995,PRETRIAL,Cruz,Gilbert,NULL,Male,Hispanic,11/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,4,High,7,Risk of Violence,-1.09,8,High,Copy,1,0 +32924,69139,31995,PRETRIAL,Cruz,Gilbert,NULL,Male,Hispanic,11/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,4,High,8,Risk of Recidivism,0.25,8,High,Copy,1,0 +32924,69139,31995,PRETRIAL,Cruz,Gilbert,NULL,Male,Hispanic,11/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +60289,69169,62709,PRETRIAL,CAPOZZI,CATHERINE,NULL,Female,Caucasian,08/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/9/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +60289,69169,62709,PRETRIAL,CAPOZZI,CATHERINE,NULL,Female,Caucasian,08/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/9/14 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +60289,69169,62709,PRETRIAL,CAPOZZI,CATHERINE,NULL,Female,Caucasian,08/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60272,69143,62685,PRETRIAL,Hodges,Johnny,A,Male,African-American,02/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.18,8,High,New,1,0 +60272,69143,62685,PRETRIAL,Hodges,Johnny,A,Male,African-American,02/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +60272,69143,62685,PRETRIAL,Hodges,Johnny,A,Male,African-American,02/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60276,69148,62690,PRETRIAL,Bailey,Creshundo,NULL,Male,African-American,12/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +60276,69148,62690,PRETRIAL,Bailey,Creshundo,NULL,Male,African-American,12/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +60276,69148,62690,PRETRIAL,Bailey,Creshundo,NULL,Male,African-American,12/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60279,69152,62694,Probation,Calle,Carlos,Andres,Male,Hispanic,11/22/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +60279,69152,62694,Probation,Calle,Carlos,Andres,Male,Hispanic,11/22/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +60279,69152,62694,Probation,Calle,Carlos,Andres,Male,Hispanic,11/22/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60292,69173,62713,PRETRIAL,ELLINGTON,CARLTON,NEIL,Male,African-American,09/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +60292,69173,62713,PRETRIAL,ELLINGTON,CARLTON,NEIL,Male,African-American,09/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +60292,69173,62713,PRETRIAL,ELLINGTON,CARLTON,NEIL,Male,African-American,09/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60282,69157,62698,Probation,White,Portia,NULL,Female,African-American,04/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,7,Risk of Violence,-3.11,1,Low,New,1,0 +60282,69157,62698,Probation,White,Portia,NULL,Female,African-American,04/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +60282,69157,62698,Probation,White,Portia,NULL,Female,African-American,04/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +45476,69155,62697,PRETRIAL,Fernandez,Nicholas,NULL,Male,Hispanic,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +45476,69155,62697,PRETRIAL,Fernandez,Nicholas,NULL,Male,Hispanic,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +45476,69155,62697,PRETRIAL,Fernandez,Nicholas,NULL,Male,Hispanic,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60286,69164,62704,Probation,Gibson,Albert,NULL,Male,Caucasian,08/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/9/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +60286,69164,62704,Probation,Gibson,Albert,NULL,Male,Caucasian,08/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/9/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +60286,69164,62704,Probation,Gibson,Albert,NULL,Male,Caucasian,08/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55505,69178,62718,Probation,Schoolfield,Javier,NULL,Male,Hispanic,03/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +55505,69178,62718,Probation,Schoolfield,Javier,NULL,Male,Hispanic,03/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +55505,69178,62718,Probation,Schoolfield,Javier,NULL,Male,Hispanic,03/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60295,69179,62719,Probation,MARQUEZ,ANDRES,MANUEL,Male,Hispanic,11/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +60295,69179,62719,Probation,MARQUEZ,ANDRES,MANUEL,Male,Hispanic,11/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +60295,69179,62719,Probation,MARQUEZ,ANDRES,MANUEL,Male,Hispanic,11/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60283,69158,62699,PRETRIAL,arne,lucia,NULL,Female,African-American,06/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +60283,69158,62699,PRETRIAL,arne,lucia,NULL,Female,African-American,06/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +60283,69158,62699,PRETRIAL,arne,lucia,NULL,Female,African-American,06/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55030,69176,62716,Probation,habe,christopher,NULL,Male,Caucasian,03/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/9/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +55030,69176,62716,Probation,habe,christopher,NULL,Male,Caucasian,03/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/9/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +55030,69176,62716,Probation,habe,christopher,NULL,Male,Caucasian,03/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60290,69171,62711,Probation,ALLEN,CLIFTON,L,Male,African-American,03/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +60290,69171,62711,Probation,ALLEN,CLIFTON,L,Male,African-American,03/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +60290,69171,62711,Probation,ALLEN,CLIFTON,L,Male,African-American,03/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +34642,69166,62706,PRETRIAL,Willingham,Joey,NULL,Male,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +34642,69166,62706,PRETRIAL,Willingham,Joey,NULL,Male,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,4,High,8,Risk of Recidivism,0.15,8,High,New,1,0 +34642,69166,62706,PRETRIAL,Willingham,Joey,NULL,Male,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60288,69168,62708,Probation,smith,jartell,NULL,Male,African-American,06/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +60288,69168,62708,Probation,smith,jartell,NULL,Male,African-American,06/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +60288,69168,62708,Probation,smith,jartell,NULL,Male,African-American,06/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60280,69153,62695,Probation,Eudes,Sylvain,NULL,Male,Caucasian,06/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +60280,69153,62695,Probation,Eudes,Sylvain,NULL,Male,Caucasian,06/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +60280,69153,62695,Probation,Eudes,Sylvain,NULL,Male,Caucasian,06/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +6136,69145,62687,PRETRIAL,BAPTISTE,DANIEL,FLOYD,Male,African-American,11/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/14 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +6136,69145,62687,PRETRIAL,BAPTISTE,DANIEL,FLOYD,Male,African-American,11/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +6136,69145,62687,PRETRIAL,BAPTISTE,DANIEL,FLOYD,Male,African-American,11/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +51910,69160,62701,Probation,Parry,Lois,NULL,Female,Caucasian,06/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +51910,69160,62701,Probation,Parry,Lois,NULL,Female,Caucasian,06/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,9,High,New,1,0 +51910,69160,62701,Probation,Parry,Lois,NULL,Female,Caucasian,06/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60293,69174,62714,Probation,Scarpati,Vincent,NULL,Male,Caucasian,02/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +60293,69174,62714,Probation,Scarpati,Vincent,NULL,Male,Caucasian,02/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +60293,69174,62714,Probation,Scarpati,Vincent,NULL,Male,Caucasian,02/26/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +13595,69140,62683,PRETRIAL,rouis,sharon,NULL,Female,African-American,09/30/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +13595,69140,62683,PRETRIAL,rouis,sharon,NULL,Female,African-American,09/30/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +13595,69140,62683,PRETRIAL,rouis,sharon,NULL,Female,African-American,09/30/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60278,69151,62693,Probation,Dinucci,James,NULL,Male,Caucasian,09/16/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +60278,69151,62693,Probation,Dinucci,James,NULL,Male,Caucasian,09/16/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +60278,69151,62693,Probation,Dinucci,James,NULL,Male,Caucasian,09/16/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +48677,69165,62705,PRETRIAL,Kims,Shanekra,NULL,Female,African-American,06/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +48677,69165,62705,PRETRIAL,Kims,Shanekra,NULL,Female,African-American,06/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +48677,69165,62705,PRETRIAL,Kims,Shanekra,NULL,Female,African-American,06/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60273,69144,62686,PRETRIAL,Goesem,Tess,NULL,Female,Caucasian,07/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,New,1,0 +60273,69144,62686,PRETRIAL,Goesem,Tess,NULL,Female,Caucasian,07/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,9,High,New,1,0 +60273,69144,62686,PRETRIAL,Goesem,Tess,NULL,Female,Caucasian,07/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60274,69147,62689,Probation,Minore,Anthony,Joseph,Male,Caucasian,03/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +60274,69147,62689,Probation,Minore,Anthony,Joseph,Male,Caucasian,03/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +60274,69147,62689,Probation,Minore,Anthony,Joseph,Male,Caucasian,03/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54532,69161,62702,PRETRIAL,Parker,Trevor,Nathaniel,Male,African-American,04/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +54532,69161,62702,PRETRIAL,Parker,Trevor,Nathaniel,Male,African-American,04/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +54532,69161,62702,PRETRIAL,Parker,Trevor,Nathaniel,Male,African-American,04/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +2047,69156,59669,PRETRIAL,BROWN,VICTOR,NULL,Male,African-American,11/02/89,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,4,High,7,Risk of Violence,0,10,High,Copy,1,0 +2047,69156,59669,PRETRIAL,BROWN,VICTOR,NULL,Male,African-American,11/02/89,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,4,High,8,Risk of Recidivism,1.13,10,High,Copy,1,0 +2047,69156,59669,PRETRIAL,BROWN,VICTOR,NULL,Male,African-American,11/02/89,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,4,High,18,Risk of Failure to Appear,24,5,Medium,Copy,1,0 +60294,69177,62717,Probation,Bourque,Kelly,Marie,Female,Caucasian,11/10/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +60294,69177,62717,Probation,Bourque,Kelly,Marie,Female,Caucasian,11/10/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +60294,69177,62717,Probation,Bourque,Kelly,Marie,Female,Caucasian,11/10/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60277,69149,62691,Probation,SHOKRAI,FATANEH,NULL,Male,Caucasian,06/18/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +60277,69149,62691,Probation,SHOKRAI,FATANEH,NULL,Male,Caucasian,06/18/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +60277,69149,62691,Probation,SHOKRAI,FATANEH,NULL,Male,Caucasian,06/18/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60285,69163,62703,Probation,tabraue,joumil,NULL,Male,Hispanic,12/08/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/9/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +60285,69163,62703,Probation,tabraue,joumil,NULL,Male,Hispanic,12/08/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/9/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +60285,69163,62703,Probation,tabraue,joumil,NULL,Male,Hispanic,12/08/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +38065,69170,62710,PRETRIAL,Durollari,Adriatik,NULL,Male,Caucasian,01/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +38065,69170,62710,PRETRIAL,Durollari,Adriatik,NULL,Male,Caucasian,01/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +38065,69170,62710,PRETRIAL,Durollari,Adriatik,NULL,Male,Caucasian,01/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60291,69172,62712,Probation,kendrick,daniel,NULL,Male,African-American,08/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +60291,69172,62712,Probation,kendrick,daniel,NULL,Male,African-American,08/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +60291,69172,62712,Probation,kendrick,daniel,NULL,Male,African-American,08/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60270,69138,62682,PRETRIAL,LOPEZ,CHRISTOPHER,NULL,Male,Caucasian,01/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +60270,69138,62682,PRETRIAL,LOPEZ,CHRISTOPHER,NULL,Male,Caucasian,01/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +60270,69138,62682,PRETRIAL,LOPEZ,CHRISTOPHER,NULL,Male,Caucasian,01/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60284,69159,62700,Probation,SANCHEZ,ERIC,MICHAEL,Male,Caucasian,07/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +60284,69159,62700,Probation,SANCHEZ,ERIC,MICHAEL,Male,Caucasian,07/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +60284,69159,62700,Probation,SANCHEZ,ERIC,MICHAEL,Male,Caucasian,07/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60275,69146,62688,Probation,ali,saad,NULL,Male,Asian,11/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +60275,69146,62688,Probation,ali,saad,NULL,Male,Asian,11/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +60275,69146,62688,Probation,ali,saad,NULL,Male,Asian,11/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60287,69167,62707,Probation,lewis,Devonte,NULL,Male,African-American,08/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +60287,69167,62707,Probation,lewis,Devonte,NULL,Male,African-American,08/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +60287,69167,62707,Probation,lewis,Devonte,NULL,Male,African-American,08/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +36458,69162,36278,PRETRIAL,Castellanos,Daniel,NULL,Male,Hispanic,05/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/9/14 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,Copy,1,0 +36458,69162,36278,PRETRIAL,Castellanos,Daniel,NULL,Male,Hispanic,05/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/9/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,Copy,1,0 +36458,69162,36278,PRETRIAL,Castellanos,Daniel,NULL,Male,Hispanic,05/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +60299,69180,62720,PRETRIAL,BELBA,HALEY,JEANNE,Female,Caucasian,12/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +60299,69180,62720,PRETRIAL,BELBA,HALEY,JEANNE,Female,Caucasian,12/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/14 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +60299,69180,62720,PRETRIAL,BELBA,HALEY,JEANNE,Female,Caucasian,12/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60281,69154,62696,PRETRIAL,GRIFFITH,BRAD,ALAN,Female,Caucasian,05/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +60281,69154,62696,PRETRIAL,GRIFFITH,BRAD,ALAN,Female,Caucasian,05/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +60281,69154,62696,PRETRIAL,GRIFFITH,BRAD,ALAN,Female,Caucasian,05/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +60271,69141,62684,PRETRIAL,Ray,Latonya,NULL,Female,African-American,04/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +60271,69141,62684,PRETRIAL,Ray,Latonya,NULL,Female,African-American,04/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +60271,69141,62684,PRETRIAL,Ray,Latonya,NULL,Female,African-American,04/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/9/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53255,69175,62715,Probation,Prophilis,Walson,NULL,Male,African-American,10/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,4,High,7,Risk of Violence,-1.05,8,High,New,1,0 +53255,69175,62715,Probation,Prophilis,Walson,NULL,Male,African-American,10/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +53255,69175,62715,Probation,Prophilis,Walson,NULL,Male,African-American,10/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/9/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +39286,69209,62744,Probation,richelieu,volci,NULL,Male,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.61,2,Low,New,1,0 +39286,69209,62744,Probation,richelieu,volci,NULL,Male,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +39286,69209,62744,Probation,richelieu,volci,NULL,Male,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60305,69188,62726,PRETRIAL,Vaughn,Stephen,A,Male,African-American,07/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1,8,High,New,1,0 +60305,69188,62726,PRETRIAL,Vaughn,Stephen,A,Male,African-American,07/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +60305,69188,62726,PRETRIAL,Vaughn,Stephen,A,Male,African-American,07/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59596,69183,61950,PRETRIAL,Valcy,Sebastian,NULL,Male,African-American,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,Copy,1,0 +59596,69183,61950,PRETRIAL,Valcy,Sebastian,NULL,Male,African-American,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,Copy,1,0 +59596,69183,61950,PRETRIAL,Valcy,Sebastian,NULL,Male,African-American,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +60316,69201,62738,Probation,dykes,fred,NULL,Male,African-American,06/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,2,Medium,7,Risk of Violence,-3.07,1,Low,New,1,0 +60316,69201,62738,Probation,dykes,fred,NULL,Male,African-American,06/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +60316,69201,62738,Probation,dykes,fred,NULL,Male,African-American,06/24/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +46163,69217,62750,PRETRIAL,Altamiranda,William,NULL,Male,Hispanic,12/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +46163,69217,62750,PRETRIAL,Altamiranda,William,NULL,Male,Hispanic,12/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +46163,69217,62750,PRETRIAL,Altamiranda,William,NULL,Male,Hispanic,12/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60311,69196,62733,Probation,Antonopoulos,Chris,NULL,Male,Caucasian,12/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/10/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +60311,69196,62733,Probation,Antonopoulos,Chris,NULL,Male,Caucasian,12/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/10/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +60311,69196,62733,Probation,Antonopoulos,Chris,NULL,Male,Caucasian,12/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60317,69204,62741,Probation,Gonzalez,Jose,juan,Male,Hispanic,09/12/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +60317,69204,62741,Probation,Gonzalez,Jose,juan,Male,Hispanic,09/12/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +60317,69204,62741,Probation,Gonzalez,Jose,juan,Male,Hispanic,09/12/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +45901,69219,46237,PRETRIAL,Williams,Larry,NULL,Male,Caucasian,09/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,Copy,1,0 +45901,69219,46237,PRETRIAL,Williams,Larry,NULL,Male,Caucasian,09/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,Copy,1,0 +45901,69219,46237,PRETRIAL,Williams,Larry,NULL,Male,Caucasian,09/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +60327,69221,62753,Probation,MCISAAC,KELLY,B,Female,Caucasian,02/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +60327,69221,62753,Probation,MCISAAC,KELLY,B,Female,Caucasian,02/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +60327,69221,62753,Probation,MCISAAC,KELLY,B,Female,Caucasian,02/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60308,69191,62729,PRETRIAL,Hein,Leah,Ann,Female,Caucasian,04/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +60308,69191,62729,PRETRIAL,Hein,Leah,Ann,Female,Caucasian,04/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +60308,69191,62729,PRETRIAL,Hein,Leah,Ann,Female,Caucasian,04/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60309,69193,62731,PRETRIAL,Ruiz,Aladdin,NULL,Male,Caucasian,02/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/10/14 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +60309,69193,62731,PRETRIAL,Ruiz,Aladdin,NULL,Male,Caucasian,02/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/10/14 0:00,4,High,8,Risk of Recidivism,0.28,8,High,New,1,0 +60309,69193,62731,PRETRIAL,Ruiz,Aladdin,NULL,Male,Caucasian,02/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/10/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60313,69198,62735,Probation,Matias,Rafael,NULL,Male,Hispanic,12/01/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +60313,69198,62735,Probation,Matias,Rafael,NULL,Male,Hispanic,12/01/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +60313,69198,62735,Probation,Matias,Rafael,NULL,Male,Hispanic,12/01/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60315,69200,62737,Probation,DECRUMPE,LASHONDA,S,Female,African-American,04/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +60315,69200,62737,Probation,DECRUMPE,LASHONDA,S,Female,African-American,04/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +60315,69200,62737,Probation,DECRUMPE,LASHONDA,S,Female,African-American,04/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60322,69214,62747,PRETRIAL,MARTINEZ,ERIC,NULL,Male,Caucasian,07/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +60322,69214,62747,PRETRIAL,MARTINEZ,ERIC,NULL,Male,Caucasian,07/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +60322,69214,62747,PRETRIAL,MARTINEZ,ERIC,NULL,Male,Caucasian,07/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +59596,69182,61950,PRETRIAL,Valcy,Sebastian,NULL,Male,African-American,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,Copy,1,0 +59596,69182,61950,PRETRIAL,Valcy,Sebastian,NULL,Male,African-American,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.64,10,High,Copy,1,0 +59596,69182,61950,PRETRIAL,Valcy,Sebastian,NULL,Male,African-American,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +60318,69207,62742,Probation,VIERA,VALTER,NULL,Male,Native American,03/27/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/10/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +60318,69207,62742,Probation,VIERA,VALTER,NULL,Male,Native American,03/27/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/10/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +60318,69207,62742,Probation,VIERA,VALTER,NULL,Male,Native American,03/27/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60323,69216,62749,PRETRIAL,burkholder,james,NULL,Male,Caucasian,12/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +60323,69216,62749,PRETRIAL,burkholder,james,NULL,Male,Caucasian,12/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +60323,69216,62749,PRETRIAL,burkholder,james,NULL,Male,Caucasian,12/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +60303,69186,62724,PRETRIAL,Basil,Maxima,NULL,Female,Other,12/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +60303,69186,62724,PRETRIAL,Basil,Maxima,NULL,Female,Other,12/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,4,High,8,Risk of Recidivism,0.44,10,High,New,1,0 +60303,69186,62724,PRETRIAL,Basil,Maxima,NULL,Female,Other,12/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60320,69210,62745,PRETRIAL,sarver,john,NULL,Male,Caucasian,04/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +60320,69210,62745,PRETRIAL,sarver,john,NULL,Male,Caucasian,04/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +60320,69210,62745,PRETRIAL,sarver,john,NULL,Male,Caucasian,04/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60300,69181,62721,PRETRIAL,Davis,Paul,NULL,Male,African-American,06/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,2,Medium,7,Risk of Violence,-3.12,1,Low,New,1,0 +60300,69181,62721,PRETRIAL,Davis,Paul,NULL,Male,African-American,06/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +60300,69181,62721,PRETRIAL,Davis,Paul,NULL,Male,African-American,06/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60310,69195,62732,PRETRIAL,OLIBRICE,RANDY,NULL,Male,African-American,09/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/10/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +60310,69195,62732,PRETRIAL,OLIBRICE,RANDY,NULL,Male,African-American,09/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +60310,69195,62732,PRETRIAL,OLIBRICE,RANDY,NULL,Male,African-American,09/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,1/10/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60304,69187,62725,PRETRIAL,Moreland,Jamil,NULL,Male,African-American,07/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +60304,69187,62725,PRETRIAL,Moreland,Jamil,NULL,Male,African-American,07/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +60304,69187,62725,PRETRIAL,Moreland,Jamil,NULL,Male,African-American,07/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +22345,69189,62727,PRETRIAL,reese,willie,NULL,Male,African-American,06/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +22345,69189,62727,PRETRIAL,reese,willie,NULL,Male,African-American,06/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +22345,69189,62727,PRETRIAL,reese,willie,NULL,Male,African-American,06/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55197,69202,62739,Probation,VARIN,DONNA,M,Female,Caucasian,05/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +55197,69202,62739,Probation,VARIN,DONNA,M,Female,Caucasian,05/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +55197,69202,62739,Probation,VARIN,DONNA,M,Female,Caucasian,05/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +60021,69205,62404,PRETRIAL,Savage,Genevieve,NULL,Female,Caucasian,10/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,Copy,1,0 +60021,69205,62404,PRETRIAL,Savage,Genevieve,NULL,Female,Caucasian,10/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,Copy,1,0 +60021,69205,62404,PRETRIAL,Savage,Genevieve,NULL,Female,Caucasian,10/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +60301,69184,62722,PRETRIAL,Salley,Eugene,W,Male,African-American,07/03/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +60301,69184,62722,PRETRIAL,Salley,Eugene,W,Male,African-American,07/03/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +60301,69184,62722,PRETRIAL,Salley,Eugene,W,Male,African-American,07/03/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60312,69197,62734,Probation,Drummond,Nicholas,NULL,Male,African-American,08/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +60312,69197,62734,Probation,Drummond,Nicholas,NULL,Male,African-American,08/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +60312,69197,62734,Probation,Drummond,Nicholas,NULL,Male,African-American,08/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +50252,69213,62255,PRETRIAL,Metelus,Nickenson,NULL,Male,Other,12/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,Copy,1,0 +50252,69213,62255,PRETRIAL,Metelus,Nickenson,NULL,Male,Other,12/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,Copy,1,0 +50252,69213,62255,PRETRIAL,Metelus,Nickenson,NULL,Male,Other,12/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +60302,69185,62723,PRETRIAL,Lindsey,John,Paul,Male,Caucasian,03/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +60302,69185,62723,PRETRIAL,Lindsey,John,Paul,Male,Caucasian,03/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +60302,69185,62723,PRETRIAL,Lindsey,John,Paul,Male,Caucasian,03/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +60307,69192,62730,PRETRIAL,Emmert,Brandon,Hagan,Male,Caucasian,10/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +60307,69192,62730,PRETRIAL,Emmert,Brandon,Hagan,Male,Caucasian,10/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +60307,69192,62730,PRETRIAL,Emmert,Brandon,Hagan,Male,Caucasian,10/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60314,69199,62736,Probation,vicente,mayco,NULL,Male,Hispanic,11/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +60314,69199,62736,Probation,vicente,mayco,NULL,Male,Hispanic,11/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +60314,69199,62736,Probation,vicente,mayco,NULL,Male,Hispanic,11/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60326,69220,62752,Probation,BUTLER,VICTORIA,NULL,Female,African-American,07/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +60326,69220,62752,Probation,BUTLER,VICTORIA,NULL,Female,African-American,07/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,8,High,New,1,0 +60326,69220,62752,Probation,BUTLER,VICTORIA,NULL,Female,African-American,07/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60306,69190,62728,PRETRIAL,Cunningham,Rasheed,NULL,Male,African-American,02/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +60306,69190,62728,PRETRIAL,Cunningham,Rasheed,NULL,Male,African-American,02/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +60306,69190,62728,PRETRIAL,Cunningham,Rasheed,NULL,Male,African-American,02/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60319,69208,62743,Probation,Howard,William,NULL,Male,Caucasian,08/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +60319,69208,62743,Probation,Howard,William,NULL,Male,Caucasian,08/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +60319,69208,62743,Probation,Howard,William,NULL,Male,Caucasian,08/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60324,69215,62748,PRETRIAL,Rios,Fernando,NULL,Male,Hispanic,08/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +60324,69215,62748,PRETRIAL,Rios,Fernando,NULL,Male,Hispanic,08/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +60324,69215,62748,PRETRIAL,Rios,Fernando,NULL,Male,Hispanic,08/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59716,69194,62077,PRETRIAL,CANNON,ROBERT,NULL,Male,African-American,01/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,Copy,1,0 +59716,69194,62077,PRETRIAL,CANNON,ROBERT,NULL,Male,African-American,01/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,Copy,1,0 +59716,69194,62077,PRETRIAL,CANNON,ROBERT,NULL,Male,African-American,01/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/10/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +60321,69211,62746,PRETRIAL,Marrero,Frank,NULL,Male,Caucasian,06/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.8,9,High,New,1,0 +60321,69211,62746,PRETRIAL,Marrero,Frank,NULL,Male,Caucasian,06/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +60321,69211,62746,PRETRIAL,Marrero,Frank,NULL,Male,Caucasian,06/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +29247,69229,62759,PRETRIAL,HOUSTON,DAVANTE,ANTOINE,Male,African-American,10/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +29247,69229,62759,PRETRIAL,HOUSTON,DAVANTE,ANTOINE,Male,African-American,10/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +29247,69229,62759,PRETRIAL,HOUSTON,DAVANTE,ANTOINE,Male,African-American,10/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +35894,69227,35124,PRETRIAL,Garcia,Michael,NULL,Male,African-American,08/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,Copy,1,0 +35894,69227,35124,PRETRIAL,Garcia,Michael,NULL,Male,African-American,08/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,Copy,1,0 +35894,69227,35124,PRETRIAL,Garcia,Michael,NULL,Male,African-American,08/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +38886,69234,62764,PRETRIAL,Brown,Cedrial,NULL,Male,African-American,11/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +38886,69234,62764,PRETRIAL,Brown,Cedrial,NULL,Male,African-American,11/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +38886,69234,62764,PRETRIAL,Brown,Cedrial,NULL,Male,African-American,11/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60331,69226,62757,PRETRIAL,JACKSON,DAVE,NULL,Male,Other,11/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/11/14 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +60331,69226,62757,PRETRIAL,JACKSON,DAVE,NULL,Male,Other,11/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/11/14 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +60331,69226,62757,PRETRIAL,JACKSON,DAVE,NULL,Male,Other,11/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60329,69223,62755,PRETRIAL,DORSAINVILLE,MICHEL,NULL,Male,Other,09/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/11/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +60329,69223,62755,PRETRIAL,DORSAINVILLE,MICHEL,NULL,Male,Other,09/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/11/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +60329,69223,62755,PRETRIAL,DORSAINVILLE,MICHEL,NULL,Male,Other,09/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55105,69231,62761,PRETRIAL,Obrien,Adam,NULL,Male,Caucasian,11/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +55105,69231,62761,PRETRIAL,Obrien,Adam,NULL,Male,Caucasian,11/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +55105,69231,62761,PRETRIAL,Obrien,Adam,NULL,Male,Caucasian,11/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60335,69233,62763,PRETRIAL,Medina,Channel,NULL,Female,African-American,09/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +60335,69233,62763,PRETRIAL,Medina,Channel,NULL,Female,African-American,09/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +60335,69233,62763,PRETRIAL,Medina,Channel,NULL,Female,African-American,09/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60332,69228,62758,PRETRIAL,Heeralal,Alicia,NULL,Female,Caucasian,03/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +60332,69228,62758,PRETRIAL,Heeralal,Alicia,NULL,Female,Caucasian,03/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +60332,69228,62758,PRETRIAL,Heeralal,Alicia,NULL,Female,Caucasian,03/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60336,69235,62765,PRETRIAL,Stanley,Charlie,NULL,Male,African-American,07/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +60336,69235,62765,PRETRIAL,Stanley,Charlie,NULL,Male,African-American,07/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +60336,69235,62765,PRETRIAL,Stanley,Charlie,NULL,Male,African-American,07/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +26135,69225,25235,PRETRIAL,wilkerson,ramon,leroy,Male,African-American,05/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,Copy,1,0 +26135,69225,25235,PRETRIAL,wilkerson,ramon,leroy,Male,African-American,05/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,Copy,1,0 +26135,69225,25235,PRETRIAL,wilkerson,ramon,leroy,Male,African-American,05/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +60334,69232,62762,PRETRIAL,Boykin,Lashonn,NULL,Female,African-American,04/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +60334,69232,62762,PRETRIAL,Boykin,Lashonn,NULL,Female,African-American,04/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +60334,69232,62762,PRETRIAL,Boykin,Lashonn,NULL,Female,African-American,04/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60330,69224,62756,PRETRIAL,Comete,Terrell,Bradley,Male,African-American,11/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +60330,69224,62756,PRETRIAL,Comete,Terrell,Bradley,Male,African-American,11/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +60330,69224,62756,PRETRIAL,Comete,Terrell,Bradley,Male,African-American,11/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60333,69230,62760,PRETRIAL,Yan,Chin,NULL,Male,Asian,02/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +60333,69230,62760,PRETRIAL,Yan,Chin,NULL,Male,Asian,02/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +60333,69230,62760,PRETRIAL,Yan,Chin,NULL,Male,Asian,02/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60328,69222,62754,PRETRIAL,Holder,Iron,NULL,Male,African-American,10/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +60328,69222,62754,PRETRIAL,Holder,Iron,NULL,Male,African-American,10/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,4,High,8,Risk of Recidivism,0.39,9,High,New,1,0 +60328,69222,62754,PRETRIAL,Holder,Iron,NULL,Male,African-American,10/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/11/14 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +21973,69243,62771,PRETRIAL,THOMAS,JOAN,NULL,Female,African-American,12/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +21973,69243,62771,PRETRIAL,THOMAS,JOAN,NULL,Female,African-American,12/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +21973,69243,62771,PRETRIAL,THOMAS,JOAN,NULL,Female,African-American,12/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +49241,69240,50053,Probation,Arbelaez,Claudia,Cristina,Female,Hispanic,02/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/12/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,Copy,1,0 +49241,69240,50053,Probation,Arbelaez,Claudia,Cristina,Female,Hispanic,02/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/12/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,Copy,1,0 +49241,69240,50053,Probation,Arbelaez,Claudia,Cristina,Female,Hispanic,02/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/12/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +60343,69245,62773,PRETRIAL,JONES,LARRY,NULL,Male,African-American,12/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,2,Medium,7,Risk of Violence,-3.17,1,Low,New,1,0 +60343,69245,62773,PRETRIAL,JONES,LARRY,NULL,Male,African-American,12/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +60343,69245,62773,PRETRIAL,JONES,LARRY,NULL,Male,African-American,12/10/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60344,69246,62774,PRETRIAL,Thomas,Tyara,NULL,Female,African-American,04/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +60344,69246,62774,PRETRIAL,Thomas,Tyara,NULL,Female,African-American,04/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +60344,69246,62774,PRETRIAL,Thomas,Tyara,NULL,Female,African-American,04/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60339,69238,62767,PRETRIAL,HAMMOND,KENNETH,BERNELL,Male,African-American,09/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +60339,69238,62767,PRETRIAL,HAMMOND,KENNETH,BERNELL,Male,African-American,09/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +60339,69238,62767,PRETRIAL,HAMMOND,KENNETH,BERNELL,Male,African-American,09/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60341,69242,62770,PRETRIAL,PETERSON,JAIMIE,KATRINA,Female,African-American,01/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +60341,69242,62770,PRETRIAL,PETERSON,JAIMIE,KATRINA,Female,African-American,01/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +60341,69242,62770,PRETRIAL,PETERSON,JAIMIE,KATRINA,Female,African-American,01/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55114,69237,56903,PRETRIAL,BROWN,RASHUN,MALIK,Male,African-American,07/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,Copy,1,0 +55114,69237,56903,PRETRIAL,BROWN,RASHUN,MALIK,Male,African-American,07/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,Copy,1,0 +55114,69237,56903,PRETRIAL,BROWN,RASHUN,MALIK,Male,African-American,07/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +46011,69244,62772,PRETRIAL,BONES,ANTHONY,NULL,Male,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +46011,69244,62772,PRETRIAL,BONES,ANTHONY,NULL,Male,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +46011,69244,62772,PRETRIAL,BONES,ANTHONY,NULL,Male,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +10805,69247,62775,PRETRIAL,brown,ramone,terrel,Male,African-American,01/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,4,High,7,Risk of Violence,-1.19,8,High,New,1,0 +10805,69247,62775,PRETRIAL,brown,ramone,terrel,Male,African-American,01/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,4,High,8,Risk of Recidivism,1,10,High,New,1,0 +10805,69247,62775,PRETRIAL,brown,ramone,terrel,Male,African-American,01/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/12/14 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +19639,69239,62768,PRETRIAL,Coulsting,Tristan,NULL,Male,Caucasian,01/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/12/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +19639,69239,62768,PRETRIAL,Coulsting,Tristan,NULL,Male,Caucasian,01/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +19639,69239,62768,PRETRIAL,Coulsting,Tristan,NULL,Male,Caucasian,01/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/12/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60337,69236,62766,PRETRIAL,HUSSAIN,HUSSAIN,ASAAD,Male,Other,06/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/12/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +60337,69236,62766,PRETRIAL,HUSSAIN,HUSSAIN,ASAAD,Male,Other,06/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/12/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +60337,69236,62766,PRETRIAL,HUSSAIN,HUSSAIN,ASAAD,Male,Other,06/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60340,69241,62769,PRETRIAL,Ramirez,Anthony,NULL,Male,Hispanic,05/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/12/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +60340,69241,62769,PRETRIAL,Ramirez,Anthony,NULL,Male,Hispanic,05/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/12/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +60340,69241,62769,PRETRIAL,Ramirez,Anthony,NULL,Male,Hispanic,05/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60347,69250,62778,PRETRIAL,Somwaru,Anil,NULL,Male,Other,07/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +60347,69250,62778,PRETRIAL,Somwaru,Anil,NULL,Male,Other,07/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +60347,69250,62778,PRETRIAL,Somwaru,Anil,NULL,Male,Other,07/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59598,69271,61952,PRETRIAL,Stroman,Xavier,NULL,Male,African-American,07/03/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,4,High,7,Risk of Violence,-1,8,High,Copy,1,0 +59598,69271,61952,PRETRIAL,Stroman,Xavier,NULL,Male,African-American,07/03/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,4,High,8,Risk of Recidivism,0.3,8,High,Copy,1,0 +59598,69271,61952,PRETRIAL,Stroman,Xavier,NULL,Male,African-American,07/03/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +60368,69280,62805,PRETRIAL,MAJEED,MUNTAZ,NULL,Male,African-American,09/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +60368,69280,62805,PRETRIAL,MAJEED,MUNTAZ,NULL,Male,African-American,09/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +60368,69280,62805,PRETRIAL,MAJEED,MUNTAZ,NULL,Male,African-American,09/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60385,69297,62820,Probation,pirajan,Marlon,NULL,Male,Hispanic,09/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/13/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +60385,69297,62820,Probation,pirajan,Marlon,NULL,Male,Hispanic,09/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/13/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +60385,69297,62820,Probation,pirajan,Marlon,NULL,Male,Hispanic,09/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60366,69276,62802,PRETRIAL,RODRIGUEZ,MARQUIS,NULL,Male,Hispanic,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +60366,69276,62802,PRETRIAL,RODRIGUEZ,MARQUIS,NULL,Male,Hispanic,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +60366,69276,62802,PRETRIAL,RODRIGUEZ,MARQUIS,NULL,Male,Hispanic,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60371,69283,62808,PRETRIAL,Johnson,Ulysses,NULL,Male,African-American,10/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/13/14 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +60371,69283,62808,PRETRIAL,Johnson,Ulysses,NULL,Male,African-American,10/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +60371,69283,62808,PRETRIAL,Johnson,Ulysses,NULL,Male,African-American,10/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/13/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +60389,69301,62824,Probation,WEST,TAMASHIA,J,Female,African-American,07/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +60389,69301,62824,Probation,WEST,TAMASHIA,J,Female,African-American,07/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +60389,69301,62824,Probation,WEST,TAMASHIA,J,Female,African-American,07/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +60351,69255,62783,PRETRIAL,Gefrard,James,NULL,Male,African-American,12/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,4,High,7,Risk of Violence,-0.64,9,High,New,1,0 +60351,69255,62783,PRETRIAL,Gefrard,James,NULL,Male,African-American,12/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +60351,69255,62783,PRETRIAL,Gefrard,James,NULL,Male,African-American,12/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +7970,69257,62785,PRETRIAL,Francois,Harvey,Daryl,Male,African-American,10/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +7970,69257,62785,PRETRIAL,Francois,Harvey,Daryl,Male,African-American,10/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +7970,69257,62785,PRETRIAL,Francois,Harvey,Daryl,Male,African-American,10/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +25559,69285,62810,Probation,simpson,brittany,NULL,Female,Native American,02/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/13/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +25559,69285,62810,Probation,simpson,brittany,NULL,Female,Native American,02/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +25559,69285,62810,Probation,simpson,brittany,NULL,Female,Native American,02/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/13/14 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +60380,69292,62815,PRETRIAL,Orange,Lisa,NULL,Female,African-American,08/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +60380,69292,62815,PRETRIAL,Orange,Lisa,NULL,Female,African-American,08/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +60380,69292,62815,PRETRIAL,Orange,Lisa,NULL,Female,African-American,08/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60387,69299,62822,Probation,mendes,paulo,NULL,Male,Caucasian,05/19/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +60387,69299,62822,Probation,mendes,paulo,NULL,Male,Caucasian,05/19/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +60387,69299,62822,Probation,mendes,paulo,NULL,Male,Caucasian,05/19/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60359,69264,62792,PRETRIAL,Alexis,Stiven,NULL,Male,African-American,02/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +60359,69264,62792,PRETRIAL,Alexis,Stiven,NULL,Male,African-American,02/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +60359,69264,62792,PRETRIAL,Alexis,Stiven,NULL,Male,African-American,02/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60363,69278,62803,Probation,DALORA,LAURA,NULL,Female,Caucasian,06/11/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/13/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +60363,69278,62803,Probation,DALORA,LAURA,NULL,Female,Caucasian,06/11/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +60363,69278,62803,Probation,DALORA,LAURA,NULL,Female,Caucasian,06/11/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +59225,69273,61513,PRETRIAL,Osceola,Dorian,NULL,Female,Native American,06/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,Copy,1,0 +59225,69273,61513,PRETRIAL,Osceola,Dorian,NULL,Female,Native American,06/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,7,Medium,Copy,1,0 +59225,69273,61513,PRETRIAL,Osceola,Dorian,NULL,Female,Native American,06/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +25656,69286,62811,Probation,league,stephen,NULL,Male,Caucasian,03/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/13/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +25656,69286,62811,Probation,league,stephen,NULL,Male,Caucasian,03/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +25656,69286,62811,Probation,league,stephen,NULL,Male,Caucasian,03/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60349,69252,62780,PRETRIAL,POWERS,TAMARA,SUE,Female,Caucasian,12/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +60349,69252,62780,PRETRIAL,POWERS,TAMARA,SUE,Female,Caucasian,12/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +60349,69252,62780,PRETRIAL,POWERS,TAMARA,SUE,Female,Caucasian,12/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60360,69265,62793,Probation,Cadeau,Rodeline,NULL,Female,African-American,10/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +60360,69265,62793,Probation,Cadeau,Rodeline,NULL,Female,African-American,10/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +60360,69265,62793,Probation,Cadeau,Rodeline,NULL,Female,African-American,10/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60382,69294,62817,Probation,OLMINO,JOSEPH,NULL,Male,Caucasian,10/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +60382,69294,62817,Probation,OLMINO,JOSEPH,NULL,Male,Caucasian,10/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +60382,69294,62817,Probation,OLMINO,JOSEPH,NULL,Male,Caucasian,10/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60369,69281,62806,Probation,Ramirez,Gerardo,NULL,Male,Hispanic,01/12/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +60369,69281,62806,Probation,Ramirez,Gerardo,NULL,Male,Hispanic,01/12/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +60369,69281,62806,Probation,Ramirez,Gerardo,NULL,Male,Hispanic,01/12/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60384,69296,62819,PRETRIAL,Harper,Adrian,NULL,Female,Caucasian,02/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +60384,69296,62819,PRETRIAL,Harper,Adrian,NULL,Female,Caucasian,02/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +60384,69296,62819,PRETRIAL,Harper,Adrian,NULL,Female,Caucasian,02/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60355,69260,62788,PRETRIAL,Davis,Rabecca,Dernel,Female,African-American,05/11/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +60355,69260,62788,PRETRIAL,Davis,Rabecca,Dernel,Female,African-American,05/11/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +60355,69260,62788,PRETRIAL,Davis,Rabecca,Dernel,Female,African-American,05/11/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +60374,69289,62813,Probation,Perez,Isidro,NULL,Male,Hispanic,08/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/13/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +60374,69289,62813,Probation,Perez,Isidro,NULL,Male,Hispanic,08/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/13/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +60374,69289,62813,Probation,Perez,Isidro,NULL,Male,Hispanic,08/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60362,69268,62796,PRETRIAL,Martinelli,John,Mauro,Male,Caucasian,09/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +60362,69268,62796,PRETRIAL,Martinelli,John,Mauro,Male,Caucasian,09/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +60362,69268,62796,PRETRIAL,Martinelli,John,Mauro,Male,Caucasian,09/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60350,69254,62782,PRETRIAL,WELLS,ANTHONY,KEITH,Male,African-American,09/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +60350,69254,62782,PRETRIAL,WELLS,ANTHONY,KEITH,Male,African-American,09/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +60350,69254,62782,PRETRIAL,WELLS,ANTHONY,KEITH,Male,African-American,09/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60373,69288,62812,Probation,perry,maria,NULL,Female,Caucasian,09/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +60373,69288,62812,Probation,perry,maria,NULL,Female,Caucasian,09/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +60373,69288,62812,Probation,perry,maria,NULL,Female,Caucasian,09/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +28258,69275,62801,PRETRIAL,Mcfadden,John,NULL,Male,African-American,01/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +28258,69275,62801,PRETRIAL,Mcfadden,John,NULL,Male,African-American,01/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +28258,69275,62801,PRETRIAL,Mcfadden,John,NULL,Male,African-American,01/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +60372,69284,62809,Probation,Young,Michael,NULL,Male,Caucasian,04/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +60372,69284,62809,Probation,Young,Michael,NULL,Male,Caucasian,04/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +60372,69284,62809,Probation,Young,Michael,NULL,Male,Caucasian,04/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60354,69258,62786,PRETRIAL,Sylvestre,kaylin,NULL,Male,African-American,11/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +60354,69258,62786,PRETRIAL,Sylvestre,kaylin,NULL,Male,African-American,11/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +60354,69258,62786,PRETRIAL,Sylvestre,kaylin,NULL,Male,African-American,11/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60367,69279,62804,Probation,BRADSHAW,DOUGLAS,NULL,Male,African-American,08/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +60367,69279,62804,Probation,BRADSHAW,DOUGLAS,NULL,Male,African-American,08/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +60367,69279,62804,Probation,BRADSHAW,DOUGLAS,NULL,Male,African-American,08/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60346,69249,62777,PRETRIAL,CODY,WILLIAM,F,Male,Caucasian,11/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +60346,69249,62777,PRETRIAL,CODY,WILLIAM,F,Male,Caucasian,11/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +60346,69249,62777,PRETRIAL,CODY,WILLIAM,F,Male,Caucasian,11/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60358,69263,62791,Probation,figueroa,kenneth,NULL,Male,Hispanic,02/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.59,2,Low,New,1,0 +60358,69263,62791,Probation,figueroa,kenneth,NULL,Male,Hispanic,02/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,New,1,0 +60358,69263,62791,Probation,figueroa,kenneth,NULL,Male,Hispanic,02/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60375,69291,62814,Probation,papp,robert,NULL,Male,Caucasian,10/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.74,2,Low,New,1,0 +60375,69291,62814,Probation,papp,robert,NULL,Male,Caucasian,10/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +60375,69291,62814,Probation,papp,robert,NULL,Male,Caucasian,10/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60381,69293,62816,Probation,Flaks,Mayer,NULL,Male,Caucasian,12/23/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/13/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +60381,69293,62816,Probation,Flaks,Mayer,NULL,Male,Caucasian,12/23/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/13/14 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +60381,69293,62816,Probation,Flaks,Mayer,NULL,Male,Caucasian,12/23/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60388,69300,62823,Probation,dattero,nicolas,NULL,Male,Hispanic,04/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +60388,69300,62823,Probation,dattero,nicolas,NULL,Male,Hispanic,04/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +60388,69300,62823,Probation,dattero,nicolas,NULL,Male,Hispanic,04/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +27887,69270,62798,Probation,baldinger,bradley,NULL,Male,Caucasian,04/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +27887,69270,62798,Probation,baldinger,bradley,NULL,Male,Caucasian,04/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +27887,69270,62798,Probation,baldinger,bradley,NULL,Male,Caucasian,04/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60364,69272,62799,Probation,Allen,Mark,Bryan,Male,Caucasian,12/31/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +60364,69272,62799,Probation,Allen,Mark,Bryan,Male,Caucasian,12/31/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +60364,69272,62799,Probation,Allen,Mark,Bryan,Male,Caucasian,12/31/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +46544,69253,62781,PRETRIAL,McConn,Kim,NULL,Male,African-American,03/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +46544,69253,62781,PRETRIAL,McConn,Kim,NULL,Male,African-American,03/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +46544,69253,62781,PRETRIAL,McConn,Kim,NULL,Male,African-American,03/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59019,69287,61281,Probation,Davis,Reginald,NULL,Male,African-American,08/13/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,Copy,1,0 +59019,69287,61281,Probation,Davis,Reginald,NULL,Male,African-American,08/13/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,Copy,1,0 +59019,69287,61281,Probation,Davis,Reginald,NULL,Male,African-American,08/13/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +60353,69259,62787,PRETRIAL,MARTIN,MATTHEW,NULL,Male,Caucasian,07/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,New,1,0 +60353,69259,62787,PRETRIAL,MARTIN,MATTHEW,NULL,Male,Caucasian,07/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +60353,69259,62787,PRETRIAL,MARTIN,MATTHEW,NULL,Male,Caucasian,07/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60361,69266,62794,Probation,Rosenkranz,Scott,Andrew,Male,Caucasian,06/27/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +60361,69266,62794,Probation,Rosenkranz,Scott,Andrew,Male,Caucasian,06/27/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +60361,69266,62794,Probation,Rosenkranz,Scott,Andrew,Male,Caucasian,06/27/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60383,69295,62818,PRETRIAL,STEIN,JOSHUA,TODD,Male,Caucasian,11/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +60383,69295,62818,PRETRIAL,STEIN,JOSHUA,TODD,Male,Caucasian,11/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +60383,69295,62818,PRETRIAL,STEIN,JOSHUA,TODD,Male,Caucasian,11/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60365,69274,62800,PRETRIAL,Kim,Brian,NULL,Male,Asian,02/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +60365,69274,62800,PRETRIAL,Kim,Brian,NULL,Male,Asian,02/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +60365,69274,62800,PRETRIAL,Kim,Brian,NULL,Male,Asian,02/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60348,69251,62779,PRETRIAL,Gonzalez,Dominique,NULL,Female,Hispanic,06/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +60348,69251,62779,PRETRIAL,Gonzalez,Dominique,NULL,Female,Hispanic,06/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +60348,69251,62779,PRETRIAL,Gonzalez,Dominique,NULL,Female,Hispanic,06/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60345,69248,62776,PRETRIAL,NUNEZ,DAPHNE,R,Female,Caucasian,07/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +60345,69248,62776,PRETRIAL,NUNEZ,DAPHNE,R,Female,Caucasian,07/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +60345,69248,62776,PRETRIAL,NUNEZ,DAPHNE,R,Female,Caucasian,07/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60356,69261,62789,PRETRIAL,BLAKEGOODWIN,LATASHA,M,Female,African-American,11/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +60356,69261,62789,PRETRIAL,BLAKEGOODWIN,LATASHA,M,Female,African-American,11/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +60356,69261,62789,PRETRIAL,BLAKEGOODWIN,LATASHA,M,Female,African-American,11/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +60386,69298,62821,Probation,Stevens,Benjamin,Fredric,Male,Caucasian,10/30/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +60386,69298,62821,Probation,Stevens,Benjamin,Fredric,Male,Caucasian,10/30/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +60386,69298,62821,Probation,Stevens,Benjamin,Fredric,Male,Caucasian,10/30/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59722,69277,62085,PRETRIAL,Kumar,Anisa,NULL,Female,Other,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,Copy,1,0 +59722,69277,62085,PRETRIAL,Kumar,Anisa,NULL,Female,Other,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,Copy,1,0 +59722,69277,62085,PRETRIAL,Kumar,Anisa,NULL,Female,Other,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +60370,69282,62807,Probation,george,adrian,NULL,Male,Caucasian,07/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +60370,69282,62807,Probation,george,adrian,NULL,Male,Caucasian,07/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +60370,69282,62807,Probation,george,adrian,NULL,Male,Caucasian,07/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60352,69256,62784,PRETRIAL,Louidor,Carmelle,NULL,Female,African-American,03/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +60352,69256,62784,PRETRIAL,Louidor,Carmelle,NULL,Female,African-American,03/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +60352,69256,62784,PRETRIAL,Louidor,Carmelle,NULL,Female,African-American,03/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/13/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60418,69337,62859,Probation,LY,VAN,CHI,Male,Asian,08/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +60418,69337,62859,Probation,LY,VAN,CHI,Male,Asian,08/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +60418,69337,62859,Probation,LY,VAN,CHI,Male,Asian,08/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60400,69316,62839,PRETRIAL,Smith,Isaac,NULL,Male,African-American,05/09/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/14 0:00,2,Medium,7,Risk of Violence,-3.13,1,Low,New,1,0 +60400,69316,62839,PRETRIAL,Smith,Isaac,NULL,Male,African-American,05/09/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +60400,69316,62839,PRETRIAL,Smith,Isaac,NULL,Male,African-American,05/09/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60396,69311,62834,PRETRIAL,Gregory,Winston,NULL,Male,Other,10/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +60396,69311,62834,PRETRIAL,Gregory,Winston,NULL,Male,Other,10/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/14 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +60396,69311,62834,PRETRIAL,Gregory,Winston,NULL,Male,Other,10/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60412,69329,62852,Probation,Hoffman,Theodore,NULL,Male,Caucasian,05/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +60412,69329,62852,Probation,Hoffman,Theodore,NULL,Male,Caucasian,05/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +60412,69329,62852,Probation,Hoffman,Theodore,NULL,Male,Caucasian,05/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60393,69308,62831,PRETRIAL,Rahman,Shourav,NULL,Male,Other,01/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +60393,69308,62831,PRETRIAL,Rahman,Shourav,NULL,Male,Other,01/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +60393,69308,62831,PRETRIAL,Rahman,Shourav,NULL,Male,Other,01/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60402,69319,62842,Probation,Willford,Rashaad,NULL,Male,African-American,10/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +60402,69319,62842,Probation,Willford,Rashaad,NULL,Male,African-American,10/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +60402,69319,62842,Probation,Willford,Rashaad,NULL,Male,African-American,10/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +60407,69324,62847,Probation,Rego,Priscila,NULL,Female,Hispanic,10/28/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/14/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +60407,69324,62847,Probation,Rego,Priscila,NULL,Female,Hispanic,10/28/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,New,1,0 +60407,69324,62847,Probation,Rego,Priscila,NULL,Female,Hispanic,10/28/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/14/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60415,69332,62855,Probation,Boone,Jasmine,NULL,Female,African-American,12/28/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,New,1,0 +60415,69332,62855,Probation,Boone,Jasmine,NULL,Female,African-American,12/28/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +60415,69332,62855,Probation,Boone,Jasmine,NULL,Female,African-American,12/28/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60421,69340,62862,Probation,Zalman,William,NULL,Male,Caucasian,09/20/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/14/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +60421,69340,62862,Probation,Zalman,William,NULL,Male,Caucasian,09/20/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +60421,69340,62862,Probation,Zalman,William,NULL,Male,Caucasian,09/20/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60404,69321,62844,Probation,Brown,Andrew,NULL,Male,African-American,04/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +60404,69321,62844,Probation,Brown,Andrew,NULL,Male,African-American,04/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +60404,69321,62844,Probation,Brown,Andrew,NULL,Male,African-American,04/20/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60398,69314,62837,Probation,Harris,Elisia,J,Female,African-American,07/11/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/14/14 0:00,2,Medium,7,Risk of Violence,-2.74,2,Low,New,1,0 +60398,69314,62837,Probation,Harris,Elisia,J,Female,African-American,07/11/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +60398,69314,62837,Probation,Harris,Elisia,J,Female,African-American,07/11/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/14/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60411,69328,62851,PRETRIAL,Brown,Seymour,NULL,Male,African-American,04/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +60411,69328,62851,PRETRIAL,Brown,Seymour,NULL,Male,African-American,04/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +60411,69328,62851,PRETRIAL,Brown,Seymour,NULL,Male,African-American,04/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60416,69335,62857,Probation,gagnon,Keith,NULL,Male,Caucasian,08/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/14/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +60416,69335,62857,Probation,gagnon,Keith,NULL,Male,Caucasian,08/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/14/14 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +60416,69335,62857,Probation,gagnon,Keith,NULL,Male,Caucasian,08/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60413,69330,62853,Probation,GONZALEZ,ALEXANDER,F,Male,Hispanic,04/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +60413,69330,62853,Probation,GONZALEZ,ALEXANDER,F,Male,Hispanic,04/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +60413,69330,62853,Probation,GONZALEZ,ALEXANDER,F,Male,Hispanic,04/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60409,69326,62849,Probation,Andrews,Robert,NULL,Male,Caucasian,03/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +60409,69326,62849,Probation,Andrews,Robert,NULL,Male,Caucasian,03/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +60409,69326,62849,Probation,Andrews,Robert,NULL,Male,Caucasian,03/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60394,69309,62832,PRETRIAL,Algur,Teoman,NULL,Male,Caucasian,07/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +60394,69309,62832,PRETRIAL,Algur,Teoman,NULL,Male,Caucasian,07/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +60394,69309,62832,PRETRIAL,Algur,Teoman,NULL,Male,Caucasian,07/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +22959,69305,62828,PRETRIAL,LACROIX,JASON,NULL,Male,African-American,01/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +22959,69305,62828,PRETRIAL,LACROIX,JASON,NULL,Male,African-American,01/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +22959,69305,62828,PRETRIAL,LACROIX,JASON,NULL,Male,African-American,01/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60390,69302,62825,PRETRIAL,Gonzolaz,Juan,Carlos,Male,Caucasian,06/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +60390,69302,62825,PRETRIAL,Gonzolaz,Juan,Carlos,Male,Caucasian,06/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +60390,69302,62825,PRETRIAL,Gonzolaz,Juan,Carlos,Male,Caucasian,06/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60408,69325,62848,PRETRIAL,martin,sean,NULL,Male,African-American,10/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +60408,69325,62848,PRETRIAL,martin,sean,NULL,Male,African-American,10/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +60408,69325,62848,PRETRIAL,martin,sean,NULL,Male,African-American,10/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60391,69304,62827,PRETRIAL,Williams,Janel,NULL,Male,African-American,07/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +60391,69304,62827,PRETRIAL,Williams,Janel,NULL,Male,African-American,07/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +60391,69304,62827,PRETRIAL,Williams,Janel,NULL,Male,African-American,07/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60406,69323,62846,Probation,Crozier,Carleron,NULL,Male,Caucasian,08/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +60406,69323,62846,Probation,Crozier,Carleron,NULL,Male,Caucasian,08/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +60406,69323,62846,Probation,Crozier,Carleron,NULL,Male,Caucasian,08/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60419,69338,62860,Broward County,Joseph,Kendrick,NULL,Male,African-American,01/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,4,High,7,Risk of Violence,-0.76,9,High,New,1,0 +60419,69338,62860,Broward County,Joseph,Kendrick,NULL,Male,African-American,01/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,4,High,8,Risk of Recidivism,0.86,10,High,New,1,0 +60419,69338,62860,Broward County,Joseph,Kendrick,NULL,Male,African-American,01/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +60395,69310,62833,PRETRIAL,Long,Michael,NULL,Male,African-American,04/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +60395,69310,62833,PRETRIAL,Long,Michael,NULL,Male,African-American,04/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +60395,69310,62833,PRETRIAL,Long,Michael,NULL,Male,African-American,04/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52673,69317,62840,PRETRIAL,Mora,Michael,Steven,Male,Hispanic,01/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +52673,69317,62840,PRETRIAL,Mora,Michael,Steven,Male,Hispanic,01/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +52673,69317,62840,PRETRIAL,Mora,Michael,Steven,Male,Hispanic,01/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60414,69331,62854,Broward County,Dukes,Vicent,NULL,Male,African-American,09/25/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.41,3,Low,New,1,0 +60414,69331,62854,Broward County,Dukes,Vicent,NULL,Male,African-American,09/25/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +60414,69331,62854,Broward County,Dukes,Vicent,NULL,Male,African-American,09/25/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +60399,69315,62838,Probation,Winslow,Brandon,NULL,Male,Caucasian,06/28/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +60399,69315,62838,Probation,Winslow,Brandon,NULL,Male,Caucasian,06/28/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +60399,69315,62838,Probation,Winslow,Brandon,NULL,Male,Caucasian,06/28/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +47048,69333,62856,PRETRIAL,CABRAL,RONNA,NULL,Female,Caucasian,01/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/14/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +47048,69333,62856,PRETRIAL,CABRAL,RONNA,NULL,Female,Caucasian,01/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/14/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +47048,69333,62856,PRETRIAL,CABRAL,RONNA,NULL,Female,Caucasian,01/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60397,69312,62835,PRETRIAL,Holston,Jeffery,NULL,Male,African-American,06/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +60397,69312,62835,PRETRIAL,Holston,Jeffery,NULL,Male,African-American,06/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +60397,69312,62835,PRETRIAL,Holston,Jeffery,NULL,Male,African-American,06/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60392,69307,62830,PRETRIAL,James,Stephen,NULL,Male,African-American,11/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +60392,69307,62830,PRETRIAL,James,Stephen,NULL,Male,African-American,11/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +60392,69307,62830,PRETRIAL,James,Stephen,NULL,Male,African-American,11/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +25425,69313,62836,PRETRIAL,Spurgeon,Lawrence,NULL,Male,African-American,01/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +25425,69313,62836,PRETRIAL,Spurgeon,Lawrence,NULL,Male,African-American,01/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,4,High,8,Risk of Recidivism,1.11,10,High,New,1,0 +25425,69313,62836,PRETRIAL,Spurgeon,Lawrence,NULL,Male,African-American,01/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,4,High,18,Risk of Failure to Appear,38,10,High,New,1,0 +60410,69327,62850,PRETRIAL,PHETAKOUNE,BARBARA,NULL,Female,Caucasian,10/29/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/14/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +60410,69327,62850,PRETRIAL,PHETAKOUNE,BARBARA,NULL,Female,Caucasian,10/29/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/14/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +60410,69327,62850,PRETRIAL,PHETAKOUNE,BARBARA,NULL,Female,Caucasian,10/29/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59564,69334,61916,PRETRIAL,PHILLIPS,STACY,NULL,Female,Caucasian,04/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,Copy,1,0 +59564,69334,61916,PRETRIAL,PHILLIPS,STACY,NULL,Female,Caucasian,04/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,Copy,1,0 +59564,69334,61916,PRETRIAL,PHILLIPS,STACY,NULL,Female,Caucasian,04/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,29,9,High,Copy,1,0 +56995,69306,62829,PRETRIAL,Lane,Marcus,NULL,Male,African-American,03/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +56995,69306,62829,PRETRIAL,Lane,Marcus,NULL,Male,African-American,03/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +56995,69306,62829,PRETRIAL,Lane,Marcus,NULL,Male,African-American,03/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60417,69336,62858,PRETRIAL,hayes,david,NULL,Male,Caucasian,08/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.96,5,Medium,New,1,0 +60417,69336,62858,PRETRIAL,hayes,david,NULL,Male,Caucasian,08/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +60417,69336,62858,PRETRIAL,hayes,david,NULL,Male,Caucasian,08/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60405,69322,62845,PRETRIAL,mcclam,marvin,NULL,Male,African-American,01/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,New,1,0 +60405,69322,62845,PRETRIAL,mcclam,marvin,NULL,Male,African-American,01/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +60405,69322,62845,PRETRIAL,mcclam,marvin,NULL,Male,African-American,01/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +60420,69339,62861,PRETRIAL,Lutar,Roger,NULL,Male,Caucasian,06/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/14 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +60420,69339,62861,PRETRIAL,Lutar,Roger,NULL,Male,Caucasian,06/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +60420,69339,62861,PRETRIAL,Lutar,Roger,NULL,Male,Caucasian,06/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/14/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60401,69318,62841,Probation,Hodgins,Joanna,Marie,Female,Caucasian,01/29/88,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/14/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +60401,69318,62841,Probation,Hodgins,Joanna,Marie,Female,Caucasian,01/29/88,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/14/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +60401,69318,62841,Probation,Hodgins,Joanna,Marie,Female,Caucasian,01/29/88,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60423,69343,62865,PRETRIAL,GORHAM,KENNETH,ALEXANDER,Male,African-American,09/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.72,2,Low,New,1,0 +60423,69343,62865,PRETRIAL,GORHAM,KENNETH,ALEXANDER,Male,African-American,09/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,New,1,0 +60423,69343,62865,PRETRIAL,GORHAM,KENNETH,ALEXANDER,Male,African-American,09/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60430,69352,62871,Probation,McCormack,Brian,NULL,Male,Caucasian,04/06/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +60430,69352,62871,Probation,McCormack,Brian,NULL,Male,Caucasian,04/06/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +60430,69352,62871,Probation,McCormack,Brian,NULL,Male,Caucasian,04/06/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60443,69369,62886,DRRD,Patrick,Shane,Kirk,Male,African-American,03/15/92,17,All Scales,Intake,English,Probation Violator,Probation,Single,1/15/14 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +60443,69369,62886,DRRD,Patrick,Shane,Kirk,Male,African-American,03/15/92,17,All Scales,Intake,English,Probation Violator,Probation,Single,1/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,5,Medium,New,1,0 +60443,69369,62886,DRRD,Patrick,Shane,Kirk,Male,African-American,03/15/92,17,All Scales,Intake,English,Probation Violator,Probation,Single,1/15/14 0:00,2,Medium,18,Risk of Failure to Appear,23,4,Low,New,1,0 +60426,69348,62868,PRETRIAL,Watts,Gary,Alexander,Male,African-American,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,4,High,7,Risk of Violence,-0.7,9,High,New,1,0 +60426,69348,62868,PRETRIAL,Watts,Gary,Alexander,Male,African-American,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,4,High,8,Risk of Recidivism,0.74,10,High,New,1,0 +60426,69348,62868,PRETRIAL,Watts,Gary,Alexander,Male,African-American,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60433,69355,62874,Probation,pierre,jessy,NULL,Male,African-American,09/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +60433,69355,62874,Probation,pierre,jessy,NULL,Male,African-American,09/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +60433,69355,62874,Probation,pierre,jessy,NULL,Male,African-American,09/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60434,69357,62875,Probation,Ingram,Anthony,NULL,Male,African-American,09/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +60434,69357,62875,Probation,Ingram,Anthony,NULL,Male,African-American,09/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +60434,69357,62875,Probation,Ingram,Anthony,NULL,Male,African-American,09/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60439,69364,62881,PRETRIAL,RUGGIERO,MARK,NULL,Male,Caucasian,07/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +60439,69364,62881,PRETRIAL,RUGGIERO,MARK,NULL,Male,Caucasian,07/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +60439,69364,62881,PRETRIAL,RUGGIERO,MARK,NULL,Male,Caucasian,07/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60422,69341,62863,PRETRIAL,McCrea,Michael,NULL,Male,African-American,01/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.88,2,Low,New,1,0 +60422,69341,62863,PRETRIAL,McCrea,Michael,NULL,Male,African-American,01/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +60422,69341,62863,PRETRIAL,McCrea,Michael,NULL,Male,African-American,01/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +60432,69354,62873,Probation,Hasnali,Rajesh,Vikki,Male,Other,03/05/88,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/15/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +60432,69354,62873,Probation,Hasnali,Rajesh,Vikki,Male,Other,03/05/88,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/15/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +60432,69354,62873,Probation,Hasnali,Rajesh,Vikki,Male,Other,03/05/88,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +35653,38087,34879,PRETRIAL,Robinson,Stephen,A,Male,African-American,03/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +35653,38087,34879,PRETRIAL,Robinson,Stephen,A,Male,African-American,03/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +35653,38087,34879,PRETRIAL,Robinson,Stephen,A,Male,African-American,03/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60438,69362,62880,Probation,Abel,Reynold,NULL,Male,African-American,06/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +60438,69362,62880,Probation,Abel,Reynold,NULL,Male,African-American,06/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +60438,69362,62880,Probation,Abel,Reynold,NULL,Male,African-American,06/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60425,69346,62867,PRETRIAL,Lee,Dewayne,Ingraham,Male,African-American,02/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +60425,69346,62867,PRETRIAL,Lee,Dewayne,Ingraham,Male,African-American,02/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +60425,69346,62867,PRETRIAL,Lee,Dewayne,Ingraham,Male,African-American,02/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60435,69359,62877,Probation,Rivera,Saira,NULL,Female,Hispanic,04/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,2,Medium,7,Risk of Violence,-2.85,2,Low,New,1,0 +60435,69359,62877,Probation,Rivera,Saira,NULL,Female,Hispanic,04/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +60435,69359,62877,Probation,Rivera,Saira,NULL,Female,Hispanic,04/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +38456,69356,37900,PRETRIAL,Jimenez,Brandon,NULL,Male,Caucasian,05/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/15/14 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,Copy,1,0 +38456,69356,37900,PRETRIAL,Jimenez,Brandon,NULL,Male,Caucasian,05/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,Copy,1,0 +38456,69356,37900,PRETRIAL,Jimenez,Brandon,NULL,Male,Caucasian,05/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/15/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +51415,69344,61743,PRETRIAL,Hamilton,Alfonso,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,Copy,1,0 +51415,69344,61743,PRETRIAL,Hamilton,Alfonso,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,Copy,1,0 +51415,69344,61743,PRETRIAL,Hamilton,Alfonso,NULL,Male,Hispanic,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +59809,69351,62172,PRETRIAL,MORRIS,MINDY,NULL,Female,Caucasian,08/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,Copy,1,0 +59809,69351,62172,PRETRIAL,MORRIS,MINDY,NULL,Female,Caucasian,08/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,9,High,Copy,1,0 +59809,69351,62172,PRETRIAL,MORRIS,MINDY,NULL,Female,Caucasian,08/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +57288,69347,59379,PRETRIAL,Lewis,Tereatha,NULL,Male,African-American,02/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,Copy,1,0 +57288,69347,59379,PRETRIAL,Lewis,Tereatha,NULL,Male,African-American,02/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,Copy,1,0 +57288,69347,59379,PRETRIAL,Lewis,Tereatha,NULL,Male,African-American,02/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +49472,69361,62879,Probation,villafane,david,NULL,Male,Caucasian,04/04/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +49472,69361,62879,Probation,villafane,david,NULL,Male,Caucasian,04/04/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +49472,69361,62879,Probation,villafane,david,NULL,Male,Caucasian,04/04/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +46835,69342,62864,PRETRIAL,Frazier,Patrick,NULL,Male,African-American,01/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,4,High,7,Risk of Violence,-0.68,9,High,New,1,0 +46835,69342,62864,PRETRIAL,Frazier,Patrick,NULL,Male,African-American,01/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,4,High,8,Risk of Recidivism,0.42,9,High,New,1,0 +46835,69342,62864,PRETRIAL,Frazier,Patrick,NULL,Male,African-American,01/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60428,69349,62869,PRETRIAL,Sibblis,Kenttrell,NULL,Female,African-American,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +60428,69349,62869,PRETRIAL,Sibblis,Kenttrell,NULL,Female,African-American,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/14 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +60428,69349,62869,PRETRIAL,Sibblis,Kenttrell,NULL,Female,African-American,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60431,69353,62872,Probation,Hoff,Joseoh,NULL,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +60431,69353,62872,Probation,Hoff,Joseoh,NULL,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +60431,69353,62872,Probation,Hoff,Joseoh,NULL,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60442,69368,62885,Probation,Finnikin,Trisha,antonette,Female,African-American,09/21/81,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/15/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +60442,69368,62885,Probation,Finnikin,Trisha,antonette,Female,African-American,09/21/81,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/15/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +60442,69368,62885,Probation,Finnikin,Trisha,antonette,Female,African-American,09/21/81,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60437,69360,62878,PRETRIAL,ROSS,ROBERT,ANDREW,Male,Caucasian,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +60437,69360,62878,PRETRIAL,ROSS,ROBERT,ANDREW,Male,Caucasian,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +60437,69360,62878,PRETRIAL,ROSS,ROBERT,ANDREW,Male,Caucasian,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60424,69345,62866,PRETRIAL,Uersel,John,NULL,Male,Caucasian,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +60424,69345,62866,PRETRIAL,Uersel,John,NULL,Male,Caucasian,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +60424,69345,62866,PRETRIAL,Uersel,John,NULL,Male,Caucasian,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60436,69358,62876,PRETRIAL,Joseph,Raymond,NULL,Male,African-American,02/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +60436,69358,62876,PRETRIAL,Joseph,Raymond,NULL,Male,African-American,02/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +60436,69358,62876,PRETRIAL,Joseph,Raymond,NULL,Male,African-American,02/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60429,69350,62870,Probation,Inchaustegui,Astrid,NULL,Female,Hispanic,07/07/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/15/14 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +60429,69350,62870,Probation,Inchaustegui,Astrid,NULL,Female,Hispanic,07/07/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/15/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +60429,69350,62870,Probation,Inchaustegui,Astrid,NULL,Female,Hispanic,07/07/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60458,69384,62901,PRETRIAL,HENRY,DELROY,NULL,Male,African-American,07/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +60458,69384,62901,PRETRIAL,HENRY,DELROY,NULL,Male,African-American,07/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +60458,69384,62901,PRETRIAL,HENRY,DELROY,NULL,Male,African-American,07/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60445,69371,62888,PRETRIAL,Vazquez,Jennifer,NULL,Female,Caucasian,06/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +60445,69371,62888,PRETRIAL,Vazquez,Jennifer,NULL,Female,Caucasian,06/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +60445,69371,62888,PRETRIAL,Vazquez,Jennifer,NULL,Female,Caucasian,06/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +9579,69405,62921,PRETRIAL,SCUTT,ENRICO,GEDEON,Male,Other,04/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +9579,69405,62921,PRETRIAL,SCUTT,ENRICO,GEDEON,Male,Other,04/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +9579,69405,62921,PRETRIAL,SCUTT,ENRICO,GEDEON,Male,Other,04/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60450,69376,62893,PRETRIAL,COOMBS,SHANE,DWABENHE,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +60450,69376,62893,PRETRIAL,COOMBS,SHANE,DWABENHE,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +60450,69376,62893,PRETRIAL,COOMBS,SHANE,DWABENHE,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60453,69379,62896,Probation,Stephenson,Derrick,NULL,Male,African-American,03/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +60453,69379,62896,Probation,Stephenson,Derrick,NULL,Male,African-American,03/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +60453,69379,62896,Probation,Stephenson,Derrick,NULL,Male,African-American,03/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54856,69397,62913,Probation,maldonado,milagros,NULL,Female,Hispanic,03/25/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +54856,69397,62913,Probation,maldonado,milagros,NULL,Female,Hispanic,03/25/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +54856,69397,62913,Probation,maldonado,milagros,NULL,Female,Hispanic,03/25/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +60454,69381,62898,PRETRIAL,Horton,Gregory,NULL,Male,African-American,08/01/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/16/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +60454,69381,62898,PRETRIAL,Horton,Gregory,NULL,Male,African-American,08/01/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/16/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +60454,69381,62898,PRETRIAL,Horton,Gregory,NULL,Male,African-American,08/01/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60468,69395,62911,Probation,Pena,Rafael,NULL,Male,Hispanic,09/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.57,2,Low,New,1,0 +60468,69395,62911,Probation,Pena,Rafael,NULL,Male,Hispanic,09/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +60468,69395,62911,Probation,Pena,Rafael,NULL,Male,Hispanic,09/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60448,69374,62891,PRETRIAL,Brown,Cynthia,Veronica,Female,African-American,12/20/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +60448,69374,62891,PRETRIAL,Brown,Cynthia,Veronica,Female,African-American,12/20/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +60448,69374,62891,PRETRIAL,Brown,Cynthia,Veronica,Female,African-American,12/20/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50103,69402,62918,PRETRIAL,Gardner,Shanequa,NULL,Female,African-American,09/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +50103,69402,62918,PRETRIAL,Gardner,Shanequa,NULL,Female,African-American,09/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +50103,69402,62918,PRETRIAL,Gardner,Shanequa,NULL,Female,African-American,09/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60462,69387,62904,Probation,sampedro,katie,NULL,Female,Caucasian,08/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +60462,69387,62904,Probation,sampedro,katie,NULL,Female,Caucasian,08/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +60462,69387,62904,Probation,sampedro,katie,NULL,Female,Caucasian,08/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +48795,69389,49536,PRETRIAL,thomas,lashenta,NULL,Female,African-American,02/23/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +48795,69389,49536,PRETRIAL,thomas,lashenta,NULL,Female,African-American,02/23/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,New,1,0 +48795,69389,49536,PRETRIAL,thomas,lashenta,NULL,Female,African-American,02/23/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +60444,69370,62887,PRETRIAL,West,Justin,NULL,Male,African-American,01/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +60444,69370,62887,PRETRIAL,West,Justin,NULL,Male,African-American,01/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,4,High,8,Risk of Recidivism,0.9,10,High,New,1,0 +60444,69370,62887,PRETRIAL,West,Justin,NULL,Male,African-American,01/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60446,69372,62889,PRETRIAL,Jent,Cara,NULL,Male,Caucasian,06/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +60446,69372,62889,PRETRIAL,Jent,Cara,NULL,Male,Caucasian,06/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +60446,69372,62889,PRETRIAL,Jent,Cara,NULL,Male,Caucasian,06/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60464,69391,62907,Probation,Evans,jacienth,NULL,Female,African-American,08/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +60464,69391,62907,Probation,Evans,jacienth,NULL,Female,African-American,08/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.9,10,High,New,1,0 +60464,69391,62907,Probation,Evans,jacienth,NULL,Female,African-American,08/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60466,69393,62909,PRETRIAL,CICCIO,FRANK,A,Male,Caucasian,12/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/16/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +60466,69393,62909,PRETRIAL,CICCIO,FRANK,A,Male,Caucasian,12/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/16/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +60466,69393,62909,PRETRIAL,CICCIO,FRANK,A,Male,Caucasian,12/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54533,69400,62916,Probation,Romero,Marcos,NULL,Male,Hispanic,06/26/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +54533,69400,62916,Probation,Romero,Marcos,NULL,Male,Hispanic,06/26/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +54533,69400,62916,Probation,Romero,Marcos,NULL,Male,Hispanic,06/26/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60470,69398,62914,Probation,ADAMS,MARC,NULL,Male,African-American,03/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +60470,69398,62914,Probation,ADAMS,MARC,NULL,Male,African-American,03/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +60470,69398,62914,Probation,ADAMS,MARC,NULL,Male,African-American,03/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60460,69386,62903,Probation,Henry,Antonio,NULL,Male,African-American,06/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +60460,69386,62903,Probation,Henry,Antonio,NULL,Male,African-American,06/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +60460,69386,62903,Probation,Henry,Antonio,NULL,Male,African-American,06/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60473,69403,62919,Probation,CABRERA,ANDRES,NULL,Male,Hispanic,02/17/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/16/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +60473,69403,62919,Probation,CABRERA,ANDRES,NULL,Male,Hispanic,02/17/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/16/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +60473,69403,62919,Probation,CABRERA,ANDRES,NULL,Male,Hispanic,02/17/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60456,69382,62899,Probation,Jones,Gregory,NULL,Male,Caucasian,01/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +60456,69382,62899,Probation,Jones,Gregory,NULL,Male,Caucasian,01/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +60456,69382,62899,Probation,Jones,Gregory,NULL,Male,Caucasian,01/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60477,69407,62923,PRETRIAL,Chaparteguy,Rene,NULL,Male,Caucasian,10/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,1/16/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +60477,69407,62923,PRETRIAL,Chaparteguy,Rene,NULL,Male,Caucasian,10/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,1/16/14 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +60477,69407,62923,PRETRIAL,Chaparteguy,Rene,NULL,Male,Caucasian,10/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60476,69404,62920,DRRD,Sainthilaire,Phillip,Martin,Male,African-American,07/30/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,1/16/14 0:00,2,Medium,7,Risk of Violence,-1.39,7,Medium,New,1,0 +60476,69404,62920,DRRD,Sainthilaire,Phillip,Martin,Male,African-American,07/30/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,1/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +60476,69404,62920,DRRD,Sainthilaire,Phillip,Martin,Male,African-American,07/30/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,1/16/14 0:00,2,Medium,18,Risk of Failure to Appear,18,2,Low,New,1,0 +60469,69396,62912,Probation,DAWSON,DARRELL,NULL,Male,African-American,01/05/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,2,Medium,7,Risk of Violence,-3.05,1,Low,New,1,0 +60469,69396,62912,Probation,DAWSON,DARRELL,NULL,Male,African-American,01/05/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +60469,69396,62912,Probation,DAWSON,DARRELL,NULL,Male,African-American,01/05/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +60455,69380,62897,PRETRIAL,Powers,Christine,NULL,Female,Caucasian,09/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +60455,69380,62897,PRETRIAL,Powers,Christine,NULL,Female,Caucasian,09/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-1.62,2,Low,New,1,0 +60455,69380,62897,PRETRIAL,Powers,Christine,NULL,Female,Caucasian,09/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60457,69383,62900,Probation,SANTA,JARET,NULL,Male,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +60457,69383,62900,Probation,SANTA,JARET,NULL,Male,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +60457,69383,62900,Probation,SANTA,JARET,NULL,Male,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60472,69401,62917,Probation,Mareus,Jerry,NULL,Male,African-American,02/24/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +60472,69401,62917,Probation,Mareus,Jerry,NULL,Male,African-American,02/24/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +60472,69401,62917,Probation,Mareus,Jerry,NULL,Male,African-American,02/24/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60461,69388,62905,PRETRIAL,GREEN,TINA,NULL,Male,African-American,09/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +60461,69388,62905,PRETRIAL,GREEN,TINA,NULL,Male,African-American,09/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +60461,69388,62905,PRETRIAL,GREEN,TINA,NULL,Male,African-American,09/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60449,69375,62892,PRETRIAL,Ogbummcnair,Pillar,NULL,Female,African-American,09/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +60449,69375,62892,PRETRIAL,Ogbummcnair,Pillar,NULL,Female,African-American,09/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +60449,69375,62892,PRETRIAL,Ogbummcnair,Pillar,NULL,Female,African-American,09/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60452,69378,62895,PRETRIAL,Brown,Kedra,NULL,Male,African-American,02/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +60452,69378,62895,PRETRIAL,Brown,Kedra,NULL,Male,African-American,02/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +60452,69378,62895,PRETRIAL,Brown,Kedra,NULL,Male,African-American,02/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60459,69385,62902,Probation,Parker,Shanastkei,Akiel,Female,African-American,05/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +60459,69385,62902,Probation,Parker,Shanastkei,Akiel,Female,African-American,05/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +60459,69385,62902,Probation,Parker,Shanastkei,Akiel,Female,African-American,05/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60465,69392,62908,Probation,Jumper,Andre,NULL,Male,Native American,11/30/76,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/16/14 0:00,2,Medium,7,Risk of Violence,-2.83,2,Low,New,1,0 +60465,69392,62908,Probation,Jumper,Andre,NULL,Male,Native American,11/30/76,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +60465,69392,62908,Probation,Jumper,Andre,NULL,Male,Native American,11/30/76,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/16/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +6113,69406,62922,Probation,little,latoya,NULL,Female,African-American,01/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +6113,69406,62922,Probation,little,latoya,NULL,Female,African-American,01/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +6113,69406,62922,Probation,little,latoya,NULL,Female,African-American,01/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +40666,62378,56612,PRETRIAL,PASS,KHALIL,NULL,Male,African-American,01/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,4,High,7,Risk of Violence,-0.57,10,High,New,1,0 +40666,62378,56612,PRETRIAL,PASS,KHALIL,NULL,Male,African-American,01/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,4,High,8,Risk of Recidivism,0.39,9,High,New,1,0 +40666,62378,56612,PRETRIAL,PASS,KHALIL,NULL,Male,African-American,01/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60467,69394,62910,PRETRIAL,BASSARAGH,RYAN,NULL,Male,African-American,03/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +60467,69394,62910,PRETRIAL,BASSARAGH,RYAN,NULL,Male,African-American,03/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +60467,69394,62910,PRETRIAL,BASSARAGH,RYAN,NULL,Male,African-American,03/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60447,69373,62890,PRETRIAL,Opert,Josefa,NULL,Female,Caucasian,01/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +60447,69373,62890,PRETRIAL,Opert,Josefa,NULL,Female,Caucasian,01/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +60447,69373,62890,PRETRIAL,Opert,Josefa,NULL,Female,Caucasian,01/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60463,69390,62906,Probation,McClain,Jennifer,NULL,Female,Caucasian,04/02/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +60463,69390,62906,Probation,McClain,Jennifer,NULL,Female,Caucasian,04/02/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +60463,69390,62906,Probation,McClain,Jennifer,NULL,Female,Caucasian,04/02/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60496,69420,62936,Probation,Kent,Malarie,NULL,Female,African-American,03/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +60496,69420,62936,Probation,Kent,Malarie,NULL,Female,African-American,03/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +60496,69420,62936,Probation,Kent,Malarie,NULL,Female,African-American,03/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60481,69411,62927,PRETRIAL,Lopez,Joseph,Jerome,Male,African-American,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +60481,69411,62927,PRETRIAL,Lopez,Joseph,Jerome,Male,African-American,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +60481,69411,62927,PRETRIAL,Lopez,Joseph,Jerome,Male,African-American,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60491,69415,62931,PRETRIAL,Graulich,Jonathan,NULL,Male,Caucasian,08/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +60491,69415,62931,PRETRIAL,Graulich,Jonathan,NULL,Male,Caucasian,08/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +60491,69415,62931,PRETRIAL,Graulich,Jonathan,NULL,Male,Caucasian,08/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +22543,69429,62945,PRETRIAL,Bakst,Jennifer,NULL,Female,Caucasian,04/25/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/17/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +22543,69429,62945,PRETRIAL,Bakst,Jennifer,NULL,Female,Caucasian,04/25/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +22543,69429,62945,PRETRIAL,Bakst,Jennifer,NULL,Female,Caucasian,04/25/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60503,69427,62943,Probation,Jeanty,Louicius,NULL,Male,Other,02/02/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +60503,69427,62943,Probation,Jeanty,Louicius,NULL,Male,Other,02/02/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +60503,69427,62943,Probation,Jeanty,Louicius,NULL,Male,Other,02/02/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60509,69434,62950,Probation,Cuenca,Ivan,Florencio,Male,Hispanic,07/04/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +60509,69434,62950,Probation,Cuenca,Ivan,Florencio,Male,Hispanic,07/04/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +60509,69434,62950,Probation,Cuenca,Ivan,Florencio,Male,Hispanic,07/04/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60512,69436,62952,Probation,VIRGILE,STANLEY,NULL,Male,African-American,06/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +60512,69436,62952,Probation,VIRGILE,STANLEY,NULL,Male,African-American,06/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +60512,69436,62952,Probation,VIRGILE,STANLEY,NULL,Male,African-American,06/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60483,69413,62929,PRETRIAL,Wagner,Celia,NULL,Female,Caucasian,01/30/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/14 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +60483,69413,62929,PRETRIAL,Wagner,Celia,NULL,Female,Caucasian,01/30/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/14 0:00,1,Low,8,Risk of Recidivism,-2.67,1,Low,New,1,0 +60483,69413,62929,PRETRIAL,Wagner,Celia,NULL,Female,Caucasian,01/30/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60479,69409,62925,PRETRIAL,Campbell,Simone,NULL,Female,African-American,08/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +60479,69409,62925,PRETRIAL,Campbell,Simone,NULL,Female,African-American,08/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +60479,69409,62925,PRETRIAL,Campbell,Simone,NULL,Female,African-American,08/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60518,69443,62959,Probation,pilarte,rafael,NULL,Male,Hispanic,08/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +60518,69443,62959,Probation,pilarte,rafael,NULL,Male,Hispanic,08/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +60518,69443,62959,Probation,pilarte,rafael,NULL,Male,Hispanic,08/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60498,69422,62938,Probation,Defeo,Andrew,NULL,Male,Caucasian,07/14/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/17/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +60498,69422,62938,Probation,Defeo,Andrew,NULL,Male,Caucasian,07/14/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +60498,69422,62938,Probation,Defeo,Andrew,NULL,Male,Caucasian,07/14/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55018,69430,62946,Probation,Perez,Tammy,Lynn,Female,Hispanic,08/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +55018,69430,62946,Probation,Perez,Tammy,Lynn,Female,Hispanic,08/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +55018,69430,62946,Probation,Perez,Tammy,Lynn,Female,Hispanic,08/15/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +9885,69446,62962,PRETRIAL,PETROZZO,MATTHEW,NULL,Male,Caucasian,05/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +9885,69446,62962,PRETRIAL,PETROZZO,MATTHEW,NULL,Male,Caucasian,05/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +9885,69446,62962,PRETRIAL,PETROZZO,MATTHEW,NULL,Male,Caucasian,05/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60493,69417,62933,PRETRIAL,Jones,Ebony,Ennette,Female,African-American,01/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +60493,69417,62933,PRETRIAL,Jones,Ebony,Ennette,Female,African-American,01/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +60493,69417,62933,PRETRIAL,Jones,Ebony,Ennette,Female,African-American,01/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60500,69424,62940,PRETRIAL,TREJOS,GEISON,NULL,Male,Hispanic,02/29/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/14 0:00,4,High,7,Risk of Violence,-0.4,10,High,New,1,0 +60500,69424,62940,PRETRIAL,TREJOS,GEISON,NULL,Male,Hispanic,02/29/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/14 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +60500,69424,62940,PRETRIAL,TREJOS,GEISON,NULL,Male,Hispanic,02/29/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60514,69438,62954,PRETRIAL,MERCOGLIANO,PETER,NULL,Male,Caucasian,11/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +60514,69438,62954,PRETRIAL,MERCOGLIANO,PETER,NULL,Male,Caucasian,11/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +60514,69438,62954,PRETRIAL,MERCOGLIANO,PETER,NULL,Male,Caucasian,11/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60515,69440,62956,Probation,rodriguez,kenneth,NULL,Male,Caucasian,12/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,New,1,0 +60515,69440,62956,Probation,rodriguez,kenneth,NULL,Male,Caucasian,12/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +60515,69440,62956,Probation,rodriguez,kenneth,NULL,Male,Caucasian,12/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60501,69425,62941,Probation,davis,adam,NULL,Male,Caucasian,04/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +60501,69425,62941,Probation,davis,adam,NULL,Male,Caucasian,04/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +60501,69425,62941,Probation,davis,adam,NULL,Male,Caucasian,04/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60508,69432,62948,PRETRIAL,AKINS,DOMINIQUE,NULL,Female,Caucasian,04/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +60508,69432,62948,PRETRIAL,AKINS,DOMINIQUE,NULL,Female,Caucasian,04/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +60508,69432,62948,PRETRIAL,AKINS,DOMINIQUE,NULL,Female,Caucasian,04/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60492,69416,62932,PRETRIAL,Patterson,Krystal,Renee,Female,African-American,05/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +60492,69416,62932,PRETRIAL,Patterson,Krystal,Renee,Female,African-American,05/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +60492,69416,62932,PRETRIAL,Patterson,Krystal,Renee,Female,African-American,05/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60513,69437,62953,Probation,Dvorak,Mirtin,NULL,Male,Caucasian,09/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +60513,69437,62953,Probation,Dvorak,Mirtin,NULL,Male,Caucasian,09/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +60513,69437,62953,Probation,Dvorak,Mirtin,NULL,Male,Caucasian,09/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60482,69412,62928,PRETRIAL,Gish,John,Patrick,Male,Caucasian,04/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +60482,69412,62928,PRETRIAL,Gish,John,Patrick,Male,Caucasian,04/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +60482,69412,62928,PRETRIAL,Gish,John,Patrick,Male,Caucasian,04/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60495,69419,62935,Probation,Cortes-Perez,Raul,NULL,Male,Hispanic,03/02/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +60495,69419,62935,Probation,Cortes-Perez,Raul,NULL,Male,Hispanic,03/02/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +60495,69419,62935,Probation,Cortes-Perez,Raul,NULL,Male,Hispanic,03/02/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60510,69433,62949,PRETRIAL,BLAND,JOHNNY,CORY,Male,Caucasian,04/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +60510,69433,62949,PRETRIAL,BLAND,JOHNNY,CORY,Male,Caucasian,04/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +60510,69433,62949,PRETRIAL,BLAND,JOHNNY,CORY,Male,Caucasian,04/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60497,69421,62937,Probation,powell,jerome,NULL,Male,African-American,03/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +60497,69421,62937,Probation,powell,jerome,NULL,Male,African-American,03/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.82,10,High,New,1,0 +60497,69421,62937,Probation,powell,jerome,NULL,Male,African-American,03/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60511,69435,62951,Probation,phillips,Sheena,NULL,Female,African-American,10/22/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +60511,69435,62951,Probation,phillips,Sheena,NULL,Female,African-American,10/22/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +60511,69435,62951,Probation,phillips,Sheena,NULL,Female,African-American,10/22/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60517,69442,62958,PRETRIAL,Lefebvre,Denise,NULL,Female,Caucasian,09/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +60517,69442,62958,PRETRIAL,Lefebvre,Denise,NULL,Female,Caucasian,09/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +60517,69442,62958,PRETRIAL,Lefebvre,Denise,NULL,Female,Caucasian,09/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,29,9,High,New,1,0 +60490,69414,62930,PRETRIAL,Richards,Radcliffe,NULL,Male,Other,07/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +60490,69414,62930,PRETRIAL,Richards,Radcliffe,NULL,Male,Other,07/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +60490,69414,62930,PRETRIAL,Richards,Radcliffe,NULL,Male,Other,07/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60504,69428,62944,Probation,ALI,AFTAB,NULL,Male,Other,11/26/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +60504,69428,62944,Probation,ALI,AFTAB,NULL,Male,Other,11/26/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +60504,69428,62944,Probation,ALI,AFTAB,NULL,Male,Other,11/26/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60499,69423,62939,Probation,Cancelo,Jeremy,NULL,Male,Hispanic,08/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +60499,69423,62939,Probation,Cancelo,Jeremy,NULL,Male,Hispanic,08/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +60499,69423,62939,Probation,Cancelo,Jeremy,NULL,Male,Hispanic,08/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +60480,69410,62926,PRETRIAL,Brown,Deneen,NULL,Female,African-American,04/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/17/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +60480,69410,62926,PRETRIAL,Brown,Deneen,NULL,Female,African-American,04/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/17/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +60480,69410,62926,PRETRIAL,Brown,Deneen,NULL,Female,African-American,04/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60506,69431,62947,Probation,CORBITT,MORRIS,NULL,Male,Caucasian,08/14/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +60506,69431,62947,Probation,CORBITT,MORRIS,NULL,Male,Caucasian,08/14/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +60506,69431,62947,Probation,CORBITT,MORRIS,NULL,Male,Caucasian,08/14/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60521,69447,62963,Probation,Jeremy,Jamie,NULL,Male,African-American,04/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +60521,69447,62963,Probation,Jeremy,Jamie,NULL,Male,African-American,04/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +60521,69447,62963,Probation,Jeremy,Jamie,NULL,Male,African-American,04/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60502,69426,62942,PRETRIAL,BROOKS,FENAMARIE,NULL,Female,Caucasian,12/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/14 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +60502,69426,62942,PRETRIAL,BROOKS,FENAMARIE,NULL,Female,Caucasian,12/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +60502,69426,62942,PRETRIAL,BROOKS,FENAMARIE,NULL,Female,Caucasian,12/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/17/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60519,69444,62960,Probation,sMITH,jYSIKA,cIERRA,Female,African-American,05/31/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +60519,69444,62960,Probation,sMITH,jYSIKA,cIERRA,Female,African-American,05/31/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +60519,69444,62960,Probation,sMITH,jYSIKA,cIERRA,Female,African-American,05/31/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/17/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +53669,69439,62955,PRETRIAL,Hogan,Allatia,NULL,Male,Caucasian,01/20/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +53669,69439,62955,PRETRIAL,Hogan,Allatia,NULL,Male,Caucasian,01/20/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +53669,69439,62955,PRETRIAL,Hogan,Allatia,NULL,Male,Caucasian,01/20/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60494,69418,62934,PRETRIAL,Walker,Abraham,NULL,Male,African-American,09/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +60494,69418,62934,PRETRIAL,Walker,Abraham,NULL,Male,African-American,09/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +60494,69418,62934,PRETRIAL,Walker,Abraham,NULL,Male,African-American,09/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60525,69452,62968,PRETRIAL,Garzon,Diego,David,Male,Caucasian,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +60525,69452,62968,PRETRIAL,Garzon,Diego,David,Male,Caucasian,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +60525,69452,62968,PRETRIAL,Garzon,Diego,David,Male,Caucasian,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +37792,69449,62965,PRETRIAL,Adams,Steven,Robert,Male,Caucasian,05/29/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +37792,69449,62965,PRETRIAL,Adams,Steven,Robert,Male,Caucasian,05/29/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +37792,69449,62965,PRETRIAL,Adams,Steven,Robert,Male,Caucasian,05/29/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +39432,69454,62970,PRETRIAL,Harvard,Martavis,NULL,Male,Caucasian,11/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +39432,69454,62970,PRETRIAL,Harvard,Martavis,NULL,Male,Caucasian,11/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +39432,69454,62970,PRETRIAL,Harvard,Martavis,NULL,Male,Caucasian,11/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +33064,69453,62969,PRETRIAL,Filossaint,Adeler,NULL,Male,Other,11/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,4,High,7,Risk of Violence,-0.62,10,High,New,1,0 +33064,69453,62969,PRETRIAL,Filossaint,Adeler,NULL,Male,Other,11/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +33064,69453,62969,PRETRIAL,Filossaint,Adeler,NULL,Male,Other,11/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60524,69451,62967,PRETRIAL,ADDERLY,NATHANIEL,NULL,Male,African-American,11/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/18/14 0:00,2,Medium,7,Risk of Violence,-3.06,1,Low,New,1,0 +60524,69451,62967,PRETRIAL,ADDERLY,NATHANIEL,NULL,Male,African-American,11/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +60524,69451,62967,PRETRIAL,ADDERLY,NATHANIEL,NULL,Male,African-American,11/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/18/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60527,69456,62972,PRETRIAL,springer,bond,NULL,Male,Caucasian,06/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +60527,69456,62972,PRETRIAL,springer,bond,NULL,Male,Caucasian,06/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +60527,69456,62972,PRETRIAL,springer,bond,NULL,Male,Caucasian,06/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60523,69450,62966,PRETRIAL,Glover,Steven,NULL,Male,African-American,05/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +60523,69450,62966,PRETRIAL,Glover,Steven,NULL,Male,African-American,05/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +60523,69450,62966,PRETRIAL,Glover,Steven,NULL,Male,African-American,05/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60531,69462,62978,PRETRIAL,POIRIER,SEAN,LEE,Male,Caucasian,10/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,2,Medium,7,Risk of Violence,-1.87,5,Medium,New,1,0 +60531,69462,62978,PRETRIAL,POIRIER,SEAN,LEE,Male,Caucasian,10/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +60531,69462,62978,PRETRIAL,POIRIER,SEAN,LEE,Male,Caucasian,10/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54097,69464,62980,PRETRIAL,May,Jason,NULL,Male,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +54097,69464,62980,PRETRIAL,May,Jason,NULL,Male,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +54097,69464,62980,PRETRIAL,May,Jason,NULL,Male,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +1320,69457,62973,PRETRIAL,KELLY,BRIAN,NULL,Male,Caucasian,05/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,New,1,0 +1320,69457,62973,PRETRIAL,KELLY,BRIAN,NULL,Male,Caucasian,05/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +1320,69457,62973,PRETRIAL,KELLY,BRIAN,NULL,Male,Caucasian,05/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60537,69469,62985,PRETRIAL,Calderon,Milton,NULL,Male,Hispanic,04/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +60537,69469,62985,PRETRIAL,Calderon,Milton,NULL,Male,Hispanic,04/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +60537,69469,62985,PRETRIAL,Calderon,Milton,NULL,Male,Hispanic,04/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +26419,69459,62975,PRETRIAL,Riggins,Andrew,NULL,Male,African-American,02/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +26419,69459,62975,PRETRIAL,Riggins,Andrew,NULL,Male,African-American,02/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +26419,69459,62975,PRETRIAL,Riggins,Andrew,NULL,Male,African-American,02/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60530,69461,62977,PRETRIAL,HANKERSON,JARRETT,K,Male,African-American,08/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +60530,69461,62977,PRETRIAL,HANKERSON,JARRETT,K,Male,African-American,08/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +60530,69461,62977,PRETRIAL,HANKERSON,JARRETT,K,Male,African-American,08/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60533,69466,62982,PRETRIAL,GONZALEZ,VANESSA,NULL,Female,Caucasian,09/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +60533,69466,62982,PRETRIAL,GONZALEZ,VANESSA,NULL,Female,Caucasian,09/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +60533,69466,62982,PRETRIAL,GONZALEZ,VANESSA,NULL,Female,Caucasian,09/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60535,69467,62983,PRETRIAL,MOBLEY,ERIC,NULL,Male,African-American,06/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.07,4,Low,New,1,0 +60535,69467,62983,PRETRIAL,MOBLEY,ERIC,NULL,Male,African-American,06/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +60535,69467,62983,PRETRIAL,MOBLEY,ERIC,NULL,Male,African-American,06/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60528,69458,62974,PRETRIAL,Chance,Travas,NULL,Male,African-American,06/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +60528,69458,62974,PRETRIAL,Chance,Travas,NULL,Male,African-American,06/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +60528,69458,62974,PRETRIAL,Chance,Travas,NULL,Male,African-American,06/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +48595,54175,49297,PRETRIAL,Brantley,Brittany,Yvette,Female,African-American,06/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +48595,54175,49297,PRETRIAL,Brantley,Brittany,Yvette,Female,African-American,06/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,4,High,8,Risk of Recidivism,0.56,10,High,New,1,0 +48595,54175,49297,PRETRIAL,Brantley,Brittany,Yvette,Female,African-American,06/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,4,High,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +60532,69463,62979,PRETRIAL,Gonzalez,Nayley,NULL,Female,Hispanic,08/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +60532,69463,62979,PRETRIAL,Gonzalez,Nayley,NULL,Female,Hispanic,08/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +60532,69463,62979,PRETRIAL,Gonzalez,Nayley,NULL,Female,Hispanic,08/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60534,69465,62981,PRETRIAL,Perron,Charles,NULL,Male,Caucasian,06/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +60534,69465,62981,PRETRIAL,Perron,Charles,NULL,Male,Caucasian,06/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +60534,69465,62981,PRETRIAL,Perron,Charles,NULL,Male,Caucasian,06/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60529,69460,62976,PRETRIAL,HOUSEN,PATRICK,NULL,Male,African-American,09/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +60529,69460,62976,PRETRIAL,HOUSEN,PATRICK,NULL,Male,African-American,09/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +60529,69460,62976,PRETRIAL,HOUSEN,PATRICK,NULL,Male,African-American,09/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60536,69468,62984,PRETRIAL,Gonzalez,Francisco,NULL,Male,Hispanic,06/19/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +60536,69468,62984,PRETRIAL,Gonzalez,Francisco,NULL,Male,Hispanic,06/19/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +60536,69468,62984,PRETRIAL,Gonzalez,Francisco,NULL,Male,Hispanic,06/19/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60541,69473,62988,PRETRIAL,Franum,Francis,Ignatius,Male,Caucasian,09/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +60541,69473,62988,PRETRIAL,Franum,Francis,Ignatius,Male,Caucasian,09/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +60541,69473,62988,PRETRIAL,Franum,Francis,Ignatius,Male,Caucasian,09/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60538,69470,62986,PRETRIAL,Pruett,Jonpaul,NULL,Male,Caucasian,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +60538,69470,62986,PRETRIAL,Pruett,Jonpaul,NULL,Male,Caucasian,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +60538,69470,62986,PRETRIAL,Pruett,Jonpaul,NULL,Male,Caucasian,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +36681,69472,35980,PRETRIAL,Britton,Michael,NULL,Male,Caucasian,01/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,Copy,1,0 +36681,69472,35980,PRETRIAL,Britton,Michael,NULL,Male,Caucasian,01/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,Copy,1,0 +36681,69472,35980,PRETRIAL,Britton,Michael,NULL,Male,Caucasian,01/31/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +60542,69475,62990,PRETRIAL,CLAGETT,JOSEPH,NULL,Male,African-American,04/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +60542,69475,62990,PRETRIAL,CLAGETT,JOSEPH,NULL,Male,African-American,04/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +60542,69475,62990,PRETRIAL,CLAGETT,JOSEPH,NULL,Male,African-American,04/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60540,69474,62989,PRETRIAL,QUIMBY,DALE,NULL,Male,Caucasian,01/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +60540,69474,62989,PRETRIAL,QUIMBY,DALE,NULL,Male,Caucasian,01/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +60540,69474,62989,PRETRIAL,QUIMBY,DALE,NULL,Male,Caucasian,01/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60543,69476,62991,PRETRIAL,Labath,Learby,NULL,Male,African-American,08/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/20/14 0:00,4,High,7,Risk of Violence,0.16,10,High,New,1,0 +60543,69476,62991,PRETRIAL,Labath,Learby,NULL,Male,African-American,08/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/20/14 0:00,4,High,8,Risk of Recidivism,1.44,10,High,New,1,0 +60543,69476,62991,PRETRIAL,Labath,Learby,NULL,Male,African-American,08/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/20/14 0:00,4,High,18,Risk of Failure to Appear,35,10,High,New,1,0 +60539,69471,62987,PRETRIAL,TORGERSON,JAMES,NULL,Male,Caucasian,10/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/20/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +60539,69471,62987,PRETRIAL,TORGERSON,JAMES,NULL,Male,Caucasian,10/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/20/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +60539,69471,62987,PRETRIAL,TORGERSON,JAMES,NULL,Male,Caucasian,10/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +15671,69483,62998,PRETRIAL,ALLEN,JONANA,NULL,Male,African-American,04/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +15671,69483,62998,PRETRIAL,ALLEN,JONANA,NULL,Male,African-American,04/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +15671,69483,62998,PRETRIAL,ALLEN,JONANA,NULL,Male,African-American,04/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +60546,69480,62995,PRETRIAL,Ashley,Bryan,NULL,Male,African-American,08/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +60546,69480,62995,PRETRIAL,Ashley,Bryan,NULL,Male,African-American,08/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +60546,69480,62995,PRETRIAL,Ashley,Bryan,NULL,Male,African-American,08/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60560,69497,63012,Probation,PIERREMICHEL,WILLERMINE,NULL,Male,African-American,04/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +60560,69497,63012,Probation,PIERREMICHEL,WILLERMINE,NULL,Male,African-American,04/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +60560,69497,63012,Probation,PIERREMICHEL,WILLERMINE,NULL,Male,African-American,04/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +45817,69506,63021,Probation,young,leandre,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +45817,69506,63021,Probation,young,leandre,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +45817,69506,63021,Probation,young,leandre,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60544,69478,62993,PRETRIAL,Acosta,Julia,NULL,Female,Hispanic,06/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/21/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +60544,69478,62993,PRETRIAL,Acosta,Julia,NULL,Female,Hispanic,06/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/21/14 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +60544,69478,62993,PRETRIAL,Acosta,Julia,NULL,Female,Hispanic,06/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60549,69485,63000,PRETRIAL,MARSAN,EDWIN,NULL,Male,African-American,08/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +60549,69485,63000,PRETRIAL,MARSAN,EDWIN,NULL,Male,African-American,08/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +60549,69485,63000,PRETRIAL,MARSAN,EDWIN,NULL,Male,African-American,08/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60551,69492,63007,PRETRIAL,Miranda,Rickie,NULL,Male,Caucasian,11/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/21/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +60551,69492,63007,PRETRIAL,Miranda,Rickie,NULL,Male,Caucasian,11/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/21/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +60551,69492,63007,PRETRIAL,Miranda,Rickie,NULL,Male,Caucasian,11/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60561,69499,63014,PRETRIAL,ROBERTS,TYLER,NULL,Male,Caucasian,10/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +60561,69499,63014,PRETRIAL,ROBERTS,TYLER,NULL,Male,Caucasian,10/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +60561,69499,63014,PRETRIAL,ROBERTS,TYLER,NULL,Male,Caucasian,10/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60548,69482,62997,PRETRIAL,yarbough,james,NULL,Male,Caucasian,04/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +60548,69482,62997,PRETRIAL,yarbough,james,NULL,Male,Caucasian,04/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +60548,69482,62997,PRETRIAL,yarbough,james,NULL,Male,Caucasian,04/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +60557,69495,63010,Probation,Durocher,Rouseau,NULL,Male,African-American,07/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +60557,69495,63010,Probation,Durocher,Rouseau,NULL,Male,African-American,07/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +60557,69495,63010,Probation,Durocher,Rouseau,NULL,Male,African-American,07/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60552,69487,63002,PRETRIAL,DERUBEIS,LAWRENCE,NULL,Female,Caucasian,05/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/21/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +60552,69487,63002,PRETRIAL,DERUBEIS,LAWRENCE,NULL,Female,Caucasian,05/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/21/14 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +60552,69487,63002,PRETRIAL,DERUBEIS,LAWRENCE,NULL,Female,Caucasian,05/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60569,69508,63023,Probation,Love,Jeffery,NULL,Male,African-American,11/25/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +60569,69508,63023,Probation,Love,Jeffery,NULL,Male,African-American,11/25/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +60569,69508,63023,Probation,Love,Jeffery,NULL,Male,African-American,11/25/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60559,69498,63013,Probation,Stephens,Rusty,Allen,Male,Caucasian,10/05/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/21/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +60559,69498,63013,Probation,Stephens,Rusty,Allen,Male,Caucasian,10/05/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +60559,69498,63013,Probation,Stephens,Rusty,Allen,Male,Caucasian,10/05/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +12060,69503,63018,Probation,delgado,ricardo,NULL,Male,Hispanic,06/06/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/21/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +12060,69503,63018,Probation,delgado,ricardo,NULL,Male,Hispanic,06/06/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +12060,69503,63018,Probation,delgado,ricardo,NULL,Male,Hispanic,06/06/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +13795,69477,62992,PRETRIAL,Crowley,James,NULL,Male,Caucasian,09/22/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.58,2,Low,New,1,0 +13795,69477,62992,PRETRIAL,Crowley,James,NULL,Male,Caucasian,09/22/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +13795,69477,62992,PRETRIAL,Crowley,James,NULL,Male,Caucasian,09/22/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +50866,69484,62999,PRETRIAL,SCHWAB,GARY,NULL,Male,Caucasian,10/01/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/21/14 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +50866,69484,62999,PRETRIAL,SCHWAB,GARY,NULL,Male,Caucasian,10/01/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/21/14 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +50866,69484,62999,PRETRIAL,SCHWAB,GARY,NULL,Male,Caucasian,10/01/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60570,69509,63024,PRETRIAL,levine,Benjamin,NULL,Male,Caucasian,06/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +60570,69509,63024,PRETRIAL,levine,Benjamin,NULL,Male,Caucasian,06/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +60570,69509,63024,PRETRIAL,levine,Benjamin,NULL,Male,Caucasian,06/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60553,69488,63003,Probation,Serna,Daniel,Santiago,Male,Hispanic,06/20/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/21/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +60553,69488,63003,Probation,Serna,Daniel,Santiago,Male,Hispanic,06/20/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +60553,69488,63003,Probation,Serna,Daniel,Santiago,Male,Hispanic,06/20/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60566,69505,63020,Probation,Robles,Andres,NULL,Male,Hispanic,02/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +60566,69505,63020,Probation,Robles,Andres,NULL,Male,Hispanic,02/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +60566,69505,63020,Probation,Robles,Andres,NULL,Male,Hispanic,02/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60545,69479,62994,PRETRIAL,Fernandez,Iliana,NULL,Female,Hispanic,06/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/21/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +60545,69479,62994,PRETRIAL,Fernandez,Iliana,NULL,Female,Hispanic,06/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +60545,69479,62994,PRETRIAL,Fernandez,Iliana,NULL,Female,Hispanic,06/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60556,69491,63006,PRETRIAL,Sousa,Jailton,NULL,Male,Caucasian,09/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +60556,69491,63006,PRETRIAL,Sousa,Jailton,NULL,Male,Caucasian,09/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +60556,69491,63006,PRETRIAL,Sousa,Jailton,NULL,Male,Caucasian,09/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +9686,69493,63008,PRETRIAL,GARY,ALOYSIUS,B,Male,African-American,05/26/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +9686,69493,63008,PRETRIAL,GARY,ALOYSIUS,B,Male,African-American,05/26/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +9686,69493,63008,PRETRIAL,GARY,ALOYSIUS,B,Male,African-American,05/26/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +60568,69507,63022,PRETRIAL,Ferguson,Meshach,NULL,Male,African-American,06/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +60568,69507,63022,PRETRIAL,Ferguson,Meshach,NULL,Male,African-American,06/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +60568,69507,63022,PRETRIAL,Ferguson,Meshach,NULL,Male,African-American,06/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60550,69486,63001,PRETRIAL,congemi,frank,NULL,Male,Caucasian,03/09/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +60550,69486,63001,PRETRIAL,congemi,frank,NULL,Male,Caucasian,03/09/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-2.61,1,Low,New,1,0 +60550,69486,63001,PRETRIAL,congemi,frank,NULL,Male,Caucasian,03/09/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +59855,69494,63009,Probation,peev,Ivan,NULL,Male,Caucasian,08/23/85,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +59855,69494,63009,Probation,peev,Ivan,NULL,Male,Caucasian,08/23/85,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +59855,69494,63009,Probation,peev,Ivan,NULL,Male,Caucasian,08/23/85,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +60564,69502,63017,Probation,Sefer,Joseph,NULL,Male,Caucasian,08/18/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +60564,69502,63017,Probation,Sefer,Joseph,NULL,Male,Caucasian,08/18/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +60564,69502,63017,Probation,Sefer,Joseph,NULL,Male,Caucasian,08/18/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60554,69489,63004,Probation,KALAGARA,VENUMADHAV,NULL,Male,Other,06/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/21/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +60554,69489,63004,Probation,KALAGARA,VENUMADHAV,NULL,Male,Other,06/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +60554,69489,63004,Probation,KALAGARA,VENUMADHAV,NULL,Male,Other,06/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60565,69504,63019,Probation,Paredes,yuri,Luis,Male,Hispanic,09/20/83,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/21/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +60565,69504,63019,Probation,Paredes,yuri,Luis,Male,Hispanic,09/20/83,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +60565,69504,63019,Probation,Paredes,yuri,Luis,Male,Hispanic,09/20/83,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60547,69481,62996,PRETRIAL,Jones,Kelvin,NULL,Male,African-American,04/07/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +60547,69481,62996,PRETRIAL,Jones,Kelvin,NULL,Male,African-American,04/07/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +60547,69481,62996,PRETRIAL,Jones,Kelvin,NULL,Male,African-American,04/07/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60558,69496,63011,Probation,storr,ian,NULL,Male,African-American,09/03/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/21/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +60558,69496,63011,Probation,storr,ian,NULL,Male,African-American,09/03/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/21/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +60558,69496,63011,Probation,storr,ian,NULL,Male,African-American,09/03/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54972,69531,63045,Probation,Seoane,Kevin,NULL,Male,Hispanic,08/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +54972,69531,63045,Probation,Seoane,Kevin,NULL,Male,Hispanic,08/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +54972,69531,63045,Probation,Seoane,Kevin,NULL,Male,Hispanic,08/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +7630,69546,7219,PRETRIAL,MAJOR,MAURICE,NULL,Male,African-American,01/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,Copy,1,0 +7630,69546,7219,PRETRIAL,MAJOR,MAURICE,NULL,Male,African-American,01/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,Copy,1,0 +7630,69546,7219,PRETRIAL,MAJOR,MAURICE,NULL,Male,African-American,01/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +6761,69517,63032,PRETRIAL,Platt,Lenard,NULL,Male,African-American,04/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +6761,69517,63032,PRETRIAL,Platt,Lenard,NULL,Male,African-American,04/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +6761,69517,63032,PRETRIAL,Platt,Lenard,NULL,Male,African-American,04/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60579,69523,63037,PRETRIAL,EDRICH,ELIZABETH,BROOK,Female,Caucasian,03/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +60579,69523,63037,PRETRIAL,EDRICH,ELIZABETH,BROOK,Female,Caucasian,03/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +60579,69523,63037,PRETRIAL,EDRICH,ELIZABETH,BROOK,Female,Caucasian,03/13/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60581,69525,63039,PRETRIAL,Jones,Miesha,NULL,Female,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +60581,69525,63039,PRETRIAL,Jones,Miesha,NULL,Female,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +60581,69525,63039,PRETRIAL,Jones,Miesha,NULL,Female,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60586,69533,63047,Probation,BASS,MICHELLE,NULL,Female,Caucasian,09/12/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +60586,69533,63047,Probation,BASS,MICHELLE,NULL,Female,Caucasian,09/12/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +60586,69533,63047,Probation,BASS,MICHELLE,NULL,Female,Caucasian,09/12/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60573,69512,63027,PRETRIAL,Mcnair,Archie,NULL,Male,African-American,08/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +60573,69512,63027,PRETRIAL,Mcnair,Archie,NULL,Male,African-American,08/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +60573,69512,63027,PRETRIAL,Mcnair,Archie,NULL,Male,African-American,08/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54246,69515,63030,PRETRIAL,thomas,Brandon,NULL,Male,African-American,05/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +54246,69515,63030,PRETRIAL,thomas,Brandon,NULL,Male,African-American,05/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +54246,69515,63030,PRETRIAL,thomas,Brandon,NULL,Male,African-American,05/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60594,69541,63053,PRETRIAL,SINGH,JAROD,NULL,Male,Caucasian,06/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +60594,69541,63053,PRETRIAL,SINGH,JAROD,NULL,Male,Caucasian,06/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +60594,69541,63053,PRETRIAL,SINGH,JAROD,NULL,Male,Caucasian,06/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +12389,69520,63035,PRETRIAL,PARCHMENT,COREY,ANDRE,Male,African-American,03/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +12389,69520,63035,PRETRIAL,PARCHMENT,COREY,ANDRE,Male,African-American,03/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +12389,69520,63035,PRETRIAL,PARCHMENT,COREY,ANDRE,Male,African-American,03/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60605,69554,63064,Probation,Joseph,Edzer,NULL,Male,African-American,02/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +60605,69554,63064,Probation,Joseph,Edzer,NULL,Male,African-American,02/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +60605,69554,63064,Probation,Joseph,Edzer,NULL,Male,African-American,02/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +17876,69521,17155,PRETRIAL,JOHNSON,STEPHEN,NULL,Male,African-American,01/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,Copy,1,0 +17876,69521,17155,PRETRIAL,JOHNSON,STEPHEN,NULL,Male,African-American,01/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.73,10,High,Copy,1,0 +17876,69521,17155,PRETRIAL,JOHNSON,STEPHEN,NULL,Male,African-American,01/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +60575,69514,63029,PRETRIAL,GERMAIN-PHILISTIN,WALLY,NULL,Male,Other,01/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +60575,69514,63029,PRETRIAL,GERMAIN-PHILISTIN,WALLY,NULL,Male,Other,01/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +60575,69514,63029,PRETRIAL,GERMAIN-PHILISTIN,WALLY,NULL,Male,Other,01/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54137,69528,63042,PRETRIAL,Oktavec,Gregory,NULL,Male,Caucasian,01/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +54137,69528,63042,PRETRIAL,Oktavec,Gregory,NULL,Male,Caucasian,01/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +54137,69528,63042,PRETRIAL,Oktavec,Gregory,NULL,Male,Caucasian,01/31/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +41252,69535,63049,PRETRIAL,Simmons,Fredderick,NULL,Male,African-American,01/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +41252,69535,63049,PRETRIAL,Simmons,Fredderick,NULL,Male,African-American,01/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +41252,69535,63049,PRETRIAL,Simmons,Fredderick,NULL,Male,African-American,01/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60595,69542,63054,PRETRIAL,Mcgirt,Ceddrick,Rashad,Male,African-American,01/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +60595,69542,63054,PRETRIAL,Mcgirt,Ceddrick,Rashad,Male,African-American,01/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +60595,69542,63054,PRETRIAL,Mcgirt,Ceddrick,Rashad,Male,African-American,01/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60584,69530,63044,Probation,rugel,carlos,NULL,Male,Hispanic,01/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +60584,69530,63044,Probation,rugel,carlos,NULL,Male,Hispanic,01/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +60584,69530,63044,Probation,rugel,carlos,NULL,Male,Hispanic,01/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60598,69547,63058,Probation,Torres,Daniel,NULL,Male,Hispanic,02/21/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.24,8,High,New,1,0 +60598,69547,63058,Probation,Torres,Daniel,NULL,Male,Hispanic,02/21/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +60598,69547,63058,Probation,Torres,Daniel,NULL,Male,Hispanic,02/21/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60582,69526,63040,Probation,Stevens,Jasmine,NULL,Female,African-American,10/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +60582,69526,63040,Probation,Stevens,Jasmine,NULL,Female,African-American,10/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +60582,69526,63040,Probation,Stevens,Jasmine,NULL,Female,African-American,10/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60596,69544,63056,Probation,SIMPSON,PAYTON,NULL,Male,African-American,08/08/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/22/14 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +60596,69544,63056,Probation,SIMPSON,PAYTON,NULL,Male,African-American,08/08/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +60596,69544,63056,Probation,SIMPSON,PAYTON,NULL,Male,African-American,08/08/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +41878,69551,63061,Probation,Teri,Justin,NULL,Male,Caucasian,07/31/85,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +41878,69551,63061,Probation,Teri,Justin,NULL,Male,Caucasian,07/31/85,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +41878,69551,63061,Probation,Teri,Justin,NULL,Male,Caucasian,07/31/85,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +34087,69516,63031,DRRD,Edwards,Roderick,NULL,Male,African-American,07/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +34087,69516,63031,DRRD,Edwards,Roderick,NULL,Male,African-American,07/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +34087,69516,63031,DRRD,Edwards,Roderick,NULL,Male,African-American,07/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +31698,33577,30695,PRETRIAL,Haddock,Rubby,Sanchez,Male,African-American,01/15/77,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Divorced,1/22/14 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +31698,33577,30695,PRETRIAL,Haddock,Rubby,Sanchez,Male,African-American,01/15/77,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Divorced,1/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +31698,33577,30695,PRETRIAL,Haddock,Rubby,Sanchez,Male,African-American,01/15/77,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Divorced,1/22/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60592,69537,63051,PRETRIAL,Pierre,Alexander,NULL,Male,African-American,05/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +60592,69537,63051,PRETRIAL,Pierre,Alexander,NULL,Male,African-American,05/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +60592,69537,63051,PRETRIAL,Pierre,Alexander,NULL,Male,African-American,05/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +44826,69529,63043,PRETRIAL,MOWERY,JEFFERY,NULL,Male,Caucasian,03/16/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +44826,69529,63043,PRETRIAL,MOWERY,JEFFERY,NULL,Male,Caucasian,03/16/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +44826,69529,63043,PRETRIAL,MOWERY,JEFFERY,NULL,Male,Caucasian,03/16/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60577,69519,63034,PRETRIAL,Watson,Harvell,NULL,Male,African-American,08/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +60577,69519,63034,PRETRIAL,Watson,Harvell,NULL,Male,African-American,08/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +60577,69519,63034,PRETRIAL,Watson,Harvell,NULL,Male,African-American,08/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +31698,69540,30695,PRETRIAL,Haddock,Rubby,Sanchez,Male,African-American,01/15/77,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Divorced,1/22/14 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,Copy,1,0 +31698,69540,30695,PRETRIAL,Haddock,Rubby,Sanchez,Male,African-American,01/15/77,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Divorced,1/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,Copy,1,0 +31698,69540,30695,PRETRIAL,Haddock,Rubby,Sanchez,Male,African-American,01/15/77,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Divorced,1/22/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +60585,69532,63046,Probation,SPEAKE,LAUREN,ASHLEY,Female,Caucasian,11/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +60585,69532,63046,Probation,SPEAKE,LAUREN,ASHLEY,Female,Caucasian,11/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +60585,69532,63046,Probation,SPEAKE,LAUREN,ASHLEY,Female,Caucasian,11/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60597,69545,63057,Probation,cook,judy,NULL,Female,Caucasian,10/30/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/14 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +60597,69545,63057,Probation,cook,judy,NULL,Female,Caucasian,10/30/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +60597,69545,63057,Probation,cook,judy,NULL,Female,Caucasian,10/30/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60580,69524,63038,PRETRIAL,JOHNSTON,MICHAEL,T,Male,Caucasian,02/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/22/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +60580,69524,63038,PRETRIAL,JOHNSTON,MICHAEL,T,Male,Caucasian,02/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/22/14 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +60580,69524,63038,PRETRIAL,JOHNSTON,MICHAEL,T,Male,Caucasian,02/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60603,69553,63063,Probation,Toliver,Dwayne,NULL,Male,African-American,06/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +60603,69553,63063,Probation,Toliver,Dwayne,NULL,Male,African-American,06/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +60603,69553,63063,Probation,Toliver,Dwayne,NULL,Male,African-American,06/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +42680,46589,42534,PRETRIAL,Miller,Kyle,NULL,Male,African-American,04/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +42680,46589,42534,PRETRIAL,Miller,Kyle,NULL,Male,African-American,04/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.79,10,High,New,1,0 +42680,46589,42534,PRETRIAL,Miller,Kyle,NULL,Male,African-American,04/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +7630,7656,7219,PRETRIAL,MAJOR,MAURICE,NULL,Male,African-American,01/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +7630,7656,7219,PRETRIAL,MAJOR,MAURICE,NULL,Male,African-American,01/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +7630,7656,7219,PRETRIAL,MAJOR,MAURICE,NULL,Male,African-American,01/02/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60574,69513,63028,PRETRIAL,Watts,Jermaine,James,Male,African-American,08/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +60574,69513,63028,PRETRIAL,Watts,Jermaine,James,Male,African-American,08/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +60574,69513,63028,PRETRIAL,Watts,Jermaine,James,Male,African-American,08/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60606,69555,63065,Probation,Dinu,Jonathan,NULL,Male,African-American,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +60606,69555,63065,Probation,Dinu,Jonathan,NULL,Male,African-American,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +60606,69555,63065,Probation,Dinu,Jonathan,NULL,Male,African-American,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60583,69527,63041,PRETRIAL,Clark,Damion,NULL,Male,African-American,10/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/22/14 0:00,2,Medium,7,Risk of Violence,-1.87,5,Medium,New,1,0 +60583,69527,63041,PRETRIAL,Clark,Damion,NULL,Male,African-American,10/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +60583,69527,63041,PRETRIAL,Clark,Damion,NULL,Male,African-American,10/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/22/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60587,69534,63048,Probation,mendes,shaun,NULL,Male,African-American,10/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +60587,69534,63048,Probation,mendes,shaun,NULL,Male,African-American,10/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +60587,69534,63048,Probation,mendes,shaun,NULL,Male,African-American,10/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60591,69536,63050,PRETRIAL,Butler,Willie,NULL,Male,African-American,09/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/22/14 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +60591,69536,63050,PRETRIAL,Butler,Willie,NULL,Male,African-American,09/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/22/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +60591,69536,63050,PRETRIAL,Butler,Willie,NULL,Male,African-American,09/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/22/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60599,69548,63059,Probation,HARDWICK,JASON,GERRAD,Male,African-American,03/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/22/14 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +60599,69548,63059,Probation,HARDWICK,JASON,GERRAD,Male,African-American,03/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +60599,69548,63059,Probation,HARDWICK,JASON,GERRAD,Male,African-American,03/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/22/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60578,69522,63036,PRETRIAL,Campbell,Sharonda,NULL,Female,African-American,01/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +60578,69522,63036,PRETRIAL,Campbell,Sharonda,NULL,Female,African-American,01/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +60578,69522,63036,PRETRIAL,Campbell,Sharonda,NULL,Female,African-American,01/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60593,69539,63052,PRETRIAL,DELGADO,PAMELA,NULL,Female,Caucasian,11/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +60593,69539,63052,PRETRIAL,DELGADO,PAMELA,NULL,Female,Caucasian,11/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +60593,69539,63052,PRETRIAL,DELGADO,PAMELA,NULL,Female,Caucasian,11/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60576,69518,63033,PRETRIAL,WASHINGTON,DAVID,L,Male,African-American,10/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +60576,69518,63033,PRETRIAL,WASHINGTON,DAVID,L,Male,African-American,10/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +60576,69518,63033,PRETRIAL,WASHINGTON,DAVID,L,Male,African-American,10/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53945,69543,63055,Probation,Manjarrezgutierrez,Beatriz,NULL,Female,Hispanic,09/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +53945,69543,63055,Probation,Manjarrezgutierrez,Beatriz,NULL,Female,Hispanic,09/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +53945,69543,63055,Probation,Manjarrezgutierrez,Beatriz,NULL,Female,Hispanic,09/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60602,69552,63062,PRETRIAL,Quevedo,Graciela,NULL,Female,Hispanic,08/15/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,1/22/14 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +60602,69552,63062,PRETRIAL,Quevedo,Graciela,NULL,Female,Hispanic,08/15/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,1/22/14 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +60602,69552,63062,PRETRIAL,Quevedo,Graciela,NULL,Female,Hispanic,08/15/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,1/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60623,69573,63083,PRETRIAL,Wanger,Jared,NULL,Male,Caucasian,05/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +60623,69573,63083,PRETRIAL,Wanger,Jared,NULL,Male,Caucasian,05/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +60623,69573,63083,PRETRIAL,Wanger,Jared,NULL,Male,Caucasian,05/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60642,69590,63100,Probation,DAMPIER,AUSTIN,DOUGLAS,Male,Caucasian,04/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +60642,69590,63100,Probation,DAMPIER,AUSTIN,DOUGLAS,Male,Caucasian,04/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +60642,69590,63100,Probation,DAMPIER,AUSTIN,DOUGLAS,Male,Caucasian,04/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60618,69569,63079,Probation,Vasquez,Sergio,NULL,Male,Caucasian,03/28/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +60618,69569,63079,Probation,Vasquez,Sergio,NULL,Male,Caucasian,03/28/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +60618,69569,63079,Probation,Vasquez,Sergio,NULL,Male,Caucasian,03/28/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60646,69594,63103,PRETRIAL,Brown,Todd,J,Male,African-American,02/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/23/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +60646,69594,63103,PRETRIAL,Brown,Todd,J,Male,African-American,02/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +60646,69594,63103,PRETRIAL,Brown,Todd,J,Male,African-American,02/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60608,69557,63067,PRETRIAL,Adderly,Vatoria,NULL,Male,African-American,07/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +60608,69557,63067,PRETRIAL,Adderly,Vatoria,NULL,Male,African-American,07/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +60608,69557,63067,PRETRIAL,Adderly,Vatoria,NULL,Male,African-American,07/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60614,69564,63074,PRETRIAL,roberts,anthony,NULL,Male,African-American,01/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/23/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +60614,69564,63074,PRETRIAL,roberts,anthony,NULL,Male,African-American,01/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/23/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +60614,69564,63074,PRETRIAL,roberts,anthony,NULL,Male,African-American,01/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60651,69599,63108,DRRD,Saunders,Trayvontae,NULL,Male,African-American,11/29/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,4,High,7,Risk of Violence,-0.52,10,High,New,1,0 +60651,69599,63108,DRRD,Saunders,Trayvontae,NULL,Male,African-American,11/29/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,4,High,8,Risk of Recidivism,0.47,9,High,New,1,0 +60651,69599,63108,DRRD,Saunders,Trayvontae,NULL,Male,African-American,11/29/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,4,High,18,Risk of Failure to Appear,23,4,Low,New,1,0 +60630,69578,63088,PRETRIAL,Silva,Marcelo,NULL,Male,Hispanic,06/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +60630,69578,63088,PRETRIAL,Silva,Marcelo,NULL,Male,Hispanic,06/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +60630,69578,63088,PRETRIAL,Silva,Marcelo,NULL,Male,Hispanic,06/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60636,69585,63095,PRETRIAL,WHITE,MELINDA,NULL,Female,African-American,06/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +60636,69585,63095,PRETRIAL,WHITE,MELINDA,NULL,Female,African-American,06/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +60636,69585,63095,PRETRIAL,WHITE,MELINDA,NULL,Female,African-American,06/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60610,69560,63070,PRETRIAL,Sibblies,Keanne,Antoinette,Female,African-American,11/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +60610,69560,63070,PRETRIAL,Sibblies,Keanne,Antoinette,Female,African-American,11/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +60610,69560,63070,PRETRIAL,Sibblies,Keanne,Antoinette,Female,African-American,11/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60624,69574,63084,Probation,Bennington,Dahlton,NULL,Female,Caucasian,05/11/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/23/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +60624,69574,63084,Probation,Bennington,Dahlton,NULL,Female,Caucasian,05/11/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +60624,69574,63084,Probation,Bennington,Dahlton,NULL,Female,Caucasian,05/11/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60654,69603,63112,Probation,Nathaniel,Daniea,NULL,Female,African-American,10/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +60654,69603,63112,Probation,Nathaniel,Daniea,NULL,Female,African-American,10/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/14 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +60654,69603,63112,Probation,Nathaniel,Daniea,NULL,Female,African-American,10/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +27753,69581,63091,PRETRIAL,WILLIAMS,MARCUS,NULL,Male,African-American,11/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +27753,69581,63091,PRETRIAL,WILLIAMS,MARCUS,NULL,Male,African-American,11/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +27753,69581,63091,PRETRIAL,WILLIAMS,MARCUS,NULL,Male,African-American,11/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +60633,69582,63092,Probation,Blowe,Anthony,NULL,Male,African-American,11/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +60633,69582,63092,Probation,Blowe,Anthony,NULL,Male,African-American,11/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +60633,69582,63092,Probation,Blowe,Anthony,NULL,Male,African-American,11/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60645,69595,63104,Probation,young,beverly,NULL,Female,Caucasian,11/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +60645,69595,63104,Probation,young,beverly,NULL,Female,Caucasian,11/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.53,2,Low,New,1,0 +60645,69595,63104,Probation,young,beverly,NULL,Female,Caucasian,11/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60638,69587,63097,Probation,SAPP,JACOB,NULL,Male,African-American,08/31/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/23/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +60638,69587,63097,Probation,SAPP,JACOB,NULL,Male,African-American,08/31/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +60638,69587,63097,Probation,SAPP,JACOB,NULL,Male,African-American,08/31/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60641,69589,63099,Probation,Carrasco,Pedro,NULL,Male,Hispanic,06/29/62,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +60641,69589,63099,Probation,Carrasco,Pedro,NULL,Male,Hispanic,06/29/62,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +60641,69589,63099,Probation,Carrasco,Pedro,NULL,Male,Hispanic,06/29/62,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60611,69561,63071,PRETRIAL,Nguyen,Duc,Minh,Male,Asian,10/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.83,2,Low,New,1,0 +60611,69561,63071,PRETRIAL,Nguyen,Duc,Minh,Male,Asian,10/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +60611,69561,63071,PRETRIAL,Nguyen,Duc,Minh,Male,Asian,10/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +6986,69566,63076,PRETRIAL,FERRAILO,JAMES,E,Male,Caucasian,09/30/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/14 0:00,2,Medium,7,Risk of Violence,-2.94,2,Low,New,1,0 +6986,69566,63076,PRETRIAL,FERRAILO,JAMES,E,Male,Caucasian,09/30/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +6986,69566,63076,PRETRIAL,FERRAILO,JAMES,E,Male,Caucasian,09/30/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +60617,69568,63078,Probation,Abaroa,Alejandro,NULL,Male,Hispanic,11/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +60617,69568,63078,Probation,Abaroa,Alejandro,NULL,Male,Hispanic,11/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +60617,69568,63078,Probation,Abaroa,Alejandro,NULL,Male,Hispanic,11/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +32818,69602,63111,Probation,komec,kathleen,NULL,Female,Caucasian,06/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +32818,69602,63111,Probation,komec,kathleen,NULL,Female,Caucasian,06/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +32818,69602,63111,Probation,komec,kathleen,NULL,Female,Caucasian,06/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59534,69558,63068,PRETRIAL,MILLER,TERRY,NULL,Male,African-American,07/14/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.58,2,Low,New,1,0 +59534,69558,63068,PRETRIAL,MILLER,TERRY,NULL,Male,African-American,07/14/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +59534,69558,63068,PRETRIAL,MILLER,TERRY,NULL,Male,African-American,07/14/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60627,69576,63086,Probation,Manus,Elizabeth,NULL,Female,Caucasian,01/21/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/23/14 0:00,1,Low,7,Risk of Violence,-4.52,1,Low,New,1,0 +60627,69576,63086,Probation,Manus,Elizabeth,NULL,Female,Caucasian,01/21/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/23/14 0:00,1,Low,8,Risk of Recidivism,-2.73,1,Low,New,1,0 +60627,69576,63086,Probation,Manus,Elizabeth,NULL,Female,Caucasian,01/21/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60631,69579,63089,Probation,Delgado,Natalie,NULL,Male,Hispanic,02/04/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +60631,69579,63089,Probation,Delgado,Natalie,NULL,Male,Hispanic,02/04/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +60631,69579,63089,Probation,Delgado,Natalie,NULL,Male,Hispanic,02/04/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60648,69597,63106,PRETRIAL,Marcellus,Nickson,NULL,Male,African-American,07/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/14 0:00,4,High,7,Risk of Violence,-0.4,10,High,New,1,0 +60648,69597,63106,PRETRIAL,Marcellus,Nickson,NULL,Male,African-American,07/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/14 0:00,4,High,8,Risk of Recidivism,0.92,10,High,New,1,0 +60648,69597,63106,PRETRIAL,Marcellus,Nickson,NULL,Male,African-American,07/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60619,69571,63081,Probation,HEPBURN,CLIVE,A,Male,African-American,02/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +60619,69571,63081,Probation,HEPBURN,CLIVE,A,Male,African-American,02/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +60619,69571,63081,Probation,HEPBURN,CLIVE,A,Male,African-American,02/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60635,69584,63094,PRETRIAL,WILLIAMS,JEVON,NULL,Male,African-American,09/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +60635,69584,63094,PRETRIAL,WILLIAMS,JEVON,NULL,Male,African-American,09/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +60635,69584,63094,PRETRIAL,WILLIAMS,JEVON,NULL,Male,African-American,09/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60615,69565,63075,Probation,Kucsera,Monika,NULL,Female,Caucasian,03/29/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +60615,69565,63075,Probation,Kucsera,Monika,NULL,Female,Caucasian,03/29/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +60615,69565,63075,Probation,Kucsera,Monika,NULL,Female,Caucasian,03/29/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60607,69556,63066,PRETRIAL,Smith,Charles,NULL,Male,African-American,09/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +60607,69556,63066,PRETRIAL,Smith,Charles,NULL,Male,African-American,09/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +60607,69556,63066,PRETRIAL,Smith,Charles,NULL,Male,African-American,09/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60628,69577,63087,Probation,bello,mark,NULL,Male,Hispanic,12/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +60628,69577,63087,Probation,bello,mark,NULL,Male,Hispanic,12/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +60628,69577,63087,Probation,bello,mark,NULL,Male,Hispanic,12/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60637,69586,63096,Probation,May,Wayne,NULL,Male,Other,05/08/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +60637,69586,63096,Probation,May,Wayne,NULL,Male,Other,05/08/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +60637,69586,63096,Probation,May,Wayne,NULL,Male,Other,05/08/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +60613,69563,63073,PRETRIAL,diaz,luis,NULL,Male,Caucasian,05/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +60613,69563,63073,PRETRIAL,diaz,luis,NULL,Male,Caucasian,05/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +60613,69563,63073,PRETRIAL,diaz,luis,NULL,Male,Caucasian,05/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54511,69570,63080,PRETRIAL,Downing,Donald,James,Male,Caucasian,02/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +54511,69570,63080,PRETRIAL,Downing,Donald,James,Male,Caucasian,02/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +54511,69570,63080,PRETRIAL,Downing,Donald,James,Male,Caucasian,02/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60620,69572,63082,Probation,Johnson,Chavalier,NULL,Male,African-American,04/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.54,10,High,New,1,0 +60620,69572,63082,Probation,Johnson,Chavalier,NULL,Male,African-American,04/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,7,Medium,New,1,0 +60620,69572,63082,Probation,Johnson,Chavalier,NULL,Male,African-American,04/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60643,69591,63101,Probation,Cruz,Andino,NULL,Male,Hispanic,10/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +60643,69591,63101,Probation,Cruz,Andino,NULL,Male,Hispanic,10/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +60643,69591,63101,Probation,Cruz,Andino,NULL,Male,Hispanic,10/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60644,69593,63102,PRETRIAL,Lucas,Judge,NULL,Male,African-American,05/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/23/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,Copy,1,0 +60644,69593,63102,PRETRIAL,Lucas,Judge,NULL,Male,African-American,05/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,Copy,1,0 +60644,69593,63102,PRETRIAL,Lucas,Judge,NULL,Male,African-American,05/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +60640,69588,63098,Probation,connelly,angela,NULL,Female,African-American,01/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +60640,69588,63098,Probation,connelly,angela,NULL,Female,African-American,01/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,7,Medium,New,1,0 +60640,69588,63098,Probation,connelly,angela,NULL,Female,African-American,01/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60625,69575,63085,Probation,Fearon,Junior,NULL,Male,African-American,12/09/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +60625,69575,63085,Probation,Fearon,Junior,NULL,Male,African-American,12/09/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +60625,69575,63085,Probation,Fearon,Junior,NULL,Male,African-American,12/09/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60612,69562,63072,PRETRIAL,Woolwine,Curtis,NULL,Male,Caucasian,04/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +60612,69562,63072,PRETRIAL,Woolwine,Curtis,NULL,Male,Caucasian,04/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +60612,69562,63072,PRETRIAL,Woolwine,Curtis,NULL,Male,Caucasian,04/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60632,69580,63090,Probation,WALKER,ROYSTON,G,Male,African-American,05/14/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/23/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +60632,69580,63090,Probation,WALKER,ROYSTON,G,Male,African-American,05/14/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +60632,69580,63090,Probation,WALKER,ROYSTON,G,Male,African-American,05/14/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60634,69583,63093,PRETRIAL,OGBURN,WILLIAM,NULL,Male,African-American,08/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/23/14 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +60634,69583,63093,PRETRIAL,OGBURN,WILLIAM,NULL,Male,African-American,08/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/23/14 0:00,1,Low,8,Risk of Recidivism,-2.91,1,Low,New,1,0 +60634,69583,63093,PRETRIAL,OGBURN,WILLIAM,NULL,Male,African-American,08/15/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60609,69559,63069,PRETRIAL,Scalisi,Lina,NULL,Female,Caucasian,01/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +60609,69559,63069,PRETRIAL,Scalisi,Lina,NULL,Female,Caucasian,01/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +60609,69559,63069,PRETRIAL,Scalisi,Lina,NULL,Female,Caucasian,01/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +60655,69604,63113,Probation,Smit,Douw,NULL,Male,Caucasian,08/08/43,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/14 0:00,1,Low,7,Risk of Violence,-4.54,1,Low,New,1,0 +60655,69604,63113,Probation,Smit,Douw,NULL,Male,Caucasian,08/08/43,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/14 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +60655,69604,63113,Probation,Smit,Douw,NULL,Male,Caucasian,08/08/43,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60616,69567,63077,Probation,Guillermo,Chaviano,NULL,Male,Hispanic,06/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +60616,69567,63077,Probation,Guillermo,Chaviano,NULL,Male,Hispanic,06/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +60616,69567,63077,Probation,Guillermo,Chaviano,NULL,Male,Hispanic,06/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60647,69596,63105,PRETRIAL,Porter,Deondra,NULL,Female,African-American,11/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +60647,69596,63105,PRETRIAL,Porter,Deondra,NULL,Female,African-American,11/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,10,High,New,1,0 +60647,69596,63105,PRETRIAL,Porter,Deondra,NULL,Female,African-American,11/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60683,69632,63141,PRETRIAL,STAPLES,FABIAN,NULL,Male,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +60683,69632,63141,PRETRIAL,STAPLES,FABIAN,NULL,Male,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +60683,69632,63141,PRETRIAL,STAPLES,FABIAN,NULL,Male,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60667,69617,63126,Probation,murillo,Casto,NULL,Male,Hispanic,02/27/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +60667,69617,63126,Probation,murillo,Casto,NULL,Male,Hispanic,02/27/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +60667,69617,63126,Probation,murillo,Casto,NULL,Male,Hispanic,02/27/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54437,69638,63146,PRETRIAL,PETUSEVSKY,MONICA,NULL,Male,Caucasian,10/26/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/24/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +54437,69638,63146,PRETRIAL,PETUSEVSKY,MONICA,NULL,Male,Caucasian,10/26/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/24/14 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +54437,69638,63146,PRETRIAL,PETUSEVSKY,MONICA,NULL,Male,Caucasian,10/26/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60688,69640,63148,Probation,SUN,GUIYU,NULL,Female,Asian,09/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/24/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +60688,69640,63148,Probation,SUN,GUIYU,NULL,Female,Asian,09/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +60688,69640,63148,Probation,SUN,GUIYU,NULL,Female,Asian,09/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60676,69625,63134,Probation,Welky,Charles,NULL,Male,Caucasian,09/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +60676,69625,63134,Probation,Welky,Charles,NULL,Male,Caucasian,09/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +60676,69625,63134,Probation,Welky,Charles,NULL,Male,Caucasian,09/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47770,61271,55627,PRETRIAL,Barrington,Andre,NULL,Male,African-American,06/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/24/14 0:00,4,High,7,Risk of Violence,-0.4,10,High,New,1,0 +47770,61271,55627,PRETRIAL,Barrington,Andre,NULL,Male,African-American,06/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/24/14 0:00,4,High,8,Risk of Recidivism,1.09,10,High,New,1,0 +47770,61271,55627,PRETRIAL,Barrington,Andre,NULL,Male,African-American,06/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/24/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60693,69651,63155,PRETRIAL,francocoa,yoalbert,NULL,Male,Hispanic,07/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/24/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +60693,69651,63155,PRETRIAL,francocoa,yoalbert,NULL,Male,Hispanic,07/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +60693,69651,63155,PRETRIAL,francocoa,yoalbert,NULL,Male,Hispanic,07/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60680,69630,63139,PRETRIAL,Mapp,Joshua,NULL,Male,Caucasian,08/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +60680,69630,63139,PRETRIAL,Mapp,Joshua,NULL,Male,Caucasian,08/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +60680,69630,63139,PRETRIAL,Mapp,Joshua,NULL,Male,Caucasian,08/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60691,69648,63152,PRETRIAL,Mella,Consuelo,NULL,Female,Caucasian,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +60691,69648,63152,PRETRIAL,Mella,Consuelo,NULL,Female,Caucasian,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +60691,69648,63152,PRETRIAL,Mella,Consuelo,NULL,Female,Caucasian,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60659,69609,63118,PRETRIAL,Leonard,Ryan,Robert,Male,Caucasian,02/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +60659,69609,63118,PRETRIAL,Leonard,Ryan,Robert,Male,Caucasian,02/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +60659,69609,63118,PRETRIAL,Leonard,Ryan,Robert,Male,Caucasian,02/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60670,69622,63131,Probation,Torres,Renzo,NULL,Male,Hispanic,02/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +60670,69622,63131,Probation,Torres,Renzo,NULL,Male,Hispanic,02/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +60670,69622,63131,Probation,Torres,Renzo,NULL,Male,Hispanic,02/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60664,69614,63123,PRETRIAL,Arnold,Barney,NULL,Male,Caucasian,06/24/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +60664,69614,63123,PRETRIAL,Arnold,Barney,NULL,Male,Caucasian,06/24/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +60664,69614,63123,PRETRIAL,Arnold,Barney,NULL,Male,Caucasian,06/24/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60692,69649,63153,Probation,DOYLE,ISRAEL,L,Male,African-American,12/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,New,1,0 +60692,69649,63153,Probation,DOYLE,ISRAEL,L,Male,African-American,12/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,4,High,8,Risk of Recidivism,0.43,9,High,New,1,0 +60692,69649,63153,Probation,DOYLE,ISRAEL,L,Male,African-American,12/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60685,69635,63143,Probation,Vilma,Rose,NULL,Female,African-American,03/24/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +60685,69635,63143,Probation,Vilma,Rose,NULL,Female,African-American,03/24/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +60685,69635,63143,Probation,Vilma,Rose,NULL,Female,African-American,03/24/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60689,69642,63149,Probation,Herrera,Juan,NULL,Male,Caucasian,05/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +60689,69642,63149,Probation,Herrera,Juan,NULL,Male,Caucasian,05/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +60689,69642,63149,Probation,Herrera,Juan,NULL,Male,Caucasian,05/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60666,69616,63125,PRETRIAL,WALLACK,BRAIN,NULL,Male,Caucasian,10/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +60666,69616,63125,PRETRIAL,WALLACK,BRAIN,NULL,Male,Caucasian,10/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +60666,69616,63125,PRETRIAL,WALLACK,BRAIN,NULL,Male,Caucasian,10/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60657,69607,63116,PRETRIAL,Odom,Laroyce,NULL,Male,African-American,12/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +60657,69607,63116,PRETRIAL,Odom,Laroyce,NULL,Male,African-American,12/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,4,High,8,Risk of Recidivism,1.01,10,High,New,1,0 +60657,69607,63116,PRETRIAL,Odom,Laroyce,NULL,Male,African-American,12/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +60687,69637,63145,Probation,EVANS,DOROTHY,NULL,Female,Caucasian,09/04/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/24/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +60687,69637,63145,Probation,EVANS,DOROTHY,NULL,Female,Caucasian,09/04/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +60687,69637,63145,Probation,EVANS,DOROTHY,NULL,Female,Caucasian,09/04/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +31946,69654,61159,PRETRIAL,Reyes,Ashley,NULL,Female,African-American,08/22/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,4,High,7,Risk of Violence,-0.81,9,High,Copy,1,0 +31946,69654,61159,PRETRIAL,Reyes,Ashley,NULL,Female,African-American,08/22/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,4,High,8,Risk of Recidivism,0.45,10,High,Copy,1,0 +31946,69654,61159,PRETRIAL,Reyes,Ashley,NULL,Female,African-American,08/22/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +60662,69612,63121,PRETRIAL,Alvarez,Rodney,Alexander,Male,Caucasian,05/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +60662,69612,63121,PRETRIAL,Alvarez,Rodney,Alexander,Male,Caucasian,05/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +60662,69612,63121,PRETRIAL,Alvarez,Rodney,Alexander,Male,Caucasian,05/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60669,69619,63128,Probation,Vargas,Richard,Robert,Male,Hispanic,07/15/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +60669,69619,63128,Probation,Vargas,Richard,Robert,Male,Hispanic,07/15/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +60669,69619,63128,Probation,Vargas,Richard,Robert,Male,Hispanic,07/15/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60694,69652,63156,Probation,LACY,ERIC,NULL,Male,African-American,07/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +60694,69652,63156,Probation,LACY,ERIC,NULL,Male,African-American,07/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +60694,69652,63156,Probation,LACY,ERIC,NULL,Male,African-American,07/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60656,69605,63114,PRETRIAL,Atkinson,Christian,C,Male,Other,02/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +60656,69605,63114,PRETRIAL,Atkinson,Christian,C,Male,Other,02/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +60656,69605,63114,PRETRIAL,Atkinson,Christian,C,Male,Other,02/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +37641,69639,63147,PRETRIAL,Stokes,Letiffanie,NULL,Female,African-American,03/30/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +37641,69639,63147,PRETRIAL,Stokes,Letiffanie,NULL,Female,African-American,03/30/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +37641,69639,63147,PRETRIAL,Stokes,Letiffanie,NULL,Female,African-American,03/30/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +53013,69647,63151,Probation,Kelly,Jerry,Joseph,Male,Caucasian,06/29/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +53013,69647,63151,Probation,Kelly,Jerry,Joseph,Male,Caucasian,06/29/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +53013,69647,63151,Probation,Kelly,Jerry,Joseph,Male,Caucasian,06/29/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +60677,69626,63135,Probation,Rosier,Jacky,NULL,Male,African-American,06/03/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +60677,69626,63135,Probation,Rosier,Jacky,NULL,Male,African-American,06/03/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +60677,69626,63135,Probation,Rosier,Jacky,NULL,Male,African-American,06/03/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60682,69631,63140,Probation,Gibson,Suset,NULL,Female,Hispanic,02/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/24/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +60682,69631,63140,Probation,Gibson,Suset,NULL,Female,Hispanic,02/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +60682,69631,63140,Probation,Gibson,Suset,NULL,Female,Hispanic,02/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60660,69610,63119,PRETRIAL,Rivera,Denny,Cuevas,Male,Caucasian,10/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/24/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +60660,69610,63119,PRETRIAL,Rivera,Denny,Cuevas,Male,Caucasian,10/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +60660,69610,63119,PRETRIAL,Rivera,Denny,Cuevas,Male,Caucasian,10/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60663,69613,63122,PRETRIAL,Werba,Kellie,Ann,Female,Caucasian,11/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +60663,69613,63122,PRETRIAL,Werba,Kellie,Ann,Female,Caucasian,11/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +60663,69613,63122,PRETRIAL,Werba,Kellie,Ann,Female,Caucasian,11/25/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +26441,69606,63115,PRETRIAL,Hidalgo,Neil,Joseph,Male,Caucasian,07/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +26441,69606,63115,PRETRIAL,Hidalgo,Neil,Joseph,Male,Caucasian,07/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +26441,69606,63115,PRETRIAL,Hidalgo,Neil,Joseph,Male,Caucasian,07/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +49112,69655,63157,PRETRIAL,Dulcio,Dave,NULL,Male,African-American,03/25/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +49112,69655,63157,PRETRIAL,Dulcio,Dave,NULL,Male,African-American,03/25/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +49112,69655,63157,PRETRIAL,Dulcio,Dave,NULL,Male,African-American,03/25/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60678,69627,63136,Probation,Talon,Rafael,NULL,Male,Hispanic,05/26/83,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/24/14 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +60678,69627,63136,Probation,Talon,Rafael,NULL,Male,Hispanic,05/26/83,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +60678,69627,63136,Probation,Talon,Rafael,NULL,Male,Hispanic,05/26/83,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/24/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60684,69634,63142,Probation,Moran,Angel,NULL,Male,Hispanic,03/22/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +60684,69634,63142,Probation,Moran,Angel,NULL,Male,Hispanic,03/22/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +60684,69634,63142,Probation,Moran,Angel,NULL,Male,Hispanic,03/22/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60686,69636,63144,PRETRIAL,deary,anthony,NULL,Male,African-American,03/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +60686,69636,63144,PRETRIAL,deary,anthony,NULL,Male,African-American,03/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +60686,69636,63144,PRETRIAL,deary,anthony,NULL,Male,African-American,03/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60658,69608,63117,PRETRIAL,Cabral,Marcelle,NULL,Female,African-American,07/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +60658,69608,63117,PRETRIAL,Cabral,Marcelle,NULL,Female,African-American,07/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +60658,69608,63117,PRETRIAL,Cabral,Marcelle,NULL,Female,African-American,07/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60665,69615,63124,PRETRIAL,Gray,William,L,Male,Other,11/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +60665,69615,63124,PRETRIAL,Gray,William,L,Male,Other,11/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +60665,69615,63124,PRETRIAL,Gray,William,L,Male,Other,11/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60671,69620,63129,Probation,Hayes,Justin,NULL,Male,Caucasian,04/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +60671,69620,63129,Probation,Hayes,Justin,NULL,Male,Caucasian,04/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.88,10,High,New,1,0 +60671,69620,63129,Probation,Hayes,Justin,NULL,Male,Caucasian,04/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60675,69624,63133,Probation,Mejia,Madeline,NULL,Female,Hispanic,04/28/67,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/24/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +60675,69624,63133,Probation,Mejia,Madeline,NULL,Female,Hispanic,04/28/67,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/24/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +60675,69624,63133,Probation,Mejia,Madeline,NULL,Female,Hispanic,04/28/67,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60661,69611,63120,PRETRIAL,Marochnik,Dmitry,NULL,Male,Caucasian,01/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +60661,69611,63120,PRETRIAL,Marochnik,Dmitry,NULL,Male,Caucasian,01/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +60661,69611,63120,PRETRIAL,Marochnik,Dmitry,NULL,Male,Caucasian,01/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/24/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +35453,69650,63154,PRETRIAL,GRACE,ROBERT,NULL,Male,Caucasian,01/01/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +35453,69650,63154,PRETRIAL,GRACE,ROBERT,NULL,Male,Caucasian,01/01/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +35453,69650,63154,PRETRIAL,GRACE,ROBERT,NULL,Male,Caucasian,01/01/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/24/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +60699,69662,63163,PRETRIAL,PETERSON,RICHARD,ALEXANDER,Male,Caucasian,01/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +60699,69662,63163,PRETRIAL,PETERSON,RICHARD,ALEXANDER,Male,Caucasian,01/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +60699,69662,63163,PRETRIAL,PETERSON,RICHARD,ALEXANDER,Male,Caucasian,01/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60695,69657,63159,PRETRIAL,Scott,Bryan,Omar,Male,Other,09/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +60695,69657,63159,PRETRIAL,Scott,Bryan,Omar,Male,Other,09/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +60695,69657,63159,PRETRIAL,Scott,Bryan,Omar,Male,Other,09/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30696,69664,63165,PRETRIAL,Harden,Darryl,NULL,Male,African-American,09/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +30696,69664,63165,PRETRIAL,Harden,Darryl,NULL,Male,African-American,09/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +30696,69664,63165,PRETRIAL,Harden,Darryl,NULL,Male,African-American,09/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60697,69660,63161,PRETRIAL,Delgado,Melina,NULL,Female,Hispanic,11/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +60697,69660,63161,PRETRIAL,Delgado,Melina,NULL,Female,Hispanic,11/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +60697,69660,63161,PRETRIAL,Delgado,Melina,NULL,Female,Hispanic,11/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60701,69665,63166,PRETRIAL,Quinonez,Tania,NULL,Male,African-American,08/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +60701,69665,63166,PRETRIAL,Quinonez,Tania,NULL,Male,African-American,08/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +60701,69665,63166,PRETRIAL,Quinonez,Tania,NULL,Male,African-American,08/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59487,69658,61824,PRETRIAL,kelly,Kelsian,NULL,Male,African-American,02/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.48,3,Low,Copy,1,0 +59487,69658,61824,PRETRIAL,kelly,Kelsian,NULL,Male,African-American,02/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,Copy,1,0 +59487,69658,61824,PRETRIAL,kelly,Kelsian,NULL,Male,African-American,02/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +60700,69663,63164,PRETRIAL,ALEXANDRE,FABRICE,NULL,Male,African-American,10/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +60700,69663,63164,PRETRIAL,ALEXANDRE,FABRICE,NULL,Male,African-American,10/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +60700,69663,63164,PRETRIAL,ALEXANDRE,FABRICE,NULL,Male,African-American,10/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56342,69656,63158,PRETRIAL,LEWIS,SHANE,NULL,Male,African-American,07/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +56342,69656,63158,PRETRIAL,LEWIS,SHANE,NULL,Male,African-American,07/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +56342,69656,63158,PRETRIAL,LEWIS,SHANE,NULL,Male,African-American,07/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60696,69659,63160,PRETRIAL,Gorshechnikov,Alexander,NULL,Male,Caucasian,10/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +60696,69659,63160,PRETRIAL,Gorshechnikov,Alexander,NULL,Male,Caucasian,10/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +60696,69659,63160,PRETRIAL,Gorshechnikov,Alexander,NULL,Male,Caucasian,10/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60698,69661,63162,PRETRIAL,LOUIS,ANTHONY,VONTERR,Male,African-American,11/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/25/14 0:00,2,Medium,7,Risk of Violence,-3.29,1,Low,New,1,0 +60698,69661,63162,PRETRIAL,LOUIS,ANTHONY,VONTERR,Male,African-American,11/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +60698,69661,63162,PRETRIAL,LOUIS,ANTHONY,VONTERR,Male,African-American,11/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/25/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60702,69666,63167,PRETRIAL,STEVENS,LAURENCE,NULL,Female,Other,11/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +60702,69666,63167,PRETRIAL,STEVENS,LAURENCE,NULL,Female,Other,11/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +60702,69666,63167,PRETRIAL,STEVENS,LAURENCE,NULL,Female,Other,11/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/25/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60709,69674,63174,PRETRIAL,Mayors,Brian,NULL,Male,Caucasian,12/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +60709,69674,63174,PRETRIAL,Mayors,Brian,NULL,Male,Caucasian,12/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +60709,69674,63174,PRETRIAL,Mayors,Brian,NULL,Male,Caucasian,12/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60703,69667,63168,PRETRIAL,Haywood,Zandra,NULL,Female,African-American,12/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +60703,69667,63168,PRETRIAL,Haywood,Zandra,NULL,Female,African-American,12/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +60703,69667,63168,PRETRIAL,Haywood,Zandra,NULL,Female,African-American,12/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60705,69669,63170,PRETRIAL,SAINTELUS,WALDER,NULL,Male,Other,01/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.73,9,High,New,1,0 +60705,69669,63170,PRETRIAL,SAINTELUS,WALDER,NULL,Male,Other,01/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +60705,69669,63170,PRETRIAL,SAINTELUS,WALDER,NULL,Male,Other,01/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60706,69670,63171,PRETRIAL,Pearson,Steven,NULL,Male,African-Am,08/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +60706,69670,63171,PRETRIAL,Pearson,Steven,NULL,Male,African-Am,08/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +60706,69670,63171,PRETRIAL,Pearson,Steven,NULL,Male,African-Am,08/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60708,69672,63172,PRETRIAL,Gabriel,Devonne,NULL,Male,African-American,11/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +60708,69672,63172,PRETRIAL,Gabriel,Devonne,NULL,Male,African-American,11/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +60708,69672,63172,PRETRIAL,Gabriel,Devonne,NULL,Male,African-American,11/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60710,69675,63175,PRETRIAL,FLORES,MICHAEL,ALLEN,Male,Caucasian,05/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/26/14 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,New,1,0 +60710,69675,63175,PRETRIAL,FLORES,MICHAEL,ALLEN,Male,Caucasian,05/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +60710,69675,63175,PRETRIAL,FLORES,MICHAEL,ALLEN,Male,Caucasian,05/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/26/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60704,69668,63169,PRETRIAL,DODSON,BRANDY,I,Female,Caucasian,12/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +60704,69668,63169,PRETRIAL,DODSON,BRANDY,I,Female,Caucasian,12/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +60704,69668,63169,PRETRIAL,DODSON,BRANDY,I,Female,Caucasian,12/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60711,69676,63176,PRETRIAL,lopez,gabriel,NULL,Male,Caucasian,07/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +60711,69676,63176,PRETRIAL,lopez,gabriel,NULL,Male,Caucasian,07/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +60711,69676,63176,PRETRIAL,lopez,gabriel,NULL,Male,Caucasian,07/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +1405,69671,38154,PRETRIAL,Jefferson,Deverick,Dewayne,Male,African-American,04/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,Copy,1,0 +1405,69671,38154,PRETRIAL,Jefferson,Deverick,Dewayne,Male,African-American,04/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,Copy,1,0 +1405,69671,38154,PRETRIAL,Jefferson,Deverick,Dewayne,Male,African-American,04/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +60744,69722,63217,PRETRIAL,Avril,Edel,NULL,Male,Other,07/15/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +60744,69722,63217,PRETRIAL,Avril,Edel,NULL,Male,Other,07/15/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +60744,69722,63217,PRETRIAL,Avril,Edel,NULL,Male,Other,07/15/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60742,69718,63214,PRETRIAL,TORRES,JOSEPH,NULL,Male,Caucasian,11/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +60742,69718,63214,PRETRIAL,TORRES,JOSEPH,NULL,Male,Caucasian,11/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +60742,69718,63214,PRETRIAL,TORRES,JOSEPH,NULL,Male,Caucasian,11/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +60717,69683,63182,PRETRIAL,Kadler,Erik,NULL,Male,Caucasian,11/26/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/27/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +60717,69683,63182,PRETRIAL,Kadler,Erik,NULL,Male,Caucasian,11/26/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +60717,69683,63182,PRETRIAL,Kadler,Erik,NULL,Male,Caucasian,11/26/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60730,69701,63197,PRETRIAL,allaire,maggi,NULL,Female,Caucasian,07/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/27/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +60730,69701,63197,PRETRIAL,allaire,maggi,NULL,Female,Caucasian,07/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +60730,69701,63197,PRETRIAL,allaire,maggi,NULL,Female,Caucasian,07/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60714,69680,63179,PRETRIAL,MENDOZA,JOSE,G,Male,Hispanic,08/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +60714,69680,63179,PRETRIAL,MENDOZA,JOSE,G,Male,Hispanic,08/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +60714,69680,63179,PRETRIAL,MENDOZA,JOSE,G,Male,Hispanic,08/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60726,69697,63193,Probation,Couture,Timothy,NULL,Male,Caucasian,09/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +60726,69697,63193,Probation,Couture,Timothy,NULL,Male,Caucasian,09/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.78,10,High,New,1,0 +60726,69697,63193,Probation,Couture,Timothy,NULL,Male,Caucasian,09/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60729,69699,63195,Probation,Bonilla,Matthew,David,Male,Hispanic,05/24/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +60729,69699,63195,Probation,Bonilla,Matthew,David,Male,Hispanic,05/24/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +60729,69699,63195,Probation,Bonilla,Matthew,David,Male,Hispanic,05/24/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +40165,69713,63209,PRETRIAL,HOLMAN,CHRISTIAN,L,Male,African-American,12/28/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +40165,69713,63209,PRETRIAL,HOLMAN,CHRISTIAN,L,Male,African-American,12/28/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +40165,69713,63209,PRETRIAL,HOLMAN,CHRISTIAN,L,Male,African-American,12/28/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60713,69678,63178,PRETRIAL,Lawrence,David,NULL,Male,Caucasian,05/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +60713,69678,63178,PRETRIAL,Lawrence,David,NULL,Male,Caucasian,05/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +60713,69678,63178,PRETRIAL,Lawrence,David,NULL,Male,Caucasian,05/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60723,69692,63189,Probation,Ferdinand,Garth,NULL,Male,Hispanic,05/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/27/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +60723,69692,63189,Probation,Ferdinand,Garth,NULL,Male,Hispanic,05/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +60723,69692,63189,Probation,Ferdinand,Garth,NULL,Male,Hispanic,05/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60734,69706,63202,Probation,Muniz,Andro,NULL,Male,Hispanic,08/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +60734,69706,63202,Probation,Muniz,Andro,NULL,Male,Hispanic,08/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +60734,69706,63202,Probation,Muniz,Andro,NULL,Male,Hispanic,08/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60749,69727,63222,PRETRIAL,Giglio,Lori,NULL,Female,Caucasian,11/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +60749,69727,63222,PRETRIAL,Giglio,Lori,NULL,Female,Caucasian,11/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +60749,69727,63222,PRETRIAL,Giglio,Lori,NULL,Female,Caucasian,11/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +53490,69702,63198,Probation,Williams,Brian,David,Male,African-American,02/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/27/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +53490,69702,63198,Probation,Williams,Brian,David,Male,African-American,02/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +53490,69702,63198,Probation,Williams,Brian,David,Male,African-American,02/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60747,69725,63220,PRETRIAL,Depalma,John,NULL,Male,Caucasian,09/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +60747,69725,63220,PRETRIAL,Depalma,John,NULL,Male,Caucasian,09/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +60747,69725,63220,PRETRIAL,Depalma,John,NULL,Male,Caucasian,09/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60195,69689,62602,PRETRIAL,llanos,iyana,NULL,Female,African-American,03/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,Copy,1,0 +60195,69689,62602,PRETRIAL,llanos,iyana,NULL,Female,African-American,03/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,Copy,1,0 +60195,69689,62602,PRETRIAL,llanos,iyana,NULL,Female,African-American,03/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +35500,69704,63200,Probation,Garcia,Leopoldo,Federico,Male,Hispanic,07/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +35500,69704,63200,Probation,Garcia,Leopoldo,Federico,Male,Hispanic,07/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +35500,69704,63200,Probation,Garcia,Leopoldo,Federico,Male,Hispanic,07/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53878,69710,63206,PRETRIAL,Bergeron,Kayla,NULL,Female,Caucasian,11/15/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +53878,69710,63206,PRETRIAL,Bergeron,Kayla,NULL,Female,Caucasian,11/15/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +53878,69710,63206,PRETRIAL,Bergeron,Kayla,NULL,Female,Caucasian,11/15/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60741,69717,63213,Probation,Newman,Marcus,NULL,Male,African-American,07/09/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/27/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +60741,69717,63213,Probation,Newman,Marcus,NULL,Male,African-American,07/09/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +60741,69717,63213,Probation,Newman,Marcus,NULL,Male,African-American,07/09/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/27/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60715,69681,63180,PRETRIAL,Abdul-Malik,Ameer,NULL,Male,African-American,10/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +60715,69681,63180,PRETRIAL,Abdul-Malik,Ameer,NULL,Male,African-American,10/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +60715,69681,63180,PRETRIAL,Abdul-Malik,Ameer,NULL,Male,African-American,10/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60727,69696,63192,Probation,Orton,Michael,NULL,Male,Caucasian,03/27/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +60727,69696,63192,Probation,Orton,Michael,NULL,Male,Caucasian,03/27/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +60727,69696,63192,Probation,Orton,Michael,NULL,Male,Caucasian,03/27/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +42782,69712,63208,PRETRIAL,MYERS,KIANNA,NULL,Female,Caucasian,10/10/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,4,High,7,Risk of Violence,-1.23,8,High,New,1,0 +42782,69712,63208,PRETRIAL,MYERS,KIANNA,NULL,Female,Caucasian,10/10/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,4,High,8,Risk of Recidivism,-0.03,8,High,New,1,0 +42782,69712,63208,PRETRIAL,MYERS,KIANNA,NULL,Female,Caucasian,10/10/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +11316,69715,63211,PRETRIAL,Igles,Alford,NULL,Male,African-American,10/13/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,New,1,0 +11316,69715,63211,PRETRIAL,Igles,Alford,NULL,Male,African-American,10/13/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +11316,69715,63211,PRETRIAL,Igles,Alford,NULL,Male,African-American,10/13/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +60736,69707,63203,Probation,bailey,raynaldo,NULL,Male,African-American,10/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +60736,69707,63203,Probation,bailey,raynaldo,NULL,Male,African-American,10/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +60736,69707,63203,Probation,bailey,raynaldo,NULL,Male,African-American,10/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60719,69686,63185,PRETRIAL,Choreno,Ignacio,NULL,Male,Hispanic,02/02/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/27/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +60719,69686,63185,PRETRIAL,Choreno,Ignacio,NULL,Male,Hispanic,02/02/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/27/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +60719,69686,63185,PRETRIAL,Choreno,Ignacio,NULL,Male,Hispanic,02/02/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +3179,69720,63130,PRETRIAL,michel,shannon,christine,Female,Caucasian,04/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,Copy,1,0 +3179,69720,63130,PRETRIAL,michel,shannon,christine,Female,Caucasian,04/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,Copy,1,0 +3179,69720,63130,PRETRIAL,michel,shannon,christine,Female,Caucasian,04/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +60718,69684,63183,PRETRIAL,Esporrin,Brian,NULL,Male,Caucasian,09/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +60718,69684,63183,PRETRIAL,Esporrin,Brian,NULL,Male,Caucasian,09/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +60718,69684,63183,PRETRIAL,Esporrin,Brian,NULL,Male,Caucasian,09/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60735,69709,63205,Probation,Davis,Bradley,NULL,Male,Caucasian,08/23/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/27/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +60735,69709,63205,Probation,Davis,Bradley,NULL,Male,Caucasian,08/23/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +60735,69709,63205,Probation,Davis,Bradley,NULL,Male,Caucasian,08/23/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60733,69705,63201,PRETRIAL,GEORGE,LUCAS,NULL,Male,Caucasian,06/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +60733,69705,63201,PRETRIAL,GEORGE,LUCAS,NULL,Male,Caucasian,06/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +60733,69705,63201,PRETRIAL,GEORGE,LUCAS,NULL,Male,Caucasian,06/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60748,69726,63221,Probation,Matthews,Tafolia,NULL,Female,African-American,04/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +60748,69726,63221,Probation,Matthews,Tafolia,NULL,Female,African-American,04/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,8,High,New,1,0 +60748,69726,63221,Probation,Matthews,Tafolia,NULL,Female,African-American,04/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +7564,69679,7156,PRETRIAL,Gispert,Juan,NULL,Male,Caucasian,07/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,Copy,1,0 +7564,69679,7156,PRETRIAL,Gispert,Juan,NULL,Male,Caucasian,07/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,Copy,1,0 +7564,69679,7156,PRETRIAL,Gispert,Juan,NULL,Male,Caucasian,07/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +37689,69721,63216,PRETRIAL,FERGUSON,STERLING,EUGENE,Male,African-American,09/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +37689,69721,63216,PRETRIAL,FERGUSON,STERLING,EUGENE,Male,African-American,09/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +37689,69721,63216,PRETRIAL,FERGUSON,STERLING,EUGENE,Male,African-American,09/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60722,69691,63188,PRETRIAL,Ramage,Christina,NULL,Female,Caucasian,01/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +60722,69691,63188,PRETRIAL,Ramage,Christina,NULL,Female,Caucasian,01/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,2,Medium,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +60722,69691,63188,PRETRIAL,Ramage,Christina,NULL,Female,Caucasian,01/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60724,69693,63190,Probation,Cornish,Leslie,NULL,Female,Caucasian,11/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +60724,69693,63190,Probation,Cornish,Leslie,NULL,Female,Caucasian,11/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +60724,69693,63190,Probation,Cornish,Leslie,NULL,Female,Caucasian,11/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60739,69714,63210,PRETRIAL,COTILLO,STEPHEN,NULL,Male,Caucasian,08/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/27/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +60739,69714,63210,PRETRIAL,COTILLO,STEPHEN,NULL,Male,Caucasian,08/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +60739,69714,63210,PRETRIAL,COTILLO,STEPHEN,NULL,Male,Caucasian,08/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60751,69728,63223,PRETRIAL,Robinson,Andrew,NULL,Male,African-American,07/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +60751,69728,63223,PRETRIAL,Robinson,Andrew,NULL,Male,African-American,07/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +60751,69728,63223,PRETRIAL,Robinson,Andrew,NULL,Male,African-American,07/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60737,69708,63204,Probation,Manuel,Donald,NULL,Male,Caucasian,09/08/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +60737,69708,63204,Probation,Manuel,Donald,NULL,Male,Caucasian,09/08/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +60737,69708,63204,Probation,Manuel,Donald,NULL,Male,Caucasian,09/08/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60743,69719,63215,PRETRIAL,Baker,Heather,NULL,Female,Caucasian,07/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +60743,69719,63215,PRETRIAL,Baker,Heather,NULL,Female,Caucasian,07/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +60743,69719,63215,PRETRIAL,Baker,Heather,NULL,Female,Caucasian,07/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60728,69698,63194,Probation,keenan,michael,NULL,Male,Caucasian,02/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +60728,69698,63194,Probation,keenan,michael,NULL,Male,Caucasian,02/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +60728,69698,63194,Probation,keenan,michael,NULL,Male,Caucasian,02/24/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60740,69716,63212,Probation,HOOSUE,PATRICK,NULL,Male,Hispanic,09/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/27/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +60740,69716,63212,Probation,HOOSUE,PATRICK,NULL,Male,Hispanic,09/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/27/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +60740,69716,63212,Probation,HOOSUE,PATRICK,NULL,Male,Hispanic,09/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60721,69690,63187,PRETRIAL,Young,Jeremiah,NULL,Female,African-American,07/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +60721,69690,63187,PRETRIAL,Young,Jeremiah,NULL,Female,African-American,07/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,4,High,8,Risk of Recidivism,0.5,10,High,New,1,0 +60721,69690,63187,PRETRIAL,Young,Jeremiah,NULL,Female,African-American,07/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60746,69724,63219,PRETRIAL,Rodriguez-Hernandez,Reinaldo,NULL,Male,Hispanic,10/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +60746,69724,63219,PRETRIAL,Rodriguez-Hernandez,Reinaldo,NULL,Male,Hispanic,10/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +60746,69724,63219,PRETRIAL,Rodriguez-Hernandez,Reinaldo,NULL,Male,Hispanic,10/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +54819,62304,56539,Probation,Smart,Cambrell,NULL,Male,African-American,10/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +54819,62304,56539,Probation,Smart,Cambrell,NULL,Male,African-American,10/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.09,10,High,New,1,0 +54819,62304,56539,Probation,Smart,Cambrell,NULL,Male,African-American,10/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60712,69677,63177,PRETRIAL,Laffite,Daniel,Jovon,Male,African-American,11/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +60712,69677,63177,PRETRIAL,Laffite,Daniel,Jovon,Male,African-American,11/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +60712,69677,63177,PRETRIAL,Laffite,Daniel,Jovon,Male,African-American,11/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60738,69711,63207,Probation,Daley,Melford,NULL,Male,African-American,06/01/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/27/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +60738,69711,63207,Probation,Daley,Melford,NULL,Male,African-American,06/01/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +60738,69711,63207,Probation,Daley,Melford,NULL,Male,African-American,06/01/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60732,69703,63199,Probation,Casellas,Brandon,NULL,Male,Hispanic,12/31/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +60732,69703,63199,Probation,Casellas,Brandon,NULL,Male,Hispanic,12/31/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +60732,69703,63199,Probation,Casellas,Brandon,NULL,Male,Hispanic,12/31/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60716,69682,63181,PRETRIAL,CAREY,CECIL,NULL,Male,African-American,11/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +60716,69682,63181,PRETRIAL,CAREY,CECIL,NULL,Male,African-American,11/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +60716,69682,63181,PRETRIAL,CAREY,CECIL,NULL,Male,African-American,11/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60720,69687,63186,PRETRIAL,MALGAARD,DANIEL,NULL,Male,Caucasian,03/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +60720,69687,63186,PRETRIAL,MALGAARD,DANIEL,NULL,Male,Caucasian,03/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +60720,69687,63186,PRETRIAL,MALGAARD,DANIEL,NULL,Male,Caucasian,03/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60725,69695,63191,PRETRIAL,Guadagino,Judith,Snowden,Female,Caucasian,02/12/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,1/27/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +60725,69695,63191,PRETRIAL,Guadagino,Judith,Snowden,Female,Caucasian,02/12/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,1/27/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +60725,69695,63191,PRETRIAL,Guadagino,Judith,Snowden,Female,Caucasian,02/12/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,1/27/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60777,69761,63253,Probation,Carragino,Michael,Joseph,Male,Caucasian,12/26/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +60777,69761,63253,Probation,Carragino,Michael,Joseph,Male,Caucasian,12/26/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +60777,69761,63253,Probation,Carragino,Michael,Joseph,Male,Caucasian,12/26/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +17688,69768,63258,PRETRIAL,PAVONE,MICHAEL,T,Male,Caucasian,01/24/70,17,All Scales,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +17688,69768,63258,PRETRIAL,PAVONE,MICHAEL,T,Male,Caucasian,01/24/70,17,All Scales,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-0.4,4,Low,New,1,0 +17688,69768,63258,PRETRIAL,PAVONE,MICHAEL,T,Male,Caucasian,01/24/70,17,All Scales,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +60760,69740,63234,Probation,latortue,michelle,NULL,Female,African-American,09/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +60760,69740,63234,Probation,latortue,michelle,NULL,Female,African-American,09/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +60760,69740,63234,Probation,latortue,michelle,NULL,Female,African-American,09/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60783,69774,63262,Probation,gwaltney,jennifer,NULL,Female,Caucasian,10/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +60783,69774,63262,Probation,gwaltney,jennifer,NULL,Female,Caucasian,10/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +60783,69774,63262,Probation,gwaltney,jennifer,NULL,Female,Caucasian,10/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +43821,69732,63227,PRETRIAL,FRANK,CACHALONI,NULL,Male,Other,10/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +43821,69732,63227,PRETRIAL,FRANK,CACHALONI,NULL,Male,Other,10/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +43821,69732,63227,PRETRIAL,FRANK,CACHALONI,NULL,Male,Other,10/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60770,69753,63245,Probation,Mendoza Guillen,Erian,Jadiel,Male,Hispanic,06/06/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +60770,69753,63245,Probation,Mendoza Guillen,Erian,Jadiel,Male,Hispanic,06/06/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +60770,69753,63245,Probation,Mendoza Guillen,Erian,Jadiel,Male,Hispanic,06/06/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +32000,69760,63252,PRETRIAL,WALCZAK,DAVID,NULL,Male,Caucasian,10/18/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +32000,69760,63252,PRETRIAL,WALCZAK,DAVID,NULL,Male,Caucasian,10/18/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +32000,69760,63252,PRETRIAL,WALCZAK,DAVID,NULL,Male,Caucasian,10/18/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60763,69745,63239,Probation,Cambareri,John,Erik,Male,Caucasian,10/10/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/28/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +60763,69745,63239,Probation,Cambareri,John,Erik,Male,Caucasian,10/10/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/28/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +60763,69745,63239,Probation,Cambareri,John,Erik,Male,Caucasian,10/10/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60767,69750,63242,DRRD,Nuby,Brandon,NULL,Male,African-American,04/24/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +60767,69750,63242,DRRD,Nuby,Brandon,NULL,Male,African-American,04/24/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +60767,69750,63242,DRRD,Nuby,Brandon,NULL,Male,African-American,04/24/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +48685,69737,49401,PRETRIAL,Bryant,Michelle,Latavia,Female,African-American,01/08/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,Copy,1,0 +48685,69737,49401,PRETRIAL,Bryant,Michelle,Latavia,Female,African-American,01/08/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,Copy,1,0 +48685,69737,49401,PRETRIAL,Bryant,Michelle,Latavia,Female,African-American,01/08/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +11232,69771,50528,PRETRIAL,NICOLAS,AUDLEY,O,Male,African-American,12/04/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,Copy,1,0 +11232,69771,50528,PRETRIAL,NICOLAS,AUDLEY,O,Male,African-American,12/04/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,Copy,1,0 +11232,69771,50528,PRETRIAL,NICOLAS,AUDLEY,O,Male,African-American,12/04/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +60752,69729,63224,PRETRIAL,Alexis,Everson,Zeemaka,Male,Other,05/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +60752,69729,63224,PRETRIAL,Alexis,Everson,Zeemaka,Male,Other,05/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +60752,69729,63224,PRETRIAL,Alexis,Everson,Zeemaka,Male,Other,05/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60779,69766,63256,Probation,sealy,mariano,NULL,Male,African-American,03/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/28/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +60779,69766,63256,Probation,sealy,mariano,NULL,Male,African-American,03/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +60779,69766,63256,Probation,sealy,mariano,NULL,Male,African-American,03/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60775,69758,63250,Probation,Hernandezposadas,German,Mabricio,Male,Hispanic,10/26/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +60775,69758,63250,Probation,Hernandezposadas,German,Mabricio,Male,Hispanic,10/26/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +60775,69758,63250,Probation,Hernandezposadas,German,Mabricio,Male,Hispanic,10/26/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60754,69735,63230,PRETRIAL,Vives,Edwin,NULL,Male,Hispanic,11/14/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,1/28/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +60754,69735,63230,PRETRIAL,Vives,Edwin,NULL,Male,Hispanic,11/14/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +60754,69735,63230,PRETRIAL,Vives,Edwin,NULL,Male,Hispanic,11/14/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +60761,69742,63236,PRETRIAL,Lingwood,Matthew,NULL,Male,Caucasian,08/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +60761,69742,63236,PRETRIAL,Lingwood,Matthew,NULL,Male,Caucasian,08/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +60761,69742,63236,PRETRIAL,Lingwood,Matthew,NULL,Male,Caucasian,08/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +37553,69749,63241,PRETRIAL,PATTERSON,JOHN,ROBERT,Male,Caucasian,04/28/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/28/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +37553,69749,63241,PRETRIAL,PATTERSON,JOHN,ROBERT,Male,Caucasian,04/28/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +37553,69749,63241,PRETRIAL,PATTERSON,JOHN,ROBERT,Male,Caucasian,04/28/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +29963,69763,28930,PRETRIAL,Fernandez,Abel,Jesus,Male,Caucasian,09/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,Copy,1,0 +29963,69763,28930,PRETRIAL,Fernandez,Abel,Jesus,Male,Caucasian,09/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,Copy,1,0 +29963,69763,28930,PRETRIAL,Fernandez,Abel,Jesus,Male,Caucasian,09/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +39329,69770,63260,PRETRIAL,BRINO,SADATE,NULL,Male,Other,05/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +39329,69770,63260,PRETRIAL,BRINO,SADATE,NULL,Male,Other,05/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +39329,69770,63260,PRETRIAL,BRINO,SADATE,NULL,Male,Other,05/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60782,69772,63261,Probation,Diaz,Richard,NULL,Male,Hispanic,10/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +60782,69772,63261,Probation,Diaz,Richard,NULL,Male,Hispanic,10/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +60782,69772,63261,Probation,Diaz,Richard,NULL,Male,Hispanic,10/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +39444,69730,63225,PRETRIAL,Narcisse,Louivens,NULL,Male,African-American,07/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +39444,69730,63225,PRETRIAL,Narcisse,Louivens,NULL,Male,African-American,07/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,4,High,8,Risk of Recidivism,0.48,9,High,New,1,0 +39444,69730,63225,PRETRIAL,Narcisse,Louivens,NULL,Male,African-American,07/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59845,69765,62213,Probation,padron,michael,NULL,Male,Hispanic,09/06/74,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,1/28/14 0:00,2,Medium,7,Risk of Violence,-2.97,1,Low,New,1,0 +59845,69765,62213,Probation,padron,michael,NULL,Male,Hispanic,09/06/74,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,1/28/14 0:00,2,Medium,8,Risk of Recidivism,0.18,7,Medium,New,1,0 +59845,69765,62213,Probation,padron,michael,NULL,Male,Hispanic,09/06/74,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,1/28/14 0:00,2,Medium,18,Risk of Failure to Appear,34,9,High,New,1,0 +60765,69744,63238,Probation,lamontagne,kathyrn,NULL,Female,Caucasian,07/01/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/28/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +60765,69744,63238,Probation,lamontagne,kathyrn,NULL,Female,Caucasian,07/01/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +60765,69744,63238,Probation,lamontagne,kathyrn,NULL,Female,Caucasian,07/01/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60768,69751,63243,PRETRIAL,Bailey,Sadieanne,Natalee,Female,African-American,10/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/28/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +60768,69751,63243,PRETRIAL,Bailey,Sadieanne,Natalee,Female,African-American,10/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +60768,69751,63243,PRETRIAL,Bailey,Sadieanne,Natalee,Female,African-American,10/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60773,69756,63248,DRRD,O'Daniel,Donald,NULL,Male,Caucasian,03/17/58,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +60773,69756,63248,DRRD,O'Daniel,Donald,NULL,Male,Caucasian,03/17/58,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +60773,69756,63248,DRRD,O'Daniel,Donald,NULL,Male,Caucasian,03/17/58,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +47455,69741,63235,PRETRIAL,Neil,Valerio,NULL,Male,Caucasian,05/20/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +47455,69741,63235,PRETRIAL,Neil,Valerio,NULL,Male,Caucasian,05/20/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +47455,69741,63235,PRETRIAL,Neil,Valerio,NULL,Male,Caucasian,05/20/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60771,69754,63246,Probation,Thibault,Sherry,NULL,Female,Caucasian,06/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/28/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +60771,69754,63246,Probation,Thibault,Sherry,NULL,Female,Caucasian,06/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/28/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +60771,69754,63246,Probation,Thibault,Sherry,NULL,Female,Caucasian,06/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60753,69733,63228,PRETRIAL,Goodrum,Brushod,Deon,Male,African-American,04/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.85,9,High,New,1,0 +60753,69733,63228,PRETRIAL,Goodrum,Brushod,Deon,Male,African-American,04/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +60753,69733,63228,PRETRIAL,Goodrum,Brushod,Deon,Male,African-American,04/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60778,69762,63254,Probation,hellmuth,robert,NULL,Male,Caucasian,04/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/28/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +60778,69762,63254,Probation,hellmuth,robert,NULL,Male,Caucasian,04/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +60778,69762,63254,Probation,hellmuth,robert,NULL,Male,Caucasian,04/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +6944,69731,63226,PRETRIAL,DENMARK,JACKIE,ALEXANDER,Male,African-American,07/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,4,High,7,Risk of Violence,-0.54,10,High,New,1,0 +6944,69731,63226,PRETRIAL,DENMARK,JACKIE,ALEXANDER,Male,African-American,07/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +6944,69731,63226,PRETRIAL,DENMARK,JACKIE,ALEXANDER,Male,African-American,07/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60759,69738,63232,Probation,Daniel,John,Stevens,Male,African-American,09/15/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +60759,69738,63232,Probation,Daniel,John,Stevens,Male,African-American,09/15/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +60759,69738,63232,Probation,Daniel,John,Stevens,Male,African-American,09/15/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60776,69759,63251,Probation,Perez,Ohichi,NULL,Female,Hispanic,09/25/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +60776,69759,63251,Probation,Perez,Ohichi,NULL,Female,Hispanic,09/25/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +60776,69759,63251,Probation,Perez,Ohichi,NULL,Female,Hispanic,09/25/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +30343,69734,63229,PRETRIAL,Strachan,Shaun,NULL,Male,African-American,09/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +30343,69734,63229,PRETRIAL,Strachan,Shaun,NULL,Male,African-American,09/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +30343,69734,63229,PRETRIAL,Strachan,Shaun,NULL,Male,African-American,09/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/28/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60755,69736,63231,PRETRIAL,JOHNSON,CHRISTIAN,NULL,Male,Caucasian,01/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/28/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +60755,69736,63231,PRETRIAL,JOHNSON,CHRISTIAN,NULL,Male,Caucasian,01/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +60755,69736,63231,PRETRIAL,JOHNSON,CHRISTIAN,NULL,Male,Caucasian,01/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60772,69755,63247,Probation,mitchell,james,NULL,Male,African-American,12/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +60772,69755,63247,Probation,mitchell,james,NULL,Male,African-American,12/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +60772,69755,63247,Probation,mitchell,james,NULL,Male,African-American,12/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60774,69757,63249,PRETRIAL,Tetoff,Anthony,NULL,Male,Caucasian,03/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +60774,69757,63249,PRETRIAL,Tetoff,Anthony,NULL,Male,Caucasian,03/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +60774,69757,63249,PRETRIAL,Tetoff,Anthony,NULL,Male,Caucasian,03/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50537,69764,63255,PRETRIAL,Canion,Isaac,NULL,Male,African-American,09/29/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +50537,69764,63255,PRETRIAL,Canion,Isaac,NULL,Male,African-American,09/29/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +50537,69764,63255,PRETRIAL,Canion,Isaac,NULL,Male,African-American,09/29/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +60610,69748,63070,PRETRIAL,Sibblies,Keanne,Antoinette,Female,African-American,11/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,Copy,1,0 +60610,69748,63070,PRETRIAL,Sibblies,Keanne,Antoinette,Female,African-American,11/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,Copy,1,0 +60610,69748,63070,PRETRIAL,Sibblies,Keanne,Antoinette,Female,African-American,11/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +60781,69769,63259,Probation,Simmonds,Luchien,NULL,Male,African-American,07/02/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/28/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +60781,69769,63259,Probation,Simmonds,Luchien,NULL,Male,African-American,07/02/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/28/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +60781,69769,63259,Probation,Simmonds,Luchien,NULL,Male,African-American,07/02/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60762,69743,63237,Probation,Kinsella,John,NULL,Male,Caucasian,12/29/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +60762,69743,63237,Probation,Kinsella,John,NULL,Male,Caucasian,12/29/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +60762,69743,63237,Probation,Kinsella,John,NULL,Male,Caucasian,12/29/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60769,69752,63244,PRETRIAL,PEARARAY,BALDEO,NULL,Male,Other,07/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/28/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +60769,69752,63244,PRETRIAL,PEARARAY,BALDEO,NULL,Male,Other,07/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/28/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +60769,69752,63244,PRETRIAL,PEARARAY,BALDEO,NULL,Male,Other,07/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +37618,69739,63233,PRETRIAL,Studemire,Corey,NULL,Male,African-American,04/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +37618,69739,63233,PRETRIAL,Studemire,Corey,NULL,Male,African-American,04/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,4,High,8,Risk of Recidivism,0.31,9,High,New,1,0 +37618,69739,63233,PRETRIAL,Studemire,Corey,NULL,Male,African-American,04/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/28/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +60800,69790,63278,PRETRIAL,Jackson,Mellick,NULL,Male,African-American,04/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/14 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +60800,69790,63278,PRETRIAL,Jackson,Mellick,NULL,Male,African-American,04/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +60800,69790,63278,PRETRIAL,Jackson,Mellick,NULL,Male,African-American,04/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +30899,69811,63298,PRETRIAL,Cunningham,Shaquetta,Lavette,Female,African-American,07/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +30899,69811,63298,PRETRIAL,Cunningham,Shaquetta,Lavette,Female,African-American,07/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,7,Medium,New,1,0 +30899,69811,63298,PRETRIAL,Cunningham,Shaquetta,Lavette,Female,African-American,07/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60804,69794,63282,Probation,solis,joel,NULL,Male,Caucasian,01/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +60804,69794,63282,Probation,solis,joel,NULL,Male,Caucasian,01/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +60804,69794,63282,Probation,solis,joel,NULL,Male,Caucasian,01/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60817,69808,63295,PRETRIAL,MEJIA,EDWARD,NULL,Male,Hispanic,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +60817,69808,63295,PRETRIAL,MEJIA,EDWARD,NULL,Male,Hispanic,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +60817,69808,63295,PRETRIAL,MEJIA,EDWARD,NULL,Male,Hispanic,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60822,69815,63302,Probation,NGUYEN,HUY,NULL,Male,Asian,03/08/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +60822,69815,63302,Probation,NGUYEN,HUY,NULL,Male,Asian,03/08/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +60822,69815,63302,Probation,NGUYEN,HUY,NULL,Male,Asian,03/08/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60808,69799,63286,Probation,moranherrera,jose,NULL,Male,Hispanic,06/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +60808,69799,63286,Probation,moranherrera,jose,NULL,Male,Hispanic,06/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +60808,69799,63286,Probation,moranherrera,jose,NULL,Male,Hispanic,06/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60819,69813,63300,Probation,Downing,Joshua,NULL,Male,Caucasian,12/18/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +60819,69813,63300,Probation,Downing,Joshua,NULL,Male,Caucasian,12/18/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +60819,69813,63300,Probation,Downing,Joshua,NULL,Male,Caucasian,12/18/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60790,69778,63266,PRETRIAL,Adams,William,NULL,Male,African-American,03/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +60790,69778,63266,PRETRIAL,Adams,William,NULL,Male,African-American,03/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +60790,69778,63266,PRETRIAL,Adams,William,NULL,Male,African-American,03/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60796,69785,63273,Probation,jones,justin,NULL,Male,African-American,11/08/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +60796,69785,63273,Probation,jones,justin,NULL,Male,African-American,11/08/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.4,4,Low,New,1,0 +60796,69785,63273,Probation,jones,justin,NULL,Male,African-American,11/08/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,2,Medium,18,Risk of Failure to Appear,19,2,Low,New,1,0 +60802,69792,63280,Probation,sutton,michael,NULL,Male,Caucasian,05/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +60802,69792,63280,Probation,sutton,michael,NULL,Male,Caucasian,05/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +60802,69792,63280,Probation,sutton,michael,NULL,Male,Caucasian,05/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60815,69806,63293,PRETRIAL,GRIFFITH,JOSEPH,NULL,Male,Caucasian,06/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +60815,69806,63293,PRETRIAL,GRIFFITH,JOSEPH,NULL,Male,Caucasian,06/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +60815,69806,63293,PRETRIAL,GRIFFITH,JOSEPH,NULL,Male,Caucasian,06/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60813,69804,63291,PRETRIAL,IRWIN,TAYLOR,NULL,Female,Caucasian,08/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +60813,69804,63291,PRETRIAL,IRWIN,TAYLOR,NULL,Female,Caucasian,08/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +60813,69804,63291,PRETRIAL,IRWIN,TAYLOR,NULL,Female,Caucasian,08/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60806,69796,63284,Probation,Jean-Baptist,Frito,NULL,Male,African-American,01/18/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +60806,69796,63284,Probation,Jean-Baptist,Frito,NULL,Male,African-American,01/18/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +60806,69796,63284,Probation,Jean-Baptist,Frito,NULL,Male,African-American,01/18/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +48334,69817,63303,Probation,spencer,cameron,NULL,Male,African-American,01/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +48334,69817,63303,Probation,spencer,cameron,NULL,Male,African-American,01/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +48334,69817,63303,Probation,spencer,cameron,NULL,Male,African-American,01/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60794,69783,63271,PRETRIAL,Underwood,Stephanie,NULL,Female,African-American,03/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +60794,69783,63271,PRETRIAL,Underwood,Stephanie,NULL,Female,African-American,03/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +60794,69783,63271,PRETRIAL,Underwood,Stephanie,NULL,Female,African-American,03/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60810,69801,63288,Probation,DITTMEIER,MICHAEL,ANDREW,Male,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +60810,69801,63288,Probation,DITTMEIER,MICHAEL,ANDREW,Male,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +60810,69801,63288,Probation,DITTMEIER,MICHAEL,ANDREW,Male,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60791,69780,63268,PRETRIAL,LUCAS,JASEN,DANIEL,Male,Caucasian,09/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/29/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +60791,69780,63268,PRETRIAL,LUCAS,JASEN,DANIEL,Male,Caucasian,09/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +60791,69780,63268,PRETRIAL,LUCAS,JASEN,DANIEL,Male,Caucasian,09/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60798,69788,63276,PRETRIAL,Zukowski,Henry,NULL,Male,Caucasian,07/31/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +60798,69788,63276,PRETRIAL,Zukowski,Henry,NULL,Male,Caucasian,07/31/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +60798,69788,63276,PRETRIAL,Zukowski,Henry,NULL,Male,Caucasian,07/31/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60784,69775,63263,PRETRIAL,Smith,James,Kinsey,Male,Caucasian,12/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +60784,69775,63263,PRETRIAL,Smith,James,Kinsey,Male,Caucasian,12/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +60784,69775,63263,PRETRIAL,Smith,James,Kinsey,Male,Caucasian,12/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +54775,69809,63296,Probation,rex,leslie,NULL,Female,Caucasian,08/24/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +54775,69809,63296,Probation,rex,leslie,NULL,Female,Caucasian,08/24/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +54775,69809,63296,Probation,rex,leslie,NULL,Female,Caucasian,08/24/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60816,69807,63294,Probation,GARCIA,CARIDAD,NULL,Female,Hispanic,11/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +60816,69807,63294,Probation,GARCIA,CARIDAD,NULL,Female,Hispanic,11/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +60816,69807,63294,Probation,GARCIA,CARIDAD,NULL,Female,Hispanic,11/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +60789,69777,63265,PRETRIAL,Mckever,Daryle,NULL,Male,African-American,05/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +60789,69777,63265,PRETRIAL,Mckever,Daryle,NULL,Male,African-American,05/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +60789,69777,63265,PRETRIAL,Mckever,Daryle,NULL,Male,African-American,05/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60820,69812,63299,Probation,estinord,edna,NULL,Female,African-American,04/11/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +60820,69812,63299,Probation,estinord,edna,NULL,Female,African-American,04/11/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +60820,69812,63299,Probation,estinord,edna,NULL,Female,African-American,04/11/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60807,69798,63285,PRETRIAL,Thomas,Travis,NULL,Male,African-American,08/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/29/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +60807,69798,63285,PRETRIAL,Thomas,Travis,NULL,Male,African-American,08/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +60807,69798,63285,PRETRIAL,Thomas,Travis,NULL,Male,African-American,08/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/29/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60801,69791,63279,Probation,George,Jason,NULL,Male,Asian,09/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +60801,69791,63279,Probation,George,Jason,NULL,Male,Asian,09/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +60801,69791,63279,Probation,George,Jason,NULL,Male,Asian,09/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60809,69800,63287,Probation,Hannon,Sean,NULL,Male,Caucasian,09/29/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +60809,69800,63287,Probation,Hannon,Sean,NULL,Male,Caucasian,09/29/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +60809,69800,63287,Probation,Hannon,Sean,NULL,Male,Caucasian,09/29/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60821,69814,63301,Probation,Ibanez,Julio,Eddy,Male,Hispanic,10/28/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +60821,69814,63301,Probation,Ibanez,Julio,Eddy,Male,Hispanic,10/28/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +60821,69814,63301,Probation,Ibanez,Julio,Eddy,Male,Hispanic,10/28/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60788,69776,63264,PRETRIAL,Jeanpierre,Brunsweck,NULL,Male,African-American,01/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +60788,69776,63264,PRETRIAL,Jeanpierre,Brunsweck,NULL,Male,African-American,01/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +60788,69776,63264,PRETRIAL,Jeanpierre,Brunsweck,NULL,Male,African-American,01/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60797,69787,63275,Probation,laws,curly,NULL,Male,African-American,04/08/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +60797,69787,63275,Probation,laws,curly,NULL,Male,African-American,04/08/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +60797,69787,63275,Probation,laws,curly,NULL,Male,African-American,04/08/40,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60143,69797,62542,PRETRIAL,White,Hassheim,NULL,Male,African-American,10/31/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/14 0:00,4,High,7,Risk of Violence,-0.42,10,High,Copy,1,0 +60143,69797,62542,PRETRIAL,White,Hassheim,NULL,Male,African-American,10/31/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/14 0:00,4,High,8,Risk of Recidivism,0.16,8,High,Copy,1,0 +60143,69797,62542,PRETRIAL,White,Hassheim,NULL,Male,African-American,10/31/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,1/29/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +60814,69805,63292,Probation,Carrington,Frederick,NULL,Male,Caucasian,01/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +60814,69805,63292,Probation,Carrington,Frederick,NULL,Male,Caucasian,01/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +60814,69805,63292,Probation,Carrington,Frederick,NULL,Male,Caucasian,01/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60795,69784,63272,PRETRIAL,Guerrier,Sarah,NULL,Female,Other,09/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +60795,69784,63272,PRETRIAL,Guerrier,Sarah,NULL,Female,Other,09/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +60795,69784,63272,PRETRIAL,Guerrier,Sarah,NULL,Female,Other,09/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60826,69818,63304,Probation,ROSS,MARVIN,LEE,Male,African-American,09/21/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +60826,69818,63304,Probation,ROSS,MARVIN,LEE,Male,African-American,09/21/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +60826,69818,63304,Probation,ROSS,MARVIN,LEE,Male,African-American,09/21/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60812,69803,63290,Probation,constant,jones,NULL,Male,African-American,04/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,New,1,0 +60812,69803,63290,Probation,constant,jones,NULL,Male,African-American,04/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +60812,69803,63290,Probation,constant,jones,NULL,Male,African-American,04/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60792,69781,63269,PRETRIAL,ALLEN,BRIAN,KEITH,Male,African-American,03/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +60792,69781,63269,PRETRIAL,ALLEN,BRIAN,KEITH,Male,African-American,03/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +60792,69781,63269,PRETRIAL,ALLEN,BRIAN,KEITH,Male,African-American,03/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60793,69782,63270,PRETRIAL,Woodard,Brittany,Denise,Female,African-American,03/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +60793,69782,63270,PRETRIAL,Woodard,Brittany,Denise,Female,African-American,03/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +60793,69782,63270,PRETRIAL,Woodard,Brittany,Denise,Female,African-American,03/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60799,69789,63277,Probation,Burton,Roshane,NULL,Male,African-American,03/01/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/29/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +60799,69789,63277,Probation,Burton,Roshane,NULL,Male,African-American,03/01/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/29/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +60799,69789,63277,Probation,Burton,Roshane,NULL,Male,African-American,03/01/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60805,69795,63283,Probation,VERA,EDUARDO,NULL,Male,Hispanic,11/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +60805,69795,63283,Probation,VERA,EDUARDO,NULL,Male,Hispanic,11/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +60805,69795,63283,Probation,VERA,EDUARDO,NULL,Male,Hispanic,11/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60811,69802,63289,PRETRIAL,Jackson,Mariah,S,Female,African-American,02/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/29/14 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +60811,69802,63289,PRETRIAL,Jackson,Mariah,S,Female,African-American,02/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/29/14 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +60811,69802,63289,PRETRIAL,Jackson,Mariah,S,Female,African-American,02/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,1/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56147,69823,63309,PRETRIAL,ROA,JESUS,NULL,Male,Caucasian,07/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +56147,69823,63309,PRETRIAL,ROA,JESUS,NULL,Male,Caucasian,07/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +56147,69823,63309,PRETRIAL,ROA,JESUS,NULL,Male,Caucasian,07/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +3372,69831,63316,Probation,Freeman,Willis,NULL,Male,African-American,06/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +3372,69831,63316,Probation,Freeman,Willis,NULL,Male,African-American,06/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +3372,69831,63316,Probation,Freeman,Willis,NULL,Male,African-American,06/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +53868,69860,63342,PRETRIAL,hurtado,david,NULL,Male,Caucasian,05/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +53868,69860,63342,PRETRIAL,hurtado,david,NULL,Male,Caucasian,05/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +53868,69860,63342,PRETRIAL,hurtado,david,NULL,Male,Caucasian,05/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60848,69852,63335,Probation,Torresgalvan,Obdulio,NULL,Male,Hispanic,01/08/65,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/30/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +60848,69852,63335,Probation,Torresgalvan,Obdulio,NULL,Male,Hispanic,01/08/65,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/30/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +60848,69852,63335,Probation,Torresgalvan,Obdulio,NULL,Male,Hispanic,01/08/65,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50212,69839,51193,PRETRIAL,Jackson,Bryan,Shaun,Male,African-American,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,Copy,1,0 +50212,69839,51193,PRETRIAL,Jackson,Bryan,Shaun,Male,African-American,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,Copy,1,0 +50212,69839,51193,PRETRIAL,Jackson,Bryan,Shaun,Male,African-American,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +28758,69847,63330,PRETRIAL,Murphy,Terrance,NULL,Male,African-American,09/15/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/30/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +28758,69847,63330,PRETRIAL,Murphy,Terrance,NULL,Male,African-American,09/15/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/30/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +28758,69847,63330,PRETRIAL,Murphy,Terrance,NULL,Male,African-American,09/15/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +38085,69826,37505,PRETRIAL,Antoine,Lucien,NULL,Male,Other,07/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,Copy,1,0 +38085,69826,37505,PRETRIAL,Antoine,Lucien,NULL,Male,Other,07/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,Copy,1,0 +38085,69826,37505,PRETRIAL,Antoine,Lucien,NULL,Male,Other,07/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +57509,69844,59621,PRETRIAL,Dundis,Joshua,NULL,Male,Caucasian,01/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,Copy,1,0 +57509,69844,59621,PRETRIAL,Dundis,Joshua,NULL,Male,Caucasian,01/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,Copy,1,0 +57509,69844,59621,PRETRIAL,Dundis,Joshua,NULL,Male,Caucasian,01/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +60833,69828,63313,PRETRIAL,Higgs,Shakeria,NULL,Female,African-American,05/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +60833,69828,63313,PRETRIAL,Higgs,Shakeria,NULL,Female,African-American,05/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +60833,69828,63313,PRETRIAL,Higgs,Shakeria,NULL,Female,African-American,05/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60838,69835,63320,PRETRIAL,DINITTO,DOMINICK,MARK,Male,Caucasian,06/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +60838,69835,63320,PRETRIAL,DINITTO,DOMINICK,MARK,Male,Caucasian,06/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +60838,69835,63320,PRETRIAL,DINITTO,DOMINICK,MARK,Male,Caucasian,06/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60844,69842,63326,Probation,Joachin,Edsonne,NULL,Male,African-American,06/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +60844,69842,63326,Probation,Joachin,Edsonne,NULL,Male,African-American,06/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.09,10,High,New,1,0 +60844,69842,63326,Probation,Joachin,Edsonne,NULL,Male,African-American,06/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60828,69821,63307,PRETRIAL,Tommer,Ira,NULL,Male,African-American,09/13/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +60828,69821,63307,PRETRIAL,Tommer,Ira,NULL,Male,African-American,09/13/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +60828,69821,63307,PRETRIAL,Tommer,Ira,NULL,Male,African-American,09/13/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60836,69833,63318,Probation,Palazzolo,Michelle,NULL,Female,Caucasian,06/21/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/30/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +60836,69833,63318,Probation,Palazzolo,Michelle,NULL,Female,Caucasian,06/21/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/30/14 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +60836,69833,63318,Probation,Palazzolo,Michelle,NULL,Female,Caucasian,06/21/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60840,69837,63322,Probation,Skaro,Matthew,NULL,Male,Caucasian,11/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +60840,69837,63322,Probation,Skaro,Matthew,NULL,Male,Caucasian,11/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +60840,69837,63322,Probation,Skaro,Matthew,NULL,Male,Caucasian,11/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60850,69854,63337,Probation,mills,quianti,NULL,Female,African-American,05/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/30/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +60850,69854,63337,Probation,mills,quianti,NULL,Female,African-American,05/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/30/14 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +60850,69854,63337,Probation,mills,quianti,NULL,Female,African-American,05/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59124,69858,61400,Probation,JAMES,DARIUS,R,Male,African-American,08/18/85,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/30/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +59124,69858,61400,Probation,JAMES,DARIUS,R,Male,African-American,08/18/85,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/30/14 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +59124,69858,61400,Probation,JAMES,DARIUS,R,Male,African-American,08/18/85,17,All Scales,Intake,English,Conditional Release,Probation,Single,1/30/14 0:00,4,High,18,Risk of Failure to Appear,22,4,Low,New,1,0 +60829,69822,63308,PRETRIAL,Figueroa,Alexandra,M,Female,Caucasian,02/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +60829,69822,63308,PRETRIAL,Figueroa,Alexandra,M,Female,Caucasian,02/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +60829,69822,63308,PRETRIAL,Figueroa,Alexandra,M,Female,Caucasian,02/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60851,69856,63339,Probation,bingham,Robert,allen,Male,African-American,02/27/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/30/14 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +60851,69856,63339,Probation,bingham,Robert,allen,Male,African-American,02/27/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +60851,69856,63339,Probation,bingham,Robert,allen,Male,African-American,02/27/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,1/30/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60834,69830,63315,PRETRIAL,ADEYMI,JUSTIN,NULL,Male,African-American,09/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +60834,69830,63315,PRETRIAL,ADEYMI,JUSTIN,NULL,Male,African-American,09/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +60834,69830,63315,PRETRIAL,ADEYMI,JUSTIN,NULL,Male,African-American,09/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60846,69848,63331,Probation,Vazquez,Roderico,NULL,Male,Hispanic,06/26/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +60846,69848,63331,Probation,Vazquez,Roderico,NULL,Male,Hispanic,06/26/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +60846,69848,63331,Probation,Vazquez,Roderico,NULL,Male,Hispanic,06/26/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60847,69851,63334,PRETRIAL,CALDERON,LULIO,NULL,Male,Caucasian,09/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +60847,69851,63334,PRETRIAL,CALDERON,LULIO,NULL,Male,Caucasian,09/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +60847,69851,63334,PRETRIAL,CALDERON,LULIO,NULL,Male,Caucasian,09/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54674,69853,63336,PRETRIAL,Spoth,Deborah,NULL,Female,Caucasian,04/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +54674,69853,63336,PRETRIAL,Spoth,Deborah,NULL,Female,Caucasian,04/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +54674,69853,63336,PRETRIAL,Spoth,Deborah,NULL,Female,Caucasian,04/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60835,69832,63317,Probation,suhanosky,stephen,NULL,Male,Caucasian,05/13/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +60835,69832,63317,Probation,suhanosky,stephen,NULL,Male,Caucasian,05/13/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +60835,69832,63317,Probation,suhanosky,stephen,NULL,Male,Caucasian,05/13/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51196,69846,63329,PRETRIAL,MEDDERS,MARQUES,NULL,Male,African-American,11/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +51196,69846,63329,PRETRIAL,MEDDERS,MARQUES,NULL,Male,African-American,11/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +51196,69846,63329,PRETRIAL,MEDDERS,MARQUES,NULL,Male,African-American,11/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60841,69838,63323,Probation,Diaz,Oscar,NULL,Male,Hispanic,07/18/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +60841,69838,63323,Probation,Diaz,Oscar,NULL,Male,Hispanic,07/18/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +60841,69838,63323,Probation,Diaz,Oscar,NULL,Male,Hispanic,07/18/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60842,69840,63324,Probation,coleman,zefferniece,NULL,Female,African-American,09/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +60842,69840,63324,Probation,coleman,zefferniece,NULL,Female,African-American,09/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +60842,69840,63324,Probation,coleman,zefferniece,NULL,Female,African-American,09/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60831,69825,63311,PRETRIAL,Taylor,Gerrod,NULL,Male,African-American,01/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +60831,69825,63311,PRETRIAL,Taylor,Gerrod,NULL,Male,African-American,01/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +60831,69825,63311,PRETRIAL,Taylor,Gerrod,NULL,Male,African-American,01/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60853,69859,63341,Probation,Edward,Dolison,NULL,Male,African-American,02/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +60853,69859,63341,Probation,Edward,Dolison,NULL,Male,African-American,02/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +60853,69859,63341,Probation,Edward,Dolison,NULL,Male,African-American,02/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +13790,69861,63343,Probation,Bruno,Jose,NULL,Male,Caucasian,03/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,4,High,7,Risk of Violence,-0.55,10,High,New,1,0 +13790,69861,63343,Probation,Bruno,Jose,NULL,Male,Caucasian,03/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,4,High,8,Risk of Recidivism,0.41,9,High,New,1,0 +13790,69861,63343,Probation,Bruno,Jose,NULL,Male,Caucasian,03/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60849,69855,63338,Probation,martino,daniel,NULL,Female,African-American,08/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +60849,69855,63338,Probation,martino,daniel,NULL,Female,African-American,08/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +60849,69855,63338,Probation,martino,daniel,NULL,Female,African-American,08/28/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +60852,69857,63340,Probation,Fowler,Tina,NULL,Female,African-American,12/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +60852,69857,63340,Probation,Fowler,Tina,NULL,Female,African-American,12/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +60852,69857,63340,Probation,Fowler,Tina,NULL,Female,African-American,12/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +37728,69827,63312,Probation,Joseph,Danise,NULL,Female,African-American,09/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +37728,69827,63312,Probation,Joseph,Danise,NULL,Female,African-American,09/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +37728,69827,63312,Probation,Joseph,Danise,NULL,Female,African-American,09/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60837,69834,63319,Probation,FRANCISCO,GABRIELLA,NICOLE,Female,Hispanic,03/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +60837,69834,63319,Probation,FRANCISCO,GABRIELLA,NICOLE,Female,Hispanic,03/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +60837,69834,63319,Probation,FRANCISCO,GABRIELLA,NICOLE,Female,Hispanic,03/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60839,69836,63321,Probation,Houlihan,William,NULL,Male,Caucasian,10/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +60839,69836,63321,Probation,Houlihan,William,NULL,Male,Caucasian,10/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +60839,69836,63321,Probation,Houlihan,William,NULL,Male,Caucasian,10/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55075,69829,63314,PRETRIAL,POPE,LENARIS,MARQUI,Male,African-American,12/07/84,17,All Scales,Intake,English,Pretrial,Probation,Single,1/30/14 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +55075,69829,63314,PRETRIAL,POPE,LENARIS,MARQUI,Male,African-American,12/07/84,17,All Scales,Intake,English,Pretrial,Probation,Single,1/30/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +55075,69829,63314,PRETRIAL,POPE,LENARIS,MARQUI,Male,African-American,12/07/84,17,All Scales,Intake,English,Pretrial,Probation,Single,1/30/14 0:00,2,Medium,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +17529,69862,16802,PRETRIAL,JONES,CORY,L,Male,African-American,11/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,Copy,1,0 +17529,69862,16802,PRETRIAL,JONES,CORY,L,Male,African-American,11/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,Copy,1,0 +17529,69862,16802,PRETRIAL,JONES,CORY,L,Male,African-American,11/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +31761,69820,63306,PRETRIAL,Johnson,Amanda,NULL,Female,Caucasian,12/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +31761,69820,63306,PRETRIAL,Johnson,Amanda,NULL,Female,Caucasian,12/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +31761,69820,63306,PRETRIAL,Johnson,Amanda,NULL,Female,Caucasian,12/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60845,69845,63328,Probation,Heussman,Travis,NULL,Male,Caucasian,09/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +60845,69845,63328,Probation,Heussman,Travis,NULL,Male,Caucasian,09/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +60845,69845,63328,Probation,Heussman,Travis,NULL,Male,Caucasian,09/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53623,69850,63333,PRETRIAL,Duguay,Boyd,NULL,Male,Caucasian,10/15/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +53623,69850,63333,PRETRIAL,Duguay,Boyd,NULL,Male,Caucasian,10/15/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +53623,69850,63333,PRETRIAL,Duguay,Boyd,NULL,Male,Caucasian,10/15/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60830,69824,63310,PRETRIAL,Coffey,Aurelia,Elena,Female,Caucasian,09/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/30/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +60830,69824,63310,PRETRIAL,Coffey,Aurelia,Elena,Female,Caucasian,09/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/30/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +60830,69824,63310,PRETRIAL,Coffey,Aurelia,Elena,Female,Caucasian,09/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60843,69841,63325,PRETRIAL,durand,sixto,NULL,Male,Caucasian,09/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +60843,69841,63325,PRETRIAL,durand,sixto,NULL,Male,Caucasian,09/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +60843,69841,63325,PRETRIAL,durand,sixto,NULL,Male,Caucasian,09/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/30/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60861,69871,63351,PRETRIAL,Soussi,Samir,Salah,Male,Other,07/10/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/31/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +60861,69871,63351,PRETRIAL,Soussi,Samir,Salah,Male,Other,07/10/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/31/14 0:00,1,Low,8,Risk of Recidivism,-2.6,1,Low,New,1,0 +60861,69871,63351,PRETRIAL,Soussi,Samir,Salah,Male,Other,07/10/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60866,69876,63356,PRETRIAL,Torres,Albalidia,NULL,Female,African-American,04/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +60866,69876,63356,PRETRIAL,Torres,Albalidia,NULL,Female,African-American,04/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +60866,69876,63356,PRETRIAL,Torres,Albalidia,NULL,Female,African-American,04/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60875,69887,63365,Probation,Mims,John,NULL,Male,Caucasian,11/06/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/31/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +60875,69887,63365,Probation,Mims,John,NULL,Male,Caucasian,11/06/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/31/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +60875,69887,63365,Probation,Mims,John,NULL,Male,Caucasian,11/06/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60857,69866,63347,PRETRIAL,Burch,Melissa,NULL,Female,Caucasian,02/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/31/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +60857,69866,63347,PRETRIAL,Burch,Melissa,NULL,Female,Caucasian,02/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/31/14 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +60857,69866,63347,PRETRIAL,Burch,Melissa,NULL,Female,Caucasian,02/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60871,69883,63361,PRETRIAL,bethel,nikko,NULL,Male,African-American,08/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +60871,69883,63361,PRETRIAL,bethel,nikko,NULL,Male,African-American,08/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +60871,69883,63361,PRETRIAL,bethel,nikko,NULL,Male,African-American,08/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60867,69878,63357,Probation,Epps,Nathaniel,NULL,Male,Caucasian,07/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.12,4,Low,New,1,0 +60867,69878,63357,Probation,Epps,Nathaniel,NULL,Male,Caucasian,07/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +60867,69878,63357,Probation,Epps,Nathaniel,NULL,Male,Caucasian,07/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60873,69885,63363,Probation,Janes,Chris,Susanne,Female,Caucasian,08/17/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +60873,69885,63363,Probation,Janes,Chris,Susanne,Female,Caucasian,08/17/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/14 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +60873,69885,63363,Probation,Janes,Chris,Susanne,Female,Caucasian,08/17/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60856,69864,63345,PRETRIAL,Newkirk,Brianna,R,Female,African-American,08/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +60856,69864,63345,PRETRIAL,Newkirk,Brianna,R,Female,African-American,08/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +60856,69864,63345,PRETRIAL,Newkirk,Brianna,R,Female,African-American,08/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60864,69874,63354,PRETRIAL,Gwynn,Quon,Louis,Male,African-American,06/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +60864,69874,63354,PRETRIAL,Gwynn,Quon,Louis,Male,African-American,06/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +60864,69874,63354,PRETRIAL,Gwynn,Quon,Louis,Male,African-American,06/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60870,69882,63360,Probation,NOVELLO,ROBERT,ANTHONY,Male,Caucasian,11/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +60870,69882,63360,Probation,NOVELLO,ROBERT,ANTHONY,Male,Caucasian,11/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +60870,69882,63360,Probation,NOVELLO,ROBERT,ANTHONY,Male,Caucasian,11/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60858,69867,63348,PRETRIAL,Pena,Fanny,NULL,Female,Hispanic,03/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/31/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +60858,69867,63348,PRETRIAL,Pena,Fanny,NULL,Female,Hispanic,03/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/31/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +60858,69867,63348,PRETRIAL,Pena,Fanny,NULL,Female,Hispanic,03/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60859,69869,63349,PRETRIAL,Rodriguez,Wilfredo,Freddy,Male,Caucasian,12/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +60859,69869,63349,PRETRIAL,Rodriguez,Wilfredo,Freddy,Male,Caucasian,12/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +60859,69869,63349,PRETRIAL,Rodriguez,Wilfredo,Freddy,Male,Caucasian,12/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60877,69890,63367,PRETRIAL,Antolick,Keith,NULL,Male,Caucasian,06/19/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +60877,69890,63367,PRETRIAL,Antolick,Keith,NULL,Male,Caucasian,06/19/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +60877,69890,63367,PRETRIAL,Antolick,Keith,NULL,Male,Caucasian,06/19/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60876,69888,63366,Broward County,Mayer,Christopher,NULL,Male,Caucasian,04/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +60876,69888,63366,Broward County,Mayer,Christopher,NULL,Male,Caucasian,04/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +60876,69888,63366,Broward County,Mayer,Christopher,NULL,Male,Caucasian,04/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60865,69875,63355,PRETRIAL,Wooden,Ebony,NULL,Female,African-American,01/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +60865,69875,63355,PRETRIAL,Wooden,Ebony,NULL,Female,African-American,01/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +60865,69875,63355,PRETRIAL,Wooden,Ebony,NULL,Female,African-American,01/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60868,69879,63358,Probation,Zabardi,Krystian,NULL,Male,Caucasian,04/30/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +60868,69879,63358,Probation,Zabardi,Krystian,NULL,Male,Caucasian,04/30/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +60868,69879,63358,Probation,Zabardi,Krystian,NULL,Male,Caucasian,04/30/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60872,69884,63362,Probation,Day,Mark,NULL,Male,Caucasian,11/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +60872,69884,63362,Probation,Day,Mark,NULL,Male,Caucasian,11/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +60872,69884,63362,Probation,Day,Mark,NULL,Male,Caucasian,11/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60862,69872,63352,PRETRIAL,McCree,Clifton,NULL,Male,African-American,03/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +60862,69872,63352,PRETRIAL,McCree,Clifton,NULL,Male,African-American,03/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +60862,69872,63352,PRETRIAL,McCree,Clifton,NULL,Male,African-American,03/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60878,69891,63368,PRETRIAL,Franklin,Akeel,NULL,Male,African-American,09/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +60878,69891,63368,PRETRIAL,Franklin,Akeel,NULL,Male,African-American,09/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +60878,69891,63368,PRETRIAL,Franklin,Akeel,NULL,Male,African-American,09/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60860,69870,63350,PRETRIAL,Martin,Christopher,NULL,Male,African-American,07/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +60860,69870,63350,PRETRIAL,Martin,Christopher,NULL,Male,African-American,07/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +60860,69870,63350,PRETRIAL,Martin,Christopher,NULL,Male,African-American,07/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60855,69863,63344,PRETRIAL,Dellapi,Vincent,NULL,Male,Caucasian,09/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +60855,69863,63344,PRETRIAL,Dellapi,Vincent,NULL,Male,Caucasian,09/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +60855,69863,63344,PRETRIAL,Dellapi,Vincent,NULL,Male,Caucasian,09/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60863,69873,63353,PRETRIAL,Jumper,Kelcie,NULL,Male,African-American,03/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +60863,69873,63353,PRETRIAL,Jumper,Kelcie,NULL,Male,African-American,03/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +60863,69873,63353,PRETRIAL,Jumper,Kelcie,NULL,Male,African-American,03/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +42888,69881,42765,PRETRIAL,Dorceus,Stephanie,NULL,Female,African-American,01/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,Copy,1,0 +42888,69881,42765,PRETRIAL,Dorceus,Stephanie,NULL,Female,African-American,01/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,9,High,Copy,1,0 +42888,69881,42765,PRETRIAL,Dorceus,Stephanie,NULL,Female,African-American,01/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +60571,69889,63025,PRETRIAL,BROADHEAD,ALANA,NULL,Female,Caucasian,05/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.29,3,Low,Copy,1,0 +60571,69889,63025,PRETRIAL,BROADHEAD,ALANA,NULL,Female,Caucasian,05/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,9,High,Copy,1,0 +60571,69889,63025,PRETRIAL,BROADHEAD,ALANA,NULL,Female,Caucasian,05/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,1/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +28048,69868,27117,PRETRIAL,byrum,lisa,NULL,Female,African-American,07/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,Copy,1,0 +28048,69868,27117,PRETRIAL,byrum,lisa,NULL,Female,African-American,07/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,Copy,1,0 +28048,69868,27117,PRETRIAL,byrum,lisa,NULL,Female,African-American,07/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,1/31/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +60886,69902,63379,PRETRIAL,WINTER,STEVEN,MITCHELL,Male,Caucasian,01/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +60886,69902,63379,PRETRIAL,WINTER,STEVEN,MITCHELL,Male,Caucasian,01/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +60886,69902,63379,PRETRIAL,WINTER,STEVEN,MITCHELL,Male,Caucasian,01/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60888,69904,63381,PRETRIAL,Pabon,Amadeo,B,Male,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +60888,69904,63381,PRETRIAL,Pabon,Amadeo,B,Male,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +60888,69904,63381,PRETRIAL,Pabon,Amadeo,B,Male,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60881,69896,63373,PRETRIAL,GRANDELLI,LOUIS,NULL,Male,Caucasian,09/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/1/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +60881,69896,63373,PRETRIAL,GRANDELLI,LOUIS,NULL,Male,Caucasian,09/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/1/14 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +60881,69896,63373,PRETRIAL,GRANDELLI,LOUIS,NULL,Male,Caucasian,09/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60879,69894,63371,PRETRIAL,Penaranda,Rogrigo,NULL,Male,Hispanic,10/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/1/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +60879,69894,63371,PRETRIAL,Penaranda,Rogrigo,NULL,Male,Hispanic,10/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/1/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +60879,69894,63371,PRETRIAL,Penaranda,Rogrigo,NULL,Male,Hispanic,10/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/1/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51697,69893,63370,PRETRIAL,koze,timothy,NULL,Male,Caucasian,09/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +51697,69893,63370,PRETRIAL,koze,timothy,NULL,Male,Caucasian,09/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +51697,69893,63370,PRETRIAL,koze,timothy,NULL,Male,Caucasian,09/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60884,69900,63377,PRETRIAL,Simmons,Malcolm,NULL,Male,African-American,03/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +60884,69900,63377,PRETRIAL,Simmons,Malcolm,NULL,Male,African-American,03/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +60884,69900,63377,PRETRIAL,Simmons,Malcolm,NULL,Male,African-American,03/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60889,69905,63382,PRETRIAL,Deprima,John,Anthony,Male,Caucasian,05/11/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +60889,69905,63382,PRETRIAL,Deprima,John,Anthony,Male,Caucasian,05/11/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +60889,69905,63382,PRETRIAL,Deprima,John,Anthony,Male,Caucasian,05/11/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60883,69898,63375,PRETRIAL,Felix,Joshua,Manuel,Male,African-American,02/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +60883,69898,63375,PRETRIAL,Felix,Joshua,Manuel,Male,African-American,02/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +60883,69898,63375,PRETRIAL,Felix,Joshua,Manuel,Male,African-American,02/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60887,69903,63380,PRETRIAL,Collier,Sheridan,NULL,Male,African-American,08/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +60887,69903,63380,PRETRIAL,Collier,Sheridan,NULL,Male,African-American,08/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +60887,69903,63380,PRETRIAL,Collier,Sheridan,NULL,Male,African-American,08/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60880,69895,63372,PRETRIAL,WARD,VANSTON,GLENN,Male,African-American,08/30/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +60880,69895,63372,PRETRIAL,WARD,VANSTON,GLENN,Male,African-American,08/30/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +60880,69895,63372,PRETRIAL,WARD,VANSTON,GLENN,Male,African-American,08/30/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +49180,69899,63376,PRETRIAL,Eason,Kevin,Lester,Male,African-American,09/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +49180,69899,63376,PRETRIAL,Eason,Kevin,Lester,Male,African-American,09/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +49180,69899,63376,PRETRIAL,Eason,Kevin,Lester,Male,African-American,09/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60882,69897,63374,PRETRIAL,Bravo,Angel,M,Male,Hispanic,06/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +60882,69897,63374,PRETRIAL,Bravo,Angel,M,Male,Hispanic,06/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +60882,69897,63374,PRETRIAL,Bravo,Angel,M,Male,Hispanic,06/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60885,69901,63378,PRETRIAL,HEWITT,WINSTON,NIGEL,Male,African-American,09/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +60885,69901,63378,PRETRIAL,HEWITT,WINSTON,NIGEL,Male,African-American,09/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +60885,69901,63378,PRETRIAL,HEWITT,WINSTON,NIGEL,Male,African-American,09/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/1/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60901,69918,63396,PRETRIAL,APOLLON,JOSEPH,NULL,Male,African-American,01/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +60901,69918,63396,PRETRIAL,APOLLON,JOSEPH,NULL,Male,African-American,01/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/14 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +60901,69918,63396,PRETRIAL,APOLLON,JOSEPH,NULL,Male,African-American,01/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51151,69913,63391,PRETRIAL,Rodriguez,Pedro,NULL,Male,Hispanic,05/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +51151,69913,63391,PRETRIAL,Rodriguez,Pedro,NULL,Male,Hispanic,05/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +51151,69913,63391,PRETRIAL,Rodriguez,Pedro,NULL,Male,Hispanic,05/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60890,69906,63383,PRETRIAL,Ryabov,Alexey,NULL,Male,Caucasian,06/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +60890,69906,63383,PRETRIAL,Ryabov,Alexey,NULL,Male,Caucasian,06/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +60890,69906,63383,PRETRIAL,Ryabov,Alexey,NULL,Male,Caucasian,06/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60892,69908,63385,PRETRIAL,Exilus,Yves,NULL,Male,Other,01/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +60892,69908,63385,PRETRIAL,Exilus,Yves,NULL,Male,Other,01/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +60892,69908,63385,PRETRIAL,Exilus,Yves,NULL,Male,Other,01/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60899,69916,63394,PRETRIAL,MARTINS,DANIEL,ALEXANDER,Male,African-American,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +60899,69916,63394,PRETRIAL,MARTINS,DANIEL,ALEXANDER,Male,African-American,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +60899,69916,63394,PRETRIAL,MARTINS,DANIEL,ALEXANDER,Male,African-American,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60902,69919,63397,PRETRIAL,Singh,Ivor,NULL,Male,Other,07/08/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +60902,69919,63397,PRETRIAL,Singh,Ivor,NULL,Male,Other,07/08/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +60902,69919,63397,PRETRIAL,Singh,Ivor,NULL,Male,Other,07/08/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60895,69911,63389,PRETRIAL,Dasilva,Elias,NULL,Male,Caucasian,08/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +60895,69911,63389,PRETRIAL,Dasilva,Elias,NULL,Male,Caucasian,08/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +60895,69911,63389,PRETRIAL,Dasilva,Elias,NULL,Male,Caucasian,08/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60893,69909,63387,PRETRIAL,Brown,Micheal,NULL,Male,African-American,03/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +60893,69909,63387,PRETRIAL,Brown,Micheal,NULL,Male,African-American,03/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +60893,69909,63387,PRETRIAL,Brown,Micheal,NULL,Male,African-American,03/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60904,69921,63399,PRETRIAL,Pardo,Andrew,NULL,Male,African-American,01/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +60904,69921,63399,PRETRIAL,Pardo,Andrew,NULL,Male,African-American,01/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +60904,69921,63399,PRETRIAL,Pardo,Andrew,NULL,Male,African-American,01/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60897,69914,63392,PRETRIAL,LEVY,ANDRE,NULL,Male,African-American,06/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +60897,69914,63392,PRETRIAL,LEVY,ANDRE,NULL,Male,African-American,06/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +60897,69914,63392,PRETRIAL,LEVY,ANDRE,NULL,Male,African-American,06/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60896,69912,63390,PRETRIAL,Lewis,Jeremiah,NULL,Male,African-American,06/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +60896,69912,63390,PRETRIAL,Lewis,Jeremiah,NULL,Male,African-American,06/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +60896,69912,63390,PRETRIAL,Lewis,Jeremiah,NULL,Male,African-American,06/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60898,69915,63393,PRETRIAL,CALLISTE,LINSEY,NULL,Female,African-American,11/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +60898,69915,63393,PRETRIAL,CALLISTE,LINSEY,NULL,Female,African-American,11/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +60898,69915,63393,PRETRIAL,CALLISTE,LINSEY,NULL,Female,African-American,11/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60891,69907,63384,PRETRIAL,Lewis,Denzel,NULL,Male,African-American,06/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +60891,69907,63384,PRETRIAL,Lewis,Denzel,NULL,Male,African-American,06/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +60891,69907,63384,PRETRIAL,Lewis,Denzel,NULL,Male,African-American,06/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60903,69920,63398,PRETRIAL,BOWLING,ADRIAN,NULL,Male,African-American,04/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +60903,69920,63398,PRETRIAL,BOWLING,ADRIAN,NULL,Male,African-American,04/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +60903,69920,63398,PRETRIAL,BOWLING,ADRIAN,NULL,Male,African-American,04/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60894,69910,63388,PRETRIAL,Cervantes,Vidal,NULL,Male,Caucasian,12/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +60894,69910,63388,PRETRIAL,Cervantes,Vidal,NULL,Male,Caucasian,12/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +60894,69910,63388,PRETRIAL,Cervantes,Vidal,NULL,Male,Caucasian,12/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60900,69917,63395,PRETRIAL,APOLLON,NADINE,NULL,Female,African-American,01/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +60900,69917,63395,PRETRIAL,APOLLON,NADINE,NULL,Female,African-American,01/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +60900,69917,63395,PRETRIAL,APOLLON,NADINE,NULL,Female,African-American,01/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60943,69967,63442,Probation,Cepeda,THOMAS,NULL,Male,Caucasian,06/21/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +60943,69967,63442,Probation,Cepeda,THOMAS,NULL,Male,Caucasian,06/21/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +60943,69967,63442,Probation,Cepeda,THOMAS,NULL,Male,Caucasian,06/21/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60912,69931,63409,PRETRIAL,CALDERON,LULIO,NULL,Male,Caucasian,09/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +60912,69931,63409,PRETRIAL,CALDERON,LULIO,NULL,Male,Caucasian,09/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +60912,69931,63409,PRETRIAL,CALDERON,LULIO,NULL,Male,Caucasian,09/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60925,69946,63423,Probation,SCHARF,LAURA,NULL,Female,Caucasian,11/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +60925,69946,63423,Probation,SCHARF,LAURA,NULL,Female,Caucasian,11/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +60925,69946,63423,Probation,SCHARF,LAURA,NULL,Female,Caucasian,11/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60908,69925,63403,PRETRIAL,WELLS,WILLIAM,NULL,Male,African-American,09/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +60908,69925,63403,PRETRIAL,WELLS,WILLIAM,NULL,Male,African-American,09/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +60908,69925,63403,PRETRIAL,WELLS,WILLIAM,NULL,Male,African-American,09/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60937,69959,63435,Probation,CRESPI,ALEJANDRO,NULL,Male,Hispanic,11/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +60937,69959,63435,Probation,CRESPI,ALEJANDRO,NULL,Male,Hispanic,11/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +60937,69959,63435,Probation,CRESPI,ALEJANDRO,NULL,Male,Hispanic,11/25/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60906,69923,63401,PRETRIAL,NOEL,MARCEL,NULL,Male,African-American,01/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +60906,69923,63401,PRETRIAL,NOEL,MARCEL,NULL,Male,African-American,01/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +60906,69923,63401,PRETRIAL,NOEL,MARCEL,NULL,Male,African-American,01/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60917,69938,63415,PRETRIAL,Cazacu,Christine,NULL,Female,Other,05/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/3/14 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +60917,69938,63415,PRETRIAL,Cazacu,Christine,NULL,Female,Other,05/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +60917,69938,63415,PRETRIAL,Cazacu,Christine,NULL,Female,Other,05/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/3/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60932,69954,63430,Probation,guyan,james,NULL,Male,Caucasian,09/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +60932,69954,63430,Probation,guyan,james,NULL,Male,Caucasian,09/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +60932,69954,63430,Probation,guyan,james,NULL,Male,Caucasian,09/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50633,69933,63411,PRETRIAL,MATOS,DAVID,PAUL,Male,Caucasian,01/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/3/14 0:00,4,High,7,Risk of Violence,-0.95,9,High,New,1,0 +50633,69933,63411,PRETRIAL,MATOS,DAVID,PAUL,Male,Caucasian,01/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/3/14 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +50633,69933,63411,PRETRIAL,MATOS,DAVID,PAUL,Male,Caucasian,01/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/3/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +60940,69962,63438,Probation,Enriquez,Ivan,NULL,Male,Hispanic,02/23/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/3/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +60940,69962,63438,Probation,Enriquez,Ivan,NULL,Male,Hispanic,02/23/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +60940,69962,63438,Probation,Enriquez,Ivan,NULL,Male,Hispanic,02/23/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60928,69949,63426,Probation,Alvarez Luquetta,Fabio,NULL,Male,Hispanic,10/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +60928,69949,63426,Probation,Alvarez Luquetta,Fabio,NULL,Male,Hispanic,10/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +60928,69949,63426,Probation,Alvarez Luquetta,Fabio,NULL,Male,Hispanic,10/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60941,69963,63439,PRETRIAL,Janvier,Rabe,NULL,Male,African-American,08/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +60941,69963,63439,PRETRIAL,Janvier,Rabe,NULL,Male,African-American,08/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +60941,69963,63439,PRETRIAL,Janvier,Rabe,NULL,Male,African-American,08/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60909,69928,63406,PRETRIAL,Myers,Glen,NULL,Male,Caucasian,10/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +60909,69928,63406,PRETRIAL,Myers,Glen,NULL,Male,Caucasian,10/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +60909,69928,63406,PRETRIAL,Myers,Glen,NULL,Male,Caucasian,10/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60922,69942,63419,Probation,Smith,Elizabeth,NULL,Female,Caucasian,08/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,2,Medium,7,Risk of Violence,-2.89,2,Low,New,1,0 +60922,69942,63419,Probation,Smith,Elizabeth,NULL,Female,Caucasian,08/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +60922,69942,63419,Probation,Smith,Elizabeth,NULL,Female,Caucasian,08/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57529,69970,59639,PRETRIAL,URREA,HELBERT,ANDREAS,Male,Hispanic,07/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,Copy,1,0 +57529,69970,59639,PRETRIAL,URREA,HELBERT,ANDREAS,Male,Hispanic,07/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,Copy,1,0 +57529,69970,59639,PRETRIAL,URREA,HELBERT,ANDREAS,Male,Hispanic,07/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +60934,69956,63432,PRETRIAL,DOLGAN,JEFFREY,NULL,Male,Caucasian,11/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/3/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +60934,69956,63432,PRETRIAL,DOLGAN,JEFFREY,NULL,Male,Caucasian,11/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +60934,69956,63432,PRETRIAL,DOLGAN,JEFFREY,NULL,Male,Caucasian,11/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54524,69926,63404,PRETRIAL,RODRIQUEZ,KIA,NULL,Female,African-American,07/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +54524,69926,63404,PRETRIAL,RODRIQUEZ,KIA,NULL,Female,African-American,07/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +54524,69926,63404,PRETRIAL,RODRIQUEZ,KIA,NULL,Female,African-American,07/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60923,69944,63421,Probation,weeder,carolyn,NULL,Female,Caucasian,05/03/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/3/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +60923,69944,63421,Probation,weeder,carolyn,NULL,Female,Caucasian,05/03/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/3/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +60923,69944,63421,Probation,weeder,carolyn,NULL,Female,Caucasian,05/03/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60930,69951,63428,Probation,Fria,Juan,Carlos,Male,Hispanic,02/22/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/3/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +60930,69951,63428,Probation,Fria,Juan,Carlos,Male,Hispanic,02/22/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +60930,69951,63428,Probation,Fria,Juan,Carlos,Male,Hispanic,02/22/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60911,69930,63408,PRETRIAL,NELSON,MARY,NULL,Female,African-American,05/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/3/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +60911,69930,63408,PRETRIAL,NELSON,MARY,NULL,Female,African-American,05/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +60911,69930,63408,PRETRIAL,NELSON,MARY,NULL,Female,African-American,05/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/3/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60926,69947,63424,PRETRIAL,Pineda,Douglas,NULL,Male,Hispanic,09/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/3/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +60926,69947,63424,PRETRIAL,Pineda,Douglas,NULL,Male,Hispanic,09/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +60926,69947,63424,PRETRIAL,Pineda,Douglas,NULL,Male,Hispanic,09/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60924,69945,63422,Probation,Gomez,Johnny,NULL,Male,Hispanic,06/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/3/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +60924,69945,63422,Probation,Gomez,Johnny,NULL,Male,Hispanic,06/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/3/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +60924,69945,63422,Probation,Gomez,Johnny,NULL,Male,Hispanic,06/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60907,69924,63402,PRETRIAL,Kelly,Norval,Lloyd,Male,Other,12/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +60907,69924,63402,PRETRIAL,Kelly,Norval,Lloyd,Male,Other,12/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +60907,69924,63402,PRETRIAL,Kelly,Norval,Lloyd,Male,Other,12/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60914,69937,63413,PRETRIAL,FIELDS,WESLEY,NULL,Male,Caucasian,05/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/3/14 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,Copy,1,0 +60914,69937,63413,PRETRIAL,FIELDS,WESLEY,NULL,Male,Caucasian,05/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,Copy,1,0 +60914,69937,63413,PRETRIAL,FIELDS,WESLEY,NULL,Male,Caucasian,05/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/3/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +949,69966,60778,PRETRIAL,MOISE,CHEDLINE,NULL,Female,African-American,05/05/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +949,69966,60778,PRETRIAL,MOISE,CHEDLINE,NULL,Female,African-American,05/05/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +949,69966,60778,PRETRIAL,MOISE,CHEDLINE,NULL,Female,African-American,05/05/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60939,69961,63437,Probation,LOBO,RAFAEL,NULL,Male,Hispanic,07/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +60939,69961,63437,Probation,LOBO,RAFAEL,NULL,Male,Hispanic,07/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +60939,69961,63437,Probation,LOBO,RAFAEL,NULL,Male,Hispanic,07/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60944,69968,63443,Probation,Geiger,Alexandria,NULL,Female,Caucasian,06/01/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +60944,69968,63443,Probation,Geiger,Alexandria,NULL,Female,Caucasian,06/01/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +60944,69968,63443,Probation,Geiger,Alexandria,NULL,Female,Caucasian,06/01/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60920,69940,63417,Probation,Barreau,Pierre,NULL,Male,African-American,04/09/50,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +60920,69940,63417,Probation,Barreau,Pierre,NULL,Male,African-American,04/09/50,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +60920,69940,63417,Probation,Barreau,Pierre,NULL,Male,African-American,04/09/50,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60931,69953,63429,Probation,ZEDNEK,george,NULL,Male,Caucasian,10/14/30,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/3/14 0:00,1,Low,7,Risk of Violence,-4.79,1,Low,New,1,0 +60931,69953,63429,Probation,ZEDNEK,george,NULL,Male,Caucasian,10/14/30,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/3/14 0:00,1,Low,8,Risk of Recidivism,-2.98,1,Low,New,1,0 +60931,69953,63429,Probation,ZEDNEK,george,NULL,Male,Caucasian,10/14/30,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60938,69960,63436,Probation,castano,Alejandro,NULL,Male,Hispanic,10/04/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +60938,69960,63436,Probation,castano,Alejandro,NULL,Male,Hispanic,10/04/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +60938,69960,63436,Probation,castano,Alejandro,NULL,Male,Hispanic,10/04/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60913,69932,63410,PRETRIAL,Tejada,Elsa,NULL,Female,Hispanic,11/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/3/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +60913,69932,63410,PRETRIAL,Tejada,Elsa,NULL,Female,Hispanic,11/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +60913,69932,63410,PRETRIAL,Tejada,Elsa,NULL,Female,Hispanic,11/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60933,69955,63431,PRETRIAL,ZAVALA,JAHAIDA,NULL,Female,Hispanic,11/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/3/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +60933,69955,63431,PRETRIAL,ZAVALA,JAHAIDA,NULL,Female,Hispanic,11/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/3/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +60933,69955,63431,PRETRIAL,ZAVALA,JAHAIDA,NULL,Female,Hispanic,11/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60935,69957,63433,PRETRIAL,FASHAW,MICHAEL,NULL,Male,African-American,06/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/3/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +60935,69957,63433,PRETRIAL,FASHAW,MICHAEL,NULL,Male,African-American,06/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/3/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +60935,69957,63433,PRETRIAL,FASHAW,MICHAEL,NULL,Male,African-American,06/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +34682,69927,63405,PRETRIAL,Mauney,Robert,NULL,Male,African-American,07/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/3/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +34682,69927,63405,PRETRIAL,Mauney,Robert,NULL,Male,African-American,07/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +34682,69927,63405,PRETRIAL,Mauney,Robert,NULL,Male,African-American,07/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60910,69929,63407,PRETRIAL,Johnson,Keon,L,Male,African-American,07/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +60910,69929,63407,PRETRIAL,Johnson,Keon,L,Male,African-American,07/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +60910,69929,63407,PRETRIAL,Johnson,Keon,L,Male,African-American,07/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +1692,69934,63412,PRETRIAL,Samuels,Walter,NULL,Male,African-American,09/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +1692,69934,63412,PRETRIAL,Samuels,Walter,NULL,Male,African-American,09/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +1692,69934,63412,PRETRIAL,Samuels,Walter,NULL,Male,African-American,09/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +20342,21236,19569,PRETRIAL,JONES,RYAN,CHRISTOPHE,Male,African-American,07/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +20342,21236,19569,PRETRIAL,JONES,RYAN,CHRISTOPHE,Male,African-American,07/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +20342,21236,19569,PRETRIAL,JONES,RYAN,CHRISTOPHE,Male,African-American,07/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60929,69950,63427,PRETRIAL,Devaswamparambil,Veugoplalan,NULL,Male,Other,05/13/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/3/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +60929,69950,63427,PRETRIAL,Devaswamparambil,Veugoplalan,NULL,Male,Other,05/13/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/3/14 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +60929,69950,63427,PRETRIAL,Devaswamparambil,Veugoplalan,NULL,Male,Other,05/13/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60942,69964,63440,Probation,kurtgis,caryn,NULL,Female,Caucasian,03/28/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/3/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +60942,69964,63440,Probation,kurtgis,caryn,NULL,Female,Caucasian,03/28/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/3/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +60942,69964,63440,Probation,kurtgis,caryn,NULL,Female,Caucasian,03/28/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60921,69943,63420,PRETRIAL,Teart,Khalid,NULL,Male,African-American,02/24/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,4,High,7,Risk of Violence,-1.19,8,High,New,1,0 +60921,69943,63420,PRETRIAL,Teart,Khalid,NULL,Male,African-American,02/24/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,4,High,8,Risk of Recidivism,0.94,10,High,New,1,0 +60921,69943,63420,PRETRIAL,Teart,Khalid,NULL,Male,African-American,02/24/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,4,High,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +20342,69952,19569,PRETRIAL,JONES,RYAN,CHRISTOPHE,Male,African-American,07/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,Copy,1,0 +20342,69952,19569,PRETRIAL,JONES,RYAN,CHRISTOPHE,Male,African-American,07/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,Copy,1,0 +20342,69952,19569,PRETRIAL,JONES,RYAN,CHRISTOPHE,Male,African-American,07/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +60905,69922,63400,PRETRIAL,Hannan,Johnny,NULL,Male,African-American,07/02/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +60905,69922,63400,PRETRIAL,Hannan,Johnny,NULL,Male,African-American,07/02/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +60905,69922,63400,PRETRIAL,Hannan,Johnny,NULL,Male,African-American,07/02/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +60919,69939,63416,PRETRIAL,Cross,Antoine,NULL,Male,African-American,01/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +60919,69939,63416,PRETRIAL,Cross,Antoine,NULL,Male,African-American,01/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +60919,69939,63416,PRETRIAL,Cross,Antoine,NULL,Male,African-American,01/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +60945,69969,63444,Probation,mondesir,michael,NULL,Male,Caucasian,11/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +60945,69969,63444,Probation,mondesir,michael,NULL,Male,Caucasian,11/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +60945,69969,63444,Probation,mondesir,michael,NULL,Male,Caucasian,11/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60927,69948,63425,PRETRIAL,Beljour,Barclay,Mompoint,Male,African-American,07/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +60927,69948,63425,PRETRIAL,Beljour,Barclay,Mompoint,Male,African-American,07/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +60927,69948,63425,PRETRIAL,Beljour,Barclay,Mompoint,Male,African-American,07/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/3/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60983,70015,63486,Probation,MALONE,STEVEN,NULL,Male,African-American,07/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +60983,70015,63486,Probation,MALONE,STEVEN,NULL,Male,African-American,07/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +60983,70015,63486,Probation,MALONE,STEVEN,NULL,Male,African-American,07/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60966,69994,63467,PRETRIAL,Casey,Paul,Thomas,Male,Caucasian,02/16/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +60966,69994,63467,PRETRIAL,Casey,Paul,Thomas,Male,Caucasian,02/16/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +60966,69994,63467,PRETRIAL,Casey,Paul,Thomas,Male,Caucasian,02/16/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60948,69973,63447,PRETRIAL,HANKS,KEITH,DJ,Male,African-American,09/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +60948,69973,63447,PRETRIAL,HANKS,KEITH,DJ,Male,African-American,09/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +60948,69973,63447,PRETRIAL,HANKS,KEITH,DJ,Male,African-American,09/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60963,69990,63463,Probation,Needhamnoel,Seon,NULL,Male,African-American,12/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +60963,69990,63463,Probation,Needhamnoel,Seon,NULL,Male,African-American,12/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +60963,69990,63463,Probation,Needhamnoel,Seon,NULL,Male,African-American,12/31/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60979,70011,63482,Probation,baillie,john,NULL,Male,Caucasian,01/05/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/4/14 0:00,2,Medium,7,Risk of Violence,-2.61,2,Low,New,1,0 +60979,70011,63482,Probation,baillie,john,NULL,Male,Caucasian,01/05/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +60979,70011,63482,Probation,baillie,john,NULL,Male,Caucasian,01/05/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/4/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +5391,69999,63472,PRETRIAL,BRADLEY,LASHONDA,NULL,Male,African-American,05/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +5391,69999,63472,PRETRIAL,BRADLEY,LASHONDA,NULL,Male,African-American,05/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +5391,69999,63472,PRETRIAL,BRADLEY,LASHONDA,NULL,Male,African-American,05/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60981,70013,63484,PRETRIAL,SAINTFLEUR,ALAN,NULL,Male,African-American,08/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +60981,70013,63484,PRETRIAL,SAINTFLEUR,ALAN,NULL,Male,African-American,08/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.81,10,High,New,1,0 +60981,70013,63484,PRETRIAL,SAINTFLEUR,ALAN,NULL,Male,African-American,08/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +46368,69978,63452,PRETRIAL,Foy,Robin,Lee,Female,Caucasian,02/07/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +46368,69978,63452,PRETRIAL,Foy,Robin,Lee,Female,Caucasian,02/07/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +46368,69978,63452,PRETRIAL,Foy,Robin,Lee,Female,Caucasian,02/07/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60959,69985,63459,Probation,Jansonkellman,Charlotta,NULL,Female,Caucasian,11/22/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/4/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +60959,69985,63459,Probation,Jansonkellman,Charlotta,NULL,Female,Caucasian,11/22/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +60959,69985,63459,Probation,Jansonkellman,Charlotta,NULL,Female,Caucasian,11/22/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +60964,69992,63465,Probation,Anderson,Kenneth,NULL,Male,African-American,10/09/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +60964,69992,63465,Probation,Anderson,Kenneth,NULL,Male,African-American,10/09/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +60964,69992,63465,Probation,Anderson,Kenneth,NULL,Male,African-American,10/09/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60975,70006,63478,Probation,Morley,Donald,NULL,Male,Caucasian,12/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +60975,70006,63478,Probation,Morley,Donald,NULL,Male,Caucasian,12/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +60975,70006,63478,Probation,Morley,Donald,NULL,Male,Caucasian,12/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +60955,69981,63455,PRETRIAL,Beckford,Devon,NULL,Male,African-American,05/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +60955,69981,63455,PRETRIAL,Beckford,Devon,NULL,Male,African-American,05/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +60955,69981,63455,PRETRIAL,Beckford,Devon,NULL,Male,African-American,05/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60956,69982,63456,PRETRIAL,Keroes,Howard,Kevin,Male,Caucasian,05/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/4/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +60956,69982,63456,PRETRIAL,Keroes,Howard,Kevin,Male,Caucasian,05/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/4/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +60956,69982,63456,PRETRIAL,Keroes,Howard,Kevin,Male,Caucasian,05/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +1409,70003,63476,PRETRIAL,mackeroy,keevin,anton,Male,African-American,06/08/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +1409,70003,63476,PRETRIAL,mackeroy,keevin,anton,Male,African-American,06/08/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +1409,70003,63476,PRETRIAL,mackeroy,keevin,anton,Male,African-American,06/08/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60978,70010,63481,Probation,TOLEDO,LAUREN,MARIE,Female,Hispanic,06/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +60978,70010,63481,Probation,TOLEDO,LAUREN,MARIE,Female,Hispanic,06/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +60978,70010,63481,Probation,TOLEDO,LAUREN,MARIE,Female,Hispanic,06/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60949,69974,63448,PRETRIAL,TAYLOR,ERICKA,NULL,Female,African-American,03/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/4/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +60949,69974,63448,PRETRIAL,TAYLOR,ERICKA,NULL,Female,African-American,03/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +60949,69974,63448,PRETRIAL,TAYLOR,ERICKA,NULL,Female,African-American,03/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50210,69989,63462,PRETRIAL,MCCRARY,BRIAN,SCOTT,Male,Caucasian,07/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +50210,69989,63462,PRETRIAL,MCCRARY,BRIAN,SCOTT,Male,Caucasian,07/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +50210,69989,63462,PRETRIAL,MCCRARY,BRIAN,SCOTT,Male,Caucasian,07/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60967,69995,63468,PRETRIAL,Hettinger,Carson,NULL,Male,Caucasian,06/01/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/4/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +60967,69995,63468,PRETRIAL,Hettinger,Carson,NULL,Male,Caucasian,06/01/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/4/14 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +60967,69995,63468,PRETRIAL,Hettinger,Carson,NULL,Male,Caucasian,06/01/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60973,70002,63475,Probation,Mock,June,NULL,Female,Caucasian,04/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +60973,70002,63475,Probation,Mock,June,NULL,Female,Caucasian,04/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +60973,70002,63475,Probation,Mock,June,NULL,Female,Caucasian,04/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60969,69997,63470,PRETRIAL,LORFILS,BENSON,NULL,Male,African-American,08/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +60969,69997,63470,PRETRIAL,LORFILS,BENSON,NULL,Male,African-American,08/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +60969,69997,63470,PRETRIAL,LORFILS,BENSON,NULL,Male,African-American,08/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60951,69976,63450,PRETRIAL,RISOR,CHRISTOPHER,W,Male,Caucasian,10/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +60951,69976,63450,PRETRIAL,RISOR,CHRISTOPHER,W,Male,Caucasian,10/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +60951,69976,63450,PRETRIAL,RISOR,CHRISTOPHER,W,Male,Caucasian,10/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60960,69987,63461,Probation,Oneal,Raenesha,NULL,Female,African-American,04/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +60960,69987,63461,Probation,Oneal,Raenesha,NULL,Female,African-American,04/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,4,High,8,Risk of Recidivism,0.37,9,High,New,1,0 +60960,69987,63461,Probation,Oneal,Raenesha,NULL,Female,African-American,04/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,4,High,18,Risk of Failure to Appear,20,4,Low,New,1,0 +60946,69971,63445,PRETRIAL,ANDREU,LLOREN,NULL,Male,Caucasian,09/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +60946,69971,63445,PRETRIAL,ANDREU,LLOREN,NULL,Male,Caucasian,09/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +60946,69971,63445,PRETRIAL,ANDREU,LLOREN,NULL,Male,Caucasian,09/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +49929,70005,50868,PRETRIAL,Walton,Johnie,Lee,Male,African-American,06/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/4/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,Copy,1,0 +49929,70005,50868,PRETRIAL,Walton,Johnie,Lee,Male,African-American,06/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,Copy,1,0 +49929,70005,50868,PRETRIAL,Walton,Johnie,Lee,Male,African-American,06/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/4/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +60953,69979,63453,PRETRIAL,Panton,Sheldon,R,Male,African-American,05/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +60953,69979,63453,PRETRIAL,Panton,Sheldon,R,Male,African-American,05/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,4,High,8,Risk of Recidivism,0.17,8,High,New,1,0 +60953,69979,63453,PRETRIAL,Panton,Sheldon,R,Male,African-American,05/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60958,69984,63458,PRETRIAL,Joyce,Jeremy,A,Male,Caucasian,08/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/4/14 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +60958,69984,63458,PRETRIAL,Joyce,Jeremy,A,Male,Caucasian,08/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/4/14 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +60958,69984,63458,PRETRIAL,Joyce,Jeremy,A,Male,Caucasian,08/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60970,69998,63471,Probation,Tran,Anhnhi,NULL,Female,Oriental,08/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +60970,69998,63471,Probation,Tran,Anhnhi,NULL,Female,Oriental,08/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +60970,69998,63471,Probation,Tran,Anhnhi,NULL,Female,Oriental,08/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60984,70016,63487,PRETRIAL,Adams,Paul,NULL,Male,African-American,01/30/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +60984,70016,63487,PRETRIAL,Adams,Paul,NULL,Male,African-American,01/30/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.29,5,Medium,New,1,0 +60984,70016,63487,PRETRIAL,Adams,Paul,NULL,Male,African-American,01/30/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,New,1,0 +60980,70012,63483,Probation,WRIGHT,STEVEN,NULL,Male,African-American,04/29/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +60980,70012,63483,Probation,WRIGHT,STEVEN,NULL,Male,African-American,04/29/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +60980,70012,63483,Probation,WRIGHT,STEVEN,NULL,Male,African-American,04/29/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60976,70007,63479,Probation,McKenzie,Michael,NULL,Male,African-American,08/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +60976,70007,63479,Probation,McKenzie,Michael,NULL,Male,African-American,08/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.86,10,High,New,1,0 +60976,70007,63479,Probation,McKenzie,Michael,NULL,Male,African-American,08/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60952,69977,63451,PRETRIAL,GRIER,JONDRA,RUTH,Female,African-American,09/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +60952,69977,63451,PRETRIAL,GRIER,JONDRA,RUTH,Female,African-American,09/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +60952,69977,63451,PRETRIAL,GRIER,JONDRA,RUTH,Female,African-American,09/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60961,69986,63460,PRETRIAL,Girlie,Mark,NULL,Male,African-American,10/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,4,High,7,Risk of Violence,0.38,10,High,New,1,0 +60961,69986,63460,PRETRIAL,Girlie,Mark,NULL,Male,African-American,10/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,4,High,8,Risk of Recidivism,1.12,10,High,New,1,0 +60961,69986,63460,PRETRIAL,Girlie,Mark,NULL,Male,African-American,10/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60965,69993,63466,Probation,Zabala,Hedwing,NULL,Male,Caucasian,10/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/4/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +60965,69993,63466,Probation,Zabala,Hedwing,NULL,Male,Caucasian,10/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +60965,69993,63466,Probation,Zabala,Hedwing,NULL,Male,Caucasian,10/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60947,69972,63446,PRETRIAL,Dukes,Robert,Cord,Male,African-American,02/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/4/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +60947,69972,63446,PRETRIAL,Dukes,Robert,Cord,Male,African-American,02/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/4/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +60947,69972,63446,PRETRIAL,Dukes,Robert,Cord,Male,African-American,02/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60962,69991,63464,PRETRIAL,joseph,venson,NULL,Male,African-American,10/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +60962,69991,63464,PRETRIAL,joseph,venson,NULL,Male,African-American,10/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +60962,69991,63464,PRETRIAL,joseph,venson,NULL,Male,African-American,10/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60971,70000,63473,Probation,Saunders,Susan,NULL,Female,Caucasian,10/21/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +60971,70000,63473,Probation,Saunders,Susan,NULL,Female,Caucasian,10/21/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +60971,70000,63473,Probation,Saunders,Susan,NULL,Female,Caucasian,10/21/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60982,70014,63485,Probation,Sanchez Escobar,Barbara,NULL,Female,Hispanic,12/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +60982,70014,63485,Probation,Sanchez Escobar,Barbara,NULL,Female,Hispanic,12/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +60982,70014,63485,Probation,Sanchez Escobar,Barbara,NULL,Female,Hispanic,12/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60972,70001,63474,Probation,SELF,DAULTON,NULL,Male,Caucasian,08/22/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +60972,70001,63474,Probation,SELF,DAULTON,NULL,Male,Caucasian,08/22/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +60972,70001,63474,Probation,SELF,DAULTON,NULL,Male,Caucasian,08/22/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60954,69980,63454,PRETRIAL,Tilghman,Kenneth,NULL,Male,African-American,09/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,4,High,7,Risk of Violence,-0.42,10,High,New,1,0 +60954,69980,63454,PRETRIAL,Tilghman,Kenneth,NULL,Male,African-American,09/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,4,High,8,Risk of Recidivism,0.91,10,High,New,1,0 +60954,69980,63454,PRETRIAL,Tilghman,Kenneth,NULL,Male,African-American,09/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60957,69983,63457,PRETRIAL,BALWAH,VINDAR,NULL,Male,Other,05/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +60957,69983,63457,PRETRIAL,BALWAH,VINDAR,NULL,Male,Other,05/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +60957,69983,63457,PRETRIAL,BALWAH,VINDAR,NULL,Male,Other,05/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +49456,70009,50305,PRETRIAL,Coleman,John,Henry,Male,African-American,08/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/4/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,Copy,1,0 +49456,70009,50305,PRETRIAL,Coleman,John,Henry,Male,African-American,08/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/4/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,Copy,1,0 +49456,70009,50305,PRETRIAL,Coleman,John,Henry,Male,African-American,08/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +60950,69975,63449,PRETRIAL,healey,patrice,marie,Female,African-American,04/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +60950,69975,63449,PRETRIAL,healey,patrice,marie,Female,African-American,04/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.41,6,Medium,New,1,0 +60950,69975,63449,PRETRIAL,healey,patrice,marie,Female,African-American,04/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/4/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +60961,69988,63460,PRETRIAL,Girlie,Mark,NULL,Male,African-American,10/09/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,4,High,7,Risk of Violence,0.38,10,High,Copy,1,0 +60961,69988,63460,PRETRIAL,Girlie,Mark,NULL,Male,African-American,10/09/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,4,High,8,Risk of Recidivism,1.12,10,High,Copy,1,0 +60961,69988,63460,PRETRIAL,Girlie,Mark,NULL,Male,African-American,10/09/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/4/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +60974,70004,63477,Probation,prosise,kenneth,NULL,Male,Hispanic,04/25/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +60974,70004,63477,Probation,prosise,kenneth,NULL,Male,Hispanic,04/25/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +60974,70004,63477,Probation,prosise,kenneth,NULL,Male,Hispanic,04/25/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/4/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60968,69996,63469,PRETRIAL,MAYNARD,JACOB,NULL,Male,Caucasian,01/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/4/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +60968,69996,63469,PRETRIAL,MAYNARD,JACOB,NULL,Male,Caucasian,01/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/4/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +60968,69996,63469,PRETRIAL,MAYNARD,JACOB,NULL,Male,Caucasian,01/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60998,70032,63502,PRETRIAL,DEFELICE,THOMAS,NULL,Male,Caucasian,02/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +60998,70032,63502,PRETRIAL,DEFELICE,THOMAS,NULL,Male,Caucasian,02/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +60998,70032,63502,PRETRIAL,DEFELICE,THOMAS,NULL,Male,Caucasian,02/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60985,70017,63488,PRETRIAL,MONTGOMERY,ARRINGTON,XAVIER,Male,African-American,11/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +60985,70017,63488,PRETRIAL,MONTGOMERY,ARRINGTON,XAVIER,Male,African-American,11/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +60985,70017,63488,PRETRIAL,MONTGOMERY,ARRINGTON,XAVIER,Male,African-American,11/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61009,70046,63515,PRETRIAL,Pacchiana,John,NULL,Male,Caucasian,06/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +61009,70046,63515,PRETRIAL,Pacchiana,John,NULL,Male,Caucasian,06/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +61009,70046,63515,PRETRIAL,Pacchiana,John,NULL,Male,Caucasian,06/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60992,70025,63495,Probation,loughan,john,NULL,Male,Caucasian,02/09/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/5/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +60992,70025,63495,Probation,loughan,john,NULL,Male,Caucasian,02/09/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/5/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +60992,70025,63495,Probation,loughan,john,NULL,Male,Caucasian,02/09/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61003,70038,63507,Probation,Fouts,William,NULL,Male,Caucasian,10/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +61003,70038,63507,Probation,Fouts,William,NULL,Male,Caucasian,10/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +61003,70038,63507,Probation,Fouts,William,NULL,Male,Caucasian,10/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61006,70040,63509,Probation,PIERRE,PETERSON,NULL,Male,African-American,10/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +61006,70040,63509,Probation,PIERRE,PETERSON,NULL,Male,African-American,10/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +61006,70040,63509,Probation,PIERRE,PETERSON,NULL,Male,African-American,10/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +47684,70022,48260,Probation,Pinkney,Shanaice,NULL,Female,African-American,09/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,Copy,1,0 +47684,70022,48260,Probation,Pinkney,Shanaice,NULL,Female,African-American,09/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,Copy,1,0 +47684,70022,48260,Probation,Pinkney,Shanaice,NULL,Female,African-American,09/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +61008,70043,63512,Probation,duggan,michael,NULL,Male,Caucasian,01/31/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +61008,70043,63512,Probation,duggan,michael,NULL,Male,Caucasian,01/31/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +61008,70043,63512,Probation,duggan,michael,NULL,Male,Caucasian,01/31/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60997,70030,63500,Probation,GIAMBRONE,PAUL,WILLIAM,Male,Caucasian,11/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +60997,70030,63500,Probation,GIAMBRONE,PAUL,WILLIAM,Male,Caucasian,11/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +60997,70030,63500,Probation,GIAMBRONE,PAUL,WILLIAM,Male,Caucasian,11/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61011,70048,63517,Probation,LOVETT,RODQUEZ,NULL,Male,African-American,12/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.13,8,High,New,1,0 +61011,70048,63517,Probation,LOVETT,RODQUEZ,NULL,Male,African-American,12/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +61011,70048,63517,Probation,LOVETT,RODQUEZ,NULL,Male,African-American,12/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60989,70021,63492,PRETRIAL,Early,Eriane,L,Female,African-American,09/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +60989,70021,63492,PRETRIAL,Early,Eriane,L,Female,African-American,09/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +60989,70021,63492,PRETRIAL,Early,Eriane,L,Female,African-American,09/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60995,70028,63498,Probation,Mingoia,Joseph,NULL,Male,Caucasian,01/14/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +60995,70028,63498,Probation,Mingoia,Joseph,NULL,Male,Caucasian,01/14/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +60995,70028,63498,Probation,Mingoia,Joseph,NULL,Male,Caucasian,01/14/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58348,70035,60574,PRETRIAL,GUILLAUME,JOHN,JONERCE,Male,African-American,05/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +58348,70035,60574,PRETRIAL,GUILLAUME,JOHN,JONERCE,Male,African-American,05/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +58348,70035,60574,PRETRIAL,GUILLAUME,JOHN,JONERCE,Male,African-American,05/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61007,70042,63511,PRETRIAL,MURDOCK,TENESHA,NULL,Female,African-American,09/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +61007,70042,63511,PRETRIAL,MURDOCK,TENESHA,NULL,Female,African-American,09/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +61007,70042,63511,PRETRIAL,MURDOCK,TENESHA,NULL,Female,African-American,09/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60987,70019,63490,PRETRIAL,Bessard,Jimmy,NULL,Male,Other,06/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +60987,70019,63490,PRETRIAL,Bessard,Jimmy,NULL,Male,Other,06/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +60987,70019,63490,PRETRIAL,Bessard,Jimmy,NULL,Male,Other,06/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61002,70037,63506,Probation,LANDAU,MYLES,NULL,Male,Caucasian,07/03/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +61002,70037,63506,Probation,LANDAU,MYLES,NULL,Male,Caucasian,07/03/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +61002,70037,63506,Probation,LANDAU,MYLES,NULL,Male,Caucasian,07/03/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61000,70033,63503,Probation,Miller,Terence,NULL,Male,African-American,03/08/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +61000,70033,63503,Probation,Miller,Terence,NULL,Male,African-American,03/08/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +61000,70033,63503,Probation,Miller,Terence,NULL,Male,African-American,03/08/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60986,70018,63489,PRETRIAL,Hawkins,Lakesia,Davida,Female,African-American,04/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +60986,70018,63489,PRETRIAL,Hawkins,Lakesia,Davida,Female,African-American,04/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +60986,70018,63489,PRETRIAL,Hawkins,Lakesia,Davida,Female,African-American,04/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61005,70039,63508,Probation,cruz,jeremiah,NULL,Male,Hispanic,01/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,2,Medium,7,Risk of Violence,-2.63,2,Low,New,1,0 +61005,70039,63508,Probation,cruz,jeremiah,NULL,Male,Hispanic,01/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +61005,70039,63508,Probation,cruz,jeremiah,NULL,Male,Hispanic,01/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60993,70026,63496,Probation,Carlin,Joseph,Michael,Male,Caucasian,10/04/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/5/14 0:00,2,Medium,7,Risk of Violence,-3.01,1,Low,New,1,0 +60993,70026,63496,Probation,Carlin,Joseph,Michael,Male,Caucasian,10/04/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +60993,70026,63496,Probation,Carlin,Joseph,Michael,Male,Caucasian,10/04/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/5/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +40286,70044,63513,PRETRIAL,Bryant,Anton,NULL,Male,African-American,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +40286,70044,63513,PRETRIAL,Bryant,Anton,NULL,Male,African-American,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,4,High,8,Risk of Recidivism,0.43,9,High,New,1,0 +40286,70044,63513,PRETRIAL,Bryant,Anton,NULL,Male,African-American,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61010,70047,63516,Probation,Gomez,Jose,NULL,Male,Hispanic,08/19/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/5/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +61010,70047,63516,Probation,Gomez,Jose,NULL,Male,Hispanic,08/19/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/5/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +61010,70047,63516,Probation,Gomez,Jose,NULL,Male,Hispanic,08/19/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60990,70023,63493,PRETRIAL,MANNING,DAVID,ALAN,Male,Caucasian,03/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/5/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +60990,70023,63493,PRETRIAL,MANNING,DAVID,ALAN,Male,Caucasian,03/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/5/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +60990,70023,63493,PRETRIAL,MANNING,DAVID,ALAN,Male,Caucasian,03/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60999,70031,63501,Probation,Campbell,Leroy,NULL,Male,African-American,04/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/5/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +60999,70031,63501,Probation,Campbell,Leroy,NULL,Male,African-American,04/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/5/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +60999,70031,63501,Probation,Campbell,Leroy,NULL,Male,African-American,04/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60994,70027,63497,PRETRIAL,LACAYO,CARLOS,NULL,Male,Hispanic,02/03/53,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +60994,70027,63497,PRETRIAL,LACAYO,CARLOS,NULL,Male,Hispanic,02/03/53,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +60994,70027,63497,PRETRIAL,LACAYO,CARLOS,NULL,Male,Hispanic,02/03/53,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +60996,70029,63499,Probation,Herrera,Miguel,NULL,Male,Hispanic,04/22/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/5/14 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +60996,70029,63499,Probation,Herrera,Miguel,NULL,Male,Hispanic,04/22/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/5/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +60996,70029,63499,Probation,Herrera,Miguel,NULL,Male,Hispanic,04/22/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +38617,70034,63504,PRETRIAL,Williams,Quenton,NULL,Male,African-American,07/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +38617,70034,63504,PRETRIAL,Williams,Quenton,NULL,Male,African-American,07/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +38617,70034,63504,PRETRIAL,Williams,Quenton,NULL,Male,African-American,07/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61001,70036,63505,Probation,harris,jamaar,NULL,Male,African-American,06/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +61001,70036,63505,Probation,harris,jamaar,NULL,Male,African-American,06/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +61001,70036,63505,Probation,harris,jamaar,NULL,Male,African-American,06/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61013,70050,63519,PRETRIAL,Bouma,Chad,NULL,Male,Caucasian,08/31/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +61013,70050,63519,PRETRIAL,Bouma,Chad,NULL,Male,Caucasian,08/31/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +61013,70050,63519,PRETRIAL,Bouma,Chad,NULL,Male,Caucasian,08/31/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,23,4,Low,New,1,0 +60988,70020,63491,PRETRIAL,Anderson,Curtis,Dewayne,Male,African-American,07/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +60988,70020,63491,PRETRIAL,Anderson,Curtis,Dewayne,Male,African-American,07/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +60988,70020,63491,PRETRIAL,Anderson,Curtis,Dewayne,Male,African-American,07/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +46804,70045,63514,PRETRIAL,BUFFORD,BRADEN,NULL,Male,Caucasian,05/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +46804,70045,63514,PRETRIAL,BUFFORD,BRADEN,NULL,Male,Caucasian,05/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +46804,70045,63514,PRETRIAL,BUFFORD,BRADEN,NULL,Male,Caucasian,05/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/5/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60991,70024,63494,PRETRIAL,Palmer,Brandy,Kishon,Female,African-American,12/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +60991,70024,63494,PRETRIAL,Palmer,Brandy,Kishon,Female,African-American,12/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +60991,70024,63494,PRETRIAL,Palmer,Brandy,Kishon,Female,African-American,12/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/5/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61004,70041,63510,Probation,Distefano,Christopher,NULL,Male,Caucasian,08/27/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/5/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +61004,70041,63510,Probation,Distefano,Christopher,NULL,Male,Caucasian,08/27/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/5/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +61004,70041,63510,Probation,Distefano,Christopher,NULL,Male,Caucasian,08/27/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61059,70092,63555,Probation,GIRALDO,JIMMY,ALBERTO,Male,Hispanic,07/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +61059,70092,63555,Probation,GIRALDO,JIMMY,ALBERTO,Male,Hispanic,07/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +61059,70092,63555,Probation,GIRALDO,JIMMY,ALBERTO,Male,Hispanic,07/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61035,70062,63529,PRETRIAL,Fleurima,Chantel,NULL,Male,African-American,06/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +61035,70062,63529,PRETRIAL,Fleurima,Chantel,NULL,Male,African-American,06/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +61035,70062,63529,PRETRIAL,Fleurima,Chantel,NULL,Male,African-American,06/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61045,70076,63541,Probation,Peterson,Jeffrey,NULL,Male,African-American,01/12/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.96,1,Low,New,1,0 +61045,70076,63541,Probation,Peterson,Jeffrey,NULL,Male,African-American,01/12/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +61045,70076,63541,Probation,Peterson,Jeffrey,NULL,Male,African-American,01/12/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61054,70087,63550,Probation,Salazar,John,Bravlio,Male,Hispanic,10/11/69,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/6/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +61054,70087,63550,Probation,Salazar,John,Bravlio,Male,Hispanic,10/11/69,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +61054,70087,63550,Probation,Salazar,John,Bravlio,Male,Hispanic,10/11/69,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +45090,70101,63564,PRETRIAL,Rosales,Daniel,NULL,Male,Hispanic,02/15/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/6/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +45090,70101,63564,PRETRIAL,Rosales,Daniel,NULL,Male,Hispanic,02/15/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +45090,70101,63564,PRETRIAL,Rosales,Daniel,NULL,Male,Hispanic,02/15/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +12228,12613,11719,PRETRIAL,MILLICAN,ANDREW,NULL,Male,Caucasian,03/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +12228,12613,11719,PRETRIAL,MILLICAN,ANDREW,NULL,Male,Caucasian,03/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +12228,12613,11719,PRETRIAL,MILLICAN,ANDREW,NULL,Male,Caucasian,03/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61038,70066,63533,PRETRIAL,Hampton,Christopher,NULL,Male,African-American,03/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +61038,70066,63533,PRETRIAL,Hampton,Christopher,NULL,Male,African-American,03/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +61038,70066,63533,PRETRIAL,Hampton,Christopher,NULL,Male,African-American,03/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61048,70080,63544,Probation,marquez,stephanie,NULL,Female,Caucasian,09/21/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +61048,70080,63544,Probation,marquez,stephanie,NULL,Female,Caucasian,09/21/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +61048,70080,63544,Probation,marquez,stephanie,NULL,Female,Caucasian,09/21/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61051,70083,63547,Probation,Sanevere,Nicole,NULL,Female,Hispanic,02/19/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +61051,70083,63547,Probation,Sanevere,Nicole,NULL,Female,Hispanic,02/19/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +61051,70083,63547,Probation,Sanevere,Nicole,NULL,Female,Hispanic,02/19/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61036,70064,63531,PRETRIAL,Glenn,Alfonso,B,Male,African-American,12/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +61036,70064,63531,PRETRIAL,Glenn,Alfonso,B,Male,African-American,12/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +61036,70064,63531,PRETRIAL,Glenn,Alfonso,B,Male,African-American,12/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61066,70099,63562,Probation,olaiyar,jonathan,NULL,Male,Other,04/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +61066,70099,63562,Probation,olaiyar,jonathan,NULL,Male,Other,04/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +61066,70099,63562,Probation,olaiyar,jonathan,NULL,Male,Other,04/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61042,70071,63537,Probation,Gheorghe,Ilie,NULL,Male,Caucasian,09/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +61042,70071,63537,Probation,Gheorghe,Ilie,NULL,Male,Caucasian,09/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +61042,70071,63537,Probation,Gheorghe,Ilie,NULL,Male,Caucasian,09/11/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61046,70078,63542,PRETRIAL,Robert,Taylor,NULL,Male,Native American,12/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/6/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +61046,70078,63542,PRETRIAL,Robert,Taylor,NULL,Male,Native American,12/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +61046,70078,63542,PRETRIAL,Robert,Taylor,NULL,Male,Native American,12/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61052,70085,63548,Probation,thacker,jeffrey,NULL,Male,Caucasian,12/26/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +61052,70085,63548,Probation,thacker,jeffrey,NULL,Male,Caucasian,12/26/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +61052,70085,63548,Probation,thacker,jeffrey,NULL,Male,Caucasian,12/26/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61018,70055,63522,PRETRIAL,GARCIA,CARLOS,ALONSO,Male,Hispanic,12/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,New,1,0 +61018,70055,63522,PRETRIAL,GARCIA,CARLOS,ALONSO,Male,Hispanic,12/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +61018,70055,63522,PRETRIAL,GARCIA,CARLOS,ALONSO,Male,Hispanic,12/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61023,70057,63524,PRETRIAL,Ziegler,Leon,Andrew,Male,African-American,09/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +61023,70057,63524,PRETRIAL,Ziegler,Leon,Andrew,Male,African-American,09/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +61023,70057,63524,PRETRIAL,Ziegler,Leon,Andrew,Male,African-American,09/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59359,70106,61678,Probation,Philo,Ed,NULL,Male,African-American,05/14/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.31,7,Medium,New,1,0 +59359,70106,61678,Probation,Philo,Ed,NULL,Male,African-American,05/14/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +59359,70106,61678,Probation,Philo,Ed,NULL,Male,African-American,05/14/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +61049,70081,63545,Probation,Wright,Timothy,Daquay,Male,African-American,07/31/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +61049,70081,63545,Probation,Wright,Timothy,Daquay,Male,African-American,07/31/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +61049,70081,63545,Probation,Wright,Timothy,Daquay,Male,African-American,07/31/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61032,70060,63527,PRETRIAL,Ramson,Cavoan,NULL,Male,African-American,10/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +61032,70060,63527,PRETRIAL,Ramson,Cavoan,NULL,Male,African-American,10/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +61032,70060,63527,PRETRIAL,Ramson,Cavoan,NULL,Male,African-American,10/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61063,70096,63559,Probation,Janitelli,Paul,NULL,Male,Other,07/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +61063,70096,63559,Probation,Janitelli,Paul,NULL,Male,Other,07/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +61063,70096,63559,Probation,Janitelli,Paul,NULL,Male,Other,07/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61056,70089,63552,PRETRIAL,Jackson,Jack,NULL,Male,Caucasian,11/05/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +61056,70089,63552,PRETRIAL,Jackson,Jack,NULL,Male,Caucasian,11/05/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +61056,70089,63552,PRETRIAL,Jackson,Jack,NULL,Male,Caucasian,11/05/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61040,70068,63535,PRETRIAL,Bruce,Andrew,NULL,Male,Caucasian,08/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +61040,70068,63535,PRETRIAL,Bruce,Andrew,NULL,Male,Caucasian,08/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +61040,70068,63535,PRETRIAL,Bruce,Andrew,NULL,Male,Caucasian,08/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61067,70102,63565,Probation,Campos,Celio,Cezar,Male,Hispanic,12/15/62,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +61067,70102,63565,Probation,Campos,Celio,Cezar,Male,Hispanic,12/15/62,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +61067,70102,63565,Probation,Campos,Celio,Cezar,Male,Hispanic,12/15/62,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50565,70104,63567,PRETRIAL,Ramirez,Steven,NULL,Male,Hispanic,12/29/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +50565,70104,63567,PRETRIAL,Ramirez,Steven,NULL,Male,Hispanic,12/29/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +50565,70104,63567,PRETRIAL,Ramirez,Steven,NULL,Male,Hispanic,12/29/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61037,70065,63532,PRETRIAL,Hampton,Larry,NULL,Male,African-American,09/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +61037,70065,63532,PRETRIAL,Hampton,Larry,NULL,Male,African-American,09/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +61037,70065,63532,PRETRIAL,Hampton,Larry,NULL,Male,African-American,09/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61061,70094,63557,Probation,Meenan,Nichlas,Anthony,Male,Caucasian,12/21/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/6/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +61061,70094,63557,Probation,Meenan,Nichlas,Anthony,Male,Caucasian,12/21/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +61061,70094,63557,Probation,Meenan,Nichlas,Anthony,Male,Caucasian,12/21/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61043,70073,63538,Probation,Miller,Vince,William,Male,Caucasian,08/27/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/6/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +61043,70073,63538,Probation,Miller,Vince,William,Male,Caucasian,08/27/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +61043,70073,63538,Probation,Miller,Vince,William,Male,Caucasian,08/27/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61014,70052,63520,PRETRIAL,Wells,Cortay,D,Male,African-American,05/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,New,1,0 +61014,70052,63520,PRETRIAL,Wells,Cortay,D,Male,African-American,05/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +61014,70052,63520,PRETRIAL,Wells,Cortay,D,Male,African-American,05/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61053,70086,63549,PRETRIAL,Kluenie,Dawn,NULL,Female,Caucasian,09/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/6/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +61053,70086,63549,PRETRIAL,Kluenie,Dawn,NULL,Female,Caucasian,09/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/6/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +61053,70086,63549,PRETRIAL,Kluenie,Dawn,NULL,Female,Caucasian,09/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61017,70054,63521,PRETRIAL,CLARKE,SHAWN,ANDRE,Male,African-American,03/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +61017,70054,63521,PRETRIAL,CLARKE,SHAWN,ANDRE,Male,African-American,03/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +61017,70054,63521,PRETRIAL,CLARKE,SHAWN,ANDRE,Male,African-American,03/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61047,70079,63543,Probation,Kidane,Fertuna,NULL,Female,African-American,03/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +61047,70079,63543,Probation,Kidane,Fertuna,NULL,Female,African-American,03/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +61047,70079,63543,Probation,Kidane,Fertuna,NULL,Female,African-American,03/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +49377,70084,50213,Probation,simon,mania,NULL,Male,African-American,06/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,Copy,1,0 +49377,70084,50213,Probation,simon,mania,NULL,Male,African-American,06/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,Copy,1,0 +49377,70084,50213,Probation,simon,mania,NULL,Male,African-American,06/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +51119,70058,63525,Probation,Paredes,DIONISQUI,NULL,Female,Hispanic,05/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +51119,70058,63525,Probation,Paredes,DIONISQUI,NULL,Female,Hispanic,05/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +51119,70058,63525,Probation,Paredes,DIONISQUI,NULL,Female,Hispanic,05/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61044,70075,63540,Probation,rowles,lucy,NULL,Female,Caucasian,01/24/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +61044,70075,63540,Probation,rowles,lucy,NULL,Female,Caucasian,01/24/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +61044,70075,63540,Probation,rowles,lucy,NULL,Female,Caucasian,01/24/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61069,70105,63568,Probation,singleton,quinten,NULL,Male,African-American,12/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +61069,70105,63568,Probation,singleton,quinten,NULL,Male,African-American,12/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +61069,70105,63568,Probation,singleton,quinten,NULL,Male,African-American,12/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61034,70063,63530,PRETRIAL,CLERISIER,JACKSON,RITCHI,Male,African-American,09/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/6/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +61034,70063,63530,PRETRIAL,CLERISIER,JACKSON,RITCHI,Male,African-American,09/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +61034,70063,63530,PRETRIAL,CLERISIER,JACKSON,RITCHI,Male,African-American,09/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54032,70100,63563,PRETRIAL,Navasmejia,Jhonatan,NULL,Male,Hispanic,07/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +54032,70100,63563,PRETRIAL,Navasmejia,Jhonatan,NULL,Male,Hispanic,07/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +54032,70100,63563,PRETRIAL,Navasmejia,Jhonatan,NULL,Male,Hispanic,07/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60196,70072,62603,Probation,Lynch,Danielle,NULL,Female,African-American,07/28/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.12,4,Low,Copy,1,0 +60196,70072,62603,Probation,Lynch,Danielle,NULL,Female,African-American,07/28/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,Copy,1,0 +60196,70072,62603,Probation,Lynch,Danielle,NULL,Female,African-American,07/28/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +61058,70091,63554,Probation,ridener,eric,NULL,Male,Caucasian,09/09/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/6/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +61058,70091,63554,Probation,ridener,eric,NULL,Male,Caucasian,09/09/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +61058,70091,63554,Probation,ridener,eric,NULL,Male,Caucasian,09/09/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61041,70070,63536,Probation,Decarlos,Marlene,NULL,Female,Caucasian,08/17/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +61041,70070,63536,Probation,Decarlos,Marlene,NULL,Female,Caucasian,08/17/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +61041,70070,63536,Probation,Decarlos,Marlene,NULL,Female,Caucasian,08/17/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61060,70093,63556,PRETRIAL,VLADO,ALLEN,NULL,Male,Caucasian,03/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.63,2,Low,New,1,0 +61060,70093,63556,PRETRIAL,VLADO,ALLEN,NULL,Male,Caucasian,03/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +61060,70093,63556,PRETRIAL,VLADO,ALLEN,NULL,Male,Caucasian,03/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +33228,61010,55392,PRETRIAL,DOUGLAS,JEVON,NULL,Male,Other,04/01/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +33228,61010,55392,PRETRIAL,DOUGLAS,JEVON,NULL,Male,Other,04/01/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +33228,61010,55392,PRETRIAL,DOUGLAS,JEVON,NULL,Male,Other,04/01/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61064,70098,63561,Probation,Maraancelmo,Jolber,NULL,Male,Hispanic,10/22/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +61064,70098,63561,Probation,Maraancelmo,Jolber,NULL,Male,Hispanic,10/22/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +61064,70098,63561,Probation,Maraancelmo,Jolber,NULL,Male,Hispanic,10/22/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +37476,70051,50449,PRETRIAL,MCQUEEN,PERRY,NULL,Male,African-American,03/26/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/6/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,Copy,1,0 +37476,70051,50449,PRETRIAL,MCQUEEN,PERRY,NULL,Male,African-American,03/26/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,Copy,1,0 +37476,70051,50449,PRETRIAL,MCQUEEN,PERRY,NULL,Male,African-American,03/26/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +49440,70069,50285,Probation,Fitzgerald,Lee,NULL,Female,Caucasian,11/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/6/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,Copy,1,0 +49440,70069,50285,Probation,Fitzgerald,Lee,NULL,Female,Caucasian,11/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,Copy,1,0 +49440,70069,50285,Probation,Fitzgerald,Lee,NULL,Female,Caucasian,11/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +15663,70077,62572,PRETRIAL,REYES,CHARLIE,NULL,Male,Hispanic,02/02/92,17,All Scales,Intake,English,Other,Probation,Single,2/6/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +15663,70077,62572,PRETRIAL,REYES,CHARLIE,NULL,Male,Hispanic,02/02/92,17,All Scales,Intake,English,Other,Probation,Single,2/6/14 0:00,2,Medium,8,Risk of Recidivism,0.09,7,Medium,New,1,0 +15663,70077,62572,PRETRIAL,REYES,CHARLIE,NULL,Male,Hispanic,02/02/92,17,All Scales,Intake,English,Other,Probation,Single,2/6/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +61022,70056,63523,PRETRIAL,Anderson,Wesley,Kyreecharl,Male,African-American,09/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +61022,70056,63523,PRETRIAL,Anderson,Wesley,Kyreecharl,Male,African-American,09/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +61022,70056,63523,PRETRIAL,Anderson,Wesley,Kyreecharl,Male,African-American,09/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61057,70090,63553,Probation,Armstrong,Julie,NULL,Female,Caucasian,10/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +61057,70090,63553,Probation,Armstrong,Julie,NULL,Female,Caucasian,10/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +61057,70090,63553,Probation,Armstrong,Julie,NULL,Female,Caucasian,10/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +41449,70059,63526,PRETRIAL,Darby,Billy,Joe,Male,African-American,01/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +41449,70059,63526,PRETRIAL,Darby,Billy,Joe,Male,African-American,01/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +41449,70059,63526,PRETRIAL,Darby,Billy,Joe,Male,African-American,01/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61033,70061,63528,PRETRIAL,Semple,Andrew,NULL,Male,Caucasian,05/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +61033,70061,63528,PRETRIAL,Semple,Andrew,NULL,Male,Caucasian,05/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +61033,70061,63528,PRETRIAL,Semple,Andrew,NULL,Male,Caucasian,05/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61062,70095,63558,Probation,Lacombe,Tania,NULL,Female,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +61062,70095,63558,Probation,Lacombe,Tania,NULL,Female,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +61062,70095,63558,Probation,Lacombe,Tania,NULL,Female,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +35016,70053,45441,Probation,taylor,javon,NULL,Male,African-American,06/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,4,High,7,Risk of Violence,-1.23,8,High,Copy,1,0 +35016,70053,45441,Probation,taylor,javon,NULL,Male,African-American,06/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,4,High,8,Risk of Recidivism,0.61,9,High,Copy,1,0 +35016,70053,45441,Probation,taylor,javon,NULL,Male,African-American,06/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +61068,70103,63566,Probation,Johnson,Tawana,NULL,Female,African-American,11/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +61068,70103,63566,Probation,Johnson,Tawana,NULL,Female,African-American,11/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +61068,70103,63566,Probation,Johnson,Tawana,NULL,Female,African-American,11/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61039,70067,63534,PRETRIAL,Green,Jerome,NULL,Male,African-American,07/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +61039,70067,63534,PRETRIAL,Green,Jerome,NULL,Male,African-American,07/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +61039,70067,63534,PRETRIAL,Green,Jerome,NULL,Male,African-American,07/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61050,70082,63546,PRETRIAL,Sirmons,John,NULL,Male,African-American,06/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/6/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +61050,70082,63546,PRETRIAL,Sirmons,John,NULL,Male,African-American,06/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/6/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +61050,70082,63546,PRETRIAL,Sirmons,John,NULL,Male,African-American,06/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61094,70132,63594,Probation,martinez-feliciano,gisela,NULL,Female,Hispanic,05/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +61094,70132,63594,Probation,martinez-feliciano,gisela,NULL,Female,Hispanic,05/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +61094,70132,63594,Probation,martinez-feliciano,gisela,NULL,Female,Hispanic,05/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61087,70124,63586,PRETRIAL,Janes,Joseph,NULL,Male,African-American,10/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +61087,70124,63586,PRETRIAL,Janes,Joseph,NULL,Male,African-American,10/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +61087,70124,63586,PRETRIAL,Janes,Joseph,NULL,Male,African-American,10/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61074,70111,63573,PRETRIAL,Kapell,Lloyd,NULL,Male,Caucasian,10/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +61074,70111,63573,PRETRIAL,Kapell,Lloyd,NULL,Male,Caucasian,10/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +61074,70111,63573,PRETRIAL,Kapell,Lloyd,NULL,Male,Caucasian,10/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61083,70119,63581,Probation,thompson,mark,NULL,Male,Caucasian,05/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +61083,70119,63581,Probation,thompson,mark,NULL,Male,Caucasian,05/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +61083,70119,63581,Probation,thompson,mark,NULL,Male,Caucasian,05/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61079,70116,63578,PRETRIAL,ALAMO,MARK,NULL,Male,Hispanic,06/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/14 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +61079,70116,63578,PRETRIAL,ALAMO,MARK,NULL,Male,Hispanic,06/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/14 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +61079,70116,63578,PRETRIAL,ALAMO,MARK,NULL,Male,Hispanic,06/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/7/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +2188,70114,63576,PRETRIAL,kendrick,corey,NULL,Male,African-American,02/27/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/7/14 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +2188,70114,63576,PRETRIAL,kendrick,corey,NULL,Male,African-American,02/27/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +2188,70114,63576,PRETRIAL,kendrick,corey,NULL,Male,African-American,02/27/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/7/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +35171,70121,63583,PRETRIAL,Brown,Jack,NULL,Male,African-American,03/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +35171,70121,63583,PRETRIAL,Brown,Jack,NULL,Male,African-American,03/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +35171,70121,63583,PRETRIAL,Brown,Jack,NULL,Male,African-American,03/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +61091,70128,63590,Probation,DEPIETRI,DAVID,ALLEN,Male,Caucasian,04/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +61091,70128,63590,Probation,DEPIETRI,DAVID,ALLEN,Male,Caucasian,04/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +61091,70128,63590,Probation,DEPIETRI,DAVID,ALLEN,Male,Caucasian,04/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61072,70109,63571,PRETRIAL,Fleming,Jerome,NULL,Male,African-American,06/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +61072,70109,63571,PRETRIAL,Fleming,Jerome,NULL,Male,African-American,06/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +61072,70109,63571,PRETRIAL,Fleming,Jerome,NULL,Male,African-American,06/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57541,65765,59654,PRETRIAL,Cummings,Michelle,NULL,Female,African-American,06/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/7/14 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +57541,65765,59654,PRETRIAL,Cummings,Michelle,NULL,Female,African-American,06/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/7/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +57541,65765,59654,PRETRIAL,Cummings,Michelle,NULL,Female,African-American,06/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61093,70130,63592,Probation,STROHMANN,ROCHELLE,LYNN,Female,Caucasian,07/18/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/7/14 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +61093,70130,63592,Probation,STROHMANN,ROCHELLE,LYNN,Female,Caucasian,07/18/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/7/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +61093,70130,63592,Probation,STROHMANN,ROCHELLE,LYNN,Female,Caucasian,07/18/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61089,70126,63588,PRETRIAL,Zaren,Gusdino,NULL,Male,Caucasian,09/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +61089,70126,63588,PRETRIAL,Zaren,Gusdino,NULL,Male,Caucasian,09/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +61089,70126,63588,PRETRIAL,Zaren,Gusdino,NULL,Male,Caucasian,09/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61070,70107,63569,PRETRIAL,Goodwin,Pamela,NULL,Female,African-American,09/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +61070,70107,63569,PRETRIAL,Goodwin,Pamela,NULL,Female,African-American,09/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +61070,70107,63569,PRETRIAL,Goodwin,Pamela,NULL,Female,African-American,09/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61075,70112,63574,PRETRIAL,Yaggle,Robert,NULL,Male,Caucasian,11/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +61075,70112,63574,PRETRIAL,Yaggle,Robert,NULL,Male,Caucasian,11/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +61075,70112,63574,PRETRIAL,Yaggle,Robert,NULL,Male,Caucasian,11/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61086,70123,63585,PRETRIAL,Rodriguez,Jorge,NULL,Male,Hispanic,11/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +61086,70123,63585,PRETRIAL,Rodriguez,Jorge,NULL,Male,Hispanic,11/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +61086,70123,63585,PRETRIAL,Rodriguez,Jorge,NULL,Male,Hispanic,11/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61088,70125,63587,PRETRIAL,LAKE,LEROY,NULL,Male,African-American,03/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +61088,70125,63587,PRETRIAL,LAKE,LEROY,NULL,Male,African-American,03/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +61088,70125,63587,PRETRIAL,LAKE,LEROY,NULL,Male,African-American,03/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +61073,70110,63572,PRETRIAL,Arrieta,Ricardo,Delcristo,Male,Caucasian,04/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +61073,70110,63572,PRETRIAL,Arrieta,Ricardo,Delcristo,Male,Caucasian,04/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +61073,70110,63572,PRETRIAL,Arrieta,Ricardo,Delcristo,Male,Caucasian,04/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61080,70117,63579,PRETRIAL,Wallace,Raymond,NULL,Male,African-American,11/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/7/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +61080,70117,63579,PRETRIAL,Wallace,Raymond,NULL,Male,African-American,11/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/7/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +61080,70117,63579,PRETRIAL,Wallace,Raymond,NULL,Male,African-American,11/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +38195,70131,63593,PRETRIAL,FITZPATRICK,DAVID,BOYD,Male,Caucasian,03/27/66,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +38195,70131,63593,PRETRIAL,FITZPATRICK,DAVID,BOYD,Male,Caucasian,03/27/66,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +38195,70131,63593,PRETRIAL,FITZPATRICK,DAVID,BOYD,Male,Caucasian,03/27/66,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +61071,70108,63570,PRETRIAL,Howard,James,Francis,Male,African-American,03/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +61071,70108,63570,PRETRIAL,Howard,James,Francis,Male,African-American,03/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +61071,70108,63570,PRETRIAL,Howard,James,Francis,Male,African-American,03/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61090,70127,63589,Probation,Fray,Sheldon,Kevin,Male,African-American,04/27/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +61090,70127,63589,Probation,Fray,Sheldon,Kevin,Male,African-American,04/27/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +61090,70127,63589,Probation,Fray,Sheldon,Kevin,Male,African-American,04/27/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61092,70129,63591,Probation,Worley,John,NULL,Male,Caucasian,12/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +61092,70129,63591,Probation,Worley,John,NULL,Male,Caucasian,12/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +61092,70129,63591,Probation,Worley,John,NULL,Male,Caucasian,12/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61076,70113,63575,PRETRIAL,Dubois,Austin,NULL,Male,Caucasian,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +61076,70113,63575,PRETRIAL,Dubois,Austin,NULL,Male,Caucasian,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +61076,70113,63575,PRETRIAL,Dubois,Austin,NULL,Male,Caucasian,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61085,70122,63584,Probation,levine,amanda,NULL,Female,Caucasian,02/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +61085,70122,63584,Probation,levine,amanda,NULL,Female,Caucasian,02/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +61085,70122,63584,Probation,levine,amanda,NULL,Female,Caucasian,02/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/7/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61081,70118,63580,Probation,ACOSTA,ERIK,NULL,Male,Hispanic,08/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/7/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +61081,70118,63580,Probation,ACOSTA,ERIK,NULL,Male,Hispanic,08/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/7/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +61081,70118,63580,Probation,ACOSTA,ERIK,NULL,Male,Hispanic,08/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/7/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61099,70139,63600,PRETRIAL,WEIR,SEAN,NULL,Male,Caucasian,08/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/8/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +61099,70139,63600,PRETRIAL,WEIR,SEAN,NULL,Male,Caucasian,08/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/8/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +61099,70139,63600,PRETRIAL,WEIR,SEAN,NULL,Male,Caucasian,08/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61096,70134,63596,PRETRIAL,SANTIAGO,YOLEIDA,XIIOMARA,Female,Hispanic,08/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/8/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +61096,70134,63596,PRETRIAL,SANTIAGO,YOLEIDA,XIIOMARA,Female,Hispanic,08/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/8/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +61096,70134,63596,PRETRIAL,SANTIAGO,YOLEIDA,XIIOMARA,Female,Hispanic,08/30/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59475,70136,63598,PRETRIAL,BRUNDAGE,BRUCE,LAROSE,Male,African-American,06/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +59475,70136,63598,PRETRIAL,BRUNDAGE,BRUCE,LAROSE,Male,African-American,06/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +59475,70136,63598,PRETRIAL,BRUNDAGE,BRUCE,LAROSE,Male,African-American,06/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +61098,70138,63599,PRETRIAL,MYERS,CHRISTOPHER,RYAN,Male,Caucasian,04/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +61098,70138,63599,PRETRIAL,MYERS,CHRISTOPHER,RYAN,Male,Caucasian,04/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +61098,70138,63599,PRETRIAL,MYERS,CHRISTOPHER,RYAN,Male,Caucasian,04/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61095,70133,63595,PRETRIAL,Carter,Howard,NULL,Male,African-American,08/19/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +61095,70133,63595,PRETRIAL,Carter,Howard,NULL,Male,African-American,08/19/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +61095,70133,63595,PRETRIAL,Carter,Howard,NULL,Male,African-American,08/19/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61101,70141,63602,PRETRIAL,sites,danielle,NULL,Female,Caucasian,04/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +61101,70141,63602,PRETRIAL,sites,danielle,NULL,Female,Caucasian,04/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +61101,70141,63602,PRETRIAL,sites,danielle,NULL,Female,Caucasian,04/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61097,70135,63597,PRETRIAL,Powell,Thomas,NULL,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +61097,70135,63597,PRETRIAL,Powell,Thomas,NULL,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +61097,70135,63597,PRETRIAL,Powell,Thomas,NULL,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +35758,70137,34987,Probation,hatcher,michael,NULL,Male,Caucasian,01/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,Copy,1,0 +35758,70137,34987,Probation,hatcher,michael,NULL,Male,Caucasian,01/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,Copy,1,0 +35758,70137,34987,Probation,hatcher,michael,NULL,Male,Caucasian,01/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +61100,70140,63601,PRETRIAL,Berges,Osmar,NULL,Male,African-American,12/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,2,Medium,7,Risk of Violence,-2.49,3,Low,New,1,0 +61100,70140,63601,PRETRIAL,Berges,Osmar,NULL,Male,African-American,12/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +61100,70140,63601,PRETRIAL,Berges,Osmar,NULL,Male,African-American,12/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/8/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61108,70153,63611,PRETRIAL,ARDUZ,ERNESTO,NULL,Male,Caucasian,05/11/45,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +61108,70153,63611,PRETRIAL,ARDUZ,ERNESTO,NULL,Male,Caucasian,05/11/45,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,8,Risk of Recidivism,-2.77,1,Low,New,1,0 +61108,70153,63611,PRETRIAL,ARDUZ,ERNESTO,NULL,Male,Caucasian,05/11/45,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +20838,70145,63604,PRETRIAL,Michel,Berton,F,Male,African-American,09/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +20838,70145,63604,PRETRIAL,Michel,Berton,F,Male,African-American,09/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +20838,70145,63604,PRETRIAL,Michel,Berton,F,Male,African-American,09/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61105,70149,63607,PRETRIAL,Solomon,Prasada,NULL,Male,African-American,02/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +61105,70149,63607,PRETRIAL,Solomon,Prasada,NULL,Male,African-American,02/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +61105,70149,63607,PRETRIAL,Solomon,Prasada,NULL,Male,African-American,02/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +8728,70142,8262,PRETRIAL,FLOYD,MICHAEL,NULL,Male,African-American,12/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,Copy,1,0 +8728,70142,8262,PRETRIAL,FLOYD,MICHAEL,NULL,Male,African-American,12/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,Copy,1,0 +8728,70142,8262,PRETRIAL,FLOYD,MICHAEL,NULL,Male,African-American,12/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +31012,70144,47420,PRETRIAL,WILLIAMS,SAMMIE,NULL,Male,African-American,04/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/9/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,Copy,1,0 +31012,70144,47420,PRETRIAL,WILLIAMS,SAMMIE,NULL,Male,African-American,04/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/9/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,Copy,1,0 +31012,70144,47420,PRETRIAL,WILLIAMS,SAMMIE,NULL,Male,African-American,04/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/9/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +61107,70151,63609,PRETRIAL,SALES,RONALD,JEROME,Male,African-American,10/10/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +61107,70151,63609,PRETRIAL,SALES,RONALD,JEROME,Male,African-American,10/10/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +61107,70151,63609,PRETRIAL,SALES,RONALD,JEROME,Male,African-American,10/10/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61104,70147,63606,PRETRIAL,CRUZ,JONATHAN,NULL,Male,Caucasian,03/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +61104,70147,63606,PRETRIAL,CRUZ,JONATHAN,NULL,Male,Caucasian,03/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +61104,70147,63606,PRETRIAL,CRUZ,JONATHAN,NULL,Male,Caucasian,03/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61103,70146,63605,PRETRIAL,BARRETT,MERCEDES,IESHA,Female,African-American,12/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +61103,70146,63605,PRETRIAL,BARRETT,MERCEDES,IESHA,Female,African-American,12/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +61103,70146,63605,PRETRIAL,BARRETT,MERCEDES,IESHA,Female,African-American,12/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +61106,70150,63608,PRETRIAL,FOSCA,DANIEL,NULL,Male,Caucasian,10/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +61106,70150,63608,PRETRIAL,FOSCA,DANIEL,NULL,Male,Caucasian,10/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +61106,70150,63608,PRETRIAL,FOSCA,DANIEL,NULL,Male,Caucasian,10/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61102,70143,63603,PRETRIAL,MAYES,SYLENA,NULL,Female,African-American,05/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.44,3,Low,New,1,0 +61102,70143,63603,PRETRIAL,MAYES,SYLENA,NULL,Female,African-American,05/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,10,High,New,1,0 +61102,70143,63603,PRETRIAL,MAYES,SYLENA,NULL,Female,African-American,05/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +40490,70148,40108,PRETRIAL,Boney,Jimmy,Kenneth,Male,African-American,03/24/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,Copy,1,0 +40490,70148,40108,PRETRIAL,Boney,Jimmy,Kenneth,Male,African-American,03/24/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,Copy,1,0 +40490,70148,40108,PRETRIAL,Boney,Jimmy,Kenneth,Male,African-American,03/24/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +48466,70194,63651,PRETRIAL,Sims,Jerome,Aaron,Male,African-American,10/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +48466,70194,63651,PRETRIAL,Sims,Jerome,Aaron,Male,African-American,10/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +48466,70194,63651,PRETRIAL,Sims,Jerome,Aaron,Male,African-American,10/18/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61124,70173,63630,Probation,khan,Mofaz,Nicholas,Male,Caucasian,07/18/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +61124,70173,63630,Probation,khan,Mofaz,Nicholas,Male,Caucasian,07/18/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +61124,70173,63630,Probation,khan,Mofaz,Nicholas,Male,Caucasian,07/18/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61142,70190,63647,Probation,Phillips,Rodrick,Myers,Male,African-American,02/24/53,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +61142,70190,63647,Probation,Phillips,Rodrick,Myers,Male,African-American,02/24/53,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +61142,70190,63647,Probation,Phillips,Rodrick,Myers,Male,African-American,02/24/53,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61117,70164,63622,PRETRIAL,Babkin,Alexander,NULL,Male,Caucasian,06/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +61117,70164,63622,PRETRIAL,Babkin,Alexander,NULL,Male,Caucasian,06/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/14 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +61117,70164,63622,PRETRIAL,Babkin,Alexander,NULL,Male,Caucasian,06/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +41815,70199,63656,PRETRIAL,Wilson,John,NULL,Male,African-American,03/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +41815,70199,63656,PRETRIAL,Wilson,John,NULL,Male,African-American,03/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +41815,70199,63656,PRETRIAL,Wilson,John,NULL,Male,African-American,03/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61123,70171,63628,Probation,JACKSON,ERVIN,NULL,Male,African-American,07/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,7,Risk of Violence,-2.71,2,Low,New,1,0 +61123,70171,63628,Probation,JACKSON,ERVIN,NULL,Male,African-American,07/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +61123,70171,63628,Probation,JACKSON,ERVIN,NULL,Male,African-American,07/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61130,70178,63635,Probation,davis,johnny,NULL,Male,African-American,06/02/73,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,2/10/14 0:00,2,Medium,7,Risk of Violence,-2.52,3,Low,New,1,0 +61130,70178,63635,Probation,davis,johnny,NULL,Male,African-American,06/02/73,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,2/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +61130,70178,63635,Probation,davis,johnny,NULL,Male,African-American,06/02/73,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,2/10/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +48612,70185,63642,Probation,LUCCARELLI,SHAWN,NULL,Male,Caucasian,08/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +48612,70185,63642,Probation,LUCCARELLI,SHAWN,NULL,Male,Caucasian,08/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +48612,70185,63642,Probation,LUCCARELLI,SHAWN,NULL,Male,Caucasian,08/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61110,70155,63613,PRETRIAL,ANDERSON,MATTHEW,EARL,Male,Caucasian,06/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,New,1,0 +61110,70155,63613,PRETRIAL,ANDERSON,MATTHEW,EARL,Male,Caucasian,06/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +61110,70155,63613,PRETRIAL,ANDERSON,MATTHEW,EARL,Male,Caucasian,06/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61112,70157,63615,PRETRIAL,BIENAIME,ZANETI,NULL,Male,Other,10/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,4,High,7,Risk of Violence,-0.76,9,High,New,1,0 +61112,70157,63615,PRETRIAL,BIENAIME,ZANETI,NULL,Male,Other,10/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,4,High,8,Risk of Recidivism,0.67,10,High,New,1,0 +61112,70157,63615,PRETRIAL,BIENAIME,ZANETI,NULL,Male,Other,10/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +44063,70196,63653,PRETRIAL,Kenefick,Sharon,NULL,Female,Caucasian,07/26/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +44063,70196,63653,PRETRIAL,Kenefick,Sharon,NULL,Female,Caucasian,07/26/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +44063,70196,63653,PRETRIAL,Kenefick,Sharon,NULL,Female,Caucasian,07/26/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61120,70167,63625,Probation,kalinowski,scott,robert,Male,Caucasian,03/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +61120,70167,63625,Probation,kalinowski,scott,robert,Male,Caucasian,03/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +61120,70167,63625,Probation,kalinowski,scott,robert,Male,Caucasian,03/20/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61161,70217,63672,Probation,SPRUILL,FRED,NULL,Male,Caucasian,12/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +61161,70217,63672,Probation,SPRUILL,FRED,NULL,Male,Caucasian,12/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +61161,70217,63672,Probation,SPRUILL,FRED,NULL,Male,Caucasian,12/05/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61114,70159,63617,PRETRIAL,Dale,Tifany,Denise,Female,Caucasian,09/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +61114,70159,63617,PRETRIAL,Dale,Tifany,Denise,Female,Caucasian,09/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +61114,70159,63617,PRETRIAL,Dale,Tifany,Denise,Female,Caucasian,09/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61127,70175,63632,Probation,Martinez,Danny,NULL,Male,Hispanic,06/26/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +61127,70175,63632,Probation,Martinez,Danny,NULL,Male,Hispanic,06/26/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +61127,70175,63632,Probation,Martinez,Danny,NULL,Male,Hispanic,06/26/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61109,70154,63612,PRETRIAL,Stacy,Felder,NULL,Male,African-American,02/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +61109,70154,63612,PRETRIAL,Stacy,Felder,NULL,Male,African-American,02/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +61109,70154,63612,PRETRIAL,Stacy,Felder,NULL,Male,African-American,02/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +49961,70180,63637,PRETRIAL,MONTGOMERY,ANTOWAN,NULL,Male,African-American,02/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/10/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +49961,70180,63637,PRETRIAL,MONTGOMERY,ANTOWAN,NULL,Male,African-American,02/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +49961,70180,63637,PRETRIAL,MONTGOMERY,ANTOWAN,NULL,Male,African-American,02/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61136,70183,63640,PRETRIAL,HERNANDEZ,ROLFI,NULL,Male,Hispanic,06/27/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +61136,70183,63640,PRETRIAL,HERNANDEZ,ROLFI,NULL,Male,Hispanic,06/27/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +61136,70183,63640,PRETRIAL,HERNANDEZ,ROLFI,NULL,Male,Hispanic,06/27/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +49128,70162,63620,PRETRIAL,Whitehead,Devon,NULL,Male,African-American,10/18/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +49128,70162,63620,PRETRIAL,Whitehead,Devon,NULL,Male,African-American,10/18/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +49128,70162,63620,PRETRIAL,Whitehead,Devon,NULL,Male,African-American,10/18/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +61118,70165,63623,PRETRIAL,Librun,Franceline,NULL,Male,African-American,09/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +61118,70165,63623,PRETRIAL,Librun,Franceline,NULL,Male,African-American,09/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +61118,70165,63623,PRETRIAL,Librun,Franceline,NULL,Male,African-American,09/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61148,70198,63655,Probation,Diaz,Eduardo,NULL,Male,Hispanic,12/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +61148,70198,63655,Probation,Diaz,Eduardo,NULL,Male,Hispanic,12/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +61148,70198,63655,Probation,Diaz,Eduardo,NULL,Male,Hispanic,12/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61129,70177,63634,PRETRIAL,Batchanoo,Jays,NULL,Male,Caucasian,01/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +61129,70177,63634,PRETRIAL,Batchanoo,Jays,NULL,Male,Caucasian,01/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +61129,70177,63634,PRETRIAL,Batchanoo,Jays,NULL,Male,Caucasian,01/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61138,70186,63643,PRETRIAL,Godette,Greg,NULL,Male,Caucasian,10/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +61138,70186,63643,PRETRIAL,Godette,Greg,NULL,Male,Caucasian,10/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +61138,70186,63643,PRETRIAL,Godette,Greg,NULL,Male,Caucasian,10/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61111,70156,63614,PRETRIAL,Tole,Wesley,NULL,Male,Caucasian,05/15/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +61111,70156,63614,PRETRIAL,Tole,Wesley,NULL,Male,Caucasian,05/15/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +61111,70156,63614,PRETRIAL,Tole,Wesley,NULL,Male,Caucasian,05/15/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61125,70172,63629,PRETRIAL,Rodriguez,Julio,NULL,Male,Hispanic,03/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +61125,70172,63629,PRETRIAL,Rodriguez,Julio,NULL,Male,Hispanic,03/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +61125,70172,63629,PRETRIAL,Rodriguez,Julio,NULL,Male,Hispanic,03/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61143,70191,63648,Probation,conto,nicholas,NULL,Male,Caucasian,05/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +61143,70191,63648,Probation,conto,nicholas,NULL,Male,Caucasian,05/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +61143,70191,63648,Probation,conto,nicholas,NULL,Male,Caucasian,05/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61116,70163,63621,PRETRIAL,Cobb,Lashunda,NULL,Female,African-American,02/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,New,1,0 +61116,70163,63621,PRETRIAL,Cobb,Lashunda,NULL,Female,African-American,02/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,8,High,New,1,0 +61116,70163,63621,PRETRIAL,Cobb,Lashunda,NULL,Female,African-American,02/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +39896,70170,39484,PRETRIAL,Wimberly,William,NULL,Female,African-American,12/19/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,Copy,1,0 +39896,70170,39484,PRETRIAL,Wimberly,William,NULL,Female,African-American,12/19/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,Copy,1,0 +39896,70170,39484,PRETRIAL,Wimberly,William,NULL,Female,African-American,12/19/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +61145,70193,63650,Probation,Patel,Harshadbhai,NULL,Male,Asian,08/31/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/10/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +61145,70193,63650,Probation,Patel,Harshadbhai,NULL,Male,Asian,08/31/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/10/14 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +61145,70193,63650,Probation,Patel,Harshadbhai,NULL,Male,Asian,08/31/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61149,70200,63657,Probation,TAYLOR,TYRONE,NULL,Male,African-American,11/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +61149,70200,63657,Probation,TAYLOR,TYRONE,NULL,Male,African-American,11/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +61149,70200,63657,Probation,TAYLOR,TYRONE,NULL,Male,African-American,11/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61131,70179,63636,Probation,VANEGAS,JONATHAN,NULL,Male,Hispanic,03/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +61131,70179,63636,Probation,VANEGAS,JONATHAN,NULL,Male,Hispanic,03/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +61131,70179,63636,Probation,VANEGAS,JONATHAN,NULL,Male,Hispanic,03/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61113,70158,63616,PRETRIAL,MCKINNEY,LARRY,EVAN,Male,Caucasian,07/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +61113,70158,63616,PRETRIAL,MCKINNEY,LARRY,EVAN,Male,Caucasian,07/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +61113,70158,63616,PRETRIAL,MCKINNEY,LARRY,EVAN,Male,Caucasian,07/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +61144,70192,63649,Probation,ORDONEZ,CAMILO,NULL,Male,Hispanic,08/31/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +61144,70192,63649,Probation,ORDONEZ,CAMILO,NULL,Male,Hispanic,08/31/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +61144,70192,63649,Probation,ORDONEZ,CAMILO,NULL,Male,Hispanic,08/31/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61128,70176,63633,Probation,ilus,jonathan,NULL,Male,African-American,02/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +61128,70176,63633,Probation,ilus,jonathan,NULL,Male,African-American,02/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +61128,70176,63633,Probation,ilus,jonathan,NULL,Male,African-American,02/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61119,70166,63624,PRETRIAL,Grant,John,NULL,Male,Caucasian,09/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +61119,70166,63624,PRETRIAL,Grant,John,NULL,Male,Caucasian,09/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +61119,70166,63624,PRETRIAL,Grant,John,NULL,Male,Caucasian,09/03/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61137,70184,63641,PRETRIAL,Adams,Latoria,NULL,Female,African-American,12/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,New,1,0 +61137,70184,63641,PRETRIAL,Adams,Latoria,NULL,Female,African-American,12/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,8,High,New,1,0 +61137,70184,63641,PRETRIAL,Adams,Latoria,NULL,Female,African-American,12/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61147,70197,63654,Probation,Aldana,Henry,Ramon,Male,Hispanic,02/15/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/10/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +61147,70197,63654,Probation,Aldana,Henry,Ramon,Male,Hispanic,02/15/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +61147,70197,63654,Probation,Aldana,Henry,Ramon,Male,Hispanic,02/15/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61115,70160,63618,PRETRIAL,Chery,Apollon,NULL,Male,Other,01/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +61115,70160,63618,PRETRIAL,Chery,Apollon,NULL,Male,Other,01/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +61115,70160,63618,PRETRIAL,Chery,Apollon,NULL,Male,Other,01/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61134,70181,63638,DRRD,Thomas,Anthony,Quinton,Male,African-American,09/07/90,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.23,8,High,New,1,0 +61134,70181,63638,DRRD,Thomas,Anthony,Quinton,Male,African-American,09/07/90,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,7,Medium,New,1,0 +61134,70181,63638,DRRD,Thomas,Anthony,Quinton,Male,African-American,09/07/90,17,All Scales,Intake,English,Probation Violator,Probation,Single,2/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61135,70182,63639,PRETRIAL,JOSEPH,YVENS,NULL,Male,African-American,04/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,4,High,7,Risk of Violence,-0.64,9,High,New,1,0 +61135,70182,63639,PRETRIAL,JOSEPH,YVENS,NULL,Male,African-American,04/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,4,High,8,Risk of Recidivism,0.86,10,High,New,1,0 +61135,70182,63639,PRETRIAL,JOSEPH,YVENS,NULL,Male,African-American,04/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61126,70174,63631,Probation,SWARZAK,CARRIE,ANN,Female,Caucasian,07/24/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/10/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +61126,70174,63631,Probation,SWARZAK,CARRIE,ANN,Female,Caucasian,07/24/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +61126,70174,63631,Probation,SWARZAK,CARRIE,ANN,Female,Caucasian,07/24/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +11698,70189,63646,Probation,Wright,Glenn,NULL,Male,Caucasian,11/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +11698,70189,63646,Probation,Wright,Glenn,NULL,Male,Caucasian,11/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +11698,70189,63646,Probation,Wright,Glenn,NULL,Male,Caucasian,11/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/10/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57459,70161,63619,PRETRIAL,Toledo,David,NULL,Male,Caucasian,09/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +57459,70161,63619,PRETRIAL,Toledo,David,NULL,Male,Caucasian,09/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +57459,70161,63619,PRETRIAL,Toledo,David,NULL,Male,Caucasian,09/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61121,70168,63626,Probation,Todd,Kafus,NULL,Male,African-American,09/09/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +61121,70168,63626,Probation,Todd,Kafus,NULL,Male,African-American,09/09/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +61121,70168,63626,Probation,Todd,Kafus,NULL,Male,African-American,09/09/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61146,70195,63652,Probation,olive,patrick,NULL,Male,Caucasian,12/08/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +61146,70195,63652,Probation,olive,patrick,NULL,Male,Caucasian,12/08/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +61146,70195,63652,Probation,olive,patrick,NULL,Male,Caucasian,12/08/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50658,70202,51715,PRETRIAL,Wiley,Earnest,NULL,Male,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,2,Medium,7,Risk of Violence,-2.89,2,Low,Copy,1,0 +50658,70202,51715,PRETRIAL,Wiley,Earnest,NULL,Male,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +50658,70202,51715,PRETRIAL,Wiley,Earnest,NULL,Male,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +61165,70223,63677,Probation,Singh,Chetram,NULL,Male,Asian,03/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +61165,70223,63677,Probation,Singh,Chetram,NULL,Male,Asian,03/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +61165,70223,63677,Probation,Singh,Chetram,NULL,Male,Asian,03/14/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61170,70231,63684,Probation,rodriguez,lorenzo,NULL,Male,Hispanic,11/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +61170,70231,63684,Probation,rodriguez,lorenzo,NULL,Male,Hispanic,11/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +61170,70231,63684,Probation,rodriguez,lorenzo,NULL,Male,Hispanic,11/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +36350,70203,63659,PRETRIAL,Rodriguez,Miguel,Angel,Male,Hispanic,11/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,New,1,0 +36350,70203,63659,PRETRIAL,Rodriguez,Miguel,Angel,Male,Hispanic,11/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +36350,70203,63659,PRETRIAL,Rodriguez,Miguel,Angel,Male,Hispanic,11/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61154,70210,63666,PRETRIAL,ROYSTER,RASHENNA,QUANTRELL,Male,African-American,10/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/11/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +61154,70210,63666,PRETRIAL,ROYSTER,RASHENNA,QUANTRELL,Male,African-American,10/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/11/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +61154,70210,63666,PRETRIAL,ROYSTER,RASHENNA,QUANTRELL,Male,African-American,10/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61172,70234,63687,PRETRIAL,LARKINS,ROBERT,NULL,Male,African-American,07/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.99,4,Low,New,1,0 +61172,70234,63687,PRETRIAL,LARKINS,ROBERT,NULL,Male,African-American,07/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +61172,70234,63687,PRETRIAL,LARKINS,ROBERT,NULL,Male,African-American,07/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61180,70244,63697,Probation,Cagigas,Luvy,judith,Female,Hispanic,09/03/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/11/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +61180,70244,63697,Probation,Cagigas,Luvy,judith,Female,Hispanic,09/03/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/11/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +61180,70244,63697,Probation,Cagigas,Luvy,judith,Female,Hispanic,09/03/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61150,70205,63661,PRETRIAL,Hudson,Rodney,Larinso,Male,African-American,12/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +61150,70205,63661,PRETRIAL,Hudson,Rodney,Larinso,Male,African-American,12/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +61150,70205,63661,PRETRIAL,Hudson,Rodney,Larinso,Male,African-American,12/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61176,70239,63692,Probation,smith,cyril,NULL,Male,African-American,04/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +61176,70239,63692,Probation,smith,cyril,NULL,Male,African-American,04/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +61176,70239,63692,Probation,smith,cyril,NULL,Male,African-American,04/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61156,70213,63668,PRETRIAL,Gonzalez,Lance,NULL,Male,Hispanic,12/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +61156,70213,63668,PRETRIAL,Gonzalez,Lance,NULL,Male,Hispanic,12/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +61156,70213,63668,PRETRIAL,Gonzalez,Lance,NULL,Male,Hispanic,12/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54616,70218,63673,Probation,Alvarez,Mauricio,NULL,Male,Hispanic,03/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/11/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +54616,70218,63673,Probation,Alvarez,Mauricio,NULL,Male,Hispanic,03/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/11/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +54616,70218,63673,Probation,Alvarez,Mauricio,NULL,Male,Hispanic,03/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61157,70214,63669,PRETRIAL,Coar,Sasha,NULL,Female,African-American,07/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +61157,70214,63669,PRETRIAL,Coar,Sasha,NULL,Female,African-American,07/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +61157,70214,63669,PRETRIAL,Coar,Sasha,NULL,Female,African-American,07/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61167,70228,63681,Probation,Ramirez,Carla,elena,Female,Hispanic,01/03/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/11/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +61167,70228,63681,Probation,Ramirez,Carla,elena,Female,Hispanic,01/03/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,7,Medium,New,1,0 +61167,70228,63681,Probation,Ramirez,Carla,elena,Female,Hispanic,01/03/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/11/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61173,70235,63688,PRETRIAL,LAIKNICKAS,PAUL,NULL,Male,Caucasian,05/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/11/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +61173,70235,63688,PRETRIAL,LAIKNICKAS,PAUL,NULL,Male,Caucasian,05/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/11/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +61173,70235,63688,PRETRIAL,LAIKNICKAS,PAUL,NULL,Male,Caucasian,05/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61178,70242,63695,Probation,Tobon Mermudez,Edward,NULL,Male,Hispanic,06/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +61178,70242,63695,Probation,Tobon Mermudez,Edward,NULL,Male,Hispanic,06/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +61178,70242,63695,Probation,Tobon Mermudez,Edward,NULL,Male,Hispanic,06/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61152,70207,63663,PRETRIAL,Ruiz,Julian,Dimofilo,Male,Hispanic,03/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +61152,70207,63663,PRETRIAL,Ruiz,Julian,Dimofilo,Male,Hispanic,03/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +61152,70207,63663,PRETRIAL,Ruiz,Julian,Dimofilo,Male,Hispanic,03/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61159,70216,63671,Probation,Clarke,Denise,NULL,Female,African-American,05/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +61159,70216,63671,Probation,Clarke,Denise,NULL,Female,African-American,05/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +61159,70216,63671,Probation,Clarke,Denise,NULL,Female,African-American,05/30/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55157,70233,63686,Probation,PHELPS,CHRISTIAN,ALEX,Male,African-American,01/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.96,5,Medium,New,1,0 +55157,70233,63686,Probation,PHELPS,CHRISTIAN,ALEX,Male,African-American,01/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +55157,70233,63686,Probation,PHELPS,CHRISTIAN,ALEX,Male,African-American,01/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61155,70212,63667,PRETRIAL,WILLIS,EDWARD,NULL,Male,Caucasian,09/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +61155,70212,63667,PRETRIAL,WILLIS,EDWARD,NULL,Male,Caucasian,09/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +61155,70212,63667,PRETRIAL,WILLIS,EDWARD,NULL,Male,Caucasian,09/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +61162,70219,63674,PRETRIAL,HILLER-BALCAZAR,MONICA,NULL,Female,Caucasian,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/14 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +61162,70219,63674,PRETRIAL,HILLER-BALCAZAR,MONICA,NULL,Female,Caucasian,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +61162,70219,63674,PRETRIAL,HILLER-BALCAZAR,MONICA,NULL,Female,Caucasian,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +44874,70237,63690,Probation,Thompson,Nicholas,NULL,Male,Caucasian,01/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +44874,70237,63690,Probation,Thompson,Nicholas,NULL,Male,Caucasian,01/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +44874,70237,63690,Probation,Thompson,Nicholas,NULL,Male,Caucasian,01/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +5665,70201,63658,PRETRIAL,BYRD,JERRY,L,Male,African-American,11/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,4,High,7,Risk of Violence,0.15,10,High,New,1,0 +5665,70201,63658,PRETRIAL,BYRD,JERRY,L,Male,African-American,11/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,4,High,8,Risk of Recidivism,1.39,10,High,New,1,0 +5665,70201,63658,PRETRIAL,BYRD,JERRY,L,Male,African-American,11/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +61169,70230,63683,PRETRIAL,Browne,Roger,NULL,Male,African-American,10/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/11/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +61169,70230,63683,PRETRIAL,Browne,Roger,NULL,Male,African-American,10/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/11/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +61169,70230,63683,PRETRIAL,Browne,Roger,NULL,Male,African-American,10/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +39395,70243,63696,Probation,Calhoun,BYRON,NULL,Male,Caucasian,07/23/40,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,2/11/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +39395,70243,63696,Probation,Calhoun,BYRON,NULL,Male,Caucasian,07/23/40,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,2/11/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +39395,70243,63696,Probation,Calhoun,BYRON,NULL,Male,Caucasian,07/23/40,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61153,70209,63665,PRETRIAL,Santiago,Kimberly,Nicole,Female,Hispanic,02/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +61153,70209,63665,PRETRIAL,Santiago,Kimberly,Nicole,Female,Hispanic,02/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +61153,70209,63665,PRETRIAL,Santiago,Kimberly,Nicole,Female,Hispanic,02/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61164,70222,63676,Probation,Velasquez,juan,NULL,Male,Hispanic,11/09/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +61164,70222,63676,Probation,Velasquez,juan,NULL,Male,Hispanic,11/09/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +61164,70222,63676,Probation,Velasquez,juan,NULL,Male,Hispanic,11/09/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +50544,70204,63660,PRETRIAL,DESMANGLES,JASON,NULL,Male,African-American,11/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +50544,70204,63660,PRETRIAL,DESMANGLES,JASON,NULL,Male,African-American,11/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +50544,70204,63660,PRETRIAL,DESMANGLES,JASON,NULL,Male,African-American,11/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61175,70238,63691,Probation,Charles,Joseph,NULL,Male,African-American,09/02/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +61175,70238,63691,Probation,Charles,Joseph,NULL,Male,African-American,09/02/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.98,10,High,New,1,0 +61175,70238,63691,Probation,Charles,Joseph,NULL,Male,African-American,09/02/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +61166,70225,63679,Probation,PERUGINE,JAMES,J,Male,Caucasian,01/22/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/11/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +61166,70225,63679,Probation,PERUGINE,JAMES,J,Male,Caucasian,01/22/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/11/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +61166,70225,63679,Probation,PERUGINE,JAMES,J,Male,Caucasian,01/22/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +42708,70240,63693,PRETRIAL,RODRIGUEZ,EMIGDIO,NULL,Male,Caucasian,02/10/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +42708,70240,63693,PRETRIAL,RODRIGUEZ,EMIGDIO,NULL,Male,Caucasian,02/10/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +42708,70240,63693,PRETRIAL,RODRIGUEZ,EMIGDIO,NULL,Male,Caucasian,02/10/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61171,70232,63685,PRETRIAL,FORTNER,COREY,NULL,Male,Caucasian,03/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,4,High,7,Risk of Violence,-1.19,8,High,New,1,0 +61171,70232,63685,PRETRIAL,FORTNER,COREY,NULL,Male,Caucasian,03/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,4,High,8,Risk of Recidivism,0.17,8,High,New,1,0 +61171,70232,63685,PRETRIAL,FORTNER,COREY,NULL,Male,Caucasian,03/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61151,70206,63662,PRETRIAL,Sandrin,Bryan,NULL,Male,Caucasian,06/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +61151,70206,63662,PRETRIAL,Sandrin,Bryan,NULL,Male,Caucasian,06/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +61151,70206,63662,PRETRIAL,Sandrin,Bryan,NULL,Male,Caucasian,06/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +32134,70208,63664,PRETRIAL,BAKER,CRAIG,NULL,Male,African-American,04/06/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/14 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +32134,70208,63664,PRETRIAL,BAKER,CRAIG,NULL,Male,African-American,04/06/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +32134,70208,63664,PRETRIAL,BAKER,CRAIG,NULL,Male,African-American,04/06/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61168,70227,63680,Probation,Buchroe,Matthew,NULL,Male,Caucasian,05/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +61168,70227,63680,Probation,Buchroe,Matthew,NULL,Male,Caucasian,05/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +61168,70227,63680,Probation,Buchroe,Matthew,NULL,Male,Caucasian,05/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +20187,70229,63682,Probation,Condon,Philip,Oneil,Male,Caucasian,08/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Parole,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +20187,70229,63682,Probation,Condon,Philip,Oneil,Male,Caucasian,08/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Parole,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +20187,70229,63682,Probation,Condon,Philip,Oneil,Male,Caucasian,08/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Parole,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +24365,70224,63678,PRETRIAL,Rivas,Yorleni,NULL,Male,Caucasian,04/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/11/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +24365,70224,63678,PRETRIAL,Rivas,Yorleni,NULL,Male,Caucasian,04/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/11/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +24365,70224,63678,PRETRIAL,Rivas,Yorleni,NULL,Male,Caucasian,04/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +42243,70211,42046,PRETRIAL,King,Jonathan,Kevin,Male,African-American,07/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,Copy,1,0 +42243,70211,42046,PRETRIAL,King,Jonathan,Kevin,Male,African-American,07/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,Copy,1,0 +42243,70211,42046,PRETRIAL,King,Jonathan,Kevin,Male,African-American,07/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/11/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +59773,70220,62126,PRETRIAL,Toro-Perez,Rama,NULL,Male,Hispanic,11/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/11/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,Copy,1,0 +59773,70220,62126,PRETRIAL,Toro-Perez,Rama,NULL,Male,Hispanic,11/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/11/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,Copy,1,0 +59773,70220,62126,PRETRIAL,Toro-Perez,Rama,NULL,Male,Hispanic,11/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +61181,70245,63698,Probation,Morgan,Tamarch,NULL,Female,African-American,06/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +61181,70245,63698,Probation,Morgan,Tamarch,NULL,Female,African-American,06/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +61181,70245,63698,Probation,Morgan,Tamarch,NULL,Female,African-American,06/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61158,70215,63670,PRETRIAL,hudson,kevin,NULL,Male,African-American,03/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +61158,70215,63670,PRETRIAL,hudson,kevin,NULL,Male,African-American,03/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +61158,70215,63670,PRETRIAL,hudson,kevin,NULL,Male,African-American,03/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54337,70266,63716,PRETRIAL,Valle,Maritza,NULL,Female,Hispanic,03/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +54337,70266,63716,PRETRIAL,Valle,Maritza,NULL,Female,Hispanic,03/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +54337,70266,63716,PRETRIAL,Valle,Maritza,NULL,Female,Hispanic,03/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +16322,70283,63731,PRETRIAL,CHERRY,JAMAAL,WILLIAM,Male,African-American,07/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +16322,70283,63731,PRETRIAL,CHERRY,JAMAAL,WILLIAM,Male,African-American,07/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +16322,70283,63731,PRETRIAL,CHERRY,JAMAAL,WILLIAM,Male,African-American,07/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +2607,70262,63713,DRRD,John,Christopher,NULL,Male,Caucasian,05/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +2607,70262,63713,DRRD,John,Christopher,NULL,Male,Caucasian,05/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +2607,70262,63713,DRRD,John,Christopher,NULL,Male,Caucasian,05/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +60769,70276,63725,PRETRIAL,PEARARAY,BALDEO,NULL,Male,Other,07/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/12/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +60769,70276,63725,PRETRIAL,PEARARAY,BALDEO,NULL,Male,Other,07/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/12/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +60769,70276,63725,PRETRIAL,PEARARAY,BALDEO,NULL,Male,Other,07/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61206,70280,63729,PRETRIAL,Mitchell,Spanky,NULL,Male,Caucasian,08/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +61206,70280,63729,PRETRIAL,Mitchell,Spanky,NULL,Male,Caucasian,08/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +61206,70280,63729,PRETRIAL,Mitchell,Spanky,NULL,Male,Caucasian,08/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61191,70257,63708,PRETRIAL,MARKO,EDWARD,JAMES,Male,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +61191,70257,63708,PRETRIAL,MARKO,EDWARD,JAMES,Male,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +61191,70257,63708,PRETRIAL,MARKO,EDWARD,JAMES,Male,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61200,70271,63721,Probation,Richard-Simon,Rosa,NULL,Female,Hispanic,06/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +61200,70271,63721,Probation,Richard-Simon,Rosa,NULL,Female,Hispanic,06/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +61200,70271,63721,Probation,Richard-Simon,Rosa,NULL,Female,Hispanic,06/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +24077,70278,63727,PRETRIAL,JOSEPH,JAMES,NULL,Male,African-American,08/15/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +24077,70278,63727,PRETRIAL,JOSEPH,JAMES,NULL,Male,African-American,08/15/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +24077,70278,63727,PRETRIAL,JOSEPH,JAMES,NULL,Male,African-American,08/15/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61177,70285,63694,PRETRIAL,ROGINA,IRINA,NULL,Female,Caucasian,01/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,Copy,1,0 +61177,70285,63694,PRETRIAL,ROGINA,IRINA,NULL,Female,Caucasian,01/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,Copy,1,0 +61177,70285,63694,PRETRIAL,ROGINA,IRINA,NULL,Female,Caucasian,01/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,Copy,1,0 +61185,70250,63702,PRETRIAL,Koven,Justin,Nathaniel,Male,Caucasian,05/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +61185,70250,63702,PRETRIAL,Koven,Justin,Nathaniel,Male,Caucasian,05/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +61185,70250,63702,PRETRIAL,Koven,Justin,Nathaniel,Male,Caucasian,05/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61196,70264,63714,PRETRIAL,ELDER,QUINNELL,NULL,Male,African-American,11/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +61196,70264,63714,PRETRIAL,ELDER,QUINNELL,NULL,Male,African-American,11/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +61196,70264,63714,PRETRIAL,ELDER,QUINNELL,NULL,Male,African-American,11/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61197,70267,63717,Probation,Ferguson,Lesley,NULL,Female,Caucasian,01/13/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/12/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +61197,70267,63717,Probation,Ferguson,Lesley,NULL,Female,Caucasian,01/13/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/12/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +61197,70267,63717,Probation,Ferguson,Lesley,NULL,Female,Caucasian,01/13/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61207,70282,63730,Probation,Young,Joseph,NULL,Male,Caucasian,06/14/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/12/14 0:00,2,Medium,7,Risk of Violence,-2.95,1,Low,New,1,0 +61207,70282,63730,Probation,Young,Joseph,NULL,Male,Caucasian,06/14/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +61207,70282,63730,Probation,Young,Joseph,NULL,Male,Caucasian,06/14/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/12/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +61188,70253,63705,PRETRIAL,OMORUYI,RICH,NULL,Male,African-American,11/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +61188,70253,63705,PRETRIAL,OMORUYI,RICH,NULL,Male,African-American,11/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +61188,70253,63705,PRETRIAL,OMORUYI,RICH,NULL,Male,African-American,11/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61193,70259,63710,PRETRIAL,Neal,William,NULL,Male,African-American,07/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +61193,70259,63710,PRETRIAL,Neal,William,NULL,Male,African-American,07/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +61193,70259,63710,PRETRIAL,Neal,William,NULL,Male,African-American,07/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61195,70261,63712,PRETRIAL,Dean,Charles,NULL,Male,African-American,10/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.12,4,Low,New,1,0 +61195,70261,63712,PRETRIAL,Dean,Charles,NULL,Male,African-American,10/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +61195,70261,63712,PRETRIAL,Dean,Charles,NULL,Male,African-American,10/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +12698,70256,12182,PRETRIAL,Ortiz,Johnny,Luis,Female,African-American,11/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,Copy,1,0 +12698,70256,12182,PRETRIAL,Ortiz,Johnny,Luis,Female,African-American,11/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,9,High,Copy,1,0 +12698,70256,12182,PRETRIAL,Ortiz,Johnny,Luis,Female,African-American,11/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +61212,70290,63736,PRETRIAL,Grisham,Michael,NULL,Male,African-American,11/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +61212,70290,63736,PRETRIAL,Grisham,Michael,NULL,Male,African-American,11/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +61212,70290,63736,PRETRIAL,Grisham,Michael,NULL,Male,African-American,11/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,4,High,18,Risk of Failure to Appear,41,10,High,New,1,0 +61183,70248,63700,PRETRIAL,Conde,Juan,NULL,Male,Caucasian,01/16/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,2,Medium,7,Risk of Violence,-2.94,2,Low,New,1,0 +61183,70248,63700,PRETRIAL,Conde,Juan,NULL,Male,Caucasian,01/16/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +61183,70248,63700,PRETRIAL,Conde,Juan,NULL,Male,Caucasian,01/16/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61186,70251,63703,PRETRIAL,Gilmore,Gary,Anthony,Male,African-American,12/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +61186,70251,63703,PRETRIAL,Gilmore,Gary,Anthony,Male,African-American,12/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +61186,70251,63703,PRETRIAL,Gilmore,Gary,Anthony,Male,African-American,12/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61198,70269,63719,Probation,Nicosia,ryan,Anthony,Male,Caucasian,01/18/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +61198,70269,63719,Probation,Nicosia,ryan,Anthony,Male,Caucasian,01/18/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +61198,70269,63719,Probation,Nicosia,ryan,Anthony,Male,Caucasian,01/18/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61208,70284,63732,Probation,Crowe,Barbara,NULL,Female,African-American,03/09/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/12/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +61208,70284,63732,Probation,Crowe,Barbara,NULL,Female,African-American,03/09/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/12/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +61208,70284,63732,Probation,Crowe,Barbara,NULL,Female,African-American,03/09/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61192,70258,63709,PRETRIAL,Dominguez,Eric,NULL,Male,Other,02/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +61192,70258,63709,PRETRIAL,Dominguez,Eric,NULL,Male,Other,02/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +61192,70258,63709,PRETRIAL,Dominguez,Eric,NULL,Male,Other,02/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54540,70275,63724,PRETRIAL,ABSOLU,ARISNO,NULL,Male,African-American,07/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/12/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +54540,70275,63724,PRETRIAL,ABSOLU,ARISNO,NULL,Male,African-American,07/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/12/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +54540,70275,63724,PRETRIAL,ABSOLU,ARISNO,NULL,Male,African-American,07/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61189,70254,63706,PRETRIAL,CACERES,MAZEN,EAD,Male,Caucasian,10/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +61189,70254,63706,PRETRIAL,CACERES,MAZEN,EAD,Male,Caucasian,10/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +61189,70254,63706,PRETRIAL,CACERES,MAZEN,EAD,Male,Caucasian,10/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61205,70279,63728,Probation,brown,montoya,NULL,Male,African-American,10/12/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +61205,70279,63728,Probation,brown,montoya,NULL,Male,African-American,10/12/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +61205,70279,63728,Probation,brown,montoya,NULL,Male,African-American,10/12/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61210,70288,63734,PRETRIAL,Delgadillo,Diego,NULL,Male,Hispanic,11/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/12/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +61210,70288,63734,PRETRIAL,Delgadillo,Diego,NULL,Male,Hispanic,11/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/12/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +61210,70288,63734,PRETRIAL,Delgadillo,Diego,NULL,Male,Hispanic,11/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61201,70272,63722,Probation,Peoples,Regginald,Dale,Male,African-American,04/09/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +61201,70272,63722,Probation,Peoples,Regginald,Dale,Male,African-American,04/09/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +61201,70272,63722,Probation,Peoples,Regginald,Dale,Male,African-American,04/09/58,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +50660,70263,58607,PRETRIAL,Sharpe,Bernard,NULL,Male,African-American,08/22/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,Copy,1,0 +50660,70263,58607,PRETRIAL,Sharpe,Bernard,NULL,Male,African-American,08/22/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/14 0:00,4,High,8,Risk of Recidivism,0.19,8,High,Copy,1,0 +50660,70263,58607,PRETRIAL,Sharpe,Bernard,NULL,Male,African-American,08/22/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/12/14 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +61199,70270,63720,PRETRIAL,GREEN,JORDAN,NULL,Male,African-American,07/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +61199,70270,63720,PRETRIAL,GREEN,JORDAN,NULL,Male,African-American,07/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +61199,70270,63720,PRETRIAL,GREEN,JORDAN,NULL,Male,African-American,07/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61184,70249,63701,PRETRIAL,Hall,Terrell,Jamal,Male,African-American,01/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,New,1,0 +61184,70249,63701,PRETRIAL,Hall,Terrell,Jamal,Male,African-American,01/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +61184,70249,63701,PRETRIAL,Hall,Terrell,Jamal,Male,African-American,01/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61187,70252,63704,PRETRIAL,WAIN,JOSEPH,NULL,Male,Caucasian,03/16/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +61187,70252,63704,PRETRIAL,WAIN,JOSEPH,NULL,Male,Caucasian,03/16/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +61187,70252,63704,PRETRIAL,WAIN,JOSEPH,NULL,Male,Caucasian,03/16/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,35,10,High,New,1,0 +40426,70286,40040,PRETRIAL,Mackrell,Michael,NULL,Male,Caucasian,05/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,Copy,1,0 +40426,70286,40040,PRETRIAL,Mackrell,Michael,NULL,Male,Caucasian,05/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,Copy,1,0 +40426,70286,40040,PRETRIAL,Mackrell,Michael,NULL,Male,Caucasian,05/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +61202,70273,63723,Probation,Perez,Gabriella,NULL,Female,Hispanic,04/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +61202,70273,63723,Probation,Perez,Gabriella,NULL,Female,Hispanic,04/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +61202,70273,63723,Probation,Perez,Gabriella,NULL,Female,Hispanic,04/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61190,70255,63707,PRETRIAL,Esposito,Michael,Richard,Male,Caucasian,09/29/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/12/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +61190,70255,63707,PRETRIAL,Esposito,Michael,Richard,Male,Caucasian,09/29/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/12/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +61190,70255,63707,PRETRIAL,Esposito,Michael,Richard,Male,Caucasian,09/29/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +35825,70247,35046,PRETRIAL,Jeanhilaire,Samuel,NULL,Male,African-American,06/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,Copy,1,0 +35825,70247,35046,PRETRIAL,Jeanhilaire,Samuel,NULL,Male,African-American,06/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,Copy,1,0 +35825,70247,35046,PRETRIAL,Jeanhilaire,Samuel,NULL,Male,African-American,06/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +61194,70260,63711,PRETRIAL,rotati,stefano,NULL,Male,Caucasian,03/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +61194,70260,63711,PRETRIAL,rotati,stefano,NULL,Male,Caucasian,03/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +61194,70260,63711,PRETRIAL,rotati,stefano,NULL,Male,Caucasian,03/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +40669,70268,63718,PRETRIAL,BAGNALL,DAVID,NULL,Male,Caucasian,10/11/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +40669,70268,63718,PRETRIAL,BAGNALL,DAVID,NULL,Male,Caucasian,10/11/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +40669,70268,63718,PRETRIAL,BAGNALL,DAVID,NULL,Male,Caucasian,10/11/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/12/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61222,70302,63748,PRETRIAL,McAllister,Breeann,NULL,Female,Caucasian,08/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +61222,70302,63748,PRETRIAL,McAllister,Breeann,NULL,Female,Caucasian,08/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +61222,70302,63748,PRETRIAL,McAllister,Breeann,NULL,Female,Caucasian,08/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +7552,70304,63750,PRETRIAL,Birdsong,Bradey,Robert,Female,Caucasian,06/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,New,1,0 +7552,70304,63750,PRETRIAL,Birdsong,Bradey,Robert,Female,Caucasian,06/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +7552,70304,63750,PRETRIAL,Birdsong,Bradey,Robert,Female,Caucasian,06/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +34200,70323,63766,PRETRIAL,Lester,Lee,NULL,Male,African-American,10/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.14,4,Low,New,1,0 +34200,70323,63766,PRETRIAL,Lester,Lee,NULL,Male,African-American,10/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +34200,70323,63766,PRETRIAL,Lester,Lee,NULL,Male,African-American,10/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +61237,70325,63768,PRETRIAL,Mcgowan,Dalton,NULL,Male,African-American,11/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,New,1,0 +61237,70325,63768,PRETRIAL,Mcgowan,Dalton,NULL,Male,African-American,11/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +61237,70325,63768,PRETRIAL,Mcgowan,Dalton,NULL,Male,African-American,11/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +28378,70296,63742,PRETRIAL,SCOGNAMIGLO,JOSEPH,ANTHONY,Male,Caucasian,11/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +28378,70296,63742,PRETRIAL,SCOGNAMIGLO,JOSEPH,ANTHONY,Male,Caucasian,11/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +28378,70296,63742,PRETRIAL,SCOGNAMIGLO,JOSEPH,ANTHONY,Male,Caucasian,11/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52058,70310,63756,PRETRIAL,Slason,Melissa,NULL,Female,Caucasian,08/27/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/13/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +52058,70310,63756,PRETRIAL,Slason,Melissa,NULL,Female,Caucasian,08/27/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.61,2,Low,New,1,0 +52058,70310,63756,PRETRIAL,Slason,Melissa,NULL,Female,Caucasian,08/27/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61240,70331,63773,Probation,HALL,RICHARD,FOREST,Male,Caucasian,01/17/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +61240,70331,63773,Probation,HALL,RICHARD,FOREST,Male,Caucasian,01/17/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +61240,70331,63773,Probation,HALL,RICHARD,FOREST,Male,Caucasian,01/17/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61230,70315,63760,PRETRIAL,Abreu,Kevin,NULL,Male,Caucasian,10/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +61230,70315,63760,PRETRIAL,Abreu,Kevin,NULL,Male,Caucasian,10/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +61230,70315,63760,PRETRIAL,Abreu,Kevin,NULL,Male,Caucasian,10/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61241,70333,63774,Probation,callahan,judy,NULL,Female,Caucasian,05/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.25,3,Low,New,1,0 +61241,70333,63774,Probation,callahan,judy,NULL,Female,Caucasian,05/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,10,High,New,1,0 +61241,70333,63774,Probation,callahan,judy,NULL,Female,Caucasian,05/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61214,70294,63740,PRETRIAL,Griffin,Alshunard,NULL,Male,African-American,06/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +61214,70294,63740,PRETRIAL,Griffin,Alshunard,NULL,Male,African-American,06/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +61214,70294,63740,PRETRIAL,Griffin,Alshunard,NULL,Male,African-American,06/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61228,70312,63757,Probation,Franco,Ruben,NULL,Male,Hispanic,06/21/56,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/13/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +61228,70312,63757,Probation,Franco,Ruben,NULL,Male,Hispanic,06/21/56,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +61228,70312,63757,Probation,Franco,Ruben,NULL,Male,Hispanic,06/21/56,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61225,70307,63753,Probation,Boynt,Roland,Edward,Male,Caucasian,11/06/62,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +61225,70307,63753,Probation,Boynt,Roland,Edward,Male,Caucasian,11/06/62,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +61225,70307,63753,Probation,Boynt,Roland,Edward,Male,Caucasian,11/06/62,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +61233,70320,63763,PRETRIAL,love,daniel,NULL,Male,African-American,02/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +61233,70320,63763,PRETRIAL,love,daniel,NULL,Male,African-American,02/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +61233,70320,63763,PRETRIAL,love,daniel,NULL,Male,African-American,02/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +61219,70300,63746,PRETRIAL,Johnson,Fatima,NULL,Female,African-American,04/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +61219,70300,63746,PRETRIAL,Johnson,Fatima,NULL,Female,African-American,04/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.53,2,Low,New,1,0 +61219,70300,63746,PRETRIAL,Johnson,Fatima,NULL,Female,African-American,04/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61234,70321,63764,PRETRIAL,zuniga,nelson,NULL,Male,Caucasian,05/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +61234,70321,63764,PRETRIAL,zuniga,nelson,NULL,Male,Caucasian,05/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +61234,70321,63764,PRETRIAL,zuniga,nelson,NULL,Male,Caucasian,05/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53390,70328,63771,PRETRIAL,Ocasio,Gerald,NULL,Male,Hispanic,12/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +53390,70328,63771,PRETRIAL,Ocasio,Gerald,NULL,Male,Hispanic,12/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +53390,70328,63771,PRETRIAL,Ocasio,Gerald,NULL,Male,Hispanic,12/21/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +24355,70293,63739,PRETRIAL,Jonesgerald,Connie,NULL,Male,Caucasian,06/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/13/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +24355,70293,63739,PRETRIAL,Jonesgerald,Connie,NULL,Male,Caucasian,06/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/13/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +24355,70293,63739,PRETRIAL,Jonesgerald,Connie,NULL,Male,Caucasian,06/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +28758,70291,63737,PRETRIAL,Murphy,Terrance,NULL,Male,African-American,09/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +28758,70291,63737,PRETRIAL,Murphy,Terrance,NULL,Male,African-American,09/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +28758,70291,63737,PRETRIAL,Murphy,Terrance,NULL,Male,African-American,09/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61226,70309,63755,Probation,Aucella,Eugenio,NULL,Male,Caucasian,07/17/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +61226,70309,63755,Probation,Aucella,Eugenio,NULL,Male,Caucasian,07/17/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +61226,70309,63755,Probation,Aucella,Eugenio,NULL,Male,Caucasian,07/17/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61238,70326,63769,Probation,Frazier,Dana,Lee,Female,Caucasian,04/08/70,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/13/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +61238,70326,63769,Probation,Frazier,Dana,Lee,Female,Caucasian,04/08/70,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +61238,70326,63769,Probation,Frazier,Dana,Lee,Female,Caucasian,04/08/70,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +9652,70305,63751,PRETRIAL,Henry,Alonzo,NULL,Male,African-American,11/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,2,Medium,7,Risk of Violence,-2.82,2,Low,New,1,0 +9652,70305,63751,PRETRIAL,Henry,Alonzo,NULL,Male,African-American,11/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +9652,70305,63751,PRETRIAL,Henry,Alonzo,NULL,Male,African-American,11/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60571,70330,63025,PRETRIAL,BROADHEAD,ALANA,NULL,Female,Caucasian,05/10/79,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.29,3,Low,Copy,1,0 +60571,70330,63025,PRETRIAL,BROADHEAD,ALANA,NULL,Female,Caucasian,05/10/79,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,9,High,Copy,1,0 +60571,70330,63025,PRETRIAL,BROADHEAD,ALANA,NULL,Female,Caucasian,05/10/79,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +48900,70319,58041,PRETRIAL,FIELDS,ANTHONY,NULL,Male,Caucasian,02/20/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/13/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,Copy,1,0 +48900,70319,58041,PRETRIAL,FIELDS,ANTHONY,NULL,Male,Caucasian,02/20/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/13/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,Copy,1,0 +48900,70319,58041,PRETRIAL,FIELDS,ANTHONY,NULL,Male,Caucasian,02/20/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +61217,70298,63744,PRETRIAL,PHILLIPS,LLOY,NULL,Female,African-American,07/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/13/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +61217,70298,63744,PRETRIAL,PHILLIPS,LLOY,NULL,Female,African-American,07/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +61217,70298,63744,PRETRIAL,PHILLIPS,LLOY,NULL,Female,African-American,07/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61231,70316,63761,Probation,Swackard,Yanick,NULL,Female,African-American,09/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +61231,70316,63761,Probation,Swackard,Yanick,NULL,Female,African-American,09/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +61231,70316,63761,Probation,Swackard,Yanick,NULL,Female,African-American,09/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61236,70324,63767,Probation,Askaran,Sandeep,NULL,Male,Other,05/11/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/13/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +61236,70324,63767,Probation,Askaran,Sandeep,NULL,Male,Other,05/11/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +61236,70324,63767,Probation,Askaran,Sandeep,NULL,Male,Other,05/11/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50236,70311,61567,PRETRIAL,Gilbert,Myrticea,NULL,Female,African-American,06/03/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.31,7,Medium,Copy,1,0 +50236,70311,61567,PRETRIAL,Gilbert,Myrticea,NULL,Female,African-American,06/03/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,10,High,Copy,1,0 +50236,70311,61567,PRETRIAL,Gilbert,Myrticea,NULL,Female,African-American,06/03/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +61215,70295,63741,PRETRIAL,Severns,Elijah,James,Male,Caucasian,07/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +61215,70295,63741,PRETRIAL,Severns,Elijah,James,Male,Caucasian,07/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +61215,70295,63741,PRETRIAL,Severns,Elijah,James,Male,Caucasian,07/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61223,70303,63749,PRETRIAL,MELERO,JESUS,NULL,Male,Caucasian,05/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +61223,70303,63749,PRETRIAL,MELERO,JESUS,NULL,Male,Caucasian,05/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +61223,70303,63749,PRETRIAL,MELERO,JESUS,NULL,Male,Caucasian,05/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61218,70299,63745,PRETRIAL,Howard,Nikki,G,Female,African-American,11/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +61218,70299,63745,PRETRIAL,Howard,Nikki,G,Female,African-American,11/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.87,10,High,New,1,0 +61218,70299,63745,PRETRIAL,Howard,Nikki,G,Female,African-American,11/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61224,70306,63752,Probation,YOST,SHAWN,NULL,Male,Caucasian,09/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +61224,70306,63752,Probation,YOST,SHAWN,NULL,Male,Caucasian,09/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +61224,70306,63752,Probation,YOST,SHAWN,NULL,Male,Caucasian,09/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +12525,70327,63770,Broward County,DIAH,OMARI,NULL,Male,African-American,08/01/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/13/14 0:00,2,Medium,7,Risk of Violence,-2.85,2,Low,New,1,0 +12525,70327,63770,Broward County,DIAH,OMARI,NULL,Male,African-American,08/01/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +12525,70327,63770,Broward County,DIAH,OMARI,NULL,Male,African-American,08/01/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/13/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61239,70329,63772,Probation,GREEN,JOHN,NULL,Male,Caucasian,12/04/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +61239,70329,63772,Probation,GREEN,JOHN,NULL,Male,Caucasian,12/04/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +61239,70329,63772,Probation,GREEN,JOHN,NULL,Male,Caucasian,12/04/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61220,70301,63747,PRETRIAL,Quintero,John,NULL,Male,Hispanic,04/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +61220,70301,63747,PRETRIAL,Quintero,John,NULL,Male,Hispanic,04/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +61220,70301,63747,PRETRIAL,Quintero,John,NULL,Male,Hispanic,04/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61216,70297,63743,PRETRIAL,CASTILLO,JOSE,NULL,Male,Caucasian,07/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +61216,70297,63743,PRETRIAL,CASTILLO,JOSE,NULL,Male,Caucasian,07/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +61216,70297,63743,PRETRIAL,CASTILLO,JOSE,NULL,Male,Caucasian,07/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61242,70334,63775,PRETRIAL,Farquharson,Alvin,NULL,Male,African-American,09/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +61242,70334,63775,PRETRIAL,Farquharson,Alvin,NULL,Male,African-American,09/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +61242,70334,63775,PRETRIAL,Farquharson,Alvin,NULL,Male,African-American,09/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61232,70318,63762,Probation,Acevedo,Michael,NULL,Male,Hispanic,05/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +61232,70318,63762,Probation,Acevedo,Michael,NULL,Male,Hispanic,05/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +61232,70318,63762,Probation,Acevedo,Michael,NULL,Male,Hispanic,05/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61213,70292,63738,PRETRIAL,Joseph,Nathalie,NULL,Female,Caucasian,01/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +61213,70292,63738,PRETRIAL,Joseph,Nathalie,NULL,Female,Caucasian,01/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +61213,70292,63738,PRETRIAL,Joseph,Nathalie,NULL,Female,Caucasian,01/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61246,70343,63781,PRETRIAL,Tomlin,Marcel,NULL,Male,African-American,08/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +61246,70343,63781,PRETRIAL,Tomlin,Marcel,NULL,Male,African-American,08/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +61246,70343,63781,PRETRIAL,Tomlin,Marcel,NULL,Male,African-American,08/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61252,70352,63790,Probation,Davis,Krystal,NULL,Female,African-American,01/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +61252,70352,63790,Probation,Davis,Krystal,NULL,Female,African-American,01/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +61252,70352,63790,Probation,Davis,Krystal,NULL,Female,African-American,01/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61249,70348,63786,PRETRIAL,Jorden,Donald,NULL,Male,African-American,03/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +61249,70348,63786,PRETRIAL,Jorden,Donald,NULL,Male,African-American,03/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,4,High,8,Risk of Recidivism,0.25,8,High,New,1,0 +61249,70348,63786,PRETRIAL,Jorden,Donald,NULL,Male,African-American,03/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +38377,70336,63776,PRETRIAL,Jeanhilaire,Benson,NULL,Male,African-American,02/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +38377,70336,63776,PRETRIAL,Jeanhilaire,Benson,NULL,Male,African-American,02/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +38377,70336,63776,PRETRIAL,Jeanhilaire,Benson,NULL,Male,African-American,02/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +28182,70350,63788,PRETRIAL,OATTS,BREYON,NULL,Male,African-American,09/16/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +28182,70350,63788,PRETRIAL,OATTS,BREYON,NULL,Male,African-American,09/16/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,8,High,New,1,0 +28182,70350,63788,PRETRIAL,OATTS,BREYON,NULL,Male,African-American,09/16/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +61253,70353,63791,Probation,young,robert,NULL,Male,African-American,05/02/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +61253,70353,63791,Probation,young,robert,NULL,Male,African-American,05/02/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +61253,70353,63791,Probation,young,robert,NULL,Male,African-American,05/02/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61258,70360,63796,Probation,gundin,mark,NULL,Male,Hispanic,11/19/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +61258,70360,63796,Probation,gundin,mark,NULL,Male,Hispanic,11/19/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +61258,70360,63796,Probation,gundin,mark,NULL,Male,Hispanic,11/19/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +15292,70361,63797,Probation,goodwin,david,NULL,Male,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +15292,70361,63797,Probation,goodwin,david,NULL,Male,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.41,10,High,New,1,0 +15292,70361,63797,Probation,goodwin,david,NULL,Male,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +58592,70340,60802,PRETRIAL,HOLAWAY,TROY,NULL,Male,African-American,12/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,Copy,1,0 +58592,70340,60802,PRETRIAL,HOLAWAY,TROY,NULL,Male,African-American,12/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,Copy,1,0 +58592,70340,60802,PRETRIAL,HOLAWAY,TROY,NULL,Male,African-American,12/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +61247,70345,63783,PRETRIAL,Harbison,Shawn,Michael,Male,Caucasian,11/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/14/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +61247,70345,63783,PRETRIAL,Harbison,Shawn,Michael,Male,Caucasian,11/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/14/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +61247,70345,63783,PRETRIAL,Harbison,Shawn,Michael,Male,Caucasian,11/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61256,70358,63794,PRETRIAL,COLEMAN,VERON,NULL,Male,African-American,10/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/14/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +61256,70358,63794,PRETRIAL,COLEMAN,VERON,NULL,Male,African-American,10/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/14/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +61256,70358,63794,PRETRIAL,COLEMAN,VERON,NULL,Male,African-American,10/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/14/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +48355,70337,63777,PRETRIAL,Bonbon,Peter,NULL,Male,African-American,02/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +48355,70337,63777,PRETRIAL,Bonbon,Peter,NULL,Male,African-American,02/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,4,High,8,Risk of Recidivism,0.39,9,High,New,1,0 +48355,70337,63777,PRETRIAL,Bonbon,Peter,NULL,Male,African-American,02/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +22722,70344,63782,Probation,wood,brian,NULL,Male,Hispanic,06/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,New,1,0 +22722,70344,63782,Probation,wood,brian,NULL,Male,Hispanic,06/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +22722,70344,63782,Probation,wood,brian,NULL,Male,Hispanic,06/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51429,70347,63785,PRETRIAL,Rich,Courtland,Bernard,Male,African-American,04/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +51429,70347,63785,PRETRIAL,Rich,Courtland,Bernard,Male,African-American,04/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +51429,70347,63785,PRETRIAL,Rich,Courtland,Bernard,Male,African-American,04/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61251,70351,63789,Probation,SHORE,ABBEY,NOEL,Female,Caucasian,12/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +61251,70351,63789,Probation,SHORE,ABBEY,NOEL,Female,Caucasian,12/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +61251,70351,63789,Probation,SHORE,ABBEY,NOEL,Female,Caucasian,12/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61245,70342,63780,PRETRIAL,Garcia,Masiely,NULL,Female,Hispanic,08/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/14/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +61245,70342,63780,PRETRIAL,Garcia,Masiely,NULL,Female,Hispanic,08/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/14/14 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +61245,70342,63780,PRETRIAL,Garcia,Masiely,NULL,Female,Hispanic,08/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61250,70349,63787,Probation,Maros,Natasha,NULL,Female,Caucasian,06/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +61250,70349,63787,Probation,Maros,Natasha,NULL,Female,Caucasian,06/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +61250,70349,63787,Probation,Maros,Natasha,NULL,Female,Caucasian,06/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61254,70354,63792,Probation,DISLA,EMILY,E,Female,Caucasian,02/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.96,5,Medium,New,1,0 +61254,70354,63792,Probation,DISLA,EMILY,E,Female,Caucasian,02/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,8,High,New,1,0 +61254,70354,63792,Probation,DISLA,EMILY,E,Female,Caucasian,02/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61248,70346,63784,PRETRIAL,Strobridge,Steven,NULL,Male,African-American,08/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +61248,70346,63784,PRETRIAL,Strobridge,Steven,NULL,Male,African-American,08/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +61248,70346,63784,PRETRIAL,Strobridge,Steven,NULL,Male,African-American,08/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61257,70359,63795,PRETRIAL,WILLIAMS,KEVIN,ANTHONY,Male,African-American,04/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +61257,70359,63795,PRETRIAL,WILLIAMS,KEVIN,ANTHONY,Male,African-American,04/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +61257,70359,63795,PRETRIAL,WILLIAMS,KEVIN,ANTHONY,Male,African-American,04/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61243,70338,63778,PRETRIAL,Shenett,Brittany,NULL,Male,African-American,03/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +61243,70338,63778,PRETRIAL,Shenett,Brittany,NULL,Male,African-American,03/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +61243,70338,63778,PRETRIAL,Shenett,Brittany,NULL,Male,African-American,03/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +7906,70367,63802,PRETRIAL,RODRIGUEZ,ALBERTO,CARLOS,Male,Hispanic,12/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +7906,70367,63802,PRETRIAL,RODRIGUEZ,ALBERTO,CARLOS,Male,Hispanic,12/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,4,High,8,Risk of Recidivism,0.58,9,High,New,1,0 +7906,70367,63802,PRETRIAL,RODRIGUEZ,ALBERTO,CARLOS,Male,Hispanic,12/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +32421,70370,63805,PRETRIAL,DIAZ,DANIEL,NULL,Male,Hispanic,04/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.19,4,Low,New,1,0 +32421,70370,63805,PRETRIAL,DIAZ,DANIEL,NULL,Male,Hispanic,04/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +32421,70370,63805,PRETRIAL,DIAZ,DANIEL,NULL,Male,Hispanic,04/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +61268,70372,63807,PRETRIAL,Grillo,Jason,NULL,Male,Caucasian,10/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +61268,70372,63807,PRETRIAL,Grillo,Jason,NULL,Male,Caucasian,10/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +61268,70372,63807,PRETRIAL,Grillo,Jason,NULL,Male,Caucasian,10/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61263,70365,63800,PRETRIAL,Noel,Merrill,NULL,Male,African-American,07/16/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +61263,70365,63800,PRETRIAL,Noel,Merrill,NULL,Male,African-American,07/16/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +61263,70365,63800,PRETRIAL,Noel,Merrill,NULL,Male,African-American,07/16/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61264,70366,63801,PRETRIAL,Finley,Ferris,E,Male,African-American,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +61264,70366,63801,PRETRIAL,Finley,Ferris,E,Male,African-American,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +61264,70366,63801,PRETRIAL,Finley,Ferris,E,Male,African-American,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61270,70374,63809,PRETRIAL,MORLEY,TERRILL,NULL,Male,African-American,08/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +61270,70374,63809,PRETRIAL,MORLEY,TERRILL,NULL,Male,African-American,08/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +61270,70374,63809,PRETRIAL,MORLEY,TERRILL,NULL,Male,African-American,08/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61265,70368,63803,PRETRIAL,Nelson,Loreia,NULL,Female,African-American,03/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +61265,70368,63803,PRETRIAL,Nelson,Loreia,NULL,Female,African-American,03/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +61265,70368,63803,PRETRIAL,Nelson,Loreia,NULL,Female,African-American,03/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61262,70364,63799,PRETRIAL,Fox,Reginald,NULL,Male,African-American,03/18/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/15/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +61262,70364,63799,PRETRIAL,Fox,Reginald,NULL,Male,African-American,03/18/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/15/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +61262,70364,63799,PRETRIAL,Fox,Reginald,NULL,Male,African-American,03/18/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61267,70371,63806,PRETRIAL,Cardal,Wyche,NULL,Male,African-American,10/23/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +61267,70371,63806,PRETRIAL,Cardal,Wyche,NULL,Male,African-American,10/23/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +61267,70371,63806,PRETRIAL,Cardal,Wyche,NULL,Male,African-American,10/23/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61266,70369,63804,PRETRIAL,Love,Jalandon,NULL,Male,African-American,10/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +61266,70369,63804,PRETRIAL,Love,Jalandon,NULL,Male,African-American,10/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +61266,70369,63804,PRETRIAL,Love,Jalandon,NULL,Male,African-American,10/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61269,70373,63808,PRETRIAL,YOUNG,JAMES,NULL,Male,Caucasian,04/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +61269,70373,63808,PRETRIAL,YOUNG,JAMES,NULL,Male,Caucasian,04/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +61269,70373,63808,PRETRIAL,YOUNG,JAMES,NULL,Male,Caucasian,04/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/15/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61273,70378,63813,PRETRIAL,Carter,Arthicha,NULL,Female,African-American,11/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +61273,70378,63813,PRETRIAL,Carter,Arthicha,NULL,Female,African-American,11/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +61273,70378,63813,PRETRIAL,Carter,Arthicha,NULL,Female,African-American,11/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +16397,70385,63820,PRETRIAL,BURTON,CARLTON,LEON,Male,African-American,11/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +16397,70385,63820,PRETRIAL,BURTON,CARLTON,LEON,Male,African-American,11/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +16397,70385,63820,PRETRIAL,BURTON,CARLTON,LEON,Male,African-American,11/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +35022,70376,63811,PRETRIAL,Pierre,Brisley,NULL,Male,African-American,10/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +35022,70376,63811,PRETRIAL,Pierre,Brisley,NULL,Male,African-American,10/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +35022,70376,63811,PRETRIAL,Pierre,Brisley,NULL,Male,African-American,10/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +2920,70381,63816,PRETRIAL,treveus,emmanuel,NULL,Male,African-American,12/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +2920,70381,63816,PRETRIAL,treveus,emmanuel,NULL,Male,African-American,12/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +2920,70381,63816,PRETRIAL,treveus,emmanuel,NULL,Male,African-American,12/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61274,70382,63817,PRETRIAL,FRANCIS,ROSETTA,NULL,Female,Other,12/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/16/14 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +61274,70382,63817,PRETRIAL,FRANCIS,ROSETTA,NULL,Female,Other,12/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/16/14 0:00,1,Low,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +61274,70382,63817,PRETRIAL,FRANCIS,ROSETTA,NULL,Female,Other,12/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/16/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +61276,70384,63819,PRETRIAL,LEE,LANIQUE,NULL,Female,African-American,08/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +61276,70384,63819,PRETRIAL,LEE,LANIQUE,NULL,Female,African-American,08/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +61276,70384,63819,PRETRIAL,LEE,LANIQUE,NULL,Female,African-American,08/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55200,70387,63822,PRETRIAL,Duenas,Daniel,NULL,Male,Caucasian,06/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +55200,70387,63822,PRETRIAL,Duenas,Daniel,NULL,Male,Caucasian,06/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +55200,70387,63822,PRETRIAL,Duenas,Daniel,NULL,Male,Caucasian,06/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +30176,70379,63814,PRETRIAL,Dowlatram,Richard,NULL,Male,Other,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +30176,70379,63814,PRETRIAL,Dowlatram,Richard,NULL,Male,Other,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +30176,70379,63814,PRETRIAL,Dowlatram,Richard,NULL,Male,Other,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61272,70377,63812,PRETRIAL,GUZMANSILVA,JESUS,J,Male,Caucasian,12/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/16/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +61272,70377,63812,PRETRIAL,GUZMANSILVA,JESUS,J,Male,Caucasian,12/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/16/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +61272,70377,63812,PRETRIAL,GUZMANSILVA,JESUS,J,Male,Caucasian,12/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61277,70386,63821,PRETRIAL,LONGLEY,SHAWNNETTE,NULL,Female,African-American,11/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +61277,70386,63821,PRETRIAL,LONGLEY,SHAWNNETTE,NULL,Female,African-American,11/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +61277,70386,63821,PRETRIAL,LONGLEY,SHAWNNETTE,NULL,Female,African-American,11/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61278,70388,63823,PRETRIAL,WASHBURN,STEPHEN,JAMES,Male,Caucasian,05/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +61278,70388,63823,PRETRIAL,WASHBURN,STEPHEN,JAMES,Male,Caucasian,05/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +61278,70388,63823,PRETRIAL,WASHBURN,STEPHEN,JAMES,Male,Caucasian,05/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61271,70375,63810,PRETRIAL,Ramirez,Juan,Hiram,Male,Hispanic,03/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/16/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +61271,70375,63810,PRETRIAL,Ramirez,Juan,Hiram,Male,Hispanic,03/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/16/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +61271,70375,63810,PRETRIAL,Ramirez,Juan,Hiram,Male,Hispanic,03/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59949,70380,63815,PRETRIAL,Daniel,Miesha,NULL,Female,African-American,02/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +59949,70380,63815,PRETRIAL,Daniel,Miesha,NULL,Female,African-American,02/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,7,Medium,New,1,0 +59949,70380,63815,PRETRIAL,Daniel,Miesha,NULL,Female,African-American,02/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/16/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61275,70383,63818,PRETRIAL,OLIVER,CLARENCE,NULL,Male,African-American,05/20/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/16/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +61275,70383,63818,PRETRIAL,OLIVER,CLARENCE,NULL,Male,African-American,05/20/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/16/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +61275,70383,63818,PRETRIAL,OLIVER,CLARENCE,NULL,Male,African-American,05/20/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/16/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61290,70401,63835,PRETRIAL,HIRST,JOSHUA,NULL,Male,Caucasian,08/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +61290,70401,63835,PRETRIAL,HIRST,JOSHUA,NULL,Male,Caucasian,08/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,4,High,8,Risk of Recidivism,0.14,8,High,New,1,0 +61290,70401,63835,PRETRIAL,HIRST,JOSHUA,NULL,Male,Caucasian,08/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61286,70396,63831,PRETRIAL,ROBERTS,XOCHITL,NULL,Female,Caucasian,10/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/17/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +61286,70396,63831,PRETRIAL,ROBERTS,XOCHITL,NULL,Female,Caucasian,10/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/17/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +61286,70396,63831,PRETRIAL,ROBERTS,XOCHITL,NULL,Female,Caucasian,10/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +33548,61928,56205,PRETRIAL,Malo,William,NULL,Male,Caucasian,10/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/17/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +33548,61928,56205,PRETRIAL,Malo,William,NULL,Male,Caucasian,10/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/17/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +33548,61928,56205,PRETRIAL,Malo,William,NULL,Male,Caucasian,10/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/17/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61288,70398,63833,PRETRIAL,Ramirez,Leonor,NULL,Female,Hispanic,05/22/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/17/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +61288,70398,63833,PRETRIAL,Ramirez,Leonor,NULL,Female,Hispanic,05/22/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/17/14 0:00,1,Low,8,Risk of Recidivism,-2.82,1,Low,New,1,0 +61288,70398,63833,PRETRIAL,Ramirez,Leonor,NULL,Female,Hispanic,05/22/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61283,70393,63828,PRETRIAL,Anderson,Leanord,Linden,Male,African-American,07/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +61283,70393,63828,PRETRIAL,Anderson,Leanord,Linden,Male,African-American,07/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +61283,70393,63828,PRETRIAL,Anderson,Leanord,Linden,Male,African-American,07/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61281,70391,63826,PRETRIAL,Joachim,Daniot,NULL,Male,Other,10/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +61281,70391,63826,PRETRIAL,Joachim,Daniot,NULL,Male,Other,10/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +61281,70391,63826,PRETRIAL,Joachim,Daniot,NULL,Male,Other,10/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +33548,70400,56205,PRETRIAL,Malo,William,NULL,Male,Caucasian,10/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/17/14 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,Copy,1,0 +33548,70400,56205,PRETRIAL,Malo,William,NULL,Male,Caucasian,10/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/17/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,Copy,1,0 +33548,70400,56205,PRETRIAL,Malo,William,NULL,Male,Caucasian,10/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/17/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +61282,70392,63827,PRETRIAL,Anderson,Linden,S,Male,Other,03/01/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/17/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +61282,70392,63827,PRETRIAL,Anderson,Linden,S,Male,Other,03/01/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/17/14 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +61282,70392,63827,PRETRIAL,Anderson,Linden,S,Male,Other,03/01/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/17/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61279,70389,63824,PRETRIAL,SMITH,WESLEY,AUSTIN,Male,African-American,09/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +61279,70389,63824,PRETRIAL,SMITH,WESLEY,AUSTIN,Male,African-American,09/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +61279,70389,63824,PRETRIAL,SMITH,WESLEY,AUSTIN,Male,African-American,09/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61285,70395,63830,PRETRIAL,Lafond,Laterria,Yvette,Female,African-American,07/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,2,Medium,7,Risk of Violence,-2.57,2,Low,New,1,0 +61285,70395,63830,PRETRIAL,Lafond,Laterria,Yvette,Female,African-American,07/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +61285,70395,63830,PRETRIAL,Lafond,Laterria,Yvette,Female,African-American,07/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61287,70397,63832,PRETRIAL,Davis,Mary,NULL,Female,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +61287,70397,63832,PRETRIAL,Davis,Mary,NULL,Female,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +61287,70397,63832,PRETRIAL,Davis,Mary,NULL,Female,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61291,70402,63836,PRETRIAL,BETHEA,JAMES,EARL,Male,African-American,08/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +61291,70402,63836,PRETRIAL,BETHEA,JAMES,EARL,Male,African-American,08/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +61291,70402,63836,PRETRIAL,BETHEA,JAMES,EARL,Male,African-American,08/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61289,70399,63834,PRETRIAL,HOOD,APRIL,NULL,Female,Caucasian,04/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +61289,70399,63834,PRETRIAL,HOOD,APRIL,NULL,Female,Caucasian,04/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +61289,70399,63834,PRETRIAL,HOOD,APRIL,NULL,Female,Caucasian,04/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +61280,70390,63825,PRETRIAL,GROOVER-WRIGHT,JARRELL,ROMONDO,Male,African-American,07/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +61280,70390,63825,PRETRIAL,GROOVER-WRIGHT,JARRELL,ROMONDO,Male,African-American,07/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +61280,70390,63825,PRETRIAL,GROOVER-WRIGHT,JARRELL,ROMONDO,Male,African-American,07/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61284,70394,63829,PRETRIAL,Pascal,DAVE,NULL,Male,African-American,03/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +61284,70394,63829,PRETRIAL,Pascal,DAVE,NULL,Male,African-American,03/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.78,10,High,New,1,0 +61284,70394,63829,PRETRIAL,Pascal,DAVE,NULL,Male,African-American,03/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61297,70415,63847,PRETRIAL,DOUGHTY,DAVID,NULL,Male,African-American,03/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/18/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +61297,70415,63847,PRETRIAL,DOUGHTY,DAVID,NULL,Male,African-American,03/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +61297,70415,63847,PRETRIAL,DOUGHTY,DAVID,NULL,Male,African-American,03/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/18/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +53675,70424,63856,PRETRIAL,castro,maximo,NULL,Male,Hispanic,09/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +53675,70424,63856,PRETRIAL,castro,maximo,NULL,Male,Hispanic,09/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +53675,70424,63856,PRETRIAL,castro,maximo,NULL,Male,Hispanic,09/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55838,70441,63872,Probation,Richardson,Emanuel,NULL,Male,African-American,06/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +55838,70441,63872,Probation,Richardson,Emanuel,NULL,Male,African-American,06/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +55838,70441,63872,Probation,Richardson,Emanuel,NULL,Male,African-American,06/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +11734,18867,17494,PRETRIAL,Lawrence,Altero,NULL,Male,African-American,02/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,4,High,7,Risk of Violence,-0.97,9,High,New,1,0 +11734,18867,17494,PRETRIAL,Lawrence,Altero,NULL,Male,African-American,02/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,4,High,8,Risk of Recidivism,0.98,10,High,New,1,0 +11734,18867,17494,PRETRIAL,Lawrence,Altero,NULL,Male,African-American,02/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,4,High,18,Risk of Failure to Appear,38,10,High,New,1,0 +57421,70411,63843,PRETRIAL,Washington,Travis,NULL,Male,African-American,05/27/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +57421,70411,63843,PRETRIAL,Washington,Travis,NULL,Male,African-American,05/27/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +57421,70411,63843,PRETRIAL,Washington,Travis,NULL,Male,African-American,05/27/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +9631,70420,63852,PRETRIAL,mills,lorenzo,NULL,Male,African-American,07/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +9631,70420,63852,PRETRIAL,mills,lorenzo,NULL,Male,African-American,07/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +9631,70420,63852,PRETRIAL,mills,lorenzo,NULL,Male,African-American,07/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +61327,70445,63876,Probation,torris,roberts,NULL,Male,African-American,01/23/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +61327,70445,63876,Probation,torris,roberts,NULL,Male,African-American,01/23/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +61327,70445,63876,Probation,torris,roberts,NULL,Male,African-American,01/23/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51975,70427,63859,PRETRIAL,Mcneil,Tony,NULL,Male,African-American,11/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +51975,70427,63859,PRETRIAL,Mcneil,Tony,NULL,Male,African-American,11/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +51975,70427,63859,PRETRIAL,Mcneil,Tony,NULL,Male,African-American,11/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61313,70429,63861,Probation,kraus,steven,NULL,Male,Caucasian,06/03/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/18/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +61313,70429,63861,Probation,kraus,steven,NULL,Male,Caucasian,06/03/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +61313,70429,63861,Probation,kraus,steven,NULL,Male,Caucasian,06/03/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61319,70436,63867,PRETRIAL,Johnson,Anthony,NULL,Male,African-American,07/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/18/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +61319,70436,63867,PRETRIAL,Johnson,Anthony,NULL,Male,African-American,07/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +61319,70436,63867,PRETRIAL,Johnson,Anthony,NULL,Male,African-American,07/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +46443,70406,63840,PRETRIAL,Wright,Livingstone,NULL,Male,African-American,03/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +46443,70406,63840,PRETRIAL,Wright,Livingstone,NULL,Male,African-American,03/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +46443,70406,63840,PRETRIAL,Wright,Livingstone,NULL,Male,African-American,03/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60572,70408,63026,PRETRIAL,Daniel,Carlos,NULL,Male,African-American,05/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,Copy,1,0 +60572,70408,63026,PRETRIAL,Daniel,Carlos,NULL,Male,African-American,05/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,Copy,1,0 +60572,70408,63026,PRETRIAL,Daniel,Carlos,NULL,Male,African-American,05/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +61309,70423,63855,Probation,Romero,Cesar,Lehi,Male,Hispanic,06/14/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +61309,70423,63855,Probation,Romero,Cesar,Lehi,Male,Hispanic,06/14/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +61309,70423,63855,Probation,Romero,Cesar,Lehi,Male,Hispanic,06/14/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61315,70431,63863,Probation,smith,precious,NULL,Female,African-American,01/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +61315,70431,63863,Probation,smith,precious,NULL,Female,African-American,01/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.42,6,Medium,New,1,0 +61315,70431,63863,Probation,smith,precious,NULL,Female,African-American,01/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61292,70403,63837,PRETRIAL,Thomas,Ferriod,NULL,Male,African-American,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,4,High,7,Risk of Violence,-0.62,10,High,New,1,0 +61292,70403,63837,PRETRIAL,Thomas,Ferriod,NULL,Male,African-American,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +61292,70403,63837,PRETRIAL,Thomas,Ferriod,NULL,Male,African-American,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61294,70410,63842,Probation,Escobar,Jorge,NULL,Male,Hispanic,08/10/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/18/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +61294,70410,63842,Probation,Escobar,Jorge,NULL,Male,Hispanic,08/10/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/18/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +61294,70410,63842,Probation,Escobar,Jorge,NULL,Male,Hispanic,08/10/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61311,70426,63858,Probation,Marchini,Angelina,NULL,Female,Caucasian,12/25/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +61311,70426,63858,Probation,Marchini,Angelina,NULL,Female,Caucasian,12/25/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +61311,70426,63858,Probation,Marchini,Angelina,NULL,Female,Caucasian,12/25/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61322,70439,63870,Probation,Garcia,Luis,NULL,Male,Hispanic,01/16/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/18/14 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +61322,70439,63870,Probation,Garcia,Luis,NULL,Male,Hispanic,01/16/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/18/14 0:00,1,Low,8,Risk of Recidivism,-2.56,1,Low,New,1,0 +61322,70439,63870,Probation,Garcia,Luis,NULL,Male,Hispanic,01/16/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61296,70413,63845,Probation,RICCIARDELLI,JOSEPH,J,Male,Caucasian,01/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/18/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +61296,70413,63845,Probation,RICCIARDELLI,JOSEPH,J,Male,Caucasian,01/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/18/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +61296,70413,63845,Probation,RICCIARDELLI,JOSEPH,J,Male,Caucasian,01/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61305,70418,63850,Probation,copeland,tyrone,NULL,Male,African-American,07/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,4,High,7,Risk of Violence,-0.54,10,High,New,1,0 +61305,70418,63850,Probation,copeland,tyrone,NULL,Male,African-American,07/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +61305,70418,63850,Probation,copeland,tyrone,NULL,Male,African-American,07/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +59028,70405,63839,PRETRIAL,Thompson,Jeremy,NULL,Male,African-American,06/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +59028,70405,63839,PRETRIAL,Thompson,Jeremy,NULL,Male,African-American,06/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +59028,70405,63839,PRETRIAL,Thompson,Jeremy,NULL,Male,African-American,06/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61326,70444,63875,Probation,VEGA,CARLOS,L,Male,Hispanic,11/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,New,1,0 +61326,70444,63875,Probation,VEGA,CARLOS,L,Male,Hispanic,11/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +61326,70444,63875,Probation,VEGA,CARLOS,L,Male,Hispanic,11/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61317,70434,63865,Probation,Ferrell,Lee,Alexander,Male,Caucasian,04/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/18/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +61317,70434,63865,Probation,Ferrell,Lee,Alexander,Male,Caucasian,04/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +61317,70434,63865,Probation,Ferrell,Lee,Alexander,Male,Caucasian,04/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/18/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61303,70414,63846,Probation,Saahir,Ramee,Salamah,Male,African-American,10/22/49,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/18/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +61303,70414,63846,Probation,Saahir,Ramee,Salamah,Male,African-American,10/22/49,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +61303,70414,63846,Probation,Saahir,Ramee,Salamah,Male,African-American,10/22/49,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61307,70421,63853,PRETRIAL,DADA,CHRISTOPHER,NULL,Male,African-American,05/29/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/18/14 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +61307,70421,63853,PRETRIAL,DADA,CHRISTOPHER,NULL,Male,African-American,05/29/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/18/14 0:00,1,Low,8,Risk of Recidivism,-2.72,1,Low,New,1,0 +61307,70421,63853,PRETRIAL,DADA,CHRISTOPHER,NULL,Male,African-American,05/29/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61312,70428,63860,Probation,Scanlon,Michael,NULL,Male,Caucasian,05/08/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/18/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +61312,70428,63860,Probation,Scanlon,Michael,NULL,Male,Caucasian,05/08/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +61312,70428,63860,Probation,Scanlon,Michael,NULL,Male,Caucasian,05/08/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61318,70435,63866,Probation,wemple,hattie,NULL,Female,Caucasian,07/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +61318,70435,63866,Probation,wemple,hattie,NULL,Female,Caucasian,07/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +61318,70435,63866,Probation,wemple,hattie,NULL,Female,Caucasian,07/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61324,70442,63873,Probation,Wright,Wayne,Anthony,Male,African-American,08/31/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/18/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +61324,70442,63873,Probation,Wright,Wayne,Anthony,Male,African-American,08/31/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +61324,70442,63873,Probation,Wright,Wayne,Anthony,Male,African-American,08/31/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61304,70416,63848,Probation,callaghan,amoy,NULL,Female,African-American,10/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +61304,70416,63848,Probation,callaghan,amoy,NULL,Female,African-American,10/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,9,High,New,1,0 +61304,70416,63848,Probation,callaghan,amoy,NULL,Female,African-American,10/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61295,70412,63844,Probation,Striegle,Notosha,NULL,Female,Caucasian,10/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +61295,70412,63844,Probation,Striegle,Notosha,NULL,Female,Caucasian,10/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +61295,70412,63844,Probation,Striegle,Notosha,NULL,Female,Caucasian,10/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61306,70419,63851,Probation,Feinstein,Robert,NULL,Male,Caucasian,08/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/18/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +61306,70419,63851,Probation,Feinstein,Robert,NULL,Male,Caucasian,08/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/18/14 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +61306,70419,63851,Probation,Feinstein,Robert,NULL,Male,Caucasian,08/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +34280,70407,33422,PRETRIAL,Hilaire,Garcia,NULL,Male,African-American,12/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,Copy,1,0 +34280,70407,33422,PRETRIAL,Hilaire,Garcia,NULL,Male,African-American,12/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.82,10,High,Copy,1,0 +34280,70407,33422,PRETRIAL,Hilaire,Garcia,NULL,Male,African-American,12/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +28951,70417,63849,Probation,DOYLE,KEVIN,MICHAEL,Male,Caucasian,03/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +28951,70417,63849,Probation,DOYLE,KEVIN,MICHAEL,Male,Caucasian,03/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +28951,70417,63849,Probation,DOYLE,KEVIN,MICHAEL,Male,Caucasian,03/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +61316,70432,63864,Probation,Rucker,Christopher,NULL,Male,Caucasian,02/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +61316,70432,63864,Probation,Rucker,Christopher,NULL,Male,Caucasian,02/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +61316,70432,63864,Probation,Rucker,Christopher,NULL,Male,Caucasian,02/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +11592,70404,63838,Probation,Dunn,John,Frederick,Male,Caucasian,06/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +11592,70404,63838,Probation,Dunn,John,Frederick,Male,Caucasian,06/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +11592,70404,63838,Probation,Dunn,John,Frederick,Male,Caucasian,06/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +61321,70438,63869,Probation,perez,alberto,NULL,Male,Hispanic,01/15/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +61321,70438,63869,Probation,perez,alberto,NULL,Male,Hispanic,01/15/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +61321,70438,63869,Probation,perez,alberto,NULL,Male,Hispanic,01/15/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61310,70425,63857,Probation,DIXON,KENMODIE,OME,Male,African-American,06/15/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +61310,70425,63857,Probation,DIXON,KENMODIE,OME,Male,African-American,06/15/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +61310,70425,63857,Probation,DIXON,KENMODIE,OME,Male,African-American,06/15/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61323,70440,63871,Probation,Massenburg,Cedric,NULL,Male,African-American,10/03/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +61323,70440,63871,Probation,Massenburg,Cedric,NULL,Male,African-American,10/03/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +61323,70440,63871,Probation,Massenburg,Cedric,NULL,Male,African-American,10/03/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61314,70430,63862,Probation,BRENNAN,KRISTEN,ELIZABETH,Female,Caucasian,08/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +61314,70430,63862,Probation,BRENNAN,KRISTEN,ELIZABETH,Female,Caucasian,08/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +61314,70430,63862,Probation,BRENNAN,KRISTEN,ELIZABETH,Female,Caucasian,08/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61293,70409,63841,PRETRIAL,KUCHERICK,SHERI,NULL,Female,Caucasian,10/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +61293,70409,63841,PRETRIAL,KUCHERICK,SHERI,NULL,Female,Caucasian,10/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +61293,70409,63841,PRETRIAL,KUCHERICK,SHERI,NULL,Female,Caucasian,10/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61325,70443,63874,Probation,Marley,Brooke,NULL,Female,Caucasian,02/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +61325,70443,63874,Probation,Marley,Brooke,NULL,Female,Caucasian,02/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +61325,70443,63874,Probation,Marley,Brooke,NULL,Female,Caucasian,02/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61308,70422,63854,Probation,Medina,Cruz,NULL,Male,Hispanic,06/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/18/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +61308,70422,63854,Probation,Medina,Cruz,NULL,Male,Hispanic,06/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/18/14 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +61308,70422,63854,Probation,Medina,Cruz,NULL,Male,Hispanic,06/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/18/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +9694,70477,49433,PRETRIAL,HOLMES,ALREEGUS,NULL,Male,African-American,09/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,Copy,1,0 +9694,70477,49433,PRETRIAL,HOLMES,ALREEGUS,NULL,Male,African-American,09/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,Copy,1,0 +9694,70477,49433,PRETRIAL,HOLMES,ALREEGUS,NULL,Male,African-American,09/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +12411,70456,63885,Probation,Everett,Kenneth,NULL,Male,African-American,06/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +12411,70456,63885,Probation,Everett,Kenneth,NULL,Male,African-American,06/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +12411,70456,63885,Probation,Everett,Kenneth,NULL,Male,African-American,06/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +61360,70490,63915,Probation,PADRON,CANDICE,NULL,Female,Caucasian,10/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.38,3,Low,New,1,0 +61360,70490,63915,Probation,PADRON,CANDICE,NULL,Female,Caucasian,10/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,8,High,New,1,0 +61360,70490,63915,Probation,PADRON,CANDICE,NULL,Female,Caucasian,10/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61343,70469,63897,Probation,Walker,Kenneth,NULL,Male,Asian,11/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/19/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +61343,70469,63897,Probation,Walker,Kenneth,NULL,Male,Asian,11/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +61343,70469,63897,Probation,Walker,Kenneth,NULL,Male,Asian,11/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59571,70448,61923,PRETRIAL,Rowe,Glenn,NULL,Male,Caucasian,10/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,Copy,1,0 +59571,70448,61923,PRETRIAL,Rowe,Glenn,NULL,Male,Caucasian,10/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,Copy,1,0 +59571,70448,61923,PRETRIAL,Rowe,Glenn,NULL,Male,Caucasian,10/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +61331,70451,63881,PRETRIAL,APOINTE,EFRAIN,NULL,Male,Caucasian,11/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +61331,70451,63881,PRETRIAL,APOINTE,EFRAIN,NULL,Male,Caucasian,11/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +61331,70451,63881,PRETRIAL,APOINTE,EFRAIN,NULL,Male,Caucasian,11/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61336,70459,63888,PRETRIAL,Akinpello,Dominick,NULL,Male,African-American,04/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +61336,70459,63888,PRETRIAL,Akinpello,Dominick,NULL,Male,African-American,04/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +61336,70459,63888,PRETRIAL,Akinpello,Dominick,NULL,Male,African-American,04/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61338,70461,63890,Probation,Pino,Nicole,NULL,Female,Hispanic,07/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +61338,70461,63890,Probation,Pino,Nicole,NULL,Female,Hispanic,07/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +61338,70461,63890,Probation,Pino,Nicole,NULL,Female,Hispanic,07/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61342,70467,63895,Probation,Chappie,Zachary,NULL,Male,Caucasian,10/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +61342,70467,63895,Probation,Chappie,Zachary,NULL,Male,Caucasian,10/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +61342,70467,63895,Probation,Chappie,Zachary,NULL,Male,Caucasian,10/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61353,70482,63907,Probation,Bodiford,Ricky,NULL,Male,Caucasian,06/16/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +61353,70482,63907,Probation,Bodiford,Ricky,NULL,Male,Caucasian,06/16/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +61353,70482,63907,Probation,Bodiford,Ricky,NULL,Male,Caucasian,06/16/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61328,70446,63877,PRETRIAL,Ross,Johnny,NULL,Male,African-American,01/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +61328,70446,63877,PRETRIAL,Ross,Johnny,NULL,Male,African-American,01/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +61328,70446,63877,PRETRIAL,Ross,Johnny,NULL,Male,African-American,01/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61333,70453,63883,PRETRIAL,WATSON,SCOTT,EDWARD,Male,Caucasian,07/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +61333,70453,63883,PRETRIAL,WATSON,SCOTT,EDWARD,Male,Caucasian,07/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +61333,70453,63883,PRETRIAL,WATSON,SCOTT,EDWARD,Male,Caucasian,07/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +16903,67502,61206,PRETRIAL,WILLIAMS,ROSE,MARIE,Female,African-American,06/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.51,3,Low,New,1,0 +16903,67502,61206,PRETRIAL,WILLIAMS,ROSE,MARIE,Female,African-American,06/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,8,High,New,1,0 +16903,67502,61206,PRETRIAL,WILLIAMS,ROSE,MARIE,Female,African-American,06/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +59694,70458,63887,PRETRIAL,Crawford,Garrick,Allen,Male,Caucasian,11/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,4,High,7,Risk of Violence,-0.95,9,High,New,1,0 +59694,70458,63887,PRETRIAL,Crawford,Garrick,Allen,Male,Caucasian,11/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +59694,70458,63887,PRETRIAL,Crawford,Garrick,Allen,Male,Caucasian,11/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61348,70475,63901,Probation,umpierre,johnuel,NULL,Male,Hispanic,01/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +61348,70475,63901,Probation,umpierre,johnuel,NULL,Male,Hispanic,01/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +61348,70475,63901,Probation,umpierre,johnuel,NULL,Male,Hispanic,01/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61334,70454,63884,PRETRIAL,LYNCH,SAMANTHA,NULL,Male,Caucasian,02/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +61334,70454,63884,PRETRIAL,LYNCH,SAMANTHA,NULL,Male,Caucasian,02/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +61334,70454,63884,PRETRIAL,LYNCH,SAMANTHA,NULL,Male,Caucasian,02/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61351,70479,63904,PRETRIAL,Hayes,Aphonso,NULL,Male,African-American,08/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,4,High,7,Risk of Violence,-0.96,9,High,New,1,0 +61351,70479,63904,PRETRIAL,Hayes,Aphonso,NULL,Male,African-American,08/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +61351,70479,63904,PRETRIAL,Hayes,Aphonso,NULL,Male,African-American,08/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,4,High,18,Risk of Failure to Appear,40,10,High,New,1,0 +61358,70488,63913,PRETRIAL,Nazario- Cruz,Edgardo,Javier,Male,Hispanic,09/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +61358,70488,63913,PRETRIAL,Nazario- Cruz,Edgardo,Javier,Male,Hispanic,09/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +61358,70488,63913,PRETRIAL,Nazario- Cruz,Edgardo,Javier,Male,Hispanic,09/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +16453,70484,63909,Probation,Cocchi,Steven,Matthew,Male,Caucasian,09/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +16453,70484,63909,Probation,Cocchi,Steven,Matthew,Male,Caucasian,09/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +16453,70484,63909,Probation,Cocchi,Steven,Matthew,Male,Caucasian,09/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61361,70491,63916,Probation,OLSEN,ELIZABETH,CLEMENT,Female,Caucasian,08/09/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/19/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +61361,70491,63916,Probation,OLSEN,ELIZABETH,CLEMENT,Female,Caucasian,08/09/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +61361,70491,63916,Probation,OLSEN,ELIZABETH,CLEMENT,Female,Caucasian,08/09/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +7803,70463,63891,PRETRIAL,GUIMOND,RAYMOND,NULL,Male,Caucasian,10/16/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/19/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +7803,70463,63891,PRETRIAL,GUIMOND,RAYMOND,NULL,Male,Caucasian,10/16/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/19/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +7803,70463,63891,PRETRIAL,GUIMOND,RAYMOND,NULL,Male,Caucasian,10/16/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +61174,70470,63689,PRETRIAL,White,Cedrick,NULL,Male,African-American,05/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,Copy,1,0 +61174,70470,63689,PRETRIAL,White,Cedrick,NULL,Male,African-American,05/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,Copy,1,0 +61174,70470,63689,PRETRIAL,White,Cedrick,NULL,Male,African-American,05/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +61345,70472,63899,Probation,sarafian,richard,NULL,Male,Caucasian,10/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +61345,70472,63899,Probation,sarafian,richard,NULL,Male,Caucasian,10/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +61345,70472,63899,Probation,sarafian,richard,NULL,Male,Caucasian,10/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51078,70449,63879,PRETRIAL,SAINTILUS,SAVANNA,NULL,Female,African-American,06/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +51078,70449,63879,PRETRIAL,SAINTILUS,SAVANNA,NULL,Female,African-American,06/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +51078,70449,63879,PRETRIAL,SAINTILUS,SAVANNA,NULL,Female,African-American,06/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61340,70465,63893,Probation,MARCETIC,MARkO,NULL,Male,Caucasian,04/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +61340,70465,63893,Probation,MARCETIC,MARkO,NULL,Male,Caucasian,04/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +61340,70465,63893,Probation,MARCETIC,MARkO,NULL,Male,Caucasian,04/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +20466,70455,19689,Probation,Dixon,Demario,Barcleor,Male,African-American,03/19/89,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,Copy,1,0 +20466,70455,19689,Probation,Dixon,Demario,Barcleor,Male,African-American,03/19/89,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,Copy,1,0 +20466,70455,19689,Probation,Dixon,Demario,Barcleor,Male,African-American,03/19/89,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +61367,70494,63919,PRETRIAL,Werman,Naomi,NULL,Female,African-American,02/24/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +61367,70494,63919,PRETRIAL,Werman,Naomi,NULL,Female,African-American,02/24/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +61367,70494,63919,PRETRIAL,Werman,Naomi,NULL,Female,African-American,02/24/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61329,70447,63878,PRETRIAL,Garcia,Christopher,Joseph,Male,Caucasian,12/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +61329,70447,63878,PRETRIAL,Garcia,Christopher,Joseph,Male,Caucasian,12/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,4,High,8,Risk of Recidivism,0.26,8,High,New,1,0 +61329,70447,63878,PRETRIAL,Garcia,Christopher,Joseph,Male,Caucasian,12/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61332,70452,63882,PRETRIAL,Irvin,Keith,NULL,Male,African-American,03/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +61332,70452,63882,PRETRIAL,Irvin,Keith,NULL,Male,African-American,03/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +61332,70452,63882,PRETRIAL,Irvin,Keith,NULL,Male,African-American,03/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61356,70486,63911,Probation,Jones,Lockie,Dorson,Male,African-American,10/12/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/14 0:00,2,Medium,7,Risk of Violence,-3.19,1,Low,New,1,0 +61356,70486,63911,Probation,Jones,Lockie,Dorson,Male,African-American,10/12/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +61356,70486,63911,Probation,Jones,Lockie,Dorson,Male,African-American,10/12/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +60827,70473,63305,PRETRIAL,Burton,Travon,NULL,Male,African-American,08/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,Copy,1,0 +60827,70473,63305,PRETRIAL,Burton,Travon,NULL,Male,African-American,08/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.72,4,Low,Copy,1,0 +60827,70473,63305,PRETRIAL,Burton,Travon,NULL,Male,African-American,08/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +61337,70460,63889,PRETRIAL,Egbarin,Blessing,NULL,Female,Other,04/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/19/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +61337,70460,63889,PRETRIAL,Egbarin,Blessing,NULL,Female,Other,04/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/19/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +61337,70460,63889,PRETRIAL,Egbarin,Blessing,NULL,Female,Other,04/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61359,70489,63914,Probation,williams,yudy,NULL,Female,Hispanic,02/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +61359,70489,63914,Probation,williams,yudy,NULL,Female,Hispanic,02/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +61359,70489,63914,Probation,williams,yudy,NULL,Female,Hispanic,02/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51335,70468,63896,PRETRIAL,vanderwynkle,jason,john,Male,Caucasian,07/09/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +51335,70468,63896,PRETRIAL,vanderwynkle,jason,john,Male,Caucasian,07/09/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +51335,70468,63896,PRETRIAL,vanderwynkle,jason,john,Male,Caucasian,07/09/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61352,70481,63906,Probation,BARDUGONE,KATIE,NULL,Female,Caucasian,11/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.41,3,Low,New,1,0 +61352,70481,63906,Probation,BARDUGONE,KATIE,NULL,Female,Caucasian,11/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +61352,70481,63906,Probation,BARDUGONE,KATIE,NULL,Female,Caucasian,11/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61349,70476,63902,PRETRIAL,Weir,Jennifer,NULL,Female,Caucasian,09/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.31,3,Low,New,1,0 +61349,70476,63902,PRETRIAL,Weir,Jennifer,NULL,Female,Caucasian,09/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,8,High,New,1,0 +61349,70476,63902,PRETRIAL,Weir,Jennifer,NULL,Female,Caucasian,09/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +61335,70457,63886,PRETRIAL,Parker,Robert,Earl,Male,African-American,02/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/19/14 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +61335,70457,63886,PRETRIAL,Parker,Robert,Earl,Male,African-American,02/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/19/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +61335,70457,63886,PRETRIAL,Parker,Robert,Earl,Male,African-American,02/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61330,70450,63880,PRETRIAL,RIDDLE,EDWARD,LAWRENCE,Male,Caucasian,07/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,2,Medium,7,Risk of Violence,-2.89,2,Low,New,1,0 +61330,70450,63880,PRETRIAL,RIDDLE,EDWARD,LAWRENCE,Male,Caucasian,07/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +61330,70450,63880,PRETRIAL,RIDDLE,EDWARD,LAWRENCE,Male,Caucasian,07/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +61339,70464,63892,Probation,Gregory,Austin,J,Male,Caucasian,09/17/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +61339,70464,63892,Probation,Gregory,Austin,J,Male,Caucasian,09/17/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +61339,70464,63892,Probation,Gregory,Austin,J,Male,Caucasian,09/17/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/19/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61344,70471,63898,Probation,Pennington,Charles,NULL,Male,Caucasian,03/27/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +61344,70471,63898,Probation,Pennington,Charles,NULL,Male,Caucasian,03/27/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +61344,70471,63898,Probation,Pennington,Charles,NULL,Male,Caucasian,03/27/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61350,70478,63903,PRETRIAL,Givens,Stanley,NULL,Male,African-American,10/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +61350,70478,63903,PRETRIAL,Givens,Stanley,NULL,Male,African-American,10/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +61350,70478,63903,PRETRIAL,Givens,Stanley,NULL,Male,African-American,10/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61365,70492,63917,DRRD,Johnson,Daquan,Rakeem,Male,African-American,02/20/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +61365,70492,63917,DRRD,Johnson,Daquan,Rakeem,Male,African-American,02/20/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,2,Medium,8,Risk of Recidivism,0.11,7,Medium,New,1,0 +61365,70492,63917,DRRD,Johnson,Daquan,Rakeem,Male,African-American,02/20/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61341,70466,63894,Probation,BROWN,DARRICK,S,Male,African-American,03/23/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/19/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +61341,70466,63894,Probation,BROWN,DARRICK,S,Male,African-American,03/23/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +61341,70466,63894,Probation,BROWN,DARRICK,S,Male,African-American,03/23/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61354,70483,63908,PRETRIAL,MINCEY,TASHAUN,NULL,Male,African-American,05/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,2,Medium,7,Risk of Violence,-1.39,7,Medium,New,1,0 +61354,70483,63908,PRETRIAL,MINCEY,TASHAUN,NULL,Male,African-American,05/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +61354,70483,63908,PRETRIAL,MINCEY,TASHAUN,NULL,Male,African-American,05/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +60874,70462,63364,PRETRIAL,Trentman,John,NULL,Male,Caucasian,03/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,Copy,1,0 +60874,70462,63364,PRETRIAL,Trentman,John,NULL,Male,Caucasian,03/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,Copy,1,0 +60874,70462,63364,PRETRIAL,Trentman,John,NULL,Male,Caucasian,03/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/19/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +53386,70480,63905,Probation,Cason,Bridgett,NULL,Female,African-American,11/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +53386,70480,63905,Probation,Cason,Bridgett,NULL,Female,African-American,11/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +53386,70480,63905,Probation,Cason,Bridgett,NULL,Female,African-American,11/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61357,70487,63912,Probation,atiles,ALEXANDER,NULL,Male,Hispanic,11/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +61357,70487,63912,Probation,atiles,ALEXANDER,NULL,Male,Hispanic,11/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +61357,70487,63912,Probation,atiles,ALEXANDER,NULL,Male,Hispanic,11/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/19/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +9694,54325,49433,PRETRIAL,HOLMES,ALREEGUS,NULL,Male,African-American,09/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +9694,54325,49433,PRETRIAL,HOLMES,ALREEGUS,NULL,Male,African-American,09/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +9694,54325,49433,PRETRIAL,HOLMES,ALREEGUS,NULL,Male,African-American,09/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/19/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61372,70501,63926,PRETRIAL,Mattis,Omar,NULL,Male,African-American,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +61372,70501,63926,PRETRIAL,Mattis,Omar,NULL,Male,African-American,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +61372,70501,63926,PRETRIAL,Mattis,Omar,NULL,Male,African-American,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61399,70534,63955,PRETRIAL,Rodriguez,Andres,NULL,Male,Hispanic,03/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +61399,70534,63955,PRETRIAL,Rodriguez,Andres,NULL,Male,Hispanic,03/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +61399,70534,63955,PRETRIAL,Rodriguez,Andres,NULL,Male,Hispanic,03/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61381,70513,63937,Probation,Flowers,Lisa,Marie,Female,Caucasian,10/02/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +61381,70513,63937,Probation,Flowers,Lisa,Marie,Female,Caucasian,10/02/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +61381,70513,63937,Probation,Flowers,Lisa,Marie,Female,Caucasian,10/02/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +29332,70522,63715,Probation,CIRIAGO,MICHAEL,S,Male,Caucasian,09/23/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,4,High,7,Risk of Violence,-1.23,8,High,Copy,1,0 +29332,70522,63715,Probation,CIRIAGO,MICHAEL,S,Male,Caucasian,09/23/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,4,High,8,Risk of Recidivism,0.44,9,High,Copy,1,0 +29332,70522,63715,Probation,CIRIAGO,MICHAEL,S,Male,Caucasian,09/23/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +61370,70499,63924,PRETRIAL,Brown,Shaquille,NULL,Male,African-American,06/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +61370,70499,63924,PRETRIAL,Brown,Shaquille,NULL,Male,African-American,06/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +61370,70499,63924,PRETRIAL,Brown,Shaquille,NULL,Male,African-American,06/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61378,70508,63933,PRETRIAL,RIGG,CHARLES,NULL,Male,African-American,01/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +61378,70508,63933,PRETRIAL,RIGG,CHARLES,NULL,Male,African-American,01/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +61378,70508,63933,PRETRIAL,RIGG,CHARLES,NULL,Male,African-American,01/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61394,70527,63949,Probation,Nazere,Garry,NULL,Male,African-American,07/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +61394,70527,63949,Probation,Nazere,Garry,NULL,Male,African-American,07/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +61394,70527,63949,Probation,Nazere,Garry,NULL,Male,African-American,07/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61396,70529,63951,PRETRIAL,JOHNSON,JAZZIE,LAVANTE,Female,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +61396,70529,63951,PRETRIAL,JOHNSON,JAZZIE,LAVANTE,Female,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.07,8,High,New,1,0 +61396,70529,63951,PRETRIAL,JOHNSON,JAZZIE,LAVANTE,Female,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +21025,70536,63957,PRETRIAL,Digraziano,Christopher,NULL,Male,Hispanic,09/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,4,High,7,Risk of Violence,-0.68,9,High,New,1,0 +21025,70536,63957,PRETRIAL,Digraziano,Christopher,NULL,Male,Hispanic,09/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,4,High,8,Risk of Recidivism,0.11,8,High,New,1,0 +21025,70536,63957,PRETRIAL,Digraziano,Christopher,NULL,Male,Hispanic,09/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +61390,70523,63945,Probation,Jones,Charlene,NULL,Female,Caucasian,08/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +61390,70523,63945,Probation,Jones,Charlene,NULL,Female,Caucasian,08/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +61390,70523,63945,Probation,Jones,Charlene,NULL,Female,Caucasian,08/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61392,70525,63947,PRETRIAL,Torres,Jose,Angel,Male,Caucasian,07/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +61392,70525,63947,PRETRIAL,Torres,Jose,Angel,Male,Caucasian,07/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +61392,70525,63947,PRETRIAL,Torres,Jose,Angel,Male,Caucasian,07/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61369,70497,63922,PRETRIAL,Camejo,Bernardo,NULL,Male,Caucasian,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +61369,70497,63922,PRETRIAL,Camejo,Bernardo,NULL,Male,Caucasian,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +61369,70497,63922,PRETRIAL,Camejo,Bernardo,NULL,Male,Caucasian,08/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61373,70502,63927,PRETRIAL,Santos,Richard,NULL,Male,Hispanic,12/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +61373,70502,63927,PRETRIAL,Santos,Richard,NULL,Male,Hispanic,12/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +61373,70502,63927,PRETRIAL,Santos,Richard,NULL,Male,Hispanic,12/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61374,70504,63929,Probation,Martinez,Jorge,Enrique,Male,Hispanic,06/20/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/20/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +61374,70504,63929,Probation,Martinez,Jorge,Enrique,Male,Hispanic,06/20/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +61374,70504,63929,Probation,Martinez,Jorge,Enrique,Male,Hispanic,06/20/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58848,70538,61082,Probation,WILLIAMS,LATOSHA,NULL,Female,African-American,11/02/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +58848,70538,61082,Probation,WILLIAMS,LATOSHA,NULL,Female,African-American,11/02/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +58848,70538,61082,Probation,WILLIAMS,LATOSHA,NULL,Female,African-American,11/02/87,17,All Scales,Intake,English,Conditional Release,Probation,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61385,70517,63941,PRETRIAL,MAGGIE,PHYLICHIA,NULL,Female,Caucasian,05/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +61385,70517,63941,PRETRIAL,MAGGIE,PHYLICHIA,NULL,Female,Caucasian,05/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +61385,70517,63941,PRETRIAL,MAGGIE,PHYLICHIA,NULL,Female,Caucasian,05/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +41400,70531,63952,Probation,Benavidessanchez,Carlos,NULL,Male,Hispanic,09/15/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +41400,70531,63952,Probation,Benavidessanchez,Carlos,NULL,Male,Hispanic,09/15/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +41400,70531,63952,Probation,Benavidessanchez,Carlos,NULL,Male,Hispanic,09/15/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61368,70496,63921,PRETRIAL,Khan,Sabrina,NULL,Male,African-American,03/25/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +61368,70496,63921,PRETRIAL,Khan,Sabrina,NULL,Male,African-American,03/25/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +61368,70496,63921,PRETRIAL,Khan,Sabrina,NULL,Male,African-American,03/25/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55175,70510,63935,Probation,williams,brantil,NULL,Female,African-American,02/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +55175,70510,63935,Probation,williams,brantil,NULL,Female,African-American,02/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +55175,70510,63935,Probation,williams,brantil,NULL,Female,African-American,02/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +10045,70539,35975,PRETRIAL,ROSELVA,KERBY,NULL,Male,African-American,09/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,Copy,1,0 +10045,70539,35975,PRETRIAL,ROSELVA,KERBY,NULL,Male,African-American,09/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,Copy,1,0 +10045,70539,35975,PRETRIAL,ROSELVA,KERBY,NULL,Male,African-American,09/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +61377,70507,63932,PRETRIAL,Goulbourne,Adlai,NULL,Male,Other,05/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +61377,70507,63932,PRETRIAL,Goulbourne,Adlai,NULL,Male,Other,05/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +61377,70507,63932,PRETRIAL,Goulbourne,Adlai,NULL,Male,Other,05/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +29332,70520,63715,Probation,CIRIAGO,MICHAEL,S,Male,Caucasian,09/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,4,High,7,Risk of Violence,-1.23,8,High,Copy,1,0 +29332,70520,63715,Probation,CIRIAGO,MICHAEL,S,Male,Caucasian,09/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,4,High,8,Risk of Recidivism,0.44,9,High,Copy,1,0 +29332,70520,63715,Probation,CIRIAGO,MICHAEL,S,Male,Caucasian,09/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +61380,70512,63936,Probation,ROUSSEAU,RENEE,NULL,Female,Caucasian,02/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +61380,70512,63936,Probation,ROUSSEAU,RENEE,NULL,Female,Caucasian,02/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.53,2,Low,New,1,0 +61380,70512,63936,Probation,ROUSSEAU,RENEE,NULL,Female,Caucasian,02/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61383,70515,63939,PRETRIAL,PALMER,YANIK,NULL,Male,African-American,01/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +61383,70515,63939,PRETRIAL,PALMER,YANIK,NULL,Male,African-American,01/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +61383,70515,63939,PRETRIAL,PALMER,YANIK,NULL,Male,African-American,01/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61398,70533,63954,PRETRIAL,CASEY,BRENDAN,NULL,Male,Caucasian,05/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +61398,70533,63954,PRETRIAL,CASEY,BRENDAN,NULL,Male,Caucasian,05/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +61398,70533,63954,PRETRIAL,CASEY,BRENDAN,NULL,Male,Caucasian,05/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61371,70500,63925,PRETRIAL,Downshumpries,Jane,NULL,Male,Caucasian,12/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +61371,70500,63925,PRETRIAL,Downshumpries,Jane,NULL,Male,Caucasian,12/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +61371,70500,63925,PRETRIAL,Downshumpries,Jane,NULL,Male,Caucasian,12/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56397,70521,63944,Probation,Bryant,James,NULL,Male,African-American,04/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +56397,70521,63944,Probation,Bryant,James,NULL,Male,African-American,04/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +56397,70521,63944,Probation,Bryant,James,NULL,Male,African-American,04/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61395,70528,63950,Probation,Alcira,Litanis,NULL,Male,African-American,01/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +61395,70528,63950,Probation,Alcira,Litanis,NULL,Male,African-American,01/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +61395,70528,63950,Probation,Alcira,Litanis,NULL,Male,African-American,01/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61375,70505,63930,Probation,Joyner,Leonard,NULL,Male,African-American,09/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/20/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +61375,70505,63930,Probation,Joyner,Leonard,NULL,Male,African-American,09/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +61375,70505,63930,Probation,Joyner,Leonard,NULL,Male,African-American,09/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59648,70530,62009,Probation,COBB,CYNTHIA,NULL,Female,Caucasian,08/18/64,17,All Scales,Intake,English,Conditional Release,Probation,Married,2/20/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +59648,70530,62009,Probation,COBB,CYNTHIA,NULL,Female,Caucasian,08/18/64,17,All Scales,Intake,English,Conditional Release,Probation,Married,2/20/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +59648,70530,62009,Probation,COBB,CYNTHIA,NULL,Female,Caucasian,08/18/64,17,All Scales,Intake,English,Conditional Release,Probation,Married,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61393,70526,63948,Probation,LAKHAN,ADRIAN,NULL,Male,African-American,07/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +61393,70526,63948,Probation,LAKHAN,ADRIAN,NULL,Male,African-American,07/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +61393,70526,63948,Probation,LAKHAN,ADRIAN,NULL,Male,African-American,07/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +15272,70503,63928,PRETRIAL,butler,david,NULL,Male,African-American,08/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +15272,70503,63928,PRETRIAL,butler,david,NULL,Male,African-American,08/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +15272,70503,63928,PRETRIAL,butler,david,NULL,Male,African-American,08/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61397,70532,63953,Probation,ANDERSON,michael,NULL,Male,Caucasian,07/27/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +61397,70532,63953,Probation,ANDERSON,michael,NULL,Male,Caucasian,07/27/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +61397,70532,63953,Probation,ANDERSON,michael,NULL,Male,Caucasian,07/27/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +25578,70495,63920,PRETRIAL,Perez,Emilio,NULL,Male,Hispanic,12/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +25578,70495,63920,PRETRIAL,Perez,Emilio,NULL,Male,Hispanic,12/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +25578,70495,63920,PRETRIAL,Perez,Emilio,NULL,Male,Hispanic,12/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +45166,70498,63923,PRETRIAL,Lewis,Alan,NULL,Male,African-American,10/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +45166,70498,63923,PRETRIAL,Lewis,Alan,NULL,Male,African-American,10/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +45166,70498,63923,PRETRIAL,Lewis,Alan,NULL,Male,African-American,10/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/20/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61389,70519,63943,Probation,Hernandez,Melvin,De Jesus,Male,Hispanic,12/24/79,22,Risk and Prescreen,Intake,English,Other,Probation,Significant Other,2/20/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +61389,70519,63943,Probation,Hernandez,Melvin,De Jesus,Male,Hispanic,12/24/79,22,Risk and Prescreen,Intake,English,Other,Probation,Significant Other,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +61389,70519,63943,Probation,Hernandez,Melvin,De Jesus,Male,Hispanic,12/24/79,22,Risk and Prescreen,Intake,English,Other,Probation,Significant Other,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61401,70537,63958,Probation,malysheva,anastasia,NULL,Female,Caucasian,12/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/20/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +61401,70537,63958,Probation,malysheva,anastasia,NULL,Female,Caucasian,12/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +61401,70537,63958,Probation,malysheva,anastasia,NULL,Female,Caucasian,12/13/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61391,70524,63946,Probation,donegan,shamoree,NULL,Male,African-American,05/29/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/20/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +61391,70524,63946,Probation,donegan,shamoree,NULL,Male,African-American,05/29/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/20/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +61391,70524,63946,Probation,donegan,shamoree,NULL,Male,African-American,05/29/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +20621,70511,19808,DRRD,Bozeman,Oliver,NULL,Male,African-American,09/28/88,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,2/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,Copy,1,0 +20621,70511,19808,DRRD,Bozeman,Oliver,NULL,Male,African-American,09/28/88,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,2/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.98,10,High,Copy,1,0 +20621,70511,19808,DRRD,Bozeman,Oliver,NULL,Male,African-American,09/28/88,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,2/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,Copy,1,0 +61425,70566,63984,PRETRIAL,Byrd,Serina,NULL,Female,African-American,11/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +61425,70566,63984,PRETRIAL,Byrd,Serina,NULL,Female,African-American,11/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +61425,70566,63984,PRETRIAL,Byrd,Serina,NULL,Female,African-American,11/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61402,70540,63959,PRETRIAL,Todd,Brian,Joseph,Male,Caucasian,01/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/21/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +61402,70540,63959,PRETRIAL,Todd,Brian,Joseph,Male,Caucasian,01/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/21/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +61402,70540,63959,PRETRIAL,Todd,Brian,Joseph,Male,Caucasian,01/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/21/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +11754,70568,63986,PRETRIAL,HALL,CHARLES,NULL,Male,African-American,10/11/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/21/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +11754,70568,63986,PRETRIAL,HALL,CHARLES,NULL,Male,African-American,10/11/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/21/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +11754,70568,63986,PRETRIAL,HALL,CHARLES,NULL,Male,African-American,10/11/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/21/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +61404,70542,63961,PRETRIAL,White,John,NULL,Male,Caucasian,06/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +61404,70542,63961,PRETRIAL,White,John,NULL,Male,Caucasian,06/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +61404,70542,63961,PRETRIAL,White,John,NULL,Male,Caucasian,06/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61403,70541,63960,PRETRIAL,King,Shanice,Shantell,Female,African-American,05/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/14 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +61403,70541,63960,PRETRIAL,King,Shanice,Shantell,Female,African-American,05/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +61403,70541,63960,PRETRIAL,King,Shanice,Shantell,Female,African-American,05/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/21/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61426,70567,63985,Probation,DAHER,JAMELL,DAVID,Male,Caucasian,12/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +61426,70567,63985,Probation,DAHER,JAMELL,DAVID,Male,Caucasian,12/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +61426,70567,63985,Probation,DAHER,JAMELL,DAVID,Male,Caucasian,12/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61409,70546,63965,Probation,PHILLIPS,scott,NULL,Male,Caucasian,05/18/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +61409,70546,63965,Probation,PHILLIPS,scott,NULL,Male,Caucasian,05/18/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +61409,70546,63965,Probation,PHILLIPS,scott,NULL,Male,Caucasian,05/18/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61421,70559,63978,Probation,Bowe,Vincent,NULL,Male,African-American,02/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +61421,70559,63978,Probation,Bowe,Vincent,NULL,Male,African-American,02/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +61421,70559,63978,Probation,Bowe,Vincent,NULL,Male,African-American,02/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61417,70554,63973,Probation,URBANEK,ROBERT,NULL,Male,Caucasian,09/12/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +61417,70554,63973,Probation,URBANEK,ROBERT,NULL,Male,Caucasian,09/12/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +61417,70554,63973,Probation,URBANEK,ROBERT,NULL,Male,Caucasian,09/12/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57810,70562,59951,Probation,Wolfe,Theodore,Lee,Male,Caucasian,06/18/76,17,All Scales,Intake,English,Conditional Release,Probation,Widowed,2/21/14 12:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +57810,70562,59951,Probation,Wolfe,Theodore,Lee,Male,Caucasian,06/18/76,17,All Scales,Intake,English,Conditional Release,Probation,Widowed,2/21/14 12:00,1,Low,8,Risk of Recidivism,-0.95,2,Low,New,1,0 +57810,70562,59951,Probation,Wolfe,Theodore,Lee,Male,Caucasian,06/18/76,17,All Scales,Intake,English,Conditional Release,Probation,Widowed,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +61418,70557,63976,Probation,Moya,Jose,Ernesto,Male,Hispanic,11/07/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/21/14 12:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +61418,70557,63976,Probation,Moya,Jose,Ernesto,Male,Hispanic,11/07/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/21/14 12:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +61418,70557,63976,Probation,Moya,Jose,Ernesto,Male,Hispanic,11/07/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61413,70550,63969,Probation,Allen,Byron,NULL,Male,African-American,04/19/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +61413,70550,63969,Probation,Allen,Byron,NULL,Male,African-American,04/19/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +61413,70550,63969,Probation,Allen,Byron,NULL,Male,African-American,04/19/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +44141,70564,63982,Probation,VALDERRAMA,JOSE,NULL,Male,Hispanic,03/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/14 12:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +44141,70564,63982,Probation,VALDERRAMA,JOSE,NULL,Male,Hispanic,03/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/14 12:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +44141,70564,63982,Probation,VALDERRAMA,JOSE,NULL,Male,Hispanic,03/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61415,70552,63971,Probation,Krueger,Jeremy,NULL,Male,Caucasian,03/07/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/21/14 12:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +61415,70552,63971,Probation,Krueger,Jeremy,NULL,Male,Caucasian,03/07/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/21/14 12:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +61415,70552,63971,Probation,Krueger,Jeremy,NULL,Male,Caucasian,03/07/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61405,70543,63962,PRETRIAL,FELIX,LEONARD,NULL,Male,Hispanic,02/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/14 12:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +61405,70543,63962,PRETRIAL,FELIX,LEONARD,NULL,Male,Hispanic,02/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/14 12:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +61405,70543,63962,PRETRIAL,FELIX,LEONARD,NULL,Male,Hispanic,02/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61411,70548,63967,PRETRIAL,SANTIAGO,RUBEN,NULL,Male,Hispanic,02/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/14 12:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +61411,70548,63967,PRETRIAL,SANTIAGO,RUBEN,NULL,Male,Hispanic,02/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/14 12:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +61411,70548,63967,PRETRIAL,SANTIAGO,RUBEN,NULL,Male,Hispanic,02/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52886,70555,63974,PRETRIAL,Jussim,Joao,NULL,Male,Hispanic,10/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +52886,70555,63974,PRETRIAL,Jussim,Joao,NULL,Male,Hispanic,10/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +52886,70555,63974,PRETRIAL,Jussim,Joao,NULL,Male,Hispanic,10/11/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61424,70563,63981,Probation,Zarate,Fabian,Ricardo,Male,Hispanic,01/16/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/21/14 12:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +61424,70563,63981,Probation,Zarate,Fabian,Ricardo,Male,Hispanic,01/16/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/21/14 12:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +61424,70563,63981,Probation,Zarate,Fabian,Ricardo,Male,Hispanic,01/16/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61412,70549,63968,Probation,FREEMAN,AUBREY,NULL,Male,African-American,10/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +61412,70549,63968,Probation,FREEMAN,AUBREY,NULL,Male,African-American,10/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +61412,70549,63968,Probation,FREEMAN,AUBREY,NULL,Male,African-American,10/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61419,70556,63975,PRETRIAL,Thurlow,Christopher,NULL,Male,Caucasian,09/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/14 12:00,3,Medium with Override Consideration,7,Risk of Violence,-2.58,2,Low,New,1,0 +61419,70556,63975,PRETRIAL,Thurlow,Christopher,NULL,Male,Caucasian,09/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/14 12:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +61419,70556,63975,PRETRIAL,Thurlow,Christopher,NULL,Male,Caucasian,09/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/21/14 12:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +61422,70560,63979,Probation,SEEMAN,NORMAN,ALEXANDER,Male,Caucasian,01/26/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +61422,70560,63979,Probation,SEEMAN,NORMAN,ALEXANDER,Male,Caucasian,01/26/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +61422,70560,63979,Probation,SEEMAN,NORMAN,ALEXANDER,Male,Caucasian,01/26/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61410,70547,63966,Probation,williams,carl,NULL,Male,African-American,01/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +61410,70547,63966,Probation,williams,carl,NULL,Male,African-American,01/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +61410,70547,63966,Probation,williams,carl,NULL,Male,African-American,01/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61406,70544,63963,Probation,lorenz,kyle,NULL,Male,Caucasian,09/25/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/14 12:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +61406,70544,63963,Probation,lorenz,kyle,NULL,Male,Caucasian,09/25/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/14 12:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +61406,70544,63963,Probation,lorenz,kyle,NULL,Male,Caucasian,09/25/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61414,70551,63970,Probation,maharaj,anand,NULL,Male,Other,07/08/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/21/14 12:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +61414,70551,63970,Probation,maharaj,anand,NULL,Male,Other,07/08/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/21/14 12:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +61414,70551,63970,Probation,maharaj,anand,NULL,Male,Other,07/08/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61416,70553,63972,Probation,Caperton,Alisa,NULL,Female,Caucasian,04/17/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/21/14 12:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +61416,70553,63972,Probation,Caperton,Alisa,NULL,Female,Caucasian,04/17/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/21/14 12:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +61416,70553,63972,Probation,Caperton,Alisa,NULL,Female,Caucasian,04/17/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +43192,70561,63980,PRETRIAL,Ameerally,Fenton,NULL,Male,African-American,04/24/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +43192,70561,63980,PRETRIAL,Ameerally,Fenton,NULL,Male,African-American,04/24/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +43192,70561,63980,PRETRIAL,Ameerally,Fenton,NULL,Male,African-American,04/24/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61407,70545,63964,Probation,Osborn,Montana,NULL,Male,Hispanic,10/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +61407,70545,63964,Probation,Osborn,Montana,NULL,Male,Hispanic,10/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +61407,70545,63964,Probation,Osborn,Montana,NULL,Male,Hispanic,10/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/21/14 12:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +29546,70579,28553,PRETRIAL,MAMMARELLI,BRADLEY,RICK,Male,Caucasian,05/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/22/14 0:00,4,High,7,Risk of Violence,-0.82,9,High,Copy,1,0 +29546,70579,28553,PRETRIAL,MAMMARELLI,BRADLEY,RICK,Male,Caucasian,05/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/22/14 0:00,4,High,8,Risk of Recidivism,1.69,10,High,Copy,1,0 +29546,70579,28553,PRETRIAL,MAMMARELLI,BRADLEY,RICK,Male,Caucasian,05/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/22/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +59636,70574,63990,PRETRIAL,Jenkins,Dominick,NULL,Male,African-American,10/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +59636,70574,63990,PRETRIAL,Jenkins,Dominick,NULL,Male,African-American,10/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +59636,70574,63990,PRETRIAL,Jenkins,Dominick,NULL,Male,African-American,10/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +37324,70576,43326,PRETRIAL,BREWER,EARL,NULL,Male,African-American,10/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,Copy,1,0 +37324,70576,43326,PRETRIAL,BREWER,EARL,NULL,Male,African-American,10/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.64,10,High,Copy,1,0 +37324,70576,43326,PRETRIAL,BREWER,EARL,NULL,Male,African-American,10/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +61431,70577,63992,PRETRIAL,Harris,Christopher,NULL,Male,African-American,04/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/22/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +61431,70577,63992,PRETRIAL,Harris,Christopher,NULL,Male,African-American,04/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/22/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +61431,70577,63992,PRETRIAL,Harris,Christopher,NULL,Male,African-American,04/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61428,70570,63988,PRETRIAL,ETIENNE,ANGELES,NULL,Male,Other,04/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.08,8,High,New,1,0 +61428,70570,63988,PRETRIAL,ETIENNE,ANGELES,NULL,Male,Other,04/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +61428,70570,63988,PRETRIAL,ETIENNE,ANGELES,NULL,Male,Other,04/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61429,70572,63989,PRETRIAL,Smith,Zanelle,NULL,Female,African-American,10/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/22/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +61429,70572,63989,PRETRIAL,Smith,Zanelle,NULL,Female,African-American,10/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/22/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +61429,70572,63989,PRETRIAL,Smith,Zanelle,NULL,Female,African-American,10/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +28302,70573,49983,PRETRIAL,Bertrane,Latavia,NULL,Female,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,4,High,7,Risk of Violence,-0.86,9,High,Copy,1,0 +28302,70573,49983,PRETRIAL,Bertrane,Latavia,NULL,Female,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,4,High,8,Risk of Recidivism,0.78,10,High,Copy,1,0 +28302,70573,49983,PRETRIAL,Bertrane,Latavia,NULL,Female,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +4722,70571,4412,PRETRIAL,Mack,Christopher,NULL,Male,African-American,01/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.29,3,Low,Copy,1,0 +4722,70571,4412,PRETRIAL,Mack,Christopher,NULL,Male,African-American,01/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,Copy,1,0 +4722,70571,4412,PRETRIAL,Mack,Christopher,NULL,Male,African-American,01/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +61432,70578,63993,PRETRIAL,Newbold,Frederick,NULL,Male,African-American,05/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +61432,70578,63993,PRETRIAL,Newbold,Frederick,NULL,Male,African-American,05/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +61432,70578,63993,PRETRIAL,Newbold,Frederick,NULL,Male,African-American,05/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61430,70575,63991,PRETRIAL,NUNEZ,ELENAIDA,NULL,Female,Other,11/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/22/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +61430,70575,63991,PRETRIAL,NUNEZ,ELENAIDA,NULL,Female,Other,11/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/22/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +61430,70575,63991,PRETRIAL,NUNEZ,ELENAIDA,NULL,Female,Other,11/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +27863,70588,26960,PRETRIAL,Hardy,Shandedra,NULL,Female,African-American,10/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.07,4,Low,Copy,1,0 +27863,70588,26960,PRETRIAL,Hardy,Shandedra,NULL,Female,African-American,10/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,Copy,1,0 +27863,70588,26960,PRETRIAL,Hardy,Shandedra,NULL,Female,African-American,10/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +61433,70580,63994,PRETRIAL,Jolly,Alexander,G,Male,Other,08/02/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/23/14 0:00,1,Low,7,Risk of Violence,-4.37,1,Low,New,1,0 +61433,70580,63994,PRETRIAL,Jolly,Alexander,G,Male,Other,08/02/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/23/14 0:00,1,Low,8,Risk of Recidivism,-2.79,1,Low,New,1,0 +61433,70580,63994,PRETRIAL,Jolly,Alexander,G,Male,Other,08/02/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/23/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61435,70583,63997,PRETRIAL,Prem,Stephen,NULL,Male,Caucasian,07/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +61435,70583,63997,PRETRIAL,Prem,Stephen,NULL,Male,Caucasian,07/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +61435,70583,63997,PRETRIAL,Prem,Stephen,NULL,Male,Caucasian,07/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61437,70585,63999,PRETRIAL,FULTON,HAKEEM,J,Male,African-American,01/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,4,High,7,Risk of Violence,-0.51,10,High,New,1,0 +61437,70585,63999,PRETRIAL,FULTON,HAKEEM,J,Male,African-American,01/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,4,High,8,Risk of Recidivism,1.13,10,High,New,1,0 +61437,70585,63999,PRETRIAL,FULTON,HAKEEM,J,Male,African-American,01/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +43099,70590,45303,PRETRIAL,Hyatt,Akeem,H,Male,African-American,08/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,Copy,1,0 +43099,70590,45303,PRETRIAL,Hyatt,Akeem,H,Male,African-American,08/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,Copy,1,0 +43099,70590,45303,PRETRIAL,Hyatt,Akeem,H,Male,African-American,08/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +61438,70586,64000,PRETRIAL,JABARIS,GIBSON,L,Male,African-American,09/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +61438,70586,64000,PRETRIAL,JABARIS,GIBSON,L,Male,African-American,09/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +61438,70586,64000,PRETRIAL,JABARIS,GIBSON,L,Male,African-American,09/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +43099,49684,45303,PRETRIAL,Hyatt,Akeem,H,Male,African-American,08/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +43099,49684,45303,PRETRIAL,Hyatt,Akeem,H,Male,African-American,08/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +43099,49684,45303,PRETRIAL,Hyatt,Akeem,H,Male,African-American,08/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61439,70589,64001,PRETRIAL,GAITAN,LUIS,NULL,Male,Hispanic,10/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/23/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +61439,70589,64001,PRETRIAL,GAITAN,LUIS,NULL,Male,Hispanic,10/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/23/14 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +61439,70589,64001,PRETRIAL,GAITAN,LUIS,NULL,Male,Hispanic,10/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +21238,70581,63995,PRETRIAL,RENOSA,JOE,NULL,Male,African-American,12/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/23/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +21238,70581,63995,PRETRIAL,RENOSA,JOE,NULL,Male,African-American,12/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/23/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +21238,70581,63995,PRETRIAL,RENOSA,JOE,NULL,Male,African-American,12/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61434,70582,63996,PRETRIAL,Lisinicchia,Anthony,NULL,Male,African-American,10/22/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +61434,70582,63996,PRETRIAL,Lisinicchia,Anthony,NULL,Male,African-American,10/22/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +61434,70582,63996,PRETRIAL,Lisinicchia,Anthony,NULL,Male,African-American,10/22/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61436,70584,63998,PRETRIAL,Bailey,Aston,NULL,Male,African-American,11/28/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +61436,70584,63998,PRETRIAL,Bailey,Aston,NULL,Male,African-American,11/28/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +61436,70584,63998,PRETRIAL,Bailey,Aston,NULL,Male,African-American,11/28/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +15663,70587,62572,PRETRIAL,REYES,CHARLIE,NULL,Male,Hispanic,02/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,Copy,1,0 +15663,70587,62572,PRETRIAL,REYES,CHARLIE,NULL,Male,Hispanic,02/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,6,Medium,Copy,1,0 +15663,70587,62572,PRETRIAL,REYES,CHARLIE,NULL,Male,Hispanic,02/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/23/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +61452,70605,64016,Probation,buenrostro,reno,NULL,Male,Hispanic,02/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +61452,70605,64016,Probation,buenrostro,reno,NULL,Male,Hispanic,02/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +61452,70605,64016,Probation,buenrostro,reno,NULL,Male,Hispanic,02/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +61459,70613,64023,Probation,Bridger,Roswell,Carter,Male,Caucasian,09/09/52,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/24/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +61459,70613,64023,Probation,Bridger,Roswell,Carter,Male,Caucasian,09/09/52,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +61459,70613,64023,Probation,Bridger,Roswell,Carter,Male,Caucasian,09/09/52,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61440,70592,64003,PRETRIAL,ANDERSON,AHKEEM,NULL,Male,African-American,08/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +61440,70592,64003,PRETRIAL,ANDERSON,AHKEEM,NULL,Male,African-American,08/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,4,High,8,Risk of Recidivism,0.25,8,High,New,1,0 +61440,70592,64003,PRETRIAL,ANDERSON,AHKEEM,NULL,Male,African-American,08/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50689,70626,64036,PRETRIAL,Powers,Christina,NULL,Female,Caucasian,10/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +50689,70626,64036,PRETRIAL,Powers,Christina,NULL,Female,Caucasian,10/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +50689,70626,64036,PRETRIAL,Powers,Christina,NULL,Female,Caucasian,10/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61464,70618,64028,Probation,diaz,david,NULL,Male,Hispanic,08/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +61464,70618,64028,Probation,diaz,david,NULL,Male,Hispanic,08/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +61464,70618,64028,Probation,diaz,david,NULL,Male,Hispanic,08/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61449,70603,64014,PRETRIAL,Wilson,Thaffi,NULL,Female,African-American,10/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +61449,70603,64014,PRETRIAL,Wilson,Thaffi,NULL,Female,African-American,10/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +61449,70603,64014,PRETRIAL,Wilson,Thaffi,NULL,Female,African-American,10/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61457,70610,64020,PRETRIAL,DIXON,JAMIA,NULL,Female,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +61457,70610,64020,PRETRIAL,DIXON,JAMIA,NULL,Female,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +61457,70610,64020,PRETRIAL,DIXON,JAMIA,NULL,Female,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61442,70595,64006,PRETRIAL,EMERY,FLORA,NULL,Female,African-American,02/20/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/24/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +61442,70595,64006,PRETRIAL,EMERY,FLORA,NULL,Female,African-American,02/20/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +61442,70595,64006,PRETRIAL,EMERY,FLORA,NULL,Female,African-American,02/20/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61444,70597,64008,PRETRIAL,Scire,Philip,NULL,Male,Caucasian,09/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +61444,70597,64008,PRETRIAL,Scire,Philip,NULL,Male,Caucasian,09/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +61444,70597,64008,PRETRIAL,Scire,Philip,NULL,Male,Caucasian,09/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61448,70602,64013,Probation,Williams,Mikhail,NULL,Male,African-American,01/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +61448,70602,64013,Probation,Williams,Mikhail,NULL,Male,African-American,01/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +61448,70602,64013,Probation,Williams,Mikhail,NULL,Male,African-American,01/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61454,70607,64018,Probation,McLeod,Rheinna,NULL,Female,African-American,09/04/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +61454,70607,64018,Probation,McLeod,Rheinna,NULL,Female,African-American,09/04/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +61454,70607,64018,Probation,McLeod,Rheinna,NULL,Female,African-American,09/04/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +61445,70598,64009,PRETRIAL,Kiefer,Christopher,NULL,Male,Caucasian,04/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +61445,70598,64009,PRETRIAL,Kiefer,Christopher,NULL,Male,Caucasian,04/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +61445,70598,64009,PRETRIAL,Kiefer,Christopher,NULL,Male,Caucasian,04/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61462,70616,64026,Probation,haynes,monica,NULL,Female,African-American,05/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +61462,70616,64026,Probation,haynes,monica,NULL,Female,African-American,05/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +61462,70616,64026,Probation,haynes,monica,NULL,Female,African-American,05/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +61458,70612,64022,Probation,SAMUELS,WAYNE,C,Male,Caucasian,12/27/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +61458,70612,64022,Probation,SAMUELS,WAYNE,C,Male,Caucasian,12/27/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +61458,70612,64022,Probation,SAMUELS,WAYNE,C,Male,Caucasian,12/27/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61465,70619,64029,Probation,Sharpstein,Jessica,NULL,Female,Caucasian,03/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +61465,70619,64029,Probation,Sharpstein,Jessica,NULL,Female,Caucasian,03/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +61465,70619,64029,Probation,Sharpstein,Jessica,NULL,Female,Caucasian,03/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60531,70591,64002,PRETRIAL,POIRIER,SEAN,LEE,Male,Caucasian,10/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +60531,70591,64002,PRETRIAL,POIRIER,SEAN,LEE,Male,Caucasian,10/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +60531,70591,64002,PRETRIAL,POIRIER,SEAN,LEE,Male,Caucasian,10/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57977,70593,64004,PRETRIAL,ALFORD,DANNY,DEVON,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,4,High,7,Risk of Violence,-0.84,9,High,New,1,0 +57977,70593,64004,PRETRIAL,ALFORD,DANNY,DEVON,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +57977,70593,64004,PRETRIAL,ALFORD,DANNY,DEVON,Male,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61447,70600,64011,Probation,rodriguez,jose,NULL,Male,Hispanic,07/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +61447,70600,64011,Probation,rodriguez,jose,NULL,Male,Hispanic,07/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +61447,70600,64011,Probation,rodriguez,jose,NULL,Male,Hispanic,07/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61460,70614,64024,Probation,Tammaro,Gregory,NULL,Male,Caucasian,05/18/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-4.27,1,Low,New,1,0 +61460,70614,64024,Probation,Tammaro,Gregory,NULL,Male,Caucasian,05/18/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +61460,70614,64024,Probation,Tammaro,Gregory,NULL,Male,Caucasian,05/18/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61467,70621,64031,Probation,VIGNA,MARINO,FRANK,Male,Caucasian,10/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +61467,70621,64031,Probation,VIGNA,MARINO,FRANK,Male,Caucasian,10/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +61467,70621,64031,Probation,VIGNA,MARINO,FRANK,Male,Caucasian,10/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +41469,70628,64038,PRETRIAL,Caraballo,Josue,NULL,Male,Caucasian,02/18/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +41469,70628,64038,PRETRIAL,Caraballo,Josue,NULL,Male,Caucasian,02/18/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +41469,70628,64038,PRETRIAL,Caraballo,Josue,NULL,Male,Caucasian,02/18/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61471,70624,64034,PRETRIAL,ST.AIME,DANIEL,NULL,Male,Other,01/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +61471,70624,64034,PRETRIAL,ST.AIME,DANIEL,NULL,Male,Other,01/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +61471,70624,64034,PRETRIAL,ST.AIME,DANIEL,NULL,Male,Other,01/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +30745,70611,64021,PRETRIAL,Minge,Nicolas,Charles,Male,Caucasian,12/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,4,High,7,Risk of Violence,-0.56,10,High,New,1,0 +30745,70611,64021,PRETRIAL,Minge,Nicolas,Charles,Male,Caucasian,12/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +30745,70611,64021,PRETRIAL,Minge,Nicolas,Charles,Male,Caucasian,12/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61466,70620,64030,PRETRIAL,Reloba,Leonel,NULL,Male,Hispanic,12/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +61466,70620,64030,PRETRIAL,Reloba,Leonel,NULL,Male,Hispanic,12/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +61466,70620,64030,PRETRIAL,Reloba,Leonel,NULL,Male,Hispanic,12/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61441,70594,64005,PRETRIAL,Morris,Herbert,NULL,Male,African-American,01/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/24/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +61441,70594,64005,PRETRIAL,Morris,Herbert,NULL,Male,African-American,01/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/24/14 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +61441,70594,64005,PRETRIAL,Morris,Herbert,NULL,Male,African-American,01/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61461,70615,64025,PRETRIAL,Wilhelm,Ian,NULL,Male,Caucasian,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/24/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +61461,70615,64025,PRETRIAL,Wilhelm,Ian,NULL,Male,Caucasian,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/24/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +61461,70615,64025,PRETRIAL,Wilhelm,Ian,NULL,Male,Caucasian,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61446,70599,64010,PRETRIAL,PARRISH,VALENTINA,NULL,Female,Caucasian,01/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +61446,70599,64010,PRETRIAL,PARRISH,VALENTINA,NULL,Female,Caucasian,01/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +61446,70599,64010,PRETRIAL,PARRISH,VALENTINA,NULL,Female,Caucasian,01/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61453,70606,64017,Probation,ROMAN,BENIGNO,NULL,Male,African-American,01/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,2,Medium,7,Risk of Violence,-2.23,4,Low,New,1,0 +61453,70606,64017,Probation,ROMAN,BENIGNO,NULL,Male,African-American,01/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +61453,70606,64017,Probation,ROMAN,BENIGNO,NULL,Male,African-American,01/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +61456,70608,64019,PRETRIAL,MATUTE,RAMON,NULL,Male,Hispanic,09/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +61456,70608,64019,PRETRIAL,MATUTE,RAMON,NULL,Male,Hispanic,09/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +61456,70608,64019,PRETRIAL,MATUTE,RAMON,NULL,Male,Hispanic,09/01/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58746,70627,64037,PRETRIAL,Brown,Jarod,NULL,Male,African-American,11/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +58746,70627,64037,PRETRIAL,Brown,Jarod,NULL,Male,African-American,11/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +58746,70627,64037,PRETRIAL,Brown,Jarod,NULL,Male,African-American,11/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61473,70629,64039,Probation,chorba,kate,NULL,Female,Caucasian,10/24/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.46,3,Low,New,1,0 +61473,70629,64039,Probation,chorba,kate,NULL,Female,Caucasian,10/24/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +61473,70629,64039,Probation,chorba,kate,NULL,Female,Caucasian,10/24/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +47384,70601,64012,PRETRIAL,SALA,JEAN,NULL,Female,Caucasian,01/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +47384,70601,64012,PRETRIAL,SALA,JEAN,NULL,Female,Caucasian,01/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +47384,70601,64012,PRETRIAL,SALA,JEAN,NULL,Female,Caucasian,01/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61468,70622,64032,Probation,blount,terry,NULL,Female,African-American,09/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +61468,70622,64032,Probation,blount,terry,NULL,Female,African-American,09/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +61468,70622,64032,Probation,blount,terry,NULL,Female,African-American,09/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61472,70625,64035,Probation,STEPHENS,JAMES,J,Male,Caucasian,12/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +61472,70625,64035,Probation,STEPHENS,JAMES,J,Male,Caucasian,12/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +61472,70625,64035,Probation,STEPHENS,JAMES,J,Male,Caucasian,12/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61450,70604,64015,Probation,LEHOUILLIER,RENE,A,Male,Caucasian,01/05/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +61450,70604,64015,Probation,LEHOUILLIER,RENE,A,Male,Caucasian,01/05/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +61450,70604,64015,Probation,LEHOUILLIER,RENE,A,Male,Caucasian,01/05/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61443,70596,64007,PRETRIAL,Metellus,Sam,NULL,Male,Other,11/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +61443,70596,64007,PRETRIAL,Metellus,Sam,NULL,Male,Other,11/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +61443,70596,64007,PRETRIAL,Metellus,Sam,NULL,Male,Other,11/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61463,70617,64027,Probation,Campo,Luis,NULL,Male,Hispanic,09/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +61463,70617,64027,Probation,Campo,Luis,NULL,Male,Hispanic,09/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,New,1,0 +61463,70617,64027,Probation,Campo,Luis,NULL,Male,Hispanic,09/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61474,70632,64042,PRETRIAL,BROWN,CALVIN,LEE,Male,African-American,04/30/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.54,3,Low,New,1,0 +61474,70632,64042,PRETRIAL,BROWN,CALVIN,LEE,Male,African-American,04/30/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +61474,70632,64042,PRETRIAL,BROWN,CALVIN,LEE,Male,African-American,04/30/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61507,70667,64075,PRETRIAL,Akel,Christopher,N,Male,Caucasian,05/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/14 0:00,1,Low,7,Risk of Violence,-1.81,5,Medium,New,1,0 +61507,70667,64075,PRETRIAL,Akel,Christopher,N,Male,Caucasian,05/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +61507,70667,64075,PRETRIAL,Akel,Christopher,N,Male,Caucasian,05/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61490,70646,64056,Probation,Nelson,Cynthia,NULL,Female,Caucasian,08/30/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/25/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +61490,70646,64056,Probation,Nelson,Cynthia,NULL,Female,Caucasian,08/30/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/25/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +61490,70646,64056,Probation,Nelson,Cynthia,NULL,Female,Caucasian,08/30/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +61497,70653,64063,Probation,SASKIN,ALLICIA,NULL,Female,Caucasian,07/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +61497,70653,64063,Probation,SASKIN,ALLICIA,NULL,Female,Caucasian,07/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +61497,70653,64063,Probation,SASKIN,ALLICIA,NULL,Female,Caucasian,07/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61480,70638,64048,PRETRIAL,Kaplan,Scott,David,Male,Caucasian,11/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +61480,70638,64048,PRETRIAL,Kaplan,Scott,David,Male,Caucasian,11/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +61480,70638,64048,PRETRIAL,Kaplan,Scott,David,Male,Caucasian,11/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61502,70661,64070,PRETRIAL,Mendez,Leonardo,NULL,Male,Hispanic,06/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,2/25/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +61502,70661,64070,PRETRIAL,Mendez,Leonardo,NULL,Male,Hispanic,06/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,2/25/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +61502,70661,64070,PRETRIAL,Mendez,Leonardo,NULL,Male,Hispanic,06/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61482,70640,64050,PRETRIAL,Neloms,Nicholas,NULL,Male,African-American,10/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.31,7,Medium,New,1,0 +61482,70640,64050,PRETRIAL,Neloms,Nicholas,NULL,Male,African-American,10/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +61482,70640,64050,PRETRIAL,Neloms,Nicholas,NULL,Male,African-American,10/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50254,70656,64066,PRETRIAL,Truini,Enrico,R,Male,Caucasian,10/24/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/25/14 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +50254,70656,64066,PRETRIAL,Truini,Enrico,R,Male,Caucasian,10/24/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/25/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +50254,70656,64066,PRETRIAL,Truini,Enrico,R,Male,Caucasian,10/24/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61484,70643,64053,PRETRIAL,ROSA,GREYMI,ANTONIO,Male,Caucasian,03/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/25/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +61484,70643,64053,PRETRIAL,ROSA,GREYMI,ANTONIO,Male,Caucasian,03/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/25/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +61484,70643,64053,PRETRIAL,ROSA,GREYMI,ANTONIO,Male,Caucasian,03/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61493,70648,64058,Probation,lobe,arthur,NULL,Male,Caucasian,05/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/25/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +61493,70648,64058,Probation,lobe,arthur,NULL,Male,Caucasian,05/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/25/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +61493,70648,64058,Probation,lobe,arthur,NULL,Male,Caucasian,05/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +48758,70651,64061,Probation,HACKETT,LYNN,CORTLAND,Female,Caucasian,06/03/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/25/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +48758,70651,64061,Probation,HACKETT,LYNN,CORTLAND,Female,Caucasian,06/03/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/25/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +48758,70651,64061,Probation,HACKETT,LYNN,CORTLAND,Female,Caucasian,06/03/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +43712,70630,64040,PRETRIAL,Holmes,Travis,NULL,Male,African-American,12/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +43712,70630,64040,PRETRIAL,Holmes,Travis,NULL,Male,African-American,12/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,4,High,8,Risk of Recidivism,0.26,8,High,New,1,0 +43712,70630,64040,PRETRIAL,Holmes,Travis,NULL,Male,African-American,12/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54010,70669,64077,Probation,thomas,elridge,NULL,Male,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/25/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +54010,70669,64077,Probation,thomas,elridge,NULL,Male,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/25/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +54010,70669,64077,Probation,thomas,elridge,NULL,Male,African-American,12/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61478,70636,64046,PRETRIAL,Jean,Makenlie,NULL,Male,Other,01/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +61478,70636,64046,PRETRIAL,Jean,Makenlie,NULL,Male,Other,01/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +61478,70636,64046,PRETRIAL,Jean,Makenlie,NULL,Male,Other,01/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61495,70650,64060,Probation,Deangelis,William,NULL,Male,Caucasian,12/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.47,3,Low,New,1,0 +61495,70650,64060,Probation,Deangelis,William,NULL,Male,Caucasian,12/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +61495,70650,64060,Probation,Deangelis,William,NULL,Male,Caucasian,12/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61504,70664,64072,PRETRIAL,plancher,andy,NULL,Male,African-American,04/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/14 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +61504,70664,64072,PRETRIAL,plancher,andy,NULL,Male,African-American,04/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +61504,70664,64072,PRETRIAL,plancher,andy,NULL,Male,African-American,04/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61509,70671,64079,Probation,Isaacs,Jacqueline,NULL,Female,Caucasian,04/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +61509,70671,64079,Probation,Isaacs,Jacqueline,NULL,Female,Caucasian,04/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +61509,70671,64079,Probation,Isaacs,Jacqueline,NULL,Female,Caucasian,04/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61506,70666,64074,PRETRIAL,Gratz,Kenneth,NULL,Male,Caucasian,12/23/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/25/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +61506,70666,64074,PRETRIAL,Gratz,Kenneth,NULL,Male,Caucasian,12/23/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/25/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +61506,70666,64074,PRETRIAL,Gratz,Kenneth,NULL,Male,Caucasian,12/23/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61487,70645,64055,PRETRIAL,Powell,Glenroy,Shane,Male,African-American,06/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/25/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +61487,70645,64055,PRETRIAL,Powell,Glenroy,Shane,Male,African-American,06/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/25/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +61487,70645,64055,PRETRIAL,Powell,Glenroy,Shane,Male,African-American,06/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61483,70641,64051,PRETRIAL,ALMEIDA-GARCIA,JESUS,O,Male,Caucasian,08/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/25/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +61483,70641,64051,PRETRIAL,ALMEIDA-GARCIA,JESUS,O,Male,Caucasian,08/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/25/14 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +61483,70641,64051,PRETRIAL,ALMEIDA-GARCIA,JESUS,O,Male,Caucasian,08/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61476,70635,64045,PRETRIAL,Heath,Earl,Francis,Male,Caucasian,08/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +61476,70635,64045,PRETRIAL,Heath,Earl,Francis,Male,Caucasian,08/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +61476,70635,64045,PRETRIAL,Heath,Earl,Francis,Male,Caucasian,08/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +61494,70649,64059,Probation,Salasvalderrama,Juan,NULL,Male,Hispanic,05/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +61494,70649,64059,Probation,Salasvalderrama,Juan,NULL,Male,Hispanic,05/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +61494,70649,64059,Probation,Salasvalderrama,Juan,NULL,Male,Hispanic,05/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61485,70642,64052,PRETRIAL,Gonzalez,Daniel,NULL,Male,Caucasian,06/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +61485,70642,64052,PRETRIAL,Gonzalez,Daniel,NULL,Male,Caucasian,06/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +61485,70642,64052,PRETRIAL,Gonzalez,Daniel,NULL,Male,Caucasian,06/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61503,70663,64071,PRETRIAL,ARENCIBIA,PEDRO,NULL,Male,Hispanic,08/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/25/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,Copy,1,0 +61503,70663,64071,PRETRIAL,ARENCIBIA,PEDRO,NULL,Male,Hispanic,08/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/25/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,Copy,1,0 +61503,70663,64071,PRETRIAL,ARENCIBIA,PEDRO,NULL,Male,Hispanic,08/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +61508,70670,64078,Probation,torres,maricela,NULL,Female,Hispanic,06/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +61508,70670,64078,Probation,torres,maricela,NULL,Female,Hispanic,06/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +61508,70670,64078,Probation,torres,maricela,NULL,Female,Hispanic,06/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61479,70637,64047,PRETRIAL,Dameus,Daphne,NULL,Female,Other,09/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +61479,70637,64047,PRETRIAL,Dameus,Daphne,NULL,Female,Other,09/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +61479,70637,64047,PRETRIAL,Dameus,Daphne,NULL,Female,Other,09/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +61475,70633,64043,PRETRIAL,Harmon,Stephen,M,Male,Caucasian,07/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +61475,70633,64043,PRETRIAL,Harmon,Stephen,M,Male,Caucasian,07/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +61475,70633,64043,PRETRIAL,Harmon,Stephen,M,Male,Caucasian,07/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61498,70654,64064,PRETRIAL,atwell,alfonso,NULL,Male,African-American,02/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +61498,70654,64064,PRETRIAL,atwell,alfonso,NULL,Male,African-American,02/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/14 0:00,4,High,8,Risk of Recidivism,1.03,10,High,New,1,0 +61498,70654,64064,PRETRIAL,atwell,alfonso,NULL,Male,African-American,02/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/14 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +40074,70631,64041,PRETRIAL,MITCHELL,LARRY,NULL,Male,African-American,07/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.11,1,Low,New,1,0 +40074,70631,64041,PRETRIAL,MITCHELL,LARRY,NULL,Male,African-American,07/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +40074,70631,64041,PRETRIAL,MITCHELL,LARRY,NULL,Male,African-American,07/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +61481,70639,64049,PRETRIAL,Ruizgonzalez,Eloy,David,Male,Hispanic,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.01,8,High,New,1,0 +61481,70639,64049,PRETRIAL,Ruizgonzalez,Eloy,David,Male,Hispanic,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,7,Medium,New,1,0 +61481,70639,64049,PRETRIAL,Ruizgonzalez,Eloy,David,Male,Hispanic,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59506,70668,64076,PRETRIAL,jones,konrad,NULL,Male,Caucasian,03/17/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +59506,70668,64076,PRETRIAL,jones,konrad,NULL,Male,Caucasian,03/17/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,4,High,8,Risk of Recidivism,1.17,10,High,New,1,0 +59506,70668,64076,PRETRIAL,jones,konrad,NULL,Male,Caucasian,03/17/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61501,70660,64069,PRETRIAL,Mendoza,Alfonso,NULL,Male,Caucasian,09/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,2/25/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +61501,70660,64069,PRETRIAL,Mendoza,Alfonso,NULL,Male,Caucasian,09/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,2/25/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +61501,70660,64069,PRETRIAL,Mendoza,Alfonso,NULL,Male,Caucasian,09/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +61492,70647,64057,PRETRIAL,Morse,Michael,NULL,Male,Caucasian,08/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/14 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +61492,70647,64057,PRETRIAL,Morse,Michael,NULL,Male,Caucasian,08/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +61492,70647,64057,PRETRIAL,Morse,Michael,NULL,Male,Caucasian,08/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/25/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61496,70652,64062,Probation,Hershey,Kimberly,NULL,Female,Caucasian,09/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +61496,70652,64062,Probation,Hershey,Kimberly,NULL,Female,Caucasian,09/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +61496,70652,64062,Probation,Hershey,Kimberly,NULL,Female,Caucasian,09/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +61486,70644,64054,PRETRIAL,Abreu,Ramon,NULL,Male,Caucasian,12/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/25/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +61486,70644,64054,PRETRIAL,Abreu,Ramon,NULL,Male,Caucasian,12/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/25/14 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +61486,70644,64054,PRETRIAL,Abreu,Ramon,NULL,Male,Caucasian,12/05/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61499,70655,64065,Probation,Stevenson,Paul,NULL,Male,Caucasian,03/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.67,2,Low,New,1,0 +61499,70655,64065,Probation,Stevenson,Paul,NULL,Male,Caucasian,03/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +61499,70655,64065,Probation,Stevenson,Paul,NULL,Male,Caucasian,03/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61477,70634,64044,PRETRIAL,Dor,Johnny,NULL,Male,African-American,02/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/25/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +61477,70634,64044,PRETRIAL,Dor,Johnny,NULL,Male,African-American,02/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/25/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +61477,70634,64044,PRETRIAL,Dor,Johnny,NULL,Male,African-American,02/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61505,70665,64073,PRETRIAL,Williams,Lee,NULL,Male,African-American,12/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/25/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +61505,70665,64073,PRETRIAL,Williams,Lee,NULL,Male,African-American,12/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/25/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +61505,70665,64073,PRETRIAL,Williams,Lee,NULL,Male,African-American,12/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,2/25/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +1132,70702,64105,PRETRIAL,YOUNG,KISER,NULL,Male,African-American,06/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +1132,70702,64105,PRETRIAL,YOUNG,KISER,NULL,Male,African-American,06/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +1132,70702,64105,PRETRIAL,YOUNG,KISER,NULL,Male,African-American,06/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61541,70715,64117,PRETRIAL,cousino,charlene,NULL,Female,Caucasian,05/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/26/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +61541,70715,64117,PRETRIAL,cousino,charlene,NULL,Female,Caucasian,05/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +61541,70715,64117,PRETRIAL,cousino,charlene,NULL,Female,Caucasian,05/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61529,70694,64101,Probation,PLANT,KAILEY,NICOLE,Female,Caucasian,12/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +61529,70694,64101,Probation,PLANT,KAILEY,NICOLE,Female,Caucasian,12/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +61529,70694,64101,Probation,PLANT,KAILEY,NICOLE,Female,Caucasian,12/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61538,70712,64114,Probation,Love,Lynn,NULL,Male,Caucasian,09/09/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/26/14 0:00,1,Low,7,Risk of Violence,-4.39,1,Low,New,1,0 +61538,70712,64114,Probation,Love,Lynn,NULL,Male,Caucasian,09/09/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/26/14 0:00,1,Low,8,Risk of Recidivism,-2.87,1,Low,New,1,0 +61538,70712,64114,Probation,Love,Lynn,NULL,Male,Caucasian,09/09/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +24748,70686,64093,Probation,Wilks,Marlon,Alfa,Male,African-American,02/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +24748,70686,64093,Probation,Wilks,Marlon,Alfa,Male,African-American,02/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +24748,70686,64093,Probation,Wilks,Marlon,Alfa,Male,African-American,02/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61511,70673,64081,PRETRIAL,Brooks,Darius,NULL,Male,African-American,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +61511,70673,64081,PRETRIAL,Brooks,Darius,NULL,Male,African-American,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +61511,70673,64081,PRETRIAL,Brooks,Darius,NULL,Male,African-American,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61534,70707,64109,Probation,Tavalera,Efrain,NULL,Male,Hispanic,08/05/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/26/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +61534,70707,64109,Probation,Tavalera,Efrain,NULL,Male,Hispanic,08/05/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/26/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +61534,70707,64109,Probation,Tavalera,Efrain,NULL,Male,Hispanic,08/05/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61524,70689,64096,PRETRIAL,CASTELLANOS,JUSTIN,NULL,Male,Caucasian,03/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +61524,70689,64096,PRETRIAL,CASTELLANOS,JUSTIN,NULL,Male,Caucasian,03/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +61524,70689,64096,PRETRIAL,CASTELLANOS,JUSTIN,NULL,Male,Caucasian,03/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +26139,70696,25254,PRETRIAL,DICKERSON,CAMEO,NULL,Female,Caucasian,01/01/89,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +26139,70696,25254,PRETRIAL,DICKERSON,CAMEO,NULL,Female,Caucasian,01/01/89,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,7,Medium,New,1,0 +26139,70696,25254,PRETRIAL,DICKERSON,CAMEO,NULL,Female,Caucasian,01/01/89,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,2,Medium,18,Risk of Failure to Appear,16,1,Low,New,1,0 +36886,70697,64102,PRETRIAL,Cameron,Lennox,NULL,Male,African-American,01/06/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/26/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +36886,70697,64102,PRETRIAL,Cameron,Lennox,NULL,Male,African-American,01/06/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +36886,70697,64102,PRETRIAL,Cameron,Lennox,NULL,Male,African-American,01/06/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61513,70676,64083,PRETRIAL,BATISTA MATARRANZ,FRANYER,RAFAEL,Male,Caucasian,07/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +61513,70676,64083,PRETRIAL,BATISTA MATARRANZ,FRANYER,RAFAEL,Male,Caucasian,07/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +61513,70676,64083,PRETRIAL,BATISTA MATARRANZ,FRANYER,RAFAEL,Male,Caucasian,07/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61537,70710,64112,PRETRIAL,Marks,Phillip,NULL,Male,Caucasian,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +61537,70710,64112,PRETRIAL,Marks,Phillip,NULL,Male,Caucasian,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +61537,70710,64112,PRETRIAL,Marks,Phillip,NULL,Male,Caucasian,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61516,70679,64086,PRETRIAL,Gary,Zakendra,A,Male,African-American,11/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +61516,70679,64086,PRETRIAL,Gary,Zakendra,A,Male,African-American,11/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +61516,70679,64086,PRETRIAL,Gary,Zakendra,A,Male,African-American,11/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61523,70688,64095,PRETRIAL,Kinchen,Zelda,NULL,Female,African-American,04/10/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +61523,70688,64095,PRETRIAL,Kinchen,Zelda,NULL,Female,African-American,04/10/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +61523,70688,64095,PRETRIAL,Kinchen,Zelda,NULL,Female,African-American,04/10/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,2,Medium,18,Risk of Failure to Appear,29,9,High,New,1,0 +61512,70675,64082,PRETRIAL,WONG-COOPER,AMINA,NULL,Female,African-American,06/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +61512,70675,64082,PRETRIAL,WONG-COOPER,AMINA,NULL,Female,African-American,06/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +61512,70675,64082,PRETRIAL,WONG-COOPER,AMINA,NULL,Female,African-American,06/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61536,70709,64111,Probation,Joseph,George,NULL,Male,Caucasian,08/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +61536,70709,64111,Probation,Joseph,George,NULL,Male,Caucasian,08/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +61536,70709,64111,Probation,Joseph,George,NULL,Male,Caucasian,08/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +61520,70684,64091,PRETRIAL,Klein,Dori,NULL,Male,Caucasian,04/17/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +61520,70684,64091,PRETRIAL,Klein,Dori,NULL,Male,Caucasian,04/17/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +61520,70684,64091,PRETRIAL,Klein,Dori,NULL,Male,Caucasian,04/17/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61510,70672,64080,PRETRIAL,Cox,Daniel,NULL,Male,Caucasian,01/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +61510,70672,64080,PRETRIAL,Cox,Daniel,NULL,Male,Caucasian,01/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +61510,70672,64080,PRETRIAL,Cox,Daniel,NULL,Male,Caucasian,01/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61528,70693,64100,Probation,johnson,mercedes,NULL,Female,African-American,06/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +61528,70693,64100,Probation,johnson,mercedes,NULL,Female,African-American,06/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +61528,70693,64100,Probation,johnson,mercedes,NULL,Female,African-American,06/02/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +9499,70700,62305,PRETRIAL,CATIS,WILL,NULL,Male,African-American,05/12/82,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +9499,70700,62305,PRETRIAL,CATIS,WILL,NULL,Male,African-American,05/12/82,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,4,High,8,Risk of Recidivism,0.76,10,High,New,1,0 +9499,70700,62305,PRETRIAL,CATIS,WILL,NULL,Male,African-American,05/12/82,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,4,High,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +61540,70714,64116,Probation,Aghazadian,Christine,NULL,Female,Caucasian,10/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +61540,70714,64116,Probation,Aghazadian,Christine,NULL,Female,Caucasian,10/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +61540,70714,64116,Probation,Aghazadian,Christine,NULL,Female,Caucasian,10/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61527,70692,64099,Probation,Rodriguez,Ariel,NULL,Male,Hispanic,12/18/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +61527,70692,64099,Probation,Rodriguez,Ariel,NULL,Male,Hispanic,12/18/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +61527,70692,64099,Probation,Rodriguez,Ariel,NULL,Male,Hispanic,12/18/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61519,70683,64090,PRETRIAL,Roberts,Orville,NULL,Male,African-American,01/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +61519,70683,64090,PRETRIAL,Roberts,Orville,NULL,Male,African-American,01/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +61519,70683,64090,PRETRIAL,Roberts,Orville,NULL,Male,African-American,01/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +46971,70680,64087,PRETRIAL,Ogilvie,Fitzroy,Anthony,Male,African-American,07/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +46971,70680,64087,PRETRIAL,Ogilvie,Fitzroy,Anthony,Male,African-American,07/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +46971,70680,64087,PRETRIAL,Ogilvie,Fitzroy,Anthony,Male,African-American,07/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61522,70687,64094,PRETRIAL,Dalo,Michael,NULL,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +61522,70687,64094,PRETRIAL,Dalo,Michael,NULL,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +61522,70687,64094,PRETRIAL,Dalo,Michael,NULL,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/26/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61515,70678,64085,PRETRIAL,Pinnock,Rayan,Anthony,Male,Other,10/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +61515,70678,64085,PRETRIAL,Pinnock,Rayan,Anthony,Male,Other,10/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +61515,70678,64085,PRETRIAL,Pinnock,Rayan,Anthony,Male,Other,10/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61521,70685,64092,PRETRIAL,GUILLAUME,ALAIN,NULL,Male,African-American,03/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/26/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +61521,70685,64092,PRETRIAL,GUILLAUME,ALAIN,NULL,Male,African-American,03/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +61521,70685,64092,PRETRIAL,GUILLAUME,ALAIN,NULL,Male,African-American,03/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61531,70699,64104,PRETRIAL,Campbell,Miguel,NULL,Male,African-American,06/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,New,1,0 +61531,70699,64104,PRETRIAL,Campbell,Miguel,NULL,Male,African-American,06/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +61531,70699,64104,PRETRIAL,Campbell,Miguel,NULL,Male,African-American,06/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61533,70706,64108,PRETRIAL,Hawthorne,Kevin,Alexander,Male,Caucasian,07/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +61533,70706,64108,PRETRIAL,Hawthorne,Kevin,Alexander,Male,Caucasian,07/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +61533,70706,64108,PRETRIAL,Hawthorne,Kevin,Alexander,Male,Caucasian,07/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61535,70708,64110,PRETRIAL,miner,riley,NULL,Male,Caucasian,06/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +61535,70708,64110,PRETRIAL,miner,riley,NULL,Male,Caucasian,06/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +61535,70708,64110,PRETRIAL,miner,riley,NULL,Male,Caucasian,06/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61530,70698,64103,PRETRIAL,Morgan,Jeffry,NULL,Male,Caucasian,09/28/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/26/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +61530,70698,64103,PRETRIAL,Morgan,Jeffry,NULL,Male,Caucasian,09/28/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +61530,70698,64103,PRETRIAL,Morgan,Jeffry,NULL,Male,Caucasian,09/28/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61514,70677,64084,PRETRIAL,DAVIS,RASHAAD,KHABAR,Male,African-American,12/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +61514,70677,64084,PRETRIAL,DAVIS,RASHAAD,KHABAR,Male,African-American,12/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +61514,70677,64084,PRETRIAL,DAVIS,RASHAAD,KHABAR,Male,African-American,12/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +15679,70711,64113,PRETRIAL,MARTINEZHERNADNEZ,RAFAEL,E,Male,Hispanic,04/28/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +15679,70711,64113,PRETRIAL,MARTINEZHERNADNEZ,RAFAEL,E,Male,Hispanic,04/28/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +15679,70711,64113,PRETRIAL,MARTINEZHERNADNEZ,RAFAEL,E,Male,Hispanic,04/28/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +54310,70674,55915,PRETRIAL,Natta,Tazomi,NULL,Male,African-American,07/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,Copy,1,0 +54310,70674,55915,PRETRIAL,Natta,Tazomi,NULL,Male,African-American,07/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,Copy,1,0 +54310,70674,55915,PRETRIAL,Natta,Tazomi,NULL,Male,African-American,07/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +61532,70703,64106,Probation,Martin,Patricia,NULL,Female,Caucasian,02/09/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/26/14 0:00,1,Low,7,Risk of Violence,-4.45,1,Low,New,1,0 +61532,70703,64106,Probation,Martin,Patricia,NULL,Female,Caucasian,02/09/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/26/14 0:00,1,Low,8,Risk of Recidivism,-2.65,1,Low,New,1,0 +61532,70703,64106,Probation,Martin,Patricia,NULL,Female,Caucasian,02/09/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61518,70682,64089,PRETRIAL,DUVAL,YVELOURDES,NULL,Female,African-American,04/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +61518,70682,64089,PRETRIAL,DUVAL,YVELOURDES,NULL,Female,African-American,04/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +61518,70682,64089,PRETRIAL,DUVAL,YVELOURDES,NULL,Female,African-American,04/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/26/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59941,70732,62312,PRETRIAL,Vassallo,Giovanni,NULL,Male,Caucasian,11/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,Copy,1,0 +59941,70732,62312,PRETRIAL,Vassallo,Giovanni,NULL,Male,Caucasian,11/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,Copy,1,0 +59941,70732,62312,PRETRIAL,Vassallo,Giovanni,NULL,Male,Caucasian,11/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +61572,70753,64151,Probation,Osorio Calero,Juan,Ramon,Male,Hispanic,03/09/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/27/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +61572,70753,64151,Probation,Osorio Calero,Juan,Ramon,Male,Hispanic,03/09/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +61572,70753,64151,Probation,Osorio Calero,Juan,Ramon,Male,Hispanic,03/09/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61559,70740,64138,PRETRIAL,Morrison,Harry,NULL,Male,African-American,11/30/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +61559,70740,64138,PRETRIAL,Morrison,Harry,NULL,Male,African-American,11/30/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +61559,70740,64138,PRETRIAL,Morrison,Harry,NULL,Male,African-American,11/30/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61565,70745,64143,PRETRIAL,Doerfor,Patrick,NULL,Male,Caucasian,03/17/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/27/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +61565,70745,64143,PRETRIAL,Doerfor,Patrick,NULL,Male,Caucasian,03/17/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +61565,70745,64143,PRETRIAL,Doerfor,Patrick,NULL,Male,Caucasian,03/17/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61012,70724,63518,PRETRIAL,HAYNES,DEXTER,NULL,Male,African-American,05/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,Copy,1,0 +61012,70724,63518,PRETRIAL,HAYNES,DEXTER,NULL,Male,African-American,05/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,Copy,1,0 +61012,70724,63518,PRETRIAL,HAYNES,DEXTER,NULL,Male,African-American,05/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +61542,70716,64118,PRETRIAL,McKenzie,Mickelia,NULL,Female,Other,12/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +61542,70716,64118,PRETRIAL,McKenzie,Mickelia,NULL,Female,Other,12/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +61542,70716,64118,PRETRIAL,McKenzie,Mickelia,NULL,Female,Other,12/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61545,70719,64121,PRETRIAL,NG,WAILIM,NULL,Male,Asian,07/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +61545,70719,64121,PRETRIAL,NG,WAILIM,NULL,Male,Asian,07/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +61545,70719,64121,PRETRIAL,NG,WAILIM,NULL,Male,Asian,07/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51347,70737,64136,PRETRIAL,SINISTERRA,JORGE,NULL,Male,Hispanic,04/04/71,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,2/27/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +51347,70737,64136,PRETRIAL,SINISTERRA,JORGE,NULL,Male,Hispanic,04/04/71,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +51347,70737,64136,PRETRIAL,SINISTERRA,JORGE,NULL,Male,Hispanic,04/04/71,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61550,70727,64127,Probation,Singletary,Ashley,Reese,Female,African-American,06/21/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +61550,70727,64127,Probation,Singletary,Ashley,Reese,Female,African-American,06/21/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +61550,70727,64127,Probation,Singletary,Ashley,Reese,Female,African-American,06/21/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +39476,70729,64129,PRETRIAL,Conner,Christina,R,Female,Caucasian,02/20/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +39476,70729,64129,PRETRIAL,Conner,Christina,R,Female,Caucasian,02/20/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +39476,70729,64129,PRETRIAL,Conner,Christina,R,Female,Caucasian,02/20/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61556,70736,64135,Probation,Sanders,Bruce,NULL,Male,African-American,09/05/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +61556,70736,64135,Probation,Sanders,Bruce,NULL,Male,African-American,09/05/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +61556,70736,64135,Probation,Sanders,Bruce,NULL,Male,African-American,09/05/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61568,70750,64148,Probation,robertson,angie,NULL,Female,Caucasian,10/05/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +61568,70750,64148,Probation,robertson,angie,NULL,Female,Caucasian,10/05/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +61568,70750,64148,Probation,robertson,angie,NULL,Female,Caucasian,10/05/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +44066,70748,64146,PRETRIAL,Espinal,John,NULL,Male,Caucasian,06/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +44066,70748,64146,PRETRIAL,Espinal,John,NULL,Male,Caucasian,06/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +44066,70748,64146,PRETRIAL,Espinal,John,NULL,Male,Caucasian,06/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61554,70734,64133,Probation,roman,elvin,NULL,Male,Hispanic,02/24/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +61554,70734,64133,Probation,roman,elvin,NULL,Male,Hispanic,02/24/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +61554,70734,64133,Probation,roman,elvin,NULL,Male,Hispanic,02/24/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61571,70752,64150,Probation,Marien,Justin,NULL,Male,Caucasian,12/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +61571,70752,64150,Probation,Marien,Justin,NULL,Male,Caucasian,12/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +61571,70752,64150,Probation,Marien,Justin,NULL,Male,Caucasian,12/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61563,70743,64141,Probation,BERT,PAUL,A,Male,Caucasian,10/22/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +61563,70743,64141,Probation,BERT,PAUL,A,Male,Caucasian,10/22/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +61563,70743,64141,Probation,BERT,PAUL,A,Male,Caucasian,10/22/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +12883,70722,12366,PRETRIAL,PLATT,RAYMOND,NULL,Male,Caucasian,08/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,Copy,1,0 +12883,70722,12366,PRETRIAL,PLATT,RAYMOND,NULL,Male,Caucasian,08/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,Copy,1,0 +12883,70722,12366,PRETRIAL,PLATT,RAYMOND,NULL,Male,Caucasian,08/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +59218,70721,64123,PRETRIAL,TAYLOR,WILLIAM,FRANCIS,Male,African-American,11/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +59218,70721,64123,PRETRIAL,TAYLOR,WILLIAM,FRANCIS,Male,African-American,11/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +59218,70721,64123,PRETRIAL,TAYLOR,WILLIAM,FRANCIS,Male,African-American,11/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +42782,70728,64128,PRETRIAL,MYERS,KIANNA,NULL,Female,Caucasian,10/10/93,17,All Scales,Intake,English,Pretrial,Probation,Single,2/27/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +42782,70728,64128,PRETRIAL,MYERS,KIANNA,NULL,Female,Caucasian,10/10/93,17,All Scales,Intake,English,Pretrial,Probation,Single,2/27/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +42782,70728,64128,PRETRIAL,MYERS,KIANNA,NULL,Female,Caucasian,10/10/93,17,All Scales,Intake,English,Pretrial,Probation,Single,2/27/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61555,70735,64134,Probation,STAMPER,DANIEL,H,Male,Caucasian,02/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +61555,70735,64134,Probation,STAMPER,DANIEL,H,Male,Caucasian,02/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +61555,70735,64134,Probation,STAMPER,DANIEL,H,Male,Caucasian,02/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61567,70749,64147,Probation,VILLALOBOS,RANDALL,NULL,Male,Hispanic,05/16/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/27/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +61567,70749,64147,Probation,VILLALOBOS,RANDALL,NULL,Male,Hispanic,05/16/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +61567,70749,64147,Probation,VILLALOBOS,RANDALL,NULL,Male,Hispanic,05/16/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61562,70742,64140,Probation,williams,robert,NULL,Male,African-American,08/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +61562,70742,64140,Probation,williams,robert,NULL,Male,African-American,08/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +61562,70742,64140,Probation,williams,robert,NULL,Male,African-American,08/17/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61569,70751,64149,Probation,Clendinen,Victor,NULL,Male,Hispanic,09/16/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/27/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +61569,70751,64149,Probation,Clendinen,Victor,NULL,Male,Hispanic,09/16/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +61569,70751,64149,Probation,Clendinen,Victor,NULL,Male,Hispanic,09/16/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61551,70730,64130,Probation,Afterman,Eriach,NULL,Male,Caucasian,05/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +61551,70730,64130,Probation,Afterman,Eriach,NULL,Male,Caucasian,05/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +61551,70730,64130,Probation,Afterman,Eriach,NULL,Male,Caucasian,05/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61564,70744,64142,Probation,Lefavre,Sergine,NULL,Female,African-American,12/03/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/14 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +61564,70744,64142,Probation,Lefavre,Sergine,NULL,Female,African-American,12/03/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,New,1,0 +61564,70744,64142,Probation,Lefavre,Sergine,NULL,Female,African-American,12/03/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/27/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61549,70726,64126,Probation,sananes,carly,NULL,Female,Caucasian,11/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +61549,70726,64126,Probation,sananes,carly,NULL,Female,Caucasian,11/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +61549,70726,64126,Probation,sananes,carly,NULL,Female,Caucasian,11/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +12572,12987,12056,PRETRIAL,ROLLE,KENNETH,NULL,Male,African-American,06/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,Copy,1,0 +12572,12987,12056,PRETRIAL,ROLLE,KENNETH,NULL,Male,African-American,06/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.4,4,Low,Copy,1,0 +12572,12987,12056,PRETRIAL,ROLLE,KENNETH,NULL,Male,African-American,06/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,2,Low,Copy,1,0 +61547,70723,64124,Probation,champion,thomas,brantley,Male,Caucasian,01/03/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +61547,70723,64124,Probation,champion,thomas,brantley,Male,Caucasian,01/03/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +61547,70723,64124,Probation,champion,thomas,brantley,Male,Caucasian,01/03/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +61548,70725,64125,PRETRIAL,HOTARY,STEPHEN,NULL,Male,Caucasian,11/30/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +61548,70725,64125,PRETRIAL,HOTARY,STEPHEN,NULL,Male,Caucasian,11/30/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +61548,70725,64125,PRETRIAL,HOTARY,STEPHEN,NULL,Male,Caucasian,11/30/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +12572,70738,12056,PRETRIAL,ROLLE,KENNETH,NULL,Male,African-American,06/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,Copy,1,0 +12572,70738,12056,PRETRIAL,ROLLE,KENNETH,NULL,Male,African-American,06/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.6,3,Low,Copy,1,0 +12572,70738,12056,PRETRIAL,ROLLE,KENNETH,NULL,Male,African-American,06/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,2,Low,Copy,1,0 +61558,70739,64137,Probation,Robinson,Kyle,NULL,Male,Caucasian,01/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +61558,70739,64137,Probation,Robinson,Kyle,NULL,Male,Caucasian,01/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +61558,70739,64137,Probation,Robinson,Kyle,NULL,Male,Caucasian,01/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61566,70746,64144,Probation,watson,kelly,NULL,Female,Caucasian,07/26/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +61566,70746,64144,Probation,watson,kelly,NULL,Female,Caucasian,07/26/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +61566,70746,64144,Probation,watson,kelly,NULL,Female,Caucasian,07/26/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +61543,70717,64119,PRETRIAL,DOUGLAS,JORDAN,DOMINIC,Male,African-American,03/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +61543,70717,64119,PRETRIAL,DOUGLAS,JORDAN,DOMINIC,Male,African-American,03/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +61543,70717,64119,PRETRIAL,DOUGLAS,JORDAN,DOMINIC,Male,African-American,03/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61544,70718,64120,PRETRIAL,Saintil,Jonathan,NULL,Male,African-American,02/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +61544,70718,64120,PRETRIAL,Saintil,Jonathan,NULL,Male,African-American,02/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +61544,70718,64120,PRETRIAL,Saintil,Jonathan,NULL,Male,African-American,02/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61560,70741,64139,Probation,grande,sofia,NULL,Female,Hispanic,11/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +61560,70741,64139,Probation,grande,sofia,NULL,Female,Hispanic,11/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +61560,70741,64139,Probation,grande,sofia,NULL,Female,Hispanic,11/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61546,70720,64122,PRETRIAL,Yates,Jarvis,Trevino,Male,African-American,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +61546,70720,64122,PRETRIAL,Yates,Jarvis,Trevino,Male,African-American,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +61546,70720,64122,PRETRIAL,Yates,Jarvis,Trevino,Male,African-American,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +47480,70754,64152,PRETRIAL,Morrison,Patrick,NULL,Male,African-American,05/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +47480,70754,64152,PRETRIAL,Morrison,Patrick,NULL,Male,African-American,05/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +47480,70754,64152,PRETRIAL,Morrison,Patrick,NULL,Male,African-American,05/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/27/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61553,70733,64132,PRETRIAL,GARAY,ALEX,NULL,Male,Caucasian,05/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +61553,70733,64132,PRETRIAL,GARAY,ALEX,NULL,Male,Caucasian,05/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +61553,70733,64132,PRETRIAL,GARAY,ALEX,NULL,Male,Caucasian,05/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/27/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +29242,70783,64180,PRETRIAL,Tactuk,Aaron,Douglas,Male,African-American,01/03/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2,4,Low,New,1,0 +29242,70783,64180,PRETRIAL,Tactuk,Aaron,Douglas,Male,African-American,01/03/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +29242,70783,64180,PRETRIAL,Tactuk,Aaron,Douglas,Male,African-American,01/03/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61576,70762,64159,PRETRIAL,Cupidore,Kareem,Staubyn,Male,Other,06/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +61576,70762,64159,PRETRIAL,Cupidore,Kareem,Staubyn,Male,Other,06/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +61576,70762,64159,PRETRIAL,Cupidore,Kareem,Staubyn,Male,Other,06/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +46399,70780,64177,PRETRIAL,Plummer,Mark,NULL,Male,African-American,12/22/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/28/14 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +46399,70780,64177,PRETRIAL,Plummer,Mark,NULL,Male,African-American,12/22/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/28/14 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +46399,70780,64177,PRETRIAL,Plummer,Mark,NULL,Male,African-American,12/22/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,2/28/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61598,70788,64184,PRETRIAL,DOLPH,BRAD,NULL,Male,Caucasian,03/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +61598,70788,64184,PRETRIAL,DOLPH,BRAD,NULL,Male,Caucasian,03/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +61598,70788,64184,PRETRIAL,DOLPH,BRAD,NULL,Male,Caucasian,03/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61588,70775,64172,PRETRIAL,carvajal,alejandro,NULL,Male,Hispanic,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +61588,70775,64172,PRETRIAL,carvajal,alejandro,NULL,Male,Hispanic,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +61588,70775,64172,PRETRIAL,carvajal,alejandro,NULL,Male,Hispanic,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61581,70767,64164,PRETRIAL,Minter,Brandon,NULL,Male,African-American,11/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +61581,70767,64164,PRETRIAL,Minter,Brandon,NULL,Male,African-American,11/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +61581,70767,64164,PRETRIAL,Minter,Brandon,NULL,Male,African-American,11/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61574,70759,64156,PRETRIAL,Garcon,Patricia,NULL,Female,African-American,03/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +61574,70759,64156,PRETRIAL,Garcon,Patricia,NULL,Female,African-American,03/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +61574,70759,64156,PRETRIAL,Garcon,Patricia,NULL,Female,African-American,03/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44003,70756,44049,PRETRIAL,wilson,brandon,NULL,Male,African-American,09/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,4,High,7,Risk of Violence,-0.57,10,High,Copy,1,0 +44003,70756,44049,PRETRIAL,wilson,brandon,NULL,Male,African-American,09/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,4,High,8,Risk of Recidivism,0.33,8,High,Copy,1,0 +44003,70756,44049,PRETRIAL,wilson,brandon,NULL,Male,African-American,09/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +61593,70781,64178,Probation,crocker,tracy,NULL,Female,Caucasian,10/05/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/28/14 0:00,2,Medium,7,Risk of Violence,-3.31,1,Low,New,1,0 +61593,70781,64178,Probation,crocker,tracy,NULL,Female,Caucasian,10/05/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.42,6,Medium,New,1,0 +61593,70781,64178,Probation,crocker,tracy,NULL,Female,Caucasian,10/05/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/28/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +22990,70760,64157,PRETRIAL,HOWARD,MISS,NULL,Female,African-American,02/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,2,Medium,7,Risk of Violence,-2.47,3,Low,New,1,0 +22990,70760,64157,PRETRIAL,HOWARD,MISS,NULL,Female,African-American,02/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +22990,70760,64157,PRETRIAL,HOWARD,MISS,NULL,Female,African-American,02/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +61590,70777,64174,Probation,Padilla,Esther,NULL,Female,Hispanic,09/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +61590,70777,64174,Probation,Padilla,Esther,NULL,Female,Hispanic,09/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +61590,70777,64174,Probation,Padilla,Esther,NULL,Female,Hispanic,09/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +61579,70765,64162,Probation,Mar,Hugo,NULL,Male,Hispanic,09/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/28/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +61579,70765,64162,Probation,Mar,Hugo,NULL,Male,Hispanic,09/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/28/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +61579,70765,64162,Probation,Mar,Hugo,NULL,Male,Hispanic,09/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61600,70791,64187,PRETRIAL,HANNMANN,MICHAEL,NULL,Male,Caucasian,02/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +61600,70791,64187,PRETRIAL,HANNMANN,MICHAEL,NULL,Male,Caucasian,02/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +61600,70791,64187,PRETRIAL,HANNMANN,MICHAEL,NULL,Male,Caucasian,02/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61577,70763,64160,PRETRIAL,Eady,Walter,NULL,Male,African-American,11/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +61577,70763,64160,PRETRIAL,Eady,Walter,NULL,Male,African-American,11/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +61577,70763,64160,PRETRIAL,Eady,Walter,NULL,Male,African-American,11/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61583,70770,64167,Probation,Ng,kityun,NULL,Male,Asian,02/28/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +61583,70770,64167,Probation,Ng,kityun,NULL,Male,Asian,02/28/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +61583,70770,64167,Probation,Ng,kityun,NULL,Male,Asian,02/28/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +29430,70772,64169,PRETRIAL,VENTURA,MOISES,NULL,Male,Caucasian,06/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +29430,70772,64169,PRETRIAL,VENTURA,MOISES,NULL,Male,Caucasian,06/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +29430,70772,64169,PRETRIAL,VENTURA,MOISES,NULL,Male,Caucasian,06/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61599,70790,64186,PRETRIAL,Fogarty,Lisa,NULL,Female,Caucasian,08/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/28/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +61599,70790,64186,PRETRIAL,Fogarty,Lisa,NULL,Female,Caucasian,08/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/28/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +61599,70790,64186,PRETRIAL,Fogarty,Lisa,NULL,Female,Caucasian,08/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61573,70755,64153,PRETRIAL,Johnson,Dextervanness,J,Male,African-American,08/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +61573,70755,64153,PRETRIAL,Johnson,Dextervanness,J,Male,African-American,08/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +61573,70755,64153,PRETRIAL,Johnson,Dextervanness,J,Male,African-American,08/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61585,70773,64170,Probation,JAROCKI,JENNIFER,NULL,Female,Caucasian,05/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/28/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +61585,70773,64170,Probation,JAROCKI,JENNIFER,NULL,Female,Caucasian,05/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/28/14 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +61585,70773,64170,Probation,JAROCKI,JENNIFER,NULL,Female,Caucasian,05/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61595,70785,64181,Probation,Walker,Gregory,NULL,Male,African-American,05/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +61595,70785,64181,Probation,Walker,Gregory,NULL,Male,African-American,05/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +61595,70785,64181,Probation,Walker,Gregory,NULL,Male,African-American,05/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61584,70771,64168,DRRD,Black,Anthony,None,Male,African-American,04/11/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +61584,70771,64168,DRRD,Black,Anthony,None,Male,African-American,04/11/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-0.44,4,Low,New,1,0 +61584,70771,64168,DRRD,Black,Anthony,None,Male,African-American,04/11/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61591,70778,64175,Probation,Ferrara,Luigino,NULL,Male,Caucasian,05/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +61591,70778,64175,Probation,Ferrara,Luigino,NULL,Male,Caucasian,05/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +61591,70778,64175,Probation,Ferrara,Luigino,NULL,Male,Caucasian,05/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +24390,70757,64154,PRETRIAL,MORGAN,SHAWN,P,Male,Caucasian,09/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/28/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +24390,70757,64154,PRETRIAL,MORGAN,SHAWN,P,Male,Caucasian,09/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/28/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +24390,70757,64154,PRETRIAL,MORGAN,SHAWN,P,Male,Caucasian,09/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61597,70787,64183,PRETRIAL,CATALA,ESTHER,NULL,Female,Caucasian,11/30/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +61597,70787,64183,PRETRIAL,CATALA,ESTHER,NULL,Female,Caucasian,11/30/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +61597,70787,64183,PRETRIAL,CATALA,ESTHER,NULL,Female,Caucasian,11/30/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61580,70766,64163,PRETRIAL,john,matthew,NULL,Male,Caucasian,01/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +61580,70766,64163,PRETRIAL,john,matthew,NULL,Male,Caucasian,01/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +61580,70766,64163,PRETRIAL,john,matthew,NULL,Male,Caucasian,01/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55672,70784,57558,PRETRIAL,Laflamme,Ellan,NULL,Female,Caucasian,08/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,Copy,1,0 +55672,70784,57558,PRETRIAL,Laflamme,Ellan,NULL,Female,Caucasian,08/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,Copy,1,0 +55672,70784,57558,PRETRIAL,Laflamme,Ellan,NULL,Female,Caucasian,08/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +54111,70758,64155,PRETRIAL,Ruddock,Shaka,NULL,Male,African-American,02/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +54111,70758,64155,PRETRIAL,Ruddock,Shaka,NULL,Male,African-American,02/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +54111,70758,64155,PRETRIAL,Ruddock,Shaka,NULL,Male,African-American,02/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +38933,70792,64188,PRETRIAL,Laferlita,John,NULL,Male,Caucasian,10/09/38,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-4.72,1,Low,New,1,0 +38933,70792,64188,PRETRIAL,Laferlita,John,NULL,Male,Caucasian,10/09/38,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-2.92,1,Low,New,1,0 +38933,70792,64188,PRETRIAL,Laferlita,John,NULL,Male,Caucasian,10/09/38,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55903,70779,64176,Probation,GOINS,TYNESHA,NULL,Female,African-American,08/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +55903,70779,64176,Probation,GOINS,TYNESHA,NULL,Female,African-American,08/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +55903,70779,64176,Probation,GOINS,TYNESHA,NULL,Female,African-American,08/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61587,70774,64171,PRETRIAL,Ramsey,Jermaine,NULL,Male,African-American,11/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +61587,70774,64171,PRETRIAL,Ramsey,Jermaine,NULL,Male,African-American,11/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,4,High,8,Risk of Recidivism,1.08,10,High,New,1,0 +61587,70774,64171,PRETRIAL,Ramsey,Jermaine,NULL,Male,African-American,11/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61589,70776,64173,PRETRIAL,Bueno,Joannery,NULL,Male,Caucasian,03/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +61589,70776,64173,PRETRIAL,Bueno,Joannery,NULL,Male,Caucasian,03/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +61589,70776,64173,PRETRIAL,Bueno,Joannery,NULL,Male,Caucasian,03/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61575,70761,64158,PRETRIAL,Mims,Tommie,Earl,Male,African-American,02/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +61575,70761,64158,PRETRIAL,Mims,Tommie,Earl,Male,African-American,02/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +61575,70761,64158,PRETRIAL,Mims,Tommie,Earl,Male,African-American,02/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,2/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +42658,70789,64185,PRETRIAL,Enck,Michael,NULL,Male,Caucasian,04/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.08,8,High,New,1,0 +42658,70789,64185,PRETRIAL,Enck,Michael,NULL,Male,Caucasian,04/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +42658,70789,64185,PRETRIAL,Enck,Michael,NULL,Male,Caucasian,04/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,2/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +61582,70768,64165,Probation,FOXWORTH,FREDRICK,NULL,Male,African-American,12/15/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/28/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +61582,70768,64165,Probation,FOXWORTH,FREDRICK,NULL,Male,African-American,12/15/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/28/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +61582,70768,64165,Probation,FOXWORTH,FREDRICK,NULL,Male,African-American,12/15/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61594,70782,64179,PRETRIAL,Spalliero,Anthony,NULL,Male,Caucasian,02/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +61594,70782,64179,PRETRIAL,Spalliero,Anthony,NULL,Male,Caucasian,02/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +61594,70782,64179,PRETRIAL,Spalliero,Anthony,NULL,Male,Caucasian,02/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,2/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +13550,70795,12948,PRETRIAL,KEEL,ERIC,NULL,Male,African-American,11/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,Copy,1,0 +13550,70795,12948,PRETRIAL,KEEL,ERIC,NULL,Male,African-American,11/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,Copy,1,0 +13550,70795,12948,PRETRIAL,KEEL,ERIC,NULL,Male,African-American,11/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +61603,70797,64191,PRETRIAL,Russell,Ben,NULL,Male,African-American,08/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +61603,70797,64191,PRETRIAL,Russell,Ben,NULL,Male,African-American,08/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +61603,70797,64191,PRETRIAL,Russell,Ben,NULL,Male,African-American,08/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +21475,70799,64193,PRETRIAL,Gibson,Patricia,Ann,Female,African-American,01/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,2,Medium,7,Risk of Violence,-2.78,2,Low,New,1,0 +21475,70799,64193,PRETRIAL,Gibson,Patricia,Ann,Female,African-American,01/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +21475,70799,64193,PRETRIAL,Gibson,Patricia,Ann,Female,African-American,01/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61602,70794,64190,PRETRIAL,Woodberry,Tony,NULL,Male,African-American,12/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,2,Medium,7,Risk of Violence,-2.72,2,Low,New,1,0 +61602,70794,64190,PRETRIAL,Woodberry,Tony,NULL,Male,African-American,12/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +61602,70794,64190,PRETRIAL,Woodberry,Tony,NULL,Male,African-American,12/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61601,70793,64189,PRETRIAL,Jean-Baptiste,Lucane,NULL,Male,Other,09/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/1/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +61601,70793,64189,PRETRIAL,Jean-Baptiste,Lucane,NULL,Male,Other,09/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/1/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +61601,70793,64189,PRETRIAL,Jean-Baptiste,Lucane,NULL,Male,Other,09/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61605,70800,64194,PRETRIAL,etienne,evintz,NULL,Male,African-American,08/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.78,2,Low,New,1,0 +61605,70800,64194,PRETRIAL,etienne,evintz,NULL,Male,African-American,08/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +61605,70800,64194,PRETRIAL,etienne,evintz,NULL,Male,African-American,08/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61616,70802,64196,PRETRIAL,clarington,hamilton,NULL,Male,African-American,06/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +61616,70802,64196,PRETRIAL,clarington,hamilton,NULL,Male,African-American,06/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +61616,70802,64196,PRETRIAL,clarington,hamilton,NULL,Male,African-American,06/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61604,70798,64192,PRETRIAL,Howard,Norrissie,NULL,Female,African-American,10/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/1/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +61604,70798,64192,PRETRIAL,Howard,Norrissie,NULL,Female,African-American,10/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/1/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +61604,70798,64192,PRETRIAL,Howard,Norrissie,NULL,Female,African-American,10/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/1/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +22340,70796,21505,PRETRIAL,CARWELL,JOSEPH,J,Male,African-American,02/10/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,Copy,1,0 +22340,70796,21505,PRETRIAL,CARWELL,JOSEPH,J,Male,African-American,02/10/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,Copy,1,0 +22340,70796,21505,PRETRIAL,CARWELL,JOSEPH,J,Male,African-American,02/10/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +61606,70801,64195,PRETRIAL,Sanchez,Pedro,Alfonso,Male,Caucasian,07/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +61606,70801,64195,PRETRIAL,Sanchez,Pedro,Alfonso,Male,Caucasian,07/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +61606,70801,64195,PRETRIAL,Sanchez,Pedro,Alfonso,Male,Caucasian,07/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/1/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +61623,70809,64203,PRETRIAL,Smith,John,NULL,Male,Caucasian,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +61623,70809,64203,PRETRIAL,Smith,John,NULL,Male,Caucasian,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +61623,70809,64203,PRETRIAL,Smith,John,NULL,Male,Caucasian,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61631,70817,64211,PRETRIAL,Mannino,Paolo,NULL,Male,Caucasian,03/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +61631,70817,64211,PRETRIAL,Mannino,Paolo,NULL,Male,Caucasian,03/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +61631,70817,64211,PRETRIAL,Mannino,Paolo,NULL,Male,Caucasian,03/08/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61619,70804,64198,PRETRIAL,MALCOLM,VANESSA,T,Female,African-American,05/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/2/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +61619,70804,64198,PRETRIAL,MALCOLM,VANESSA,T,Female,African-American,05/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/2/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +61619,70804,64198,PRETRIAL,MALCOLM,VANESSA,T,Female,African-American,05/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61626,70812,64206,PRETRIAL,LEATH,JARVON,T,Male,African-American,06/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +61626,70812,64206,PRETRIAL,LEATH,JARVON,T,Male,African-American,06/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,4,High,8,Risk of Recidivism,0.97,10,High,New,1,0 +61626,70812,64206,PRETRIAL,LEATH,JARVON,T,Male,African-American,06/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61630,70816,64210,PRETRIAL,Zapata,Silvio,NULL,Male,Other,11/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/2/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +61630,70816,64210,PRETRIAL,Zapata,Silvio,NULL,Male,Other,11/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/2/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +61630,70816,64210,PRETRIAL,Zapata,Silvio,NULL,Male,Other,11/29/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61633,70819,64213,PRETRIAL,greguer,odige,NULL,Male,African-American,10/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.09,8,High,New,1,0 +61633,70819,64213,PRETRIAL,greguer,odige,NULL,Male,African-American,10/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +61633,70819,64213,PRETRIAL,greguer,odige,NULL,Male,African-American,10/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61621,70807,64201,PRETRIAL,LOVINSKY,WALKER,NULL,Male,African-American,04/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +61621,70807,64201,PRETRIAL,LOVINSKY,WALKER,NULL,Male,African-American,04/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +61621,70807,64201,PRETRIAL,LOVINSKY,WALKER,NULL,Male,African-American,04/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61628,70814,64208,PRETRIAL,JAHMEKIE,JAMES,NULL,Female,Other,06/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/2/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +61628,70814,64208,PRETRIAL,JAHMEKIE,JAMES,NULL,Female,Other,06/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +61628,70814,64208,PRETRIAL,JAHMEKIE,JAMES,NULL,Female,Other,06/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/2/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61625,70811,64205,PRETRIAL,Harris,Frank,NULL,Male,African-American,10/28/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.8,2,Low,New,1,0 +61625,70811,64205,PRETRIAL,Harris,Frank,NULL,Male,African-American,10/28/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +61625,70811,64205,PRETRIAL,Harris,Frank,NULL,Male,African-American,10/28/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61629,70815,64209,PRETRIAL,Huynh,Phat,NULL,Male,Asian,09/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/2/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +61629,70815,64209,PRETRIAL,Huynh,Phat,NULL,Male,Asian,09/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/2/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +61629,70815,64209,PRETRIAL,Huynh,Phat,NULL,Male,Asian,09/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61622,70808,64202,PRETRIAL,WALKER,DARRELL,LEMONT,Male,African-American,09/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +61622,70808,64202,PRETRIAL,WALKER,DARRELL,LEMONT,Male,African-American,09/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +61622,70808,64202,PRETRIAL,WALKER,DARRELL,LEMONT,Male,African-American,09/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +37356,70806,64200,PRETRIAL,Jackson,Brandon,NULL,Male,African-American,02/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +37356,70806,64200,PRETRIAL,Jackson,Brandon,NULL,Male,African-American,02/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +37356,70806,64200,PRETRIAL,Jackson,Brandon,NULL,Male,African-American,02/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61624,70810,64204,PRETRIAL,GRAY,JOSEPH,NULL,Male,African-American,04/19/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +61624,70810,64204,PRETRIAL,GRAY,JOSEPH,NULL,Male,African-American,04/19/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +61624,70810,64204,PRETRIAL,GRAY,JOSEPH,NULL,Male,African-American,04/19/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61632,70818,64212,PRETRIAL,Rangelsantana,Jonathon,NULL,Male,Caucasian,11/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +61632,70818,64212,PRETRIAL,Rangelsantana,Jonathon,NULL,Male,Caucasian,11/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +61632,70818,64212,PRETRIAL,Rangelsantana,Jonathon,NULL,Male,Caucasian,11/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61617,70803,64197,PRETRIAL,Rentas,John,Michael,Male,Caucasian,09/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +61617,70803,64197,PRETRIAL,Rentas,John,Michael,Male,Caucasian,09/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +61617,70803,64197,PRETRIAL,Rentas,John,Michael,Male,Caucasian,09/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61627,70813,64207,PRETRIAL,Chang-Scott,Tracee,NULL,Male,African-American,05/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +61627,70813,64207,PRETRIAL,Chang-Scott,Tracee,NULL,Male,African-American,05/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +61627,70813,64207,PRETRIAL,Chang-Scott,Tracee,NULL,Male,African-American,05/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61620,70805,64199,PRETRIAL,ROBERSON,STEPHON,LEE,Male,African-American,12/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +61620,70805,64199,PRETRIAL,ROBERSON,STEPHON,LEE,Male,African-American,12/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +61620,70805,64199,PRETRIAL,ROBERSON,STEPHON,LEE,Male,African-American,12/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/2/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61663,70855,64244,PRETRIAL,george,wanglee,NULL,Male,African-American,01/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +61663,70855,64244,PRETRIAL,george,wanglee,NULL,Male,African-American,01/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +61663,70855,64244,PRETRIAL,george,wanglee,NULL,Male,African-American,01/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +44921,70852,64241,Probation,whitehead,travis,NULL,Male,African-American,05/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +44921,70852,64241,Probation,whitehead,travis,NULL,Male,African-American,05/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +44921,70852,64241,Probation,whitehead,travis,NULL,Male,African-American,05/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +2300,70847,2020,Probation,Michel,Fabensky,NULL,Male,African-American,01/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,Copy,1,0 +2300,70847,2020,Probation,Michel,Fabensky,NULL,Male,African-American,01/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,Copy,1,0 +2300,70847,2020,Probation,Michel,Fabensky,NULL,Male,African-American,01/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +61639,70826,64219,PRETRIAL,CONTRERAS,HECTOR,NULL,Male,Hispanic,02/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +61639,70826,64219,PRETRIAL,CONTRERAS,HECTOR,NULL,Male,Hispanic,02/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +61639,70826,64219,PRETRIAL,CONTRERAS,HECTOR,NULL,Male,Hispanic,02/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61651,70839,64231,PRETRIAL,ANDERSON,LISA,M,Female,Other,10/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/3/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +61651,70839,64231,PRETRIAL,ANDERSON,LISA,M,Female,Other,10/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +61651,70839,64231,PRETRIAL,ANDERSON,LISA,M,Female,Other,10/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61676,70868,64257,Probation,Rosenkranz,Barbara,Sharyn,Female,Caucasian,02/23/45,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,3/3/14 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +61676,70868,64257,Probation,Rosenkranz,Barbara,Sharyn,Female,Caucasian,02/23/45,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,3/3/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +61676,70868,64257,Probation,Rosenkranz,Barbara,Sharyn,Female,Caucasian,02/23/45,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +46334,70831,46735,Probation,Bostick,Tara,NULL,Female,African-American,06/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,2,Medium,7,Risk of Violence,-2.88,2,Low,Copy,1,0 +46334,70831,46735,Probation,Bostick,Tara,NULL,Female,African-American,06/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,Copy,1,0 +46334,70831,46735,Probation,Bostick,Tara,NULL,Female,African-American,06/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +61642,70829,64222,PRETRIAL,Mirucki,Michael,NULL,Male,Caucasian,08/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/3/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +61642,70829,64222,PRETRIAL,Mirucki,Michael,NULL,Male,Caucasian,08/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/3/14 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +61642,70829,64222,PRETRIAL,Mirucki,Michael,NULL,Male,Caucasian,08/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61648,70836,64228,Probation,KAMRUZZAMAN,AKM,NULL,Male,Asian,01/01/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/3/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +61648,70836,64228,Probation,KAMRUZZAMAN,AKM,NULL,Male,Asian,01/01/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +61648,70836,64228,Probation,KAMRUZZAMAN,AKM,NULL,Male,Asian,01/01/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61640,70827,64220,PRETRIAL,GONZALEZ,UBERENE,NULL,Male,Caucasian,01/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/3/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +61640,70827,64220,PRETRIAL,GONZALEZ,UBERENE,NULL,Male,Caucasian,01/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +61640,70827,64220,PRETRIAL,GONZALEZ,UBERENE,NULL,Male,Caucasian,01/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61665,70857,64246,PRETRIAL,RAMOS,ERICA,NULL,Female,Caucasian,07/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/3/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +61665,70857,64246,PRETRIAL,RAMOS,ERICA,NULL,Female,Caucasian,07/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.53,2,Low,New,1,0 +61665,70857,64246,PRETRIAL,RAMOS,ERICA,NULL,Female,Caucasian,07/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +10634,70850,10160,PRETRIAL,WILLIAMS,JASON,J,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,4,High,7,Risk of Violence,-0.93,9,High,Copy,1,0 +10634,70850,10160,PRETRIAL,WILLIAMS,JASON,J,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,4,High,8,Risk of Recidivism,0.83,10,High,Copy,1,0 +10634,70850,10160,PRETRIAL,WILLIAMS,JASON,J,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +61673,70864,64253,Probation,SCHULTZ,ROBERT,CHARLES,Male,Caucasian,01/08/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/3/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +61673,70864,64253,Probation,SCHULTZ,ROBERT,CHARLES,Male,Caucasian,01/08/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/3/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +61673,70864,64253,Probation,SCHULTZ,ROBERT,CHARLES,Male,Caucasian,01/08/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61678,70871,64259,PRETRIAL,Webb,Joseph,NULL,Male,Caucasian,09/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/3/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +61678,70871,64259,PRETRIAL,Webb,Joseph,NULL,Male,Caucasian,09/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +61678,70871,64259,PRETRIAL,Webb,Joseph,NULL,Male,Caucasian,09/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61675,70866,64255,Probation,Rojas,Giovanni,NULL,Male,Hispanic,09/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +61675,70866,64255,Probation,Rojas,Giovanni,NULL,Male,Hispanic,09/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +61675,70866,64255,Probation,Rojas,Giovanni,NULL,Male,Hispanic,09/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61634,70820,64214,PRETRIAL,Williams,Onique,NULL,Male,Other,06/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +61634,70820,64214,PRETRIAL,Williams,Onique,NULL,Male,Other,06/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +61634,70820,64214,PRETRIAL,Williams,Onique,NULL,Male,Other,06/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61656,70845,64236,Probation,VALLON,CARL,HENRY,Male,African-American,07/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +61656,70845,64236,Probation,VALLON,CARL,HENRY,Male,African-American,07/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +61656,70845,64236,Probation,VALLON,CARL,HENRY,Male,African-American,07/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61637,70824,64217,PRETRIAL,Regidor,Marcial,NULL,Male,Caucasian,12/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/3/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +61637,70824,64217,PRETRIAL,Regidor,Marcial,NULL,Male,Caucasian,12/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +61637,70824,64217,PRETRIAL,Regidor,Marcial,NULL,Male,Caucasian,12/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61652,70841,64232,Probation,garcia,artemio,NULL,Male,Hispanic,12/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/3/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +61652,70841,64232,Probation,garcia,artemio,NULL,Male,Hispanic,12/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/3/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +61652,70841,64232,Probation,garcia,artemio,NULL,Male,Hispanic,12/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61635,70821,64215,PRETRIAL,DILLMAN,KEITH,NULL,Male,Caucasian,11/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +61635,70821,64215,PRETRIAL,DILLMAN,KEITH,NULL,Male,Caucasian,11/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +61635,70821,64215,PRETRIAL,DILLMAN,KEITH,NULL,Male,Caucasian,11/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61641,70828,64221,PRETRIAL,GARCIA,NORBERTO,NULL,Male,Caucasian,11/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +61641,70828,64221,PRETRIAL,GARCIA,NORBERTO,NULL,Male,Caucasian,11/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +61641,70828,64221,PRETRIAL,GARCIA,NORBERTO,NULL,Male,Caucasian,11/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +11779,70835,64227,Probation,bennett,jeffrey,scott,Male,Caucasian,05/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +11779,70835,64227,Probation,bennett,jeffrey,scott,Male,Caucasian,05/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +11779,70835,64227,Probation,bennett,jeffrey,scott,Male,Caucasian,05/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61658,70849,64239,Probation,Castro,Wilson,Luis,Male,Hispanic,03/27/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/3/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +61658,70849,64239,Probation,Castro,Wilson,Luis,Male,Hispanic,03/27/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/3/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +61658,70849,64239,Probation,Castro,Wilson,Luis,Male,Hispanic,03/27/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61655,70844,64235,PRETRIAL,Villalobos,Norma,Rose,Female,Hispanic,02/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/3/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +61655,70844,64235,PRETRIAL,Villalobos,Norma,Rose,Female,Hispanic,02/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +61655,70844,64235,PRETRIAL,Villalobos,Norma,Rose,Female,Hispanic,02/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61672,70863,64252,PRETRIAL,KNOLL,JUSTIN,NULL,Male,Caucasian,02/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +61672,70863,64252,PRETRIAL,KNOLL,JUSTIN,NULL,Male,Caucasian,02/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +61672,70863,64252,PRETRIAL,KNOLL,JUSTIN,NULL,Male,Caucasian,02/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61666,70858,64247,Probation,Santiago,Christopher,Mark,Male,Hispanic,04/09/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +61666,70858,64247,Probation,Santiago,Christopher,Mark,Male,Hispanic,04/09/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +61666,70858,64247,Probation,Santiago,Christopher,Mark,Male,Hispanic,04/09/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61662,70854,64243,Probation,Naughton,Michael,NULL,Male,Caucasian,08/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +61662,70854,64243,Probation,Naughton,Michael,NULL,Male,Caucasian,08/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +61662,70854,64243,Probation,Naughton,Michael,NULL,Male,Caucasian,08/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61646,70833,64225,PRETRIAL,Gilles,Pascal,NULL,Male,African-American,12/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +61646,70833,64225,PRETRIAL,Gilles,Pascal,NULL,Male,African-American,12/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +61646,70833,64225,PRETRIAL,Gilles,Pascal,NULL,Male,African-American,12/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61636,70823,64216,PRETRIAL,Massicot,Marcus,NULL,Male,African-American,01/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +61636,70823,64216,PRETRIAL,Massicot,Marcus,NULL,Male,African-American,01/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +61636,70823,64216,PRETRIAL,Massicot,Marcus,NULL,Male,African-American,01/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61649,70837,64229,PRETRIAL,Wright,Euriette,NULL,Female,African-American,07/14/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-4.33,1,Low,New,1,0 +61649,70837,64229,PRETRIAL,Wright,Euriette,NULL,Female,African-American,07/14/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-2.74,1,Low,New,1,0 +61649,70837,64229,PRETRIAL,Wright,Euriette,NULL,Female,African-American,07/14/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61650,70838,64230,Probation,WILLIAMS,PHILLIPE,CLAUDE,Male,Caucasian,05/30/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +61650,70838,64230,Probation,WILLIAMS,PHILLIPE,CLAUDE,Male,Caucasian,05/30/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +61650,70838,64230,Probation,WILLIAMS,PHILLIPE,CLAUDE,Male,Caucasian,05/30/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61669,70861,64250,Probation,DUKES,ELON,NULL,Female,African-American,09/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +61669,70861,64250,Probation,DUKES,ELON,NULL,Female,African-American,09/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +61669,70861,64250,Probation,DUKES,ELON,NULL,Female,African-American,09/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61638,70825,64218,PRETRIAL,FABIYI,AKIN,NULL,Male,African-American,02/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +61638,70825,64218,PRETRIAL,FABIYI,AKIN,NULL,Male,African-American,02/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +61638,70825,64218,PRETRIAL,FABIYI,AKIN,NULL,Male,African-American,02/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61667,70859,64248,Probation,cullen,moira,NULL,Female,Caucasian,01/28/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/3/14 0:00,1,Low,7,Risk of Violence,-4.5,1,Low,New,1,0 +61667,70859,64248,Probation,cullen,moira,NULL,Female,Caucasian,01/28/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/3/14 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +61667,70859,64248,Probation,cullen,moira,NULL,Female,Caucasian,01/28/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61644,70832,64224,PRETRIAL,JACKSON,JACOBIE,NULL,Male,African-American,06/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +61644,70832,64224,PRETRIAL,JACKSON,JACOBIE,NULL,Male,African-American,06/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +61644,70832,64224,PRETRIAL,JACKSON,JACOBIE,NULL,Male,African-American,06/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/3/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +43636,70867,64256,PRETRIAL,Beauzieux,Yvena,NULL,Female,African-American,01/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +43636,70867,64256,PRETRIAL,Beauzieux,Yvena,NULL,Female,African-American,01/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +43636,70867,64256,PRETRIAL,Beauzieux,Yvena,NULL,Female,African-American,01/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61660,70853,64242,PRETRIAL,Mims,Derrick,NULL,Male,African-American,03/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,New,1,0 +61660,70853,64242,PRETRIAL,Mims,Derrick,NULL,Male,African-American,03/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +61660,70853,64242,PRETRIAL,Mims,Derrick,NULL,Male,African-American,03/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61654,70843,64234,Probation,Campbell,Scott,NULL,Male,Caucasian,08/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +61654,70843,64234,Probation,Campbell,Scott,NULL,Male,Caucasian,08/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +61654,70843,64234,Probation,Campbell,Scott,NULL,Male,Caucasian,08/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58146,70822,61317,PRETRIAL,Tenney,Tyler,NULL,Male,African-American,07/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,Copy,1,0 +58146,70822,61317,PRETRIAL,Tenney,Tyler,NULL,Male,African-American,07/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,Copy,1,0 +58146,70822,61317,PRETRIAL,Tenney,Tyler,NULL,Male,African-American,07/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +61664,70856,64245,PRETRIAL,thompson,scott,NULL,Male,Caucasian,01/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/3/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +61664,70856,64245,PRETRIAL,thompson,scott,NULL,Male,Caucasian,01/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +61664,70856,64245,PRETRIAL,thompson,scott,NULL,Male,Caucasian,01/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/3/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +61659,70851,64240,Probation,blanton,timmy,NULL,Male,Caucasian,10/08/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +61659,70851,64240,Probation,blanton,timmy,NULL,Male,Caucasian,10/08/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +61659,70851,64240,Probation,blanton,timmy,NULL,Male,Caucasian,10/08/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61677,70869,64258,Probation,GILBERT,JAMES,R,Male,African-American,08/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +61677,70869,64258,Probation,GILBERT,JAMES,R,Male,African-American,08/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +61677,70869,64258,Probation,GILBERT,JAMES,R,Male,African-American,08/18/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61643,70830,64223,PRETRIAL,HOPSON,MALIK,NULL,Female,African-American,11/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/3/14 0:00,4,High,7,Risk of Violence,-0.54,10,High,New,1,0 +61643,70830,64223,PRETRIAL,HOPSON,MALIK,NULL,Female,African-American,11/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/3/14 0:00,4,High,8,Risk of Recidivism,0.88,10,High,New,1,0 +61643,70830,64223,PRETRIAL,HOPSON,MALIK,NULL,Female,African-American,11/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/3/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53076,70848,64238,Probation,Davey,Mark,S,Male,Caucasian,06/28/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +53076,70848,64238,Probation,Davey,Mark,S,Male,Caucasian,06/28/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +53076,70848,64238,Probation,Davey,Mark,S,Male,Caucasian,06/28/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/3/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61698,70898,64281,Probation,JEWEL,RANDY,M,Male,African-American,08/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.7,2,Low,New,1,0 +61698,70898,64281,Probation,JEWEL,RANDY,M,Male,African-American,08/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +61698,70898,64281,Probation,JEWEL,RANDY,M,Male,African-American,08/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +48973,70916,64297,PRETRIAL,Harmon,Matthew,NULL,Male,Caucasian,05/02/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +48973,70916,64297,PRETRIAL,Harmon,Matthew,NULL,Male,Caucasian,05/02/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +48973,70916,64297,PRETRIAL,Harmon,Matthew,NULL,Male,Caucasian,05/02/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61710,70919,64299,Probation,Orlando,Zachary,NULL,Male,Caucasian,02/17/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/4/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +61710,70919,64299,Probation,Orlando,Zachary,NULL,Male,Caucasian,02/17/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +61710,70919,64299,Probation,Orlando,Zachary,NULL,Male,Caucasian,02/17/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/4/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61706,70911,64292,Probation,GILLIAM,BOBBY,RAY,Male,Caucasian,12/01/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.58,2,Low,New,1,0 +61706,70911,64292,Probation,GILLIAM,BOBBY,RAY,Male,Caucasian,12/01/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.7,10,High,New,1,0 +61706,70911,64292,Probation,GILLIAM,BOBBY,RAY,Male,Caucasian,12/01/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +61603,70877,64265,PRETRIAL,Russell,Ben,NULL,Male,African-American,08/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +61603,70877,64265,PRETRIAL,Russell,Ben,NULL,Male,African-American,08/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +61603,70877,64265,PRETRIAL,Russell,Ben,NULL,Male,African-American,08/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61702,70903,64286,Probation,Calveiro,Eric,NULL,Male,Hispanic,12/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +61702,70903,64286,Probation,Calveiro,Eric,NULL,Male,Hispanic,12/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +61702,70903,64286,Probation,Calveiro,Eric,NULL,Male,Hispanic,12/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61686,70882,64270,PRETRIAL,McQueen,Arthur,NULL,Male,African-American,08/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +61686,70882,64270,PRETRIAL,McQueen,Arthur,NULL,Male,African-American,08/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +61686,70882,64270,PRETRIAL,McQueen,Arthur,NULL,Male,African-American,08/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61680,70874,64262,PRETRIAL,Vasquez,Carlos,Bienvenido,Male,Hispanic,11/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +61680,70874,64262,PRETRIAL,Vasquez,Carlos,Bienvenido,Male,Hispanic,11/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +61680,70874,64262,PRETRIAL,Vasquez,Carlos,Bienvenido,Male,Hispanic,11/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61704,70905,64288,Probation,PARLA,CHARISEL,A,Male,Hispanic,06/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +61704,70905,64288,Probation,PARLA,CHARISEL,A,Male,Hispanic,06/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +61704,70905,64288,Probation,PARLA,CHARISEL,A,Male,Hispanic,06/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61688,70884,64272,PRETRIAL,Farley,Leroy,NULL,Male,African-American,07/26/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,2,Medium,7,Risk of Violence,-3.15,1,Low,New,1,0 +61688,70884,64272,PRETRIAL,Farley,Leroy,NULL,Male,African-American,07/26/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +61688,70884,64272,PRETRIAL,Farley,Leroy,NULL,Male,African-American,07/26/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61684,70879,64267,PRETRIAL,WILSON,LEON,NULL,Male,African-American,06/06/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/4/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +61684,70879,64267,PRETRIAL,WILSON,LEON,NULL,Male,African-American,06/06/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/4/14 0:00,1,Low,8,Risk of Recidivism,-2.56,1,Low,New,1,0 +61684,70879,64267,PRETRIAL,WILSON,LEON,NULL,Male,African-American,06/06/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60735,70888,63205,Probation,Davis,Bradley,NULL,Male,Caucasian,08/23/70,17,All Scales,Intake,English,Conditional Release,Probation,Married,3/4/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +60735,70888,63205,Probation,Davis,Bradley,NULL,Male,Caucasian,08/23/70,17,All Scales,Intake,English,Conditional Release,Probation,Married,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +60735,70888,63205,Probation,Davis,Bradley,NULL,Male,Caucasian,08/23/70,17,All Scales,Intake,English,Conditional Release,Probation,Married,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,23,4,Low,New,1,0 +61681,70875,64263,PRETRIAL,Mills,Delvin,NULL,Male,African-American,12/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +61681,70875,64263,PRETRIAL,Mills,Delvin,NULL,Male,African-American,12/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +61681,70875,64263,PRETRIAL,Mills,Delvin,NULL,Male,African-American,12/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +47081,70872,64260,PRETRIAL,DEY,ROBERT,VINCENT,Male,Caucasian,07/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +47081,70872,64260,PRETRIAL,DEY,ROBERT,VINCENT,Male,Caucasian,07/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +47081,70872,64260,PRETRIAL,DEY,ROBERT,VINCENT,Male,Caucasian,07/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61692,70891,64276,PRETRIAL,Sanchez,John,NULL,Male,Hispanic,02/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +61692,70891,64276,PRETRIAL,Sanchez,John,NULL,Male,Hispanic,02/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +61692,70891,64276,PRETRIAL,Sanchez,John,NULL,Male,Hispanic,02/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61694,70893,64278,Probation,Dalencour,Charles,Edwige,Male,African-American,03/14/81,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/4/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +61694,70893,64278,Probation,Dalencour,Charles,Edwige,Male,African-American,03/14/81,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +61694,70893,64278,Probation,Dalencour,Charles,Edwige,Male,African-American,03/14/81,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61700,70900,64283,Probation,Deer,Ryan,NULL,Male,African-American,11/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +61700,70900,64283,Probation,Deer,Ryan,NULL,Male,African-American,11/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +61700,70900,64283,Probation,Deer,Ryan,NULL,Male,African-American,11/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61708,70914,64295,Probation,Streicher,Marsha,NULL,Female,Caucasian,01/31/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +61708,70914,64295,Probation,Streicher,Marsha,NULL,Female,Caucasian,01/31/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +61708,70914,64295,Probation,Streicher,Marsha,NULL,Female,Caucasian,01/31/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61693,70892,64277,Probation,williams,gregory,NULL,Male,Caucasian,03/25/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/4/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +61693,70892,64277,Probation,williams,gregory,NULL,Male,Caucasian,03/25/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +61693,70892,64277,Probation,williams,gregory,NULL,Male,Caucasian,03/25/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61705,70913,64294,Probation,Hotte,Michael,NULL,Male,Caucasian,10/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +61705,70913,64294,Probation,Hotte,Michael,NULL,Male,Caucasian,10/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +61705,70913,64294,Probation,Hotte,Michael,NULL,Male,Caucasian,10/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +37977,70922,64301,PRETRIAL,Coleman,Marquis,NULL,Male,African-American,09/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +37977,70922,64301,PRETRIAL,Coleman,Marquis,NULL,Male,African-American,09/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +37977,70922,64301,PRETRIAL,Coleman,Marquis,NULL,Male,African-American,09/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61687,70883,64271,PRETRIAL,MONDESTIN,ROBERTSON,NULL,Male,African-American,11/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/14 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +61687,70883,64271,PRETRIAL,MONDESTIN,ROBERTSON,NULL,Male,African-American,11/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +61687,70883,64271,PRETRIAL,MONDESTIN,ROBERTSON,NULL,Male,African-American,11/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +48487,70901,64284,PRETRIAL,PAVLIK,SEANN,NULL,Male,Caucasian,09/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +48487,70901,64284,PRETRIAL,PAVLIK,SEANN,NULL,Male,Caucasian,09/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +48487,70901,64284,PRETRIAL,PAVLIK,SEANN,NULL,Male,Caucasian,09/03/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61685,70880,64268,PRETRIAL,Shokov,Sergi,NULL,Male,Caucasian,09/01/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +61685,70880,64268,PRETRIAL,Shokov,Sergi,NULL,Male,Caucasian,09/01/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +61685,70880,64268,PRETRIAL,Shokov,Sergi,NULL,Male,Caucasian,09/01/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61690,70887,64274,PRETRIAL,McGowan,Eddie,NULL,Male,African-American,10/14/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +61690,70887,64274,PRETRIAL,McGowan,Eddie,NULL,Male,African-American,10/14/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +61690,70887,64274,PRETRIAL,McGowan,Eddie,NULL,Male,African-American,10/14/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61683,70878,64266,PRETRIAL,Huey,Hodges,Al-Salaam,Female,African-American,10/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/14 0:00,2,Medium,7,Risk of Violence,-2.82,2,Low,New,1,0 +61683,70878,64266,PRETRIAL,Huey,Hodges,Al-Salaam,Female,African-American,10/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,New,1,0 +61683,70878,64266,PRETRIAL,Huey,Hodges,Al-Salaam,Female,African-American,10/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/4/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61689,70885,64273,PRETRIAL,Campbell,Cian,NULL,Male,African-American,07/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +61689,70885,64273,PRETRIAL,Campbell,Cian,NULL,Male,African-American,07/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +61689,70885,64273,PRETRIAL,Campbell,Cian,NULL,Male,African-American,07/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61699,70899,64282,Probation,Valeronalcantara,Armando,NULL,Male,Hispanic,04/13/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/4/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +61699,70899,64282,Probation,Valeronalcantara,Armando,NULL,Male,Hispanic,04/13/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +61699,70899,64282,Probation,Valeronalcantara,Armando,NULL,Male,Hispanic,04/13/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61209,70908,63733,PRETRIAL,LUMPKIN,MAURICE,NULL,Male,African-American,10/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,Copy,1,0 +61209,70908,63733,PRETRIAL,LUMPKIN,MAURICE,NULL,Male,African-American,10/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,Copy,1,0 +61209,70908,63733,PRETRIAL,LUMPKIN,MAURICE,NULL,Male,African-American,10/03/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +61182,70906,63699,PRETRIAL,Cordell,Christopher,Daniel,Male,Caucasian,04/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +61182,70906,63699,PRETRIAL,Cordell,Christopher,Daniel,Male,Caucasian,04/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,Copy,1,0 +61182,70906,63699,PRETRIAL,Cordell,Christopher,Daniel,Male,Caucasian,04/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +61695,70897,64279,PRETRIAL,Amabile,Marc,NULL,Male,Caucasian,09/14/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,Copy,1,0 +61695,70897,64279,PRETRIAL,Amabile,Marc,NULL,Male,Caucasian,09/14/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,Copy,1,0 +61695,70897,64279,PRETRIAL,Amabile,Marc,NULL,Male,Caucasian,09/14/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +61682,70876,64264,PRETRIAL,Pichardo,Willie,NULL,Male,Hispanic,12/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +61682,70876,64264,PRETRIAL,Pichardo,Willie,NULL,Male,Hispanic,12/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +61682,70876,64264,PRETRIAL,Pichardo,Willie,NULL,Male,Hispanic,12/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +9674,70910,64291,PRETRIAL,hansberry,anthony,NULL,Male,African-American,09/19/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/4/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +9674,70910,64291,PRETRIAL,hansberry,anthony,NULL,Male,African-American,09/19/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +9674,70910,64291,PRETRIAL,hansberry,anthony,NULL,Male,African-American,09/19/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/4/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +48334,70917,63303,Probation,spencer,cameron,NULL,Male,African-American,01/01/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +48334,70917,63303,Probation,spencer,cameron,NULL,Male,African-American,01/01/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,4,High,8,Risk of Recidivism,0.64,9,High,New,1,0 +48334,70917,63303,Probation,spencer,cameron,NULL,Male,African-American,01/01/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +19355,70918,64298,PRETRIAL,RICKARD,RAYMOND,NULL,Male,Caucasian,05/01/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/4/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +19355,70918,64298,PRETRIAL,RICKARD,RAYMOND,NULL,Male,Caucasian,05/01/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/4/14 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +19355,70918,64298,PRETRIAL,RICKARD,RAYMOND,NULL,Male,Caucasian,05/01/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61691,70889,64275,Probation,krizanic,christina,NULL,Female,Caucasian,06/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/4/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +61691,70889,64275,Probation,krizanic,christina,NULL,Female,Caucasian,06/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +61691,70889,64275,Probation,krizanic,christina,NULL,Female,Caucasian,06/30/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56288,70907,64289,Probation,marxmeyer,bryan,NULL,Male,Caucasian,03/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/4/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +56288,70907,64289,Probation,marxmeyer,bryan,NULL,Male,Caucasian,03/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +56288,70907,64289,Probation,marxmeyer,bryan,NULL,Male,Caucasian,03/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +60712,70881,64269,PRETRIAL,Laffite,Daniel,Jovon,Male,African-American,11/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +60712,70881,64269,PRETRIAL,Laffite,Daniel,Jovon,Male,African-American,11/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +60712,70881,64269,PRETRIAL,Laffite,Daniel,Jovon,Male,African-American,11/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +44774,70886,44918,PRETRIAL,Walden,Brandom,Jarod,Male,African-American,01/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/4/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,Copy,1,0 +44774,70886,44918,PRETRIAL,Walden,Brandom,Jarod,Male,African-American,01/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/4/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,Copy,1,0 +44774,70886,44918,PRETRIAL,Walden,Brandom,Jarod,Male,African-American,01/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +61709,70915,64296,Probation,allonce,jacques,NULL,Male,African-American,02/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +61709,70915,64296,Probation,allonce,jacques,NULL,Male,African-American,02/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.7,10,High,New,1,0 +61709,70915,64296,Probation,allonce,jacques,NULL,Male,African-American,02/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61711,70920,64300,Probation,moore,virginia,NULL,Female,Caucasian,08/23/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +61711,70920,64300,Probation,moore,virginia,NULL,Female,Caucasian,08/23/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +61711,70920,64300,Probation,moore,virginia,NULL,Female,Caucasian,08/23/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61701,70902,64285,Probation,bjordahl,joseph,NULL,Male,Caucasian,12/02/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/4/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +61701,70902,64285,Probation,bjordahl,joseph,NULL,Male,Caucasian,12/02/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/4/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +61701,70902,64285,Probation,bjordahl,joseph,NULL,Male,Caucasian,12/02/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61679,70873,64261,PRETRIAL,McClame,Raymond,NULL,Male,African-American,11/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +61679,70873,64261,PRETRIAL,McClame,Raymond,NULL,Male,African-American,11/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +61679,70873,64261,PRETRIAL,McClame,Raymond,NULL,Male,African-American,11/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61712,70923,64302,PRETRIAL,Jean,Angelo,NULL,Male,African-American,12/31/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +61712,70923,64302,PRETRIAL,Jean,Angelo,NULL,Male,African-American,12/31/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +61712,70923,64302,PRETRIAL,Jean,Angelo,NULL,Male,African-American,12/31/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61726,70933,64311,PRETRIAL,Wolter,Christopher,NULL,Male,Caucasian,05/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +61726,70933,64311,PRETRIAL,Wolter,Christopher,NULL,Male,Caucasian,05/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +61726,70933,64311,PRETRIAL,Wolter,Christopher,NULL,Male,Caucasian,05/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61741,70954,64331,PRETRIAL,ervin,danielle,NULL,Female,African-American,05/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +61741,70954,64331,PRETRIAL,ervin,danielle,NULL,Female,African-American,05/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +61741,70954,64331,PRETRIAL,ervin,danielle,NULL,Female,African-American,05/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61732,70941,64319,PRETRIAL,MOORE,TOMMY,NULL,Male,African-American,05/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +61732,70941,64319,PRETRIAL,MOORE,TOMMY,NULL,Male,African-American,05/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +61732,70941,64319,PRETRIAL,MOORE,TOMMY,NULL,Male,African-American,05/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +25706,70939,64317,PRETRIAL,Joseph,Aldophe,NULL,Male,African-American,09/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +25706,70939,64317,PRETRIAL,Joseph,Aldophe,NULL,Male,African-American,09/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +25706,70939,64317,PRETRIAL,Joseph,Aldophe,NULL,Male,African-American,09/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +28571,70946,64324,PRETRIAL,SABILLON,LUDWIG,NULL,Male,Caucasian,08/25/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/5/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +28571,70946,64324,PRETRIAL,SABILLON,LUDWIG,NULL,Male,Caucasian,08/25/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +28571,70946,64324,PRETRIAL,SABILLON,LUDWIG,NULL,Male,Caucasian,08/25/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +10651,70925,10177,Probation,Jones,Anthony,NULL,Male,African-American,08/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,4,High,7,Risk of Violence,-0.71,9,High,Copy,1,0 +10651,70925,10177,Probation,Jones,Anthony,NULL,Male,African-American,08/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,4,High,8,Risk of Recidivism,1.12,10,High,Copy,1,0 +10651,70925,10177,Probation,Jones,Anthony,NULL,Male,African-American,08/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +60766,70959,64335,PRETRIAL,HENDERSON,ANDREW,NULL,Male,African-American,12/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +60766,70959,64335,PRETRIAL,HENDERSON,ANDREW,NULL,Male,African-American,12/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +60766,70959,64335,PRETRIAL,HENDERSON,ANDREW,NULL,Male,African-American,12/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +18698,70931,64309,PRETRIAL,Boone,Brandon,NULL,Male,African-American,10/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +18698,70931,64309,PRETRIAL,Boone,Brandon,NULL,Male,African-American,10/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +18698,70931,64309,PRETRIAL,Boone,Brandon,NULL,Male,African-American,10/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +44717,70938,64316,PRETRIAL,Thomas,Andrew,NULL,Male,Caucasian,07/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +44717,70938,64316,PRETRIAL,Thomas,Andrew,NULL,Male,Caucasian,07/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +44717,70938,64316,PRETRIAL,Thomas,Andrew,NULL,Male,Caucasian,07/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61723,70929,64307,PRETRIAL,Roundtree,Kole,Douglas,Male,Caucasian,12/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +61723,70929,64307,PRETRIAL,Roundtree,Kole,Douglas,Male,Caucasian,12/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +61723,70929,64307,PRETRIAL,Roundtree,Kole,Douglas,Male,Caucasian,12/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61721,70927,64305,PRETRIAL,Purvis,Thomas,NULL,Male,Caucasian,11/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +61721,70927,64305,PRETRIAL,Purvis,Thomas,NULL,Male,Caucasian,11/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +61721,70927,64305,PRETRIAL,Purvis,Thomas,NULL,Male,Caucasian,11/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50508,70957,51543,Probation,FIGUEROA,JOSE,ANTONIO,Male,Hispanic,11/19/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/5/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,Copy,1,0 +50508,70957,51543,Probation,FIGUEROA,JOSE,ANTONIO,Male,Hispanic,11/19/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/5/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,Copy,1,0 +50508,70957,51543,Probation,FIGUEROA,JOSE,ANTONIO,Male,Hispanic,11/19/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +61729,70936,64314,Probation,Pergolini,Ronald,Anthony,Male,Caucasian,10/06/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +61729,70936,64314,Probation,Pergolini,Ronald,Anthony,Male,Caucasian,10/06/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +61729,70936,64314,Probation,Pergolini,Ronald,Anthony,Male,Caucasian,10/06/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +17624,70950,64328,Probation,hamann,richard,NULL,Male,Caucasian,12/20/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +17624,70950,64328,Probation,hamann,richard,NULL,Male,Caucasian,12/20/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +17624,70950,64328,Probation,hamann,richard,NULL,Male,Caucasian,12/20/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57730,70964,64340,Probation,Gayeski,Jennifer,NULL,Female,Caucasian,01/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +57730,70964,64340,Probation,Gayeski,Jennifer,NULL,Female,Caucasian,01/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +57730,70964,64340,Probation,Gayeski,Jennifer,NULL,Female,Caucasian,01/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61737,70948,64326,Probation,pearce,lucious,NULL,Male,African-American,01/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +61737,70948,64326,Probation,pearce,lucious,NULL,Male,African-American,01/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +61737,70948,64326,Probation,pearce,lucious,NULL,Male,African-American,01/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61742,70955,64332,Probation,Delisser,Christian,Lorcan,Male,African-American,01/16/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +61742,70955,64332,Probation,Delisser,Christian,Lorcan,Male,African-American,01/16/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +61742,70955,64332,Probation,Delisser,Christian,Lorcan,Male,African-American,01/16/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61727,70934,64312,Probation,Gonzalez Bermudez,Bennezza,NULL,Female,Hispanic,01/16/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +61727,70934,64312,Probation,Gonzalez Bermudez,Bennezza,NULL,Female,Hispanic,01/16/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +61727,70934,64312,Probation,Gonzalez Bermudez,Bennezza,NULL,Female,Hispanic,01/16/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +19078,70952,60045,PRETRIAL,Walquer,Eyzzaquirre,NULL,Male,African-American,12/13/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +19078,70952,60045,PRETRIAL,Walquer,Eyzzaquirre,NULL,Male,African-American,12/13/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-0.28,5,Medium,New,1,0 +19078,70952,60045,PRETRIAL,Walquer,Eyzzaquirre,NULL,Male,African-American,12/13/89,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +61722,70928,64306,PRETRIAL,Ireland,Robby,NULL,Male,African-American,02/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +61722,70928,64306,PRETRIAL,Ireland,Robby,NULL,Male,African-American,02/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,4,High,8,Risk of Recidivism,0.63,10,High,New,1,0 +61722,70928,64306,PRETRIAL,Ireland,Robby,NULL,Male,African-American,02/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61728,70935,64313,Probation,Kraskiewicz,Jason,NULL,Male,Caucasian,01/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/5/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +61728,70935,64313,Probation,Kraskiewicz,Jason,NULL,Male,Caucasian,01/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +61728,70935,64313,Probation,Kraskiewicz,Jason,NULL,Male,Caucasian,01/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61738,70949,64327,Probation,Contramaestre,Gustavo,NULL,Male,Hispanic,02/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +61738,70949,64327,Probation,Contramaestre,Gustavo,NULL,Male,Hispanic,02/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +61738,70949,64327,Probation,Contramaestre,Gustavo,NULL,Male,Hispanic,02/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61733,70942,64320,Probation,Barclay,Kaitlyn,NULL,Female,Caucasian,06/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +61733,70942,64320,Probation,Barclay,Kaitlyn,NULL,Female,Caucasian,06/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +61733,70942,64320,Probation,Barclay,Kaitlyn,NULL,Female,Caucasian,06/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +61734,70944,64322,PRETRIAL,RANDELL,JOHNNIE,NULL,Female,African-American,12/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +61734,70944,64322,PRETRIAL,RANDELL,JOHNNIE,NULL,Female,African-American,12/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +61734,70944,64322,PRETRIAL,RANDELL,JOHNNIE,NULL,Female,African-American,12/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54118,70963,64339,PRETRIAL,carvallo,vincent,NULL,Male,Caucasian,06/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +54118,70963,64339,PRETRIAL,carvallo,vincent,NULL,Male,Caucasian,06/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +54118,70963,64339,PRETRIAL,carvallo,vincent,NULL,Male,Caucasian,06/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61747,70965,64341,PRETRIAL,Ivy,Andrew,NULL,Male,African-American,06/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +61747,70965,64341,PRETRIAL,Ivy,Andrew,NULL,Male,African-American,06/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +61747,70965,64341,PRETRIAL,Ivy,Andrew,NULL,Male,African-American,06/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61720,70926,64304,PRETRIAL,Boujaoude,Elie,NULL,Male,Caucasian,09/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +61720,70926,64304,PRETRIAL,Boujaoude,Elie,NULL,Male,Caucasian,09/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +61720,70926,64304,PRETRIAL,Boujaoude,Elie,NULL,Male,Caucasian,09/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +10772,70960,64336,PRETRIAL,MOOKEN,SUNIL,NULL,Male,Other,01/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +10772,70960,64336,PRETRIAL,MOOKEN,SUNIL,NULL,Male,Other,01/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +10772,70960,64336,PRETRIAL,MOOKEN,SUNIL,NULL,Male,Other,01/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61736,70947,64325,PRETRIAL,Mccloud,Cornelius,NULL,Male,African-American,01/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +61736,70947,64325,PRETRIAL,Mccloud,Cornelius,NULL,Male,African-American,01/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +61736,70947,64325,PRETRIAL,Mccloud,Cornelius,NULL,Male,African-American,01/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61743,70956,64333,Probation,renaud,travis,NULL,Male,Caucasian,12/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +61743,70956,64333,Probation,renaud,travis,NULL,Male,Caucasian,12/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +61743,70956,64333,Probation,renaud,travis,NULL,Male,Caucasian,12/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61739,70951,64329,Probation,Zimmerman,Roderick,K,Male,Caucasian,07/02/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +61739,70951,64329,Probation,Zimmerman,Roderick,K,Male,Caucasian,07/02/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +61739,70951,64329,Probation,Zimmerman,Roderick,K,Male,Caucasian,07/02/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61724,70930,64308,PRETRIAL,Castro,Heriberto,NULL,Male,Caucasian,06/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +61724,70930,64308,PRETRIAL,Castro,Heriberto,NULL,Male,Caucasian,06/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +61724,70930,64308,PRETRIAL,Castro,Heriberto,NULL,Male,Caucasian,06/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61745,70961,64337,Probation,GRAU,MICHELLE,NULL,Female,Hispanic,04/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +61745,70961,64337,Probation,GRAU,MICHELLE,NULL,Female,Hispanic,04/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +61745,70961,64337,Probation,GRAU,MICHELLE,NULL,Female,Hispanic,04/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +18809,70940,64318,PRETRIAL,onyiuke,chinwe,NULL,Female,African-American,08/31/78,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/5/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +18809,70940,64318,PRETRIAL,onyiuke,chinwe,NULL,Female,African-American,08/31/78,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +18809,70940,64318,PRETRIAL,onyiuke,chinwe,NULL,Female,African-American,08/31/78,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61725,70932,64310,Probation,Williams,Kadyja,NULL,Female,African-American,11/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +61725,70932,64310,Probation,Williams,Kadyja,NULL,Female,African-American,11/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +61725,70932,64310,Probation,Williams,Kadyja,NULL,Female,African-American,11/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +61740,70953,64330,Probation,fosback,eric,NULL,Male,Caucasian,09/27/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,New,1,0 +61740,70953,64330,Probation,fosback,eric,NULL,Male,Caucasian,09/27/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +61740,70953,64330,Probation,fosback,eric,NULL,Male,Caucasian,09/27/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61718,70924,64303,PRETRIAL,Thomas,Brenda,NULL,Male,African-American,12/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +61718,70924,64303,PRETRIAL,Thomas,Brenda,NULL,Male,African-American,12/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +61718,70924,64303,PRETRIAL,Thomas,Brenda,NULL,Male,African-American,12/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61744,70958,64334,Probation,Jacques,Jeffery,NULL,Male,Caucasian,01/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +61744,70958,64334,Probation,Jacques,Jeffery,NULL,Male,Caucasian,01/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +61744,70958,64334,Probation,Jacques,Jeffery,NULL,Male,Caucasian,01/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +61735,70945,64323,Probation,PEREZ,GEORGE,JAMES,Male,Caucasian,09/25/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +61735,70945,64323,Probation,PEREZ,GEORGE,JAMES,Male,Caucasian,09/25/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +61735,70945,64323,Probation,PEREZ,GEORGE,JAMES,Male,Caucasian,09/25/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +38528,70966,37974,PRETRIAL,PELLEGRINO,ROBERT,NULL,Male,Caucasian,11/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,4,High,7,Risk of Violence,-0.79,9,High,Copy,1,0 +38528,70966,37974,PRETRIAL,PELLEGRINO,ROBERT,NULL,Male,Caucasian,11/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,4,High,8,Risk of Recidivism,0.58,9,High,Copy,1,0 +38528,70966,37974,PRETRIAL,PELLEGRINO,ROBERT,NULL,Male,Caucasian,11/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/5/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +61730,70937,64315,Probation,GARCIA,KAYLA,NULL,Female,Hispanic,12/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +61730,70937,64315,Probation,GARCIA,KAYLA,NULL,Female,Hispanic,12/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,10,High,New,1,0 +61730,70937,64315,Probation,GARCIA,KAYLA,NULL,Female,Hispanic,12/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61703,70987,64287,PRETRIAL,PICART,KERRICE,NULL,Female,Other,05/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,2,Medium,7,Risk of Violence,-2.92,2,Low,Copy,1,0 +61703,70987,64287,PRETRIAL,PICART,KERRICE,NULL,Female,Other,05/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,Copy,1,0 +61703,70987,64287,PRETRIAL,PICART,KERRICE,NULL,Female,Other,05/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,Copy,1,0 +22264,71005,64375,Probation,rouss,diana,NULL,Female,Hispanic,04/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,2,Medium,7,Risk of Violence,-2.86,2,Low,New,1,0 +22264,71005,64375,Probation,rouss,diana,NULL,Female,Hispanic,04/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +22264,71005,64375,Probation,rouss,diana,NULL,Female,Hispanic,04/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61764,70984,64356,PRETRIAL,Paul,Showanda,NULL,Female,African-American,11/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/6/14 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +61764,70984,64356,PRETRIAL,Paul,Showanda,NULL,Female,African-American,11/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/6/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +61764,70984,64356,PRETRIAL,Paul,Showanda,NULL,Female,African-American,11/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61761,70979,64351,PRETRIAL,Clark,Patrick,NULL,Male,African-American,03/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +61761,70979,64351,PRETRIAL,Clark,Patrick,NULL,Male,African-American,03/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +61761,70979,64351,PRETRIAL,Clark,Patrick,NULL,Male,African-American,03/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61770,70992,64362,Probation,MORRISON,TASHA,NULL,Female,African-American,06/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +61770,70992,64362,Probation,MORRISON,TASHA,NULL,Female,African-American,06/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +61770,70992,64362,Probation,MORRISON,TASHA,NULL,Female,African-American,06/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +61762,70982,64354,PRETRIAL,Ballestas,Abraham,NULL,Male,Hispanic,10/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +61762,70982,64354,PRETRIAL,Ballestas,Abraham,NULL,Male,Hispanic,10/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +61762,70982,64354,PRETRIAL,Ballestas,Abraham,NULL,Male,Hispanic,10/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61767,70989,64359,Probation,Vega,Angel,Manuel,Male,Hispanic,11/16/85,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +61767,70989,64359,Probation,Vega,Angel,Manuel,Male,Hispanic,11/16/85,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +61767,70989,64359,Probation,Vega,Angel,Manuel,Male,Hispanic,11/16/85,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61778,71003,64373,Probation,Hernandez-Tenziente,enrique,NULL,Male,Hispanic,06/08/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +61778,71003,64373,Probation,Hernandez-Tenziente,enrique,NULL,Male,Hispanic,06/08/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +61778,71003,64373,Probation,Hernandez-Tenziente,enrique,NULL,Male,Hispanic,06/08/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61773,70995,64365,Probation,Flowers,Dwayne,NULL,Male,African-American,06/03/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +61773,70995,64365,Probation,Flowers,Dwayne,NULL,Male,African-American,06/03/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +61773,70995,64365,Probation,Flowers,Dwayne,NULL,Male,African-American,06/03/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56756,70997,64367,Probation,Abdel-Rahman,Mohamad,NULL,Male,African-American,11/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +56756,70997,64367,Probation,Abdel-Rahman,Mohamad,NULL,Male,African-American,11/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +56756,70997,64367,Probation,Abdel-Rahman,Mohamad,NULL,Male,African-American,11/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61757,70974,64346,PRETRIAL,Young,Charlie,NULL,Male,African-American,10/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +61757,70974,64346,PRETRIAL,Young,Charlie,NULL,Male,African-American,10/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +61757,70974,64346,PRETRIAL,Young,Charlie,NULL,Male,African-American,10/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61759,70976,64348,PRETRIAL,Stettner,Russell,NULL,Male,Caucasian,05/21/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +61759,70976,64348,PRETRIAL,Stettner,Russell,NULL,Male,Caucasian,05/21/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +61759,70976,64348,PRETRIAL,Stettner,Russell,NULL,Male,Caucasian,05/21/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60803,71002,64372,PRETRIAL,GLOVER,ROYNESTO,NULL,Male,African-American,08/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.03,8,High,New,1,0 +60803,71002,64372,PRETRIAL,GLOVER,ROYNESTO,NULL,Male,African-American,08/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +60803,71002,64372,PRETRIAL,GLOVER,ROYNESTO,NULL,Male,African-American,08/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61575,70981,64353,PRETRIAL,Mims,Tommie,Earl,Male,African-American,02/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +61575,70981,64353,PRETRIAL,Mims,Tommie,Earl,Male,African-American,02/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +61575,70981,64353,PRETRIAL,Mims,Tommie,Earl,Male,African-American,02/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +57599,70977,64349,PRETRIAL,Hills,Rakesha,NULL,Female,African-American,04/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +57599,70977,64349,PRETRIAL,Hills,Rakesha,NULL,Female,African-American,04/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +57599,70977,64349,PRETRIAL,Hills,Rakesha,NULL,Female,African-American,04/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61754,70970,64342,PRETRIAL,BRANTLEY,KATARUIS,ELIJUS,Male,African-American,06/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +61754,70970,64342,PRETRIAL,BRANTLEY,KATARUIS,ELIJUS,Male,African-American,06/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +61754,70970,64342,PRETRIAL,BRANTLEY,KATARUIS,ELIJUS,Male,African-American,06/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61756,70972,64344,PRETRIAL,Gonzalez,Richard,NULL,Male,Caucasian,09/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +61756,70972,64344,PRETRIAL,Gonzalez,Richard,NULL,Male,Caucasian,09/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +61756,70972,64344,PRETRIAL,Gonzalez,Richard,NULL,Male,Caucasian,09/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61769,70991,64361,Probation,didonna,michael,NULL,Male,Caucasian,07/01/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/6/14 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +61769,70991,64361,Probation,didonna,michael,NULL,Male,Caucasian,07/01/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/6/14 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +61769,70991,64361,Probation,didonna,michael,NULL,Male,Caucasian,07/01/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61771,70993,64363,Probation,Bradford,Lawrence,NULL,Male,Caucasian,02/05/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/6/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +61771,70993,64363,Probation,Bradford,Lawrence,NULL,Male,Caucasian,02/05/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/6/14 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +61771,70993,64363,Probation,Bradford,Lawrence,NULL,Male,Caucasian,02/05/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +2461,70986,64357,PRETRIAL,FARMER,BRANDON,NULL,Male,African-American,12/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +2461,70986,64357,PRETRIAL,FARMER,BRANDON,NULL,Male,African-American,12/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +2461,70986,64357,PRETRIAL,FARMER,BRANDON,NULL,Male,African-American,12/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61776,71000,64370,Probation,SALAME,EDWIN,NULL,Male,Hispanic,09/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.82,2,Low,New,1,0 +61776,71000,64370,Probation,SALAME,EDWIN,NULL,Male,Hispanic,09/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +61776,71000,64370,Probation,SALAME,EDWIN,NULL,Male,Hispanic,09/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61781,71007,64377,Probation,rodriguez,elizabeth,NULL,Male,Hispanic,03/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +61781,71007,64377,Probation,rodriguez,elizabeth,NULL,Male,Hispanic,03/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +61781,71007,64377,Probation,rodriguez,elizabeth,NULL,Male,Hispanic,03/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50428,70969,51447,PRETRIAL,MEDINA,LUIS,DANIEL,Male,Caucasian,11/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,Copy,1,0 +50428,70969,51447,PRETRIAL,MEDINA,LUIS,DANIEL,Male,Caucasian,11/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,Copy,1,0 +50428,70969,51447,PRETRIAL,MEDINA,LUIS,DANIEL,Male,Caucasian,11/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +61768,70990,64360,Probation,Tutoni,Robert,NULL,Male,Caucasian,02/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +61768,70990,64360,Probation,Tutoni,Robert,NULL,Male,Caucasian,02/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +61768,70990,64360,Probation,Tutoni,Robert,NULL,Male,Caucasian,02/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61772,70994,64364,Probation,BRADFORD,FELICIA,DELORIS,Female,African-American,11/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +61772,70994,64364,Probation,BRADFORD,FELICIA,DELORIS,Female,African-American,11/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +61772,70994,64364,Probation,BRADFORD,FELICIA,DELORIS,Female,African-American,11/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61755,70971,64343,PRETRIAL,Lennox,Ryan,NULL,Male,African-American,03/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +61755,70971,64343,PRETRIAL,Lennox,Ryan,NULL,Male,African-American,03/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +61755,70971,64343,PRETRIAL,Lennox,Ryan,NULL,Male,African-American,03/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61760,70978,64350,PRETRIAL,Wright,Waldren,Gladstone,Male,Other,09/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,1,Low,7,Risk of Violence,-4.42,1,Low,New,1,0 +61760,70978,64350,PRETRIAL,Wright,Waldren,Gladstone,Male,Other,09/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,1,Low,8,Risk of Recidivism,-2.83,1,Low,New,1,0 +61760,70978,64350,PRETRIAL,Wright,Waldren,Gladstone,Male,Other,09/24/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60598,70985,63058,Probation,Torres,Daniel,NULL,Male,Hispanic,02/21/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.24,8,High,Copy,1,0 +60598,70985,63058,Probation,Torres,Daniel,NULL,Male,Hispanic,02/21/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.16,6,Medium,Copy,1,0 +60598,70985,63058,Probation,Torres,Daniel,NULL,Male,Hispanic,02/21/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +61782,71008,64378,Probation,dorival,stanley,NULL,Male,African-American,10/30/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +61782,71008,64378,Probation,dorival,stanley,NULL,Male,African-American,10/30/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +61782,71008,64378,Probation,dorival,stanley,NULL,Male,African-American,10/30/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61780,71006,64376,Probation,Cordobabojorge,Lenin,Jose,Male,Hispanic,11/05/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +61780,71006,64376,Probation,Cordobabojorge,Lenin,Jose,Male,Hispanic,11/05/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +61780,71006,64376,Probation,Cordobabojorge,Lenin,Jose,Male,Hispanic,11/05/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61779,71004,64374,Probation,Perez,EDUARDO,NULL,Male,Hispanic,02/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +61779,71004,64374,Probation,Perez,EDUARDO,NULL,Male,Hispanic,02/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +61779,71004,64374,Probation,Perez,EDUARDO,NULL,Male,Hispanic,02/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61774,70996,64366,Probation,Nahar,Juan,NULL,Male,Hispanic,02/22/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/14 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +61774,70996,64366,Probation,Nahar,Juan,NULL,Male,Hispanic,02/22/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +61774,70996,64366,Probation,Nahar,Juan,NULL,Male,Hispanic,02/22/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61758,70975,64347,PRETRIAL,Ashley,Ava,Denise,Female,African-American,12/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +61758,70975,64347,PRETRIAL,Ashley,Ava,Denise,Female,African-American,12/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +61758,70975,64347,PRETRIAL,Ashley,Ava,Denise,Female,African-American,12/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,New,1,0 +61783,71009,64379,Probation,LABO,MARY,R,Female,Caucasian,10/02/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/6/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +61783,71009,64379,Probation,LABO,MARY,R,Female,Caucasian,10/02/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/6/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +61783,71009,64379,Probation,LABO,MARY,R,Female,Caucasian,10/02/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61766,70988,64358,Probation,Weinzirl,Michael,NULL,Male,Caucasian,04/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +61766,70988,64358,Probation,Weinzirl,Michael,NULL,Male,Caucasian,04/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +61766,70988,64358,Probation,Weinzirl,Michael,NULL,Male,Caucasian,04/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61922,71179,64532,Probation,DEVITO,kENNETH,NULL,Male,Caucasian,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +61922,71179,64532,Probation,DEVITO,kENNETH,NULL,Male,Caucasian,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +61922,71179,64532,Probation,DEVITO,kENNETH,NULL,Male,Caucasian,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61763,70983,64355,PRETRIAL,Anderson,Nicole,NULL,Female,African-American,08/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +61763,70983,64355,PRETRIAL,Anderson,Nicole,NULL,Female,African-American,08/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +61763,70983,64355,PRETRIAL,Anderson,Nicole,NULL,Female,African-American,08/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61777,71001,64371,PRETRIAL,Ayme,Richar,Edgar,Male,Hispanic,12/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +61777,71001,64371,PRETRIAL,Ayme,Richar,Edgar,Male,Hispanic,12/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +61777,71001,64371,PRETRIAL,Ayme,Richar,Edgar,Male,Hispanic,12/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +21150,70980,64352,PRETRIAL,Scottjr,Hubert,Dale,Male,Caucasian,12/05/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +21150,70980,64352,PRETRIAL,Scottjr,Hubert,Dale,Male,Caucasian,12/05/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +21150,70980,64352,PRETRIAL,Scottjr,Hubert,Dale,Male,Caucasian,12/05/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/6/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61790,71017,64387,PRETRIAL,Crescenti,Daniel,NULL,Male,Caucasian,08/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,4,High,7,Risk of Violence,-0.36,10,High,New,1,0 +61790,71017,64387,PRETRIAL,Crescenti,Daniel,NULL,Male,Caucasian,08/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,4,High,8,Risk of Recidivism,0.9,10,High,New,1,0 +61790,71017,64387,PRETRIAL,Crescenti,Daniel,NULL,Male,Caucasian,08/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61796,71025,64393,PRETRIAL,Pineda,Sebastian,NULL,Male,Hispanic,07/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +61796,71025,64393,PRETRIAL,Pineda,Sebastian,NULL,Male,Hispanic,07/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +61796,71025,64393,PRETRIAL,Pineda,Sebastian,NULL,Male,Hispanic,07/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61785,71011,64381,PRETRIAL,Verne,Carlos,NULL,Male,Hispanic,05/22/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/7/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +61785,71011,64381,PRETRIAL,Verne,Carlos,NULL,Male,Hispanic,05/22/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/7/14 0:00,1,Low,8,Risk of Recidivism,-2.65,1,Low,New,1,0 +61785,71011,64381,PRETRIAL,Verne,Carlos,NULL,Male,Hispanic,05/22/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61795,71024,64392,PRETRIAL,FORSHAW,SHANE,MARIE,Female,Hispanic,07/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/7/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +61795,71024,64392,PRETRIAL,FORSHAW,SHANE,MARIE,Female,Hispanic,07/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/7/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +61795,71024,64392,PRETRIAL,FORSHAW,SHANE,MARIE,Female,Hispanic,07/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61788,71015,64385,PRETRIAL,Mckenkie,Anders,Stuart,Male,Other,04/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +61788,71015,64385,PRETRIAL,Mckenkie,Anders,Stuart,Male,Other,04/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +61788,71015,64385,PRETRIAL,Mckenkie,Anders,Stuart,Male,Other,04/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61791,71020,64390,PRETRIAL,Mapp,Venetta,S,Female,Other,02/15/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/7/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +61791,71020,64390,PRETRIAL,Mapp,Venetta,S,Female,Other,02/15/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/7/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +61791,71020,64390,PRETRIAL,Mapp,Venetta,S,Female,Other,02/15/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/7/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +61787,71014,64384,PRETRIAL,St Hill,Ronald,NULL,Male,Other,11/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +61787,71014,64384,PRETRIAL,St Hill,Ronald,NULL,Male,Other,11/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +61787,71014,64384,PRETRIAL,St Hill,Ronald,NULL,Male,Other,11/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51528,71021,52718,PRETRIAL,Merico,Daniel,Ray,Male,Caucasian,01/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/14 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,Copy,1,0 +51528,71021,52718,PRETRIAL,Merico,Daniel,Ray,Male,Caucasian,01/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,Copy,1,0 +51528,71021,52718,PRETRIAL,Merico,Daniel,Ray,Male,Caucasian,01/28/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +61799,71028,64396,PRETRIAL,israel,jarryd,NULL,Male,African-American,08/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +61799,71028,64396,PRETRIAL,israel,jarryd,NULL,Male,African-American,08/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +61799,71028,64396,PRETRIAL,israel,jarryd,NULL,Male,African-American,08/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61789,71016,64386,PRETRIAL,Butler,Latrellias,NULL,Female,African-American,10/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +61789,71016,64386,PRETRIAL,Butler,Latrellias,NULL,Female,African-American,10/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +61789,71016,64386,PRETRIAL,Butler,Latrellias,NULL,Female,African-American,10/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61793,71019,64389,PRETRIAL,Falconer,Chantel,M,Male,African-American,12/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +61793,71019,64389,PRETRIAL,Falconer,Chantel,M,Male,African-American,12/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +61793,71019,64389,PRETRIAL,Falconer,Chantel,M,Male,African-American,12/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +8383,71012,64382,PRETRIAL,HOLLOWAY,BRANDON,NULL,Male,African-American,09/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +8383,71012,64382,PRETRIAL,HOLLOWAY,BRANDON,NULL,Male,African-American,09/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,4,High,8,Risk of Recidivism,0.63,10,High,New,1,0 +8383,71012,64382,PRETRIAL,HOLLOWAY,BRANDON,NULL,Male,African-American,09/19/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +11454,71023,10981,Probation,Montague,Tequina,NULL,Female,African-American,10/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/14 0:00,4,High,7,Risk of Violence,-1.06,8,High,Copy,1,0 +11454,71023,10981,Probation,Montague,Tequina,NULL,Female,African-American,10/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/14 0:00,4,High,8,Risk of Recidivism,0.25,9,High,Copy,1,0 +11454,71023,10981,Probation,Montague,Tequina,NULL,Female,African-American,10/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/7/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +61784,71010,64380,PRETRIAL,Graham,Bobby,NULL,Male,African-American,06/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +61784,71010,64380,PRETRIAL,Graham,Bobby,NULL,Male,African-American,06/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +61784,71010,64380,PRETRIAL,Graham,Bobby,NULL,Male,African-American,06/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61792,71018,64388,PRETRIAL,Sapp,Jamie,NULL,Male,African-American,03/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +61792,71018,64388,PRETRIAL,Sapp,Jamie,NULL,Male,African-American,03/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +61792,71018,64388,PRETRIAL,Sapp,Jamie,NULL,Male,African-American,03/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61797,71026,64394,PRETRIAL,MORENO,SONIA,LEE,Female,Caucasian,11/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/7/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +61797,71026,64394,PRETRIAL,MORENO,SONIA,LEE,Female,Caucasian,11/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/7/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +61797,71026,64394,PRETRIAL,MORENO,SONIA,LEE,Female,Caucasian,11/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61786,71013,64383,PRETRIAL,Archibald,Jonray,NULL,Male,African-American,10/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +61786,71013,64383,PRETRIAL,Archibald,Jonray,NULL,Male,African-American,10/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +61786,71013,64383,PRETRIAL,Archibald,Jonray,NULL,Male,African-American,10/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/7/14 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +61802,71031,64399,PRETRIAL,Garcia,Elisa,NULL,Female,Caucasian,02/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +61802,71031,64399,PRETRIAL,Garcia,Elisa,NULL,Female,Caucasian,02/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +61802,71031,64399,PRETRIAL,Garcia,Elisa,NULL,Female,Caucasian,02/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61804,71033,64401,PRETRIAL,Castellanos,Freedom,NULL,Male,Caucasian,11/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,2,Medium,7,Risk of Violence,-3.32,1,Low,New,1,0 +61804,71033,64401,PRETRIAL,Castellanos,Freedom,NULL,Male,Caucasian,11/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +61804,71033,64401,PRETRIAL,Castellanos,Freedom,NULL,Male,Caucasian,11/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,New,1,0 +61800,71029,64397,PRETRIAL,Cook,Virgil,NULL,Male,Caucasian,08/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.48,3,Low,New,1,0 +61800,71029,64397,PRETRIAL,Cook,Virgil,NULL,Male,Caucasian,08/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +61800,71029,64397,PRETRIAL,Cook,Virgil,NULL,Male,Caucasian,08/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61803,71032,64400,PRETRIAL,Liantonio,James,NULL,Male,Caucasian,10/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +61803,71032,64400,PRETRIAL,Liantonio,James,NULL,Male,Caucasian,10/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +61803,71032,64400,PRETRIAL,Liantonio,James,NULL,Male,Caucasian,10/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61801,71030,64398,PRETRIAL,Haynes,Richard,NULL,Male,African-American,09/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +61801,71030,64398,PRETRIAL,Haynes,Richard,NULL,Male,African-American,09/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +61801,71030,64398,PRETRIAL,Haynes,Richard,NULL,Male,African-American,09/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/8/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61817,71048,64415,PRETRIAL,Rall,Robert,NULL,Male,Caucasian,11/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +61817,71048,64415,PRETRIAL,Rall,Robert,NULL,Male,Caucasian,11/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +61817,71048,64415,PRETRIAL,Rall,Robert,NULL,Male,Caucasian,11/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61819,71051,64417,PRETRIAL,EDELEN,KENNETH,ERIC,Male,Caucasian,11/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +61819,71051,64417,PRETRIAL,EDELEN,KENNETH,ERIC,Male,Caucasian,11/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +61819,71051,64417,PRETRIAL,EDELEN,KENNETH,ERIC,Male,Caucasian,11/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61812,71043,64410,PRETRIAL,MUNOZ,ALBEIRO,JOSHUA,Male,Hispanic,07/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +61812,71043,64410,PRETRIAL,MUNOZ,ALBEIRO,JOSHUA,Male,Hispanic,07/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +61812,71043,64410,PRETRIAL,MUNOZ,ALBEIRO,JOSHUA,Male,Hispanic,07/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61815,71046,64413,PRETRIAL,Cullen,Todd,NULL,Male,Caucasian,01/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +61815,71046,64413,PRETRIAL,Cullen,Todd,NULL,Male,Caucasian,01/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +61815,71046,64413,PRETRIAL,Cullen,Todd,NULL,Male,Caucasian,01/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61808,71038,64406,PRETRIAL,Dunkley,Joel,NULL,Male,African-American,10/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +61808,71038,64406,PRETRIAL,Dunkley,Joel,NULL,Male,African-American,10/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +61808,71038,64406,PRETRIAL,Dunkley,Joel,NULL,Male,African-American,10/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61810,71040,64408,PRETRIAL,Buchner,Daniel,NULL,Male,Caucasian,02/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +61810,71040,64408,PRETRIAL,Buchner,Daniel,NULL,Male,Caucasian,02/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +61810,71040,64408,PRETRIAL,Buchner,Daniel,NULL,Male,Caucasian,02/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +61818,71050,64416,PRETRIAL,THORNTON,JERALD,NULL,Male,Caucasian,12/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +61818,71050,64416,PRETRIAL,THORNTON,JERALD,NULL,Male,Caucasian,12/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +61818,71050,64416,PRETRIAL,THORNTON,JERALD,NULL,Male,Caucasian,12/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61814,71045,64412,PRETRIAL,Jean,Farrah,NULL,Female,African-American,11/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +61814,71045,64412,PRETRIAL,Jean,Farrah,NULL,Female,African-American,11/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +61814,71045,64412,PRETRIAL,Jean,Farrah,NULL,Female,African-American,11/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +21491,71041,50211,Probation,schmidt,gregory,NULL,Male,Caucasian,08/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.91,5,Medium,Copy,1,0 +21491,71041,50211,Probation,schmidt,gregory,NULL,Male,Caucasian,08/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.63,10,High,Copy,1,0 +21491,71041,50211,Probation,schmidt,gregory,NULL,Male,Caucasian,08/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +58837,71049,61070,Probation,JEAN,WILSON,NULL,Male,African-American,09/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,3/9/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,Copy,1,0 +58837,71049,61070,Probation,JEAN,WILSON,NULL,Male,African-American,09/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,3/9/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,Copy,1,0 +58837,71049,61070,Probation,JEAN,WILSON,NULL,Male,African-American,09/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,3/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +61811,71042,64409,PRETRIAL,Hollis,Hector,NULL,Male,Other,02/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +61811,71042,64409,PRETRIAL,Hollis,Hector,NULL,Male,Other,02/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +61811,71042,64409,PRETRIAL,Hollis,Hector,NULL,Male,Other,02/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61813,71044,64411,PRETRIAL,WILSON,VANTONIO,NULL,Male,African-American,09/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +61813,71044,64411,PRETRIAL,WILSON,VANTONIO,NULL,Male,African-American,09/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +61813,71044,64411,PRETRIAL,WILSON,VANTONIO,NULL,Male,African-American,09/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61809,71039,64407,PRETRIAL,Lewis,Edna,NULL,Female,Caucasian,01/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/9/14 0:00,2,Medium,7,Risk of Violence,-3.18,1,Low,New,1,0 +61809,71039,64407,PRETRIAL,Lewis,Edna,NULL,Female,Caucasian,01/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +61809,71039,64407,PRETRIAL,Lewis,Edna,NULL,Female,Caucasian,01/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/9/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61816,71047,64414,PRETRIAL,Jean,Jerline,NULL,Female,African-American,10/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +61816,71047,64414,PRETRIAL,Jean,Jerline,NULL,Female,African-American,10/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +61816,71047,64414,PRETRIAL,Jean,Jerline,NULL,Female,African-American,10/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/9/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61843,71081,64443,Probation,McGregor,Arelius,NULL,Male,African-American,10/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +61843,71081,64443,Probation,McGregor,Arelius,NULL,Male,African-American,10/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +61843,71081,64443,Probation,McGregor,Arelius,NULL,Male,African-American,10/14/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61826,71060,64426,Probation,Guerrero,Ruben,NULL,Male,Hispanic,03/10/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/10/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +61826,71060,64426,Probation,Guerrero,Ruben,NULL,Male,Hispanic,03/10/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/10/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +61826,71060,64426,Probation,Guerrero,Ruben,NULL,Male,Hispanic,03/10/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61851,71094,64453,Probation,Morgan,Tiara,NULL,Female,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +61851,71094,64453,Probation,Morgan,Tiara,NULL,Female,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,2,Medium,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +61851,71094,64453,Probation,Morgan,Tiara,NULL,Female,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +61820,71052,64418,PRETRIAL,GOLDEN,DWAYNE,NULL,Male,African-American,09/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +61820,71052,64418,PRETRIAL,GOLDEN,DWAYNE,NULL,Male,African-American,09/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +61820,71052,64418,PRETRIAL,GOLDEN,DWAYNE,NULL,Male,African-American,09/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61856,71102,64460,Probation,Rawlins,Kerwin,NULL,Male,African-American,10/18/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +61856,71102,64460,Probation,Rawlins,Kerwin,NULL,Male,African-American,10/18/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +61856,71102,64460,Probation,Rawlins,Kerwin,NULL,Male,African-American,10/18/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61823,71055,64421,PRETRIAL,LANDRESS,JASON,NULL,Male,Caucasian,08/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +61823,71055,64421,PRETRIAL,LANDRESS,JASON,NULL,Male,Caucasian,08/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +61823,71055,64421,PRETRIAL,LANDRESS,JASON,NULL,Male,Caucasian,08/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +61839,71073,64438,Probation,fleites,rogelio,NULL,Male,Hispanic,05/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/10/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +61839,71073,64438,Probation,fleites,rogelio,NULL,Male,Hispanic,05/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/10/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +61839,71073,64438,Probation,fleites,rogelio,NULL,Male,Hispanic,05/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61848,71089,64449,Probation,Estrada,Jorge,Lazaro,Male,Hispanic,08/29/47,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/10/14 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +61848,71089,64449,Probation,Estrada,Jorge,Lazaro,Male,Hispanic,08/29/47,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/10/14 0:00,1,Low,8,Risk of Recidivism,-2.6,1,Low,New,1,0 +61848,71089,64449,Probation,Estrada,Jorge,Lazaro,Male,Hispanic,08/29/47,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61853,71096,64454,Probation,Leary,David,NULL,Male,Caucasian,05/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +61853,71096,64454,Probation,Leary,David,NULL,Male,Caucasian,05/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +61853,71096,64454,Probation,Leary,David,NULL,Male,Caucasian,05/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61834,71068,64433,Probation,Montplaisir,Daniel,NULL,Male,Caucasian,08/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +61834,71068,64433,Probation,Montplaisir,Daniel,NULL,Male,Caucasian,08/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +61834,71068,64433,Probation,Montplaisir,Daniel,NULL,Male,Caucasian,08/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +61858,71104,64462,Probation,Paz,Otoniel,NULL,Male,Hispanic,03/15/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +61858,71104,64462,Probation,Paz,Otoniel,NULL,Male,Hispanic,03/15/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +61858,71104,64462,Probation,Paz,Otoniel,NULL,Male,Hispanic,03/15/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61841,71076,64440,Probation,Edwards,Equilla,NULL,Female,African-American,07/31/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +61841,71076,64440,Probation,Edwards,Equilla,NULL,Female,African-American,07/31/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +61841,71076,64440,Probation,Edwards,Equilla,NULL,Female,African-American,07/31/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61863,71110,64467,PRETRIAL,LOESER,THOMAS,NULL,Male,Caucasian,02/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +61863,71110,64467,PRETRIAL,LOESER,THOMAS,NULL,Male,Caucasian,02/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +61863,71110,64467,PRETRIAL,LOESER,THOMAS,NULL,Male,Caucasian,02/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +61850,71091,64451,Probation,Robinson,Jennifer,NULL,Female,African-American,02/26/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +61850,71091,64451,Probation,Robinson,Jennifer,NULL,Female,African-American,02/26/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +61850,71091,64451,Probation,Robinson,Jennifer,NULL,Female,African-American,02/26/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61852,71093,64452,PRETRIAL,Hegarty,Philip,NULL,Male,Caucasian,04/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +61852,71093,64452,PRETRIAL,Hegarty,Philip,NULL,Male,Caucasian,04/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +61852,71093,64452,PRETRIAL,Hegarty,Philip,NULL,Male,Caucasian,04/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +61830,71063,64429,Probation,Herrera,Rene,NULL,Male,Hispanic,05/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +61830,71063,64429,Probation,Herrera,Rene,NULL,Male,Hispanic,05/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +61830,71063,64429,Probation,Herrera,Rene,NULL,Male,Hispanic,05/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61836,71070,64435,PRETRIAL,Lopez,Ivette,NULL,Female,Caucasian,05/10/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +61836,71070,64435,PRETRIAL,Lopez,Ivette,NULL,Female,Caucasian,05/10/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +61836,71070,64435,PRETRIAL,Lopez,Ivette,NULL,Female,Caucasian,05/10/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61838,71072,64437,PRETRIAL,dyer,gary,NULL,Male,African-American,06/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +61838,71072,64437,PRETRIAL,dyer,gary,NULL,Male,African-American,06/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +61838,71072,64437,PRETRIAL,dyer,gary,NULL,Male,African-American,06/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61846,71086,64448,Probation,ApARICIO,Delvin,Henry,Male,Hispanic,12/28/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +61846,71086,64448,Probation,ApARICIO,Delvin,Henry,Male,Hispanic,12/28/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +61846,71086,64448,Probation,ApARICIO,Delvin,Henry,Male,Hispanic,12/28/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61855,71100,64458,Probation,fitzsimmons,corinne,NULL,Female,Caucasian,09/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +61855,71100,64458,Probation,fitzsimmons,corinne,NULL,Female,Caucasian,09/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +61855,71100,64458,Probation,fitzsimmons,corinne,NULL,Female,Caucasian,09/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61861,71107,64465,PRETRIAL,Omoregie,Jermaine,NULL,Male,African-American,11/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,New,1,0 +61861,71107,64465,PRETRIAL,Omoregie,Jermaine,NULL,Male,African-American,11/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +61861,71107,64465,PRETRIAL,Omoregie,Jermaine,NULL,Male,African-American,11/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61845,71084,64446,PRETRIAL,Coombs,Curtis,NULL,Male,African-American,06/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +61845,71084,64446,PRETRIAL,Coombs,Curtis,NULL,Male,African-American,06/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +61845,71084,64446,PRETRIAL,Coombs,Curtis,NULL,Male,African-American,06/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61860,71105,64463,Probation,Geffraud,Janard,NULL,Male,African-American,08/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +61860,71105,64463,Probation,Geffraud,Janard,NULL,Male,African-American,08/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +61860,71105,64463,Probation,Geffraud,Janard,NULL,Male,African-American,08/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61825,71058,64424,PRETRIAL,Brown,Larence,NULL,Male,African-American,02/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +61825,71058,64424,PRETRIAL,Brown,Larence,NULL,Male,African-American,02/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +61825,71058,64424,PRETRIAL,Brown,Larence,NULL,Male,African-American,02/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +45915,71075,46253,PRETRIAL,Brinson,Marques,NULL,Male,African-American,03/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,Copy,1,0 +45915,71075,46253,PRETRIAL,Brinson,Marques,NULL,Male,African-American,03/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,Copy,1,0 +45915,71075,46253,PRETRIAL,Brinson,Marques,NULL,Male,African-American,03/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +61862,71109,64466,PRETRIAL,BARROW,ANTHONY,AKHEEAM,Male,African-American,02/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.22,8,High,New,1,0 +61862,71109,64466,PRETRIAL,BARROW,ANTHONY,AKHEEAM,Male,African-American,02/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +61862,71109,64466,PRETRIAL,BARROW,ANTHONY,AKHEEAM,Male,African-American,02/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61822,71054,64420,PRETRIAL,Perez,Alyson,Johanna,Female,Hispanic,06/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +61822,71054,64420,PRETRIAL,Perez,Alyson,Johanna,Female,Hispanic,06/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +61822,71054,64420,PRETRIAL,Perez,Alyson,Johanna,Female,Hispanic,06/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61127,71079,63632,Probation,Martinez,Danny,NULL,Male,Hispanic,06/26/83,17,All Scales,Intake,English,Post Sentence,Probation,Significant Other,3/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +61127,71079,63632,Probation,Martinez,Danny,NULL,Male,Hispanic,06/26/83,17,All Scales,Intake,English,Post Sentence,Probation,Significant Other,3/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +61127,71079,63632,Probation,Martinez,Danny,NULL,Male,Hispanic,06/26/83,17,All Scales,Intake,English,Post Sentence,Probation,Significant Other,3/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +61831,71066,64431,Broward County,Thomas,Sandra,NULL,Female,African-American,02/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,2,Medium,7,Risk of Violence,-3.02,1,Low,Copy,1,0 +61831,71066,64431,Broward County,Thomas,Sandra,NULL,Female,African-American,02/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,7,Medium,Copy,1,0 +61831,71066,64431,Broward County,Thomas,Sandra,NULL,Female,African-American,02/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +50746,71101,64459,PRETRIAL,Marinez,Argenis,NULL,Male,Caucasian,07/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +50746,71101,64459,PRETRIAL,Marinez,Argenis,NULL,Male,Caucasian,07/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +50746,71101,64459,PRETRIAL,Marinez,Argenis,NULL,Male,Caucasian,07/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61829,71062,64428,Probation,Jennings,Darlene,Renee,Female,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +61829,71062,64428,Probation,Jennings,Darlene,Renee,Female,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.68,10,High,New,1,0 +61829,71062,64428,Probation,Jennings,Darlene,Renee,Female,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +19808,71080,64442,Probation,HORVATH,RONALD,A,Male,Caucasian,01/20/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/10/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +19808,71080,64442,Probation,HORVATH,RONALD,A,Male,Caucasian,01/20/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +19808,71080,64442,Probation,HORVATH,RONALD,A,Male,Caucasian,01/20/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +40411,71085,64447,PRETRIAL,Eubanks,Tavetric,NULL,Male,African-American,08/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +40411,71085,64447,PRETRIAL,Eubanks,Tavetric,NULL,Male,African-American,08/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +40411,71085,64447,PRETRIAL,Eubanks,Tavetric,NULL,Male,African-American,08/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61824,71057,64423,PRETRIAL,Peralta,Algin,NULL,Male,Hispanic,10/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +61824,71057,64423,PRETRIAL,Peralta,Algin,NULL,Male,Hispanic,10/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +61824,71057,64423,PRETRIAL,Peralta,Algin,NULL,Male,Hispanic,10/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61832,71064,64430,Probation,Nurrito,Alexander,NULL,Male,Hispanic,11/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +61832,71064,64430,Probation,Nurrito,Alexander,NULL,Male,Hispanic,11/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +61832,71064,64430,Probation,Nurrito,Alexander,NULL,Male,Hispanic,11/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61837,71071,64436,Probation,Douville,Luciano,NULL,Male,Caucasian,11/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +61837,71071,64436,Probation,Douville,Luciano,NULL,Male,Caucasian,11/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +61837,71071,64436,Probation,Douville,Luciano,NULL,Male,Caucasian,11/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61854,71099,64457,Probation,Bucala,Natalie,NULL,Female,Caucasian,08/15/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +61854,71099,64457,Probation,Bucala,Natalie,NULL,Female,Caucasian,08/15/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +61854,71099,64457,Probation,Bucala,Natalie,NULL,Female,Caucasian,08/15/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +47352,71106,64464,PRETRIAL,DORMAN,BRUCE,MALCOM,Male,Caucasian,08/26/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/10/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +47352,71106,64464,PRETRIAL,DORMAN,BRUCE,MALCOM,Male,Caucasian,08/26/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +47352,71106,64464,PRETRIAL,DORMAN,BRUCE,MALCOM,Male,Caucasian,08/26/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61842,71078,64441,PRETRIAL,Thomas,Roderick,NULL,Male,African-American,01/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,Copy,1,0 +61842,71078,64441,PRETRIAL,Thomas,Roderick,NULL,Male,African-American,01/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,Copy,1,0 +61842,71078,64441,PRETRIAL,Thomas,Roderick,NULL,Male,African-American,01/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +54078,71108,55625,PRETRIAL,States,Douglas,NULL,Male,Caucasian,01/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,Copy,1,0 +54078,71108,55625,PRETRIAL,States,Douglas,NULL,Male,Caucasian,01/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,Copy,1,0 +54078,71108,55625,PRETRIAL,States,Douglas,NULL,Male,Caucasian,01/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +61794,71095,64391,PRETRIAL,MAYER,CHARLES,NULL,Male,Caucasian,09/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,Copy,1,0 +61794,71095,64391,PRETRIAL,MAYER,CHARLES,NULL,Male,Caucasian,09/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,Copy,1,0 +61794,71095,64391,PRETRIAL,MAYER,CHARLES,NULL,Male,Caucasian,09/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +61840,71074,64439,Probation,Mavintorn,Vashira,NULL,Male,Asian,05/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +61840,71074,64439,Probation,Mavintorn,Vashira,NULL,Male,Asian,05/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +61840,71074,64439,Probation,Mavintorn,Vashira,NULL,Male,Asian,05/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +45702,71082,64444,PRETRIAL,Stewart,Roxana,NULL,Female,Caucasian,09/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +45702,71082,64444,PRETRIAL,Stewart,Roxana,NULL,Female,Caucasian,09/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,7,Medium,New,1,0 +45702,71082,64444,PRETRIAL,Stewart,Roxana,NULL,Female,Caucasian,09/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/10/14 0:00,2,Medium,18,Risk of Failure to Appear,35,10,High,New,1,0 +61821,71053,64419,PRETRIAL,HERNANDEZ,CRYSTAL,ELENA,Female,Caucasian,03/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +61821,71053,64419,PRETRIAL,HERNANDEZ,CRYSTAL,ELENA,Female,Caucasian,03/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +61821,71053,64419,PRETRIAL,HERNANDEZ,CRYSTAL,ELENA,Female,Caucasian,03/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61833,71067,64432,Probation,Diaz Figueroa,Tulio,Alexander,Male,Hispanic,01/28/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/10/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +61833,71067,64432,Probation,Diaz Figueroa,Tulio,Alexander,Male,Hispanic,01/28/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +61833,71067,64432,Probation,Diaz Figueroa,Tulio,Alexander,Male,Hispanic,01/28/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61859,71103,64461,Probation,monroe,devontai,NULL,Male,African-American,03/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,4,High,7,Risk of Violence,-1.05,8,High,New,1,0 +61859,71103,64461,Probation,monroe,devontai,NULL,Male,African-American,03/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,4,High,8,Risk of Recidivism,0.97,10,High,New,1,0 +61859,71103,64461,Probation,monroe,devontai,NULL,Male,African-American,03/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62648,72139,65397,Probation,parajon,homer,NULL,Male,Hispanic,05/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/10/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +62648,72139,65397,Probation,parajon,homer,NULL,Male,Hispanic,05/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +62648,72139,65397,Probation,parajon,homer,NULL,Male,Hispanic,05/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +43281,71056,64422,PRETRIAL,crayton,bradford,michael,Male,African-American,10/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +43281,71056,64422,PRETRIAL,crayton,bradford,michael,Male,African-American,10/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +43281,71056,64422,PRETRIAL,crayton,bradford,michael,Male,African-American,10/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61849,71090,64450,Probation,cuthberson,dillion,NULL,Male,Caucasian,05/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +61849,71090,64450,Probation,cuthberson,dillion,NULL,Male,Caucasian,05/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +61849,71090,64450,Probation,cuthberson,dillion,NULL,Male,Caucasian,05/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61835,71069,64434,Probation,ceci,artan,NULL,Male,Hispanic,03/18/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +61835,71069,64434,Probation,ceci,artan,NULL,Male,Hispanic,03/18/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +61835,71069,64434,Probation,ceci,artan,NULL,Male,Hispanic,03/18/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +12459,71098,64456,PRETRIAL,BAPTISTE,ELIJAH,NULL,Male,African-American,05/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +12459,71098,64456,PRETRIAL,BAPTISTE,ELIJAH,NULL,Male,African-American,05/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +12459,71098,64456,PRETRIAL,BAPTISTE,ELIJAH,NULL,Male,African-American,05/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61884,71137,64494,PRETRIAL,Paul,Glendel,NULL,Male,African-American,07/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +61884,71137,64494,PRETRIAL,Paul,Glendel,NULL,Male,African-American,07/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +61884,71137,64494,PRETRIAL,Paul,Glendel,NULL,Male,African-American,07/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61870,71116,64473,PRETRIAL,Mendieta,Adrian,NULL,Male,Caucasian,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +61870,71116,64473,PRETRIAL,Mendieta,Adrian,NULL,Male,Caucasian,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +61870,71116,64473,PRETRIAL,Mendieta,Adrian,NULL,Male,Caucasian,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61872,71119,64476,PRETRIAL,WILLIAMS,SOYEKA,NULL,Female,African-American,11/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +61872,71119,64476,PRETRIAL,WILLIAMS,SOYEKA,NULL,Female,African-American,11/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +61872,71119,64476,PRETRIAL,WILLIAMS,SOYEKA,NULL,Female,African-American,11/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61877,71124,64481,Probation,Choy,Williams,NULL,Male,Hispanic,07/26/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +61877,71124,64481,Probation,Choy,Williams,NULL,Male,Hispanic,07/26/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +61877,71124,64481,Probation,Choy,Williams,NULL,Male,Hispanic,07/26/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51585,71145,64502,PRETRIAL,Montalvo,Mark,NULL,Male,Caucasian,04/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +51585,71145,64502,PRETRIAL,Montalvo,Mark,NULL,Male,Caucasian,04/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +51585,71145,64502,PRETRIAL,Montalvo,Mark,NULL,Male,Caucasian,04/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61864,71111,64468,PRETRIAL,WINKEBLECH,JAMIE,LYNN,Female,Caucasian,02/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +61864,71111,64468,PRETRIAL,WINKEBLECH,JAMIE,LYNN,Female,Caucasian,02/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +61864,71111,64468,PRETRIAL,WINKEBLECH,JAMIE,LYNN,Female,Caucasian,02/02/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55879,71153,64509,Probation,beaudoin,patrick,NULL,Male,Caucasian,09/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +55879,71153,64509,Probation,beaudoin,patrick,NULL,Male,Caucasian,09/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +55879,71153,64509,Probation,beaudoin,patrick,NULL,Male,Caucasian,09/18/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61881,71132,64489,Probation,chatee,vasudev,NULL,Male,Other,12/20/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/11/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +61881,71132,64489,Probation,chatee,vasudev,NULL,Male,Other,12/20/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/11/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +61881,71132,64489,Probation,chatee,vasudev,NULL,Male,Other,12/20/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61887,71140,64497,PRETRIAL,KASPROW,ANTHONY,NULL,Male,Caucasian,01/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.78,9,High,New,1,0 +61887,71140,64497,PRETRIAL,KASPROW,ANTHONY,NULL,Male,Caucasian,01/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +61887,71140,64497,PRETRIAL,KASPROW,ANTHONY,NULL,Male,Caucasian,01/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +61879,71129,64486,Probation,PINTILIE,EMIL,NULL,Male,Caucasian,06/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,7,Risk of Violence,-4.37,1,Low,New,1,0 +61879,71129,64486,Probation,PINTILIE,EMIL,NULL,Male,Caucasian,06/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +61879,71129,64486,Probation,PINTILIE,EMIL,NULL,Male,Caucasian,06/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52709,59525,54079,PRETRIAL,Henley,Brandon,NULL,Male,African-American,10/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +52709,59525,54079,PRETRIAL,Henley,Brandon,NULL,Male,African-American,10/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +52709,59525,54079,PRETRIAL,Henley,Brandon,NULL,Male,African-American,10/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61883,71136,64493,PRETRIAL,Zamora,Maryuri,NULL,Female,Hispanic,10/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +61883,71136,64493,PRETRIAL,Zamora,Maryuri,NULL,Female,Hispanic,10/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +61883,71136,64493,PRETRIAL,Zamora,Maryuri,NULL,Female,Hispanic,10/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +34317,71150,33458,Probation,WEINSTEIN,JAY,NULL,Male,Caucasian,09/16/57,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +34317,71150,33458,Probation,WEINSTEIN,JAY,NULL,Male,Caucasian,09/16/57,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +34317,71150,33458,Probation,WEINSTEIN,JAY,NULL,Male,Caucasian,09/16/57,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +61895,71148,64505,Probation,Smith,Michael,Edward,Male,Caucasian,07/17/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +61895,71148,64505,Probation,Smith,Michael,Edward,Male,Caucasian,07/17/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +61895,71148,64505,Probation,Smith,Michael,Edward,Male,Caucasian,07/17/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61882,71134,64491,PRETRIAL,Sapper,Jeffrey,NULL,Male,Caucasian,01/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/11/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +61882,71134,64491,PRETRIAL,Sapper,Jeffrey,NULL,Male,Caucasian,01/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/11/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +61882,71134,64491,PRETRIAL,Sapper,Jeffrey,NULL,Male,Caucasian,01/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61890,71143,64500,Probation,wright,jeffery,NULL,Male,African-American,12/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +61890,71143,64500,Probation,wright,jeffery,NULL,Male,African-American,12/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +61890,71143,64500,Probation,wright,jeffery,NULL,Male,African-American,12/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61867,71113,64470,PRETRIAL,Cook,Torrence,NULL,Male,African-American,07/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +61867,71113,64470,PRETRIAL,Cook,Torrence,NULL,Male,African-American,07/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,4,High,8,Risk of Recidivism,0.54,9,High,New,1,0 +61867,71113,64470,PRETRIAL,Cook,Torrence,NULL,Male,African-American,07/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61874,71122,64479,Probation,SCRUGGS,CHRISTOPHER,NULL,Male,Caucasian,10/30/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +61874,71122,64479,Probation,SCRUGGS,CHRISTOPHER,NULL,Male,Caucasian,10/30/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +61874,71122,64479,Probation,SCRUGGS,CHRISTOPHER,NULL,Male,Caucasian,10/30/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +34608,71147,64504,PRETRIAL,RULKA,JOHN,EDWARD,Male,Caucasian,05/16/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +34608,71147,64504,PRETRIAL,RULKA,JOHN,EDWARD,Male,Caucasian,05/16/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +34608,71147,64504,PRETRIAL,RULKA,JOHN,EDWARD,Male,Caucasian,05/16/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +21088,71126,64483,PRETRIAL,MICHEL,LAFONTANT,NULL,Male,African-American,06/15/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/11/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +21088,71126,64483,PRETRIAL,MICHEL,LAFONTANT,NULL,Male,African-American,06/15/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +21088,71126,64483,PRETRIAL,MICHEL,LAFONTANT,NULL,Male,African-American,06/15/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +8554,71130,64487,PRETRIAL,Jenkins,Javarus,NULL,Male,African-American,09/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +8554,71130,64487,PRETRIAL,Jenkins,Javarus,NULL,Male,African-American,09/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +8554,71130,64487,PRETRIAL,Jenkins,Javarus,NULL,Male,African-American,09/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61897,71151,64507,Probation,RABAH,NADIR,SAMI,Male,Hispanic,10/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +61897,71151,64507,Probation,RABAH,NADIR,SAMI,Male,Hispanic,10/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +61897,71151,64507,Probation,RABAH,NADIR,SAMI,Male,Hispanic,10/13/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61868,71114,64471,PRETRIAL,Pierre Louis,Doll,NULL,Male,African-American,10/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +61868,71114,64471,PRETRIAL,Pierre Louis,Doll,NULL,Male,African-American,10/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +61868,71114,64471,PRETRIAL,Pierre Louis,Doll,NULL,Male,African-American,10/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56107,71121,64478,PRETRIAL,Lopez,Leny,Yesenia,Female,Hispanic,01/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +56107,71121,64478,PRETRIAL,Lopez,Leny,Yesenia,Female,Hispanic,01/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +56107,71121,64478,PRETRIAL,Lopez,Leny,Yesenia,Female,Hispanic,01/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +3680,71135,64492,PRETRIAL,worboys,roger,NULL,Male,Caucasian,10/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +3680,71135,64492,PRETRIAL,worboys,roger,NULL,Male,Caucasian,10/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +3680,71135,64492,PRETRIAL,worboys,roger,NULL,Male,Caucasian,10/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61889,71142,64499,Probation,Werdin,Mark,Richard,Male,Caucasian,09/03/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +61889,71142,64499,Probation,Werdin,Mark,Richard,Male,Caucasian,09/03/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +61889,71142,64499,Probation,Werdin,Mark,Richard,Male,Caucasian,09/03/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61891,71144,64501,Probation,CHAVEZ,JESUS,A,Male,Hispanic,09/11/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +61891,71144,64501,Probation,CHAVEZ,JESUS,A,Male,Hispanic,09/11/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +61891,71144,64501,Probation,CHAVEZ,JESUS,A,Male,Hispanic,09/11/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61876,71125,64482,Probation,palmer,natasha,NULL,Female,African-American,03/10/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +61876,71125,64482,Probation,palmer,natasha,NULL,Female,African-American,03/10/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +61876,71125,64482,Probation,palmer,natasha,NULL,Female,African-American,03/10/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61885,71138,64495,PRETRIAL,BUTLER,CHRISTIN,NULL,Female,Caucasian,05/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/11/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +61885,71138,64495,PRETRIAL,BUTLER,CHRISTIN,NULL,Female,Caucasian,05/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +61885,71138,64495,PRETRIAL,BUTLER,CHRISTIN,NULL,Female,Caucasian,05/01/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61871,71117,64474,PRETRIAL,NOCIE,MICHAEL,NULL,Male,Caucasian,03/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +61871,71117,64474,PRETRIAL,NOCIE,MICHAEL,NULL,Male,Caucasian,03/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +61871,71117,64474,PRETRIAL,NOCIE,MICHAEL,NULL,Male,Caucasian,03/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +35614,71118,64475,PRETRIAL,Carte,Terry,NULL,Male,Caucasian,02/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/11/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +35614,71118,64475,PRETRIAL,Carte,Terry,NULL,Male,Caucasian,02/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/11/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +35614,71118,64475,PRETRIAL,Carte,Terry,NULL,Male,Caucasian,02/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61886,71139,64496,Probation,Cotton,Randall,NULL,Male,Caucasian,04/23/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +61886,71139,64496,Probation,Cotton,Randall,NULL,Male,Caucasian,04/23/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +61886,71139,64496,Probation,Cotton,Randall,NULL,Male,Caucasian,04/23/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61894,71146,64503,Probation,Watkins,Jennifer,Sue,Female,Caucasian,09/30/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +61894,71146,64503,Probation,Watkins,Jennifer,Sue,Female,Caucasian,09/30/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +61894,71146,64503,Probation,Watkins,Jennifer,Sue,Female,Caucasian,09/30/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +49888,71112,64469,PRETRIAL,Ganten,Daniel,NULL,Male,Caucasian,03/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +49888,71112,64469,PRETRIAL,Ganten,Daniel,NULL,Male,Caucasian,03/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +49888,71112,64469,PRETRIAL,Ganten,Daniel,NULL,Male,Caucasian,03/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61875,71123,64480,PRETRIAL,Materiale,Alex,NULL,Male,Hispanic,06/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +61875,71123,64480,PRETRIAL,Materiale,Alex,NULL,Male,Hispanic,06/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +61875,71123,64480,PRETRIAL,Materiale,Alex,NULL,Male,Hispanic,06/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50453,71133,64490,PRETRIAL,HATSFIELD,GEORGE,EDWARD,Male,Caucasian,03/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/11/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +50453,71133,64490,PRETRIAL,HATSFIELD,GEORGE,EDWARD,Male,Caucasian,03/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +50453,71133,64490,PRETRIAL,HATSFIELD,GEORGE,EDWARD,Male,Caucasian,03/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61878,71128,64485,Probation,Williams,Mareeta,NULL,Female,African-American,11/29/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +61878,71128,64485,Probation,Williams,Mareeta,NULL,Female,African-American,11/29/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +61878,71128,64485,Probation,Williams,Mareeta,NULL,Female,African-American,11/29/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61869,71115,64472,PRETRIAL,Crane,Nevin,NULL,Male,African-American,03/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +61869,71115,64472,PRETRIAL,Crane,Nevin,NULL,Male,African-American,03/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.84,10,High,New,1,0 +61869,71115,64472,PRETRIAL,Crane,Nevin,NULL,Male,African-American,03/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61873,71120,64477,PRETRIAL,Brundidge,Donald,NULL,Male,African-American,02/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +61873,71120,64477,PRETRIAL,Brundidge,Donald,NULL,Male,African-American,02/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +61873,71120,64477,PRETRIAL,Brundidge,Donald,NULL,Male,African-American,02/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61896,71149,64506,Probation,Gurney,Alton,NULL,Male,Caucasian,05/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +61896,71149,64506,Probation,Gurney,Alton,NULL,Male,Caucasian,05/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +61896,71149,64506,Probation,Gurney,Alton,NULL,Male,Caucasian,05/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/11/14 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +61899,71154,64510,PRETRIAL,ULYSSE,STANLEY,NULL,Male,African-American,07/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +61899,71154,64510,PRETRIAL,ULYSSE,STANLEY,NULL,Male,African-American,07/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +61899,71154,64510,PRETRIAL,ULYSSE,STANLEY,NULL,Male,African-American,07/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52464,71188,64541,PRETRIAL,Gomez,Orlando,NULL,Male,Caucasian,11/28/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/12/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +52464,71188,64541,PRETRIAL,Gomez,Orlando,NULL,Male,Caucasian,11/28/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/12/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +52464,71188,64541,PRETRIAL,Gomez,Orlando,NULL,Male,Caucasian,11/28/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61912,71175,64528,Probation,Lubin,Alix,NULL,Male,African-American,11/12/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +61912,71175,64528,Probation,Lubin,Alix,NULL,Male,African-American,11/12/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +61912,71175,64528,Probation,Lubin,Alix,NULL,Male,African-American,11/12/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61908,71170,64523,Probation,Roessler,Daniel,NULL,Male,Caucasian,08/27/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/14 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +61908,71170,64523,Probation,Roessler,Daniel,NULL,Male,Caucasian,08/27/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +61908,71170,64523,Probation,Roessler,Daniel,NULL,Male,Caucasian,08/27/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61926,71183,64536,Probation,MITCHELL,SHEM,RONALD,Male,African-American,08/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +61926,71183,64536,Probation,MITCHELL,SHEM,RONALD,Male,African-American,08/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +61926,71183,64536,Probation,MITCHELL,SHEM,RONALD,Male,African-American,08/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61904,71162,64517,PRETRIAL,Gutierrez,Antonio,NULL,Male,Caucasian,01/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +61904,71162,64517,PRETRIAL,Gutierrez,Antonio,NULL,Male,Caucasian,01/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +61904,71162,64517,PRETRIAL,Gutierrez,Antonio,NULL,Male,Caucasian,01/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61923,71180,64533,PRETRIAL,WILSON,TRAVIS,NULL,Male,African-American,04/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,4,High,7,Risk of Violence,-0.68,9,High,New,1,0 +61923,71180,64533,PRETRIAL,WILSON,TRAVIS,NULL,Male,African-American,04/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +61923,71180,64533,PRETRIAL,WILSON,TRAVIS,NULL,Male,African-American,04/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +61906,71167,64520,PRETRIAL,Madera,Robert,NULL,Male,Caucasian,09/28/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +61906,71167,64520,PRETRIAL,Madera,Robert,NULL,Male,Caucasian,09/28/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +61906,71167,64520,PRETRIAL,Madera,Robert,NULL,Male,Caucasian,09/28/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +30024,71159,64514,PRETRIAL,JACKSON,TIWANA,S,Female,African-American,04/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +30024,71159,64514,PRETRIAL,JACKSON,TIWANA,S,Female,African-American,04/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +30024,71159,64514,PRETRIAL,JACKSON,TIWANA,S,Female,African-American,04/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61933,71193,64546,Probation,MORELAND,ANGIE,DELORIS,Female,African-American,07/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +61933,71193,64546,Probation,MORELAND,ANGIE,DELORIS,Female,African-American,07/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +61933,71193,64546,Probation,MORELAND,ANGIE,DELORIS,Female,African-American,07/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61905,71163,64518,PRETRIAL,GUERRERO,BRANDON,ANTHONY,Male,Caucasian,07/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,4,High,7,Risk of Violence,-0.33,10,High,New,1,0 +61905,71163,64518,PRETRIAL,GUERRERO,BRANDON,ANTHONY,Male,Caucasian,07/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,4,High,8,Risk of Recidivism,0.76,10,High,New,1,0 +61905,71163,64518,PRETRIAL,GUERRERO,BRANDON,ANTHONY,Male,Caucasian,07/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +44229,71165,44309,PRETRIAL,James,Ahmad,NULL,Male,African-American,07/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,Copy,1,0 +44229,71165,44309,PRETRIAL,James,Ahmad,NULL,Male,African-American,07/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +44229,71165,44309,PRETRIAL,James,Ahmad,NULL,Male,African-American,07/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +61909,71172,64525,Probation,Escobedo,Kimberly,NULL,Female,Hispanic,11/23/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/12/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +61909,71172,64525,Probation,Escobedo,Kimberly,NULL,Female,Hispanic,11/23/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/12/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +61909,71172,64525,Probation,Escobedo,Kimberly,NULL,Female,Hispanic,11/23/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +61929,71186,64539,Probation,Odom,Jennifer,NULL,Female,African-American,11/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +61929,71186,64539,Probation,Odom,Jennifer,NULL,Female,African-American,11/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +61929,71186,64539,Probation,Odom,Jennifer,NULL,Female,African-American,11/02/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61902,71160,64515,PRETRIAL,WU,SAM,NULL,Male,Other,06/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +61902,71160,64515,PRETRIAL,WU,SAM,NULL,Male,Other,06/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +61902,71160,64515,PRETRIAL,WU,SAM,NULL,Male,Other,06/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61919,71177,64530,Probation,Heyward,Dawan,NULL,Male,African-American,10/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +61919,71177,64530,Probation,Heyward,Dawan,NULL,Male,African-American,10/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +61919,71177,64530,Probation,Heyward,Dawan,NULL,Male,African-American,10/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +31552,71156,30561,PRETRIAL,Wheaton,George,NULL,Male,Caucasian,06/24/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.37,3,Low,Copy,1,0 +31552,71156,30561,PRETRIAL,Wheaton,George,NULL,Male,Caucasian,06/24/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,Copy,1,0 +31552,71156,30561,PRETRIAL,Wheaton,George,NULL,Male,Caucasian,06/24/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,Copy,1,0 +61924,71181,64534,Probation,rivera-peeples,brandon,NULL,Male,Other,11/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +61924,71181,64534,Probation,rivera-peeples,brandon,NULL,Male,Other,11/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +61924,71181,64534,Probation,rivera-peeples,brandon,NULL,Male,Other,11/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61932,71190,64543,Probation,prefontaine,luc,NULL,Male,Caucasian,08/24/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/12/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +61932,71190,64543,Probation,prefontaine,luc,NULL,Male,Caucasian,08/24/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/12/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +61932,71190,64543,Probation,prefontaine,luc,NULL,Male,Caucasian,08/24/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +19184,71169,64522,PRETRIAL,HOPPUS,ERIN,NULL,Female,Caucasian,05/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +19184,71169,64522,PRETRIAL,HOPPUS,ERIN,NULL,Female,Caucasian,05/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +19184,71169,64522,PRETRIAL,HOPPUS,ERIN,NULL,Female,Caucasian,05/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61900,71155,64511,PRETRIAL,EDIE,ANTHONY,TREVOR,Male,African-American,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +61900,71155,64511,PRETRIAL,EDIE,ANTHONY,TREVOR,Male,African-American,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +61900,71155,64511,PRETRIAL,EDIE,ANTHONY,TREVOR,Male,African-American,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61910,71173,64526,Probation,Kakuschke,Dmitriy,NULL,Male,Caucasian,07/10/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +61910,71173,64526,Probation,Kakuschke,Dmitriy,NULL,Male,Caucasian,07/10/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +61910,71173,64526,Probation,Kakuschke,Dmitriy,NULL,Male,Caucasian,07/10/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +24946,71185,64538,PRETRIAL,PINARD,JOELLE,NULL,Female,African-American,12/27/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/12/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +24946,71185,64538,PRETRIAL,PINARD,JOELLE,NULL,Female,African-American,12/27/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/12/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +24946,71185,64538,PRETRIAL,PINARD,JOELLE,NULL,Female,African-American,12/27/63,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59115,71157,64512,PRETRIAL,Spencer,Randail,NULL,Male,African-American,02/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +59115,71157,64512,PRETRIAL,Spencer,Randail,NULL,Male,African-American,02/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +59115,71157,64512,PRETRIAL,Spencer,Randail,NULL,Male,African-American,02/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51785,71164,64519,PRETRIAL,RIVERA-GARCIA,EDWIN,A,Male,Caucasian,01/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +51785,71164,64519,PRETRIAL,RIVERA-GARCIA,EDWIN,A,Male,Caucasian,01/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +51785,71164,64519,PRETRIAL,RIVERA-GARCIA,EDWIN,A,Male,Caucasian,01/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57469,71171,64524,PRETRIAL,Francois,Kerry,NULL,Male,African-American,12/18/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +57469,71171,64524,PRETRIAL,Francois,Kerry,NULL,Male,African-American,12/18/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +57469,71171,64524,PRETRIAL,Francois,Kerry,NULL,Male,African-American,12/18/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61920,71178,64531,Probation,JOSEPH,MICHELET,NULL,Male,African-American,03/05/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/12/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +61920,71178,64531,Probation,JOSEPH,MICHELET,NULL,Male,African-American,03/05/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/12/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +61920,71178,64531,Probation,JOSEPH,MICHELET,NULL,Male,African-American,03/05/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61911,71174,64527,PRETRIAL,THORNTON,ANDREW,NULL,Male,African-American,03/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +61911,71174,64527,PRETRIAL,THORNTON,ANDREW,NULL,Male,African-American,03/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +61911,71174,64527,PRETRIAL,THORNTON,ANDREW,NULL,Male,African-American,03/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61903,71161,64516,PRETRIAL,Soto,Gabriel,NULL,Male,Caucasian,09/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +61903,71161,64516,PRETRIAL,Soto,Gabriel,NULL,Male,Caucasian,09/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,4,High,8,Risk of Recidivism,0.81,10,High,New,1,0 +61903,71161,64516,PRETRIAL,Soto,Gabriel,NULL,Male,Caucasian,09/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61913,71176,64529,Probation,Jackson,Brittany,NULL,Female,African-American,06/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.52,3,Low,New,1,0 +61913,71176,64529,Probation,Jackson,Brittany,NULL,Female,African-American,06/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,8,High,New,1,0 +61913,71176,64529,Probation,Jackson,Brittany,NULL,Female,African-American,06/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61925,71182,64535,PRETRIAL,Davila-Alvarez,Maria,NULL,Female,Hispanic,06/09/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +61925,71182,64535,PRETRIAL,Davila-Alvarez,Maria,NULL,Female,Hispanic,06/09/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/14 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +61925,71182,64535,PRETRIAL,Davila-Alvarez,Maria,NULL,Female,Hispanic,06/09/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +61931,71189,64542,Probation,Hazen,Stephanie,NULL,Female,Caucasian,07/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +61931,71189,64542,Probation,Hazen,Stephanie,NULL,Female,Caucasian,07/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +61931,71189,64542,Probation,Hazen,Stephanie,NULL,Female,Caucasian,07/03/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61907,71168,64521,PRETRIAL,May,Justin,Wayne,Male,Caucasian,09/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +61907,71168,64521,PRETRIAL,May,Justin,Wayne,Male,Caucasian,09/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +61907,71168,64521,PRETRIAL,May,Justin,Wayne,Male,Caucasian,09/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61901,71158,64513,PRETRIAL,Dolcine,Mitton,None,Male,Other,07/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +61901,71158,64513,PRETRIAL,Dolcine,Mitton,None,Male,Other,07/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +61901,71158,64513,PRETRIAL,Dolcine,Mitton,None,Male,Other,07/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58327,71166,60551,PRETRIAL,WORTHY,BILLY,NULL,Male,African-American,02/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,Copy,1,0 +58327,71166,60551,PRETRIAL,WORTHY,BILLY,NULL,Male,African-American,02/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,Copy,1,0 +58327,71166,60551,PRETRIAL,WORTHY,BILLY,NULL,Male,African-American,02/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/12/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +61927,71184,64537,PRETRIAL,MUNRO,ROY,NULL,Male,Caucasian,06/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/12/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +61927,71184,64537,PRETRIAL,MUNRO,ROY,NULL,Male,Caucasian,06/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/12/14 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +61927,71184,64537,PRETRIAL,MUNRO,ROY,NULL,Male,Caucasian,06/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61930,71187,64540,Probation,Bailey,Alfred,NULL,Male,African-American,09/12/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +61930,71187,64540,Probation,Bailey,Alfred,NULL,Male,African-American,09/12/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +61930,71187,64540,Probation,Bailey,Alfred,NULL,Male,African-American,09/12/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61942,71205,64557,PRETRIAL,Blake,Tressing,NULL,Female,Other,07/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +61942,71205,64557,PRETRIAL,Blake,Tressing,NULL,Female,Other,07/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +61942,71205,64557,PRETRIAL,Blake,Tressing,NULL,Female,Other,07/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61962,71226,64577,Probation,lopez,luis,alberto,Male,Hispanic,08/08/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,4,High,7,Risk of Violence,-0.97,9,High,New,1,0 +61962,71226,64577,Probation,lopez,luis,alberto,Male,Hispanic,08/08/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,4,High,8,Risk of Recidivism,0.83,10,High,New,1,0 +61962,71226,64577,Probation,lopez,luis,alberto,Male,Hispanic,08/08/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +34115,71213,64564,PRETRIAL,Austin,Eniee,NULL,Female,African-American,05/01/90,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,4,High,7,Risk of Violence,-0.18,10,High,Copy,1,0 +34115,71213,64564,PRETRIAL,Austin,Eniee,NULL,Female,African-American,05/01/90,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,4,High,8,Risk of Recidivism,0.36,9,High,Copy,1,0 +34115,71213,64564,PRETRIAL,Austin,Eniee,NULL,Female,African-American,05/01/90,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,4,High,18,Risk of Failure to Appear,29,9,High,Copy,1,0 +61941,71203,64555,PRETRIAL,Edwards,Britney,NULL,Female,African-American,05/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +61941,71203,64555,PRETRIAL,Edwards,Britney,NULL,Female,African-American,05/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +61941,71203,64555,PRETRIAL,Edwards,Britney,NULL,Female,African-American,05/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61953,71218,64569,Probation,Mushlin,Anastasiya,NULL,Male,Caucasian,06/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/13/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +61953,71218,64569,Probation,Mushlin,Anastasiya,NULL,Male,Caucasian,06/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/13/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +61953,71218,64569,Probation,Mushlin,Anastasiya,NULL,Male,Caucasian,06/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61935,71195,64548,PRETRIAL,Pascual,Joe,NULL,Male,Caucasian,01/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +61935,71195,64548,PRETRIAL,Pascual,Joe,NULL,Male,Caucasian,01/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +61935,71195,64548,PRETRIAL,Pascual,Joe,NULL,Male,Caucasian,01/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +25340,71197,39499,PRETRIAL,grayheart,tavarus,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,4,High,7,Risk of Violence,-1.03,8,High,Copy,1,0 +25340,71197,39499,PRETRIAL,grayheart,tavarus,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,4,High,8,Risk of Recidivism,0.58,9,High,Copy,1,0 +25340,71197,39499,PRETRIAL,grayheart,tavarus,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +8801,71231,8336,PRETRIAL,ROTELA,RYAN,NULL,Male,Caucasian,03/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,Copy,1,0 +8801,71231,8336,PRETRIAL,ROTELA,RYAN,NULL,Male,Caucasian,03/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +8801,71231,8336,PRETRIAL,ROTELA,RYAN,NULL,Male,Caucasian,03/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +61937,71199,64551,PRETRIAL,Wade,Robert,Lee,Male,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +61937,71199,64551,PRETRIAL,Wade,Robert,Lee,Male,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +61937,71199,64551,PRETRIAL,Wade,Robert,Lee,Male,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61943,71206,64558,PRETRIAL,Garcia,Efrain,NULL,Male,Hispanic,05/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/13/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +61943,71206,64558,PRETRIAL,Garcia,Efrain,NULL,Male,Hispanic,05/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/13/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +61943,71206,64558,PRETRIAL,Garcia,Efrain,NULL,Male,Hispanic,05/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61964,71229,64580,Probation,Brickel,keith,NULL,Male,Caucasian,07/18/39,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-4.45,1,Low,New,1,0 +61964,71229,64580,Probation,Brickel,keith,NULL,Male,Caucasian,07/18/39,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +61964,71229,64580,Probation,Brickel,keith,NULL,Male,Caucasian,07/18/39,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61955,71220,64571,Probation,Williams,Centwane,Decriox,Male,African-American,04/11/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +61955,71220,64571,Probation,Williams,Centwane,Decriox,Male,African-American,04/11/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +61955,71220,64571,Probation,Williams,Centwane,Decriox,Male,African-American,04/11/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61950,71215,64566,Probation,Smith,Keosha,NULL,Female,African-American,03/20/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,4,High,7,Risk of Violence,-0.31,10,High,New,1,0 +61950,71215,64566,Probation,Smith,Keosha,NULL,Female,African-American,03/20/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,4,High,8,Risk of Recidivism,1.07,10,High,New,1,0 +61950,71215,64566,Probation,Smith,Keosha,NULL,Female,African-American,03/20/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61959,71224,64575,Probation,Harrison,Luis,NULL,Male,African-American,10/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +61959,71224,64575,Probation,Harrison,Luis,NULL,Male,African-American,10/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +61959,71224,64575,Probation,Harrison,Luis,NULL,Male,African-American,10/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61934,71194,64547,PRETRIAL,Lundy,Gregory,NULL,Male,Other,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/13/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +61934,71194,64547,PRETRIAL,Lundy,Gregory,NULL,Male,Other,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/13/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +61934,71194,64547,PRETRIAL,Lundy,Gregory,NULL,Male,Other,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61963,71228,64579,Probation,coghlin,john,NULL,Male,Caucasian,10/24/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/13/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +61963,71228,64579,Probation,coghlin,john,NULL,Male,Caucasian,10/24/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/13/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +61963,71228,64579,Probation,coghlin,john,NULL,Male,Caucasian,10/24/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61940,71202,64554,PRETRIAL,Williams,Theronardo,NULL,Male,African-American,04/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +61940,71202,64554,PRETRIAL,Williams,Theronardo,NULL,Male,African-American,04/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +61940,71202,64554,PRETRIAL,Williams,Theronardo,NULL,Male,African-American,04/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61951,71216,64567,Probation,Sosa,Christopher,NULL,Male,Hispanic,09/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +61951,71216,64567,Probation,Sosa,Christopher,NULL,Male,Hispanic,09/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +61951,71216,64567,Probation,Sosa,Christopher,NULL,Male,Hispanic,09/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61954,71219,64570,Probation,kinney,idanoel,NULL,Female,Caucasian,05/20/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +61954,71219,64570,Probation,kinney,idanoel,NULL,Female,Caucasian,05/20/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +61954,71219,64570,Probation,kinney,idanoel,NULL,Female,Caucasian,05/20/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +11116,71198,64550,PRETRIAL,Nealy,Cornelius,NULL,Male,African-American,07/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,4,High,7,Risk of Violence,-0.7,9,High,New,1,0 +11116,71198,64550,PRETRIAL,Nealy,Cornelius,NULL,Male,African-American,07/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,4,High,8,Risk of Recidivism,0.87,10,High,New,1,0 +11116,71198,64550,PRETRIAL,Nealy,Cornelius,NULL,Male,African-American,07/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +34115,71212,64564,PRETRIAL,Austin,Eniee,NULL,Female,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,4,High,7,Risk of Violence,-0.18,10,High,New,1,0 +34115,71212,64564,PRETRIAL,Austin,Eniee,NULL,Female,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,4,High,8,Risk of Recidivism,0.36,9,High,New,1,0 +34115,71212,64564,PRETRIAL,Austin,Eniee,NULL,Female,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,4,High,18,Risk of Failure to Appear,29,9,High,New,1,0 +61958,71223,64574,PRETRIAL,Brown,Randerick,NULL,Male,African-American,04/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.03,8,High,New,1,0 +61958,71223,64574,PRETRIAL,Brown,Randerick,NULL,Male,African-American,04/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +61958,71223,64574,PRETRIAL,Brown,Randerick,NULL,Male,African-American,04/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61938,71200,64552,PRETRIAL,Vanegas,Ivan,NULL,Male,Caucasian,11/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +61938,71200,64552,PRETRIAL,Vanegas,Ivan,NULL,Male,Caucasian,11/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +61938,71200,64552,PRETRIAL,Vanegas,Ivan,NULL,Male,Caucasian,11/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61944,71207,64559,PRETRIAL,BYNUM,RICKY,NULL,Male,African-American,05/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +61944,71207,64559,PRETRIAL,BYNUM,RICKY,NULL,Male,African-American,05/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,4,High,8,Risk of Recidivism,0.84,10,High,New,1,0 +61944,71207,64559,PRETRIAL,BYNUM,RICKY,NULL,Male,African-American,05/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +61949,71214,64565,Probation,Cash,Steve,A,Male,Hispanic,01/03/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +61949,71214,64565,Probation,Cash,Steve,A,Male,Hispanic,01/03/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +61949,71214,64565,Probation,Cash,Steve,A,Male,Hispanic,01/03/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61956,71221,64572,Probation,Schoensee,Thomas,NULL,Male,Caucasian,02/11/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +61956,71221,64572,Probation,Schoensee,Thomas,NULL,Male,Caucasian,02/11/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +61956,71221,64572,Probation,Schoensee,Thomas,NULL,Male,Caucasian,02/11/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61961,71225,64576,PRETRIAL,Gray,Wayne,NULL,Male,Caucasian,01/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +61961,71225,64576,PRETRIAL,Gray,Wayne,NULL,Male,Caucasian,01/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +61961,71225,64576,PRETRIAL,Gray,Wayne,NULL,Male,Caucasian,01/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +18294,71204,64556,PRETRIAL,TERRANCE,ROGERS,DESHAWN,Male,African-American,09/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +18294,71204,64556,PRETRIAL,TERRANCE,ROGERS,DESHAWN,Male,African-American,09/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +18294,71204,64556,PRETRIAL,TERRANCE,ROGERS,DESHAWN,Male,African-American,09/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61952,71217,64568,Probation,RIVERA,ROBERTO,NULL,Male,Hispanic,09/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +61952,71217,64568,Probation,RIVERA,ROBERTO,NULL,Male,Hispanic,09/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +61952,71217,64568,Probation,RIVERA,ROBERTO,NULL,Male,Hispanic,09/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61936,71196,64549,PRETRIAL,Sanchez,Kevin,NULL,Male,Hispanic,07/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +61936,71196,64549,PRETRIAL,Sanchez,Kevin,NULL,Male,Hispanic,07/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +61936,71196,64549,PRETRIAL,Sanchez,Kevin,NULL,Male,Hispanic,07/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61965,71230,64581,Probation,HERNANDEZ,VICTOR,NULL,Male,Hispanic,09/04/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +61965,71230,64581,Probation,HERNANDEZ,VICTOR,NULL,Male,Hispanic,09/04/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +61965,71230,64581,Probation,HERNANDEZ,VICTOR,NULL,Male,Hispanic,09/04/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61939,71201,64553,PRETRIAL,Grace,Marcravio,NULL,Male,African-American,08/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.14,8,High,New,1,0 +61939,71201,64553,PRETRIAL,Grace,Marcravio,NULL,Male,African-American,08/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,7,Medium,New,1,0 +61939,71201,64553,PRETRIAL,Grace,Marcravio,NULL,Male,African-American,08/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +44416,71209,64561,PRETRIAL,francisco,michael,NULL,Male,Caucasian,05/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +44416,71209,64561,PRETRIAL,francisco,michael,NULL,Male,Caucasian,05/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +44416,71209,64561,PRETRIAL,francisco,michael,NULL,Male,Caucasian,05/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61957,71222,64573,Probation,vera,carlos,NULL,Male,Caucasian,02/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +61957,71222,64573,Probation,vera,carlos,NULL,Male,Caucasian,02/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +61957,71222,64573,Probation,vera,carlos,NULL,Male,Caucasian,02/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61983,71256,64604,Probation,nole,michael,NULL,Male,Caucasian,12/16/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/14/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +61983,71256,64604,Probation,nole,michael,NULL,Male,Caucasian,12/16/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/14/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +61983,71256,64604,Probation,nole,michael,NULL,Male,Caucasian,12/16/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61972,71243,64591,Probation,Edwards,Melissa Edwards,Lynn,Female,Caucasian,01/26/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/14/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +61972,71243,64591,Probation,Edwards,Melissa Edwards,Lynn,Female,Caucasian,01/26/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/14/14 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +61972,71243,64591,Probation,Edwards,Melissa Edwards,Lynn,Female,Caucasian,01/26/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,29,9,High,New,1,0 +61977,71251,64599,Probation,Carmon,Lee,NULL,Male,African-American,09/18/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +61977,71251,64599,Probation,Carmon,Lee,NULL,Male,African-American,09/18/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +61977,71251,64599,Probation,Carmon,Lee,NULL,Male,African-American,09/18/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61975,71248,64596,Probation,Padaovano,Laina,Marie,Female,Caucasian,03/28/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/14/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +61975,71248,64596,Probation,Padaovano,Laina,Marie,Female,Caucasian,03/28/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/14/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +61975,71248,64596,Probation,Padaovano,Laina,Marie,Female,Caucasian,03/28/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61381,71232,63937,Probation,Flowers,Lisa,Marie,Female,Caucasian,10/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,2,Medium,7,Risk of Violence,-2.82,2,Low,Copy,1,0 +61381,71232,63937,Probation,Flowers,Lisa,Marie,Female,Caucasian,10/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,Copy,1,0 +61381,71232,63937,Probation,Flowers,Lisa,Marie,Female,Caucasian,10/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +61973,71246,64594,Probation,Carlos,Grilli,NULL,Male,Hispanic,12/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,New,1,0 +61973,71246,64594,Probation,Carlos,Grilli,NULL,Male,Hispanic,12/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +61973,71246,64594,Probation,Carlos,Grilli,NULL,Male,Hispanic,12/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61980,71253,64601,Probation,Mugno,Alfredo,NULL,Male,Caucasian,11/05/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/14/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +61980,71253,64601,Probation,Mugno,Alfredo,NULL,Male,Caucasian,11/05/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/14/14 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +61980,71253,64601,Probation,Mugno,Alfredo,NULL,Male,Caucasian,11/05/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61968,71238,64586,Probation,Lauderdale,Daniel,Lee,Male,Caucasian,02/29/84,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/14/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +61968,71238,64586,Probation,Lauderdale,Daniel,Lee,Male,Caucasian,02/29/84,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/14/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +61968,71238,64586,Probation,Lauderdale,Daniel,Lee,Male,Caucasian,02/29/84,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61967,71235,64584,Probation,HOUSTON,MICHAEL,NULL,Male,African-American,03/21/69,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +61967,71235,64584,Probation,HOUSTON,MICHAEL,NULL,Male,African-American,03/21/69,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +61967,71235,64584,Probation,HOUSTON,MICHAEL,NULL,Male,African-American,03/21/69,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,2,Low,New,1,0 +61971,71242,64590,PRETRIAL,Otero,Luis,Fernando,Male,Hispanic,01/28/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/14/14 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +61971,71242,64590,PRETRIAL,Otero,Luis,Fernando,Male,Hispanic,01/28/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/14/14 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +61971,71242,64590,PRETRIAL,Otero,Luis,Fernando,Male,Hispanic,01/28/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +31257,71237,30273,PRETRIAL,Rivera,Victor,Manuel,Male,Caucasian,11/19/68,17,All Scales,Intake,Spanish,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,Copy,1,0 +31257,71237,30273,PRETRIAL,Rivera,Victor,Manuel,Male,Caucasian,11/19/68,17,All Scales,Intake,Spanish,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,Copy,1,0 +31257,71237,30273,PRETRIAL,Rivera,Victor,Manuel,Male,Caucasian,11/19/68,17,All Scales,Intake,Spanish,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +61966,71233,64582,PRETRIAL,Green,Krystal,NULL,Female,African-American,09/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.28,3,Low,New,1,0 +61966,71233,64582,PRETRIAL,Green,Krystal,NULL,Female,African-American,09/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.03,8,High,New,1,0 +61966,71233,64582,PRETRIAL,Green,Krystal,NULL,Female,African-American,09/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +61984,71258,64605,PRETRIAL,MacPherson,John,NULL,Male,Caucasian,07/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +61984,71258,64605,PRETRIAL,MacPherson,John,NULL,Male,Caucasian,07/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +61984,71258,64605,PRETRIAL,MacPherson,John,NULL,Male,Caucasian,07/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61976,71249,64597,Probation,falero,eseban,NULL,Male,Hispanic,02/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +61976,71249,64597,Probation,falero,eseban,NULL,Male,Hispanic,02/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +61976,71249,64597,Probation,falero,eseban,NULL,Male,Hispanic,02/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61981,71254,64602,Probation,DERBAREMDIKER,LEV,NULL,Male,Caucasian,07/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +61981,71254,64602,Probation,DERBAREMDIKER,LEV,NULL,Male,Caucasian,07/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +61981,71254,64602,Probation,DERBAREMDIKER,LEV,NULL,Male,Caucasian,07/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +52136,71245,64593,PRETRIAL,Blade,Johnnie,NULL,Male,African-American,06/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +52136,71245,64593,PRETRIAL,Blade,Johnnie,NULL,Male,African-American,06/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.64,10,High,New,1,0 +52136,71245,64593,PRETRIAL,Blade,Johnnie,NULL,Male,African-American,06/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +16219,71241,64589,PRETRIAL,president,larry,NULL,Male,African-American,06/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +16219,71241,64589,PRETRIAL,president,larry,NULL,Male,African-American,06/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +16219,71241,64589,PRETRIAL,president,larry,NULL,Male,African-American,06/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56996,71236,64585,PRETRIAL,MARIANI,MICHAEL,NULL,Male,Caucasian,04/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.14,4,Low,New,1,0 +56996,71236,64585,PRETRIAL,MARIANI,MICHAEL,NULL,Male,Caucasian,04/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +56996,71236,64585,PRETRIAL,MARIANI,MICHAEL,NULL,Male,Caucasian,04/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +61978,71250,64598,PRETRIAL,SHELL,ELEXUS,RENEE,Female,African-American,12/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +61978,71250,64598,PRETRIAL,SHELL,ELEXUS,RENEE,Female,African-American,12/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +61978,71250,64598,PRETRIAL,SHELL,ELEXUS,RENEE,Female,African-American,12/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61969,71239,64587,Probation,NORELIUS,KEITH,JAMES,Male,Caucasian,02/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.37,3,Low,New,1,0 +61969,71239,64587,Probation,NORELIUS,KEITH,JAMES,Male,Caucasian,02/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.88,10,High,New,1,0 +61969,71239,64587,Probation,NORELIUS,KEITH,JAMES,Male,Caucasian,02/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61974,71247,64595,PRETRIAL,Merrick,David,NULL,Male,Caucasian,01/01/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,3/14/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +61974,71247,64595,PRETRIAL,Merrick,David,NULL,Male,Caucasian,01/01/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,3/14/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +61974,71247,64595,PRETRIAL,Merrick,David,NULL,Male,Caucasian,01/01/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61982,71255,64603,Probation,Salazar,Jeffrey,NULL,Male,Hispanic,12/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +61982,71255,64603,Probation,Salazar,Jeffrey,NULL,Male,Hispanic,12/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +61982,71255,64603,Probation,Salazar,Jeffrey,NULL,Male,Hispanic,12/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57536,71234,64583,PRETRIAL,Turner,Tamika,NULL,Female,African-American,07/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +57536,71234,64583,PRETRIAL,Turner,Tamika,NULL,Female,African-American,07/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,7,Medium,New,1,0 +57536,71234,64583,PRETRIAL,Turner,Tamika,NULL,Female,African-American,07/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61979,71252,64600,PRETRIAL,PELICIEUX,RUDNEY,NULL,Male,African-American,11/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +61979,71252,64600,PRETRIAL,PELICIEUX,RUDNEY,NULL,Male,African-American,11/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +61979,71252,64600,PRETRIAL,PELICIEUX,RUDNEY,NULL,Male,African-American,11/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +8382,71260,49933,PRETRIAL,DAMICO,PATRICK,VALENTINO,Male,Caucasian,08/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,Copy,1,0 +8382,71260,49933,PRETRIAL,DAMICO,PATRICK,VALENTINO,Male,Caucasian,08/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,Copy,1,0 +8382,71260,49933,PRETRIAL,DAMICO,PATRICK,VALENTINO,Male,Caucasian,08/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,Copy,1,0 +43912,71268,43948,Probation,green,donovan,NULL,Male,African-American,09/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,Copy,1,0 +43912,71268,43948,Probation,green,donovan,NULL,Male,African-American,09/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,Copy,1,0 +43912,71268,43948,Probation,green,donovan,NULL,Male,African-American,09/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +61988,71264,64610,PRETRIAL,Williams,Dariale,NULL,Male,African-American,04/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +61988,71264,64610,PRETRIAL,Williams,Dariale,NULL,Male,African-American,04/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,4,High,8,Risk of Recidivism,0.18,8,High,New,1,0 +61988,71264,64610,PRETRIAL,Williams,Dariale,NULL,Male,African-American,04/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61994,71271,64616,PRETRIAL,BOLANO,HERING,NULL,Male,African-American,07/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/15/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +61994,71271,64616,PRETRIAL,BOLANO,HERING,NULL,Male,African-American,07/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/15/14 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +61994,71271,64616,PRETRIAL,BOLANO,HERING,NULL,Male,African-American,07/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61986,71262,64608,PRETRIAL,Saintgermain,Robertson,NULL,Male,Other,12/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +61986,71262,64608,PRETRIAL,Saintgermain,Robertson,NULL,Male,Other,12/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +61986,71262,64608,PRETRIAL,Saintgermain,Robertson,NULL,Male,Other,12/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61990,71266,64612,PRETRIAL,ARCHAT,ANDRE,DPMINIQUE,Male,African-American,02/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/15/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +61990,71266,64612,PRETRIAL,ARCHAT,ANDRE,DPMINIQUE,Male,African-American,02/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/15/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +61990,71266,64612,PRETRIAL,ARCHAT,ANDRE,DPMINIQUE,Male,African-American,02/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61993,71270,64615,PRETRIAL,CARSON,JORDAN,NULL,Male,African-American,08/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +61993,71270,64615,PRETRIAL,CARSON,JORDAN,NULL,Male,African-American,08/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +61993,71270,64615,PRETRIAL,CARSON,JORDAN,NULL,Male,African-American,08/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61987,71263,64609,PRETRIAL,Lipsey,Ricky,NULL,Male,African-American,02/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +61987,71263,64609,PRETRIAL,Lipsey,Ricky,NULL,Male,African-American,02/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +61987,71263,64609,PRETRIAL,Lipsey,Ricky,NULL,Male,African-American,02/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61989,71265,64611,PRETRIAL,Guignard,Yves,NULL,Male,African-American,11/28/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +61989,71265,64611,PRETRIAL,Guignard,Yves,NULL,Male,African-American,11/28/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +61989,71265,64611,PRETRIAL,Guignard,Yves,NULL,Male,African-American,11/28/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51163,71272,52323,PRETRIAL,MANZE,GREGORY,ROBERT,Male,Caucasian,12/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,4,High,7,Risk of Violence,-0.93,9,High,Copy,1,0 +51163,71272,52323,PRETRIAL,MANZE,GREGORY,ROBERT,Male,Caucasian,12/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,4,High,8,Risk of Recidivism,0.13,8,High,Copy,1,0 +51163,71272,52323,PRETRIAL,MANZE,GREGORY,ROBERT,Male,Caucasian,12/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +54089,71261,64607,PRETRIAL,Benghiat,Steven,NULL,Male,Caucasian,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +54089,71261,64607,PRETRIAL,Benghiat,Steven,NULL,Male,Caucasian,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +54089,71261,64607,PRETRIAL,Benghiat,Steven,NULL,Male,Caucasian,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61991,71267,64613,PRETRIAL,PEREZ,MATTHEW,JAMES,Male,Caucasian,01/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +61991,71267,64613,PRETRIAL,PEREZ,MATTHEW,JAMES,Male,Caucasian,01/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +61991,71267,64613,PRETRIAL,PEREZ,MATTHEW,JAMES,Male,Caucasian,01/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61992,71269,64614,PRETRIAL,Joseph,Ricky,NULL,Male,African-American,06/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +61992,71269,64614,PRETRIAL,Joseph,Ricky,NULL,Male,African-American,06/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +61992,71269,64614,PRETRIAL,Joseph,Ricky,NULL,Male,African-American,06/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/15/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62001,71277,64621,PRETRIAL,PENA,MIGUEL,EDUARDO,Male,Caucasian,07/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +62001,71277,64621,PRETRIAL,PENA,MIGUEL,EDUARDO,Male,Caucasian,07/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +62001,71277,64621,PRETRIAL,PENA,MIGUEL,EDUARDO,Male,Caucasian,07/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62005,71282,64626,PRETRIAL,Gonzalez,Christopher,NULL,Male,Hispanic,08/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +62005,71282,64626,PRETRIAL,Gonzalez,Christopher,NULL,Male,Hispanic,08/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +62005,71282,64626,PRETRIAL,Gonzalez,Christopher,NULL,Male,Hispanic,08/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +61996,71274,64618,PRETRIAL,THIEME,ELIZABETH,ANNE,Female,Caucasian,06/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +61996,71274,64618,PRETRIAL,THIEME,ELIZABETH,ANNE,Female,Caucasian,06/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +61996,71274,64618,PRETRIAL,THIEME,ELIZABETH,ANNE,Female,Caucasian,06/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62007,71284,64628,PRETRIAL,Velky,Stuart,NULL,Male,Caucasian,01/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +62007,71284,64628,PRETRIAL,Velky,Stuart,NULL,Male,Caucasian,01/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +62007,71284,64628,PRETRIAL,Velky,Stuart,NULL,Male,Caucasian,01/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62003,71279,64623,PRETRIAL,Parker,Christina,NULL,Female,Caucasian,09/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/16/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +62003,71279,64623,PRETRIAL,Parker,Christina,NULL,Female,Caucasian,09/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/16/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +62003,71279,64623,PRETRIAL,Parker,Christina,NULL,Female,Caucasian,09/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61997,71275,64619,PRETRIAL,DOERR,HOLGER,E,Male,Caucasian,08/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/16/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +61997,71275,64619,PRETRIAL,DOERR,HOLGER,E,Male,Caucasian,08/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/16/14 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +61997,71275,64619,PRETRIAL,DOERR,HOLGER,E,Male,Caucasian,08/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +32908,71280,64624,PRETRIAL,James,Cedric,NULL,Male,African-American,11/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,4,High,7,Risk of Violence,-0.97,9,High,New,1,0 +32908,71280,64624,PRETRIAL,James,Cedric,NULL,Male,African-American,11/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +32908,71280,64624,PRETRIAL,James,Cedric,NULL,Male,African-American,11/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +62006,71283,64627,PRETRIAL,SWAN,RHYS,NULL,Male,Caucasian,12/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +62006,71283,64627,PRETRIAL,SWAN,RHYS,NULL,Male,Caucasian,12/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +62006,71283,64627,PRETRIAL,SWAN,RHYS,NULL,Male,Caucasian,12/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +9264,71285,59894,PRETRIAL,WHIPPLE,ADRIAN,MARNEL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,4,High,7,Risk of Violence,-0.88,9,High,Copy,1,0 +9264,71285,59894,PRETRIAL,WHIPPLE,ADRIAN,MARNEL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,4,High,8,Risk of Recidivism,0.39,9,High,Copy,1,0 +9264,71285,59894,PRETRIAL,WHIPPLE,ADRIAN,MARNEL,Male,African-American,01/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,4,High,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +62002,71278,64622,PRETRIAL,MATTOCKS,KENYETTA,NULL,Male,African-American,03/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/16/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +62002,71278,64622,PRETRIAL,MATTOCKS,KENYETTA,NULL,Male,African-American,03/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/16/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +62002,71278,64622,PRETRIAL,MATTOCKS,KENYETTA,NULL,Male,African-American,03/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62000,71276,64620,PRETRIAL,GARCIA,LUIS,A,Male,Caucasian,12/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +62000,71276,64620,PRETRIAL,GARCIA,LUIS,A,Male,Caucasian,12/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +62000,71276,64620,PRETRIAL,GARCIA,LUIS,A,Male,Caucasian,12/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62004,71281,64625,PRETRIAL,HARGROVE,DALE,ALLEN,Male,Caucasian,03/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/16/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +62004,71281,64625,PRETRIAL,HARGROVE,DALE,ALLEN,Male,Caucasian,03/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/16/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +62004,71281,64625,PRETRIAL,HARGROVE,DALE,ALLEN,Male,Caucasian,03/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/16/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61995,71273,64617,PRETRIAL,Graham,Jerry,Lewis,Male,African-American,04/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +61995,71273,64617,PRETRIAL,Graham,Jerry,Lewis,Male,African-American,04/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +61995,71273,64617,PRETRIAL,Graham,Jerry,Lewis,Male,African-American,04/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/16/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62040,71323,64665,Probation,Pierre,Fritz,NULL,Male,African-American,06/11/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +62040,71323,64665,Probation,Pierre,Fritz,NULL,Male,African-American,06/11/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +62040,71323,64665,Probation,Pierre,Fritz,NULL,Male,African-American,06/11/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62056,71341,64683,Probation,mohammed,shazim,NULL,Male,Other,01/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/17/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +62056,71341,64683,Probation,mohammed,shazim,NULL,Male,Other,01/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +62056,71341,64683,Probation,mohammed,shazim,NULL,Male,Other,01/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +30649,71302,64645,PRETRIAL,Hawkins,Robert,NULL,Male,African-American,10/26/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +30649,71302,64645,PRETRIAL,Hawkins,Robert,NULL,Male,African-American,10/26/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +30649,71302,64645,PRETRIAL,Hawkins,Robert,NULL,Male,African-American,10/26/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +41813,71320,64662,PRETRIAL,CruzBrooks,Melinda,NULL,Female,Caucasian,08/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/17/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +41813,71320,64662,PRETRIAL,CruzBrooks,Melinda,NULL,Female,Caucasian,08/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +41813,71320,64662,PRETRIAL,CruzBrooks,Melinda,NULL,Female,Caucasian,08/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +18031,71333,64675,Probation,Holelscher,Sandra,NULL,Female,Caucasian,10/08/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +18031,71333,64675,Probation,Holelscher,Sandra,NULL,Female,Caucasian,10/08/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +18031,71333,64675,Probation,Holelscher,Sandra,NULL,Female,Caucasian,10/08/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +54656,71315,64657,Probation,Reyes,Ryan,NULL,Male,Hispanic,12/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +54656,71315,64657,Probation,Reyes,Ryan,NULL,Male,Hispanic,12/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +54656,71315,64657,Probation,Reyes,Ryan,NULL,Male,Hispanic,12/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62014,71294,64637,PRETRIAL,Aurelus,Jeff,Clifford,Male,African-American,12/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +62014,71294,64637,PRETRIAL,Aurelus,Jeff,Clifford,Male,African-American,12/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +62014,71294,64637,PRETRIAL,Aurelus,Jeff,Clifford,Male,African-American,12/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62046,71328,64670,PRETRIAL,Naville,Larry,NULL,Male,Caucasian,08/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +62046,71328,64670,PRETRIAL,Naville,Larry,NULL,Male,Caucasian,08/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +62046,71328,64670,PRETRIAL,Naville,Larry,NULL,Male,Caucasian,08/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62029,71310,64652,Probation,mullaney,raymond,NULL,Male,Caucasian,09/10/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +62029,71310,64652,Probation,mullaney,raymond,NULL,Male,Caucasian,09/10/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +62029,71310,64652,Probation,mullaney,raymond,NULL,Male,Caucasian,09/10/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62032,71312,64654,Probation,Biscotto,Jessica,NULL,Female,Caucasian,01/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +62032,71312,64654,Probation,Biscotto,Jessica,NULL,Female,Caucasian,01/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +62032,71312,64654,Probation,Biscotto,Jessica,NULL,Female,Caucasian,01/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62043,71325,64667,Probation,JAUNDOOBABB,JOHN,NULL,Male,Other,01/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,New,1,0 +62043,71325,64667,Probation,JAUNDOOBABB,JOHN,NULL,Male,Other,01/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +62043,71325,64667,Probation,JAUNDOOBABB,JOHN,NULL,Male,Other,01/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62017,71297,64640,PRETRIAL,PINKNEY,CHRISTAL,NULL,Female,African-American,11/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +62017,71297,64640,PRETRIAL,PINKNEY,CHRISTAL,NULL,Female,African-American,11/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +62017,71297,64640,PRETRIAL,PINKNEY,CHRISTAL,NULL,Female,African-American,11/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62025,71304,64647,Probation,paez,edgardo,NULL,Male,Hispanic,03/08/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,7,Risk of Violence,-4.27,1,Low,New,1,0 +62025,71304,64647,Probation,paez,edgardo,NULL,Male,Hispanic,03/08/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +62025,71304,64647,Probation,paez,edgardo,NULL,Male,Hispanic,03/08/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62055,71338,64680,Probation,CARSON,TYLER,NULL,Male,Caucasian,05/07/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +62055,71338,64680,Probation,CARSON,TYLER,NULL,Male,Caucasian,05/07/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +62055,71338,64680,Probation,CARSON,TYLER,NULL,Male,Caucasian,05/07/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62036,71317,64659,Probation,Demesa,Sergio,NULL,Male,Hispanic,05/24/41,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +62036,71317,64659,Probation,Demesa,Sergio,NULL,Male,Hispanic,05/24/41,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +62036,71317,64659,Probation,Demesa,Sergio,NULL,Male,Hispanic,05/24/41,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60692,71318,64660,Probation,DOYLE,ISRAEL,L,Male,African-American,12/07/92,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +60692,71318,64660,Probation,DOYLE,ISRAEL,L,Male,African-American,12/07/92,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,7,Medium,New,1,0 +60692,71318,64660,Probation,DOYLE,ISRAEL,L,Male,African-American,12/07/92,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,3,Low,New,1,0 +62011,71289,64632,PRETRIAL,SANCHEZ,JOSUE,DANIEL,Male,Hispanic,08/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62011,71289,64632,PRETRIAL,SANCHEZ,JOSUE,DANIEL,Male,Hispanic,08/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +62011,71289,64632,PRETRIAL,SANCHEZ,JOSUE,DANIEL,Male,Hispanic,08/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62016,71296,64639,PRETRIAL,HARRIS,SHAUNTORIA,NULL,Female,African-American,10/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +62016,71296,64639,PRETRIAL,HARRIS,SHAUNTORIA,NULL,Female,African-American,10/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +62016,71296,64639,PRETRIAL,HARRIS,SHAUNTORIA,NULL,Female,African-American,10/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +11754,71339,64681,PRETRIAL,HALL,CHARLES,NULL,Male,African-American,10/11/43,17,All Scales,Intake,English,Post Sentence,Probation,Widowed,3/17/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +11754,71339,64681,PRETRIAL,HALL,CHARLES,NULL,Male,African-American,10/11/43,17,All Scales,Intake,English,Post Sentence,Probation,Widowed,3/17/14 0:00,1,Low,8,Risk of Recidivism,-0.46,4,Low,New,1,0 +11754,71339,64681,PRETRIAL,HALL,CHARLES,NULL,Male,African-American,10/11/43,17,All Scales,Intake,English,Post Sentence,Probation,Widowed,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +50621,71327,64669,PRETRIAL,CALIXTE,CLARENS,NULL,Male,African-American,05/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +50621,71327,64669,PRETRIAL,CALIXTE,CLARENS,NULL,Male,African-American,05/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +50621,71327,64669,PRETRIAL,CALIXTE,CLARENS,NULL,Male,African-American,05/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +22079,71299,64642,Probation,Mundth,Nancy,J,Female,Caucasian,09/12/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +22079,71299,64642,Probation,Mundth,Nancy,J,Female,Caucasian,09/12/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +22079,71299,64642,Probation,Mundth,Nancy,J,Female,Caucasian,09/12/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62026,71306,64649,Probation,Ellikal,Anthony,Pavlose,Male,Asian,04/17/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/17/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +62026,71306,64649,Probation,Ellikal,Anthony,Pavlose,Male,Asian,04/17/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +62026,71306,64649,Probation,Ellikal,Anthony,Pavlose,Male,Asian,04/17/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62047,71329,64671,Probation,DIAS,TOBIAS,B,Male,Hispanic,10/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +62047,71329,64671,Probation,DIAS,TOBIAS,B,Male,Hispanic,10/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +62047,71329,64671,Probation,DIAS,TOBIAS,B,Male,Hispanic,10/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62053,71336,64678,Probation,Boyne,Owen,NULL,Male,African-American,08/01/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +62053,71336,64678,Probation,Boyne,Owen,NULL,Male,African-American,08/01/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +62053,71336,64678,Probation,Boyne,Owen,NULL,Male,African-American,08/01/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62009,71287,64630,PRETRIAL,CUNNINGHAM,MICHAEL,KEVIN,Male,African-American,02/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +62009,71287,64630,PRETRIAL,CUNNINGHAM,MICHAEL,KEVIN,Male,African-American,02/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +62009,71287,64630,PRETRIAL,CUNNINGHAM,MICHAEL,KEVIN,Male,African-American,02/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62024,71301,64644,Probation,Sandoval,Christian,Eduard,Male,Hispanic,03/19/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +62024,71301,64644,Probation,Sandoval,Christian,Eduard,Male,Hispanic,03/19/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +62024,71301,64644,Probation,Sandoval,Christian,Eduard,Male,Hispanic,03/19/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62051,71334,64676,Probation,PITTMAN,LAVERN,DANICA,Male,African-American,10/29/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +62051,71334,64676,Probation,PITTMAN,LAVERN,DANICA,Male,African-American,10/29/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +62051,71334,64676,Probation,PITTMAN,LAVERN,DANICA,Male,African-American,10/29/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +1118,71292,64635,PRETRIAL,Collins,Oscar,NULL,Male,African-American,03/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +1118,71292,64635,PRETRIAL,Collins,Oscar,NULL,Male,African-American,03/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +1118,71292,64635,PRETRIAL,Collins,Oscar,NULL,Male,African-American,03/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62033,71313,64655,Probation,Perez,Jose,Martinez,Male,Hispanic,07/08/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +62033,71313,64655,Probation,Perez,Jose,Martinez,Male,Hispanic,07/08/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +62033,71313,64655,Probation,Perez,Jose,Martinez,Male,Hispanic,07/08/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58785,71309,61011,Probation,McCoy,Charles,NULL,Male,African-American,11/13/79,17,All Scales,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,New,1,0 +58785,71309,61011,Probation,McCoy,Charles,NULL,Male,African-American,11/13/79,17,All Scales,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +58785,71309,61011,Probation,McCoy,Charles,NULL,Male,African-American,11/13/79,17,All Scales,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +62044,71326,64668,Probation,Richardson,Denise,NULL,Female,African-American,04/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.61,2,Low,New,1,0 +62044,71326,64668,Probation,Richardson,Denise,NULL,Female,African-American,04/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,8,High,New,1,0 +62044,71326,64668,Probation,Richardson,Denise,NULL,Female,African-American,04/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +62010,71288,64631,PRETRIAL,CRUZ,CARLOS,CESAR,Male,Hispanic,09/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +62010,71288,64631,PRETRIAL,CRUZ,CARLOS,CESAR,Male,Hispanic,09/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +62010,71288,64631,PRETRIAL,CRUZ,CARLOS,CESAR,Male,Hispanic,09/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62013,71291,64634,PRETRIAL,SARDINAS,CHRISTINE,NULL,Female,Caucasian,08/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +62013,71291,64634,PRETRIAL,SARDINAS,CHRISTINE,NULL,Female,Caucasian,08/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +62013,71291,64634,PRETRIAL,SARDINAS,CHRISTINE,NULL,Female,Caucasian,08/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +5572,71305,64648,PRETRIAL,SINCLAIR,CHARLES,SAMUEL,Male,African-American,05/01/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +5572,71305,64648,PRETRIAL,SINCLAIR,CHARLES,SAMUEL,Male,African-American,05/01/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.77,10,High,New,1,0 +5572,71305,64648,PRETRIAL,SINCLAIR,CHARLES,SAMUEL,Male,African-American,05/01/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +2733,71293,64636,PRETRIAL,JOHNSON,Patrick,NULL,Male,African-American,10/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +2733,71293,64636,PRETRIAL,JOHNSON,Patrick,NULL,Male,African-American,10/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +2733,71293,64636,PRETRIAL,JOHNSON,Patrick,NULL,Male,African-American,10/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +52321,71342,64684,Probation,Cole,Sandy,NULL,Female,African-American,12/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +52321,71342,64684,Probation,Cole,Sandy,NULL,Female,African-American,12/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +52321,71342,64684,Probation,Cole,Sandy,NULL,Female,African-American,12/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62008,71286,64629,PRETRIAL,BERNARD,LAMAR,DESEAN,Male,African-American,12/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/17/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +62008,71286,64629,PRETRIAL,BERNARD,LAMAR,DESEAN,Male,African-American,12/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +62008,71286,64629,PRETRIAL,BERNARD,LAMAR,DESEAN,Male,African-American,12/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62023,71300,64643,Probation,ivonov,raji,NULL,Female,Caucasian,12/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,2,Medium,7,Risk of Violence,-2.86,2,Low,New,1,0 +62023,71300,64643,Probation,ivonov,raji,NULL,Female,Caucasian,12/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,New,1,0 +62023,71300,64643,Probation,ivonov,raji,NULL,Female,Caucasian,12/02/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62052,71335,64677,Probation,kirby,emily,NULL,Female,Caucasian,09/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +62052,71335,64677,Probation,kirby,emily,NULL,Female,Caucasian,09/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +62052,71335,64677,Probation,kirby,emily,NULL,Female,Caucasian,09/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62027,71307,64650,Probation,MCCREA,SAMUEL,NULL,Male,African-American,05/14/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/17/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +62027,71307,64650,Probation,MCCREA,SAMUEL,NULL,Male,African-American,05/14/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +62027,71307,64650,Probation,MCCREA,SAMUEL,NULL,Male,African-American,05/14/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62034,71314,64656,Probation,WILLIAMS,DAIRELL,IVORY,Male,African-American,01/26/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +62034,71314,64656,Probation,WILLIAMS,DAIRELL,IVORY,Male,African-American,01/26/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +62034,71314,64656,Probation,WILLIAMS,DAIRELL,IVORY,Male,African-American,01/26/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62039,71321,64663,PRETRIAL,WARNER,JUSTIN,NULL,Male,African-American,09/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +62039,71321,64663,PRETRIAL,WARNER,JUSTIN,NULL,Male,African-American,09/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +62039,71321,64663,PRETRIAL,WARNER,JUSTIN,NULL,Male,African-American,09/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56104,71340,64682,PRETRIAL,Boone,Demetrice,Antrod,Male,African-American,03/01/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +56104,71340,64682,PRETRIAL,Boone,Demetrice,Antrod,Male,African-American,03/01/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +56104,71340,64682,PRETRIAL,Boone,Demetrice,Antrod,Male,African-American,03/01/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62015,71295,64638,PRETRIAL,MCMULLIN,PAUL,PAUL,Male,Caucasian,01/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/17/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +62015,71295,64638,PRETRIAL,MCMULLIN,PAUL,PAUL,Male,Caucasian,01/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/17/14 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +62015,71295,64638,PRETRIAL,MCMULLIN,PAUL,PAUL,Male,Caucasian,01/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62050,71332,64674,Probation,Dimas,Jose,Antonio,Male,Hispanic,12/08/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/17/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +62050,71332,64674,Probation,Dimas,Jose,Antonio,Male,Hispanic,12/08/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +62050,71332,64674,Probation,Dimas,Jose,Antonio,Male,Hispanic,12/08/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +20348,71303,64646,PRETRIAL,CLARK,DERRICK,NULL,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,4,High,7,Risk of Violence,-0.68,9,High,New,1,0 +20348,71303,64646,PRETRIAL,CLARK,DERRICK,NULL,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,4,High,8,Risk of Recidivism,0.91,10,High,New,1,0 +20348,71303,64646,PRETRIAL,CLARK,DERRICK,NULL,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62031,71311,64653,PRETRIAL,garcia,maria,NULL,Female,Hispanic,09/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +62031,71311,64653,PRETRIAL,garcia,maria,NULL,Female,Hispanic,09/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +62031,71311,64653,PRETRIAL,garcia,maria,NULL,Female,Hispanic,09/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62012,71290,64633,PRETRIAL,Sucarichi,Jason,NULL,Male,African-American,08/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62012,71290,64633,PRETRIAL,Sucarichi,Jason,NULL,Male,African-American,08/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +62012,71290,64633,PRETRIAL,Sucarichi,Jason,NULL,Male,African-American,08/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62042,71324,64666,Probation,Frawley,Arthur,NULL,Male,Caucasian,05/09/38,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/17/14 0:00,1,Low,7,Risk of Violence,-4.33,1,Low,New,1,0 +62042,71324,64666,Probation,Frawley,Arthur,NULL,Male,Caucasian,05/09/38,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/17/14 0:00,1,Low,8,Risk of Recidivism,-2.61,1,Low,New,1,0 +62042,71324,64666,Probation,Frawley,Arthur,NULL,Male,Caucasian,05/09/38,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62054,71337,64679,Probation,Likhang,Wu,NULL,Male,Oriental,11/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +62054,71337,64679,Probation,Likhang,Wu,NULL,Male,Oriental,11/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +62054,71337,64679,Probation,Likhang,Wu,NULL,Male,Oriental,11/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62018,71298,64641,PRETRIAL,Lane,Kamiyla,Marie,Male,African-American,02/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +62018,71298,64641,PRETRIAL,Lane,Kamiyla,Marie,Male,African-American,02/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +62018,71298,64641,PRETRIAL,Lane,Kamiyla,Marie,Male,African-American,02/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62035,71316,64658,Probation,banks,bernika,NULL,Female,African-American,12/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,2,Medium,7,Risk of Violence,-2.76,2,Low,New,1,0 +62035,71316,64658,Probation,banks,bernika,NULL,Female,African-American,12/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +62035,71316,64658,Probation,banks,bernika,NULL,Female,African-American,12/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/17/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +62076,71366,64707,Probation,Palmer,Stephen,NULL,Male,Caucasian,05/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +62076,71366,64707,Probation,Palmer,Stephen,NULL,Male,Caucasian,05/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +62076,71366,64707,Probation,Palmer,Stephen,NULL,Male,Caucasian,05/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +10282,71345,64687,PRETRIAL,CARRY,NATHANIEL,L,Male,Caucasian,11/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +10282,71345,64687,PRETRIAL,CARRY,NATHANIEL,L,Male,Caucasian,11/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +10282,71345,64687,PRETRIAL,CARRY,NATHANIEL,L,Male,Caucasian,11/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56522,71368,64709,PRETRIAL,Stringer,Samesha,NULL,Female,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +56522,71368,64709,PRETRIAL,Stringer,Samesha,NULL,Female,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +56522,71368,64709,PRETRIAL,Stringer,Samesha,NULL,Female,African-American,08/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +46399,71382,64177,PRETRIAL,Plummer,Mark,NULL,Male,African-American,12/22/93,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +46399,71382,64177,PRETRIAL,Plummer,Mark,NULL,Male,African-American,12/22/93,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,4,High,8,Risk of Recidivism,0.49,9,High,New,1,0 +46399,71382,64177,PRETRIAL,Plummer,Mark,NULL,Male,African-American,12/22/93,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,4,High,18,Risk of Failure to Appear,23,4,Low,New,1,0 +62071,71361,64702,PRETRIAL,Larkins,Xavier,NULL,Male,African-American,11/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/14 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +62071,71361,64702,PRETRIAL,Larkins,Xavier,NULL,Male,African-American,11/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/14 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +62071,71361,64702,PRETRIAL,Larkins,Xavier,NULL,Male,African-American,11/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62081,71376,64717,Broward County,Jackson,Sherry,NULL,Female,Caucasian,11/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/14 0:00,2,Medium,7,Risk of Violence,-2.99,1,Low,New,1,0 +62081,71376,64717,Broward County,Jackson,Sherry,NULL,Female,Caucasian,11/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +62081,71376,64717,Broward County,Jackson,Sherry,NULL,Female,Caucasian,11/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/14 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +62079,71374,64715,Probation,Moralesesquilin,Angel,NULL,Male,Hispanic,07/20/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +62079,71374,64715,Probation,Moralesesquilin,Angel,NULL,Male,Hispanic,07/20/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +62079,71374,64715,Probation,Moralesesquilin,Angel,NULL,Male,Hispanic,07/20/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62059,71344,64686,PRETRIAL,Cruz,Justin,NULL,Male,African-American,07/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +62059,71344,64686,PRETRIAL,Cruz,Justin,NULL,Male,African-American,07/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +62059,71344,64686,PRETRIAL,Cruz,Justin,NULL,Male,African-American,07/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62073,71363,64704,PRETRIAL,kalafos,jordan,NULL,Male,Caucasian,09/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +62073,71363,64704,PRETRIAL,kalafos,jordan,NULL,Male,Caucasian,09/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +62073,71363,64704,PRETRIAL,kalafos,jordan,NULL,Male,Caucasian,09/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +29577,71372,64713,PRETRIAL,Burgoa,Jorge,NULL,Male,Caucasian,02/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +29577,71372,64713,PRETRIAL,Burgoa,Jorge,NULL,Male,Caucasian,02/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +29577,71372,64713,PRETRIAL,Burgoa,Jorge,NULL,Male,Caucasian,02/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62065,71351,64693,PRETRIAL,Grindstaff,Margery,NULL,Female,Caucasian,05/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +62065,71351,64693,PRETRIAL,Grindstaff,Margery,NULL,Female,Caucasian,05/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +62065,71351,64693,PRETRIAL,Grindstaff,Margery,NULL,Female,Caucasian,05/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62061,71347,64689,PRETRIAL,Sevilla,Roberto,Carlos,Male,Hispanic,03/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +62061,71347,64689,PRETRIAL,Sevilla,Roberto,Carlos,Male,Hispanic,03/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +62061,71347,64689,PRETRIAL,Sevilla,Roberto,Carlos,Male,Hispanic,03/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62070,71356,64698,Probation,Kelleher,John,NULL,Male,Caucasian,01/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +62070,71356,64698,Probation,Kelleher,John,NULL,Male,Caucasian,01/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +62070,71356,64698,Probation,Kelleher,John,NULL,Male,Caucasian,01/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +50802,71381,64721,PRETRIAL,Jones,Nathaniel,NULL,Male,African-American,07/04/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +50802,71381,64721,PRETRIAL,Jones,Nathaniel,NULL,Male,African-American,07/04/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +50802,71381,64721,PRETRIAL,Jones,Nathaniel,NULL,Male,African-American,07/04/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62082,71377,64718,Probation,joseph,jerry,NULL,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,3/18/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +62082,71377,64718,Probation,joseph,jerry,NULL,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,3/18/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +62082,71377,64718,Probation,joseph,jerry,NULL,Male,African-American,09/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62058,71343,64685,PRETRIAL,Lynch,Theodore,NULL,Male,African-American,09/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,2,Medium,7,Risk of Violence,-3.15,1,Low,New,1,0 +62058,71343,64685,PRETRIAL,Lynch,Theodore,NULL,Male,African-American,09/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +62058,71343,64685,PRETRIAL,Lynch,Theodore,NULL,Male,African-American,09/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62066,71352,64694,PRETRIAL,Garcia,Lanette,Monique,Female,Caucasian,02/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/18/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +62066,71352,64694,PRETRIAL,Garcia,Lanette,Monique,Female,Caucasian,02/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/18/14 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +62066,71352,64694,PRETRIAL,Garcia,Lanette,Monique,Female,Caucasian,02/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62077,71369,64710,PRETRIAL,Roman,Preston,NULL,Male,Caucasian,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/18/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +62077,71369,64710,PRETRIAL,Roman,Preston,NULL,Male,Caucasian,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +62077,71369,64710,PRETRIAL,Roman,Preston,NULL,Male,Caucasian,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/18/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62062,71348,64690,PRETRIAL,Hyacinth,Jennifer,NULL,Female,African-American,08/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +62062,71348,64690,PRETRIAL,Hyacinth,Jennifer,NULL,Female,African-American,08/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +62062,71348,64690,PRETRIAL,Hyacinth,Jennifer,NULL,Female,African-American,08/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62069,71355,64697,PRETRIAL,ROBERTS,JEROME,W,Male,African-American,08/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +62069,71355,64697,PRETRIAL,ROBERTS,JEROME,W,Male,African-American,08/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +62069,71355,64697,PRETRIAL,ROBERTS,JEROME,W,Male,African-American,08/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62080,71373,64714,Probation,Vallejo,Alexa,NULL,Female,Hispanic,07/24/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +62080,71373,64714,Probation,Vallejo,Alexa,NULL,Female,Hispanic,07/24/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +62080,71373,64714,Probation,Vallejo,Alexa,NULL,Female,Hispanic,07/24/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62064,71350,64692,PRETRIAL,Reynoso,Justin,Caleb,Male,Caucasian,03/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +62064,71350,64692,PRETRIAL,Reynoso,Justin,Caleb,Male,Caucasian,03/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +62064,71350,64692,PRETRIAL,Reynoso,Justin,Caleb,Male,Caucasian,03/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +55433,71357,64699,Probation,michelin,donald,NULL,Male,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +55433,71357,64699,Probation,michelin,donald,NULL,Male,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +55433,71357,64699,Probation,michelin,donald,NULL,Male,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +42300,71364,64705,PRETRIAL,JIMENEZ,ITZAMNA,S,Male,Caucasian,11/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,New,1,0 +42300,71364,64705,PRETRIAL,JIMENEZ,ITZAMNA,S,Male,Caucasian,11/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +42300,71364,64705,PRETRIAL,JIMENEZ,ITZAMNA,S,Male,Caucasian,11/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62078,71371,64712,Probation,valentine,veronica,NULL,Female,Caucasian,08/01/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/18/14 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +62078,71371,64712,Probation,valentine,veronica,NULL,Female,Caucasian,08/01/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/18/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +62078,71371,64712,Probation,valentine,veronica,NULL,Female,Caucasian,08/01/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +48684,71378,56044,PRETRIAL,Oneal,Chaslin,NULL,Female,African-American,11/17/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,Copy,1,0 +48684,71378,56044,PRETRIAL,Oneal,Chaslin,NULL,Female,African-American,11/17/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,8,High,Copy,1,0 +48684,71378,56044,PRETRIAL,Oneal,Chaslin,NULL,Female,African-American,11/17/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +62060,71346,64688,PRETRIAL,RAPHEL,ROBERT,E,Male,African-American,07/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +62060,71346,64688,PRETRIAL,RAPHEL,ROBERT,E,Male,African-American,07/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +62060,71346,64688,PRETRIAL,RAPHEL,ROBERT,E,Male,African-American,07/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +30211,71359,64700,PRETRIAL,rodriguez,jamie,NULL,Male,Hispanic,07/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +30211,71359,64700,PRETRIAL,rodriguez,jamie,NULL,Male,Hispanic,07/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +30211,71359,64700,PRETRIAL,rodriguez,jamie,NULL,Male,Hispanic,07/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62072,71362,64703,Probation,Moreno,Oscar,NULL,Male,Hispanic,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +62072,71362,64703,Probation,Moreno,Oscar,NULL,Male,Hispanic,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +62072,71362,64703,Probation,Moreno,Oscar,NULL,Male,Hispanic,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54837,71375,64716,PRETRIAL,PEDERSEN,SEAN,NULL,Male,Caucasian,01/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.31,7,Medium,New,1,0 +54837,71375,64716,PRETRIAL,PEDERSEN,SEAN,NULL,Male,Caucasian,01/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +54837,71375,64716,PRETRIAL,PEDERSEN,SEAN,NULL,Male,Caucasian,01/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62063,71349,64691,PRETRIAL,Burburan,Ella,NULL,Female,Caucasian,05/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +62063,71349,64691,PRETRIAL,Burburan,Ella,NULL,Female,Caucasian,05/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +62063,71349,64691,PRETRIAL,Burburan,Ella,NULL,Female,Caucasian,05/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62068,71354,64696,PRETRIAL,LOAIZA,VICTOR,JR,Male,Caucasian,05/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +62068,71354,64696,PRETRIAL,LOAIZA,VICTOR,JR,Male,Caucasian,05/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +62068,71354,64696,PRETRIAL,LOAIZA,VICTOR,JR,Male,Caucasian,05/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +26237,71383,64722,Probation,Ellis,kristi,NULL,Female,Caucasian,01/05/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/18/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +26237,71383,64722,Probation,Ellis,kristi,NULL,Female,Caucasian,01/05/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/18/14 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +26237,71383,64722,Probation,Ellis,kristi,NULL,Female,Caucasian,01/05/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56528,71370,64711,PRETRIAL,KOURY,SAMUEL,JUDE,Male,Caucasian,01/01/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +56528,71370,64711,PRETRIAL,KOURY,SAMUEL,JUDE,Male,Caucasian,01/01/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +56528,71370,64711,PRETRIAL,KOURY,SAMUEL,JUDE,Male,Caucasian,01/01/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/18/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +44511,71380,64720,PRETRIAL,Tagariello,Tony,NULL,Male,Caucasian,07/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.44,3,Low,New,1,0 +44511,71380,64720,PRETRIAL,Tagariello,Tony,NULL,Male,Caucasian,07/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +44511,71380,64720,PRETRIAL,Tagariello,Tony,NULL,Male,Caucasian,07/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +62090,71391,64729,PRETRIAL,Singletary,Josha,Bionca,Female,African-American,07/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/19/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +62090,71391,64729,PRETRIAL,Singletary,Josha,Bionca,Female,African-American,07/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/19/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +62090,71391,64729,PRETRIAL,Singletary,Josha,Bionca,Female,African-American,07/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +46254,71401,64739,PRETRIAL,Gallagher,Patrick,NULL,Male,Caucasian,08/27/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +46254,71401,64739,PRETRIAL,Gallagher,Patrick,NULL,Male,Caucasian,08/27/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +46254,71401,64739,PRETRIAL,Gallagher,Patrick,NULL,Male,Caucasian,08/27/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62087,71388,64726,PRETRIAL,Lenworth,Litherland,NULL,Male,African-American,10/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +62087,71388,64726,PRETRIAL,Lenworth,Litherland,NULL,Male,African-American,10/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +62087,71388,64726,PRETRIAL,Lenworth,Litherland,NULL,Male,African-American,10/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62106,71409,64747,Probation,Perez,Jonathan,NULL,Male,Hispanic,03/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +62106,71409,64747,Probation,Perez,Jonathan,NULL,Male,Hispanic,03/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +62106,71409,64747,Probation,Perez,Jonathan,NULL,Male,Hispanic,03/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62108,71412,64750,Probation,Cruz,Osbel,NULL,Male,Hispanic,10/04/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +62108,71412,64750,Probation,Cruz,Osbel,NULL,Male,Hispanic,10/04/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +62108,71412,64750,Probation,Cruz,Osbel,NULL,Male,Hispanic,10/04/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62094,71396,64734,Probation,hernandez,Hector,NULL,Male,Hispanic,07/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/19/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +62094,71396,64734,Probation,hernandez,Hector,NULL,Male,Hispanic,07/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/19/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +62094,71396,64734,Probation,hernandez,Hector,NULL,Male,Hispanic,07/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53223,71417,64754,PRETRIAL,Bartron,Darren,NULL,Male,Caucasian,12/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +53223,71417,64754,PRETRIAL,Bartron,Darren,NULL,Male,Caucasian,12/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +53223,71417,64754,PRETRIAL,Bartron,Darren,NULL,Male,Caucasian,12/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62103,71406,64744,Probation,knox,Jeremy,Daniel,Male,Caucasian,02/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/19/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +62103,71406,64744,Probation,knox,Jeremy,Daniel,Male,Caucasian,02/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/19/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +62103,71406,64744,Probation,knox,Jeremy,Daniel,Male,Caucasian,02/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62105,71408,64746,Probation,Persaud,Devon,NULL,Male,African-American,07/25/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +62105,71408,64746,Probation,Persaud,Devon,NULL,Male,African-American,07/25/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +62105,71408,64746,Probation,Persaud,Devon,NULL,Male,African-American,07/25/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61731,71385,64723,PRETRIAL,Peteron,Lewantarius,NULL,Male,African-American,06/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +61731,71385,64723,PRETRIAL,Peteron,Lewantarius,NULL,Male,African-American,06/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +61731,71385,64723,PRETRIAL,Peteron,Lewantarius,NULL,Male,African-American,06/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +62113,71420,64757,PRETRIAL,JIMENEZ,NANCY,NULL,Female,Hispanic,08/06/75,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/19/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +62113,71420,64757,PRETRIAL,JIMENEZ,NANCY,NULL,Female,Hispanic,08/06/75,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/19/14 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +62113,71420,64757,PRETRIAL,JIMENEZ,NANCY,NULL,Female,Hispanic,08/06/75,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62092,71394,64732,Probation,Teicher,Justin,Holland,Male,Caucasian,06/19/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +62092,71394,64732,Probation,Teicher,Justin,Holland,Male,Caucasian,06/19/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +62092,71394,64732,Probation,Teicher,Justin,Holland,Male,Caucasian,06/19/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62107,71411,64749,Probation,caparelli,ashley,NULL,Female,Caucasian,11/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,3/19/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +62107,71411,64749,Probation,caparelli,ashley,NULL,Female,Caucasian,11/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,3/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,7,Medium,New,1,0 +62107,71411,64749,Probation,caparelli,ashley,NULL,Female,Caucasian,11/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,3/19/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62088,71390,64728,PRETRIAL,PUGLIA,EDGAR,FRANCISCO,Male,Caucasian,03/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/19/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +62088,71390,64728,PRETRIAL,PUGLIA,EDGAR,FRANCISCO,Male,Caucasian,03/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/19/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +62088,71390,64728,PRETRIAL,PUGLIA,EDGAR,FRANCISCO,Male,Caucasian,03/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62109,71415,64753,Probation,Villalobos,Liliana,NULL,Female,Hispanic,01/31/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +62109,71415,64753,Probation,Villalobos,Liliana,NULL,Female,Hispanic,01/31/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +62109,71415,64753,Probation,Villalobos,Liliana,NULL,Female,Hispanic,01/31/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62100,71402,64740,PRETRIAL,Gordon,Tanya,NULL,Female,Caucasian,09/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/19/14 0:00,2,Medium,7,Risk of Violence,-2.89,2,Low,New,1,0 +62100,71402,64740,PRETRIAL,Gordon,Tanya,NULL,Female,Caucasian,09/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +62100,71402,64740,PRETRIAL,Gordon,Tanya,NULL,Female,Caucasian,09/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/19/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62111,71419,64756,Probation,UPBIN,BARRY,NULL,Male,Caucasian,05/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +62111,71419,64756,Probation,UPBIN,BARRY,NULL,Male,Caucasian,05/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +62111,71419,64756,Probation,UPBIN,BARRY,NULL,Male,Caucasian,05/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62099,71398,64736,PRETRIAL,Banks,Kirkland,NULL,Male,African-American,02/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +62099,71398,64736,PRETRIAL,Banks,Kirkland,NULL,Male,African-American,02/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +62099,71398,64736,PRETRIAL,Banks,Kirkland,NULL,Male,African-American,02/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +29099,71416,54372,PRETRIAL,Carswell,Ellis,NULL,Male,African-American,08/22/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,Copy,1,0 +29099,71416,54372,PRETRIAL,Carswell,Ellis,NULL,Male,African-American,08/22/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,Copy,1,0 +29099,71416,54372,PRETRIAL,Carswell,Ellis,NULL,Male,African-American,08/22/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +62091,71393,64731,Probation,brham,marlon,NULL,Male,Hispanic,06/29/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +62091,71393,64731,Probation,brham,marlon,NULL,Male,Hispanic,06/29/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +62091,71393,64731,Probation,brham,marlon,NULL,Male,Hispanic,06/29/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62085,71386,64724,PRETRIAL,Raffa,Robert,NULL,Male,Caucasian,05/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,2,Medium,7,Risk of Violence,-1.35,7,Medium,New,1,0 +62085,71386,64724,PRETRIAL,Raffa,Robert,NULL,Male,Caucasian,05/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +62085,71386,64724,PRETRIAL,Raffa,Robert,NULL,Male,Caucasian,05/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +19520,71400,64738,PRETRIAL,HENFIELD,MICHAEL,NULL,Male,African-American,08/28/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +19520,71400,64738,PRETRIAL,HENFIELD,MICHAEL,NULL,Male,African-American,08/28/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +19520,71400,64738,PRETRIAL,HENFIELD,MICHAEL,NULL,Male,African-American,08/28/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +9124,71397,64735,PRETRIAL,harned,jay,NULL,Male,Caucasian,09/09/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/14 0:00,1,Low,7,Risk of Violence,-4.34,1,Low,New,1,0 +9124,71397,64735,PRETRIAL,harned,jay,NULL,Male,Caucasian,09/09/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/14 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +9124,71397,64735,PRETRIAL,harned,jay,NULL,Male,Caucasian,09/09/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62093,71395,64733,Probation,Whiteleather,Daniel,NULL,Male,Caucasian,05/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/19/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +62093,71395,64733,Probation,Whiteleather,Daniel,NULL,Male,Caucasian,05/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/19/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +62093,71395,64733,Probation,Whiteleather,Daniel,NULL,Male,Caucasian,05/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56726,71410,64748,PRETRIAL,Rose,Robert,NULL,Male,Caucasian,07/24/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +56726,71410,64748,PRETRIAL,Rose,Robert,NULL,Male,Caucasian,07/24/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +56726,71410,64748,PRETRIAL,Rose,Robert,NULL,Male,Caucasian,07/24/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +28258,71389,64727,PRETRIAL,Mcfadden,John,NULL,Male,African-American,01/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +28258,71389,64727,PRETRIAL,Mcfadden,John,NULL,Male,African-American,01/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +28258,71389,64727,PRETRIAL,Mcfadden,John,NULL,Male,African-American,01/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,4,High,18,Risk of Failure to Appear,38,10,High,New,1,0 +62101,71403,64741,Probation,Jenkins,Deandre,NULL,Male,African-American,01/02/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +62101,71403,64741,Probation,Jenkins,Deandre,NULL,Male,African-American,01/02/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +62101,71403,64741,Probation,Jenkins,Deandre,NULL,Male,African-American,01/02/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62112,71418,64755,PRETRIAL,Hutton,David,NULL,Male,Caucasian,01/22/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/19/14 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +62112,71418,64755,PRETRIAL,Hutton,David,NULL,Male,Caucasian,01/22/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/19/14 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +62112,71418,64755,PRETRIAL,Hutton,David,NULL,Male,Caucasian,01/22/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +10620,71413,64751,PRETRIAL,LIPPELT,MICHAEL,NULL,Male,Caucasian,10/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.12,4,Low,New,1,0 +10620,71413,64751,PRETRIAL,LIPPELT,MICHAEL,NULL,Male,Caucasian,10/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +10620,71413,64751,PRETRIAL,LIPPELT,MICHAEL,NULL,Male,Caucasian,10/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +56152,71405,64743,PRETRIAL,KING,JARAH,NULL,Female,African-American,03/11/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/19/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +56152,71405,64743,PRETRIAL,KING,JARAH,NULL,Female,African-American,03/11/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/19/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +56152,71405,64743,PRETRIAL,KING,JARAH,NULL,Female,African-American,03/11/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +53367,71384,54839,PRETRIAL,Grajales,Fermin,NULL,Male,Hispanic,10/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,Copy,1,0 +53367,71384,54839,PRETRIAL,Grajales,Fermin,NULL,Male,Hispanic,10/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,Copy,1,0 +53367,71384,54839,PRETRIAL,Grajales,Fermin,NULL,Male,Hispanic,10/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +62086,71387,64725,PRETRIAL,Belancourt,Piterson,NULL,Male,Other,04/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +62086,71387,64725,PRETRIAL,Belancourt,Piterson,NULL,Male,Other,04/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +62086,71387,64725,PRETRIAL,Belancourt,Piterson,NULL,Male,Other,04/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62126,71434,64771,PRETRIAL,osby,patrick,NULL,Male,African-American,08/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +62126,71434,64771,PRETRIAL,osby,patrick,NULL,Male,African-American,08/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +62126,71434,64771,PRETRIAL,osby,patrick,NULL,Male,African-American,08/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62138,71452,64785,PRETRIAL,DORRIETY,AREEJ,MOHAMMAD,Female,African-American,07/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +62138,71452,64785,PRETRIAL,DORRIETY,AREEJ,MOHAMMAD,Female,African-American,07/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +62138,71452,64785,PRETRIAL,DORRIETY,AREEJ,MOHAMMAD,Female,African-American,07/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62142,71455,64787,Probation,SADA,ROGER,NULL,Male,Caucasian,12/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +62142,71455,64787,Probation,SADA,ROGER,NULL,Male,Caucasian,12/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +62142,71455,64787,Probation,SADA,ROGER,NULL,Male,Caucasian,12/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +24787,71473,64805,PRETRIAL,HICKS,KIMYONNA,NULL,Female,African-American,02/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +24787,71473,64805,PRETRIAL,HICKS,KIMYONNA,NULL,Female,African-American,02/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,8,High,New,1,0 +24787,71473,64805,PRETRIAL,HICKS,KIMYONNA,NULL,Female,African-American,02/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62137,71447,64782,Probation,Woodfill,Jimmy,NULL,Male,Caucasian,09/09/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +62137,71447,64782,Probation,Woodfill,Jimmy,NULL,Male,Caucasian,09/09/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +62137,71447,64782,Probation,Woodfill,Jimmy,NULL,Male,Caucasian,09/09/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62119,71426,64763,PRETRIAL,DAAL,GIUSEPPE,NULL,Male,Caucasian,04/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +62119,71426,64763,PRETRIAL,DAAL,GIUSEPPE,NULL,Male,Caucasian,04/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +62119,71426,64763,PRETRIAL,DAAL,GIUSEPPE,NULL,Male,Caucasian,04/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62146,71460,64792,Probation,Brown,Kathleen,Sawyer,Female,Caucasian,11/10/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/20/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +62146,71460,64792,Probation,Brown,Kathleen,Sawyer,Female,Caucasian,11/10/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +62146,71460,64792,Probation,Brown,Kathleen,Sawyer,Female,Caucasian,11/10/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62067,71353,64695,PRETRIAL,CAMPBELL,KAMELEA,NULL,Female,African-American,03/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +62067,71353,64695,PRETRIAL,CAMPBELL,KAMELEA,NULL,Female,African-American,03/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +62067,71353,64695,PRETRIAL,CAMPBELL,KAMELEA,NULL,Female,African-American,03/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62123,71431,64768,PRETRIAL,McClellan,Olivia,Dawn,Female,Caucasian,07/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +62123,71431,64768,PRETRIAL,McClellan,Olivia,Dawn,Female,Caucasian,07/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +62123,71431,64768,PRETRIAL,McClellan,Olivia,Dawn,Female,Caucasian,07/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62127,71435,64772,PRETRIAL,WEINER,BRANDON,NULL,Male,Caucasian,02/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +62127,71435,64772,PRETRIAL,WEINER,BRANDON,NULL,Male,Caucasian,02/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +62127,71435,64772,PRETRIAL,WEINER,BRANDON,NULL,Male,Caucasian,02/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62114,71421,64758,PRETRIAL,Saint-Geraud,Rosario,NULL,Male,African-American,03/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.66,2,Low,New,1,0 +62114,71421,64758,PRETRIAL,Saint-Geraud,Rosario,NULL,Male,African-American,03/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +62114,71421,64758,PRETRIAL,Saint-Geraud,Rosario,NULL,Male,African-American,03/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62132,71442,64777,Probation,Lamoree,Christopher,NULL,Male,Caucasian,05/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +62132,71442,64777,Probation,Lamoree,Christopher,NULL,Male,Caucasian,05/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +62132,71442,64777,Probation,Lamoree,Christopher,NULL,Male,Caucasian,05/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62134,71444,64779,Probation,Izzo,Brenda,Sue,Female,Caucasian,06/30/70,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/20/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +62134,71444,64779,Probation,Izzo,Brenda,Sue,Female,Caucasian,06/30/70,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +62134,71444,64779,Probation,Izzo,Brenda,Sue,Female,Caucasian,06/30/70,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62149,71463,64795,Probation,Arthur,kelsey,NULL,Male,African-American,09/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62149,71463,64795,Probation,Arthur,kelsey,NULL,Male,African-American,09/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +62149,71463,64795,Probation,Arthur,kelsey,NULL,Male,African-American,09/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +62151,71465,64797,Probation,avila,jorge,NULL,Male,Hispanic,01/03/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/20/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +62151,71465,64797,Probation,avila,jorge,NULL,Male,Hispanic,01/03/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +62151,71465,64797,Probation,avila,jorge,NULL,Male,Hispanic,01/03/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62156,71472,64804,Probation,Warner,Gary,NULL,Male,Caucasian,08/03/57,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/20/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +62156,71472,64804,Probation,Warner,Gary,NULL,Male,Caucasian,08/03/57,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +62156,71472,64804,Probation,Warner,Gary,NULL,Male,Caucasian,08/03/57,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62116,71423,64760,PRETRIAL,Jackson,Janiqua,NULL,Female,African-American,09/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +62116,71423,64760,PRETRIAL,Jackson,Janiqua,NULL,Female,African-American,09/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +62116,71423,64760,PRETRIAL,Jackson,Janiqua,NULL,Female,African-American,09/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +14476,71437,13851,Probation,WIGGINS,JEREMY,NULL,Male,African-American,12/03/77,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/14 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +14476,71437,13851,Probation,WIGGINS,JEREMY,NULL,Male,African-American,12/03/77,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/14 0:00,4,High,8,Risk of Recidivism,0.36,8,High,New,1,0 +14476,71437,13851,Probation,WIGGINS,JEREMY,NULL,Male,African-American,12/03/77,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/14 0:00,4,High,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +62154,71470,64802,PRETRIAL,Pettigrew,Paul,NULL,Male,Caucasian,08/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/14 0:00,4,High,7,Risk of Violence,-0.97,9,High,New,1,0 +62154,71470,64802,PRETRIAL,Pettigrew,Paul,NULL,Male,Caucasian,08/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/14 0:00,4,High,8,Risk of Recidivism,0.39,9,High,New,1,0 +62154,71470,64802,PRETRIAL,Pettigrew,Paul,NULL,Male,Caucasian,08/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/14 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +19384,71428,64765,Probation,LEWIS,NICOLE,NULL,Female,African-American,12/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +19384,71428,64765,Probation,LEWIS,NICOLE,NULL,Female,African-American,12/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +19384,71428,64765,Probation,LEWIS,NICOLE,NULL,Female,African-American,12/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62067,71449,64695,PRETRIAL,CAMPBELL,KAMELEA,NULL,Female,African-American,03/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,Copy,1,0 +62067,71449,64695,PRETRIAL,CAMPBELL,KAMELEA,NULL,Female,African-American,03/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,Copy,1,0 +62067,71449,64695,PRETRIAL,CAMPBELL,KAMELEA,NULL,Female,African-American,03/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +62144,71458,64790,Probation,maceo,maria,NULL,Female,Hispanic,10/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/20/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +62144,71458,64790,Probation,maceo,maria,NULL,Female,Hispanic,10/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +62144,71458,64790,Probation,maceo,maria,NULL,Female,Hispanic,10/08/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62117,71424,64761,PRETRIAL,Cabrera,Sussan,NULL,Female,Hispanic,09/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +62117,71424,64761,PRETRIAL,Cabrera,Sussan,NULL,Female,Hispanic,09/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +62117,71424,64761,PRETRIAL,Cabrera,Sussan,NULL,Female,Hispanic,09/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62135,71445,64780,PRETRIAL,Knosblach,Sarah,Marie,Female,Caucasian,10/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/20/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +62135,71445,64780,PRETRIAL,Knosblach,Sarah,Marie,Female,Caucasian,10/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +62135,71445,64780,PRETRIAL,Knosblach,Sarah,Marie,Female,Caucasian,10/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62131,71441,64776,Probation,Caiafa,Anthony,NULL,Male,Caucasian,05/15/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +62131,71441,64776,Probation,Caiafa,Anthony,NULL,Male,Caucasian,05/15/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +62131,71441,64776,Probation,Caiafa,Anthony,NULL,Male,Caucasian,05/15/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +1559,71466,64798,PRETRIAL,tucker,eugene,NULL,Male,African-American,11/11/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,3/20/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +1559,71466,64798,PRETRIAL,tucker,eugene,NULL,Male,African-American,11/11/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +1559,71466,64798,PRETRIAL,tucker,eugene,NULL,Male,African-American,11/11/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +62143,71457,64789,Probation,torres,Eugenio,Jose,Male,Hispanic,03/13/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +62143,71457,64789,Probation,torres,Eugenio,Jose,Male,Hispanic,03/13/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +62143,71457,64789,Probation,torres,Eugenio,Jose,Male,Hispanic,03/13/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62150,71464,64796,Probation,cha,Dong,Ho,Male,Asian,12/26/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/20/14 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +62150,71464,64796,Probation,cha,Dong,Ho,Male,Asian,12/26/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +62150,71464,64796,Probation,cha,Dong,Ho,Male,Asian,12/26/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62155,71471,64803,Probation,Calixte,Yougens,NULL,Male,African-American,06/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,2,Medium,7,Risk of Violence,-2.87,2,Low,New,1,0 +62155,71471,64803,Probation,Calixte,Yougens,NULL,Male,African-American,06/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +62155,71471,64803,Probation,Calixte,Yougens,NULL,Male,African-American,06/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62120,71427,64764,PRETRIAL,Brown,Princess,Monlikea,Female,African-American,10/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +62120,71427,64764,PRETRIAL,Brown,Princess,Monlikea,Female,African-American,10/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +62120,71427,64764,PRETRIAL,Brown,Princess,Monlikea,Female,African-American,10/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62121,71429,64766,PRETRIAL,DUVIGNAUD,SAMANTHA,NULL,Female,African-American,05/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +62121,71429,64766,PRETRIAL,DUVIGNAUD,SAMANTHA,NULL,Female,African-American,05/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +62121,71429,64766,PRETRIAL,DUVIGNAUD,SAMANTHA,NULL,Female,African-American,05/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62141,71453,64786,PRETRIAL,NAVARRO,ANGEL,JESUS,Male,Caucasian,10/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +62141,71453,64786,PRETRIAL,NAVARRO,ANGEL,JESUS,Male,Caucasian,10/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +62141,71453,64786,PRETRIAL,NAVARRO,ANGEL,JESUS,Male,Caucasian,10/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62152,71467,64799,Probation,jules,gilbert,NULL,Male,African-American,12/17/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/20/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +62152,71467,64799,Probation,jules,gilbert,NULL,Male,African-American,12/17/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +62152,71467,64799,Probation,jules,gilbert,NULL,Male,African-American,12/17/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62124,71432,64769,PRETRIAL,Taylor,Gregory,NULL,Male,African-American,02/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +62124,71432,64769,PRETRIAL,Taylor,Gregory,NULL,Male,African-American,02/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +62124,71432,64769,PRETRIAL,Taylor,Gregory,NULL,Male,African-American,02/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62136,71446,64781,PRETRIAL,Walker,Michael,NULL,Male,African-American,09/22/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/20/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +62136,71446,64781,PRETRIAL,Walker,Michael,NULL,Male,African-American,09/22/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +62136,71446,64781,PRETRIAL,Walker,Michael,NULL,Male,African-American,09/22/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51051,71475,64807,Probation,Robinson,Rudolph,NULL,Male,African-American,12/08/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +51051,71475,64807,Probation,Robinson,Rudolph,NULL,Male,African-American,12/08/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +51051,71475,64807,Probation,Robinson,Rudolph,NULL,Male,African-American,12/08/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62118,71425,64762,PRETRIAL,BROWNLEE,TANIKA,LATRICIA,Female,African-American,11/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +62118,71425,64762,PRETRIAL,BROWNLEE,TANIKA,LATRICIA,Female,African-American,11/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +62118,71425,64762,PRETRIAL,BROWNLEE,TANIKA,LATRICIA,Female,African-American,11/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62145,71459,64791,Probation,Vincent,Rilet,NULL,Male,African-American,02/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +62145,71459,64791,Probation,Vincent,Rilet,NULL,Male,African-American,02/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +62145,71459,64791,Probation,Vincent,Rilet,NULL,Male,African-American,02/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62147,71461,64793,PRETRIAL,Mckenzie,Jonathon,NULL,Male,Caucasian,10/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +62147,71461,64793,PRETRIAL,Mckenzie,Jonathon,NULL,Male,Caucasian,10/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +62147,71461,64793,PRETRIAL,Mckenzie,Jonathon,NULL,Male,Caucasian,10/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62125,71433,64770,PRETRIAL,Hervin,Ronnie,NULL,Male,African-American,10/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +62125,71433,64770,PRETRIAL,Hervin,Ronnie,NULL,Male,African-American,10/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +62125,71433,64770,PRETRIAL,Hervin,Ronnie,NULL,Male,African-American,10/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62157,71474,64806,Probation,Shiloh,Gordon,NULL,Male,Caucasian,04/17/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/20/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +62157,71474,64806,Probation,Shiloh,Gordon,NULL,Male,Caucasian,04/17/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +62157,71474,64806,Probation,Shiloh,Gordon,NULL,Male,Caucasian,04/17/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,38,10,High,New,1,0 +62115,71422,64759,PRETRIAL,HOWELL,JASON,NULL,Male,African-American,02/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +62115,71422,64759,PRETRIAL,HOWELL,JASON,NULL,Male,African-American,02/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +62115,71422,64759,PRETRIAL,HOWELL,JASON,NULL,Male,African-American,02/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62140,71451,64784,PRETRIAL,Curry,Carlos,NULL,Female,Caucasian,09/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +62140,71451,64784,PRETRIAL,Curry,Carlos,NULL,Female,Caucasian,09/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +62140,71451,64784,PRETRIAL,Curry,Carlos,NULL,Female,Caucasian,09/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +7834,71469,64801,PRETRIAL,SANTIAGO,EUGENE,JAVIE,Male,Hispanic,08/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +7834,71469,64801,PRETRIAL,SANTIAGO,EUGENE,JAVIE,Male,Hispanic,08/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,4,High,8,Risk of Recidivism,1.22,10,High,New,1,0 +7834,71469,64801,PRETRIAL,SANTIAGO,EUGENE,JAVIE,Male,Hispanic,08/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/20/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62122,71430,64767,PRETRIAL,Viera,Laura,NULL,Male,Caucasian,01/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +62122,71430,64767,PRETRIAL,Viera,Laura,NULL,Male,Caucasian,01/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +62122,71430,64767,PRETRIAL,Viera,Laura,NULL,Male,Caucasian,01/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62174,71498,64828,Probation,rafferty,cornelius,NULL,Male,Caucasian,06/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +62174,71498,64828,Probation,rafferty,cornelius,NULL,Male,Caucasian,06/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +62174,71498,64828,Probation,rafferty,cornelius,NULL,Male,Caucasian,06/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56433,71490,64820,PRETRIAL,shaw,William,Ralph,Male,Caucasian,05/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +56433,71490,64820,PRETRIAL,shaw,William,Ralph,Male,Caucasian,05/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +56433,71490,64820,PRETRIAL,shaw,William,Ralph,Male,Caucasian,05/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +62158,71477,64808,PRETRIAL,Monroe,Rodney,NULL,Male,African-American,12/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +62158,71477,64808,PRETRIAL,Monroe,Rodney,NULL,Male,African-American,12/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +62158,71477,64808,PRETRIAL,Monroe,Rodney,NULL,Male,African-American,12/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55025,71511,64841,Probation,Charles,Jimmy,NULL,Male,African-American,08/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +55025,71511,64841,Probation,Charles,Jimmy,NULL,Male,African-American,08/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +55025,71511,64841,Probation,Charles,Jimmy,NULL,Male,African-American,08/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62171,71495,64825,Probation,Cochrane,Mark,NULL,Male,Caucasian,05/31/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +62171,71495,64825,Probation,Cochrane,Mark,NULL,Male,Caucasian,05/31/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +62171,71495,64825,Probation,Cochrane,Mark,NULL,Male,Caucasian,05/31/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +32659,71482,64812,PRETRIAL,Skipper,Joseph,Aaron,Male,African-American,11/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +32659,71482,64812,PRETRIAL,Skipper,Joseph,Aaron,Male,African-American,11/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +32659,71482,64812,PRETRIAL,Skipper,Joseph,Aaron,Male,African-American,11/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62179,71503,64833,Probation,murrilloperalta,lester,NULL,Male,Hispanic,11/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +62179,71503,64833,Probation,murrilloperalta,lester,NULL,Male,Hispanic,11/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +62179,71503,64833,Probation,murrilloperalta,lester,NULL,Male,Hispanic,11/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62159,71478,64809,PRETRIAL,Disdiel,Eric,NULL,Male,Caucasian,11/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +62159,71478,64809,PRETRIAL,Disdiel,Eric,NULL,Male,Caucasian,11/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +62159,71478,64809,PRETRIAL,Disdiel,Eric,NULL,Male,Caucasian,11/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62175,71499,64829,Probation,Rhodes,Jay,NULL,Male,Caucasian,04/04/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-4.54,1,Low,New,1,0 +62175,71499,64829,Probation,Rhodes,Jay,NULL,Male,Caucasian,04/04/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-2.76,1,Low,New,1,0 +62175,71499,64829,Probation,Rhodes,Jay,NULL,Male,Caucasian,04/04/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62181,71506,64836,PRETRIAL,CAMPBELL,SHIVAUGHN,NULL,Male,African-American,09/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +62181,71506,64836,PRETRIAL,CAMPBELL,SHIVAUGHN,NULL,Male,African-American,09/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +62181,71506,64836,PRETRIAL,CAMPBELL,SHIVAUGHN,NULL,Male,African-American,09/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +40788,71508,64838,PRETRIAL,HARRIS,DONTAI,NULL,Male,African-American,08/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +40788,71508,64838,PRETRIAL,HARRIS,DONTAI,NULL,Male,African-American,08/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,New,1,0 +40788,71508,64838,PRETRIAL,HARRIS,DONTAI,NULL,Male,African-American,08/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62163,71485,64815,PRETRIAL,karamolengos,michael,NULL,Male,Caucasian,01/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +62163,71485,64815,PRETRIAL,karamolengos,michael,NULL,Male,Caucasian,01/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +62163,71485,64815,PRETRIAL,karamolengos,michael,NULL,Male,Caucasian,01/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59552,71480,61901,PRETRIAL,Perez-Cuyuch,Eugenio,Jehu,Male,Hispanic,02/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,Copy,1,0 +59552,71480,61901,PRETRIAL,Perez-Cuyuch,Eugenio,Jehu,Male,Hispanic,02/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,Copy,1,0 +59552,71480,61901,PRETRIAL,Perez-Cuyuch,Eugenio,Jehu,Male,Hispanic,02/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +62177,71501,64831,PRETRIAL,CARLTON,HEATHER,NULL,Female,Caucasian,02/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +62177,71501,64831,PRETRIAL,CARLTON,HEATHER,NULL,Female,Caucasian,02/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,7,Medium,New,1,0 +62177,71501,64831,PRETRIAL,CARLTON,HEATHER,NULL,Female,Caucasian,02/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62168,71492,64822,Probation,Ciriello,Debra,NULL,Female,Hispanic,07/14/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/14 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +62168,71492,64822,Probation,Ciriello,Debra,NULL,Female,Hispanic,07/14/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +62168,71492,64822,Probation,Ciriello,Debra,NULL,Female,Hispanic,07/14/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62161,71483,64813,PRETRIAL,Twensey,Shanard,Antwan,Male,African-American,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,3/21/14 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +62161,71483,64813,PRETRIAL,Twensey,Shanard,Antwan,Male,African-American,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,3/21/14 0:00,4,High,8,Risk of Recidivism,0.12,8,High,New,1,0 +62161,71483,64813,PRETRIAL,Twensey,Shanard,Antwan,Male,African-American,02/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,3/21/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62165,71488,64818,Probation,smith,anthony,NULL,Male,African-American,12/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +62165,71488,64818,Probation,smith,anthony,NULL,Male,African-American,12/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +62165,71488,64818,Probation,smith,anthony,NULL,Male,African-American,12/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62160,71479,64810,PRETRIAL,Daniels,Joshua,NULL,Male,African-American,09/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +62160,71479,64810,PRETRIAL,Daniels,Joshua,NULL,Male,African-American,09/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +62160,71479,64810,PRETRIAL,Daniels,Joshua,NULL,Male,African-American,09/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +62183,71509,64839,PRETRIAL,ALVARADO,JOSE,NULL,Male,Hispanic,12/24/88,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +62183,71509,64839,PRETRIAL,ALVARADO,JOSE,NULL,Male,Hispanic,12/24/88,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +62183,71509,64839,PRETRIAL,ALVARADO,JOSE,NULL,Male,Hispanic,12/24/88,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62162,71484,64814,PRETRIAL,Hall,Ramone,A,Male,African-American,07/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +62162,71484,64814,PRETRIAL,Hall,Ramone,A,Male,African-American,07/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +62162,71484,64814,PRETRIAL,Hall,Ramone,A,Male,African-American,07/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62167,71491,64821,Probation,frasier,jeannie,NULL,Female,African-American,12/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +62167,71491,64821,Probation,frasier,jeannie,NULL,Female,African-American,12/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +62167,71491,64821,Probation,frasier,jeannie,NULL,Female,African-American,12/14/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62180,71505,64835,Probation,Godnick,David,NULL,Male,Caucasian,09/10/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +62180,71505,64835,Probation,Godnick,David,NULL,Male,Caucasian,09/10/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +62180,71505,64835,Probation,Godnick,David,NULL,Male,Caucasian,09/10/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62169,71493,64823,PRETRIAL,Storm,Bart,NULL,Male,Caucasian,07/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/21/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +62169,71493,64823,PRETRIAL,Storm,Bart,NULL,Male,Caucasian,07/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/21/14 0:00,1,Low,8,Risk of Recidivism,-2.71,1,Low,New,1,0 +62169,71493,64823,PRETRIAL,Storm,Bart,NULL,Male,Caucasian,07/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62176,71500,64830,PRETRIAL,RAMSEY,ERROL,NULL,Male,African-American,11/23/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +62176,71500,64830,PRETRIAL,RAMSEY,ERROL,NULL,Male,African-American,11/23/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +62176,71500,64830,PRETRIAL,RAMSEY,ERROL,NULL,Male,African-American,11/23/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62182,71507,64837,Probation,Harden,Anthony,NULL,Male,African-American,01/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.01,4,Low,New,1,0 +62182,71507,64837,Probation,Harden,Anthony,NULL,Male,African-American,01/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +62182,71507,64837,Probation,Harden,Anthony,NULL,Male,African-American,01/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62173,71497,64827,PRETRIAL,PFLANZER,MICHEAL,NULL,Male,Caucasian,09/07/43,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +62173,71497,64827,PRETRIAL,PFLANZER,MICHEAL,NULL,Male,Caucasian,09/07/43,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +62173,71497,64827,PRETRIAL,PFLANZER,MICHEAL,NULL,Male,Caucasian,09/07/43,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58727,71476,60942,PRETRIAL,Miller,Trevin,Trammond,Male,African-American,09/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,Copy,1,0 +58727,71476,60942,PRETRIAL,Miller,Trevin,Trammond,Male,African-American,09/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,Copy,1,0 +58727,71476,60942,PRETRIAL,Miller,Trevin,Trammond,Male,African-American,09/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +11165,71510,64840,PRETRIAL,ALLEN,JERMAIN,OMAR,Male,African-American,12/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +11165,71510,64840,PRETRIAL,ALLEN,JERMAIN,OMAR,Male,African-American,12/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.71,10,High,New,1,0 +11165,71510,64840,PRETRIAL,ALLEN,JERMAIN,OMAR,Male,African-American,12/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +55292,71504,64834,Probation,Robinson,Tavarius,NULL,Male,African-American,11/08/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +55292,71504,64834,Probation,Robinson,Tavarius,NULL,Male,African-American,11/08/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +55292,71504,64834,Probation,Robinson,Tavarius,NULL,Male,African-American,11/08/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62166,71489,64819,Probation,York,Atnhony,NULL,Male,Caucasian,03/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +62166,71489,64819,Probation,York,Atnhony,NULL,Male,Caucasian,03/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +62166,71489,64819,Probation,York,Atnhony,NULL,Male,Caucasian,03/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62172,71496,64826,Probation,Osceola,Jaime,Renee,Female,Native American,08/07/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +62172,71496,64826,Probation,Osceola,Jaime,Renee,Female,Native American,08/07/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +62172,71496,64826,Probation,Osceola,Jaime,Renee,Female,Native American,08/07/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62170,71494,64824,Probation,Martinsdasilva,Daniel,NULL,Male,Hispanic,06/21/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +62170,71494,64824,Probation,Martinsdasilva,Daniel,NULL,Male,Hispanic,06/21/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +62170,71494,64824,Probation,Martinsdasilva,Daniel,NULL,Male,Hispanic,06/21/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +10655,71481,64811,PRETRIAL,Woodcock,Denzil,Robert,Male,African-American,12/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +10655,71481,64811,PRETRIAL,Woodcock,Denzil,Robert,Male,African-American,12/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +10655,71481,64811,PRETRIAL,Woodcock,Denzil,Robert,Male,African-American,12/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62178,71502,64832,Probation,Castellanos,Johanna,NULL,Female,Hispanic,06/06/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +62178,71502,64832,Probation,Castellanos,Johanna,NULL,Female,Hispanic,06/06/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/14 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +62178,71502,64832,Probation,Castellanos,Johanna,NULL,Female,Hispanic,06/06/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62190,71520,64849,PRETRIAL,LOPEZ,SELVIN,RAY,Male,African-American,06/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +62190,71520,64849,PRETRIAL,LOPEZ,SELVIN,RAY,Male,African-American,06/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +62190,71520,64849,PRETRIAL,LOPEZ,SELVIN,RAY,Male,African-American,06/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62193,71523,64852,PRETRIAL,Henderson,Antione,NULL,Male,African-American,08/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +62193,71523,64852,PRETRIAL,Henderson,Antione,NULL,Male,African-American,08/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +62193,71523,64852,PRETRIAL,Henderson,Antione,NULL,Male,African-American,08/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62187,71515,64845,PRETRIAL,THOMPSON,JAMES,NULL,Male,African-American,11/17/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +62187,71515,64845,PRETRIAL,THOMPSON,JAMES,NULL,Male,African-American,11/17/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +62187,71515,64845,PRETRIAL,THOMPSON,JAMES,NULL,Male,African-American,11/17/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62198,71528,64857,PRETRIAL,CASSAGNOL,ANN-MARIE,NULL,Female,Caucasian,08/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +62198,71528,64857,PRETRIAL,CASSAGNOL,ANN-MARIE,NULL,Female,Caucasian,08/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +62198,71528,64857,PRETRIAL,CASSAGNOL,ANN-MARIE,NULL,Female,Caucasian,08/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62195,71525,64854,PRETRIAL,Ballesteros,Ulrike,NULL,Male,Caucasian,09/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +62195,71525,64854,PRETRIAL,Ballesteros,Ulrike,NULL,Male,Caucasian,09/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +62195,71525,64854,PRETRIAL,Ballesteros,Ulrike,NULL,Male,Caucasian,09/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58124,71517,64846,PRETRIAL,Noronha,Emily,NULL,Female,Other,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +58124,71517,64846,PRETRIAL,Noronha,Emily,NULL,Female,Other,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +58124,71517,64846,PRETRIAL,Noronha,Emily,NULL,Female,Other,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62188,71518,64847,PRETRIAL,Simon,Margarita,NULL,Female,Hispanic,11/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/22/14 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +62188,71518,64847,PRETRIAL,Simon,Margarita,NULL,Female,Hispanic,11/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/22/14 0:00,1,Low,8,Risk of Recidivism,-2.62,1,Low,New,1,0 +62188,71518,64847,PRETRIAL,Simon,Margarita,NULL,Female,Hispanic,11/17/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62184,71512,64842,PRETRIAL,Barrett,Joshua,NULL,Male,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +62184,71512,64842,PRETRIAL,Barrett,Joshua,NULL,Male,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +62184,71512,64842,PRETRIAL,Barrett,Joshua,NULL,Male,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62186,71514,64844,PRETRIAL,ALCEUS,MOISE,NULL,Male,African-American,11/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +62186,71514,64844,PRETRIAL,ALCEUS,MOISE,NULL,Male,African-American,11/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +62186,71514,64844,PRETRIAL,ALCEUS,MOISE,NULL,Male,African-American,11/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62191,71521,64850,PRETRIAL,Boyd,William,NULL,Male,African-American,11/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.98,9,High,New,1,0 +62191,71521,64850,PRETRIAL,Boyd,William,NULL,Male,African-American,11/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +62191,71521,64850,PRETRIAL,Boyd,William,NULL,Male,African-American,11/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62196,71526,64855,PRETRIAL,Chou,Wen,NULL,Male,Other,08/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +62196,71526,64855,PRETRIAL,Chou,Wen,NULL,Male,Other,08/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +62196,71526,64855,PRETRIAL,Chou,Wen,NULL,Male,Other,08/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62192,71522,64851,PRETRIAL,NANCY,HOWARD,L,Female,Caucasian,01/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/14 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +62192,71522,64851,PRETRIAL,NANCY,HOWARD,L,Female,Caucasian,01/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/14 0:00,1,Low,8,Risk of Recidivism,-2.67,1,Low,New,1,0 +62192,71522,64851,PRETRIAL,NANCY,HOWARD,L,Female,Caucasian,01/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62197,71527,64856,PRETRIAL,clark,oscar,NULL,Male,African-American,06/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +62197,71527,64856,PRETRIAL,clark,oscar,NULL,Male,African-American,06/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +62197,71527,64856,PRETRIAL,clark,oscar,NULL,Male,African-American,06/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62194,71524,64853,PRETRIAL,CASTRO,ALEXANDRO,DANIEL,Male,Hispanic,09/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +62194,71524,64853,PRETRIAL,CASTRO,ALEXANDRO,DANIEL,Male,Hispanic,09/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +62194,71524,64853,PRETRIAL,CASTRO,ALEXANDRO,DANIEL,Male,Hispanic,09/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +29843,71516,28827,PRETRIAL,BURNS,JAMES,NULL,Male,African-American,03/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,2,Medium,7,Risk of Violence,-2.23,4,Low,Copy,1,0 +29843,71516,28827,PRETRIAL,BURNS,JAMES,NULL,Male,African-American,03/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,Copy,1,0 +29843,71516,28827,PRETRIAL,BURNS,JAMES,NULL,Male,African-American,03/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/22/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +62189,71519,64848,PRETRIAL,WARTHEN,MARLO,ROCHELL,Female,African-American,09/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/22/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +62189,71519,64848,PRETRIAL,WARTHEN,MARLO,ROCHELL,Female,African-American,09/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/22/14 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +62189,71519,64848,PRETRIAL,WARTHEN,MARLO,ROCHELL,Female,African-American,09/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +23151,71537,64865,PRETRIAL,Flecther,Shawn,Anthony,Male,African-American,01/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/23/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +23151,71537,64865,PRETRIAL,Flecther,Shawn,Anthony,Male,African-American,01/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/23/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +23151,71537,64865,PRETRIAL,Flecther,Shawn,Anthony,Male,African-American,01/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62200,71532,64860,PRETRIAL,Peoples,Gary,NULL,Male,African-American,07/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +62200,71532,64860,PRETRIAL,Peoples,Gary,NULL,Male,African-American,07/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +62200,71532,64860,PRETRIAL,Peoples,Gary,NULL,Male,African-American,07/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62207,71540,64868,PRETRIAL,FLEENOR,RICHARD,NULL,Male,Caucasian,09/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +62207,71540,64868,PRETRIAL,FLEENOR,RICHARD,NULL,Male,Caucasian,09/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +62207,71540,64868,PRETRIAL,FLEENOR,RICHARD,NULL,Male,Caucasian,09/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +7342,71529,61825,PRETRIAL,LAPAIX,JAMES,NULL,Male,African-American,10/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/14 0:00,4,High,7,Risk of Violence,-0.57,10,High,Copy,1,0 +7342,71529,61825,PRETRIAL,LAPAIX,JAMES,NULL,Male,African-American,10/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/14 0:00,4,High,8,Risk of Recidivism,0.67,10,High,Copy,1,0 +7342,71529,61825,PRETRIAL,LAPAIX,JAMES,NULL,Male,African-American,10/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +62204,71536,64864,PRETRIAL,MCLEOD,SAMUEL,E,Male,African-American,09/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +62204,71536,64864,PRETRIAL,MCLEOD,SAMUEL,E,Male,African-American,09/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +62204,71536,64864,PRETRIAL,MCLEOD,SAMUEL,E,Male,African-American,09/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62202,71534,64862,PRETRIAL,Graham,Romania,NULL,Female,African-American,08/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +62202,71534,64862,PRETRIAL,Graham,Romania,NULL,Female,African-American,08/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +62202,71534,64862,PRETRIAL,Graham,Romania,NULL,Female,African-American,08/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +41486,71530,64858,PRETRIAL,Register,Nicholas,NULL,Male,Caucasian,02/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +41486,71530,64858,PRETRIAL,Register,Nicholas,NULL,Male,Caucasian,02/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +41486,71530,64858,PRETRIAL,Register,Nicholas,NULL,Male,Caucasian,02/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62203,71535,64863,PRETRIAL,SUFIYAN,MOHAMMED,NULL,Male,Other,08/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +62203,71535,64863,PRETRIAL,SUFIYAN,MOHAMMED,NULL,Male,Other,08/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +62203,71535,64863,PRETRIAL,SUFIYAN,MOHAMMED,NULL,Male,Other,08/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62209,71542,64870,PRETRIAL,King,Vivian,NULL,Female,Caucasian,01/14/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +62209,71542,64870,PRETRIAL,King,Vivian,NULL,Female,Caucasian,01/14/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +62209,71542,64870,PRETRIAL,King,Vivian,NULL,Female,Caucasian,01/14/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62199,71531,64859,PRETRIAL,wilcox,dexter,NULL,Male,African-American,11/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +62199,71531,64859,PRETRIAL,wilcox,dexter,NULL,Male,African-American,11/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +62199,71531,64859,PRETRIAL,wilcox,dexter,NULL,Male,African-American,11/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62201,71533,64861,PRETRIAL,Prospere,Carmelle,NULL,Female,African-American,02/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +62201,71533,64861,PRETRIAL,Prospere,Carmelle,NULL,Female,African-American,02/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +62201,71533,64861,PRETRIAL,Prospere,Carmelle,NULL,Female,African-American,02/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62205,71538,64866,PRETRIAL,ARMSTRONG,ROBERT,A,Male,African-American,09/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +62205,71538,64866,PRETRIAL,ARMSTRONG,ROBERT,A,Male,African-American,09/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +62205,71538,64866,PRETRIAL,ARMSTRONG,ROBERT,A,Male,African-American,09/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/23/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62206,71539,64867,PRETRIAL,FRAZIER,DANTONIO,NULL,Male,African-American,10/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +62206,71539,64867,PRETRIAL,FRAZIER,DANTONIO,NULL,Male,African-American,10/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +62206,71539,64867,PRETRIAL,FRAZIER,DANTONIO,NULL,Male,African-American,10/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62208,71541,64869,PRETRIAL,Bradley,Tequisha,NULL,Female,African-American,02/27/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.31,7,Medium,New,1,0 +62208,71541,64869,PRETRIAL,Bradley,Tequisha,NULL,Female,African-American,02/27/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.11,8,High,New,1,0 +62208,71541,64869,PRETRIAL,Bradley,Tequisha,NULL,Female,African-American,02/27/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62237,71580,64906,Probation,lopez,Rocael,NULL,Male,Hispanic,02/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +62237,71580,64906,Probation,lopez,Rocael,NULL,Male,Hispanic,02/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +62237,71580,64906,Probation,lopez,Rocael,NULL,Male,Hispanic,02/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62230,71570,64896,PRETRIAL,Hernandez,Mario,Ernesto,Male,Hispanic,01/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/24/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +62230,71570,64896,PRETRIAL,Hernandez,Mario,Ernesto,Male,Hispanic,01/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/24/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +62230,71570,64896,PRETRIAL,Hernandez,Mario,Ernesto,Male,Hispanic,01/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62226,71562,64889,DRRD,Augustin,Luben,Bernard,Male,African-American,11/24/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +62226,71562,64889,DRRD,Augustin,Luben,Bernard,Male,African-American,11/24/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,2,Medium,8,Risk of Recidivism,0.18,7,Medium,New,1,0 +62226,71562,64889,DRRD,Augustin,Luben,Bernard,Male,African-American,11/24/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,2,Medium,18,Risk of Failure to Appear,18,2,Low,New,1,0 +62216,71549,64877,PRETRIAL,WALSH,ANTONIO,MAURICE,Male,African-American,04/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +62216,71549,64877,PRETRIAL,WALSH,ANTONIO,MAURICE,Male,African-American,04/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +62216,71549,64877,PRETRIAL,WALSH,ANTONIO,MAURICE,Male,African-American,04/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +62233,71575,64901,Probation,BEDOVA,JUAN,PABLO,Male,Hispanic,04/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +62233,71575,64901,Probation,BEDOVA,JUAN,PABLO,Male,Hispanic,04/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +62233,71575,64901,Probation,BEDOVA,JUAN,PABLO,Male,Hispanic,04/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62219,71554,64882,Probation,Derico,Lashayla,NULL,Female,African-American,09/24/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/24/14 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +62219,71554,64882,Probation,Derico,Lashayla,NULL,Female,African-American,09/24/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +62219,71554,64882,Probation,Derico,Lashayla,NULL,Female,African-American,09/24/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/24/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +40011,71567,39597,PRETRIAL,GALLAHAN,AMY,NULL,Female,Caucasian,11/15/78,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Married,3/24/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +40011,71567,39597,PRETRIAL,GALLAHAN,AMY,NULL,Female,Caucasian,11/15/78,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Married,3/24/14 0:00,1,Low,8,Risk of Recidivism,-0.56,5,Medium,New,1,0 +40011,71567,39597,PRETRIAL,GALLAHAN,AMY,NULL,Female,Caucasian,11/15/78,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Married,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +62213,71546,64874,PRETRIAL,Josephs,Sheldon,Cecil,Male,African-American,07/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +62213,71546,64874,PRETRIAL,Josephs,Sheldon,Cecil,Male,African-American,07/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +62213,71546,64874,PRETRIAL,Josephs,Sheldon,Cecil,Male,African-American,07/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +22542,71559,64886,PRETRIAL,CASTILLO,MOISES,NULL,Male,Hispanic,06/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +22542,71559,64886,PRETRIAL,CASTILLO,MOISES,NULL,Male,Hispanic,06/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +22542,71559,64886,PRETRIAL,CASTILLO,MOISES,NULL,Male,Hispanic,06/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62211,71544,64872,PRETRIAL,JULIAN,GONZALEZ,FELIPE,Male,Hispanic,05/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,2,Medium,7,Risk of Violence,-1.39,7,Medium,New,1,0 +62211,71544,64872,PRETRIAL,JULIAN,GONZALEZ,FELIPE,Male,Hispanic,05/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +62211,71544,64872,PRETRIAL,JULIAN,GONZALEZ,FELIPE,Male,Hispanic,05/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62225,71563,64890,Probation,Mayberry,Scott,NULL,Male,Caucasian,09/29/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.32,3,Low,New,1,0 +62225,71563,64890,Probation,Mayberry,Scott,NULL,Male,Caucasian,09/29/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +62225,71563,64890,Probation,Mayberry,Scott,NULL,Male,Caucasian,09/29/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,42,10,High,New,1,0 +62227,71565,64892,Probation,Gillen,David,NULL,Male,Caucasian,02/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +62227,71565,64892,Probation,Gillen,David,NULL,Male,Caucasian,02/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +62227,71565,64892,Probation,Gillen,David,NULL,Male,Caucasian,02/23/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +26870,71572,64898,PRETRIAL,Marshall,Arthur,NULL,Male,Caucasian,03/03/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +26870,71572,64898,PRETRIAL,Marshall,Arthur,NULL,Male,Caucasian,03/03/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +26870,71572,64898,PRETRIAL,Marshall,Arthur,NULL,Male,Caucasian,03/03/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +16522,71551,64879,Probation,Portillo,Jose,NULL,Male,Hispanic,12/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +16522,71551,64879,Probation,Portillo,Jose,NULL,Male,Hispanic,12/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +16522,71551,64879,Probation,Portillo,Jose,NULL,Male,Hispanic,12/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62222,71560,64887,Probation,bolden,quentin,NULL,Male,African-American,02/09/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +62222,71560,64887,Probation,bolden,quentin,NULL,Male,African-American,02/09/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +62222,71560,64887,Probation,bolden,quentin,NULL,Male,African-American,02/09/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62235,71577,64903,Probation,caillas,reina,NULL,Female,Hispanic,11/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,2,Medium,7,Risk of Violence,-2.99,1,Low,New,1,0 +62235,71577,64903,Probation,caillas,reina,NULL,Female,Hispanic,11/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +62235,71577,64903,Probation,caillas,reina,NULL,Female,Hispanic,11/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62214,71547,64875,PRETRIAL,VILLA,JOSEPH,EMERSON,Male,Caucasian,06/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +62214,71547,64875,PRETRIAL,VILLA,JOSEPH,EMERSON,Male,Caucasian,06/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +62214,71547,64875,PRETRIAL,VILLA,JOSEPH,EMERSON,Male,Caucasian,06/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62221,71556,64884,Probation,lovelace,albert,NULL,Male,African-American,09/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +62221,71556,64884,Probation,lovelace,albert,NULL,Male,African-American,09/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +62221,71556,64884,Probation,lovelace,albert,NULL,Male,African-American,09/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +3214,71552,64880,PRETRIAL,Stearns,James,C,Male,Caucasian,04/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +3214,71552,64880,PRETRIAL,Stearns,James,C,Male,Caucasian,04/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +3214,71552,64880,PRETRIAL,Stearns,James,C,Male,Caucasian,04/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +62215,71548,64876,PRETRIAL,DUCARDY,JOCELYN,NULL,Male,African-American,02/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +62215,71548,64876,PRETRIAL,DUCARDY,JOCELYN,NULL,Male,African-American,02/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +62215,71548,64876,PRETRIAL,DUCARDY,JOCELYN,NULL,Male,African-American,02/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57559,71573,64899,PRETRIAL,ELLIS,ANDREW,NULL,Male,African-American,06/04/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/24/14 0:00,2,Medium,7,Risk of Violence,-2.92,2,Low,New,1,0 +57559,71573,64899,PRETRIAL,ELLIS,ANDREW,NULL,Male,African-American,06/04/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +57559,71573,64899,PRETRIAL,ELLIS,ANDREW,NULL,Male,African-American,06/04/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/24/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62210,71543,64871,PRETRIAL,NELSON,ENRICO,GAILOUS,Male,African-American,01/18/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +62210,71543,64871,PRETRIAL,NELSON,ENRICO,GAILOUS,Male,African-American,01/18/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +62210,71543,64871,PRETRIAL,NELSON,ENRICO,GAILOUS,Male,African-American,01/18/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +62231,71571,64897,PRETRIAL,Haynes,Tayaisha,NULL,Female,African-American,08/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +62231,71571,64897,PRETRIAL,Haynes,Tayaisha,NULL,Female,African-American,08/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +62231,71571,64897,PRETRIAL,Haynes,Tayaisha,NULL,Female,African-American,08/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62217,71550,64878,PRETRIAL,Hinton,Allen,NULL,Male,Native American,03/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +62217,71550,64878,PRETRIAL,Hinton,Allen,NULL,Male,Native American,03/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +62217,71550,64878,PRETRIAL,Hinton,Allen,NULL,Male,Native American,03/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +27066,71557,55925,PRETRIAL,Hicks,Sylvester,NULL,Male,African-American,04/06/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,Copy,1,0 +27066,71557,55925,PRETRIAL,Hicks,Sylvester,NULL,Male,African-American,04/06/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,Copy,1,0 +27066,71557,55925,PRETRIAL,Hicks,Sylvester,NULL,Male,African-American,04/06/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +56396,71564,64891,PRETRIAL,Cyr,Danielle,NULL,Female,Caucasian,05/22/66,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/24/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +56396,71564,64891,PRETRIAL,Cyr,Danielle,NULL,Female,Caucasian,05/22/66,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/24/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +56396,71564,64891,PRETRIAL,Cyr,Danielle,NULL,Female,Caucasian,05/22/66,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +19137,71578,64904,Probation,Engroff,Victor,Philip,Male,Caucasian,05/04/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +19137,71578,64904,Probation,Engroff,Victor,Philip,Male,Caucasian,05/04/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +19137,71578,64904,Probation,Engroff,Victor,Philip,Male,Caucasian,05/04/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,New,1,0 +62232,71574,64900,PRETRIAL,Ackerman,Corey,M,Male,Caucasian,04/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +62232,71574,64900,PRETRIAL,Ackerman,Corey,M,Male,Caucasian,04/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +62232,71574,64900,PRETRIAL,Ackerman,Corey,M,Male,Caucasian,04/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62223,71561,64888,Probation,arriaga,Oscar,NULL,Male,Hispanic,06/15/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +62223,71561,64888,Probation,arriaga,Oscar,NULL,Male,Hispanic,06/15/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +62223,71561,64888,Probation,arriaga,Oscar,NULL,Male,Hispanic,06/15/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62234,71576,64902,Probation,Henry,Anne,NULL,Female,African-American,07/31/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +62234,71576,64902,Probation,Henry,Anne,NULL,Female,African-American,07/31/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +62234,71576,64902,Probation,Henry,Anne,NULL,Female,African-American,07/31/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62218,71553,64881,PRETRIAL,MANZANARES,CARMEN,NULL,Female,Hispanic,12/03/64,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,3/24/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +62218,71553,64881,PRETRIAL,MANZANARES,CARMEN,NULL,Female,Hispanic,12/03/64,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,3/24/14 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +62218,71553,64881,PRETRIAL,MANZANARES,CARMEN,NULL,Female,Hispanic,12/03/64,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62228,71568,64894,PRETRIAL,Rozo,Ariane,NULL,Female,Hispanic,10/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/24/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +62228,71568,64894,PRETRIAL,Rozo,Ariane,NULL,Female,Hispanic,10/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/24/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +62228,71568,64894,PRETRIAL,Rozo,Ariane,NULL,Female,Hispanic,10/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +24228,71566,64893,Probation,Mulkey,William,Taylor,Male,Caucasian,06/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +24228,71566,64893,Probation,Mulkey,William,Taylor,Male,Caucasian,06/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +24228,71566,64893,Probation,Mulkey,William,Taylor,Male,Caucasian,06/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56953,71558,64885,Probation,MIRANDA,JOSE,LUIS,Male,Hispanic,10/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +56953,71558,64885,Probation,MIRANDA,JOSE,LUIS,Male,Hispanic,10/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +56953,71558,64885,Probation,MIRANDA,JOSE,LUIS,Male,Hispanic,10/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62212,71545,64873,PRETRIAL,Olivo,Alex,NULL,Male,Hispanic,11/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +62212,71545,64873,PRETRIAL,Olivo,Alex,NULL,Male,Hispanic,11/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +62212,71545,64873,PRETRIAL,Olivo,Alex,NULL,Male,Hispanic,11/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52814,71592,64918,PRETRIAL,Massaro,Marc,NULL,Male,Caucasian,03/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +52814,71592,64918,PRETRIAL,Massaro,Marc,NULL,Male,Caucasian,03/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +52814,71592,64918,PRETRIAL,Massaro,Marc,NULL,Male,Caucasian,03/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62260,71605,64931,Probation,HOLLIDAY,SHANKIA,NULL,Female,African-American,02/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +62260,71605,64931,Probation,HOLLIDAY,SHANKIA,NULL,Female,African-American,02/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +62260,71605,64931,Probation,HOLLIDAY,SHANKIA,NULL,Female,African-American,02/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62244,71587,64913,PRETRIAL,McKenzie,Malcolm,Malachi,Male,African-American,01/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +62244,71587,64913,PRETRIAL,McKenzie,Malcolm,Malachi,Male,African-American,01/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +62244,71587,64913,PRETRIAL,McKenzie,Malcolm,Malachi,Male,African-American,01/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62258,71603,64929,Probation,Torres,Jose,Francisco,Male,Hispanic,03/27/51,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/25/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +62258,71603,64929,Probation,Torres,Jose,Francisco,Male,Hispanic,03/27/51,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/25/14 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +62258,71603,64929,Probation,Torres,Jose,Francisco,Male,Hispanic,03/27/51,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62239,71582,64908,PRETRIAL,Fernandez,Ares,Veitia,Male,Caucasian,03/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.32,3,Low,New,1,0 +62239,71582,64908,PRETRIAL,Fernandez,Ares,Veitia,Male,Caucasian,03/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +62239,71582,64908,PRETRIAL,Fernandez,Ares,Veitia,Male,Caucasian,03/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62246,71589,64915,PRETRIAL,Brackett,Tanamra,NULL,Female,African-American,06/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +62246,71589,64915,PRETRIAL,Brackett,Tanamra,NULL,Female,African-American,06/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +62246,71589,64915,PRETRIAL,Brackett,Tanamra,NULL,Female,African-American,06/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62251,71595,64921,Probation,stein,Brandt,NULL,Male,Caucasian,11/09/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/25/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +62251,71595,64921,Probation,stein,Brandt,NULL,Male,Caucasian,11/09/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/25/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +62251,71595,64921,Probation,stein,Brandt,NULL,Male,Caucasian,11/09/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +55546,71610,64935,Probation,shaw,jeffrey,NULL,Male,African-American,09/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.02,1,Low,New,1,0 +55546,71610,64935,Probation,shaw,jeffrey,NULL,Male,African-American,09/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +55546,71610,64935,Probation,shaw,jeffrey,NULL,Male,African-American,09/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +62253,71597,64923,PRETRIAL,bell,derek,NULL,Male,African-American,05/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +62253,71597,64923,PRETRIAL,bell,derek,NULL,Male,African-American,05/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +62253,71597,64923,PRETRIAL,bell,derek,NULL,Male,African-American,05/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +39516,71599,64925,PRETRIAL,Haynes,Andreasseeze,NULL,Male,African-American,10/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +39516,71599,64925,PRETRIAL,Haynes,Andreasseeze,NULL,Male,African-American,10/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +39516,71599,64925,PRETRIAL,Haynes,Andreasseeze,NULL,Male,African-American,10/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62261,71608,64933,Probation,Eloi,James,NULL,Male,African-American,05/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +62261,71608,64933,Probation,Eloi,James,NULL,Male,African-American,05/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +62261,71608,64933,Probation,Eloi,James,NULL,Male,African-American,05/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62242,71585,64911,PRETRIAL,HENRY,JOHN,ISOM,Male,African-American,09/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/25/14 0:00,2,Medium,7,Risk of Violence,-2.65,2,Low,New,1,0 +62242,71585,64911,PRETRIAL,HENRY,JOHN,ISOM,Male,African-American,09/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +62242,71585,64911,PRETRIAL,HENRY,JOHN,ISOM,Male,African-American,09/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,3/25/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62250,71594,64920,PRETRIAL,DELGADO,ALBERTO,NULL,Male,Hispanic,12/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/14 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +62250,71594,64920,PRETRIAL,DELGADO,ALBERTO,NULL,Male,Hispanic,12/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/14 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +62250,71594,64920,PRETRIAL,DELGADO,ALBERTO,NULL,Male,Hispanic,12/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62263,71611,64936,Probation,MAGNUSON,AUBREE,A,Female,Caucasian,11/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +62263,71611,64936,Probation,MAGNUSON,AUBREE,A,Female,Caucasian,11/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +62263,71611,64936,Probation,MAGNUSON,AUBREE,A,Female,Caucasian,11/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62247,71590,64916,PRETRIAL,WHITE,CHIANTI,NULL,Female,African-American,06/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +62247,71590,64916,PRETRIAL,WHITE,CHIANTI,NULL,Female,African-American,06/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +62247,71590,64916,PRETRIAL,WHITE,CHIANTI,NULL,Female,African-American,06/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62238,71581,64907,PRETRIAL,BENITEZ,CARLOS,MANUEL,Male,Caucasian,05/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.5,3,Low,New,1,0 +62238,71581,64907,PRETRIAL,BENITEZ,CARLOS,MANUEL,Male,Caucasian,05/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +62238,71581,64907,PRETRIAL,BENITEZ,CARLOS,MANUEL,Male,Caucasian,05/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +54328,71602,64928,PRETRIAL,Charles,Carleb,NULL,Male,African-American,10/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/25/14 0:00,4,High,7,Risk of Violence,-0.71,9,High,New,1,0 +54328,71602,64928,PRETRIAL,Charles,Carleb,NULL,Male,African-American,10/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/25/14 0:00,4,High,8,Risk of Recidivism,0.55,9,High,New,1,0 +54328,71602,64928,PRETRIAL,Charles,Carleb,NULL,Male,African-American,10/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/25/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62255,71598,64924,Probation,mcbride,shirley,marie,Female,African-American,07/14/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +62255,71598,64924,Probation,mcbride,shirley,marie,Female,African-American,07/14/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +62255,71598,64924,Probation,mcbride,shirley,marie,Female,African-American,07/14/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62243,71586,64912,PRETRIAL,Mullarky,Ian,Thomas,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +62243,71586,64912,PRETRIAL,Mullarky,Ian,Thomas,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +62243,71586,64912,PRETRIAL,Mullarky,Ian,Thomas,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62256,71600,64926,Probation,Gonzalez,Dorelys,NULL,Female,Hispanic,06/02/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/25/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +62256,71600,64926,Probation,Gonzalez,Dorelys,NULL,Female,Hispanic,06/02/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/25/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +62256,71600,64926,Probation,Gonzalez,Dorelys,NULL,Female,Hispanic,06/02/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +36257,71607,64932,PRETRIAL,DAVIS,KIMBERLY,AYNE,Female,Caucasian,04/18/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/25/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +36257,71607,64932,PRETRIAL,DAVIS,KIMBERLY,AYNE,Female,Caucasian,04/18/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/25/14 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +36257,71607,64932,PRETRIAL,DAVIS,KIMBERLY,AYNE,Female,Caucasian,04/18/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +62259,71604,64930,PRETRIAL,LUCTHAMAS,ELITHANNE,NULL,Female,African-American,02/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/25/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +62259,71604,64930,PRETRIAL,LUCTHAMAS,ELITHANNE,NULL,Female,African-American,02/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/25/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +62259,71604,64930,PRETRIAL,LUCTHAMAS,ELITHANNE,NULL,Female,African-American,02/12/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62240,71583,64909,PRETRIAL,Ortega,Carlos,NULL,Male,Caucasian,12/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +62240,71583,64909,PRETRIAL,Ortega,Carlos,NULL,Male,Caucasian,12/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +62240,71583,64909,PRETRIAL,Ortega,Carlos,NULL,Male,Caucasian,12/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62245,71588,64914,PRETRIAL,Johnson,Kenneth,Melvin,Male,Caucasian,08/14/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/25/14 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +62245,71588,64914,PRETRIAL,Johnson,Kenneth,Melvin,Male,Caucasian,08/14/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/25/14 0:00,1,Low,8,Risk of Recidivism,-2.77,1,Low,New,1,0 +62245,71588,64914,PRETRIAL,Johnson,Kenneth,Melvin,Male,Caucasian,08/14/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62252,71596,64922,PRETRIAL,cerpa,james,NULL,Male,Caucasian,10/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/14 0:00,4,High,7,Risk of Violence,-1.03,8,High,New,1,0 +62252,71596,64922,PRETRIAL,cerpa,james,NULL,Male,Caucasian,10/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/14 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +62252,71596,64922,PRETRIAL,cerpa,james,NULL,Male,Caucasian,10/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +62262,71609,64934,PRETRIAL,Masnik,Sainmelus,NULL,Male,African-American,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +62262,71609,64934,PRETRIAL,Masnik,Sainmelus,NULL,Male,African-American,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +62262,71609,64934,PRETRIAL,Masnik,Sainmelus,NULL,Male,African-American,10/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/25/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62257,71601,64927,PRETRIAL,Strickland,Nathan,NULL,Male,Caucasian,02/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/25/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +62257,71601,64927,PRETRIAL,Strickland,Nathan,NULL,Male,Caucasian,02/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/25/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +62257,71601,64927,PRETRIAL,Strickland,Nathan,NULL,Male,Caucasian,02/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62248,71591,64917,Probation,collins,neiman marcus,jonathan,Male,African-American,04/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,4,High,7,Risk of Violence,-0.9,9,High,New,1,0 +62248,71591,64917,Probation,collins,neiman marcus,jonathan,Male,African-American,04/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +62248,71591,64917,Probation,collins,neiman marcus,jonathan,Male,African-American,04/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/25/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62279,71630,64953,PRETRIAL,Lake,Ronald,NULL,Male,Caucasian,08/15/45,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +62279,71630,64953,PRETRIAL,Lake,Ronald,NULL,Male,Caucasian,08/15/45,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +62279,71630,64953,PRETRIAL,Lake,Ronald,NULL,Male,Caucasian,08/15/45,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62290,71643,64965,Probation,Jean,Louisette,NULL,Female,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/26/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +62290,71643,64965,Probation,Jean,Louisette,NULL,Female,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +62290,71643,64965,Probation,Jean,Louisette,NULL,Female,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62268,71617,64941,PRETRIAL,LEE,TERRENCE,LAMONT,Male,African-American,09/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +62268,71617,64941,PRETRIAL,LEE,TERRENCE,LAMONT,Male,African-American,09/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +62268,71617,64941,PRETRIAL,LEE,TERRENCE,LAMONT,Male,African-American,09/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62272,71622,64945,PRETRIAL,Bridges,Savannah,NULL,Male,African-American,02/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +62272,71622,64945,PRETRIAL,Bridges,Savannah,NULL,Male,African-American,02/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +62272,71622,64945,PRETRIAL,Bridges,Savannah,NULL,Male,African-American,02/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61536,71625,64948,Probation,Joseph,George,NULL,Male,Caucasian,08/15/79,17,All Scales,Intake,English,Pretrial,Probation,Single,3/26/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +61536,71625,64948,Probation,Joseph,George,NULL,Male,Caucasian,08/15/79,17,All Scales,Intake,English,Pretrial,Probation,Single,3/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,6,Medium,New,1,0 +61536,71625,64948,Probation,Joseph,George,NULL,Male,Caucasian,08/15/79,17,All Scales,Intake,English,Pretrial,Probation,Single,3/26/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62280,71632,64954,Probation,smith,jane,NULL,Female,Hispanic,09/12/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/26/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +62280,71632,64954,Probation,smith,jane,NULL,Female,Hispanic,09/12/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/26/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +62280,71632,64954,Probation,smith,jane,NULL,Female,Hispanic,09/12/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +1597,71612,1292,PRETRIAL,OWENS,LARRY,J,Male,African-American,02/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,Copy,1,0 +1597,71612,1292,PRETRIAL,OWENS,LARRY,J,Male,African-American,02/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,Copy,1,0 +1597,71612,1292,PRETRIAL,OWENS,LARRY,J,Male,African-American,02/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +62291,71646,64967,Probation,HYLYER,CHRISTOPHER,NULL,Male,African-American,09/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +62291,71646,64967,Probation,HYLYER,CHRISTOPHER,NULL,Male,African-American,09/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +62291,71646,64967,Probation,HYLYER,CHRISTOPHER,NULL,Male,African-American,09/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47276,71633,64955,PRETRIAL,Jimenez,Gabriela,NULL,Female,Caucasian,07/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +47276,71633,64955,PRETRIAL,Jimenez,Gabriela,NULL,Female,Caucasian,07/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +47276,71633,64955,PRETRIAL,Jimenez,Gabriela,NULL,Female,Caucasian,07/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +24842,71638,64960,PRETRIAL,Lorenz,Michael,Elliot,Male,Caucasian,01/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +24842,71638,64960,PRETRIAL,Lorenz,Michael,Elliot,Male,Caucasian,01/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +24842,71638,64960,PRETRIAL,Lorenz,Michael,Elliot,Male,Caucasian,01/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62286,71640,64962,Probation,PANEBIANCO,MARIE,NULL,Female,Caucasian,11/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +62286,71640,64962,Probation,PANEBIANCO,MARIE,NULL,Female,Caucasian,11/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +62286,71640,64962,Probation,PANEBIANCO,MARIE,NULL,Female,Caucasian,11/27/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62265,71614,64938,PRETRIAL,GORDON,TERRANCE,D,Male,African-American,11/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +62265,71614,64938,PRETRIAL,GORDON,TERRANCE,D,Male,African-American,11/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +62265,71614,64938,PRETRIAL,GORDON,TERRANCE,D,Male,African-American,11/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +20972,71621,30644,PRETRIAL,BLACK,DANNY,NULL,Male,African-American,12/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,4,High,7,Risk of Violence,-1.03,8,High,Copy,1,0 +20972,71621,30644,PRETRIAL,BLACK,DANNY,NULL,Male,African-American,12/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,4,High,8,Risk of Recidivism,0.29,8,High,Copy,1,0 +20972,71621,30644,PRETRIAL,BLACK,DANNY,NULL,Male,African-American,12/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +62282,71635,64957,PRETRIAL,ABADIA,DANNY,NULL,Male,Caucasian,11/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/26/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +62282,71635,64957,PRETRIAL,ABADIA,DANNY,NULL,Male,Caucasian,11/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/26/14 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +62282,71635,64957,PRETRIAL,ABADIA,DANNY,NULL,Male,Caucasian,11/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +10226,71642,64964,PRETRIAL,MCNAIR,ANTWAN,P,Male,African-American,04/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +10226,71642,64964,PRETRIAL,MCNAIR,ANTWAN,P,Male,African-American,04/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +10226,71642,64964,PRETRIAL,MCNAIR,ANTWAN,P,Male,African-American,04/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62289,71644,64966,PRETRIAL,Ramos-Otero,Jose,NULL,Male,Hispanic,10/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/26/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +62289,71644,64966,PRETRIAL,Ramos-Otero,Jose,NULL,Male,Hispanic,10/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/26/14 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +62289,71644,64966,PRETRIAL,Ramos-Otero,Jose,NULL,Male,Hispanic,10/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62267,71616,64940,PRETRIAL,Chviech,David,Henry,Male,Caucasian,10/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/26/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +62267,71616,64940,PRETRIAL,Chviech,David,Henry,Male,Caucasian,10/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/26/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +62267,71616,64940,PRETRIAL,Chviech,David,Henry,Male,Caucasian,10/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62273,71623,64946,PRETRIAL,Bush,Ern,NULL,Male,African-American,11/04/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/26/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +62273,71623,64946,PRETRIAL,Bush,Ern,NULL,Male,African-American,11/04/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +62273,71623,64946,PRETRIAL,Bush,Ern,NULL,Male,African-American,11/04/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62270,71619,64943,PRETRIAL,Oliver,Addison,Harlan,Male,African-American,11/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +62270,71619,64943,PRETRIAL,Oliver,Addison,Harlan,Male,African-American,11/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +62270,71619,64943,PRETRIAL,Oliver,Addison,Harlan,Male,African-American,11/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62284,71637,64959,PRETRIAL,BROCK,ALEXANDER,GEORGE,Male,Caucasian,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +62284,71637,64959,PRETRIAL,BROCK,ALEXANDER,GEORGE,Male,Caucasian,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +62284,71637,64959,PRETRIAL,BROCK,ALEXANDER,GEORGE,Male,Caucasian,12/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62277,71628,64951,PRETRIAL,STIEFELD,SCOTT,NULL,Male,Caucasian,04/27/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +62277,71628,64951,PRETRIAL,STIEFELD,SCOTT,NULL,Male,Caucasian,04/27/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +62277,71628,64951,PRETRIAL,STIEFELD,SCOTT,NULL,Male,Caucasian,04/27/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62266,71615,64939,PRETRIAL,SCIARRETTI,GABRIEL,VENTURA,Male,Caucasian,05/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,New,1,0 +62266,71615,64939,PRETRIAL,SCIARRETTI,GABRIEL,VENTURA,Male,Caucasian,05/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +62266,71615,64939,PRETRIAL,SCIARRETTI,GABRIEL,VENTURA,Male,Caucasian,05/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62274,71624,64947,PRETRIAL,Guggino,Danielle,Rose,Female,Caucasian,12/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +62274,71624,64947,PRETRIAL,Guggino,Danielle,Rose,Female,Caucasian,12/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +62274,71624,64947,PRETRIAL,Guggino,Danielle,Rose,Female,Caucasian,12/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61495,71645,64060,Probation,Deangelis,William,NULL,Male,Caucasian,12/01/88,17,All Scales,Intake,English,Other,Probation,Single,3/26/14 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,New,1,0 +61495,71645,64060,Probation,Deangelis,William,NULL,Male,Caucasian,12/01/88,17,All Scales,Intake,English,Other,Probation,Single,3/26/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +61495,71645,64060,Probation,Deangelis,William,NULL,Male,Caucasian,12/01/88,17,All Scales,Intake,English,Other,Probation,Single,3/26/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62287,71641,64963,PRETRIAL,Thorpe,Shellene,NULL,Female,African-American,06/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/26/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +62287,71641,64963,PRETRIAL,Thorpe,Shellene,NULL,Female,African-American,06/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +62287,71641,64963,PRETRIAL,Thorpe,Shellene,NULL,Female,African-American,06/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62271,71620,64944,PRETRIAL,Bridges,Chloe,V,Female,Caucasian,06/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +62271,71620,64944,PRETRIAL,Bridges,Chloe,V,Female,Caucasian,06/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,4,High,8,Risk of Recidivism,0.47,10,High,New,1,0 +62271,71620,64944,PRETRIAL,Bridges,Chloe,V,Female,Caucasian,06/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62283,71636,64958,PRETRIAL,WELCHER,ARIELLE,NULL,Female,Caucasian,02/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +62283,71636,64958,PRETRIAL,WELCHER,ARIELLE,NULL,Female,Caucasian,02/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,New,1,0 +62283,71636,64958,PRETRIAL,WELCHER,ARIELLE,NULL,Female,Caucasian,02/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62276,71627,64950,Probation,Charleston,Eda,NULL,Female,African-American,10/05/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/26/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +62276,71627,64950,Probation,Charleston,Eda,NULL,Female,African-American,10/05/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +62276,71627,64950,Probation,Charleston,Eda,NULL,Female,African-American,10/05/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62278,71629,64952,Probation,Powell,Keyera,Danielle,Female,African-American,08/12/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +62278,71629,64952,Probation,Powell,Keyera,Danielle,Female,African-American,08/12/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +62278,71629,64952,Probation,Powell,Keyera,Danielle,Female,African-American,08/12/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62285,71639,64961,PRETRIAL,Ondic,Raymond,NULL,Male,Caucasian,08/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/26/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +62285,71639,64961,PRETRIAL,Ondic,Raymond,NULL,Male,Caucasian,08/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/26/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +62285,71639,64961,PRETRIAL,Ondic,Raymond,NULL,Male,Caucasian,08/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62269,71618,64942,PRETRIAL,Lopez,Alexander,NULL,Male,Caucasian,06/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +62269,71618,64942,PRETRIAL,Lopez,Alexander,NULL,Male,Caucasian,06/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +62269,71618,64942,PRETRIAL,Lopez,Alexander,NULL,Male,Caucasian,06/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62281,71634,64956,Probation,Silva,Monica,NULL,Female,Hispanic,03/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/26/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62281,71634,64956,Probation,Silva,Monica,NULL,Female,Hispanic,03/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/26/14 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +62281,71634,64956,Probation,Silva,Monica,NULL,Female,Hispanic,03/03/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62264,71613,64937,PRETRIAL,Kirkland,Terry,Leon,Male,African-American,06/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +62264,71613,64937,PRETRIAL,Kirkland,Terry,Leon,Male,African-American,06/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +62264,71613,64937,PRETRIAL,Kirkland,Terry,Leon,Male,African-American,06/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/26/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62275,71626,64949,Probation,BELL,DAVID,S,Male,African-American,03/06/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +62275,71626,64949,Probation,BELL,DAVID,S,Male,African-American,03/06/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +62275,71626,64949,Probation,BELL,DAVID,S,Male,African-American,03/06/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/26/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +62304,71660,64980,PRETRIAL,Floyd,Javionne,NULL,Male,African-American,05/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +62304,71660,64980,PRETRIAL,Floyd,Javionne,NULL,Male,African-American,05/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +62304,71660,64980,PRETRIAL,Floyd,Javionne,NULL,Male,African-American,05/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +10867,71647,10387,Probation,Randall,Fred,M,Male,African-American,11/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,Copy,1,0 +10867,71647,10387,Probation,Randall,Fred,M,Male,African-American,11/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,Copy,1,0 +10867,71647,10387,Probation,Randall,Fred,M,Male,African-American,11/13/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +62320,71681,65000,Probation,Davis,Reginald,NULL,Male,African-American,08/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +62320,71681,65000,Probation,Davis,Reginald,NULL,Male,African-American,08/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +62320,71681,65000,Probation,Davis,Reginald,NULL,Male,African-American,08/13/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62295,71652,64972,PRETRIAL,Felix,Pathelin,NULL,Male,Other,09/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +62295,71652,64972,PRETRIAL,Felix,Pathelin,NULL,Male,Other,09/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +62295,71652,64972,PRETRIAL,Felix,Pathelin,NULL,Male,Other,09/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62298,71655,64975,PRETRIAL,Chamberlain,Rasheem,Jamal,Male,African-American,03/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,4,High,7,Risk of Violence,-0.41,10,High,New,1,0 +62298,71655,64975,PRETRIAL,Chamberlain,Rasheem,Jamal,Male,African-American,03/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,4,High,8,Risk of Recidivism,0.91,10,High,New,1,0 +62298,71655,64975,PRETRIAL,Chamberlain,Rasheem,Jamal,Male,African-American,03/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62315,71673,64992,PRETRIAL,NICHOLAS,DAMON,D,Male,African-American,10/18/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +62315,71673,64992,PRETRIAL,NICHOLAS,DAMON,D,Male,African-American,10/18/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +62315,71673,64992,PRETRIAL,NICHOLAS,DAMON,D,Male,African-American,10/18/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62311,71668,64988,PRETRIAL,Rahman,Alim,NULL,Male,Caucasian,11/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +62311,71668,64988,PRETRIAL,Rahman,Alim,NULL,Male,Caucasian,11/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +62311,71668,64988,PRETRIAL,Rahman,Alim,NULL,Male,Caucasian,11/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +14316,71676,64995,Probation,jerome,odney,NULL,Male,African-American,05/05/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,3/27/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +14316,71676,64995,Probation,jerome,odney,NULL,Male,African-American,05/05/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,3/27/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +14316,71676,64995,Probation,jerome,odney,NULL,Male,African-American,05/05/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62318,71678,64997,Probation,Cochran,Lori,Jean,Female,African-American,01/27/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,2,Medium,7,Risk of Violence,-2.79,2,Low,New,1,0 +62318,71678,64997,Probation,Cochran,Lori,Jean,Female,African-American,01/27/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +62318,71678,64997,Probation,Cochran,Lori,Jean,Female,African-American,01/27/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +62313,71671,64990,Probation,Daniel,Miesha,NULL,Female,African-American,02/12/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.96,5,Medium,New,1,0 +62313,71671,64990,Probation,Daniel,Miesha,NULL,Female,African-American,02/12/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,8,High,New,1,0 +62313,71671,64990,Probation,Daniel,Miesha,NULL,Female,African-American,02/12/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62293,71650,64970,PRETRIAL,Kirk,Richard,NULL,Male,Caucasian,01/11/43,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-4.29,1,Low,New,1,0 +62293,71650,64970,PRETRIAL,Kirk,Richard,NULL,Male,Caucasian,01/11/43,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-2.63,1,Low,New,1,0 +62293,71650,64970,PRETRIAL,Kirk,Richard,NULL,Male,Caucasian,01/11/43,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62303,71664,64984,PRETRIAL,Mosley,Javaris,NULL,Male,African-American,08/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/14 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +62303,71664,64984,PRETRIAL,Mosley,Javaris,NULL,Male,African-American,08/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/14 0:00,4,High,8,Risk of Recidivism,0.43,9,High,New,1,0 +62303,71664,64984,PRETRIAL,Mosley,Javaris,NULL,Male,African-American,08/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62309,71666,64986,Probation,McGuinness,Dennis,John,Male,Caucasian,12/03/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +62309,71666,64986,Probation,McGuinness,Dennis,John,Male,Caucasian,12/03/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +62309,71666,64986,Probation,McGuinness,Dennis,John,Male,Caucasian,12/03/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62319,71680,64999,Probation,Prophete,Bob,NULL,Male,African-American,08/11/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +62319,71680,64999,Probation,Prophete,Bob,NULL,Male,African-American,08/11/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +62319,71680,64999,Probation,Prophete,Bob,NULL,Male,African-American,08/11/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62307,71662,64982,Probation,Aracri,Vanessa,NULL,Female,Caucasian,07/15/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +62307,71662,64982,Probation,Aracri,Vanessa,NULL,Female,Caucasian,07/15/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +62307,71662,64982,Probation,Aracri,Vanessa,NULL,Female,Caucasian,07/15/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +62324,71683,65002,PRETRIAL,Sherrer,Charles,NULL,Male,African-American,10/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +62324,71683,65002,PRETRIAL,Sherrer,Charles,NULL,Male,African-American,10/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +62324,71683,65002,PRETRIAL,Sherrer,Charles,NULL,Male,African-American,10/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45590,71679,64998,PRETRIAL,Messina,Alan,Drew,Male,Other,05/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +45590,71679,64998,PRETRIAL,Messina,Alan,Drew,Male,Other,05/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +45590,71679,64998,PRETRIAL,Messina,Alan,Drew,Male,Other,05/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62292,71649,64969,PRETRIAL,KELLEY,RHETT,DONALD,Male,African-American,11/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/27/14 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +62292,71649,64969,PRETRIAL,KELLEY,RHETT,DONALD,Male,African-American,11/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +62292,71649,64969,PRETRIAL,KELLEY,RHETT,DONALD,Male,African-American,11/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/27/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62300,71658,64978,Probation,Beckford,Rajiv,NULL,Male,African-American,05/24/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +62300,71658,64978,Probation,Beckford,Rajiv,NULL,Male,African-American,05/24/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.83,10,High,New,1,0 +62300,71658,64978,Probation,Beckford,Rajiv,NULL,Male,African-American,05/24/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +865,71663,64983,PRETRIAL,Mitchell,Jermaine,NULL,Male,African-American,03/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +865,71663,64983,PRETRIAL,Mitchell,Jermaine,NULL,Male,African-American,03/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +865,71663,64983,PRETRIAL,Mitchell,Jermaine,NULL,Male,African-American,03/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62308,71665,64985,Probation,Tirado,Nicole,NULL,Female,Hispanic,01/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +62308,71665,64985,Probation,Tirado,Nicole,NULL,Female,Hispanic,01/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +62308,71665,64985,Probation,Tirado,Nicole,NULL,Female,Hispanic,01/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62314,71672,64991,PRETRIAL,SPENCER,SHELDON,A,Male,African-American,09/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +62314,71672,64991,PRETRIAL,SPENCER,SHELDON,A,Male,African-American,09/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +62314,71672,64991,PRETRIAL,SPENCER,SHELDON,A,Male,African-American,09/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62310,71667,64987,Probation,Louis,Jolicoeur J,NULL,Male,Caucasian,09/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +62310,71667,64987,Probation,Louis,Jolicoeur J,NULL,Male,Caucasian,09/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +62310,71667,64987,Probation,Louis,Jolicoeur J,NULL,Male,Caucasian,09/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62316,71674,64993,PRETRIAL,jefferson,lashawn,NULL,Female,African-American,12/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.57,2,Low,New,1,0 +62316,71674,64993,PRETRIAL,jefferson,lashawn,NULL,Female,African-American,12/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +62316,71674,64993,PRETRIAL,jefferson,lashawn,NULL,Female,African-American,12/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62301,71659,64979,PRETRIAL,Sharo,Elizabeth,NULL,Female,Caucasian,12/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/27/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +62301,71659,64979,PRETRIAL,Sharo,Elizabeth,NULL,Female,Caucasian,12/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/27/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +62301,71659,64979,PRETRIAL,Sharo,Elizabeth,NULL,Female,Caucasian,12/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62305,71661,64981,Probation,Zaidi,Hassan,NULL,Male,Other,06/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/27/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +62305,71661,64981,Probation,Zaidi,Hassan,NULL,Male,Other,06/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/27/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +62305,71661,64981,Probation,Zaidi,Hassan,NULL,Male,Other,06/27/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62323,71682,65001,Broward County,Irvin,Bryan,NULL,Male,African-American,02/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +62323,71682,65001,Broward County,Irvin,Bryan,NULL,Male,African-American,02/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,4,High,8,Risk of Recidivism,0.98,10,High,New,1,0 +62323,71682,65001,Broward County,Irvin,Bryan,NULL,Male,African-American,02/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62296,71653,64973,PRETRIAL,HARDEN,MARK,I,Male,African-American,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +62296,71653,64973,PRETRIAL,HARDEN,MARK,I,Male,African-American,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +62296,71653,64973,PRETRIAL,HARDEN,MARK,I,Male,African-American,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62297,71654,64974,PRETRIAL,Aguront,William,NULL,Male,Hispanic,06/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/27/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +62297,71654,64974,PRETRIAL,Aguront,William,NULL,Male,Hispanic,06/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/27/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +62297,71654,64974,PRETRIAL,Aguront,William,NULL,Male,Hispanic,06/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +1105,71677,64996,Probation,Plant,William,R,Male,Caucasian,07/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +1105,71677,64996,Probation,Plant,William,R,Male,Caucasian,07/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +1105,71677,64996,Probation,Plant,William,R,Male,Caucasian,07/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/27/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62294,71651,64971,PRETRIAL,Akbar,Alijon,NULL,Male,Caucasian,08/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +62294,71651,64971,PRETRIAL,Akbar,Alijon,NULL,Male,Caucasian,08/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +62294,71651,64971,PRETRIAL,Akbar,Alijon,NULL,Male,Caucasian,08/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +62312,71669,64989,PRETRIAL,Valcin,Phillip,NULL,Male,African-American,06/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +62312,71669,64989,PRETRIAL,Valcin,Phillip,NULL,Male,African-American,06/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +62312,71669,64989,PRETRIAL,Valcin,Phillip,NULL,Male,African-American,06/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/27/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62354,71719,65035,Probation,suarez,carlos,NULL,Male,Hispanic,01/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +62354,71719,65035,Probation,suarez,carlos,NULL,Male,Hispanic,01/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +62354,71719,65035,Probation,suarez,carlos,NULL,Male,Hispanic,01/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +38057,71716,37473,PRETRIAL,Roberts,Anthony,NULL,Male,African-American,03/01/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,Copy,1,0 +38057,71716,37473,PRETRIAL,Roberts,Anthony,NULL,Male,African-American,03/01/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,Copy,1,0 +38057,71716,37473,PRETRIAL,Roberts,Anthony,NULL,Male,African-American,03/01/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +57938,66257,60093,PRETRIAL,FLETCHER,MARCUS,NULL,Male,African-American,04/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/28/14 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +57938,66257,60093,PRETRIAL,FLETCHER,MARCUS,NULL,Male,African-American,04/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/28/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +57938,66257,60093,PRETRIAL,FLETCHER,MARCUS,NULL,Male,African-American,04/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62331,71690,65009,PRETRIAL,Barrett,Glenn,NULL,Male,African-American,12/13/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +62331,71690,65009,PRETRIAL,Barrett,Glenn,NULL,Male,African-American,12/13/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +62331,71690,65009,PRETRIAL,Barrett,Glenn,NULL,Male,African-American,12/13/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62340,71703,65021,Probation,DUNCAN,CHANCE,NULL,Male,Caucasian,01/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +62340,71703,65021,Probation,DUNCAN,CHANCE,NULL,Male,Caucasian,01/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +62340,71703,65021,Probation,DUNCAN,CHANCE,NULL,Male,Caucasian,01/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62334,71695,65013,PRETRIAL,Bey,Jenna,NULL,Female,Caucasian,08/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +62334,71695,65013,PRETRIAL,Bey,Jenna,NULL,Female,Caucasian,08/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +62334,71695,65013,PRETRIAL,Bey,Jenna,NULL,Female,Caucasian,08/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62333,71693,65012,PRETRIAL,Danovich,Jonathan,NULL,Male,Caucasian,12/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +62333,71693,65012,PRETRIAL,Danovich,Jonathan,NULL,Male,Caucasian,12/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +62333,71693,65012,PRETRIAL,Danovich,Jonathan,NULL,Male,Caucasian,12/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62327,71686,65005,PRETRIAL,Garris,Ashley,Marie,Female,African-American,03/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +62327,71686,65005,PRETRIAL,Garris,Ashley,Marie,Female,African-American,03/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +62327,71686,65005,PRETRIAL,Garris,Ashley,Marie,Female,African-American,03/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +14028,71721,65037,PRETRIAL,marsh,stephen,NULL,Male,Caucasian,09/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +14028,71721,65037,PRETRIAL,marsh,stephen,NULL,Male,Caucasian,09/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +14028,71721,65037,PRETRIAL,marsh,stephen,NULL,Male,Caucasian,09/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62339,71700,65018,Probation,Sanchez,Jairo,Rios,Male,Hispanic,11/30/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/28/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +62339,71700,65018,Probation,Sanchez,Jairo,Rios,Male,Hispanic,11/30/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/28/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +62339,71700,65018,Probation,Sanchez,Jairo,Rios,Male,Hispanic,11/30/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62345,71707,65025,Probation,Hernandez,Rodolfo,NULL,Male,Hispanic,10/26/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +62345,71707,65025,Probation,Hernandez,Rodolfo,NULL,Male,Hispanic,10/26/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +62345,71707,65025,Probation,Hernandez,Rodolfo,NULL,Male,Hispanic,10/26/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62350,71714,65031,PRETRIAL,harrison,harry,NULL,Male,African-American,03/26/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +62350,71714,65031,PRETRIAL,harrison,harry,NULL,Male,African-American,03/26/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +62350,71714,65031,PRETRIAL,harrison,harry,NULL,Male,African-American,03/26/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62325,71684,65003,PRETRIAL,Gillstrap,Adam,NULL,Male,Caucasian,04/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +62325,71684,65003,PRETRIAL,Gillstrap,Adam,NULL,Male,Caucasian,04/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +62325,71684,65003,PRETRIAL,Gillstrap,Adam,NULL,Male,Caucasian,04/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62329,71688,65007,PRETRIAL,Dowdy,Jeffery,NULL,Male,Caucasian,05/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +62329,71688,65007,PRETRIAL,Dowdy,Jeffery,NULL,Male,Caucasian,05/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,4,High,8,Risk of Recidivism,1.07,10,High,New,1,0 +62329,71688,65007,PRETRIAL,Dowdy,Jeffery,NULL,Male,Caucasian,05/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62332,71691,65010,PRETRIAL,Johnson,Marcus,NULL,Female,African-American,03/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +62332,71691,65010,PRETRIAL,Johnson,Marcus,NULL,Female,African-American,03/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +62332,71691,65010,PRETRIAL,Johnson,Marcus,NULL,Female,African-American,03/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62346,71709,65027,Probation,PHILLIPS,PAMELA,NULL,Female,Caucasian,06/07/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +62346,71709,65027,Probation,PHILLIPS,PAMELA,NULL,Female,Caucasian,06/07/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +62346,71709,65027,Probation,PHILLIPS,PAMELA,NULL,Female,Caucasian,06/07/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53037,71692,65011,PRETRIAL,Collier,Trena,NULL,Female,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/28/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +53037,71692,65011,PRETRIAL,Collier,Trena,NULL,Female,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/28/14 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +53037,71692,65011,PRETRIAL,Collier,Trena,NULL,Female,African-American,03/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62352,71717,65033,Probation,Lesmez,Esteban,NULL,Male,Hispanic,06/09/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/28/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +62352,71717,65033,Probation,Lesmez,Esteban,NULL,Male,Hispanic,06/09/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +62352,71717,65033,Probation,Lesmez,Esteban,NULL,Male,Hispanic,06/09/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/28/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62335,71696,65014,PRETRIAL,Assadi,Abraham,NULL,Male,Caucasian,12/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +62335,71696,65014,PRETRIAL,Assadi,Abraham,NULL,Male,Caucasian,12/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +62335,71696,65014,PRETRIAL,Assadi,Abraham,NULL,Male,Caucasian,12/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62349,71713,65030,Probation,Esquivel,Osnely,Guzmely,Male,Hispanic,12/26/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +62349,71713,65030,Probation,Esquivel,Osnely,Guzmely,Male,Hispanic,12/26/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +62349,71713,65030,Probation,Esquivel,Osnely,Guzmely,Male,Hispanic,12/26/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62328,71687,65006,PRETRIAL,Hise,David,Edward,Male,Caucasian,01/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,2,Medium,7,Risk of Violence,-1.43,7,Medium,New,1,0 +62328,71687,65006,PRETRIAL,Hise,David,Edward,Male,Caucasian,01/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +62328,71687,65006,PRETRIAL,Hise,David,Edward,Male,Caucasian,01/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +8996,71701,65019,Probation,stone,shannon,NULL,Male,Caucasian,10/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +8996,71701,65019,Probation,stone,shannon,NULL,Male,Caucasian,10/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +8996,71701,65019,Probation,stone,shannon,NULL,Male,Caucasian,10/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62326,71685,65004,PRETRIAL,Bu Medina,Serbelio,NULL,Male,Hispanic,03/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/28/14 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +62326,71685,65004,PRETRIAL,Bu Medina,Serbelio,NULL,Male,Hispanic,03/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/28/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +62326,71685,65004,PRETRIAL,Bu Medina,Serbelio,NULL,Male,Hispanic,03/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62338,71699,65017,Probation,salter,christina,NULL,Female,Caucasian,01/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.14,4,Low,New,1,0 +62338,71699,65017,Probation,salter,christina,NULL,Female,Caucasian,01/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.03,8,High,New,1,0 +62338,71699,65017,Probation,salter,christina,NULL,Female,Caucasian,01/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62344,71706,65024,Probation,Glenn,Wallace,NULL,Male,African-American,05/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/14 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +62344,71706,65024,Probation,Glenn,Wallace,NULL,Male,African-American,05/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +62344,71706,65024,Probation,Glenn,Wallace,NULL,Male,African-American,05/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,3/28/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62343,71708,65026,PRETRIAL,APRILE,AARON,NULL,Male,Hispanic,11/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/28/14 0:00,4,High,7,Risk of Violence,-0.54,10,High,New,1,0 +62343,71708,65026,PRETRIAL,APRILE,AARON,NULL,Male,Hispanic,11/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/28/14 0:00,4,High,8,Risk of Recidivism,1.12,10,High,New,1,0 +62343,71708,65026,PRETRIAL,APRILE,AARON,NULL,Male,Hispanic,11/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/28/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +62348,71712,65029,DRRD,Jones,Eric,NULL,Male,African-American,02/13/95,17,All Scales,Intake,English,Pretrial,Probation,Single,3/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.06,8,High,New,1,0 +62348,71712,65029,DRRD,Jones,Eric,NULL,Male,African-American,02/13/95,17,All Scales,Intake,English,Pretrial,Probation,Single,3/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.46,4,Low,New,1,0 +62348,71712,65029,DRRD,Jones,Eric,NULL,Male,African-American,02/13/95,17,All Scales,Intake,English,Pretrial,Probation,Single,3/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62336,71697,65015,PRETRIAL,ANTHONY,CAMILL,NULL,Male,African-American,11/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +62336,71697,65015,PRETRIAL,ANTHONY,CAMILL,NULL,Male,African-American,11/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +62336,71697,65015,PRETRIAL,ANTHONY,CAMILL,NULL,Male,African-American,11/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62341,71704,65022,PRETRIAL,JIMINEZ,JUAN,OCASIO,Male,Hispanic,10/04/76,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +62341,71704,65022,PRETRIAL,JIMINEZ,JUAN,OCASIO,Male,Hispanic,10/04/76,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +62341,71704,65022,PRETRIAL,JIMINEZ,JUAN,OCASIO,Male,Hispanic,10/04/76,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62353,71718,65034,Probation,Troy,Comarcho,NULL,Male,Hispanic,11/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +62353,71718,65034,Probation,Troy,Comarcho,NULL,Male,Hispanic,11/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +62353,71718,65034,Probation,Troy,Comarcho,NULL,Male,Hispanic,11/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62330,71689,65008,PRETRIAL,Poulard,Fritz,NULL,Male,Caucasian,06/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +62330,71689,65008,PRETRIAL,Poulard,Fritz,NULL,Male,Caucasian,06/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +62330,71689,65008,PRETRIAL,Poulard,Fritz,NULL,Male,Caucasian,06/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/28/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57426,71702,65020,Probation,sabb,harvey,NULL,Male,African-American,09/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +57426,71702,65020,Probation,sabb,harvey,NULL,Male,African-American,09/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +57426,71702,65020,Probation,sabb,harvey,NULL,Male,African-American,09/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +6086,71720,65036,PRETRIAL,LUBIN,DANIEL,NULL,Male,African-American,07/30/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +6086,71720,65036,PRETRIAL,LUBIN,DANIEL,NULL,Male,African-American,07/30/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +6086,71720,65036,PRETRIAL,LUBIN,DANIEL,NULL,Male,African-American,07/30/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62351,71715,65032,PRETRIAL,Lemmon,Richard,NULL,Male,Caucasian,03/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +62351,71715,65032,PRETRIAL,Lemmon,Richard,NULL,Male,Caucasian,03/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +62351,71715,65032,PRETRIAL,Lemmon,Richard,NULL,Male,Caucasian,03/27/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62359,71728,65043,PRETRIAL,GODDARD,RODERICK,LOUIS,Male,African-American,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +62359,71728,65043,PRETRIAL,GODDARD,RODERICK,LOUIS,Male,African-American,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +62359,71728,65043,PRETRIAL,GODDARD,RODERICK,LOUIS,Male,African-American,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62356,71723,65039,PRETRIAL,Burrows,Reynard,NULL,Male,African-American,08/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +62356,71723,65039,PRETRIAL,Burrows,Reynard,NULL,Male,African-American,08/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +62356,71723,65039,PRETRIAL,Burrows,Reynard,NULL,Male,African-American,08/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +37981,71725,37384,PRETRIAL,MCKINNEY,MICHEAL,NULL,Male,African-American,12/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,4,High,7,Risk of Violence,-1.15,8,High,Copy,1,0 +37981,71725,37384,PRETRIAL,MCKINNEY,MICHEAL,NULL,Male,African-American,12/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,4,High,8,Risk of Recidivism,2.36,10,High,Copy,1,0 +37981,71725,37384,PRETRIAL,MCKINNEY,MICHEAL,NULL,Male,African-American,12/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +46131,71731,46491,PRETRIAL,Joseph,Vitay,NULL,Male,African-American,09/06/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,Copy,1,0 +46131,71731,46491,PRETRIAL,Joseph,Vitay,NULL,Male,African-American,09/06/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,Copy,1,0 +46131,71731,46491,PRETRIAL,Joseph,Vitay,NULL,Male,African-American,09/06/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +62358,71727,65042,PRETRIAL,PULLENS,JOSEPH,ANTHONY,Male,Caucasian,10/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +62358,71727,65042,PRETRIAL,PULLENS,JOSEPH,ANTHONY,Male,Caucasian,10/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +62358,71727,65042,PRETRIAL,PULLENS,JOSEPH,ANTHONY,Male,Caucasian,10/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62360,71729,65044,PRETRIAL,ROSARIO,ADAM,ANTHONY,Male,Caucasian,03/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +62360,71729,65044,PRETRIAL,ROSARIO,ADAM,ANTHONY,Male,Caucasian,03/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +62360,71729,65044,PRETRIAL,ROSARIO,ADAM,ANTHONY,Male,Caucasian,03/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62355,71722,65038,PRETRIAL,Piper,Danny,NULL,Male,Caucasian,12/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/29/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +62355,71722,65038,PRETRIAL,Piper,Danny,NULL,Male,Caucasian,12/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/29/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +62355,71722,65038,PRETRIAL,Piper,Danny,NULL,Male,Caucasian,12/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62361,71730,65045,PRETRIAL,Titus,Willie,L,Male,African-American,11/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62361,71730,65045,PRETRIAL,Titus,Willie,L,Male,African-American,11/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +62361,71730,65045,PRETRIAL,Titus,Willie,L,Male,African-American,11/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +3369,71726,65041,Probation,Potter,Brian,L,Male,African-American,07/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +3369,71726,65041,Probation,Potter,Brian,L,Male,African-American,07/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +3369,71726,65041,Probation,Potter,Brian,L,Male,African-American,07/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62357,71724,65040,PRETRIAL,WHALEN,ZACHARY,FRANK,Male,African-American,09/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +62357,71724,65040,PRETRIAL,WHALEN,ZACHARY,FRANK,Male,African-American,09/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +62357,71724,65040,PRETRIAL,WHALEN,ZACHARY,FRANK,Male,African-American,09/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62367,71737,65051,PRETRIAL,Tovar,Jonathan,NULL,Male,Caucasian,05/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +62367,71737,65051,PRETRIAL,Tovar,Jonathan,NULL,Male,Caucasian,05/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +62367,71737,65051,PRETRIAL,Tovar,Jonathan,NULL,Male,Caucasian,05/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62369,71740,65053,PRETRIAL,RAY,KENNETH,NULL,Male,Caucasian,12/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.69,9,High,New,1,0 +62369,71740,65053,PRETRIAL,RAY,KENNETH,NULL,Male,Caucasian,12/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +62369,71740,65053,PRETRIAL,RAY,KENNETH,NULL,Male,Caucasian,12/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +62362,71732,65046,PRETRIAL,Sheridan,Ward,NULL,Male,Caucasian,03/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +62362,71732,65046,PRETRIAL,Sheridan,Ward,NULL,Male,Caucasian,03/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +62362,71732,65046,PRETRIAL,Sheridan,Ward,NULL,Male,Caucasian,03/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62365,71735,65049,PRETRIAL,Menendez,Marilyn,NULL,Female,Caucasian,04/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +62365,71735,65049,PRETRIAL,Menendez,Marilyn,NULL,Female,Caucasian,04/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +62365,71735,65049,PRETRIAL,Menendez,Marilyn,NULL,Female,Caucasian,04/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58536,71744,60733,Probation,Hylton,Gervaise,NULL,Male,African-American,06/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,Copy,1,0 +58536,71744,60733,Probation,Hylton,Gervaise,NULL,Male,African-American,06/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,Copy,1,0 +58536,71744,60733,Probation,Hylton,Gervaise,NULL,Male,African-American,06/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +62371,71742,65055,PRETRIAL,STEWART,MILTON,NULL,Male,Other,12/07/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/30/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +62371,71742,65055,PRETRIAL,STEWART,MILTON,NULL,Male,Other,12/07/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/30/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +62371,71742,65055,PRETRIAL,STEWART,MILTON,NULL,Male,Other,12/07/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/30/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +62372,71743,65056,PRETRIAL,MARTINEZ,PABLO,NULL,Male,Hispanic,03/02/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +62372,71743,65056,PRETRIAL,MARTINEZ,PABLO,NULL,Male,Hispanic,03/02/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +62372,71743,65056,PRETRIAL,MARTINEZ,PABLO,NULL,Male,Hispanic,03/02/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62368,71738,65052,PRETRIAL,DUROSEAU,OURIAN,NULL,Male,African-American,09/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +62368,71738,65052,PRETRIAL,DUROSEAU,OURIAN,NULL,Male,African-American,09/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,4,High,8,Risk of Recidivism,0.76,10,High,New,1,0 +62368,71738,65052,PRETRIAL,DUROSEAU,OURIAN,NULL,Male,African-American,09/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62366,71736,65050,PRETRIAL,Angotti,Anthony,NULL,Male,Caucasian,06/10/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +62366,71736,65050,PRETRIAL,Angotti,Anthony,NULL,Male,Caucasian,06/10/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +62366,71736,65050,PRETRIAL,Angotti,Anthony,NULL,Male,Caucasian,06/10/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62363,71733,65047,PRETRIAL,DRZEWUCKI,ALEXANDER,NULL,Male,Caucasian,05/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +62363,71733,65047,PRETRIAL,DRZEWUCKI,ALEXANDER,NULL,Male,Caucasian,05/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +62363,71733,65047,PRETRIAL,DRZEWUCKI,ALEXANDER,NULL,Male,Caucasian,05/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62364,71739,65048,PRETRIAL,NAVARRO,GILBERT,NULL,Male,Caucasian,10/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,Copy,1,0 +62364,71739,65048,PRETRIAL,NAVARRO,GILBERT,NULL,Male,Caucasian,10/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,Copy,1,0 +62364,71739,65048,PRETRIAL,NAVARRO,GILBERT,NULL,Male,Caucasian,10/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/30/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +62370,71741,65054,PRETRIAL,Griffin,Dale,NULL,Male,Caucasian,09/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +62370,71741,65054,PRETRIAL,Griffin,Dale,NULL,Male,Caucasian,09/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +62370,71741,65054,PRETRIAL,Griffin,Dale,NULL,Male,Caucasian,09/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/30/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62395,71770,65080,PRETRIAL,middleton,sue,NULL,Female,Caucasian,02/19/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/31/14 0:00,1,Low,7,Risk of Violence,-4.36,1,Low,New,1,0 +62395,71770,65080,PRETRIAL,middleton,sue,NULL,Female,Caucasian,02/19/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/31/14 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +62395,71770,65080,PRETRIAL,middleton,sue,NULL,Female,Caucasian,02/19/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +48323,71762,49005,PRETRIAL,Fredricks,Evins,NULL,Male,African-American,07/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,4,High,7,Risk of Violence,-1.2,8,High,Copy,1,0 +48323,71762,49005,PRETRIAL,Fredricks,Evins,NULL,Male,African-American,07/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,4,High,8,Risk of Recidivism,1.33,10,High,Copy,1,0 +48323,71762,49005,PRETRIAL,Fredricks,Evins,NULL,Male,African-American,07/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,4,High,18,Risk of Failure to Appear,34,10,High,Copy,1,0 +62377,71749,65061,PRETRIAL,MUNOZ,RANDY,NULL,Male,Caucasian,03/29/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +62377,71749,65061,PRETRIAL,MUNOZ,RANDY,NULL,Male,Caucasian,03/29/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +62377,71749,65061,PRETRIAL,MUNOZ,RANDY,NULL,Male,Caucasian,03/29/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62405,71783,65091,Probation,Flores,Reymundo,NULL,Male,Hispanic,10/25/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/31/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +62405,71783,65091,Probation,Flores,Reymundo,NULL,Male,Hispanic,10/25/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +62405,71783,65091,Probation,Flores,Reymundo,NULL,Male,Hispanic,10/25/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62382,71754,65066,PRETRIAL,SaintHilaire,Ketchmarken,NULL,Male,Other,01/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +62382,71754,65066,PRETRIAL,SaintHilaire,Ketchmarken,NULL,Male,Other,01/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +62382,71754,65066,PRETRIAL,SaintHilaire,Ketchmarken,NULL,Male,Other,01/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62392,71767,65077,PRETRIAL,Casalino,Mikrko,Jose,Male,Hispanic,06/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/31/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +62392,71767,65077,PRETRIAL,Casalino,Mikrko,Jose,Male,Hispanic,06/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/31/14 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +62392,71767,65077,PRETRIAL,Casalino,Mikrko,Jose,Male,Hispanic,06/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62374,71746,65058,PRETRIAL,EMILE,RAOUL,JUNIOR,Male,African-American,01/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +62374,71746,65058,PRETRIAL,EMILE,RAOUL,JUNIOR,Male,African-American,01/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +62374,71746,65058,PRETRIAL,EMILE,RAOUL,JUNIOR,Male,African-American,01/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62396,71771,65081,Probation,Davis,tamara,Lynley,Female,Caucasian,08/13/66,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +62396,71771,65081,Probation,Davis,tamara,Lynley,Female,Caucasian,08/13/66,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +62396,71771,65081,Probation,Davis,tamara,Lynley,Female,Caucasian,08/13/66,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +62407,71785,65093,Probation,Tate,Christopher,NULL,Male,Hispanic,10/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +62407,71785,65093,Probation,Tate,Christopher,NULL,Male,Hispanic,10/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +62407,71785,65093,Probation,Tate,Christopher,NULL,Male,Hispanic,10/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62378,71750,65062,PRETRIAL,GARCIA,JAVIER,NULL,Male,Hispanic,04/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +62378,71750,65062,PRETRIAL,GARCIA,JAVIER,NULL,Male,Hispanic,04/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +62378,71750,65062,PRETRIAL,GARCIA,JAVIER,NULL,Male,Hispanic,04/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62385,71757,65069,Probation,Andres,Francisco,Juan,Male,Hispanic,04/25/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/31/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +62385,71757,65069,Probation,Andres,Francisco,Juan,Male,Hispanic,04/25/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/31/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +62385,71757,65069,Probation,Andres,Francisco,Juan,Male,Hispanic,04/25/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62390,71764,65074,Probation,jack,nemorin,NULL,Male,African-American,01/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +62390,71764,65074,Probation,jack,nemorin,NULL,Male,African-American,01/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +62390,71764,65074,Probation,jack,nemorin,NULL,Male,African-American,01/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62401,71778,65086,Probation,Bustillo,Stacey,NULL,Female,Caucasian,05/19/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +62401,71778,65086,Probation,Bustillo,Stacey,NULL,Female,Caucasian,05/19/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +62401,71778,65086,Probation,Bustillo,Stacey,NULL,Female,Caucasian,05/19/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +18877,71780,65088,PRETRIAL,COLEY,HERMAN,NULL,Male,African-American,06/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +18877,71780,65088,PRETRIAL,COLEY,HERMAN,NULL,Male,African-American,06/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +18877,71780,65088,PRETRIAL,COLEY,HERMAN,NULL,Male,African-American,06/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +62380,71752,65064,PRETRIAL,CASTANEDA,JORGE,ENRIQUE,Male,Hispanic,03/26/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/31/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +62380,71752,65064,PRETRIAL,CASTANEDA,JORGE,ENRIQUE,Male,Hispanic,03/26/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/31/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +62380,71752,65064,PRETRIAL,CASTANEDA,JORGE,ENRIQUE,Male,Hispanic,03/26/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62394,71769,65079,PRETRIAL,WHIDDON,ELIZABETH,NULL,Female,Caucasian,01/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/31/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +62394,71769,65079,PRETRIAL,WHIDDON,ELIZABETH,NULL,Female,Caucasian,01/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/31/14 0:00,1,Low,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +62394,71769,65079,PRETRIAL,WHIDDON,ELIZABETH,NULL,Female,Caucasian,01/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62376,71748,65060,PRETRIAL,TISDALE,KEENAN,D,Male,African-American,07/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +62376,71748,65060,PRETRIAL,TISDALE,KEENAN,D,Male,African-American,07/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +62376,71748,65060,PRETRIAL,TISDALE,KEENAN,D,Male,African-American,07/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62383,71755,65067,PRETRIAL,Pinedaboteo,Rodrigo,NULL,Male,Hispanic,04/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/31/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +62383,71755,65067,PRETRIAL,Pinedaboteo,Rodrigo,NULL,Male,Hispanic,04/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +62383,71755,65067,PRETRIAL,Pinedaboteo,Rodrigo,NULL,Male,Hispanic,04/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58538,71759,60736,PRETRIAL,Reed,Michael,NULL,Male,African-American,04/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/31/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,Copy,1,0 +58538,71759,60736,PRETRIAL,Reed,Michael,NULL,Male,African-American,04/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/31/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,Copy,1,0 +58538,71759,60736,PRETRIAL,Reed,Michael,NULL,Male,African-American,04/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +62397,71773,65082,PRETRIAL,RIVAS,JIMMY,NULL,Male,Hispanic,12/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +62397,71773,65082,PRETRIAL,RIVAS,JIMMY,NULL,Male,Hispanic,12/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +62397,71773,65082,PRETRIAL,RIVAS,JIMMY,NULL,Male,Hispanic,12/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +52867,71765,65075,PRETRIAL,KANE,KYLE,KEITH,Male,Caucasian,06/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +52867,71765,65075,PRETRIAL,KANE,KYLE,KEITH,Male,Caucasian,06/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +52867,71765,65075,PRETRIAL,KANE,KYLE,KEITH,Male,Caucasian,06/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62389,71763,65073,Probation,Gayoso,Guillermo,NULL,Male,Hispanic,05/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/31/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +62389,71763,65073,Probation,Gayoso,Guillermo,NULL,Male,Hispanic,05/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/31/14 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +62389,71763,65073,Probation,Gayoso,Guillermo,NULL,Male,Hispanic,05/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62387,71760,65071,Probation,menendez,yoanled,NULL,Male,Hispanic,11/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/31/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +62387,71760,65071,Probation,menendez,yoanled,NULL,Male,Hispanic,11/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +62387,71760,65071,Probation,menendez,yoanled,NULL,Male,Hispanic,11/17/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62400,71777,65085,Probation,ruiz,lysette,NULL,Female,Hispanic,12/27/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/31/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +62400,71777,65085,Probation,ruiz,lysette,NULL,Female,Hispanic,12/27/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +62400,71777,65085,Probation,ruiz,lysette,NULL,Female,Hispanic,12/27/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62375,71747,65059,PRETRIAL,Allencoveyou,Cody,NULL,Male,Caucasian,02/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +62375,71747,65059,PRETRIAL,Allencoveyou,Cody,NULL,Male,Caucasian,02/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +62375,71747,65059,PRETRIAL,Allencoveyou,Cody,NULL,Male,Caucasian,02/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,3/31/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62384,71756,65068,PRETRIAL,Castro,Jorge,NULL,Male,Hispanic,10/14/19,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,3/31/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +62384,71756,65068,PRETRIAL,Castro,Jorge,NULL,Male,Hispanic,10/14/19,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +62384,71756,65068,PRETRIAL,Castro,Jorge,NULL,Male,Hispanic,10/14/19,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62403,71781,65089,Probation,Keegan,Peter,NULL,Male,Caucasian,02/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/31/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +62403,71781,65089,Probation,Keegan,Peter,NULL,Male,Caucasian,02/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/31/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +62403,71781,65089,Probation,Keegan,Peter,NULL,Male,Caucasian,02/12/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +62379,71751,65063,PRETRIAL,JORDAN,CHRISTOPHER,NULL,Male,African-American,05/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +62379,71751,65063,PRETRIAL,JORDAN,CHRISTOPHER,NULL,Male,African-American,05/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +62379,71751,65063,PRETRIAL,JORDAN,CHRISTOPHER,NULL,Male,African-American,05/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62404,71782,65090,Probation,STEWART,AMANDA,GRACE,Female,Caucasian,01/17/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +62404,71782,65090,Probation,STEWART,AMANDA,GRACE,Female,Caucasian,01/17/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +62404,71782,65090,Probation,STEWART,AMANDA,GRACE,Female,Caucasian,01/17/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62381,71753,65065,PRETRIAL,Gopaul-Hilaire,Joy,NULL,Female,Other,02/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +62381,71753,65065,PRETRIAL,Gopaul-Hilaire,Joy,NULL,Female,Other,02/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +62381,71753,65065,PRETRIAL,Gopaul-Hilaire,Joy,NULL,Female,Other,02/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62393,71768,65078,Probation,STILLMAN,JESSE,NULL,Male,Caucasian,06/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +62393,71768,65078,Probation,STILLMAN,JESSE,NULL,Male,Caucasian,06/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +62393,71768,65078,Probation,STILLMAN,JESSE,NULL,Male,Caucasian,06/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58831,71774,61063,Probation,RODRIGUEZ,ROBERTO,NULL,Male,African-American,12/18/81,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +58831,71774,61063,Probation,RODRIGUEZ,ROBERTO,NULL,Male,African-American,12/18/81,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +58831,71774,61063,Probation,RODRIGUEZ,ROBERTO,NULL,Male,African-American,12/18/81,17,All Scales,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +62388,71761,65072,PRETRIAL,Nevarezsarria,Caridad,NULL,Female,Hispanic,12/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/31/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +62388,71761,65072,PRETRIAL,Nevarezsarria,Caridad,NULL,Female,Hispanic,12/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/31/14 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +62388,71761,65072,PRETRIAL,Nevarezsarria,Caridad,NULL,Female,Hispanic,12/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62399,71776,65084,Probation,Bernasek,Bradley,Todd,Male,Caucasian,10/14/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +62399,71776,65084,Probation,Bernasek,Bradley,Todd,Male,Caucasian,10/14/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +62399,71776,65084,Probation,Bernasek,Bradley,Todd,Male,Caucasian,10/14/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62391,71766,65076,Probation,BRYANT,JERICO,NULL,Male,Caucasian,04/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,2,Medium,7,Risk of Violence,-2.64,2,Low,New,1,0 +62391,71766,65076,Probation,BRYANT,JERICO,NULL,Male,Caucasian,04/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +62391,71766,65076,Probation,BRYANT,JERICO,NULL,Male,Caucasian,04/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +62406,71784,65092,Probation,wilson,DONOVAN,NULL,Male,African-American,08/06/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +62406,71784,65092,Probation,wilson,DONOVAN,NULL,Male,African-American,08/06/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +62406,71784,65092,Probation,wilson,DONOVAN,NULL,Male,African-American,08/06/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62386,71758,65070,PRETRIAL,Baade,Stuart,NULL,Male,Caucasian,08/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +62386,71758,65070,PRETRIAL,Baade,Stuart,NULL,Male,Caucasian,08/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +62386,71758,65070,PRETRIAL,Baade,Stuart,NULL,Male,Caucasian,08/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62373,71745,65057,PRETRIAL,Davila,Marcelo,NULL,Male,Hispanic,04/09/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +62373,71745,65057,PRETRIAL,Davila,Marcelo,NULL,Male,Hispanic,04/09/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/14 0:00,1,Low,8,Risk of Recidivism,-2.76,1,Low,New,1,0 +62373,71745,65057,PRETRIAL,Davila,Marcelo,NULL,Male,Hispanic,04/09/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62402,71779,65087,Probation,fadevkin,aleksandr,NULL,Male,Caucasian,09/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +62402,71779,65087,Probation,fadevkin,aleksandr,NULL,Male,Caucasian,09/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +62402,71779,65087,Probation,fadevkin,aleksandr,NULL,Male,Caucasian,09/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,3/31/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62426,71813,65118,PRETRIAL,HARTSELL,JESSE,NULL,Male,Caucasian,06/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +62426,71813,65118,PRETRIAL,HARTSELL,JESSE,NULL,Male,Caucasian,06/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +62426,71813,65118,PRETRIAL,HARTSELL,JESSE,NULL,Male,Caucasian,06/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +62412,71792,65099,PRETRIAL,Phillips,Kenneth,Ray,Male,Caucasian,01/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +62412,71792,65099,PRETRIAL,Phillips,Kenneth,Ray,Male,Caucasian,01/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +62412,71792,65099,PRETRIAL,Phillips,Kenneth,Ray,Male,Caucasian,01/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +62409,71787,65095,PRETRIAL,WILLIAMS,LEMY,NULL,Male,African-American,09/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,New,1,0 +62409,71787,65095,PRETRIAL,WILLIAMS,LEMY,NULL,Male,African-American,09/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +62409,71787,65095,PRETRIAL,WILLIAMS,LEMY,NULL,Male,African-American,09/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62421,71805,65112,Probation,Miller,Robert,NULL,Male,Caucasian,08/13/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +62421,71805,65112,Probation,Miller,Robert,NULL,Male,Caucasian,08/13/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +62421,71805,65112,Probation,Miller,Robert,NULL,Male,Caucasian,08/13/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62414,71795,65102,PRETRIAL,WATSON,ROBERT,E,Male,African-American,07/29/38,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/1/14 0:00,1,Low,7,Risk of Violence,-4.46,1,Low,New,1,0 +62414,71795,65102,PRETRIAL,WATSON,ROBERT,E,Male,African-American,07/29/38,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/1/14 0:00,1,Low,8,Risk of Recidivism,-2.8,1,Low,New,1,0 +62414,71795,65102,PRETRIAL,WATSON,ROBERT,E,Male,African-American,07/29/38,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62424,71810,65115,Probation,cameron,kane,NULL,Male,African-American,03/16/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +62424,71810,65115,Probation,cameron,kane,NULL,Male,African-American,03/16/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,8,Risk of Recidivism,-0.23,5,Medium,New,1,0 +62424,71810,65115,Probation,cameron,kane,NULL,Male,African-American,03/16/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62416,71797,65104,PRETRIAL,Parra,Jose,Luis,Male,Caucasian,07/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +62416,71797,65104,PRETRIAL,Parra,Jose,Luis,Male,Caucasian,07/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +62416,71797,65104,PRETRIAL,Parra,Jose,Luis,Male,Caucasian,07/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62420,71803,65110,Probation,RUIZ,CHERYL,NULL,Female,Caucasian,01/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,2,Medium,7,Risk of Violence,-2.7,2,Low,New,1,0 +62420,71803,65110,Probation,RUIZ,CHERYL,NULL,Female,Caucasian,01/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +62420,71803,65110,Probation,RUIZ,CHERYL,NULL,Female,Caucasian,01/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62410,71789,65096,PRETRIAL,FRANCES,MARK,ANTHONY,Male,African-American,03/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +62410,71789,65096,PRETRIAL,FRANCES,MARK,ANTHONY,Male,African-American,03/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +62410,71789,65096,PRETRIAL,FRANCES,MARK,ANTHONY,Male,African-American,03/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62343,71802,65109,PRETRIAL,APRILE,AARON,NULL,Male,Hispanic,11/02/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/14 0:00,4,High,7,Risk of Violence,-0.55,10,High,New,1,0 +62343,71802,65109,PRETRIAL,APRILE,AARON,NULL,Male,Hispanic,11/02/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/14 0:00,4,High,8,Risk of Recidivism,1.07,10,High,New,1,0 +62343,71802,65109,PRETRIAL,APRILE,AARON,NULL,Male,Hispanic,11/02/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/1/14 0:00,4,High,18,Risk of Failure to Appear,36,10,High,New,1,0 +62417,71798,65105,PRETRIAL,Miranda,Stefanie,NULL,Female,Hispanic,01/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/1/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +62417,71798,65105,PRETRIAL,Miranda,Stefanie,NULL,Female,Hispanic,01/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/1/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +62417,71798,65105,PRETRIAL,Miranda,Stefanie,NULL,Female,Hispanic,01/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62428,71816,65121,Probation,allen,marchelle,NULL,Female,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +62428,71816,65121,Probation,allen,marchelle,NULL,Female,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +62428,71816,65121,Probation,allen,marchelle,NULL,Female,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55404,71793,65100,PRETRIAL,Lewis,Rodney,NULL,Male,African-American,06/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,2,Medium,7,Risk of Violence,-2.73,2,Low,New,1,0 +55404,71793,65100,PRETRIAL,Lewis,Rodney,NULL,Male,African-American,06/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +55404,71793,65100,PRETRIAL,Lewis,Rodney,NULL,Male,African-American,06/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +62408,71786,65094,PRETRIAL,ELLIS,CALVIN,LEE,Male,African-American,01/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +62408,71786,65094,PRETRIAL,ELLIS,CALVIN,LEE,Male,African-American,01/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +62408,71786,65094,PRETRIAL,ELLIS,CALVIN,LEE,Male,African-American,01/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62418,71800,65107,Probation,Veliky,Brandon,NULL,Male,Caucasian,12/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +62418,71800,65107,Probation,Veliky,Brandon,NULL,Male,Caucasian,12/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +62418,71800,65107,Probation,Veliky,Brandon,NULL,Male,Caucasian,12/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62413,71794,65101,PRETRIAL,Roberts,Vivian,NULL,Male,Other,01/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/1/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +62413,71794,65101,PRETRIAL,Roberts,Vivian,NULL,Male,Other,01/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/1/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +62413,71794,65101,PRETRIAL,Roberts,Vivian,NULL,Male,Other,01/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +36795,71811,65116,PRETRIAL,Fortner,Wayne,NULL,Male,Caucasian,01/27/58,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Separated,4/1/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +36795,71811,65116,PRETRIAL,Fortner,Wayne,NULL,Male,Caucasian,01/27/58,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Separated,4/1/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +36795,71811,65116,PRETRIAL,Fortner,Wayne,NULL,Male,Caucasian,01/27/58,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Separated,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62411,71790,65097,PRETRIAL,Archer,Taryck,Andrew,Male,Other,08/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +62411,71790,65097,PRETRIAL,Archer,Taryck,Andrew,Male,Other,08/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +62411,71790,65097,PRETRIAL,Archer,Taryck,Andrew,Male,Other,08/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62427,71815,65120,Probation,May,Daniel,NULL,Male,Caucasian,06/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +62427,71815,65120,Probation,May,Daniel,NULL,Male,Caucasian,06/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +62427,71815,65120,Probation,May,Daniel,NULL,Male,Caucasian,06/06/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +62422,71808,65113,Probation,Stamand,Joseph,NULL,Male,Caucasian,11/29/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +62422,71808,65113,Probation,Stamand,Joseph,NULL,Male,Caucasian,11/29/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +62422,71808,65113,Probation,Stamand,Joseph,NULL,Male,Caucasian,11/29/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62425,71812,65117,PRETRIAL,Bergeron,Ryan,NULL,Male,Caucasian,04/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.07,8,High,New,1,0 +62425,71812,65117,PRETRIAL,Bergeron,Ryan,NULL,Male,Caucasian,04/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +62425,71812,65117,PRETRIAL,Bergeron,Ryan,NULL,Male,Caucasian,04/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62415,71796,65103,PRETRIAL,WARREN,DEON,B,Male,African-American,08/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/14 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +62415,71796,65103,PRETRIAL,WARREN,DEON,B,Male,African-American,08/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +62415,71796,65103,PRETRIAL,WARREN,DEON,B,Male,African-American,08/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/1/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54199,71788,55781,PRETRIAL,MCKINNEY,TERRANCE,NULL,Male,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,4,High,7,Risk of Violence,-0.65,9,High,Copy,1,0 +54199,71788,55781,PRETRIAL,MCKINNEY,TERRANCE,NULL,Male,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,4,High,8,Risk of Recidivism,0.19,8,High,Copy,1,0 +54199,71788,55781,PRETRIAL,MCKINNEY,TERRANCE,NULL,Male,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +62419,71801,65108,Probation,pinnock,tamark,NULL,Male,African-American,09/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/1/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +62419,71801,65108,Probation,pinnock,tamark,NULL,Male,African-American,09/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/1/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +62419,71801,65108,Probation,pinnock,tamark,NULL,Male,African-American,09/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +15910,71791,65098,PRETRIAL,PEREZ,JOSHUA,NULL,Male,Hispanic,02/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.23,8,High,New,1,0 +15910,71791,65098,PRETRIAL,PEREZ,JOSHUA,NULL,Male,Hispanic,02/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +15910,71791,65098,PRETRIAL,PEREZ,JOSHUA,NULL,Male,Hispanic,02/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62423,71809,65114,Probation,cabrera,rafael,NULL,Male,Caucasian,11/16/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/1/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +62423,71809,65114,Probation,cabrera,rafael,NULL,Male,Caucasian,11/16/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/1/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +62423,71809,65114,Probation,cabrera,rafael,NULL,Male,Caucasian,11/16/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/1/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +27903,71838,65139,PRETRIAL,Edwards,Brandon,NULL,Male,African-American,01/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +27903,71838,65139,PRETRIAL,Edwards,Brandon,NULL,Male,African-American,01/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,4,High,8,Risk of Recidivism,1.06,10,High,New,1,0 +27903,71838,65139,PRETRIAL,Edwards,Brandon,NULL,Male,African-American,01/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +13441,71843,65144,PRETRIAL,SINGLETARY,MICHAEL,A,Male,African-American,06/12/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +13441,71843,65144,PRETRIAL,SINGLETARY,MICHAEL,A,Male,African-American,06/12/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +13441,71843,65144,PRETRIAL,SINGLETARY,MICHAEL,A,Male,African-American,06/12/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +39325,71817,65122,PRETRIAL,Whitsett,Jamal,NULL,Male,African-American,10/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,4,High,7,Risk of Violence,-0.7,9,High,New,1,0 +39325,71817,65122,PRETRIAL,Whitsett,Jamal,NULL,Male,African-American,10/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,4,High,8,Risk of Recidivism,0.62,10,High,New,1,0 +39325,71817,65122,PRETRIAL,Whitsett,Jamal,NULL,Male,African-American,10/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +8184,71822,65127,Probation,BENNETT,PEKEDA,ORLANDO,Male,African-American,07/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +8184,71822,65127,Probation,BENNETT,PEKEDA,ORLANDO,Male,African-American,07/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +8184,71822,65127,Probation,BENNETT,PEKEDA,ORLANDO,Male,African-American,07/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61961,71833,64576,PRETRIAL,Gray,Wayne,NULL,Male,Caucasian,01/27/81,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +61961,71833,64576,PRETRIAL,Gray,Wayne,NULL,Male,Caucasian,01/27/81,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,2,Medium,8,Risk of Recidivism,0.15,7,Medium,New,1,0 +61961,71833,64576,PRETRIAL,Gray,Wayne,NULL,Male,Caucasian,01/27/81,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +62449,71840,65141,Probation,Stevenson,Bradley,NULL,Male,Caucasian,05/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +62449,71840,65141,Probation,Stevenson,Bradley,NULL,Male,Caucasian,05/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +62449,71840,65141,Probation,Stevenson,Bradley,NULL,Male,Caucasian,05/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62433,71825,65130,PRETRIAL,MCGRIFF,CIARA,NULL,Female,African-American,08/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +62433,71825,65130,PRETRIAL,MCGRIFF,CIARA,NULL,Female,African-American,08/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,9,High,New,1,0 +62433,71825,65130,PRETRIAL,MCGRIFF,CIARA,NULL,Female,African-American,08/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62442,71832,65134,Probation,Taylor,Richard,Robert,Male,Caucasian,01/25/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/2/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +62442,71832,65134,Probation,Taylor,Richard,Robert,Male,Caucasian,01/25/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/2/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +62442,71832,65134,Probation,Taylor,Richard,Robert,Male,Caucasian,01/25/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62438,71827,65131,Probation,Brandt,Robert,NULL,Male,Caucasian,08/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/14 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +62438,71827,65131,Probation,Brandt,Robert,NULL,Male,Caucasian,08/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +62438,71827,65131,Probation,Brandt,Robert,NULL,Male,Caucasian,08/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/2/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +33903,71829,52719,PRETRIAL,Jeanpierre,Roosevelt,NULL,Male,African-American,07/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/2/14 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,Copy,1,0 +33903,71829,52719,PRETRIAL,Jeanpierre,Roosevelt,NULL,Male,African-American,07/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,Copy,1,0 +33903,71829,52719,PRETRIAL,Jeanpierre,Roosevelt,NULL,Male,African-American,07/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/2/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +62446,71836,65137,PRETRIAL,Arroyave,Mariana,NULL,Female,Hispanic,06/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +62446,71836,65137,PRETRIAL,Arroyave,Mariana,NULL,Female,Hispanic,06/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +62446,71836,65137,PRETRIAL,Arroyave,Mariana,NULL,Female,Hispanic,06/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62432,71824,65129,PRETRIAL,Donald,Israel,NULL,Male,African-American,06/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +62432,71824,65129,PRETRIAL,Donald,Israel,NULL,Male,African-American,06/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +62432,71824,65129,PRETRIAL,Donald,Israel,NULL,Male,African-American,06/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62453,71845,65146,PRETRIAL,Dean,Ervin,NULL,Male,African-American,03/02/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +62453,71845,65146,PRETRIAL,Dean,Ervin,NULL,Male,African-American,03/02/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +62453,71845,65146,PRETRIAL,Dean,Ervin,NULL,Male,African-American,03/02/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62450,71841,65142,Probation,Moreno,Oscar,NULL,Male,Hispanic,05/09/79,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/2/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +62450,71841,65142,Probation,Moreno,Oscar,NULL,Male,Hispanic,05/09/79,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/2/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +62450,71841,65142,Probation,Moreno,Oscar,NULL,Male,Hispanic,05/09/79,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62430,71820,65125,PRETRIAL,ROSENBERG,VIRGINIA,GREENE,Female,Caucasian,03/18/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +62430,71820,65125,PRETRIAL,ROSENBERG,VIRGINIA,GREENE,Female,Caucasian,03/18/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +62430,71820,65125,PRETRIAL,ROSENBERG,VIRGINIA,GREENE,Female,Caucasian,03/18/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,29,9,High,New,1,0 +57501,71835,65136,PRETRIAL,Martinez,Jorge,NULL,Male,Hispanic,07/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +57501,71835,65136,PRETRIAL,Martinez,Jorge,NULL,Male,Hispanic,07/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +57501,71835,65136,PRETRIAL,Martinez,Jorge,NULL,Male,Hispanic,07/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62452,71844,65145,DRRD,Carroll,"Anthony, Jr",Jerome,Male,African-American,09/28/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/2/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +62452,71844,65145,DRRD,Carroll,"Anthony, Jr",Jerome,Male,African-American,09/28/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/2/14 0:00,1,Low,8,Risk of Recidivism,-0.43,4,Low,New,1,0 +62452,71844,65145,DRRD,Carroll,"Anthony, Jr",Jerome,Male,African-American,09/28/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +22773,71842,65143,PRETRIAL,ZELLNER,KATHY,LYNN,Female,Caucasian,05/23/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/2/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +22773,71842,65143,PRETRIAL,ZELLNER,KATHY,LYNN,Female,Caucasian,05/23/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/2/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +22773,71842,65143,PRETRIAL,ZELLNER,KATHY,LYNN,Female,Caucasian,05/23/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62431,71823,65128,PRETRIAL,Marshall,Michael,NULL,Male,African-American,01/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.96,5,Medium,New,1,0 +62431,71823,65128,PRETRIAL,Marshall,Michael,NULL,Male,African-American,01/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +62431,71823,65128,PRETRIAL,Marshall,Michael,NULL,Male,African-American,01/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62429,71819,65124,PRETRIAL,Outten,Tajnika,NULL,Male,African-American,03/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +62429,71819,65124,PRETRIAL,Outten,Tajnika,NULL,Male,African-American,03/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +62429,71819,65124,PRETRIAL,Outten,Tajnika,NULL,Male,African-American,03/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62447,71837,65138,Probation,gonzalez,jacqueline,NULL,Female,Caucasian,08/29/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/2/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +62447,71837,65138,Probation,gonzalez,jacqueline,NULL,Female,Caucasian,08/29/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/2/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +62447,71837,65138,Probation,gonzalez,jacqueline,NULL,Female,Caucasian,08/29/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62439,71828,65132,Probation,Luzon-Santana,Jael,Rafael,Male,Hispanic,03/19/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/2/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +62439,71828,65132,Probation,Luzon-Santana,Jael,Rafael,Male,Hispanic,03/19/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/2/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +62439,71828,65132,Probation,Luzon-Santana,Jael,Rafael,Male,Hispanic,03/19/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62448,71839,65140,Broward County,Purdom,Lonnie,NULL,Male,Caucasian,04/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.99,1,Low,New,1,0 +62448,71839,65140,Broward County,Purdom,Lonnie,NULL,Male,Caucasian,04/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +62448,71839,65140,Broward County,Purdom,Lonnie,NULL,Male,Caucasian,04/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +5023,71818,65123,PRETRIAL,Nicholls,Grantley,hengrick,Male,African-American,06/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,4,High,7,Risk of Violence,-0.5,10,High,New,1,0 +5023,71818,65123,PRETRIAL,Nicholls,Grantley,hengrick,Male,African-American,06/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,4,High,8,Risk of Recidivism,1.19,10,High,New,1,0 +5023,71818,65123,PRETRIAL,Nicholls,Grantley,hengrick,Male,African-American,06/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/2/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +39707,71831,39257,Probation,CORBIN,DAVID,W,Male,African-American,02/18/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/14 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +39707,71831,39257,Probation,CORBIN,DAVID,W,Male,African-American,02/18/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/14 0:00,4,High,8,Risk of Recidivism,0.71,10,High,New,1,0 +39707,71831,39257,Probation,CORBIN,DAVID,W,Male,African-American,02/18/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/14 0:00,4,High,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +61746,71826,64338,PRETRIAL,ROSAS,RICARDO,NULL,Male,Hispanic,11/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,Copy,1,0 +61746,71826,64338,PRETRIAL,ROSAS,RICARDO,NULL,Male,Hispanic,11/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,Copy,1,0 +61746,71826,64338,PRETRIAL,ROSAS,RICARDO,NULL,Male,Hispanic,11/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/2/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +62454,71847,65148,PRETRIAL,Olson,Brian,NULL,Male,Caucasian,03/22/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +62454,71847,65148,PRETRIAL,Olson,Brian,NULL,Male,Caucasian,03/22/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +62454,71847,65148,PRETRIAL,Olson,Brian,NULL,Male,Caucasian,03/22/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +4720,71860,53583,PRETRIAL,GRIFFIN,JAMAL,NULL,Male,African-American,08/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,Copy,1,0 +4720,71860,53583,PRETRIAL,GRIFFIN,JAMAL,NULL,Male,African-American,08/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,1,Low,8,Risk of Recidivism,-0.44,4,Low,Copy,1,0 +4720,71860,53583,PRETRIAL,GRIFFIN,JAMAL,NULL,Male,African-American,08/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +62459,71852,65153,PRETRIAL,FAUSTIN,LUREINE,NULL,Female,African-American,10/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +62459,71852,65153,PRETRIAL,FAUSTIN,LUREINE,NULL,Female,African-American,10/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +62459,71852,65153,PRETRIAL,FAUSTIN,LUREINE,NULL,Female,African-American,10/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +46794,71855,47238,PRETRIAL,Murdock,Lorenzo,J.,Male,Other,11/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,Copy,1,0 +46794,71855,47238,PRETRIAL,Murdock,Lorenzo,J.,Male,Other,11/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,Copy,1,0 +46794,71855,47238,PRETRIAL,Murdock,Lorenzo,J.,Male,Other,11/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +62473,71873,65171,Probation,crawford,karl,NULL,Male,African-American,11/22/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +62473,71873,65171,Probation,crawford,karl,NULL,Male,African-American,11/22/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +62473,71873,65171,Probation,crawford,karl,NULL,Male,African-American,11/22/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62474,71876,65174,PRETRIAL,Bates,Christine,NULL,Female,African-American,11/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +62474,71876,65174,PRETRIAL,Bates,Christine,NULL,Female,African-American,11/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,1,Low,8,Risk of Recidivism,-2.71,1,Low,New,1,0 +62474,71876,65174,PRETRIAL,Bates,Christine,NULL,Female,African-American,11/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62468,71868,65166,Probation,Forbes,Julian,NULL,Male,African-American,03/16/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +62468,71868,65166,Probation,Forbes,Julian,NULL,Male,African-American,03/16/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +62468,71868,65166,Probation,Forbes,Julian,NULL,Male,African-American,03/16/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +51900,71879,65177,PRETRIAL,Rattray,Latosha,NULL,Female,African-American,12/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,New,1,0 +51900,71879,65177,PRETRIAL,Rattray,Latosha,NULL,Female,African-American,12/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.33,7,Medium,New,1,0 +51900,71879,65177,PRETRIAL,Rattray,Latosha,NULL,Female,African-American,12/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62456,71849,65150,PRETRIAL,ADAMS,DAVID,MARSHALL,Male,Caucasian,05/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +62456,71849,65150,PRETRIAL,ADAMS,DAVID,MARSHALL,Male,Caucasian,05/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +62456,71849,65150,PRETRIAL,ADAMS,DAVID,MARSHALL,Male,Caucasian,05/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62462,71858,65157,Probation,Terry,Jeanne,NULL,Male,Caucasian,11/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/3/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +62462,71858,65157,Probation,Terry,Jeanne,NULL,Male,Caucasian,11/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/3/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +62462,71858,65157,Probation,Terry,Jeanne,NULL,Male,Caucasian,11/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62477,71884,65182,Probation,LOYA,COLBY,NULL,Male,Caucasian,07/15/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +62477,71884,65182,Probation,LOYA,COLBY,NULL,Male,Caucasian,07/15/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +62477,71884,65182,Probation,LOYA,COLBY,NULL,Male,Caucasian,07/15/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62465,71865,65163,Probation,Munera Ramirez,Cesar,NULL,Male,Hispanic,07/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +62465,71865,65163,Probation,Munera Ramirez,Cesar,NULL,Male,Hispanic,07/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +62465,71865,65163,Probation,Munera Ramirez,Cesar,NULL,Male,Hispanic,07/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62472,71872,65170,Probation,Sotomayor,Jose,NULL,Male,Hispanic,07/08/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +62472,71872,65170,Probation,Sotomayor,Jose,NULL,Male,Hispanic,07/08/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +62472,71872,65170,Probation,Sotomayor,Jose,NULL,Male,Hispanic,07/08/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62466,71866,65164,Probation,Rodriguez,Darwin,NULL,Male,Hispanic,01/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,7,Risk of Violence,-2.7,2,Low,New,1,0 +62466,71866,65164,Probation,Rodriguez,Darwin,NULL,Male,Hispanic,01/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +62466,71866,65164,Probation,Rodriguez,Darwin,NULL,Male,Hispanic,01/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62464,71862,65160,PRETRIAL,BRANCH,KENNETH,NULL,Female,African-American,12/23/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +62464,71862,65160,PRETRIAL,BRANCH,KENNETH,NULL,Female,African-American,12/23/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.92,10,High,New,1,0 +62464,71862,65160,PRETRIAL,BRANCH,KENNETH,NULL,Female,African-American,12/23/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +37586,71883,65181,Probation,mccloud,marc,NULL,Male,African-American,09/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +37586,71883,65181,Probation,mccloud,marc,NULL,Male,African-American,09/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +37586,71883,65181,Probation,mccloud,marc,NULL,Male,African-American,09/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +62457,71850,65151,PRETRIAL,Gonzalez,Juan,NULL,Male,Caucasian,02/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +62457,71850,65151,PRETRIAL,Gonzalez,Juan,NULL,Male,Caucasian,02/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +62457,71850,65151,PRETRIAL,Gonzalez,Juan,NULL,Male,Caucasian,02/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62250,71857,64920,PRETRIAL,DELGADO,ALBERTO,NULL,Male,Hispanic,12/31/91,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,4,High,7,Risk of Violence,-1.21,8,High,Copy,1,0 +62250,71857,64920,PRETRIAL,DELGADO,ALBERTO,NULL,Male,Hispanic,12/31/91,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,4,High,8,Risk of Recidivism,0.53,9,High,Copy,1,0 +62250,71857,64920,PRETRIAL,DELGADO,ALBERTO,NULL,Male,Hispanic,12/31/91,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/3/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +52584,71864,65162,PRETRIAL,Mujica,Juan,NULL,Male,Hispanic,09/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +52584,71864,65162,PRETRIAL,Mujica,Juan,NULL,Male,Hispanic,09/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +52584,71864,65162,PRETRIAL,Mujica,Juan,NULL,Male,Hispanic,09/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62475,71878,65176,Probation,Salas,Pedro,NULL,Male,Hispanic,12/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +62475,71878,65176,Probation,Salas,Pedro,NULL,Male,Hispanic,12/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +62475,71878,65176,Probation,Salas,Pedro,NULL,Male,Hispanic,12/31/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56531,71880,65178,PRETRIAL,REMBERT,WESLEY,CARDELL,Male,African-American,03/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +56531,71880,65178,PRETRIAL,REMBERT,WESLEY,CARDELL,Male,African-American,03/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +56531,71880,65178,PRETRIAL,REMBERT,WESLEY,CARDELL,Male,African-American,03/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58343,71875,65173,PRETRIAL,Butler,Ira,NULL,Male,African-American,09/20/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/3/14 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +58343,71875,65173,PRETRIAL,Butler,Ira,NULL,Male,African-American,09/20/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/3/14 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +58343,71875,65173,PRETRIAL,Butler,Ira,NULL,Male,African-American,09/20/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55100,71882,65180,PRETRIAL,Brown,Calvin,Kelly,Male,African-American,07/15/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +55100,71882,65180,PRETRIAL,Brown,Calvin,Kelly,Male,African-American,07/15/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +55100,71882,65180,PRETRIAL,Brown,Calvin,Kelly,Male,African-American,07/15/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +52938,71853,65154,Probation,Jennings,Sandy,Ross,Male,Caucasian,01/18/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +52938,71853,65154,Probation,Jennings,Sandy,Ross,Male,Caucasian,01/18/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +52938,71853,65154,Probation,Jennings,Sandy,Ross,Male,Caucasian,01/18/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62467,71867,65165,Probation,polonio,servio,f,Male,Hispanic,01/02/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +62467,71867,65165,Probation,polonio,servio,f,Male,Hispanic,01/02/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +62467,71867,65165,Probation,polonio,servio,f,Male,Hispanic,01/02/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +50625,71874,65172,PRETRIAL,DEJESUS,GERARDO,LUIS,Male,Caucasian,01/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +50625,71874,65172,PRETRIAL,DEJESUS,GERARDO,LUIS,Male,Caucasian,01/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +50625,71874,65172,PRETRIAL,DEJESUS,GERARDO,LUIS,Male,Caucasian,01/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +42674,71846,65147,PRETRIAL,Cozzi,Michael,Brando,Male,Caucasian,08/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +42674,71846,65147,PRETRIAL,Cozzi,Michael,Brando,Male,Caucasian,08/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,4,High,8,Risk of Recidivism,0.33,9,High,New,1,0 +42674,71846,65147,PRETRIAL,Cozzi,Michael,Brando,Male,Caucasian,08/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/3/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62463,71861,65159,Probation,bouchard,dustin,NULL,Male,Caucasian,07/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +62463,71861,65159,Probation,bouchard,dustin,NULL,Male,Caucasian,07/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +62463,71861,65159,Probation,bouchard,dustin,NULL,Male,Caucasian,07/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62458,71851,65152,PRETRIAL,Cherisol,Guize,NULL,Female,African-American,11/05/40,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/3/14 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +62458,71851,65152,PRETRIAL,Cherisol,Guize,NULL,Female,African-American,11/05/40,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/3/14 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +62458,71851,65152,PRETRIAL,Cherisol,Guize,NULL,Female,African-American,11/05/40,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62461,71856,65156,Probation,Juman,Damion,NULL,Male,African-American,05/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +62461,71856,65156,Probation,Juman,Damion,NULL,Male,African-American,05/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +62461,71856,65156,Probation,Juman,Damion,NULL,Male,African-American,05/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57484,71877,65175,PRETRIAL,Saunders,Bari,Alexander,Male,African-American,09/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +57484,71877,65175,PRETRIAL,Saunders,Bari,Alexander,Male,African-American,09/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +57484,71877,65175,PRETRIAL,Saunders,Bari,Alexander,Male,African-American,09/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62469,71869,65167,Probation,Padua,Huey,NULL,Male,Asian,01/12/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +62469,71869,65167,Probation,Padua,Huey,NULL,Male,Asian,01/12/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +62469,71869,65167,Probation,Padua,Huey,NULL,Male,Asian,01/12/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62455,71848,65149,PRETRIAL,Barra-Rivera,Ernesto,NULL,Male,Hispanic,11/07/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/3/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +62455,71848,65149,PRETRIAL,Barra-Rivera,Ernesto,NULL,Male,Hispanic,11/07/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/3/14 0:00,1,Low,8,Risk of Recidivism,-2.63,1,Low,New,1,0 +62455,71848,65149,PRETRIAL,Barra-Rivera,Ernesto,NULL,Male,Hispanic,11/07/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +38821,71859,65158,Probation,CALDERON,FABIO,ABELCANO,Male,Caucasian,12/23/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +38821,71859,65158,Probation,CALDERON,FABIO,ABELCANO,Male,Caucasian,12/23/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +38821,71859,65158,Probation,CALDERON,FABIO,ABELCANO,Male,Caucasian,12/23/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62489,71898,65196,PRETRIAL,Charlot,Al,NULL,Male,African-American,08/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +62489,71898,65196,PRETRIAL,Charlot,Al,NULL,Male,African-American,08/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +62489,71898,65196,PRETRIAL,Charlot,Al,NULL,Male,African-American,08/29/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62483,71890,65188,Probation,williams,norman,NULL,Male,African-American,12/20/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +62483,71890,65188,Probation,williams,norman,NULL,Male,African-American,12/20/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +62483,71890,65188,Probation,williams,norman,NULL,Male,African-American,12/20/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +32280,71895,65193,PRETRIAL,Caplan,Suzanne,Dee,Female,Caucasian,10/27/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +32280,71895,65193,PRETRIAL,Caplan,Suzanne,Dee,Female,Caucasian,10/27/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +32280,71895,65193,PRETRIAL,Caplan,Suzanne,Dee,Female,Caucasian,10/27/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62493,71903,65200,PRETRIAL,Rivers,Vonda,NULL,Female,African-American,03/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,4,High,7,Risk of Violence,-0.66,9,High,New,1,0 +62493,71903,65200,PRETRIAL,Rivers,Vonda,NULL,Female,African-American,03/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,4,High,8,Risk of Recidivism,0.61,10,High,New,1,0 +62493,71903,65200,PRETRIAL,Rivers,Vonda,NULL,Female,African-American,03/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61668,71899,64249,PRETRIAL,Ruiz,Jessica,NULL,Female,Hispanic,06/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,Copy,1,0 +61668,71899,64249,PRETRIAL,Ruiz,Jessica,NULL,Female,Hispanic,06/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,Copy,1,0 +61668,71899,64249,PRETRIAL,Ruiz,Jessica,NULL,Female,Hispanic,06/15/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +62491,71901,65198,Probation,merolus,david,NULL,Male,African-American,01/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +62491,71901,65198,Probation,merolus,david,NULL,Male,African-American,01/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.75,10,High,New,1,0 +62491,71901,65198,Probation,merolus,david,NULL,Male,African-American,01/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +53493,71906,65203,PRETRIAL,Nieves,Glenn,Joseph,Male,Hispanic,05/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +53493,71906,65203,PRETRIAL,Nieves,Glenn,Joseph,Male,Hispanic,05/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +53493,71906,65203,PRETRIAL,Nieves,Glenn,Joseph,Male,Hispanic,05/19/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +30556,71908,65205,Probation,martinez,stephanie,NULL,Female,Hispanic,07/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +30556,71908,65205,Probation,martinez,stephanie,NULL,Female,Hispanic,07/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.8,10,High,New,1,0 +30556,71908,65205,Probation,martinez,stephanie,NULL,Female,Hispanic,07/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62478,71885,65183,PRETRIAL,Georges,Clieve,NULL,Male,Caucasian,07/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +62478,71885,65183,PRETRIAL,Georges,Clieve,NULL,Male,Caucasian,07/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +62478,71885,65183,PRETRIAL,Georges,Clieve,NULL,Male,Caucasian,07/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62487,71896,65194,PRETRIAL,FRANCIS,SOPHIA,NULL,Female,African-American,09/20/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +62487,71896,65194,PRETRIAL,FRANCIS,SOPHIA,NULL,Female,African-American,09/20/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +62487,71896,65194,PRETRIAL,FRANCIS,SOPHIA,NULL,Female,African-American,09/20/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62480,71887,65185,PRETRIAL,Magloire,Rasheed,Bernard,Male,African-American,12/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +62480,71887,65185,PRETRIAL,Magloire,Rasheed,Bernard,Male,African-American,12/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +62480,71887,65185,PRETRIAL,Magloire,Rasheed,Bernard,Male,African-American,12/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62484,71893,65191,Probation,Layun,Ulysses,NULL,Male,Caucasian,12/31/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/4/14 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +62484,71893,65191,Probation,Layun,Ulysses,NULL,Male,Caucasian,12/31/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/4/14 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +62484,71893,65191,Probation,Layun,Ulysses,NULL,Male,Caucasian,12/31/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62479,71886,65184,PRETRIAL,BELFON-HACKETT,MICHELLE,NULL,Male,African-American,02/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/4/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +62479,71886,65184,PRETRIAL,BELFON-HACKETT,MICHELLE,NULL,Male,African-American,02/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/4/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +62479,71886,65184,PRETRIAL,BELFON-HACKETT,MICHELLE,NULL,Male,African-American,02/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62490,71900,65197,Probation,DIAZ,DANNY,NULL,Male,Hispanic,05/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/4/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +62490,71900,65197,Probation,DIAZ,DANNY,NULL,Male,Hispanic,05/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/4/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +62490,71900,65197,Probation,DIAZ,DANNY,NULL,Male,Hispanic,05/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +7737,71907,65204,PRETRIAL,KIRKLAND,STEVEN,NULL,Male,African-American,03/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +7737,71907,65204,PRETRIAL,KIRKLAND,STEVEN,NULL,Male,African-American,03/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,4,High,8,Risk of Recidivism,0.94,10,High,New,1,0 +7737,71907,65204,PRETRIAL,KIRKLAND,STEVEN,NULL,Male,African-American,03/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +54750,71891,65189,PRETRIAL,De Souza,Robson,NULL,Male,Caucasian,03/22/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +54750,71891,65189,PRETRIAL,De Souza,Robson,NULL,Male,Caucasian,03/22/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +54750,71891,65189,PRETRIAL,De Souza,Robson,NULL,Male,Caucasian,03/22/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62495,71909,65206,Probation,slocomb,joan,NULL,Male,Caucasian,01/28/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +62495,71909,65206,Probation,slocomb,joan,NULL,Male,Caucasian,01/28/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +62495,71909,65206,Probation,slocomb,joan,NULL,Male,Caucasian,01/28/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62481,71888,65186,PRETRIAL,Garn,Sharon,NULL,Female,Caucasian,07/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +62481,71888,65186,PRETRIAL,Garn,Sharon,NULL,Female,Caucasian,07/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +62481,71888,65186,PRETRIAL,Garn,Sharon,NULL,Female,Caucasian,07/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +40780,71905,65202,PRETRIAL,SPATE,GERALD,NULL,Male,African-American,09/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +40780,71905,65202,PRETRIAL,SPATE,GERALD,NULL,Male,African-American,09/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +40780,71905,65202,PRETRIAL,SPATE,GERALD,NULL,Male,African-American,09/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62494,71904,65201,Probation,octavien,evans,NULL,Male,African-American,09/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +62494,71904,65201,Probation,octavien,evans,NULL,Male,African-American,09/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +62494,71904,65201,Probation,octavien,evans,NULL,Male,African-American,09/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62482,71889,65187,Probation,Depicciotto,James,NULL,Male,Caucasian,08/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.43,3,Low,New,1,0 +62482,71889,65187,Probation,Depicciotto,James,NULL,Male,Caucasian,08/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +62482,71889,65187,Probation,Depicciotto,James,NULL,Male,Caucasian,08/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +62488,71897,65195,Probation,dulaney,zachery,NULL,Male,Caucasian,04/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +62488,71897,65195,Probation,dulaney,zachery,NULL,Male,Caucasian,04/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +62488,71897,65195,Probation,dulaney,zachery,NULL,Male,Caucasian,04/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62492,71902,65199,PRETRIAL,Cesar,Brittany,NULL,Female,African-American,08/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +62492,71902,65199,PRETRIAL,Cesar,Brittany,NULL,Female,African-American,08/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +62492,71902,65199,PRETRIAL,Cesar,Brittany,NULL,Female,African-American,08/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/4/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62486,71894,65192,Probation,MCANALLY,JASON,NULL,Male,Caucasian,09/12/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +62486,71894,65192,Probation,MCANALLY,JASON,NULL,Male,Caucasian,09/12/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +62486,71894,65192,Probation,MCANALLY,JASON,NULL,Male,Caucasian,09/12/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/4/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +48227,71915,48904,PRETRIAL,Francisco,Rudolfo,NULL,Male,Hispanic,07/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/5/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,Copy,1,0 +48227,71915,48904,PRETRIAL,Francisco,Rudolfo,NULL,Male,Hispanic,07/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/5/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,Copy,1,0 +48227,71915,48904,PRETRIAL,Francisco,Rudolfo,NULL,Male,Hispanic,07/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +62501,71920,65214,PRETRIAL,Pippins,Charlie,NULL,Male,African-American,10/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +62501,71920,65214,PRETRIAL,Pippins,Charlie,NULL,Male,African-American,10/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.81,10,High,New,1,0 +62501,71920,65214,PRETRIAL,Pippins,Charlie,NULL,Male,African-American,10/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +49294,71910,65207,PRETRIAL,WATSON,EDDIE,NULL,Male,African-American,06/22/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,4,High,7,Risk of Violence,-0.9,9,High,New,1,0 +49294,71910,65207,PRETRIAL,WATSON,EDDIE,NULL,Male,African-American,06/22/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,4,High,8,Risk of Recidivism,0.85,10,High,New,1,0 +49294,71910,65207,PRETRIAL,WATSON,EDDIE,NULL,Male,African-American,06/22/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +13833,71918,65212,PRETRIAL,FRANCK,LOUIS,NULL,Male,Caucasian,12/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +13833,71918,65212,PRETRIAL,FRANCK,LOUIS,NULL,Male,Caucasian,12/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +13833,71918,65212,PRETRIAL,FRANCK,LOUIS,NULL,Male,Caucasian,12/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62498,71914,65210,PRETRIAL,Shelton,Denariuius,NULL,Male,African-American,05/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,4,High,7,Risk of Violence,-0.35,10,High,New,1,0 +62498,71914,65210,PRETRIAL,Shelton,Denariuius,NULL,Male,African-American,05/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,4,High,8,Risk of Recidivism,0.39,9,High,New,1,0 +62498,71914,65210,PRETRIAL,Shelton,Denariuius,NULL,Male,African-American,05/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +6242,71921,48273,PRETRIAL,Darryl,Kelly,NULL,Male,African-American,10/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,4,High,7,Risk of Violence,-0.15,10,High,Copy,1,0 +6242,71921,48273,PRETRIAL,Darryl,Kelly,NULL,Male,African-American,10/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,4,High,8,Risk of Recidivism,0.7,10,High,Copy,1,0 +6242,71921,48273,PRETRIAL,Darryl,Kelly,NULL,Male,African-American,10/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,4,High,18,Risk of Failure to Appear,37,10,High,Copy,1,0 +62497,71913,65209,PRETRIAL,Jeanbaptiste,Nicole,NULL,Female,African-American,10/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +62497,71913,65209,PRETRIAL,Jeanbaptiste,Nicole,NULL,Female,African-American,10/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +62497,71913,65209,PRETRIAL,Jeanbaptiste,Nicole,NULL,Female,African-American,10/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +52643,71917,53986,Probation,fiddeman,jeronald,NULL,Male,African-American,07/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,Copy,1,0 +52643,71917,53986,Probation,fiddeman,jeronald,NULL,Male,African-American,07/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,Copy,1,0 +52643,71917,53986,Probation,fiddeman,jeronald,NULL,Male,African-American,07/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +58905,71911,61144,Probation,PARK,SUNG,NULL,Male,Asian,06/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/5/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,Copy,1,0 +58905,71911,61144,Probation,PARK,SUNG,NULL,Male,Asian,06/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/5/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +58905,71911,61144,Probation,PARK,SUNG,NULL,Male,Asian,06/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +62499,71916,65211,PRETRIAL,Tanon,Monica,NULL,Female,Hispanic,03/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +62499,71916,65211,PRETRIAL,Tanon,Monica,NULL,Female,Hispanic,03/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +62499,71916,65211,PRETRIAL,Tanon,Monica,NULL,Female,Hispanic,03/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62500,71919,65213,PRETRIAL,Berg,Ronnie,Ira,Male,Caucasian,12/12/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +62500,71919,65213,PRETRIAL,Berg,Ronnie,Ira,Male,Caucasian,12/12/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +62500,71919,65213,PRETRIAL,Berg,Ronnie,Ira,Male,Caucasian,12/12/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62504,71924,65217,PRETRIAL,Dahan,Haim,NULL,Male,Caucasian,12/10/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/14 0:00,1,Low,7,Risk of Violence,-4.46,1,Low,New,1,0 +62504,71924,65217,PRETRIAL,Dahan,Haim,NULL,Male,Caucasian,12/10/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/14 0:00,1,Low,8,Risk of Recidivism,-2.88,1,Low,New,1,0 +62504,71924,65217,PRETRIAL,Dahan,Haim,NULL,Male,Caucasian,12/10/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62508,71932,65222,PRETRIAL,Greene,Sherod,NULL,Male,African-American,10/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +62508,71932,65222,PRETRIAL,Greene,Sherod,NULL,Male,African-American,10/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +62508,71932,65222,PRETRIAL,Greene,Sherod,NULL,Male,African-American,10/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62502,71922,65215,PRETRIAL,Vaysbeg,Boris,NULL,Male,Caucasian,08/18/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +62502,71922,65215,PRETRIAL,Vaysbeg,Boris,NULL,Male,Caucasian,08/18/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +62502,71922,65215,PRETRIAL,Vaysbeg,Boris,NULL,Male,Caucasian,08/18/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59701,71927,65220,PRETRIAL,Stewart,Raquel,NULL,Female,African-American,10/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +59701,71927,65220,PRETRIAL,Stewart,Raquel,NULL,Female,African-American,10/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +59701,71927,65220,PRETRIAL,Stewart,Raquel,NULL,Female,African-American,10/31/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +62507,71929,65221,PRETRIAL,Guistolisi,Robert,NULL,Male,Caucasian,10/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +62507,71929,65221,PRETRIAL,Guistolisi,Robert,NULL,Male,Caucasian,10/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +62507,71929,65221,PRETRIAL,Guistolisi,Robert,NULL,Male,Caucasian,10/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +62506,71926,65219,PRETRIAL,OVERTON,ANGELA,NULL,Female,African-American,01/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +62506,71926,65219,PRETRIAL,OVERTON,ANGELA,NULL,Female,African-American,01/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +62506,71926,65219,PRETRIAL,OVERTON,ANGELA,NULL,Female,African-American,01/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +21395,71930,20549,PRETRIAL,MIRANDA,MOISES,NULL,Male,Caucasian,06/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,Copy,1,0 +21395,71930,20549,PRETRIAL,MIRANDA,MOISES,NULL,Male,Caucasian,06/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,Copy,1,0 +21395,71930,20549,PRETRIAL,MIRANDA,MOISES,NULL,Male,Caucasian,06/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +62505,71925,65218,PRETRIAL,Lawrence,Jorge,Alberto,Male,African-American,01/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +62505,71925,65218,PRETRIAL,Lawrence,Jorge,Alberto,Male,African-American,01/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/14 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +62505,71925,65218,PRETRIAL,Lawrence,Jorge,Alberto,Male,African-American,01/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +737,71931,430,PRETRIAL,Sorto,Alan,J,Male,Caucasian,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,Copy,1,0 +737,71931,430,PRETRIAL,Sorto,Alan,J,Male,Caucasian,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,Copy,1,0 +737,71931,430,PRETRIAL,Sorto,Alan,J,Male,Caucasian,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +62503,71923,65216,PRETRIAL,Nichols,Shaquana,NULL,Female,African-American,01/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +62503,71923,65216,PRETRIAL,Nichols,Shaquana,NULL,Female,African-American,01/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +62503,71923,65216,PRETRIAL,Nichols,Shaquana,NULL,Female,African-American,01/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +16861,71928,59136,PRETRIAL,Jones,Elton,A,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/6/14 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,Copy,1,0 +16861,71928,59136,PRETRIAL,Jones,Elton,A,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,Copy,1,0 +16861,71928,59136,PRETRIAL,Jones,Elton,A,Male,African-American,02/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/6/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +62303,71962,64984,PRETRIAL,Mosley,Javaris,NULL,Male,African-American,08/23/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,4,High,7,Risk of Violence,-1.18,8,High,Copy,1,0 +62303,71962,64984,PRETRIAL,Mosley,Javaris,NULL,Male,African-American,08/23/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,4,High,8,Risk of Recidivism,0.43,9,High,Copy,1,0 +62303,71962,64984,PRETRIAL,Mosley,Javaris,NULL,Male,African-American,08/23/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +56837,71996,65276,PRETRIAL,MASOOD,HARIS,NULL,Male,Native American,01/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +56837,71996,65276,PRETRIAL,MASOOD,HARIS,NULL,Male,Native American,01/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +56837,71996,65276,PRETRIAL,MASOOD,HARIS,NULL,Male,Native American,01/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61204,71949,63726,PRETRIAL,PAGERIE,TARA,NULL,Female,Caucasian,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,Copy,1,0 +61204,71949,63726,PRETRIAL,PAGERIE,TARA,NULL,Female,Caucasian,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,Copy,1,0 +61204,71949,63726,PRETRIAL,PAGERIE,TARA,NULL,Female,Caucasian,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +62545,71983,65264,Probation,Myles-Young,Hurtado,NULL,Male,Hispanic,05/01/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +62545,71983,65264,Probation,Myles-Young,Hurtado,NULL,Male,Hispanic,05/01/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +62545,71983,65264,Probation,Myles-Young,Hurtado,NULL,Male,Hispanic,05/01/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62516,71941,65231,PRETRIAL,MUNDEE,PATRICK,D,Male,Caucasian,08/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +62516,71941,65231,PRETRIAL,MUNDEE,PATRICK,D,Male,Caucasian,08/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +62516,71941,65231,PRETRIAL,MUNDEE,PATRICK,D,Male,Caucasian,08/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62550,71991,65271,Probation,Blount,Hubert,NULL,Male,African-American,02/05/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +62550,71991,65271,Probation,Blount,Hubert,NULL,Male,African-American,02/05/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +62550,71991,65271,Probation,Blount,Hubert,NULL,Male,African-American,02/05/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +35905,71970,35135,PRETRIAL,JOHNSON,STEVEN,NULL,Male,Caucasian,06/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,Copy,1,0 +35905,71970,35135,PRETRIAL,JOHNSON,STEVEN,NULL,Male,Caucasian,06/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,Copy,1,0 +35905,71970,35135,PRETRIAL,JOHNSON,STEVEN,NULL,Male,Caucasian,06/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +60219,71988,62623,Probation,Vaitoska,Justinas,NULL,Male,Caucasian,07/21/77,17,All Scales,Intake,English,Conditional Release,Probation,Widowed,4/7/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +60219,71988,62623,Probation,Vaitoska,Justinas,NULL,Male,Caucasian,07/21/77,17,All Scales,Intake,English,Conditional Release,Probation,Widowed,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +60219,71988,62623,Probation,Vaitoska,Justinas,NULL,Male,Caucasian,07/21/77,17,All Scales,Intake,English,Conditional Release,Probation,Widowed,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,31,8,High,New,1,0 +62509,71933,65223,PRETRIAL,Wright,Edward,NULL,Male,Caucasian,05/06/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/14 0:00,1,Low,7,Risk of Violence,-4.62,1,Low,New,1,0 +62509,71933,65223,PRETRIAL,Wright,Edward,NULL,Male,Caucasian,05/06/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/14 0:00,1,Low,8,Risk of Recidivism,-3.03,1,Low,New,1,0 +62509,71933,65223,PRETRIAL,Wright,Edward,NULL,Male,Caucasian,05/06/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62529,71967,65250,Probation,Metelus,Eniel,NULL,Male,African-American,02/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +62529,71967,65250,Probation,Metelus,Eniel,NULL,Male,African-American,02/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +62529,71967,65250,Probation,Metelus,Eniel,NULL,Male,African-American,02/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62521,71946,65236,PRETRIAL,Jenkins,Bobby,Everett,Male,African-American,11/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +62521,71946,65236,PRETRIAL,Jenkins,Bobby,Everett,Male,African-American,11/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +62521,71946,65236,PRETRIAL,Jenkins,Bobby,Everett,Male,African-American,11/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60538,71939,65229,PRETRIAL,Pruett,Jonpaul,NULL,Male,Caucasian,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +60538,71939,65229,PRETRIAL,Pruett,Jonpaul,NULL,Male,Caucasian,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +60538,71939,65229,PRETRIAL,Pruett,Jonpaul,NULL,Male,Caucasian,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +62527,71954,65241,PRETRIAL,Assa,Andrew,NULL,Male,Caucasian,09/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +62527,71954,65241,PRETRIAL,Assa,Andrew,NULL,Male,Caucasian,09/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +62527,71954,65241,PRETRIAL,Assa,Andrew,NULL,Male,Caucasian,09/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62522,71947,65237,PRETRIAL,Mosquera,Alberto,Jose,Male,Hispanic,07/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +62522,71947,65237,PRETRIAL,Mosquera,Alberto,Jose,Male,Hispanic,07/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +62522,71947,65237,PRETRIAL,Mosquera,Alberto,Jose,Male,Hispanic,07/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62541,71977,65259,PRETRIAL,stewart,dvonte,NULL,Male,African-American,11/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,4,High,7,Risk of Violence,-0.3,10,High,New,1,0 +62541,71977,65259,PRETRIAL,stewart,dvonte,NULL,Male,African-American,11/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,4,High,8,Risk of Recidivism,1.08,10,High,New,1,0 +62541,71977,65259,PRETRIAL,stewart,dvonte,NULL,Male,African-American,11/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62523,71951,65238,Probation,DELATE,JON,NULL,Male,Caucasian,03/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +62523,71951,65238,Probation,DELATE,JON,NULL,Male,Caucasian,03/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +62523,71951,65238,Probation,DELATE,JON,NULL,Male,Caucasian,03/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62526,71956,65242,Probation,Satchell,Samuel,NULL,Male,African-American,05/27/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/7/14 0:00,1,Low,7,Risk of Violence,-4.37,1,Low,New,1,0 +62526,71956,65242,Probation,Satchell,Samuel,NULL,Male,African-American,05/27/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/7/14 0:00,1,Low,8,Risk of Recidivism,-2.75,1,Low,New,1,0 +62526,71956,65242,Probation,Satchell,Samuel,NULL,Male,African-American,05/27/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62511,71935,65225,PRETRIAL,BANKS,KEVIN,NULL,Male,African-American,05/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,7,Risk of Violence,-1.39,7,Medium,New,1,0 +62511,71935,65225,PRETRIAL,BANKS,KEVIN,NULL,Male,African-American,05/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +62511,71935,65225,PRETRIAL,BANKS,KEVIN,NULL,Male,African-American,05/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62536,71972,65254,Probation,Tyson,Brandon,NULL,Male,African-American,02/28/81,17,All Scales,Intake,English,Post Sentence,Probation,Separated,4/7/14 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +62536,71972,65254,Probation,Tyson,Brandon,NULL,Male,African-American,02/28/81,17,All Scales,Intake,English,Post Sentence,Probation,Separated,4/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,6,Medium,New,1,0 +62536,71972,65254,Probation,Tyson,Brandon,NULL,Male,African-American,02/28/81,17,All Scales,Intake,English,Post Sentence,Probation,Separated,4/7/14 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,New,1,0 +62548,71986,65267,PRETRIAL,Johnson,Scott,NULL,Male,Caucasian,05/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +62548,71986,65267,PRETRIAL,Johnson,Scott,NULL,Male,Caucasian,05/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +62548,71986,65267,PRETRIAL,Johnson,Scott,NULL,Male,Caucasian,05/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62519,71944,65234,PRETRIAL,Montoya,Santiago,NULL,Male,Caucasian,03/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +62519,71944,65234,PRETRIAL,Montoya,Santiago,NULL,Male,Caucasian,03/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +62519,71944,65234,PRETRIAL,Montoya,Santiago,NULL,Male,Caucasian,03/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62530,71963,65246,Probation,knight,tamesiha,NULL,Female,African-American,06/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +62530,71963,65246,Probation,knight,tamesiha,NULL,Female,African-American,06/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +62530,71963,65246,Probation,knight,tamesiha,NULL,Female,African-American,06/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62517,71942,65232,PRETRIAL,Bradshaw,Nigel,NULL,Male,African-American,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,7,Risk of Violence,-1.27,7,Medium,New,1,0 +62517,71942,65232,PRETRIAL,Bradshaw,Nigel,NULL,Male,African-American,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +62517,71942,65232,PRETRIAL,Bradshaw,Nigel,NULL,Male,African-American,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62532,71965,65248,Probation,Shawn,Ball,NULL,Male,Caucasian,10/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +62532,71965,65248,Probation,Shawn,Ball,NULL,Male,Caucasian,10/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,New,1,0 +62532,71965,65248,Probation,Shawn,Ball,NULL,Male,Caucasian,10/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +28949,71978,65260,PRETRIAL,MAYBERRY,TIFFANY,NULL,Female,Caucasian,05/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/7/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +28949,71978,65260,PRETRIAL,MAYBERRY,TIFFANY,NULL,Female,Caucasian,05/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +28949,71978,65260,PRETRIAL,MAYBERRY,TIFFANY,NULL,Female,Caucasian,05/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62542,71980,65262,Probation,Madrid,Sebastian,NULL,Male,Hispanic,12/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +62542,71980,65262,Probation,Madrid,Sebastian,NULL,Male,Hispanic,12/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +62542,71980,65262,Probation,Madrid,Sebastian,NULL,Male,Hispanic,12/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62512,71936,65226,PRETRIAL,Mosiman,Thomas,NULL,Male,Caucasian,11/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +62512,71936,65226,PRETRIAL,Mosiman,Thomas,NULL,Male,Caucasian,11/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +62512,71936,65226,PRETRIAL,Mosiman,Thomas,NULL,Male,Caucasian,11/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62535,71971,65253,Probation,Ford,Phillip,NULL,Male,Caucasian,07/19/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +62535,71971,65253,Probation,Ford,Phillip,NULL,Male,Caucasian,07/19/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +62535,71971,65253,Probation,Ford,Phillip,NULL,Male,Caucasian,07/19/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62547,71985,65266,Probation,cartolana,michael,a,Male,Caucasian,01/18/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/7/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +62547,71985,65266,Probation,cartolana,michael,a,Male,Caucasian,01/18/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +62547,71985,65266,Probation,cartolana,michael,a,Male,Caucasian,01/18/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +35584,71950,51922,PRETRIAL,Robinson,Nandy,NULL,Female,African-American,06/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,Copy,1,0 +35584,71950,51922,PRETRIAL,Robinson,Nandy,NULL,Female,African-American,06/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,Copy,1,0 +35584,71950,51922,PRETRIAL,Robinson,Nandy,NULL,Female,African-American,06/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +62531,71964,65247,PRETRIAL,Ibanez,Michael,NULL,Male,Hispanic,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +62531,71964,65247,PRETRIAL,Ibanez,Michael,NULL,Male,Hispanic,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +62531,71964,65247,PRETRIAL,Ibanez,Michael,NULL,Male,Hispanic,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +56390,71990,65270,PRETRIAL,DIXON,DONOVAM,NULL,Male,African-American,11/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +56390,71990,65270,PRETRIAL,DIXON,DONOVAM,NULL,Male,African-American,11/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +56390,71990,65270,PRETRIAL,DIXON,DONOVAM,NULL,Male,African-American,11/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62518,71943,65233,PRETRIAL,Frederick,Daniel,NULL,Male,Caucasian,04/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62518,71943,65233,PRETRIAL,Frederick,Daniel,NULL,Male,Caucasian,04/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +62518,71943,65233,PRETRIAL,Frederick,Daniel,NULL,Male,Caucasian,04/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62551,71994,65274,Probation,Callegari,Lucianco,NULL,Male,Hispanic,10/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/7/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +62551,71994,65274,Probation,Callegari,Lucianco,NULL,Male,Hispanic,10/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +62551,71994,65274,Probation,Callegari,Lucianco,NULL,Male,Hispanic,10/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62514,71938,65228,PRETRIAL,Eluett,Davis,NULL,Male,African-American,11/05/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +62514,71938,65228,PRETRIAL,Eluett,Davis,NULL,Male,African-American,11/05/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-2.97,1,Low,New,1,0 +62514,71938,65228,PRETRIAL,Eluett,Davis,NULL,Male,African-American,11/05/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62524,71952,65239,Probation,HODGE,DARRELL,MAURICE,Male,African-American,05/07/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/7/14 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +62524,71952,65239,Probation,HODGE,DARRELL,MAURICE,Male,African-American,05/07/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/7/14 0:00,4,High,8,Risk of Recidivism,1.02,10,High,New,1,0 +62524,71952,65239,Probation,HODGE,DARRELL,MAURICE,Male,African-American,05/07/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/7/14 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +62041,71955,64664,PRETRIAL,Babitz,Howard,NULL,Male,Caucasian,06/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,Copy,1,0 +62041,71955,64664,PRETRIAL,Babitz,Howard,NULL,Male,Caucasian,06/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,Copy,1,0 +62041,71955,64664,PRETRIAL,Babitz,Howard,NULL,Male,Caucasian,06/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +51713,71969,65252,PRETRIAL,Rabinowitz,Barry,NULL,Male,Caucasian,11/16/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +51713,71969,65252,PRETRIAL,Rabinowitz,Barry,NULL,Male,Caucasian,11/16/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +51713,71969,65252,PRETRIAL,Rabinowitz,Barry,NULL,Male,Caucasian,11/16/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62510,71934,65224,PRETRIAL,WALKER,JEFFREY,DAVIS,Male,Caucasian,08/09/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +62510,71934,65224,PRETRIAL,WALKER,JEFFREY,DAVIS,Male,Caucasian,08/09/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/14 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +62510,71934,65224,PRETRIAL,WALKER,JEFFREY,DAVIS,Male,Caucasian,08/09/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +61539,71948,64115,PRETRIAL,Harbett,John,NULL,Male,Caucasian,07/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,Copy,1,0 +61539,71948,64115,PRETRIAL,Harbett,John,NULL,Male,Caucasian,07/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,Copy,1,0 +61539,71948,64115,PRETRIAL,Harbett,John,NULL,Male,Caucasian,07/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +35753,71959,65245,Probation,huezo,pablo,NULL,Male,Hispanic,09/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/7/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +35753,71959,65245,Probation,huezo,pablo,NULL,Male,Hispanic,09/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +35753,71959,65245,Probation,huezo,pablo,NULL,Male,Hispanic,09/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +870,71973,65255,PRETRIAL,KNISKERN,JULIE,Ann,Female,Other,04/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/7/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +870,71973,65255,PRETRIAL,KNISKERN,JULIE,Ann,Female,Other,04/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +870,71973,65255,PRETRIAL,KNISKERN,JULIE,Ann,Female,Other,04/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +62534,71968,65251,Probation,Mathis,Tiffany,NULL,Female,African-American,06/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +62534,71968,65251,Probation,Mathis,Tiffany,NULL,Female,African-American,06/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,8,High,New,1,0 +62534,71968,65251,Probation,Mathis,Tiffany,NULL,Female,African-American,06/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +5531,71982,5189,DRRD,THOMPSON,SEDRICK,NONE,Male,African-American,12/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,Copy,1,0 +5531,71982,5189,DRRD,THOMPSON,SEDRICK,NONE,Male,African-American,12/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.41,4,Low,Copy,1,0 +5531,71982,5189,DRRD,THOMPSON,SEDRICK,NONE,Male,African-American,12/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +62549,71989,65269,PRETRIAL,JACKSON,WILLIAM,NULL,Male,Caucasian,05/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +62549,71989,65269,PRETRIAL,JACKSON,WILLIAM,NULL,Male,Caucasian,05/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +62549,71989,65269,PRETRIAL,JACKSON,WILLIAM,NULL,Male,Caucasian,05/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62525,71953,65240,PRETRIAL,Waugh,Dwayne,NULL,Male,Other,10/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +62525,71953,65240,PRETRIAL,Waugh,Dwayne,NULL,Male,Other,10/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +62525,71953,65240,PRETRIAL,Waugh,Dwayne,NULL,Male,Other,10/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +37433,71995,65275,PRETRIAL,Neri,Clemente,NULL,Male,Caucasian,12/30/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +37433,71995,65275,PRETRIAL,Neri,Clemente,NULL,Male,Caucasian,12/30/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +37433,71995,65275,PRETRIAL,Neri,Clemente,NULL,Male,Caucasian,12/30/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +53446,71997,65277,PRETRIAL,Silva,Caesar,NULL,Male,Caucasian,11/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +53446,71997,65277,PRETRIAL,Silva,Caesar,NULL,Male,Caucasian,11/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +53446,71997,65277,PRETRIAL,Silva,Caesar,NULL,Male,Caucasian,11/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62515,71940,65230,PRETRIAL,JACKSON,KARA,NULL,Female,Caucasian,02/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +62515,71940,65230,PRETRIAL,JACKSON,KARA,NULL,Female,Caucasian,02/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,New,1,0 +62515,71940,65230,PRETRIAL,JACKSON,KARA,NULL,Female,Caucasian,02/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62540,71976,65258,Probation,simpson,alexander,NULL,Male,Caucasian,12/07/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +62540,71976,65258,Probation,simpson,alexander,NULL,Male,Caucasian,12/07/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +62540,71976,65258,Probation,simpson,alexander,NULL,Male,Caucasian,12/07/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +13995,71958,65244,PRETRIAL,mitchell,corey,NULL,Male,African-American,07/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +13995,71958,65244,PRETRIAL,mitchell,corey,NULL,Male,African-American,07/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +13995,71958,65244,PRETRIAL,mitchell,corey,NULL,Male,African-American,07/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +55090,71992,65272,PRETRIAL,Cardona,Gian,NULL,Male,Hispanic,01/10/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +55090,71992,65272,PRETRIAL,Cardona,Gian,NULL,Male,Hispanic,01/10/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,4,High,8,Risk of Recidivism,0.38,9,High,New,1,0 +55090,71992,65272,PRETRIAL,Cardona,Gian,NULL,Male,Hispanic,01/10/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62520,71945,65235,PRETRIAL,JONES,WAYNE,LLOYD,Male,African-American,07/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +62520,71945,65235,PRETRIAL,JONES,WAYNE,LLOYD,Male,African-American,07/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +62520,71945,65235,PRETRIAL,JONES,WAYNE,LLOYD,Male,African-American,07/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62543,71979,65261,PRETRIAL,Miller,Lorenzo,NULL,Male,African-American,03/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +62543,71979,65261,PRETRIAL,Miller,Lorenzo,NULL,Male,African-American,03/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +62543,71979,65261,PRETRIAL,Miller,Lorenzo,NULL,Male,African-American,03/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/7/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62513,71937,65227,PRETRIAL,Gayle,Andrew,NULL,Male,African-American,10/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +62513,71937,65227,PRETRIAL,Gayle,Andrew,NULL,Male,African-American,10/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +62513,71937,65227,PRETRIAL,Gayle,Andrew,NULL,Male,African-American,10/09/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54136,71987,65268,PRETRIAL,Cardona,Freddy,NULL,Male,Caucasian,02/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/7/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +54136,71987,65268,PRETRIAL,Cardona,Freddy,NULL,Male,Caucasian,02/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +54136,71987,65268,PRETRIAL,Cardona,Freddy,NULL,Male,Caucasian,02/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62533,71966,65249,Probation,chitwood,Ryan,NULL,Male,Caucasian,02/09/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/7/14 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +62533,71966,65249,Probation,chitwood,Ryan,NULL,Male,Caucasian,02/09/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +62533,71966,65249,Probation,chitwood,Ryan,NULL,Male,Caucasian,02/09/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/7/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62546,71984,65265,Probation,Cundari,Cathi,NULL,Female,Caucasian,02/21/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +62546,71984,65265,Probation,Cundari,Cathi,NULL,Female,Caucasian,02/21/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +62546,71984,65265,Probation,Cundari,Cathi,NULL,Female,Caucasian,02/21/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +47485,72034,65309,PRETRIAL,Garcia,Julian,Andres,Male,Hispanic,01/11/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +47485,72034,65309,PRETRIAL,Garcia,Julian,Andres,Male,Hispanic,01/11/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +47485,72034,65309,PRETRIAL,Garcia,Julian,Andres,Male,Hispanic,01/11/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62559,72005,65285,Probation,Christopher,Lee,NULL,Male,Hispanic,10/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +62559,72005,65285,Probation,Christopher,Lee,NULL,Male,Hispanic,10/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +62559,72005,65285,Probation,Christopher,Lee,NULL,Male,Hispanic,10/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62564,72013,65291,PRETRIAL,Thomas,Steven,NULL,Male,African-American,12/02/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,2,Medium,7,Risk of Violence,-3.03,1,Low,New,1,0 +62564,72013,65291,PRETRIAL,Thomas,Steven,NULL,Male,African-American,12/02/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +62564,72013,65291,PRETRIAL,Thomas,Steven,NULL,Male,African-American,12/02/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62575,72026,65302,PRETRIAL,NINO,OSVALDO,NULL,Male,Other,04/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +62575,72026,65302,PRETRIAL,NINO,OSVALDO,NULL,Male,Other,04/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +62575,72026,65302,PRETRIAL,NINO,OSVALDO,NULL,Male,Other,04/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +45109,72031,65306,PRETRIAL,Milfort,Calvin,NULL,Male,Other,12/03/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/8/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +45109,72031,65306,PRETRIAL,Milfort,Calvin,NULL,Male,Other,12/03/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +45109,72031,65306,PRETRIAL,Milfort,Calvin,NULL,Male,Other,12/03/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62562,72010,65288,Probation,Grinion,Dwight,NULL,Male,African-American,10/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +62562,72010,65288,Probation,Grinion,Dwight,NULL,Male,African-American,10/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +62562,72010,65288,Probation,Grinion,Dwight,NULL,Male,African-American,10/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62557,72003,65283,PRETRIAL,Anderson,Ciara,Rayniesha,Female,African-American,08/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +62557,72003,65283,PRETRIAL,Anderson,Ciara,Rayniesha,Female,African-American,08/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +62557,72003,65283,PRETRIAL,Anderson,Ciara,Rayniesha,Female,African-American,08/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58887,72018,61127,PRETRIAL,Hernani,Fabio,NULL,Male,Caucasian,06/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,4,High,7,Risk of Violence,-1.06,8,High,Copy,1,0 +58887,72018,61127,PRETRIAL,Hernani,Fabio,NULL,Male,Caucasian,06/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,4,High,8,Risk of Recidivism,0.87,10,High,Copy,1,0 +58887,72018,61127,PRETRIAL,Hernani,Fabio,NULL,Male,Caucasian,06/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +62569,72020,65296,Probation,Jones,Robert,NULL,Male,African-American,01/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/8/14 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +62569,72020,65296,Probation,Jones,Robert,NULL,Male,African-American,01/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +62569,72020,65296,Probation,Jones,Robert,NULL,Male,African-American,01/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/8/14 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +62563,72011,65289,Probation,dalessandro,giuseppe,NULL,Male,Hispanic,04/18/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/8/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +62563,72011,65289,Probation,dalessandro,giuseppe,NULL,Male,Hispanic,04/18/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +62563,72011,65289,Probation,dalessandro,giuseppe,NULL,Male,Hispanic,04/18/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62566,72015,65293,Probation,Singh,Robin,NULL,Male,Other,12/31/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +62566,72015,65293,Probation,Singh,Robin,NULL,Male,Other,12/31/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +62566,72015,65293,Probation,Singh,Robin,NULL,Male,Other,12/31/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62573,72024,65300,PRETRIAL,Charles,James,NULL,Male,African-American,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +62573,72024,65300,PRETRIAL,Charles,James,NULL,Male,African-American,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,4,High,8,Risk of Recidivism,0.21,8,High,New,1,0 +62573,72024,65300,PRETRIAL,Charles,James,NULL,Male,African-American,09/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62570,72022,65298,Probation,Porry,Steve,NULL,Male,Caucasian,04/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +62570,72022,65298,Probation,Porry,Steve,NULL,Male,Caucasian,04/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +62570,72022,65298,Probation,Porry,Steve,NULL,Male,Caucasian,04/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62576,72027,65303,PRETRIAL,Bowlin,Rohan,NULL,Male,African-American,06/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +62576,72027,65303,PRETRIAL,Bowlin,Rohan,NULL,Male,African-American,06/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +62576,72027,65303,PRETRIAL,Bowlin,Rohan,NULL,Male,African-American,06/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62578,72029,65305,Probation,Rawls,John,NULL,Male,Caucasian,08/07/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +62578,72029,65305,Probation,Rawls,John,NULL,Male,Caucasian,08/07/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +62578,72029,65305,Probation,Rawls,John,NULL,Male,Caucasian,08/07/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62553,71999,65279,PRETRIAL,MCNAIR,CHARESE,NICOLE,Female,African-American,03/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,4,High,7,Risk of Violence,-0.69,9,High,New,1,0 +62553,71999,65279,PRETRIAL,MCNAIR,CHARESE,NICOLE,Female,African-American,03/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +62553,71999,65279,PRETRIAL,MCNAIR,CHARESE,NICOLE,Female,African-American,03/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62555,72001,65281,PRETRIAL,DROBIAZKO,PAVEL,NULL,Male,Caucasian,02/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +62555,72001,65281,PRETRIAL,DROBIAZKO,PAVEL,NULL,Male,Caucasian,02/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +62555,72001,65281,PRETRIAL,DROBIAZKO,PAVEL,NULL,Male,Caucasian,02/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +9364,72006,37806,PRETRIAL,TURNQUEST,KEVIN,M,Male,African-American,06/29/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,Copy,1,0 +9364,72006,37806,PRETRIAL,TURNQUEST,KEVIN,M,Male,African-American,06/29/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,Copy,1,0 +9364,72006,37806,PRETRIAL,TURNQUEST,KEVIN,M,Male,African-American,06/29/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,42,10,High,Copy,1,0 +62561,72008,65287,Probation,Wells-Ferguson,Grace,NULL,Female,Caucasian,08/04/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/8/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +62561,72008,65287,Probation,Wells-Ferguson,Grace,NULL,Female,Caucasian,08/04/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +62561,72008,65287,Probation,Wells-Ferguson,Grace,NULL,Female,Caucasian,08/04/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62565,72014,65292,PRETRIAL,Sparks,Tasheika,NULL,Female,African-American,08/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +62565,72014,65292,PRETRIAL,Sparks,Tasheika,NULL,Female,African-American,08/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +62565,72014,65292,PRETRIAL,Sparks,Tasheika,NULL,Female,African-American,08/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62571,72021,65297,PRETRIAL,HULL,STUART,NULL,Male,Caucasian,06/07/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +62571,72021,65297,PRETRIAL,HULL,STUART,NULL,Male,Caucasian,06/07/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +62571,72021,65297,PRETRIAL,HULL,STUART,NULL,Male,Caucasian,06/07/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62581,72035,65310,Probation,Clayton,Otis,Earl,Male,African-American,12/24/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +62581,72035,65310,Probation,Clayton,Otis,Earl,Male,African-American,12/24/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +62581,72035,65310,Probation,Clayton,Otis,Earl,Male,African-American,12/24/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62554,72000,65280,PRETRIAL,Codorniu,Sandra,Elena,Female,Caucasian,10/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +62554,72000,65280,PRETRIAL,Codorniu,Sandra,Elena,Female,Caucasian,10/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/14 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +62554,72000,65280,PRETRIAL,Codorniu,Sandra,Elena,Female,Caucasian,10/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62577,72028,65304,Probation,Cooke,Richard,NULL,Male,African-American,11/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +62577,72028,65304,Probation,Cooke,Richard,NULL,Male,African-American,11/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +62577,72028,65304,Probation,Cooke,Richard,NULL,Male,African-American,11/22/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62556,72002,65282,PRETRIAL,WISE,RYAN,C,Male,African-American,01/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/8/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +62556,72002,65282,PRETRIAL,WISE,RYAN,C,Male,African-American,01/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +62556,72002,65282,PRETRIAL,WISE,RYAN,C,Male,African-American,01/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58887,72019,61127,PRETRIAL,Hernani,Fabio,NULL,Male,Caucasian,06/17/95,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,4,High,7,Risk of Violence,-1.06,8,High,Copy,1,0 +58887,72019,61127,PRETRIAL,Hernani,Fabio,NULL,Male,Caucasian,06/17/95,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,4,High,8,Risk of Recidivism,0.87,10,High,Copy,1,0 +58887,72019,61127,PRETRIAL,Hernani,Fabio,NULL,Male,Caucasian,06/17/95,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +62582,72037,65312,Probation,Alexandre,Bernadette,NULL,Female,African-American,06/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +62582,72037,65312,Probation,Alexandre,Bernadette,NULL,Female,African-American,06/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +62582,72037,65312,Probation,Alexandre,Bernadette,NULL,Female,African-American,06/20/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62552,71998,65278,PRETRIAL,WELLINGTON,ODANE,NULL,Male,African-American,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +62552,71998,65278,PRETRIAL,WELLINGTON,ODANE,NULL,Male,African-American,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,4,High,8,Risk of Recidivism,0.89,10,High,New,1,0 +62552,71998,65278,PRETRIAL,WELLINGTON,ODANE,NULL,Male,African-American,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62567,72016,65294,Probation,Minuto,Antoinette,NULL,Female,Caucasian,03/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/8/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +62567,72016,65294,Probation,Minuto,Antoinette,NULL,Female,Caucasian,03/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +62567,72016,65294,Probation,Minuto,Antoinette,NULL,Female,Caucasian,03/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62572,72023,65299,Probation,DosRamos,Domingo,Enrique,Male,Hispanic,10/11/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +62572,72023,65299,Probation,DosRamos,Domingo,Enrique,Male,Hispanic,10/11/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +62572,72023,65299,Probation,DosRamos,Domingo,Enrique,Male,Hispanic,10/11/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62558,72004,65284,PRETRIAL,Mohammad,Michael,Akil,Male,African-American,09/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +62558,72004,65284,PRETRIAL,Mohammad,Michael,Akil,Male,African-American,09/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +62558,72004,65284,PRETRIAL,Mohammad,Michael,Akil,Male,African-American,09/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62574,72025,65301,PRETRIAL,OUKRUST,JOSHUA,NULL,Male,Caucasian,10/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +62574,72025,65301,PRETRIAL,OUKRUST,JOSHUA,NULL,Male,Caucasian,10/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +62574,72025,65301,PRETRIAL,OUKRUST,JOSHUA,NULL,Male,Caucasian,10/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56624,72012,65290,Probation,BROWN,TATYANA,L,Female,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +56624,72012,65290,Probation,BROWN,TATYANA,L,Female,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,New,1,0 +56624,72012,65290,Probation,BROWN,TATYANA,L,Female,African-American,12/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62580,72033,65308,PRETRIAL,Klepach,Bertha,NULL,Female,African-American,12/20/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +62580,72033,65308,PRETRIAL,Klepach,Bertha,NULL,Female,African-American,12/20/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +62580,72033,65308,PRETRIAL,Klepach,Bertha,NULL,Female,African-American,12/20/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +32426,72040,65315,PRETRIAL,ahearn,robert,NULL,Male,Caucasian,09/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,2,Medium,7,Risk of Violence,-2.76,2,Low,New,1,0 +32426,72040,65315,PRETRIAL,ahearn,robert,NULL,Male,Caucasian,09/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +32426,72040,65315,PRETRIAL,ahearn,robert,NULL,Male,Caucasian,09/04/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/8/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53929,72038,65313,PRETRIAL,Belmont,Estella,NULL,Female,Hispanic,01/22/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/8/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +53929,72038,65313,PRETRIAL,Belmont,Estella,NULL,Female,Hispanic,01/22/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +53929,72038,65313,PRETRIAL,Belmont,Estella,NULL,Female,Hispanic,01/22/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +47352,72009,64464,PRETRIAL,DORMAN,BRUCE,MALCOM,Male,Caucasian,08/26/49,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,4/8/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +47352,72009,64464,PRETRIAL,DORMAN,BRUCE,MALCOM,Male,Caucasian,08/26/49,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.27,1,Low,New,1,0 +47352,72009,64464,PRETRIAL,DORMAN,BRUCE,MALCOM,Male,Caucasian,08/26/49,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +62568,72017,65295,PRETRIAL,fain,jermain,NULL,Male,African-American,05/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +62568,72017,65295,PRETRIAL,fain,jermain,NULL,Male,African-American,05/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +62568,72017,65295,PRETRIAL,fain,jermain,NULL,Male,African-American,05/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52982,72030,54386,PRETRIAL,White,Carmen,NULL,Female,African-American,11/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +52982,72030,54386,PRETRIAL,White,Carmen,NULL,Female,African-American,11/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +52982,72030,54386,PRETRIAL,White,Carmen,NULL,Female,African-American,11/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/8/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +62599,72064,65335,Probation,Khan,Ryan,NULL,Male,Other,10/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +62599,72064,65335,Probation,Khan,Ryan,NULL,Male,Other,10/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +62599,72064,65335,Probation,Khan,Ryan,NULL,Male,Other,10/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62607,72077,65345,Probation,Fox,Kelsey,NULL,Female,Caucasian,09/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +62607,72077,65345,Probation,Fox,Kelsey,NULL,Female,Caucasian,09/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +62607,72077,65345,Probation,Fox,Kelsey,NULL,Female,Caucasian,09/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62041,72051,64664,PRETRIAL,Babitz,Howard,NULL,Male,Caucasian,06/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,Copy,1,0 +62041,72051,64664,PRETRIAL,Babitz,Howard,NULL,Male,Caucasian,06/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,Copy,1,0 +62041,72051,64664,PRETRIAL,Babitz,Howard,NULL,Male,Caucasian,06/20/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +18857,72056,65328,PRETRIAL,Kersey,Robin,NULL,Female,Caucasian,01/22/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +18857,72056,65328,PRETRIAL,Kersey,Robin,NULL,Female,Caucasian,01/22/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +18857,72056,65328,PRETRIAL,Kersey,Robin,NULL,Female,Caucasian,01/22/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62590,72048,65323,PRETRIAL,Castillo,Jon,Carlos,Male,Caucasian,10/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +62590,72048,65323,PRETRIAL,Castillo,Jon,Carlos,Male,Caucasian,10/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +62590,72048,65323,PRETRIAL,Castillo,Jon,Carlos,Male,Caucasian,10/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50874,72059,65331,PRETRIAL,talavera,veronica,NULL,Female,African-American,10/28/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +50874,72059,65331,PRETRIAL,talavera,veronica,NULL,Female,African-American,10/28/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +50874,72059,65331,PRETRIAL,talavera,veronica,NULL,Female,African-American,10/28/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +34031,72069,65339,PRETRIAL,Kinsey,Michael,NULL,Male,African-American,06/24/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/9/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +34031,72069,65339,PRETRIAL,Kinsey,Michael,NULL,Male,African-American,06/24/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/9/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +34031,72069,65339,PRETRIAL,Kinsey,Michael,NULL,Male,African-American,06/24/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62601,72067,65338,Probation,Williams,Khaleel,NULL,Male,African-American,02/22/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +62601,72067,65338,Probation,Williams,Khaleel,NULL,Male,African-American,02/22/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +62601,72067,65338,Probation,Williams,Khaleel,NULL,Male,African-American,02/22/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62604,72074,65342,PRETRIAL,WHILBY,TEGRAY,NULL,Male,African-American,03/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,New,1,0 +62604,72074,65342,PRETRIAL,WHILBY,TEGRAY,NULL,Male,African-American,03/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +62604,72074,65342,PRETRIAL,WHILBY,TEGRAY,NULL,Male,African-American,03/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62588,72046,65321,PRETRIAL,Diaz,Joseph,NULL,Male,Caucasian,06/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/9/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +62588,72046,65321,PRETRIAL,Diaz,Joseph,NULL,Male,Caucasian,06/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/9/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +62588,72046,65321,PRETRIAL,Diaz,Joseph,NULL,Male,Caucasian,06/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62605,72075,65343,PRETRIAL,NOEL,JEAN,NULL,Male,African-American,01/06/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-4.32,1,Low,New,1,0 +62605,72075,65343,PRETRIAL,NOEL,JEAN,NULL,Male,African-American,01/06/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-2.74,1,Low,New,1,0 +62605,72075,65343,PRETRIAL,NOEL,JEAN,NULL,Male,African-American,01/06/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62611,72082,65349,PRETRIAL,RYALS,BRANDON,NULL,Male,African-American,10/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +62611,72082,65349,PRETRIAL,RYALS,BRANDON,NULL,Male,African-American,10/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +62611,72082,65349,PRETRIAL,RYALS,BRANDON,NULL,Male,African-American,10/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62110,72053,64752,PRETRIAL,Hatzel,Tiffany,NULL,Female,Caucasian,12/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,Copy,1,0 +62110,72053,64752,PRETRIAL,Hatzel,Tiffany,NULL,Female,Caucasian,12/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,Copy,1,0 +62110,72053,64752,PRETRIAL,Hatzel,Tiffany,NULL,Female,Caucasian,12/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +62110,72054,65327,PRETRIAL,Hatzel,Tiffany,NULL,Female,Caucasian,12/01/82,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +62110,72054,65327,PRETRIAL,Hatzel,Tiffany,NULL,Female,Caucasian,12/01/82,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +62110,72054,65327,PRETRIAL,Hatzel,Tiffany,NULL,Female,Caucasian,12/01/82,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,8,High,New,1,0 +62602,72070,65340,Probation,MILLER,JERRY,JEROME,Male,African-American,11/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/9/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +62602,72070,65340,Probation,MILLER,JERRY,JEROME,Male,African-American,11/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/9/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +62602,72070,65340,Probation,MILLER,JERRY,JEROME,Male,African-American,11/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +62608,72079,65346,Probation,Williams,Natasia,NULL,Female,African-American,09/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.37,3,Low,New,1,0 +62608,72079,65346,Probation,Williams,Natasia,NULL,Female,African-American,09/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +62608,72079,65346,Probation,Williams,Natasia,NULL,Female,African-American,09/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +62591,72049,65324,PRETRIAL,GARCIA,BENNY,LUIS,Male,Caucasian,08/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/9/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +62591,72049,65324,PRETRIAL,GARCIA,BENNY,LUIS,Male,Caucasian,08/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/9/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +62591,72049,65324,PRETRIAL,GARCIA,BENNY,LUIS,Male,Caucasian,08/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62595,72058,65330,Probation,Lorika,steven,NULL,Male,Other,08/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +62595,72058,65330,Probation,Lorika,steven,NULL,Male,Other,08/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +62595,72058,65330,Probation,Lorika,steven,NULL,Male,Other,08/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62586,72044,65319,PRETRIAL,MESA,MARCO,MANUEL,Male,Hispanic,02/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +62586,72044,65319,PRETRIAL,MESA,MARCO,MANUEL,Male,Hispanic,02/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +62586,72044,65319,PRETRIAL,MESA,MARCO,MANUEL,Male,Hispanic,02/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62598,72063,65334,Probation,Murphy,Corey,Joseph,Male,Caucasian,10/16/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/9/14 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +62598,72063,65334,Probation,Murphy,Corey,Joseph,Male,Caucasian,10/16/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +62598,72063,65334,Probation,Murphy,Corey,Joseph,Male,Caucasian,10/16/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/9/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +36863,72065,65336,Probation,WOLF,JONATHAN,LEE,Male,Caucasian,03/31/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/9/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +36863,72065,65336,Probation,WOLF,JONATHAN,LEE,Male,Caucasian,03/31/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/9/14 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +36863,72065,65336,Probation,WOLF,JONATHAN,LEE,Male,Caucasian,03/31/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +22394,72078,65106,PRETRIAL,MCBURROWS,PRESTON,NULL,Male,African-American,05/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,Copy,1,0 +22394,72078,65106,PRETRIAL,MCBURROWS,PRESTON,NULL,Male,African-American,05/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,Copy,1,0 +22394,72078,65106,PRETRIAL,MCBURROWS,PRESTON,NULL,Male,African-American,05/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +62609,72080,65347,Probation,Flack,Patrick,James,Male,Caucasian,07/11/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +62609,72080,65347,Probation,Flack,Patrick,James,Male,Caucasian,07/11/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +62609,72080,65347,Probation,Flack,Patrick,James,Male,Caucasian,07/11/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62603,72071,65341,PRETRIAL,LEWIS,DWIGHT,NULL,Male,African-American,11/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +62603,72071,65341,PRETRIAL,LEWIS,DWIGHT,NULL,Male,African-American,11/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +62603,72071,65341,PRETRIAL,LEWIS,DWIGHT,NULL,Male,African-American,11/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62585,72043,65318,PRETRIAL,Williams,Jeremy,NULL,Male,African-American,03/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +62585,72043,65318,PRETRIAL,Williams,Jeremy,NULL,Male,African-American,03/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +62585,72043,65318,PRETRIAL,Williams,Jeremy,NULL,Male,African-American,03/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62592,72050,65325,PRETRIAL,Calderon,Joseph,David,Male,Caucasian,05/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/9/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +62592,72050,65325,PRETRIAL,Calderon,Joseph,David,Male,Caucasian,05/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/9/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +62592,72050,65325,PRETRIAL,Calderon,Joseph,David,Male,Caucasian,05/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62594,72057,65329,Probation,Todd,Yennard,NULL,Male,Caucasian,01/23/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,New,1,0 +62594,72057,65329,Probation,Todd,Yennard,NULL,Male,Caucasian,01/23/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.73,10,High,New,1,0 +62594,72057,65329,Probation,Todd,Yennard,NULL,Male,Caucasian,01/23/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62587,72045,65320,PRETRIAL,Accurso,Sande,NULL,Male,Caucasian,02/21/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +62587,72045,65320,PRETRIAL,Accurso,Sande,NULL,Male,Caucasian,02/21/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +62587,72045,65320,PRETRIAL,Accurso,Sande,NULL,Male,Caucasian,02/21/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +41924,72062,41674,PRETRIAL,THOMAS,VALDON,CHARLES,Male,African-American,02/08/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/9/14 0:00,2,Medium,7,Risk of Violence,-3.43,1,Low,Copy,1,0 +41924,72062,41674,PRETRIAL,THOMAS,VALDON,CHARLES,Male,African-American,02/08/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,Copy,1,0 +41924,72062,41674,PRETRIAL,THOMAS,VALDON,CHARLES,Male,African-American,02/08/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/9/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +62443,72068,65135,PRETRIAL,castellano,timothy,NULL,Male,Caucasian,11/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,Copy,1,0 +62443,72068,65135,PRETRIAL,castellano,timothy,NULL,Male,Caucasian,11/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,Copy,1,0 +62443,72068,65135,PRETRIAL,castellano,timothy,NULL,Male,Caucasian,11/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +62606,72076,65344,Probation,Campbell,Jermaine,Andre,Male,African-American,02/23/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/9/14 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +62606,72076,65344,Probation,Campbell,Jermaine,Andre,Male,African-American,02/23/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/9/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +62606,72076,65344,Probation,Campbell,Jermaine,Andre,Male,African-American,02/23/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/9/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59434,68123,61763,Probation,harper,bruce,NULL,Male,African-American,07/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +59434,68123,61763,Probation,harper,bruce,NULL,Male,African-American,07/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +59434,68123,61763,Probation,harper,bruce,NULL,Male,African-American,07/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62610,72081,65348,PRETRIAL,Brandal,Russell,NULL,Male,Caucasian,02/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +62610,72081,65348,PRETRIAL,Brandal,Russell,NULL,Male,Caucasian,02/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +62610,72081,65348,PRETRIAL,Brandal,Russell,NULL,Male,Caucasian,02/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62589,72047,65322,PRETRIAL,Thornton,Jeffrey,NULL,Male,African-American,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +62589,72047,65322,PRETRIAL,Thornton,Jeffrey,NULL,Male,African-American,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +62589,72047,65322,PRETRIAL,Thornton,Jeffrey,NULL,Male,African-American,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/9/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62596,72060,65332,Probation,Peter,Margaret,Anne,Female,Other,09/19/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +62596,72060,65332,Probation,Peter,Margaret,Anne,Female,Other,09/19/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +62596,72060,65332,Probation,Peter,Margaret,Anne,Female,Other,09/19/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62593,72052,65326,Probation,Capellan,Michael,NULL,Male,Hispanic,04/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +62593,72052,65326,Probation,Capellan,Michael,NULL,Male,Hispanic,04/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +62593,72052,65326,Probation,Capellan,Michael,NULL,Male,Hispanic,04/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62083,72055,64719,PRETRIAL,CLARKE,DAVE,NULL,Male,African-American,08/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,Copy,1,0 +62083,72055,64719,PRETRIAL,CLARKE,DAVE,NULL,Male,African-American,08/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,Copy,1,0 +62083,72055,64719,PRETRIAL,CLARKE,DAVE,NULL,Male,African-American,08/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +59434,72073,61763,Probation,harper,bruce,NULL,Male,African-American,07/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,4/9/14 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,Copy,1,0 +59434,72073,61763,Probation,harper,bruce,NULL,Male,African-American,07/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,4/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,Copy,1,0 +59434,72073,61763,Probation,harper,bruce,NULL,Male,African-American,07/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,4/9/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +61419,72123,65384,PRETRIAL,Thurlow,Christopher,NULL,Male,Caucasian,09/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.76,2,Low,New,1,0 +61419,72123,65384,PRETRIAL,Thurlow,Christopher,NULL,Male,Caucasian,09/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +61419,72123,65384,PRETRIAL,Thurlow,Christopher,NULL,Male,Caucasian,09/19/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +62624,72102,65366,Probation,RYAN,KEVIN,BRANDON,Male,Caucasian,11/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +62624,72102,65366,Probation,RYAN,KEVIN,BRANDON,Male,Caucasian,11/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +62624,72102,65366,Probation,RYAN,KEVIN,BRANDON,Male,Caucasian,11/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62636,72120,65381,Probation,comeau,paul,NULL,Male,Caucasian,03/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,2,Medium,7,Risk of Violence,-3.45,1,Low,New,1,0 +62636,72120,65381,Probation,comeau,paul,NULL,Male,Caucasian,03/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +62636,72120,65381,Probation,comeau,paul,NULL,Male,Caucasian,03/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62620,72094,65359,PRETRIAL,Martinez,Edwin,NULL,Male,Hispanic,02/09/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,4/10/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +62620,72094,65359,PRETRIAL,Martinez,Edwin,NULL,Male,Hispanic,02/09/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,4/10/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +62620,72094,65359,PRETRIAL,Martinez,Edwin,NULL,Male,Hispanic,02/09/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62643,72128,65389,Probation,anderson,janine,NULL,Female,Caucasian,06/28/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,2,Medium,7,Risk of Violence,-3.13,1,Low,New,1,0 +62643,72128,65389,Probation,anderson,janine,NULL,Female,Caucasian,06/28/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +62643,72128,65389,Probation,anderson,janine,NULL,Female,Caucasian,06/28/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +34696,72115,33858,PRETRIAL,brodnax,sean,NULL,Male,Caucasian,08/06/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +34696,72115,33858,PRETRIAL,brodnax,sean,NULL,Male,Caucasian,08/06/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/14 0:00,4,High,8,Risk of Recidivism,0.39,8,High,New,1,0 +34696,72115,33858,PRETRIAL,brodnax,sean,NULL,Male,Caucasian,08/06/93,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/14 0:00,4,High,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +62631,72110,65374,PRETRIAL,BRICENO,DARWIN,NULL,Male,Hispanic,04/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +62631,72110,65374,PRETRIAL,BRICENO,DARWIN,NULL,Male,Hispanic,04/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +62631,72110,65374,PRETRIAL,BRICENO,DARWIN,NULL,Male,Hispanic,04/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62621,72097,65362,Probation,Taborda,Andres,NULL,Male,Hispanic,06/02/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +62621,72097,65362,Probation,Taborda,Andres,NULL,Male,Hispanic,06/02/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +62621,72097,65362,Probation,Taborda,Andres,NULL,Male,Hispanic,06/02/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +12411,72112,63885,Probation,Everett,Kenneth,NULL,Male,African-American,06/01/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +12411,72112,63885,Probation,Everett,Kenneth,NULL,Male,African-American,06/01/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,8,High,New,1,0 +12411,72112,63885,Probation,Everett,Kenneth,NULL,Male,African-American,06/01/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,8,High,New,1,0 +38908,72118,65379,PRETRIAL,hawkins,timothy,NULL,Male,African-American,12/18/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +38908,72118,65379,PRETRIAL,hawkins,timothy,NULL,Male,African-American,12/18/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +38908,72118,65379,PRETRIAL,hawkins,timothy,NULL,Male,African-American,12/18/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +62639,72125,65386,Probation,Rivas,Franquy,NULL,Male,Hispanic,04/02/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/10/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +62639,72125,65386,Probation,Rivas,Franquy,NULL,Male,Hispanic,04/02/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/10/14 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +62639,72125,65386,Probation,Rivas,Franquy,NULL,Male,Hispanic,04/02/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62618,72089,65356,PRETRIAL,Koehler,Larry,michael,Male,Caucasian,09/23/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/10/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +62618,72089,65356,PRETRIAL,Koehler,Larry,michael,Male,Caucasian,09/23/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/10/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +62618,72089,65356,PRETRIAL,Koehler,Larry,michael,Male,Caucasian,09/23/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62626,72104,65368,Probation,Callejas,Antonio,Mejia,Male,Hispanic,10/19/81,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/10/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +62626,72104,65368,Probation,Callejas,Antonio,Mejia,Male,Hispanic,10/19/81,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/10/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +62626,72104,65368,Probation,Callejas,Antonio,Mejia,Male,Hispanic,10/19/81,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62633,72113,65376,Probation,McGinley,Patrick,NULL,Male,Caucasian,02/16/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +62633,72113,65376,Probation,McGinley,Patrick,NULL,Male,Caucasian,02/16/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +62633,72113,65376,Probation,McGinley,Patrick,NULL,Male,Caucasian,02/16/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62612,72083,65350,PRETRIAL,Hayes,Fred,NULL,Female,African-American,01/11/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/10/14 0:00,2,Medium,7,Risk of Violence,-2.52,3,Low,New,1,0 +62612,72083,65350,PRETRIAL,Hayes,Fred,NULL,Female,African-American,01/11/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +62612,72083,65350,PRETRIAL,Hayes,Fred,NULL,Female,African-American,01/11/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/10/14 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +62619,72092,65358,PRETRIAL,Parker,Matthew,NULL,Male,Caucasian,11/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/10/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +62619,72092,65358,PRETRIAL,Parker,Matthew,NULL,Male,Caucasian,11/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +62619,72092,65358,PRETRIAL,Parker,Matthew,NULL,Male,Caucasian,11/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/10/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62616,72087,65354,PRETRIAL,Brown,Beaulah,NULL,Female,African-American,04/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +62616,72087,65354,PRETRIAL,Brown,Beaulah,NULL,Female,African-American,04/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +62616,72087,65354,PRETRIAL,Brown,Beaulah,NULL,Female,African-American,04/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +62638,72122,65383,Probation,Ortega,Juan,NULL,Male,Hispanic,07/29/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.08,8,High,New,1,0 +62638,72122,65383,Probation,Ortega,Juan,NULL,Male,Hispanic,07/29/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +62638,72122,65383,Probation,Ortega,Juan,NULL,Male,Hispanic,07/29/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62641,72127,65388,Probation,avila,loly,NULL,Male,Hispanic,11/24/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +62641,72127,65388,Probation,avila,loly,NULL,Male,Hispanic,11/24/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +62641,72127,65388,Probation,avila,loly,NULL,Male,Hispanic,11/24/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +30796,72129,65390,PRETRIAL,BAXTER,IRWIN,NULL,Male,African-American,03/11/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +30796,72129,65390,PRETRIAL,BAXTER,IRWIN,NULL,Male,African-American,03/11/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +30796,72129,65390,PRETRIAL,BAXTER,IRWIN,NULL,Male,African-American,03/11/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +62623,72101,65365,PRETRIAL,Gonzalez,Alicia,NULL,Female,Other,01/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/10/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +62623,72101,65365,PRETRIAL,Gonzalez,Alicia,NULL,Female,Other,01/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/10/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +62623,72101,65365,PRETRIAL,Gonzalez,Alicia,NULL,Female,Other,01/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62628,72106,65370,Probation,Thompson,Nykia,NULL,Male,African-American,06/16/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,4,High,7,Risk of Violence,-0.95,9,High,New,1,0 +62628,72106,65370,Probation,Thompson,Nykia,NULL,Male,African-American,06/16/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,4,High,8,Risk of Recidivism,0.98,10,High,New,1,0 +62628,72106,65370,Probation,Thompson,Nykia,NULL,Male,African-American,06/16/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62629,72108,65372,Probation,Carroll,Travis,Edward,Male,Caucasian,01/23/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +62629,72108,65372,Probation,Carroll,Travis,Edward,Male,Caucasian,01/23/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +62629,72108,65372,Probation,Carroll,Travis,Edward,Male,Caucasian,01/23/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62634,72114,65377,Probation,BASKIN,MICHAEL,RAY,Male,Caucasian,02/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,4/10/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +62634,72114,65377,Probation,BASKIN,MICHAEL,RAY,Male,Caucasian,02/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,4/10/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +62634,72114,65377,Probation,BASKIN,MICHAEL,RAY,Male,Caucasian,02/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +54402,72093,56033,PRETRIAL,Fraser,Paul,NULL,Male,African-American,09/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,Copy,1,0 +54402,72093,56033,PRETRIAL,Fraser,Paul,NULL,Male,African-American,09/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,Copy,1,0 +54402,72093,56033,PRETRIAL,Fraser,Paul,NULL,Male,African-American,09/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +9742,72100,9268,PRETRIAL,FLORENCE,CURTIS,NULL,Male,African-American,01/14/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.44,3,Low,Copy,1,0 +9742,72100,9268,PRETRIAL,FLORENCE,CURTIS,NULL,Male,African-American,01/14/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,Copy,1,0 +9742,72100,9268,PRETRIAL,FLORENCE,CURTIS,NULL,Male,African-American,01/14/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +62630,72107,65371,Probation,Mileto,james,NULL,Male,Caucasian,08/02/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-4.33,1,Low,New,1,0 +62630,72107,65371,Probation,Mileto,james,NULL,Male,Caucasian,08/02/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +62630,72107,65371,Probation,Mileto,james,NULL,Male,Caucasian,08/02/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62615,72086,65353,PRETRIAL,Septembre,Peter,Louis,Male,Other,02/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +62615,72086,65353,PRETRIAL,Septembre,Peter,Louis,Male,Other,02/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +62615,72086,65353,PRETRIAL,Septembre,Peter,Louis,Male,Other,02/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62637,72121,65382,Probation,Norris,Willie,NULL,Male,African-American,04/23/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.12,1,Low,New,1,0 +62637,72121,65382,Probation,Norris,Willie,NULL,Male,African-American,04/23/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +62637,72121,65382,Probation,Norris,Willie,NULL,Male,African-American,04/23/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +57056,72126,65387,PRETRIAL,Santiago,Patrick,NULL,Male,African-American,05/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +57056,72126,65387,PRETRIAL,Santiago,Patrick,NULL,Male,African-American,05/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +57056,72126,65387,PRETRIAL,Santiago,Patrick,NULL,Male,African-American,05/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62627,72105,65369,Probation,gavagni,kenneth,NULL,Male,Caucasian,11/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +62627,72105,65369,Probation,gavagni,kenneth,NULL,Male,Caucasian,11/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +62627,72105,65369,Probation,gavagni,kenneth,NULL,Male,Caucasian,11/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62613,72084,65351,PRETRIAL,Gangemi,Robert,NULL,Male,Caucasian,05/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +62613,72084,65351,PRETRIAL,Gangemi,Robert,NULL,Male,Caucasian,05/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +62613,72084,65351,PRETRIAL,Gangemi,Robert,NULL,Male,Caucasian,05/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61762,72091,65357,PRETRIAL,Ballestas,Abraham,NULL,Male,Hispanic,10/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/10/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +61762,72091,65357,PRETRIAL,Ballestas,Abraham,NULL,Male,Hispanic,10/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/10/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +61762,72091,65357,PRETRIAL,Ballestas,Abraham,NULL,Male,Hispanic,10/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57159,72109,65373,PRETRIAL,Butler,Tabria,NULL,Female,African-American,06/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +57159,72109,65373,PRETRIAL,Butler,Tabria,NULL,Female,African-American,06/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +57159,72109,65373,PRETRIAL,Butler,Tabria,NULL,Female,African-American,06/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +62625,72103,65367,Probation,Mccall,Tyrance,NULL,Male,African-American,12/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,2,Medium,7,Risk of Violence,-3.02,1,Low,New,1,0 +62625,72103,65367,Probation,Mccall,Tyrance,NULL,Male,African-American,12/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +62625,72103,65367,Probation,Mccall,Tyrance,NULL,Male,African-American,12/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62635,72119,65380,Probation,Astiazarain,Allen,NULL,Male,Caucasian,08/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +62635,72119,65380,Probation,Astiazarain,Allen,NULL,Male,Caucasian,08/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +62635,72119,65380,Probation,Astiazarain,Allen,NULL,Male,Caucasian,08/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +34219,72098,65363,Probation,Forman,Jason,Thomas,Male,Caucasian,01/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,2,Medium,7,Risk of Violence,-2.86,2,Low,New,1,0 +34219,72098,65363,Probation,Forman,Jason,Thomas,Male,Caucasian,01/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +34219,72098,65363,Probation,Forman,Jason,Thomas,Male,Caucasian,01/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +62614,72085,65352,PRETRIAL,Allnutt,Beatriz,E,Female,Caucasian,08/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +62614,72085,65352,PRETRIAL,Allnutt,Beatriz,E,Female,Caucasian,08/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +62614,72085,65352,PRETRIAL,Allnutt,Beatriz,E,Female,Caucasian,08/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62617,72090,65355,PRETRIAL,Ealey,Neiko,NULL,Male,African-American,11/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,Copy,1,0 +62617,72090,65355,PRETRIAL,Ealey,Neiko,NULL,Male,African-American,11/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,Copy,1,0 +62617,72090,65355,PRETRIAL,Ealey,Neiko,NULL,Male,African-American,11/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +62640,72124,65385,Probation,hughes,geraldine,NULL,Female,African-American,06/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +62640,72124,65385,Probation,hughes,geraldine,NULL,Female,African-American,06/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +62640,72124,65385,Probation,hughes,geraldine,NULL,Female,African-American,06/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/10/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62662,72158,65411,Probation,CHUSID,ROBERT,F,Male,Caucasian,08/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +62662,72158,65411,Probation,CHUSID,ROBERT,F,Male,Caucasian,08/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +62662,72158,65411,Probation,CHUSID,ROBERT,F,Male,Caucasian,08/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62653,72145,65403,Probation,JEAN,WAYNE,NULL,Male,African-American,05/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +62653,72145,65403,Probation,JEAN,WAYNE,NULL,Male,African-American,05/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +62653,72145,65403,Probation,JEAN,WAYNE,NULL,Male,African-American,05/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62667,72166,65418,PRETRIAL,Raybon,Nichol,NULL,Female,African-American,11/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/11/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +62667,72166,65418,PRETRIAL,Raybon,Nichol,NULL,Female,African-American,11/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/11/14 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +62667,72166,65418,PRETRIAL,Raybon,Nichol,NULL,Female,African-American,11/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62646,72137,65395,PRETRIAL,Lockett,David,NULL,Male,African-American,09/29/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +62646,72137,65395,PRETRIAL,Lockett,David,NULL,Male,African-American,09/29/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +62646,72137,65395,PRETRIAL,Lockett,David,NULL,Male,African-American,09/29/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62649,72140,65398,Probation,BROWN,JOHN,NULL,Male,African-American,09/02/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/11/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +62649,72140,65398,Probation,BROWN,JOHN,NULL,Male,African-American,09/02/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/11/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +62649,72140,65398,Probation,BROWN,JOHN,NULL,Male,African-American,09/02/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62660,72151,65409,Probation,osbourne,daison,NULL,Male,African-American,02/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +62660,72151,65409,Probation,osbourne,daison,NULL,Male,African-American,02/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +62660,72151,65409,Probation,osbourne,daison,NULL,Male,African-American,02/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62655,72147,65405,Probation,dobrolezhin,julimar,NULL,Female,Hispanic,07/11/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +62655,72147,65405,Probation,dobrolezhin,julimar,NULL,Female,Hispanic,07/11/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +62655,72147,65405,Probation,dobrolezhin,julimar,NULL,Female,Hispanic,07/11/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51360,72144,65402,PRETRIAL,CHURCHILL,MONICA,NULL,Female,Caucasian,10/05/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/11/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +51360,72144,65402,PRETRIAL,CHURCHILL,MONICA,NULL,Female,Caucasian,10/05/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/11/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +51360,72144,65402,PRETRIAL,CHURCHILL,MONICA,NULL,Female,Caucasian,10/05/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62665,72163,65415,Probation,Banks,Ronald,Earl,Male,Caucasian,05/10/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/11/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +62665,72163,65415,Probation,Banks,Ronald,Earl,Male,Caucasian,05/10/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/11/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +62665,72163,65415,Probation,Banks,Ronald,Earl,Male,Caucasian,05/10/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62651,72142,65400,Probation,MORELL,JOHNNY,MARTIN,Male,Caucasian,08/18/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +62651,72142,65400,Probation,MORELL,JOHNNY,MARTIN,Male,Caucasian,08/18/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +62651,72142,65400,Probation,MORELL,JOHNNY,MARTIN,Male,Caucasian,08/18/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62666,72165,65417,Probation,Bonilla,Charmen,NULL,Female,Hispanic,11/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +62666,72165,65417,Probation,Bonilla,Charmen,NULL,Female,Hispanic,11/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +62666,72165,65417,Probation,Bonilla,Charmen,NULL,Female,Hispanic,11/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62645,72136,65394,PRETRIAL,Verhagen,Joey,NULL,Male,Hispanic,01/29/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +62645,72136,65394,PRETRIAL,Verhagen,Joey,NULL,Male,Hispanic,01/29/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,4,High,8,Risk of Recidivism,0.73,10,High,New,1,0 +62645,72136,65394,PRETRIAL,Verhagen,Joey,NULL,Male,Hispanic,01/29/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62652,72143,65401,Probation,campbell,taraneh,NULL,Female,Caucasian,12/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +62652,72143,65401,Probation,campbell,taraneh,NULL,Female,Caucasian,12/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +62652,72143,65401,Probation,campbell,taraneh,NULL,Female,Caucasian,12/14/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +48323,72157,49005,PRETRIAL,Fredricks,Evins,NULL,Male,African-American,07/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,4,High,7,Risk of Violence,-1.2,8,High,Copy,1,0 +48323,72157,49005,PRETRIAL,Fredricks,Evins,NULL,Male,African-American,07/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,4,High,8,Risk of Recidivism,1.34,10,High,Copy,1,0 +48323,72157,49005,PRETRIAL,Fredricks,Evins,NULL,Male,African-American,07/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,4,High,18,Risk of Failure to Appear,34,10,High,Copy,1,0 +62647,72138,65396,PRETRIAL,FernandezCalana,Jorge,Enrique,Male,Hispanic,06/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +62647,72138,65396,PRETRIAL,FernandezCalana,Jorge,Enrique,Male,Hispanic,06/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +62647,72138,65396,PRETRIAL,FernandezCalana,Jorge,Enrique,Male,Hispanic,06/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +12534,72152,12017,PRETRIAL,NEFF,CHRISTOPHER,NULL,Male,Caucasian,06/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,2,Medium,7,Risk of Violence,-1.51,6,Medium,Copy,1,0 +12534,72152,12017,PRETRIAL,NEFF,CHRISTOPHER,NULL,Male,Caucasian,06/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,Copy,1,0 +12534,72152,12017,PRETRIAL,NEFF,CHRISTOPHER,NULL,Male,Caucasian,06/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +62661,72155,65410,PRETRIAL,Senior,Dillion,NULL,Male,African-American,11/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +62661,72155,65410,PRETRIAL,Senior,Dillion,NULL,Male,African-American,11/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.81,3,Low,Copy,1,0 +62661,72155,65410,PRETRIAL,Senior,Dillion,NULL,Male,African-American,11/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +12368,72134,65393,PRETRIAL,SIMMON,TERRON,NULL,Male,African-American,01/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,4,High,7,Risk of Violence,-0.73,9,High,New,1,0 +12368,72134,65393,PRETRIAL,SIMMON,TERRON,NULL,Male,African-American,01/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,4,High,8,Risk of Recidivism,1.27,10,High,New,1,0 +12368,72134,65393,PRETRIAL,SIMMON,TERRON,NULL,Male,African-American,01/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +62657,72148,65406,DRRD,Grinion,Dwight,Courtney,Male,African-American,10/20/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/11/14 0:00,4,High,7,Risk of Violence,-0.76,9,High,New,1,0 +62657,72148,65406,DRRD,Grinion,Dwight,Courtney,Male,African-American,10/20/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/11/14 0:00,4,High,8,Risk of Recidivism,0.58,9,High,New,1,0 +62657,72148,65406,DRRD,Grinion,Dwight,Courtney,Male,African-American,10/20/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/11/14 0:00,4,High,18,Risk of Failure to Appear,16,1,Low,New,1,0 +62663,72159,65412,Probation,anderson,darryl,NULL,Male,African-American,11/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +62663,72159,65412,Probation,anderson,darryl,NULL,Male,African-American,11/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +62663,72159,65412,Probation,anderson,darryl,NULL,Male,African-American,11/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54021,72164,65416,PRETRIAL,Williams,Vandivuiet,NULL,Male,African-American,11/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +54021,72164,65416,PRETRIAL,Williams,Vandivuiet,NULL,Male,African-American,11/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +54021,72164,65416,PRETRIAL,Williams,Vandivuiet,NULL,Male,African-American,11/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62644,72131,65391,PRETRIAL,McRae,Bernice,NULL,Male,African-American,11/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.53,3,Low,New,1,0 +62644,72131,65391,PRETRIAL,McRae,Bernice,NULL,Male,African-American,11/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +62644,72131,65391,PRETRIAL,McRae,Bernice,NULL,Male,African-American,11/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +62654,72146,65404,Probation,SKEETE,KENDALL,DEMON,Male,African-American,06/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +62654,72146,65404,Probation,SKEETE,KENDALL,DEMON,Male,African-American,06/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +62654,72146,65404,Probation,SKEETE,KENDALL,DEMON,Male,African-American,06/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +7211,72133,6799,PRETRIAL,LYNCH,GERMAINE,ANTHONY,Male,African-American,09/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,Copy,1,0 +7211,72133,6799,PRETRIAL,LYNCH,GERMAINE,ANTHONY,Male,African-American,09/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,Copy,1,0 +7211,72133,6799,PRETRIAL,LYNCH,GERMAINE,ANTHONY,Male,African-American,09/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +25542,72167,65419,PRETRIAL,BRENNEMAN,RICHARD,MATTHEW,Male,Caucasian,06/13/84,17,All Scales,Intake,English,Other,Probation,Single,4/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,New,1,0 +25542,72167,65419,PRETRIAL,BRENNEMAN,RICHARD,MATTHEW,Male,Caucasian,06/13/84,17,All Scales,Intake,English,Other,Probation,Single,4/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +25542,72167,65419,PRETRIAL,BRENNEMAN,RICHARD,MATTHEW,Male,Caucasian,06/13/84,17,All Scales,Intake,English,Other,Probation,Single,4/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,8,High,New,1,0 +62658,72149,65407,PRETRIAL,Infantolino,Diane,NULL,Female,Caucasian,02/15/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,4/11/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +62658,72149,65407,PRETRIAL,Infantolino,Diane,NULL,Female,Caucasian,02/15/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,4/11/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +62658,72149,65407,PRETRIAL,Infantolino,Diane,NULL,Female,Caucasian,02/15/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +56259,72162,65414,Probation,Casseus,Pierre,NULL,Male,African-American,08/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +56259,72162,65414,Probation,Casseus,Pierre,NULL,Male,African-American,08/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +56259,72162,65414,Probation,Casseus,Pierre,NULL,Male,African-American,08/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/11/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62650,72141,65399,Probation,DIAZ,CARLOS,NULL,Male,Hispanic,08/11/85,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/11/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62650,72141,65399,Probation,DIAZ,CARLOS,NULL,Male,Hispanic,08/11/85,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/11/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +62650,72141,65399,Probation,DIAZ,CARLOS,NULL,Male,Hispanic,08/11/85,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/11/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59944,72170,65421,PRETRIAL,CELESTIN,SHELIA,NULL,Female,African-American,11/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +59944,72170,65421,PRETRIAL,CELESTIN,SHELIA,NULL,Female,African-American,11/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,9,High,New,1,0 +59944,72170,65421,PRETRIAL,CELESTIN,SHELIA,NULL,Female,African-American,11/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62673,72175,65426,PRETRIAL,Crespo,Ricardo,NULL,Male,Hispanic,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +62673,72175,65426,PRETRIAL,Crespo,Ricardo,NULL,Male,Hispanic,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +62673,72175,65426,PRETRIAL,Crespo,Ricardo,NULL,Male,Hispanic,12/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62671,72173,65424,PRETRIAL,mair,carl,NULL,Male,Other,03/08/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +62671,72173,65424,PRETRIAL,mair,carl,NULL,Male,Other,03/08/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +62671,72173,65424,PRETRIAL,mair,carl,NULL,Male,Other,03/08/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +57384,72169,59495,PRETRIAL,Alcy,Kendy,NULL,Male,African-American,08/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/12/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,Copy,1,0 +57384,72169,59495,PRETRIAL,Alcy,Kendy,NULL,Male,African-American,08/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/12/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,Copy,1,0 +57384,72169,59495,PRETRIAL,Alcy,Kendy,NULL,Male,African-American,08/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +62669,72171,65422,PRETRIAL,RIPERT,GASNER,NULL,Male,Other,03/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/12/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +62669,72171,65422,PRETRIAL,RIPERT,GASNER,NULL,Male,Other,03/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/12/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +62669,72171,65422,PRETRIAL,RIPERT,GASNER,NULL,Male,Other,03/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/12/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62676,72178,65429,PRETRIAL,Estilien,Jonathan,NULL,Male,African-American,02/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +62676,72178,65429,PRETRIAL,Estilien,Jonathan,NULL,Male,African-American,02/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +62676,72178,65429,PRETRIAL,Estilien,Jonathan,NULL,Male,African-American,02/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62670,72172,65423,PRETRIAL,Reid,Merlene,NULL,Female,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +62670,72172,65423,PRETRIAL,Reid,Merlene,NULL,Female,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,4,High,8,Risk of Recidivism,0.27,9,High,New,1,0 +62670,72172,65423,PRETRIAL,Reid,Merlene,NULL,Female,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62675,72177,65428,PRETRIAL,Veltchev,Jordan,NULL,Male,Caucasian,08/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +62675,72177,65428,PRETRIAL,Veltchev,Jordan,NULL,Male,Caucasian,08/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +62675,72177,65428,PRETRIAL,Veltchev,Jordan,NULL,Male,Caucasian,08/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62672,72174,65425,PRETRIAL,Lagrandeur,Roberto,NULL,Male,African-American,04/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +62672,72174,65425,PRETRIAL,Lagrandeur,Roberto,NULL,Male,African-American,04/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,4,High,8,Risk of Recidivism,0.8,10,High,New,1,0 +62672,72174,65425,PRETRIAL,Lagrandeur,Roberto,NULL,Male,African-American,04/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62674,72176,65427,PRETRIAL,FORSYTH,ANDREW,NULL,Male,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +62674,72176,65427,PRETRIAL,FORSYTH,ANDREW,NULL,Male,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +62674,72176,65427,PRETRIAL,FORSYTH,ANDREW,NULL,Male,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62668,72168,65420,PRETRIAL,Menkes,Kelly,Ann,Female,Caucasian,04/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +62668,72168,65420,PRETRIAL,Menkes,Kelly,Ann,Female,Caucasian,04/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +62668,72168,65420,PRETRIAL,Menkes,Kelly,Ann,Female,Caucasian,04/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/12/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62678,72182,65432,PRETRIAL,NOAKES,NICOLE,AUDRA,Female,Caucasian,09/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +62678,72182,65432,PRETRIAL,NOAKES,NICOLE,AUDRA,Female,Caucasian,09/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +62678,72182,65432,PRETRIAL,NOAKES,NICOLE,AUDRA,Female,Caucasian,09/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62682,72189,65437,PRETRIAL,Falmer,Samuel,NULL,Male,African-American,05/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,2,Medium,7,Risk of Violence,-2.7,2,Low,New,1,0 +62682,72189,65437,PRETRIAL,Falmer,Samuel,NULL,Male,African-American,05/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +62682,72189,65437,PRETRIAL,Falmer,Samuel,NULL,Male,African-American,05/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +745,72187,438,PRETRIAL,johnson,roderick,NULL,Male,African-American,09/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,Copy,1,0 +745,72187,438,PRETRIAL,johnson,roderick,NULL,Male,African-American,09/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,Copy,1,0 +745,72187,438,PRETRIAL,johnson,roderick,NULL,Male,African-American,09/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +62679,72184,65434,PRETRIAL,WILLIAMS,GREGORY,NASYMTH,Male,Caucasian,06/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +62679,72184,65434,PRETRIAL,WILLIAMS,GREGORY,NASYMTH,Male,Caucasian,06/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +62679,72184,65434,PRETRIAL,WILLIAMS,GREGORY,NASYMTH,Male,Caucasian,06/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +46476,72179,46889,PRETRIAL,Pierre,Jerry,NULL,Male,African-American,12/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,Copy,1,0 +46476,72179,46889,PRETRIAL,Pierre,Jerry,NULL,Male,African-American,12/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,Copy,1,0 +46476,72179,46889,PRETRIAL,Pierre,Jerry,NULL,Male,African-American,12/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +19460,72181,65431,PRETRIAL,Singletary,Mark,A,Male,African-American,12/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +19460,72181,65431,PRETRIAL,Singletary,Mark,A,Male,African-American,12/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +19460,72181,65431,PRETRIAL,Singletary,Mark,A,Male,African-American,12/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +31727,72186,47680,PRETRIAL,GRAYHEART,CHRISTOPHER,NULL,Male,African-American,01/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,4,High,7,Risk of Violence,-1.07,8,High,Copy,1,0 +31727,72186,47680,PRETRIAL,GRAYHEART,CHRISTOPHER,NULL,Male,African-American,01/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,4,High,8,Risk of Recidivism,0.5,9,High,Copy,1,0 +31727,72186,47680,PRETRIAL,GRAYHEART,CHRISTOPHER,NULL,Male,African-American,01/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +62677,72180,65430,PRETRIAL,Joseph,Rivenson,NULL,Male,African-American,01/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +62677,72180,65430,PRETRIAL,Joseph,Rivenson,NULL,Male,African-American,01/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +62677,72180,65430,PRETRIAL,Joseph,Rivenson,NULL,Male,African-American,01/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62680,72185,65435,PRETRIAL,MCCLAMROCK,LEMUEL,ERVIN,Male,Caucasian,09/01/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +62680,72185,65435,PRETRIAL,MCCLAMROCK,LEMUEL,ERVIN,Male,Caucasian,09/01/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +62680,72185,65435,PRETRIAL,MCCLAMROCK,LEMUEL,ERVIN,Male,Caucasian,09/01/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62683,72190,65438,PRETRIAL,Beckford,Kaleen,NULL,Female,Other,02/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +62683,72190,65438,PRETRIAL,Beckford,Kaleen,NULL,Female,Other,02/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +62683,72190,65438,PRETRIAL,Beckford,Kaleen,NULL,Female,Other,02/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +62681,72188,65436,PRETRIAL,PASTOR,GEOFFREY,ALLEN,Male,Caucasian,08/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/13/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +62681,72188,65436,PRETRIAL,PASTOR,GEOFFREY,ALLEN,Male,Caucasian,08/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/13/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +62681,72188,65436,PRETRIAL,PASTOR,GEOFFREY,ALLEN,Male,Caucasian,08/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47225,72183,65433,Probation,harris,alrick,NULL,Male,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +47225,72183,65433,Probation,harris,alrick,NULL,Male,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +47225,72183,65433,Probation,harris,alrick,NULL,Male,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62714,72217,65465,Probation,Dacres,Chantel,NULL,Female,African-American,12/11/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/14/14 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +62714,72217,65465,Probation,Dacres,Chantel,NULL,Female,African-American,12/11/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +62714,72217,65465,Probation,Dacres,Chantel,NULL,Female,African-American,12/11/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/14/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62706,72209,65457,Probation,THOMAS,CLINTON,NULL,Male,African-American,03/29/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +62706,72209,65457,Probation,THOMAS,CLINTON,NULL,Male,African-American,03/29/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +62706,72209,65457,Probation,THOMAS,CLINTON,NULL,Male,African-American,03/29/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62720,72225,65473,Probation,schreck,alexandra,NULL,Female,Caucasian,01/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,New,1,0 +62720,72225,65473,Probation,schreck,alexandra,NULL,Female,Caucasian,01/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +62720,72225,65473,Probation,schreck,alexandra,NULL,Female,Caucasian,01/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56729,72212,65460,PRETRIAL,CREIGHTNEY,MICHAEL,GARTH,Male,African-American,05/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2,4,Low,New,1,0 +56729,72212,65460,PRETRIAL,CREIGHTNEY,MICHAEL,GARTH,Male,African-American,05/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +56729,72212,65460,PRETRIAL,CREIGHTNEY,MICHAEL,GARTH,Male,African-American,05/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62712,72215,65463,Probation,Balkissoon,David,NULL,Male,Other,08/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/14/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +62712,72215,65463,Probation,Balkissoon,David,NULL,Male,Other,08/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +62712,72215,65463,Probation,Balkissoon,David,NULL,Male,Other,08/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62719,72224,65472,PRETRIAL,Martinez,Natalie,NULL,Female,Caucasian,01/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/14/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +62719,72224,65472,PRETRIAL,Martinez,Natalie,NULL,Female,Caucasian,01/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +62719,72224,65472,PRETRIAL,Martinez,Natalie,NULL,Female,Caucasian,01/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62691,72194,65442,PRETRIAL,TRAUTMAN,BRUCE,ALAN,Male,Caucasian,07/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/14/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +62691,72194,65442,PRETRIAL,TRAUTMAN,BRUCE,ALAN,Male,Caucasian,07/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +62691,72194,65442,PRETRIAL,TRAUTMAN,BRUCE,ALAN,Male,Caucasian,07/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62708,72211,65459,Probation,Douglas,YOLANDA,NULL,Female,African-American,06/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/14/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +62708,72211,65459,Probation,Douglas,YOLANDA,NULL,Female,African-American,06/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +62708,72211,65459,Probation,Douglas,YOLANDA,NULL,Female,African-American,06/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62717,72220,65468,Probation,tito,Yusimi,NULL,Female,Hispanic,08/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/14/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +62717,72220,65468,Probation,tito,Yusimi,NULL,Female,Hispanic,08/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/14/14 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +62717,72220,65468,Probation,tito,Yusimi,NULL,Female,Hispanic,08/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +62722,72227,65475,Probation,OSBORNE,TRENT,NULL,Male,African-American,05/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +62722,72227,65475,Probation,OSBORNE,TRENT,NULL,Male,African-American,05/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +62722,72227,65475,Probation,OSBORNE,TRENT,NULL,Male,African-American,05/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62697,72199,65447,Probation,CHAVEZ,ERIKA,E,Female,Hispanic,08/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +62697,72199,65447,Probation,CHAVEZ,ERIKA,E,Female,Hispanic,08/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +62697,72199,65447,Probation,CHAVEZ,ERIKA,E,Female,Hispanic,08/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62699,72201,65449,Probation,davis,andre,NULL,Male,African-American,01/31/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +62699,72201,65449,Probation,davis,andre,NULL,Male,African-American,01/31/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +62699,72201,65449,Probation,davis,andre,NULL,Male,African-American,01/31/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62705,72208,65456,Probation,Calloway,Freddie,NULL,Male,African-American,03/29/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.77,2,Low,New,1,0 +62705,72208,65456,Probation,Calloway,Freddie,NULL,Male,African-American,03/29/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +62705,72208,65456,Probation,Calloway,Freddie,NULL,Male,African-American,03/29/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62690,72193,65441,PRETRIAL,Barnett,Dwayne,NULL,Male,Other,11/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +62690,72193,65441,PRETRIAL,Barnett,Dwayne,NULL,Male,Other,11/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +62690,72193,65441,PRETRIAL,Barnett,Dwayne,NULL,Male,Other,11/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62698,72200,65448,Probation,Markowitz,Michael,David,Male,Caucasian,11/27/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/14/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +62698,72200,65448,Probation,Markowitz,Michael,David,Male,Caucasian,11/27/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/14/14 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +62698,72200,65448,Probation,Markowitz,Michael,David,Male,Caucasian,11/27/58,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62704,72207,65455,PRETRIAL,antonopoulos,christian,NULL,Male,Caucasian,12/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/14/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +62704,72207,65455,PRETRIAL,antonopoulos,christian,NULL,Male,Caucasian,12/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +62704,72207,65455,PRETRIAL,antonopoulos,christian,NULL,Male,Caucasian,12/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62723,72228,65476,Probation,ehret,christopher,NULL,Male,Caucasian,12/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,2,Medium,7,Risk of Violence,-2.27,3,Low,New,1,0 +62723,72228,65476,Probation,ehret,christopher,NULL,Male,Caucasian,12/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +62723,72228,65476,Probation,ehret,christopher,NULL,Male,Caucasian,12/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62696,72198,65446,Probation,Kerolle,Daniel,NULL,Male,African-American,04/24/90,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/14/14 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +62696,72198,65446,Probation,Kerolle,Daniel,NULL,Male,African-American,04/24/90,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/14/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +62696,72198,65446,Probation,Kerolle,Daniel,NULL,Male,African-American,04/24/90,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62700,72202,65450,Probation,DIPPOLITO,ANTHONY,E,Male,Caucasian,10/09/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +62700,72202,65450,Probation,DIPPOLITO,ANTHONY,E,Male,Caucasian,10/09/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +62700,72202,65450,Probation,DIPPOLITO,ANTHONY,E,Male,Caucasian,10/09/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62713,72216,65464,Probation,corzon,pedro,NULL,Male,Hispanic,06/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +62713,72216,65464,Probation,corzon,pedro,NULL,Male,Hispanic,06/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +62713,72216,65464,Probation,corzon,pedro,NULL,Male,Hispanic,06/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62718,72223,65471,PRETRIAL,OVALLE-RODRIGUEZ,JOSE,NULL,Male,Hispanic,05/24/81,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,4/14/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +62718,72223,65471,PRETRIAL,OVALLE-RODRIGUEZ,JOSE,NULL,Male,Hispanic,05/24/81,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +62718,72223,65471,PRETRIAL,OVALLE-RODRIGUEZ,JOSE,NULL,Male,Hispanic,05/24/81,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62709,72213,65461,PRETRIAL,Valadez,Chase,Anthony,Male,Caucasian,05/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +62709,72213,65461,PRETRIAL,Valadez,Chase,Anthony,Male,Caucasian,05/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +62709,72213,65461,PRETRIAL,Valadez,Chase,Anthony,Male,Caucasian,05/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62689,72192,65440,PRETRIAL,JONES,TRACYANN,ALECIA,Female,Other,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/14/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +62689,72192,65440,PRETRIAL,JONES,TRACYANN,ALECIA,Female,Other,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +62689,72192,65440,PRETRIAL,JONES,TRACYANN,ALECIA,Female,Other,09/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62721,72226,65474,Probation,Lidowski,Michelle,NULL,Female,Caucasian,12/29/79,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/14/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +62721,72226,65474,Probation,Lidowski,Michelle,NULL,Female,Caucasian,12/29/79,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +62721,72226,65474,Probation,Lidowski,Michelle,NULL,Female,Caucasian,12/29/79,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62702,72205,65453,Probation,Alcalde,Angie,NULL,Female,Hispanic,10/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +62702,72205,65453,Probation,Alcalde,Angie,NULL,Female,Hispanic,10/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +62702,72205,65453,Probation,Alcalde,Angie,NULL,Female,Hispanic,10/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +36975,72203,65451,PRETRIAL,Brown,Norris,L,Male,African-American,08/16/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,2,Medium,7,Risk of Violence,-2.97,1,Low,New,1,0 +36975,72203,65451,PRETRIAL,Brown,Norris,L,Male,African-American,08/16/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +36975,72203,65451,PRETRIAL,Brown,Norris,L,Male,African-American,08/16/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62715,72218,65466,Probation,westmoreland,sean,NULL,Male,African-American,04/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +62715,72218,65466,Probation,westmoreland,sean,NULL,Male,African-American,04/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +62715,72218,65466,Probation,westmoreland,sean,NULL,Male,African-American,04/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62707,72210,65458,Probation,underwood,isaiah,NULL,Male,African-American,01/05/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +62707,72210,65458,Probation,underwood,isaiah,NULL,Male,African-American,01/05/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,4,High,8,Risk of Recidivism,0.66,10,High,New,1,0 +62707,72210,65458,Probation,underwood,isaiah,NULL,Male,African-American,01/05/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/14/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62692,72195,65443,PRETRIAL,HAURSTON,AYUSHAUN,NULL,Male,African-American,08/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/14/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +62692,72195,65443,PRETRIAL,HAURSTON,AYUSHAUN,NULL,Male,African-American,08/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/14/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +62692,72195,65443,PRETRIAL,HAURSTON,AYUSHAUN,NULL,Male,African-American,08/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62694,72197,65445,PRETRIAL,Copeland,John,Clark,Male,Caucasian,01/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +62694,72197,65445,PRETRIAL,Copeland,John,Clark,Male,Caucasian,01/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +62694,72197,65445,PRETRIAL,Copeland,John,Clark,Male,Caucasian,01/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62725,72231,65478,PRETRIAL,ATKINS,MORRIS,NULL,Male,African-American,10/21/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +62725,72231,65478,PRETRIAL,ATKINS,MORRIS,NULL,Male,African-American,10/21/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +62725,72231,65478,PRETRIAL,ATKINS,MORRIS,NULL,Male,African-American,10/21/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +47994,72268,65514,PRETRIAL,Holland,Jamile,NULL,Male,African-American,03/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +47994,72268,65514,PRETRIAL,Holland,Jamile,NULL,Male,African-American,03/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +47994,72268,65514,PRETRIAL,Holland,Jamile,NULL,Male,African-American,03/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62732,72239,65486,PRETRIAL,Hall,Anthony,Michael,Male,African-American,10/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +62732,72239,65486,PRETRIAL,Hall,Anthony,Michael,Male,African-American,10/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +62732,72239,65486,PRETRIAL,Hall,Anthony,Michael,Male,African-American,10/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62743,72255,65501,PRETRIAL,gardner,edwin,NULL,Male,African-American,06/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +62743,72255,65501,PRETRIAL,gardner,edwin,NULL,Male,African-American,06/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +62743,72255,65501,PRETRIAL,gardner,edwin,NULL,Male,African-American,06/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62727,72234,65481,PRETRIAL,Campea,Michael,NULL,Male,Caucasian,03/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +62727,72234,65481,PRETRIAL,Campea,Michael,NULL,Male,Caucasian,03/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +62727,72234,65481,PRETRIAL,Campea,Michael,NULL,Male,Caucasian,03/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62740,72252,65498,Probation,Perez,Mateo,NULL,Male,Hispanic,08/12/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/15/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +62740,72252,65498,Probation,Perez,Mateo,NULL,Male,Hispanic,08/12/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +62740,72252,65498,Probation,Perez,Mateo,NULL,Male,Hispanic,08/12/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62737,72247,65493,Probation,levitch,daniel,NULL,Male,Caucasian,11/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +62737,72247,65493,Probation,levitch,daniel,NULL,Male,Caucasian,11/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +62737,72247,65493,Probation,levitch,daniel,NULL,Male,Caucasian,11/30/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +50585,56801,51631,PRETRIAL,Rice,Darrell,NULL,Male,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +50585,56801,51631,PRETRIAL,Rice,Darrell,NULL,Male,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.21,10,High,New,1,0 +50585,56801,51631,PRETRIAL,Rice,Darrell,NULL,Male,African-American,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62730,72237,65484,PRETRIAL,Barrows,Sanjay,NULL,Male,Caucasian,04/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +62730,72237,65484,PRETRIAL,Barrows,Sanjay,NULL,Male,Caucasian,04/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +62730,72237,65484,PRETRIAL,Barrows,Sanjay,NULL,Male,Caucasian,04/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57968,72270,65515,Probation,PROPHETE,BOB,NULL,Male,African-American,08/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +57968,72270,65515,Probation,PROPHETE,BOB,NULL,Male,African-American,08/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +57968,72270,65515,Probation,PROPHETE,BOB,NULL,Male,African-American,08/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62738,72249,65495,PRETRIAL,PUGLIESE,RICHARD,NULL,Male,Caucasian,10/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/15/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +62738,72249,65495,PRETRIAL,PUGLIESE,RICHARD,NULL,Male,Caucasian,10/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +62738,72249,65495,PRETRIAL,PUGLIESE,RICHARD,NULL,Male,Caucasian,10/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +48863,72258,65504,PRETRIAL,ANDERSON,GABRIEL,NULL,Male,African-American,08/06/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +48863,72258,65504,PRETRIAL,ANDERSON,GABRIEL,NULL,Male,African-American,08/06/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +48863,72258,65504,PRETRIAL,ANDERSON,GABRIEL,NULL,Male,African-American,08/06/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62729,72235,65482,PRETRIAL,Van,Hoang,NULL,Male,Asian,06/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/15/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +62729,72235,65482,PRETRIAL,Van,Hoang,NULL,Male,Asian,06/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +62729,72235,65482,PRETRIAL,Van,Hoang,NULL,Male,Asian,06/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62734,72242,65489,Probation,Nelson,Kelli,NULL,Female,Caucasian,04/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,2,Medium,7,Risk of Violence,-2.7,2,Low,New,1,0 +62734,72242,65489,Probation,Nelson,Kelli,NULL,Female,Caucasian,04/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +62734,72242,65489,Probation,Nelson,Kelli,NULL,Female,Caucasian,04/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62735,72244,65491,Probation,DEGEL,JACOB,Q,Male,Caucasian,10/06/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +62735,72244,65491,Probation,DEGEL,JACOB,Q,Male,Caucasian,10/06/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +62735,72244,65491,Probation,DEGEL,JACOB,Q,Male,Caucasian,10/06/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62747,72263,65509,Probation,beliles,yvonne,NULL,Female,Caucasian,12/01/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/15/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +62747,72263,65509,Probation,beliles,yvonne,NULL,Female,Caucasian,12/01/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +62747,72263,65509,Probation,beliles,yvonne,NULL,Female,Caucasian,12/01/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62724,72229,65477,PRETRIAL,Beauplan,Patrick,NULL,Male,African-American,09/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +62724,72229,65477,PRETRIAL,Beauplan,Patrick,NULL,Male,African-American,09/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +62724,72229,65477,PRETRIAL,Beauplan,Patrick,NULL,Male,African-American,09/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62728,72236,65483,PRETRIAL,LAURENT,KINBERLY,NICOLE,Female,African-American,03/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +62728,72236,65483,PRETRIAL,LAURENT,KINBERLY,NICOLE,Female,African-American,03/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +62728,72236,65483,PRETRIAL,LAURENT,KINBERLY,NICOLE,Female,African-American,03/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +18244,72243,65490,Probation,Stocker,Michael,NULL,Male,Caucasian,02/20/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +18244,72243,65490,Probation,Stocker,Michael,NULL,Male,Caucasian,02/20/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +18244,72243,65490,Probation,Stocker,Michael,NULL,Male,Caucasian,02/20/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +10819,72250,65496,Probation,Chapman,Jonathan,Ross,Male,Caucasian,09/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/15/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +10819,72250,65496,Probation,Chapman,Jonathan,Ross,Male,Caucasian,09/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +10819,72250,65496,Probation,Chapman,Jonathan,Ross,Male,Caucasian,09/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62744,72257,65503,PRETRIAL,LOPEZ,MARLON,NULL,Male,Hispanic,09/20/80,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +62744,72257,65503,PRETRIAL,LOPEZ,MARLON,NULL,Male,Hispanic,09/20/80,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +62744,72257,65503,PRETRIAL,LOPEZ,MARLON,NULL,Male,Hispanic,09/20/80,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62733,72241,65488,PRETRIAL,fashsw,joe,NULL,Male,African-American,03/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +62733,72241,65488,PRETRIAL,fashsw,joe,NULL,Male,African-American,03/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +62733,72241,65488,PRETRIAL,fashsw,joe,NULL,Male,African-American,03/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62749,72266,65512,Probation,Pitchford,Sheldrick,juan,Male,African-American,07/17/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.07,4,Low,New,1,0 +62749,72266,65512,Probation,Pitchford,Sheldrick,juan,Male,African-American,07/17/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +62749,72266,65512,Probation,Pitchford,Sheldrick,juan,Male,African-American,07/17/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62148,72245,64794,PRETRIAL,Korn,Joanna,NULL,Female,Caucasian,11/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,Copy,1,0 +62148,72245,64794,PRETRIAL,Korn,Joanna,NULL,Female,Caucasian,11/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,Copy,1,0 +62148,72245,64794,PRETRIAL,Korn,Joanna,NULL,Female,Caucasian,11/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +50553,72262,65508,PRETRIAL,Leonard,Brian,NULL,Male,Caucasian,01/06/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/15/14 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +50553,72262,65508,PRETRIAL,Leonard,Brian,NULL,Male,Caucasian,01/06/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/15/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +50553,72262,65508,PRETRIAL,Leonard,Brian,NULL,Male,Caucasian,01/06/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62736,72246,65492,Probation,Felipe,Pedro,Esteban,Male,Hispanic,04/01/90,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/15/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +62736,72246,65492,Probation,Felipe,Pedro,Esteban,Male,Hispanic,04/01/90,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +62736,72246,65492,Probation,Felipe,Pedro,Esteban,Male,Hispanic,04/01/90,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62746,72261,65507,Probation,Fontilme,Enock,NULL,Male,African-American,03/09/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +62746,72261,65507,Probation,Fontilme,Enock,NULL,Male,African-American,03/09/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +62746,72261,65507,Probation,Fontilme,Enock,NULL,Male,African-American,03/09/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62726,72233,65480,PRETRIAL,King,Latravien,Deon,Male,African-American,05/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,2,Medium,7,Risk of Violence,-2.66,2,Low,New,1,0 +62726,72233,65480,PRETRIAL,King,Latravien,Deon,Male,African-American,05/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +62726,72233,65480,PRETRIAL,King,Latravien,Deon,Male,African-American,05/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +5352,72240,65487,PRETRIAL,Rogel,Kevin,James,Male,Caucasian,11/06/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +5352,72240,65487,PRETRIAL,Rogel,Kevin,James,Male,Caucasian,11/06/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +5352,72240,65487,PRETRIAL,Rogel,Kevin,James,Male,Caucasian,11/06/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62750,72267,65513,Probation,Scandreth,Jonathan,NULL,Male,Caucasian,01/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +62750,72267,65513,Probation,Scandreth,Jonathan,NULL,Male,Caucasian,01/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +62750,72267,65513,Probation,Scandreth,Jonathan,NULL,Male,Caucasian,01/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62831,72369,65603,Probation,stanbury,delmar,NULL,Male,African-American,07/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +62831,72369,65603,Probation,stanbury,delmar,NULL,Male,African-American,07/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +62831,72369,65603,Probation,stanbury,delmar,NULL,Male,African-American,07/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62741,72253,65499,Probation,MOLLICA,THOMAS,R,Male,Caucasian,10/29/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/15/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +62741,72253,65499,Probation,MOLLICA,THOMAS,R,Male,Caucasian,10/29/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +62741,72253,65499,Probation,MOLLICA,THOMAS,R,Male,Caucasian,10/29/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62742,72254,65500,Probation,nasalski,alexander,NULL,Male,Caucasian,10/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +62742,72254,65500,Probation,nasalski,alexander,NULL,Male,Caucasian,10/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +62742,72254,65500,Probation,nasalski,alexander,NULL,Male,Caucasian,10/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +48764,72248,65494,PRETRIAL,EVANS,MICHAEL,NULL,Male,Caucasian,03/31/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.62,2,Low,New,1,0 +48764,72248,65494,PRETRIAL,EVANS,MICHAEL,NULL,Male,Caucasian,03/31/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +48764,72248,65494,PRETRIAL,EVANS,MICHAEL,NULL,Male,Caucasian,03/31/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54515,72259,65505,PRETRIAL,Constant,Donald,NULL,Male,African-American,12/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +54515,72259,65505,PRETRIAL,Constant,Donald,NULL,Male,African-American,12/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +54515,72259,65505,PRETRIAL,Constant,Donald,NULL,Male,African-American,12/15/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62731,72238,65485,PRETRIAL,Bent,Keyon,Danisha,Female,Other,05/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +62731,72238,65485,PRETRIAL,Bent,Keyon,Danisha,Female,Other,05/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +62731,72238,65485,PRETRIAL,Bent,Keyon,Danisha,Female,Other,05/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +49763,72256,65502,PRETRIAL,Foley,Trevor,NULL,Male,Caucasian,05/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +49763,72256,65502,PRETRIAL,Foley,Trevor,NULL,Male,Caucasian,05/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +49763,72256,65502,PRETRIAL,Foley,Trevor,NULL,Male,Caucasian,05/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57968,72269,60129,Probation,PROPHETE,BOB,NULL,Male,African-American,08/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +57968,72269,60129,Probation,PROPHETE,BOB,NULL,Male,African-American,08/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +57968,72269,60129,Probation,PROPHETE,BOB,NULL,Male,African-American,08/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62739,72251,65497,Probation,Welsh,Matthew,NULL,Male,Caucasian,07/06/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,New,1,0 +62739,72251,65497,Probation,Welsh,Matthew,NULL,Male,Caucasian,07/06/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.34,10,High,New,1,0 +62739,72251,65497,Probation,Welsh,Matthew,NULL,Male,Caucasian,07/06/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +15039,72230,14388,Probation,khan,sultan,NULL,Male,Asian,08/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,Copy,1,0 +15039,72230,14388,Probation,khan,sultan,NULL,Male,Asian,08/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,Copy,1,0 +15039,72230,14388,Probation,khan,sultan,NULL,Male,Asian,08/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +62748,72264,65510,PRETRIAL,Hake,Michael,NULL,Male,Caucasian,12/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +62748,72264,65510,PRETRIAL,Hake,Michael,NULL,Male,Caucasian,12/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +62748,72264,65510,PRETRIAL,Hake,Michael,NULL,Male,Caucasian,12/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62761,72285,65528,PRETRIAL,Rijos,Edmond,NULL,Male,Hispanic,06/11/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/14 0:00,4,High,7,Risk of Violence,-0.24,10,High,New,1,0 +62761,72285,65528,PRETRIAL,Rijos,Edmond,NULL,Male,Hispanic,06/11/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/14 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +62761,72285,65528,PRETRIAL,Rijos,Edmond,NULL,Male,Hispanic,06/11/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62767,72290,65532,Probation,looper,Cheryl,Ann,Female,Caucasian,10/05/69,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/16/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +62767,72290,65532,Probation,looper,Cheryl,Ann,Female,Caucasian,10/05/69,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +62767,72290,65532,Probation,looper,Cheryl,Ann,Female,Caucasian,10/05/69,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62778,72306,65545,PRETRIAL,Pierre,Edwina,NULL,Female,African-American,09/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +62778,72306,65545,PRETRIAL,Pierre,Edwina,NULL,Female,African-American,09/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +62778,72306,65545,PRETRIAL,Pierre,Edwina,NULL,Female,African-American,09/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62241,71584,64910,PRETRIAL,SANTIAGO,MARIA,NULL,Male,Caucasian,01/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/16/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +62241,71584,64910,PRETRIAL,SANTIAGO,MARIA,NULL,Male,Caucasian,01/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +62241,71584,64910,PRETRIAL,SANTIAGO,MARIA,NULL,Male,Caucasian,01/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62754,72277,65520,PRETRIAL,Freeman,Antonio,NULL,Male,African-American,06/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62754,72277,65520,PRETRIAL,Freeman,Antonio,NULL,Male,African-American,06/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +62754,72277,65520,PRETRIAL,Freeman,Antonio,NULL,Male,African-American,06/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62775,72303,65542,Probation,hanson,bryan,NULL,Male,African-American,12/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +62775,72303,65542,Probation,hanson,bryan,NULL,Male,African-American,12/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +62775,72303,65542,Probation,hanson,bryan,NULL,Male,African-American,12/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62753,72275,65518,PRETRIAL,John,Jason,NULL,Male,African-American,05/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +62753,72275,65518,PRETRIAL,John,Jason,NULL,Male,African-American,05/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +62753,72275,65518,PRETRIAL,John,Jason,NULL,Male,African-American,05/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62759,72282,65525,Probation,Lawton,PJ,NULL,Male,African-American,06/22/56,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/16/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +62759,72282,65525,Probation,Lawton,PJ,NULL,Male,African-American,06/22/56,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/16/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +62759,72282,65525,Probation,Lawton,PJ,NULL,Male,African-American,06/22/56,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62752,72274,65517,PRETRIAL,DEY,ROBERT,ALAN,Male,Caucasian,02/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,4,High,7,Risk of Violence,-1.17,8,High,New,1,0 +62752,72274,65517,PRETRIAL,DEY,ROBERT,ALAN,Male,Caucasian,02/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,4,High,8,Risk of Recidivism,0.48,9,High,New,1,0 +62752,72274,65517,PRETRIAL,DEY,ROBERT,ALAN,Male,Caucasian,02/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +48188,53683,48861,PRETRIAL,Benyard,Ronnie,NULL,Male,African-American,01/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +48188,53683,48861,PRETRIAL,Benyard,Ronnie,NULL,Male,African-American,01/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +48188,53683,48861,PRETRIAL,Benyard,Ronnie,NULL,Male,African-American,01/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62772,72295,65537,Probation,druzbik,nicholas,NULL,Male,Caucasian,04/08/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +62772,72295,65537,Probation,druzbik,nicholas,NULL,Male,Caucasian,04/08/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +62772,72295,65537,Probation,druzbik,nicholas,NULL,Male,Caucasian,04/08/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +16362,72296,65538,PRETRIAL,Cave,Christopher,NULL,Male,African-American,09/12/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +16362,72296,65538,PRETRIAL,Cave,Christopher,NULL,Male,African-American,09/12/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +16362,72296,65538,PRETRIAL,Cave,Christopher,NULL,Male,African-American,09/12/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62760,72283,65526,Probation,Janes,Daniel,NULL,Male,Caucasian,07/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +62760,72283,65526,Probation,Janes,Daniel,NULL,Male,Caucasian,07/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +62760,72283,65526,Probation,Janes,Daniel,NULL,Male,Caucasian,07/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62769,72292,65534,Probation,ramdhanie,brian,NULL,Male,Caucasian,10/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +62769,72292,65534,Probation,ramdhanie,brian,NULL,Male,Caucasian,10/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +62769,72292,65534,Probation,ramdhanie,brian,NULL,Male,Caucasian,10/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52585,72287,53917,DRRD,Auguste,Kareem,Iliones,Male,African-American,05/03/93,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,New,1,0 +52585,72287,53917,DRRD,Auguste,Kareem,Iliones,Male,African-American,05/03/93,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,6,Medium,New,1,0 +52585,72287,53917,DRRD,Auguste,Kareem,Iliones,Male,African-American,05/03/93,17,All Scales,Intake,English,Probation Violator,Probation,Single,4/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,New,1,0 +3532,72271,35977,PRETRIAL,MURRELL,WILLIAM,L,Male,African-American,01/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.51,3,Low,Copy,1,0 +3532,72271,35977,PRETRIAL,MURRELL,WILLIAM,L,Male,African-American,01/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,Copy,1,0 +3532,72271,35977,PRETRIAL,MURRELL,WILLIAM,L,Male,African-American,01/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +62755,72278,65521,PRETRIAL,ALVES-DASILVA,JOSE,NULL,Male,Caucasian,10/10/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/16/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +62755,72278,65521,PRETRIAL,ALVES-DASILVA,JOSE,NULL,Male,Caucasian,10/10/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/16/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +62755,72278,65521,PRETRIAL,ALVES-DASILVA,JOSE,NULL,Male,Caucasian,10/10/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62757,72280,65523,PRETRIAL,Smith,Shartikia,NULL,Male,African-American,10/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +62757,72280,65523,PRETRIAL,Smith,Shartikia,NULL,Male,African-American,10/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +62757,72280,65523,PRETRIAL,Smith,Shartikia,NULL,Male,African-American,10/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53484,72299,54990,Probation,Williams,Peter,NULL,Male,African-American,10/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/16/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,Copy,1,0 +53484,72299,54990,Probation,Williams,Peter,NULL,Male,African-American,10/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/16/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,Copy,1,0 +53484,72299,54990,Probation,Williams,Peter,NULL,Male,African-American,10/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +62774,72301,65541,Probation,Poole,Brian,David,Male,Caucasian,02/05/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +62774,72301,65541,Probation,Poole,Brian,David,Male,Caucasian,02/05/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +62774,72301,65541,Probation,Poole,Brian,David,Male,Caucasian,02/05/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62780,72308,65547,Probation,Crafton,Immanuel,NULL,Male,African-American,05/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +62780,72308,65547,Probation,Crafton,Immanuel,NULL,Male,African-American,05/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +62780,72308,65547,Probation,Crafton,Immanuel,NULL,Male,African-American,05/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +41572,45200,41283,PRETRIAL,Caicedo,Samantha,NULL,Female,Caucasian,11/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.12,4,Low,New,1,0 +41572,45200,41283,PRETRIAL,Caicedo,Samantha,NULL,Female,Caucasian,11/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +41572,45200,41283,PRETRIAL,Caicedo,Samantha,NULL,Female,Caucasian,11/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62770,72293,65535,Probation,Affanato,Paul,NULL,Male,Caucasian,08/31/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +62770,72293,65535,Probation,Affanato,Paul,NULL,Male,Caucasian,08/31/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +62770,72293,65535,Probation,Affanato,Paul,NULL,Male,Caucasian,08/31/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58413,72300,65540,PRETRIAL,NIEVES,VICTOR,NULL,Male,Hispanic,11/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +58413,72300,65540,PRETRIAL,NIEVES,VICTOR,NULL,Male,Hispanic,11/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +58413,72300,65540,PRETRIAL,NIEVES,VICTOR,NULL,Male,Hispanic,11/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62779,72307,65546,Probation,ANDERSON,MIKISHA,N,Female,African-American,05/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +62779,72307,65546,Probation,ANDERSON,MIKISHA,N,Female,African-American,05/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +62779,72307,65546,Probation,ANDERSON,MIKISHA,N,Female,African-American,05/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +27044,72272,26157,Probation,WILLIAMS,XAVIER,NULL,Male,African-American,01/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,4,High,7,Risk of Violence,-1.13,8,High,Copy,1,0 +27044,72272,26157,Probation,WILLIAMS,XAVIER,NULL,Male,African-American,01/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,4,High,8,Risk of Recidivism,0.91,10,High,Copy,1,0 +27044,72272,26157,Probation,WILLIAMS,XAVIER,NULL,Male,African-American,01/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,4,High,18,Risk of Failure to Appear,21,3,Low,Copy,1,0 +62763,72286,65529,Probation,Ganz,Brad,NULL,Male,Caucasian,01/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +62763,72286,65529,Probation,Ganz,Brad,NULL,Male,Caucasian,01/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +62763,72286,65529,Probation,Ganz,Brad,NULL,Male,Caucasian,01/03/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62756,72279,65522,PRETRIAL,Bell,Janessa,Denise,Female,African-American,07/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +62756,72279,65522,PRETRIAL,Bell,Janessa,Denise,Female,African-American,07/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +62756,72279,65522,PRETRIAL,Bell,Janessa,Denise,Female,African-American,07/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62764,72288,65530,Probation,collins,calvin,NULL,Male,African-American,01/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +62764,72288,65530,Probation,collins,calvin,NULL,Male,African-American,01/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +62764,72288,65530,Probation,collins,calvin,NULL,Male,African-American,01/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62777,72305,65544,PRETRIAL,Bihary,Irina,NULL,Female,Other,12/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/16/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +62777,72305,65544,PRETRIAL,Bihary,Irina,NULL,Female,Other,12/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +62777,72305,65544,PRETRIAL,Bihary,Irina,NULL,Female,Other,12/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62762,72284,65527,PRETRIAL,irizarry,megan,NULL,Female,Caucasian,10/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/16/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +62762,72284,65527,PRETRIAL,irizarry,megan,NULL,Female,Caucasian,10/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.43,2,Low,New,1,0 +62762,72284,65527,PRETRIAL,irizarry,megan,NULL,Female,Caucasian,10/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +49516,72291,65533,PRETRIAL,Kabirov,Dinar,NULL,Male,Caucasian,05/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +49516,72291,65533,PRETRIAL,Kabirov,Dinar,NULL,Male,Caucasian,05/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +49516,72291,65533,PRETRIAL,Kabirov,Dinar,NULL,Male,Caucasian,05/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +39120,72309,65548,PRETRIAL,MENDOZA,DAYTRON,NULL,Male,Caucasian,04/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/16/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +39120,72309,65548,PRETRIAL,MENDOZA,DAYTRON,NULL,Male,Caucasian,04/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +39120,72309,65548,PRETRIAL,MENDOZA,DAYTRON,NULL,Male,Caucasian,04/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62758,72281,65524,PRETRIAL,WITHERSPOON,ASHLEY,C,Female,African-American,07/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,New,1,0 +62758,72281,65524,PRETRIAL,WITHERSPOON,ASHLEY,C,Female,African-American,07/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +62758,72281,65524,PRETRIAL,WITHERSPOON,ASHLEY,C,Female,African-American,07/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +48188,72302,48861,PRETRIAL,Benyard,Ronnie,NULL,Male,African-American,01/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,4,High,7,Risk of Violence,-1.08,8,High,Copy,1,0 +48188,72302,48861,PRETRIAL,Benyard,Ronnie,NULL,Male,African-American,01/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,4,High,8,Risk of Recidivism,0.15,8,High,Copy,1,0 +48188,72302,48861,PRETRIAL,Benyard,Ronnie,NULL,Male,African-American,01/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +62751,72273,65516,PRETRIAL,DEAHORA,ENRIQUE,NULL,Male,Caucasian,12/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +62751,72273,65516,PRETRIAL,DEAHORA,ENRIQUE,NULL,Male,Caucasian,12/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +62751,72273,65516,PRETRIAL,DEAHORA,ENRIQUE,NULL,Male,Caucasian,12/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62765,72289,65531,Probation,Diamond,Gina,NULL,Female,Caucasian,04/14/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/16/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +62765,72289,65531,Probation,Diamond,Gina,NULL,Female,Caucasian,04/14/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/16/14 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +62765,72289,65531,Probation,Diamond,Gina,NULL,Female,Caucasian,04/14/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62776,72304,65543,Probation,GRIFFIN,BRENDAN,NULL,Male,African-American,03/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +62776,72304,65543,Probation,GRIFFIN,BRENDAN,NULL,Male,African-American,03/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +62776,72304,65543,Probation,GRIFFIN,BRENDAN,NULL,Male,African-American,03/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62773,72297,65539,Probation,white,kim,NULL,Female,African-American,08/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +62773,72297,65539,Probation,white,kim,NULL,Female,African-American,08/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +62773,72297,65539,Probation,white,kim,NULL,Female,African-American,08/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +9232,72276,65519,PRETRIAL,SMITH,BRENT,NULL,Male,African-American,05/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,4,High,7,Risk of Violence,-0.97,9,High,New,1,0 +9232,72276,65519,PRETRIAL,SMITH,BRENT,NULL,Male,African-American,05/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +9232,72276,65519,PRETRIAL,SMITH,BRENT,NULL,Male,African-American,05/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/16/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62782,72310,65549,PRETRIAL,davis,reginald,NULL,Male,African-American,08/13/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +62782,72310,65549,PRETRIAL,davis,reginald,NULL,Male,African-American,08/13/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,8,Risk of Recidivism,-0.88,2,Low,New,1,0 +62782,72310,65549,PRETRIAL,davis,reginald,NULL,Male,African-American,08/13/72,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/16/14 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +62804,72333,65571,Probation,Perezabreu,Oniel,NULL,Male,Hispanic,09/27/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/17/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +62804,72333,65571,Probation,Perezabreu,Oniel,NULL,Male,Hispanic,09/27/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/17/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +62804,72333,65571,Probation,Perezabreu,Oniel,NULL,Male,Hispanic,09/27/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62784,72312,65551,PRETRIAL,Robinson,Derrick,S,Male,African-American,04/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +62784,72312,65551,PRETRIAL,Robinson,Derrick,S,Male,African-American,04/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +62784,72312,65551,PRETRIAL,Robinson,Derrick,S,Male,African-American,04/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62800,72331,65569,PRETRIAL,Hamilton,Christopher,NULL,Male,African-American,05/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,4,High,7,Risk of Violence,-1.23,8,High,New,1,0 +62800,72331,65569,PRETRIAL,Hamilton,Christopher,NULL,Male,African-American,05/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,4,High,8,Risk of Recidivism,0.41,9,High,New,1,0 +62800,72331,65569,PRETRIAL,Hamilton,Christopher,NULL,Male,African-American,05/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62817,72346,65584,PRETRIAL,Cardoza,Flavio,NULL,Male,Caucasian,03/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +62817,72346,65584,PRETRIAL,Cardoza,Flavio,NULL,Male,Caucasian,03/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +62817,72346,65584,PRETRIAL,Cardoza,Flavio,NULL,Male,Caucasian,03/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62810,72339,65577,Probation,williams,milton,NULL,Male,African-American,09/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +62810,72339,65577,Probation,williams,milton,NULL,Male,African-American,09/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +62810,72339,65577,Probation,williams,milton,NULL,Male,African-American,09/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62823,72354,65590,PRETRIAL,Jonson,Chris,NULL,Male,Caucasian,01/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +62823,72354,65590,PRETRIAL,Jonson,Chris,NULL,Male,Caucasian,01/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +62823,72354,65590,PRETRIAL,Jonson,Chris,NULL,Male,Caucasian,01/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62789,72318,65557,PRETRIAL,BENAVIDES,CARMEN,NOELIA,Female,Caucasian,11/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/17/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +62789,72318,65557,PRETRIAL,BENAVIDES,CARMEN,NOELIA,Female,Caucasian,11/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/17/14 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +62789,72318,65557,PRETRIAL,BENAVIDES,CARMEN,NOELIA,Female,Caucasian,11/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62795,72325,65563,PRETRIAL,forhan,shannon,NULL,Female,Caucasian,11/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,2,Medium,7,Risk of Violence,-3.29,1,Low,New,1,0 +62795,72325,65563,PRETRIAL,forhan,shannon,NULL,Female,Caucasian,11/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.42,6,Medium,New,1,0 +62795,72325,65563,PRETRIAL,forhan,shannon,NULL,Female,Caucasian,11/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +8093,72320,65559,PRETRIAL,IBARGUEN,STEVE,NULL,Male,African-American,01/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +8093,72320,65559,PRETRIAL,IBARGUEN,STEVE,NULL,Male,African-American,01/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +8093,72320,65559,PRETRIAL,IBARGUEN,STEVE,NULL,Male,African-American,01/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62791,72323,65561,Probation,Rodriguez,Gustavo,NULL,Male,Hispanic,05/07/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/17/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +62791,72323,65561,Probation,Rodriguez,Gustavo,NULL,Male,Hispanic,05/07/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/17/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +62791,72323,65561,Probation,Rodriguez,Gustavo,NULL,Male,Hispanic,05/07/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62812,72341,65579,Probation,mckail,lovell,NULL,Male,African-American,01/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/17/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +62812,72341,65579,Probation,mckail,lovell,NULL,Male,African-American,01/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/17/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +62812,72341,65579,Probation,mckail,lovell,NULL,Male,African-American,01/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62798,72328,65566,Probation,JEMAIL,LORNA,M,Female,Hispanic,01/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/17/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +62798,72328,65566,Probation,JEMAIL,LORNA,M,Female,Hispanic,01/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/17/14 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +62798,72328,65566,Probation,JEMAIL,LORNA,M,Female,Hispanic,01/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +20399,72315,65554,PRETRIAL,obry,gerald,NULL,Male,Other,02/09/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +20399,72315,65554,PRETRIAL,obry,gerald,NULL,Male,Other,02/09/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +20399,72315,65554,PRETRIAL,obry,gerald,NULL,Male,Other,02/09/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62820,72349,65587,PRETRIAL,Johnson,Xavier,NULL,Male,African-American,10/01/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,New,1,0 +62820,72349,65587,PRETRIAL,Johnson,Xavier,NULL,Male,African-American,10/01/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-0.5,4,Low,New,1,0 +62820,72349,65587,PRETRIAL,Johnson,Xavier,NULL,Male,African-American,10/01/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62799,72330,65568,Probation,Imming,Garrett,NULL,Male,Caucasian,02/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +62799,72330,65568,Probation,Imming,Garrett,NULL,Male,Caucasian,02/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +62799,72330,65568,Probation,Imming,Garrett,NULL,Male,Caucasian,02/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62818,72347,65585,Probation,Jackson,Octavia,NULL,Female,African-American,07/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +62818,72347,65585,Probation,Jackson,Octavia,NULL,Female,African-American,07/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +62818,72347,65585,Probation,Jackson,Octavia,NULL,Female,African-American,07/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62796,72326,65564,Probation,hines,brian,NULL,Male,African-American,01/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/17/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +62796,72326,65564,Probation,hines,brian,NULL,Male,African-American,01/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/17/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +62796,72326,65564,Probation,hines,brian,NULL,Male,African-American,01/09/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58124,72321,65560,PRETRIAL,Noronha,Emily,NULL,Female,Other,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +58124,72321,65560,PRETRIAL,Noronha,Emily,NULL,Female,Other,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +58124,72321,65560,PRETRIAL,Noronha,Emily,NULL,Female,Other,09/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62786,72314,65553,PRETRIAL,Thompson,Freddie,NULL,Male,African-American,12/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.99,1,Low,New,1,0 +62786,72314,65553,PRETRIAL,Thompson,Freddie,NULL,Male,African-American,12/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +62786,72314,65553,PRETRIAL,Thompson,Freddie,NULL,Male,African-American,12/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62806,72335,65573,Probation,hart,cesar,NULL,Male,Hispanic,10/01/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/17/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +62806,72335,65573,Probation,hart,cesar,NULL,Male,Hispanic,10/01/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/17/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +62806,72335,65573,Probation,hart,cesar,NULL,Male,Hispanic,10/01/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62813,72342,65580,Probation,Alberuerque,Eric,NULL,Male,Hispanic,12/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +62813,72342,65580,Probation,Alberuerque,Eric,NULL,Male,Hispanic,12/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +62813,72342,65580,Probation,Alberuerque,Eric,NULL,Male,Hispanic,12/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62815,72344,65582,PRETRIAL,Cocaine,Edward,NULL,Male,Caucasian,03/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +62815,72344,65582,PRETRIAL,Cocaine,Edward,NULL,Male,Caucasian,03/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +62815,72344,65582,PRETRIAL,Cocaine,Edward,NULL,Male,Caucasian,03/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62794,72329,65567,PRETRIAL,Rubio,Reinaldo,NULL,Male,Caucasian,09/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,2,Medium,7,Risk of Violence,-2.64,2,Low,New,1,0 +62794,72329,65567,PRETRIAL,Rubio,Reinaldo,NULL,Male,Caucasian,09/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +62794,72329,65567,PRETRIAL,Rubio,Reinaldo,NULL,Male,Caucasian,09/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +61896,72322,64506,Probation,Gurney,Alton,NULL,Male,Caucasian,05/25/77,17,All Scales,Intake,English,Other,Probation,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +61896,72322,64506,Probation,Gurney,Alton,NULL,Male,Caucasian,05/25/77,17,All Scales,Intake,English,Other,Probation,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +61896,72322,64506,Probation,Gurney,Alton,NULL,Male,Caucasian,05/25/77,17,All Scales,Intake,English,Other,Probation,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +62814,72343,65581,PRETRIAL,Tembras,Maria,NULL,Female,Hispanic,09/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/17/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +62814,72343,65581,PRETRIAL,Tembras,Maria,NULL,Female,Hispanic,09/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/17/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +62814,72343,65581,PRETRIAL,Tembras,Maria,NULL,Female,Hispanic,09/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +28278,72350,65588,PRETRIAL,AZEMARD,DANIEL,NULL,Male,Other,08/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +28278,72350,65588,PRETRIAL,AZEMARD,DANIEL,NULL,Male,Other,08/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +28278,72350,65588,PRETRIAL,AZEMARD,DANIEL,NULL,Male,Other,08/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62809,72338,65576,PRETRIAL,TORRES,BRITTNEY,NULL,Female,Caucasian,10/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +62809,72338,65576,PRETRIAL,TORRES,BRITTNEY,NULL,Female,Caucasian,10/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +62809,72338,65576,PRETRIAL,TORRES,BRITTNEY,NULL,Female,Caucasian,10/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62805,72334,65572,Probation,Marinari,adrienne,NULL,Female,Caucasian,10/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +62805,72334,65572,Probation,Marinari,adrienne,NULL,Female,Caucasian,10/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +62805,72334,65572,Probation,Marinari,adrienne,NULL,Female,Caucasian,10/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +20781,72352,19953,PRETRIAL,ROGERS,TERRACE,NULL,Male,Caucasian,09/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,Copy,1,0 +20781,72352,19953,PRETRIAL,ROGERS,TERRACE,NULL,Male,Caucasian,09/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,Copy,1,0 +20781,72352,19953,PRETRIAL,ROGERS,TERRACE,NULL,Male,Caucasian,09/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +62787,72317,65556,PRETRIAL,BROWN,MATTHEW,EMANUEL,Male,African-American,11/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +62787,72317,65556,PRETRIAL,BROWN,MATTHEW,EMANUEL,Male,African-American,11/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +62787,72317,65556,PRETRIAL,BROWN,MATTHEW,EMANUEL,Male,African-American,11/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62785,72313,65552,PRETRIAL,Madison,Bryan,Markell,Male,African-American,10/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +62785,72313,65552,PRETRIAL,Madison,Bryan,Markell,Male,African-American,10/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +62785,72313,65552,PRETRIAL,Madison,Bryan,Markell,Male,African-American,10/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62819,72348,65586,PRETRIAL,Beckford,Wolselean,NULL,Female,African-American,10/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +62819,72348,65586,PRETRIAL,Beckford,Wolselean,NULL,Female,African-American,10/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,7,Medium,New,1,0 +62819,72348,65586,PRETRIAL,Beckford,Wolselean,NULL,Female,African-American,10/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62801,72332,65570,Probation,Rall,Daniel,NULL,Male,Hispanic,08/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +62801,72332,65570,Probation,Rall,Daniel,NULL,Male,Hispanic,08/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +62801,72332,65570,Probation,Rall,Daniel,NULL,Male,Hispanic,08/27/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62788,72316,65555,PRETRIAL,Cooley,Charmon,NULL,Male,Caucasian,06/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,2,Medium,7,Risk of Violence,-2.81,2,Low,New,1,0 +62788,72316,65555,PRETRIAL,Cooley,Charmon,NULL,Male,Caucasian,06/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +62788,72316,65555,PRETRIAL,Cooley,Charmon,NULL,Male,Caucasian,06/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62797,72327,65565,PRETRIAL,CORVINO,timothy,NULL,Male,Caucasian,05/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +62797,72327,65565,PRETRIAL,CORVINO,timothy,NULL,Male,Caucasian,05/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +62797,72327,65565,PRETRIAL,CORVINO,timothy,NULL,Male,Caucasian,05/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62808,72337,65575,PRETRIAL,SARI,RAMSEY,NULL,Male,Caucasian,11/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/17/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +62808,72337,65575,PRETRIAL,SARI,RAMSEY,NULL,Male,Caucasian,11/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/17/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +62808,72337,65575,PRETRIAL,SARI,RAMSEY,NULL,Male,Caucasian,11/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62790,72319,65558,PRETRIAL,Toliver,Darrius,NULL,Male,African-American,09/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +62790,72319,65558,PRETRIAL,Toliver,Darrius,NULL,Male,African-American,09/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +62790,72319,65558,PRETRIAL,Toliver,Darrius,NULL,Male,African-American,09/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62792,72324,65562,Probation,Garcia,Cristian,NULL,Male,Hispanic,10/10/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +62792,72324,65562,Probation,Garcia,Cristian,NULL,Male,Hispanic,10/10/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +62792,72324,65562,Probation,Garcia,Cristian,NULL,Male,Hispanic,10/10/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62783,72311,65550,PRETRIAL,Striggles,Tequila,NULL,Male,African-American,08/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +62783,72311,65550,PRETRIAL,Striggles,Tequila,NULL,Male,African-American,08/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +62783,72311,65550,PRETRIAL,Striggles,Tequila,NULL,Male,African-American,08/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62816,72345,65583,Probation,Schaefer,Jeremy,NULL,Male,Caucasian,04/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +62816,72345,65583,Probation,Schaefer,Jeremy,NULL,Male,Caucasian,04/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +62816,72345,65583,Probation,Schaefer,Jeremy,NULL,Male,Caucasian,04/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/17/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +61117,72358,65594,PRETRIAL,Babkin,Alexander,NULL,Male,Caucasian,06/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +61117,72358,65594,PRETRIAL,Babkin,Alexander,NULL,Male,Caucasian,06/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +61117,72358,65594,PRETRIAL,Babkin,Alexander,NULL,Male,Caucasian,06/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62830,72366,65600,Probation,Noriega,Michael,NULL,Male,Hispanic,04/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +62830,72366,65600,Probation,Noriega,Michael,NULL,Male,Hispanic,04/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +62830,72366,65600,Probation,Noriega,Michael,NULL,Male,Hispanic,04/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62827,72361,65597,PRETRIAL,Andrews,Bernard,Omar,Male,Other,04/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,New,1,0 +62827,72361,65597,PRETRIAL,Andrews,Bernard,Omar,Male,Other,04/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +62827,72361,65597,PRETRIAL,Andrews,Bernard,Omar,Male,Other,04/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62835,72374,65608,PRETRIAL,Mudano,Chrstopher,J,Male,Caucasian,10/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/14 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +62835,72374,65608,PRETRIAL,Mudano,Chrstopher,J,Male,Caucasian,10/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/14 0:00,4,High,8,Risk of Recidivism,1.11,10,High,New,1,0 +62835,72374,65608,PRETRIAL,Mudano,Chrstopher,J,Male,Caucasian,10/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/18/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +62200,72364,64860,PRETRIAL,Peoples,Gary,NULL,Male,African-American,07/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,Copy,1,0 +62200,72364,64860,PRETRIAL,Peoples,Gary,NULL,Male,African-American,07/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,Copy,1,0 +62200,72364,64860,PRETRIAL,Peoples,Gary,NULL,Male,African-American,07/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +62826,72359,65595,PRETRIAL,George,Donald,NULL,Male,Caucasian,01/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +62826,72359,65595,PRETRIAL,George,Donald,NULL,Male,Caucasian,01/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +62826,72359,65595,PRETRIAL,George,Donald,NULL,Male,Caucasian,01/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +49494,72355,65591,PRETRIAL,Adderley,Elizabeth,NULL,Female,Other,09/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +49494,72355,65591,PRETRIAL,Adderley,Elizabeth,NULL,Female,Other,09/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.33,7,Medium,New,1,0 +49494,72355,65591,PRETRIAL,Adderley,Elizabeth,NULL,Female,Other,09/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62834,72373,65607,Probation,mcclain,carolyn,NULL,Female,African-American,12/10/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +62834,72373,65607,Probation,mcclain,carolyn,NULL,Female,African-American,12/10/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +62834,72373,65607,Probation,mcclain,carolyn,NULL,Female,African-American,12/10/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62825,72357,65593,PRETRIAL,Vincent,Britney,NULL,Female,African-American,06/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +62825,72357,65593,PRETRIAL,Vincent,Britney,NULL,Female,African-American,06/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +62825,72357,65593,PRETRIAL,Vincent,Britney,NULL,Female,African-American,06/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62833,72371,65605,Probation,Brown,Kurt,NULL,Male,African-American,03/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +62833,72371,65605,Probation,Brown,Kurt,NULL,Male,African-American,03/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +62833,72371,65605,Probation,Brown,Kurt,NULL,Male,African-American,03/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62829,72365,65599,PRETRIAL,GLOVER,LADORIA,NULL,Female,African-American,05/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +62829,72365,65599,PRETRIAL,GLOVER,LADORIA,NULL,Female,African-American,05/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +62829,72365,65599,PRETRIAL,GLOVER,LADORIA,NULL,Female,African-American,05/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +23197,72363,22385,PRETRIAL,ANDY,VANESSA,NULL,Female,Caucasian,04/15/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,Copy,1,0 +23197,72363,22385,PRETRIAL,ANDY,VANESSA,NULL,Female,Caucasian,04/15/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,Copy,1,0 +23197,72363,22385,PRETRIAL,ANDY,VANESSA,NULL,Female,Caucasian,04/15/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +19556,72372,65606,Probation,Kasper,Robert,Bruce,Male,Caucasian,10/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +19556,72372,65606,Probation,Kasper,Robert,Bruce,Male,Caucasian,10/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +19556,72372,65606,Probation,Kasper,Robert,Bruce,Male,Caucasian,10/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +42425,72360,65596,PRETRIAL,SHOUSE,JESSICA,LADAWN,Female,Caucasian,08/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +42425,72360,65596,PRETRIAL,SHOUSE,JESSICA,LADAWN,Female,Caucasian,08/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +42425,72360,65596,PRETRIAL,SHOUSE,JESSICA,LADAWN,Female,Caucasian,08/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62824,72356,65592,PRETRIAL,Berg,wOLFGANG,NULL,Male,Caucasian,03/06/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/14 0:00,1,Low,7,Risk of Violence,-4.63,1,Low,New,1,0 +62824,72356,65592,PRETRIAL,Berg,wOLFGANG,NULL,Male,Caucasian,03/06/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/14 0:00,1,Low,8,Risk of Recidivism,-3.05,1,Low,New,1,0 +62824,72356,65592,PRETRIAL,Berg,wOLFGANG,NULL,Male,Caucasian,03/06/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/18/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62828,72362,65598,PRETRIAL,THOMAS,KARRON,NULL,Male,African-American,02/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +62828,72362,65598,PRETRIAL,THOMAS,KARRON,NULL,Male,African-American,02/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +62828,72362,65598,PRETRIAL,THOMAS,KARRON,NULL,Male,African-American,02/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/18/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62832,72370,65604,Probation,Davis,Mary,NULL,Female,African-American,08/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,2,Medium,7,Risk of Violence,-2.52,3,Low,New,1,0 +62832,72370,65604,Probation,Davis,Mary,NULL,Female,African-American,08/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +62832,72370,65604,Probation,Davis,Mary,NULL,Female,African-American,08/15/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +56946,72367,65601,PRETRIAL,Perez,Jesse,NULL,Male,Hispanic,01/30/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,2,Medium,7,Risk of Violence,-2.45,3,Low,New,1,0 +56946,72367,65601,PRETRIAL,Perez,Jesse,NULL,Male,Hispanic,01/30/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +56946,72367,65601,PRETRIAL,Perez,Jesse,NULL,Male,Hispanic,01/30/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/18/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62836,72375,65609,PRETRIAL,Payne,Kelly,NULL,Male,Caucasian,07/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62836,72375,65609,PRETRIAL,Payne,Kelly,NULL,Male,Caucasian,07/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +62836,72375,65609,PRETRIAL,Payne,Kelly,NULL,Male,Caucasian,07/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62842,72383,65616,PRETRIAL,SMITH,FREDERICK,NULL,Male,African-American,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/19/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +62842,72383,65616,PRETRIAL,SMITH,FREDERICK,NULL,Male,African-American,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/19/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +62842,72383,65616,PRETRIAL,SMITH,FREDERICK,NULL,Male,African-American,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62840,72381,65614,PRETRIAL,Worley,Dustin,NULL,Male,Caucasian,07/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +62840,72381,65614,PRETRIAL,Worley,Dustin,NULL,Male,Caucasian,07/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +62840,72381,65614,PRETRIAL,Worley,Dustin,NULL,Male,Caucasian,07/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62837,72378,65611,PRETRIAL,Cooper,Ferrell,NULL,Male,African-American,11/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +62837,72378,65611,PRETRIAL,Cooper,Ferrell,NULL,Male,African-American,11/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +62837,72378,65611,PRETRIAL,Cooper,Ferrell,NULL,Male,African-American,11/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62839,72380,65613,PRETRIAL,Baeuger,Fritzi,NULL,Male,African-American,09/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +62839,72380,65613,PRETRIAL,Baeuger,Fritzi,NULL,Male,African-American,09/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +62839,72380,65613,PRETRIAL,Baeuger,Fritzi,NULL,Male,African-American,09/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62841,72382,65615,PRETRIAL,Canovasquez,Fancheska,NULL,Female,Hispanic,04/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,4,High,7,Risk of Violence,-0.76,9,High,New,1,0 +62841,72382,65615,PRETRIAL,Canovasquez,Fancheska,NULL,Female,Hispanic,04/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +62841,72382,65615,PRETRIAL,Canovasquez,Fancheska,NULL,Female,Hispanic,04/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62838,72379,65612,PRETRIAL,Davis,Henry,NULL,Male,African-American,12/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +62838,72379,65612,PRETRIAL,Davis,Henry,NULL,Male,African-American,12/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +62838,72379,65612,PRETRIAL,Davis,Henry,NULL,Male,African-American,12/28/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62843,72384,65617,PRETRIAL,Jimenez,Yunior,NULL,Male,Hispanic,06/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +62843,72384,65617,PRETRIAL,Jimenez,Yunior,NULL,Male,Hispanic,06/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +62843,72384,65617,PRETRIAL,Jimenez,Yunior,NULL,Male,Hispanic,06/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62846,72387,65620,PRETRIAL,Lewis,Robert,NULL,Male,African-American,10/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +62846,72387,65620,PRETRIAL,Lewis,Robert,NULL,Male,African-American,10/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +62846,72387,65620,PRETRIAL,Lewis,Robert,NULL,Male,African-American,10/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62848,72389,65622,PRETRIAL,STEWART,JAMIE,BRYAN,Male,African-American,02/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/20/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +62848,72389,65622,PRETRIAL,STEWART,JAMIE,BRYAN,Male,African-American,02/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +62848,72389,65622,PRETRIAL,STEWART,JAMIE,BRYAN,Male,African-American,02/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/20/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62849,72390,65623,PRETRIAL,CLAIRMONT-FOLKES,CHANTELL,NULL,Female,African-American,02/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +62849,72390,65623,PRETRIAL,CLAIRMONT-FOLKES,CHANTELL,NULL,Female,African-American,02/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +62849,72390,65623,PRETRIAL,CLAIRMONT-FOLKES,CHANTELL,NULL,Female,African-American,02/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62851,72395,65625,PRETRIAL,Marquez,Monica,NULL,Female,Caucasian,07/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +62851,72395,65625,PRETRIAL,Marquez,Monica,NULL,Female,Caucasian,07/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +62851,72395,65625,PRETRIAL,Marquez,Monica,NULL,Female,Caucasian,07/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62844,72385,65618,PRETRIAL,WIMBER,TIMARA,STEPHANIE,Female,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +62844,72385,65618,PRETRIAL,WIMBER,TIMARA,STEPHANIE,Female,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +62844,72385,65618,PRETRIAL,WIMBER,TIMARA,STEPHANIE,Female,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +7961,72394,7541,PRETRIAL,SMART,ANTHONY,C,Male,African-American,05/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,Copy,1,0 +7961,72394,7541,PRETRIAL,SMART,ANTHONY,C,Male,African-American,05/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +7961,72394,7541,PRETRIAL,SMART,ANTHONY,C,Male,African-American,05/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +62845,72386,65619,PRETRIAL,Amaya,Hector,NULL,Male,Caucasian,02/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +62845,72386,65619,PRETRIAL,Amaya,Hector,NULL,Male,Caucasian,02/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +62845,72386,65619,PRETRIAL,Amaya,Hector,NULL,Male,Caucasian,02/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62850,72393,65624,PRETRIAL,olivera,bill,NULL,Male,Hispanic,06/18/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/14 0:00,1,Low,7,Risk of Violence,-4.33,1,Low,New,1,0 +62850,72393,65624,PRETRIAL,olivera,bill,NULL,Male,Hispanic,06/18/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/14 0:00,1,Low,8,Risk of Recidivism,-2.74,1,Low,New,1,0 +62850,72393,65624,PRETRIAL,olivera,bill,NULL,Male,Hispanic,06/18/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62847,72388,65621,PRETRIAL,JEANBAPTISTE,BEZONY,NULL,Male,African-American,06/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +62847,72388,65621,PRETRIAL,JEANBAPTISTE,BEZONY,NULL,Male,African-American,06/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +62847,72388,65621,PRETRIAL,JEANBAPTISTE,BEZONY,NULL,Male,African-American,06/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62862,72409,65637,PRETRIAL,Thiena,Antrell,NULL,Male,African-American,11/03/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.11,8,High,New,1,0 +62862,72409,65637,PRETRIAL,Thiena,Antrell,NULL,Male,African-American,11/03/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +62862,72409,65637,PRETRIAL,Thiena,Antrell,NULL,Male,African-American,11/03/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,2,Low,New,1,0 +62869,72417,65644,PRETRIAL,Fendt,Jeff,NULL,Male,Caucasian,06/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/21/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +62869,72417,65644,PRETRIAL,Fendt,Jeff,NULL,Male,Caucasian,06/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/21/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +62869,72417,65644,PRETRIAL,Fendt,Jeff,NULL,Male,Caucasian,06/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62852,72396,65626,PRETRIAL,HARRIS,MAURICE,DEMETRICE,Male,African-American,08/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +62852,72396,65626,PRETRIAL,HARRIS,MAURICE,DEMETRICE,Male,African-American,08/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +62852,72396,65626,PRETRIAL,HARRIS,MAURICE,DEMETRICE,Male,African-American,08/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +26662,72430,65657,PRETRIAL,Blake,Patrick,NULL,Male,African-American,12/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +26662,72430,65657,PRETRIAL,Blake,Patrick,NULL,Male,African-American,12/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +26662,72430,65657,PRETRIAL,Blake,Patrick,NULL,Male,African-American,12/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +4694,72425,65652,PRETRIAL,Roques,Perle,C,Male,Other,04/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/21/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +4694,72425,65652,PRETRIAL,Roques,Perle,C,Male,Other,04/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/21/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +4694,72425,65652,PRETRIAL,Roques,Perle,C,Male,Other,04/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +17520,72432,16793,PRETRIAL,BINGHAM,JIMMY,NULL,Male,African-American,11/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,Copy,1,0 +17520,72432,16793,PRETRIAL,BINGHAM,JIMMY,NULL,Male,African-American,11/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,Copy,1,0 +17520,72432,16793,PRETRIAL,BINGHAM,JIMMY,NULL,Male,African-American,11/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +62857,72404,65632,PRETRIAL,Saintsurin,Mackendy,NULL,Male,Other,11/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +62857,72404,65632,PRETRIAL,Saintsurin,Mackendy,NULL,Male,Other,11/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +62857,72404,65632,PRETRIAL,Saintsurin,Mackendy,NULL,Male,Other,11/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +62878,72433,65659,Probation,DUSTIN,WIGGINS,S,Male,African-American,12/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +62878,72433,65659,Probation,DUSTIN,WIGGINS,S,Male,African-American,12/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +62878,72433,65659,Probation,DUSTIN,WIGGINS,S,Male,African-American,12/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62855,72400,65630,PRETRIAL,DELRIO,MATTHEW,LUIS,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +62855,72400,65630,PRETRIAL,DELRIO,MATTHEW,LUIS,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +62855,72400,65630,PRETRIAL,DELRIO,MATTHEW,LUIS,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62859,72407,65635,Probation,cooley,zackary,NULL,Male,Caucasian,04/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,2,Medium,7,Risk of Violence,-2.81,2,Low,New,1,0 +62859,72407,65635,Probation,cooley,zackary,NULL,Male,Caucasian,04/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +62859,72407,65635,Probation,cooley,zackary,NULL,Male,Caucasian,04/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +42300,72414,64705,PRETRIAL,JIMENEZ,ITZAMNA,S,Male,Caucasian,11/09/92,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,New,1,0 +42300,72414,64705,PRETRIAL,JIMENEZ,ITZAMNA,S,Male,Caucasian,11/09/92,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +42300,72414,64705,PRETRIAL,JIMENEZ,ITZAMNA,S,Male,Caucasian,11/09/92,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,2,Low,New,1,0 +27585,72435,65661,PRETRIAL,angert,Ryan,patrick,Male,Caucasian,09/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +27585,72435,65661,PRETRIAL,angert,Ryan,patrick,Male,Caucasian,09/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +27585,72435,65661,PRETRIAL,angert,Ryan,patrick,Male,Caucasian,09/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62853,72398,65628,PRETRIAL,Fogle,Anthony,NULL,Male,Caucasian,12/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +62853,72398,65628,PRETRIAL,Fogle,Anthony,NULL,Male,Caucasian,12/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +62853,72398,65628,PRETRIAL,Fogle,Anthony,NULL,Male,Caucasian,12/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62876,72428,65655,PRETRIAL,ALEXANDER,DIONTE,NULL,Male,African-American,06/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,4,High,7,Risk of Violence,-0.54,10,High,New,1,0 +62876,72428,65655,PRETRIAL,ALEXANDER,DIONTE,NULL,Male,African-American,06/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +62876,72428,65655,PRETRIAL,ALEXANDER,DIONTE,NULL,Male,African-American,06/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58950,72423,65650,Probation,bradley,jeffery,NULL,Male,African-American,08/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.56,2,Low,New,1,0 +58950,72423,65650,Probation,bradley,jeffery,NULL,Male,African-American,08/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +58950,72423,65650,Probation,bradley,jeffery,NULL,Male,African-American,08/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +48976,72437,65663,PRETRIAL,Echevarria,Ivan,NULL,Male,Hispanic,03/31/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/21/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +48976,72437,65663,PRETRIAL,Echevarria,Ivan,NULL,Male,Hispanic,03/31/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/21/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +48976,72437,65663,PRETRIAL,Echevarria,Ivan,NULL,Male,Hispanic,03/31/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60060,72402,62448,PRETRIAL,Resiles,Davonte,Omar,Male,African-American,09/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,4,High,7,Risk of Violence,-0.76,9,High,Copy,1,0 +60060,72402,62448,PRETRIAL,Resiles,Davonte,Omar,Male,African-American,09/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,4,High,8,Risk of Recidivism,0.55,9,High,Copy,1,0 +60060,72402,62448,PRETRIAL,Resiles,Davonte,Omar,Male,African-American,09/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +62867,72416,65643,Probation,barnett,gentle,NULL,Male,African-American,09/13/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/21/14 0:00,1,Low,7,Risk of Violence,-4.48,1,Low,New,1,0 +62867,72416,65643,Probation,barnett,gentle,NULL,Male,African-American,09/13/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/21/14 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +62867,72416,65643,Probation,barnett,gentle,NULL,Male,African-American,09/13/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62874,72424,65651,Probation,Fleming,Kyle,William,Male,Caucasian,05/23/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +62874,72424,65651,Probation,Fleming,Kyle,William,Male,Caucasian,05/23/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +62874,72424,65651,Probation,Fleming,Kyle,William,Male,Caucasian,05/23/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62864,72411,65639,Probation,Camargo,Michael,NULL,Male,Hispanic,01/30/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +62864,72411,65639,Probation,Camargo,Michael,NULL,Male,Hispanic,01/30/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +62864,72411,65639,Probation,Camargo,Michael,NULL,Male,Hispanic,01/30/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62866,72415,65642,Probation,Moreno,jose,Manuel,Male,Hispanic,10/21/53,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/21/14 0:00,1,Low,7,Risk of Violence,-4.27,1,Low,New,1,0 +62866,72415,65642,Probation,Moreno,jose,Manuel,Male,Hispanic,10/21/53,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/21/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +62866,72415,65642,Probation,Moreno,jose,Manuel,Male,Hispanic,10/21/53,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62871,72420,65647,Probation,MARQUEZ,JOAN,NULL,Male,Hispanic,09/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +62871,72420,65647,Probation,MARQUEZ,JOAN,NULL,Male,Hispanic,09/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +62871,72420,65647,Probation,MARQUEZ,JOAN,NULL,Male,Hispanic,09/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62875,72427,65654,PRETRIAL,MEEKS,JARRETT,NULL,Male,Caucasian,02/28/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +62875,72427,65654,PRETRIAL,MEEKS,JARRETT,NULL,Male,Caucasian,02/28/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +62875,72427,65654,PRETRIAL,MEEKS,JARRETT,NULL,Male,Caucasian,02/28/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +41982,72429,65656,PRETRIAL,BarnesBlake,Roslyn,NULL,Female,African-American,09/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/21/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +41982,72429,65656,PRETRIAL,BarnesBlake,Roslyn,NULL,Female,African-American,09/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/21/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +41982,72429,65656,PRETRIAL,BarnesBlake,Roslyn,NULL,Female,African-American,09/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62854,72399,65629,PRETRIAL,Bermudez,Lori,NULL,Female,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +62854,72399,65629,PRETRIAL,Bermudez,Lori,NULL,Female,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +62854,72399,65629,PRETRIAL,Bermudez,Lori,NULL,Female,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62856,72401,65631,PRETRIAL,ROBINSON,LESLEY,NULL,Female,African-American,04/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +62856,72401,65631,PRETRIAL,ROBINSON,LESLEY,NULL,Female,African-American,04/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +62856,72401,65631,PRETRIAL,ROBINSON,LESLEY,NULL,Female,African-American,04/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62860,72408,65636,Probation,Perez,Walfare,Gabriel,Male,Hispanic,07/07/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +62860,72408,65636,Probation,Perez,Walfare,Gabriel,Male,Hispanic,07/07/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +62860,72408,65636,Probation,Perez,Walfare,Gabriel,Male,Hispanic,07/07/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62873,72422,65649,Probation,Sparkman,Leah,NULL,Female,Caucasian,02/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/21/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +62873,72422,65649,Probation,Sparkman,Leah,NULL,Female,Caucasian,02/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/21/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +62873,72422,65649,Probation,Sparkman,Leah,NULL,Female,Caucasian,02/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62880,72436,65662,Probation,Kanhai,Samaroo,NULL,Male,Other,06/21/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/21/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +62880,72436,65662,Probation,Kanhai,Samaroo,NULL,Male,Other,06/21/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/21/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +62880,72436,65662,Probation,Kanhai,Samaroo,NULL,Male,Other,06/21/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +34459,72397,65627,PRETRIAL,davis,kim,NULL,Female,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +34459,72397,65627,PRETRIAL,davis,kim,NULL,Female,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +34459,72397,65627,PRETRIAL,davis,kim,NULL,Female,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62863,72410,65638,PRETRIAL,Carpenter,Terri,Elizabeth,Female,Caucasian,12/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +62863,72410,65638,PRETRIAL,Carpenter,Terri,Elizabeth,Female,Caucasian,12/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +62863,72410,65638,PRETRIAL,Carpenter,Terri,Elizabeth,Female,Caucasian,12/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +17053,72403,16358,PRETRIAL,HOLLAND,TRODRICK,D,Male,African-American,01/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,Copy,1,0 +17053,72403,16358,PRETRIAL,HOLLAND,TRODRICK,D,Male,African-American,01/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +17053,72403,16358,PRETRIAL,HOLLAND,TRODRICK,D,Male,African-American,01/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +62881,72439,65665,Probation,GARCIA,JORGE,NULL,Male,Hispanic,01/10/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/21/14 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,New,1,0 +62881,72439,65665,Probation,GARCIA,JORGE,NULL,Male,Hispanic,01/10/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/21/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +62881,72439,65665,Probation,GARCIA,JORGE,NULL,Male,Hispanic,01/10/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +62868,72418,65645,Probation,carrodeguas,david,s,Male,Hispanic,10/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +62868,72418,65645,Probation,carrodeguas,david,s,Male,Hispanic,10/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +62868,72418,65645,Probation,carrodeguas,david,s,Male,Hispanic,10/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +62858,72405,65633,PRETRIAL,Perez,Pedro,NULL,Male,Hispanic,08/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +62858,72405,65633,PRETRIAL,Perez,Pedro,NULL,Male,Hispanic,08/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +62858,72405,65633,PRETRIAL,Perez,Pedro,NULL,Male,Hispanic,08/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62879,72434,65660,Probation,Geiss,Briian,NULL,Male,Caucasian,07/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +62879,72434,65660,Probation,Geiss,Briian,NULL,Male,Caucasian,07/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +62879,72434,65660,Probation,Geiss,Briian,NULL,Male,Caucasian,07/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62865,72413,65641,Probation,brisk,Joshua,NULL,Male,Caucasian,02/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +62865,72413,65641,Probation,brisk,Joshua,NULL,Male,Caucasian,02/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +62865,72413,65641,Probation,brisk,Joshua,NULL,Male,Caucasian,02/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52912,72426,65653,PRETRIAL,CASHES,MICHAEL,NULL,Male,Caucasian,05/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +52912,72426,65653,PRETRIAL,CASHES,MICHAEL,NULL,Male,Caucasian,05/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +52912,72426,65653,PRETRIAL,CASHES,MICHAEL,NULL,Male,Caucasian,05/04/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62895,72460,65683,Probation,Desrameaux,Udelle,NULL,Female,African-American,06/03/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +62895,72460,65683,Probation,Desrameaux,Udelle,NULL,Female,African-American,06/03/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +62895,72460,65683,Probation,Desrameaux,Udelle,NULL,Female,African-American,06/03/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +8483,72447,65672,PRETRIAL,LINDON,TAYLOR,NULL,Male,African-American,04/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +8483,72447,65672,PRETRIAL,LINDON,TAYLOR,NULL,Male,African-American,04/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +8483,72447,65672,PRETRIAL,LINDON,TAYLOR,NULL,Male,African-American,04/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +26267,72452,49588,PRETRIAL,RHOULHAC,DUANE,DONTE,Male,African-American,11/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,Copy,1,0 +26267,72452,49588,PRETRIAL,RHOULHAC,DUANE,DONTE,Male,African-American,11/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,Copy,1,0 +26267,72452,49588,PRETRIAL,RHOULHAC,DUANE,DONTE,Male,African-American,11/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +62892,72455,65679,PRETRIAL,Thomas,Jermaine,NULL,Male,African-American,08/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +62892,72455,65679,PRETRIAL,Thomas,Jermaine,NULL,Male,African-American,08/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +62892,72455,65679,PRETRIAL,Thomas,Jermaine,NULL,Male,African-American,08/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62884,72443,65668,PRETRIAL,Evans,Sean,NULL,Male,Caucasian,02/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +62884,72443,65668,PRETRIAL,Evans,Sean,NULL,Male,Caucasian,02/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +62884,72443,65668,PRETRIAL,Evans,Sean,NULL,Male,Caucasian,02/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62890,72450,65675,PRETRIAL,Clarke,Deandra,NULL,Female,Other,07/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +62890,72450,65675,PRETRIAL,Clarke,Deandra,NULL,Female,Other,07/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +62890,72450,65675,PRETRIAL,Clarke,Deandra,NULL,Female,Other,07/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +50797,72457,65681,Probation,ospina,fabian,NULL,Male,Hispanic,04/10/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +50797,72457,65681,Probation,ospina,fabian,NULL,Male,Hispanic,04/10/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +50797,72457,65681,Probation,ospina,fabian,NULL,Male,Hispanic,04/10/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62905,72471,65693,Probation,Diaz,Gladys,NULL,Female,Hispanic,10/09/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +62905,72471,65693,Probation,Diaz,Gladys,NULL,Female,Hispanic,10/09/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +62905,72471,65693,Probation,Diaz,Gladys,NULL,Female,Hispanic,10/09/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62882,72441,65666,PRETRIAL,BONILLA,JAMES,NULL,Male,Caucasian,09/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +62882,72441,65666,PRETRIAL,BONILLA,JAMES,NULL,Male,Caucasian,09/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +62882,72441,65666,PRETRIAL,BONILLA,JAMES,NULL,Male,Caucasian,09/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62886,72445,65670,PRETRIAL,Brown,Robert,NULL,Male,Other,09/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +62886,72445,65670,PRETRIAL,Brown,Robert,NULL,Male,Other,09/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +62886,72445,65670,PRETRIAL,Brown,Robert,NULL,Male,Other,09/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53008,72462,65685,PRETRIAL,Corallo,Vincent,NULL,Male,Caucasian,03/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +53008,72462,65685,PRETRIAL,Corallo,Vincent,NULL,Male,Caucasian,03/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +53008,72462,65685,PRETRIAL,Corallo,Vincent,NULL,Male,Caucasian,03/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62904,72470,65692,Probation,Bryan,Briana,Capri,Female,African-American,01/03/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +62904,72470,65692,Probation,Bryan,Briana,Capri,Female,African-American,01/03/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,4,High,8,Risk of Recidivism,0.22,8,High,New,1,0 +62904,72470,65692,Probation,Bryan,Briana,Capri,Female,African-American,01/03/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62889,72449,65674,PRETRIAL,AVELLO,ANTHONY,NULL,Male,Caucasian,12/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/22/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +62889,72449,65674,PRETRIAL,AVELLO,ANTHONY,NULL,Male,Caucasian,12/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +62889,72449,65674,PRETRIAL,AVELLO,ANTHONY,NULL,Male,Caucasian,12/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62894,72458,65682,Probation,Angeltoledo,Roberto,NULL,Male,Hispanic,03/30/87,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/22/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +62894,72458,65682,Probation,Angeltoledo,Roberto,NULL,Male,Hispanic,03/30/87,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +62894,72458,65682,Probation,Angeltoledo,Roberto,NULL,Male,Hispanic,03/30/87,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62883,72442,65667,PRETRIAL,Garraway,Anthony,M,Male,Other,05/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +62883,72442,65667,PRETRIAL,Garraway,Anthony,M,Male,Other,05/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +62883,72442,65667,PRETRIAL,Garraway,Anthony,M,Male,Other,05/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62885,72444,65669,PRETRIAL,MCCREA,KARITA,NULL,Female,African-American,11/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +62885,72444,65669,PRETRIAL,MCCREA,KARITA,NULL,Female,African-American,11/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,7,Medium,New,1,0 +62885,72444,65669,PRETRIAL,MCCREA,KARITA,NULL,Female,African-American,11/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +62898,72463,65686,Probation,Syriac,Smith,NULL,Male,African-American,10/01/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/22/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +62898,72463,65686,Probation,Syriac,Smith,NULL,Male,African-American,10/01/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/22/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +62898,72463,65686,Probation,Syriac,Smith,NULL,Male,African-American,10/01/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62900,72465,65688,PRETRIAL,Byrd,Cameshia,NULL,Female,African-American,11/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +62900,72465,65688,PRETRIAL,Byrd,Cameshia,NULL,Female,African-American,11/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +62900,72465,65688,PRETRIAL,Byrd,Cameshia,NULL,Female,African-American,11/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +62902,72467,65690,PRETRIAL,ZELSTER,DIANA,NULL,Female,Caucasian,11/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +62902,72467,65690,PRETRIAL,ZELSTER,DIANA,NULL,Female,Caucasian,11/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +62902,72467,65690,PRETRIAL,ZELSTER,DIANA,NULL,Female,Caucasian,11/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62903,72469,65691,PRETRIAL,URBINA,JOHN,NULL,Male,Caucasian,12/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +62903,72469,65691,PRETRIAL,URBINA,JOHN,NULL,Male,Caucasian,12/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +62903,72469,65691,PRETRIAL,URBINA,JOHN,NULL,Male,Caucasian,12/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62907,72474,65696,PRETRIAL,Mccloud,Herbert,NULL,Male,African-American,04/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +62907,72474,65696,PRETRIAL,Mccloud,Herbert,NULL,Male,African-American,04/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,4,High,8,Risk of Recidivism,1.11,10,High,New,1,0 +62907,72474,65696,PRETRIAL,Mccloud,Herbert,NULL,Male,African-American,04/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62887,72446,65671,PRETRIAL,Loxton,Euegene,Paul,Male,Caucasian,05/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +62887,72446,65671,PRETRIAL,Loxton,Euegene,Paul,Male,Caucasian,05/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +62887,72446,65671,PRETRIAL,Loxton,Euegene,Paul,Male,Caucasian,05/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62888,72448,65673,PRETRIAL,Delice,Johnson,NULL,Male,African-American,12/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +62888,72448,65673,PRETRIAL,Delice,Johnson,NULL,Male,African-American,12/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +62888,72448,65673,PRETRIAL,Delice,Johnson,NULL,Male,African-American,12/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53872,72440,55386,PRETRIAL,Evans,Donny,NULL,Male,Caucasian,09/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,Copy,1,0 +53872,72440,55386,PRETRIAL,Evans,Donny,NULL,Male,Caucasian,09/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,Copy,1,0 +53872,72440,55386,PRETRIAL,Evans,Donny,NULL,Male,Caucasian,09/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +62877,72453,65677,PRETRIAL,King,Kimanie,NULL,Male,African-American,01/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/14 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +62877,72453,65677,PRETRIAL,King,Kimanie,NULL,Male,African-American,01/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +62877,72453,65677,PRETRIAL,King,Kimanie,NULL,Male,African-American,01/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/22/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57425,72454,65678,PRETRIAL,augustin,austin,NULL,Male,African-American,09/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +57425,72454,65678,PRETRIAL,augustin,austin,NULL,Male,African-American,09/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +57425,72454,65678,PRETRIAL,augustin,austin,NULL,Male,African-American,09/17/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62897,72461,65684,Probation,scalzo,saverio,NULL,Male,Caucasian,02/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +62897,72461,65684,Probation,scalzo,saverio,NULL,Male,Caucasian,02/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +62897,72461,65684,Probation,scalzo,saverio,NULL,Male,Caucasian,02/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +42372,72475,65697,PRETRIAL,Denmark,Tiffany,NULL,Female,African-American,02/06/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +42372,72475,65697,PRETRIAL,Denmark,Tiffany,NULL,Female,African-American,02/06/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +42372,72475,65697,PRETRIAL,Denmark,Tiffany,NULL,Female,African-American,02/06/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62899,72464,65687,Probation,LAMPHER,PHILLIP,R,Male,Caucasian,06/26/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/22/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +62899,72464,65687,Probation,LAMPHER,PHILLIP,R,Male,Caucasian,06/26/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/22/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +62899,72464,65687,Probation,LAMPHER,PHILLIP,R,Male,Caucasian,06/26/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62891,72451,65676,PRETRIAL,Torres,Allan,NULL,Male,Caucasian,02/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +62891,72451,65676,PRETRIAL,Torres,Allan,NULL,Male,Caucasian,02/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +62891,72451,65676,PRETRIAL,Torres,Allan,NULL,Male,Caucasian,02/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/22/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +15039,72459,14388,Probation,khan,sultan,NULL,Male,Asian,08/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/22/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,Copy,1,0 +15039,72459,14388,Probation,khan,sultan,NULL,Male,Asian,08/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/22/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,Copy,1,0 +15039,72459,14388,Probation,khan,sultan,NULL,Male,Asian,08/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +62893,72456,65680,PRETRIAL,Marafino,Michael,NULL,Male,Caucasian,08/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/22/14 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +62893,72456,65680,PRETRIAL,Marafino,Michael,NULL,Male,Caucasian,08/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +62893,72456,65680,PRETRIAL,Marafino,Michael,NULL,Male,Caucasian,08/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/22/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +62910,72477,65699,PRETRIAL,Maharaj,Roshan,NULL,Male,Other,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +62910,72477,65699,PRETRIAL,Maharaj,Roshan,NULL,Male,Other,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +62910,72477,65699,PRETRIAL,Maharaj,Roshan,NULL,Male,Other,03/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62916,72485,65706,Probation,santana,david,NULL,Male,Hispanic,05/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/23/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +62916,72485,65706,Probation,santana,david,NULL,Male,Hispanic,05/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/23/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +62916,72485,65706,Probation,santana,david,NULL,Male,Hispanic,05/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30626,72498,65719,PRETRIAL,joseph,wilton,NULL,Male,African-American,06/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.91,5,Medium,New,1,0 +30626,72498,65719,PRETRIAL,joseph,wilton,NULL,Male,African-American,06/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +30626,72498,65719,PRETRIAL,joseph,wilton,NULL,Male,African-American,06/12/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62914,72482,65703,Probation,Roy,Michael,NULL,Male,Caucasian,01/20/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +62914,72482,65703,Probation,Roy,Michael,NULL,Male,Caucasian,01/20/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +62914,72482,65703,Probation,Roy,Michael,NULL,Male,Caucasian,01/20/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +62919,72490,65711,Probation,Paz,Gemblar,NULL,Male,Hispanic,06/12/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/23/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +62919,72490,65711,Probation,Paz,Gemblar,NULL,Male,Hispanic,06/12/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/23/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +62919,72490,65711,Probation,Paz,Gemblar,NULL,Male,Hispanic,06/12/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57746,72503,59888,PRETRIAL,Murphy,Morgan,NULL,Male,Caucasian,09/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,Copy,1,0 +57746,72503,59888,PRETRIAL,Murphy,Morgan,NULL,Male,Caucasian,09/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,Copy,1,0 +57746,72503,59888,PRETRIAL,Murphy,Morgan,NULL,Male,Caucasian,09/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +62925,72495,65716,Probation,Gomezarmada,Ernesto,NULL,Male,Hispanic,04/17/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/23/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +62925,72495,65716,Probation,Gomezarmada,Ernesto,NULL,Male,Hispanic,04/17/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/23/14 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +62925,72495,65716,Probation,Gomezarmada,Ernesto,NULL,Male,Hispanic,04/17/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +24379,72486,65707,PRETRIAL,Paredes,Ecduard,NULL,Male,African-American,03/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +24379,72486,65707,PRETRIAL,Paredes,Ecduard,NULL,Male,African-American,03/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +24379,72486,65707,PRETRIAL,Paredes,Ecduard,NULL,Male,African-American,03/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62921,72493,65714,PRETRIAL,Brown,Latanya,NULL,Female,African-American,09/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62921,72493,65714,PRETRIAL,Brown,Latanya,NULL,Female,African-American,09/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +62921,72493,65714,PRETRIAL,Brown,Latanya,NULL,Female,African-American,09/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62928,72500,65721,PRETRIAL,Campbell,Michael,NULL,Male,African-American,07/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +62928,72500,65721,PRETRIAL,Campbell,Michael,NULL,Male,African-American,07/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +62928,72500,65721,PRETRIAL,Campbell,Michael,NULL,Male,African-American,07/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +62911,72479,65700,PRETRIAL,Brown,John,NULL,Male,African-American,04/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +62911,72479,65700,PRETRIAL,Brown,John,NULL,Male,African-American,04/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +62911,72479,65700,PRETRIAL,Brown,John,NULL,Male,African-American,04/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +49359,72488,65709,PRETRIAL,jackson,marvin,NULL,Male,African-American,11/02/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/23/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +49359,72488,65709,PRETRIAL,jackson,marvin,NULL,Male,African-American,11/02/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/23/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +49359,72488,65709,PRETRIAL,jackson,marvin,NULL,Male,African-American,11/02/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +8950,72484,65705,PRETRIAL,WILLIAMS,ZACHARY,LASELLE,Male,African-American,03/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +8950,72484,65705,PRETRIAL,WILLIAMS,ZACHARY,LASELLE,Male,African-American,03/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +8950,72484,65705,PRETRIAL,WILLIAMS,ZACHARY,LASELLE,Male,African-American,03/05/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +62920,72491,65712,PRETRIAL,Mecklembourg,Joshua,NULL,Male,Other,10/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/23/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +62920,72491,65712,PRETRIAL,Mecklembourg,Joshua,NULL,Male,Other,10/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/23/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +62920,72491,65712,PRETRIAL,Mecklembourg,Joshua,NULL,Male,Other,10/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50724,72496,65717,PRETRIAL,Rushton,Kevin,NULL,Male,Caucasian,04/19/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +50724,72496,65717,PRETRIAL,Rushton,Kevin,NULL,Male,Caucasian,04/19/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +50724,72496,65717,PRETRIAL,Rushton,Kevin,NULL,Male,Caucasian,04/19/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62915,72483,65704,PRETRIAL,Baader,Karen,NULL,Female,Caucasian,09/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +62915,72483,65704,PRETRIAL,Baader,Karen,NULL,Female,Caucasian,09/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +62915,72483,65704,PRETRIAL,Baader,Karen,NULL,Female,Caucasian,09/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62922,72492,65713,PRETRIAL,Reid,Tiffany,Dawn,Female,African-American,02/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/14 0:00,4,High,7,Risk of Violence,-0.65,9,High,New,1,0 +62922,72492,65713,PRETRIAL,Reid,Tiffany,Dawn,Female,African-American,02/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/14 0:00,4,High,8,Risk of Recidivism,0.57,10,High,New,1,0 +62922,72492,65713,PRETRIAL,Reid,Tiffany,Dawn,Female,African-American,02/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/23/14 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +62917,72487,65708,Probation,correa,jordan,NULL,Male,Caucasian,05/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +62917,72487,65708,Probation,correa,jordan,NULL,Male,Caucasian,05/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +62917,72487,65708,Probation,correa,jordan,NULL,Male,Caucasian,05/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62927,72499,65720,Probation,Dawson,Gregg,NULL,Male,Caucasian,08/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,2,Medium,7,Risk of Violence,-2.99,1,Low,New,1,0 +62927,72499,65720,Probation,Dawson,Gregg,NULL,Male,Caucasian,08/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +62927,72499,65720,Probation,Dawson,Gregg,NULL,Male,Caucasian,08/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +61424,72501,63981,Probation,Zarate,Fabian,Ricardo,Male,Hispanic,01/16/70,17,All Scales,Intake,English,Conditional Release,Probation,Married,4/23/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +61424,72501,63981,Probation,Zarate,Fabian,Ricardo,Male,Hispanic,01/16/70,17,All Scales,Intake,English,Conditional Release,Probation,Married,4/23/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +61424,72501,63981,Probation,Zarate,Fabian,Ricardo,Male,Hispanic,01/16/70,17,All Scales,Intake,English,Conditional Release,Probation,Married,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +17667,72478,16944,PRETRIAL,King,Sonja,NULL,Female,African-American,10/27/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,Copy,1,0 +17667,72478,16944,PRETRIAL,King,Sonja,NULL,Female,African-American,10/27/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,9,High,Copy,1,0 +17667,72478,16944,PRETRIAL,King,Sonja,NULL,Female,African-American,10/27/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,Copy,1,0 +62912,72480,65701,PRETRIAL,Baldwin,Sandra,Denise,Female,African-American,11/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +62912,72480,65701,PRETRIAL,Baldwin,Sandra,Denise,Female,African-American,11/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +62912,72480,65701,PRETRIAL,Baldwin,Sandra,Denise,Female,African-American,11/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62929,72502,65722,Probation,NELFRARD,MICHAEL,NULL,Male,African-American,01/21/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +62929,72502,65722,Probation,NELFRARD,MICHAEL,NULL,Male,African-American,01/21/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +62929,72502,65722,Probation,NELFRARD,MICHAEL,NULL,Male,African-American,01/21/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62913,72481,65702,Probation,Parkinson,Tiffany,Kerisha,Female,African-American,11/29/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,New,1,0 +62913,72481,65702,Probation,Parkinson,Tiffany,Kerisha,Female,African-American,11/29/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.03,8,High,New,1,0 +62913,72481,65702,Probation,Parkinson,Tiffany,Kerisha,Female,African-American,11/29/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62923,72494,65715,PRETRIAL,gonzalez-gomez,jovan,DELRAY,Male,Caucasian,09/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +62923,72494,65715,PRETRIAL,gonzalez-gomez,jovan,DELRAY,Male,Caucasian,09/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +62923,72494,65715,PRETRIAL,gonzalez-gomez,jovan,DELRAY,Male,Caucasian,09/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62918,72489,65710,Probation,glover,tiffany,NULL,Female,African-American,11/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +62918,72489,65710,Probation,glover,tiffany,NULL,Female,African-American,11/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +62918,72489,65710,Probation,glover,tiffany,NULL,Female,African-American,11/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62909,72476,65698,PRETRIAL,RAYMOND,JEFF,NULL,Male,African-American,09/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +62909,72476,65698,PRETRIAL,RAYMOND,JEFF,NULL,Male,African-American,09/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +62909,72476,65698,PRETRIAL,RAYMOND,JEFF,NULL,Male,African-American,09/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62926,72497,65718,PRETRIAL,JAMISON,BRIAN,ROBERT,Male,Caucasian,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +62926,72497,65718,PRETRIAL,JAMISON,BRIAN,ROBERT,Male,Caucasian,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +62926,72497,65718,PRETRIAL,JAMISON,BRIAN,ROBERT,Male,Caucasian,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/23/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62938,72512,65731,DRRD,Almonte,Melvin,NULL,Male,Hispanic,12/13/77,17,All Scales,Intake,English,Post Sentence,Probation,Married,4/24/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +62938,72512,65731,DRRD,Almonte,Melvin,NULL,Male,Hispanic,12/13/77,17,All Scales,Intake,English,Post Sentence,Probation,Married,4/24/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +62938,72512,65731,DRRD,Almonte,Melvin,NULL,Male,Hispanic,12/13/77,17,All Scales,Intake,English,Post Sentence,Probation,Married,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +3849,72531,65747,PRETRIAL,PIZARRO,MICHAEL,DAVID,Male,Hispanic,03/06/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +3849,72531,65747,PRETRIAL,PIZARRO,MICHAEL,DAVID,Male,Hispanic,03/06/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +3849,72531,65747,PRETRIAL,PIZARRO,MICHAEL,DAVID,Male,Hispanic,03/06/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62963,72546,65760,PRETRIAL,Roundtree,Allen,NULL,Male,African-American,04/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +62963,72546,65760,PRETRIAL,Roundtree,Allen,NULL,Male,African-American,04/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +62963,72546,65760,PRETRIAL,Roundtree,Allen,NULL,Male,African-American,04/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62936,72510,65729,PRETRIAL,Kirfman,Troy,NULL,Male,Caucasian,08/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +62936,72510,65729,PRETRIAL,Kirfman,Troy,NULL,Male,Caucasian,08/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +62936,72510,65729,PRETRIAL,Kirfman,Troy,NULL,Male,Caucasian,08/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62954,72533,65748,PRETRIAL,Lawhorne,Angela,NULL,Female,Caucasian,02/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/24/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +62954,72533,65748,PRETRIAL,Lawhorne,Angela,NULL,Female,Caucasian,02/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +62954,72533,65748,PRETRIAL,Lawhorne,Angela,NULL,Female,Caucasian,02/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62930,72504,65723,PRETRIAL,Foulkes,Vermont,NULL,Male,African-American,09/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +62930,72504,65723,PRETRIAL,Foulkes,Vermont,NULL,Male,African-American,09/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +62930,72504,65723,PRETRIAL,Foulkes,Vermont,NULL,Male,African-American,09/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62960,72539,65754,Probation,Krause,Keith,NULL,Male,Caucasian,09/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +62960,72539,65754,Probation,Krause,Keith,NULL,Male,Caucasian,09/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +62960,72539,65754,Probation,Krause,Keith,NULL,Male,Caucasian,09/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62944,72518,65736,Probation,Richardson,Sophia,NULL,Female,African-American,04/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +62944,72518,65736,Probation,Richardson,Sophia,NULL,Female,African-American,04/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +62944,72518,65736,Probation,Richardson,Sophia,NULL,Female,African-American,04/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62950,72525,65741,Probation,totaro,george,NULL,Male,Caucasian,06/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +62950,72525,65741,Probation,totaro,george,NULL,Male,Caucasian,06/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +62950,72525,65741,Probation,totaro,george,NULL,Male,Caucasian,06/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +2462,72541,65755,PRETRIAL,PERRONE,VICTORINO,NULL,Male,Caucasian,03/13/59,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/24/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +2462,72541,65755,PRETRIAL,PERRONE,VICTORINO,NULL,Male,Caucasian,03/13/59,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +2462,72541,65755,PRETRIAL,PERRONE,VICTORINO,NULL,Male,Caucasian,03/13/59,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62946,72520,65737,Probation,SHANAHAN,BRIAN,P,Male,Caucasian,06/20/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +62946,72520,65737,Probation,SHANAHAN,BRIAN,P,Male,Caucasian,06/20/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +62946,72520,65737,Probation,SHANAHAN,BRIAN,P,Male,Caucasian,06/20/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62948,72523,65739,Probation,Maldonado,Sebastian,Lopez,Male,Hispanic,02/10/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +62948,72523,65739,Probation,Maldonado,Sebastian,Lopez,Male,Hispanic,02/10/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +62948,72523,65739,Probation,Maldonado,Sebastian,Lopez,Male,Hispanic,02/10/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62934,72508,65727,PRETRIAL,Spivey,Joshua,Trevor,Male,Caucasian,10/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +62934,72508,65727,PRETRIAL,Spivey,Joshua,Trevor,Male,Caucasian,10/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +62934,72508,65727,PRETRIAL,Spivey,Joshua,Trevor,Male,Caucasian,10/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62947,72522,65738,Probation,Solano,Cesar,Rojas,Male,Hispanic,05/13/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62947,72522,65738,Probation,Solano,Cesar,Rojas,Male,Hispanic,05/13/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +62947,72522,65738,Probation,Solano,Cesar,Rojas,Male,Hispanic,05/13/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62957,72536,65751,Probation,Pierre,Fredrick,NULL,Male,African-American,08/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +62957,72536,65751,Probation,Pierre,Fredrick,NULL,Male,African-American,08/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +62957,72536,65751,Probation,Pierre,Fredrick,NULL,Male,African-American,08/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +49817,72543,65757,PRETRIAL,HILL,SWANZETTA,NULL,Male,African-American,02/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +49817,72543,65757,PRETRIAL,HILL,SWANZETTA,NULL,Male,African-American,02/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +49817,72543,65757,PRETRIAL,HILL,SWANZETTA,NULL,Male,African-American,02/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62959,72538,65753,Probation,ben-shimon,ariel,NULL,Female,Hispanic,02/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +62959,72538,65753,Probation,ben-shimon,ariel,NULL,Female,Hispanic,02/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,9,High,New,1,0 +62959,72538,65753,Probation,ben-shimon,ariel,NULL,Female,Hispanic,02/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62955,72534,65749,PRETRIAL,Whitelow,Christian,NULL,Male,African-American,02/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +62955,72534,65749,PRETRIAL,Whitelow,Christian,NULL,Male,African-American,02/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +62955,72534,65749,PRETRIAL,Whitelow,Christian,NULL,Male,African-American,02/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62939,72513,65732,Probation,messina,salvatore,NULL,Male,Caucasian,06/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/24/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +62939,72513,65732,Probation,messina,salvatore,NULL,Male,Caucasian,06/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +62939,72513,65732,Probation,messina,salvatore,NULL,Male,Caucasian,06/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62935,72509,65728,PRETRIAL,Williams,Alain,Leclerc,Male,African-American,12/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +62935,72509,65728,PRETRIAL,Williams,Alain,Leclerc,Male,African-American,12/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +62935,72509,65728,PRETRIAL,Williams,Alain,Leclerc,Male,African-American,12/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +62931,72505,65724,PRETRIAL,Allen,Bradly,NULL,Male,Caucasian,11/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/24/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +62931,72505,65724,PRETRIAL,Allen,Bradly,NULL,Male,Caucasian,11/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +62931,72505,65724,PRETRIAL,Allen,Bradly,NULL,Male,Caucasian,11/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62953,72530,65746,PRETRIAL,Santos,Alberto,NULL,Male,Caucasian,01/14/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/24/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +62953,72530,65746,PRETRIAL,Santos,Alberto,NULL,Male,Caucasian,01/14/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +62953,72530,65746,PRETRIAL,Santos,Alberto,NULL,Male,Caucasian,01/14/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/24/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62745,72547,65761,Probation,miller,robert,NULL,Male,African-American,07/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +62745,72547,65761,Probation,miller,robert,NULL,Male,African-American,07/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +62745,72547,65761,Probation,miller,robert,NULL,Male,African-American,07/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,39,10,High,New,1,0 +62951,72526,65742,Probation,MEZQUIA,RAFAEL,NULL,Male,Hispanic,12/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +62951,72526,65742,Probation,MEZQUIA,RAFAEL,NULL,Male,Hispanic,12/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +62951,72526,65742,Probation,MEZQUIA,RAFAEL,NULL,Male,Hispanic,12/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62933,72507,65726,PRETRIAL,Grant,Givaris,Hakeem,Male,African-American,08/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +62933,72507,65726,PRETRIAL,Grant,Givaris,Hakeem,Male,African-American,08/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +62933,72507,65726,PRETRIAL,Grant,Givaris,Hakeem,Male,African-American,08/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62761,72521,65528,PRETRIAL,Rijos,Edmond,NULL,Male,Hispanic,06/11/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,4,High,7,Risk of Violence,-0.24,10,High,New,1,0 +62761,72521,65528,PRETRIAL,Rijos,Edmond,NULL,Male,Hispanic,06/11/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +62761,72521,65528,PRETRIAL,Rijos,Edmond,NULL,Male,Hispanic,06/11/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62940,72514,65733,Probation,Konegen,Robert,Herman,Male,Caucasian,09/13/64,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/24/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +62940,72514,65733,Probation,Konegen,Robert,Herman,Male,Caucasian,09/13/64,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +62940,72514,65733,Probation,Konegen,Robert,Herman,Male,Caucasian,09/13/64,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +62956,72535,65750,PRETRIAL,ford,buffie,NULL,Female,Caucasian,08/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/24/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +62956,72535,65750,PRETRIAL,ford,buffie,NULL,Female,Caucasian,08/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +62956,72535,65750,PRETRIAL,ford,buffie,NULL,Female,Caucasian,08/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/24/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +47465,72542,65756,Probation,Goldberg,James,NULL,Male,Caucasian,09/04/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +47465,72542,65756,Probation,Goldberg,James,NULL,Male,Caucasian,09/04/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +47465,72542,65756,Probation,Goldberg,James,NULL,Male,Caucasian,09/04/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +62964,72548,65762,PRETRIAL,Morales,Virgilio,NULL,Male,Caucasian,12/04/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +62964,72548,65762,PRETRIAL,Morales,Virgilio,NULL,Male,Caucasian,12/04/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +62964,72548,65762,PRETRIAL,Morales,Virgilio,NULL,Male,Caucasian,12/04/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62937,72511,65730,PRETRIAL,Gray,John,NULL,Male,Other,03/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/24/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +62937,72511,65730,PRETRIAL,Gray,John,NULL,Male,Other,03/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +62937,72511,65730,PRETRIAL,Gray,John,NULL,Male,Other,03/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +48415,72532,49103,PRETRIAL,Liatsos,Denise,NULL,Female,Caucasian,04/14/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.16,1,Low,Copy,1,0 +48415,72532,49103,PRETRIAL,Liatsos,Denise,NULL,Female,Caucasian,04/14/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,Copy,1,0 +48415,72532,49103,PRETRIAL,Liatsos,Denise,NULL,Female,Caucasian,04/14/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,4/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +62962,72545,65759,Probation,mercadoquinones,santos,NULL,Male,Hispanic,12/16/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +62962,72545,65759,Probation,mercadoquinones,santos,NULL,Male,Hispanic,12/16/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +62962,72545,65759,Probation,mercadoquinones,santos,NULL,Male,Hispanic,12/16/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62337,72519,65016,PRETRIAL,Greathouse,Earl,NULL,Male,Caucasian,10/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,Copy,1,0 +62337,72519,65016,PRETRIAL,Greathouse,Earl,NULL,Male,Caucasian,10/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,Copy,1,0 +62337,72519,65016,PRETRIAL,Greathouse,Earl,NULL,Male,Caucasian,10/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +62942,72516,65735,Probation,Moody,Jenny,NULL,Female,Caucasian,03/01/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +62942,72516,65735,Probation,Moody,Jenny,NULL,Female,Caucasian,03/01/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +62942,72516,65735,Probation,Moody,Jenny,NULL,Female,Caucasian,03/01/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62306,72527,65743,PRETRIAL,Williams,Dedrick,NULL,Male,African-American,03/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,4,High,7,Risk of Violence,-0.4,10,High,New,1,0 +62306,72527,65743,PRETRIAL,Williams,Dedrick,NULL,Male,African-American,03/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,4,High,8,Risk of Recidivism,0.73,10,High,New,1,0 +62306,72527,65743,PRETRIAL,Williams,Dedrick,NULL,Male,African-American,03/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/24/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +62932,72506,65725,PRETRIAL,Prophete,Justin,NULL,Male,African-American,12/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +62932,72506,65725,PRETRIAL,Prophete,Justin,NULL,Male,African-American,12/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +62932,72506,65725,PRETRIAL,Prophete,Justin,NULL,Male,African-American,12/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62958,72537,65752,Probation,Slavik,Joseph,NULL,Male,Caucasian,09/13/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/24/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +62958,72537,65752,Probation,Slavik,Joseph,NULL,Male,Caucasian,09/13/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/24/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +62958,72537,65752,Probation,Slavik,Joseph,NULL,Male,Caucasian,09/13/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62978,72566,65780,Probation,ROBIN,rick,NULL,Female,Caucasian,04/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62978,72566,65780,Probation,ROBIN,rick,NULL,Female,Caucasian,04/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +62978,72566,65780,Probation,ROBIN,rick,NULL,Female,Caucasian,04/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62986,72579,65791,Probation,Ali,ben,NULL,Male,African-American,07/26/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +62986,72579,65791,Probation,Ali,ben,NULL,Male,African-American,07/26/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +62986,72579,65791,Probation,Ali,ben,NULL,Male,African-American,07/26/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +56131,72568,58069,PRETRIAL,Smith,Jeremy,Bernard,Male,African-American,03/17/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +56131,72568,58069,PRETRIAL,Smith,Jeremy,Bernard,Male,African-American,03/17/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,8,Risk of Recidivism,-0.22,5,Medium,New,1,0 +56131,72568,58069,PRETRIAL,Smith,Jeremy,Bernard,Male,African-American,03/17/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62968,72553,65767,PRETRIAL,Orozco,Adriana,NULL,Male,Hispanic,04/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/25/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +62968,72553,65767,PRETRIAL,Orozco,Adriana,NULL,Male,Hispanic,04/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +62968,72553,65767,PRETRIAL,Orozco,Adriana,NULL,Male,Hispanic,04/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62989,72582,65794,PRETRIAL,Reckley,Varon,NULL,Male,African-American,01/29/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/25/14 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +62989,72582,65794,PRETRIAL,Reckley,Varon,NULL,Male,African-American,01/29/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/25/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +62989,72582,65794,PRETRIAL,Reckley,Varon,NULL,Male,African-American,01/29/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/25/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +62980,72569,65781,Probation,Rollins,forrest,NULL,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +62980,72569,65781,Probation,Rollins,forrest,NULL,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +62980,72569,65781,Probation,Rollins,forrest,NULL,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62984,72574,65786,Probation,McBride,Jerome,NULL,Male,African-American,06/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +62984,72574,65786,Probation,McBride,Jerome,NULL,Male,African-American,06/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +62984,72574,65786,Probation,McBride,Jerome,NULL,Male,African-American,06/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +20671,72576,65788,Probation,Perezrodriguez,Isai,NULL,Male,Hispanic,05/20/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/25/14 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +20671,72576,65788,Probation,Perezrodriguez,Isai,NULL,Male,Hispanic,05/20/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/25/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +20671,72576,65788,Probation,Perezrodriguez,Isai,NULL,Male,Hispanic,05/20/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62976,72563,65777,Probation,Reyes,Delmer,NULL,Male,Hispanic,07/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +62976,72563,65777,Probation,Reyes,Delmer,NULL,Male,Hispanic,07/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +62976,72563,65777,Probation,Reyes,Delmer,NULL,Male,Hispanic,07/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62979,72565,65779,PRETRIAL,Guzmanvasquez,Sergio,NULL,Male,Hispanic,01/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/25/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +62979,72565,65779,PRETRIAL,Guzmanvasquez,Sergio,NULL,Male,Hispanic,01/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +62979,72565,65779,PRETRIAL,Guzmanvasquez,Sergio,NULL,Male,Hispanic,01/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62993,72586,65798,Probation,SAKALA,KELLY,A,Female,Caucasian,08/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +62993,72586,65798,Probation,SAKALA,KELLY,A,Female,Caucasian,08/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +62993,72586,65798,Probation,SAKALA,KELLY,A,Female,Caucasian,08/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62966,72551,65765,PRETRIAL,Bruington,Ariel,NULL,Male,African-American,01/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +62966,72551,65765,PRETRIAL,Bruington,Ariel,NULL,Male,African-American,01/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +62966,72551,65765,PRETRIAL,Bruington,Ariel,NULL,Male,African-American,01/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62988,72581,65793,Probation,Scott,Allen,NULL,Male,Caucasian,12/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +62988,72581,65793,Probation,Scott,Allen,NULL,Male,Caucasian,12/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +62988,72581,65793,Probation,Scott,Allen,NULL,Male,Caucasian,12/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62970,72556,65770,PRETRIAL,Marrero,Orlando,NULL,Female,Caucasian,08/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/25/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +62970,72556,65770,PRETRIAL,Marrero,Orlando,NULL,Female,Caucasian,08/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/25/14 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +62970,72556,65770,PRETRIAL,Marrero,Orlando,NULL,Female,Caucasian,08/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54346,72577,65789,PRETRIAL,Clark,Brad,NULL,Male,Caucasian,03/14/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +54346,72577,65789,PRETRIAL,Clark,Brad,NULL,Male,Caucasian,03/14/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +54346,72577,65789,PRETRIAL,Clark,Brad,NULL,Male,Caucasian,03/14/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +62977,72564,65778,PRETRIAL,Everett,Xavia,NULL,Female,African-American,12/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +62977,72564,65778,PRETRIAL,Everett,Xavia,NULL,Female,African-American,12/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,8,High,New,1,0 +62977,72564,65778,PRETRIAL,Everett,Xavia,NULL,Female,African-American,12/16/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62967,72552,65766,PRETRIAL,Campbell,Daniel,NULL,Male,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +62967,72552,65766,PRETRIAL,Campbell,Daniel,NULL,Male,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +62967,72552,65766,PRETRIAL,Campbell,Daniel,NULL,Male,African-American,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62972,72559,65773,Probation,arian,matias,NULL,Male,Caucasian,04/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +62972,72559,65773,Probation,arian,matias,NULL,Male,Caucasian,04/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +62972,72559,65773,Probation,arian,matias,NULL,Male,Caucasian,04/06/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62969,72555,65769,PRETRIAL,Blanc,Jason,NULL,Male,African-American,01/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +62969,72555,65769,PRETRIAL,Blanc,Jason,NULL,Male,African-American,01/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +62969,72555,65769,PRETRIAL,Blanc,Jason,NULL,Male,African-American,01/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62983,72573,65785,PRETRIAL,GONZALEZ,LILLIANA,NULL,Female,Caucasian,09/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/25/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +62983,72573,65785,PRETRIAL,GONZALEZ,LILLIANA,NULL,Female,Caucasian,09/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,New,1,0 +62983,72573,65785,PRETRIAL,GONZALEZ,LILLIANA,NULL,Female,Caucasian,09/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62965,72550,65764,PRETRIAL,McCurdy,Jahsaiah,NULL,Male,African-American,06/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +62965,72550,65764,PRETRIAL,McCurdy,Jahsaiah,NULL,Male,African-American,06/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +62965,72550,65764,PRETRIAL,McCurdy,Jahsaiah,NULL,Male,African-American,06/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +62971,72557,65771,PRETRIAL,Hosan,Mohammed,NULL,Male,Other,02/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/25/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +62971,72557,65771,PRETRIAL,Hosan,Mohammed,NULL,Male,Other,02/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +62971,72557,65771,PRETRIAL,Hosan,Mohammed,NULL,Male,Other,02/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62982,72571,65783,Probation,Sherman,Daniel,NULL,Male,Caucasian,11/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +62982,72571,65783,Probation,Sherman,Daniel,NULL,Male,Caucasian,11/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +62982,72571,65783,Probation,Sherman,Daniel,NULL,Male,Caucasian,11/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +62985,72578,65790,Probation,VARGASMORENO,NICOLE,A,Female,Hispanic,09/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +62985,72578,65790,Probation,VARGASMORENO,NICOLE,A,Female,Hispanic,09/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,New,1,0 +62985,72578,65790,Probation,VARGASMORENO,NICOLE,A,Female,Hispanic,09/02/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62987,72580,65792,Probation,Pearson,Lauren,NULL,Female,Caucasian,09/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +62987,72580,65792,Probation,Pearson,Lauren,NULL,Female,Caucasian,09/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +62987,72580,65792,Probation,Pearson,Lauren,NULL,Female,Caucasian,09/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62981,72570,65782,Probation,Leyvaperez,Richar,NULL,Male,Hispanic,04/13/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/25/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +62981,72570,65782,Probation,Leyvaperez,Richar,NULL,Male,Hispanic,04/13/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +62981,72570,65782,Probation,Leyvaperez,Richar,NULL,Male,Hispanic,04/13/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56362,72549,65763,PRETRIAL,Foy,Rhoneisha,NULL,Female,African-American,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +56362,72549,65763,PRETRIAL,Foy,Rhoneisha,NULL,Female,African-American,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +56362,72549,65763,PRETRIAL,Foy,Rhoneisha,NULL,Female,African-American,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62990,72583,65795,Probation,george,stephanie,NULL,Female,Caucasian,05/21/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +62990,72583,65795,Probation,george,stephanie,NULL,Female,Caucasian,05/21/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/14 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +62990,72583,65795,Probation,george,stephanie,NULL,Female,Caucasian,05/21/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/25/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62975,72562,65776,Probation,GONZALEZTORRES,AMED,NULL,Male,Hispanic,10/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +62975,72562,65776,Probation,GONZALEZTORRES,AMED,NULL,Male,Hispanic,10/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +62975,72562,65776,Probation,GONZALEZTORRES,AMED,NULL,Male,Hispanic,10/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/25/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +13192,72575,65787,PRETRIAL,KOFFLER,KRISTINE,MARION,Female,Caucasian,07/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +13192,72575,65787,PRETRIAL,KOFFLER,KRISTINE,MARION,Female,Caucasian,07/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,9,High,New,1,0 +13192,72575,65787,PRETRIAL,KOFFLER,KRISTINE,MARION,Female,Caucasian,07/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +53334,72554,65768,PRETRIAL,Hilliard,Xavier,NULL,Male,African-American,05/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,New,1,0 +53334,72554,65768,PRETRIAL,Hilliard,Xavier,NULL,Male,African-American,05/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +53334,72554,65768,PRETRIAL,Hilliard,Xavier,NULL,Male,African-American,05/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59581,72567,61936,PRETRIAL,Zambrano,Stephen,NULL,Male,Hispanic,09/03/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.05,8,High,New,1,0 +59581,72567,61936,PRETRIAL,Zambrano,Stephen,NULL,Male,Hispanic,09/03/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,6,Medium,New,1,0 +59581,72567,61936,PRETRIAL,Zambrano,Stephen,NULL,Male,Hispanic,09/03/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,4/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63006,72604,65814,PRETRIAL,Leefmans,Candyce,NULL,Female,Caucasian,08/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +63006,72604,65814,PRETRIAL,Leefmans,Candyce,NULL,Female,Caucasian,08/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +63006,72604,65814,PRETRIAL,Leefmans,Candyce,NULL,Female,Caucasian,08/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +46002,72596,46350,PRETRIAL,Simmons,Jeffery,NULL,Male,African-American,10/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,4,High,7,Risk of Violence,-0.22,10,High,Copy,1,0 +46002,72596,46350,PRETRIAL,Simmons,Jeffery,NULL,Male,African-American,10/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,4,High,8,Risk of Recidivism,0.83,10,High,Copy,1,0 +46002,72596,46350,PRETRIAL,Simmons,Jeffery,NULL,Male,African-American,10/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +28316,72588,65800,PRETRIAL,Lamkin,William,NULL,Male,Caucasian,06/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/26/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +28316,72588,65800,PRETRIAL,Lamkin,William,NULL,Male,Caucasian,06/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +28316,72588,65800,PRETRIAL,Lamkin,William,NULL,Male,Caucasian,06/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,4/26/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62997,72591,65803,PRETRIAL,Jones,Tiarra,NULL,Female,African-American,11/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +62997,72591,65803,PRETRIAL,Jones,Tiarra,NULL,Female,African-American,11/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +62997,72591,65803,PRETRIAL,Jones,Tiarra,NULL,Female,African-American,11/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63001,72599,65809,PRETRIAL,MCMILLAN,BRUCE,NULL,Male,African-American,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/26/14 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +63001,72599,65809,PRETRIAL,MCMILLAN,BRUCE,NULL,Male,African-American,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/26/14 0:00,4,High,8,Risk of Recidivism,0.2,8,High,New,1,0 +63001,72599,65809,PRETRIAL,MCMILLAN,BRUCE,NULL,Male,African-American,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/26/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63003,72601,65811,PRETRIAL,Robinson,Andre,NULL,Male,African-American,10/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +63003,72601,65811,PRETRIAL,Robinson,Andre,NULL,Male,African-American,10/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +63003,72601,65811,PRETRIAL,Robinson,Andre,NULL,Male,African-American,10/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +4579,72594,65805,PRETRIAL,PORTER,REGINALD,NULL,Male,African-American,06/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +4579,72594,65805,PRETRIAL,PORTER,REGINALD,NULL,Male,African-American,06/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +4579,72594,65805,PRETRIAL,PORTER,REGINALD,NULL,Male,African-American,06/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63004,72602,65812,PRETRIAL,YOUNG,THOMAS,NULL,Male,African-American,01/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +63004,72602,65812,PRETRIAL,YOUNG,THOMAS,NULL,Male,African-American,01/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +63004,72602,65812,PRETRIAL,YOUNG,THOMAS,NULL,Male,African-American,01/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63000,72598,65808,PRETRIAL,Nance,Eujania,NULL,Male,African-American,11/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +63000,72598,65808,PRETRIAL,Nance,Eujania,NULL,Male,African-American,11/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +63000,72598,65808,PRETRIAL,Nance,Eujania,NULL,Male,African-American,11/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +34539,72593,65804,Probation,LOGAN,KAZEMBE,ATIBA,Male,African-American,05/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +34539,72593,65804,Probation,LOGAN,KAZEMBE,ATIBA,Male,African-American,05/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,4,High,8,Risk of Recidivism,0.86,10,High,New,1,0 +34539,72593,65804,Probation,LOGAN,KAZEMBE,ATIBA,Male,African-American,05/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,4,High,18,Risk of Failure to Appear,35,10,High,New,1,0 +63002,72600,65810,PRETRIAL,WALKER,SAMUEL,NULL,Male,African-American,09/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.49,3,Low,New,1,0 +63002,72600,65810,PRETRIAL,WALKER,SAMUEL,NULL,Male,African-American,09/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +63002,72600,65810,PRETRIAL,WALKER,SAMUEL,NULL,Male,African-American,09/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63005,72603,65813,PRETRIAL,FRANK,LAWRENCE,R,Male,Caucasian,04/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/26/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +63005,72603,65813,PRETRIAL,FRANK,LAWRENCE,R,Male,Caucasian,04/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/26/14 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +63005,72603,65813,PRETRIAL,FRANK,LAWRENCE,R,Male,Caucasian,04/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62998,72595,65806,PRETRIAL,WATT,DELMARIO,RICO,Male,African-American,12/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/26/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +62998,72595,65806,PRETRIAL,WATT,DELMARIO,RICO,Male,African-American,12/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/26/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +62998,72595,65806,PRETRIAL,WATT,DELMARIO,RICO,Male,African-American,12/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/26/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62999,72597,65807,PRETRIAL,CANTEEN,ACIE,ALPHONSOE,Male,African-American,01/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +62999,72597,65807,PRETRIAL,CANTEEN,ACIE,ALPHONSOE,Male,African-American,01/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +62999,72597,65807,PRETRIAL,CANTEEN,ACIE,ALPHONSOE,Male,African-American,01/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62995,72589,65801,PRETRIAL,Bueno,John,NULL,Male,Caucasian,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +62995,72589,65801,PRETRIAL,Bueno,John,NULL,Male,Caucasian,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +62995,72589,65801,PRETRIAL,Bueno,John,NULL,Male,Caucasian,01/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62996,72590,65802,PRETRIAL,Marquez,Stephanie,NULL,Female,Caucasian,08/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +62996,72590,65802,PRETRIAL,Marquez,Stephanie,NULL,Female,Caucasian,08/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +62996,72590,65802,PRETRIAL,Marquez,Stephanie,NULL,Female,Caucasian,08/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +4316,72592,4021,PRETRIAL,JOHNSON,SEAN,EDWARD,Male,Caucasian,08/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,Copy,1,0 +4316,72592,4021,PRETRIAL,JOHNSON,SEAN,EDWARD,Male,Caucasian,08/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,Copy,1,0 +4316,72592,4021,PRETRIAL,JOHNSON,SEAN,EDWARD,Male,Caucasian,08/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +62994,72587,65799,PRETRIAL,Lebrun,Obinson,NULL,Male,African-American,07/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +62994,72587,65799,PRETRIAL,Lebrun,Obinson,NULL,Male,African-American,07/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +62994,72587,65799,PRETRIAL,Lebrun,Obinson,NULL,Male,African-American,07/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/26/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63007,72605,65815,PRETRIAL,Williams,Marvin,Andrae,Male,African-American,03/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +63007,72605,65815,PRETRIAL,Williams,Marvin,Andrae,Male,African-American,03/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +63007,72605,65815,PRETRIAL,Williams,Marvin,Andrae,Male,African-American,03/11/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63014,72613,65822,PRETRIAL,Wright,David,A,Male,African-American,06/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +63014,72613,65822,PRETRIAL,Wright,David,A,Male,African-American,06/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +63014,72613,65822,PRETRIAL,Wright,David,A,Male,African-American,06/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63012,72611,65820,PRETRIAL,HERRON,DONNIE,SAM,Male,Caucasian,12/07/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/27/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +63012,72611,65820,PRETRIAL,HERRON,DONNIE,SAM,Male,Caucasian,12/07/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/27/14 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +63012,72611,65820,PRETRIAL,HERRON,DONNIE,SAM,Male,Caucasian,12/07/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,4/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63011,72610,65819,PRETRIAL,Gibson,Cilfford,NULL,Male,African-American,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +63011,72610,65819,PRETRIAL,Gibson,Cilfford,NULL,Male,African-American,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +63011,72610,65819,PRETRIAL,Gibson,Cilfford,NULL,Male,African-American,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63008,72607,65816,PRETRIAL,OWENS,ARLBREY,C,Male,African-American,07/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +63008,72607,65816,PRETRIAL,OWENS,ARLBREY,C,Male,African-American,07/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +63008,72607,65816,PRETRIAL,OWENS,ARLBREY,C,Male,African-American,07/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +45115,72606,45312,PRETRIAL,Mays-Burton,Jacoriea,Nikki,Male,African-American,11/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,Copy,1,0 +45115,72606,45312,PRETRIAL,Mays-Burton,Jacoriea,Nikki,Male,African-American,11/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,Copy,1,0 +45115,72606,45312,PRETRIAL,Mays-Burton,Jacoriea,Nikki,Male,African-American,11/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +63009,72608,65817,PRETRIAL,NTI,RASHAWN,AGYEMANG,Male,African-American,01/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +63009,72608,65817,PRETRIAL,NTI,RASHAWN,AGYEMANG,Male,African-American,01/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +63009,72608,65817,PRETRIAL,NTI,RASHAWN,AGYEMANG,Male,African-American,01/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63010,72609,65818,PRETRIAL,Gethers,Irvin,Jerome,Male,African-American,04/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +63010,72609,65818,PRETRIAL,Gethers,Irvin,Jerome,Male,African-American,04/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +63010,72609,65818,PRETRIAL,Gethers,Irvin,Jerome,Male,African-American,04/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63013,72612,65821,PRETRIAL,Marshall,Carlton,Trae,Male,African-American,08/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +63013,72612,65821,PRETRIAL,Marshall,Carlton,Trae,Male,African-American,08/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +63013,72612,65821,PRETRIAL,Marshall,Carlton,Trae,Male,African-American,08/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/27/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63038,72646,65850,DRRD,Newman,Joshua,NULL,Male,Caucasian,07/17/92,17,All Scales,Intake,English,Post Sentence,Probation,Separated,4/28/14 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +63038,72646,65850,DRRD,Newman,Joshua,NULL,Male,Caucasian,07/17/92,17,All Scales,Intake,English,Post Sentence,Probation,Separated,4/28/14 0:00,1,Low,8,Risk of Recidivism,-0.6,3,Low,New,1,0 +63038,72646,65850,DRRD,Newman,Joshua,NULL,Male,Caucasian,07/17/92,17,All Scales,Intake,English,Post Sentence,Probation,Separated,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +24560,72648,65852,PRETRIAL,JOHNSON,ANTHONY,NULL,Male,African-American,12/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +24560,72648,65852,PRETRIAL,JOHNSON,ANTHONY,NULL,Male,African-American,12/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +24560,72648,65852,PRETRIAL,JOHNSON,ANTHONY,NULL,Male,African-American,12/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63029,72633,65838,Probation,Yaniv,Liran,NULL,Male,Caucasian,05/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +63029,72633,65838,Probation,Yaniv,Liran,NULL,Male,Caucasian,05/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +63029,72633,65838,Probation,Yaniv,Liran,NULL,Male,Caucasian,05/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +44921,72640,64241,Probation,whitehead,travis,NULL,Male,African-American,05/03/86,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/28/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +44921,72640,64241,Probation,whitehead,travis,NULL,Male,African-American,05/03/86,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,6,Medium,New,1,0 +44921,72640,64241,Probation,whitehead,travis,NULL,Male,African-American,05/03/86,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/28/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63025,72625,65833,Probation,Samaroo,Andrew,Daniel,Male,African-American,12/11/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/28/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +63025,72625,65833,Probation,Samaroo,Andrew,Daniel,Male,African-American,12/11/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +63025,72625,65833,Probation,Samaroo,Andrew,Daniel,Male,African-American,12/11/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/28/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +15360,72638,65843,PRETRIAL,LENCIONI,RICHARD,J,Male,Caucasian,10/12/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.48,3,Low,New,1,0 +15360,72638,65843,PRETRIAL,LENCIONI,RICHARD,J,Male,Caucasian,10/12/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +15360,72638,65843,PRETRIAL,LENCIONI,RICHARD,J,Male,Caucasian,10/12/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +63028,72630,65836,Probation,MORANCY,OSWALD,NULL,Male,African-American,02/11/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +63028,72630,65836,Probation,MORANCY,OSWALD,NULL,Male,African-American,02/11/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +63028,72630,65836,Probation,MORANCY,OSWALD,NULL,Male,African-American,02/11/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63017,72617,65826,PRETRIAL,Caicedo,Andres,Miguel,Male,Hispanic,02/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +63017,72617,65826,PRETRIAL,Caicedo,Andres,Miguel,Male,Hispanic,02/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +63017,72617,65826,PRETRIAL,Caicedo,Andres,Miguel,Male,Hispanic,02/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63042,72651,65855,Probation,Gramer,Maria,NULL,Female,Hispanic,03/01/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/28/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +63042,72651,65855,Probation,Gramer,Maria,NULL,Female,Hispanic,03/01/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/28/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +63042,72651,65855,Probation,Gramer,Maria,NULL,Female,Hispanic,03/01/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63022,72622,65830,PRETRIAL,Rivera,Jose,NULL,Male,Caucasian,09/08/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +63022,72622,65830,PRETRIAL,Rivera,Jose,NULL,Male,Caucasian,09/08/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +63022,72622,65830,PRETRIAL,Rivera,Jose,NULL,Male,Caucasian,09/08/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +57267,72636,65841,Probation,Woodward,Fred,NULL,Male,Caucasian,12/22/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.44,3,Low,New,1,0 +57267,72636,65841,Probation,Woodward,Fred,NULL,Male,Caucasian,12/22/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.74,10,High,New,1,0 +57267,72636,65841,Probation,Woodward,Fred,NULL,Male,Caucasian,12/22/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,38,10,High,New,1,0 +59089,72643,65847,PRETRIAL,Bentley,Travon,NULL,Male,African-American,11/11/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +59089,72643,65847,PRETRIAL,Bentley,Travon,NULL,Male,African-American,11/11/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +59089,72643,65847,PRETRIAL,Bentley,Travon,NULL,Male,African-American,11/11/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63040,72650,65854,Probation,thomas,patricia,NULL,Female,African-American,10/01/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +63040,72650,65854,Probation,thomas,patricia,NULL,Female,African-American,10/01/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +63040,72650,65854,Probation,thomas,patricia,NULL,Female,African-American,10/01/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63019,72620,65828,PRETRIAL,Diaz,Joshua,NULL,Male,Hispanic,03/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +63019,72620,65828,PRETRIAL,Diaz,Joshua,NULL,Male,Hispanic,03/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +63019,72620,65828,PRETRIAL,Diaz,Joshua,NULL,Male,Hispanic,03/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63024,72624,65832,PRETRIAL,Marseille,Elda,NULL,Female,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +63024,72624,65832,PRETRIAL,Marseille,Elda,NULL,Female,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +63024,72624,65832,PRETRIAL,Marseille,Elda,NULL,Female,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +39409,72641,65845,PRETRIAL,Haynes,Lashontrell,Shakura,Male,African-American,03/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +39409,72641,65845,PRETRIAL,Haynes,Lashontrell,Shakura,Male,African-American,03/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +39409,72641,65845,PRETRIAL,Haynes,Lashontrell,Shakura,Male,African-American,03/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63016,72615,65824,PRETRIAL,PAZ,JERIMEY,NELO,Male,Hispanic,11/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +63016,72615,65824,PRETRIAL,PAZ,JERIMEY,NELO,Male,Hispanic,11/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +63016,72615,65824,PRETRIAL,PAZ,JERIMEY,NELO,Male,Hispanic,11/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63037,72645,65849,Probation,mohorn,douglas,e,Male,African-American,10/29/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +63037,72645,65849,Probation,mohorn,douglas,e,Male,African-American,10/29/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.93,10,High,New,1,0 +63037,72645,65849,Probation,mohorn,douglas,e,Male,African-American,10/29/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63020,72621,65829,PRETRIAL,RAZUMOVSKIY,ALEXANDER,NULL,Male,Caucasian,02/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/28/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +63020,72621,65829,PRETRIAL,RAZUMOVSKIY,ALEXANDER,NULL,Male,Caucasian,02/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/28/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +63020,72621,65829,PRETRIAL,RAZUMOVSKIY,ALEXANDER,NULL,Male,Caucasian,02/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63015,72614,65823,PRETRIAL,Fava,Donald,NULL,Male,African-American,06/01/45,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-4.49,1,Low,New,1,0 +63015,72614,65823,PRETRIAL,Fava,Donald,NULL,Male,African-American,06/01/45,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-3.04,1,Low,New,1,0 +63015,72614,65823,PRETRIAL,Fava,Donald,NULL,Male,African-American,06/01/45,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63030,72635,65840,Probation,Lopez,Alex,NULL,Male,Hispanic,02/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +63030,72635,65840,Probation,Lopez,Alex,NULL,Male,Hispanic,02/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +63030,72635,65840,Probation,Lopez,Alex,NULL,Male,Hispanic,02/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63034,72642,65846,Probation,MONTGOMERY,PATRICE,NULL,Female,African-American,02/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +63034,72642,65846,Probation,MONTGOMERY,PATRICE,NULL,Female,African-American,02/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +63034,72642,65846,Probation,MONTGOMERY,PATRICE,NULL,Female,African-American,02/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +63035,72644,65848,PRETRIAL,Times,Casey,NULL,Male,African-American,01/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +63035,72644,65848,PRETRIAL,Times,Casey,NULL,Male,African-American,01/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +63035,72644,65848,PRETRIAL,Times,Casey,NULL,Male,African-American,01/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +63041,72649,65853,Probation,Capriola,Courtney,NULL,Female,Caucasian,12/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +63041,72649,65853,Probation,Capriola,Courtney,NULL,Female,Caucasian,12/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +63041,72649,65853,Probation,Capriola,Courtney,NULL,Female,Caucasian,12/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +63018,72619,65827,PRETRIAL,Stucki,Michael,NULL,Male,Caucasian,11/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +63018,72619,65827,PRETRIAL,Stucki,Michael,NULL,Male,Caucasian,11/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +63018,72619,65827,PRETRIAL,Stucki,Michael,NULL,Male,Caucasian,11/29/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63027,72628,65835,Probation,Engel,Aneurys,NULL,Male,Hispanic,01/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +63027,72628,65835,Probation,Engel,Aneurys,NULL,Male,Hispanic,01/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +63027,72628,65835,Probation,Engel,Aneurys,NULL,Male,Hispanic,01/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +32696,72616,65825,PRETRIAL,Cunningham,Duane,NULL,Male,African-American,01/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +32696,72616,65825,PRETRIAL,Cunningham,Duane,NULL,Male,African-American,01/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +32696,72616,65825,PRETRIAL,Cunningham,Duane,NULL,Male,African-American,01/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63023,72623,65831,Probation,Souffrant,Pierre,NULL,Male,African-American,12/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/28/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +63023,72623,65831,Probation,Souffrant,Pierre,NULL,Male,African-American,12/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/28/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +63023,72623,65831,Probation,Souffrant,Pierre,NULL,Male,African-American,12/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63032,72637,65842,PRETRIAL,Theodule,Patrice,NULL,Male,African-American,08/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/28/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +63032,72637,65842,PRETRIAL,Theodule,Patrice,NULL,Male,African-American,08/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/28/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +63032,72637,65842,PRETRIAL,Theodule,Patrice,NULL,Male,African-American,08/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +25315,72631,65837,PRETRIAL,BLUE,NIESHA,NULL,Female,African-American,10/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,4,High,7,Risk of Violence,-0.48,10,High,New,1,0 +25315,72631,65837,PRETRIAL,BLUE,NIESHA,NULL,Female,African-American,10/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,4,High,8,Risk of Recidivism,0.46,10,High,New,1,0 +25315,72631,65837,PRETRIAL,BLUE,NIESHA,NULL,Female,African-American,10/23/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,4,High,18,Risk of Failure to Appear,29,9,High,New,1,0 +53241,72618,54694,Probation,mccray,rodney,NULL,Male,African-American,07/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,Copy,1,0 +53241,72618,54694,Probation,mccray,rodney,NULL,Male,African-American,07/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,Copy,1,0 +53241,72618,54694,Probation,mccray,rodney,NULL,Male,African-American,07/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/28/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +63033,72639,65844,Probation,Cardenas,Ana,NULL,Female,Hispanic,07/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +63033,72639,65844,Probation,Cardenas,Ana,NULL,Female,Hispanic,07/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +63033,72639,65844,Probation,Cardenas,Ana,NULL,Female,Hispanic,07/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63026,72626,65834,PRETRIAL,DIAZ,SIMON,NULL,Male,Hispanic,09/28/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/28/14 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +63026,72626,65834,PRETRIAL,DIAZ,SIMON,NULL,Male,Hispanic,09/28/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/28/14 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +63026,72626,65834,PRETRIAL,DIAZ,SIMON,NULL,Male,Hispanic,09/28/46,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63031,72634,65839,PRETRIAL,Mcmullian,Scott,J,Male,Caucasian,02/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/28/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +63031,72634,65839,PRETRIAL,Mcmullian,Scott,J,Male,Caucasian,02/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/28/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +63031,72634,65839,PRETRIAL,Mcmullian,Scott,J,Male,Caucasian,02/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/28/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +23508,72655,65858,Probation,simon,mark,NULL,Male,African-American,08/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +23508,72655,65858,Probation,simon,mark,NULL,Male,African-American,08/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +23508,72655,65858,Probation,simon,mark,NULL,Male,African-American,08/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53821,72673,55316,PRETRIAL,Talley,Bret,NULL,Male,African-American,08/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,Copy,1,0 +53821,72673,55316,PRETRIAL,Talley,Bret,NULL,Male,African-American,08/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,Copy,1,0 +53821,72673,55316,PRETRIAL,Talley,Bret,NULL,Male,African-American,08/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +63051,72660,65863,PRETRIAL,Penton,Robert,NULL,Male,Caucasian,12/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/29/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +63051,72660,65863,PRETRIAL,Penton,Robert,NULL,Male,Caucasian,12/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +63051,72660,65863,PRETRIAL,Penton,Robert,NULL,Male,Caucasian,12/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63074,72689,65888,Probation,Sanchez,Alvaro,Agusto,Male,Hispanic,02/20/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +63074,72689,65888,Probation,Sanchez,Alvaro,Agusto,Male,Hispanic,02/20/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +63074,72689,65888,Probation,Sanchez,Alvaro,Agusto,Male,Hispanic,02/20/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +40165,72668,63209,PRETRIAL,HOLMAN,CHRISTIAN,L,Male,African-American,12/28/84,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +40165,72668,63209,PRETRIAL,HOLMAN,CHRISTIAN,L,Male,African-American,12/28/84,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.25,1,Low,New,1,0 +40165,72668,63209,PRETRIAL,HOLMAN,CHRISTIAN,L,Male,African-American,12/28/84,17,All Scales,Intake,English,Conditional Release,Probation,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +63060,72670,65871,Probation,Rinehart,William,NULL,Male,Caucasian,01/09/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +63060,72670,65871,Probation,Rinehart,William,NULL,Male,Caucasian,01/09/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +63060,72670,65871,Probation,Rinehart,William,NULL,Male,Caucasian,01/09/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +39136,72674,65874,PRETRIAL,Cannon,William,NULL,Male,African-American,06/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +39136,72674,65874,PRETRIAL,Cannon,William,NULL,Male,African-American,06/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +39136,72674,65874,PRETRIAL,Cannon,William,NULL,Male,African-American,06/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63073,72688,65887,Probation,Oates,Eric,NULL,Male,Caucasian,05/04/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +63073,72688,65887,Probation,Oates,Eric,NULL,Male,Caucasian,05/04/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +63073,72688,65887,Probation,Oates,Eric,NULL,Male,Caucasian,05/04/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +27016,72684,65883,PRETRIAL,Dolsaint,Clairville,NULL,Male,African-American,08/26/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +27016,72684,65883,PRETRIAL,Dolsaint,Clairville,NULL,Male,African-American,08/26/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +27016,72684,65883,PRETRIAL,Dolsaint,Clairville,NULL,Male,African-American,08/26/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63076,72691,65890,Probation,borrelli,jorge,NULL,Male,Caucasian,01/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/29/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +63076,72691,65890,Probation,borrelli,jorge,NULL,Male,Caucasian,01/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +63076,72691,65890,Probation,borrelli,jorge,NULL,Male,Caucasian,01/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63049,72658,65861,PRETRIAL,CRUZ,NATASHA,A,Female,Caucasian,10/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +63049,72658,65861,PRETRIAL,CRUZ,NATASHA,A,Female,Caucasian,10/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +63049,72658,65861,PRETRIAL,CRUZ,NATASHA,A,Female,Caucasian,10/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63065,72679,65878,Probation,Dennis,Harmony,NULL,Female,Caucasian,01/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/29/14 0:00,2,Medium,7,Risk of Violence,-3.2,1,Low,New,1,0 +63065,72679,65878,Probation,Dennis,Harmony,NULL,Female,Caucasian,01/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,New,1,0 +63065,72679,65878,Probation,Dennis,Harmony,NULL,Female,Caucasian,01/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/29/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63054,72663,65866,Probation,Brantley,Dejah,NULL,Female,African-American,12/28/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +63054,72663,65866,Probation,Brantley,Dejah,NULL,Female,African-American,12/28/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,9,High,New,1,0 +63054,72663,65866,Probation,Brantley,Dejah,NULL,Female,African-American,12/28/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63055,72665,65867,PRETRIAL,Thomas,Lorenzo,NULL,Male,African-American,03/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +63055,72665,65867,PRETRIAL,Thomas,Lorenzo,NULL,Male,African-American,03/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +63055,72665,65867,PRETRIAL,Thomas,Lorenzo,NULL,Male,African-American,03/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63061,72672,65873,PRETRIAL,Eubanks,Kendra,NULL,Female,African-American,12/25/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +63061,72672,65873,PRETRIAL,Eubanks,Kendra,NULL,Female,African-American,12/25/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +63061,72672,65873,PRETRIAL,Eubanks,Kendra,NULL,Female,African-American,12/25/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +63071,72686,65885,PRETRIAL,NICHOLSON,PETER,NULL,Male,African-American,05/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/29/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +63071,72686,65885,PRETRIAL,NICHOLSON,PETER,NULL,Male,African-American,05/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/29/14 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +63071,72686,65885,PRETRIAL,NICHOLSON,PETER,NULL,Male,African-American,05/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63053,72662,65865,PRETRIAL,BONNER,CLARENCE,NULL,Male,African-American,11/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +63053,72662,65865,PRETRIAL,BONNER,CLARENCE,NULL,Male,African-American,11/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +63053,72662,65865,PRETRIAL,BONNER,CLARENCE,NULL,Male,African-American,11/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63069,72683,65882,PRETRIAL,Krupski,Stephen,NULL,Male,Caucasian,01/16/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/29/14 0:00,1,Low,7,Risk of Violence,-4.42,1,Low,New,1,0 +63069,72683,65882,PRETRIAL,Krupski,Stephen,NULL,Male,Caucasian,01/16/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/29/14 0:00,1,Low,8,Risk of Recidivism,-2.71,1,Low,New,1,0 +63069,72683,65882,PRETRIAL,Krupski,Stephen,NULL,Male,Caucasian,01/16/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63056,72666,65868,Probation,SAWYER,MARSHALL,L,Male,African-American,03/12/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +63056,72666,65868,Probation,SAWYER,MARSHALL,L,Male,African-American,03/12/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +63056,72666,65868,Probation,SAWYER,MARSHALL,L,Male,African-American,03/12/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63072,72687,65886,Probation,Demence,Cilia,NULL,Female,African-American,06/15/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +63072,72687,65886,Probation,Demence,Cilia,NULL,Female,African-American,06/15/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +63072,72687,65886,Probation,Demence,Cilia,NULL,Female,African-American,06/15/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63048,72657,65860,PRETRIAL,Mol,Abraham,NULL,Male,Caucasian,04/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +63048,72657,65860,PRETRIAL,Mol,Abraham,NULL,Male,Caucasian,04/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +63048,72657,65860,PRETRIAL,Mol,Abraham,NULL,Male,Caucasian,04/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +56165,72671,65872,Probation,Plaisimond,Natasha,NULL,Female,African-American,06/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.36,3,Low,New,1,0 +56165,72671,65872,Probation,Plaisimond,Natasha,NULL,Female,African-American,06/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +56165,72671,65872,Probation,Plaisimond,Natasha,NULL,Female,African-American,06/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63064,72678,65877,Probation,Orteaga,Alejandro,NULL,Male,Hispanic,10/14/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/29/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +63064,72678,65877,Probation,Orteaga,Alejandro,NULL,Male,Hispanic,10/14/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +63064,72678,65877,Probation,Orteaga,Alejandro,NULL,Male,Hispanic,10/14/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63066,72680,65879,Probation,Mazariegos,Kevin,NULL,Male,Hispanic,11/04/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +63066,72680,65879,Probation,Mazariegos,Kevin,NULL,Male,Hispanic,11/04/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +63066,72680,65879,Probation,Mazariegos,Kevin,NULL,Male,Hispanic,11/04/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63070,72685,65884,Probation,fleurigene,Wisner,NULL,Male,African-American,10/07/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/29/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +63070,72685,65884,Probation,fleurigene,Wisner,NULL,Male,African-American,10/07/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +63070,72685,65884,Probation,fleurigene,Wisner,NULL,Male,African-American,10/07/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62560,72664,65286,PRETRIAL,Bartholomew,Edward,NULL,Male,Caucasian,08/30/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,Copy,1,0 +62560,72664,65286,PRETRIAL,Bartholomew,Edward,NULL,Male,Caucasian,08/30/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,Copy,1,0 +62560,72664,65286,PRETRIAL,Bartholomew,Edward,NULL,Male,Caucasian,08/30/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +63047,72656,65859,PRETRIAL,JARRETT,JAHMAL,NULL,Male,African-American,06/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/29/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +63047,72656,65859,PRETRIAL,JARRETT,JAHMAL,NULL,Male,African-American,06/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/29/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +63047,72656,65859,PRETRIAL,JARRETT,JAHMAL,NULL,Male,African-American,06/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63050,72659,65862,PRETRIAL,McCrea,Troy,Delmonte,Male,African-American,10/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +63050,72659,65862,PRETRIAL,McCrea,Troy,Delmonte,Male,African-American,10/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +63050,72659,65862,PRETRIAL,McCrea,Troy,Delmonte,Male,African-American,10/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63063,72677,65876,Probation,Byrnes,Brandon,NULL,Male,Caucasian,01/24/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +63063,72677,65876,Probation,Byrnes,Brandon,NULL,Male,Caucasian,01/24/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +63063,72677,65876,Probation,Byrnes,Brandon,NULL,Male,Caucasian,01/24/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63052,72661,65864,PRETRIAL,Pena,Nicholas,NULL,Male,Caucasian,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +63052,72661,65864,PRETRIAL,Pena,Nicholas,NULL,Male,Caucasian,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +63052,72661,65864,PRETRIAL,Pena,Nicholas,NULL,Male,Caucasian,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/29/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63062,72675,65875,Probation,Torress-Santos,Arquimides,NULL,Male,Hispanic,08/29/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/29/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +63062,72675,65875,Probation,Torress-Santos,Arquimides,NULL,Male,Hispanic,08/29/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/29/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +63062,72675,65875,Probation,Torress-Santos,Arquimides,NULL,Male,Hispanic,08/29/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63046,72654,65857,PRETRIAL,Vassell-Gowdie,Nadia,NULL,Female,African-American,01/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/29/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +63046,72654,65857,PRETRIAL,Vassell-Gowdie,Nadia,NULL,Female,African-American,01/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/29/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +63046,72654,65857,PRETRIAL,Vassell-Gowdie,Nadia,NULL,Female,African-American,01/11/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63075,72690,65889,Probation,ENE,SIMION,NULL,Male,Caucasian,08/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/29/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +63075,72690,65889,Probation,ENE,SIMION,NULL,Male,Caucasian,08/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +63075,72690,65889,Probation,ENE,SIMION,NULL,Male,Caucasian,08/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63057,72667,65869,Probation,Malo,William,NULL,Male,Hispanic,10/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/29/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +63057,72667,65869,Probation,Malo,William,NULL,Male,Hispanic,10/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +63057,72667,65869,Probation,Malo,William,NULL,Male,Hispanic,10/30/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +52670,72669,65870,PRETRIAL,Joseph,Donald,NULL,Male,African-American,05/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +52670,72669,65870,PRETRIAL,Joseph,Donald,NULL,Male,African-American,05/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +52670,72669,65870,PRETRIAL,Joseph,Donald,NULL,Male,African-American,05/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63068,72682,65881,Probation,WELLER,MONIQUE,M,Female,African-American,12/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +63068,72682,65881,Probation,WELLER,MONIQUE,M,Female,African-American,12/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +63068,72682,65881,Probation,WELLER,MONIQUE,M,Female,African-American,12/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63085,72703,65900,PRETRIAL,Spears,Tisa,NULL,Female,African-American,11/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +63085,72703,65900,PRETRIAL,Spears,Tisa,NULL,Female,African-American,11/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +63085,72703,65900,PRETRIAL,Spears,Tisa,NULL,Female,African-American,11/02/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63096,72716,65913,PRETRIAL,Ksiazek,Jaclyn,NULL,Female,Caucasian,05/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/30/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +63096,72716,65913,PRETRIAL,Ksiazek,Jaclyn,NULL,Female,Caucasian,05/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +63096,72716,65913,PRETRIAL,Ksiazek,Jaclyn,NULL,Female,Caucasian,05/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +49149,72727,65922,PRETRIAL,COLLINS,MARTHA,NULL,Female,African-American,03/24/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/30/14 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +49149,72727,65922,PRETRIAL,COLLINS,MARTHA,NULL,Female,African-American,03/24/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/30/14 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +49149,72727,65922,PRETRIAL,COLLINS,MARTHA,NULL,Female,African-American,03/24/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63088,72706,65903,Probation,Pierre,Diana,NULL,Female,African-American,08/23/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +63088,72706,65903,Probation,Pierre,Diana,NULL,Female,African-American,08/23/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +63088,72706,65903,Probation,Pierre,Diana,NULL,Female,African-American,08/23/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63103,72724,65920,PRETRIAL,MCFADDEN,LINDELL,NULL,Male,African-American,05/15/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,7,Risk of Violence,-2.92,2,Low,New,1,0 +63103,72724,65920,PRETRIAL,MCFADDEN,LINDELL,NULL,Male,African-American,05/15/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +63103,72724,65920,PRETRIAL,MCFADDEN,LINDELL,NULL,Male,African-American,05/15/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63080,72698,65895,PRETRIAL,Jolly,Bryan,NULL,Male,African-American,03/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +63080,72698,65895,PRETRIAL,Jolly,Bryan,NULL,Male,African-American,03/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +63080,72698,65895,PRETRIAL,Jolly,Bryan,NULL,Male,African-American,03/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63107,72732,65925,PRETRIAL,COOMANSINGH,KERLON,NULL,Male,Other,02/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +63107,72732,65925,PRETRIAL,COOMANSINGH,KERLON,NULL,Male,Other,02/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +63107,72732,65925,PRETRIAL,COOMANSINGH,KERLON,NULL,Male,Other,02/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63099,72719,65916,Probation,Robertson,Michelle,NULL,Female,African-American,06/03/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +63099,72719,65916,Probation,Robertson,Michelle,NULL,Female,African-American,06/03/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +63099,72719,65916,Probation,Robertson,Michelle,NULL,Female,African-American,06/03/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63081,72699,65896,PRETRIAL,Page,Terrin,NULL,Male,African-American,04/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,4,High,7,Risk of Violence,-0.9,9,High,New,1,0 +63081,72699,65896,PRETRIAL,Page,Terrin,NULL,Male,African-American,04/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +63081,72699,65896,PRETRIAL,Page,Terrin,NULL,Male,African-American,04/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63083,72701,65898,PRETRIAL,Lamboglia,Anthony,NULL,Male,Caucasian,09/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +63083,72701,65898,PRETRIAL,Lamboglia,Anthony,NULL,Male,Caucasian,09/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +63083,72701,65898,PRETRIAL,Lamboglia,Anthony,NULL,Male,Caucasian,09/13/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63090,72708,65905,Probation,Pierre,Gladys,NULL,Female,African-American,06/24/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +63090,72708,65905,Probation,Pierre,Gladys,NULL,Female,African-American,06/24/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +63090,72708,65905,Probation,Pierre,Gladys,NULL,Female,African-American,06/24/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63102,72722,65918,PRETRIAL,Oliver,Berry,NULL,Male,African-American,02/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/30/14 0:00,2,Medium,7,Risk of Violence,-3,1,Low,New,1,0 +63102,72722,65918,PRETRIAL,Oliver,Berry,NULL,Male,African-American,02/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/30/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +63102,72722,65918,PRETRIAL,Oliver,Berry,NULL,Male,African-American,02/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,4/30/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63110,72736,65929,PRETRIAL,Barnard,Daniel,NULL,Male,African-American,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +63110,72736,65929,PRETRIAL,Barnard,Daniel,NULL,Male,African-American,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +63110,72736,65929,PRETRIAL,Barnard,Daniel,NULL,Male,African-American,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63109,72734,65927,Probation,ETIENNE,BERNARD,NULL,Male,African-American,06/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +63109,72734,65927,Probation,ETIENNE,BERNARD,NULL,Male,African-American,06/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +63109,72734,65927,Probation,ETIENNE,BERNARD,NULL,Male,African-American,06/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63077,72692,65891,PRETRIAL,Strong,Rashad,NULL,Male,African-American,03/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +63077,72692,65891,PRETRIAL,Strong,Rashad,NULL,Male,African-American,03/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +63077,72692,65891,PRETRIAL,Strong,Rashad,NULL,Male,African-American,03/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63097,72717,65914,PRETRIAL,Wilmont,Dwayne,NULL,Male,African-American,09/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +63097,72717,65914,PRETRIAL,Wilmont,Dwayne,NULL,Male,African-American,09/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +63097,72717,65914,PRETRIAL,Wilmont,Dwayne,NULL,Male,African-American,09/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63079,72696,65894,PRETRIAL,Ganz,Don,NULL,Male,Caucasian,01/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +63079,72696,65894,PRETRIAL,Ganz,Don,NULL,Male,Caucasian,01/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +63079,72696,65894,PRETRIAL,Ganz,Don,NULL,Male,Caucasian,01/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63095,72713,65910,Probation,Prats,Lazaro,NULL,Male,Hispanic,05/18/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +63095,72713,65910,Probation,Prats,Lazaro,NULL,Male,Hispanic,05/18/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +63095,72713,65910,Probation,Prats,Lazaro,NULL,Male,Hispanic,05/18/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +25607,27057,24776,Probation,coomansingh,kerlon,NULL,Male,Other,02/01/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +25607,27057,24776,Probation,coomansingh,kerlon,NULL,Male,Other,02/01/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +25607,27057,24776,Probation,coomansingh,kerlon,NULL,Male,Other,02/01/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53225,72693,54675,PRETRIAL,Koepke,Kameron,NULL,Male,Caucasian,10/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,Copy,1,0 +53225,72693,54675,PRETRIAL,Koepke,Kameron,NULL,Male,Caucasian,10/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,Copy,1,0 +53225,72693,54675,PRETRIAL,Koepke,Kameron,NULL,Male,Caucasian,10/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +63082,72700,65897,PRETRIAL,Wilson,Shaun,NULL,Male,African-American,09/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +63082,72700,65897,PRETRIAL,Wilson,Shaun,NULL,Male,African-American,09/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +63082,72700,65897,PRETRIAL,Wilson,Shaun,NULL,Male,African-American,09/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63089,72707,65904,PRETRIAL,JONES,ALEA,NULL,Female,African-American,03/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +63089,72707,65904,PRETRIAL,JONES,ALEA,NULL,Female,African-American,03/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +63089,72707,65904,PRETRIAL,JONES,ALEA,NULL,Female,African-American,03/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +23741,72721,65774,PRETRIAL,Jackson,Secret,NULL,Female,African-American,11/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +23741,72721,65774,PRETRIAL,Jackson,Secret,NULL,Female,African-American,11/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,Copy,1,0 +23741,72721,65774,PRETRIAL,Jackson,Secret,NULL,Female,African-American,11/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +43109,72714,65911,Probation,monroedickerson,cleondra,NULL,Female,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.07,4,Low,New,1,0 +43109,72714,65911,Probation,monroedickerson,cleondra,NULL,Female,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,8,High,New,1,0 +43109,72714,65911,Probation,monroedickerson,cleondra,NULL,Female,African-American,11/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +51707,72735,65928,PRETRIAL,Franco,Jhonatan,NULL,Male,Hispanic,05/29/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +51707,72735,65928,PRETRIAL,Franco,Jhonatan,NULL,Male,Hispanic,05/29/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +51707,72735,65928,PRETRIAL,Franco,Jhonatan,NULL,Male,Hispanic,05/29/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63106,72730,65924,Probation,Pavkovich,Patricia,NULL,Female,Caucasian,09/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/30/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +63106,72730,65924,Probation,Pavkovich,Patricia,NULL,Female,Caucasian,09/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +63106,72730,65924,Probation,Pavkovich,Patricia,NULL,Female,Caucasian,09/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +20241,72726,19462,Probation,Ferguson,Larry,Gay,Male,African-American,08/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,Copy,1,0 +20241,72726,19462,Probation,Ferguson,Larry,Gay,Male,African-American,08/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,Copy,1,0 +20241,72726,19462,Probation,Ferguson,Larry,Gay,Male,African-American,08/01/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,4/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +63078,72695,65893,PRETRIAL,Davis,Harold,NULL,Male,African-American,08/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +63078,72695,65893,PRETRIAL,Davis,Harold,NULL,Male,African-American,08/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +63078,72695,65893,PRETRIAL,Davis,Harold,NULL,Male,African-American,08/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63091,72709,65906,Probation,BUDINGER,DAVID,K,Male,Caucasian,04/22/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-4.41,1,Low,New,1,0 +63091,72709,65906,Probation,BUDINGER,DAVID,K,Male,Caucasian,04/22/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +63091,72709,65906,Probation,BUDINGER,DAVID,K,Male,Caucasian,04/22/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63087,72705,65902,PRETRIAL,FLAHERTY,MATTHEW,JOHN,Male,Caucasian,08/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +63087,72705,65902,PRETRIAL,FLAHERTY,MATTHEW,JOHN,Male,Caucasian,08/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +63087,72705,65902,PRETRIAL,FLAHERTY,MATTHEW,JOHN,Male,Caucasian,08/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63098,72718,65915,PRETRIAL,McIntyre,Tanya,NULL,Female,Caucasian,11/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +63098,72718,65915,PRETRIAL,McIntyre,Tanya,NULL,Female,Caucasian,11/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +63098,72718,65915,PRETRIAL,McIntyre,Tanya,NULL,Female,Caucasian,11/17/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63086,72704,65901,PRETRIAL,Affiltto,Joseph,NULL,Male,African-American,11/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +63086,72704,65901,PRETRIAL,Affiltto,Joseph,NULL,Male,African-American,11/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +63086,72704,65901,PRETRIAL,Affiltto,Joseph,NULL,Male,African-American,11/10/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55084,72697,56870,PRETRIAL,Wright,Lee,NULL,Male,African-American,09/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,Copy,1,0 +55084,72697,56870,PRETRIAL,Wright,Lee,NULL,Male,African-American,09/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,Copy,1,0 +55084,72697,56870,PRETRIAL,Wright,Lee,NULL,Male,African-American,09/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +63094,72712,65909,Probation,THIRKELL,SARAH,JINE,Female,Caucasian,02/06/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +63094,72712,65909,Probation,THIRKELL,SARAH,JINE,Female,Caucasian,02/06/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +63094,72712,65909,Probation,THIRKELL,SARAH,JINE,Female,Caucasian,02/06/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +25607,72731,24776,Probation,coomansingh,kerlon,NULL,Male,Other,02/01/83,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,Copy,1,0 +25607,72731,24776,Probation,coomansingh,kerlon,NULL,Male,Other,02/01/83,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,Copy,1,0 +25607,72731,24776,Probation,coomansingh,kerlon,NULL,Male,Other,02/01/83,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +63092,72710,65907,Probation,wright,kenneth,NULL,Male,African-American,08/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/30/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +63092,72710,65907,Probation,wright,kenneth,NULL,Male,African-American,08/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/30/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +63092,72710,65907,Probation,wright,kenneth,NULL,Male,African-American,08/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63108,72733,65926,DRRD,Plummer,Kory,Omar,Male,African-American,03/11/77,17,All Scales,Intake,English,Probation Violator,Parole,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +63108,72733,65926,DRRD,Plummer,Kory,Omar,Male,African-American,03/11/77,17,All Scales,Intake,English,Probation Violator,Parole,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-0.63,3,Low,New,1,0 +63108,72733,65926,DRRD,Plummer,Kory,Omar,Male,African-American,03/11/77,17,All Scales,Intake,English,Probation Violator,Parole,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,31,8,High,New,1,0 +1407,72694,65892,PRETRIAL,Grenyion,Leon,Dewayne,Male,African-American,12/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +1407,72694,65892,PRETRIAL,Grenyion,Leon,Dewayne,Male,African-American,12/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +1407,72694,65892,PRETRIAL,Grenyion,Leon,Dewayne,Male,African-American,12/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63105,72728,65923,Probation,Lloyd,Giovonni,NULL,Male,African-American,05/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +63105,72728,65923,Probation,Lloyd,Giovonni,NULL,Male,African-American,05/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +63105,72728,65923,Probation,Lloyd,Giovonni,NULL,Male,African-American,05/05/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +53947,72715,65912,PRETRIAL,Murphy,Deanna,NULL,Female,Caucasian,11/10/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +53947,72715,65912,PRETRIAL,Murphy,Deanna,NULL,Female,Caucasian,11/10/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +53947,72715,65912,PRETRIAL,Murphy,Deanna,NULL,Female,Caucasian,11/10/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63101,72723,65919,Probation,VANSTEENBURGH,JOSEPH,G,Male,Caucasian,09/14/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +63101,72723,65919,Probation,VANSTEENBURGH,JOSEPH,G,Male,Caucasian,09/14/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +63101,72723,65919,Probation,VANSTEENBURGH,JOSEPH,G,Male,Caucasian,09/14/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63084,72702,65899,PRETRIAL,Vitiello,Anthony,Frank,Male,Caucasian,10/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +63084,72702,65899,PRETRIAL,Vitiello,Anthony,Frank,Male,Caucasian,10/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +63084,72702,65899,PRETRIAL,Vitiello,Anthony,Frank,Male,Caucasian,10/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63100,72720,65917,PRETRIAL,SAJOUS,NATASHA,NULL,Female,African-American,07/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +63100,72720,65917,PRETRIAL,SAJOUS,NATASHA,NULL,Female,African-American,07/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +63100,72720,65917,PRETRIAL,SAJOUS,NATASHA,NULL,Female,African-American,07/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,4/30/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54186,72741,65933,PRETRIAL,Alfonso,Jose,Luis,Male,Hispanic,06/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +54186,72741,65933,PRETRIAL,Alfonso,Jose,Luis,Male,Hispanic,06/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +54186,72741,65933,PRETRIAL,Alfonso,Jose,Luis,Male,Hispanic,06/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63118,72749,65940,Probation,Bayer,Joshua,NULL,Male,Caucasian,07/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +63118,72749,65940,Probation,Bayer,Joshua,NULL,Male,Caucasian,07/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +63118,72749,65940,Probation,Bayer,Joshua,NULL,Male,Caucasian,07/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63127,72762,65952,PRETRIAL,Harold,Kierra,NULL,Female,African-American,04/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +63127,72762,65952,PRETRIAL,Harold,Kierra,NULL,Female,African-American,04/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,10,High,New,1,0 +63127,72762,65952,PRETRIAL,Harold,Kierra,NULL,Female,African-American,04/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +63132,72767,65957,Probation,Castro,Jose,NULL,Male,Hispanic,05/21/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/14 0:00,2,Medium,7,Risk of Violence,-2.78,2,Low,New,1,0 +63132,72767,65957,Probation,Castro,Jose,NULL,Male,Hispanic,05/21/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +63132,72767,65957,Probation,Castro,Jose,NULL,Male,Hispanic,05/21/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63115,72746,65937,PRETRIAL,Alcivar,Victor,NULL,Male,Hispanic,04/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/1/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +63115,72746,65937,PRETRIAL,Alcivar,Victor,NULL,Male,Hispanic,04/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +63115,72746,65937,PRETRIAL,Alcivar,Victor,NULL,Male,Hispanic,04/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63111,72739,65931,PRETRIAL,Frank,Jason,NULL,Male,Caucasian,07/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/1/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +63111,72739,65931,PRETRIAL,Frank,Jason,NULL,Male,Caucasian,07/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +63111,72739,65931,PRETRIAL,Frank,Jason,NULL,Male,Caucasian,07/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +30216,72754,65945,DRRD,Babich,David,Robert,Male,Caucasian,02/15/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +30216,72754,65945,DRRD,Babich,David,Robert,Male,Caucasian,02/15/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +30216,72754,65945,DRRD,Babich,David,Robert,Male,Caucasian,02/15/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +52013,72775,65964,PRETRIAL,Alejo-Dominguez,Wilfredo,NULL,Male,Hispanic,05/18/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +52013,72775,65964,PRETRIAL,Alejo-Dominguez,Wilfredo,NULL,Male,Hispanic,05/18/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +52013,72775,65964,PRETRIAL,Alejo-Dominguez,Wilfredo,NULL,Male,Hispanic,05/18/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63121,72756,65947,Probation,Avera,Jack,NULL,Male,African-American,05/04/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +63121,72756,65947,Probation,Avera,Jack,NULL,Male,African-American,05/04/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +63121,72756,65947,Probation,Avera,Jack,NULL,Male,African-American,05/04/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63140,72777,65966,PRETRIAL,Rozhon,Trice,NULL,Male,Caucasian,12/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +63140,72777,65966,PRETRIAL,Rozhon,Trice,NULL,Male,Caucasian,12/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +63140,72777,65966,PRETRIAL,Rozhon,Trice,NULL,Male,Caucasian,12/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54086,72751,65942,Probation,uragacastillo,stacy,NULL,Female,Hispanic,02/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/1/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +54086,72751,65942,Probation,uragacastillo,stacy,NULL,Female,Hispanic,02/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/1/14 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +54086,72751,65942,Probation,uragacastillo,stacy,NULL,Female,Hispanic,02/13/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63126,72760,65950,Probation,KILPATRICK,ALEC,T,Male,African-American,08/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +63126,72760,65950,Probation,KILPATRICK,ALEC,T,Male,African-American,08/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +63126,72760,65950,Probation,KILPATRICK,ALEC,T,Male,African-American,08/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63116,72747,65938,Probation,LUCAS,CAST,L,Male,African-American,07/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +63116,72747,65938,Probation,LUCAS,CAST,L,Male,African-American,07/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.64,10,High,New,1,0 +63116,72747,65938,Probation,LUCAS,CAST,L,Male,African-American,07/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +24514,72742,23698,Probation,Elasraoui,Khalil,NULL,Male,Caucasian,06/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,Copy,1,0 +24514,72742,23698,Probation,Elasraoui,Khalil,NULL,Male,Caucasian,06/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,Copy,1,0 +24514,72742,23698,Probation,Elasraoui,Khalil,NULL,Male,Caucasian,06/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +63113,72744,65935,PRETRIAL,Oliviel,Larrell,NULL,Male,African-American,07/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +63113,72744,65935,PRETRIAL,Oliviel,Larrell,NULL,Male,African-American,07/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +63113,72744,65935,PRETRIAL,Oliviel,Larrell,NULL,Male,African-American,07/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63128,72763,65953,Probation,roberts,David,NULL,Male,African-American,09/22/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +63128,72763,65953,Probation,roberts,David,NULL,Male,African-American,09/22/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +63128,72763,65953,Probation,roberts,David,NULL,Male,African-American,09/22/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63130,72765,65955,PRETRIAL,Woodward,Ralph,NULL,Male,Caucasian,11/18/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/1/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +63130,72765,65955,PRETRIAL,Woodward,Ralph,NULL,Male,Caucasian,11/18/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +63130,72765,65955,PRETRIAL,Woodward,Ralph,NULL,Male,Caucasian,11/18/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +63138,72772,65962,Probation,Comesana,Karim,NULL,Female,Hispanic,01/26/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/1/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +63138,72772,65962,Probation,Comesana,Karim,NULL,Female,Hispanic,01/26/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +63138,72772,65962,Probation,Comesana,Karim,NULL,Female,Hispanic,01/26/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63129,72764,65954,PRETRIAL,Roscoe,Datron,NULL,Male,African-American,07/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +63129,72764,65954,PRETRIAL,Roscoe,Datron,NULL,Male,African-American,07/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +63129,72764,65954,PRETRIAL,Roscoe,Datron,NULL,Male,African-American,07/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63119,72752,65943,Broward County,Cash,Dori,NULL,Female,Caucasian,03/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/1/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +63119,72752,65943,Broward County,Cash,Dori,NULL,Female,Caucasian,03/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +63119,72752,65943,Broward County,Cash,Dori,NULL,Female,Caucasian,03/14/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63125,72759,65949,Probation,Stanciu,Jonel,NULL,Male,Hispanic,06/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +63125,72759,65949,Probation,Stanciu,Jonel,NULL,Male,Hispanic,06/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +63125,72759,65949,Probation,Stanciu,Jonel,NULL,Male,Hispanic,06/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56672,72738,65930,PRETRIAL,Eliacin,Romario,Scott,Male,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +56672,72738,65930,PRETRIAL,Eliacin,Romario,Scott,Male,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +56672,72738,65930,PRETRIAL,Eliacin,Romario,Scott,Male,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63122,72755,65946,PRETRIAL,PAOLINO,LOUIS,NULL,Male,Caucasian,01/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +63122,72755,65946,PRETRIAL,PAOLINO,LOUIS,NULL,Male,Caucasian,01/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +63122,72755,65946,PRETRIAL,PAOLINO,LOUIS,NULL,Male,Caucasian,01/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +18927,72773,18181,DRRD,Capiola,Nicholas,NULL,Male,Caucasian,11/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,Copy,1,0 +18927,72773,18181,DRRD,Capiola,Nicholas,NULL,Male,Caucasian,11/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,Copy,1,0 +18927,72773,18181,DRRD,Capiola,Nicholas,NULL,Male,Caucasian,11/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,Copy,1,0 +32831,72743,65934,PRETRIAL,kennedy,stephanie,NULL,Female,Caucasian,02/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,2,Medium,7,Risk of Violence,-2.87,2,Low,New,1,0 +32831,72743,65934,PRETRIAL,kennedy,stephanie,NULL,Female,Caucasian,02/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +32831,72743,65934,PRETRIAL,kennedy,stephanie,NULL,Female,Caucasian,02/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +38355,72750,65941,PRETRIAL,CAESAR,MCCARLOS,C,Male,African-American,11/17/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/1/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +38355,72750,65941,PRETRIAL,CAESAR,MCCARLOS,C,Male,African-American,11/17/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/1/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +38355,72750,65941,PRETRIAL,CAESAR,MCCARLOS,C,Male,African-American,11/17/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63124,72757,65948,Probation,owens,nathaniel,NULL,Male,African-American,07/24/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +63124,72757,65948,Probation,owens,nathaniel,NULL,Male,African-American,07/24/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +63124,72757,65948,Probation,owens,nathaniel,NULL,Male,African-American,07/24/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63120,72753,65944,PRETRIAL,Smith,Jerome,Hugh,Male,African-American,12/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +63120,72753,65944,PRETRIAL,Smith,Jerome,Hugh,Male,African-American,12/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +63120,72753,65944,PRETRIAL,Smith,Jerome,Hugh,Male,African-American,12/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +18809,72758,64318,PRETRIAL,onyiuke,chinwe,NULL,Female,African-American,08/31/78,17,All Scales,Intake,English,Conditional Release,Probation,Significant Other,5/1/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +18809,72758,64318,PRETRIAL,onyiuke,chinwe,NULL,Female,African-American,08/31/78,17,All Scales,Intake,English,Conditional Release,Probation,Significant Other,5/1/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +18809,72758,64318,PRETRIAL,onyiuke,chinwe,NULL,Female,African-American,08/31/78,17,All Scales,Intake,English,Conditional Release,Probation,Significant Other,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,18,2,Low,New,1,0 +63131,72766,65956,Probation,HOLLIDAY,CHARLES,ARTHUR,Male,Caucasian,04/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +63131,72766,65956,Probation,HOLLIDAY,CHARLES,ARTHUR,Male,Caucasian,04/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.05,10,High,New,1,0 +63131,72766,65956,Probation,HOLLIDAY,CHARLES,ARTHUR,Male,Caucasian,04/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +43246,72737,57800,PRETRIAL,Trotter,Tammy,L,Female,Caucasian,05/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.96,5,Medium,Copy,1,0 +43246,72737,57800,PRETRIAL,Trotter,Tammy,L,Female,Caucasian,05/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,Copy,1,0 +43246,72737,57800,PRETRIAL,Trotter,Tammy,L,Female,Caucasian,05/03/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +46587,72774,65963,PRETRIAL,DIAZ,AMANDA,NULL,Female,Hispanic,02/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +46587,72774,65963,PRETRIAL,DIAZ,AMANDA,NULL,Female,Hispanic,02/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +46587,72774,65963,PRETRIAL,DIAZ,AMANDA,NULL,Female,Hispanic,02/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63114,72745,65936,PRETRIAL,BAKER,CHADWICK,NULL,Male,Caucasian,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +63114,72745,65936,PRETRIAL,BAKER,CHADWICK,NULL,Male,Caucasian,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +63114,72745,65936,PRETRIAL,BAKER,CHADWICK,NULL,Male,Caucasian,09/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63135,72769,65959,PRETRIAL,Woodson,Olivier,NULL,Male,African-American,01/31/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,4,High,7,Risk of Violence,-0.16,10,High,New,1,0 +63135,72769,65959,PRETRIAL,Woodson,Olivier,NULL,Male,African-American,01/31/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +63135,72769,65959,PRETRIAL,Woodson,Olivier,NULL,Male,African-American,01/31/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63139,72776,65965,Probation,Acuna,Kennya,NULL,Female,Hispanic,03/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +63139,72776,65965,Probation,Acuna,Kennya,NULL,Female,Hispanic,03/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +63139,72776,65965,Probation,Acuna,Kennya,NULL,Female,Hispanic,03/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63117,72748,65939,Probation,Lemuz-Morales,felix,NULL,Male,Hispanic,04/04/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +63117,72748,65939,Probation,Lemuz-Morales,felix,NULL,Male,Hispanic,04/04/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +63117,72748,65939,Probation,Lemuz-Morales,felix,NULL,Male,Hispanic,04/04/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63112,72740,65932,PRETRIAL,Dowels,Jonathan,NULL,Male,African-American,01/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +63112,72740,65932,PRETRIAL,Dowels,Jonathan,NULL,Male,African-American,01/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +63112,72740,65932,PRETRIAL,Dowels,Jonathan,NULL,Male,African-American,01/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63123,72761,65951,PRETRIAL,PUCCI,ANGELA,NULL,Female,Caucasian,02/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/1/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +63123,72761,65951,PRETRIAL,PUCCI,ANGELA,NULL,Female,Caucasian,02/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/1/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +63123,72761,65951,PRETRIAL,PUCCI,ANGELA,NULL,Female,Caucasian,02/21/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63134,72768,65958,PRETRIAL,BALBOSA,FRANCISCO,NULL,Male,Hispanic,04/02/51,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +63134,72768,65958,PRETRIAL,BALBOSA,FRANCISCO,NULL,Male,Hispanic,04/02/51,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,1,Low,8,Risk of Recidivism,-2.64,1,Low,New,1,0 +63134,72768,65958,PRETRIAL,BALBOSA,FRANCISCO,NULL,Male,Hispanic,04/02/51,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,5/1/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +21777,72818,61380,Probation,SANTIAGOGRIER,JOSEPH,NULL,Male,Hispanic,10/24/61,17,All Scales,Intake,English,Post Sentence,Probation,Separated,5/2/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +21777,72818,61380,Probation,SANTIAGOGRIER,JOSEPH,NULL,Male,Hispanic,10/24/61,17,All Scales,Intake,English,Post Sentence,Probation,Separated,5/2/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +21777,72818,61380,Probation,SANTIAGOGRIER,JOSEPH,NULL,Male,Hispanic,10/24/61,17,All Scales,Intake,English,Post Sentence,Probation,Separated,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +63151,72789,65978,PRETRIAL,Ortiz,Fritz,NULL,Male,African-American,03/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +63151,72789,65978,PRETRIAL,Ortiz,Fritz,NULL,Male,African-American,03/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +63151,72789,65978,PRETRIAL,Ortiz,Fritz,NULL,Male,African-American,03/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63152,72790,65979,PRETRIAL,Wilson,Columbus,NULL,Male,African-American,06/28/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/2/14 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +63152,72790,65979,PRETRIAL,Wilson,Columbus,NULL,Male,African-American,06/28/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +63152,72790,65979,PRETRIAL,Wilson,Columbus,NULL,Male,African-American,06/28/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/2/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +21645,22625,20801,PRETRIAL,TOMMIE,SAM,LEON,Male,Hispanic,08/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,2,Medium,7,Risk of Violence,-1.51,6,Medium,New,1,0 +21645,22625,20801,PRETRIAL,TOMMIE,SAM,LEON,Male,Hispanic,08/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +21645,22625,20801,PRETRIAL,TOMMIE,SAM,LEON,Male,Hispanic,08/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63145,72782,65971,PRETRIAL,Reynolds,Tasman,Alfred,Male,Other,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/2/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +63145,72782,65971,PRETRIAL,Reynolds,Tasman,Alfred,Male,Other,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +63145,72782,65971,PRETRIAL,Reynolds,Tasman,Alfred,Male,Other,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/2/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +40230,72797,65985,PRETRIAL,Singh,Dwayne,Demar,Male,Caucasian,10/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +40230,72797,65985,PRETRIAL,Singh,Dwayne,Demar,Male,Caucasian,10/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +40230,72797,65985,PRETRIAL,Singh,Dwayne,Demar,Male,Caucasian,10/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63162,72803,65991,PRETRIAL,ZAYAS,ADAM,NULL,Male,Hispanic,02/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.99,4,Low,New,1,0 +63162,72803,65991,PRETRIAL,ZAYAS,ADAM,NULL,Male,Hispanic,02/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +63162,72803,65991,PRETRIAL,ZAYAS,ADAM,NULL,Male,Hispanic,02/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61270,72810,63809,PRETRIAL,MORLEY,TERRILL,NULL,Male,African-American,08/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,Copy,1,0 +61270,72810,63809,PRETRIAL,MORLEY,TERRILL,NULL,Male,African-American,08/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,Copy,1,0 +61270,72810,63809,PRETRIAL,MORLEY,TERRILL,NULL,Male,African-American,08/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +22075,72784,65973,PRETRIAL,HARLIS,JEROME,NULL,Male,African-American,12/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,2,Medium,7,Risk of Violence,-2.27,3,Low,New,1,0 +22075,72784,65973,PRETRIAL,HARLIS,JEROME,NULL,Male,African-American,12/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +22075,72784,65973,PRETRIAL,HARLIS,JEROME,NULL,Male,African-American,12/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63156,72795,65983,PRETRIAL,Huth,Cora,NULL,Female,Caucasian,05/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +63156,72795,65983,PRETRIAL,Huth,Cora,NULL,Female,Caucasian,05/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +63156,72795,65983,PRETRIAL,Huth,Cora,NULL,Female,Caucasian,05/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63149,72787,65976,PRETRIAL,Cherfrere,Mirelene,NULL,Female,African-American,10/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +63149,72787,65976,PRETRIAL,Cherfrere,Mirelene,NULL,Female,African-American,10/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +63149,72787,65976,PRETRIAL,Cherfrere,Mirelene,NULL,Female,African-American,10/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62101,72805,64741,Probation,Jenkins,Deandre,NULL,Male,African-American,01/02/95,17,All Scales,Intake,English,Other,Probation,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +62101,72805,64741,Probation,Jenkins,Deandre,NULL,Male,African-American,01/02/95,17,All Scales,Intake,English,Other,Probation,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-0.42,4,Low,New,1,0 +62101,72805,64741,Probation,Jenkins,Deandre,NULL,Male,African-American,01/02/95,17,All Scales,Intake,English,Other,Probation,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63142,72779,65968,PRETRIAL,Suarez,Edwin,NULL,Male,Hispanic,08/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +63142,72779,65968,PRETRIAL,Suarez,Edwin,NULL,Male,Hispanic,08/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +63142,72779,65968,PRETRIAL,Suarez,Edwin,NULL,Male,Hispanic,08/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63169,72813,65999,PRETRIAL,Hidalgo,Victor,NULL,Male,Hispanic,10/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +63169,72813,65999,PRETRIAL,Hidalgo,Victor,NULL,Male,Hispanic,10/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +63169,72813,65999,PRETRIAL,Hidalgo,Victor,NULL,Male,Hispanic,10/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63154,72792,65981,PRETRIAL,Loubeau,Diana,Joanne,Female,African-American,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +63154,72792,65981,PRETRIAL,Loubeau,Diana,Joanne,Female,African-American,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +63154,72792,65981,PRETRIAL,Loubeau,Diana,Joanne,Female,African-American,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +5449,72822,66007,PRETRIAL,mitchell,tremaine,NULL,Male,African-American,07/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +5449,72822,66007,PRETRIAL,mitchell,tremaine,NULL,Male,African-American,07/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +5449,72822,66007,PRETRIAL,mitchell,tremaine,NULL,Male,African-American,07/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63141,72778,65967,PRETRIAL,Felton,Bria,NULL,Female,African-American,09/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +63141,72778,65967,PRETRIAL,Felton,Bria,NULL,Female,African-American,09/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,9,High,New,1,0 +63141,72778,65967,PRETRIAL,Felton,Bria,NULL,Female,African-American,09/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63161,72801,65989,Probation,Patrick,Joseph,NULL,Male,Caucasian,05/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +63161,72801,65989,Probation,Patrick,Joseph,NULL,Male,Caucasian,05/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +63161,72801,65989,Probation,Patrick,Joseph,NULL,Male,Caucasian,05/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +55053,72808,65995,Probation,USSA,ANDRES,NULL,Male,Hispanic,04/16/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +55053,72808,65995,Probation,USSA,ANDRES,NULL,Male,Hispanic,04/16/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +55053,72808,65995,Probation,USSA,ANDRES,NULL,Male,Hispanic,04/16/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63143,72780,65969,PRETRIAL,Tosti,Tonja,Nicole,Female,Caucasian,01/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +63143,72780,65969,PRETRIAL,Tosti,Tonja,Nicole,Female,Caucasian,01/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +63143,72780,65969,PRETRIAL,Tosti,Tonja,Nicole,Female,Caucasian,01/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63160,72799,65987,Probation,CACCAMO,JENNIFER,L,Female,Hispanic,03/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/2/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +63160,72799,65987,Probation,CACCAMO,JENNIFER,L,Female,Hispanic,03/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +63160,72799,65987,Probation,CACCAMO,JENNIFER,L,Female,Hispanic,03/08/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63164,72806,65993,Probation,BENITEZHERNANDEZ,MANUEL,A,Male,Hispanic,01/11/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/2/14 0:00,4,High,7,Risk of Violence,-1.17,8,High,New,1,0 +63164,72806,65993,Probation,BENITEZHERNANDEZ,MANUEL,A,Male,Hispanic,01/11/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/2/14 0:00,4,High,8,Risk of Recidivism,1.22,10,High,New,1,0 +63164,72806,65993,Probation,BENITEZHERNANDEZ,MANUEL,A,Male,Hispanic,01/11/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/2/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63171,72815,66001,PRETRIAL,Owens,Martin,NULL,Male,Caucasian,02/23/38,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/2/14 0:00,1,Low,7,Risk of Violence,-4.59,1,Low,New,1,0 +63171,72815,66001,PRETRIAL,Owens,Martin,NULL,Male,Caucasian,02/23/38,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/2/14 0:00,1,Low,8,Risk of Recidivism,-2.96,1,Low,New,1,0 +63171,72815,66001,PRETRIAL,Owens,Martin,NULL,Male,Caucasian,02/23/38,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63147,72785,65974,PRETRIAL,Pierre,Laika,NULL,Male,African-American,03/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +63147,72785,65974,PRETRIAL,Pierre,Laika,NULL,Male,African-American,03/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +63147,72785,65974,PRETRIAL,Pierre,Laika,NULL,Male,African-American,03/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +47893,72794,48514,PRETRIAL,Taulbert,Moses,NULL,Male,African-American,06/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.37,3,Low,Copy,1,0 +47893,72794,48514,PRETRIAL,Taulbert,Moses,NULL,Male,African-American,06/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,Copy,1,0 +47893,72794,48514,PRETRIAL,Taulbert,Moses,NULL,Male,African-American,06/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +63165,72807,65994,PRETRIAL,Blake,Gary,Michael,Male,African-American,01/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +63165,72807,65994,PRETRIAL,Blake,Gary,Michael,Male,African-American,01/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +63165,72807,65994,PRETRIAL,Blake,Gary,Michael,Male,African-American,01/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63183,72821,66006,PRETRIAL,deloach,jimmy,NULL,Male,African-American,04/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +63183,72821,66006,PRETRIAL,deloach,jimmy,NULL,Male,African-American,04/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +63183,72821,66006,PRETRIAL,deloach,jimmy,NULL,Male,African-American,04/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63148,72786,65975,PRETRIAL,Minnis,Alex,NULL,Female,African-American,07/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +63148,72786,65975,PRETRIAL,Minnis,Alex,NULL,Female,African-American,07/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.07,8,High,New,1,0 +63148,72786,65975,PRETRIAL,Minnis,Alex,NULL,Female,African-American,07/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63155,72793,65982,PRETRIAL,Taylor,Andre,NULL,Male,Other,07/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +63155,72793,65982,PRETRIAL,Taylor,Andre,NULL,Male,Other,07/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +63155,72793,65982,PRETRIAL,Taylor,Andre,NULL,Male,Other,07/09/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63159,72800,65988,Probation,RODRIGUEZ,LUIS,NULL,Male,Hispanic,12/25/96,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +63159,72800,65988,Probation,RODRIGUEZ,LUIS,NULL,Male,Hispanic,12/25/96,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +63159,72800,65988,Probation,RODRIGUEZ,LUIS,NULL,Male,Hispanic,12/25/96,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63170,72814,66000,Probation,Pallai,Stephanie,NULL,Female,Hispanic,04/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +63170,72814,66000,Probation,Pallai,Stephanie,NULL,Female,Hispanic,04/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +63170,72814,66000,Probation,Pallai,Stephanie,NULL,Female,Hispanic,04/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +63177,72816,66002,DRRD,McBurrows,Zackery,NULL,Male,African-American,04/05/88,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,5/2/14 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +63177,72816,66002,DRRD,McBurrows,Zackery,NULL,Male,African-American,04/05/88,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,5/2/14 0:00,2,Medium,8,Risk of Recidivism,0.14,7,Medium,New,1,0 +63177,72816,66002,DRRD,McBurrows,Zackery,NULL,Male,African-American,04/05/88,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,5/2/14 0:00,2,Medium,18,Risk of Failure to Appear,22,4,Low,New,1,0 +63144,72781,65970,PRETRIAL,Nager,Carly,NULL,Male,Caucasian,04/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +63144,72781,65970,PRETRIAL,Nager,Carly,NULL,Male,Caucasian,04/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +63144,72781,65970,PRETRIAL,Nager,Carly,NULL,Male,Caucasian,04/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63158,72798,65986,PRETRIAL,SCREEN,DAVID,NULL,Male,African-American,10/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.49,3,Low,New,1,0 +63158,72798,65986,PRETRIAL,SCREEN,DAVID,NULL,Male,African-American,10/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +63158,72798,65986,PRETRIAL,SCREEN,DAVID,NULL,Male,African-American,10/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63181,72819,66004,Probation,French,James,David,Male,Caucasian,04/24/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +63181,72819,66004,Probation,French,James,David,Male,Caucasian,04/24/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +63181,72819,66004,Probation,French,James,David,Male,Caucasian,04/24/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +55767,72802,65990,Probation,Altamiranozarate,Cristian,NULL,Male,Hispanic,12/05/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/2/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +55767,72802,65990,Probation,Altamiranozarate,Cristian,NULL,Male,Hispanic,12/05/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +55767,72802,65990,Probation,Altamiranozarate,Cristian,NULL,Male,Hispanic,12/05/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63184,72823,66008,Probation,Bennie,Christina,NULL,Female,African-American,12/05/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +63184,72823,66008,Probation,Bennie,Christina,NULL,Female,African-American,12/05/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,New,1,0 +63184,72823,66008,Probation,Bennie,Christina,NULL,Female,African-American,12/05/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63163,72804,65992,Probation,Salomon,Juan,NULL,Male,Hispanic,11/12/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/2/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +63163,72804,65992,Probation,Salomon,Juan,NULL,Male,Hispanic,11/12/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/2/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +63163,72804,65992,Probation,Salomon,Juan,NULL,Male,Hispanic,11/12/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63168,72812,65998,PRETRIAL,Deharde,John,NULL,Male,Caucasian,02/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/2/14 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +63168,72812,65998,PRETRIAL,Deharde,John,NULL,Male,Caucasian,02/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/2/14 0:00,4,High,8,Risk of Recidivism,0.48,9,High,New,1,0 +63168,72812,65998,PRETRIAL,Deharde,John,NULL,Male,Caucasian,02/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/2/14 0:00,4,High,18,Risk of Failure to Appear,35,10,High,New,1,0 +63157,72796,65984,Probation,Miller,Wallcott,NULL,Male,African-American,02/22/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +63157,72796,65984,Probation,Miller,Wallcott,NULL,Male,African-American,02/22/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +63157,72796,65984,Probation,Miller,Wallcott,NULL,Male,African-American,02/22/55,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63146,72783,65972,PRETRIAL,Williams,Diana,NULL,Female,African-American,07/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +63146,72783,65972,PRETRIAL,Williams,Diana,NULL,Female,African-American,07/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +63146,72783,65972,PRETRIAL,Williams,Diana,NULL,Female,African-American,07/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63179,72817,66003,Probation,Hall,Andrew,Scot,Male,Caucasian,12/07/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +63179,72817,66003,Probation,Hall,Andrew,Scot,Male,Caucasian,12/07/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +63179,72817,66003,Probation,Hall,Andrew,Scot,Male,Caucasian,12/07/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63150,72788,65977,PRETRIAL,Marts,Tierra,NULL,Female,African-American,08/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +63150,72788,65977,PRETRIAL,Marts,Tierra,NULL,Female,African-American,08/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +63150,72788,65977,PRETRIAL,Marts,Tierra,NULL,Female,African-American,08/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63153,72791,65980,PRETRIAL,Ivery,Ebony,Shelen,Female,African-American,02/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +63153,72791,65980,PRETRIAL,Ivery,Ebony,Shelen,Female,African-American,02/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +63153,72791,65980,PRETRIAL,Ivery,Ebony,Shelen,Female,African-American,02/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/2/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63166,72809,65996,Probation,Sandoval,Jorge,NULL,Male,Hispanic,02/18/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +63166,72809,65996,Probation,Sandoval,Jorge,NULL,Male,Hispanic,02/18/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +63166,72809,65996,Probation,Sandoval,Jorge,NULL,Male,Hispanic,02/18/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/2/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63186,72825,66010,PRETRIAL,Sias,John,NULL,Male,Caucasian,10/22/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +63186,72825,66010,PRETRIAL,Sias,John,NULL,Male,Caucasian,10/22/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +63186,72825,66010,PRETRIAL,Sias,John,NULL,Male,Caucasian,10/22/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +23282,72828,22468,PRETRIAL,KING,BRITTANY,NULL,Female,African-American,03/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,Copy,1,0 +23282,72828,22468,PRETRIAL,KING,BRITTANY,NULL,Female,African-American,03/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,Copy,1,0 +23282,72828,22468,PRETRIAL,KING,BRITTANY,NULL,Female,African-American,03/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +63185,72824,66009,PRETRIAL,Paul,Clemin,NULL,Male,African-American,12/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,4,High,7,Risk of Violence,-1.17,8,High,New,1,0 +63185,72824,66009,PRETRIAL,Paul,Clemin,NULL,Male,African-American,12/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,4,High,8,Risk of Recidivism,0.32,9,High,New,1,0 +63185,72824,66009,PRETRIAL,Paul,Clemin,NULL,Male,African-American,12/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63187,72827,66011,PRETRIAL,mortimer,elvens,NULL,Male,Other,01/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,2,Medium,7,Risk of Violence,-2.69,2,Low,New,1,0 +63187,72827,66011,PRETRIAL,mortimer,elvens,NULL,Male,Other,01/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +63187,72827,66011,PRETRIAL,mortimer,elvens,NULL,Male,Other,01/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +31079,72826,30092,PRETRIAL,Francis,Leonard,NULL,Male,African-American,06/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,4,High,7,Risk of Violence,-1.13,8,High,Copy,1,0 +31079,72826,30092,PRETRIAL,Francis,Leonard,NULL,Male,African-American,06/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,4,High,8,Risk of Recidivism,0.11,8,High,Copy,1,0 +31079,72826,30092,PRETRIAL,Francis,Leonard,NULL,Male,African-American,06/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/3/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +63189,72834,66015,PRETRIAL,EKWERE,EMAEYAK,EMEM,Male,African-American,06/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +63189,72834,66015,PRETRIAL,EKWERE,EMAEYAK,EMEM,Male,African-American,06/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +63189,72834,66015,PRETRIAL,EKWERE,EMAEYAK,EMEM,Male,African-American,06/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +24532,72831,66012,PRETRIAL,Cassidy,Telise,NULL,Female,Caucasian,06/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +24532,72831,66012,PRETRIAL,Cassidy,Telise,NULL,Female,Caucasian,06/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.03,8,High,New,1,0 +24532,72831,66012,PRETRIAL,Cassidy,Telise,NULL,Female,Caucasian,06/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +63192,72839,66018,PRETRIAL,CARUSO,JEFFREY,ALLEN,Male,Caucasian,03/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,Copy,1,0 +63192,72839,66018,PRETRIAL,CARUSO,JEFFREY,ALLEN,Male,Caucasian,03/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,Copy,1,0 +63192,72839,66018,PRETRIAL,CARUSO,JEFFREY,ALLEN,Male,Caucasian,03/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +61688,72829,64272,PRETRIAL,Farley,Leroy,NULL,Male,African-American,07/26/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,2,Medium,7,Risk of Violence,-3.15,1,Low,Copy,1,0 +61688,72829,64272,PRETRIAL,Farley,Leroy,NULL,Male,African-American,07/26/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,Copy,1,0 +61688,72829,64272,PRETRIAL,Farley,Leroy,NULL,Male,African-American,07/26/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +61660,72836,64242,PRETRIAL,Mims,Derrick,NULL,Male,African-American,03/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,Copy,1,0 +61660,72836,64242,PRETRIAL,Mims,Derrick,NULL,Male,African-American,03/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,Copy,1,0 +61660,72836,64242,PRETRIAL,Mims,Derrick,NULL,Male,African-American,03/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +58961,72832,66013,PRETRIAL,CORKER,BRIAN,MAURICE,Male,African-American,07/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +58961,72832,66013,PRETRIAL,CORKER,BRIAN,MAURICE,Male,African-American,07/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +58961,72832,66013,PRETRIAL,CORKER,BRIAN,MAURICE,Male,African-American,07/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63190,72835,66016,PRETRIAL,Chismar,Jacob,NULL,Male,Caucasian,11/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/4/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +63190,72835,66016,PRETRIAL,Chismar,Jacob,NULL,Male,Caucasian,11/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/4/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +63190,72835,66016,PRETRIAL,Chismar,Jacob,NULL,Male,Caucasian,11/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63191,72837,66017,PRETRIAL,MOONEY,EMILY,NULL,Female,Caucasian,07/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +63191,72837,66017,PRETRIAL,MOONEY,EMILY,NULL,Female,Caucasian,07/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +63191,72837,66017,PRETRIAL,MOONEY,EMILY,NULL,Female,Caucasian,07/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63193,72840,66019,PRETRIAL,Seays,Jeffery,Bernard,Male,African-American,04/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,New,1,0 +63193,72840,66019,PRETRIAL,Seays,Jeffery,Bernard,Male,African-American,04/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +63193,72840,66019,PRETRIAL,Seays,Jeffery,Bernard,Male,African-American,04/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63188,72833,66014,PRETRIAL,EADY,JAMES,NULL,Male,African-American,02/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +63188,72833,66014,PRETRIAL,EADY,JAMES,NULL,Male,African-American,02/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +63188,72833,66014,PRETRIAL,EADY,JAMES,NULL,Male,African-American,02/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +31991,72830,30987,PRETRIAL,Wiggins,Lawrence,NULL,Male,African-American,08/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,Copy,1,0 +31991,72830,30987,PRETRIAL,Wiggins,Lawrence,NULL,Male,African-American,08/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,Copy,1,0 +31991,72830,30987,PRETRIAL,Wiggins,Lawrence,NULL,Male,African-American,08/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +63216,72864,66042,Probation,Morley,Michael,NULL,Male,Caucasian,07/06/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +63216,72864,66042,Probation,Morley,Michael,NULL,Male,Caucasian,07/06/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +63216,72864,66042,Probation,Morley,Michael,NULL,Male,Caucasian,07/06/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63203,72851,66030,PRETRIAL,Wispe,Hernan,Manuel,Male,Caucasian,03/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +63203,72851,66030,PRETRIAL,Wispe,Hernan,Manuel,Male,Caucasian,03/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +63203,72851,66030,PRETRIAL,Wispe,Hernan,Manuel,Male,Caucasian,03/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63237,72885,66062,PRETRIAL,Perkins,Travis,George,Male,Caucasian,07/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +63237,72885,66062,PRETRIAL,Perkins,Travis,George,Male,Caucasian,07/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +63237,72885,66062,PRETRIAL,Perkins,Travis,George,Male,Caucasian,07/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63212,72859,66038,PRETRIAL,Bryant,Stephanie,NULL,Female,Caucasian,04/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,5/5/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +63212,72859,66038,PRETRIAL,Bryant,Stephanie,NULL,Female,Caucasian,04/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,5/5/14 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +63212,72859,66038,PRETRIAL,Bryant,Stephanie,NULL,Female,Caucasian,04/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +63231,72877,66054,Probation,Hatcher,Cassandra,NULL,Female,African-American,08/21/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +63231,72877,66054,Probation,Hatcher,Cassandra,NULL,Female,African-American,08/21/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +63231,72877,66054,Probation,Hatcher,Cassandra,NULL,Female,African-American,08/21/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63209,72856,66035,PRETRIAL,Howe,Richard,Edward,Male,Caucasian,09/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/5/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +63209,72856,66035,PRETRIAL,Howe,Richard,Edward,Male,Caucasian,09/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/5/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +63209,72856,66035,PRETRIAL,Howe,Richard,Edward,Male,Caucasian,09/15/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63219,72867,66045,PRETRIAL,SIMON,STEPHANIE,NULL,Female,Caucasian,03/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +63219,72867,66045,PRETRIAL,SIMON,STEPHANIE,NULL,Female,Caucasian,03/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +63219,72867,66045,PRETRIAL,SIMON,STEPHANIE,NULL,Female,Caucasian,03/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63224,72869,66047,PRETRIAL,Sisson,Kevin,NULL,Male,Caucasian,01/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +63224,72869,66047,PRETRIAL,Sisson,Kevin,NULL,Male,Caucasian,01/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +63224,72869,66047,PRETRIAL,Sisson,Kevin,NULL,Male,Caucasian,01/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63199,72846,66025,PRETRIAL,Arevalo Ruiz,Marcela,NULL,Female,Hispanic,10/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +63199,72846,66025,PRETRIAL,Arevalo Ruiz,Marcela,NULL,Female,Hispanic,10/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-1.43,2,Low,New,1,0 +63199,72846,66025,PRETRIAL,Arevalo Ruiz,Marcela,NULL,Female,Hispanic,10/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63200,72848,66027,PRETRIAL,PAGAN,GUY,N,Male,Caucasian,11/16/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/5/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +63200,72848,66027,PRETRIAL,PAGAN,GUY,N,Male,Caucasian,11/16/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/5/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +63200,72848,66027,PRETRIAL,PAGAN,GUY,N,Male,Caucasian,11/16/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63236,72882,66059,Probation,Keough,Linda,NULL,Female,Caucasian,02/10/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/5/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +63236,72882,66059,Probation,Keough,Linda,NULL,Female,Caucasian,02/10/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/5/14 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +63236,72882,66059,Probation,Keough,Linda,NULL,Female,Caucasian,02/10/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +63207,72854,66033,PRETRIAL,Johnson,Terry,NULL,Male,African-American,08/22/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +63207,72854,66033,PRETRIAL,Johnson,Terry,NULL,Male,African-American,08/22/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +63207,72854,66033,PRETRIAL,Johnson,Terry,NULL,Male,African-American,08/22/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +30482,72861,29440,PRETRIAL,PALNCHER,JONATIN,NULL,Male,African-American,12/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,Copy,1,0 +30482,72861,29440,PRETRIAL,PALNCHER,JONATIN,NULL,Male,African-American,12/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,Copy,1,0 +30482,72861,29440,PRETRIAL,PALNCHER,JONATIN,NULL,Male,African-American,12/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +63195,72842,66021,PRETRIAL,CAMPBELL,PATRICK,BRIAN,Male,Caucasian,10/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.29,1,Low,New,1,0 +63195,72842,66021,PRETRIAL,CAMPBELL,PATRICK,BRIAN,Male,Caucasian,10/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +63195,72842,66021,PRETRIAL,CAMPBELL,PATRICK,BRIAN,Male,Caucasian,10/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63197,72844,66023,PRETRIAL,Deleon,Felix,NULL,Male,Hispanic,12/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +63197,72844,66023,PRETRIAL,Deleon,Felix,NULL,Male,Hispanic,12/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +63197,72844,66023,PRETRIAL,Deleon,Felix,NULL,Male,Hispanic,12/09/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63215,72863,66041,Probation,gutierrez,julian,NULL,Male,Hispanic,05/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/5/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +63215,72863,66041,Probation,gutierrez,julian,NULL,Male,Hispanic,05/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/5/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +63215,72863,66041,Probation,gutierrez,julian,NULL,Male,Hispanic,05/03/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63227,72872,66050,PRETRIAL,UMANA-WILLIAMS,LUIS,NULL,Male,Hispanic,12/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/5/14 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +63227,72872,66050,PRETRIAL,UMANA-WILLIAMS,LUIS,NULL,Male,Hispanic,12/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/5/14 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +63227,72872,66050,PRETRIAL,UMANA-WILLIAMS,LUIS,NULL,Male,Hispanic,12/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63201,72849,66028,PRETRIAL,MENDEZ,BASIL,NULL,Male,African-American,02/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/5/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +63201,72849,66028,PRETRIAL,MENDEZ,BASIL,NULL,Male,African-American,02/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/5/14 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +63201,72849,66028,PRETRIAL,MENDEZ,BASIL,NULL,Male,African-American,02/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63233,72879,66056,Probation,Allen,Scot,NULL,Male,Caucasian,11/11/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/5/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +63233,72879,66056,Probation,Allen,Scot,NULL,Male,Caucasian,11/11/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/5/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +63233,72879,66056,Probation,Allen,Scot,NULL,Male,Caucasian,11/11/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63206,72853,66032,Probation,Harris,Samantha,NULL,Female,Caucasian,08/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +63206,72853,66032,Probation,Harris,Samantha,NULL,Female,Caucasian,08/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,New,1,0 +63206,72853,66032,Probation,Harris,Samantha,NULL,Female,Caucasian,08/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63211,72858,66037,Probation,Martin,James,Christopher,Male,Hispanic,12/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/5/14 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +63211,72858,66037,Probation,Martin,James,Christopher,Male,Hispanic,12/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +63211,72858,66037,Probation,Martin,James,Christopher,Male,Hispanic,12/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/5/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +36365,72884,66061,PRETRIAL,allen,tommy,NULL,Male,African-American,11/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +36365,72884,66061,PRETRIAL,allen,tommy,NULL,Male,African-American,11/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +36365,72884,66061,PRETRIAL,allen,tommy,NULL,Male,African-American,11/03/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +63196,72843,66022,PRETRIAL,Schiano,Cindy,NULL,Female,Caucasian,12/14/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/5/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +63196,72843,66022,PRETRIAL,Schiano,Cindy,NULL,Female,Caucasian,12/14/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/5/14 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +63196,72843,66022,PRETRIAL,Schiano,Cindy,NULL,Female,Caucasian,12/14/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +63202,72850,66029,PRETRIAL,Sisson,Brianna,NULL,Female,Caucasian,04/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +63202,72850,66029,PRETRIAL,Sisson,Brianna,NULL,Female,Caucasian,04/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +63202,72850,66029,PRETRIAL,Sisson,Brianna,NULL,Female,Caucasian,04/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63210,72857,66036,Probation,Barra-Rivera,ernesto,NULL,Male,Hispanic,11/07/62,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/5/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +63210,72857,66036,Probation,Barra-Rivera,ernesto,NULL,Male,Hispanic,11/07/62,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/5/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +63210,72857,66036,Probation,Barra-Rivera,ernesto,NULL,Male,Hispanic,11/07/62,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63226,72871,66049,Probation,mcconnell,valeri,NULL,Female,Caucasian,02/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +63226,72871,66049,Probation,mcconnell,valeri,NULL,Female,Caucasian,02/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +63226,72871,66049,Probation,mcconnell,valeri,NULL,Female,Caucasian,02/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63234,72880,66057,Probation,Neal,Johnny,NULL,Male,African-American,04/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +63234,72880,66057,Probation,Neal,Johnny,NULL,Male,African-American,04/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +63234,72880,66057,Probation,Neal,Johnny,NULL,Male,African-American,04/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63232,72878,66055,Probation,marshalleck,kirkland,NULL,Male,African-American,10/20/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/5/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +63232,72878,66055,Probation,marshalleck,kirkland,NULL,Male,African-American,10/20/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/5/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +63232,72878,66055,Probation,marshalleck,kirkland,NULL,Male,African-American,10/20/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63198,72845,66024,PRETRIAL,Hisler,Samantha,NULL,Female,Native American,03/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/5/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +63198,72845,66024,PRETRIAL,Hisler,Samantha,NULL,Female,Native American,03/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/5/14 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +63198,72845,66024,PRETRIAL,Hisler,Samantha,NULL,Female,Native American,03/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63194,72841,66020,PRETRIAL,Lewis,Stephon,NULL,Male,African-American,08/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +63194,72841,66020,PRETRIAL,Lewis,Stephon,NULL,Male,African-American,08/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +63194,72841,66020,PRETRIAL,Lewis,Stephon,NULL,Male,African-American,08/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63214,72862,66040,Probation,Lpowe,Joseph,Alexander,Male,Caucasian,12/10/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +63214,72862,66040,Probation,Lpowe,Joseph,Alexander,Male,Caucasian,12/10/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +63214,72862,66040,Probation,Lpowe,Joseph,Alexander,Male,Caucasian,12/10/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63218,72866,66044,PRETRIAL,Davis,Delroy,NULL,Male,African-American,12/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/5/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +63218,72866,66044,PRETRIAL,Davis,Delroy,NULL,Male,African-American,12/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/5/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +63218,72866,66044,PRETRIAL,Davis,Delroy,NULL,Male,African-American,12/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +25259,72883,66060,PRETRIAL,WILLIAMS,CONSTANCE,NULL,Female,African-American,02/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,New,1,0 +25259,72883,66060,PRETRIAL,WILLIAMS,CONSTANCE,NULL,Female,African-American,02/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,8,High,New,1,0 +25259,72883,66060,PRETRIAL,WILLIAMS,CONSTANCE,NULL,Female,African-American,02/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +15533,72868,66046,Probation,graham,michael,NULL,Male,Caucasian,03/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/5/14 0:00,2,Medium,7,Risk of Violence,-2.57,2,Low,New,1,0 +15533,72868,66046,Probation,graham,michael,NULL,Male,Caucasian,03/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +15533,72868,66046,Probation,graham,michael,NULL,Male,Caucasian,03/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/5/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63230,72876,66053,Probation,Dejesus,Carismilis,NULL,Female,Hispanic,05/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +63230,72876,66053,Probation,Dejesus,Carismilis,NULL,Female,Hispanic,05/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +63230,72876,66053,Probation,Dejesus,Carismilis,NULL,Female,Hispanic,05/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63204,72852,66031,PRETRIAL,KELLY,WILLIAM,NULL,Male,Caucasian,12/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +63204,72852,66031,PRETRIAL,KELLY,WILLIAM,NULL,Male,Caucasian,12/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +63204,72852,66031,PRETRIAL,KELLY,WILLIAM,NULL,Male,Caucasian,12/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63208,72855,66034,Probation,barbour,david,NULL,Male,Caucasian,07/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +63208,72855,66034,Probation,barbour,david,NULL,Male,Caucasian,07/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +63208,72855,66034,Probation,barbour,david,NULL,Male,Caucasian,07/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63228,72873,66051,Probation,Avila,Fany,Carolina,Female,Hispanic,06/27/73,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,5/5/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +63228,72873,66051,Probation,Avila,Fany,Carolina,Female,Hispanic,06/27/73,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,5/5/14 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +63228,72873,66051,Probation,Avila,Fany,Carolina,Female,Hispanic,06/27/73,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63213,72860,66039,Probation,PRYCE,PAUL,D,Male,African-American,10/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/5/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +63213,72860,66039,Probation,PRYCE,PAUL,D,Male,African-American,10/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/5/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +63213,72860,66039,Probation,PRYCE,PAUL,D,Male,African-American,10/02/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +4614,72847,66026,PRETRIAL,mack,jaruis,j,Male,African-American,03/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +4614,72847,66026,PRETRIAL,mack,jaruis,j,Male,African-American,03/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,4,High,8,Risk of Recidivism,0.38,9,High,New,1,0 +4614,72847,66026,PRETRIAL,mack,jaruis,j,Male,African-American,03/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/5/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63235,72881,66058,Probation,SUAREZ,DANIEL,J,Male,Hispanic,12/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +63235,72881,66058,Probation,SUAREZ,DANIEL,J,Male,Hispanic,12/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +63235,72881,66058,Probation,SUAREZ,DANIEL,J,Male,Hispanic,12/05/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/5/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63254,72915,66083,PRETRIAL,Davis,Deandre,NULL,Male,African-American,07/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,Copy,1,0 +63254,72915,66083,PRETRIAL,Davis,Deandre,NULL,Male,African-American,07/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,Copy,1,0 +63254,72915,66083,PRETRIAL,Davis,Deandre,NULL,Male,African-American,07/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +63245,72894,66071,PRETRIAL,Pharin,Ilosela,NULL,Female,Other,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +63245,72894,66071,PRETRIAL,Pharin,Ilosela,NULL,Female,Other,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +63245,72894,66071,PRETRIAL,Pharin,Ilosela,NULL,Female,Other,12/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62807,72902,65574,PRETRIAL,Jones,Ashley,NULL,Female,African-American,07/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,Copy,1,0 +62807,72902,65574,PRETRIAL,Jones,Ashley,NULL,Female,African-American,07/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,Copy,1,0 +62807,72902,65574,PRETRIAL,Jones,Ashley,NULL,Female,African-American,07/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +63257,72920,66086,Probation,Tipton,Lesli,NULL,Female,Caucasian,07/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +63257,72920,66086,Probation,Tipton,Lesli,NULL,Female,Caucasian,07/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +63257,72920,66086,Probation,Tipton,Lesli,NULL,Female,Caucasian,07/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58817,72910,66082,PRETRIAL,Mcphee,Ebony,NULL,Female,African-American,10/04/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +58817,72910,66082,PRETRIAL,Mcphee,Ebony,NULL,Female,African-American,10/04/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +58817,72910,66082,PRETRIAL,Mcphee,Ebony,NULL,Female,African-American,10/04/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63248,72897,66074,PRETRIAL,Alvarado,Edwin,NULL,Male,Hispanic,10/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +63248,72897,66074,PRETRIAL,Alvarado,Edwin,NULL,Male,Hispanic,10/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +63248,72897,66074,PRETRIAL,Alvarado,Edwin,NULL,Male,Hispanic,10/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +56689,72918,58736,PRETRIAL,Hollis,David,NULL,Male,African-American,05/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,Copy,1,0 +56689,72918,58736,PRETRIAL,Hollis,David,NULL,Male,African-American,05/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,Copy,1,0 +56689,72918,58736,PRETRIAL,Hollis,David,NULL,Male,African-American,05/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +63240,72889,66066,PRETRIAL,MELICE,SAMUEL,NULL,Male,Caucasian,06/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/6/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +63240,72889,66066,PRETRIAL,MELICE,SAMUEL,NULL,Male,Caucasian,06/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +63240,72889,66066,PRETRIAL,MELICE,SAMUEL,NULL,Male,Caucasian,06/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54199,72904,55781,PRETRIAL,MCKINNEY,TERRANCE,NULL,Male,African-American,01/08/89,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,4,High,7,Risk of Violence,-0.65,9,High,Copy,1,0 +54199,72904,55781,PRETRIAL,MCKINNEY,TERRANCE,NULL,Male,African-American,01/08/89,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,4,High,8,Risk of Recidivism,0.19,8,High,Copy,1,0 +54199,72904,55781,PRETRIAL,MCKINNEY,TERRANCE,NULL,Male,African-American,01/08/89,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +63247,72896,66073,PRETRIAL,Wooten,Christopher,NULL,Male,African-American,05/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +63247,72896,66073,PRETRIAL,Wooten,Christopher,NULL,Male,African-American,05/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +63247,72896,66073,PRETRIAL,Wooten,Christopher,NULL,Male,African-American,05/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63239,72887,66064,PRETRIAL,Barnes,Fitzroy,NULL,Male,Other,12/13/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/6/14 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +63239,72887,66064,PRETRIAL,Barnes,Fitzroy,NULL,Male,Other,12/13/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/6/14 0:00,1,Low,8,Risk of Recidivism,-2.84,1,Low,New,1,0 +63239,72887,66064,PRETRIAL,Barnes,Fitzroy,NULL,Male,Other,12/13/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63243,72892,66069,PRETRIAL,Correggio,Christopher,Daniel,Male,Caucasian,09/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +63243,72892,66069,PRETRIAL,Correggio,Christopher,Daniel,Male,Caucasian,09/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +63243,72892,66069,PRETRIAL,Correggio,Christopher,Daniel,Male,Caucasian,09/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63255,72917,66084,Probation,hicks,elton,NULL,Male,African-American,07/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +63255,72917,66084,Probation,hicks,elton,NULL,Male,African-American,07/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +63255,72917,66084,Probation,hicks,elton,NULL,Male,African-American,07/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +30800,72899,66076,PRETRIAL,TASCILLO,ADRAIN,SEBASTIAN,Male,Caucasian,06/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.01,4,Low,New,1,0 +30800,72899,66076,PRETRIAL,TASCILLO,ADRAIN,SEBASTIAN,Male,Caucasian,06/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +30800,72899,66076,PRETRIAL,TASCILLO,ADRAIN,SEBASTIAN,Male,Caucasian,06/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +37680,72922,66088,PRETRIAL,GUERRIER,JEAN,NULL,Male,African-American,03/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +37680,72922,66088,PRETRIAL,GUERRIER,JEAN,NULL,Male,African-American,03/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +37680,72922,66088,PRETRIAL,GUERRIER,JEAN,NULL,Male,African-American,03/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63246,72895,66072,PRETRIAL,Beauplan,Marc,E,Male,Other,01/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +63246,72895,66072,PRETRIAL,Beauplan,Marc,E,Male,Other,01/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +63246,72895,66072,PRETRIAL,Beauplan,Marc,E,Male,Other,01/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63253,72909,66081,PRETRIAL,FIGUEROA,ALBERTO,NULL,Male,Hispanic,07/01/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +63253,72909,66081,PRETRIAL,FIGUEROA,ALBERTO,NULL,Male,Hispanic,07/01/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +63253,72909,66081,PRETRIAL,FIGUEROA,ALBERTO,NULL,Male,Hispanic,07/01/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63241,72888,66065,PRETRIAL,Llewelyn-Miller,Jason,NULL,Male,Other,02/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +63241,72888,66065,PRETRIAL,Llewelyn-Miller,Jason,NULL,Male,Other,02/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +63241,72888,66065,PRETRIAL,Llewelyn-Miller,Jason,NULL,Male,Other,02/10/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63242,72891,66068,PRETRIAL,ULLOA,RAFAEL,HERMOGENES,Male,Caucasian,10/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +63242,72891,66068,PRETRIAL,ULLOA,RAFAEL,HERMOGENES,Male,Caucasian,10/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +63242,72891,66068,PRETRIAL,ULLOA,RAFAEL,HERMOGENES,Male,Caucasian,10/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63250,72905,66078,Probation,CHERISMA,TOBY,NULL,Male,African-American,05/25/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +63250,72905,66078,Probation,CHERISMA,TOBY,NULL,Male,African-American,05/25/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +63250,72905,66078,Probation,CHERISMA,TOBY,NULL,Male,African-American,05/25/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63252,72907,66080,Probation,costa,andrew,NULL,Male,Hispanic,06/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +63252,72907,66080,Probation,costa,andrew,NULL,Male,Hispanic,06/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +63252,72907,66080,Probation,costa,andrew,NULL,Male,Hispanic,06/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50716,72921,66087,PRETRIAL,JELICKS,MICHELLE,DIANE,Female,Caucasian,01/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +50716,72921,66087,PRETRIAL,JELICKS,MICHELLE,DIANE,Female,Caucasian,01/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +50716,72921,66087,PRETRIAL,JELICKS,MICHELLE,DIANE,Female,Caucasian,01/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,29,9,High,New,1,0 +63238,72886,66063,PRETRIAL,BARTOLINO,DAVID,J,Male,Caucasian,07/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +63238,72886,66063,PRETRIAL,BARTOLINO,DAVID,J,Male,Caucasian,07/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +63238,72886,66063,PRETRIAL,BARTOLINO,DAVID,J,Male,Caucasian,07/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63244,72893,66070,PRETRIAL,Falcon-Leon,Alexis,NULL,Male,Caucasian,05/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +63244,72893,66070,PRETRIAL,Falcon-Leon,Alexis,NULL,Male,Caucasian,05/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +63244,72893,66070,PRETRIAL,Falcon-Leon,Alexis,NULL,Male,Caucasian,05/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63249,72900,66077,PRETRIAL,Johnson,Ralph,NULL,Female,African-American,10/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +63249,72900,66077,PRETRIAL,Johnson,Ralph,NULL,Female,African-American,10/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +63249,72900,66077,PRETRIAL,Johnson,Ralph,NULL,Female,African-American,10/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56689,64726,58736,PRETRIAL,Hollis,David,NULL,Male,African-American,05/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +56689,64726,58736,PRETRIAL,Hollis,David,NULL,Male,African-American,05/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +56689,64726,58736,PRETRIAL,Hollis,David,NULL,Male,African-American,05/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +21857,72911,21018,PRETRIAL,Allen,Eric,NULL,Male,African-American,08/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/14 0:00,4,High,7,Risk of Violence,-0.91,9,High,Copy,1,0 +21857,72911,21018,PRETRIAL,Allen,Eric,NULL,Male,African-American,08/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/14 0:00,4,High,8,Risk of Recidivism,0.12,8,High,Copy,1,0 +21857,72911,21018,PRETRIAL,Allen,Eric,NULL,Male,African-American,08/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/6/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +19198,72890,66067,PRETRIAL,WEAVER,HERMESHA,A,Female,African-American,11/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +19198,72890,66067,PRETRIAL,WEAVER,HERMESHA,A,Female,African-American,11/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +19198,72890,66067,PRETRIAL,WEAVER,HERMESHA,A,Female,African-American,11/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63251,72906,66079,Probation,Scire,Fredrick,NULL,Male,Caucasian,10/09/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +63251,72906,66079,Probation,Scire,Fredrick,NULL,Male,Caucasian,10/09/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +63251,72906,66079,Probation,Scire,Fredrick,NULL,Male,Caucasian,10/09/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63256,72919,66085,Probation,Crooks,Sade,alexis,Female,African-American,10/16/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/14 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +63256,72919,66085,Probation,Crooks,Sade,alexis,Female,African-American,10/16/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +63256,72919,66085,Probation,Crooks,Sade,alexis,Female,African-American,10/16/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/6/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +33837,72898,66075,PRETRIAL,Ruel,Claude,NULL,Male,Caucasian,01/15/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.06,1,Low,New,1,0 +33837,72898,66075,PRETRIAL,Ruel,Claude,NULL,Male,Caucasian,01/15/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +33837,72898,66075,PRETRIAL,Ruel,Claude,NULL,Male,Caucasian,01/15/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +63265,72932,66098,PRETRIAL,Booth,Tashia,Sadino,Female,African-American,05/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +63265,72932,66098,PRETRIAL,Booth,Tashia,Sadino,Female,African-American,05/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +63265,72932,66098,PRETRIAL,Booth,Tashia,Sadino,Female,African-American,05/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63258,72924,66090,PRETRIAL,BALENTINE,JESSALYN,CODY,Female,Other,02/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +63258,72924,66090,PRETRIAL,BALENTINE,JESSALYN,CODY,Female,Other,02/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +63258,72924,66090,PRETRIAL,BALENTINE,JESSALYN,CODY,Female,Other,02/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59266,72927,66093,PRETRIAL,thorpe,keith,NULL,Male,African-American,07/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,4,High,7,Risk of Violence,-0.71,9,High,New,1,0 +59266,72927,66093,PRETRIAL,thorpe,keith,NULL,Male,African-American,07/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,4,High,8,Risk of Recidivism,0.24,8,High,New,1,0 +59266,72927,66093,PRETRIAL,thorpe,keith,NULL,Male,African-American,07/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63276,72945,66110,Probation,Cooper,Tony,Curtis,Male,Hispanic,10/16/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/7/14 0:00,4,High,7,Risk of Violence,-0.67,9,High,New,1,0 +63276,72945,66110,Probation,Cooper,Tony,Curtis,Male,Hispanic,10/16/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/7/14 0:00,4,High,8,Risk of Recidivism,1.69,10,High,New,1,0 +63276,72945,66110,Probation,Cooper,Tony,Curtis,Male,Hispanic,10/16/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/7/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63272,72940,66105,Probation,WRIGHT,PAUL,S,Male,African-American,08/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +63272,72940,66105,Probation,WRIGHT,PAUL,S,Male,African-American,08/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +63272,72940,66105,Probation,WRIGHT,PAUL,S,Male,African-American,08/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +18144,72961,66124,PRETRIAL,young,henry,NULL,Male,African-American,12/08/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +18144,72961,66124,PRETRIAL,young,henry,NULL,Male,African-American,12/08/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +18144,72961,66124,PRETRIAL,young,henry,NULL,Male,African-American,12/08/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63279,72948,66113,PRETRIAL,Holthe,Carl,NULL,Male,Caucasian,12/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +63279,72948,66113,PRETRIAL,Holthe,Carl,NULL,Male,Caucasian,12/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +63279,72948,66113,PRETRIAL,Holthe,Carl,NULL,Male,Caucasian,12/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63268,72935,66101,Probation,HOLLOWAY,ERIC,TODD,Male,Caucasian,09/10/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/7/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +63268,72935,66101,Probation,HOLLOWAY,ERIC,TODD,Male,Caucasian,09/10/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/7/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +63268,72935,66101,Probation,HOLLOWAY,ERIC,TODD,Male,Caucasian,09/10/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63270,72937,66103,Probation,Lespinasse,Galdyr,NULL,Male,African-American,01/27/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +63270,72937,66103,Probation,Lespinasse,Galdyr,NULL,Male,African-American,01/27/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +63270,72937,66103,Probation,Lespinasse,Galdyr,NULL,Male,African-American,01/27/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63274,72942,66107,Probation,dixon,chalanta,NULL,Female,African-American,11/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +63274,72942,66107,Probation,dixon,chalanta,NULL,Female,African-American,11/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +63274,72942,66107,Probation,dixon,chalanta,NULL,Female,African-American,11/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63275,72944,66109,Probation,LOWERY,FELICIA,DENISE,Female,African-American,06/09/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +63275,72944,66109,Probation,LOWERY,FELICIA,DENISE,Female,African-American,06/09/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +63275,72944,66109,Probation,LOWERY,FELICIA,DENISE,Female,African-American,06/09/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +56551,72958,66121,PRETRIAL,Baptista,Christopher,Andrew,Male,Hispanic,09/20/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/7/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +56551,72958,66121,PRETRIAL,Baptista,Christopher,Andrew,Male,Hispanic,09/20/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/7/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +56551,72958,66121,PRETRIAL,Baptista,Christopher,Andrew,Male,Hispanic,09/20/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63283,72956,66119,Probation,shutts,jason,NULL,Male,Caucasian,10/16/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +63283,72956,66119,Probation,shutts,jason,NULL,Male,Caucasian,10/16/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +63283,72956,66119,Probation,shutts,jason,NULL,Male,Caucasian,10/16/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63260,72926,66092,PRETRIAL,Straussberger,Karen,NULL,Female,Caucasian,08/19/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/7/14 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +63260,72926,66092,PRETRIAL,Straussberger,Karen,NULL,Female,Caucasian,08/19/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +63260,72926,66092,PRETRIAL,Straussberger,Karen,NULL,Female,Caucasian,08/19/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/7/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +63281,72951,66115,PRETRIAL,Gerard,Kenneth,James,Male,Caucasian,09/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,5/7/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +63281,72951,66115,PRETRIAL,Gerard,Kenneth,James,Male,Caucasian,09/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,5/7/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +63281,72951,66115,PRETRIAL,Gerard,Kenneth,James,Male,Caucasian,09/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55113,72960,66123,PRETRIAL,VALENTINE,ALICIA,SIMONE,Female,African-American,01/14/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +55113,72960,66123,PRETRIAL,VALENTINE,ALICIA,SIMONE,Female,African-American,01/14/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,4,High,8,Risk of Recidivism,-0.13,8,High,New,1,0 +55113,72960,66123,PRETRIAL,VALENTINE,ALICIA,SIMONE,Female,African-American,01/14/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63263,72930,66096,PRETRIAL,Knowles,Marquise,Reynaul,Male,African-American,09/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +63263,72930,66096,PRETRIAL,Knowles,Marquise,Reynaul,Male,African-American,09/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +63263,72930,66096,PRETRIAL,Knowles,Marquise,Reynaul,Male,African-American,09/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63278,72947,66112,PRETRIAL,Perry,George,NULL,Male,Caucasian,04/08/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,5/7/14 0:00,1,Low,7,Risk of Violence,-4.39,1,Low,New,1,0 +63278,72947,66112,PRETRIAL,Perry,George,NULL,Male,Caucasian,04/08/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,5/7/14 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +63278,72947,66112,PRETRIAL,Perry,George,NULL,Male,Caucasian,04/08/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63284,72957,66120,Probation,llaguno,eloy,NULL,Male,Hispanic,02/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.7,2,Low,New,1,0 +63284,72957,66120,Probation,llaguno,eloy,NULL,Male,Hispanic,02/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +63284,72957,66120,Probation,llaguno,eloy,NULL,Male,Hispanic,02/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63262,72929,66095,PRETRIAL,Delee,Antawn,NULL,Male,African-American,02/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +63262,72929,66095,PRETRIAL,Delee,Antawn,NULL,Male,African-American,02/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.73,10,High,New,1,0 +63262,72929,66095,PRETRIAL,Delee,Antawn,NULL,Male,African-American,02/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63269,72936,66102,Probation,sharma,akshay,NULL,Male,Caucasian,04/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/7/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +63269,72936,66102,Probation,sharma,akshay,NULL,Male,Caucasian,04/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/7/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +63269,72936,66102,Probation,sharma,akshay,NULL,Male,Caucasian,04/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +10862,72943,66108,PRETRIAL,WILLIAM,RAMOS,NARDI,Male,Caucasian,08/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +10862,72943,66108,PRETRIAL,WILLIAM,RAMOS,NARDI,Male,Caucasian,08/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +10862,72943,66108,PRETRIAL,WILLIAM,RAMOS,NARDI,Male,Caucasian,08/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63280,72950,66114,Probation,Gonzalez,Amador,Mesa,Male,Hispanic,11/05/58,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/7/14 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +63280,72950,66114,Probation,Gonzalez,Amador,Mesa,Male,Hispanic,11/05/58,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/7/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +63280,72950,66114,Probation,Gonzalez,Amador,Mesa,Male,Hispanic,11/05/58,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +25552,49672,24717,PRETRIAL,TURNER,QUASAUN,NULL,Male,African-American,12/12/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,5/7/14 0:00,4,High,7,Risk of Violence,-0.26,10,High,Copy,1,0 +25552,49672,24717,PRETRIAL,TURNER,QUASAUN,NULL,Male,African-American,12/12/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,5/7/14 0:00,4,High,8,Risk of Recidivism,0.75,10,High,Copy,1,0 +25552,49672,24717,PRETRIAL,TURNER,QUASAUN,NULL,Male,African-American,12/12/91,17,All Scales,Intake,English,Probation Violator,Probation,Single,5/7/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +62524,72938,65239,Probation,HODGE,DARRELL,MAURICE,Male,African-American,05/07/67,17,All Scales,Intake,English,Other,Probation,Married,5/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,New,1,0 +62524,72938,65239,Probation,HODGE,DARRELL,MAURICE,Male,African-American,05/07/67,17,All Scales,Intake,English,Other,Probation,Married,5/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.04,10,High,New,1,0 +62524,72938,65239,Probation,HODGE,DARRELL,MAURICE,Male,African-American,05/07/67,17,All Scales,Intake,English,Other,Probation,Married,5/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +57268,72955,66118,PRETRIAL,COCUZZA,CHARLES,NULL,Male,Caucasian,05/20/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +57268,72955,66118,PRETRIAL,COCUZZA,CHARLES,NULL,Male,Caucasian,05/20/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +57268,72955,66118,PRETRIAL,COCUZZA,CHARLES,NULL,Male,Caucasian,05/20/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63267,72934,66100,PRETRIAL,Dorfman,Gary,Marc,Male,Caucasian,10/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/7/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +63267,72934,66100,PRETRIAL,Dorfman,Gary,Marc,Male,Caucasian,10/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/7/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +63267,72934,66100,PRETRIAL,Dorfman,Gary,Marc,Male,Caucasian,10/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63282,72952,66116,Probation,fernandes,shawn,NULL,Male,African-American,07/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +63282,72952,66116,Probation,fernandes,shawn,NULL,Male,African-American,07/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +63282,72952,66116,Probation,fernandes,shawn,NULL,Male,African-American,07/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63285,72959,66122,Probation,cunningham,vinson,NULL,Male,African-American,08/04/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +63285,72959,66122,Probation,cunningham,vinson,NULL,Male,African-American,08/04/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +63285,72959,66122,Probation,cunningham,vinson,NULL,Male,African-American,08/04/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63271,72939,66104,Probation,Duque,bryan,NULL,Male,Hispanic,07/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +63271,72939,66104,Probation,Duque,bryan,NULL,Male,Hispanic,07/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +63271,72939,66104,Probation,Duque,bryan,NULL,Male,Hispanic,07/01/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63259,72925,66091,PRETRIAL,Sykes,Maxwell,NULL,Male,Caucasian,09/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +63259,72925,66091,PRETRIAL,Sykes,Maxwell,NULL,Male,Caucasian,09/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +63259,72925,66091,PRETRIAL,Sykes,Maxwell,NULL,Male,Caucasian,09/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +27955,72954,66117,Probation,HARRISON,STEPHANIE,DENISE,Female,African-American,03/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +27955,72954,66117,Probation,HARRISON,STEPHANIE,DENISE,Female,African-American,03/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +27955,72954,66117,Probation,HARRISON,STEPHANIE,DENISE,Female,African-American,03/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +63264,72931,66097,PRETRIAL,Edwards,Courtney,R,Male,African-American,03/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,New,1,0 +63264,72931,66097,PRETRIAL,Edwards,Courtney,R,Male,African-American,03/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +63264,72931,66097,PRETRIAL,Edwards,Courtney,R,Male,African-American,03/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63277,72946,66111,PRETRIAL,SAMAAROSTEGUI,JOSHUA,NULL,Male,Hispanic,01/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-1.81,5,Medium,New,1,0 +63277,72946,66111,PRETRIAL,SAMAAROSTEGUI,JOSHUA,NULL,Male,Hispanic,01/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +63277,72946,66111,PRETRIAL,SAMAAROSTEGUI,JOSHUA,NULL,Male,Hispanic,01/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61924,72923,66089,Probation,rivera-peeples,brandon,NULL,Male,Other,11/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +61924,72923,66089,Probation,rivera-peeples,brandon,NULL,Male,Other,11/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +61924,72923,66089,Probation,rivera-peeples,brandon,NULL,Male,Other,11/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63273,72941,66106,Probation,Sangare,David,NULL,Male,African-American,10/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +63273,72941,66106,Probation,Sangare,David,NULL,Male,African-American,10/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +63273,72941,66106,Probation,Sangare,David,NULL,Male,African-American,10/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63261,72928,66094,PRETRIAL,Scott,Brandon,Antwon,Male,African-American,09/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +63261,72928,66094,PRETRIAL,Scott,Brandon,Antwon,Male,African-American,09/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +63261,72928,66094,PRETRIAL,Scott,Brandon,Antwon,Male,African-American,09/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63286,72962,66125,Probation,HILL,BRANDON,NULL,Male,Caucasian,11/21/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +63286,72962,66125,Probation,HILL,BRANDON,NULL,Male,Caucasian,11/21/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +63286,72962,66125,Probation,HILL,BRANDON,NULL,Male,Caucasian,11/21/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +25552,72949,24717,PRETRIAL,TURNER,QUASAUN,NULL,Male,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/14 0:00,4,High,7,Risk of Violence,-0.36,10,High,Copy,1,0 +25552,72949,24717,PRETRIAL,TURNER,QUASAUN,NULL,Male,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/14 0:00,4,High,8,Risk of Recidivism,0.59,9,High,Copy,1,0 +25552,72949,24717,PRETRIAL,TURNER,QUASAUN,NULL,Male,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/7/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +63303,72983,66145,Probation,FALCONE,GUY,NULL,Male,Caucasian,04/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +63303,72983,66145,Probation,FALCONE,GUY,NULL,Male,Caucasian,04/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +63303,72983,66145,Probation,FALCONE,GUY,NULL,Male,Caucasian,04/27/68,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63293,72970,66133,Probation,Glantz,Howard,NULL,Male,Caucasian,08/21/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +63293,72970,66133,Probation,Glantz,Howard,NULL,Male,Caucasian,08/21/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +63293,72970,66133,Probation,Glantz,Howard,NULL,Male,Caucasian,08/21/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63295,72973,66136,PRETRIAL,Toussaint,Juckendra,NULL,Female,African-American,12/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +63295,72973,66136,PRETRIAL,Toussaint,Juckendra,NULL,Female,African-American,12/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +63295,72973,66136,PRETRIAL,Toussaint,Juckendra,NULL,Female,African-American,12/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56145,72964,66127,PRETRIAL,buitrago,mauricio,NULL,Male,Hispanic,12/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/8/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +56145,72964,66127,PRETRIAL,buitrago,mauricio,NULL,Male,Hispanic,12/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +56145,72964,66127,PRETRIAL,buitrago,mauricio,NULL,Male,Hispanic,12/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63294,72971,66134,Probation,Dogagis,Geronimos,Alex,Male,Caucasian,03/03/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +63294,72971,66134,Probation,Dogagis,Geronimos,Alex,Male,Caucasian,03/03/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +63294,72971,66134,Probation,Dogagis,Geronimos,Alex,Male,Caucasian,03/03/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63300,72980,66142,PRETRIAL,Moise,Sara,NULL,Female,African-American,01/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +63300,72980,66142,PRETRIAL,Moise,Sara,NULL,Female,African-American,01/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +63300,72980,66142,PRETRIAL,Moise,Sara,NULL,Female,African-American,01/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63298,72978,66140,Probation,Venter,Max,NULL,Male,Caucasian,03/11/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,New,1,0 +63298,72978,66140,Probation,Venter,Max,NULL,Male,Caucasian,03/11/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +63298,72978,66140,Probation,Venter,Max,NULL,Male,Caucasian,03/11/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63301,72981,66143,Probation,Molina,Rhomer,NULL,Male,Hispanic,09/30/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/8/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +63301,72981,66143,Probation,Molina,Rhomer,NULL,Male,Hispanic,09/30/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/8/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +63301,72981,66143,Probation,Molina,Rhomer,NULL,Male,Hispanic,09/30/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63297,72977,66139,Probation,Neethling,Johannes,NULL,Male,Caucasian,05/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,5/8/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +63297,72977,66139,Probation,Neethling,Johannes,NULL,Male,Caucasian,05/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +63297,72977,66139,Probation,Neethling,Johannes,NULL,Male,Caucasian,05/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +8818,72972,66135,PRETRIAL,Wilfehrt,Michael,Patrick,Male,Caucasian,01/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/14 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +8818,72972,66135,PRETRIAL,Wilfehrt,Michael,Patrick,Male,Caucasian,01/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +8818,72972,66135,PRETRIAL,Wilfehrt,Michael,Patrick,Male,Caucasian,01/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63299,72979,66141,Probation,dixon,leticia,NULL,Female,African-American,01/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +63299,72979,66141,Probation,dixon,leticia,NULL,Female,African-American,01/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +63299,72979,66141,Probation,dixon,leticia,NULL,Female,African-American,01/19/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63306,72986,66148,PRETRIAL,MAharaj,Nicholas,NULL,Male,African-American,02/25/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +63306,72986,66148,PRETRIAL,MAharaj,Nicholas,NULL,Male,African-American,02/25/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-0.45,4,Low,New,1,0 +63306,72986,66148,PRETRIAL,MAharaj,Nicholas,NULL,Male,African-American,02/25/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +63287,72963,66126,PRETRIAL,KELLEY,DAVID,SHANE,Male,Caucasian,08/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +63287,72963,66126,PRETRIAL,KELLEY,DAVID,SHANE,Male,Caucasian,08/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +63287,72963,66126,PRETRIAL,KELLEY,DAVID,SHANE,Male,Caucasian,08/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63288,72965,66128,PRETRIAL,Guerra,Carlos,NULL,Male,Caucasian,01/26/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/8/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +63288,72965,66128,PRETRIAL,Guerra,Carlos,NULL,Male,Caucasian,01/26/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/8/14 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +63288,72965,66128,PRETRIAL,Guerra,Carlos,NULL,Male,Caucasian,01/26/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63302,72982,66144,Probation,waugh,britt,NULL,Female,Caucasian,02/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +63302,72982,66144,Probation,waugh,britt,NULL,Female,Caucasian,02/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +63302,72982,66144,Probation,waugh,britt,NULL,Female,Caucasian,02/10/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63292,72969,66132,PRETRIAL,BEAUDET,FRANK,NULL,Male,Caucasian,11/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +63292,72969,66132,PRETRIAL,BEAUDET,FRANK,NULL,Male,Caucasian,11/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +63292,72969,66132,PRETRIAL,BEAUDET,FRANK,NULL,Male,Caucasian,11/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +35895,72976,42609,PRETRIAL,Caraballo,Keston,NULL,Male,African-American,01/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,Copy,1,0 +35895,72976,42609,PRETRIAL,Caraballo,Keston,NULL,Male,African-American,01/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,Copy,1,0 +35895,72976,42609,PRETRIAL,Caraballo,Keston,NULL,Male,African-American,01/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +63291,72968,66131,PRETRIAL,ketchum,christopher,NULL,Male,Caucasian,08/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +63291,72968,66131,PRETRIAL,ketchum,christopher,NULL,Male,Caucasian,08/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +63291,72968,66131,PRETRIAL,ketchum,christopher,NULL,Male,Caucasian,08/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +10016,72990,66152,Probation,Gordon,Askia,NULL,Male,African-American,10/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +10016,72990,66152,Probation,Gordon,Askia,NULL,Male,African-American,10/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +10016,72990,66152,Probation,Gordon,Askia,NULL,Male,African-American,10/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63304,72984,66146,Probation,Lane,Demarquis,NULL,Male,African-American,07/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +63304,72984,66146,Probation,Lane,Demarquis,NULL,Male,African-American,07/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +63304,72984,66146,Probation,Lane,Demarquis,NULL,Male,African-American,07/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63296,72974,66137,Probation,posada,jessie,NULL,Male,Caucasian,11/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +63296,72974,66137,Probation,posada,jessie,NULL,Male,Caucasian,11/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +63296,72974,66137,Probation,posada,jessie,NULL,Male,Caucasian,11/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63289,72966,66129,PRETRIAL,Valli,Joel,NULL,Male,Caucasian,03/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +63289,72966,66129,PRETRIAL,Valli,Joel,NULL,Male,Caucasian,03/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.96,10,High,New,1,0 +63289,72966,66129,PRETRIAL,Valli,Joel,NULL,Male,Caucasian,03/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +63307,72987,66149,Probation,becker,derek,NULL,Male,Caucasian,05/31/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +63307,72987,66149,Probation,becker,derek,NULL,Male,Caucasian,05/31/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +63307,72987,66149,Probation,becker,derek,NULL,Male,Caucasian,05/31/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63310,72992,66154,PRETRIAL,Gordon,Neville,NULL,Male,Other,08/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/9/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +63310,72992,66154,PRETRIAL,Gordon,Neville,NULL,Male,Other,08/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/9/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +63310,72992,66154,PRETRIAL,Gordon,Neville,NULL,Male,Other,08/26/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63317,73000,66162,PRETRIAL,Espinal,Ezequiel,NULL,Male,Caucasian,08/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +63317,73000,66162,PRETRIAL,Espinal,Ezequiel,NULL,Male,Caucasian,08/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +63317,73000,66162,PRETRIAL,Espinal,Ezequiel,NULL,Male,Caucasian,08/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63328,73013,66174,Probation,Evaristo,Williams,NULL,Male,Hispanic,07/30/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +63328,73013,66174,Probation,Evaristo,Williams,NULL,Male,Hispanic,07/30/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +63328,73013,66174,Probation,Evaristo,Williams,NULL,Male,Hispanic,07/30/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63322,73005,66166,Probation,MacEachern,Matthew,NULL,Male,Caucasian,09/25/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/9/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +63322,73005,66166,Probation,MacEachern,Matthew,NULL,Male,Caucasian,09/25/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/9/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +63322,73005,66166,Probation,MacEachern,Matthew,NULL,Male,Caucasian,09/25/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63312,72995,66157,PRETRIAL,Simmons,Raymond,NULL,Male,African-American,12/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.17,4,Low,New,1,0 +63312,72995,66157,PRETRIAL,Simmons,Raymond,NULL,Male,African-American,12/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +63312,72995,66157,PRETRIAL,Simmons,Raymond,NULL,Male,African-American,12/17/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63326,73011,66172,Probation,Heredia,Solange,Julianna,Female,Hispanic,12/18/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +63326,73011,66172,Probation,Heredia,Solange,Julianna,Female,Hispanic,12/18/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.41,6,Medium,New,1,0 +63326,73011,66172,Probation,Heredia,Solange,Julianna,Female,Hispanic,12/18/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +35974,73003,66165,PRETRIAL,COVINGTON,NEMIAH,NULL,Male,African-American,04/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +35974,73003,66165,PRETRIAL,COVINGTON,NEMIAH,NULL,Male,African-American,04/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +35974,73003,66165,PRETRIAL,COVINGTON,NEMIAH,NULL,Male,African-American,04/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53073,73010,66171,Probation,BUTLER,SHAQUILLE,ONEAL,Male,African-American,07/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/9/14 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +53073,73010,66171,Probation,BUTLER,SHAQUILLE,ONEAL,Male,African-American,07/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/9/14 0:00,4,High,8,Risk of Recidivism,0.95,10,High,New,1,0 +53073,73010,66171,Probation,BUTLER,SHAQUILLE,ONEAL,Male,African-American,07/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/9/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63314,72997,66159,PRETRIAL,Baker,Lonnae,lashun,Female,African-American,07/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +63314,72997,66159,PRETRIAL,Baker,Lonnae,lashun,Female,African-American,07/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +63314,72997,66159,PRETRIAL,Baker,Lonnae,lashun,Female,African-American,07/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +16662,73014,66175,Probation,Smilovits,Yonatan,NULL,Male,Caucasian,03/27/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +16662,73014,66175,Probation,Smilovits,Yonatan,NULL,Male,Caucasian,03/27/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +16662,73014,66175,Probation,Smilovits,Yonatan,NULL,Male,Caucasian,03/27/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58295,73016,66177,PRETRIAL,Ravino,James,NULL,Male,Caucasian,09/05/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +58295,73016,66177,PRETRIAL,Ravino,James,NULL,Male,Caucasian,09/05/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +58295,73016,66177,PRETRIAL,Ravino,James,NULL,Male,Caucasian,09/05/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63311,72993,66155,PRETRIAL,Fredrick,Roberts,NULL,Male,African-American,06/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/9/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +63311,72993,66155,PRETRIAL,Fredrick,Roberts,NULL,Male,African-American,06/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/9/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +63311,72993,66155,PRETRIAL,Fredrick,Roberts,NULL,Male,African-American,06/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63333,73021,66182,Probation,Forde,Khason,NULL,Male,African-American,05/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +63333,73021,66182,Probation,Forde,Khason,NULL,Male,African-American,05/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +63333,73021,66182,Probation,Forde,Khason,NULL,Male,African-American,05/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63339,73023,66184,Probation,haleem,jason,NULL,Male,Caucasian,08/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.07,4,Low,New,1,0 +63339,73023,66184,Probation,haleem,jason,NULL,Male,Caucasian,08/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.79,10,High,New,1,0 +63339,73023,66184,Probation,haleem,jason,NULL,Male,Caucasian,08/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +63315,72998,66160,PRETRIAL,Smith,Catherine,E,Female,Caucasian,01/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +63315,72998,66160,PRETRIAL,Smith,Catherine,E,Female,Caucasian,01/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-1.53,2,Low,New,1,0 +63315,72998,66160,PRETRIAL,Smith,Catherine,E,Female,Caucasian,01/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63340,73028,66185,Probation,Assari,Atessa,NULL,Female,Caucasian,09/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +63340,73028,66185,Probation,Assari,Atessa,NULL,Female,Caucasian,09/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +63340,73028,66185,Probation,Assari,Atessa,NULL,Female,Caucasian,09/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61478,73001,66163,PRETRIAL,Jean,Makenlie,NULL,Male,Other,01/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +61478,73001,66163,PRETRIAL,Jean,Makenlie,NULL,Male,Other,01/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +61478,73001,66163,PRETRIAL,Jean,Makenlie,NULL,Male,Other,01/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63316,72999,66161,PRETRIAL,Burner,Nicholas,Anthony,Male,Caucasian,03/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +63316,72999,66161,PRETRIAL,Burner,Nicholas,Anthony,Male,Caucasian,03/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +63316,72999,66161,PRETRIAL,Burner,Nicholas,Anthony,Male,Caucasian,03/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54581,73008,66169,PRETRIAL,Sherman,Maria,M,Female,Caucasian,07/29/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +54581,73008,66169,PRETRIAL,Sherman,Maria,M,Female,Caucasian,07/29/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +54581,73008,66169,PRETRIAL,Sherman,Maria,M,Female,Caucasian,07/29/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63338,73022,66183,Probation,Jackson,Irene,NULL,Female,African-American,07/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.6,2,Low,New,1,0 +63338,73022,66183,Probation,Jackson,Irene,NULL,Female,African-American,07/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,8,High,New,1,0 +63338,73022,66183,Probation,Jackson,Irene,NULL,Female,African-American,07/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56936,73015,66176,Probation,Morris,Tonia,Roxan,Female,African-American,05/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +56936,73015,66176,Probation,Morris,Tonia,Roxan,Female,African-American,05/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +56936,73015,66176,Probation,Morris,Tonia,Roxan,Female,African-American,05/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +17028,72994,66156,Probation,JORDAN,DARIAN,M,Male,African-American,05/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,New,1,0 +17028,72994,66156,Probation,JORDAN,DARIAN,M,Male,African-American,05/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +17028,72994,66156,Probation,JORDAN,DARIAN,M,Male,African-American,05/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +23647,73006,66167,Probation,Cassidy,Michelle,NULL,Female,Caucasian,08/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +23647,73006,66167,Probation,Cassidy,Michelle,NULL,Female,Caucasian,08/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +23647,73006,66167,Probation,Cassidy,Michelle,NULL,Female,Caucasian,08/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +29258,73024,32656,DRRD,Walker,John,Willy,Male,African-American,12/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/14 0:00,4,High,7,Risk of Violence,-0.7,9,High,Copy,1,0 +29258,73024,32656,DRRD,Walker,John,Willy,Male,African-American,12/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/14 0:00,4,High,8,Risk of Recidivism,1.1,10,High,Copy,1,0 +29258,73024,32656,DRRD,Walker,John,Willy,Male,African-American,12/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/9/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +63332,73020,66181,PRETRIAL,Cahill,Meghan,NULL,Female,Caucasian,07/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +63332,73020,66181,PRETRIAL,Cahill,Meghan,NULL,Female,Caucasian,07/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +63332,73020,66181,PRETRIAL,Cahill,Meghan,NULL,Female,Caucasian,07/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63313,72996,66158,PRETRIAL,Branum,Joseph,NULL,Male,Caucasian,07/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +63313,72996,66158,PRETRIAL,Branum,Joseph,NULL,Male,Caucasian,07/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +63313,72996,66158,PRETRIAL,Branum,Joseph,NULL,Male,Caucasian,07/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63329,73017,66178,Probation,Hicks,Charles,NULL,Male,Caucasian,03/09/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/9/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +63329,73017,66178,Probation,Hicks,Charles,NULL,Male,Caucasian,03/09/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/9/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +63329,73017,66178,Probation,Hicks,Charles,NULL,Male,Caucasian,03/09/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/9/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63327,73012,66173,Probation,Cooper,Theophers,NULL,Male,African-American,12/29/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +63327,73012,66173,Probation,Cooper,Theophers,NULL,Male,African-American,12/29/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +63327,73012,66173,Probation,Cooper,Theophers,NULL,Male,African-American,12/29/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/9/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +63345,73033,66190,PRETRIAL,Ward,Michael,NULL,Male,African-American,03/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +63345,73033,66190,PRETRIAL,Ward,Michael,NULL,Male,African-American,03/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +63345,73033,66190,PRETRIAL,Ward,Michael,NULL,Male,African-American,03/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63352,73040,66197,PRETRIAL,Payne,Jarred,NULL,Male,African-American,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +63352,73040,66197,PRETRIAL,Payne,Jarred,NULL,Male,African-American,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +63352,73040,66197,PRETRIAL,Payne,Jarred,NULL,Male,African-American,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63342,73030,66187,PRETRIAL,McCray,Rodney,NULL,Male,African-American,07/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +63342,73030,66187,PRETRIAL,McCray,Rodney,NULL,Male,African-American,07/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +63342,73030,66187,PRETRIAL,McCray,Rodney,NULL,Male,African-American,07/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63350,73038,66195,PRETRIAL,Hursey,Darren,NULL,Male,African-American,07/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +63350,73038,66195,PRETRIAL,Hursey,Darren,NULL,Male,African-American,07/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +63350,73038,66195,PRETRIAL,Hursey,Darren,NULL,Male,African-American,07/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63359,73045,66200,PRETRIAL,Marshall,Antonio,NULL,Male,African-American,05/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +63359,73045,66200,PRETRIAL,Marshall,Antonio,NULL,Male,African-American,05/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +63359,73045,66200,PRETRIAL,Marshall,Antonio,NULL,Male,African-American,05/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +11391,73041,10914,PRETRIAL,MOMENT,JOSEPH,NULL,Male,African-American,09/30/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,Copy,1,0 +11391,73041,10914,PRETRIAL,MOMENT,JOSEPH,NULL,Male,African-American,09/30/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,Copy,1,0 +11391,73041,10914,PRETRIAL,MOMENT,JOSEPH,NULL,Male,African-American,09/30/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +63348,73036,66193,PRETRIAL,Gordon,Hussain,Necofranz,Male,Other,01/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +63348,73036,66193,PRETRIAL,Gordon,Hussain,Necofranz,Male,Other,01/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +63348,73036,66193,PRETRIAL,Gordon,Hussain,Necofranz,Male,Other,01/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63358,73043,66199,PRETRIAL,Clicouot,Cherryl,NULL,Female,African-American,08/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +63358,73043,66199,PRETRIAL,Clicouot,Cherryl,NULL,Female,African-American,08/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +63358,73043,66199,PRETRIAL,Clicouot,Cherryl,NULL,Female,African-American,08/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63344,73032,66189,PRETRIAL,Hochstadt,Andrew,NULL,Male,Caucasian,07/26/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +63344,73032,66189,PRETRIAL,Hochstadt,Andrew,NULL,Male,Caucasian,07/26/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +63344,73032,66189,PRETRIAL,Hochstadt,Andrew,NULL,Male,Caucasian,07/26/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63347,73035,66192,PRETRIAL,Bassett,Stephen,Richard,Male,Caucasian,07/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +63347,73035,66192,PRETRIAL,Bassett,Stephen,Richard,Male,Caucasian,07/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +63347,73035,66192,PRETRIAL,Bassett,Stephen,Richard,Male,Caucasian,07/03/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +63349,73037,66194,PRETRIAL,Mejia,Ulysses,NULL,Male,African-American,11/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,2,Medium,7,Risk of Violence,-2.23,4,Low,New,1,0 +63349,73037,66194,PRETRIAL,Mejia,Ulysses,NULL,Male,African-American,11/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +63349,73037,66194,PRETRIAL,Mejia,Ulysses,NULL,Male,African-American,11/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63353,73042,66198,PRETRIAL,Kippenberger,Joseph,Scott,Male,Native American,06/10/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/10/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +63353,73042,66198,PRETRIAL,Kippenberger,Joseph,Scott,Male,Native American,06/10/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/10/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +63353,73042,66198,PRETRIAL,Kippenberger,Joseph,Scott,Male,Native American,06/10/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +13721,73044,13117,PRETRIAL,Cherfils,Sean,Kurtz,Male,African-American,01/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +13721,73044,13117,PRETRIAL,Cherfils,Sean,Kurtz,Male,African-American,01/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,Copy,1,0 +13721,73044,13117,PRETRIAL,Cherfils,Sean,Kurtz,Male,African-American,01/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +63343,73031,66188,PRETRIAL,Pierre,Emmanuel,NULL,Male,Other,12/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/10/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +63343,73031,66188,PRETRIAL,Pierre,Emmanuel,NULL,Male,Other,12/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/10/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +63343,73031,66188,PRETRIAL,Pierre,Emmanuel,NULL,Male,Other,12/24/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63351,73039,66196,PRETRIAL,Merei,Mostafa,NULL,Male,Arabic,05/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/10/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +63351,73039,66196,PRETRIAL,Merei,Mostafa,NULL,Male,Arabic,05/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/10/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +63351,73039,66196,PRETRIAL,Merei,Mostafa,NULL,Male,Arabic,05/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63346,73034,66191,PRETRIAL,Almonte,Aryam,NULL,Female,Caucasian,02/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +63346,73034,66191,PRETRIAL,Almonte,Aryam,NULL,Female,Caucasian,02/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +63346,73034,66191,PRETRIAL,Almonte,Aryam,NULL,Female,Caucasian,02/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/10/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63361,73047,66202,PRETRIAL,HORA,JOHN,CLAUDY,Male,Caucasian,02/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +63361,73047,66202,PRETRIAL,HORA,JOHN,CLAUDY,Male,Caucasian,02/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +63361,73047,66202,PRETRIAL,HORA,JOHN,CLAUDY,Male,Caucasian,02/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63363,73049,66204,PRETRIAL,Washington,Kenny,NULL,Male,African-American,10/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +63363,73049,66204,PRETRIAL,Washington,Kenny,NULL,Male,African-American,10/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +63363,73049,66204,PRETRIAL,Washington,Kenny,NULL,Male,African-American,10/24/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +36615,73050,66205,PRETRIAL,FRANCOIS,JAMES,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +36615,73050,66205,PRETRIAL,FRANCOIS,JAMES,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +36615,73050,66205,PRETRIAL,FRANCOIS,JAMES,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63364,73051,66206,PRETRIAL,SMITH,KAMBRYON,NULL,Male,African-American,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +63364,73051,66206,PRETRIAL,SMITH,KAMBRYON,NULL,Male,African-American,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +63364,73051,66206,PRETRIAL,SMITH,KAMBRYON,NULL,Male,African-American,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63362,73048,66203,PRETRIAL,PETERS,ROSLYN,NULL,Female,Caucasian,06/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +63362,73048,66203,PRETRIAL,PETERS,ROSLYN,NULL,Female,Caucasian,06/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +63362,73048,66203,PRETRIAL,PETERS,ROSLYN,NULL,Female,Caucasian,06/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63360,73046,66201,PRETRIAL,HURST,ERIC,NULL,Male,Caucasian,09/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +63360,73046,66201,PRETRIAL,HURST,ERIC,NULL,Male,Caucasian,09/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +63360,73046,66201,PRETRIAL,HURST,ERIC,NULL,Male,Caucasian,09/16/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/11/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63375,73067,66222,Probation,Wahdan,Ehab,NULL,Male,Arabic,03/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +63375,73067,66222,Probation,Wahdan,Ehab,NULL,Male,Arabic,03/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +63375,73067,66222,Probation,Wahdan,Ehab,NULL,Male,Arabic,03/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63392,73082,66235,PRETRIAL,DIXON,TRAVIS,NULL,Male,African-American,01/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,New,1,0 +63392,73082,66235,PRETRIAL,DIXON,TRAVIS,NULL,Male,African-American,01/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +63392,73082,66235,PRETRIAL,DIXON,TRAVIS,NULL,Male,African-American,01/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63398,73090,66243,Probation,MORAN,RAFAEL,NULL,Male,Hispanic,04/17/70,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/12/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +63398,73090,66243,Probation,MORAN,RAFAEL,NULL,Male,Hispanic,04/17/70,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/12/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +63398,73090,66243,Probation,MORAN,RAFAEL,NULL,Male,Hispanic,04/17/70,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63366,73054,66209,PRETRIAL,DURHAM,CHRISTOPHER,NULL,Male,African-American,10/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/12/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +63366,73054,66209,PRETRIAL,DURHAM,CHRISTOPHER,NULL,Male,African-American,10/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +63366,73054,66209,PRETRIAL,DURHAM,CHRISTOPHER,NULL,Male,African-American,10/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/12/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63372,73061,66216,PRETRIAL,KESTLER,ASHLY,M,Female,Caucasian,06/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/12/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +63372,73061,66216,PRETRIAL,KESTLER,ASHLY,M,Female,Caucasian,06/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/12/14 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +63372,73061,66216,PRETRIAL,KESTLER,ASHLY,M,Female,Caucasian,06/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +63393,73085,66238,PRETRIAL,Osceola,Angelo,NULL,Male,Native American,11/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +63393,73085,66238,PRETRIAL,Osceola,Angelo,NULL,Male,Native American,11/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,New,1,0 +63393,73085,66238,PRETRIAL,Osceola,Angelo,NULL,Male,Native American,11/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63374,73064,66219,PRETRIAL,SEVAK,ANKUR,NULL,Male,Other,01/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +63374,73064,66219,PRETRIAL,SEVAK,ANKUR,NULL,Male,Other,01/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +63374,73064,66219,PRETRIAL,SEVAK,ANKUR,NULL,Male,Other,01/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63368,73056,66211,PRETRIAL,CASTRO,JOSE,NULL,Male,Caucasian,03/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +63368,73056,66211,PRETRIAL,CASTRO,JOSE,NULL,Male,Caucasian,03/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +63368,73056,66211,PRETRIAL,CASTRO,JOSE,NULL,Male,Caucasian,03/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63370,73059,66214,PRETRIAL,MORTIMER,AMEENA-MARIE,NULL,Female,African-American,05/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +63370,73059,66214,PRETRIAL,MORTIMER,AMEENA-MARIE,NULL,Female,African-American,05/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +63370,73059,66214,PRETRIAL,MORTIMER,AMEENA-MARIE,NULL,Female,African-American,05/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63389,73077,66231,Probation,Graham,Monty,NULL,Male,African-American,08/09/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +63389,73077,66231,Probation,Graham,Monty,NULL,Male,African-American,08/09/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +63389,73077,66231,Probation,Graham,Monty,NULL,Male,African-American,08/09/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63391,73080,66233,Probation,Andan,Gilbert,NULL,Male,Hispanic,08/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +63391,73080,66233,Probation,Andan,Gilbert,NULL,Male,Hispanic,08/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +63391,73080,66233,Probation,Andan,Gilbert,NULL,Male,Hispanic,08/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63379,73071,66225,Probation,Jaffer,Nancy,NULL,Female,Caucasian,03/19/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +63379,73071,66225,Probation,Jaffer,Nancy,NULL,Female,Caucasian,03/19/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +63379,73071,66225,Probation,Jaffer,Nancy,NULL,Female,Caucasian,03/19/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63390,73078,66232,Probation,Peralta,Melvin,NULL,Male,Hispanic,06/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/12/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +63390,73078,66232,Probation,Peralta,Melvin,NULL,Male,Hispanic,06/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +63390,73078,66232,Probation,Peralta,Melvin,NULL,Male,Hispanic,06/12/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +10115,73057,66212,Probation,Lee,Tyran,NULL,Male,African-American,04/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +10115,73057,66212,Probation,Lee,Tyran,NULL,Male,African-American,04/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +10115,73057,66212,Probation,Lee,Tyran,NULL,Male,African-American,04/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +15667,73062,66217,PRETRIAL,SUBU,VALENTIN,DANIEL,Male,Caucasian,11/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/12/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +15667,73062,66217,PRETRIAL,SUBU,VALENTIN,DANIEL,Male,Caucasian,11/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +15667,73062,66217,PRETRIAL,SUBU,VALENTIN,DANIEL,Male,Caucasian,11/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63395,73087,66240,Probation,Crawford,Saverlyn,NULL,Female,African-American,09/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.24,1,Low,New,1,0 +63395,73087,66240,Probation,Crawford,Saverlyn,NULL,Female,African-American,09/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,New,1,0 +63395,73087,66240,Probation,Crawford,Saverlyn,NULL,Female,African-American,09/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +36878,73066,66221,PRETRIAL,Rodriguez,Ethen,NULL,Male,Hispanic,08/01/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +36878,73066,66221,PRETRIAL,Rodriguez,Ethen,NULL,Male,Hispanic,08/01/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +36878,73066,66221,PRETRIAL,Rodriguez,Ethen,NULL,Male,Hispanic,08/01/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63365,73053,66208,PRETRIAL,OLIPHANT,JAMES,ALEXANDER,Male,African-American,03/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,4,High,7,Risk of Violence,-0.72,9,High,New,1,0 +63365,73053,66208,PRETRIAL,OLIPHANT,JAMES,ALEXANDER,Male,African-American,03/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +63365,73053,66208,PRETRIAL,OLIPHANT,JAMES,ALEXANDER,Male,African-American,03/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63396,73088,66241,Probation,Cusano,Margaret,Eldeen,Female,Hispanic,05/17/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +63396,73088,66241,Probation,Cusano,Margaret,Eldeen,Female,Hispanic,05/17/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +63396,73088,66241,Probation,Cusano,Margaret,Eldeen,Female,Hispanic,05/17/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63378,73070,66224,PRETRIAL,Menke,krystal,NULL,Female,Caucasian,09/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +63378,73070,66224,PRETRIAL,Menke,krystal,NULL,Female,Caucasian,09/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +63378,73070,66224,PRETRIAL,Menke,krystal,NULL,Female,Caucasian,09/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50787,73084,66237,PRETRIAL,Sanabria,Janet,Miriam,Female,Caucasian,05/26/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +50787,73084,66237,PRETRIAL,Sanabria,Janet,Miriam,Female,Caucasian,05/26/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +50787,73084,66237,PRETRIAL,Sanabria,Janet,Miriam,Female,Caucasian,05/26/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63373,73063,66218,PRETRIAL,dungan,george,NULL,Male,Caucasian,01/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/12/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +63373,73063,66218,PRETRIAL,dungan,george,NULL,Male,Caucasian,01/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +63373,73063,66218,PRETRIAL,dungan,george,NULL,Male,Caucasian,01/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +53896,73065,66220,PRETRIAL,WILSON,DARRON,NULL,Male,African-American,09/18/66,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/12/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +53896,73065,66220,PRETRIAL,WILSON,DARRON,NULL,Male,African-American,09/18/66,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +53896,73065,66220,PRETRIAL,WILSON,DARRON,NULL,Male,African-American,09/18/66,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63369,73058,66213,PRETRIAL,PUTNAM,QUINTEN,NULL,Male,Caucasian,12/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +63369,73058,66213,PRETRIAL,PUTNAM,QUINTEN,NULL,Male,Caucasian,12/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +63369,73058,66213,PRETRIAL,PUTNAM,QUINTEN,NULL,Male,Caucasian,12/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +49187,73072,66226,PRETRIAL,Decaro,Anntonette,NULL,Female,Caucasian,08/17/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +49187,73072,66226,PRETRIAL,Decaro,Anntonette,NULL,Female,Caucasian,08/17/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +49187,73072,66226,PRETRIAL,Decaro,Anntonette,NULL,Female,Caucasian,08/17/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +63394,73086,66239,Probation,gutierrez,jennifer,NULL,Female,Hispanic,02/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +63394,73086,66239,Probation,gutierrez,jennifer,NULL,Female,Hispanic,02/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +63394,73086,66239,Probation,gutierrez,jennifer,NULL,Female,Hispanic,02/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63400,73093,66246,Probation,Sharapov,Konstantin,NULL,Male,Caucasian,03/11/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +63400,73093,66246,Probation,Sharapov,Konstantin,NULL,Male,Caucasian,03/11/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +63400,73093,66246,Probation,Sharapov,Konstantin,NULL,Male,Caucasian,03/11/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +22910,73081,66234,Probation,Saunders,Kayla,Joycelyn,Female,African-American,06/21/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +22910,73081,66234,Probation,Saunders,Kayla,Joycelyn,Female,African-American,06/21/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +22910,73081,66234,Probation,Saunders,Kayla,Joycelyn,Female,African-American,06/21/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63371,73060,66215,PRETRIAL,Gooden,Abria,NULL,Female,African-American,09/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +63371,73060,66215,PRETRIAL,Gooden,Abria,NULL,Female,African-American,09/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +63371,73060,66215,PRETRIAL,Gooden,Abria,NULL,Female,African-American,09/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +22624,73052,66207,PRETRIAL,murphy,willie,NULL,Male,African-American,03/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +22624,73052,66207,PRETRIAL,murphy,willie,NULL,Male,African-American,03/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,4,High,8,Risk of Recidivism,0.19,8,High,New,1,0 +22624,73052,66207,PRETRIAL,murphy,willie,NULL,Male,African-American,03/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/12/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63367,73055,66210,PRETRIAL,BYRDO,JAVARIS,D,Male,African-American,06/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,New,1,0 +63367,73055,66210,PRETRIAL,BYRDO,JAVARIS,D,Male,African-American,06/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +63367,73055,66210,PRETRIAL,BYRDO,JAVARIS,D,Male,African-American,06/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63380,73073,66227,PRETRIAL,shaw,carola,NULL,Female,African-American,07/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +63380,73073,66227,PRETRIAL,shaw,carola,NULL,Female,African-American,07/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +63380,73073,66227,PRETRIAL,shaw,carola,NULL,Female,African-American,07/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63397,73089,66242,Probation,Schmidt,Georgio,NULL,Male,Hispanic,01/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +63397,73089,66242,Probation,Schmidt,Georgio,NULL,Male,Hispanic,01/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +63397,73089,66242,Probation,Schmidt,Georgio,NULL,Male,Hispanic,01/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/12/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63388,73076,66230,PRETRIAL,SCOTT,JARVIS,NULL,Male,African-American,03/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.6,2,Low,New,1,0 +63388,73076,66230,PRETRIAL,SCOTT,JARVIS,NULL,Male,African-American,03/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.71,10,High,New,1,0 +63388,73076,66230,PRETRIAL,SCOTT,JARVIS,NULL,Male,African-American,03/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63412,73110,66261,PRETRIAL,RICHARDSON,DUSTIN,NULL,Male,Caucasian,12/23/83,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +63412,73110,66261,PRETRIAL,RICHARDSON,DUSTIN,NULL,Male,Caucasian,12/23/83,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +63412,73110,66261,PRETRIAL,RICHARDSON,DUSTIN,NULL,Male,Caucasian,12/23/83,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,2,Medium,18,Risk of Failure to Appear,21,3,Low,New,1,0 +63414,73112,66263,Probation,Sussman,Stephan,NULL,Male,Caucasian,05/22/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +63414,73112,66263,Probation,Sussman,Stephan,NULL,Male,Caucasian,05/22/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-2.72,1,Low,New,1,0 +63414,73112,66263,Probation,Sussman,Stephan,NULL,Male,Caucasian,05/22/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63402,73097,66250,PRETRIAL,Whitmour,Craig,Shawn,Male,African-American,11/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +63402,73097,66250,PRETRIAL,Whitmour,Craig,Shawn,Male,African-American,11/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +63402,73097,66250,PRETRIAL,Whitmour,Craig,Shawn,Male,African-American,11/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +63426,73131,66279,Probation,duverna,duguesne,NULL,Male,African-American,07/14/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +63426,73131,66279,Probation,duverna,duguesne,NULL,Male,African-American,07/14/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +63426,73131,66279,Probation,duverna,duguesne,NULL,Male,African-American,07/14/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63423,73125,66274,PRETRIAL,Cooper,Nicole,Marie,Female,African-American,03/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +63423,73125,66274,PRETRIAL,Cooper,Nicole,Marie,Female,African-American,03/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,4,High,8,Risk of Recidivism,0.1,8,High,New,1,0 +63423,73125,66274,PRETRIAL,Cooper,Nicole,Marie,Female,African-American,03/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +63432,73139,66287,PRETRIAL,DELGADO,MIKE,NULL,Male,Caucasian,01/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +63432,73139,66287,PRETRIAL,DELGADO,MIKE,NULL,Male,Caucasian,01/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +63432,73139,66287,PRETRIAL,DELGADO,MIKE,NULL,Male,Caucasian,01/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63408,73104,66257,PRETRIAL,Thorbjornsson,Unnar,NULL,Male,Caucasian,11/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +63408,73104,66257,PRETRIAL,Thorbjornsson,Unnar,NULL,Male,Caucasian,11/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +63408,73104,66257,PRETRIAL,Thorbjornsson,Unnar,NULL,Male,Caucasian,11/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +47350,73118,66268,PRETRIAL,SNEED,EMMANUEL,LEON,Male,African-American,08/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +47350,73118,66268,PRETRIAL,SNEED,EMMANUEL,LEON,Male,African-American,08/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +47350,73118,66268,PRETRIAL,SNEED,EMMANUEL,LEON,Male,African-American,08/13/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63421,73123,66272,Probation,Windsor,Scott,NULL,Male,Caucasian,03/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +63421,73123,66272,Probation,Windsor,Scott,NULL,Male,Caucasian,03/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +63421,73123,66272,Probation,Windsor,Scott,NULL,Male,Caucasian,03/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63406,73102,66255,PRETRIAL,Anderson,Jamarl,NULL,Male,Other,10/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +63406,73102,66255,PRETRIAL,Anderson,Jamarl,NULL,Male,Other,10/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +63406,73102,66255,PRETRIAL,Anderson,Jamarl,NULL,Male,Other,10/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +46665,73120,66269,PRETRIAL,DALEY,JEROME,J,Male,African-American,09/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +46665,73120,66269,PRETRIAL,DALEY,JEROME,J,Male,African-American,09/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +46665,73120,66269,PRETRIAL,DALEY,JEROME,J,Male,African-American,09/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63425,73128,66276,Probation,Cavallo,Anthony,NULL,Male,Hispanic,11/16/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +63425,73128,66276,Probation,Cavallo,Anthony,NULL,Male,Hispanic,11/16/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +63425,73128,66276,Probation,Cavallo,Anthony,NULL,Male,Hispanic,11/16/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +12601,73115,65664,PRETRIAL,MULA,ELLYSE,NULL,Female,Caucasian,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,Copy,1,0 +12601,73115,65664,PRETRIAL,MULA,ELLYSE,NULL,Female,Caucasian,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,Copy,1,0 +12601,73115,65664,PRETRIAL,MULA,ELLYSE,NULL,Female,Caucasian,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +63417,73116,66266,Probation,Schenk,Ingrid,NULL,Female,Caucasian,08/29/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/14 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +63417,73116,66266,Probation,Schenk,Ingrid,NULL,Female,Caucasian,08/29/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/14 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +63417,73116,66266,Probation,Schenk,Ingrid,NULL,Female,Caucasian,08/29/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63429,73135,66283,Probation,Rodriguez,Christopher,NULL,Male,Hispanic,03/08/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +63429,73135,66283,Probation,Rodriguez,Christopher,NULL,Male,Hispanic,03/08/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +63429,73135,66283,Probation,Rodriguez,Christopher,NULL,Male,Hispanic,03/08/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63431,73137,66285,Probation,westover,richard,NULL,Male,Caucasian,10/28/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +63431,73137,66285,Probation,westover,richard,NULL,Male,Caucasian,10/28/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +63431,73137,66285,Probation,westover,richard,NULL,Male,Caucasian,10/28/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52093,73095,66248,PRETRIAL,Brown,Shatara,NULL,Female,African-American,11/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +52093,73095,66248,PRETRIAL,Brown,Shatara,NULL,Female,African-American,11/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,9,High,New,1,0 +52093,73095,66248,PRETRIAL,Brown,Shatara,NULL,Female,African-American,11/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63411,73109,66260,PRETRIAL,Leguillow,Chazz,NULL,Male,Caucasian,10/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +63411,73109,66260,PRETRIAL,Leguillow,Chazz,NULL,Male,Caucasian,10/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +63411,73109,66260,PRETRIAL,Leguillow,Chazz,NULL,Male,Caucasian,10/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63409,73105,66258,PRETRIAL,Appleby,Racquel,NULL,Female,Other,02/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/14 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +63409,73105,66258,PRETRIAL,Appleby,Racquel,NULL,Female,Other,02/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,New,1,0 +63409,73105,66258,PRETRIAL,Appleby,Racquel,NULL,Female,Other,02/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/13/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63419,73121,66270,Probation,chapman,jaklin,NULL,Male,African-American,04/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +63419,73121,66270,Probation,chapman,jaklin,NULL,Male,African-American,04/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +63419,73121,66270,Probation,chapman,jaklin,NULL,Male,African-American,04/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63424,73126,66275,Probation,feil,jonathan,NULL,Male,Caucasian,10/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +63424,73126,66275,Probation,feil,jonathan,NULL,Male,Caucasian,10/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +63424,73126,66275,Probation,feil,jonathan,NULL,Male,Caucasian,10/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63404,73100,66253,PRETRIAL,Guillaume,Waldy,NULL,Male,Other,07/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +63404,73100,66253,PRETRIAL,Guillaume,Waldy,NULL,Male,Other,07/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +63404,73100,66253,PRETRIAL,Guillaume,Waldy,NULL,Male,Other,07/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +924,73130,66278,PRETRIAL,WARD,PATRICE,SHANTA,Female,African-American,08/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +924,73130,66278,PRETRIAL,WARD,PATRICE,SHANTA,Female,African-American,08/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-1.43,2,Low,New,1,0 +924,73130,66278,PRETRIAL,WARD,PATRICE,SHANTA,Female,African-American,08/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63415,73113,66264,Probation,isaacs,hugh,NULL,Male,African-American,02/06/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +63415,73113,66264,Probation,isaacs,hugh,NULL,Male,African-American,02/06/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +63415,73113,66264,Probation,isaacs,hugh,NULL,Male,African-American,02/06/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63418,73117,66267,PRETRIAL,Minihane,Michael,NULL,Male,Caucasian,09/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +63418,73117,66267,PRETRIAL,Minihane,Michael,NULL,Male,Caucasian,09/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +63418,73117,66267,PRETRIAL,Minihane,Michael,NULL,Male,Caucasian,09/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63401,73096,66249,PRETRIAL,Senger,Kenneth,NULL,Male,Caucasian,01/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +63401,73096,66249,PRETRIAL,Senger,Kenneth,NULL,Male,Caucasian,01/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +63401,73096,66249,PRETRIAL,Senger,Kenneth,NULL,Male,Caucasian,01/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +9942,73138,66286,PRETRIAL,grant,alvin,NULL,Male,African-American,04/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +9942,73138,66286,PRETRIAL,grant,alvin,NULL,Male,African-American,04/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +9942,73138,66286,PRETRIAL,grant,alvin,NULL,Male,African-American,04/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/13/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +62872,73108,65648,PRETRIAL,JEANLORD,GERALD,NULL,Male,African-American,11/24/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,Copy,1,0 +62872,73108,65648,PRETRIAL,JEANLORD,GERALD,NULL,Male,African-American,11/24/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-2.76,1,Low,Copy,1,0 +62872,73108,65648,PRETRIAL,JEANLORD,GERALD,NULL,Male,African-American,11/24/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +63420,73122,66271,Probation,Rutherford,Lucas,Michael,Male,Caucasian,11/07/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +63420,73122,66271,Probation,Rutherford,Lucas,Michael,Male,Caucasian,11/07/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +63420,73122,66271,Probation,Rutherford,Lucas,Michael,Male,Caucasian,11/07/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +30419,73129,66277,PRETRIAL,Walker,Lakevis,NULL,Male,African-American,04/14/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +30419,73129,66277,PRETRIAL,Walker,Lakevis,NULL,Male,African-American,04/14/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +30419,73129,66277,PRETRIAL,Walker,Lakevis,NULL,Male,African-American,04/14/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63430,73136,66284,PRETRIAL,Brown,Tevin,NULL,Male,African-American,12/08/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.54,10,High,New,1,0 +63430,73136,66284,PRETRIAL,Brown,Tevin,NULL,Male,African-American,12/08/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +63430,73136,66284,PRETRIAL,Brown,Tevin,NULL,Male,African-American,12/08/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63405,73101,66254,PRETRIAL,Brown,Charles,NULL,Male,Caucasian,10/22/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-4.29,1,Low,New,1,0 +63405,73101,66254,PRETRIAL,Brown,Charles,NULL,Male,Caucasian,10/22/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-2.87,1,Low,New,1,0 +63405,73101,66254,PRETRIAL,Brown,Charles,NULL,Male,Caucasian,10/22/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63403,73099,66252,PRETRIAL,PHILIPS,MELANIE,BETH,Female,Caucasian,10/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +63403,73099,66252,PRETRIAL,PHILIPS,MELANIE,BETH,Female,Caucasian,10/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +63403,73099,66252,PRETRIAL,PHILIPS,MELANIE,BETH,Female,Caucasian,10/08/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63423,73127,66274,PRETRIAL,Cooper,Nicole,Marie,Female,African-American,03/14/86,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,4,High,7,Risk of Violence,-1.11,8,High,Copy,1,0 +63423,73127,66274,PRETRIAL,Cooper,Nicole,Marie,Female,African-American,03/14/86,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,4,High,8,Risk of Recidivism,0.1,8,High,Copy,1,0 +63423,73127,66274,PRETRIAL,Cooper,Nicole,Marie,Female,African-American,03/14/86,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,4,High,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +45605,73098,66251,PRETRIAL,Hodge,Lawrence,NULL,Male,Caucasian,05/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +45605,73098,66251,PRETRIAL,Hodge,Lawrence,NULL,Male,Caucasian,05/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +45605,73098,66251,PRETRIAL,Hodge,Lawrence,NULL,Male,Caucasian,05/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63427,73132,66280,PRETRIAL,Ulisse,Sinie,NULL,Female,African-American,01/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +63427,73132,66280,PRETRIAL,Ulisse,Sinie,NULL,Female,African-American,01/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +63427,73132,66280,PRETRIAL,Ulisse,Sinie,NULL,Female,African-American,01/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +63093,73119,65908,PRETRIAL,Weldon,Quinton,NULL,Male,African-American,02/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,Copy,1,0 +63093,73119,65908,PRETRIAL,Weldon,Quinton,NULL,Male,African-American,02/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,Copy,1,0 +63093,73119,65908,PRETRIAL,Weldon,Quinton,NULL,Male,African-American,02/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +63413,73111,66262,Probation,VARONA,ROLANDO,NULL,Male,Hispanic,12/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +63413,73111,66262,Probation,VARONA,ROLANDO,NULL,Male,Hispanic,12/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +63413,73111,66262,Probation,VARONA,ROLANDO,NULL,Male,Hispanic,12/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63407,73103,66256,PRETRIAL,Harden,Barry,Fitzgerald,Male,African-American,03/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +63407,73103,66256,PRETRIAL,Harden,Barry,Fitzgerald,Male,African-American,03/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +63407,73103,66256,PRETRIAL,Harden,Barry,Fitzgerald,Male,African-American,03/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63457,73169,66313,Probation,Stahl,Pavel,NULL,Male,Caucasian,05/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +63457,73169,66313,Probation,Stahl,Pavel,NULL,Male,Caucasian,05/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +63457,73169,66313,Probation,Stahl,Pavel,NULL,Male,Caucasian,05/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63460,73176,66320,Probation,Khan,Adam,NULL,Male,Hispanic,05/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +63460,73176,66320,Probation,Khan,Adam,NULL,Male,Hispanic,05/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +63460,73176,66320,Probation,Khan,Adam,NULL,Male,Hispanic,05/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63464,73182,66325,Probation,VILLATA,JOSE,NULL,Male,Hispanic,03/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/14/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +63464,73182,66325,Probation,VILLATA,JOSE,NULL,Male,Hispanic,03/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/14/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +63464,73182,66325,Probation,VILLATA,JOSE,NULL,Male,Hispanic,03/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63449,73161,66306,Probation,salerno,christian,NULL,Male,Caucasian,12/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +63449,73161,66306,Probation,salerno,christian,NULL,Male,Caucasian,12/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +63449,73161,66306,Probation,salerno,christian,NULL,Male,Caucasian,12/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63324,73168,66168,PRETRIAL,Garcia,Emilio,NULL,Male,Hispanic,12/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,Copy,1,0 +63324,73168,66168,PRETRIAL,Garcia,Emilio,NULL,Male,Hispanic,12/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,Copy,1,0 +63324,73168,66168,PRETRIAL,Garcia,Emilio,NULL,Male,Hispanic,12/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +42760,73140,42620,PRETRIAL,Hopkins,Robert,Vincent,Male,Caucasian,06/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,2,Medium,7,Risk of Violence,-3,1,Low,Copy,1,0 +42760,73140,42620,PRETRIAL,Hopkins,Robert,Vincent,Male,Caucasian,06/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +42760,73140,42620,PRETRIAL,Hopkins,Robert,Vincent,Male,Caucasian,06/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +63442,73153,66298,PRETRIAL,Geimer,Jesse,NULL,Male,Caucasian,08/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +63442,73153,66298,PRETRIAL,Geimer,Jesse,NULL,Male,Caucasian,08/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +63442,73153,66298,PRETRIAL,Geimer,Jesse,NULL,Male,Caucasian,08/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63454,73166,66311,PRETRIAL,ayers,nathan,NULL,Male,Caucasian,03/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +63454,73166,66311,PRETRIAL,ayers,nathan,NULL,Male,Caucasian,03/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +63454,73166,66311,PRETRIAL,ayers,nathan,NULL,Male,Caucasian,03/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63436,73145,66292,PRETRIAL,Mighty,Camille,NULL,Female,African-American,04/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.27,3,Low,New,1,0 +63436,73145,66292,PRETRIAL,Mighty,Camille,NULL,Female,African-American,04/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +63436,73145,66292,PRETRIAL,Mighty,Camille,NULL,Female,African-American,04/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63466,73184,66327,PRETRIAL,Bess,Megan,NULL,Female,Caucasian,05/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +63466,73184,66327,PRETRIAL,Bess,Megan,NULL,Female,Caucasian,05/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +63466,73184,66327,PRETRIAL,Bess,Megan,NULL,Female,Caucasian,05/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +36680,54668,49753,PRETRIAL,Jones,Robert,NULL,Male,African-American,03/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,4,High,7,Risk of Violence,-0.52,10,High,New,1,0 +36680,54668,49753,PRETRIAL,Jones,Robert,NULL,Male,African-American,03/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +36680,54668,49753,PRETRIAL,Jones,Robert,NULL,Male,African-American,03/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +63439,73150,66295,PRETRIAL,JACKSON,CHARITY,NULL,Female,African-American,05/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +63439,73150,66295,PRETRIAL,JACKSON,CHARITY,NULL,Female,African-American,05/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +63439,73150,66295,PRETRIAL,JACKSON,CHARITY,NULL,Female,African-American,05/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63463,73180,66324,PRETRIAL,Mathis,marquel,NULL,Male,African-American,06/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,4,High,7,Risk of Violence,-1.03,8,High,New,1,0 +63463,73180,66324,PRETRIAL,Mathis,marquel,NULL,Male,African-American,06/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,4,High,8,Risk of Recidivism,0.26,8,High,New,1,0 +63463,73180,66324,PRETRIAL,Mathis,marquel,NULL,Male,African-American,06/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63458,73171,66315,Probation,kam,farrell,NULL,Female,Caucasian,09/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,New,1,0 +63458,73171,66315,Probation,kam,farrell,NULL,Female,Caucasian,09/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,8,High,New,1,0 +63458,73171,66315,Probation,kam,farrell,NULL,Female,Caucasian,09/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +30354,73178,66322,PRETRIAL,ANDRE,MILO,NULL,Male,African-American,04/27/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,4,High,7,Risk of Violence,-0.64,9,High,New,1,0 +30354,73178,66322,PRETRIAL,ANDRE,MILO,NULL,Male,African-American,04/27/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,4,High,8,Risk of Recidivism,0.38,9,High,New,1,0 +30354,73178,66322,PRETRIAL,ANDRE,MILO,NULL,Male,African-American,04/27/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51413,73143,66290,PRETRIAL,FELDER,JOEL,NULL,Male,African-American,08/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,New,1,0 +51413,73143,66290,PRETRIAL,FELDER,JOEL,NULL,Male,African-American,08/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,4,High,8,Risk of Recidivism,0.41,9,High,New,1,0 +51413,73143,66290,PRETRIAL,FELDER,JOEL,NULL,Male,African-American,08/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63445,73157,66302,Probation,REYES,GIUSSEPPE,NULL,Male,Hispanic,12/15/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/14/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +63445,73157,66302,Probation,REYES,GIUSSEPPE,NULL,Male,Hispanic,12/15/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +63445,73157,66302,Probation,REYES,GIUSSEPPE,NULL,Male,Hispanic,12/15/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/14/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +63443,73155,66300,Probation,Tobin,Jody,NULL,Male,Other,01/20/70,17,All Scales,Intake,English,Post Sentence,Probation,Married,5/14/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +63443,73155,66300,Probation,Tobin,Jody,NULL,Male,Other,01/20/70,17,All Scales,Intake,English,Post Sentence,Probation,Married,5/14/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +63443,73155,66300,Probation,Tobin,Jody,NULL,Male,Other,01/20/70,17,All Scales,Intake,English,Post Sentence,Probation,Married,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63441,73152,66297,PRETRIAL,Tillman,Latoya,Yvette,Female,African-American,08/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +63441,73152,66297,PRETRIAL,Tillman,Latoya,Yvette,Female,African-American,08/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +63441,73152,66297,PRETRIAL,Tillman,Latoya,Yvette,Female,African-American,08/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63447,73159,66304,Probation,pace,steven,NULL,Male,Caucasian,12/18/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/14/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +63447,73159,66304,Probation,pace,steven,NULL,Male,Caucasian,12/18/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +63447,73159,66304,Probation,pace,steven,NULL,Male,Caucasian,12/18/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63467,73185,66328,PRETRIAL,Eutsey,Victoria,Shanell,Female,African-American,07/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +63467,73185,66328,PRETRIAL,Eutsey,Victoria,Shanell,Female,African-American,07/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +63467,73185,66328,PRETRIAL,Eutsey,Victoria,Shanell,Female,African-American,07/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63452,73164,66309,PRETRIAL,BRYANT,DAVID,NULL,Male,African-American,10/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +63452,73164,66309,PRETRIAL,BRYANT,DAVID,NULL,Male,African-American,10/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +63452,73164,66309,PRETRIAL,BRYANT,DAVID,NULL,Male,African-American,10/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63437,73147,66293,PRETRIAL,Perez,Rissely,NULL,Female,Caucasian,08/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +63437,73147,66293,PRETRIAL,Perez,Rissely,NULL,Female,Caucasian,08/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +63437,73147,66293,PRETRIAL,Perez,Rissely,NULL,Female,Caucasian,08/24/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +36262,73181,35524,PRETRIAL,Rodriguez,Freddy,NULL,Male,Caucasian,05/23/60,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,Copy,1,0 +36262,73181,35524,PRETRIAL,Rodriguez,Freddy,NULL,Male,Caucasian,05/23/60,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,Copy,1,0 +36262,73181,35524,PRETRIAL,Rodriguez,Freddy,NULL,Male,Caucasian,05/23/60,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +63440,73151,66296,PRETRIAL,Garrison,Tina,Marie,Female,Caucasian,03/12/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +63440,73151,66296,PRETRIAL,Garrison,Tina,Marie,Female,Caucasian,03/12/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.8,5,Medium,New,1,0 +63440,73151,66296,PRETRIAL,Garrison,Tina,Marie,Female,Caucasian,03/12/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +63448,73160,66305,Probation,Anestal,Isabelle,NULL,Female,African-American,08/18/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +63448,73160,66305,Probation,Anestal,Isabelle,NULL,Female,African-American,08/18/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +63448,73160,66305,Probation,Anestal,Isabelle,NULL,Female,African-American,08/18/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63434,73142,66289,PRETRIAL,DOROBIALA,CYNTHIA,E,Female,Caucasian,04/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/14/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +63434,73142,66289,PRETRIAL,DOROBIALA,CYNTHIA,E,Female,Caucasian,04/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/14/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +63434,73142,66289,PRETRIAL,DOROBIALA,CYNTHIA,E,Female,Caucasian,04/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63451,73163,66308,Probation,NOTH,FREDERICK,M,Male,Caucasian,11/19/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +63451,73163,66308,Probation,NOTH,FREDERICK,M,Male,Caucasian,11/19/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +63451,73163,66308,Probation,NOTH,FREDERICK,M,Male,Caucasian,11/19/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63461,73177,66321,PRETRIAL,Hewitt,James,NULL,Male,African-American,08/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,4,High,7,Risk of Violence,0.46,10,High,New,1,0 +63461,73177,66321,PRETRIAL,Hewitt,James,NULL,Male,African-American,08/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,4,High,8,Risk of Recidivism,1.51,10,High,New,1,0 +63461,73177,66321,PRETRIAL,Hewitt,James,NULL,Male,African-American,08/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,4,High,18,Risk of Failure to Appear,38,10,High,New,1,0 +63435,73144,66291,PRETRIAL,Styles,Thomas,De Quincy,Male,African-American,10/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +63435,73144,66291,PRETRIAL,Styles,Thomas,De Quincy,Male,African-American,10/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +63435,73144,66291,PRETRIAL,Styles,Thomas,De Quincy,Male,African-American,10/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63453,73165,66310,Probation,Vieira,Shane,NULL,Male,Caucasian,11/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +63453,73165,66310,Probation,Vieira,Shane,NULL,Male,Caucasian,11/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +63453,73165,66310,Probation,Vieira,Shane,NULL,Male,Caucasian,11/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +63462,73179,66323,PRETRIAL,SHIVERS,CHEYENNE,NULL,Female,African-American,05/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +63462,73179,66323,PRETRIAL,SHIVERS,CHEYENNE,NULL,Female,African-American,05/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +63462,73179,66323,PRETRIAL,SHIVERS,CHEYENNE,NULL,Female,African-American,05/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +63446,73158,66303,Probation,Olivera,Geraldy,NULL,Male,African-American,04/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +63446,73158,66303,Probation,Olivera,Geraldy,NULL,Male,African-American,04/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +63446,73158,66303,Probation,Olivera,Geraldy,NULL,Male,African-American,04/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63459,73172,66316,PRETRIAL,ELAM,LISA,NULL,Female,Caucasian,12/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +63459,73172,66316,PRETRIAL,ELAM,LISA,NULL,Female,Caucasian,12/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +63459,73172,66316,PRETRIAL,ELAM,LISA,NULL,Female,Caucasian,12/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/14/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63438,73149,66294,PRETRIAL,LIGGINS,ADRIAN,DIMETRIAN,Male,African-American,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,Copy,1,0 +63438,73149,66294,PRETRIAL,LIGGINS,ADRIAN,DIMETRIAN,Male,African-American,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +63438,73149,66294,PRETRIAL,LIGGINS,ADRIAN,DIMETRIAN,Male,African-American,09/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +63450,73162,66307,Probation,Sitra,Vincent,NULL,Male,Hispanic,05/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +63450,73162,66307,Probation,Sitra,Vincent,NULL,Male,Hispanic,05/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +63450,73162,66307,Probation,Sitra,Vincent,NULL,Male,Hispanic,05/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63456,73170,66314,Probation,DEJESUSRODRIGUEZ,FREDY,NULL,Male,Hispanic,12/22/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/14/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +63456,73170,66314,Probation,DEJESUSRODRIGUEZ,FREDY,NULL,Male,Hispanic,12/22/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/14/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +63456,73170,66314,Probation,DEJESUSRODRIGUEZ,FREDY,NULL,Male,Hispanic,12/22/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63433,73141,66288,PRETRIAL,Newman,Howard,NULL,Male,Caucasian,09/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +63433,73141,66288,PRETRIAL,Newman,Howard,NULL,Male,Caucasian,09/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +63433,73141,66288,PRETRIAL,Newman,Howard,NULL,Male,Caucasian,09/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52282,73175,66319,PRETRIAL,goffee,caswell,antonio,Male,African-American,10/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +52282,73175,66319,PRETRIAL,goffee,caswell,antonio,Male,African-American,10/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +52282,73175,66319,PRETRIAL,goffee,caswell,antonio,Male,African-American,10/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63455,73167,66312,Probation,Montes,Charles,NULL,Male,Caucasian,05/17/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/14/14 0:00,2,Medium,7,Risk of Violence,-2.52,3,Low,New,1,0 +63455,73167,66312,Probation,Montes,Charles,NULL,Male,Caucasian,05/17/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/14/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +63455,73167,66312,Probation,Montes,Charles,NULL,Male,Caucasian,05/17/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/14/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58045,73146,60226,Probation,selzer,david,NULL,Male,Caucasian,01/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,Copy,1,0 +58045,73146,60226,Probation,selzer,david,NULL,Male,Caucasian,01/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,Copy,1,0 +58045,73146,60226,Probation,selzer,david,NULL,Male,Caucasian,01/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +53566,73212,66352,PRETRIAL,DINAPOLI,STEVEN,NULL,Male,Caucasian,04/26/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/15/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +53566,73212,66352,PRETRIAL,DINAPOLI,STEVEN,NULL,Male,Caucasian,04/26/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/15/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +53566,73212,66352,PRETRIAL,DINAPOLI,STEVEN,NULL,Male,Caucasian,04/26/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63482,73204,66345,Probation,JOHNSON,SHADAE,NULL,Female,African-American,04/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +63482,73204,66345,Probation,JOHNSON,SHADAE,NULL,Female,African-American,04/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +63482,73204,66345,Probation,JOHNSON,SHADAE,NULL,Female,African-American,04/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63471,73191,66333,PRETRIAL,Robinson,Antoinette,NULL,Female,African-American,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +63471,73191,66333,PRETRIAL,Robinson,Antoinette,NULL,Female,African-American,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +63471,73191,66333,PRETRIAL,Robinson,Antoinette,NULL,Female,African-American,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63469,73188,66330,PRETRIAL,Boudreau,Joseph,Young,Male,Caucasian,03/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +63469,73188,66330,PRETRIAL,Boudreau,Joseph,Young,Male,Caucasian,03/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +63469,73188,66330,PRETRIAL,Boudreau,Joseph,Young,Male,Caucasian,03/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54763,73209,66349,PRETRIAL,Peralta,Ivan,NULL,Male,Hispanic,09/22/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/15/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +54763,73209,66349,PRETRIAL,Peralta,Ivan,NULL,Male,Hispanic,09/22/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/15/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +54763,73209,66349,PRETRIAL,Peralta,Ivan,NULL,Male,Hispanic,09/22/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63115,73207,65937,PRETRIAL,Alcivar,Victor,NULL,Male,Hispanic,04/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,5/15/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,Copy,1,0 +63115,73207,65937,PRETRIAL,Alcivar,Victor,NULL,Male,Hispanic,04/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,5/15/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,Copy,1,0 +63115,73207,65937,PRETRIAL,Alcivar,Victor,NULL,Male,Hispanic,04/23/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +35747,73186,34977,PRETRIAL,Golden,Robert,NULL,Male,Caucasian,08/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,Copy,1,0 +35747,73186,34977,PRETRIAL,Golden,Robert,NULL,Male,Caucasian,08/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,Copy,1,0 +35747,73186,34977,PRETRIAL,Golden,Robert,NULL,Male,Caucasian,08/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,Copy,1,0 +7206,73193,6793,DRRD,Thelemaque,Peterson,Joseph,Male,African-American,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,4,High,7,Risk of Violence,-1.23,8,High,Copy,1,0 +7206,73193,6793,DRRD,Thelemaque,Peterson,Joseph,Male,African-American,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,4,High,8,Risk of Recidivism,0.57,9,High,Copy,1,0 +7206,73193,6793,DRRD,Thelemaque,Peterson,Joseph,Male,African-American,12/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +63488,73214,66354,Probation,Wyatts,Renee,NULL,Female,African-American,01/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +63488,73214,66354,Probation,Wyatts,Renee,NULL,Female,African-American,01/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,7,Medium,New,1,0 +63488,73214,66354,Probation,Wyatts,Renee,NULL,Female,African-American,01/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63495,73235,66373,Probation,CAMACHO,GLORIMAR,NULL,Female,Hispanic,01/03/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +63495,73235,66373,Probation,CAMACHO,GLORIMAR,NULL,Female,Hispanic,01/03/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +63495,73235,66373,Probation,CAMACHO,GLORIMAR,NULL,Female,Hispanic,01/03/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63479,73202,66343,Probation,Schulman,Keith,NULL,Male,Caucasian,11/01/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +63479,73202,66343,Probation,Schulman,Keith,NULL,Male,Caucasian,11/01/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +63479,73202,66343,Probation,Schulman,Keith,NULL,Male,Caucasian,11/01/56,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63491,73219,66359,Probation,Estiverne,Islene,Betty,Female,African-American,02/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +63491,73219,66359,Probation,Estiverne,Islene,Betty,Female,African-American,02/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,10,High,New,1,0 +63491,73219,66359,Probation,Estiverne,Islene,Betty,Female,African-American,02/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +63475,73198,66339,Probation,Nicholas,Sonya,NULL,Female,Caucasian,03/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +63475,73198,66339,Probation,Nicholas,Sonya,NULL,Female,Caucasian,03/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +63475,73198,66339,Probation,Nicholas,Sonya,NULL,Female,Caucasian,03/17/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +43269,73232,66370,PRETRIAL,Guillen,Gerardo,NULL,Male,Caucasian,10/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +43269,73232,66370,PRETRIAL,Guillen,Gerardo,NULL,Male,Caucasian,10/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +43269,73232,66370,PRETRIAL,Guillen,Gerardo,NULL,Male,Caucasian,10/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63489,73215,66355,Probation,Robionson,Rod,NULL,Male,African-American,10/08/51,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/15/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +63489,73215,66355,Probation,Robionson,Rod,NULL,Male,African-American,10/08/51,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/15/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +63489,73215,66355,Probation,Robionson,Rod,NULL,Male,African-American,10/08/51,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63472,73194,66335,PRETRIAL,DELGADO,EDDIE,NULL,Male,Hispanic,02/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +63472,73194,66335,PRETRIAL,DELGADO,EDDIE,NULL,Male,Hispanic,02/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +63472,73194,66335,PRETRIAL,DELGADO,EDDIE,NULL,Male,Hispanic,02/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63492,73220,66360,Probation,Jackson,brandon,NULL,Male,African-American,07/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +63492,73220,66360,Probation,Jackson,brandon,NULL,Male,African-American,07/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +63492,73220,66360,Probation,Jackson,brandon,NULL,Male,African-American,07/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63484,73206,66347,Probation,Fernandez,Jessica,NULL,Female,Hispanic,07/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +63484,73206,66347,Probation,Fernandez,Jessica,NULL,Female,Hispanic,07/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-1.61,2,Low,New,1,0 +63484,73206,66347,Probation,Fernandez,Jessica,NULL,Female,Hispanic,07/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63493,73224,66364,PRETRIAL,Fenner,Shawn,NULL,Male,Caucasian,07/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/14 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,New,1,0 +63493,73224,66364,PRETRIAL,Fenner,Shawn,NULL,Male,Caucasian,07/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +63493,73224,66364,PRETRIAL,Fenner,Shawn,NULL,Male,Caucasian,07/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63485,73208,66348,Probation,harris,randall,NULL,Male,Caucasian,11/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +63485,73208,66348,Probation,harris,randall,NULL,Male,Caucasian,11/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +63485,73208,66348,Probation,harris,randall,NULL,Male,Caucasian,11/01/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +36184,73222,66362,PRETRIAL,Julien,Brandon,NULL,Male,African-American,07/31/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +36184,73222,66362,PRETRIAL,Julien,Brandon,NULL,Male,African-American,07/31/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,4,High,8,Risk of Recidivism,0.66,10,High,New,1,0 +36184,73222,66362,PRETRIAL,Julien,Brandon,NULL,Male,African-American,07/31/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +63480,73201,66342,PRETRIAL,PREMOCK,ZACHARY,NULL,Male,Caucasian,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +63480,73201,66342,PRETRIAL,PREMOCK,ZACHARY,NULL,Male,Caucasian,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +63480,73201,66342,PRETRIAL,PREMOCK,ZACHARY,NULL,Male,Caucasian,11/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63476,73199,66340,Probation,sarkozy,nicholas,NULL,Male,Hispanic,01/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +63476,73199,66340,Probation,sarkozy,nicholas,NULL,Male,Hispanic,01/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +63476,73199,66340,Probation,sarkozy,nicholas,NULL,Male,Hispanic,01/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63473,73195,66336,PRETRIAL,Wilson,Jaleesa,Maxine,Female,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +63473,73195,66336,PRETRIAL,Wilson,Jaleesa,Maxine,Female,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +63473,73195,66336,PRETRIAL,Wilson,Jaleesa,Maxine,Female,African-American,12/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +29239,73192,66334,PRETRIAL,Roux,Sabrina,NULL,Female,Caucasian,11/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/14 0:00,2,Medium,7,Risk of Violence,-2.92,2,Low,New,1,0 +29239,73192,66334,PRETRIAL,Roux,Sabrina,NULL,Female,Caucasian,11/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +29239,73192,66334,PRETRIAL,Roux,Sabrina,NULL,Female,Caucasian,11/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/15/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63483,73205,66346,Probation,Green,Ronald,Allen,Male,Caucasian,04/15/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/15/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +63483,73205,66346,Probation,Green,Ronald,Allen,Male,Caucasian,04/15/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/15/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +63483,73205,66346,Probation,Green,Ronald,Allen,Male,Caucasian,04/15/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63478,73200,66341,PRETRIAL,Lantiguavargas,Winfi,NULL,Male,Hispanic,12/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +63478,73200,66341,PRETRIAL,Lantiguavargas,Winfi,NULL,Male,Hispanic,12/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +63478,73200,66341,PRETRIAL,Lantiguavargas,Winfi,NULL,Male,Hispanic,12/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63468,73187,66329,PRETRIAL,COTTO,MICHAEL,PHILLIP,Male,Caucasian,11/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +63468,73187,66329,PRETRIAL,COTTO,MICHAEL,PHILLIP,Male,Caucasian,11/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +63468,73187,66329,PRETRIAL,COTTO,MICHAEL,PHILLIP,Male,Caucasian,11/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53064,73221,66361,PRETRIAL,Isaac,Erika,Jesscia,Female,African-American,06/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,New,1,0 +53064,73221,66361,PRETRIAL,Isaac,Erika,Jesscia,Female,African-American,06/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,8,High,New,1,0 +53064,73221,66361,PRETRIAL,Isaac,Erika,Jesscia,Female,African-American,06/03/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63470,73189,66331,PRETRIAL,FRIEDMAN,HEATHER,NULL,Female,Caucasian,07/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +63470,73189,66331,PRETRIAL,FRIEDMAN,HEATHER,NULL,Female,Caucasian,07/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +63470,73189,66331,PRETRIAL,FRIEDMAN,HEATHER,NULL,Female,Caucasian,07/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +15292,73190,66332,Probation,goodwin,david,NULL,Male,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,4,High,7,Risk of Violence,-0.65,9,High,New,1,0 +15292,73190,66332,Probation,goodwin,david,NULL,Male,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,4,High,8,Risk of Recidivism,1.36,10,High,New,1,0 +15292,73190,66332,Probation,goodwin,david,NULL,Male,African-American,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/15/14 0:00,4,High,18,Risk of Failure to Appear,37,10,High,New,1,0 +63487,73211,66351,Probation,Ayala,Alvaro,NULL,Male,Hispanic,10/23/72,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,5/15/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +63487,73211,66351,Probation,Ayala,Alvaro,NULL,Male,Hispanic,10/23/72,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,5/15/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +63487,73211,66351,Probation,Ayala,Alvaro,NULL,Male,Hispanic,10/23/72,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63490,73218,66358,Probation,rice,christopher,NULL,Male,Caucasian,01/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +63490,73218,66358,Probation,rice,christopher,NULL,Male,Caucasian,01/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +63490,73218,66358,Probation,rice,christopher,NULL,Male,Caucasian,01/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63481,73203,66344,Probation,Williams,Ricurt,NULL,Male,African-American,11/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +63481,73203,66344,Probation,Williams,Ricurt,NULL,Male,African-American,11/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +63481,73203,66344,Probation,Williams,Ricurt,NULL,Male,African-American,11/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63486,73210,66350,PRETRIAL,Mcgriff,Andre,NULL,Male,African-American,07/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +63486,73210,66350,PRETRIAL,Mcgriff,Andre,NULL,Male,African-American,07/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +63486,73210,66350,PRETRIAL,Mcgriff,Andre,NULL,Male,African-American,07/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/15/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63520,73268,66405,Probation,mersan,stevenson,NULL,Male,African-American,01/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +63520,73268,66405,Probation,mersan,stevenson,NULL,Male,African-American,01/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +63520,73268,66405,Probation,mersan,stevenson,NULL,Male,African-American,01/15/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63508,73247,66384,Probation,Tynes,Teneshia,NULL,Female,African-American,07/21/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +63508,73247,66384,Probation,Tynes,Teneshia,NULL,Female,African-American,07/21/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +63508,73247,66384,Probation,Tynes,Teneshia,NULL,Female,African-American,07/21/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +22825,73242,21993,PRETRIAL,WATKINS,FEDERICO,NULL,Male,Caucasian,04/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,Copy,1,0 +22825,73242,21993,PRETRIAL,WATKINS,FEDERICO,NULL,Male,Caucasian,04/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,Copy,1,0 +22825,73242,21993,PRETRIAL,WATKINS,FEDERICO,NULL,Male,Caucasian,04/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +63510,73252,66389,PRETRIAL,Pires,Phyllis,NULL,Female,Caucasian,07/14/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/16/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +63510,73252,66389,PRETRIAL,Pires,Phyllis,NULL,Female,Caucasian,07/14/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/16/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +63510,73252,66389,PRETRIAL,Pires,Phyllis,NULL,Female,Caucasian,07/14/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63517,73263,66400,PRETRIAL,BROOKS,ZACHARY,NULL,Male,Caucasian,08/01/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +63517,73263,66400,PRETRIAL,BROOKS,ZACHARY,NULL,Male,Caucasian,08/01/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,4,High,8,Risk of Recidivism,0.14,8,High,New,1,0 +63517,73263,66400,PRETRIAL,BROOKS,ZACHARY,NULL,Male,Caucasian,08/01/97,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63509,73250,66387,PRETRIAL,LAW,TRAVIS,NULL,Male,African-American,11/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +63509,73250,66387,PRETRIAL,LAW,TRAVIS,NULL,Male,African-American,11/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +63509,73250,66387,PRETRIAL,LAW,TRAVIS,NULL,Male,African-American,11/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +31256,73257,66394,PRETRIAL,somra,rajindra,NULL,Male,Other,01/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +31256,73257,66394,PRETRIAL,somra,rajindra,NULL,Male,Other,01/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +31256,73257,66394,PRETRIAL,somra,rajindra,NULL,Male,Other,01/08/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63505,73243,66380,PRETRIAL,Baziak,Jocob,John,Male,Caucasian,09/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +63505,73243,66380,PRETRIAL,Baziak,Jocob,John,Male,Caucasian,09/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +63505,73243,66380,PRETRIAL,Baziak,Jocob,John,Male,Caucasian,09/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63504,73241,66379,PRETRIAL,McCray,Precious,NULL,Female,African-American,10/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,New,1,0 +63504,73241,66379,PRETRIAL,McCray,Precious,NULL,Female,African-American,10/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,8,High,New,1,0 +63504,73241,66379,PRETRIAL,McCray,Precious,NULL,Female,African-American,10/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63506,73245,66382,Probation,Vasquez,Victor,NULL,Male,Hispanic,09/15/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +63506,73245,66382,Probation,Vasquez,Victor,NULL,Male,Hispanic,09/15/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +63506,73245,66382,Probation,Vasquez,Victor,NULL,Male,Hispanic,09/15/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63516,73262,66399,Probation,Dillon,Dennis,NULL,Male,Caucasian,12/18/50,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/16/14 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +63516,73262,66399,Probation,Dillon,Dennis,NULL,Male,Caucasian,12/18/50,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/16/14 0:00,1,Low,8,Risk of Recidivism,-2.69,1,Low,New,1,0 +63516,73262,66399,Probation,Dillon,Dennis,NULL,Male,Caucasian,12/18/50,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59989,73266,66403,PRETRIAL,Rowe,Derrick,NULL,Male,Other,08/02/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +59989,73266,66403,PRETRIAL,Rowe,Derrick,NULL,Male,Other,08/02/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +59989,73266,66403,PRETRIAL,Rowe,Derrick,NULL,Male,Other,08/02/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54384,73249,66386,PRETRIAL,Perkins,Sidney,NULL,Male,Caucasian,11/21/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +54384,73249,66386,PRETRIAL,Perkins,Sidney,NULL,Male,Caucasian,11/21/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +54384,73249,66386,PRETRIAL,Perkins,Sidney,NULL,Male,Caucasian,11/21/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63512,73253,66390,Probation,Stokes,Shamia,NULL,Female,African-American,06/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,2,Medium,7,Risk of Violence,-2.71,2,Low,New,1,0 +63512,73253,66390,Probation,Stokes,Shamia,NULL,Female,African-American,06/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +63512,73253,66390,Probation,Stokes,Shamia,NULL,Female,African-American,06/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +2100,73244,66381,PRETRIAL,RAMSEY,MARSHALL,L,Male,African-American,01/02/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +2100,73244,66381,PRETRIAL,RAMSEY,MARSHALL,L,Male,African-American,01/02/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +2100,73244,66381,PRETRIAL,RAMSEY,MARSHALL,L,Male,African-American,01/02/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63518,73265,66402,PRETRIAL,Cunningham,Jon,NULL,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +63518,73265,66402,PRETRIAL,Cunningham,Jon,NULL,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +63518,73265,66402,PRETRIAL,Cunningham,Jon,NULL,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +42680,73258,66395,PRETRIAL,Miller,Kyle,NULL,Male,African-American,04/08/86,17,All Scales,Intake,English,Other,Probation,Single,5/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +42680,73258,66395,PRETRIAL,Miller,Kyle,NULL,Male,African-American,04/08/86,17,All Scales,Intake,English,Other,Probation,Single,5/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,8,High,New,1,0 +42680,73258,66395,PRETRIAL,Miller,Kyle,NULL,Male,African-American,04/08/86,17,All Scales,Intake,English,Other,Probation,Single,5/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,3,Low,New,1,0 +54257,73256,66393,Probation,MESYEUX,CHRISTINE,NULL,Female,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,4,High,7,Risk of Violence,-0.61,10,High,New,1,0 +54257,73256,66393,Probation,MESYEUX,CHRISTINE,NULL,Female,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,4,High,8,Risk of Recidivism,0.31,9,High,New,1,0 +54257,73256,66393,Probation,MESYEUX,CHRISTINE,NULL,Female,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +63514,73259,66396,Probation,Lee,David,NULL,Male,Caucasian,05/10/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/16/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +63514,73259,66396,Probation,Lee,David,NULL,Male,Caucasian,05/10/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/16/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +63514,73259,66396,Probation,Lee,David,NULL,Male,Caucasian,05/10/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63511,73251,66388,PRETRIAL,Odell,Brandon,Thomas,Male,Caucasian,07/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +63511,73251,66388,PRETRIAL,Odell,Brandon,Thomas,Male,Caucasian,07/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +63511,73251,66388,PRETRIAL,Odell,Brandon,Thomas,Male,Caucasian,07/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30520,73264,66401,PRETRIAL,Law,Timothy,J,Male,African-American,08/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,4,High,7,Risk of Violence,-0.57,10,High,New,1,0 +30520,73264,66401,PRETRIAL,Law,Timothy,J,Male,African-American,08/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,4,High,8,Risk of Recidivism,1.03,10,High,New,1,0 +30520,73264,66401,PRETRIAL,Law,Timothy,J,Male,African-American,08/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +49199,73254,66391,PRETRIAL,Barbosa,Diego,NULL,Male,Hispanic,11/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +49199,73254,66391,PRETRIAL,Barbosa,Diego,NULL,Male,Hispanic,11/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +49199,73254,66391,PRETRIAL,Barbosa,Diego,NULL,Male,Hispanic,11/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/16/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63515,73261,66398,PRETRIAL,WALKER,MAURICE,NULL,Male,African-American,06/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +63515,73261,66398,PRETRIAL,WALKER,MAURICE,NULL,Male,African-American,06/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +63515,73261,66398,PRETRIAL,WALKER,MAURICE,NULL,Male,African-American,06/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63503,73240,66378,PRETRIAL,Hughes,Hubert,Marvin,Male,African-American,01/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +63503,73240,66378,PRETRIAL,Hughes,Hubert,Marvin,Male,African-American,01/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +63503,73240,66378,PRETRIAL,Hughes,Hubert,Marvin,Male,African-American,01/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63507,73246,66383,PRETRIAL,QUIRAMAMUNERA,MARIA,NULL,Female,Hispanic,10/07/67,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +63507,73246,66383,PRETRIAL,QUIRAMAMUNERA,MARIA,NULL,Female,Hispanic,10/07/67,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +63507,73246,66383,PRETRIAL,QUIRAMAMUNERA,MARIA,NULL,Female,Hispanic,10/07/67,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,5/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +27871,73248,66385,Probation,Vanderkuyp,Jean,Pierre,Male,Caucasian,03/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +27871,73248,66385,Probation,Vanderkuyp,Jean,Pierre,Male,Caucasian,03/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +27871,73248,66385,Probation,Vanderkuyp,Jean,Pierre,Male,Caucasian,03/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/16/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63531,73282,66418,PRETRIAL,metellus,Marvens,NULL,Male,African-American,07/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,5/17/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,Copy,1,0 +63531,73282,66418,PRETRIAL,metellus,Marvens,NULL,Male,African-American,07/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,5/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +63531,73282,66418,PRETRIAL,metellus,Marvens,NULL,Male,African-American,07/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,5/17/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +63521,73269,66406,PRETRIAL,Garsonbaquero,Julian,NULL,Male,Hispanic,01/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +63521,73269,66406,PRETRIAL,Garsonbaquero,Julian,NULL,Male,Hispanic,01/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +63521,73269,66406,PRETRIAL,Garsonbaquero,Julian,NULL,Male,Hispanic,01/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63525,73275,66412,PRETRIAL,Levers,Herbert,Deandonova,Male,Other,11/01/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +63525,73275,66412,PRETRIAL,Levers,Herbert,Deandonova,Male,Other,11/01/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +63525,73275,66412,PRETRIAL,Levers,Herbert,Deandonova,Male,Other,11/01/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63527,73277,66414,PRETRIAL,Patrick,Amanda,Fae,Female,Caucasian,01/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +63527,73277,66414,PRETRIAL,Patrick,Amanda,Fae,Female,Caucasian,01/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +63527,73277,66414,PRETRIAL,Patrick,Amanda,Fae,Female,Caucasian,01/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63524,73272,66409,PRETRIAL,Patino,Fernando,Luis,Male,Caucasian,05/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/17/14 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +63524,73272,66409,PRETRIAL,Patino,Fernando,Luis,Male,Caucasian,05/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +63524,73272,66409,PRETRIAL,Patino,Fernando,Luis,Male,Caucasian,05/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/17/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63529,73279,66416,PRETRIAL,SOLAGES,GREGORY,NULL,Male,Caucasian,04/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/17/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +63529,73279,66416,PRETRIAL,SOLAGES,GREGORY,NULL,Male,Caucasian,04/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/17/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +63529,73279,66416,PRETRIAL,SOLAGES,GREGORY,NULL,Male,Caucasian,04/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63522,73270,66407,PRETRIAL,Goindoo,Roger,NULL,Male,Other,08/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/17/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +63522,73270,66407,PRETRIAL,Goindoo,Roger,NULL,Male,Other,08/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/17/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +63522,73270,66407,PRETRIAL,Goindoo,Roger,NULL,Male,Other,08/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57943,73274,66411,PRETRIAL,FRAZIER,DIJOHN,NULL,Male,African-American,02/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,4,High,7,Risk of Violence,-0.37,10,High,New,1,0 +57943,73274,66411,PRETRIAL,FRAZIER,DIJOHN,NULL,Male,African-American,02/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,4,High,8,Risk of Recidivism,0.74,10,High,New,1,0 +57943,73274,66411,PRETRIAL,FRAZIER,DIJOHN,NULL,Male,African-American,02/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63530,73280,66417,PRETRIAL,Walker,Lavoris,NULL,Male,African-American,05/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +63530,73280,66417,PRETRIAL,Walker,Lavoris,NULL,Male,African-American,05/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +63530,73280,66417,PRETRIAL,Walker,Lavoris,NULL,Male,African-American,05/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63523,73271,66408,PRETRIAL,TENREYRO,HENRY,NULL,Male,Caucasian,11/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +63523,73271,66408,PRETRIAL,TENREYRO,HENRY,NULL,Male,Caucasian,11/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +63523,73271,66408,PRETRIAL,TENREYRO,HENRY,NULL,Male,Caucasian,11/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63528,73278,66415,PRETRIAL,POMALAZA,MARCO,ANTONIO,Male,Caucasian,08/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +63528,73278,66415,PRETRIAL,POMALAZA,MARCO,ANTONIO,Male,Caucasian,08/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +63528,73278,66415,PRETRIAL,POMALAZA,MARCO,ANTONIO,Male,Caucasian,08/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60329,73273,66410,PRETRIAL,DORSAINVILLE,MICHEL,NULL,Male,Other,09/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/17/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +60329,73273,66410,PRETRIAL,DORSAINVILLE,MICHEL,NULL,Male,Other,09/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/17/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +60329,73273,66410,PRETRIAL,DORSAINVILLE,MICHEL,NULL,Male,Other,09/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63526,73276,66413,PRETRIAL,Richards,Floyd,J,Male,African-American,04/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +63526,73276,66413,PRETRIAL,Richards,Floyd,J,Male,African-American,04/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +63526,73276,66413,PRETRIAL,Richards,Floyd,J,Male,African-American,04/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63533,73284,66420,PRETRIAL,Valle,Jorge,NULL,Male,Hispanic,04/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +63533,73284,66420,PRETRIAL,Valle,Jorge,NULL,Male,Hispanic,04/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +63533,73284,66420,PRETRIAL,Valle,Jorge,NULL,Male,Hispanic,04/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50886,73289,66425,PRETRIAL,Wallace,Leon,Rohan,Male,Other,04/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +50886,73289,66425,PRETRIAL,Wallace,Leon,Rohan,Male,Other,04/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +50886,73289,66425,PRETRIAL,Wallace,Leon,Rohan,Male,Other,04/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +5642,5620,5285,PRETRIAL,Johnson,Michael,NULL,Male,African-American,10/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/18/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +5642,5620,5285,PRETRIAL,Johnson,Michael,NULL,Male,African-American,10/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/18/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +5642,5620,5285,PRETRIAL,Johnson,Michael,NULL,Male,African-American,10/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/18/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63532,73283,66419,PRETRIAL,Pedrosa,Ricardo,NULL,Male,Hispanic,07/31/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +63532,73283,66419,PRETRIAL,Pedrosa,Ricardo,NULL,Male,Hispanic,07/31/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/14 0:00,1,Low,8,Risk of Recidivism,-2.56,1,Low,New,1,0 +63532,73283,66419,PRETRIAL,Pedrosa,Ricardo,NULL,Male,Hispanic,07/31/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60713,73287,63178,PRETRIAL,Lawrence,David,NULL,Male,Caucasian,05/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,Copy,1,0 +60713,73287,63178,PRETRIAL,Lawrence,David,NULL,Male,Caucasian,05/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,Copy,1,0 +60713,73287,63178,PRETRIAL,Lawrence,David,NULL,Male,Caucasian,05/14/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +63538,73292,66428,PRETRIAL,TEJADA,JONATHAN,NULL,Male,Caucasian,05/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +63538,73292,66428,PRETRIAL,TEJADA,JONATHAN,NULL,Male,Caucasian,05/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,4,High,8,Risk of Recidivism,0.85,10,High,New,1,0 +63538,73292,66428,PRETRIAL,TEJADA,JONATHAN,NULL,Male,Caucasian,05/18/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49884,73291,66427,PRETRIAL,Rosario,Eliezer,NULL,Male,Hispanic,05/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.71,9,High,New,1,0 +49884,73291,66427,PRETRIAL,Rosario,Eliezer,NULL,Male,Hispanic,05/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +49884,73291,66427,PRETRIAL,Rosario,Eliezer,NULL,Male,Hispanic,05/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63536,73288,66424,PRETRIAL,KING,ASHLEY,NIKOLE,Male,Caucasian,09/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +63536,73288,66424,PRETRIAL,KING,ASHLEY,NIKOLE,Male,Caucasian,09/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +63536,73288,66424,PRETRIAL,KING,ASHLEY,NIKOLE,Male,Caucasian,09/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63539,73295,66430,PRETRIAL,Giraldo-Font,Yoan,Eliceo,Male,Hispanic,12/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/18/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +63539,73295,66430,PRETRIAL,Giraldo-Font,Yoan,Eliceo,Male,Hispanic,12/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/18/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +63539,73295,66430,PRETRIAL,Giraldo-Font,Yoan,Eliceo,Male,Hispanic,12/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63535,73286,66422,PRETRIAL,HOLLIS,SYLVESTER,SIMMS,Male,African-American,11/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +63535,73286,66422,PRETRIAL,HOLLIS,SYLVESTER,SIMMS,Male,African-American,11/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +63535,73286,66422,PRETRIAL,HOLLIS,SYLVESTER,SIMMS,Male,African-American,11/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +5642,73293,5285,PRETRIAL,Johnson,Michael,NULL,Male,African-American,10/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/18/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,Copy,1,0 +5642,73293,5285,PRETRIAL,Johnson,Michael,NULL,Male,African-American,10/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/18/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,Copy,1,0 +5642,73293,5285,PRETRIAL,Johnson,Michael,NULL,Male,African-American,10/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/18/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +63540,73298,66431,PRETRIAL,Petrovich,Clinton,Lee,Male,Caucasian,02/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,Copy,1,0 +63540,73298,66431,PRETRIAL,Petrovich,Clinton,Lee,Male,Caucasian,02/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,Copy,1,0 +63540,73298,66431,PRETRIAL,Petrovich,Clinton,Lee,Male,Caucasian,02/19/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/18/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +63534,73285,66421,PRETRIAL,MARKELL,HILL,NULL,Male,African-American,05/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/18/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +63534,73285,66421,PRETRIAL,MARKELL,HILL,NULL,Male,African-American,05/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +63534,73285,66421,PRETRIAL,MARKELL,HILL,NULL,Male,African-American,05/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/18/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63537,73290,66426,PRETRIAL,LAWS,MARLANIA,E,Female,African-American,09/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +63537,73290,66426,PRETRIAL,LAWS,MARLANIA,E,Female,African-American,09/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +63537,73290,66426,PRETRIAL,LAWS,MARLANIA,E,Female,African-American,09/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/18/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63552,73311,66443,Probation,Shmandura,Sofya,NULL,Female,Caucasian,05/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +63552,73311,66443,Probation,Shmandura,Sofya,NULL,Female,Caucasian,05/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +63552,73311,66443,Probation,Shmandura,Sofya,NULL,Female,Caucasian,05/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63543,73303,66435,PRETRIAL,LISI,ROBERT,ANGELO,Male,Caucasian,09/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/19/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +63543,73303,66435,PRETRIAL,LISI,ROBERT,ANGELO,Male,Caucasian,09/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +63543,73303,66435,PRETRIAL,LISI,ROBERT,ANGELO,Male,Caucasian,09/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/19/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63551,73319,66442,PRETRIAL,KISIELINSKI,MARIUSZ,NULL,Male,Caucasian,04/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,Copy,1,0 +63551,73319,66442,PRETRIAL,KISIELINSKI,MARIUSZ,NULL,Male,Caucasian,04/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,Copy,1,0 +63551,73319,66442,PRETRIAL,KISIELINSKI,MARIUSZ,NULL,Male,Caucasian,04/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +63561,73324,66454,Probation,GIGUERE,RACHEL,NULL,Female,Caucasian,05/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,2,Medium,7,Risk of Violence,-2.87,2,Low,New,1,0 +63561,73324,66454,Probation,GIGUERE,RACHEL,NULL,Female,Caucasian,05/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +63561,73324,66454,Probation,GIGUERE,RACHEL,NULL,Female,Caucasian,05/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63547,73307,66439,PRETRIAL,Stenquist,Michael,NULL,Male,Caucasian,12/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +63547,73307,66439,PRETRIAL,Stenquist,Michael,NULL,Male,Caucasian,12/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +63547,73307,66439,PRETRIAL,Stenquist,Michael,NULL,Male,Caucasian,12/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +8371,73314,66446,PRETRIAL,PATTERSON,CHRISTOPHER,ANTHONY,Male,African-American,06/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,4,High,7,Risk of Violence,-0.48,10,High,New,1,0 +8371,73314,66446,PRETRIAL,PATTERSON,CHRISTOPHER,ANTHONY,Male,African-American,06/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +8371,73314,66446,PRETRIAL,PATTERSON,CHRISTOPHER,ANTHONY,Male,African-American,06/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63556,73316,66448,PRETRIAL,montano,jorge,NULL,Male,Caucasian,09/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +63556,73316,66448,PRETRIAL,montano,jorge,NULL,Male,Caucasian,09/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +63556,73316,66448,PRETRIAL,montano,jorge,NULL,Male,Caucasian,09/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63550,73309,66441,Probation,PEGNATORE,JACLYN,TARA,Female,Caucasian,11/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/19/14 0:00,2,Medium,7,Risk of Violence,-2.94,2,Low,New,1,0 +63550,73309,66441,Probation,PEGNATORE,JACLYN,TARA,Female,Caucasian,11/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +63550,73309,66441,Probation,PEGNATORE,JACLYN,TARA,Female,Caucasian,11/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/19/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63549,73321,66451,PRETRIAL,Guillory,Cedric,NULL,Male,African-American,06/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/19/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +63549,73321,66451,PRETRIAL,Guillory,Cedric,NULL,Male,African-American,06/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/19/14 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +63549,73321,66451,PRETRIAL,Guillory,Cedric,NULL,Male,African-American,06/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +27532,73326,66455,Probation,Grinos,Daniel,James,Male,Caucasian,04/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +27532,73326,66455,Probation,Grinos,Daniel,James,Male,Caucasian,04/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +27532,73326,66455,Probation,Grinos,Daniel,James,Male,Caucasian,04/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63541,73300,66433,PRETRIAL,Jones,Eddie,NULL,Male,African-American,01/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.54,3,Low,New,1,0 +63541,73300,66433,PRETRIAL,Jones,Eddie,NULL,Male,African-American,01/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +63541,73300,66433,PRETRIAL,Jones,Eddie,NULL,Male,African-American,01/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63554,73313,66445,PRETRIAL,Cariglio,Michael,George,Male,Caucasian,11/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/19/14 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +63554,73313,66445,PRETRIAL,Cariglio,Michael,George,Male,Caucasian,11/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/19/14 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +63554,73313,66445,PRETRIAL,Cariglio,Michael,George,Male,Caucasian,11/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63557,73317,66449,PRETRIAL,cAPELLO,mARTIN,NULL,Male,Caucasian,08/14/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +63557,73317,66449,PRETRIAL,cAPELLO,mARTIN,NULL,Male,Caucasian,08/14/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +63557,73317,66449,PRETRIAL,cAPELLO,mARTIN,NULL,Male,Caucasian,08/14/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +47135,73301,58671,PRETRIAL,Bowens,Reshaud,NULL,Male,African-American,12/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,Copy,1,0 +47135,73301,58671,PRETRIAL,Bowens,Reshaud,NULL,Male,African-American,12/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,Copy,1,0 +47135,73301,58671,PRETRIAL,Bowens,Reshaud,NULL,Male,African-American,12/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +38614,73299,66432,PRETRIAL,Alvarado,Elliot,C,Male,Caucasian,08/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/19/14 0:00,4,High,7,Risk of Violence,-0.69,9,High,New,1,0 +38614,73299,66432,PRETRIAL,Alvarado,Elliot,C,Male,Caucasian,08/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/19/14 0:00,4,High,8,Risk of Recidivism,0.42,9,High,New,1,0 +38614,73299,66432,PRETRIAL,Alvarado,Elliot,C,Male,Caucasian,08/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/19/14 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +63548,73308,66440,Probation,garcia,juan,NULL,Male,Hispanic,06/16/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/19/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +63548,73308,66440,Probation,garcia,juan,NULL,Male,Hispanic,06/16/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/19/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +63548,73308,66440,Probation,garcia,juan,NULL,Male,Hispanic,06/16/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63559,73322,66452,Probation,MCDANIEL,BOBBY,DALE,Male,Caucasian,12/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/19/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +63559,73322,66452,Probation,MCDANIEL,BOBBY,DALE,Male,Caucasian,12/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/19/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +63559,73322,66452,Probation,MCDANIEL,BOBBY,DALE,Male,Caucasian,12/18/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63544,73304,66436,PRETRIAL,DAVIS,NICOLE,LEE,Female,Caucasian,05/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/19/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +63544,73304,66436,PRETRIAL,DAVIS,NICOLE,LEE,Female,Caucasian,05/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/19/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +63544,73304,66436,PRETRIAL,DAVIS,NICOLE,LEE,Female,Caucasian,05/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63545,73305,66437,PRETRIAL,Smith,Rachel,NULL,Female,Caucasian,11/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +63545,73305,66437,PRETRIAL,Smith,Rachel,NULL,Female,Caucasian,11/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +63545,73305,66437,PRETRIAL,Smith,Rachel,NULL,Female,Caucasian,11/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63553,73312,66444,PRETRIAL,Roberts,Hayden,Douglas,Male,Native American,03/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +63553,73312,66444,PRETRIAL,Roberts,Hayden,Douglas,Male,Native American,03/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +63553,73312,66444,PRETRIAL,Roberts,Hayden,Douglas,Male,Native American,03/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63560,73323,66453,Probation,Dotson,Nashoa,NULL,Female,African-American,03/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +63560,73323,66453,Probation,Dotson,Nashoa,NULL,Female,African-American,03/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +63560,73323,66453,Probation,Dotson,Nashoa,NULL,Female,African-American,03/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63542,73302,66434,PRETRIAL,GLASGOW,KENDALL,ASANTE,Male,African-American,04/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +63542,73302,66434,PRETRIAL,GLASGOW,KENDALL,ASANTE,Male,African-American,04/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +63542,73302,66434,PRETRIAL,GLASGOW,KENDALL,ASANTE,Male,African-American,04/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63558,73320,66450,PRETRIAL,Cossick,Kyle,NULL,Male,Caucasian,01/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +63558,73320,66450,PRETRIAL,Cossick,Kyle,NULL,Male,Caucasian,01/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,4,High,8,Risk of Recidivism,0.27,8,High,New,1,0 +63558,73320,66450,PRETRIAL,Cossick,Kyle,NULL,Male,Caucasian,01/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/19/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63555,73315,66447,PRETRIAL,Wilkins,Larry,Joseph,Male,Caucasian,10/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/19/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +63555,73315,66447,PRETRIAL,Wilkins,Larry,Joseph,Male,Caucasian,10/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/19/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +63555,73315,66447,PRETRIAL,Wilkins,Larry,Joseph,Male,Caucasian,10/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63410,73349,66259,PRETRIAL,CULLUM,ROY,NULL,Male,Caucasian,02/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,Copy,1,0 +63410,73349,66259,PRETRIAL,CULLUM,ROY,NULL,Male,Caucasian,02/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +63410,73349,66259,PRETRIAL,CULLUM,ROY,NULL,Male,Caucasian,02/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +63563,73328,66457,PRETRIAL,Testamark,Wayne,J,Male,African-American,01/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +63563,73328,66457,PRETRIAL,Testamark,Wayne,J,Male,African-American,01/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +63563,73328,66457,PRETRIAL,Testamark,Wayne,J,Male,African-American,01/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63573,73341,66470,PRETRIAL,King,Clarence,Courtney,Male,African-American,11/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/20/14 0:00,4,High,7,Risk of Violence,-0.84,9,High,New,1,0 +63573,73341,66470,PRETRIAL,King,Clarence,Courtney,Male,African-American,11/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/20/14 0:00,4,High,8,Risk of Recidivism,0.81,10,High,New,1,0 +63573,73341,66470,PRETRIAL,King,Clarence,Courtney,Male,African-American,11/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/20/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63577,73346,66474,Probation,carlson,gary,NULL,Male,Caucasian,05/13/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +63577,73346,66474,Probation,carlson,gary,NULL,Male,Caucasian,05/13/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +63577,73346,66474,Probation,carlson,gary,NULL,Male,Caucasian,05/13/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +11936,73331,66460,PRETRIAL,Dukes,Michael,Bernard,Male,African-American,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +11936,73331,66460,PRETRIAL,Dukes,Michael,Bernard,Male,African-American,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +11936,73331,66460,PRETRIAL,Dukes,Michael,Bernard,Male,African-American,02/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63566,73333,66462,PRETRIAL,Ryan,Austin,Kash,Male,Caucasian,07/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +63566,73333,66462,PRETRIAL,Ryan,Austin,Kash,Male,Caucasian,07/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +63566,73333,66462,PRETRIAL,Ryan,Austin,Kash,Male,Caucasian,07/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53449,73354,66480,PRETRIAL,James,Romario,NULL,Male,Other,01/02/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +53449,73354,66480,PRETRIAL,James,Romario,NULL,Male,Other,01/02/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +53449,73354,66480,PRETRIAL,James,Romario,NULL,Male,Other,01/02/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63572,73339,66468,Probation,Vargas,Eric,NULL,Male,Hispanic,05/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +63572,73339,66468,Probation,Vargas,Eric,NULL,Male,Hispanic,05/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.87,10,High,New,1,0 +63572,73339,66468,Probation,Vargas,Eric,NULL,Male,Hispanic,05/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +49991,73357,66483,PRETRIAL,Abdelghani,Abdellah,NULL,Male,Caucasian,03/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/20/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +49991,73357,66483,PRETRIAL,Abdelghani,Abdellah,NULL,Male,Caucasian,03/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/20/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +49991,73357,66483,PRETRIAL,Abdelghani,Abdellah,NULL,Male,Caucasian,03/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63564,73329,66458,PRETRIAL,Garland,Marlon,NULL,Male,African-American,08/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +63564,73329,66458,PRETRIAL,Garland,Marlon,NULL,Male,African-American,08/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +63564,73329,66458,PRETRIAL,Garland,Marlon,NULL,Male,African-American,08/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63569,73336,66465,Probation,ahmed,helen,NULL,Female,Caucasian,05/24/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/20/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +63569,73336,66465,Probation,ahmed,helen,NULL,Female,Caucasian,05/24/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/20/14 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +63569,73336,66465,Probation,ahmed,helen,NULL,Female,Caucasian,05/24/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63574,73343,66471,Probation,Mott,Donovan,NULL,Male,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +63574,73343,66471,Probation,Mott,Donovan,NULL,Male,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +63574,73343,66471,Probation,Mott,Donovan,NULL,Male,Caucasian,09/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63579,73350,66477,Probation,Gomezdibenedetto,Jenny,NULL,Female,Hispanic,09/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/20/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +63579,73350,66477,Probation,Gomezdibenedetto,Jenny,NULL,Female,Hispanic,09/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/20/14 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +63579,73350,66477,Probation,Gomezdibenedetto,Jenny,NULL,Female,Hispanic,09/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63567,73334,66463,PRETRIAL,Vaughn,Keisha,NULL,Female,African-American,07/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +63567,73334,66463,PRETRIAL,Vaughn,Keisha,NULL,Female,African-American,07/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +63567,73334,66463,PRETRIAL,Vaughn,Keisha,NULL,Female,African-American,07/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +15132,73355,66481,PRETRIAL,JAMISON,DAVID,WILLIAM,Male,Caucasian,12/24/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/20/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +15132,73355,66481,PRETRIAL,JAMISON,DAVID,WILLIAM,Male,Caucasian,12/24/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/20/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +15132,73355,66481,PRETRIAL,JAMISON,DAVID,WILLIAM,Male,Caucasian,12/24/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63571,73338,66467,Probation,tinneny,amanda,marie,Female,Caucasian,02/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.31,3,Low,New,1,0 +63571,73338,66467,Probation,tinneny,amanda,marie,Female,Caucasian,02/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,9,High,New,1,0 +63571,73338,66467,Probation,tinneny,amanda,marie,Female,Caucasian,02/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +14632,73352,14002,PRETRIAL,MIRANDA,NELSON,NULL,Male,Hispanic,11/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +14632,73352,14002,PRETRIAL,MIRANDA,NELSON,NULL,Male,Hispanic,11/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,4,High,8,Risk of Recidivism,0.89,10,High,New,1,0 +14632,73352,14002,PRETRIAL,MIRANDA,NELSON,NULL,Male,Hispanic,11/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,4,High,18,Risk of Failure to Appear,38,10,High,New,1,0 +63583,73359,66485,Probation,Sirolli,Michele,NULL,Female,Caucasian,07/11/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +63583,73359,66485,Probation,Sirolli,Michele,NULL,Female,Caucasian,07/11/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +63583,73359,66485,Probation,Sirolli,Michele,NULL,Female,Caucasian,07/11/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63578,73347,66475,PRETRIAL,fleuirnor,enock,NULL,Male,African-American,05/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +63578,73347,66475,PRETRIAL,fleuirnor,enock,NULL,Male,African-American,05/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +63578,73347,66475,PRETRIAL,fleuirnor,enock,NULL,Male,African-American,05/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +36274,73351,66478,PRETRIAL,WIGGINS,BLAINE,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +36274,73351,66478,PRETRIAL,WIGGINS,BLAINE,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +36274,73351,66478,PRETRIAL,WIGGINS,BLAINE,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +63565,73330,66459,PRETRIAL,EVERETT,LARRY,JAMES,Male,African-American,06/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/20/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +63565,73330,66459,PRETRIAL,EVERETT,LARRY,JAMES,Male,African-American,06/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/20/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +63565,73330,66459,PRETRIAL,EVERETT,LARRY,JAMES,Male,African-American,06/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +31958,73360,30960,PRETRIAL,Steinmetz,William,NULL,Male,African-American,08/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,Copy,1,0 +31958,73360,30960,PRETRIAL,Steinmetz,William,NULL,Male,African-American,08/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,Copy,1,0 +31958,73360,30960,PRETRIAL,Steinmetz,William,NULL,Male,African-American,08/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +63573,73342,66470,PRETRIAL,King,Clarence,Courtney,Male,African-American,11/27/85,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Married,5/20/14 0:00,4,High,7,Risk of Violence,-0.84,9,High,Copy,1,0 +63573,73342,66470,PRETRIAL,King,Clarence,Courtney,Male,African-American,11/27/85,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Married,5/20/14 0:00,4,High,8,Risk of Recidivism,0.81,10,High,Copy,1,0 +63573,73342,66470,PRETRIAL,King,Clarence,Courtney,Male,African-American,11/27/85,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Married,5/20/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +63581,73356,66482,Probation,Baruch,Shimon,NULL,Male,Caucasian,02/09/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/20/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +63581,73356,66482,Probation,Baruch,Shimon,NULL,Male,Caucasian,02/09/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/20/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +63581,73356,66482,Probation,Baruch,Shimon,NULL,Male,Caucasian,02/09/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63570,73337,66466,Probation,Bautista,Augusto,Pablo,Male,Hispanic,01/12/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/20/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +63570,73337,66466,Probation,Bautista,Augusto,Pablo,Male,Hispanic,01/12/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/20/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +63570,73337,66466,Probation,Bautista,Augusto,Pablo,Male,Hispanic,01/12/89,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63575,73344,66472,Probation,GAY,ALLISON,EMILY,Female,Caucasian,04/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +63575,73344,66472,Probation,GAY,ALLISON,EMILY,Female,Caucasian,04/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +63575,73344,66472,Probation,GAY,ALLISON,EMILY,Female,Caucasian,04/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63582,73358,66484,Probation,Peddlar,Donald,NULL,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +63582,73358,66484,Probation,Peddlar,Donald,NULL,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +63582,73358,66484,Probation,Peddlar,Donald,NULL,Male,African-American,02/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63562,73327,66456,PRETRIAL,DUFOUR,EVERETT,ORVILLE,Male,Caucasian,12/25/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/20/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +63562,73327,66456,PRETRIAL,DUFOUR,EVERETT,ORVILLE,Male,Caucasian,12/25/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/20/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +63562,73327,66456,PRETRIAL,DUFOUR,EVERETT,ORVILLE,Male,Caucasian,12/25/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63576,73345,66473,Probation,FERNANDEZ,YUSET,NULL,Male,Caucasian,02/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.86,2,Low,New,1,0 +63576,73345,66473,Probation,FERNANDEZ,YUSET,NULL,Male,Caucasian,02/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +63576,73345,66473,Probation,FERNANDEZ,YUSET,NULL,Male,Caucasian,02/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63580,73353,66479,Probation,gavrilov,eugene,NULL,Male,Other,11/22/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +63580,73353,66479,Probation,gavrilov,eugene,NULL,Male,Other,11/22/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +63580,73353,66479,Probation,gavrilov,eugene,NULL,Male,Other,11/22/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +43939,73332,66461,PRETRIAL,Baptiste,Barry,NULL,Male,African-American,01/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +43939,73332,66461,PRETRIAL,Baptiste,Barry,NULL,Male,African-American,01/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +43939,73332,66461,PRETRIAL,Baptiste,Barry,NULL,Male,African-American,01/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/20/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57070,73348,66476,PRETRIAL,DUBICKI,PHILIP,JOSEPH,Male,Caucasian,10/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/20/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +57070,73348,66476,PRETRIAL,DUBICKI,PHILIP,JOSEPH,Male,Caucasian,10/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/20/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +57070,73348,66476,PRETRIAL,DUBICKI,PHILIP,JOSEPH,Male,Caucasian,10/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/20/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +21688,73340,66469,PRETRIAL,THURSTON,OMAR,NULL,Male,African-American,10/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +21688,73340,66469,PRETRIAL,THURSTON,OMAR,NULL,Male,African-American,10/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +21688,73340,66469,PRETRIAL,THURSTON,OMAR,NULL,Male,African-American,10/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63596,73376,66498,PRETRIAL,Ortiz,Marcial,NULL,Male,Hispanic,07/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/21/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +63596,73376,66498,PRETRIAL,Ortiz,Marcial,NULL,Male,Hispanic,07/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +63596,73376,66498,PRETRIAL,Ortiz,Marcial,NULL,Male,Hispanic,07/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63604,73389,66509,Probation,MICCO,AMANDA,APRIL,Female,Native American,04/21/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +63604,73389,66509,Probation,MICCO,AMANDA,APRIL,Female,Native American,04/21/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,8,High,New,1,0 +63604,73389,66509,Probation,MICCO,AMANDA,APRIL,Female,Native American,04/21/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63605,73390,66510,Probation,rafford,clifton,NULL,Male,Caucasian,09/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +63605,73390,66510,Probation,rafford,clifton,NULL,Male,Caucasian,09/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +63605,73390,66510,Probation,rafford,clifton,NULL,Male,Caucasian,09/05/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63590,73368,66491,Probation,foster,rashad,NULL,Male,African-American,10/02/88,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +63590,73368,66491,Probation,foster,rashad,NULL,Male,African-American,10/02/88,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +63590,73368,66491,Probation,foster,rashad,NULL,Male,African-American,10/02/88,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63600,73382,66503,Probation,Milligan,Michael,NULL,Male,African-American,04/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +63600,73382,66503,Probation,Milligan,Michael,NULL,Male,African-American,04/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +63600,73382,66503,Probation,Milligan,Michael,NULL,Male,African-American,04/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63601,73384,66505,Probation,Jalinas,Debra,NULL,Female,Caucasian,05/11/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/21/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +63601,73384,66505,Probation,Jalinas,Debra,NULL,Female,Caucasian,05/11/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +63601,73384,66505,Probation,Jalinas,Debra,NULL,Female,Caucasian,05/11/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63591,73369,66492,PRETRIAL,johnson,yul,NULL,Male,African-American,02/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +63591,73369,66492,PRETRIAL,johnson,yul,NULL,Male,African-American,02/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +63591,73369,66492,PRETRIAL,johnson,yul,NULL,Male,African-American,02/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63589,73366,66490,Probation,sainval,jaylor,NULL,Male,African-American,02/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +63589,73366,66490,Probation,sainval,jaylor,NULL,Male,African-American,02/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +63589,73366,66490,Probation,sainval,jaylor,NULL,Male,African-American,02/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63602,73387,66507,PRETRIAL,Garcia,Julio,NULL,Male,Hispanic,04/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +63602,73387,66507,PRETRIAL,Garcia,Julio,NULL,Male,Hispanic,04/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +63602,73387,66507,PRETRIAL,Garcia,Julio,NULL,Male,Hispanic,04/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63594,73374,66496,Probation,welch,Andrew,Mildon,Male,Caucasian,05/05/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +63594,73374,66496,Probation,welch,Andrew,Mildon,Male,Caucasian,05/05/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +63594,73374,66496,Probation,welch,Andrew,Mildon,Male,Caucasian,05/05/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +57768,73372,66494,Probation,Margri,Grace,Margaret,Female,Caucasian,07/08/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/21/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +57768,73372,66494,Probation,Margri,Grace,Margaret,Female,Caucasian,07/08/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +57768,73372,66494,Probation,Margri,Grace,Margaret,Female,Caucasian,07/08/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +45637,73379,66500,PRETRIAL,Ramos,Hector,NULL,Male,African-American,11/03/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +45637,73379,66500,PRETRIAL,Ramos,Hector,NULL,Male,African-American,11/03/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +45637,73379,66500,PRETRIAL,Ramos,Hector,NULL,Male,African-American,11/03/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +48252,73386,66506,PRETRIAL,Vazquez,Edwin,NULL,Male,Hispanic,02/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +48252,73386,66506,PRETRIAL,Vazquez,Edwin,NULL,Male,Hispanic,02/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +48252,73386,66506,PRETRIAL,Vazquez,Edwin,NULL,Male,Hispanic,02/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63587,73365,66489,PRETRIAL,MODAFFARI,MICHEAL,CRAIG,Male,Caucasian,09/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +63587,73365,66489,PRETRIAL,MODAFFARI,MICHEAL,CRAIG,Male,Caucasian,09/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +63587,73365,66489,PRETRIAL,MODAFFARI,MICHEAL,CRAIG,Male,Caucasian,09/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63586,73363,66488,PRETRIAL,BARON,KEANI,NULL,Male,African-American,08/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/14 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +63586,73363,66488,PRETRIAL,BARON,KEANI,NULL,Male,African-American,08/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +63586,73363,66488,PRETRIAL,BARON,KEANI,NULL,Male,African-American,08/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57985,73377,60151,PRETRIAL,Thomas,Jaron,NULL,Male,African-American,07/23/91,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,New,1,0 +57985,73377,60151,PRETRIAL,Thomas,Jaron,NULL,Male,African-American,07/23/91,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/14 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +57985,73377,60151,PRETRIAL,Thomas,Jaron,NULL,Male,African-American,07/23/91,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/14 0:00,4,High,18,Risk of Failure to Appear,23,4,Low,New,1,0 +63599,73381,66502,PRETRIAL,Dunbar,Kendall,NULL,Male,African-American,10/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/21/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +63599,73381,66502,PRETRIAL,Dunbar,Kendall,NULL,Male,African-American,10/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +63599,73381,66502,PRETRIAL,Dunbar,Kendall,NULL,Male,African-American,10/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63593,73373,66495,Probation,chancey,janine,NULL,Female,Caucasian,01/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +63593,73373,66495,Probation,chancey,janine,NULL,Female,Caucasian,01/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +63593,73373,66495,Probation,chancey,janine,NULL,Female,Caucasian,01/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +2017,73385,66357,PRETRIAL,WELLS,GARY,NULL,Male,African-American,01/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/21/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,Copy,1,0 +2017,73385,66357,PRETRIAL,WELLS,GARY,NULL,Male,African-American,01/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/21/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,Copy,1,0 +2017,73385,66357,PRETRIAL,WELLS,GARY,NULL,Male,African-American,01/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +26605,73364,25706,PRETRIAL,Friday,Karen,NULL,Female,African-American,08/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/21/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,Copy,1,0 +26605,73364,25706,PRETRIAL,Friday,Karen,NULL,Female,African-American,08/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,Copy,1,0 +26605,73364,25706,PRETRIAL,Friday,Karen,NULL,Female,African-American,08/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/21/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +63592,73371,66493,Probation,Mejia,Ivan,NULL,Male,Hispanic,08/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +63592,73371,66493,Probation,Mejia,Ivan,NULL,Male,Hispanic,08/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +63592,73371,66493,Probation,Mejia,Ivan,NULL,Male,Hispanic,08/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63597,73378,66499,PRETRIAL,MILLAN,AICARDO,NULL,Male,Hispanic,01/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +63597,73378,66499,PRETRIAL,MILLAN,AICARDO,NULL,Male,Hispanic,01/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +63597,73378,66499,PRETRIAL,MILLAN,AICARDO,NULL,Male,Hispanic,01/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63598,73380,66501,PRETRIAL,Gaboton,James,NULL,Male,African-American,01/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/21/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +63598,73380,66501,PRETRIAL,Gaboton,James,NULL,Male,African-American,01/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +63598,73380,66501,PRETRIAL,Gaboton,James,NULL,Male,African-American,01/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63595,73375,66497,Probation,koecher,brittany,NULL,Female,African-American,12/16/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +63595,73375,66497,Probation,koecher,brittany,NULL,Female,African-American,12/16/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +63595,73375,66497,Probation,koecher,brittany,NULL,Female,African-American,12/16/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62868,73367,65645,Probation,carrodeguas,david,s,Male,Hispanic,10/07/69,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/21/14 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +62868,73367,65645,Probation,carrodeguas,david,s,Male,Hispanic,10/07/69,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,6,Medium,New,1,0 +62868,73367,65645,Probation,carrodeguas,david,s,Male,Hispanic,10/07/69,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/21/14 0:00,2,Medium,18,Risk of Failure to Appear,31,8,High,New,1,0 +63606,73391,66511,Probation,jones,archie,NULL,Male,African-American,02/06/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +63606,73391,66511,Probation,jones,archie,NULL,Male,African-American,02/06/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +63606,73391,66511,Probation,jones,archie,NULL,Male,African-American,02/06/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63603,73388,66508,Probation,Espinosa,Mitchell,NULL,Male,Hispanic,09/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +63603,73388,66508,Probation,Espinosa,Mitchell,NULL,Male,Hispanic,09/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +63603,73388,66508,Probation,Espinosa,Mitchell,NULL,Male,Hispanic,09/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63585,73362,66487,PRETRIAL,BRADDY,JONATHAN,GEORGE,Male,Caucasian,05/13/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +63585,73362,66487,PRETRIAL,BRADDY,JONATHAN,GEORGE,Male,Caucasian,05/13/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +63585,73362,66487,PRETRIAL,BRADDY,JONATHAN,GEORGE,Male,Caucasian,05/13/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +43798,73383,66504,PRETRIAL,Santos,Luciano,NULL,Male,Hispanic,08/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/21/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +43798,73383,66504,PRETRIAL,Santos,Luciano,NULL,Male,Hispanic,08/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/21/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +43798,73383,66504,PRETRIAL,Santos,Luciano,NULL,Male,Hispanic,08/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/21/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63623,73417,66532,Probation,LOPEZ,RICARDO,H,Male,Hispanic,11/22/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +63623,73417,66532,Probation,LOPEZ,RICARDO,H,Male,Hispanic,11/22/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +63623,73417,66532,Probation,LOPEZ,RICARDO,H,Male,Hispanic,11/22/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60527,73396,66514,PRETRIAL,springer,bond,NULL,Male,Caucasian,06/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +60527,73396,66514,PRETRIAL,springer,bond,NULL,Male,Caucasian,06/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +60527,73396,66514,PRETRIAL,springer,bond,NULL,Male,Caucasian,06/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +9730,73409,66526,PRETRIAL,BERRIOS,MICHAEL,M,Male,Hispanic,09/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/22/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +9730,73409,66526,PRETRIAL,BERRIOS,MICHAEL,M,Male,Hispanic,09/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +9730,73409,66526,PRETRIAL,BERRIOS,MICHAEL,M,Male,Hispanic,09/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63620,73412,66528,PRETRIAL,MCDONALD,MARCELL,ANTHONY,Male,African-American,04/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +63620,73412,66528,PRETRIAL,MCDONALD,MARCELL,ANTHONY,Male,African-American,04/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +63620,73412,66528,PRETRIAL,MCDONALD,MARCELL,ANTHONY,Male,African-American,04/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50745,73425,66539,PRETRIAL,NAVARRO,MIGUEL,A,Male,Caucasian,07/05/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/22/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +50745,73425,66539,PRETRIAL,NAVARRO,MIGUEL,A,Male,Caucasian,07/05/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/22/14 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +50745,73425,66539,PRETRIAL,NAVARRO,MIGUEL,A,Male,Caucasian,07/05/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63616,73404,66522,Probation,murphy,patrick,NULL,Male,Caucasian,03/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +63616,73404,66522,Probation,murphy,patrick,NULL,Male,Caucasian,03/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +63616,73404,66522,Probation,murphy,patrick,NULL,Male,Caucasian,03/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63611,73399,66517,PRETRIAL,Fox,Sonny,Johnson,Male,Caucasian,05/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/22/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +63611,73399,66517,PRETRIAL,Fox,Sonny,Johnson,Male,Caucasian,05/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +63611,73399,66517,PRETRIAL,Fox,Sonny,Johnson,Male,Caucasian,05/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63613,73401,66519,PRETRIAL,BAUMAN,SHELLEY,NULL,Female,Caucasian,03/20/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +63613,73401,66519,PRETRIAL,BAUMAN,SHELLEY,NULL,Female,Caucasian,03/20/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +63613,73401,66519,PRETRIAL,BAUMAN,SHELLEY,NULL,Female,Caucasian,03/20/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +63626,73422,66536,Probation,Nucamendi,Rafael,NULL,Male,Hispanic,09/23/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +63626,73422,66536,Probation,Nucamendi,Rafael,NULL,Male,Hispanic,09/23/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +63626,73422,66536,Probation,Nucamendi,Rafael,NULL,Male,Hispanic,09/23/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63619,73408,66525,Probation,REYNOLDS,WILLIAM,C,Male,Caucasian,08/10/41,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/22/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +63619,73408,66525,Probation,REYNOLDS,WILLIAM,C,Male,Caucasian,08/10/41,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +63619,73408,66525,Probation,REYNOLDS,WILLIAM,C,Male,Caucasian,08/10/41,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63622,73415,66531,Probation,WILIAMS,ALICE,NULL,Female,African-American,10/14/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/22/14 0:00,2,Medium,7,Risk of Violence,-2.88,2,Low,New,1,0 +63622,73415,66531,Probation,WILIAMS,ALICE,NULL,Female,African-American,10/14/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +63622,73415,66531,Probation,WILIAMS,ALICE,NULL,Female,African-American,10/14/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/22/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57467,73394,59575,PRETRIAL,Delatorre,Carlos,Ernesto,Male,Hispanic,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,Copy,1,0 +57467,73394,59575,PRETRIAL,Delatorre,Carlos,Ernesto,Male,Hispanic,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,Copy,1,0 +57467,73394,59575,PRETRIAL,Delatorre,Carlos,Ernesto,Male,Hispanic,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +63627,73424,66538,Probation,Wheatley,Martha,NULL,Female,Hispanic,05/04/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +63627,73424,66538,Probation,Wheatley,Martha,NULL,Female,Hispanic,05/04/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +63627,73424,66538,Probation,Wheatley,Martha,NULL,Female,Hispanic,05/04/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +11500,73420,66534,Probation,Ohagan,Linda,Helen,Female,Caucasian,02/23/52,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,5/22/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +11500,73420,66534,Probation,Ohagan,Linda,Helen,Female,Caucasian,02/23/52,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +11500,73420,66534,Probation,Ohagan,Linda,Helen,Female,Caucasian,02/23/52,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63629,73427,66541,Probation,Berges,Angel,NULL,Male,Hispanic,02/24/55,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/22/14 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +63629,73427,66541,Probation,Berges,Angel,NULL,Male,Hispanic,02/24/55,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/22/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +63629,73427,66541,Probation,Berges,Angel,NULL,Male,Hispanic,02/24/55,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63610,73398,66516,PRETRIAL,Thorpe,Jovanni,NULL,Male,African-American,06/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +63610,73398,66516,PRETRIAL,Thorpe,Jovanni,NULL,Male,African-American,06/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +63610,73398,66516,PRETRIAL,Thorpe,Jovanni,NULL,Male,African-American,06/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63624,73419,66533,Probation,mendoza,renee,NULL,Female,Caucasian,06/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +63624,73419,66533,Probation,mendoza,renee,NULL,Female,Caucasian,06/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +63624,73419,66533,Probation,mendoza,renee,NULL,Female,Caucasian,06/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63631,73428,66542,Probation,short,kyle,NULL,Male,Caucasian,01/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +63631,73428,66542,Probation,short,kyle,NULL,Male,Caucasian,01/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +63631,73428,66542,Probation,short,kyle,NULL,Male,Caucasian,01/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +8802,73402,66520,PRETRIAL,Chong,Tyler,Morgan,Male,Oriental,03/12/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +8802,73402,66520,PRETRIAL,Chong,Tyler,Morgan,Male,Oriental,03/12/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +8802,73402,66520,PRETRIAL,Chong,Tyler,Morgan,Male,Oriental,03/12/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +34589,73423,66537,PRETRIAL,WILLIE,ELSIE,NULL,Female,Native American,03/24/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +34589,73423,66537,PRETRIAL,WILLIE,ELSIE,NULL,Female,Native American,03/24/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +34589,73423,66537,PRETRIAL,WILLIE,ELSIE,NULL,Female,Native American,03/24/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63621,73414,66530,Probation,Perez,Debra,NULL,Female,Hispanic,07/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +63621,73414,66530,Probation,Perez,Debra,NULL,Female,Hispanic,07/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +63621,73414,66530,Probation,Perez,Debra,NULL,Female,Hispanic,07/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63609,73416,66515,PRETRIAL,Lopez-Bumgartner,Victoria,Leigh,Male,Caucasian,06/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,Copy,1,0 +63609,73416,66515,PRETRIAL,Lopez-Bumgartner,Victoria,Leigh,Male,Caucasian,06/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,Copy,1,0 +63609,73416,66515,PRETRIAL,Lopez-Bumgartner,Victoria,Leigh,Male,Caucasian,06/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +18301,18949,17569,PRETRIAL,COLEMAN,JAMES,NULL,Male,African-American,10/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +18301,18949,17569,PRETRIAL,COLEMAN,JAMES,NULL,Male,African-American,10/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +18301,18949,17569,PRETRIAL,COLEMAN,JAMES,NULL,Male,African-American,10/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63607,73393,66512,PRETRIAL,Phanard,Gregory,NULL,Male,African-American,06/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +63607,73393,66512,PRETRIAL,Phanard,Gregory,NULL,Male,African-American,06/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +63607,73393,66512,PRETRIAL,Phanard,Gregory,NULL,Male,African-American,06/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63618,73407,66524,Broward County,ROUSSEAU,JEAN,NULL,Male,Hispanic,10/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +63618,73407,66524,Broward County,ROUSSEAU,JEAN,NULL,Male,Hispanic,10/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +63618,73407,66524,Broward County,ROUSSEAU,JEAN,NULL,Male,Hispanic,10/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63608,73395,66513,PRETRIAL,ROSALES,ALBERT,NULL,Male,Caucasian,08/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/22/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +63608,73395,66513,PRETRIAL,ROSALES,ALBERT,NULL,Male,Caucasian,08/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +63608,73395,66513,PRETRIAL,ROSALES,ALBERT,NULL,Male,Caucasian,08/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56256,73413,66529,PRETRIAL,Spurgin,Brian,James,Male,African-American,05/11/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +56256,73413,66529,PRETRIAL,Spurgin,Brian,James,Male,African-American,05/11/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +56256,73413,66529,PRETRIAL,Spurgin,Brian,James,Male,African-American,05/11/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63625,73421,66535,PRETRIAL,Johnson,Larry,NULL,Male,African-American,04/14/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/22/14 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +63625,73421,66535,PRETRIAL,Johnson,Larry,NULL,Male,African-American,04/14/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/22/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +63625,73421,66535,PRETRIAL,Johnson,Larry,NULL,Male,African-American,04/14/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,5/22/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +63612,73400,66518,PRETRIAL,STUBBS,ARIEL,LAKESHIA,Female,African-American,11/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +63612,73400,66518,PRETRIAL,STUBBS,ARIEL,LAKESHIA,Female,African-American,11/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +63612,73400,66518,PRETRIAL,STUBBS,ARIEL,LAKESHIA,Female,African-American,11/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53339,73403,66521,PRETRIAL,REID,ADREAN,NULL,Male,African-American,08/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +53339,73403,66521,PRETRIAL,REID,ADREAN,NULL,Male,African-American,08/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +53339,73403,66521,PRETRIAL,REID,ADREAN,NULL,Male,African-American,08/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63617,73405,66523,Probation,Smith,Kenneth,NULL,Male,African-American,02/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +63617,73405,66523,Probation,Smith,Kenneth,NULL,Male,African-American,02/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +63617,73405,66523,Probation,Smith,Kenneth,NULL,Male,African-American,02/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +3171,73410,66338,PRETRIAL,Sepulveda,Brenda,NULL,Female,Hispanic,06/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,Copy,1,0 +3171,73410,66338,PRETRIAL,Sepulveda,Brenda,NULL,Female,Hispanic,06/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,Copy,1,0 +3171,73410,66338,PRETRIAL,Sepulveda,Brenda,NULL,Female,Hispanic,06/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +63609,73397,66515,PRETRIAL,Lopez-Bumgartner,Victoria,Leigh,Male,Caucasian,06/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +63609,73397,66515,PRETRIAL,Lopez-Bumgartner,Victoria,Leigh,Male,Caucasian,06/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +63609,73397,66515,PRETRIAL,Lopez-Bumgartner,Victoria,Leigh,Male,Caucasian,06/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +4055,73411,66527,Probation,King,Morris,NULL,Male,African-American,11/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +4055,73411,66527,Probation,King,Morris,NULL,Male,African-American,11/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,4,High,8,Risk of Recidivism,0.94,10,High,New,1,0 +4055,73411,66527,Probation,King,Morris,NULL,Male,African-American,11/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63609,73418,66515,PRETRIAL,Lopez-Bumgartner,Victoria,Leigh,Male,Caucasian,06/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,Copy,1,0 +63609,73418,66515,PRETRIAL,Lopez-Bumgartner,Victoria,Leigh,Male,Caucasian,06/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,Copy,1,0 +63609,73418,66515,PRETRIAL,Lopez-Bumgartner,Victoria,Leigh,Male,Caucasian,06/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +63628,73426,66540,Probation,Cohen,Raisa,NULL,Female,Hispanic,07/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +63628,73426,66540,Probation,Cohen,Raisa,NULL,Female,Hispanic,07/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +63628,73426,66540,Probation,Cohen,Raisa,NULL,Female,Hispanic,07/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63636,73439,66551,PRETRIAL,Johnson,Le'Nardra,Nakita,Female,African-American,11/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +63636,73439,66551,PRETRIAL,Johnson,Le'Nardra,Nakita,Female,African-American,11/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +63636,73439,66551,PRETRIAL,Johnson,Le'Nardra,Nakita,Female,African-American,11/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63643,73447,66559,PRETRIAL,Boukzam,Alexander,Scott,Male,Caucasian,02/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/14 0:00,2,Medium,7,Risk of Violence,-1.43,7,Medium,New,1,0 +63643,73447,66559,PRETRIAL,Boukzam,Alexander,Scott,Male,Caucasian,02/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +63643,73447,66559,PRETRIAL,Boukzam,Alexander,Scott,Male,Caucasian,02/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +48227,73431,48904,PRETRIAL,Francisco,Rudolfo,NULL,Male,Hispanic,07/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/23/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,Copy,1,0 +48227,73431,48904,PRETRIAL,Francisco,Rudolfo,NULL,Male,Hispanic,07/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/23/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,Copy,1,0 +48227,73431,48904,PRETRIAL,Francisco,Rudolfo,NULL,Male,Hispanic,07/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +63633,73434,66547,PRETRIAL,Swakcerd,Daniel,NULL,Male,African-American,02/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +63633,73434,66547,PRETRIAL,Swakcerd,Daniel,NULL,Male,African-American,02/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,4,High,8,Risk of Recidivism,0.24,8,High,New,1,0 +63633,73434,66547,PRETRIAL,Swakcerd,Daniel,NULL,Male,African-American,02/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63652,73460,66571,PRETRIAL,MCNULTY,PATRICK,NULL,Male,Caucasian,03/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +63652,73460,66571,PRETRIAL,MCNULTY,PATRICK,NULL,Male,Caucasian,03/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +63652,73460,66571,PRETRIAL,MCNULTY,PATRICK,NULL,Male,Caucasian,03/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +46583,73452,66563,PRETRIAL,Zambrano,Juan,NULL,Male,Hispanic,04/11/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +46583,73452,66563,PRETRIAL,Zambrano,Juan,NULL,Male,Hispanic,04/11/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +46583,73452,66563,PRETRIAL,Zambrano,Juan,NULL,Male,Hispanic,04/11/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +13010,73463,66574,PRETRIAL,CORTES,ROBERT,DARIO,Male,Caucasian,04/25/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/23/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +13010,73463,66574,PRETRIAL,CORTES,ROBERT,DARIO,Male,Caucasian,04/25/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +13010,73463,66574,PRETRIAL,CORTES,ROBERT,DARIO,Male,Caucasian,04/25/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/23/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63638,73442,66554,Probation,Martin,Valery,NULL,Female,Caucasian,03/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +63638,73442,66554,Probation,Martin,Valery,NULL,Female,Caucasian,03/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +63638,73442,66554,Probation,Martin,Valery,NULL,Female,Caucasian,03/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63650,73458,66569,Probation,Gedman,Heather,NULL,Female,Hispanic,09/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +63650,73458,66569,Probation,Gedman,Heather,NULL,Female,Hispanic,09/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +63650,73458,66569,Probation,Gedman,Heather,NULL,Female,Hispanic,09/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +36401,73465,35665,PRETRIAL,Jackson,Frank,NULL,Male,African-American,02/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,Copy,1,0 +36401,73465,35665,PRETRIAL,Jackson,Frank,NULL,Male,African-American,02/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,Copy,1,0 +36401,73465,35665,PRETRIAL,Jackson,Frank,NULL,Male,African-American,02/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +56017,73435,57936,Probation,Douglas,Kemisha,NULL,Female,African-American,12/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.17,4,Low,Copy,1,0 +56017,73435,57936,Probation,Douglas,Kemisha,NULL,Female,African-American,12/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,8,High,Copy,1,0 +56017,73435,57936,Probation,Douglas,Kemisha,NULL,Female,African-American,12/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +58733,73437,66549,PRETRIAL,Jamelle,Tucker,N,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,New,1,0 +58733,73437,66549,PRETRIAL,Jamelle,Tucker,N,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +58733,73437,66549,PRETRIAL,Jamelle,Tucker,N,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63640,73444,66556,Probation,ALI,ASHIQ,NULL,Male,Asian,06/01/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/23/14 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +63640,73444,66556,Probation,ALI,ASHIQ,NULL,Male,Asian,06/01/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/23/14 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +63640,73444,66556,Probation,ALI,ASHIQ,NULL,Male,Asian,06/01/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63646,73453,66564,Probation,RATLIFF,AINSLEY,NICOLE,Female,Caucasian,09/20/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +63646,73453,66564,Probation,RATLIFF,AINSLEY,NICOLE,Female,Caucasian,09/20/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,9,High,New,1,0 +63646,73453,66564,Probation,RATLIFF,AINSLEY,NICOLE,Female,Caucasian,09/20/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,9,High,New,1,0 +63632,73432,66545,PRETRIAL,Monagas,Jordan,NULL,Male,Caucasian,02/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +63632,73432,66545,PRETRIAL,Monagas,Jordan,NULL,Male,Caucasian,02/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +63632,73432,66545,PRETRIAL,Monagas,Jordan,NULL,Male,Caucasian,02/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53843,73449,61938,Probation,ARISTIZABAL,LORENA,NULL,Female,Hispanic,06/25/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +53843,73449,61938,Probation,ARISTIZABAL,LORENA,NULL,Female,Hispanic,06/25/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-0.79,4,Low,New,1,0 +53843,73449,61938,Probation,ARISTIZABAL,LORENA,NULL,Female,Hispanic,06/25/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,1,Low,New,1,0 +8950,73445,66557,PRETRIAL,WILLIAMS,ZACHARY,LASELLE,Male,African-American,03/05/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,4,High,7,Risk of Violence,-1.05,8,High,New,1,0 +8950,73445,66557,PRETRIAL,WILLIAMS,ZACHARY,LASELLE,Male,African-American,03/05/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,4,High,8,Risk of Recidivism,0.63,9,High,New,1,0 +8950,73445,66557,PRETRIAL,WILLIAMS,ZACHARY,LASELLE,Male,African-American,03/05/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,4,High,18,Risk of Failure to Appear,35,9,High,New,1,0 +63637,73441,66553,PRETRIAL,Fenelon,Weithzer,NULL,Male,African-American,06/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/23/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +63637,73441,66553,PRETRIAL,Fenelon,Weithzer,NULL,Male,African-American,06/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +63637,73441,66553,PRETRIAL,Fenelon,Weithzer,NULL,Male,African-American,06/25/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/23/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58430,73457,66568,PRETRIAL,LAMBERT,RAY,GARNET,Male,African-American,09/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +58430,73457,66568,PRETRIAL,LAMBERT,RAY,GARNET,Male,African-American,09/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +58430,73457,66568,PRETRIAL,LAMBERT,RAY,GARNET,Male,African-American,09/19/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +18316,73429,66543,PRETRIAL,colon,christopher,NULL,Male,Caucasian,11/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,4,High,7,Risk of Violence,-1.19,8,High,New,1,0 +18316,73429,66543,PRETRIAL,colon,christopher,NULL,Male,Caucasian,11/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,4,High,8,Risk of Recidivism,0.76,10,High,New,1,0 +18316,73429,66543,PRETRIAL,colon,christopher,NULL,Male,Caucasian,11/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +63634,73436,66548,PRETRIAL,Evans,Mark,NULL,Male,African-American,03/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +63634,73436,66548,PRETRIAL,Evans,Mark,NULL,Male,African-American,03/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +63634,73436,66548,PRETRIAL,Evans,Mark,NULL,Male,African-American,03/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63639,73443,66555,Probation,Merulla,Kristopher,NULL,Male,Caucasian,03/09/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +63639,73443,66555,Probation,Merulla,Kristopher,NULL,Male,Caucasian,03/09/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +63639,73443,66555,Probation,Merulla,Kristopher,NULL,Male,Caucasian,03/09/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63645,73450,66561,Probation,Cigini,Michael,Patrick,Male,Caucasian,05/19/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +63645,73450,66561,Probation,Cigini,Michael,Patrick,Male,Caucasian,05/19/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +63645,73450,66561,Probation,Cigini,Michael,Patrick,Male,Caucasian,05/19/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63647,73454,66565,PRETRIAL,MARTIN,NATHANIEL,NULL,Male,Caucasian,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +63647,73454,66565,PRETRIAL,MARTIN,NATHANIEL,NULL,Male,Caucasian,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +63647,73454,66565,PRETRIAL,MARTIN,NATHANIEL,NULL,Male,Caucasian,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +17223,73440,66552,PRETRIAL,Schwartz,Curtis,A,Male,Caucasian,04/27/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/23/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +17223,73440,66552,PRETRIAL,Schwartz,Curtis,A,Male,Caucasian,04/27/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/23/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +17223,73440,66552,PRETRIAL,Schwartz,Curtis,A,Male,Caucasian,04/27/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63641,73446,66558,Probation,ISAACS,JERLYN,V,Female,African-American,02/03/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +63641,73446,66558,Probation,ISAACS,JERLYN,V,Female,African-American,02/03/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +63641,73446,66558,Probation,ISAACS,JERLYN,V,Female,African-American,02/03/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51351,73433,66546,PRETRIAL,Taffe,Horace,NULL,Male,African-American,11/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/23/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +51351,73433,66546,PRETRIAL,Taffe,Horace,NULL,Male,African-American,11/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/23/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +51351,73433,66546,PRETRIAL,Taffe,Horace,NULL,Male,African-American,11/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63644,73448,66560,PRETRIAL,Jean,Saraphin,NULL,Male,Other,04/05/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/23/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +63644,73448,66560,PRETRIAL,Jean,Saraphin,NULL,Male,Other,04/05/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/23/14 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +63644,73448,66560,PRETRIAL,Jean,Saraphin,NULL,Male,Other,04/05/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63649,73456,66567,Probation,Manfred,David,NULL,Male,Caucasian,05/11/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +63649,73456,66567,Probation,Manfred,David,NULL,Male,Caucasian,05/11/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +63649,73456,66567,Probation,Manfred,David,NULL,Male,Caucasian,05/11/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63651,73459,66570,PRETRIAL,Mata-Gonzalez,Erica,Ann,Female,Native American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,5/23/14 0:00,4,High,7,Risk of Violence,-0.82,9,High,New,1,0 +63651,73459,66570,PRETRIAL,Mata-Gonzalez,Erica,Ann,Female,Native American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,5/23/14 0:00,4,High,8,Risk of Recidivism,1.31,10,High,New,1,0 +63651,73459,66570,PRETRIAL,Mata-Gonzalez,Erica,Ann,Female,Native American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,5/23/14 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +63635,73438,66550,PRETRIAL,Vassell,Jordan,M,Male,Other,04/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +63635,73438,66550,PRETRIAL,Vassell,Jordan,M,Male,Other,04/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +63635,73438,66550,PRETRIAL,Vassell,Jordan,M,Male,Other,04/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57618,73430,66544,PRETRIAL,moreland,Jamaree,NULL,Male,African-American,08/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +57618,73430,66544,PRETRIAL,moreland,Jamaree,NULL,Male,African-American,08/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +57618,73430,66544,PRETRIAL,moreland,Jamaree,NULL,Male,African-American,08/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50599,73451,66562,PRETRIAL,resto,alexander,NULL,Male,African-American,06/27/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,7,Risk of Violence,-4.51,1,Low,New,1,0 +50599,73451,66562,PRETRIAL,resto,alexander,NULL,Male,African-American,06/27/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,8,Risk of Recidivism,-2.72,1,Low,New,1,0 +50599,73451,66562,PRETRIAL,resto,alexander,NULL,Male,African-American,06/27/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49561,73464,66575,PRETRIAL,Londonotrujillo,Andres,NULL,Male,Hispanic,04/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/23/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +49561,73464,66575,PRETRIAL,Londonotrujillo,Andres,NULL,Male,Hispanic,04/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/23/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +49561,73464,66575,PRETRIAL,Londonotrujillo,Andres,NULL,Male,Hispanic,04/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,5/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63656,73467,66577,PRETRIAL,Foster,Calvin,Lewis,Male,African-American,09/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +63656,73467,66577,PRETRIAL,Foster,Calvin,Lewis,Male,African-American,09/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +63656,73467,66577,PRETRIAL,Foster,Calvin,Lewis,Male,African-American,09/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53961,73469,66579,PRETRIAL,ST FLEUR,FRENZY,NULL,Male,African-American,09/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +53961,73469,66579,PRETRIAL,ST FLEUR,FRENZY,NULL,Male,African-American,09/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +53961,73469,66579,PRETRIAL,ST FLEUR,FRENZY,NULL,Male,African-American,09/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63658,73471,66581,PRETRIAL,CLOWERS,JAMES,NULL,Male,Caucasian,10/20/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/24/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +63658,73471,66581,PRETRIAL,CLOWERS,JAMES,NULL,Male,Caucasian,10/20/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/24/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +63658,73471,66581,PRETRIAL,CLOWERS,JAMES,NULL,Male,Caucasian,10/20/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,5/24/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +63655,73466,66576,PRETRIAL,MARIUS,BERSON,NULL,Male,African-American,05/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/24/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +63655,73466,66576,PRETRIAL,MARIUS,BERSON,NULL,Male,African-American,05/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/24/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +63655,73466,66576,PRETRIAL,MARIUS,BERSON,NULL,Male,African-American,05/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +11993,73474,11510,Probation,Perez,Tianraheem,NULL,Male,African-American,10/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,Copy,1,0 +11993,73474,11510,Probation,Perez,Tianraheem,NULL,Male,African-American,10/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,Copy,1,0 +11993,73474,11510,Probation,Perez,Tianraheem,NULL,Male,African-American,10/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +63657,73470,66580,PRETRIAL,Chacon,Sabrina,NULL,Male,Caucasian,09/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +63657,73470,66580,PRETRIAL,Chacon,Sabrina,NULL,Male,Caucasian,09/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +63657,73470,66580,PRETRIAL,Chacon,Sabrina,NULL,Male,Caucasian,09/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63659,73472,66582,PRETRIAL,Rodriguez,Jean,NULL,Male,Hispanic,12/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,1,Low,7,Risk of Violence,-1.81,5,Medium,New,1,0 +63659,73472,66582,PRETRIAL,Rodriguez,Jean,NULL,Male,Hispanic,12/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +63659,73472,66582,PRETRIAL,Rodriguez,Jean,NULL,Male,Hispanic,12/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +47977,73468,66578,PRETRIAL,Joseph,Jeff,NULL,Male,African-American,01/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +47977,73468,66578,PRETRIAL,Joseph,Jeff,NULL,Male,African-American,01/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,4,High,8,Risk of Recidivism,0.12,8,High,New,1,0 +47977,73468,66578,PRETRIAL,Joseph,Jeff,NULL,Male,African-American,01/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/24/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63669,73481,66589,PRETRIAL,Godfrey,Michael,NULL,Male,Caucasian,09/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +63669,73481,66589,PRETRIAL,Godfrey,Michael,NULL,Male,Caucasian,09/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +63669,73481,66589,PRETRIAL,Godfrey,Michael,NULL,Male,Caucasian,09/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63671,73484,66592,PRETRIAL,Shaw-Pittman,Bernice,NULL,Female,African-American,10/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/25/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +63671,73484,66592,PRETRIAL,Shaw-Pittman,Bernice,NULL,Female,African-American,10/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/25/14 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +63671,73484,66592,PRETRIAL,Shaw-Pittman,Bernice,NULL,Female,African-American,10/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63664,73476,66584,PRETRIAL,RIVERA,JIMMY,NULL,Male,Caucasian,06/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +63664,73476,66584,PRETRIAL,RIVERA,JIMMY,NULL,Male,Caucasian,06/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +63664,73476,66584,PRETRIAL,RIVERA,JIMMY,NULL,Male,Caucasian,06/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63666,73479,66587,PRETRIAL,Rivera,Jimmy,NULL,Male,Hispanic,01/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/25/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +63666,73479,66587,PRETRIAL,Rivera,Jimmy,NULL,Male,Hispanic,01/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/25/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +63666,73479,66587,PRETRIAL,Rivera,Jimmy,NULL,Male,Hispanic,01/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63670,73483,66591,PRETRIAL,ANDREWS,LAWRENCE,JOSEPH,Male,Caucasian,11/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,New,1,0 +63670,73483,66591,PRETRIAL,ANDREWS,LAWRENCE,JOSEPH,Male,Caucasian,11/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,4,High,8,Risk of Recidivism,0.35,9,High,New,1,0 +63670,73483,66591,PRETRIAL,ANDREWS,LAWRENCE,JOSEPH,Male,Caucasian,11/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63665,73478,66586,PRETRIAL,Soriano,Mike,NULL,Male,Caucasian,07/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +63665,73478,66586,PRETRIAL,Soriano,Mike,NULL,Male,Caucasian,07/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +63665,73478,66586,PRETRIAL,Soriano,Mike,NULL,Male,Caucasian,07/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63668,73480,66588,PRETRIAL,ORTIZ,AJAI,NAJEE,Male,African-American,02/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +63668,73480,66588,PRETRIAL,ORTIZ,AJAI,NAJEE,Male,African-American,02/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +63668,73480,66588,PRETRIAL,ORTIZ,AJAI,NAJEE,Male,African-American,02/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63667,73482,66590,PRETRIAL,LYNCH,JOSEPH,COLIN,Male,Native American,02/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/25/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +63667,73482,66590,PRETRIAL,LYNCH,JOSEPH,COLIN,Male,Native American,02/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +63667,73482,66590,PRETRIAL,LYNCH,JOSEPH,COLIN,Male,Native American,02/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/25/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63663,73475,66583,PRETRIAL,DALEY,NOVIA,NULL,Female,African-American,07/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/25/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +63663,73475,66583,PRETRIAL,DALEY,NOVIA,NULL,Female,African-American,07/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/25/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +63663,73475,66583,PRETRIAL,DALEY,NOVIA,NULL,Female,African-American,07/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63521,73477,66585,PRETRIAL,Garsonbaquero,Julian,NULL,Male,Hispanic,01/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +63521,73477,66585,PRETRIAL,Garsonbaquero,Julian,NULL,Male,Hispanic,01/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +63521,73477,66585,PRETRIAL,Garsonbaquero,Julian,NULL,Male,Hispanic,01/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/25/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63672,73485,66593,PRETRIAL,Miller,Federick,NULL,Male,Caucasian,02/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +63672,73485,66593,PRETRIAL,Miller,Federick,NULL,Male,Caucasian,02/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +63672,73485,66593,PRETRIAL,Miller,Federick,NULL,Male,Caucasian,02/15/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63676,73490,66597,PRETRIAL,Bennie,Horatio,NULL,Male,Other,12/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/26/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +63676,73490,66597,PRETRIAL,Bennie,Horatio,NULL,Male,Other,12/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/26/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +63676,73490,66597,PRETRIAL,Bennie,Horatio,NULL,Male,Other,12/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63674,73487,66595,PRETRIAL,Floyd,Barry,T,Male,Caucasian,12/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/26/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +63674,73487,66595,PRETRIAL,Floyd,Barry,T,Male,Caucasian,12/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/26/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +63674,73487,66595,PRETRIAL,Floyd,Barry,T,Male,Caucasian,12/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63678,73492,66599,PRETRIAL,Tinoco,Alvaro,J,Male,Hispanic,09/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/26/14 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +63678,73492,66599,PRETRIAL,Tinoco,Alvaro,J,Male,Hispanic,09/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +63678,73492,66599,PRETRIAL,Tinoco,Alvaro,J,Male,Hispanic,09/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/26/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63673,73486,66594,PRETRIAL,Galvao,Daniel,Venturini,Male,Hispanic,01/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +63673,73486,66594,PRETRIAL,Galvao,Daniel,Venturini,Male,Hispanic,01/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +63673,73486,66594,PRETRIAL,Galvao,Daniel,Venturini,Male,Hispanic,01/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +21237,73488,27192,PRETRIAL,Boykins,Jermiah,NULL,Male,African-American,05/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +21237,73488,27192,PRETRIAL,Boykins,Jermiah,NULL,Male,African-American,05/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,Copy,1,0 +21237,73488,27192,PRETRIAL,Boykins,Jermiah,NULL,Male,African-American,05/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +63677,73491,66598,PRETRIAL,Brewton,Tanisha,NULL,Female,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +63677,73491,66598,PRETRIAL,Brewton,Tanisha,NULL,Female,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +63677,73491,66598,PRETRIAL,Brewton,Tanisha,NULL,Female,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63675,73489,66596,PRETRIAL,EISWERTH,ERICA,NULL,Female,Caucasian,01/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +63675,73489,66596,PRETRIAL,EISWERTH,ERICA,NULL,Female,Caucasian,01/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +63675,73489,66596,PRETRIAL,EISWERTH,ERICA,NULL,Female,Caucasian,01/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/26/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59621,73525,61979,Probation,SGAMBATI-SHEIL,LISA,MARIE,Female,Caucasian,05/19/64,17,All Scales,Intake,English,Conditional Release,Probation,Separated,5/27/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +59621,73525,61979,Probation,SGAMBATI-SHEIL,LISA,MARIE,Female,Caucasian,05/19/64,17,All Scales,Intake,English,Conditional Release,Probation,Separated,5/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +59621,73525,61979,Probation,SGAMBATI-SHEIL,LISA,MARIE,Female,Caucasian,05/19/64,17,All Scales,Intake,English,Conditional Release,Probation,Separated,5/27/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +63709,73526,66629,Probation,THOMAS,RICO,NULL,Male,African-American,01/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +63709,73526,66629,Probation,THOMAS,RICO,NULL,Male,African-American,01/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +63709,73526,66629,Probation,THOMAS,RICO,NULL,Male,African-American,01/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63683,73497,66604,PRETRIAL,Carroll,Loretta,NULL,Female,Caucasian,03/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +63683,73497,66604,PRETRIAL,Carroll,Loretta,NULL,Female,Caucasian,03/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-2.63,1,Low,New,1,0 +63683,73497,66604,PRETRIAL,Carroll,Loretta,NULL,Female,Caucasian,03/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +44416,73504,64561,PRETRIAL,francisco,michael,NULL,Male,Caucasian,05/23/80,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +44416,73504,64561,PRETRIAL,francisco,michael,NULL,Male,Caucasian,05/23/80,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-0.71,3,Low,New,1,0 +44416,73504,64561,PRETRIAL,francisco,michael,NULL,Male,Caucasian,05/23/80,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +63702,73518,66622,PRETRIAL,Vereen,William,NULL,Male,African-American,06/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +63702,73518,66622,PRETRIAL,Vereen,William,NULL,Male,African-American,06/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +63702,73518,66622,PRETRIAL,Vereen,William,NULL,Male,African-American,06/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63713,73531,66634,PRETRIAL,crommett,michael,NULL,Male,Caucasian,01/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +63713,73531,66634,PRETRIAL,crommett,michael,NULL,Male,Caucasian,01/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +63713,73531,66634,PRETRIAL,crommett,michael,NULL,Male,Caucasian,01/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63691,73505,66611,Probation,SMITH,FREDERICK,L,Male,African-American,12/12/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +63691,73505,66611,Probation,SMITH,FREDERICK,L,Male,African-American,12/12/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +63691,73505,66611,Probation,SMITH,FREDERICK,L,Male,African-American,12/12/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63695,73510,66616,Probation,Shuldman,Andrew,NULL,Male,Caucasian,11/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,2,Medium,7,Risk of Violence,-2.82,2,Low,New,1,0 +63695,73510,66616,Probation,Shuldman,Andrew,NULL,Male,Caucasian,11/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +63695,73510,66616,Probation,Shuldman,Andrew,NULL,Male,Caucasian,11/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +58388,73512,60616,PRETRIAL,Cooper,Martez,keith,Male,African-American,05/13/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,Copy,1,0 +58388,73512,60616,PRETRIAL,Cooper,Martez,keith,Male,African-American,05/13/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,Copy,1,0 +58388,73512,60616,PRETRIAL,Cooper,Martez,keith,Male,African-American,05/13/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +63680,73494,66601,PRETRIAL,Murray,Francessa,NULL,Female,Caucasian,01/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +63680,73494,66601,PRETRIAL,Murray,Francessa,NULL,Female,Caucasian,01/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +63680,73494,66601,PRETRIAL,Murray,Francessa,NULL,Female,Caucasian,01/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63711,73528,66631,PRETRIAL,KIRBY,RYAN,NULL,Male,Caucasian,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +63711,73528,66631,PRETRIAL,KIRBY,RYAN,NULL,Male,Caucasian,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +63711,73528,66631,PRETRIAL,KIRBY,RYAN,NULL,Male,Caucasian,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63707,73523,66627,Probation,GOMEZ,PAUL,NULL,Male,Hispanic,04/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +63707,73523,66627,Probation,GOMEZ,PAUL,NULL,Male,Hispanic,04/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +63707,73523,66627,Probation,GOMEZ,PAUL,NULL,Male,Hispanic,04/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +5981,73502,66609,PRETRIAL,LUNA,ENRICO,RAMON,Male,Hispanic,10/28/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/27/14 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +5981,73502,66609,PRETRIAL,LUNA,ENRICO,RAMON,Male,Hispanic,10/28/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/27/14 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +5981,73502,66609,PRETRIAL,LUNA,ENRICO,RAMON,Male,Hispanic,10/28/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/27/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63704,73520,66624,PRETRIAL,DIPEGO,CLAUDIO,NULL,Male,Other,04/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +63704,73520,66624,PRETRIAL,DIPEGO,CLAUDIO,NULL,Male,Other,04/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +63704,73520,66624,PRETRIAL,DIPEGO,CLAUDIO,NULL,Male,Other,04/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63696,73509,66615,PRETRIAL,Cohen,Pete,NULL,Male,Caucasian,11/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +63696,73509,66615,PRETRIAL,Cohen,Pete,NULL,Male,Caucasian,11/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +63696,73509,66615,PRETRIAL,Cohen,Pete,NULL,Male,Caucasian,11/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63681,73495,66602,PRETRIAL,HELLER,DAVID,PRESTON,Male,African-American,01/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +63681,73495,66602,PRETRIAL,HELLER,DAVID,PRESTON,Male,African-American,01/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +63681,73495,66602,PRETRIAL,HELLER,DAVID,PRESTON,Male,African-American,01/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63688,73500,66607,PRETRIAL,Samuels,Sierra,Lashay,Female,African-American,11/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +63688,73500,66607,PRETRIAL,Samuels,Sierra,Lashay,Female,African-American,11/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +63688,73500,66607,PRETRIAL,Samuels,Sierra,Lashay,Female,African-American,11/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63705,73521,66625,PRETRIAL,HETZEL,TROY,A,Male,Caucasian,12/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,4,High,7,Risk of Violence,-1.17,8,High,New,1,0 +63705,73521,66625,PRETRIAL,HETZEL,TROY,A,Male,Caucasian,12/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,4,High,8,Risk of Recidivism,0.28,8,High,New,1,0 +63705,73521,66625,PRETRIAL,HETZEL,TROY,A,Male,Caucasian,12/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +40005,73530,66633,PRETRIAL,Jammel,Greg,NULL,Male,Caucasian,01/30/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,2,Medium,7,Risk of Violence,-2.95,1,Low,New,1,0 +40005,73530,66633,PRETRIAL,Jammel,Greg,NULL,Male,Caucasian,01/30/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +40005,73530,66633,PRETRIAL,Jammel,Greg,NULL,Male,Caucasian,01/30/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63679,73493,66600,PRETRIAL,Ussa,Andres,NULL,Male,Hispanic,04/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +63679,73493,66600,PRETRIAL,Ussa,Andres,NULL,Male,Hispanic,04/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +63679,73493,66600,PRETRIAL,Ussa,Andres,NULL,Male,Hispanic,04/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63693,73507,66613,Probation,KUHN,BRETT,NULL,Male,Other,08/27/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +63693,73507,66613,Probation,KUHN,BRETT,NULL,Male,Other,08/27/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +63693,73507,66613,Probation,KUHN,BRETT,NULL,Male,Other,08/27/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63700,73514,66619,PRETRIAL,MARRERO,MARIA,NULL,Female,Hispanic,12/18/81,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +63700,73514,66619,PRETRIAL,MARRERO,MARIA,NULL,Female,Hispanic,12/18/81,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +63700,73514,66619,PRETRIAL,MARRERO,MARIA,NULL,Female,Hispanic,12/18/81,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63697,73516,66621,PRETRIAL,Noel,Carnes,NULL,Male,African-American,07/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +63697,73516,66621,PRETRIAL,Noel,Carnes,NULL,Male,African-American,07/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +63697,73516,66621,PRETRIAL,Noel,Carnes,NULL,Male,African-American,07/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63699,73513,66618,Probation,Rivas,Jesus,Evelio,Male,Hispanic,06/02/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/27/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +63699,73513,66618,Probation,Rivas,Jesus,Evelio,Male,Hispanic,06/02/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/27/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +63699,73513,66618,Probation,Rivas,Jesus,Evelio,Male,Hispanic,06/02/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63682,73496,66603,PRETRIAL,SIRJOO,NARENDRA,NULL,Male,Other,11/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +63682,73496,66603,PRETRIAL,SIRJOO,NARENDRA,NULL,Male,Other,11/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +63682,73496,66603,PRETRIAL,SIRJOO,NARENDRA,NULL,Male,Other,11/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +25315,73517,65837,PRETRIAL,BLUE,NIESHA,NULL,Female,African-American,10/23/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/27/14 0:00,4,High,7,Risk of Violence,-0.44,10,High,New,1,0 +25315,73517,65837,PRETRIAL,BLUE,NIESHA,NULL,Female,African-American,10/23/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/27/14 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +25315,73517,65837,PRETRIAL,BLUE,NIESHA,NULL,Female,African-American,10/23/92,17,All Scales,Intake,English,Conditional Release,Probation,Single,5/27/14 0:00,4,High,18,Risk of Failure to Appear,36,10,High,New,1,0 +50892,73499,66606,PRETRIAL,Yunis,Omar,Nassim,Male,Caucasian,08/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +50892,73499,66606,PRETRIAL,Yunis,Omar,Nassim,Male,Caucasian,08/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +50892,73499,66606,PRETRIAL,Yunis,Omar,Nassim,Male,Caucasian,08/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63689,73501,66608,PRETRIAL,Dobney,Valrene,Judith,Female,Other,09/27/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +63689,73501,66608,PRETRIAL,Dobney,Valrene,Judith,Female,Other,09/27/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/14 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +63689,73501,66608,PRETRIAL,Dobney,Valrene,Judith,Female,Other,09/27/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63706,73522,66626,PRETRIAL,Myrtil,Nina,NULL,Female,African-American,03/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +63706,73522,66626,PRETRIAL,Myrtil,Nina,NULL,Female,African-American,03/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +63706,73522,66626,PRETRIAL,Myrtil,Nina,NULL,Female,African-American,03/21/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63712,73529,66632,Probation,kilheeney,michael,NULL,Male,Caucasian,06/13/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/27/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +63712,73529,66632,Probation,kilheeney,michael,NULL,Male,Caucasian,06/13/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/27/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +63712,73529,66632,Probation,kilheeney,michael,NULL,Male,Caucasian,06/13/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63703,73519,66623,PRETRIAL,PERDOMO,GARCIELA,DELCARMEN,Female,Caucasian,11/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +63703,73519,66623,PRETRIAL,PERDOMO,GARCIELA,DELCARMEN,Female,Caucasian,11/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +63703,73519,66623,PRETRIAL,PERDOMO,GARCIELA,DELCARMEN,Female,Caucasian,11/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63684,73498,66605,PRETRIAL,GIORLANDO,JOHN,NULL,Male,Caucasian,09/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +63684,73498,66605,PRETRIAL,GIORLANDO,JOHN,NULL,Male,Caucasian,09/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +63684,73498,66605,PRETRIAL,GIORLANDO,JOHN,NULL,Male,Caucasian,09/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63714,73532,66635,Probation,mayes,antwan,NULL,Male,African-American,11/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/27/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +63714,73532,66635,Probation,mayes,antwan,NULL,Male,African-American,11/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/27/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +63714,73532,66635,Probation,mayes,antwan,NULL,Male,African-American,11/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63710,73527,66630,Probation,myers,james,NULL,Male,Caucasian,03/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +63710,73527,66630,Probation,myers,james,NULL,Male,Caucasian,03/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +63710,73527,66630,Probation,myers,james,NULL,Male,Caucasian,03/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63692,73506,66612,Probation,pabon,eric,NULL,Male,Caucasian,11/07/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/27/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +63692,73506,66612,Probation,pabon,eric,NULL,Male,Caucasian,11/07/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/27/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +63692,73506,66612,Probation,pabon,eric,NULL,Male,Caucasian,11/07/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/27/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63754,73574,66673,Probation,LAU,LILLY,INEZ,Female,Hispanic,04/20/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +63754,73574,66673,Probation,LAU,LILLY,INEZ,Female,Hispanic,04/20/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +63754,73574,66673,Probation,LAU,LILLY,INEZ,Female,Hispanic,04/20/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58765,73545,60988,PRETRIAL,Wyatt,Paul,NULL,Male,Caucasian,09/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,Copy,1,0 +58765,73545,60988,PRETRIAL,Wyatt,Paul,NULL,Male,Caucasian,09/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,Copy,1,0 +58765,73545,60988,PRETRIAL,Wyatt,Paul,NULL,Male,Caucasian,09/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +3501,73566,66665,Probation,Bailey,Quavon,Levar,Male,African-American,10/11/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,New,1,0 +3501,73566,66665,Probation,Bailey,Quavon,Levar,Male,African-American,10/11/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +3501,73566,66665,Probation,Bailey,Quavon,Levar,Male,African-American,10/11/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62440,71830,65133,Probation,GORDON,DELANDO,D,Male,African-American,05/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,5/28/14 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +62440,71830,65133,Probation,GORDON,DELANDO,D,Male,African-American,05/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,5/28/14 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +62440,71830,65133,Probation,GORDON,DELANDO,D,Male,African-American,05/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,5/28/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63733,73553,66653,PRETRIAL,Lyseight,Nicholas,NULL,Male,African-American,03/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.84,9,High,New,1,0 +63733,73553,66653,PRETRIAL,Lyseight,Nicholas,NULL,Male,African-American,03/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +63733,73553,66653,PRETRIAL,Lyseight,Nicholas,NULL,Male,African-American,03/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63747,73561,66660,Probation,Blanchette,Brian,NULL,Male,Caucasian,03/19/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +63747,73561,66660,Probation,Blanchette,Brian,NULL,Male,Caucasian,03/19/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +63747,73561,66660,Probation,Blanchette,Brian,NULL,Male,Caucasian,03/19/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63729,73548,66648,Probation,Sands,Vincent,NULL,Male,African-American,08/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +63729,73548,66648,Probation,Sands,Vincent,NULL,Male,African-American,08/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +63729,73548,66648,Probation,Sands,Vincent,NULL,Male,African-American,08/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63750,73569,66668,Probation,Wiggins,Michele,Ann,Female,Caucasian,07/18/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +63750,73569,66668,Probation,Wiggins,Michele,Ann,Female,Caucasian,07/18/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,New,1,0 +63750,73569,66668,Probation,Wiggins,Michele,Ann,Female,Caucasian,07/18/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63721,73536,66639,PRETRIAL,Reyes,Raul,NULL,Male,African-American,06/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +63721,73536,66639,PRETRIAL,Reyes,Raul,NULL,Male,African-American,06/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +63721,73536,66639,PRETRIAL,Reyes,Raul,NULL,Male,African-American,06/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63726,73543,66644,Probation,Farella,Delicia,NULL,Female,Caucasian,10/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +63726,73543,66644,Probation,Farella,Delicia,NULL,Female,Caucasian,10/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +63726,73543,66644,Probation,Farella,Delicia,NULL,Female,Caucasian,10/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63738,73557,66657,Probation,Galdamez,Carolina,NULL,Female,Hispanic,04/14/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +63738,73557,66657,Probation,Galdamez,Carolina,NULL,Female,Hispanic,04/14/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +63738,73557,66657,Probation,Galdamez,Carolina,NULL,Female,Hispanic,04/14/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63752,73571,66670,Probation,Woullard,Dominic,NULL,Male,African-American,07/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +63752,73571,66670,Probation,Woullard,Dominic,NULL,Male,African-American,07/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +63752,73571,66670,Probation,Woullard,Dominic,NULL,Male,African-American,07/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +6405,73534,66637,PRETRIAL,WALKER,LEWIS,THOMAS,Male,African-American,07/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +6405,73534,66637,PRETRIAL,WALKER,LEWIS,THOMAS,Male,African-American,07/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +6405,73534,66637,PRETRIAL,WALKER,LEWIS,THOMAS,Male,African-American,07/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +2846,73568,66667,PRETRIAL,lucken,laura,NULL,Female,Caucasian,02/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +2846,73568,66667,PRETRIAL,lucken,laura,NULL,Female,Caucasian,02/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +2846,73568,66667,PRETRIAL,lucken,laura,NULL,Female,Caucasian,02/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57066,73564,66663,PRETRIAL,Waller,Angela,Dawn,Female,Caucasian,07/22/69,22,Risk and Prescreen,Intake,English,Probation Violator,Jail Inmate,Divorced,5/28/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +57066,73564,66663,PRETRIAL,Waller,Angela,Dawn,Female,Caucasian,07/22/69,22,Risk and Prescreen,Intake,English,Probation Violator,Jail Inmate,Divorced,5/28/14 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +57066,73564,66663,PRETRIAL,Waller,Angela,Dawn,Female,Caucasian,07/22/69,22,Risk and Prescreen,Intake,English,Probation Violator,Jail Inmate,Divorced,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63723,73538,66641,PRETRIAL,Davis,Gregory,NULL,Male,African-American,03/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +63723,73538,66641,PRETRIAL,Davis,Gregory,NULL,Male,African-American,03/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +63723,73538,66641,PRETRIAL,Davis,Gregory,NULL,Male,African-American,03/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63734,73552,66652,Probation,VALENCIA,ILIANA,NULL,Female,Hispanic,06/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/28/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +63734,73552,66652,Probation,VALENCIA,ILIANA,NULL,Female,Hispanic,06/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/28/14 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +63734,73552,66652,Probation,VALENCIA,ILIANA,NULL,Female,Hispanic,06/18/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63746,73559,66658,Probation,SINGLETARY,KILLIAN,NULL,Male,African-American,06/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +63746,73559,66658,Probation,SINGLETARY,KILLIAN,NULL,Male,African-American,06/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +63746,73559,66658,Probation,SINGLETARY,KILLIAN,NULL,Male,African-American,06/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63753,73573,66672,Probation,Miller,adam,NULL,Male,Caucasian,03/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +63753,73573,66672,Probation,Miller,adam,NULL,Male,Caucasian,03/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +63753,73573,66672,Probation,Miller,adam,NULL,Male,Caucasian,03/23/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +44192,73565,66664,PRETRIAL,Adler,Gregory,NULL,Male,Caucasian,07/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +44192,73565,66664,PRETRIAL,Adler,Gregory,NULL,Male,Caucasian,07/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +44192,73565,66664,PRETRIAL,Adler,Gregory,NULL,Male,Caucasian,07/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57791,73535,66638,Probation,waddell,michael,NULL,Male,Caucasian,03/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +57791,73535,66638,Probation,waddell,michael,NULL,Male,Caucasian,03/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.73,10,High,New,1,0 +57791,73535,66638,Probation,waddell,michael,NULL,Male,Caucasian,03/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63722,73537,66640,PRETRIAL,Pierre,Herode,NULL,Male,African-American,03/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +63722,73537,66640,PRETRIAL,Pierre,Herode,NULL,Male,African-American,03/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +63722,73537,66640,PRETRIAL,Pierre,Herode,NULL,Male,African-American,03/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62440,73558,65133,Probation,GORDON,DELANDO,D,Male,African-American,05/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,5/28/14 0:00,4,High,7,Risk of Violence,-0.98,9,High,Copy,1,0 +62440,73558,65133,Probation,GORDON,DELANDO,D,Male,African-American,05/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,5/28/14 0:00,4,High,8,Risk of Recidivism,0.46,9,High,Copy,1,0 +62440,73558,65133,Probation,GORDON,DELANDO,D,Male,African-American,05/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,5/28/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +54909,73572,66671,PRETRIAL,Young,Rudolph,NULL,Male,African-American,01/02/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.44,3,Low,New,1,0 +54909,73572,66671,PRETRIAL,Young,Rudolph,NULL,Male,African-American,01/02/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,9,High,New,1,0 +54909,73572,66671,PRETRIAL,Young,Rudolph,NULL,Male,African-American,01/02/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +56099,73560,66659,PRETRIAL,Sawyer,Stephanie,NULL,Female,Caucasian,12/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +56099,73560,66659,PRETRIAL,Sawyer,Stephanie,NULL,Female,Caucasian,12/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +56099,73560,66659,PRETRIAL,Sawyer,Stephanie,NULL,Female,Caucasian,12/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +63732,73551,66651,PRETRIAL,STEWART,RICARDO,PAUL,Female,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +63732,73551,66651,PRETRIAL,STEWART,RICARDO,PAUL,Female,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +63732,73551,66651,PRETRIAL,STEWART,RICARDO,PAUL,Female,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +9996,73563,66662,PRETRIAL,PRINCIPE,LIANA,NULL,Female,Caucasian,05/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,2,Medium,7,Risk of Violence,-3.5,1,Low,New,1,0 +9996,73563,66662,PRETRIAL,PRINCIPE,LIANA,NULL,Female,Caucasian,05/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +9996,73563,66662,PRETRIAL,PRINCIPE,LIANA,NULL,Female,Caucasian,05/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +63757,73577,66676,PRETRIAL,Curry,Asa,I,Male,African-American,04/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,5/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +63757,73577,66676,PRETRIAL,Curry,Asa,I,Male,African-American,04/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,5/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +63757,73577,66676,PRETRIAL,Curry,Asa,I,Male,African-American,04/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,5/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63725,73542,66643,Probation,REISS,WESTCOTT,NULL,Male,Caucasian,10/20/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/28/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +63725,73542,66643,Probation,REISS,WESTCOTT,NULL,Male,Caucasian,10/20/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/28/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +63725,73542,66643,Probation,REISS,WESTCOTT,NULL,Male,Caucasian,10/20/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63736,73556,66656,Probation,Viscarra,Erlan,NULL,Female,Hispanic,08/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +63736,73556,66656,Probation,Viscarra,Erlan,NULL,Female,Hispanic,08/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +63736,73556,66656,Probation,Viscarra,Erlan,NULL,Female,Hispanic,08/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +63751,73570,66669,Probation,FINN,FREDERICK,KEITH,Male,Caucasian,12/09/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +63751,73570,66669,Probation,FINN,FREDERICK,KEITH,Male,Caucasian,12/09/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +63751,73570,66669,Probation,FINN,FREDERICK,KEITH,Male,Caucasian,12/09/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +53675,73541,63856,PRETRIAL,castro,maximo,NULL,Male,Hispanic,09/12/68,17,All Scales,Intake,English,Conditional Release,Probation,Married,5/28/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +53675,73541,63856,PRETRIAL,castro,maximo,NULL,Male,Hispanic,09/12/68,17,All Scales,Intake,English,Conditional Release,Probation,Married,5/28/14 0:00,1,Low,8,Risk of Recidivism,-1.38,1,Low,New,1,0 +53675,73541,63856,PRETRIAL,castro,maximo,NULL,Male,Hispanic,09/12/68,17,All Scales,Intake,English,Conditional Release,Probation,Married,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +63749,73562,66661,Probation,Betito,Shiela,NULL,Female,Asian,06/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +63749,73562,66661,Probation,Betito,Shiela,NULL,Female,Asian,06/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +63749,73562,66661,Probation,Betito,Shiela,NULL,Female,Asian,06/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63724,73539,66642,PRETRIAL,Luzey,Ryan,C,Male,Caucasian,10/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +63724,73539,66642,PRETRIAL,Luzey,Ryan,C,Male,Caucasian,10/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +63724,73539,66642,PRETRIAL,Luzey,Ryan,C,Male,Caucasian,10/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63715,73533,66636,PRETRIAL,Augustin,Ralph,NULL,Male,African-American,08/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +63715,73533,66636,PRETRIAL,Augustin,Ralph,NULL,Male,African-American,08/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +63715,73533,66636,PRETRIAL,Augustin,Ralph,NULL,Male,African-American,08/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58155,73567,66666,PRETRIAL,GARCIA,SERGIO,NULL,Male,Caucasian,02/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +58155,73567,66666,PRETRIAL,GARCIA,SERGIO,NULL,Male,Caucasian,02/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +58155,73567,66666,PRETRIAL,GARCIA,SERGIO,NULL,Male,Caucasian,02/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +57675,73547,66647,PRETRIAL,GOMEZ,ERIK,NULL,Male,Hispanic,08/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +57675,73547,66647,PRETRIAL,GOMEZ,ERIK,NULL,Male,Hispanic,08/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +57675,73547,66647,PRETRIAL,GOMEZ,ERIK,NULL,Male,Hispanic,08/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63735,73554,66654,Probation,Deonarine,Kapil,NULL,Male,Asian,05/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +63735,73554,66654,Probation,Deonarine,Kapil,NULL,Male,Asian,05/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +63735,73554,66654,Probation,Deonarine,Kapil,NULL,Male,Asian,05/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63755,73575,66674,Probation,Moreta,Doris,NULL,Female,African-American,08/26/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +63755,73575,66674,Probation,Moreta,Doris,NULL,Female,African-American,08/26/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +63755,73575,66674,Probation,Moreta,Doris,NULL,Female,African-American,08/26/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/28/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +20321,73604,66700,PRETRIAL,Lanza,Anthony,NULL,Male,Caucasian,11/12/88,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,5/29/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +20321,73604,66700,PRETRIAL,Lanza,Anthony,NULL,Male,Caucasian,11/12/88,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,5/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +20321,73604,66700,PRETRIAL,Lanza,Anthony,NULL,Male,Caucasian,11/12/88,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,5/29/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55512,73612,66706,PRETRIAL,FRANCOIS,JOHN,NULL,Male,African-American,12/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +55512,73612,66706,PRETRIAL,FRANCOIS,JOHN,NULL,Male,African-American,12/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +55512,73612,66706,PRETRIAL,FRANCOIS,JOHN,NULL,Male,African-American,12/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63771,73596,66693,Probation,kimbrough,ana,NULL,Female,Other,05/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +63771,73596,66693,Probation,kimbrough,ana,NULL,Female,Other,05/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +63771,73596,66693,Probation,kimbrough,ana,NULL,Female,Other,05/11/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63761,73583,66681,PRETRIAL,Ramos,Carlos,Enrique,Male,Hispanic,11/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +63761,73583,66681,PRETRIAL,Ramos,Carlos,Enrique,Male,Hispanic,11/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +63761,73583,66681,PRETRIAL,Ramos,Carlos,Enrique,Male,Hispanic,11/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +45741,73617,46053,PRETRIAL,Ferrad,Pedro,NULL,Male,Hispanic,04/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,Copy,1,0 +45741,73617,46053,PRETRIAL,Ferrad,Pedro,NULL,Male,Hispanic,04/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,Copy,1,0 +45741,73617,46053,PRETRIAL,Ferrad,Pedro,NULL,Male,Hispanic,04/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +63781,73609,66704,PRETRIAL,Stirrup,Dwight,NULL,Male,African-American,09/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/29/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +63781,73609,66704,PRETRIAL,Stirrup,Dwight,NULL,Male,African-American,09/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +63781,73609,66704,PRETRIAL,Stirrup,Dwight,NULL,Male,African-American,09/02/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63764,73588,66686,PRETRIAL,Grant,Xzantiny,NULL,Male,African-American,02/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +63764,73588,66686,PRETRIAL,Grant,Xzantiny,NULL,Male,African-American,02/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +63764,73588,66686,PRETRIAL,Grant,Xzantiny,NULL,Male,African-American,02/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59663,73602,66698,PRETRIAL,SCHWARTZBACH,ALONA,NULL,Female,Caucasian,08/16/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/29/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +59663,73602,66698,PRETRIAL,SCHWARTZBACH,ALONA,NULL,Female,Caucasian,08/16/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +59663,73602,66698,PRETRIAL,SCHWARTZBACH,ALONA,NULL,Female,Caucasian,08/16/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63760,73581,66680,PRETRIAL,Antunes,Andre,Cantergian,Male,Caucasian,08/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +63760,73581,66680,PRETRIAL,Antunes,Andre,Cantergian,Male,Caucasian,08/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +63760,73581,66680,PRETRIAL,Antunes,Andre,Cantergian,Male,Caucasian,08/25/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63773,73598,66695,Probation,obryan,Samantha,NULL,Female,African-American,04/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,2,Medium,7,Risk of Violence,-2.63,2,Low,New,1,0 +63773,73598,66695,Probation,obryan,Samantha,NULL,Female,African-American,04/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +63773,73598,66695,Probation,obryan,Samantha,NULL,Female,African-American,04/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +45741,50534,46053,PRETRIAL,Ferrad,Pedro,NULL,Male,Hispanic,04/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +45741,50534,46053,PRETRIAL,Ferrad,Pedro,NULL,Male,Hispanic,04/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +45741,50534,46053,PRETRIAL,Ferrad,Pedro,NULL,Male,Hispanic,04/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +47916,73579,66678,PRETRIAL,ANDREWS,JEREMY,NULL,Male,African-American,08/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +47916,73579,66678,PRETRIAL,ANDREWS,JEREMY,NULL,Male,African-American,08/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +47916,73579,66678,PRETRIAL,ANDREWS,JEREMY,NULL,Male,African-American,08/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63763,73586,66684,PRETRIAL,Jones,Sade,NULL,Female,African-American,05/02/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +63763,73586,66684,PRETRIAL,Jones,Sade,NULL,Female,African-American,05/02/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +63763,73586,66684,PRETRIAL,Jones,Sade,NULL,Female,African-American,05/02/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63769,73593,66691,PRETRIAL,Borden,Brisha,NULL,Female,African-American,08/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +63769,73593,66691,PRETRIAL,Borden,Brisha,NULL,Female,African-American,08/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,8,High,New,1,0 +63769,73593,66691,PRETRIAL,Borden,Brisha,NULL,Female,African-American,08/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +3851,73607,3568,PRETRIAL,CHEW,NICHOLAS,PETER,Male,Hispanic,12/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,Copy,1,0 +3851,73607,3568,PRETRIAL,CHEW,NICHOLAS,PETER,Male,Hispanic,12/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,Copy,1,0 +3851,73607,3568,PRETRIAL,CHEW,NICHOLAS,PETER,Male,Hispanic,12/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +63783,73614,66707,PRETRIAL,Williams,Antonio,NULL,Male,African-American,10/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +63783,73614,66707,PRETRIAL,Williams,Antonio,NULL,Male,African-American,10/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +63783,73614,66707,PRETRIAL,Williams,Antonio,NULL,Male,African-American,10/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63779,73606,66702,Probation,washington,lorenzo,NULL,Male,African-American,08/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +63779,73606,66702,Probation,washington,lorenzo,NULL,Male,African-American,08/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +63779,73606,66702,Probation,washington,lorenzo,NULL,Male,African-American,08/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63782,73610,66705,Probation,JOSEPH,COBY,H,Male,African-American,08/15/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +63782,73610,66705,Probation,JOSEPH,COBY,H,Male,African-American,08/15/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +63782,73610,66705,Probation,JOSEPH,COBY,H,Male,African-American,08/15/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +54130,73620,66710,PRETRIAL,Coronell,Yonnatan,NULL,Male,Hispanic,08/03/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/29/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +54130,73620,66710,PRETRIAL,Coronell,Yonnatan,NULL,Male,Hispanic,08/03/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/29/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +54130,73620,66710,PRETRIAL,Coronell,Yonnatan,NULL,Male,Hispanic,08/03/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +16002,73585,66683,PRETRIAL,mcdougle,delvin,NULL,Male,African-American,09/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +16002,73585,66683,PRETRIAL,mcdougle,delvin,NULL,Male,African-American,09/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +16002,73585,66683,PRETRIAL,mcdougle,delvin,NULL,Male,African-American,09/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63765,73589,66687,PRETRIAL,Straub,Brian,John,Male,Caucasian,02/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +63765,73589,66687,PRETRIAL,Straub,Brian,John,Male,Caucasian,02/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +63765,73589,66687,PRETRIAL,Straub,Brian,John,Male,Caucasian,02/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63770,73594,66692,PRETRIAL,DOCE,FRANK,E,Male,Caucasian,06/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +63770,73594,66692,PRETRIAL,DOCE,FRANK,E,Male,Caucasian,06/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +63770,73594,66692,PRETRIAL,DOCE,FRANK,E,Male,Caucasian,06/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63787,73615,66708,PRETRIAL,Alicearamos,Wilson,NULL,Male,Hispanic,09/08/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/29/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +63787,73615,66708,PRETRIAL,Alicearamos,Wilson,NULL,Male,Hispanic,09/08/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +63787,73615,66708,PRETRIAL,Alicearamos,Wilson,NULL,Male,Hispanic,09/08/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63758,73578,66677,PRETRIAL,Scott,Torey,NULL,Male,African-American,12/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +63758,73578,66677,PRETRIAL,Scott,Torey,NULL,Male,African-American,12/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +63758,73578,66677,PRETRIAL,Scott,Torey,NULL,Male,African-American,12/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63759,73580,66679,PRETRIAL,Dixon,Demario,NULL,Male,Other,03/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +63759,73580,66679,PRETRIAL,Dixon,Demario,NULL,Male,Other,03/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +63759,73580,66679,PRETRIAL,Dixon,Demario,NULL,Male,Other,03/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63305,73599,66147,PRETRIAL,patino,andres,NULL,Male,Caucasian,06/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,Copy,1,0 +63305,73599,66147,PRETRIAL,patino,andres,NULL,Male,Caucasian,06/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,Copy,1,0 +63305,73599,66147,PRETRIAL,patino,andres,NULL,Male,Caucasian,06/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +63780,73608,66703,Probation,Graesch,Dennis,Sullivan,Male,Caucasian,05/24/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +63780,73608,66703,Probation,Graesch,Dennis,Sullivan,Male,Caucasian,05/24/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +63780,73608,66703,Probation,Graesch,Dennis,Sullivan,Male,Caucasian,05/24/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63790,73622,66712,Probation,LASTER,CASSANDRA,NULL,Female,African-American,01/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.44,3,Low,New,1,0 +63790,73622,66712,Probation,LASTER,CASSANDRA,NULL,Female,African-American,01/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.11,8,High,New,1,0 +63790,73622,66712,Probation,LASTER,CASSANDRA,NULL,Female,African-American,01/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63775,73603,66699,Probation,young,Christopher,Anthony,Male,African-American,12/31/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +63775,73603,66699,Probation,young,Christopher,Anthony,Male,African-American,12/31/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +63775,73603,66699,Probation,young,Christopher,Anthony,Male,African-American,12/31/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63778,73605,66701,Probation,Cumberbatch,Andre,NULL,Male,African-American,01/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/29/14 0:00,2,Medium,7,Risk of Violence,-2.66,2,Low,New,1,0 +63778,73605,66701,Probation,Cumberbatch,Andre,NULL,Male,African-American,01/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +63778,73605,66701,Probation,Cumberbatch,Andre,NULL,Male,African-American,01/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,5/29/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +21988,73582,36879,PRETRIAL,Rogers,Theophillus,NULL,Male,African-American,05/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.64,2,Low,Copy,1,0 +21988,73582,36879,PRETRIAL,Rogers,Theophillus,NULL,Male,African-American,05/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,Copy,1,0 +21988,73582,36879,PRETRIAL,Rogers,Theophillus,NULL,Male,African-American,05/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +63762,73584,66682,PRETRIAL,Greene,Constance,NULL,Male,Caucasian,09/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +63762,73584,66682,PRETRIAL,Greene,Constance,NULL,Male,Caucasian,09/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +63762,73584,66682,PRETRIAL,Greene,Constance,NULL,Male,Caucasian,09/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63788,73618,66709,PRETRIAL,Iacobelli,Angela,NULL,Female,Caucasian,05/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +63788,73618,66709,PRETRIAL,Iacobelli,Angela,NULL,Female,Caucasian,05/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +63788,73618,66709,PRETRIAL,Iacobelli,Angela,NULL,Female,Caucasian,05/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63772,73597,66694,Probation,Piunno,Robert,Anthyony,Male,Caucasian,04/05/52,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/29/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +63772,73597,66694,Probation,Piunno,Robert,Anthyony,Male,Caucasian,04/05/52,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/29/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +63772,73597,66694,Probation,Piunno,Robert,Anthyony,Male,Caucasian,04/05/52,22,Risk and Prescreen,Intake,English,Other,Probation,Married,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55839,73611,57750,PRETRIAL,Cadet,David,NULL,Male,African-American,03/02/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,Copy,1,0 +55839,73611,57750,PRETRIAL,Cadet,David,NULL,Male,African-American,03/02/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +55839,73611,57750,PRETRIAL,Cadet,David,NULL,Male,African-American,03/02/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +63766,73590,66688,PRETRIAL,Shade,Bruce,NULL,Male,African-American,12/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +63766,73590,66688,PRETRIAL,Shade,Bruce,NULL,Male,African-American,12/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +63766,73590,66688,PRETRIAL,Shade,Bruce,NULL,Male,African-American,12/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +33456,73587,66685,PRETRIAL,Davis,Neal,NULL,Male,African-American,07/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +33456,73587,66685,PRETRIAL,Davis,Neal,NULL,Male,African-American,07/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +33456,73587,66685,PRETRIAL,Davis,Neal,NULL,Male,African-American,07/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63789,73621,66711,Probation,pumphrey,joe,NULL,Male,Caucasian,02/28/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-4.53,1,Low,New,1,0 +63789,73621,66711,Probation,pumphrey,joe,NULL,Male,Caucasian,02/28/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +63789,73621,66711,Probation,pumphrey,joe,NULL,Male,Caucasian,02/28/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63774,73600,66696,Probation,Alfonso,Alexander,NULL,Male,Hispanic,04/29/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/29/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +63774,73600,66696,Probation,Alfonso,Alexander,NULL,Male,Hispanic,04/29/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/29/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +63774,73600,66696,Probation,Alfonso,Alexander,NULL,Male,Hispanic,04/29/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63041,73595,65853,Probation,Capriola,Courtney,NULL,Female,Caucasian,12/20/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +63041,73595,65853,Probation,Capriola,Courtney,NULL,Female,Caucasian,12/20/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +63041,73595,65853,Probation,Capriola,Courtney,NULL,Female,Caucasian,12/20/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,5/29/14 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +63768,73592,66690,PRETRIAL,HUMPHREY,TERRY,D,Male,African-American,10/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +63768,73592,66690,PRETRIAL,HUMPHREY,TERRY,D,Male,African-American,10/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +63768,73592,66690,PRETRIAL,HUMPHREY,TERRY,D,Male,African-American,10/11/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63814,73652,66739,Probation,Carbajal,Lorenzo,Ernesto,Male,Native American,12/03/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/30/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +63814,73652,66739,Probation,Carbajal,Lorenzo,Ernesto,Male,Native American,12/03/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/30/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +63814,73652,66739,Probation,Carbajal,Lorenzo,Ernesto,Male,Native American,12/03/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63799,73634,66723,PRETRIAL,Jackson,Scottie,NULL,Male,African-American,11/29/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +63799,73634,66723,PRETRIAL,Jackson,Scottie,NULL,Male,African-American,11/29/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +63799,73634,66723,PRETRIAL,Jackson,Scottie,NULL,Male,African-American,11/29/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +21667,73626,20821,PRETRIAL,Pierre,Josue,NULL,Male,African-American,12/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,Copy,1,0 +21667,73626,20821,PRETRIAL,Pierre,Josue,NULL,Male,African-American,12/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.88,10,High,Copy,1,0 +21667,73626,20821,PRETRIAL,Pierre,Josue,NULL,Male,African-American,12/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +63810,73647,66735,Probation,Canales,Alfonso,alberto,Male,Hispanic,03/21/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/30/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +63810,73647,66735,Probation,Canales,Alfonso,alberto,Male,Hispanic,03/21/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/30/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +63810,73647,66735,Probation,Canales,Alfonso,alberto,Male,Hispanic,03/21/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63797,73631,66720,PRETRIAL,Becklum,Roger,NULL,Male,African-American,11/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.12,8,High,New,1,0 +63797,73631,66720,PRETRIAL,Becklum,Roger,NULL,Male,African-American,11/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +63797,73631,66720,PRETRIAL,Becklum,Roger,NULL,Male,African-American,11/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63802,73639,66727,PRETRIAL,Graham,Stacie,NULL,Female,African-American,10/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/30/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +63802,73639,66727,PRETRIAL,Graham,Stacie,NULL,Female,African-American,10/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/30/14 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +63802,73639,66727,PRETRIAL,Graham,Stacie,NULL,Female,African-American,10/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51718,73629,66718,PRETRIAL,OWENS,JOHNNY,L,Male,African-American,06/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +51718,73629,66718,PRETRIAL,OWENS,JOHNNY,L,Male,African-American,06/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +51718,73629,66718,PRETRIAL,OWENS,JOHNNY,L,Male,African-American,06/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63800,73636,66725,Probation,Kovalsky,David,NULL,Male,Caucasian,10/27/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/30/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +63800,73636,66725,Probation,Kovalsky,David,NULL,Male,Caucasian,10/27/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/30/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +63800,73636,66725,Probation,Kovalsky,David,NULL,Male,Caucasian,10/27/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58052,73643,66731,PRETRIAL,Bauman,Lawrence,NULL,Male,Caucasian,06/28/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/30/14 0:00,1,Low,7,Risk of Violence,-4.38,1,Low,New,1,0 +58052,73643,66731,PRETRIAL,Bauman,Lawrence,NULL,Male,Caucasian,06/28/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/30/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +58052,73643,66731,PRETRIAL,Bauman,Lawrence,NULL,Male,Caucasian,06/28/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63812,73650,66737,Probation,TRAMUTOLA,RYAN,JOHN,Male,Caucasian,10/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +63812,73650,66737,Probation,TRAMUTOLA,RYAN,JOHN,Male,Caucasian,10/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +63812,73650,66737,Probation,TRAMUTOLA,RYAN,JOHN,Male,Caucasian,10/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63794,73627,66716,PRETRIAL,Gilmore,Loron,NULL,Male,African-American,04/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.49,3,Low,New,1,0 +63794,73627,66716,PRETRIAL,Gilmore,Loron,NULL,Male,African-American,04/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +63794,73627,66716,PRETRIAL,Gilmore,Loron,NULL,Male,African-American,04/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +63806,73645,66733,PRETRIAL,Vergel,John,NULL,Male,Hispanic,10/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +63806,73645,66733,PRETRIAL,Vergel,John,NULL,Male,Hispanic,10/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +63806,73645,66733,PRETRIAL,Vergel,John,NULL,Male,Hispanic,10/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63792,73624,66714,PRETRIAL,Sheppard,Jimmy,NULL,Male,African-American,12/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +63792,73624,66714,PRETRIAL,Sheppard,Jimmy,NULL,Male,African-American,12/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +63792,73624,66714,PRETRIAL,Sheppard,Jimmy,NULL,Male,African-American,12/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63804,73641,66729,Probation,Davis,Lateice,NULL,Female,African-American,07/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +63804,73641,66729,Probation,Davis,Lateice,NULL,Female,African-American,07/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +63804,73641,66729,Probation,Davis,Lateice,NULL,Female,African-American,07/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63801,73637,66726,PRETRIAL,Kintchen,Terris,NULL,Male,African-American,01/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +63801,73637,66726,PRETRIAL,Kintchen,Terris,NULL,Male,African-American,01/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +63801,73637,66726,PRETRIAL,Kintchen,Terris,NULL,Male,African-American,01/21/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63809,73644,66732,DRRD,Williams,Jermaine,Antonio,Male,African-American,10/16/89,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,5/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,New,1,0 +63809,73644,66732,DRRD,Williams,Jermaine,Antonio,Male,African-American,10/16/89,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,5/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +63809,73644,66732,DRRD,Williams,Jermaine,Antonio,Male,African-American,10/16/89,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,5/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,2,Low,New,1,0 +63795,73628,66717,PRETRIAL,Brown,Maurice,NULL,Male,African-American,04/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +63795,73628,66717,PRETRIAL,Brown,Maurice,NULL,Male,African-American,04/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +63795,73628,66717,PRETRIAL,Brown,Maurice,NULL,Male,African-American,04/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63798,73632,66721,Probation,WARD,PARIS,NULL,Female,African-American,12/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +63798,73632,66721,Probation,WARD,PARIS,NULL,Female,African-American,12/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +63798,73632,66721,Probation,WARD,PARIS,NULL,Female,African-American,12/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63811,73649,66736,Probation,Moreira,Geovanni,NULL,Male,Hispanic,04/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +63811,73649,66736,Probation,Moreira,Geovanni,NULL,Male,Hispanic,04/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +63811,73649,66736,Probation,Moreira,Geovanni,NULL,Male,Hispanic,04/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63791,73623,66713,PRETRIAL,Toussaint,Jonathan,NULL,Male,African-American,01/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +63791,73623,66713,PRETRIAL,Toussaint,Jonathan,NULL,Male,African-American,01/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +63791,73623,66713,PRETRIAL,Toussaint,Jonathan,NULL,Male,African-American,01/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62638,73638,65383,Probation,Ortega,Juan,NULL,Male,Hispanic,07/29/95,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.08,8,High,New,1,0 +62638,73638,65383,Probation,Ortega,Juan,NULL,Male,Hispanic,07/29/95,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +62638,73638,65383,Probation,Ortega,Juan,NULL,Male,Hispanic,07/29/95,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,2,Low,New,1,0 +63813,73651,66738,Probation,Bullard,Jonson,NULL,Male,Caucasian,06/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +63813,73651,66738,Probation,Bullard,Jonson,NULL,Male,Caucasian,06/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +63813,73651,66738,Probation,Bullard,Jonson,NULL,Male,Caucasian,06/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63796,73630,66719,PRETRIAL,Clermond,Stanley,NULL,Male,Other,01/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +63796,73630,66719,PRETRIAL,Clermond,Stanley,NULL,Male,Other,01/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +63796,73630,66719,PRETRIAL,Clermond,Stanley,NULL,Male,Other,01/09/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/30/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +15581,73646,66734,Probation,Hammond,AAron,Scott,Male,Caucasian,05/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +15581,73646,66734,Probation,Hammond,AAron,Scott,Male,Caucasian,05/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +15581,73646,66734,Probation,Hammond,AAron,Scott,Male,Caucasian,05/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +33275,73633,66722,PRETRIAL,Dunford,Ryanne,NULL,Male,Caucasian,10/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +33275,73633,66722,PRETRIAL,Dunford,Ryanne,NULL,Male,Caucasian,10/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,4,High,8,Risk of Recidivism,0.39,9,High,New,1,0 +33275,73633,66722,PRETRIAL,Dunford,Ryanne,NULL,Male,Caucasian,10/26/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +27072,73648,26182,PRETRIAL,Hunt,Jeffrey,NULL,Male,Caucasian,01/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,2,Medium,7,Risk of Violence,-2.92,2,Low,Copy,1,0 +27072,73648,26182,PRETRIAL,Hunt,Jeffrey,NULL,Male,Caucasian,01/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,Copy,1,0 +27072,73648,26182,PRETRIAL,Hunt,Jeffrey,NULL,Male,Caucasian,01/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,5/30/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +63793,73625,66715,PRETRIAL,Munoz,Maricela,NULL,Female,Hispanic,04/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/30/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +63793,73625,66715,PRETRIAL,Munoz,Maricela,NULL,Female,Hispanic,04/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/30/14 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +63793,73625,66715,PRETRIAL,Munoz,Maricela,NULL,Female,Hispanic,04/05/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63803,73640,66728,Probation,CARROLL,DEMETREE,NULL,Female,African-American,12/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +63803,73640,66728,Probation,CARROLL,DEMETREE,NULL,Female,African-American,12/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +63803,73640,66728,Probation,CARROLL,DEMETREE,NULL,Female,African-American,12/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,5/30/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51176,73654,52338,PRETRIAL,TORRES,ALFONSO,A,Male,Hispanic,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,Copy,1,0 +51176,73654,52338,PRETRIAL,TORRES,ALFONSO,A,Male,Hispanic,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.79,10,High,Copy,1,0 +51176,73654,52338,PRETRIAL,TORRES,ALFONSO,A,Male,Hispanic,12/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +1499,73661,66747,PRETRIAL,SEVIL,STEVE,NULL,Male,African-American,07/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +1499,73661,66747,PRETRIAL,SEVIL,STEVE,NULL,Male,African-American,07/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +1499,73661,66747,PRETRIAL,SEVIL,STEVE,NULL,Male,African-American,07/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63826,73667,66752,PRETRIAL,Mathis,Kwauniesha,Chaneka,Female,African-American,10/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +63826,73667,66752,PRETRIAL,Mathis,Kwauniesha,Chaneka,Female,African-American,10/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +63826,73667,66752,PRETRIAL,Mathis,Kwauniesha,Chaneka,Female,African-American,10/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62367,73664,65051,PRETRIAL,Tovar,Jonathan,NULL,Male,Caucasian,05/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,Copy,1,0 +62367,73664,65051,PRETRIAL,Tovar,Jonathan,NULL,Male,Caucasian,05/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,Copy,1,0 +62367,73664,65051,PRETRIAL,Tovar,Jonathan,NULL,Male,Caucasian,05/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +63818,73656,66742,PRETRIAL,Hannan,Quinton,NULL,Male,African-American,05/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +63818,73656,66742,PRETRIAL,Hannan,Quinton,NULL,Male,African-American,05/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +63818,73656,66742,PRETRIAL,Hannan,Quinton,NULL,Male,African-American,05/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63821,73659,66745,PRETRIAL,Lopez,Carlo,NULL,Male,Caucasian,11/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +63821,73659,66745,PRETRIAL,Lopez,Carlo,NULL,Male,Caucasian,11/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +63821,73659,66745,PRETRIAL,Lopez,Carlo,NULL,Male,Caucasian,11/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63815,73653,66740,PRETRIAL,MITCHELL,JAMES,HENRY,Male,African-American,12/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +63815,73653,66740,PRETRIAL,MITCHELL,JAMES,HENRY,Male,African-American,12/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +63815,73653,66740,PRETRIAL,MITCHELL,JAMES,HENRY,Male,African-American,12/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63824,73665,66750,PRETRIAL,Franklin,Milton,Elbert,Male,African-American,07/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +63824,73665,66750,PRETRIAL,Franklin,Milton,Elbert,Male,African-American,07/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +63824,73665,66750,PRETRIAL,Franklin,Milton,Elbert,Male,African-American,07/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63820,73658,66744,PRETRIAL,Vasquez,Melvin,NULL,Male,Hispanic,09/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +63820,73658,66744,PRETRIAL,Vasquez,Melvin,NULL,Male,Hispanic,09/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +63820,73658,66744,PRETRIAL,Vasquez,Melvin,NULL,Male,Hispanic,09/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63825,73666,66751,PRETRIAL,Gustafson,Peter,Harold,Male,Caucasian,05/31/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +63825,73666,66751,PRETRIAL,Gustafson,Peter,Harold,Male,Caucasian,05/31/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +63825,73666,66751,PRETRIAL,Gustafson,Peter,Harold,Male,Caucasian,05/31/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +10335,73662,66748,Probation,Hughes,John,NULL,Male,Caucasian,10/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +10335,73662,66748,Probation,Hughes,John,NULL,Male,Caucasian,10/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +10335,73662,66748,Probation,Hughes,John,NULL,Male,Caucasian,10/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63819,73657,66743,PRETRIAL,Pierre,Daline,NULL,Female,African-American,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +63819,73657,66743,PRETRIAL,Pierre,Daline,NULL,Female,African-American,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +63819,73657,66743,PRETRIAL,Pierre,Daline,NULL,Female,African-American,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63827,73668,66753,PRETRIAL,Allen,Irene,NULL,Female,Caucasian,03/16/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.06,1,Low,New,1,0 +63827,73668,66753,PRETRIAL,Allen,Irene,NULL,Female,Caucasian,03/16/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +63827,73668,66753,PRETRIAL,Allen,Irene,NULL,Female,Caucasian,03/16/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,New,1,0 +63817,73655,66741,PRETRIAL,Veasy,Alexis,NULL,Female,African-American,11/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/31/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +63817,73655,66741,PRETRIAL,Veasy,Alexis,NULL,Female,African-American,11/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/31/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +63817,73655,66741,PRETRIAL,Veasy,Alexis,NULL,Female,African-American,11/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,5/31/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63823,73663,66749,PRETRIAL,Bedward,George,NULL,Male,African-American,05/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +63823,73663,66749,PRETRIAL,Bedward,George,NULL,Male,African-American,05/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +63823,73663,66749,PRETRIAL,Bedward,George,NULL,Male,African-American,05/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63822,73660,66746,PRETRIAL,Robinson,Christopher,NULL,Male,Caucasian,06/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2,4,Low,New,1,0 +63822,73660,66746,PRETRIAL,Robinson,Christopher,NULL,Male,Caucasian,06/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +63822,73660,66746,PRETRIAL,Robinson,Christopher,NULL,Male,Caucasian,06/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,5/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +47265,73673,47788,Probation,LEVINS,JOSEPH,NULL,Male,African-American,03/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +47265,73673,47788,Probation,LEVINS,JOSEPH,NULL,Male,African-American,03/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,Copy,1,0 +47265,73673,47788,Probation,LEVINS,JOSEPH,NULL,Male,African-American,03/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,6,Medium,Copy,1,0 +63838,73681,66764,PRETRIAL,HELMS,TARA,M,Female,Caucasian,06/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/1/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +63838,73681,66764,PRETRIAL,HELMS,TARA,M,Female,Caucasian,06/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/1/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +63838,73681,66764,PRETRIAL,HELMS,TARA,M,Female,Caucasian,06/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63841,73684,66767,PRETRIAL,CRESPO,JUAN,CARLOS,Male,Caucasian,07/21/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +63841,73684,66767,PRETRIAL,CRESPO,JUAN,CARLOS,Male,Caucasian,07/21/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +63841,73684,66767,PRETRIAL,CRESPO,JUAN,CARLOS,Male,Caucasian,07/21/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63834,73676,66760,PRETRIAL,MCKAY,TIFFANY,SHARELL,Female,African-American,11/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +63834,73676,66760,PRETRIAL,MCKAY,TIFFANY,SHARELL,Female,African-American,11/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +63834,73676,66760,PRETRIAL,MCKAY,TIFFANY,SHARELL,Female,African-American,11/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63830,73671,66756,PRETRIAL,JEANBAPTISTE,JEAN,NULL,Male,African-American,10/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +63830,73671,66756,PRETRIAL,JEANBAPTISTE,JEAN,NULL,Male,African-American,10/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +63830,73671,66756,PRETRIAL,JEANBAPTISTE,JEAN,NULL,Male,African-American,10/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63835,73678,66761,PRETRIAL,SHUPERT,DONALD,MICHAEL,Male,Caucasian,05/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +63835,73678,66761,PRETRIAL,SHUPERT,DONALD,MICHAEL,Male,Caucasian,05/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +63835,73678,66761,PRETRIAL,SHUPERT,DONALD,MICHAEL,Male,Caucasian,05/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63837,73680,66763,PRETRIAL,VANIER,MELINDA,NULL,Female,Caucasian,09/10/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +63837,73680,66763,PRETRIAL,VANIER,MELINDA,NULL,Female,Caucasian,09/10/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +63837,73680,66763,PRETRIAL,VANIER,MELINDA,NULL,Female,Caucasian,09/10/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +5481,73687,5141,Probation,Haase,Ian,D,Male,Other,05/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/1/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,Copy,1,0 +5481,73687,5141,Probation,Haase,Ian,D,Male,Other,05/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/1/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,Copy,1,0 +5481,73687,5141,Probation,Haase,Ian,D,Male,Other,05/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +63840,73683,66766,PRETRIAL,Joseph,Widney,NULL,Male,African-American,09/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/1/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +63840,73683,66766,PRETRIAL,Joseph,Widney,NULL,Male,African-American,09/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/1/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +63840,73683,66766,PRETRIAL,Joseph,Widney,NULL,Male,African-American,09/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63831,73672,66757,PRETRIAL,Clerge,Rony,NULL,Male,African-American,02/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +63831,73672,66757,PRETRIAL,Clerge,Rony,NULL,Male,African-American,02/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +63831,73672,66757,PRETRIAL,Clerge,Rony,NULL,Male,African-American,02/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63836,73679,66762,PRETRIAL,Higgins,Jessica,NULL,Male,African-American,05/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +63836,73679,66762,PRETRIAL,Higgins,Jessica,NULL,Male,African-American,05/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +63836,73679,66762,PRETRIAL,Higgins,Jessica,NULL,Male,African-American,05/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63842,73686,66768,PRETRIAL,Aumack,Kevin,NULL,Male,Caucasian,03/10/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +63842,73686,66768,PRETRIAL,Aumack,Kevin,NULL,Male,Caucasian,03/10/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +63842,73686,66768,PRETRIAL,Aumack,Kevin,NULL,Male,Caucasian,03/10/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63832,73674,66758,PRETRIAL,JACOBS,ROY,EDWARD,Female,Caucasian,08/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +63832,73674,66758,PRETRIAL,JACOBS,ROY,EDWARD,Female,Caucasian,08/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,9,High,New,1,0 +63832,73674,66758,PRETRIAL,JACOBS,ROY,EDWARD,Female,Caucasian,08/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63829,73670,66755,PRETRIAL,FRANCIS,BARRINGTON,NULL,Male,African-American,06/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +63829,73670,66755,PRETRIAL,FRANCIS,BARRINGTON,NULL,Male,African-American,06/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +63829,73670,66755,PRETRIAL,FRANCIS,BARRINGTON,NULL,Male,African-American,06/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63843,73688,66769,PRETRIAL,WALKER,TERRY,NULL,Male,African-American,11/24/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +63843,73688,66769,PRETRIAL,WALKER,TERRY,NULL,Male,African-American,11/24/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +63843,73688,66769,PRETRIAL,WALKER,TERRY,NULL,Male,African-American,11/24/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +2055,73677,53259,PRETRIAL,JONES,MYRON,NULL,Male,African-American,07/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,Copy,1,0 +2055,73677,53259,PRETRIAL,JONES,MYRON,NULL,Male,African-American,07/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,Copy,1,0 +2055,73677,53259,PRETRIAL,JONES,MYRON,NULL,Male,African-American,07/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +63839,73682,66765,PRETRIAL,SHURPERT,DONALD,C,Male,Caucasian,10/02/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/1/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +63839,73682,66765,PRETRIAL,SHURPERT,DONALD,C,Male,Caucasian,10/02/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/1/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +63839,73682,66765,PRETRIAL,SHURPERT,DONALD,C,Male,Caucasian,10/02/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63828,73669,66754,PRETRIAL,JENKINS,COLETTER,LEVETTE,Female,African-American,10/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +63828,73669,66754,PRETRIAL,JENKINS,COLETTER,LEVETTE,Female,African-American,10/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +63828,73669,66754,PRETRIAL,JENKINS,COLETTER,LEVETTE,Female,African-American,10/31/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/1/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63833,73675,66759,PRETRIAL,Oliver,Shawn,NULL,Male,African-American,07/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +63833,73675,66759,PRETRIAL,Oliver,Shawn,NULL,Male,African-American,07/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.8,10,High,New,1,0 +63833,73675,66759,PRETRIAL,Oliver,Shawn,NULL,Male,African-American,07/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63845,73690,66771,PRETRIAL,APPLY,SHAWNA,SHAWN,Female,African-American,03/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +63845,73690,66771,PRETRIAL,APPLY,SHAWNA,SHAWN,Female,African-American,03/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +63845,73690,66771,PRETRIAL,APPLY,SHAWNA,SHAWN,Female,African-American,03/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63866,73711,66790,Probation,GARRAWAY,JOEL,NULL,Male,African-American,06/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/2/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +63866,73711,66790,Probation,GARRAWAY,JOEL,NULL,Male,African-American,06/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +63866,73711,66790,Probation,GARRAWAY,JOEL,NULL,Male,African-American,06/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63860,73703,66783,PRETRIAL,Brown,Daniel,NULL,Male,African-American,11/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +63860,73703,66783,PRETRIAL,Brown,Daniel,NULL,Male,African-American,11/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,4,High,8,Risk of Recidivism,1.26,10,High,New,1,0 +63860,73703,66783,PRETRIAL,Brown,Daniel,NULL,Male,African-American,11/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63862,73706,66785,Probation,TOUSSAINT,CLAIREMISE,NULL,Female,African-American,10/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +63862,73706,66785,Probation,TOUSSAINT,CLAIREMISE,NULL,Female,African-American,10/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +63862,73706,66785,Probation,TOUSSAINT,CLAIREMISE,NULL,Female,African-American,10/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53863,73724,66801,PRETRIAL,Richards,Juvuan,NULL,Male,African-American,06/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +53863,73724,66801,PRETRIAL,Richards,Juvuan,NULL,Male,African-American,06/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +53863,73724,66801,PRETRIAL,Richards,Juvuan,NULL,Male,African-American,06/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63879,73727,66804,Probation,Johnson,Arkee,Rosha,Male,African-American,04/02/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +63879,73727,66804,Probation,Johnson,Arkee,Rosha,Male,African-American,04/02/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +63879,73727,66804,Probation,Johnson,Arkee,Rosha,Male,African-American,04/02/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63855,73698,66778,PRETRIAL,Cunningham,Michael,NULL,Male,African-American,01/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/2/14 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +63855,73698,66778,PRETRIAL,Cunningham,Michael,NULL,Male,African-American,01/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +63855,73698,66778,PRETRIAL,Cunningham,Michael,NULL,Male,African-American,01/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/2/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63882,73732,66808,PRETRIAL,Donofrino,Michael,NULL,Male,Caucasian,07/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/2/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +63882,73732,66808,PRETRIAL,Donofrino,Michael,NULL,Male,Caucasian,07/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +63882,73732,66808,PRETRIAL,Donofrino,Michael,NULL,Male,Caucasian,07/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63853,73695,66776,PRETRIAL,Quiroz-Bonilla,Claussen,NULL,Male,Hispanic,05/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +63853,73695,66776,PRETRIAL,Quiroz-Bonilla,Claussen,NULL,Male,Hispanic,05/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +63853,73695,66776,PRETRIAL,Quiroz-Bonilla,Claussen,NULL,Male,Hispanic,05/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +34691,73691,66772,PRETRIAL,wells,andy,NULL,Male,African-American,03/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/2/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +34691,73691,66772,PRETRIAL,wells,andy,NULL,Male,African-American,03/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +34691,73691,66772,PRETRIAL,wells,andy,NULL,Male,African-American,03/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/2/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63865,73709,66788,Probation,Hamilton,Seth,NULL,Male,African-American,02/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +63865,73709,66788,Probation,Hamilton,Seth,NULL,Male,African-American,02/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +63865,73709,66788,Probation,Hamilton,Seth,NULL,Male,African-American,02/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63893,73742,66816,Probation,Winston,Christine,NULL,Female,Caucasian,11/15/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/2/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +63893,73742,66816,Probation,Winston,Christine,NULL,Female,Caucasian,11/15/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/2/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +63893,73742,66816,Probation,Winston,Christine,NULL,Female,Caucasian,11/15/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +63875,73721,66799,Probation,Jordan,Bryan,NULL,Male,African-American,01/03/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +63875,73721,66799,Probation,Jordan,Bryan,NULL,Male,African-American,01/03/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +63875,73721,66799,Probation,Jordan,Bryan,NULL,Male,African-American,01/03/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63857,73700,66780,PRETRIAL,ENDARA,ANDRES,ANTONIO,Male,Caucasian,09/29/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +63857,73700,66780,PRETRIAL,ENDARA,ANDRES,ANTONIO,Male,Caucasian,09/29/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +63857,73700,66780,PRETRIAL,ENDARA,ANDRES,ANTONIO,Male,Caucasian,09/29/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63851,73693,66774,PRETRIAL,TAYLOR,QUINTON,D,Male,Caucasian,09/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +63851,73693,66774,PRETRIAL,TAYLOR,QUINTON,D,Male,Caucasian,09/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +63851,73693,66774,PRETRIAL,TAYLOR,QUINTON,D,Male,Caucasian,09/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63863,73707,66786,Probation,Taylor,Frederick,NULL,Male,African-American,09/07/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +63863,73707,66786,Probation,Taylor,Frederick,NULL,Male,African-American,09/07/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +63863,73707,66786,Probation,Taylor,Frederick,NULL,Male,African-American,09/07/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63871,73716,66795,Probation,moss,robin,NULL,Female,African-American,06/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +63871,73716,66795,Probation,moss,robin,NULL,Female,African-American,06/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +63871,73716,66795,Probation,moss,robin,NULL,Female,African-American,06/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63869,73714,66793,Probation,Perez,Gladys,NULL,Female,Hispanic,07/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/2/14 0:00,2,Medium,7,Risk of Violence,-1.85,5,Medium,New,1,0 +63869,73714,66793,Probation,Perez,Gladys,NULL,Female,Hispanic,07/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +63869,73714,66793,Probation,Perez,Gladys,NULL,Female,Hispanic,07/09/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/2/14 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +48391,73737,66812,PRETRIAL,Viverossolis,Richard,Joseph,Male,African-American,01/01/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +48391,73737,66812,PRETRIAL,Viverossolis,Richard,Joseph,Male,African-American,01/01/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +48391,73737,66812,PRETRIAL,Viverossolis,Richard,Joseph,Male,African-American,01/01/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63872,73717,66796,PRETRIAL,MCCREA,JAMAAL,NULL,Male,African-American,02/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/2/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +63872,73717,66796,PRETRIAL,MCCREA,JAMAAL,NULL,Male,African-American,02/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +63872,73717,66796,PRETRIAL,MCCREA,JAMAAL,NULL,Male,African-American,02/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +30073,73734,53898,Probation,ETIENNE,EDELINE,NULL,Female,African-American,03/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,Copy,1,0 +30073,73734,53898,Probation,ETIENNE,EDELINE,NULL,Female,African-American,03/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,Copy,1,0 +30073,73734,53898,Probation,ETIENNE,EDELINE,NULL,Female,African-American,03/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +37020,73696,36358,PRETRIAL,MATUSZEWSKI,CARISSA,N,Female,Caucasian,10/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,Copy,1,0 +37020,73696,36358,PRETRIAL,MATUSZEWSKI,CARISSA,N,Female,Caucasian,10/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,Copy,1,0 +37020,73696,36358,PRETRIAL,MATUSZEWSKI,CARISSA,N,Female,Caucasian,10/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +63850,73692,66773,PRETRIAL,BOBSOS,EUGENE,IRVIN,Male,African-American,04/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +63850,73692,66773,PRETRIAL,BOBSOS,EUGENE,IRVIN,Male,African-American,04/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +63850,73692,66773,PRETRIAL,BOBSOS,EUGENE,IRVIN,Male,African-American,04/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63868,73713,66792,PRETRIAL,Pena,Viviana,NULL,Female,Hispanic,04/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/2/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +63868,73713,66792,PRETRIAL,Pena,Viviana,NULL,Female,Hispanic,04/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +63868,73713,66792,PRETRIAL,Pena,Viviana,NULL,Female,Hispanic,04/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63885,73738,66813,Probation,Rolle,Kenneth,NULL,Male,African-American,04/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +63885,73738,66813,Probation,Rolle,Kenneth,NULL,Male,African-American,04/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +63885,73738,66813,Probation,Rolle,Kenneth,NULL,Male,African-American,04/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63856,73699,66779,PRETRIAL,PIERRE,RUUD,NULL,Male,Other,12/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +63856,73699,66779,PRETRIAL,PIERRE,RUUD,NULL,Male,Other,12/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +63856,73699,66779,PRETRIAL,PIERRE,RUUD,NULL,Male,Other,12/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63864,73708,66787,PRETRIAL,Perez,Frank,NULL,Male,Hispanic,10/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/2/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +63864,73708,66787,PRETRIAL,Perez,Frank,NULL,Male,Hispanic,10/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +63864,73708,66787,PRETRIAL,Perez,Frank,NULL,Male,Hispanic,10/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63393,73722,66238,PRETRIAL,Osceola,Angelo,NULL,Male,Native American,11/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,Copy,1,0 +63393,73722,66238,PRETRIAL,Osceola,Angelo,NULL,Male,Native American,11/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.63,10,High,Copy,1,0 +63393,73722,66238,PRETRIAL,Osceola,Angelo,NULL,Male,Native American,11/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +27539,73729,66806,DRRD,Sullivan,Miriam,NULL,Female,Hispanic,09/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +27539,73729,66806,DRRD,Sullivan,Miriam,NULL,Female,Hispanic,09/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +27539,73729,66806,DRRD,Sullivan,Miriam,NULL,Female,Hispanic,09/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +63884,73736,66811,Probation,Taylor,Nkechi,NULL,Female,African-American,05/14/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/2/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +63884,73736,66811,Probation,Taylor,Nkechi,NULL,Female,African-American,05/14/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +63884,73736,66811,Probation,Taylor,Nkechi,NULL,Female,African-American,05/14/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63877,73725,66802,PRETRIAL,Burdugo,Ariel,NULL,Male,Hispanic,09/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/2/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +63877,73725,66802,PRETRIAL,Burdugo,Ariel,NULL,Male,Hispanic,09/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +63877,73725,66802,PRETRIAL,Burdugo,Ariel,NULL,Male,Hispanic,09/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63878,73726,66803,Probation,melchizedek,abraham,NULL,Male,African-American,05/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/2/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +63878,73726,66803,Probation,melchizedek,abraham,NULL,Male,African-American,05/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +63878,73726,66803,Probation,melchizedek,abraham,NULL,Male,African-American,05/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63854,73697,66777,PRETRIAL,Johnson,Kyle,NULL,Female,Caucasian,11/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +63854,73697,66777,PRETRIAL,Johnson,Kyle,NULL,Female,Caucasian,11/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +63854,73697,66777,PRETRIAL,Johnson,Kyle,NULL,Female,Caucasian,11/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,30,9,High,New,1,0 +63861,73704,66784,PRETRIAL,BROWN,DAMANI,NULL,Male,African-American,07/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,2,Medium,7,Risk of Violence,-1.28,7,Medium,New,1,0 +63861,73704,66784,PRETRIAL,BROWN,DAMANI,NULL,Male,African-American,07/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +63861,73704,66784,PRETRIAL,BROWN,DAMANI,NULL,Male,African-American,07/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63873,73718,66797,Probation,hanks,shatara,NULL,Female,African-American,06/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +63873,73718,66797,Probation,hanks,shatara,NULL,Female,African-American,06/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,7,Medium,New,1,0 +63873,73718,66797,Probation,hanks,shatara,NULL,Female,African-American,06/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54482,73733,66809,Probation,TINTORI,TIMOTHY,NEIL,Male,Caucasian,03/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +54482,73733,66809,Probation,TINTORI,TIMOTHY,NEIL,Male,Caucasian,03/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +54482,73733,66809,Probation,TINTORI,TIMOTHY,NEIL,Male,Caucasian,03/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +45569,73705,53992,PRETRIAL,Williams,Terrance,NULL,Male,African-American,11/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/2/14 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,Copy,1,0 +45569,73705,53992,PRETRIAL,Williams,Terrance,NULL,Male,African-American,11/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,Copy,1,0 +45569,73705,53992,PRETRIAL,Williams,Terrance,NULL,Male,African-American,11/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/2/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +63867,73712,66791,PRETRIAL,Joseph,Assad,NULL,Male,African-American,04/21/81,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +63867,73712,66791,PRETRIAL,Joseph,Assad,NULL,Male,African-American,04/21/81,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-0.74,3,Low,New,1,0 +63867,73712,66791,PRETRIAL,Joseph,Assad,NULL,Male,African-American,04/21/81,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +63890,73739,66814,PRETRIAL,KENNEDY,BARBARA,NULL,Female,African-American,10/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +63890,73739,66814,PRETRIAL,KENNEDY,BARBARA,NULL,Female,African-American,10/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +63890,73739,66814,PRETRIAL,KENNEDY,BARBARA,NULL,Female,African-American,10/11/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63859,73702,66782,PRETRIAL,horan,michael,NULL,Male,Caucasian,08/22/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +63859,73702,66782,PRETRIAL,horan,michael,NULL,Male,Caucasian,08/22/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +63859,73702,66782,PRETRIAL,horan,michael,NULL,Male,Caucasian,08/22/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63881,73731,66807,PRETRIAL,Major,James,NULL,Male,African-American,05/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +63881,73731,66807,PRETRIAL,Major,James,NULL,Male,African-American,05/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.27,10,High,New,1,0 +63881,73731,66807,PRETRIAL,Major,James,NULL,Male,African-American,05/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +58916,73710,66789,Probation,EDWARDS,VINCENT,NULL,Male,African-American,07/15/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/2/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +58916,73710,66789,Probation,EDWARDS,VINCENT,NULL,Male,African-American,07/15/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +58916,73710,66789,Probation,EDWARDS,VINCENT,NULL,Male,African-American,07/15/61,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63876,73723,66800,PRETRIAL,PATRICK,MICHAEL,NULL,Male,Caucasian,07/31/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +63876,73723,66800,PRETRIAL,PATRICK,MICHAEL,NULL,Male,Caucasian,07/31/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +63876,73723,66800,PRETRIAL,PATRICK,MICHAEL,NULL,Male,Caucasian,07/31/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54322,73741,66815,PRETRIAL,Boyd,Eben,NULL,Male,Caucasian,07/19/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +54322,73741,66815,PRETRIAL,Boyd,Eben,NULL,Male,Caucasian,07/19/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +54322,73741,66815,PRETRIAL,Boyd,Eben,NULL,Male,Caucasian,07/19/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63844,73689,66770,PRETRIAL,Sasson,David,NULL,Male,Caucasian,02/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +63844,73689,66770,PRETRIAL,Sasson,David,NULL,Male,Caucasian,02/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +63844,73689,66770,PRETRIAL,Sasson,David,NULL,Male,Caucasian,02/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63852,73694,66775,PRETRIAL,DELIARD,JEAN,ROBERT,Male,Other,11/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +63852,73694,66775,PRETRIAL,DELIARD,JEAN,ROBERT,Male,Other,11/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +63852,73694,66775,PRETRIAL,DELIARD,JEAN,ROBERT,Male,Other,11/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63880,73728,66805,Probation,Lloret,Lizette,NULL,Female,Hispanic,01/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +63880,73728,66805,Probation,Lloret,Lizette,NULL,Female,Hispanic,01/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.36,7,Medium,New,1,0 +63880,73728,66805,Probation,Lloret,Lizette,NULL,Female,Hispanic,01/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/2/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63907,73762,66835,PRETRIAL,GILBERTI,VINCENT,LOUIS,Male,Caucasian,08/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +63907,73762,66835,PRETRIAL,GILBERTI,VINCENT,LOUIS,Male,Caucasian,08/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +63907,73762,66835,PRETRIAL,GILBERTI,VINCENT,LOUIS,Male,Caucasian,08/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63898,73749,66822,PRETRIAL,JOHN,NADIA,NULL,Female,Other,08/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +63898,73749,66822,PRETRIAL,JOHN,NADIA,NULL,Female,Other,08/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +63898,73749,66822,PRETRIAL,JOHN,NADIA,NULL,Female,Other,08/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63927,73783,66855,Probation,Hines,Timothy,NULL,Male,African-American,09/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +63927,73783,66855,Probation,Hines,Timothy,NULL,Male,African-American,09/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +63927,73783,66855,Probation,Hines,Timothy,NULL,Male,African-American,09/18/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63914,73770,66842,PRETRIAL,Seraphin,Samuel,NULL,Male,African-American,03/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +63914,73770,66842,PRETRIAL,Seraphin,Samuel,NULL,Male,African-American,03/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +63914,73770,66842,PRETRIAL,Seraphin,Samuel,NULL,Male,African-American,03/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63896,73746,66819,PRETRIAL,Altidort,Mervyns,NULL,Male,Other,01/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +63896,73746,66819,PRETRIAL,Altidort,Mervyns,NULL,Male,Other,01/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +63896,73746,66819,PRETRIAL,Altidort,Mervyns,NULL,Male,Other,01/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63912,73767,66840,Probation,Oates,Elwood,NULL,Male,African-American,03/27/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/3/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +63912,73767,66840,Probation,Oates,Elwood,NULL,Male,African-American,03/27/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/3/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +63912,73767,66840,Probation,Oates,Elwood,NULL,Male,African-American,03/27/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59217,73747,66820,PRETRIAL,Pantaleon,Jose,NULL,Male,Hispanic,07/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +59217,73747,66820,PRETRIAL,Pantaleon,Jose,NULL,Male,Hispanic,07/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +59217,73747,66820,PRETRIAL,Pantaleon,Jose,NULL,Male,Hispanic,07/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +3242,73754,66827,PRETRIAL,rampartap,darryl,NULL,Male,Other,10/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +3242,73754,66827,PRETRIAL,rampartap,darryl,NULL,Male,Other,10/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +3242,73754,66827,PRETRIAL,rampartap,darryl,NULL,Male,Other,10/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63921,73775,66847,PRETRIAL,Cornileus,Gideon,NULL,Male,African-American,04/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +63921,73775,66847,PRETRIAL,Cornileus,Gideon,NULL,Male,African-American,04/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +63921,73775,66847,PRETRIAL,Cornileus,Gideon,NULL,Male,African-American,04/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +33877,73743,32989,PRETRIAL,Hollis,Delton,NULL,Male,African-American,06/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,Copy,1,0 +33877,73743,32989,PRETRIAL,Hollis,Delton,NULL,Male,African-American,06/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.68,10,High,Copy,1,0 +33877,73743,32989,PRETRIAL,Hollis,Delton,NULL,Male,African-American,06/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +63903,73757,66830,PRETRIAL,CUITO,LISA,NULL,Female,Caucasian,12/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +63903,73757,66830,PRETRIAL,CUITO,LISA,NULL,Female,Caucasian,12/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +63903,73757,66830,PRETRIAL,CUITO,LISA,NULL,Female,Caucasian,12/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63899,73750,66823,PRETRIAL,Brown,Arturo,NULL,Male,Hispanic,11/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +63899,73750,66823,PRETRIAL,Brown,Arturo,NULL,Male,Hispanic,11/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +63899,73750,66823,PRETRIAL,Brown,Arturo,NULL,Male,Hispanic,11/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +37909,73752,66825,PRETRIAL,WRIGHT,AQUIEL,K,Male,African-American,05/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,4,High,7,Risk of Violence,-0.82,9,High,New,1,0 +37909,73752,66825,PRETRIAL,WRIGHT,AQUIEL,K,Male,African-American,05/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +37909,73752,66825,PRETRIAL,WRIGHT,AQUIEL,K,Male,African-American,05/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63915,73771,66843,Probation,paige,justin,NULL,Male,Caucasian,08/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +63915,73771,66843,Probation,paige,justin,NULL,Male,Caucasian,08/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +63915,73771,66843,Probation,paige,justin,NULL,Male,Caucasian,08/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63917,73773,66845,Probation,Reyes,Carlos,NULL,Male,Hispanic,09/30/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/3/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +63917,73773,66845,Probation,Reyes,Carlos,NULL,Male,Hispanic,09/30/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/3/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +63917,73773,66845,Probation,Reyes,Carlos,NULL,Male,Hispanic,09/30/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63923,73778,66850,Probation,Hughes,Omar,NULL,Male,Hispanic,05/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +63923,73778,66850,Probation,Hughes,Omar,NULL,Male,Hispanic,05/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +63923,73778,66850,Probation,Hughes,Omar,NULL,Male,Hispanic,05/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +53496,73780,66852,Broward County,Artz,Jessica,NULL,Female,Caucasian,07/13/71,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +53496,73780,66852,Broward County,Artz,Jessica,NULL,Female,Caucasian,07/13/71,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +53496,73780,66852,Broward County,Artz,Jessica,NULL,Female,Caucasian,07/13/71,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63904,73759,66832,PRETRIAL,KENNEY,ALLYSON,NULL,Female,Caucasian,06/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +63904,73759,66832,PRETRIAL,KENNEY,ALLYSON,NULL,Female,Caucasian,06/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +63904,73759,66832,PRETRIAL,KENNEY,ALLYSON,NULL,Female,Caucasian,06/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63901,73755,66828,PRETRIAL,Delice,Armand,NULL,Male,Other,06/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +63901,73755,66828,PRETRIAL,Delice,Armand,NULL,Male,Other,06/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +63901,73755,66828,PRETRIAL,Delice,Armand,NULL,Male,Other,06/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63909,73764,66837,Probation,Ryan,Michael,NULL,Male,Caucasian,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +63909,73764,66837,Probation,Ryan,Michael,NULL,Male,Caucasian,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +63909,73764,66837,Probation,Ryan,Michael,NULL,Male,Caucasian,02/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63913,73768,66841,Probation,OSTROWSKI,JANUSZ,NULL,Male,Caucasian,04/30/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +63913,73768,66841,Probation,OSTROWSKI,JANUSZ,NULL,Male,Caucasian,04/30/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +63913,73768,66841,Probation,OSTROWSKI,JANUSZ,NULL,Male,Caucasian,04/30/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63894,73744,66817,PRETRIAL,GORDON,ALLISON,JANEL,Male,African-American,08/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +63894,73744,66817,PRETRIAL,GORDON,ALLISON,JANEL,Male,African-American,08/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +63894,73744,66817,PRETRIAL,GORDON,ALLISON,JANEL,Male,African-American,08/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63910,73765,66838,Probation,ENTENZA,CINDY,NULL,Female,Hispanic,07/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/3/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +63910,73765,66838,Probation,ENTENZA,CINDY,NULL,Female,Hispanic,07/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/3/14 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +63910,73765,66838,Probation,ENTENZA,CINDY,NULL,Female,Hispanic,07/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +24542,73758,66831,PRETRIAL,Gminder,John,NULL,Male,Caucasian,10/28/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +24542,73758,66831,PRETRIAL,Gminder,John,NULL,Male,Caucasian,10/28/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +24542,73758,66831,PRETRIAL,Gminder,John,NULL,Male,Caucasian,10/28/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +28707,30388,27754,Probation,Green,James,NULL,Male,African-American,08/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,6/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +28707,30388,27754,Probation,Green,James,NULL,Male,African-American,08/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,6/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +28707,30388,27754,Probation,Green,James,NULL,Male,African-American,08/11/78,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Single,6/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +63916,73772,66844,Probation,Costa,Mitchel,NULL,Male,Caucasian,01/28/55,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/3/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +63916,73772,66844,Probation,Costa,Mitchel,NULL,Male,Caucasian,01/28/55,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/3/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +63916,73772,66844,Probation,Costa,Mitchel,NULL,Male,Caucasian,01/28/55,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63924,73779,66851,Probation,Baum,Gregory,NULL,Male,Caucasian,01/04/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/3/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +63924,73779,66851,Probation,Baum,Gregory,NULL,Male,Caucasian,01/04/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/3/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +63924,73779,66851,Probation,Baum,Gregory,NULL,Male,Caucasian,01/04/68,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +32581,73751,66824,PRETRIAL,BROWN,TONY,NULL,Male,African-American,11/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +32581,73751,66824,PRETRIAL,BROWN,TONY,NULL,Male,African-American,11/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +32581,73751,66824,PRETRIAL,BROWN,TONY,NULL,Male,African-American,11/24/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63905,73760,66833,Probation,WHITE,AARON,M,Male,Caucasian,11/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/3/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +63905,73760,66833,Probation,WHITE,AARON,M,Male,Caucasian,11/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/3/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +63905,73760,66833,Probation,WHITE,AARON,M,Male,Caucasian,11/15/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58287,73777,66849,PRETRIAL,Reinosolopez,Franklin,NULL,Male,Other,02/10/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/3/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +58287,73777,66849,PRETRIAL,Reinosolopez,Franklin,NULL,Male,Other,02/10/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/3/14 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +58287,73777,66849,PRETRIAL,Reinosolopez,Franklin,NULL,Male,Other,02/10/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63902,73756,66829,PRETRIAL,Paret,Yvette,NULL,Female,Caucasian,05/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/3/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +63902,73756,66829,PRETRIAL,Paret,Yvette,NULL,Female,Caucasian,05/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/3/14 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +63902,73756,66829,PRETRIAL,Paret,Yvette,NULL,Female,Caucasian,05/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63908,73763,66836,Probation,Henrickson,Lori,NULL,Female,Caucasian,05/06/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +63908,73763,66836,Probation,Henrickson,Lori,NULL,Female,Caucasian,05/06/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +63908,73763,66836,Probation,Henrickson,Lori,NULL,Female,Caucasian,05/06/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63926,73781,66853,Probation,Lara,Erick,NULL,Male,Hispanic,04/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +63926,73781,66853,Probation,Lara,Erick,NULL,Male,Hispanic,04/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +63926,73781,66853,Probation,Lara,Erick,NULL,Male,Hispanic,04/16/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63911,73766,66839,PRETRIAL,Nardo,Daniel,Joseph,Male,Caucasian,09/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +63911,73766,66839,PRETRIAL,Nardo,Daniel,Joseph,Male,Caucasian,09/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +63911,73766,66839,PRETRIAL,Nardo,Daniel,Joseph,Male,Caucasian,09/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63900,73753,66826,PRETRIAL,Durva,Jamesly,NULL,Male,African-American,03/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +63900,73753,66826,PRETRIAL,Durva,Jamesly,NULL,Male,African-American,03/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +63900,73753,66826,PRETRIAL,Durva,Jamesly,NULL,Male,African-American,03/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63918,73774,66846,PRETRIAL,PICHARDO,RAFAEL,NULL,Male,Hispanic,01/24/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,1,Low,7,Risk of Violence,-4.29,1,Low,New,1,0 +63918,73774,66846,PRETRIAL,PICHARDO,RAFAEL,NULL,Male,Hispanic,01/24/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,1,Low,8,Risk of Recidivism,-2.69,1,Low,New,1,0 +63918,73774,66846,PRETRIAL,PICHARDO,RAFAEL,NULL,Male,Hispanic,01/24/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63895,73745,66818,PRETRIAL,HAMMOND,VIOLET,R,Female,African-American,10/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +63895,73745,66818,PRETRIAL,HAMMOND,VIOLET,R,Female,African-American,10/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +63895,73745,66818,PRETRIAL,HAMMOND,VIOLET,R,Female,African-American,10/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63897,73748,66821,PRETRIAL,Arroyo-Rodriguez,Jose,NULL,Male,Hispanic,02/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.16,8,High,New,1,0 +63897,73748,66821,PRETRIAL,Arroyo-Rodriguez,Jose,NULL,Male,Hispanic,02/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +63897,73748,66821,PRETRIAL,Arroyo-Rodriguez,Jose,NULL,Male,Hispanic,02/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63928,73782,66854,Probation,palmer,timothy,NULL,Male,Caucasian,03/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +63928,73782,66854,Probation,palmer,timothy,NULL,Male,Caucasian,03/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +63928,73782,66854,Probation,palmer,timothy,NULL,Male,Caucasian,03/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63929,73784,66856,PRETRIAL,GOVEA,RICARDO,NULL,Male,Hispanic,06/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/14 0:00,4,High,7,Risk of Violence,-1.05,8,High,New,1,0 +63929,73784,66856,PRETRIAL,GOVEA,RICARDO,NULL,Male,Hispanic,06/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/14 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +63929,73784,66856,PRETRIAL,GOVEA,RICARDO,NULL,Male,Hispanic,06/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/3/14 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +63906,73761,66834,Probation,Rogers,Tameka,NULL,Female,African-American,07/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/3/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +63906,73761,66834,Probation,Rogers,Tameka,NULL,Female,African-American,07/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/3/14 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +63906,73761,66834,Probation,Rogers,Tameka,NULL,Female,African-American,07/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +63922,73776,66848,Probation,Major,urekas,NULL,Female,African-American,10/04/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +63922,73776,66848,Probation,Major,urekas,NULL,Female,African-American,10/04/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +63922,73776,66848,Probation,Major,urekas,NULL,Female,African-American,10/04/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/3/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63934,73790,66862,PRETRIAL,ROGERS,BRYANT,BRANDON,Male,African-American,10/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +63934,73790,66862,PRETRIAL,ROGERS,BRYANT,BRANDON,Male,African-American,10/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +63934,73790,66862,PRETRIAL,ROGERS,BRYANT,BRANDON,Male,African-American,10/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +18100,73797,66867,PRETRIAL,CRESPO,FREDDY,ANTONIO,Male,African-American,11/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +18100,73797,66867,PRETRIAL,CRESPO,FREDDY,ANTONIO,Male,African-American,11/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,4,High,8,Risk of Recidivism,0.44,9,High,New,1,0 +18100,73797,66867,PRETRIAL,CRESPO,FREDDY,ANTONIO,Male,African-American,11/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +56729,73811,66878,PRETRIAL,CREIGHTNEY,MICHAEL,GARTH,Male,African-American,05/08/92,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,6/4/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +56729,73811,66878,PRETRIAL,CREIGHTNEY,MICHAEL,GARTH,Male,African-American,05/08/92,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,6/4/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +56729,73811,66878,PRETRIAL,CREIGHTNEY,MICHAEL,GARTH,Male,African-American,05/08/92,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,6/4/14 0:00,2,Medium,18,Risk of Failure to Appear,22,4,Low,New,1,0 +63942,73803,66872,PRETRIAL,VALDES-PEREZ,OSIEL,NULL,Male,Hispanic,12/04/93,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +63942,73803,66872,PRETRIAL,VALDES-PEREZ,OSIEL,NULL,Male,Hispanic,12/04/93,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +63942,73803,66872,PRETRIAL,VALDES-PEREZ,OSIEL,NULL,Male,Hispanic,12/04/93,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63946,73805,66874,Probation,ALLENDE,JULIO,A,Male,Hispanic,11/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/14 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +63946,73805,66874,Probation,ALLENDE,JULIO,A,Male,Hispanic,11/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/14 0:00,4,High,8,Risk of Recidivism,0.79,10,High,New,1,0 +63946,73805,66874,Probation,ALLENDE,JULIO,A,Male,Hispanic,11/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63937,73795,66865,PRETRIAL,Hart,Marijah,NULL,Female,African-American,07/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +63937,73795,66865,PRETRIAL,Hart,Marijah,NULL,Female,African-American,07/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +63937,73795,66865,PRETRIAL,Hart,Marijah,NULL,Female,African-American,07/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63948,73813,66880,PRETRIAL,williams,danielle,NULL,Male,African-American,12/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +63948,73813,66880,PRETRIAL,williams,danielle,NULL,Male,African-American,12/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +63948,73813,66880,PRETRIAL,williams,danielle,NULL,Male,African-American,12/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63931,73787,66859,PRETRIAL,COOPRIDER,WILLIAM,DWAYNE,Male,Caucasian,12/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +63931,73787,66859,PRETRIAL,COOPRIDER,WILLIAM,DWAYNE,Male,Caucasian,12/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +63931,73787,66859,PRETRIAL,COOPRIDER,WILLIAM,DWAYNE,Male,Caucasian,12/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63956,73821,66885,Probation,Zevallos,Luis,NULL,Male,Hispanic,11/28/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +63956,73821,66885,Probation,Zevallos,Luis,NULL,Male,Hispanic,11/28/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +63956,73821,66885,Probation,Zevallos,Luis,NULL,Male,Hispanic,11/28/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63941,73800,66870,Probation,Fagan,Matthew,NULL,Male,Caucasian,10/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.71,2,Low,New,1,0 +63941,73800,66870,Probation,Fagan,Matthew,NULL,Male,Caucasian,10/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +63941,73800,66870,Probation,Fagan,Matthew,NULL,Male,Caucasian,10/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +61944,73802,64559,PRETRIAL,BYNUM,RICKY,NULL,Male,African-American,05/22/85,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/14 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +61944,73802,64559,PRETRIAL,BYNUM,RICKY,NULL,Male,African-American,05/22/85,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/14 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +61944,73802,64559,PRETRIAL,BYNUM,RICKY,NULL,Male,African-American,05/22/85,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/14 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +63939,73798,66868,Probation,young,Joseph,john,Male,Caucasian,06/14/60,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,6/4/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +63939,73798,66868,Probation,young,Joseph,john,Male,Caucasian,06/14/60,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,6/4/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +63939,73798,66868,Probation,young,Joseph,john,Male,Caucasian,06/14/60,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58312,73819,60533,PRETRIAL,Lalanne,Ronald,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,7,Risk of Violence,-2.49,3,Low,Copy,1,0 +58312,73819,60533,PRETRIAL,Lalanne,Ronald,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,Copy,1,0 +58312,73819,60533,PRETRIAL,Lalanne,Ronald,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +63958,73823,66887,Probation,Avolio,Christopher,NULL,Male,Hispanic,05/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/14 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +63958,73823,66887,Probation,Avolio,Christopher,NULL,Male,Hispanic,05/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +63958,73823,66887,Probation,Avolio,Christopher,NULL,Male,Hispanic,05/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/4/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63930,73786,66858,PRETRIAL,Scollon,Marlene,NULL,Female,Hispanic,03/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/4/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +63930,73786,66858,PRETRIAL,Scollon,Marlene,NULL,Female,Hispanic,03/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/4/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +63930,73786,66858,PRETRIAL,Scollon,Marlene,NULL,Female,Hispanic,03/03/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63936,73793,66864,PRETRIAL,Garcia,Christian,NULL,Male,Caucasian,01/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +63936,73793,66864,PRETRIAL,Garcia,Christian,NULL,Male,Caucasian,01/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +63936,73793,66864,PRETRIAL,Garcia,Christian,NULL,Male,Caucasian,01/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62540,73807,65258,Probation,simpson,alexander,NULL,Male,Caucasian,12/07/45,17,All Scales,Intake,English,Post Sentence,Probation,Married,6/4/14 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +62540,73807,65258,Probation,simpson,alexander,NULL,Male,Caucasian,12/07/45,17,All Scales,Intake,English,Post Sentence,Probation,Married,6/4/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +62540,73807,65258,Probation,simpson,alexander,NULL,Male,Caucasian,12/07/45,17,All Scales,Intake,English,Post Sentence,Probation,Married,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54897,73816,66882,PRETRIAL,JAMISON,PHILIP,NULL,Male,Caucasian,01/19/61,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/4/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +54897,73816,66882,PRETRIAL,JAMISON,PHILIP,NULL,Male,Caucasian,01/19/61,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/4/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +54897,73816,66882,PRETRIAL,JAMISON,PHILIP,NULL,Male,Caucasian,01/19/61,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63950,73814,66881,PRETRIAL,Mendez,Xavier,NULL,Male,Caucasian,08/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +63950,73814,66881,PRETRIAL,Mendez,Xavier,NULL,Male,Caucasian,08/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +63950,73814,66881,PRETRIAL,Mendez,Xavier,NULL,Male,Caucasian,08/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59640,73785,66857,PRETRIAL,Torres,Christian,NULL,Male,Caucasian,10/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +59640,73785,66857,PRETRIAL,Torres,Christian,NULL,Male,Caucasian,10/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +59640,73785,66857,PRETRIAL,Torres,Christian,NULL,Male,Caucasian,10/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63933,73789,66861,PRETRIAL,Clark,Jarmal,Antonio,Male,African-American,07/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +63933,73789,66861,PRETRIAL,Clark,Jarmal,Antonio,Male,African-American,07/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +63933,73789,66861,PRETRIAL,Clark,Jarmal,Antonio,Male,African-American,07/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +13400,73794,12809,PRETRIAL,FRAZIER,FABIAN,D,Male,African-American,07/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,Copy,1,0 +13400,73794,12809,PRETRIAL,FRAZIER,FABIAN,D,Male,African-American,07/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,Copy,1,0 +13400,73794,12809,PRETRIAL,FRAZIER,FABIAN,D,Male,African-American,07/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +63959,73824,66888,PRETRIAL,ROBBIO,LINDA,NULL,Female,Caucasian,02/17/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +63959,73824,66888,PRETRIAL,ROBBIO,LINDA,NULL,Female,Caucasian,02/17/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +63959,73824,66888,PRETRIAL,ROBBIO,LINDA,NULL,Female,Caucasian,02/17/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,29,9,High,New,1,0 +63945,73806,66875,PRETRIAL,Berson,Michael,Joseph,Male,Caucasian,06/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/14 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +63945,73806,66875,PRETRIAL,Berson,Michael,Joseph,Male,Caucasian,06/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +63945,73806,66875,PRETRIAL,Berson,Michael,Joseph,Male,Caucasian,06/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/4/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63955,73820,66884,PRETRIAL,FORBES,SHAVORN,NULL,Male,African-American,12/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +63955,73820,66884,PRETRIAL,FORBES,SHAVORN,NULL,Male,African-American,12/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +63955,73820,66884,PRETRIAL,FORBES,SHAVORN,NULL,Male,African-American,12/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63940,73799,66869,Probation,Hicks,Alicia,Darlene,Female,African-American,12/29/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/4/14 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +63940,73799,66869,Probation,Hicks,Alicia,Darlene,Female,African-American,12/29/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +63940,73799,66869,Probation,Hicks,Alicia,Darlene,Female,African-American,12/29/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/4/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63943,73801,66871,Probation,ortiz,Vladimir,NULL,Male,Hispanic,05/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +63943,73801,66871,Probation,ortiz,Vladimir,NULL,Male,Hispanic,05/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +63943,73801,66871,Probation,ortiz,Vladimir,NULL,Male,Hispanic,05/22/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63957,73822,66886,Probation,BONGIORNO,LEONARDO,NULL,Male,Caucasian,04/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/4/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +63957,73822,66886,Probation,BONGIORNO,LEONARDO,NULL,Male,Caucasian,04/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/4/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +63957,73822,66886,Probation,BONGIORNO,LEONARDO,NULL,Male,Caucasian,04/10/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63944,73804,66873,PRETRIAL,Vilsaint,Charles,NULL,Male,African-American,06/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +63944,73804,66873,PRETRIAL,Vilsaint,Charles,NULL,Male,African-American,06/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +63944,73804,66873,PRETRIAL,Vilsaint,Charles,NULL,Male,African-American,06/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63949,73812,66879,PRETRIAL,Henderson,Samantha,NULL,Female,Caucasian,12/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +63949,73812,66879,PRETRIAL,Henderson,Samantha,NULL,Female,Caucasian,12/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +63949,73812,66879,PRETRIAL,Henderson,Samantha,NULL,Female,Caucasian,12/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63932,73788,66860,PRETRIAL,Flaiani,Frank,NULL,Male,Caucasian,04/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +63932,73788,66860,PRETRIAL,Flaiani,Frank,NULL,Male,Caucasian,04/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +63932,73788,66860,PRETRIAL,Flaiani,Frank,NULL,Male,Caucasian,04/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58312,66750,60533,PRETRIAL,Lalanne,Ronald,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +58312,66750,60533,PRETRIAL,Lalanne,Ronald,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +58312,66750,60533,PRETRIAL,Lalanne,Ronald,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63932,73791,66860,PRETRIAL,Flaiani,Frank,NULL,Male,Caucasian,04/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,Copy,1,0 +63932,73791,66860,PRETRIAL,Flaiani,Frank,NULL,Male,Caucasian,04/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,Copy,1,0 +63932,73791,66860,PRETRIAL,Flaiani,Frank,NULL,Male,Caucasian,04/02/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +63947,73809,66877,Probation,Brantley,Robert,Lee,Male,African-American,06/26/89,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/4/14 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +63947,73809,66877,Probation,Brantley,Robert,Lee,Male,African-American,06/26/89,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +63947,73809,66877,Probation,Brantley,Robert,Lee,Male,African-American,06/26/89,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/4/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63954,73817,66883,PRETRIAL,SUAREZRAMIREZ,LEONOR,NULL,Female,Caucasian,01/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +63954,73817,66883,PRETRIAL,SUAREZRAMIREZ,LEONOR,NULL,Female,Caucasian,01/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +63954,73817,66883,PRETRIAL,SUAREZRAMIREZ,LEONOR,NULL,Female,Caucasian,01/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63938,73796,66866,PRETRIAL,Shoultz,Leonard,Junior,Male,African-American,02/22/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.83,2,Low,New,1,0 +63938,73796,66866,PRETRIAL,Shoultz,Leonard,Junior,Male,African-American,02/22/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +63938,73796,66866,PRETRIAL,Shoultz,Leonard,Junior,Male,African-American,02/22/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +63968,73830,66894,PRETRIAL,Haynes,Raymond,NULL,Male,African-American,12/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +63968,73830,66894,PRETRIAL,Haynes,Raymond,NULL,Male,African-American,12/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +63968,73830,66894,PRETRIAL,Haynes,Raymond,NULL,Male,African-American,12/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63972,73838,66899,PRETRIAL,SIROTKIN,STEPHANIE,NULL,Female,Caucasian,01/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +63972,73838,66899,PRETRIAL,SIROTKIN,STEPHANIE,NULL,Female,Caucasian,01/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,9,High,New,1,0 +63972,73838,66899,PRETRIAL,SIROTKIN,STEPHANIE,NULL,Female,Caucasian,01/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63977,73846,66907,PRETRIAL,Vargasmedina,Jean,Carlos,Male,Hispanic,05/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +63977,73846,66907,PRETRIAL,Vargasmedina,Jean,Carlos,Male,Hispanic,05/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +63977,73846,66907,PRETRIAL,Vargasmedina,Jean,Carlos,Male,Hispanic,05/16/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63979,73848,66909,Probation,Lumsdon,Jessica,lorriane,Female,African-American,11/30/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.45,3,Low,New,1,0 +63979,73848,66909,Probation,Lumsdon,Jessica,lorriane,Female,African-American,11/30/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,9,High,New,1,0 +63979,73848,66909,Probation,Lumsdon,Jessica,lorriane,Female,African-American,11/30/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63969,73833,66896,PRETRIAL,PEREZ,MANUEL,NULL,Male,Hispanic,06/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +63969,73833,66896,PRETRIAL,PEREZ,MANUEL,NULL,Male,Hispanic,06/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +63969,73833,66896,PRETRIAL,PEREZ,MANUEL,NULL,Male,Hispanic,06/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63962,73825,66889,PRETRIAL,Pena,Magdiel,Alejandro,Male,Caucasian,09/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +63962,73825,66889,PRETRIAL,Pena,Magdiel,Alejandro,Male,Caucasian,09/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +63962,73825,66889,PRETRIAL,Pena,Magdiel,Alejandro,Male,Caucasian,09/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54605,73840,66901,PRETRIAL,BAILEY,RICKIE,NULL,Male,Caucasian,04/08/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,6/5/14 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +54605,73840,66901,PRETRIAL,BAILEY,RICKIE,NULL,Male,Caucasian,04/08/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,6/5/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +54605,73840,66901,PRETRIAL,BAILEY,RICKIE,NULL,Male,Caucasian,04/08/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63967,73829,66893,PRETRIAL,Cochrane,Sterling,Reed,Male,Caucasian,09/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +63967,73829,66893,PRETRIAL,Cochrane,Sterling,Reed,Male,Caucasian,09/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +63967,73829,66893,PRETRIAL,Cochrane,Sterling,Reed,Male,Caucasian,09/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +14221,73843,66904,PRETRIAL,ROBERTS,HENRY,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/5/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +14221,73843,66904,PRETRIAL,ROBERTS,HENRY,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/5/14 0:00,4,High,8,Risk of Recidivism,0.16,8,High,New,1,0 +14221,73843,66904,PRETRIAL,ROBERTS,HENRY,NULL,Male,African-American,10/24/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/5/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +63980,73850,66911,Probation,Toledo,Justin,NULL,Male,Caucasian,03/17/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +63980,73850,66911,Probation,Toledo,Justin,NULL,Male,Caucasian,03/17/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +63980,73850,66911,Probation,Toledo,Justin,NULL,Male,Caucasian,03/17/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +30798,73831,29783,PRETRIAL,Altidor,Jacques,Michel,Male,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,4,High,7,Risk of Violence,-0.81,9,High,Copy,1,0 +30798,73831,29783,PRETRIAL,Altidor,Jacques,Michel,Male,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,4,High,8,Risk of Recidivism,0.83,10,High,Copy,1,0 +30798,73831,29783,PRETRIAL,Altidor,Jacques,Michel,Male,African-American,01/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +63976,73845,66906,Probation,morgan,keith,NULL,Male,Caucasian,07/25/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +63976,73845,66906,Probation,morgan,keith,NULL,Male,Caucasian,07/25/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +63976,73845,66906,Probation,morgan,keith,NULL,Male,Caucasian,07/25/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63965,73827,66891,PRETRIAL,Pereira,Miriam,NULL,Female,Hispanic,06/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +63965,73827,66891,PRETRIAL,Pereira,Miriam,NULL,Female,Hispanic,06/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +63965,73827,66891,PRETRIAL,Pereira,Miriam,NULL,Female,Hispanic,06/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +53307,73841,66902,PRETRIAL,Ramsey,Mark,Anthony,Male,African-American,02/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +53307,73841,66902,PRETRIAL,Ramsey,Mark,Anthony,Male,African-American,02/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +53307,73841,66902,PRETRIAL,Ramsey,Mark,Anthony,Male,African-American,02/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63731,73837,66650,PRETRIAL,Awan,Kyle,NULL,Male,Native American,10/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,Copy,1,0 +63731,73837,66650,PRETRIAL,Awan,Kyle,NULL,Male,Native American,10/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,Copy,1,0 +63731,73837,66650,PRETRIAL,Awan,Kyle,NULL,Male,Native American,10/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +63975,73844,66905,Probation,Ecchio,Michael,NULL,Male,Caucasian,05/09/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +63975,73844,66905,Probation,Ecchio,Michael,NULL,Male,Caucasian,05/09/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +63975,73844,66905,Probation,Ecchio,Michael,NULL,Male,Caucasian,05/09/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63966,73828,66892,PRETRIAL,Stanley,John,Tavers,Male,African-American,07/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/5/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +63966,73828,66892,PRETRIAL,Stanley,John,Tavers,Male,African-American,07/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +63966,73828,66892,PRETRIAL,Stanley,John,Tavers,Male,African-American,07/31/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/5/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63964,73832,66895,PRETRIAL,Tate,Tashay,Tasheka,Female,Other,05/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/5/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +63964,73832,66895,PRETRIAL,Tate,Tashay,Tasheka,Female,Other,05/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/5/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +63964,73832,66895,PRETRIAL,Tate,Tashay,Tasheka,Female,Other,05/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63970,73834,66897,PRETRIAL,Spivey- Carter,April,NULL,Female,Caucasian,04/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +63970,73834,66897,PRETRIAL,Spivey- Carter,April,NULL,Female,Caucasian,04/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +63970,73834,66897,PRETRIAL,Spivey- Carter,April,NULL,Female,Caucasian,04/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63974,73842,66903,Probation,Morgan,Romeish,NULL,Male,African-American,12/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +63974,73842,66903,Probation,Morgan,Romeish,NULL,Male,African-American,12/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +63974,73842,66903,Probation,Morgan,Romeish,NULL,Male,African-American,12/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63978,73847,66908,Probation,bencosme,arlington,NULL,Male,Hispanic,09/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/5/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +63978,73847,66908,Probation,bencosme,arlington,NULL,Male,Hispanic,09/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/5/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +63978,73847,66908,Probation,bencosme,arlington,NULL,Male,Hispanic,09/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63960,73826,66890,PRETRIAL,PIERRELOUIS,JEAN,CARLOS,Male,African-American,11/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +63960,73826,66890,PRETRIAL,PIERRELOUIS,JEAN,CARLOS,Male,African-American,11/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +63960,73826,66890,PRETRIAL,PIERRELOUIS,JEAN,CARLOS,Male,African-American,11/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/5/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64004,73884,66944,Broward County,Lallemand,Waltley,NULL,Male,African-American,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +64004,73884,66944,Broward County,Lallemand,Waltley,NULL,Male,African-American,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +64004,73884,66944,Broward County,Lallemand,Waltley,NULL,Male,African-American,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63987,73860,66920,PRETRIAL,Price,Brooke,NULL,Male,African-American,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +63987,73860,66920,PRETRIAL,Price,Brooke,NULL,Male,African-American,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +63987,73860,66920,PRETRIAL,Price,Brooke,NULL,Male,African-American,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63991,73863,66923,PRETRIAL,Sanders,Willie,NULL,Male,African-American,08/28/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +63991,73863,66923,PRETRIAL,Sanders,Willie,NULL,Male,African-American,08/28/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +63991,73863,66923,PRETRIAL,Sanders,Willie,NULL,Male,African-American,08/28/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +45154,73881,66941,PRETRIAL,Darman,David,NULL,Male,Caucasian,01/06/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +45154,73881,66941,PRETRIAL,Darman,David,NULL,Male,Caucasian,01/06/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +45154,73881,66941,PRETRIAL,Darman,David,NULL,Male,Caucasian,01/06/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63995,73868,66928,Probation,LANG,JASON,ALLEN,Male,Caucasian,06/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +63995,73868,66928,Probation,LANG,JASON,ALLEN,Male,Caucasian,06/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +63995,73868,66928,Probation,LANG,JASON,ALLEN,Male,Caucasian,06/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +63984,73855,66915,PRETRIAL,Vaughn,Merville,NULL,Male,African-American,12/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,Copy,1,0 +63984,73855,66915,PRETRIAL,Vaughn,Merville,NULL,Male,African-American,12/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,Copy,1,0 +63984,73855,66915,PRETRIAL,Vaughn,Merville,NULL,Male,African-American,12/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +64007,73889,66948,PRETRIAL,Lange,Brian,NULL,Male,Caucasian,08/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +64007,73889,66948,PRETRIAL,Lange,Brian,NULL,Male,Caucasian,08/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +64007,73889,66948,PRETRIAL,Lange,Brian,NULL,Male,Caucasian,08/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63983,73853,66914,PRETRIAL,Monerrojas,Roberto,NULL,Male,Hispanic,04/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +63983,73853,66914,PRETRIAL,Monerrojas,Roberto,NULL,Male,Hispanic,04/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +63983,73853,66914,PRETRIAL,Monerrojas,Roberto,NULL,Male,Hispanic,04/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63997,73870,66930,Probation,docio,magali,NULL,Female,Caucasian,01/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,2,Medium,7,Risk of Violence,-2.27,3,Low,New,1,0 +63997,73870,66930,Probation,docio,magali,NULL,Female,Caucasian,01/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,7,Medium,New,1,0 +63997,73870,66930,Probation,docio,magali,NULL,Female,Caucasian,01/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64006,73888,66947,PRETRIAL,Torres,Luis,NULL,Male,Hispanic,03/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/6/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +64006,73888,66947,PRETRIAL,Torres,Luis,NULL,Male,Hispanic,03/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/6/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +64006,73888,66947,PRETRIAL,Torres,Luis,NULL,Male,Hispanic,03/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +31052,62038,56300,PRETRIAL,JACKSON,TEVON,DONTE,Male,African-American,12/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/14 0:00,4,High,7,Risk of Violence,-0.49,10,High,New,1,0 +31052,62038,56300,PRETRIAL,JACKSON,TEVON,DONTE,Male,African-American,12/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/14 0:00,4,High,8,Risk of Recidivism,0.66,10,High,New,1,0 +31052,62038,56300,PRETRIAL,JACKSON,TEVON,DONTE,Male,African-American,12/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +63999,73874,66934,PRETRIAL,tucker,george,NULL,Male,African-American,12/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +63999,73874,66934,PRETRIAL,tucker,george,NULL,Male,African-American,12/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +63999,73874,66934,PRETRIAL,tucker,george,NULL,Male,African-American,12/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63985,73858,66918,PRETRIAL,Delgado,Vincente,Martin,Male,Hispanic,07/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +63985,73858,66918,PRETRIAL,Delgado,Vincente,Martin,Male,Hispanic,07/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +63985,73858,66918,PRETRIAL,Delgado,Vincente,Martin,Male,Hispanic,07/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63998,73872,66932,PRETRIAL,Johnson,Daniel,NULL,Male,Caucasian,11/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,6/6/14 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +63998,73872,66932,PRETRIAL,Johnson,Daniel,NULL,Male,Caucasian,11/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,6/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +63998,73872,66932,PRETRIAL,Johnson,Daniel,NULL,Male,Caucasian,11/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,6/6/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +26310,73886,25417,PRETRIAL,BEARD,TRAMAINE,NULL,Male,African-American,08/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,Copy,1,0 +26310,73886,25417,PRETRIAL,BEARD,TRAMAINE,NULL,Male,African-American,08/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,Copy,1,0 +26310,73886,25417,PRETRIAL,BEARD,TRAMAINE,NULL,Male,African-American,08/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +63992,73865,66925,PRETRIAL,Holder,Petula,NULL,Female,Other,09/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +63992,73865,66925,PRETRIAL,Holder,Petula,NULL,Female,Other,09/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +63992,73865,66925,PRETRIAL,Holder,Petula,NULL,Female,Other,09/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +63989,73862,66922,PRETRIAL,Ambrose,Charlton,NULL,Male,African-American,09/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +63989,73862,66922,PRETRIAL,Ambrose,Charlton,NULL,Male,African-American,09/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +63989,73862,66922,PRETRIAL,Ambrose,Charlton,NULL,Male,African-American,09/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63993,73866,66926,Probation,ALANIZ,anthony,NULL,Male,Hispanic,02/21/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +63993,73866,66926,Probation,ALANIZ,anthony,NULL,Male,Hispanic,02/21/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +63993,73866,66926,Probation,ALANIZ,anthony,NULL,Male,Hispanic,02/21/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,4,High,18,Risk of Failure to Appear,40,10,High,New,1,0 +6394,73883,66943,PRETRIAL,RASPBERRY,RICHARD,LEON,Male,African-American,07/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +6394,73883,66943,PRETRIAL,RASPBERRY,RICHARD,LEON,Male,African-American,07/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +6394,73883,66943,PRETRIAL,RASPBERRY,RICHARD,LEON,Male,African-American,07/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63982,73852,66913,PRETRIAL,Sigona,Joseph,NULL,Male,Caucasian,09/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +63982,73852,66913,PRETRIAL,Sigona,Joseph,NULL,Male,Caucasian,09/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +63982,73852,66913,PRETRIAL,Sigona,Joseph,NULL,Male,Caucasian,09/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50157,73871,66931,PRETRIAL,LABOY,ADALBERTO,NULL,Male,Caucasian,10/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +50157,73871,66931,PRETRIAL,LABOY,ADALBERTO,NULL,Male,Caucasian,10/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +50157,73871,66931,PRETRIAL,LABOY,ADALBERTO,NULL,Male,Caucasian,10/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +20243,73873,66933,Probation,levy,zachary,NULL,Male,Caucasian,05/14/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.25,3,Low,New,1,0 +20243,73873,66933,Probation,levy,zachary,NULL,Male,Caucasian,05/14/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +20243,73873,66933,Probation,levy,zachary,NULL,Male,Caucasian,05/14/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64002,73878,66938,Probation,Reagan,Michael,NULL,Male,Caucasian,08/21/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +64002,73878,66938,Probation,Reagan,Michael,NULL,Male,Caucasian,08/21/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +64002,73878,66938,Probation,Reagan,Michael,NULL,Male,Caucasian,08/21/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +61272,73857,66917,PRETRIAL,GUZMANSILVA,JESUS,J,Male,Caucasian,12/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/6/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +61272,73857,66917,PRETRIAL,GUZMANSILVA,JESUS,J,Male,Caucasian,12/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/6/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +61272,73857,66917,PRETRIAL,GUZMANSILVA,JESUS,J,Male,Caucasian,12/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64000,73875,66935,Probation,Saucier,Kerry,NULL,Female,Caucasian,10/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +64000,73875,66935,Probation,Saucier,Kerry,NULL,Female,Caucasian,10/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +64000,73875,66935,Probation,Saucier,Kerry,NULL,Female,Caucasian,10/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63984,73854,66915,PRETRIAL,Vaughn,Merville,NULL,Male,African-American,12/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +63984,73854,66915,PRETRIAL,Vaughn,Merville,NULL,Male,African-American,12/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +63984,73854,66915,PRETRIAL,Vaughn,Merville,NULL,Male,African-American,12/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63988,73861,66921,PRETRIAL,Davis,Kwamayne,NULL,Male,African-American,10/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +63988,73861,66921,PRETRIAL,Davis,Kwamayne,NULL,Male,African-American,10/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +63988,73861,66921,PRETRIAL,Davis,Kwamayne,NULL,Male,African-American,10/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63994,73867,66927,PRETRIAL,Unguru,Marius,NULL,Male,Caucasian,12/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/6/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +63994,73867,66927,PRETRIAL,Unguru,Marius,NULL,Male,Caucasian,12/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/6/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +63994,73867,66927,PRETRIAL,Unguru,Marius,NULL,Male,Caucasian,12/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63996,73869,66929,Probation,Nicole-Carter,Christina,NULL,Female,Caucasian,11/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/6/14 0:00,4,High,7,Risk of Violence,-0.56,10,High,New,1,0 +63996,73869,66929,Probation,Nicole-Carter,Christina,NULL,Female,Caucasian,11/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/6/14 0:00,4,High,8,Risk of Recidivism,1.52,10,High,New,1,0 +63996,73869,66929,Probation,Nicole-Carter,Christina,NULL,Female,Caucasian,11/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/6/14 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +36606,73882,66942,PRETRIAL,Straussberger,Melaine,NULL,Female,Caucasian,12/22/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +36606,73882,66942,PRETRIAL,Straussberger,Melaine,NULL,Female,Caucasian,12/22/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +36606,73882,66942,PRETRIAL,Straussberger,Melaine,NULL,Female,Caucasian,12/22/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +7953,73856,66916,PRETRIAL,RODRIUEZ,DANIEL,NULL,Male,Hispanic,03/28/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +7953,73856,66916,PRETRIAL,RODRIUEZ,DANIEL,NULL,Male,Hispanic,03/28/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +7953,73856,66916,PRETRIAL,RODRIUEZ,DANIEL,NULL,Male,Hispanic,03/28/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63986,73859,66919,PRETRIAL,Fonseca,Aida,NULL,Male,Hispanic,03/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +63986,73859,66919,PRETRIAL,Fonseca,Aida,NULL,Male,Hispanic,03/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +63986,73859,66919,PRETRIAL,Fonseca,Aida,NULL,Male,Hispanic,03/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58549,73877,66937,PRETRIAL,Watrous,Kevin,Keith,Male,Caucasian,03/22/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/6/14 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +58549,73877,66937,PRETRIAL,Watrous,Kevin,Keith,Male,Caucasian,03/22/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/6/14 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +58549,73877,66937,PRETRIAL,Watrous,Kevin,Keith,Male,Caucasian,03/22/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63990,73864,66924,PRETRIAL,Mabra,Edwin,NULL,Male,African-American,11/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +63990,73864,66924,PRETRIAL,Mabra,Edwin,NULL,Male,African-American,11/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +63990,73864,66924,PRETRIAL,Mabra,Edwin,NULL,Male,African-American,11/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63981,73851,66912,PRETRIAL,Dorvil,Guyvencchi,NULL,Male,African-American,07/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +63981,73851,66912,PRETRIAL,Dorvil,Guyvencchi,NULL,Male,African-American,07/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +63981,73851,66912,PRETRIAL,Dorvil,Guyvencchi,NULL,Male,African-American,07/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/6/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64015,73898,66956,PRETRIAL,Jackson,Royal,NULL,Male,African-American,02/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +64015,73898,66956,PRETRIAL,Jackson,Royal,NULL,Male,African-American,02/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.79,10,High,New,1,0 +64015,73898,66956,PRETRIAL,Jackson,Royal,NULL,Male,African-American,02/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64018,73903,66961,PRETRIAL,Perez,Rafael,NULL,Male,Hispanic,06/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +64018,73903,66961,PRETRIAL,Perez,Rafael,NULL,Male,Hispanic,06/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +64018,73903,66961,PRETRIAL,Perez,Rafael,NULL,Male,Hispanic,06/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64012,73894,66953,PRETRIAL,CONRAD,TYLER,ANDRUS,Male,Caucasian,01/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +64012,73894,66953,PRETRIAL,CONRAD,TYLER,ANDRUS,Male,Caucasian,01/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +64012,73894,66953,PRETRIAL,CONRAD,TYLER,ANDRUS,Male,Caucasian,01/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64016,73899,66957,PRETRIAL,sieber,shayne,garrett,Male,Caucasian,11/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +64016,73899,66957,PRETRIAL,sieber,shayne,garrett,Male,Caucasian,11/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +64016,73899,66957,PRETRIAL,sieber,shayne,garrett,Male,Caucasian,11/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56531,73901,66959,PRETRIAL,REMBERT,WESLEY,CARDELL,Male,African-American,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +56531,73901,66959,PRETRIAL,REMBERT,WESLEY,CARDELL,Male,African-American,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.78,10,High,New,1,0 +56531,73901,66959,PRETRIAL,REMBERT,WESLEY,CARDELL,Male,African-American,03/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64014,73896,66955,PRETRIAL,Ansby,Shanese,NULL,Female,African-American,03/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +64014,73896,66955,PRETRIAL,Ansby,Shanese,NULL,Female,African-American,03/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +64014,73896,66955,PRETRIAL,Ansby,Shanese,NULL,Female,African-American,03/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64010,73892,66951,PRETRIAL,Ramos,Aracelio,NULL,Male,Caucasian,04/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +64010,73892,66951,PRETRIAL,Ramos,Aracelio,NULL,Male,Caucasian,04/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +64010,73892,66951,PRETRIAL,Ramos,Aracelio,NULL,Male,Caucasian,04/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64011,73893,66952,PRETRIAL,THOMPSON,SUZY,NULL,Female,Caucasian,09/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,6/7/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +64011,73893,66952,PRETRIAL,THOMPSON,SUZY,NULL,Female,Caucasian,09/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,6/7/14 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +64011,73893,66952,PRETRIAL,THOMPSON,SUZY,NULL,Female,Caucasian,09/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,6/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64009,73891,66950,PRETRIAL,Brown,Jamye,Lauren,Female,African-American,07/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +64009,73891,66950,PRETRIAL,Brown,Jamye,Lauren,Female,African-American,07/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +64009,73891,66950,PRETRIAL,Brown,Jamye,Lauren,Female,African-American,07/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64013,73895,66954,PRETRIAL,MCFARLANE,JAMAR,NULL,Male,African-American,11/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +64013,73895,66954,PRETRIAL,MCFARLANE,JAMAR,NULL,Male,African-American,11/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +64013,73895,66954,PRETRIAL,MCFARLANE,JAMAR,NULL,Male,African-American,11/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +16946,73900,66958,Probation,Thomas,Telly,NULL,Male,African-American,01/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.36,3,Low,New,1,0 +16946,73900,66958,Probation,Thomas,Telly,NULL,Male,African-American,01/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,New,1,0 +16946,73900,66958,Probation,Thomas,Telly,NULL,Male,African-American,01/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64017,73902,66960,PRETRIAL,Borkowicz,Peter,NULL,Male,Caucasian,07/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/7/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +64017,73902,66960,PRETRIAL,Borkowicz,Peter,NULL,Male,Caucasian,07/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/7/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +64017,73902,66960,PRETRIAL,Borkowicz,Peter,NULL,Male,Caucasian,07/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +44206,73897,54729,PRETRIAL,Singh,Robert,Taylor,Male,African-American,01/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,4,High,7,Risk of Violence,-1.04,8,High,Copy,1,0 +44206,73897,54729,PRETRIAL,Singh,Robert,Taylor,Male,African-American,01/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,4,High,8,Risk of Recidivism,0.18,8,High,Copy,1,0 +44206,73897,54729,PRETRIAL,Singh,Robert,Taylor,Male,African-American,01/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/7/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +64019,73904,66962,PRETRIAL,Homere,Virgilien,NULL,Male,African-American,02/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/7/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +64019,73904,66962,PRETRIAL,Homere,Virgilien,NULL,Male,African-American,02/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/7/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +64019,73904,66962,PRETRIAL,Homere,Virgilien,NULL,Male,African-American,02/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64020,73905,66963,PRETRIAL,JACKSON,LUCILLE,NULL,Female,African-American,07/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.6,2,Low,New,1,0 +64020,73905,66963,PRETRIAL,JACKSON,LUCILLE,NULL,Female,African-American,07/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,8,High,New,1,0 +64020,73905,66963,PRETRIAL,JACKSON,LUCILLE,NULL,Female,African-American,07/21/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64023,73910,66966,PRETRIAL,Taylor,Tiffany,NULL,Female,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,6/8/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +64023,73910,66966,PRETRIAL,Taylor,Tiffany,NULL,Female,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,6/8/14 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +64023,73910,66966,PRETRIAL,Taylor,Tiffany,NULL,Female,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,6/8/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +21165,73909,20344,PRETRIAL,ATEHORTUA,JOSE,NULL,Male,Hispanic,07/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,4,High,7,Risk of Violence,-0.98,9,High,Copy,1,0 +21165,73909,20344,PRETRIAL,ATEHORTUA,JOSE,NULL,Male,Hispanic,07/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,4,High,8,Risk of Recidivism,0.45,9,High,Copy,1,0 +21165,73909,20344,PRETRIAL,ATEHORTUA,JOSE,NULL,Male,Hispanic,07/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +64022,73907,66965,PRETRIAL,Font,Manuel,NULL,Male,Caucasian,12/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +64022,73907,66965,PRETRIAL,Font,Manuel,NULL,Male,Caucasian,12/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +64022,73907,66965,PRETRIAL,Font,Manuel,NULL,Male,Caucasian,12/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +5155,73908,4829,PRETRIAL,Toledo,Eric,NULL,Male,Caucasian,02/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,Copy,1,0 +5155,73908,4829,PRETRIAL,Toledo,Eric,NULL,Male,Caucasian,02/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,10,High,Copy,1,0 +5155,73908,4829,PRETRIAL,Toledo,Eric,NULL,Male,Caucasian,02/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +64021,73906,66964,PRETRIAL,WILLIAMS,ANTHONY,DEVON,Male,African-American,09/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +64021,73906,66964,PRETRIAL,WILLIAMS,ANTHONY,DEVON,Male,African-American,09/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +64021,73906,66964,PRETRIAL,WILLIAMS,ANTHONY,DEVON,Male,African-American,09/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/8/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64035,73924,66979,PRETRIAL,Wojcik,Ronald,NULL,Male,Caucasian,05/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +64035,73924,66979,PRETRIAL,Wojcik,Ronald,NULL,Male,Caucasian,05/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +64035,73924,66979,PRETRIAL,Wojcik,Ronald,NULL,Male,Caucasian,05/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +48868,73927,66981,PRETRIAL,Farhady,Jamil,Jonathan,Male,Caucasian,03/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +48868,73927,66981,PRETRIAL,Farhady,Jamil,Jonathan,Male,Caucasian,03/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +48868,73927,66981,PRETRIAL,Farhady,Jamil,Jonathan,Male,Caucasian,03/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47879,73919,66974,PRETRIAL,James,Ashley,NULL,Male,African-American,05/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +47879,73919,66974,PRETRIAL,James,Ashley,NULL,Male,African-American,05/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +47879,73919,66974,PRETRIAL,James,Ashley,NULL,Male,African-American,05/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51612,73932,56773,PRETRIAL,MOORE,ZACHARY,NULL,Male,Caucasian,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,Copy,1,0 +51612,73932,56773,PRETRIAL,MOORE,ZACHARY,NULL,Male,Caucasian,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,9,High,Copy,1,0 +51612,73932,56773,PRETRIAL,MOORE,ZACHARY,NULL,Male,Caucasian,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +61291,73911,63836,PRETRIAL,BETHEA,JAMES,EARL,Male,African-American,08/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,Copy,1,0 +61291,73911,63836,PRETRIAL,BETHEA,JAMES,EARL,Male,African-American,08/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,Copy,1,0 +61291,73911,63836,PRETRIAL,BETHEA,JAMES,EARL,Male,African-American,08/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +64026,73915,66970,PRETRIAL,ROSALES,KARLA,TOBIAS,Female,Caucasian,10/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/9/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +64026,73915,66970,PRETRIAL,ROSALES,KARLA,TOBIAS,Female,Caucasian,10/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +64026,73915,66970,PRETRIAL,ROSALES,KARLA,TOBIAS,Female,Caucasian,10/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64033,73922,66977,Probation,Hinkley,Jeremy,NULL,Male,Caucasian,07/18/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +64033,73922,66977,Probation,Hinkley,Jeremy,NULL,Male,Caucasian,07/18/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +64033,73922,66977,Probation,Hinkley,Jeremy,NULL,Male,Caucasian,07/18/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64038,73929,66983,Probation,Luciano,Rafael,NULL,Male,Hispanic,07/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +64038,73929,66983,Probation,Luciano,Rafael,NULL,Male,Hispanic,07/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +64038,73929,66983,Probation,Luciano,Rafael,NULL,Male,Hispanic,07/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64025,73913,66968,PRETRIAL,JOHNSON,JOCELYN,ANN,Female,African-American,09/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/9/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +64025,73913,66968,PRETRIAL,JOHNSON,JOCELYN,ANN,Female,African-American,09/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +64025,73913,66968,PRETRIAL,JOHNSON,JOCELYN,ANN,Female,African-American,09/18/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64028,73917,66972,PRETRIAL,Crestoba,Carlos,NULL,Male,Hispanic,11/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/9/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +64028,73917,66972,PRETRIAL,Crestoba,Carlos,NULL,Male,Hispanic,11/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +64028,73917,66972,PRETRIAL,Crestoba,Carlos,NULL,Male,Hispanic,11/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64027,73916,66971,PRETRIAL,Vazquez,Vickki,NULL,Female,African-American,04/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +64027,73916,66971,PRETRIAL,Vazquez,Vickki,NULL,Female,African-American,04/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +64027,73916,66971,PRETRIAL,Vazquez,Vickki,NULL,Female,African-American,04/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +54213,73914,66969,PRETRIAL,MCCARTHY,ADAM,NULL,Male,African-American,10/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +54213,73914,66969,PRETRIAL,MCCARTHY,ADAM,NULL,Male,African-American,10/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +54213,73914,66969,PRETRIAL,MCCARTHY,ADAM,NULL,Male,African-American,10/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64034,73921,66976,PRETRIAL,Castro,Alexander,NULL,Male,Hispanic,03/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/9/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +64034,73921,66976,PRETRIAL,Castro,Alexander,NULL,Male,Hispanic,03/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +64034,73921,66976,PRETRIAL,Castro,Alexander,NULL,Male,Hispanic,03/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64039,73930,66984,Probation,ROSENBERG,SIDENY,NULL,Female,Caucasian,04/19/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/9/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +64039,73930,66984,Probation,ROSENBERG,SIDENY,NULL,Female,Caucasian,04/19/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +64039,73930,66984,Probation,ROSENBERG,SIDENY,NULL,Female,Caucasian,04/19/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64031,73920,66975,Probation,hanley,leravious,NULL,Male,African-American,03/01/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +64031,73920,66975,Probation,hanley,leravious,NULL,Male,African-American,03/01/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +64031,73920,66975,Probation,hanley,leravious,NULL,Male,African-American,03/01/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57706,73923,66978,PRETRIAL,Patterson,Therese,V,Male,Caucasian,08/20/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/9/14 0:00,1,Low,7,Risk of Violence,-4.58,1,Low,New,1,0 +57706,73923,66978,PRETRIAL,Patterson,Therese,V,Male,Caucasian,08/20/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/9/14 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +57706,73923,66978,PRETRIAL,Patterson,Therese,V,Male,Caucasian,08/20/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64037,73928,66982,Probation,LAMY,MANUSHKA,NULL,Female,African-American,09/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +64037,73928,66982,Probation,LAMY,MANUSHKA,NULL,Female,African-American,09/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +64037,73928,66982,Probation,LAMY,MANUSHKA,NULL,Female,African-American,09/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64024,73912,66967,PRETRIAL,Calix,Anselo,NULL,Male,Other,01/10/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/9/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +64024,73912,66967,PRETRIAL,Calix,Anselo,NULL,Male,Other,01/10/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +64024,73912,66967,PRETRIAL,Calix,Anselo,NULL,Male,Other,01/10/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64029,73918,66973,Probation,Campos,Valdinei,NULL,Male,Hispanic,10/26/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +64029,73918,66973,Probation,Campos,Valdinei,NULL,Male,Hispanic,10/26/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +64029,73918,66973,Probation,Campos,Valdinei,NULL,Male,Hispanic,10/26/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64040,73933,66985,PRETRIAL,Alfonso,Roldan,NULL,Male,Hispanic,04/03/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/9/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +64040,73933,66985,PRETRIAL,Alfonso,Roldan,NULL,Male,Hispanic,04/03/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/9/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +64040,73933,66985,PRETRIAL,Alfonso,Roldan,NULL,Male,Hispanic,04/03/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64036,73925,66980,Probation,petithomme,bettinya,NULL,Female,African-American,10/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/9/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +64036,73925,66980,Probation,petithomme,bettinya,NULL,Female,African-American,10/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/9/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +64036,73925,66980,Probation,petithomme,bettinya,NULL,Female,African-American,10/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +30700,73926,48364,PRETRIAL,Abuelhawa,James,NULL,Male,Arabic,02/20/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,Copy,1,0 +30700,73926,48364,PRETRIAL,Abuelhawa,James,NULL,Male,Arabic,02/20/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,Copy,1,0 +30700,73926,48364,PRETRIAL,Abuelhawa,James,NULL,Male,Arabic,02/20/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/9/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +64053,73947,66998,PRETRIAL,funez,giovanni,NULL,Male,Hispanic,05/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +64053,73947,66998,PRETRIAL,funez,giovanni,NULL,Male,Hispanic,05/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +64053,73947,66998,PRETRIAL,funez,giovanni,NULL,Male,Hispanic,05/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64058,73954,67004,PRETRIAL,Pinkney,Dequronda,NULL,Female,African-American,03/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +64058,73954,67004,PRETRIAL,Pinkney,Dequronda,NULL,Female,African-American,03/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +64058,73954,67004,PRETRIAL,Pinkney,Dequronda,NULL,Female,African-American,03/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55926,73967,57848,Probation,abdelgili,ahmed,NULL,Male,Caucasian,12/06/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,Copy,1,0 +55926,73967,57848,Probation,abdelgili,ahmed,NULL,Male,Caucasian,12/06/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,Copy,1,0 +55926,73967,57848,Probation,abdelgili,ahmed,NULL,Male,Caucasian,12/06/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +64045,73939,66990,PRETRIAL,CARLSON,ANDREw,ERIK,Male,Caucasian,08/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +64045,73939,66990,PRETRIAL,CARLSON,ANDREw,ERIK,Male,Caucasian,08/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +64045,73939,66990,PRETRIAL,CARLSON,ANDREw,ERIK,Male,Caucasian,08/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64052,73946,66997,Probation,stuart,kenneth,NULL,Male,Caucasian,06/05/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +64052,73946,66997,Probation,stuart,kenneth,NULL,Male,Caucasian,06/05/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +64052,73946,66997,Probation,stuart,kenneth,NULL,Male,Caucasian,06/05/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64054,73949,66999,PRETRIAL,Filsaime,Wilbert,NULL,Male,African-American,05/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +64054,73949,66999,PRETRIAL,Filsaime,Wilbert,NULL,Male,African-American,05/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +64054,73949,66999,PRETRIAL,Filsaime,Wilbert,NULL,Male,African-American,05/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64047,73941,66992,PRETRIAL,Privott,Adam,D,Male,African-American,10/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/10/14 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +64047,73941,66992,PRETRIAL,Privott,Adam,D,Male,African-American,10/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +64047,73941,66992,PRETRIAL,Privott,Adam,D,Male,African-American,10/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/10/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +64056,73951,67001,Probation,Lofton,Shanae,NULL,Female,African-American,05/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +64056,73951,67001,Probation,Lofton,Shanae,NULL,Female,African-American,05/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +64056,73951,67001,Probation,Lofton,Shanae,NULL,Female,African-American,05/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64048,73942,66993,Probation,Espinoza,Adrian,NULL,Male,Hispanic,09/16/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/10/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +64048,73942,66993,Probation,Espinoza,Adrian,NULL,Male,Hispanic,09/16/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/10/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +64048,73942,66993,Probation,Espinoza,Adrian,NULL,Male,Hispanic,09/16/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64065,73963,67011,PRETRIAL,Malcolm,Donovan,NULL,Male,African-American,05/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/10/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +64065,73963,67011,PRETRIAL,Malcolm,Donovan,NULL,Male,African-American,05/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/10/14 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +64065,73963,67011,PRETRIAL,Malcolm,Donovan,NULL,Male,African-American,05/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +29113,73937,28135,PRETRIAL,FERBIL,WICHI,NULL,Male,Other,07/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,Copy,1,0 +29113,73937,28135,PRETRIAL,FERBIL,WICHI,NULL,Male,Other,07/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,Copy,1,0 +29113,73937,28135,PRETRIAL,FERBIL,WICHI,NULL,Male,Other,07/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +64042,73935,66987,PRETRIAL,Moreno,Eulaida,Antonia,Female,Hispanic,04/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +64042,73935,66987,PRETRIAL,Moreno,Eulaida,Antonia,Female,Hispanic,04/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +64042,73935,66987,PRETRIAL,Moreno,Eulaida,Antonia,Female,Hispanic,04/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64050,73944,66995,Probation,herbert,jonathan,NULL,Male,Caucasian,09/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +64050,73944,66995,Probation,herbert,jonathan,NULL,Male,Caucasian,09/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +64050,73944,66995,Probation,herbert,jonathan,NULL,Male,Caucasian,09/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +64061,73958,67007,Probation,Micheletti,Christopher,NULL,Male,Hispanic,04/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/10/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +64061,73958,67007,Probation,Micheletti,Christopher,NULL,Male,Hispanic,04/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/10/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +64061,73958,67007,Probation,Micheletti,Christopher,NULL,Male,Hispanic,04/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52726,73965,67013,Probation,EVANS,DOMINICK,NULL,Male,Caucasian,02/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +52726,73965,67013,Probation,EVANS,DOMINICK,NULL,Male,Caucasian,02/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +52726,73965,67013,Probation,EVANS,DOMINICK,NULL,Male,Caucasian,02/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +64041,73934,66986,PRETRIAL,Wildman,Christopher,Vincent,Male,Other,11/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +64041,73934,66986,PRETRIAL,Wildman,Christopher,Vincent,Male,Other,11/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +64041,73934,66986,PRETRIAL,Wildman,Christopher,Vincent,Male,Other,11/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64059,73955,67005,Probation,dossantos,rodinelli,NULL,Male,Caucasian,08/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +64059,73955,67005,Probation,dossantos,rodinelli,NULL,Male,Caucasian,08/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +64059,73955,67005,Probation,dossantos,rodinelli,NULL,Male,Caucasian,08/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +36931,73964,67012,PRETRIAL,Bedford,Terrace,NULL,Male,African-American,12/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +36931,73964,67012,PRETRIAL,Bedford,Terrace,NULL,Male,African-American,12/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +36931,73964,67012,PRETRIAL,Bedford,Terrace,NULL,Male,African-American,12/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64044,73938,66989,PRETRIAL,Guzman,Julio,NULL,Male,Hispanic,08/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +64044,73938,66989,PRETRIAL,Guzman,Julio,NULL,Male,Hispanic,08/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +64044,73938,66989,PRETRIAL,Guzman,Julio,NULL,Male,Hispanic,08/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +60960,73959,63461,Probation,Oneal,Raenesha,NULL,Female,African-American,04/26/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,4,High,7,Risk of Violence,-0.92,9,High,New,1,0 +60960,73959,63461,Probation,Oneal,Raenesha,NULL,Female,African-American,04/26/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,4,High,8,Risk of Recidivism,0.32,9,High,New,1,0 +60960,73959,63461,Probation,Oneal,Raenesha,NULL,Female,African-American,04/26/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,4,High,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +64043,73936,66988,PRETRIAL,MINGO,LAWRENCE,NULL,Male,African-American,08/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +64043,73936,66988,PRETRIAL,MINGO,LAWRENCE,NULL,Male,African-American,08/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +64043,73936,66988,PRETRIAL,MINGO,LAWRENCE,NULL,Male,African-American,08/06/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64049,73943,66994,PRETRIAL,DAVIS,RODNEY,NULL,Male,African-American,01/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/14 0:00,4,High,7,Risk of Violence,-0.66,9,High,New,1,0 +64049,73943,66994,PRETRIAL,DAVIS,RODNEY,NULL,Male,African-American,01/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/14 0:00,4,High,8,Risk of Recidivism,0.84,10,High,New,1,0 +64049,73943,66994,PRETRIAL,DAVIS,RODNEY,NULL,Male,African-American,01/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64055,73950,67000,Probation,Arcinigeagutierrez,Carlos,NULL,Male,Hispanic,01/19/62,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/10/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +64055,73950,67000,Probation,Arcinigeagutierrez,Carlos,NULL,Male,Hispanic,01/19/62,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/10/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +64055,73950,67000,Probation,Arcinigeagutierrez,Carlos,NULL,Male,Hispanic,01/19/62,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +15369,73952,67002,PRETRIAL,Glass,Darance,NULL,Male,African-American,02/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +15369,73952,67002,PRETRIAL,Glass,Darance,NULL,Male,African-American,02/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +15369,73952,67002,PRETRIAL,Glass,Darance,NULL,Male,African-American,02/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64046,73940,66991,PRETRIAL,MOUSSA,JARED,NULL,Male,Caucasian,10/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,2,Medium,7,Risk of Violence,-3.15,1,Low,New,1,0 +64046,73940,66991,PRETRIAL,MOUSSA,JARED,NULL,Male,Caucasian,10/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +64046,73940,66991,PRETRIAL,MOUSSA,JARED,NULL,Male,Caucasian,10/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63815,73948,66740,PRETRIAL,MITCHELL,JAMES,HENRY,Male,African-American,12/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,Copy,1,0 +63815,73948,66740,PRETRIAL,MITCHELL,JAMES,HENRY,Male,African-American,12/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +63815,73948,66740,PRETRIAL,MITCHELL,JAMES,HENRY,Male,African-American,12/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +63342,73966,66187,PRETRIAL,McCray,Rodney,NULL,Male,African-American,07/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +63342,73966,66187,PRETRIAL,McCray,Rodney,NULL,Male,African-American,07/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +63342,73966,66187,PRETRIAL,McCray,Rodney,NULL,Male,African-American,07/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64057,73953,67003,Probation,PRIMUS,MICHAEL,NULL,Male,African-American,09/10/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +64057,73953,67003,Probation,PRIMUS,MICHAEL,NULL,Male,African-American,09/10/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +64057,73953,67003,Probation,PRIMUS,MICHAEL,NULL,Male,African-American,09/10/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64051,73945,66996,Probation,Obrien,James,NULL,Male,Caucasian,06/18/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/10/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +64051,73945,66996,Probation,Obrien,James,NULL,Male,Caucasian,06/18/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/10/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +64051,73945,66996,Probation,Obrien,James,NULL,Male,Caucasian,06/18/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64067,73974,67018,PRETRIAL,Roderick,Christopher,NULL,Male,Caucasian,12/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,6/11/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +64067,73974,67018,PRETRIAL,Roderick,Christopher,NULL,Male,Caucasian,12/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,6/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +64067,73974,67018,PRETRIAL,Roderick,Christopher,NULL,Male,Caucasian,12/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,6/11/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +39864,73992,39441,PRETRIAL,green,franklin,NULL,Male,African-American,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,Copy,1,0 +39864,73992,39441,PRETRIAL,green,franklin,NULL,Male,African-American,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.64,10,High,Copy,1,0 +39864,73992,39441,PRETRIAL,green,franklin,NULL,Male,African-American,11/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +57109,65265,59203,Probation,patfield,anthony,NULL,Male,Caucasian,02/21/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +57109,65265,59203,Probation,patfield,anthony,NULL,Male,Caucasian,02/21/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +57109,65265,59203,Probation,patfield,anthony,NULL,Male,Caucasian,02/21/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +35016,73969,45441,Probation,taylor,javon,NULL,Male,African-American,06/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,Copy,1,0 +35016,73969,45441,Probation,taylor,javon,NULL,Male,African-American,06/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,Copy,1,0 +35016,73969,45441,Probation,taylor,javon,NULL,Male,African-American,06/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +64071,73982,67023,PRETRIAL,Helms,Paul,NULL,Male,Caucasian,08/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +64071,73982,67023,PRETRIAL,Helms,Paul,NULL,Male,Caucasian,08/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +64071,73982,67023,PRETRIAL,Helms,Paul,NULL,Male,Caucasian,08/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64073,73984,67025,PRETRIAL,shepard,terry,NULL,Male,African-American,10/08/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +64073,73984,67025,PRETRIAL,shepard,terry,NULL,Male,African-American,10/08/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +64073,73984,67025,PRETRIAL,shepard,terry,NULL,Male,African-American,10/08/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64077,73990,67030,PRETRIAL,Savio,Michael,NULL,Male,Caucasian,02/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/11/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +64077,73990,67030,PRETRIAL,Savio,Michael,NULL,Male,Caucasian,02/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/11/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +64077,73990,67030,PRETRIAL,Savio,Michael,NULL,Male,Caucasian,02/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64069,73976,67020,Probation,Cruz,Marcia,NULL,Female,Hispanic,06/05/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +64069,73976,67020,Probation,Cruz,Marcia,NULL,Female,Hispanic,06/05/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +64069,73976,67020,Probation,Cruz,Marcia,NULL,Female,Hispanic,06/05/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52304,73971,67016,PRETRIAL,jackson,deon,NULL,Male,African-American,10/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +52304,73971,67016,PRETRIAL,jackson,deon,NULL,Male,African-American,10/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,4,High,8,Risk of Recidivism,0.71,10,High,New,1,0 +52304,73971,67016,PRETRIAL,jackson,deon,NULL,Male,African-American,10/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61563,73973,64141,Probation,BERT,PAUL,A,Male,Caucasian,10/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,Copy,1,0 +61563,73973,64141,Probation,BERT,PAUL,A,Male,Caucasian,10/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,Copy,1,0 +61563,73973,64141,Probation,BERT,PAUL,A,Male,Caucasian,10/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +63135,73978,65959,PRETRIAL,Woodson,Olivier,NULL,Male,African-American,01/31/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,4,High,7,Risk of Violence,-0.16,10,High,Copy,1,0 +63135,73978,65959,PRETRIAL,Woodson,Olivier,NULL,Male,African-American,01/31/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,4,High,8,Risk of Recidivism,0.78,10,High,Copy,1,0 +63135,73978,65959,PRETRIAL,Woodson,Olivier,NULL,Male,African-American,01/31/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +64070,73980,67021,Probation,anderson,Joanne,NULL,Female,African-American,05/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +64070,73980,67021,Probation,anderson,Joanne,NULL,Female,African-American,05/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +64070,73980,67021,Probation,anderson,Joanne,NULL,Female,African-American,05/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64079,73994,67032,PRETRIAL,Rhett,Andra,NULL,Male,African-American,09/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/11/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +64079,73994,67032,PRETRIAL,Rhett,Andra,NULL,Male,African-American,09/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/11/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +64079,73994,67032,PRETRIAL,Rhett,Andra,NULL,Male,African-American,09/26/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,38,10,High,New,1,0 +64076,73989,67029,PRETRIAL,HICKS,TYRUS,NULL,Male,African-American,08/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +64076,73989,67029,PRETRIAL,HICKS,TYRUS,NULL,Male,African-American,08/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +64076,73989,67029,PRETRIAL,HICKS,TYRUS,NULL,Male,African-American,08/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +44130,73968,67014,PRETRIAL,Mccrea,Carlis,NULL,Male,African-American,08/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +44130,73968,67014,PRETRIAL,Mccrea,Carlis,NULL,Male,African-American,08/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +44130,73968,67014,PRETRIAL,Mccrea,Carlis,NULL,Male,African-American,08/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64074,73985,67026,Probation,mcgrath,sean,NULL,Male,Caucasian,02/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +64074,73985,67026,Probation,mcgrath,sean,NULL,Male,Caucasian,02/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +64074,73985,67026,Probation,mcgrath,sean,NULL,Male,Caucasian,02/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +37170,73972,67017,PRETRIAL,Johnson,Willie,NULL,Male,African-American,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,4,High,7,Risk of Violence,-0.76,9,High,New,1,0 +37170,73972,67017,PRETRIAL,Johnson,Willie,NULL,Male,African-American,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,4,High,8,Risk of Recidivism,0.88,10,High,New,1,0 +37170,73972,67017,PRETRIAL,Johnson,Willie,NULL,Male,African-American,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63229,73979,66052,PRETRIAL,Grant,Bonnie,NULL,Female,Caucasian,10/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/11/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,Copy,1,0 +63229,73979,66052,PRETRIAL,Grant,Bonnie,NULL,Female,Caucasian,10/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/11/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,Copy,1,0 +63229,73979,66052,PRETRIAL,Grant,Bonnie,NULL,Female,Caucasian,10/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +2577,73993,48221,PRETRIAL,shears,joseph,andrew,Male,African-American,08/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +2577,73993,48221,PRETRIAL,shears,joseph,andrew,Male,African-American,08/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,Copy,1,0 +2577,73993,48221,PRETRIAL,shears,joseph,andrew,Male,African-American,08/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +50997,73986,52139,PRETRIAL,Demeritte,Raphale,NULL,Male,African-American,10/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,Copy,1,0 +50997,73986,52139,PRETRIAL,Demeritte,Raphale,NULL,Male,African-American,10/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,Copy,1,0 +50997,73986,52139,PRETRIAL,Demeritte,Raphale,NULL,Male,African-American,10/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +23992,73981,67022,PRETRIAL,Foster,Eddie,NULL,Male,African-American,04/08/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/11/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +23992,73981,67022,PRETRIAL,Foster,Eddie,NULL,Male,African-American,04/08/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/11/14 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +23992,73981,67022,PRETRIAL,Foster,Eddie,NULL,Male,African-American,04/08/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/11/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +64078,73991,67031,PRETRIAL,POLLARD,Debrah,NULL,Female,African-American,10/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,2,Medium,7,Risk of Violence,-3.28,1,Low,New,1,0 +64078,73991,67031,PRETRIAL,POLLARD,Debrah,NULL,Female,African-American,10/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +64078,73991,67031,PRETRIAL,POLLARD,Debrah,NULL,Female,African-American,10/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/11/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64066,73970,67015,PRETRIAL,Webb,Nicholas,Mark,Male,African-American,02/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +64066,73970,67015,PRETRIAL,Webb,Nicholas,Mark,Male,African-American,02/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +64066,73970,67015,PRETRIAL,Webb,Nicholas,Mark,Male,African-American,02/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64075,73988,67028,PRETRIAL,GUERRIER,CINDY,NULL,Female,African-American,04/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +64075,73988,67028,PRETRIAL,GUERRIER,CINDY,NULL,Female,African-American,04/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +64075,73988,67028,PRETRIAL,GUERRIER,CINDY,NULL,Female,African-American,04/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +64072,73983,67024,PRETRIAL,mckinney,damion,NULL,Male,African-American,12/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,New,1,0 +64072,73983,67024,PRETRIAL,mckinney,damion,NULL,Male,African-American,12/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +64072,73983,67024,PRETRIAL,mckinney,damion,NULL,Male,African-American,12/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64068,73975,67019,PRETRIAL,Larosa,Yenia,NULL,Female,Hispanic,11/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/11/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +64068,73975,67019,PRETRIAL,Larosa,Yenia,NULL,Female,Hispanic,11/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/11/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +64068,73975,67019,PRETRIAL,Larosa,Yenia,NULL,Female,Hispanic,11/20/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64087,74004,67042,Probation,Fernandez,Carlos,emmanuel,Male,Hispanic,04/07/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +64087,74004,67042,Probation,Fernandez,Carlos,emmanuel,Male,Hispanic,04/07/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +64087,74004,67042,Probation,Fernandez,Carlos,emmanuel,Male,Hispanic,04/07/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62600,74012,65337,PRETRIAL,Munnings,Olga,NULL,Female,African-American,03/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/12/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,Copy,1,0 +62600,74012,65337,PRETRIAL,Munnings,Olga,NULL,Female,African-American,03/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/12/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,Copy,1,0 +62600,74012,65337,PRETRIAL,Munnings,Olga,NULL,Female,African-American,03/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +64081,73996,67034,PRETRIAL,Hightower,Shauntrell,NULL,Female,African-American,02/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +64081,73996,67034,PRETRIAL,Hightower,Shauntrell,NULL,Female,African-American,02/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +64081,73996,67034,PRETRIAL,Hightower,Shauntrell,NULL,Female,African-American,02/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +28274,74009,57822,PRETRIAL,Reese,Jeffrey,NULL,Male,African-American,12/03/87,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Significant Other,6/12/14 0:00,4,High,7,Risk of Violence,-0.7,9,High,Copy,1,0 +28274,74009,57822,PRETRIAL,Reese,Jeffrey,NULL,Male,African-American,12/03/87,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Significant Other,6/12/14 0:00,4,High,8,Risk of Recidivism,0.6,9,High,Copy,1,0 +28274,74009,57822,PRETRIAL,Reese,Jeffrey,NULL,Male,African-American,12/03/87,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Significant Other,6/12/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +6242,74002,67040,PRETRIAL,Darryl,Kelly,NULL,Male,African-American,10/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,4,High,7,Risk of Violence,-0.26,10,High,New,1,0 +6242,74002,67040,PRETRIAL,Darryl,Kelly,NULL,Male,African-American,10/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +6242,74002,67040,PRETRIAL,Darryl,Kelly,NULL,Male,African-American,10/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +59112,74016,67051,PRETRIAL,BROWN,MARIO,LETROY,Male,Caucasian,11/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/12/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +59112,74016,67051,PRETRIAL,BROWN,MARIO,LETROY,Male,Caucasian,11/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/12/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +59112,74016,67051,PRETRIAL,BROWN,MARIO,LETROY,Male,Caucasian,11/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +2954,74014,67049,PRETRIAL,THOMPSON,XAVIER,KEITH,Male,African-American,12/11/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +2954,74014,67049,PRETRIAL,THOMPSON,XAVIER,KEITH,Male,African-American,12/11/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +2954,74014,67049,PRETRIAL,THOMPSON,XAVIER,KEITH,Male,African-American,12/11/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +27589,74007,67045,PRETRIAL,TORRES,DANETTE,WARREN,Female,Caucasian,09/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/12/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +27589,74007,67045,PRETRIAL,TORRES,DANETTE,WARREN,Female,Caucasian,09/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/12/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +27589,74007,67045,PRETRIAL,TORRES,DANETTE,WARREN,Female,Caucasian,09/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64090,74010,67046,PRETRIAL,Pinnock,Damion,NULL,Male,African-American,05/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/12/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +64090,74010,67046,PRETRIAL,Pinnock,Damion,NULL,Male,African-American,05/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/12/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +64090,74010,67046,PRETRIAL,Pinnock,Damion,NULL,Male,African-American,05/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64088,74006,67044,PRETRIAL,Metzger,Lawrence,NULL,Male,Caucasian,05/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +64088,74006,67044,PRETRIAL,Metzger,Lawrence,NULL,Male,Caucasian,05/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +64088,74006,67044,PRETRIAL,Metzger,Lawrence,NULL,Male,Caucasian,05/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64093,74015,67050,PRETRIAL,Faison,Cheryl,NULL,Female,Caucasian,02/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,2,Medium,7,Risk of Violence,-2.63,2,Low,New,1,0 +64093,74015,67050,PRETRIAL,Faison,Cheryl,NULL,Female,Caucasian,02/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,7,Medium,New,1,0 +64093,74015,67050,PRETRIAL,Faison,Cheryl,NULL,Female,Caucasian,02/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,New,1,0 +64084,73999,67037,PRETRIAL,Pallazo,Alan,D,Male,African-American,07/10/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +64084,73999,67037,PRETRIAL,Pallazo,Alan,D,Male,African-American,07/10/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +64084,73999,67037,PRETRIAL,Pallazo,Alan,D,Male,African-American,07/10/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64086,74001,67039,PRETRIAL,Chernin,Zachary,Arronsun,Male,Caucasian,09/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +64086,74001,67039,PRETRIAL,Chernin,Zachary,Arronsun,Male,Caucasian,09/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +64086,74001,67039,PRETRIAL,Chernin,Zachary,Arronsun,Male,Caucasian,09/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64082,73997,67035,PRETRIAL,Garay,Raul,Omar,Male,Hispanic,04/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/12/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +64082,73997,67035,PRETRIAL,Garay,Raul,Omar,Male,Hispanic,04/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/12/14 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +64082,73997,67035,PRETRIAL,Garay,Raul,Omar,Male,Hispanic,04/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +30243,74003,67041,Probation,mitchell,aquaria,NULL,Female,African-American,01/14/93,17,All Scales,Intake,English,Other,Probation,Single,6/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +30243,74003,67041,Probation,mitchell,aquaria,NULL,Female,African-American,01/14/93,17,All Scales,Intake,English,Other,Probation,Single,6/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +30243,74003,67041,Probation,mitchell,aquaria,NULL,Female,African-American,01/14/93,17,All Scales,Intake,English,Other,Probation,Single,6/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,New,1,0 +55116,74005,67043,PRETRIAL,Roberti,Asher,NULL,Male,Caucasian,10/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +55116,74005,67043,PRETRIAL,Roberti,Asher,NULL,Male,Caucasian,10/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +55116,74005,67043,PRETRIAL,Roberti,Asher,NULL,Male,Caucasian,10/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64085,74000,67038,PRETRIAL,Inzinna,Brandon,NULL,Male,Caucasian,10/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +64085,74000,67038,PRETRIAL,Inzinna,Brandon,NULL,Male,Caucasian,10/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +64085,74000,67038,PRETRIAL,Inzinna,Brandon,NULL,Male,Caucasian,10/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/12/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64080,73995,67033,PRETRIAL,DAVIS,KENNETH,AUSTIN,Male,Caucasian,09/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/12/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +64080,73995,67033,PRETRIAL,DAVIS,KENNETH,AUSTIN,Male,Caucasian,09/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/12/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +64080,73995,67033,PRETRIAL,DAVIS,KENNETH,AUSTIN,Male,Caucasian,09/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64092,74013,67048,Probation,laichak,robert,NULL,Male,Caucasian,09/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +64092,74013,67048,Probation,laichak,robert,NULL,Male,Caucasian,09/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +64092,74013,67048,Probation,laichak,robert,NULL,Male,Caucasian,09/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +40082,74042,67076,PRETRIAL,Flodin,Christopher,NULL,Male,Caucasian,05/07/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/13/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +40082,74042,67076,PRETRIAL,Flodin,Christopher,NULL,Male,Caucasian,05/07/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/13/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +40082,74042,67076,PRETRIAL,Flodin,Christopher,NULL,Male,Caucasian,05/07/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +35660,38095,34887,PRETRIAL,Daniels,Ruth,NULL,Female,African-American,05/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,4,High,7,Risk of Violence,-0.6,10,High,New,1,0 +35660,38095,34887,PRETRIAL,Daniels,Ruth,NULL,Female,African-American,05/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,4,High,8,Risk of Recidivism,1.04,10,High,New,1,0 +35660,38095,34887,PRETRIAL,Daniels,Ruth,NULL,Female,African-American,05/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,4,High,18,Risk of Failure to Appear,20,4,Low,New,1,0 +64109,74034,67069,PRETRIAL,BOLLMANN,WILLIAM,NULL,Male,Caucasian,01/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +64109,74034,67069,PRETRIAL,BOLLMANN,WILLIAM,NULL,Male,Caucasian,01/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +64109,74034,67069,PRETRIAL,BOLLMANN,WILLIAM,NULL,Male,Caucasian,01/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64097,74021,67056,PRETRIAL,Kendricks,Alexander,NULL,Male,African-American,10/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +64097,74021,67056,PRETRIAL,Kendricks,Alexander,NULL,Male,African-American,10/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,4,High,8,Risk of Recidivism,0.65,10,High,New,1,0 +64097,74021,67056,PRETRIAL,Kendricks,Alexander,NULL,Male,African-American,10/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +45552,74055,67088,PRETRIAL,Cleveland,Nico,Minardos,Male,African-American,08/18/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +45552,74055,67088,PRETRIAL,Cleveland,Nico,Minardos,Male,African-American,08/18/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +45552,74055,67088,PRETRIAL,Cleveland,Nico,Minardos,Male,African-American,08/18/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64112,74039,67073,PRETRIAL,boyer,catie,NULL,Female,Caucasian,06/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +64112,74039,67073,PRETRIAL,boyer,catie,NULL,Female,Caucasian,06/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,8,High,New,1,0 +64112,74039,67073,PRETRIAL,boyer,catie,NULL,Female,Caucasian,06/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64121,74047,67080,Probation,Garcia,Fabio,NULL,Male,Hispanic,12/21/62,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/13/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +64121,74047,67080,Probation,Garcia,Fabio,NULL,Male,Hispanic,12/21/62,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/13/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +64121,74047,67080,Probation,Garcia,Fabio,NULL,Male,Hispanic,12/21/62,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64101,74026,67061,PRETRIAL,Penso,David,NULL,Male,African-American,01/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +64101,74026,67061,PRETRIAL,Penso,David,NULL,Male,African-American,01/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +64101,74026,67061,PRETRIAL,Penso,David,NULL,Male,African-American,01/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +32662,74050,67083,PRETRIAL,Sepulveda,Edward,DeJesus,Male,Caucasian,07/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,New,1,0 +32662,74050,67083,PRETRIAL,Sepulveda,Edward,DeJesus,Male,Caucasian,07/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +32662,74050,67083,PRETRIAL,Sepulveda,Edward,DeJesus,Male,Caucasian,07/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64124,74052,67085,Probation,East,Jessica,NULL,Female,Hispanic,09/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +64124,74052,67085,Probation,East,Jessica,NULL,Female,Hispanic,09/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +64124,74052,67085,Probation,East,Jessica,NULL,Female,Hispanic,09/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64098,74022,67057,PRETRIAL,Lockwood,Darius,NULL,Male,African-American,05/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +64098,74022,67057,PRETRIAL,Lockwood,Darius,NULL,Male,African-American,05/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +64098,74022,67057,PRETRIAL,Lockwood,Darius,NULL,Male,African-American,05/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64104,74029,67064,PRETRIAL,Abrell,Cass,NULL,Male,Caucasian,07/10/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +64104,74029,67064,PRETRIAL,Abrell,Cass,NULL,Male,Caucasian,07/10/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +64104,74029,67064,PRETRIAL,Abrell,Cass,NULL,Male,Caucasian,07/10/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64119,74043,67077,Probation,John,Daniel,NULL,Male,Caucasian,05/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/13/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +64119,74043,67077,Probation,John,Daniel,NULL,Male,Caucasian,05/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/13/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +64119,74043,67077,Probation,John,Daniel,NULL,Male,Caucasian,05/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64096,74020,67055,PRETRIAL,Candiolli,Luis,A,Male,Caucasian,10/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/13/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +64096,74020,67055,PRETRIAL,Candiolli,Luis,A,Male,Caucasian,10/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/13/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +64096,74020,67055,PRETRIAL,Candiolli,Luis,A,Male,Caucasian,10/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64106,74031,67066,PRETRIAL,Richards,Roger,Samuel,Male,African-American,01/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.94,9,High,New,1,0 +64106,74031,67066,PRETRIAL,Richards,Roger,Samuel,Male,African-American,01/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +64106,74031,67066,PRETRIAL,Richards,Roger,Samuel,Male,African-American,01/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56332,74045,58291,PRETRIAL,LYTLE,ANTONIO,J,Male,African-American,07/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,Copy,1,0 +56332,74045,58291,PRETRIAL,LYTLE,ANTONIO,J,Male,African-American,07/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,Copy,1,0 +56332,74045,58291,PRETRIAL,LYTLE,ANTONIO,J,Male,African-American,07/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +42172,74024,67059,PRETRIAL,SHEFFIELD,DONOVAN,ANTWAN,Male,African-American,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +42172,74024,67059,PRETRIAL,SHEFFIELD,DONOVAN,ANTWAN,Male,African-American,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +42172,74024,67059,PRETRIAL,SHEFFIELD,DONOVAN,ANTWAN,Male,African-American,12/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64102,74027,67062,PRETRIAL,Arbolaez,Robert,NULL,Male,African-American,12/20/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +64102,74027,67062,PRETRIAL,Arbolaez,Robert,NULL,Male,African-American,12/20/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +64102,74027,67062,PRETRIAL,Arbolaez,Robert,NULL,Male,African-American,12/20/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64110,74036,67070,PRETRIAL,Bernadin,Jean,Joseph,Male,African-American,11/10/45,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,6/13/14 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +64110,74036,67070,PRETRIAL,Bernadin,Jean,Joseph,Male,African-American,11/10/45,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,6/13/14 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +64110,74036,67070,PRETRIAL,Bernadin,Jean,Joseph,Male,African-American,11/10/45,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +48914,74044,67078,PRETRIAL,Lobban,Dexton,W,Male,African-American,10/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +48914,74044,67078,PRETRIAL,Lobban,Dexton,W,Male,African-American,10/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +48914,74044,67078,PRETRIAL,Lobban,Dexton,W,Male,African-American,10/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64111,74037,67071,PRETRIAL,Bonsignore,Lance,NULL,Male,Caucasian,11/04/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +64111,74037,67071,PRETRIAL,Bonsignore,Lance,NULL,Male,Caucasian,11/04/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +64111,74037,67071,PRETRIAL,Bonsignore,Lance,NULL,Male,Caucasian,11/04/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61744,74035,64334,Probation,Jacques,Jeffery,NULL,Male,Caucasian,01/28/65,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +61744,74035,64334,Probation,Jacques,Jeffery,NULL,Male,Caucasian,01/28/65,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-0.6,3,Low,New,1,0 +61744,74035,64334,Probation,Jacques,Jeffery,NULL,Male,Caucasian,01/28/65,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +48729,74019,67054,Probation,Nichols,Roger,NULL,Male,Caucasian,11/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/13/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +48729,74019,67054,Probation,Nichols,Roger,NULL,Male,Caucasian,11/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/13/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +48729,74019,67054,Probation,Nichols,Roger,NULL,Male,Caucasian,11/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64099,74023,67058,PRETRIAL,Harmon,Niketa,Valsha,Female,African-American,11/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,New,1,0 +64099,74023,67058,PRETRIAL,Harmon,Niketa,Valsha,Female,African-American,11/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,9,High,New,1,0 +64099,74023,67058,PRETRIAL,Harmon,Niketa,Valsha,Female,African-American,11/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +64103,74028,67063,PRETRIAL,Martinez,Leslie,Jeanette,Female,Hispanic,10/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +64103,74028,67063,PRETRIAL,Martinez,Leslie,Jeanette,Female,Hispanic,10/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +64103,74028,67063,PRETRIAL,Martinez,Leslie,Jeanette,Female,Hispanic,10/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64107,74032,67067,PRETRIAL,Peters,James,Daniel,Male,Caucasian,03/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +64107,74032,67067,PRETRIAL,Peters,James,Daniel,Male,Caucasian,03/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +64107,74032,67067,PRETRIAL,Peters,James,Daniel,Male,Caucasian,03/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +63453,74038,67072,Probation,Vieira,Shane,NULL,Male,Caucasian,11/28/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +63453,74038,67072,Probation,Vieira,Shane,NULL,Male,Caucasian,11/28/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-0.63,3,Low,New,1,0 +63453,74038,67072,Probation,Vieira,Shane,NULL,Male,Caucasian,11/28/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +48727,74056,67089,PRETRIAL,ROSEN,ROMINA,NULL,Female,Caucasian,05/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/13/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +48727,74056,67089,PRETRIAL,ROSEN,ROMINA,NULL,Female,Caucasian,05/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/13/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +48727,74056,67089,PRETRIAL,ROSEN,ROMINA,NULL,Female,Caucasian,05/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64105,74030,67065,PRETRIAL,Lamar,Jeremy,Bernard,Male,African-American,01/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +64105,74030,67065,PRETRIAL,Lamar,Jeremy,Bernard,Male,African-American,01/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +64105,74030,67065,PRETRIAL,Lamar,Jeremy,Bernard,Male,African-American,01/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64123,74051,67084,Probation,Paolucci,Tina,NULL,Female,Caucasian,02/08/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +64123,74051,67084,Probation,Paolucci,Tina,NULL,Female,Caucasian,02/08/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +64123,74051,67084,Probation,Paolucci,Tina,NULL,Female,Caucasian,02/08/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64120,74046,67079,PRETRIAL,JeanBaptise,Ysmereleda,NULL,Female,African-American,09/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/13/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +64120,74046,67079,PRETRIAL,JeanBaptise,Ysmereleda,NULL,Female,African-American,09/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/13/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +64120,74046,67079,PRETRIAL,JeanBaptise,Ysmereleda,NULL,Female,African-American,09/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64122,74048,67081,Probation,Mullino,Jerome,NULL,Male,African-American,11/04/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +64122,74048,67081,Probation,Mullino,Jerome,NULL,Male,African-American,11/04/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +64122,74048,67081,Probation,Mullino,Jerome,NULL,Male,African-American,11/04/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64108,74033,67068,PRETRIAL,Vasquez,Mitchell,NULL,Male,Caucasian,04/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +64108,74033,67068,PRETRIAL,Vasquez,Mitchell,NULL,Male,Caucasian,04/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +64108,74033,67068,PRETRIAL,Vasquez,Mitchell,NULL,Male,Caucasian,04/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64117,74040,67074,PRETRIAL,Sanon,Jahsan,NULL,Male,Hispanic,05/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +64117,74040,67074,PRETRIAL,Sanon,Jahsan,NULL,Male,Hispanic,05/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +64117,74040,67074,PRETRIAL,Sanon,Jahsan,NULL,Male,Hispanic,05/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/13/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62637,74054,67087,Probation,Norris,Willie,NULL,Male,African-American,04/23/59,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,6/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.14,1,Low,New,1,0 +62637,74054,67087,Probation,Norris,Willie,NULL,Male,African-American,04/23/59,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,6/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +62637,74054,67087,Probation,Norris,Willie,NULL,Male,African-American,04/23/59,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,6/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +64100,74025,67060,PRETRIAL,Costa,Karine,NULL,Female,Caucasian,08/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +64100,74025,67060,PRETRIAL,Costa,Karine,NULL,Female,Caucasian,08/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +64100,74025,67060,PRETRIAL,Costa,Karine,NULL,Female,Caucasian,08/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64129,74061,67093,PRETRIAL,Mclemore,Anthony,NULL,Male,African-American,06/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +64129,74061,67093,PRETRIAL,Mclemore,Anthony,NULL,Male,African-American,06/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +64129,74061,67093,PRETRIAL,Mclemore,Anthony,NULL,Male,African-American,06/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63052,74067,67100,PRETRIAL,Pena,Nicholas,NULL,Male,Caucasian,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.24,8,High,New,1,0 +63052,74067,67100,PRETRIAL,Pena,Nicholas,NULL,Male,Caucasian,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +63052,74067,67100,PRETRIAL,Pena,Nicholas,NULL,Male,Caucasian,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +47311,74069,67102,PRETRIAL,Davila,Ralph,Justin,Male,Caucasian,10/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +47311,74069,67102,PRETRIAL,Davila,Ralph,Justin,Male,Caucasian,10/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +47311,74069,67102,PRETRIAL,Davila,Ralph,Justin,Male,Caucasian,10/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64132,74064,67097,PRETRIAL,Fiallos,Carlos,Alberto,Male,Caucasian,07/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/14/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +64132,74064,67097,PRETRIAL,Fiallos,Carlos,Alberto,Male,Caucasian,07/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/14/14 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +64132,74064,67097,PRETRIAL,Fiallos,Carlos,Alberto,Male,Caucasian,07/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/14/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64127,74059,67091,PRETRIAL,Tribie,Christopher,NULL,Male,African-American,05/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +64127,74059,67091,PRETRIAL,Tribie,Christopher,NULL,Male,African-American,05/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +64127,74059,67091,PRETRIAL,Tribie,Christopher,NULL,Male,African-American,05/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64138,74074,67107,PRETRIAL,Saintil,Huberman,NULL,Male,African-American,08/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +64138,74074,67107,PRETRIAL,Saintil,Huberman,NULL,Male,African-American,08/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +64138,74074,67107,PRETRIAL,Saintil,Huberman,NULL,Male,African-American,08/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +14740,74058,14091,PRETRIAL,DUSTON,DILLON,NULL,Male,Caucasian,03/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,Copy,1,0 +14740,74058,14091,PRETRIAL,DUSTON,DILLON,NULL,Male,Caucasian,03/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,4,High,8,Risk of Recidivism,0.51,9,High,Copy,1,0 +14740,74058,14091,PRETRIAL,DUSTON,DILLON,NULL,Male,Caucasian,03/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +64136,74072,67105,PRETRIAL,Robles,Javier,NULL,Male,Hispanic,10/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/14/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +64136,74072,67105,PRETRIAL,Robles,Javier,NULL,Male,Hispanic,10/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/14/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +64136,74072,67105,PRETRIAL,Robles,Javier,NULL,Male,Hispanic,10/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +22739,74066,67099,PRETRIAL,mims,javaris,NULL,Male,African-American,09/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +22739,74066,67099,PRETRIAL,mims,javaris,NULL,Male,African-American,09/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +22739,74066,67099,PRETRIAL,mims,javaris,NULL,Male,African-American,09/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64126,74057,67090,PRETRIAL,Barnes,Elliot,NULL,Male,African-American,01/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +64126,74057,67090,PRETRIAL,Barnes,Elliot,NULL,Male,African-American,01/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +64126,74057,67090,PRETRIAL,Barnes,Elliot,NULL,Male,African-American,01/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64130,74062,67094,PRETRIAL,Christian,Willie,NULL,Male,African-American,08/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +64130,74062,67094,PRETRIAL,Christian,Willie,NULL,Male,African-American,08/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +64130,74062,67094,PRETRIAL,Christian,Willie,NULL,Male,African-American,08/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64135,74071,67104,PRETRIAL,rodriguez,sebastian,NULL,Male,Caucasian,05/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +64135,74071,67104,PRETRIAL,rodriguez,sebastian,NULL,Male,Caucasian,05/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +64135,74071,67104,PRETRIAL,rodriguez,sebastian,NULL,Male,Caucasian,05/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64137,74073,67106,PRETRIAL,GRIECO,ANGEL,NULL,Female,Caucasian,11/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/14/14 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +64137,74073,67106,PRETRIAL,GRIECO,ANGEL,NULL,Female,Caucasian,11/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +64137,74073,67106,PRETRIAL,GRIECO,ANGEL,NULL,Female,Caucasian,11/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/14/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30641,74068,67101,PRETRIAL,NELSON,KEVIN,DENNARD,Male,African-American,12/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +30641,74068,67101,PRETRIAL,NELSON,KEVIN,DENNARD,Male,African-American,12/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +30641,74068,67101,PRETRIAL,NELSON,KEVIN,DENNARD,Male,African-American,12/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64128,74060,67092,PRETRIAL,Arango,Paola,NULL,Male,Caucasian,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +64128,74060,67092,PRETRIAL,Arango,Paola,NULL,Male,Caucasian,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +64128,74060,67092,PRETRIAL,Arango,Paola,NULL,Male,Caucasian,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64131,74063,67095,PRETRIAL,Campos,Aline,NULL,Female,Caucasian,01/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +64131,74063,67095,PRETRIAL,Campos,Aline,NULL,Female,Caucasian,01/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +64131,74063,67095,PRETRIAL,Campos,Aline,NULL,Female,Caucasian,01/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64142,74081,67113,PRETRIAL,Flood,William,NULL,Male,African-American,09/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +64142,74081,67113,PRETRIAL,Flood,William,NULL,Male,African-American,09/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +64142,74081,67113,PRETRIAL,Flood,William,NULL,Male,African-American,09/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64139,74076,67109,PRETRIAL,GARAFALO,JASON,F,Male,Caucasian,10/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/15/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +64139,74076,67109,PRETRIAL,GARAFALO,JASON,F,Male,Caucasian,10/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/15/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +64139,74076,67109,PRETRIAL,GARAFALO,JASON,F,Male,Caucasian,10/16/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64144,74084,67115,PRETRIAL,Dieppa,Vilma,i,Female,Caucasian,02/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,6/15/14 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,Copy,1,0 +64144,74084,67115,PRETRIAL,Dieppa,Vilma,i,Female,Caucasian,02/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,6/15/14 0:00,1,Low,8,Risk of Recidivism,-2.65,1,Low,Copy,1,0 +64144,74084,67115,PRETRIAL,Dieppa,Vilma,i,Female,Caucasian,02/15/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,6/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +37715,74080,56267,PRETRIAL,MIKS,JEREMY,NULL,Male,Caucasian,03/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.68,2,Low,Copy,1,0 +37715,74080,56267,PRETRIAL,MIKS,JEREMY,NULL,Male,Caucasian,03/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,Copy,1,0 +37715,74080,56267,PRETRIAL,MIKS,JEREMY,NULL,Male,Caucasian,03/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +64140,74078,67111,PRETRIAL,HOWARD,RODNEY,NULL,Male,African-American,11/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +64140,74078,67111,PRETRIAL,HOWARD,RODNEY,NULL,Male,African-American,11/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +64140,74078,67111,PRETRIAL,HOWARD,RODNEY,NULL,Male,African-American,11/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +64141,74079,67112,PRETRIAL,Amireh,Salah,NULL,Male,Caucasian,04/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +64141,74079,67112,PRETRIAL,Amireh,Salah,NULL,Male,Caucasian,04/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +64141,74079,67112,PRETRIAL,Amireh,Salah,NULL,Male,Caucasian,04/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +24212,74077,67110,PRETRIAL,SLOCUM,SHANE,NULL,Male,African-American,08/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +24212,74077,67110,PRETRIAL,SLOCUM,SHANE,NULL,Male,African-American,08/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +24212,74077,67110,PRETRIAL,SLOCUM,SHANE,NULL,Male,African-American,08/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64145,74085,67116,PRETRIAL,Ramos,Samuel,NULL,Male,Caucasian,03/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/15/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +64145,74085,67116,PRETRIAL,Ramos,Samuel,NULL,Male,Caucasian,03/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/15/14 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +64145,74085,67116,PRETRIAL,Ramos,Samuel,NULL,Male,Caucasian,03/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/15/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64143,74082,67114,PRETRIAL,Martina,Darnell,NULL,Male,African-American,09/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +64143,74082,67114,PRETRIAL,Martina,Darnell,NULL,Male,African-American,09/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,4,High,8,Risk of Recidivism,0.11,8,High,New,1,0 +64143,74082,67114,PRETRIAL,Martina,Darnell,NULL,Male,African-American,09/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,4,High,18,Risk of Failure to Appear,12,1,Low,New,1,0 +37576,74075,67108,PRETRIAL,shaw,sandy,NULL,Male,African-American,12/12/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +37576,74075,67108,PRETRIAL,shaw,sandy,NULL,Male,African-American,12/12/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +37576,74075,67108,PRETRIAL,shaw,sandy,NULL,Male,African-American,12/12/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/15/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +40138,74111,67140,PRETRIAL,CARABALLO,STARLIN,NULL,Male,Hispanic,05/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +40138,74111,67140,PRETRIAL,CARABALLO,STARLIN,NULL,Male,Hispanic,05/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +40138,74111,67140,PRETRIAL,CARABALLO,STARLIN,NULL,Male,Hispanic,05/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +24450,74090,67119,PRETRIAL,MORALESMORALES,LUIS,NULL,Male,Hispanic,11/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +24450,74090,67119,PRETRIAL,MORALESMORALES,LUIS,NULL,Male,Hispanic,11/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +24450,74090,67119,PRETRIAL,MORALESMORALES,LUIS,NULL,Male,Hispanic,11/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58243,74103,67132,PRETRIAL,Reffner,Sire,NULL,Male,Caucasian,09/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +58243,74103,67132,PRETRIAL,Reffner,Sire,NULL,Male,Caucasian,09/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +58243,74103,67132,PRETRIAL,Reffner,Sire,NULL,Male,Caucasian,09/23/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64173,74119,67148,Probation,SAINTVICTOR,PATRICK,NULL,Male,African-American,11/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +64173,74119,67148,Probation,SAINTVICTOR,PATRICK,NULL,Male,African-American,11/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +64173,74119,67148,Probation,SAINTVICTOR,PATRICK,NULL,Male,African-American,11/13/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64154,74098,67127,PRETRIAL,Berringer,Lisa,Ann,Female,Caucasian,07/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/16/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +64154,74098,67127,PRETRIAL,Berringer,Lisa,Ann,Female,Caucasian,07/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +64154,74098,67127,PRETRIAL,Berringer,Lisa,Ann,Female,Caucasian,07/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64178,74124,67153,Probation,Ingrebeightson,Cynthia,NULL,Female,Caucasian,10/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +64178,74124,67153,Probation,Ingrebeightson,Cynthia,NULL,Female,Caucasian,10/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +64178,74124,67153,Probation,Ingrebeightson,Cynthia,NULL,Female,Caucasian,10/30/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64160,74106,67135,PRETRIAL,Dass,Carlamendra,NULL,Male,Other,10/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/16/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +64160,74106,67135,PRETRIAL,Dass,Carlamendra,NULL,Male,Other,10/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/16/14 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +64160,74106,67135,PRETRIAL,Dass,Carlamendra,NULL,Male,Other,10/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64150,74093,67122,PRETRIAL,LATIF,IYAD,EDMON,Male,Caucasian,12/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/16/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +64150,74093,67122,PRETRIAL,LATIF,IYAD,EDMON,Male,Caucasian,12/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/16/14 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +64150,74093,67122,PRETRIAL,LATIF,IYAD,EDMON,Male,Caucasian,12/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64171,74116,67145,Probation,comfort,David,NULL,Male,African-American,04/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +64171,74116,67145,Probation,comfort,David,NULL,Male,African-American,04/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +64171,74116,67145,Probation,comfort,David,NULL,Male,African-American,04/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64161,74107,67136,Probation,GREEN,KRISTEN,D,Female,Caucasian,03/29/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +64161,74107,67136,Probation,GREEN,KRISTEN,D,Female,Caucasian,03/29/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +64161,74107,67136,Probation,GREEN,KRISTEN,D,Female,Caucasian,03/29/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64148,74091,67120,PRETRIAL,RAMIRES,DIEGO,SILVA,Male,Other,12/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/16/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +64148,74091,67120,PRETRIAL,RAMIRES,DIEGO,SILVA,Male,Other,12/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +64148,74091,67120,PRETRIAL,RAMIRES,DIEGO,SILVA,Male,Other,12/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64166,74109,67138,Probation,Brescia,Joseph,NULL,Male,Caucasian,03/30/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/16/14 0:00,2,Medium,7,Risk of Violence,-2.73,2,Low,New,1,0 +64166,74109,67138,Probation,Brescia,Joseph,NULL,Male,Caucasian,03/30/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +64166,74109,67138,Probation,Brescia,Joseph,NULL,Male,Caucasian,03/30/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/16/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +5005,74088,4687,PRETRIAL,Nordelus,Rony,NULL,Male,African-American,02/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,Copy,1,0 +5005,74088,4687,PRETRIAL,Nordelus,Rony,NULL,Male,African-American,02/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.95,10,High,Copy,1,0 +5005,74088,4687,PRETRIAL,Nordelus,Rony,NULL,Male,African-American,02/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +64152,74095,67124,PRETRIAL,CUMMINGS,KERIE,ANTONIO,Male,Other,02/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/16/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +64152,74095,67124,PRETRIAL,CUMMINGS,KERIE,ANTONIO,Male,Other,02/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +64152,74095,67124,PRETRIAL,CUMMINGS,KERIE,ANTONIO,Male,Other,02/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64176,74121,67150,PRETRIAL,SHELDON,MICHAEL,NULL,Male,Caucasian,02/19/41,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-4.38,1,Low,New,1,0 +64176,74121,67150,PRETRIAL,SHELDON,MICHAEL,NULL,Male,Caucasian,02/19/41,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +64176,74121,67150,PRETRIAL,SHELDON,MICHAEL,NULL,Male,Caucasian,02/19/41,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64156,74100,67129,PRETRIAL,Kestler,Timothy,NULL,Male,Caucasian,04/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +64156,74100,67129,PRETRIAL,Kestler,Timothy,NULL,Male,Caucasian,04/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +64156,74100,67129,PRETRIAL,Kestler,Timothy,NULL,Male,Caucasian,04/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64149,74092,67121,PRETRIAL,Davis,Lesly,D,Male,African-American,10/17/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +64149,74092,67121,PRETRIAL,Davis,Lesly,D,Male,African-American,10/17/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +64149,74092,67121,PRETRIAL,Davis,Lesly,D,Male,African-American,10/17/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64168,74113,67142,Probation,JACOBWITZ,JOSHUA,ADAM,Male,Caucasian,04/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +64168,74113,67142,Probation,JACOBWITZ,JOSHUA,ADAM,Male,Caucasian,04/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +64168,74113,67142,Probation,JACOBWITZ,JOSHUA,ADAM,Male,Caucasian,04/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +18099,74087,17372,PRETRIAL,Randal,Ramsey,NULL,Male,African-American,03/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,Copy,1,0 +18099,74087,17372,PRETRIAL,Randal,Ramsey,NULL,Male,African-American,03/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,Copy,1,0 +18099,74087,17372,PRETRIAL,Randal,Ramsey,NULL,Male,African-American,03/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +64153,74096,67125,PRETRIAL,MERCADO,MARIMEL,FAVIOLA,Male,Hispanic,05/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +64153,74096,67125,PRETRIAL,MERCADO,MARIMEL,FAVIOLA,Male,Hispanic,05/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +64153,74096,67125,PRETRIAL,MERCADO,MARIMEL,FAVIOLA,Male,Hispanic,05/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57036,74117,67146,PRETRIAL,Morgan,Tiffany,Denise,Female,African-American,07/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +57036,74117,67146,PRETRIAL,Morgan,Tiffany,Denise,Female,African-American,07/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +57036,74117,67146,PRETRIAL,Morgan,Tiffany,Denise,Female,African-American,07/10/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64155,74099,67128,PRETRIAL,Davis,Turquora,Shamoka,Female,African-American,07/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +64155,74099,67128,PRETRIAL,Davis,Turquora,Shamoka,Female,African-American,07/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +64155,74099,67128,PRETRIAL,Davis,Turquora,Shamoka,Female,African-American,07/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64157,74101,67130,Probation,Herrera,Luis,Enriquee,Male,Hispanic,01/30/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/16/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +64157,74101,67130,Probation,Herrera,Luis,Enriquee,Male,Hispanic,01/30/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +64157,74101,67130,Probation,Herrera,Luis,Enriquee,Male,Hispanic,01/30/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64151,74094,67123,PRETRIAL,WADDICK,MICHAEL,WILLIAM,Male,Caucasian,12/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +64151,74094,67123,PRETRIAL,WADDICK,MICHAEL,WILLIAM,Male,Caucasian,12/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +64151,74094,67123,PRETRIAL,WADDICK,MICHAEL,WILLIAM,Male,Caucasian,12/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64165,74108,67137,PRETRIAL,Pettineo,Charles,NULL,Male,Caucasian,12/01/42,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +64165,74108,67137,PRETRIAL,Pettineo,Charles,NULL,Male,Caucasian,12/01/42,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-2.73,1,Low,New,1,0 +64165,74108,67137,PRETRIAL,Pettineo,Charles,NULL,Male,Caucasian,12/01/42,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +64172,74118,67147,PRETRIAL,hollis,patricia,NULL,Female,Caucasian,08/23/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/16/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +64172,74118,67147,PRETRIAL,hollis,patricia,NULL,Female,Caucasian,08/23/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +64172,74118,67147,PRETRIAL,hollis,patricia,NULL,Female,Caucasian,08/23/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64159,74105,67134,PRETRIAL,Gil,Michael,Anthony,Male,Caucasian,12/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,6/16/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +64159,74105,67134,PRETRIAL,Gil,Michael,Anthony,Male,Caucasian,12/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,6/16/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +64159,74105,67134,PRETRIAL,Gil,Michael,Anthony,Male,Caucasian,12/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64167,74112,67141,Probation,Morales,Xiomari,Luz,Female,Hispanic,09/23/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +64167,74112,67141,Probation,Morales,Xiomari,Luz,Female,Hispanic,09/23/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +64167,74112,67141,Probation,Morales,Xiomari,Luz,Female,Hispanic,09/23/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64179,74125,67154,PRETRIAL,Onarjai,Allen,NULL,Male,African-American,08/07/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +64179,74125,67154,PRETRIAL,Onarjai,Allen,NULL,Male,African-American,08/07/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,4,High,8,Risk of Recidivism,0.36,8,High,New,1,0 +64179,74125,67154,PRETRIAL,Onarjai,Allen,NULL,Male,African-American,08/07/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,4,High,18,Risk of Failure to Appear,23,4,Low,New,1,0 +56658,74097,67126,PRETRIAL,MARTIN,JANEY,NULL,Female,African-American,05/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +56658,74097,67126,PRETRIAL,MARTIN,JANEY,NULL,Female,African-American,05/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +56658,74097,67126,PRETRIAL,MARTIN,JANEY,NULL,Female,African-American,05/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/16/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64158,74104,67133,PRETRIAL,Sena,Jodie,NULL,Female,Caucasian,01/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,6/16/14 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +64158,74104,67133,PRETRIAL,Sena,Jodie,NULL,Female,Caucasian,01/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,6/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.33,7,Medium,New,1,0 +64158,74104,67133,PRETRIAL,Sena,Jodie,NULL,Female,Caucasian,01/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,6/16/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64174,74120,67149,Probation,Ayestastoledo,Nasser,NULL,Male,Hispanic,10/07/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/16/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +64174,74120,67149,Probation,Ayestastoledo,Nasser,NULL,Male,Hispanic,10/07/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/16/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +64174,74120,67149,Probation,Ayestastoledo,Nasser,NULL,Male,Hispanic,10/07/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59295,74102,67131,PRETRIAL,Fairbrother,Thomas,Roy,Male,Caucasian,01/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,New,1,0 +59295,74102,67131,PRETRIAL,Fairbrother,Thomas,Roy,Male,Caucasian,01/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +59295,74102,67131,PRETRIAL,Fairbrother,Thomas,Roy,Male,Caucasian,01/30/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +64147,74089,67118,PRETRIAL,Thompson,Amos,NULL,Male,Other,09/04/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/16/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +64147,74089,67118,PRETRIAL,Thompson,Amos,NULL,Male,Other,09/04/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/16/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +64147,74089,67118,PRETRIAL,Thompson,Amos,NULL,Male,Other,09/04/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64205,74157,67182,Probation,Previl,Stephyner,NULL,Male,African-American,01/28/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/17/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +64205,74157,67182,Probation,Previl,Stephyner,NULL,Male,African-American,01/28/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/17/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +64205,74157,67182,Probation,Previl,Stephyner,NULL,Male,African-American,01/28/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64188,74136,67164,PRETRIAL,Singh,Troy,NULL,Male,African-American,05/10/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +64188,74136,67164,PRETRIAL,Singh,Troy,NULL,Male,African-American,05/10/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,8,Risk of Recidivism,1.2,10,High,New,1,0 +64188,74136,67164,PRETRIAL,Singh,Troy,NULL,Male,African-American,05/10/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64183,74131,67159,PRETRIAL,Alexander,Frankie,Laine,Male,African-American,05/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +64183,74131,67159,PRETRIAL,Alexander,Frankie,Laine,Male,African-American,05/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,8,Risk of Recidivism,1.04,10,High,New,1,0 +64183,74131,67159,PRETRIAL,Alexander,Frankie,Laine,Male,African-American,05/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64198,74149,67175,Probation,OBSTBAUM,JULIO,J,Male,Hispanic,06/19/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/17/14 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +64198,74149,67175,Probation,OBSTBAUM,JULIO,J,Male,Hispanic,06/19/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/17/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +64198,74149,67175,Probation,OBSTBAUM,JULIO,J,Male,Hispanic,06/19/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64181,74128,67157,PRETRIAL,WALKER,CLIFFORD,BARN,Male,African-American,01/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +64181,74128,67157,PRETRIAL,WALKER,CLIFFORD,BARN,Male,African-American,01/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +64181,74128,67157,PRETRIAL,WALKER,CLIFFORD,BARN,Male,African-American,01/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64191,74141,67168,PRETRIAL,Pershadsingh,Amir,Rajkumar,Male,Native American,05/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +64191,74141,67168,PRETRIAL,Pershadsingh,Amir,Rajkumar,Male,Native American,05/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +64191,74141,67168,PRETRIAL,Pershadsingh,Amir,Rajkumar,Male,Native American,05/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64196,74154,67173,PRETRIAL,Givens,Justin,Kiel,Male,Caucasian,04/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,6/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,Copy,1,0 +64196,74154,67173,PRETRIAL,Givens,Justin,Kiel,Male,Caucasian,04/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,6/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,Copy,1,0 +64196,74154,67173,PRETRIAL,Givens,Justin,Kiel,Male,Caucasian,04/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,6/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +46002,74126,67155,PRETRIAL,Simmons,Jeffery,NULL,Male,African-American,10/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,7,Risk of Violence,-0.23,10,High,New,1,0 +46002,74126,67155,PRETRIAL,Simmons,Jeffery,NULL,Male,African-American,10/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,8,Risk of Recidivism,0.89,10,High,New,1,0 +46002,74126,67155,PRETRIAL,Simmons,Jeffery,NULL,Male,African-American,10/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +64190,74139,67166,PRETRIAL,Edwards,Martin,NULL,Male,African-American,11/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +64190,74139,67166,PRETRIAL,Edwards,Martin,NULL,Male,African-American,11/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +64190,74139,67166,PRETRIAL,Edwards,Martin,NULL,Male,African-American,11/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64195,74146,67172,Probation,Hill,Anthony,Darnell,Male,African-American,06/19/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/17/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +64195,74146,67172,Probation,Hill,Anthony,Darnell,Male,African-American,06/19/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +64195,74146,67172,Probation,Hill,Anthony,Darnell,Male,African-American,06/19/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/17/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64185,74133,67161,PRETRIAL,Sultan,Sean,Richard,Male,Caucasian,11/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +64185,74133,67161,PRETRIAL,Sultan,Sean,Richard,Male,Caucasian,11/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +64185,74133,67161,PRETRIAL,Sultan,Sean,Richard,Male,Caucasian,11/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63694,74143,66614,PRETRIAL,Brown,Travoris,NULL,Male,African-American,07/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,Copy,1,0 +63694,74143,66614,PRETRIAL,Brown,Travoris,NULL,Male,African-American,07/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,Copy,1,0 +63694,74143,66614,PRETRIAL,Brown,Travoris,NULL,Male,African-American,07/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +64182,74129,67158,PRETRIAL,SMART,ROBERT,NULL,Male,Caucasian,08/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +64182,74129,67158,PRETRIAL,SMART,ROBERT,NULL,Male,Caucasian,08/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +64182,74129,67158,PRETRIAL,SMART,ROBERT,NULL,Male,Caucasian,08/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64199,74150,67176,Probation,santospaulino,almenie,NULL,Female,African-American,06/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +64199,74150,67176,Probation,santospaulino,almenie,NULL,Female,African-American,06/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +64199,74150,67176,Probation,santospaulino,almenie,NULL,Female,African-American,06/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64201,74152,67178,PRETRIAL,Sansone,Robert,NULL,Male,Caucasian,10/08/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +64201,74152,67178,PRETRIAL,Sansone,Robert,NULL,Male,Caucasian,10/08/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +64201,74152,67178,PRETRIAL,Sansone,Robert,NULL,Male,Caucasian,10/08/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +64186,74134,67162,PRETRIAL,Johnson,Dalton,NULL,Male,Caucasian,03/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +64186,74134,67162,PRETRIAL,Johnson,Dalton,NULL,Male,Caucasian,03/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +64186,74134,67162,PRETRIAL,Johnson,Dalton,NULL,Male,Caucasian,03/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55918,74155,67180,PRETRIAL,De Paola,Giovanni,NULL,Male,Caucasian,09/30/69,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,6/17/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +55918,74155,67180,PRETRIAL,De Paola,Giovanni,NULL,Male,Caucasian,09/30/69,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,6/17/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +55918,74155,67180,PRETRIAL,De Paola,Giovanni,NULL,Male,Caucasian,09/30/69,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +49848,74138,56516,PRETRIAL,Henry,Neville,Paul,Male,African-American,11/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,Copy,1,0 +49848,74138,56516,PRETRIAL,Henry,Neville,Paul,Male,African-American,11/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,8,Risk of Recidivism,0.45,9,High,Copy,1,0 +49848,74138,56516,PRETRIAL,Henry,Neville,Paul,Male,African-American,11/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +64200,74151,67177,Probation,Langarica,Ainoa,NULL,Female,Hispanic,06/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +64200,74151,67177,Probation,Langarica,Ainoa,NULL,Female,Hispanic,06/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +64200,74151,67177,Probation,Langarica,Ainoa,NULL,Female,Hispanic,06/23/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +3036,74130,2749,PRETRIAL,CURRY,WAYNE,B,Male,African-American,02/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.46,1,Low,Copy,1,0 +3036,74130,2749,PRETRIAL,CURRY,WAYNE,B,Male,African-American,02/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,Copy,1,0 +3036,74130,2749,PRETRIAL,CURRY,WAYNE,B,Male,African-American,02/14/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +64204,74156,67181,Probation,Joseph,Jean,NULL,Male,Other,07/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +64204,74156,67181,Probation,Joseph,Jean,NULL,Male,Other,07/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +64204,74156,67181,Probation,Joseph,Jean,NULL,Male,Other,07/23/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64193,74142,67169,PRETRIAL,robinson,llotoya,NULL,Female,African-American,09/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +64193,74142,67169,PRETRIAL,robinson,llotoya,NULL,Female,African-American,09/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +64193,74142,67169,PRETRIAL,robinson,llotoya,NULL,Female,African-American,09/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64207,74160,67184,Probation,Villalobos,Alexander,NULL,Male,Hispanic,01/27/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/17/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +64207,74160,67184,Probation,Villalobos,Alexander,NULL,Male,Hispanic,01/27/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/17/14 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +64207,74160,67184,Probation,Villalobos,Alexander,NULL,Male,Hispanic,01/27/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64189,74137,67165,PRETRIAL,McAvinue,Walter,NULL,Male,Caucasian,06/11/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +64189,74137,67165,PRETRIAL,McAvinue,Walter,NULL,Male,Caucasian,06/11/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +64189,74137,67165,PRETRIAL,McAvinue,Walter,NULL,Male,Caucasian,06/11/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +64187,74135,67163,PRETRIAL,CHARLES,QUINCY,T,Male,African-American,06/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,7,Risk of Violence,-0.39,10,High,New,1,0 +64187,74135,67163,PRETRIAL,CHARLES,QUINCY,T,Male,African-American,06/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,8,Risk of Recidivism,0.66,10,High,New,1,0 +64187,74135,67163,PRETRIAL,CHARLES,QUINCY,T,Male,African-American,06/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59310,74144,67170,PRETRIAL,strowbridge,rebecca,NULL,Female,African-American,07/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +59310,74144,67170,PRETRIAL,strowbridge,rebecca,NULL,Female,African-American,07/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,8,High,New,1,0 +59310,74144,67170,PRETRIAL,strowbridge,rebecca,NULL,Female,African-American,07/23/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64206,74158,67183,Probation,henao,david,NULL,Male,Hispanic,10/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,New,1,0 +64206,74158,67183,Probation,henao,david,NULL,Male,Hispanic,10/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +64206,74158,67183,Probation,henao,david,NULL,Male,Hispanic,10/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64194,74145,67171,Probation,Stice,Lee,NULL,Male,Caucasian,01/11/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +64194,74145,67171,Probation,Stice,Lee,NULL,Male,Caucasian,01/11/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +64194,74145,67171,Probation,Stice,Lee,NULL,Male,Caucasian,01/11/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64180,74127,67156,PRETRIAL,JACKSON,ROBERT,NULL,Male,African-American,12/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.81,9,High,New,1,0 +64180,74127,67156,PRETRIAL,JACKSON,ROBERT,NULL,Male,African-American,12/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +64180,74127,67156,PRETRIAL,JACKSON,ROBERT,NULL,Male,African-American,12/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +64184,74132,67160,PRETRIAL,Lang,Juana,Maria,Female,Hispanic,03/13/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +64184,74132,67160,PRETRIAL,Lang,Juana,Maria,Female,Hispanic,03/13/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +64184,74132,67160,PRETRIAL,Lang,Juana,Maria,Female,Hispanic,03/13/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64202,74153,67179,Probation,patterson,torrey,NULL,Male,African-American,10/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +64202,74153,67179,Probation,patterson,torrey,NULL,Male,African-American,10/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +64202,74153,67179,Probation,patterson,torrey,NULL,Male,African-American,10/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64192,74140,67167,PRETRIAL,MEDINA,JOHNNY,NULL,Male,Caucasian,03/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +64192,74140,67167,PRETRIAL,MEDINA,JOHNNY,NULL,Male,Caucasian,03/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +64192,74140,67167,PRETRIAL,MEDINA,JOHNNY,NULL,Male,Caucasian,03/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/17/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64230,74190,67212,Probation,ALEZY,STEVE,NULL,Male,African-American,02/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,4,High,7,Risk of Violence,-0.67,9,High,New,1,0 +64230,74190,67212,Probation,ALEZY,STEVE,NULL,Male,African-American,02/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +64230,74190,67212,Probation,ALEZY,STEVE,NULL,Male,African-American,02/17/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +64208,74161,67185,PRETRIAL,Darlington,Jack,NULL,Male,African-American,04/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.54,3,Low,New,1,0 +64208,74161,67185,PRETRIAL,Darlington,Jack,NULL,Male,African-American,04/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +64208,74161,67185,PRETRIAL,Darlington,Jack,NULL,Male,African-American,04/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64221,74176,67199,PRETRIAL,RICHARDSON,PETER,NULL,Male,Caucasian,10/17/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/18/14 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +64221,74176,67199,PRETRIAL,RICHARDSON,PETER,NULL,Male,Caucasian,10/17/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/18/14 0:00,1,Low,8,Risk of Recidivism,-2.69,1,Low,New,1,0 +64221,74176,67199,PRETRIAL,RICHARDSON,PETER,NULL,Male,Caucasian,10/17/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64217,74169,67193,Probation,FLOWERS,HAROLD,NULL,Male,African-American,10/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +64217,74169,67193,Probation,FLOWERS,HAROLD,NULL,Male,African-American,10/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +64217,74169,67193,Probation,FLOWERS,HAROLD,NULL,Male,African-American,10/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64225,74184,67206,Probation,Martin,Tiara,Louise,Female,African-American,05/02/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +64225,74184,67206,Probation,Martin,Tiara,Louise,Female,African-American,05/02/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +64225,74184,67206,Probation,Martin,Tiara,Louise,Female,African-American,05/02/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +64214,74166,67190,PRETRIAL,SCHWARTZ,RICHARD,NULL,Male,Caucasian,01/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/18/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +64214,74166,67190,PRETRIAL,SCHWARTZ,RICHARD,NULL,Male,Caucasian,01/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/18/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +64214,74166,67190,PRETRIAL,SCHWARTZ,RICHARD,NULL,Male,Caucasian,01/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64228,74187,67209,Probation,webb,denise,NULL,Female,Caucasian,11/05/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/18/14 0:00,2,Medium,7,Risk of Violence,-3.2,1,Low,New,1,0 +64228,74187,67209,Probation,webb,denise,NULL,Female,Caucasian,11/05/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +64228,74187,67209,Probation,webb,denise,NULL,Female,Caucasian,11/05/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/18/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64220,74174,67198,Probation,RODRIGUEZ,SALLY,NULL,Female,Hispanic,10/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,6/18/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +64220,74174,67198,Probation,RODRIGUEZ,SALLY,NULL,Female,Hispanic,10/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,6/18/14 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +64220,74174,67198,Probation,RODRIGUEZ,SALLY,NULL,Female,Hispanic,10/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +56330,74195,67217,PRETRIAL,Hutchinson,Donald,Peart,Male,African-American,06/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.03,8,High,New,1,0 +56330,74195,67217,PRETRIAL,Hutchinson,Donald,Peart,Male,African-American,06/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +56330,74195,67217,PRETRIAL,Hutchinson,Donald,Peart,Male,African-American,06/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64233,74193,67215,Probation,Jorden,Andre,NULL,Male,African-American,11/07/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +64233,74193,67215,Probation,Jorden,Andre,NULL,Male,African-American,11/07/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +64233,74193,67215,Probation,Jorden,Andre,NULL,Male,African-American,11/07/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64213,74165,67189,Probation,coupanger,tammy,NULL,Female,Caucasian,01/30/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/14 0:00,2,Medium,7,Risk of Violence,-3.35,1,Low,New,1,0 +64213,74165,67189,Probation,coupanger,tammy,NULL,Female,Caucasian,01/30/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +64213,74165,67189,Probation,coupanger,tammy,NULL,Female,Caucasian,01/30/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64219,74172,67196,Probation,HODOSI,SANDOR,NULL,Male,Caucasian,04/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +64219,74172,67196,Probation,HODOSI,SANDOR,NULL,Male,Caucasian,04/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +64219,74172,67196,Probation,HODOSI,SANDOR,NULL,Male,Caucasian,04/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64227,74186,67208,Probation,Wims,Ebony,NULL,Female,African-American,02/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,2,Medium,7,Risk of Violence,-2.51,3,Low,New,1,0 +64227,74186,67208,Probation,Wims,Ebony,NULL,Female,African-American,02/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +64227,74186,67208,Probation,Wims,Ebony,NULL,Female,African-American,02/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64210,74163,67187,PRETRIAL,PEREIRA,FABIO,VALDEIR,Male,Hispanic,02/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/18/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +64210,74163,67187,PRETRIAL,PEREIRA,FABIO,VALDEIR,Male,Hispanic,02/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/18/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +64210,74163,67187,PRETRIAL,PEREIRA,FABIO,VALDEIR,Male,Hispanic,02/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +21025,74181,67203,PRETRIAL,Digraziano,Christopher,NULL,Male,Hispanic,09/10/80,17,All Scales,Intake,English,Other,Jail Inmate,Single,6/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.68,9,High,New,1,0 +21025,74181,67203,PRETRIAL,Digraziano,Christopher,NULL,Male,Hispanic,09/10/80,17,All Scales,Intake,English,Other,Jail Inmate,Single,6/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,7,Medium,New,1,0 +21025,74181,67203,PRETRIAL,Digraziano,Christopher,NULL,Male,Hispanic,09/10/80,17,All Scales,Intake,English,Other,Jail Inmate,Single,6/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,8,High,New,1,0 +64211,74164,67188,PRETRIAL,Hernandez,Ashley,NULL,Female,Caucasian,05/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +64211,74164,67188,PRETRIAL,Hernandez,Ashley,NULL,Female,Caucasian,05/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +64211,74164,67188,PRETRIAL,Hernandez,Ashley,NULL,Female,Caucasian,05/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +46012,74189,67211,PRETRIAL,Chacon,Theodore,NULL,Male,Caucasian,11/20/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,2,Medium,7,Risk of Violence,-2.95,1,Low,New,1,0 +46012,74189,67211,PRETRIAL,Chacon,Theodore,NULL,Male,Caucasian,11/20/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +46012,74189,67211,PRETRIAL,Chacon,Theodore,NULL,Male,Caucasian,11/20/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64216,74168,67192,Probation,Jackson,Brett,NULL,Male,Caucasian,04/11/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/18/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +64216,74168,67192,Probation,Jackson,Brett,NULL,Male,Caucasian,04/11/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/18/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +64216,74168,67192,Probation,Jackson,Brett,NULL,Male,Caucasian,04/11/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64226,74185,67207,PRETRIAL,OSBORNE,ROHAN,NULL,Male,African-American,04/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +64226,74185,67207,PRETRIAL,OSBORNE,ROHAN,NULL,Male,African-American,04/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,4,High,8,Risk of Recidivism,0.79,10,High,New,1,0 +64226,74185,67207,PRETRIAL,OSBORNE,ROHAN,NULL,Male,African-American,04/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +50117,74171,67195,PRETRIAL,TINEO,YAURICASA,SIXTO,Female,Oriental,02/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +50117,74171,67195,PRETRIAL,TINEO,YAURICASA,SIXTO,Female,Oriental,02/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +50117,74171,67195,PRETRIAL,TINEO,YAURICASA,SIXTO,Female,Oriental,02/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58882,74173,67197,PRETRIAL,Derose,Larry,NULL,Male,Caucasian,07/08/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,2,Medium,7,Risk of Violence,-2.98,1,Low,New,1,0 +58882,74173,67197,PRETRIAL,Derose,Larry,NULL,Male,Caucasian,07/08/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +58882,74173,67197,PRETRIAL,Derose,Larry,NULL,Male,Caucasian,07/08/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +44174,74180,67202,PRETRIAL,Newkirk,Joshua,NULL,Male,African-American,03/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +44174,74180,67202,PRETRIAL,Newkirk,Joshua,NULL,Male,African-American,03/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +44174,74180,67202,PRETRIAL,Newkirk,Joshua,NULL,Male,African-American,03/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +44174,56281,51177,PRETRIAL,Newkirk,Joshua,NULL,Male,African-American,03/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +44174,56281,51177,PRETRIAL,Newkirk,Joshua,NULL,Male,African-American,03/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +44174,56281,51177,PRETRIAL,Newkirk,Joshua,NULL,Male,African-American,03/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64234,74194,67216,Probation,Ireland,John,NULL,Male,African-American,05/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/14 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +64234,74194,67216,Probation,Ireland,John,NULL,Male,African-American,05/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/14 0:00,4,High,8,Risk of Recidivism,1.01,10,High,New,1,0 +64234,74194,67216,Probation,Ireland,John,NULL,Male,African-American,05/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/18/14 0:00,4,High,18,Risk of Failure to Appear,40,10,High,New,1,0 +64215,74167,67191,Probation,Bridgelal,Ricky,NULL,Male,Other,05/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +64215,74167,67191,Probation,Bridgelal,Ricky,NULL,Male,Other,05/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +64215,74167,67191,Probation,Bridgelal,Ricky,NULL,Male,Other,05/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62749,74175,65512,Probation,Pitchford,Sheldrick,juan,Male,African-American,07/17/77,17,All Scales,Intake,English,Other,Probation,Single,6/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.41,3,Low,New,1,0 +62749,74175,65512,Probation,Pitchford,Sheldrick,juan,Male,African-American,07/17/77,17,All Scales,Intake,English,Other,Probation,Single,6/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +62749,74175,65512,Probation,Pitchford,Sheldrick,juan,Male,African-American,07/17/77,17,All Scales,Intake,English,Other,Probation,Single,6/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,3,Low,New,1,0 +8162,74178,67201,PRETRIAL,PLUMMER,JOEL,LEE,Male,African-American,04/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +8162,74178,67201,PRETRIAL,PLUMMER,JOEL,LEE,Male,African-American,04/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +8162,74178,67201,PRETRIAL,PLUMMER,JOEL,LEE,Male,African-American,04/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/18/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +64231,74191,67213,PRETRIAL,Houtmann-Vacca,Jacqueline,NULL,Female,Hispanic,09/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/18/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +64231,74191,67213,PRETRIAL,Houtmann-Vacca,Jacqueline,NULL,Female,Hispanic,09/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/18/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +64231,74191,67213,PRETRIAL,Houtmann-Vacca,Jacqueline,NULL,Female,Hispanic,09/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64218,74170,67194,Probation,Fuller,John,NULL,Male,Caucasian,06/09/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.57,1,Low,New,1,0 +64218,74170,67194,Probation,Fuller,John,NULL,Male,Caucasian,06/09/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +64218,74170,67194,Probation,Fuller,John,NULL,Male,Caucasian,06/09/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64229,74188,67210,PRETRIAL,Cypress,Karen,Rose,Female,Other,07/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/14 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +64229,74188,67210,PRETRIAL,Cypress,Karen,Rose,Female,Other,07/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +64229,74188,67210,PRETRIAL,Cypress,Karen,Rose,Female,Other,07/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/18/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64224,74183,67205,Probation,almeida,izaltina,NULL,Female,Other,05/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,6/18/14 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +64224,74183,67205,Probation,almeida,izaltina,NULL,Female,Other,05/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,6/18/14 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +64224,74183,67205,Probation,almeida,izaltina,NULL,Female,Other,05/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64209,74162,67186,PRETRIAL,Legrand,Tanisha,Ertha,Female,African-American,11/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +64209,74162,67186,PRETRIAL,Legrand,Tanisha,Ertha,Female,African-American,11/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +64209,74162,67186,PRETRIAL,Legrand,Tanisha,Ertha,Female,African-American,11/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/18/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64235,74196,67218,PRETRIAL,Burch,Tarcy,NULL,Male,African-American,10/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +64235,74196,67218,PRETRIAL,Burch,Tarcy,NULL,Male,African-American,10/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +64235,74196,67218,PRETRIAL,Burch,Tarcy,NULL,Male,African-American,10/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64237,74199,67220,PRETRIAL,Jeangilles,Jean,P,Male,Other,12/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +64237,74199,67220,PRETRIAL,Jeangilles,Jean,P,Male,Other,12/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +64237,74199,67220,PRETRIAL,Jeangilles,Jean,P,Male,Other,12/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64244,74209,67229,Probation,VASQUEZ,RALDY,NULL,Male,Hispanic,08/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +64244,74209,67229,Probation,VASQUEZ,RALDY,NULL,Male,Hispanic,08/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +64244,74209,67229,Probation,VASQUEZ,RALDY,NULL,Male,Hispanic,08/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64257,74225,67244,Probation,negrette,adriana,NULL,Female,Hispanic,10/28/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/19/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +64257,74225,67244,Probation,negrette,adriana,NULL,Female,Hispanic,10/28/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +64257,74225,67244,Probation,negrette,adriana,NULL,Female,Hispanic,10/28/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +64240,74204,67225,Probation,OLIVER,KEITH,ALLEN,Male,Caucasian,08/24/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/19/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +64240,74204,67225,Probation,OLIVER,KEITH,ALLEN,Male,Caucasian,08/24/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +64240,74204,67225,Probation,OLIVER,KEITH,ALLEN,Male,Caucasian,08/24/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64252,74220,67239,Probation,hughes,james,NULL,Male,Caucasian,10/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +64252,74220,67239,Probation,hughes,james,NULL,Male,Caucasian,10/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +64252,74220,67239,Probation,hughes,james,NULL,Male,Caucasian,10/23/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64246,74212,67232,Probation,lamie,sherry,NULL,Female,Caucasian,10/08/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +64246,74212,67232,Probation,lamie,sherry,NULL,Female,Caucasian,10/08/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +64246,74212,67232,Probation,lamie,sherry,NULL,Female,Caucasian,10/08/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64243,74208,67228,PRETRIAL,ELLYN,TRACY,NULL,Female,Caucasian,09/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +64243,74208,67228,PRETRIAL,ELLYN,TRACY,NULL,Female,Caucasian,09/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +64243,74208,67228,PRETRIAL,ELLYN,TRACY,NULL,Female,Caucasian,09/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +34571,74215,33730,PRETRIAL,THARP,KENNETH,NULL,Male,Caucasian,03/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.74,2,Low,Copy,1,0 +34571,74215,33730,PRETRIAL,THARP,KENNETH,NULL,Male,Caucasian,03/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,Copy,1,0 +34571,74215,33730,PRETRIAL,THARP,KENNETH,NULL,Male,Caucasian,03/12/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,Copy,1,0 +64254,74222,67241,Probation,ETIENE,BERNADIN,NULL,Male,African-American,09/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +64254,74222,67241,Probation,ETIENE,BERNADIN,NULL,Male,African-American,09/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +64254,74222,67241,Probation,ETIENE,BERNADIN,NULL,Male,African-American,09/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59383,74229,67248,Probation,WILSON,BRIAN,A,Male,Hispanic,10/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/19/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +59383,74229,67248,Probation,WILSON,BRIAN,A,Male,Hispanic,10/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +59383,74229,67248,Probation,WILSON,BRIAN,A,Male,Hispanic,10/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64238,74201,67222,PRETRIAL,DiazSanchez,Diana,NULL,Female,Caucasian,01/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/19/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +64238,74201,67222,PRETRIAL,DiazSanchez,Diana,NULL,Female,Caucasian,01/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +64238,74201,67222,PRETRIAL,DiazSanchez,Diana,NULL,Female,Caucasian,01/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64256,74224,67243,Probation,SCHUPBACH,JOHN,E,Male,Caucasian,08/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +64256,74224,67243,Probation,SCHUPBACH,JOHN,E,Male,Caucasian,08/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +64256,74224,67243,Probation,SCHUPBACH,JOHN,E,Male,Caucasian,08/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64245,74210,67230,Probation,Mott,Nicholas,NULL,Male,Caucasian,05/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +64245,74210,67230,Probation,Mott,Nicholas,NULL,Male,Caucasian,05/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +64245,74210,67230,Probation,Mott,Nicholas,NULL,Male,Caucasian,05/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56089,74227,67246,Probation,daniels,TIFFANY,NULL,Female,African-American,11/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.39,3,Low,New,1,0 +56089,74227,67246,Probation,daniels,TIFFANY,NULL,Female,African-American,11/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,8,High,New,1,0 +56089,74227,67246,Probation,daniels,TIFFANY,NULL,Female,African-American,11/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +64258,74228,67247,PRETRIAL,MATHIEUX,MARIE,NULL,Female,African-American,10/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +64258,74228,67247,PRETRIAL,MATHIEUX,MARIE,NULL,Female,African-American,10/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +64258,74228,67247,PRETRIAL,MATHIEUX,MARIE,NULL,Female,African-American,10/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +49717,74198,50623,Probation,nelson,wayne,NULL,Male,African-American,11/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/19/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,Copy,1,0 +49717,74198,50623,Probation,nelson,wayne,NULL,Male,African-American,11/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,Copy,1,0 +49717,74198,50623,Probation,nelson,wayne,NULL,Male,African-American,11/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +64255,74223,67242,Probation,Matchanickal,John,NULL,Male,Asian,10/25/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/19/14 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +64255,74223,67242,Probation,Matchanickal,John,NULL,Male,Asian,10/25/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/19/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +64255,74223,67242,Probation,Matchanickal,John,NULL,Male,Asian,10/25/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64239,74202,67223,Probation,Hill,Felipe,NULL,Male,Hispanic,09/15/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +64239,74202,67223,Probation,Hill,Felipe,NULL,Male,Hispanic,09/15/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +64239,74202,67223,Probation,Hill,Felipe,NULL,Male,Hispanic,09/15/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64253,74219,67238,PRETRIAL,SELZ,MICHAEL,DAVID,Male,Caucasian,05/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +64253,74219,67238,PRETRIAL,SELZ,MICHAEL,DAVID,Male,Caucasian,05/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +64253,74219,67238,PRETRIAL,SELZ,MICHAEL,DAVID,Male,Caucasian,05/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +25871,27321,25023,Probation,marcetic,marko,NULL,Male,Caucasian,04/07/81,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,6/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +25871,27321,25023,Probation,marcetic,marko,NULL,Male,Caucasian,04/07/81,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,6/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +25871,27321,25023,Probation,marcetic,marko,NULL,Male,Caucasian,04/07/81,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,6/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64249,74216,67235,Probation,Marker,Cassandra,NULL,Female,Caucasian,11/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +64249,74216,67235,Probation,Marker,Cassandra,NULL,Female,Caucasian,11/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +64249,74216,67235,Probation,Marker,Cassandra,NULL,Female,Caucasian,11/18/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64242,74207,67227,Probation,thomas,lamonte,NULL,Male,African-American,12/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/19/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +64242,74207,67227,Probation,thomas,lamonte,NULL,Male,African-American,12/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +64242,74207,67227,Probation,thomas,lamonte,NULL,Male,African-American,12/08/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64247,74213,67233,Probation,Labranche,Rigaud,NULL,Male,African-American,05/15/70,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/19/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +64247,74213,67233,Probation,Labranche,Rigaud,NULL,Male,African-American,05/15/70,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +64247,74213,67233,Probation,Labranche,Rigaud,NULL,Male,African-American,05/15/70,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57539,74200,67221,PRETRIAL,COBB,HAVEARD,NULL,Male,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +57539,74200,67221,PRETRIAL,COBB,HAVEARD,NULL,Male,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +57539,74200,67221,PRETRIAL,COBB,HAVEARD,NULL,Male,African-American,07/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54915,74203,67224,PRETRIAL,Ebanks,Roxana,Alvarez,Female,Hispanic,06/28/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +54915,74203,67224,PRETRIAL,Ebanks,Roxana,Alvarez,Female,Hispanic,06/28/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +54915,74203,67224,PRETRIAL,Ebanks,Roxana,Alvarez,Female,Hispanic,06/28/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64251,74218,67237,Probation,Morsehead,Christie,NULL,Female,Caucasian,12/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +64251,74218,67237,Probation,Morsehead,Christie,NULL,Female,Caucasian,12/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +64251,74218,67237,Probation,Morsehead,Christie,NULL,Female,Caucasian,12/03/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +24625,74205,23799,PRETRIAL,Dormeis,Willeme,NULL,Male,Other,11/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/19/14 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,Copy,1,0 +24625,74205,23799,PRETRIAL,Dormeis,Willeme,NULL,Male,Other,11/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,Copy,1,0 +24625,74205,23799,PRETRIAL,Dormeis,Willeme,NULL,Male,Other,11/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/19/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +41636,74211,67231,PRETRIAL,Jackson,Garold,NULL,Male,African-American,10/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +41636,74211,67231,PRETRIAL,Jackson,Garold,NULL,Male,African-American,10/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +41636,74211,67231,PRETRIAL,Jackson,Garold,NULL,Male,African-American,10/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +48971,74226,67245,PRETRIAL,BOYER,CARIE,LYNN,Female,Caucasian,03/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +48971,74226,67245,PRETRIAL,BOYER,CARIE,LYNN,Female,Caucasian,03/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,4,High,8,Risk of Recidivism,0.29,9,High,New,1,0 +48971,74226,67245,PRETRIAL,BOYER,CARIE,LYNN,Female,Caucasian,03/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/19/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64236,74197,67219,PRETRIAL,Arnold,Wilbur,Q,Male,African-American,03/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +64236,74197,67219,PRETRIAL,Arnold,Wilbur,Q,Male,African-American,03/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +64236,74197,67219,PRETRIAL,Arnold,Wilbur,Q,Male,African-American,03/15/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/19/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +61079,74247,67263,PRETRIAL,ALAMO,MARK,NULL,Male,Hispanic,06/08/95,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +61079,74247,67263,PRETRIAL,ALAMO,MARK,NULL,Male,Hispanic,06/08/95,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,4,High,8,Risk of Recidivism,0.76,10,High,New,1,0 +61079,74247,67263,PRETRIAL,ALAMO,MARK,NULL,Male,Hispanic,06/08/95,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,4,High,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +64264,74239,67257,PRETRIAL,Haage,Kevin,NULL,Male,African-American,05/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +64264,74239,67257,PRETRIAL,Haage,Kevin,NULL,Male,African-American,05/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +64264,74239,67257,PRETRIAL,Haage,Kevin,NULL,Male,African-American,05/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64260,74234,67252,PRETRIAL,Ruffin,Octavius,NULL,Male,African-American,02/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +64260,74234,67252,PRETRIAL,Ruffin,Octavius,NULL,Male,African-American,02/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +64260,74234,67252,PRETRIAL,Ruffin,Octavius,NULL,Male,African-American,02/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64281,74268,67282,Probation,Pilger,Edwin,NULL,Male,Hispanic,03/06/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/20/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +64281,74268,67282,Probation,Pilger,Edwin,NULL,Male,Hispanic,03/06/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +64281,74268,67282,Probation,Pilger,Edwin,NULL,Male,Hispanic,03/06/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64272,74255,67270,PRETRIAL,cox,andre,NULL,Male,African-American,11/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +64272,74255,67270,PRETRIAL,cox,andre,NULL,Male,African-American,11/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +64272,74255,67270,PRETRIAL,cox,andre,NULL,Male,African-American,11/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58464,74242,67260,PRETRIAL,Pantaleon,Carlos,NULL,Male,Hispanic,06/12/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +58464,74242,67260,PRETRIAL,Pantaleon,Carlos,NULL,Male,Hispanic,06/12/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +58464,74242,67260,PRETRIAL,Pantaleon,Carlos,NULL,Male,Hispanic,06/12/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55996,74260,67274,Probation,busto,sergio,NULL,Male,Caucasian,05/14/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +55996,74260,67274,Probation,busto,sergio,NULL,Male,Caucasian,05/14/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +55996,74260,67274,Probation,busto,sergio,NULL,Male,Caucasian,05/14/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64263,74237,67255,PRETRIAL,Lee,Jeffrey,NULL,Male,African-American,01/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +64263,74237,67255,PRETRIAL,Lee,Jeffrey,NULL,Male,African-American,01/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +64263,74237,67255,PRETRIAL,Lee,Jeffrey,NULL,Male,African-American,01/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64261,74235,67253,PRETRIAL,Syzmanek,Daniel,NULL,Male,Caucasian,03/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +64261,74235,67253,PRETRIAL,Syzmanek,Daniel,NULL,Male,Caucasian,03/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +64261,74235,67253,PRETRIAL,Syzmanek,Daniel,NULL,Male,Caucasian,03/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64278,74265,67279,Probation,WOODARD,ANDREW,NULL,Male,African-American,10/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +64278,74265,67279,Probation,WOODARD,ANDREW,NULL,Male,African-American,10/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +64278,74265,67279,Probation,WOODARD,ANDREW,NULL,Male,African-American,10/13/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57162,74244,67261,PRETRIAL,Denonno,Michael,NULL,Male,Caucasian,05/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +57162,74244,67261,PRETRIAL,Denonno,Michael,NULL,Male,Caucasian,05/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +57162,74244,67261,PRETRIAL,Denonno,Michael,NULL,Male,Caucasian,05/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62780,74258,67268,Probation,Crafton,Immanuel,NULL,Male,African-American,05/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,Copy,1,0 +62780,74258,67268,Probation,Crafton,Immanuel,NULL,Male,African-American,05/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-0.39,4,Low,Copy,1,0 +62780,74258,67268,Probation,Crafton,Immanuel,NULL,Male,African-American,05/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,25,5,Medium,Copy,1,0 +62780,74253,67268,Probation,Crafton,Immanuel,NULL,Male,African-American,05/17/87,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +62780,74253,67268,Probation,Crafton,Immanuel,NULL,Male,African-American,05/17/87,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-0.39,4,Low,New,1,0 +62780,74253,67268,Probation,Crafton,Immanuel,NULL,Male,African-American,05/17/87,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +64283,74270,67284,Probation,Coyne,Jordan,NULL,Male,Caucasian,12/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +64283,74270,67284,Probation,Coyne,Jordan,NULL,Male,Caucasian,12/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +64283,74270,67284,Probation,Coyne,Jordan,NULL,Male,Caucasian,12/19/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64259,74232,67251,PRETRIAL,Blair,Denis,NULL,Male,Other,06/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +64259,74232,67251,PRETRIAL,Blair,Denis,NULL,Male,Other,06/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +64259,74232,67251,PRETRIAL,Blair,Denis,NULL,Male,Other,06/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64267,74245,67262,Probation,Foreman,Katherine,NULL,Female,Caucasian,01/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +64267,74245,67262,Probation,Foreman,Katherine,NULL,Female,Caucasian,01/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +64267,74245,67262,Probation,Foreman,Katherine,NULL,Female,Caucasian,01/29/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +16679,74231,67250,PRETRIAL,Lee,Kevin,NULL,Male,Other,04/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/20/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +16679,74231,67250,PRETRIAL,Lee,Kevin,NULL,Male,Other,04/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +16679,74231,67250,PRETRIAL,Lee,Kevin,NULL,Male,Other,04/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64262,74236,67254,PRETRIAL,Shannon,Jacklyn,NULL,Female,African-American,04/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +64262,74236,67254,PRETRIAL,Shannon,Jacklyn,NULL,Female,African-American,04/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +64262,74236,67254,PRETRIAL,Shannon,Jacklyn,NULL,Female,African-American,04/07/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64273,74257,67272,PRETRIAL,Brannon,Sam,Vernard,Male,African-American,04/26/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +64273,74257,67272,PRETRIAL,Brannon,Sam,Vernard,Male,African-American,04/26/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +64273,74257,67272,PRETRIAL,Brannon,Sam,Vernard,Male,African-American,04/26/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64276,74262,67276,Probation,reyes,anna,NULL,Female,Hispanic,05/02/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/20/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +64276,74262,67276,Probation,reyes,anna,NULL,Female,Hispanic,05/02/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +64276,74262,67276,Probation,reyes,anna,NULL,Female,Hispanic,05/02/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64279,74266,67280,PRETRIAL,gonzalez,frank,NULL,Male,Hispanic,12/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +64279,74266,67280,PRETRIAL,gonzalez,frank,NULL,Male,Hispanic,12/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +64279,74266,67280,PRETRIAL,gonzalez,frank,NULL,Male,Hispanic,12/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +64269,74250,67265,Probation,Porras,Jessica,NULL,Female,Hispanic,06/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +64269,74250,67265,Probation,Porras,Jessica,NULL,Female,Hispanic,06/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +64269,74250,67265,Probation,Porras,Jessica,NULL,Female,Hispanic,06/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64270,74252,67267,Probation,Archibald,Patricia,NULL,Female,Caucasian,05/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/20/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +64270,74252,67267,Probation,Archibald,Patricia,NULL,Female,Caucasian,05/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +64270,74252,67267,Probation,Archibald,Patricia,NULL,Female,Caucasian,05/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64284,74271,67285,Probation,McClure,Justin,william,Male,Caucasian,08/06/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +64284,74271,67285,Probation,McClure,Justin,william,Male,Caucasian,08/06/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +64284,74271,67285,Probation,McClure,Justin,william,Male,Caucasian,08/06/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +39731,74243,60097,PRETRIAL,FOLWER,MICHAEL,NULL,Male,African-American,11/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,Copy,1,0 +39731,74243,60097,PRETRIAL,FOLWER,MICHAEL,NULL,Male,African-American,11/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,9,High,Copy,1,0 +39731,74243,60097,PRETRIAL,FOLWER,MICHAEL,NULL,Male,African-American,11/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +62628,74233,65370,Probation,Thompson,Nykia,NULL,Male,African-American,06/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,4,High,7,Risk of Violence,-0.91,9,High,Copy,1,0 +62628,74233,65370,Probation,Thompson,Nykia,NULL,Male,African-American,06/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,4,High,8,Risk of Recidivism,1.05,10,High,Copy,1,0 +62628,74233,65370,Probation,Thompson,Nykia,NULL,Male,African-American,06/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +64280,74267,67281,PRETRIAL,Deleonrodriguez,Camila,NULL,Female,Hispanic,03/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/20/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +64280,74267,67281,PRETRIAL,Deleonrodriguez,Camila,NULL,Female,Hispanic,03/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +64280,74267,67281,PRETRIAL,Deleonrodriguez,Camila,NULL,Female,Hispanic,03/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64282,74269,67283,Probation,BRICE,KEVIN,NULL,Male,African-American,09/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +64282,74269,67283,Probation,BRICE,KEVIN,NULL,Male,African-American,09/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +64282,74269,67283,Probation,BRICE,KEVIN,NULL,Male,African-American,09/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64265,74240,67258,PRETRIAL,sconiers,jamila,NULL,Female,African-American,08/09/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +64265,74240,67258,PRETRIAL,sconiers,jamila,NULL,Female,African-American,08/09/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +64265,74240,67258,PRETRIAL,sconiers,jamila,NULL,Female,African-American,08/09/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64271,74254,67269,Probation,Mcfaddenjackson,Ann,NULL,Female,African-American,10/16/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/20/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +64271,74254,67269,Probation,Mcfaddenjackson,Ann,NULL,Female,African-American,10/16/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +64271,74254,67269,Probation,Mcfaddenjackson,Ann,NULL,Female,African-American,10/16/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58037,74261,67275,Probation,Mtchell,John,NULL,Male,Caucasian,11/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,6/20/14 0:00,2,Medium,7,Risk of Violence,-2.97,1,Low,New,1,0 +58037,74261,67275,Probation,Mtchell,John,NULL,Male,Caucasian,11/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,6/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +58037,74261,67275,Probation,Mtchell,John,NULL,Male,Caucasian,11/03/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,6/20/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +29716,74238,67256,PRETRIAL,laffiteau,Guillermo,N,Male,Hispanic,05/23/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +29716,74238,67256,PRETRIAL,laffiteau,Guillermo,N,Male,Hispanic,05/23/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +29716,74238,67256,PRETRIAL,laffiteau,Guillermo,N,Male,Hispanic,05/23/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56347,74256,67271,PRETRIAL,Margison,Angela,NULL,Female,Caucasian,02/04/61,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,6/20/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +56347,74256,67271,PRETRIAL,Margison,Angela,NULL,Female,Caucasian,02/04/61,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,6/20/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +56347,74256,67271,PRETRIAL,Margison,Angela,NULL,Female,Caucasian,02/04/61,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +27025,74230,67249,PRETRIAL,dessources,shmide,jeanbaptiste,Male,Other,10/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/20/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +27025,74230,67249,PRETRIAL,dessources,shmide,jeanbaptiste,Male,Other,10/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +27025,74230,67249,PRETRIAL,dessources,shmide,jeanbaptiste,Male,Other,10/11/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64277,74264,67278,Probation,Gutierrez,Nelson,NULL,Male,Hispanic,11/08/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/20/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +64277,74264,67278,Probation,Gutierrez,Nelson,NULL,Male,Hispanic,11/08/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/20/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +64277,74264,67278,Probation,Gutierrez,Nelson,NULL,Male,Hispanic,11/08/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54443,74251,67266,PRETRIAL,YOUNG,MONIQUE,NULL,Female,Caucasian,07/13/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/20/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +54443,74251,67266,PRETRIAL,YOUNG,MONIQUE,NULL,Female,Caucasian,07/13/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/20/14 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +54443,74251,67266,PRETRIAL,YOUNG,MONIQUE,NULL,Female,Caucasian,07/13/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64296,74285,67298,PRETRIAL,Oliveira,Marcos,Antonio,Male,Caucasian,02/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +64296,74285,67298,PRETRIAL,Oliveira,Marcos,Antonio,Male,Caucasian,02/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +64296,74285,67298,PRETRIAL,Oliveira,Marcos,Antonio,Male,Caucasian,02/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64290,74277,67291,PRETRIAL,Edwards,Devaughn,Ignatius,Male,African-American,07/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,4,High,7,Risk of Violence,-0.76,9,High,New,1,0 +64290,74277,67291,PRETRIAL,Edwards,Devaughn,Ignatius,Male,African-American,07/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,4,High,8,Risk of Recidivism,0.84,10,High,New,1,0 +64290,74277,67291,PRETRIAL,Edwards,Devaughn,Ignatius,Male,African-American,07/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64288,74275,67289,PRETRIAL,HICKMAN,THOMAS,JR,Male,African-American,06/23/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/21/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +64288,74275,67289,PRETRIAL,HICKMAN,THOMAS,JR,Male,African-American,06/23/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/21/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +64288,74275,67289,PRETRIAL,HICKMAN,THOMAS,JR,Male,African-American,06/23/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/21/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60425,74282,62867,PRETRIAL,Lee,Dewayne,Ingraham,Male,African-American,02/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,4,High,7,Risk of Violence,-1.04,8,High,Copy,1,0 +60425,74282,62867,PRETRIAL,Lee,Dewayne,Ingraham,Male,African-American,02/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,4,High,8,Risk of Recidivism,0.28,8,High,Copy,1,0 +60425,74282,62867,PRETRIAL,Lee,Dewayne,Ingraham,Male,African-American,02/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +64286,74273,67287,PRETRIAL,LOUISSAINT,LOUTESS,NULL,Male,Other,11/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +64286,74273,67287,PRETRIAL,LOUISSAINT,LOUTESS,NULL,Male,Other,11/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +64286,74273,67287,PRETRIAL,LOUISSAINT,LOUTESS,NULL,Male,Other,11/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64292,74280,67294,PRETRIAL,TRUMP,ARTHUR,A,Male,Caucasian,11/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +64292,74280,67294,PRETRIAL,TRUMP,ARTHUR,A,Male,Caucasian,11/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +64292,74280,67294,PRETRIAL,TRUMP,ARTHUR,A,Male,Caucasian,11/20/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64294,74283,67296,PRETRIAL,LOUISJEUNE,BARCLAY,NULL,Male,African-American,09/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +64294,74283,67296,PRETRIAL,LOUISJEUNE,BARCLAY,NULL,Male,African-American,09/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +64294,74283,67296,PRETRIAL,LOUISJEUNE,BARCLAY,NULL,Male,African-American,09/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +58388,74278,67292,PRETRIAL,Cooper,Martez,keith,Male,African-American,05/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +58388,74278,67292,PRETRIAL,Cooper,Martez,keith,Male,African-American,05/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +58388,74278,67292,PRETRIAL,Cooper,Martez,keith,Male,African-American,05/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64287,74274,67288,PRETRIAL,HARRIS,MARTIN,HOGAN,Male,African-American,05/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +64287,74274,67288,PRETRIAL,HARRIS,MARTIN,HOGAN,Male,African-American,05/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +64287,74274,67288,PRETRIAL,HARRIS,MARTIN,HOGAN,Male,African-American,05/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64285,74272,67286,PRETRIAL,DEPAIVA,EDVALDO,NULL,Male,Other,08/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +64285,74272,67286,PRETRIAL,DEPAIVA,EDVALDO,NULL,Male,Other,08/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +64285,74272,67286,PRETRIAL,DEPAIVA,EDVALDO,NULL,Male,Other,08/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64291,74279,67293,PRETRIAL,Lumas,Jacksin,NULL,Male,African-American,09/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +64291,74279,67293,PRETRIAL,Lumas,Jacksin,NULL,Male,African-American,09/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +64291,74279,67293,PRETRIAL,Lumas,Jacksin,NULL,Male,African-American,09/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64293,74281,67295,PRETRIAL,Butler,Chantelle,NULL,Female,African-American,08/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +64293,74281,67295,PRETRIAL,Butler,Chantelle,NULL,Female,African-American,08/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,10,High,New,1,0 +64293,74281,67295,PRETRIAL,Butler,Chantelle,NULL,Female,African-American,08/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64295,74284,67297,PRETRIAL,Dauphin,Rochenel,NULL,Male,Other,03/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/21/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +64295,74284,67297,PRETRIAL,Dauphin,Rochenel,NULL,Male,Other,03/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/21/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +64295,74284,67297,PRETRIAL,Dauphin,Rochenel,NULL,Male,Other,03/15/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64289,74276,67290,PRETRIAL,Murray,Shaniqua,Lashaye,Female,African-American,12/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,4,High,7,Risk of Violence,-0.66,9,High,New,1,0 +64289,74276,67290,PRETRIAL,Murray,Shaniqua,Lashaye,Female,African-American,12/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,4,High,8,Risk of Recidivism,0.61,10,High,New,1,0 +64289,74276,67290,PRETRIAL,Murray,Shaniqua,Lashaye,Female,African-American,12/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/21/14 0:00,4,High,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +27809,74297,26907,DRRD,Andrews,Dorothy,NULL,Female,Caucasian,02/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,Copy,1,0 +27809,74297,26907,DRRD,Andrews,Dorothy,NULL,Female,Caucasian,02/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,8,Risk of Recidivism,-0.57,5,Medium,Copy,1,0 +27809,74297,26907,DRRD,Andrews,Dorothy,NULL,Female,Caucasian,02/06/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +64311,74304,67315,PRETRIAL,TAYLOR,WAYNE,BERNARD,Male,African-American,08/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,New,1,0 +64311,74304,67315,PRETRIAL,TAYLOR,WAYNE,BERNARD,Male,African-American,08/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +64311,74304,67315,PRETRIAL,TAYLOR,WAYNE,BERNARD,Male,African-American,08/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +64299,74289,67302,PRETRIAL,BARNES,STACEY,NULL,Female,Caucasian,02/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,New,1,0 +64299,74289,67302,PRETRIAL,BARNES,STACEY,NULL,Female,Caucasian,02/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,8,High,New,1,0 +64299,74289,67302,PRETRIAL,BARNES,STACEY,NULL,Female,Caucasian,02/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +64309,74302,67313,PRETRIAL,cruz,tomas,NULL,Male,Caucasian,06/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +64309,74302,67313,PRETRIAL,cruz,tomas,NULL,Male,Caucasian,06/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +64309,74302,67313,PRETRIAL,cruz,tomas,NULL,Male,Caucasian,06/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64303,74293,67306,PRETRIAL,JACKSON,DAVID,NULL,Male,Caucasian,09/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +64303,74293,67306,PRETRIAL,JACKSON,DAVID,NULL,Male,Caucasian,09/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +64303,74293,67306,PRETRIAL,JACKSON,DAVID,NULL,Male,Caucasian,09/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64297,74286,67299,PRETRIAL,GUZMAN,FIDEL,NULL,Male,Caucasian,02/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/22/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +64297,74286,67299,PRETRIAL,GUZMAN,FIDEL,NULL,Male,Caucasian,02/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/22/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +64297,74286,67299,PRETRIAL,GUZMAN,FIDEL,NULL,Male,Caucasian,02/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64298,74288,67301,PRETRIAL,THOMAS,MICHAEL,LANARD,Male,African-American,10/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +64298,74288,67301,PRETRIAL,THOMAS,MICHAEL,LANARD,Male,African-American,10/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +64298,74288,67301,PRETRIAL,THOMAS,MICHAEL,LANARD,Male,African-American,10/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64305,74295,67308,PRETRIAL,SIMON,LOUINEL,NULL,Male,Other,05/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/22/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +64305,74295,67308,PRETRIAL,SIMON,LOUINEL,NULL,Male,Other,05/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/22/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +64305,74295,67308,PRETRIAL,SIMON,LOUINEL,NULL,Male,Other,05/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64301,74291,67304,PRETRIAL,MOYA,LUIS,JOSE,Male,Caucasian,08/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +64301,74291,67304,PRETRIAL,MOYA,LUIS,JOSE,Male,Caucasian,08/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +64301,74291,67304,PRETRIAL,MOYA,LUIS,JOSE,Male,Caucasian,08/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64302,74300,67305,PRETRIAL,WHEELER,JAMES,ALLAN,Male,Caucasian,01/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,Copy,1,0 +64302,74300,67305,PRETRIAL,WHEELER,JAMES,ALLAN,Male,Caucasian,01/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,Copy,1,0 +64302,74300,67305,PRETRIAL,WHEELER,JAMES,ALLAN,Male,Caucasian,01/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +64302,74292,67305,PRETRIAL,WHEELER,JAMES,ALLAN,Male,Caucasian,01/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +64302,74292,67305,PRETRIAL,WHEELER,JAMES,ALLAN,Male,Caucasian,01/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +64302,74292,67305,PRETRIAL,WHEELER,JAMES,ALLAN,Male,Caucasian,01/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64308,74299,67311,PRETRIAL,MCFARLANE,ROLLAND,S,Male,African-American,03/04/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/22/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +64308,74299,67311,PRETRIAL,MCFARLANE,ROLLAND,S,Male,African-American,03/04/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/22/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +64308,74299,67311,PRETRIAL,MCFARLANE,ROLLAND,S,Male,African-American,03/04/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +29408,74287,67300,PRETRIAL,DANIELS,SYLVESTER,NULL,Male,African-American,04/26/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +29408,74287,67300,PRETRIAL,DANIELS,SYLVESTER,NULL,Male,African-American,04/26/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +29408,74287,67300,PRETRIAL,DANIELS,SYLVESTER,NULL,Male,African-American,04/26/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64306,74296,67309,PRETRIAL,CARRILLO,ROBERTO,NULL,Male,Hispanic,08/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/22/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +64306,74296,67309,PRETRIAL,CARRILLO,ROBERTO,NULL,Male,Hispanic,08/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/22/14 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +64306,74296,67309,PRETRIAL,CARRILLO,ROBERTO,NULL,Male,Hispanic,08/27/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +36680,74301,67312,PRETRIAL,Jones,Robert,NULL,Male,African-American,03/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,4,High,7,Risk of Violence,-0.54,10,High,New,1,0 +36680,74301,67312,PRETRIAL,Jones,Robert,NULL,Male,African-American,03/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +36680,74301,67312,PRETRIAL,Jones,Robert,NULL,Male,African-American,03/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64304,74294,67307,PRETRIAL,CUBAS,JULIO,RICARDO,Male,Hispanic,12/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/22/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +64304,74294,67307,PRETRIAL,CUBAS,JULIO,RICARDO,Male,Hispanic,12/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/22/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +64304,74294,67307,PRETRIAL,CUBAS,JULIO,RICARDO,Male,Hispanic,12/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64310,74303,67314,PRETRIAL,ALCIME,EVENS,NULL,Male,African-American,12/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.03,8,High,New,1,0 +64310,74303,67314,PRETRIAL,ALCIME,EVENS,NULL,Male,African-American,12/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +64310,74303,67314,PRETRIAL,ALCIME,EVENS,NULL,Male,African-American,12/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64300,74290,67303,PRETRIAL,TAYLOR,JERMAINE,NULL,Male,African-American,04/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +64300,74290,67303,PRETRIAL,TAYLOR,JERMAINE,NULL,Male,African-American,04/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +64300,74290,67303,PRETRIAL,TAYLOR,JERMAINE,NULL,Male,African-American,04/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64307,74298,67310,PRETRIAL,HINES,CHRITIAN,DEAN,Male,Caucasian,06/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +64307,74298,67310,PRETRIAL,HINES,CHRITIAN,DEAN,Male,Caucasian,06/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +64307,74298,67310,PRETRIAL,HINES,CHRITIAN,DEAN,Male,Caucasian,06/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64335,74332,67343,PRETRIAL,Grant,Jehmiah,NULL,Male,African-American,07/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +64335,74332,67343,PRETRIAL,Grant,Jehmiah,NULL,Male,African-American,07/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,4,High,8,Risk of Recidivism,0.37,9,High,New,1,0 +64335,74332,67343,PRETRIAL,Grant,Jehmiah,NULL,Male,African-American,07/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64324,74319,67330,Probation,Amachree,Dateme,NULL,Male,African-American,11/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/23/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +64324,74319,67330,Probation,Amachree,Dateme,NULL,Male,African-American,11/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/23/14 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +64324,74319,67330,Probation,Amachree,Dateme,NULL,Male,African-American,11/07/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53661,74327,67338,PRETRIAL,Soto,Jessica,NULL,Female,Hispanic,03/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +53661,74327,67338,PRETRIAL,Soto,Jessica,NULL,Female,Hispanic,03/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +53661,74327,67338,PRETRIAL,Soto,Jessica,NULL,Female,Hispanic,03/02/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64313,74306,67317,PRETRIAL,GITTA,JEFFREY,CARSON,Male,Caucasian,10/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +64313,74306,67317,PRETRIAL,GITTA,JEFFREY,CARSON,Male,Caucasian,10/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +64313,74306,67317,PRETRIAL,GITTA,JEFFREY,CARSON,Male,Caucasian,10/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64329,74324,67335,PRETRIAL,Remlinger,Richard,NULL,Male,Caucasian,04/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/23/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +64329,74324,67335,PRETRIAL,Remlinger,Richard,NULL,Male,Caucasian,04/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/23/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +64329,74324,67335,PRETRIAL,Remlinger,Richard,NULL,Male,Caucasian,04/26/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64342,74340,67351,Probation,louis,Darryl,Michael,Male,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/23/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +64342,74340,67351,Probation,louis,Darryl,Michael,Male,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +64342,74340,67351,Probation,louis,Darryl,Michael,Male,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/23/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64316,74308,67319,PRETRIAL,DONEGAL,ALTON,O,Male,Other,02/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/23/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +64316,74308,67319,PRETRIAL,DONEGAL,ALTON,O,Male,Other,02/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/23/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +64316,74308,67319,PRETRIAL,DONEGAL,ALTON,O,Male,Other,02/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64357,74343,67354,Probation,Rosazza,Eddie,NULL,Male,Hispanic,07/05/80,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/23/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +64357,74343,67354,Probation,Rosazza,Eddie,NULL,Male,Hispanic,07/05/80,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/23/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +64357,74343,67354,Probation,Rosazza,Eddie,NULL,Male,Hispanic,07/05/80,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59165,74315,67326,Probation,Ungerland,Joseph,NULL,Male,Caucasian,11/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +59165,74315,67326,Probation,Ungerland,Joseph,NULL,Male,Caucasian,11/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +59165,74315,67326,Probation,Ungerland,Joseph,NULL,Male,Caucasian,11/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64327,74322,67333,Probation,Louis,Steven,NULL,Male,African-American,05/04/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +64327,74322,67333,Probation,Louis,Steven,NULL,Male,African-American,05/04/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +64327,74322,67333,Probation,Louis,Steven,NULL,Male,African-American,05/04/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +45950,74329,67340,PRETRIAL,Pacifico,Richard,NULL,Male,Caucasian,11/10/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +45950,74329,67340,PRETRIAL,Pacifico,Richard,NULL,Male,Caucasian,11/10/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +45950,74329,67340,PRETRIAL,Pacifico,Richard,NULL,Male,Caucasian,11/10/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64323,74317,67328,PRETRIAL,ZBEDA,DAVID,NULL,Male,Caucasian,11/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/23/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +64323,74317,67328,PRETRIAL,ZBEDA,DAVID,NULL,Male,Caucasian,11/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/23/14 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +64323,74317,67328,PRETRIAL,ZBEDA,DAVID,NULL,Male,Caucasian,11/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64337,74334,67345,Probation,Bolanos,Cesar,NULL,Male,Hispanic,08/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +64337,74334,67345,Probation,Bolanos,Cesar,NULL,Male,Hispanic,08/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +64337,74334,67345,Probation,Bolanos,Cesar,NULL,Male,Hispanic,08/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64321,74313,67324,PRETRIAL,Hawkins,Duane,Lamar,Male,African-American,12/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +64321,74313,67324,PRETRIAL,Hawkins,Duane,Lamar,Male,African-American,12/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +64321,74313,67324,PRETRIAL,Hawkins,Duane,Lamar,Male,African-American,12/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64340,74338,67349,Probation,Silva,Custodio,NULL,Male,Hispanic,12/25/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/23/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +64340,74338,67349,Probation,Silva,Custodio,NULL,Male,Hispanic,12/25/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/23/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +64340,74338,67349,Probation,Silva,Custodio,NULL,Male,Hispanic,12/25/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64326,74321,67332,PRETRIAL,Maldonado,Cristina,NULL,Female,Hispanic,01/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/23/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +64326,74321,67332,PRETRIAL,Maldonado,Cristina,NULL,Female,Hispanic,01/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/23/14 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +64326,74321,67332,PRETRIAL,Maldonado,Cristina,NULL,Female,Hispanic,01/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64333,74330,67341,Probation,atwell,xavier,NULL,Male,African-American,12/24/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +64333,74330,67341,Probation,atwell,xavier,NULL,Male,African-American,12/24/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +64333,74330,67341,Probation,atwell,xavier,NULL,Male,African-American,12/24/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64317,74309,67320,PRETRIAL,BENITEZ,OLIVIA,DIONE,Female,Caucasian,07/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +64317,74309,67320,PRETRIAL,BENITEZ,OLIVIA,DIONE,Female,Caucasian,07/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +64317,74309,67320,PRETRIAL,BENITEZ,OLIVIA,DIONE,Female,Caucasian,07/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57372,74342,67353,Probation,Pitter,Derrick,NULL,Male,African-American,06/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +57372,74342,67353,Probation,Pitter,Derrick,NULL,Male,African-American,06/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +57372,74342,67353,Probation,Pitter,Derrick,NULL,Male,African-American,06/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +25071,74335,67346,PRETRIAL,JORDAN,DERRICK,NULL,Male,African-American,09/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,New,1,0 +25071,74335,67346,PRETRIAL,JORDAN,DERRICK,NULL,Male,African-American,09/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +25071,74335,67346,PRETRIAL,JORDAN,DERRICK,NULL,Male,African-American,09/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64339,74337,67348,Probation,Piccirilli,Gary,NULL,Male,Other,05/06/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +64339,74337,67348,Probation,Piccirilli,Gary,NULL,Male,Other,05/06/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +64339,74337,67348,Probation,Piccirilli,Gary,NULL,Male,Other,05/06/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64315,74307,67318,PRETRIAL,Smith,Cheryl,Ann,Female,Caucasian,12/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +64315,74307,67318,PRETRIAL,Smith,Cheryl,Ann,Female,Caucasian,12/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +64315,74307,67318,PRETRIAL,Smith,Cheryl,Ann,Female,Caucasian,12/08/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57167,74314,67325,Probation,Lucas,Lester,NULL,Male,African-American,12/25/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +57167,74314,67325,Probation,Lucas,Lester,NULL,Male,African-American,12/25/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +57167,74314,67325,Probation,Lucas,Lester,NULL,Male,African-American,12/25/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64338,74336,67347,PRETRIAL,Dooley,Sue,NULL,Female,Caucasian,04/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,6/23/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +64338,74336,67347,PRETRIAL,Dooley,Sue,NULL,Female,Caucasian,04/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,6/23/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +64338,74336,67347,PRETRIAL,Dooley,Sue,NULL,Female,Caucasian,04/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64328,74323,67334,Probation,VILLABOLOS,GERMAN,NULL,Male,Hispanic,12/04/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +64328,74323,67334,Probation,VILLABOLOS,GERMAN,NULL,Male,Hispanic,12/04/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +64328,74323,67334,Probation,VILLABOLOS,GERMAN,NULL,Male,Hispanic,12/04/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64334,74331,67342,Probation,Williams,Avery,Dexter,Male,African-American,05/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +64334,74331,67342,Probation,Williams,Avery,Dexter,Male,African-American,05/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +64334,74331,67342,Probation,Williams,Avery,Dexter,Male,African-American,05/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64318,74310,67321,PRETRIAL,BRYANT,SHEARA,NULL,Female,African-American,03/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/23/14 0:00,2,Medium,7,Risk of Violence,-3.62,1,Low,New,1,0 +64318,74310,67321,PRETRIAL,BRYANT,SHEARA,NULL,Female,African-American,03/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +64318,74310,67321,PRETRIAL,BRYANT,SHEARA,NULL,Female,African-American,03/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/23/14 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +64330,74325,67336,Probation,zaccaro,christine,NULL,Female,Caucasian,06/14/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +64330,74325,67336,Probation,zaccaro,christine,NULL,Female,Caucasian,06/14/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +64330,74325,67336,Probation,zaccaro,christine,NULL,Female,Caucasian,06/14/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +64331,74326,67337,PRETRIAL,Zambrana,Erick,Josue,Male,Hispanic,08/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/23/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +64331,74326,67337,PRETRIAL,Zambrana,Erick,Josue,Male,Hispanic,08/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/23/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +64331,74326,67337,PRETRIAL,Zambrana,Erick,Josue,Male,Hispanic,08/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50913,74318,67329,PRETRIAL,Augustin,James,NULL,Male,African-American,07/23/85,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/23/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +50913,74318,67329,PRETRIAL,Augustin,James,NULL,Male,African-American,07/23/85,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/23/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +50913,74318,67329,PRETRIAL,Augustin,James,NULL,Male,African-American,07/23/85,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64325,74320,67331,PRETRIAL,picken,william,NULL,Male,Caucasian,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +64325,74320,67331,PRETRIAL,picken,william,NULL,Male,Caucasian,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +64325,74320,67331,PRETRIAL,picken,william,NULL,Male,Caucasian,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64336,74333,67344,PRETRIAL,ROBINSON,BENNY,L,Male,African-American,06/18/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/23/14 0:00,1,Low,7,Risk of Violence,-4.38,1,Low,New,1,0 +64336,74333,67344,PRETRIAL,ROBINSON,BENNY,L,Male,African-American,06/18/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/23/14 0:00,1,Low,8,Risk of Recidivism,-2.78,1,Low,New,1,0 +64336,74333,67344,PRETRIAL,ROBINSON,BENNY,L,Male,African-American,06/18/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64312,74305,67316,PRETRIAL,WHEELER,RAYMOND,NULL,Male,African-American,01/16/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/23/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +64312,74305,67316,PRETRIAL,WHEELER,RAYMOND,NULL,Male,African-American,01/16/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/23/14 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +64312,74305,67316,PRETRIAL,WHEELER,RAYMOND,NULL,Male,African-American,01/16/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64320,74312,67323,PRETRIAL,Deacy,Johsua,NULL,Male,Caucasian,07/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +64320,74312,67323,PRETRIAL,Deacy,Johsua,NULL,Male,Caucasian,07/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +64320,74312,67323,PRETRIAL,Deacy,Johsua,NULL,Male,Caucasian,07/05/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64356,74341,67352,Probation,Roberts,Jeffrey,NULL,Male,Caucasian,04/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +64356,74341,67352,Probation,Roberts,Jeffrey,NULL,Male,Caucasian,04/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +64356,74341,67352,Probation,Roberts,Jeffrey,NULL,Male,Caucasian,04/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64360,74346,67357,PRETRIAL,LOTT,ANDRE,NULL,Male,African-American,09/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/24/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +64360,74346,67357,PRETRIAL,LOTT,ANDRE,NULL,Male,African-American,09/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/24/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +64360,74346,67357,PRETRIAL,LOTT,ANDRE,NULL,Male,African-American,09/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64374,74362,67372,Probation,Umana,raul,NULL,Male,Hispanic,11/15/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/24/14 0:00,1,Low,7,Risk of Violence,-4.37,1,Low,New,1,0 +64374,74362,67372,Probation,Umana,raul,NULL,Male,Hispanic,11/15/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/24/14 0:00,1,Low,8,Risk of Recidivism,-2.58,1,Low,New,1,0 +64374,74362,67372,Probation,Umana,raul,NULL,Male,Hispanic,11/15/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64381,74375,67381,Probation,VEDRINE,MULLER,NULL,Male,African-American,11/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +64381,74375,67381,Probation,VEDRINE,MULLER,NULL,Male,African-American,11/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +64381,74375,67381,Probation,VEDRINE,MULLER,NULL,Male,African-American,11/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64361,74347,67358,PRETRIAL,Williams,Earl,E,Male,African-American,07/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/24/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +64361,74347,67358,PRETRIAL,Williams,Earl,E,Male,African-American,07/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/24/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +64361,74347,67358,PRETRIAL,Williams,Earl,E,Male,African-American,07/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64368,74354,67365,PRETRIAL,Brown,Denny,Hoyt,Male,Caucasian,04/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +64368,74354,67365,PRETRIAL,Brown,Denny,Hoyt,Male,Caucasian,04/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +64368,74354,67365,PRETRIAL,Brown,Denny,Hoyt,Male,Caucasian,04/02/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64383,74378,67384,Probation,VELASQUEZ,NOEHMI,CRISTAL,Male,Hispanic,10/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +64383,74378,67384,Probation,VELASQUEZ,NOEHMI,CRISTAL,Male,Hispanic,10/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +64383,74378,67384,Probation,VELASQUEZ,NOEHMI,CRISTAL,Male,Hispanic,10/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64363,74349,67360,PRETRIAL,Lemon,Dilica,NULL,Female,African-American,09/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +64363,74349,67360,PRETRIAL,Lemon,Dilica,NULL,Female,African-American,09/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +64363,74349,67360,PRETRIAL,Lemon,Dilica,NULL,Female,African-American,09/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +60877,74357,63367,PRETRIAL,Antolick,Keith,NULL,Male,Caucasian,06/19/52,17,All Scales,Intake,English,Other,Probation,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,Copy,1,0 +60877,74357,63367,PRETRIAL,Antolick,Keith,NULL,Male,Caucasian,06/19/52,17,All Scales,Intake,English,Other,Probation,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,Copy,1,0 +60877,74357,63367,PRETRIAL,Antolick,Keith,NULL,Male,Caucasian,06/19/52,17,All Scales,Intake,English,Other,Probation,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +21398,74370,67376,PRETRIAL,BOSTIC,NICHOLAS,NULL,Male,African-American,09/04/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +21398,74370,67376,PRETRIAL,BOSTIC,NICHOLAS,NULL,Male,African-American,09/04/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +21398,74370,67376,PRETRIAL,BOSTIC,NICHOLAS,NULL,Male,African-American,09/04/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +64358,74344,67355,PRETRIAL,CORTES,ABRAHAM,NULL,Male,Hispanic,12/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +64358,74344,67355,PRETRIAL,CORTES,ABRAHAM,NULL,Male,Hispanic,12/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +64358,74344,67355,PRETRIAL,CORTES,ABRAHAM,NULL,Male,Hispanic,12/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64371,74358,67368,PRETRIAL,ANDREWS,ANTHONY,NULL,Male,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,New,1,0 +64371,74358,67368,PRETRIAL,ANDREWS,ANTHONY,NULL,Male,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.07,10,High,New,1,0 +64371,74358,67368,PRETRIAL,ANDREWS,ANTHONY,NULL,Male,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64376,74365,67374,Probation,Miller,Dorian,NULL,Female,Caucasian,05/30/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/24/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +64376,74365,67374,Probation,Miller,Dorian,NULL,Female,Caucasian,05/30/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/24/14 0:00,1,Low,8,Risk of Recidivism,-2.72,1,Low,New,1,0 +64376,74365,67374,Probation,Miller,Dorian,NULL,Female,Caucasian,05/30/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64378,74372,67378,Probation,eugene,jovenel,NULL,Male,African-American,02/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +64378,74372,67378,Probation,eugene,jovenel,NULL,Male,African-American,02/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +64378,74372,67378,Probation,eugene,jovenel,NULL,Male,African-American,02/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64384,74379,67385,PRETRIAL,Minnifield,Tiffany,NULL,Male,African-American,05/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +64384,74379,67385,PRETRIAL,Minnifield,Tiffany,NULL,Male,African-American,05/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +64384,74379,67385,PRETRIAL,Minnifield,Tiffany,NULL,Male,African-American,05/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64373,74360,67370,PRETRIAL,Branker,Clynton,NULL,Male,Other,05/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/24/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +64373,74360,67370,PRETRIAL,Branker,Clynton,NULL,Male,Other,05/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/24/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +64373,74360,67370,PRETRIAL,Branker,Clynton,NULL,Male,Other,05/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64382,74377,67383,PRETRIAL,Kallis,Kevin,NULL,Male,Caucasian,12/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/14 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +64382,74377,67383,PRETRIAL,Kallis,Kevin,NULL,Male,Caucasian,12/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +64382,74377,67383,PRETRIAL,Kallis,Kevin,NULL,Male,Caucasian,12/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64370,74356,67367,PRETRIAL,Foreman,Rorey,David,Male,Other,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +64370,74356,67367,PRETRIAL,Foreman,Rorey,David,Male,Other,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +64370,74356,67367,PRETRIAL,Foreman,Rorey,David,Male,Other,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64375,74363,67373,PRETRIAL,Veras,Justin,NULL,Male,Caucasian,01/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +64375,74363,67373,PRETRIAL,Veras,Justin,NULL,Male,Caucasian,01/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +64375,74363,67373,PRETRIAL,Veras,Justin,NULL,Male,Caucasian,01/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64365,74351,67362,PRETRIAL,Henry,Austin,NULL,Male,African-American,10/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +64365,74351,67362,PRETRIAL,Henry,Austin,NULL,Male,African-American,10/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,4,High,8,Risk of Recidivism,0.71,10,High,New,1,0 +64365,74351,67362,PRETRIAL,Henry,Austin,NULL,Male,African-American,10/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64372,74359,67369,PRETRIAL,Seigel,Lawrence,Scott,Male,Caucasian,03/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/24/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +64372,74359,67369,PRETRIAL,Seigel,Lawrence,Scott,Male,Caucasian,03/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/24/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +64372,74359,67369,PRETRIAL,Seigel,Lawrence,Scott,Male,Caucasian,03/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +22632,23738,21809,PRETRIAL,CASANOVA-COSTA,RAUL,NULL,Male,Hispanic,08/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +22632,23738,21809,PRETRIAL,CASANOVA-COSTA,RAUL,NULL,Male,Hispanic,08/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +22632,23738,21809,PRETRIAL,CASANOVA-COSTA,RAUL,NULL,Male,Hispanic,08/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64369,74355,67366,PRETRIAL,Lewis,Vincent,Shane,Male,Other,10/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/24/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +64369,74355,67366,PRETRIAL,Lewis,Vincent,Shane,Male,Other,10/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/24/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +64369,74355,67366,PRETRIAL,Lewis,Vincent,Shane,Male,Other,10/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53547,74364,55043,PRETRIAL,Shore,Jay,NULL,Male,Caucasian,01/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,Copy,1,0 +53547,74364,55043,PRETRIAL,Shore,Jay,NULL,Male,Caucasian,01/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,Copy,1,0 +53547,74364,55043,PRETRIAL,Shore,Jay,NULL,Male,Caucasian,01/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +64364,74350,67361,PRETRIAL,Coleman,Nichole,NULL,Female,African-American,09/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/24/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +64364,74350,67361,PRETRIAL,Coleman,Nichole,NULL,Female,African-American,09/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/24/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +64364,74350,67361,PRETRIAL,Coleman,Nichole,NULL,Female,African-American,09/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +64366,74352,67363,PRETRIAL,Omar,Manal,Abou,Female,Caucasian,03/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/24/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +64366,74352,67363,PRETRIAL,Omar,Manal,Abou,Female,Caucasian,03/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/24/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +64366,74352,67363,PRETRIAL,Omar,Manal,Abou,Female,Caucasian,03/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64377,74371,67377,Probation,Delatorre,lino,NULL,Male,Hispanic,10/23/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/24/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +64377,74371,67377,Probation,Delatorre,lino,NULL,Male,Hispanic,10/23/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/24/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +64377,74371,67377,Probation,Delatorre,lino,NULL,Male,Hispanic,10/23/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64379,74373,67379,Probation,Negron,Paul,Ken,Male,Hispanic,03/06/69,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/24/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +64379,74373,67379,Probation,Negron,Paul,Ken,Male,Hispanic,03/06/69,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/24/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +64379,74373,67379,Probation,Negron,Paul,Ken,Male,Hispanic,03/06/69,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64385,74380,67386,PRETRIAL,WILLIS,LASHAVER,L,Male,African-American,05/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +64385,74380,67386,PRETRIAL,WILLIS,LASHAVER,L,Male,African-American,05/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,4,High,8,Risk of Recidivism,1.33,10,High,New,1,0 +64385,74380,67386,PRETRIAL,WILLIS,LASHAVER,L,Male,African-American,05/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62248,74361,67371,Probation,collins,neiman marcus,jonathan,Male,African-American,04/10/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.94,9,High,New,1,0 +62248,74361,67371,Probation,collins,neiman marcus,jonathan,Male,African-American,04/10/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +62248,74361,67371,Probation,collins,neiman marcus,jonathan,Male,African-American,04/10/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +6665,74376,67382,Probation,Sacco,Dino,NULL,Male,Caucasian,10/22/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +6665,74376,67382,Probation,Sacco,Dino,NULL,Male,Caucasian,10/22/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +6665,74376,67382,Probation,Sacco,Dino,NULL,Male,Caucasian,10/22/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58289,74369,67375,PRETRIAL,Bailey,Leroy,NULL,Male,Other,05/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +58289,74369,67375,PRETRIAL,Bailey,Leroy,NULL,Male,Other,05/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +58289,74369,67375,PRETRIAL,Bailey,Leroy,NULL,Male,Other,05/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64362,74348,67359,PRETRIAL,Holland,Thomas,Alan,Male,Caucasian,12/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +64362,74348,67359,PRETRIAL,Holland,Thomas,Alan,Male,Caucasian,12/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +64362,74348,67359,PRETRIAL,Holland,Thomas,Alan,Male,Caucasian,12/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64380,74374,67380,PRETRIAL,ford,christopher,NULL,Male,African-American,09/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +64380,74374,67380,PRETRIAL,ford,christopher,NULL,Male,African-American,09/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +64380,74374,67380,PRETRIAL,ford,christopher,NULL,Male,African-American,09/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64359,74345,67356,PRETRIAL,DALHOUSE,CHRISTINA,LEE,Female,Caucasian,10/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/24/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +64359,74345,67356,PRETRIAL,DALHOUSE,CHRISTINA,LEE,Female,Caucasian,10/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/24/14 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +64359,74345,67356,PRETRIAL,DALHOUSE,CHRISTINA,LEE,Female,Caucasian,10/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64367,74353,67364,PRETRIAL,Tinoco,Carlos,NULL,Male,Caucasian,09/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +64367,74353,67364,PRETRIAL,Tinoco,Carlos,NULL,Male,Caucasian,09/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +64367,74353,67364,PRETRIAL,Tinoco,Carlos,NULL,Male,Caucasian,09/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64390,74387,67392,PRETRIAL,Jean,Louvens,NULL,Male,African-American,10/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.02,8,High,New,1,0 +64390,74387,67392,PRETRIAL,Jean,Louvens,NULL,Male,African-American,10/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +64390,74387,67392,PRETRIAL,Jean,Louvens,NULL,Male,African-American,10/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +43854,74400,67404,PRETRIAL,Vanterpool,keyshawn,NULL,Male,African-American,12/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +43854,74400,67404,PRETRIAL,Vanterpool,keyshawn,NULL,Male,African-American,12/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +43854,74400,67404,PRETRIAL,Vanterpool,keyshawn,NULL,Male,African-American,12/11/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64395,74392,67396,PRETRIAL,Rodriguez,Antonio,NULL,Male,Hispanic,09/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/25/14 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +64395,74392,67396,PRETRIAL,Rodriguez,Antonio,NULL,Male,Hispanic,09/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +64395,74392,67396,PRETRIAL,Rodriguez,Antonio,NULL,Male,Hispanic,09/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/25/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64397,74395,67399,PRETRIAL,Galarce,Paulo,NULL,Male,Caucasian,04/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +64397,74395,67399,PRETRIAL,Galarce,Paulo,NULL,Male,Caucasian,04/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +64397,74395,67399,PRETRIAL,Galarce,Paulo,NULL,Male,Caucasian,04/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64409,74413,67414,PRETRIAL,Gabriel,Devonne,NULL,Male,African-American,11/08/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +64409,74413,67414,PRETRIAL,Gabriel,Devonne,NULL,Male,African-American,11/08/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.51,4,Low,New,1,0 +64409,74413,67414,PRETRIAL,Gabriel,Devonne,NULL,Male,African-American,11/08/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64386,74382,67387,PRETRIAL,Miles,Latasha,Emmanicol,Female,African-American,02/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +64386,74382,67387,PRETRIAL,Miles,Latasha,Emmanicol,Female,African-American,02/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +64386,74382,67387,PRETRIAL,Miles,Latasha,Emmanicol,Female,African-American,02/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64404,74405,67409,PRETRIAL,Billie,Nathan,Darryl,Male,Other,02/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/25/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +64404,74405,67409,PRETRIAL,Billie,Nathan,Darryl,Male,Other,02/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +64404,74405,67409,PRETRIAL,Billie,Nathan,Darryl,Male,Other,02/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/25/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64388,74384,67389,PRETRIAL,Williams,Jeffrey,NULL,Male,African-American,10/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +64388,74384,67389,PRETRIAL,Williams,Jeffrey,NULL,Male,African-American,10/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +64388,74384,67389,PRETRIAL,Williams,Jeffrey,NULL,Male,African-American,10/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64402,74403,67407,PRETRIAL,Cummings,Pedro,NULL,Male,African-American,10/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +64402,74403,67407,PRETRIAL,Cummings,Pedro,NULL,Male,African-American,10/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +64402,74403,67407,PRETRIAL,Cummings,Pedro,NULL,Male,African-American,10/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64408,74411,67413,Probation,TRIPP,DANIEL,JAMES,Male,Caucasian,06/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +64408,74411,67413,Probation,TRIPP,DANIEL,JAMES,Male,Caucasian,06/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +64408,74411,67413,Probation,TRIPP,DANIEL,JAMES,Male,Caucasian,06/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64394,74390,67395,PRETRIAL,Whyte,Catherine,NULL,Male,Caucasian,10/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +64394,74390,67395,PRETRIAL,Whyte,Catherine,NULL,Male,Caucasian,10/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +64394,74390,67395,PRETRIAL,Whyte,Catherine,NULL,Male,Caucasian,10/02/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +49911,74397,67401,PRETRIAL,Delgado,Mike,NULL,Male,Caucasian,08/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,6/25/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +49911,74397,67401,PRETRIAL,Delgado,Mike,NULL,Male,Caucasian,08/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,6/25/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +49911,74397,67401,PRETRIAL,Delgado,Mike,NULL,Male,Caucasian,08/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64401,74401,67405,Probation,SARAVIA,NERVIS,CAROLIONA,Female,Hispanic,12/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +64401,74401,67405,Probation,SARAVIA,NERVIS,CAROLIONA,Female,Hispanic,12/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +64401,74401,67405,Probation,SARAVIA,NERVIS,CAROLIONA,Female,Hispanic,12/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63858,73701,66781,PRETRIAL,LESTER,LORI,NULL,Female,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/25/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +63858,73701,66781,PRETRIAL,LESTER,LORI,NULL,Female,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/25/14 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +63858,73701,66781,PRETRIAL,LESTER,LORI,NULL,Female,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +36034,74408,35278,PRETRIAL,Rozier,Demetrius,Levon,Male,African-American,12/31/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,Copy,1,0 +36034,74408,35278,PRETRIAL,Rozier,Demetrius,Levon,Male,African-American,12/31/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,Copy,1,0 +36034,74408,35278,PRETRIAL,Rozier,Demetrius,Levon,Male,African-American,12/31/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +64396,74394,67398,PRETRIAL,Wright,Melvin,NULL,Male,African-American,05/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +64396,74394,67398,PRETRIAL,Wright,Melvin,NULL,Male,African-American,05/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +64396,74394,67398,PRETRIAL,Wright,Melvin,NULL,Male,African-American,05/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64393,74389,67394,PRETRIAL,Tobar,Patrick,Brian,Male,Caucasian,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/25/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +64393,74389,67394,PRETRIAL,Tobar,Patrick,Brian,Male,Caucasian,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/25/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +64393,74389,67394,PRETRIAL,Tobar,Patrick,Brian,Male,Caucasian,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64389,74385,67390,PRETRIAL,REYES,JONATHAN,NULL,Male,Caucasian,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/25/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +64389,74385,67390,PRETRIAL,REYES,JONATHAN,NULL,Male,Caucasian,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +64389,74385,67390,PRETRIAL,REYES,JONATHAN,NULL,Male,Caucasian,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/25/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64407,74410,67412,Probation,Burns,Diane,NULL,Female,Caucasian,02/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +64407,74410,67412,Probation,Burns,Diane,NULL,Female,Caucasian,02/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +64407,74410,67412,Probation,Burns,Diane,NULL,Female,Caucasian,02/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64405,74406,67410,Probation,ocampo,arlette,NULL,Female,Hispanic,03/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +64405,74406,67410,Probation,ocampo,arlette,NULL,Female,Hispanic,03/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +64405,74406,67410,Probation,ocampo,arlette,NULL,Female,Hispanic,03/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,2,Medium,18,Risk of Failure to Appear,30,9,High,New,1,0 +2423,74402,67406,Probation,Mascola,Jonathan,R,Male,Caucasian,08/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +2423,74402,67406,Probation,Mascola,Jonathan,R,Male,Caucasian,08/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +2423,74402,67406,Probation,Mascola,Jonathan,R,Male,Caucasian,08/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64399,74398,67402,Probation,McDonald,Kevin,NULL,Male,Caucasian,12/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +64399,74398,67402,Probation,McDonald,Kevin,NULL,Male,Caucasian,12/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +64399,74398,67402,Probation,McDonald,Kevin,NULL,Male,Caucasian,12/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +31078,74381,30091,PRETRIAL,Bell,Tawan,NULL,Male,African-American,08/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/25/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,Copy,1,0 +31078,74381,30091,PRETRIAL,Bell,Tawan,NULL,Male,African-American,08/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,Copy,1,0 +31078,74381,30091,PRETRIAL,Bell,Tawan,NULL,Male,African-American,08/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,6/25/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +63858,74407,66781,PRETRIAL,LESTER,LORI,NULL,Female,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/25/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,Copy,1,0 +63858,74407,66781,PRETRIAL,LESTER,LORI,NULL,Female,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/25/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,Copy,1,0 +63858,74407,66781,PRETRIAL,LESTER,LORI,NULL,Female,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +64410,74414,67415,Probation,Henrich,Robert,NULL,Male,Caucasian,11/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +64410,74414,67415,Probation,Henrich,Robert,NULL,Male,Caucasian,11/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +64410,74414,67415,Probation,Henrich,Robert,NULL,Male,Caucasian,11/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64391,74386,67391,PRETRIAL,Collins,Christopher,Anthony,Male,African-American,10/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.98,9,High,New,1,0 +64391,74386,67391,PRETRIAL,Collins,Christopher,Anthony,Male,African-American,10/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +64391,74386,67391,PRETRIAL,Collins,Christopher,Anthony,Male,African-American,10/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +47265,74391,47788,Probation,LEVINS,JOSEPH,NULL,Male,African-American,03/16/81,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +47265,74391,47788,Probation,LEVINS,JOSEPH,NULL,Male,African-American,03/16/81,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,2,Medium,8,Risk of Recidivism,0.13,7,Medium,Copy,1,0 +47265,74391,47788,Probation,LEVINS,JOSEPH,NULL,Male,African-American,03/16/81,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,2,Medium,18,Risk of Failure to Appear,27,6,Medium,Copy,1,0 +64398,74396,67400,PRETRIAL,Potter,Troy,Douglas,Male,Caucasian,03/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +64398,74396,67400,PRETRIAL,Potter,Troy,Douglas,Male,Caucasian,03/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +64398,74396,67400,PRETRIAL,Potter,Troy,Douglas,Male,Caucasian,03/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64392,74388,67393,PRETRIAL,James,Oliver,A,Male,African-American,01/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +64392,74388,67393,PRETRIAL,James,Oliver,A,Male,African-American,01/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +64392,74388,67393,PRETRIAL,James,Oliver,A,Male,African-American,01/06/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64400,74399,67403,Probation,Jordan,Kimberly,NULL,Female,Caucasian,04/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +64400,74399,67403,Probation,Jordan,Kimberly,NULL,Female,Caucasian,04/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +64400,74399,67403,Probation,Jordan,Kimberly,NULL,Female,Caucasian,04/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +46217,74409,67411,PRETRIAL,Figueroa,Licet,NULL,Female,Caucasian,12/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +46217,74409,67411,PRETRIAL,Figueroa,Licet,NULL,Female,Caucasian,12/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +46217,74409,67411,PRETRIAL,Figueroa,Licet,NULL,Female,Caucasian,12/04/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +64387,74383,67388,PRETRIAL,Perli,Gustavo,Simon,Male,Caucasian,02/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/25/14 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +64387,74383,67388,PRETRIAL,Perli,Gustavo,Simon,Male,Caucasian,02/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/25/14 0:00,1,Low,8,Risk of Recidivism,-2.69,1,Low,New,1,0 +64387,74383,67388,PRETRIAL,Perli,Gustavo,Simon,Male,Caucasian,02/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64403,74404,67408,PRETRIAL,Bhuiyan,Mokiader,NULL,Male,Asian,09/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +64403,74404,67408,PRETRIAL,Bhuiyan,Mokiader,NULL,Male,Asian,09/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +64403,74404,67408,PRETRIAL,Bhuiyan,Mokiader,NULL,Male,Asian,09/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/25/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +62562,74412,65288,Probation,Grinion,Dwight,NULL,Male,African-American,10/20/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.11,8,High,New,1,0 +62562,74412,65288,Probation,Grinion,Dwight,NULL,Male,African-American,10/20/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,7,Medium,New,1,0 +62562,74412,65288,Probation,Grinion,Dwight,NULL,Male,African-American,10/20/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64420,74425,67425,PRETRIAL,Infante,Leopoldo,NULL,Male,Hispanic,08/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/26/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +64420,74425,67425,PRETRIAL,Infante,Leopoldo,NULL,Male,Hispanic,08/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/26/14 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +64420,74425,67425,PRETRIAL,Infante,Leopoldo,NULL,Male,Hispanic,08/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64426,74433,67432,PRETRIAL,Hernandez,Daniel,NULL,Male,Hispanic,03/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +64426,74433,67432,PRETRIAL,Hernandez,Daniel,NULL,Male,Hispanic,03/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +64426,74433,67432,PRETRIAL,Hernandez,Daniel,NULL,Male,Hispanic,03/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64431,74440,67438,Probation,Hansen,Thomas,NULL,Male,Hispanic,12/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +64431,74440,67438,Probation,Hansen,Thomas,NULL,Male,Hispanic,12/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +64431,74440,67438,Probation,Hansen,Thomas,NULL,Male,Hispanic,12/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64432,74441,67439,Probation,rosati,sergio,NULL,Male,Caucasian,11/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +64432,74441,67439,Probation,rosati,sergio,NULL,Male,Caucasian,11/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +64432,74441,67439,Probation,rosati,sergio,NULL,Male,Caucasian,11/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64435,74446,67444,Probation,church,tammy,NULL,Female,Caucasian,01/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +64435,74446,67444,Probation,church,tammy,NULL,Female,Caucasian,01/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +64435,74446,67444,Probation,church,tammy,NULL,Female,Caucasian,01/28/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64437,74448,67446,Probation,rafeca,walter,NULL,Male,Caucasian,09/08/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +64437,74448,67446,Probation,rafeca,walter,NULL,Male,Caucasian,09/08/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +64437,74448,67446,Probation,rafeca,walter,NULL,Male,Caucasian,09/08/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64416,74420,67421,PRETRIAL,RamirezCampo,Daniela,NULL,Female,Hispanic,02/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +64416,74420,67421,PRETRIAL,RamirezCampo,Daniela,NULL,Female,Hispanic,02/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +64416,74420,67421,PRETRIAL,RamirezCampo,Daniela,NULL,Female,Hispanic,02/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64430,74438,67436,Probation,KUSTELEGA,CARMEN,NULL,Male,Caucasian,09/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +64430,74438,67436,Probation,KUSTELEGA,CARMEN,NULL,Male,Caucasian,09/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +64430,74438,67436,Probation,KUSTELEGA,CARMEN,NULL,Male,Caucasian,09/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64411,74417,67418,PRETRIAL,DEAMGELO,CAITO,NULL,Male,African-American,06/01/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +64411,74417,67418,PRETRIAL,DEAMGELO,CAITO,NULL,Male,African-American,06/01/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +64411,74417,67418,PRETRIAL,DEAMGELO,CAITO,NULL,Male,African-American,06/01/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64440,74451,67449,PRETRIAL,Mills,Travis,Duran,Male,African-American,01/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +64440,74451,67449,PRETRIAL,Mills,Travis,Duran,Male,African-American,01/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +64440,74451,67449,PRETRIAL,Mills,Travis,Duran,Male,African-American,01/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +55671,74435,67426,PRETRIAL,Smitley,Robert,NULL,Male,Caucasian,03/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,Copy,1,0 +55671,74435,67426,PRETRIAL,Smitley,Robert,NULL,Male,Caucasian,03/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,Copy,1,0 +55671,74435,67426,PRETRIAL,Smitley,Robert,NULL,Male,Caucasian,03/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +64429,74437,67435,PRETRIAL,Jean-Louis,Kerry,NULL,Male,African-American,04/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +64429,74437,67435,PRETRIAL,Jean-Louis,Kerry,NULL,Male,African-American,04/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +64429,74437,67435,PRETRIAL,Jean-Louis,Kerry,NULL,Male,African-American,04/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64413,74416,67417,PRETRIAL,Berbert,Angela,Leigh,Female,Caucasian,05/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +64413,74416,67417,PRETRIAL,Berbert,Angela,Leigh,Female,Caucasian,05/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +64413,74416,67417,PRETRIAL,Berbert,Angela,Leigh,Female,Caucasian,05/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64434,74444,67442,Probation,michel,donald,NULL,Male,African-American,08/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +64434,74444,67442,Probation,michel,donald,NULL,Male,African-American,08/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +64434,74444,67442,Probation,michel,donald,NULL,Male,African-American,08/02/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64421,74428,67427,Probation,Marrero Duncab,Javaln,NULL,Female,Hispanic,05/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +64421,74428,67427,Probation,Marrero Duncab,Javaln,NULL,Female,Hispanic,05/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +64421,74428,67427,Probation,Marrero Duncab,Javaln,NULL,Female,Hispanic,05/23/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +64419,74423,67424,PRETRIAL,BRANCO,DANIEL,CARDOSO,Male,Caucasian,03/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +64419,74423,67424,PRETRIAL,BRANCO,DANIEL,CARDOSO,Male,Caucasian,03/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +64419,74423,67424,PRETRIAL,BRANCO,DANIEL,CARDOSO,Male,Caucasian,03/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64415,74419,67420,PRETRIAL,Thomas,Justin,J,Male,African-American,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +64415,74419,67420,PRETRIAL,Thomas,Justin,J,Male,African-American,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +64415,74419,67420,PRETRIAL,Thomas,Justin,J,Male,African-American,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +33001,74424,32076,PRETRIAL,Cox,Norman,NULL,Male,African-American,04/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/26/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,Copy,1,0 +33001,74424,32076,PRETRIAL,Cox,Norman,NULL,Male,African-American,04/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,Copy,1,0 +33001,74424,32076,PRETRIAL,Cox,Norman,NULL,Male,African-American,04/25/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +64424,74431,67430,Probation,Mendez,Juan,M,Male,Hispanic,01/07/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/26/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +64424,74431,67430,Probation,Mendez,Juan,M,Male,Hispanic,01/07/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/26/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +64424,74431,67430,Probation,Mendez,Juan,M,Male,Hispanic,01/07/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +55127,74427,66910,PRETRIAL,LINDO,NICOLE,NULL,Female,African-American,01/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/26/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,Copy,1,0 +55127,74427,66910,PRETRIAL,LINDO,NICOLE,NULL,Female,African-American,01/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/26/14 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,Copy,1,0 +55127,74427,66910,PRETRIAL,LINDO,NICOLE,NULL,Female,African-American,01/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +39930,74445,67443,PRETRIAL,Phillips,Lanard,NULL,Male,African-American,01/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,New,1,0 +39930,74445,67443,PRETRIAL,Phillips,Lanard,NULL,Male,African-American,01/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.64,10,High,New,1,0 +39930,74445,67443,PRETRIAL,Phillips,Lanard,NULL,Male,African-American,01/26/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64428,74436,67434,PRETRIAL,mandel,daniel,NULL,Male,Caucasian,12/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +64428,74436,67434,PRETRIAL,mandel,daniel,NULL,Male,Caucasian,12/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +64428,74436,67434,PRETRIAL,mandel,daniel,NULL,Male,Caucasian,12/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64433,74443,67441,Probation,McCormick,Darrell,NULL,Male,African-American,06/30/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +64433,74443,67441,Probation,McCormick,Darrell,NULL,Male,African-American,06/30/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +64433,74443,67441,Probation,McCormick,Darrell,NULL,Male,African-American,06/30/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64412,74415,67416,PRETRIAL,Garayoa,Alberto,NULL,Male,Caucasian,03/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +64412,74415,67416,PRETRIAL,Garayoa,Alberto,NULL,Male,Caucasian,03/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +64412,74415,67416,PRETRIAL,Garayoa,Alberto,NULL,Male,Caucasian,03/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64418,74422,67423,PRETRIAL,SAMP,JACOB,ANTHONY,Male,Caucasian,07/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +64418,74422,67423,PRETRIAL,SAMP,JACOB,ANTHONY,Male,Caucasian,07/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +64418,74422,67423,PRETRIAL,SAMP,JACOB,ANTHONY,Male,Caucasian,07/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64439,74450,67448,Probation,BALLARD,SEAN,M,Male,African-American,11/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +64439,74450,67448,Probation,BALLARD,SEAN,M,Male,African-American,11/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +64439,74450,67448,Probation,BALLARD,SEAN,M,Male,African-American,11/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64436,74447,67445,Probation,jordan,case,NULL,Male,Caucasian,12/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.27,3,Low,New,1,0 +64436,74447,67445,Probation,jordan,case,NULL,Male,Caucasian,12/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +64436,74447,67445,Probation,jordan,case,NULL,Male,Caucasian,12/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64414,74418,67419,PRETRIAL,Echeverri,Mario,NULL,Male,Hispanic,02/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +64414,74418,67419,PRETRIAL,Echeverri,Mario,NULL,Male,Hispanic,02/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +64414,74418,67419,PRETRIAL,Echeverri,Mario,NULL,Male,Hispanic,02/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57133,74439,67437,Probation,Motta,Bruna,NULL,Female,Caucasian,02/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +57133,74439,67437,Probation,Motta,Bruna,NULL,Female,Caucasian,02/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +57133,74439,67437,Probation,Motta,Bruna,NULL,Female,Caucasian,02/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54564,74442,67440,PRETRIAL,Aguiar,Frank,NULL,Male,Hispanic,02/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/26/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +54564,74442,67440,PRETRIAL,Aguiar,Frank,NULL,Male,Hispanic,02/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/26/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +54564,74442,67440,PRETRIAL,Aguiar,Frank,NULL,Male,Hispanic,02/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64427,74434,67433,Probation,merritt,andreos,devaughn,Male,African-American,11/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,2,Medium,7,Risk of Violence,-2.76,2,Low,New,1,0 +64427,74434,67433,Probation,merritt,andreos,devaughn,Male,African-American,11/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +64427,74434,67433,Probation,merritt,andreos,devaughn,Male,African-American,11/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/26/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64417,74421,67422,PRETRIAL,FORD,ALLISON,MICHELLE,Female,Caucasian,04/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +64417,74421,67422,PRETRIAL,FORD,ALLISON,MICHELLE,Female,Caucasian,04/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +64417,74421,67422,PRETRIAL,FORD,ALLISON,MICHELLE,Female,Caucasian,04/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/26/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56244,74455,58187,PRETRIAL,HOWARD,MONIQUE,COFFEY,Female,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,Copy,1,0 +56244,74455,58187,PRETRIAL,HOWARD,MONIQUE,COFFEY,Female,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,Copy,1,0 +56244,74455,58187,PRETRIAL,HOWARD,MONIQUE,COFFEY,Female,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +63164,74468,67463,Probation,BENITEZHERNANDEZ,MANUEL,A,Male,Hispanic,01/11/95,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +63164,74468,67463,Probation,BENITEZHERNANDEZ,MANUEL,A,Male,Hispanic,01/11/95,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,4,High,8,Risk of Recidivism,1.17,10,High,New,1,0 +63164,74468,67463,Probation,BENITEZHERNANDEZ,MANUEL,A,Male,Hispanic,01/11/95,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,4,High,18,Risk of Failure to Appear,16,1,Low,New,1,0 +64450,74463,67459,Probation,Myers,Cynthia,NULL,Female,African-American,08/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/27/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +64450,74463,67459,Probation,Myers,Cynthia,NULL,Female,African-American,08/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/27/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +64450,74463,67459,Probation,Myers,Cynthia,NULL,Female,African-American,08/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +64458,74476,67470,PRETRIAL,HODGSON,BRIAN,DANIEL,Male,Caucasian,10/16/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.93,2,Low,New,1,0 +64458,74476,67470,PRETRIAL,HODGSON,BRIAN,DANIEL,Male,Caucasian,10/16/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +64458,74476,67470,PRETRIAL,HODGSON,BRIAN,DANIEL,Male,Caucasian,10/16/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +64456,74473,67467,Probation,FORD,CHANDRA,D,Female,African-American,05/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +64456,74473,67467,Probation,FORD,CHANDRA,D,Female,African-American,05/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +64456,74473,67467,Probation,FORD,CHANDRA,D,Female,African-American,05/13/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64444,74457,67453,Probation,Contreras,Tamatha,NULL,Female,Caucasian,08/05/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +64444,74457,67453,Probation,Contreras,Tamatha,NULL,Female,Caucasian,08/05/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +64444,74457,67453,Probation,Contreras,Tamatha,NULL,Female,Caucasian,08/05/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64452,74466,67462,Probation,Austin,Linden,NULL,Male,African-American,10/31/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,4,High,7,Risk of Violence,-0.52,10,High,New,1,0 +64452,74466,67462,Probation,Austin,Linden,NULL,Male,African-American,10/31/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,4,High,8,Risk of Recidivism,0.4,8,High,New,1,0 +64452,74466,67462,Probation,Austin,Linden,NULL,Male,African-American,10/31/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64459,74478,67472,Probation,Kosuda,Gary,NULL,Male,Caucasian,03/23/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/14 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +64459,74478,67472,Probation,Kosuda,Gary,NULL,Male,Caucasian,03/23/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +64459,74478,67472,Probation,Kosuda,Gary,NULL,Male,Caucasian,03/23/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64441,74453,67450,PRETRIAL,Elmore,Preston,NULL,Male,African-American,10/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,Copy,1,0 +64441,74453,67450,PRETRIAL,Elmore,Preston,NULL,Male,African-American,10/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,Copy,1,0 +64441,74453,67450,PRETRIAL,Elmore,Preston,NULL,Male,African-American,10/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +64454,74470,67465,Probation,Madison,Linda,NULL,Female,Caucasian,08/06/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/14 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +64454,74470,67465,Probation,Madison,Linda,NULL,Female,Caucasian,08/06/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/14 0:00,1,Low,8,Risk of Recidivism,-2.58,1,Low,New,1,0 +64454,74470,67465,Probation,Madison,Linda,NULL,Female,Caucasian,08/06/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64457,74474,67468,Probation,Chinwilliams,Starr,NULL,Female,Asian,08/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +64457,74474,67468,Probation,Chinwilliams,Starr,NULL,Female,Asian,08/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +64457,74474,67468,Probation,Chinwilliams,Starr,NULL,Female,Asian,08/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,4,High,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +64460,74479,67473,Probation,SAMS,KEVIN,M,Male,African-American,06/30/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/14 0:00,4,High,7,Risk of Violence,-0.97,9,High,New,1,0 +64460,74479,67473,Probation,SAMS,KEVIN,M,Male,African-American,06/30/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/14 0:00,4,High,8,Risk of Recidivism,1.11,10,High,New,1,0 +64460,74479,67473,Probation,SAMS,KEVIN,M,Male,African-American,06/30/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/27/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64446,74458,67454,Probation,Dickenson,Cooper,NULL,Male,Caucasian,02/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +64446,74458,67454,Probation,Dickenson,Cooper,NULL,Male,Caucasian,02/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +64446,74458,67454,Probation,Dickenson,Cooper,NULL,Male,Caucasian,02/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64455,74472,67466,Probation,Brown,Nathan,NULL,Male,Caucasian,03/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +64455,74472,67466,Probation,Brown,Nathan,NULL,Male,Caucasian,03/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +64455,74472,67466,Probation,Brown,Nathan,NULL,Male,Caucasian,03/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64451,74464,67460,Probation,West,Robert,NULL,Male,Caucasian,03/26/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +64451,74464,67460,Probation,West,Robert,NULL,Male,Caucasian,03/26/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +64451,74464,67460,Probation,West,Robert,NULL,Male,Caucasian,03/26/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64443,74456,67452,PRETRIAL,OWENS,TYRONE,NULL,Male,African-American,10/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +64443,74456,67452,PRETRIAL,OWENS,TYRONE,NULL,Male,African-American,10/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +64443,74456,67452,PRETRIAL,OWENS,TYRONE,NULL,Male,African-American,10/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52269,74459,67455,PRETRIAL,Dillon,Paul,NULL,Male,Other,07/07/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +52269,74459,67455,PRETRIAL,Dillon,Paul,NULL,Male,Other,07/07/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +52269,74459,67455,PRETRIAL,Dillon,Paul,NULL,Male,Other,07/07/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52510,74477,67471,PRETRIAL,Martinez,Maria,E.,Female,Hispanic,09/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +52510,74477,67471,PRETRIAL,Martinez,Maria,E.,Female,Hispanic,09/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +52510,74477,67471,PRETRIAL,Martinez,Maria,E.,Female,Hispanic,09/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64442,74454,67451,PRETRIAL,Otero-Andrews,Joshua,W,Male,Hispanic,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +64442,74454,67451,PRETRIAL,Otero-Andrews,Joshua,W,Male,Hispanic,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +64442,74454,67451,PRETRIAL,Otero-Andrews,Joshua,W,Male,Hispanic,06/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/27/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64453,74469,67464,Probation,Moreau,Joel,NULL,Male,Caucasian,09/05/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/27/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +64453,74469,67464,Probation,Moreau,Joel,NULL,Male,Caucasian,09/05/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/27/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +64453,74469,67464,Probation,Moreau,Joel,NULL,Male,Caucasian,09/05/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64448,74461,67457,PRETRIAL,Campos,Rodrigo,NULL,Male,Hispanic,06/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +64448,74461,67457,PRETRIAL,Campos,Rodrigo,NULL,Male,Hispanic,06/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +64448,74461,67457,PRETRIAL,Campos,Rodrigo,NULL,Male,Hispanic,06/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64449,74462,67458,PRETRIAL,Diaz,Joshua,NULL,Male,Hispanic,06/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/14 0:00,4,High,7,Risk of Violence,-0.85,9,High,New,1,0 +64449,74462,67458,PRETRIAL,Diaz,Joshua,NULL,Male,Hispanic,06/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/14 0:00,4,High,8,Risk of Recidivism,0.19,8,High,New,1,0 +64449,74462,67458,PRETRIAL,Diaz,Joshua,NULL,Male,Hispanic,06/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/27/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64464,74483,67477,PRETRIAL,BENNETT,JOHN,NULL,Male,African-American,08/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,4,High,7,Risk of Violence,-0.63,9,High,New,1,0 +64464,74483,67477,PRETRIAL,BENNETT,JOHN,NULL,Male,African-American,08/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +64464,74483,67477,PRETRIAL,BENNETT,JOHN,NULL,Male,African-American,08/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64463,74482,67476,PRETRIAL,Carballea,Carlos,NULL,Male,Caucasian,12/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,New,1,0 +64463,74482,67476,PRETRIAL,Carballea,Carlos,NULL,Male,Caucasian,12/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +64463,74482,67476,PRETRIAL,Carballea,Carlos,NULL,Male,Caucasian,12/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64467,74485,67479,PRETRIAL,Harris,Jason,NULL,Male,African-American,04/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +64467,74485,67479,PRETRIAL,Harris,Jason,NULL,Male,African-American,04/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +64467,74485,67479,PRETRIAL,Harris,Jason,NULL,Male,African-American,04/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64468,74486,67480,PRETRIAL,Pethers,Clarence,NULL,Male,Caucasian,01/31/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,7,Risk of Violence,-4.33,1,Low,New,1,0 +64468,74486,67480,PRETRIAL,Pethers,Clarence,NULL,Male,Caucasian,01/31/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,8,Risk of Recidivism,-2.68,1,Low,New,1,0 +64468,74486,67480,PRETRIAL,Pethers,Clarence,NULL,Male,Caucasian,01/31/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64469,74488,67481,PRETRIAL,Cooper,Isis,NULL,Female,African-American,01/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +64469,74488,67481,PRETRIAL,Cooper,Isis,NULL,Female,African-American,01/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +64469,74488,67481,PRETRIAL,Cooper,Isis,NULL,Female,African-American,01/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +53132,74487,54562,PRETRIAL,Ferrer,Lea,NULL,Female,Caucasian,01/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,Copy,1,0 +53132,74487,54562,PRETRIAL,Ferrer,Lea,NULL,Female,Caucasian,01/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,Copy,1,0 +53132,74487,54562,PRETRIAL,Ferrer,Lea,NULL,Female,Caucasian,01/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +64461,74480,67474,PRETRIAL,Boyd,Devante,NULL,Male,African-American,06/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +64461,74480,67474,PRETRIAL,Boyd,Devante,NULL,Male,African-American,06/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,4,High,8,Risk of Recidivism,0.47,9,High,New,1,0 +64461,74480,67474,PRETRIAL,Boyd,Devante,NULL,Male,African-American,06/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64466,74484,67478,PRETRIAL,FAIRLEY,WILLIE,NULL,Male,African-American,02/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +64466,74484,67478,PRETRIAL,FAIRLEY,WILLIE,NULL,Male,African-American,02/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +64466,74484,67478,PRETRIAL,FAIRLEY,WILLIE,NULL,Male,African-American,02/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64462,74481,67475,PRETRIAL,Monti,Madison,NULL,Female,Caucasian,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +64462,74481,67475,PRETRIAL,Monti,Madison,NULL,Female,Caucasian,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +64462,74481,67475,PRETRIAL,Monti,Madison,NULL,Female,Caucasian,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62693,72196,65444,PRETRIAL,MALDONADO,ROBERT,NULL,Male,Caucasian,07/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/29/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +62693,72196,65444,PRETRIAL,MALDONADO,ROBERT,NULL,Male,Caucasian,07/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/29/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +62693,72196,65444,PRETRIAL,MALDONADO,ROBERT,NULL,Male,Caucasian,07/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/29/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64472,74497,67485,PRETRIAL,Rojas,Alexander,David,Male,Hispanic,09/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +64472,74497,67485,PRETRIAL,Rojas,Alexander,David,Male,Hispanic,09/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +64472,74497,67485,PRETRIAL,Rojas,Alexander,David,Male,Hispanic,09/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64470,74494,67483,PRETRIAL,GUTIERREZ,RODOLFO,NULL,Male,Hispanic,09/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +64470,74494,67483,PRETRIAL,GUTIERREZ,RODOLFO,NULL,Male,Hispanic,09/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +64470,74494,67483,PRETRIAL,GUTIERREZ,RODOLFO,NULL,Male,Hispanic,09/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64471,74496,67484,PRETRIAL,Shanefelt,Kenneth,NULL,Male,Caucasian,10/29/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +64471,74496,67484,PRETRIAL,Shanefelt,Kenneth,NULL,Male,Caucasian,10/29/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +64471,74496,67484,PRETRIAL,Shanefelt,Kenneth,NULL,Male,Caucasian,10/29/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +54705,74492,67482,PRETRIAL,MARINEY,GERARD,KEITH,Male,African-American,12/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +54705,74492,67482,PRETRIAL,MARINEY,GERARD,KEITH,Male,African-American,12/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +54705,74492,67482,PRETRIAL,MARINEY,GERARD,KEITH,Male,African-American,12/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +64473,74499,67486,PRETRIAL,ARNDT,ANDREW,NULL,Male,Caucasian,04/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +64473,74499,67486,PRETRIAL,ARNDT,ANDREW,NULL,Male,Caucasian,04/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +64473,74499,67486,PRETRIAL,ARNDT,ANDREW,NULL,Male,Caucasian,04/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +20572,74495,19763,PRETRIAL,Ramos,Angelo,NULL,Male,Caucasian,10/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,Copy,1,0 +20572,74495,19763,PRETRIAL,Ramos,Angelo,NULL,Male,Caucasian,10/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,Copy,1,0 +20572,74495,19763,PRETRIAL,Ramos,Angelo,NULL,Male,Caucasian,10/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +12844,74491,12328,PRETRIAL,TILLMAN,HORACE,NULL,Male,African-American,03/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,Copy,1,0 +12844,74491,12328,PRETRIAL,TILLMAN,HORACE,NULL,Male,African-American,03/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,Copy,1,0 +12844,74491,12328,PRETRIAL,TILLMAN,HORACE,NULL,Male,African-American,03/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +54819,74493,56539,Probation,Smart,Cambrell,NULL,Male,African-American,10/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,Copy,1,0 +54819,74493,56539,Probation,Smart,Cambrell,NULL,Male,African-American,10/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.94,10,High,Copy,1,0 +54819,74493,56539,Probation,Smart,Cambrell,NULL,Male,African-American,10/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +62693,74498,65444,PRETRIAL,MALDONADO,ROBERT,NULL,Male,Caucasian,07/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/29/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,Copy,1,0 +62693,74498,65444,PRETRIAL,MALDONADO,ROBERT,NULL,Male,Caucasian,07/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/29/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,Copy,1,0 +62693,74498,65444,PRETRIAL,MALDONADO,ROBERT,NULL,Male,Caucasian,07/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/29/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +64504,74532,67515,PRETRIAL,barens,frans,NULL,Male,Caucasian,05/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +64504,74532,67515,PRETRIAL,barens,frans,NULL,Male,Caucasian,05/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +64504,74532,67515,PRETRIAL,barens,frans,NULL,Male,Caucasian,05/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64492,74519,67503,Probation,keith,addrine,NULL,Female,African-American,07/26/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +64492,74519,67503,Probation,keith,addrine,NULL,Female,African-American,07/26/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +64492,74519,67503,Probation,keith,addrine,NULL,Female,African-American,07/26/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +59889,74506,67493,PRETRIAL,Hernandez,Martin,NULL,Male,Hispanic,01/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +59889,74506,67493,PRETRIAL,Hernandez,Martin,NULL,Male,Hispanic,01/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +59889,74506,67493,PRETRIAL,Hernandez,Martin,NULL,Male,Hispanic,01/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64497,74524,67508,Probation,Brannan,Clinton,NULL,Male,Caucasian,11/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +64497,74524,67508,Probation,Brannan,Clinton,NULL,Male,Caucasian,11/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +64497,74524,67508,Probation,Brannan,Clinton,NULL,Male,Caucasian,11/13/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64477,74503,67490,PRETRIAL,ANGLADE,JOI,CIARA,Female,African-American,02/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/30/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +64477,74503,67490,PRETRIAL,ANGLADE,JOI,CIARA,Female,African-American,02/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/30/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +64477,74503,67490,PRETRIAL,ANGLADE,JOI,CIARA,Female,African-American,02/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64510,74540,67523,PRETRIAL,Butler,Tracy,NULL,Male,African-American,08/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/30/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +64510,74540,67523,PRETRIAL,Butler,Tracy,NULL,Male,African-American,08/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/30/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +64510,74540,67523,PRETRIAL,Butler,Tracy,NULL,Male,African-American,08/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64506,74535,67518,Probation,Hulse,Daniel,NULL,Male,Hispanic,10/31/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +64506,74535,67518,Probation,Hulse,Daniel,NULL,Male,Hispanic,10/31/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +64506,74535,67518,Probation,Hulse,Daniel,NULL,Male,Hispanic,10/31/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +49684,74537,67520,PRETRIAL,Fort,Lataurus,NULL,Male,African-American,10/12/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +49684,74537,67520,PRETRIAL,Fort,Lataurus,NULL,Male,African-American,10/12/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +49684,74537,67520,PRETRIAL,Fort,Lataurus,NULL,Male,African-American,10/12/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +27431,74507,26546,PRETRIAL,HAIRSTON,JUSTIN,NULL,Male,African-American,09/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,Copy,1,0 +27431,74507,26546,PRETRIAL,HAIRSTON,JUSTIN,NULL,Male,African-American,09/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,Copy,1,0 +27431,74507,26546,PRETRIAL,HAIRSTON,JUSTIN,NULL,Male,African-American,09/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +64489,74516,67500,PRETRIAL,SANMARTIN,FLORENCIA,NULL,Female,Hispanic,12/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +64489,74516,67500,PRETRIAL,SANMARTIN,FLORENCIA,NULL,Female,Hispanic,12/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +64489,74516,67500,PRETRIAL,SANMARTIN,FLORENCIA,NULL,Female,Hispanic,12/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64494,74521,67505,PRETRIAL,LEGER,CESAR,NULL,Male,Hispanic,06/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +64494,74521,67505,PRETRIAL,LEGER,CESAR,NULL,Male,Hispanic,06/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +64494,74521,67505,PRETRIAL,LEGER,CESAR,NULL,Male,Hispanic,06/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64498,74525,67509,Probation,walker,geroise,NULL,Male,African-American,02/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +64498,74525,67509,Probation,walker,geroise,NULL,Male,African-American,02/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +64498,74525,67509,Probation,walker,geroise,NULL,Male,African-American,02/17/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64474,74500,67487,PRETRIAL,FRANCOIS,AIRVEN,NULL,Male,African-American,11/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +64474,74500,67487,PRETRIAL,FRANCOIS,AIRVEN,NULL,Male,African-American,11/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +64474,74500,67487,PRETRIAL,FRANCOIS,AIRVEN,NULL,Male,African-American,11/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64478,74504,67491,PRETRIAL,Jordan,Christopher,Alexander,Male,African-American,11/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +64478,74504,67491,PRETRIAL,Jordan,Christopher,Alexander,Male,African-American,11/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +64478,74504,67491,PRETRIAL,Jordan,Christopher,Alexander,Male,African-American,11/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +5946,74509,5565,Probation,ramosmurillo,cristhian,NULL,Male,Hispanic,08/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,4,High,7,Risk of Violence,-1.16,8,High,Copy,1,0 +5946,74509,5565,Probation,ramosmurillo,cristhian,NULL,Male,Hispanic,08/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,4,High,8,Risk of Recidivism,0.28,8,High,Copy,1,0 +5946,74509,5565,Probation,ramosmurillo,cristhian,NULL,Male,Hispanic,08/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +56896,74513,67497,Probation,Harrold,Alan,NULL,Male,Caucasian,12/11/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/30/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +56896,74513,67497,Probation,Harrold,Alan,NULL,Male,Caucasian,12/11/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/30/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +56896,74513,67497,Probation,Harrold,Alan,NULL,Male,Caucasian,12/11/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,6/30/14 0:00,2,Medium,18,Risk of Failure to Appear,37,10,High,New,1,0 +64507,74538,67521,Probation,Wilson,Reginald,NULL,Male,African-American,11/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.53,3,Low,New,1,0 +64507,74538,67521,Probation,Wilson,Reginald,NULL,Male,African-American,11/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,9,High,New,1,0 +64507,74538,67521,Probation,Wilson,Reginald,NULL,Male,African-American,11/04/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64490,74517,67501,PRETRIAL,toroquintero,juan,NULL,Male,Caucasian,03/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +64490,74517,67501,PRETRIAL,toroquintero,juan,NULL,Male,Caucasian,03/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +64490,74517,67501,PRETRIAL,toroquintero,juan,NULL,Male,Caucasian,03/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +48828,74534,67517,PRETRIAL,wolcott,delbert,NULL,Male,Caucasian,06/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/30/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +48828,74534,67517,PRETRIAL,wolcott,delbert,NULL,Male,Caucasian,06/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/30/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +48828,74534,67517,PRETRIAL,wolcott,delbert,NULL,Male,Caucasian,06/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64502,74529,67513,PRETRIAL,murray,earl,NULL,Male,African-American,12/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.07,4,Low,New,1,0 +64502,74529,67513,PRETRIAL,murray,earl,NULL,Male,African-American,12/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.8,10,High,New,1,0 +64502,74529,67513,PRETRIAL,murray,earl,NULL,Male,African-American,12/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64479,74508,67494,PRETRIAL,RAJI,TAMIRAH,GULLY,Female,African-American,08/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +64479,74508,67494,PRETRIAL,RAJI,TAMIRAH,GULLY,Female,African-American,08/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +64479,74508,67494,PRETRIAL,RAJI,TAMIRAH,GULLY,Female,African-American,08/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64488,74515,67499,PRETRIAL,tammie,brown,NULL,Female,Asian,02/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/30/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +64488,74515,67499,PRETRIAL,tammie,brown,NULL,Female,Asian,02/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/30/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +64488,74515,67499,PRETRIAL,tammie,brown,NULL,Female,Asian,02/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64495,74522,67506,Probation,Rosado,Frank,NULL,Male,Hispanic,11/03/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +64495,74522,67506,Probation,Rosado,Frank,NULL,Male,Hispanic,11/03/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +64495,74522,67506,Probation,Rosado,Frank,NULL,Male,Hispanic,11/03/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64475,74501,67488,PRETRIAL,Vasquez,Rodrigo,NULL,Male,Hispanic,05/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +64475,74501,67488,PRETRIAL,Vasquez,Rodrigo,NULL,Male,Hispanic,05/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +64475,74501,67488,PRETRIAL,Vasquez,Rodrigo,NULL,Male,Hispanic,05/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64505,74533,67516,Probation,kourtis,anthony,NULL,Male,Caucasian,04/28/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +64505,74533,67516,Probation,kourtis,anthony,NULL,Male,Caucasian,04/28/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +64505,74533,67516,Probation,kourtis,anthony,NULL,Male,Caucasian,04/28/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64491,74518,67502,Probation,Miraglia,Maximiliano,NULL,Male,Hispanic,06/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/30/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +64491,74518,67502,Probation,Miraglia,Maximiliano,NULL,Male,Hispanic,06/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/30/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +64491,74518,67502,Probation,Miraglia,Maximiliano,NULL,Male,Hispanic,06/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +30525,74505,67492,Probation,williams,timothy,NULL,Male,African-American,04/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +30525,74505,67492,Probation,williams,timothy,NULL,Male,African-American,04/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +30525,74505,67492,Probation,williams,timothy,NULL,Male,African-American,04/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +64509,74539,67522,Probation,biogris,herve,NULL,Male,African-American,03/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +64509,74539,67522,Probation,biogris,herve,NULL,Male,African-American,03/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +64509,74539,67522,Probation,biogris,herve,NULL,Male,African-American,03/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64476,74502,67489,PRETRIAL,Bercy,Woodley,Ronald,Male,African-American,02/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +64476,74502,67489,PRETRIAL,Bercy,Woodley,Ronald,Male,African-American,02/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +64476,74502,67489,PRETRIAL,Bercy,Woodley,Ronald,Male,African-American,02/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64508,74536,67519,Probation,glass,brittany,NULL,Female,African-American,05/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +64508,74536,67519,Probation,glass,brittany,NULL,Female,African-American,05/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +64508,74536,67519,Probation,glass,brittany,NULL,Female,African-American,05/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64496,74523,67507,PRETRIAL,Grimes,Anjelica,NULL,Female,Caucasian,01/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +64496,74523,67507,PRETRIAL,Grimes,Anjelica,NULL,Female,Caucasian,01/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +64496,74523,67507,PRETRIAL,Grimes,Anjelica,NULL,Female,Caucasian,01/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64503,74531,67514,Probation,petit-homme,gilbert,NULL,Male,African-American,08/02/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,7,Risk of Violence,-4.33,1,Low,New,1,0 +64503,74531,67514,Probation,petit-homme,gilbert,NULL,Male,African-American,08/02/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,8,Risk of Recidivism,-2.95,1,Low,New,1,0 +64503,74531,67514,Probation,petit-homme,gilbert,NULL,Male,African-American,08/02/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64480,74510,67495,PRETRIAL,Perez-Carachure,ALberto,NULL,Male,Hispanic,02/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/30/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +64480,74510,67495,PRETRIAL,Perez-Carachure,ALberto,NULL,Male,Hispanic,02/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/30/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +64480,74510,67495,PRETRIAL,Perez-Carachure,ALberto,NULL,Male,Hispanic,02/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,6/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64501,74528,67512,PRETRIAL,BROWN,SHAWN,NULL,Male,African-American,01/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,New,1,0 +64501,74528,67512,PRETRIAL,BROWN,SHAWN,NULL,Male,African-American,01/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +64501,74528,67512,PRETRIAL,BROWN,SHAWN,NULL,Male,African-American,01/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,6/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50806,74557,67538,PRETRIAL,Richard,Mahindra,NULL,Male,Other,02/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +50806,74557,67538,PRETRIAL,Richard,Mahindra,NULL,Male,Other,02/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +50806,74557,67538,PRETRIAL,Richard,Mahindra,NULL,Male,Other,02/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64532,74570,67551,Probation,Feliciano,Priscilla,Isis,Female,Hispanic,07/31/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/1/14 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +64532,74570,67551,Probation,Feliciano,Priscilla,Isis,Female,Hispanic,07/31/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,7,Medium,New,1,0 +64532,74570,67551,Probation,Feliciano,Priscilla,Isis,Female,Hispanic,07/31/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/1/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64511,74541,67524,PRETRIAL,Moody,Isaac,Daniel,Male,African-American,01/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/1/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +64511,74541,67524,PRETRIAL,Moody,Isaac,Daniel,Male,African-American,01/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/1/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +64511,74541,67524,PRETRIAL,Moody,Isaac,Daniel,Male,African-American,01/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64515,74546,67529,PRETRIAL,Alardo,Steven,W,Male,Hispanic,11/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +64515,74546,67529,PRETRIAL,Alardo,Steven,W,Male,Hispanic,11/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +64515,74546,67529,PRETRIAL,Alardo,Steven,W,Male,Hispanic,11/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58729,74575,67556,PRETRIAL,StFort,Shantrina,NULL,Female,African-American,06/06/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +58729,74575,67556,PRETRIAL,StFort,Shantrina,NULL,Female,African-American,06/06/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +58729,74575,67556,PRETRIAL,StFort,Shantrina,NULL,Female,African-American,06/06/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64521,74554,67536,Probation,gallagher,jennifer,NULL,Female,Hispanic,02/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +64521,74554,67536,Probation,gallagher,jennifer,NULL,Female,Hispanic,02/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +64521,74554,67536,Probation,gallagher,jennifer,NULL,Female,Hispanic,02/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +64516,74547,67530,PRETRIAL,Nicholasi,Anthony,NULL,Male,Caucasian,11/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +64516,74547,67530,PRETRIAL,Nicholasi,Anthony,NULL,Male,Caucasian,11/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +64516,74547,67530,PRETRIAL,Nicholasi,Anthony,NULL,Male,Caucasian,11/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56747,74562,67543,PRETRIAL,JENSEN,WAYNE,NULL,Male,Caucasian,07/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +56747,74562,67543,PRETRIAL,JENSEN,WAYNE,NULL,Male,Caucasian,07/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +56747,74562,67543,PRETRIAL,JENSEN,WAYNE,NULL,Male,Caucasian,07/22/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63756,74552,67534,Probation,kyhl,christopher,NULL,Male,Caucasian,08/04/76,17,All Scales,Intake,English,Other,Probation,Single,7/1/14 0:00,4,High,7,Risk of Violence,0.05,10,High,New,1,0 +63756,74552,67534,Probation,kyhl,christopher,NULL,Male,Caucasian,08/04/76,17,All Scales,Intake,English,Other,Probation,Single,7/1/14 0:00,4,High,8,Risk of Recidivism,0.77,10,High,New,1,0 +63756,74552,67534,Probation,kyhl,christopher,NULL,Male,Caucasian,08/04/76,17,All Scales,Intake,English,Other,Probation,Single,7/1/14 0:00,4,High,18,Risk of Failure to Appear,51,10,High,New,1,0 +26693,74571,67552,Probation,williams,joseph,NULL,Male,Hispanic,07/06/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/1/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +26693,74571,67552,Probation,williams,joseph,NULL,Male,Hispanic,07/06/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +26693,74571,67552,Probation,williams,joseph,NULL,Male,Hispanic,07/06/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64518,74550,67532,PRETRIAL,BAKER,MANUEL,NULL,Male,Native American,02/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,4,High,7,Risk of Violence,-0.64,9,High,New,1,0 +64518,74550,67532,PRETRIAL,BAKER,MANUEL,NULL,Male,Native American,02/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +64518,74550,67532,PRETRIAL,BAKER,MANUEL,NULL,Male,Native American,02/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +41846,74573,67554,PRETRIAL,Gallardo,Joel,NULL,Male,Hispanic,07/16/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/1/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +41846,74573,67554,PRETRIAL,Gallardo,Joel,NULL,Male,Hispanic,07/16/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/1/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +41846,74573,67554,PRETRIAL,Gallardo,Joel,NULL,Male,Hispanic,07/16/79,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +43056,74543,67526,Probation,carter,walter,NULL,Male,African-American,07/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,New,1,0 +43056,74543,67526,Probation,carter,walter,NULL,Male,African-American,07/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +43056,74543,67526,Probation,carter,walter,NULL,Male,African-American,07/08/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64531,74568,67549,Probation,chubb,joshua,NULL,Male,Caucasian,06/23/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/1/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +64531,74568,67549,Probation,chubb,joshua,NULL,Male,Caucasian,06/23/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +64531,74568,67549,Probation,chubb,joshua,NULL,Male,Caucasian,06/23/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64522,74555,67537,Probation,Johnson,Brian,NULL,Male,Caucasian,08/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/1/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +64522,74555,67537,Probation,Johnson,Brian,NULL,Male,Caucasian,08/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +64522,74555,67537,Probation,Johnson,Brian,NULL,Male,Caucasian,08/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64527,74564,67545,Probation,Grant,Willie,NULL,Male,African-American,01/31/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +64527,74564,67545,Probation,Grant,Willie,NULL,Male,African-American,01/31/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +64527,74564,67545,Probation,Grant,Willie,NULL,Male,African-American,01/31/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +64525,74559,67540,PRETRIAL,Krimmel,William,NULL,Male,Caucasian,08/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +64525,74559,67540,PRETRIAL,Krimmel,William,NULL,Male,Caucasian,08/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +64525,74559,67540,PRETRIAL,Krimmel,William,NULL,Male,Caucasian,08/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64512,74542,67525,PRETRIAL,Jace,Amanda,NULL,Female,Caucasian,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +64512,74542,67525,PRETRIAL,Jace,Amanda,NULL,Female,Caucasian,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +64512,74542,67525,PRETRIAL,Jace,Amanda,NULL,Female,Caucasian,08/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64524,74560,67541,Probation,Smith,Nikia,Yashon,Female,African-American,08/21/87,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/1/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +64524,74560,67541,Probation,Smith,Nikia,Yashon,Female,African-American,08/21/87,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +64524,74560,67541,Probation,Smith,Nikia,Yashon,Female,African-American,08/21/87,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +45346,74556,52422,PRETRIAL,Watson,Kennan,NULL,Male,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,Copy,1,0 +45346,74556,52422,PRETRIAL,Watson,Kennan,NULL,Male,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-0.71,3,Low,Copy,1,0 +45346,74556,52422,PRETRIAL,Watson,Kennan,NULL,Male,African-American,12/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,Copy,1,0 +64528,74563,67544,PRETRIAL,Magnone,Gabriel,NULL,Male,Caucasian,03/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/1/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +64528,74563,67544,PRETRIAL,Magnone,Gabriel,NULL,Male,Caucasian,03/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/1/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +64528,74563,67544,PRETRIAL,Magnone,Gabriel,NULL,Male,Caucasian,03/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64519,74551,67533,Probation,Lemuspalma,Kevin,NULL,Male,Hispanic,06/08/92,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/1/14 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +64519,74551,67533,Probation,Lemuspalma,Kevin,NULL,Male,Hispanic,06/08/92,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +64519,74551,67533,Probation,Lemuspalma,Kevin,NULL,Male,Hispanic,06/08/92,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/1/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64513,74544,67527,PRETRIAL,BENNETT,WILLIAM,CHRISTOPHE,Male,Caucasian,09/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/1/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +64513,74544,67527,PRETRIAL,BENNETT,WILLIAM,CHRISTOPHE,Male,Caucasian,09/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/1/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +64513,74544,67527,PRETRIAL,BENNETT,WILLIAM,CHRISTOPHE,Male,Caucasian,09/04/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64523,74558,67539,Probation,bryan,paul,NULL,Male,African-American,10/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +64523,74558,67539,Probation,bryan,paul,NULL,Male,African-American,10/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +64523,74558,67539,Probation,bryan,paul,NULL,Male,African-American,10/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55819,74565,67546,PRETRIAL,Keaty,Mark,C,Male,Caucasian,05/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +55819,74565,67546,PRETRIAL,Keaty,Mark,C,Male,Caucasian,05/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +55819,74565,67546,PRETRIAL,Keaty,Mark,C,Male,Caucasian,05/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57451,65666,59561,PRETRIAL,SAMUELS,SEAN,NULL,Male,African-American,03/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +57451,65666,59561,PRETRIAL,SAMUELS,SEAN,NULL,Male,African-American,03/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +57451,65666,59561,PRETRIAL,SAMUELS,SEAN,NULL,Male,African-American,03/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64526,74561,67542,PRETRIAL,SANTELLA,ANTHONY,NULL,Male,Caucasian,04/18/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +64526,74561,67542,PRETRIAL,SANTELLA,ANTHONY,NULL,Male,Caucasian,04/18/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +64526,74561,67542,PRETRIAL,SANTELLA,ANTHONY,NULL,Male,Caucasian,04/18/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64534,74576,67557,PRETRIAL,Hill,Monica,NULL,Female,African-American,10/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/1/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +64534,74576,67557,PRETRIAL,Hill,Monica,NULL,Female,African-American,10/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +64534,74576,67557,PRETRIAL,Hill,Monica,NULL,Female,African-American,10/14/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57711,74569,67550,PRETRIAL,COBY,JONATHAN,NULL,Male,African-American,05/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +57711,74569,67550,PRETRIAL,COBY,JONATHAN,NULL,Male,African-American,05/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +57711,74569,67550,PRETRIAL,COBY,JONATHAN,NULL,Male,African-American,05/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +7113,74574,67555,PRETRIAL,Estrella,Joshua,NULL,Male,Caucasian,11/30/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +7113,74574,67555,PRETRIAL,Estrella,Joshua,NULL,Male,Caucasian,11/30/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +7113,74574,67555,PRETRIAL,Estrella,Joshua,NULL,Male,Caucasian,11/30/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/1/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +64514,74545,67528,PRETRIAL,FERGUSON,VICTOR,NULL,Male,African-American,01/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/1/14 0:00,2,Medium,7,Risk of Violence,-3.08,1,Low,New,1,0 +64514,74545,67528,PRETRIAL,FERGUSON,VICTOR,NULL,Male,African-American,01/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +64514,74545,67528,PRETRIAL,FERGUSON,VICTOR,NULL,Male,African-American,01/22/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/1/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64529,74566,67547,PRETRIAL,Beckles,Antequilia,NULL,Female,African-American,04/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +64529,74566,67547,PRETRIAL,Beckles,Antequilia,NULL,Female,African-American,04/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +64529,74566,67547,PRETRIAL,Beckles,Antequilia,NULL,Female,African-American,04/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/1/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64556,74600,67578,PRETRIAL,Moise,Kervins,Landy,Male,African-American,12/08/82,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,Copy,1,0 +64556,74600,67578,PRETRIAL,Moise,Kervins,Landy,Male,African-American,12/08/82,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,Copy,1,0 +64556,74600,67578,PRETRIAL,Moise,Kervins,Landy,Male,African-American,12/08/82,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +64543,74587,67567,PRETRIAL,Ogiste,Victor,NULL,Male,African-American,11/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/2/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +64543,74587,67567,PRETRIAL,Ogiste,Victor,NULL,Male,African-American,11/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +64543,74587,67567,PRETRIAL,Ogiste,Victor,NULL,Male,African-American,11/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/2/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64548,74592,67572,PRETRIAL,Dyer,Jaheel,NULL,Male,African-American,02/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +64548,74592,67572,PRETRIAL,Dyer,Jaheel,NULL,Male,African-American,02/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +64548,74592,67572,PRETRIAL,Dyer,Jaheel,NULL,Male,African-American,02/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64554,74595,67575,PRETRIAL,Lovett,Reginald,NULL,Male,African-American,12/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +64554,74595,67575,PRETRIAL,Lovett,Reginald,NULL,Male,African-American,12/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,4,High,8,Risk of Recidivism,0.35,9,High,New,1,0 +64554,74595,67575,PRETRIAL,Lovett,Reginald,NULL,Male,African-American,12/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +64540,74584,67564,Probation,Hanna,Sebastian,NULL,Male,African-American,01/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +64540,74584,67564,Probation,Hanna,Sebastian,NULL,Male,African-American,01/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +64540,74584,67564,Probation,Hanna,Sebastian,NULL,Male,African-American,01/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63286,74603,66125,Probation,HILL,BRANDON,NULL,Male,Caucasian,11/21/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,Copy,1,0 +63286,74603,66125,Probation,HILL,BRANDON,NULL,Male,Caucasian,11/21/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,Copy,1,0 +63286,74603,66125,Probation,HILL,BRANDON,NULL,Male,Caucasian,11/21/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +64538,74582,67561,PRETRIAL,gordon,jonathan,NULL,Male,Caucasian,04/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,Copy,1,0 +64538,74582,67561,PRETRIAL,gordon,jonathan,NULL,Male,Caucasian,04/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,Copy,1,0 +64538,74582,67561,PRETRIAL,gordon,jonathan,NULL,Male,Caucasian,04/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +64560,74605,67582,Probation,Miner,Sharif,NULL,Male,African-American,06/12/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +64560,74605,67582,Probation,Miner,Sharif,NULL,Male,African-American,06/12/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +64560,74605,67582,Probation,Miner,Sharif,NULL,Male,African-American,06/12/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62644,74611,67588,PRETRIAL,McRae,Bernice,NULL,Male,African-American,11/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +62644,74611,67588,PRETRIAL,McRae,Bernice,NULL,Male,African-American,11/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +62644,74611,67588,PRETRIAL,McRae,Bernice,NULL,Male,African-American,11/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +64546,74590,67570,PRETRIAL,RICHARDSON,MEGAHN,NULL,Female,Hispanic,06/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +64546,74590,67570,PRETRIAL,RICHARDSON,MEGAHN,NULL,Female,Hispanic,06/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,7,Medium,New,1,0 +64546,74590,67570,PRETRIAL,RICHARDSON,MEGAHN,NULL,Female,Hispanic,06/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64537,74579,67560,PRETRIAL,Leeks,Joseph,C,Male,African-American,11/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +64537,74579,67560,PRETRIAL,Leeks,Joseph,C,Male,African-American,11/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +64537,74579,67560,PRETRIAL,Leeks,Joseph,C,Male,African-American,11/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64549,74593,67573,Probation,cueva,gustavo,NULL,Male,Hispanic,03/09/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/2/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +64549,74593,67573,Probation,cueva,gustavo,NULL,Male,Hispanic,03/09/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/2/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +64549,74593,67573,Probation,cueva,gustavo,NULL,Male,Hispanic,03/09/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64562,74607,67584,Probation,reynoso,raul,NULL,Male,Hispanic,10/30/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +64562,74607,67584,Probation,reynoso,raul,NULL,Male,Hispanic,10/30/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +64562,74607,67584,Probation,reynoso,raul,NULL,Male,Hispanic,10/30/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64558,74602,67580,Probation,Albaestrada,Omar,NULL,Male,Hispanic,09/30/48,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,7/2/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +64558,74602,67580,Probation,Albaestrada,Omar,NULL,Male,Hispanic,09/30/48,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,7/2/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +64558,74602,67580,Probation,Albaestrada,Omar,NULL,Male,Hispanic,09/30/48,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61531,74598,64104,PRETRIAL,Campbell,Miguel,NULL,Male,African-American,06/11/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +61531,74598,64104,PRETRIAL,Campbell,Miguel,NULL,Male,African-American,06/11/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +61531,74598,64104,PRETRIAL,Campbell,Miguel,NULL,Male,African-American,06/11/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,4,Low,New,1,0 +64539,74581,67562,Probation,Polston,Gene,NULL,Male,Caucasian,07/02/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +64539,74581,67562,Probation,Polston,Gene,NULL,Male,Caucasian,07/02/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +64539,74581,67562,Probation,Polston,Gene,NULL,Male,Caucasian,07/02/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,35,10,High,New,1,0 +64535,74577,67558,PRETRIAL,Manderville,Christopher,Eugene,Male,Caucasian,04/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/2/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +64535,74577,67558,PRETRIAL,Manderville,Christopher,Eugene,Male,Caucasian,04/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/2/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +64535,74577,67558,PRETRIAL,Manderville,Christopher,Eugene,Male,Caucasian,04/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64561,74606,67583,Probation,issa,nabil,NULL,Male,Caucasian,12/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +64561,74606,67583,Probation,issa,nabil,NULL,Male,Caucasian,12/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +64561,74606,67583,Probation,issa,nabil,NULL,Male,Caucasian,12/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64545,74589,67569,Probation,Powell,Dennis,NULL,Male,African-American,01/26/61,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,7/2/14 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +64545,74589,67569,Probation,Powell,Dennis,NULL,Male,African-American,01/26/61,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,7/2/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +64545,74589,67569,Probation,Powell,Dennis,NULL,Male,African-American,01/26/61,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64541,74585,67565,Probation,stvictor,kelly,NULL,Male,African-American,07/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +64541,74585,67565,Probation,stvictor,kelly,NULL,Male,African-American,07/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,New,1,0 +64541,74585,67565,Probation,stvictor,kelly,NULL,Male,African-American,07/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +64551,74594,67574,PRETRIAL,OLIVAS,ERNEST,NULL,Male,Hispanic,10/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +64551,74594,67574,PRETRIAL,OLIVAS,ERNEST,NULL,Male,Hispanic,10/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,8,Risk of Recidivism,-2.64,1,Low,New,1,0 +64551,74594,67574,PRETRIAL,OLIVAS,ERNEST,NULL,Male,Hispanic,10/31/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64557,74601,67579,Probation,FINK,AMANDA,NULL,Female,Caucasian,02/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +64557,74601,67579,Probation,FINK,AMANDA,NULL,Female,Caucasian,02/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +64557,74601,67579,Probation,FINK,AMANDA,NULL,Female,Caucasian,02/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +53035,59942,54449,PRETRIAL,Hall,Vonkeith,NULL,Male,African-American,03/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +53035,59942,54449,PRETRIAL,Hall,Vonkeith,NULL,Male,African-American,03/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.86,10,High,New,1,0 +53035,59942,54449,PRETRIAL,Hall,Vonkeith,NULL,Male,African-American,03/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55688,74604,67581,Probation,calderon,cristian,NULL,Male,Hispanic,04/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +55688,74604,67581,Probation,calderon,cristian,NULL,Male,Hispanic,04/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +55688,74604,67581,Probation,calderon,cristian,NULL,Male,Hispanic,04/18/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64547,74591,67571,PRETRIAL,Hackett,Tiffany,NULL,Female,Caucasian,07/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +64547,74591,67571,PRETRIAL,Hackett,Tiffany,NULL,Female,Caucasian,07/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +64547,74591,67571,PRETRIAL,Hackett,Tiffany,NULL,Female,Caucasian,07/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64536,74578,67559,PRETRIAL,Clarke,Kadeem,H,Male,Other,10/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +64536,74578,67559,PRETRIAL,Clarke,Kadeem,H,Male,Other,10/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +64536,74578,67559,PRETRIAL,Clarke,Kadeem,H,Male,Other,10/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64555,74596,67576,Probation,hazan,michael,NULL,Male,Caucasian,10/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.42,3,Low,New,1,0 +64555,74596,67576,Probation,hazan,michael,NULL,Male,Caucasian,10/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +64555,74596,67576,Probation,hazan,michael,NULL,Male,Caucasian,10/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64544,74588,67568,Probation,DAVIS,DEMETRIUS,ANTONIO,Male,African-American,02/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +64544,74588,67568,Probation,DAVIS,DEMETRIUS,ANTONIO,Male,African-American,02/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +64544,74588,67568,Probation,DAVIS,DEMETRIUS,ANTONIO,Male,African-American,02/02/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/2/14 0:00,1,Low,18,Risk of Failure to Appear,35,10,High,New,1,0 +64556,74599,67578,PRETRIAL,Moise,Kervins,Landy,Male,African-American,12/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +64556,74599,67578,PRETRIAL,Moise,Kervins,Landy,Male,African-American,12/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +64556,74599,67578,PRETRIAL,Moise,Kervins,Landy,Male,African-American,12/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64585,74638,67613,Probation,Da Silva,Marcelo,NULL,Male,Hispanic,03/03/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +64585,74638,67613,Probation,Da Silva,Marcelo,NULL,Male,Hispanic,03/03/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +64585,74638,67613,Probation,Da Silva,Marcelo,NULL,Male,Hispanic,03/03/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64590,74646,67620,Probation,Moreno,Christopher,NULL,Male,African-American,03/30/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +64590,74646,67620,Probation,Moreno,Christopher,NULL,Male,African-American,03/30/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +64590,74646,67620,Probation,Moreno,Christopher,NULL,Male,African-American,03/30/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64573,74625,67601,Probation,Rodriguez,Jason,NULL,Male,Hispanic,10/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +64573,74625,67601,Probation,Rodriguez,Jason,NULL,Male,Hispanic,10/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +64573,74625,67601,Probation,Rodriguez,Jason,NULL,Male,Hispanic,10/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64578,74630,67606,Probation,Ferreiradasliva,Marcile,NULL,Female,Hispanic,01/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/3/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +64578,74630,67606,Probation,Ferreiradasliva,Marcile,NULL,Female,Hispanic,01/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/3/14 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +64578,74630,67606,Probation,Ferreiradasliva,Marcile,NULL,Female,Hispanic,01/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +35807,75540,68415,PRETRIAL,Martin,Xavier,NULL,Male,African-American,09/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +35807,75540,68415,PRETRIAL,Martin,Xavier,NULL,Male,African-American,09/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +35807,75540,68415,PRETRIAL,Martin,Xavier,NULL,Male,African-American,09/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64588,74641,67616,Probation,Conly,James,Harris,Male,Caucasian,05/11/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +64588,74641,67616,Probation,Conly,James,Harris,Male,Caucasian,05/11/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +64588,74641,67616,Probation,Conly,James,Harris,Male,Caucasian,05/11/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +53239,74648,67622,Probation,Romero,Joel,NULL,Male,Hispanic,08/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +53239,74648,67622,Probation,Romero,Joel,NULL,Male,Hispanic,08/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +53239,74648,67622,Probation,Romero,Joel,NULL,Male,Hispanic,08/24/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57039,74620,67596,PRETRIAL,Andujar,Jessica,NULL,Female,Caucasian,12/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +57039,74620,67596,PRETRIAL,Andujar,Jessica,NULL,Female,Caucasian,12/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +57039,74620,67596,PRETRIAL,Andujar,Jessica,NULL,Female,Caucasian,12/28/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +8445,74612,7995,PRETRIAL,linn,tammie,NULL,Female,Caucasian,09/01/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,Copy,1,0 +8445,74612,7995,PRETRIAL,linn,tammie,NULL,Female,Caucasian,09/01/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,Copy,1,0 +8445,74612,7995,PRETRIAL,linn,tammie,NULL,Female,Caucasian,09/01/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,2,Medium,18,Risk of Failure to Appear,29,9,High,Copy,1,0 +64581,74633,67609,PRETRIAL,Wilson,Frank,NULL,Male,African-American,07/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +64581,74633,67609,PRETRIAL,Wilson,Frank,NULL,Male,African-American,07/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +64581,74633,67609,PRETRIAL,Wilson,Frank,NULL,Male,African-American,07/01/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64587,74640,67615,PRETRIAL,Caldreon,Yvette,NULL,Female,Hispanic,11/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,7/3/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +64587,74640,67615,PRETRIAL,Caldreon,Yvette,NULL,Female,Hispanic,11/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,7/3/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +64587,74640,67615,PRETRIAL,Caldreon,Yvette,NULL,Female,Hispanic,11/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59159,74650,67623,Probation,Hincapie,John,NULL,Male,Hispanic,12/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +59159,74650,67623,Probation,Hincapie,John,NULL,Male,Hispanic,12/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +59159,74650,67623,Probation,Hincapie,John,NULL,Male,Hispanic,12/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64577,74629,67605,PRETRIAL,SLASINSKY,TIMOTHY,NULL,Male,Caucasian,12/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/3/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +64577,74629,67605,PRETRIAL,SLASINSKY,TIMOTHY,NULL,Male,Caucasian,12/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/3/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +64577,74629,67605,PRETRIAL,SLASINSKY,TIMOTHY,NULL,Male,Caucasian,12/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63906,74643,67617,Probation,Rogers,Tameka,NULL,Female,African-American,07/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,7/3/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,Copy,1,0 +63906,74643,67617,Probation,Rogers,Tameka,NULL,Female,African-American,07/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,7/3/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,Copy,1,0 +63906,74643,67617,Probation,Rogers,Tameka,NULL,Female,African-American,07/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +64566,74615,67591,PRETRIAL,Goins,Tynesha,S,Female,African-American,08/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +64566,74615,67591,PRETRIAL,Goins,Tynesha,S,Female,African-American,08/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +64566,74615,67591,PRETRIAL,Goins,Tynesha,S,Female,African-American,08/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64571,74622,67598,Probation,shannon,Tucker,NULL,Female,Caucasian,04/19/81,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +64571,74622,67598,Probation,shannon,Tucker,NULL,Female,Caucasian,04/19/81,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +64571,74622,67598,Probation,shannon,Tucker,NULL,Female,Caucasian,04/19/81,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +56409,74636,58383,PRETRIAL,lacy,chance,NULL,Male,Caucasian,08/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/3/14 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,Copy,1,0 +56409,74636,58383,PRETRIAL,lacy,chance,NULL,Male,Caucasian,08/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/3/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,Copy,1,0 +56409,74636,58383,PRETRIAL,lacy,chance,NULL,Male,Caucasian,08/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +57551,74624,67600,Probation,Calvino,Oscar,NULL,Male,Hispanic,08/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +57551,74624,67600,Probation,Calvino,Oscar,NULL,Male,Hispanic,08/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +57551,74624,67600,Probation,Calvino,Oscar,NULL,Male,Hispanic,08/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64579,74631,67607,PRETRIAL,Rucker,Darren,NULL,Male,African-American,08/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +64579,74631,67607,PRETRIAL,Rucker,Darren,NULL,Male,African-American,08/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +64579,74631,67607,PRETRIAL,Rucker,Darren,NULL,Male,African-American,08/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +28844,74645,67619,PRETRIAL,BARTZ,DANIELLE,NULL,Female,Caucasian,11/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +28844,74645,67619,PRETRIAL,BARTZ,DANIELLE,NULL,Female,Caucasian,11/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +28844,74645,67619,PRETRIAL,BARTZ,DANIELLE,NULL,Female,Caucasian,11/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +64586,74649,67614,PRETRIAL,Rogers,James,NULL,Male,Hispanic,01/29/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,Copy,1,0 +64586,74649,67614,PRETRIAL,Rogers,James,NULL,Male,Hispanic,01/29/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,Copy,1,0 +64586,74649,67614,PRETRIAL,Rogers,James,NULL,Male,Hispanic,01/29/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +64580,74632,67608,PRETRIAL,MILLS,TAVARIS,NULL,Male,African-American,09/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +64580,74632,67608,PRETRIAL,MILLS,TAVARIS,NULL,Male,African-American,09/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +64580,74632,67608,PRETRIAL,MILLS,TAVARIS,NULL,Male,African-American,09/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64570,74619,67595,PRETRIAL,MORRIS,CHRISTOPHER,NULL,Male,African-American,11/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,New,1,0 +64570,74619,67595,PRETRIAL,MORRIS,CHRISTOPHER,NULL,Male,African-American,11/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +64570,74619,67595,PRETRIAL,MORRIS,CHRISTOPHER,NULL,Male,African-American,11/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64565,74614,67590,PRETRIAL,Irons,Richard,G,Male,African-American,04/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +64565,74614,67590,PRETRIAL,Irons,Richard,G,Male,African-American,04/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +64565,74614,67590,PRETRIAL,Irons,Richard,G,Male,African-American,04/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64567,74616,67592,PRETRIAL,ROBINSON,TAYESHA,CAROL,Female,African-American,07/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +64567,74616,67592,PRETRIAL,ROBINSON,TAYESHA,CAROL,Female,African-American,07/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +64567,74616,67592,PRETRIAL,ROBINSON,TAYESHA,CAROL,Female,African-American,07/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64584,74637,67612,Probation,LAFOSSE,RALPH,NULL,Male,African-American,04/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/3/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +64584,74637,67612,Probation,LAFOSSE,RALPH,NULL,Male,African-American,04/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/3/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +64584,74637,67612,Probation,LAFOSSE,RALPH,NULL,Male,African-American,04/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64589,74644,67618,Probation,Bailey,Samuel,Anthony,Male,African-American,02/17/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/3/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +64589,74644,67618,Probation,Bailey,Samuel,Anthony,Male,African-American,02/17/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/3/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +64589,74644,67618,Probation,Bailey,Samuel,Anthony,Male,African-American,02/17/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64591,74647,67621,Probation,Ross,Donald,NULL,Male,Caucasian,08/02/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/3/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +64591,74647,67621,Probation,Ross,Donald,NULL,Male,Caucasian,08/02/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/3/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +64591,74647,67621,Probation,Ross,Donald,NULL,Male,Caucasian,08/02/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64574,74626,67602,Probation,LOPEZ,XIOMARA,D,Female,Hispanic,12/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +64574,74626,67602,Probation,LOPEZ,XIOMARA,D,Female,Hispanic,12/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +64574,74626,67602,Probation,LOPEZ,XIOMARA,D,Female,Hispanic,12/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64569,74618,67594,Probation,Martinez,Nicholas,NULL,Male,Hispanic,05/27/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/3/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +64569,74618,67594,Probation,Martinez,Nicholas,NULL,Male,Hispanic,05/27/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/3/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +64569,74618,67594,Probation,Martinez,Nicholas,NULL,Male,Hispanic,05/27/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64564,74613,67589,PRETRIAL,Caron,Valeri,NULL,Female,Caucasian,09/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +64564,74613,67589,PRETRIAL,Caron,Valeri,NULL,Female,Caucasian,09/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +64564,74613,67589,PRETRIAL,Caron,Valeri,NULL,Female,Caucasian,09/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64572,74621,67597,PRETRIAL,Noll,Jerome,NULL,Male,Caucasian,08/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/3/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +64572,74621,67597,PRETRIAL,Noll,Jerome,NULL,Male,Caucasian,08/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/3/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +64572,74621,67597,PRETRIAL,Noll,Jerome,NULL,Male,Caucasian,08/14/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64582,74634,67610,Probation,Serrano sosa,Josue,NULL,Male,Hispanic,04/17/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/3/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +64582,74634,67610,Probation,Serrano sosa,Josue,NULL,Male,Hispanic,04/17/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/3/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +64582,74634,67610,Probation,Serrano sosa,Josue,NULL,Male,Hispanic,04/17/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64606,74668,67640,PRETRIAL,Persad,Kristy,Lillian,Female,Other,01/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +64606,74668,67640,PRETRIAL,Persad,Kristy,Lillian,Female,Other,01/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +64606,74668,67640,PRETRIAL,Persad,Kristy,Lillian,Female,Other,01/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58385,74655,67628,PRETRIAL,Burgess,Justin,P,Male,African-American,09/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +58385,74655,67628,PRETRIAL,Burgess,Justin,P,Male,African-American,09/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +58385,74655,67628,PRETRIAL,Burgess,Justin,P,Male,African-American,09/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64601,74663,67635,PRETRIAL,Washington,Crystal,NULL,Female,African-American,10/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +64601,74663,67635,PRETRIAL,Washington,Crystal,NULL,Female,African-American,10/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.36,7,Medium,New,1,0 +64601,74663,67635,PRETRIAL,Washington,Crystal,NULL,Female,African-American,10/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64596,74658,67630,PRETRIAL,Coley,Osevelt,NULL,Male,African-American,08/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +64596,74658,67630,PRETRIAL,Coley,Osevelt,NULL,Male,African-American,08/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +64596,74658,67630,PRETRIAL,Coley,Osevelt,NULL,Male,African-American,08/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64603,74665,67637,PRETRIAL,Lopresti,Michele,Kimberly,Female,Caucasian,01/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +64603,74665,67637,PRETRIAL,Lopresti,Michele,Kimberly,Female,Caucasian,01/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +64603,74665,67637,PRETRIAL,Lopresti,Michele,Kimberly,Female,Caucasian,01/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64594,74653,67626,PRETRIAL,Gillis,Jashon,NULL,Male,African-American,06/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +64594,74653,67626,PRETRIAL,Gillis,Jashon,NULL,Male,African-American,06/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +64594,74653,67626,PRETRIAL,Gillis,Jashon,NULL,Male,African-American,06/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58386,74657,60614,PRETRIAL,Owen,Shamar,Lloyd,Male,African-American,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,Copy,1,0 +58386,74657,60614,PRETRIAL,Owen,Shamar,Lloyd,Male,African-American,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,Copy,1,0 +58386,74657,60614,PRETRIAL,Owen,Shamar,Lloyd,Male,African-American,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +64604,74666,67638,PRETRIAL,Velizsantana,Lilia,C,Female,Caucasian,10/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +64604,74666,67638,PRETRIAL,Velizsantana,Lilia,C,Female,Caucasian,10/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +64604,74666,67638,PRETRIAL,Velizsantana,Lilia,C,Female,Caucasian,10/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64593,74652,67625,PRETRIAL,Fox,James,NULL,Male,Caucasian,08/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +64593,74652,67625,PRETRIAL,Fox,James,NULL,Male,Caucasian,08/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +64593,74652,67625,PRETRIAL,Fox,James,NULL,Male,Caucasian,08/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64599,74661,67633,PRETRIAL,Campbell,Maquira,NULL,Female,African-American,12/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +64599,74661,67633,PRETRIAL,Campbell,Maquira,NULL,Female,African-American,12/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +64599,74661,67633,PRETRIAL,Campbell,Maquira,NULL,Female,African-American,12/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64600,74662,67634,PRETRIAL,Accius,Junnie,NULL,Female,African-American,05/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +64600,74662,67634,PRETRIAL,Accius,Junnie,NULL,Female,African-American,05/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +64600,74662,67634,PRETRIAL,Accius,Junnie,NULL,Female,African-American,05/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +42289,74654,67627,PRETRIAL,Wells,Jacarre,NULL,Male,African-American,04/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +42289,74654,67627,PRETRIAL,Wells,Jacarre,NULL,Male,African-American,04/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,4,High,8,Risk of Recidivism,0.21,8,High,New,1,0 +42289,74654,67627,PRETRIAL,Wells,Jacarre,NULL,Male,African-American,04/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64592,74651,67624,PRETRIAL,Wilson,Eddie,NULL,Male,African-American,02/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +64592,74651,67624,PRETRIAL,Wilson,Eddie,NULL,Male,African-American,02/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +64592,74651,67624,PRETRIAL,Wilson,Eddie,NULL,Male,African-American,02/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64602,74664,67636,PRETRIAL,King,Ralvin,NULL,Male,Other,01/31/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/4/14 0:00,1,Low,7,Risk of Violence,-4.45,1,Low,New,1,0 +64602,74664,67636,PRETRIAL,King,Ralvin,NULL,Male,Other,01/31/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/4/14 0:00,1,Low,8,Risk of Recidivism,-2.88,1,Low,New,1,0 +64602,74664,67636,PRETRIAL,King,Ralvin,NULL,Male,Other,01/31/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/4/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64598,74659,67631,PRETRIAL,Fallacaro,Ariel,NULL,Male,Caucasian,06/17/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.76,9,High,New,1,0 +64598,74659,67631,PRETRIAL,Fallacaro,Ariel,NULL,Male,Caucasian,06/17/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +64598,74659,67631,PRETRIAL,Fallacaro,Ariel,NULL,Male,Caucasian,06/17/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64595,74656,67629,PRETRIAL,Eliazar,Peterson,NULL,Male,African-American,07/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +64595,74656,67629,PRETRIAL,Eliazar,Peterson,NULL,Male,African-American,07/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +64595,74656,67629,PRETRIAL,Eliazar,Peterson,NULL,Male,African-American,07/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64605,74667,67639,PRETRIAL,Brzuchalski,Douglas,Anthony,Male,Caucasian,10/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +64605,74667,67639,PRETRIAL,Brzuchalski,Douglas,Anthony,Male,Caucasian,10/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +64605,74667,67639,PRETRIAL,Brzuchalski,Douglas,Anthony,Male,Caucasian,10/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57604,74677,67649,Probation,JOHN,MICHAEL,NULL,Male,Caucasian,05/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/5/14 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +57604,74677,67649,Probation,JOHN,MICHAEL,NULL,Male,Caucasian,05/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/5/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +57604,74677,67649,Probation,JOHN,MICHAEL,NULL,Male,Caucasian,05/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/5/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64607,74669,67641,PRETRIAL,Dukes,Kenitra,NULL,Male,African-American,01/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +64607,74669,67641,PRETRIAL,Dukes,Kenitra,NULL,Male,African-American,01/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +64607,74669,67641,PRETRIAL,Dukes,Kenitra,NULL,Male,African-American,01/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64612,74675,67647,PRETRIAL,Mercado,Glenn,NULL,Male,Caucasian,10/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +64612,74675,67647,PRETRIAL,Mercado,Glenn,NULL,Male,Caucasian,10/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +64612,74675,67647,PRETRIAL,Mercado,Glenn,NULL,Male,Caucasian,10/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64608,74671,67643,PRETRIAL,Lopez,Brandi,NULL,Female,Hispanic,01/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +64608,74671,67643,PRETRIAL,Lopez,Brandi,NULL,Female,Hispanic,01/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +64608,74671,67643,PRETRIAL,Lopez,Brandi,NULL,Female,Hispanic,01/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +64610,74673,67645,PRETRIAL,Jarovits,Erik,NULL,Male,Caucasian,06/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +64610,74673,67645,PRETRIAL,Jarovits,Erik,NULL,Male,Caucasian,06/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +64610,74673,67645,PRETRIAL,Jarovits,Erik,NULL,Male,Caucasian,06/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64615,74680,67652,PRETRIAL,Hoskins,Frederick,NULL,Male,African-American,09/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,New,1,0 +64615,74680,67652,PRETRIAL,Hoskins,Frederick,NULL,Male,African-American,09/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +64615,74680,67652,PRETRIAL,Hoskins,Frederick,NULL,Male,African-American,09/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64613,74678,67650,PRETRIAL,Belter,Jennifer,NULL,Female,Caucasian,10/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +64613,74678,67650,PRETRIAL,Belter,Jennifer,NULL,Female,Caucasian,10/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +64613,74678,67650,PRETRIAL,Belter,Jennifer,NULL,Female,Caucasian,10/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +10695,74670,67642,PRETRIAL,CHILDS,RAYSHAWN,D,Male,African-American,03/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,4,High,7,Risk of Violence,-0.68,9,High,New,1,0 +10695,74670,67642,PRETRIAL,CHILDS,RAYSHAWN,D,Male,African-American,03/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,4,High,8,Risk of Recidivism,0.65,10,High,New,1,0 +10695,74670,67642,PRETRIAL,CHILDS,RAYSHAWN,D,Male,African-American,03/19/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64611,74674,67646,PRETRIAL,Addison,Richard,NULL,Male,African-American,12/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +64611,74674,67646,PRETRIAL,Addison,Richard,NULL,Male,African-American,12/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +64611,74674,67646,PRETRIAL,Addison,Richard,NULL,Male,African-American,12/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64609,74672,67644,PRETRIAL,Veira,Andre,NULL,Male,African-American,11/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +64609,74672,67644,PRETRIAL,Veira,Andre,NULL,Male,African-American,11/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.02,10,High,New,1,0 +64609,74672,67644,PRETRIAL,Veira,Andre,NULL,Male,African-American,11/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64614,74679,67651,PRETRIAL,Breau,Fritz,NULL,Male,Other,03/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +64614,74679,67651,PRETRIAL,Breau,Fritz,NULL,Male,Other,03/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +64614,74679,67651,PRETRIAL,Breau,Fritz,NULL,Male,Other,03/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64616,74681,67653,PRETRIAL,Jeanbaptiste,Les,NULL,Male,African-American,08/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/5/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +64616,74681,67653,PRETRIAL,Jeanbaptiste,Les,NULL,Male,African-American,08/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/5/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +64616,74681,67653,PRETRIAL,Jeanbaptiste,Les,NULL,Male,African-American,08/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +46587,74676,67648,PRETRIAL,DIAZ,AMANDA,NULL,Female,Hispanic,02/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +46587,74676,67648,PRETRIAL,DIAZ,AMANDA,NULL,Female,Hispanic,02/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,8,High,New,1,0 +46587,74676,67648,PRETRIAL,DIAZ,AMANDA,NULL,Female,Hispanic,02/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64627,74697,67667,PRETRIAL,MILLER,EILEEN,THERESA,Female,Caucasian,09/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/6/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +64627,74697,67667,PRETRIAL,MILLER,EILEEN,THERESA,Female,Caucasian,09/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/6/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +64627,74697,67667,PRETRIAL,MILLER,EILEEN,THERESA,Female,Caucasian,09/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +64617,74684,67656,PRETRIAL,Adrien,David,NULL,Male,African-American,12/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +64617,74684,67656,PRETRIAL,Adrien,David,NULL,Male,African-American,12/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +64617,74684,67656,PRETRIAL,Adrien,David,NULL,Male,African-American,12/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64622,74689,67661,PRETRIAL,Cleveland,Matthew,NULL,Male,Caucasian,11/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +64622,74689,67661,PRETRIAL,Cleveland,Matthew,NULL,Male,Caucasian,11/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +64622,74689,67661,PRETRIAL,Cleveland,Matthew,NULL,Male,Caucasian,11/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +22158,74702,67672,PRETRIAL,urquhart,kirk,NULL,Male,Other,12/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/6/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +22158,74702,67672,PRETRIAL,urquhart,kirk,NULL,Male,Other,12/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/6/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +22158,74702,67672,PRETRIAL,urquhart,kirk,NULL,Male,Other,12/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/6/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64624,74693,67664,PRETRIAL,MILLER,TRAVIS,DEMALE,Male,African-American,08/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,New,1,0 +64624,74693,67664,PRETRIAL,MILLER,TRAVIS,DEMALE,Male,African-American,08/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +64624,74693,67664,PRETRIAL,MILLER,TRAVIS,DEMALE,Male,African-American,08/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64619,74686,67658,PRETRIAL,Ghent,Angel,NULL,Female,African-American,11/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +64619,74686,67658,PRETRIAL,Ghent,Angel,NULL,Female,African-American,11/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,8,High,New,1,0 +64619,74686,67658,PRETRIAL,Ghent,Angel,NULL,Female,African-American,11/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64621,74688,67660,PRETRIAL,CULVER,TAWONA,YVETTE,Female,African-American,09/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,2,Medium,7,Risk of Violence,-1.8,5,Medium,New,1,0 +64621,74688,67660,PRETRIAL,CULVER,TAWONA,YVETTE,Female,African-American,09/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +64621,74688,67660,PRETRIAL,CULVER,TAWONA,YVETTE,Female,African-American,09/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64625,74695,67665,PRETRIAL,GILLISPIE,RICHARD,WESLEY,Male,African-American,10/31/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/6/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +64625,74695,67665,PRETRIAL,GILLISPIE,RICHARD,WESLEY,Male,African-American,10/31/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/6/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +64625,74695,67665,PRETRIAL,GILLISPIE,RICHARD,WESLEY,Male,African-American,10/31/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +10384,74691,40411,PRETRIAL,SALUM,ADAM,JAMES,Male,Caucasian,04/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,Copy,1,0 +10384,74691,40411,PRETRIAL,SALUM,ADAM,JAMES,Male,Caucasian,04/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,Copy,1,0 +10384,74691,40411,PRETRIAL,SALUM,ADAM,JAMES,Male,Caucasian,04/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +64630,74700,67670,PRETRIAL,ZOGBY,ROBERT,NULL,Male,Caucasian,08/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/6/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +64630,74700,67670,PRETRIAL,ZOGBY,ROBERT,NULL,Male,Caucasian,08/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/6/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +64630,74700,67670,PRETRIAL,ZOGBY,ROBERT,NULL,Male,Caucasian,08/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64626,74696,67666,PRETRIAL,GRIFFIN,JERROD,A,Male,African-American,10/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +64626,74696,67666,PRETRIAL,GRIFFIN,JERROD,A,Male,African-American,10/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +64626,74696,67666,PRETRIAL,GRIFFIN,JERROD,A,Male,African-American,10/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +34932,74692,67663,PRETRIAL,Troutman,Dominique,NULL,Male,African-American,02/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +34932,74692,67663,PRETRIAL,Troutman,Dominique,NULL,Male,African-American,02/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +34932,74692,67663,PRETRIAL,Troutman,Dominique,NULL,Male,African-American,02/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64629,74699,67669,PRETRIAL,BARREDO,MANUEL,D,Male,Hispanic,02/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +64629,74699,67669,PRETRIAL,BARREDO,MANUEL,D,Male,Hispanic,02/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +64629,74699,67669,PRETRIAL,BARREDO,MANUEL,D,Male,Hispanic,02/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64620,74687,67659,PRETRIAL,SMITH,DELIA,NULL,Female,Native American,11/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +64620,74687,67659,PRETRIAL,SMITH,DELIA,NULL,Female,Native American,11/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +64620,74687,67659,PRETRIAL,SMITH,DELIA,NULL,Female,Native American,11/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64631,74701,67671,PRETRIAL,Colbert,Eric,NULL,Male,African-American,05/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/6/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +64631,74701,67671,PRETRIAL,Colbert,Eric,NULL,Male,African-American,05/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/6/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +64631,74701,67671,PRETRIAL,Colbert,Eric,NULL,Male,African-American,05/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +10621,74694,10147,PRETRIAL,LEON,MIGUEL,A,Male,Caucasian,06/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,Copy,1,0 +10621,74694,10147,PRETRIAL,LEON,MIGUEL,A,Male,Caucasian,06/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,Copy,1,0 +10621,74694,10147,PRETRIAL,LEON,MIGUEL,A,Male,Caucasian,06/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +1104,74682,67654,PRETRIAL,Beasley,Devin,Bernard,Male,African-American,12/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +1104,74682,67654,PRETRIAL,Beasley,Devin,Bernard,Male,African-American,12/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,4,High,8,Risk of Recidivism,0.29,8,High,New,1,0 +1104,74682,67654,PRETRIAL,Beasley,Devin,Bernard,Male,African-American,12/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +7167,74683,67655,Probation,Kenol,Mark,NULL,Male,African-American,10/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +7167,74683,67655,Probation,Kenol,Mark,NULL,Male,African-American,10/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +7167,74683,67655,Probation,Kenol,Mark,NULL,Male,African-American,10/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +64623,74690,67662,PRETRIAL,PHILLIPS,CHARLES,R,Male,African-American,12/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +64623,74690,67662,PRETRIAL,PHILLIPS,CHARLES,R,Male,African-American,12/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +64623,74690,67662,PRETRIAL,PHILLIPS,CHARLES,R,Male,African-American,12/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64628,74698,67668,PRETRIAL,Martinez,Christopher,NULL,Male,Hispanic,07/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +64628,74698,67668,PRETRIAL,Martinez,Christopher,NULL,Male,Hispanic,07/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +64628,74698,67668,PRETRIAL,Martinez,Christopher,NULL,Male,Hispanic,07/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64618,74685,67657,PRETRIAL,Jackson,Robert,NULL,Male,African-American,12/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +64618,74685,67657,PRETRIAL,Jackson,Robert,NULL,Male,African-American,12/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +64618,74685,67657,PRETRIAL,Jackson,Robert,NULL,Male,African-American,12/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64646,74719,67688,PRETRIAL,CARFORA,DAWN,NULL,Female,Caucasian,04/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +64646,74719,67688,PRETRIAL,CARFORA,DAWN,NULL,Female,Caucasian,04/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +64646,74719,67688,PRETRIAL,CARFORA,DAWN,NULL,Female,Caucasian,04/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +45781,74732,67701,PRETRIAL,Cruz,Carlos,NULL,Male,Hispanic,09/19/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.91,5,Medium,New,1,0 +45781,74732,67701,PRETRIAL,Cruz,Carlos,NULL,Male,Hispanic,09/19/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +45781,74732,67701,PRETRIAL,Cruz,Carlos,NULL,Male,Hispanic,09/19/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +64650,74727,67696,PRETRIAL,Holzberg,David,NULL,Male,Caucasian,02/26/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/7/14 0:00,2,Medium,7,Risk of Violence,-2.83,2,Low,New,1,0 +64650,74727,67696,PRETRIAL,Holzberg,David,NULL,Male,Caucasian,02/26/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +64650,74727,67696,PRETRIAL,Holzberg,David,NULL,Male,Caucasian,02/26/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/7/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64634,74706,67675,PRETRIAL,Noble,Jaison,Cornelius,Male,African-American,04/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.01,8,High,New,1,0 +64634,74706,67675,PRETRIAL,Noble,Jaison,Cornelius,Male,African-American,04/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +64634,74706,67675,PRETRIAL,Noble,Jaison,Cornelius,Male,African-American,04/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63996,74724,67693,Probation,Nicole-Carter,Christina,NULL,Female,Caucasian,11/09/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,4,High,7,Risk of Violence,-0.27,10,High,New,1,0 +63996,74724,67693,Probation,Nicole-Carter,Christina,NULL,Female,Caucasian,11/09/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,4,High,8,Risk of Recidivism,1.52,10,High,New,1,0 +63996,74724,67693,Probation,Nicole-Carter,Christina,NULL,Female,Caucasian,11/09/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,4,High,18,Risk of Failure to Appear,42,10,High,New,1,0 +64639,74711,67680,PRETRIAL,HARRISON,RAVEN,L,Female,African-American,06/25/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +64639,74711,67680,PRETRIAL,HARRISON,RAVEN,L,Female,African-American,06/25/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,4,High,8,Risk of Recidivism,0.05,8,High,New,1,0 +64639,74711,67680,PRETRIAL,HARRISON,RAVEN,L,Female,African-American,06/25/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +22383,74703,21548,PRETRIAL,LINTON,ORAL,NULL,Male,African-American,11/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,Copy,1,0 +22383,74703,21548,PRETRIAL,LINTON,ORAL,NULL,Male,African-American,11/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,Copy,1,0 +22383,74703,21548,PRETRIAL,LINTON,ORAL,NULL,Male,African-American,11/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +64652,74729,67698,Probation,Castro,Petronila,NULL,Female,Hispanic,07/17/80,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/7/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +64652,74729,67698,Probation,Castro,Petronila,NULL,Female,Hispanic,07/17/80,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/7/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +64652,74729,67698,Probation,Castro,Petronila,NULL,Female,Hispanic,07/17/80,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64636,74708,67677,PRETRIAL,Phillips,Sonia,NULL,Female,Other,07/10/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/7/14 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +64636,74708,67677,PRETRIAL,Phillips,Sonia,NULL,Female,Other,07/10/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/7/14 0:00,1,Low,8,Risk of Recidivism,-2.65,1,Low,New,1,0 +64636,74708,67677,PRETRIAL,Phillips,Sonia,NULL,Female,Other,07/10/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +19514,74715,67684,PRETRIAL,Caggiano,Vincent,J,Male,Caucasian,09/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +19514,74715,67684,PRETRIAL,Caggiano,Vincent,J,Male,Caucasian,09/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +19514,74715,67684,PRETRIAL,Caggiano,Vincent,J,Male,Caucasian,09/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64648,74722,67691,Probation,MEJIASFLORES,GABRIEL,A,Male,Hispanic,08/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/7/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +64648,74722,67691,Probation,MEJIASFLORES,GABRIEL,A,Male,Hispanic,08/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/7/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +64648,74722,67691,Probation,MEJIASFLORES,GABRIEL,A,Male,Hispanic,08/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64644,74717,67686,PRETRIAL,Roldan,Natalie,NULL,Female,Hispanic,01/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/7/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +64644,74717,67686,PRETRIAL,Roldan,Natalie,NULL,Female,Hispanic,01/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/7/14 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +64644,74717,67686,PRETRIAL,Roldan,Natalie,NULL,Female,Hispanic,01/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64641,74713,67682,PRETRIAL,Aponte,Henry,NULL,Male,African-American,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +64641,74713,67682,PRETRIAL,Aponte,Henry,NULL,Male,African-American,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +64641,74713,67682,PRETRIAL,Aponte,Henry,NULL,Male,African-American,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +49532,74725,67694,PRETRIAL,Blagman,Latif,NULL,Male,African-American,04/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +49532,74725,67694,PRETRIAL,Blagman,Latif,NULL,Male,African-American,04/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +49532,74725,67694,PRETRIAL,Blagman,Latif,NULL,Male,African-American,04/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64632,74704,67673,PRETRIAL,Daigle,Randy,NULL,Male,Caucasian,01/17/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/7/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +64632,74704,67673,PRETRIAL,Daigle,Randy,NULL,Male,Caucasian,01/17/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/7/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +64632,74704,67673,PRETRIAL,Daigle,Randy,NULL,Male,Caucasian,01/17/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +43447,74721,67690,PRETRIAL,Hawkins,James,NULL,Male,African-American,08/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +43447,74721,67690,PRETRIAL,Hawkins,James,NULL,Male,African-American,08/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +43447,74721,67690,PRETRIAL,Hawkins,James,NULL,Male,African-American,08/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64637,74709,67678,PRETRIAL,Arellano,Jay Fernandeo,NULL,Male,Hispanic,11/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +64637,74709,67678,PRETRIAL,Arellano,Jay Fernandeo,NULL,Male,Hispanic,11/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +64637,74709,67678,PRETRIAL,Arellano,Jay Fernandeo,NULL,Male,Hispanic,11/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64635,74707,67676,PRETRIAL,CRAWFORD,TERRYL,NULL,Male,African-American,05/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/7/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +64635,74707,67676,PRETRIAL,CRAWFORD,TERRYL,NULL,Male,African-American,05/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/7/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +64635,74707,67676,PRETRIAL,CRAWFORD,TERRYL,NULL,Male,African-American,05/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64642,74714,67683,PRETRIAL,Francois,Frantz,NULL,Male,African-American,09/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-1.77,5,Medium,New,1,0 +64642,74714,67683,PRETRIAL,Francois,Frantz,NULL,Male,African-American,09/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +64642,74714,67683,PRETRIAL,Francois,Frantz,NULL,Male,African-American,09/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64643,74716,67685,PRETRIAL,HILL,QUINELLA,SELANDRIA,Female,African-American,02/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +64643,74716,67685,PRETRIAL,HILL,QUINELLA,SELANDRIA,Female,African-American,02/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +64643,74716,67685,PRETRIAL,HILL,QUINELLA,SELANDRIA,Female,African-American,02/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +49641,74723,67692,PRETRIAL,stella,charles,NULL,Male,Caucasian,06/22/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/7/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +49641,74723,67692,PRETRIAL,stella,charles,NULL,Male,Caucasian,06/22/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/7/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +49641,74723,67692,PRETRIAL,stella,charles,NULL,Male,Caucasian,06/22/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +35842,74731,67700,PRETRIAL,Cabrera,Pablo,NULL,Male,Caucasian,09/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +35842,74731,67700,PRETRIAL,Cabrera,Pablo,NULL,Male,Caucasian,09/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +35842,74731,67700,PRETRIAL,Cabrera,Pablo,NULL,Male,Caucasian,09/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64638,74710,67679,PRETRIAL,MALDONADO,ELLIOT,ANGEL,Male,Caucasian,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/7/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +64638,74710,67679,PRETRIAL,MALDONADO,ELLIOT,ANGEL,Male,Caucasian,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/7/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +64638,74710,67679,PRETRIAL,MALDONADO,ELLIOT,ANGEL,Male,Caucasian,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64651,74728,67697,PRETRIAL,PUENTE,LUIS,NULL,Male,Hispanic,08/24/64,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +64651,74728,67697,PRETRIAL,PUENTE,LUIS,NULL,Male,Hispanic,08/24/64,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +64651,74728,67697,PRETRIAL,PUENTE,LUIS,NULL,Male,Hispanic,08/24/64,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64645,74718,67687,PRETRIAL,SANTIAGO,JORGE,ANTONIO,Male,Caucasian,10/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/7/14 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +64645,74718,67687,PRETRIAL,SANTIAGO,JORGE,ANTONIO,Male,Caucasian,10/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +64645,74718,67687,PRETRIAL,SANTIAGO,JORGE,ANTONIO,Male,Caucasian,10/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/7/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64647,74720,67689,PRETRIAL,karp,gary,NULL,Male,Caucasian,05/17/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +64647,74720,67689,PRETRIAL,karp,gary,NULL,Male,Caucasian,05/17/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +64647,74720,67689,PRETRIAL,karp,gary,NULL,Male,Caucasian,05/17/48,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64633,74705,67674,PRETRIAL,AMIREH,ALAA,MUSTAFA,Male,Arabic,03/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +64633,74705,67674,PRETRIAL,AMIREH,ALAA,MUSTAFA,Male,Arabic,03/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +64633,74705,67674,PRETRIAL,AMIREH,ALAA,MUSTAFA,Male,Arabic,03/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +55401,74733,67702,Probation,gomez,alex,NULL,Male,Caucasian,06/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,New,1,0 +55401,74733,67702,Probation,gomez,alex,NULL,Male,Caucasian,06/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.84,10,High,New,1,0 +55401,74733,67702,Probation,gomez,alex,NULL,Male,Caucasian,06/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +64640,74712,67681,PRETRIAL,HERRERA,KEVIN,IVAN,Male,Caucasian,11/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +64640,74712,67681,PRETRIAL,HERRERA,KEVIN,IVAN,Male,Caucasian,11/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +64640,74712,67681,PRETRIAL,HERRERA,KEVIN,IVAN,Male,Caucasian,11/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/7/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +49338,74726,67695,PRETRIAL,McLaughlin,Mary,NULL,Female,Caucasian,10/14/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +49338,74726,67695,PRETRIAL,McLaughlin,Mary,NULL,Female,Caucasian,10/14/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +49338,74726,67695,PRETRIAL,McLaughlin,Mary,NULL,Female,Caucasian,10/14/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +38838,74747,67713,PRETRIAL,Jenkins,James,Feon,Male,African-American,09/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,4,High,7,Risk of Violence,-0.66,9,High,New,1,0 +38838,74747,67713,PRETRIAL,Jenkins,James,Feon,Male,African-American,09/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,4,High,8,Risk of Recidivism,0.92,10,High,New,1,0 +38838,74747,67713,PRETRIAL,Jenkins,James,Feon,Male,African-American,09/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50955,74739,67709,PRETRIAL,burdin,Bruce,allen,Male,Caucasian,10/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +50955,74739,67709,PRETRIAL,burdin,Bruce,allen,Male,Caucasian,10/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +50955,74739,67709,PRETRIAL,burdin,Bruce,allen,Male,Caucasian,10/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64341,74741,67350,PRETRIAL,Marcantel,Brian,NULL,Male,Caucasian,08/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,Copy,1,0 +64341,74741,67350,PRETRIAL,Marcantel,Brian,NULL,Male,Caucasian,08/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,Copy,1,0 +64341,74741,67350,PRETRIAL,Marcantel,Brian,NULL,Male,Caucasian,08/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +64667,74754,67720,PRETRIAL,Shrock,John,NULL,Male,Caucasian,10/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +64667,74754,67720,PRETRIAL,Shrock,John,NULL,Male,Caucasian,10/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +64667,74754,67720,PRETRIAL,Shrock,John,NULL,Male,Caucasian,10/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64663,74749,67715,PRETRIAL,LEE,ANTHONY,NULL,Male,African-American,07/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/8/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +64663,74749,67715,PRETRIAL,LEE,ANTHONY,NULL,Male,African-American,07/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/8/14 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +64663,74749,67715,PRETRIAL,LEE,ANTHONY,NULL,Male,African-American,07/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64669,74757,67722,DRRD,Butler,Eddrick,Lee,Male,African-American,12/08/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/8/14 0:00,4,High,7,Risk of Violence,-0.44,10,High,New,1,0 +64669,74757,67722,DRRD,Butler,Eddrick,Lee,Male,African-American,12/08/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/8/14 0:00,4,High,8,Risk of Recidivism,0.88,10,High,New,1,0 +64669,74757,67722,DRRD,Butler,Eddrick,Lee,Male,African-American,12/08/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/8/14 0:00,4,High,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +64657,74736,67706,PRETRIAL,Hunley,Wanda,NULL,Female,African-American,01/20/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/8/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +64657,74736,67706,PRETRIAL,Hunley,Wanda,NULL,Female,African-American,01/20/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/8/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +64657,74736,67706,PRETRIAL,Hunley,Wanda,NULL,Female,African-American,01/20/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64655,74735,67704,PRETRIAL,Wiggins,Jamilah,Tauquia,Female,African-American,08/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +64655,74735,67704,PRETRIAL,Wiggins,Jamilah,Tauquia,Female,African-American,08/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +64655,74735,67704,PRETRIAL,Wiggins,Jamilah,Tauquia,Female,African-American,08/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64656,74737,67707,PRETRIAL,Ross,Ryko,NULL,Male,Caucasian,10/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +64656,74737,67707,PRETRIAL,Ross,Ryko,NULL,Male,Caucasian,10/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +64656,74737,67707,PRETRIAL,Ross,Ryko,NULL,Male,Caucasian,10/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64659,74744,67710,PRETRIAL,Smith,Shantel,NULL,Female,African-American,06/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +64659,74744,67710,PRETRIAL,Smith,Shantel,NULL,Female,African-American,06/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +64659,74744,67710,PRETRIAL,Smith,Shantel,NULL,Female,African-American,06/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64661,74746,67712,PRETRIAL,England,Amanda,NULL,Female,Other,03/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/8/14 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +64661,74746,67712,PRETRIAL,England,Amanda,NULL,Female,Other,03/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +64661,74746,67712,PRETRIAL,England,Amanda,NULL,Female,Other,03/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/8/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64664,74751,67717,PRETRIAL,RUCKER,VINCENT,NULL,Male,African-American,01/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +64664,74751,67717,PRETRIAL,RUCKER,VINCENT,NULL,Male,African-American,01/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +64664,74751,67717,PRETRIAL,RUCKER,VINCENT,NULL,Male,African-American,01/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64658,74738,67708,PRETRIAL,Travis,Brian,Roger Croft,Male,Caucasian,07/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +64658,74738,67708,PRETRIAL,Travis,Brian,Roger Croft,Male,Caucasian,07/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +64658,74738,67708,PRETRIAL,Travis,Brian,Roger Croft,Male,Caucasian,07/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64668,74755,67721,PRETRIAL,MIRANTI,JOHN,NULL,Male,Caucasian,11/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +64668,74755,67721,PRETRIAL,MIRANTI,JOHN,NULL,Male,Caucasian,11/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +64668,74755,67721,PRETRIAL,MIRANTI,JOHN,NULL,Male,Caucasian,11/01/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64576,74743,67604,PRETRIAL,pierre,danege,NULL,Female,African-American,09/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +64576,74743,67604,PRETRIAL,pierre,danege,NULL,Female,African-American,09/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,Copy,1,0 +64576,74743,67604,PRETRIAL,pierre,danege,NULL,Female,African-American,09/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +64665,74752,67718,PRETRIAL,SHERWOOD,MCDOWELL,NULL,Male,Caucasian,06/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +64665,74752,67718,PRETRIAL,SHERWOOD,MCDOWELL,NULL,Male,Caucasian,06/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,4,High,8,Risk of Recidivism,0.7,10,High,New,1,0 +64665,74752,67718,PRETRIAL,SHERWOOD,MCDOWELL,NULL,Male,Caucasian,06/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/8/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +2708,74750,67716,Probation,Alfieri,Evelina,NULL,Female,Caucasian,12/23/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +2708,74750,67716,Probation,Alfieri,Evelina,NULL,Female,Caucasian,12/23/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,7,Medium,New,1,0 +2708,74750,67716,Probation,Alfieri,Evelina,NULL,Female,Caucasian,12/23/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/8/14 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +64662,74748,67714,PRETRIAL,Fernandez,Randall,NULL,Male,Caucasian,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +64662,74748,67714,PRETRIAL,Fernandez,Randall,NULL,Male,Caucasian,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +64662,74748,67714,PRETRIAL,Fernandez,Randall,NULL,Male,Caucasian,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64660,74745,67711,PRETRIAL,OFARRILL,EDGARDO,NULL,Male,Caucasian,09/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/8/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +64660,74745,67711,PRETRIAL,OFARRILL,EDGARDO,NULL,Male,Caucasian,09/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/8/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +64660,74745,67711,PRETRIAL,OFARRILL,EDGARDO,NULL,Male,Caucasian,09/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64677,74766,67731,PRETRIAL,Gillion,Devone,NULL,Male,African-American,09/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,2,Medium,7,Risk of Violence,-1.26,7,Medium,New,1,0 +64677,74766,67731,PRETRIAL,Gillion,Devone,NULL,Male,African-American,09/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +64677,74766,67731,PRETRIAL,Gillion,Devone,NULL,Male,African-American,09/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64688,74782,67744,Probation,badillo,edgar,NULL,Male,Hispanic,10/27/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/9/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +64688,74782,67744,Probation,badillo,edgar,NULL,Male,Hispanic,10/27/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/9/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +64688,74782,67744,Probation,badillo,edgar,NULL,Male,Hispanic,10/27/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64680,74769,67734,PRETRIAL,Pires,Anthony,NULL,Male,African-American,10/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +64680,74769,67734,PRETRIAL,Pires,Anthony,NULL,Male,African-American,10/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +64680,74769,67734,PRETRIAL,Pires,Anthony,NULL,Male,African-American,10/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +64672,74761,67726,PRETRIAL,Fletcher,Rohan,Orane,Male,Other,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/9/14 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +64672,74761,67726,PRETRIAL,Fletcher,Rohan,Orane,Male,Other,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/9/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +64672,74761,67726,PRETRIAL,Fletcher,Rohan,Orane,Male,Other,09/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64696,74790,67750,DRRD,Johnson,Joshua,NULL,Male,African-American,08/28/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/9/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +64696,74790,67750,DRRD,Johnson,Joshua,NULL,Male,African-American,08/28/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,6,Medium,New,1,0 +64696,74790,67750,DRRD,Johnson,Joshua,NULL,Male,African-American,08/28/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/9/14 0:00,2,Medium,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +62567,74773,65294,Probation,Minuto,Antoinette,NULL,Female,Caucasian,03/18/78,17,All Scales,Intake,English,Post Sentence,Probation,Married,7/9/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,Copy,1,0 +62567,74773,65294,Probation,Minuto,Antoinette,NULL,Female,Caucasian,03/18/78,17,All Scales,Intake,English,Post Sentence,Probation,Married,7/9/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,Copy,1,0 +62567,74773,65294,Probation,Minuto,Antoinette,NULL,Female,Caucasian,03/18/78,17,All Scales,Intake,English,Post Sentence,Probation,Married,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +44216,74771,44298,Probation,Mills,Pablo,NULL,Male,Hispanic,06/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,Copy,1,0 +44216,74771,44298,Probation,Mills,Pablo,NULL,Male,Hispanic,06/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,Copy,1,0 +44216,74771,44298,Probation,Mills,Pablo,NULL,Male,Hispanic,06/09/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +64671,74759,67724,PRETRIAL,Harmon,Louise,NULL,Female,African-American,11/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +64671,74759,67724,PRETRIAL,Harmon,Louise,NULL,Female,African-American,11/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +64671,74759,67724,PRETRIAL,Harmon,Louise,NULL,Female,African-American,11/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64675,74764,67729,PRETRIAL,TORRES,MICHEL,NULL,Male,Caucasian,09/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/9/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +64675,74764,67729,PRETRIAL,TORRES,MICHEL,NULL,Male,Caucasian,09/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/9/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +64675,74764,67729,PRETRIAL,TORRES,MICHEL,NULL,Male,Caucasian,09/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64694,74789,67749,Probation,fabian,howard,NULL,Male,Caucasian,08/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/9/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +64694,74789,67749,Probation,fabian,howard,NULL,Male,Caucasian,08/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/9/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +64694,74789,67749,Probation,fabian,howard,NULL,Male,Caucasian,08/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64679,74768,67733,PRETRIAL,JOHNSON,CARLETHA,MARIA,Female,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +64679,74768,67733,PRETRIAL,JOHNSON,CARLETHA,MARIA,Female,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +64679,74768,67733,PRETRIAL,JOHNSON,CARLETHA,MARIA,Female,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64686,74785,67747,PRETRIAL,cooper,antonio,NULL,Male,African-American,02/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +64686,74785,67747,PRETRIAL,cooper,antonio,NULL,Male,African-American,02/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +64686,74785,67747,PRETRIAL,cooper,antonio,NULL,Male,African-American,02/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +24326,74760,67725,PRETRIAL,Arboleda,Alex,NULL,Male,African-American,12/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +24326,74760,67725,PRETRIAL,Arboleda,Alex,NULL,Male,African-American,12/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +24326,74760,67725,PRETRIAL,Arboleda,Alex,NULL,Male,African-American,12/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64674,74763,67728,PRETRIAL,Levy-Buissereth,Janelle,H,Female,Other,11/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +64674,74763,67728,PRETRIAL,Levy-Buissereth,Janelle,H,Female,Other,11/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +64674,74763,67728,PRETRIAL,Levy-Buissereth,Janelle,H,Female,Other,11/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64678,74767,67732,PRETRIAL,THOMAS,DEMONT,D,Male,African-American,03/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.53,3,Low,New,1,0 +64678,74767,67732,PRETRIAL,THOMAS,DEMONT,D,Male,African-American,03/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +64678,74767,67732,PRETRIAL,THOMAS,DEMONT,D,Male,African-American,03/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64687,74781,67743,Probation,lopez,tracy,NULL,Male,Hispanic,07/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/9/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +64687,74781,67743,Probation,lopez,tracy,NULL,Male,Hispanic,07/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/9/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +64687,74781,67743,Probation,lopez,tracy,NULL,Male,Hispanic,07/26/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +23734,74779,67741,PRETRIAL,DIAZ,CHRISTOPER,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/14 0:00,4,High,7,Risk of Violence,-0.63,9,High,New,1,0 +23734,74779,67741,PRETRIAL,DIAZ,CHRISTOPER,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/14 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +23734,74779,67741,PRETRIAL,DIAZ,CHRISTOPER,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/9/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64670,74758,67723,PRETRIAL,COLLINS,KADARELL,K,Male,African-American,01/01/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,4,High,7,Risk of Violence,-0.34,10,High,New,1,0 +64670,74758,67723,PRETRIAL,COLLINS,KADARELL,K,Male,African-American,01/01/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,4,High,8,Risk of Recidivism,1.06,10,High,New,1,0 +64670,74758,67723,PRETRIAL,COLLINS,KADARELL,K,Male,African-American,01/01/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64676,74765,67730,PRETRIAL,Espinosa,Javier,NULL,Male,Caucasian,05/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/9/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +64676,74765,67730,PRETRIAL,Espinosa,Javier,NULL,Male,Caucasian,05/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/9/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +64676,74765,67730,PRETRIAL,Espinosa,Javier,NULL,Male,Caucasian,05/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64682,74772,67736,Probation,Rhule,Taylor,anthony,Male,African-American,09/06/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/9/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +64682,74772,67736,Probation,Rhule,Taylor,anthony,Male,African-American,09/06/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/9/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +64682,74772,67736,Probation,Rhule,Taylor,anthony,Male,African-American,09/06/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +17083,74786,53924,PRETRIAL,BENITEZ,ANTHONY,NULL,Male,Caucasian,01/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/14 0:00,4,High,7,Risk of Violence,-0.52,10,High,Copy,1,0 +17083,74786,53924,PRETRIAL,BENITEZ,ANTHONY,NULL,Male,Caucasian,01/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/14 0:00,4,High,8,Risk of Recidivism,0.53,9,High,Copy,1,0 +17083,74786,53924,PRETRIAL,BENITEZ,ANTHONY,NULL,Male,Caucasian,01/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/9/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +64692,74788,67748,Probation,adams,Jasmine,aroshina,Female,African-American,09/29/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/9/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +64692,74788,67748,Probation,adams,Jasmine,aroshina,Female,African-American,09/29/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/9/14 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +64692,74788,67748,Probation,adams,Jasmine,aroshina,Female,African-American,09/29/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64681,74770,67735,PRETRIAL,REID,NATHAN,JOSHUA,Male,African-American,06/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.99,9,High,New,1,0 +64681,74770,67735,PRETRIAL,REID,NATHAN,JOSHUA,Male,African-American,06/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +64681,74770,67735,PRETRIAL,REID,NATHAN,JOSHUA,Male,African-American,06/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64684,74778,67740,Probation,garcia,tayhaan,d,Male,Hispanic,01/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/9/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +64684,74778,67740,Probation,garcia,tayhaan,d,Male,Hispanic,01/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/9/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +64684,74778,67740,Probation,garcia,tayhaan,d,Male,Hispanic,01/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64673,74762,67727,PRETRIAL,Cyma,Jean,Pierre,Male,Oriental,03/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,4,High,7,Risk of Violence,-1.05,8,High,New,1,0 +64673,74762,67727,PRETRIAL,Cyma,Jean,Pierre,Male,Oriental,03/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +64673,74762,67727,PRETRIAL,Cyma,Jean,Pierre,Male,Oriental,03/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/9/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +56119,63980,58056,PRETRIAL,rodriguez,roland,NULL,Male,Native American,09/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/9/14 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +56119,63980,58056,PRETRIAL,rodriguez,roland,NULL,Male,Native American,09/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +56119,63980,58056,PRETRIAL,rodriguez,roland,NULL,Male,Native American,09/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/9/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64712,74812,67767,Probation,Rodriguez,Leonardo,NULL,Male,Hispanic,03/01/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/10/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +64712,74812,67767,Probation,Rodriguez,Leonardo,NULL,Male,Hispanic,03/01/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/10/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +64712,74812,67767,Probation,Rodriguez,Leonardo,NULL,Male,Hispanic,03/01/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64701,74796,67755,PRETRIAL,Irizarry,Jose,NULL,Male,Caucasian,12/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +64701,74796,67755,PRETRIAL,Irizarry,Jose,NULL,Male,Caucasian,12/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +64701,74796,67755,PRETRIAL,Irizarry,Jose,NULL,Male,Caucasian,12/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64703,74799,67758,PRETRIAL,Nevarez,Jonathan,NULL,Male,Caucasian,07/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +64703,74799,67758,PRETRIAL,Nevarez,Jonathan,NULL,Male,Caucasian,07/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +64703,74799,67758,PRETRIAL,Nevarez,Jonathan,NULL,Male,Caucasian,07/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64708,74804,67763,PRETRIAL,Willis,Robyn,Athlyn,Female,African-American,01/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +64708,74804,67763,PRETRIAL,Willis,Robyn,Athlyn,Female,African-American,01/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +64708,74804,67763,PRETRIAL,Willis,Robyn,Athlyn,Female,African-American,01/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64697,74791,67751,PRETRIAL,Morley,Edmond,NULL,Male,Caucasian,06/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +64697,74791,67751,PRETRIAL,Morley,Edmond,NULL,Male,Caucasian,06/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +64697,74791,67751,PRETRIAL,Morley,Edmond,NULL,Male,Caucasian,06/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64710,74807,67765,PRETRIAL,Bunker,Leonard,NULL,Male,Caucasian,12/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/10/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +64710,74807,67765,PRETRIAL,Bunker,Leonard,NULL,Male,Caucasian,12/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/10/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +64710,74807,67765,PRETRIAL,Bunker,Leonard,NULL,Male,Caucasian,12/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52386,74809,53679,PRETRIAL,FERMOILE,JOSEPH,NULL,Male,Caucasian,10/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/14 0:00,2,Medium,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +52386,74809,53679,PRETRIAL,FERMOILE,JOSEPH,NULL,Male,Caucasian,10/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,Copy,1,0 +52386,74809,53679,PRETRIAL,FERMOILE,JOSEPH,NULL,Male,Caucasian,10/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +64714,74814,67769,Probation,Ortega,Gerardo,NULL,Male,Hispanic,05/03/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/10/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +64714,74814,67769,Probation,Ortega,Gerardo,NULL,Male,Hispanic,05/03/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/10/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +64714,74814,67769,Probation,Ortega,Gerardo,NULL,Male,Hispanic,05/03/69,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64699,74793,67753,PRETRIAL,Lebron,Rosalie,NULL,Male,Caucasian,10/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +64699,74793,67753,PRETRIAL,Lebron,Rosalie,NULL,Male,Caucasian,10/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +64699,74793,67753,PRETRIAL,Lebron,Rosalie,NULL,Male,Caucasian,10/10/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64706,74802,67761,PRETRIAL,Hall,Jamar,NULL,Male,African-American,08/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +64706,74802,67761,PRETRIAL,Hall,Jamar,NULL,Male,African-American,08/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +64706,74802,67761,PRETRIAL,Hall,Jamar,NULL,Male,African-American,08/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64711,74810,67766,Probation,Franco-Abugattas,Nicola,NULL,Male,Arabic,10/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,New,1,0 +64711,74810,67766,Probation,Franco-Abugattas,Nicola,NULL,Male,Arabic,10/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +64711,74810,67766,Probation,Franco-Abugattas,Nicola,NULL,Male,Arabic,10/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +64438,74806,67447,PRETRIAL,Michalek,Joseph,NULL,Male,Caucasian,05/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,Copy,1,0 +64438,74806,67447,PRETRIAL,Michalek,Joseph,NULL,Male,Caucasian,05/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,Copy,1,0 +64438,74806,67447,PRETRIAL,Michalek,Joseph,NULL,Male,Caucasian,05/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +64705,74801,67760,PRETRIAL,Echavarria,Natalia,NULL,Female,Caucasian,12/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +64705,74801,67760,PRETRIAL,Echavarria,Natalia,NULL,Female,Caucasian,12/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +64705,74801,67760,PRETRIAL,Echavarria,Natalia,NULL,Female,Caucasian,12/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64568,74808,67593,PRETRIAL,EASTMAN,ALEJANDRO,NULL,Male,Caucasian,11/16/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/10/14 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,Copy,1,0 +64568,74808,67593,PRETRIAL,EASTMAN,ALEJANDRO,NULL,Male,Caucasian,11/16/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/10/14 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,Copy,1,0 +64568,74808,67593,PRETRIAL,EASTMAN,ALEJANDRO,NULL,Male,Caucasian,11/16/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +64715,74815,67770,Probation,harzand,ashkan,NULL,Male,Caucasian,08/28/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +64715,74815,67770,Probation,harzand,ashkan,NULL,Male,Caucasian,08/28/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.75,10,High,New,1,0 +64715,74815,67770,Probation,harzand,ashkan,NULL,Male,Caucasian,08/28/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64702,74797,67756,PRETRIAL,Marks,Keith,Alan,Male,Caucasian,10/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +64702,74797,67756,PRETRIAL,Marks,Keith,Alan,Male,Caucasian,10/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +64702,74797,67756,PRETRIAL,Marks,Keith,Alan,Male,Caucasian,10/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63646,74811,66564,Probation,RATLIFF,AINSLEY,NICOLE,Female,Caucasian,09/20/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +63646,74811,66564,Probation,RATLIFF,AINSLEY,NICOLE,Female,Caucasian,09/20/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +63646,74811,66564,Probation,RATLIFF,AINSLEY,NICOLE,Female,Caucasian,09/20/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +64707,74803,67762,PRETRIAL,Myrick,Damon,Jerod,Male,African-American,02/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +64707,74803,67762,PRETRIAL,Myrick,Damon,Jerod,Male,African-American,02/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +64707,74803,67762,PRETRIAL,Myrick,Damon,Jerod,Male,African-American,02/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64709,74805,67764,PRETRIAL,HYMAN,WAYNE,MCCOO,Male,African-American,10/23/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +64709,74805,67764,PRETRIAL,HYMAN,WAYNE,MCCOO,Male,African-American,10/23/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +64709,74805,67764,PRETRIAL,HYMAN,WAYNE,MCCOO,Male,African-American,10/23/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64704,74800,67759,PRETRIAL,Beaver,Bettina,NULL,Female,Caucasian,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +64704,74800,67759,PRETRIAL,Beaver,Bettina,NULL,Female,Caucasian,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +64704,74800,67759,PRETRIAL,Beaver,Bettina,NULL,Female,Caucasian,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +64700,74795,67754,PRETRIAL,Pastwa,Catrina,pauline,Female,Caucasian,05/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +64700,74795,67754,PRETRIAL,Pastwa,Catrina,pauline,Female,Caucasian,05/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +64700,74795,67754,PRETRIAL,Pastwa,Catrina,pauline,Female,Caucasian,05/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64713,74813,67768,PRETRIAL,chance,willie,NULL,Male,African-American,07/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +64713,74813,67768,PRETRIAL,chance,willie,NULL,Male,African-American,07/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +64713,74813,67768,PRETRIAL,chance,willie,NULL,Male,African-American,07/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64698,74792,67752,PRETRIAL,Vidurrazaga,Charles,NULL,Male,Caucasian,02/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,2,Medium,7,Risk of Violence,-2.78,2,Low,New,1,0 +64698,74792,67752,PRETRIAL,Vidurrazaga,Charles,NULL,Male,Caucasian,02/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +64698,74792,67752,PRETRIAL,Vidurrazaga,Charles,NULL,Male,Caucasian,02/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/10/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +47859,74834,67789,PRETRIAL,Thomas,Maurice,NULL,Male,African-American,11/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +47859,74834,67789,PRETRIAL,Thomas,Maurice,NULL,Male,African-American,11/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +47859,74834,67789,PRETRIAL,Thomas,Maurice,NULL,Male,African-American,11/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +51099,74821,67776,PRETRIAL,Sparks,Eric,NULL,Male,African-American,07/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +51099,74821,67776,PRETRIAL,Sparks,Eric,NULL,Male,African-American,07/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +51099,74821,67776,PRETRIAL,Sparks,Eric,NULL,Male,African-American,07/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64717,74818,67773,PRETRIAL,Gedeon,Samuel,NULL,Male,African-American,05/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +64717,74818,67773,PRETRIAL,Gedeon,Samuel,NULL,Male,African-American,05/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +64717,74818,67773,PRETRIAL,Gedeon,Samuel,NULL,Male,African-American,05/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64739,74839,67794,PRETRIAL,ZIMMERMAN,BETH,NULL,Female,Caucasian,12/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +64739,74839,67794,PRETRIAL,ZIMMERMAN,BETH,NULL,Female,Caucasian,12/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +64739,74839,67794,PRETRIAL,ZIMMERMAN,BETH,NULL,Female,Caucasian,12/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +8441,74826,67781,PRETRIAL,LOUISTAL,DEON,NULL,Male,African-American,08/28/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +8441,74826,67781,PRETRIAL,LOUISTAL,DEON,NULL,Male,African-American,08/28/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +8441,74826,67781,PRETRIAL,LOUISTAL,DEON,NULL,Male,African-American,08/28/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +64720,74822,67777,PRETRIAL,Perrelli,Nichola,NULL,Male,Caucasian,12/07/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/11/14 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +64720,74822,67777,PRETRIAL,Perrelli,Nichola,NULL,Male,Caucasian,12/07/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +64720,74822,67777,PRETRIAL,Perrelli,Nichola,NULL,Male,Caucasian,12/07/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/11/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64725,74829,67784,Probation,Clarke,Tarike,NULL,Female,African-American,12/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +64725,74829,67784,Probation,Clarke,Tarike,NULL,Female,African-American,12/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +64725,74829,67784,Probation,Clarke,Tarike,NULL,Female,African-American,12/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64722,74824,67779,PRETRIAL,Dudley,Pamela,NULL,Male,African-American,04/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +64722,74824,67779,PRETRIAL,Dudley,Pamela,NULL,Male,African-American,04/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +64722,74824,67779,PRETRIAL,Dudley,Pamela,NULL,Male,African-American,04/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64727,74831,67786,PRETRIAL,ROFF,FREDERICK,NULL,Male,Caucasian,02/23/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +64727,74831,67786,PRETRIAL,ROFF,FREDERICK,NULL,Male,Caucasian,02/23/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +64727,74831,67786,PRETRIAL,ROFF,FREDERICK,NULL,Male,Caucasian,02/23/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,41,10,High,New,1,0 +64736,74836,67791,PRETRIAL,Volf,Dan,NULL,Male,Caucasian,02/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +64736,74836,67791,PRETRIAL,Volf,Dan,NULL,Male,Caucasian,02/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +64736,74836,67791,PRETRIAL,Volf,Dan,NULL,Male,Caucasian,02/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64718,74819,67774,PRETRIAL,Honora,Christopher,NULL,Male,African-American,04/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +64718,74819,67774,PRETRIAL,Honora,Christopher,NULL,Male,African-American,04/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +64718,74819,67774,PRETRIAL,Honora,Christopher,NULL,Male,African-American,04/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64721,74823,67778,PRETRIAL,Anderson,Harold,Keith,Male,African-American,02/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +64721,74823,67778,PRETRIAL,Anderson,Harold,Keith,Male,African-American,02/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +64721,74823,67778,PRETRIAL,Anderson,Harold,Keith,Male,African-American,02/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64724,74828,67783,PRETRIAL,Champagne,Joseph,NULL,Male,African-American,08/16/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/11/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +64724,74828,67783,PRETRIAL,Champagne,Joseph,NULL,Male,African-American,08/16/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/11/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +64724,74828,67783,PRETRIAL,Champagne,Joseph,NULL,Male,African-American,08/16/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +64726,74830,67785,Probation,Long,Radley,NULL,Male,African-American,01/03/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +64726,74830,67785,Probation,Long,Radley,NULL,Male,African-American,01/03/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +64726,74830,67785,Probation,Long,Radley,NULL,Male,African-American,01/03/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64737,74837,67792,PRETRIAL,Flowers,Tyler,NULL,Male,African-American,04/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,4,High,7,Risk of Violence,-0.32,10,High,New,1,0 +64737,74837,67792,PRETRIAL,Flowers,Tyler,NULL,Male,African-American,04/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +64737,74837,67792,PRETRIAL,Flowers,Tyler,NULL,Male,African-American,04/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/11/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64723,74825,67780,PRETRIAL,Li,Xiaorong,NULL,Female,Asian,09/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +64723,74825,67780,PRETRIAL,Li,Xiaorong,NULL,Female,Asian,09/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +64723,74825,67780,PRETRIAL,Li,Xiaorong,NULL,Female,Asian,09/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64738,74838,67793,Probation,Ventura,Starlin,NULL,Male,Hispanic,04/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/14 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +64738,74838,67793,Probation,Ventura,Starlin,NULL,Male,Hispanic,04/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +64738,74838,67793,Probation,Ventura,Starlin,NULL,Male,Hispanic,04/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/11/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +32147,74817,67772,PRETRIAL,Lanford,Cynthia,NULL,Female,Caucasian,07/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +32147,74817,67772,PRETRIAL,Lanford,Cynthia,NULL,Female,Caucasian,07/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,10,High,New,1,0 +32147,74817,67772,PRETRIAL,Lanford,Cynthia,NULL,Female,Caucasian,07/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +64733,74833,67788,Probation,Pierson,Timothy,NULL,Male,Caucasian,06/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/11/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +64733,74833,67788,Probation,Pierson,Timothy,NULL,Male,Caucasian,06/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/11/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +64733,74833,67788,Probation,Pierson,Timothy,NULL,Male,Caucasian,06/25/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64719,74820,67775,PRETRIAL,Prestino,Joseph,NULL,Male,Caucasian,12/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +64719,74820,67775,PRETRIAL,Prestino,Joseph,NULL,Male,Caucasian,12/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +64719,74820,67775,PRETRIAL,Prestino,Joseph,NULL,Male,Caucasian,12/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +37392,74841,67796,PRETRIAL,Hankerson,Herman,NULL,Male,African-American,07/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +37392,74841,67796,PRETRIAL,Hankerson,Herman,NULL,Male,African-American,07/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,New,1,0 +37392,74841,67796,PRETRIAL,Hankerson,Herman,NULL,Male,African-American,07/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +64745,74848,67802,PRETRIAL,Sanchez,Richard,NULL,Male,Caucasian,07/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +64745,74848,67802,PRETRIAL,Sanchez,Richard,NULL,Male,Caucasian,07/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +64745,74848,67802,PRETRIAL,Sanchez,Richard,NULL,Male,Caucasian,07/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +43425,74846,43368,PRETRIAL,Ducenord,Patrick,NULL,Male,African-American,01/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/12/14 0:00,2,Medium,7,Risk of Violence,-2.89,2,Low,Copy,1,0 +43425,74846,43368,PRETRIAL,Ducenord,Patrick,NULL,Male,African-American,01/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,Copy,1,0 +43425,74846,43368,PRETRIAL,Ducenord,Patrick,NULL,Male,African-American,01/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/12/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +64748,74851,67805,PRETRIAL,Crown,Evan,NULL,Male,Caucasian,01/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +64748,74851,67805,PRETRIAL,Crown,Evan,NULL,Male,Caucasian,01/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +64748,74851,67805,PRETRIAL,Crown,Evan,NULL,Male,Caucasian,01/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64742,74844,67799,PRETRIAL,SNELL,MERLEE,LAVON,Male,African-American,02/12/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +64742,74844,67799,PRETRIAL,SNELL,MERLEE,LAVON,Male,African-American,02/12/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +64742,74844,67799,PRETRIAL,SNELL,MERLEE,LAVON,Male,African-American,02/12/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64746,74849,67803,PRETRIAL,Higgs,Denante,NULL,Male,African-American,11/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +64746,74849,67803,PRETRIAL,Higgs,Denante,NULL,Male,African-American,11/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +64746,74849,67803,PRETRIAL,Higgs,Denante,NULL,Male,African-American,11/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +12387,74853,11879,PRETRIAL,FLOYD,MILES,NULL,Male,African-American,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,Copy,1,0 +12387,74853,11879,PRETRIAL,FLOYD,MILES,NULL,Male,African-American,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,Copy,1,0 +12387,74853,11879,PRETRIAL,FLOYD,MILES,NULL,Male,African-American,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +64743,74845,67800,PRETRIAL,Carl,Sidney,NULL,Male,African-American,08/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +64743,74845,67800,PRETRIAL,Carl,Sidney,NULL,Male,African-American,08/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +64743,74845,67800,PRETRIAL,Carl,Sidney,NULL,Male,African-American,08/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64741,74843,67798,PRETRIAL,Foster,Garvin,NULL,Male,African-American,02/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +64741,74843,67798,PRETRIAL,Foster,Garvin,NULL,Male,African-American,02/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +64741,74843,67798,PRETRIAL,Foster,Garvin,NULL,Male,African-American,02/13/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64749,74852,67806,PRETRIAL,CREW,BRIAN,NULL,Male,African-American,08/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +64749,74852,67806,PRETRIAL,CREW,BRIAN,NULL,Male,African-American,08/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +64749,74852,67806,PRETRIAL,CREW,BRIAN,NULL,Male,African-American,08/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64747,74850,67804,PRETRIAL,Brooks,Mickeal,NULL,Female,African-American,07/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/12/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +64747,74850,67804,PRETRIAL,Brooks,Mickeal,NULL,Female,African-American,07/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/12/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +64747,74850,67804,PRETRIAL,Brooks,Mickeal,NULL,Female,African-American,07/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64744,74847,67801,PRETRIAL,CONEY,CEDRIC,DEQUAN,Male,African-American,04/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,4,High,7,Risk of Violence,-0.52,10,High,New,1,0 +64744,74847,67801,PRETRIAL,CONEY,CEDRIC,DEQUAN,Male,African-American,04/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,4,High,8,Risk of Recidivism,1.1,10,High,New,1,0 +64744,74847,67801,PRETRIAL,CONEY,CEDRIC,DEQUAN,Male,African-American,04/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/12/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64740,74842,67797,PRETRIAL,Stebbing,John,NULL,Male,Caucasian,04/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/12/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +64740,74842,67797,PRETRIAL,Stebbing,John,NULL,Male,Caucasian,04/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/12/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +64740,74842,67797,PRETRIAL,Stebbing,John,NULL,Male,Caucasian,04/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/12/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64753,74860,67810,PRETRIAL,Johnson,Channey,NULL,Female,African-American,12/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +64753,74860,67810,PRETRIAL,Johnson,Channey,NULL,Female,African-American,12/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +64753,74860,67810,PRETRIAL,Johnson,Channey,NULL,Female,African-American,12/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64756,74863,67813,PRETRIAL,DONN,NATALIE,NULL,Female,Caucasian,06/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +64756,74863,67813,PRETRIAL,DONN,NATALIE,NULL,Female,Caucasian,06/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +64756,74863,67813,PRETRIAL,DONN,NATALIE,NULL,Female,Caucasian,06/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64751,74855,67808,PRETRIAL,WEISS,WILLIAM,NULL,Male,Caucasian,11/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +64751,74855,67808,PRETRIAL,WEISS,WILLIAM,NULL,Male,Caucasian,11/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +64751,74855,67808,PRETRIAL,WEISS,WILLIAM,NULL,Male,Caucasian,11/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +64761,74868,67818,PRETRIAL,BURNS,ROBERT,DONTE,Female,African-American,10/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +64761,74868,67818,PRETRIAL,BURNS,ROBERT,DONTE,Female,African-American,10/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +64761,74868,67818,PRETRIAL,BURNS,ROBERT,DONTE,Female,African-American,10/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64763,74871,67820,PRETRIAL,Garcia,Jose,Angel,Male,Caucasian,09/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,Copy,1,0 +64763,74871,67820,PRETRIAL,Garcia,Jose,Angel,Male,Caucasian,09/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,Copy,1,0 +64763,74871,67820,PRETRIAL,Garcia,Jose,Angel,Male,Caucasian,09/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +34467,74857,33626,PRETRIAL,Douze,Mike,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,Copy,1,0 +34467,74857,33626,PRETRIAL,Douze,Mike,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,Copy,1,0 +34467,74857,33626,PRETRIAL,Douze,Mike,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +64759,74866,67816,PRETRIAL,JOHNSON,XAVIER,RAMONDE,Male,African-American,03/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +64759,74866,67816,PRETRIAL,JOHNSON,XAVIER,RAMONDE,Male,African-American,03/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +64759,74866,67816,PRETRIAL,JOHNSON,XAVIER,RAMONDE,Male,African-American,03/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +6833,74858,51760,Probation,Hay,Stephanie,Denise,Female,African-American,05/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.39,3,Low,Copy,1,0 +6833,74858,51760,Probation,Hay,Stephanie,Denise,Female,African-American,05/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,10,High,Copy,1,0 +6833,74858,51760,Probation,Hay,Stephanie,Denise,Female,African-American,05/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,9,High,Copy,1,0 +64758,74865,67815,PRETRIAL,GOODINSON,MARIA,NULL,Female,Caucasian,03/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/13/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +64758,74865,67815,PRETRIAL,GOODINSON,MARIA,NULL,Female,Caucasian,03/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/13/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +64758,74865,67815,PRETRIAL,GOODINSON,MARIA,NULL,Female,Caucasian,03/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64764,74872,67821,PRETRIAL,MANZANAREZ,ESTEBAN,NULL,Male,Hispanic,09/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/13/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +64764,74872,67821,PRETRIAL,MANZANAREZ,ESTEBAN,NULL,Male,Hispanic,09/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/13/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +64764,74872,67821,PRETRIAL,MANZANAREZ,ESTEBAN,NULL,Male,Hispanic,09/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +656,74859,350,Broward County,DAVIS,LAKISHA,LATRICE,Female,African-American,01/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,4,High,7,Risk of Violence,-0.67,9,High,Copy,1,0 +656,74859,350,Broward County,DAVIS,LAKISHA,LATRICE,Female,African-American,01/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,4,High,8,Risk of Recidivism,0.4,9,High,Copy,1,0 +656,74859,350,Broward County,DAVIS,LAKISHA,LATRICE,Female,African-American,01/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,4,High,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +64757,74864,67814,PRETRIAL,MELENDEZ,DEFERINO,SOLANO,Male,Other,04/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/13/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +64757,74864,67814,PRETRIAL,MELENDEZ,DEFERINO,SOLANO,Male,Other,04/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/13/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +64757,74864,67814,PRETRIAL,MELENDEZ,DEFERINO,SOLANO,Male,Other,04/20/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64752,74856,67809,PRETRIAL,Deatley,Edward,NULL,Male,Caucasian,02/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +64752,74856,67809,PRETRIAL,Deatley,Edward,NULL,Male,Caucasian,02/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +64752,74856,67809,PRETRIAL,Deatley,Edward,NULL,Male,Caucasian,02/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64760,74867,67817,PRETRIAL,WARREN,DANIELLE,NULL,Female,African-American,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,4,High,7,Risk of Violence,-0.95,9,High,New,1,0 +64760,74867,67817,PRETRIAL,WARREN,DANIELLE,NULL,Female,African-American,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,4,High,8,Risk of Recidivism,0.16,9,High,New,1,0 +64760,74867,67817,PRETRIAL,WARREN,DANIELLE,NULL,Female,African-American,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,4,High,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +64762,74869,67819,PRETRIAL,FIELDS,MAX,NULL,Male,African-American,12/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.31,7,Medium,New,1,0 +64762,74869,67819,PRETRIAL,FIELDS,MAX,NULL,Male,African-American,12/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.84,10,High,New,1,0 +64762,74869,67819,PRETRIAL,FIELDS,MAX,NULL,Male,African-American,12/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +64754,74861,67811,PRETRIAL,ADHEMAR,SHANICE,NULL,Female,African-American,08/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +64754,74861,67811,PRETRIAL,ADHEMAR,SHANICE,NULL,Female,African-American,08/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +64754,74861,67811,PRETRIAL,ADHEMAR,SHANICE,NULL,Female,African-American,08/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64755,74862,67812,PRETRIAL,Sagee,Liel,NULL,Male,Caucasian,12/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +64755,74862,67812,PRETRIAL,Sagee,Liel,NULL,Male,Caucasian,12/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +64755,74862,67812,PRETRIAL,Sagee,Liel,NULL,Male,Caucasian,12/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +47884,74911,67858,Probation,dixon,erin,NULL,Female,African-American,06/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +47884,74911,67858,Probation,dixon,erin,NULL,Female,African-American,06/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,9,High,New,1,0 +47884,74911,67858,Probation,dixon,erin,NULL,Female,African-American,06/18/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64773,74883,67831,PRETRIAL,Naccarato,Giovanni,NULL,Male,Caucasian,08/14/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/14/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +64773,74883,67831,PRETRIAL,Naccarato,Giovanni,NULL,Male,Caucasian,08/14/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/14/14 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +64773,74883,67831,PRETRIAL,Naccarato,Giovanni,NULL,Male,Caucasian,08/14/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64778,74890,67838,PRETRIAL,Lewis,John,NULL,Male,African-American,10/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/14/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +64778,74890,67838,PRETRIAL,Lewis,John,NULL,Male,African-American,10/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/14/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +64778,74890,67838,PRETRIAL,Lewis,John,NULL,Male,African-American,10/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64772,74882,67830,PRETRIAL,Alpern,Anthony,Leroy,Male,African-American,08/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +64772,74882,67830,PRETRIAL,Alpern,Anthony,Leroy,Male,African-American,08/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +64772,74882,67830,PRETRIAL,Alpern,Anthony,Leroy,Male,African-American,08/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64766,74877,67825,PRETRIAL,TONGE,CURTIS,NULL,Male,African-American,04/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/14/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +64766,74877,67825,PRETRIAL,TONGE,CURTIS,NULL,Male,African-American,04/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/14/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +64766,74877,67825,PRETRIAL,TONGE,CURTIS,NULL,Male,African-American,04/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59357,74898,67845,PRETRIAL,Ibanez,Marco,NULL,Male,Hispanic,04/15/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +59357,74898,67845,PRETRIAL,Ibanez,Marco,NULL,Male,Hispanic,04/15/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +59357,74898,67845,PRETRIAL,Ibanez,Marco,NULL,Male,Hispanic,04/15/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +22483,74885,67833,Probation,thompson,blake,NULL,Male,Caucasian,04/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,New,1,0 +22483,74885,67833,Probation,thompson,blake,NULL,Male,Caucasian,04/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +22483,74885,67833,Probation,thompson,blake,NULL,Male,Caucasian,04/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64770,74879,67827,PRETRIAL,Ortiz,Alejandro,NULL,Male,Hispanic,08/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/14/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +64770,74879,67827,PRETRIAL,Ortiz,Alejandro,NULL,Male,Hispanic,08/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/14/14 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +64770,74879,67827,PRETRIAL,Ortiz,Alejandro,NULL,Male,Hispanic,08/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +36184,74893,66362,PRETRIAL,Julien,Brandon,NULL,Male,African-American,07/31/93,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +36184,74893,66362,PRETRIAL,Julien,Brandon,NULL,Male,African-American,07/31/93,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,4,High,8,Risk of Recidivism,0.56,9,High,New,1,0 +36184,74893,66362,PRETRIAL,Julien,Brandon,NULL,Male,African-American,07/31/93,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +64774,74886,67834,PRETRIAL,Quintanapino,Alexander,NULL,Male,Hispanic,09/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +64774,74886,67834,PRETRIAL,Quintanapino,Alexander,NULL,Male,Hispanic,09/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +64774,74886,67834,PRETRIAL,Quintanapino,Alexander,NULL,Male,Hispanic,09/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64776,74888,67836,Probation,Borchetta,Dallas,NULL,Male,Caucasian,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +64776,74888,67836,Probation,Borchetta,Dallas,NULL,Male,Caucasian,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,10,High,New,1,0 +64776,74888,67836,Probation,Borchetta,Dallas,NULL,Male,Caucasian,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64793,74907,67854,Probation,Scacco,Louis,NULL,Male,Caucasian,06/20/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/14/14 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +64793,74907,67854,Probation,Scacco,Louis,NULL,Male,Caucasian,06/20/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/14/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +64793,74907,67854,Probation,Scacco,Louis,NULL,Male,Caucasian,06/20/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64794,74909,67856,Probation,JONES,KENNETH,WAYNE,Male,African-American,02/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +64794,74909,67856,Probation,JONES,KENNETH,WAYNE,Male,African-American,02/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +64794,74909,67856,Probation,JONES,KENNETH,WAYNE,Male,African-American,02/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64797,74914,67861,Probation,nash,allyson,NULL,Female,Caucasian,07/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +64797,74914,67861,Probation,nash,allyson,NULL,Female,Caucasian,07/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,7,Medium,New,1,0 +64797,74914,67861,Probation,nash,allyson,NULL,Female,Caucasian,07/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64800,74916,67862,Probation,Elisias,Kindson,NULL,Male,African-American,05/21/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +64800,74916,67862,Probation,Elisias,Kindson,NULL,Male,African-American,05/21/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +64800,74916,67862,Probation,Elisias,Kindson,NULL,Male,African-American,05/21/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +64790,74904,67851,Probation,aranda,dieter,NULL,Male,Hispanic,07/09/69,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,7/14/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +64790,74904,67851,Probation,aranda,dieter,NULL,Male,Hispanic,07/09/69,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,7/14/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +64790,74904,67851,Probation,aranda,dieter,NULL,Male,Hispanic,07/09/69,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64779,74891,67839,PRETRIAL,Allenlengel,Audrey,NULL,Female,Caucasian,09/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/14/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +64779,74891,67839,PRETRIAL,Allenlengel,Audrey,NULL,Female,Caucasian,09/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/14/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +64779,74891,67839,PRETRIAL,Allenlengel,Audrey,NULL,Female,Caucasian,09/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64785,74900,67847,Probation,RAMOS,CHRISTOPHER,RAMON,Male,Hispanic,01/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +64785,74900,67847,Probation,RAMOS,CHRISTOPHER,RAMON,Male,Hispanic,01/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +64785,74900,67847,Probation,RAMOS,CHRISTOPHER,RAMON,Male,Hispanic,01/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64765,74874,67822,PRETRIAL,Smith,Tomas,H,Male,Caucasian,04/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/14/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +64765,74874,67822,PRETRIAL,Smith,Tomas,H,Male,Caucasian,04/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +64765,74874,67822,PRETRIAL,Smith,Tomas,H,Male,Caucasian,04/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64781,74895,67842,PRETRIAL,Green,Demetra,NULL,Female,African-American,12/13/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +64781,74895,67842,PRETRIAL,Green,Demetra,NULL,Female,African-American,12/13/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +64781,74895,67842,PRETRIAL,Green,Demetra,NULL,Female,African-American,12/13/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +64775,74887,67835,Probation,moss,brandon,NULL,Male,African-American,01/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +64775,74887,67835,Probation,moss,brandon,NULL,Male,African-American,01/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +64775,74887,67835,Probation,moss,brandon,NULL,Male,African-American,01/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64769,74878,67826,PRETRIAL,GONZALEZDURAN,DANIEL,A,Male,Hispanic,10/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +64769,74878,67826,PRETRIAL,GONZALEZDURAN,DANIEL,A,Male,Hispanic,10/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +64769,74878,67826,PRETRIAL,GONZALEZDURAN,DANIEL,A,Male,Hispanic,10/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64782,74896,67843,Probation,LUSSIER,WILLIAM,EUGENE,Male,Caucasian,02/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,7,Risk of Violence,-2.77,2,Low,New,1,0 +64782,74896,67843,Probation,LUSSIER,WILLIAM,EUGENE,Male,Caucasian,02/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +64782,74896,67843,Probation,LUSSIER,WILLIAM,EUGENE,Male,Caucasian,02/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59376,74892,67840,PRETRIAL,Fennell,Kenneth,NULL,Male,African-American,08/15/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/14/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +59376,74892,67840,PRETRIAL,Fennell,Kenneth,NULL,Male,African-American,08/15/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +59376,74892,67840,PRETRIAL,Fennell,Kenneth,NULL,Male,African-American,08/15/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/14/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64784,74899,67846,Probation,williams,frederick,NULL,Male,Caucasian,10/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +64784,74899,67846,Probation,williams,frederick,NULL,Male,Caucasian,10/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +64784,74899,67846,Probation,williams,frederick,NULL,Male,Caucasian,10/26/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64801,74917,67863,Probation,Peterson,Arsenio,NULL,Male,African-American,12/10/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +64801,74917,67863,Probation,Peterson,Arsenio,NULL,Male,African-American,12/10/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +64801,74917,67863,Probation,Peterson,Arsenio,NULL,Male,African-American,12/10/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +4975,74873,4659,PRETRIAL,Peaz,Candido,NULL,Male,African-American,05/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.38,3,Low,Copy,1,0 +4975,74873,4659,PRETRIAL,Peaz,Candido,NULL,Male,African-American,05/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,Copy,1,0 +4975,74873,4659,PRETRIAL,Peaz,Candido,NULL,Male,African-American,05/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +64771,74880,67828,PRETRIAL,graham,joseph,NULL,Male,Other,12/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +64771,74880,67828,PRETRIAL,graham,joseph,NULL,Male,Other,12/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +64771,74880,67828,PRETRIAL,graham,joseph,NULL,Male,Other,12/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64780,74894,67841,PRETRIAL,loden,christopher,NULL,Male,Caucasian,06/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +64780,74894,67841,PRETRIAL,loden,christopher,NULL,Male,Caucasian,06/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +64780,74894,67841,PRETRIAL,loden,christopher,NULL,Male,Caucasian,06/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64786,74901,67848,Probation,naimoli,michael,NULL,Male,Caucasian,07/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +64786,74901,67848,Probation,naimoli,michael,NULL,Male,Caucasian,07/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +64786,74901,67848,Probation,naimoli,michael,NULL,Male,Caucasian,07/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +2223,74908,67855,PRETRIAL,BARNES,ANTONIO,NULL,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +2223,74908,67855,PRETRIAL,BARNES,ANTONIO,NULL,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +2223,74908,67855,PRETRIAL,BARNES,ANTONIO,NULL,Male,African-American,06/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +40082,74915,67076,PRETRIAL,Flodin,Christopher,NULL,Male,Caucasian,05/07/76,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +40082,74915,67076,PRETRIAL,Flodin,Christopher,NULL,Male,Caucasian,05/07/76,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.88,2,Low,New,1,0 +40082,74915,67076,PRETRIAL,Flodin,Christopher,NULL,Male,Caucasian,05/07/76,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,2,Low,New,1,0 +64787,74902,67849,Probation,Mejia,christopher,NULL,Male,Hispanic,10/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +64787,74902,67849,Probation,Mejia,christopher,NULL,Male,Hispanic,10/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +64787,74902,67849,Probation,Mejia,christopher,NULL,Male,Hispanic,10/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64777,74889,67837,Probation,CAREY,TAMARA,M,Female,African-American,05/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +64777,74889,67837,Probation,CAREY,TAMARA,M,Female,African-American,05/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +64777,74889,67837,Probation,CAREY,TAMARA,M,Female,African-American,05/28/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64795,74910,67857,Probation,Figuereo,Ivan,NULL,Male,Hispanic,06/27/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/14/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +64795,74910,67857,Probation,Figuereo,Ivan,NULL,Male,Hispanic,06/27/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/14/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +64795,74910,67857,Probation,Figuereo,Ivan,NULL,Male,Hispanic,06/27/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64767,74876,67824,PRETRIAL,DESIRE,MARVIN,NULL,Male,African-American,01/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +64767,74876,67824,PRETRIAL,DESIRE,MARVIN,NULL,Male,African-American,01/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,4,High,8,Risk of Recidivism,0.28,8,High,New,1,0 +64767,74876,67824,PRETRIAL,DESIRE,MARVIN,NULL,Male,African-American,01/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/14/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64783,74897,67844,Probation,campbell,linda,NULL,Female,Caucasian,01/16/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/14/14 0:00,1,Low,7,Risk of Violence,-4.32,1,Low,New,1,0 +64783,74897,67844,Probation,campbell,linda,NULL,Female,Caucasian,01/16/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/14/14 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +64783,74897,67844,Probation,campbell,linda,NULL,Female,Caucasian,01/16/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +14755,74912,67859,PRETRIAL,LEE,CARLOS,NULL,Male,African-American,10/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +14755,74912,67859,PRETRIAL,LEE,CARLOS,NULL,Male,African-American,10/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +14755,74912,67859,PRETRIAL,LEE,CARLOS,NULL,Male,African-American,10/07/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +55115,74884,67832,PRETRIAL,DAVIS,UTWAIN,NULL,Male,African-American,08/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +55115,74884,67832,PRETRIAL,DAVIS,UTWAIN,NULL,Male,African-American,08/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +55115,74884,67832,PRETRIAL,DAVIS,UTWAIN,NULL,Male,African-American,08/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/14/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64789,74905,67852,Probation,Achedou,Saint,NULL,Male,African-American,06/20/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/14/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +64789,74905,67852,Probation,Achedou,Saint,NULL,Male,African-American,06/20/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/14/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +64789,74905,67852,Probation,Achedou,Saint,NULL,Male,African-American,06/20/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64802,74918,67864,PRETRIAL,Mohammed,Ashraff,NULL,Male,Other,08/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +64802,74918,67864,PRETRIAL,Mohammed,Ashraff,NULL,Male,Other,08/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +64802,74918,67864,PRETRIAL,Mohammed,Ashraff,NULL,Male,Other,08/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64804,74920,67866,PRETRIAL,Williams,Devin,NULL,Male,African-American,09/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +64804,74920,67866,PRETRIAL,Williams,Devin,NULL,Male,African-American,09/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +64804,74920,67866,PRETRIAL,Williams,Devin,NULL,Male,African-American,09/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64830,74954,67893,Probation,Berto,Juan,Marcelo,Male,Hispanic,02/23/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/15/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +64830,74954,67893,Probation,Berto,Juan,Marcelo,Male,Hispanic,02/23/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +64830,74954,67893,Probation,Berto,Juan,Marcelo,Male,Hispanic,02/23/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64815,74939,67880,Probation,RODRIGUEZ,REYNALDO,JORGE,Male,Hispanic,08/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +64815,74939,67880,Probation,RODRIGUEZ,REYNALDO,JORGE,Male,Hispanic,08/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +64815,74939,67880,Probation,RODRIGUEZ,REYNALDO,JORGE,Male,Hispanic,08/02/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64735,74941,67790,PRETRIAL,Scott,Shalika,NULL,Female,African-American,06/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,4,High,7,Risk of Violence,-0.63,9,High,Copy,1,0 +64735,74941,67790,PRETRIAL,Scott,Shalika,NULL,Female,African-American,06/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,4,High,8,Risk of Recidivism,0.72,10,High,Copy,1,0 +64735,74941,67790,PRETRIAL,Scott,Shalika,NULL,Female,African-American,06/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,4,High,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +64823,74947,67886,Probation,CAMPBELL,kAREN,NULL,Female,African-American,05/29/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/15/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +64823,74947,67886,Probation,CAMPBELL,kAREN,NULL,Female,African-American,05/29/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/15/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +64823,74947,67886,Probation,CAMPBELL,kAREN,NULL,Female,African-American,05/29/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64808,74926,67871,PRETRIAL,Gray,Joseph,NULL,Male,African-American,09/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +64808,74926,67871,PRETRIAL,Gray,Joseph,NULL,Male,African-American,09/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +64808,74926,67871,PRETRIAL,Gray,Joseph,NULL,Male,African-American,09/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64813,74933,67878,PRETRIAL,gibbon,richard,NULL,Male,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +64813,74933,67878,PRETRIAL,gibbon,richard,NULL,Male,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +64813,74933,67878,PRETRIAL,gibbon,richard,NULL,Male,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +45421,74931,67876,PRETRIAL,NODLAND,MICHAEL,NULL,Male,African-American,02/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +45421,74931,67876,PRETRIAL,NODLAND,MICHAEL,NULL,Male,African-American,02/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +45421,74931,67876,PRETRIAL,NODLAND,MICHAEL,NULL,Male,African-American,02/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64824,74949,67888,Probation,McIntosh,William,Alexander,Male,Hispanic,10/22/50,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/15/14 0:00,1,Low,7,Risk of Violence,-4.37,1,Low,New,1,0 +64824,74949,67888,Probation,McIntosh,William,Alexander,Male,Hispanic,10/22/50,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/15/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +64824,74949,67888,Probation,McIntosh,William,Alexander,Male,Hispanic,10/22/50,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +35944,74923,35176,PRETRIAL,Laguerre,Mchason,NULL,Male,African-American,11/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,Copy,1,0 +35944,74923,35176,PRETRIAL,Laguerre,Mchason,NULL,Male,African-American,11/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,Copy,1,0 +35944,74923,35176,PRETRIAL,Laguerre,Mchason,NULL,Male,African-American,11/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +64832,74957,67896,Probation,Lynch,John,NULL,Male,Caucasian,03/07/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +64832,74957,67896,Probation,Lynch,John,NULL,Male,Caucasian,03/07/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +64832,74957,67896,Probation,Lynch,John,NULL,Male,Caucasian,03/07/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +33076,74936,32153,PRETRIAL,Fanuelsem,Thomas,Lee,Male,African-American,04/17/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,Copy,1,0 +33076,74936,32153,PRETRIAL,Fanuelsem,Thomas,Lee,Male,African-American,04/17/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,Copy,1,0 +33076,74936,32153,PRETRIAL,Fanuelsem,Thomas,Lee,Male,African-American,04/17/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +64805,74922,67868,PRETRIAL,FREEMAN-FLORENCE,SHAREESE,MONIQUE,Female,African-American,05/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/15/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +64805,74922,67868,PRETRIAL,FREEMAN-FLORENCE,SHAREESE,MONIQUE,Female,African-American,05/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.62,2,Low,New,1,0 +64805,74922,67868,PRETRIAL,FREEMAN-FLORENCE,SHAREESE,MONIQUE,Female,African-American,05/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64811,74929,67874,PRETRIAL,Rockfeld,Garrett,NULL,Male,Caucasian,03/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +64811,74929,67874,PRETRIAL,Rockfeld,Garrett,NULL,Male,Caucasian,03/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +64811,74929,67874,PRETRIAL,Rockfeld,Garrett,NULL,Male,Caucasian,03/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64818,74943,67883,Probation,nieves,michael,NULL,Male,Caucasian,07/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +64818,74943,67883,Probation,nieves,michael,NULL,Male,Caucasian,07/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +64818,74943,67883,Probation,nieves,michael,NULL,Male,Caucasian,07/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64828,74952,67891,Probation,lafavor,brittney,NULL,Female,African-American,03/19/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +64828,74952,67891,Probation,lafavor,brittney,NULL,Female,African-American,03/19/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-0.9,4,Low,New,1,0 +64828,74952,67891,Probation,lafavor,brittney,NULL,Female,African-American,03/19/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +32036,74938,31040,PRETRIAL,TORRES,JORDAN,NULL,Male,Caucasian,05/15/93,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,4,High,7,Risk of Violence,-0.57,10,High,Copy,1,0 +32036,74938,31040,PRETRIAL,TORRES,JORDAN,NULL,Male,Caucasian,05/15/93,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,4,High,8,Risk of Recidivism,0.8,10,High,Copy,1,0 +32036,74938,31040,PRETRIAL,TORRES,JORDAN,NULL,Male,Caucasian,05/15/93,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +56580,74955,67894,PRETRIAL,chudicek,kristi,NULL,Female,Caucasian,06/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +56580,74955,67894,PRETRIAL,chudicek,kristi,NULL,Female,Caucasian,06/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.43,2,Low,New,1,0 +56580,74955,67894,PRETRIAL,chudicek,kristi,NULL,Female,Caucasian,06/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64814,74934,67879,Probation,Agudelo,Mario,NULL,Male,Hispanic,02/01/68,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/15/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +64814,74934,67879,Probation,Agudelo,Mario,NULL,Male,Hispanic,02/01/68,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +64814,74934,67879,Probation,Agudelo,Mario,NULL,Male,Hispanic,02/01/68,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64822,74946,67885,PRETRIAL,Kruglick,Daniel,George,Male,Caucasian,06/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +64822,74946,67885,PRETRIAL,Kruglick,Daniel,George,Male,Caucasian,06/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +64822,74946,67885,PRETRIAL,Kruglick,Daniel,George,Male,Caucasian,06/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64834,74960,67899,Probation,NORD,RICARDO,NULL,Male,African-American,05/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +64834,74960,67899,Probation,NORD,RICARDO,NULL,Male,African-American,05/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +64834,74960,67899,Probation,NORD,RICARDO,NULL,Male,African-American,05/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64817,74942,67882,PRETRIAL,Meltzer,Michael,NULL,Male,Caucasian,06/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +64817,74942,67882,PRETRIAL,Meltzer,Michael,NULL,Male,Caucasian,06/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +64817,74942,67882,PRETRIAL,Meltzer,Michael,NULL,Male,Caucasian,06/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64831,74956,67895,Probation,Soto-Martinez,Ruben,NULL,Male,Hispanic,08/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Separated,7/15/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +64831,74956,67895,Probation,Soto-Martinez,Ruben,NULL,Male,Hispanic,08/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Separated,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +64831,74956,67895,Probation,Soto-Martinez,Ruben,NULL,Male,Hispanic,08/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Separated,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64807,74925,67870,PRETRIAL,Burns,Shinney,Lee,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,4,High,7,Risk of Violence,-0.9,9,High,New,1,0 +64807,74925,67870,PRETRIAL,Burns,Shinney,Lee,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,4,High,8,Risk of Recidivism,0.41,9,High,New,1,0 +64807,74925,67870,PRETRIAL,Burns,Shinney,Lee,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +23439,74921,67867,PRETRIAL,Paul,Ervin,NULL,Male,African-American,09/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +23439,74921,67867,PRETRIAL,Paul,Ervin,NULL,Male,African-American,09/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +23439,74921,67867,PRETRIAL,Paul,Ervin,NULL,Male,African-American,09/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +33076,74935,32153,PRETRIAL,Fanuelsem,Thomas,Lee,Male,African-American,04/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,Copy,1,0 +33076,74935,32153,PRETRIAL,Fanuelsem,Thomas,Lee,Male,African-American,04/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,4,High,8,Risk of Recidivism,0.62,10,High,Copy,1,0 +33076,74935,32153,PRETRIAL,Fanuelsem,Thomas,Lee,Male,African-American,04/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +64812,74930,67875,PRETRIAL,Emile,Marc,NULL,Male,African-American,12/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +64812,74930,67875,PRETRIAL,Emile,Marc,NULL,Male,African-American,12/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +64812,74930,67875,PRETRIAL,Emile,Marc,NULL,Male,African-American,12/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64735,74944,67790,PRETRIAL,Scott,Shalika,NULL,Female,African-American,06/19/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,4,High,7,Risk of Violence,-0.7,9,High,Copy,1,0 +64735,74944,67790,PRETRIAL,Scott,Shalika,NULL,Female,African-American,06/19/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,4,High,8,Risk of Recidivism,0.72,10,High,Copy,1,0 +64735,74944,67790,PRETRIAL,Scott,Shalika,NULL,Female,African-American,06/19/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,4,High,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +64827,74951,67890,Probation,johnson,tyrone,NULL,Male,African-American,03/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/15/14 0:00,2,Medium,7,Risk of Violence,-2.47,3,Low,New,1,0 +64827,74951,67890,Probation,johnson,tyrone,NULL,Male,African-American,03/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/15/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +64827,74951,67890,Probation,johnson,tyrone,NULL,Male,African-American,03/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/15/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64833,74958,67897,Probation,schoedinger,Ileana,NULL,Female,Caucasian,05/26/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/15/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +64833,74958,67897,Probation,schoedinger,Ileana,NULL,Female,Caucasian,05/26/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +64833,74958,67897,Probation,schoedinger,Ileana,NULL,Female,Caucasian,05/26/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64803,74919,67865,PRETRIAL,BASTIAN,MILOT,NULL,Male,African-American,09/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +64803,74919,67865,PRETRIAL,BASTIAN,MILOT,NULL,Male,African-American,09/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +64803,74919,67865,PRETRIAL,BASTIAN,MILOT,NULL,Male,African-American,09/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64829,74953,67892,PRETRIAL,Florentine,Robert,Joseph,Male,Caucasian,12/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +64829,74953,67892,PRETRIAL,Florentine,Robert,Joseph,Male,Caucasian,12/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +64829,74953,67892,PRETRIAL,Florentine,Robert,Joseph,Male,Caucasian,12/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +5711,74932,67877,Probation,Loud,Willie,James,Male,African-American,11/28/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +5711,74932,67877,Probation,Loud,Willie,James,Male,African-American,11/28/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +5711,74932,67877,Probation,Loud,Willie,James,Male,African-American,11/28/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64821,74945,67884,PRETRIAL,Arellano,Alejandro,NULL,Male,Hispanic,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +64821,74945,67884,PRETRIAL,Arellano,Alejandro,NULL,Male,Hispanic,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +64821,74945,67884,PRETRIAL,Arellano,Alejandro,NULL,Male,Hispanic,03/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64806,74924,67869,PRETRIAL,Lee,Allan,James,Male,African-American,01/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +64806,74924,67869,PRETRIAL,Lee,Allan,James,Male,African-American,01/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +64806,74924,67869,PRETRIAL,Lee,Allan,James,Male,African-American,01/25/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64825,74948,67887,PRETRIAL,PEREZHERNANDEZ,ANA,NULL,Male,Hispanic,10/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/15/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +64825,74948,67887,PRETRIAL,PEREZHERNANDEZ,ANA,NULL,Male,Hispanic,10/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/15/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +64825,74948,67887,PRETRIAL,PEREZHERNANDEZ,ANA,NULL,Male,Hispanic,10/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64816,74940,67881,PRETRIAL,Muha,John,NULL,Male,Caucasian,03/18/91,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,7/15/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +64816,74940,67881,PRETRIAL,Muha,John,NULL,Male,Caucasian,03/18/91,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,7/15/14 0:00,1,Low,8,Risk of Recidivism,-0.41,4,Low,New,1,0 +64816,74940,67881,PRETRIAL,Muha,John,NULL,Male,Caucasian,03/18/91,17,All Scales,Intake,English,Post Sentence,Jail Inmate,Single,7/15/14 0:00,1,Low,18,Risk of Failure to Appear,16,1,Low,New,1,0 +64844,74976,67912,Probation,Bedregal,Fancisco,NULL,Male,Hispanic,11/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +64844,74976,67912,Probation,Bedregal,Fancisco,NULL,Male,Hispanic,11/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +64844,74976,67912,Probation,Bedregal,Fancisco,NULL,Male,Hispanic,11/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +43485,74961,67900,PRETRIAL,Daniels,Deon,NULL,Male,African-American,09/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.18,8,High,New,1,0 +43485,74961,67900,PRETRIAL,Daniels,Deon,NULL,Male,African-American,09/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +43485,74961,67900,PRETRIAL,Daniels,Deon,NULL,Male,African-American,09/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58876,74982,67918,PRETRIAL,Dowlings,Eldred,D,Male,African-American,12/11/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,2,Medium,7,Risk of Violence,-1.97,5,Medium,New,1,0 +58876,74982,67918,PRETRIAL,Dowlings,Eldred,D,Male,African-American,12/11/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +58876,74982,67918,PRETRIAL,Dowlings,Eldred,D,Male,African-American,12/11/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +2447,74974,67909,PRETRIAL,RICH,STANLEY,NULL,Male,African-American,11/16/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,Copy,1,0 +2447,74974,67909,PRETRIAL,RICH,STANLEY,NULL,Male,African-American,11/16/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/14 0:00,4,High,8,Risk of Recidivism,0.64,10,High,Copy,1,0 +2447,74974,67909,PRETRIAL,RICH,STANLEY,NULL,Male,African-American,11/16/88,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +64836,74965,67903,PRETRIAL,Maldonado,Jesus,Aquilio,Male,Hispanic,12/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/16/14 0:00,2,Medium,7,Risk of Violence,-1.32,7,Medium,New,1,0 +64836,74965,67903,PRETRIAL,Maldonado,Jesus,Aquilio,Male,Hispanic,12/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +64836,74965,67903,PRETRIAL,Maldonado,Jesus,Aquilio,Male,Hispanic,12/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/16/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64847,74979,67915,Probation,Bryant,Theresa,NULL,Female,Caucasian,02/17/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/16/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +64847,74979,67915,Probation,Bryant,Theresa,NULL,Female,Caucasian,02/17/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/16/14 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +64847,74979,67915,Probation,Bryant,Theresa,NULL,Female,Caucasian,02/17/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/16/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +2447,74972,67909,PRETRIAL,RICH,STANLEY,NULL,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +2447,74972,67909,PRETRIAL,RICH,STANLEY,NULL,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/14 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +2447,74972,67909,PRETRIAL,RICH,STANLEY,NULL,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64838,74967,67905,Probation,Brooks,Lance,NULL,Male,African-American,02/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +64838,74967,67905,Probation,Brooks,Lance,NULL,Male,African-American,02/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +64838,74967,67905,Probation,Brooks,Lance,NULL,Male,African-American,02/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64849,74981,67917,Probation,hoogstraten,stephane,j,Male,Hispanic,12/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +64849,74981,67917,Probation,hoogstraten,stephane,j,Male,Hispanic,12/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +64849,74981,67917,Probation,hoogstraten,stephane,j,Male,Hispanic,12/10/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +64835,74963,67901,PRETRIAL,Stubbs,Maurice,Jerome,Male,African-American,04/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/16/14 0:00,4,High,7,Risk of Violence,-0.99,9,High,New,1,0 +64835,74963,67901,PRETRIAL,Stubbs,Maurice,Jerome,Male,African-American,04/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/16/14 0:00,4,High,8,Risk of Recidivism,0.44,9,High,New,1,0 +64835,74963,67901,PRETRIAL,Stubbs,Maurice,Jerome,Male,African-American,04/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/16/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64845,74977,67913,PRETRIAL,Miglio,Paul,NULL,Male,Caucasian,07/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +64845,74977,67913,PRETRIAL,Miglio,Paul,NULL,Male,Caucasian,07/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +64845,74977,67913,PRETRIAL,Miglio,Paul,NULL,Male,Caucasian,07/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +26771,74964,67902,PRETRIAL,WILSON,RASHOD,ANTWAIN,Male,African-American,11/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/16/14 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +26771,74964,67902,PRETRIAL,WILSON,RASHOD,ANTWAIN,Male,African-American,11/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/16/14 0:00,4,High,8,Risk of Recidivism,0.42,9,High,New,1,0 +26771,74964,67902,PRETRIAL,WILSON,RASHOD,ANTWAIN,Male,African-American,11/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/16/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64839,74968,67906,Probation,DORCILUS,PATRICK,NULL,Male,African-American,05/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2,4,Low,New,1,0 +64839,74968,67906,Probation,DORCILUS,PATRICK,NULL,Male,African-American,05/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +64839,74968,67906,Probation,DORCILUS,PATRICK,NULL,Male,African-American,05/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64842,74971,67908,Probation,moreno,jeremy,NULL,Male,Caucasian,04/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +64842,74971,67908,Probation,moreno,jeremy,NULL,Male,Caucasian,04/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +64842,74971,67908,Probation,moreno,jeremy,NULL,Male,Caucasian,04/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +38599,74973,67910,PRETRIAL,McClam,Anthony,NULL,Male,African-American,11/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +38599,74973,67910,PRETRIAL,McClam,Anthony,NULL,Male,African-American,11/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +38599,74973,67910,PRETRIAL,McClam,Anthony,NULL,Male,African-American,11/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64848,74980,67916,Probation,Charles,Georges,NULL,Male,African-American,03/20/66,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,7/16/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +64848,74980,67916,Probation,Charles,Georges,NULL,Male,African-American,03/20/66,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,7/16/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +64848,74980,67916,Probation,Charles,Georges,NULL,Male,African-American,03/20/66,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Married,7/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64846,74978,67914,Probation,silva,jesel,NULL,Female,Caucasian,03/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +64846,74978,67914,Probation,silva,jesel,NULL,Female,Caucasian,03/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +64846,74978,67914,Probation,silva,jesel,NULL,Female,Caucasian,03/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/16/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64678,74962,67732,PRETRIAL,THOMAS,DEMONT,D,Male,African-American,03/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.76,2,Low,Copy,1,0 +64678,74962,67732,PRETRIAL,THOMAS,DEMONT,D,Male,African-American,03/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,Copy,1,0 +64678,74962,67732,PRETRIAL,THOMAS,DEMONT,D,Male,African-American,03/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +64843,74975,67911,Probation,Garciamoreno,Maykel,NULL,Male,Hispanic,05/13/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/16/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +64843,74975,67911,Probation,Garciamoreno,Maykel,NULL,Male,Hispanic,05/13/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/16/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +64843,74975,67911,Probation,Garciamoreno,Maykel,NULL,Male,Hispanic,05/13/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64880,75020,67952,Probation,Manchame,Mynor,Joel,Male,Hispanic,02/03/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +64880,75020,67952,Probation,Manchame,Mynor,Joel,Male,Hispanic,02/03/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +64880,75020,67952,Probation,Manchame,Mynor,Joel,Male,Hispanic,02/03/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64874,75012,67946,Probation,Fonseca,Manuel,Rodolfin,Male,Hispanic,02/06/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/17/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +64874,75012,67946,Probation,Fonseca,Manuel,Rodolfin,Male,Hispanic,02/06/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/17/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +64874,75012,67946,Probation,Fonseca,Manuel,Rodolfin,Male,Hispanic,02/06/64,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64861,74996,67932,PRETRIAL,Kendrick,Dominick,NULL,Male,African-American,08/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,4,High,7,Risk of Violence,-1.17,8,High,New,1,0 +64861,74996,67932,PRETRIAL,Kendrick,Dominick,NULL,Male,African-American,08/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,4,High,8,Risk of Recidivism,0.11,8,High,New,1,0 +64861,74996,67932,PRETRIAL,Kendrick,Dominick,NULL,Male,African-American,08/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58992,74999,61254,PRETRIAL,Wright,Travis,NULL,Male,African-American,01/05/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +58992,74999,61254,PRETRIAL,Wright,Travis,NULL,Male,African-American,01/05/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +58992,74999,61254,PRETRIAL,Wright,Travis,NULL,Male,African-American,01/05/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +48617,54200,49321,PRETRIAL,TILMAN,GARY,NULL,Male,African-American,01/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/14 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +48617,54200,49321,PRETRIAL,TILMAN,GARY,NULL,Male,African-American,01/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +48617,54200,49321,PRETRIAL,TILMAN,GARY,NULL,Male,African-American,01/08/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +64867,75004,67938,Probation,carstensen,nicole,NULL,Female,Caucasian,05/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +64867,75004,67938,Probation,carstensen,nicole,NULL,Female,Caucasian,05/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +64867,75004,67938,Probation,carstensen,nicole,NULL,Female,Caucasian,05/07/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64857,74991,67927,PRETRIAL,Pyram,Henri,Germain,Male,Other,12/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +64857,74991,67927,PRETRIAL,Pyram,Henri,Germain,Male,Other,12/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +64857,74991,67927,PRETRIAL,Pyram,Henri,Germain,Male,Other,12/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +39981,75025,67957,PRETRIAL,owens,makenya,NULL,Female,African-American,11/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +39981,75025,67957,PRETRIAL,owens,makenya,NULL,Female,African-American,11/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.93,10,High,New,1,0 +39981,75025,67957,PRETRIAL,owens,makenya,NULL,Female,African-American,11/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64859,74994,67930,PRETRIAL,FOSTER,RASHAD,BERNARD,Male,African-American,09/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +64859,74994,67930,PRETRIAL,FOSTER,RASHAD,BERNARD,Male,African-American,09/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +64859,74994,67930,PRETRIAL,FOSTER,RASHAD,BERNARD,Male,African-American,09/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51615,75029,67960,PRETRIAL,Caldwell,Alan-Michael,NULL,Male,African-American,05/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +51615,75029,67960,PRETRIAL,Caldwell,Alan-Michael,NULL,Male,African-American,05/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +51615,75029,67960,PRETRIAL,Caldwell,Alan-Michael,NULL,Male,African-American,05/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55340,75001,67935,Probation,CLEMENTS,RHONDA,NULL,Female,African-American,05/23/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +55340,75001,67935,Probation,CLEMENTS,RHONDA,NULL,Female,African-American,05/23/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +55340,75001,67935,Probation,CLEMENTS,RHONDA,NULL,Female,African-American,05/23/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64870,75008,67942,Broward County,Strickland,Roy,NULL,Male,Caucasian,12/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +64870,75008,67942,Broward County,Strickland,Roy,NULL,Male,Caucasian,12/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +64870,75008,67942,Broward County,Strickland,Roy,NULL,Male,Caucasian,12/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +64882,75022,67954,Probation,woods,justin,NULL,Male,Caucasian,08/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +64882,75022,67954,Probation,woods,justin,NULL,Male,Caucasian,08/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +64882,75022,67954,Probation,woods,justin,NULL,Male,Caucasian,08/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64852,74985,67921,PRETRIAL,ROYAL,TABATHA,NULL,Female,African-American,07/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +64852,74985,67921,PRETRIAL,ROYAL,TABATHA,NULL,Female,African-American,07/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +64852,74985,67921,PRETRIAL,ROYAL,TABATHA,NULL,Female,African-American,07/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +15096,74989,67925,PRETRIAL,Fernandez,Marleny,NULL,Female,Hispanic,05/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/17/14 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +15096,74989,67925,PRETRIAL,Fernandez,Marleny,NULL,Female,Hispanic,05/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.41,6,Medium,New,1,0 +15096,74989,67925,PRETRIAL,Fernandez,Marleny,NULL,Female,Hispanic,05/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/17/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +64869,75006,67940,PRETRIAL,Johnson,Demetrian,NULL,Female,African-American,07/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/17/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +64869,75006,67940,PRETRIAL,Johnson,Demetrian,NULL,Female,African-American,07/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/17/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +64869,75006,67940,PRETRIAL,Johnson,Demetrian,NULL,Female,African-American,07/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64884,75024,67956,Probation,suchman,BRANDON,NULL,Male,Caucasian,01/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,2,Medium,7,Risk of Violence,-1.87,5,Medium,New,1,0 +64884,75024,67956,Probation,suchman,BRANDON,NULL,Male,Caucasian,01/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +64884,75024,67956,Probation,suchman,BRANDON,NULL,Male,Caucasian,01/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64885,75027,67958,Probation,VANBUREN,LABARON,NULL,Male,African-American,12/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +64885,75027,67958,Probation,VANBUREN,LABARON,NULL,Male,African-American,12/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +64885,75027,67958,Probation,VANBUREN,LABARON,NULL,Male,African-American,12/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +34253,75028,67959,PRETRIAL,CLAYTON,CARL,DENVER,Male,African-American,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +34253,75028,67959,PRETRIAL,CLAYTON,CARL,DENVER,Male,African-American,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +34253,75028,67959,PRETRIAL,CLAYTON,CARL,DENVER,Male,African-American,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56897,65017,58989,PRETRIAL,Polynice,Gregory,NULL,Male,African-American,01/06/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/14 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +56897,65017,58989,PRETRIAL,Polynice,Gregory,NULL,Male,African-American,01/06/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +56897,65017,58989,PRETRIAL,Polynice,Gregory,NULL,Male,African-American,01/06/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/17/14 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +64866,75002,67936,Probation,Mercado,Irving,NULL,Male,Hispanic,07/10/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/17/14 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +64866,75002,67936,Probation,Mercado,Irving,NULL,Male,Hispanic,07/10/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/17/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +64866,75002,67936,Probation,Mercado,Irving,NULL,Male,Hispanic,07/10/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64879,75019,67951,Probation,gilbert,orellans,NULL,Male,Hispanic,08/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/17/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +64879,75019,67951,Probation,gilbert,orellans,NULL,Male,Hispanic,08/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/17/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +64879,75019,67951,Probation,gilbert,orellans,NULL,Male,Hispanic,08/02/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64858,74993,67929,PRETRIAL,Lee,Joann,NULL,Male,African-American,01/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/17/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +64858,74993,67929,PRETRIAL,Lee,Joann,NULL,Male,African-American,01/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/17/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +64858,74993,67929,PRETRIAL,Lee,Joann,NULL,Male,African-American,01/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64862,74998,67933,Probation,Blair,Justin,NULL,Male,Caucasian,01/03/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +64862,74998,67933,Probation,Blair,Justin,NULL,Male,Caucasian,01/03/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +64862,74998,67933,Probation,Blair,Justin,NULL,Male,Caucasian,01/03/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64883,75023,67955,Probation,BHAWANI,SOMNAUTH,NULL,Male,Other,02/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +64883,75023,67955,Probation,BHAWANI,SOMNAUTH,NULL,Male,Other,02/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +64883,75023,67955,Probation,BHAWANI,SOMNAUTH,NULL,Male,Other,02/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64853,74986,67922,PRETRIAL,MCCLENDON,ELEZABETH,NULL,Female,African-American,08/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +64853,74986,67922,PRETRIAL,MCCLENDON,ELEZABETH,NULL,Female,African-American,08/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +64853,74986,67922,PRETRIAL,MCCLENDON,ELEZABETH,NULL,Female,African-American,08/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64855,74988,67924,PRETRIAL,Matherly,Derek,Steven,Male,Caucasian,09/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +64855,74988,67924,PRETRIAL,Matherly,Derek,Steven,Male,Caucasian,09/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +64855,74988,67924,PRETRIAL,Matherly,Derek,Steven,Male,Caucasian,09/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64871,75007,67941,Probation,doura,craig,NULL,Male,Caucasian,12/17/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/17/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +64871,75007,67941,Probation,doura,craig,NULL,Male,Caucasian,12/17/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/17/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +64871,75007,67941,Probation,doura,craig,NULL,Male,Caucasian,12/17/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64872,75009,67943,Probation,Sarmiento,Sandro,NULL,Male,Hispanic,09/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +64872,75009,67943,Probation,Sarmiento,Sandro,NULL,Male,Hispanic,09/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +64872,75009,67943,Probation,Sarmiento,Sandro,NULL,Male,Hispanic,09/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64875,75014,67947,Probation,WILFORK,TANGELA,NULL,Female,African-American,02/14/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +64875,75014,67947,Probation,WILFORK,TANGELA,NULL,Female,African-American,02/14/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +64875,75014,67947,Probation,WILFORK,TANGELA,NULL,Female,African-American,02/14/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64877,75016,67949,Probation,MILSTEAD,KRISTINE,NULL,Female,Caucasian,02/16/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/17/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +64877,75016,67949,Probation,MILSTEAD,KRISTINE,NULL,Female,Caucasian,02/16/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/17/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +64877,75016,67949,Probation,MILSTEAD,KRISTINE,NULL,Female,Caucasian,02/16/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +63782,74992,67928,Probation,JOSEPH,COBY,H,Male,African-American,08/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/17/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +63782,74992,67928,Probation,JOSEPH,COBY,H,Male,African-American,08/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/17/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +63782,74992,67928,Probation,JOSEPH,COBY,H,Male,African-American,08/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +64860,74995,67931,PRETRIAL,Belgrave,Antwon,NULL,Male,African-American,02/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +64860,74995,67931,PRETRIAL,Belgrave,Antwon,NULL,Male,African-American,02/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +64860,74995,67931,PRETRIAL,Belgrave,Antwon,NULL,Male,African-American,02/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64865,75000,67934,Probation,Cartwright,Dylan,NULL,Male,African-American,06/15/95,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,7/17/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +64865,75000,67934,Probation,Cartwright,Dylan,NULL,Male,African-American,06/15/95,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,7/17/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +64865,75000,67934,Probation,Cartwright,Dylan,NULL,Male,African-American,06/15/95,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,7/17/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64854,74987,67923,PRETRIAL,Adams,Melissa,NULL,Female,Caucasian,04/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +64854,74987,67923,PRETRIAL,Adams,Melissa,NULL,Female,Caucasian,04/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +64854,74987,67923,PRETRIAL,Adams,Melissa,NULL,Female,Caucasian,04/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64881,75021,67953,Probation,Morrison,Jefferey,NULL,Male,Caucasian,07/13/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/17/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +64881,75021,67953,Probation,Morrison,Jefferey,NULL,Male,Caucasian,07/13/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/17/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +64881,75021,67953,Probation,Morrison,Jefferey,NULL,Male,Caucasian,07/13/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64851,74984,67920,PRETRIAL,Jackson,Larry,NULL,Male,African-American,01/01/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/17/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +64851,74984,67920,PRETRIAL,Jackson,Larry,NULL,Male,African-American,01/01/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/17/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +64851,74984,67920,PRETRIAL,Jackson,Larry,NULL,Male,African-American,01/01/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51381,75003,67937,PRETRIAL,Osceloa,Nelson,NULL,Male,Native American,10/02/90,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +51381,75003,67937,PRETRIAL,Osceloa,Nelson,NULL,Male,Native American,10/02/90,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +51381,75003,67937,PRETRIAL,Osceloa,Nelson,NULL,Male,Native American,10/02/90,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64868,75005,67939,PRETRIAL,Haughton,Shikem,NULL,Male,African-American,06/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/17/14 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +64868,75005,67939,PRETRIAL,Haughton,Shikem,NULL,Male,African-American,06/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +64868,75005,67939,PRETRIAL,Haughton,Shikem,NULL,Male,African-American,06/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/17/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +63946,74997,66874,Probation,ALLENDE,JULIO,A,Male,Hispanic,11/02/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,4,High,7,Risk of Violence,-0.59,10,High,Copy,1,0 +63946,74997,66874,Probation,ALLENDE,JULIO,A,Male,Hispanic,11/02/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,4,High,8,Risk of Recidivism,0.79,10,High,Copy,1,0 +63946,74997,66874,Probation,ALLENDE,JULIO,A,Male,Hispanic,11/02/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/17/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +61725,75011,67945,Probation,Williams,Kadyja,NULL,Female,African-American,11/18/93,17,All Scales,Intake,English,Other,Probation,Single,7/17/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +61725,75011,67945,Probation,Williams,Kadyja,NULL,Female,African-American,11/18/93,17,All Scales,Intake,English,Other,Probation,Single,7/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +61725,75011,67945,Probation,Williams,Kadyja,NULL,Female,African-American,11/18/93,17,All Scales,Intake,English,Other,Probation,Single,7/17/14 0:00,2,Medium,18,Risk of Failure to Appear,22,4,Low,New,1,0 +64856,74990,67926,PRETRIAL,Grace,Samuel,NULL,Male,African-American,02/02/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +64856,74990,67926,PRETRIAL,Grace,Samuel,NULL,Male,African-American,02/02/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +64856,74990,67926,PRETRIAL,Grace,Samuel,NULL,Male,African-American,02/02/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/17/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64897,75047,67975,Probation,Berthold,Rolf,NULL,Male,African-American,10/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +64897,75047,67975,Probation,Berthold,Rolf,NULL,Male,African-American,10/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +64897,75047,67975,Probation,Berthold,Rolf,NULL,Male,African-American,10/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64891,75039,67967,Probation,Northrup,Daniell,Ann,Female,Caucasian,11/11/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +64891,75039,67967,Probation,Northrup,Daniell,Ann,Female,Caucasian,11/11/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,8,High,New,1,0 +64891,75039,67967,Probation,Northrup,Daniell,Ann,Female,Caucasian,11/11/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64904,75055,67982,Probation,Higgins,jerry,NULL,Male,Caucasian,10/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +64904,75055,67982,Probation,Higgins,jerry,NULL,Male,Caucasian,10/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +64904,75055,67982,Probation,Higgins,jerry,NULL,Male,Caucasian,10/12/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +21629,75034,67964,PRETRIAL,HATCHER,STEPHONNE,NULL,Male,African-American,03/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +21629,75034,67964,PRETRIAL,HATCHER,STEPHONNE,NULL,Male,African-American,03/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +21629,75034,67964,PRETRIAL,HATCHER,STEPHONNE,NULL,Male,African-American,03/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59111,75060,67987,PRETRIAL,Quarrie,Leighton,NULL,Male,African-American,04/06/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +59111,75060,67987,PRETRIAL,Quarrie,Leighton,NULL,Male,African-American,04/06/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +59111,75060,67987,PRETRIAL,Quarrie,Leighton,NULL,Male,African-American,04/06/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64892,75042,67970,Probation,Hewitt,Ronnell,NULL,Male,African-American,10/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +64892,75042,67970,Probation,Hewitt,Ronnell,NULL,Male,African-American,10/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +64892,75042,67970,Probation,Hewitt,Ronnell,NULL,Male,African-American,10/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47869,75035,48489,Probation,levy,aneika,NULL,Female,African-American,06/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,Copy,1,0 +47869,75035,48489,Probation,levy,aneika,NULL,Female,African-American,06/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,Copy,1,0 +47869,75035,48489,Probation,levy,aneika,NULL,Female,African-American,06/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +64889,75037,67966,PRETRIAL,Gervin,Curtis,NULL,Male,African-American,02/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +64889,75037,67966,PRETRIAL,Gervin,Curtis,NULL,Male,African-American,02/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +64889,75037,67966,PRETRIAL,Gervin,Curtis,NULL,Male,African-American,02/25/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +19081,75030,18327,PRETRIAL,Cherry,Vernet,NULL,Male,African-American,07/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,Copy,1,0 +19081,75030,18327,PRETRIAL,Cherry,Vernet,NULL,Male,African-American,07/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,Copy,1,0 +19081,75030,18327,PRETRIAL,Cherry,Vernet,NULL,Male,African-American,07/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +64894,75044,67972,PRETRIAL,Metayer,Julian,NULL,Male,Caucasian,06/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/14 0:00,4,High,7,Risk of Violence,-0.84,9,High,New,1,0 +64894,75044,67972,PRETRIAL,Metayer,Julian,NULL,Male,Caucasian,06/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/14 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +64894,75044,67972,PRETRIAL,Metayer,Julian,NULL,Male,Caucasian,06/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64901,75051,67979,PRETRIAL,Domigues,Jose,NULL,Male,Hispanic,12/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/18/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +64901,75051,67979,PRETRIAL,Domigues,Jose,NULL,Male,Hispanic,12/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/18/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +64901,75051,67979,PRETRIAL,Domigues,Jose,NULL,Male,Hispanic,12/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64910,75058,67985,PRETRIAL,Hutchinson,Courtney,NULL,Male,African-American,08/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +64910,75058,67985,PRETRIAL,Hutchinson,Courtney,NULL,Male,African-American,08/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +64910,75058,67985,PRETRIAL,Hutchinson,Courtney,NULL,Male,African-American,08/24/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +26028,75065,67991,PRETRIAL,ROBINSON,ANTHONY,NULL,Male,African-American,10/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +26028,75065,67991,PRETRIAL,ROBINSON,ANTHONY,NULL,Male,African-American,10/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +26028,75065,67991,PRETRIAL,ROBINSON,ANTHONY,NULL,Male,African-American,10/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64886,75032,67962,PRETRIAL,Castanedacifuentes,Viviana,NULL,Female,Hispanic,08/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +64886,75032,67962,PRETRIAL,Castanedacifuentes,Viviana,NULL,Female,Hispanic,08/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +64886,75032,67962,PRETRIAL,Castanedacifuentes,Viviana,NULL,Female,Hispanic,08/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64899,75049,67977,PRETRIAL,aracena,dolores,NULL,Female,Caucasian,11/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/18/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +64899,75049,67977,PRETRIAL,aracena,dolores,NULL,Female,Caucasian,11/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/18/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +64899,75049,67977,PRETRIAL,aracena,dolores,NULL,Female,Caucasian,11/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64895,75045,67973,Probation,WARE,AARON,NULL,Male,African-American,01/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +64895,75045,67973,Probation,WARE,AARON,NULL,Male,African-American,01/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +64895,75045,67973,Probation,WARE,AARON,NULL,Male,African-American,01/05/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +38908,75031,67961,PRETRIAL,hawkins,timothy,NULL,Male,African-American,12/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +38908,75031,67961,PRETRIAL,hawkins,timothy,NULL,Male,African-American,12/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +38908,75031,67961,PRETRIAL,hawkins,timothy,NULL,Male,African-American,12/18/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64907,75057,67984,Probation,Lopez,Andres,NULL,Male,Hispanic,11/09/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +64907,75057,67984,Probation,Lopez,Andres,NULL,Male,Hispanic,11/09/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +64907,75057,67984,Probation,Lopez,Andres,NULL,Male,Hispanic,11/09/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64888,75036,67965,PRETRIAL,Munroe,Everette,NULL,Male,Other,04/24/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/14 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +64888,75036,67965,PRETRIAL,Munroe,Everette,NULL,Male,Other,04/24/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/14 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +64888,75036,67965,PRETRIAL,Munroe,Everette,NULL,Male,Other,04/24/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64902,75052,67980,Probation,Azulay,Edan,NULL,Male,Caucasian,07/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +64902,75052,67980,Probation,Azulay,Edan,NULL,Male,Caucasian,07/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +64902,75052,67980,Probation,Azulay,Edan,NULL,Male,Caucasian,07/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64893,75043,67971,PRETRIAL,ELKINS,MICHAEL,NULL,Male,Caucasian,07/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +64893,75043,67971,PRETRIAL,ELKINS,MICHAEL,NULL,Male,Caucasian,07/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +64893,75043,67971,PRETRIAL,ELKINS,MICHAEL,NULL,Male,Caucasian,07/27/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +5384,75059,67986,Probation,rudnick,rodney,NULL,Male,Caucasian,04/11/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.05,1,Low,New,1,0 +5384,75059,67986,Probation,rudnick,rodney,NULL,Male,Caucasian,04/11/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +5384,75059,67986,Probation,rudnick,rodney,NULL,Male,Caucasian,04/11/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +34334,75038,33478,PRETRIAL,Adams,Demetris,NULL,Male,African-American,12/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,Copy,1,0 +34334,75038,33478,PRETRIAL,Adams,Demetris,NULL,Male,African-American,12/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,10,High,Copy,1,0 +34334,75038,33478,PRETRIAL,Adams,Demetris,NULL,Male,African-American,12/23/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +64909,75056,67983,PRETRIAL,dryden,ronnie,NULL,Male,African-American,08/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.07,8,High,New,1,0 +64909,75056,67983,PRETRIAL,dryden,ronnie,NULL,Male,African-American,08/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +64909,75056,67983,PRETRIAL,dryden,ronnie,NULL,Male,African-American,08/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +64916,75067,67993,PRETRIAL,LAMB,LAINA,NULL,Female,African-American,02/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +64916,75067,67993,PRETRIAL,LAMB,LAINA,NULL,Female,African-American,02/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +64916,75067,67993,PRETRIAL,LAMB,LAINA,NULL,Female,African-American,02/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/18/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +64896,75046,67974,Probation,kangas,donovan,NULL,Male,Caucasian,06/18/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +64896,75046,67974,Probation,kangas,donovan,NULL,Male,Caucasian,06/18/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +64896,75046,67974,Probation,kangas,donovan,NULL,Male,Caucasian,06/18/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64914,75064,67990,Probation,Swartz,Alexander,NULL,Male,Caucasian,09/02/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +64914,75064,67990,Probation,Swartz,Alexander,NULL,Male,Caucasian,09/02/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +64914,75064,67990,Probation,Swartz,Alexander,NULL,Male,Caucasian,09/02/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +64912,75062,67988,PRETRIAL,MOORE,TYLER,NULL,Male,Caucasian,10/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +64912,75062,67988,PRETRIAL,MOORE,TYLER,NULL,Male,Caucasian,10/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +64912,75062,67988,PRETRIAL,MOORE,TYLER,NULL,Male,Caucasian,10/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64887,75033,67963,PRETRIAL,Cunningham,Michael,Everton,Male,Other,03/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +64887,75033,67963,PRETRIAL,Cunningham,Michael,Everton,Male,Other,03/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/14 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +64887,75033,67963,PRETRIAL,Cunningham,Michael,Everton,Male,Other,03/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +18357,75040,67968,Probation,Wong,Edward,NULL,Male,Caucasian,03/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/18/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +18357,75040,67968,Probation,Wong,Edward,NULL,Male,Caucasian,03/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/18/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +18357,75040,67968,Probation,Wong,Edward,NULL,Male,Caucasian,03/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64903,75054,67981,Probation,CALABRIA,KENNETH,NULL,Male,Caucasian,07/08/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +64903,75054,67981,Probation,CALABRIA,KENNETH,NULL,Male,Caucasian,07/08/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +64903,75054,67981,Probation,CALABRIA,KENNETH,NULL,Male,Caucasian,07/08/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50748,75041,67969,PRETRIAL,taylor,TIMOTHY,NULL,Male,Caucasian,03/19/70,17,All Scales,Intake,English,Other,Jail Inmate,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +50748,75041,67969,PRETRIAL,taylor,TIMOTHY,NULL,Male,Caucasian,03/19/70,17,All Scales,Intake,English,Other,Jail Inmate,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-0.89,2,Low,New,1,0 +50748,75041,67969,PRETRIAL,taylor,TIMOTHY,NULL,Male,Caucasian,03/19/70,17,All Scales,Intake,English,Other,Jail Inmate,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,29,7,Medium,New,1,0 +64898,75048,67976,Probation,bondy,eric,NULL,Male,Caucasian,12/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +64898,75048,67976,Probation,bondy,eric,NULL,Male,Caucasian,12/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +64898,75048,67976,Probation,bondy,eric,NULL,Male,Caucasian,12/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64918,75069,67995,PRETRIAL,Johnson,Frazier,NULL,Male,African-American,08/24/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +64918,75069,67995,PRETRIAL,Johnson,Frazier,NULL,Male,African-American,08/24/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,1,Low,8,Risk of Recidivism,-2.87,1,Low,New,1,0 +64918,75069,67995,PRETRIAL,Johnson,Frazier,NULL,Male,African-American,08/24/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59215,75072,61502,PRETRIAL,Smith,Ladarious,NULL,Male,African-American,04/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,4,High,7,Risk of Violence,-0.73,9,High,Copy,1,0 +59215,75072,61502,PRETRIAL,Smith,Ladarious,NULL,Male,African-American,04/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,4,High,8,Risk of Recidivism,0.25,8,High,Copy,1,0 +59215,75072,61502,PRETRIAL,Smith,Ladarious,NULL,Male,African-American,04/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +56089,75073,67246,Probation,daniels,TIFFANY,NULL,Female,African-American,11/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/19/14 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,Copy,1,0 +56089,75073,67246,Probation,daniels,TIFFANY,NULL,Female,African-American,11/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,Copy,1,0 +56089,75073,67246,Probation,daniels,TIFFANY,NULL,Female,African-American,11/17/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/19/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +64919,75071,67997,PRETRIAL,Sainvil,Junio,NULL,Male,African-American,11/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +64919,75071,67997,PRETRIAL,Sainvil,Junio,NULL,Male,African-American,11/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.74,10,High,New,1,0 +64919,75071,67997,PRETRIAL,Sainvil,Junio,NULL,Male,African-American,11/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +6575,75074,67998,PRETRIAL,PICKNEY,THEOPHILIS,NULL,Male,African-American,10/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +6575,75074,67998,PRETRIAL,PICKNEY,THEOPHILIS,NULL,Male,African-American,10/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +6575,75074,67998,PRETRIAL,PICKNEY,THEOPHILIS,NULL,Male,African-American,10/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +4878,75070,67996,PRETRIAL,CHARVIN,DARRYL,NULL,Male,Caucasian,08/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +4878,75070,67996,PRETRIAL,CHARVIN,DARRYL,NULL,Male,Caucasian,08/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +4878,75070,67996,PRETRIAL,CHARVIN,DARRYL,NULL,Male,Caucasian,08/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/19/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64917,75068,67994,PRETRIAL,Alvarez,Abilio,NULL,Male,Hispanic,05/29/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/19/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +64917,75068,67994,PRETRIAL,Alvarez,Abilio,NULL,Male,Hispanic,05/29/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/19/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +64917,75068,67994,PRETRIAL,Alvarez,Abilio,NULL,Male,Hispanic,05/29/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64929,75089,68010,PRETRIAL,MOSLEY,LAPORSHA,NULL,Female,African-American,12/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +64929,75089,68010,PRETRIAL,MOSLEY,LAPORSHA,NULL,Female,African-American,12/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +64929,75089,68010,PRETRIAL,MOSLEY,LAPORSHA,NULL,Female,African-American,12/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64925,75081,68004,PRETRIAL,CLARK,GWEDOLYN,NULL,Female,African-American,06/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +64925,75081,68004,PRETRIAL,CLARK,GWEDOLYN,NULL,Female,African-American,06/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +64925,75081,68004,PRETRIAL,CLARK,GWEDOLYN,NULL,Female,African-American,06/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64927,75084,68006,PRETRIAL,WIJESUNDERA,DINOO,Y,Male,Caucasian,07/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/20/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +64927,75084,68006,PRETRIAL,WIJESUNDERA,DINOO,Y,Male,Caucasian,07/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/20/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +64927,75084,68006,PRETRIAL,WIJESUNDERA,DINOO,Y,Male,Caucasian,07/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64920,75076,68000,PRETRIAL,Baez,Yusniel,NULL,Male,Hispanic,07/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +64920,75076,68000,PRETRIAL,Baez,Yusniel,NULL,Male,Hispanic,07/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +64920,75076,68000,PRETRIAL,Baez,Yusniel,NULL,Male,Hispanic,07/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64931,75091,68012,PRETRIAL,CHIN,CLIFTON,DENMARK,Male,African-American,05/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/20/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +64931,75091,68012,PRETRIAL,CHIN,CLIFTON,DENMARK,Male,African-American,05/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/20/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +64931,75091,68012,PRETRIAL,CHIN,CLIFTON,DENMARK,Male,African-American,05/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64922,75079,68002,PRETRIAL,Pollard,Destinie,NULL,Female,African-American,09/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +64922,75079,68002,PRETRIAL,Pollard,Destinie,NULL,Female,African-American,09/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +64922,75079,68002,PRETRIAL,Pollard,Destinie,NULL,Female,African-American,09/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +52668,75086,54024,PRETRIAL,LOUIS,COURTNEY,NULL,Male,African-American,05/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,Copy,1,0 +52668,75086,54024,PRETRIAL,LOUIS,COURTNEY,NULL,Male,African-American,05/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,Copy,1,0 +52668,75086,54024,PRETRIAL,LOUIS,COURTNEY,NULL,Male,African-American,05/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +64928,75088,68009,PRETRIAL,BARRY,COLLEEN,NULL,Female,Caucasian,07/16/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/20/14 0:00,1,Low,7,Risk of Violence,-4.32,1,Low,New,1,0 +64928,75088,68009,PRETRIAL,BARRY,COLLEEN,NULL,Female,Caucasian,07/16/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/20/14 0:00,1,Low,8,Risk of Recidivism,-2.77,1,Low,New,1,0 +64928,75088,68009,PRETRIAL,BARRY,COLLEEN,NULL,Female,Caucasian,07/16/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64924,75080,68003,PRETRIAL,HUERTA,FRANCISCO,NULL,Male,Hispanic,04/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/20/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +64924,75080,68003,PRETRIAL,HUERTA,FRANCISCO,NULL,Male,Hispanic,04/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/20/14 0:00,1,Low,8,Risk of Recidivism,-2.48,1,Low,New,1,0 +64924,75080,68003,PRETRIAL,HUERTA,FRANCISCO,NULL,Male,Hispanic,04/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/20/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +26521,75087,68008,PRETRIAL,Rajman,Chapin,NULL,Male,African-American,03/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,New,1,0 +26521,75087,68008,PRETRIAL,Rajman,Chapin,NULL,Male,African-American,03/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +26521,75087,68008,PRETRIAL,Rajman,Chapin,NULL,Male,African-American,03/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64932,75092,68013,PRETRIAL,bullard,quentin,NULL,Male,African-American,03/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +64932,75092,68013,PRETRIAL,bullard,quentin,NULL,Male,African-American,03/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +64932,75092,68013,PRETRIAL,bullard,quentin,NULL,Male,African-American,03/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +9194,75078,8730,PRETRIAL,THOMAS,MARK,DEMETRIUS,Male,African-American,12/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,Copy,1,0 +9194,75078,8730,PRETRIAL,THOMAS,MARK,DEMETRIUS,Male,African-American,12/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,Copy,1,0 +9194,75078,8730,PRETRIAL,THOMAS,MARK,DEMETRIUS,Male,African-American,12/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +44713,75085,68007,PRETRIAL,Murphy,Tamesha,NULL,Female,African-American,11/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +44713,75085,68007,PRETRIAL,Murphy,Tamesha,NULL,Female,African-American,11/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +44713,75085,68007,PRETRIAL,Murphy,Tamesha,NULL,Female,African-American,11/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64921,75077,68001,PRETRIAL,McLemore,Adonica,NULL,Female,African-American,08/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/20/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +64921,75077,68001,PRETRIAL,McLemore,Adonica,NULL,Female,African-American,08/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/20/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +64921,75077,68001,PRETRIAL,McLemore,Adonica,NULL,Female,African-American,08/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +667,75075,67999,Broward County,RICKS,DEVON,NULL,Male,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +667,75075,67999,Broward County,RICKS,DEVON,NULL,Male,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +667,75075,67999,Broward County,RICKS,DEVON,NULL,Male,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +26556,75082,25656,PRETRIAL,ANTHONY,CURTIS,NULL,Male,African-American,05/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,Copy,1,0 +26556,75082,25656,PRETRIAL,ANTHONY,CURTIS,NULL,Male,African-American,05/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,Copy,1,0 +26556,75082,25656,PRETRIAL,ANTHONY,CURTIS,NULL,Male,African-American,05/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,2,Medium,18,Risk of Failure to Appear,42,10,High,Copy,1,0 +64926,75083,68005,PRETRIAL,MOSCOSO,DARIO,NULL,Male,Caucasian,05/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +64926,75083,68005,PRETRIAL,MOSCOSO,DARIO,NULL,Male,Caucasian,05/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +64926,75083,68005,PRETRIAL,MOSCOSO,DARIO,NULL,Male,Caucasian,05/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64930,75090,68011,PRETRIAL,WELCH,BONITA,EVETTE,Male,African-American,11/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/20/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +64930,75090,68011,PRETRIAL,WELCH,BONITA,EVETTE,Male,African-American,11/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/20/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +64930,75090,68011,PRETRIAL,WELCH,BONITA,EVETTE,Male,African-American,11/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64946,75111,68030,Probation,Aleman,Leonard,NULL,Male,Hispanic,03/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/21/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +64946,75111,68030,Probation,Aleman,Leonard,NULL,Male,Hispanic,03/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +64946,75111,68030,Probation,Aleman,Leonard,NULL,Male,Hispanic,03/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64940,75103,68023,PRETRIAL,Salcedo,Carlos,NULL,Male,Hispanic,04/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +64940,75103,68023,PRETRIAL,Salcedo,Carlos,NULL,Male,Hispanic,04/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +64940,75103,68023,PRETRIAL,Salcedo,Carlos,NULL,Male,Hispanic,04/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64948,75114,68033,Probation,Valencia,Felipe,NULL,Female,Hispanic,09/10/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/21/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +64948,75114,68033,Probation,Valencia,Felipe,NULL,Female,Hispanic,09/10/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +64948,75114,68033,Probation,Valencia,Felipe,NULL,Female,Hispanic,09/10/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +26329,75127,68045,PRETRIAL,Xavier,Chad,NULL,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +26329,75127,68045,PRETRIAL,Xavier,Chad,NULL,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.82,10,High,New,1,0 +26329,75127,68045,PRETRIAL,Xavier,Chad,NULL,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56934,75106,68025,Probation,RAYMOND,LEGITIME,NULL,Male,African-American,06/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +56934,75106,68025,Probation,RAYMOND,LEGITIME,NULL,Male,African-American,06/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +56934,75106,68025,Probation,RAYMOND,LEGITIME,NULL,Male,African-American,06/09/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +8591,75124,68042,Probation,Rodriguez,Felix,NULL,Male,Hispanic,08/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +8591,75124,68042,Probation,Rodriguez,Felix,NULL,Male,Hispanic,08/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +8591,75124,68042,Probation,Rodriguez,Felix,NULL,Male,Hispanic,08/29/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64933,75093,68014,PRETRIAL,Roberts,Kenneth,NULL,Male,Caucasian,06/20/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +64933,75093,68014,PRETRIAL,Roberts,Kenneth,NULL,Male,Caucasian,06/20/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +64933,75093,68014,PRETRIAL,Roberts,Kenneth,NULL,Male,Caucasian,06/20/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +56609,75098,68019,PRETRIAL,Lopez,Kathleen,NULL,Female,Hispanic,10/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +56609,75098,68019,PRETRIAL,Lopez,Kathleen,NULL,Female,Hispanic,10/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +56609,75098,68019,PRETRIAL,Lopez,Kathleen,NULL,Female,Hispanic,10/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64936,75096,68017,PRETRIAL,WEINKLE,PAIGE,NULL,Female,Caucasian,03/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +64936,75096,68017,PRETRIAL,WEINKLE,PAIGE,NULL,Female,Caucasian,03/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +64936,75096,68017,PRETRIAL,WEINKLE,PAIGE,NULL,Female,Caucasian,03/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64947,75113,68032,Probation,Abelto,Jerry,NULL,Male,African-American,12/08/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +64947,75113,68032,Probation,Abelto,Jerry,NULL,Male,African-American,12/08/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +64947,75113,68032,Probation,Abelto,Jerry,NULL,Male,African-American,12/08/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64938,75099,68020,PRETRIAL,KEYES,RENAE,RESHON,Female,African-American,12/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.46,3,Low,New,1,0 +64938,75099,68020,PRETRIAL,KEYES,RENAE,RESHON,Female,African-American,12/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,9,High,New,1,0 +64938,75099,68020,PRETRIAL,KEYES,RENAE,RESHON,Female,African-American,12/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +64949,75117,68035,Probation,Strong,Felicia,Fayo,Female,African-American,08/09/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.07,4,Low,New,1,0 +64949,75117,68035,Probation,Strong,Felicia,Fayo,Female,African-American,08/09/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +64949,75117,68035,Probation,Strong,Felicia,Fayo,Female,African-American,08/09/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64934,75094,68015,PRETRIAL,Glinton,Vincent,NULL,Male,African-American,08/12/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +64934,75094,68015,PRETRIAL,Glinton,Vincent,NULL,Male,African-American,08/12/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +64934,75094,68015,PRETRIAL,Glinton,Vincent,NULL,Male,African-American,08/12/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64959,75129,68047,Probation,MATERA,SOPHIE,NULL,Female,Caucasian,01/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +64959,75129,68047,Probation,MATERA,SOPHIE,NULL,Female,Caucasian,01/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +64959,75129,68047,Probation,MATERA,SOPHIE,NULL,Female,Caucasian,01/10/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64939,75101,68022,PRETRIAL,Tal-Mason,David,NULL,Male,Caucasian,12/14/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/21/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +64939,75101,68022,PRETRIAL,Tal-Mason,David,NULL,Male,Caucasian,12/14/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +64939,75101,68022,PRETRIAL,Tal-Mason,David,NULL,Male,Caucasian,12/14/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64942,75108,68027,PRETRIAL,Lanciault,Melyssa,NULL,Female,Caucasian,04/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,2,Medium,7,Risk of Violence,-2.83,2,Low,New,1,0 +64942,75108,68027,PRETRIAL,Lanciault,Melyssa,NULL,Female,Caucasian,04/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +64942,75108,68027,PRETRIAL,Lanciault,Melyssa,NULL,Female,Caucasian,04/14/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +60547,75115,62996,PRETRIAL,Jones,Kelvin,NULL,Male,African-American,04/07/64,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +60547,75115,62996,PRETRIAL,Jones,Kelvin,NULL,Male,African-American,04/07/64,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +60547,75115,62996,PRETRIAL,Jones,Kelvin,NULL,Male,African-American,04/07/64,17,All Scales,Intake,English,Conditional Release,Probation,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,35,9,High,New,1,0 +47715,75122,68040,PRETRIAL,Kelson,Damon,NULL,Male,African-American,12/29/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +47715,75122,68040,PRETRIAL,Kelson,Damon,NULL,Male,African-American,12/29/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +47715,75122,68040,PRETRIAL,Kelson,Damon,NULL,Male,African-American,12/29/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64941,75107,68026,Probation,GARCIA,RAUL,ERNESTO,Male,Hispanic,10/08/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/21/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +64941,75107,68026,Probation,GARCIA,RAUL,ERNESTO,Male,Hispanic,10/08/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/21/14 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +64941,75107,68026,Probation,GARCIA,RAUL,ERNESTO,Male,Hispanic,10/08/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64943,75109,68028,Probation,vallejo,carlos,NULL,Male,Hispanic,02/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +64943,75109,68028,Probation,vallejo,carlos,NULL,Male,Hispanic,02/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +64943,75109,68028,Probation,vallejo,carlos,NULL,Male,Hispanic,02/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64666,75116,68034,PRETRIAL,Boggs,Lennon,NULL,Male,Caucasian,09/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +64666,75116,68034,PRETRIAL,Boggs,Lennon,NULL,Male,Caucasian,09/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +64666,75116,68034,PRETRIAL,Boggs,Lennon,NULL,Male,Caucasian,09/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64923,75130,68048,PRETRIAL,LOPERENA,CHRISTIAN,NULL,Male,Caucasian,12/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +64923,75130,68048,PRETRIAL,LOPERENA,CHRISTIAN,NULL,Male,Caucasian,12/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +64923,75130,68048,PRETRIAL,LOPERENA,CHRISTIAN,NULL,Male,Caucasian,12/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +50256,75100,68021,PRETRIAL,GRAHAM JR,DERRYLNICK,MONDELL,Male,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +50256,75100,68021,PRETRIAL,GRAHAM JR,DERRYLNICK,MONDELL,Male,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +50256,75100,68021,PRETRIAL,GRAHAM JR,DERRYLNICK,MONDELL,Male,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64957,75125,68043,Probation,CURRAN,RAYMOND,JOHN,Male,Hispanic,03/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +64957,75125,68043,Probation,CURRAN,RAYMOND,JOHN,Male,Hispanic,03/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +64957,75125,68043,Probation,CURRAN,RAYMOND,JOHN,Male,Hispanic,03/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +64953,75121,68039,Probation,HARE,KORTNEY,DAWN,Female,Caucasian,03/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +64953,75121,68039,Probation,HARE,KORTNEY,DAWN,Female,Caucasian,03/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +64953,75121,68039,Probation,HARE,KORTNEY,DAWN,Female,Caucasian,03/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +64935,75095,68016,PRETRIAL,McDonald,Richard,George,Male,African-American,03/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/21/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +64935,75095,68016,PRETRIAL,McDonald,Richard,George,Male,African-American,03/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +64935,75095,68016,PRETRIAL,McDonald,Richard,George,Male,African-American,03/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64958,75126,68044,Probation,Velasco,jaime,NULL,Male,Hispanic,08/26/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/21/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +64958,75126,68044,Probation,Velasco,jaime,NULL,Male,Hispanic,08/26/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +64958,75126,68044,Probation,Velasco,jaime,NULL,Male,Hispanic,08/26/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64937,75097,68018,PRETRIAL,JACKMAN,MARCUS,H,Male,African-American,08/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +64937,75097,68018,PRETRIAL,JACKMAN,MARCUS,H,Male,African-American,08/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +64937,75097,68018,PRETRIAL,JACKMAN,MARCUS,H,Male,African-American,08/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/21/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +15244,75112,68031,PRETRIAL,JEAN,BERNIE,M,Male,African-American,05/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +15244,75112,68031,PRETRIAL,JEAN,BERNIE,M,Male,African-American,05/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.89,10,High,New,1,0 +15244,75112,68031,PRETRIAL,JEAN,BERNIE,M,Male,African-American,05/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64950,75118,68036,Probation,JOSEPH,RICKY,NULL,Male,Caucasian,10/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/21/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +64950,75118,68036,Probation,JOSEPH,RICKY,NULL,Male,Caucasian,10/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/21/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +64950,75118,68036,Probation,JOSEPH,RICKY,NULL,Male,Caucasian,10/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58008,75105,68024,PRETRIAL,Degrange,David,NULL,Male,Caucasian,10/28/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +58008,75105,68024,PRETRIAL,Degrange,David,NULL,Male,Caucasian,10/28/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +58008,75105,68024,PRETRIAL,Degrange,David,NULL,Male,Caucasian,10/28/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64952,75120,68038,Probation,eggers,edwards,NULL,Male,Caucasian,05/01/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +64952,75120,68038,Probation,eggers,edwards,NULL,Male,Caucasian,05/01/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +64952,75120,68038,Probation,eggers,edwards,NULL,Male,Caucasian,05/01/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64944,75110,68029,Probation,graziano,Christine,Marie,Female,Caucasian,06/21/62,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,7/21/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +64944,75110,68029,Probation,graziano,Christine,Marie,Female,Caucasian,06/21/62,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +64944,75110,68029,Probation,graziano,Christine,Marie,Female,Caucasian,06/21/62,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64960,75131,68049,Probation,NUNEZ,ROFEL,LUIS,Male,Hispanic,05/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +64960,75131,68049,Probation,NUNEZ,ROFEL,LUIS,Male,Hispanic,05/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +64960,75131,68049,Probation,NUNEZ,ROFEL,LUIS,Male,Hispanic,05/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +56601,75128,68046,Probation,Desravines,James,NULL,Male,African-American,05/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/21/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +56601,75128,68046,Probation,Desravines,James,NULL,Male,African-American,05/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/21/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +56601,75128,68046,Probation,Desravines,James,NULL,Male,African-American,05/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64481,75102,67496,PRETRIAL,Meadows,David,NULL,Male,Caucasian,10/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,Copy,1,0 +64481,75102,67496,PRETRIAL,Meadows,David,NULL,Male,Caucasian,10/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,7,Medium,Copy,1,0 +64481,75102,67496,PRETRIAL,Meadows,David,NULL,Male,Caucasian,10/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +64954,75123,68041,Probation,hurtado,dionne,NULL,Female,Hispanic,12/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/21/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +64954,75123,68041,Probation,hurtado,dionne,NULL,Female,Hispanic,12/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/21/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +64954,75123,68041,Probation,hurtado,dionne,NULL,Female,Hispanic,12/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +64983,75157,68073,Probation,williams,cambre,NULL,Female,African-American,08/28/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +64983,75157,68073,Probation,williams,cambre,NULL,Female,African-American,08/28/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +64983,75157,68073,Probation,williams,cambre,NULL,Female,African-American,08/28/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +32610,75136,68053,PRETRIAL,Brown,Charles,NULL,Male,African-American,05/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +32610,75136,68053,PRETRIAL,Brown,Charles,NULL,Male,African-American,05/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,4,High,8,Risk of Recidivism,0.75,10,High,New,1,0 +32610,75136,68053,PRETRIAL,Brown,Charles,NULL,Male,African-American,05/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +43171,47192,43078,PRETRIAL,Bizcaino,Jonathan,NULL,Male,Hispanic,03/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.85,9,High,New,1,0 +43171,47192,43078,PRETRIAL,Bizcaino,Jonathan,NULL,Male,Hispanic,03/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +43171,47192,43078,PRETRIAL,Bizcaino,Jonathan,NULL,Male,Hispanic,03/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64974,75149,68065,PRETRIAL,Trobridge,Donnell,NULL,Male,African-American,01/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +64974,75149,68065,PRETRIAL,Trobridge,Donnell,NULL,Male,African-American,01/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +64974,75149,68065,PRETRIAL,Trobridge,Donnell,NULL,Male,African-American,01/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +29388,75139,28416,PRETRIAL,Deconti,Ernest,N,Male,Caucasian,07/20/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/22/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,Copy,1,0 +29388,75139,28416,PRETRIAL,Deconti,Ernest,N,Male,Caucasian,07/20/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/22/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,Copy,1,0 +29388,75139,28416,PRETRIAL,Deconti,Ernest,N,Male,Caucasian,07/20/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +64979,75154,68070,Probation,DOMKOSKI,KENNETH,NULL,Male,Caucasian,01/30/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +64979,75154,68070,Probation,DOMKOSKI,KENNETH,NULL,Male,Caucasian,01/30/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +64979,75154,68070,Probation,DOMKOSKI,KENNETH,NULL,Male,Caucasian,01/30/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64967,75141,68057,PRETRIAL,Joseph,Veronica,NULL,Female,African-American,02/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +64967,75141,68057,PRETRIAL,Joseph,Veronica,NULL,Female,African-American,02/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +64967,75141,68057,PRETRIAL,Joseph,Veronica,NULL,Female,African-American,02/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64973,75147,68063,Probation,ALBUALYAN,WALEED,AHMED,Male,Arabic,08/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +64973,75147,68063,Probation,ALBUALYAN,WALEED,AHMED,Male,Arabic,08/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +64973,75147,68063,Probation,ALBUALYAN,WALEED,AHMED,Male,Arabic,08/22/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64986,75162,68077,Probation,DORTELUS,MARTHE,S,Female,African-American,04/30/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +64986,75162,68077,Probation,DORTELUS,MARTHE,S,Female,African-American,04/30/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +64986,75162,68077,Probation,DORTELUS,MARTHE,S,Female,African-American,04/30/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64961,75133,68050,PRETRIAL,ALAVAREZ,MANUEL,NULL,Male,Hispanic,01/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +64961,75133,68050,PRETRIAL,ALAVAREZ,MANUEL,NULL,Male,Hispanic,01/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +64961,75133,68050,PRETRIAL,ALAVAREZ,MANUEL,NULL,Male,Hispanic,01/15/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64972,75146,68062,Probation,burke,michael,NULL,Male,Caucasian,11/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +64972,75146,68062,Probation,burke,michael,NULL,Male,Caucasian,11/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +64972,75146,68062,Probation,burke,michael,NULL,Male,Caucasian,11/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64987,75163,68078,Probation,JOHNSON,ALICIA,NULL,Male,African-American,10/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +64987,75163,68078,Probation,JOHNSON,ALICIA,NULL,Male,African-American,10/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +64987,75163,68078,Probation,JOHNSON,ALICIA,NULL,Male,African-American,10/17/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +50801,57112,51901,PRETRIAL,RIKER,KENNETH,NULL,Male,Caucasian,04/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/22/14 0:00,4,High,7,Risk of Violence,0.25,10,High,New,1,0 +50801,57112,51901,PRETRIAL,RIKER,KENNETH,NULL,Male,Caucasian,04/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/22/14 0:00,4,High,8,Risk of Recidivism,1.31,10,High,New,1,0 +50801,57112,51901,PRETRIAL,RIKER,KENNETH,NULL,Male,Caucasian,04/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/22/14 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +64982,75156,68072,Probation,BOYLE,CHRISTOPHER,M,Male,Caucasian,07/28/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/22/14 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +64982,75156,68072,Probation,BOYLE,CHRISTOPHER,M,Male,Caucasian,07/28/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +64982,75156,68072,Probation,BOYLE,CHRISTOPHER,M,Male,Caucasian,07/28/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/22/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +64981,75160,68075,Probation,Hazlett,Sophia,NULL,Female,Caucasian,07/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/22/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +64981,75160,68075,Probation,Hazlett,Sophia,NULL,Female,Caucasian,07/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/22/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +64981,75160,68075,Probation,Hazlett,Sophia,NULL,Female,Caucasian,07/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64990,75167,68081,PRETRIAL,Dauch,Kerri,A,Female,Caucasian,06/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +64990,75167,68081,PRETRIAL,Dauch,Kerri,A,Female,Caucasian,06/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +64990,75167,68081,PRETRIAL,Dauch,Kerri,A,Female,Caucasian,06/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64976,75151,68067,Probation,DOWNER,BRIAN,J,Male,Hispanic,08/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +64976,75151,68067,Probation,DOWNER,BRIAN,J,Male,Hispanic,08/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +64976,75151,68067,Probation,DOWNER,BRIAN,J,Male,Hispanic,08/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +32917,75158,31985,PRETRIAL,Wilson,Herbert,NULL,Male,African-American,03/22/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/22/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +32917,75158,31985,PRETRIAL,Wilson,Herbert,NULL,Male,African-American,03/22/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/22/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +32917,75158,31985,PRETRIAL,Wilson,Herbert,NULL,Male,African-American,03/22/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64988,75165,68079,PRETRIAL,Charles,Rodney,NULL,Male,African-American,10/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +64988,75165,68079,PRETRIAL,Charles,Rodney,NULL,Male,African-American,10/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/14 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +64988,75165,68079,PRETRIAL,Charles,Rodney,NULL,Male,African-American,10/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/22/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64964,75137,68054,PRETRIAL,HOLT,HANNAH,NICOLE,Female,Caucasian,08/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +64964,75137,68054,PRETRIAL,HOLT,HANNAH,NICOLE,Female,Caucasian,08/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +64964,75137,68054,PRETRIAL,HOLT,HANNAH,NICOLE,Female,Caucasian,08/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +64969,75143,68059,Probation,sugarman,william,NULL,Male,Caucasian,10/05/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/22/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +64969,75143,68059,Probation,sugarman,william,NULL,Male,Caucasian,10/05/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/22/14 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +64969,75143,68059,Probation,sugarman,william,NULL,Male,Caucasian,10/05/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64975,75150,68066,Probation,willie,Merritt,NULL,Male,African-American,02/07/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/22/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +64975,75150,68066,Probation,willie,Merritt,NULL,Male,African-American,02/07/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/22/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +64975,75150,68066,Probation,willie,Merritt,NULL,Male,African-American,02/07/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58883,75164,61120,PRETRIAL,Senior,Michael,Tyron,Male,African-American,10/20/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,Copy,1,0 +58883,75164,61120,PRETRIAL,Senior,Michael,Tyron,Male,African-American,10/20/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,Copy,1,0 +58883,75164,61120,PRETRIAL,Senior,Michael,Tyron,Male,African-American,10/20/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +64965,75138,68055,PRETRIAL,WILLIAMS,PRECIOUS,NULL,Male,African-American,09/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +64965,75138,68055,PRETRIAL,WILLIAMS,PRECIOUS,NULL,Male,African-American,09/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +64965,75138,68055,PRETRIAL,WILLIAMS,PRECIOUS,NULL,Male,African-American,09/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64980,75155,68071,Probation,buscarello,john,NULL,Male,Caucasian,10/22/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.01,4,Low,New,1,0 +64980,75155,68071,Probation,buscarello,john,NULL,Male,Caucasian,10/22/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +64980,75155,68071,Probation,buscarello,john,NULL,Male,Caucasian,10/22/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64962,75134,68051,PRETRIAL,DONAWA,MARIO,M,Male,African-American,05/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +64962,75134,68051,PRETRIAL,DONAWA,MARIO,M,Male,African-American,05/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +64962,75134,68051,PRETRIAL,DONAWA,MARIO,M,Male,African-American,05/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64984,75159,68074,Probation,UMANA,JOSE,NULL,Male,Hispanic,08/06/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/22/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +64984,75159,68074,Probation,UMANA,JOSE,NULL,Male,Hispanic,08/06/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/22/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +64984,75159,68074,Probation,UMANA,JOSE,NULL,Male,Hispanic,08/06/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64991,75168,68082,Probation,west,gerry,NULL,Male,African-American,08/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,New,1,0 +64991,75168,68082,Probation,west,gerry,NULL,Male,African-American,08/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +64991,75168,68082,Probation,west,gerry,NULL,Male,African-American,08/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64978,75153,68069,Probation,Dipietro,Michael,NULL,Male,Caucasian,10/03/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +64978,75153,68069,Probation,Dipietro,Michael,NULL,Male,Caucasian,10/03/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,8,Risk of Recidivism,-2.73,1,Low,New,1,0 +64978,75153,68069,Probation,Dipietro,Michael,NULL,Male,Caucasian,10/03/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64963,75135,68052,PRETRIAL,Rodriguez,Luis,NULL,Male,Hispanic,07/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +64963,75135,68052,PRETRIAL,Rodriguez,Luis,NULL,Male,Hispanic,07/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +64963,75135,68052,PRETRIAL,Rodriguez,Luis,NULL,Male,Hispanic,07/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64971,75145,68061,PRETRIAL,Roman,Merida,NULL,Female,Hispanic,05/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/22/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +64971,75145,68061,PRETRIAL,Roman,Merida,NULL,Female,Hispanic,05/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/22/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +64971,75145,68061,PRETRIAL,Roman,Merida,NULL,Female,Hispanic,05/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64992,75169,68083,Probation,El,Alicia,NULL,Female,African-American,06/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +64992,75169,68083,Probation,El,Alicia,NULL,Female,African-American,06/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +64992,75169,68083,Probation,El,Alicia,NULL,Female,African-American,06/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +36960,75148,68064,PRETRIAL,Thomas,Joseph,NULL,Male,Caucasian,02/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +36960,75148,68064,PRETRIAL,Thomas,Joseph,NULL,Male,Caucasian,02/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +36960,75148,68064,PRETRIAL,Thomas,Joseph,NULL,Male,Caucasian,02/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64966,75140,68056,PRETRIAL,Jones,Demetius,NULL,Male,African-American,01/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/22/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +64966,75140,68056,PRETRIAL,Jones,Demetius,NULL,Male,African-American,01/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/22/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +64966,75140,68056,PRETRIAL,Jones,Demetius,NULL,Male,African-American,01/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64998,75176,68090,PRETRIAL,ORENBUCH,TYLER,NULL,Male,Caucasian,12/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.18,8,High,New,1,0 +64998,75176,68090,PRETRIAL,ORENBUCH,TYLER,NULL,Male,Caucasian,12/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +64998,75176,68090,PRETRIAL,ORENBUCH,TYLER,NULL,Male,Caucasian,12/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +28423,75197,27467,PRETRIAL,Lewis,Christopher,NULL,Male,African-American,03/15/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,Copy,1,0 +28423,75197,27467,PRETRIAL,Lewis,Christopher,NULL,Male,African-American,03/15/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,Copy,1,0 +28423,75197,27467,PRETRIAL,Lewis,Christopher,NULL,Male,African-American,03/15/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +65001,75182,68094,PRETRIAL,Francois,Alex,Marquis,Male,African-American,07/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +65001,75182,68094,PRETRIAL,Francois,Alex,Marquis,Male,African-American,07/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,4,High,8,Risk of Recidivism,0.22,8,High,New,1,0 +65001,75182,68094,PRETRIAL,Francois,Alex,Marquis,Male,African-American,07/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65002,75184,68096,PRETRIAL,knepper,ralph,NULL,Male,African-American,12/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +65002,75184,68096,PRETRIAL,knepper,ralph,NULL,Male,African-American,12/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +65002,75184,68096,PRETRIAL,knepper,ralph,NULL,Male,African-American,12/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65011,75195,68107,Probation,Cosper,Hypatia,NULL,Female,Caucasian,03/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/23/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +65011,75195,68107,Probation,Cosper,Hypatia,NULL,Female,Caucasian,03/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/23/14 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +65011,75195,68107,Probation,Cosper,Hypatia,NULL,Female,Caucasian,03/14/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +35842,75174,68088,PRETRIAL,Cabrera,Pablo,NULL,Male,Caucasian,09/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +35842,75174,68088,PRETRIAL,Cabrera,Pablo,NULL,Male,Caucasian,09/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +35842,75174,68088,PRETRIAL,Cabrera,Pablo,NULL,Male,Caucasian,09/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65009,75192,68104,Probation,howard,mary,NULL,Female,Caucasian,10/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +65009,75192,68104,Probation,howard,mary,NULL,Female,Caucasian,10/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +65009,75192,68104,Probation,howard,mary,NULL,Female,Caucasian,10/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65005,75187,68099,Probation,gigger,tommy,NULL,Male,African-American,03/28/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +65005,75187,68099,Probation,gigger,tommy,NULL,Male,African-American,03/28/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +65005,75187,68099,Probation,gigger,tommy,NULL,Male,African-American,03/28/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65018,75200,68111,PRETRIAL,laute,alexander,NULL,Male,Caucasian,06/10/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,New,1,0 +65018,75200,68111,PRETRIAL,laute,alexander,NULL,Male,Caucasian,06/10/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +65018,75200,68111,PRETRIAL,laute,alexander,NULL,Male,Caucasian,06/10/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,2,Low,New,1,0 +65006,75189,68101,Probation,BASTO,ACELA,JOSEFA,Male,Hispanic,08/27/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +65006,75189,68101,Probation,BASTO,ACELA,JOSEFA,Male,Hispanic,08/27/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/14 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +65006,75189,68101,Probation,BASTO,ACELA,JOSEFA,Male,Hispanic,08/27/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64996,75173,68087,PRETRIAL,Lozada,Luis,Roberto,Male,Caucasian,04/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +64996,75173,68087,PRETRIAL,Lozada,Luis,Roberto,Male,Caucasian,04/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +64996,75173,68087,PRETRIAL,Lozada,Luis,Roberto,Male,Caucasian,04/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64994,75171,68085,PRETRIAL,COLBERT,KAITLIN,ALEXIS,Female,Caucasian,12/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +64994,75171,68085,PRETRIAL,COLBERT,KAITLIN,ALEXIS,Female,Caucasian,12/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +64994,75171,68085,PRETRIAL,COLBERT,KAITLIN,ALEXIS,Female,Caucasian,12/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65019,75201,68112,PRETRIAL,Velasquez,Rony,J,Male,Hispanic,05/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +65019,75201,68112,PRETRIAL,Velasquez,Rony,J,Male,Hispanic,05/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +65019,75201,68112,PRETRIAL,Velasquez,Rony,J,Male,Hispanic,05/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +48578,75180,68092,PRETRIAL,Finklin,Jeremy,NULL,Male,African-American,02/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,4,High,7,Risk of Violence,-0.92,9,High,New,1,0 +48578,75180,68092,PRETRIAL,Finklin,Jeremy,NULL,Male,African-American,02/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +48578,75180,68092,PRETRIAL,Finklin,Jeremy,NULL,Male,African-American,02/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +49769,75194,68106,PRETRIAL,SUAREZ,francisco,NULL,Male,Caucasian,10/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +49769,75194,68106,PRETRIAL,SUAREZ,francisco,NULL,Male,Caucasian,10/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +49769,75194,68106,PRETRIAL,SUAREZ,francisco,NULL,Male,Caucasian,10/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65004,75186,68098,Probation,Betancourt,Sebastian,NULL,Male,Hispanic,10/19/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +65004,75186,68098,Probation,Betancourt,Sebastian,NULL,Male,Hispanic,10/19/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +65004,75186,68098,Probation,Betancourt,Sebastian,NULL,Male,Hispanic,10/19/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +11475,75188,68100,PRETRIAL,CONEY,ARTHUR,LEE,Male,African-American,03/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +11475,75188,68100,PRETRIAL,CONEY,ARTHUR,LEE,Male,African-American,03/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +11475,75188,68100,PRETRIAL,CONEY,ARTHUR,LEE,Male,African-American,03/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +64999,75179,68091,PRETRIAL,Mcfadden,Jarvis,NULL,Male,African-American,11/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/23/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +64999,75179,68091,PRETRIAL,Mcfadden,Jarvis,NULL,Male,African-American,11/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/23/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +64999,75179,68091,PRETRIAL,Mcfadden,Jarvis,NULL,Male,African-American,11/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65000,75181,68093,PRETRIAL,Youngblood,Reginald,NULL,Male,African-American,09/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +65000,75181,68093,PRETRIAL,Youngblood,Reginald,NULL,Male,African-American,09/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +65000,75181,68093,PRETRIAL,Youngblood,Reginald,NULL,Male,African-American,09/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +64995,75172,68086,PRETRIAL,MARTINEZ,BRABDYN,REY,Male,Caucasian,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +64995,75172,68086,PRETRIAL,MARTINEZ,BRABDYN,REY,Male,Caucasian,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +64995,75172,68086,PRETRIAL,MARTINEZ,BRABDYN,REY,Male,Caucasian,03/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65010,75193,68105,Probation,Pittman,William,NULL,Male,Caucasian,07/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.43,3,Low,New,1,0 +65010,75193,68105,Probation,Pittman,William,NULL,Male,Caucasian,07/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +65010,75193,68105,Probation,Pittman,William,NULL,Male,Caucasian,07/05/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +65013,75198,68109,Probation,Virgile,Rodly,NULL,Male,African-American,12/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.15,4,Low,New,1,0 +65013,75198,68109,Probation,Virgile,Rodly,NULL,Male,African-American,12/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +65013,75198,68109,Probation,Virgile,Rodly,NULL,Male,African-American,12/08/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58286,75183,68095,PRETRIAL,Rolle,Tarell,NULL,Male,African-American,04/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +58286,75183,68095,PRETRIAL,Rolle,Tarell,NULL,Male,African-American,04/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,4,High,8,Risk of Recidivism,0.77,10,High,New,1,0 +58286,75183,68095,PRETRIAL,Rolle,Tarell,NULL,Male,African-American,04/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64997,75175,68089,PRETRIAL,Dawkins,Kashema,NULL,Male,African-American,10/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +64997,75175,68089,PRETRIAL,Dawkins,Kashema,NULL,Male,African-American,10/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +64997,75175,68089,PRETRIAL,Dawkins,Kashema,NULL,Male,African-American,10/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +33233,75199,68110,Probation,Ricozzi,Lawrence,Joshua,Male,Caucasian,08/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +33233,75199,68110,Probation,Ricozzi,Lawrence,Joshua,Male,Caucasian,08/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +33233,75199,68110,Probation,Ricozzi,Lawrence,Joshua,Male,Caucasian,08/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +57529,75178,59639,PRETRIAL,URREA,HELBERT,ANDREAS,Male,Hispanic,07/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,Copy,1,0 +57529,75178,59639,PRETRIAL,URREA,HELBERT,ANDREAS,Male,Hispanic,07/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,Copy,1,0 +57529,75178,59639,PRETRIAL,URREA,HELBERT,ANDREAS,Male,Hispanic,07/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +65012,75196,68108,PRETRIAL,Schnider,Jean,NULL,Male,African-American,01/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +65012,75196,68108,PRETRIAL,Schnider,Jean,NULL,Male,African-American,01/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +65012,75196,68108,PRETRIAL,Schnider,Jean,NULL,Male,African-American,01/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64993,75170,68084,PRETRIAL,SAINTFLEUR,MOSLEY,NULL,Male,Other,12/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +64993,75170,68084,PRETRIAL,SAINTFLEUR,MOSLEY,NULL,Male,Other,12/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +64993,75170,68084,PRETRIAL,SAINTFLEUR,MOSLEY,NULL,Male,Other,12/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65008,75191,68103,Probation,Phillips,Rodrick,NULL,Male,African-American,02/24/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +65008,75191,68103,Probation,Phillips,Rodrick,NULL,Male,African-American,02/24/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +65008,75191,68103,Probation,Phillips,Rodrick,NULL,Male,African-American,02/24/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/23/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65022,75204,68115,PRETRIAL,GALARZA,JENNIFER,ERICA,Female,African-American,12/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +65022,75204,68115,PRETRIAL,GALARZA,JENNIFER,ERICA,Female,African-American,12/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,4,High,8,Risk of Recidivism,0.45,10,High,New,1,0 +65022,75204,68115,PRETRIAL,GALARZA,JENNIFER,ERICA,Female,African-American,12/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65036,75217,68128,Probation,Aguirre-Londono,Juan,NULL,Male,Hispanic,10/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/24/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +65036,75217,68128,Probation,Aguirre-Londono,Juan,NULL,Male,Hispanic,10/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/24/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +65036,75217,68128,Probation,Aguirre-Londono,Juan,NULL,Male,Hispanic,10/07/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65039,75220,68131,Probation,Bauman,Richard,NULL,Male,Caucasian,09/03/42,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,7,Risk of Violence,-4.19,1,Low,New,1,0 +65039,75220,68131,Probation,Bauman,Richard,NULL,Male,Caucasian,09/03/42,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +65039,75220,68131,Probation,Bauman,Richard,NULL,Male,Caucasian,09/03/42,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65031,75212,68123,Probation,dollinger,sharon,NULL,Female,Other,10/08/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/24/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +65031,75212,68123,Probation,dollinger,sharon,NULL,Female,Other,10/08/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/24/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +65031,75212,68123,Probation,dollinger,sharon,NULL,Female,Other,10/08/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50303,75223,68134,PRETRIAL,PARKS,BRETT,NULL,Male,African-American,06/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,7/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +50303,75223,68134,PRETRIAL,PARKS,BRETT,NULL,Male,African-American,06/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,7/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +50303,75223,68134,PRETRIAL,PARKS,BRETT,NULL,Male,African-American,06/23/91,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,7/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65047,75232,68142,PRETRIAL,Foster,Kyle,NULL,Male,African-American,08/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +65047,75232,68142,PRETRIAL,Foster,Kyle,NULL,Male,African-American,08/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +65047,75232,68142,PRETRIAL,Foster,Kyle,NULL,Male,African-American,08/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65020,75202,68113,PRETRIAL,Clare,Kenton,Orlick,Male,Other,06/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +65020,75202,68113,PRETRIAL,Clare,Kenton,Orlick,Male,Other,06/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +65020,75202,68113,PRETRIAL,Clare,Kenton,Orlick,Male,Other,06/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65033,75214,68125,Probation,CASASUS,JOHANSON,NULL,Male,Hispanic,12/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +65033,75214,68125,Probation,CASASUS,JOHANSON,NULL,Male,Hispanic,12/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +65033,75214,68125,Probation,CASASUS,JOHANSON,NULL,Male,Hispanic,12/28/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65044,75228,68138,Probation,mchenry,garry,NULL,Male,Caucasian,01/17/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/24/14 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +65044,75228,68138,Probation,mchenry,garry,NULL,Male,Caucasian,01/17/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/24/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +65044,75228,68138,Probation,mchenry,garry,NULL,Male,Caucasian,01/17/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65046,75230,68140,Probation,zebrowski,sandra,NULL,Female,Caucasian,01/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +65046,75230,68140,Probation,zebrowski,sandra,NULL,Female,Caucasian,01/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +65046,75230,68140,Probation,zebrowski,sandra,NULL,Female,Caucasian,01/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +65026,75207,68118,Probation,wahden,ehab,NULL,Male,Arabic,03/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/14 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +65026,75207,68118,Probation,wahden,ehab,NULL,Male,Arabic,03/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +65026,75207,68118,Probation,wahden,ehab,NULL,Male,Arabic,03/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65028,75209,68120,Probation,Rimple,Jean,NULL,Male,African-American,11/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +65028,75209,68120,Probation,Rimple,Jean,NULL,Male,African-American,11/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +65028,75209,68120,Probation,Rimple,Jean,NULL,Male,African-American,11/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65035,75216,68127,Probation,crasper,sean,NULL,Male,Caucasian,04/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +65035,75216,68127,Probation,crasper,sean,NULL,Male,Caucasian,04/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +65035,75216,68127,Probation,crasper,sean,NULL,Male,Caucasian,04/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65045,75229,68139,Probation,Charles,Alan,NULL,Male,African-American,04/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +65045,75229,68139,Probation,Charles,Alan,NULL,Male,African-American,04/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +65045,75229,68139,Probation,Charles,Alan,NULL,Male,African-American,04/10/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65027,75208,68119,Probation,HERRERA,CAROLINA,NULL,Female,Hispanic,09/30/84,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +65027,75208,68119,Probation,HERRERA,CAROLINA,NULL,Female,Hispanic,09/30/84,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +65027,75208,68119,Probation,HERRERA,CAROLINA,NULL,Female,Hispanic,09/30/84,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +65034,75215,68126,PRETRIAL,adams,carl,NULL,Male,African-American,07/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +65034,75215,68126,PRETRIAL,adams,carl,NULL,Male,African-American,07/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +65034,75215,68126,PRETRIAL,adams,carl,NULL,Male,African-American,07/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +65024,75206,68117,PRETRIAL,Olaya,David,NULL,Male,Hispanic,02/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +65024,75206,68117,PRETRIAL,Olaya,David,NULL,Male,Hispanic,02/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +65024,75206,68117,PRETRIAL,Olaya,David,NULL,Male,Hispanic,02/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +29319,75231,68141,Probation,brown,kevin,NULL,Male,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +29319,75231,68141,Probation,brown,kevin,NULL,Male,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +29319,75231,68141,Probation,brown,kevin,NULL,Male,African-American,08/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65029,75210,68121,Probation,RODENA,HENRY,NULL,Male,Hispanic,06/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +65029,75210,68121,Probation,RODENA,HENRY,NULL,Male,Hispanic,06/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +65029,75210,68121,Probation,RODENA,HENRY,NULL,Male,Hispanic,06/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56780,75224,68135,PRETRIAL,Manson,Leon,NULL,Male,African-American,11/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +56780,75224,68135,PRETRIAL,Manson,Leon,NULL,Male,African-American,11/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +56780,75224,68135,PRETRIAL,Manson,Leon,NULL,Male,African-American,11/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +65040,75221,68132,PRETRIAL,fair,charmaine,NULL,Female,African-American,12/02/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +65040,75221,68132,PRETRIAL,fair,charmaine,NULL,Female,African-American,12/02/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/14 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,New,1,0 +65040,75221,68132,PRETRIAL,fair,charmaine,NULL,Female,African-American,12/02/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65032,75213,68124,Probation,Butler,Kevin,NULL,Male,African-American,02/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +65032,75213,68124,Probation,Butler,Kevin,NULL,Male,African-American,02/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +65032,75213,68124,Probation,Butler,Kevin,NULL,Male,African-American,02/26/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65037,75218,68129,Probation,SWEETING,SHANEICE,L,Female,African-American,09/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +65037,75218,68129,Probation,SWEETING,SHANEICE,L,Female,African-American,09/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +65037,75218,68129,Probation,SWEETING,SHANEICE,L,Female,African-American,09/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/24/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65021,75203,68114,PRETRIAL,BETANCES,MILKA,NULL,Female,African-American,03/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +65021,75203,68114,PRETRIAL,BETANCES,MILKA,NULL,Female,African-American,03/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +65021,75203,68114,PRETRIAL,BETANCES,MILKA,NULL,Female,African-American,03/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +65023,75205,68116,PRETRIAL,JENSEN,MICHAEL,JAMES- ALAN,Male,Caucasian,11/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +65023,75205,68116,PRETRIAL,JENSEN,MICHAEL,JAMES- ALAN,Male,Caucasian,11/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +65023,75205,68116,PRETRIAL,JENSEN,MICHAEL,JAMES- ALAN,Male,Caucasian,11/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65030,75211,68122,PRETRIAL,Howard,Willie,NULL,Male,African-American,02/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +65030,75211,68122,PRETRIAL,Howard,Willie,NULL,Male,African-American,02/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +65030,75211,68122,PRETRIAL,Howard,Willie,NULL,Male,African-American,02/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/24/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58303,75247,68155,Probation,Kamoo,Mohamed,NULL,Male,Other,07/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +58303,75247,68155,Probation,Kamoo,Mohamed,NULL,Male,Other,07/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +58303,75247,68155,Probation,Kamoo,Mohamed,NULL,Male,Other,07/18/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65051,75239,68148,Probation,BURCH,MARVIN,D,Male,African-American,01/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +65051,75239,68148,Probation,BURCH,MARVIN,D,Male,African-American,01/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,4,High,8,Risk of Recidivism,0.59,9,High,New,1,0 +65051,75239,68148,Probation,BURCH,MARVIN,D,Male,African-American,01/13/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +65075,75263,68170,Probation,RODRIGUEZ,ELIER,PANTOJA,Male,Hispanic,07/28/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,2,Medium,7,Risk of Violence,-1.4,7,Medium,New,1,0 +65075,75263,68170,Probation,RODRIGUEZ,ELIER,PANTOJA,Male,Hispanic,07/28/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +65075,75263,68170,Probation,RODRIGUEZ,ELIER,PANTOJA,Male,Hispanic,07/28/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65054,75242,68151,Probation,ACOSTA-HIDALGO,JAMES,V,Male,Hispanic,09/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +65054,75242,68151,Probation,ACOSTA-HIDALGO,JAMES,V,Male,Hispanic,09/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +65054,75242,68151,Probation,ACOSTA-HIDALGO,JAMES,V,Male,Hispanic,09/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65073,75260,68167,Probation,BRASSENS,CHRISTIAN,Y,Male,African-American,10/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/25/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +65073,75260,68167,Probation,BRASSENS,CHRISTIAN,Y,Male,African-American,10/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +65073,75260,68167,Probation,BRASSENS,CHRISTIAN,Y,Male,African-American,10/28/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,7/25/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65068,75255,68162,Probation,Lubin,Marc,NULL,Male,African-American,04/15/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +65068,75255,68162,Probation,Lubin,Marc,NULL,Male,African-American,04/15/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +65068,75255,68162,Probation,Lubin,Marc,NULL,Male,African-American,04/15/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +40652,75234,68144,PRETRIAL,Flowers,Terry,NULL,Male,African-American,06/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/25/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +40652,75234,68144,PRETRIAL,Flowers,Terry,NULL,Male,African-American,06/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/25/14 0:00,4,High,8,Risk of Recidivism,0.31,9,High,New,1,0 +40652,75234,68144,PRETRIAL,Flowers,Terry,NULL,Male,African-American,06/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/25/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +64685,75245,67742,PRETRIAL,campbell,katie,NULL,Female,Caucasian,07/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,Copy,1,0 +64685,75245,67742,PRETRIAL,campbell,katie,NULL,Female,Caucasian,07/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,Copy,1,0 +64685,75245,67742,PRETRIAL,campbell,katie,NULL,Female,Caucasian,07/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +18851,75236,68146,PRETRIAL,WARREN,JOHN,DAN,Male,Caucasian,09/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/25/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +18851,75236,68146,PRETRIAL,WARREN,JOHN,DAN,Male,Caucasian,09/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +18851,75236,68146,PRETRIAL,WARREN,JOHN,DAN,Male,Caucasian,09/28/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51501,75257,68164,PRETRIAL,Jones,Johnny,NULL,Male,African-Am,10/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.15,4,Low,New,1,0 +51501,75257,68164,PRETRIAL,Jones,Johnny,NULL,Male,African-Am,10/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +51501,75257,68164,PRETRIAL,Jones,Johnny,NULL,Male,African-Am,10/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +65055,75243,68152,Probation,Frederick,Jeffrey,NULL,Male,Caucasian,01/02/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +65055,75243,68152,Probation,Frederick,Jeffrey,NULL,Male,Caucasian,01/02/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +65055,75243,68152,Probation,Frederick,Jeffrey,NULL,Male,Caucasian,01/02/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65059,75250,68158,Probation,EXANTUS,JAMESON,NULL,Male,African-American,11/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +65059,75250,68158,Probation,EXANTUS,JAMESON,NULL,Male,African-American,11/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +65059,75250,68158,Probation,EXANTUS,JAMESON,NULL,Male,African-American,11/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65065,75252,68159,PRETRIAL,NEGRINI,LIANDRA,NULL,Female,Other,06/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +65065,75252,68159,PRETRIAL,NEGRINI,LIANDRA,NULL,Female,Other,06/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +65065,75252,68159,PRETRIAL,NEGRINI,LIANDRA,NULL,Female,Other,06/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64583,75237,67611,PRETRIAL,JEAN-CHARLES,SLOAWN,NULL,Female,African-American,07/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/14 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +64583,75237,67611,PRETRIAL,JEAN-CHARLES,SLOAWN,NULL,Female,African-American,07/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/14 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,Copy,1,0 +64583,75237,67611,PRETRIAL,JEAN-CHARLES,SLOAWN,NULL,Female,African-American,07/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +35243,75244,68153,Probation,POWERS,RAYMOND,CRAIG,Male,Caucasian,06/09/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +35243,75244,68153,Probation,POWERS,RAYMOND,CRAIG,Male,Caucasian,06/09/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +35243,75244,68153,Probation,POWERS,RAYMOND,CRAIG,Male,Caucasian,06/09/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +34830,75251,33995,PRETRIAL,prince,meghan,NULL,Female,African-American,12/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.31,7,Medium,Copy,1,0 +34830,75251,33995,PRETRIAL,prince,meghan,NULL,Female,African-American,12/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,Copy,1,0 +34830,75251,33995,PRETRIAL,prince,meghan,NULL,Female,African-American,12/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +65070,75258,68165,Probation,allan,isaac,NULL,Male,African-American,08/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +65070,75258,68165,Probation,allan,isaac,NULL,Male,African-American,08/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +65070,75258,68165,Probation,allan,isaac,NULL,Male,African-American,08/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65077,75265,68172,Probation,zeidman,elizabeth,NULL,Female,Caucasian,09/08/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/25/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +65077,75265,68172,Probation,zeidman,elizabeth,NULL,Female,Caucasian,09/08/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/25/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +65077,75265,68172,Probation,zeidman,elizabeth,NULL,Female,Caucasian,09/08/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65049,75235,68145,PRETRIAL,Wenkartsteenson,Atlantis,NULL,Female,Caucasian,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.83,5,Medium,New,1,0 +65049,75235,68145,PRETRIAL,Wenkartsteenson,Atlantis,NULL,Female,Caucasian,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +65049,75235,68145,PRETRIAL,Wenkartsteenson,Atlantis,NULL,Female,Caucasian,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65057,75249,68157,Probation,tashman,neil,NULL,Male,Caucasian,12/12/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +65057,75249,68157,Probation,tashman,neil,NULL,Male,Caucasian,12/12/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +65057,75249,68157,Probation,tashman,neil,NULL,Male,Caucasian,12/12/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65066,75253,68160,Probation,Duque,Leeza,NULL,Female,Hispanic,12/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +65066,75253,68160,Probation,Duque,Leeza,NULL,Female,Hispanic,12/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +65066,75253,68160,Probation,Duque,Leeza,NULL,Female,Hispanic,12/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56532,75261,68168,PRETRIAL,Russell,Trevor,NULL,Male,African-American,02/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +56532,75261,68168,PRETRIAL,Russell,Trevor,NULL,Male,African-American,02/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +56532,75261,68168,PRETRIAL,Russell,Trevor,NULL,Male,African-American,02/13/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65074,75262,68169,Probation,Marcusky,Derek,NULL,Male,Caucasian,09/30/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +65074,75262,68169,Probation,Marcusky,Derek,NULL,Male,Caucasian,09/30/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +65074,75262,68169,Probation,Marcusky,Derek,NULL,Male,Caucasian,09/30/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65048,75233,68143,PRETRIAL,Montalvan,Yuvis,Selenia,Female,Hispanic,10/25/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/25/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +65048,75233,68143,PRETRIAL,Montalvan,Yuvis,Selenia,Female,Hispanic,10/25/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/25/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +65048,75233,68143,PRETRIAL,Montalvan,Yuvis,Selenia,Female,Hispanic,10/25/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65052,75240,68149,Probation,Andrews,Keith,NULL,Male,African-American,05/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +65052,75240,68149,Probation,Andrews,Keith,NULL,Male,African-American,05/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +65052,75240,68149,Probation,Andrews,Keith,NULL,Male,African-American,05/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65067,75254,68161,PRETRIAL,Jules,James,NULL,Male,Other,08/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/25/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +65067,75254,68161,PRETRIAL,Jules,James,NULL,Male,Other,08/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/25/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +65067,75254,68161,PRETRIAL,Jules,James,NULL,Male,Other,08/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65069,75256,68163,Probation,solano,carlos,NULL,Male,Hispanic,03/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +65069,75256,68163,Probation,solano,carlos,NULL,Male,Hispanic,03/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +65069,75256,68163,Probation,solano,carlos,NULL,Male,Hispanic,03/03/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65053,75241,68150,Probation,todas,maria,NULL,Female,Asian,11/18/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +65053,75241,68150,Probation,todas,maria,NULL,Female,Asian,11/18/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +65053,75241,68150,Probation,todas,maria,NULL,Female,Asian,11/18/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65056,75246,68154,Probation,Bynum,Christopher,NULL,Male,Caucasian,12/01/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +65056,75246,68154,Probation,Bynum,Christopher,NULL,Male,Caucasian,12/01/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +65056,75246,68154,Probation,Bynum,Christopher,NULL,Male,Caucasian,12/01/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65076,75264,68171,Probation,binns,Kanhai,NULL,Male,African-American,02/29/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +65076,75264,68171,Probation,binns,Kanhai,NULL,Male,African-American,02/29/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +65076,75264,68171,Probation,binns,Kanhai,NULL,Male,African-American,02/29/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65050,75238,68147,PRETRIAL,Grant,Jose,NULL,Male,African-American,10/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +65050,75238,68147,PRETRIAL,Grant,Jose,NULL,Male,African-American,10/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +65050,75238,68147,PRETRIAL,Grant,Jose,NULL,Male,African-American,10/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65072,75259,68166,Probation,ROBINSON,JARED,NULL,Male,Caucasian,05/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +65072,75259,68166,Probation,ROBINSON,JARED,NULL,Male,Caucasian,05/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +65072,75259,68166,Probation,ROBINSON,JARED,NULL,Male,Caucasian,05/22/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65083,75272,68179,PRETRIAL,Moulton,Robert,NULL,Male,Other,09/11/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/26/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +65083,75272,68179,PRETRIAL,Moulton,Robert,NULL,Male,Other,09/11/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/26/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +65083,75272,68179,PRETRIAL,Moulton,Robert,NULL,Male,Other,09/11/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65079,75267,68174,PRETRIAL,Durandisse,Jeremiah,NULL,Male,African-American,04/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +65079,75267,68174,PRETRIAL,Durandisse,Jeremiah,NULL,Male,African-American,04/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +65079,75267,68174,PRETRIAL,Durandisse,Jeremiah,NULL,Male,African-American,04/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65081,75269,68176,PRETRIAL,Izzo,Jason,NULL,Male,Caucasian,09/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +65081,75269,68176,PRETRIAL,Izzo,Jason,NULL,Male,Caucasian,09/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +65081,75269,68176,PRETRIAL,Izzo,Jason,NULL,Male,Caucasian,09/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65082,75270,68177,PRETRIAL,Senra,Andrew,NULL,Male,Caucasian,02/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,2,Medium,7,Risk of Violence,-2.66,2,Low,New,1,0 +65082,75270,68177,PRETRIAL,Senra,Andrew,NULL,Male,Caucasian,02/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +65082,75270,68177,PRETRIAL,Senra,Andrew,NULL,Male,Caucasian,02/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +47155,59124,53716,PRETRIAL,Johnson,Shantae,NULL,Female,African-American,06/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +47155,59124,53716,PRETRIAL,Johnson,Shantae,NULL,Female,African-American,06/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +47155,59124,53716,PRETRIAL,Johnson,Shantae,NULL,Female,African-American,06/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65085,75274,68181,PRETRIAL,Hall,Kemani,NULL,Male,Other,09/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +65085,75274,68181,PRETRIAL,Hall,Kemani,NULL,Male,Other,09/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +65085,75274,68181,PRETRIAL,Hall,Kemani,NULL,Male,Other,09/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65084,75273,68180,PRETRIAL,Ortiz,Gilberto,NULL,Male,Hispanic,09/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +65084,75273,68180,PRETRIAL,Ortiz,Gilberto,NULL,Male,Hispanic,09/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +65084,75273,68180,PRETRIAL,Ortiz,Gilberto,NULL,Male,Hispanic,09/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +54433,75271,68178,PRETRIAL,Christie,Barrington,NULL,Male,Other,03/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/26/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +54433,75271,68178,PRETRIAL,Christie,Barrington,NULL,Male,Other,03/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/26/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +54433,75271,68178,PRETRIAL,Christie,Barrington,NULL,Male,Other,03/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65078,75266,68173,PRETRIAL,Holt,Walter,NULL,Male,Caucasian,11/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +65078,75266,68173,PRETRIAL,Holt,Walter,NULL,Male,Caucasian,11/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +65078,75266,68173,PRETRIAL,Holt,Walter,NULL,Male,Caucasian,11/29/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65080,75268,68175,PRETRIAL,Gibson,Breana,NULL,Female,African-American,02/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +65080,75268,68175,PRETRIAL,Gibson,Breana,NULL,Female,African-American,02/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +65080,75268,68175,PRETRIAL,Gibson,Breana,NULL,Female,African-American,02/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/26/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65086,75276,68182,PRETRIAL,Bostick,Larry,NULL,Male,African-American,01/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,7/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +65086,75276,68182,PRETRIAL,Bostick,Larry,NULL,Male,African-American,01/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,7/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +65086,75276,68182,PRETRIAL,Bostick,Larry,NULL,Male,African-American,01/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,7/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65092,75284,68188,PRETRIAL,BELNAVIS,FORREST,MATTHEW,Male,African-American,11/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/27/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +65092,75284,68188,PRETRIAL,BELNAVIS,FORREST,MATTHEW,Male,African-American,11/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/27/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +65092,75284,68188,PRETRIAL,BELNAVIS,FORREST,MATTHEW,Male,African-American,11/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/27/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +1716,75289,26929,PRETRIAL,HALL,CARRELL,L,Male,African-American,03/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,Copy,1,0 +1716,75289,26929,PRETRIAL,HALL,CARRELL,L,Male,African-American,03/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.76,10,High,Copy,1,0 +1716,75289,26929,PRETRIAL,HALL,CARRELL,L,Male,African-American,03/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +65090,75281,68186,PRETRIAL,IRVING,CHARLES,DONALD,Male,African-American,07/26/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/27/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +65090,75281,68186,PRETRIAL,IRVING,CHARLES,DONALD,Male,African-American,07/26/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/27/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +65090,75281,68186,PRETRIAL,IRVING,CHARLES,DONALD,Male,African-American,07/26/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/27/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65095,75287,68191,PRETRIAL,Gordon,David,NULL,Male,Caucasian,02/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +65095,75287,68191,PRETRIAL,Gordon,David,NULL,Male,Caucasian,02/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +65095,75287,68191,PRETRIAL,Gordon,David,NULL,Male,Caucasian,02/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65088,75278,68184,PRETRIAL,Pedromo-Guzman,Jonathan,NULL,Male,Hispanic,08/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +65088,75278,68184,PRETRIAL,Pedromo-Guzman,Jonathan,NULL,Male,Hispanic,08/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +65088,75278,68184,PRETRIAL,Pedromo-Guzman,Jonathan,NULL,Male,Hispanic,08/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +45817,75280,63021,Probation,young,leandre,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,7/27/14 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,Copy,1,0 +45817,75280,63021,Probation,young,leandre,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,7/27/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,Copy,1,0 +45817,75280,63021,Probation,young,leandre,NULL,Male,African-American,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,7/27/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +65098,75291,68194,PRETRIAL,Kercivil,Andy,NULL,Male,African-American,10/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,4,High,7,Risk of Violence,-0.6,10,High,New,1,0 +65098,75291,68194,PRETRIAL,Kercivil,Andy,NULL,Male,African-American,10/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,4,High,8,Risk of Recidivism,1,10,High,New,1,0 +65098,75291,68194,PRETRIAL,Kercivil,Andy,NULL,Male,African-American,10/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65089,75279,68185,PRETRIAL,Niedda,Jaime,NULL,Male,Caucasian,09/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.9,2,Low,New,1,0 +65089,75279,68185,PRETRIAL,Niedda,Jaime,NULL,Male,Caucasian,09/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +65089,75279,68185,PRETRIAL,Niedda,Jaime,NULL,Male,Caucasian,09/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65094,75286,68190,PRETRIAL,CORTESHUERTAS,NELSO,NULL,Male,Caucasian,10/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +65094,75286,68190,PRETRIAL,CORTESHUERTAS,NELSO,NULL,Male,Caucasian,10/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +65094,75286,68190,PRETRIAL,CORTESHUERTAS,NELSO,NULL,Male,Caucasian,10/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65096,75288,68192,PRETRIAL,Deochoa,Carolina,NULL,Male,Hispanic,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/27/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +65096,75288,68192,PRETRIAL,Deochoa,Carolina,NULL,Male,Hispanic,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/27/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +65096,75288,68192,PRETRIAL,Deochoa,Carolina,NULL,Male,Hispanic,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65087,75277,68183,PRETRIAL,Alexidor,Jean,NULL,Male,Other,04/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/27/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +65087,75277,68183,PRETRIAL,Alexidor,Jean,NULL,Male,Other,04/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/27/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +65087,75277,68183,PRETRIAL,Alexidor,Jean,NULL,Male,Other,04/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/27/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +52044,75282,53300,PRETRIAL,Graf,Lizzette,NULL,Female,Caucasian,12/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/27/14 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,Copy,1,0 +52044,75282,53300,PRETRIAL,Graf,Lizzette,NULL,Female,Caucasian,12/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,Copy,1,0 +52044,75282,53300,PRETRIAL,Graf,Lizzette,NULL,Female,Caucasian,12/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/27/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +65091,75283,68187,PRETRIAL,HAMPSHIRE,DONALD,EDWARD,Male,Caucasian,12/30/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/27/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +65091,75283,68187,PRETRIAL,HAMPSHIRE,DONALD,EDWARD,Male,Caucasian,12/30/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/27/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +65091,75283,68187,PRETRIAL,HAMPSHIRE,DONALD,EDWARD,Male,Caucasian,12/30/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65097,75290,68193,PRETRIAL,Melendez,Mario,NULL,Male,Caucasian,11/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +65097,75290,68193,PRETRIAL,Melendez,Mario,NULL,Male,Caucasian,11/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +65097,75290,68193,PRETRIAL,Melendez,Mario,NULL,Male,Caucasian,11/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65093,75285,68189,PRETRIAL,Woods,Michael,NULL,Male,African-American,07/16/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.35,3,Low,New,1,0 +65093,75285,68189,PRETRIAL,Woods,Michael,NULL,Male,African-American,07/16/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +65093,75285,68189,PRETRIAL,Woods,Michael,NULL,Male,African-American,07/16/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65143,75335,68235,Probation,Gabriel,Patrick,NULL,Male,Caucasian,08/28/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-4.27,1,Low,New,1,0 +65143,75335,68235,Probation,Gabriel,Patrick,NULL,Male,Caucasian,08/28/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +65143,75335,68235,Probation,Gabriel,Patrick,NULL,Male,Caucasian,08/28/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65125,75314,68215,PRETRIAL,Suazo,Jose,NULL,Male,Hispanic,05/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/28/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +65125,75314,68215,PRETRIAL,Suazo,Jose,NULL,Male,Hispanic,05/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/28/14 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +65125,75314,68215,PRETRIAL,Suazo,Jose,NULL,Male,Hispanic,05/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65118,75306,68208,PRETRIAL,Kilensky,Darlene,Anne,Female,Caucasian,09/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +65118,75306,68208,PRETRIAL,Kilensky,Darlene,Anne,Female,Caucasian,09/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +65118,75306,68208,PRETRIAL,Kilensky,Darlene,Anne,Female,Caucasian,09/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65129,75319,68220,Probation,Gaudin,Gilbert,NULL,Male,African-American,07/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/28/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +65129,75319,68220,Probation,Gaudin,Gilbert,NULL,Male,African-American,07/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +65129,75319,68220,Probation,Gaudin,Gilbert,NULL,Male,African-American,07/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65136,75327,68227,Probation,saintilus,ralph,NULL,Male,African-American,07/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +65136,75327,68227,Probation,saintilus,ralph,NULL,Male,African-American,07/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +65136,75327,68227,Probation,saintilus,ralph,NULL,Male,African-American,07/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65112,75298,68201,PRETRIAL,Battiste,Joseph,NULL,Male,African-American,09/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +65112,75298,68201,PRETRIAL,Battiste,Joseph,NULL,Male,African-American,09/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +65112,75298,68201,PRETRIAL,Battiste,Joseph,NULL,Male,African-American,09/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65123,75311,68212,Probation,Klippenstein,Denise,NULL,Female,African-American,11/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/28/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +65123,75311,68212,Probation,Klippenstein,Denise,NULL,Female,African-American,11/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +65123,75311,68212,Probation,Klippenstein,Denise,NULL,Female,African-American,11/17/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65116,75303,68206,PRETRIAL,ROCHA,PABLO,G,Male,Caucasian,05/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +65116,75303,68206,PRETRIAL,ROCHA,PABLO,G,Male,Caucasian,05/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,4,High,8,Risk of Recidivism,1.09,10,High,New,1,0 +65116,75303,68206,PRETRIAL,ROCHA,PABLO,G,Male,Caucasian,05/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65119,75307,68209,PRETRIAL,Larretaflores,Alex,NULL,Male,Hispanic,01/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +65119,75307,68209,PRETRIAL,Larretaflores,Alex,NULL,Male,Hispanic,01/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +65119,75307,68209,PRETRIAL,Larretaflores,Alex,NULL,Male,Hispanic,01/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65120,75309,68210,Probation,Benson,Kenwyn,NULL,Male,African-American,09/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,2,Medium,7,Risk of Violence,-2.47,3,Low,New,1,0 +65120,75309,68210,Probation,Benson,Kenwyn,NULL,Male,African-American,09/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +65120,75309,68210,Probation,Benson,Kenwyn,NULL,Male,African-American,09/06/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65127,75316,68217,PRETRIAL,Nanchernandez,Eutiquo,NULL,Male,Hispanic,12/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/28/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +65127,75316,68217,PRETRIAL,Nanchernandez,Eutiquo,NULL,Male,Hispanic,12/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +65127,75316,68217,PRETRIAL,Nanchernandez,Eutiquo,NULL,Male,Hispanic,12/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65139,75330,68230,PRETRIAL,Redfern,Michael,NULL,Male,Caucasian,04/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +65139,75330,68230,PRETRIAL,Redfern,Michael,NULL,Male,Caucasian,04/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +65139,75330,68230,PRETRIAL,Redfern,Michael,NULL,Male,Caucasian,04/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65113,75300,68203,PRETRIAL,Mansfield,Kabrecia,Nicole,Female,African-American,08/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +65113,75300,68203,PRETRIAL,Mansfield,Kabrecia,Nicole,Female,African-American,08/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +65113,75300,68203,PRETRIAL,Mansfield,Kabrecia,Nicole,Female,African-American,08/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65134,75325,68225,PRETRIAL,Gannon,Maik,J,Male,Caucasian,06/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +65134,75325,68225,PRETRIAL,Gannon,Maik,J,Male,Caucasian,06/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +65134,75325,68225,PRETRIAL,Gannon,Maik,J,Male,Caucasian,06/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +5033,75304,4715,PRETRIAL,MARTINEZ,JOE,NULL,Male,Hispanic,02/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/28/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,Copy,1,0 +5033,75304,4715,PRETRIAL,MARTINEZ,JOE,NULL,Male,Hispanic,02/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/28/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,Copy,1,0 +5033,75304,4715,PRETRIAL,MARTINEZ,JOE,NULL,Male,Hispanic,02/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +65131,75321,68222,PRETRIAL,ORELLANA,KARLA,NULL,Female,Hispanic,08/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/28/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +65131,75321,68222,PRETRIAL,ORELLANA,KARLA,NULL,Female,Hispanic,08/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +65131,75321,68222,PRETRIAL,ORELLANA,KARLA,NULL,Female,Hispanic,08/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65100,75294,68197,PRETRIAL,Hightower,Brianna,NULL,Female,African-American,02/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +65100,75294,68197,PRETRIAL,Hightower,Brianna,NULL,Female,African-American,02/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +65100,75294,68197,PRETRIAL,Hightower,Brianna,NULL,Female,African-American,02/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65138,75329,68229,Probation,Depompa,Marco,NULL,Male,Caucasian,07/10/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/28/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +65138,75329,68229,Probation,Depompa,Marco,NULL,Male,Caucasian,07/10/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +65138,75329,68229,Probation,Depompa,Marco,NULL,Male,Caucasian,07/10/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65114,75301,68204,PRETRIAL,SMITH,DENISHA,L,Female,African-American,04/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,4,High,7,Risk of Violence,-0.7,9,High,New,1,0 +65114,75301,68204,PRETRIAL,SMITH,DENISHA,L,Female,African-American,04/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,4,High,8,Risk of Recidivism,1.26,10,High,New,1,0 +65114,75301,68204,PRETRIAL,SMITH,DENISHA,L,Female,African-American,04/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,4,High,18,Risk of Failure to Appear,20,4,Low,New,1,0 +62532,75308,65248,Probation,Shawn,Ball,NULL,Male,Caucasian,10/29/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,Copy,1,0 +62532,75308,65248,Probation,Shawn,Ball,NULL,Male,Caucasian,10/29/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +62532,75308,65248,Probation,Shawn,Ball,NULL,Male,Caucasian,10/29/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +65126,75315,68216,Probation,joachim,jesse,NULL,Male,African-American,07/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +65126,75315,68216,Probation,joachim,jesse,NULL,Male,African-American,07/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +65126,75315,68216,Probation,joachim,jesse,NULL,Male,African-American,07/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61242,75322,63775,PRETRIAL,Farquharson,Alvin,NULL,Male,African-American,09/21/59,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +61242,75322,63775,PRETRIAL,Farquharson,Alvin,NULL,Male,African-American,09/21/59,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +61242,75322,63775,PRETRIAL,Farquharson,Alvin,NULL,Male,African-American,09/21/59,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65110,75296,68199,PRETRIAL,Baptiste,MarcJosue,Philipe,Male,African-American,11/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-1.76,5,Medium,New,1,0 +65110,75296,68199,PRETRIAL,Baptiste,MarcJosue,Philipe,Male,African-American,11/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +65110,75296,68199,PRETRIAL,Baptiste,MarcJosue,Philipe,Male,African-American,11/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65099,75292,68195,PRETRIAL,Prosper,Shelder,NULL,Female,African-American,04/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +65099,75292,68195,PRETRIAL,Prosper,Shelder,NULL,Female,African-American,04/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +65099,75292,68195,PRETRIAL,Prosper,Shelder,NULL,Female,African-American,04/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +44613,75299,68202,PRETRIAL,Orys,Jeffrey,NULL,Male,African-American,05/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,4,High,7,Risk of Violence,-0.95,9,High,New,1,0 +44613,75299,68202,PRETRIAL,Orys,Jeffrey,NULL,Male,African-American,05/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +44613,75299,68202,PRETRIAL,Orys,Jeffrey,NULL,Male,African-American,05/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65142,75334,68234,Probation,Battaglia,John,Anthony,Male,Caucasian,01/23/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/28/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +65142,75334,68234,Probation,Battaglia,John,Anthony,Male,Caucasian,01/23/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +65142,75334,68234,Probation,Battaglia,John,Anthony,Male,Caucasian,01/23/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65140,75331,68231,Probation,Jeanbaptiste,Jimsrully,NULL,Male,African-American,11/29/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +65140,75331,68231,Probation,Jeanbaptiste,Jimsrully,NULL,Male,African-American,11/29/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +65140,75331,68231,Probation,Jeanbaptiste,Jimsrully,NULL,Male,African-American,11/29/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65122,75310,68211,Probation,miniel,yalitza,NULL,Female,Hispanic,03/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +65122,75310,68211,Probation,miniel,yalitza,NULL,Female,Hispanic,03/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.33,7,Medium,New,1,0 +65122,75310,68211,Probation,miniel,yalitza,NULL,Female,Hispanic,03/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65132,75323,68223,Probation,Guerrero,Ana,Cristina,Female,Hispanic,07/26/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +65132,75323,68223,Probation,Guerrero,Ana,Cristina,Female,Hispanic,07/26/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +65132,75323,68223,Probation,Guerrero,Ana,Cristina,Female,Hispanic,07/26/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +26214,75336,68236,PRETRIAL,Moore,Dana,NULL,Male,African-American,01/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.31,3,Low,New,1,0 +26214,75336,68236,PRETRIAL,Moore,Dana,NULL,Male,African-American,01/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +26214,75336,68236,PRETRIAL,Moore,Dana,NULL,Male,African-American,01/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65115,75302,68205,PRETRIAL,LOVETT,JERMAINE,NULL,Male,African-American,05/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +65115,75302,68205,PRETRIAL,LOVETT,JERMAINE,NULL,Male,African-American,05/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.71,10,High,New,1,0 +65115,75302,68205,PRETRIAL,LOVETT,JERMAINE,NULL,Male,African-American,05/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +65128,75318,68219,PRETRIAL,Hyde,Marlon,NULL,Male,African-American,03/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/28/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +65128,75318,68219,PRETRIAL,Hyde,Marlon,NULL,Male,African-American,03/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +65128,75318,68219,PRETRIAL,Hyde,Marlon,NULL,Male,African-American,03/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65117,75305,68207,PRETRIAL,Diaz,Mayelin,NULL,Female,Hispanic,05/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/28/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +65117,75305,68207,PRETRIAL,Diaz,Mayelin,NULL,Female,Hispanic,05/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +65117,75305,68207,PRETRIAL,Diaz,Mayelin,NULL,Female,Hispanic,05/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65130,75320,68221,PRETRIAL,SMITH,ANTHONY,NULL,Male,Caucasian,02/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/28/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +65130,75320,68221,PRETRIAL,SMITH,ANTHONY,NULL,Male,Caucasian,02/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/28/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +65130,75320,68221,PRETRIAL,SMITH,ANTHONY,NULL,Male,Caucasian,02/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65135,75326,68226,Probation,McBride,chanzel,NULL,Male,African-American,05/22/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/28/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +65135,75326,68226,Probation,McBride,chanzel,NULL,Male,African-American,05/22/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/28/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +65135,75326,68226,Probation,McBride,chanzel,NULL,Male,African-American,05/22/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57914,75333,68233,PRETRIAL,Cadet,Marie,NULL,Female,African-American,02/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +57914,75333,68233,PRETRIAL,Cadet,Marie,NULL,Female,African-American,02/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +57914,75333,68233,PRETRIAL,Cadet,Marie,NULL,Female,African-American,02/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/28/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65111,75297,68200,PRETRIAL,EDWARD,RICHARD,WILSON,Female,African-American,10/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/28/14 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +65111,75297,68200,PRETRIAL,EDWARD,RICHARD,WILSON,Female,African-American,10/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +65111,75297,68200,PRETRIAL,EDWARD,RICHARD,WILSON,Female,African-American,10/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/28/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65151,75347,68245,PRETRIAL,Vega,Javier,NULL,Male,African-American,02/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +65151,75347,68245,PRETRIAL,Vega,Javier,NULL,Male,African-American,02/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +65151,75347,68245,PRETRIAL,Vega,Javier,NULL,Male,African-American,02/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +45761,75339,68239,PRETRIAL,Juan,Rojas-Soto,Felipe,Male,Hispanic,12/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +45761,75339,68239,PRETRIAL,Juan,Rojas-Soto,Felipe,Male,Hispanic,12/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +45761,75339,68239,PRETRIAL,Juan,Rojas-Soto,Felipe,Male,Hispanic,12/11/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65171,75354,68250,PRETRIAL,Jones,Allana,NULL,Female,African-American,03/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +65171,75354,68250,PRETRIAL,Jones,Allana,NULL,Female,African-American,03/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +65171,75354,68250,PRETRIAL,Jones,Allana,NULL,Female,African-American,03/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +65147,75341,68241,PRETRIAL,CROSSMAN,THERESA,ANN,Female,Caucasian,01/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/29/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +65147,75341,68241,PRETRIAL,CROSSMAN,THERESA,ANN,Female,Caucasian,01/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +65147,75341,68241,PRETRIAL,CROSSMAN,THERESA,ANN,Female,Caucasian,01/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +54909,75375,66671,PRETRIAL,Young,Rudolph,NULL,Male,African-American,01/02/55,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,7/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.5,3,Low,New,1,0 +54909,75375,66671,PRETRIAL,Young,Rudolph,NULL,Male,African-American,01/02/55,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,7/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +54909,75375,66671,PRETRIAL,Young,Rudolph,NULL,Male,African-American,01/02/55,17,All Scales,Intake,English,Conditional Release,Probation,Divorced,7/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,9,High,New,1,0 +65174,75357,68253,PRETRIAL,GRIFFITH,JORDAN,ALEXIS,Female,Caucasian,12/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +65174,75357,68253,PRETRIAL,GRIFFITH,JORDAN,ALEXIS,Female,Caucasian,12/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +65174,75357,68253,PRETRIAL,GRIFFITH,JORDAN,ALEXIS,Female,Caucasian,12/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65184,75370,68265,Probation,sutherland,Bruce,NULL,Male,Caucasian,11/01/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/29/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +65184,75370,68265,Probation,sutherland,Bruce,NULL,Male,Caucasian,11/01/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +65184,75370,68265,Probation,sutherland,Bruce,NULL,Male,Caucasian,11/01/61,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65153,75349,68247,PRETRIAL,Roberts,Frank,NULL,Male,African-American,07/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +65153,75349,68247,PRETRIAL,Roberts,Frank,NULL,Male,African-American,07/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +65153,75349,68247,PRETRIAL,Roberts,Frank,NULL,Male,African-American,07/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65182,75368,68263,PRETRIAL,Davis,Sharon,NULL,Female,African-American,09/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/29/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +65182,75368,68263,PRETRIAL,Davis,Sharon,NULL,Female,African-American,09/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/29/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +65182,75368,68263,PRETRIAL,Davis,Sharon,NULL,Female,African-American,09/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65145,75338,68238,PRETRIAL,Brooks,Jalicia,M,Female,African-American,06/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +65145,75338,68238,PRETRIAL,Brooks,Jalicia,M,Female,African-American,06/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,8,High,New,1,0 +65145,75338,68238,PRETRIAL,Brooks,Jalicia,M,Female,African-American,06/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65172,75355,68251,PRETRIAL,BONHOMME,EDSON,NULL,Male,African-American,01/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +65172,75355,68251,PRETRIAL,BONHOMME,EDSON,NULL,Male,African-American,01/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +65172,75355,68251,PRETRIAL,BONHOMME,EDSON,NULL,Male,African-American,01/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65179,75364,68259,Probation,Vazquez,erika,NULL,Female,Hispanic,05/09/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/29/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +65179,75364,68259,Probation,Vazquez,erika,NULL,Female,Hispanic,05/09/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.62,2,Low,New,1,0 +65179,75364,68259,Probation,Vazquez,erika,NULL,Female,Hispanic,05/09/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65185,75371,68266,Probation,STONE,ASHLEY,NULL,Female,Caucasian,03/26/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,2,Medium,7,Risk of Violence,-2.78,2,Low,New,1,0 +65185,75371,68266,Probation,STONE,ASHLEY,NULL,Female,Caucasian,03/26/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +65185,75371,68266,Probation,STONE,ASHLEY,NULL,Female,Caucasian,03/26/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65187,75373,68268,PRETRIAL,MCKINNEY,ISAIAH,NULL,Male,African-American,07/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.1,8,High,New,1,0 +65187,75373,68268,PRETRIAL,MCKINNEY,ISAIAH,NULL,Male,African-American,07/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +65187,75373,68268,PRETRIAL,MCKINNEY,ISAIAH,NULL,Male,African-American,07/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +874,75343,567,PRETRIAL,Nichols,Dyan,Bronstein,Female,Caucasian,06/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/29/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,Copy,1,0 +874,75343,567,PRETRIAL,Nichols,Dyan,Bronstein,Female,Caucasian,06/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,Copy,1,0 +874,75343,567,PRETRIAL,Nichols,Dyan,Bronstein,Female,Caucasian,06/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +3876,3837,3593,PRETRIAL,RANDALL,FERONDO,L,Male,African-American,07/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,7/29/14 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +3876,3837,3593,PRETRIAL,RANDALL,FERONDO,L,Male,African-American,07/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,7/29/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +3876,3837,3593,PRETRIAL,RANDALL,FERONDO,L,Male,African-American,07/23/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,7/29/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +65186,75372,68267,Probation,black,adrian,NULL,Male,African-American,01/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +65186,75372,68267,Probation,black,adrian,NULL,Male,African-American,01/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +65186,75372,68267,Probation,black,adrian,NULL,Male,African-American,01/27/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65148,75342,68242,PRETRIAL,Gaskins,Mark,Allen,Male,African-American,01/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +65148,75342,68242,PRETRIAL,Gaskins,Mark,Allen,Male,African-American,01/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +65148,75342,68242,PRETRIAL,Gaskins,Mark,Allen,Male,African-American,01/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65176,75360,68256,PRETRIAL,Robrish,Jonathan,Daniel,Male,Caucasian,04/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +65176,75360,68256,PRETRIAL,Robrish,Jonathan,Daniel,Male,Caucasian,04/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +65176,75360,68256,PRETRIAL,Robrish,Jonathan,Daniel,Male,Caucasian,04/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65181,75367,68262,Probation,earle,johnathan,NULL,Male,Caucasian,06/06/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +65181,75367,68262,Probation,earle,johnathan,NULL,Male,Caucasian,06/06/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +65181,75367,68262,Probation,earle,johnathan,NULL,Male,Caucasian,06/06/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65150,75346,68244,PRETRIAL,Barias,Ariel,Nephtaly,Male,African-American,10/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +65150,75346,68244,PRETRIAL,Barias,Ariel,Nephtaly,Male,African-American,10/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +65150,75346,68244,PRETRIAL,Barias,Ariel,Nephtaly,Male,African-American,10/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65178,75363,68258,Probation,bennett,michael,NULL,Male,Caucasian,01/03/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +65178,75363,68258,Probation,bennett,michael,NULL,Male,Caucasian,01/03/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +65178,75363,68258,Probation,bennett,michael,NULL,Male,Caucasian,01/03/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65149,75344,68243,PRETRIAL,CHILDS,JENCHELLE,NULL,Female,African-American,04/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/29/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +65149,75344,68243,PRETRIAL,CHILDS,JENCHELLE,NULL,Female,African-American,04/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +65149,75344,68243,PRETRIAL,CHILDS,JENCHELLE,NULL,Female,African-American,04/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65154,75351,68249,PRETRIAL,SIMMONS,KYLEE,NULL,Female,Caucasian,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +65154,75351,68249,PRETRIAL,SIMMONS,KYLEE,NULL,Female,Caucasian,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +65154,75351,68249,PRETRIAL,SIMMONS,KYLEE,NULL,Female,Caucasian,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +3467,75358,68254,PRETRIAL,jackson,jermaine,NULL,Male,African-American,06/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +3467,75358,68254,PRETRIAL,jackson,jermaine,NULL,Male,African-American,06/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +3467,75358,68254,PRETRIAL,jackson,jermaine,NULL,Male,African-American,06/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65180,75365,68260,PRETRIAL,ASAD,ISSA,NULL,Male,Caucasian,03/04/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +65180,75365,68260,PRETRIAL,ASAD,ISSA,NULL,Male,Caucasian,03/04/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +65180,75365,68260,PRETRIAL,ASAD,ISSA,NULL,Male,Caucasian,03/04/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65173,75356,68252,Probation,Salas,Jose,NULL,Male,Hispanic,04/10/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/29/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +65173,75356,68252,Probation,Salas,Jose,NULL,Male,Hispanic,04/10/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +65173,75356,68252,Probation,Salas,Jose,NULL,Male,Hispanic,04/10/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65152,75348,68246,PRETRIAL,Thomas,Stacey,Deshawn,Female,Other,02/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +65152,75348,68246,PRETRIAL,Thomas,Stacey,Deshawn,Female,Other,02/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +65152,75348,68246,PRETRIAL,Thomas,Stacey,Deshawn,Female,Other,02/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60778,75361,63254,Probation,hellmuth,robert,NULL,Male,Caucasian,04/02/78,17,All Scales,Intake,English,Conditional Release,Probation,Married,7/29/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +60778,75361,63254,Probation,hellmuth,robert,NULL,Male,Caucasian,04/02/78,17,All Scales,Intake,English,Conditional Release,Probation,Married,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +60778,75361,63254,Probation,hellmuth,robert,NULL,Male,Caucasian,04/02/78,17,All Scales,Intake,English,Conditional Release,Probation,Married,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,22,4,Low,New,1,0 +65146,75340,68240,PRETRIAL,LOUIS,JARYAM,LORIE,Female,African-American,06/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +65146,75340,68240,PRETRIAL,LOUIS,JARYAM,LORIE,Female,African-American,06/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +65146,75340,68240,PRETRIAL,LOUIS,JARYAM,LORIE,Female,African-American,06/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65183,75369,68264,PRETRIAL,Gardner,Marlon,Antwane,Male,African-American,05/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +65183,75369,68264,PRETRIAL,Gardner,Marlon,Antwane,Male,African-American,05/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +65183,75369,68264,PRETRIAL,Gardner,Marlon,Antwane,Male,African-American,05/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65189,75376,68270,Probation,Peralta,Maria,NULL,Female,Hispanic,06/30/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/29/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +65189,75376,68270,Probation,Peralta,Maria,NULL,Female,Hispanic,06/30/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +65189,75376,68270,Probation,Peralta,Maria,NULL,Female,Hispanic,06/30/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51323,75345,52506,PRETRIAL,Brooks,Luke,NULL,Male,African-American,11/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,7,Risk of Violence,-1.77,5,Medium,Copy,1,0 +51323,75345,52506,PRETRIAL,Brooks,Luke,NULL,Male,African-American,11/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +51323,75345,52506,PRETRIAL,Brooks,Luke,NULL,Male,African-American,11/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +65188,75374,68269,Probation,feliciano,christopher,NULL,Male,Hispanic,07/27/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +65188,75374,68269,Probation,feliciano,christopher,NULL,Male,Hispanic,07/27/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +65188,75374,68269,Probation,feliciano,christopher,NULL,Male,Hispanic,07/27/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +42375,75392,68285,PRETRIAL,ALI,RYAN,NULL,Male,African-American,07/26/85,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,7/30/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +42375,75392,68285,PRETRIAL,ALI,RYAN,NULL,Male,African-American,07/26/85,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,7/30/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +42375,75392,68285,PRETRIAL,ALI,RYAN,NULL,Male,African-American,07/26/85,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,7/30/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65204,75395,68287,Probation,lebron,linda,NULL,Female,African-American,03/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +65204,75395,68287,Probation,lebron,linda,NULL,Female,African-American,03/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +65204,75395,68287,Probation,lebron,linda,NULL,Female,African-American,03/28/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65229,75413,68305,PRETRIAL,WINT,JEVAUGHN,NULL,Male,African-American,06/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +65229,75413,68305,PRETRIAL,WINT,JEVAUGHN,NULL,Male,African-American,06/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +65229,75413,68305,PRETRIAL,WINT,JEVAUGHN,NULL,Male,African-American,06/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65218,75400,68292,Probation,amazouz,laila,NULL,Female,Caucasian,07/29/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/30/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +65218,75400,68292,Probation,amazouz,laila,NULL,Female,Caucasian,07/29/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +65218,75400,68292,Probation,amazouz,laila,NULL,Female,Caucasian,07/29/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65198,75387,68280,PRETRIAL,Degeorge,Jennie,NULL,Female,Caucasian,07/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/30/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +65198,75387,68280,PRETRIAL,Degeorge,Jennie,NULL,Female,Caucasian,07/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +65198,75387,68280,PRETRIAL,Degeorge,Jennie,NULL,Female,Caucasian,07/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65201,75390,68283,Probation,Lynch,Danielle,NULL,Female,African-American,02/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +65201,75390,68283,Probation,Lynch,Danielle,NULL,Female,African-American,02/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,8,High,New,1,0 +65201,75390,68283,Probation,Lynch,Danielle,NULL,Female,African-American,02/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65216,75397,68289,Probation,Roopchan,Shane,NULL,Male,Asian,04/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +65216,75397,68289,Probation,Roopchan,Shane,NULL,Male,Asian,04/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +65216,75397,68289,Probation,Roopchan,Shane,NULL,Male,Asian,04/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65217,75398,68290,PRETRIAL,Pershadsingh,Jamila,NULL,Female,Caucasian,09/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/30/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +65217,75398,68290,PRETRIAL,Pershadsingh,Jamila,NULL,Female,Caucasian,09/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +65217,75398,68290,PRETRIAL,Pershadsingh,Jamila,NULL,Female,Caucasian,09/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65222,75403,68295,PRETRIAL,Posada,Erik,NULL,Male,Caucasian,10/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +65222,75403,68295,PRETRIAL,Posada,Erik,NULL,Male,Caucasian,10/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +65222,75403,68295,PRETRIAL,Posada,Erik,NULL,Male,Caucasian,10/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65223,75405,68297,Probation,Gabriel,Antoine,NULL,Male,African-American,12/05/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/30/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +65223,75405,68297,Probation,Gabriel,Antoine,NULL,Male,African-American,12/05/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +65223,75405,68297,Probation,Gabriel,Antoine,NULL,Male,African-American,12/05/73,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65190,75377,68271,PRETRIAL,Daniels,Jeremy,NULL,Male,African-American,10/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +65190,75377,68271,PRETRIAL,Daniels,Jeremy,NULL,Male,African-American,10/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +65190,75377,68271,PRETRIAL,Daniels,Jeremy,NULL,Male,African-American,10/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65195,75382,68276,PRETRIAL,Bonbon,Ketteline,NULL,Female,African-American,02/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +65195,75382,68276,PRETRIAL,Bonbon,Ketteline,NULL,Female,African-American,02/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +65195,75382,68276,PRETRIAL,Bonbon,Ketteline,NULL,Female,African-American,02/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52388,75384,53683,Probation,spain,lashondra,NULL,Female,African-American,09/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.37,3,Low,Copy,1,0 +52388,75384,53683,Probation,spain,lashondra,NULL,Female,African-American,09/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,8,High,Copy,1,0 +52388,75384,53683,Probation,spain,lashondra,NULL,Female,African-American,09/25/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +65192,75379,68273,PRETRIAL,Tillman,Storm,NULL,Male,African-American,04/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +65192,75379,68273,PRETRIAL,Tillman,Storm,NULL,Male,African-American,04/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +65192,75379,68273,PRETRIAL,Tillman,Storm,NULL,Male,African-American,04/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65224,75407,68299,Probation,steller,stephanie,NULL,Female,Caucasian,12/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +65224,75407,68299,Probation,steller,stephanie,NULL,Female,Caucasian,12/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,4,High,8,Risk of Recidivism,0.8,10,High,New,1,0 +65224,75407,68299,Probation,steller,stephanie,NULL,Female,Caucasian,12/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65226,75409,68301,PRETRIAL,Smith,Eric,NULL,Male,Caucasian,11/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,7/30/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +65226,75409,68301,PRETRIAL,Smith,Eric,NULL,Male,Caucasian,11/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,7/30/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +65226,75409,68301,PRETRIAL,Smith,Eric,NULL,Male,Caucasian,11/01/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +65197,75386,68279,PRETRIAL,Bailey,Omar,NULL,Male,African-American,01/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +65197,75386,68279,PRETRIAL,Bailey,Omar,NULL,Male,African-American,01/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +65197,75386,68279,PRETRIAL,Bailey,Omar,NULL,Male,African-American,01/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65199,75388,68281,PRETRIAL,Evans,Tavaris,NULL,Male,African-American,01/20/98,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.99,9,High,New,1,0 +65199,75388,68281,PRETRIAL,Evans,Tavaris,NULL,Male,African-American,01/20/98,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +65199,75388,68281,PRETRIAL,Evans,Tavaris,NULL,Male,African-American,01/20/98,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65194,75381,68275,PRETRIAL,WILLIAMS,JIMMY,VINE,Male,Caucasian,12/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.71,2,Low,New,1,0 +65194,75381,68275,PRETRIAL,WILLIAMS,JIMMY,VINE,Male,Caucasian,12/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +65194,75381,68275,PRETRIAL,WILLIAMS,JIMMY,VINE,Male,Caucasian,12/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64915,75414,67992,PRETRIAL,HECTOR,LUCRETA,NULL,Female,African-American,02/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,Copy,1,0 +64915,75414,67992,PRETRIAL,HECTOR,LUCRETA,NULL,Female,African-American,02/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,Copy,1,0 +64915,75414,67992,PRETRIAL,HECTOR,LUCRETA,NULL,Female,African-American,02/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +65221,75402,68294,PRETRIAL,Graham,Jeremiah,NULL,Male,African-American,03/29/98,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,4,High,7,Risk of Violence,-0.53,10,High,New,1,0 +65221,75402,68294,PRETRIAL,Graham,Jeremiah,NULL,Male,African-American,03/29/98,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +65221,75402,68294,PRETRIAL,Graham,Jeremiah,NULL,Male,African-American,03/29/98,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +63679,75394,66600,PRETRIAL,Ussa,Andres,NULL,Male,Hispanic,04/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,Copy,1,0 +63679,75394,66600,PRETRIAL,Ussa,Andres,NULL,Male,Hispanic,04/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,Copy,1,0 +63679,75394,66600,PRETRIAL,Ussa,Andres,NULL,Male,Hispanic,04/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +65220,75401,68293,PRETRIAL,Basdeo,jason,NULL,Male,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/30/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +65220,75401,68293,PRETRIAL,Basdeo,jason,NULL,Male,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/30/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +65220,75401,68293,PRETRIAL,Basdeo,jason,NULL,Male,African-American,07/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65193,75380,68274,PRETRIAL,Payne,James,Cody,Male,Caucasian,05/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +65193,75380,68274,PRETRIAL,Payne,James,Cody,Male,Caucasian,05/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +65193,75380,68274,PRETRIAL,Payne,James,Cody,Male,Caucasian,05/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30716,75385,68278,PRETRIAL,KOONS,MICHAEL,NULL,Male,Caucasian,08/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +30716,75385,68278,PRETRIAL,KOONS,MICHAEL,NULL,Male,Caucasian,08/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +30716,75385,68278,PRETRIAL,KOONS,MICHAEL,NULL,Male,Caucasian,08/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +65227,75410,68302,PRETRIAL,Mueller,Kimberly,Ann,Female,Caucasian,02/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/30/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +65227,75410,68302,PRETRIAL,Mueller,Kimberly,Ann,Female,Caucasian,02/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +65227,75410,68302,PRETRIAL,Mueller,Kimberly,Ann,Female,Caucasian,02/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65200,75389,68282,Probation,Orellana,Carlos,Orlando,Male,Hispanic,06/10/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/30/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +65200,75389,68282,Probation,Orellana,Carlos,Orlando,Male,Hispanic,06/10/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +65200,75389,68282,Probation,Orellana,Carlos,Orlando,Male,Hispanic,06/10/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44625,75406,68298,PRETRIAL,Martinez,Joseph,M,Male,Hispanic,01/29/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/30/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +44625,75406,68298,PRETRIAL,Martinez,Joseph,M,Male,Hispanic,01/29/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +44625,75406,68298,PRETRIAL,Martinez,Joseph,M,Male,Hispanic,01/29/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65219,75399,68291,PRETRIAL,Simeon,Esperant,NULL,Male,African-American,07/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/30/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +65219,75399,68291,PRETRIAL,Simeon,Esperant,NULL,Male,African-American,07/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/30/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +65219,75399,68291,PRETRIAL,Simeon,Esperant,NULL,Male,African-American,07/04/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65191,75378,68272,PRETRIAL,Dames,Josie,Spurgeon,Male,Other,01/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +65191,75378,68272,PRETRIAL,Dames,Josie,Spurgeon,Male,Other,01/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +65191,75378,68272,PRETRIAL,Dames,Josie,Spurgeon,Male,Other,01/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60457,75396,68288,Probation,SANTA,JARET,NULL,Male,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +60457,75396,68288,Probation,SANTA,JARET,NULL,Male,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +60457,75396,68288,Probation,SANTA,JARET,NULL,Male,Caucasian,03/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +14833,75404,68296,PRETRIAL,JONES,RICKY,NULL,Male,African-American,08/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +14833,75404,68296,PRETRIAL,JONES,RICKY,NULL,Male,African-American,08/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,4,High,8,Risk of Recidivism,0.45,9,High,New,1,0 +14833,75404,68296,PRETRIAL,JONES,RICKY,NULL,Male,African-American,08/31/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/30/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65202,75391,68284,PRETRIAL,Payne,Jesse,NULL,Male,Caucasian,06/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +65202,75391,68284,PRETRIAL,Payne,Jesse,NULL,Male,Caucasian,06/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +65202,75391,68284,PRETRIAL,Payne,Jesse,NULL,Male,Caucasian,06/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65228,75412,68304,PRETRIAL,Scarfo,Richard,NULL,Male,Caucasian,02/09/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +65228,75412,68304,PRETRIAL,Scarfo,Richard,NULL,Male,Caucasian,02/09/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +65228,75412,68304,PRETRIAL,Scarfo,Richard,NULL,Male,Caucasian,02/09/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +65196,75383,68277,PRETRIAL,MARTINEZ,JORGE,DANIEL,Male,Caucasian,05/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +65196,75383,68277,PRETRIAL,MARTINEZ,JORGE,DANIEL,Male,Caucasian,05/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +65196,75383,68277,PRETRIAL,MARTINEZ,JORGE,DANIEL,Male,Caucasian,05/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65246,75433,68323,Probation,DUGGINS,KATHERINE,NULL,Female,Caucasian,11/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +65246,75433,68323,Probation,DUGGINS,KATHERINE,NULL,Female,Caucasian,11/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +65246,75433,68323,Probation,DUGGINS,KATHERINE,NULL,Female,Caucasian,11/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +18604,75448,68336,PRETRIAL,HAMIN,TAWFIQ,NULL,Male,African-American,01/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +18604,75448,68336,PRETRIAL,HAMIN,TAWFIQ,NULL,Male,African-American,01/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +18604,75448,68336,PRETRIAL,HAMIN,TAWFIQ,NULL,Male,African-American,01/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65267,75461,68348,Probation,Copeland,Richard,NULL,Male,African-American,06/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +65267,75461,68348,Probation,Copeland,Richard,NULL,Male,African-American,06/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +65267,75461,68348,Probation,Copeland,Richard,NULL,Male,African-American,06/22/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65268,75462,68349,Probation,Saravia,Jony,Matute,Male,Hispanic,07/05/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +65268,75462,68349,Probation,Saravia,Jony,Matute,Male,Hispanic,07/05/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +65268,75462,68349,Probation,Saravia,Jony,Matute,Male,Hispanic,07/05/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65252,75441,68329,Probation,Darius,Cleeford,NULL,Male,African-American,01/15/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +65252,75441,68329,Probation,Darius,Cleeford,NULL,Male,African-American,01/15/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +65252,75441,68329,Probation,Darius,Cleeford,NULL,Male,African-American,01/15/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65235,75420,68311,PRETRIAL,Key,Travon,NULL,Male,African-American,03/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +65235,75420,68311,PRETRIAL,Key,Travon,NULL,Male,African-American,03/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +65235,75420,68311,PRETRIAL,Key,Travon,NULL,Male,African-American,03/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +32765,75454,68341,PRETRIAL,duris,michael,NULL,Male,Caucasian,11/01/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +32765,75454,68341,PRETRIAL,duris,michael,NULL,Male,Caucasian,11/01/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +32765,75454,68341,PRETRIAL,duris,michael,NULL,Male,Caucasian,11/01/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65262,75456,68343,Probation,Warren,Richard,Lee,Male,Caucasian,06/02/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +65262,75456,68343,Probation,Warren,Richard,Lee,Male,Caucasian,06/02/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +65262,75456,68343,Probation,Warren,Richard,Lee,Male,Caucasian,06/02/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65239,75425,68316,PRETRIAL,Lucius,Brian,NULL,Male,African-American,05/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +65239,75425,68316,PRETRIAL,Lucius,Brian,NULL,Male,African-American,05/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +65239,75425,68316,PRETRIAL,Lucius,Brian,NULL,Male,African-American,05/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65265,75459,68346,Probation,Millan,Luz,Carime,Female,Hispanic,12/19/60,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/31/14 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +65265,75459,68346,Probation,Millan,Luz,Carime,Female,Hispanic,12/19/60,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/31/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +65265,75459,68346,Probation,Millan,Luz,Carime,Female,Hispanic,12/19/60,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65255,75446,68334,PRETRIAL,Joseph,Olmando,NULL,Male,African-American,05/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/31/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +65255,75446,68334,PRETRIAL,Joseph,Olmando,NULL,Male,African-American,05/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/31/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +65255,75446,68334,PRETRIAL,Joseph,Olmando,NULL,Male,African-American,05/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65271,75464,68351,Probation,Flores,Vivian,NULL,Female,Hispanic,07/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +65271,75464,68351,Probation,Flores,Vivian,NULL,Female,Hispanic,07/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +65271,75464,68351,Probation,Flores,Vivian,NULL,Female,Hispanic,07/09/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64759,75417,68308,PRETRIAL,JOHNSON,XAVIER,RAMONDE,Male,African-American,03/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +64759,75417,68308,PRETRIAL,JOHNSON,XAVIER,RAMONDE,Male,African-American,03/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +64759,75417,68308,PRETRIAL,JOHNSON,XAVIER,RAMONDE,Male,African-American,03/11/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +33232,75436,62168,Probation,francois,sandy,NULL,Female,African-American,09/18/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +33232,75436,62168,Probation,francois,sandy,NULL,Female,African-American,09/18/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +33232,75436,62168,Probation,francois,sandy,NULL,Female,African-American,09/18/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,2,Medium,18,Risk of Failure to Appear,22,4,Low,New,1,0 +65251,75440,68328,Probation,Brooks,Cody,NULL,Male,Caucasian,12/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +65251,75440,68328,Probation,Brooks,Cody,NULL,Male,Caucasian,12/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +65251,75440,68328,Probation,Brooks,Cody,NULL,Male,Caucasian,12/12/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65241,75427,68318,PRETRIAL,Sanchez,Victor,NULL,Male,Hispanic,04/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/31/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +65241,75427,68318,PRETRIAL,Sanchez,Victor,NULL,Male,Hispanic,04/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/31/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +65241,75427,68318,PRETRIAL,Sanchez,Victor,NULL,Male,Hispanic,04/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65244,75431,68321,PRETRIAL,COLEMAN,ALONZO,NULL,Male,African-American,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.01,8,High,New,1,0 +65244,75431,68321,PRETRIAL,COLEMAN,ALONZO,NULL,Male,African-American,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +65244,75431,68321,PRETRIAL,COLEMAN,ALONZO,NULL,Male,African-American,07/15/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65254,75445,68333,Probation,Bloom,Michael,NULL,Male,Caucasian,07/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +65254,75445,68333,Probation,Bloom,Michael,NULL,Male,Caucasian,07/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +65254,75445,68333,Probation,Bloom,Michael,NULL,Male,Caucasian,07/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64575,74627,67603,PRETRIAL,BAPTISTE,ELIO,NULL,Male,African-American,03/15/88,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +64575,74627,67603,PRETRIAL,BAPTISTE,ELIO,NULL,Male,African-American,03/15/88,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +64575,74627,67603,PRETRIAL,BAPTISTE,ELIO,NULL,Male,African-American,03/15/88,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65233,75415,68306,PRETRIAL,Issac,Walter,NULL,Male,Caucasian,10/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/31/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +65233,75415,68306,PRETRIAL,Issac,Walter,NULL,Male,Caucasian,10/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +65233,75415,68306,PRETRIAL,Issac,Walter,NULL,Male,Caucasian,10/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65221,75429,68294,PRETRIAL,Graham,Jeremiah,NULL,Male,African-American,03/29/98,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,4,High,7,Risk of Violence,-0.53,10,High,New,1,0 +65221,75429,68294,PRETRIAL,Graham,Jeremiah,NULL,Male,African-American,03/29/98,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +65221,75429,68294,PRETRIAL,Graham,Jeremiah,NULL,Male,African-American,03/29/98,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,4,High,18,Risk of Failure to Appear,21,3,Low,New,1,0 +65257,75450,68337,PRETRIAL,Harrison,Joseph,NULL,Male,African-American,01/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/31/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +65257,75450,68337,PRETRIAL,Harrison,Joseph,NULL,Male,African-American,01/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +65257,75450,68337,PRETRIAL,Harrison,Joseph,NULL,Male,African-American,01/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65259,75452,68339,Probation,jules,guito,NULL,Male,African-American,07/24/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/31/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +65259,75452,68339,Probation,jules,guito,NULL,Male,African-American,07/24/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/31/14 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +65259,75452,68339,Probation,jules,guito,NULL,Male,African-American,07/24/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58728,75422,68313,PRETRIAL,CETOUTE,JARNY,NULL,Male,African-American,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +58728,75422,68313,PRETRIAL,CETOUTE,JARNY,NULL,Male,African-American,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +58728,75422,68313,PRETRIAL,CETOUTE,JARNY,NULL,Male,African-American,02/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65245,75432,68322,Probation,Luterman,Marvin,NULL,Male,Caucasian,08/31/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/31/14 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +65245,75432,68322,Probation,Luterman,Marvin,NULL,Male,Caucasian,08/31/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/31/14 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +65245,75432,68322,Probation,Luterman,Marvin,NULL,Male,Caucasian,08/31/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65237,75423,68314,PRETRIAL,Justin,Nelguy,NULL,Male,Other,10/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +65237,75423,68314,PRETRIAL,Justin,Nelguy,NULL,Male,Other,10/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +65237,75423,68314,PRETRIAL,Justin,Nelguy,NULL,Male,Other,10/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +13278,75453,68340,PRETRIAL,SWINT,ADAM,NULL,Male,African-American,01/16/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +13278,75453,68340,PRETRIAL,SWINT,ADAM,NULL,Male,African-American,01/16/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +13278,75453,68340,PRETRIAL,SWINT,ADAM,NULL,Male,African-American,01/16/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65248,75435,68325,Probation,Morello,Juliana,Maria,Female,Hispanic,03/04/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +65248,75435,68325,Probation,Morello,Juliana,Maria,Female,Hispanic,03/04/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +65248,75435,68325,Probation,Morello,Juliana,Maria,Female,Hispanic,03/04/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +8498,75449,52749,PRETRIAL,BECKFORD,ERIKA,DEON,Female,African-American,10/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,Copy,1,0 +8498,75449,52749,PRETRIAL,BECKFORD,ERIKA,DEON,Female,African-American,10/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,Copy,1,0 +8498,75449,52749,PRETRIAL,BECKFORD,ERIKA,DEON,Female,African-American,10/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +65249,75437,68326,Probation,Menezes,Janilson,NULL,Male,Hispanic,03/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +65249,75437,68326,Probation,Menezes,Janilson,NULL,Male,Hispanic,03/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +65249,75437,68326,Probation,Menezes,Janilson,NULL,Male,Hispanic,03/23/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +15244,75416,68307,PRETRIAL,JEAN,BERNIE,M,Male,African-American,05/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,New,1,0 +15244,75416,68307,PRETRIAL,JEAN,BERNIE,M,Male,African-American,05/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,4,High,8,Risk of Recidivism,0.75,10,High,New,1,0 +15244,75416,68307,PRETRIAL,JEAN,BERNIE,M,Male,African-American,05/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65243,75430,68320,Probation,singletary,kayla,NULL,Female,African-American,08/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +65243,75430,68320,Probation,singletary,kayla,NULL,Female,African-American,08/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +65243,75430,68320,Probation,singletary,kayla,NULL,Female,African-American,08/06/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +21681,75444,68332,PRETRIAL,James,Clarence,NULL,Male,African-American,07/24/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +21681,75444,68332,PRETRIAL,James,Clarence,NULL,Male,African-American,07/24/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +21681,75444,68332,PRETRIAL,James,Clarence,NULL,Male,African-American,07/24/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65258,75451,68338,PRETRIAL,maestas,herman,NULL,Male,Caucasian,02/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,New,1,0 +65258,75451,68338,PRETRIAL,maestas,herman,NULL,Male,Caucasian,02/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +65258,75451,68338,PRETRIAL,maestas,herman,NULL,Male,Caucasian,02/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,39,10,High,New,1,0 +65264,75458,68345,Probation,Alexander-Wilcox,Dionte,NULL,Male,African-American,06/09/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,4,High,7,Risk of Violence,-0.4,10,High,New,1,0 +65264,75458,68345,Probation,Alexander-Wilcox,Dionte,NULL,Male,African-American,06/09/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,4,High,8,Risk of Recidivism,1.65,10,High,New,1,0 +65264,75458,68345,Probation,Alexander-Wilcox,Dionte,NULL,Male,African-American,06/09/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65234,75418,68309,PRETRIAL,Greene,Alexandria,Felicia,Female,African-American,09/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +65234,75418,68309,PRETRIAL,Greene,Alexandria,Felicia,Female,African-American,09/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +65234,75418,68309,PRETRIAL,Greene,Alexandria,Felicia,Female,African-American,09/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65256,75447,68335,PRETRIAL,Lewis,Kyle,NULL,Male,Caucasian,04/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +65256,75447,68335,PRETRIAL,Lewis,Kyle,NULL,Male,Caucasian,04/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +65256,75447,68335,PRETRIAL,Lewis,Kyle,NULL,Male,Caucasian,04/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +7648,75419,68310,PRETRIAL,thomas,byron,NULL,Male,African-American,08/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +7648,75419,68310,PRETRIAL,thomas,byron,NULL,Male,African-American,08/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,2,Medium,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +7648,75419,68310,PRETRIAL,thomas,byron,NULL,Male,African-American,08/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65240,75426,68317,PRETRIAL,Jalisa,Lee,NULL,Female,African-American,12/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,2,Medium,7,Risk of Violence,-2.49,3,Low,New,1,0 +65240,75426,68317,PRETRIAL,Jalisa,Lee,NULL,Female,African-American,12/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +65240,75426,68317,PRETRIAL,Jalisa,Lee,NULL,Female,African-American,12/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,7/31/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +39372,42502,38882,PRETRIAL,Wilson,Allen,NULL,Male,African-American,04/22/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/31/14 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +39372,42502,38882,PRETRIAL,Wilson,Allen,NULL,Male,African-American,04/22/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/31/14 0:00,4,High,8,Risk of Recidivism,0.55,9,High,New,1,0 +39372,42502,38882,PRETRIAL,Wilson,Allen,NULL,Male,African-American,04/22/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,7/31/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +65236,75421,68312,PRETRIAL,Brey,Joshua,Michael,Male,African-American,11/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +65236,75421,68312,PRETRIAL,Brey,Joshua,Michael,Male,African-American,11/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +65236,75421,68312,PRETRIAL,Brey,Joshua,Michael,Male,African-American,11/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65260,75455,68342,Probation,Cabrera,Ashley,NULL,Female,Hispanic,04/15/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +65260,75455,68342,Probation,Cabrera,Ashley,NULL,Female,Hispanic,04/15/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +65260,75455,68342,Probation,Cabrera,Ashley,NULL,Female,Hispanic,04/15/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65247,75434,68324,Probation,Prindible,Jayne,NULL,Female,Caucasian,02/23/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +65247,75434,68324,Probation,Prindible,Jayne,NULL,Female,Caucasian,02/23/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-1.53,2,Low,New,1,0 +65247,75434,68324,Probation,Prindible,Jayne,NULL,Female,Caucasian,02/23/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65269,75463,68350,Probation,REIG,LUIS,NULL,Male,Hispanic,10/26/78,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +65269,75463,68350,Probation,REIG,LUIS,NULL,Male,Hispanic,10/26/78,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +65269,75463,68350,Probation,REIG,LUIS,NULL,Male,Hispanic,10/26/78,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65253,75442,68330,PRETRIAL,Steggerda,Daniel,NULL,Male,Caucasian,10/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +65253,75442,68330,PRETRIAL,Steggerda,Daniel,NULL,Male,Caucasian,10/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +65253,75442,68330,PRETRIAL,Steggerda,Daniel,NULL,Male,Caucasian,10/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65266,75460,68347,Probation,Correa,Michelle,NULL,Female,Caucasian,04/18/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/31/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +65266,75460,68347,Probation,Correa,Michelle,NULL,Female,Caucasian,04/18/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/31/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +65266,75460,68347,Probation,Correa,Michelle,NULL,Female,Caucasian,04/18/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,7/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +63858,75481,68366,PRETRIAL,LESTER,LORI,NULL,Female,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,2,Medium,7,Risk of Violence,-2.89,2,Low,New,1,0 +63858,75481,68366,PRETRIAL,LESTER,LORI,NULL,Female,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +63858,75481,68366,PRETRIAL,LESTER,LORI,NULL,Female,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65274,75468,68354,PRETRIAL,Anderson,Paula,NULL,Female,African-American,02/12/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.64,2,Low,New,1,0 +65274,75468,68354,PRETRIAL,Anderson,Paula,NULL,Female,African-American,02/12/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +65274,75468,68354,PRETRIAL,Anderson,Paula,NULL,Female,African-American,02/12/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65291,75489,68372,Probation,"Allen, Jr.",David,NULL,Male,African-American,05/14/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.74,9,High,New,1,0 +65291,75489,68372,Probation,"Allen, Jr.",David,NULL,Male,African-American,05/14/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.03,6,Medium,New,1,0 +65291,75489,68372,Probation,"Allen, Jr.",David,NULL,Male,African-American,05/14/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,3,Low,New,1,0 +65281,75476,68362,PRETRIAL,Rome,Paris,NULL,Male,African-American,08/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,8/1/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +65281,75476,68362,PRETRIAL,Rome,Paris,NULL,Male,African-American,08/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,8/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +65281,75476,68362,PRETRIAL,Rome,Paris,NULL,Male,African-American,08/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Prison Inmate,Single,8/1/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65288,75484,68367,Probation,wright,laron,NULL,Male,African-American,09/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +65288,75484,68367,Probation,wright,laron,NULL,Male,African-American,09/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +65288,75484,68367,Probation,wright,laron,NULL,Male,African-American,09/18/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65272,75465,68352,PRETRIAL,Dor,Rick,NULL,Male,African-American,01/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +65272,75465,68352,PRETRIAL,Dor,Rick,NULL,Male,African-American,01/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +65272,75465,68352,PRETRIAL,Dor,Rick,NULL,Male,African-American,01/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65283,75479,68364,PRETRIAL,Flanagan,Catrina,NULL,Female,Caucasian,03/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +65283,75479,68364,PRETRIAL,Flanagan,Catrina,NULL,Female,Caucasian,03/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +65283,75479,68364,PRETRIAL,Flanagan,Catrina,NULL,Female,Caucasian,03/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +59088,75488,68371,PRETRIAL,Session,Tavon,Jauwan,Male,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/1/14 0:00,4,High,7,Risk of Violence,-0.4,10,High,New,1,0 +59088,75488,68371,PRETRIAL,Session,Tavon,Jauwan,Male,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/1/14 0:00,4,High,8,Risk of Recidivism,1.04,10,High,New,1,0 +59088,75488,68371,PRETRIAL,Session,Tavon,Jauwan,Male,African-American,09/20/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/1/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +37153,75474,68360,Probation,Gooden,CLIFTON,NULL,Male,African-American,04/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,8/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +37153,75474,68360,Probation,Gooden,CLIFTON,NULL,Male,African-American,04/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,8/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +37153,75474,68360,Probation,Gooden,CLIFTON,NULL,Male,African-American,04/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,8/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +65276,75470,68356,PRETRIAL,Hess,Benjamin,M,Male,Caucasian,08/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +65276,75470,68356,PRETRIAL,Hess,Benjamin,M,Male,Caucasian,08/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +65276,75470,68356,PRETRIAL,Hess,Benjamin,M,Male,Caucasian,08/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65277,75471,68357,PRETRIAL,HAYWARD,JESSICA,NULL,Female,African-American,04/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +65277,75471,68357,PRETRIAL,HAYWARD,JESSICA,NULL,Female,African-American,04/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +65277,75471,68357,PRETRIAL,HAYWARD,JESSICA,NULL,Female,African-American,04/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65279,75473,68359,Probation,Melton,Emanuel,NULL,Male,African-American,05/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.24,8,High,New,1,0 +65279,75473,68359,Probation,Melton,Emanuel,NULL,Male,African-American,05/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +65279,75473,68359,Probation,Melton,Emanuel,NULL,Male,African-American,05/14/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65284,75480,68365,PRETRIAL,Allen,Anthony,Letron,Male,African-American,10/23/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +65284,75480,68365,PRETRIAL,Allen,Anthony,Letron,Male,African-American,10/23/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +65284,75480,68365,PRETRIAL,Allen,Anthony,Letron,Male,African-American,10/23/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +62957,75478,65751,Probation,Pierre,Fredrick,NULL,Male,African-American,08/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,Copy,1,0 +62957,75478,65751,Probation,Pierre,Fredrick,NULL,Male,African-American,08/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,Copy,1,0 +62957,75478,65751,Probation,Pierre,Fredrick,NULL,Male,African-American,08/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +65273,75466,68353,PRETRIAL,Reeve,Richard,Irving,Male,Caucasian,03/21/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +65273,75466,68353,PRETRIAL,Reeve,Richard,Irving,Male,Caucasian,03/21/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +65273,75466,68353,PRETRIAL,Reeve,Richard,Irving,Male,Caucasian,03/21/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65290,75487,68370,Probation,guarneiri,Michael,NULL,Male,Caucasian,03/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +65290,75487,68370,Probation,guarneiri,Michael,NULL,Male,Caucasian,03/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +65290,75487,68370,Probation,guarneiri,Michael,NULL,Male,Caucasian,03/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +39276,75467,49822,PRETRIAL,Anderson,Rohan,NULL,Male,African-American,07/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.91,5,Medium,Copy,1,0 +39276,75467,49822,PRETRIAL,Anderson,Rohan,NULL,Male,African-American,07/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,Copy,1,0 +39276,75467,49822,PRETRIAL,Anderson,Rohan,NULL,Male,African-American,07/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +65278,75472,68358,PRETRIAL,clarke,lennox,NULL,Male,African-American,12/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +65278,75472,68358,PRETRIAL,clarke,lennox,NULL,Male,African-American,12/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +65278,75472,68358,PRETRIAL,clarke,lennox,NULL,Male,African-American,12/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +59511,75490,68373,PRETRIAL,Heim,Daniel,NULL,Male,Caucasian,10/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +59511,75490,68373,PRETRIAL,Heim,Daniel,NULL,Male,Caucasian,10/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +59511,75490,68373,PRETRIAL,Heim,Daniel,NULL,Male,Caucasian,10/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/1/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65282,75477,68363,PRETRIAL,berthel,qutell,NULL,Female,Other,02/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/14 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +65282,75477,68363,PRETRIAL,berthel,qutell,NULL,Female,Other,02/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/14 0:00,2,Medium,8,Risk of Recidivism,-1,4,Low,New,1,0 +65282,75477,68363,PRETRIAL,berthel,qutell,NULL,Female,Other,02/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60147,75482,62546,PRETRIAL,WILLIAMSON,DYLAN,JAMES,Male,Caucasian,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/14 0:00,4,High,7,Risk of Violence,-0.99,9,High,Copy,1,0 +60147,75482,62546,PRETRIAL,WILLIAMSON,DYLAN,JAMES,Male,Caucasian,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/14 0:00,4,High,8,Risk of Recidivism,0.43,9,High,Copy,1,0 +60147,75482,62546,PRETRIAL,WILLIAMSON,DYLAN,JAMES,Male,Caucasian,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +65275,75469,68355,PRETRIAL,Macias,Anthony,Robert,Male,Caucasian,06/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +65275,75469,68355,PRETRIAL,Macias,Anthony,Robert,Male,Caucasian,06/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +65275,75469,68355,PRETRIAL,Macias,Anthony,Robert,Male,Caucasian,06/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/1/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60147,75483,62546,PRETRIAL,WILLIAMSON,DYLAN,JAMES,Male,Caucasian,09/29/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,Copy,1,0 +60147,75483,62546,PRETRIAL,WILLIAMSON,DYLAN,JAMES,Male,Caucasian,09/29/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,Copy,1,0 +60147,75483,62546,PRETRIAL,WILLIAMSON,DYLAN,JAMES,Male,Caucasian,09/29/94,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +65300,75503,68384,PRETRIAL,Jones,Victor,Anthony,Male,African-American,03/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +65300,75503,68384,PRETRIAL,Jones,Victor,Anthony,Male,African-American,03/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +65300,75503,68384,PRETRIAL,Jones,Victor,Anthony,Male,African-American,03/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65301,75506,68386,PRETRIAL,Jeanty,Gerald,NULL,Male,African-American,12/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +65301,75506,68386,PRETRIAL,Jeanty,Gerald,NULL,Male,African-American,12/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +65301,75506,68386,PRETRIAL,Jeanty,Gerald,NULL,Male,African-American,12/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +18161,75493,68376,PRETRIAL,Aponte,Ricardo,NULL,Male,Hispanic,11/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +18161,75493,68376,PRETRIAL,Aponte,Ricardo,NULL,Male,Hispanic,11/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +18161,75493,68376,PRETRIAL,Aponte,Ricardo,NULL,Male,Hispanic,11/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65296,75496,68379,PRETRIAL,Hart,Raunie,NULL,Male,African-American,10/27/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.35,3,Low,New,1,0 +65296,75496,68379,PRETRIAL,Hart,Raunie,NULL,Male,African-American,10/27/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +65296,75496,68379,PRETRIAL,Hart,Raunie,NULL,Male,African-American,10/27/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65293,75492,68375,PRETRIAL,Bastien,Luckner,NULL,Male,Other,10/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +65293,75492,68375,PRETRIAL,Bastien,Luckner,NULL,Male,Other,10/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +65293,75492,68375,PRETRIAL,Bastien,Luckner,NULL,Male,Other,10/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +23919,75499,42253,PRETRIAL,Davis,Brittany,NULL,Female,African-American,08/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,Copy,1,0 +23919,75499,42253,PRETRIAL,Davis,Brittany,NULL,Female,African-American,08/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.15,10,High,Copy,1,0 +23919,75499,42253,PRETRIAL,Davis,Brittany,NULL,Female,African-American,08/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +65294,75494,68377,PRETRIAL,Ambers,Joseph,NULL,Male,Caucasian,09/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,2,Medium,7,Risk of Violence,-3.4,1,Low,New,1,0 +65294,75494,68377,PRETRIAL,Ambers,Joseph,NULL,Male,Caucasian,09/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +65294,75494,68377,PRETRIAL,Ambers,Joseph,NULL,Male,Caucasian,09/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65299,75501,68382,PRETRIAL,Bonner,Daritte,NULL,Female,African-American,01/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +65299,75501,68382,PRETRIAL,Bonner,Daritte,NULL,Female,African-American,01/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +65299,75501,68382,PRETRIAL,Bonner,Daritte,NULL,Female,African-American,01/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +48208,75504,68385,PRETRIAL,Bradshaw,Javon,NULL,Male,African-American,04/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +48208,75504,68385,PRETRIAL,Bradshaw,Javon,NULL,Male,African-American,04/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +48208,75504,68385,PRETRIAL,Bradshaw,Javon,NULL,Male,African-American,04/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65292,75491,68374,PRETRIAL,Drummond,Lakavious,NULL,Male,African-American,01/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +65292,75491,68374,PRETRIAL,Drummond,Lakavious,NULL,Male,African-American,01/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +65292,75491,68374,PRETRIAL,Drummond,Lakavious,NULL,Male,African-American,01/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65298,75500,68381,PRETRIAL,Ling,Xiao,NULL,Male,Asian,10/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +65298,75500,68381,PRETRIAL,Ling,Xiao,NULL,Male,Asian,10/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/14 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +65298,75500,68381,PRETRIAL,Ling,Xiao,NULL,Male,Asian,10/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65295,75495,68378,PRETRIAL,jones,richard,lee,Male,African-American,09/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/2/14 0:00,2,Medium,7,Risk of Violence,-3.07,1,Low,New,1,0 +65295,75495,68378,PRETRIAL,jones,richard,lee,Male,African-American,09/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +65295,75495,68378,PRETRIAL,jones,richard,lee,Male,African-American,09/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/2/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51951,75505,53206,PRETRIAL,Morales,Angie,NULL,Female,Caucasian,04/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,Copy,1,0 +51951,75505,53206,PRETRIAL,Morales,Angie,NULL,Female,Caucasian,04/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.11,8,High,Copy,1,0 +51951,75505,53206,PRETRIAL,Morales,Angie,NULL,Female,Caucasian,04/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +65297,75497,68380,PRETRIAL,Brown,Carlton,NULL,Male,African-American,01/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.12,4,Low,New,1,0 +65297,75497,68380,PRETRIAL,Brown,Carlton,NULL,Male,African-American,01/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.7,10,High,New,1,0 +65297,75497,68380,PRETRIAL,Brown,Carlton,NULL,Male,African-American,01/21/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61336,75502,68383,PRETRIAL,Akinpello,Dominick,NULL,Male,African-American,04/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +61336,75502,68383,PRETRIAL,Akinpello,Dominick,NULL,Male,African-American,04/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +61336,75502,68383,PRETRIAL,Akinpello,Dominick,NULL,Male,African-American,04/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65303,75510,68389,PRETRIAL,CLAUDE,NATHANIEL,NULL,Male,Native American,12/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +65303,75510,68389,PRETRIAL,CLAUDE,NATHANIEL,NULL,Male,Native American,12/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +65303,75510,68389,PRETRIAL,CLAUDE,NATHANIEL,NULL,Male,Native American,12/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +31113,75512,30129,Probation,rosado,maison,NULL,Male,Hispanic,11/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,Copy,1,0 +31113,75512,30129,Probation,rosado,maison,NULL,Male,Hispanic,11/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,Copy,1,0 +31113,75512,30129,Probation,rosado,maison,NULL,Male,Hispanic,11/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +39297,75507,68387,PRETRIAL,LAWSON,FREDERICK,J,Male,African-American,02/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +39297,75507,68387,PRETRIAL,LAWSON,FREDERICK,J,Male,African-American,02/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +39297,75507,68387,PRETRIAL,LAWSON,FREDERICK,J,Male,African-American,02/11/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +65302,75509,68388,PRETRIAL,Siel,Darrell,NULL,Male,African-American,01/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,Copy,1,0 +65302,75509,68388,PRETRIAL,Siel,Darrell,NULL,Male,African-American,01/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,Copy,1,0 +65302,75509,68388,PRETRIAL,Siel,Darrell,NULL,Male,African-American,01/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +65307,75516,68394,PRETRIAL,Gilbert,Jorge,NULL,Male,Hispanic,12/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +65307,75516,68394,PRETRIAL,Gilbert,Jorge,NULL,Male,Hispanic,12/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +65307,75516,68394,PRETRIAL,Gilbert,Jorge,NULL,Male,Hispanic,12/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65306,75515,68393,PRETRIAL,Rodriguez,Dayner,NULL,Male,Hispanic,01/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +65306,75515,68393,PRETRIAL,Rodriguez,Dayner,NULL,Male,Hispanic,01/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +65306,75515,68393,PRETRIAL,Rodriguez,Dayner,NULL,Male,Hispanic,01/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65304,75513,68391,PRETRIAL,AMODEI,KRISTY,NULL,Female,Caucasian,04/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +65304,75513,68391,PRETRIAL,AMODEI,KRISTY,NULL,Female,Caucasian,04/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +65304,75513,68391,PRETRIAL,AMODEI,KRISTY,NULL,Female,Caucasian,04/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65305,75514,68392,PRETRIAL,ASTRORGA,RUDY,NULL,Male,Caucasian,12/20/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +65305,75514,68392,PRETRIAL,ASTRORGA,RUDY,NULL,Male,Caucasian,12/20/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +65305,75514,68392,PRETRIAL,ASTRORGA,RUDY,NULL,Male,Caucasian,12/20/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +793,75511,68390,Probation,Hyder,Geoffrey,G,Male,Caucasian,03/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.12,8,High,New,1,0 +793,75511,68390,Probation,Hyder,Geoffrey,G,Male,Caucasian,03/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +793,75511,68390,Probation,Hyder,Geoffrey,G,Male,Caucasian,03/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +2447,75519,67909,PRETRIAL,RICH,STANLEY,NULL,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,Copy,1,0 +2447,75519,67909,PRETRIAL,RICH,STANLEY,NULL,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/14 0:00,4,High,8,Risk of Recidivism,0.66,10,High,Copy,1,0 +2447,75519,67909,PRETRIAL,RICH,STANLEY,NULL,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +65314,75524,68401,PRETRIAL,HATCHER,LEON,ANTONIO,Male,African-American,01/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +65314,75524,68401,PRETRIAL,HATCHER,LEON,ANTONIO,Male,African-American,01/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +65314,75524,68401,PRETRIAL,HATCHER,LEON,ANTONIO,Male,African-American,01/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +19339,75535,68411,PRETRIAL,MATA,ZOILO,NULL,Male,Caucasian,09/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/4/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +19339,75535,68411,PRETRIAL,MATA,ZOILO,NULL,Male,Caucasian,09/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +19339,75535,68411,PRETRIAL,MATA,ZOILO,NULL,Male,Caucasian,09/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +7300,75527,68404,PRETRIAL,LEWIS,KIBWE,NULL,Male,African-American,02/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +7300,75527,68404,PRETRIAL,LEWIS,KIBWE,NULL,Male,African-American,02/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +7300,75527,68404,PRETRIAL,LEWIS,KIBWE,NULL,Male,African-American,02/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +26234,75532,68408,PRETRIAL,BROWN,KEITH,NULL,Male,Caucasian,08/10/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/4/14 0:00,2,Medium,7,Risk of Violence,-3.02,1,Low,New,1,0 +26234,75532,68408,PRETRIAL,BROWN,KEITH,NULL,Male,Caucasian,08/10/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +26234,75532,68408,PRETRIAL,BROWN,KEITH,NULL,Male,Caucasian,08/10/72,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/4/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65308,75517,68395,PRETRIAL,JONES,RICHARD,LAWRENCE,Male,African-American,10/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +65308,75517,68395,PRETRIAL,JONES,RICHARD,LAWRENCE,Male,African-American,10/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +65308,75517,68395,PRETRIAL,JONES,RICHARD,LAWRENCE,Male,African-American,10/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55795,75538,68413,PRETRIAL,Roche,Caritasse,NULL,Female,African-American,05/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/4/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +55795,75538,68413,PRETRIAL,Roche,Caritasse,NULL,Female,African-American,05/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +55795,75538,68413,PRETRIAL,Roche,Caritasse,NULL,Female,African-American,05/13/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65320,75534,68410,PRETRIAL,Castaneda,Joel,NULL,Male,Hispanic,05/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +65320,75534,68410,PRETRIAL,Castaneda,Joel,NULL,Male,Hispanic,05/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +65320,75534,68410,PRETRIAL,Castaneda,Joel,NULL,Male,Hispanic,05/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65317,75529,68406,PRETRIAL,Tamayoaguilar,Nelson,NULL,Male,Hispanic,05/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/4/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +65317,75529,68406,PRETRIAL,Tamayoaguilar,Nelson,NULL,Male,Hispanic,05/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +65317,75529,68406,PRETRIAL,Tamayoaguilar,Nelson,NULL,Male,Hispanic,05/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65312,75522,68399,PRETRIAL,GONZALEZ,ARTURO,NULL,Male,Other,02/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +65312,75522,68399,PRETRIAL,GONZALEZ,ARTURO,NULL,Male,Other,02/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +65312,75522,68399,PRETRIAL,GONZALEZ,ARTURO,NULL,Male,Other,02/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +13477,75537,12881,PRETRIAL,ELDINE,FANEL,NULL,Male,African-American,03/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,Copy,1,0 +13477,75537,12881,PRETRIAL,ELDINE,FANEL,NULL,Male,African-American,03/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,Copy,1,0 +13477,75537,12881,PRETRIAL,ELDINE,FANEL,NULL,Male,African-American,03/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +65318,75530,68407,Probation,Rocks,Jennifer,NULL,Female,Caucasian,01/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/4/14 0:00,2,Medium,7,Risk of Violence,-2.86,2,Low,New,1,0 +65318,75530,68407,Probation,Rocks,Jennifer,NULL,Female,Caucasian,01/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +65318,75530,68407,Probation,Rocks,Jennifer,NULL,Female,Caucasian,01/24/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/4/14 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,New,1,0 +65311,75521,68398,PRETRIAL,Thompson,Nickel,Jospeh,Male,Other,03/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/4/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +65311,75521,68398,PRETRIAL,Thompson,Nickel,Jospeh,Male,Other,03/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +65311,75521,68398,PRETRIAL,Thompson,Nickel,Jospeh,Male,Other,03/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65315,75526,68403,PRETRIAL,CAPERS,CEDRIC,NULL,Male,African-American,08/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +65315,75526,68403,PRETRIAL,CAPERS,CEDRIC,NULL,Male,African-American,08/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +65315,75526,68403,PRETRIAL,CAPERS,CEDRIC,NULL,Male,African-American,08/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65319,75533,68409,Probation,creegan,william,NULL,Male,Caucasian,07/08/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/4/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +65319,75533,68409,Probation,creegan,william,NULL,Male,Caucasian,07/08/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +65319,75533,68409,Probation,creegan,william,NULL,Male,Caucasian,07/08/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65310,75520,68397,PRETRIAL,Pendergrass,Courtney,NULL,Male,African-American,12/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +65310,75520,68397,PRETRIAL,Pendergrass,Courtney,NULL,Male,African-American,12/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +65310,75520,68397,PRETRIAL,Pendergrass,Courtney,NULL,Male,African-American,12/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65321,75539,68414,Probation,Velez,Daniel,Alexis,Male,Hispanic,03/14/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/4/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +65321,75539,68414,Probation,Velez,Daniel,Alexis,Male,Hispanic,03/14/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/4/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +65321,75539,68414,Probation,Velez,Daniel,Alexis,Male,Hispanic,03/14/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65309,75518,68396,PRETRIAL,CLARK,BREON,NATHANIEL,Male,African-American,04/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +65309,75518,68396,PRETRIAL,CLARK,BREON,NATHANIEL,Male,African-American,04/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +65309,75518,68396,PRETRIAL,CLARK,BREON,NATHANIEL,Male,African-American,04/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65316,75528,68405,PRETRIAL,hoffman,josiah,NULL,Male,Caucasian,10/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/14 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +65316,75528,68405,PRETRIAL,hoffman,josiah,NULL,Male,Caucasian,10/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +65316,75528,68405,PRETRIAL,hoffman,josiah,NULL,Male,Caucasian,10/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +8550,75531,52096,PRETRIAL,Jackson,Leon,NULL,Male,African-American,01/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,Copy,1,0 +8550,75531,52096,PRETRIAL,Jackson,Leon,NULL,Male,African-American,01/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +8550,75531,52096,PRETRIAL,Jackson,Leon,NULL,Male,African-American,01/18/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +60188,75536,68412,Probation,Lafrance,Mario,NULL,Male,African-American,01/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/4/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +60188,75536,68412,Probation,Lafrance,Mario,NULL,Male,African-American,01/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +60188,75536,68412,Probation,Lafrance,Mario,NULL,Male,African-American,01/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65313,75523,68400,PRETRIAL,BARON,ERNEST,NULL,Male,Other,04/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/4/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +65313,75523,68400,PRETRIAL,BARON,ERNEST,NULL,Male,Other,04/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/4/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +65313,75523,68400,PRETRIAL,BARON,ERNEST,NULL,Male,Other,04/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +63928,75557,66854,Probation,palmer,timothy,NULL,Male,Caucasian,03/06/82,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/5/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +63928,75557,66854,Probation,palmer,timothy,NULL,Male,Caucasian,03/06/82,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/5/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +63928,75557,66854,Probation,palmer,timothy,NULL,Male,Caucasian,03/06/82,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65327,75549,68421,PRETRIAL,o'neill,joseph,NULL,Male,Caucasian,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/5/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +65327,75549,68421,PRETRIAL,o'neill,joseph,NULL,Male,Caucasian,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/5/14 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +65327,75549,68421,PRETRIAL,o'neill,joseph,NULL,Male,Caucasian,01/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/5/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +65330,75554,68424,Probation,Lake,Mark,NULL,Male,Caucasian,12/23/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +65330,75554,68424,Probation,Lake,Mark,NULL,Male,Caucasian,12/23/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +65330,75554,68424,Probation,Lake,Mark,NULL,Male,Caucasian,12/23/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63054,75547,65866,Probation,Brantley,Dejah,NULL,Female,African-American,12/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,8/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,Copy,1,0 +63054,75547,65866,Probation,Brantley,Dejah,NULL,Female,African-American,12/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,8/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,9,High,Copy,1,0 +63054,75547,65866,Probation,Brantley,Dejah,NULL,Female,African-American,12/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,8/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +65335,75562,68430,Probation,Gil,Andres,NULL,Male,Hispanic,12/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +65335,75562,68430,Probation,Gil,Andres,NULL,Male,Hispanic,12/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +65335,75562,68430,Probation,Gil,Andres,NULL,Male,Hispanic,12/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65324,75546,68419,PRETRIAL,CAMPOI,SONNY,NULL,Male,Hispanic,06/29/89,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,8/5/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +65324,75546,68419,PRETRIAL,CAMPOI,SONNY,NULL,Male,Hispanic,06/29/89,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,8/5/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +65324,75546,68419,PRETRIAL,CAMPOI,SONNY,NULL,Male,Hispanic,06/29/89,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +13461,75563,68431,Probation,Anastasia,Anthony,Alan,Male,Caucasian,12/09/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/14 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +13461,75563,68431,Probation,Anastasia,Anthony,Alan,Male,Caucasian,12/09/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +13461,75563,68431,Probation,Anastasia,Anthony,Alan,Male,Caucasian,12/09/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65322,75542,68416,PRETRIAL,Massey,Reginald,Anthony,Male,African-American,03/19/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.97,9,High,New,1,0 +65322,75542,68416,PRETRIAL,Massey,Reginald,Anthony,Male,African-American,03/19/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +65322,75542,68416,PRETRIAL,Massey,Reginald,Anthony,Male,African-American,03/19/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65334,75560,68428,Probation,ewart,scott,m,Male,Caucasian,11/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/5/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +65334,75560,68428,Probation,ewart,scott,m,Male,Caucasian,11/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/5/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +65334,75560,68428,Probation,ewart,scott,m,Male,Caucasian,11/05/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64049,75544,66994,PRETRIAL,DAVIS,RODNEY,NULL,Male,African-American,01/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,4,High,7,Risk of Violence,-0.71,9,High,Copy,1,0 +64049,75544,66994,PRETRIAL,DAVIS,RODNEY,NULL,Male,African-American,01/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,4,High,8,Risk of Recidivism,0.82,10,High,Copy,1,0 +64049,75544,66994,PRETRIAL,DAVIS,RODNEY,NULL,Male,African-American,01/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +65329,75551,68423,PRETRIAL,BLAKE,HYACINTH,NULL,Female,African-American,06/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/5/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +65329,75551,68423,PRETRIAL,BLAKE,HYACINTH,NULL,Female,African-American,06/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/5/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +65329,75551,68423,PRETRIAL,BLAKE,HYACINTH,NULL,Female,African-American,06/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65333,75558,68427,PRETRIAL,HALL,TAMIKA,NULL,Female,African-American,12/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +65333,75558,68427,PRETRIAL,HALL,TAMIKA,NULL,Female,African-American,12/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +65333,75558,68427,PRETRIAL,HALL,TAMIKA,NULL,Female,African-American,12/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +20316,75543,68417,PRETRIAL,DAISE,KENDRICK,NULL,Male,African-American,08/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +20316,75543,68417,PRETRIAL,DAISE,KENDRICK,NULL,Male,African-American,08/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.88,10,High,New,1,0 +20316,75543,68417,PRETRIAL,DAISE,KENDRICK,NULL,Male,African-American,08/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65328,75550,68422,PRETRIAL,mori,joe,NULL,Male,Caucasian,12/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/5/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +65328,75550,68422,PRETRIAL,mori,joe,NULL,Male,Caucasian,12/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/5/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +65328,75550,68422,PRETRIAL,mori,joe,NULL,Male,Caucasian,12/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +65327,75552,68421,PRETRIAL,o'neill,joseph,NULL,Male,Caucasian,01/12/81,17,All Scales,Intake,English,Pretrial,Jail Inmate,Married,8/5/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,Copy,1,0 +65327,75552,68421,PRETRIAL,o'neill,joseph,NULL,Male,Caucasian,01/12/81,17,All Scales,Intake,English,Pretrial,Jail Inmate,Married,8/5/14 0:00,4,High,8,Risk of Recidivism,0.61,9,High,Copy,1,0 +65327,75552,68421,PRETRIAL,o'neill,joseph,NULL,Male,Caucasian,01/12/81,17,All Scales,Intake,English,Pretrial,Jail Inmate,Married,8/5/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +65144,75559,68237,PRETRIAL,Fornasiero,Christopher,NULL,Male,Caucasian,12/21/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +65144,75559,68237,PRETRIAL,Fornasiero,Christopher,NULL,Male,Caucasian,12/21/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +65144,75559,68237,PRETRIAL,Fornasiero,Christopher,NULL,Male,Caucasian,12/21/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65331,75555,68425,PRETRIAL,Shogan,Dushan,NULL,Male,Caucasian,05/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/5/14 0:00,1,Low,7,Risk of Violence,-4.43,1,Low,New,1,0 +65331,75555,68425,PRETRIAL,Shogan,Dushan,NULL,Male,Caucasian,05/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/5/14 0:00,1,Low,8,Risk of Recidivism,-2.75,1,Low,New,1,0 +65331,75555,68425,PRETRIAL,Shogan,Dushan,NULL,Male,Caucasian,05/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52354,75564,68432,Probation,Bak,Jason,M,Male,Caucasian,03/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +52354,75564,68432,Probation,Bak,Jason,M,Male,Caucasian,03/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +52354,75564,68432,Probation,Bak,Jason,M,Male,Caucasian,03/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65336,75561,68429,Probation,yan,cheong,NULL,Male,Other,09/30/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/5/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +65336,75561,68429,Probation,yan,cheong,NULL,Male,Other,09/30/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/5/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +65336,75561,68429,Probation,yan,cheong,NULL,Male,Other,09/30/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +36606,75553,66942,PRETRIAL,Straussberger,Melaine,NULL,Female,Caucasian,12/22/60,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/5/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +36606,75553,66942,PRETRIAL,Straussberger,Melaine,NULL,Female,Caucasian,12/22/60,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/5/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +36606,75553,66942,PRETRIAL,Straussberger,Melaine,NULL,Female,Caucasian,12/22/60,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +65323,75545,68418,PRETRIAL,Leon,Vicente,E,Male,Hispanic,09/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/5/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +65323,75545,68418,PRETRIAL,Leon,Vicente,E,Male,Hispanic,09/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/5/14 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +65323,75545,68418,PRETRIAL,Leon,Vicente,E,Male,Hispanic,09/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65326,75548,68420,Probation,Cherisca,Deve,NULL,Male,African-American,10/23/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/5/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +65326,75548,68420,Probation,Cherisca,Deve,NULL,Male,African-American,10/23/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +65326,75548,68420,Probation,Cherisca,Deve,NULL,Male,African-American,10/23/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/5/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65332,75556,68426,PRETRIAL,MALONE,MILES,NULL,Male,Caucasian,02/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/5/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +65332,75556,68426,PRETRIAL,MALONE,MILES,NULL,Male,Caucasian,02/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/5/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +65332,75556,68426,PRETRIAL,MALONE,MILES,NULL,Male,Caucasian,02/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51073,75590,52223,PRETRIAL,CORDERO,JAYSON,NULL,Male,Other,03/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/6/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,Copy,1,0 +51073,75590,52223,PRETRIAL,CORDERO,JAYSON,NULL,Male,Other,03/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/6/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,Copy,1,0 +51073,75590,52223,PRETRIAL,CORDERO,JAYSON,NULL,Male,Other,03/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +65345,75577,68442,PRETRIAL,Baker,Philip,NULL,Male,African-American,04/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +65345,75577,68442,PRETRIAL,Baker,Philip,NULL,Male,African-American,04/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +65345,75577,68442,PRETRIAL,Baker,Philip,NULL,Male,African-American,04/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65365,75598,68461,PRETRIAL,McGee,john,NULL,Male,African-American,01/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/14 0:00,2,Medium,7,Risk of Violence,-2.73,2,Low,New,1,0 +65365,75598,68461,PRETRIAL,McGee,john,NULL,Male,African-American,01/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +65365,75598,68461,PRETRIAL,McGee,john,NULL,Male,African-American,01/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +32986,75569,41912,PRETRIAL,Slayden,Marvin,NULL,Male,African-American,10/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,Copy,1,0 +32986,75569,41912,PRETRIAL,Slayden,Marvin,NULL,Male,African-American,10/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.81,10,High,Copy,1,0 +32986,75569,41912,PRETRIAL,Slayden,Marvin,NULL,Male,African-American,10/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +65344,75576,68441,PRETRIAL,TIRREL,MICHAEL,JONES,Male,African-American,04/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +65344,75576,68441,PRETRIAL,TIRREL,MICHAEL,JONES,Male,African-American,04/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +65344,75576,68441,PRETRIAL,TIRREL,MICHAEL,JONES,Male,African-American,04/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,39,10,High,New,1,0 +65361,75595,68459,PRETRIAL,Saa,Jose,NULL,Male,Caucasian,12/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +65361,75595,68459,PRETRIAL,Saa,Jose,NULL,Male,Caucasian,12/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +65361,75595,68459,PRETRIAL,Saa,Jose,NULL,Male,Caucasian,12/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +47269,75574,48830,PRETRIAL,Villinis,Mary,NULL,Female,Caucasian,04/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.36,3,Low,Copy,1,0 +47269,75574,48830,PRETRIAL,Villinis,Mary,NULL,Female,Caucasian,04/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,9,High,Copy,1,0 +47269,75574,48830,PRETRIAL,Villinis,Mary,NULL,Female,Caucasian,04/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +65358,75592,68456,Probation,leuchs,edward,NULL,Male,Caucasian,05/09/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/6/14 0:00,1,Low,7,Risk of Violence,-4.52,1,Low,New,1,0 +65358,75592,68456,Probation,leuchs,edward,NULL,Male,Caucasian,05/09/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/6/14 0:00,1,Low,8,Risk of Recidivism,-2.76,1,Low,New,1,0 +65358,75592,68456,Probation,leuchs,edward,NULL,Male,Caucasian,05/09/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +51073,57476,52223,PRETRIAL,CORDERO,JAYSON,NULL,Male,Other,03/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/6/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +51073,57476,52223,PRETRIAL,CORDERO,JAYSON,NULL,Male,Other,03/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/6/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +51073,57476,52223,PRETRIAL,CORDERO,JAYSON,NULL,Male,Other,03/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65353,75587,68452,Probation,Reilly,Patrick,NULL,Male,Caucasian,10/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +65353,75587,68452,Probation,Reilly,Patrick,NULL,Male,Caucasian,10/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +65353,75587,68452,Probation,Reilly,Patrick,NULL,Male,Caucasian,10/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +8410,75566,68434,PRETRIAL,ALTIDOR,SIDNEY,NULL,Male,African-American,02/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +8410,75566,68434,PRETRIAL,ALTIDOR,SIDNEY,NULL,Male,African-American,02/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +8410,75566,68434,PRETRIAL,ALTIDOR,SIDNEY,NULL,Male,African-American,02/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65371,75600,68463,PRETRIAL,Stephens,Calvin,NULL,Male,African-American,07/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +65371,75600,68463,PRETRIAL,Stephens,Calvin,NULL,Male,African-American,07/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,10,High,New,1,0 +65371,75600,68463,PRETRIAL,Stephens,Calvin,NULL,Male,African-American,07/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65352,75585,68450,Probation,EDWARDS,AKEEM,R,Male,African-American,11/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +65352,75585,68450,Probation,EDWARDS,AKEEM,R,Male,African-American,11/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +65352,75585,68450,Probation,EDWARDS,AKEEM,R,Male,African-American,11/29/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65356,75589,68454,PRETRIAL,Terrell,Stacey,NULL,Female,African-American,03/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +65356,75589,68454,PRETRIAL,Terrell,Stacey,NULL,Female,African-American,03/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,7,Medium,New,1,0 +65356,75589,68454,PRETRIAL,Terrell,Stacey,NULL,Female,African-American,03/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65339,75568,68436,PRETRIAL,Etienne,Suzay,Jean,Male,Other,05/01/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +65339,75568,68436,PRETRIAL,Etienne,Suzay,Jean,Male,Other,05/01/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/14 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +65339,75568,68436,PRETRIAL,Etienne,Suzay,Jean,Male,Other,05/01/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +36558,75571,35843,PRETRIAL,SIMS,WILLIE,NULL,Male,African-American,10/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,Copy,1,0 +36558,75571,35843,PRETRIAL,SIMS,WILLIE,NULL,Male,African-American,10/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,Copy,1,0 +36558,75571,35843,PRETRIAL,SIMS,WILLIE,NULL,Male,African-American,10/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +65342,75573,68439,PRETRIAL,WALKER,NICHOLAS,KLYE,Male,Caucasian,04/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +65342,75573,68439,PRETRIAL,WALKER,NICHOLAS,KLYE,Male,Caucasian,04/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +65342,75573,68439,PRETRIAL,WALKER,NICHOLAS,KLYE,Male,Caucasian,04/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65348,75580,68445,PRETRIAL,Jones,Donald,Jamier,Male,African-American,01/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +65348,75580,68445,PRETRIAL,Jones,Donald,Jamier,Male,African-American,01/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +65348,75580,68445,PRETRIAL,Jones,Donald,Jamier,Male,African-American,01/25/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65360,75594,68458,PRETRIAL,Torres,Julian,NULL,Male,Caucasian,11/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +65360,75594,68458,PRETRIAL,Torres,Julian,NULL,Male,Caucasian,11/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +65360,75594,68458,PRETRIAL,Torres,Julian,NULL,Male,Caucasian,11/27/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65337,75565,68433,PRETRIAL,Rose,Cordelia,NULL,Female,Other,11/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +65337,75565,68433,PRETRIAL,Rose,Cordelia,NULL,Female,Other,11/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +65337,75565,68433,PRETRIAL,Rose,Cordelia,NULL,Female,Other,11/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65347,75579,68444,PRETRIAL,Dixon,Ronnie,NULL,Male,African-American,08/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.38,3,Low,New,1,0 +65347,75579,68444,PRETRIAL,Dixon,Ronnie,NULL,Male,African-American,08/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +65347,75579,68444,PRETRIAL,Dixon,Ronnie,NULL,Male,African-American,08/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65355,75588,68453,PRETRIAL,CAMPBELL,DUDLEY,NULL,Female,African-American,06/07/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +65355,75588,68453,PRETRIAL,CAMPBELL,DUDLEY,NULL,Female,African-American,06/07/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +65355,75588,68453,PRETRIAL,CAMPBELL,DUDLEY,NULL,Female,African-American,06/07/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65354,75586,68451,Probation,Cossio Cordoba,Ramon,NULL,Male,Hispanic,07/15/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/6/14 0:00,1,Low,7,Risk of Violence,-4.29,1,Low,New,1,0 +65354,75586,68451,Probation,Cossio Cordoba,Ramon,NULL,Male,Hispanic,07/15/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/6/14 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +65354,75586,68451,Probation,Cossio Cordoba,Ramon,NULL,Male,Hispanic,07/15/55,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65338,75567,68435,PRETRIAL,Sykes,Jay,NULL,Male,African-American,04/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +65338,75567,68435,PRETRIAL,Sykes,Jay,NULL,Male,African-American,04/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +65338,75567,68435,PRETRIAL,Sykes,Jay,NULL,Male,African-American,04/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65349,75581,68446,PRETRIAL,Mosley,Angela,Denise,Female,African-American,05/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +65349,75581,68446,PRETRIAL,Mosley,Angela,Denise,Female,African-American,05/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +65349,75581,68446,PRETRIAL,Mosley,Angela,Denise,Female,African-American,05/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65341,75572,68438,PRETRIAL,Macklin,Nicholaus,NULL,Female,African-American,05/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +65341,75572,68438,PRETRIAL,Macklin,Nicholaus,NULL,Female,African-American,05/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +65341,75572,68438,PRETRIAL,Macklin,Nicholaus,NULL,Female,African-American,05/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65359,75593,68457,PRETRIAL,Burdick,Daniel,John,Male,Caucasian,06/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +65359,75593,68457,PRETRIAL,Burdick,Daniel,John,Male,Caucasian,06/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +65359,75593,68457,PRETRIAL,Burdick,Daniel,John,Male,Caucasian,06/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +47351,75583,68448,PRETRIAL,Jones,Alexis,Sheree,Female,Caucasian,02/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +47351,75583,68448,PRETRIAL,Jones,Alexis,Sheree,Female,Caucasian,02/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +47351,75583,68448,PRETRIAL,Jones,Alexis,Sheree,Female,Caucasian,02/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65343,75575,68440,PRETRIAL,Walton,James,CalvinMic,Male,African-American,06/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +65343,75575,68440,PRETRIAL,Walton,James,CalvinMic,Male,African-American,06/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +65343,75575,68440,PRETRIAL,Walton,James,CalvinMic,Male,African-American,06/27/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65369,75599,68462,Probation,starks,jamesha,NULL,Female,African-American,11/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +65369,75599,68462,Probation,starks,jamesha,NULL,Female,African-American,11/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +65369,75599,68462,Probation,starks,jamesha,NULL,Female,African-American,11/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65346,75578,68443,PRETRIAL,Cortes,Charles,Anthony,Male,Caucasian,01/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +65346,75578,68443,PRETRIAL,Cortes,Charles,Anthony,Male,Caucasian,01/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +65346,75578,68443,PRETRIAL,Cortes,Charles,Anthony,Male,Caucasian,01/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65362,75596,68460,PRETRIAL,Pratt,Robert,Cornelius,Male,African-American,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +65362,75596,68460,PRETRIAL,Pratt,Robert,Cornelius,Male,African-American,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +65362,75596,68460,PRETRIAL,Pratt,Robert,Cornelius,Male,African-American,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/6/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65340,75570,68437,PRETRIAL,Robinson,Malcolm,Edward,Male,African-American,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +65340,75570,68437,PRETRIAL,Robinson,Malcolm,Edward,Male,African-American,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +65340,75570,68437,PRETRIAL,Robinson,Malcolm,Edward,Male,African-American,09/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/6/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65357,75591,68455,Probation,kirton,errol,NULL,Male,African-American,09/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +65357,75591,68455,Probation,kirton,errol,NULL,Male,African-American,09/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +65357,75591,68455,Probation,kirton,errol,NULL,Male,African-American,09/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65388,75625,68488,PRETRIAL,BURGESS,ANTUAN,LEON,Male,African-American,07/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +65388,75625,68488,PRETRIAL,BURGESS,ANTUAN,LEON,Male,African-American,07/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +65388,75625,68488,PRETRIAL,BURGESS,ANTUAN,LEON,Male,African-American,07/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +65374,75604,68467,PRETRIAL,Lee,Desmond,Everton,Male,Other,10/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/7/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +65374,75604,68467,PRETRIAL,Lee,Desmond,Everton,Male,Other,10/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/7/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +65374,75604,68467,PRETRIAL,Lee,Desmond,Everton,Male,Other,10/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65382,75617,68480,Probation,WEBSTER,JAMES,ARTHUR,Male,Caucasian,07/29/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +65382,75617,68480,Probation,WEBSTER,JAMES,ARTHUR,Male,Caucasian,07/29/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +65382,75617,68480,Probation,WEBSTER,JAMES,ARTHUR,Male,Caucasian,07/29/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +56551,75633,66121,PRETRIAL,Baptista,Christopher,Andrew,Male,Hispanic,09/20/80,17,All Scales,Intake,English,Conditional Release,Probation,Separated,8/7/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +56551,75633,66121,PRETRIAL,Baptista,Christopher,Andrew,Male,Hispanic,09/20/80,17,All Scales,Intake,English,Conditional Release,Probation,Separated,8/7/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +56551,75633,66121,PRETRIAL,Baptista,Christopher,Andrew,Male,Hispanic,09/20/80,17,All Scales,Intake,English,Conditional Release,Probation,Separated,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +65380,75612,68475,PRETRIAL,LEE,KRISTYN,Athaline,Female,African-American,09/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +65380,75612,68475,PRETRIAL,LEE,KRISTYN,Athaline,Female,African-American,09/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +65380,75612,68475,PRETRIAL,LEE,KRISTYN,Athaline,Female,African-American,09/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65373,75602,68465,PRETRIAL,Lauer,Katlyn,Jessica,Female,Caucasian,04/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +65373,75602,68465,PRETRIAL,Lauer,Katlyn,Jessica,Female,Caucasian,04/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +65373,75602,68465,PRETRIAL,Lauer,Katlyn,Jessica,Female,Caucasian,04/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65386,75623,68486,PRETRIAL,Epstein,David,Alan,Male,Caucasian,09/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +65386,75623,68486,PRETRIAL,Epstein,David,Alan,Male,Caucasian,09/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +65386,75623,68486,PRETRIAL,Epstein,David,Alan,Male,Caucasian,09/08/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +32893,75614,68477,PRETRIAL,Martin,Moses,NULL,Male,African-American,05/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/14 0:00,4,High,7,Risk of Violence,-0.73,9,High,New,1,0 +32893,75614,68477,PRETRIAL,Martin,Moses,NULL,Male,African-American,05/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/14 0:00,4,High,8,Risk of Recidivism,0.47,9,High,New,1,0 +32893,75614,68477,PRETRIAL,Martin,Moses,NULL,Male,African-American,05/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +23826,75632,68494,PRETRIAL,Donjoie,Kevin,NULL,Male,African-American,08/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +23826,75632,68494,PRETRIAL,Donjoie,Kevin,NULL,Male,African-American,08/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +23826,75632,68494,PRETRIAL,Donjoie,Kevin,NULL,Male,African-American,08/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +65390,75628,68490,PRETRIAL,Salisbury,Michael,NULL,Male,Caucasian,12/31/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/7/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +65390,75628,68490,PRETRIAL,Salisbury,Michael,NULL,Male,Caucasian,12/31/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/7/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +65390,75628,68490,PRETRIAL,Salisbury,Michael,NULL,Male,Caucasian,12/31/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65395,75635,68496,DRRD,Loubeau,Henry,Phillipe,Male,African-American,09/13/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +65395,75635,68496,DRRD,Loubeau,Henry,Phillipe,Male,African-American,09/13/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.73,10,High,New,1,0 +65395,75635,68496,DRRD,Loubeau,Henry,Phillipe,Male,African-American,09/13/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,New,1,0 +65378,75609,68472,PRETRIAL,Dejean,Sekeyia,NULL,Female,African-American,09/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +65378,75609,68472,PRETRIAL,Dejean,Sekeyia,NULL,Female,African-American,09/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +65378,75609,68472,PRETRIAL,Dejean,Sekeyia,NULL,Female,African-American,09/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50668,75616,68479,Probation,Gonzalez,Camilo,NULL,Male,Hispanic,05/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +50668,75616,68479,Probation,Gonzalez,Camilo,NULL,Male,Hispanic,05/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +50668,75616,68479,Probation,Gonzalez,Camilo,NULL,Male,Hispanic,05/06/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +9285,75607,68470,PRETRIAL,BENWAY,EDWARD,NULL,Male,Caucasian,08/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/7/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +9285,75607,68470,PRETRIAL,BENWAY,EDWARD,NULL,Male,Caucasian,08/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/7/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +9285,75607,68470,PRETRIAL,BENWAY,EDWARD,NULL,Male,Caucasian,08/21/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65392,75630,68492,DRRD,Newsome,Bravon,J,Male,African-American,04/23/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.82,9,High,New,1,0 +65392,75630,68492,DRRD,Newsome,Bravon,J,Male,African-American,04/23/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,7,Medium,New,1,0 +65392,75630,68492,DRRD,Newsome,Bravon,J,Male,African-American,04/23/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,1,Low,New,1,0 +65372,75601,68464,PRETRIAL,Laylor,Lashae,NULL,Female,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +65372,75601,68464,PRETRIAL,Laylor,Lashae,NULL,Female,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +65372,75601,68464,PRETRIAL,Laylor,Lashae,NULL,Female,African-American,07/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65377,75608,68471,PRETRIAL,Rodriguez,Ashli,Monique,Female,Caucasian,03/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/7/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +65377,75608,68471,PRETRIAL,Rodriguez,Ashli,Monique,Female,Caucasian,03/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/7/14 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +65377,75608,68471,PRETRIAL,Rodriguez,Ashli,Monique,Female,Caucasian,03/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65381,75615,68478,PRETRIAL,Jeanjules,Jeanherard,NULL,Male,Other,09/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +65381,75615,68478,PRETRIAL,Jeanjules,Jeanherard,NULL,Male,Other,09/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +65381,75615,68478,PRETRIAL,Jeanjules,Jeanherard,NULL,Male,Other,09/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65391,75629,68491,Probation,tyler,Largarious,Shunna,Male,African-American,12/04/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/7/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +65391,75629,68491,Probation,tyler,Largarious,Shunna,Male,African-American,12/04/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/7/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +65391,75629,68491,Probation,tyler,Largarious,Shunna,Male,African-American,12/04/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60000,75622,68485,PRETRIAL,Magana,Rafael,NULL,Male,Hispanic,05/15/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/7/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +60000,75622,68485,PRETRIAL,Magana,Rafael,NULL,Male,Hispanic,05/15/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/7/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +60000,75622,68485,PRETRIAL,Magana,Rafael,NULL,Male,Hispanic,05/15/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65389,75627,68489,Probation,Tierney,Lucus,NULL,Male,Caucasian,06/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +65389,75627,68489,Probation,Tierney,Lucus,NULL,Male,Caucasian,06/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +65389,75627,68489,Probation,Tierney,Lucus,NULL,Male,Caucasian,06/19/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65376,75606,68469,PRETRIAL,Justice,Steven,Ray,Male,Caucasian,07/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +65376,75606,68469,PRETRIAL,Justice,Steven,Ray,Male,Caucasian,07/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +65376,75606,68469,PRETRIAL,Justice,Steven,Ray,Male,Caucasian,07/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +55336,75610,68473,PRETRIAL,Paul,Rondha,NULL,Female,African-American,09/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +55336,75610,68473,PRETRIAL,Paul,Rondha,NULL,Female,African-American,09/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.8,10,High,New,1,0 +55336,75610,68473,PRETRIAL,Paul,Rondha,NULL,Female,African-American,09/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65387,75624,68487,Probation,altschuler,ronda,NULL,Female,Caucasian,12/18/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/7/14 0:00,1,Low,7,Risk of Violence,-4.25,1,Low,New,1,0 +65387,75624,68487,Probation,altschuler,ronda,NULL,Female,Caucasian,12/18/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/7/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +65387,75624,68487,Probation,altschuler,ronda,NULL,Female,Caucasian,12/18/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62795,75634,68495,PRETRIAL,forhan,shannon,NULL,Female,Caucasian,11/08/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,2,Medium,7,Risk of Violence,-3.17,1,Low,New,1,0 +62795,75634,68495,PRETRIAL,forhan,shannon,NULL,Female,Caucasian,11/08/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +62795,75634,68495,PRETRIAL,forhan,shannon,NULL,Female,Caucasian,11/08/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,New,1,0 +23381,75621,68484,PRETRIAL,Colas,Daniel,NULL,Male,African-American,09/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +23381,75621,68484,PRETRIAL,Colas,Daniel,NULL,Male,African-American,09/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +23381,75621,68484,PRETRIAL,Colas,Daniel,NULL,Male,African-American,09/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +41976,75603,68466,PRETRIAL,Mitchell,Lawrence,NULL,Male,African-American,06/14/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +41976,75603,68466,PRETRIAL,Mitchell,Lawrence,NULL,Male,African-American,06/14/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +41976,75603,68466,PRETRIAL,Mitchell,Lawrence,NULL,Male,African-American,06/14/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +65379,75613,68476,Probation,James,Ned,Wilson,Male,African-American,06/25/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/7/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +65379,75613,68476,Probation,James,Ned,Wilson,Male,African-American,06/25/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/7/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +65379,75613,68476,Probation,James,Ned,Wilson,Male,African-American,06/25/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65384,75619,68482,PRETRIAL,Fields,Lakasha,NULL,Female,African-American,12/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +65384,75619,68482,PRETRIAL,Fields,Lakasha,NULL,Female,African-American,12/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +65384,75619,68482,PRETRIAL,Fields,Lakasha,NULL,Female,African-American,12/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54998,75611,68474,Probation,Koscak,James,NULL,Male,Caucasian,05/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +54998,75611,68474,Probation,Koscak,James,NULL,Male,Caucasian,05/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +54998,75611,68474,Probation,Koscak,James,NULL,Male,Caucasian,05/14/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +65383,75618,68481,Probation,Neldon,Selvin,NULL,Male,African-American,03/28/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/7/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +65383,75618,68481,Probation,Neldon,Selvin,NULL,Male,African-American,03/28/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/7/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +65383,75618,68481,Probation,Neldon,Selvin,NULL,Male,African-American,03/28/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65375,75605,68468,PRETRIAL,Rodriguez,Bradley,Cruz,Male,Hispanic,08/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +65375,75605,68468,PRETRIAL,Rodriguez,Bradley,Cruz,Male,Hispanic,08/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +65375,75605,68468,PRETRIAL,Rodriguez,Bradley,Cruz,Male,Hispanic,08/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65405,75647,68507,PRETRIAL,Armour,Inakesha,Shakarra,Female,African-American,12/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/8/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +65405,75647,68507,PRETRIAL,Armour,Inakesha,Shakarra,Female,African-American,12/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/8/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +65405,75647,68507,PRETRIAL,Armour,Inakesha,Shakarra,Female,African-American,12/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65400,75642,68502,PRETRIAL,Adams,Kayron,Caeece,Male,African-American,09/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +65400,75642,68502,PRETRIAL,Adams,Kayron,Caeece,Male,African-American,09/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +65400,75642,68502,PRETRIAL,Adams,Kayron,Caeece,Male,African-American,09/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +19650,75660,18883,PRETRIAL,Mitchell,Elizabeth,NULL,Female,African-American,11/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/8/14 0:00,2,Medium,7,Risk of Violence,-2.77,2,Low,Copy,1,0 +19650,75660,18883,PRETRIAL,Mitchell,Elizabeth,NULL,Female,African-American,11/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,Copy,1,0 +19650,75660,18883,PRETRIAL,Mitchell,Elizabeth,NULL,Female,African-American,11/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/8/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +65412,75655,68514,PRETRIAL,ROACH,DARRELL,NULL,Male,African-American,08/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +65412,75655,68514,PRETRIAL,ROACH,DARRELL,NULL,Male,African-American,08/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +65412,75655,68514,PRETRIAL,ROACH,DARRELL,NULL,Male,African-American,08/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65403,75645,68505,Probation,Garcia Ochoa,Christian,NULL,Male,Hispanic,08/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/8/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +65403,75645,68505,Probation,Garcia Ochoa,Christian,NULL,Male,Hispanic,08/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/8/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +65403,75645,68505,Probation,Garcia Ochoa,Christian,NULL,Male,Hispanic,08/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65000,75640,68093,PRETRIAL,Youngblood,Reginald,NULL,Male,African-American,09/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,Copy,1,0 +65000,75640,68093,PRETRIAL,Youngblood,Reginald,NULL,Male,African-American,09/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,Copy,1,0 +65000,75640,68093,PRETRIAL,Youngblood,Reginald,NULL,Male,African-American,09/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +65414,75657,68516,Probation,pengsalood,apinyapirom,NULL,Female,Asian,03/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/8/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +65414,75657,68516,Probation,pengsalood,apinyapirom,NULL,Female,Asian,03/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/8/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +65414,75657,68516,Probation,pengsalood,apinyapirom,NULL,Female,Asian,03/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65401,75643,68503,PRETRIAL,Daniel,Larenz,NULL,Male,African-American,07/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.08,8,High,New,1,0 +65401,75643,68503,PRETRIAL,Daniel,Larenz,NULL,Male,African-American,07/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +65401,75643,68503,PRETRIAL,Daniel,Larenz,NULL,Male,African-American,07/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65408,75650,68509,Probation,Vassallo,Patricia,NULL,Female,Hispanic,09/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +65408,75650,68509,Probation,Vassallo,Patricia,NULL,Female,Hispanic,09/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +65408,75650,68509,Probation,Vassallo,Patricia,NULL,Female,Hispanic,09/29/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65407,75652,68511,PRETRIAL,MAYERS,VINCENT,NULL,Male,African-American,11/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +65407,75652,68511,PRETRIAL,MAYERS,VINCENT,NULL,Male,African-American,11/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +65407,75652,68511,PRETRIAL,MAYERS,VINCENT,NULL,Male,African-American,11/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65402,75644,68504,PRETRIAL,Means,Eric,NULL,Male,African-American,08/20/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +65402,75644,68504,PRETRIAL,Means,Eric,NULL,Male,African-American,08/20/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +65402,75644,68504,PRETRIAL,Means,Eric,NULL,Male,African-American,08/20/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65409,75651,68510,Probation,campbell,keri,NULL,Female,Caucasian,07/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +65409,75651,68510,Probation,campbell,keri,NULL,Female,Caucasian,07/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/14 0:00,1,Low,8,Risk of Recidivism,-0.65,5,Medium,New,1,0 +65409,75651,68510,Probation,campbell,keri,NULL,Female,Caucasian,07/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65415,75658,68517,PRETRIAL,AmickLafollette,Victoria,NULL,Female,Caucasian,10/25/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +65415,75658,68517,PRETRIAL,AmickLafollette,Victoria,NULL,Female,Caucasian,10/25/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +65415,75658,68517,PRETRIAL,AmickLafollette,Victoria,NULL,Female,Caucasian,10/25/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65397,75637,68498,PRETRIAL,Alt,Alan,NULL,Male,Caucasian,03/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +65397,75637,68498,PRETRIAL,Alt,Alan,NULL,Male,Caucasian,03/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +65397,75637,68498,PRETRIAL,Alt,Alan,NULL,Male,Caucasian,03/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +48223,75649,48898,PRETRIAL,Smith,Oshane,Oran,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/8/14 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,Copy,1,0 +48223,75649,48898,PRETRIAL,Smith,Oshane,Oran,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/8/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,Copy,1,0 +48223,75649,48898,PRETRIAL,Smith,Oshane,Oran,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +65406,75648,68508,PRETRIAL,Montgomery,Christopher,NULL,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,2,Medium,7,Risk of Violence,-1.26,7,Medium,New,1,0 +65406,75648,68508,PRETRIAL,Montgomery,Christopher,NULL,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +65406,75648,68508,PRETRIAL,Montgomery,Christopher,NULL,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +34691,75641,68501,PRETRIAL,wells,andy,NULL,Male,African-American,03/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,2,Medium,7,Risk of Violence,-1.55,6,Medium,New,1,0 +34691,75641,68501,PRETRIAL,wells,andy,NULL,Male,African-American,03/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +34691,75641,68501,PRETRIAL,wells,andy,NULL,Male,African-American,03/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65411,75654,68513,Probation,Vidal,Ainsworth,NULL,Male,African-American,10/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/8/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +65411,75654,68513,Probation,Vidal,Ainsworth,NULL,Male,African-American,10/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/8/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +65411,75654,68513,Probation,Vidal,Ainsworth,NULL,Male,African-American,10/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65413,75656,68515,Probation,SHORTT,CIELO,NULL,Male,Hispanic,03/20/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +65413,75656,68515,Probation,SHORTT,CIELO,NULL,Male,Hispanic,03/20/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +65413,75656,68515,Probation,SHORTT,CIELO,NULL,Male,Hispanic,03/20/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65404,75646,68506,PRETRIAL,Philips,Nikisha,NULL,Female,African-American,12/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +65404,75646,68506,PRETRIAL,Philips,Nikisha,NULL,Female,African-American,12/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +65404,75646,68506,PRETRIAL,Philips,Nikisha,NULL,Female,African-American,12/31/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65398,75638,68499,PRETRIAL,Pante,Adonte,NULL,Male,African-American,09/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.09,8,High,New,1,0 +65398,75638,68499,PRETRIAL,Pante,Adonte,NULL,Male,African-American,09/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +65398,75638,68499,PRETRIAL,Pante,Adonte,NULL,Male,African-American,09/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +51596,75659,68518,PRETRIAL,Jagpal,Sunil,NULL,Female,African-American,01/20/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/8/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +51596,75659,68518,PRETRIAL,Jagpal,Sunil,NULL,Female,African-American,01/20/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/8/14 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +51596,75659,68518,PRETRIAL,Jagpal,Sunil,NULL,Female,African-American,01/20/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/8/14 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +65417,75662,68520,PRETRIAL,Ritz,Daniel,NULL,Male,Caucasian,03/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +65417,75662,68520,PRETRIAL,Ritz,Daniel,NULL,Male,Caucasian,03/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +65417,75662,68520,PRETRIAL,Ritz,Daniel,NULL,Male,Caucasian,03/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/9/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65424,75669,68527,PRETRIAL,Burrows,Whitemore,Roscoe,Male,Caucasian,05/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,8/10/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +65424,75669,68527,PRETRIAL,Burrows,Whitemore,Roscoe,Male,Caucasian,05/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,8/10/14 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +65424,75669,68527,PRETRIAL,Burrows,Whitemore,Roscoe,Male,Caucasian,05/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,8/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65419,75664,68522,PRETRIAL,Albu,Conner,NULL,Male,Caucasian,03/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +65419,75664,68522,PRETRIAL,Albu,Conner,NULL,Male,Caucasian,03/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +65419,75664,68522,PRETRIAL,Albu,Conner,NULL,Male,Caucasian,03/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65422,75667,68525,PRETRIAL,JONES,JOHNNA,JULEA,Female,African-American,09/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +65422,75667,68525,PRETRIAL,JONES,JOHNNA,JULEA,Female,African-American,09/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +65422,75667,68525,PRETRIAL,JONES,JOHNNA,JULEA,Female,African-American,09/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59101,75670,68528,PRETRIAL,CEMELUS,CELOUES,NULL,Male,African-American,01/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,4,High,7,Risk of Violence,-0.67,9,High,New,1,0 +59101,75670,68528,PRETRIAL,CEMELUS,CELOUES,NULL,Male,African-American,01/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,4,High,8,Risk of Recidivism,0.38,9,High,New,1,0 +59101,75670,68528,PRETRIAL,CEMELUS,CELOUES,NULL,Male,African-American,01/31/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65420,75665,68523,PRETRIAL,Conley,Herbert,NULL,Male,Caucasian,02/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +65420,75665,68523,PRETRIAL,Conley,Herbert,NULL,Male,Caucasian,02/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +65420,75665,68523,PRETRIAL,Conley,Herbert,NULL,Male,Caucasian,02/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65425,75671,68529,PRETRIAL,CUELLAR,JUAN,CARLOS,Male,Caucasian,05/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +65425,75671,68529,PRETRIAL,CUELLAR,JUAN,CARLOS,Male,Caucasian,05/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +65425,75671,68529,PRETRIAL,CUELLAR,JUAN,CARLOS,Male,Caucasian,05/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65421,75666,68524,PRETRIAL,ALBELAEZ,LUIS,ENRIQUE,Male,Caucasian,05/20/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +65421,75666,68524,PRETRIAL,ALBELAEZ,LUIS,ENRIQUE,Male,Caucasian,05/20/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +65421,75666,68524,PRETRIAL,ALBELAEZ,LUIS,ENRIQUE,Male,Caucasian,05/20/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65423,75668,68526,PRETRIAL,NOTISE,NIKITA,AHAJALIA,Male,African-American,09/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +65423,75668,68526,PRETRIAL,NOTISE,NIKITA,AHAJALIA,Male,African-American,09/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +65423,75668,68526,PRETRIAL,NOTISE,NIKITA,AHAJALIA,Male,African-American,09/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/10/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65418,75663,68521,PRETRIAL,HILARION,JEAN,R,Male,Other,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/10/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +65418,75663,68521,PRETRIAL,HILARION,JEAN,R,Male,Other,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/10/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +65418,75663,68521,PRETRIAL,HILARION,JEAN,R,Male,Other,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65433,75681,68538,PRETRIAL,CABANAS,VERONICA,NULL,Female,Caucasian,06/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +65433,75681,68538,PRETRIAL,CABANAS,VERONICA,NULL,Female,Caucasian,06/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +65433,75681,68538,PRETRIAL,CABANAS,VERONICA,NULL,Female,Caucasian,06/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65451,75702,68556,PRETRIAL,Osorio,Jacqueline,NULL,Female,Caucasian,12/08/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +65451,75702,68556,PRETRIAL,Osorio,Jacqueline,NULL,Female,Caucasian,12/08/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +65451,75702,68556,PRETRIAL,Osorio,Jacqueline,NULL,Female,Caucasian,12/08/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65440,75689,68545,PRETRIAL,Lundy,John-Pierre,NULL,Male,African-American,12/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +65440,75689,68545,PRETRIAL,Lundy,John-Pierre,NULL,Male,African-American,12/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +65440,75689,68545,PRETRIAL,Lundy,John-Pierre,NULL,Male,African-American,12/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65428,75676,68533,PRETRIAL,Castellon,Nancy,Y,Female,Hispanic,01/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/11/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +65428,75676,68533,PRETRIAL,Castellon,Nancy,Y,Female,Hispanic,01/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/11/14 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +65428,75676,68533,PRETRIAL,Castellon,Nancy,Y,Female,Hispanic,01/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65453,75705,68559,Probation,Cruzmunoz,Alejandro,NULL,Male,Hispanic,09/05/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +65453,75705,68559,Probation,Cruzmunoz,Alejandro,NULL,Male,Hispanic,09/05/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +65453,75705,68559,Probation,Cruzmunoz,Alejandro,NULL,Male,Hispanic,09/05/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65434,75682,68539,PRETRIAL,McCarther,Marcus,Eugene,Male,African-American,02/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,2,Medium,7,Risk of Violence,-2.11,4,Low,New,1,0 +65434,75682,68539,PRETRIAL,McCarther,Marcus,Eugene,Male,African-American,02/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +65434,75682,68539,PRETRIAL,McCarther,Marcus,Eugene,Male,African-American,02/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +65448,75696,68551,Probation,Bloemer,Matheus,NULL,Male,Caucasian,06/08/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +65448,75696,68551,Probation,Bloemer,Matheus,NULL,Male,Caucasian,06/08/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +65448,75696,68551,Probation,Bloemer,Matheus,NULL,Male,Caucasian,06/08/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65450,75699,68554,PRETRIAL,mcbride,patrick,NULL,Male,African-American,11/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +65450,75699,68554,PRETRIAL,mcbride,patrick,NULL,Male,African-American,11/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +65450,75699,68554,PRETRIAL,mcbride,patrick,NULL,Male,African-American,11/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65430,75678,68535,PRETRIAL,PIERRE,WILBERT,NULL,Male,Other,12/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/11/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +65430,75678,68535,PRETRIAL,PIERRE,WILBERT,NULL,Male,Other,12/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/11/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +65430,75678,68535,PRETRIAL,PIERRE,WILBERT,NULL,Male,Other,12/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65443,75692,68548,Probation,Dawes,kimberly,NULL,Female,African-American,04/22/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +65443,75692,68548,Probation,Dawes,kimberly,NULL,Female,African-American,04/22/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +65443,75692,68548,Probation,Dawes,kimberly,NULL,Female,African-American,04/22/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60942,75703,68557,Probation,kurtgis,caryn,NULL,Female,Caucasian,03/28/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +60942,75703,68557,Probation,kurtgis,caryn,NULL,Female,Caucasian,03/28/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +60942,75703,68557,Probation,kurtgis,caryn,NULL,Female,Caucasian,03/28/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +875,75673,43115,Probation,Dibenedetto,Michael,NULL,Male,Caucasian,04/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/11/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,Copy,1,0 +875,75673,43115,Probation,Dibenedetto,Michael,NULL,Male,Caucasian,04/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/11/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,Copy,1,0 +875,75673,43115,Probation,Dibenedetto,Michael,NULL,Male,Caucasian,04/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/11/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +65432,75680,68537,PRETRIAL,Coleman,Lorraine,NULL,Female,Caucasian,03/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/11/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +65432,75680,68537,PRETRIAL,Coleman,Lorraine,NULL,Female,Caucasian,03/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/11/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +65432,75680,68537,PRETRIAL,Coleman,Lorraine,NULL,Female,Caucasian,03/05/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65444,75694,68550,Probation,Ford,Julianne,NULL,Female,Caucasian,02/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +65444,75694,68550,Probation,Ford,Julianne,NULL,Female,Caucasian,02/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +65444,75694,68550,Probation,Ford,Julianne,NULL,Female,Caucasian,02/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +6831,75701,68555,PRETRIAL,DAVIES,WALTER,FREDERICK,Male,African-American,07/10/59,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +6831,75701,68555,PRETRIAL,DAVIES,WALTER,FREDERICK,Male,African-American,07/10/59,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +6831,75701,68555,PRETRIAL,DAVIES,WALTER,FREDERICK,Male,African-American,07/10/59,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +41218,44742,40890,Probation,cruz,MIGUEL,NULL,Male,Hispanic,10/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +41218,44742,40890,Probation,cruz,MIGUEL,NULL,Male,Hispanic,10/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +41218,44742,40890,Probation,cruz,MIGUEL,NULL,Male,Hispanic,10/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65431,75679,68536,PRETRIAL,Williams,Dexter,NULL,Male,African-American,01/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.15,4,Low,New,1,0 +65431,75679,68536,PRETRIAL,Williams,Dexter,NULL,Male,African-American,01/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +65431,75679,68536,PRETRIAL,Williams,Dexter,NULL,Male,African-American,01/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65439,75688,68544,PRETRIAL,Shiner,Drew,NULL,Male,Caucasian,03/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +65439,75688,68544,PRETRIAL,Shiner,Drew,NULL,Male,Caucasian,03/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +65439,75688,68544,PRETRIAL,Shiner,Drew,NULL,Male,Caucasian,03/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65455,75707,68561,Probation,MASSENBURG,SHELBY,NULL,Male,African-American,11/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/11/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +65455,75707,68561,Probation,MASSENBURG,SHELBY,NULL,Male,African-American,11/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/11/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +65455,75707,68561,Probation,MASSENBURG,SHELBY,NULL,Male,African-American,11/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +65438,75686,68543,Probation,Etienne,Steve,NULL,Male,African-American,04/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/11/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +65438,75686,68543,Probation,Etienne,Steve,NULL,Male,African-American,04/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/11/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +65438,75686,68543,Probation,Etienne,Steve,NULL,Male,African-American,04/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +6418,75674,68531,DRRD,Ware,Vincent,NULL,Male,African-American,06/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +6418,75674,68531,DRRD,Ware,Vincent,NULL,Male,African-American,06/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +6418,75674,68531,DRRD,Ware,Vincent,NULL,Male,African-American,06/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65452,75704,68558,Probation,erickson,james,NULL,Male,Caucasian,07/05/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/11/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +65452,75704,68558,Probation,erickson,james,NULL,Male,Caucasian,07/05/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/11/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +65452,75704,68558,Probation,erickson,james,NULL,Male,Caucasian,07/05/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65442,75691,68547,Probation,Sarchiz,John,NULL,Male,Hispanic,09/03/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +65442,75691,68547,Probation,Sarchiz,John,NULL,Male,Hispanic,09/03/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +65442,75691,68547,Probation,Sarchiz,John,NULL,Male,Hispanic,09/03/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65437,75700,68542,PRETRIAL,DIXON,KHADIJAH,NULL,Female,African-American,02/16/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/11/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,Copy,1,0 +65437,75700,68542,PRETRIAL,DIXON,KHADIJAH,NULL,Female,African-American,02/16/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.82,4,Low,Copy,1,0 +65437,75700,68542,PRETRIAL,DIXON,KHADIJAH,NULL,Female,African-American,02/16/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/11/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +41218,75695,40890,Probation,cruz,MIGUEL,NULL,Male,Hispanic,10/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,2,Medium,7,Risk of Violence,-2.45,3,Low,Copy,1,0 +41218,75695,40890,Probation,cruz,MIGUEL,NULL,Male,Hispanic,10/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,Copy,1,0 +41218,75695,40890,Probation,cruz,MIGUEL,NULL,Male,Hispanic,10/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +65445,75693,68549,Probation,lopez,fernando,NULL,Male,Hispanic,12/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +65445,75693,68549,Probation,lopez,fernando,NULL,Male,Hispanic,12/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +65445,75693,68549,Probation,lopez,fernando,NULL,Male,Hispanic,12/01/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65410,75683,68540,PRETRIAL,Allen,Sedainel,NULL,Male,African-American,04/16/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/11/14 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +65410,75683,68540,PRETRIAL,Allen,Sedainel,NULL,Male,African-American,04/16/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +65410,75683,68540,PRETRIAL,Allen,Sedainel,NULL,Male,African-American,04/16/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/11/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +65449,75698,68553,PRETRIAL,FARRIS,EUGENE,NULL,Male,African-American,01/14/97,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +65449,75698,68553,PRETRIAL,FARRIS,EUGENE,NULL,Male,African-American,01/14/97,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +65449,75698,68553,PRETRIAL,FARRIS,EUGENE,NULL,Male,African-American,01/14/97,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65441,75690,68546,PRETRIAL,Gardner,Carol,NULL,Female,African-American,12/25/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +65441,75690,68546,PRETRIAL,Gardner,Carol,NULL,Female,African-American,12/25/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +65441,75690,68546,PRETRIAL,Gardner,Carol,NULL,Female,African-American,12/25/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65427,75675,68532,PRETRIAL,Antonio,Shaquille,NULL,Male,African-American,10/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +65427,75675,68532,PRETRIAL,Antonio,Shaquille,NULL,Male,African-American,10/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +65427,75675,68532,PRETRIAL,Antonio,Shaquille,NULL,Male,African-American,10/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65429,75677,68534,PRETRIAL,TELFORT,BRANDON,RASHAD,Male,African-American,12/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +65429,75677,68534,PRETRIAL,TELFORT,BRANDON,RASHAD,Male,African-American,12/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +65429,75677,68534,PRETRIAL,TELFORT,BRANDON,RASHAD,Male,African-American,12/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65459,75711,68565,PRETRIAL,Williams,Shaqita,S,Female,African-American,10/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +65459,75711,68565,PRETRIAL,Williams,Shaqita,S,Female,African-American,10/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,8,High,New,1,0 +65459,75711,68565,PRETRIAL,Williams,Shaqita,S,Female,African-American,10/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64968,75719,68058,PRETRIAL,rand,michael,NULL,Male,Caucasian,02/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,Copy,1,0 +64968,75719,68058,PRETRIAL,rand,michael,NULL,Male,Caucasian,02/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,Copy,1,0 +64968,75719,68058,PRETRIAL,rand,michael,NULL,Male,Caucasian,02/15/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +65470,75727,68579,Probation,HOLLOMAN,BRANDON,SHAROD,Male,African-American,09/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +65470,75727,68579,Probation,HOLLOMAN,BRANDON,SHAROD,Male,African-American,09/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +65470,75727,68579,Probation,HOLLOMAN,BRANDON,SHAROD,Male,African-American,09/17/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65475,75735,68586,PRETRIAL,Dooley,Charles,NULL,Male,African-American,07/13/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/12/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +65475,75735,68586,PRETRIAL,Dooley,Charles,NULL,Male,African-American,07/13/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/12/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +65475,75735,68586,PRETRIAL,Dooley,Charles,NULL,Male,African-American,07/13/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65462,75714,68568,PRETRIAL,Pearce,Karl,NULL,Male,African-American,04/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +65462,75714,68568,PRETRIAL,Pearce,Karl,NULL,Male,African-American,04/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.9,10,High,New,1,0 +65462,75714,68568,PRETRIAL,Pearce,Karl,NULL,Male,African-American,04/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +56891,75732,68583,PRETRIAL,Falkman,Cullen,NULL,Male,Caucasian,06/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/12/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +56891,75732,68583,PRETRIAL,Falkman,Cullen,NULL,Male,Caucasian,06/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/12/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +56891,75732,68583,PRETRIAL,Falkman,Cullen,NULL,Male,Caucasian,06/07/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65468,75725,68577,PRETRIAL,Breault,Shelly,NULL,Female,Caucasian,07/17/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +65468,75725,68577,PRETRIAL,Breault,Shelly,NULL,Female,Caucasian,07/17/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/14 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +65468,75725,68577,PRETRIAL,Breault,Shelly,NULL,Female,Caucasian,07/17/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65465,75721,68573,Probation,NEWMAN,DENISE,NULL,Male,Caucasian,08/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +65465,75721,68573,Probation,NEWMAN,DENISE,NULL,Male,Caucasian,08/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +65465,75721,68573,Probation,NEWMAN,DENISE,NULL,Male,Caucasian,08/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65457,75709,68563,PRETRIAL,Rivelli,James,V,Male,Caucasian,07/02/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/12/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +65457,75709,68563,PRETRIAL,Rivelli,James,V,Male,Caucasian,07/02/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/12/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +65457,75709,68563,PRETRIAL,Rivelli,James,V,Male,Caucasian,07/02/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +13544,75716,68570,PRETRIAL,Young,Alfonso,NULL,Male,African-American,06/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,New,1,0 +13544,75716,68570,PRETRIAL,Young,Alfonso,NULL,Male,African-American,06/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +13544,75716,68570,PRETRIAL,Young,Alfonso,NULL,Male,African-American,06/30/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +65477,75737,68588,Probation,flamenco,Olga,Jeanneth,Female,Hispanic,07/28/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/12/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +65477,75737,68588,Probation,flamenco,Olga,Jeanneth,Female,Hispanic,07/28/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/12/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +65477,75737,68588,Probation,flamenco,Olga,Jeanneth,Female,Hispanic,07/28/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65472,75730,68581,PRETRIAL,Hall,Tervon,NULL,Male,African-American,01/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +65472,75730,68581,PRETRIAL,Hall,Tervon,NULL,Male,African-American,01/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +65472,75730,68581,PRETRIAL,Hall,Tervon,NULL,Male,African-American,01/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65456,75708,68562,PRETRIAL,DORSAINT,MICHENOSE,NULL,Female,Other,08/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +65456,75708,68562,PRETRIAL,DORSAINT,MICHENOSE,NULL,Female,Other,08/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +65456,75708,68562,PRETRIAL,DORSAINT,MICHENOSE,NULL,Female,Other,08/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65463,75715,68569,PRETRIAL,WILLIAMS,CHARLITHA,EBONY,Female,Other,03/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/12/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +65463,75715,68569,PRETRIAL,WILLIAMS,CHARLITHA,EBONY,Female,Other,03/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +65463,75715,68569,PRETRIAL,WILLIAMS,CHARLITHA,EBONY,Female,Other,03/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/12/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +58250,75722,68574,PRETRIAL,Renteria,Meyer,Francisco,Male,Hispanic,04/30/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/12/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +58250,75722,68574,PRETRIAL,Renteria,Meyer,Francisco,Male,Hispanic,04/30/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/12/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +58250,75722,68574,PRETRIAL,Renteria,Meyer,Francisco,Male,Hispanic,04/30/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65467,75724,68576,PRETRIAL,MARQUEZ,THEO,NULL,Male,Caucasian,07/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +65467,75724,68576,PRETRIAL,MARQUEZ,THEO,NULL,Male,Caucasian,07/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +65467,75724,68576,PRETRIAL,MARQUEZ,THEO,NULL,Male,Caucasian,07/06/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65464,75717,68571,Probation,Odonnell,Heather,NULL,Female,Caucasian,12/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +65464,75717,68571,Probation,Odonnell,Heather,NULL,Female,Caucasian,12/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +65464,75717,68571,Probation,Odonnell,Heather,NULL,Female,Caucasian,12/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65461,75713,68567,PRETRIAL,Bucholtz,Melissa,Marie,Female,Caucasian,07/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +65461,75713,68567,PRETRIAL,Bucholtz,Melissa,Marie,Female,Caucasian,07/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,10,High,New,1,0 +65461,75713,68567,PRETRIAL,Bucholtz,Melissa,Marie,Female,Caucasian,07/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65203,75734,68585,PRETRIAL,DERIENZO,NICOLE,NULL,Female,Caucasian,02/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +65203,75734,68585,PRETRIAL,DERIENZO,NICOLE,NULL,Female,Caucasian,02/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +65203,75734,68585,PRETRIAL,DERIENZO,NICOLE,NULL,Female,Caucasian,02/27/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64423,75739,68590,PRETRIAL,Wilson,Corey,NULL,Male,African-American,07/19/69,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,8/12/14 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +64423,75739,68590,PRETRIAL,Wilson,Corey,NULL,Male,African-American,07/19/69,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,8/12/14 0:00,4,High,8,Risk of Recidivism,0.34,8,High,New,1,0 +64423,75739,68590,PRETRIAL,Wilson,Corey,NULL,Male,African-American,07/19/69,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,8/12/14 0:00,4,High,18,Risk of Failure to Appear,22,4,Low,New,1,0 +61136,75718,68572,PRETRIAL,HERNANDEZ,ROLFI,NULL,Male,Hispanic,06/27/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/12/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +61136,75718,68572,PRETRIAL,HERNANDEZ,ROLFI,NULL,Male,Hispanic,06/27/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/12/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +61136,75718,68572,PRETRIAL,HERNANDEZ,ROLFI,NULL,Male,Hispanic,06/27/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +23443,75720,22637,PRETRIAL,MINNITI,JOSEPH,NULL,Male,Caucasian,11/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/14 0:00,4,High,7,Risk of Violence,-1.13,8,High,Copy,1,0 +23443,75720,22637,PRETRIAL,MINNITI,JOSEPH,NULL,Male,Caucasian,11/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/14 0:00,4,High,8,Risk of Recidivism,0.13,8,High,Copy,1,0 +23443,75720,22637,PRETRIAL,MINNITI,JOSEPH,NULL,Male,Caucasian,11/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +65469,75726,68578,PRETRIAL,RAMOSOTOYA,HERMAN,NULL,Male,Hispanic,04/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/12/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +65469,75726,68578,PRETRIAL,RAMOSOTOYA,HERMAN,NULL,Male,Hispanic,04/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/12/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +65469,75726,68578,PRETRIAL,RAMOSOTOYA,HERMAN,NULL,Male,Hispanic,04/05/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65474,75733,68584,Probation,Broder,Christina,marie,Female,Caucasian,01/19/74,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/12/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +65474,75733,68584,Probation,Broder,Christina,marie,Female,Caucasian,01/19/74,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/12/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +65474,75733,68584,Probation,Broder,Christina,marie,Female,Caucasian,01/19/74,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65460,75712,68566,PRETRIAL,Dowe,Catherine,NULL,Female,African-American,02/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +65460,75712,68566,PRETRIAL,Dowe,Catherine,NULL,Female,African-American,02/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/14 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +65460,75712,68566,PRETRIAL,Dowe,Catherine,NULL,Female,African-American,02/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65466,75723,68575,Probation,Lerczak,Frank,NULL,Male,Caucasian,03/14/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +65466,75723,68575,Probation,Lerczak,Frank,NULL,Male,Caucasian,03/14/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +65466,75723,68575,Probation,Lerczak,Frank,NULL,Male,Caucasian,03/14/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65476,75736,68587,Probation,BURNAP,PATRICK,NULL,Male,Caucasian,05/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +65476,75736,68587,Probation,BURNAP,PATRICK,NULL,Male,Caucasian,05/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +65476,75736,68587,Probation,BURNAP,PATRICK,NULL,Male,Caucasian,05/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +65458,75710,68564,PRETRIAL,GLINTON,GERALD,D,Male,African-American,09/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.07,4,Low,New,1,0 +65458,75710,68564,PRETRIAL,GLINTON,GERALD,D,Male,African-American,09/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.04,10,High,New,1,0 +65458,75710,68564,PRETRIAL,GLINTON,GERALD,D,Male,African-American,09/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +65471,75728,68580,PRETRIAL,velasquez,brandon,NULL,Male,Caucasian,09/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.22,8,High,New,1,0 +65471,75728,68580,PRETRIAL,velasquez,brandon,NULL,Male,Caucasian,09/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +65471,75728,68580,PRETRIAL,velasquez,brandon,NULL,Male,Caucasian,09/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65506,75778,68624,Probation,Dixon,Devon,NULL,Male,African-American,03/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/13/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +65506,75778,68624,Probation,Dixon,Devon,NULL,Male,African-American,03/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/13/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +65506,75778,68624,Probation,Dixon,Devon,NULL,Male,African-American,03/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54431,74881,67829,PRETRIAL,Miller,Ivory,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +54431,74881,67829,PRETRIAL,Miller,Ivory,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,9,High,New,1,0 +54431,74881,67829,PRETRIAL,Miller,Ivory,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65499,75770,68617,PRETRIAL,Peters,Craig,NULL,Male,Caucasian,11/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +65499,75770,68617,PRETRIAL,Peters,Craig,NULL,Male,Caucasian,11/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +65499,75770,68617,PRETRIAL,Peters,Craig,NULL,Male,Caucasian,11/11/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65489,75757,68606,PRETRIAL,Lubin,Ivan,NULL,Male,African-American,04/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +65489,75757,68606,PRETRIAL,Lubin,Ivan,NULL,Male,African-American,04/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +65489,75757,68606,PRETRIAL,Lubin,Ivan,NULL,Male,African-American,04/15/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65483,75747,68597,PRETRIAL,MCCRAY,KEITH,LEONARD,Male,African-American,09/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +65483,75747,68597,PRETRIAL,MCCRAY,KEITH,LEONARD,Male,African-American,09/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +65483,75747,68597,PRETRIAL,MCCRAY,KEITH,LEONARD,Male,African-American,09/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64737,75762,67792,PRETRIAL,Flowers,Tyler,NULL,Male,African-American,04/18/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,4,High,7,Risk of Violence,-0.24,10,High,Copy,1,0 +64737,75762,67792,PRETRIAL,Flowers,Tyler,NULL,Male,African-American,04/18/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,4,High,8,Risk of Recidivism,0.77,10,High,Copy,1,0 +64737,75762,67792,PRETRIAL,Flowers,Tyler,NULL,Male,African-American,04/18/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +65511,75783,68629,PRETRIAL,DINUNNO,APRIL,NULL,Female,Caucasian,04/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +65511,75783,68629,PRETRIAL,DINUNNO,APRIL,NULL,Female,Caucasian,04/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +65511,75783,68629,PRETRIAL,DINUNNO,APRIL,NULL,Female,Caucasian,04/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65479,75741,68592,PRETRIAL,Rivera,Natasha,A,Female,African-American,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +65479,75741,68592,PRETRIAL,Rivera,Natasha,A,Female,African-American,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +65479,75741,68592,PRETRIAL,Rivera,Natasha,A,Female,African-American,06/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65504,75775,68622,PRETRIAL,WILLIAMS,PRICELLA,NULL,Female,African-American,09/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +65504,75775,68622,PRETRIAL,WILLIAMS,PRICELLA,NULL,Female,African-American,09/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +65504,75775,68622,PRETRIAL,WILLIAMS,PRICELLA,NULL,Female,African-American,09/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65488,75754,68603,PRETRIAL,Strobridge,Darren,Jermaine,Male,African-American,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +65488,75754,68603,PRETRIAL,Strobridge,Darren,Jermaine,Male,African-American,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +65488,75754,68603,PRETRIAL,Strobridge,Darren,Jermaine,Male,African-American,10/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65491,75759,68608,PRETRIAL,TAYLOR,ROBERT,GREGORY,Male,Caucasian,12/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +65491,75759,68608,PRETRIAL,TAYLOR,ROBERT,GREGORY,Male,Caucasian,12/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +65491,75759,68608,PRETRIAL,TAYLOR,ROBERT,GREGORY,Male,Caucasian,12/14/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65497,75768,68615,PRETRIAL,Kelmann,Alexis,NULL,Female,Caucasian,10/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +65497,75768,68615,PRETRIAL,Kelmann,Alexis,NULL,Female,Caucasian,10/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +65497,75768,68615,PRETRIAL,Kelmann,Alexis,NULL,Female,Caucasian,10/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +29781,75755,68604,PRETRIAL,ELMA,JEAN,C,Male,African-American,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.24,8,High,New,1,0 +29781,75755,68604,PRETRIAL,ELMA,JEAN,C,Male,African-American,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +29781,75755,68604,PRETRIAL,ELMA,JEAN,C,Male,African-American,11/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +51726,75764,68611,Broward County,test,test,NULL,Male,Caucasian,01/01/58,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.08,8,High,New,1,0 +51726,75764,68611,Broward County,test,test,NULL,Male,Caucasian,01/01/58,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.41,4,Low,New,1,0 +51726,75764,68611,Broward County,test,test,NULL,Male,Caucasian,01/01/58,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,8,High,New,1,0 +65513,75785,68631,PRETRIAL,Dasilva,Sebastiao,NULL,Male,Hispanic,03/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/13/14 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +65513,75785,68631,PRETRIAL,Dasilva,Sebastiao,NULL,Male,Hispanic,03/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/13/14 0:00,1,Low,8,Risk of Recidivism,-2.81,1,Low,New,1,0 +65513,75785,68631,PRETRIAL,Dasilva,Sebastiao,NULL,Male,Hispanic,03/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65500,75771,68618,Probation,Betancourt,Jodie,NULL,Female,Caucasian,08/16/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/13/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +65500,75771,68618,Probation,Betancourt,Jodie,NULL,Female,Caucasian,08/16/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/13/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +65500,75771,68618,Probation,Betancourt,Jodie,NULL,Female,Caucasian,08/16/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65501,75773,68620,Probation,Pierre,Kensley,NULL,Male,African-American,09/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +65501,75773,68620,Probation,Pierre,Kensley,NULL,Male,African-American,09/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +65501,75773,68620,Probation,Pierre,Kensley,NULL,Male,African-American,09/01/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +45617,75743,45900,PRETRIAL,Hall,Cleophas,James,Male,African-American,12/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,Copy,1,0 +45617,75743,45900,PRETRIAL,Hall,Cleophas,James,Male,African-American,12/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,Copy,1,0 +45617,75743,45900,PRETRIAL,Hall,Cleophas,James,Male,African-American,12/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +65481,75745,68595,PRETRIAL,grey,mary,brinson,Female,African-American,04/27/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +65481,75745,68595,PRETRIAL,grey,mary,brinson,Female,African-American,04/27/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +65481,75745,68595,PRETRIAL,grey,mary,brinson,Female,African-American,04/27/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65485,75750,68599,PRETRIAL,MORALES,JOSE,ANTONIO,Male,Caucasian,11/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,Copy,1,0 +65485,75750,68599,PRETRIAL,MORALES,JOSE,ANTONIO,Male,Caucasian,11/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,Copy,1,0 +65485,75750,68599,PRETRIAL,MORALES,JOSE,ANTONIO,Male,Caucasian,11/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +65487,75752,68601,PRETRIAL,Mills,Tashoni,Patrice,Male,African-American,11/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +65487,75752,68601,PRETRIAL,Mills,Tashoni,Patrice,Male,African-American,11/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +65487,75752,68601,PRETRIAL,Mills,Tashoni,Patrice,Male,African-American,11/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65508,75780,68626,PRETRIAL,Navarro,Christian,NULL,Male,Hispanic,07/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +65508,75780,68626,PRETRIAL,Navarro,Christian,NULL,Male,Hispanic,07/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +65508,75780,68626,PRETRIAL,Navarro,Christian,NULL,Male,Hispanic,07/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Residential Program,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +12699,75744,68594,PRETRIAL,scott,keanorris,NULL,Male,African-American,01/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,4,High,7,Risk of Violence,-0.31,10,High,New,1,0 +12699,75744,68594,PRETRIAL,scott,keanorris,NULL,Male,African-American,01/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,4,High,8,Risk of Recidivism,0.67,10,High,New,1,0 +12699,75744,68594,PRETRIAL,scott,keanorris,NULL,Male,African-American,01/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65486,75751,68600,PRETRIAL,Francois,Kervens,Wisly,Male,Other,05/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +65486,75751,68600,PRETRIAL,Francois,Kervens,Wisly,Male,Other,05/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +65486,75751,68600,PRETRIAL,Francois,Kervens,Wisly,Male,Other,05/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +2668,75758,68607,PRETRIAL,corprew,david,roberts,Male,African-American,04/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.26,3,Low,New,1,0 +2668,75758,68607,PRETRIAL,corprew,david,roberts,Male,African-American,04/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.08,10,High,New,1,0 +2668,75758,68607,PRETRIAL,corprew,david,roberts,Male,African-American,04/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,38,10,High,New,1,0 +65502,75772,68619,PRETRIAL,BLANDFORD,ALEXANDER,NULL,Male,Hispanic,12/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +65502,75772,68619,PRETRIAL,BLANDFORD,ALEXANDER,NULL,Male,Hispanic,12/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +65502,75772,68619,PRETRIAL,BLANDFORD,ALEXANDER,NULL,Male,Hispanic,12/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65482,75746,68596,PRETRIAL,Richardson,Damieth,Lamont,Male,African-American,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,4,High,7,Risk of Violence,-0.31,10,High,New,1,0 +65482,75746,68596,PRETRIAL,Richardson,Damieth,Lamont,Male,African-American,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,4,High,8,Risk of Recidivism,0.58,9,High,New,1,0 +65482,75746,68596,PRETRIAL,Richardson,Damieth,Lamont,Male,African-American,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,4,High,18,Risk of Failure to Appear,37,10,High,New,1,0 +65493,75763,68610,Probation,Maragh,Brandon,Joseph,Male,Asian,12/14/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +65493,75763,68610,Probation,Maragh,Brandon,Joseph,Male,Asian,12/14/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +65493,75763,68610,Probation,Maragh,Brandon,Joseph,Male,Asian,12/14/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65509,75781,68627,Probation,corvalan,courney,NULL,Female,Caucasian,12/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/14 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +65509,75781,68627,Probation,corvalan,courney,NULL,Female,Caucasian,12/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,7,Medium,New,1,0 +65509,75781,68627,Probation,corvalan,courney,NULL,Female,Caucasian,12/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +65480,75742,68593,PRETRIAL,JENKINS,JOVEL,ALEXANDRIX,Male,African-American,09/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +65480,75742,68593,PRETRIAL,JENKINS,JOVEL,ALEXANDRIX,Male,African-American,09/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +65480,75742,68593,PRETRIAL,JENKINS,JOVEL,ALEXANDRIX,Male,African-American,09/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65492,75760,68609,PRETRIAL,Rodulfo,Nikiesha,NULL,Female,African-American,08/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +65492,75760,68609,PRETRIAL,Rodulfo,Nikiesha,NULL,Female,African-American,08/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +65492,75760,68609,PRETRIAL,Rodulfo,Nikiesha,NULL,Female,African-American,08/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65510,75782,68628,PRETRIAL,MATUSKA,JAMES,NULL,Male,Caucasian,01/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +65510,75782,68628,PRETRIAL,MATUSKA,JAMES,NULL,Male,Caucasian,01/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +65510,75782,68628,PRETRIAL,MATUSKA,JAMES,NULL,Male,Caucasian,01/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58795,75753,68602,PRETRIAL,Mckennie,Edward,NULL,Male,African-American,09/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,New,1,0 +58795,75753,68602,PRETRIAL,Mckennie,Edward,NULL,Male,African-American,09/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +58795,75753,68602,PRETRIAL,Mckennie,Edward,NULL,Male,African-American,09/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65495,75766,68613,Probation,Lopez,Christopher,NULL,Male,Hispanic,01/02/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/14 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +65495,75766,68613,Probation,Lopez,Christopher,NULL,Male,Hispanic,01/02/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +65495,75766,68613,Probation,Lopez,Christopher,NULL,Male,Hispanic,01/02/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/13/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65478,75740,68591,PRETRIAL,"Lindor, Sr",Meres,NULL,Male,Other,07/30/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +65478,75740,68591,PRETRIAL,"Lindor, Sr",Meres,NULL,Male,Other,07/30/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +65478,75740,68591,PRETRIAL,"Lindor, Sr",Meres,NULL,Male,Other,07/30/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65503,75774,68621,PRETRIAL,Gunuskey,Thomas,William,Male,Caucasian,02/18/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +65503,75774,68621,PRETRIAL,Gunuskey,Thomas,William,Male,Caucasian,02/18/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,8,Risk of Recidivism,-2.65,1,Low,New,1,0 +65503,75774,68621,PRETRIAL,Gunuskey,Thomas,William,Male,Caucasian,02/18/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65498,75769,68616,PRETRIAL,Lipner,Ryan,Adam,Male,Caucasian,09/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/13/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +65498,75769,68616,PRETRIAL,Lipner,Ryan,Adam,Male,Caucasian,09/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/13/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +65498,75769,68616,PRETRIAL,Lipner,Ryan,Adam,Male,Caucasian,09/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +54431,75776,67829,PRETRIAL,Miller,Ivory,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,Copy,1,0 +54431,75776,67829,PRETRIAL,Miller,Ivory,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.68,10,High,Copy,1,0 +54431,75776,67829,PRETRIAL,Miller,Ivory,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +65484,75748,68598,PRETRIAL,JeanPierre,David,loucito,Male,Other,04/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/13/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +65484,75748,68598,PRETRIAL,JeanPierre,David,loucito,Male,Other,04/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/13/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +65484,75748,68598,PRETRIAL,JeanPierre,David,loucito,Male,Other,04/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65505,75777,68623,PRETRIAL,Suckie,Rohan,Rampal,Male,Other,07/28/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +65505,75777,68623,PRETRIAL,Suckie,Rohan,Rampal,Male,Other,07/28/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,1,Low,8,Risk of Recidivism,-2.58,1,Low,New,1,0 +65505,75777,68623,PRETRIAL,Suckie,Rohan,Rampal,Male,Other,07/28/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65512,75784,68630,Probation,CALVARESE,BRIAN,C,Male,Caucasian,07/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/13/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +65512,75784,68630,Probation,CALVARESE,BRIAN,C,Male,Caucasian,07/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/13/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +65512,75784,68630,Probation,CALVARESE,BRIAN,C,Male,Caucasian,07/10/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65490,75756,68605,PRETRIAL,HURTADO,ENRIQUE,NULL,Male,Caucasian,11/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +65490,75756,68605,PRETRIAL,HURTADO,ENRIQUE,NULL,Male,Caucasian,11/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +65490,75756,68605,PRETRIAL,HURTADO,ENRIQUE,NULL,Male,Caucasian,11/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/13/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52668,75790,68636,PRETRIAL,LOUIS,COURTNEY,NULL,Male,African-American,05/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +52668,75790,68636,PRETRIAL,LOUIS,COURTNEY,NULL,Male,African-American,05/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +52668,75790,68636,PRETRIAL,LOUIS,COURTNEY,NULL,Male,African-American,05/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65527,75805,68649,Probation,HOLMES,GEARRARD,NULL,Male,African-American,11/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/14/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +65527,75805,68649,Probation,HOLMES,GEARRARD,NULL,Male,African-American,11/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/14/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +65527,75805,68649,Probation,HOLMES,GEARRARD,NULL,Male,African-American,11/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65529,75811,68652,PRETRIAL,Leon,Orlando,NULL,Male,Caucasian,07/10/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/14/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +65529,75811,68652,PRETRIAL,Leon,Orlando,NULL,Male,Caucasian,07/10/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/14/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +65529,75811,68652,PRETRIAL,Leon,Orlando,NULL,Male,Caucasian,07/10/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65534,75818,68659,Probation,McGauley,Michelle,NULL,Female,African-American,05/28/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +65534,75818,68659,Probation,McGauley,Michelle,NULL,Female,African-American,05/28/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +65534,75818,68659,Probation,McGauley,Michelle,NULL,Female,African-American,05/28/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +65522,75797,68642,Probation,Henry,Lanival,E,Male,African-American,12/13/51,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/14/14 0:00,1,Low,7,Risk of Violence,-4.34,1,Low,New,1,0 +65522,75797,68642,Probation,Henry,Lanival,E,Male,African-American,12/13/51,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/14/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +65522,75797,68642,Probation,Henry,Lanival,E,Male,African-American,12/13/51,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65523,75798,68643,Probation,Gawrych,Christopher,NULL,Male,Caucasian,11/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +65523,75798,68643,Probation,Gawrych,Christopher,NULL,Male,Caucasian,11/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +65523,75798,68643,Probation,Gawrych,Christopher,NULL,Male,Caucasian,11/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +62795,75819,68495,PRETRIAL,forhan,shannon,NULL,Female,Caucasian,11/08/65,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,8/14/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +62795,75819,68495,PRETRIAL,forhan,shannon,NULL,Female,Caucasian,11/08/65,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,8/14/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +62795,75819,68495,PRETRIAL,forhan,shannon,NULL,Female,Caucasian,11/08/65,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65514,75787,68633,PRETRIAL,Jules,Judith,Jean,Female,African-American,10/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +65514,75787,68633,PRETRIAL,Jules,Judith,Jean,Female,African-American,10/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +65514,75787,68633,PRETRIAL,Jules,Judith,Jean,Female,African-American,10/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65520,75795,68640,Probation,WARD,DAWN,C,Female,Caucasian,01/17/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +65520,75795,68640,Probation,WARD,DAWN,C,Female,Caucasian,01/17/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +65520,75795,68640,Probation,WARD,DAWN,C,Female,Caucasian,01/17/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65042,75792,68136,PRETRIAL,Beaver,Donald,NULL,Male,Caucasian,09/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/14/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,Copy,1,0 +65042,75792,68136,PRETRIAL,Beaver,Donald,NULL,Male,Caucasian,09/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/14/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,Copy,1,0 +65042,75792,68136,PRETRIAL,Beaver,Donald,NULL,Male,Caucasian,09/09/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +65526,75803,68647,PRETRIAL,Douze,Nicolas,NULL,Male,African-American,07/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +65526,75803,68647,PRETRIAL,Douze,Nicolas,NULL,Male,African-American,07/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +65526,75803,68647,PRETRIAL,Douze,Nicolas,NULL,Male,African-American,07/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65531,75813,68654,Probation,Leonard,Robert,NULL,Male,Caucasian,08/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +65531,75813,68654,Probation,Leonard,Robert,NULL,Male,Caucasian,08/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +65531,75813,68654,Probation,Leonard,Robert,NULL,Male,Caucasian,08/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +37476,75814,68655,PRETRIAL,MCQUEEN,PERRY,NULL,Male,African-American,03/26/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +37476,75814,68655,PRETRIAL,MCQUEEN,PERRY,NULL,Male,African-American,03/26/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +37476,75814,68655,PRETRIAL,MCQUEEN,PERRY,NULL,Male,African-American,03/26/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +65518,75793,68638,PRETRIAL,Caine,Elizabeth,NULL,Female,Caucasian,07/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.31,3,Low,New,1,0 +65518,75793,68638,PRETRIAL,Caine,Elizabeth,NULL,Female,Caucasian,07/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,9,High,New,1,0 +65518,75793,68638,PRETRIAL,Caine,Elizabeth,NULL,Female,Caucasian,07/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +58896,75802,61136,PRETRIAL,Mccrea,Malik,NULL,Male,African-American,06/20/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/14 0:00,4,High,7,Risk of Violence,-0.37,10,High,New,1,0 +58896,75802,61136,PRETRIAL,Mccrea,Malik,NULL,Male,African-American,06/20/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/14 0:00,4,High,8,Risk of Recidivism,0.71,10,High,New,1,0 +58896,75802,61136,PRETRIAL,Mccrea,Malik,NULL,Male,African-American,06/20/97,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/14/14 0:00,4,High,18,Risk of Failure to Appear,16,1,Low,New,1,0 +58058,75816,68657,PRETRIAL,Zachary,Deborah,NULL,Female,Caucasian,08/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/14/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +58058,75816,68657,PRETRIAL,Zachary,Deborah,NULL,Female,Caucasian,08/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/14/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +58058,75816,68657,PRETRIAL,Zachary,Deborah,NULL,Female,Caucasian,08/18/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60001,75788,68634,Probation,REINIGER,LAVANDA,L,Female,African-American,07/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2,4,Low,New,1,0 +60001,75788,68634,Probation,REINIGER,LAVANDA,L,Female,African-American,07/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,10,High,New,1,0 +60001,75788,68634,Probation,REINIGER,LAVANDA,L,Female,African-American,07/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50665,75786,68632,PRETRIAL,Valentin,George,NULL,Male,Hispanic,08/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,8/14/14 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +50665,75786,68632,PRETRIAL,Valentin,George,NULL,Male,Hispanic,08/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,8/14/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +50665,75786,68632,PRETRIAL,Valentin,George,NULL,Male,Hispanic,08/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,8/14/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65528,75809,68651,PRETRIAL,Barrett,Jonathan,NULL,Male,African-American,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +65528,75809,68651,PRETRIAL,Barrett,Jonathan,NULL,Male,African-American,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +65528,75809,68651,PRETRIAL,Barrett,Jonathan,NULL,Male,African-American,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65532,75815,68656,Probation,taylor,cordero,NULL,Male,African-American,04/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +65532,75815,68656,Probation,taylor,cordero,NULL,Male,African-American,04/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +65532,75815,68656,Probation,taylor,cordero,NULL,Male,African-American,04/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65519,75794,68639,Probation,Fahey,Robert,NULL,Male,Caucasian,10/02/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/14/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +65519,75794,68639,Probation,Fahey,Robert,NULL,Male,Caucasian,10/02/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/14/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +65519,75794,68639,Probation,Fahey,Robert,NULL,Male,Caucasian,10/02/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65525,75801,68646,Probation,MCMEANS,ROBERT,LOUIS,Male,African-American,09/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/14/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +65525,75801,68646,Probation,MCMEANS,ROBERT,LOUIS,Male,African-American,09/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/14/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +65525,75801,68646,Probation,MCMEANS,ROBERT,LOUIS,Male,African-American,09/29/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65410,75808,68512,PRETRIAL,Allen,Sedainel,NULL,Male,African-American,04/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/14/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,Copy,1,0 +65410,75808,68512,PRETRIAL,Allen,Sedainel,NULL,Male,African-American,04/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/14/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,Copy,1,0 +65410,75808,68512,PRETRIAL,Allen,Sedainel,NULL,Male,African-American,04/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +53315,75810,54771,PRETRIAL,Stepp,Jaime,NULL,Female,Caucasian,06/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/14/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,Copy,1,0 +53315,75810,54771,PRETRIAL,Stepp,Jaime,NULL,Female,Caucasian,06/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/14/14 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,Copy,1,0 +53315,75810,54771,PRETRIAL,Stepp,Jaime,NULL,Female,Caucasian,06/25/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +65516,75789,68635,PRETRIAL,Daniels,Glenn,Edward,Male,African-American,07/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +65516,75789,68635,PRETRIAL,Daniels,Glenn,Edward,Male,African-American,07/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +65516,75789,68635,PRETRIAL,Daniels,Glenn,Edward,Male,African-American,07/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59095,75806,68650,PRETRIAL,Hoyt,Kyle,NULL,Male,Caucasian,05/01/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +59095,75806,68650,PRETRIAL,Hoyt,Kyle,NULL,Male,Caucasian,05/01/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +59095,75806,68650,PRETRIAL,Hoyt,Kyle,NULL,Male,Caucasian,05/01/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65535,75820,68660,PRETRIAL,Poole,Shrieff,NULL,Male,African-American,05/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/14/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +65535,75820,68660,PRETRIAL,Poole,Shrieff,NULL,Male,African-American,05/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/14/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +65535,75820,68660,PRETRIAL,Poole,Shrieff,NULL,Male,African-American,05/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65530,75812,68653,Probation,Melgar,Gustavo,NULL,Male,Hispanic,05/14/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +65530,75812,68653,Probation,Melgar,Gustavo,NULL,Male,Hispanic,05/14/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +65530,75812,68653,Probation,Melgar,Gustavo,NULL,Male,Hispanic,05/14/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65517,75791,68637,PRETRIAL,Greer,Rashan,E,Male,African-American,03/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +65517,75791,68637,PRETRIAL,Greer,Rashan,E,Male,African-American,03/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +65517,75791,68637,PRETRIAL,Greer,Rashan,E,Male,African-American,03/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/14/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +58871,75804,68648,PRETRIAL,MILLER,DUANE,ANTONIO,Male,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +58871,75804,68648,PRETRIAL,MILLER,DUANE,ANTONIO,Male,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +58871,75804,68648,PRETRIAL,MILLER,DUANE,ANTONIO,Male,African-American,09/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65533,75817,68658,Probation,morgan,sebastian,NULL,Male,Caucasian,08/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +65533,75817,68658,Probation,morgan,sebastian,NULL,Male,Caucasian,08/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +65533,75817,68658,Probation,morgan,sebastian,NULL,Male,Caucasian,08/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65521,75796,68641,Probation,robinson,derrick,NULL,Male,African-American,12/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +65521,75796,68641,Probation,robinson,derrick,NULL,Male,African-American,12/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +65521,75796,68641,Probation,robinson,derrick,NULL,Male,African-American,12/19/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65524,75799,68644,Probation,Chambers,Kevin,NULL,Male,Caucasian,01/21/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +65524,75799,68644,Probation,Chambers,Kevin,NULL,Male,Caucasian,01/21/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +65524,75799,68644,Probation,Chambers,Kevin,NULL,Male,Caucasian,01/21/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/14/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65544,75838,68673,Probation,Amentini,Brian,Philip,Male,Caucasian,07/16/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/15/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +65544,75838,68673,Probation,Amentini,Brian,Philip,Male,Caucasian,07/16/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/15/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +65544,75838,68673,Probation,Amentini,Brian,Philip,Male,Caucasian,07/16/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/15/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +34420,75825,68665,PRETRIAL,FEAGIN,CALVIN,NULL,Male,African-American,09/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +34420,75825,68665,PRETRIAL,FEAGIN,CALVIN,NULL,Male,African-American,09/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +34420,75825,68665,PRETRIAL,FEAGIN,CALVIN,NULL,Male,African-American,09/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +22215,75833,68303,Probation,Powell,Ginger,NULL,Female,Caucasian,10/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/14 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,Copy,1,0 +22215,75833,68303,Probation,Powell,Ginger,NULL,Female,Caucasian,10/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,Copy,1,0 +22215,75833,68303,Probation,Powell,Ginger,NULL,Female,Caucasian,10/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +49827,75841,68675,PRETRIAL,Tipler,Michael,NULL,Male,Caucasian,04/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +49827,75841,68675,PRETRIAL,Tipler,Michael,NULL,Male,Caucasian,04/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +49827,75841,68675,PRETRIAL,Tipler,Michael,NULL,Male,Caucasian,04/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +63273,75840,66106,Probation,Sangare,David,NULL,Male,African-American,10/09/83,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/15/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +63273,75840,66106,Probation,Sangare,David,NULL,Male,African-American,10/09/83,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/15/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +63273,75840,66106,Probation,Sangare,David,NULL,Male,African-American,10/09/83,17,All Scales,Intake,English,Conditional Release,Probation,Single,8/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,2,Low,New,1,0 +65542,75831,68669,Probation,chavez,priscilla,NULL,Female,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/14 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +65542,75831,68669,Probation,chavez,priscilla,NULL,Female,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +65542,75831,68669,Probation,chavez,priscilla,NULL,Female,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65541,75829,68668,Probation,Correa,Kimberly,Suzanne,Female,Caucasian,01/08/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/15/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +65541,75829,68668,Probation,Correa,Kimberly,Suzanne,Female,Caucasian,01/08/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/15/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +65541,75829,68668,Probation,Correa,Kimberly,Suzanne,Female,Caucasian,01/08/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59681,75843,68677,PRETRIAL,Jacobs,Marshall,NULL,Male,Caucasian,04/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +59681,75843,68677,PRETRIAL,Jacobs,Marshall,NULL,Male,Caucasian,04/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +59681,75843,68677,PRETRIAL,Jacobs,Marshall,NULL,Male,Caucasian,04/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/15/14 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +48223,75822,68662,PRETRIAL,Smith,Oshane,Oran,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +48223,75822,68662,PRETRIAL,Smith,Oshane,Oran,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +48223,75822,68662,PRETRIAL,Smith,Oshane,Oran,Male,African-American,02/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65538,75824,68664,PRETRIAL,Montalvo,Jose,NULL,Male,Hispanic,11/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +65538,75824,68664,PRETRIAL,Montalvo,Jose,NULL,Male,Hispanic,11/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,4,High,8,Risk of Recidivism,0.33,9,High,New,1,0 +65538,75824,68664,PRETRIAL,Montalvo,Jose,NULL,Male,Hispanic,11/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +37436,75830,36801,PRETRIAL,BLANKENSHIP,THOMAS,NULL,Male,Caucasian,07/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/14 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,Copy,1,0 +37436,75830,36801,PRETRIAL,BLANKENSHIP,THOMAS,NULL,Male,Caucasian,07/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,Copy,1,0 +37436,75830,36801,PRETRIAL,BLANKENSHIP,THOMAS,NULL,Male,Caucasian,07/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +65537,75823,68663,PRETRIAL,Ramosrivera,Ana,Marie,Female,Hispanic,02/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +65537,75823,68663,PRETRIAL,Ramosrivera,Ana,Marie,Female,Hispanic,02/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +65537,75823,68663,PRETRIAL,Ramosrivera,Ana,Marie,Female,Hispanic,02/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64517,75828,67531,PRETRIAL,stephens,jazlyn,NULL,Female,African-American,10/01/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.91,9,High,Copy,1,0 +64517,75828,67531,PRETRIAL,stephens,jazlyn,NULL,Female,African-American,10/01/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,7,Medium,Copy,1,0 +64517,75828,67531,PRETRIAL,stephens,jazlyn,NULL,Female,African-American,10/01/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,7,Medium,Copy,1,0 +65543,75835,68671,PRETRIAL,Flowers,Charles,NULL,Male,African-American,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +65543,75835,68671,PRETRIAL,Flowers,Charles,NULL,Male,African-American,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +65543,75835,68671,PRETRIAL,Flowers,Charles,NULL,Male,African-American,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65546,75842,68676,DRRD,ortiz,jorge,NULL,Male,Caucasian,07/04/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/15/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +65546,75842,68676,DRRD,ortiz,jorge,NULL,Male,Caucasian,07/04/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/15/14 0:00,1,Low,8,Risk of Recidivism,-0.98,2,Low,New,1,0 +65546,75842,68676,DRRD,ortiz,jorge,NULL,Male,Caucasian,07/04/88,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65539,75826,68666,PRETRIAL,Currie,Chadwick,Edward,Male,Other,11/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +65539,75826,68666,PRETRIAL,Currie,Chadwick,Edward,Male,Other,11/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +65539,75826,68666,PRETRIAL,Currie,Chadwick,Edward,Male,Other,11/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64223,74182,67204,PRETRIAL,BROWN,DAMION,NULL,Male,African-American,10/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +64223,74182,67204,PRETRIAL,BROWN,DAMION,NULL,Male,African-American,10/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +64223,74182,67204,PRETRIAL,BROWN,DAMION,NULL,Male,African-American,10/20/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/15/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65545,75839,68674,Probation,patrick,allen,NULL,Male,Caucasian,03/16/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/15/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +65545,75839,68674,Probation,patrick,allen,NULL,Male,Caucasian,03/16/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/15/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +65545,75839,68674,Probation,patrick,allen,NULL,Male,Caucasian,03/16/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/15/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65550,75847,68681,PRETRIAL,DOWELS,JEREL,DION,Male,African-American,10/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.22,8,High,New,1,0 +65550,75847,68681,PRETRIAL,DOWELS,JEREL,DION,Male,African-American,10/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +65550,75847,68681,PRETRIAL,DOWELS,JEREL,DION,Male,African-American,10/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65551,75849,68682,PRETRIAL,Hockaday,Billy,Howard,Male,Caucasian,04/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +65551,75849,68682,PRETRIAL,Hockaday,Billy,Howard,Male,Caucasian,04/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +65551,75849,68682,PRETRIAL,Hockaday,Billy,Howard,Male,Caucasian,04/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65547,75844,68678,PRETRIAL,Adeyemiorigho,Christopher,NULL,Male,African-American,12/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +65547,75844,68678,PRETRIAL,Adeyemiorigho,Christopher,NULL,Male,African-American,12/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +65547,75844,68678,PRETRIAL,Adeyemiorigho,Christopher,NULL,Male,African-American,12/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65548,75845,68679,PRETRIAL,Maxwell,Joshua,NULL,Male,African-American,04/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +65548,75845,68679,PRETRIAL,Maxwell,Joshua,NULL,Male,African-American,04/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +65548,75845,68679,PRETRIAL,Maxwell,Joshua,NULL,Male,African-American,04/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +58327,75848,60551,PRETRIAL,WORTHY,BILLY,NULL,Male,African-American,02/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/16/14 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,Copy,1,0 +58327,75848,60551,PRETRIAL,WORTHY,BILLY,NULL,Male,African-American,02/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,Copy,1,0 +58327,75848,60551,PRETRIAL,WORTHY,BILLY,NULL,Male,African-American,02/18/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/16/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +65549,75846,68680,PRETRIAL,Coutilien,Laurens,NULL,Male,African-American,03/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +65549,75846,68680,PRETRIAL,Coutilien,Laurens,NULL,Male,African-American,03/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +65549,75846,68680,PRETRIAL,Coutilien,Laurens,NULL,Male,African-American,03/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/16/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65561,75864,68694,PRETRIAL,LARSEN,DEREK,RICHARD,Male,Caucasian,05/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +65561,75864,68694,PRETRIAL,LARSEN,DEREK,RICHARD,Male,Caucasian,05/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +65561,75864,68694,PRETRIAL,LARSEN,DEREK,RICHARD,Male,Caucasian,05/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,41,10,High,New,1,0 +65556,75859,68689,PRETRIAL,ESPINOSA,MARIA,A,Female,Hispanic,04/07/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/17/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +65556,75859,68689,PRETRIAL,ESPINOSA,MARIA,A,Female,Hispanic,04/07/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/17/14 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +65556,75859,68689,PRETRIAL,ESPINOSA,MARIA,A,Female,Hispanic,04/07/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65559,75862,68692,PRETRIAL,Jones,John,NULL,Male,African-American,06/07/39,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/17/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +65559,75862,68692,PRETRIAL,Jones,John,NULL,Male,African-American,06/07/39,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/17/14 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +65559,75862,68692,PRETRIAL,Jones,John,NULL,Male,African-American,06/07/39,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65553,75854,68685,PRETRIAL,Martin,Jeffrey,NULL,Male,Caucasian,01/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,Copy,1,0 +65553,75854,68685,PRETRIAL,Martin,Jeffrey,NULL,Male,Caucasian,01/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,Copy,1,0 +65553,75854,68685,PRETRIAL,Martin,Jeffrey,NULL,Male,Caucasian,01/09/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +3291,75856,68686,PRETRIAL,harriott,james,NULL,Male,African-American,07/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +3291,75856,68686,PRETRIAL,harriott,james,NULL,Male,African-American,07/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +3291,75856,68686,PRETRIAL,harriott,james,NULL,Male,African-American,07/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65552,75850,68683,PRETRIAL,Barrero,Helen,NULL,Female,Caucasian,06/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/17/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +65552,75850,68683,PRETRIAL,Barrero,Helen,NULL,Female,Caucasian,06/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/17/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +65552,75850,68683,PRETRIAL,Barrero,Helen,NULL,Female,Caucasian,06/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +63124,75852,65948,Probation,owens,nathaniel,NULL,Male,African-American,07/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,Copy,1,0 +63124,75852,65948,Probation,owens,nathaniel,NULL,Male,African-American,07/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,Copy,1,0 +63124,75852,65948,Probation,owens,nathaniel,NULL,Male,African-American,07/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +65554,75857,68687,PRETRIAL,FOSTER,KEVIN,NULL,Male,African-American,03/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.96,1,Low,New,1,0 +65554,75857,68687,PRETRIAL,FOSTER,KEVIN,NULL,Male,African-American,03/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +65554,75857,68687,PRETRIAL,FOSTER,KEVIN,NULL,Male,African-American,03/18/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65558,75861,68691,PRETRIAL,TRACEY,RAHIEM,NULL,Male,African-American,01/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +65558,75861,68691,PRETRIAL,TRACEY,RAHIEM,NULL,Male,African-American,01/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +65558,75861,68691,PRETRIAL,TRACEY,RAHIEM,NULL,Male,African-American,01/26/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +37251,75851,68684,PRETRIAL,Malone,Kristi,NULL,Female,Caucasian,11/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/17/14 0:00,4,High,7,Risk of Violence,-1.02,8,High,New,1,0 +37251,75851,68684,PRETRIAL,Malone,Kristi,NULL,Female,Caucasian,11/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/17/14 0:00,4,High,8,Risk of Recidivism,0.08,8,High,New,1,0 +37251,75851,68684,PRETRIAL,Malone,Kristi,NULL,Female,Caucasian,11/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/17/14 0:00,4,High,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +65555,75858,68688,PRETRIAL,HALL,ANDRE,NULL,Male,African-American,11/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +65555,75858,68688,PRETRIAL,HALL,ANDRE,NULL,Male,African-American,11/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +65555,75858,68688,PRETRIAL,HALL,ANDRE,NULL,Male,African-American,11/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65557,75860,68690,PRETRIAL,GUTIERREZ,ADITA,O,Female,Caucasian,02/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/17/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +65557,75860,68690,PRETRIAL,GUTIERREZ,ADITA,O,Female,Caucasian,02/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/17/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +65557,75860,68690,PRETRIAL,GUTIERREZ,ADITA,O,Female,Caucasian,02/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65560,75863,68693,PRETRIAL,Holgate,Crystal,NULL,Male,African-American,05/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +65560,75863,68693,PRETRIAL,Holgate,Crystal,NULL,Male,African-American,05/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +65560,75863,68693,PRETRIAL,Holgate,Crystal,NULL,Male,African-American,05/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58509,75855,60727,PRETRIAL,Zayas,Sissy,NULL,Female,Caucasian,06/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,Copy,1,0 +58509,75855,60727,PRETRIAL,Zayas,Sissy,NULL,Female,Caucasian,06/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,Copy,1,0 +58509,75855,60727,PRETRIAL,Zayas,Sissy,NULL,Female,Caucasian,06/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +65565,75868,68698,PRETRIAL,Gomez,Dillon,Steven,Male,Caucasian,11/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +65565,75868,68698,PRETRIAL,Gomez,Dillon,Steven,Male,Caucasian,11/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +65565,75868,68698,PRETRIAL,Gomez,Dillon,Steven,Male,Caucasian,11/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65593,75902,68731,Probation,Patterson,Erin,NULL,Female,Caucasian,04/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/18/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +65593,75902,68731,Probation,Patterson,Erin,NULL,Female,Caucasian,04/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/18/14 0:00,1,Low,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +65593,75902,68731,Probation,Patterson,Erin,NULL,Female,Caucasian,04/15/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +65577,75881,68711,Probation,Uner,Andria,Karina,Female,Caucasian,01/09/78,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/18/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +65577,75881,68711,Probation,Uner,Andria,Karina,Female,Caucasian,01/09/78,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/18/14 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +65577,75881,68711,Probation,Uner,Andria,Karina,Female,Caucasian,01/09/78,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65573,75876,68706,Probation,Hetrick,Kim,Frank,Male,Caucasian,09/20/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +65573,75876,68706,Probation,Hetrick,Kim,Frank,Male,Caucasian,09/20/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +65573,75876,68706,Probation,Hetrick,Kim,Frank,Male,Caucasian,09/20/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65580,75884,68714,Probation,SEARLES,MACHELLE,NULL,Female,African-American,01/15/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +65580,75884,68714,Probation,SEARLES,MACHELLE,NULL,Female,African-American,01/15/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +65580,75884,68714,Probation,SEARLES,MACHELLE,NULL,Female,African-American,01/15/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65562,75865,68695,PRETRIAL,ROSTAMIAN,CYRUS,NULL,Male,Hispanic,11/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/18/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +65562,75865,68695,PRETRIAL,ROSTAMIAN,CYRUS,NULL,Male,Hispanic,11/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/18/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +65562,75865,68695,PRETRIAL,ROSTAMIAN,CYRUS,NULL,Male,Hispanic,11/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65575,75879,68709,PRETRIAL,Felts,Divonte,NULL,Male,African-American,12/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +65575,75879,68709,PRETRIAL,Felts,Divonte,NULL,Male,African-American,12/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +65575,75879,68709,PRETRIAL,Felts,Divonte,NULL,Male,African-American,12/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65583,75888,68718,Probation,peraza,jordan,NULL,Male,Hispanic,04/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/18/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +65583,75888,68718,Probation,peraza,jordan,NULL,Male,Hispanic,04/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/18/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +65583,75888,68718,Probation,peraza,jordan,NULL,Male,Hispanic,04/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65571,75874,68704,Probation,GUTIERREZ,CHRISTIAN,NULL,Male,Hispanic,09/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +65571,75874,68704,Probation,GUTIERREZ,CHRISTIAN,NULL,Male,Hispanic,09/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +65571,75874,68704,Probation,GUTIERREZ,CHRISTIAN,NULL,Male,Hispanic,09/22/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65587,75891,68721,PRETRIAL,Kohner,Roy,Joseph,Male,Caucasian,03/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/18/14 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +65587,75891,68721,PRETRIAL,Kohner,Roy,Joseph,Male,Caucasian,03/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/18/14 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +65587,75891,68721,PRETRIAL,Kohner,Roy,Joseph,Male,Caucasian,03/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65567,75870,68700,PRETRIAL,Thompson,Donna,NULL,Female,African-American,09/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +65567,75870,68700,PRETRIAL,Thompson,Donna,NULL,Female,African-American,09/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,8,High,New,1,0 +65567,75870,68700,PRETRIAL,Thompson,Donna,NULL,Female,African-American,09/10/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +30968,75895,68725,PRETRIAL,Fritts,Craig,NULL,Male,Caucasian,07/23/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +30968,75895,68725,PRETRIAL,Fritts,Craig,NULL,Male,Caucasian,07/23/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +30968,75895,68725,PRETRIAL,Fritts,Craig,NULL,Male,Caucasian,07/23/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57535,75900,59646,PRETRIAL,Staggewise,Nicholas,NULL,Male,Caucasian,02/28/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +57535,75900,59646,PRETRIAL,Staggewise,Nicholas,NULL,Male,Caucasian,02/28/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +57535,75900,59646,PRETRIAL,Staggewise,Nicholas,NULL,Male,Caucasian,02/28/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +37436,75896,68726,PRETRIAL,BLANKENSHIP,THOMAS,NULL,Male,Caucasian,07/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +37436,75896,68726,PRETRIAL,BLANKENSHIP,THOMAS,NULL,Male,Caucasian,07/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +37436,75896,68726,PRETRIAL,BLANKENSHIP,THOMAS,NULL,Male,Caucasian,07/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65591,75899,68729,Probation,MENEGHEL,RAPHAEL,N,Male,Hispanic,07/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +65591,75899,68729,Probation,MENEGHEL,RAPHAEL,N,Male,Hispanic,07/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +65591,75899,68729,Probation,MENEGHEL,RAPHAEL,N,Male,Hispanic,07/20/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +49652,75878,68708,PRETRIAL,Wilson,Nastastear,NULL,Female,African-American,01/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +49652,75878,68708,PRETRIAL,Wilson,Nastastear,NULL,Female,African-American,01/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,9,High,New,1,0 +49652,75878,68708,PRETRIAL,Wilson,Nastastear,NULL,Female,African-American,01/04/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +65586,75892,68722,Probation,Leopold,Ashley,NULL,Female,Caucasian,10/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/18/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +65586,75892,68722,Probation,Leopold,Ashley,NULL,Female,Caucasian,10/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/18/14 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +65586,75892,68722,Probation,Leopold,Ashley,NULL,Female,Caucasian,10/07/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65594,75903,68732,DRRD,Jones,D'Jon,NULL,Male,African-American,12/07/86,17,All Scales,Intake,English,Other,Probation,Married,8/18/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +65594,75903,68732,DRRD,Jones,D'Jon,NULL,Male,African-American,12/07/86,17,All Scales,Intake,English,Other,Probation,Married,8/18/14 0:00,1,Low,8,Risk of Recidivism,-1.34,1,Low,New,1,0 +65594,75903,68732,DRRD,Jones,D'Jon,NULL,Male,African-American,12/07/86,17,All Scales,Intake,English,Other,Probation,Married,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65568,75871,68701,Probation,Arce,ernesto,Daniel,Male,Hispanic,03/13/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +65568,75871,68701,Probation,Arce,ernesto,Daniel,Male,Hispanic,03/13/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +65568,75871,68701,Probation,Arce,ernesto,Daniel,Male,Hispanic,03/13/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65563,75866,68696,PRETRIAL,DURHAM,DAVID,WILLIAM,Male,African-American,02/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +65563,75866,68696,PRETRIAL,DURHAM,DAVID,WILLIAM,Male,African-American,02/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +65563,75866,68696,PRETRIAL,DURHAM,DAVID,WILLIAM,Male,African-American,02/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65576,75880,68710,Probation,jonatas,kelly,NULL,Female,African-American,03/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/18/14 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +65576,75880,68710,Probation,jonatas,kelly,NULL,Female,African-American,03/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +65576,75880,68710,Probation,jonatas,kelly,NULL,Female,African-American,03/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,8/18/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65582,75887,68717,Probation,Warren,Dean,Bernard,Male,African-American,05/31/96,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +65582,75887,68717,Probation,Warren,Dean,Bernard,Male,African-American,05/31/96,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.67,10,High,New,1,0 +65582,75887,68717,Probation,Warren,Dean,Bernard,Male,African-American,05/31/96,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65592,75901,68730,Probation,Ferdinand,Ramonde,NULL,Female,African-American,07/02/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +65592,75901,68730,Probation,Ferdinand,Ramonde,NULL,Female,African-American,07/02/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +65592,75901,68730,Probation,Ferdinand,Ramonde,NULL,Female,African-American,07/02/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65585,75890,68720,PRETRIAL,Seppi,Kristina,Marie,Female,Caucasian,12/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +65585,75890,68720,PRETRIAL,Seppi,Kristina,Marie,Female,Caucasian,12/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +65585,75890,68720,PRETRIAL,Seppi,Kristina,Marie,Female,Caucasian,12/31/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65572,75875,68705,Probation,Lazarus,David,NULL,Male,Asian,06/03/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/18/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +65572,75875,68705,Probation,Lazarus,David,NULL,Male,Asian,06/03/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/18/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +65572,75875,68705,Probation,Lazarus,David,NULL,Male,Asian,06/03/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65566,75869,68699,PRETRIAL,Gabriel,AngieMarie,NULL,Female,African-American,06/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +65566,75869,68699,PRETRIAL,Gabriel,AngieMarie,NULL,Female,African-American,06/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +65566,75869,68699,PRETRIAL,Gabriel,AngieMarie,NULL,Female,African-American,06/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +42242,75898,68728,PRETRIAL,Lahens,Jairzinho,Manuel,Male,African-American,01/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +42242,75898,68728,PRETRIAL,Lahens,Jairzinho,Manuel,Male,African-American,01/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +42242,75898,68728,PRETRIAL,Lahens,Jairzinho,Manuel,Male,African-American,01/09/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65589,75893,68723,Probation,FLETCHER,STEPHANIE,NULL,Female,Hispanic,09/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +65589,75893,68723,Probation,FLETCHER,STEPHANIE,NULL,Female,Hispanic,09/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +65589,75893,68723,Probation,FLETCHER,STEPHANIE,NULL,Female,Hispanic,09/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65569,75872,68702,PRETRIAL,CORDERO,SANTIAGO,NULL,Male,African-American,11/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +65569,75872,68702,PRETRIAL,CORDERO,SANTIAGO,NULL,Male,African-American,11/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +65569,75872,68702,PRETRIAL,CORDERO,SANTIAGO,NULL,Male,African-American,11/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +65564,75867,68697,PRETRIAL,Jngeorges,Geraldson,NULL,Male,Other,10/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +65564,75867,68697,PRETRIAL,Jngeorges,Geraldson,NULL,Male,Other,10/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +65564,75867,68697,PRETRIAL,Jngeorges,Geraldson,NULL,Male,Other,10/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65581,75885,68715,Probation,McKown,Crystal,NULL,Female,Caucasian,02/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +65581,75885,68715,Probation,McKown,Crystal,NULL,Female,Caucasian,02/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +65581,75885,68715,Probation,McKown,Crystal,NULL,Female,Caucasian,02/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/18/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +65618,75935,68761,Probation,Gutierrez,Julio,NULL,Male,Hispanic,01/02/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +65618,75935,68761,Probation,Gutierrez,Julio,NULL,Male,Hispanic,01/02/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +65618,75935,68761,Probation,Gutierrez,Julio,NULL,Male,Hispanic,01/02/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65616,75932,68758,Probation,SIEKIEWICZ,LAURA,J,Female,Caucasian,01/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +65616,75932,68758,Probation,SIEKIEWICZ,LAURA,J,Female,Caucasian,01/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +65616,75932,68758,Probation,SIEKIEWICZ,LAURA,J,Female,Caucasian,01/01/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +27200,75906,68735,PRETRIAL,BERNHARDT,STEPHEN,NULL,Male,Caucasian,04/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +27200,75906,68735,PRETRIAL,BERNHARDT,STEPHEN,NULL,Male,Caucasian,04/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +27200,75906,68735,PRETRIAL,BERNHARDT,STEPHEN,NULL,Male,Caucasian,04/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65609,75927,68753,PRETRIAL,EDOUARD,STEVENSON,NULL,Male,African-American,08/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +65609,75927,68753,PRETRIAL,EDOUARD,STEVENSON,NULL,Male,African-American,08/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +65609,75927,68753,PRETRIAL,EDOUARD,STEVENSON,NULL,Male,African-American,08/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51349,75919,68745,PRETRIAL,Oscrola,Ravenne,NULL,Female,Native American,08/17/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +51349,75919,68745,PRETRIAL,Oscrola,Ravenne,NULL,Female,Native American,08/17/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.11,8,High,New,1,0 +51349,75919,68745,PRETRIAL,Oscrola,Ravenne,NULL,Female,Native American,08/17/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65601,75911,68740,PRETRIAL,CHRISTIAN,JENSEN,ALEXANDER,Male,African-American,10/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +65601,75911,68740,PRETRIAL,CHRISTIAN,JENSEN,ALEXANDER,Male,African-American,10/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +65601,75911,68740,PRETRIAL,CHRISTIAN,JENSEN,ALEXANDER,Male,African-American,10/26/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58110,75915,60299,PRETRIAL,Francois,Daniel,NULL,Male,African-American,12/11/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.08,8,High,Copy,1,0 +58110,75915,60299,PRETRIAL,Francois,Daniel,NULL,Male,African-American,12/11/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.16,6,Medium,Copy,1,0 +58110,75915,60299,PRETRIAL,Francois,Daniel,NULL,Male,African-American,12/11/82,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +65613,75929,68755,DRRD,colas,frandy,NULL,Male,African-American,08/12/91,17,All Scales,Intake,English,Other,Probation,Single,8/19/14 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +65613,75929,68755,DRRD,colas,frandy,NULL,Male,African-American,08/12/91,17,All Scales,Intake,English,Other,Probation,Single,8/19/14 0:00,1,Low,8,Risk of Recidivism,-0.25,5,Medium,New,1,0 +65613,75929,68755,DRRD,colas,frandy,NULL,Male,African-American,08/12/91,17,All Scales,Intake,English,Other,Probation,Single,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +33539,75922,68748,Probation,Boxer,Mitchell,NULL,Male,Caucasian,05/17/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/19/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +33539,75922,68748,Probation,Boxer,Mitchell,NULL,Male,Caucasian,05/17/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/19/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +33539,75922,68748,Probation,Boxer,Mitchell,NULL,Male,Caucasian,05/17/61,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65607,75924,68750,Probation,Basil,Joseph,NULL,Male,Caucasian,11/28/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +65607,75924,68750,Probation,Basil,Joseph,NULL,Male,Caucasian,11/28/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +65607,75924,68750,Probation,Basil,Joseph,NULL,Male,Caucasian,11/28/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65605,75917,68744,Probation,Kasmaii,Nima,NULL,Male,Caucasian,06/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +65605,75917,68744,Probation,Kasmaii,Nima,NULL,Male,Caucasian,06/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +65605,75917,68744,Probation,Kasmaii,Nima,NULL,Male,Caucasian,06/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65603,75913,68742,Probation,Niedda,Jaime,NULL,Male,Hispanic,09/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +65603,75913,68742,Probation,Niedda,Jaime,NULL,Male,Hispanic,09/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +65603,75913,68742,Probation,Niedda,Jaime,NULL,Male,Hispanic,09/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65598,75908,68737,PRETRIAL,PIERRE,BENSON,NULL,Male,Other,06/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/19/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +65598,75908,68737,PRETRIAL,PIERRE,BENSON,NULL,Male,Other,06/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/19/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +65598,75908,68737,PRETRIAL,PIERRE,BENSON,NULL,Male,Other,06/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65608,75925,68751,PRETRIAL,Da silva,Sebastian,NULL,Male,Hispanic,03/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/19/14 0:00,1,Low,7,Risk of Violence,-4.27,1,Low,New,1,0 +65608,75925,68751,PRETRIAL,Da silva,Sebastian,NULL,Male,Hispanic,03/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/19/14 0:00,1,Low,8,Risk of Recidivism,-2.97,1,Low,New,1,0 +65608,75925,68751,PRETRIAL,Da silva,Sebastian,NULL,Male,Hispanic,03/11/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65595,75904,68733,PRETRIAL,MATHIS,TIFFANY,NULL,Female,African-American,06/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/19/14 0:00,2,Medium,7,Risk of Violence,-2.66,2,Low,New,1,0 +65595,75904,68733,PRETRIAL,MATHIS,TIFFANY,NULL,Female,African-American,06/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +65595,75904,68733,PRETRIAL,MATHIS,TIFFANY,NULL,Female,African-American,06/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/19/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +58079,75921,68747,PRETRIAL,Pirolo,Anthony,NULL,Male,Caucasian,04/25/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/19/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +58079,75921,68747,PRETRIAL,Pirolo,Anthony,NULL,Male,Caucasian,04/25/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/19/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +58079,75921,68747,PRETRIAL,Pirolo,Anthony,NULL,Male,Caucasian,04/25/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65597,75907,68736,PRETRIAL,Aristide,Wayne,NULL,Male,African-American,05/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,4,High,7,Risk of Violence,-0.84,9,High,New,1,0 +65597,75907,68736,PRETRIAL,Aristide,Wayne,NULL,Male,African-American,05/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,4,High,8,Risk of Recidivism,0.73,10,High,New,1,0 +65597,75907,68736,PRETRIAL,Aristide,Wayne,NULL,Male,African-American,05/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65599,75909,68738,PRETRIAL,brown,julian,NULL,Male,African-American,02/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +65599,75909,68738,PRETRIAL,brown,julian,NULL,Male,African-American,02/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +65599,75909,68738,PRETRIAL,brown,julian,NULL,Male,African-American,02/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65604,75916,68743,Probation,perez,daniel,NULL,Male,Hispanic,07/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +65604,75916,68743,Probation,perez,daniel,NULL,Male,Hispanic,07/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +65604,75916,68743,Probation,perez,daniel,NULL,Male,Hispanic,07/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65141,75918,68232,PRETRIAL,Walker,Shahidah,NULL,Female,African-American,06/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,Copy,1,0 +65141,75918,68232,PRETRIAL,Walker,Shahidah,NULL,Female,African-American,06/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,Copy,1,0 +65141,75918,68232,PRETRIAL,Walker,Shahidah,NULL,Female,African-American,06/20/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +61245,75920,68746,PRETRIAL,Garcia,Masiely,NULL,Female,Hispanic,08/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,8/19/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +61245,75920,68746,PRETRIAL,Garcia,Masiely,NULL,Female,Hispanic,08/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,8/19/14 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +61245,75920,68746,PRETRIAL,Garcia,Masiely,NULL,Female,Hispanic,08/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65596,75905,68734,PRETRIAL,Fleurinord,Fandy,NULL,Male,Other,02/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +65596,75905,68734,PRETRIAL,Fleurinord,Fandy,NULL,Male,Other,02/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.92,10,High,New,1,0 +65596,75905,68734,PRETRIAL,Fleurinord,Fandy,NULL,Male,Other,02/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65602,75912,68741,Probation,ARGUETA,RICARDO,JOSE,Male,Hispanic,10/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +65602,75912,68741,Probation,ARGUETA,RICARDO,JOSE,Male,Hispanic,10/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +65602,75912,68741,Probation,ARGUETA,RICARDO,JOSE,Male,Hispanic,10/28/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44403,75926,68752,PRETRIAL,Brown,Jamar,NULL,Male,African-American,11/04/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/19/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +44403,75926,68752,PRETRIAL,Brown,Jamar,NULL,Male,African-American,11/04/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/19/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +44403,75926,68752,PRETRIAL,Brown,Jamar,NULL,Male,African-American,11/04/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65617,75933,68759,PRETRIAL,PULOPEZ,BERTILIO,NULL,Male,Hispanic,01/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +65617,75933,68759,PRETRIAL,PULOPEZ,BERTILIO,NULL,Male,Hispanic,01/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +65617,75933,68759,PRETRIAL,PULOPEZ,BERTILIO,NULL,Male,Hispanic,01/22/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65615,75931,68757,DRRD,Smart,Dwight,NULL,Male,African-American,04/14/60,17,All Scales,Intake,English,Post Sentence,Probation,Widowed,8/19/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +65615,75931,68757,DRRD,Smart,Dwight,NULL,Male,African-American,04/14/60,17,All Scales,Intake,English,Post Sentence,Probation,Widowed,8/19/14 0:00,1,Low,8,Risk of Recidivism,-0.88,2,Low,New,1,0 +65615,75931,68757,DRRD,Smart,Dwight,NULL,Male,African-American,04/14/60,17,All Scales,Intake,English,Post Sentence,Probation,Widowed,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65600,75910,68739,PRETRIAL,Labasco,Brian,Edward,Male,Caucasian,11/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +65600,75910,68739,PRETRIAL,Labasco,Brian,Edward,Male,Caucasian,11/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +65600,75910,68739,PRETRIAL,Labasco,Brian,Edward,Male,Caucasian,11/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65610,75928,68754,Probation,coleman,jennifer,NULL,Female,Caucasian,02/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +65610,75928,68754,Probation,coleman,jennifer,NULL,Female,Caucasian,02/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +65610,75928,68754,Probation,coleman,jennifer,NULL,Female,Caucasian,02/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65622,75936,68762,DRRD,Shorey,Byron,Keyon,Male,African-American,01/08/93,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,8/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,0.06,10,High,New,1,0 +65622,75936,68762,DRRD,Shorey,Byron,Keyon,Male,African-American,01/08/93,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,8/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,7,Medium,New,1,0 +65622,75936,68762,DRRD,Shorey,Byron,Keyon,Male,African-American,01/08/93,17,All Scales,Intake,English,Probation Violator,Jail Inmate,Single,8/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,8,High,New,1,0 +65606,75923,68749,Probation,johnson,travis,NULL,Male,African-American,08/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +65606,75923,68749,Probation,johnson,travis,NULL,Male,African-American,08/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +65606,75923,68749,Probation,johnson,travis,NULL,Male,African-American,08/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65637,75957,68782,DRRD,Cardona,Steven,NULL,Male,Hispanic,06/30/94,17,All Scales,Intake,English,Pretrial,Probation,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +65637,75957,68782,DRRD,Cardona,Steven,NULL,Male,Hispanic,06/30/94,17,All Scales,Intake,English,Pretrial,Probation,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +65637,75957,68782,DRRD,Cardona,Steven,NULL,Male,Hispanic,06/30/94,17,All Scales,Intake,English,Pretrial,Probation,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65645,75970,68792,Probation,joseph,esther,NULL,Female,African-American,10/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +65645,75970,68792,Probation,joseph,esther,NULL,Female,African-American,10/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +65645,75970,68792,Probation,joseph,esther,NULL,Female,African-American,10/21/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +43431,47524,43374,PRETRIAL,Aragon,Oscar,NULL,Male,Hispanic,08/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +43431,47524,43374,PRETRIAL,Aragon,Oscar,NULL,Male,Hispanic,08/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +43431,47524,43374,PRETRIAL,Aragon,Oscar,NULL,Male,Hispanic,08/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65649,75978,68798,Probation,heller,daneshia,l,Female,African-American,08/25/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +65649,75978,68798,Probation,heller,daneshia,l,Female,African-American,08/25/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,4,High,8,Risk of Recidivism,0.56,10,High,New,1,0 +65649,75978,68798,Probation,heller,daneshia,l,Female,African-American,08/25/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65630,75949,68774,PRETRIAL,trojanouvs,dmmitrijs,NULL,Male,Other,04/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/20/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +65630,75949,68774,PRETRIAL,trojanouvs,dmmitrijs,NULL,Male,Other,04/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +65630,75949,68774,PRETRIAL,trojanouvs,dmmitrijs,NULL,Male,Other,04/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +58086,75947,68772,PRETRIAL,PEREZ,OMAR,CHAVEZ,Male,Hispanic,07/18/80,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/20/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +58086,75947,68772,PRETRIAL,PEREZ,OMAR,CHAVEZ,Male,Hispanic,07/18/80,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +58086,75947,68772,PRETRIAL,PEREZ,OMAR,CHAVEZ,Male,Hispanic,07/18/80,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65639,75962,68785,Probation,Rodriguez Fajardo,Juan,NULL,Male,Hispanic,08/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +65639,75962,68785,Probation,Rodriguez Fajardo,Juan,NULL,Male,Hispanic,08/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +65639,75962,68785,Probation,Rodriguez Fajardo,Juan,NULL,Male,Hispanic,08/15/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65624,75939,68764,PRETRIAL,Jean,McKenzie,NULL,Male,African-American,02/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +65624,75939,68764,PRETRIAL,Jean,McKenzie,NULL,Male,African-American,02/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +65624,75939,68764,PRETRIAL,Jean,McKenzie,NULL,Male,African-American,02/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +37676,75941,68766,PRETRIAL,HORNSBY,LEONARD,NULL,Male,African-American,09/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +37676,75941,68766,PRETRIAL,HORNSBY,LEONARD,NULL,Male,African-American,09/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +37676,75941,68766,PRETRIAL,HORNSBY,LEONARD,NULL,Male,African-American,09/25/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65635,75954,68779,PRETRIAL,ALVARADO,JOSUE,NULL,Male,Caucasian,04/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +65635,75954,68779,PRETRIAL,ALVARADO,JOSUE,NULL,Male,Caucasian,04/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +65635,75954,68779,PRETRIAL,ALVARADO,JOSUE,NULL,Male,Caucasian,04/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65648,75975,68796,Probation,Dessaint,Bobruby,NULL,Male,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +65648,75975,68796,Probation,Dessaint,Bobruby,NULL,Male,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +65648,75975,68796,Probation,Dessaint,Bobruby,NULL,Male,African-American,12/15/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65642,75965,68788,DRRD,RodriquezVega,John,NULL,Male,Hispanic,12/18/86,17,All Scales,Intake,English,Other,Pretrial Defendant,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +65642,75965,68788,DRRD,RodriquezVega,John,NULL,Male,Hispanic,12/18/86,17,All Scales,Intake,English,Other,Pretrial Defendant,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +65642,75965,68788,DRRD,RodriquezVega,John,NULL,Male,Hispanic,12/18/86,17,All Scales,Intake,English,Other,Pretrial Defendant,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65628,75944,68769,PRETRIAL,LARKINS,COURTNEY,NULL,Male,African-American,01/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +65628,75944,68769,PRETRIAL,LARKINS,COURTNEY,NULL,Male,African-American,01/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.64,10,High,New,1,0 +65628,75944,68769,PRETRIAL,LARKINS,COURTNEY,NULL,Male,African-American,01/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65632,75951,68776,Probation,HERNANDEZ MARIA,RICHARD,G,Male,Hispanic,08/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +65632,75951,68776,Probation,HERNANDEZ MARIA,RICHARD,G,Male,Hispanic,08/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +65632,75951,68776,Probation,HERNANDEZ MARIA,RICHARD,G,Male,Hispanic,08/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65650,75979,68799,DRRD,Knox,Yanicka,Cashania,Male,African-American,08/27/81,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +65650,75979,68799,DRRD,Knox,Yanicka,Cashania,Male,African-American,08/27/81,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.94,2,Low,New,1,0 +65650,75979,68799,DRRD,Knox,Yanicka,Cashania,Male,African-American,08/27/81,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65636,75958,68783,Probation,elias,mitchell,NULL,Male,Caucasian,02/07/55,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +65636,75958,68783,Probation,elias,mitchell,NULL,Male,Caucasian,02/07/55,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +65636,75958,68783,Probation,elias,mitchell,NULL,Male,Caucasian,02/07/55,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65646,75972,68794,PRETRIAL,LUBIN,KERLINE,NULL,Female,African-American,11/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +65646,75972,68794,PRETRIAL,LUBIN,KERLINE,NULL,Female,African-American,11/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +65646,75972,68794,PRETRIAL,LUBIN,KERLINE,NULL,Female,African-American,11/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65640,75963,68786,Probation,Johnston,Scott,NULL,Male,Caucasian,01/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +65640,75963,68786,Probation,Johnston,Scott,NULL,Male,Caucasian,01/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +65640,75963,68786,Probation,Johnston,Scott,NULL,Male,Caucasian,01/23/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65627,75942,68767,PRETRIAL,WILCOX,JOSE,SYLVESTER,Male,African-American,01/16/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,4,High,7,Risk of Violence,-0.47,10,High,New,1,0 +65627,75942,68767,PRETRIAL,WILCOX,JOSE,SYLVESTER,Male,African-American,01/16/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +65627,75942,68767,PRETRIAL,WILCOX,JOSE,SYLVESTER,Male,African-American,01/16/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +43431,75960,43374,PRETRIAL,Aragon,Oscar,NULL,Male,Hispanic,08/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,Copy,1,0 +43431,75960,43374,PRETRIAL,Aragon,Oscar,NULL,Male,Hispanic,08/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,Copy,1,0 +43431,75960,43374,PRETRIAL,Aragon,Oscar,NULL,Male,Hispanic,08/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +65643,75967,68790,PRETRIAL,MOLINES,JENNYFER,NULL,Female,African-American,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +65643,75967,68790,PRETRIAL,MOLINES,JENNYFER,NULL,Female,African-American,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +65643,75967,68790,PRETRIAL,MOLINES,JENNYFER,NULL,Female,African-American,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65623,75938,68763,PRETRIAL,McCrea,Terrell,Van,Male,African-American,11/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +65623,75938,68763,PRETRIAL,McCrea,Terrell,Van,Male,African-American,11/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +65623,75938,68763,PRETRIAL,McCrea,Terrell,Van,Male,African-American,11/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65644,75968,68791,PRETRIAL,SIERRA,ALFREDO,NULL,Male,Hispanic,03/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/20/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +65644,75968,68791,PRETRIAL,SIERRA,ALFREDO,NULL,Male,Hispanic,03/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +65644,75968,68791,PRETRIAL,SIERRA,ALFREDO,NULL,Male,Hispanic,03/24/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65641,75964,68787,PRETRIAL,Wentz,Brian,NULL,Male,Caucasian,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/20/14 0:00,2,Medium,7,Risk of Violence,-1.95,5,Medium,New,1,0 +65641,75964,68787,PRETRIAL,Wentz,Brian,NULL,Male,Caucasian,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/20/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +65641,75964,68787,PRETRIAL,Wentz,Brian,NULL,Male,Caucasian,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/20/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +7113,75971,68793,PRETRIAL,Estrella,Joshua,NULL,Male,Caucasian,11/30/86,17,All Scales,Intake,English,Pretrial,Probation,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +7113,75971,68793,PRETRIAL,Estrella,Joshua,NULL,Male,Caucasian,11/30/86,17,All Scales,Intake,English,Pretrial,Probation,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.19,5,Medium,New,1,0 +7113,75971,68793,PRETRIAL,Estrella,Joshua,NULL,Male,Caucasian,11/30/86,17,All Scales,Intake,English,Pretrial,Probation,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,31,8,High,New,1,0 +65647,75973,68795,PRETRIAL,Hill,Charles,NULL,Male,African-American,11/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +65647,75973,68795,PRETRIAL,Hill,Charles,NULL,Male,African-American,11/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +65647,75973,68795,PRETRIAL,Hill,Charles,NULL,Male,African-American,11/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +1954,75945,68770,PRETRIAL,KRAMER,JORDAN,JAMIE,Male,Hispanic,08/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,New,1,0 +1954,75945,68770,PRETRIAL,KRAMER,JORDAN,JAMIE,Male,Hispanic,08/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +1954,75945,68770,PRETRIAL,KRAMER,JORDAN,JAMIE,Male,Hispanic,08/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65633,75952,68777,Probation,Umana,German,NULL,Male,Hispanic,07/28/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/20/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +65633,75952,68777,Probation,Umana,German,NULL,Male,Hispanic,07/28/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +65633,75952,68777,Probation,Umana,German,NULL,Male,Hispanic,07/28/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62527,75980,65241,PRETRIAL,Assa,Andrew,NULL,Male,Caucasian,09/08/73,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,Copy,1,0 +62527,75980,65241,PRETRIAL,Assa,Andrew,NULL,Male,Caucasian,09/08/73,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,Copy,1,0 +62527,75980,65241,PRETRIAL,Assa,Andrew,NULL,Male,Caucasian,09/08/73,17,All Scales,Intake,English,Post Sentence,Pretrial Defendant,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +56001,75977,57921,Probation,COATS,SHERMILLA,NULL,Female,African-American,07/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,Copy,1,0 +56001,75977,57921,Probation,COATS,SHERMILLA,NULL,Female,African-American,07/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,Copy,1,0 +56001,75977,57921,Probation,COATS,SHERMILLA,NULL,Female,African-American,07/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +65638,75956,68781,Probation,SCHAIBLEY,ADAM,C,Male,Caucasian,10/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +65638,75956,68781,Probation,SCHAIBLEY,ADAM,C,Male,Caucasian,10/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +65638,75956,68781,Probation,SCHAIBLEY,ADAM,C,Male,Caucasian,10/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +31821,75976,68797,PRETRIAL,HEARD,ANTHONY,ALLEN,Male,African-American,03/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +31821,75976,68797,PRETRIAL,HEARD,ANTHONY,ALLEN,Male,African-American,03/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +31821,75976,68797,PRETRIAL,HEARD,ANTHONY,ALLEN,Male,African-American,03/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65626,75940,68765,PRETRIAL,Cherisnord,Marc,NULL,Male,Other,09/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +65626,75940,68765,PRETRIAL,Cherisnord,Marc,NULL,Male,Other,09/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +65626,75940,68765,PRETRIAL,Cherisnord,Marc,NULL,Male,Other,09/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/20/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +36967,75974,36301,PRETRIAL,Francisco,Sanchezlago,NULL,Male,Hispanic,12/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/20/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,Copy,1,0 +36967,75974,36301,PRETRIAL,Francisco,Sanchezlago,NULL,Male,Hispanic,12/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,Copy,1,0 +36967,75974,36301,PRETRIAL,Francisco,Sanchezlago,NULL,Male,Hispanic,12/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +65634,75953,68778,DRRD,Taylor,Julian,NULL,Male,African-American,09/13/94,17,All Scales,Intake,English,Other,Pretrial Defendant,Single,8/20/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +65634,75953,68778,DRRD,Taylor,Julian,NULL,Male,African-American,09/13/94,17,All Scales,Intake,English,Other,Pretrial Defendant,Single,8/20/14 0:00,1,Low,8,Risk of Recidivism,-0.71,3,Low,New,1,0 +65634,75953,68778,DRRD,Taylor,Julian,NULL,Male,African-American,09/13/94,17,All Scales,Intake,English,Other,Pretrial Defendant,Single,8/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65665,76003,68819,PRETRIAL,Nazere,Luisbens,NULL,Male,African-American,03/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +65665,76003,68819,PRETRIAL,Nazere,Luisbens,NULL,Male,African-American,03/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +65665,76003,68819,PRETRIAL,Nazere,Luisbens,NULL,Male,African-American,03/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65652,75982,68801,PRETRIAL,Arostegui,Diego,NULL,Male,Caucasian,09/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +65652,75982,68801,PRETRIAL,Arostegui,Diego,NULL,Male,Caucasian,09/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +65652,75982,68801,PRETRIAL,Arostegui,Diego,NULL,Male,Caucasian,09/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +35376,76013,68827,PRETRIAL,Laguerre,Nicholas,NULL,Male,Caucasian,04/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +35376,76013,68827,PRETRIAL,Laguerre,Nicholas,NULL,Male,Caucasian,04/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +35376,76013,68827,PRETRIAL,Laguerre,Nicholas,NULL,Male,Caucasian,04/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +46825,76008,68822,Probation,Feldman,Samuel,NULL,Male,Caucasian,04/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +46825,76008,68822,Probation,Feldman,Samuel,NULL,Male,Caucasian,04/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +46825,76008,68822,Probation,Feldman,Samuel,NULL,Male,Caucasian,04/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65677,76021,68835,Probation,Leiva,Danny,NULL,Male,Hispanic,11/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +65677,76021,68835,Probation,Leiva,Danny,NULL,Male,Hispanic,11/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +65677,76021,68835,Probation,Leiva,Danny,NULL,Male,Hispanic,11/03/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +65658,75995,68813,Probation,Fowler,Daniel,Robert,Male,Hispanic,01/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +65658,75995,68813,Probation,Fowler,Daniel,Robert,Male,Hispanic,01/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +65658,75995,68813,Probation,Fowler,Daniel,Robert,Male,Hispanic,01/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65662,76000,68816,Probation,RIOSOSHO,CELINA,NULL,Female,Hispanic,10/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +65662,76000,68816,Probation,RIOSOSHO,CELINA,NULL,Female,Hispanic,10/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +65662,76000,68816,Probation,RIOSOSHO,CELINA,NULL,Female,Hispanic,10/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65676,76019,68833,PRETRIAL,COLLINS,MICHAEL,NULL,Male,African-American,10/28/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +65676,76019,68833,PRETRIAL,COLLINS,MICHAEL,NULL,Male,African-American,10/28/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +65676,76019,68833,PRETRIAL,COLLINS,MICHAEL,NULL,Male,African-American,10/28/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +875,75998,43115,Probation,Dibenedetto,Michael,NULL,Male,Caucasian,04/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/21/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,Copy,1,0 +875,75998,43115,Probation,Dibenedetto,Michael,NULL,Male,Caucasian,04/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/21/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,Copy,1,0 +875,75998,43115,Probation,Dibenedetto,Michael,NULL,Male,Caucasian,04/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/21/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +23790,75990,68809,PRETRIAL,Vipond,Joshua,Robert,Male,Caucasian,11/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +23790,75990,68809,PRETRIAL,Vipond,Joshua,Robert,Male,Caucasian,11/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +23790,75990,68809,PRETRIAL,Vipond,Joshua,Robert,Male,Caucasian,11/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +32887,76005,31951,PRETRIAL,fishman,dean,NULL,Male,Caucasian,07/13/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/21/14 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,Copy,1,0 +32887,76005,31951,PRETRIAL,fishman,dean,NULL,Male,Caucasian,07/13/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/21/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,Copy,1,0 +32887,76005,31951,PRETRIAL,fishman,dean,NULL,Male,Caucasian,07/13/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +65654,75984,68803,PRETRIAL,DELANCY,ROLAND,RENELLE,Female,African-American,02/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +65654,75984,68803,PRETRIAL,DELANCY,ROLAND,RENELLE,Female,African-American,02/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +65654,75984,68803,PRETRIAL,DELANCY,ROLAND,RENELLE,Female,African-American,02/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65670,76011,68825,Probation,Harrell,Norma,NULL,Female,African-American,09/13/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +65670,76011,68825,Probation,Harrell,Norma,NULL,Female,African-American,09/13/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +65670,76011,68825,Probation,Harrell,Norma,NULL,Female,African-American,09/13/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +44615,76018,68832,PRETRIAL,GLASCO,AARON,CHRISTOPHE,Male,African-American,09/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +44615,76018,68832,PRETRIAL,GLASCO,AARON,CHRISTOPHE,Male,African-American,09/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,4,High,8,Risk of Recidivism,1.4,10,High,New,1,0 +44615,76018,68832,PRETRIAL,GLASCO,AARON,CHRISTOPHE,Male,African-American,09/29/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65673,76015,68829,PRETRIAL,COLSON,PEGGY,NULL,Female,Caucasian,12/18/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +65673,76015,68829,PRETRIAL,COLSON,PEGGY,NULL,Female,Caucasian,12/18/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/14 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +65673,76015,68829,PRETRIAL,COLSON,PEGGY,NULL,Female,Caucasian,12/18/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +62333,75987,68806,PRETRIAL,Danovich,Jonathan,NULL,Male,Caucasian,12/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +62333,75987,68806,PRETRIAL,Danovich,Jonathan,NULL,Male,Caucasian,12/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +62333,75987,68806,PRETRIAL,Danovich,Jonathan,NULL,Male,Caucasian,12/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60698,69685,63184,PRETRIAL,LOUIS,ANTHONY,VONTERR,Male,African-American,11/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,New,1,0 +60698,69685,63184,PRETRIAL,LOUIS,ANTHONY,VONTERR,Male,African-American,11/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +60698,69685,63184,PRETRIAL,LOUIS,ANTHONY,VONTERR,Male,African-American,11/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +42676,75985,68804,PRETRIAL,TAVERAS,MANUEL,EUGENIO,Male,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +42676,75985,68804,PRETRIAL,TAVERAS,MANUEL,EUGENIO,Male,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +42676,75985,68804,PRETRIAL,TAVERAS,MANUEL,EUGENIO,Male,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65669,76010,68824,Probation,ramos,kevin,NULL,Male,Hispanic,12/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +65669,76010,68824,Probation,ramos,kevin,NULL,Male,Hispanic,12/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +65669,76010,68824,Probation,ramos,kevin,NULL,Male,Hispanic,12/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65655,75989,68808,PRETRIAL,KLIWINSKI,MICHAEL,JOHN,Male,Caucasian,11/22/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +65655,75989,68808,PRETRIAL,KLIWINSKI,MICHAEL,JOHN,Male,Caucasian,11/22/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +65655,75989,68808,PRETRIAL,KLIWINSKI,MICHAEL,JOHN,Male,Caucasian,11/22/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64481,76006,67496,PRETRIAL,Meadows,David,NULL,Male,Caucasian,10/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,Copy,1,0 +64481,76006,67496,PRETRIAL,Meadows,David,NULL,Male,Caucasian,10/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.06,7,Medium,Copy,1,0 +64481,76006,67496,PRETRIAL,Meadows,David,NULL,Male,Caucasian,10/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +65672,76014,68828,Probation,DALEY,NICOLE,S,Female,African-American,04/21/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +65672,76014,68828,Probation,DALEY,NICOLE,S,Female,African-American,04/21/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +65672,76014,68828,Probation,DALEY,NICOLE,S,Female,African-American,04/21/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +30597,75993,68214,PRETRIAL,Brooks,Christopher,NULL,Male,Caucasian,07/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,Copy,1,0 +30597,75993,68214,PRETRIAL,Brooks,Christopher,NULL,Male,Caucasian,07/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,Copy,1,0 +30597,75993,68214,PRETRIAL,Brooks,Christopher,NULL,Male,Caucasian,07/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +65664,76002,68818,PRETRIAL,Thompson,Michael,NULL,Male,African-American,01/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/21/14 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +65664,76002,68818,PRETRIAL,Thompson,Michael,NULL,Male,African-American,01/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +65664,76002,68818,PRETRIAL,Thompson,Michael,NULL,Male,African-American,01/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/21/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +1695,75988,68807,PRETRIAL,Scott,Michael,Liveal,Male,African-American,01/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,7,Risk of Violence,-1.81,5,Medium,New,1,0 +1695,75988,68807,PRETRIAL,Scott,Michael,Liveal,Male,African-American,01/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +1695,75988,68807,PRETRIAL,Scott,Michael,Liveal,Male,African-American,01/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65667,76007,68821,Probation,West,James,NULL,Male,African-American,06/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +65667,76007,68821,Probation,West,James,NULL,Male,African-American,06/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +65667,76007,68821,Probation,West,James,NULL,Male,African-American,06/21/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,37,10,High,New,1,0 +59626,75986,68805,PRETRIAL,Archibald,Ralante,NULL,Male,African-American,08/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,New,1,0 +59626,75986,68805,PRETRIAL,Archibald,Ralante,NULL,Male,African-American,08/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +59626,75986,68805,PRETRIAL,Archibald,Ralante,NULL,Male,African-American,08/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65668,76009,68823,Probation,Valdes,Jeffrey,NULL,Male,Hispanic,03/25/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +65668,76009,68823,Probation,Valdes,Jeffrey,NULL,Male,Hispanic,03/25/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +65668,76009,68823,Probation,Valdes,Jeffrey,NULL,Male,Hispanic,03/25/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65675,76016,68830,Probation,allen,george,NULL,Male,Caucasian,04/27/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +65675,76016,68830,Probation,allen,george,NULL,Male,Caucasian,04/27/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +65675,76016,68830,Probation,allen,george,NULL,Male,Caucasian,04/27/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +51626,76020,68834,PRETRIAL,GARDNER,MICHAEL,ROBERT,Male,Caucasian,04/02/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +51626,76020,68834,PRETRIAL,GARDNER,MICHAEL,ROBERT,Male,Caucasian,04/02/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +51626,76020,68834,PRETRIAL,GARDNER,MICHAEL,ROBERT,Male,Caucasian,04/02/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +65671,76012,68826,Probation,Julien,Ted,NULL,Male,African-American,03/14/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Significant Other,8/21/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +65671,76012,68826,Probation,Julien,Ted,NULL,Male,African-American,03/14/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Significant Other,8/21/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +65671,76012,68826,Probation,Julien,Ted,NULL,Male,African-American,03/14/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Significant Other,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65653,75983,68802,PRETRIAL,Stevenson,Sally,Dinah,Female,Caucasian,04/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +65653,75983,68802,PRETRIAL,Stevenson,Sally,Dinah,Female,Caucasian,04/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +65653,75983,68802,PRETRIAL,Stevenson,Sally,Dinah,Female,Caucasian,04/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65660,75999,68815,PRETRIAL,WALEROWICZ,ROBERT,NULL,Male,Caucasian,06/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,2,Medium,7,Risk of Violence,-2.86,2,Low,New,1,0 +65660,75999,68815,PRETRIAL,WALEROWICZ,ROBERT,NULL,Male,Caucasian,06/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +65660,75999,68815,PRETRIAL,WALEROWICZ,ROBERT,NULL,Male,Caucasian,06/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +65674,76017,68831,Probation,MENDIETA,ELEANA,NULL,Female,Hispanic,06/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/21/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +65674,76017,68831,Probation,MENDIETA,ELEANA,NULL,Female,Hispanic,06/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/21/14 0:00,1,Low,8,Risk of Recidivism,-1.52,2,Low,New,1,0 +65674,76017,68831,Probation,MENDIETA,ELEANA,NULL,Female,Hispanic,06/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/21/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65666,76004,68820,Probation,delacruz,edric,NULL,Male,Hispanic,06/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +65666,76004,68820,Probation,delacruz,edric,NULL,Male,Hispanic,06/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +65666,76004,68820,Probation,delacruz,edric,NULL,Male,Hispanic,06/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/21/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65656,75991,68810,PRETRIAL,Mckinley,William,NULL,Male,Caucasian,08/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +65656,75991,68810,PRETRIAL,Mckinley,William,NULL,Male,Caucasian,08/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +65656,75991,68810,PRETRIAL,Mckinley,William,NULL,Male,Caucasian,08/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/21/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +49081,76025,68838,PRETRIAL,Limato,Seamus,NULL,Male,Caucasian,11/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +49081,76025,68838,PRETRIAL,Limato,Seamus,NULL,Male,Caucasian,11/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +49081,76025,68838,PRETRIAL,Limato,Seamus,NULL,Male,Caucasian,11/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65689,76038,68851,Probation,ZAMORANO,MIGUEL,NULL,Male,Hispanic,01/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +65689,76038,68851,Probation,ZAMORANO,MIGUEL,NULL,Male,Hispanic,01/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +65689,76038,68851,Probation,ZAMORANO,MIGUEL,NULL,Male,Hispanic,01/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65721,76072,68884,Probation,harris,Sony,NULL,Male,African-American,01/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/22/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +65721,76072,68884,Probation,harris,Sony,NULL,Male,African-American,01/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/22/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +65721,76072,68884,Probation,harris,Sony,NULL,Male,African-American,01/28/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65696,76048,68861,PRETRIAL,Perez,Rose,NULL,Female,Caucasian,06/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.38,3,Low,New,1,0 +65696,76048,68861,PRETRIAL,Perez,Rose,NULL,Female,Caucasian,06/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,10,High,New,1,0 +65696,76048,68861,PRETRIAL,Perez,Rose,NULL,Female,Caucasian,06/11/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +40666,76083,68894,PRETRIAL,PASS,KHALIL,NULL,Male,African-American,01/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +40666,76083,68894,PRETRIAL,PASS,KHALIL,NULL,Male,African-American,01/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +40666,76083,68894,PRETRIAL,PASS,KHALIL,NULL,Male,African-American,01/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65712,76062,68874,Probation,Navarrette,Cesar,NULL,Male,Hispanic,02/06/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +65712,76062,68874,Probation,Navarrette,Cesar,NULL,Male,Hispanic,02/06/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +65712,76062,68874,Probation,Navarrette,Cesar,NULL,Male,Hispanic,02/06/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65718,76069,68881,Probation,Jackson,Arriba,Yquim,Female,African-American,08/20/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,2,Medium,7,Risk of Violence,-2.82,2,Low,New,1,0 +65718,76069,68881,Probation,Jackson,Arriba,Yquim,Female,African-American,08/20/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +65718,76069,68881,Probation,Jackson,Arriba,Yquim,Female,African-American,08/20/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65701,76054,68867,Probation,Bericocheabaralt,Sheryl,Marie,Female,Caucasian,02/15/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +65701,76054,68867,Probation,Bericocheabaralt,Sheryl,Marie,Female,Caucasian,02/15/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +65701,76054,68867,Probation,Bericocheabaralt,Sheryl,Marie,Female,Caucasian,02/15/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65725,76077,68889,Probation,Bradwell,Brittney,NULL,Female,African-American,09/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +65725,76077,68889,Probation,Bradwell,Brittney,NULL,Female,African-American,09/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +65725,76077,68889,Probation,Bradwell,Brittney,NULL,Female,African-American,09/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65691,76041,68854,PRETRIAL,Baptista,Armando,Lopes,Male,African-American,03/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/22/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +65691,76041,68854,PRETRIAL,Baptista,Armando,Lopes,Male,African-American,03/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/22/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +65691,76041,68854,PRETRIAL,Baptista,Armando,Lopes,Male,African-American,03/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59437,76056,68868,Probation,hirsch,steven,NULL,Male,Other,06/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +59437,76056,68868,Probation,hirsch,steven,NULL,Male,Other,06/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +59437,76056,68868,Probation,hirsch,steven,NULL,Male,Other,06/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +46033,76030,68843,PRETRIAL,Verdi,Elijah,Nathaniel,Male,African-American,08/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +46033,76030,68843,PRETRIAL,Verdi,Elijah,Nathaniel,Male,African-American,08/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +46033,76030,68843,PRETRIAL,Verdi,Elijah,Nathaniel,Male,African-American,08/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59470,76037,68850,PRETRIAL,Arenas,William,NULL,Male,Hispanic,09/26/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +59470,76037,68850,PRETRIAL,Arenas,William,NULL,Male,Hispanic,09/26/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +59470,76037,68850,PRETRIAL,Arenas,William,NULL,Male,Hispanic,09/26/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65694,76044,68857,Probation,hipperling,jonathan,NULL,Male,Caucasian,04/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +65694,76044,68857,Probation,hipperling,jonathan,NULL,Male,Caucasian,04/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +65694,76044,68857,Probation,hipperling,jonathan,NULL,Male,Caucasian,04/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65724,76079,68890,Probation,Toussaint,Michelle,NULL,Female,Hispanic,04/25/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +65724,76079,68890,Probation,Toussaint,Michelle,NULL,Female,Hispanic,04/25/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/14 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +65724,76079,68890,Probation,Toussaint,Michelle,NULL,Female,Hispanic,04/25/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +65706,76058,68870,Probation,brown,cavaughn,NULL,Male,African-American,11/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +65706,76058,68870,Probation,brown,cavaughn,NULL,Male,African-American,11/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +65706,76058,68870,Probation,brown,cavaughn,NULL,Male,African-American,11/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65716,76070,68882,Probation,simonelli,jonathan,NULL,Male,Hispanic,12/01/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +65716,76070,68882,Probation,simonelli,jonathan,NULL,Male,Hispanic,12/01/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +65716,76070,68882,Probation,simonelli,jonathan,NULL,Male,Hispanic,12/01/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +39890,76023,39474,PRETRIAL,Bynes,Kevin,NULL,Male,African-American,03/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,2,Medium,7,Risk of Violence,-1.33,7,Medium,Copy,1,0 +39890,76023,39474,PRETRIAL,Bynes,Kevin,NULL,Male,African-American,03/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,Copy,1,0 +39890,76023,39474,PRETRIAL,Bynes,Kevin,NULL,Male,African-American,03/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +65723,76074,68886,PRETRIAL,HUNT,JERUSALEM,NULL,Female,African-American,02/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +65723,76074,68886,PRETRIAL,HUNT,JERUSALEM,NULL,Female,African-American,02/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +65723,76074,68886,PRETRIAL,HUNT,JERUSALEM,NULL,Female,African-American,02/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65682,76032,68845,Probation,White,Dillon,S,Male,Caucasian,04/28/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +65682,76032,68845,Probation,White,Dillon,S,Male,Caucasian,04/28/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +65682,76032,68845,Probation,White,Dillon,S,Male,Caucasian,04/28/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65680,76028,68841,PRETRIAL,Brown,Shakime,NULL,Male,African-American,06/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +65680,76028,68841,PRETRIAL,Brown,Shakime,NULL,Male,African-American,06/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +65680,76028,68841,PRETRIAL,Brown,Shakime,NULL,Male,African-American,06/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65685,76035,68848,Probation,Gomez,Nicholas,NULL,Male,Hispanic,08/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +65685,76035,68848,Probation,Gomez,Nicholas,NULL,Male,Hispanic,08/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +65685,76035,68848,Probation,Gomez,Nicholas,NULL,Male,Hispanic,08/11/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65687,76040,68853,DRRD,Walker,Clifford,NULL,Male,African-American,11/01/65,22,Risk and Prescreen,Intake,English,Deferred Sentencing,Probation,Divorced,8/22/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +65687,76040,68853,DRRD,Walker,Clifford,NULL,Male,African-American,11/01/65,22,Risk and Prescreen,Intake,English,Deferred Sentencing,Probation,Divorced,8/22/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +65687,76040,68853,DRRD,Walker,Clifford,NULL,Male,African-American,11/01/65,22,Risk and Prescreen,Intake,English,Deferred Sentencing,Probation,Divorced,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61117,76027,68840,PRETRIAL,Babkin,Alexander,NULL,Male,Caucasian,06/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/22/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +61117,76027,68840,PRETRIAL,Babkin,Alexander,NULL,Male,Caucasian,06/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/22/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +61117,76027,68840,PRETRIAL,Babkin,Alexander,NULL,Male,Caucasian,06/28/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65711,76061,68873,PRETRIAL,guess,samuel,NULL,Male,African-American,06/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/22/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +65711,76061,68873,PRETRIAL,guess,samuel,NULL,Male,African-American,06/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/22/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +65711,76061,68873,PRETRIAL,guess,samuel,NULL,Male,African-American,06/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +40349,76031,68844,PRETRIAL,Sapp,Ronald,NULL,Male,African-American,01/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/22/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +40349,76031,68844,PRETRIAL,Sapp,Ronald,NULL,Male,African-American,01/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +40349,76031,68844,PRETRIAL,Sapp,Ronald,NULL,Male,African-American,01/12/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/22/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +65727,76082,68893,Probation,Camacho,Julian,NULL,Male,Hispanic,01/28/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/22/14 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +65727,76082,68893,Probation,Camacho,Julian,NULL,Male,Hispanic,01/28/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/22/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +65727,76082,68893,Probation,Camacho,Julian,NULL,Male,Hispanic,01/28/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65726,76080,68891,DRRD,Serrano,Crystal,NULL,Female,Hispanic,03/28/93,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,8/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,New,1,0 +65726,76080,68891,DRRD,Serrano,Crystal,NULL,Female,Hispanic,03/28/93,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,8/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,8,High,New,1,0 +65726,76080,68891,DRRD,Serrano,Crystal,NULL,Female,Hispanic,03/28/93,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,8/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65692,76043,68856,Probation,Lockhart,Roland,oliver,Male,Caucasian,01/21/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/22/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +65692,76043,68856,Probation,Lockhart,Roland,oliver,Male,Caucasian,01/21/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/22/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +65692,76043,68856,Probation,Lockhart,Roland,oliver,Male,Caucasian,01/21/77,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +7844,76022,68836,PRETRIAL,JOHNKINS,OLIVER,NULL,Male,African-American,09/03/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +7844,76022,68836,PRETRIAL,JOHNKINS,OLIVER,NULL,Male,African-American,09/03/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +7844,76022,68836,PRETRIAL,JOHNKINS,OLIVER,NULL,Male,African-American,09/03/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +65678,76024,68837,PRETRIAL,Pepperine,John,NULL,Male,Caucasian,04/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/22/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +65678,76024,68837,PRETRIAL,Pepperine,John,NULL,Male,Caucasian,04/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/22/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +65678,76024,68837,PRETRIAL,Pepperine,John,NULL,Male,Caucasian,04/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65720,76071,68883,Probation,nguyen,coung,NULL,Male,Asian,08/04/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +65720,76071,68883,Probation,nguyen,coung,NULL,Male,Asian,08/04/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +65720,76071,68883,Probation,nguyen,coung,NULL,Male,Asian,08/04/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65722,76073,68885,PRETRIAL,gonzalez,aquilino,NULL,Male,Hispanic,04/17/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,4,High,7,Risk of Violence,-0.92,9,High,New,1,0 +65722,76073,68885,PRETRIAL,gonzalez,aquilino,NULL,Male,Hispanic,04/17/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,4,High,8,Risk of Recidivism,0.47,9,High,New,1,0 +65722,76073,68885,PRETRIAL,gonzalez,aquilino,NULL,Male,Hispanic,04/17/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,4,High,18,Risk of Failure to Appear,19,2,Low,New,1,0 +65690,76039,68852,Probation,Pastorius,Julius,NULL,Male,Caucasian,06/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +65690,76039,68852,Probation,Pastorius,Julius,NULL,Male,Caucasian,06/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +65690,76039,68852,Probation,Pastorius,Julius,NULL,Male,Caucasian,06/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +28366,76047,68860,PRETRIAL,Head,Brittany,Lynn,Male,Caucasian,09/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +28366,76047,68860,PRETRIAL,Head,Brittany,Lynn,Male,Caucasian,09/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.8,10,High,New,1,0 +28366,76047,68860,PRETRIAL,Head,Brittany,Lynn,Male,Caucasian,09/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65679,76026,68839,PRETRIAL,Stevens,Charles,NULL,Male,African-American,11/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,4,High,7,Risk of Violence,-1.03,8,High,New,1,0 +65679,76026,68839,PRETRIAL,Stevens,Charles,NULL,Male,African-American,11/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +65679,76026,68839,PRETRIAL,Stevens,Charles,NULL,Male,African-American,11/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/22/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60926,76076,68888,PRETRIAL,Pineda,Douglas,NULL,Male,Hispanic,09/12/78,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/22/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +60926,76076,68888,PRETRIAL,Pineda,Douglas,NULL,Male,Hispanic,09/12/78,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/22/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +60926,76076,68888,PRETRIAL,Pineda,Douglas,NULL,Male,Hispanic,09/12/78,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65684,76034,68847,Probation,Apollon,Reginald,NULL,Male,African-American,12/25/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,New,1,0 +65684,76034,68847,Probation,Apollon,Reginald,NULL,Male,African-American,12/25/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +65684,76034,68847,Probation,Apollon,Reginald,NULL,Male,African-American,12/25/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,2,Medium,18,Risk of Failure to Appear,40,10,High,New,1,0 +59270,76050,68863,PRETRIAL,Brown,John,NULL,Male,Caucasian,04/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +59270,76050,68863,PRETRIAL,Brown,John,NULL,Male,Caucasian,04/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +59270,76050,68863,PRETRIAL,Brown,John,NULL,Male,Caucasian,04/05/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +48047,76042,68855,PRETRIAL,severin,Jaylan,NULL,Male,African-American,06/03/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.95,5,Medium,New,1,0 +48047,76042,68855,PRETRIAL,severin,Jaylan,NULL,Male,African-American,06/03/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +48047,76042,68855,PRETRIAL,severin,Jaylan,NULL,Male,African-American,06/03/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56761,76060,68872,Probation,Cooper,Devin,NULL,Male,African-American,11/01/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.14,4,Low,New,1,0 +56761,76060,68872,Probation,Cooper,Devin,NULL,Male,African-American,11/01/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +56761,76060,68872,Probation,Cooper,Devin,NULL,Male,African-American,11/01/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65731,76089,68899,PRETRIAL,Howard,Derrica,S,Female,African-American,06/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +65731,76089,68899,PRETRIAL,Howard,Derrica,S,Female,African-American,06/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,8,High,New,1,0 +65731,76089,68899,PRETRIAL,Howard,Derrica,S,Female,African-American,06/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +41580,76084,41293,PRETRIAL,Vassel,Travis,NULL,Male,Other,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,Copy,1,0 +41580,76084,41293,PRETRIAL,Vassel,Travis,NULL,Male,Other,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,Copy,1,0 +41580,76084,41293,PRETRIAL,Vassel,Travis,NULL,Male,Other,10/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +65728,76087,68897,PRETRIAL,Raymond,Frantz,NULL,Male,Other,05/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +65728,76087,68897,PRETRIAL,Raymond,Frantz,NULL,Male,Other,05/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +65728,76087,68897,PRETRIAL,Raymond,Frantz,NULL,Male,Other,05/02/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65733,76091,68901,PRETRIAL,MART,GERALD,NULL,Male,Caucasian,05/26/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/23/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +65733,76091,68901,PRETRIAL,MART,GERALD,NULL,Male,Caucasian,05/26/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/23/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +65733,76091,68901,PRETRIAL,MART,GERALD,NULL,Male,Caucasian,05/26/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65730,76088,68898,PRETRIAL,Godoy,Dominique,Alexander,Male,Hispanic,07/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +65730,76088,68898,PRETRIAL,Godoy,Dominique,Alexander,Male,Hispanic,07/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +65730,76088,68898,PRETRIAL,Godoy,Dominique,Alexander,Male,Hispanic,07/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65729,76086,68896,PRETRIAL,Cofre,Cesar,NULL,Male,Caucasian,12/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +65729,76086,68896,PRETRIAL,Cofre,Cesar,NULL,Male,Caucasian,12/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +65729,76086,68896,PRETRIAL,Cofre,Cesar,NULL,Male,Caucasian,12/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65732,76090,68900,PRETRIAL,Stratigeas,Nicholas,George,Male,Caucasian,04/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +65732,76090,68900,PRETRIAL,Stratigeas,Nicholas,George,Male,Caucasian,04/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +65732,76090,68900,PRETRIAL,Stratigeas,Nicholas,George,Male,Caucasian,04/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +15220,76085,68895,DRRD,Caldwell,Dinson,NULL,Male,Caucasian,06/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +15220,76085,68895,DRRD,Caldwell,Dinson,NULL,Male,Caucasian,06/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +15220,76085,68895,DRRD,Caldwell,Dinson,NULL,Male,Caucasian,06/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65735,76093,68903,PRETRIAL,Santiago,Adrian,Alberto,Male,Hispanic,06/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +65735,76093,68903,PRETRIAL,Santiago,Adrian,Alberto,Male,Hispanic,06/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +65735,76093,68903,PRETRIAL,Santiago,Adrian,Alberto,Male,Hispanic,06/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65737,76095,68905,PRETRIAL,THOMAS,KENTON,NULL,Male,African-American,03/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +65737,76095,68905,PRETRIAL,THOMAS,KENTON,NULL,Male,African-American,03/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +65737,76095,68905,PRETRIAL,THOMAS,KENTON,NULL,Male,African-American,03/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65739,76100,68908,PRETRIAL,hull,janae,NULL,Female,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.75,5,Medium,New,1,0 +65739,76100,68908,PRETRIAL,hull,janae,NULL,Female,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,10,High,New,1,0 +65739,76100,68908,PRETRIAL,hull,janae,NULL,Female,African-American,01/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65736,76094,68904,PRETRIAL,Parker,Michael,NULL,Male,Caucasian,04/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +65736,76094,68904,PRETRIAL,Parker,Michael,NULL,Male,Caucasian,04/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +65736,76094,68904,PRETRIAL,Parker,Michael,NULL,Male,Caucasian,04/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65738,76099,68907,PRETRIAL,Grehl,Michael,Scott,Male,Caucasian,12/07/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/24/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,Copy,1,0 +65738,76099,68907,PRETRIAL,Grehl,Michael,Scott,Male,Caucasian,12/07/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/24/14 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,Copy,1,0 +65738,76099,68907,PRETRIAL,Grehl,Michael,Scott,Male,Caucasian,12/07/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/24/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +65734,76092,68902,PRETRIAL,Appleton,Antoine,NULL,Male,African-American,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +65734,76092,68902,PRETRIAL,Appleton,Antoine,NULL,Male,African-American,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +65734,76092,68902,PRETRIAL,Appleton,Antoine,NULL,Male,African-American,04/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +31182,76096,68906,PRETRIAL,smith,antoine,NULL,Male,African-American,01/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +31182,76096,68906,PRETRIAL,smith,antoine,NULL,Male,African-American,01/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +31182,76096,68906,PRETRIAL,smith,antoine,NULL,Male,African-American,01/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63634,76097,66548,PRETRIAL,Evans,Mark,NULL,Male,African-American,03/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,Copy,1,0 +63634,76097,66548,PRETRIAL,Evans,Mark,NULL,Male,African-American,03/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +63634,76097,66548,PRETRIAL,Evans,Mark,NULL,Male,African-American,03/03/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +65765,76133,68934,PRETRIAL,Cruz,Eliel,NULL,Male,Hispanic,05/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +65765,76133,68934,PRETRIAL,Cruz,Eliel,NULL,Male,Hispanic,05/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +65765,76133,68934,PRETRIAL,Cruz,Eliel,NULL,Male,Hispanic,05/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65775,76147,68947,Probation,smith,mark,NULL,Male,Caucasian,09/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +65775,76147,68947,Probation,smith,mark,NULL,Male,Caucasian,09/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +65775,76147,68947,Probation,smith,mark,NULL,Male,Caucasian,09/25/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65762,76126,68930,PRETRIAL,TURNER,STEVEN,M,Male,Caucasian,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +65762,76126,68930,PRETRIAL,TURNER,STEVEN,M,Male,Caucasian,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +65762,76126,68930,PRETRIAL,TURNER,STEVEN,M,Male,Caucasian,12/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +57258,76118,68924,PRETRIAL,Blackwood,Britton,NULL,Male,African-American,05/25/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,4,High,7,Risk of Violence,-0.52,10,High,New,1,0 +57258,76118,68924,PRETRIAL,Blackwood,Britton,NULL,Male,African-American,05/25/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,4,High,8,Risk of Recidivism,0.92,10,High,New,1,0 +57258,76118,68924,PRETRIAL,Blackwood,Britton,NULL,Male,African-American,05/25/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +34020,76120,33148,PRETRIAL,EXCELLENT,STEVE,NULL,Male,African-American,09/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/25/14 0:00,4,High,7,Risk of Violence,-1.06,8,High,Copy,1,0 +34020,76120,33148,PRETRIAL,EXCELLENT,STEVE,NULL,Male,African-American,09/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/25/14 0:00,4,High,8,Risk of Recidivism,0.54,9,High,Copy,1,0 +34020,76120,33148,PRETRIAL,EXCELLENT,STEVE,NULL,Male,African-American,09/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/25/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +65779,76154,68953,Probation,burch,christopher,NULL,Male,Caucasian,01/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +65779,76154,68953,Probation,burch,christopher,NULL,Male,Caucasian,01/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +65779,76154,68953,Probation,burch,christopher,NULL,Male,Caucasian,01/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65743,76105,68913,PRETRIAL,MOLLI,SULAMYN,NULL,Female,Caucasian,01/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/25/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +65743,76105,68913,PRETRIAL,MOLLI,SULAMYN,NULL,Female,Caucasian,01/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/25/14 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +65743,76105,68913,PRETRIAL,MOLLI,SULAMYN,NULL,Female,Caucasian,01/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57108,76139,59202,PRETRIAL,Irby,Anthony,NULL,Male,African-American,01/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/25/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,Copy,1,0 +57108,76139,59202,PRETRIAL,Irby,Anthony,NULL,Male,African-American,01/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/25/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,Copy,1,0 +57108,76139,59202,PRETRIAL,Irby,Anthony,NULL,Male,African-American,01/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +65772,76141,68941,Probation,Bent,Bradley,NULL,Male,African-American,04/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +65772,76141,68941,Probation,Bent,Bradley,NULL,Male,African-American,04/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +65772,76141,68941,Probation,Bent,Bradley,NULL,Male,African-American,04/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51670,76123,68927,PRETRIAL,Salnave,Fidel,NULL,Male,Caucasian,07/04/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +51670,76123,68927,PRETRIAL,Salnave,Fidel,NULL,Male,Caucasian,07/04/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +51670,76123,68927,PRETRIAL,Salnave,Fidel,NULL,Male,Caucasian,07/04/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65782,76157,68956,DRRD,Murray,Marissa,NULL,Female,African-American,03/13/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/25/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +65782,76157,68956,DRRD,Murray,Marissa,NULL,Female,African-American,03/13/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +65782,76157,68956,DRRD,Murray,Marissa,NULL,Female,African-American,03/13/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65741,76102,68910,PRETRIAL,BAUM,GARY,N,Male,Caucasian,03/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +65741,76102,68910,PRETRIAL,BAUM,GARY,N,Male,Caucasian,03/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +65741,76102,68910,PRETRIAL,BAUM,GARY,N,Male,Caucasian,03/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65768,76136,68937,PRETRIAL,Miller,Alexander,NULL,Male,Caucasian,11/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +65768,76136,68937,PRETRIAL,Miller,Alexander,NULL,Male,Caucasian,11/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +65768,76136,68937,PRETRIAL,Miller,Alexander,NULL,Male,Caucasian,11/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65825,76196,68988,PRETRIAL,Alfred,Mckinsy,NULL,Male,African-American,04/12/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/25/14 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +65825,76196,68988,PRETRIAL,Alfred,Mckinsy,NULL,Male,African-American,04/12/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +65825,76196,68988,PRETRIAL,Alfred,Mckinsy,NULL,Male,African-American,04/12/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65764,76131,68933,Probation,Flores,Michael,NULL,Male,Caucasian,12/09/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +65764,76131,68933,Probation,Flores,Michael,NULL,Male,Caucasian,12/09/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +65764,76131,68933,Probation,Flores,Michael,NULL,Male,Caucasian,12/09/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65776,76149,68949,Probation,Cramasta,Brandon,NULL,Male,Caucasian,10/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +65776,76149,68949,Probation,Cramasta,Brandon,NULL,Male,Caucasian,10/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +65776,76149,68949,Probation,Cramasta,Brandon,NULL,Male,Caucasian,10/27/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +5107,76103,68911,PRETRIAL,TOLBERT,GARTRELL,DEVON,Male,African-American,06/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +5107,76103,68911,PRETRIAL,TOLBERT,GARTRELL,DEVON,Male,African-American,06/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,4,High,8,Risk of Recidivism,0.41,9,High,New,1,0 +5107,76103,68911,PRETRIAL,TOLBERT,GARTRELL,DEVON,Male,African-American,06/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65754,76113,68920,PRETRIAL,cheek,natasha,NULL,Female,Caucasian,01/18/78,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +65754,76113,68920,PRETRIAL,cheek,natasha,NULL,Female,Caucasian,01/18/78,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +65754,76113,68920,PRETRIAL,cheek,natasha,NULL,Female,Caucasian,01/18/78,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65766,76134,68935,PRETRIAL,Durand,Mathiel,NULL,Male,African-American,04/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +65766,76134,68935,PRETRIAL,Durand,Mathiel,NULL,Male,African-American,04/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +65766,76134,68935,PRETRIAL,Durand,Mathiel,NULL,Male,African-American,04/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65746,76108,68916,PRETRIAL,BROWN,VINROY,D,Male,African-American,01/06/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/25/14 0:00,1,Low,7,Risk of Violence,-4.54,1,Low,New,1,0 +65746,76108,68916,PRETRIAL,BROWN,VINROY,D,Male,African-American,01/06/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/25/14 0:00,1,Low,8,Risk of Recidivism,-2.94,1,Low,New,1,0 +65746,76108,68916,PRETRIAL,BROWN,VINROY,D,Male,African-American,01/06/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65770,76138,68939,Probation,Franchino,Joseph,NULL,Male,Caucasian,05/04/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +65770,76138,68939,Probation,Franchino,Joseph,NULL,Male,Caucasian,05/04/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +65770,76138,68939,Probation,Franchino,Joseph,NULL,Male,Caucasian,05/04/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65780,76155,68954,Probation,Ramos,Armando,NULL,Male,Hispanic,02/09/62,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/25/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +65780,76155,68954,Probation,Ramos,Armando,NULL,Male,Hispanic,02/09/62,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +65780,76155,68954,Probation,Ramos,Armando,NULL,Male,Hispanic,02/09/62,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65740,76101,68909,PRETRIAL,SIMMONS,NICHOLAS,L,Male,African-American,10/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +65740,76101,68909,PRETRIAL,SIMMONS,NICHOLAS,L,Male,African-American,10/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +65740,76101,68909,PRETRIAL,SIMMONS,NICHOLAS,L,Male,African-American,10/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65758,76122,68926,DRRD,Brown,Brandon,NULL,Male,African-American,04/29/87,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,8/25/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +65758,76122,68926,DRRD,Brown,Brandon,NULL,Male,African-American,04/29/87,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,8/25/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +65758,76122,68926,DRRD,Brown,Brandon,NULL,Male,African-American,04/29/87,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65773,76143,68943,Probation,santiago,gerardo,NULL,Male,Hispanic,02/24/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +65773,76143,68943,Probation,santiago,gerardo,NULL,Male,Hispanic,02/24/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +65773,76143,68943,Probation,santiago,gerardo,NULL,Male,Hispanic,02/24/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65777,76152,68951,Probation,Stjeansierralane,Sandra,NULL,Female,African-American,01/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +65777,76152,68951,Probation,Stjeansierralane,Sandra,NULL,Female,African-American,01/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,New,1,0 +65777,76152,68951,Probation,Stjeansierralane,Sandra,NULL,Female,African-American,01/08/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +1636,76142,68942,PRETRIAL,Bates,Wesley,Ryan,Male,Caucasian,08/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +1636,76142,68942,PRETRIAL,Bates,Wesley,Ryan,Male,Caucasian,08/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,4,High,8,Risk of Recidivism,0.2,8,High,New,1,0 +1636,76142,68942,PRETRIAL,Bates,Wesley,Ryan,Male,Caucasian,08/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +46473,76146,68946,PRETRIAL,WILSON,RASHAAD,DWAYNE,Male,African-American,03/22/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +46473,76146,68946,PRETRIAL,WILSON,RASHAAD,DWAYNE,Male,African-American,03/22/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,4,High,8,Risk of Recidivism,0.63,9,High,New,1,0 +46473,76146,68946,PRETRIAL,WILSON,RASHAAD,DWAYNE,Male,African-American,03/22/85,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,4,High,18,Risk of Failure to Appear,22,4,Low,New,1,0 +65742,76104,68912,PRETRIAL,Barnett,Andrea,NULL,Female,Other,10/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.23,1,Low,New,1,0 +65742,76104,68912,PRETRIAL,Barnett,Andrea,NULL,Female,Other,10/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,8,High,New,1,0 +65742,76104,68912,PRETRIAL,Barnett,Andrea,NULL,Female,Other,10/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65761,76125,68929,Probation,SMITH,VIRGIL,NULL,Male,African-American,12/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +65761,76125,68929,Probation,SMITH,VIRGIL,NULL,Male,African-American,12/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +65761,76125,68929,Probation,SMITH,VIRGIL,NULL,Male,African-American,12/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65664,76109,68818,PRETRIAL,Thompson,Michael,NULL,Male,African-American,01/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/14 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,Copy,1,0 +65664,76109,68818,PRETRIAL,Thompson,Michael,NULL,Male,African-American,01/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,Copy,1,0 +65664,76109,68818,PRETRIAL,Thompson,Michael,NULL,Male,African-American,01/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +65745,76107,68915,PRETRIAL,Robert,Sami,NULL,Male,Other,07/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/25/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +65745,76107,68915,PRETRIAL,Robert,Sami,NULL,Male,Other,07/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +65745,76107,68915,PRETRIAL,Robert,Sami,NULL,Male,Other,07/22/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65769,76137,68938,Probation,Auguste,Jehu,NULL,Male,African-American,08/29/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/25/14 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,New,1,0 +65769,76137,68938,Probation,Auguste,Jehu,NULL,Male,African-American,08/29/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +65769,76137,68938,Probation,Auguste,Jehu,NULL,Male,African-American,08/29/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +21673,76144,68944,Probation,Evra,Jean,NULL,Male,African-American,05/04/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +21673,76144,68944,Probation,Evra,Jean,NULL,Male,African-American,05/04/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +21673,76144,68944,Probation,Evra,Jean,NULL,Male,African-American,05/04/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65763,76130,68932,Probation,Skillon,Tiare,NULL,Female,African-American,05/08/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +65763,76130,68932,Probation,Skillon,Tiare,NULL,Female,African-American,05/08/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +65763,76130,68932,Probation,Skillon,Tiare,NULL,Female,African-American,05/08/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +58818,76127,68931,Probation,DAVIS,ALPHEUS,NULL,Male,African-American,08/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +58818,76127,68931,Probation,DAVIS,ALPHEUS,NULL,Male,African-American,08/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +58818,76127,68931,Probation,DAVIS,ALPHEUS,NULL,Male,African-American,08/15/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65744,76106,68914,PRETRIAL,Fitzpatrick,Genevieve,Grace,Female,Caucasian,10/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +65744,76106,68914,PRETRIAL,Fitzpatrick,Genevieve,Grace,Female,Caucasian,10/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +65744,76106,68914,PRETRIAL,Fitzpatrick,Genevieve,Grace,Female,Caucasian,10/10/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65771,76140,68940,Probation,Watson,Trayvon,NULL,Male,African-American,08/24/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +65771,76140,68940,Probation,Watson,Trayvon,NULL,Male,African-American,08/24/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +65771,76140,68940,Probation,Watson,Trayvon,NULL,Male,African-American,08/24/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65767,76135,68936,Probation,Ferrada,Pedro,NULL,Male,Hispanic,04/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +65767,76135,68936,Probation,Ferrada,Pedro,NULL,Male,Hispanic,04/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +65767,76135,68936,Probation,Ferrada,Pedro,NULL,Male,Hispanic,04/17/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +65778,76153,68952,Probation,Estrada,Nestor,NULL,Male,Hispanic,12/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +65778,76153,68952,Probation,Estrada,Nestor,NULL,Male,Hispanic,12/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +65778,76153,68952,Probation,Estrada,Nestor,NULL,Male,Hispanic,12/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +8805,76132,8340,PRETRIAL,Williams,Antoine,NULL,Male,African-American,04/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,Copy,1,0 +8805,76132,8340,PRETRIAL,Williams,Antoine,NULL,Male,African-American,04/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,Copy,1,0 +8805,76132,8340,PRETRIAL,Williams,Antoine,NULL,Male,African-American,04/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +65781,76156,68955,Probation,NELSON,ALEXANDER,NULL,Male,African-American,09/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +65781,76156,68955,Probation,NELSON,ALEXANDER,NULL,Male,African-American,09/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +65781,76156,68955,Probation,NELSON,ALEXANDER,NULL,Male,African-American,09/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65753,76111,68918,DRRD,Josephs,Clayton,NULL,Male,African-American,01/04/92,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,8/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +65753,76111,68918,DRRD,Josephs,Clayton,NULL,Male,African-American,01/04/92,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,8/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +65753,76111,68918,DRRD,Josephs,Clayton,NULL,Male,African-American,01/04/92,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,8/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +8805,8900,8340,PRETRIAL,Williams,Antoine,NULL,Male,African-American,04/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +8805,8900,8340,PRETRIAL,Williams,Antoine,NULL,Male,African-American,04/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +8805,8900,8340,PRETRIAL,Williams,Antoine,NULL,Male,African-American,04/13/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/25/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +59980,76119,62355,PRETRIAL,Mauro,John,NULL,Male,Caucasian,03/07/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +59980,76119,62355,PRETRIAL,Mauro,John,NULL,Male,Caucasian,03/07/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +59980,76119,62355,PRETRIAL,Mauro,John,NULL,Male,Caucasian,03/07/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30397,76148,68948,PRETRIAL,sartori,daniel,NULL,Male,Caucasian,05/09/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/25/14 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +30397,76148,68948,PRETRIAL,sartori,daniel,NULL,Male,Caucasian,05/09/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +30397,76148,68948,PRETRIAL,sartori,daniel,NULL,Male,Caucasian,05/09/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/25/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +49770,76197,68989,PRETRIAL,Almodovar,Alicia,NULL,Female,Caucasian,08/22/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/26/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +49770,76197,68989,PRETRIAL,Almodovar,Alicia,NULL,Female,Caucasian,08/22/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/26/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +49770,76197,68989,PRETRIAL,Almodovar,Alicia,NULL,Female,Caucasian,08/22/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65826,76198,68990,PRETRIAL,GOMEZ,JEAN,PIERRE,Male,Hispanic,04/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/26/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +65826,76198,68990,PRETRIAL,GOMEZ,JEAN,PIERRE,Male,Hispanic,04/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/26/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +65826,76198,68990,PRETRIAL,GOMEZ,JEAN,PIERRE,Male,Hispanic,04/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65813,76176,68972,PRETRIAL,Wheeler,Katrina,NULL,Female,African-American,01/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,8/26/14 0:00,2,Medium,7,Risk of Violence,-2.19,4,Low,New,1,0 +65813,76176,68972,PRETRIAL,Wheeler,Katrina,NULL,Female,African-American,01/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,8/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,7,Medium,New,1,0 +65813,76176,68972,PRETRIAL,Wheeler,Katrina,NULL,Female,African-American,01/26/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,8/26/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +65817,76184,68977,Probation,Pireta,John,NULL,Male,Hispanic,11/27/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +65817,76184,68977,Probation,Pireta,John,NULL,Male,Hispanic,11/27/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +65817,76184,68977,Probation,Pireta,John,NULL,Male,Hispanic,11/27/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +50338,76190,68982,PRETRIAL,berry,cameron,NULL,Male,Caucasian,07/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +50338,76190,68982,PRETRIAL,berry,cameron,NULL,Male,Caucasian,07/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +50338,76190,68982,PRETRIAL,berry,cameron,NULL,Male,Caucasian,07/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65823,76192,68984,Probation,Bautistadesurinach,Silvia,Joselin,Female,Hispanic,06/20/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/26/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +65823,76192,68984,Probation,Bautistadesurinach,Silvia,Joselin,Female,Hispanic,06/20/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/26/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +65823,76192,68984,Probation,Bautistadesurinach,Silvia,Joselin,Female,Hispanic,06/20/64,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54494,76182,56162,PRETRIAL,Janki,Dale,Jason,Male,Other,01/03/92,17,All Scales,Intake,English,Other,Probation,Single,8/26/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,Copy,1,0 +54494,76182,56162,PRETRIAL,Janki,Dale,Jason,Male,Other,01/03/92,17,All Scales,Intake,English,Other,Probation,Single,8/26/14 0:00,4,High,8,Risk of Recidivism,0.69,10,High,Copy,1,0 +54494,76182,56162,PRETRIAL,Janki,Dale,Jason,Male,Other,01/03/92,17,All Scales,Intake,English,Other,Probation,Single,8/26/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +65811,76174,68970,DRRD,Cunigan,Xavier,NULL,Male,African-American,12/30/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +65811,76174,68970,DRRD,Cunigan,Xavier,NULL,Male,African-American,12/30/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +65811,76174,68970,DRRD,Cunigan,Xavier,NULL,Male,African-American,12/30/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65784,76161,68958,PRETRIAL,HARDY,RONALD,EARNARD,Male,African-American,05/30/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +65784,76161,68958,PRETRIAL,HARDY,RONALD,EARNARD,Male,African-American,05/30/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +65784,76161,68958,PRETRIAL,HARDY,RONALD,EARNARD,Male,African-American,05/30/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +41504,76195,68987,PRETRIAL,Stefanescu,Ramona,NULL,Female,Caucasian,06/26/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/26/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +41504,76195,68987,PRETRIAL,Stefanescu,Ramona,NULL,Female,Caucasian,06/26/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/26/14 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,New,1,0 +41504,76195,68987,PRETRIAL,Stefanescu,Ramona,NULL,Female,Caucasian,06/26/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65788,76165,68962,PRETRIAL,Davis,Freddie,Cornelius,Male,African-American,06/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,New,1,0 +65788,76165,68962,PRETRIAL,Davis,Freddie,Cornelius,Male,African-American,06/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +65788,76165,68962,PRETRIAL,Davis,Freddie,Cornelius,Male,African-American,06/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +22345,76158,62727,PRETRIAL,reese,willie,NULL,Male,African-American,06/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,Copy,1,0 +22345,76158,62727,PRETRIAL,reese,willie,NULL,Male,African-American,06/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,Copy,1,0 +22345,76158,62727,PRETRIAL,reese,willie,NULL,Male,African-American,06/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +65821,76188,68980,PRETRIAL,HUGHES,DAVID,NULL,Male,Caucasian,08/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +65821,76188,68980,PRETRIAL,HUGHES,DAVID,NULL,Male,Caucasian,08/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +65821,76188,68980,PRETRIAL,HUGHES,DAVID,NULL,Male,Caucasian,08/10/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65815,76179,68973,PRETRIAL,Alloy,Jacqueline,Marie,Female,Caucasian,07/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/26/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,Copy,1,0 +65815,76179,68973,PRETRIAL,Alloy,Jacqueline,Marie,Female,Caucasian,07/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/26/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,Copy,1,0 +65815,76179,68973,PRETRIAL,Alloy,Jacqueline,Marie,Female,Caucasian,07/25/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +65809,76172,68968,PRETRIAL,Chanthavong,Nykky,NULL,Male,Asian,03/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/26/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +65809,76172,68968,PRETRIAL,Chanthavong,Nykky,NULL,Male,Asian,03/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/26/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +65809,76172,68968,PRETRIAL,Chanthavong,Nykky,NULL,Male,Asian,03/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +54530,76193,68985,PRETRIAL,COUNTS,DEANDRAE,NULL,Male,African-American,02/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +54530,76193,68985,PRETRIAL,COUNTS,DEANDRAE,NULL,Male,African-American,02/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +54530,76193,68985,PRETRIAL,COUNTS,DEANDRAE,NULL,Male,African-American,02/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +62401,76160,65086,Probation,Bustillo,Stacey,NULL,Female,Caucasian,05/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.6,6,Medium,Copy,1,0 +62401,76160,65086,Probation,Bustillo,Stacey,NULL,Female,Caucasian,05/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,Copy,1,0 +62401,76160,65086,Probation,Bustillo,Stacey,NULL,Female,Caucasian,05/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +65786,76163,68960,PRETRIAL,Woodin,Randall,NULL,Male,Caucasian,09/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +65786,76163,68960,PRETRIAL,Woodin,Randall,NULL,Male,Caucasian,09/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +65786,76163,68960,PRETRIAL,Woodin,Randall,NULL,Male,Caucasian,09/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65790,76167,68964,PRETRIAL,MOSS,CHAVELLONEY,M,Female,African-American,10/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +65790,76167,68964,PRETRIAL,MOSS,CHAVELLONEY,M,Female,African-American,10/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +65790,76167,68964,PRETRIAL,MOSS,CHAVELLONEY,M,Female,African-American,10/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65810,76173,68969,Probation,Vega,John,Ray,Male,Hispanic,03/09/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +65810,76173,68969,Probation,Vega,John,Ray,Male,Hispanic,03/09/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +65810,76173,68969,Probation,Vega,John,Ray,Male,Hispanic,03/09/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65820,76187,68979,PRETRIAL,Zorabedian,Michael,NULL,Male,Caucasian,04/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/26/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +65820,76187,68979,PRETRIAL,Zorabedian,Michael,NULL,Male,Caucasian,04/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/26/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +65820,76187,68979,PRETRIAL,Zorabedian,Michael,NULL,Male,Caucasian,04/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65824,76194,68986,Probation,Riviere,Dyna,NULL,Female,African-American,10/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +65824,76194,68986,Probation,Riviere,Dyna,NULL,Female,African-American,10/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +65824,76194,68986,Probation,Riviere,Dyna,NULL,Female,African-American,10/15/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +65789,76166,68963,PRETRIAL,VINCZENCZ,ZACHARIA,NULL,Male,Caucasian,05/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +65789,76166,68963,PRETRIAL,VINCZENCZ,ZACHARIA,NULL,Male,Caucasian,05/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +65789,76166,68963,PRETRIAL,VINCZENCZ,ZACHARIA,NULL,Male,Caucasian,05/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65814,76180,68974,PRETRIAL,Devito,Timothy,NULL,Male,Caucasian,01/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +65814,76180,68974,PRETRIAL,Devito,Timothy,NULL,Male,Caucasian,01/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +65814,76180,68974,PRETRIAL,Devito,Timothy,NULL,Male,Caucasian,01/12/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65783,76159,68957,PRETRIAL,Mckenzie,Dorian,NULL,Male,African-American,05/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +65783,76159,68957,PRETRIAL,Mckenzie,Dorian,NULL,Male,African-American,05/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +65783,76159,68957,PRETRIAL,Mckenzie,Dorian,NULL,Male,African-American,05/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55692,76168,68965,Probation,mazzarella,michael,NULL,Male,Caucasian,10/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +55692,76168,68965,Probation,mazzarella,michael,NULL,Male,Caucasian,10/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,4,High,8,Risk of Recidivism,0.1,8,High,New,1,0 +55692,76168,68965,Probation,mazzarella,michael,NULL,Male,Caucasian,10/25/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,4,High,18,Risk of Failure to Appear,37,10,High,New,1,0 +65787,76164,68961,PRETRIAL,Morgan,Raphael,NULL,Male,African-American,10/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +65787,76164,68961,PRETRIAL,Morgan,Raphael,NULL,Male,African-American,10/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +65787,76164,68961,PRETRIAL,Morgan,Raphael,NULL,Male,African-American,10/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65808,76171,68967,Probation,fields,shernard,NULL,Male,African-American,08/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/14 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,New,1,0 +65808,76171,68967,Probation,fields,shernard,NULL,Male,African-American,08/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +65808,76171,68967,Probation,fields,shernard,NULL,Male,African-American,08/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/26/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65819,76185,68978,Probation,Levy,Yoshua,NULL,Male,Caucasian,01/16/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +65819,76185,68978,Probation,Levy,Yoshua,NULL,Male,Caucasian,01/16/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +65819,76185,68978,Probation,Levy,Yoshua,NULL,Male,Caucasian,01/16/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65807,76170,68966,Probation,Riveracolon,Gabriel,NULL,Male,Hispanic,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +65807,76170,68966,Probation,Riveracolon,Gabriel,NULL,Male,Hispanic,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +65807,76170,68966,Probation,Riveracolon,Gabriel,NULL,Male,Hispanic,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57299,76191,68983,PRETRIAL,Allen,Jeanne,NULL,Female,Other,05/15/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +57299,76191,68983,PRETRIAL,Allen,Jeanne,NULL,Female,Other,05/15/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +57299,76191,68983,PRETRIAL,Allen,Jeanne,NULL,Female,Other,05/15/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65812,76175,68971,DRRD,Thompson,lajavius,NULL,Male,African-American,03/13/95,22,Risk and Prescreen,Intake,English,Deferred Sentencing,Probation,Significant Other,8/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.04,8,High,New,1,0 +65812,76175,68971,DRRD,Thompson,lajavius,NULL,Male,African-American,03/13/95,22,Risk and Prescreen,Intake,English,Deferred Sentencing,Probation,Significant Other,8/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +65812,76175,68971,DRRD,Thompson,lajavius,NULL,Male,African-American,03/13/95,22,Risk and Prescreen,Intake,English,Deferred Sentencing,Probation,Significant Other,8/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65785,76162,68959,PRETRIAL,HENDERSON,ANDRE,LAMONT,Male,African-American,10/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +65785,76162,68959,PRETRIAL,HENDERSON,ANDRE,LAMONT,Male,African-American,10/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +65785,76162,68959,PRETRIAL,HENDERSON,ANDRE,LAMONT,Male,African-American,10/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65818,76183,68976,Probation,WALTERMIRE,JUSTIN,S,Male,Caucasian,11/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +65818,76183,68976,Probation,WALTERMIRE,JUSTIN,S,Male,Caucasian,11/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +65818,76183,68976,Probation,WALTERMIRE,JUSTIN,S,Male,Caucasian,11/15/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65853,76233,69018,PRETRIAL,Ramos,William,NULL,Male,Hispanic,05/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/27/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +65853,76233,69018,PRETRIAL,Ramos,William,NULL,Male,Hispanic,05/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/27/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +65853,76233,69018,PRETRIAL,Ramos,William,NULL,Male,Hispanic,05/24/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65860,76241,69025,PRETRIAL,Robinson,Cassandra,NULL,Female,Caucasian,06/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +65860,76241,69025,PRETRIAL,Robinson,Cassandra,NULL,Female,Caucasian,06/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,9,High,New,1,0 +65860,76241,69025,PRETRIAL,Robinson,Cassandra,NULL,Female,Caucasian,06/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +65454,76220,68560,PRETRIAL,Roza,John,NULL,Male,Caucasian,08/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,Copy,1,0 +65454,76220,68560,PRETRIAL,Roza,John,NULL,Male,Caucasian,08/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,Copy,1,0 +65454,76220,68560,PRETRIAL,Roza,John,NULL,Male,Caucasian,08/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +65845,76225,69010,PRETRIAL,Morales,Angela,NULL,Female,African-American,10/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +65845,76225,69010,PRETRIAL,Morales,Angela,NULL,Female,African-American,10/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,4,High,8,Risk of Recidivism,0.35,9,High,New,1,0 +65845,76225,69010,PRETRIAL,Morales,Angela,NULL,Female,African-American,10/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,4,High,18,Risk of Failure to Appear,20,4,Low,New,1,0 +65831,76204,68995,PRETRIAL,Feliciano,Harry,NULL,Male,Hispanic,11/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +65831,76204,68995,PRETRIAL,Feliciano,Harry,NULL,Male,Hispanic,11/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +65831,76204,68995,PRETRIAL,Feliciano,Harry,NULL,Male,Hispanic,11/03/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65858,76238,69023,Probation,telles,valerie,NULL,Female,Caucasian,06/03/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +65858,76238,69023,Probation,telles,valerie,NULL,Female,Caucasian,06/03/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +65858,76238,69023,Probation,telles,valerie,NULL,Female,Caucasian,06/03/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65827,76199,68991,PRETRIAL,HUCKABEE,RYAN,SCOTT,Male,Caucasian,02/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +65827,76199,68991,PRETRIAL,HUCKABEE,RYAN,SCOTT,Male,Caucasian,02/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +65827,76199,68991,PRETRIAL,HUCKABEE,RYAN,SCOTT,Male,Caucasian,02/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65837,76210,69001,PRETRIAL,HEWETT,CARRIE,NULL,Female,Caucasian,07/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +65837,76210,69001,PRETRIAL,HEWETT,CARRIE,NULL,Female,Caucasian,07/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +65837,76210,69001,PRETRIAL,HEWETT,CARRIE,NULL,Female,Caucasian,07/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +65851,76231,69016,PRETRIAL,Hill,Gabriel,NULL,Male,African-American,07/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +65851,76231,69016,PRETRIAL,Hill,Gabriel,NULL,Male,African-American,07/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +65851,76231,69016,PRETRIAL,Hill,Gabriel,NULL,Male,African-American,07/22/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65847,76227,69012,PRETRIAL,LAWSON,MABLE,NULL,Female,African-American,03/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +65847,76227,69012,PRETRIAL,LAWSON,MABLE,NULL,Female,African-American,03/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +65847,76227,69012,PRETRIAL,LAWSON,MABLE,NULL,Female,African-American,03/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65855,76236,69021,Probation,Knapp,Christopher,NULL,Male,African-American,05/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.36,3,Low,New,1,0 +65855,76236,69021,Probation,Knapp,Christopher,NULL,Male,African-American,05/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +65855,76236,69021,Probation,Knapp,Christopher,NULL,Male,African-American,05/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65833,76206,68997,PRETRIAL,Castillo,Adonis,NULL,Male,Hispanic,10/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +65833,76206,68997,PRETRIAL,Castillo,Adonis,NULL,Male,Hispanic,10/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +65833,76206,68997,PRETRIAL,Castillo,Adonis,NULL,Male,Hispanic,10/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +48252,76240,66506,PRETRIAL,Vazquez,Edwin,NULL,Male,Hispanic,02/13/54,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/27/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +48252,76240,66506,PRETRIAL,Vazquez,Edwin,NULL,Male,Hispanic,02/13/54,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/27/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +48252,76240,66506,PRETRIAL,Vazquez,Edwin,NULL,Male,Hispanic,02/13/54,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,2,Low,New,1,0 +12913,76215,69005,Probation,vera,camilo,NULL,Male,Hispanic,03/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +12913,76215,69005,Probation,vera,camilo,NULL,Male,Hispanic,03/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +12913,76215,69005,Probation,vera,camilo,NULL,Male,Hispanic,03/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65829,76201,68992,PRETRIAL,Johnson,Talvet,NULL,Male,African-American,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +65829,76201,68992,PRETRIAL,Johnson,Talvet,NULL,Male,African-American,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,4,High,8,Risk of Recidivism,0.66,10,High,New,1,0 +65829,76201,68992,PRETRIAL,Johnson,Talvet,NULL,Male,African-American,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55716,63469,57599,Probation,Sanchez,Raphael,NULL,Male,Hispanic,12/20/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +55716,63469,57599,Probation,Sanchez,Raphael,NULL,Male,Hispanic,12/20/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +55716,63469,57599,Probation,Sanchez,Raphael,NULL,Male,Hispanic,12/20/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65842,76222,69007,PRETRIAL,Baker,James,Rodney,Male,African-American,07/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,Copy,1,0 +65842,76222,69007,PRETRIAL,Baker,James,Rodney,Male,African-American,07/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.63,10,High,Copy,1,0 +65842,76222,69007,PRETRIAL,Baker,James,Rodney,Male,African-American,07/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +55716,76224,57599,Probation,Sanchez,Raphael,NULL,Male,Hispanic,12/20/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,Copy,1,0 +55716,76224,57599,Probation,Sanchez,Raphael,NULL,Male,Hispanic,12/20/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,Copy,1,0 +55716,76224,57599,Probation,Sanchez,Raphael,NULL,Male,Hispanic,12/20/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +65861,76243,69026,PRETRIAL,Bolinder,Steven,NULL,Male,Caucasian,09/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +65861,76243,69026,PRETRIAL,Bolinder,Steven,NULL,Male,Caucasian,09/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +65861,76243,69026,PRETRIAL,Bolinder,Steven,NULL,Male,Caucasian,09/23/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65852,76232,69017,Probation,CASTELLANO,DAVID,NULL,Male,African-American,05/18/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,7,Risk of Violence,-4.41,1,Low,New,1,0 +65852,76232,69017,Probation,CASTELLANO,DAVID,NULL,Male,African-American,05/18/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +65852,76232,69017,Probation,CASTELLANO,DAVID,NULL,Male,African-American,05/18/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65848,76228,69013,Probation,Visbal,Christin,NULL,Female,Caucasian,10/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/27/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +65848,76228,69013,Probation,Visbal,Christin,NULL,Female,Caucasian,10/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/27/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +65848,76228,69013,Probation,Visbal,Christin,NULL,Female,Caucasian,10/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65856,76235,69020,Probation,Amaya,Juan,NULL,Male,Hispanic,04/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/27/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +65856,76235,69020,Probation,Amaya,Juan,NULL,Male,Hispanic,04/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/27/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +65856,76235,69020,Probation,Amaya,Juan,NULL,Male,Hispanic,04/21/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +41264,76202,68993,Probation,McDonald,Michael,NULL,Male,African-American,03/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,New,1,0 +41264,76202,68993,Probation,McDonald,Michael,NULL,Male,African-American,03/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,4,High,8,Risk of Recidivism,0.7,10,High,New,1,0 +41264,76202,68993,Probation,McDonald,Michael,NULL,Male,African-American,03/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,4,High,18,Risk of Failure to Appear,36,10,High,New,1,0 +65836,76209,69000,PRETRIAL,Belizaire,Rocheny,NULL,Male,African-American,08/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +65836,76209,69000,PRETRIAL,Belizaire,Rocheny,NULL,Male,African-American,08/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +65836,76209,69000,PRETRIAL,Belizaire,Rocheny,NULL,Male,African-American,08/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65834,76207,68998,PRETRIAL,Umana,German,Nelson,Male,Caucasian,07/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/27/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +65834,76207,68998,PRETRIAL,Umana,German,Nelson,Male,Caucasian,07/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/27/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +65834,76207,68998,PRETRIAL,Umana,German,Nelson,Male,Caucasian,07/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65841,76216,69006,Probation,Grantham,Robert,NULL,Male,Caucasian,09/16/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/27/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +65841,76216,69006,Probation,Grantham,Robert,NULL,Male,Caucasian,09/16/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/27/14 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +65841,76216,69006,Probation,Grantham,Robert,NULL,Male,Caucasian,09/16/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65850,76230,69015,Probation,Jensen,Jerry,Kirtland,Male,Caucasian,09/27/47,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/27/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +65850,76230,69015,Probation,Jensen,Jerry,Kirtland,Male,Caucasian,09/27/47,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/27/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +65850,76230,69015,Probation,Jensen,Jerry,Kirtland,Male,Caucasian,09/27/47,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65857,76237,69022,Probation,Loguerico,Steven,NULL,Male,Caucasian,05/12/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/27/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +65857,76237,69022,Probation,Loguerico,Steven,NULL,Male,Caucasian,05/12/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/27/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +65857,76237,69022,Probation,Loguerico,Steven,NULL,Male,Caucasian,05/12/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65849,76229,69014,Probation,Knapp,Christopher,NULL,Male,Caucasian,11/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +65849,76229,69014,Probation,Knapp,Christopher,NULL,Male,Caucasian,11/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +65849,76229,69014,Probation,Knapp,Christopher,NULL,Male,Caucasian,11/15/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65854,76234,69019,PRETRIAL,JOHNSON,ALEX,ONTERIO,Male,African-American,01/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +65854,76234,69019,PRETRIAL,JOHNSON,ALEX,ONTERIO,Male,African-American,01/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +65854,76234,69019,PRETRIAL,JOHNSON,ALEX,ONTERIO,Male,African-American,01/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65835,76208,68999,PRETRIAL,Donald,Joyce,NULL,Male,African-American,02/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +65835,76208,68999,PRETRIAL,Donald,Joyce,NULL,Male,African-American,02/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +65835,76208,68999,PRETRIAL,Donald,Joyce,NULL,Male,African-American,02/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +8715,76242,47210,Probation,Simmons,George,L,Male,African-American,11/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.86,5,Medium,Copy,1,0 +8715,76242,47210,Probation,Simmons,George,L,Male,African-American,11/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,Copy,1,0 +8715,76242,47210,Probation,Simmons,George,L,Male,African-American,11/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +25339,76200,24496,PRETRIAL,GREEN,SHATEKA,NULL,Female,African-American,09/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,Copy,1,0 +25339,76200,24496,PRETRIAL,GREEN,SHATEKA,NULL,Female,African-American,09/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,7,Medium,Copy,1,0 +25339,76200,24496,PRETRIAL,GREEN,SHATEKA,NULL,Female,African-American,09/18/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/27/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +65830,76203,68994,PRETRIAL,Formosa,Vince,M,Male,Caucasian,11/16/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/27/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +65830,76203,68994,PRETRIAL,Formosa,Vince,M,Male,Caucasian,11/16/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/27/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +65830,76203,68994,PRETRIAL,Formosa,Vince,M,Male,Caucasian,11/16/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65843,76221,69008,Probation,Jeffery,Alvin,NULL,Male,African-American,02/23/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,7,Risk of Violence,-4.39,1,Low,New,1,0 +65843,76221,69008,Probation,Jeffery,Alvin,NULL,Male,African-American,02/23/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +65843,76221,69008,Probation,Jeffery,Alvin,NULL,Male,African-American,02/23/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65832,76205,68996,PRETRIAL,Adderly,Broderick,NULL,Male,African-American,07/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/27/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +65832,76205,68996,PRETRIAL,Adderly,Broderick,NULL,Male,African-American,07/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/27/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +65832,76205,68996,PRETRIAL,Adderly,Broderick,NULL,Male,African-American,07/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65838,76211,69002,PRETRIAL,Capiola,Nicholas,NULL,Male,Caucasian,11/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +65838,76211,69002,PRETRIAL,Capiola,Nicholas,NULL,Male,Caucasian,11/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +65838,76211,69002,PRETRIAL,Capiola,Nicholas,NULL,Male,Caucasian,11/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65839,76213,69004,Probation,Giraldo,john,NULL,Male,Hispanic,03/02/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/27/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +65839,76213,69004,Probation,Giraldo,john,NULL,Male,Hispanic,03/02/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/27/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +65839,76213,69004,Probation,Giraldo,john,NULL,Male,Hispanic,03/02/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59020,76276,69055,Probation,MCKINNEY,GARRY,NULL,Male,Caucasian,05/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/28/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +59020,76276,69055,Probation,MCKINNEY,GARRY,NULL,Male,Caucasian,05/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/28/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +59020,76276,69055,Probation,MCKINNEY,GARRY,NULL,Male,Caucasian,05/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65863,76247,69030,PRETRIAL,BROWN,CEDRIC,TAVARIUS,Male,African-American,01/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +65863,76247,69030,PRETRIAL,BROWN,CEDRIC,TAVARIUS,Male,African-American,01/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +65863,76247,69030,PRETRIAL,BROWN,CEDRIC,TAVARIUS,Male,African-American,01/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65873,76260,69040,Probation,gagne,daniel,NULL,Male,Caucasian,11/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +65873,76260,69040,Probation,gagne,daniel,NULL,Male,Caucasian,11/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +65873,76260,69040,Probation,gagne,daniel,NULL,Male,Caucasian,11/26/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64900,76271,67978,PRETRIAL,Pernice,Anthony,NULL,Male,Caucasian,02/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,Copy,1,0 +64900,76271,67978,PRETRIAL,Pernice,Anthony,NULL,Male,Caucasian,02/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,Copy,1,0 +64900,76271,67978,PRETRIAL,Pernice,Anthony,NULL,Male,Caucasian,02/01/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +65865,76250,69033,PRETRIAL,Buckle,Keith,Elmo,Male,African-American,10/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/28/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +65865,76250,69033,PRETRIAL,Buckle,Keith,Elmo,Male,African-American,10/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/28/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +65865,76250,69033,PRETRIAL,Buckle,Keith,Elmo,Male,African-American,10/19/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65891,76281,69059,PRETRIAL,Ortega,David,NULL,Male,Hispanic,08/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/28/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +65891,76281,69059,PRETRIAL,Ortega,David,NULL,Male,Hispanic,08/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/28/14 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +65891,76281,69059,PRETRIAL,Ortega,David,NULL,Male,Hispanic,08/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65870,76255,69037,Probation,Echeona,Carlos,NULL,Male,Hispanic,12/18/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/28/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +65870,76255,69037,Probation,Echeona,Carlos,NULL,Male,Hispanic,12/18/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/28/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +65870,76255,69037,Probation,Echeona,Carlos,NULL,Male,Hispanic,12/18/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65875,76263,69043,Probation,Loy,Eric,Milton,Male,Caucasian,11/27/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +65875,76263,69043,Probation,Loy,Eric,Milton,Male,Caucasian,11/27/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +65875,76263,69043,Probation,Loy,Eric,Milton,Male,Caucasian,11/27/78,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65882,76268,69048,Probation,ZAMARINI,NATALIE,N,Male,Caucasian,05/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/28/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +65882,76268,69048,Probation,ZAMARINI,NATALIE,N,Male,Caucasian,05/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/28/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +65882,76268,69048,Probation,ZAMARINI,NATALIE,N,Male,Caucasian,05/24/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +64023,76244,69027,PRETRIAL,Taylor,Tiffany,NULL,Female,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +64023,76244,69027,PRETRIAL,Taylor,Tiffany,NULL,Female,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-1.26,3,Low,New,1,0 +64023,76244,69027,PRETRIAL,Taylor,Tiffany,NULL,Female,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65866,76251,69034,PRETRIAL,CARRET,JUAN,CARLOS,Male,Caucasian,07/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +65866,76251,69034,PRETRIAL,CARRET,JUAN,CARLOS,Male,Caucasian,07/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +65866,76251,69034,PRETRIAL,CARRET,JUAN,CARLOS,Male,Caucasian,07/28/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65878,76265,69045,DRRD,Maloney,Brett,NULL,Male,Caucasian,03/09/96,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Single,8/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +65878,76265,69045,DRRD,Maloney,Brett,NULL,Male,Caucasian,03/09/96,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Single,8/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +65878,76265,69045,DRRD,Maloney,Brett,NULL,Male,Caucasian,03/09/96,22,Risk and Prescreen,Intake,English,Probation Violator,Probation,Single,8/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +47525,76279,69057,PRETRIAL,Gardner,Michael,NULL,Male,African-American,08/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +47525,76279,69057,PRETRIAL,Gardner,Michael,NULL,Male,African-American,08/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.66,10,High,New,1,0 +47525,76279,69057,PRETRIAL,Gardner,Michael,NULL,Male,African-American,08/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65884,76270,69050,Probation,Puccetti Gelvez,Diana,NULL,Female,Hispanic,07/28/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/28/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +65884,76270,69050,Probation,Puccetti Gelvez,Diana,NULL,Female,Hispanic,07/28/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/28/14 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +65884,76270,69050,Probation,Puccetti Gelvez,Diana,NULL,Female,Hispanic,07/28/72,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65887,76274,69053,Probation,Aurricchio,William,NULL,Male,Caucasian,06/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.38,3,Low,New,1,0 +65887,76274,69053,Probation,Aurricchio,William,NULL,Male,Caucasian,06/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,New,1,0 +65887,76274,69053,Probation,Aurricchio,William,NULL,Male,Caucasian,06/14/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +61328,76253,63877,PRETRIAL,Ross,Johnny,NULL,Male,African-American,01/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,Copy,1,0 +61328,76253,63877,PRETRIAL,Ross,Johnny,NULL,Male,African-American,01/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,Copy,1,0 +61328,76253,63877,PRETRIAL,Ross,Johnny,NULL,Male,African-American,01/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +65864,76249,69032,PRETRIAL,Ellis-Boatwright,Winsome,NULL,Female,African-American,11/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/28/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +65864,76249,69032,PRETRIAL,Ellis-Boatwright,Winsome,NULL,Female,African-American,11/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/28/14 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +65864,76249,69032,PRETRIAL,Ellis-Boatwright,Winsome,NULL,Female,African-American,11/06/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65862,76245,69028,PRETRIAL,Watson,Adrian,NULL,Male,Other,03/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +65862,76245,69028,PRETRIAL,Watson,Adrian,NULL,Male,Other,03/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +65862,76245,69028,PRETRIAL,Watson,Adrian,NULL,Male,Other,03/18/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65867,76252,69035,PRETRIAL,Heinle,John,NULL,Male,Caucasian,04/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/28/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +65867,76252,69035,PRETRIAL,Heinle,John,NULL,Male,Caucasian,04/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/28/14 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +65867,76252,69035,PRETRIAL,Heinle,John,NULL,Male,Caucasian,04/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65886,76273,69052,Probation,ORTIZ,ANDREA,NULL,Female,Caucasian,11/21/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/28/14 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +65886,76273,69052,Probation,ORTIZ,ANDREA,NULL,Female,Caucasian,11/21/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +65886,76273,69052,Probation,ORTIZ,ANDREA,NULL,Female,Caucasian,11/21/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,8/28/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65880,76266,69046,PRETRIAL,McNally,Thomas,NULL,Male,Caucasian,03/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +65880,76266,69046,PRETRIAL,McNally,Thomas,NULL,Male,Caucasian,03/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +65880,76266,69046,PRETRIAL,McNally,Thomas,NULL,Male,Caucasian,03/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +65890,76280,69058,Probation,NOEL,LYONEL,NULL,Male,African-American,03/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +65890,76280,69058,Probation,NOEL,LYONEL,NULL,Male,African-American,03/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +65890,76280,69058,Probation,NOEL,LYONEL,NULL,Male,African-American,03/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65572,76261,69041,Probation,Lazarus,David,NULL,Male,Asian,06/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/28/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +65572,76261,69041,Probation,Lazarus,David,NULL,Male,Asian,06/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/28/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +65572,76261,69041,Probation,Lazarus,David,NULL,Male,Asian,06/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65889,76278,69056,PRETRIAL,Jabeth,Moye,NULL,Female,African-American,03/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +65889,76278,69056,PRETRIAL,Jabeth,Moye,NULL,Female,African-American,03/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +65889,76278,69056,PRETRIAL,Jabeth,Moye,NULL,Female,African-American,03/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65877,76264,69044,DRRD,Latta,Charleen,NULL,Female,Other,03/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,8/28/14 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +65877,76264,69044,DRRD,Latta,Charleen,NULL,Female,Other,03/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,8/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +65877,76264,69044,DRRD,Latta,Charleen,NULL,Female,Other,03/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Single,8/28/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65881,76267,69047,Probation,Smith,Devin,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +65881,76267,69047,Probation,Smith,Devin,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +65881,76267,69047,Probation,Smith,Devin,NULL,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65656,76246,69029,PRETRIAL,Mckinley,William,NULL,Male,Caucasian,08/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +65656,76246,69029,PRETRIAL,Mckinley,William,NULL,Male,Caucasian,08/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +65656,76246,69029,PRETRIAL,Mckinley,William,NULL,Male,Caucasian,08/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +35807,76259,68415,PRETRIAL,Martin,Xavier,NULL,Male,African-American,09/28/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +35807,76259,68415,PRETRIAL,Martin,Xavier,NULL,Male,African-American,09/28/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,4,High,8,Risk of Recidivism,0.45,9,High,New,1,0 +35807,76259,68415,PRETRIAL,Martin,Xavier,NULL,Male,African-American,09/28/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,4,High,18,Risk of Failure to Appear,21,3,Low,New,1,0 +65885,76272,69051,PRETRIAL,Jean,Jonathan,NULL,Male,African-American,05/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +65885,76272,69051,PRETRIAL,Jean,Jonathan,NULL,Male,African-American,05/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +65885,76272,69051,PRETRIAL,Jean,Jonathan,NULL,Male,African-American,05/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65869,76254,69036,DRRD,Pendleton,John,NULL,Male,African-American,11/07/60,22,Risk and Prescreen,Intake,English,Deferred Sentencing,Probation,Single,8/28/14 0:00,2,Medium,7,Risk of Violence,-2.88,2,Low,New,1,0 +65869,76254,69036,DRRD,Pendleton,John,NULL,Male,African-American,11/07/60,22,Risk and Prescreen,Intake,English,Deferred Sentencing,Probation,Single,8/28/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +65869,76254,69036,DRRD,Pendleton,John,NULL,Male,African-American,11/07/60,22,Risk and Prescreen,Intake,English,Deferred Sentencing,Probation,Single,8/28/14 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +65888,76275,69054,DRRD,Vizzi,Louis,NULL,Male,Caucasian,06/11/92,22,Risk and Prescreen,Intake,English,Deferred Sentencing,Probation,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +65888,76275,69054,DRRD,Vizzi,Louis,NULL,Male,Caucasian,06/11/92,22,Risk and Prescreen,Intake,English,Deferred Sentencing,Probation,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +65888,76275,69054,DRRD,Vizzi,Louis,NULL,Male,Caucasian,06/11/92,22,Risk and Prescreen,Intake,English,Deferred Sentencing,Probation,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65440,76248,69031,PRETRIAL,Lundy,John-Pierre,NULL,Male,African-American,12/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +65440,76248,69031,PRETRIAL,Lundy,John-Pierre,NULL,Male,African-American,12/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +65440,76248,69031,PRETRIAL,Lundy,John-Pierre,NULL,Male,African-American,12/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/28/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +2870,76262,69042,PRETRIAL,BELKO,SEAN,NULL,Male,African-American,09/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +2870,76262,69042,PRETRIAL,BELKO,SEAN,NULL,Male,African-American,09/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +2870,76262,69042,PRETRIAL,BELKO,SEAN,NULL,Male,African-American,09/30/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65883,76269,69049,PRETRIAL,Sabzaliev,Amzali,NULL,Male,Caucasian,01/10/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/28/14 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +65883,76269,69049,PRETRIAL,Sabzaliev,Amzali,NULL,Male,Caucasian,01/10/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/28/14 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +65883,76269,69049,PRETRIAL,Sabzaliev,Amzali,NULL,Male,Caucasian,01/10/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51211,76283,69061,PRETRIAL,Williams,James,NULL,Male,African-American,07/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +51211,76283,69061,PRETRIAL,Williams,James,NULL,Male,African-American,07/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +51211,76283,69061,PRETRIAL,Williams,James,NULL,Male,African-American,07/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +21724,76298,20884,PRETRIAL,SANCHIOUS,ANDREW,NULL,Male,African-American,11/20/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.79,2,Low,Copy,1,0 +21724,76298,20884,PRETRIAL,SANCHIOUS,ANDREW,NULL,Male,African-American,11/20/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,Copy,1,0 +21724,76298,20884,PRETRIAL,SANCHIOUS,ANDREW,NULL,Male,African-American,11/20/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,41,10,High,Copy,1,0 +63350,76290,69068,PRETRIAL,Hursey,Darren,NULL,Male,African-American,07/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +63350,76290,69068,PRETRIAL,Hursey,Darren,NULL,Male,African-American,07/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +63350,76290,69068,PRETRIAL,Hursey,Darren,NULL,Male,African-American,07/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +17784,76311,69084,Probation,Carswell,Brandon,Sharreon,Male,African-American,06/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.09,4,Low,New,1,0 +17784,76311,69084,Probation,Carswell,Brandon,Sharreon,Male,African-American,06/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +17784,76311,69084,Probation,Carswell,Brandon,Sharreon,Male,African-American,06/20/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55253,76306,69079,Probation,puccio,joseph,NULL,Male,Caucasian,10/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/29/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +55253,76306,69079,Probation,puccio,joseph,NULL,Male,Caucasian,10/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/29/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +55253,76306,69079,Probation,puccio,joseph,NULL,Male,Caucasian,10/30/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65899,76293,69071,PRETRIAL,Schneider,Dwayne,NULL,Male,African-American,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +65899,76293,69071,PRETRIAL,Schneider,Dwayne,NULL,Male,African-American,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +65899,76293,69071,PRETRIAL,Schneider,Dwayne,NULL,Male,African-American,04/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65894,76285,69063,PRETRIAL,Davis,Daniel,Richard,Male,African-American,12/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +65894,76285,69063,PRETRIAL,Davis,Daniel,Richard,Male,African-American,12/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +65894,76285,69063,PRETRIAL,Davis,Daniel,Richard,Male,African-American,12/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59846,76296,69073,Probation,FINZI,DAN,NULL,Male,Hispanic,01/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +59846,76296,69073,Probation,FINZI,DAN,NULL,Male,Hispanic,01/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +59846,76296,69073,Probation,FINZI,DAN,NULL,Male,Hispanic,01/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65908,76303,69077,Probation,Thompson,Lisa,NULL,Female,Caucasian,06/23/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,2,Medium,7,Risk of Violence,-2.96,1,Low,New,1,0 +65908,76303,69077,Probation,Thompson,Lisa,NULL,Female,Caucasian,06/23/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +65908,76303,69077,Probation,Thompson,Lisa,NULL,Female,Caucasian,06/23/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65892,76282,69060,PRETRIAL,Greenfield,Edward,NULL,Male,Other,05/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +65892,76282,69060,PRETRIAL,Greenfield,Edward,NULL,Male,Other,05/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +65892,76282,69060,PRETRIAL,Greenfield,Edward,NULL,Male,Other,05/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65903,76299,69075,PRETRIAL,moening,Melody,NULL,Female,Caucasian,03/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +65903,76299,69075,PRETRIAL,moening,Melody,NULL,Female,Caucasian,03/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +65903,76299,69075,PRETRIAL,moening,Melody,NULL,Female,Caucasian,03/29/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +3651,48819,3368,Probation,Morrison,Dominic,R,Male,African-American,03/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,Copy,1,0 +3651,48819,3368,Probation,Morrison,Dominic,R,Male,African-American,03/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,Copy,1,0 +3651,48819,3368,Probation,Morrison,Dominic,R,Male,African-American,03/03/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +57935,76308,69081,Probation,Rivera,Magdelina,NULL,Female,Hispanic,12/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/29/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +57935,76308,69081,Probation,Rivera,Magdelina,NULL,Female,Hispanic,12/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/29/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +57935,76308,69081,Probation,Rivera,Magdelina,NULL,Female,Hispanic,12/04/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65896,76287,69065,PRETRIAL,Astley,Renford,NULL,Male,Other,02/02/43,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/29/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +65896,76287,69065,PRETRIAL,Astley,Renford,NULL,Male,Other,02/02/43,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/29/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +65896,76287,69065,PRETRIAL,Astley,Renford,NULL,Male,Other,02/02/43,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +4812,76294,4500,Probation,Fernandez,Fernando,NULL,Male,Hispanic,06/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/29/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +4812,76294,4500,Probation,Fernandez,Fernando,NULL,Male,Hispanic,06/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/29/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +4812,76294,4500,Probation,Fernandez,Fernando,NULL,Male,Hispanic,06/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/29/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +25934,76301,45190,PRETRIAL,Haygood,Jurvon,NULL,Male,African-American,12/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,Copy,1,0 +25934,76301,45190,PRETRIAL,Haygood,Jurvon,NULL,Male,African-American,12/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,Copy,1,0 +25934,76301,45190,PRETRIAL,Haygood,Jurvon,NULL,Male,African-American,12/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,8/29/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +65898,76291,69069,PRETRIAL,Martin,Robert,Letroy,Male,African-American,03/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +65898,76291,69069,PRETRIAL,Martin,Robert,Letroy,Male,African-American,03/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +65898,76291,69069,PRETRIAL,Martin,Robert,Letroy,Male,African-American,03/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65900,76295,69072,Probation,tricoli,nicholas,NULL,Male,Caucasian,05/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +65900,76295,69072,Probation,tricoli,nicholas,NULL,Male,Caucasian,05/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +65900,76295,69072,Probation,tricoli,nicholas,NULL,Male,Caucasian,05/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +9202,76304,8739,PRETRIAL,Quintero,Juan,Sebastian,Male,Caucasian,01/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,1,Low,7,Risk of Violence,-1.81,5,Medium,Copy,1,0 +9202,76304,8739,PRETRIAL,Quintero,Juan,Sebastian,Male,Caucasian,01/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,Copy,1,0 +9202,76304,8739,PRETRIAL,Quintero,Juan,Sebastian,Male,Caucasian,01/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +65895,76286,69064,PRETRIAL,Wright,Tyrell,Umar,Male,African-American,06/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,New,1,0 +65895,76286,69064,PRETRIAL,Wright,Tyrell,Umar,Male,African-American,06/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +65895,76286,69064,PRETRIAL,Wright,Tyrell,Umar,Male,African-American,06/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65897,76288,69066,PRETRIAL,Stroud,Anthony,Romelo,Male,African-American,08/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +65897,76288,69066,PRETRIAL,Stroud,Anthony,Romelo,Male,African-American,08/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +65897,76288,69066,PRETRIAL,Stroud,Anthony,Romelo,Male,African-American,08/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65915,76307,69080,Probation,Hogan,Lebryon,Terral,Male,African-American,07/12/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +65915,76307,69080,Probation,Hogan,Lebryon,Terral,Male,African-American,07/12/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.03,10,High,New,1,0 +65915,76307,69080,Probation,Hogan,Lebryon,Terral,Male,African-American,07/12/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +8937,76309,69082,PRETRIAL,neal,markevius,NULL,Male,African-American,01/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +8937,76309,69082,PRETRIAL,neal,markevius,NULL,Male,African-American,01/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +8937,76309,69082,PRETRIAL,neal,markevius,NULL,Male,African-American,01/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65907,76302,69076,Probation,Times,Tradeena,NULL,Female,African-American,11/25/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +65907,76302,69076,Probation,Times,Tradeena,NULL,Female,African-American,11/25/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/14 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +65907,76302,69076,Probation,Times,Tradeena,NULL,Female,African-American,11/25/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +37161,76289,69067,PRETRIAL,Berrios,Stephen,NULL,Male,Hispanic,08/26/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/29/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +37161,76289,69067,PRETRIAL,Berrios,Stephen,NULL,Male,Hispanic,08/26/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +37161,76289,69067,PRETRIAL,Berrios,Stephen,NULL,Male,Hispanic,08/26/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,8/29/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65916,76310,69083,PRETRIAL,McKinley,mary,NULL,Female,African-American,10/19/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +65916,76310,69083,PRETRIAL,McKinley,mary,NULL,Female,African-American,10/19/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +65916,76310,69083,PRETRIAL,McKinley,mary,NULL,Female,African-American,10/19/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65893,76284,69062,PRETRIAL,Prophete,Rub,NULL,Male,African-American,07/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +65893,76284,69062,PRETRIAL,Prophete,Rub,NULL,Male,African-American,07/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +65893,76284,69062,PRETRIAL,Prophete,Rub,NULL,Male,African-American,07/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +65902,76297,69074,Probation,payne,andrew,douglas,Male,Caucasian,07/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +65902,76297,69074,Probation,payne,andrew,douglas,Male,Caucasian,07/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +65902,76297,69074,Probation,payne,andrew,douglas,Male,Caucasian,07/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65917,76312,69085,PRETRIAL,Louis,Willins,NULL,Male,African-American,05/16/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +65917,76312,69085,PRETRIAL,Louis,Willins,NULL,Male,African-American,05/16/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +65917,76312,69085,PRETRIAL,Louis,Willins,NULL,Male,African-American,05/16/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +25170,76292,69070,Probation,eckman,johnathon,NULL,Male,Caucasian,03/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +25170,76292,69070,Probation,eckman,johnathon,NULL,Male,Caucasian,03/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +25170,76292,69070,Probation,eckman,johnathon,NULL,Male,Caucasian,03/04/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,8/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +3819,76318,69090,PRETRIAL,SMITH,BRETT,NULL,Male,African-American,02/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,4,High,7,Risk of Violence,-0.9,9,High,New,1,0 +3819,76318,69090,PRETRIAL,SMITH,BRETT,NULL,Male,African-American,02/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +3819,76318,69090,PRETRIAL,SMITH,BRETT,NULL,Male,African-American,02/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65923,76320,69092,PRETRIAL,Steele,Tracy,Alan,Male,Caucasian,05/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +65923,76320,69092,PRETRIAL,Steele,Tracy,Alan,Male,Caucasian,05/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,1,Low,8,Risk of Recidivism,-2.39,1,Low,New,1,0 +65923,76320,69092,PRETRIAL,Steele,Tracy,Alan,Male,Caucasian,05/19/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65926,76323,69094,PRETRIAL,Lewisward,Devon,T,Male,African-American,12/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +65926,76323,69094,PRETRIAL,Lewisward,Devon,T,Male,African-American,12/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,4,High,8,Risk of Recidivism,0.17,8,High,New,1,0 +65926,76323,69094,PRETRIAL,Lewisward,Devon,T,Male,African-American,12/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +65924,76321,69093,PRETRIAL,Brown,Krystal,NULL,Female,African-American,02/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +65924,76321,69093,PRETRIAL,Brown,Krystal,NULL,Female,African-American,02/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +65924,76321,69093,PRETRIAL,Brown,Krystal,NULL,Female,African-American,02/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65920,76315,69088,PRETRIAL,Gipson,Macdarius,NULL,Male,African-American,12/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +65920,76315,69088,PRETRIAL,Gipson,Macdarius,NULL,Male,African-American,12/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +65920,76315,69088,PRETRIAL,Gipson,Macdarius,NULL,Male,African-American,12/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59500,76322,61839,PRETRIAL,Deus,Moriach,NULL,Male,African-American,08/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,Copy,1,0 +59500,76322,61839,PRETRIAL,Deus,Moriach,NULL,Male,African-American,08/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,Copy,1,0 +59500,76322,61839,PRETRIAL,Deus,Moriach,NULL,Male,African-American,08/30/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +65921,76317,69089,PRETRIAL,Hernandez,Rolando,L,Male,Caucasian,08/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,2,Medium,7,Risk of Violence,-1.26,7,Medium,New,1,0 +65921,76317,69089,PRETRIAL,Hernandez,Rolando,L,Male,Caucasian,08/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +65921,76317,69089,PRETRIAL,Hernandez,Rolando,L,Male,Caucasian,08/22/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65919,76314,69087,PRETRIAL,Lopez,Ronald,NULL,Male,African-American,10/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/30/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +65919,76314,69087,PRETRIAL,Lopez,Ronald,NULL,Male,African-American,10/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/30/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +65919,76314,69087,PRETRIAL,Lopez,Ronald,NULL,Male,African-American,10/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,8/30/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +65922,76319,69091,PRETRIAL,Roberts,Michael,John,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.25,8,High,New,1,0 +65922,76319,69091,PRETRIAL,Roberts,Michael,John,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +65922,76319,69091,PRETRIAL,Roberts,Michael,John,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,8/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65991,76369,69133,PRETRIAL,Manzo,Joann,NULL,Female,Caucasian,11/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/3/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +65991,76369,69133,PRETRIAL,Manzo,Joann,NULL,Female,Caucasian,11/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/3/14 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +65991,76369,69133,PRETRIAL,Manzo,Joann,NULL,Female,Caucasian,11/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65976,76348,69114,Probation,stephens,omarie,NULL,Male,African-American,03/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.12,4,Low,New,1,0 +65976,76348,69114,Probation,stephens,omarie,NULL,Male,African-American,03/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +65976,76348,69114,Probation,stephens,omarie,NULL,Male,African-American,03/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +65982,76356,69120,Probation,Moore,Joanna,Marcella,Female,African-American,01/20/77,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/3/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +65982,76356,69120,Probation,Moore,Joanna,Marcella,Female,African-American,01/20/77,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/3/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +65982,76356,69120,Probation,Moore,Joanna,Marcella,Female,African-American,01/20/77,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65969,76332,69102,Probation,Carter,Joseph,NULL,Male,African-American,03/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +65969,76332,69102,Probation,Carter,Joseph,NULL,Male,African-American,03/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +65969,76332,69102,Probation,Carter,Joseph,NULL,Male,African-American,03/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +59058,76335,69105,PRETRIAL,Heagle,Robert,Lydell,Male,African-American,01/23/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/3/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +59058,76335,69105,PRETRIAL,Heagle,Robert,Lydell,Male,African-American,01/23/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/3/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +59058,76335,69105,PRETRIAL,Heagle,Robert,Lydell,Male,African-American,01/23/57,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65980,76353,69118,Probation,COOPER,COURTNEY,SHERESE,Female,African-American,08/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +65980,76353,69118,Probation,COOPER,COURTNEY,SHERESE,Female,African-American,08/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +65980,76353,69118,Probation,COOPER,COURTNEY,SHERESE,Female,African-American,08/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65966,76327,69098,PRETRIAL,Earp,Sharif,NULL,Male,African-American,08/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +65966,76327,69098,PRETRIAL,Earp,Sharif,NULL,Male,African-American,08/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +65966,76327,69098,PRETRIAL,Earp,Sharif,NULL,Male,African-American,08/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62338,76361,69125,Probation,salter,christina,NULL,Female,Caucasian,01/03/89,17,All Scales,Intake,English,Other,Probation,Single,9/3/14 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +62338,76361,69125,Probation,salter,christina,NULL,Female,Caucasian,01/03/89,17,All Scales,Intake,English,Other,Probation,Single,9/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,6,Medium,New,1,0 +62338,76361,69125,Probation,salter,christina,NULL,Female,Caucasian,01/03/89,17,All Scales,Intake,English,Other,Probation,Single,9/3/14 0:00,2,Medium,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +65978,76350,69116,Probation,Petra,Craig,Leonard,Male,Caucasian,07/11/53,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/3/14 0:00,1,Low,7,Risk of Violence,-4.38,1,Low,New,1,0 +65978,76350,69116,Probation,Petra,Craig,Leonard,Male,Caucasian,07/11/53,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/3/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +65978,76350,69116,Probation,Petra,Craig,Leonard,Male,Caucasian,07/11/53,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65945,76359,69123,PRETRIAL,BRAZIEL,ADAM,NULL,Male,African-American,08/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/3/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +65945,76359,69123,PRETRIAL,BRAZIEL,ADAM,NULL,Male,African-American,08/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +65945,76359,69123,PRETRIAL,BRAZIEL,ADAM,NULL,Male,African-American,08/16/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/3/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65968,76329,69100,PRETRIAL,Hill,Valerie,NULL,Female,Caucasian,02/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.19,8,High,New,1,0 +65968,76329,69100,PRETRIAL,Hill,Valerie,NULL,Female,Caucasian,02/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.41,6,Medium,New,1,0 +65968,76329,69100,PRETRIAL,Hill,Valerie,NULL,Female,Caucasian,02/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +47483,76338,48049,PRETRIAL,Haughton,Chartavious,M,Female,African-American,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,Copy,1,0 +47483,76338,48049,PRETRIAL,Haughton,Chartavious,M,Female,African-American,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,Copy,1,0 +47483,76338,48049,PRETRIAL,Haughton,Chartavious,M,Female,African-American,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +65990,76368,69132,Probation,MONDRAGON,NORBERT,L,Male,Hispanic,04/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +65990,76368,69132,Probation,MONDRAGON,NORBERT,L,Male,Hispanic,04/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +65990,76368,69132,Probation,MONDRAGON,NORBERT,L,Male,Hispanic,04/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65972,76343,69110,Probation,Delgiudice,Gibran,NULL,Male,Hispanic,08/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.87,9,High,New,1,0 +65972,76343,69110,Probation,Delgiudice,Gibran,NULL,Male,Hispanic,08/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +65972,76343,69110,Probation,Delgiudice,Gibran,NULL,Male,Hispanic,08/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +65973,76345,69111,Probation,MARINELLI,DAVID,F,Male,Caucasian,02/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +65973,76345,69111,Probation,MARINELLI,DAVID,F,Male,Caucasian,02/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +65973,76345,69111,Probation,MARINELLI,DAVID,F,Male,Caucasian,02/07/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65979,76352,69117,Probation,Rease,Erica,NULL,Female,African-American,09/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +65979,76352,69117,Probation,Rease,Erica,NULL,Female,African-American,09/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.1,8,High,New,1,0 +65979,76352,69117,Probation,Rease,Erica,NULL,Female,African-American,09/26/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65974,76346,69112,PRETRIAL,Tarquinio,Terry,NULL,Male,Caucasian,03/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +65974,76346,69112,PRETRIAL,Tarquinio,Terry,NULL,Male,Caucasian,03/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +65974,76346,69112,PRETRIAL,Tarquinio,Terry,NULL,Male,Caucasian,03/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65985,76360,69124,Probation,nichols,lyle,NULL,Male,Caucasian,10/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/3/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +65985,76360,69124,Probation,nichols,lyle,NULL,Male,Caucasian,10/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/3/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +65985,76360,69124,Probation,nichols,lyle,NULL,Male,Caucasian,10/25/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +6830,76367,69131,Probation,contreras,eduardo,NULL,Male,Hispanic,08/05/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +6830,76367,69131,Probation,contreras,eduardo,NULL,Male,Hispanic,08/05/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +6830,76367,69131,Probation,contreras,eduardo,NULL,Male,Hispanic,08/05/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65987,76363,69127,Probation,Mazzo,Matthew,NULL,Male,Caucasian,11/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +65987,76363,69127,Probation,Mazzo,Matthew,NULL,Male,Caucasian,11/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +65987,76363,69127,Probation,Mazzo,Matthew,NULL,Male,Caucasian,11/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +65965,76325,69096,Probation,Goncalves,Lindoney,NULL,Female,Hispanic,06/20/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/3/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +65965,76325,69096,Probation,Goncalves,Lindoney,NULL,Female,Hispanic,06/20/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/3/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +65965,76325,69096,Probation,Goncalves,Lindoney,NULL,Female,Hispanic,06/20/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65536,76342,68661,PRETRIAL,Michel,Erlken,NULL,Male,African-American,06/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,4,High,7,Risk of Violence,-0.89,9,High,Copy,1,0 +65536,76342,68661,PRETRIAL,Michel,Erlken,NULL,Male,African-American,06/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,4,High,8,Risk of Recidivism,0.09,8,High,Copy,1,0 +65536,76342,68661,PRETRIAL,Michel,Erlken,NULL,Male,African-American,06/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +65984,76358,69122,PRETRIAL,Logan,Thomas,Earl,Male,African-American,11/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,9/3/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +65984,76358,69122,PRETRIAL,Logan,Thomas,Earl,Male,African-American,11/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,9/3/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +65984,76358,69122,PRETRIAL,Logan,Thomas,Earl,Male,African-American,11/05/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +47483,52773,48049,PRETRIAL,Haughton,Chartavious,M,Female,African-American,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/14 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +47483,52773,48049,PRETRIAL,Haughton,Chartavious,M,Female,African-American,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,7,Medium,New,1,0 +47483,52773,48049,PRETRIAL,Haughton,Chartavious,M,Female,African-American,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/3/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +50904,76330,69101,PRETRIAL,Rouse,Franklin,NULL,Male,African-American,09/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +50904,76330,69101,PRETRIAL,Rouse,Franklin,NULL,Male,African-American,09/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +50904,76330,69101,PRETRIAL,Rouse,Franklin,NULL,Male,African-American,09/15/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +33663,76337,32762,PRETRIAL,ferdinand,patrick,NULL,Male,African-American,03/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,Copy,1,0 +33663,76337,32762,PRETRIAL,ferdinand,patrick,NULL,Male,African-American,03/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,Copy,1,0 +33663,76337,32762,PRETRIAL,ferdinand,patrick,NULL,Male,African-American,03/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +65536,76344,68661,PRETRIAL,Michel,Erlken,NULL,Male,African-American,06/23/91,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,4,High,7,Risk of Violence,-0.89,9,High,Copy,1,0 +65536,76344,68661,PRETRIAL,Michel,Erlken,NULL,Male,African-American,06/23/91,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,4,High,8,Risk of Recidivism,0.09,8,High,Copy,1,0 +65536,76344,68661,PRETRIAL,Michel,Erlken,NULL,Male,African-American,06/23/91,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +64654,76351,67703,PRETRIAL,Young,John,C,Male,Caucasian,12/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,Copy,1,0 +64654,76351,67703,PRETRIAL,Young,John,C,Male,Caucasian,12/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,Copy,1,0 +64654,76351,67703,PRETRIAL,Young,John,C,Male,Caucasian,12/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +65983,76357,69121,Probation,Johnson,Edward,NULL,Male,African-American,06/17/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +65983,76357,69121,Probation,Johnson,Edward,NULL,Male,African-American,06/17/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +65983,76357,69121,Probation,Johnson,Edward,NULL,Male,African-American,06/17/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +65971,76336,69106,PRETRIAL,Fulmore,Jeffery,Arnold,Male,African-American,09/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/3/14 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +65971,76336,69106,PRETRIAL,Fulmore,Jeffery,Arnold,Male,African-American,09/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/3/14 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +65971,76336,69106,PRETRIAL,Fulmore,Jeffery,Arnold,Male,African-American,09/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +65967,76328,69099,Probation,ferrell,Dylan,NULL,Male,Caucasian,08/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +65967,76328,69099,Probation,ferrell,Dylan,NULL,Male,Caucasian,08/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +65967,76328,69099,Probation,ferrell,Dylan,NULL,Male,Caucasian,08/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65436,76331,68541,PRETRIAL,POWELL,KEITH,NULL,Male,African-American,06/10/57,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,Copy,1,0 +65436,76331,68541,PRETRIAL,POWELL,KEITH,NULL,Male,African-American,06/10/57,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,Copy,1,0 +65436,76331,68541,PRETRIAL,POWELL,KEITH,NULL,Male,African-American,06/10/57,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,Copy,1,0 +65977,76349,69115,PRETRIAL,Isaacs,Christopher,NULL,Male,African-American,11/28/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +65977,76349,69115,PRETRIAL,Isaacs,Christopher,NULL,Male,African-American,11/28/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +65977,76349,69115,PRETRIAL,Isaacs,Christopher,NULL,Male,African-American,11/28/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +1636,76354,68942,PRETRIAL,Bates,Wesley,Ryan,Male,Caucasian,08/27/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,4,High,7,Risk of Violence,-1.07,8,High,Copy,1,0 +1636,76354,68942,PRETRIAL,Bates,Wesley,Ryan,Male,Caucasian,08/27/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,4,High,8,Risk of Recidivism,0.2,8,High,Copy,1,0 +1636,76354,68942,PRETRIAL,Bates,Wesley,Ryan,Male,Caucasian,08/27/86,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +65950,76341,69109,Probation,REYES,JEANNETTE,N,Female,Hispanic,08/28/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/3/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +65950,76341,69109,Probation,REYES,JEANNETTE,N,Female,Hispanic,08/28/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/3/14 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +65950,76341,69109,Probation,REYES,JEANNETTE,N,Female,Hispanic,08/28/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65956,76326,69097,Probation,Wasilewki,Margaret,NULL,Female,Caucasian,08/18/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/3/14 0:00,1,Low,7,Risk of Violence,-4.29,1,Low,New,1,0 +65956,76326,69097,Probation,Wasilewki,Margaret,NULL,Female,Caucasian,08/18/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/3/14 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +65956,76326,69097,Probation,Wasilewki,Margaret,NULL,Female,Caucasian,08/18/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65981,76355,69119,PRETRIAL,Gonzalez,Georyany,NULL,Female,Hispanic,12/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +65981,76355,69119,PRETRIAL,Gonzalez,Georyany,NULL,Female,Hispanic,12/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +65981,76355,69119,PRETRIAL,Gonzalez,Georyany,NULL,Female,Hispanic,12/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65986,76362,69126,Probation,GIBSON,WILLIAM,SCOTT,Male,Caucasian,08/01/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/3/14 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +65986,76362,69126,Probation,GIBSON,WILLIAM,SCOTT,Male,Caucasian,08/01/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/3/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +65986,76362,69126,Probation,GIBSON,WILLIAM,SCOTT,Male,Caucasian,08/01/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65970,76333,69103,Probation,SMITH,GEORGE,B,Male,African-American,02/08/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +65970,76333,69103,Probation,SMITH,GEORGE,B,Male,African-American,02/08/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +65970,76333,69103,Probation,SMITH,GEORGE,B,Male,African-American,02/08/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +33555,76334,69104,PRETRIAL,Hollaway,William,NULL,Male,African-American,12/26/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +33555,76334,69104,PRETRIAL,Hollaway,William,NULL,Male,African-American,12/26/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +33555,76334,69104,PRETRIAL,Hollaway,William,NULL,Male,African-American,12/26/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/3/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65975,76347,69113,PRETRIAL,Castellanos,Marcos,NULL,Male,Hispanic,11/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +65975,76347,69113,PRETRIAL,Castellanos,Marcos,NULL,Male,Hispanic,11/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +65975,76347,69113,PRETRIAL,Castellanos,Marcos,NULL,Male,Hispanic,11/08/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/3/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +47316,76383,69146,PRETRIAL,Gibson,Laron,NULL,Male,African-American,02/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +47316,76383,69146,PRETRIAL,Gibson,Laron,NULL,Male,African-American,02/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +47316,76383,69146,PRETRIAL,Gibson,Laron,NULL,Male,African-American,02/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +65957,76375,69138,Probation,Brannigan,David,NULL,Male,Caucasian,01/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +65957,76375,69138,Probation,Brannigan,David,NULL,Male,Caucasian,01/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +65957,76375,69138,Probation,Brannigan,David,NULL,Male,Caucasian,01/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66014,76399,69161,Probation,Isidore,Precious,NULL,Female,African-American,07/25/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +66014,76399,69161,Probation,Isidore,Precious,NULL,Female,African-American,07/25/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +66014,76399,69161,Probation,Isidore,Precious,NULL,Female,African-American,07/25/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65997,76378,69141,Probation,Frazier,Adrian,NULL,Male,African-American,02/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +65997,76378,69141,Probation,Frazier,Adrian,NULL,Male,African-American,02/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +65997,76378,69141,Probation,Frazier,Adrian,NULL,Male,African-American,02/03/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66011,76396,69158,Probation,trochez,brenda,NULL,Female,African-American,05/15/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +66011,76396,69158,Probation,trochez,brenda,NULL,Female,African-American,05/15/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.71,10,High,New,1,0 +66011,76396,69158,Probation,trochez,brenda,NULL,Female,African-American,05/15/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65992,76370,69134,PRETRIAL,Cumbie,Jaime,NULL,Male,African-American,07/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,4,High,7,Risk of Violence,-0.34,10,High,New,1,0 +65992,76370,69134,PRETRIAL,Cumbie,Jaime,NULL,Male,African-American,07/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +65992,76370,69134,PRETRIAL,Cumbie,Jaime,NULL,Male,African-American,07/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66007,76391,69154,Probation,Hall,Jesse,Thomas,Male,Caucasian,12/07/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/4/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +66007,76391,69154,Probation,Hall,Jesse,Thomas,Male,Caucasian,12/07/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +66007,76391,69154,Probation,Hall,Jesse,Thomas,Male,Caucasian,12/07/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66019,76407,69169,Probation,Meran,Wilkins,NULL,Male,Hispanic,04/01/85,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/4/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +66019,76407,69169,Probation,Meran,Wilkins,NULL,Male,Hispanic,04/01/85,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +66019,76407,69169,Probation,Meran,Wilkins,NULL,Male,Hispanic,04/01/85,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +27249,76409,69171,PRETRIAL,BLISS,TYRONE,NULL,Male,African-American,05/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +27249,76409,69171,PRETRIAL,BLISS,TYRONE,NULL,Male,African-American,05/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,4,High,8,Risk of Recidivism,0.84,10,High,New,1,0 +27249,76409,69171,PRETRIAL,BLISS,TYRONE,NULL,Male,African-American,05/02/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +65998,76379,69142,PRETRIAL,Garcia,Lisa,NULL,Female,Hispanic,08/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +65998,76379,69142,PRETRIAL,Garcia,Lisa,NULL,Female,Hispanic,08/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +65998,76379,69142,PRETRIAL,Garcia,Lisa,NULL,Female,Hispanic,08/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +66003,76386,69149,PRETRIAL,VERNON,TERRENCE,NULL,Male,Caucasian,11/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +66003,76386,69149,PRETRIAL,VERNON,TERRENCE,NULL,Male,Caucasian,11/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +66003,76386,69149,PRETRIAL,VERNON,TERRENCE,NULL,Male,Caucasian,11/30/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66004,76388,69151,PRETRIAL,Rehman,Abid,NULL,Male,Other,06/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/4/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +66004,76388,69151,PRETRIAL,Rehman,Abid,NULL,Male,Other,06/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +66004,76388,69151,PRETRIAL,Rehman,Abid,NULL,Male,Other,06/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +3019,2950,2732,PRETRIAL,JOHNSON,PRINCEMALACHI,BENJAMIN,Male,African-American,04/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +3019,2950,2732,PRETRIAL,JOHNSON,PRINCEMALACHI,BENJAMIN,Male,African-American,04/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +3019,2950,2732,PRETRIAL,JOHNSON,PRINCEMALACHI,BENJAMIN,Male,African-American,04/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +46462,76372,46875,PRETRIAL,LaPierre,Francoeur,NULL,Male,Other,03/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,Copy,1,0 +46462,76372,46875,PRETRIAL,LaPierre,Francoeur,NULL,Male,Other,03/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,Copy,1,0 +46462,76372,46875,PRETRIAL,LaPierre,Francoeur,NULL,Male,Other,03/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +3019,76393,2732,PRETRIAL,JOHNSON,PRINCEMALACHI,BENJAMIN,Male,African-American,04/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,Copy,1,0 +3019,76393,2732,PRETRIAL,JOHNSON,PRINCEMALACHI,BENJAMIN,Male,African-American,04/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,Copy,1,0 +3019,76393,2732,PRETRIAL,JOHNSON,PRINCEMALACHI,BENJAMIN,Male,African-American,04/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +50155,76402,69164,PRETRIAL,Kelly,Maureen,NULL,Female,Caucasian,11/21/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/4/14 0:00,1,Low,7,Risk of Violence,-4.56,1,Low,New,1,0 +50155,76402,69164,PRETRIAL,Kelly,Maureen,NULL,Female,Caucasian,11/21/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/4/14 0:00,1,Low,8,Risk of Recidivism,-2.65,1,Low,New,1,0 +50155,76402,69164,PRETRIAL,Kelly,Maureen,NULL,Female,Caucasian,11/21/45,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66000,76381,69144,Probation,Belmonte,Antonio,NULL,Male,Hispanic,09/07/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/4/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +66000,76381,69144,Probation,Belmonte,Antonio,NULL,Male,Hispanic,09/07/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +66000,76381,69144,Probation,Belmonte,Antonio,NULL,Male,Hispanic,09/07/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65994,76373,69136,PRETRIAL,Raymond,Kendrick,NULL,Male,African-American,09/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.33,3,Low,New,1,0 +65994,76373,69136,PRETRIAL,Raymond,Kendrick,NULL,Male,African-American,09/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,New,1,0 +65994,76373,69136,PRETRIAL,Raymond,Kendrick,NULL,Male,African-American,09/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59488,76401,69163,PRETRIAL,Auguste,Karl,NULL,Male,Other,08/19/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +59488,76401,69163,PRETRIAL,Auguste,Karl,NULL,Male,Other,08/19/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +59488,76401,69163,PRETRIAL,Auguste,Karl,NULL,Male,Other,08/19/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65999,76380,69143,Probation,Benjamin,Kenson,NULL,Male,African-American,01/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +65999,76380,69143,Probation,Benjamin,Kenson,NULL,Male,African-American,01/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +65999,76380,69143,Probation,Benjamin,Kenson,NULL,Male,African-American,01/22/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66009,76394,69156,Probation,blake,christina,NULL,Female,African-American,11/15/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +66009,76394,69156,Probation,blake,christina,NULL,Female,African-American,11/15/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +66009,76394,69156,Probation,blake,christina,NULL,Female,African-American,11/15/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +66005,76389,69152,PRETRIAL,Fetty,Ronald,NULL,Male,Caucasian,08/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +66005,76389,69152,PRETRIAL,Fetty,Ronald,NULL,Male,Caucasian,08/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +66005,76389,69152,PRETRIAL,Fetty,Ronald,NULL,Male,Caucasian,08/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66018,76406,69168,Probation,dara,dennis,NULL,Male,Caucasian,01/27/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/4/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +66018,76406,69168,Probation,dara,dennis,NULL,Male,Caucasian,01/27/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +66018,76406,69168,Probation,dara,dennis,NULL,Male,Caucasian,01/27/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65993,76371,69135,PRETRIAL,Sylvain,Jerry,R,Male,African-American,06/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +65993,76371,69135,PRETRIAL,Sylvain,Jerry,R,Male,African-American,06/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +65993,76371,69135,PRETRIAL,Sylvain,Jerry,R,Male,African-American,06/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66002,76385,69148,Probation,Joseph,Frantz,NULL,Male,African-American,02/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +66002,76385,69148,Probation,Joseph,Frantz,NULL,Male,African-American,02/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +66002,76385,69148,Probation,Joseph,Frantz,NULL,Male,African-American,02/23/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66010,76395,69157,Probation,Pierce,Lee,Anthony,Male,African-American,10/31/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +66010,76395,69157,Probation,Pierce,Lee,Anthony,Male,African-American,10/31/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +66010,76395,69157,Probation,Pierce,Lee,Anthony,Male,African-American,10/31/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65995,76374,69137,PRETRIAL,Forbes,Michael,Junior,Male,Other,02/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/4/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +65995,76374,69137,PRETRIAL,Forbes,Michael,Junior,Male,Other,02/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +65995,76374,69137,PRETRIAL,Forbes,Michael,Junior,Male,Other,02/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +33014,76408,69170,PRETRIAL,ATWELL,WALTER,D,Male,African-American,06/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +33014,76408,69170,PRETRIAL,ATWELL,WALTER,D,Male,African-American,06/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +33014,76408,69170,PRETRIAL,ATWELL,WALTER,D,Male,African-American,06/09/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66001,76382,69145,PRETRIAL,PITTS,JERRON,NULL,Male,African-American,07/22/97,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +66001,76382,69145,PRETRIAL,PITTS,JERRON,NULL,Male,African-American,07/22/97,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +66001,76382,69145,PRETRIAL,PITTS,JERRON,NULL,Male,African-American,07/22/97,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66015,76400,69162,PRETRIAL,Castilo,Andres,NULL,Male,Hispanic,07/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/4/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +66015,76400,69162,PRETRIAL,Castilo,Andres,NULL,Male,Hispanic,07/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +66015,76400,69162,PRETRIAL,Castilo,Andres,NULL,Male,Hispanic,07/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66006,76390,69153,PRETRIAL,WATSON,FRANKLIN,NULL,Female,African-American,09/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +66006,76390,69153,PRETRIAL,WATSON,FRANKLIN,NULL,Female,African-American,09/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +66006,76390,69153,PRETRIAL,WATSON,FRANKLIN,NULL,Female,African-American,09/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66008,76392,69155,PRETRIAL,Magnant,Yveney,NULL,Male,African-American,08/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/4/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +66008,76392,69155,PRETRIAL,Magnant,Yveney,NULL,Male,African-American,08/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +66008,76392,69155,PRETRIAL,Magnant,Yveney,NULL,Male,African-American,08/10/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +5241,76377,69140,PRETRIAL,Poulson,Daniel,Wade,Male,Caucasian,01/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,New,1,0 +5241,76377,69140,PRETRIAL,Poulson,Daniel,Wade,Male,Caucasian,01/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +5241,76377,69140,PRETRIAL,Poulson,Daniel,Wade,Male,Caucasian,01/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66012,76397,69159,Probation,Melendez,Carlos,NULL,Male,Hispanic,10/04/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +66012,76397,69159,Probation,Melendez,Carlos,NULL,Male,Hispanic,10/04/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +66012,76397,69159,Probation,Melendez,Carlos,NULL,Male,Hispanic,10/04/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66013,76398,69160,Probation,AHMAD,IKHLEEL,NULL,Male,Caucasian,12/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +66013,76398,69160,Probation,AHMAD,IKHLEEL,NULL,Male,Caucasian,12/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +66013,76398,69160,Probation,AHMAD,IKHLEEL,NULL,Male,Caucasian,12/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65996,76376,69139,Probation,Miller,Adrian,NULL,Male,African-American,11/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +65996,76376,69139,Probation,Miller,Adrian,NULL,Male,African-American,11/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +65996,76376,69139,Probation,Miller,Adrian,NULL,Male,African-American,11/27/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66017,76405,69167,Probation,BIRMINGHAM,GEORGE,NULL,Male,Caucasian,07/19/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +66017,76405,69167,Probation,BIRMINGHAM,GEORGE,NULL,Male,Caucasian,07/19/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +66017,76405,69167,Probation,BIRMINGHAM,GEORGE,NULL,Male,Caucasian,07/19/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/4/14 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +66028,76419,69181,Probation,treptow,jane,NULL,Female,Caucasian,11/16/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/5/14 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +66028,76419,69181,Probation,treptow,jane,NULL,Female,Caucasian,11/16/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/5/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +66028,76419,69181,Probation,treptow,jane,NULL,Female,Caucasian,11/16/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66038,76434,69195,Probation,Nichols,Ronald,Albert,Male,Caucasian,03/31/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/5/14 0:00,2,Medium,7,Risk of Violence,-2.85,2,Low,New,1,0 +66038,76434,69195,Probation,Nichols,Ronald,Albert,Male,Caucasian,03/31/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +66038,76434,69195,Probation,Nichols,Ronald,Albert,Male,Caucasian,03/31/59,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/5/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +66021,76411,69173,PRETRIAL,Everett,Phillip,NULL,Male,African-American,01/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.72,2,Low,New,1,0 +66021,76411,69173,PRETRIAL,Everett,Phillip,NULL,Male,African-American,01/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +66021,76411,69173,PRETRIAL,Everett,Phillip,NULL,Male,African-American,01/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66023,76413,69175,PRETRIAL,Morrissigler,Kristofer,NULL,Male,Caucasian,04/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.14,4,Low,New,1,0 +66023,76413,69175,PRETRIAL,Morrissigler,Kristofer,NULL,Male,Caucasian,04/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +66023,76413,69175,PRETRIAL,Morrissigler,Kristofer,NULL,Male,Caucasian,04/08/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66027,76418,69180,Probation,Branch,shawn,Tyrone,Male,African-American,05/03/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/5/14 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +66027,76418,69180,Probation,Branch,shawn,Tyrone,Male,African-American,05/03/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +66027,76418,69180,Probation,Branch,shawn,Tyrone,Male,African-American,05/03/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/5/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66032,76426,69187,Probation,Delgado,Juan,NULL,Male,Caucasian,11/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +66032,76426,69187,Probation,Delgado,Juan,NULL,Male,Caucasian,11/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +66032,76426,69187,Probation,Delgado,Juan,NULL,Male,Caucasian,11/06/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61138,76421,69183,PRETRIAL,Godette,Greg,NULL,Male,Caucasian,10/24/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/5/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +61138,76421,69183,PRETRIAL,Godette,Greg,NULL,Male,Caucasian,10/24/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/5/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +61138,76421,69183,PRETRIAL,Godette,Greg,NULL,Male,Caucasian,10/24/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66034,76429,69190,Probation,FRANKLIN,JAMAL,MARC,Male,African-American,02/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +66034,76429,69190,Probation,FRANKLIN,JAMAL,MARC,Male,African-American,02/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +66034,76429,69190,Probation,FRANKLIN,JAMAL,MARC,Male,African-American,02/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66020,76410,69172,PRETRIAL,Holem,Kenneth,NULL,Male,Caucasian,07/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +66020,76410,69172,PRETRIAL,Holem,Kenneth,NULL,Male,Caucasian,07/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/14 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +66020,76410,69172,PRETRIAL,Holem,Kenneth,NULL,Male,Caucasian,07/20/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66036,76431,69192,Probation,blainkin,george,NULL,Male,Caucasian,09/19/87,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,9/5/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +66036,76431,69192,Probation,blainkin,george,NULL,Male,Caucasian,09/19/87,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,9/5/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +66036,76431,69192,Probation,blainkin,george,NULL,Male,Caucasian,09/19/87,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +21911,76427,69188,Probation,hyatt,rhoan,NULL,Male,African-American,09/06/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +21911,76427,69188,Probation,hyatt,rhoan,NULL,Male,African-American,09/06/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +21911,76427,69188,Probation,hyatt,rhoan,NULL,Male,African-American,09/06/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66041,76436,69197,Probation,trauco,christopher,NULL,Male,Caucasian,03/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +66041,76436,69197,Probation,trauco,christopher,NULL,Male,Caucasian,03/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +66041,76436,69197,Probation,trauco,christopher,NULL,Male,Caucasian,03/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66025,76415,69177,PRETRIAL,Rice,Gerald,NULL,Male,African-American,05/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1,8,High,New,1,0 +66025,76415,69177,PRETRIAL,Rice,Gerald,NULL,Male,African-American,05/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +66025,76415,69177,PRETRIAL,Rice,Gerald,NULL,Male,African-American,05/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66029,76422,69184,PRETRIAL,UCETA,WILTON,NULL,Male,Hispanic,09/30/87,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,9/5/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +66029,76422,69184,PRETRIAL,UCETA,WILTON,NULL,Male,Hispanic,09/30/87,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,9/5/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +66029,76422,69184,PRETRIAL,UCETA,WILTON,NULL,Male,Hispanic,09/30/87,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66030,76424,69186,Probation,Espana,Angelica,NULL,Female,Hispanic,06/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +66030,76424,69186,Probation,Espana,Angelica,NULL,Female,Hispanic,06/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,8,Risk of Recidivism,-1.43,2,Low,New,1,0 +66030,76424,69186,Probation,Espana,Angelica,NULL,Female,Hispanic,06/03/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66024,76414,69176,PRETRIAL,Rubio,Henry,Grandal,Male,Hispanic,08/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/5/14 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +66024,76414,69176,PRETRIAL,Rubio,Henry,Grandal,Male,Hispanic,08/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +66024,76414,69176,PRETRIAL,Rubio,Henry,Grandal,Male,Hispanic,08/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/5/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66037,76432,69193,Probation,HOOVER,MATTHEW,NULL,Male,Caucasian,02/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +66037,76432,69193,Probation,HOOVER,MATTHEW,NULL,Male,Caucasian,02/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +66037,76432,69193,Probation,HOOVER,MATTHEW,NULL,Male,Caucasian,02/17/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66040,76435,69196,PRETRIAL,Good,Jamie,NULL,Female,Caucasian,04/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/5/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +66040,76435,69196,PRETRIAL,Good,Jamie,NULL,Female,Caucasian,04/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/5/14 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +66040,76435,69196,PRETRIAL,Good,Jamie,NULL,Female,Caucasian,04/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66035,76430,69191,Probation,Gooden,Tibia,NULL,Female,African-American,01/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +66035,76430,69191,Probation,Gooden,Tibia,NULL,Female,African-American,01/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +66035,76430,69191,Probation,Gooden,Tibia,NULL,Female,African-American,01/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +66043,76437,69198,PRETRIAL,George,Christi,Tylor,Female,Caucasian,04/27/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/5/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +66043,76437,69198,PRETRIAL,George,Christi,Tylor,Female,Caucasian,04/27/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/5/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +66043,76437,69198,PRETRIAL,George,Christi,Tylor,Female,Caucasian,04/27/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +30204,76425,33596,Probation,Fain,Brian,NULL,Male,African-American,09/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +30204,76425,33596,Probation,Fain,Brian,NULL,Male,African-American,09/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.81,10,High,Copy,1,0 +30204,76425,33596,Probation,Fain,Brian,NULL,Male,African-American,09/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +66026,76417,69179,PRETRIAL,Puche-aristimuno,Dario,NULL,Male,Caucasian,04/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/14 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +66026,76417,69179,PRETRIAL,Puche-aristimuno,Dario,NULL,Male,Caucasian,04/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +66026,76417,69179,PRETRIAL,Puche-aristimuno,Dario,NULL,Male,Caucasian,04/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/5/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +45814,76420,69182,PRETRIAL,COLSON,HEATHER,NULL,Female,Caucasian,06/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/5/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +45814,76420,69182,PRETRIAL,COLSON,HEATHER,NULL,Female,Caucasian,06/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/5/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,New,1,0 +45814,76420,69182,PRETRIAL,COLSON,HEATHER,NULL,Female,Caucasian,06/08/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66022,76412,69174,PRETRIAL,Sampson,Corneilus,NULL,Male,African-American,05/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/5/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +66022,76412,69174,PRETRIAL,Sampson,Corneilus,NULL,Male,African-American,05/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/5/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +66022,76412,69174,PRETRIAL,Sampson,Corneilus,NULL,Male,African-American,05/18/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66048,76448,69206,PRETRIAL,Edwards,Kevin,NULL,Male,African-American,05/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,New,1,0 +66048,76448,69206,PRETRIAL,Edwards,Kevin,NULL,Male,African-American,05/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +66048,76448,69206,PRETRIAL,Edwards,Kevin,NULL,Male,African-American,05/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66045,76441,69202,PRETRIAL,Griffin,Roderick,NULL,Male,African-American,11/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +66045,76441,69202,PRETRIAL,Griffin,Roderick,NULL,Male,African-American,11/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +66045,76441,69202,PRETRIAL,Griffin,Roderick,NULL,Male,African-American,11/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +29183,76446,69205,PRETRIAL,Taylor,Xavier,NULL,Male,African-American,01/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +29183,76446,69205,PRETRIAL,Taylor,Xavier,NULL,Male,African-American,01/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +29183,76446,69205,PRETRIAL,Taylor,Xavier,NULL,Male,African-American,01/06/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66047,76444,69204,PRETRIAL,CUNNINGHAM,MATTHEW,LLOYD,Male,Other,03/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +66047,76444,69204,PRETRIAL,CUNNINGHAM,MATTHEW,LLOYD,Male,Other,03/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,New,1,0 +66047,76444,69204,PRETRIAL,CUNNINGHAM,MATTHEW,LLOYD,Male,Other,03/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66049,76449,69207,PRETRIAL,OBAS,MARY-KOFF,NULL,Male,Other,03/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +66049,76449,69207,PRETRIAL,OBAS,MARY-KOFF,NULL,Male,Other,03/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +66049,76449,69207,PRETRIAL,OBAS,MARY-KOFF,NULL,Male,Other,03/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54096,76443,55648,PRETRIAL,Smith,Ricoh,NULL,Male,African-American,01/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,Copy,1,0 +54096,76443,55648,PRETRIAL,Smith,Ricoh,NULL,Male,African-American,01/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.66,10,High,Copy,1,0 +54096,76443,55648,PRETRIAL,Smith,Ricoh,NULL,Male,African-American,01/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +26618,76445,25720,PRETRIAL,JONES,LANDO,NULL,Male,African-American,01/29/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,Copy,1,0 +26618,76445,25720,PRETRIAL,JONES,LANDO,NULL,Male,African-American,01/29/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,Copy,1,0 +26618,76445,25720,PRETRIAL,JONES,LANDO,NULL,Male,African-American,01/29/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +21491,76440,69201,Probation,schmidt,gregory,NULL,Male,Caucasian,08/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.91,5,Medium,New,1,0 +21491,76440,69201,Probation,schmidt,gregory,NULL,Male,Caucasian,08/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +21491,76440,69201,Probation,schmidt,gregory,NULL,Male,Caucasian,08/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,39,10,High,New,1,0 +66046,76442,69203,PRETRIAL,Peterson,Angela,Lorraine,Female,Caucasian,01/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +66046,76442,69203,PRETRIAL,Peterson,Angela,Lorraine,Female,Caucasian,01/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +66046,76442,69203,PRETRIAL,Peterson,Angela,Lorraine,Female,Caucasian,01/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66050,76450,69208,PRETRIAL,Morrison,Tawon,NULL,Male,African-American,05/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +66050,76450,69208,PRETRIAL,Morrison,Tawon,NULL,Male,African-American,05/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +66050,76450,69208,PRETRIAL,Morrison,Tawon,NULL,Male,African-American,05/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +26035,76447,25136,PRETRIAL,Jeffard,Leslie,NULL,Male,African-American,02/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,Copy,1,0 +26035,76447,25136,PRETRIAL,Jeffard,Leslie,NULL,Male,African-American,02/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,Copy,1,0 +26035,76447,25136,PRETRIAL,Jeffard,Leslie,NULL,Male,African-American,02/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +66052,76452,69210,PRETRIAL,CARTER,RICHARD,W,Male,African-American,05/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/7/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +66052,76452,69210,PRETRIAL,CARTER,RICHARD,W,Male,African-American,05/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/7/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +66052,76452,69210,PRETRIAL,CARTER,RICHARD,W,Male,African-American,05/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/7/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66053,76453,69211,PRETRIAL,MILES,JASON,RENARD,Male,African-American,02/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/7/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +66053,76453,69211,PRETRIAL,MILES,JASON,RENARD,Male,African-American,02/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/7/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +66053,76453,69211,PRETRIAL,MILES,JASON,RENARD,Male,African-American,02/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66051,76451,69209,PRETRIAL,Bledsoe,Matthew,NULL,Male,Caucasian,05/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +66051,76451,69209,PRETRIAL,Bledsoe,Matthew,NULL,Male,Caucasian,05/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +66051,76451,69209,PRETRIAL,Bledsoe,Matthew,NULL,Male,Caucasian,05/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66054,76454,69212,PRETRIAL,Pointer,Martise,NULL,Male,African-American,05/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.14,8,High,New,1,0 +66054,76454,69212,PRETRIAL,Pointer,Martise,NULL,Male,African-American,05/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +66054,76454,69212,PRETRIAL,Pointer,Martise,NULL,Male,African-American,05/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +44714,76477,44854,PRETRIAL,Joseph,Marlon,NULL,Male,African-American,06/28/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +44714,76477,44854,PRETRIAL,Joseph,Marlon,NULL,Male,African-American,06/28/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,2,Medium,8,Risk of Recidivism,0.12,7,Medium,New,1,0 +44714,76477,44854,PRETRIAL,Joseph,Marlon,NULL,Male,African-American,06/28/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,2,Medium,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +66056,76456,69214,PRETRIAL,LAWRENCE,STEVEN,ANDREW,Male,African-American,10/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +66056,76456,69214,PRETRIAL,LAWRENCE,STEVEN,ANDREW,Male,African-American,10/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +66056,76456,69214,PRETRIAL,LAWRENCE,STEVEN,ANDREW,Male,African-American,10/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66068,76475,69228,PRETRIAL,Roland,Shanard,Daniel,Male,African-American,12/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,4,High,7,Risk of Violence,-1.18,8,High,Copy,1,0 +66068,76475,69228,PRETRIAL,Roland,Shanard,Daniel,Male,African-American,12/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,4,High,8,Risk of Recidivism,0.24,8,High,Copy,1,0 +66068,76475,69228,PRETRIAL,Roland,Shanard,Daniel,Male,African-American,12/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +66078,76490,69241,PRETRIAL,Surpal,Melvin,Simeon,Male,African-American,11/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +66078,76490,69241,PRETRIAL,Surpal,Melvin,Simeon,Male,African-American,11/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +66078,76490,69241,PRETRIAL,Surpal,Melvin,Simeon,Male,African-American,11/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66061,76462,69220,Probation,Brainard,Joseph,NULL,Male,Caucasian,08/04/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/8/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +66061,76462,69220,Probation,Brainard,Joseph,NULL,Male,Caucasian,08/04/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/8/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +66061,76462,69220,Probation,Brainard,Joseph,NULL,Male,Caucasian,08/04/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66065,76469,69225,PRETRIAL,jones,gary,NULL,Male,Caucasian,12/05/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,New,1,0 +66065,76469,69225,PRETRIAL,jones,gary,NULL,Male,Caucasian,12/05/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +66065,76469,69225,PRETRIAL,jones,gary,NULL,Male,Caucasian,12/05/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +29075,76485,69236,PRETRIAL,PINKNEY,ANTHONY,NULL,Male,African-American,11/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +29075,76485,69236,PRETRIAL,PINKNEY,ANTHONY,NULL,Male,African-American,11/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +29075,76485,69236,PRETRIAL,PINKNEY,ANTHONY,NULL,Male,African-American,11/26/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60697,76464,69222,PRETRIAL,Delgado,Melina,NULL,Female,Hispanic,11/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +60697,76464,69222,PRETRIAL,Delgado,Melina,NULL,Female,Hispanic,11/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +60697,76464,69222,PRETRIAL,Delgado,Melina,NULL,Female,Hispanic,11/19/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +66059,76459,69217,PRETRIAL,FAWCETT,MELISSA,ANN,Female,Caucasian,05/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/8/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +66059,76459,69217,PRETRIAL,FAWCETT,MELISSA,ANN,Female,Caucasian,05/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/8/14 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +66059,76459,69217,PRETRIAL,FAWCETT,MELISSA,ANN,Female,Caucasian,05/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66067,76472,69227,PRETRIAL,Tapia,Oscar,Manuel,Male,Caucasian,06/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,Copy,1,0 +66067,76472,69227,PRETRIAL,Tapia,Oscar,Manuel,Male,Caucasian,06/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,Copy,1,0 +66067,76472,69227,PRETRIAL,Tapia,Oscar,Manuel,Male,Caucasian,06/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +66080,76493,69244,Probation,Perez,Ramiro,NULL,Male,Hispanic,08/10/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +66080,76493,69244,Probation,Perez,Ramiro,NULL,Male,Hispanic,08/10/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +66080,76493,69244,Probation,Perez,Ramiro,NULL,Male,Hispanic,08/10/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +64562,76465,67584,Probation,reynoso,raul,NULL,Male,Hispanic,10/30/57,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +64562,76465,67584,Probation,reynoso,raul,NULL,Male,Hispanic,10/30/57,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +64562,76465,67584,Probation,reynoso,raul,NULL,Male,Hispanic,10/30/57,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +8786,76479,69231,PRETRIAL,honaker,jamie,lynn,Female,Caucasian,03/23/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +8786,76479,69231,PRETRIAL,honaker,jamie,lynn,Female,Caucasian,03/23/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +8786,76479,69231,PRETRIAL,honaker,jamie,lynn,Female,Caucasian,03/23/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +4862,76486,69237,PRETRIAL,Lemus,Gerardo,E,Male,Hispanic,03/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +4862,76486,69237,PRETRIAL,Lemus,Gerardo,E,Male,Hispanic,03/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,4,High,8,Risk of Recidivism,0.37,9,High,New,1,0 +4862,76486,69237,PRETRIAL,Lemus,Gerardo,E,Male,Hispanic,03/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66076,76488,69239,Probation,Philip,Swinton,Selbie,Male,African-American,01/30/38,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/8/14 0:00,1,Low,7,Risk of Violence,-4.48,1,Low,New,1,0 +66076,76488,69239,Probation,Philip,Swinton,Selbie,Male,African-American,01/30/38,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/8/14 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +66076,76488,69239,Probation,Philip,Swinton,Selbie,Male,African-American,01/30/38,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66058,76458,69216,PRETRIAL,FERRIS,CHARLES,NULL,Male,Caucasian,01/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +66058,76458,69216,PRETRIAL,FERRIS,CHARLES,NULL,Male,Caucasian,01/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +66058,76458,69216,PRETRIAL,FERRIS,CHARLES,NULL,Male,Caucasian,01/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66066,76470,69226,PRETRIAL,Rodriguez,Kelly,NULL,Female,Caucasian,02/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/8/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +66066,76470,69226,PRETRIAL,Rodriguez,Kelly,NULL,Female,Caucasian,02/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/8/14 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +66066,76470,69226,PRETRIAL,Rodriguez,Kelly,NULL,Female,Caucasian,02/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66079,76491,69242,Probation,Hutchins,Claudius,NULL,Male,African-American,08/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +66079,76491,69242,Probation,Hutchins,Claudius,NULL,Male,African-American,08/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +66079,76491,69242,Probation,Hutchins,Claudius,NULL,Male,African-American,08/07/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66063,76466,69223,Probation,Robothan,Roberto,NULL,Male,Hispanic,08/17/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +66063,76466,69223,Probation,Robothan,Roberto,NULL,Male,Hispanic,08/17/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +66063,76466,69223,Probation,Robothan,Roberto,NULL,Male,Hispanic,08/17/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66071,76480,69232,Probation,ellis,herbert,NULL,Male,African-American,11/30/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/8/14 0:00,1,Low,7,Risk of Violence,-4.41,1,Low,New,1,0 +66071,76480,69232,Probation,ellis,herbert,NULL,Male,African-American,11/30/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/8/14 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +66071,76480,69232,Probation,ellis,herbert,NULL,Male,African-American,11/30/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66075,76487,69238,Probation,KELLERMAN,DAVID,NULL,Male,Caucasian,09/19/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/8/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +66075,76487,69238,Probation,KELLERMAN,DAVID,NULL,Male,Caucasian,09/19/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/8/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +66075,76487,69238,Probation,KELLERMAN,DAVID,NULL,Male,Caucasian,09/19/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55530,76494,69245,Probation,Stockton,Adriel,NULL,Male,Hispanic,08/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +55530,76494,69245,Probation,Stockton,Adriel,NULL,Male,Hispanic,08/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +55530,76494,69245,Probation,Stockton,Adriel,NULL,Male,Hispanic,08/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +66057,76457,69215,PRETRIAL,NAGY,BRIAN,LASZLO,Male,Caucasian,08/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +66057,76457,69215,PRETRIAL,NAGY,BRIAN,LASZLO,Male,Caucasian,08/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +66057,76457,69215,PRETRIAL,NAGY,BRIAN,LASZLO,Male,Caucasian,08/21/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65960,76461,69219,Probation,WHITE,MISTY,NULL,Female,African-American,12/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +65960,76461,69219,Probation,WHITE,MISTY,NULL,Female,African-American,12/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +65960,76461,69219,Probation,WHITE,MISTY,NULL,Female,African-American,12/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +66073,76482,69234,Probation,Polania,Natalia,NULL,Female,Hispanic,04/21/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +66073,76482,69234,Probation,Polania,Natalia,NULL,Female,Hispanic,04/21/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +66073,76482,69234,Probation,Polania,Natalia,NULL,Female,Hispanic,04/21/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66070,76478,69230,Probation,Ganthier,Alain,NULL,Male,Hispanic,03/06/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +66070,76478,69230,Probation,Ganthier,Alain,NULL,Male,Hispanic,03/06/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +66070,76478,69230,Probation,Ganthier,Alain,NULL,Male,Hispanic,03/06/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66084,76496,69247,Probation,Romero,Chrystal,NULL,Female,Hispanic,12/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +66084,76496,69247,Probation,Romero,Chrystal,NULL,Female,Hispanic,12/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +66084,76496,69247,Probation,Romero,Chrystal,NULL,Female,Hispanic,12/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66081,76492,69243,Probation,Defazzio,Diane,NULL,Female,Caucasian,08/29/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/8/14 0:00,1,Low,7,Risk of Violence,-4.49,1,Low,New,1,0 +66081,76492,69243,Probation,Defazzio,Diane,NULL,Female,Caucasian,08/29/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/8/14 0:00,1,Low,8,Risk of Recidivism,-2.69,1,Low,New,1,0 +66081,76492,69243,Probation,Defazzio,Diane,NULL,Female,Caucasian,08/29/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +65569,76484,68702,PRETRIAL,CORDERO,SANTIAGO,NULL,Male,African-American,11/18/79,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,Copy,1,0 +65569,76484,68702,PRETRIAL,CORDERO,SANTIAGO,NULL,Male,African-American,11/18/79,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,Copy,1,0 +65569,76484,68702,PRETRIAL,CORDERO,SANTIAGO,NULL,Male,African-American,11/18/79,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +66055,76455,69213,PRETRIAL,WEAVER,VICKIE,NULL,Female,Caucasian,10/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/8/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +66055,76455,69213,PRETRIAL,WEAVER,VICKIE,NULL,Female,Caucasian,10/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/8/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +66055,76455,69213,PRETRIAL,WEAVER,VICKIE,NULL,Female,Caucasian,10/22/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66072,76481,69233,Probation,early,ryan,NULL,Male,Caucasian,12/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,9/8/14 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,New,1,0 +66072,76481,69233,Probation,early,ryan,NULL,Male,Caucasian,12/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,9/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +66072,76481,69233,Probation,early,ryan,NULL,Male,Caucasian,12/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,9/8/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66060,76460,69218,Probation,anderson,robert,NULL,Male,African-American,01/31/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +66060,76460,69218,Probation,anderson,robert,NULL,Male,African-American,01/31/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +66060,76460,69218,Probation,anderson,robert,NULL,Male,African-American,01/31/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66069,76476,69229,PRETRIAL,Greene,Demarious,NULL,Male,African-American,09/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,4,High,7,Risk of Violence,-0.13,10,High,New,1,0 +66069,76476,69229,PRETRIAL,Greene,Demarious,NULL,Male,African-American,09/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,4,High,8,Risk of Recidivism,1.04,10,High,New,1,0 +66069,76476,69229,PRETRIAL,Greene,Demarious,NULL,Male,African-American,09/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66077,76489,69240,Probation,Schaller,Devanna,NULL,Female,Other,12/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +66077,76489,69240,Probation,Schaller,Devanna,NULL,Female,Other,12/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +66077,76489,69240,Probation,Schaller,Devanna,NULL,Female,Other,12/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66062,76463,69221,Probation,freeny,brandon,NULL,Male,African-American,01/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +66062,76463,69221,Probation,freeny,brandon,NULL,Male,African-American,01/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +66062,76463,69221,Probation,freeny,brandon,NULL,Male,African-American,01/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66064,76468,69224,Probation,Swani,Adnan,NULL,Male,Hispanic,06/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +66064,76468,69224,Probation,Swani,Adnan,NULL,Male,Hispanic,06/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +66064,76468,69224,Probation,Swani,Adnan,NULL,Male,Hispanic,06/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66085,76497,69248,PRETRIAL,VELASQUEZ,MARIA,NULL,Female,Hispanic,09/30/67,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +66085,76497,69248,PRETRIAL,VELASQUEZ,MARIA,NULL,Female,Hispanic,09/30/67,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +66085,76497,69248,PRETRIAL,VELASQUEZ,MARIA,NULL,Female,Hispanic,09/30/67,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,9/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66087,76502,69252,PRETRIAL,Saravialeon,Miguel,Antonio,Male,Hispanic,05/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +66087,76502,69252,PRETRIAL,Saravialeon,Miguel,Antonio,Male,Hispanic,05/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +66087,76502,69252,PRETRIAL,Saravialeon,Miguel,Antonio,Male,Hispanic,05/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65627,76536,68768,PRETRIAL,WILCOX,JOSE,SYLVESTER,Male,African-American,01/16/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,4,High,7,Risk of Violence,-0.55,10,High,Copy,1,0 +65627,76536,68768,PRETRIAL,WILCOX,JOSE,SYLVESTER,Male,African-American,01/16/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,4,High,8,Risk of Recidivism,0.9,10,High,Copy,1,0 +65627,76536,68768,PRETRIAL,WILCOX,JOSE,SYLVESTER,Male,African-American,01/16/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +18558,23192,21316,PRETRIAL,BLANDE,TORRIE,JERMAINE,Male,African-American,01/12/75,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-1.85,5,Medium,New,1,0 +18558,23192,21316,PRETRIAL,BLANDE,TORRIE,JERMAINE,Male,African-American,01/12/75,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +18558,23192,21316,PRETRIAL,BLANDE,TORRIE,JERMAINE,Male,African-American,01/12/75,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66083,76510,69246,PRETRIAL,Palmer,Scott,Edward,Male,Caucasian,08/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/9/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,Copy,1,0 +66083,76510,69246,PRETRIAL,Palmer,Scott,Edward,Male,Caucasian,08/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/9/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,Copy,1,0 +66083,76510,69246,PRETRIAL,Palmer,Scott,Edward,Male,Caucasian,08/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +66106,76528,69276,Probation,NETTLENTON,george,NULL,Male,Hispanic,01/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +66106,76528,69276,Probation,NETTLENTON,george,NULL,Male,Hispanic,01/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +66106,76528,69276,Probation,NETTLENTON,george,NULL,Male,Hispanic,01/17/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66099,76518,69266,Probation,branch,guadalupe,NULL,Female,Hispanic,10/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/9/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +66099,76518,69266,Probation,branch,guadalupe,NULL,Female,Hispanic,10/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/9/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +66099,76518,69266,Probation,branch,guadalupe,NULL,Female,Hispanic,10/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +858,76531,69279,PRETRIAL,BLACKMON,TIARA,DANYELLE,Female,African-American,11/17/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/14 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +858,76531,69279,PRETRIAL,BLACKMON,TIARA,DANYELLE,Female,African-American,11/17/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +858,76531,69279,PRETRIAL,BLACKMON,TIARA,DANYELLE,Female,African-American,11/17/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66089,76505,69255,PRETRIAL,EDWARDS,JAMIE,R,Male,African-American,02/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +66089,76505,69255,PRETRIAL,EDWARDS,JAMIE,R,Male,African-American,02/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +66089,76505,69255,PRETRIAL,EDWARDS,JAMIE,R,Male,African-American,02/05/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +62104,76512,69260,Probation,styers,mark,NULL,Male,Caucasian,07/24/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +62104,76512,69260,Probation,styers,mark,NULL,Male,Caucasian,07/24/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +62104,76512,69260,Probation,styers,mark,NULL,Male,Caucasian,07/24/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +66110,76534,69282,PRETRIAL,GILLINGHAM,JAMES,NULL,Male,Caucasian,10/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/9/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +66110,76534,69282,PRETRIAL,GILLINGHAM,JAMES,NULL,Male,Caucasian,10/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/9/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +66110,76534,69282,PRETRIAL,GILLINGHAM,JAMES,NULL,Male,Caucasian,10/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +26976,76526,69274,PRETRIAL,MITTLER,MICHAEL,NULL,Male,Caucasian,12/12/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +26976,76526,69274,PRETRIAL,MITTLER,MICHAEL,NULL,Male,Caucasian,12/12/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +26976,76526,69274,PRETRIAL,MITTLER,MICHAEL,NULL,Male,Caucasian,12/12/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66111,76539,69286,Probation,CHAVEZ,JUAN,NULL,Male,Hispanic,04/09/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +66111,76539,69286,Probation,CHAVEZ,JUAN,NULL,Male,Hispanic,04/09/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +66111,76539,69286,Probation,CHAVEZ,JUAN,NULL,Male,Hispanic,04/09/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66112,76541,69287,Probation,DICKINSON,DONTAVIUS,NULL,Male,African-American,07/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +66112,76541,69287,Probation,DICKINSON,DONTAVIUS,NULL,Male,African-American,07/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +66112,76541,69287,Probation,DICKINSON,DONTAVIUS,NULL,Male,African-American,07/24/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66094,76513,69261,PRETRIAL,PONCE,FELIX,NULL,Male,Hispanic,04/05/60,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +66094,76513,69261,PRETRIAL,PONCE,FELIX,NULL,Male,Hispanic,04/05/60,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +66094,76513,69261,PRETRIAL,PONCE,FELIX,NULL,Male,Hispanic,04/05/60,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55905,76520,69268,Probation,osullivan,victoria,NULL,Female,Caucasian,01/30/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +55905,76520,69268,Probation,osullivan,victoria,NULL,Female,Caucasian,01/30/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +55905,76520,69268,Probation,osullivan,victoria,NULL,Female,Caucasian,01/30/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66088,76503,69253,PRETRIAL,Dugazon,Richey,NULL,Male,African-American,09/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +66088,76503,69253,PRETRIAL,Dugazon,Richey,NULL,Male,African-American,09/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.18,10,High,New,1,0 +66088,76503,69253,PRETRIAL,Dugazon,Richey,NULL,Male,African-American,09/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +56672,76499,69249,PRETRIAL,Eliacin,Romario,Scott,Male,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +56672,76499,69249,PRETRIAL,Eliacin,Romario,Scott,Male,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.63,10,High,New,1,0 +56672,76499,69249,PRETRIAL,Eliacin,Romario,Scott,Male,African-American,09/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66098,76517,69265,PRETRIAL,marcellin,belgarde,NULL,Male,African-American,06/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +66098,76517,69265,PRETRIAL,marcellin,belgarde,NULL,Male,African-American,06/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +66098,76517,69265,PRETRIAL,marcellin,belgarde,NULL,Male,African-American,06/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66107,76529,69277,Probation,Buckmann,Claudia,NULL,Female,Hispanic,08/22/85,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/9/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +66107,76529,69277,Probation,Buckmann,Claudia,NULL,Female,Hispanic,08/22/85,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/9/14 0:00,1,Low,8,Risk of Recidivism,-1.04,3,Low,New,1,0 +66107,76529,69277,Probation,Buckmann,Claudia,NULL,Female,Hispanic,08/22/85,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +42817,76538,69285,Probation,HUSSAIN,AYUBE,NULL,Male,Asian,11/06/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,2,Medium,7,Risk of Violence,-2.36,3,Low,New,1,0 +42817,76538,69285,Probation,HUSSAIN,AYUBE,NULL,Male,Asian,11/06/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +42817,76538,69285,Probation,HUSSAIN,AYUBE,NULL,Male,Asian,11/06/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66092,76508,69258,PRETRIAL,Thomas,Welton,NULL,Male,African-American,12/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +66092,76508,69258,PRETRIAL,Thomas,Welton,NULL,Male,African-American,12/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +66092,76508,69258,PRETRIAL,Thomas,Welton,NULL,Male,African-American,12/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +21723,76501,69251,PRETRIAL,Milton,Philip,J,Male,Caucasian,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +21723,76501,69251,PRETRIAL,Milton,Philip,J,Male,Caucasian,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +21723,76501,69251,PRETRIAL,Milton,Philip,J,Male,Caucasian,02/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66096,76515,69263,PRETRIAL,Smith,Otis,Jerome,Male,African-American,12/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +66096,76515,69263,PRETRIAL,Smith,Otis,Jerome,Male,African-American,12/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +66096,76515,69263,PRETRIAL,Smith,Otis,Jerome,Male,African-American,12/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +10783,76522,69270,PRETRIAL,WHITE,WILLIAM,H,Male,African-American,04/07/63,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,New,1,0 +10783,76522,69270,PRETRIAL,WHITE,WILLIAM,H,Male,African-American,04/07/63,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +10783,76522,69270,PRETRIAL,WHITE,WILLIAM,H,Male,African-American,04/07/63,22,Risk and Prescreen,Intake,English,Conditional Release,Probation,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66103,76524,69272,PRETRIAL,Smith,Dyer,NULL,Male,African-American,10/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +66103,76524,69272,PRETRIAL,Smith,Dyer,NULL,Male,African-American,10/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +66103,76524,69272,PRETRIAL,Smith,Dyer,NULL,Male,African-American,10/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +66104,76525,69273,Probation,piccione,justin,NULL,Male,Caucasian,05/31/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/9/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +66104,76525,69273,Probation,piccione,justin,NULL,Male,Caucasian,05/31/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/9/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +66104,76525,69273,Probation,piccione,justin,NULL,Male,Caucasian,05/31/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +10678,76504,69254,PRETRIAL,Clemons,Eddie,NULL,Male,African-American,04/20/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +10678,76504,69254,PRETRIAL,Clemons,Eddie,NULL,Male,African-American,04/20/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +10678,76504,69254,PRETRIAL,Clemons,Eddie,NULL,Male,African-American,04/20/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66101,76521,69269,PRETRIAL,Echols,Robert,L,Male,African-American,07/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +66101,76521,69269,PRETRIAL,Echols,Robert,L,Male,African-American,07/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +66101,76521,69269,PRETRIAL,Echols,Robert,L,Male,African-American,07/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66086,76500,69250,PRETRIAL,PEREZ,RICHARD,NULL,Male,Caucasian,07/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,New,1,0 +66086,76500,69250,PRETRIAL,PEREZ,RICHARD,NULL,Male,Caucasian,07/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +66086,76500,69250,PRETRIAL,PEREZ,RICHARD,NULL,Male,Caucasian,07/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66091,76507,69257,PRETRIAL,Silva,Jesney,NULL,Male,Hispanic,05/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/9/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +66091,76507,69257,PRETRIAL,Silva,Jesney,NULL,Male,Hispanic,05/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/9/14 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +66091,76507,69257,PRETRIAL,Silva,Jesney,NULL,Male,Hispanic,05/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66093,76509,69259,PRETRIAL,Rehman,Iram,NULL,Female,Asian,02/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/9/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +66093,76509,69259,PRETRIAL,Rehman,Iram,NULL,Female,Asian,02/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/9/14 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +66093,76509,69259,PRETRIAL,Rehman,Iram,NULL,Female,Asian,02/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66097,76516,69264,PRETRIAL,Fleurissaint,Cnedia,NULL,Female,African-American,02/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +66097,76516,69264,PRETRIAL,Fleurissaint,Cnedia,NULL,Female,African-American,02/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +66097,76516,69264,PRETRIAL,Fleurissaint,Cnedia,NULL,Female,African-American,02/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +41073,76537,69284,PRETRIAL,Holmes,Joshua,NULL,Male,African-American,08/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +41073,76537,69284,PRETRIAL,Holmes,Joshua,NULL,Male,African-American,08/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +41073,76537,69284,PRETRIAL,Holmes,Joshua,NULL,Male,African-American,08/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66105,76527,69275,PRETRIAL,CHISOLM,CHRISTOPHER,NULL,Male,African-American,07/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +66105,76527,69275,PRETRIAL,CHISOLM,CHRISTOPHER,NULL,Male,African-American,07/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +66105,76527,69275,PRETRIAL,CHISOLM,CHRISTOPHER,NULL,Male,African-American,07/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66090,76506,69256,PRETRIAL,Duclas,Stanley,NULL,Male,Other,07/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +66090,76506,69256,PRETRIAL,Duclas,Stanley,NULL,Male,Other,07/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +66090,76506,69256,PRETRIAL,Duclas,Stanley,NULL,Male,Other,07/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66095,76514,69262,Probation,Britton,George,NULL,Male,Caucasian,09/09/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +66095,76514,69262,Probation,Britton,George,NULL,Male,Caucasian,09/09/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +66095,76514,69262,Probation,Britton,George,NULL,Male,Caucasian,09/09/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +56399,76532,69280,PRETRIAL,lyles,roberto,NULL,Male,African-American,04/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +56399,76532,69280,PRETRIAL,lyles,roberto,NULL,Male,African-American,04/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +56399,76532,69280,PRETRIAL,lyles,roberto,NULL,Male,African-American,04/25/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66100,76519,69267,Probation,Tripp,Debra,Ann,Female,Caucasian,04/15/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +66100,76519,69267,Probation,Tripp,Debra,Ann,Female,Caucasian,04/15/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/14 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +66100,76519,69267,Probation,Tripp,Debra,Ann,Female,Caucasian,04/15/67,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66118,76548,69294,PRETRIAL,PETIT-HOMME,YANDELY,NULL,Female,Other,12/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +66118,76548,69294,PRETRIAL,PETIT-HOMME,YANDELY,NULL,Female,Other,12/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +66118,76548,69294,PRETRIAL,PETIT-HOMME,YANDELY,NULL,Female,Other,12/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66124,76556,69302,PRETRIAL,Gomez,Ashton,NULL,Male,Hispanic,11/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +66124,76556,69302,PRETRIAL,Gomez,Ashton,NULL,Male,Hispanic,11/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +66124,76556,69302,PRETRIAL,Gomez,Ashton,NULL,Male,Hispanic,11/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66122,76553,69299,Probation,Kerolle,Daniel,NULL,Male,African-American,04/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/10/14 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +66122,76553,69299,Probation,Kerolle,Daniel,NULL,Male,African-American,04/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +66122,76553,69299,Probation,Kerolle,Daniel,NULL,Male,African-American,04/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/10/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +66128,76561,69306,Probation,SILVER,SEAN,NULL,Male,Caucasian,09/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +66128,76561,69306,Probation,SILVER,SEAN,NULL,Male,Caucasian,09/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +66128,76561,69306,Probation,SILVER,SEAN,NULL,Male,Caucasian,09/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66114,76544,69290,PRETRIAL,Williams,Tatiana,Jade,Female,Other,08/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +66114,76544,69290,PRETRIAL,Williams,Tatiana,Jade,Female,Other,08/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +66114,76544,69290,PRETRIAL,Williams,Tatiana,Jade,Female,Other,08/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66120,76551,69297,PRETRIAL,Gray,Robert,NULL,Male,Caucasian,07/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +66120,76551,69297,PRETRIAL,Gray,Robert,NULL,Male,Caucasian,07/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +66120,76551,69297,PRETRIAL,Gray,Robert,NULL,Male,Caucasian,07/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +60798,76565,69310,PRETRIAL,Zukowski,Henry,NULL,Male,Caucasian,07/31/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +60798,76565,69310,PRETRIAL,Zukowski,Henry,NULL,Male,Caucasian,07/31/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +60798,76565,69310,PRETRIAL,Zukowski,Henry,NULL,Male,Caucasian,07/31/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +66126,76558,69304,PRETRIAL,HENDY,MICHAEL,NULL,Male,Hispanic,02/18/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +66126,76558,69304,PRETRIAL,HENDY,MICHAEL,NULL,Male,Hispanic,02/18/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +66126,76558,69304,PRETRIAL,HENDY,MICHAEL,NULL,Male,Hispanic,02/18/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58579,76567,69312,PRETRIAL,Raiche,Marc,NULL,Male,Caucasian,10/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/10/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +58579,76567,69312,PRETRIAL,Raiche,Marc,NULL,Male,Caucasian,10/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/10/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +58579,76567,69312,PRETRIAL,Raiche,Marc,NULL,Male,Caucasian,10/19/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66116,76546,69292,PRETRIAL,Smith,Shannon,NULL,Male,Caucasian,10/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +66116,76546,69292,PRETRIAL,Smith,Shannon,NULL,Male,Caucasian,10/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +66116,76546,69292,PRETRIAL,Smith,Shannon,NULL,Male,Caucasian,10/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66127,76560,69305,Probation,Shippe,Charles,NULL,Male,Caucasian,11/12/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +66127,76560,69305,Probation,Shippe,Charles,NULL,Male,Caucasian,11/12/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +66127,76560,69305,Probation,Shippe,Charles,NULL,Male,Caucasian,11/12/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64938,76543,69289,PRETRIAL,KEYES,RENAE,RESHON,Female,African-American,12/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.26,7,Medium,New,1,0 +64938,76543,69289,PRETRIAL,KEYES,RENAE,RESHON,Female,African-American,12/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,9,High,New,1,0 +64938,76543,69289,PRETRIAL,KEYES,RENAE,RESHON,Female,African-American,12/26/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +66115,76545,69291,PRETRIAL,Isaac,Deshawn,Robert,Male,African-American,04/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,2,Medium,7,Risk of Violence,-1.43,7,Medium,New,1,0 +66115,76545,69291,PRETRIAL,Isaac,Deshawn,Robert,Male,African-American,04/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +66115,76545,69291,PRETRIAL,Isaac,Deshawn,Robert,Male,African-American,04/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66121,76552,69298,Probation,Andre,Andrine,NULL,Female,African-American,01/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.06,4,Low,New,1,0 +66121,76552,69298,Probation,Andre,Andrine,NULL,Female,African-American,01/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,8,High,New,1,0 +66121,76552,69298,Probation,Andre,Andrine,NULL,Female,African-American,01/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66132,76566,69311,Probation,Dominquez,Guillermo,NULL,Male,Hispanic,04/20/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +66132,76566,69311,Probation,Dominquez,Guillermo,NULL,Male,Hispanic,04/20/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +66132,76566,69311,Probation,Dominquez,Guillermo,NULL,Male,Hispanic,04/20/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +65918,76559,69086,PRETRIAL,Shellman,Crystal,NULL,Female,African-American,06/25/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/10/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,Copy,1,0 +65918,76559,69086,PRETRIAL,Shellman,Crystal,NULL,Female,African-American,06/25/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/10/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,Copy,1,0 +65918,76559,69086,PRETRIAL,Shellman,Crystal,NULL,Female,African-American,06/25/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +66119,76550,69296,PRETRIAL,BENDOVA,MIREILLE,NULL,Female,Caucasian,02/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +66119,76550,69296,PRETRIAL,BENDOVA,MIREILLE,NULL,Female,Caucasian,02/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/14 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +66119,76550,69296,PRETRIAL,BENDOVA,MIREILLE,NULL,Female,Caucasian,02/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66131,76564,69309,Probation,Dixon,Jamia,Charita,Female,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/10/14 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,New,1,0 +66131,76564,69309,Probation,Dixon,Jamia,Charita,Female,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +66131,76564,69309,Probation,Dixon,Jamia,Charita,Female,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/10/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66117,76547,69293,PRETRIAL,Johnson,Ben,Clyde,Male,African-American,08/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/10/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +66117,76547,69293,PRETRIAL,Johnson,Ben,Clyde,Male,African-American,08/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/10/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +66117,76547,69293,PRETRIAL,Johnson,Ben,Clyde,Male,African-American,08/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66123,76554,69300,PRETRIAL,jackson,karin,NULL,Male,African-American,09/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +66123,76554,69300,PRETRIAL,jackson,karin,NULL,Male,African-American,09/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/14 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +66123,76554,69300,PRETRIAL,jackson,karin,NULL,Male,African-American,09/08/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66129,76562,69307,Probation,griffith,david,NULL,Male,Caucasian,10/23/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +66129,76562,69307,Probation,griffith,david,NULL,Male,Caucasian,10/23/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +66129,76562,69307,Probation,griffith,david,NULL,Male,Caucasian,10/23/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +31042,76549,69295,PRETRIAL,AIELLO,CHRISTOPHER,NULL,Male,Caucasian,02/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +31042,76549,69295,PRETRIAL,AIELLO,CHRISTOPHER,NULL,Male,Caucasian,02/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +31042,76549,69295,PRETRIAL,AIELLO,CHRISTOPHER,NULL,Male,Caucasian,02/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66125,76557,69303,Probation,GREENE,DONALD,NULL,Male,Caucasian,05/18/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/10/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +66125,76557,69303,Probation,GREENE,DONALD,NULL,Male,Caucasian,05/18/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/10/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +66125,76557,69303,Probation,GREENE,DONALD,NULL,Male,Caucasian,05/18/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66154,76591,69335,PRETRIAL,Whitney,Randall,NULL,Male,Caucasian,04/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/11/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +66154,76591,69335,PRETRIAL,Whitney,Randall,NULL,Male,Caucasian,04/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/11/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +66154,76591,69335,PRETRIAL,Whitney,Randall,NULL,Male,Caucasian,04/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66135,76570,69315,PRETRIAL,Taylor,Dwyth,NULL,Male,African-American,06/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +66135,76570,69315,PRETRIAL,Taylor,Dwyth,NULL,Male,African-American,06/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +66135,76570,69315,PRETRIAL,Taylor,Dwyth,NULL,Male,African-American,06/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66167,76604,69346,Probation,diaz,irenia,NULL,Female,Hispanic,10/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/11/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +66167,76604,69346,Probation,diaz,irenia,NULL,Female,Hispanic,10/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/11/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +66167,76604,69346,Probation,diaz,irenia,NULL,Female,Hispanic,10/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +3727,76599,3442,PRETRIAL,DAUB,CAREY,ROY,Male,Caucasian,07/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,Copy,1,0 +3727,76599,3442,PRETRIAL,DAUB,CAREY,ROY,Male,Caucasian,07/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.82,10,High,Copy,1,0 +3727,76599,3442,PRETRIAL,DAUB,CAREY,ROY,Male,Caucasian,07/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +66142,76578,69322,Probation,Tappa,Theodore,Richard,Male,Caucasian,10/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +66142,76578,69322,Probation,Tappa,Theodore,Richard,Male,Caucasian,10/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +66142,76578,69322,Probation,Tappa,Theodore,Richard,Male,Caucasian,10/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,35,10,High,New,1,0 +66160,76596,69340,Probation,JACKSON,ROBERT,EARL,Male,Caucasian,04/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/11/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +66160,76596,69340,Probation,JACKSON,ROBERT,EARL,Male,Caucasian,04/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/11/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +66160,76596,69340,Probation,JACKSON,ROBERT,EARL,Male,Caucasian,04/03/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66140,76575,69320,PRETRIAL,Black,Adena,NULL,Female,African-American,02/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +66140,76575,69320,PRETRIAL,Black,Adena,NULL,Female,African-American,02/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +66140,76575,69320,PRETRIAL,Black,Adena,NULL,Female,African-American,02/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66133,76568,69313,PRETRIAL,Cloeman,Lorenzo,NULL,Male,African-American,07/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.53,1,Low,New,1,0 +66133,76568,69313,PRETRIAL,Cloeman,Lorenzo,NULL,Male,African-American,07/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +66133,76568,69313,PRETRIAL,Cloeman,Lorenzo,NULL,Male,African-American,07/27/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66136,76571,69316,PRETRIAL,Mattis,Kirk,Clive,Male,African-American,11/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +66136,76571,69316,PRETRIAL,Mattis,Kirk,Clive,Male,African-American,11/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +66136,76571,69316,PRETRIAL,Mattis,Kirk,Clive,Male,African-American,11/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66150,76585,69329,PRETRIAL,Brown,Lashawn,M,Female,African-American,12/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +66150,76585,69329,PRETRIAL,Brown,Lashawn,M,Female,African-American,12/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +66150,76585,69329,PRETRIAL,Brown,Lashawn,M,Female,African-American,12/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +52903,76589,69333,PRETRIAL,Harris,Reginald,NULL,Male,African-American,08/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.08,8,High,New,1,0 +52903,76589,69333,PRETRIAL,Harris,Reginald,NULL,Male,African-American,08/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +52903,76589,69333,PRETRIAL,Harris,Reginald,NULL,Male,African-American,08/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57972,76610,69352,PRETRIAL,Hecht,Robert,NULL,Male,Caucasian,07/14/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +57972,76610,69352,PRETRIAL,Hecht,Robert,NULL,Male,Caucasian,07/14/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +57972,76610,69352,PRETRIAL,Hecht,Robert,NULL,Male,Caucasian,07/14/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66169,76606,69348,Probation,Arana Florez,Mauricio,NULL,Male,Hispanic,03/23/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/11/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +66169,76606,69348,Probation,Arana Florez,Mauricio,NULL,Male,Hispanic,03/23/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/11/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +66169,76606,69348,Probation,Arana Florez,Mauricio,NULL,Male,Hispanic,03/23/72,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66141,76601,69321,PRETRIAL,SPENCE,TIERRA,NULL,Female,African-American,01/27/96,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,4,High,7,Risk of Violence,-0.72,9,High,New,1,0 +66141,76601,69321,PRETRIAL,SPENCE,TIERRA,NULL,Female,African-American,01/27/96,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,4,High,8,Risk of Recidivism,0.32,9,High,New,1,0 +66141,76601,69321,PRETRIAL,SPENCE,TIERRA,NULL,Female,African-American,01/27/96,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66145,76580,69324,Probation,Auguste,Samuel,NULL,Male,African-American,05/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +66145,76580,69324,Probation,Auguste,Samuel,NULL,Male,African-American,05/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +66145,76580,69324,Probation,Auguste,Samuel,NULL,Male,African-American,05/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66152,76587,69331,Probation,Jackson,Kenyatta,NULL,Male,African-American,03/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/11/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +66152,76587,69331,Probation,Jackson,Kenyatta,NULL,Male,African-American,03/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/11/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +66152,76587,69331,Probation,Jackson,Kenyatta,NULL,Male,African-American,03/09/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66158,76594,69338,PRETRIAL,PRITCHARD,NICK,NULL,Male,Caucasian,02/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/11/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +66158,76594,69338,PRETRIAL,PRITCHARD,NICK,NULL,Male,Caucasian,02/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/11/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +66158,76594,69338,PRETRIAL,PRITCHARD,NICK,NULL,Male,Caucasian,02/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66138,76573,69318,PRETRIAL,ROGER,JONTIRIA,DESIRA,Female,African-American,03/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +66138,76573,69318,PRETRIAL,ROGER,JONTIRIA,DESIRA,Female,African-American,03/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +66138,76573,69318,PRETRIAL,ROGER,JONTIRIA,DESIRA,Female,African-American,03/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66137,76572,69317,PRETRIAL,SALGADO,MONICA,NAOMI,Female,Caucasian,11/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +66137,76572,69317,PRETRIAL,SALGADO,MONICA,NAOMI,Female,Caucasian,11/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +66137,76572,69317,PRETRIAL,SALGADO,MONICA,NAOMI,Female,Caucasian,11/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66165,76602,69344,Probation,Hyndan,Leslie,NULL,Female,Caucasian,08/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +66165,76602,69344,Probation,Hyndan,Leslie,NULL,Female,Caucasian,08/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,9,High,New,1,0 +66165,76602,69344,Probation,Hyndan,Leslie,NULL,Female,Caucasian,08/19/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66157,76593,69337,PRETRIAL,ridges,debrcca,NULL,Female,African-American,01/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,2,Medium,7,Risk of Violence,-2.75,2,Low,New,1,0 +66157,76593,69337,PRETRIAL,ridges,debrcca,NULL,Female,African-American,01/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +66157,76593,69337,PRETRIAL,ridges,debrcca,NULL,Female,African-American,01/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66171,76607,69349,Probation,SIMMONS,KATIE,NULL,Female,Caucasian,11/02/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/11/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +66171,76607,69349,Probation,SIMMONS,KATIE,NULL,Female,Caucasian,11/02/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/11/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +66171,76607,69349,Probation,SIMMONS,KATIE,NULL,Female,Caucasian,11/02/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66172,76609,69351,Probation,Eide,Michael,NULL,Male,Hispanic,07/23/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-4.21,1,Low,New,1,0 +66172,76609,69351,Probation,Eide,Michael,NULL,Male,Hispanic,07/23/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +66172,76609,69351,Probation,Eide,Michael,NULL,Male,Hispanic,07/23/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66144,76579,69323,Probation,BERGER,BRANDON,ANTHONY,Male,Hispanic,01/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +66144,76579,69323,Probation,BERGER,BRANDON,ANTHONY,Male,Hispanic,01/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +66144,76579,69323,Probation,BERGER,BRANDON,ANTHONY,Male,Hispanic,01/30/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66151,76586,69330,Probation,Johnson,Lamont,Deondrick,Male,African-American,04/15/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +66151,76586,69330,Probation,Johnson,Lamont,Deondrick,Male,African-American,04/15/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +66151,76586,69330,Probation,Johnson,Lamont,Deondrick,Male,African-American,04/15/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65961,76588,69332,DRRD,Johnson,Rickeya,Cheria,Female,African-American,06/04/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +65961,76588,69332,DRRD,Johnson,Rickeya,Cheria,Female,African-American,06/04/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +65961,76588,69332,DRRD,Johnson,Rickeya,Cheria,Female,African-American,06/04/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66159,76595,69339,Probation,Beal,Blake,NULL,Male,African-American,12/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +66159,76595,69339,Probation,Beal,Blake,NULL,Male,African-American,12/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +66159,76595,69339,Probation,Beal,Blake,NULL,Male,African-American,12/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66139,76574,69319,PRETRIAL,STANLEY,BRION,ANTHONY,Male,African-American,05/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/11/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +66139,76574,69319,PRETRIAL,STANLEY,BRION,ANTHONY,Male,African-American,05/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/11/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +66139,76574,69319,PRETRIAL,STANLEY,BRION,ANTHONY,Male,African-American,05/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66166,76603,69345,PRETRIAL,Murray,Andrew,NULL,Male,Caucasian,09/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +66166,76603,69345,PRETRIAL,Murray,Andrew,NULL,Male,Caucasian,09/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +66166,76603,69345,PRETRIAL,Murray,Andrew,NULL,Male,Caucasian,09/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66147,76582,69326,Probation,jones,altaniece,NULL,Female,African-American,03/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +66147,76582,69326,Probation,jones,altaniece,NULL,Female,African-American,03/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +66147,76582,69326,Probation,jones,altaniece,NULL,Female,African-American,03/31/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66153,76590,69334,PRETRIAL,BONHAM,BRIAN,NULL,Male,Caucasian,07/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/11/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +66153,76590,69334,PRETRIAL,BONHAM,BRIAN,NULL,Male,Caucasian,07/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/11/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +66153,76590,69334,PRETRIAL,BONHAM,BRIAN,NULL,Male,Caucasian,07/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66155,76592,69336,PRETRIAL,SANTOS,NICHOLAS,NOAH,Male,African-American,09/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +66155,76592,69336,PRETRIAL,SANTOS,NICHOLAS,NOAH,Male,African-American,09/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +66155,76592,69336,PRETRIAL,SANTOS,NICHOLAS,NOAH,Male,African-American,09/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66141,76577,69321,PRETRIAL,SPENCE,TIERRA,NULL,Female,African-American,01/27/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +66141,76577,69321,PRETRIAL,SPENCE,TIERRA,NULL,Female,African-American,01/27/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,4,High,8,Risk of Recidivism,0.22,9,High,New,1,0 +66141,76577,69321,PRETRIAL,SPENCE,TIERRA,NULL,Female,African-American,01/27/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66174,76611,69353,PRETRIAL,DUCAMEL,HENRY,NULL,Male,African-American,10/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +66174,76611,69353,PRETRIAL,DUCAMEL,HENRY,NULL,Male,African-American,10/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +66174,76611,69353,PRETRIAL,DUCAMEL,HENRY,NULL,Male,African-American,10/07/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66149,76584,69328,PRETRIAL,Moore,Julius,NULL,Male,African-American,01/13/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +66149,76584,69328,PRETRIAL,Moore,Julius,NULL,Male,African-American,01/13/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +66149,76584,69328,PRETRIAL,Moore,Julius,NULL,Male,African-American,01/13/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +66163,76598,69342,Probation,estrada,victor,NULL,Male,Hispanic,03/20/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,7,Risk of Violence,-4.52,1,Low,New,1,0 +66163,76598,69342,Probation,estrada,victor,NULL,Male,Hispanic,03/20/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,8,Risk of Recidivism,-2.66,1,Low,New,1,0 +66163,76598,69342,Probation,estrada,victor,NULL,Male,Hispanic,03/20/43,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66134,76569,69314,PRETRIAL,Hardy,Jeremy,Christophe,Male,African-American,07/17/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,4,High,7,Risk of Violence,-0.92,9,High,New,1,0 +66134,76569,69314,PRETRIAL,Hardy,Jeremy,Christophe,Male,African-American,07/17/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +66134,76569,69314,PRETRIAL,Hardy,Jeremy,Christophe,Male,African-American,07/17/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/11/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66168,76605,69347,Probation,KATZ,CATHY,LYNN,Female,Caucasian,04/25/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/11/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +66168,76605,69347,Probation,KATZ,CATHY,LYNN,Female,Caucasian,04/25/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/11/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +66168,76605,69347,Probation,KATZ,CATHY,LYNN,Female,Caucasian,04/25/52,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66180,76619,69361,PRETRIAL,Dacunha,Emerson,Daniel,Male,Caucasian,07/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +66180,76619,69361,PRETRIAL,Dacunha,Emerson,Daniel,Male,Caucasian,07/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +66180,76619,69361,PRETRIAL,Dacunha,Emerson,Daniel,Male,Caucasian,07/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66191,76634,69374,Probation,Gabriel,Brian,NULL,Male,African-American,09/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +66191,76634,69374,Probation,Gabriel,Brian,NULL,Male,African-American,09/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +66191,76634,69374,Probation,Gabriel,Brian,NULL,Male,African-American,09/08/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,1,Low,18,Risk of Failure to Appear,38,10,High,New,1,0 +66185,76626,69367,Probation,keough,john,NULL,Male,Caucasian,12/19/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/12/14 0:00,2,Medium,7,Risk of Violence,-3.09,1,Low,New,1,0 +66185,76626,69367,Probation,keough,john,NULL,Male,Caucasian,12/19/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/12/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +66185,76626,69367,Probation,keough,john,NULL,Male,Caucasian,12/19/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/12/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +66181,76621,69363,PRETRIAL,Garcia,Joaquin,NULL,Male,Hispanic,12/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,New,1,0 +66181,76621,69363,PRETRIAL,Garcia,Joaquin,NULL,Male,Hispanic,12/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +66181,76621,69363,PRETRIAL,Garcia,Joaquin,NULL,Male,Hispanic,12/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66187,76629,69370,PRETRIAL,GUTIERREZ,MARCELLA,NULL,Female,Caucasian,07/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.18,8,High,New,1,0 +66187,76629,69370,PRETRIAL,GUTIERREZ,MARCELLA,NULL,Female,Caucasian,07/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +66187,76629,69370,PRETRIAL,GUTIERREZ,MARCELLA,NULL,Female,Caucasian,07/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66178,76616,69358,PRETRIAL,Brockman,Willie,Lawrence,Male,African-American,08/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/14 0:00,4,High,7,Risk of Violence,-0.89,9,High,New,1,0 +66178,76616,69358,PRETRIAL,Brockman,Willie,Lawrence,Male,African-American,08/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/14 0:00,4,High,8,Risk of Recidivism,0.28,8,High,New,1,0 +66178,76616,69358,PRETRIAL,Brockman,Willie,Lawrence,Male,African-American,08/11/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/12/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +34020,76630,33148,PRETRIAL,EXCELLENT,STEVE,NULL,Male,African-American,09/28/91,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,4,High,7,Risk of Violence,-1.06,8,High,Copy,1,0 +34020,76630,33148,PRETRIAL,EXCELLENT,STEVE,NULL,Male,African-American,09/28/91,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,4,High,8,Risk of Recidivism,0.54,9,High,Copy,1,0 +34020,76630,33148,PRETRIAL,EXCELLENT,STEVE,NULL,Male,African-American,09/28/91,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +66194,76637,69377,Probation,BUENO,ALEX,DANIEL,Male,Hispanic,11/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +66194,76637,69377,Probation,BUENO,ALEX,DANIEL,Male,Hispanic,11/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +66194,76637,69377,Probation,BUENO,ALEX,DANIEL,Male,Hispanic,11/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60500,76623,62940,PRETRIAL,TREJOS,GEISON,NULL,Male,Hispanic,02/29/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.59,10,High,New,1,0 +60500,76623,62940,PRETRIAL,TREJOS,GEISON,NULL,Male,Hispanic,02/29/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,7,Medium,New,1,0 +60500,76623,62940,PRETRIAL,TREJOS,GEISON,NULL,Male,Hispanic,02/29/96,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +47393,52657,47943,PRETRIAL,HENRY,TOYA,NULL,Female,African-American,05/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,4,High,7,Risk of Violence,-0.33,10,High,New,1,0 +47393,52657,47943,PRETRIAL,HENRY,TOYA,NULL,Female,African-American,05/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,4,High,8,Risk of Recidivism,0.23,9,High,New,1,0 +47393,52657,47943,PRETRIAL,HENRY,TOYA,NULL,Female,African-American,05/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63124,76614,69356,Probation,owens,nathaniel,NULL,Male,African-American,07/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +63124,76614,69356,Probation,owens,nathaniel,NULL,Male,African-American,07/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +63124,76614,69356,Probation,owens,nathaniel,NULL,Male,African-American,07/24/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +66186,76628,69369,PRETRIAL,Palacious,Jerard,NULL,Male,African-American,11/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +66186,76628,69369,PRETRIAL,Palacious,Jerard,NULL,Male,African-American,11/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +66186,76628,69369,PRETRIAL,Palacious,Jerard,NULL,Male,African-American,11/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66179,76618,69360,PRETRIAL,Dumond,Tuwana,NULL,Female,African-American,09/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +66179,76618,69360,PRETRIAL,Dumond,Tuwana,NULL,Female,African-American,09/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +66179,76618,69360,PRETRIAL,Dumond,Tuwana,NULL,Female,African-American,09/28/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66189,76632,69372,PRETRIAL,OROZCO,LAZARO,NULL,Male,Caucasian,12/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +66189,76632,69372,PRETRIAL,OROZCO,LAZARO,NULL,Male,Caucasian,12/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +66189,76632,69372,PRETRIAL,OROZCO,LAZARO,NULL,Male,Caucasian,12/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66192,76635,69375,PRETRIAL,Watson,Robert,NULL,Male,African-American,02/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +66192,76635,69375,PRETRIAL,Watson,Robert,NULL,Male,African-American,02/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +66192,76635,69375,PRETRIAL,Watson,Robert,NULL,Male,African-American,02/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66183,76624,69365,Probation,WILSON,JAMES,FRANKLIN,Male,African-American,03/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +66183,76624,69365,Probation,WILSON,JAMES,FRANKLIN,Male,African-American,03/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +66183,76624,69365,Probation,WILSON,JAMES,FRANKLIN,Male,African-American,03/01/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66182,76622,69364,Probation,Trainer,David,NULL,Male,Caucasian,10/03/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/12/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +66182,76622,69364,Probation,Trainer,David,NULL,Male,Caucasian,10/03/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/12/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +66182,76622,69364,Probation,Trainer,David,NULL,Male,Caucasian,10/03/64,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66177,76615,69357,PRETRIAL,Crawford,Lamar,NULL,Male,African-American,12/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.66,2,Low,New,1,0 +66177,76615,69357,PRETRIAL,Crawford,Lamar,NULL,Male,African-American,12/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +66177,76615,69357,PRETRIAL,Crawford,Lamar,NULL,Male,African-American,12/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +51536,76627,69368,Probation,Comarcho,Kyle,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +51536,76627,69368,Probation,Comarcho,Kyle,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +51536,76627,69368,Probation,Comarcho,Kyle,NULL,Male,African-American,02/24/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66193,76636,69376,PRETRIAL,Brooks,Thomas,NULL,Male,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +66193,76636,69376,PRETRIAL,Brooks,Thomas,NULL,Male,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +66193,76636,69376,PRETRIAL,Brooks,Thomas,NULL,Male,Caucasian,04/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/12/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66188,76631,69371,Probation,Pacheco,Walter,Oswald,Male,Hispanic,12/07/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/12/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +66188,76631,69371,Probation,Pacheco,Walter,Oswald,Male,Hispanic,12/07/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/12/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +66188,76631,69371,Probation,Pacheco,Walter,Oswald,Male,Hispanic,12/07/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/12/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +5797,76620,69362,PRETRIAL,CHARLEMAGNE,DASAHEV,NULL,Male,African-American,09/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +5797,76620,69362,PRETRIAL,CHARLEMAGNE,DASAHEV,NULL,Male,African-American,09/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +5797,76620,69362,PRETRIAL,CHARLEMAGNE,DASAHEV,NULL,Male,African-American,09/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +48595,76617,69359,PRETRIAL,Brantley,Brittany,Yvette,Female,African-American,06/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +48595,76617,69359,PRETRIAL,Brantley,Brittany,Yvette,Female,African-American,06/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,10,High,New,1,0 +48595,76617,69359,PRETRIAL,Brantley,Brittany,Yvette,Female,African-American,06/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65224,76638,68299,Probation,steller,stephanie,NULL,Female,Caucasian,12/20/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,4,High,7,Risk of Violence,-1.14,8,High,New,1,0 +65224,76638,68299,Probation,steller,stephanie,NULL,Female,Caucasian,12/20/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,4,High,8,Risk of Recidivism,0.8,10,High,New,1,0 +65224,76638,68299,Probation,steller,stephanie,NULL,Female,Caucasian,12/20/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/12/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66184,76625,69366,Probation,Allen,Jamsie,NULL,Female,African-American,05/11/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +66184,76625,69366,Probation,Allen,Jamsie,NULL,Female,African-American,05/11/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/14 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +66184,76625,69366,Probation,Allen,Jamsie,NULL,Female,African-American,05/11/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +9585,76646,69385,PRETRIAL,terrell,travers,NULL,Male,African-American,10/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.21,4,Low,New,1,0 +9585,76646,69385,PRETRIAL,terrell,travers,NULL,Male,African-American,10/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +9585,76646,69385,PRETRIAL,terrell,travers,NULL,Male,African-American,10/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66197,76641,69380,PRETRIAL,GASSETT,JEREMY,NULL,Male,African-American,08/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +66197,76641,69380,PRETRIAL,GASSETT,JEREMY,NULL,Male,African-American,08/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +66197,76641,69380,PRETRIAL,GASSETT,JEREMY,NULL,Male,African-American,08/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66203,76648,69387,PRETRIAL,Smith,Christopher,Rafael,Male,African-American,10/16/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +66203,76648,69387,PRETRIAL,Smith,Christopher,Rafael,Male,African-American,10/16/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +66203,76648,69387,PRETRIAL,Smith,Christopher,Rafael,Male,African-American,10/16/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66196,76640,69379,PRETRIAL,Brezina,Margaret,NULL,Female,Asian,12/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/13/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +66196,76640,69379,PRETRIAL,Brezina,Margaret,NULL,Female,Asian,12/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/13/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +66196,76640,69379,PRETRIAL,Brezina,Margaret,NULL,Female,Asian,12/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/13/14 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +66201,76645,69384,PRETRIAL,Gutierrez,Kassandra,NULL,Female,Hispanic,03/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +66201,76645,69384,PRETRIAL,Gutierrez,Kassandra,NULL,Female,Hispanic,03/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +66201,76645,69384,PRETRIAL,Gutierrez,Kassandra,NULL,Female,Hispanic,03/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66198,76643,69382,PRETRIAL,Blake,Jeremy,NULL,Male,African-American,12/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +66198,76643,69382,PRETRIAL,Blake,Jeremy,NULL,Male,African-American,12/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +66198,76643,69382,PRETRIAL,Blake,Jeremy,NULL,Male,African-American,12/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +39475,76649,38995,PRETRIAL,Clark,Scott,NULL,Male,Caucasian,01/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,Copy,1,0 +39475,76649,38995,PRETRIAL,Clark,Scott,NULL,Male,Caucasian,01/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,Copy,1,0 +39475,76649,38995,PRETRIAL,Clark,Scott,NULL,Male,Caucasian,01/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +66195,76639,69378,PRETRIAL,Gonzalez,Gabriel,NULL,Male,Hispanic,02/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +66195,76639,69378,PRETRIAL,Gonzalez,Gabriel,NULL,Male,Hispanic,02/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +66195,76639,69378,PRETRIAL,Gonzalez,Gabriel,NULL,Male,Hispanic,02/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66200,76644,69383,PRETRIAL,GARCIA-HEINTSKILL,LISA,ANN,Female,Caucasian,11/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/13/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +66200,76644,69383,PRETRIAL,GARCIA-HEINTSKILL,LISA,ANN,Female,Caucasian,11/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/13/14 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +66200,76644,69383,PRETRIAL,GARCIA-HEINTSKILL,LISA,ANN,Female,Caucasian,11/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66199,76642,69381,PRETRIAL,Hormaeche,Anthony,NULL,Male,Caucasian,06/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +66199,76642,69381,PRETRIAL,Hormaeche,Anthony,NULL,Male,Caucasian,06/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +66199,76642,69381,PRETRIAL,Hormaeche,Anthony,NULL,Male,Caucasian,06/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66202,76647,69386,PRETRIAL,Lester,Okemaya,NULL,Male,African-American,07/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +66202,76647,69386,PRETRIAL,Lester,Okemaya,NULL,Male,African-American,07/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +66202,76647,69386,PRETRIAL,Lester,Okemaya,NULL,Male,African-American,07/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +13057,76655,12495,PRETRIAL,JACKSON,TRACY,LAKIM,Female,African-American,10/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,Copy,1,0 +13057,76655,12495,PRETRIAL,JACKSON,TRACY,LAKIM,Female,African-American,10/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,9,High,Copy,1,0 +13057,76655,12495,PRETRIAL,JACKSON,TRACY,LAKIM,Female,African-American,10/04/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +66215,76663,69400,PRETRIAL,OSCEOLA,AUDREY,NULL,Female,Native American,02/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +66215,76663,69400,PRETRIAL,OSCEOLA,AUDREY,NULL,Female,Native American,02/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +66215,76663,69400,PRETRIAL,OSCEOLA,AUDREY,NULL,Female,Native American,02/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57247,76650,69388,PRETRIAL,TRAMUN,JERMAINE,NULL,Male,African-American,01/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/14/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +57247,76650,69388,PRETRIAL,TRAMUN,JERMAINE,NULL,Male,African-American,01/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/14/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +57247,76650,69388,PRETRIAL,TRAMUN,JERMAINE,NULL,Male,African-American,01/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +8910,76668,69404,PRETRIAL,GIARD,SAMUEL,WILLIAM,Male,Caucasian,05/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +8910,76668,69404,PRETRIAL,GIARD,SAMUEL,WILLIAM,Male,Caucasian,05/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +8910,76668,69404,PRETRIAL,GIARD,SAMUEL,WILLIAM,Male,Caucasian,05/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66204,76651,69389,PRETRIAL,Anderson,Elvis,NULL,Male,Other,05/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +66204,76651,69389,PRETRIAL,Anderson,Elvis,NULL,Male,Other,05/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +66204,76651,69389,PRETRIAL,Anderson,Elvis,NULL,Male,Other,05/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66217,76665,69402,PRETRIAL,Gillespie,Dallas,Alexander,Male,African-American,01/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/14/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +66217,76665,69402,PRETRIAL,Gillespie,Dallas,Alexander,Male,African-American,01/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/14/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +66217,76665,69402,PRETRIAL,Gillespie,Dallas,Alexander,Male,African-American,01/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66210,76658,69395,PRETRIAL,PEREYRA,EMMANUEL,NULL,Male,Hispanic,02/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +66210,76658,69395,PRETRIAL,PEREYRA,EMMANUEL,NULL,Male,Hispanic,02/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +66210,76658,69395,PRETRIAL,PEREYRA,EMMANUEL,NULL,Male,Hispanic,02/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66212,76660,69397,PRETRIAL,DESMANDES,CLEVENS,ST LOT,Male,Other,06/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +66212,76660,69397,PRETRIAL,DESMANDES,CLEVENS,ST LOT,Male,Other,06/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +66212,76660,69397,PRETRIAL,DESMANDES,CLEVENS,ST LOT,Male,Other,06/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66206,76653,69391,PRETRIAL,ARMBEITER,RASHAD,BRANDELL,Male,Other,10/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +66206,76653,69391,PRETRIAL,ARMBEITER,RASHAD,BRANDELL,Male,Other,10/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +66206,76653,69391,PRETRIAL,ARMBEITER,RASHAD,BRANDELL,Male,Other,10/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66205,76652,69390,PRETRIAL,Centeno,Evelyn,NULL,Female,Hispanic,11/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +66205,76652,69390,PRETRIAL,Centeno,Evelyn,NULL,Female,Hispanic,11/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +66205,76652,69390,PRETRIAL,Centeno,Evelyn,NULL,Female,Hispanic,11/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +40657,76666,40283,PRETRIAL,Ramos,Igor,Adrian,Male,Caucasian,05/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/14/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,Copy,1,0 +40657,76666,40283,PRETRIAL,Ramos,Igor,Adrian,Male,Caucasian,05/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/14/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,Copy,1,0 +40657,76666,40283,PRETRIAL,Ramos,Igor,Adrian,Male,Caucasian,05/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +66209,76657,69394,PRETRIAL,MCKENNEY,CAMEO,NULL,Male,African-American,10/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +66209,76657,69394,PRETRIAL,MCKENNEY,CAMEO,NULL,Male,African-American,10/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +66209,76657,69394,PRETRIAL,MCKENNEY,CAMEO,NULL,Male,African-American,10/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66213,76661,69398,PRETRIAL,Black,Walter,NULL,Male,African-American,04/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +66213,76661,69398,PRETRIAL,Black,Walter,NULL,Male,African-American,04/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +66213,76661,69398,PRETRIAL,Black,Walter,NULL,Male,African-American,04/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +40657,44075,40283,PRETRIAL,Ramos,Igor,Adrian,Male,Caucasian,05/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/14/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +40657,44075,40283,PRETRIAL,Ramos,Igor,Adrian,Male,Caucasian,05/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/14/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +40657,44075,40283,PRETRIAL,Ramos,Igor,Adrian,Male,Caucasian,05/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66214,76662,69399,PRETRIAL,WIGGINS,CODY,LEON,Male,Caucasian,02/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +66214,76662,69399,PRETRIAL,WIGGINS,CODY,LEON,Male,Caucasian,02/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +66214,76662,69399,PRETRIAL,WIGGINS,CODY,LEON,Male,Caucasian,02/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66208,76656,69393,PRETRIAL,CRUZ,STEVEN,JOSEPH,Male,African-American,03/22/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +66208,76656,69393,PRETRIAL,CRUZ,STEVEN,JOSEPH,Male,African-American,03/22/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +66208,76656,69393,PRETRIAL,CRUZ,STEVEN,JOSEPH,Male,African-American,03/22/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,33,9,High,New,1,0 +66207,76654,69392,PRETRIAL,JOSEPH,MIGUELSON,NULL,Male,Other,01/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +66207,76654,69392,PRETRIAL,JOSEPH,MIGUELSON,NULL,Male,Other,01/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +66207,76654,69392,PRETRIAL,JOSEPH,MIGUELSON,NULL,Male,Other,01/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66216,76664,69401,PRETRIAL,Felder,Treasa,NULL,Female,African-American,04/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +66216,76664,69401,PRETRIAL,Felder,Treasa,NULL,Female,African-American,04/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,8,High,New,1,0 +66216,76664,69401,PRETRIAL,Felder,Treasa,NULL,Female,African-American,04/23/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +66218,76667,69403,PRETRIAL,Baron,Jessica,Carmen,Female,Caucasian,07/15/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/14/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +66218,76667,69403,PRETRIAL,Baron,Jessica,Carmen,Female,Caucasian,07/15/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/14/14 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +66218,76667,69403,PRETRIAL,Baron,Jessica,Carmen,Female,Caucasian,07/15/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66211,76659,69396,PRETRIAL,Figueroa,Jason,NULL,Male,Hispanic,09/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +66211,76659,69396,PRETRIAL,Figueroa,Jason,NULL,Male,Hispanic,09/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +66211,76659,69396,PRETRIAL,Figueroa,Jason,NULL,Male,Hispanic,09/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66238,76693,69428,PRETRIAL,Lawrence,Tafari,Shaile,Male,African-American,10/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +66238,76693,69428,PRETRIAL,Lawrence,Tafari,Shaile,Male,African-American,10/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +66238,76693,69428,PRETRIAL,Lawrence,Tafari,Shaile,Male,African-American,10/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66221,76672,69408,PRETRIAL,RUCKER,FREDRICK,CLAYTON,Male,African-American,10/02/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +66221,76672,69408,PRETRIAL,RUCKER,FREDRICK,CLAYTON,Male,African-American,10/02/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +66221,76672,69408,PRETRIAL,RUCKER,FREDRICK,CLAYTON,Male,African-American,10/02/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66233,76685,69421,Probation,Serrano,Luis,NULL,Male,Hispanic,07/31/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +66233,76685,69421,Probation,Serrano,Luis,NULL,Male,Hispanic,07/31/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +66233,76685,69421,Probation,Serrano,Luis,NULL,Male,Hispanic,07/31/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66226,76677,69413,PRETRIAL,Nentwick,Christopher,Eric,Male,Caucasian,05/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +66226,76677,69413,PRETRIAL,Nentwick,Christopher,Eric,Male,Caucasian,05/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +66226,76677,69413,PRETRIAL,Nentwick,Christopher,Eric,Male,Caucasian,05/09/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66224,76675,69411,PRETRIAL,PARKER,STEPHEN,DOUGLAS,Male,Caucasian,08/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/15/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +66224,76675,69411,PRETRIAL,PARKER,STEPHEN,DOUGLAS,Male,Caucasian,08/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +66224,76675,69411,PRETRIAL,PARKER,STEPHEN,DOUGLAS,Male,Caucasian,08/23/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66237,76690,69425,Probation,Grimes,Ivan,NULL,Male,African-American,12/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/15/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +66237,76690,69425,Probation,Grimes,Ivan,NULL,Male,African-American,12/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +66237,76690,69425,Probation,Grimes,Ivan,NULL,Male,African-American,12/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +41900,76669,69405,PRETRIAL,Espinoza,Richard,NULL,Male,Caucasian,10/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +41900,76669,69405,PRETRIAL,Espinoza,Richard,NULL,Male,Caucasian,10/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +41900,76669,69405,PRETRIAL,Espinoza,Richard,NULL,Male,Caucasian,10/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66231,76683,69419,PRETRIAL,Tedlock,Dallas,NULL,Female,Caucasian,01/21/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,9/15/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +66231,76683,69419,PRETRIAL,Tedlock,Dallas,NULL,Female,Caucasian,01/21/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,9/15/14 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +66231,76683,69419,PRETRIAL,Tedlock,Dallas,NULL,Female,Caucasian,01/21/60,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66244,76698,69433,Probation,KUTNER,RAYMOND,NULL,Male,Caucasian,10/08/38,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-4.66,1,Low,New,1,0 +66244,76698,69433,Probation,KUTNER,RAYMOND,NULL,Male,Caucasian,10/08/38,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-2.63,1,Low,New,1,0 +66244,76698,69433,Probation,KUTNER,RAYMOND,NULL,Male,Caucasian,10/08/38,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +25399,76682,69418,Probation,CARBAJAL,JOSE,A,Male,Hispanic,05/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/15/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +25399,76682,69418,Probation,CARBAJAL,JOSE,A,Male,Hispanic,05/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/15/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +25399,76682,69418,Probation,CARBAJAL,JOSE,A,Male,Hispanic,05/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66227,76678,69414,PRETRIAL,Hye,Thomas,NULL,Male,African-American,07/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +66227,76678,69414,PRETRIAL,Hye,Thomas,NULL,Male,African-American,07/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +66227,76678,69414,PRETRIAL,Hye,Thomas,NULL,Male,African-American,07/07/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66242,76696,69431,Probation,robillard,Karina,NULL,Female,Hispanic,12/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/15/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +66242,76696,69431,Probation,robillard,Karina,NULL,Female,Hispanic,12/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/15/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +66242,76696,69431,Probation,robillard,Karina,NULL,Female,Hispanic,12/09/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66248,76703,69438,Probation,Vela,Iris,NULL,Female,Hispanic,03/10/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/15/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +66248,76703,69438,Probation,Vela,Iris,NULL,Female,Hispanic,03/10/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/15/14 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +66248,76703,69438,Probation,Vela,Iris,NULL,Female,Hispanic,03/10/65,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66253,76708,69443,Probation,Lasseter,Felicia,Sherree,Female,Caucasian,04/18/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/15/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +66253,76708,69443,Probation,Lasseter,Felicia,Sherree,Female,Caucasian,04/18/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/15/14 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +66253,76708,69443,Probation,Lasseter,Felicia,Sherree,Female,Caucasian,04/18/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66247,76701,69436,PRETRIAL,Sainvil,Nathalie,NULL,Female,African-American,04/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +66247,76701,69436,PRETRIAL,Sainvil,Nathalie,NULL,Female,African-American,04/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +66247,76701,69436,PRETRIAL,Sainvil,Nathalie,NULL,Female,African-American,04/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66229,76680,69416,Probation,Torres,Dylan,Anderson,Male,Hispanic,02/22/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/15/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +66229,76680,69416,Probation,Torres,Dylan,Anderson,Male,Hispanic,02/22/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +66229,76680,69416,Probation,Torres,Dylan,Anderson,Male,Hispanic,02/22/92,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/15/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66235,76687,69423,Probation,SZAFRAN,JASON,ROBERT,Male,Caucasian,05/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +66235,76687,69423,Probation,SZAFRAN,JASON,ROBERT,Male,Caucasian,05/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +66235,76687,69423,Probation,SZAFRAN,JASON,ROBERT,Male,Caucasian,05/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66240,76694,69429,DRRD,Christmas,Christina,Ashley,Male,Caucasian,11/18/87,17,All Scales,Intake,English,Probation Violator,Probation,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +66240,76694,69429,DRRD,Christmas,Christina,Ashley,Male,Caucasian,11/18/87,17,All Scales,Intake,English,Probation Violator,Probation,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-0.63,3,Low,New,1,0 +66240,76694,69429,DRRD,Christmas,Christina,Ashley,Male,Caucasian,11/18/87,17,All Scales,Intake,English,Probation Violator,Probation,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +66222,76673,69409,PRETRIAL,MCCARNAN,KENNETH,JOHN,Male,Caucasian,04/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,4,High,7,Risk of Violence,-1.09,8,High,New,1,0 +66222,76673,69409,PRETRIAL,MCCARNAN,KENNETH,JOHN,Male,Caucasian,04/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,4,High,8,Risk of Recidivism,0.16,8,High,New,1,0 +66222,76673,69409,PRETRIAL,MCCARNAN,KENNETH,JOHN,Male,Caucasian,04/02/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66246,76700,69435,Probation,Portillocruz,German,Neriz,Male,Hispanic,12/06/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/15/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +66246,76700,69435,Probation,Portillocruz,German,Neriz,Male,Hispanic,12/06/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +66246,76700,69435,Probation,Portillocruz,German,Neriz,Male,Hispanic,12/06/67,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66223,76674,69410,PRETRIAL,SKINNER,RANDOR,NULL,Male,African-American,05/22/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/15/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +66223,76674,69410,PRETRIAL,SKINNER,RANDOR,NULL,Male,African-American,05/22/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/15/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +66223,76674,69410,PRETRIAL,SKINNER,RANDOR,NULL,Male,African-American,05/22/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +57343,76691,69426,PRETRIAL,Blocker,Desmond,Rashard,Male,African-American,11/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +57343,76691,69426,PRETRIAL,Blocker,Desmond,Rashard,Male,African-American,11/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +57343,76691,69426,PRETRIAL,Blocker,Desmond,Rashard,Male,African-American,11/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66219,76670,69406,PRETRIAL,West,Jhemel,L,Male,African-American,07/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +66219,76670,69406,PRETRIAL,West,Jhemel,L,Male,African-American,07/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +66219,76670,69406,PRETRIAL,West,Jhemel,L,Male,African-American,07/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66241,76695,69430,Probation,Reyes,Stephanie,NULL,Female,Hispanic,08/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +66241,76695,69430,Probation,Reyes,Stephanie,NULL,Female,Hispanic,08/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.36,7,Medium,New,1,0 +66241,76695,69430,Probation,Reyes,Stephanie,NULL,Female,Hispanic,08/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +39140,76704,69439,PRETRIAL,Hill,David,NULL,Male,Caucasian,09/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +39140,76704,69439,PRETRIAL,Hill,David,NULL,Male,Caucasian,09/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +39140,76704,69439,PRETRIAL,Hill,David,NULL,Male,Caucasian,09/18/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +23751,76707,69442,PRETRIAL,KANTLENER,LISA,NULL,Female,Caucasian,07/07/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +23751,76707,69442,PRETRIAL,KANTLENER,LISA,NULL,Female,Caucasian,07/07/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +23751,76707,69442,PRETRIAL,KANTLENER,LISA,NULL,Female,Caucasian,07/07/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66254,76709,69444,Probation,Leach,Samantha,NULL,Female,Caucasian,08/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +66254,76709,69444,Probation,Leach,Samantha,NULL,Female,Caucasian,08/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +66254,76709,69444,Probation,Leach,Samantha,NULL,Female,Caucasian,08/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66228,76679,69415,Probation,CAMPOSDURAN,Paulina,NULL,Female,Hispanic,05/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +66228,76679,69415,Probation,CAMPOSDURAN,Paulina,NULL,Female,Hispanic,05/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.53,2,Low,New,1,0 +66228,76679,69415,Probation,CAMPOSDURAN,Paulina,NULL,Female,Hispanic,05/27/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66234,76686,69422,Probation,Logan,Katherine,NULL,Female,Caucasian,02/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +66234,76686,69422,Probation,Logan,Katherine,NULL,Female,Caucasian,02/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.62,2,Low,New,1,0 +66234,76686,69422,Probation,Logan,Katherine,NULL,Female,Caucasian,02/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +32489,76688,33371,DRRD,Metayer,Anderson,NULL,Male,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,Copy,1,0 +32489,76688,33371,DRRD,Metayer,Anderson,NULL,Male,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,Copy,1,0 +32489,76688,33371,DRRD,Metayer,Anderson,NULL,Male,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +66230,76681,69417,PRETRIAL,pinon,louis,NULL,Male,Caucasian,11/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.19,4,Low,New,1,0 +66230,76681,69417,PRETRIAL,pinon,louis,NULL,Male,Caucasian,11/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +66230,76681,69417,PRETRIAL,pinon,louis,NULL,Male,Caucasian,11/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +66220,76671,69407,PRETRIAL,patterson,Joshua,J,Male,African-American,09/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,4,High,7,Risk of Violence,-0.57,10,High,New,1,0 +66220,76671,69407,PRETRIAL,patterson,Joshua,J,Male,African-American,09/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,4,High,8,Risk of Recidivism,0.42,9,High,New,1,0 +66220,76671,69407,PRETRIAL,patterson,Joshua,J,Male,African-American,09/10/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66236,76689,69424,Probation,Lilly,Alvin,NULL,Male,African-American,05/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +66236,76689,69424,Probation,Lilly,Alvin,NULL,Male,African-American,05/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +66236,76689,69424,Probation,Lilly,Alvin,NULL,Male,African-American,05/21/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66243,76697,69432,Probation,Cato,Andrew,Laki,Male,Other,08/06/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/15/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +66243,76697,69432,Probation,Cato,Andrew,Laki,Male,Other,08/06/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/15/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +66243,76697,69432,Probation,Cato,Andrew,Laki,Male,Other,08/06/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +42234,76702,69437,Probation,Nanda,Jagdies,NULL,Male,Other,05/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +42234,76702,69437,Probation,Nanda,Jagdies,NULL,Male,Other,05/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +42234,76702,69437,Probation,Nanda,Jagdies,NULL,Male,Other,05/02/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66225,76676,69412,PRETRIAL,LUGO,MIRNA,NULL,Female,Caucasian,02/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/15/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +66225,76676,69412,PRETRIAL,LUGO,MIRNA,NULL,Female,Caucasian,02/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +66225,76676,69412,PRETRIAL,LUGO,MIRNA,NULL,Female,Caucasian,02/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66249,76705,69440,Probation,NITOIU,ADRIAN,NULL,Male,Caucasian,04/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/15/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +66249,76705,69440,Probation,NITOIU,ADRIAN,NULL,Male,Caucasian,04/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/15/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +66249,76705,69440,Probation,NITOIU,ADRIAN,NULL,Male,Caucasian,04/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66232,76684,69420,PRETRIAL,Hill,Linda,Marie,Female,African-American,11/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/15/14 0:00,2,Medium,7,Risk of Violence,-2.97,1,Low,New,1,0 +66232,76684,69420,PRETRIAL,Hill,Linda,Marie,Female,African-American,11/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +66232,76684,69420,PRETRIAL,Hill,Linda,Marie,Female,African-American,11/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/15/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +32489,36472,33371,DRRD,Metayer,Anderson,NULL,Male,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,New,1,0 +32489,36472,33371,DRRD,Metayer,Anderson,NULL,Male,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +32489,36472,33371,DRRD,Metayer,Anderson,NULL,Male,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66239,76692,69427,Probation,Alarcon,Vanessa,NULL,Female,Hispanic,08/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +66239,76692,69427,Probation,Alarcon,Vanessa,NULL,Female,Hispanic,08/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +66239,76692,69427,Probation,Alarcon,Vanessa,NULL,Female,Hispanic,08/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66267,76726,69461,PRETRIAL,Gray,Charles,NULL,Male,Caucasian,07/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/16/14 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +66267,76726,69461,PRETRIAL,Gray,Charles,NULL,Male,Caucasian,07/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +66267,76726,69461,PRETRIAL,Gray,Charles,NULL,Male,Caucasian,07/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/16/14 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +66278,76741,69476,Probation,Prado,Ermilio,NULL,Male,Hispanic,10/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/16/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +66278,76741,69476,Probation,Prado,Ermilio,NULL,Male,Hispanic,10/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +66278,76741,69476,Probation,Prado,Ermilio,NULL,Male,Hispanic,10/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66257,76713,69448,PRETRIAL,Jiron,Victor,NULL,Male,Hispanic,04/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +66257,76713,69448,PRETRIAL,Jiron,Victor,NULL,Male,Hispanic,04/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +66257,76713,69448,PRETRIAL,Jiron,Victor,NULL,Male,Hispanic,04/25/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66264,76720,69455,PRETRIAL,McFarlane,Justin-Chaz,Huge,Male,African-American,08/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +66264,76720,69455,PRETRIAL,McFarlane,Justin-Chaz,Huge,Male,African-American,08/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +66264,76720,69455,PRETRIAL,McFarlane,Justin-Chaz,Huge,Male,African-American,08/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66272,76733,69468,Probation,Molnar,Stephen,NULL,Male,Caucasian,01/18/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +66272,76733,69468,Probation,Molnar,Stephen,NULL,Male,Caucasian,01/18/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +66272,76733,69468,Probation,Molnar,Stephen,NULL,Male,Caucasian,01/18/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66273,76734,69469,Probation,Caggiano,Anthony,Mario,Male,Caucasian,05/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +66273,76734,69469,Probation,Caggiano,Anthony,Mario,Male,Caucasian,05/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +66273,76734,69469,Probation,Caggiano,Anthony,Mario,Male,Caucasian,05/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66258,76712,69447,PRETRIAL,KHAN,ZAHEER,NASR,Male,Other,02/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +66258,76712,69447,PRETRIAL,KHAN,ZAHEER,NASR,Male,Other,02/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +66258,76712,69447,PRETRIAL,KHAN,ZAHEER,NASR,Male,Other,02/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66255,76710,69445,PRETRIAL,DIVIDU,ELLIANA,A,Male,Caucasian,10/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +66255,76710,69445,PRETRIAL,DIVIDU,ELLIANA,A,Male,Caucasian,10/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +66255,76710,69445,PRETRIAL,DIVIDU,ELLIANA,A,Male,Caucasian,10/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +21238,76723,69458,PRETRIAL,RENOSA,JOE,NULL,Male,African-American,12/04/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +21238,76723,69458,PRETRIAL,RENOSA,JOE,NULL,Male,African-American,12/04/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +21238,76723,69458,PRETRIAL,RENOSA,JOE,NULL,Male,African-American,12/04/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +12951,76731,69466,PRETRIAL,Ragland,Jasmond,D,Male,African-American,12/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,New,1,0 +12951,76731,69466,PRETRIAL,Ragland,Jasmond,D,Male,African-American,12/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +12951,76731,69466,PRETRIAL,Ragland,Jasmond,D,Male,African-American,12/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66274,76736,69471,Probation,lehman,chistopher,NULL,Male,Caucasian,12/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +66274,76736,69471,Probation,lehman,chistopher,NULL,Male,Caucasian,12/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +66274,76736,69471,Probation,lehman,chistopher,NULL,Male,Caucasian,12/10/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66276,76739,69474,Probation,McGreen,Michael,NULL,Male,Caucasian,04/20/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +66276,76739,69474,Probation,McGreen,Michael,NULL,Male,Caucasian,04/20/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +66276,76739,69474,Probation,McGreen,Michael,NULL,Male,Caucasian,04/20/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66263,76718,69453,PRETRIAL,Comrie,Veronica,NULL,Female,Other,08/05/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +66263,76718,69453,PRETRIAL,Comrie,Veronica,NULL,Female,Other,08/05/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +66263,76718,69453,PRETRIAL,Comrie,Veronica,NULL,Female,Other,08/05/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66261,76716,69451,PRETRIAL,Marte,Travis,NULL,Male,Caucasian,12/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/14 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +66261,76716,69451,PRETRIAL,Marte,Travis,NULL,Male,Caucasian,12/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +66261,76716,69451,PRETRIAL,Marte,Travis,NULL,Male,Caucasian,12/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +60720,76730,69465,PRETRIAL,MALGAARD,DANIEL,NULL,Male,Caucasian,03/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +60720,76730,69465,PRETRIAL,MALGAARD,DANIEL,NULL,Male,Caucasian,03/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +60720,76730,69465,PRETRIAL,MALGAARD,DANIEL,NULL,Male,Caucasian,03/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52375,76737,69472,PRETRIAL,Thomas,Murvin,J,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +52375,76737,69472,PRETRIAL,Thomas,Murvin,J,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,4,High,8,Risk of Recidivism,0.81,10,High,New,1,0 +52375,76737,69472,PRETRIAL,Thomas,Murvin,J,Male,African-American,03/29/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +66266,76725,69460,Probation,Malave,Julio,Cesar,Male,Hispanic,07/22/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +66266,76725,69460,Probation,Malave,Julio,Cesar,Male,Hispanic,07/22/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +66266,76725,69460,Probation,Malave,Julio,Cesar,Male,Hispanic,07/22/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66279,76742,69477,Probation,vanetten,jason,NULL,Male,Caucasian,02/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +66279,76742,69477,Probation,vanetten,jason,NULL,Male,Caucasian,02/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +66279,76742,69477,Probation,vanetten,jason,NULL,Male,Caucasian,02/01/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +59681,76721,69456,PRETRIAL,Jacobs,Marshall,NULL,Male,Caucasian,04/02/84,17,All Scales,Intake,English,Other,Jail Inmate,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +59681,76721,69456,PRETRIAL,Jacobs,Marshall,NULL,Male,Caucasian,04/02/84,17,All Scales,Intake,English,Other,Jail Inmate,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-0.41,4,Low,New,1,0 +59681,76721,69456,PRETRIAL,Jacobs,Marshall,NULL,Male,Caucasian,04/02/84,17,All Scales,Intake,English,Other,Jail Inmate,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,31,8,High,New,1,0 +66282,76746,69480,Broward County,Malone,Toni,NULL,Female,Caucasian,06/08/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +66282,76746,69480,Broward County,Malone,Toni,NULL,Female,Caucasian,06/08/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,9,High,New,1,0 +66282,76746,69480,Broward County,Malone,Toni,NULL,Female,Caucasian,06/08/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +66265,76724,69459,Probation,Spaziano,Stephen,NULL,Male,Caucasian,12/11/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +66265,76724,69459,Probation,Spaziano,Stephen,NULL,Male,Caucasian,12/11/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +66265,76724,69459,Probation,Spaziano,Stephen,NULL,Male,Caucasian,12/11/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66280,76743,69478,Probation,kabbes,keith,NULL,Male,Caucasian,10/22/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +66280,76743,69478,Probation,kabbes,keith,NULL,Male,Caucasian,10/22/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +66280,76743,69478,Probation,kabbes,keith,NULL,Male,Caucasian,10/22/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +57922,76722,69457,PRETRIAL,SANTIAGO,OMAR,NULL,Male,Caucasian,05/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +57922,76722,69457,PRETRIAL,SANTIAGO,OMAR,NULL,Male,Caucasian,05/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +57922,76722,69457,PRETRIAL,SANTIAGO,OMAR,NULL,Male,Caucasian,05/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66281,76745,69479,Probation,Galvez,Cesar,alberto,Male,Hispanic,07/15/78,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/16/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +66281,76745,69479,Probation,Galvez,Cesar,alberto,Male,Hispanic,07/15/78,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +66281,76745,69479,Probation,Galvez,Cesar,alberto,Male,Hispanic,07/15/78,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66260,76715,69450,PRETRIAL,Bennett-Walker,Novey,NULL,Female,Other,09/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +66260,76715,69450,PRETRIAL,Bennett-Walker,Novey,NULL,Female,Other,09/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +66260,76715,69450,PRETRIAL,Bennett-Walker,Novey,NULL,Female,Other,09/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66270,76729,69464,Probation,LACABA,ROBERT,JOSEPH,Male,Hispanic,01/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +66270,76729,69464,Probation,LACABA,ROBERT,JOSEPH,Male,Hispanic,01/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +66270,76729,69464,Probation,LACABA,ROBERT,JOSEPH,Male,Hispanic,01/18/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66275,76738,69473,Probation,Garner,Timothy,NULL,Male,African-American,12/27/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/16/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +66275,76738,69473,Probation,Garner,Timothy,NULL,Male,African-American,12/27/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +66275,76738,69473,Probation,Garner,Timothy,NULL,Male,African-American,12/27/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/16/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +66262,76717,69452,PRETRIAL,Ellington,Mark,A,Male,Other,02/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/16/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +66262,76717,69452,PRETRIAL,Ellington,Mark,A,Male,Other,02/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/16/14 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +66262,76717,69452,PRETRIAL,Ellington,Mark,A,Male,Other,02/02/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +33851,36022,32960,Probation,Greene,Dominique,Patricia,Female,African-American,03/21/87,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,9/16/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +33851,36022,32960,Probation,Greene,Dominique,Patricia,Female,African-American,03/21/87,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,9/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.33,7,Medium,New,1,0 +33851,36022,32960,Probation,Greene,Dominique,Patricia,Female,African-American,03/21/87,22,Risk and Prescreen,Intake,English,Other,Pretrial Defendant,Single,9/16/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +62949,76719,69454,PRETRIAL,Raiford,Robert,L,Male,African-American,02/01/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.39,10,High,New,1,0 +62949,76719,69454,PRETRIAL,Raiford,Robert,L,Male,African-American,02/01/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +62949,76719,69454,PRETRIAL,Raiford,Robert,L,Male,African-American,02/01/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66256,76711,69446,PRETRIAL,Jones,Jeremiah,Eddie,Male,African-American,04/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,2,Medium,7,Risk of Violence,-1.51,6,Medium,New,1,0 +66256,76711,69446,PRETRIAL,Jones,Jeremiah,Eddie,Male,African-American,04/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +66256,76711,69446,PRETRIAL,Jones,Jeremiah,Eddie,Male,African-American,04/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/16/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66271,76732,69467,Probation,JEANBAPTISTE,DELINCE,NULL,Male,African-American,09/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +66271,76732,69467,Probation,JEANBAPTISTE,DELINCE,NULL,Male,African-American,09/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +66271,76732,69467,Probation,JEANBAPTISTE,DELINCE,NULL,Male,African-American,09/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57300,76735,69470,PRETRIAL,Ferguson,Jameka,Omoro,Male,Other,11/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +57300,76735,69470,PRETRIAL,Ferguson,Jameka,Omoro,Male,Other,11/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +57300,76735,69470,PRETRIAL,Ferguson,Jameka,Omoro,Male,Other,11/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66259,76714,69449,PRETRIAL,Alarcon,Monica,NULL,Female,Caucasian,09/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/16/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +66259,76714,69449,PRETRIAL,Alarcon,Monica,NULL,Female,Caucasian,09/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +66259,76714,69449,PRETRIAL,Alarcon,Monica,NULL,Female,Caucasian,09/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66268,76727,69462,Probation,baboolal,kameila,NULL,Female,Other,05/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +66268,76727,69462,Probation,baboolal,kameila,NULL,Female,Other,05/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/14 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +66268,76727,69462,Probation,baboolal,kameila,NULL,Female,Other,05/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/16/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66293,76761,69494,PRETRIAL,Elias,Damarys,NULL,Female,Caucasian,07/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,2,Medium,7,Risk of Violence,-1.83,5,Medium,New,1,0 +66293,76761,69494,PRETRIAL,Elias,Damarys,NULL,Female,Caucasian,07/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +66293,76761,69494,PRETRIAL,Elias,Damarys,NULL,Female,Caucasian,07/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66317,76795,69523,PRETRIAL,majeski,dana,NULL,Male,Caucasian,05/28/73,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,9/17/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +66317,76795,69523,PRETRIAL,majeski,dana,NULL,Male,Caucasian,05/28/73,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +66317,76795,69523,PRETRIAL,majeski,dana,NULL,Male,Caucasian,05/28/73,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,1,Low,New,1,0 +66304,76774,69506,PRETRIAL,Brinson,Shontrice,NULL,Female,African-American,12/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +66304,76774,69506,PRETRIAL,Brinson,Shontrice,NULL,Female,African-American,12/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +66304,76774,69506,PRETRIAL,Brinson,Shontrice,NULL,Female,African-American,12/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66287,76753,69486,PRETRIAL,Phillips,Edward,Charles,Male,African-American,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +66287,76753,69486,PRETRIAL,Phillips,Edward,Charles,Male,African-American,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +66287,76753,69486,PRETRIAL,Phillips,Edward,Charles,Male,African-American,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +59117,76782,69511,PRETRIAL,CONNELLY,CHRISTOPHER,NULL,Male,Caucasian,06/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +59117,76782,69511,PRETRIAL,CONNELLY,CHRISTOPHER,NULL,Male,Caucasian,06/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +59117,76782,69511,PRETRIAL,CONNELLY,CHRISTOPHER,NULL,Male,Caucasian,06/22/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66289,76756,69489,PRETRIAL,Alvarezcabera,Yonly,NULL,Male,Other,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +66289,76756,69489,PRETRIAL,Alvarezcabera,Yonly,NULL,Male,Other,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +66289,76756,69489,PRETRIAL,Alvarezcabera,Yonly,NULL,Male,Other,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49906,76777,69508,PRETRIAL,Thompson,Jawara,NULL,Male,African-American,01/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +49906,76777,69508,PRETRIAL,Thompson,Jawara,NULL,Male,African-American,01/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +49906,76777,69508,PRETRIAL,Thompson,Jawara,NULL,Male,African-American,01/28/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66311,76790,69518,Probation,Blue-FanFan,Medlyne,NULL,Female,African-American,08/28/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/17/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +66311,76790,69518,Probation,Blue-FanFan,Medlyne,NULL,Female,African-American,08/28/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/17/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +66311,76790,69518,Probation,Blue-FanFan,Medlyne,NULL,Female,African-American,08/28/71,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66315,76792,69520,Probation,rominger,william,NULL,Male,Caucasian,02/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +66315,76792,69520,Probation,rominger,william,NULL,Male,Caucasian,02/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +66315,76792,69520,Probation,rominger,william,NULL,Male,Caucasian,02/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66301,76769,69502,Probation,Soto,Natalia,NULL,Female,Hispanic,04/24/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +66301,76769,69502,Probation,Soto,Natalia,NULL,Female,Hispanic,04/24/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +66301,76769,69502,Probation,Soto,Natalia,NULL,Female,Hispanic,04/24/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66283,76748,69481,PRETRIAL,Coleman,Michael,NULL,Male,African-American,12/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/17/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +66283,76748,69481,PRETRIAL,Coleman,Michael,NULL,Male,African-American,12/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/17/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +66283,76748,69481,PRETRIAL,Coleman,Michael,NULL,Male,African-American,12/05/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +55733,76784,57618,Probation,woodlief,sara,frances,Female,Caucasian,04/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,Copy,1,0 +55733,76784,57618,Probation,woodlief,sara,frances,Female,Caucasian,04/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,Copy,1,0 +55733,76784,57618,Probation,woodlief,sara,frances,Female,Caucasian,04/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +66285,76750,69483,PRETRIAL,Frederic,Alteus,NULL,Male,African-American,12/06/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +66285,76750,69483,PRETRIAL,Frederic,Alteus,NULL,Male,African-American,12/06/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +66285,76750,69483,PRETRIAL,Frederic,Alteus,NULL,Male,African-American,12/06/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66300,76768,69501,Probation,TUCKER,LADONNA,A,Female,Native American,03/30/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,New,1,0 +66300,76768,69501,Probation,TUCKER,LADONNA,A,Female,Native American,03/30/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,8,High,New,1,0 +66300,76768,69501,Probation,TUCKER,LADONNA,A,Female,Native American,03/30/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +19929,76785,69513,Probation,apa,giuliano,NULL,Male,Caucasian,11/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.66,9,High,New,1,0 +19929,76785,69513,Probation,apa,giuliano,NULL,Male,Caucasian,11/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +19929,76785,69513,Probation,apa,giuliano,NULL,Male,Caucasian,11/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66296,76764,69497,Probation,Hill,Willie,Devin,Male,African-American,05/25/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/17/14 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +66296,76764,69497,Probation,Hill,Willie,Devin,Male,African-American,05/25/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +66296,76764,69497,Probation,Hill,Willie,Devin,Male,African-American,05/25/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/17/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66312,76789,69517,Probation,Frazier,Theodore,NULL,Male,African-American,05/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +66312,76789,69517,Probation,Frazier,Theodore,NULL,Male,African-American,05/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +66312,76789,69517,Probation,Frazier,Theodore,NULL,Male,African-American,05/09/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66292,76759,69492,PRETRIAL,LINDOR,RAYMOND,NULL,Male,African-American,07/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/17/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +66292,76759,69492,PRETRIAL,LINDOR,RAYMOND,NULL,Male,African-American,07/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/17/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +66292,76759,69492,PRETRIAL,LINDOR,RAYMOND,NULL,Male,African-American,07/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +37262,76752,69485,PRETRIAL,Kates,Tamisha,NULL,Female,African-American,12/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +37262,76752,69485,PRETRIAL,Kates,Tamisha,NULL,Female,African-American,12/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.11,8,High,New,1,0 +37262,76752,69485,PRETRIAL,Kates,Tamisha,NULL,Female,African-American,12/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66298,76766,69499,Probation,Bedell,Ashley,NULL,Female,Caucasian,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,New,1,0 +66298,76766,69499,Probation,Bedell,Ashley,NULL,Female,Caucasian,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +66298,76766,69499,Probation,Bedell,Ashley,NULL,Female,Caucasian,11/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +64988,76780,68079,PRETRIAL,Charles,Rodney,NULL,Male,African-American,10/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,Copy,1,0 +64988,76780,68079,PRETRIAL,Charles,Rodney,NULL,Male,African-American,10/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,4,High,8,Risk of Recidivism,0.3,8,High,Copy,1,0 +64988,76780,68079,PRETRIAL,Charles,Rodney,NULL,Male,African-American,10/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +15632,76787,69515,PRETRIAL,CHANCE,OWEN,NULL,Male,African-American,01/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.91,5,Medium,New,1,0 +15632,76787,69515,PRETRIAL,CHANCE,OWEN,NULL,Male,African-American,01/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +15632,76787,69515,PRETRIAL,CHANCE,OWEN,NULL,Male,African-American,01/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66305,76773,69505,PRETRIAL,DASS,DHARMENDRA,C,Male,Native American,12/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/17/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +66305,76773,69505,PRETRIAL,DASS,DHARMENDRA,C,Male,Native American,12/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +66305,76773,69505,PRETRIAL,DASS,DHARMENDRA,C,Male,Native American,12/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66299,76767,69500,Probation,maldonadoretreage,debbie,NULL,Female,Hispanic,09/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.56,2,Low,New,1,0 +66299,76767,69500,Probation,maldonadoretreage,debbie,NULL,Female,Hispanic,09/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,9,High,New,1,0 +66299,76767,69500,Probation,maldonadoretreage,debbie,NULL,Female,Hispanic,09/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +66306,76776,69507,Probation,CORDER,CHELSEY,PAIGE,Female,Caucasian,12/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +66306,76776,69507,Probation,CORDER,CHELSEY,PAIGE,Female,Caucasian,12/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +66306,76776,69507,Probation,CORDER,CHELSEY,PAIGE,Female,Caucasian,12/03/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66316,76793,69521,Probation,JOHNSON,JUWAUQUINN,NULL,Male,African-American,08/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +66316,76793,69521,Probation,JOHNSON,JUWAUQUINN,NULL,Male,African-American,08/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +66316,76793,69521,Probation,JOHNSON,JUWAUQUINN,NULL,Male,African-American,08/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66295,76763,69496,PRETRIAL,Aguasvivas,Manuel,Alejandro,Male,Caucasian,12/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +66295,76763,69496,PRETRIAL,Aguasvivas,Manuel,Alejandro,Male,Caucasian,12/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +66295,76763,69496,PRETRIAL,Aguasvivas,Manuel,Alejandro,Male,Caucasian,12/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66303,76772,69504,PRETRIAL,Francisco,Lorraine,NULL,Female,Hispanic,11/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +66303,76772,69504,PRETRIAL,Francisco,Lorraine,NULL,Female,Hispanic,11/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,8,High,New,1,0 +66303,76772,69504,PRETRIAL,Francisco,Lorraine,NULL,Female,Hispanic,11/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66286,76751,69484,PRETRIAL,Brutton,Celeberty,C,Female,African-American,08/30/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,4,High,7,Risk of Violence,-0.45,10,High,New,1,0 +66286,76751,69484,PRETRIAL,Brutton,Celeberty,C,Female,African-American,08/30/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,4,High,8,Risk of Recidivism,0.23,9,High,New,1,0 +66286,76751,69484,PRETRIAL,Brutton,Celeberty,C,Female,African-American,08/30/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66297,76765,69498,Probation,ANDINO,LUIS,NULL,Male,Hispanic,05/29/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +66297,76765,69498,Probation,ANDINO,LUIS,NULL,Male,Hispanic,05/29/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +66297,76765,69498,Probation,ANDINO,LUIS,NULL,Male,Hispanic,05/29/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +66308,76779,69510,Probation,Gutierrez,Rebecca,NULL,Female,Hispanic,04/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +66308,76779,69510,Probation,Gutierrez,Rebecca,NULL,Female,Hispanic,04/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +66308,76779,69510,Probation,Gutierrez,Rebecca,NULL,Female,Hispanic,04/26/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +64988,76781,68079,PRETRIAL,Charles,Rodney,NULL,Male,African-American,10/07/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,Copy,1,0 +64988,76781,68079,PRETRIAL,Charles,Rodney,NULL,Male,African-American,10/07/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,4,High,8,Risk of Recidivism,0.3,8,High,Copy,1,0 +64988,76781,68079,PRETRIAL,Charles,Rodney,NULL,Male,African-American,10/07/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +66310,76786,69514,PRETRIAL,Rosado,Kristin,NULL,Female,Caucasian,10/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +66310,76786,69514,PRETRIAL,Rosado,Kristin,NULL,Female,Caucasian,10/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +66310,76786,69514,PRETRIAL,Rosado,Kristin,NULL,Female,Caucasian,10/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66291,76758,69491,PRETRIAL,Restaino,Gerard,NULL,Male,African-American,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.99,9,High,New,1,0 +66291,76758,69491,PRETRIAL,Restaino,Gerard,NULL,Male,African-American,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +66291,76758,69491,PRETRIAL,Restaino,Gerard,NULL,Male,African-American,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +59091,76760,69493,PRETRIAL,RENDER,JAMES,NULL,Male,African-American,04/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +59091,76760,69493,PRETRIAL,RENDER,JAMES,NULL,Male,African-American,04/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +59091,76760,69493,PRETRIAL,RENDER,JAMES,NULL,Male,African-American,04/11/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66284,76749,69482,PRETRIAL,Sainvil,Arly,D,Male,Other,08/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +66284,76749,69482,PRETRIAL,Sainvil,Arly,D,Male,Other,08/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +66284,76749,69482,PRETRIAL,Sainvil,Arly,D,Male,Other,08/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66307,76778,69509,Probation,Ricketts,Tracy,NULL,Male,African-American,09/03/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +66307,76778,69509,Probation,Ricketts,Tracy,NULL,Male,African-American,09/03/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +66307,76778,69509,Probation,Ricketts,Tracy,NULL,Male,African-American,09/03/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66290,76757,69490,PRETRIAL,WHITAKER,KOLLIN,THOMAS,Male,African-American,03/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/17/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +66290,76757,69490,PRETRIAL,WHITAKER,KOLLIN,THOMAS,Male,African-American,03/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/17/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +66290,76757,69490,PRETRIAL,WHITAKER,KOLLIN,THOMAS,Male,African-American,03/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66314,76791,69519,PRETRIAL,Swalm,Stuart,NULL,Male,Caucasian,10/02/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +66314,76791,69519,PRETRIAL,Swalm,Stuart,NULL,Male,Caucasian,10/02/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +66314,76791,69519,PRETRIAL,Swalm,Stuart,NULL,Male,Caucasian,10/02/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +66288,76755,69488,PRETRIAL,Navas,Luis,NULL,Male,Caucasian,10/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +66288,76755,69488,PRETRIAL,Navas,Luis,NULL,Male,Caucasian,10/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +66288,76755,69488,PRETRIAL,Navas,Luis,NULL,Male,Caucasian,10/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66294,76762,69495,PRETRIAL,Cunningham,Irvin,NULL,Male,African-American,10/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +66294,76762,69495,PRETRIAL,Cunningham,Irvin,NULL,Male,African-American,10/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +66294,76762,69495,PRETRIAL,Cunningham,Irvin,NULL,Male,African-American,10/17/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +46885,52005,47347,PRETRIAL,Stenerwald,Edgar,NULL,Male,Caucasian,07/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +46885,52005,47347,PRETRIAL,Stenerwald,Edgar,NULL,Male,Caucasian,07/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +46885,52005,47347,PRETRIAL,Stenerwald,Edgar,NULL,Male,Caucasian,07/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66309,76783,69512,Probation,lockhart,tricia,NULL,Female,African-American,11/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +66309,76783,69512,Probation,lockhart,tricia,NULL,Female,African-American,11/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +66309,76783,69512,Probation,lockhart,tricia,NULL,Female,African-American,11/15/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +43132,76747,43030,PRETRIAL,Cheanfant,Anthony,A,Male,Other,01/13/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,Copy,1,0 +43132,76747,43030,PRETRIAL,Cheanfant,Anthony,A,Male,Other,01/13/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,Copy,1,0 +43132,76747,43030,PRETRIAL,Cheanfant,Anthony,A,Male,Other,01/13/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +65933,76754,69487,PRETRIAL,SIMON,BERLOUDI,NULL,Male,Other,11/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +65933,76754,69487,PRETRIAL,SIMON,BERLOUDI,NULL,Male,Other,11/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +65933,76754,69487,PRETRIAL,SIMON,BERLOUDI,NULL,Male,Other,11/19/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +46885,76775,47347,PRETRIAL,Stenerwald,Edgar,NULL,Male,Caucasian,07/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,Copy,1,0 +46885,76775,47347,PRETRIAL,Stenerwald,Edgar,NULL,Male,Caucasian,07/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,Copy,1,0 +46885,76775,47347,PRETRIAL,Stenerwald,Edgar,NULL,Male,Caucasian,07/07/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +66338,76820,69547,Probation,transtrum,kimberly,NULL,Female,Caucasian,04/01/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +66338,76820,69547,Probation,transtrum,kimberly,NULL,Female,Caucasian,04/01/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +66338,76820,69547,Probation,transtrum,kimberly,NULL,Female,Caucasian,04/01/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66331,76812,69539,PRETRIAL,crusoe,charles,NULL,Male,Caucasian,11/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +66331,76812,69539,PRETRIAL,crusoe,charles,NULL,Male,Caucasian,11/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +66331,76812,69539,PRETRIAL,crusoe,charles,NULL,Male,Caucasian,11/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +54879,76804,69532,PRETRIAL,BURTON,JAMAR,NULL,Male,African-American,12/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +54879,76804,69532,PRETRIAL,BURTON,JAMAR,NULL,Male,African-American,12/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +54879,76804,69532,PRETRIAL,BURTON,JAMAR,NULL,Male,African-American,12/15/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66318,76796,69524,PRETRIAL,Scott,Michael,NULL,Male,African-American,07/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +66318,76796,69524,PRETRIAL,Scott,Michael,NULL,Male,African-American,07/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +66318,76796,69524,PRETRIAL,Scott,Michael,NULL,Male,African-American,07/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66321,76799,69527,PRETRIAL,Panageotou,George,Chris,Male,Caucasian,01/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +66321,76799,69527,PRETRIAL,Panageotou,George,Chris,Male,Caucasian,01/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +66321,76799,69527,PRETRIAL,Panageotou,George,Chris,Male,Caucasian,01/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +58635,76817,69544,PRETRIAL,Lopez,Carlos,NULL,Male,Hispanic,08/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2,4,Low,New,1,0 +58635,76817,69544,PRETRIAL,Lopez,Carlos,NULL,Male,Hispanic,08/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +58635,76817,69544,PRETRIAL,Lopez,Carlos,NULL,Male,Hispanic,08/19/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66328,76809,69536,PRETRIAL,Mohamed,Mahmoud,NULL,Male,Arabic,06/15/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/18/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +66328,76809,69536,PRETRIAL,Mohamed,Mahmoud,NULL,Male,Arabic,06/15/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/18/14 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +66328,76809,69536,PRETRIAL,Mohamed,Mahmoud,NULL,Male,Arabic,06/15/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66324,76802,69530,PRETRIAL,Thompson,Kamile,NULL,Female,Other,04/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/18/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +66324,76802,69530,PRETRIAL,Thompson,Kamile,NULL,Female,Other,04/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/18/14 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +66324,76802,69530,PRETRIAL,Thompson,Kamile,NULL,Female,Other,04/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66319,76797,69525,PRETRIAL,Anderson,Eston,NULL,Male,African-American,06/24/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/18/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +66319,76797,69525,PRETRIAL,Anderson,Eston,NULL,Male,African-American,06/24/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/18/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +66319,76797,69525,PRETRIAL,Anderson,Eston,NULL,Male,African-American,06/24/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +66336,76818,69545,Probation,gura,joseph,NULL,Male,Caucasian,10/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,2,Medium,7,Risk of Violence,-3.08,1,Low,New,1,0 +66336,76818,69545,Probation,gura,joseph,NULL,Male,Caucasian,10/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +66336,76818,69545,Probation,gura,joseph,NULL,Male,Caucasian,10/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66333,76814,69541,Probation,rodriguez,jose,NULL,Male,Hispanic,03/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +66333,76814,69541,Probation,rodriguez,jose,NULL,Male,Hispanic,03/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +66333,76814,69541,Probation,rodriguez,jose,NULL,Male,Hispanic,03/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66323,76801,69529,PRETRIAL,Ramirez,Hernan,NULL,Male,Hispanic,08/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +66323,76801,69529,PRETRIAL,Ramirez,Hernan,NULL,Male,Hispanic,08/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +66323,76801,69529,PRETRIAL,Ramirez,Hernan,NULL,Male,Hispanic,08/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66334,76815,69542,Probation,Samuels,Keith,NULL,Male,African-American,06/17/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/14 0:00,1,Low,7,Risk of Violence,-4.34,1,Low,New,1,0 +66334,76815,69542,Probation,Samuels,Keith,NULL,Male,African-American,06/17/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/14 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +66334,76815,69542,Probation,Samuels,Keith,NULL,Male,African-American,06/17/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66329,76810,69537,Probation,mcgrath,clinton,NULL,Male,Caucasian,08/26/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +66329,76810,69537,Probation,mcgrath,clinton,NULL,Male,Caucasian,08/26/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +66329,76810,69537,Probation,mcgrath,clinton,NULL,Male,Caucasian,08/26/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66326,76806,69534,Probation,braddy,lauren,NULL,Female,Caucasian,09/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,2,Medium,7,Risk of Violence,-2.52,3,Low,New,1,0 +66326,76806,69534,Probation,braddy,lauren,NULL,Female,Caucasian,09/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +66326,76806,69534,Probation,braddy,lauren,NULL,Female,Caucasian,09/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66320,76798,69526,PRETRIAL,Green,Marvin,NULL,Male,African-American,04/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +66320,76798,69526,PRETRIAL,Green,Marvin,NULL,Male,African-American,04/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +66320,76798,69526,PRETRIAL,Green,Marvin,NULL,Male,African-American,04/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66325,76805,69533,PRETRIAL,Medina,Andre,Joseph,Male,Caucasian,10/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +66325,76805,69533,PRETRIAL,Medina,Andre,Joseph,Male,Caucasian,10/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +66325,76805,69533,PRETRIAL,Medina,Andre,Joseph,Male,Caucasian,10/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66337,76819,69546,Probation,weber,robert,NULL,Male,Caucasian,11/15/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/18/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,New,1,0 +66337,76819,69546,Probation,weber,robert,NULL,Male,Caucasian,11/15/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/18/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +66337,76819,69546,Probation,weber,robert,NULL,Male,Caucasian,11/15/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66330,76811,69538,Probation,Visconti,Matthew,NULL,Male,Caucasian,10/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +66330,76811,69538,Probation,Visconti,Matthew,NULL,Male,Caucasian,10/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +66330,76811,69538,Probation,Visconti,Matthew,NULL,Male,Caucasian,10/08/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66332,76813,69540,PRETRIAL,Haberkam,Joseph,NULL,Male,Caucasian,02/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/14 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +66332,76813,69540,PRETRIAL,Haberkam,Joseph,NULL,Male,Caucasian,02/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +66332,76813,69540,PRETRIAL,Haberkam,Joseph,NULL,Male,Caucasian,02/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/18/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66322,76800,69528,PRETRIAL,Ducille,Akime,NULL,Male,African-American,08/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +66322,76800,69528,PRETRIAL,Ducille,Akime,NULL,Male,African-American,08/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +66322,76800,69528,PRETRIAL,Ducille,Akime,NULL,Male,African-American,08/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63792,76803,69531,PRETRIAL,Sheppard,Jimmy,NULL,Male,African-American,12/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +63792,76803,69531,PRETRIAL,Sheppard,Jimmy,NULL,Male,African-American,12/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +63792,76803,69531,PRETRIAL,Sheppard,Jimmy,NULL,Male,African-American,12/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/18/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +35145,76821,69548,PRETRIAL,MCFADDEN,FREDERICK,LEE,Male,African-American,07/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +35145,76821,69548,PRETRIAL,MCFADDEN,FREDERICK,LEE,Male,African-American,07/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +35145,76821,69548,PRETRIAL,MCFADDEN,FREDERICK,LEE,Male,African-American,07/15/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66327,76808,69535,Probation,swint,aidan,NULL,Male,Caucasian,06/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.72,2,Low,New,1,0 +66327,76808,69535,Probation,swint,aidan,NULL,Male,Caucasian,06/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +66327,76808,69535,Probation,swint,aidan,NULL,Male,Caucasian,06/24/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66353,76842,69567,PRETRIAL,Prescovitzgider,James,NULL,Male,Other,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +66353,76842,69567,PRETRIAL,Prescovitzgider,James,NULL,Male,Other,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +66353,76842,69567,PRETRIAL,Prescovitzgider,James,NULL,Male,Other,08/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66342,76829,69555,PRETRIAL,Owens,LaJuana,NULL,Female,African-American,10/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +66342,76829,69555,PRETRIAL,Owens,LaJuana,NULL,Female,African-American,10/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,10,High,New,1,0 +66342,76829,69555,PRETRIAL,Owens,LaJuana,NULL,Female,African-American,10/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66359,76850,69575,Probation,perez,joshua,NULL,Male,Hispanic,07/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +66359,76850,69575,Probation,perez,joshua,NULL,Male,Hispanic,07/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +66359,76850,69575,Probation,perez,joshua,NULL,Male,Hispanic,07/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +66356,76847,69572,PRETRIAL,Shields,Richard,NULL,Male,Caucasian,02/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/19/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +66356,76847,69572,PRETRIAL,Shields,Richard,NULL,Male,Caucasian,02/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +66356,76847,69572,PRETRIAL,Shields,Richard,NULL,Male,Caucasian,02/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/19/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66339,76826,69549,PRETRIAL,Hester,Harrell,NULL,Male,African-American,12/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,Copy,1,0 +66339,76826,69549,PRETRIAL,Hester,Harrell,NULL,Male,African-American,12/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,Copy,1,0 +66339,76826,69549,PRETRIAL,Hester,Harrell,NULL,Male,African-American,12/02/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +66363,76855,69580,Probation,GAJRAJ,DEAN,N,Male,Asian,12/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +66363,76855,69580,Probation,GAJRAJ,DEAN,N,Male,Asian,12/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +66363,76855,69580,Probation,GAJRAJ,DEAN,N,Male,Asian,12/02/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66344,76831,69557,PRETRIAL,Blanco,Perez,Yulier,Male,Caucasian,07/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +66344,76831,69557,PRETRIAL,Blanco,Perez,Yulier,Male,Caucasian,07/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +66344,76831,69557,PRETRIAL,Blanco,Perez,Yulier,Male,Caucasian,07/29/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66350,76836,69561,Probation,PORTER,CHITIA,C,Female,African-American,06/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +66350,76836,69561,Probation,PORTER,CHITIA,C,Female,African-American,06/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,7,Medium,New,1,0 +66350,76836,69561,Probation,PORTER,CHITIA,C,Female,African-American,06/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,2,Medium,18,Risk of Failure to Appear,39,10,High,New,1,0 +66341,76827,69553,PRETRIAL,Messer,John,NULL,Male,Caucasian,02/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/19/14 0:00,2,Medium,7,Risk of Violence,-2.73,2,Low,New,1,0 +66341,76827,69553,PRETRIAL,Messer,John,NULL,Male,Caucasian,02/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +66341,76827,69553,PRETRIAL,Messer,John,NULL,Male,Caucasian,02/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/19/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58333,76840,69565,PRETRIAL,Indik,Jarrod,NULL,Male,Caucasian,04/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +58333,76840,69565,PRETRIAL,Indik,Jarrod,NULL,Male,Caucasian,04/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +58333,76840,69565,PRETRIAL,Indik,Jarrod,NULL,Male,Caucasian,04/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66365,76857,69582,Probation,MENDIOLA,EDUARDO,NULL,Male,Hispanic,09/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,New,1,0 +66365,76857,69582,Probation,MENDIOLA,EDUARDO,NULL,Male,Hispanic,09/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,New,1,0 +66365,76857,69582,Probation,MENDIOLA,EDUARDO,NULL,Male,Hispanic,09/07/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66361,76852,69577,PRETRIAL,Antoine,Marydashanah,NULL,Female,African-American,04/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +66361,76852,69577,PRETRIAL,Antoine,Marydashanah,NULL,Female,African-American,04/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +66361,76852,69577,PRETRIAL,Antoine,Marydashanah,NULL,Female,African-American,04/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +31252,76824,69551,PRETRIAL,PORTER,JOE,NULL,Male,African-American,01/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +31252,76824,69551,PRETRIAL,PORTER,JOE,NULL,Male,African-American,01/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +31252,76824,69551,PRETRIAL,PORTER,JOE,NULL,Male,African-American,01/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +65937,76843,69568,PRETRIAL,IACOBELLI,PETER,NULL,Male,Caucasian,04/29/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/14 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +65937,76843,69568,PRETRIAL,IACOBELLI,PETER,NULL,Male,Caucasian,04/29/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/14 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +65937,76843,69568,PRETRIAL,IACOBELLI,PETER,NULL,Male,Caucasian,04/29/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66355,76845,69570,Probation,ROBEST,MICHAEL,A,Male,African-American,02/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/19/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +66355,76845,69570,Probation,ROBEST,MICHAEL,A,Male,African-American,02/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/19/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +66355,76845,69570,Probation,ROBEST,MICHAEL,A,Male,African-American,02/17/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +11994,76828,69554,DRRD,Stone,Charles,Alexander,Male,Caucasian,12/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +11994,76828,69554,DRRD,Stone,Charles,Alexander,Male,Caucasian,12/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +11994,76828,69554,DRRD,Stone,Charles,Alexander,Male,Caucasian,12/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66351,76839,69564,Probation,fleites,rogelio,NULL,Male,Hispanic,05/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +66351,76839,69564,Probation,fleites,rogelio,NULL,Male,Hispanic,05/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +66351,76839,69564,Probation,fleites,rogelio,NULL,Male,Hispanic,05/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66345,76832,69558,Probation,Sotolasanta,Ashley,Corinne,Female,Hispanic,06/18/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/19/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +66345,76832,69558,Probation,Sotolasanta,Ashley,Corinne,Female,Hispanic,06/18/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/19/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +66345,76832,69558,Probation,Sotolasanta,Ashley,Corinne,Female,Hispanic,06/18/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +8689,76835,69560,PRETRIAL,FRANCOIS,LIONEL,JUMIOR,Male,African-American,08/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +8689,76835,69560,PRETRIAL,FRANCOIS,LIONEL,JUMIOR,Male,African-American,08/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +8689,76835,69560,PRETRIAL,FRANCOIS,LIONEL,JUMIOR,Male,African-American,08/01/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +66358,76849,69574,Probation,Valencia,Patricio,NULL,Male,Hispanic,04/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/19/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +66358,76849,69574,Probation,Valencia,Patricio,NULL,Male,Hispanic,04/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/19/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +66358,76849,69574,Probation,Valencia,Patricio,NULL,Male,Hispanic,04/09/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66360,76851,69576,PRETRIAL,MCCLAIN,BILLIE,R,Male,African-American,08/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +66360,76851,69576,PRETRIAL,MCCLAIN,BILLIE,R,Male,African-American,08/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +66360,76851,69576,PRETRIAL,MCCLAIN,BILLIE,R,Male,African-American,08/11/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/14 0:00,2,Medium,18,Risk of Failure to Appear,40,10,High,New,1,0 +6624,76823,69550,PRETRIAL,AARON,COURTNEY,NULL,Male,African-American,10/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +6624,76823,69550,PRETRIAL,AARON,COURTNEY,NULL,Male,African-American,10/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.41,9,High,New,1,0 +6624,76823,69550,PRETRIAL,AARON,COURTNEY,NULL,Male,African-American,10/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66343,76830,69556,PRETRIAL,Chavarriaespinosa,Christopher,NULL,Male,Caucasian,03/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +66343,76830,69556,PRETRIAL,Chavarriaespinosa,Christopher,NULL,Male,Caucasian,03/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +66343,76830,69556,PRETRIAL,Chavarriaespinosa,Christopher,NULL,Male,Caucasian,03/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +60027,76837,69562,PRETRIAL,burns,Ronald,NULL,Male,African-American,07/16/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +60027,76837,69562,PRETRIAL,burns,Ronald,NULL,Male,African-American,07/16/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +60027,76837,69562,PRETRIAL,burns,Ronald,NULL,Male,African-American,07/16/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66354,76844,69569,PRETRIAL,MILLSAP,KEVIN,BLAINE,Male,Caucasian,11/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/19/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +66354,76844,69569,PRETRIAL,MILLSAP,KEVIN,BLAINE,Male,Caucasian,11/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/19/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +66354,76844,69569,PRETRIAL,MILLSAP,KEVIN,BLAINE,Male,Caucasian,11/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +8884,76858,69583,PRETRIAL,Waldrep,Chad,NULL,Male,Caucasian,05/10/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +8884,76858,69583,PRETRIAL,Waldrep,Chad,NULL,Male,Caucasian,05/10/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +8884,76858,69583,PRETRIAL,Waldrep,Chad,NULL,Male,Caucasian,05/10/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +37469,76846,69571,PRETRIAL,Ramnarain,Druve,NULL,Male,Other,05/21/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/19/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +37469,76846,69571,PRETRIAL,Ramnarain,Druve,NULL,Male,Other,05/21/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/19/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +37469,76846,69571,PRETRIAL,Ramnarain,Druve,NULL,Male,Other,05/21/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66352,76838,69563,Probation,Mendezbamaca,Jose,NULL,Male,Hispanic,09/12/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/19/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +66352,76838,69563,Probation,Mendezbamaca,Jose,NULL,Male,Hispanic,09/12/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/19/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +66352,76838,69563,Probation,Mendezbamaca,Jose,NULL,Male,Hispanic,09/12/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66340,76825,69552,PRETRIAL,leonard,wright,NULL,Male,African-American,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +66340,76825,69552,PRETRIAL,leonard,wright,NULL,Male,African-American,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.71,10,High,New,1,0 +66340,76825,69552,PRETRIAL,leonard,wright,NULL,Male,African-American,06/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66357,76848,69573,Probation,DIEUJUSTE,BRIAN,K,Male,African-American,08/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/19/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +66357,76848,69573,Probation,DIEUJUSTE,BRIAN,K,Male,African-American,08/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/19/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +66357,76848,69573,Probation,DIEUJUSTE,BRIAN,K,Male,African-American,08/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,9/19/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66349,76833,69559,PRETRIAL,Arboleda,Jessica,NULL,Female,Hispanic,02/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +66349,76833,69559,PRETRIAL,Arboleda,Jessica,NULL,Female,Hispanic,02/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +66349,76833,69559,PRETRIAL,Arboleda,Jessica,NULL,Female,Hispanic,02/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59175,76854,69579,Probation,SWAIN,PATRICIA,ANN,Female,Caucasian,06/06/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +59175,76854,69579,Probation,SWAIN,PATRICIA,ANN,Female,Caucasian,06/06/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +59175,76854,69579,Probation,SWAIN,PATRICIA,ANN,Female,Caucasian,06/06/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66364,76856,69581,PRETRIAL,KENNEY,JODY,NULL,Female,Caucasian,06/07/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/19/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +66364,76856,69581,PRETRIAL,KENNEY,JODY,NULL,Female,Caucasian,06/07/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/19/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +66364,76856,69581,PRETRIAL,KENNEY,JODY,NULL,Female,Caucasian,06/07/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +51662,76841,69566,PRETRIAL,GOODLEY,DERRICK,FONDEL,Male,African-American,11/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +51662,76841,69566,PRETRIAL,GOODLEY,DERRICK,FONDEL,Male,African-American,11/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +51662,76841,69566,PRETRIAL,GOODLEY,DERRICK,FONDEL,Male,African-American,11/14/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/19/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +31001,76875,29998,PRETRIAL,Maxi,Peter,NULL,Male,Caucasian,12/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/20/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,Copy,1,0 +31001,76875,29998,PRETRIAL,Maxi,Peter,NULL,Male,Caucasian,12/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/20/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,Copy,1,0 +31001,76875,29998,PRETRIAL,Maxi,Peter,NULL,Male,Caucasian,12/02/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +66368,76862,69586,PRETRIAL,Wiltshire,Michael,NULL,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,2,Medium,7,Risk of Violence,-1.5,6,Medium,New,1,0 +66368,76862,69586,PRETRIAL,Wiltshire,Michael,NULL,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +66368,76862,69586,PRETRIAL,Wiltshire,Michael,NULL,Male,African-American,04/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66374,76869,69592,PRETRIAL,Ohuoha,Dammylin,NULL,Male,African-American,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +66374,76869,69592,PRETRIAL,Ohuoha,Dammylin,NULL,Male,African-American,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +66374,76869,69592,PRETRIAL,Ohuoha,Dammylin,NULL,Male,African-American,11/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +23352,76859,22542,PRETRIAL,DAVIS,EDWIN,NULL,Male,African-American,05/13/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,Copy,1,0 +23352,76859,22542,PRETRIAL,DAVIS,EDWIN,NULL,Male,African-American,05/13/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,Copy,1,0 +23352,76859,22542,PRETRIAL,DAVIS,EDWIN,NULL,Male,African-American,05/13/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +66375,76872,69594,PRETRIAL,Lam,Kwai,NULL,Male,Caucasian,10/15/37,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,1,Low,7,Risk of Violence,-4.32,1,Low,New,1,0 +66375,76872,69594,PRETRIAL,Lam,Kwai,NULL,Male,Caucasian,10/15/37,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,1,Low,8,Risk of Recidivism,-2.63,1,Low,New,1,0 +66375,76872,69594,PRETRIAL,Lam,Kwai,NULL,Male,Caucasian,10/15/37,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66370,76864,69588,PRETRIAL,Vassell,Avianna,NULL,Female,African-American,11/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +66370,76864,69588,PRETRIAL,Vassell,Avianna,NULL,Female,African-American,11/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +66370,76864,69588,PRETRIAL,Vassell,Avianna,NULL,Female,African-American,11/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +16947,76867,16257,PRETRIAL,SETTLE,DAVID,NULL,Male,Caucasian,10/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,Copy,1,0 +16947,76867,16257,PRETRIAL,SETTLE,DAVID,NULL,Male,Caucasian,10/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,Copy,1,0 +16947,76867,16257,PRETRIAL,SETTLE,DAVID,NULL,Male,Caucasian,10/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +66366,76860,69584,PRETRIAL,Archambault,Eugene,NULL,Male,Caucasian,11/22/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +66366,76860,69584,PRETRIAL,Archambault,Eugene,NULL,Male,Caucasian,11/22/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +66366,76860,69584,PRETRIAL,Archambault,Eugene,NULL,Male,Caucasian,11/22/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66371,76865,69589,PRETRIAL,LORENTE,OTNIEL,NULL,Male,Caucasian,10/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/20/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +66371,76865,69589,PRETRIAL,LORENTE,OTNIEL,NULL,Male,Caucasian,10/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/20/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +66371,76865,69589,PRETRIAL,LORENTE,OTNIEL,NULL,Male,Caucasian,10/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +43415,76870,69593,PRETRIAL,Manbeck,Gemini,NULL,Female,Caucasian,08/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +43415,76870,69593,PRETRIAL,Manbeck,Gemini,NULL,Female,Caucasian,08/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +43415,76870,69593,PRETRIAL,Manbeck,Gemini,NULL,Female,Caucasian,08/29/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66377,76874,69596,PRETRIAL,Salcedo,David,Anthony,Male,Caucasian,01/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +66377,76874,69596,PRETRIAL,Salcedo,David,Anthony,Male,Caucasian,01/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +66377,76874,69596,PRETRIAL,Salcedo,David,Anthony,Male,Caucasian,01/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66372,76866,69590,PRETRIAL,JORDAN,MATTHEW,NULL,Male,Caucasian,03/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.42,3,Low,New,1,0 +66372,76866,69590,PRETRIAL,JORDAN,MATTHEW,NULL,Male,Caucasian,03/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +66372,76866,69590,PRETRIAL,JORDAN,MATTHEW,NULL,Male,Caucasian,03/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66376,76873,69595,PRETRIAL,Iqubal,Muhammad,salman,Male,Caucasian,04/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,New,1,0 +66376,76873,69595,PRETRIAL,Iqubal,Muhammad,salman,Male,Caucasian,04/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,9,High,New,1,0 +66376,76873,69595,PRETRIAL,Iqubal,Muhammad,salman,Male,Caucasian,04/02/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66367,76861,69585,PRETRIAL,WRIGHT,JAWAN,VINCENT,Male,African-American,04/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,4,High,7,Risk of Violence,-1.07,8,High,New,1,0 +66367,76861,69585,PRETRIAL,WRIGHT,JAWAN,VINCENT,Male,African-American,04/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,4,High,8,Risk of Recidivism,0.81,10,High,New,1,0 +66367,76861,69585,PRETRIAL,WRIGHT,JAWAN,VINCENT,Male,African-American,04/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66373,76868,69591,PRETRIAL,BADILLO,STEVE,NULL,Male,Caucasian,09/02/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +66373,76868,69591,PRETRIAL,BADILLO,STEVE,NULL,Male,Caucasian,09/02/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +66373,76868,69591,PRETRIAL,BADILLO,STEVE,NULL,Male,Caucasian,09/02/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +15599,76871,14922,PRETRIAL,SPENCER,TRAVIS,DEVION,Male,African-American,07/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.32,3,Low,Copy,1,0 +15599,76871,14922,PRETRIAL,SPENCER,TRAVIS,DEVION,Male,African-American,07/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,Copy,1,0 +15599,76871,14922,PRETRIAL,SPENCER,TRAVIS,DEVION,Male,African-American,07/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +66369,76863,69587,PRETRIAL,Ahmed,Tyler,NULL,Male,Caucasian,03/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +66369,76863,69587,PRETRIAL,Ahmed,Tyler,NULL,Male,Caucasian,03/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +66369,76863,69587,PRETRIAL,Ahmed,Tyler,NULL,Male,Caucasian,03/14/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66378,76876,69597,PRETRIAL,Sanchez,Johana,NULL,Female,Hispanic,03/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +66378,76876,69597,PRETRIAL,Sanchez,Johana,NULL,Female,Hispanic,03/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +66378,76876,69597,PRETRIAL,Sanchez,Johana,NULL,Female,Hispanic,03/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/20/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +63730,76889,66649,PRETRIAL,SOLON,ERNST,NULL,Male,African-American,05/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,Copy,1,0 +63730,76889,66649,PRETRIAL,SOLON,ERNST,NULL,Male,African-American,05/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,Copy,1,0 +63730,76889,66649,PRETRIAL,SOLON,ERNST,NULL,Male,African-American,05/12/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +66382,76884,69603,PRETRIAL,ADAMS,RAYMOND,JOSEPH,Male,Caucasian,12/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +66382,76884,69603,PRETRIAL,ADAMS,RAYMOND,JOSEPH,Male,Caucasian,12/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +66382,76884,69603,PRETRIAL,ADAMS,RAYMOND,JOSEPH,Male,Caucasian,12/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66389,76892,69610,PRETRIAL,Franklin,Marvin,Adrian,Male,Other,05/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/21/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +66389,76892,69610,PRETRIAL,Franklin,Marvin,Adrian,Male,Other,05/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/21/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +66389,76892,69610,PRETRIAL,Franklin,Marvin,Adrian,Male,Other,05/25/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66380,76878,69599,PRETRIAL,Smith,Braxton,NULL,Male,African-American,07/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,New,1,0 +66380,76878,69599,PRETRIAL,Smith,Braxton,NULL,Male,African-American,07/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +66380,76878,69599,PRETRIAL,Smith,Braxton,NULL,Male,African-American,07/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66392,76896,69613,PRETRIAL,Dover,Shekinah,NULL,Female,African-American,06/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +66392,76896,69613,PRETRIAL,Dover,Shekinah,NULL,Female,African-American,06/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +66392,76896,69613,PRETRIAL,Dover,Shekinah,NULL,Female,African-American,06/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57943,76882,69602,PRETRIAL,FRAZIER,DIJOHN,NULL,Male,African-American,02/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +57943,76882,69602,PRETRIAL,FRAZIER,DIJOHN,NULL,Male,African-American,02/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +57943,76882,69602,PRETRIAL,FRAZIER,DIJOHN,NULL,Male,African-American,02/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +47483,76880,69601,PRETRIAL,Haughton,Chartavious,M,Female,African-American,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +47483,76880,69601,PRETRIAL,Haughton,Chartavious,M,Female,African-American,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +47483,76880,69601,PRETRIAL,Haughton,Chartavious,M,Female,African-American,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66385,76887,69606,PRETRIAL,SMITH,SHANNON,MICHELE,Female,Caucasian,12/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +66385,76887,69606,PRETRIAL,SMITH,SHANNON,MICHELE,Female,Caucasian,12/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +66385,76887,69606,PRETRIAL,SMITH,SHANNON,MICHELE,Female,Caucasian,12/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66390,76894,69611,PRETRIAL,Gerald,Sara,NULL,Female,African-American,02/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/21/14 0:00,2,Medium,7,Risk of Violence,-2.37,3,Low,New,1,0 +66390,76894,69611,PRETRIAL,Gerald,Sara,NULL,Female,African-American,02/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,7,Medium,New,1,0 +66390,76894,69611,PRETRIAL,Gerald,Sara,NULL,Female,African-American,02/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/21/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +66388,76891,69609,PRETRIAL,Dhanoolal,Mickel,Anthony,Male,Other,01/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/21/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +66388,76891,69609,PRETRIAL,Dhanoolal,Mickel,Anthony,Male,Other,01/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/21/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +66388,76891,69609,PRETRIAL,Dhanoolal,Mickel,Anthony,Male,Other,01/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66391,76895,69612,PRETRIAL,berkheimer,edward,NULL,Male,Caucasian,06/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +66391,76895,69612,PRETRIAL,berkheimer,edward,NULL,Male,Caucasian,06/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +66391,76895,69612,PRETRIAL,berkheimer,edward,NULL,Male,Caucasian,06/16/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66381,76879,69600,PRETRIAL,Theoc,Andy,NULL,Male,African-American,12/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +66381,76879,69600,PRETRIAL,Theoc,Andy,NULL,Male,African-American,12/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +66381,76879,69600,PRETRIAL,Theoc,Andy,NULL,Male,African-American,12/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +24998,76881,56812,PRETRIAL,RODGERS,DESIREE,NULL,Female,Caucasian,06/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +24998,76881,56812,PRETRIAL,RODGERS,DESIREE,NULL,Female,Caucasian,06/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,8,High,Copy,1,0 +24998,76881,56812,PRETRIAL,RODGERS,DESIREE,NULL,Female,Caucasian,06/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +66384,76886,69605,PRETRIAL,Vera,Henry,NULL,Male,Hispanic,01/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +66384,76886,69605,PRETRIAL,Vera,Henry,NULL,Male,Hispanic,01/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +66384,76886,69605,PRETRIAL,Vera,Henry,NULL,Male,Hispanic,01/06/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66386,76888,69607,PRETRIAL,RADOCK,John,CHARLES,Male,Caucasian,12/31/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/21/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +66386,76888,69607,PRETRIAL,RADOCK,John,CHARLES,Male,Caucasian,12/31/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/21/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +66386,76888,69607,PRETRIAL,RADOCK,John,CHARLES,Male,Caucasian,12/31/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66383,76885,69604,PRETRIAL,Anglin,Antonia,NULL,Female,Other,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +66383,76885,69604,PRETRIAL,Anglin,Antonia,NULL,Female,Other,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +66383,76885,69604,PRETRIAL,Anglin,Antonia,NULL,Female,Other,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +61605,76893,64194,PRETRIAL,etienne,evintz,NULL,Male,African-American,08/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.78,2,Low,Copy,1,0 +61605,76893,64194,PRETRIAL,etienne,evintz,NULL,Male,African-American,08/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.03,10,High,Copy,1,0 +61605,76893,64194,PRETRIAL,etienne,evintz,NULL,Male,African-American,08/07/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +40897,76883,40545,PRETRIAL,Key,Jw,NULL,Male,African-American,02/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,Copy,1,0 +40897,76883,40545,PRETRIAL,Key,Jw,NULL,Male,African-American,02/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,Copy,1,0 +40897,76883,40545,PRETRIAL,Key,Jw,NULL,Male,African-American,02/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +66379,76877,69598,PRETRIAL,Jewel,Randy,M,Male,African-American,02/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +66379,76877,69598,PRETRIAL,Jewel,Randy,M,Male,African-American,02/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,4,High,8,Risk of Recidivism,0.53,9,High,New,1,0 +66379,76877,69598,PRETRIAL,Jewel,Randy,M,Male,African-American,02/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/21/14 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66387,76890,69608,PRETRIAL,Genno,Dominic,NULL,Male,Caucasian,12/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/21/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +66387,76890,69608,PRETRIAL,Genno,Dominic,NULL,Male,Caucasian,12/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/21/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +66387,76890,69608,PRETRIAL,Genno,Dominic,NULL,Male,Caucasian,12/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66402,76911,69625,Probation,Gomezospino,Luis,NULL,Male,Hispanic,11/18/87,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/22/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +66402,76911,69625,Probation,Gomezospino,Luis,NULL,Male,Hispanic,11/18/87,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/22/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +66402,76911,69625,Probation,Gomezospino,Luis,NULL,Male,Hispanic,11/18/87,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66408,76919,69632,Probation,Ikonne,Gary,NULL,Male,African-American,10/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/22/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +66408,76919,69632,Probation,Ikonne,Gary,NULL,Male,African-American,10/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/22/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +66408,76919,69632,Probation,Ikonne,Gary,NULL,Male,African-American,10/24/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66393,76898,69615,PRETRIAL,Myers,Stephanie,Lasha,Female,Caucasian,10/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +66393,76898,69615,PRETRIAL,Myers,Stephanie,Lasha,Female,Caucasian,10/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +66393,76898,69615,PRETRIAL,Myers,Stephanie,Lasha,Female,Caucasian,10/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +38809,76927,69640,PRETRIAL,SEVERINO,MARCELO,NULL,Male,African-American,03/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/22/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +38809,76927,69640,PRETRIAL,SEVERINO,MARCELO,NULL,Male,African-American,03/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/22/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +38809,76927,69640,PRETRIAL,SEVERINO,MARCELO,NULL,Male,African-American,03/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65947,76906,69130,PRETRIAL,RUIZ,RICARDO,NULL,Male,African-American,01/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/22/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,Copy,1,0 +65947,76906,69130,PRETRIAL,RUIZ,RICARDO,NULL,Male,African-American,01/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/22/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,Copy,1,0 +65947,76906,69130,PRETRIAL,RUIZ,RICARDO,NULL,Male,African-American,01/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +35922,76932,69645,PRETRIAL,Goldsby,Avis,NULL,Male,African-American,07/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,4,High,7,Risk of Violence,-0.64,9,High,New,1,0 +35922,76932,69645,PRETRIAL,Goldsby,Avis,NULL,Male,African-American,07/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,4,High,8,Risk of Recidivism,0.44,9,High,New,1,0 +35922,76932,69645,PRETRIAL,Goldsby,Avis,NULL,Male,African-American,07/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +25499,76902,24663,PRETRIAL,Brown,Desmond,NULL,Male,African-American,01/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,Copy,1,0 +25499,76902,24663,PRETRIAL,Brown,Desmond,NULL,Male,African-American,01/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,Copy,1,0 +25499,76902,24663,PRETRIAL,Brown,Desmond,NULL,Male,African-American,01/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +66412,76923,69636,Probation,Bieber,Wayne,NULL,Male,Caucasian,07/22/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/22/14 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +66412,76923,69636,Probation,Bieber,Wayne,NULL,Male,Caucasian,07/22/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/22/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +66412,76923,69636,Probation,Bieber,Wayne,NULL,Male,Caucasian,07/22/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66416,76930,69643,Probation,fernandez,marysol,NULL,Female,Hispanic,02/16/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/22/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +66416,76930,69643,Probation,fernandez,marysol,NULL,Female,Hispanic,02/16/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/22/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +66416,76930,69643,Probation,fernandez,marysol,NULL,Female,Hispanic,02/16/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66398,76904,69620,PRETRIAL,JAYCOX,CHARLES,ALFRED,Male,Caucasian,09/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,New,1,0 +66398,76904,69620,PRETRIAL,JAYCOX,CHARLES,ALFRED,Male,Caucasian,09/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +66398,76904,69620,PRETRIAL,JAYCOX,CHARLES,ALFRED,Male,Caucasian,09/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66395,76900,69617,PRETRIAL,BRITO,PEDRO,O,Male,Hispanic,10/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +66395,76900,69617,PRETRIAL,BRITO,PEDRO,O,Male,Hispanic,10/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +66395,76900,69617,PRETRIAL,BRITO,PEDRO,O,Male,Hispanic,10/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +15866,76921,69634,Probation,robbins,david,NULL,Male,Hispanic,04/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/22/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +15866,76921,69634,Probation,robbins,david,NULL,Male,Hispanic,04/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/22/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +15866,76921,69634,Probation,robbins,david,NULL,Male,Hispanic,04/20/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +66410,76922,69635,Probation,Caraballo,Gary,John,Male,Hispanic,10/14/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/22/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +66410,76922,69635,Probation,Caraballo,Gary,John,Male,Hispanic,10/14/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/22/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +66410,76922,69635,Probation,Caraballo,Gary,John,Male,Hispanic,10/14/63,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66396,76901,69618,PRETRIAL,Escobar,Luisa,NULL,Female,Hispanic,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +66396,76901,69618,PRETRIAL,Escobar,Luisa,NULL,Female,Hispanic,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +66396,76901,69618,PRETRIAL,Escobar,Luisa,NULL,Female,Hispanic,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66405,76915,69629,PRETRIAL,Woebke,Ronald,NULL,Male,Caucasian,08/19/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +66405,76915,69629,PRETRIAL,Woebke,Ronald,NULL,Male,Caucasian,08/19/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +66405,76915,69629,PRETRIAL,Woebke,Ronald,NULL,Male,Caucasian,08/19/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66394,76899,69616,PRETRIAL,Aguirre-Dominguez,German,NULL,Male,Hispanic,06/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +66394,76899,69616,PRETRIAL,Aguirre-Dominguez,German,NULL,Male,Hispanic,06/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +66394,76899,69616,PRETRIAL,Aguirre-Dominguez,German,NULL,Male,Hispanic,06/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66406,76917,69630,PRETRIAL,Ursia,James,NULL,Male,Caucasian,09/26/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/22/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +66406,76917,69630,PRETRIAL,Ursia,James,NULL,Male,Caucasian,09/26/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/22/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +66406,76917,69630,PRETRIAL,Ursia,James,NULL,Male,Caucasian,09/26/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66397,76903,69619,PRETRIAL,Huff,John,NULL,Male,Caucasian,06/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +66397,76903,69619,PRETRIAL,Huff,John,NULL,Male,Caucasian,06/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +66397,76903,69619,PRETRIAL,Huff,John,NULL,Male,Caucasian,06/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66417,76929,69642,Probation,Martinez,Yanelis,NULL,Female,Hispanic,07/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/22/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +66417,76929,69642,Probation,Martinez,Yanelis,NULL,Female,Hispanic,07/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/22/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +66417,76929,69642,Probation,Martinez,Yanelis,NULL,Female,Hispanic,07/05/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66400,76908,69623,Probation,Mciver,Kevin,Michael,Male,Caucasian,04/19/61,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/22/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +66400,76908,69623,Probation,Mciver,Kevin,Michael,Male,Caucasian,04/19/61,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/22/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +66400,76908,69623,Probation,Mciver,Kevin,Michael,Male,Caucasian,04/19/61,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66414,76926,69639,Probation,mayo,michelle,NULL,Female,Caucasian,01/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/22/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +66414,76926,69639,Probation,mayo,michelle,NULL,Female,Caucasian,01/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/22/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +66414,76926,69639,Probation,mayo,michelle,NULL,Female,Caucasian,01/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +9238,76905,69621,Probation,Jemmott,Teshane,NULL,Male,African-American,05/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +9238,76905,69621,Probation,Jemmott,Teshane,NULL,Male,African-American,05/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +9238,76905,69621,Probation,Jemmott,Teshane,NULL,Male,African-American,05/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66403,76912,69626,PRETRIAL,Omar,Mohammed,NULL,Male,African-American,09/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +66403,76912,69626,PRETRIAL,Omar,Mohammed,NULL,Male,African-American,09/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +66403,76912,69626,PRETRIAL,Omar,Mohammed,NULL,Male,African-American,09/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66415,76928,69641,PRETRIAL,Vetensky,Frederick,NULL,Male,Caucasian,02/23/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,9/22/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +66415,76928,69641,PRETRIAL,Vetensky,Frederick,NULL,Male,Caucasian,02/23/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,9/22/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +66415,76928,69641,PRETRIAL,Vetensky,Frederick,NULL,Male,Caucasian,02/23/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66407,76918,69631,Probation,miller,jeffrey,NULL,Male,Caucasian,07/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +66407,76918,69631,Probation,miller,jeffrey,NULL,Male,Caucasian,07/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +66407,76918,69631,Probation,miller,jeffrey,NULL,Male,Caucasian,07/22/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66401,76910,69624,PRETRIAL,Trinidad,Mayling,NULL,Female,Hispanic,04/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/22/14 0:00,2,Medium,7,Risk of Violence,-2.49,3,Low,New,1,0 +66401,76910,69624,PRETRIAL,Trinidad,Mayling,NULL,Female,Hispanic,04/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +66401,76910,69624,PRETRIAL,Trinidad,Mayling,NULL,Female,Hispanic,04/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/22/14 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,New,1,0 +17436,76897,69614,PRETRIAL,SKINNER,TERRANCE,NULL,Male,African-American,07/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +17436,76897,69614,PRETRIAL,SKINNER,TERRANCE,NULL,Male,African-American,07/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +17436,76897,69614,PRETRIAL,SKINNER,TERRANCE,NULL,Male,African-American,07/15/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66418,76931,69644,PRETRIAL,NEFTELBERG,ROBERT,JOHN,Male,Caucasian,05/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/22/14 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +66418,76931,69644,PRETRIAL,NEFTELBERG,ROBERT,JOHN,Male,Caucasian,05/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/22/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +66418,76931,69644,PRETRIAL,NEFTELBERG,ROBERT,JOHN,Male,Caucasian,05/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66421,76936,69649,PRETRIAL,JONES,DEMETRIA,MONIQUE,Male,African-American,11/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +66421,76936,69649,PRETRIAL,JONES,DEMETRIA,MONIQUE,Male,African-American,11/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +66421,76936,69649,PRETRIAL,JONES,DEMETRIA,MONIQUE,Male,African-American,11/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66442,76965,69674,PRETRIAL,Lama,Kevin,NULL,Male,Caucasian,05/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,New,1,0 +66442,76965,69674,PRETRIAL,Lama,Kevin,NULL,Male,Caucasian,05/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.53,9,High,New,1,0 +66442,76965,69674,PRETRIAL,Lama,Kevin,NULL,Male,Caucasian,05/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,9/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,41,10,High,New,1,0 +65947,76944,69130,PRETRIAL,RUIZ,RICARDO,NULL,Male,African-American,01/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,Copy,1,0 +65947,76944,69130,PRETRIAL,RUIZ,RICARDO,NULL,Male,African-American,01/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,Copy,1,0 +65947,76944,69130,PRETRIAL,RUIZ,RICARDO,NULL,Male,African-American,01/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +66435,76957,69667,Probation,Krygsman,Arend,NULL,Male,Hispanic,05/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +66435,76957,69667,Probation,Krygsman,Arend,NULL,Male,Hispanic,05/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +66435,76957,69667,Probation,Krygsman,Arend,NULL,Male,Hispanic,05/30/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66429,76949,69659,PRETRIAL,Ford,Deon,Deontae,Male,African-American,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.02,8,High,New,1,0 +66429,76949,69659,PRETRIAL,Ford,Deon,Deontae,Male,African-American,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +66429,76949,69659,PRETRIAL,Ford,Deon,Deontae,Male,African-American,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66423,76939,69652,PRETRIAL,Flemming,Nicole,Scophia,Female,African-American,12/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +66423,76939,69652,PRETRIAL,Flemming,Nicole,Scophia,Female,African-American,12/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-1.41,2,Low,New,1,0 +66423,76939,69652,PRETRIAL,Flemming,Nicole,Scophia,Female,African-American,12/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +7850,76978,69687,PRETRIAL,GARVEY,BRIAN,S,Male,Caucasian,10/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,2,Medium,7,Risk of Violence,-2.99,1,Low,New,1,0 +7850,76978,69687,PRETRIAL,GARVEY,BRIAN,S,Male,Caucasian,10/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +7850,76978,69687,PRETRIAL,GARVEY,BRIAN,S,Male,Caucasian,10/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66434,76955,69665,Probation,Lafontant,Gregory,NULL,Male,African-American,11/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/23/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +66434,76955,69665,Probation,Lafontant,Gregory,NULL,Male,African-American,11/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/23/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +66434,76955,69665,Probation,Lafontant,Gregory,NULL,Male,African-American,11/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66419,76933,69646,PRETRIAL,Russell,Cheryl,NULL,Female,African-American,05/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +66419,76933,69646,PRETRIAL,Russell,Cheryl,NULL,Female,African-American,05/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +66419,76933,69646,PRETRIAL,Russell,Cheryl,NULL,Female,African-American,05/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66420,76934,69647,PRETRIAL,Julin,Xavier,Alcides,Male,Caucasian,04/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +66420,76934,69647,PRETRIAL,Julin,Xavier,Alcides,Male,Caucasian,04/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +66420,76934,69647,PRETRIAL,Julin,Xavier,Alcides,Male,Caucasian,04/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +57386,76941,69654,PRETRIAL,Daniels,Kevin,NULL,Male,African-American,03/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +57386,76941,69654,PRETRIAL,Daniels,Kevin,NULL,Male,African-American,03/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +57386,76941,69654,PRETRIAL,Daniels,Kevin,NULL,Male,African-American,03/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66450,76975,69684,Probation,therrien,brian,NULL,Male,Caucasian,03/30/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +66450,76975,69684,Probation,therrien,brian,NULL,Male,Caucasian,03/30/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +66450,76975,69684,Probation,therrien,brian,NULL,Male,Caucasian,03/30/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66433,76954,69664,Probation,henley,shion,NULL,Male,African-American,09/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +66433,76954,69664,Probation,henley,shion,NULL,Male,African-American,09/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +66433,76954,69664,Probation,henley,shion,NULL,Male,African-American,09/14/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +31309,76938,69651,PRETRIAL,Dailey,Keonah,NULL,Female,African-American,11/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +31309,76938,69651,PRETRIAL,Dailey,Keonah,NULL,Female,African-American,11/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,4,High,8,Risk of Recidivism,0.27,9,High,New,1,0 +31309,76938,69651,PRETRIAL,Dailey,Keonah,NULL,Female,African-American,11/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66441,76964,69673,Probation,McCabe,Corey,NULL,Male,Caucasian,02/27/91,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Married,9/23/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +66441,76964,69673,Probation,McCabe,Corey,NULL,Male,Caucasian,02/27/91,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Married,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +66441,76964,69673,Probation,McCabe,Corey,NULL,Male,Caucasian,02/27/91,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Married,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +56500,76971,69680,PRETRIAL,PRESTON,MICHAEL,NULL,Male,Caucasian,07/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +56500,76971,69680,PRETRIAL,PRESTON,MICHAEL,NULL,Male,Caucasian,07/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +56500,76971,69680,PRETRIAL,PRESTON,MICHAEL,NULL,Male,Caucasian,07/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66430,76950,69660,Probation,Mcknight,Kevin,NULL,Male,Caucasian,11/05/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/23/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +66430,76950,69660,Probation,Mcknight,Kevin,NULL,Male,Caucasian,11/05/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +66430,76950,69660,Probation,Mcknight,Kevin,NULL,Male,Caucasian,11/05/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66448,76973,69682,PRETRIAL,WEAVER,NANCY,NULL,Female,Caucasian,12/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +66448,76973,69682,PRETRIAL,WEAVER,NANCY,NULL,Female,Caucasian,12/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,7,Medium,New,1,0 +66448,76973,69682,PRETRIAL,WEAVER,NANCY,NULL,Female,Caucasian,12/17/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +52939,76980,54339,DRRD,Burgess,Voltaire,NULL,Male,African-American,07/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,4,High,7,Risk of Violence,-0.82,9,High,Copy,1,0 +52939,76980,54339,DRRD,Burgess,Voltaire,NULL,Male,African-American,07/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,4,High,8,Risk of Recidivism,0.64,9,High,Copy,1,0 +52939,76980,54339,DRRD,Burgess,Voltaire,NULL,Male,African-American,07/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,4,High,18,Risk of Failure to Appear,36,10,High,Copy,1,0 +65897,76945,69066,PRETRIAL,Stroud,Anthony,Romelo,Male,African-American,08/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,Copy,1,0 +65897,76945,69066,PRETRIAL,Stroud,Anthony,Romelo,Male,African-American,08/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,Copy,1,0 +65897,76945,69066,PRETRIAL,Stroud,Anthony,Romelo,Male,African-American,08/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +66426,76943,69656,PRETRIAL,Tatum,Sterling,NULL,Male,African-American,11/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +66426,76943,69656,PRETRIAL,Tatum,Sterling,NULL,Male,African-American,11/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +66426,76943,69656,PRETRIAL,Tatum,Sterling,NULL,Male,African-American,11/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65657,76946,68811,PRETRIAL,CANZANI,JEFFREY,NULL,Male,Caucasian,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,Copy,1,0 +65657,76946,68811,PRETRIAL,CANZANI,JEFFREY,NULL,Male,Caucasian,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,Copy,1,0 +65657,76946,68811,PRETRIAL,CANZANI,JEFFREY,NULL,Male,Caucasian,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +66444,76967,69676,Probation,MARTINEZ,stephanie,NULL,Female,Hispanic,04/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +66444,76967,69676,Probation,MARTINEZ,stephanie,NULL,Female,Hispanic,04/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +66444,76967,69676,Probation,MARTINEZ,stephanie,NULL,Female,Hispanic,04/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66440,76963,69672,PRETRIAL,Washburn,Donald,Ray,Male,Caucasian,09/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/23/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +66440,76963,69672,PRETRIAL,Washburn,Donald,Ray,Male,Caucasian,09/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/23/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +66440,76963,69672,PRETRIAL,Washburn,Donald,Ray,Male,Caucasian,09/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66425,76942,69655,PRETRIAL,Arcila,Anthony,NULL,Male,Caucasian,07/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +66425,76942,69655,PRETRIAL,Arcila,Anthony,NULL,Male,Caucasian,07/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +66425,76942,69655,PRETRIAL,Arcila,Anthony,NULL,Male,Caucasian,07/21/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66422,76937,69650,PRETRIAL,Almonte,Jaysa,NULL,Female,African-American,09/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +66422,76937,69650,PRETRIAL,Almonte,Jaysa,NULL,Female,African-American,09/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +66422,76937,69650,PRETRIAL,Almonte,Jaysa,NULL,Female,African-American,09/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66431,76951,69661,PRETRIAL,pryzmocki,michael,NULL,Male,Caucasian,05/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/23/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +66431,76951,69661,PRETRIAL,pryzmocki,michael,NULL,Male,Caucasian,05/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +66431,76951,69661,PRETRIAL,pryzmocki,michael,NULL,Male,Caucasian,05/24/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66453,76979,69688,Probation,frater,robert,NULL,Male,African-American,05/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +66453,76979,69688,Probation,frater,robert,NULL,Male,African-American,05/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +66453,76979,69688,Probation,frater,robert,NULL,Male,African-American,05/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66454,76981,69689,PRETRIAL,CARTER,ARTLEY,NULL,Male,Other,04/25/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/23/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +66454,76981,69689,PRETRIAL,CARTER,ARTLEY,NULL,Male,Other,04/25/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/23/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +66454,76981,69689,PRETRIAL,CARTER,ARTLEY,NULL,Male,Other,04/25/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66436,76958,69668,Probation,meredith,bryan,NULL,Male,Caucasian,02/05/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/23/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +66436,76958,69668,Probation,meredith,bryan,NULL,Male,Caucasian,02/05/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/23/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +66436,76958,69668,Probation,meredith,bryan,NULL,Male,Caucasian,02/05/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66438,76960,69670,Probation,Richter,Kordell,Lee,Male,Caucasian,11/10/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +66438,76960,69670,Probation,Richter,Kordell,Lee,Male,Caucasian,11/10/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +66438,76960,69670,Probation,Richter,Kordell,Lee,Male,Caucasian,11/10/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +18039,76935,69648,DRRD,Moses,John,NULL,Male,African-American,12/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +18039,76935,69648,DRRD,Moses,John,NULL,Male,African-American,12/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +18039,76935,69648,DRRD,Moses,John,NULL,Male,African-American,12/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65949,76953,69663,PRETRIAL,Niblack,Raymond,NULL,Male,Caucasian,09/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +65949,76953,69663,PRETRIAL,Niblack,Raymond,NULL,Male,Caucasian,09/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +65949,76953,69663,PRETRIAL,Niblack,Raymond,NULL,Male,Caucasian,09/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +66424,76940,69653,PRETRIAL,Smith,Shawn,G,Male,African-American,07/10/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +66424,76940,69653,PRETRIAL,Smith,Shawn,G,Male,African-American,07/10/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +66424,76940,69653,PRETRIAL,Smith,Shawn,G,Male,African-American,07/10/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66439,76961,69671,Probation,andrade,rodolpho,NULL,Male,Caucasian,04/27/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +66439,76961,69671,Probation,andrade,rodolpho,NULL,Male,Caucasian,04/27/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +66439,76961,69671,Probation,andrade,rodolpho,NULL,Male,Caucasian,04/27/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66449,76974,69683,Probation,joshua,askew,NULL,Male,African-American,11/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +66449,76974,69683,Probation,joshua,askew,NULL,Male,African-American,11/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +66449,76974,69683,Probation,joshua,askew,NULL,Male,African-American,11/02/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66428,76948,69658,Probation,Wilcox,Kourtney,Marie,Female,Caucasian,04/04/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +66428,76948,69658,Probation,Wilcox,Kourtney,Marie,Female,Caucasian,04/04/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +66428,76948,69658,Probation,Wilcox,Kourtney,Marie,Female,Caucasian,04/04/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66445,76969,69678,PRETRIAL,MIKELSTEIN,YONATHAN,MOSHE,Male,Hispanic,12/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +66445,76969,69678,PRETRIAL,MIKELSTEIN,YONATHAN,MOSHE,Male,Hispanic,12/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +66445,76969,69678,PRETRIAL,MIKELSTEIN,YONATHAN,MOSHE,Male,Hispanic,12/01/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57681,76956,69666,PRETRIAL,ARCACORREDERAS,ANDRES,NULL,Male,Caucasian,12/05/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +57681,76956,69666,PRETRIAL,ARCACORREDERAS,ANDRES,NULL,Male,Caucasian,12/05/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +57681,76956,69666,PRETRIAL,ARCACORREDERAS,ANDRES,NULL,Male,Caucasian,12/05/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66479,77013,69719,Probation,obrecht,douglas,NULL,Male,Caucasian,01/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +66479,77013,69719,Probation,obrecht,douglas,NULL,Male,Caucasian,01/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +66479,77013,69719,Probation,obrecht,douglas,NULL,Male,Caucasian,01/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53728,76992,69700,PRETRIAL,Martinez,Tiffany,NULL,Female,Hispanic,01/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,4,High,7,Risk of Violence,-0.48,10,High,New,1,0 +53728,76992,69700,PRETRIAL,Martinez,Tiffany,NULL,Female,Hispanic,01/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,4,High,8,Risk of Recidivism,0.66,10,High,New,1,0 +53728,76992,69700,PRETRIAL,Martinez,Tiffany,NULL,Female,Hispanic,01/26/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,4,High,18,Risk of Failure to Appear,46,10,High,New,1,0 +41743,77011,41467,PRETRIAL,MOBLEY,GLENDA,NULL,Female,African-American,06/01/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,Copy,1,0 +41743,77011,41467,PRETRIAL,MOBLEY,GLENDA,NULL,Female,African-American,06/01/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,Copy,1,0 +41743,77011,41467,PRETRIAL,MOBLEY,GLENDA,NULL,Female,African-American,06/01/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,Copy,1,0 +66457,76984,69692,PRETRIAL,Brown,Carolyn,NULL,Female,African-American,10/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +66457,76984,69692,PRETRIAL,Brown,Carolyn,NULL,Female,African-American,10/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +66457,76984,69692,PRETRIAL,Brown,Carolyn,NULL,Female,African-American,10/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66484,77019,69725,Probation,pond,esharia,NULL,Female,African-American,08/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +66484,77019,69725,Probation,pond,esharia,NULL,Female,African-American,08/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,7,Medium,New,1,0 +66484,77019,69725,Probation,pond,esharia,NULL,Female,African-American,08/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66472,77005,69712,PRETRIAL,Castro,Adam,NULL,Male,Caucasian,09/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +66472,77005,69712,PRETRIAL,Castro,Adam,NULL,Male,Caucasian,09/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +66472,77005,69712,PRETRIAL,Castro,Adam,NULL,Male,Caucasian,09/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +29710,77008,69715,PRETRIAL,CORTES,DANIEL,NULL,Male,Caucasian,04/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +29710,77008,69715,PRETRIAL,CORTES,DANIEL,NULL,Male,Caucasian,04/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,4,High,8,Risk of Recidivism,0.36,9,High,New,1,0 +29710,77008,69715,PRETRIAL,CORTES,DANIEL,NULL,Male,Caucasian,04/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66470,77003,69710,PRETRIAL,aNDERSON,SEAN,NULL,Male,Caucasian,10/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +66470,77003,69710,PRETRIAL,aNDERSON,SEAN,NULL,Male,Caucasian,10/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +66470,77003,69710,PRETRIAL,aNDERSON,SEAN,NULL,Male,Caucasian,10/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66455,76982,69690,PRETRIAL,Perkins,James,NULL,Male,African-American,01/12/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +66455,76982,69690,PRETRIAL,Perkins,James,NULL,Male,African-American,01/12/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +66455,76982,69690,PRETRIAL,Perkins,James,NULL,Male,African-American,01/12/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66469,77000,69707,PRETRIAL,Beato,Gabriela,NULL,Female,Hispanic,05/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +66469,77000,69707,PRETRIAL,Beato,Gabriela,NULL,Female,Hispanic,05/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +66469,77000,69707,PRETRIAL,Beato,Gabriela,NULL,Female,Hispanic,05/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66474,77007,69714,PRETRIAL,Flora,Jaime,NULL,Female,Caucasian,12/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +66474,77007,69714,PRETRIAL,Flora,Jaime,NULL,Female,Caucasian,12/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +66474,77007,69714,PRETRIAL,Flora,Jaime,NULL,Female,Caucasian,12/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66475,77009,69716,Probation,GONZALEZ,JESSICA,NULL,Female,Hispanic,12/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +66475,77009,69716,Probation,GONZALEZ,JESSICA,NULL,Female,Hispanic,12/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +66475,77009,69716,Probation,GONZALEZ,JESSICA,NULL,Female,Hispanic,12/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66459,76986,69694,PRETRIAL,Keen,Emmanuel,NULL,Male,African-American,04/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +66459,76986,69694,PRETRIAL,Keen,Emmanuel,NULL,Male,African-American,04/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +66459,76986,69694,PRETRIAL,Keen,Emmanuel,NULL,Male,African-American,04/13/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +48681,77002,69709,PRETRIAL,Petersen,Julia,NULL,Female,Caucasian,05/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +48681,77002,69709,PRETRIAL,Petersen,Julia,NULL,Female,Caucasian,05/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,4,High,8,Risk of Recidivism,0.09,8,High,New,1,0 +48681,77002,69709,PRETRIAL,Petersen,Julia,NULL,Female,Caucasian,05/12/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +37023,77016,69722,PRETRIAL,Allen,Andra,NULL,Male,African-American,08/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +37023,77016,69722,PRETRIAL,Allen,Andra,NULL,Male,African-American,08/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +37023,77016,69722,PRETRIAL,Allen,Andra,NULL,Male,African-American,08/25/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66465,76993,69701,Probation,FIGUEROA,JESSICA,GLORIA,Female,Hispanic,11/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +66465,76993,69701,Probation,FIGUEROA,JESSICA,GLORIA,Female,Hispanic,11/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +66465,76993,69701,Probation,FIGUEROA,JESSICA,GLORIA,Female,Hispanic,11/19/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,2,Medium,18,Risk of Failure to Appear,29,9,High,New,1,0 +66467,76997,69705,PRETRIAL,STEPHENS,ANTHONY,NULL,Male,African-American,05/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +66467,76997,69705,PRETRIAL,STEPHENS,ANTHONY,NULL,Male,African-American,05/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +66467,76997,69705,PRETRIAL,STEPHENS,ANTHONY,NULL,Male,African-American,05/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66480,77014,69720,Probation,florence,Kevin,NULL,Male,Other,05/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +66480,77014,69720,Probation,florence,Kevin,NULL,Male,Other,05/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +66480,77014,69720,Probation,florence,Kevin,NULL,Male,Other,05/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +8602,77015,69721,PRETRIAL,McCauley,Michael,James,Male,Caucasian,09/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +8602,77015,69721,PRETRIAL,McCauley,Michael,James,Male,Caucasian,09/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +8602,77015,69721,PRETRIAL,McCauley,Michael,James,Male,Caucasian,09/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +66460,76987,69695,PRETRIAL,WATERS-PEREZ,CHRISTIAN,NULL,Male,Caucasian,12/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +66460,76987,69695,PRETRIAL,WATERS-PEREZ,CHRISTIAN,NULL,Male,Caucasian,12/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +66460,76987,69695,PRETRIAL,WATERS-PEREZ,CHRISTIAN,NULL,Male,Caucasian,12/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66458,76985,69693,PRETRIAL,CLERIE,ALAIN,RAYMOND,Male,Caucasian,05/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +66458,76985,69693,PRETRIAL,CLERIE,ALAIN,RAYMOND,Male,Caucasian,05/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +66458,76985,69693,PRETRIAL,CLERIE,ALAIN,RAYMOND,Male,Caucasian,05/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66462,76989,69697,Probation,Payne,Michael,NULL,Male,African-American,02/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +66462,76989,69697,Probation,Payne,Michael,NULL,Male,African-American,02/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +66462,76989,69697,Probation,Payne,Michael,NULL,Male,African-American,02/16/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66473,77006,69713,Probation,Bido,Jose,NULL,Male,Hispanic,01/30/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/24/14 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +66473,77006,69713,Probation,Bido,Jose,NULL,Male,Hispanic,01/30/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/24/14 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +66473,77006,69713,Probation,Bido,Jose,NULL,Male,Hispanic,01/30/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66476,77010,69717,Probation,Bautista,Catalino,NULL,Male,Hispanic,04/30/79,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/24/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +66476,77010,69717,Probation,Bautista,Catalino,NULL,Male,Hispanic,04/30/79,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/24/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +66476,77010,69717,Probation,Bautista,Catalino,NULL,Male,Hispanic,04/30/79,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66456,76983,69691,PRETRIAL,LOPEZCABRERA,LUIS,O,Male,Hispanic,10/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/24/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +66456,76983,69691,PRETRIAL,LOPEZCABRERA,LUIS,O,Male,Hispanic,10/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/24/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +66456,76983,69691,PRETRIAL,LOPEZCABRERA,LUIS,O,Male,Hispanic,10/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66478,77012,69718,Probation,Ormo,Gustavo,NULL,Male,Hispanic,02/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/24/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +66478,77012,69718,Probation,Ormo,Gustavo,NULL,Male,Hispanic,02/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/24/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +66478,77012,69718,Probation,Ormo,Gustavo,NULL,Male,Hispanic,02/10/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66468,76999,69706,PRETRIAL,MULHALL,CASEY,NULL,Male,Caucasian,09/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +66468,76999,69706,PRETRIAL,MULHALL,CASEY,NULL,Male,Caucasian,09/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +66468,76999,69706,PRETRIAL,MULHALL,CASEY,NULL,Male,Caucasian,09/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +66482,77017,69723,Probation,WIGGINS,EDGAR,NULL,Male,African-American,08/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +66482,77017,69723,Probation,WIGGINS,EDGAR,NULL,Male,African-American,08/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +66482,77017,69723,Probation,WIGGINS,EDGAR,NULL,Male,African-American,08/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66464,76991,69699,Probation,Urena,Angel,Ramon,Male,Hispanic,10/10/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/24/14 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +66464,76991,69699,Probation,Urena,Angel,Ramon,Male,Hispanic,10/10/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +66464,76991,69699,Probation,Urena,Angel,Ramon,Male,Hispanic,10/10/83,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/24/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66471,77004,69711,Probation,Gamm,Kenneth,Ray,Male,Caucasian,01/24/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/24/14 0:00,1,Low,7,Risk of Violence,-4.3,1,Low,New,1,0 +66471,77004,69711,Probation,Gamm,Kenneth,Ray,Male,Caucasian,01/24/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/24/14 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +66471,77004,69711,Probation,Gamm,Kenneth,Ray,Male,Caucasian,01/24/54,22,Risk and Prescreen,Intake,English,Other,Probation,Married,9/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66502,77038,69744,PRETRIAL,SIMS,SAMANTHA,NULL,Female,African-American,09/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +66502,77038,69744,PRETRIAL,SIMS,SAMANTHA,NULL,Female,African-American,09/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +66502,77038,69744,PRETRIAL,SIMS,SAMANTHA,NULL,Female,African-American,09/14/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66490,77025,69731,PRETRIAL,Acosta,Jose,NULL,Male,Caucasian,12/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +66490,77025,69731,PRETRIAL,Acosta,Jose,NULL,Male,Caucasian,12/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +66490,77025,69731,PRETRIAL,Acosta,Jose,NULL,Male,Caucasian,12/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +20076,77033,69739,PRETRIAL,CHESTNUT,JEROME,V,Male,African-American,07/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +20076,77033,69739,PRETRIAL,CHESTNUT,JEROME,V,Male,African-American,07/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +20076,77033,69739,PRETRIAL,CHESTNUT,JEROME,V,Male,African-American,07/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66485,77020,69726,PRETRIAL,Kennon,Tanya,Ingrid,Female,Caucasian,04/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/25/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +66485,77020,69726,PRETRIAL,Kennon,Tanya,Ingrid,Female,Caucasian,04/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/25/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +66485,77020,69726,PRETRIAL,Kennon,Tanya,Ingrid,Female,Caucasian,04/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66491,77027,69733,PRETRIAL,Proctor,Michael,Phillip,Male,Caucasian,02/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +66491,77027,69733,PRETRIAL,Proctor,Michael,Phillip,Male,Caucasian,02/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +66491,77027,69733,PRETRIAL,Proctor,Michael,Phillip,Male,Caucasian,02/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66500,77036,69742,PRETRIAL,Prince,Paul,NULL,Male,African-American,06/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +66500,77036,69742,PRETRIAL,Prince,Paul,NULL,Male,African-American,06/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +66500,77036,69742,PRETRIAL,Prince,Paul,NULL,Male,African-American,06/15/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66489,77024,69730,PRETRIAL,ROBINSON,SHEIDAN,NULL,Male,African-American,05/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +66489,77024,69730,PRETRIAL,ROBINSON,SHEIDAN,NULL,Male,African-American,05/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +66489,77024,69730,PRETRIAL,ROBINSON,SHEIDAN,NULL,Male,African-American,05/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66493,77028,69734,PRETRIAL,TINDALL,MARK,NULL,Male,African-American,02/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +66493,77028,69734,PRETRIAL,TINDALL,MARK,NULL,Male,African-American,02/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +66493,77028,69734,PRETRIAL,TINDALL,MARK,NULL,Male,African-American,02/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66503,77039,69745,Broward County,Lopez,Elvis,NULL,Male,Hispanic,12/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.31,1,Low,New,1,0 +66503,77039,69745,Broward County,Lopez,Elvis,NULL,Male,Hispanic,12/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +66503,77039,69745,Broward County,Lopez,Elvis,NULL,Male,Hispanic,12/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +66498,77032,69738,PRETRIAL,JAMES,ERICA,NULL,Female,African-American,07/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +66498,77032,69738,PRETRIAL,JAMES,ERICA,NULL,Female,African-American,07/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +66498,77032,69738,PRETRIAL,JAMES,ERICA,NULL,Female,African-American,07/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +57550,77035,69741,Probation,Harris,Robert,NULL,Male,African-American,12/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +57550,77035,69741,Probation,Harris,Robert,NULL,Male,African-American,12/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +57550,77035,69741,Probation,Harris,Robert,NULL,Male,African-American,12/16/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +66488,77023,69729,PRETRIAL,THULLER,ROBSON,RODRIGUEZ,Male,Caucasian,11/14/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +66488,77023,69729,PRETRIAL,THULLER,ROBSON,RODRIGUEZ,Male,Caucasian,11/14/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +66488,77023,69729,PRETRIAL,THULLER,ROBSON,RODRIGUEZ,Male,Caucasian,11/14/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +49062,77030,69736,PRETRIAL,Brown,Timothy,NULL,Male,African-American,07/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.6,2,Low,New,1,0 +49062,77030,69736,PRETRIAL,Brown,Timothy,NULL,Male,African-American,07/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +49062,77030,69736,PRETRIAL,Brown,Timothy,NULL,Male,African-American,07/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66501,77037,69743,Probation,Rucker,Christopher,NULL,Male,African-American,05/11/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +66501,77037,69743,Probation,Rucker,Christopher,NULL,Male,African-American,05/11/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +66501,77037,69743,Probation,Rucker,Christopher,NULL,Male,African-American,05/11/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +66486,77021,69727,PRETRIAL,Taylor,Davon,Jerome,Male,African-American,06/14/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +66486,77021,69727,PRETRIAL,Taylor,Davon,Jerome,Male,African-American,06/14/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +66486,77021,69727,PRETRIAL,Taylor,Davon,Jerome,Male,African-American,06/14/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66492,77029,69735,Probation,zukowski,steven,NULL,Male,Caucasian,09/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +66492,77029,69735,Probation,zukowski,steven,NULL,Male,Caucasian,09/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +66492,77029,69735,Probation,zukowski,steven,NULL,Male,Caucasian,09/10/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/25/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +45410,66552,60358,PRETRIAL,Everett,Wardell,NULL,Male,African-American,09/23/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +45410,66552,60358,PRETRIAL,Everett,Wardell,NULL,Male,African-American,09/23/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,New,1,0 +45410,66552,60358,PRETRIAL,Everett,Wardell,NULL,Male,African-American,09/23/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +11525,77026,69732,PRETRIAL,CROCKER,ANTHONY,KEITH,Male,African-American,07/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,2,Medium,7,Risk of Violence,-2.57,2,Low,New,1,0 +11525,77026,69732,PRETRIAL,CROCKER,ANTHONY,KEITH,Male,African-American,07/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +11525,77026,69732,PRETRIAL,CROCKER,ANTHONY,KEITH,Male,African-American,07/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/25/14 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +66509,77047,69753,Probation,Ponce,Norma,Leticia,Female,Hispanic,03/31/38,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/26/14 0:00,1,Low,7,Risk of Violence,-4.39,1,Low,New,1,0 +66509,77047,69753,Probation,Ponce,Norma,Leticia,Female,Hispanic,03/31/38,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/26/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +66509,77047,69753,Probation,Ponce,Norma,Leticia,Female,Hispanic,03/31/38,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66513,77055,69760,Probation,Gavidiamendoza,Darwing,NULL,Male,Hispanic,05/03/76,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/26/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +66513,77055,69760,Probation,Gavidiamendoza,Darwing,NULL,Male,Hispanic,05/03/76,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/26/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +66513,77055,69760,Probation,Gavidiamendoza,Darwing,NULL,Male,Hispanic,05/03/76,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66519,77063,69767,PRETRIAL,rivera,miguel,NULL,Male,Hispanic,06/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/26/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +66519,77063,69767,PRETRIAL,rivera,miguel,NULL,Male,Hispanic,06/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/26/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +66519,77063,69767,PRETRIAL,rivera,miguel,NULL,Male,Hispanic,06/13/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66505,77042,69748,PRETRIAL,Stalter,James,NULL,Male,Caucasian,03/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +66505,77042,69748,PRETRIAL,Stalter,James,NULL,Male,Caucasian,03/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +66505,77042,69748,PRETRIAL,Stalter,James,NULL,Male,Caucasian,03/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +37433,77050,69756,PRETRIAL,Neri,Clemente,NULL,Male,Caucasian,12/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/26/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +37433,77050,69756,PRETRIAL,Neri,Clemente,NULL,Male,Caucasian,12/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/26/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +37433,77050,69756,PRETRIAL,Neri,Clemente,NULL,Male,Caucasian,12/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +66523,77068,69771,PRETRIAL,Johnson,Henry,NULL,Male,African-American,04/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +66523,77068,69771,PRETRIAL,Johnson,Henry,NULL,Male,African-American,04/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +66523,77068,69771,PRETRIAL,Johnson,Henry,NULL,Male,African-American,04/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66511,77051,69757,PRETRIAL,Quezadavina,Nanira,NULL,Female,Hispanic,07/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +66511,77051,69757,PRETRIAL,Quezadavina,Nanira,NULL,Female,Hispanic,07/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +66511,77051,69757,PRETRIAL,Quezadavina,Nanira,NULL,Female,Hispanic,07/03/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66515,77058,69763,Probation,Brasil,Rogerio,NULL,Male,Hispanic,02/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/14 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +66515,77058,69763,Probation,Brasil,Rogerio,NULL,Male,Hispanic,02/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/14 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +66515,77058,69763,Probation,Brasil,Rogerio,NULL,Male,Hispanic,02/13/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66517,77060,69765,PRETRIAL,rodriguezmulato,alexander,Daniel,Male,Hispanic,11/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,4,High,7,Risk of Violence,-0.24,10,High,New,1,0 +66517,77060,69765,PRETRIAL,rodriguezmulato,alexander,Daniel,Male,Hispanic,11/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,4,High,8,Risk of Recidivism,0.97,10,High,New,1,0 +66517,77060,69765,PRETRIAL,rodriguezmulato,alexander,Daniel,Male,Hispanic,11/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66510,77049,69755,PRETRIAL,Bryant,Jason,NULL,Male,Caucasian,04/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +66510,77049,69755,PRETRIAL,Bryant,Jason,NULL,Male,Caucasian,04/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +66510,77049,69755,PRETRIAL,Bryant,Jason,NULL,Male,Caucasian,04/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66512,77053,69759,PRETRIAL,MENDEZ,ALVIN,NULL,Male,Hispanic,07/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,2,Medium,7,Risk of Violence,-2.9,2,Low,New,1,0 +66512,77053,69759,PRETRIAL,MENDEZ,ALVIN,NULL,Male,Hispanic,07/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +66512,77053,69759,PRETRIAL,MENDEZ,ALVIN,NULL,Male,Hispanic,07/12/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66521,77065,69769,Probation,Guzman,Andreina,NULL,Female,Hispanic,05/27/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/26/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +66521,77065,69769,Probation,Guzman,Andreina,NULL,Female,Hispanic,05/27/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/26/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +66521,77065,69769,Probation,Guzman,Andreina,NULL,Female,Hispanic,05/27/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66507,77044,69750,PRETRIAL,Wright,Clifton,NULL,Male,Other,01/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/14 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +66507,77044,69750,PRETRIAL,Wright,Clifton,NULL,Male,Other,01/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/14 0:00,1,Low,8,Risk of Recidivism,-2.57,1,Low,New,1,0 +66507,77044,69750,PRETRIAL,Wright,Clifton,NULL,Male,Other,01/13/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66506,77043,69749,PRETRIAL,Hall,Siivon,NULL,Male,African-American,12/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +66506,77043,69749,PRETRIAL,Hall,Siivon,NULL,Male,African-American,12/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +66506,77043,69749,PRETRIAL,Hall,Siivon,NULL,Male,African-American,12/23/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58729,77045,69751,PRETRIAL,StFort,Shantrina,NULL,Female,African-American,06/06/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/26/14 0:00,2,Medium,7,Risk of Violence,-1.31,7,Medium,New,1,0 +58729,77045,69751,PRETRIAL,StFort,Shantrina,NULL,Female,African-American,06/06/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +58729,77045,69751,PRETRIAL,StFort,Shantrina,NULL,Female,African-American,06/06/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/26/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +52980,77066,54384,PRETRIAL,Edwards,Kelvin,Jamal,Male,African-American,07/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,Copy,1,0 +52980,77066,54384,PRETRIAL,Edwards,Kelvin,Jamal,Male,African-American,07/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,Copy,1,0 +52980,77066,54384,PRETRIAL,Edwards,Kelvin,Jamal,Male,African-American,07/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +66514,77057,69762,PRETRIAL,FLOWERS,JOHN,NULL,Male,African-American,05/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,2,Medium,7,Risk of Violence,-2.89,2,Low,New,1,0 +66514,77057,69762,PRETRIAL,FLOWERS,JOHN,NULL,Male,African-American,05/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +66514,77057,69762,PRETRIAL,FLOWERS,JOHN,NULL,Male,African-American,05/15/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66518,77061,69766,Probation,CHEVERE,GIOVANNI,JOEL,Male,Hispanic,05/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +66518,77061,69766,Probation,CHEVERE,GIOVANNI,JOEL,Male,Hispanic,05/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +66518,77061,69766,Probation,CHEVERE,GIOVANNI,JOEL,Male,Hispanic,05/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66504,77040,69746,PRETRIAL,Abimbola,Abayomi,NULL,Male,African-American,04/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +66504,77040,69746,PRETRIAL,Abimbola,Abayomi,NULL,Male,African-American,04/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +66504,77040,69746,PRETRIAL,Abimbola,Abayomi,NULL,Male,African-American,04/20/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64188,77054,67164,PRETRIAL,Singh,Troy,NULL,Male,African-American,05/10/96,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +64188,77054,67164,PRETRIAL,Singh,Troy,NULL,Male,African-American,05/10/96,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,4,High,8,Risk of Recidivism,1.2,10,High,New,1,0 +64188,77054,67164,PRETRIAL,Singh,Troy,NULL,Male,African-American,05/10/96,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,4,High,18,Risk of Failure to Appear,18,2,Low,New,1,0 +62225,77041,69747,Probation,Mayberry,Scott,NULL,Male,Caucasian,09/29/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +62225,77041,69747,Probation,Mayberry,Scott,NULL,Male,Caucasian,09/29/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +62225,77041,69747,Probation,Mayberry,Scott,NULL,Male,Caucasian,09/29/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,39,10,High,New,1,0 +30663,77048,69754,PRETRIAL,ochoa,allan,NULL,Male,Hispanic,05/29/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +30663,77048,69754,PRETRIAL,ochoa,allan,NULL,Male,Hispanic,05/29/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +30663,77048,69754,PRETRIAL,ochoa,allan,NULL,Male,Hispanic,05/29/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/26/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +63833,77062,66759,PRETRIAL,Oliver,Shawn,NULL,Male,African-American,07/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,Copy,1,0 +63833,77062,66759,PRETRIAL,Oliver,Shawn,NULL,Male,African-American,07/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.91,10,High,Copy,1,0 +63833,77062,66759,PRETRIAL,Oliver,Shawn,NULL,Male,African-American,07/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +66516,77059,69764,Probation,Tisdale,Elon,NULL,Male,African-American,04/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +66516,77059,69764,Probation,Tisdale,Elon,NULL,Male,African-American,04/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +66516,77059,69764,Probation,Tisdale,Elon,NULL,Male,African-American,04/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66522,77067,69770,PRETRIAL,Nazaire,Billy,NULL,Male,Other,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +66522,77067,69770,PRETRIAL,Nazaire,Billy,NULL,Male,Other,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +66522,77067,69770,PRETRIAL,Nazaire,Billy,NULL,Male,Other,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66508,77046,69752,PRETRIAL,Perry,Derrick,NULL,Male,African-American,07/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.13,10,High,New,1,0 +66508,77046,69752,PRETRIAL,Perry,Derrick,NULL,Male,African-American,07/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +66508,77046,69752,PRETRIAL,Perry,Derrick,NULL,Male,African-American,07/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,49,10,High,New,1,0 +66520,77064,69768,PRETRIAL,Alexis,Paulin,NULL,Male,African-American,11/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +66520,77064,69768,PRETRIAL,Alexis,Paulin,NULL,Male,African-American,11/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +66520,77064,69768,PRETRIAL,Alexis,Paulin,NULL,Male,African-American,11/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66527,77072,69775,PRETRIAL,Thompson,Duvon,George,Male,African-American,07/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +66527,77072,69775,PRETRIAL,Thompson,Duvon,George,Male,African-American,07/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +66527,77072,69775,PRETRIAL,Thompson,Duvon,George,Male,African-American,07/26/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66524,77069,69772,PRETRIAL,Milo,Jhony,NULL,Male,African-American,04/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.26,3,Low,New,1,0 +66524,77069,69772,PRETRIAL,Milo,Jhony,NULL,Male,African-American,04/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +66524,77069,69772,PRETRIAL,Milo,Jhony,NULL,Male,African-American,04/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +66529,77075,69777,PRETRIAL,Masson,Jonathan,NULL,Male,African-American,10/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,Copy,1,0 +66529,77075,69777,PRETRIAL,Masson,Jonathan,NULL,Male,African-American,10/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,Copy,1,0 +66529,77075,69777,PRETRIAL,Masson,Jonathan,NULL,Male,African-American,10/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +66528,77073,69776,PRETRIAL,Alexander,Chastity,Michara,Female,African-American,11/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +66528,77073,69776,PRETRIAL,Alexander,Chastity,Michara,Female,African-American,11/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +66528,77073,69776,PRETRIAL,Alexander,Chastity,Michara,Female,African-American,11/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66525,77070,69773,PRETRIAL,Alvarez,Alberto,E,Male,Hispanic,08/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +66525,77070,69773,PRETRIAL,Alvarez,Alberto,E,Male,Hispanic,08/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +66525,77070,69773,PRETRIAL,Alvarez,Alberto,E,Male,Hispanic,08/22/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66526,77071,69774,PRETRIAL,Johnson,Jordan,Oneal,Male,African-American,02/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/27/14 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +66526,77071,69774,PRETRIAL,Johnson,Jordan,Oneal,Male,African-American,02/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/27/14 0:00,4,High,8,Risk of Recidivism,0.63,10,High,New,1,0 +66526,77071,69774,PRETRIAL,Johnson,Jordan,Oneal,Male,African-American,02/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/27/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66530,77076,69778,PRETRIAL,Williams,Robert,NULL,Male,African-American,07/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.34,3,Low,New,1,0 +66530,77076,69778,PRETRIAL,Williams,Robert,NULL,Male,African-American,07/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +66530,77076,69778,PRETRIAL,Williams,Robert,NULL,Male,African-American,07/31/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66536,77084,69785,PRETRIAL,CONSTANTINE,KEVIN,JOHN,Male,African-American,10/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +66536,77084,69785,PRETRIAL,CONSTANTINE,KEVIN,JOHN,Male,African-American,10/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +66536,77084,69785,PRETRIAL,CONSTANTINE,KEVIN,JOHN,Male,African-American,10/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66531,77079,69780,PRETRIAL,Johnson,Patrice,NULL,Female,African-American,08/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +66531,77079,69780,PRETRIAL,Johnson,Patrice,NULL,Female,African-American,08/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +66531,77079,69780,PRETRIAL,Johnson,Patrice,NULL,Female,African-American,08/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66533,77081,69782,PRETRIAL,Hicks,Erica,NULL,Female,African-American,03/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +66533,77081,69782,PRETRIAL,Hicks,Erica,NULL,Female,African-American,03/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +66533,77081,69782,PRETRIAL,Hicks,Erica,NULL,Female,African-American,03/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66532,77080,69781,PRETRIAL,Eckhardt,Blake,NULL,Male,African-American,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +66532,77080,69781,PRETRIAL,Eckhardt,Blake,NULL,Male,African-American,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +66532,77080,69781,PRETRIAL,Eckhardt,Blake,NULL,Male,African-American,06/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +12201,77078,57663,DRRD,Daniels,Brion,NULL,Male,African-American,02/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,Copy,1,0 +12201,77078,57663,DRRD,Daniels,Brion,NULL,Male,African-American,02/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,9,High,Copy,1,0 +12201,77078,57663,DRRD,Daniels,Brion,NULL,Male,African-American,02/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,3,Low,Copy,1,0 +66534,77082,69783,PRETRIAL,GAROT,STALIN,NULL,Male,Caucasian,02/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +66534,77082,69783,PRETRIAL,GAROT,STALIN,NULL,Male,Caucasian,02/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +66534,77082,69783,PRETRIAL,GAROT,STALIN,NULL,Male,Caucasian,02/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +6462,77077,69779,PRETRIAL,JOHNSON,CRAIG,NULL,Male,African-American,11/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +6462,77077,69779,PRETRIAL,JOHNSON,CRAIG,NULL,Male,African-American,11/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,4,High,8,Risk of Recidivism,0.47,9,High,New,1,0 +6462,77077,69779,PRETRIAL,JOHNSON,CRAIG,NULL,Male,African-American,11/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +66535,77083,69784,PRETRIAL,KNOX,STEPHANIE,D,Female,African-American,12/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/28/14 0:00,2,Medium,7,Risk of Violence,-3.18,1,Low,New,1,0 +66535,77083,69784,PRETRIAL,KNOX,STEPHANIE,D,Female,African-American,12/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +66535,77083,69784,PRETRIAL,KNOX,STEPHANIE,D,Female,African-American,12/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/28/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +66537,77085,69786,PRETRIAL,Allen,Charles,NULL,Male,African-American,03/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +66537,77085,69786,PRETRIAL,Allen,Charles,NULL,Male,African-American,03/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +66537,77085,69786,PRETRIAL,Allen,Charles,NULL,Male,African-American,03/17/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66553,77106,69806,Probation,Borrero,Anderson,NULL,Male,Hispanic,04/24/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +66553,77106,69806,Probation,Borrero,Anderson,NULL,Male,Hispanic,04/24/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +66553,77106,69806,Probation,Borrero,Anderson,NULL,Male,Hispanic,04/24/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66543,77093,69793,PRETRIAL,WATSON,GLENN,WILLIAM,Male,Caucasian,05/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/29/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +66543,77093,69793,PRETRIAL,WATSON,GLENN,WILLIAM,Male,Caucasian,05/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +66543,77093,69793,PRETRIAL,WATSON,GLENN,WILLIAM,Male,Caucasian,05/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66567,77127,69825,Probation,Bailey,Jennifer,Rose,Female,Caucasian,11/22/57,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/29/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +66567,77127,69825,Probation,Bailey,Jennifer,Rose,Female,Caucasian,11/22/57,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/29/14 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +66567,77127,69825,Probation,Bailey,Jennifer,Rose,Female,Caucasian,11/22/57,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66560,77119,69817,PRETRIAL,Smith,Victoria,NULL,Female,Caucasian,07/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +66560,77119,69817,PRETRIAL,Smith,Victoria,NULL,Female,Caucasian,07/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +66560,77119,69817,PRETRIAL,Smith,Victoria,NULL,Female,Caucasian,07/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66548,77098,69798,PRETRIAL,Ricardo,Annaisa,NULL,Female,Caucasian,07/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +66548,77098,69798,PRETRIAL,Ricardo,Annaisa,NULL,Female,Caucasian,07/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +66548,77098,69798,PRETRIAL,Ricardo,Annaisa,NULL,Female,Caucasian,07/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66556,77111,69810,Probation,Suarez,Biannely,NULL,Female,Hispanic,01/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +66556,77111,69810,Probation,Suarez,Biannely,NULL,Female,Hispanic,01/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +66556,77111,69810,Probation,Suarez,Biannely,NULL,Female,Hispanic,01/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66540,77090,69791,PRETRIAL,FELICIANO,SAMANTHA,JANELLE,Female,Caucasian,01/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,New,1,0 +66540,77090,69791,PRETRIAL,FELICIANO,SAMANTHA,JANELLE,Female,Caucasian,01/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +66540,77090,69791,PRETRIAL,FELICIANO,SAMANTHA,JANELLE,Female,Caucasian,01/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +66546,77096,69796,PRETRIAL,CORTINA,LUIS,CARLOS,Male,Caucasian,04/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/29/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +66546,77096,69796,PRETRIAL,CORTINA,LUIS,CARLOS,Male,Caucasian,04/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/29/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +66546,77096,69796,PRETRIAL,CORTINA,LUIS,CARLOS,Male,Caucasian,04/20/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66552,77103,69803,Probation,BLANCHETTE,MICHAEL,JOSEPH,Male,Caucasian,06/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +66552,77103,69803,Probation,BLANCHETTE,MICHAEL,JOSEPH,Male,Caucasian,06/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +66552,77103,69803,Probation,BLANCHETTE,MICHAEL,JOSEPH,Male,Caucasian,06/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66549,77099,69799,PRETRIAL,Ferguson,steven,Xavier,Male,African-American,12/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +66549,77099,69799,PRETRIAL,Ferguson,steven,Xavier,Male,African-American,12/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.42,9,High,New,1,0 +66549,77099,69799,PRETRIAL,Ferguson,steven,Xavier,Male,African-American,12/17/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59544,77117,61891,PRETRIAL,CALLINS,JIMMY,NULL,Male,African-American,01/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,4,High,7,Risk of Violence,-1.1,8,High,Copy,1,0 +59544,77117,61891,PRETRIAL,CALLINS,JIMMY,NULL,Male,African-American,01/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,4,High,8,Risk of Recidivism,0.3,8,High,Copy,1,0 +59544,77117,61891,PRETRIAL,CALLINS,JIMMY,NULL,Male,African-American,01/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +66568,77129,69827,Probation,Bain,Joshua,NULL,Male,African-American,05/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +66568,77129,69827,Probation,Bain,Joshua,NULL,Male,African-American,05/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +66568,77129,69827,Probation,Bain,Joshua,NULL,Male,African-American,05/13/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66555,77108,69808,Probation,vonhedt,michael,NULL,Male,Caucasian,05/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/29/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +66555,77108,69808,Probation,vonhedt,michael,NULL,Male,Caucasian,05/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +66555,77108,69808,Probation,vonhedt,michael,NULL,Male,Caucasian,05/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +45947,77087,69788,PRETRIAL,WARD,MACKNIA,NULL,Female,African-American,10/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,4,High,7,Risk of Violence,-0.92,9,High,New,1,0 +45947,77087,69788,PRETRIAL,WARD,MACKNIA,NULL,Female,African-American,10/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,4,High,8,Risk of Recidivism,0.6,10,High,New,1,0 +45947,77087,69788,PRETRIAL,WARD,MACKNIA,NULL,Female,African-American,10/14/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,4,High,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +66551,77101,69801,Probation,McFarlane,Richard,NULL,Male,African-American,08/31/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +66551,77101,69801,Probation,McFarlane,Richard,NULL,Male,African-American,08/31/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +66551,77101,69801,Probation,McFarlane,Richard,NULL,Male,African-American,08/31/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +66557,77115,69814,Probation,Herrera,Rolando,NULL,Male,Hispanic,01/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +66557,77115,69814,Probation,Herrera,Rolando,NULL,Male,Hispanic,01/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +66557,77115,69814,Probation,Herrera,Rolando,NULL,Male,Hispanic,01/31/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66563,77122,69820,Probation,Santiago,Joseph,NULL,Male,Hispanic,07/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +66563,77122,69820,Probation,Santiago,Joseph,NULL,Male,Hispanic,07/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +66563,77122,69820,Probation,Santiago,Joseph,NULL,Male,Hispanic,07/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59544,68264,61891,PRETRIAL,CALLINS,JIMMY,NULL,Male,African-American,01/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +59544,68264,61891,PRETRIAL,CALLINS,JIMMY,NULL,Male,African-American,01/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +59544,68264,61891,PRETRIAL,CALLINS,JIMMY,NULL,Male,African-American,01/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66544,77094,69794,PRETRIAL,GRIVOREV,BORIS,NULL,Male,Caucasian,12/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +66544,77094,69794,PRETRIAL,GRIVOREV,BORIS,NULL,Male,Caucasian,12/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +66544,77094,69794,PRETRIAL,GRIVOREV,BORIS,NULL,Male,Caucasian,12/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +51059,77124,69822,PRETRIAL,CERVANTES,MAIKEL,NULL,Male,Caucasian,09/22/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +51059,77124,69822,PRETRIAL,CERVANTES,MAIKEL,NULL,Male,Caucasian,09/22/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +51059,77124,69822,PRETRIAL,CERVANTES,MAIKEL,NULL,Male,Caucasian,09/22/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66539,77088,69789,PRETRIAL,GIRON,ALVY,D,Male,Hispanic,08/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/29/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +66539,77088,69789,PRETRIAL,GIRON,ALVY,D,Male,Hispanic,08/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/29/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +66539,77088,69789,PRETRIAL,GIRON,ALVY,D,Male,Hispanic,08/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +15515,77109,69809,Probation,Robinson,Jonathan,NULL,Male,African-American,11/02/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,9/29/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +15515,77109,69809,Probation,Robinson,Jonathan,NULL,Male,African-American,11/02/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +15515,77109,69809,Probation,Robinson,Jonathan,NULL,Male,African-American,11/02/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +47499,77102,69802,PRETRIAL,BELL,RODNEY,NULL,Male,African-American,08/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/29/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +47499,77102,69802,PRETRIAL,BELL,RODNEY,NULL,Male,African-American,08/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/29/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +47499,77102,69802,PRETRIAL,BELL,RODNEY,NULL,Male,African-American,08/24/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66564,77123,69821,Probation,souza,jocenildo,NULL,Male,Hispanic,11/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +66564,77123,69821,Probation,souza,jocenildo,NULL,Male,Hispanic,11/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +66564,77123,69821,Probation,souza,jocenildo,NULL,Male,Hispanic,11/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66545,77095,69795,PRETRIAL,Haynes,Josalyn,NULL,Female,Caucasian,08/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/29/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +66545,77095,69795,PRETRIAL,Haynes,Josalyn,NULL,Female,Caucasian,08/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/29/14 0:00,1,Low,8,Risk of Recidivism,-2.14,1,Low,New,1,0 +66545,77095,69795,PRETRIAL,Haynes,Josalyn,NULL,Female,Caucasian,08/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +17803,77104,69804,PRETRIAL,Caldwell,Trenard,NULL,Male,African-American,01/19/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/29/14 0:00,2,Medium,7,Risk of Violence,-2.05,4,Low,New,1,0 +17803,77104,69804,PRETRIAL,Caldwell,Trenard,NULL,Male,African-American,01/19/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/29/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +17803,77104,69804,PRETRIAL,Caldwell,Trenard,NULL,Male,African-American,01/19/91,17,All Scales,Intake,English,Conditional Release,Probation,Single,9/29/14 0:00,2,Medium,18,Risk of Failure to Appear,18,2,Low,New,1,0 +30674,77091,29652,PRETRIAL,Gonzalez,Miguel,Antonio,Male,Caucasian,10/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/29/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,Copy,1,0 +30674,77091,29652,PRETRIAL,Gonzalez,Miguel,Antonio,Male,Caucasian,10/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/29/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,Copy,1,0 +30674,77091,29652,PRETRIAL,Gonzalez,Miguel,Antonio,Male,Caucasian,10/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +66565,77125,69823,Probation,MOSS-JORDAN,CORNELIUS,NULL,Male,African-American,01/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +66565,77125,69823,Probation,MOSS-JORDAN,CORNELIUS,NULL,Male,African-American,01/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +66565,77125,69823,Probation,MOSS-JORDAN,CORNELIUS,NULL,Male,African-American,01/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66554,77107,69807,PRETRIAL,EWING,DANIEL,NULL,Male,Caucasian,09/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +66554,77107,69807,PRETRIAL,EWING,DANIEL,NULL,Male,Caucasian,09/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +66554,77107,69807,PRETRIAL,EWING,DANIEL,NULL,Male,Caucasian,09/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66562,77121,69819,PRETRIAL,Park,Gene,NULL,Male,Asian,07/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +66562,77121,69819,PRETRIAL,Park,Gene,NULL,Male,Asian,07/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +66562,77121,69819,PRETRIAL,Park,Gene,NULL,Male,Asian,07/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66538,77086,69787,PRETRIAL,Saint Preux,Emmanuel,NULL,Male,Other,02/21/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/29/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +66538,77086,69787,PRETRIAL,Saint Preux,Emmanuel,NULL,Male,Other,02/21/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/29/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +66538,77086,69787,PRETRIAL,Saint Preux,Emmanuel,NULL,Male,Other,02/21/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +39852,77105,69805,PRETRIAL,Loud,Brandon,NULL,Male,African-American,06/30/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +39852,77105,69805,PRETRIAL,Loud,Brandon,NULL,Male,African-American,06/30/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.7,10,High,New,1,0 +39852,77105,69805,PRETRIAL,Loud,Brandon,NULL,Male,African-American,06/30/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,2,Low,New,1,0 +34075,77112,69811,Probation,Toppas,Jason,Michael,Male,Caucasian,02/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +34075,77112,69811,Probation,Toppas,Jason,Michael,Male,Caucasian,02/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +34075,77112,69811,Probation,Toppas,Jason,Michael,Male,Caucasian,02/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +61162,77113,69812,PRETRIAL,HILLER-BALCAZAR,MONICA,NULL,Female,Caucasian,12/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/29/14 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +61162,77113,69812,PRETRIAL,HILLER-BALCAZAR,MONICA,NULL,Female,Caucasian,12/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,7,Medium,New,1,0 +61162,77113,69812,PRETRIAL,HILLER-BALCAZAR,MONICA,NULL,Female,Caucasian,12/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/29/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66542,77092,69792,PRETRIAL,Altidor,Brion,Lil John,Male,African-American,08/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,4,High,7,Risk of Violence,-0.37,10,High,New,1,0 +66542,77092,69792,PRETRIAL,Altidor,Brion,Lil John,Male,African-American,08/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,4,High,8,Risk of Recidivism,0.93,10,High,New,1,0 +66542,77092,69792,PRETRIAL,Altidor,Brion,Lil John,Male,African-American,08/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66566,77126,69824,Probation,deluca,michael,NULL,Male,Caucasian,10/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +66566,77126,69824,Probation,deluca,michael,NULL,Male,Caucasian,10/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +66566,77126,69824,Probation,deluca,michael,NULL,Male,Caucasian,10/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +47617,77128,69826,PRETRIAL,LATOUR,ISAAC,NULL,Male,African-American,01/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.13,8,High,New,1,0 +47617,77128,69826,PRETRIAL,LATOUR,ISAAC,NULL,Male,African-American,01/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +47617,77128,69826,PRETRIAL,LATOUR,ISAAC,NULL,Male,African-American,01/24/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +27358,77110,26474,PRETRIAL,McQueen,Perry,NULL,Male,African-American,02/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.23,8,High,Copy,1,0 +27358,77110,26474,PRETRIAL,McQueen,Perry,NULL,Male,African-American,02/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.31,6,Medium,Copy,1,0 +27358,77110,26474,PRETRIAL,McQueen,Perry,NULL,Male,African-American,02/28/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +66547,77097,69797,PRETRIAL,Beja-Mcclennan,Katherine,NULL,Female,Caucasian,05/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/29/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +66547,77097,69797,PRETRIAL,Beja-Mcclennan,Katherine,NULL,Female,Caucasian,05/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/29/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +66547,77097,69797,PRETRIAL,Beja-Mcclennan,Katherine,NULL,Female,Caucasian,05/11/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66541,77089,69790,PRETRIAL,MaGray,Ryan,NULL,Male,Caucasian,07/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +66541,77089,69790,PRETRIAL,MaGray,Ryan,NULL,Male,Caucasian,07/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +66541,77089,69790,PRETRIAL,MaGray,Ryan,NULL,Male,Caucasian,07/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66558,77118,69816,PRETRIAL,Haley,Jeffrey,NULL,Male,Caucasian,09/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,2,Medium,7,Risk of Violence,-2.66,2,Low,New,1,0 +66558,77118,69816,PRETRIAL,Haley,Jeffrey,NULL,Male,Caucasian,09/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +66558,77118,69816,PRETRIAL,Haley,Jeffrey,NULL,Male,Caucasian,09/19/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/29/14 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,New,1,0 +66573,77136,69832,PRETRIAL,SNEED,CURTIS,LEE,Male,African-American,03/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +66573,77136,69832,PRETRIAL,SNEED,CURTIS,LEE,Male,African-American,03/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +66573,77136,69832,PRETRIAL,SNEED,CURTIS,LEE,Male,African-American,03/13/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66587,77149,69845,PRETRIAL,SMITH,SHAMEL,NULL,Male,African-American,10/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +66587,77149,69845,PRETRIAL,SMITH,SHAMEL,NULL,Male,African-American,10/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +66587,77149,69845,PRETRIAL,SMITH,SHAMEL,NULL,Male,African-American,10/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66576,77139,69835,PRETRIAL,Carabjal,Noe,NULL,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/30/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +66576,77139,69835,PRETRIAL,Carabjal,Noe,NULL,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +66576,77139,69835,PRETRIAL,Carabjal,Noe,NULL,Male,Caucasian,12/19/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66591,77157,69851,Probation,GARCIA,VICTOR,NULL,Male,Hispanic,12/19/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +66591,77157,69851,Probation,GARCIA,VICTOR,NULL,Male,Hispanic,12/19/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +66591,77157,69851,Probation,GARCIA,VICTOR,NULL,Male,Hispanic,12/19/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +32722,77131,31770,PRETRIAL,Amador,Jose,Angel,Male,Hispanic,03/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,Copy,1,0 +32722,77131,31770,PRETRIAL,Amador,Jose,Angel,Male,Hispanic,03/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,10,High,Copy,1,0 +32722,77131,31770,PRETRIAL,Amador,Jose,Angel,Male,Hispanic,03/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +8494,77165,69858,PRETRIAL,GONZALEZ,CARLOS,EDGARDO,Male,Hispanic,07/24/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,2,Medium,7,Risk of Violence,-1.28,7,Medium,New,1,0 +8494,77165,69858,PRETRIAL,GONZALEZ,CARLOS,EDGARDO,Male,Hispanic,07/24/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +8494,77165,69858,PRETRIAL,GONZALEZ,CARLOS,EDGARDO,Male,Hispanic,07/24/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,2,Medium,18,Risk of Failure to Appear,37,10,High,New,1,0 +66602,77170,69863,Probation,Taylor,Kenesha,NULL,Female,African-American,12/15/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +66602,77170,69863,Probation,Taylor,Kenesha,NULL,Female,African-American,12/15/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +66602,77170,69863,Probation,Taylor,Kenesha,NULL,Female,African-American,12/15/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66581,77144,69840,PRETRIAL,MOORE,JUSTIN,NULL,Male,Caucasian,04/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +66581,77144,69840,PRETRIAL,MOORE,JUSTIN,NULL,Male,Caucasian,04/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +66581,77144,69840,PRETRIAL,MOORE,JUSTIN,NULL,Male,Caucasian,04/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +66578,77141,69837,Probation,Velez,Melisa,NULL,Female,Hispanic,12/30/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +66578,77141,69837,Probation,Velez,Melisa,NULL,Female,Hispanic,12/30/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/14 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,New,1,0 +66578,77141,69837,Probation,Velez,Melisa,NULL,Female,Hispanic,12/30/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66585,77147,69843,PRETRIAL,Pham,Lam,NULL,Male,Asian,11/21/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/30/14 0:00,1,Low,7,Risk of Violence,-4.19,1,Low,New,1,0 +66585,77147,69843,PRETRIAL,Pham,Lam,NULL,Male,Asian,11/21/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/30/14 0:00,1,Low,8,Risk of Recidivism,-2.46,1,Low,New,1,0 +66585,77147,69843,PRETRIAL,Pham,Lam,NULL,Male,Asian,11/21/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66584,77154,69847,PRETRIAL,Walker,Keydrum,Bernard,Male,African-American,10/28/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/14 0:00,4,High,7,Risk of Violence,0.12,10,High,Copy,1,0 +66584,77154,69847,PRETRIAL,Walker,Keydrum,Bernard,Male,African-American,10/28/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/14 0:00,4,High,8,Risk of Recidivism,0.94,10,High,Copy,1,0 +66584,77154,69847,PRETRIAL,Walker,Keydrum,Bernard,Male,African-American,10/28/95,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +66105,77155,69275,PRETRIAL,CHISOLM,CHRISTOPHER,NULL,Male,African-American,07/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,Copy,1,0 +66105,77155,69275,PRETRIAL,CHISOLM,CHRISTOPHER,NULL,Male,African-American,07/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,Copy,1,0 +66105,77155,69275,PRETRIAL,CHISOLM,CHRISTOPHER,NULL,Male,African-American,07/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +66570,77133,69829,PRETRIAL,Azevedo,Carlos,Wmdaclope,Male,Other,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-1.89,5,Medium,New,1,0 +66570,77133,69829,PRETRIAL,Azevedo,Carlos,Wmdaclope,Male,Other,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +66570,77133,69829,PRETRIAL,Azevedo,Carlos,Wmdaclope,Male,Other,05/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66571,77134,69830,PRETRIAL,DRUMMER,OTIS,VINCENT,Male,African-American,01/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +66571,77134,69830,PRETRIAL,DRUMMER,OTIS,VINCENT,Male,African-American,01/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +66571,77134,69830,PRETRIAL,DRUMMER,OTIS,VINCENT,Male,African-American,01/26/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66583,77146,69842,PRETRIAL,Theard,Gasmy,NULL,Male,Other,09/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +66583,77146,69842,PRETRIAL,Theard,Gasmy,NULL,Male,Other,09/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +66583,77146,69842,PRETRIAL,Theard,Gasmy,NULL,Male,Other,09/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66579,77142,69838,Probation,OCONNOR,SHAWN,NULL,Male,Caucasian,05/06/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/30/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +66579,77142,69838,Probation,OCONNOR,SHAWN,NULL,Male,Caucasian,05/06/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/30/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +66579,77142,69838,Probation,OCONNOR,SHAWN,NULL,Male,Caucasian,05/06/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66604,77172,69865,Probation,POER,RICHARD,JOSEPH,Male,Caucasian,02/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +66604,77172,69865,Probation,POER,RICHARD,JOSEPH,Male,Caucasian,02/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +66604,77172,69865,Probation,POER,RICHARD,JOSEPH,Male,Caucasian,02/09/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66569,77130,69828,PRETRIAL,Miller,Monique,NULL,Female,African-American,04/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +66569,77130,69828,PRETRIAL,Miller,Monique,NULL,Female,African-American,04/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +66569,77130,69828,PRETRIAL,Miller,Monique,NULL,Female,African-American,04/03/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66574,77137,69833,PRETRIAL,Vigil,Christian,Gilbert,Male,Hispanic,10/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +66574,77137,69833,PRETRIAL,Vigil,Christian,Gilbert,Male,Hispanic,10/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +66574,77137,69833,PRETRIAL,Vigil,Christian,Gilbert,Male,Hispanic,10/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66584,77151,69847,PRETRIAL,Walker,Keydrum,Bernard,Male,African-American,10/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/14 0:00,4,High,7,Risk of Violence,0.12,10,High,New,1,0 +66584,77151,69847,PRETRIAL,Walker,Keydrum,Bernard,Male,African-American,10/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/14 0:00,4,High,8,Risk of Recidivism,0.94,10,High,New,1,0 +66584,77151,69847,PRETRIAL,Walker,Keydrum,Bernard,Male,African-American,10/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,9/30/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66592,77158,69852,Probation,Mejia,Natalia,NULL,Female,Hispanic,03/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +66592,77158,69852,Probation,Mejia,Natalia,NULL,Female,Hispanic,03/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-1.22,3,Low,New,1,0 +66592,77158,69852,Probation,Mejia,Natalia,NULL,Female,Hispanic,03/21/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +33470,77160,69853,PRETRIAL,Edouard,Maxene,NULL,Male,African-American,06/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +33470,77160,69853,PRETRIAL,Edouard,Maxene,NULL,Male,African-American,06/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +33470,77160,69853,PRETRIAL,Edouard,Maxene,NULL,Male,African-American,06/30/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66580,77143,69839,Probation,OTTO,RICHARD,A,Male,Caucasian,03/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +66580,77143,69839,Probation,OTTO,RICHARD,A,Male,Caucasian,03/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +66580,77143,69839,Probation,OTTO,RICHARD,A,Male,Caucasian,03/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +16932,77152,69848,PRETRIAL,Allen,Wymaneka,J,Female,African-American,10/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +16932,77152,69848,PRETRIAL,Allen,Wymaneka,J,Female,African-American,10/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +16932,77152,69848,PRETRIAL,Allen,Wymaneka,J,Female,African-American,10/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +7927,77166,69859,PRETRIAL,Dent,Erica,Lavora,Male,African-American,10/03/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/14 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +7927,77166,69859,PRETRIAL,Dent,Erica,Lavora,Male,African-American,10/03/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +7927,77166,69859,PRETRIAL,Dent,Erica,Lavora,Male,African-American,10/03/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,9/30/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +48047,77159,68855,PRETRIAL,severin,Jaylan,NULL,Male,African-American,06/03/93,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +48047,77159,68855,PRETRIAL,severin,Jaylan,NULL,Male,African-American,06/03/93,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,2,Medium,8,Risk of Recidivism,0.15,7,Medium,New,1,0 +48047,77159,68855,PRETRIAL,severin,Jaylan,NULL,Male,African-American,06/03/93,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,2,Medium,18,Risk of Failure to Appear,18,2,Low,New,1,0 +66575,77138,69834,PRETRIAL,Isma,Servenley,NULL,Male,African-American,06/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +66575,77138,69834,PRETRIAL,Isma,Servenley,NULL,Male,African-American,06/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +66575,77138,69834,PRETRIAL,Isma,Servenley,NULL,Male,African-American,06/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66588,77150,69846,Probation,WHITE,HENRY,NULL,Male,Hispanic,11/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +66588,77150,69846,Probation,WHITE,HENRY,NULL,Male,Hispanic,11/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +66588,77150,69846,Probation,WHITE,HENRY,NULL,Male,Hispanic,11/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66594,77164,69857,Probation,presas,ilanie,NULL,Female,Hispanic,01/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,New,1,0 +66594,77164,69857,Probation,presas,ilanie,NULL,Female,Hispanic,01/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,9,High,New,1,0 +66594,77164,69857,Probation,presas,ilanie,NULL,Female,Hispanic,01/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +66603,77171,69864,PRETRIAL,Fagley,Eric,NULL,Male,Caucasian,01/31/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/30/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +66603,77171,69864,PRETRIAL,Fagley,Eric,NULL,Male,Caucasian,01/31/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +66603,77171,69864,PRETRIAL,Fagley,Eric,NULL,Male,Caucasian,01/31/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +66590,77156,69850,Probation,Sandibenavides,Jose,NULL,Male,Caucasian,07/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +66590,77156,69850,Probation,Sandibenavides,Jose,NULL,Male,Caucasian,07/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +66590,77156,69850,Probation,Sandibenavides,Jose,NULL,Male,Caucasian,07/06/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66586,77148,69844,Probation,maldonado,melissa,NULL,Female,Hispanic,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +66586,77148,69844,Probation,maldonado,melissa,NULL,Female,Hispanic,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +66586,77148,69844,Probation,maldonado,melissa,NULL,Female,Hispanic,11/12/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66593,77161,69854,Probation,marc,gadner,NULL,Male,African-American,09/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +66593,77161,69854,Probation,marc,gadner,NULL,Male,African-American,09/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +66593,77161,69854,Probation,marc,gadner,NULL,Male,African-American,09/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66577,77140,69836,PRETRIAL,Clem,Michael,NULL,Male,Caucasian,08/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/30/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +66577,77140,69836,PRETRIAL,Clem,Michael,NULL,Male,Caucasian,08/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/30/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +66577,77140,69836,PRETRIAL,Clem,Michael,NULL,Male,Caucasian,08/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66572,77135,69831,PRETRIAL,Minott,Jermaine,Lenord,Male,Other,05/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +66572,77135,69831,PRETRIAL,Minott,Jermaine,Lenord,Male,Other,05/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +66572,77135,69831,PRETRIAL,Minott,Jermaine,Lenord,Male,Other,05/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66589,77153,69849,Probation,Moodie,Augustus,NULL,Male,African-American,08/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/30/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +66589,77153,69849,Probation,Moodie,Augustus,NULL,Male,African-American,08/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/30/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +66589,77153,69849,Probation,Moodie,Augustus,NULL,Male,African-American,08/05/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,9/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +8183,77132,49853,Probation,WRIGHT,TELLY,D,Male,African-American,07/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,4,High,7,Risk of Violence,-1.16,8,High,Copy,1,0 +8183,77132,49853,Probation,WRIGHT,TELLY,D,Male,African-American,07/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,4,High,8,Risk of Recidivism,0.73,10,High,Copy,1,0 +8183,77132,49853,Probation,WRIGHT,TELLY,D,Male,African-American,07/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,9/30/14 0:00,4,High,18,Risk of Failure to Appear,36,10,High,Copy,1,0 +66610,77182,69872,PRETRIAL,Turner,Willie,D,Male,African-American,02/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/14 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +66610,77182,69872,PRETRIAL,Turner,Willie,D,Male,African-American,02/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/14 0:00,4,High,8,Risk of Recidivism,0.88,10,High,New,1,0 +66610,77182,69872,PRETRIAL,Turner,Willie,D,Male,African-American,02/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66628,77203,69892,Probation,Paulson,James,Craig,Male,Caucasian,12/16/53,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,10/1/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +66628,77203,69892,Probation,Paulson,James,Craig,Male,Caucasian,12/16/53,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +66628,77203,69892,Probation,Paulson,James,Craig,Male,Caucasian,12/16/53,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66622,77195,69884,Probation,Kenny,Marthajane,NULL,Female,Caucasian,08/04/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/1/14 0:00,1,Low,7,Risk of Violence,-4.42,1,Low,New,1,0 +66622,77195,69884,Probation,Kenny,Marthajane,NULL,Female,Caucasian,08/04/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/1/14 0:00,1,Low,8,Risk of Recidivism,-2.65,1,Low,New,1,0 +66622,77195,69884,Probation,Kenny,Marthajane,NULL,Female,Caucasian,08/04/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +15192,77174,14531,PRETRIAL,ISMAEL,GASNER,PECOIS,Male,African-American,10/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,Copy,1,0 +15192,77174,14531,PRETRIAL,ISMAEL,GASNER,PECOIS,Male,African-American,10/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.35,8,High,Copy,1,0 +15192,77174,14531,PRETRIAL,ISMAEL,GASNER,PECOIS,Male,African-American,10/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,3,Low,Copy,1,0 +66625,77198,69887,PRETRIAL,Waters,Mason,NULL,Male,African-American,11/10/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/1/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +66625,77198,69887,PRETRIAL,Waters,Mason,NULL,Male,African-American,11/10/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/1/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +66625,77198,69887,PRETRIAL,Waters,Mason,NULL,Male,African-American,11/10/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,35,10,High,New,1,0 +20326,77205,19553,PRETRIAL,clemente,michael,NULL,Male,Caucasian,09/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,Copy,1,0 +20326,77205,19553,PRETRIAL,clemente,michael,NULL,Male,Caucasian,09/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,Copy,1,0 +20326,77205,19553,PRETRIAL,clemente,michael,NULL,Male,Caucasian,09/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +66612,77184,69874,PRETRIAL,Hodges,David,Irvin,Male,African-American,04/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +66612,77184,69874,PRETRIAL,Hodges,David,Irvin,Male,African-American,04/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +66612,77184,69874,PRETRIAL,Hodges,David,Irvin,Male,African-American,04/28/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66617,77190,69879,PRETRIAL,delnegro,lucas,NULL,Male,Hispanic,01/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/14 0:00,4,High,7,Risk of Violence,-0.2,10,High,New,1,0 +66617,77190,69879,PRETRIAL,delnegro,lucas,NULL,Male,Hispanic,01/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/14 0:00,4,High,8,Risk of Recidivism,1.05,10,High,New,1,0 +66617,77190,69879,PRETRIAL,delnegro,lucas,NULL,Male,Hispanic,01/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +51230,77177,52399,DRRD,Boyd,Antwon,NULL,Male,African-American,09/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,4,High,7,Risk of Violence,-0.68,9,High,Copy,1,0 +51230,77177,52399,DRRD,Boyd,Antwon,NULL,Male,African-American,09/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,4,High,8,Risk of Recidivism,0.53,9,High,Copy,1,0 +51230,77177,52399,DRRD,Boyd,Antwon,NULL,Male,African-American,09/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,4,High,18,Risk of Failure to Appear,18,2,Low,Copy,1,0 +66619,77192,69881,Probation,Whitcraft,Roy,NULL,Male,Asian,03/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/1/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +66619,77192,69881,Probation,Whitcraft,Roy,NULL,Male,Asian,03/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +66619,77192,69881,Probation,Whitcraft,Roy,NULL,Male,Asian,03/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +66616,77189,69878,PRETRIAL,Chavez,Victor,NULL,Male,Hispanic,10/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +66616,77189,69878,PRETRIAL,Chavez,Victor,NULL,Male,Hispanic,10/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +66616,77189,69878,PRETRIAL,Chavez,Victor,NULL,Male,Hispanic,10/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66613,77185,69875,PRETRIAL,TARAMONA,CARLOS,NULL,Male,Hispanic,08/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/1/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +66613,77185,69875,PRETRIAL,TARAMONA,CARLOS,NULL,Male,Hispanic,08/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +66613,77185,69875,PRETRIAL,TARAMONA,CARLOS,NULL,Male,Hispanic,08/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/1/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +27194,77206,69894,DRRD,Vixama,Franki,NULL,Male,Other,07/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +27194,77206,69894,DRRD,Vixama,Franki,NULL,Male,Other,07/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,4,High,8,Risk of Recidivism,0.58,9,High,New,1,0 +27194,77206,69894,DRRD,Vixama,Franki,NULL,Male,Other,07/21/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66627,77201,69890,Probation,Pedrosos,Giselle,NULL,Female,Caucasian,10/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +66627,77201,69890,Probation,Pedrosos,Giselle,NULL,Female,Caucasian,10/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +66627,77201,69890,Probation,Pedrosos,Giselle,NULL,Female,Caucasian,10/26/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66605,77173,69866,PRETRIAL,GREEN,ANTHONY,ALEXANDER,Male,African-American,11/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +66605,77173,69866,PRETRIAL,GREEN,ANTHONY,ALEXANDER,Male,African-American,11/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +66605,77173,69866,PRETRIAL,GREEN,ANTHONY,ALEXANDER,Male,African-American,11/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66609,77180,69870,PRETRIAL,Boatwright,Demeteria,NULL,Female,African-American,01/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +66609,77180,69870,PRETRIAL,Boatwright,Demeteria,NULL,Female,African-American,01/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,8,High,New,1,0 +66609,77180,69870,PRETRIAL,Boatwright,Demeteria,NULL,Female,African-American,01/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +65846,77187,69011,PRETRIAL,Devin,Paige,NULL,Male,African-American,02/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,Copy,1,0 +65846,77187,69011,PRETRIAL,Devin,Paige,NULL,Male,African-American,02/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.56,4,Low,Copy,1,0 +65846,77187,69011,PRETRIAL,Devin,Paige,NULL,Male,African-American,02/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/1/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +66621,77194,69883,Probation,Haigler,Jerry,NULL,Male,Caucasian,12/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +66621,77194,69883,Probation,Haigler,Jerry,NULL,Male,Caucasian,12/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +66621,77194,69883,Probation,Haigler,Jerry,NULL,Male,Caucasian,12/13/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66607,77179,69869,PRETRIAL,Appolon,Nenka,NULL,Female,African-American,06/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +66607,77179,69869,PRETRIAL,Appolon,Nenka,NULL,Female,African-American,06/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +66607,77179,69869,PRETRIAL,Appolon,Nenka,NULL,Female,African-American,06/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +30761,77181,69871,PRETRIAL,Moore,Patrick,NULL,Male,African-American,04/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,New,1,0 +30761,77181,69871,PRETRIAL,Moore,Patrick,NULL,Male,African-American,04/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +30761,77181,69871,PRETRIAL,Moore,Patrick,NULL,Male,African-American,04/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66615,77188,69877,Probation,SOIVILIEN,RIMAULD,NULL,Male,African-American,11/25/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +66615,77188,69877,Probation,SOIVILIEN,RIMAULD,NULL,Male,African-American,11/25/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.81,10,High,New,1,0 +66615,77188,69877,Probation,SOIVILIEN,RIMAULD,NULL,Male,African-American,11/25/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +56879,77202,69891,Probation,WHITEMAN,MICHAEL,NULL,Male,Caucasian,08/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +56879,77202,69891,Probation,WHITEMAN,MICHAEL,NULL,Male,Caucasian,08/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +56879,77202,69891,Probation,WHITEMAN,MICHAEL,NULL,Male,Caucasian,08/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +66624,77197,69886,Probation,Diaz,Hector,NULL,Male,Hispanic,11/02/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/1/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +66624,77197,69886,Probation,Diaz,Hector,NULL,Male,Hispanic,11/02/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +66624,77197,69886,Probation,Diaz,Hector,NULL,Male,Hispanic,11/02/71,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +36874,77176,36185,PRETRIAL,Alexander,Christopher,NULL,Male,African-American,09/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,4,High,7,Risk of Violence,-1.2,8,High,Copy,1,0 +36874,77176,36185,PRETRIAL,Alexander,Christopher,NULL,Male,African-American,09/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,4,High,8,Risk of Recidivism,0.29,8,High,Copy,1,0 +36874,77176,36185,PRETRIAL,Alexander,Christopher,NULL,Male,African-American,09/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +66620,77193,69882,Probation,Martinez,Joel,NULL,Male,Hispanic,07/20/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/1/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +66620,77193,69882,Probation,Martinez,Joel,NULL,Male,Hispanic,07/20/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +66620,77193,69882,Probation,Martinez,Joel,NULL,Male,Hispanic,07/20/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66611,77183,69873,PRETRIAL,Baker,Makia,NULL,Female,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +66611,77183,69873,PRETRIAL,Baker,Makia,NULL,Female,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +66611,77183,69873,PRETRIAL,Baker,Makia,NULL,Female,African-American,11/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +20326,21217,19553,PRETRIAL,clemente,michael,NULL,Male,Caucasian,09/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +20326,21217,19553,PRETRIAL,clemente,michael,NULL,Male,Caucasian,09/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +20326,21217,19553,PRETRIAL,clemente,michael,NULL,Male,Caucasian,09/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66606,77175,69867,PRETRIAL,SIMEON,FRAYDEL,C,Male,African-American,10/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +66606,77175,69867,PRETRIAL,SIMEON,FRAYDEL,C,Male,African-American,10/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +66606,77175,69867,PRETRIAL,SIMEON,FRAYDEL,C,Male,African-American,10/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66608,77178,69868,PRETRIAL,Arezo,Maria,NULL,Female,Hispanic,04/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +66608,77178,69868,PRETRIAL,Arezo,Maria,NULL,Female,Hispanic,04/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.23,3,Low,New,1,0 +66608,77178,69868,PRETRIAL,Arezo,Maria,NULL,Female,Hispanic,04/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66618,77191,69880,Probation,ESTACIOAPONTE,EDWIN,PAUL,Male,Hispanic,06/20/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +66618,77191,69880,Probation,ESTACIOAPONTE,EDWIN,PAUL,Male,Hispanic,06/20/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +66618,77191,69880,Probation,ESTACIOAPONTE,EDWIN,PAUL,Male,Hispanic,06/20/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66626,77199,69888,Probation,ELWOOD,SUSAN,MARY,Female,Hispanic,05/04/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/1/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +66626,77199,69888,Probation,ELWOOD,SUSAN,MARY,Female,Hispanic,05/04/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/1/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +66626,77199,69888,Probation,ELWOOD,SUSAN,MARY,Female,Hispanic,05/04/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66629,77204,69893,Probation,Weiss,kristopher,NULL,Male,Caucasian,10/13/70,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,10/1/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +66629,77204,69893,Probation,Weiss,kristopher,NULL,Male,Caucasian,10/13/70,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +66629,77204,69893,Probation,Weiss,kristopher,NULL,Male,Caucasian,10/13/70,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66623,77196,69885,Probation,Williams,Glendese,NULL,Female,African-American,03/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/1/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +66623,77196,69885,Probation,Williams,Glendese,NULL,Female,African-American,03/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.27,3,Low,New,1,0 +66623,77196,69885,Probation,Williams,Glendese,NULL,Female,African-American,03/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66630,77207,69895,PRETRIAL,Vertus,Luxson,NULL,Male,African-American,01/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +66630,77207,69895,PRETRIAL,Vertus,Luxson,NULL,Male,African-American,01/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +66630,77207,69895,PRETRIAL,Vertus,Luxson,NULL,Male,African-American,01/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66614,77186,69876,Probation,Stickney,Evander,Tyrell,Male,African-American,06/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/1/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +66614,77186,69876,Probation,Stickney,Evander,Tyrell,Male,African-American,06/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/1/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +66614,77186,69876,Probation,Stickney,Evander,Tyrell,Male,African-American,06/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/1/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66446,77217,69679,PRETRIAL,BUTLER,MALCOLM,NULL,Male,African-American,02/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,Copy,1,0 +66446,77217,69679,PRETRIAL,BUTLER,MALCOLM,NULL,Male,African-American,02/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,Copy,1,0 +66446,77217,69679,PRETRIAL,BUTLER,MALCOLM,NULL,Male,African-American,02/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +66653,77238,69923,PRETRIAL,Chrupcala,Samuel,NULL,Male,Caucasian,01/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +66653,77238,69923,PRETRIAL,Chrupcala,Samuel,NULL,Male,Caucasian,01/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +66653,77238,69923,PRETRIAL,Chrupcala,Samuel,NULL,Male,Caucasian,01/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66644,77225,69911,Probation,smith,horace,j,Male,African-American,11/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +66644,77225,69911,Probation,smith,horace,j,Male,African-American,11/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +66644,77225,69911,Probation,smith,horace,j,Male,African-American,11/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66655,77241,69926,PRETRIAL,SHAMIN,AHASSAN,NULL,Male,Other,12/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +66655,77241,69926,PRETRIAL,SHAMIN,AHASSAN,NULL,Male,Other,12/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,New,1,0 +66655,77241,69926,PRETRIAL,SHAMIN,AHASSAN,NULL,Male,Other,12/16/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +33745,77212,69900,PRETRIAL,RICHARD,TED,L,Male,African-American,10/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,2,Medium,7,Risk of Violence,-1.26,7,Medium,New,1,0 +33745,77212,69900,PRETRIAL,RICHARD,TED,L,Male,African-American,10/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +33745,77212,69900,PRETRIAL,RICHARD,TED,L,Male,African-American,10/24/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,2,Medium,18,Risk of Failure to Appear,35,10,High,New,1,0 +66650,77233,69919,Probation,King,Chad,Airelio,Male,Other,01/16/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +66650,77233,69919,Probation,King,Chad,Airelio,Male,Other,01/16/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +66650,77233,69919,Probation,King,Chad,Airelio,Male,Other,01/16/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66636,77214,69902,PRETRIAL,Nolasco,Antonio,NULL,Male,Hispanic,03/05/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/2/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +66636,77214,69902,PRETRIAL,Nolasco,Antonio,NULL,Male,Hispanic,03/05/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/2/14 0:00,1,Low,8,Risk of Recidivism,-2.66,1,Low,New,1,0 +66636,77214,69902,PRETRIAL,Nolasco,Antonio,NULL,Male,Hispanic,03/05/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66649,77232,69918,Probation,Black,Justin,NULL,Male,African-American,06/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,4,High,7,Risk of Violence,-1.19,8,High,New,1,0 +66649,77232,69918,Probation,Black,Justin,NULL,Male,African-American,06/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +66649,77232,69918,Probation,Black,Justin,NULL,Male,African-American,06/01/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +774,77239,69924,PRETRIAL,MCGROARTHY,MICHAEL,JOSEPH,Male,Caucasian,12/12/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +774,77239,69924,PRETRIAL,MCGROARTHY,MICHAEL,JOSEPH,Male,Caucasian,12/12/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +774,77239,69924,PRETRIAL,MCGROARTHY,MICHAEL,JOSEPH,Male,Caucasian,12/12/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66637,77218,69904,Probation,Lynch,Henry,NULL,Male,Caucasian,11/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +66637,77218,69904,Probation,Lynch,Henry,NULL,Male,Caucasian,11/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +66637,77218,69904,Probation,Lynch,Henry,NULL,Male,Caucasian,11/04/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +64665,77216,67718,PRETRIAL,SHERWOOD,MCDOWELL,NULL,Male,Caucasian,06/05/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +64665,77216,67718,PRETRIAL,SHERWOOD,MCDOWELL,NULL,Male,Caucasian,06/05/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,4,High,8,Risk of Recidivism,0.76,10,High,New,1,0 +64665,77216,67718,PRETRIAL,SHERWOOD,MCDOWELL,NULL,Male,Caucasian,06/05/91,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,4,High,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +66642,77223,69909,Probation,Miller,Troy,NULL,Male,Caucasian,10/01/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/2/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +66642,77223,69909,Probation,Miller,Troy,NULL,Male,Caucasian,10/01/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/2/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +66642,77223,69909,Probation,Miller,Troy,NULL,Male,Caucasian,10/01/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66647,77230,69916,Probation,Diaz Gamboa,Alem,NULL,Male,Hispanic,08/31/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +66647,77230,69916,Probation,Diaz Gamboa,Alem,NULL,Male,Hispanic,08/31/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +66647,77230,69916,Probation,Diaz Gamboa,Alem,NULL,Male,Hispanic,08/31/80,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +36743,77237,69922,PRETRIAL,micco,jerry,cyrus,Male,Other,08/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +36743,77237,69922,PRETRIAL,micco,jerry,cyrus,Male,Other,08/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.85,10,High,New,1,0 +36743,77237,69922,PRETRIAL,micco,jerry,cyrus,Male,Other,08/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +66632,77209,69897,PRETRIAL,Charles,Molaine,NULL,Female,Other,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/2/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +66632,77209,69897,PRETRIAL,Charles,Molaine,NULL,Female,Other,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/2/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +66632,77209,69897,PRETRIAL,Charles,Molaine,NULL,Female,Other,01/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +36234,77215,69903,PRETRIAL,Williams,Debra,NULL,Female,Caucasian,09/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/2/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +36234,77215,69903,PRETRIAL,Williams,Debra,NULL,Female,Caucasian,09/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/2/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +36234,77215,69903,PRETRIAL,Williams,Debra,NULL,Female,Caucasian,09/30/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +66641,77222,69908,Probation,Perry,Mitchell,NULL,Male,Caucasian,02/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +66641,77222,69908,Probation,Perry,Mitchell,NULL,Male,Caucasian,02/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +66641,77222,69908,Probation,Perry,Mitchell,NULL,Male,Caucasian,02/14/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66643,77224,69910,PRETRIAL,LOUIS,STANLEY,NULL,Male,African-American,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +66643,77224,69910,PRETRIAL,LOUIS,STANLEY,NULL,Male,African-American,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +66643,77224,69910,PRETRIAL,LOUIS,STANLEY,NULL,Male,African-American,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66648,77231,69917,PRETRIAL,zalloum,sondra,NULL,Female,Caucasian,10/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +66648,77231,69917,PRETRIAL,zalloum,sondra,NULL,Female,Caucasian,10/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +66648,77231,69917,PRETRIAL,zalloum,sondra,NULL,Female,Caucasian,10/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66633,77210,69898,PRETRIAL,Murphy,Rosiland,Michelle,Female,African-American,09/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +66633,77210,69898,PRETRIAL,Murphy,Rosiland,Michelle,Female,African-American,09/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +66633,77210,69898,PRETRIAL,Murphy,Rosiland,Michelle,Female,African-American,09/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66645,77227,69913,PRETRIAL,MARING,CHRISTOPHER,NULL,Male,African-American,10/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +66645,77227,69913,PRETRIAL,MARING,CHRISTOPHER,NULL,Male,African-American,10/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.05,10,High,New,1,0 +66645,77227,69913,PRETRIAL,MARING,CHRISTOPHER,NULL,Male,African-American,10/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66634,77211,69899,PRETRIAL,Long,Joshua,Eugene,Male,Caucasian,10/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +66634,77211,69899,PRETRIAL,Long,Joshua,Eugene,Male,Caucasian,10/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +66634,77211,69899,PRETRIAL,Long,Joshua,Eugene,Male,Caucasian,10/01/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +5845,77226,69912,PRETRIAL,HOLMES,TONY,Denard,Male,African-American,12/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,4,High,7,Risk of Violence,-0.88,9,High,New,1,0 +5845,77226,69912,PRETRIAL,HOLMES,TONY,Denard,Male,African-American,12/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +5845,77226,69912,PRETRIAL,HOLMES,TONY,Denard,Male,African-American,12/09/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/2/14 0:00,4,High,18,Risk of Failure to Appear,35,10,High,New,1,0 +66635,77213,69901,PRETRIAL,Walls,Tavoris,D,Male,African-American,06/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +66635,77213,69901,PRETRIAL,Walls,Tavoris,D,Male,African-American,06/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +66635,77213,69901,PRETRIAL,Walls,Tavoris,D,Male,African-American,06/07/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66638,77219,69905,Probation,ellis,Priscilla,NULL,Female,Hispanic,01/19/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/2/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +66638,77219,69905,Probation,ellis,Priscilla,NULL,Female,Hispanic,01/19/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/2/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +66638,77219,69905,Probation,ellis,Priscilla,NULL,Female,Hispanic,01/19/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66651,77234,69920,PRETRIAL,GIURGIUVEANU,EMILI,NULL,Male,Caucasian,03/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/2/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +66651,77234,69920,PRETRIAL,GIURGIUVEANU,EMILI,NULL,Male,Caucasian,03/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/2/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +66651,77234,69920,PRETRIAL,GIURGIUVEANU,EMILI,NULL,Male,Caucasian,03/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +1733,1547,1430,PRETRIAL,Orie,Horace,NULL,Male,African-American,04/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +1733,1547,1430,PRETRIAL,Orie,Horace,NULL,Male,African-American,04/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +1733,1547,1430,PRETRIAL,Orie,Horace,NULL,Male,African-American,04/17/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66631,77208,69896,PRETRIAL,Brayboy,Tina,NULL,Male,African-American,05/31/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +66631,77208,69896,PRETRIAL,Brayboy,Tina,NULL,Male,African-American,05/31/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +66631,77208,69896,PRETRIAL,Brayboy,Tina,NULL,Male,African-American,05/31/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +66646,77229,69915,PRETRIAL,Terrell,Randy,NULL,Male,Caucasian,03/07/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,10/2/14 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +66646,77229,69915,PRETRIAL,Terrell,Randy,NULL,Male,Caucasian,03/07/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,10/2/14 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +66646,77229,69915,PRETRIAL,Terrell,Randy,NULL,Male,Caucasian,03/07/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66640,77221,69907,Probation,Derry,Beth,Ann,Female,Caucasian,10/30/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/2/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +66640,77221,69907,Probation,Derry,Beth,Ann,Female,Caucasian,10/30/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/2/14 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +66640,77221,69907,Probation,Derry,Beth,Ann,Female,Caucasian,10/30/73,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/2/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +66663,77250,69935,PRETRIAL,Hathaway,Ema,V,Female,Caucasian,02/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +66663,77250,69935,PRETRIAL,Hathaway,Ema,V,Female,Caucasian,02/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +66663,77250,69935,PRETRIAL,Hathaway,Ema,V,Female,Caucasian,02/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66656,77242,69927,PRETRIAL,Giacci,Kenneth,NULL,Male,Caucasian,10/17/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +66656,77242,69927,PRETRIAL,Giacci,Kenneth,NULL,Male,Caucasian,10/17/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +66656,77242,69927,PRETRIAL,Giacci,Kenneth,NULL,Male,Caucasian,10/17/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +66683,77276,69958,PRETRIAL,MONTGOMERY,NICOLE,NULL,Female,Caucasian,01/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +66683,77276,69958,PRETRIAL,MONTGOMERY,NICOLE,NULL,Female,Caucasian,01/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +66683,77276,69958,PRETRIAL,MONTGOMERY,NICOLE,NULL,Female,Caucasian,01/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58177,77255,69940,PRETRIAL,Frazier,Clyde,A,Male,African-American,07/21/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +58177,77255,69940,PRETRIAL,Frazier,Clyde,A,Male,African-American,07/21/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.92,10,High,New,1,0 +58177,77255,69940,PRETRIAL,Frazier,Clyde,A,Male,African-American,07/21/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,2,Low,New,1,0 +66661,77247,69932,PRETRIAL,Metelus,Alphonce,NULL,Male,African-American,07/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +66661,77247,69932,PRETRIAL,Metelus,Alphonce,NULL,Male,African-American,07/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +66661,77247,69932,PRETRIAL,Metelus,Alphonce,NULL,Male,African-American,07/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66669,77261,69946,PRETRIAL,Montez,Katherine,NULL,Female,Caucasian,04/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +66669,77261,69946,PRETRIAL,Montez,Katherine,NULL,Female,Caucasian,04/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +66669,77261,69946,PRETRIAL,Montez,Katherine,NULL,Female,Caucasian,04/08/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66686,77278,69959,PRETRIAL,Perez-Adams,Jessica,NULL,Female,Hispanic,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,2,Medium,7,Risk of Violence,-2.52,3,Low,New,1,0 +66686,77278,69959,PRETRIAL,Perez-Adams,Jessica,NULL,Female,Hispanic,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +66686,77278,69959,PRETRIAL,Perez-Adams,Jessica,NULL,Female,Hispanic,07/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +3879,77257,69942,PRETRIAL,OHANA,JOSHUA,NULL,Male,Other,10/20/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +3879,77257,69942,PRETRIAL,OHANA,JOSHUA,NULL,Male,Other,10/20/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +3879,77257,69942,PRETRIAL,OHANA,JOSHUA,NULL,Male,Other,10/20/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66657,77243,69928,PRETRIAL,Arroya,Juan,NULL,Male,African-American,02/05/41,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-4.46,1,Low,New,1,0 +66657,77243,69928,PRETRIAL,Arroya,Juan,NULL,Male,African-American,02/05/41,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-2.7,1,Low,New,1,0 +66657,77243,69928,PRETRIAL,Arroya,Juan,NULL,Male,African-American,02/05/41,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66659,77245,69930,PRETRIAL,Vittman,Tibor,Istvan,Male,Caucasian,04/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +66659,77245,69930,PRETRIAL,Vittman,Tibor,Istvan,Male,Caucasian,04/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +66659,77245,69930,PRETRIAL,Vittman,Tibor,Istvan,Male,Caucasian,04/24/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +50532,77273,51570,PRETRIAL,Giordano,Rocco,NULL,Male,Caucasian,12/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,Copy,1,0 +50532,77273,51570,PRETRIAL,Giordano,Rocco,NULL,Male,Caucasian,12/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,Copy,1,0 +50532,77273,51570,PRETRIAL,Giordano,Rocco,NULL,Male,Caucasian,12/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +66665,77252,69937,PRETRIAL,GARCIA,ALFONSO,NULL,Male,Hispanic,01/23/54,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-4.34,1,Low,New,1,0 +66665,77252,69937,PRETRIAL,GARCIA,ALFONSO,NULL,Male,Hispanic,01/23/54,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-2.74,1,Low,New,1,0 +66665,77252,69937,PRETRIAL,GARCIA,ALFONSO,NULL,Male,Hispanic,01/23/54,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58979,77258,69943,PRETRIAL,benitez-morales,angelica,NULL,Female,Hispanic,11/14/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +58979,77258,69943,PRETRIAL,benitez-morales,angelica,NULL,Female,Hispanic,11/14/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +58979,77258,69943,PRETRIAL,benitez-morales,angelica,NULL,Female,Hispanic,11/14/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66668,77260,69945,Probation,Martinez,Brandon,Alexander,Male,Hispanic,07/07/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/14 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +66668,77260,69945,Probation,Martinez,Brandon,Alexander,Male,Hispanic,07/07/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +66668,77260,69945,Probation,Martinez,Brandon,Alexander,Male,Hispanic,07/07/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/3/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +49776,77251,69936,PRETRIAL,Navarrette,George,NULL,Male,Hispanic,09/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +49776,77251,69936,PRETRIAL,Navarrette,George,NULL,Male,Hispanic,09/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +49776,77251,69936,PRETRIAL,Navarrette,George,NULL,Male,Hispanic,09/25/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +65972,77253,69938,Probation,Delgiudice,Gibran,NULL,Male,Hispanic,08/01/86,17,All Scales,Intake,English,Other,Probation,Single,10/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.87,9,High,New,1,0 +65972,77253,69938,Probation,Delgiudice,Gibran,NULL,Male,Hispanic,08/01/86,17,All Scales,Intake,English,Other,Probation,Single,10/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.1,6,Medium,New,1,0 +65972,77253,69938,Probation,Delgiudice,Gibran,NULL,Male,Hispanic,08/01/86,17,All Scales,Intake,English,Other,Probation,Single,10/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +66658,77244,69929,PRETRIAL,Williams,Ricardo,Bricenco,Male,Other,01/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +66658,77244,69929,PRETRIAL,Williams,Ricardo,Bricenco,Male,Other,01/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +66658,77244,69929,PRETRIAL,Williams,Ricardo,Bricenco,Male,Other,01/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66682,77274,69956,PRETRIAL,Fulmore,Eric,NULL,Male,African-American,02/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +66682,77274,69956,PRETRIAL,Fulmore,Eric,NULL,Male,African-American,02/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +66682,77274,69956,PRETRIAL,Fulmore,Eric,NULL,Male,African-American,02/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66639,77269,69906,PRETRIAL,Benemerito,Christina,NULL,Female,Caucasian,02/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,2,Medium,7,Risk of Violence,-2.79,2,Low,Copy,1,0 +66639,77269,69906,PRETRIAL,Benemerito,Christina,NULL,Female,Caucasian,02/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,Copy,1,0 +66639,77269,69906,PRETRIAL,Benemerito,Christina,NULL,Female,Caucasian,02/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/3/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +37797,77270,53718,PRETRIAL,Cooper,Linton,NULL,Male,African-American,01/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/3/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,Copy,1,0 +37797,77270,53718,PRETRIAL,Cooper,Linton,NULL,Male,African-American,01/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/3/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,Copy,1,0 +37797,77270,53718,PRETRIAL,Cooper,Linton,NULL,Male,African-American,01/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +64627,77248,69933,PRETRIAL,MILLER,EILEEN,THERESA,Female,Caucasian,09/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-3.73,1,Low,New,1,0 +64627,77248,69933,PRETRIAL,MILLER,EILEEN,THERESA,Female,Caucasian,09/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +64627,77248,69933,PRETRIAL,MILLER,EILEEN,THERESA,Female,Caucasian,09/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +8828,77262,69947,Probation,sebasty,robb,NULL,Male,Caucasian,07/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +8828,77262,69947,Probation,sebasty,robb,NULL,Male,Caucasian,07/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +8828,77262,69947,Probation,sebasty,robb,NULL,Male,Caucasian,07/22/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66684,77275,69957,PRETRIAL,MAXWELL,ALLEN,DENARD,Male,African-American,03/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.69,6,Medium,New,1,0 +66684,77275,69957,PRETRIAL,MAXWELL,ALLEN,DENARD,Male,African-American,03/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +66684,77275,69957,PRETRIAL,MAXWELL,ALLEN,DENARD,Male,African-American,03/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +66662,77249,69934,PRETRIAL,Franklin,Quatrona,NULL,Female,African-American,02/17/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +66662,77249,69934,PRETRIAL,Franklin,Quatrona,NULL,Female,African-American,02/17/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,8,High,New,1,0 +66662,77249,69934,PRETRIAL,Franklin,Quatrona,NULL,Female,African-American,02/17/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66666,77254,69939,Probation,SCHUTZ,DAVID,NULL,Male,Caucasian,05/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +66666,77254,69939,Probation,SCHUTZ,DAVID,NULL,Male,Caucasian,05/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +66666,77254,69939,Probation,SCHUTZ,DAVID,NULL,Male,Caucasian,05/10/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66667,77256,69941,Probation,Jack,Thibaut,NULL,Male,Caucasian,05/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/3/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +66667,77256,69941,Probation,Jack,Thibaut,NULL,Male,Caucasian,05/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/3/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +66667,77256,69941,Probation,Jack,Thibaut,NULL,Male,Caucasian,05/20/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +40286,77259,69944,PRETRIAL,Bryant,Anton,NULL,Male,African-American,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +40286,77259,69944,PRETRIAL,Bryant,Anton,NULL,Male,African-American,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +40286,77259,69944,PRETRIAL,Bryant,Anton,NULL,Male,African-American,06/10/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +66660,77246,69931,PRETRIAL,Lester,Charlene,NULL,Female,African-American,12/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +66660,77246,69931,PRETRIAL,Lester,Charlene,NULL,Female,African-American,12/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +66660,77246,69931,PRETRIAL,Lester,Charlene,NULL,Female,African-American,12/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/3/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +36274,77285,69963,PRETRIAL,WIGGINS,BLAINE,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +36274,77285,69963,PRETRIAL,WIGGINS,BLAINE,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.87,10,High,New,1,0 +36274,77285,69963,PRETRIAL,WIGGINS,BLAINE,NULL,Male,African-American,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66700,77293,69969,PRETRIAL,FREITASGONZALEZ,luis,NULL,Male,Hispanic,02/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +66700,77293,69969,PRETRIAL,FREITASGONZALEZ,luis,NULL,Male,Hispanic,02/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +66700,77293,69969,PRETRIAL,FREITASGONZALEZ,luis,NULL,Male,Hispanic,02/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66697,77290,69967,PRETRIAL,Akhter,Shazia,NULL,Female,Caucasian,04/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +66697,77290,69967,PRETRIAL,Akhter,Shazia,NULL,Female,Caucasian,04/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/14 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,New,1,0 +66697,77290,69967,PRETRIAL,Akhter,Shazia,NULL,Female,Caucasian,04/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66689,77283,69962,PRETRIAL,KELLOM,JERMEL,NULL,Female,African-American,05/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +66689,77283,69962,PRETRIAL,KELLOM,JERMEL,NULL,Female,African-American,05/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +66689,77283,69962,PRETRIAL,KELLOM,JERMEL,NULL,Female,African-American,05/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +20002,77291,19222,PRETRIAL,Danson,Jeffrey,Bristando,Male,African-American,12/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,Copy,1,0 +20002,77291,19222,PRETRIAL,Danson,Jeffrey,Bristando,Male,African-American,12/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,Copy,1,0 +20002,77291,19222,PRETRIAL,Danson,Jeffrey,Bristando,Male,African-American,12/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +66702,77295,69971,PRETRIAL,Williams,Sannie,NULL,Male,African-American,06/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +66702,77295,69971,PRETRIAL,Williams,Sannie,NULL,Male,African-American,06/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +66702,77295,69971,PRETRIAL,Williams,Sannie,NULL,Male,African-American,06/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66687,77279,69960,PRETRIAL,Valcin,Markenson,NULL,Male,African-American,08/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +66687,77279,69960,PRETRIAL,Valcin,Markenson,NULL,Male,African-American,08/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +66687,77279,69960,PRETRIAL,Valcin,Markenson,NULL,Male,African-American,08/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66695,77288,69965,PRETRIAL,cooper,dan,NULL,Male,African-American,06/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +66695,77288,69965,PRETRIAL,cooper,dan,NULL,Male,African-American,06/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.71,10,High,New,1,0 +66695,77288,69965,PRETRIAL,cooper,dan,NULL,Male,African-American,06/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,40,10,High,New,1,0 +66688,77280,69961,PRETRIAL,Oliva-diaz,Donel,NULL,Male,Caucasian,08/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +66688,77280,69961,PRETRIAL,Oliva-diaz,Donel,NULL,Male,Caucasian,08/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +66688,77280,69961,PRETRIAL,Oliva-diaz,Donel,NULL,Male,Caucasian,08/20/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +31819,77287,30821,PRETRIAL,rathburn,rebecca,NULL,Female,Caucasian,01/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/4/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,Copy,1,0 +31819,77287,30821,PRETRIAL,rathburn,rebecca,NULL,Female,Caucasian,01/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/4/14 0:00,1,Low,8,Risk of Recidivism,-1.18,3,Low,Copy,1,0 +31819,77287,30821,PRETRIAL,rathburn,rebecca,NULL,Female,Caucasian,01/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +66701,77294,69970,PRETRIAL,Aguilar,Lester,NULL,Male,Other,08/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +66701,77294,69970,PRETRIAL,Aguilar,Lester,NULL,Male,Other,08/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +66701,77294,69970,PRETRIAL,Aguilar,Lester,NULL,Male,Other,08/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +45856,77282,46185,PRETRIAL,Graham,Nicholas,Barrington,Male,African-American,08/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,Copy,1,0 +45856,77282,46185,PRETRIAL,Graham,Nicholas,Barrington,Male,African-American,08/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,Copy,1,0 +45856,77282,46185,PRETRIAL,Graham,Nicholas,Barrington,Male,African-American,08/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +29710,77296,69972,PRETRIAL,CORTES,DANIEL,NULL,Male,Caucasian,04/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +29710,77296,69972,PRETRIAL,CORTES,DANIEL,NULL,Male,Caucasian,04/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +29710,77296,69972,PRETRIAL,CORTES,DANIEL,NULL,Male,Caucasian,04/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66699,77292,69968,PRETRIAL,PAPANTONIO,DIANE,NULL,Female,Caucasian,03/02/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/4/14 0:00,1,Low,7,Risk of Violence,-4.22,1,Low,New,1,0 +66699,77292,69968,PRETRIAL,PAPANTONIO,DIANE,NULL,Female,Caucasian,03/02/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/4/14 0:00,1,Low,8,Risk of Recidivism,-2.6,1,Low,New,1,0 +66699,77292,69968,PRETRIAL,PAPANTONIO,DIANE,NULL,Female,Caucasian,03/02/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/4/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +32340,77284,31367,PRETRIAL,FERGUSON,ANTHONY,G,Male,African-American,12/02/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,10/4/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,Copy,1,0 +32340,77284,31367,PRETRIAL,FERGUSON,ANTHONY,G,Male,African-American,12/02/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,10/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,Copy,1,0 +32340,77284,31367,PRETRIAL,FERGUSON,ANTHONY,G,Male,African-American,12/02/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,10/4/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +66696,77289,69966,PRETRIAL,baptiste,rakeem,NULL,Female,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,New,1,0 +66696,77289,69966,PRETRIAL,baptiste,rakeem,NULL,Female,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +66696,77289,69966,PRETRIAL,baptiste,rakeem,NULL,Female,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/4/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66713,77310,69985,PRETRIAL,RESTORODRIGUEZ,BERNARDO,NULL,Male,Hispanic,02/26/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/5/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +66713,77310,69985,PRETRIAL,RESTORODRIGUEZ,BERNARDO,NULL,Male,Hispanic,02/26/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/5/14 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +66713,77310,69985,PRETRIAL,RESTORODRIGUEZ,BERNARDO,NULL,Male,Hispanic,02/26/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66703,77297,69973,PRETRIAL,HOBAUGH,EDWARD,GEORGE,Male,Caucasian,01/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +66703,77297,69973,PRETRIAL,HOBAUGH,EDWARD,GEORGE,Male,Caucasian,01/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +66703,77297,69973,PRETRIAL,HOBAUGH,EDWARD,GEORGE,Male,Caucasian,01/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66708,77305,69980,PRETRIAL,Graham,Dustin,NULL,Male,Caucasian,04/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +66708,77305,69980,PRETRIAL,Graham,Dustin,NULL,Male,Caucasian,04/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +66708,77305,69980,PRETRIAL,Graham,Dustin,NULL,Male,Caucasian,04/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66717,77312,69987,PRETRIAL,Acevedo,Jose,A,Male,Hispanic,08/23/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/5/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +66717,77312,69987,PRETRIAL,Acevedo,Jose,A,Male,Hispanic,08/23/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/5/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +66717,77312,69987,PRETRIAL,Acevedo,Jose,A,Male,Hispanic,08/23/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66707,77303,69978,PRETRIAL,Benton,Nicholas,NULL,Male,Caucasian,07/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +66707,77303,69978,PRETRIAL,Benton,Nicholas,NULL,Male,Caucasian,07/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +66707,77303,69978,PRETRIAL,Benton,Nicholas,NULL,Male,Caucasian,07/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66711,77308,69983,PRETRIAL,FRASER,CEDRIC,PAULIUS,Male,African-American,12/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +66711,77308,69983,PRETRIAL,FRASER,CEDRIC,PAULIUS,Male,African-American,12/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +66711,77308,69983,PRETRIAL,FRASER,CEDRIC,PAULIUS,Male,African-American,12/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +18591,77301,17853,PRETRIAL,BETTENCOURT,RYAN,NULL,Male,Caucasian,06/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.31,3,Low,Copy,1,0 +18591,77301,17853,PRETRIAL,BETTENCOURT,RYAN,NULL,Male,Caucasian,06/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,Copy,1,0 +18591,77301,17853,PRETRIAL,BETTENCOURT,RYAN,NULL,Male,Caucasian,06/28/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +66712,77309,69984,PRETRIAL,HIBBERT,CLOVIS,RICHARD,Male,Caucasian,04/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +66712,77309,69984,PRETRIAL,HIBBERT,CLOVIS,RICHARD,Male,Caucasian,04/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +66712,77309,69984,PRETRIAL,HIBBERT,CLOVIS,RICHARD,Male,Caucasian,04/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66705,77302,69977,PRETRIAL,MARINERO,JUAN,CARLOS,Male,Hispanic,02/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +66705,77302,69977,PRETRIAL,MARINERO,JUAN,CARLOS,Male,Hispanic,02/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +66705,77302,69977,PRETRIAL,MARINERO,JUAN,CARLOS,Male,Hispanic,02/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66706,77304,69979,PRETRIAL,Spencer,Anthony,NULL,Male,African-American,09/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +66706,77304,69979,PRETRIAL,Spencer,Anthony,NULL,Male,African-American,09/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +66706,77304,69979,PRETRIAL,Spencer,Anthony,NULL,Male,African-American,09/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66704,77300,69976,PRETRIAL,HERON,PATRICK,ROMAINE,Male,African-American,12/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +66704,77300,69976,PRETRIAL,HERON,PATRICK,ROMAINE,Male,African-American,12/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/14 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +66704,77300,69976,PRETRIAL,HERON,PATRICK,ROMAINE,Male,African-American,12/17/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/5/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66710,77307,69982,PRETRIAL,Ingentito,Gary,T,Male,Caucasian,03/31/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/5/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +66710,77307,69982,PRETRIAL,Ingentito,Gary,T,Male,Caucasian,03/31/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/5/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +66710,77307,69982,PRETRIAL,Ingentito,Gary,T,Male,Caucasian,03/31/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +34535,77298,69974,PRETRIAL,Sands,Barel,NULL,Male,African-American,07/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,New,1,0 +34535,77298,69974,PRETRIAL,Sands,Barel,NULL,Male,African-American,07/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +34535,77298,69974,PRETRIAL,Sands,Barel,NULL,Male,African-American,07/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66714,77311,69986,PRETRIAL,JEANBAPTISTE,FRANTZ,NULL,Male,African-American,07/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +66714,77311,69986,PRETRIAL,JEANBAPTISTE,FRANTZ,NULL,Male,African-American,07/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +66714,77311,69986,PRETRIAL,JEANBAPTISTE,FRANTZ,NULL,Male,African-American,07/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/5/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66709,77306,69981,PRETRIAL,GOLDSTON,HARSAIN,BAYYAN,Male,African-American,10/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/5/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +66709,77306,69981,PRETRIAL,GOLDSTON,HARSAIN,BAYYAN,Male,African-American,10/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/5/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +66709,77306,69981,PRETRIAL,GOLDSTON,HARSAIN,BAYYAN,Male,African-American,10/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66727,77327,70002,Probation,Iwanow,Jesse,NULL,Male,Caucasian,06/12/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,2,Medium,7,Risk of Violence,-2.42,3,Low,New,1,0 +66727,77327,70002,Probation,Iwanow,Jesse,NULL,Male,Caucasian,06/12/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +66727,77327,70002,Probation,Iwanow,Jesse,NULL,Male,Caucasian,06/12/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,New,1,0 +18770,77335,70009,PRETRIAL,Reddicks,Tasten,NULL,Male,African-American,12/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +18770,77335,70009,PRETRIAL,Reddicks,Tasten,NULL,Male,African-American,12/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +18770,77335,70009,PRETRIAL,Reddicks,Tasten,NULL,Male,African-American,12/10/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57840,77314,69989,PRETRIAL,Flewellyn,Joshua,Michael,Male,Caucasian,04/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/6/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +57840,77314,69989,PRETRIAL,Flewellyn,Joshua,Michael,Male,Caucasian,04/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/6/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +57840,77314,69989,PRETRIAL,Flewellyn,Joshua,Michael,Male,Caucasian,04/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66722,77319,69994,PRETRIAL,Perez,Kenny,NULL,Male,Hispanic,07/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +66722,77319,69994,PRETRIAL,Perez,Kenny,NULL,Male,Hispanic,07/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +66722,77319,69994,PRETRIAL,Perez,Kenny,NULL,Male,Hispanic,07/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66723,77321,69996,PRETRIAL,NGUYEN,JERRY,NULL,Male,Caucasian,08/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +66723,77321,69996,PRETRIAL,NGUYEN,JERRY,NULL,Male,Caucasian,08/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +66723,77321,69996,PRETRIAL,NGUYEN,JERRY,NULL,Male,Caucasian,08/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66743,77346,70019,PRETRIAL,DIAS,TYSHAWN,RAY,Male,African-American,05/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.1,8,High,New,1,0 +66743,77346,70019,PRETRIAL,DIAS,TYSHAWN,RAY,Male,African-American,05/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +66743,77346,70019,PRETRIAL,DIAS,TYSHAWN,RAY,Male,African-American,05/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66726,77325,70000,PRETRIAL,wachington,janae,NULL,Female,African-American,03/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +66726,77325,70000,PRETRIAL,wachington,janae,NULL,Female,African-American,03/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +66726,77325,70000,PRETRIAL,wachington,janae,NULL,Female,African-American,03/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66740,77342,70015,Probation,Wade,Morgan,NULL,Female,Caucasian,07/18/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/6/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +66740,77342,70015,Probation,Wade,Morgan,NULL,Female,Caucasian,07/18/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/6/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +66740,77342,70015,Probation,Wade,Morgan,NULL,Female,Caucasian,07/18/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +32562,77316,69991,PRETRIAL,Pew,kevin,NULL,Male,African-American,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/6/14 0:00,2,Medium,7,Risk of Violence,-2.27,3,Low,New,1,0 +32562,77316,69991,PRETRIAL,Pew,kevin,NULL,Male,African-American,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +32562,77316,69991,PRETRIAL,Pew,kevin,NULL,Male,African-American,10/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/6/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66725,77323,69998,PRETRIAL,CONYERS,SHAMIKA,NULL,Female,African-American,09/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.67,2,Low,New,1,0 +66725,77323,69998,PRETRIAL,CONYERS,SHAMIKA,NULL,Female,African-American,09/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,9,High,New,1,0 +66725,77323,69998,PRETRIAL,CONYERS,SHAMIKA,NULL,Female,African-American,09/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +66730,77330,70005,Probation,VALDEZ,ALEXA,NULL,Female,Hispanic,12/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +66730,77330,70005,Probation,VALDEZ,ALEXA,NULL,Female,Hispanic,12/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +66730,77330,70005,Probation,VALDEZ,ALEXA,NULL,Female,Hispanic,12/04/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66736,77337,70011,PRETRIAL,Sacks,Lisa,NULL,Female,Caucasian,08/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/6/14 0:00,2,Medium,7,Risk of Violence,-3.08,1,Low,New,1,0 +66736,77337,70011,PRETRIAL,Sacks,Lisa,NULL,Female,Caucasian,08/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +66736,77337,70011,PRETRIAL,Sacks,Lisa,NULL,Female,Caucasian,08/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/6/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +46205,64262,46579,PRETRIAL,Johnson,Jacob,NULL,Male,African-American,05/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,4,High,7,Risk of Violence,-1.1,8,High,Copy,1,0 +46205,64262,46579,PRETRIAL,Johnson,Jacob,NULL,Male,African-American,05/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,4,High,8,Risk of Recidivism,1.06,10,High,Copy,1,0 +46205,64262,46579,PRETRIAL,Johnson,Jacob,NULL,Male,African-American,05/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,4,High,18,Risk of Failure to Appear,36,10,High,Copy,1,0 +66741,77343,70016,PRETRIAL,Moroney,Donald,Edward,Male,Caucasian,08/20/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/6/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +66741,77343,70016,PRETRIAL,Moroney,Donald,Edward,Male,Caucasian,08/20/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/6/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +66741,77343,70016,PRETRIAL,Moroney,Donald,Edward,Male,Caucasian,08/20/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +66742,77345,70018,Probation,HERNANDEZ,CHRIS,NULL,Male,Hispanic,07/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/6/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +66742,77345,70018,Probation,HERNANDEZ,CHRIS,NULL,Male,Hispanic,07/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/6/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +66742,77345,70018,Probation,HERNANDEZ,CHRIS,NULL,Male,Hispanic,07/29/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66719,77315,69990,PRETRIAL,MAKOVSKY,BRIAN,KEITH,Male,Caucasian,06/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/6/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +66719,77315,69990,PRETRIAL,MAKOVSKY,BRIAN,KEITH,Male,Caucasian,06/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/6/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +66719,77315,69990,PRETRIAL,MAKOVSKY,BRIAN,KEITH,Male,Caucasian,06/01/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +10387,77322,69997,PRETRIAL,HOUSTON,TERRACNE,LEVON,Male,African-American,09/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,2,Medium,7,Risk of Violence,-2.66,2,Low,New,1,0 +10387,77322,69997,PRETRIAL,HOUSTON,TERRACNE,LEVON,Male,African-American,09/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +10387,77322,69997,PRETRIAL,HOUSTON,TERRACNE,LEVON,Male,African-American,09/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58855,77324,69999,PRETRIAL,Higgs,Tiara,NULL,Female,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +58855,77324,69999,PRETRIAL,Higgs,Tiara,NULL,Female,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +58855,77324,69999,PRETRIAL,Higgs,Tiara,NULL,Female,African-American,11/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66729,77329,70004,PRETRIAL,Zelaya,Pedro,NULL,Male,Hispanic,09/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +66729,77329,70004,PRETRIAL,Zelaya,Pedro,NULL,Male,Hispanic,09/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +66729,77329,70004,PRETRIAL,Zelaya,Pedro,NULL,Male,Hispanic,09/27/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66737,77338,70012,PRETRIAL,VILLANUEVA,MARITZA,NULL,Female,Caucasian,09/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +66737,77338,70012,PRETRIAL,VILLANUEVA,MARITZA,NULL,Female,Caucasian,09/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +66737,77338,70012,PRETRIAL,VILLANUEVA,MARITZA,NULL,Female,Caucasian,09/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66720,77317,69992,PRETRIAL,Campbell,Christopher,Oneil,Male,Other,01/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +66720,77317,69992,PRETRIAL,Campbell,Christopher,Oneil,Male,Other,01/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +66720,77317,69992,PRETRIAL,Campbell,Christopher,Oneil,Male,Other,01/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66739,77341,70014,Probation,chavarria,Maria,NULL,Female,Hispanic,05/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +66739,77341,70014,Probation,chavarria,Maria,NULL,Female,Hispanic,05/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +66739,77341,70014,Probation,chavarria,Maria,NULL,Female,Hispanic,05/04/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66724,77320,69995,PRETRIAL,Caffrey,Audra,NULL,Female,Caucasian,07/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +66724,77320,69995,PRETRIAL,Caffrey,Audra,NULL,Female,Caucasian,07/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +66724,77320,69995,PRETRIAL,Caffrey,Audra,NULL,Female,Caucasian,07/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +66733,77333,70008,Probation,Menezes,Luciana,NULL,Female,Hispanic,02/28/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/6/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +66733,77333,70008,Probation,Menezes,Luciana,NULL,Female,Hispanic,02/28/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/6/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +66733,77333,70008,Probation,Menezes,Luciana,NULL,Female,Hispanic,02/28/76,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +46205,77334,46579,PRETRIAL,Johnson,Jacob,NULL,Male,African-American,05/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,4,High,7,Risk of Violence,-1.12,8,High,Copy,1,0 +46205,77334,46579,PRETRIAL,Johnson,Jacob,NULL,Male,African-American,05/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,4,High,8,Risk of Recidivism,1.16,10,High,Copy,1,0 +46205,77334,46579,PRETRIAL,Johnson,Jacob,NULL,Male,African-American,05/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,4,High,18,Risk of Failure to Appear,36,10,High,Copy,1,0 +66728,77326,70001,PRETRIAL,Rivera,Michele,NULL,Female,Caucasian,01/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +66728,77326,70001,PRETRIAL,Rivera,Michele,NULL,Female,Caucasian,01/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-1.28,3,Low,New,1,0 +66728,77326,70001,PRETRIAL,Rivera,Michele,NULL,Female,Caucasian,01/25/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +50783,77328,70003,PRETRIAL,Salkeld,Tamara,Leana,Female,Caucasian,10/21/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,New,1,0 +50783,77328,70003,PRETRIAL,Salkeld,Tamara,Leana,Female,Caucasian,10/21/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.86,10,High,New,1,0 +50783,77328,70003,PRETRIAL,Salkeld,Tamara,Leana,Female,Caucasian,10/21/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +66718,77313,69988,PRETRIAL,CASTRO,NAIBOBY,NULL,Male,Hispanic,09/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/6/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +66718,77313,69988,PRETRIAL,CASTRO,NAIBOBY,NULL,Male,Hispanic,09/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/6/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +66718,77313,69988,PRETRIAL,CASTRO,NAIBOBY,NULL,Male,Hispanic,09/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66731,77331,70006,PRETRIAL,Villalobos,Guillermo,Rafael,Male,Caucasian,01/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/6/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +66731,77331,70006,PRETRIAL,Villalobos,Guillermo,Rafael,Male,Caucasian,01/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/6/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +66731,77331,70006,PRETRIAL,Villalobos,Guillermo,Rafael,Male,Caucasian,01/29/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +55243,77344,70017,PRETRIAL,Young,Kenneth,NULL,Male,Caucasian,10/31/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +55243,77344,70017,PRETRIAL,Young,Kenneth,NULL,Male,Caucasian,10/31/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +55243,77344,70017,PRETRIAL,Young,Kenneth,NULL,Male,Caucasian,10/31/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66738,77339,70013,Probation,Garcia,Ruddy,Savier,Male,Hispanic,03/15/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/6/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +66738,77339,70013,Probation,Garcia,Ruddy,Savier,Male,Hispanic,03/15/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/6/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +66738,77339,70013,Probation,Garcia,Ruddy,Savier,Male,Hispanic,03/15/82,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66721,77318,69993,PRETRIAL,Reyes,Amanda,NULL,Female,Caucasian,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +66721,77318,69993,PRETRIAL,Reyes,Amanda,NULL,Female,Caucasian,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +66721,77318,69993,PRETRIAL,Reyes,Amanda,NULL,Female,Caucasian,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66735,77336,70010,Probation,Dolgon,Matthew,NULL,Male,Caucasian,08/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +66735,77336,70010,Probation,Dolgon,Matthew,NULL,Male,Caucasian,08/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +66735,77336,70010,Probation,Dolgon,Matthew,NULL,Male,Caucasian,08/29/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/6/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66771,77386,70054,PRETRIAL,Pierre,allande,NULL,Male,African-American,12/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +66771,77386,70054,PRETRIAL,Pierre,allande,NULL,Male,African-American,12/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +66771,77386,70054,PRETRIAL,Pierre,allande,NULL,Male,African-American,12/23/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66752,77357,70029,PRETRIAL,GRIFFIN,GWENDOLYNE,RENEE,Female,African-American,09/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,2,Medium,7,Risk of Violence,-3.12,1,Low,New,1,0 +66752,77357,70029,PRETRIAL,GRIFFIN,GWENDOLYNE,RENEE,Female,African-American,09/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +66752,77357,70029,PRETRIAL,GRIFFIN,GWENDOLYNE,RENEE,Female,African-American,09/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +28837,77378,70046,PRETRIAL,SINGH,ARVIN,NULL,Male,Other,09/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +28837,77378,70046,PRETRIAL,SINGH,ARVIN,NULL,Male,Other,09/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +28837,77378,70046,PRETRIAL,SINGH,ARVIN,NULL,Male,Other,09/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66757,77365,70036,Probation,Cabrera,Angel,NULL,Male,Hispanic,12/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/7/14 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +66757,77365,70036,Probation,Cabrera,Angel,NULL,Male,Hispanic,12/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +66757,77365,70036,Probation,Cabrera,Angel,NULL,Male,Hispanic,12/08/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/7/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +66746,77349,70022,PRETRIAL,Mercado Quijano,Marcos,NULL,Male,Hispanic,04/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +66746,77349,70022,PRETRIAL,Mercado Quijano,Marcos,NULL,Male,Hispanic,04/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +66746,77349,70022,PRETRIAL,Mercado Quijano,Marcos,NULL,Male,Hispanic,04/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +66750,77354,70026,PRETRIAL,Mcclayton,Merritt,NULL,Female,Caucasian,05/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +66750,77354,70026,PRETRIAL,Mcclayton,Merritt,NULL,Female,Caucasian,05/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +66750,77354,70026,PRETRIAL,Mcclayton,Merritt,NULL,Female,Caucasian,05/09/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66269,77362,69463,PRETRIAL,Ortizgay,Gonzalo,NULL,Male,Hispanic,03/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,Copy,1,0 +66269,77362,69463,PRETRIAL,Ortizgay,Gonzalo,NULL,Male,Hispanic,03/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,Copy,1,0 +66269,77362,69463,PRETRIAL,Ortizgay,Gonzalo,NULL,Male,Hispanic,03/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +58177,77370,60380,PRETRIAL,Frazier,Clyde,A,Male,African-American,07/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,Copy,1,0 +58177,77370,60380,PRETRIAL,Frazier,Clyde,A,Male,African-American,07/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.78,10,High,Copy,1,0 +58177,77370,60380,PRETRIAL,Frazier,Clyde,A,Male,African-American,07/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +66751,77355,70027,PRETRIAL,SANTOUSE,SHAN,NULL,Female,African-American,08/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/7/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +66751,77355,70027,PRETRIAL,SANTOUSE,SHAN,NULL,Female,African-American,08/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/7/14 0:00,1,Low,8,Risk of Recidivism,-2.24,1,Low,New,1,0 +66751,77355,70027,PRETRIAL,SANTOUSE,SHAN,NULL,Female,African-American,08/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66747,77350,70023,PRETRIAL,Dimeo,Anthony,NULL,Female,Caucasian,09/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +66747,77350,70023,PRETRIAL,Dimeo,Anthony,NULL,Female,Caucasian,09/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +66747,77350,70023,PRETRIAL,Dimeo,Anthony,NULL,Female,Caucasian,09/25/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66758,77368,70037,Probation,MERKERSON,GERALD,A,Male,African-American,11/03/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/7/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +66758,77368,70037,Probation,MERKERSON,GERALD,A,Male,African-American,11/03/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +66758,77368,70037,Probation,MERKERSON,GERALD,A,Male,African-American,11/03/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66770,77385,70053,Probation,Hernandez,Lisa,NULL,Female,Hispanic,05/28/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +66770,77385,70053,Probation,Hernandez,Lisa,NULL,Female,Hispanic,05/28/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +66770,77385,70053,Probation,Hernandez,Lisa,NULL,Female,Hispanic,05/28/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66760,77371,70039,Probation,gregory,cordell,NULL,Male,Caucasian,01/14/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/14 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +66760,77371,70039,Probation,gregory,cordell,NULL,Male,Caucasian,01/14/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +66760,77371,70039,Probation,gregory,cordell,NULL,Male,Caucasian,01/14/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66754,77359,70031,PRETRIAL,Cadeau,Alex,Claude,Male,African-American,08/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +66754,77359,70031,PRETRIAL,Cadeau,Alex,Claude,Male,African-American,08/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +66754,77359,70031,PRETRIAL,Cadeau,Alex,Claude,Male,African-American,08/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +55544,77366,57405,Probation,Tellez,Javier,NULL,Male,Hispanic,12/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,Copy,1,0 +55544,77366,57405,Probation,Tellez,Javier,NULL,Male,Hispanic,12/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,Copy,1,0 +55544,77366,57405,Probation,Tellez,Javier,NULL,Male,Hispanic,12/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +66762,77373,70041,PRETRIAL,Casamassa,Cesare,NULL,Male,Caucasian,09/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +66762,77373,70041,PRETRIAL,Casamassa,Cesare,NULL,Male,Caucasian,09/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +66762,77373,70041,PRETRIAL,Casamassa,Cesare,NULL,Male,Caucasian,09/22/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66766,77380,70048,Probation,Duke,Tyler,Edward,Male,Caucasian,09/06/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +66766,77380,70048,Probation,Duke,Tyler,Edward,Male,Caucasian,09/06/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +66766,77380,70048,Probation,Duke,Tyler,Edward,Male,Caucasian,09/06/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66748,77352,70024,PRETRIAL,Conserve,Michelet,NULL,Male,Other,01/20/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/7/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +66748,77352,70024,PRETRIAL,Conserve,Michelet,NULL,Male,Other,01/20/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +66748,77352,70024,PRETRIAL,Conserve,Michelet,NULL,Male,Other,01/20/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51612,77351,56773,PRETRIAL,MOORE,ZACHARY,NULL,Male,Caucasian,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,Copy,1,0 +51612,77351,56773,PRETRIAL,MOORE,ZACHARY,NULL,Male,Caucasian,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,9,High,Copy,1,0 +51612,77351,56773,PRETRIAL,MOORE,ZACHARY,NULL,Male,Caucasian,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +66753,77358,70030,PRETRIAL,Ramos,Richard,NULL,Male,Other,11/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/7/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +66753,77358,70030,PRETRIAL,Ramos,Richard,NULL,Male,Other,11/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +66753,77358,70030,PRETRIAL,Ramos,Richard,NULL,Male,Other,11/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +23502,77360,70032,PRETRIAL,COAKLEY,LECHARLES,RASHAD,Male,African-American,03/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,4,High,7,Risk of Violence,-0.87,9,High,New,1,0 +23502,77360,70032,PRETRIAL,COAKLEY,LECHARLES,RASHAD,Male,African-American,03/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,4,High,8,Risk of Recidivism,0.21,8,High,New,1,0 +23502,77360,70032,PRETRIAL,COAKLEY,LECHARLES,RASHAD,Male,African-American,03/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,4,High,18,Risk of Failure to Appear,34,10,High,New,1,0 +66765,77379,70047,PRETRIAL,JONES,JERRY,NULL,Male,African-American,09/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +66765,77379,70047,PRETRIAL,JONES,JERRY,NULL,Male,African-American,09/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +66765,77379,70047,PRETRIAL,JONES,JERRY,NULL,Male,African-American,09/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66767,77381,70049,PRETRIAL,Douglas,Vishnu,NULL,Male,African-American,02/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +66767,77381,70049,PRETRIAL,Douglas,Vishnu,NULL,Male,African-American,02/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +66767,77381,70049,PRETRIAL,Douglas,Vishnu,NULL,Male,African-American,02/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66763,77376,70044,Probation,AGUERO,RICARDO,NULL,Male,Hispanic,07/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/7/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +66763,77376,70044,Probation,AGUERO,RICARDO,NULL,Male,Hispanic,07/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/7/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +66763,77376,70044,Probation,AGUERO,RICARDO,NULL,Male,Hispanic,07/05/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66756,77363,70034,Probation,Rojas,Juan,Jose,Male,Hispanic,07/17/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/7/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +66756,77363,70034,Probation,Rojas,Juan,Jose,Male,Hispanic,07/17/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +66756,77363,70034,Probation,Rojas,Juan,Jose,Male,Hispanic,07/17/78,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66761,77372,70040,Probation,Drummond,Earl,NULL,Male,African-American,09/08/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/14 0:00,2,Medium,7,Risk of Violence,-2.72,2,Low,New,1,0 +66761,77372,70040,Probation,Drummond,Earl,NULL,Male,African-American,09/08/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +66761,77372,70040,Probation,Drummond,Earl,NULL,Male,African-American,09/08/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/7/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64522,77367,67537,Probation,Johnson,Brian,NULL,Male,Caucasian,08/22/74,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,10/7/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,Copy,1,0 +64522,77367,67537,Probation,Johnson,Brian,NULL,Male,Caucasian,08/22/74,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,Copy,1,0 +64522,77367,67537,Probation,Johnson,Brian,NULL,Male,Caucasian,08/22/74,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +66759,77369,70038,PRETRIAL,Serna,Daniel,S,Male,Hispanic,06/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +66759,77369,70038,PRETRIAL,Serna,Daniel,S,Male,Hispanic,06/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +66759,77369,70038,PRETRIAL,Serna,Daniel,S,Male,Hispanic,06/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66745,77348,70021,PRETRIAL,Toliver,Brittany,Chanel,Female,African-American,11/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +66745,77348,70021,PRETRIAL,Toliver,Brittany,Chanel,Female,African-American,11/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +66745,77348,70021,PRETRIAL,Toliver,Brittany,Chanel,Female,African-American,11/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66764,77377,70045,Probation,REDMOND,DAVID,PAUL,Male,Caucasian,05/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/7/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +66764,77377,70045,Probation,REDMOND,DAVID,PAUL,Male,Caucasian,05/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/7/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +66764,77377,70045,Probation,REDMOND,DAVID,PAUL,Male,Caucasian,05/23/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/7/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66291,77356,70028,PRETRIAL,Restaino,Gerard,NULL,Male,African-American,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,2,Medium,7,Risk of Violence,-1.28,7,Medium,New,1,0 +66291,77356,70028,PRETRIAL,Restaino,Gerard,NULL,Male,African-American,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +66291,77356,70028,PRETRIAL,Restaino,Gerard,NULL,Male,African-American,08/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66749,77353,70025,PRETRIAL,Harris,Kwamane,NULL,Male,African-American,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +66749,77353,70025,PRETRIAL,Harris,Kwamane,NULL,Male,African-American,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +66749,77353,70025,PRETRIAL,Harris,Kwamane,NULL,Male,African-American,08/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/7/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +42210,77374,70042,PRETRIAL,Balda,Spencer,NULL,Male,Caucasian,01/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/14 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +42210,77374,70042,PRETRIAL,Balda,Spencer,NULL,Male,Caucasian,01/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +42210,77374,70042,PRETRIAL,Balda,Spencer,NULL,Male,Caucasian,01/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/7/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66778,77395,70062,PRETRIAL,McGowan,Trashundra,NULL,Female,African-American,10/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +66778,77395,70062,PRETRIAL,McGowan,Trashundra,NULL,Female,African-American,10/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +66778,77395,70062,PRETRIAL,McGowan,Trashundra,NULL,Female,African-American,10/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66789,77408,70073,PRETRIAL,Bush,Jaquez,Dantrell,Male,African-American,02/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +66789,77408,70073,PRETRIAL,Bush,Jaquez,Dantrell,Male,African-American,02/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +66789,77408,70073,PRETRIAL,Bush,Jaquez,Dantrell,Male,African-American,02/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66783,77400,70067,PRETRIAL,Duprey,Harry,Isaac,Male,Caucasian,09/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/14 0:00,2,Medium,7,Risk of Violence,-1.34,7,Medium,New,1,0 +66783,77400,70067,PRETRIAL,Duprey,Harry,Isaac,Male,Caucasian,09/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +66783,77400,70067,PRETRIAL,Duprey,Harry,Isaac,Male,Caucasian,09/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66785,77403,70069,Probation,Horn,Richard,NULL,Male,Caucasian,06/11/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +66785,77403,70069,Probation,Horn,Richard,NULL,Male,Caucasian,06/11/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +66785,77403,70069,Probation,Horn,Richard,NULL,Male,Caucasian,06/11/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66775,77390,70058,PRETRIAL,MCBEAN,KERR,LEE,Male,Other,10/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/8/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +66775,77390,70058,PRETRIAL,MCBEAN,KERR,LEE,Male,Other,10/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +66775,77390,70058,PRETRIAL,MCBEAN,KERR,LEE,Male,Other,10/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65835,77392,68999,PRETRIAL,Donald,Joyce,NULL,Male,African-American,02/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,Copy,1,0 +65835,77392,68999,PRETRIAL,Donald,Joyce,NULL,Male,African-American,02/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,Copy,1,0 +65835,77392,68999,PRETRIAL,Donald,Joyce,NULL,Male,African-American,02/23/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +66792,77411,70076,Probation,richards,vincent,NULL,Male,African-American,01/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-2.47,3,Low,New,1,0 +66792,77411,70076,Probation,richards,vincent,NULL,Male,African-American,01/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +66792,77411,70076,Probation,richards,vincent,NULL,Male,African-American,01/01/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66781,77398,70065,PRETRIAL,Pierre-Gilles,Dieuseul,NULL,Male,Other,01/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +66781,77398,70065,PRETRIAL,Pierre-Gilles,Dieuseul,NULL,Male,Other,01/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +66781,77398,70065,PRETRIAL,Pierre-Gilles,Dieuseul,NULL,Male,Other,01/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +50381,77419,70083,PRETRIAL,Karns,Ricardo,NULL,Male,Other,02/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +50381,77419,70083,PRETRIAL,Karns,Ricardo,NULL,Male,Other,02/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +50381,77419,70083,PRETRIAL,Karns,Ricardo,NULL,Male,Other,02/09/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66795,77418,70082,Probation,Castanopetit,Isis,NULL,Female,Hispanic,05/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +66795,77418,70082,Probation,Castanopetit,Isis,NULL,Female,Hispanic,05/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +66795,77418,70082,Probation,Castanopetit,Isis,NULL,Female,Hispanic,05/21/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66780,77397,70064,PRETRIAL,Escobar,Marta,NULL,Female,Caucasian,06/29/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/8/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +66780,77397,70064,PRETRIAL,Escobar,Marta,NULL,Female,Caucasian,06/29/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/8/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +66780,77397,70064,PRETRIAL,Escobar,Marta,NULL,Female,Caucasian,06/29/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66776,77393,70060,PRETRIAL,Bonevelle,Bryan,James,Male,Caucasian,05/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +66776,77393,70060,PRETRIAL,Bonevelle,Bryan,James,Male,Caucasian,05/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +66776,77393,70060,PRETRIAL,Bonevelle,Bryan,James,Male,Caucasian,05/06/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66773,77388,70056,PRETRIAL,LEVY,DANIEL,NULL,Male,Other,09/14/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +66773,77388,70056,PRETRIAL,LEVY,DANIEL,NULL,Male,Other,09/14/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,4,High,8,Risk of Recidivism,0.42,9,High,New,1,0 +66773,77388,70056,PRETRIAL,LEVY,DANIEL,NULL,Male,Other,09/14/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66790,77409,70074,PRETRIAL,Sandberg,John,NULL,Male,Caucasian,01/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +66790,77409,70074,PRETRIAL,Sandberg,John,NULL,Male,Caucasian,01/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +66790,77409,70074,PRETRIAL,Sandberg,John,NULL,Male,Caucasian,01/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66784,77402,70068,Probation,Davenport,Leslie,NULL,Female,African-American,12/22/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +66784,77402,70068,Probation,Davenport,Leslie,NULL,Female,African-American,12/22/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.66,5,Medium,New,1,0 +66784,77402,70068,Probation,Davenport,Leslie,NULL,Female,African-American,12/22/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +61640,77416,70081,PRETRIAL,GONZALEZ,UBERENE,NULL,Male,Caucasian,01/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +61640,77416,70081,PRETRIAL,GONZALEZ,UBERENE,NULL,Male,Caucasian,01/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +61640,77416,70081,PRETRIAL,GONZALEZ,UBERENE,NULL,Male,Caucasian,01/16/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66768,77401,70051,PRETRIAL,Smith-Claxton,Brenda,NULL,Female,Caucasian,05/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/8/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,Copy,1,0 +66768,77401,70051,PRETRIAL,Smith-Claxton,Brenda,NULL,Female,Caucasian,05/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/8/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,Copy,1,0 +66768,77401,70051,PRETRIAL,Smith-Claxton,Brenda,NULL,Female,Caucasian,05/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +58937,77422,70086,PRETRIAL,Valdes,Javier,Amado,Male,Caucasian,04/04/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +58937,77422,70086,PRETRIAL,Valdes,Javier,Amado,Male,Caucasian,04/04/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +58937,77422,70086,PRETRIAL,Valdes,Javier,Amado,Male,Caucasian,04/04/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +20794,77424,70088,PRETRIAL,wagner,richard,NULL,Male,Caucasian,03/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.08,4,Low,New,1,0 +20794,77424,70088,PRETRIAL,wagner,richard,NULL,Male,Caucasian,03/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +20794,77424,70088,PRETRIAL,wagner,richard,NULL,Male,Caucasian,03/12/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +66777,77394,70061,PRETRIAL,Bynes,Latara,Tierra,Female,African-American,11/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-1.75,5,Medium,New,1,0 +66777,77394,70061,PRETRIAL,Bynes,Latara,Tierra,Female,African-American,11/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.72,5,Medium,New,1,0 +66777,77394,70061,PRETRIAL,Bynes,Latara,Tierra,Female,African-American,11/25/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66791,77410,70075,PRETRIAL,KOONCE,CHRISTOPHER,NULL,Male,Caucasian,03/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +66791,77410,70075,PRETRIAL,KOONCE,CHRISTOPHER,NULL,Male,Caucasian,03/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +66791,77410,70075,PRETRIAL,KOONCE,CHRISTOPHER,NULL,Male,Caucasian,03/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66799,77427,70090,PRETRIAL,SHIPP,MICHAEL,NULL,Male,African-American,01/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/8/14 0:00,2,Medium,7,Risk of Violence,-2.61,2,Low,New,1,0 +66799,77427,70090,PRETRIAL,SHIPP,MICHAEL,NULL,Male,African-American,01/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +66799,77427,70090,PRETRIAL,SHIPP,MICHAEL,NULL,Male,African-American,01/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/8/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66787,77406,70071,Probation,Brow,Kamala,NULL,Female,African-American,08/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +66787,77406,70071,Probation,Brow,Kamala,NULL,Female,African-American,08/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +66787,77406,70071,Probation,Brow,Kamala,NULL,Female,African-American,08/27/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66774,77389,70057,PRETRIAL,LENOX,CHAD,ALAN,Male,Caucasian,05/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +66774,77389,70057,PRETRIAL,LENOX,CHAD,ALAN,Male,Caucasian,05/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,4,High,8,Risk of Recidivism,1.02,10,High,New,1,0 +66774,77389,70057,PRETRIAL,LENOX,CHAD,ALAN,Male,Caucasian,05/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +4055,77391,70059,Probation,King,Morris,NULL,Male,African-American,11/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,4,High,7,Risk of Violence,-0.77,9,High,New,1,0 +4055,77391,70059,Probation,King,Morris,NULL,Male,African-American,11/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,4,High,8,Risk of Recidivism,1.03,10,High,New,1,0 +4055,77391,70059,Probation,King,Morris,NULL,Male,African-American,11/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66796,77420,70084,Probation,McKaig,Aaron,NULL,Male,Caucasian,03/03/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/8/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +66796,77420,70084,Probation,McKaig,Aaron,NULL,Male,Caucasian,03/03/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/8/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +66796,77420,70084,Probation,McKaig,Aaron,NULL,Male,Caucasian,03/03/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66782,77399,70066,PRETRIAL,Smith,Abrielle,Shantel,Female,African-American,01/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +66782,77399,70066,PRETRIAL,Smith,Abrielle,Shantel,Female,African-American,01/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +66782,77399,70066,PRETRIAL,Smith,Abrielle,Shantel,Female,African-American,01/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +39324,77404,38827,PRETRIAL,Brown,Quetarilkea,Lavern,Female,African-American,12/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,Copy,1,0 +39324,77404,38827,PRETRIAL,Brown,Quetarilkea,Lavern,Female,African-American,12/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-1.24,3,Low,Copy,1,0 +39324,77404,38827,PRETRIAL,Brown,Quetarilkea,Lavern,Female,African-American,12/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +66793,77412,70077,PRETRIAL,Feliciano,Justin,Aaron,Male,Caucasian,04/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +66793,77412,70077,PRETRIAL,Feliciano,Justin,Aaron,Male,Caucasian,04/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +66793,77412,70077,PRETRIAL,Feliciano,Justin,Aaron,Male,Caucasian,04/23/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53700,77425,70089,PRETRIAL,Harrigan,Bernirust,NULL,Male,African-American,09/06/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +53700,77425,70089,PRETRIAL,Harrigan,Bernirust,NULL,Male,African-American,09/06/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +53700,77425,70089,PRETRIAL,Harrigan,Bernirust,NULL,Male,African-American,09/06/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66779,77396,70063,PRETRIAL,HOPE,SHONQUAVIA,LATREL,Female,African-American,07/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +66779,77396,70063,PRETRIAL,HOPE,SHONQUAVIA,LATREL,Female,African-American,07/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +66779,77396,70063,PRETRIAL,HOPE,SHONQUAVIA,LATREL,Female,African-American,07/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66788,77407,70072,PRETRIAL,Valoy,Bienvenido,NULL,Male,African-American,01/25/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +66788,77407,70072,PRETRIAL,Valoy,Bienvenido,NULL,Male,African-American,01/25/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +66788,77407,70072,PRETRIAL,Valoy,Bienvenido,NULL,Male,African-American,01/25/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66652,77417,69921,PRETRIAL,Isaacs,Herman,NULL,Male,African-American,05/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,10/8/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,Copy,1,0 +66652,77417,69921,PRETRIAL,Isaacs,Herman,NULL,Male,African-American,05/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,10/8/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,Copy,1,0 +66652,77417,69921,PRETRIAL,Isaacs,Herman,NULL,Male,African-American,05/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,10/8/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +66815,77446,70108,PRETRIAL,Krishamoorthy,Arunkumar,NULL,Male,Caucasian,06/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/9/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +66815,77446,70108,PRETRIAL,Krishamoorthy,Arunkumar,NULL,Male,Caucasian,06/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +66815,77446,70108,PRETRIAL,Krishamoorthy,Arunkumar,NULL,Male,Caucasian,06/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66826,77459,70119,PRETRIAL,Wiggins,Christopher,NULL,Male,African-American,05/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,New,1,0 +66826,77459,70119,PRETRIAL,Wiggins,Christopher,NULL,Male,African-American,05/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +66826,77459,70119,PRETRIAL,Wiggins,Christopher,NULL,Male,African-American,05/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55838,77433,70095,Probation,Richardson,Emanuel,NULL,Male,African-American,06/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-1.81,5,Medium,New,1,0 +55838,77433,70095,Probation,Richardson,Emanuel,NULL,Male,African-American,06/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +55838,77433,70095,Probation,Richardson,Emanuel,NULL,Male,African-American,06/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66808,77438,70100,PRETRIAL,Matthews,Jarvis,Fitzgerald,Male,African-American,04/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +66808,77438,70100,PRETRIAL,Matthews,Jarvis,Fitzgerald,Male,African-American,04/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +66808,77438,70100,PRETRIAL,Matthews,Jarvis,Fitzgerald,Male,African-American,04/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66810,77441,70103,Probation,Ponce,Felix,Miguel,Male,Hispanic,04/05/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/9/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +66810,77441,70103,Probation,Ponce,Felix,Miguel,Male,Hispanic,04/05/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +66810,77441,70103,Probation,Ponce,Felix,Miguel,Male,Hispanic,04/05/60,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66817,77448,70110,Probation,Ryan,Rebecca,NULL,Female,Caucasian,09/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/9/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +66817,77448,70110,Probation,Ryan,Rebecca,NULL,Female,Caucasian,09/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/9/14 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +66817,77448,70110,Probation,Ryan,Rebecca,NULL,Female,Caucasian,09/02/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66818,77449,70111,Probation,Jean,Joanel,NULL,Male,African-American,07/07/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/9/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +66818,77449,70111,Probation,Jean,Joanel,NULL,Male,African-American,07/07/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +66818,77449,70111,Probation,Jean,Joanel,NULL,Male,African-American,07/07/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66824,77456,70117,Probation,perez,mark,NULL,Male,Caucasian,04/16/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +66824,77456,70117,Probation,perez,mark,NULL,Male,Caucasian,04/16/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +66824,77456,70117,Probation,perez,mark,NULL,Male,Caucasian,04/16/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66806,77436,70098,PRETRIAL,Finnegan,Daniel,NULL,Male,Caucasian,05/25/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +66806,77436,70098,PRETRIAL,Finnegan,Daniel,NULL,Male,Caucasian,05/25/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +66806,77436,70098,PRETRIAL,Finnegan,Daniel,NULL,Male,Caucasian,05/25/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66802,77431,70093,PRETRIAL,Hope,Gavin,NULL,Male,Other,11/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +66802,77431,70093,PRETRIAL,Hope,Gavin,NULL,Male,Other,11/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +66802,77431,70093,PRETRIAL,Hope,Gavin,NULL,Male,Other,11/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66809,77440,70102,Probation,GONZALEZ,CARLOS,NULL,Male,Hispanic,04/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +66809,77440,70102,Probation,GONZALEZ,CARLOS,NULL,Male,Hispanic,04/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +66809,77440,70102,Probation,GONZALEZ,CARLOS,NULL,Male,Hispanic,04/14/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66811,77443,70105,Probation,Tramposh,Lauren,NULL,Female,Caucasian,08/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/9/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +66811,77443,70105,Probation,Tramposh,Lauren,NULL,Female,Caucasian,08/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +66811,77443,70105,Probation,Tramposh,Lauren,NULL,Female,Caucasian,08/15/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66814,77445,70107,Probation,Cedeno,Manuel,NULL,Male,Caucasian,06/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/9/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +66814,77445,70107,Probation,Cedeno,Manuel,NULL,Male,Caucasian,06/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +66814,77445,70107,Probation,Cedeno,Manuel,NULL,Male,Caucasian,06/16/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66820,77452,70113,Probation,Fuentes,christina,NULL,Female,Hispanic,10/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +66820,77452,70113,Probation,Fuentes,christina,NULL,Female,Hispanic,10/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,New,1,0 +66820,77452,70113,Probation,Fuentes,christina,NULL,Female,Hispanic,10/10/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66801,77430,70092,PRETRIAL,Joseph,Julius,Mario,Male,African-American,03/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,2,Medium,7,Risk of Violence,-1.3,7,Medium,New,1,0 +66801,77430,70092,PRETRIAL,Joseph,Julius,Mario,Male,African-American,03/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +66801,77430,70092,PRETRIAL,Joseph,Julius,Mario,Male,African-American,03/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66807,77437,70099,PRETRIAL,BERNARD,MELINDA,NULL,Female,African-American,02/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,New,1,0 +66807,77437,70099,PRETRIAL,BERNARD,MELINDA,NULL,Female,African-American,02/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +66807,77437,70099,PRETRIAL,BERNARD,MELINDA,NULL,Female,African-American,02/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66819,77451,70112,Probation,Liebelt,John,Gregory,Male,Caucasian,03/06/47,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/9/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +66819,77451,70112,Probation,Liebelt,John,Gregory,Male,Caucasian,03/06/47,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +66819,77451,70112,Probation,Liebelt,John,Gregory,Male,Caucasian,03/06/47,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66827,77460,70120,Probation,Salmon,Marc,NULL,Male,Hispanic,03/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +66827,77460,70120,Probation,Salmon,Marc,NULL,Male,Hispanic,03/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +66827,77460,70120,Probation,Salmon,Marc,NULL,Male,Hispanic,03/21/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66825,77458,70118,Probation,andrews,devon,NULL,Male,African-American,11/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.25,3,Low,New,1,0 +66825,77458,70118,Probation,andrews,devon,NULL,Male,African-American,11/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +66825,77458,70118,Probation,andrews,devon,NULL,Male,African-American,11/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +66813,77444,70106,Probation,Cruz,Ruth,Roberta,Female,Hispanic,08/03/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/9/14 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +66813,77444,70106,Probation,Cruz,Ruth,Roberta,Female,Hispanic,08/03/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +66813,77444,70106,Probation,Cruz,Ruth,Roberta,Female,Hispanic,08/03/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/9/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66805,77435,70097,PRETRIAL,Burke,Brenton,Oliver,Male,Other,09/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +66805,77435,70097,PRETRIAL,Burke,Brenton,Oliver,Male,Other,09/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +66805,77435,70097,PRETRIAL,Burke,Brenton,Oliver,Male,Other,09/14/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66821,77453,70114,Probation,Lugo,Andres,NULL,Male,Hispanic,09/22/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +66821,77453,70114,Probation,Lugo,Andres,NULL,Male,Hispanic,09/22/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +66821,77453,70114,Probation,Lugo,Andres,NULL,Male,Hispanic,09/22/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66803,77432,70094,PRETRIAL,VillaCampa,Aaron,NULL,Male,Hispanic,01/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +66803,77432,70094,PRETRIAL,VillaCampa,Aaron,NULL,Male,Hispanic,01/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +66803,77432,70094,PRETRIAL,VillaCampa,Aaron,NULL,Male,Hispanic,01/18/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +55240,77439,70101,Probation,Daleo,Francesco,NULL,Male,Caucasian,02/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +55240,77439,70101,Probation,Daleo,Francesco,NULL,Male,Caucasian,02/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +55240,77439,70101,Probation,Daleo,Francesco,NULL,Male,Caucasian,02/19/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66804,77434,70096,PRETRIAL,FERDINAND,USBEL,NULL,Male,African-American,09/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +66804,77434,70096,PRETRIAL,FERDINAND,USBEL,NULL,Male,African-American,09/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +66804,77434,70096,PRETRIAL,FERDINAND,USBEL,NULL,Male,African-American,09/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66823,77455,70116,Probation,Gamba,Christopher,NULL,Male,Caucasian,09/10/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +66823,77455,70116,Probation,Gamba,Christopher,NULL,Male,Caucasian,09/10/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,8,Risk of Recidivism,-2.51,1,Low,New,1,0 +66823,77455,70116,Probation,Gamba,Christopher,NULL,Male,Caucasian,09/10/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66816,77447,70109,Probation,perez,marcela,NULL,Female,Caucasian,09/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/9/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +66816,77447,70109,Probation,perez,marcela,NULL,Female,Caucasian,09/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/9/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +66816,77447,70109,Probation,perez,marcela,NULL,Female,Caucasian,09/21/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66812,77442,70104,PRETRIAL,Kent,Kelvin,NULL,Male,African-American,02/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/9/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +66812,77442,70104,PRETRIAL,Kent,Kelvin,NULL,Male,African-American,02/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/9/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +66812,77442,70104,PRETRIAL,Kent,Kelvin,NULL,Male,African-American,02/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +36486,77429,35764,PRETRIAL,Eddins,Aaron,T,Male,African-American,12/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,4,High,7,Risk of Violence,-1.13,8,High,Copy,1,0 +36486,77429,35764,PRETRIAL,Eddins,Aaron,T,Male,African-American,12/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,4,High,8,Risk of Recidivism,0.34,9,High,Copy,1,0 +36486,77429,35764,PRETRIAL,Eddins,Aaron,T,Male,African-American,12/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/9/14 0:00,4,High,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +66829,77463,70122,PRETRIAL,Williams,Reneka,Crystal,Female,African-American,02/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +66829,77463,70122,PRETRIAL,Williams,Reneka,Crystal,Female,African-American,02/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,New,1,0 +66829,77463,70122,PRETRIAL,Williams,Reneka,Crystal,Female,African-American,02/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66832,77468,70126,PRETRIAL,Nazarova,Darea,NULL,Female,Caucasian,05/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +66832,77468,70126,PRETRIAL,Nazarova,Darea,NULL,Female,Caucasian,05/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +66832,77468,70126,PRETRIAL,Nazarova,Darea,NULL,Female,Caucasian,05/23/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +66834,77471,70129,PRETRIAL,Williams,Shekirra,NULL,Male,African-American,09/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +66834,77471,70129,PRETRIAL,Williams,Shekirra,NULL,Male,African-American,09/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +66834,77471,70129,PRETRIAL,Williams,Shekirra,NULL,Male,African-American,09/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66847,77489,70145,Probation,Rice,MICHAEL,NULL,Male,African-American,11/10/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +66847,77489,70145,Probation,Rice,MICHAEL,NULL,Male,African-American,11/10/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +66847,77489,70145,Probation,Rice,MICHAEL,NULL,Male,African-American,11/10/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66843,77484,70140,Probation,DeFrancesco,Paul,NULL,Male,Caucasian,03/13/83,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +66843,77484,70140,Probation,DeFrancesco,Paul,NULL,Male,Caucasian,03/13/83,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +66843,77484,70140,Probation,DeFrancesco,Paul,NULL,Male,Caucasian,03/13/83,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +35399,77465,34614,PRETRIAL,Williams,Dequaiver,NULL,Male,African-American,06/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/10/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,Copy,1,0 +35399,77465,34614,PRETRIAL,Williams,Dequaiver,NULL,Male,African-American,06/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/10/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,Copy,1,0 +35399,77465,34614,PRETRIAL,Williams,Dequaiver,NULL,Male,African-American,06/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +66837,77474,70132,PRETRIAL,PIER,JULES,NULL,Male,Caucasian,01/30/43,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-4.13,1,Low,New,1,0 +66837,77474,70132,PRETRIAL,PIER,JULES,NULL,Male,Caucasian,01/30/43,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +66837,77474,70132,PRETRIAL,PIER,JULES,NULL,Male,Caucasian,01/30/43,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66840,77479,70136,PRETRIAL,Jelescu,Vasile,NULL,Male,Caucasian,09/13/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +66840,77479,70136,PRETRIAL,Jelescu,Vasile,NULL,Male,Caucasian,09/13/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-2.72,1,Low,New,1,0 +66840,77479,70136,PRETRIAL,Jelescu,Vasile,NULL,Male,Caucasian,09/13/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66841,77481,70138,PRETRIAL,Allen,Adagio,NULL,Male,African-American,08/12/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.17,8,High,New,1,0 +66841,77481,70138,PRETRIAL,Allen,Adagio,NULL,Male,African-American,08/12/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +66841,77481,70138,PRETRIAL,Allen,Adagio,NULL,Male,African-American,08/12/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +17164,77488,70144,PRETRIAL,SaintGermain,Abenson,NULL,Male,African-American,11/07/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/10/14 0:00,2,Medium,7,Risk of Violence,-2.64,2,Low,New,1,0 +17164,77488,70144,PRETRIAL,SaintGermain,Abenson,NULL,Male,African-American,11/07/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +17164,77488,70144,PRETRIAL,SaintGermain,Abenson,NULL,Male,African-American,11/07/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/10/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66831,77466,70124,PRETRIAL,Macneil,John,NULL,Male,Caucasian,08/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,2,Medium,7,Risk of Violence,-2.22,4,Low,New,1,0 +66831,77466,70124,PRETRIAL,Macneil,John,NULL,Male,Caucasian,08/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +66831,77466,70124,PRETRIAL,Macneil,John,NULL,Male,Caucasian,08/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66836,77473,70131,Probation,Grecco,Catherine,NULL,Female,Caucasian,12/15/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/10/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +66836,77473,70131,Probation,Grecco,Catherine,NULL,Female,Caucasian,12/15/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/10/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +66836,77473,70131,Probation,Grecco,Catherine,NULL,Female,Caucasian,12/15/63,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +48411,77480,70137,PRETRIAL,burns,ian,NULL,Male,Caucasian,10/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.29,3,Low,New,1,0 +48411,77480,70137,PRETRIAL,burns,ian,NULL,Male,Caucasian,10/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,New,1,0 +48411,77480,70137,PRETRIAL,burns,ian,NULL,Male,Caucasian,10/04/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +33017,77478,70135,PRETRIAL,Patnaude,Philip,NULL,Male,Caucasian,06/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/10/14 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +33017,77478,70135,PRETRIAL,Patnaude,Philip,NULL,Male,Caucasian,06/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +33017,77478,70135,PRETRIAL,Patnaude,Philip,NULL,Male,Caucasian,06/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/10/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66842,77482,70139,PRETRIAL,Hankerson,Justin,Stephon,Male,African-American,11/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/10/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +66842,77482,70139,PRETRIAL,Hankerson,Justin,Stephon,Male,African-American,11/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/10/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +66842,77482,70139,PRETRIAL,Hankerson,Justin,Stephon,Male,African-American,11/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +43470,77483,56347,PRETRIAL,LEWIS,RIVELINO,NULL,Male,African-American,10/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-1.86,5,Medium,Copy,1,0 +43470,77483,56347,PRETRIAL,LEWIS,RIVELINO,NULL,Male,African-American,10/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,Copy,1,0 +43470,77483,56347,PRETRIAL,LEWIS,RIVELINO,NULL,Male,African-American,10/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +66848,77490,70146,Probation,Demps,Quinkka,NULL,Female,Caucasian,05/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.09,4,Low,New,1,0 +66848,77490,70146,Probation,Demps,Quinkka,NULL,Female,Caucasian,05/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,9,High,New,1,0 +66848,77490,70146,Probation,Demps,Quinkka,NULL,Female,Caucasian,05/25/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66828,77462,70121,PRETRIAL,saintlouis,Edwice,NULL,Male,African-American,09/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +66828,77462,70121,PRETRIAL,saintlouis,Edwice,NULL,Male,African-American,09/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +66828,77462,70121,PRETRIAL,saintlouis,Edwice,NULL,Male,African-American,09/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66838,77475,70133,Probation,Lopez,Micah,NULL,Male,Hispanic,05/22/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +66838,77475,70133,Probation,Lopez,Micah,NULL,Male,Hispanic,05/22/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +66838,77475,70133,Probation,Lopez,Micah,NULL,Male,Hispanic,05/22/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66833,77469,70127,PRETRIAL,Wessells,Ralph,Douglas,Male,Caucasian,02/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +66833,77469,70127,PRETRIAL,Wessells,Ralph,Douglas,Male,Caucasian,02/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +66833,77469,70127,PRETRIAL,Wessells,Ralph,Douglas,Male,Caucasian,02/25/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64749,77470,70128,PRETRIAL,CREW,BRIAN,NULL,Male,African-American,08/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +64749,77470,70128,PRETRIAL,CREW,BRIAN,NULL,Male,African-American,08/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +64749,77470,70128,PRETRIAL,CREW,BRIAN,NULL,Male,African-American,08/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +56929,77472,70130,PRETRIAL,Walker,Tylicia,NULL,Female,African-American,06/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +56929,77472,70130,PRETRIAL,Walker,Tylicia,NULL,Female,African-American,06/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,8,High,New,1,0 +56929,77472,70130,PRETRIAL,Walker,Tylicia,NULL,Female,African-American,06/20/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +58585,67048,60794,PRETRIAL,Arrow,Sarah,NULL,Female,Caucasian,11/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +58585,67048,60794,PRETRIAL,Arrow,Sarah,NULL,Female,Caucasian,11/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +58585,67048,60794,PRETRIAL,Arrow,Sarah,NULL,Female,Caucasian,11/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66830,77464,70123,PRETRIAL,Prince,Shameka,Genell,Female,African-American,02/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +66830,77464,70123,PRETRIAL,Prince,Shameka,Genell,Female,African-American,02/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +66830,77464,70123,PRETRIAL,Prince,Shameka,Genell,Female,African-American,02/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +49398,77467,70125,PRETRIAL,ROSALES,DANY,JAVIER,Male,Caucasian,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +49398,77467,70125,PRETRIAL,ROSALES,DANY,JAVIER,Male,Caucasian,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +49398,77467,70125,PRETRIAL,ROSALES,DANY,JAVIER,Male,Caucasian,09/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66844,77485,70141,Probation,Harper,Ralph,NULL,Male,Caucasian,05/15/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +66844,77485,70141,Probation,Harper,Ralph,NULL,Male,Caucasian,05/15/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +66844,77485,70141,Probation,Harper,Ralph,NULL,Male,Caucasian,05/15/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/10/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66855,77493,70149,PRETRIAL,Payton,Zachary,Ian,Male,African-American,11/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +66855,77493,70149,PRETRIAL,Payton,Zachary,Ian,Male,African-American,11/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +66855,77493,70149,PRETRIAL,Payton,Zachary,Ian,Male,African-American,11/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66853,77491,70147,PRETRIAL,Williams,Marcus,Allen,Male,African-American,03/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +66853,77491,70147,PRETRIAL,Williams,Marcus,Allen,Male,African-American,03/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +66853,77491,70147,PRETRIAL,Williams,Marcus,Allen,Male,African-American,03/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66858,77498,70153,PRETRIAL,Chance,Michael,NULL,Male,African-American,09/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +66858,77498,70153,PRETRIAL,Chance,Michael,NULL,Male,African-American,09/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +66858,77498,70153,PRETRIAL,Chance,Michael,NULL,Male,African-American,09/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53861,77496,55372,PRETRIAL,Coleman,Demetrius,NULL,Male,African-American,11/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,Copy,1,0 +53861,77496,55372,PRETRIAL,Coleman,Demetrius,NULL,Male,African-American,11/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,Copy,1,0 +53861,77496,55372,PRETRIAL,Coleman,Demetrius,NULL,Male,African-American,11/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +66863,77503,70158,PRETRIAL,Watson,Shafonda,NULL,Female,African-American,12/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +66863,77503,70158,PRETRIAL,Watson,Shafonda,NULL,Female,African-American,12/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +66863,77503,70158,PRETRIAL,Watson,Shafonda,NULL,Female,African-American,12/07/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66859,77499,70154,PRETRIAL,Lopez,FREDERICO,NULL,Male,Hispanic,04/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +66859,77499,70154,PRETRIAL,Lopez,FREDERICO,NULL,Male,Hispanic,04/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +66859,77499,70154,PRETRIAL,Lopez,FREDERICO,NULL,Male,Hispanic,04/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66861,77501,70156,PRETRIAL,TELSAINT,WILVELINOT,NULL,Male,African-American,01/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +66861,77501,70156,PRETRIAL,TELSAINT,WILVELINOT,NULL,Male,African-American,01/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +66861,77501,70156,PRETRIAL,TELSAINT,WILVELINOT,NULL,Male,African-American,01/23/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66849,77494,70150,PRETRIAL,FERMINCIVOLANI,MARCO,A,Male,Caucasian,11/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +66849,77494,70150,PRETRIAL,FERMINCIVOLANI,MARCO,A,Male,Caucasian,11/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +66849,77494,70150,PRETRIAL,FERMINCIVOLANI,MARCO,A,Male,Caucasian,11/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66862,77502,70157,PRETRIAL,Grant,willie,Frank,Male,African-American,05/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/11/14 0:00,2,Medium,7,Risk of Violence,-3.02,1,Low,New,1,0 +66862,77502,70157,PRETRIAL,Grant,willie,Frank,Male,African-American,05/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +66862,77502,70157,PRETRIAL,Grant,willie,Frank,Male,African-American,05/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/11/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66856,77495,70151,PRETRIAL,GALEASFUENTES,CHRISTIAN,NULL,Male,Hispanic,10/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +66856,77495,70151,PRETRIAL,GALEASFUENTES,CHRISTIAN,NULL,Male,Hispanic,10/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +66856,77495,70151,PRETRIAL,GALEASFUENTES,CHRISTIAN,NULL,Male,Hispanic,10/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66860,77500,70155,PRETRIAL,Bahoque,Dorca,NULL,Female,Caucasian,02/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +66860,77500,70155,PRETRIAL,Bahoque,Dorca,NULL,Female,Caucasian,02/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,8,High,New,1,0 +66860,77500,70155,PRETRIAL,Bahoque,Dorca,NULL,Female,Caucasian,02/19/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66854,77492,70148,PRETRIAL,Everton,Michael,Cytall,Male,African-American,07/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +66854,77492,70148,PRETRIAL,Everton,Michael,Cytall,Male,African-American,07/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +66854,77492,70148,PRETRIAL,Everton,Michael,Cytall,Male,African-American,07/09/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66857,77497,70152,PRETRIAL,EWALD,CHRISTOPHER,NULL,Male,African-American,02/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/11/14 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +66857,77497,70152,PRETRIAL,EWALD,CHRISTOPHER,NULL,Male,African-American,02/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +66857,77497,70152,PRETRIAL,EWALD,CHRISTOPHER,NULL,Male,African-American,02/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/11/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +42400,77510,70163,PRETRIAL,Daniels,David,NULL,Male,African-American,10/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.62,2,Low,New,1,0 +42400,77510,70163,PRETRIAL,Daniels,David,NULL,Male,African-American,10/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +42400,77510,70163,PRETRIAL,Daniels,David,NULL,Male,African-American,10/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66865,77505,70160,PRETRIAL,Stein,Shane,NULL,Female,Caucasian,11/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/12/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +66865,77505,70160,PRETRIAL,Stein,Shane,NULL,Female,Caucasian,11/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/12/14 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +66865,77505,70160,PRETRIAL,Stein,Shane,NULL,Female,Caucasian,11/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/12/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +66864,77504,70159,PRETRIAL,ALMIROL,BONIFACIO,RILLORAZA,Male,Asian,01/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/12/14 0:00,1,Low,7,Risk of Violence,-4.01,1,Low,New,1,0 +66864,77504,70159,PRETRIAL,ALMIROL,BONIFACIO,RILLORAZA,Male,Asian,01/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/12/14 0:00,1,Low,8,Risk of Recidivism,-2.47,1,Low,New,1,0 +66864,77504,70159,PRETRIAL,ALMIROL,BONIFACIO,RILLORAZA,Male,Asian,01/14/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66867,77507,70162,PRETRIAL,BROWN,SHANE,CHRISTOPHER,Male,African-American,07/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +66867,77507,70162,PRETRIAL,BROWN,SHANE,CHRISTOPHER,Male,African-American,07/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +66867,77507,70162,PRETRIAL,BROWN,SHANE,CHRISTOPHER,Male,African-American,07/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66869,77512,70165,PRETRIAL,PITTS,WILLIE,JOSEPH,Male,African-American,02/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/12/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +66869,77512,70165,PRETRIAL,PITTS,WILLIE,JOSEPH,Male,African-American,02/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/12/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +66869,77512,70165,PRETRIAL,PITTS,WILLIE,JOSEPH,Male,African-American,02/26/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/12/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66868,77511,70164,PRETRIAL,Edwards,Matthew,Rufus,Male,African-American,08/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/12/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +66868,77511,70164,PRETRIAL,Edwards,Matthew,Rufus,Male,African-American,08/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/12/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +66868,77511,70164,PRETRIAL,Edwards,Matthew,Rufus,Male,African-American,08/05/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/12/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66866,77506,70161,PRETRIAL,WEEDEN,BRANDI,NULL,Female,African-American,11/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +66866,77506,70161,PRETRIAL,WEEDEN,BRANDI,NULL,Female,African-American,11/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +66866,77506,70161,PRETRIAL,WEEDEN,BRANDI,NULL,Female,African-American,11/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66883,77527,70180,Probation,FREIBURG,ABBEY,NULL,Female,Caucasian,09/19/62,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,10/13/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +66883,77527,70180,Probation,FREIBURG,ABBEY,NULL,Female,Caucasian,09/19/62,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +66883,77527,70180,Probation,FREIBURG,ABBEY,NULL,Female,Caucasian,09/19/62,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Married,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +42000,77535,70188,PRETRIAL,Jackson,Anthony,Beretta,Male,African-American,02/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.57,6,Medium,New,1,0 +42000,77535,70188,PRETRIAL,Jackson,Anthony,Beretta,Male,African-American,02/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +42000,77535,70188,PRETRIAL,Jackson,Anthony,Beretta,Male,African-American,02/20/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66871,77514,70167,PRETRIAL,Santiago,Christopher,NULL,Male,African-American,02/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,4,High,7,Risk of Violence,-0.2,10,High,New,1,0 +66871,77514,70167,PRETRIAL,Santiago,Christopher,NULL,Male,African-American,02/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,4,High,8,Risk of Recidivism,0.91,10,High,New,1,0 +66871,77514,70167,PRETRIAL,Santiago,Christopher,NULL,Male,African-American,02/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +66888,77532,70185,PRETRIAL,SANCHEZ,CRYSTAL,NULL,Female,Hispanic,07/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +66888,77532,70185,PRETRIAL,SANCHEZ,CRYSTAL,NULL,Female,Hispanic,07/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +66888,77532,70185,PRETRIAL,SANCHEZ,CRYSTAL,NULL,Female,Hispanic,07/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +50711,77519,70172,PRETRIAL,Turnquest,Jacel,NULL,Male,African-American,12/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +50711,77519,70172,PRETRIAL,Turnquest,Jacel,NULL,Male,African-American,12/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +50711,77519,70172,PRETRIAL,Turnquest,Jacel,NULL,Male,African-American,12/04/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66885,77529,70182,Probation,Khan,Lee,NULL,Male,Asian,01/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +66885,77529,70182,Probation,Khan,Lee,NULL,Male,Asian,01/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +66885,77529,70182,Probation,Khan,Lee,NULL,Male,Asian,01/12/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +22928,77533,70186,Probation,CROSTA,WILLIAM,CHARLES,Male,Caucasian,04/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/13/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +22928,77533,70186,Probation,CROSTA,WILLIAM,CHARLES,Male,Caucasian,04/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +22928,77533,70186,Probation,CROSTA,WILLIAM,CHARLES,Male,Caucasian,04/21/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66891,77538,70189,PRETRIAL,BOSCIO,ROBETO,NULL,Male,Caucasian,03/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/13/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +66891,77538,70189,PRETRIAL,BOSCIO,ROBETO,NULL,Male,Caucasian,03/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +66891,77538,70189,PRETRIAL,BOSCIO,ROBETO,NULL,Male,Caucasian,03/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66874,77517,70170,Probation,DISTEFANO,richard,NULL,Male,Caucasian,11/09/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/13/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +66874,77517,70170,Probation,DISTEFANO,richard,NULL,Male,Caucasian,11/09/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +66874,77517,70170,Probation,DISTEFANO,richard,NULL,Male,Caucasian,11/09/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/13/14 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +66896,77543,70194,Probation,waltermire,jason,NULL,Male,Caucasian,03/30/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/13/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +66896,77543,70194,Probation,waltermire,jason,NULL,Male,Caucasian,03/30/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +66896,77543,70194,Probation,waltermire,jason,NULL,Male,Caucasian,03/30/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66872,77515,70168,PRETRIAL,Short,Mary,NULL,Female,Caucasian,02/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/13/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +66872,77515,70168,PRETRIAL,Short,Mary,NULL,Female,Caucasian,02/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.57,2,Low,New,1,0 +66872,77515,70168,PRETRIAL,Short,Mary,NULL,Female,Caucasian,02/09/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66879,77522,70175,PRETRIAL,Arteaga,Luis,NULL,Male,Hispanic,11/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/13/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +66879,77522,70175,PRETRIAL,Arteaga,Luis,NULL,Male,Hispanic,11/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +66879,77522,70175,PRETRIAL,Arteaga,Luis,NULL,Male,Hispanic,11/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66881,77524,70177,Probation,bowman,michelle,NULL,Female,Caucasian,10/14/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/13/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +66881,77524,70177,Probation,bowman,michelle,NULL,Female,Caucasian,10/14/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +66881,77524,70177,Probation,bowman,michelle,NULL,Female,Caucasian,10/14/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58252,77525,70178,PRETRIAL,TORRES,BRYAN,NULL,Male,Hispanic,02/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/13/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +58252,77525,70178,PRETRIAL,TORRES,BRYAN,NULL,Male,Hispanic,02/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +58252,77525,70178,PRETRIAL,TORRES,BRYAN,NULL,Male,Hispanic,02/25/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +54246,77537,63030,PRETRIAL,thomas,Brandon,NULL,Male,African-American,05/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/13/14 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,Copy,1,0 +54246,77537,63030,PRETRIAL,thomas,Brandon,NULL,Male,African-American,05/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,Copy,1,0 +54246,77537,63030,PRETRIAL,thomas,Brandon,NULL,Male,African-American,05/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/13/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +66873,77516,70169,Probation,STANLEY,JARVIS,N,Male,African-American,10/02/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +66873,77516,70169,Probation,STANLEY,JARVIS,N,Male,African-American,10/02/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +66873,77516,70169,Probation,STANLEY,JARVIS,N,Male,African-American,10/02/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66880,77523,70176,PRETRIAL,Gomez,Maria,Elena,Female,Hispanic,06/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/13/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +66880,77523,70176,PRETRIAL,Gomez,Maria,Elena,Female,Hispanic,06/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/13/14 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +66880,77523,70176,PRETRIAL,Gomez,Maria,Elena,Female,Hispanic,06/13/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66886,77530,70183,PRETRIAL,magana,joseph,NULL,Male,Hispanic,07/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.23,8,High,New,1,0 +66886,77530,70183,PRETRIAL,magana,joseph,NULL,Male,Hispanic,07/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +66886,77530,70183,PRETRIAL,magana,joseph,NULL,Male,Hispanic,07/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66877,77520,70173,Probation,THOMPSON,SHAWN,T,Male,African-American,09/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/13/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +66877,77520,70173,Probation,THOMPSON,SHAWN,T,Male,African-American,09/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/13/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +66877,77520,70173,Probation,THOMPSON,SHAWN,T,Male,African-American,09/12/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66889,77534,70187,PRETRIAL,smith,mark,NULL,Male,Caucasian,04/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/13/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +66889,77534,70187,PRETRIAL,smith,mark,NULL,Male,Caucasian,04/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +66889,77534,70187,PRETRIAL,smith,mark,NULL,Male,Caucasian,04/08/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66882,77526,70179,PRETRIAL,Poveda,Michael,NULL,Male,Caucasian,09/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +66882,77526,70179,PRETRIAL,Poveda,Michael,NULL,Male,Caucasian,09/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +66882,77526,70179,PRETRIAL,Poveda,Michael,NULL,Male,Caucasian,09/17/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66884,77528,70181,PRETRIAL,Zito,Henry,NULL,Male,Caucasian,03/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +66884,77528,70181,PRETRIAL,Zito,Henry,NULL,Male,Caucasian,03/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +66884,77528,70181,PRETRIAL,Zito,Henry,NULL,Male,Caucasian,03/01/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66870,77513,70166,PRETRIAL,EDMOND,WENSLEY,PHILLIPPE,Male,African-American,10/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/13/14 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +66870,77513,70166,PRETRIAL,EDMOND,WENSLEY,PHILLIPPE,Male,African-American,10/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/13/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +66870,77513,70166,PRETRIAL,EDMOND,WENSLEY,PHILLIPPE,Male,African-American,10/31/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66887,77531,70184,Probation,jacques,frantz,NULL,Male,African-American,07/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,2,Medium,7,Risk of Violence,-2.61,2,Low,New,1,0 +66887,77531,70184,Probation,jacques,frantz,NULL,Male,African-American,07/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +66887,77531,70184,Probation,jacques,frantz,NULL,Male,African-American,07/25/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/13/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66892,77539,70190,Probation,musgrave,martin,NULL,Male,Caucasian,01/27/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/13/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +66892,77539,70190,Probation,musgrave,martin,NULL,Male,Caucasian,01/27/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/13/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +66892,77539,70190,Probation,musgrave,martin,NULL,Male,Caucasian,01/27/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66876,77518,70171,PRETRIAL,Pippen,Charles,NULL,Male,African-American,10/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +66876,77518,70171,PRETRIAL,Pippen,Charles,NULL,Male,African-American,10/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +66876,77518,70171,PRETRIAL,Pippen,Charles,NULL,Male,African-American,10/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +62174,77536,64828,Probation,rafferty,cornelius,NULL,Male,Caucasian,06/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/13/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,Copy,1,0 +62174,77536,64828,Probation,rafferty,cornelius,NULL,Male,Caucasian,06/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,Copy,1,0 +62174,77536,64828,Probation,rafferty,cornelius,NULL,Male,Caucasian,06/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/13/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +66921,77586,70229,Probation,Dela Rosa,Angel,NULL,Male,Hispanic,04/06/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +66921,77586,70229,Probation,Dela Rosa,Angel,NULL,Male,Hispanic,04/06/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +66921,77586,70229,Probation,Dela Rosa,Angel,NULL,Male,Hispanic,04/06/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66432,77557,69662,PRETRIAL,Shatas,Sean,NULL,Male,Caucasian,09/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/14/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,Copy,1,0 +66432,77557,69662,PRETRIAL,Shatas,Sean,NULL,Male,Caucasian,09/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/14/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,Copy,1,0 +66432,77557,69662,PRETRIAL,Shatas,Sean,NULL,Male,Caucasian,09/04/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +66910,77565,70213,PRETRIAL,Major,Terrize,NULL,Female,African-American,03/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.26,3,Low,New,1,0 +66910,77565,70213,PRETRIAL,Major,Terrize,NULL,Female,African-American,03/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +66910,77565,70213,PRETRIAL,Major,Terrize,NULL,Female,African-American,03/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +36662,77544,70195,PRETRIAL,Docteur,Jacky,NULL,Male,African-American,10/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +36662,77544,70195,PRETRIAL,Docteur,Jacky,NULL,Male,African-American,10/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +36662,77544,70195,PRETRIAL,Docteur,Jacky,NULL,Male,African-American,10/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66897,77547,70198,PRETRIAL,Bates,Joe,NULL,Male,African-American,10/12/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,2,Medium,7,Risk of Violence,-3.53,1,Low,New,1,0 +66897,77547,70198,PRETRIAL,Bates,Joe,NULL,Male,African-American,10/12/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +66897,77547,70198,PRETRIAL,Bates,Joe,NULL,Male,African-American,10/12/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66899,77549,70200,PRETRIAL,Logan,Meghan,Elizabeth,Female,Caucasian,05/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +66899,77549,70200,PRETRIAL,Logan,Meghan,Elizabeth,Female,Caucasian,05/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +66899,77549,70200,PRETRIAL,Logan,Meghan,Elizabeth,Female,Caucasian,05/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61191,77583,70226,PRETRIAL,MARKO,EDWARD,JAMES,Male,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +61191,77583,70226,PRETRIAL,MARKO,EDWARD,JAMES,Male,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +61191,77583,70226,PRETRIAL,MARKO,EDWARD,JAMES,Male,Caucasian,06/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +3660,77562,70209,PRETRIAL,Schild,Bradley,Curtiss,Male,Caucasian,07/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,Copy,1,0 +3660,77562,70209,PRETRIAL,Schild,Bradley,Curtiss,Male,Caucasian,07/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,Copy,1,0 +3660,77562,70209,PRETRIAL,Schild,Bradley,Curtiss,Male,Caucasian,07/29/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +66903,77555,70205,PRETRIAL,HICKS,DARRYL,NULL,Male,African-American,11/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +66903,77555,70205,PRETRIAL,HICKS,DARRYL,NULL,Male,African-American,11/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +66903,77555,70205,PRETRIAL,HICKS,DARRYL,NULL,Male,African-American,11/27/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +2629,77551,16087,PRETRIAL,KOLB,PAUL,JENNINGS,Male,Caucasian,12/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,Copy,1,0 +2629,77551,16087,PRETRIAL,KOLB,PAUL,JENNINGS,Male,Caucasian,12/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,Copy,1,0 +2629,77551,16087,PRETRIAL,KOLB,PAUL,JENNINGS,Male,Caucasian,12/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +66905,77558,70207,Probation,Mclaughlin,Daniel,NULL,Male,Caucasian,12/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +66905,77558,70207,Probation,Mclaughlin,Daniel,NULL,Male,Caucasian,12/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +66905,77558,70207,Probation,Mclaughlin,Daniel,NULL,Male,Caucasian,12/06/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +54877,77588,69914,PRETRIAL,NORALUS,TONY,NULL,Male,African-American,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/14 0:00,2,Medium,7,Risk of Violence,-2.85,2,Low,Copy,1,0 +54877,77588,69914,PRETRIAL,NORALUS,TONY,NULL,Male,African-American,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,Copy,1,0 +54877,77588,69914,PRETRIAL,NORALUS,TONY,NULL,Male,African-American,04/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +66916,77576,70222,Probation,Herrera,Jorge,Mauricio,Male,Hispanic,06/21/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/14 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +66916,77576,70222,Probation,Herrera,Jorge,Mauricio,Male,Hispanic,06/21/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +66916,77576,70222,Probation,Herrera,Jorge,Mauricio,Male,Hispanic,06/21/94,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66908,77563,70211,PRETRIAL,Zambrano,Andrea,NULL,Female,Caucasian,05/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +66908,77563,70211,PRETRIAL,Zambrano,Andrea,NULL,Female,Caucasian,05/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +66908,77563,70211,PRETRIAL,Zambrano,Andrea,NULL,Female,Caucasian,05/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +59656,77572,70219,PRETRIAL,HAWKINS,PAUL,ROBERT,Male,Caucasian,12/11/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +59656,77572,70219,PRETRIAL,HAWKINS,PAUL,ROBERT,Male,Caucasian,12/11/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +59656,77572,70219,PRETRIAL,HAWKINS,PAUL,ROBERT,Male,Caucasian,12/11/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66898,77546,70197,PRETRIAL,Cadevil,Clifford,Anel,Male,African-American,01/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,4,High,7,Risk of Violence,-0.95,9,High,New,1,0 +66898,77546,70197,PRETRIAL,Cadevil,Clifford,Anel,Male,African-American,01/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +66898,77546,70197,PRETRIAL,Cadevil,Clifford,Anel,Male,African-American,01/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +63863,77567,66786,Probation,Taylor,Frederick,NULL,Male,African-American,09/07/57,17,All Scales,Intake,English,Other,Probation,Divorced,10/14/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +63863,77567,66786,Probation,Taylor,Frederick,NULL,Male,African-American,09/07/57,17,All Scales,Intake,English,Other,Probation,Divorced,10/14/14 0:00,1,Low,8,Risk of Recidivism,-0.67,3,Low,New,1,0 +63863,77567,66786,Probation,Taylor,Frederick,NULL,Male,African-American,09/07/57,17,All Scales,Intake,English,Other,Probation,Divorced,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +66900,77552,70202,PRETRIAL,JOHNSON,RAYMOND,WILSON,Male,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +66900,77552,70202,PRETRIAL,JOHNSON,RAYMOND,WILSON,Male,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.78,10,High,New,1,0 +66900,77552,70202,PRETRIAL,JOHNSON,RAYMOND,WILSON,Male,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66922,77587,70230,Probation,pinto,felipe,NULL,Male,Hispanic,04/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +66922,77587,70230,Probation,pinto,felipe,NULL,Male,Hispanic,04/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +66922,77587,70230,Probation,pinto,felipe,NULL,Male,Hispanic,04/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66911,77566,70214,Probation,mcconnachie,kelly,NULL,Female,Caucasian,06/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +66911,77566,70214,Probation,mcconnachie,kelly,NULL,Female,Caucasian,06/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +66911,77566,70214,Probation,mcconnachie,kelly,NULL,Female,Caucasian,06/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +23759,77573,70220,Probation,nolton,david,NULL,Male,African-American,05/04/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/14/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +23759,77573,70220,Probation,nolton,david,NULL,Male,African-American,05/04/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/14/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +23759,77573,70220,Probation,nolton,david,NULL,Male,African-American,05/04/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Widowed,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +55773,77580,70224,PRETRIAL,Jacob,Robert,NULL,Male,Caucasian,02/09/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +55773,77580,70224,PRETRIAL,Jacob,Robert,NULL,Male,Caucasian,02/09/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-2.74,1,Low,New,1,0 +55773,77580,70224,PRETRIAL,Jacob,Robert,NULL,Male,Caucasian,02/09/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66902,77554,70204,PRETRIAL,Metzger,Matthew,NULL,Male,Caucasian,08/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +66902,77554,70204,PRETRIAL,Metzger,Matthew,NULL,Male,Caucasian,08/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +66902,77554,70204,PRETRIAL,Metzger,Matthew,NULL,Male,Caucasian,08/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66912,77568,70215,PRETRIAL,Davis,Derrick,NULL,Male,African-American,05/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/14/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +66912,77568,70215,PRETRIAL,Davis,Derrick,NULL,Male,African-American,05/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/14/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +66912,77568,70215,PRETRIAL,Davis,Derrick,NULL,Male,African-American,05/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66920,77585,70228,Probation,Oneal,Kryron,NULL,Male,African-American,05/28/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,2,Medium,7,Risk of Violence,-2.62,2,Low,New,1,0 +66920,77585,70228,Probation,Oneal,Kryron,NULL,Male,African-American,05/28/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +66920,77585,70228,Probation,Oneal,Kryron,NULL,Male,African-American,05/28/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +5284,77550,70201,PRETRIAL,FONTANEZ,JOSE,L,Male,Hispanic,10/21/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/14/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +5284,77550,70201,PRETRIAL,FONTANEZ,JOSE,L,Male,Hispanic,10/21/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/14/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +5284,77550,70201,PRETRIAL,FONTANEZ,JOSE,L,Male,Hispanic,10/21/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66909,77564,70212,Probation,Posso,Luis,NULL,Male,Hispanic,05/04/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/14 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +66909,77564,70212,Probation,Posso,Luis,NULL,Male,Hispanic,05/04/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/14 0:00,1,Low,8,Risk of Recidivism,-2.29,1,Low,New,1,0 +66909,77564,70212,Probation,Posso,Luis,NULL,Male,Hispanic,05/04/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62011,77571,70218,PRETRIAL,SANCHEZ,JOSUE,DANIEL,Male,Hispanic,08/05/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/14/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +62011,77571,70218,PRETRIAL,SANCHEZ,JOSUE,DANIEL,Male,Hispanic,08/05/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/14/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +62011,77571,70218,PRETRIAL,SANCHEZ,JOSUE,DANIEL,Male,Hispanic,08/05/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +64865,77575,67934,Probation,Cartwright,Dylan,NULL,Male,African-American,06/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,Copy,1,0 +64865,77575,67934,Probation,Cartwright,Dylan,NULL,Male,African-American,06/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,Copy,1,0 +64865,77575,67934,Probation,Cartwright,Dylan,NULL,Male,African-American,06/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +66906,77559,70208,PRETRIAL,Gregorovic,Michelle,Joette,Female,Caucasian,05/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +66906,77559,70208,PRETRIAL,Gregorovic,Michelle,Joette,Female,Caucasian,05/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-0.75,5,Medium,New,1,0 +66906,77559,70208,PRETRIAL,Gregorovic,Michelle,Joette,Female,Caucasian,05/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66913,77569,70216,Probation,BURROWS,PATRICK,A,Male,African-American,09/27/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +66913,77569,70216,Probation,BURROWS,PATRICK,A,Male,African-American,09/27/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +66913,77569,70216,Probation,BURROWS,PATRICK,A,Male,African-American,09/27/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66919,77584,70227,Probation,HOPLER,JAMES,F,Male,Caucasian,01/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +66919,77584,70227,Probation,HOPLER,JAMES,F,Male,Caucasian,01/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +66919,77584,70227,Probation,HOPLER,JAMES,F,Male,Caucasian,01/20/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +32629,77548,70199,Probation,jones,demetrias,NULL,Female,African-American,12/21/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,2,Medium,7,Risk of Violence,-2.7,2,Low,New,1,0 +32629,77548,70199,Probation,jones,demetrias,NULL,Female,African-American,12/21/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +32629,77548,70199,Probation,jones,demetrias,NULL,Female,African-American,12/21/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66917,77577,70223,Probation,sisler,barry,NULL,Male,Caucasian,08/15/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +66917,77577,70223,Probation,sisler,barry,NULL,Male,Caucasian,08/15/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +66917,77577,70223,Probation,sisler,barry,NULL,Male,Caucasian,08/15/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66904,77556,70206,PRETRIAL,XIMINES,MARLO,ORLANDO,Male,Other,07/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +66904,77556,70206,PRETRIAL,XIMINES,MARLO,ORLANDO,Male,Other,07/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +66904,77556,70206,PRETRIAL,XIMINES,MARLO,ORLANDO,Male,Other,07/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66901,77553,70203,PRETRIAL,Christian,Vinas,NULL,Male,Caucasian,12/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +66901,77553,70203,PRETRIAL,Christian,Vinas,NULL,Male,Caucasian,12/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +66901,77553,70203,PRETRIAL,Christian,Vinas,NULL,Male,Caucasian,12/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66907,77561,70210,PRETRIAL,Luina,Christopher,NULL,Male,Caucasian,06/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +66907,77561,70210,PRETRIAL,Luina,Christopher,NULL,Male,Caucasian,06/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +66907,77561,70210,PRETRIAL,Luina,Christopher,NULL,Male,Caucasian,06/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66925,77595,70236,PRETRIAL,Frazier,Terrance,NULL,Male,African-American,03/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +66925,77595,70236,PRETRIAL,Frazier,Terrance,NULL,Male,African-American,03/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +66925,77595,70236,PRETRIAL,Frazier,Terrance,NULL,Male,African-American,03/19/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66934,77608,70248,Probation,JIMENEZMDELARIVA,RAUL,NULL,Male,Hispanic,09/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/15/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +66934,77608,70248,Probation,JIMENEZMDELARIVA,RAUL,NULL,Male,Hispanic,09/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/15/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +66934,77608,70248,Probation,JIMENEZMDELARIVA,RAUL,NULL,Male,Hispanic,09/29/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +66929,77600,70241,Probation,Ramsey,Khiry,NULL,Male,Native American,01/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +66929,77600,70241,Probation,Ramsey,Khiry,NULL,Male,Native American,01/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +66929,77600,70241,Probation,Ramsey,Khiry,NULL,Male,Native American,01/18/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66923,77590,70232,PRETRIAL,Ortiz,Jose,NULL,Male,African-American,11/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,New,1,0 +66923,77590,70232,PRETRIAL,Ortiz,Jose,NULL,Male,African-American,11/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.77,10,High,New,1,0 +66923,77590,70232,PRETRIAL,Ortiz,Jose,NULL,Male,African-American,11/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +57318,77613,59415,Probation,MARTIN,MILTON,NULL,Male,Hispanic,12/12/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,Copy,1,0 +57318,77613,59415,Probation,MARTIN,MILTON,NULL,Male,Hispanic,12/12/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,Copy,1,0 +57318,77613,59415,Probation,MARTIN,MILTON,NULL,Male,Hispanic,12/12/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +66924,77592,70233,PRETRIAL,WELLS,JONATHAN,SABAHATTIN,Male,Caucasian,05/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +66924,77592,70233,PRETRIAL,WELLS,JONATHAN,SABAHATTIN,Male,Caucasian,05/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +66924,77592,70233,PRETRIAL,WELLS,JONATHAN,SABAHATTIN,Male,Caucasian,05/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66928,77598,70239,Probation,Bradwell,Jared,NULL,Male,African-American,04/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,2,Medium,7,Risk of Violence,-2.59,2,Low,New,1,0 +66928,77598,70239,Probation,Bradwell,Jared,NULL,Male,African-American,04/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +66928,77598,70239,Probation,Bradwell,Jared,NULL,Male,African-American,04/01/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66933,77605,70246,Probation,ramroop,roger,NULL,Male,Other,05/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +66933,77605,70246,Probation,ramroop,roger,NULL,Male,Other,05/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +66933,77605,70246,Probation,ramroop,roger,NULL,Male,Other,05/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66937,77610,70249,Probation,Jafri,Arshad,NULL,Male,Arabic,04/20/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/15/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +66937,77610,70249,Probation,Jafri,Arshad,NULL,Male,Arabic,04/20/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/15/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +66937,77610,70249,Probation,Jafri,Arshad,NULL,Male,Arabic,04/20/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +21395,77606,70247,PRETRIAL,MIRANDA,MOISES,NULL,Male,Caucasian,06/27/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/15/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +21395,77606,70247,PRETRIAL,MIRANDA,MOISES,NULL,Male,Caucasian,06/27/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/15/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +21395,77606,70247,PRETRIAL,MIRANDA,MOISES,NULL,Male,Caucasian,06/27/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +64827,77589,70231,Probation,johnson,tyrone,NULL,Male,African-American,03/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +64827,77589,70231,Probation,johnson,tyrone,NULL,Male,African-American,03/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +64827,77589,70231,Probation,johnson,tyrone,NULL,Male,African-American,03/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66930,77601,70242,PRETRIAL,Johnson,Dammieum,NULL,Male,African-American,05/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +66930,77601,70242,PRETRIAL,Johnson,Dammieum,NULL,Male,African-American,05/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +66930,77601,70242,PRETRIAL,Johnson,Dammieum,NULL,Male,African-American,05/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +8771,77615,70253,PRETRIAL,WEATHERHOLT,RICHARD,NULL,Male,Caucasian,11/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +8771,77615,70253,PRETRIAL,WEATHERHOLT,RICHARD,NULL,Male,Caucasian,11/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +8771,77615,70253,PRETRIAL,WEATHERHOLT,RICHARD,NULL,Male,Caucasian,11/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +52709,77594,70235,PRETRIAL,Henley,Brandon,NULL,Male,African-American,10/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +52709,77594,70235,PRETRIAL,Henley,Brandon,NULL,Male,African-American,10/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +52709,77594,70235,PRETRIAL,Henley,Brandon,NULL,Male,African-American,10/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +66927,77597,70238,PRETRIAL,SWASKEE,SYLAS,NULL,Male,Caucasian,01/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +66927,77597,70238,PRETRIAL,SWASKEE,SYLAS,NULL,Male,Caucasian,01/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +66927,77597,70238,PRETRIAL,SWASKEE,SYLAS,NULL,Male,Caucasian,01/10/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +22575,77593,70234,PRETRIAL,BEIN,GEORGE,NULL,Male,Caucasian,06/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,4,High,7,Risk of Violence,-1.2,8,High,New,1,0 +22575,77593,70234,PRETRIAL,BEIN,GEORGE,NULL,Male,Caucasian,06/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +22575,77593,70234,PRETRIAL,BEIN,GEORGE,NULL,Male,Caucasian,06/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +66595,77609,69860,PRETRIAL,Aguilar,Johanna,NULL,Female,Hispanic,10/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,Copy,1,0 +66595,77609,69860,PRETRIAL,Aguilar,Johanna,NULL,Female,Hispanic,10/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,Copy,1,0 +66595,77609,69860,PRETRIAL,Aguilar,Johanna,NULL,Female,Hispanic,10/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +14232,77602,70243,PRETRIAL,Ruiz,Thomas,L,Male,Caucasian,07/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,New,1,0 +14232,77602,70243,PRETRIAL,Ruiz,Thomas,L,Male,Caucasian,07/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +14232,77602,70243,PRETRIAL,Ruiz,Thomas,L,Male,Caucasian,07/14/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +66941,77616,70254,PRETRIAL,CORONADO,KIMBERLY,NULL,Female,Caucasian,02/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +66941,77616,70254,PRETRIAL,CORONADO,KIMBERLY,NULL,Female,Caucasian,02/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +66941,77616,70254,PRETRIAL,CORONADO,KIMBERLY,NULL,Female,Caucasian,02/08/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +49647,77591,59854,PRETRIAL,Dorsey,Trevor,NULL,Male,African-American,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/15/14 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,Copy,1,0 +49647,77591,59854,PRETRIAL,Dorsey,Trevor,NULL,Male,African-American,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,Copy,1,0 +49647,77591,59854,PRETRIAL,Dorsey,Trevor,NULL,Male,African-American,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/15/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +66939,77612,70251,Probation,Wilson,Benjamin,Carlos,Male,Hispanic,06/01/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/15/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +66939,77612,70251,Probation,Wilson,Benjamin,Carlos,Male,Hispanic,06/01/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/15/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +66939,77612,70251,Probation,Wilson,Benjamin,Carlos,Male,Hispanic,06/01/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +41700,77599,70240,PRETRIAL,FERNANDEZROBLES,GIANCARLO,NULL,Male,Caucasian,12/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +41700,77599,70240,PRETRIAL,FERNANDEZROBLES,GIANCARLO,NULL,Male,Caucasian,12/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +41700,77599,70240,PRETRIAL,FERNANDEZROBLES,GIANCARLO,NULL,Male,Caucasian,12/25/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66926,77596,70237,PRETRIAL,Anglero,AmANDA,NULL,Female,Caucasian,11/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +66926,77596,70237,PRETRIAL,Anglero,AmANDA,NULL,Female,Caucasian,11/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +66926,77596,70237,PRETRIAL,Anglero,AmANDA,NULL,Female,Caucasian,11/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66932,77604,70245,Probation,GONZALEZ,JOHN,NULL,Male,Caucasian,01/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/15/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +66932,77604,70245,Probation,GONZALEZ,JOHN,NULL,Male,Caucasian,01/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/15/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +66932,77604,70245,Probation,GONZALEZ,JOHN,NULL,Male,Caucasian,01/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66940,77617,70255,PRETRIAL,Tolliver,Russell,NULL,Male,Caucasian,02/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/15/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +66940,77617,70255,PRETRIAL,Tolliver,Russell,NULL,Male,Caucasian,02/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/15/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +66940,77617,70255,PRETRIAL,Tolliver,Russell,NULL,Male,Caucasian,02/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/15/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +40321,77654,70291,PRETRIAL,Kozma,Joseph,NULL,Male,Caucasian,09/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +40321,77654,70291,PRETRIAL,Kozma,Joseph,NULL,Male,Caucasian,09/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +40321,77654,70291,PRETRIAL,Kozma,Joseph,NULL,Male,Caucasian,09/08/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66947,77625,70263,PRETRIAL,Bruck,Bas,NULL,Female,Caucasian,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/16/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +66947,77625,70263,PRETRIAL,Bruck,Bas,NULL,Female,Caucasian,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/16/14 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +66947,77625,70263,PRETRIAL,Bruck,Bas,NULL,Female,Caucasian,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66958,77638,70276,Probation,san pedro,christopher,NULL,Male,Hispanic,03/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +66958,77638,70276,Probation,san pedro,christopher,NULL,Male,Hispanic,03/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +66958,77638,70276,Probation,san pedro,christopher,NULL,Male,Hispanic,03/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66965,77646,70283,Probation,Primeaux,prima,NULL,Female,Native American,08/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,2,Medium,7,Risk of Violence,-2.86,2,Low,New,1,0 +66965,77646,70283,Probation,Primeaux,prima,NULL,Female,Native American,08/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,New,1,0 +66965,77646,70283,Probation,Primeaux,prima,NULL,Female,Native American,08/15/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66976,77659,70296,Probation,DIAZ,MICHAEL,NULL,Male,Hispanic,02/07/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +66976,77659,70296,Probation,DIAZ,MICHAEL,NULL,Male,Hispanic,02/07/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,4,High,8,Risk of Recidivism,0.36,8,High,New,1,0 +66976,77659,70296,Probation,DIAZ,MICHAEL,NULL,Male,Hispanic,02/07/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,4,High,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +66962,77641,70279,Probation,Treadwell,Maurice,NULL,Male,African-American,07/25/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +66962,77641,70279,Probation,Treadwell,Maurice,NULL,Male,African-American,07/25/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +66962,77641,70279,Probation,Treadwell,Maurice,NULL,Male,African-American,07/25/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66967,77648,70285,Probation,Solis,Maria,NULL,Female,Hispanic,04/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +66967,77648,70285,Probation,Solis,Maria,NULL,Female,Hispanic,04/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +66967,77648,70285,Probation,Solis,Maria,NULL,Female,Hispanic,04/15/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44894,77620,70258,PRETRIAL,Jeannot,Kirby,NULL,Male,African-American,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +44894,77620,70258,PRETRIAL,Jeannot,Kirby,NULL,Male,African-American,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +44894,77620,70258,PRETRIAL,Jeannot,Kirby,NULL,Male,African-American,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66949,77628,70266,PRETRIAL,welch,robert,NULL,Male,Caucasian,09/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +66949,77628,70266,PRETRIAL,welch,robert,NULL,Male,Caucasian,09/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +66949,77628,70266,PRETRIAL,welch,robert,NULL,Male,Caucasian,09/07/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66968,77649,70286,Probation,Sarsfield,Stephen,NULL,Male,Asian,07/08/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +66968,77649,70286,Probation,Sarsfield,Stephen,NULL,Male,Asian,07/08/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +66968,77649,70286,Probation,Sarsfield,Stephen,NULL,Male,Asian,07/08/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60153,77656,70293,PRETRIAL,BILLION,STEPHON,NULL,Male,African-American,07/23/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +60153,77656,70293,PRETRIAL,BILLION,STEPHON,NULL,Male,African-American,07/23/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +60153,77656,70293,PRETRIAL,BILLION,STEPHON,NULL,Male,African-American,07/23/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66945,77623,70261,PRETRIAL,Kassie,Trevon,Anthony,Male,African-American,07/20/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +66945,77623,70261,PRETRIAL,Kassie,Trevon,Anthony,Male,African-American,07/20/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +66945,77623,70261,PRETRIAL,Kassie,Trevon,Anthony,Male,African-American,07/20/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +57536,77630,70268,PRETRIAL,Turner,Tamika,NULL,Female,African-American,07/06/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/16/14 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +57536,77630,70268,PRETRIAL,Turner,Tamika,NULL,Female,African-American,07/06/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,6,Medium,New,1,0 +57536,77630,70268,PRETRIAL,Turner,Tamika,NULL,Female,African-American,07/06/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/16/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +66957,77637,70275,PRETRIAL,ELTRINGHAM,RONALD,BRUCE,Male,Caucasian,01/23/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/16/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +66957,77637,70275,PRETRIAL,ELTRINGHAM,RONALD,BRUCE,Male,Caucasian,01/23/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +66957,77637,70275,PRETRIAL,ELTRINGHAM,RONALD,BRUCE,Male,Caucasian,01/23/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66970,77651,70288,Probation,Heist,Vincent,NULL,Male,Caucasian,05/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +66970,77651,70288,Probation,Heist,Vincent,NULL,Male,Caucasian,05/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +66970,77651,70288,Probation,Heist,Vincent,NULL,Male,Caucasian,05/04/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66977,77660,70297,PRETRIAL,Maxwell,Erik,NULL,Male,African-American,10/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +66977,77660,70297,PRETRIAL,Maxwell,Erik,NULL,Male,African-American,10/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +66977,77660,70297,PRETRIAL,Maxwell,Erik,NULL,Male,African-American,10/19/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66942,77618,70256,PRETRIAL,Torres,Sigfredo,NULL,Male,Hispanic,02/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +66942,77618,70256,PRETRIAL,Torres,Sigfredo,NULL,Male,Hispanic,02/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +66942,77618,70256,PRETRIAL,Torres,Sigfredo,NULL,Male,Hispanic,02/16/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66955,77635,70273,Probation,DIDONATO,MICHELLE,D,Female,Hispanic,02/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +66955,77635,70273,Probation,DIDONATO,MICHELLE,D,Female,Hispanic,02/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.3,3,Low,New,1,0 +66955,77635,70273,Probation,DIDONATO,MICHELLE,D,Female,Hispanic,02/14/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66972,77653,70290,Probation,mills,tavia,NULL,Female,African-American,11/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +66972,77653,70290,Probation,mills,tavia,NULL,Female,African-American,11/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +66972,77653,70290,Probation,mills,tavia,NULL,Female,African-American,11/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66952,77632,70270,PRETRIAL,Garcia,Kevin,NULL,Male,Hispanic,08/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +66952,77632,70270,PRETRIAL,Garcia,Kevin,NULL,Male,Hispanic,08/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +66952,77632,70270,PRETRIAL,Garcia,Kevin,NULL,Male,Hispanic,08/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +66959,77639,70277,PRETRIAL,Avalo,Nelson,NULL,Male,Caucasian,08/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +66959,77639,70277,PRETRIAL,Avalo,Nelson,NULL,Male,Caucasian,08/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +66959,77639,70277,PRETRIAL,Avalo,Nelson,NULL,Male,Caucasian,08/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66961,77643,70281,PRETRIAL,JOSEPH,JEREMIAH,NULL,Male,African-American,08/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +66961,77643,70281,PRETRIAL,JOSEPH,JEREMIAH,NULL,Male,African-American,08/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,2,Medium,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +66961,77643,70281,PRETRIAL,JOSEPH,JEREMIAH,NULL,Male,African-American,08/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66963,77645,70282,Probation,DRIVER,RICHARD,NULL,Male,Native American,12/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +66963,77645,70282,Probation,DRIVER,RICHARD,NULL,Male,Native American,12/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +66963,77645,70282,Probation,DRIVER,RICHARD,NULL,Male,Native American,12/22/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66944,77622,70260,PRETRIAL,Quintraille,Javoris,G,Male,African-American,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +66944,77622,70260,PRETRIAL,Quintraille,Javoris,G,Male,African-American,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +66944,77622,70260,PRETRIAL,Quintraille,Javoris,G,Male,African-American,01/27/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66946,77624,70262,PRETRIAL,Flores,Abraham,NULL,Male,Hispanic,09/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +66946,77624,70262,PRETRIAL,Flores,Abraham,NULL,Male,Hispanic,09/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +66946,77624,70262,PRETRIAL,Flores,Abraham,NULL,Male,Hispanic,09/22/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66971,77652,70289,Probation,KEARNEY,PATRICIA,M,Female,Caucasian,11/02/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +66971,77652,70289,Probation,KEARNEY,PATRICIA,M,Female,Caucasian,11/02/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +66971,77652,70289,Probation,KEARNEY,PATRICIA,M,Female,Caucasian,11/02/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +54117,77657,70294,PRETRIAL,caraveo,cedgar,NULL,Male,Hispanic,10/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +54117,77657,70294,PRETRIAL,caraveo,cedgar,NULL,Male,Hispanic,10/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +54117,77657,70294,PRETRIAL,caraveo,cedgar,NULL,Male,Hispanic,10/30/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66951,77631,70269,PRETRIAL,farmer,douglas,NULL,Male,Caucasian,02/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.11,4,Low,New,1,0 +66951,77631,70269,PRETRIAL,farmer,douglas,NULL,Male,Caucasian,02/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +66951,77631,70269,PRETRIAL,farmer,douglas,NULL,Male,Caucasian,02/04/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +19645,77619,70257,PRETRIAL,PULIDO,JEREMY,BENJAMIN,Male,Caucasian,03/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +19645,77619,70257,PRETRIAL,PULIDO,JEREMY,BENJAMIN,Male,Caucasian,03/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +19645,77619,70257,PRETRIAL,PULIDO,JEREMY,BENJAMIN,Male,Caucasian,03/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66954,77634,70272,Probation,Territo,Jennifer,NULL,Female,Caucasian,12/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +66954,77634,70272,Probation,Territo,Jennifer,NULL,Female,Caucasian,12/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +66954,77634,70272,Probation,Territo,Jennifer,NULL,Female,Caucasian,12/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66966,77647,70284,PRETRIAL,bailey,mary,NULL,Male,African-American,05/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +66966,77647,70284,PRETRIAL,bailey,mary,NULL,Male,African-American,05/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,New,1,0 +66966,77647,70284,PRETRIAL,bailey,mary,NULL,Male,African-American,05/06/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66969,77650,70287,Probation,tomassoni,ricardo,NULL,Male,Caucasian,11/18/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +66969,77650,70287,Probation,tomassoni,ricardo,NULL,Male,Caucasian,11/18/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +66969,77650,70287,Probation,tomassoni,ricardo,NULL,Male,Caucasian,11/18/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +66943,77621,70259,PRETRIAL,Cole,Debbie,NULL,Female,African-American,01/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +66943,77621,70259,PRETRIAL,Cole,Debbie,NULL,Female,African-American,01/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +66943,77621,70259,PRETRIAL,Cole,Debbie,NULL,Female,African-American,01/21/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66950,77629,70267,PRETRIAL,Taylor,Marquis,NULL,Male,African-American,05/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/16/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +66950,77629,70267,PRETRIAL,Taylor,Marquis,NULL,Male,African-American,05/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/16/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +66950,77629,70267,PRETRIAL,Taylor,Marquis,NULL,Male,African-American,05/09/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/16/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +3570,77642,70280,PRETRIAL,dalonzo,merle,v,Male,Caucasian,03/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/14 0:00,2,Medium,7,Risk of Violence,-2.99,1,Low,New,1,0 +3570,77642,70280,PRETRIAL,dalonzo,merle,v,Male,Caucasian,03/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +3570,77642,70280,PRETRIAL,dalonzo,merle,v,Male,Caucasian,03/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/16/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66979,77663,70299,PRETRIAL,Matthew,Jonathan,Bert,Male,African-American,03/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +66979,77663,70299,PRETRIAL,Matthew,Jonathan,Bert,Male,African-American,03/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +66979,77663,70299,PRETRIAL,Matthew,Jonathan,Bert,Male,African-American,03/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +7685,77671,7269,PRETRIAL,John,Deverlaude,NULL,Male,African-American,05/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,Copy,1,0 +7685,77671,7269,PRETRIAL,John,Deverlaude,NULL,Male,African-American,05/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,Copy,1,0 +7685,77671,7269,PRETRIAL,John,Deverlaude,NULL,Male,African-American,05/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +66998,77689,70321,PRETRIAL,Wantuck,Erick,NULL,Male,Caucasian,08/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/14 0:00,2,Medium,7,Risk of Violence,-2.73,2,Low,New,1,0 +66998,77689,70321,PRETRIAL,Wantuck,Erick,NULL,Male,Caucasian,08/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +66998,77689,70321,PRETRIAL,Wantuck,Erick,NULL,Male,Caucasian,08/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +66993,77684,70316,Probation,dukes,reginald,emmanuel,Male,African-American,05/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +66993,77684,70316,Probation,dukes,reginald,emmanuel,Male,African-American,05/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +66993,77684,70316,Probation,dukes,reginald,emmanuel,Male,African-American,05/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +66978,77661,70298,PRETRIAL,Ledoux,Sander,NULL,Male,African-American,11/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,New,1,0 +66978,77661,70298,PRETRIAL,Ledoux,Sander,NULL,Male,African-American,11/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,New,1,0 +66978,77661,70298,PRETRIAL,Ledoux,Sander,NULL,Male,African-American,11/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66988,77678,70311,PRETRIAL,cote,thomas,NULL,Male,Caucasian,03/27/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +66988,77678,70311,PRETRIAL,cote,thomas,NULL,Male,Caucasian,03/27/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,6,Medium,New,1,0 +66988,77678,70311,PRETRIAL,cote,thomas,NULL,Male,Caucasian,03/27/87,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,2,Medium,18,Risk of Failure to Appear,23,4,Low,New,1,0 +66996,77687,70319,PRETRIAL,CLARK,DAVID,NULL,Male,Caucasian,11/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +66996,77687,70319,PRETRIAL,CLARK,DAVID,NULL,Male,Caucasian,11/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +66996,77687,70319,PRETRIAL,CLARK,DAVID,NULL,Male,Caucasian,11/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66982,77666,70302,PRETRIAL,Mers,John,Bruce,Male,Caucasian,06/10/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +66982,77666,70302,PRETRIAL,Mers,John,Bruce,Male,Caucasian,06/10/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +66982,77666,70302,PRETRIAL,Mers,John,Bruce,Male,Caucasian,06/10/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +66985,77673,70307,Probation,Selleck,Floyd,NULL,Male,Caucasian,06/18/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/17/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +66985,77673,70307,Probation,Selleck,Floyd,NULL,Male,Caucasian,06/18/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/17/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +66985,77673,70307,Probation,Selleck,Floyd,NULL,Male,Caucasian,06/18/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +57729,77680,70313,Probation,Lopez,Carlos,NULL,Male,Hispanic,03/03/61,17,All Scales,Intake,English,Pretrial,Probation,Single,10/17/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +57729,77680,70313,Probation,Lopez,Carlos,NULL,Male,Hispanic,03/03/61,17,All Scales,Intake,English,Pretrial,Probation,Single,10/17/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +57729,77680,70313,Probation,Lopez,Carlos,NULL,Male,Hispanic,03/03/61,17,All Scales,Intake,English,Pretrial,Probation,Single,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66995,77686,70318,Probation,PLASKER,DEBRA,L,Female,Caucasian,09/09/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +66995,77686,70318,Probation,PLASKER,DEBRA,L,Female,Caucasian,09/09/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +66995,77686,70318,Probation,PLASKER,DEBRA,L,Female,Caucasian,09/09/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +66981,77665,70301,PRETRIAL,Green,Richard,A,Male,Caucasian,04/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +66981,77665,70301,PRETRIAL,Green,Richard,A,Male,Caucasian,04/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +66981,77665,70301,PRETRIAL,Green,Richard,A,Male,Caucasian,04/21/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +8689,77674,70308,PRETRIAL,FRANCOIS,LIONEL,JUMIOR,Male,African-American,08/01/86,17,All Scales,Intake,English,Pretrial,Probation,Single,10/17/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +8689,77674,70308,PRETRIAL,FRANCOIS,LIONEL,JUMIOR,Male,African-American,08/01/86,17,All Scales,Intake,English,Pretrial,Probation,Single,10/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,5,Medium,New,1,0 +8689,77674,70308,PRETRIAL,FRANCOIS,LIONEL,JUMIOR,Male,African-American,08/01/86,17,All Scales,Intake,English,Pretrial,Probation,Single,10/17/14 0:00,2,Medium,18,Risk of Failure to Appear,28,7,Medium,New,1,0 +66989,77679,70312,Probation,Mangual,Nestor,Adam,Male,Hispanic,05/06/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/17/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +66989,77679,70312,Probation,Mangual,Nestor,Adam,Male,Hispanic,05/06/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/17/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +66989,77679,70312,Probation,Mangual,Nestor,Adam,Male,Hispanic,05/06/73,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +30014,77681,28981,PRETRIAL,Benitez,Carlos,Rene,Male,Hispanic,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.07,8,High,Copy,1,0 +30014,77681,28981,PRETRIAL,Benitez,Carlos,Rene,Male,Hispanic,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,7,Medium,Copy,1,0 +30014,77681,28981,PRETRIAL,Benitez,Carlos,Rene,Male,Hispanic,12/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +66997,77688,70320,Probation,kooper,kenneth,NULL,Male,Caucasian,07/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/17/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +66997,77688,70320,Probation,kooper,kenneth,NULL,Male,Caucasian,07/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/17/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +66997,77688,70320,Probation,kooper,kenneth,NULL,Male,Caucasian,07/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66992,77683,70315,Probation,Vought,Toby,David,Male,Caucasian,09/18/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/17/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +66992,77683,70315,Probation,Vought,Toby,David,Male,Caucasian,09/18/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/17/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +66992,77683,70315,Probation,Vought,Toby,David,Male,Caucasian,09/18/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66999,77690,70322,PRETRIAL,LOPEZ,ELIZABETH,NULL,Female,Hispanic,09/07/62,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,10/17/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +66999,77690,70322,PRETRIAL,LOPEZ,ELIZABETH,NULL,Female,Hispanic,09/07/62,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,10/17/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +66999,77690,70322,PRETRIAL,LOPEZ,ELIZABETH,NULL,Female,Hispanic,09/07/62,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56761,77662,68872,Probation,Cooper,Devin,NULL,Male,African-American,11/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,Copy,1,0 +56761,77662,68872,Probation,Cooper,Devin,NULL,Male,African-American,11/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,Copy,1,0 +56761,77662,68872,Probation,Cooper,Devin,NULL,Male,African-American,11/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +66987,77677,70310,Probation,Martin,John,NULL,Male,Caucasian,11/22/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +66987,77677,70310,Probation,Martin,John,NULL,Male,Caucasian,11/22/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +66987,77677,70310,Probation,Martin,John,NULL,Male,Caucasian,11/22/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +66984,77670,70306,PRETRIAL,Montes,Christopher,NULL,Male,Caucasian,05/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +66984,77670,70306,PRETRIAL,Montes,Christopher,NULL,Male,Caucasian,05/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +66984,77670,70306,PRETRIAL,Montes,Christopher,NULL,Male,Caucasian,05/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +23405,77672,47817,PRETRIAL,SESSIONS,EDDIE,NULL,Male,African-American,01/22/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.52,3,Low,Copy,1,0 +23405,77672,47817,PRETRIAL,SESSIONS,EDDIE,NULL,Male,African-American,01/22/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,Copy,1,0 +23405,77672,47817,PRETRIAL,SESSIONS,EDDIE,NULL,Male,African-American,01/22/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +66980,77664,70300,PRETRIAL,Clausell,Dietrich,Marcel,Male,African-American,10/22/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +66980,77664,70300,PRETRIAL,Clausell,Dietrich,Marcel,Male,African-American,10/22/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +66980,77664,70300,PRETRIAL,Clausell,Dietrich,Marcel,Male,African-American,10/22/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +66986,77675,70309,PRETRIAL,TAYLOR,RAVEN,NULL,Female,African-American,07/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +66986,77675,70309,PRETRIAL,TAYLOR,RAVEN,NULL,Female,African-American,07/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,9,High,New,1,0 +66986,77675,70309,PRETRIAL,TAYLOR,RAVEN,NULL,Female,African-American,07/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66994,77685,70317,Probation,Borgese,Michael,NULL,Male,Caucasian,07/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +66994,77685,70317,Probation,Borgese,Michael,NULL,Male,Caucasian,07/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,1,Low,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +66994,77685,70317,Probation,Borgese,Michael,NULL,Male,Caucasian,07/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/17/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65895,77706,69064,PRETRIAL,Wright,Tyrell,Umar,Male,African-American,06/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,4,High,7,Risk of Violence,-1.15,8,High,Copy,1,0 +65895,77706,69064,PRETRIAL,Wright,Tyrell,Umar,Male,African-American,06/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,4,High,8,Risk of Recidivism,0.58,9,High,Copy,1,0 +65895,77706,69064,PRETRIAL,Wright,Tyrell,Umar,Male,African-American,06/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +17673,77693,47602,PRETRIAL,JACKSON,JAVON,NULL,Male,African-American,09/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.45,7,Medium,Copy,1,0 +17673,77693,47602,PRETRIAL,JACKSON,JAVON,NULL,Male,African-American,09/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,Copy,1,0 +17673,77693,47602,PRETRIAL,JACKSON,JAVON,NULL,Male,African-American,09/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +67002,77698,70327,PRETRIAL,FOSTER,ROBERT,NULL,Male,African-American,03/04/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/18/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +67002,77698,70327,PRETRIAL,FOSTER,ROBERT,NULL,Male,African-American,03/04/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/18/14 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +67002,77698,70327,PRETRIAL,FOSTER,ROBERT,NULL,Male,African-American,03/04/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67011,77709,70337,PRETRIAL,Jazmin,Vonmarie,NULL,Female,African-American,06/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +67011,77709,70337,PRETRIAL,Jazmin,Vonmarie,NULL,Female,African-American,06/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +67011,77709,70337,PRETRIAL,Jazmin,Vonmarie,NULL,Female,African-American,06/20/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67006,77702,70331,PRETRIAL,Pydykowski,Jessica,Lynn,Female,Caucasian,11/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +67006,77702,70331,PRETRIAL,Pydykowski,Jessica,Lynn,Female,Caucasian,11/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +67006,77702,70331,PRETRIAL,Pydykowski,Jessica,Lynn,Female,Caucasian,11/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +67008,77704,70333,PRETRIAL,Cruz,Ruth,Roberta,Female,African-American,08/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +67008,77704,70333,PRETRIAL,Cruz,Ruth,Roberta,Female,African-American,08/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,7,Medium,New,1,0 +67008,77704,70333,PRETRIAL,Cruz,Ruth,Roberta,Female,African-American,08/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67003,77700,70329,PRETRIAL,Legra,Roger,NULL,Male,Caucasian,05/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +67003,77700,70329,PRETRIAL,Legra,Roger,NULL,Male,Caucasian,05/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +67003,77700,70329,PRETRIAL,Legra,Roger,NULL,Male,Caucasian,05/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +66045,77707,70335,PRETRIAL,Griffin,Roderick,NULL,Male,African-American,11/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.32,3,Low,New,1,0 +66045,77707,70335,PRETRIAL,Griffin,Roderick,NULL,Male,African-American,11/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +66045,77707,70335,PRETRIAL,Griffin,Roderick,NULL,Male,African-American,11/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67005,77701,70330,PRETRIAL,Dillion,Steven,NULL,Male,African-American,10/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +67005,77701,70330,PRETRIAL,Dillion,Steven,NULL,Male,African-American,10/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +67005,77701,70330,PRETRIAL,Dillion,Steven,NULL,Male,African-American,10/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +31309,77694,69651,PRETRIAL,Dailey,Keonah,NULL,Female,African-American,11/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,4,High,7,Risk of Violence,-1.2,8,High,Copy,1,0 +31309,77694,69651,PRETRIAL,Dailey,Keonah,NULL,Female,African-American,11/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,4,High,8,Risk of Recidivism,0.28,9,High,Copy,1,0 +31309,77694,69651,PRETRIAL,Dailey,Keonah,NULL,Female,African-American,11/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +67004,77699,70328,PRETRIAL,Sanford,Stephen,NULL,Male,Caucasian,06/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +67004,77699,70328,PRETRIAL,Sanford,Stephen,NULL,Male,Caucasian,06/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +67004,77699,70328,PRETRIAL,Sanford,Stephen,NULL,Male,Caucasian,06/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67010,77708,70336,PRETRIAL,Graham,Covaney,Evan,Male,African-American,06/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +67010,77708,70336,PRETRIAL,Graham,Covaney,Evan,Male,African-American,06/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +67010,77708,70336,PRETRIAL,Graham,Covaney,Evan,Male,African-American,06/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67007,77703,70332,PRETRIAL,Menard,Evodie,NULL,Female,African-American,01/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +67007,77703,70332,PRETRIAL,Menard,Evodie,NULL,Female,African-American,01/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,8,Risk of Recidivism,-2.35,1,Low,New,1,0 +67007,77703,70332,PRETRIAL,Menard,Evodie,NULL,Female,African-American,01/08/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67009,77705,70334,PRETRIAL,Bouma,Timothy,a,Male,Caucasian,02/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +67009,77705,70334,PRETRIAL,Bouma,Timothy,a,Male,Caucasian,02/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +67009,77705,70334,PRETRIAL,Bouma,Timothy,a,Male,Caucasian,02/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67001,77697,70326,PRETRIAL,Jones,Robert,NULL,Male,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +67001,77697,70326,PRETRIAL,Jones,Robert,NULL,Male,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +67001,77697,70326,PRETRIAL,Jones,Robert,NULL,Male,African-American,06/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67013,77710,70338,PRETRIAL,Untalan,Feymarie,NULL,Female,Other,11/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,2,Medium,7,Risk of Violence,-2.81,2,Low,New,1,0 +67013,77710,70338,PRETRIAL,Untalan,Feymarie,NULL,Female,Other,11/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.41,6,Medium,New,1,0 +67013,77710,70338,PRETRIAL,Untalan,Feymarie,NULL,Female,Other,11/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +9770,77718,70344,PRETRIAL,ebanks,thomas,NULL,Male,Caucasian,02/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +9770,77718,70344,PRETRIAL,ebanks,thomas,NULL,Male,Caucasian,02/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.77,10,High,New,1,0 +9770,77718,70344,PRETRIAL,ebanks,thomas,NULL,Male,Caucasian,02/09/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +66914,77720,70217,PRETRIAL,Jewel,Demetrius,NULL,Male,African-American,01/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/19/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,Copy,1,0 +66914,77720,70217,PRETRIAL,Jewel,Demetrius,NULL,Male,African-American,01/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,Copy,1,0 +66914,77720,70217,PRETRIAL,Jewel,Demetrius,NULL,Male,African-American,01/19/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/19/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +12561,77713,12045,PRETRIAL,Brown,Jamaal,Maurice,Male,African-American,07/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,Copy,1,0 +12561,77713,12045,PRETRIAL,Brown,Jamaal,Maurice,Male,African-American,07/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,Copy,1,0 +12561,77713,12045,PRETRIAL,Brown,Jamaal,Maurice,Male,African-American,07/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +67024,77726,70351,PRETRIAL,Carvello,Juanita,NULL,Female,Caucasian,11/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/19/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +67024,77726,70351,PRETRIAL,Carvello,Juanita,NULL,Female,Caucasian,11/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/19/14 0:00,1,Low,8,Risk of Recidivism,-1.56,2,Low,New,1,0 +67024,77726,70351,PRETRIAL,Carvello,Juanita,NULL,Female,Caucasian,11/20/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67025,77728,70353,PRETRIAL,Fishman,Jared,HY,Male,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +67025,77728,70353,PRETRIAL,Fishman,Jared,HY,Male,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +67025,77728,70353,PRETRIAL,Fishman,Jared,HY,Male,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67014,77712,70340,PRETRIAL,HINCAPIEROMAN,ISAIAS,IVAN,Male,Caucasian,11/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/19/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +67014,77712,70340,PRETRIAL,HINCAPIEROMAN,ISAIAS,IVAN,Male,Caucasian,11/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/19/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +67014,77712,70340,PRETRIAL,HINCAPIEROMAN,ISAIAS,IVAN,Male,Caucasian,11/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67026,77729,70354,PRETRIAL,guerrero,dubian,NULL,Male,Hispanic,01/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +67026,77729,70354,PRETRIAL,guerrero,dubian,NULL,Male,Hispanic,01/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +67026,77729,70354,PRETRIAL,guerrero,dubian,NULL,Male,Hispanic,01/28/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67015,77715,70341,PRETRIAL,SANTANA,ESTEBAN,NULL,Male,Caucasian,10/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +67015,77715,70341,PRETRIAL,SANTANA,ESTEBAN,NULL,Male,Caucasian,10/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,4,High,8,Risk of Recidivism,0.14,8,High,New,1,0 +67015,77715,70341,PRETRIAL,SANTANA,ESTEBAN,NULL,Male,Caucasian,10/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +31289,77717,70343,PRETRIAL,Murzike,Brain,NULL,Male,African-American,03/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +31289,77717,70343,PRETRIAL,Murzike,Brain,NULL,Male,African-American,03/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +31289,77717,70343,PRETRIAL,Murzike,Brain,NULL,Male,African-American,03/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67019,77722,70347,PRETRIAL,RICHARDS,GARTH,NULL,Male,African-American,10/15/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +67019,77722,70347,PRETRIAL,RICHARDS,GARTH,NULL,Male,African-American,10/15/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,New,1,0 +67019,77722,70347,PRETRIAL,RICHARDS,GARTH,NULL,Male,African-American,10/15/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67021,77724,70349,PRETRIAL,Gunning,Mark,Alan,Male,Caucasian,06/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/19/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +67021,77724,70349,PRETRIAL,Gunning,Mark,Alan,Male,Caucasian,06/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/19/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +67021,77724,70349,PRETRIAL,Gunning,Mark,Alan,Male,Caucasian,06/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67023,77725,70350,PRETRIAL,Florio,Joseph,Henry,Male,Caucasian,03/15/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/19/14 0:00,1,Low,7,Risk of Violence,-4.39,1,Low,New,1,0 +67023,77725,70350,PRETRIAL,Florio,Joseph,Henry,Male,Caucasian,03/15/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/19/14 0:00,1,Low,8,Risk of Recidivism,-2.78,1,Low,New,1,0 +67023,77725,70350,PRETRIAL,Florio,Joseph,Henry,Male,Caucasian,03/15/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67018,77721,70346,PRETRIAL,Smith,Robert,NULL,Male,Caucasian,03/21/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +67018,77721,70346,PRETRIAL,Smith,Robert,NULL,Male,Caucasian,03/21/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +67018,77721,70346,PRETRIAL,Smith,Robert,NULL,Male,Caucasian,03/21/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67020,77723,70348,PRETRIAL,Lopez,Christopher,NULL,Male,Caucasian,07/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/19/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +67020,77723,70348,PRETRIAL,Lopez,Christopher,NULL,Male,Caucasian,07/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/19/14 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +67020,77723,70348,PRETRIAL,Lopez,Christopher,NULL,Male,Caucasian,07/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67028,77730,70355,PRETRIAL,FELINOR,WILKERSON,NULL,Male,African-American,10/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +67028,77730,70355,PRETRIAL,FELINOR,WILKERSON,NULL,Male,African-American,10/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +67028,77730,70355,PRETRIAL,FELINOR,WILKERSON,NULL,Male,African-American,10/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67017,77719,70345,PRETRIAL,Bryant,Joquial,NULL,Female,African-American,12/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +67017,77719,70345,PRETRIAL,Bryant,Joquial,NULL,Female,African-American,12/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +67017,77719,70345,PRETRIAL,Bryant,Joquial,NULL,Female,African-American,12/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67012,77711,70339,PRETRIAL,RODRIGUEZ,KIMBERLY,YVETTE,Female,Caucasian,09/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +67012,77711,70339,PRETRIAL,RODRIGUEZ,KIMBERLY,YVETTE,Female,Caucasian,09/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +67012,77711,70339,PRETRIAL,RODRIGUEZ,KIMBERLY,YVETTE,Female,Caucasian,09/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67022,77727,70352,PRETRIAL,jonassaint,emile,NULL,Male,African-American,12/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +67022,77727,70352,PRETRIAL,jonassaint,emile,NULL,Male,African-American,12/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +67022,77727,70352,PRETRIAL,jonassaint,emile,NULL,Male,African-American,12/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +12347,77714,11841,PRETRIAL,SMALL,TERRANCE,NULL,Male,African-American,03/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,Copy,1,0 +12347,77714,11841,PRETRIAL,SMALL,TERRANCE,NULL,Male,African-American,03/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,Copy,1,0 +12347,77714,11841,PRETRIAL,SMALL,TERRANCE,NULL,Male,African-American,03/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/19/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +67039,77732,70357,PRETRIAL,McBride,Henry,NULL,Male,African-American,04/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +67039,77732,70357,PRETRIAL,McBride,Henry,NULL,Male,African-American,04/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +67039,77732,70357,PRETRIAL,McBride,Henry,NULL,Male,African-American,04/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67041,77735,70360,PRETRIAL,FERNANDEZ,JACLYN,MARIE,Female,Caucasian,10/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +67041,77735,70360,PRETRIAL,FERNANDEZ,JACLYN,MARIE,Female,Caucasian,10/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +67041,77735,70360,PRETRIAL,FERNANDEZ,JACLYN,MARIE,Female,Caucasian,10/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67056,77753,70376,PRETRIAL,Dopps,Erica,Marie,Female,Caucasian,06/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,10/20/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +67056,77753,70376,PRETRIAL,Dopps,Erica,Marie,Female,Caucasian,06/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +67056,77753,70376,PRETRIAL,Dopps,Erica,Marie,Female,Caucasian,06/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +52375,77761,69472,PRETRIAL,Thomas,Murvin,J,Male,African-American,03/29/86,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,4,High,7,Risk of Violence,-0.8,9,High,New,1,0 +52375,77761,69472,PRETRIAL,Thomas,Murvin,J,Male,African-American,03/29/86,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,4,High,8,Risk of Recidivism,0.67,9,High,New,1,0 +52375,77761,69472,PRETRIAL,Thomas,Murvin,J,Male,African-American,03/29/86,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +67046,77740,70364,PRETRIAL,MCGAUGH,HANNAH,ELIZABETH,Female,Caucasian,08/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +67046,77740,70364,PRETRIAL,MCGAUGH,HANNAH,ELIZABETH,Female,Caucasian,08/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,9,High,New,1,0 +67046,77740,70364,PRETRIAL,MCGAUGH,HANNAH,ELIZABETH,Female,Caucasian,08/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +27466,77774,70394,PRETRIAL,Smith,Ebony,NULL,Male,African-American,04/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +27466,77774,70394,PRETRIAL,Smith,Ebony,NULL,Male,African-American,04/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +27466,77774,70394,PRETRIAL,Smith,Ebony,NULL,Male,African-American,04/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67070,77777,70396,Probation,delarosa,david,NULL,Male,Caucasian,05/01/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +67070,77777,70396,Probation,delarosa,david,NULL,Male,Caucasian,05/01/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +67070,77777,70396,Probation,delarosa,david,NULL,Male,Caucasian,05/01/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67057,77756,70377,PRETRIAL,Ali,Frank,Isiah,Male,African-American,11/23/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/20/14 0:00,2,Medium,7,Risk of Violence,-3.48,1,Low,New,1,0 +67057,77756,70377,PRETRIAL,Ali,Frank,Isiah,Male,African-American,11/23/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +67057,77756,70377,PRETRIAL,Ali,Frank,Isiah,Male,African-American,11/23/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/20/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67065,77769,70389,PRETRIAL,ALBRITTON,LAWRENCE,NULL,Male,African-American,10/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +67065,77769,70389,PRETRIAL,ALBRITTON,LAWRENCE,NULL,Male,African-American,10/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +67065,77769,70389,PRETRIAL,ALBRITTON,LAWRENCE,NULL,Male,African-American,10/11/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67043,77737,70361,PRETRIAL,Robinson,Sherry,Kay,Female,African-American,11/23/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-2.35,3,Low,New,1,0 +67043,77737,70361,PRETRIAL,Robinson,Sherry,Kay,Female,African-American,11/23/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +67043,77737,70361,PRETRIAL,Robinson,Sherry,Kay,Female,African-American,11/23/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67054,77751,70374,Probation,clarke,Wllie,NULL,Male,African-American,07/01/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +67054,77751,70374,Probation,clarke,Wllie,NULL,Male,African-American,07/01/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +67054,77751,70374,Probation,clarke,Wllie,NULL,Male,African-American,07/01/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67059,77760,70381,DRRD,Kennedy,Peter,Henry,Male,Caucasian,02/17/90,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/20/14 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +67059,77760,70381,DRRD,Kennedy,Peter,Henry,Male,Caucasian,02/17/90,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,6,Medium,New,1,0 +67059,77760,70381,DRRD,Kennedy,Peter,Henry,Male,Caucasian,02/17/90,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/20/14 0:00,2,Medium,18,Risk of Failure to Appear,26,6,Medium,New,1,0 +54136,77779,70398,PRETRIAL,Cardona,Freddy,NULL,Male,Caucasian,02/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/20/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +54136,77779,70398,PRETRIAL,Cardona,Freddy,NULL,Male,Caucasian,02/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/20/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +54136,77779,70398,PRETRIAL,Cardona,Freddy,NULL,Male,Caucasian,02/15/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +11240,77758,70379,PRETRIAL,PREAL,JOSHUA,NULL,Male,African-American,05/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +11240,77758,70379,PRETRIAL,PREAL,JOSHUA,NULL,Male,African-American,05/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +11240,77758,70379,PRETRIAL,PREAL,JOSHUA,NULL,Male,African-American,05/03/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67074,77781,70400,Probation,cruz,pedro,NULL,Male,Hispanic,01/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +67074,77781,70400,Probation,cruz,pedro,NULL,Male,Hispanic,01/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +67074,77781,70400,Probation,cruz,pedro,NULL,Male,Hispanic,01/13/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +35254,77742,70366,PRETRIAL,Donaldson,Anthony,NULL,Female,African-American,10/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +35254,77742,70366,PRETRIAL,Donaldson,Anthony,NULL,Female,African-American,10/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +35254,77742,70366,PRETRIAL,Donaldson,Anthony,NULL,Female,African-American,10/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +67064,77767,70387,Probation,Carcamo,Osiris,NULL,Male,Hispanic,08/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,2,Medium,7,Risk of Violence,-2.72,2,Low,New,1,0 +67064,77767,70387,Probation,Carcamo,Osiris,NULL,Male,Hispanic,08/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +67064,77767,70387,Probation,Carcamo,Osiris,NULL,Male,Hispanic,08/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67068,77772,70392,Probation,Caraballo,Nelson,NULL,Male,Hispanic,06/26/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/20/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +67068,77772,70392,Probation,Caraballo,Nelson,NULL,Male,Hispanic,06/26/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/20/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +67068,77772,70392,Probation,Caraballo,Nelson,NULL,Male,Hispanic,06/26/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67050,77746,70370,PRETRIAL,WELCOME,JEFFERY,NULL,Male,African-American,02/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +67050,77746,70370,PRETRIAL,WELCOME,JEFFERY,NULL,Male,African-American,02/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +67050,77746,70370,PRETRIAL,WELCOME,JEFFERY,NULL,Male,African-American,02/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67047,77743,70367,PRETRIAL,Carmichael,Richard,Lee,Male,Caucasian,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +67047,77743,70367,PRETRIAL,Carmichael,Richard,Lee,Male,Caucasian,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +67047,77743,70367,PRETRIAL,Carmichael,Richard,Lee,Male,Caucasian,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67049,77745,70369,PRETRIAL,Boles,Tracy,Wendell,Male,African-American,06/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +67049,77745,70369,PRETRIAL,Boles,Tracy,Wendell,Male,African-American,06/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +67049,77745,70369,PRETRIAL,Boles,Tracy,Wendell,Male,African-American,06/02/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67044,77738,70362,PRETRIAL,Mayor,Horacio,Enrique,Male,Hispanic,12/07/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/20/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +67044,77738,70362,PRETRIAL,Mayor,Horacio,Enrique,Male,Hispanic,12/07/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/20/14 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +67044,77738,70362,PRETRIAL,Mayor,Horacio,Enrique,Male,Hispanic,12/07/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67055,77752,70375,PRETRIAL,Barber,Larrell,NULL,Male,African-American,04/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.4,3,Low,New,1,0 +67055,77752,70375,PRETRIAL,Barber,Larrell,NULL,Male,African-American,04/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +67055,77752,70375,PRETRIAL,Barber,Larrell,NULL,Male,African-American,04/12/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +67073,77780,70399,PRETRIAL,SAMPSON,MICHAEL,NULL,Male,African-American,02/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +67073,77780,70399,PRETRIAL,SAMPSON,MICHAEL,NULL,Male,African-American,02/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +67073,77780,70399,PRETRIAL,SAMPSON,MICHAEL,NULL,Male,African-American,02/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67058,77759,70380,PRETRIAL,cooke,steven,NULL,Male,Caucasian,04/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +67058,77759,70380,PRETRIAL,cooke,steven,NULL,Male,Caucasian,04/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +67058,77759,70380,PRETRIAL,cooke,steven,NULL,Male,Caucasian,04/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67040,77733,70358,PRETRIAL,BYRD,CHRISTOPHER,NULL,Male,African-American,05/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/20/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +67040,77733,70358,PRETRIAL,BYRD,CHRISTOPHER,NULL,Male,African-American,05/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +67040,77733,70358,PRETRIAL,BYRD,CHRISTOPHER,NULL,Male,African-American,05/02/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61293,77768,70388,PRETRIAL,KUCHERICK,SHERI,NULL,Female,Caucasian,10/01/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +61293,77768,70388,PRETRIAL,KUCHERICK,SHERI,NULL,Female,Caucasian,10/01/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +61293,77768,70388,PRETRIAL,KUCHERICK,SHERI,NULL,Female,Caucasian,10/01/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67067,77771,70391,Probation,Eaves,Dawn,NULL,Female,Caucasian,04/08/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +67067,77771,70391,Probation,Eaves,Dawn,NULL,Female,Caucasian,04/08/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +67067,77771,70391,Probation,Eaves,Dawn,NULL,Female,Caucasian,04/08/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +67053,77750,70373,PRETRIAL,Gow,Alexis,NULL,Female,Caucasian,09/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +67053,77750,70373,PRETRIAL,Gow,Alexis,NULL,Female,Caucasian,09/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +67053,77750,70373,PRETRIAL,Gow,Alexis,NULL,Female,Caucasian,09/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67069,77775,70395,PRETRIAL,Douglas,christopher,NULL,Male,African-American,11/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +67069,77775,70395,PRETRIAL,Douglas,christopher,NULL,Male,African-American,11/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +67069,77775,70395,PRETRIAL,Douglas,christopher,NULL,Male,African-American,11/29/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67061,77762,70382,PRETRIAL,Carlisle,Jeffrey,NULL,Male,Caucasian,10/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.85,9,High,New,1,0 +67061,77762,70382,PRETRIAL,Carlisle,Jeffrey,NULL,Male,Caucasian,10/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +67061,77762,70382,PRETRIAL,Carlisle,Jeffrey,NULL,Male,Caucasian,10/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66804,77747,70096,PRETRIAL,FERDINAND,USBEL,NULL,Male,African-American,09/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,Copy,1,0 +66804,77747,70096,PRETRIAL,FERDINAND,USBEL,NULL,Male,African-American,09/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,Copy,1,0 +66804,77747,70096,PRETRIAL,FERDINAND,USBEL,NULL,Male,African-American,09/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +67052,77749,70372,PRETRIAL,Jeudy,Dieucica,NULL,Female,African-American,03/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/20/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +67052,77749,70372,PRETRIAL,Jeudy,Dieucica,NULL,Female,African-American,03/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +67052,77749,70372,PRETRIAL,Jeudy,Dieucica,NULL,Female,African-American,03/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67042,77734,70359,PRETRIAL,Dawkins,Rayon,Oneil,Male,Other,09/24/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/20/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +67042,77734,70359,PRETRIAL,Dawkins,Rayon,Oneil,Male,Other,09/24/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/20/14 0:00,1,Low,8,Risk of Recidivism,-2.56,1,Low,New,1,0 +67042,77734,70359,PRETRIAL,Dawkins,Rayon,Oneil,Male,Other,09/24/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67066,77770,70390,Probation,COLLINS,CARL,NULL,Male,Caucasian,08/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.27,3,Low,New,1,0 +67066,77770,70390,Probation,COLLINS,CARL,NULL,Male,Caucasian,08/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.66,10,High,New,1,0 +67066,77770,70390,Probation,COLLINS,CARL,NULL,Male,Caucasian,08/27/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +51161,77741,70365,PRETRIAL,CASIMIR,DELAMA,NULL,Male,African-American,12/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,7,Risk of Violence,-1.75,5,Medium,New,1,0 +51161,77741,70365,PRETRIAL,CASIMIR,DELAMA,NULL,Male,African-American,12/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +51161,77741,70365,PRETRIAL,CASIMIR,DELAMA,NULL,Male,African-American,12/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +66974,77755,70295,PRETRIAL,Matthews,Damion,NULL,Male,African-American,07/23/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,Copy,1,0 +66974,77755,70295,PRETRIAL,Matthews,Damion,NULL,Male,African-American,07/23/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,Copy,1,0 +66974,77755,70295,PRETRIAL,Matthews,Damion,NULL,Male,African-American,07/23/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +65264,77736,68345,Probation,Alexander-Wilcox,Dionte,NULL,Male,African-American,06/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,4,High,7,Risk of Violence,-0.42,10,High,Copy,1,0 +65264,77736,68345,Probation,Alexander-Wilcox,Dionte,NULL,Male,African-American,06/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,4,High,8,Risk of Recidivism,0.97,10,High,Copy,1,0 +65264,77736,68345,Probation,Alexander-Wilcox,Dionte,NULL,Male,African-American,06/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +67045,77739,70363,PRETRIAL,MOTTER,GREGORY,LYNN,Male,Caucasian,03/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/20/14 0:00,1,Low,7,Risk of Violence,-4.5,1,Low,New,1,0 +67045,77739,70363,PRETRIAL,MOTTER,GREGORY,LYNN,Male,Caucasian,03/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/20/14 0:00,1,Low,8,Risk of Recidivism,-2.9,1,Low,New,1,0 +67045,77739,70363,PRETRIAL,MOTTER,GREGORY,LYNN,Male,Caucasian,03/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +25847,77757,70378,PRETRIAL,MERKELL,JOSHUA,NULL,Male,Caucasian,11/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +25847,77757,70378,PRETRIAL,MERKELL,JOSHUA,NULL,Male,Caucasian,11/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +25847,77757,70378,PRETRIAL,MERKELL,JOSHUA,NULL,Male,Caucasian,11/12/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67048,77744,70368,PRETRIAL,Chaney,Darrick,Keith,Male,African-American,02/04/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +67048,77744,70368,PRETRIAL,Chaney,Darrick,Keith,Male,African-American,02/04/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +67048,77744,70368,PRETRIAL,Chaney,Darrick,Keith,Male,African-American,02/04/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67071,77778,70397,Probation,Taft,Donald,NULL,Male,African-American,01/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/20/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +67071,77778,70397,Probation,Taft,Donald,NULL,Male,African-American,01/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/20/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +67071,77778,70397,Probation,Taft,Donald,NULL,Male,African-American,01/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66542,77731,70356,PRETRIAL,Altidor,Brion,Lil John,Male,African-American,08/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,4,High,7,Risk of Violence,0.93,10,High,New,1,0 +66542,77731,70356,PRETRIAL,Altidor,Brion,Lil John,Male,African-American,08/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,4,High,8,Risk of Recidivism,1.2,10,High,New,1,0 +66542,77731,70356,PRETRIAL,Altidor,Brion,Lil John,Male,African-American,08/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/20/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +67062,77765,70385,Probation,kelly,yolanda,NULL,Female,African-American,01/31/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +67062,77765,70385,Probation,kelly,yolanda,NULL,Female,African-American,01/31/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,8,Risk of Recidivism,-1.16,3,Low,New,1,0 +67062,77765,70385,Probation,kelly,yolanda,NULL,Female,African-American,01/31/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/20/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +67093,77812,70428,PRETRIAL,Bell,Lario,NULL,Male,African-American,02/01/58,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,Copy,1,0 +67093,77812,70428,PRETRIAL,Bell,Lario,NULL,Male,African-American,02/01/58,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,Copy,1,0 +67093,77812,70428,PRETRIAL,Bell,Lario,NULL,Male,African-American,02/01/58,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +67077,77786,70405,PRETRIAL,Belfleur,Marie,Noel,Female,Other,12/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +67077,77786,70405,PRETRIAL,Belfleur,Marie,Noel,Female,Other,12/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +67077,77786,70405,PRETRIAL,Belfleur,Marie,Noel,Female,Other,12/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60368,77804,70422,PRETRIAL,MAJEED,MUNTAZ,NULL,Male,African-American,09/26/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/21/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +60368,77804,70422,PRETRIAL,MAJEED,MUNTAZ,NULL,Male,African-American,09/26/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/21/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +60368,77804,70422,PRETRIAL,MAJEED,MUNTAZ,NULL,Male,African-American,09/26/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67078,77791,70409,PRETRIAL,Robinson,Carnell,NULL,Male,African-American,01/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,4,High,7,Risk of Violence,-0.76,9,High,New,1,0 +67078,77791,70409,PRETRIAL,Robinson,Carnell,NULL,Male,African-American,01/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +67078,77791,70409,PRETRIAL,Robinson,Carnell,NULL,Male,African-American,01/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67075,77783,70402,PRETRIAL,Geneve,Agathe,NULL,Female,Other,01/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +67075,77783,70402,PRETRIAL,Geneve,Agathe,NULL,Female,Other,01/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +67075,77783,70402,PRETRIAL,Geneve,Agathe,NULL,Female,Other,01/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +40037,77789,70408,PRETRIAL,TYLER,LEROY,NULL,Male,African-American,04/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +40037,77789,70408,PRETRIAL,TYLER,LEROY,NULL,Male,African-American,04/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +40037,77789,70408,PRETRIAL,TYLER,LEROY,NULL,Male,African-American,04/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +13923,77785,70404,PRETRIAL,SCOTT,TONY,NULL,Male,African-American,09/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.04,8,High,New,1,0 +13923,77785,70404,PRETRIAL,SCOTT,TONY,NULL,Male,African-American,09/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +13923,77785,70404,PRETRIAL,SCOTT,TONY,NULL,Male,African-American,09/03/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67089,77806,70424,Probation,urena-vasquez,juan,NULL,Male,Hispanic,05/15/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +67089,77806,70424,Probation,urena-vasquez,juan,NULL,Male,Hispanic,05/15/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +67089,77806,70424,Probation,urena-vasquez,juan,NULL,Male,Hispanic,05/15/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67093,77810,70428,PRETRIAL,Bell,Lario,NULL,Male,African-American,02/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +67093,77810,70428,PRETRIAL,Bell,Lario,NULL,Male,African-American,02/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.2,8,High,New,1,0 +67093,77810,70428,PRETRIAL,Bell,Lario,NULL,Male,African-American,02/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +66696,77787,70406,PRETRIAL,baptiste,rakeem,NULL,Female,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +66696,77787,70406,PRETRIAL,baptiste,rakeem,NULL,Female,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,9,High,New,1,0 +66696,77787,70406,PRETRIAL,baptiste,rakeem,NULL,Female,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67086,77801,70419,Probation,Hernandez,Obdulio,NULL,Male,Hispanic,07/31/76,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/21/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +67086,77801,70419,Probation,Hernandez,Obdulio,NULL,Male,Hispanic,07/31/76,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/21/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +67086,77801,70419,Probation,Hernandez,Obdulio,NULL,Male,Hispanic,07/31/76,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67081,77794,70412,PRETRIAL,BELLO,ALAIN,ALDUNCIN,Male,Hispanic,12/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +67081,77794,70412,PRETRIAL,BELLO,ALAIN,ALDUNCIN,Male,Hispanic,12/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +67081,77794,70412,PRETRIAL,BELLO,ALAIN,ALDUNCIN,Male,Hispanic,12/06/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67082,77796,70414,PRETRIAL,WRIGHT,JOHN,WESLEY,Male,African-American,09/14/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +67082,77796,70414,PRETRIAL,WRIGHT,JOHN,WESLEY,Male,African-American,09/14/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +67082,77796,70414,PRETRIAL,WRIGHT,JOHN,WESLEY,Male,African-American,09/14/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +67096,77815,70432,PRETRIAL,Ulrich,Jacob,NULL,Male,Caucasian,09/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +67096,77815,70432,PRETRIAL,Ulrich,Jacob,NULL,Male,Caucasian,09/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,New,1,0 +67096,77815,70432,PRETRIAL,Ulrich,Jacob,NULL,Male,Caucasian,09/19/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +26441,77793,70411,PRETRIAL,Hidalgo,Neil,Joseph,Male,Caucasian,07/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +26441,77793,70411,PRETRIAL,Hidalgo,Neil,Joseph,Male,Caucasian,07/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +26441,77793,70411,PRETRIAL,Hidalgo,Neil,Joseph,Male,Caucasian,07/09/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +17462,77797,70415,Probation,Patterson,Ernestine,NULL,Female,African-American,04/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,2,Medium,7,Risk of Violence,-2.81,2,Low,New,1,0 +17462,77797,70415,Probation,Patterson,Ernestine,NULL,Female,African-American,04/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +17462,77797,70415,Probation,Patterson,Ernestine,NULL,Female,African-American,04/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67098,77818,70434,Probation,Rodriguez,Jason,David,Male,Hispanic,08/13/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/21/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +67098,77818,70434,Probation,Rodriguez,Jason,David,Male,Hispanic,08/13/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/21/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +67098,77818,70434,Probation,Rodriguez,Jason,David,Male,Hispanic,08/13/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62961,77814,70431,Probation,jones,wesley,NULL,Male,African-American,09/20/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +62961,77814,70431,Probation,jones,wesley,NULL,Male,African-American,09/20/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +62961,77814,70431,Probation,jones,wesley,NULL,Male,African-American,09/20/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +50157,77788,70407,PRETRIAL,LABOY,ADALBERTO,NULL,Male,Caucasian,10/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +50157,77788,70407,PRETRIAL,LABOY,ADALBERTO,NULL,Male,Caucasian,10/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +50157,77788,70407,PRETRIAL,LABOY,ADALBERTO,NULL,Male,Caucasian,10/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67087,77802,70420,Probation,Taylorlaury,Laura,NULL,Female,Caucasian,10/19/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/21/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +67087,77802,70420,Probation,Taylorlaury,Laura,NULL,Female,Caucasian,10/19/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/21/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +67087,77802,70420,Probation,Taylorlaury,Laura,NULL,Female,Caucasian,10/19/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67092,77809,70427,PRETRIAL,ALVAREZ,RUBIN,NULL,Male,Hispanic,12/24/69,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,10/21/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +67092,77809,70427,PRETRIAL,ALVAREZ,RUBIN,NULL,Male,Hispanic,12/24/69,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,10/21/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +67092,77809,70427,PRETRIAL,ALVAREZ,RUBIN,NULL,Male,Hispanic,12/24/69,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67076,77784,70403,PRETRIAL,Nevadomski,Anthony,Joseph,Male,Caucasian,08/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +67076,77784,70403,PRETRIAL,Nevadomski,Anthony,Joseph,Male,Caucasian,08/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +67076,77784,70403,PRETRIAL,Nevadomski,Anthony,Joseph,Male,Caucasian,08/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67099,77819,70435,Probation,LAMONT,JOHN,GERALD,Male,Caucasian,05/16/42,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/21/14 0:00,1,Low,7,Risk of Violence,-4.43,1,Low,New,1,0 +67099,77819,70435,Probation,LAMONT,JOHN,GERALD,Male,Caucasian,05/16/42,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/21/14 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,New,1,0 +67099,77819,70435,Probation,LAMONT,JOHN,GERALD,Male,Caucasian,05/16/42,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67083,77798,70416,Probation,Wright,Rawlston,NULL,Male,African-American,04/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +67083,77798,70416,Probation,Wright,Rawlston,NULL,Male,African-American,04/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +67083,77798,70416,Probation,Wright,Rawlston,NULL,Male,African-American,04/16/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67088,77805,70423,PRETRIAL,Finkel,Donald,NULL,Male,Caucasian,07/26/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/14 0:00,1,Low,7,Risk of Violence,-4.55,1,Low,New,1,0 +67088,77805,70423,PRETRIAL,Finkel,Donald,NULL,Male,Caucasian,07/26/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/14 0:00,1,Low,8,Risk of Recidivism,-2.95,1,Low,New,1,0 +67088,77805,70423,PRETRIAL,Finkel,Donald,NULL,Male,Caucasian,07/26/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +26480,77790,40087,PRETRIAL,Thompson,James,Alfred,Male,Caucasian,09/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.39,3,Low,Copy,1,0 +26480,77790,40087,PRETRIAL,Thompson,James,Alfred,Male,Caucasian,09/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +26480,77790,40087,PRETRIAL,Thompson,James,Alfred,Male,Caucasian,09/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,Copy,1,0 +67079,77792,70410,Probation,Coleman,Travis,NULL,Male,African-American,10/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +67079,77792,70410,Probation,Coleman,Travis,NULL,Male,African-American,10/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +67079,77792,70410,Probation,Coleman,Travis,NULL,Male,African-American,10/18/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67094,77811,70429,Probation,Garnica,Rolando,NULL,Male,Hispanic,05/23/80,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/21/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +67094,77811,70429,Probation,Garnica,Rolando,NULL,Male,Hispanic,05/23/80,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/21/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +67094,77811,70429,Probation,Garnica,Rolando,NULL,Male,Hispanic,05/23/80,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67095,77813,70430,PRETRIAL,SWISHER,CASSYE,NULL,Female,Caucasian,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +67095,77813,70430,PRETRIAL,SWISHER,CASSYE,NULL,Female,Caucasian,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +67095,77813,70430,PRETRIAL,SWISHER,CASSYE,NULL,Female,Caucasian,07/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +26480,43853,40087,PRETRIAL,Thompson,James,Alfred,Male,Caucasian,09/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +26480,43853,40087,PRETRIAL,Thompson,James,Alfred,Male,Caucasian,09/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +26480,43853,40087,PRETRIAL,Thompson,James,Alfred,Male,Caucasian,09/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +67080,77795,70413,PRETRIAL,Trinidad,Alejandro,NULL,Male,Caucasian,09/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/21/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +67080,77795,70413,PRETRIAL,Trinidad,Alejandro,NULL,Male,Caucasian,09/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/21/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +67080,77795,70413,PRETRIAL,Trinidad,Alejandro,NULL,Male,Caucasian,09/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67106,77829,70444,Probation,McGirt,Tamika,NULL,Female,African-American,03/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +67106,77829,70444,Probation,McGirt,Tamika,NULL,Female,African-American,03/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +67106,77829,70444,Probation,McGirt,Tamika,NULL,Female,African-American,03/13/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61123,77803,70421,Probation,JACKSON,ERVIN,NULL,Male,African-American,07/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +61123,77803,70421,Probation,JACKSON,ERVIN,NULL,Male,African-American,07/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +61123,77803,70421,Probation,JACKSON,ERVIN,NULL,Male,African-American,07/28/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +55693,77821,70436,Probation,FLETCHER,MARK,ANTHONY,Male,African-American,08/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +55693,77821,70436,Probation,FLETCHER,MARK,ANTHONY,Male,African-American,08/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +55693,77821,70436,Probation,FLETCHER,MARK,ANTHONY,Male,African-American,08/02/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +47180,77782,70401,PRETRIAL,SCHULTHEISS,RONALD,CARL,Male,Caucasian,12/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +47180,77782,70401,PRETRIAL,SCHULTHEISS,RONALD,CARL,Male,Caucasian,12/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +47180,77782,70401,PRETRIAL,SCHULTHEISS,RONALD,CARL,Male,Caucasian,12/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/21/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67085,77800,70418,PRETRIAL,Smith,Heaher,Ray,Female,Caucasian,09/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/21/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +67085,77800,70418,PRETRIAL,Smith,Heaher,Ray,Female,Caucasian,09/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/21/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +67085,77800,70418,PRETRIAL,Smith,Heaher,Ray,Female,Caucasian,09/19/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67124,77850,70464,PRETRIAL,loftis,lorraine,NULL,Female,Caucasian,12/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.96,1,Low,New,1,0 +67124,77850,70464,PRETRIAL,loftis,lorraine,NULL,Female,Caucasian,12/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,8,High,New,1,0 +67124,77850,70464,PRETRIAL,loftis,lorraine,NULL,Female,Caucasian,12/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +67117,77842,70456,PRETRIAL,CLELLAND,ROBERT,NULL,Male,Caucasian,04/20/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/22/14 0:00,2,Medium,7,Risk of Violence,-3.03,1,Low,New,1,0 +67117,77842,70456,PRETRIAL,CLELLAND,ROBERT,NULL,Male,Caucasian,04/20/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +67117,77842,70456,PRETRIAL,CLELLAND,ROBERT,NULL,Male,Caucasian,04/20/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/22/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67103,77826,70441,PRETRIAL,Walcott,Ivorie,NULL,Male,African-American,11/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +67103,77826,70441,PRETRIAL,Walcott,Ivorie,NULL,Male,African-American,11/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +67103,77826,70441,PRETRIAL,Walcott,Ivorie,NULL,Male,African-American,11/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +36407,77847,70461,PRETRIAL,Raquepaw,Zachary,NULL,Male,Caucasian,06/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/14 0:00,2,Medium,7,Risk of Violence,-1.87,5,Medium,New,1,0 +36407,77847,70461,PRETRIAL,Raquepaw,Zachary,NULL,Male,Caucasian,06/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +36407,77847,70461,PRETRIAL,Raquepaw,Zachary,NULL,Male,Caucasian,06/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67110,77834,70448,PRETRIAL,Haggins,warrick,NULL,Male,African-American,07/22/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.88,9,High,New,1,0 +67110,77834,70448,PRETRIAL,Haggins,warrick,NULL,Male,African-American,07/22/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +67110,77834,70448,PRETRIAL,Haggins,warrick,NULL,Male,African-American,07/22/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +39478,77855,70468,PRETRIAL,ARIAS,DONNA,ELIZABETH,Female,Caucasian,01/14/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +39478,77855,70468,PRETRIAL,ARIAS,DONNA,ELIZABETH,Female,Caucasian,01/14/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +39478,77855,70468,PRETRIAL,ARIAS,DONNA,ELIZABETH,Female,Caucasian,01/14/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67101,77823,70438,PRETRIAL,Dayment,Pamela,NULL,Female,Caucasian,01/01/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.12,8,High,New,1,0 +67101,77823,70438,PRETRIAL,Dayment,Pamela,NULL,Female,Caucasian,01/01/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +67101,77823,70438,PRETRIAL,Dayment,Pamela,NULL,Female,Caucasian,01/01/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57499,77851,60485,PRETRIAL,Alonso,Jenny,NULL,Female,Hispanic,12/09/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,2,Medium,7,Risk of Violence,-1.81,5,Medium,Copy,1,0 +57499,77851,60485,PRETRIAL,Alonso,Jenny,NULL,Female,Hispanic,12/09/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,Copy,1,0 +57499,77851,60485,PRETRIAL,Alonso,Jenny,NULL,Female,Hispanic,12/09/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +67128,77858,70470,PRETRIAL,Mata,Jose,NULL,Male,Hispanic,08/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,Copy,1,0 +67128,77858,70470,PRETRIAL,Mata,Jose,NULL,Male,Hispanic,08/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,Copy,1,0 +67128,77858,70470,PRETRIAL,Mata,Jose,NULL,Male,Hispanic,08/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +67129,77860,70471,Probation,Urbano,Jean,NULL,Male,Hispanic,03/22/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +67129,77860,70471,Probation,Urbano,Jean,NULL,Male,Hispanic,03/22/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +67129,77860,70471,Probation,Urbano,Jean,NULL,Male,Hispanic,03/22/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67108,77832,70446,PRETRIAL,Pellerito,Russell,Joseph,Male,Caucasian,12/04/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +67108,77832,70446,PRETRIAL,Pellerito,Russell,Joseph,Male,Caucasian,12/04/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +67108,77832,70446,PRETRIAL,Pellerito,Russell,Joseph,Male,Caucasian,12/04/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67114,77839,70453,Probation,DIAZ,GABRIEL,E,Male,Hispanic,07/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +67114,77839,70453,Probation,DIAZ,GABRIEL,E,Male,Hispanic,07/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +67114,77839,70453,Probation,DIAZ,GABRIEL,E,Male,Hispanic,07/23/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67111,77835,70449,PRETRIAL,HUAROTTE,FABIO,NULL,Male,Caucasian,08/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,4,High,7,Risk of Violence,-1.23,8,High,New,1,0 +67111,77835,70449,PRETRIAL,HUAROTTE,FABIO,NULL,Male,Caucasian,08/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,4,High,8,Risk of Recidivism,0.25,8,High,New,1,0 +67111,77835,70449,PRETRIAL,HUAROTTE,FABIO,NULL,Male,Caucasian,08/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +15603,77853,70466,PRETRIAL,dorso,doreen,NULL,Female,Caucasian,03/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +15603,77853,70466,PRETRIAL,dorso,doreen,NULL,Female,Caucasian,03/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +15603,77853,70466,PRETRIAL,dorso,doreen,NULL,Female,Caucasian,03/06/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67119,77844,70458,PRETRIAL,Bowen,Jesse,NULL,Male,African-American,08/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +67119,77844,70458,PRETRIAL,Bowen,Jesse,NULL,Male,African-American,08/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +67119,77844,70458,PRETRIAL,Bowen,Jesse,NULL,Male,African-American,08/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67100,77822,70437,PRETRIAL,John,Robert,Erle,Male,African-American,08/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/22/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +67100,77822,70437,PRETRIAL,John,Robert,Erle,Male,African-American,08/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +67100,77822,70437,PRETRIAL,John,Robert,Erle,Male,African-American,08/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67102,77824,70439,PRETRIAL,VICTOR,JOHN,NULL,Male,African-American,12/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.57,10,High,New,1,0 +67102,77824,70439,PRETRIAL,VICTOR,JOHN,NULL,Male,African-American,12/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +67102,77824,70439,PRETRIAL,VICTOR,JOHN,NULL,Male,African-American,12/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67118,77843,70457,PRETRIAL,BAZAON,JUAN,NULL,Male,Hispanic,06/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +67118,77843,70457,PRETRIAL,BAZAON,JUAN,NULL,Male,Hispanic,06/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +67118,77843,70457,PRETRIAL,BAZAON,JUAN,NULL,Male,Hispanic,06/24/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67120,77845,70459,Probation,Anderson,Michael,NULL,Male,Caucasian,08/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +67120,77845,70459,Probation,Anderson,Michael,NULL,Male,Caucasian,08/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +67120,77845,70459,Probation,Anderson,Michael,NULL,Male,Caucasian,08/26/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67113,77838,70452,Probation,Guigon,Nicolas,NULL,Male,Hispanic,05/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/22/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +67113,77838,70452,Probation,Guigon,Nicolas,NULL,Male,Hispanic,05/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +67113,77838,70452,Probation,Guigon,Nicolas,NULL,Male,Hispanic,05/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +62383,77852,70465,PRETRIAL,Pinedaboteo,Rodrigo,NULL,Male,Hispanic,04/15/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/22/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +62383,77852,70465,PRETRIAL,Pinedaboteo,Rodrigo,NULL,Male,Hispanic,04/15/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +62383,77852,70465,PRETRIAL,Pinedaboteo,Rodrigo,NULL,Male,Hispanic,04/15/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65776,77859,68949,Probation,Cramasta,Brandon,NULL,Male,Caucasian,10/27/85,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +65776,77859,68949,Probation,Cramasta,Brandon,NULL,Male,Caucasian,10/27/85,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.73,10,High,New,1,0 +65776,77859,68949,Probation,Cramasta,Brandon,NULL,Male,Caucasian,10/27/85,17,All Scales,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +67104,77827,70442,PRETRIAL,Zacharias,Michael,NULL,Male,Caucasian,04/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +67104,77827,70442,PRETRIAL,Zacharias,Michael,NULL,Male,Caucasian,04/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +67104,77827,70442,PRETRIAL,Zacharias,Michael,NULL,Male,Caucasian,04/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67107,77831,70445,PRETRIAL,Abel,Kevin,Thomas,Male,Caucasian,05/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +67107,77831,70445,PRETRIAL,Abel,Kevin,Thomas,Male,Caucasian,05/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +67107,77831,70445,PRETRIAL,Abel,Kevin,Thomas,Male,Caucasian,05/22/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67115,77840,70454,Probation,Garcia,Luis,NULL,Male,Hispanic,06/27/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/22/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +67115,77840,70454,Probation,Garcia,Luis,NULL,Male,Hispanic,06/27/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +67115,77840,70454,Probation,Garcia,Luis,NULL,Male,Hispanic,06/27/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67112,77836,70450,Probation,Glatt,David,NULL,Male,Caucasian,09/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/22/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +67112,77836,70450,Probation,Glatt,David,NULL,Male,Caucasian,09/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +67112,77836,70450,Probation,Glatt,David,NULL,Male,Caucasian,09/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67123,77849,70463,Probation,bailey,robert,NULL,Male,Caucasian,02/16/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/22/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +67123,77849,70463,Probation,bailey,robert,NULL,Male,Caucasian,02/16/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +67123,77849,70463,Probation,bailey,robert,NULL,Male,Caucasian,02/16/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67127,77856,70469,Probation,Rodriguez,Luis,NULL,Male,Hispanic,11/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +67127,77856,70469,Probation,Rodriguez,Luis,NULL,Male,Hispanic,11/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +67127,77856,70469,Probation,Rodriguez,Luis,NULL,Male,Hispanic,11/11/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +67105,77828,70443,PRETRIAL,Butler,Brian,NULL,Male,African-American,01/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +67105,77828,70443,PRETRIAL,Butler,Brian,NULL,Male,African-American,01/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +67105,77828,70443,PRETRIAL,Butler,Brian,NULL,Male,African-American,01/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67116,77841,70455,PRETRIAL,Jefferson,Carl,NULL,Male,African-American,11/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/22/14 0:00,2,Medium,7,Risk of Violence,-2.71,2,Low,New,1,0 +67116,77841,70455,PRETRIAL,Jefferson,Carl,NULL,Male,African-American,11/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +67116,77841,70455,PRETRIAL,Jefferson,Carl,NULL,Male,African-American,11/16/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/22/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67122,77848,70462,Probation,Alban,Diego,NULL,Male,Hispanic,11/29/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/22/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +67122,77848,70462,Probation,Alban,Diego,NULL,Male,Hispanic,11/29/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +67122,77848,70462,Probation,Alban,Diego,NULL,Male,Hispanic,11/29/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67126,77854,70467,Probation,FENDRICH,RICKY,NULL,Male,Caucasian,07/06/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/22/14 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +67126,77854,70467,Probation,FENDRICH,RICKY,NULL,Male,Caucasian,07/06/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/22/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +67126,77854,70467,Probation,FENDRICH,RICKY,NULL,Male,Caucasian,07/06/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +47796,77825,70440,PRETRIAL,Gill,Rico,NULL,Male,Other,01/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +47796,77825,70440,PRETRIAL,Gill,Rico,NULL,Male,Other,01/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +47796,77825,70440,PRETRIAL,Gill,Rico,NULL,Male,Other,01/06/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67121,77846,70460,Probation,MCCLARNEY,RAYMOND,A,Male,Caucasian,09/17/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +67121,77846,70460,Probation,MCCLARNEY,RAYMOND,A,Male,Caucasian,09/17/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +67121,77846,70460,Probation,MCCLARNEY,RAYMOND,A,Male,Caucasian,09/17/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67145,77880,70489,PRETRIAL,Crapps,Elizabeth,NULL,Female,Caucasian,07/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,10/23/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +67145,77880,70489,PRETRIAL,Crapps,Elizabeth,NULL,Female,Caucasian,07/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,10/23/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +67145,77880,70489,PRETRIAL,Crapps,Elizabeth,NULL,Female,Caucasian,07/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67157,77893,70501,Probation,Burns,Erica,NULL,Female,African-American,06/27/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +67157,77893,70501,Probation,Burns,Erica,NULL,Female,African-American,06/27/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +67157,77893,70501,Probation,Burns,Erica,NULL,Female,African-American,06/27/74,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67136,77867,70478,PRETRIAL,Jean,Judith,NULL,Female,Other,12/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +67136,77867,70478,PRETRIAL,Jean,Judith,NULL,Female,Other,12/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +67136,77867,70478,PRETRIAL,Jean,Judith,NULL,Female,Other,12/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +9304,77872,70483,Probation,Bellamy,Ralph,NULL,Male,African-American,08/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,4,High,7,Risk of Violence,-1.23,8,High,New,1,0 +9304,77872,70483,Probation,Bellamy,Ralph,NULL,Male,African-American,08/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,4,High,8,Risk of Recidivism,0.34,9,High,New,1,0 +9304,77872,70483,Probation,Bellamy,Ralph,NULL,Male,African-American,08/18/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67132,77864,70475,PRETRIAL,STRICKLAND,LLOYD,ALEXANDER,Male,African-American,04/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +67132,77864,70475,PRETRIAL,STRICKLAND,LLOYD,ALEXANDER,Male,African-American,04/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.49,9,High,New,1,0 +67132,77864,70475,PRETRIAL,STRICKLAND,LLOYD,ALEXANDER,Male,African-American,04/09/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67148,77885,70493,Probation,Zvolanek,alexander,NULL,Female,Caucasian,05/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.09,4,Low,New,1,0 +67148,77885,70493,Probation,Zvolanek,alexander,NULL,Female,Caucasian,05/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +67148,77885,70493,Probation,Zvolanek,alexander,NULL,Female,Caucasian,05/10/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +67155,77891,70499,Probation,Kenausis,Bejamin,Michael,Male,Caucasian,05/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +67155,77891,70499,Probation,Kenausis,Bejamin,Michael,Male,Caucasian,05/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +67155,77891,70499,Probation,Kenausis,Bejamin,Michael,Male,Caucasian,05/06/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67161,77898,70506,Probation,LEWIS,ERIC,K,Male,African-American,08/28/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/23/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +67161,77898,70506,Probation,LEWIS,ERIC,K,Male,African-American,08/28/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +67161,77898,70506,Probation,LEWIS,ERIC,K,Male,African-American,08/28/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +3953,77869,70480,PRETRIAL,JOHNSON,TOMMY,NULL,Male,African-American,11/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.68,6,Medium,New,1,0 +3953,77869,70480,PRETRIAL,JOHNSON,TOMMY,NULL,Male,African-American,11/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +3953,77869,70480,PRETRIAL,JOHNSON,TOMMY,NULL,Male,African-American,11/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,New,1,0 +67138,77870,70481,PRETRIAL,DAVIS,ANTHONY,M,Male,African-American,11/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.15,4,Low,New,1,0 +67138,77870,70481,PRETRIAL,DAVIS,ANTHONY,M,Male,African-American,11/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +67138,77870,70481,PRETRIAL,DAVIS,ANTHONY,M,Male,African-American,11/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67131,77862,70473,PRETRIAL,Fields,Caleb,NULL,Male,African-American,10/22/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +67131,77862,70473,PRETRIAL,Fields,Caleb,NULL,Male,African-American,10/22/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +67131,77862,70473,PRETRIAL,Fields,Caleb,NULL,Male,African-American,10/22/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67143,77877,70487,PRETRIAL,ETIENNE,LINDA,NULL,Female,African-American,01/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +67143,77877,70487,PRETRIAL,ETIENNE,LINDA,NULL,Female,African-American,01/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +67143,77877,70487,PRETRIAL,ETIENNE,LINDA,NULL,Female,African-American,01/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67154,77890,70498,Probation,Albert,David,NULL,Male,Caucasian,10/01/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/23/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +67154,77890,70498,Probation,Albert,David,NULL,Male,Caucasian,10/01/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/23/14 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +67154,77890,70498,Probation,Albert,David,NULL,Male,Caucasian,10/01/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67146,77882,70491,Probation,Escobar,Marco,NULL,Male,Hispanic,06/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/23/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +67146,77882,70491,Probation,Escobar,Marco,NULL,Male,Hispanic,06/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/23/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +67146,77882,70491,Probation,Escobar,Marco,NULL,Male,Hispanic,06/30/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +44068,77899,70507,Probation,Hines,Robert,NULL,Male,Caucasian,10/29/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +44068,77899,70507,Probation,Hines,Robert,NULL,Male,Caucasian,10/29/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +44068,77899,70507,Probation,Hines,Robert,NULL,Male,Caucasian,10/29/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +58172,77878,60374,Probation,SHEETS,ROBERT,C,Male,Caucasian,08/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Separated,10/23/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,Copy,1,0 +58172,77878,60374,Probation,SHEETS,ROBERT,C,Male,Caucasian,08/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Separated,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,Copy,1,0 +58172,77878,60374,Probation,SHEETS,ROBERT,C,Male,Caucasian,08/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Pretrial Defendant,Separated,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +67135,77866,70477,PRETRIAL,Jeancy,Yaminah,Wilson,Female,African-American,06/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/23/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +67135,77866,70477,PRETRIAL,Jeancy,Yaminah,Wilson,Female,African-American,06/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +67135,77866,70477,PRETRIAL,Jeancy,Yaminah,Wilson,Female,African-American,06/26/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67140,77873,70484,PRETRIAL,Baboolal,Triliya,NULL,Male,Caucasian,02/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +67140,77873,70484,PRETRIAL,Baboolal,Triliya,NULL,Male,Caucasian,02/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +67140,77873,70484,PRETRIAL,Baboolal,Triliya,NULL,Male,Caucasian,02/29/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67151,77887,70495,PRETRIAL,TINKER,RORY,GENE,Male,Caucasian,08/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +67151,77887,70495,PRETRIAL,TINKER,RORY,GENE,Male,Caucasian,08/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +67151,77887,70495,PRETRIAL,TINKER,RORY,GENE,Male,Caucasian,08/30/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67163,77901,70509,Probation,Witherington,Dainoral,NULL,Female,Caucasian,12/01/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/23/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +67163,77901,70509,Probation,Witherington,Dainoral,NULL,Female,Caucasian,12/01/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +67163,77901,70509,Probation,Witherington,Dainoral,NULL,Female,Caucasian,12/01/62,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67158,77894,70502,Probation,Anchante,Anthony,NULL,Male,Caucasian,07/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +67158,77894,70502,Probation,Anchante,Anthony,NULL,Male,Caucasian,07/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +67158,77894,70502,Probation,Anchante,Anthony,NULL,Male,Caucasian,07/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60009,77896,70504,PRETRIAL,Heidegger,Kevin,NULL,Male,Caucasian,02/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +60009,77896,70504,PRETRIAL,Heidegger,Kevin,NULL,Male,Caucasian,02/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +60009,77896,70504,PRETRIAL,Heidegger,Kevin,NULL,Male,Caucasian,02/08/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +67159,77895,70503,PRETRIAL,Taylor,Danielle,NULL,Female,African-American,09/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +67159,77895,70503,PRETRIAL,Taylor,Danielle,NULL,Female,African-American,09/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +67159,77895,70503,PRETRIAL,Taylor,Danielle,NULL,Female,African-American,09/26/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67134,77865,70476,PRETRIAL,LOPEZ,KEVIN,KLEIN,Male,Caucasian,10/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +67134,77865,70476,PRETRIAL,LOPEZ,KEVIN,KLEIN,Male,Caucasian,10/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +67134,77865,70476,PRETRIAL,LOPEZ,KEVIN,KLEIN,Male,Caucasian,10/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67150,77886,70494,Probation,quevedobecerra,miguel,NULL,Male,Caucasian,06/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +67150,77886,70494,Probation,quevedobecerra,miguel,NULL,Male,Caucasian,06/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +67150,77886,70494,Probation,quevedobecerra,miguel,NULL,Male,Caucasian,06/05/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67144,77879,70488,PRETRIAL,SHAW,JOSHUA,LOREN,Male,Caucasian,02/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +67144,77879,70488,PRETRIAL,SHAW,JOSHUA,LOREN,Male,Caucasian,02/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +67144,77879,70488,PRETRIAL,SHAW,JOSHUA,LOREN,Male,Caucasian,02/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67147,77881,70490,Probation,MCFARLANE,CONRADE,JOSEP,Male,African-American,12/31/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/23/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +67147,77881,70490,Probation,MCFARLANE,CONRADE,JOSEP,Male,African-American,12/31/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +67147,77881,70490,Probation,MCFARLANE,CONRADE,JOSEP,Male,African-American,12/31/57,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67152,77888,70496,Probation,Martinez,Francisco,NULL,Male,Hispanic,12/22/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +67152,77888,70496,Probation,Martinez,Francisco,NULL,Male,Hispanic,12/22/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +67152,77888,70496,Probation,Martinez,Francisco,NULL,Male,Hispanic,12/22/69,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67149,77884,70492,Probation,Charlemagne,Gerald,NULL,Male,African-American,05/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +67149,77884,70492,Probation,Charlemagne,Gerald,NULL,Male,African-American,05/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +67149,77884,70492,Probation,Charlemagne,Gerald,NULL,Male,African-American,05/02/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67156,77892,70500,Probation,Hislop,Norman,NULL,Male,Other,07/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +67156,77892,70500,Probation,Hislop,Norman,NULL,Male,Other,07/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +67156,77892,70500,Probation,Hislop,Norman,NULL,Male,Other,07/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67160,77897,70505,PRETRIAL,Dimeglio,Anthony,NULL,Male,Caucasian,04/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +67160,77897,70505,PRETRIAL,Dimeglio,Anthony,NULL,Male,Caucasian,04/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,New,1,0 +67160,77897,70505,PRETRIAL,Dimeglio,Anthony,NULL,Male,Caucasian,04/04/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67133,77863,70474,PRETRIAL,Snell,Tarance,NULL,Male,African-American,12/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +67133,77863,70474,PRETRIAL,Snell,Tarance,NULL,Male,African-American,12/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +67133,77863,70474,PRETRIAL,Snell,Tarance,NULL,Male,African-American,12/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67142,77876,70486,PRETRIAL,Simmons,Dwayne,Bouviea,Male,African-American,10/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,4,High,7,Risk of Violence,-0.9,9,High,New,1,0 +67142,77876,70486,PRETRIAL,Simmons,Dwayne,Bouviea,Male,African-American,10/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,4,High,8,Risk of Recidivism,0.79,10,High,New,1,0 +67142,77876,70486,PRETRIAL,Simmons,Dwayne,Bouviea,Male,African-American,10/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +67153,77889,70497,PRETRIAL,RAMOS,GUSTAVO,NULL,Male,Hispanic,11/12/69,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,10/23/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +67153,77889,70497,PRETRIAL,RAMOS,GUSTAVO,NULL,Male,Hispanic,11/12/69,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +67153,77889,70497,PRETRIAL,RAMOS,GUSTAVO,NULL,Male,Hispanic,11/12/69,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Married,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67137,77868,70479,PRETRIAL,Cifuentes-Esteban,Selvin,NULL,Male,Hispanic,02/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +67137,77868,70479,PRETRIAL,Cifuentes-Esteban,Selvin,NULL,Male,Hispanic,02/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +67137,77868,70479,PRETRIAL,Cifuentes-Esteban,Selvin,NULL,Male,Hispanic,02/28/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67139,77871,70482,PRETRIAL,Pena,Joseph,NULL,Male,African-American,09/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +67139,77871,70482,PRETRIAL,Pena,Joseph,NULL,Male,African-American,09/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +67139,77871,70482,PRETRIAL,Pena,Joseph,NULL,Male,African-American,09/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/23/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +65662,77918,68816,Probation,RIOSOSHO,CELINA,NULL,Female,Hispanic,10/19/80,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +65662,77918,68816,Probation,RIOSOSHO,CELINA,NULL,Female,Hispanic,10/19/80,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-1.01,3,Low,New,1,0 +65662,77918,68816,Probation,RIOSOSHO,CELINA,NULL,Female,Hispanic,10/19/80,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67188,77936,70539,Probation,bleyer,shawn,NULL,Male,Caucasian,07/13/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +67188,77936,70539,Probation,bleyer,shawn,NULL,Male,Caucasian,07/13/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +67188,77936,70539,Probation,bleyer,shawn,NULL,Male,Caucasian,07/13/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67170,77910,70517,PRETRIAL,LEROY,VENDAR,NULL,Female,African-American,12/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +67170,77910,70517,PRETRIAL,LEROY,VENDAR,NULL,Female,African-American,12/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +67170,77910,70517,PRETRIAL,LEROY,VENDAR,NULL,Female,African-American,12/16/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67181,77926,70529,PRETRIAL,martinez,ALFREDO,NULL,Male,Caucasian,12/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,4,High,7,Risk of Violence,-0.45,10,High,New,1,0 +67181,77926,70529,PRETRIAL,martinez,ALFREDO,NULL,Male,Caucasian,12/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,4,High,8,Risk of Recidivism,0.42,9,High,New,1,0 +67181,77926,70529,PRETRIAL,martinez,ALFREDO,NULL,Male,Caucasian,12/30/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +67171,77913,70519,PRETRIAL,simmons,bryan,NULL,Male,African-American,12/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +67171,77913,70519,PRETRIAL,simmons,bryan,NULL,Male,African-American,12/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +67171,77913,70519,PRETRIAL,simmons,bryan,NULL,Male,African-American,12/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67183,77928,70531,PRETRIAL,Lamelas,Henry,NULL,Male,Other,11/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.01,4,Low,New,1,0 +67183,77928,70531,PRETRIAL,Lamelas,Henry,NULL,Male,Other,11/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +67183,77928,70531,PRETRIAL,Lamelas,Henry,NULL,Male,Other,11/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +5391,77934,70537,PRETRIAL,BRADLEY,LASHONDA,NULL,Male,African-American,05/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +5391,77934,70537,PRETRIAL,BRADLEY,LASHONDA,NULL,Male,African-American,05/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +5391,77934,70537,PRETRIAL,BRADLEY,LASHONDA,NULL,Male,African-American,05/30/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67166,77905,70513,PRETRIAL,Alfano,Jonathan,NULL,Male,Hispanic,10/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +67166,77905,70513,PRETRIAL,Alfano,Jonathan,NULL,Male,Hispanic,10/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,4,High,8,Risk of Recidivism,0.18,8,High,New,1,0 +67166,77905,70513,PRETRIAL,Alfano,Jonathan,NULL,Male,Hispanic,10/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67177,77920,70524,Probation,simion,maureen,NULL,Female,Caucasian,10/14/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/14 0:00,2,Medium,7,Risk of Violence,-3.24,1,Low,New,1,0 +67177,77920,70524,Probation,simion,maureen,NULL,Female,Caucasian,10/14/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +67177,77920,70524,Probation,simion,maureen,NULL,Female,Caucasian,10/14/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/24/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67164,77902,70510,PRETRIAL,Marouf,Joseph,NULL,Male,Caucasian,11/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +67164,77902,70510,PRETRIAL,Marouf,Joseph,NULL,Male,Caucasian,11/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +67164,77902,70510,PRETRIAL,Marouf,Joseph,NULL,Male,Caucasian,11/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67189,77937,70540,Probation,Ogiste,Victory,NULL,Male,African-American,12/10/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,4,High,7,Risk of Violence,0.28,10,High,New,1,0 +67189,77937,70540,Probation,Ogiste,Victory,NULL,Male,African-American,12/10/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,4,High,8,Risk of Recidivism,0.88,10,High,New,1,0 +67189,77937,70540,Probation,Ogiste,Victory,NULL,Male,African-American,12/10/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,4,High,18,Risk of Failure to Appear,23,4,Low,New,1,0 +46296,77909,46688,PRETRIAL,glindmeier,lutz,NULL,Male,Caucasian,11/24/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,2,Medium,7,Risk of Violence,-3.56,1,Low,Copy,1,0 +46296,77909,46688,PRETRIAL,glindmeier,lutz,NULL,Male,Caucasian,11/24/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,Copy,1,0 +46296,77909,46688,PRETRIAL,glindmeier,lutz,NULL,Male,Caucasian,11/24/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +24487,77916,23671,PRETRIAL,Cummings,Alfred,NULL,Male,African-American,05/31/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.48,3,Low,Copy,1,0 +24487,77916,23671,PRETRIAL,Cummings,Alfred,NULL,Male,African-American,05/31/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,Copy,1,0 +24487,77916,23671,PRETRIAL,Cummings,Alfred,NULL,Male,African-American,05/31/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +46387,77923,47379,Probation,mitchell,sabra,NULL,Female,Caucasian,10/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +46387,77923,47379,Probation,mitchell,sabra,NULL,Female,Caucasian,10/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.41,6,Medium,Copy,1,0 +46387,77923,47379,Probation,mitchell,sabra,NULL,Female,Caucasian,10/17/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +67185,77930,70533,Probation,Lamay,Joey,Paul,Male,Caucasian,05/22/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +67185,77930,70533,Probation,Lamay,Joey,Paul,Male,Caucasian,05/22/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +67185,77930,70533,Probation,Lamay,Joey,Paul,Male,Caucasian,05/22/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67165,77904,70512,PRETRIAL,Edwards,Jerry,NULL,Male,African-American,07/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +67165,77904,70512,PRETRIAL,Edwards,Jerry,NULL,Male,African-American,07/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +67165,77904,70512,PRETRIAL,Edwards,Jerry,NULL,Male,African-American,07/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67178,77921,70525,Probation,Campos,Alex,NULL,Male,Hispanic,11/26/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-2.57,2,Low,New,1,0 +67178,77921,70525,Probation,Campos,Alex,NULL,Male,Hispanic,11/26/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +67178,77921,70525,Probation,Campos,Alex,NULL,Male,Hispanic,11/26/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67168,77907,70515,PRETRIAL,Dorce,Kerby,NULL,Male,Other,08/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-2.77,2,Low,New,1,0 +67168,77907,70515,PRETRIAL,Dorce,Kerby,NULL,Male,Other,08/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +67168,77907,70515,PRETRIAL,Dorce,Kerby,NULL,Male,Other,08/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67180,77925,70528,PRETRIAL,BENNETT,AUSTIN,NULL,Male,Caucasian,02/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +67180,77925,70528,PRETRIAL,BENNETT,AUSTIN,NULL,Male,Caucasian,02/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +67180,77925,70528,PRETRIAL,BENNETT,AUSTIN,NULL,Male,Caucasian,02/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67174,77915,70521,Probation,Young,Bruce,NULL,Male,Caucasian,06/30/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +67174,77915,70521,Probation,Young,Bruce,NULL,Male,Caucasian,06/30/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +67174,77915,70521,Probation,Young,Bruce,NULL,Male,Caucasian,06/30/60,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67175,77917,70522,Probation,kopelman,helene,NULL,Female,African-American,05/26/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/24/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +67175,77917,70522,Probation,kopelman,helene,NULL,Female,African-American,05/26/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/24/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +67175,77917,70522,Probation,kopelman,helene,NULL,Female,African-American,05/26/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +52668,77922,70526,PRETRIAL,LOUIS,COURTNEY,NULL,Male,African-American,05/11/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +52668,77922,70526,PRETRIAL,LOUIS,COURTNEY,NULL,Male,African-American,05/11/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +52668,77922,70526,PRETRIAL,LOUIS,COURTNEY,NULL,Male,African-American,05/11/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +67179,77924,70527,Probation,Sapp,Jamie,NULL,Male,African-American,03/24/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +67179,77924,70527,Probation,Sapp,Jamie,NULL,Male,African-American,03/24/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +67179,77924,70527,Probation,Sapp,Jamie,NULL,Male,African-American,03/24/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +60777,77938,70541,Probation,Carragino,Michael,Joseph,Male,Caucasian,12/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +60777,77938,70541,Probation,Carragino,Michael,Joseph,Male,Caucasian,12/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +60777,77938,70541,Probation,Carragino,Michael,Joseph,Male,Caucasian,12/26/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67172,77912,70518,PRETRIAL,Moreno,Victor,NULL,Male,African-American,02/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +67172,77912,70518,PRETRIAL,Moreno,Victor,NULL,Male,African-American,02/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.82,10,High,New,1,0 +67172,77912,70518,PRETRIAL,Moreno,Victor,NULL,Male,African-American,02/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67184,77929,70532,PRETRIAL,SHAH,RAVIH,NULL,Male,Caucasian,07/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +67184,77929,70532,PRETRIAL,SHAH,RAVIH,NULL,Male,Caucasian,07/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +67184,77929,70532,PRETRIAL,SHAH,RAVIH,NULL,Male,Caucasian,07/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +46509,77933,70536,PRETRIAL,Johnson,Keith,NULL,Male,African-American,12/03/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/24/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +46509,77933,70536,PRETRIAL,Johnson,Keith,NULL,Male,African-American,12/03/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/24/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +46509,77933,70536,PRETRIAL,Johnson,Keith,NULL,Male,African-American,12/03/74,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +27966,77903,70511,DRRD,Negron,Steven,NULL,Male,Hispanic,07/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +27966,77903,70511,DRRD,Negron,Steven,NULL,Male,Hispanic,07/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +27966,77903,70511,DRRD,Negron,Steven,NULL,Male,Hispanic,07/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +33719,35873,32821,PRETRIAL,sciacca,steven,NULL,Male,Caucasian,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.27,10,High,New,1,0 +33719,35873,32821,PRETRIAL,sciacca,steven,NULL,Male,Caucasian,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +33719,35873,32821,PRETRIAL,sciacca,steven,NULL,Male,Caucasian,09/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +66501,77911,69743,Probation,Rucker,Christopher,NULL,Male,African-American,05/11/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +66501,77911,69743,Probation,Rucker,Christopher,NULL,Male,African-American,05/11/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +66501,77911,69743,Probation,Rucker,Christopher,NULL,Male,African-American,05/11/80,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +67176,77919,70523,Probation,Barraclough,Christian,NULL,Male,Caucasian,08/14/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +67176,77919,70523,Probation,Barraclough,Christian,NULL,Male,Caucasian,08/14/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +67176,77919,70523,Probation,Barraclough,Christian,NULL,Male,Caucasian,08/14/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +17004,77935,70538,PRETRIAL,farquharson,andrew,NULL,Male,African-American,09/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +17004,77935,70538,PRETRIAL,farquharson,andrew,NULL,Male,African-American,09/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +17004,77935,70538,PRETRIAL,farquharson,andrew,NULL,Male,African-American,09/19/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67173,77914,70520,PRETRIAL,Pardue,Jacklean,NULL,Female,Caucasian,07/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +67173,77914,70520,PRETRIAL,Pardue,Jacklean,NULL,Female,Caucasian,07/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +67173,77914,70520,PRETRIAL,Pardue,Jacklean,NULL,Female,Caucasian,07/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67187,77932,70535,PRETRIAL,Arenson,Zachary,NULL,Male,Caucasian,08/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +67187,77932,70535,PRETRIAL,Arenson,Zachary,NULL,Male,Caucasian,08/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +67187,77932,70535,PRETRIAL,Arenson,Zachary,NULL,Male,Caucasian,08/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/24/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67167,77906,70514,PRETRIAL,Corker,Valerie,NULL,Female,African-American,04/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +67167,77906,70514,PRETRIAL,Corker,Valerie,NULL,Female,African-American,04/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +67167,77906,70514,PRETRIAL,Corker,Valerie,NULL,Female,African-American,04/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/24/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67196,77948,70550,PRETRIAL,EVANS,Amanda,NULL,Female,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,New,1,0 +67196,77948,70550,PRETRIAL,EVANS,Amanda,NULL,Female,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,9,High,New,1,0 +67196,77948,70550,PRETRIAL,EVANS,Amanda,NULL,Female,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67203,77956,70557,PRETRIAL,Greer,Anthony,Wayne,Male,Caucasian,09/08/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/25/14 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +67203,77956,70557,PRETRIAL,Greer,Anthony,Wayne,Male,Caucasian,09/08/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/25/14 0:00,1,Low,8,Risk of Recidivism,-2.55,1,Low,New,1,0 +67203,77956,70557,PRETRIAL,Greer,Anthony,Wayne,Male,Caucasian,09/08/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67201,77954,70555,PRETRIAL,Blunt,Sandra,Donaldson,Female,African-American,12/16/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/25/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +67201,77954,70555,PRETRIAL,Blunt,Sandra,Donaldson,Female,African-American,12/16/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/25/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +67201,77954,70555,PRETRIAL,Blunt,Sandra,Donaldson,Female,African-American,12/16/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,10/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +67197,77950,70551,PRETRIAL,MALIN,DANIELLE,MICHELE,Female,Caucasian,05/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.36,7,Medium,New,1,0 +67197,77950,70551,PRETRIAL,MALIN,DANIELLE,MICHELE,Female,Caucasian,05/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,10,High,New,1,0 +67197,77950,70551,PRETRIAL,MALIN,DANIELLE,MICHELE,Female,Caucasian,05/08/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67199,77952,70553,PRETRIAL,Alexander,Rodney,Darnell,Male,African-American,10/21/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +67199,77952,70553,PRETRIAL,Alexander,Rodney,Darnell,Male,African-American,10/21/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +67199,77952,70553,PRETRIAL,Alexander,Rodney,Darnell,Male,African-American,10/21/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67192,77945,70547,PRETRIAL,OCHOA,OSCAR,NULL,Male,Hispanic,06/17/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +67192,77945,70547,PRETRIAL,OCHOA,OSCAR,NULL,Male,Hispanic,06/17/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +67192,77945,70547,PRETRIAL,OCHOA,OSCAR,NULL,Male,Hispanic,06/17/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67193,77946,70548,PRETRIAL,JOSEPJH,DONNA,MARIE,Female,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +67193,77946,70548,PRETRIAL,JOSEPJH,DONNA,MARIE,Female,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,1,Low,8,Risk of Recidivism,-1.09,3,Low,New,1,0 +67193,77946,70548,PRETRIAL,JOSEPJH,DONNA,MARIE,Female,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67198,77951,70552,PRETRIAL,Saunders,Steven,NULL,Male,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +67198,77951,70552,PRETRIAL,Saunders,Steven,NULL,Male,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +67198,77951,70552,PRETRIAL,Saunders,Steven,NULL,Male,African-American,07/06/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +67202,77955,70556,PRETRIAL,Frazier,Dominick,Clanard,Male,African-American,08/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +67202,77955,70556,PRETRIAL,Frazier,Dominick,Clanard,Male,African-American,08/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +67202,77955,70556,PRETRIAL,Frazier,Dominick,Clanard,Male,African-American,08/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67194,77947,70549,PRETRIAL,ZORRILA,HARLEN,A,Male,Caucasian,09/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,2,Medium,7,Risk of Violence,-2.58,2,Low,New,1,0 +67194,77947,70549,PRETRIAL,ZORRILA,HARLEN,A,Male,Caucasian,09/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +67194,77947,70549,PRETRIAL,ZORRILA,HARLEN,A,Male,Caucasian,09/30/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +61192,77949,63709,PRETRIAL,Dominguez,Eric,NULL,Male,Other,02/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,2,Medium,7,Risk of Violence,-2.88,2,Low,Copy,1,0 +61192,77949,63709,PRETRIAL,Dominguez,Eric,NULL,Male,Other,02/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,Copy,1,0 +61192,77949,63709,PRETRIAL,Dominguez,Eric,NULL,Male,Other,02/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +67204,77957,70558,PRETRIAL,StFort,Gregory,NULL,Male,African-American,05/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,4,High,7,Risk of Violence,-1.1,8,High,New,1,0 +67204,77957,70558,PRETRIAL,StFort,Gregory,NULL,Male,African-American,05/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,4,High,8,Risk of Recidivism,0.45,9,High,New,1,0 +67204,77957,70558,PRETRIAL,StFort,Gregory,NULL,Male,African-American,05/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/25/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67211,77965,70566,PRETRIAL,TALBOT,JOHN,D,Male,Caucasian,04/02/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +67211,77965,70566,PRETRIAL,TALBOT,JOHN,D,Male,Caucasian,04/02/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +67211,77965,70566,PRETRIAL,TALBOT,JOHN,D,Male,Caucasian,04/02/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67209,77962,70563,PRETRIAL,CUMMINGS,QUANNESHIA,SHAKEILA,Female,African-American,12/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +67209,77962,70563,PRETRIAL,CUMMINGS,QUANNESHIA,SHAKEILA,Female,African-American,12/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +67209,77962,70563,PRETRIAL,CUMMINGS,QUANNESHIA,SHAKEILA,Female,African-American,12/25/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +15747,77970,15072,PRETRIAL,mccloud,shannon,NULL,Male,African-American,08/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,2,Medium,7,Risk of Violence,-2.85,2,Low,Copy,1,0 +15747,77970,15072,PRETRIAL,mccloud,shannon,NULL,Male,African-American,08/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,Copy,1,0 +15747,77970,15072,PRETRIAL,mccloud,shannon,NULL,Male,African-American,08/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +67207,77960,70561,PRETRIAL,Bueso,Daniel,Augusto,Male,Hispanic,09/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/26/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +67207,77960,70561,PRETRIAL,Bueso,Daniel,Augusto,Male,Hispanic,09/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/26/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +67207,77960,70561,PRETRIAL,Bueso,Daniel,Augusto,Male,Hispanic,09/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67213,77967,70568,PRETRIAL,Zunno,Daniel,NULL,Male,Caucasian,08/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +67213,77967,70568,PRETRIAL,Zunno,Daniel,NULL,Male,Caucasian,08/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +67213,77967,70568,PRETRIAL,Zunno,Daniel,NULL,Male,Caucasian,08/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67216,77972,70571,PRETRIAL,Reyes,Hilvin,NULL,Male,Hispanic,11/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/26/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +67216,77972,70571,PRETRIAL,Reyes,Hilvin,NULL,Male,Hispanic,11/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/26/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +67216,77972,70571,PRETRIAL,Reyes,Hilvin,NULL,Male,Hispanic,11/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67212,77966,70567,PRETRIAL,REES,ROBERT,LAWRENCE,Male,Caucasian,05/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +67212,77966,70567,PRETRIAL,REES,ROBERT,LAWRENCE,Male,Caucasian,05/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +67212,77966,70567,PRETRIAL,REES,ROBERT,LAWRENCE,Male,Caucasian,05/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67210,77964,70565,PRETRIAL,Jackson,Dave,NULL,Male,Other,09/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +67210,77964,70565,PRETRIAL,Jackson,Dave,NULL,Male,Other,09/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,8,Risk of Recidivism,-1.68,1,Low,New,1,0 +67210,77964,70565,PRETRIAL,Jackson,Dave,NULL,Male,Other,09/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +46327,77968,46723,PRETRIAL,Battle,Antonio,NULL,Male,African-American,02/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,Copy,1,0 +46327,77968,46723,PRETRIAL,Battle,Antonio,NULL,Male,African-American,02/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,Copy,1,0 +46327,77968,46723,PRETRIAL,Battle,Antonio,NULL,Male,African-American,02/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +67215,77971,70570,PRETRIAL,Rivera,River,NULL,Male,Hispanic,04/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +67215,77971,70570,PRETRIAL,Rivera,River,NULL,Male,Hispanic,04/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +67215,77971,70570,PRETRIAL,Rivera,River,NULL,Male,Hispanic,04/16/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67214,77969,70569,PRETRIAL,Keppley,Edwin,NULL,Male,Caucasian,03/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/26/14 0:00,2,Medium,7,Risk of Violence,-3.03,1,Low,New,1,0 +67214,77969,70569,PRETRIAL,Keppley,Edwin,NULL,Male,Caucasian,03/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +67214,77969,70569,PRETRIAL,Keppley,Edwin,NULL,Male,Caucasian,03/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/26/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +67208,77961,70562,PRETRIAL,Jeanbaptiste,Everett,NULL,Male,African-American,06/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +67208,77961,70562,PRETRIAL,Jeanbaptiste,Everett,NULL,Male,African-American,06/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +67208,77961,70562,PRETRIAL,Jeanbaptiste,Everett,NULL,Male,African-American,06/09/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67219,77974,70573,PRETRIAL,JOSEPH,WILDLINE,NULL,Female,African-American,07/28/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +67219,77974,70573,PRETRIAL,JOSEPH,WILDLINE,NULL,Female,African-American,07/28/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,4,High,8,Risk of Recidivism,0.58,10,High,New,1,0 +67219,77974,70573,PRETRIAL,JOSEPH,WILDLINE,NULL,Female,African-American,07/28/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67240,78008,70602,Probation,Franetovich,Ralph,NULL,Male,Caucasian,02/21/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +67240,78008,70602,Probation,Franetovich,Ralph,NULL,Male,Caucasian,02/21/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +67240,78008,70602,Probation,Franetovich,Ralph,NULL,Male,Caucasian,02/21/49,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67225,77982,70581,PRETRIAL,gray,sabrina,NULL,Female,African-American,12/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +67225,77982,70581,PRETRIAL,gray,sabrina,NULL,Female,African-American,12/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +67225,77982,70581,PRETRIAL,gray,sabrina,NULL,Female,African-American,12/19/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +59731,78000,70596,PRETRIAL,SANDERS,CURTIS,LEON,Male,African-American,03/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,4,High,7,Risk of Violence,-0.86,9,High,New,1,0 +59731,78000,70596,PRETRIAL,SANDERS,CURTIS,LEON,Male,African-American,03/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +59731,78000,70596,PRETRIAL,SANDERS,CURTIS,LEON,Male,African-American,03/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67237,78003,70597,Probation,Brown,Mikaela,NULL,Female,Hispanic,07/19/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +67237,78003,70597,Probation,Brown,Mikaela,NULL,Female,Hispanic,07/19/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +67237,78003,70597,Probation,Brown,Mikaela,NULL,Female,Hispanic,07/19/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +64624,78005,70599,PRETRIAL,MILLER,TRAVIS,DEMALE,Male,African-American,08/30/82,17,All Scales,Intake,English,Other,Jail Inmate,Married,10/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,New,1,0 +64624,78005,70599,PRETRIAL,MILLER,TRAVIS,DEMALE,Male,African-American,08/30/82,17,All Scales,Intake,English,Other,Jail Inmate,Married,10/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,8,High,New,1,0 +64624,78005,70599,PRETRIAL,MILLER,TRAVIS,DEMALE,Male,African-American,08/30/82,17,All Scales,Intake,English,Other,Jail Inmate,Married,10/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +56504,78019,70613,PRETRIAL,Rapone,Peter,Anthony,Male,Caucasian,12/10/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +56504,78019,70613,PRETRIAL,Rapone,Peter,Anthony,Male,Caucasian,12/10/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +56504,78019,70613,PRETRIAL,Rapone,Peter,Anthony,Male,Caucasian,12/10/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67227,77984,70583,PRETRIAL,Gonzalez,Cesar,NULL,Male,Caucasian,10/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +67227,77984,70583,PRETRIAL,Gonzalez,Cesar,NULL,Male,Caucasian,10/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +67227,77984,70583,PRETRIAL,Gonzalez,Cesar,NULL,Male,Caucasian,10/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,10/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54573,77998,70594,PRETRIAL,CONROY,DEBORAH,A,Female,Caucasian,09/05/62,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/27/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +54573,77998,70594,PRETRIAL,CONROY,DEBORAH,A,Female,Caucasian,09/05/62,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/27/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +54573,77998,70594,PRETRIAL,CONROY,DEBORAH,A,Female,Caucasian,09/05/62,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +19645,77990,70257,PRETRIAL,PULIDO,JEREMY,BENJAMIN,Male,Caucasian,03/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,Copy,1,0 +19645,77990,70257,PRETRIAL,PULIDO,JEREMY,BENJAMIN,Male,Caucasian,03/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-0.41,5,Medium,Copy,1,0 +19645,77990,70257,PRETRIAL,PULIDO,JEREMY,BENJAMIN,Male,Caucasian,03/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +67229,77992,70589,Probation,albro,Joshua,Anthony,Male,Caucasian,09/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,2,Medium,7,Risk of Violence,-2.82,2,Low,New,1,0 +67229,77992,70589,Probation,albro,Joshua,Anthony,Male,Caucasian,09/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +67229,77992,70589,Probation,albro,Joshua,Anthony,Male,Caucasian,09/27/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67221,77977,70576,PRETRIAL,MartinezMorales,Lydia,Luz,Female,Hispanic,09/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +67221,77977,70576,PRETRIAL,MartinezMorales,Lydia,Luz,Female,Hispanic,09/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +67221,77977,70576,PRETRIAL,MartinezMorales,Lydia,Luz,Female,Hispanic,09/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67243,78011,70605,PRETRIAL,PLETCHER,PAUL,NULL,Male,Caucasian,02/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +67243,78011,70605,PRETRIAL,PLETCHER,PAUL,NULL,Male,Caucasian,02/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +67243,78011,70605,PRETRIAL,PLETCHER,PAUL,NULL,Male,Caucasian,02/04/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67245,78013,70607,Probation,MONTALVA FERRANDO,FIORELLA,NULL,Female,Hispanic,10/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +67245,78013,70607,Probation,MONTALVA FERRANDO,FIORELLA,NULL,Female,Hispanic,10/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +67245,78013,70607,Probation,MONTALVA FERRANDO,FIORELLA,NULL,Female,Hispanic,10/14/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67228,77985,70584,PRETRIAL,Grijalva,Edwin,NULL,Male,Hispanic,08/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +67228,77985,70584,PRETRIAL,Grijalva,Edwin,NULL,Male,Hispanic,08/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +67228,77985,70584,PRETRIAL,Grijalva,Edwin,NULL,Male,Hispanic,08/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +52433,77975,70574,PRETRIAL,Tharpe,Secunda,NULL,Female,African-American,06/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,7,Risk of Violence,-2.81,2,Low,New,1,0 +52433,77975,70574,PRETRIAL,Tharpe,Secunda,NULL,Female,African-American,06/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +52433,77975,70574,PRETRIAL,Tharpe,Secunda,NULL,Female,African-American,06/30/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,18,Risk of Failure to Appear,27,8,High,New,1,0 +56793,77989,70587,PRETRIAL,Rodriquez,Osvaldo,NULL,Male,Hispanic,03/28/57,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/27/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +56793,77989,70587,PRETRIAL,Rodriquez,Osvaldo,NULL,Male,Hispanic,03/28/57,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/27/14 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +56793,77989,70587,PRETRIAL,Rodriquez,Osvaldo,NULL,Male,Hispanic,03/28/57,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +36600,78001,53131,PRETRIAL,Rhone,Derryel,NULL,Male,African-American,02/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,Copy,1,0 +36600,78001,53131,PRETRIAL,Rhone,Derryel,NULL,Male,African-American,02/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,Copy,1,0 +36600,78001,53131,PRETRIAL,Rhone,Derryel,NULL,Male,African-American,02/18/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +67238,78006,70600,PRETRIAL,Joseph,Steve,NULL,Male,African-American,10/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +67238,78006,70600,PRETRIAL,Joseph,Steve,NULL,Male,African-American,10/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +67238,78006,70600,PRETRIAL,Joseph,Steve,NULL,Male,African-American,10/31/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67224,77980,70579,PRETRIAL,Ross,Diamond,NULL,Female,African-American,06/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/14 0:00,2,Medium,7,Risk of Violence,-1.78,5,Medium,New,1,0 +67224,77980,70579,PRETRIAL,Ross,Diamond,NULL,Female,African-American,06/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +67224,77980,70579,PRETRIAL,Ross,Diamond,NULL,Female,African-American,06/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67242,78010,70604,Probation,hoose,robert,NULL,Male,Caucasian,10/24/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/27/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +67242,78010,70604,Probation,hoose,robert,NULL,Male,Caucasian,10/24/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +67242,78010,70604,Probation,hoose,robert,NULL,Male,Caucasian,10/24/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67218,77973,70572,PRETRIAL,SMITH,JEFFREY,O,Male,African-American,11/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +67218,77973,70572,PRETRIAL,SMITH,JEFFREY,O,Male,African-American,11/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +67218,77973,70572,PRETRIAL,SMITH,JEFFREY,O,Male,African-American,11/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66517,77987,69765,PRETRIAL,rodriguezmulato,alexander,Daniel,Male,Hispanic,11/14/89,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,10/27/14 0:00,4,High,7,Risk of Violence,-0.2,10,High,New,1,0 +66517,77987,69765,PRETRIAL,rodriguezmulato,alexander,Daniel,Male,Hispanic,11/14/89,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,10/27/14 0:00,4,High,8,Risk of Recidivism,1.02,10,High,New,1,0 +66517,77987,69765,PRETRIAL,rodriguezmulato,alexander,Daniel,Male,Hispanic,11/14/89,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,10/27/14 0:00,4,High,18,Risk of Failure to Appear,29,7,Medium,New,1,0 +67233,77994,70590,Probation,Tejada,Nicolas,NULL,Male,Hispanic,05/18/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +67233,77994,70590,Probation,Tejada,Nicolas,NULL,Male,Hispanic,05/18/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +67233,77994,70590,Probation,Tejada,Nicolas,NULL,Male,Hispanic,05/18/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67235,77996,70592,Probation,Sotomayor,Kathi,NULL,Female,Caucasian,01/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/27/14 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +67235,77996,70592,Probation,Sotomayor,Kathi,NULL,Female,Caucasian,01/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/27/14 0:00,1,Low,8,Risk of Recidivism,-2.34,1,Low,New,1,0 +67235,77996,70592,Probation,Sotomayor,Kathi,NULL,Female,Caucasian,01/15/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67246,78015,70609,Probation,zuech,john,NULL,Male,Caucasian,07/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/27/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +67246,78015,70609,Probation,zuech,john,NULL,Male,Caucasian,07/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +67246,78015,70609,Probation,zuech,john,NULL,Male,Caucasian,07/22/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67248,78017,70611,Probation,PALACIO,CARLOS,ANTONIO,Male,Hispanic,07/15/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +67248,78017,70611,Probation,PALACIO,CARLOS,ANTONIO,Male,Hispanic,07/15/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +67248,78017,70611,Probation,PALACIO,CARLOS,ANTONIO,Male,Hispanic,07/15/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67249,78018,70612,Probation,BLOCK,HAGAN,NULL,Male,Caucasian,10/10/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +67249,78018,70612,Probation,BLOCK,HAGAN,NULL,Male,Caucasian,10/10/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-0.43,4,Low,New,1,0 +67249,78018,70612,Probation,BLOCK,HAGAN,NULL,Male,Caucasian,10/10/82,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,21,3,Low,New,1,0 +15891,78014,70608,PRETRIAL,Hicks,Jeremy,NULL,Male,African-American,05/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +15891,78014,70608,PRETRIAL,Hicks,Jeremy,NULL,Male,African-American,05/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +15891,78014,70608,PRETRIAL,Hicks,Jeremy,NULL,Male,African-American,05/07/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67220,77976,70575,PRETRIAL,Wright,James,Douglas,Male,African-American,02/01/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +67220,77976,70575,PRETRIAL,Wright,James,Douglas,Male,African-American,02/01/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/14 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +67220,77976,70575,PRETRIAL,Wright,James,Douglas,Male,African-American,02/01/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +64597,77993,67632,PRETRIAL,Porter,William,NULL,Male,African-American,10/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,Copy,1,0 +64597,77993,67632,PRETRIAL,Porter,William,NULL,Male,African-American,10/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +64597,77993,67632,PRETRIAL,Porter,William,NULL,Male,African-American,10/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +63025,77997,70593,Probation,Samaroo,Andrew,Daniel,Male,African-American,12/11/92,17,All Scales,Intake,English,Other,Probation,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +63025,77997,70593,Probation,Samaroo,Andrew,Daniel,Male,African-American,12/11/92,17,All Scales,Intake,English,Other,Probation,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +63025,77997,70593,Probation,Samaroo,Andrew,Daniel,Male,African-American,12/11/92,17,All Scales,Intake,English,Other,Probation,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,23,4,Low,New,1,0 +67223,77979,70578,PRETRIAL,MARTIN,KEOSHIA,DEMARIA,Female,African-American,12/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,7,Risk of Violence,-1.48,7,Medium,New,1,0 +67223,77979,70578,PRETRIAL,MARTIN,KEOSHIA,DEMARIA,Female,African-American,12/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +67223,77979,70578,PRETRIAL,MARTIN,KEOSHIA,DEMARIA,Female,African-American,12/30/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +12622,77981,70580,PRETRIAL,CHAMBERS,FABIAN,ANTWAUN,Male,African-American,07/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,New,1,0 +12622,77981,70580,PRETRIAL,CHAMBERS,FABIAN,ANTWAUN,Male,African-American,07/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,4,High,8,Risk of Recidivism,0.18,8,High,New,1,0 +12622,77981,70580,PRETRIAL,CHAMBERS,FABIAN,ANTWAUN,Male,African-American,07/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +51927,78009,70603,Probation,MORONY,JEFFREY,SCOTT,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +51927,78009,70603,Probation,MORONY,JEFFREY,SCOTT,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +51927,78009,70603,Probation,MORONY,JEFFREY,SCOTT,Male,Caucasian,10/09/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67247,78016,70610,Probation,Sepulveda,dora,NULL,Female,Hispanic,08/24/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/27/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +67247,78016,70610,Probation,Sepulveda,dora,NULL,Female,Hispanic,08/24/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +67247,78016,70610,Probation,Sepulveda,dora,NULL,Female,Hispanic,08/24/66,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67231,77988,70586,PRETRIAL,Reyes,Simone,NULL,Female,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +67231,77988,70586,PRETRIAL,Reyes,Simone,NULL,Female,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-0.78,5,Medium,New,1,0 +67231,77988,70586,PRETRIAL,Reyes,Simone,NULL,Female,Hispanic,03/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61459,78002,64023,Probation,Bridger,Roswell,Carter,Male,Caucasian,09/09/52,17,All Scales,Intake,English,Conditional Release,Probation,Married,10/27/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +61459,78002,64023,Probation,Bridger,Roswell,Carter,Male,Caucasian,09/09/52,17,All Scales,Intake,English,Conditional Release,Probation,Married,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +61459,78002,64023,Probation,Bridger,Roswell,Carter,Male,Caucasian,09/09/52,17,All Scales,Intake,English,Conditional Release,Probation,Married,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,16,1,Low,New,1,0 +67232,77991,70588,PRETRIAL,Miles,Natalie,NULL,Female,Caucasian,06/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +67232,77991,70588,PRETRIAL,Miles,Natalie,NULL,Female,Caucasian,06/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.62,2,Low,New,1,0 +67232,77991,70588,PRETRIAL,Miles,Natalie,NULL,Female,Caucasian,06/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67226,77983,70582,PRETRIAL,Freeman,Daniel,NULL,Male,African-American,05/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,New,1,0 +67226,77983,70582,PRETRIAL,Freeman,Daniel,NULL,Male,African-American,05/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +67226,77983,70582,PRETRIAL,Freeman,Daniel,NULL,Male,African-American,05/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67236,77999,70595,Probation,WILLIAMS,MARIO,NULL,Male,Hispanic,10/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +67236,77999,70595,Probation,WILLIAMS,MARIO,NULL,Male,Hispanic,10/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +67236,77999,70595,Probation,WILLIAMS,MARIO,NULL,Male,Hispanic,10/25/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67222,77978,70577,PRETRIAL,Watts,Jeremy,NULL,Male,African-American,03/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +67222,77978,70577,PRETRIAL,Watts,Jeremy,NULL,Male,African-American,03/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +67222,77978,70577,PRETRIAL,Watts,Jeremy,NULL,Male,African-American,03/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67244,78012,70606,Probation,Salese,Mary,NULL,Female,Caucasian,11/18/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/27/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +67244,78012,70606,Probation,Salese,Mary,NULL,Female,Caucasian,11/18/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +67244,78012,70606,Probation,Salese,Mary,NULL,Female,Caucasian,11/18/59,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67239,78007,70601,Probation,HERON,CHRISTOFF,NULL,Male,African-American,04/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.81,5,Medium,New,1,0 +67239,78007,70601,Probation,HERON,CHRISTOFF,NULL,Male,African-American,04/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +67239,78007,70601,Probation,HERON,CHRISTOFF,NULL,Male,African-American,04/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67230,77986,70585,Probation,cauvin,elta,NULL,Female,African-American,09/05/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/27/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +67230,77986,70585,Probation,cauvin,elta,NULL,Female,African-American,09/05/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/27/14 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +67230,77986,70585,Probation,cauvin,elta,NULL,Female,African-American,09/05/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +25001,78004,70598,Probation,STANLEY,VINCENT,RENARD,Male,African-American,06/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +25001,78004,70598,Probation,STANLEY,VINCENT,RENARD,Male,African-American,06/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +25001,78004,70598,Probation,STANLEY,VINCENT,RENARD,Male,African-American,06/29/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/27/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +64597,74660,67632,PRETRIAL,Porter,William,NULL,Male,African-American,10/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +64597,74660,67632,PRETRIAL,Porter,William,NULL,Male,African-American,10/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +64597,74660,67632,PRETRIAL,Porter,William,NULL,Male,African-American,10/10/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/27/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67274,78054,70644,Probation,JOSEPH,LOUIS,NULL,Male,African-American,09/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +67274,78054,70644,Probation,JOSEPH,LOUIS,NULL,Male,African-American,09/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +67274,78054,70644,Probation,JOSEPH,LOUIS,NULL,Male,African-American,09/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67255,78025,70619,PRETRIAL,INGLIS,BARBARA,NULL,Female,Caucasian,06/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +67255,78025,70619,PRETRIAL,INGLIS,BARBARA,NULL,Female,Caucasian,06/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +67255,78025,70619,PRETRIAL,INGLIS,BARBARA,NULL,Female,Caucasian,06/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +66876,78046,70171,PRETRIAL,Pippen,Charles,NULL,Male,African-American,10/04/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,Copy,1,0 +66876,78046,70171,PRETRIAL,Pippen,Charles,NULL,Male,African-American,10/04/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,Copy,1,0 +66876,78046,70171,PRETRIAL,Pippen,Charles,NULL,Male,African-American,10/04/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +67271,78049,70640,PRETRIAL,german,valeria,NULL,Female,Caucasian,09/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +67271,78049,70640,PRETRIAL,german,valeria,NULL,Female,Caucasian,09/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,1,Low,8,Risk of Recidivism,-1.65,2,Low,New,1,0 +67271,78049,70640,PRETRIAL,german,valeria,NULL,Female,Caucasian,09/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +53105,78056,55265,Probation,fowks,kurt,NULL,Male,Caucasian,02/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,7,Risk of Violence,-1.16,8,High,Copy,1,0 +53105,78056,55265,Probation,fowks,kurt,NULL,Male,Caucasian,02/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,8,Risk of Recidivism,0.09,8,High,Copy,1,0 +53105,78056,55265,Probation,fowks,kurt,NULL,Male,Caucasian,02/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +67256,78028,70622,PRETRIAL,Harris,Damian,NULL,Male,African-American,06/30/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +67256,78028,70622,PRETRIAL,Harris,Damian,NULL,Male,African-American,06/30/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +67256,78028,70622,PRETRIAL,Harris,Damian,NULL,Male,African-American,06/30/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +2171,78041,70634,PRETRIAL,MCLAWRENCE,DAVID,SAMUEL,Male,African-American,11/24/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/14 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +2171,78041,70634,PRETRIAL,MCLAWRENCE,DAVID,SAMUEL,Male,African-American,11/24/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +2171,78041,70634,PRETRIAL,MCLAWRENCE,DAVID,SAMUEL,Male,African-American,11/24/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67270,78048,70639,Probation,Macdonald,Hamish,NULL,Male,Caucasian,10/18/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/28/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +67270,78048,70639,Probation,Macdonald,Hamish,NULL,Male,Caucasian,10/18/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/28/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +67270,78048,70639,Probation,Macdonald,Hamish,NULL,Male,Caucasian,10/18/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67251,78020,70614,PRETRIAL,Caraballo,Pamela,Caroline,Female,Caucasian,12/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +67251,78020,70614,PRETRIAL,Caraballo,Pamela,Caroline,Female,Caucasian,12/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +67251,78020,70614,PRETRIAL,Caraballo,Pamela,Caroline,Female,Caucasian,12/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67264,78037,70630,Probation,Rivadeneira,Jack,NULL,Male,Hispanic,03/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +67264,78037,70630,Probation,Rivadeneira,Jack,NULL,Male,Hispanic,03/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +67264,78037,70630,Probation,Rivadeneira,Jack,NULL,Male,Hispanic,03/07/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67253,78023,70617,PRETRIAL,Mosco,Zachary,Daniel,Male,Caucasian,09/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,2,Medium,7,Risk of Violence,-1.93,5,Medium,New,1,0 +67253,78023,70617,PRETRIAL,Mosco,Zachary,Daniel,Male,Caucasian,09/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +67253,78023,70617,PRETRIAL,Mosco,Zachary,Daniel,Male,Caucasian,09/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +11263,78058,70646,PRETRIAL,robinson,rayson,NULL,Male,African-American,09/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +11263,78058,70646,PRETRIAL,robinson,rayson,NULL,Male,African-American,09/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +11263,78058,70646,PRETRIAL,robinson,rayson,NULL,Male,African-American,09/17/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +60648,78060,70648,PRETRIAL,Marcellus,Nickson,NULL,Male,African-American,07/11/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,4,High,7,Risk of Violence,-0.44,10,High,New,1,0 +60648,78060,70648,PRETRIAL,Marcellus,Nickson,NULL,Male,African-American,07/11/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,4,High,8,Risk of Recidivism,0.92,10,High,New,1,0 +60648,78060,70648,PRETRIAL,Marcellus,Nickson,NULL,Male,African-American,07/11/96,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67268,78044,70637,PRETRIAL,GIERBOLINI,JOMAR,NULL,Male,Caucasian,10/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.38,7,Medium,New,1,0 +67268,78044,70637,PRETRIAL,GIERBOLINI,JOMAR,NULL,Male,Caucasian,10/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.08,10,High,New,1,0 +67268,78044,70637,PRETRIAL,GIERBOLINI,JOMAR,NULL,Male,Caucasian,10/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +10828,41429,10351,PRETRIAL,MARTIN,JUSTIN,DWAYNE,Male,African-American,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,7,Risk of Violence,-0.09,10,High,Copy,1,0 +10828,41429,10351,PRETRIAL,MARTIN,JUSTIN,DWAYNE,Male,African-American,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,8,Risk of Recidivism,1.08,10,High,Copy,1,0 +10828,41429,10351,PRETRIAL,MARTIN,JUSTIN,DWAYNE,Male,African-American,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +67259,78032,70625,Probation,Brook,Shambria,NULL,Female,African-American,08/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +67259,78032,70625,Probation,Brook,Shambria,NULL,Female,African-American,08/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +67259,78032,70625,Probation,Brook,Shambria,NULL,Female,African-American,08/18/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67266,78039,70632,Probation,Ferris,Pearl,NULL,Female,African-American,11/05/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/28/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +67266,78039,70632,Probation,Ferris,Pearl,NULL,Female,African-American,11/05/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/28/14 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +67266,78039,70632,Probation,Ferris,Pearl,NULL,Female,African-American,11/05/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +67262,78035,70628,PRETRIAL,Wilson,Napoleon,NULL,Male,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +67262,78035,70628,PRETRIAL,Wilson,Napoleon,NULL,Male,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +67262,78035,70628,PRETRIAL,Wilson,Napoleon,NULL,Male,African-American,08/31/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67254,78024,70618,PRETRIAL,LAURENT,ALAIN,NULL,Male,African-American,05/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/28/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +67254,78024,70618,PRETRIAL,LAURENT,ALAIN,NULL,Male,African-American,05/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/28/14 0:00,1,Low,8,Risk of Recidivism,-1.89,1,Low,New,1,0 +67254,78024,70618,PRETRIAL,LAURENT,ALAIN,NULL,Male,African-American,05/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67265,78038,70631,Probation,MINTO-VESPIA,CORRINE,NULL,Female,African-American,02/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +67265,78038,70631,Probation,MINTO-VESPIA,CORRINE,NULL,Female,African-American,02/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +67265,78038,70631,Probation,MINTO-VESPIA,CORRINE,NULL,Female,African-American,02/28/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67275,78059,70647,Probation,salow,Alexander,NULL,Male,Hispanic,10/09/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/14 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +67275,78059,70647,Probation,salow,Alexander,NULL,Male,Hispanic,10/09/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/14 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +67275,78059,70647,Probation,salow,Alexander,NULL,Male,Hispanic,10/09/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +49014,78027,70621,PRETRIAL,Perry,Willie,NULL,Male,African-American,01/03/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +49014,78027,70621,PRETRIAL,Perry,Willie,NULL,Male,African-American,01/03/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +49014,78027,70621,PRETRIAL,Perry,Willie,NULL,Male,African-American,01/03/52,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +18165,78031,17431,PRETRIAL,Exceus,Victpr,NULL,Male,African-American,09/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/28/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,Copy,1,0 +18165,78031,17431,PRETRIAL,Exceus,Victpr,NULL,Male,African-American,09/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/28/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,Copy,1,0 +18165,78031,17431,PRETRIAL,Exceus,Victpr,NULL,Male,African-American,09/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +57311,78040,70633,PRETRIAL,Posada,Carlos,NULL,Male,Hispanic,05/05/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +57311,78040,70633,PRETRIAL,Posada,Carlos,NULL,Male,Hispanic,05/05/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +57311,78040,70633,PRETRIAL,Posada,Carlos,NULL,Male,Hispanic,05/05/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +46170,78043,70636,Probation,biggs,cheryl,NULL,Female,Caucasian,12/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +46170,78043,70636,Probation,biggs,cheryl,NULL,Female,Caucasian,12/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +46170,78043,70636,Probation,biggs,cheryl,NULL,Female,Caucasian,12/01/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +10828,78057,10351,PRETRIAL,MARTIN,JUSTIN,DWAYNE,Male,African-American,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,7,Risk of Violence,-0.39,10,High,Copy,1,0 +10828,78057,10351,PRETRIAL,MARTIN,JUSTIN,DWAYNE,Male,African-American,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,8,Risk of Recidivism,0.95,10,High,Copy,1,0 +10828,78057,10351,PRETRIAL,MARTIN,JUSTIN,DWAYNE,Male,African-American,08/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +48799,78022,70616,PRETRIAL,COLEBROOKE,KEVIN,NULL,Male,African-American,08/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +48799,78022,70616,PRETRIAL,COLEBROOKE,KEVIN,NULL,Male,African-American,08/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +48799,78022,70616,PRETRIAL,COLEBROOKE,KEVIN,NULL,Male,African-American,08/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67263,78036,70629,Probation,Chen,Frank,Edward,Male,Hispanic,05/31/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/28/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +67263,78036,70629,Probation,Chen,Frank,Edward,Male,Hispanic,05/31/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/28/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +67263,78036,70629,Probation,Chen,Frank,Edward,Male,Hispanic,05/31/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67269,78047,70638,PRETRIAL,PUCASTRO,BALTAZAR,NULL,Male,Asian,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +67269,78047,70638,PRETRIAL,PUCASTRO,BALTAZAR,NULL,Male,Asian,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +67269,78047,70638,PRETRIAL,PUCASTRO,BALTAZAR,NULL,Male,Asian,10/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67165,78026,70620,PRETRIAL,Edwards,Jerry,NULL,Male,African-American,07/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,7,Risk of Violence,-0.58,10,High,New,1,0 +67165,78026,70620,PRETRIAL,Edwards,Jerry,NULL,Male,African-American,07/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +67165,78026,70620,PRETRIAL,Edwards,Jerry,NULL,Male,African-American,07/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67261,78034,70627,Probation,ziol,thomas,NULL,Male,Caucasian,04/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +67261,78034,70627,Probation,ziol,thomas,NULL,Male,Caucasian,04/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +67261,78034,70627,Probation,ziol,thomas,NULL,Male,Caucasian,04/04/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +1343,78055,70645,Probation,Lovett,Reginald,NULL,Male,African-American,12/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,4,High,7,Risk of Violence,-1.15,8,High,New,1,0 +1343,78055,70645,Probation,Lovett,Reginald,NULL,Male,African-American,12/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,4,High,8,Risk of Recidivism,0.38,9,High,New,1,0 +1343,78055,70645,Probation,Lovett,Reginald,NULL,Male,African-American,12/28/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/28/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +67252,78021,70615,PRETRIAL,Gallo,Michael,NULL,Male,Caucasian,05/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,7,Risk of Violence,-0.53,10,High,New,1,0 +67252,78021,70615,PRETRIAL,Gallo,Michael,NULL,Male,Caucasian,05/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,8,Risk of Recidivism,0.44,9,High,New,1,0 +67252,78021,70615,PRETRIAL,Gallo,Michael,NULL,Male,Caucasian,05/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/28/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67272,78050,70641,PRETRIAL,Austin,Darryl,NULL,Male,African-American,08/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/14 0:00,4,High,7,Risk of Violence,-0.41,10,High,New,1,0 +67272,78050,70641,PRETRIAL,Austin,Darryl,NULL,Male,African-American,08/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/14 0:00,4,High,8,Risk of Recidivism,0.57,9,High,New,1,0 +67272,78050,70641,PRETRIAL,Austin,Darryl,NULL,Male,African-American,08/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/28/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67257,78029,70623,PRETRIAL,Lugo,Gregory,Lance,Male,Caucasian,01/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/28/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +67257,78029,70623,PRETRIAL,Lugo,Gregory,Lance,Male,Caucasian,01/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/28/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +67257,78029,70623,PRETRIAL,Lugo,Gregory,Lance,Male,Caucasian,01/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/28/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67277,78063,70651,PRETRIAL,MCNAIR,SHARITA,NULL,Female,African-American,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +67277,78063,70651,PRETRIAL,MCNAIR,SHARITA,NULL,Female,African-American,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +67277,78063,70651,PRETRIAL,MCNAIR,SHARITA,NULL,Female,African-American,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67333,78144,70722,Probation,Beas-Gonzalez,SARAI,NULL,Female,Hispanic,04/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +67333,78144,70722,Probation,Beas-Gonzalez,SARAI,NULL,Female,Hispanic,04/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +67333,78144,70722,Probation,Beas-Gonzalez,SARAI,NULL,Female,Hispanic,04/24/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +27906,78076,27004,PRETRIAL,BETSY,HARRIS,LEE,Female,African-American,02/28/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.14,4,Low,Copy,1,0 +27906,78076,27004,PRETRIAL,BETSY,HARRIS,LEE,Female,African-American,02/28/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,9,High,Copy,1,0 +27906,78076,27004,PRETRIAL,BETSY,HARRIS,LEE,Female,African-American,02/28/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +67281,78068,70656,PRETRIAL,Brignoni,Carlos,NULL,Male,African-American,10/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,New,1,0 +67281,78068,70656,PRETRIAL,Brignoni,Carlos,NULL,Male,African-American,10/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,9,High,New,1,0 +67281,78068,70656,PRETRIAL,Brignoni,Carlos,NULL,Male,African-American,10/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +63405,78071,66254,PRETRIAL,Brown,Charles,NULL,Male,Caucasian,10/22/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,Copy,1,0 +63405,78071,66254,PRETRIAL,Brown,Charles,NULL,Male,Caucasian,10/22/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,Copy,1,0 +63405,78071,66254,PRETRIAL,Brown,Charles,NULL,Male,Caucasian,10/22/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +67295,78089,70673,Probation,Rodriguez,Dennis,NULL,Male,Hispanic,10/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,2,Medium,7,Risk of Violence,-3.08,1,Low,New,1,0 +67295,78089,70673,Probation,Rodriguez,Dennis,NULL,Male,Hispanic,10/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +67295,78089,70673,Probation,Rodriguez,Dennis,NULL,Male,Hispanic,10/08/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67291,78084,70668,PRETRIAL,Lombard,Cindy,NULL,Female,Caucasian,12/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,10/29/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +67291,78084,70668,PRETRIAL,Lombard,Cindy,NULL,Female,Caucasian,12/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,10/29/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +67291,78084,70668,PRETRIAL,Lombard,Cindy,NULL,Female,Caucasian,12/10/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +18440,78082,70666,PRETRIAL,TRIBBLE,PATRICIA,NULL,Female,Caucasian,05/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +18440,78082,70666,PRETRIAL,TRIBBLE,PATRICIA,NULL,Female,Caucasian,05/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +18440,78082,70666,PRETRIAL,TRIBBLE,PATRICIA,NULL,Female,Caucasian,05/10/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +1172,78066,70654,PRETRIAL,SHELL,DENARD,R,Male,African-American,06/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,4,High,7,Risk of Violence,-1.21,8,High,New,1,0 +1172,78066,70654,PRETRIAL,SHELL,DENARD,R,Male,African-American,06/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,4,High,8,Risk of Recidivism,0.16,8,High,New,1,0 +1172,78066,70654,PRETRIAL,SHELL,DENARD,R,Male,African-American,06/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67284,78073,70660,Probation,Pepper,John,NULL,Male,Caucasian,08/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/29/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +67284,78073,70660,Probation,Pepper,John,NULL,Male,Caucasian,08/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/29/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +67284,78073,70660,Probation,Pepper,John,NULL,Male,Caucasian,08/14/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67294,78087,70671,PRETRIAL,Boyd,William,NULL,Male,Caucasian,10/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +67294,78087,70671,PRETRIAL,Boyd,William,NULL,Male,Caucasian,10/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +67294,78087,70671,PRETRIAL,Boyd,William,NULL,Male,Caucasian,10/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67293,78086,70670,PRETRIAL,Keel,Douglas,NULL,Male,African-American,10/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +67293,78086,70670,PRETRIAL,Keel,Douglas,NULL,Male,African-American,10/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +67293,78086,70670,PRETRIAL,Keel,Douglas,NULL,Male,African-American,10/04/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67279,78065,70653,PRETRIAL,MUNOZ,EDGAR,MIGUEL,Male,Hispanic,11/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/29/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +67279,78065,70653,PRETRIAL,MUNOZ,EDGAR,MIGUEL,Male,Hispanic,11/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/29/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +67279,78065,70653,PRETRIAL,MUNOZ,EDGAR,MIGUEL,Male,Hispanic,11/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67285,78074,70661,Probation,Knight,Calvin,NULL,Male,African-American,02/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +67285,78074,70661,Probation,Knight,Calvin,NULL,Male,African-American,02/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,4,High,8,Risk of Recidivism,0.4,9,High,New,1,0 +67285,78074,70661,Probation,Knight,Calvin,NULL,Male,African-American,02/14/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67289,78081,70665,DRRD,Eafford,Marlese,Lashawn,Male,African-American,09/16/92,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/29/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +67289,78081,70665,DRRD,Eafford,Marlese,Lashawn,Male,African-American,09/16/92,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/29/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +67289,78081,70665,DRRD,Eafford,Marlese,Lashawn,Male,African-American,09/16/92,17,All Scales,Intake,English,Probation Violator,Probation,Single,10/29/14 0:00,2,Medium,18,Risk of Failure to Appear,19,2,Low,New,1,0 +42665,78088,70672,PRETRIAL,Garcia,Joseph,NULL,Male,Caucasian,11/05/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +42665,78088,70672,PRETRIAL,Garcia,Joseph,NULL,Male,Caucasian,11/05/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +42665,78088,70672,PRETRIAL,Garcia,Joseph,NULL,Male,Caucasian,11/05/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67282,78069,70657,PRETRIAL,ellis,jonathan,NULL,Male,Caucasian,06/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +67282,78069,70657,PRETRIAL,ellis,jonathan,NULL,Male,Caucasian,06/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,1,Low,8,Risk of Recidivism,-1.61,1,Low,New,1,0 +67282,78069,70657,PRETRIAL,ellis,jonathan,NULL,Male,Caucasian,06/29/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +53386,78070,70658,Probation,Cason,Bridgett,NULL,Female,African-American,11/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,New,1,0 +53386,78070,70658,Probation,Cason,Bridgett,NULL,Female,African-American,11/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +53386,78070,70658,Probation,Cason,Bridgett,NULL,Female,African-American,11/28/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/29/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +58207,78062,70650,PRETRIAL,Martin,Daquan,Imani,Male,African-American,11/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +58207,78062,70650,PRETRIAL,Martin,Daquan,Imani,Male,African-American,11/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +58207,78062,70650,PRETRIAL,Martin,Daquan,Imani,Male,African-American,11/22/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67290,78083,70667,Probation,Sama,Jose,NULL,Male,Hispanic,07/02/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/29/14 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +67290,78083,70667,Probation,Sama,Jose,NULL,Male,Hispanic,07/02/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +67290,78083,70667,Probation,Sama,Jose,NULL,Male,Hispanic,07/02/80,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/29/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +21521,78090,20672,PRETRIAL,HERBERT,ZEONE,NULL,Male,African-American,07/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,4,High,7,Risk of Violence,-0.9,9,High,Copy,1,0 +21521,78090,20672,PRETRIAL,HERBERT,ZEONE,NULL,Male,African-American,07/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,4,High,8,Risk of Recidivism,0.42,9,High,Copy,1,0 +21521,78090,20672,PRETRIAL,HERBERT,ZEONE,NULL,Male,African-American,07/27/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/29/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +67280,78067,70655,PRETRIAL,Mendoza,Luis,NULL,Male,Hispanic,10/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +67280,78067,70655,PRETRIAL,Mendoza,Luis,NULL,Male,Hispanic,10/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +67280,78067,70655,PRETRIAL,Mendoza,Luis,NULL,Male,Hispanic,10/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67278,78064,70652,PRETRIAL,Cohen,Maria,NULL,Female,Hispanic,06/01/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +67278,78064,70652,PRETRIAL,Cohen,Maria,NULL,Female,Hispanic,06/01/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,8,Risk of Recidivism,-1.99,1,Low,New,1,0 +67278,78064,70652,PRETRIAL,Cohen,Maria,NULL,Female,Hispanic,06/01/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67287,78075,70662,PRETRIAL,Adamson,Diamond,NULL,Female,African-American,07/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +67287,78075,70662,PRETRIAL,Adamson,Diamond,NULL,Female,African-American,07/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +67287,78075,70662,PRETRIAL,Adamson,Diamond,NULL,Female,African-American,07/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/29/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67283,78072,70659,PRETRIAL,Di Boscio,Gain,NULL,Male,Caucasian,04/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/29/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +67283,78072,70659,PRETRIAL,Di Boscio,Gain,NULL,Male,Caucasian,04/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/29/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +67283,78072,70659,PRETRIAL,Di Boscio,Gain,NULL,Male,Caucasian,04/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67292,78085,70669,Probation,Reyes,Miguel,Angel,Male,Hispanic,02/02/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/29/14 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +67292,78085,70669,Probation,Reyes,Miguel,Angel,Male,Hispanic,02/02/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/29/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +67292,78085,70669,Probation,Reyes,Miguel,Angel,Male,Hispanic,02/02/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/29/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56858,78122,70703,PRETRIAL,Bladd,Marc,Lewis,Male,Caucasian,11/13/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +56858,78122,70703,PRETRIAL,Bladd,Marc,Lewis,Male,Caucasian,11/13/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-2.23,1,Low,New,1,0 +56858,78122,70703,PRETRIAL,Bladd,Marc,Lewis,Male,Caucasian,11/13/47,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67329,78135,70715,Probation,knox,nickie,NULL,Male,African-American,12/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +67329,78135,70715,Probation,knox,nickie,NULL,Male,African-American,12/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +67329,78135,70715,Probation,knox,nickie,NULL,Male,African-American,12/16/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67297,78093,70676,PRETRIAL,Williams,Trevoy,Joseph,Male,Other,08/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.64,6,Medium,New,1,0 +67297,78093,70676,PRETRIAL,Williams,Trevoy,Joseph,Male,Other,08/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +67297,78093,70676,PRETRIAL,Williams,Trevoy,Joseph,Male,Other,08/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67326,78132,70712,Probation,FILEDS,JAMES,E,Male,African-American,11/23/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +67326,78132,70712,Probation,FILEDS,JAMES,E,Male,African-American,11/23/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +67326,78132,70712,Probation,FILEDS,JAMES,E,Male,African-American,11/23/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +46508,78101,70684,PRETRIAL,McFarlane,James,NULL,Male,Caucasian,10/22/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +46508,78101,70684,PRETRIAL,McFarlane,James,NULL,Male,Caucasian,10/22/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +46508,78101,70684,PRETRIAL,McFarlane,James,NULL,Male,Caucasian,10/22/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67305,78106,70689,PRETRIAL,SENATUS,SHARICCA,NULL,Female,African-American,06/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +67305,78106,70689,PRETRIAL,SENATUS,SHARICCA,NULL,Female,African-American,06/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +67305,78106,70689,PRETRIAL,SENATUS,SHARICCA,NULL,Female,African-American,06/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +57258,78114,70695,PRETRIAL,Blackwood,Britton,NULL,Male,African-American,05/25/94,17,All Scales,Intake,English,Pretrial,Probation,Single,10/30/14 0:00,4,High,7,Risk of Violence,-0.56,10,High,New,1,0 +57258,78114,70695,PRETRIAL,Blackwood,Britton,NULL,Male,African-American,05/25/94,17,All Scales,Intake,English,Pretrial,Probation,Single,10/30/14 0:00,4,High,8,Risk of Recidivism,0.98,10,High,New,1,0 +57258,78114,70695,PRETRIAL,Blackwood,Britton,NULL,Male,African-American,05/25/94,17,All Scales,Intake,English,Pretrial,Probation,Single,10/30/14 0:00,4,High,18,Risk of Failure to Appear,19,2,Low,New,1,0 +14844,78127,70707,PRETRIAL,BURGESS,ROBERT,NULL,Male,African-American,05/07/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.48,7,Medium,New,1,0 +14844,78127,70707,PRETRIAL,BURGESS,ROBERT,NULL,Male,African-American,05/07/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +14844,78127,70707,PRETRIAL,BURGESS,ROBERT,NULL,Male,African-American,05/07/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +67316,78119,70700,PRETRIAL,NAVEDO,EFRAIN,NULL,Male,Caucasian,08/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +67316,78119,70700,PRETRIAL,NAVEDO,EFRAIN,NULL,Male,Caucasian,08/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +67316,78119,70700,PRETRIAL,NAVEDO,EFRAIN,NULL,Male,Caucasian,08/20/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +34320,78091,70674,PRETRIAL,betancourt,gioavanni,NULL,Male,African-American,03/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.16,8,High,New,1,0 +34320,78091,70674,PRETRIAL,betancourt,gioavanni,NULL,Male,African-American,03/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +34320,78091,70674,PRETRIAL,betancourt,gioavanni,NULL,Male,African-American,03/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67301,78098,70681,PRETRIAL,Saravia,Brian,German,Male,Caucasian,09/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +67301,78098,70681,PRETRIAL,Saravia,Brian,German,Male,Caucasian,09/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +67301,78098,70681,PRETRIAL,Saravia,Brian,German,Male,Caucasian,09/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +24244,78137,70716,Probation,dampman,christopher,NULL,Female,Caucasian,04/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +24244,78137,70716,Probation,dampman,christopher,NULL,Female,Caucasian,04/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-0.63,5,Medium,New,1,0 +24244,78137,70716,Probation,dampman,christopher,NULL,Female,Caucasian,04/04/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67308,78109,70692,Probation,Morris,Leighton,NULL,Male,African-American,04/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +67308,78109,70692,Probation,Morris,Leighton,NULL,Male,African-American,04/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.81,1,Low,New,1,0 +67308,78109,70692,Probation,Morris,Leighton,NULL,Male,African-American,04/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67313,78116,70697,Probation,Allen,Tiffany,Nicole,Female,African-American,08/10/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +67313,78116,70697,Probation,Allen,Tiffany,Nicole,Female,African-American,08/10/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +67313,78116,70697,Probation,Allen,Tiffany,Nicole,Female,African-American,08/10/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +55067,78123,56851,PRETRIAL,Washington,Arthur,NULL,Male,African-American,12/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/14 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,Copy,1,0 +55067,78123,56851,PRETRIAL,Washington,Arthur,NULL,Male,African-American,12/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,Copy,1,0 +55067,78123,56851,PRETRIAL,Washington,Arthur,NULL,Male,African-American,12/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +67324,78130,70710,PRETRIAL,jenkins,zirrion,NULL,Male,African-American,06/12/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +67324,78130,70710,PRETRIAL,jenkins,zirrion,NULL,Male,African-American,06/12/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.8,10,High,New,1,0 +67324,78130,70710,PRETRIAL,jenkins,zirrion,NULL,Male,African-American,06/12/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,4,Low,New,1,0 +62119,78095,70678,PRETRIAL,DAAL,GIUSEPPE,NULL,Male,Caucasian,04/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/30/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +62119,78095,70678,PRETRIAL,DAAL,GIUSEPPE,NULL,Male,Caucasian,04/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/30/14 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +62119,78095,70678,PRETRIAL,DAAL,GIUSEPPE,NULL,Male,Caucasian,04/07/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67303,78104,70687,PRETRIAL,Flores,Pedro,NULL,Male,Hispanic,12/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,4,High,7,Risk of Violence,-0.04,10,High,New,1,0 +67303,78104,70687,PRETRIAL,Flores,Pedro,NULL,Male,Hispanic,12/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,4,High,8,Risk of Recidivism,0.63,10,High,New,1,0 +67303,78104,70687,PRETRIAL,Flores,Pedro,NULL,Male,Hispanic,12/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,4,High,18,Risk of Failure to Appear,35,10,High,New,1,0 +67318,78121,70702,PRETRIAL,BROWN,XAVIER,LEWIS,Male,African-American,03/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +67318,78121,70702,PRETRIAL,BROWN,XAVIER,LEWIS,Male,African-American,03/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +67318,78121,70702,PRETRIAL,BROWN,XAVIER,LEWIS,Male,African-American,03/01/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +24971,78100,70683,PRETRIAL,wyatt,michael,NULL,Male,African-American,07/26/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +24971,78100,70683,PRETRIAL,wyatt,michael,NULL,Male,African-American,07/26/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +24971,78100,70683,PRETRIAL,wyatt,michael,NULL,Male,African-American,07/26/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +67306,78107,70690,PRETRIAL,SEEBACH,CHERYL,LYNN,Female,Caucasian,07/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/30/14 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +67306,78107,70690,PRETRIAL,SEEBACH,CHERYL,LYNN,Female,Caucasian,07/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +67306,78107,70690,PRETRIAL,SEEBACH,CHERYL,LYNN,Female,Caucasian,07/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/30/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +44283,48645,44369,PRETRIAL,Kehrle,Crystal,NULL,Female,Caucasian,07/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +44283,48645,44369,PRETRIAL,Kehrle,Crystal,NULL,Female,Caucasian,07/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +44283,48645,44369,PRETRIAL,Kehrle,Crystal,NULL,Female,Caucasian,07/12/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +67330,78138,70717,Probation,Riveros,Gladys,NULL,Female,Hispanic,12/06/40,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/30/14 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +67330,78138,70717,Probation,Riveros,Gladys,NULL,Female,Hispanic,12/06/40,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/30/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +67330,78138,70717,Probation,Riveros,Gladys,NULL,Female,Hispanic,12/06/40,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67312,78115,70696,Probation,KENNY,MICHAEL,P,Male,Caucasian,11/07/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +67312,78115,70696,Probation,KENNY,MICHAEL,P,Male,Caucasian,11/07/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +67312,78115,70696,Probation,KENNY,MICHAEL,P,Male,Caucasian,11/07/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67314,78117,70698,Probation,ke,yun,NULL,Male,Oriental,09/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,7,Risk of Violence,-3.37,1,Low,New,1,0 +67314,78117,70698,Probation,ke,yun,NULL,Male,Oriental,09/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +67314,78117,70698,Probation,ke,yun,NULL,Male,Oriental,09/21/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67319,78124,70704,Probation,Jacome,Jorge,NULL,Male,Hispanic,02/09/55,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/30/14 0:00,1,Low,7,Risk of Violence,-4.28,1,Low,New,1,0 +67319,78124,70704,Probation,Jacome,Jorge,NULL,Male,Hispanic,02/09/55,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/30/14 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +67319,78124,70704,Probation,Jacome,Jorge,NULL,Male,Hispanic,02/09/55,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67298,78094,70677,PRETRIAL,Francis,Ramario,NULL,Male,African-American,05/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,4,High,7,Risk of Violence,-0.62,10,High,New,1,0 +67298,78094,70677,PRETRIAL,Francis,Ramario,NULL,Male,African-American,05/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,4,High,8,Risk of Recidivism,0.71,10,High,New,1,0 +67298,78094,70677,PRETRIAL,Francis,Ramario,NULL,Male,African-American,05/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67299,78096,70679,PRETRIAL,TORRES,SHANE,KEENAN,Male,Caucasian,03/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +67299,78096,70679,PRETRIAL,TORRES,SHANE,KEENAN,Male,Caucasian,03/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +67299,78096,70679,PRETRIAL,TORRES,SHANE,KEENAN,Male,Caucasian,03/31/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67302,78103,70686,PRETRIAL,Needel,Zachary,NULL,Male,African-American,06/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +67302,78103,70686,PRETRIAL,Needel,Zachary,NULL,Male,African-American,06/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +67302,78103,70686,PRETRIAL,Needel,Zachary,NULL,Male,African-American,06/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +58503,78099,70682,PRETRIAL,THOMAS,EDWARD,L,Male,African-American,04/07/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +58503,78099,70682,PRETRIAL,THOMAS,EDWARD,L,Male,African-American,04/07/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +58503,78099,70682,PRETRIAL,THOMAS,EDWARD,L,Male,African-American,04/07/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +67307,78108,70691,PRETRIAL,Delaespriella,Alexander,NULL,Male,Hispanic,07/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +67307,78108,70691,PRETRIAL,Delaespriella,Alexander,NULL,Male,Hispanic,07/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +67307,78108,70691,PRETRIAL,Delaespriella,Alexander,NULL,Male,Hispanic,07/23/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67328,78133,70713,Probation,pangerl,nichole,NULL,Female,Caucasian,02/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +67328,78133,70713,Probation,pangerl,nichole,NULL,Female,Caucasian,02/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.13,3,Low,New,1,0 +67328,78133,70713,Probation,pangerl,nichole,NULL,Female,Caucasian,02/22/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +64061,78112,67007,Probation,Micheletti,Christopher,NULL,Male,Hispanic,04/24/76,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +64061,78112,67007,Probation,Micheletti,Christopher,NULL,Male,Hispanic,04/24/76,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +64061,78112,67007,Probation,Micheletti,Christopher,NULL,Male,Hispanic,04/24/76,17,All Scales,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +67323,78129,70709,Probation,DiDonato,Anthony,Mark,Male,Caucasian,08/23/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/30/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +67323,78129,70709,Probation,DiDonato,Anthony,Mark,Male,Caucasian,08/23/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +67323,78129,70709,Probation,DiDonato,Anthony,Mark,Male,Caucasian,08/23/60,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +20333,78134,70714,PRETRIAL,Smith,Kevin,NULL,Male,African-American,04/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +20333,78134,70714,PRETRIAL,Smith,Kevin,NULL,Male,African-American,04/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +20333,78134,70714,PRETRIAL,Smith,Kevin,NULL,Male,African-American,04/25/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67304,78105,70688,PRETRIAL,VOSS,SARA,CATHERINE,Female,Caucasian,09/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +67304,78105,70688,PRETRIAL,VOSS,SARA,CATHERINE,Female,Caucasian,09/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +67304,78105,70688,PRETRIAL,VOSS,SARA,CATHERINE,Female,Caucasian,09/18/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67317,78120,70701,Probation,Zanatta-Kowalski,Kiker,NULL,Male,Hispanic,05/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +67317,78120,70701,Probation,Zanatta-Kowalski,Kiker,NULL,Male,Hispanic,05/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +67317,78120,70701,Probation,Zanatta-Kowalski,Kiker,NULL,Male,Hispanic,05/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67296,78092,70675,PRETRIAL,Betancourt,Adrian,NULL,Male,African-American,09/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +67296,78092,70675,PRETRIAL,Betancourt,Adrian,NULL,Male,African-American,09/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +67296,78092,70675,PRETRIAL,Betancourt,Adrian,NULL,Male,African-American,09/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67321,78126,70706,PRETRIAL,Shiver,Willie,Barry,Male,African-American,10/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/30/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +67321,78126,70706,PRETRIAL,Shiver,Willie,Barry,Male,African-American,10/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +67321,78126,70706,PRETRIAL,Shiver,Willie,Barry,Male,African-American,10/09/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67322,78128,70708,Probation,Vazquez,Alexander,NULL,Male,Hispanic,11/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +67322,78128,70708,Probation,Vazquez,Alexander,NULL,Male,Hispanic,11/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +67322,78128,70708,Probation,Vazquez,Alexander,NULL,Male,Hispanic,11/16/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67331,78139,70718,Probation,olivencia,heber,NULL,Male,Hispanic,01/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +67331,78139,70718,Probation,olivencia,heber,NULL,Male,Hispanic,01/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +67331,78139,70718,Probation,olivencia,heber,NULL,Male,Hispanic,01/21/74,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67315,78118,70699,Probation,allen,steve,NULL,Male,African-American,01/25/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,7,Risk of Violence,-4.32,1,Low,New,1,0 +67315,78118,70699,Probation,allen,steve,NULL,Male,African-American,01/25/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +67315,78118,70699,Probation,allen,steve,NULL,Male,African-American,01/25/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67325,78131,70711,Probation,Stephens,Christine,NULL,Female,Caucasian,07/06/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +67325,78131,70711,Probation,Stephens,Christine,NULL,Female,Caucasian,07/06/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +67325,78131,70711,Probation,Stephens,Christine,NULL,Female,Caucasian,07/06/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67300,78097,70680,PRETRIAL,Rogers,Brandon,NULL,Male,Caucasian,02/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +67300,78097,70680,PRETRIAL,Rogers,Brandon,NULL,Male,Caucasian,02/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +67300,78097,70680,PRETRIAL,Rogers,Brandon,NULL,Male,Caucasian,02/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/30/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67309,78110,70693,Probation,Lord,Crystal,Jolene,Female,Caucasian,08/12/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,New,1,0 +67309,78110,70693,Probation,Lord,Crystal,Jolene,Female,Caucasian,08/12/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,9,High,New,1,0 +67309,78110,70693,Probation,Lord,Crystal,Jolene,Female,Caucasian,08/12/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,New,1,0 +67360,78178,70752,PRETRIAL,Smith,Colin,NULL,Male,Caucasian,08/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/31/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +67360,78178,70752,PRETRIAL,Smith,Colin,NULL,Male,Caucasian,08/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/31/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +67360,78178,70752,PRETRIAL,Smith,Colin,NULL,Male,Caucasian,08/05/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67351,78165,70740,PRETRIAL,Bragdon,Jaquan,NULL,Male,African-American,10/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,4,High,7,Risk of Violence,-0.51,10,High,New,1,0 +67351,78165,70740,PRETRIAL,Bragdon,Jaquan,NULL,Male,African-American,10/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,4,High,8,Risk of Recidivism,0.28,8,High,New,1,0 +67351,78165,70740,PRETRIAL,Bragdon,Jaquan,NULL,Male,African-American,10/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67336,78147,70725,PRETRIAL,TRIPP,LEEANN,NULL,Female,Caucasian,11/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,10/31/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +67336,78147,70725,PRETRIAL,TRIPP,LEEANN,NULL,Female,Caucasian,11/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,10/31/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +67336,78147,70725,PRETRIAL,TRIPP,LEEANN,NULL,Female,Caucasian,11/16/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67349,78162,70737,PRETRIAL,Berra,Whitney,NULL,Female,Caucasian,12/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +67349,78162,70737,PRETRIAL,Berra,Whitney,NULL,Female,Caucasian,12/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +67349,78162,70737,PRETRIAL,Berra,Whitney,NULL,Female,Caucasian,12/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +67338,78149,70727,PRETRIAL,Dirette,James,NULL,Male,Caucasian,04/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +67338,78149,70727,PRETRIAL,Dirette,James,NULL,Male,Caucasian,04/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +67338,78149,70727,PRETRIAL,Dirette,James,NULL,Male,Caucasian,04/24/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67342,78155,70731,PRETRIAL,J,Burrows,Eric,Male,Caucasian,04/20/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +67342,78155,70731,PRETRIAL,J,Burrows,Eric,Male,Caucasian,04/20/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +67342,78155,70731,PRETRIAL,J,Burrows,Eric,Male,Caucasian,04/20/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67354,78170,70744,PRETRIAL,Mccall,Shanard,NULL,Male,African-American,02/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.09,4,Low,New,1,0 +67354,78170,70744,PRETRIAL,Mccall,Shanard,NULL,Male,African-American,02/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +67354,78170,70744,PRETRIAL,Mccall,Shanard,NULL,Male,African-American,02/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +60445,78141,70720,PRETRIAL,Vazquez,Jennifer,NULL,Female,Caucasian,06/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,7,Risk of Violence,-1.99,4,Low,New,1,0 +60445,78141,70720,PRETRIAL,Vazquez,Jennifer,NULL,Female,Caucasian,06/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +60445,78141,70720,PRETRIAL,Vazquez,Jennifer,NULL,Female,Caucasian,06/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67339,78150,70728,PRETRIAL,Kennedy,Erika,Lee,Female,Caucasian,01/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/31/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +67339,78150,70728,PRETRIAL,Kennedy,Erika,Lee,Female,Caucasian,01/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +67339,78150,70728,PRETRIAL,Kennedy,Erika,Lee,Female,Caucasian,01/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,10/31/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67353,78168,70743,Probation,Bennett,Joseph,Earl,Male,Caucasian,12/24/49,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/31/14 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +67353,78168,70743,Probation,Bennett,Joseph,Earl,Male,Caucasian,12/24/49,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/31/14 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +67353,78168,70743,Probation,Bennett,Joseph,Earl,Male,Caucasian,12/24/49,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67358,78175,70749,PRETRIAL,Torres,Nancy,NULL,Female,Caucasian,12/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +67358,78175,70749,PRETRIAL,Torres,Nancy,NULL,Female,Caucasian,12/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,8,Risk of Recidivism,-0.92,4,Low,New,1,0 +67358,78175,70749,PRETRIAL,Torres,Nancy,NULL,Female,Caucasian,12/19/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,30,9,High,New,1,0 +67340,78152,70729,PRETRIAL,Desousa,Maick,NULL,Male,Other,03/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,2,Medium,7,Risk of Violence,-2.04,4,Low,New,1,0 +67340,78152,70729,PRETRIAL,Desousa,Maick,NULL,Male,Other,03/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +67340,78152,70729,PRETRIAL,Desousa,Maick,NULL,Male,Other,03/18/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67345,78159,70734,DRRD,Charlemagne,Kenny,None,Male,African-American,07/30/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/31/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +67345,78159,70734,DRRD,Charlemagne,Kenny,None,Male,African-American,07/30/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/31/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +67345,78159,70734,DRRD,Charlemagne,Kenny,None,Male,African-American,07/30/93,17,All Scales,Intake,English,Conditional Release,Probation,Single,10/31/14 0:00,2,Medium,18,Risk of Failure to Appear,21,3,Low,New,1,0 +67352,78166,70741,PRETRIAL,West,Gary,NULL,Male,African-American,02/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/31/14 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +67352,78166,70741,PRETRIAL,West,Gary,NULL,Male,African-American,02/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +67352,78166,70741,PRETRIAL,West,Gary,NULL,Male,African-American,02/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/31/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +67356,78173,70747,Probation,Daley,Joann,NULL,Female,Caucasian,10/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +67356,78173,70747,Probation,Daley,Joann,NULL,Female,Caucasian,10/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/14 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +67356,78173,70747,Probation,Daley,Joann,NULL,Female,Caucasian,10/05/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +48947,78172,70746,PRETRIAL,Sullivan,Christopher,NULL,Male,Caucasian,12/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +48947,78172,70746,PRETRIAL,Sullivan,Christopher,NULL,Male,Caucasian,12/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +48947,78172,70746,PRETRIAL,Sullivan,Christopher,NULL,Male,Caucasian,12/12/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +67335,78146,70724,PRETRIAL,MELO,PEDRO,DIMAS,Female,Caucasian,07/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +67335,78146,70724,PRETRIAL,MELO,PEDRO,DIMAS,Female,Caucasian,07/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +67335,78146,70724,PRETRIAL,MELO,PEDRO,DIMAS,Female,Caucasian,07/12/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67348,78163,70738,PRETRIAL,gray,willie,NULL,Male,African-American,01/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +67348,78163,70738,PRETRIAL,gray,willie,NULL,Male,African-American,01/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +67348,78163,70738,PRETRIAL,gray,willie,NULL,Male,African-American,01/12/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67257,78142,70721,PRETRIAL,Lugo,Gregory,Lance,Male,Caucasian,01/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/31/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +67257,78142,70721,PRETRIAL,Lugo,Gregory,Lance,Male,Caucasian,01/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/31/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +67257,78142,70721,PRETRIAL,Lugo,Gregory,Lance,Male,Caucasian,01/13/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +35931,78167,70742,PRETRIAL,Ricci,Ryan,NULL,Male,Caucasian,07/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +35931,78167,70742,PRETRIAL,Ricci,Ryan,NULL,Male,Caucasian,07/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +35931,78167,70742,PRETRIAL,Ricci,Ryan,NULL,Male,Caucasian,07/03/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67359,78176,70750,PRETRIAL,Jones,James,NULL,Male,African-American,10/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,4,High,7,Risk of Violence,0.35,10,High,New,1,0 +67359,78176,70750,PRETRIAL,Jones,James,NULL,Male,African-American,10/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,4,High,8,Risk of Recidivism,0.74,10,High,New,1,0 +67359,78176,70750,PRETRIAL,Jones,James,NULL,Male,African-American,10/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,4,High,18,Risk of Failure to Appear,46,10,High,New,1,0 +67343,78158,70733,PRETRIAL,gonzalez,kadir,NULL,Male,Hispanic,06/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/31/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +67343,78158,70733,PRETRIAL,gonzalez,kadir,NULL,Male,Hispanic,06/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/31/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +67343,78158,70733,PRETRIAL,gonzalez,kadir,NULL,Male,Hispanic,06/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67346,78160,70735,Probation,Cherry,Dondrick,Vernon,Male,African-American,03/29/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/31/14 0:00,2,Medium,7,Risk of Violence,-3.25,1,Low,New,1,0 +67346,78160,70735,Probation,Cherry,Dondrick,Vernon,Male,African-American,03/29/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +67346,78160,70735,Probation,Cherry,Dondrick,Vernon,Male,African-American,03/29/71,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/31/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67337,78148,70726,Probation,Elizee,Jamaze,NULL,Male,African-American,09/13/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/31/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +67337,78148,70726,Probation,Elizee,Jamaze,NULL,Male,African-American,09/13/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/31/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +67337,78148,70726,Probation,Elizee,Jamaze,NULL,Male,African-American,09/13/87,22,Risk and Prescreen,Intake,English,Other,Probation,Single,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +49993,78156,50929,PRETRIAL,Battie,Leroy,NULL,Male,African-American,06/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,Copy,1,0 +49993,78156,50929,PRETRIAL,Battie,Leroy,NULL,Male,African-American,06/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,Copy,1,0 +49993,78156,50929,PRETRIAL,Battie,Leroy,NULL,Male,African-American,06/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +67350,78164,70739,PRETRIAL,Bernardine,Dominic,NULL,Male,Caucasian,04/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.06,8,High,New,1,0 +67350,78164,70739,PRETRIAL,Bernardine,Dominic,NULL,Male,Caucasian,04/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +67350,78164,70739,PRETRIAL,Bernardine,Dominic,NULL,Male,Caucasian,04/26/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,10/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +46548,78177,70751,PRETRIAL,LAUERRE,ALAND,NULL,Male,African-American,11/15/51,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/31/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +46548,78177,70751,PRETRIAL,LAUERRE,ALAND,NULL,Male,African-American,11/15/51,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/31/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +46548,78177,70751,PRETRIAL,LAUERRE,ALAND,NULL,Male,African-American,11/15/51,22,Risk and Prescreen,Intake,English,Other,Probation,Married,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67347,78161,70736,PRETRIAL,williams,chevon,NULL,Male,African-American,11/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +67347,78161,70736,PRETRIAL,williams,chevon,NULL,Male,African-American,11/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +67347,78161,70736,PRETRIAL,williams,chevon,NULL,Male,African-American,11/24/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67332,78140,70719,PRETRIAL,Maximes,Sugar,Ray,Male,African-American,10/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +67332,78140,70719,PRETRIAL,Maximes,Sugar,Ray,Male,African-American,10/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +67332,78140,70719,PRETRIAL,Maximes,Sugar,Ray,Male,African-American,10/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +67357,78174,70748,PRETRIAL,Repp,Brittany,NULL,Female,Caucasian,06/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +67357,78174,70748,PRETRIAL,Repp,Brittany,NULL,Female,Caucasian,06/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +67357,78174,70748,PRETRIAL,Repp,Brittany,NULL,Female,Caucasian,06/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +57954,78143,60113,PRETRIAL,Johnson,Brenley,K,Male,African-American,08/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,Copy,1,0 +57954,78143,60113,PRETRIAL,Johnson,Brenley,K,Male,African-American,08/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,Copy,1,0 +57954,78143,60113,PRETRIAL,Johnson,Brenley,K,Male,African-American,08/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,10/31/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +40673,78153,40299,PRETRIAL,Maddy,Guyrson,NULL,Male,African-American,06/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,Copy,1,0 +40673,78153,40299,PRETRIAL,Maddy,Guyrson,NULL,Male,African-American,06/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,4,High,8,Risk of Recidivism,0.87,10,High,Copy,1,0 +40673,78153,40299,PRETRIAL,Maddy,Guyrson,NULL,Male,African-American,06/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,10/31/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +37743,78182,70755,PRETRIAL,Simmons,Ralph,NULL,Male,African-American,05/05/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +37743,78182,70755,PRETRIAL,Simmons,Ralph,NULL,Male,African-American,05/05/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +37743,78182,70755,PRETRIAL,Simmons,Ralph,NULL,Male,African-American,05/05/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67363,78185,70757,PRETRIAL,Feingold,Deridra,NULL,Female,Caucasian,12/28/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +67363,78185,70757,PRETRIAL,Feingold,Deridra,NULL,Female,Caucasian,12/28/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +67363,78185,70757,PRETRIAL,Feingold,Deridra,NULL,Female,Caucasian,12/28/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67367,78190,70761,PRETRIAL,taylor,yvonne,NULL,Female,African-American,07/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +67367,78190,70761,PRETRIAL,taylor,yvonne,NULL,Female,African-American,07/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +67367,78190,70761,PRETRIAL,taylor,yvonne,NULL,Female,African-American,07/23/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67362,78184,70756,PRETRIAL,Mackens,Samantha,NULL,Male,African-American,08/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.93,5,Medium,New,1,0 +67362,78184,70756,PRETRIAL,Mackens,Samantha,NULL,Male,African-American,08/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,New,1,0 +67362,78184,70756,PRETRIAL,Mackens,Samantha,NULL,Male,African-American,08/26/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +11998,78181,70754,PRETRIAL,travis,james,NULL,Male,African-American,03/22/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,2,Medium,7,Risk of Violence,-1.33,7,Medium,New,1,0 +11998,78181,70754,PRETRIAL,travis,james,NULL,Male,African-American,03/22/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +11998,78181,70754,PRETRIAL,travis,james,NULL,Male,African-American,03/22/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,2,Medium,18,Risk of Failure to Appear,38,10,High,New,1,0 +67365,78187,70759,PRETRIAL,Harris,Jode,NULL,Male,African-American,04/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +67365,78187,70759,PRETRIAL,Harris,Jode,NULL,Male,African-American,04/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +67365,78187,70759,PRETRIAL,Harris,Jode,NULL,Male,African-American,04/30/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67366,78189,70760,PRETRIAL,bazal,brandon,NULL,Male,Caucasian,04/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +67366,78189,70760,PRETRIAL,bazal,brandon,NULL,Male,Caucasian,04/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +67366,78189,70760,PRETRIAL,bazal,brandon,NULL,Male,Caucasian,04/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67361,78180,70753,PRETRIAL,Whittington,Martin,NULL,Male,African-American,07/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +67361,78180,70753,PRETRIAL,Whittington,Martin,NULL,Male,African-American,07/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +67361,78180,70753,PRETRIAL,Whittington,Martin,NULL,Male,African-American,07/18/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +32252,78183,31277,PRETRIAL,holston,jajuan,NULL,Male,African-American,08/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/1/14 0:00,4,High,7,Risk of Violence,-0.81,9,High,Copy,1,0 +32252,78183,31277,PRETRIAL,holston,jajuan,NULL,Male,African-American,08/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/1/14 0:00,4,High,8,Risk of Recidivism,0.26,8,High,Copy,1,0 +32252,78183,31277,PRETRIAL,holston,jajuan,NULL,Male,African-American,08/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/1/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +67364,78186,70758,PRETRIAL,Kirk,Colleen,NULL,Female,Caucasian,05/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.92,2,Low,New,1,0 +67364,78186,70758,PRETRIAL,Kirk,Colleen,NULL,Female,Caucasian,05/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +67364,78186,70758,PRETRIAL,Kirk,Colleen,NULL,Female,Caucasian,05/03/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +60611,78204,63071,PRETRIAL,Nguyen,Duc,Minh,Male,Asian,10/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,2,Medium,7,Risk of Violence,-2.87,2,Low,Copy,1,0 +60611,78204,63071,PRETRIAL,Nguyen,Duc,Minh,Male,Asian,10/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,2,Medium,8,Risk of Recidivism,0.02,7,Medium,Copy,1,0 +60611,78204,63071,PRETRIAL,Nguyen,Duc,Minh,Male,Asian,10/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +67381,78207,70775,PRETRIAL,Thomas,Dante,NULL,Male,African-American,09/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +67381,78207,70775,PRETRIAL,Thomas,Dante,NULL,Male,African-American,09/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,New,1,0 +67381,78207,70775,PRETRIAL,Thomas,Dante,NULL,Male,African-American,09/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67374,78199,70768,PRETRIAL,JOB,RISHIRAJ,NULL,Male,Other,11/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,2,Medium,7,Risk of Violence,-2.77,2,Low,New,1,0 +67374,78199,70768,PRETRIAL,JOB,RISHIRAJ,NULL,Male,Other,11/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +67374,78199,70768,PRETRIAL,JOB,RISHIRAJ,NULL,Male,Other,11/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +54955,78191,56714,PRETRIAL,Sharp,Earl,Raymond,Male,Caucasian,02/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/2/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,Copy,1,0 +54955,78191,56714,PRETRIAL,Sharp,Earl,Raymond,Male,Caucasian,02/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/2/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,Copy,1,0 +54955,78191,56714,PRETRIAL,Sharp,Earl,Raymond,Male,Caucasian,02/12/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +67376,78201,70770,PRETRIAL,BAKER,REBECCA,NULL,Female,Caucasian,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/2/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +67376,78201,70770,PRETRIAL,BAKER,REBECCA,NULL,Female,Caucasian,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/2/14 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +67376,78201,70770,PRETRIAL,BAKER,REBECCA,NULL,Female,Caucasian,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67380,78206,70774,PRETRIAL,Zebo,James,NULL,Male,African-American,05/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +67380,78206,70774,PRETRIAL,Zebo,James,NULL,Male,African-American,05/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,4,Low,New,1,0 +67380,78206,70774,PRETRIAL,Zebo,James,NULL,Male,African-American,05/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +29364,78210,59014,Probation,EVANS,FREDERICK,NULL,Male,African-Am,09/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/2/14 0:00,4,High,7,Risk of Violence,-0.49,10,High,Copy,1,0 +29364,78210,59014,Probation,EVANS,FREDERICK,NULL,Male,African-Am,09/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/2/14 0:00,4,High,8,Risk of Recidivism,0.7,10,High,Copy,1,0 +29364,78210,59014,Probation,EVANS,FREDERICK,NULL,Male,African-Am,09/18/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/2/14 0:00,4,High,18,Risk of Failure to Appear,39,10,High,Copy,1,0 +67370,78194,70764,PRETRIAL,CRAGG,ALEXANDRIA,NULL,Female,Caucasian,09/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,7,Risk of Violence,-1.77,5,Medium,New,1,0 +67370,78194,70764,PRETRIAL,CRAGG,ALEXANDRIA,NULL,Female,Caucasian,09/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +67370,78194,70764,PRETRIAL,CRAGG,ALEXANDRIA,NULL,Female,Caucasian,09/09/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67385,78215,70780,PRETRIAL,Chanardip,Amit,NULL,Male,Caucasian,10/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +67385,78215,70780,PRETRIAL,Chanardip,Amit,NULL,Male,Caucasian,10/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +67385,78215,70780,PRETRIAL,Chanardip,Amit,NULL,Male,Caucasian,10/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67383,78209,70777,PRETRIAL,Smith,James,Edward,Male,African-American,09/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +67383,78209,70777,PRETRIAL,Smith,James,Edward,Male,African-American,09/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +67383,78209,70777,PRETRIAL,Smith,James,Edward,Male,African-American,09/06/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +67386,78216,70781,PRETRIAL,Talleyrand,Neyaha,Lowinsky,Female,African-American,05/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +67386,78216,70781,PRETRIAL,Talleyrand,Neyaha,Lowinsky,Female,African-American,05/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +67386,78216,70781,PRETRIAL,Talleyrand,Neyaha,Lowinsky,Female,African-American,05/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67377,78202,70771,PRETRIAL,CHARLOCK,CHAD,NULL,Male,Caucasian,06/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/2/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +67377,78202,70771,PRETRIAL,CHARLOCK,CHAD,NULL,Male,Caucasian,06/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +67377,78202,70771,PRETRIAL,CHARLOCK,CHAD,NULL,Male,Caucasian,06/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +29364,66256,59014,Probation,EVANS,FREDERICK,NULL,Male,African-Am,09/18/61,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/2/14 0:00,4,High,7,Risk of Violence,-0.47,10,High,New,1,0 +29364,66256,59014,Probation,EVANS,FREDERICK,NULL,Male,African-Am,09/18/61,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/2/14 0:00,4,High,8,Risk of Recidivism,0.6,9,High,New,1,0 +29364,66256,59014,Probation,EVANS,FREDERICK,NULL,Male,African-Am,09/18/61,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/2/14 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +67372,78197,70766,PRETRIAL,SLIKER,MATTHEW,GLENN,Male,Caucasian,02/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +67372,78197,70766,PRETRIAL,SLIKER,MATTHEW,GLENN,Male,Caucasian,02/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +67372,78197,70766,PRETRIAL,SLIKER,MATTHEW,GLENN,Male,Caucasian,02/26/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +61376,78214,63931,PRETRIAL,Diane,Perez,NULL,Female,Hispanic,12/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/2/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,Copy,1,0 +61376,78214,63931,PRETRIAL,Diane,Perez,NULL,Female,Hispanic,12/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,Copy,1,0 +61376,78214,63931,PRETRIAL,Diane,Perez,NULL,Female,Hispanic,12/31/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +67369,78193,70763,PRETRIAL,Caruso,Angela,NULL,Male,Caucasian,07/10/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +67369,78193,70763,PRETRIAL,Caruso,Angela,NULL,Male,Caucasian,07/10/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +67369,78193,70763,PRETRIAL,Caruso,Angela,NULL,Male,Caucasian,07/10/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67373,78198,70767,PRETRIAL,JABUSCH,RYAN,NULL,Male,Caucasian,07/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +67373,78198,70767,PRETRIAL,JABUSCH,RYAN,NULL,Male,Caucasian,07/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +67373,78198,70767,PRETRIAL,JABUSCH,RYAN,NULL,Male,Caucasian,07/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67379,78205,70773,PRETRIAL,WILLIAMS,RICKY,NULL,Male,African-American,02/10/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/2/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +67379,78205,70773,PRETRIAL,WILLIAMS,RICKY,NULL,Male,African-American,02/10/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +67379,78205,70773,PRETRIAL,WILLIAMS,RICKY,NULL,Male,African-American,02/10/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67368,78192,70762,PRETRIAL,Pady,Kenneth,NULL,Male,Caucasian,05/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +67368,78192,70762,PRETRIAL,Pady,Kenneth,NULL,Male,Caucasian,05/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +67368,78192,70762,PRETRIAL,Pady,Kenneth,NULL,Male,Caucasian,05/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67384,78213,70779,PRETRIAL,Messadra,Oscar,Leonardo,Male,Hispanic,12/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/2/14 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +67384,78213,70779,PRETRIAL,Messadra,Oscar,Leonardo,Male,Hispanic,12/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +67384,78213,70779,PRETRIAL,Messadra,Oscar,Leonardo,Male,Hispanic,12/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/2/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67375,78200,70769,PRETRIAL,DOZIER,IAN,NULL,Male,African-American,11/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/2/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +67375,78200,70769,PRETRIAL,DOZIER,IAN,NULL,Male,African-American,11/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/2/14 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +67375,78200,70769,PRETRIAL,DOZIER,IAN,NULL,Male,African-American,11/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67378,78203,70772,PRETRIAL,THOMPSON,CONROY,NULL,Male,African-American,12/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +67378,78203,70772,PRETRIAL,THOMPSON,CONROY,NULL,Male,African-American,12/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +67378,78203,70772,PRETRIAL,THOMPSON,CONROY,NULL,Male,African-American,12/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67382,78208,70776,PRETRIAL,Aguirre,Richard,Ariel,Male,Hispanic,10/01/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +67382,78208,70776,PRETRIAL,Aguirre,Richard,Ariel,Male,Hispanic,10/01/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +67382,78208,70776,PRETRIAL,Aguirre,Richard,Ariel,Male,Hispanic,10/01/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67371,78195,70765,PRETRIAL,CHESTER,KATHERINE,NULL,Female,Caucasian,10/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +67371,78195,70765,PRETRIAL,CHESTER,KATHERINE,NULL,Female,Caucasian,10/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +67371,78195,70765,PRETRIAL,CHESTER,KATHERINE,NULL,Female,Caucasian,10/11/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/2/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67399,78229,70794,Probation,kenny,kristopher,NULL,Male,Caucasian,07/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +67399,78229,70794,Probation,kenny,kristopher,NULL,Male,Caucasian,07/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +67399,78229,70794,Probation,kenny,kristopher,NULL,Male,Caucasian,07/13/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +30397,78263,68948,PRETRIAL,sartori,daniel,NULL,Male,Caucasian,05/09/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +30397,78263,68948,PRETRIAL,sartori,daniel,NULL,Male,Caucasian,05/09/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-0.3,5,Medium,New,1,0 +30397,78263,68948,PRETRIAL,sartori,daniel,NULL,Male,Caucasian,05/09/90,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +67407,78242,70805,Probation,Bershesky,Ann,Christine,Female,Caucasian,08/12/42,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,11/3/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +67407,78242,70805,Probation,Bershesky,Ann,Christine,Female,Caucasian,08/12/42,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,11/3/14 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +67407,78242,70805,Probation,Bershesky,Ann,Christine,Female,Caucasian,08/12/42,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67391,78221,70786,PRETRIAL,WALTERS,DARREN,B,Male,African-American,03/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +67391,78221,70786,PRETRIAL,WALTERS,DARREN,B,Male,African-American,03/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +67391,78221,70786,PRETRIAL,WALTERS,DARREN,B,Male,African-American,03/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67415,78250,70813,PRETRIAL,Holloway,Edward,NULL,Male,Caucasian,11/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +67415,78250,70813,PRETRIAL,Holloway,Edward,NULL,Male,Caucasian,11/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +67415,78250,70813,PRETRIAL,Holloway,Edward,NULL,Male,Caucasian,11/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67428,78268,70830,Probation,BURGOS,DANIEL,NULL,Male,Hispanic,02/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +67428,78268,70830,Probation,BURGOS,DANIEL,NULL,Male,Hispanic,02/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +67428,78268,70830,Probation,BURGOS,DANIEL,NULL,Male,Hispanic,02/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67412,78247,70810,Probation,Alam,Elizabeth,NULL,Female,Caucasian,09/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/3/14 0:00,2,Medium,7,Risk of Violence,-2.66,2,Low,New,1,0 +67412,78247,70810,Probation,Alam,Elizabeth,NULL,Female,Caucasian,09/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +67412,78247,70810,Probation,Alam,Elizabeth,NULL,Female,Caucasian,09/08/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/3/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67396,78226,70791,PRETRIAL,DAVIS,ANTONIO,EUGENE,Male,African-American,12/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +67396,78226,70791,PRETRIAL,DAVIS,ANTONIO,EUGENE,Male,African-American,12/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +67396,78226,70791,PRETRIAL,DAVIS,ANTONIO,EUGENE,Male,African-American,12/17/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67389,78219,70784,PRETRIAL,Blount,Gregory,Reshad,Male,African-American,07/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +67389,78219,70784,PRETRIAL,Blount,Gregory,Reshad,Male,African-American,07/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +67389,78219,70784,PRETRIAL,Blount,Gregory,Reshad,Male,African-American,07/24/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67419,78255,70818,Probation,Palacios,Alexander,NULL,Male,Hispanic,03/27/88,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.73,2,Low,New,1,0 +67419,78255,70818,Probation,Palacios,Alexander,NULL,Male,Hispanic,03/27/88,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +67419,78255,70818,Probation,Palacios,Alexander,NULL,Male,Hispanic,03/27/88,22,Risk and Prescreen,Intake,English,Parole Violator,Probation,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67388,78218,70783,PRETRIAL,Bannon,Keith,Mark,Male,Caucasian,01/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/3/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +67388,78218,70783,PRETRIAL,Bannon,Keith,Mark,Male,Caucasian,01/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +67388,78218,70783,PRETRIAL,Bannon,Keith,Mark,Male,Caucasian,01/18/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67401,78232,70797,PRETRIAL,Taft,Joshua,J,Male,Caucasian,07/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +67401,78232,70797,PRETRIAL,Taft,Joshua,J,Male,Caucasian,07/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +67401,78232,70797,PRETRIAL,Taft,Joshua,J,Male,Caucasian,07/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67404,78239,70802,PRETRIAL,James,Keon,NULL,Male,African-American,11/10/84,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +67404,78239,70802,PRETRIAL,James,Keon,NULL,Male,African-American,11/10/84,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,6,Medium,New,1,0 +67404,78239,70802,PRETRIAL,James,Keon,NULL,Male,African-American,11/10/84,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,18,Risk of Failure to Appear,23,4,Low,New,1,0 +49071,78235,70800,PRETRIAL,Wilson,Ladarius,NULL,Male,African-American,09/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +49071,78235,70800,PRETRIAL,Wilson,Ladarius,NULL,Male,African-American,09/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +49071,78235,70800,PRETRIAL,Wilson,Ladarius,NULL,Male,African-American,09/08/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +49812,78265,70827,PRETRIAL,CASEY,APRIL,NULL,Female,Caucasian,04/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +49812,78265,70827,PRETRIAL,CASEY,APRIL,NULL,Female,Caucasian,04/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +49812,78265,70827,PRETRIAL,CASEY,APRIL,NULL,Female,Caucasian,04/10/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,18,Risk of Failure to Appear,29,9,High,New,1,0 +67393,78223,70788,PRETRIAL,BROOKS,KATIE,NULL,Female,Caucasian,09/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +67393,78223,70788,PRETRIAL,BROOKS,KATIE,NULL,Female,Caucasian,09/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +67393,78223,70788,PRETRIAL,BROOKS,KATIE,NULL,Female,Caucasian,09/19/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67416,78251,70814,PRETRIAL,Torres,Jose,NULL,Male,Hispanic,12/15/88,22,Risk and Prescreen,Intake,Spanish,Pretrial,Jail Inmate,Unknown,11/3/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +67416,78251,70814,PRETRIAL,Torres,Jose,NULL,Male,Hispanic,12/15/88,22,Risk and Prescreen,Intake,Spanish,Pretrial,Jail Inmate,Unknown,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +67416,78251,70814,PRETRIAL,Torres,Jose,NULL,Male,Hispanic,12/15/88,22,Risk and Prescreen,Intake,Spanish,Pretrial,Jail Inmate,Unknown,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +60200,78258,70821,PRETRIAL,Everhardt,Christopher,Charles,Male,Caucasian,04/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +60200,78258,70821,PRETRIAL,Everhardt,Christopher,Charles,Male,Caucasian,04/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +60200,78258,70821,PRETRIAL,Everhardt,Christopher,Charles,Male,Caucasian,04/20/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +60091,78260,70823,PRETRIAL,Huggins,Clifton,E,Female,Caucasian,11/02/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/3/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +60091,78260,70823,PRETRIAL,Huggins,Clifton,E,Female,Caucasian,11/02/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,6,Medium,New,1,0 +60091,78260,70823,PRETRIAL,Huggins,Clifton,E,Female,Caucasian,11/02/91,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/3/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67387,78217,70782,PRETRIAL,SHIPMAN,GARY,MARTIN,Male,African-American,11/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +67387,78217,70782,PRETRIAL,SHIPMAN,GARY,MARTIN,Male,African-American,11/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.86,1,Low,New,1,0 +67387,78217,70782,PRETRIAL,SHIPMAN,GARY,MARTIN,Male,African-American,11/12/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67394,78224,70789,PRETRIAL,Arteta,Wilmer,Jose,Male,Hispanic,11/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +67394,78224,70789,PRETRIAL,Arteta,Wilmer,Jose,Male,Hispanic,11/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +67394,78224,70789,PRETRIAL,Arteta,Wilmer,Jose,Male,Hispanic,11/16/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67410,78245,70808,Probation,HENRY,LEIGHA,ANN,Female,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +67410,78245,70808,Probation,HENRY,LEIGHA,ANN,Female,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +67410,78245,70808,Probation,HENRY,LEIGHA,ANN,Female,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67403,78238,70801,PRETRIAL,Pajon,Jesus,Anibal,Male,Hispanic,05/19/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-4.42,1,Low,Copy,1,0 +67403,78238,70801,PRETRIAL,Pajon,Jesus,Anibal,Male,Hispanic,05/19/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-2.72,1,Low,Copy,1,0 +67403,78238,70801,PRETRIAL,Pajon,Jesus,Anibal,Male,Hispanic,05/19/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +67417,78252,70815,Probation,Addison,Damian,NULL,Male,African-American,06/29/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +67417,78252,70815,Probation,Addison,Damian,NULL,Male,African-American,06/29/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +67417,78252,70815,Probation,Addison,Damian,NULL,Male,African-American,06/29/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67422,78259,70822,Probation,LOPEZ,AXEL,B,Male,Caucasian,01/12/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +67422,78259,70822,Probation,LOPEZ,AXEL,B,Male,Caucasian,01/12/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +67422,78259,70822,Probation,LOPEZ,AXEL,B,Male,Caucasian,01/12/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67426,78266,70828,PRETRIAL,Perry,Marc,NULL,Male,Caucasian,10/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +67426,78266,70828,PRETRIAL,Perry,Marc,NULL,Male,Caucasian,10/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-2.04,1,Low,New,1,0 +67426,78266,70828,PRETRIAL,Perry,Marc,NULL,Male,Caucasian,10/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67405,78240,70803,PRETRIAL,Romanyuk,Orysya,NULL,Female,Other,04/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-4.16,1,Low,New,1,0 +67405,78240,70803,PRETRIAL,Romanyuk,Orysya,NULL,Female,Other,04/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +67405,78240,70803,PRETRIAL,Romanyuk,Orysya,NULL,Female,Other,04/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67397,78227,70792,Probation,Olson,Ronald,NULL,Male,Hispanic,02/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/3/14 0:00,2,Medium,7,Risk of Violence,-1.82,5,Medium,New,1,0 +67397,78227,70792,Probation,Olson,Ronald,NULL,Male,Hispanic,02/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/3/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,New,1,0 +67397,78227,70792,Probation,Olson,Ronald,NULL,Male,Hispanic,02/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/3/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67400,78231,70796,PRETRIAL,Hoffmann,Jamie,Beth,Female,Caucasian,11/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +67400,78231,70796,PRETRIAL,Hoffmann,Jamie,Beth,Female,Caucasian,11/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +67400,78231,70796,PRETRIAL,Hoffmann,Jamie,Beth,Female,Caucasian,11/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67392,78222,70787,PRETRIAL,Green,Erica,NULL,Female,African-American,12/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +67392,78222,70787,PRETRIAL,Green,Erica,NULL,Female,African-American,12/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +67392,78222,70787,PRETRIAL,Green,Erica,NULL,Female,African-American,12/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67408,78243,70806,Probation,Hjelmeir,Steven,NULL,Male,Caucasian,08/07/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/3/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +67408,78243,70806,Probation,Hjelmeir,Steven,NULL,Male,Caucasian,08/07/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +67408,78243,70806,Probation,Hjelmeir,Steven,NULL,Male,Caucasian,08/07/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67421,78257,70820,Probation,SOUZA,THOMAS,NULL,Male,Caucasian,12/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +67421,78257,70820,Probation,SOUZA,THOMAS,NULL,Male,Caucasian,12/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +67421,78257,70820,Probation,SOUZA,THOMAS,NULL,Male,Caucasian,12/08/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67406,78241,70804,PRETRIAL,Baptiste,Ebonie,NULL,Female,African-American,06/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +67406,78241,70804,PRETRIAL,Baptiste,Ebonie,NULL,Female,African-American,06/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +67406,78241,70804,PRETRIAL,Baptiste,Ebonie,NULL,Female,African-American,06/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67413,78248,70811,Probation,green,donna,NULL,Female,African-American,04/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/3/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +67413,78248,70811,Probation,green,donna,NULL,Female,African-American,04/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +67413,78248,70811,Probation,green,donna,NULL,Female,African-American,04/07/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67390,78220,70785,PRETRIAL,HOBBS,MICHEAL,LEE,Male,Caucasian,02/15/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/3/14 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +67390,78220,70785,PRETRIAL,HOBBS,MICHEAL,LEE,Male,Caucasian,02/15/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/3/14 0:00,1,Low,8,Risk of Recidivism,-2.54,1,Low,New,1,0 +67390,78220,70785,PRETRIAL,HOBBS,MICHEAL,LEE,Male,Caucasian,02/15/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67420,78256,70819,PRETRIAL,Gearing,Derik,NULL,Male,Caucasian,11/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,4,High,7,Risk of Violence,-1.22,8,High,New,1,0 +67420,78256,70819,PRETRIAL,Gearing,Derik,NULL,Male,Caucasian,11/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,4,High,8,Risk of Recidivism,0.18,8,High,New,1,0 +67420,78256,70819,PRETRIAL,Gearing,Derik,NULL,Male,Caucasian,11/02/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,New,1,0 +59340,78269,70831,Probation,CARDOSO,stephanie,NULL,Female,Caucasian,09/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.19,4,Low,New,1,0 +59340,78269,70831,Probation,CARDOSO,stephanie,NULL,Female,Caucasian,09/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,9,High,New,1,0 +59340,78269,70831,Probation,CARDOSO,stephanie,NULL,Female,Caucasian,09/21/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67429,78270,70832,Probation,novo,luis,NULL,Male,Hispanic,09/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +67429,78270,70832,Probation,novo,luis,NULL,Male,Hispanic,09/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +67429,78270,70832,Probation,novo,luis,NULL,Male,Hispanic,09/14/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67414,78249,70812,Probation,WILLIAMS,GARY,ANTHONY,Male,African-American,05/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +67414,78249,70812,Probation,WILLIAMS,GARY,ANTHONY,Male,African-American,05/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +67414,78249,70812,Probation,WILLIAMS,GARY,ANTHONY,Male,African-American,05/27/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +31728,78228,70793,DRRD,Carty,Romeo,Ladaro,Male,African-American,02/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +31728,78228,70793,DRRD,Carty,Romeo,Ladaro,Male,African-American,02/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +31728,78228,70793,DRRD,Carty,Romeo,Ladaro,Male,African-American,02/28/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67425,78264,70826,Probation,Lopez,Karla,NULL,Female,Hispanic,03/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +67425,78264,70826,Probation,Lopez,Karla,NULL,Female,Hispanic,03/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +67425,78264,70826,Probation,Lopez,Karla,NULL,Female,Hispanic,03/07/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67427,78267,70829,Probation,gelband,justin,NULL,Male,Caucasian,02/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +67427,78267,70829,Probation,gelband,justin,NULL,Male,Caucasian,02/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +67427,78267,70829,Probation,gelband,justin,NULL,Male,Caucasian,02/16/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +67411,78246,70809,Probation,Borras,Christopher,George,Male,Hispanic,05/08/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +67411,78246,70809,Probation,Borras,Christopher,George,Male,Hispanic,05/08/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +67411,78246,70809,Probation,Borras,Christopher,George,Male,Hispanic,05/08/82,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67395,78225,70790,PRETRIAL,SPENCE,DESHAWN,M,Male,African-American,05/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +67395,78225,70790,PRETRIAL,SPENCE,DESHAWN,M,Male,African-American,05/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +67395,78225,70790,PRETRIAL,SPENCE,DESHAWN,M,Male,African-American,05/23/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +18404,78254,70817,PRETRIAL,Worlds,JonPierre,NULL,Male,African-American,04/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,7,Risk of Violence,-2.14,4,Low,New,1,0 +18404,78254,70817,PRETRIAL,Worlds,JonPierre,NULL,Male,African-American,04/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +18404,78254,70817,PRETRIAL,Worlds,JonPierre,NULL,Male,African-American,04/23/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/3/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67431,78272,70834,PRETRIAL,Crowley,Kevin,Demetrius,Male,African-American,08/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/4/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +67431,78272,70834,PRETRIAL,Crowley,Kevin,Demetrius,Male,African-American,08/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +67431,78272,70834,PRETRIAL,Crowley,Kevin,Demetrius,Male,African-American,08/19/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/4/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67435,78275,70837,PRETRIAL,Aragunde,Joseph,NULL,Male,Hispanic,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +67435,78275,70837,PRETRIAL,Aragunde,Joseph,NULL,Male,Hispanic,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +67435,78275,70837,PRETRIAL,Aragunde,Joseph,NULL,Male,Hispanic,09/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67451,78293,70853,PRETRIAL,GUNN,AARON,NULL,Male,Caucasian,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +67451,78293,70853,PRETRIAL,GUNN,AARON,NULL,Male,Caucasian,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +67451,78293,70853,PRETRIAL,GUNN,AARON,NULL,Male,Caucasian,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67456,78301,70859,PRETRIAL,CRUZ,PANFILO,NULL,Male,Hispanic,09/06/76,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +67456,78301,70859,PRETRIAL,CRUZ,PANFILO,NULL,Male,Hispanic,09/06/76,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +67456,78301,70859,PRETRIAL,CRUZ,PANFILO,NULL,Male,Hispanic,09/06/76,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67443,78285,70846,PRETRIAL,Gomez,Phillip,NULL,Male,Caucasian,12/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,2,Medium,7,Risk of Violence,-1.47,7,Medium,New,1,0 +67443,78285,70846,PRETRIAL,Gomez,Phillip,NULL,Male,Caucasian,12/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +67443,78285,70846,PRETRIAL,Gomez,Phillip,NULL,Male,Caucasian,12/12/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,2,Medium,18,Risk of Failure to Appear,44,10,High,New,1,0 +26605,78306,25706,PRETRIAL,Friday,Karen,NULL,Female,African-American,08/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/4/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,Copy,1,0 +26605,78306,25706,PRETRIAL,Friday,Karen,NULL,Female,African-American,08/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.36,7,Medium,Copy,1,0 +26605,78306,25706,PRETRIAL,Friday,Karen,NULL,Female,African-American,08/19/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/4/14 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,Copy,1,0 +67436,78277,70838,PRETRIAL,HARRINARINE,FEROZA,NULL,Female,Caucasian,04/03/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/4/14 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +67436,78277,70838,PRETRIAL,HARRINARINE,FEROZA,NULL,Female,Caucasian,04/03/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/4/14 0:00,1,Low,8,Risk of Recidivism,-2.67,1,Low,New,1,0 +67436,78277,70838,PRETRIAL,HARRINARINE,FEROZA,NULL,Female,Caucasian,04/03/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67449,78291,70851,Probation,solodyna,christopher,c,Male,Caucasian,01/05/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/4/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +67449,78291,70851,Probation,solodyna,christopher,c,Male,Caucasian,01/05/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.62,1,Low,New,1,0 +67449,78291,70851,Probation,solodyna,christopher,c,Male,Caucasian,01/05/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67454,78298,70857,Probation,CURIEL,DILESKY,NULL,Female,Hispanic,03/30/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +67454,78298,70857,Probation,CURIEL,DILESKY,NULL,Female,Hispanic,03/30/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.1,3,Low,New,1,0 +67454,78298,70857,Probation,CURIEL,DILESKY,NULL,Female,Hispanic,03/30/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67441,78282,70843,PRETRIAL,Clermont,Michael,NULL,Male,Caucasian,02/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.18,8,High,New,1,0 +67441,78282,70843,PRETRIAL,Clermont,Michael,NULL,Male,Caucasian,02/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +67441,78282,70843,PRETRIAL,Clermont,Michael,NULL,Male,Caucasian,02/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +67458,78303,70861,Probation,BRYER,STAFFORD,NULL,Male,Caucasian,02/24/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +67458,78303,70861,Probation,BRYER,STAFFORD,NULL,Male,Caucasian,02/24/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-2.22,1,Low,New,1,0 +67458,78303,70861,Probation,BRYER,STAFFORD,NULL,Male,Caucasian,02/24/66,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67437,78278,70839,PRETRIAL,WILSON,JAMES,BERNARD,Male,African-American,12/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.82,2,Low,New,1,0 +67437,78278,70839,PRETRIAL,WILSON,JAMES,BERNARD,Male,African-American,12/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +67437,78278,70839,PRETRIAL,WILSON,JAMES,BERNARD,Male,African-American,12/30/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67464,78312,70868,Probation,Reid,Tyson,mark,Male,African-American,08/17/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +67464,78312,70868,Probation,Reid,Tyson,mark,Male,African-American,08/17/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +67464,78312,70868,Probation,Reid,Tyson,mark,Male,African-American,08/17/68,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67462,78308,70865,PRETRIAL,Borrero,Jonathan,NULL,Male,Caucasian,01/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +67462,78308,70865,PRETRIAL,Borrero,Jonathan,NULL,Male,Caucasian,01/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +67462,78308,70865,PRETRIAL,Borrero,Jonathan,NULL,Male,Caucasian,01/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67432,78273,70835,PRETRIAL,Palaciorodriguez,Andres,E,Male,Hispanic,04/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +67432,78273,70835,PRETRIAL,Palaciorodriguez,Andres,E,Male,Hispanic,04/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +67432,78273,70835,PRETRIAL,Palaciorodriguez,Andres,E,Male,Hispanic,04/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67445,78287,70848,Probation,BROWN,TREVOR,NULL,Male,African-American,01/07/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +67445,78287,70848,Probation,BROWN,TREVOR,NULL,Male,African-American,01/07/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-2.16,1,Low,New,1,0 +67445,78287,70848,Probation,BROWN,TREVOR,NULL,Male,African-American,01/07/51,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67450,78294,70854,Probation,Brown,Vanasha,NULL,Female,African-American,10/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +67450,78294,70854,Probation,Brown,Vanasha,NULL,Female,African-American,10/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +67450,78294,70854,Probation,Brown,Vanasha,NULL,Female,African-American,10/19/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67453,78296,70856,PRETRIAL,Dominguez-Quintana,Honan,NULL,Male,Hispanic,08/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/4/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +67453,78296,70856,PRETRIAL,Dominguez-Quintana,Honan,NULL,Male,Hispanic,08/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +67453,78296,70856,PRETRIAL,Dominguez-Quintana,Honan,NULL,Male,Hispanic,08/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +47662,78315,70871,PRETRIAL,Homes,Genesie,NULL,Female,African-American,07/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +47662,78315,70871,PRETRIAL,Homes,Genesie,NULL,Female,African-American,07/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +47662,78315,70871,PRETRIAL,Homes,Genesie,NULL,Female,African-American,07/12/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +67438,78279,70840,PRETRIAL,REYNOLDS,ALLISON,M,Female,Caucasian,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.98,4,Low,New,1,0 +67438,78279,70840,PRETRIAL,REYNOLDS,ALLISON,M,Female,Caucasian,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +67438,78279,70840,PRETRIAL,REYNOLDS,ALLISON,M,Female,Caucasian,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67440,78281,70842,PRETRIAL,Garcia Demenezes,Guilherme,NULL,Male,Hispanic,07/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/4/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +67440,78281,70842,PRETRIAL,Garcia Demenezes,Guilherme,NULL,Male,Hispanic,07/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +67440,78281,70842,PRETRIAL,Garcia Demenezes,Guilherme,NULL,Male,Hispanic,07/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67457,78302,70860,Probation,Ilyas,Asim,NULL,Male,Arabic,07/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/4/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +67457,78302,70860,Probation,Ilyas,Asim,NULL,Male,Arabic,07/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +67457,78302,70860,Probation,Ilyas,Asim,NULL,Male,Arabic,07/21/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +41077,78309,70866,PRETRIAL,Adams,Russell,John,Male,Caucasian,11/10/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +41077,78309,70866,PRETRIAL,Adams,Russell,John,Male,Caucasian,11/10/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +41077,78309,70866,PRETRIAL,Adams,Russell,John,Male,Caucasian,11/10/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67446,78288,70849,Probation,Selz,Joseph,NULL,Male,Caucasian,09/02/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-3.93,1,Low,New,1,0 +67446,78288,70849,Probation,Selz,Joseph,NULL,Male,Caucasian,09/02/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +67446,78288,70849,Probation,Selz,Joseph,NULL,Male,Caucasian,09/02/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +26389,78274,70836,DRRD,Winn,Anthony,Khambrel,Male,African-American,06/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.86,9,High,New,1,0 +26389,78274,70836,DRRD,Winn,Anthony,Khambrel,Male,African-American,06/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +26389,78274,70836,DRRD,Winn,Anthony,Khambrel,Male,African-American,06/04/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67452,78295,70855,PRETRIAL,SEELOFF,JUSTIN,NULL,Male,Caucasian,03/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +67452,78295,70855,PRETRIAL,SEELOFF,JUSTIN,NULL,Male,Caucasian,03/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +67452,78295,70855,PRETRIAL,SEELOFF,JUSTIN,NULL,Male,Caucasian,03/31/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67444,78286,70847,Probation,Matherly,Erica,NULL,Female,Caucasian,09/18/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +67444,78286,70847,Probation,Matherly,Erica,NULL,Female,Caucasian,09/18/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +67444,78286,70847,Probation,Matherly,Erica,NULL,Female,Caucasian,09/18/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67459,78304,70862,PRETRIAL,Manet,Jonathan,NULL,Male,African-American,05/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/4/14 0:00,4,High,7,Risk of Violence,0.02,10,High,New,1,0 +67459,78304,70862,PRETRIAL,Manet,Jonathan,NULL,Male,African-American,05/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/4/14 0:00,4,High,8,Risk of Recidivism,0.3,8,High,New,1,0 +67459,78304,70862,PRETRIAL,Manet,Jonathan,NULL,Male,African-American,05/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/4/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67455,78300,70858,Probation,Dandreo,Roger,NULL,Male,Caucasian,02/16/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +67455,78300,70858,Probation,Dandreo,Roger,NULL,Male,Caucasian,02/16/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +67455,78300,70858,Probation,Dandreo,Roger,NULL,Male,Caucasian,02/16/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67461,78307,70864,PRETRIAL,Gamlin,Jay,NULL,Male,Caucasian,11/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,New,1,0 +67461,78307,70864,PRETRIAL,Gamlin,Jay,NULL,Male,Caucasian,11/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +67461,78307,70864,PRETRIAL,Gamlin,Jay,NULL,Male,Caucasian,11/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67460,78305,70863,Probation,Wallance,Michael,NULL,Male,Caucasian,08/21/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +67460,78305,70863,Probation,Wallance,Michael,NULL,Male,Caucasian,08/21/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +67460,78305,70863,Probation,Wallance,Michael,NULL,Male,Caucasian,08/21/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50417,56578,51436,PRETRIAL,Rocha,Brian,NULL,Male,Caucasian,04/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,2,Medium,7,Risk of Violence,-1.98,4,Low,New,1,0 +50417,56578,51436,PRETRIAL,Rocha,Brian,NULL,Male,Caucasian,04/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +50417,56578,51436,PRETRIAL,Rocha,Brian,NULL,Male,Caucasian,04/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67442,78284,70845,Probation,Garciaquiroga,Osmany,NULL,Male,Hispanic,01/30/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +67442,78284,70845,Probation,Garciaquiroga,Osmany,NULL,Male,Hispanic,01/30/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +67442,78284,70845,Probation,Garciaquiroga,Osmany,NULL,Male,Hispanic,01/30/81,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +54715,78313,70869,PRETRIAL,McNish,Katt,NULL,Female,Caucasian,05/14/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +54715,78313,70869,PRETRIAL,McNish,Katt,NULL,Female,Caucasian,05/14/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +54715,78313,70869,PRETRIAL,McNish,Katt,NULL,Female,Caucasian,05/14/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67430,78271,70833,PRETRIAL,BROWN,TERRY,JAMES,Male,African-American,02/04/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/4/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +67430,78271,70833,PRETRIAL,BROWN,TERRY,JAMES,Male,African-American,02/04/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +67430,78271,70833,PRETRIAL,BROWN,TERRY,JAMES,Male,African-American,02/04/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +51573,78289,70850,PRETRIAL,Ramos,Ismael,NULL,Male,Caucasian,12/02/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/4/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +51573,78289,70850,PRETRIAL,Ramos,Ismael,NULL,Male,Caucasian,12/02/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/4/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +51573,78289,70850,PRETRIAL,Ramos,Ismael,NULL,Male,Caucasian,12/02/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67381,78310,70775,PRETRIAL,Thomas,Dante,NULL,Male,African-American,09/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,Copy,1,0 +67381,78310,70775,PRETRIAL,Thomas,Dante,NULL,Male,African-American,09/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,1,Low,8,Risk of Recidivism,-0.54,4,Low,Copy,1,0 +67381,78310,70775,PRETRIAL,Thomas,Dante,NULL,Male,African-American,09/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/4/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +33460,78331,32565,PRETRIAL,Osceola,Robert,NULL,Male,Native American,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,Copy,1,0 +33460,78331,32565,PRETRIAL,Osceola,Robert,NULL,Male,Native American,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.28,8,High,Copy,1,0 +33460,78331,32565,PRETRIAL,Osceola,Robert,NULL,Male,Native American,12/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +67482,78336,70888,Probation,MEDAL,CARMEN,NULL,Female,Hispanic,10/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +67482,78336,70888,Probation,MEDAL,CARMEN,NULL,Female,Hispanic,10/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +67482,78336,70888,Probation,MEDAL,CARMEN,NULL,Female,Hispanic,10/30/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67483,78339,70890,PRETRIAL,CRUZHENRIQUEZ,NELSON,NULL,Male,Hispanic,02/27/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +67483,78339,70890,PRETRIAL,CRUZHENRIQUEZ,NELSON,NULL,Male,Hispanic,02/27/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +67483,78339,70890,PRETRIAL,CRUZHENRIQUEZ,NELSON,NULL,Male,Hispanic,02/27/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67468,78318,70874,PRETRIAL,Gray,Romone,NULL,Male,African-American,12/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +67468,78318,70874,PRETRIAL,Gray,Romone,NULL,Male,African-American,12/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +67468,78318,70874,PRETRIAL,Gray,Romone,NULL,Male,African-American,12/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67477,78328,70883,PRETRIAL,CELESTINO,JASON,NULL,Male,African-American,07/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +67477,78328,70883,PRETRIAL,CELESTINO,JASON,NULL,Male,African-American,07/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,1,Low,8,Risk of Recidivism,-1.43,1,Low,New,1,0 +67477,78328,70883,PRETRIAL,CELESTINO,JASON,NULL,Male,African-American,07/08/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67490,78347,70897,Probation,Velasquezjoyz,Nixon,NULL,Male,Hispanic,01/05/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +67490,78347,70897,Probation,Velasquezjoyz,Nixon,NULL,Male,Hispanic,01/05/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +67490,78347,70897,Probation,Velasquezjoyz,Nixon,NULL,Male,Hispanic,01/05/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67475,78326,70882,PRETRIAL,Stokes,Joel,NULL,Male,African-American,10/14/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +67475,78326,70882,PRETRIAL,Stokes,Joel,NULL,Male,African-American,10/14/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.7,10,High,New,1,0 +67475,78326,70882,PRETRIAL,Stokes,Joel,NULL,Male,African-American,10/14/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,4,Low,New,1,0 +67481,78334,70887,Probation,Budhu,Jeetrinda,NULL,Male,Other,02/02/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/5/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +67481,78334,70887,Probation,Budhu,Jeetrinda,NULL,Male,Other,02/02/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/5/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +67481,78334,70887,Probation,Budhu,Jeetrinda,NULL,Male,Other,02/02/84,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67485,78341,70892,Probation,louis,Rudolfo,NULL,Male,African-American,02/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/14 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +67485,78341,70892,Probation,louis,Rudolfo,NULL,Male,African-American,02/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +67485,78341,70892,Probation,louis,Rudolfo,NULL,Male,African-American,02/13/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67469,78320,70876,PRETRIAL,CAMERON,JEMMAL,NULL,Male,African-American,12/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.61,2,Low,New,1,0 +67469,78320,70876,PRETRIAL,CAMERON,JEMMAL,NULL,Male,African-American,12/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +67469,78320,70876,PRETRIAL,CAMERON,JEMMAL,NULL,Male,African-American,12/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +8384,8440,7934,PRETRIAL,FORREST,JEFFREY,LLOYD,Male,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,4,High,7,Risk of Violence,-0.4,10,High,New,1,0 +8384,8440,7934,PRETRIAL,FORREST,JEFFREY,LLOYD,Male,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +8384,8440,7934,PRETRIAL,FORREST,JEFFREY,LLOYD,Male,African-American,10/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +67470,78321,70877,PRETRIAL,Notise,Ricardo,Montana,Male,Other,04/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +67470,78321,70877,PRETRIAL,Notise,Ricardo,Montana,Male,Other,04/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,1,Low,8,Risk of Recidivism,-1.06,2,Low,New,1,0 +67470,78321,70877,PRETRIAL,Notise,Ricardo,Montana,Male,Other,04/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67489,78346,70896,PRETRIAL,FACALLOPEZ,DAIANA,NULL,Female,Hispanic,06/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +67489,78346,70896,PRETRIAL,FACALLOPEZ,DAIANA,NULL,Female,Hispanic,06/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +67489,78346,70896,PRETRIAL,FACALLOPEZ,DAIANA,NULL,Female,Hispanic,06/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67486,78342,70893,PRETRIAL,Hayes,Brandon,NULL,Male,Caucasian,10/10/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.42,7,Medium,New,1,0 +67486,78342,70893,PRETRIAL,Hayes,Brandon,NULL,Male,Caucasian,10/10/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +67486,78342,70893,PRETRIAL,Hayes,Brandon,NULL,Male,Caucasian,10/10/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +46327,78337,46723,PRETRIAL,Battle,Antonio,NULL,Male,African-American,02/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,Copy,1,0 +46327,78337,46723,PRETRIAL,Battle,Antonio,NULL,Male,African-American,02/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +46327,78337,46723,PRETRIAL,Battle,Antonio,NULL,Male,African-American,02/03/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +67466,78316,70872,PRETRIAL,GORDON,KARLVENSKI,MICHAEL,Male,African-American,09/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/5/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +67466,78316,70872,PRETRIAL,GORDON,KARLVENSKI,MICHAEL,Male,African-American,09/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/5/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +67466,78316,70872,PRETRIAL,GORDON,KARLVENSKI,MICHAEL,Male,African-American,09/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +37653,78330,37042,PRETRIAL,seymore,christopher,NULL,Male,African-American,05/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,Copy,1,0 +37653,78330,37042,PRETRIAL,seymore,christopher,NULL,Male,African-American,05/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,4,High,8,Risk of Recidivism,0.42,9,High,Copy,1,0 +37653,78330,37042,PRETRIAL,seymore,christopher,NULL,Male,African-American,05/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,4,High,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +67467,78317,70873,PRETRIAL,Higgs,Mitchell,NULL,Male,African-American,02/08/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +67467,78317,70873,PRETRIAL,Higgs,Mitchell,NULL,Male,African-American,02/08/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +67467,78317,70873,PRETRIAL,Higgs,Mitchell,NULL,Male,African-American,02/08/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,2,Medium,18,Risk of Failure to Appear,33,9,High,New,1,0 +67473,78324,70880,PRETRIAL,FERGUS,COLLISA,JAQUAY,Female,African-American,05/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,2,Medium,7,Risk of Violence,-2.03,4,Low,New,1,0 +67473,78324,70880,PRETRIAL,FERGUS,COLLISA,JAQUAY,Female,African-American,05/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +67473,78324,70880,PRETRIAL,FERGUS,COLLISA,JAQUAY,Female,African-American,05/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +12216,78338,70889,PRETRIAL,MCLEOD,ANDREW,WILLAM,Male,Caucasian,09/27/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,2,Medium,7,Risk of Violence,-1.27,7,Medium,New,1,0 +12216,78338,70889,PRETRIAL,MCLEOD,ANDREW,WILLAM,Male,Caucasian,09/27/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +12216,78338,70889,PRETRIAL,MCLEOD,ANDREW,WILLAM,Male,Caucasian,09/27/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,2,Medium,18,Risk of Failure to Appear,34,10,High,New,1,0 +67479,78333,70886,PRETRIAL,Gilmore,Deanell,Lepre,Male,African-American,09/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/5/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +67479,78333,70886,PRETRIAL,Gilmore,Deanell,Lepre,Male,African-American,09/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/5/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +67479,78333,70886,PRETRIAL,Gilmore,Deanell,Lepre,Male,African-American,09/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67478,78329,70884,Probation,Kulbaba,Devin,NULL,Male,Caucasian,01/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/14 0:00,1,Low,7,Risk of Violence,-2.53,3,Low,New,1,0 +67478,78329,70884,Probation,Kulbaba,Devin,NULL,Male,Caucasian,01/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +67478,78329,70884,Probation,Kulbaba,Devin,NULL,Male,Caucasian,01/11/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +17704,78327,16981,PRETRIAL,martin,fred,NULL,Male,African-American,09/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,Copy,1,0 +17704,78327,16981,PRETRIAL,martin,fred,NULL,Male,African-American,09/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,Copy,1,0 +17704,78327,16981,PRETRIAL,martin,fred,NULL,Male,African-American,09/05/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +12615,13029,12097,PRETRIAL,Moore,Joe,Nathan,Male,African-American,03/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,2,Medium,7,Risk of Violence,-2.48,3,Low,New,1,0 +12615,13029,12097,PRETRIAL,Moore,Joe,Nathan,Male,African-American,03/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +12615,13029,12097,PRETRIAL,Moore,Joe,Nathan,Male,African-American,03/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +63185,78319,70875,PRETRIAL,Paul,Clemin,NULL,Male,African-American,12/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +63185,78319,70875,PRETRIAL,Paul,Clemin,NULL,Male,African-American,12/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.6,9,High,New,1,0 +63185,78319,70875,PRETRIAL,Paul,Clemin,NULL,Male,African-American,12/27/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +64037,78335,66982,Probation,LAMY,MANUSHKA,NULL,Female,African-American,09/14/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,11/5/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +64037,78335,66982,Probation,LAMY,MANUSHKA,NULL,Female,African-American,09/14/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,11/5/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +64037,78335,66982,Probation,LAMY,MANUSHKA,NULL,Female,African-American,09/14/89,17,All Scales,Intake,English,Conditional Release,Probation,Single,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,1,Low,New,1,0 +67484,78340,70891,PRETRIAL,PECKHAM,ROBERT,NULL,Male,Caucasian,06/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +67484,78340,70891,PRETRIAL,PECKHAM,ROBERT,NULL,Male,Caucasian,06/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +67484,78340,70891,PRETRIAL,PECKHAM,ROBERT,NULL,Male,Caucasian,06/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67491,78348,70898,PRETRIAL,Johnson,Kesneil,NULL,Male,African-American,11/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +67491,78348,70898,PRETRIAL,Johnson,Kesneil,NULL,Male,African-American,11/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,1,Low,8,Risk of Recidivism,-0.98,3,Low,New,1,0 +67491,78348,70898,PRETRIAL,Johnson,Kesneil,NULL,Male,African-American,11/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50173,56250,51146,PRETRIAL,SHELTON,GLENN,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.39,7,Medium,New,1,0 +50173,56250,51146,PRETRIAL,SHELTON,GLENN,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.1,10,High,New,1,0 +50173,56250,51146,PRETRIAL,SHELTON,GLENN,NULL,Male,African-American,12/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67480,78332,70885,Probation,Weston,Alicia,NULL,Female,Caucasian,12/31/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/5/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +67480,78332,70885,Probation,Weston,Alicia,NULL,Female,Caucasian,12/31/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/5/14 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +67480,78332,70885,Probation,Weston,Alicia,NULL,Female,Caucasian,12/31/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/5/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +67471,78322,70878,PRETRIAL,Hillery,Craig,Robert,Male,African-American,08/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.83,2,Low,New,1,0 +67471,78322,70878,PRETRIAL,Hillery,Craig,Robert,Male,African-American,08/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +67471,78322,70878,PRETRIAL,Hillery,Craig,Robert,Male,African-American,08/25/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67494,78353,70902,PRETRIAL,Desouza,Ailton,NULL,Male,Caucasian,01/11/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/6/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +67494,78353,70902,PRETRIAL,Desouza,Ailton,NULL,Male,Caucasian,01/11/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/6/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +67494,78353,70902,PRETRIAL,Desouza,Ailton,NULL,Male,Caucasian,01/11/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67520,78382,70929,Probation,Burke,Kenneth,NULL,Male,African-American,02/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +67520,78382,70929,Probation,Burke,Kenneth,NULL,Male,African-American,02/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +67520,78382,70929,Probation,Burke,Kenneth,NULL,Male,African-American,02/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +40482,78361,42793,Probation,Jean,Paul,NULL,Male,African-American,01/20/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.91,5,Medium,Copy,1,0 +40482,78361,42793,Probation,Jean,Paul,NULL,Male,African-American,01/20/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,9,High,Copy,1,0 +40482,78361,42793,Probation,Jean,Paul,NULL,Male,African-American,01/20/83,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,2,Low,Copy,1,0 +67509,78369,70916,PRETRIAL,rodriguez,michael,A,Male,Caucasian,12/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/6/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +67509,78369,70916,PRETRIAL,rodriguez,michael,A,Male,Caucasian,12/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/6/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +67509,78369,70916,PRETRIAL,rodriguez,michael,A,Male,Caucasian,12/27/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67515,78377,70924,Probation,GONZALES,PETERSON,NULL,Male,Other,05/23/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/6/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +67515,78377,70924,Probation,GONZALES,PETERSON,NULL,Male,Other,05/23/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/6/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +67515,78377,70924,Probation,GONZALES,PETERSON,NULL,Male,Other,05/23/68,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +52652,78384,70931,PRETRIAL,Gutierrez,Eleasar,NULL,Male,Hispanic,10/16/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/14 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +52652,78384,70931,PRETRIAL,Gutierrez,Eleasar,NULL,Male,Hispanic,10/16/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +52652,78384,70931,PRETRIAL,Gutierrez,Eleasar,NULL,Male,Hispanic,10/16/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67522,78385,70932,PRETRIAL,GONZALEZ,LUIS,NULL,Male,Caucasian,11/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +67522,78385,70932,PRETRIAL,GONZALEZ,LUIS,NULL,Male,Caucasian,11/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +67522,78385,70932,PRETRIAL,GONZALEZ,LUIS,NULL,Male,Caucasian,11/01/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67502,78364,70911,PRETRIAL,PEZZIMENTI,DONNA,NULL,Female,Caucasian,12/24/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/6/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +67502,78364,70911,PRETRIAL,PEZZIMENTI,DONNA,NULL,Female,Caucasian,12/24/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/6/14 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +67502,78364,70911,PRETRIAL,PEZZIMENTI,DONNA,NULL,Female,Caucasian,12/24/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67518,78380,70927,Probation,Nuby,Christine,NULL,Female,African-American,03/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +67518,78380,70927,Probation,Nuby,Christine,NULL,Female,African-American,03/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-1.01,4,Low,New,1,0 +67518,78380,70927,Probation,Nuby,Christine,NULL,Female,African-American,03/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67495,78354,70903,PRETRIAL,SINGER,HUNTER,SCOTT,Male,Caucasian,08/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +67495,78354,70903,PRETRIAL,SINGER,HUNTER,SCOTT,Male,Caucasian,08/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +67495,78354,70903,PRETRIAL,SINGER,HUNTER,SCOTT,Male,Caucasian,08/23/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67510,78371,70918,PRETRIAL,RAMOS,ALEX,NULL,Male,Caucasian,06/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +67510,78371,70918,PRETRIAL,RAMOS,ALEX,NULL,Male,Caucasian,06/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +67510,78371,70918,PRETRIAL,RAMOS,ALEX,NULL,Male,Caucasian,06/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67508,78368,70915,Probation,Kineard,Shakila,NULL,Female,African-American,04/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/6/14 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +67508,78368,70915,Probation,Kineard,Shakila,NULL,Female,African-American,04/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +67508,78368,70915,Probation,Kineard,Shakila,NULL,Female,African-American,04/22/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/6/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +44301,78375,70922,PRETRIAL,Forbes,Richard,NULL,Male,Caucasian,07/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +44301,78375,70922,PRETRIAL,Forbes,Richard,NULL,Male,Caucasian,07/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +44301,78375,70922,PRETRIAL,Forbes,Richard,NULL,Male,Caucasian,07/16/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67512,78373,70920,Probation,Romerotiburcio,Miguel,NULL,Male,Hispanic,09/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +67512,78373,70920,Probation,Romerotiburcio,Miguel,NULL,Male,Hispanic,09/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +67512,78373,70920,Probation,Romerotiburcio,Miguel,NULL,Male,Hispanic,09/13/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67493,78352,70901,PRETRIAL,SUTTON,ROSEAMARIA,NULL,Female,African-American,02/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.48,3,Low,New,1,0 +67493,78352,70901,PRETRIAL,SUTTON,ROSEAMARIA,NULL,Female,African-American,02/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,9,High,New,1,0 +67493,78352,70901,PRETRIAL,SUTTON,ROSEAMARIA,NULL,Female,African-American,02/18/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +67498,78359,70907,Probation,Matheny,Timothy,NULL,Male,Caucasian,03/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/6/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +67498,78359,70907,Probation,Matheny,Timothy,NULL,Male,Caucasian,03/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/6/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +67498,78359,70907,Probation,Matheny,Timothy,NULL,Male,Caucasian,03/12/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,37,10,High,New,1,0 +67506,78366,70913,Probation,Reyes,Oscar,NULL,Male,Hispanic,05/28/88,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/6/14 0:00,2,Medium,7,Risk of Violence,-2.46,3,Low,New,1,0 +67506,78366,70913,Probation,Reyes,Oscar,NULL,Male,Hispanic,05/28/88,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +67506,78366,70913,Probation,Reyes,Oscar,NULL,Male,Hispanic,05/28/88,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/6/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +20488,21392,19709,PRETRIAL,MCCALL,STACEY,LINELL,Female,African-American,05/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.96,5,Medium,New,1,0 +20488,21392,19709,PRETRIAL,MCCALL,STACEY,LINELL,Female,African-American,05/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0,8,High,New,1,0 +20488,21392,19709,PRETRIAL,MCCALL,STACEY,LINELL,Female,African-American,05/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67517,78379,70926,Probation,Hill,Deneal,NULL,Male,African-American,07/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +67517,78379,70926,Probation,Hill,Deneal,NULL,Male,African-American,07/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +67517,78379,70926,Probation,Hill,Deneal,NULL,Male,African-American,07/22/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67519,78381,70928,Probation,Potter,Natalie,NULL,Female,Caucasian,03/22/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +67519,78381,70928,Probation,Potter,Natalie,NULL,Female,Caucasian,03/22/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +67519,78381,70928,Probation,Potter,Natalie,NULL,Female,Caucasian,03/22/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +42512,78351,42340,Probation,LEWIS,HOMER,NULL,Male,African-American,03/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,Copy,1,0 +42512,78351,42340,Probation,LEWIS,HOMER,NULL,Male,African-American,03/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,Copy,1,0 +42512,78351,42340,Probation,LEWIS,HOMER,NULL,Male,African-American,03/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +67499,78360,70908,PRETRIAL,Dean,Sherman,NULL,Male,African-American,08/09/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +67499,78360,70908,PRETRIAL,Dean,Sherman,NULL,Male,African-American,08/09/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,New,1,0 +67499,78360,70908,PRETRIAL,Dean,Sherman,NULL,Male,African-American,08/09/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,2,Medium,18,Risk of Failure to Appear,37,10,High,New,1,0 +67507,78367,70914,PRETRIAL,Audatte,Elcye,NULL,Female,African-American,06/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +67507,78367,70914,PRETRIAL,Audatte,Elcye,NULL,Female,African-American,06/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +67507,78367,70914,PRETRIAL,Audatte,Elcye,NULL,Female,African-American,06/07/69,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67501,78363,70910,Probation,Joseph,Susie,NULL,Female,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +67501,78363,70910,Probation,Joseph,Susie,NULL,Female,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-1.53,2,Low,New,1,0 +67501,78363,70910,Probation,Joseph,Susie,NULL,Female,African-American,12/09/75,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67511,78372,70919,Probation,Rasool,Shahabudeen,NULL,Male,Other,12/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +67511,78372,70919,Probation,Rasool,Shahabudeen,NULL,Male,Other,12/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +67511,78372,70919,Probation,Rasool,Shahabudeen,NULL,Male,Other,12/29/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67496,78355,70904,PRETRIAL,Sams,Doneshia,NULL,Female,African-American,05/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,New,1,0 +67496,78355,70904,PRETRIAL,Sams,Doneshia,NULL,Female,African-American,05/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +67496,78355,70904,PRETRIAL,Sams,Doneshia,NULL,Female,African-American,05/25/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/6/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +4623,78370,70917,PRETRIAL,WRIGHT,ALPHONSO,NULL,Male,African-American,05/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +4623,78370,70917,PRETRIAL,WRIGHT,ALPHONSO,NULL,Male,African-American,05/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +4623,78370,70917,PRETRIAL,WRIGHT,ALPHONSO,NULL,Male,African-American,05/16/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67500,78362,70909,Probation,Andrews,Tarnisha,Cabrelle,Female,African-American,08/23/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/14 0:00,2,Medium,7,Risk of Violence,-1.92,5,Medium,New,1,0 +67500,78362,70909,Probation,Andrews,Tarnisha,Cabrelle,Female,African-American,08/23/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +67500,78362,70909,Probation,Andrews,Tarnisha,Cabrelle,Female,African-American,08/23/90,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/6/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +66953,78357,70271,PRETRIAL,Anderson,Cody,NULL,Male,Caucasian,09/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/14 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,Copy,1,0 +66953,78357,70271,PRETRIAL,Anderson,Cody,NULL,Male,Caucasian,09/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.33,5,Medium,Copy,1,0 +66953,78357,70271,PRETRIAL,Anderson,Cody,NULL,Male,Caucasian,09/21/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/6/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +67523,78386,70933,Probation,switzer,Daniel,NULL,Male,Hispanic,06/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/6/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +67523,78386,70933,Probation,switzer,Daniel,NULL,Male,Hispanic,06/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/6/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +67523,78386,70933,Probation,switzer,Daniel,NULL,Male,Hispanic,06/13/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67516,78378,70925,Probation,Fucito,Mark,NULL,Male,Caucasian,01/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +67516,78378,70925,Probation,Fucito,Mark,NULL,Male,Caucasian,01/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +67516,78378,70925,Probation,Fucito,Mark,NULL,Male,Caucasian,01/01/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67503,78365,70912,Probation,HENLEY,RAYMOND,L,Male,Caucasian,05/05/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +67503,78365,70912,Probation,HENLEY,RAYMOND,L,Male,Caucasian,05/05/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +67503,78365,70912,Probation,HENLEY,RAYMOND,L,Male,Caucasian,05/05/78,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/6/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +64034,78399,70946,PRETRIAL,Castro,Alexander,NULL,Male,Hispanic,03/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,1,Low,7,Risk of Violence,-2.98,1,Low,New,1,0 +64034,78399,70946,PRETRIAL,Castro,Alexander,NULL,Male,Hispanic,03/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +64034,78399,70946,PRETRIAL,Castro,Alexander,NULL,Male,Hispanic,03/03/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67535,78404,70951,PRETRIAL,Dykstra,Jonathan,Sterling,Male,Caucasian,04/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +67535,78404,70951,PRETRIAL,Dykstra,Jonathan,Sterling,Male,Caucasian,04/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +67535,78404,70951,PRETRIAL,Dykstra,Jonathan,Sterling,Male,Caucasian,04/10/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67538,78407,70954,PRETRIAL,Ross,Sharon,Hindle,Female,Caucasian,11/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +67538,78407,70954,PRETRIAL,Ross,Sharon,Hindle,Female,Caucasian,11/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.62,2,Low,New,1,0 +67538,78407,70954,PRETRIAL,Ross,Sharon,Hindle,Female,Caucasian,11/15/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67556,78420,70965,PRETRIAL,Hubbard,Robert,NULL,Male,Caucasian,11/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/7/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +67556,78420,70965,PRETRIAL,Hubbard,Robert,NULL,Male,Caucasian,11/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +67556,78420,70965,PRETRIAL,Hubbard,Robert,NULL,Male,Caucasian,11/20/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67526,78391,70938,PRETRIAL,Follen,Mark,NULL,Male,Caucasian,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/7/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +67526,78391,70938,PRETRIAL,Follen,Mark,NULL,Male,Caucasian,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +67526,78391,70938,PRETRIAL,Follen,Mark,NULL,Male,Caucasian,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/7/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +59559,78393,70940,PRETRIAL,Colman,Luis,NULL,Male,Caucasian,08/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +59559,78393,70940,PRETRIAL,Colman,Luis,NULL,Male,Caucasian,08/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +59559,78393,70940,PRETRIAL,Colman,Luis,NULL,Male,Caucasian,08/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67554,78418,70963,PRETRIAL,JOSEPH,JOHNNY,NULL,Male,African-American,02/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1,8,High,New,1,0 +67554,78418,70963,PRETRIAL,JOSEPH,JOHNNY,NULL,Male,African-American,02/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +67554,78418,70963,PRETRIAL,JOSEPH,JOHNNY,NULL,Male,African-American,02/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67529,78397,70944,PRETRIAL,Perry,Vernon,LEE,Male,Caucasian,09/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +67529,78397,70944,PRETRIAL,Perry,Vernon,LEE,Male,Caucasian,09/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +67529,78397,70944,PRETRIAL,Perry,Vernon,LEE,Male,Caucasian,09/21/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67260,78414,70626,PRETRIAL,thompson,dorian,NULL,Male,Caucasian,01/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.35,7,Medium,Copy,1,0 +67260,78414,70626,PRETRIAL,thompson,dorian,NULL,Male,Caucasian,01/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,Copy,1,0 +67260,78414,70626,PRETRIAL,thompson,dorian,NULL,Male,Caucasian,01/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,36,10,High,Copy,1,0 +67533,78402,70949,PRETRIAL,Thompson,Kirstin,C,Male,African-American,06/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.8,5,Medium,New,1,0 +67533,78402,70949,PRETRIAL,Thompson,Kirstin,C,Male,African-American,06/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +67533,78402,70949,PRETRIAL,Thompson,Kirstin,C,Male,African-American,06/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67547,78409,70956,Probation,ammon,christine,NULL,Female,Caucasian,02/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,New,1,0 +67547,78409,70956,Probation,ammon,christine,NULL,Female,Caucasian,02/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,8,High,New,1,0 +67547,78409,70956,Probation,ammon,christine,NULL,Female,Caucasian,02/01/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,New,1,0 +67552,78416,70961,Probation,Whylie,Michael,NULL,Male,African-American,11/25/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +67552,78416,70961,Probation,Whylie,Michael,NULL,Male,African-American,11/25/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +67552,78416,70961,Probation,Whylie,Michael,NULL,Male,African-American,11/25/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67559,78423,70968,PRETRIAL,Everett,Lakita,NULL,Female,African-American,04/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.04,1,Low,New,1,0 +67559,78423,70968,PRETRIAL,Everett,Lakita,NULL,Female,African-American,04/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,9,High,New,1,0 +67559,78423,70968,PRETRIAL,Everett,Lakita,NULL,Female,African-American,04/24/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +67551,78415,70960,PRETRIAL,Morency,Evenson,NULL,Male,African-American,06/07/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +67551,78415,70960,PRETRIAL,Morency,Evenson,NULL,Male,African-American,06/07/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +67551,78415,70960,PRETRIAL,Morency,Evenson,NULL,Male,African-American,06/07/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,5,Medium,New,1,0 +67553,78417,70962,PRETRIAL,SEPULVEDA,MANUEL,NULL,Male,Caucasian,01/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,New,1,0 +67553,78417,70962,PRETRIAL,SEPULVEDA,MANUEL,NULL,Male,Caucasian,01/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +67553,78417,70962,PRETRIAL,SEPULVEDA,MANUEL,NULL,Male,Caucasian,01/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +4049,78424,70969,PRETRIAL,Walsh,Tara,Rose,Female,Caucasian,07/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,New,1,0 +4049,78424,70969,PRETRIAL,Walsh,Tara,Rose,Female,Caucasian,07/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,New,1,0 +4049,78424,70969,PRETRIAL,Walsh,Tara,Rose,Female,Caucasian,07/18/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67528,78396,70943,PRETRIAL,Stephens,Virgil,Dale,Male,African-American,08/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.07,8,High,New,1,0 +67528,78396,70943,PRETRIAL,Stephens,Virgil,Dale,Male,African-American,08/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +67528,78396,70943,PRETRIAL,Stephens,Virgil,Dale,Male,African-American,08/08/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +684,78389,70936,PRETRIAL,MENDEZ,NELSON,ANDRE,Female,Caucasian,09/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +684,78389,70936,PRETRIAL,MENDEZ,NELSON,ANDRE,Female,Caucasian,09/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,9,High,New,1,0 +684,78389,70936,PRETRIAL,MENDEZ,NELSON,ANDRE,Female,Caucasian,09/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67558,78422,70967,Probation,Negron,Melvin,NULL,Male,Hispanic,01/24/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/14 0:00,1,Low,7,Risk of Violence,-3.86,1,Low,New,1,0 +67558,78422,70967,Probation,Negron,Melvin,NULL,Male,Hispanic,01/24/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +67558,78422,70967,Probation,Negron,Melvin,NULL,Male,Hispanic,01/24/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67532,78401,70948,PRETRIAL,Smith,Cory,Roberto,Male,African-American,10/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +67532,78401,70948,PRETRIAL,Smith,Cory,Roberto,Male,African-American,10/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +67532,78401,70948,PRETRIAL,Smith,Cory,Roberto,Male,African-American,10/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67548,78410,70957,Probation,Genhold,Kevin,NULL,Male,Caucasian,06/14/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,2,Medium,7,Risk of Violence,-1.7,6,Medium,New,1,0 +67548,78410,70957,Probation,Genhold,Kevin,NULL,Male,Caucasian,06/14/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +67548,78410,70957,Probation,Genhold,Kevin,NULL,Male,Caucasian,06/14/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67530,78398,70945,PRETRIAL,Pierre,Myriam,NULL,Female,African-American,05/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +67530,78398,70945,PRETRIAL,Pierre,Myriam,NULL,Female,African-American,05/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +67530,78398,70945,PRETRIAL,Pierre,Myriam,NULL,Female,African-American,05/27/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67549,78411,70958,Probation,HIGGINS,Michelle,NULL,Female,African-American,03/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +67549,78411,70958,Probation,HIGGINS,Michelle,NULL,Female,African-American,03/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +67549,78411,70958,Probation,HIGGINS,Michelle,NULL,Female,African-American,03/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +67550,78413,70959,Probation,wells,Derek,NULL,Male,Caucasian,11/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +67550,78413,70959,Probation,wells,Derek,NULL,Male,Caucasian,11/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +67550,78413,70959,Probation,wells,Derek,NULL,Male,Caucasian,11/17/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67525,78390,70937,PRETRIAL,Altomari,Philippi,NULL,Male,Caucasian,11/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +67525,78390,70937,PRETRIAL,Altomari,Philippi,NULL,Male,Caucasian,11/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +67525,78390,70937,PRETRIAL,Altomari,Philippi,NULL,Male,Caucasian,11/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67527,78392,70939,PRETRIAL,Morris,Shavelle,M,Female,African-American,06/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +67527,78392,70939,PRETRIAL,Morris,Shavelle,M,Female,African-American,06/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +67527,78392,70939,PRETRIAL,Morris,Shavelle,M,Female,African-American,06/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67555,78419,70964,PRETRIAL,Baker,Sean,NULL,Male,Caucasian,08/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/7/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +67555,78419,70964,PRETRIAL,Baker,Sean,NULL,Male,Caucasian,08/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +67555,78419,70964,PRETRIAL,Baker,Sean,NULL,Male,Caucasian,08/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67536,78405,70952,PRETRIAL,Pintucci,Louis,NULL,Male,Caucasian,10/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.51,3,Low,New,1,0 +67536,78405,70952,PRETRIAL,Pintucci,Louis,NULL,Male,Caucasian,10/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +67536,78405,70952,PRETRIAL,Pintucci,Louis,NULL,Male,Caucasian,10/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67537,78406,70953,PRETRIAL,Acevedo,Julio,NULL,Male,Hispanic,04/07/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.17,10,High,New,1,0 +67537,78406,70953,PRETRIAL,Acevedo,Julio,NULL,Male,Hispanic,04/07/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,7,Medium,New,1,0 +67537,78406,70953,PRETRIAL,Acevedo,Julio,NULL,Male,Hispanic,04/07/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +64930,78395,70942,PRETRIAL,WELCH,BONITA,EVETTE,Male,African-American,11/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +64930,78395,70942,PRETRIAL,WELCH,BONITA,EVETTE,Male,African-American,11/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +64930,78395,70942,PRETRIAL,WELCH,BONITA,EVETTE,Male,African-American,11/22/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +10721,10977,10242,Probation,Desvergers,Denae,NULL,Female,Caucasian,10/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +10721,10977,10242,Probation,Desvergers,Denae,NULL,Female,Caucasian,10/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.72,10,High,New,1,0 +10721,10977,10242,Probation,Desvergers,Denae,NULL,Female,Caucasian,10/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +67546,78408,70955,PRETRIAL,Hess,Christine,NULL,Female,Caucasian,04/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +67546,78408,70955,PRETRIAL,Hess,Christine,NULL,Female,Caucasian,04/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +67546,78408,70955,PRETRIAL,Hess,Christine,NULL,Female,Caucasian,04/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,9,High,New,1,0 +67531,78400,70947,PRETRIAL,Rodriguezmercado,Anthony,NULL,Male,Caucasian,02/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +67531,78400,70947,PRETRIAL,Rodriguezmercado,Anthony,NULL,Male,Caucasian,02/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +67531,78400,70947,PRETRIAL,Rodriguezmercado,Anthony,NULL,Male,Caucasian,02/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67534,78403,70950,PRETRIAL,Zepeda,Kattya,NULL,Female,Hispanic,06/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +67534,78403,70950,PRETRIAL,Zepeda,Kattya,NULL,Female,Hispanic,06/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +67534,78403,70950,PRETRIAL,Zepeda,Kattya,NULL,Female,Hispanic,06/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67557,78421,70966,PRETRIAL,Knight,Michael,K,Male,African-American,03/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/7/14 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +67557,78421,70966,PRETRIAL,Knight,Michael,K,Male,African-American,03/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/7/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +67557,78421,70966,PRETRIAL,Knight,Michael,K,Male,African-American,03/27/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67562,78429,70973,PRETRIAL,Harvey,kadeem,NULL,Male,African-American,02/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +67562,78429,70973,PRETRIAL,Harvey,kadeem,NULL,Male,African-American,02/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +67562,78429,70973,PRETRIAL,Harvey,kadeem,NULL,Male,African-American,02/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67561,78427,70972,PRETRIAL,Casey,Leopold,Constanin,Male,African-American,07/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,7,Risk of Violence,-3.95,1,Low,New,1,0 +67561,78427,70972,PRETRIAL,Casey,Leopold,Constanin,Male,African-American,07/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +67561,78427,70972,PRETRIAL,Casey,Leopold,Constanin,Male,African-American,07/26/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67568,78434,70978,PRETRIAL,Parker,Marlanea,NULL,Female,Caucasian,03/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,2,Medium,7,Risk of Violence,-2.73,2,Low,New,1,0 +67568,78434,70978,PRETRIAL,Parker,Marlanea,NULL,Female,Caucasian,03/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.52,6,Medium,New,1,0 +67568,78434,70978,PRETRIAL,Parker,Marlanea,NULL,Female,Caucasian,03/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +56450,78426,70971,PRETRIAL,McNair,Derek,NULL,Male,African-American,03/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +56450,78426,70971,PRETRIAL,McNair,Derek,NULL,Male,African-American,03/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,4,High,8,Risk of Recidivism,0.1,8,High,New,1,0 +56450,78426,70971,PRETRIAL,McNair,Derek,NULL,Male,African-American,03/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67564,78431,70975,PRETRIAL,Knight,Bryant,NULL,Male,African-American,05/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +67564,78431,70975,PRETRIAL,Knight,Bryant,NULL,Male,African-American,05/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +67564,78431,70975,PRETRIAL,Knight,Bryant,NULL,Male,African-American,05/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67569,78436,70980,PRETRIAL,Nivar,Elizabeth,J,Female,Caucasian,03/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +67569,78436,70980,PRETRIAL,Nivar,Elizabeth,J,Female,Caucasian,03/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +67569,78436,70980,PRETRIAL,Nivar,Elizabeth,J,Female,Caucasian,03/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67570,78437,70981,PRETRIAL,StHilaire,Vikie,NULL,Female,African-American,01/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +67570,78437,70981,PRETRIAL,StHilaire,Vikie,NULL,Female,African-American,01/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,8,Risk of Recidivism,-1.29,3,Low,New,1,0 +67570,78437,70981,PRETRIAL,StHilaire,Vikie,NULL,Female,African-American,01/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67563,78430,70974,PRETRIAL,King,Deandre,Marquis,Male,African-American,01/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +67563,78430,70974,PRETRIAL,King,Deandre,Marquis,Male,African-American,01/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,New,1,0 +67563,78430,70974,PRETRIAL,King,Deandre,Marquis,Male,African-American,01/02/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67567,78435,70979,PRETRIAL,dangelo,jose,NULL,Male,Native American,04/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +67567,78435,70979,PRETRIAL,dangelo,jose,NULL,Male,Native American,04/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +67567,78435,70979,PRETRIAL,dangelo,jose,NULL,Male,Native American,04/17/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67565,78432,70976,PRETRIAL,Upper,Stephen,Michael,Male,African-American,05/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +67565,78432,70976,PRETRIAL,Upper,Stephen,Michael,Male,African-American,05/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +67565,78432,70976,PRETRIAL,Upper,Stephen,Michael,Male,African-American,05/10/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67572,78439,70983,PRETRIAL,Favors,Lucuis,John,Male,African-American,11/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,New,1,0 +67572,78439,70983,PRETRIAL,Favors,Lucuis,John,Male,African-American,11/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +67572,78439,70983,PRETRIAL,Favors,Lucuis,John,Male,African-American,11/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +66705,78428,69977,PRETRIAL,MARINERO,JUAN,CARLOS,Male,Hispanic,02/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/8/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,Copy,1,0 +66705,78428,69977,PRETRIAL,MARINERO,JUAN,CARLOS,Male,Hispanic,02/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/8/14 0:00,1,Low,8,Risk of Recidivism,-1.56,1,Low,Copy,1,0 +66705,78428,69977,PRETRIAL,MARINERO,JUAN,CARLOS,Male,Hispanic,02/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/8/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +67560,78425,70970,PRETRIAL,Gonen,Arik,NULL,Male,Other,12/31/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +67560,78425,70970,PRETRIAL,Gonen,Arik,NULL,Male,Other,12/31/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +67560,78425,70970,PRETRIAL,Gonen,Arik,NULL,Male,Other,12/31/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/8/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67566,78433,70977,PRETRIAL,AVILA,LUIS,HENRY,Male,Hispanic,02/09/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/8/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,New,1,0 +67566,78433,70977,PRETRIAL,AVILA,LUIS,HENRY,Male,Hispanic,02/09/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/8/14 0:00,1,Low,8,Risk of Recidivism,-2.4,1,Low,New,1,0 +67566,78433,70977,PRETRIAL,AVILA,LUIS,HENRY,Male,Hispanic,02/09/54,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +10582,78446,10108,Probation,Smith,Ladarious,NULL,Male,African-American,04/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,Copy,1,0 +10582,78446,10108,Probation,Smith,Ladarious,NULL,Male,African-American,04/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,Copy,1,0 +10582,78446,10108,Probation,Smith,Ladarious,NULL,Male,African-American,04/05/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +67593,78454,70995,PRETRIAL,Casas Luis,Humberto,NULL,Male,Hispanic,08/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/9/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +67593,78454,70995,PRETRIAL,Casas Luis,Humberto,NULL,Male,Hispanic,08/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/9/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +67593,78454,70995,PRETRIAL,Casas Luis,Humberto,NULL,Male,Hispanic,08/30/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67589,78449,70991,PRETRIAL,ADAMS,BOBBY,L,Male,Caucasian,04/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/9/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +67589,78449,70991,PRETRIAL,ADAMS,BOBBY,L,Male,Caucasian,04/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/9/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +67589,78449,70991,PRETRIAL,ADAMS,BOBBY,L,Male,Caucasian,04/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/9/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67574,78441,70985,PRETRIAL,JEAN,QUINCY,NULL,Male,African-American,05/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +67574,78441,70985,PRETRIAL,JEAN,QUINCY,NULL,Male,African-American,05/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,4,High,8,Risk of Recidivism,0.14,8,High,New,1,0 +67574,78441,70985,PRETRIAL,JEAN,QUINCY,NULL,Male,African-American,05/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67595,78456,70997,PRETRIAL,Leyba,Luis,NULL,Male,Hispanic,06/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +67595,78456,70997,PRETRIAL,Leyba,Luis,NULL,Male,Hispanic,06/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +67595,78456,70997,PRETRIAL,Leyba,Luis,NULL,Male,Hispanic,06/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,50,10,High,New,1,0 +67592,78453,70994,PRETRIAL,Uwanawich,Sandy,NULL,Female,Caucasian,08/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/9/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +67592,78453,70994,PRETRIAL,Uwanawich,Sandy,NULL,Female,Caucasian,08/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/9/14 0:00,1,Low,8,Risk of Recidivism,-1.4,2,Low,New,1,0 +67592,78453,70994,PRETRIAL,Uwanawich,Sandy,NULL,Female,Caucasian,08/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +65109,75295,68198,PRETRIAL,Norman,Robert,NULL,Male,African-American,07/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,New,1,0 +65109,75295,68198,PRETRIAL,Norman,Robert,NULL,Male,African-American,07/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +65109,75295,68198,PRETRIAL,Norman,Robert,NULL,Male,African-American,07/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67581,78444,70988,PRETRIAL,ULTSSE,PATRICK,NULL,Male,Caucasian,02/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.12,8,High,New,1,0 +67581,78444,70988,PRETRIAL,ULTSSE,PATRICK,NULL,Male,Caucasian,02/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +67581,78444,70988,PRETRIAL,ULTSSE,PATRICK,NULL,Male,Caucasian,02/15/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67588,78448,70990,PRETRIAL,FARJARDO,MICHAEL,ANTHONY,Male,Caucasian,08/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,2,Medium,7,Risk of Violence,-2.29,3,Low,New,1,0 +67588,78448,70990,PRETRIAL,FARJARDO,MICHAEL,ANTHONY,Male,Caucasian,08/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +67588,78448,70990,PRETRIAL,FARJARDO,MICHAEL,ANTHONY,Male,Caucasian,08/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65109,78451,68198,PRETRIAL,Norman,Robert,NULL,Male,African-American,07/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,2,Medium,7,Risk of Violence,-2.8,2,Low,Copy,1,0 +65109,78451,68198,PRETRIAL,Norman,Robert,NULL,Male,African-American,07/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,Copy,1,0 +65109,78451,68198,PRETRIAL,Norman,Robert,NULL,Male,African-American,07/04/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +67580,78443,70987,PRETRIAL,Lewis,Craig,NULL,Male,African-American,04/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +67580,78443,70987,PRETRIAL,Lewis,Craig,NULL,Male,African-American,04/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +67580,78443,70987,PRETRIAL,Lewis,Craig,NULL,Male,African-American,04/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67573,78440,70984,PRETRIAL,JAMES,AKEEM,S,Male,African-American,03/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,2,Medium,7,Risk of Violence,-1.36,7,Medium,New,1,0 +67573,78440,70984,PRETRIAL,JAMES,AKEEM,S,Male,African-American,03/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +67573,78440,70984,PRETRIAL,JAMES,AKEEM,S,Male,African-American,03/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +39627,78445,51283,PRETRIAL,Jennings,Christopher,NULL,Male,African-American,01/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,4,High,7,Risk of Violence,-1.12,8,High,Copy,1,0 +39627,78445,51283,PRETRIAL,Jennings,Christopher,NULL,Male,African-American,01/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,4,High,8,Risk of Recidivism,0.61,9,High,Copy,1,0 +39627,78445,51283,PRETRIAL,Jennings,Christopher,NULL,Male,African-American,01/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +67591,78452,70993,PRETRIAL,Guanchecruz,Dianeelys,NULL,Female,Hispanic,06/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/9/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +67591,78452,70993,PRETRIAL,Guanchecruz,Dianeelys,NULL,Female,Hispanic,06/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/9/14 0:00,1,Low,8,Risk of Recidivism,-1.64,2,Low,New,1,0 +67591,78452,70993,PRETRIAL,Guanchecruz,Dianeelys,NULL,Female,Hispanic,06/06/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67582,78447,70989,PRETRIAL,MCCLOSKEY,SUSAN,INA,Female,Caucasian,11/28/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +67582,78447,70989,PRETRIAL,MCCLOSKEY,SUSAN,INA,Female,Caucasian,11/28/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +67582,78447,70989,PRETRIAL,MCCLOSKEY,SUSAN,INA,Female,Caucasian,11/28/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67594,78455,70996,PRETRIAL,Khan,Alexander,NULL,Male,Caucasian,06/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.66,6,Medium,New,1,0 +67594,78455,70996,PRETRIAL,Khan,Alexander,NULL,Male,Caucasian,06/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.12,8,High,New,1,0 +67594,78455,70996,PRETRIAL,Khan,Alexander,NULL,Male,Caucasian,06/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67575,78442,70986,PRETRIAL,Ramessar,Christopher,NULL,Male,African-American,08/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +67575,78442,70986,PRETRIAL,Ramessar,Christopher,NULL,Male,African-American,08/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +67575,78442,70986,PRETRIAL,Ramessar,Christopher,NULL,Male,African-American,08/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/9/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67590,78450,70992,PRETRIAL,BLOOM,REBECCA,ANN,Female,Caucasian,10/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/9/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +67590,78450,70992,PRETRIAL,BLOOM,REBECCA,ANN,Female,Caucasian,10/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/9/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +67590,78450,70992,PRETRIAL,BLOOM,REBECCA,ANN,Female,Caucasian,10/18/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/9/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +26032,27446,25131,PRETRIAL,MCKAY,MARLON,ADRIAN,Male,African-American,11/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.83,9,High,New,1,0 +26032,27446,25131,PRETRIAL,MCKAY,MARLON,ADRIAN,Male,African-American,11/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +26032,27446,25131,PRETRIAL,MCKAY,MARLON,ADRIAN,Male,African-American,11/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67605,78471,71007,PRETRIAL,MCKENZIE,BERRIS,NULL,Male,Other,10/06/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,Copy,1,0 +67605,78471,71007,PRETRIAL,MCKENZIE,BERRIS,NULL,Male,Other,10/06/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/14 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,Copy,1,0 +67605,78471,71007,PRETRIAL,MCKENZIE,BERRIS,NULL,Male,Other,10/06/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,Copy,1,0 +67610,78476,71013,PRETRIAL,Rodriguez,Teodoro,NULL,Male,Hispanic,10/08/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/10/14 0:00,1,Low,7,Risk of Violence,-4.27,1,Low,New,1,0 +67610,78476,71013,PRETRIAL,Rodriguez,Teodoro,NULL,Male,Hispanic,10/08/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/10/14 0:00,1,Low,8,Risk of Recidivism,-2.61,1,Low,New,1,0 +67610,78476,71013,PRETRIAL,Rodriguez,Teodoro,NULL,Male,Hispanic,10/08/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67602,78463,71004,PRETRIAL,PRUNEDA,SELENA,LEE,Female,Caucasian,11/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +67602,78463,71004,PRETRIAL,PRUNEDA,SELENA,LEE,Female,Caucasian,11/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,4,High,8,Risk of Recidivism,-0.13,8,High,New,1,0 +67602,78463,71004,PRETRIAL,PRUNEDA,SELENA,LEE,Female,Caucasian,11/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +67634,78497,71033,Probation,hall,shawn,NULL,Male,African-American,04/07/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +67634,78497,71033,Probation,hall,shawn,NULL,Male,African-American,04/07/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,New,1,0 +67634,78497,71033,Probation,hall,shawn,NULL,Male,African-American,04/07/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +67623,78484,71021,Probation,Miller,Gary,NULL,Male,African-American,07/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +67623,78484,71021,Probation,Miller,Gary,NULL,Male,African-American,07/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +67623,78484,71021,Probation,Miller,Gary,NULL,Male,African-American,07/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67630,78492,71029,Probation,molina,henry,NULL,Male,Caucasian,08/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +67630,78492,71029,Probation,molina,henry,NULL,Male,Caucasian,08/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +67630,78492,71029,Probation,molina,henry,NULL,Male,Caucasian,08/07/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67598,78459,71000,PRETRIAL,Pierre,Fabiola,NULL,Female,African-American,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +67598,78459,71000,PRETRIAL,Pierre,Fabiola,NULL,Female,African-American,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +67598,78459,71000,PRETRIAL,Pierre,Fabiola,NULL,Female,African-American,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58364,78466,60589,PRETRIAL,Tommie,Kenneth,NULL,Male,Other,01/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,Copy,1,0 +58364,78466,60589,PRETRIAL,Tommie,Kenneth,NULL,Male,Other,01/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,Copy,1,0 +58364,78466,60589,PRETRIAL,Tommie,Kenneth,NULL,Male,Other,01/25/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +67608,78473,71011,PRETRIAL,Morris,Nathan,NULL,Male,Caucasian,10/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +67608,78473,71011,PRETRIAL,Morris,Nathan,NULL,Male,Caucasian,10/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.15,6,Medium,New,1,0 +67608,78473,71011,PRETRIAL,Morris,Nathan,NULL,Male,Caucasian,10/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +67625,78487,71024,Probation,bailey,shawnee,NULL,Female,African-American,09/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +67625,78487,71024,Probation,bailey,shawnee,NULL,Female,African-American,09/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +67625,78487,71024,Probation,bailey,shawnee,NULL,Female,African-American,09/11/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67633,78496,71032,Probation,jandasek,jeannette,NULL,Female,Caucasian,02/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,2,Medium,7,Risk of Violence,-2.52,3,Low,New,1,0 +67633,78496,71032,Probation,jandasek,jeannette,NULL,Female,Caucasian,02/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,New,1,0 +67633,78496,71032,Probation,jandasek,jeannette,NULL,Female,Caucasian,02/07/72,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,2,Medium,18,Risk of Failure to Appear,31,9,High,New,1,0 +67632,78494,71031,PRETRIAL,HOWARD,LATONYA,NULL,Female,African-American,04/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,2,Medium,7,Risk of Violence,-2.23,4,Low,New,1,0 +67632,78494,71031,PRETRIAL,HOWARD,LATONYA,NULL,Female,African-American,04/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +67632,78494,71031,PRETRIAL,HOWARD,LATONYA,NULL,Female,African-American,04/20/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67635,78499,71035,Probation,Jean-Jacques,Jim,NULL,Male,African-American,10/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +67635,78499,71035,Probation,Jean-Jacques,Jim,NULL,Male,African-American,10/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +67635,78499,71035,Probation,Jean-Jacques,Jim,NULL,Male,African-American,10/04/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67600,78461,71002,PRETRIAL,Hale,Edward,Charles,Male,Hispanic,02/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +67600,78461,71002,PRETRIAL,Hale,Edward,Charles,Male,Hispanic,02/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +67600,78461,71002,PRETRIAL,Hale,Edward,Charles,Male,Hispanic,02/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67618,78478,71015,PRETRIAL,Bryant,Elijah,NULL,Male,African-American,07/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.27,7,Medium,New,1,0 +67618,78478,71015,PRETRIAL,Bryant,Elijah,NULL,Male,African-American,07/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +67618,78478,71015,PRETRIAL,Bryant,Elijah,NULL,Male,African-American,07/22/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +67621,78482,71019,Probation,patel,jay,NULL,Male,Caucasian,01/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +67621,78482,71019,Probation,patel,jay,NULL,Male,Caucasian,01/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +67621,78482,71019,Probation,patel,jay,NULL,Male,Caucasian,01/06/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67597,78458,70999,PRETRIAL,Alba,Tracie,NULL,Female,Caucasian,02/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +67597,78458,70999,PRETRIAL,Alba,Tracie,NULL,Female,Caucasian,02/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +67597,78458,70999,PRETRIAL,Alba,Tracie,NULL,Female,Caucasian,02/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67599,78460,71001,PRETRIAL,Khan,Jamal,Nason,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +67599,78460,71001,PRETRIAL,Khan,Jamal,Nason,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +67599,78460,71001,PRETRIAL,Khan,Jamal,Nason,Male,African-American,10/15/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +30789,78479,71016,PRETRIAL,Quiles,Victor,NULL,Male,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +30789,78479,71016,PRETRIAL,Quiles,Victor,NULL,Male,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,4,High,8,Risk of Recidivism,0.63,10,High,New,1,0 +30789,78479,71016,PRETRIAL,Quiles,Victor,NULL,Male,Caucasian,07/13/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67620,78481,71018,PRETRIAL,Stevens,Dennis,NULL,Male,African-American,10/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/10/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +67620,78481,71018,PRETRIAL,Stevens,Dennis,NULL,Male,African-American,10/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/10/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +67620,78481,71018,PRETRIAL,Stevens,Dennis,NULL,Male,African-American,10/11/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67626,78488,71025,PRETRIAL,Parascram,Kawall,NULL,Male,African-American,08/11/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +67626,78488,71025,PRETRIAL,Parascram,Kawall,NULL,Male,African-American,08/11/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +67626,78488,71025,PRETRIAL,Parascram,Kawall,NULL,Male,African-American,08/11/65,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67604,78465,71006,PRETRIAL,CABOT,KEVIN,JEROME,Male,Caucasian,12/20/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/10/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +67604,78465,71006,PRETRIAL,CABOT,KEVIN,JEROME,Male,Caucasian,12/20/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +67604,78465,71006,PRETRIAL,CABOT,KEVIN,JEROME,Male,Caucasian,12/20/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67606,78469,71008,PRETRIAL,PITT,BASIL,NULL,Male,Other,05/21/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/14 0:00,1,Low,7,Risk of Violence,-4.38,1,Low,Copy,1,0 +67606,78469,71008,PRETRIAL,PITT,BASIL,NULL,Male,Other,05/21/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/14 0:00,1,Low,8,Risk of Recidivism,-2.78,1,Low,Copy,1,0 +67606,78469,71008,PRETRIAL,PITT,BASIL,NULL,Male,Other,05/21/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +31180,78474,36935,PRETRIAL,HUGHES,ED,NULL,Male,African-American,06/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,Copy,1,0 +31180,78474,36935,PRETRIAL,HUGHES,ED,NULL,Male,African-American,06/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,Copy,1,0 +31180,78474,36935,PRETRIAL,HUGHES,ED,NULL,Male,African-American,06/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +58862,78486,71023,PRETRIAL,Huynh,Suong,NULL,Male,Caucasian,10/18/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +58862,78486,71023,PRETRIAL,Huynh,Suong,NULL,Male,Caucasian,10/18/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +58862,78486,71023,PRETRIAL,Huynh,Suong,NULL,Male,Caucasian,10/18/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67628,78490,71027,Probation,Minaya,Fredrick,NULL,Male,Hispanic,12/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +67628,78490,71027,Probation,Minaya,Fredrick,NULL,Male,Hispanic,12/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +67628,78490,71027,Probation,Minaya,Fredrick,NULL,Male,Hispanic,12/18/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +63110,78470,71009,PRETRIAL,Barnard,Daniel,NULL,Male,African-American,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +63110,78470,71009,PRETRIAL,Barnard,Daniel,NULL,Male,African-American,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +63110,78470,71009,PRETRIAL,Barnard,Daniel,NULL,Male,African-American,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +2919,78477,71014,PRETRIAL,TEJEIRA,DANIEL,NULL,Male,Caucasian,01/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +2919,78477,71014,PRETRIAL,TEJEIRA,DANIEL,NULL,Male,Caucasian,01/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +2919,78477,71014,PRETRIAL,TEJEIRA,DANIEL,NULL,Male,Caucasian,01/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67629,78491,71028,Probation,Laing,Tyler,NULL,Male,Caucasian,06/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +67629,78491,71028,Probation,Laing,Tyler,NULL,Male,Caucasian,06/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +67629,78491,71028,Probation,Laing,Tyler,NULL,Male,Caucasian,06/13/93,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +31180,40344,36935,PRETRIAL,HUGHES,ED,NULL,Male,African-American,06/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,2,Medium,7,Risk of Violence,-2.43,3,Low,New,1,0 +31180,40344,36935,PRETRIAL,HUGHES,ED,NULL,Male,African-American,06/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +31180,40344,36935,PRETRIAL,HUGHES,ED,NULL,Male,African-American,06/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67622,78483,71020,Probation,Frey,Edward,NULL,Male,Caucasian,11/13/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/10/14 0:00,1,Low,7,Risk of Violence,-4.46,1,Low,New,1,0 +67622,78483,71020,Probation,Frey,Edward,NULL,Male,Caucasian,11/13/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/10/14 0:00,1,Low,8,Risk of Recidivism,-2.33,1,Low,New,1,0 +67622,78483,71020,Probation,Frey,Edward,NULL,Male,Caucasian,11/13/46,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67624,78485,71022,PRETRIAL,Nelson,Devante,NULL,Male,African-American,09/02/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/10/14 0:00,4,High,7,Risk of Violence,-0.61,10,High,New,1,0 +67624,78485,71022,PRETRIAL,Nelson,Devante,NULL,Male,African-American,09/02/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/10/14 0:00,4,High,8,Risk of Recidivism,0.98,10,High,New,1,0 +67624,78485,71022,PRETRIAL,Nelson,Devante,NULL,Male,African-American,09/02/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/10/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67601,78462,71003,PRETRIAL,Garcia-Silverio,Miguel,Angel,Male,Caucasian,11/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +67601,78462,71003,PRETRIAL,Garcia-Silverio,Miguel,Angel,Male,Caucasian,11/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +67601,78462,71003,PRETRIAL,Garcia-Silverio,Miguel,Angel,Male,Caucasian,11/18/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67603,78464,71005,PRETRIAL,ROSATO,MICHAEL,NULL,Male,Caucasian,12/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.3,3,Low,New,1,0 +67603,78464,71005,PRETRIAL,ROSATO,MICHAEL,NULL,Male,Caucasian,12/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +67603,78464,71005,PRETRIAL,ROSATO,MICHAEL,NULL,Male,Caucasian,12/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +58708,78498,71034,PRETRIAL,Kaye,Lisa,NULL,Female,Caucasian,10/08/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/10/14 0:00,1,Low,7,Risk of Violence,-3.83,1,Low,New,1,0 +58708,78498,71034,PRETRIAL,Kaye,Lisa,NULL,Female,Caucasian,10/08/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +58708,78498,71034,PRETRIAL,Kaye,Lisa,NULL,Female,Caucasian,10/08/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67607,78472,71010,PRETRIAL,Depre,Michael,NULL,Male,African-American,01/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +67607,78472,71010,PRETRIAL,Depre,Michael,NULL,Male,African-American,01/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +67607,78472,71010,PRETRIAL,Depre,Michael,NULL,Male,African-American,01/21/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67609,78475,71012,Probation,Pratt,Samuel,NULL,Male,African-American,09/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +67609,78475,71012,Probation,Pratt,Samuel,NULL,Male,African-American,09/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +67609,78475,71012,Probation,Pratt,Samuel,NULL,Male,African-American,09/06/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67631,78493,71030,Probation,Fernandez,Jesus,NULL,Male,Hispanic,05/05/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/10/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +67631,78493,71030,Probation,Fernandez,Jesus,NULL,Male,Hispanic,05/05/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +67631,78493,71030,Probation,Fernandez,Jesus,NULL,Male,Hispanic,05/05/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67619,78480,71017,Probation,luma,Malherbe,NULL,Male,African-American,05/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/10/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +67619,78480,71017,Probation,luma,Malherbe,NULL,Male,African-American,05/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/10/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +67619,78480,71017,Probation,luma,Malherbe,NULL,Male,African-American,05/20/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67605,78467,71007,PRETRIAL,MCKENZIE,BERRIS,NULL,Male,Other,10/06/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/14 0:00,1,Low,7,Risk of Violence,-3.98,1,Low,New,1,0 +67605,78467,71007,PRETRIAL,MCKENZIE,BERRIS,NULL,Male,Other,10/06/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/14 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +67605,78467,71007,PRETRIAL,MCKENZIE,BERRIS,NULL,Male,Other,10/06/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/10/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67637,78501,71037,PRETRIAL,QAZI,SHAHZAD,A,Male,Other,11/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/11/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +67637,78501,71037,PRETRIAL,QAZI,SHAHZAD,A,Male,Other,11/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/11/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +67637,78501,71037,PRETRIAL,QAZI,SHAHZAD,A,Male,Other,11/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67647,78514,71050,PRETRIAL,Mazzeo,Krista,NULL,Female,Caucasian,05/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +67647,78514,71050,PRETRIAL,Mazzeo,Krista,NULL,Female,Caucasian,05/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +67647,78514,71050,PRETRIAL,Mazzeo,Krista,NULL,Female,Caucasian,05/27/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67644,78511,71047,PRETRIAL,Wright,Marisa,NULL,Female,Other,05/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +67644,78511,71047,PRETRIAL,Wright,Marisa,NULL,Female,Other,05/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,8,Risk of Recidivism,-0.96,4,Low,New,1,0 +67644,78511,71047,PRETRIAL,Wright,Marisa,NULL,Female,Other,05/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67651,78519,71055,PRETRIAL,Pande,Timothy,NULL,Male,Caucasian,12/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +67651,78519,71055,PRETRIAL,Pande,Timothy,NULL,Male,Caucasian,12/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +67651,78519,71055,PRETRIAL,Pande,Timothy,NULL,Male,Caucasian,12/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67641,78506,71042,PRETRIAL,WELLINGTON,CLIFFORD,RUNNINGHOU,Male,Caucasian,04/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.87,5,Medium,New,1,0 +67641,78506,71042,PRETRIAL,WELLINGTON,CLIFFORD,RUNNINGHOU,Male,Caucasian,04/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.66,10,High,New,1,0 +67641,78506,71042,PRETRIAL,WELLINGTON,CLIFFORD,RUNNINGHOU,Male,Caucasian,04/15/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67640,78504,71040,PRETRIAL,MAISONET,ADRIAN,MIGUEL,Male,African-American,05/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +67640,78504,71040,PRETRIAL,MAISONET,ADRIAN,MIGUEL,Male,African-American,05/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +67640,78504,71040,PRETRIAL,MAISONET,ADRIAN,MIGUEL,Male,African-American,05/13/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67654,78521,71057,PRETRIAL,HODGE,DARRIAN,NULL,Male,African-American,05/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,4,High,7,Risk of Violence,-0.69,9,High,New,1,0 +67654,78521,71057,PRETRIAL,HODGE,DARRIAN,NULL,Male,African-American,05/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,4,High,8,Risk of Recidivism,0.54,9,High,New,1,0 +67654,78521,71057,PRETRIAL,HODGE,DARRIAN,NULL,Male,African-American,05/18/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67636,78500,71036,PRETRIAL,Miller,Deadra,Arquita,Female,African-American,02/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +67636,78500,71036,PRETRIAL,Miller,Deadra,Arquita,Female,African-American,02/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +67636,78500,71036,PRETRIAL,Miller,Deadra,Arquita,Female,African-American,02/04/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67642,78507,71043,PRETRIAL,Nelson,Jean,Malphonse,Male,Other,05/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +67642,78507,71043,PRETRIAL,Nelson,Jean,Malphonse,Male,Other,05/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +67642,78507,71043,PRETRIAL,Nelson,Jean,Malphonse,Male,Other,05/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67638,78502,71038,PRETRIAL,Libson,Kory,Michael,Male,African-American,05/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +67638,78502,71038,PRETRIAL,Libson,Kory,Michael,Male,African-American,05/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +67638,78502,71038,PRETRIAL,Libson,Kory,Michael,Male,African-American,05/16/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67643,78509,71045,PRETRIAL,MCFADDEN,KIMBERLY,NULL,Male,African-American,12/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/11/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +67643,78509,71045,PRETRIAL,MCFADDEN,KIMBERLY,NULL,Male,African-American,12/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/11/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +67643,78509,71045,PRETRIAL,MCFADDEN,KIMBERLY,NULL,Male,African-American,12/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67649,78516,71052,PRETRIAL,BROWN,HEATHER,NULL,Female,Caucasian,04/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/11/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +67649,78516,71052,PRETRIAL,BROWN,HEATHER,NULL,Female,Caucasian,04/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/11/14 0:00,1,Low,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +67649,78516,71052,PRETRIAL,BROWN,HEATHER,NULL,Female,Caucasian,04/19/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67639,78503,71039,PRETRIAL,Jones,Tavon,Xavier,Male,African-American,02/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,7,Risk of Violence,-1.72,6,Medium,New,1,0 +67639,78503,71039,PRETRIAL,Jones,Tavon,Xavier,Male,African-American,02/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +67639,78503,71039,PRETRIAL,Jones,Tavon,Xavier,Male,African-American,02/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67645,78512,71048,PRETRIAL,Millien,Muranda,Yola,Female,Other,03/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +67645,78512,71048,PRETRIAL,Millien,Muranda,Yola,Female,Other,03/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +67645,78512,71048,PRETRIAL,Millien,Muranda,Yola,Female,Other,03/27/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +65357,78508,71044,Probation,kirton,errol,NULL,Male,African-American,09/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +65357,78508,71044,Probation,kirton,errol,NULL,Male,African-American,09/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +65357,78508,71044,Probation,kirton,errol,NULL,Male,African-American,09/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67650,78517,71053,PRETRIAL,Holbrook,Emily,NULL,Female,Caucasian,10/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,7,Risk of Violence,-1.89,5,Medium,New,1,0 +67650,78517,71053,PRETRIAL,Holbrook,Emily,NULL,Female,Caucasian,10/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +67650,78517,71053,PRETRIAL,Holbrook,Emily,NULL,Female,Caucasian,10/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67648,78515,71051,PRETRIAL,Hardemon,Leroy,NULL,Male,African-American,02/02/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +67648,78515,71051,PRETRIAL,Hardemon,Leroy,NULL,Male,African-American,02/02/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +67648,78515,71051,PRETRIAL,Hardemon,Leroy,NULL,Male,African-American,02/02/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67646,78513,71049,PRETRIAL,Henry,Meghan,NULL,Female,Other,10/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +67646,78513,71049,PRETRIAL,Henry,Meghan,NULL,Female,Other,10/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,8,Risk of Recidivism,-0.74,5,Medium,New,1,0 +67646,78513,71049,PRETRIAL,Henry,Meghan,NULL,Female,Other,10/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59791,78505,71041,PRETRIAL,Stremy,Jonathan,NULL,Male,African-American,08/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +59791,78505,71041,PRETRIAL,Stremy,Jonathan,NULL,Male,African-American,08/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +59791,78505,71041,PRETRIAL,Stremy,Jonathan,NULL,Male,African-American,08/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +21888,78510,71046,PRETRIAL,CADY,TAYLOR,M,Male,Caucasian,07/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +21888,78510,71046,PRETRIAL,CADY,TAYLOR,M,Male,Caucasian,07/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +21888,78510,71046,PRETRIAL,CADY,TAYLOR,M,Male,Caucasian,07/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67652,78518,71054,PRETRIAL,Mcshine,Koffi,Koffi,Male,African-American,12/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/11/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +67652,78518,71054,PRETRIAL,Mcshine,Koffi,Koffi,Male,African-American,12/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/11/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +67652,78518,71054,PRETRIAL,Mcshine,Koffi,Koffi,Male,African-American,12/12/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/11/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +48005,78536,71070,PRETRIAL,HARRIS,SEAN,ANTHONY,Male,African-American,06/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.91,5,Medium,New,1,0 +48005,78536,71070,PRETRIAL,HARRIS,SEAN,ANTHONY,Male,African-American,06/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +48005,78536,71070,PRETRIAL,HARRIS,SEAN,ANTHONY,Male,African-American,06/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67681,78557,71090,PRETRIAL,Doe,Tyrel,NULL,Male,African-American,11/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,4,High,7,Risk of Violence,-1.06,8,High,New,1,0 +67681,78557,71090,PRETRIAL,Doe,Tyrel,NULL,Male,African-American,11/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,4,High,8,Risk of Recidivism,0.18,8,High,New,1,0 +67681,78557,71090,PRETRIAL,Doe,Tyrel,NULL,Male,African-American,11/14/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67667,78539,71073,PRETRIAL,CHALAKO,LISA,43314,Female,Caucasian,04/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +67667,78539,71073,PRETRIAL,CHALAKO,LISA,43314,Female,Caucasian,04/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +67667,78539,71073,PRETRIAL,CHALAKO,LISA,43314,Female,Caucasian,04/22/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +67670,78544,71077,PRETRIAL,brooks,wesley,NULL,Male,African-American,02/17/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.45,3,Low,New,1,0 +67670,78544,71077,PRETRIAL,brooks,wesley,NULL,Male,African-American,02/17/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +67670,78544,71077,PRETRIAL,brooks,wesley,NULL,Male,African-American,02/17/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +67663,78531,71066,PRETRIAL,Porras,Robert,louis,Male,Caucasian,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,New,1,0 +67663,78531,71066,PRETRIAL,Porras,Robert,louis,Male,Caucasian,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +67663,78531,71066,PRETRIAL,Porras,Robert,louis,Male,Caucasian,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +67679,78555,71088,Probation,Carter,David,NULL,Male,Caucasian,10/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +67679,78555,71088,Probation,Carter,David,NULL,Male,Caucasian,10/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +67679,78555,71088,Probation,Carter,David,NULL,Male,Caucasian,10/27/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67693,78570,71103,Probation,De Araujo,Leandro,NULL,Male,Hispanic,05/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +67693,78570,71103,Probation,De Araujo,Leandro,NULL,Male,Hispanic,05/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-0.65,4,Low,New,1,0 +67693,78570,71103,Probation,De Araujo,Leandro,NULL,Male,Hispanic,05/26/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66800,78534,70091,PRETRIAL,Ricano,Amelia,NULL,Female,Caucasian,04/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,4,High,7,Risk of Violence,-0.84,9,High,Copy,1,0 +66800,78534,70091,PRETRIAL,Ricano,Amelia,NULL,Female,Caucasian,04/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,4,High,8,Risk of Recidivism,0.38,9,High,Copy,1,0 +66800,78534,70091,PRETRIAL,Ricano,Amelia,NULL,Female,Caucasian,04/29/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +67669,78541,71075,PRETRIAL,CACCAMO,CHRISTINA,MARIE,Female,Caucasian,02/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,2,Medium,7,Risk of Violence,-2.23,4,Low,New,1,0 +67669,78541,71075,PRETRIAL,CACCAMO,CHRISTINA,MARIE,Female,Caucasian,02/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +67669,78541,71075,PRETRIAL,CACCAMO,CHRISTINA,MARIE,Female,Caucasian,02/26/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67660,78528,71064,PRETRIAL,Mcgee,Robert,Lee,Male,African-American,10/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +67660,78528,71064,PRETRIAL,Mcgee,Robert,Lee,Male,African-American,10/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +67660,78528,71064,PRETRIAL,Mcgee,Robert,Lee,Male,African-American,10/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67673,78547,71080,Probation,Pastukhov,Yvacheslav,NULL,Male,Caucasian,05/06/82,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/12/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +67673,78547,71080,Probation,Pastukhov,Yvacheslav,NULL,Male,Caucasian,05/06/82,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +67673,78547,71080,Probation,Pastukhov,Yvacheslav,NULL,Male,Caucasian,05/06/82,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67686,78562,71095,PRETRIAL,Peri,Meni,NULL,Male,Caucasian,08/09/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +67686,78562,71095,PRETRIAL,Peri,Meni,NULL,Male,Caucasian,08/09/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +67686,78562,71095,PRETRIAL,Peri,Meni,NULL,Male,Caucasian,08/09/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67658,78526,71062,PRETRIAL,JOSEPH,YVES,NULL,Male,African-American,03/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +67658,78526,71062,PRETRIAL,JOSEPH,YVES,NULL,Male,African-American,03/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +67658,78526,71062,PRETRIAL,JOSEPH,YVES,NULL,Male,African-American,03/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +56128,78549,71082,Probation,harvard,markevis,NULL,Male,African-American,11/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +56128,78549,71082,Probation,harvard,markevis,NULL,Male,African-American,11/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +56128,78549,71082,Probation,harvard,markevis,NULL,Male,African-American,11/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67671,78545,71078,Probation,Kardan,Mozhgan,NULL,Female,Caucasian,06/06/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +67671,78545,71078,Probation,Kardan,Mozhgan,NULL,Female,Caucasian,06/06/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +67671,78545,71078,Probation,Kardan,Mozhgan,NULL,Female,Caucasian,06/06/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59819,78524,71060,PRETRIAL,DANIELS,DENSMORE,NULL,Male,African-American,10/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,4,High,7,Risk of Violence,-0.73,9,High,New,1,0 +59819,78524,71060,PRETRIAL,DANIELS,DENSMORE,NULL,Male,African-American,10/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,4,High,8,Risk of Recidivism,0.68,10,High,New,1,0 +59819,78524,71060,PRETRIAL,DANIELS,DENSMORE,NULL,Male,African-American,10/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +46650,52781,47082,PRETRIAL,durden,tony,NULL,Male,African-American,12/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.73,6,Medium,Copy,1,0 +46650,52781,47082,PRETRIAL,durden,tony,NULL,Male,African-American,12/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.05,10,High,Copy,1,0 +46650,52781,47082,PRETRIAL,durden,tony,NULL,Male,African-American,12/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,Copy,1,0 +67666,78538,71072,PRETRIAL,VALDES,WILLIAM,NULL,Male,Caucasian,05/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +67666,78538,71072,PRETRIAL,VALDES,WILLIAM,NULL,Male,Caucasian,05/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +67666,78538,71072,PRETRIAL,VALDES,WILLIAM,NULL,Male,Caucasian,05/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +57881,78573,71105,PRETRIAL,MUNIZ,JONATHAN,NULL,Male,Hispanic,09/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +57881,78573,71105,PRETRIAL,MUNIZ,JONATHAN,NULL,Male,Hispanic,09/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +57881,78573,71105,PRETRIAL,MUNIZ,JONATHAN,NULL,Male,Hispanic,09/03/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +61261,78552,71085,PRETRIAL,Mullings,Amy,Lynn,Female,Caucasian,04/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/12/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +61261,78552,71085,PRETRIAL,Mullings,Amy,Lynn,Female,Caucasian,04/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.48,2,Low,New,1,0 +61261,78552,71085,PRETRIAL,Mullings,Amy,Lynn,Female,Caucasian,04/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67683,78559,71092,Probation,Cairo,Michael,NULL,Male,Caucasian,10/16/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +67683,78559,71092,Probation,Cairo,Michael,NULL,Male,Caucasian,10/16/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +67683,78559,71092,Probation,Cairo,Michael,NULL,Male,Caucasian,10/16/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67662,78533,71068,Probation,Marshall,James,NULL,Male,African-American,04/17/62,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/12/14 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +67662,78533,71068,Probation,Marshall,James,NULL,Male,African-American,04/17/62,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/12/14 0:00,2,Medium,8,Risk of Recidivism,0.07,7,Medium,New,1,0 +67662,78533,71068,Probation,Marshall,James,NULL,Male,African-American,04/17/62,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/12/14 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,New,1,0 +27176,78529,38932,Probation,JOHNSON,MARCUS,ANTHONY,Male,African-American,07/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,2,Medium,7,Risk of Violence,-2.61,2,Low,Copy,1,0 +27176,78529,38932,Probation,JOHNSON,MARCUS,ANTHONY,Male,African-American,07/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.01,7,Medium,Copy,1,0 +27176,78529,38932,Probation,JOHNSON,MARCUS,ANTHONY,Male,African-American,07/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +67678,78554,71087,PRETRIAL,Ortiz,Matthew,NULL,Male,Caucasian,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +67678,78554,71087,PRETRIAL,Ortiz,Matthew,NULL,Male,Caucasian,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +67678,78554,71087,PRETRIAL,Ortiz,Matthew,NULL,Male,Caucasian,09/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67694,78571,71104,Probation,LE,PHUC,HONG,Male,Asian,08/25/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +67694,78571,71104,Probation,LE,PHUC,HONG,Male,Asian,08/25/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +67694,78571,71104,Probation,LE,PHUC,HONG,Male,Asian,08/25/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67676,78550,71083,PRETRIAL,MULLIN,JAMES,NULL,Male,Caucasian,09/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +67676,78550,71083,PRETRIAL,MULLIN,JAMES,NULL,Male,Caucasian,09/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.41,5,Medium,New,1,0 +67676,78550,71083,PRETRIAL,MULLIN,JAMES,NULL,Male,Caucasian,09/12/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67691,78568,71101,Probation,Mceachrane,Jent,NULL,Male,African-American,02/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +67691,78568,71101,Probation,Mceachrane,Jent,NULL,Male,African-American,02/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +67691,78568,71101,Probation,Mceachrane,Jent,NULL,Male,African-American,02/25/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67656,78523,71059,PRETRIAL,Shaw,Giovanni,Rolando,Male,Other,05/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +67656,78523,71059,PRETRIAL,Shaw,Giovanni,Rolando,Male,Other,05/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +67656,78523,71059,PRETRIAL,Shaw,Giovanni,Rolando,Male,Other,05/07/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67665,78537,71071,PRETRIAL,Williams,Rudolph,NULL,Male,Caucasian,09/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.84,9,High,New,1,0 +67665,78537,71071,PRETRIAL,Williams,Rudolph,NULL,Male,Caucasian,09/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.02,7,Medium,New,1,0 +67665,78537,71071,PRETRIAL,Williams,Rudolph,NULL,Male,Caucasian,09/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67661,78530,71065,PRETRIAL,Molina,Juan,NULL,Male,Hispanic,05/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-4.14,1,Low,New,1,0 +67661,78530,71065,PRETRIAL,Molina,Juan,NULL,Male,Hispanic,05/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-2.59,1,Low,New,1,0 +67661,78530,71065,PRETRIAL,Molina,Juan,NULL,Male,Hispanic,05/22/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67657,78525,71061,PRETRIAL,SHOPOVICK,JASON,JASON,Male,Caucasian,12/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/12/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +67657,78525,71061,PRETRIAL,SHOPOVICK,JASON,JASON,Male,Caucasian,12/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +67657,78525,71061,PRETRIAL,SHOPOVICK,JASON,JASON,Male,Caucasian,12/17/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63115,78572,65937,PRETRIAL,Alcivar,Victor,NULL,Male,Hispanic,04/23/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,Copy,1,0 +63115,78572,65937,PRETRIAL,Alcivar,Victor,NULL,Male,Hispanic,04/23/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,Copy,1,0 +63115,78572,65937,PRETRIAL,Alcivar,Victor,NULL,Male,Hispanic,04/23/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +53337,78542,71076,PRETRIAL,Davenport,Najeh,NULL,Male,African-American,02/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/12/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +53337,78542,71076,PRETRIAL,Davenport,Najeh,NULL,Male,African-American,02/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +53337,78542,71076,PRETRIAL,Davenport,Najeh,NULL,Male,African-American,02/08/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67690,78567,71100,PRETRIAL,Holmes,Mercedes,NULL,Female,African-American,02/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +67690,78567,71100,PRETRIAL,Holmes,Mercedes,NULL,Female,African-American,02/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-0.59,5,Medium,New,1,0 +67690,78567,71100,PRETRIAL,Holmes,Mercedes,NULL,Female,African-American,02/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67672,78546,71079,Probation,ortizcalderon,ninoshka,NULL,Female,Hispanic,09/15/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +67672,78546,71079,Probation,ortizcalderon,ninoshka,NULL,Female,Hispanic,09/15/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.04,8,High,New,1,0 +67672,78546,71079,Probation,ortizcalderon,ninoshka,NULL,Female,Hispanic,09/15/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67685,78563,71096,PRETRIAL,HUERTASLEBRON,CHRISTIAN,NULL,Male,Hispanic,11/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +67685,78563,71096,PRETRIAL,HUERTASLEBRON,CHRISTIAN,NULL,Male,Hispanic,11/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +67685,78563,71096,PRETRIAL,HUERTASLEBRON,CHRISTIAN,NULL,Male,Hispanic,11/26/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67680,78556,71089,PRETRIAL,Lowe,Christopher,NULL,Male,African-American,12/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/12/14 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +67680,78556,71089,PRETRIAL,Lowe,Christopher,NULL,Male,African-American,12/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/12/14 0:00,4,High,8,Risk of Recidivism,0.74,10,High,New,1,0 +67680,78556,71089,PRETRIAL,Lowe,Christopher,NULL,Male,African-American,12/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/12/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67659,78527,71063,PRETRIAL,Yunis,Erquilly,NULL,Female,Caucasian,01/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +67659,78527,71063,PRETRIAL,Yunis,Erquilly,NULL,Female,Caucasian,01/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +67659,78527,71063,PRETRIAL,Yunis,Erquilly,NULL,Female,Caucasian,01/18/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67687,78564,71097,Probation,cruz,gerardo,NULL,Male,Hispanic,05/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/14 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +67687,78564,71097,Probation,cruz,gerardo,NULL,Male,Hispanic,05/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +67687,78564,71097,Probation,cruz,gerardo,NULL,Male,Hispanic,05/21/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/12/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67674,78548,71081,PRETRIAL,Lapatin,Dennis,NULL,Male,Caucasian,01/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +67674,78548,71081,PRETRIAL,Lapatin,Dennis,NULL,Male,Caucasian,01/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +67674,78548,71081,PRETRIAL,Lapatin,Dennis,NULL,Male,Caucasian,01/21/49,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +63701,73515,66620,Probation,Thomas,Oshea,NULL,Male,African-American,03/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,4,High,7,Risk of Violence,-0.95,9,High,New,1,0 +63701,73515,66620,Probation,Thomas,Oshea,NULL,Male,African-American,03/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,4,High,8,Risk of Recidivism,0.62,10,High,New,1,0 +63701,73515,66620,Probation,Thomas,Oshea,NULL,Male,African-American,03/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/12/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67664,78535,71069,PRETRIAL,Palermo,Jason,NULL,Male,Caucasian,02/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +67664,78535,71069,PRETRIAL,Palermo,Jason,NULL,Male,Caucasian,02/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +67664,78535,71069,PRETRIAL,Palermo,Jason,NULL,Male,Caucasian,02/15/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67692,78569,71102,Probation,Lambert,Lauren,Kelly,Female,Caucasian,01/17/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-2.82,2,Low,New,1,0 +67692,78569,71102,Probation,Lambert,Lauren,Kelly,Female,Caucasian,01/17/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +67692,78569,71102,Probation,Lambert,Lauren,Kelly,Female,Caucasian,01/17/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +31160,78574,71106,PRETRIAL,Wargo,Alexander,NULL,Male,Caucasian,07/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,2,Medium,7,Risk of Violence,-2.67,2,Low,New,1,0 +31160,78574,71106,PRETRIAL,Wargo,Alexander,NULL,Male,Caucasian,07/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +31160,78574,71106,PRETRIAL,Wargo,Alexander,NULL,Male,Caucasian,07/05/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/12/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +7735,78532,71067,PRETRIAL,COOPER,TORRANCE,NULL,Male,African-American,08/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.17,4,Low,New,1,0 +7735,78532,71067,PRETRIAL,COOPER,TORRANCE,NULL,Male,African-American,08/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +7735,78532,71067,PRETRIAL,COOPER,TORRANCE,NULL,Male,African-American,08/22/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +67655,78522,71058,PRETRIAL,Yetts,Nathan,NULL,Male,African-American,10/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +67655,78522,71058,PRETRIAL,Yetts,Nathan,NULL,Male,African-American,10/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +67655,78522,71058,PRETRIAL,Yetts,Nathan,NULL,Male,African-American,10/05/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67668,78540,71074,PRETRIAL,BENITEZ,ENER,NULL,Male,Caucasian,10/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,4,High,7,Risk of Violence,-0.19,10,High,New,1,0 +67668,78540,71074,PRETRIAL,BENITEZ,ENER,NULL,Male,Caucasian,10/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,4,High,8,Risk of Recidivism,1.24,10,High,New,1,0 +67668,78540,71074,PRETRIAL,BENITEZ,ENER,NULL,Male,Caucasian,10/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67677,78553,71086,PRETRIAL,Coronel,Yesenia,NULL,Female,Caucasian,04/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,7,Risk of Violence,-2.97,1,Low,New,1,0 +67677,78553,71086,PRETRIAL,Coronel,Yesenia,NULL,Female,Caucasian,04/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +67677,78553,71086,PRETRIAL,Coronel,Yesenia,NULL,Female,Caucasian,04/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/12/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +32908,78590,64624,PRETRIAL,James,Cedric,NULL,Male,African-American,11/01/84,17,All Scales,Intake,English,Conditional Release,Probation,Married,11/13/14 0:00,4,High,7,Risk of Violence,-1.19,8,High,New,1,0 +32908,78590,64624,PRETRIAL,James,Cedric,NULL,Male,African-American,11/01/84,17,All Scales,Intake,English,Conditional Release,Probation,Married,11/13/14 0:00,4,High,8,Risk of Recidivism,0.37,8,High,New,1,0 +32908,78590,64624,PRETRIAL,James,Cedric,NULL,Male,African-American,11/01/84,17,All Scales,Intake,English,Conditional Release,Probation,Married,11/13/14 0:00,4,High,18,Risk of Failure to Appear,30,8,High,New,1,0 +67727,78621,71145,Probation,Harris,michael,NULL,Male,African-American,01/28/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +67727,78621,71145,Probation,Harris,michael,NULL,Male,African-American,01/28/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +67727,78621,71145,Probation,Harris,michael,NULL,Male,African-American,01/28/69,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +12344,51749,47123,PRETRIAL,PRINGLE,RANDOLPH,NULL,Male,African-American,05/08/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.68,9,High,New,1,0 +12344,51749,47123,PRETRIAL,PRINGLE,RANDOLPH,NULL,Male,African-American,05/08/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +12344,51749,47123,PRETRIAL,PRINGLE,RANDOLPH,NULL,Male,African-American,05/08/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67715,78600,71129,PRETRIAL,Smith,Robert,Joseph,Male,Caucasian,01/13/39,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/13/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +67715,78600,71129,PRETRIAL,Smith,Robert,Joseph,Male,Caucasian,01/13/39,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/13/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +67715,78600,71129,PRETRIAL,Smith,Robert,Joseph,Male,Caucasian,01/13/39,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67723,78611,71139,Probation,Martinez,Luis,NULL,Male,Hispanic,07/22/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +67723,78611,71139,Probation,Martinez,Luis,NULL,Male,Hispanic,07/22/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +67723,78611,71139,Probation,Martinez,Luis,NULL,Male,Hispanic,07/22/68,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67720,78608,71136,Probation,FERNANDEZ,JESSIE,K,Female,Hispanic,08/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +67720,78608,71136,Probation,FERNANDEZ,JESSIE,K,Female,Hispanic,08/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-0.99,4,Low,New,1,0 +67720,78608,71136,Probation,FERNANDEZ,JESSIE,K,Female,Hispanic,08/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67701,78582,71114,PRETRIAL,WEST,SAMANTHA,LEE,Female,Caucasian,11/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +67701,78582,71114,PRETRIAL,WEST,SAMANTHA,LEE,Female,Caucasian,11/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,7,Medium,New,1,0 +67701,78582,71114,PRETRIAL,WEST,SAMANTHA,LEE,Female,Caucasian,11/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67711,78595,71125,PRETRIAL,CHAVEZ,RAFAEL,NULL,Male,Caucasian,06/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/13/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +67711,78595,71125,PRETRIAL,CHAVEZ,RAFAEL,NULL,Male,Caucasian,06/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/13/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +67711,78595,71125,PRETRIAL,CHAVEZ,RAFAEL,NULL,Male,Caucasian,06/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67734,78629,71153,Probation,battle,lakisha,NULL,Female,African-American,06/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,2,Medium,7,Risk of Violence,-2.82,2,Low,New,1,0 +67734,78629,71153,Probation,battle,lakisha,NULL,Female,African-American,06/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +67734,78629,71153,Probation,battle,lakisha,NULL,Female,African-American,06/12/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67713,78598,71128,Probation,Castro,Thiago,NULL,Male,Other,01/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +67713,78598,71128,Probation,Castro,Thiago,NULL,Male,Other,01/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/14 0:00,1,Low,8,Risk of Recidivism,-1.46,1,Low,New,1,0 +67713,78598,71128,Probation,Castro,Thiago,NULL,Male,Other,01/12/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +22337,23397,21502,PRETRIAL,MATHIS,TODD,NULL,Male,African-American,12/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +22337,23397,21502,PRETRIAL,MATHIS,TODD,NULL,Male,African-American,12/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.55,9,High,New,1,0 +22337,23397,21502,PRETRIAL,MATHIS,TODD,NULL,Male,African-American,12/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67703,78585,71117,PRETRIAL,Crook,Bridget,NULL,Female,Caucasian,05/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +67703,78585,71117,PRETRIAL,Crook,Bridget,NULL,Female,Caucasian,05/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,9,High,New,1,0 +67703,78585,71117,PRETRIAL,Crook,Bridget,NULL,Female,Caucasian,05/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +67709,78592,71123,Probation,Gallo,Vincent,NULL,Male,Caucasian,09/30/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/13/14 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,New,1,0 +67709,78592,71123,Probation,Gallo,Vincent,NULL,Male,Caucasian,09/30/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/13/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +67709,78592,71123,Probation,Gallo,Vincent,NULL,Male,Caucasian,09/30/44,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67726,78619,71144,PRETRIAL,grady,robert,NULL,Male,Caucasian,07/06/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/13/14 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +67726,78619,71144,PRETRIAL,grady,robert,NULL,Male,Caucasian,07/06/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/13/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +67726,78619,71144,PRETRIAL,grady,robert,NULL,Male,Caucasian,07/06/56,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67731,78626,71150,Probation,Antunez,Oslin,NULL,Male,Hispanic,10/18/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +67731,78626,71150,Probation,Antunez,Oslin,NULL,Male,Hispanic,10/18/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +67731,78626,71150,Probation,Antunez,Oslin,NULL,Male,Hispanic,10/18/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67697,78577,71109,PRETRIAL,Jones,Franklin,R,Male,African-American,11/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +67697,78577,71109,PRETRIAL,Jones,Franklin,R,Male,African-American,11/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +67697,78577,71109,PRETRIAL,Jones,Franklin,R,Male,African-American,11/18/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +67702,78584,71116,PRETRIAL,Robinson,Quincel,Martell,Male,African-American,06/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +67702,78584,71116,PRETRIAL,Robinson,Quincel,Martell,Male,African-American,06/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,1.34,10,High,New,1,0 +67702,78584,71116,PRETRIAL,Robinson,Quincel,Martell,Male,African-American,06/16/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67732,78627,71151,Probation,Marjakangas,Ina,NULL,Female,Caucasian,07/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +67732,78627,71151,Probation,Marjakangas,Ina,NULL,Female,Caucasian,07/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +67732,78627,71151,Probation,Marjakangas,Ina,NULL,Female,Caucasian,07/28/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67718,78605,71134,Probation,Gruschow,Kenneth,NULL,Male,Caucasian,07/20/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/13/14 0:00,1,Low,7,Risk of Violence,-4.1,1,Low,New,1,0 +67718,78605,71134,Probation,Gruschow,Kenneth,NULL,Male,Caucasian,07/20/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/13/14 0:00,1,Low,8,Risk of Recidivism,-3.1,1,Low,New,1,0 +67718,78605,71134,Probation,Gruschow,Kenneth,NULL,Male,Caucasian,07/20/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +48415,78606,49103,PRETRIAL,Liatsos,Denise,NULL,Female,Caucasian,04/14/62,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,11/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.18,1,Low,Copy,1,0 +48415,78606,49103,PRETRIAL,Liatsos,Denise,NULL,Female,Caucasian,04/14/62,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,11/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,Copy,1,0 +48415,78606,49103,PRETRIAL,Liatsos,Denise,NULL,Female,Caucasian,04/14/62,17,All Scales,Intake,English,Post Sentence,Probation,Divorced,11/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +12086,31842,29094,PRETRIAL,AARON,JARVIS,NULL,Male,African-American,07/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +12086,31842,29094,PRETRIAL,AARON,JARVIS,NULL,Male,African-American,07/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +12086,31842,29094,PRETRIAL,AARON,JARVIS,NULL,Male,African-American,07/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59236,78597,71127,PRETRIAL,Mallen,Michael,NULL,Male,Caucasian,11/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +59236,78597,71127,PRETRIAL,Mallen,Michael,NULL,Male,Caucasian,11/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +59236,78597,71127,PRETRIAL,Mallen,Michael,NULL,Male,Caucasian,11/25/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +66843,78614,70140,Probation,DeFrancesco,Paul,NULL,Male,Caucasian,03/13/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +66843,78614,70140,Probation,DeFrancesco,Paul,NULL,Male,Caucasian,03/13/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-1.35,1,Low,New,1,0 +66843,78614,70140,Probation,DeFrancesco,Paul,NULL,Male,Caucasian,03/13/83,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67696,78576,71108,PRETRIAL,Marquez,Daniel,Alex,Male,Hispanic,12/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +67696,78576,71108,PRETRIAL,Marquez,Daniel,Alex,Male,Hispanic,12/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +67696,78576,71108,PRETRIAL,Marquez,Daniel,Alex,Male,Hispanic,12/07/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +34539,78593,65804,Probation,LOGAN,KAZEMBE,ATIBA,Male,African-American,05/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,4,High,7,Risk of Violence,-1.14,8,High,Copy,1,0 +34539,78593,65804,Probation,LOGAN,KAZEMBE,ATIBA,Male,African-American,05/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,4,High,8,Risk of Recidivism,0.88,10,High,Copy,1,0 +34539,78593,65804,Probation,LOGAN,KAZEMBE,ATIBA,Male,African-American,05/04/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,4,High,18,Risk of Failure to Appear,34,10,High,Copy,1,0 +67725,78618,71143,PRETRIAL,Lloyd,Lance,NULL,Male,African-American,04/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +67725,78618,71143,PRETRIAL,Lloyd,Lance,NULL,Male,African-American,04/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +67725,78618,71143,PRETRIAL,Lloyd,Lance,NULL,Male,African-American,04/16/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67699,78579,71111,PRETRIAL,Lantigua,Yoziel,NULL,Male,Caucasian,05/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +67699,78579,71111,PRETRIAL,Lantigua,Yoziel,NULL,Male,Caucasian,05/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,6,Medium,New,1,0 +67699,78579,71111,PRETRIAL,Lantigua,Yoziel,NULL,Male,Caucasian,05/24/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67700,78581,71113,PRETRIAL,BAER,ASHLYE,NULL,Female,Caucasian,04/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +67700,78581,71113,PRETRIAL,BAER,ASHLYE,NULL,Female,Caucasian,04/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,4,High,8,Risk of Recidivism,0.18,9,High,New,1,0 +67700,78581,71113,PRETRIAL,BAER,ASHLYE,NULL,Female,Caucasian,04/29/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,4,High,18,Risk of Failure to Appear,30,9,High,New,1,0 +67735,78630,71154,Probation,soto,edelyn,NULL,Female,Hispanic,09/02/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +67735,78630,71154,Probation,soto,edelyn,NULL,Female,Hispanic,09/02/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +67735,78630,71154,Probation,soto,edelyn,NULL,Female,Hispanic,09/02/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67706,78588,71120,Probation,pyburne,francis,NULL,Male,Caucasian,10/05/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +67706,78588,71120,Probation,pyburne,francis,NULL,Male,Caucasian,10/05/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +67706,78588,71120,Probation,pyburne,francis,NULL,Male,Caucasian,10/05/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67728,78623,71147,Probation,Palacios,Juanita,NULL,Female,Hispanic,11/20/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +67728,78623,71147,Probation,Palacios,Juanita,NULL,Female,Hispanic,11/20/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +67728,78623,71147,Probation,Palacios,Juanita,NULL,Female,Hispanic,11/20/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67721,78609,71137,Probation,Thomas,Patrick,NULL,Male,African-American,08/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,2,Medium,7,Risk of Violence,-2.01,4,Low,New,1,0 +67721,78609,71137,Probation,Thomas,Patrick,NULL,Male,African-American,08/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +67721,78609,71137,Probation,Thomas,Patrick,NULL,Male,African-American,08/05/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67162,78616,71141,PRETRIAL,RAMBUS,AMANDA,NULL,Female,Caucasian,06/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.32,3,Low,New,1,0 +67162,78616,71141,PRETRIAL,RAMBUS,AMANDA,NULL,Female,Caucasian,06/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,8,High,New,1,0 +67162,78616,71141,PRETRIAL,RAMBUS,AMANDA,NULL,Female,Caucasian,06/04/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67695,78575,71107,PRETRIAL,Marziano,Angelica,NULL,Female,Caucasian,11/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,2,Medium,7,Risk of Violence,-1.73,6,Medium,New,1,0 +67695,78575,71107,PRETRIAL,Marziano,Angelica,NULL,Female,Caucasian,11/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +67695,78575,71107,PRETRIAL,Marziano,Angelica,NULL,Female,Caucasian,11/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67707,78589,71121,Probation,Houk,Michael,NULL,Male,Caucasian,04/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +67707,78589,71121,Probation,Houk,Michael,NULL,Male,Caucasian,04/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +67707,78589,71121,Probation,Houk,Michael,NULL,Male,Caucasian,04/24/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67729,78622,71146,Probation,Martinez maldonado,Crescencio,NULL,Male,Hispanic,03/08/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +67729,78622,71146,Probation,Martinez maldonado,Crescencio,NULL,Male,Hispanic,03/08/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +67729,78622,71146,Probation,Martinez maldonado,Crescencio,NULL,Male,Hispanic,03/08/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +33428,35570,32532,PRETRIAL,piggott,brian,NULL,Male,Caucasian,01/18/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +33428,35570,32532,PRETRIAL,piggott,brian,NULL,Male,Caucasian,01/18/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +33428,35570,32532,PRETRIAL,piggott,brian,NULL,Male,Caucasian,01/18/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +31116,78580,71112,PRETRIAL,Jeanbaptiste,Terence,NULL,Male,African-American,10/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/13/14 0:00,2,Medium,7,Risk of Violence,-1.6,6,Medium,New,1,0 +31116,78580,71112,PRETRIAL,Jeanbaptiste,Terence,NULL,Male,African-American,10/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +31116,78580,71112,PRETRIAL,Jeanbaptiste,Terence,NULL,Male,African-American,10/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/13/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67736,78631,71155,Probation,Vasquez,Stephanie,NULL,Female,Hispanic,07/25/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +67736,78631,71155,Probation,Vasquez,Stephanie,NULL,Female,Hispanic,07/25/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +67736,78631,71155,Probation,Vasquez,Stephanie,NULL,Female,Hispanic,07/25/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +18102,36315,17375,PRETRIAL,HUGHES,DARREN,NULL,Male,Caucasian,07/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.92,2,Low,Copy,1,0 +18102,36315,17375,PRETRIAL,HUGHES,DARREN,NULL,Male,Caucasian,07/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,Copy,1,0 +18102,36315,17375,PRETRIAL,HUGHES,DARREN,NULL,Male,Caucasian,07/25/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +67722,78610,71138,PRETRIAL,Freeman,George,NULL,Male,African-American,02/24/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +67722,78610,71138,PRETRIAL,Freeman,George,NULL,Male,African-American,02/24/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +67722,78610,71138,PRETRIAL,Freeman,George,NULL,Male,African-American,02/24/51,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67705,78587,71119,Probation,tijean,Wilson,NULL,Male,African-American,08/29/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/13/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +67705,78587,71119,Probation,tijean,Wilson,NULL,Male,African-American,08/29/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/13/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +67705,78587,71119,Probation,tijean,Wilson,NULL,Male,African-American,08/29/74,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67710,78594,71124,PRETRIAL,borges,brett,NULL,Male,Caucasian,06/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +67710,78594,71124,PRETRIAL,borges,brett,NULL,Male,Caucasian,06/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +67710,78594,71124,PRETRIAL,borges,brett,NULL,Male,Caucasian,06/17/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67724,78617,71142,Probation,addison,oliver,NULL,Male,African-American,04/16/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +67724,78617,71142,Probation,addison,oliver,NULL,Male,African-American,04/16/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +67724,78617,71142,Probation,addison,oliver,NULL,Male,African-American,04/16/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +62854,78624,71148,PRETRIAL,Bermudez,Lori,NULL,Female,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,2,Medium,7,Risk of Violence,-2.17,4,Low,New,1,0 +62854,78624,71148,PRETRIAL,Bermudez,Lori,NULL,Female,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,7,Medium,New,1,0 +62854,78624,71148,PRETRIAL,Bermudez,Lori,NULL,Female,Caucasian,09/08/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +67712,78596,71126,PRETRIAL,JOSEPH,FRANTZ,NULL,Male,African-American,06/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +67712,78596,71126,PRETRIAL,JOSEPH,FRANTZ,NULL,Male,African-American,06/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +67712,78596,71126,PRETRIAL,JOSEPH,FRANTZ,NULL,Male,African-American,06/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67409,78615,70807,PRETRIAL,MEZA,WILMOR,NULL,Male,Hispanic,11/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-1.95,5,Medium,Copy,1,0 +67409,78615,70807,PRETRIAL,MEZA,WILMOR,NULL,Male,Hispanic,11/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,Copy,1,0 +67409,78615,70807,PRETRIAL,MEZA,WILMOR,NULL,Male,Hispanic,11/20/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +67733,78628,71152,Probation,Cronrath,Carl,NULL,Male,Caucasian,07/26/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,7,Risk of Violence,-4.49,1,Low,New,1,0 +67733,78628,71152,Probation,Cronrath,Carl,NULL,Male,Caucasian,07/26/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,8,Risk of Recidivism,-2.72,1,Low,New,1,0 +67733,78628,71152,Probation,Cronrath,Carl,NULL,Male,Caucasian,07/26/50,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67708,78591,71122,PRETRIAL,Terrell,William,Robert,Male,Caucasian,04/07/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/13/14 0:00,1,Low,7,Risk of Violence,-4.5,1,Low,New,1,0 +67708,78591,71122,PRETRIAL,Terrell,William,Robert,Male,Caucasian,04/07/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/13/14 0:00,1,Low,8,Risk of Recidivism,-2.89,1,Low,New,1,0 +67708,78591,71122,PRETRIAL,Terrell,William,Robert,Male,Caucasian,04/07/47,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64568,78620,67593,PRETRIAL,EASTMAN,ALEJANDRO,NULL,Male,Caucasian,11/16/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/13/14 0:00,1,Low,7,Risk of Violence,-4.18,1,Low,Copy,1,0 +64568,78620,67593,PRETRIAL,EASTMAN,ALEJANDRO,NULL,Male,Caucasian,11/16/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/13/14 0:00,1,Low,8,Risk of Recidivism,-2.5,1,Low,Copy,1,0 +64568,78620,67593,PRETRIAL,EASTMAN,ALEJANDRO,NULL,Male,Caucasian,11/16/44,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +67698,78578,71110,PRETRIAL,Porter,Christopher,Livingston,Male,African-American,02/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.78,5,Medium,New,1,0 +67698,78578,71110,PRETRIAL,Porter,Christopher,Livingston,Male,African-American,02/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,10,High,New,1,0 +67698,78578,71110,PRETRIAL,Porter,Christopher,Livingston,Male,African-American,02/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +40791,78612,71140,PRETRIAL,Mascio,Scott,Thomas,Male,Caucasian,09/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,New,1,0 +40791,78612,71140,PRETRIAL,Mascio,Scott,Thomas,Male,Caucasian,09/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +40791,78612,71140,PRETRIAL,Mascio,Scott,Thomas,Male,Caucasian,09/17/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +49647,78599,59854,PRETRIAL,Dorsey,Trevor,NULL,Male,African-American,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/13/14 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,Copy,1,0 +49647,78599,59854,PRETRIAL,Dorsey,Trevor,NULL,Male,African-American,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,Copy,1,0 +49647,78599,59854,PRETRIAL,Dorsey,Trevor,NULL,Male,African-American,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/13/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +67719,78607,71135,Probation,Walker,Yonel,NULL,Male,African-American,03/11/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,4,High,7,Risk of Violence,-1.24,8,High,New,1,0 +67719,78607,71135,Probation,Walker,Yonel,NULL,Male,African-American,03/11/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,4,High,8,Risk of Recidivism,0.54,9,High,New,1,0 +67719,78607,71135,Probation,Walker,Yonel,NULL,Male,African-American,03/11/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/13/14 0:00,4,High,18,Risk of Failure to Appear,18,2,Low,New,1,0 +67704,78586,71118,PRETRIAL,Mcclam,Javaris,NULL,Male,African-American,08/20/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/14 0:00,4,High,7,Risk of Violence,-0.6,10,High,New,1,0 +67704,78586,71118,PRETRIAL,Mcclam,Javaris,NULL,Male,African-American,08/20/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/14 0:00,4,High,8,Risk of Recidivism,0.61,9,High,New,1,0 +67704,78586,71118,PRETRIAL,Mcclam,Javaris,NULL,Male,African-American,08/20/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/13/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67730,78625,71149,Probation,HOCK,JEFFREY,NULL,Male,Caucasian,10/16/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/13/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +67730,78625,71149,Probation,HOCK,JEFFREY,NULL,Male,Caucasian,10/16/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/13/14 0:00,1,Low,8,Risk of Recidivism,-1.76,1,Low,New,1,0 +67730,78625,71149,Probation,HOCK,JEFFREY,NULL,Male,Caucasian,10/16/48,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/13/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67765,78675,71191,Probation,HUNT,JOHN,W,Male,Caucasian,03/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +67765,78675,71191,Probation,HUNT,JOHN,W,Male,Caucasian,03/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +67765,78675,71191,Probation,HUNT,JOHN,W,Male,Caucasian,03/22/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67751,78654,71175,PRETRIAL,Pinder,Cragory,NULL,Male,African-American,07/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +67751,78654,71175,PRETRIAL,Pinder,Cragory,NULL,Male,African-American,07/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +67751,78654,71175,PRETRIAL,Pinder,Cragory,NULL,Male,African-American,07/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +5750,78672,5377,Probation,Clark,Tron,J,Male,African-American,01/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,Copy,1,0 +5750,78672,5377,Probation,Clark,Tron,J,Male,African-American,01/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,4,High,8,Risk of Recidivism,0.5,9,High,Copy,1,0 +5750,78672,5377,Probation,Clark,Tron,J,Male,African-American,01/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +67737,78633,71156,PRETRIAL,Brown,Shanice,NULL,Female,African-American,08/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +67737,78633,71156,PRETRIAL,Brown,Shanice,NULL,Female,African-American,08/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +67737,78633,71156,PRETRIAL,Brown,Shanice,NULL,Female,African-American,08/31/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67745,78646,71168,PRETRIAL,Ferdinand,Donique,NULL,Male,Other,03/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +67745,78646,71168,PRETRIAL,Ferdinand,Donique,NULL,Male,Other,03/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +67745,78646,71168,PRETRIAL,Ferdinand,Donique,NULL,Male,Other,03/28/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67770,78680,71196,PRETRIAL,Martinez,Randall,NULL,Male,Caucasian,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +67770,78680,71196,PRETRIAL,Martinez,Randall,NULL,Male,Caucasian,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +67770,78680,71196,PRETRIAL,Martinez,Randall,NULL,Male,Caucasian,11/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67762,78670,71188,PRETRIAL,lomberg,tracy,NULL,Female,Caucasian,10/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +67762,78670,71188,PRETRIAL,lomberg,tracy,NULL,Female,Caucasian,10/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +67762,78670,71188,PRETRIAL,lomberg,tracy,NULL,Female,Caucasian,10/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +49455,78641,71163,PRETRIAL,Menendez,Emily,NULL,Female,Hispanic,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +49455,78641,71163,PRETRIAL,Menendez,Emily,NULL,Female,Hispanic,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +49455,78641,71163,PRETRIAL,Menendez,Emily,NULL,Female,Hispanic,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67767,78677,71193,PRETRIAL,Morris,Willie,NULL,Male,African-American,08/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/14 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +67767,78677,71193,PRETRIAL,Morris,Willie,NULL,Male,African-American,08/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +67767,78677,71193,PRETRIAL,Morris,Willie,NULL,Male,African-American,08/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67757,78662,71181,PRETRIAL,Burgess,Voltaire,k,Male,African-American,07/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,4,High,7,Risk of Violence,-0.65,9,High,New,1,0 +67757,78662,71181,PRETRIAL,Burgess,Voltaire,k,Male,African-American,07/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,4,High,8,Risk of Recidivism,0.72,10,High,New,1,0 +67757,78662,71181,PRETRIAL,Burgess,Voltaire,k,Male,African-American,07/25/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +39565,78664,71182,PRETRIAL,WORTHY,SHANE,LAQUONE,Male,African-American,08/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.3,7,Medium,New,1,0 +39565,78664,71182,PRETRIAL,WORTHY,SHANE,LAQUONE,Male,African-American,08/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +39565,78664,71182,PRETRIAL,WORTHY,SHANE,LAQUONE,Male,African-American,08/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +67772,78683,71199,PRETRIAL,Rohman,MD,NULL,Male,Asian,08/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/14/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +67772,78683,71199,PRETRIAL,Rohman,MD,NULL,Male,Asian,08/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/14/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +67772,78683,71199,PRETRIAL,Rohman,MD,NULL,Male,Asian,08/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67774,78685,71201,Probation,Speid,Damian,NULL,Male,African-American,09/14/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.41,3,Low,New,1,0 +67774,78685,71201,Probation,Speid,Damian,NULL,Male,African-American,09/14/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,8,High,New,1,0 +67774,78685,71201,Probation,Speid,Damian,NULL,Male,African-American,09/14/75,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +63670,78645,71167,PRETRIAL,ANDREWS,LAWRENCE,JOSEPH,Male,Caucasian,11/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +63670,78645,71167,PRETRIAL,ANDREWS,LAWRENCE,JOSEPH,Male,Caucasian,11/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +63670,78645,71167,PRETRIAL,ANDREWS,LAWRENCE,JOSEPH,Male,Caucasian,11/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +10005,78638,71160,PRETRIAL,JEANS,WILLIE,NULL,Male,African-American,10/09/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.17,10,High,New,1,0 +10005,78638,71160,PRETRIAL,JEANS,WILLIE,NULL,Male,African-American,10/09/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +10005,78638,71160,PRETRIAL,JEANS,WILLIE,NULL,Male,African-American,10/09/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +67764,78673,71190,PRETRIAL,Myers,Alex,NULL,Male,Caucasian,07/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,11/14/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +67764,78673,71190,PRETRIAL,Myers,Alex,NULL,Male,Caucasian,07/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,11/14/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +67764,78673,71190,PRETRIAL,Myers,Alex,NULL,Male,Caucasian,07/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67749,78652,71173,Probation,Mathis,Jeramy,NULL,Male,African-American,01/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +67749,78652,71173,Probation,Mathis,Jeramy,NULL,Male,African-American,01/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +67749,78652,71173,Probation,Mathis,Jeramy,NULL,Male,African-American,01/08/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67754,78659,71178,PRETRIAL,Richardso9n,Moses,NULL,Male,African-American,04/06/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,4,High,7,Risk of Violence,-0.98,9,High,New,1,0 +67754,78659,71178,PRETRIAL,Richardso9n,Moses,NULL,Male,African-American,04/06/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,4,High,8,Risk of Recidivism,0.64,9,High,New,1,0 +67754,78659,71178,PRETRIAL,Richardso9n,Moses,NULL,Male,African-American,04/06/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,4,High,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +67768,78678,71194,Probation,CANAS,RUBEN,NULL,Male,Hispanic,11/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/14/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +67768,78678,71194,Probation,CANAS,RUBEN,NULL,Male,Hispanic,11/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/14/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +67768,78678,71194,Probation,CANAS,RUBEN,NULL,Male,Hispanic,11/13/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +47092,78682,71198,PRETRIAL,Wilson,John,NULL,Male,Caucasian,04/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +47092,78682,71198,PRETRIAL,Wilson,John,NULL,Male,Caucasian,04/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.09,8,High,New,1,0 +47092,78682,71198,PRETRIAL,Wilson,John,NULL,Male,Caucasian,04/01/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67742,78640,71162,PRETRIAL,Rodriguez,Natalia,NULL,Female,Caucasian,07/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,7,Risk of Violence,-2.34,3,Low,New,1,0 +67742,78640,71162,PRETRIAL,Rodriguez,Natalia,NULL,Female,Caucasian,07/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,New,1,0 +67742,78640,71162,PRETRIAL,Rodriguez,Natalia,NULL,Female,Caucasian,07/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +13745,78657,56237,PRETRIAL,TUTES,RICKY,NULL,Male,African-American,07/21/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,Copy,1,0 +13745,78657,56237,PRETRIAL,TUTES,RICKY,NULL,Male,African-American,07/21/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,Copy,1,0 +13745,78657,56237,PRETRIAL,TUTES,RICKY,NULL,Male,African-American,07/21/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,41,10,High,Copy,1,0 +67739,78636,71158,PRETRIAL,Ramsey,Anthony,Brian,Male,African-American,11/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +67739,78636,71158,PRETRIAL,Ramsey,Anthony,Brian,Male,African-American,11/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +67739,78636,71158,PRETRIAL,Ramsey,Anthony,Brian,Male,African-American,11/15/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +66045,78643,71165,PRETRIAL,Griffin,Roderick,NULL,Male,African-American,11/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +66045,78643,71165,PRETRIAL,Griffin,Roderick,NULL,Male,African-American,11/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +66045,78643,71165,PRETRIAL,Griffin,Roderick,NULL,Male,African-American,11/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67756,78661,71180,Probation,GOMEZBORRERO,JOSE,D,Male,Hispanic,05/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +67756,78661,71180,Probation,GOMEZBORRERO,JOSE,D,Male,Hispanic,05/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +67756,78661,71180,Probation,GOMEZBORRERO,JOSE,D,Male,Hispanic,05/17/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67740,78637,71159,PRETRIAL,Ramos,Peter,Andrew,Male,Caucasian,02/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +67740,78637,71159,PRETRIAL,Ramos,Peter,Andrew,Male,Caucasian,02/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +67740,78637,71159,PRETRIAL,Ramos,Peter,Andrew,Male,Caucasian,02/14/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +15123,78632,14473,PRETRIAL,LIVINGSTON,DERRICK,NULL,Male,African-American,05/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,Copy,1,0 +15123,78632,14473,PRETRIAL,LIVINGSTON,DERRICK,NULL,Male,African-American,05/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,Copy,1,0 +15123,78632,14473,PRETRIAL,LIVINGSTON,DERRICK,NULL,Male,African-American,05/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +67769,78679,71195,Probation,Martin,Timothy,Carl,Male,Native American,07/14/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.31,3,Low,New,1,0 +67769,78679,71195,Probation,Martin,Timothy,Carl,Male,Native American,07/14/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +67769,78679,71195,Probation,Martin,Timothy,Carl,Male,Native American,07/14/83,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +67771,78681,71197,PRETRIAL,Jordan,Alexander,NULL,Male,Caucasian,11/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +67771,78681,71197,PRETRIAL,Jordan,Alexander,NULL,Male,Caucasian,11/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +67771,78681,71197,PRETRIAL,Jordan,Alexander,NULL,Male,Caucasian,11/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67748,78651,71172,PRETRIAL,Pannell,Marco,NULL,Male,African-American,04/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +67748,78651,71172,PRETRIAL,Pannell,Marco,NULL,Male,African-American,04/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +67748,78651,71172,PRETRIAL,Pannell,Marco,NULL,Male,African-American,04/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67750,78653,71174,PRETRIAL,Bryant,James,NULL,Male,African-American,05/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,4,High,7,Risk of Violence,-0.51,10,High,New,1,0 +67750,78653,71174,PRETRIAL,Bryant,James,NULL,Male,African-American,05/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,4,High,8,Risk of Recidivism,0.13,8,High,New,1,0 +67750,78653,71174,PRETRIAL,Bryant,James,NULL,Male,African-American,05/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +16951,78658,16261,Probation,Diaz,Danny,Rafael,Male,Hispanic,06/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,Copy,1,0 +16951,78658,16261,Probation,Diaz,Danny,Rafael,Male,Hispanic,06/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,Copy,1,0 +16951,78658,16261,Probation,Diaz,Danny,Rafael,Male,Hispanic,06/03/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +67755,78660,71179,Probation,Asprilla,Andres,NULL,Male,Hispanic,12/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +67755,78660,71179,Probation,Asprilla,Andres,NULL,Male,Hispanic,12/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +67755,78660,71179,Probation,Asprilla,Andres,NULL,Male,Hispanic,12/12/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67741,78639,71161,PRETRIAL,Sapp,Kandyce,D,Male,African-American,01/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.43,7,Medium,New,1,0 +67741,78639,71161,PRETRIAL,Sapp,Kandyce,D,Male,African-American,01/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +67741,78639,71161,PRETRIAL,Sapp,Kandyce,D,Male,African-American,01/30/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67738,78635,71157,PRETRIAL,Davis,Martin,Miguel,Male,Hispanic,11/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/14/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +67738,78635,71157,PRETRIAL,Davis,Martin,Miguel,Male,Hispanic,11/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/14/14 0:00,1,Low,8,Risk of Recidivism,-2.05,1,Low,New,1,0 +67738,78635,71157,PRETRIAL,Davis,Martin,Miguel,Male,Hispanic,11/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67744,78644,71166,PRETRIAL,Poe,Brandon,Gene,Male,Caucasian,05/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +67744,78644,71166,PRETRIAL,Poe,Brandon,Gene,Male,Caucasian,05/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +67744,78644,71166,PRETRIAL,Poe,Brandon,Gene,Male,Caucasian,05/27/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67761,78669,71187,Probation,Sanchez,Steve,NULL,Male,Hispanic,08/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +67761,78669,71187,Probation,Sanchez,Steve,NULL,Male,Hispanic,08/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +67761,78669,71187,Probation,Sanchez,Steve,NULL,Male,Hispanic,08/02/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +16607,78674,15920,PRETRIAL,Jackson,Jamal,NULL,Male,African-American,03/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,4,High,7,Risk of Violence,-0.67,9,High,Copy,1,0 +16607,78674,15920,PRETRIAL,Jackson,Jamal,NULL,Male,African-American,03/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,4,High,8,Risk of Recidivism,1.04,10,High,Copy,1,0 +16607,78674,15920,PRETRIAL,Jackson,Jamal,NULL,Male,African-American,03/13/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +67746,78648,71170,PRETRIAL,Francois,Jovaney,Lentz,Male,African-American,11/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +67746,78648,71170,PRETRIAL,Francois,Jovaney,Lentz,Male,African-American,11/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +67746,78648,71170,PRETRIAL,Francois,Jovaney,Lentz,Male,African-American,11/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +51037,78665,71183,Probation,Walls,Sergio,NULL,Male,African-American,05/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.84,5,Medium,New,1,0 +51037,78665,71183,Probation,Walls,Sergio,NULL,Male,African-American,05/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.63,10,High,New,1,0 +51037,78665,71183,Probation,Walls,Sergio,NULL,Male,African-American,05/29/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +5532,78634,5188,PRETRIAL,SUFRA,VLADIMIR,N,Female,African-American,04/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,Copy,1,0 +5532,78634,5188,PRETRIAL,SUFRA,VLADIMIR,N,Female,African-American,04/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,Copy,1,0 +5532,78634,5188,PRETRIAL,SUFRA,VLADIMIR,N,Female,African-American,04/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +67773,78684,71200,Probation,briefman,elyse,NULL,Female,Caucasian,04/14/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/14/14 0:00,1,Low,7,Risk of Violence,-4.12,1,Low,New,1,0 +67773,78684,71200,Probation,briefman,elyse,NULL,Female,Caucasian,04/14/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/14/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +67773,78684,71200,Probation,briefman,elyse,NULL,Female,Caucasian,04/14/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +64593,78647,71169,PRETRIAL,Fox,James,NULL,Male,Caucasian,08/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-1.91,5,Medium,New,1,0 +64593,78647,71169,PRETRIAL,Fox,James,NULL,Male,Caucasian,08/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-0.46,5,Medium,New,1,0 +64593,78647,71169,PRETRIAL,Fox,James,NULL,Male,Caucasian,08/03/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +66894,78663,70192,PRETRIAL,MCDONALD,CHRISTOPHER,NULL,Male,Caucasian,12/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.29,3,Low,Copy,1,0 +66894,78663,70192,PRETRIAL,MCDONALD,CHRISTOPHER,NULL,Male,Caucasian,12/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,Copy,1,0 +66894,78663,70192,PRETRIAL,MCDONALD,CHRISTOPHER,NULL,Male,Caucasian,12/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/14/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +67743,78642,71164,PRETRIAL,Thomas,Winnidella,Theresa,Female,Other,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +67743,78642,71164,PRETRIAL,Thomas,Winnidella,Theresa,Female,Other,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +67743,78642,71164,PRETRIAL,Thomas,Winnidella,Theresa,Female,Other,08/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67747,78650,71171,PRETRIAL,Cortes,Anthony,NULL,Male,Caucasian,02/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,7,Risk of Violence,-2.69,2,Low,New,1,0 +67747,78650,71171,PRETRIAL,Cortes,Anthony,NULL,Male,Caucasian,02/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +67747,78650,71171,PRETRIAL,Cortes,Anthony,NULL,Male,Caucasian,02/21/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/14/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67760,78668,71186,Probation,Spartz,Robert,NULL,Male,Caucasian,04/28/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,7,Risk of Violence,-3.94,1,Low,New,1,0 +67760,78668,71186,Probation,Spartz,Robert,NULL,Male,Caucasian,04/28/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +67760,78668,71186,Probation,Spartz,Robert,NULL,Male,Caucasian,04/28/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67763,78671,71189,Probation,Palombi,Gary,Lee,Male,Caucasian,12/08/47,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/14/14 0:00,1,Low,7,Risk of Violence,-4.48,1,Low,New,1,0 +67763,78671,71189,Probation,Palombi,Gary,Lee,Male,Caucasian,12/08/47,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/14/14 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +67763,78671,71189,Probation,Palombi,Gary,Lee,Male,Caucasian,12/08/47,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/14/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +6022,78689,71205,Probation,Lawrence,Danterious,NULL,Male,African-American,12/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,4,High,7,Risk of Violence,-0.27,10,High,New,1,0 +6022,78689,71205,Probation,Lawrence,Danterious,NULL,Male,African-American,12/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,4,High,8,Risk of Recidivism,0.73,10,High,New,1,0 +6022,78689,71205,Probation,Lawrence,Danterious,NULL,Male,African-American,12/19/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +23254,24456,22442,PRETRIAL,THOMAS,RONNIE,NULL,Male,African-American,05/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +23254,24456,22442,PRETRIAL,THOMAS,RONNIE,NULL,Male,African-American,05/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +23254,24456,22442,PRETRIAL,THOMAS,RONNIE,NULL,Male,African-American,05/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67792,78710,71224,PRETRIAL,FRANCIS,ATON,NULL,Male,African-American,04/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +67792,78710,71224,PRETRIAL,FRANCIS,ATON,NULL,Male,African-American,04/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +67792,78710,71224,PRETRIAL,FRANCIS,ATON,NULL,Male,African-American,04/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67783,78697,71213,PRETRIAL,AUSTIN,FREDERIC,F,Male,African-American,03/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/15/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +67783,78697,71213,PRETRIAL,AUSTIN,FREDERIC,F,Male,African-American,03/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/15/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +67783,78697,71213,PRETRIAL,AUSTIN,FREDERIC,F,Male,African-American,03/11/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67779,78692,71208,PRETRIAL,Oliver,Brandee,NULL,Female,African-American,03/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +67779,78692,71208,PRETRIAL,Oliver,Brandee,NULL,Female,African-American,03/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +67779,78692,71208,PRETRIAL,Oliver,Brandee,NULL,Female,African-American,03/08/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67787,78705,71219,PRETRIAL,Linares,Elizabeth,NULL,Female,Caucasian,11/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,7,Risk of Violence,-3.38,1,Low,New,1,0 +67787,78705,71219,PRETRIAL,Linares,Elizabeth,NULL,Female,Caucasian,11/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +67787,78705,71219,PRETRIAL,Linares,Elizabeth,NULL,Female,Caucasian,11/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67781,78695,71211,PRETRIAL,HILL,VIVIAN,MARKELAND,Male,African-American,04/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +67781,78695,71211,PRETRIAL,HILL,VIVIAN,MARKELAND,Male,African-American,04/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +67781,78695,71211,PRETRIAL,HILL,VIVIAN,MARKELAND,Male,African-American,04/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67777,78690,71206,PRETRIAL,PITTS,IVORY,NULL,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.12,4,Low,New,1,0 +67777,78690,71206,PRETRIAL,PITTS,IVORY,NULL,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +67777,78690,71206,PRETRIAL,PITTS,IVORY,NULL,Male,African-American,11/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67786,78704,71218,PRETRIAL,Kokay,Beth,Ann,Female,Caucasian,01/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,2,Medium,7,Risk of Violence,-2.61,2,Low,New,1,0 +67786,78704,71218,PRETRIAL,Kokay,Beth,Ann,Female,Caucasian,01/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +67786,78704,71218,PRETRIAL,Kokay,Beth,Ann,Female,Caucasian,01/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67784,78700,71215,PRETRIAL,COMEAUX,KENT,ALAN,Male,Caucasian,01/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/15/14 0:00,1,Low,7,Risk of Violence,-3.9,1,Low,New,1,0 +67784,78700,71215,PRETRIAL,COMEAUX,KENT,ALAN,Male,Caucasian,01/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/15/14 0:00,1,Low,8,Risk of Recidivism,-2.37,1,Low,New,1,0 +67784,78700,71215,PRETRIAL,COMEAUX,KENT,ALAN,Male,Caucasian,01/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/15/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +23254,78711,22442,PRETRIAL,THOMAS,RONNIE,NULL,Male,African-American,05/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,Copy,1,0 +23254,78711,22442,PRETRIAL,THOMAS,RONNIE,NULL,Male,African-American,05/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,Copy,1,0 +23254,78711,22442,PRETRIAL,THOMAS,RONNIE,NULL,Male,African-American,05/20/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +67776,78688,71204,PRETRIAL,ROBINSON,TAVARIS,NULL,Male,African-American,06/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +67776,78688,71204,PRETRIAL,ROBINSON,TAVARIS,NULL,Male,African-American,06/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.5,9,High,New,1,0 +67776,78688,71204,PRETRIAL,ROBINSON,TAVARIS,NULL,Male,African-American,06/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +65935,78699,71214,PRETRIAL,Lee,Jamarion,NULL,Male,African-American,07/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,4,High,7,Risk of Violence,-0.79,9,High,New,1,0 +65935,78699,71214,PRETRIAL,Lee,Jamarion,NULL,Male,African-American,07/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,4,High,8,Risk of Recidivism,0.5,9,High,New,1,0 +65935,78699,71214,PRETRIAL,Lee,Jamarion,NULL,Male,African-American,07/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67785,78703,71217,PRETRIAL,Muringer,David,Michael,Male,Caucasian,10/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,2,Medium,7,Risk of Violence,-2.95,1,Low,New,1,0 +67785,78703,71217,PRETRIAL,Muringer,David,Michael,Male,Caucasian,10/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,2,Medium,8,Risk of Recidivism,0,7,Medium,New,1,0 +67785,78703,71217,PRETRIAL,Muringer,David,Michael,Male,Caucasian,10/30/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +67790,78708,71222,PRETRIAL,gray,tamika,NULL,Female,African-American,06/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +67790,78708,71222,PRETRIAL,gray,tamika,NULL,Female,African-American,06/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.96,10,High,New,1,0 +67790,78708,71222,PRETRIAL,gray,tamika,NULL,Female,African-American,06/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +34055,78687,71203,PRETRIAL,brutus,maslin,NULL,Male,African-American,03/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +34055,78687,71203,PRETRIAL,brutus,maslin,NULL,Male,African-American,03/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +34055,78687,71203,PRETRIAL,brutus,maslin,NULL,Male,African-American,03/16/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67782,78696,71212,PRETRIAL,LLOYD,DURAN,MICHAEL,Male,African-American,08/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,4,High,7,Risk of Violence,-0.92,9,High,New,1,0 +67782,78696,71212,PRETRIAL,LLOYD,DURAN,MICHAEL,Male,African-American,08/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,4,High,8,Risk of Recidivism,0.94,10,High,New,1,0 +67782,78696,71212,PRETRIAL,LLOYD,DURAN,MICHAEL,Male,African-American,08/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67780,78694,71210,PRETRIAL,Gonzaga,Justin,NULL,Male,Caucasian,06/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +67780,78694,71210,PRETRIAL,Gonzaga,Justin,NULL,Male,Caucasian,06/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +67780,78694,71210,PRETRIAL,Gonzaga,Justin,NULL,Male,Caucasian,06/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +22653,78698,21831,PRETRIAL,LEWIS,CALVIN,NULL,Male,African-American,08/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,Copy,1,0 +22653,78698,21831,PRETRIAL,LEWIS,CALVIN,NULL,Male,African-American,08/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,Copy,1,0 +22653,78698,21831,PRETRIAL,LEWIS,CALVIN,NULL,Male,African-American,08/11/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +67778,78691,71207,PRETRIAL,LUX,MICHAEL,NULL,Male,Caucasian,01/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +67778,78691,71207,PRETRIAL,LUX,MICHAEL,NULL,Male,Caucasian,01/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +67778,78691,71207,PRETRIAL,LUX,MICHAEL,NULL,Male,Caucasian,01/08/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67788,78706,71220,PRETRIAL,ORTIZRUBIO,EDUARDO,NULL,Male,Hispanic,10/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +67788,78706,71220,PRETRIAL,ORTIZRUBIO,EDUARDO,NULL,Male,Hispanic,10/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +67788,78706,71220,PRETRIAL,ORTIZRUBIO,EDUARDO,NULL,Male,Hispanic,10/08/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +9115,78701,8648,PRETRIAL,BAPTISTE,REGINALD,NULL,Male,African-American,03/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.23,4,Low,Copy,1,0 +9115,78701,8648,PRETRIAL,BAPTISTE,REGINALD,NULL,Male,African-American,03/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,Copy,1,0 +9115,78701,8648,PRETRIAL,BAPTISTE,REGINALD,NULL,Male,African-American,03/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +43572,78693,71209,PRETRIAL,Merilus,Pierre,NULL,Male,African-American,03/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.77,5,Medium,New,1,0 +43572,78693,71209,PRETRIAL,Merilus,Pierre,NULL,Male,African-American,03/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +43572,78693,71209,PRETRIAL,Merilus,Pierre,NULL,Male,African-American,03/31/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67804,78722,71234,PRETRIAL,Wilson,Walter,NULL,Male,African-American,02/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +67804,78722,71234,PRETRIAL,Wilson,Walter,NULL,Male,African-American,02/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +67804,78722,71234,PRETRIAL,Wilson,Walter,NULL,Male,African-American,02/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67815,78735,71241,PRETRIAL,GREIGG,MICHELLE,NULL,Female,African-American,10/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +67815,78735,71241,PRETRIAL,GREIGG,MICHELLE,NULL,Female,African-American,10/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +67815,78735,71241,PRETRIAL,GREIGG,MICHELLE,NULL,Female,African-American,10/06/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +59539,68259,61886,PRETRIAL,MURPHY,ROBERT,NULL,Male,Caucasian,02/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/16/14 0:00,2,Medium,7,Risk of Violence,-3.21,1,Low,New,1,0 +59539,68259,61886,PRETRIAL,MURPHY,ROBERT,NULL,Male,Caucasian,02/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +59539,68259,61886,PRETRIAL,MURPHY,ROBERT,NULL,Male,Caucasian,02/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/16/14 0:00,2,Medium,18,Risk of Failure to Appear,30,8,High,New,1,0 +67802,78719,71232,PRETRIAL,Jusino,Tanya,NULL,Female,Caucasian,05/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +67802,78719,71232,PRETRIAL,Jusino,Tanya,NULL,Female,Caucasian,05/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +67802,78719,71232,PRETRIAL,Jusino,Tanya,NULL,Female,Caucasian,05/23/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67800,78717,71230,PRETRIAL,Williams,James,NULL,Male,African-American,02/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +67800,78717,71230,PRETRIAL,Williams,James,NULL,Male,African-American,02/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +67800,78717,71230,PRETRIAL,Williams,James,NULL,Male,African-American,02/22/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67795,78715,71228,PRETRIAL,Cela,Christine,NULL,Female,Caucasian,11/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +67795,78715,71228,PRETRIAL,Cela,Christine,NULL,Female,Caucasian,11/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +67795,78715,71228,PRETRIAL,Cela,Christine,NULL,Female,Caucasian,11/21/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67806,78724,71236,PRETRIAL,NUNEZ,FREDDY,ALEXANDER,Male,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +67806,78724,71236,PRETRIAL,NUNEZ,FREDDY,ALEXANDER,Male,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +67806,78724,71236,PRETRIAL,NUNEZ,FREDDY,ALEXANDER,Male,Caucasian,04/19/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67818,78738,71244,PRETRIAL,Martin,Jermey,NULL,Male,Caucasian,10/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +67818,78738,71244,PRETRIAL,Martin,Jermey,NULL,Male,Caucasian,10/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +67818,78738,71244,PRETRIAL,Martin,Jermey,NULL,Male,Caucasian,10/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67814,78733,71240,PRETRIAL,ATHANASAW,ALEXANDER,NULL,Male,Caucasian,06/28/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +67814,78733,71240,PRETRIAL,ATHANASAW,ALEXANDER,NULL,Male,Caucasian,06/28/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +67814,78733,71240,PRETRIAL,ATHANASAW,ALEXANDER,NULL,Male,Caucasian,06/28/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67793,78712,71225,PRETRIAL,Gossett,Lynette,NULL,Female,Caucasian,10/22/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/16/14 0:00,1,Low,7,Risk of Violence,-3.99,1,Low,New,1,0 +67793,78712,71225,PRETRIAL,Gossett,Lynette,NULL,Female,Caucasian,10/22/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/16/14 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +67793,78712,71225,PRETRIAL,Gossett,Lynette,NULL,Female,Caucasian,10/22/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +29998,78729,28970,Probation,WILLIAMS,Bilal,NULL,Male,African-American,05/12/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,Copy,1,0 +29998,78729,28970,Probation,WILLIAMS,Bilal,NULL,Male,African-American,05/12/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.68,10,High,Copy,1,0 +29998,78729,28970,Probation,WILLIAMS,Bilal,NULL,Male,African-American,05/12/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,39,10,High,Copy,1,0 +67805,78723,71235,PRETRIAL,CHIRONNO,ROBERT,JOHN,Male,Caucasian,09/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +67805,78723,71235,PRETRIAL,CHIRONNO,ROBERT,JOHN,Male,Caucasian,09/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +67805,78723,71235,PRETRIAL,CHIRONNO,ROBERT,JOHN,Male,Caucasian,09/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67799,78716,71229,PRETRIAL,Daurel,Carl,NULL,Male,Other,12/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +67799,78716,71229,PRETRIAL,Daurel,Carl,NULL,Male,Other,12/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +67799,78716,71229,PRETRIAL,Daurel,Carl,NULL,Male,Other,12/23/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67808,78730,71238,PRETRIAL,LEWIS,FRERICK,NULL,Male,African-American,06/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +67808,78730,71238,PRETRIAL,LEWIS,FRERICK,NULL,Male,African-American,06/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +67808,78730,71238,PRETRIAL,LEWIS,FRERICK,NULL,Male,African-American,06/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67813,78732,71239,PRETRIAL,Shim,Craig,NULL,Male,Other,03/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +67813,78732,71239,PRETRIAL,Shim,Craig,NULL,Male,Other,03/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +67813,78732,71239,PRETRIAL,Shim,Craig,NULL,Male,Other,03/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +46840,78725,47296,PRETRIAL,spence,frankie,NULL,Female,African-American,11/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,7,Risk of Violence,-3.11,1,Low,Copy,1,0 +46840,78725,47296,PRETRIAL,spence,frankie,NULL,Female,African-American,11/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.49,6,Medium,Copy,1,0 +46840,78725,47296,PRETRIAL,spence,frankie,NULL,Female,African-American,11/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,Copy,1,0 +67822,78742,71247,PRETRIAL,PERKINS,BISHUP,NULL,Male,African-American,08/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +67822,78742,71247,PRETRIAL,PERKINS,BISHUP,NULL,Male,African-American,08/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +67822,78742,71247,PRETRIAL,PERKINS,BISHUP,NULL,Male,African-American,08/29/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +49960,78720,50902,PRETRIAL,Charles,Davidson,NULL,Male,African-American,02/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,7,Risk of Violence,-1.87,5,Medium,Copy,1,0 +49960,78720,50902,PRETRIAL,Charles,Davidson,NULL,Male,African-American,02/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,Copy,1,0 +49960,78720,50902,PRETRIAL,Charles,Davidson,NULL,Male,African-American,02/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +57040,78734,59123,PRETRIAL,Uter,Andre,NULL,Male,African-American,05/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,Copy,1,0 +57040,78734,59123,PRETRIAL,Uter,Andre,NULL,Male,African-American,05/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,Copy,1,0 +57040,78734,59123,PRETRIAL,Uter,Andre,NULL,Male,African-American,05/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,Copy,1,0 +67821,78741,71246,PRETRIAL,Evans,Howard,NULL,Male,African-American,09/28/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,4,High,7,Risk of Violence,-1.04,8,High,New,1,0 +67821,78741,71246,PRETRIAL,Evans,Howard,NULL,Male,African-American,09/28/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,4,High,8,Risk of Recidivism,0.36,9,High,New,1,0 +67821,78741,71246,PRETRIAL,Evans,Howard,NULL,Male,African-American,09/28/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67807,78726,71237,PRETRIAL,Tarbet,Barry,NULL,Male,Caucasian,09/29/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/16/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +67807,78726,71237,PRETRIAL,Tarbet,Barry,NULL,Male,Caucasian,09/29/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/16/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +67807,78726,71237,PRETRIAL,Tarbet,Barry,NULL,Male,Caucasian,09/29/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67594,78728,70996,PRETRIAL,Khan,Alexander,NULL,Male,Caucasian,06/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.29,7,Medium,Copy,1,0 +67594,78728,70996,PRETRIAL,Khan,Alexander,NULL,Male,Caucasian,06/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,Copy,1,0 +67594,78728,70996,PRETRIAL,Khan,Alexander,NULL,Male,Caucasian,06/10/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +67794,78713,71226,PRETRIAL,Perez,Robernis,NULL,Male,Caucasian,07/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +67794,78713,71226,PRETRIAL,Perez,Robernis,NULL,Male,Caucasian,07/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +67794,78713,71226,PRETRIAL,Perez,Robernis,NULL,Male,Caucasian,07/16/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +59539,78731,61886,PRETRIAL,MURPHY,ROBERT,NULL,Male,Caucasian,02/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/16/14 0:00,2,Medium,7,Risk of Violence,-3.24,1,Low,Copy,1,0 +59539,78731,61886,PRETRIAL,MURPHY,ROBERT,NULL,Male,Caucasian,02/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,Copy,1,0 +59539,78731,61886,PRETRIAL,MURPHY,ROBERT,NULL,Male,Caucasian,02/20/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/16/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +67817,78739,71243,PRETRIAL,PORTNOY,ISAAC,NULL,Male,Hispanic,04/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,Copy,1,0 +67817,78739,71243,PRETRIAL,PORTNOY,ISAAC,NULL,Male,Hispanic,04/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,Copy,1,0 +67817,78739,71243,PRETRIAL,PORTNOY,ISAAC,NULL,Male,Hispanic,04/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +67801,78718,71231,PRETRIAL,Chironno,John,Angelo,Male,Caucasian,11/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +67801,78718,71231,PRETRIAL,Chironno,John,Angelo,Male,Caucasian,11/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +67801,78718,71231,PRETRIAL,Chironno,John,Angelo,Male,Caucasian,11/23/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67816,78736,71242,PRETRIAL,Hart,Amanda,NULL,Female,Caucasian,09/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +67816,78736,71242,PRETRIAL,Hart,Amanda,NULL,Female,Caucasian,09/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +67816,78736,71242,PRETRIAL,Hart,Amanda,NULL,Female,Caucasian,09/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67830,78757,71257,Probation,Baker,Javarius,NULL,Male,African-American,10/18/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/17/14 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,New,1,0 +67830,78757,71257,Probation,Baker,Javarius,NULL,Male,African-American,10/18/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +67830,78757,71257,Probation,Baker,Javarius,NULL,Male,African-American,10/18/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/17/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67824,78744,71249,PRETRIAL,Martinez,Sequoia,L,Female,Caucasian,05/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,2,Medium,7,Risk of Violence,-1.76,5,Medium,New,1,0 +67824,78744,71249,PRETRIAL,Martinez,Sequoia,L,Female,Caucasian,05/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,7,Medium,New,1,0 +67824,78744,71249,PRETRIAL,Martinez,Sequoia,L,Female,Caucasian,05/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +27213,78778,71277,Probation,carvalho,ligia,NULL,Female,Caucasian,06/01/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +27213,78778,71277,Probation,carvalho,ligia,NULL,Female,Caucasian,06/01/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +27213,78778,71277,Probation,carvalho,ligia,NULL,Female,Caucasian,06/01/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +22610,78747,21786,Probation,james,terrell,NULL,Male,African-American,03/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,2,Medium,7,Risk of Violence,-2.23,4,Low,Copy,1,0 +22610,78747,21786,Probation,james,terrell,NULL,Male,African-American,03/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,Copy,1,0 +22610,78747,21786,Probation,james,terrell,NULL,Male,African-American,03/08/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +67834,78762,71262,Probation,Toliver,Yadeja,NULL,Female,African-American,12/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +67834,78762,71262,Probation,Toliver,Yadeja,NULL,Female,African-American,12/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +67834,78762,71262,Probation,Toliver,Yadeja,NULL,Female,African-American,12/07/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +67847,78783,71282,Probation,breland,jason,NULL,Male,Caucasian,07/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +67847,78783,71282,Probation,breland,jason,NULL,Male,Caucasian,07/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +67847,78783,71282,Probation,breland,jason,NULL,Male,Caucasian,07/29/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +63291,78770,71269,PRETRIAL,ketchum,christopher,NULL,Male,Caucasian,08/16/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +63291,78770,71269,PRETRIAL,ketchum,christopher,NULL,Male,Caucasian,08/16/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +63291,78770,71269,PRETRIAL,ketchum,christopher,NULL,Male,Caucasian,08/16/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +7271,26726,24475,PRETRIAL,SHAW,SHAWN,ROSS,Male,Caucasian,07/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,2,Medium,7,Risk of Violence,-1.71,6,Medium,New,1,0 +7271,26726,24475,PRETRIAL,SHAW,SHAWN,ROSS,Male,Caucasian,07/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +7271,26726,24475,PRETRIAL,SHAW,SHAWN,ROSS,Male,Caucasian,07/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67684,78767,71093,PRETRIAL,Brown,Raechel,NULL,Female,Caucasian,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,Copy,1,0 +67684,78767,71093,PRETRIAL,Brown,Raechel,NULL,Female,Caucasian,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,Copy,1,0 +67684,78767,71093,PRETRIAL,Brown,Raechel,NULL,Female,Caucasian,02/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +67843,78776,71275,Probation,JEAN,AVONETTE,NULL,Female,African-American,09/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/17/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +67843,78776,71275,Probation,JEAN,AVONETTE,NULL,Female,African-American,09/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/17/14 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +67843,78776,71275,Probation,JEAN,AVONETTE,NULL,Female,African-American,09/06/82,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67141,77874,70485,PRETRIAL,BECK,ANGELA,NULL,Female,Caucasian,07/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +67141,77874,70485,PRETRIAL,BECK,ANGELA,NULL,Female,Caucasian,07/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-0.62,5,Medium,New,1,0 +67141,77874,70485,PRETRIAL,BECK,ANGELA,NULL,Female,Caucasian,07/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +66395,78746,71251,PRETRIAL,BRITO,PEDRO,O,Male,Hispanic,10/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +66395,78746,71251,PRETRIAL,BRITO,PEDRO,O,Male,Hispanic,10/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +66395,78746,71251,PRETRIAL,BRITO,PEDRO,O,Male,Hispanic,10/26/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67835,78763,71263,PRETRIAL,Higgs,Gregory,NULL,Male,African-American,02/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/17/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +67835,78763,71263,PRETRIAL,Higgs,Gregory,NULL,Male,African-American,02/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +67835,78763,71263,PRETRIAL,Higgs,Gregory,NULL,Male,African-American,02/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +61440,78772,71271,PRETRIAL,ANDERSON,AHKEEM,NULL,Male,African-American,08/21/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.37,7,Medium,New,1,0 +61440,78772,71271,PRETRIAL,ANDERSON,AHKEEM,NULL,Male,African-American,08/21/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,8,High,New,1,0 +61440,78772,71271,PRETRIAL,ANDERSON,AHKEEM,NULL,Male,African-American,08/21/89,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67845,78779,71278,Probation,MCKENZIE,DARRON,C,Male,African-American,07/24/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,New,1,0 +67845,78779,71278,Probation,MCKENZIE,DARRON,C,Male,African-American,07/24/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +67845,78779,71278,Probation,MCKENZIE,DARRON,C,Male,African-American,07/24/64,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +67846,78781,71280,Probation,Marques,Christopher,NULL,Male,Caucasian,09/01/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +67846,78781,71280,Probation,Marques,Christopher,NULL,Male,Caucasian,09/01/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +67846,78781,71280,Probation,Marques,Christopher,NULL,Male,Caucasian,09/01/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +5601,78753,71254,PRETRIAL,Conley,Jeffrey,Allen,Male,Caucasian,06/30/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/17/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +5601,78753,71254,PRETRIAL,Conley,Jeffrey,Allen,Male,Caucasian,06/30/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +5601,78753,71254,PRETRIAL,Conley,Jeffrey,Allen,Male,Caucasian,06/30/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,31,9,High,New,1,0 +23175,78758,71258,PRETRIAL,Rozo,maria,NULL,Female,Hispanic,02/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +23175,78758,71258,PRETRIAL,Rozo,maria,NULL,Female,Hispanic,02/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.46,2,Low,New,1,0 +23175,78758,71258,PRETRIAL,Rozo,maria,NULL,Female,Hispanic,02/03/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +67832,78760,71260,PRETRIAL,Vasquez,Carlos,NULL,Male,Hispanic,01/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/17/14 0:00,1,Low,7,Risk of Violence,-2.38,3,Low,New,1,0 +67832,78760,71260,PRETRIAL,Vasquez,Carlos,NULL,Male,Hispanic,01/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +67832,78760,71260,PRETRIAL,Vasquez,Carlos,NULL,Male,Hispanic,01/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67839,78774,71273,PRETRIAL,LYNCH,DOMINIC,NULL,Male,African-American,06/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +67839,78774,71273,PRETRIAL,LYNCH,DOMINIC,NULL,Male,African-American,06/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.52,9,High,New,1,0 +67839,78774,71273,PRETRIAL,LYNCH,DOMINIC,NULL,Male,African-American,06/09/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +41699,78780,71279,PRETRIAL,GRADY,BROOKLYN,KEYSHAWN,Female,African-American,09/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +41699,78780,71279,PRETRIAL,GRADY,BROOKLYN,KEYSHAWN,Female,African-American,09/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,8,High,New,1,0 +41699,78780,71279,PRETRIAL,GRADY,BROOKLYN,KEYSHAWN,Female,African-American,09/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +61235,70322,63765,PRETRIAL,Cochran,Michael,NULL,Male,Caucasian,06/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +61235,70322,63765,PRETRIAL,Cochran,Michael,NULL,Male,Caucasian,06/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +61235,70322,63765,PRETRIAL,Cochran,Michael,NULL,Male,Caucasian,06/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67827,78750,71253,Probation,candelario,william,NULL,Male,Caucasian,01/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,New,1,0 +67827,78750,71253,Probation,candelario,william,NULL,Male,Caucasian,01/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +67827,78750,71253,Probation,candelario,william,NULL,Male,Caucasian,01/16/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +29311,78768,71267,PRETRIAL,McLaughlin,Delmar,A,Male,Other,09/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +29311,78768,71267,PRETRIAL,McLaughlin,Delmar,A,Male,Other,09/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +29311,78768,71267,PRETRIAL,McLaughlin,Delmar,A,Male,Other,09/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67841,78775,71274,PRETRIAL,Snyder,Daniel,NULL,Male,Caucasian,11/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,11/17/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +67841,78775,71274,PRETRIAL,Snyder,Daniel,NULL,Male,Caucasian,11/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +67841,78775,71274,PRETRIAL,Snyder,Daniel,NULL,Male,Caucasian,11/20/78,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67828,78754,71255,Probation,Shryack,John,NULL,Male,Caucasian,01/05/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/17/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +67828,78754,71255,Probation,Shryack,John,NULL,Male,Caucasian,01/05/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +67828,78754,71255,Probation,Shryack,John,NULL,Male,Caucasian,01/05/53,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +776,78771,71270,PRETRIAL,ODONNELL,RYAN,NULL,Male,Caucasian,12/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/17/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +776,78771,71270,PRETRIAL,ODONNELL,RYAN,NULL,Male,Caucasian,12/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/17/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +776,78771,71270,PRETRIAL,ODONNELL,RYAN,NULL,Male,Caucasian,12/02/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67840,78773,71272,PRETRIAL,hernandez,adrian,NULL,Male,Hispanic,08/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-3.31,1,Low,New,1,0 +67840,78773,71272,PRETRIAL,hernandez,adrian,NULL,Male,Hispanic,08/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +67840,78773,71272,PRETRIAL,hernandez,adrian,NULL,Male,Hispanic,08/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +60008,78752,62388,PRETRIAL,JOHNSON,STEVIE,LAMAR,Male,African-American,07/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/17/14 0:00,2,Medium,7,Risk of Violence,-2.5,3,Low,Copy,1,0 +60008,78752,62388,PRETRIAL,JOHNSON,STEVIE,LAMAR,Male,African-American,07/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,Copy,1,0 +60008,78752,62388,PRETRIAL,JOHNSON,STEVIE,LAMAR,Male,African-American,07/31/70,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/17/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +67831,78759,71259,Probation,Canosa,Daniel,NULL,Male,Caucasian,05/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +67831,78759,71259,Probation,Canosa,Daniel,NULL,Male,Caucasian,05/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +67831,78759,71259,Probation,Canosa,Daniel,NULL,Male,Caucasian,05/28/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67837,78766,71266,Probation,BOUCUGNANY,RODOLFO,NULL,Male,Hispanic,07/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +67837,78766,71266,Probation,BOUCUGNANY,RODOLFO,NULL,Male,Hispanic,07/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +67837,78766,71266,Probation,BOUCUGNANY,RODOLFO,NULL,Male,Hispanic,07/14/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67825,78745,71250,PRETRIAL,TORRES,ALEJANDRO,FERNANDO,Male,Other,12/12/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/17/14 0:00,1,Low,7,Risk of Violence,-4.45,1,Low,New,1,0 +67825,78745,71250,PRETRIAL,TORRES,ALEJANDRO,FERNANDO,Male,Other,12/12/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/17/14 0:00,1,Low,8,Risk of Recidivism,-3.21,1,Low,New,1,0 +67825,78745,71250,PRETRIAL,TORRES,ALEJANDRO,FERNANDO,Male,Other,12/12/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +7877,78764,71264,PRETRIAL,SMITH,STEPHEN,WILLIAMS,Male,Caucasian,05/20/81,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,New,1,0 +7877,78764,71264,PRETRIAL,SMITH,STEPHEN,WILLIAMS,Male,Caucasian,05/20/81,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,2,Medium,8,Risk of Recidivism,0.16,7,Medium,New,1,0 +7877,78764,71264,PRETRIAL,SMITH,STEPHEN,WILLIAMS,Male,Caucasian,05/20/81,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,2,Medium,18,Risk of Failure to Appear,29,7,Medium,New,1,0 +67829,78756,71256,PRETRIAL,MARTIN,DANNY,NULL,Male,African-American,10/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/17/14 0:00,2,Medium,7,Risk of Violence,-3.5,1,Low,New,1,0 +67829,78756,71256,PRETRIAL,MARTIN,DANNY,NULL,Male,African-American,10/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +67829,78756,71256,PRETRIAL,MARTIN,DANNY,NULL,Male,African-American,10/27/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/17/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67844,78777,71276,Probation,Brown,Candice,NULL,Female,Caucasian,11/06/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.74,2,Low,New,1,0 +67844,78777,71276,Probation,Brown,Candice,NULL,Female,Caucasian,11/06/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,10,High,New,1,0 +67844,78777,71276,Probation,Brown,Candice,NULL,Female,Caucasian,11/06/79,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67848,78784,71283,PRETRIAL,Ferguson,Ivan,NULL,Male,African-American,01/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +67848,78784,71283,PRETRIAL,Ferguson,Ivan,NULL,Male,African-American,01/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +67848,78784,71283,PRETRIAL,Ferguson,Ivan,NULL,Male,African-American,01/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67838,78769,71268,Probation,manchola,carolina,NULL,Female,Hispanic,05/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/17/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +67838,78769,71268,Probation,manchola,carolina,NULL,Female,Hispanic,05/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.45,2,Low,New,1,0 +67838,78769,71268,Probation,manchola,carolina,NULL,Female,Hispanic,05/24/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +7271,78748,24475,PRETRIAL,SHAW,SHAWN,ROSS,Male,Caucasian,07/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,2,Medium,7,Risk of Violence,-1.91,5,Medium,Copy,1,0 +7271,78748,24475,PRETRIAL,SHAW,SHAWN,ROSS,Male,Caucasian,07/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,2,Medium,8,Risk of Recidivism,0.04,7,Medium,Copy,1,0 +7271,78748,24475,PRETRIAL,SHAW,SHAWN,ROSS,Male,Caucasian,07/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/17/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +45343,78782,71281,PRETRIAL,Ogden,Ezra,Christophe,Male,Caucasian,07/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +45343,78782,71281,PRETRIAL,Ogden,Ezra,Christophe,Male,Caucasian,07/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +45343,78782,71281,PRETRIAL,Ogden,Ezra,Christophe,Male,Caucasian,07/09/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67823,78743,71248,PRETRIAL,BURKE,ORAL,DWAYNE,Male,African-American,09/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-3.57,1,Low,New,1,0 +67823,78743,71248,PRETRIAL,BURKE,ORAL,DWAYNE,Male,African-American,09/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +67823,78743,71248,PRETRIAL,BURKE,ORAL,DWAYNE,Male,African-American,09/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67833,78761,71261,Probation,conn,rebecca,NULL,Female,Caucasian,02/24/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +67833,78761,71261,Probation,conn,rebecca,NULL,Female,Caucasian,02/24/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +67833,78761,71261,Probation,conn,rebecca,NULL,Female,Caucasian,02/24/63,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67663,78811,71066,PRETRIAL,Porras,Robert,louis,Male,Caucasian,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.54,6,Medium,Copy,1,0 +67663,78811,71066,PRETRIAL,Porras,Robert,louis,Male,Caucasian,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,Copy,1,0 +67663,78811,71066,PRETRIAL,Porras,Robert,louis,Male,Caucasian,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +67854,78790,71289,PRETRIAL,Gardner,kerisha,NULL,Female,Other,09/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/18/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +67854,78790,71289,PRETRIAL,Gardner,kerisha,NULL,Female,Other,09/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/18/14 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +67854,78790,71289,PRETRIAL,Gardner,kerisha,NULL,Female,Other,09/26/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +67861,78803,71296,PRETRIAL,Foster,Letitia,NULL,Female,African-American,09/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +67861,78803,71296,PRETRIAL,Foster,Letitia,NULL,Female,African-American,09/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +67861,78803,71296,PRETRIAL,Foster,Letitia,NULL,Female,African-American,09/09/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67865,78808,71301,Probation,Valera,Oscar,NULL,Male,Hispanic,06/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/18/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +67865,78808,71301,Probation,Valera,Oscar,NULL,Male,Hispanic,06/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/18/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +67865,78808,71301,Probation,Valera,Oscar,NULL,Male,Hispanic,06/15/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +18766,78805,71298,PRETRIAL,Javaris,Shields,NULL,Male,African-American,05/31/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/14 0:00,1,Low,7,Risk of Violence,-2.23,4,Low,New,1,0 +18766,78805,71298,PRETRIAL,Javaris,Shields,NULL,Male,African-American,05/31/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +18766,78805,71298,PRETRIAL,Javaris,Shields,NULL,Male,African-American,05/31/91,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67863,78806,71299,Probation,Holloway,Nehekia,Nicole,Female,African-American,05/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/14 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +67863,78806,71299,Probation,Holloway,Nehekia,Nicole,Female,African-American,05/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,7,Medium,New,1,0 +67863,78806,71299,Probation,Holloway,Nehekia,Nicole,Female,African-American,05/27/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67860,78798,71295,Probation,Bethea,Tony,NULL,Male,African-American,08/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,New,1,0 +67860,78798,71295,Probation,Bethea,Tony,NULL,Male,African-American,08/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,New,1,0 +67860,78798,71295,Probation,Bethea,Tony,NULL,Male,African-American,08/07/65,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,37,10,High,New,1,0 +8061,78813,71303,PRETRIAL,Hodge,Kerry,NULL,Male,African-American,10/10/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +8061,78813,71303,PRETRIAL,Hodge,Kerry,NULL,Male,African-American,10/10/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +8061,78813,71303,PRETRIAL,Hodge,Kerry,NULL,Male,African-American,10/10/81,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/18/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +67849,78785,71284,PRETRIAL,QUINTANA,FELIX,CARLOS,Male,Caucasian,11/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.2,8,High,New,1,0 +67849,78785,71284,PRETRIAL,QUINTANA,FELIX,CARLOS,Male,Caucasian,11/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +67849,78785,71284,PRETRIAL,QUINTANA,FELIX,CARLOS,Male,Caucasian,11/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67855,78792,71290,PRETRIAL,Saintlouis,Cherline,NULL,Female,African-American,08/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +67855,78792,71290,PRETRIAL,Saintlouis,Cherline,NULL,Female,African-American,08/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,1,Low,8,Risk of Recidivism,-1.21,3,Low,New,1,0 +67855,78792,71290,PRETRIAL,Saintlouis,Cherline,NULL,Female,African-American,08/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67859,78796,71294,Probation,RAMBARRAT,BRIAN,NULL,Male,Other,08/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +67859,78796,71294,Probation,RAMBARRAT,BRIAN,NULL,Male,Other,08/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/14 0:00,1,Low,8,Risk of Recidivism,-1.1,2,Low,New,1,0 +67859,78796,71294,Probation,RAMBARRAT,BRIAN,NULL,Male,Other,08/07/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67868,78815,71304,PRETRIAL,MORTIMER,CARMELLA,NULL,Female,Caucasian,06/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/18/14 0:00,2,Medium,7,Risk of Violence,-3.49,1,Low,New,1,0 +67868,78815,71304,PRETRIAL,MORTIMER,CARMELLA,NULL,Female,Caucasian,06/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.45,6,Medium,New,1,0 +67868,78815,71304,PRETRIAL,MORTIMER,CARMELLA,NULL,Female,Caucasian,06/06/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/18/14 0:00,2,Medium,18,Risk of Failure to Appear,30,9,High,New,1,0 +67857,78794,71292,PRETRIAL,Mutrux,Jason,Christophe,Male,Caucasian,01/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,2,Medium,7,Risk of Violence,-2.9,2,Low,New,1,0 +67857,78794,71292,PRETRIAL,Mutrux,Jason,Christophe,Male,Caucasian,01/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +67857,78794,71292,PRETRIAL,Mutrux,Jason,Christophe,Male,Caucasian,01/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67869,78817,71306,PRETRIAL,CLEMONS,MICHELLE,NULL,Female,African-American,04/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.3,3,Low,New,1,0 +67869,78817,71306,PRETRIAL,CLEMONS,MICHELLE,NULL,Female,African-American,04/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.94,10,High,New,1,0 +67869,78817,71306,PRETRIAL,CLEMONS,MICHELLE,NULL,Female,African-American,04/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +67851,78787,71286,PRETRIAL,MENDONCA,MANUEL,VITORINO,Male,Caucasian,06/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +67851,78787,71286,PRETRIAL,MENDONCA,MANUEL,VITORINO,Male,Caucasian,06/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +67851,78787,71286,PRETRIAL,MENDONCA,MANUEL,VITORINO,Male,Caucasian,06/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67853,78789,71288,PRETRIAL,Kulack,Louis,NULL,Male,Caucasian,11/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +67853,78789,71288,PRETRIAL,Kulack,Louis,NULL,Male,Caucasian,11/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +67853,78789,71288,PRETRIAL,Kulack,Louis,NULL,Male,Caucasian,11/30/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +7106,78801,71216,PRETRIAL,Westbrook,Jermaine,NULL,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,Copy,1,0 +7106,78801,71216,PRETRIAL,Westbrook,Jermaine,NULL,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.88,10,High,Copy,1,0 +7106,78801,71216,PRETRIAL,Westbrook,Jermaine,NULL,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +7106,78810,71216,PRETRIAL,Westbrook,Jermaine,NULL,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,Copy,1,0 +7106,78810,71216,PRETRIAL,Westbrook,Jermaine,NULL,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.88,10,High,Copy,1,0 +7106,78810,71216,PRETRIAL,Westbrook,Jermaine,NULL,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +67852,78788,71287,PRETRIAL,George,Johnnie,Edward,Male,African-American,11/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +67852,78788,71287,PRETRIAL,George,Johnnie,Edward,Male,African-American,11/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +67852,78788,71287,PRETRIAL,George,Johnnie,Edward,Male,African-American,11/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +17958,78802,37463,PRETRIAL,Duarte,David,A,Male,African-American,12/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +17958,78802,37463,PRETRIAL,Duarte,David,A,Male,African-American,12/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +17958,78802,37463,PRETRIAL,Duarte,David,A,Male,African-American,12/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +37726,78816,71305,Probation,Cerros,Raul,NULL,Male,Hispanic,03/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/18/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +37726,78816,71305,Probation,Cerros,Raul,NULL,Male,Hispanic,03/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/18/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +37726,78816,71305,Probation,Cerros,Raul,NULL,Male,Hispanic,03/21/71,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +7106,78702,71216,PRETRIAL,Westbrook,Jermaine,NULL,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.59,6,Medium,New,1,0 +7106,78702,71216,PRETRIAL,Westbrook,Jermaine,NULL,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.88,10,High,New,1,0 +7106,78702,71216,PRETRIAL,Westbrook,Jermaine,NULL,Male,African-American,10/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67856,78793,71291,PRETRIAL,Ingham,Jennifer,NULL,Female,Caucasian,07/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,2,Medium,7,Risk of Violence,-2.32,3,Low,New,1,0 +67856,78793,71291,PRETRIAL,Ingham,Jennifer,NULL,Female,Caucasian,07/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.4,6,Medium,New,1,0 +67856,78793,71291,PRETRIAL,Ingham,Jennifer,NULL,Female,Caucasian,07/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67870,78818,71307,PRETRIAL,Thomas,Christopher,Shawn,Male,Caucasian,10/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +67870,78818,71307,PRETRIAL,Thomas,Christopher,Shawn,Male,Caucasian,10/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +67870,78818,71307,PRETRIAL,Thomas,Christopher,Shawn,Male,Caucasian,10/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +54595,78797,56281,PRETRIAL,BARR,WILLIAM,NULL,Male,African-American,12/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,2,Medium,7,Risk of Violence,-2.54,3,Low,Copy,1,0 +54595,78797,56281,PRETRIAL,BARR,WILLIAM,NULL,Male,African-American,12/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,Copy,1,0 +54595,78797,56281,PRETRIAL,BARR,WILLIAM,NULL,Male,African-American,12/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +67463,78791,70867,PRETRIAL,Aaron,william,P,Male,African-American,11/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.16,4,Low,Copy,1,0 +67463,78791,70867,PRETRIAL,Aaron,william,P,Male,African-American,11/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.38,9,High,Copy,1,0 +67463,78791,70867,PRETRIAL,Aaron,william,P,Male,African-American,11/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +67867,78812,71302,Probation,Skaare,Kevin,NULL,Male,Caucasian,04/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +67867,78812,71302,Probation,Skaare,Kevin,NULL,Male,Caucasian,04/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +67867,78812,71302,Probation,Skaare,Kevin,NULL,Male,Caucasian,04/23/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67862,78804,71297,Probation,Beaton,Tamura,NULL,Female,Caucasian,01/04/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/14 0:00,1,Low,7,Risk of Violence,-3.78,1,Low,New,1,0 +67862,78804,71297,Probation,Beaton,Tamura,NULL,Female,Caucasian,01/04/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/14 0:00,1,Low,8,Risk of Recidivism,-1.5,2,Low,New,1,0 +67862,78804,71297,Probation,Beaton,Tamura,NULL,Female,Caucasian,01/04/60,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67864,78807,71300,Probation,ramirez,jose,NULL,Male,Caucasian,01/10/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/18/14 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +67864,78807,71300,Probation,ramirez,jose,NULL,Male,Caucasian,01/10/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/18/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +67864,78807,71300,Probation,ramirez,jose,NULL,Male,Caucasian,01/10/55,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67850,78786,71285,PRETRIAL,Vassar,Max,NULL,Male,Other,03/29/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/14 0:00,1,Low,7,Risk of Violence,-3.79,1,Low,New,1,0 +67850,78786,71285,PRETRIAL,Vassar,Max,NULL,Male,Other,03/29/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +67850,78786,71285,PRETRIAL,Vassar,Max,NULL,Male,Other,03/29/50,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/18/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67876,78825,71313,PRETRIAL,BROWN,JAMES,ALFRED,Male,African-American,10/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +67876,78825,71313,PRETRIAL,BROWN,JAMES,ALFRED,Male,African-American,10/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +67876,78825,71313,PRETRIAL,BROWN,JAMES,ALFRED,Male,African-American,10/06/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67883,78833,71321,PRETRIAL,Walker,Fernando,Leon,Male,African-American,12/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +67883,78833,71321,PRETRIAL,Walker,Fernando,Leon,Male,African-American,12/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +67883,78833,71321,PRETRIAL,Walker,Fernando,Leon,Male,African-American,12/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67872,78820,71309,PRETRIAL,Walsh,Michael,NULL,Male,Caucasian,11/02/39,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/19/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +67872,78820,71309,PRETRIAL,Walsh,Michael,NULL,Male,Caucasian,11/02/39,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/19/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +67872,78820,71309,PRETRIAL,Walsh,Michael,NULL,Male,Caucasian,11/02/39,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67889,78841,71329,PRETRIAL,Walton,Crystal,Dawn,Female,African-American,10/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +67889,78841,71329,PRETRIAL,Walton,Crystal,Dawn,Female,African-American,10/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,1,Low,8,Risk of Recidivism,-0.94,4,Low,New,1,0 +67889,78841,71329,PRETRIAL,Walton,Crystal,Dawn,Female,African-American,10/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +67879,78828,71316,PRETRIAL,VANVLIET,NATHANIEL,NULL,Male,Caucasian,04/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.88,5,Medium,New,1,0 +67879,78828,71316,PRETRIAL,VANVLIET,NATHANIEL,NULL,Male,Caucasian,04/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +67879,78828,71316,PRETRIAL,VANVLIET,NATHANIEL,NULL,Male,Caucasian,04/14/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +67894,78844,71332,PRETRIAL,POZO,ELIZABETH,NULL,Female,Caucasian,01/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +67894,78844,71332,PRETRIAL,POZO,ELIZABETH,NULL,Female,Caucasian,01/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +67894,78844,71332,PRETRIAL,POZO,ELIZABETH,NULL,Female,Caucasian,01/23/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +43996,78839,71327,Probation,Alderson,Dale,NULL,Male,Caucasian,02/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +43996,78839,71327,Probation,Alderson,Dale,NULL,Male,Caucasian,02/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +43996,78839,71327,Probation,Alderson,Dale,NULL,Male,Caucasian,02/14/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67875,78823,71312,PRETRIAL,jarhiyah,Jathiyah,NULL,Female,African-American,05/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +67875,78823,71312,PRETRIAL,jarhiyah,Jathiyah,NULL,Female,African-American,05/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +67875,78823,71312,PRETRIAL,jarhiyah,Jathiyah,NULL,Female,African-American,05/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +67887,78837,71325,Probation,Frye,Eric,NULL,Male,Caucasian,03/22/68,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/19/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +67887,78837,71325,Probation,Frye,Eric,NULL,Male,Caucasian,03/22/68,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/19/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +67887,78837,71325,Probation,Frye,Eric,NULL,Male,Caucasian,03/22/68,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +36253,78831,71319,PRETRIAL,SURF,DAVID,VERNAL,Male,African-American,08/05/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +36253,78831,71319,PRETRIAL,SURF,DAVID,VERNAL,Male,African-American,08/05/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +36253,78831,71319,PRETRIAL,SURF,DAVID,VERNAL,Male,African-American,08/05/74,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67874,78822,71311,PRETRIAL,HENDRICKS,CAMILLE,NULL,Female,African-American,06/24/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +67874,78822,71311,PRETRIAL,HENDRICKS,CAMILLE,NULL,Female,African-American,06/24/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +67874,78822,71311,PRETRIAL,HENDRICKS,CAMILLE,NULL,Female,African-American,06/24/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67888,78840,71328,Probation,Lessa,Rodrigo,NULL,Male,Other,07/24/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/19/14 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +67888,78840,71328,Probation,Lessa,Rodrigo,NULL,Male,Other,07/24/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/19/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +67888,78840,71328,Probation,Lessa,Rodrigo,NULL,Male,Other,07/24/93,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67886,78836,71324,Probation,COWAN,TIMOTHY,W,Male,Caucasian,12/27/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +67886,78836,71324,Probation,COWAN,TIMOTHY,W,Male,Caucasian,12/27/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +67886,78836,71324,Probation,COWAN,TIMOTHY,W,Male,Caucasian,12/27/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +16324,78838,71326,Probation,RODRIGUEZCUELLAR,SANDRA,PATRICIA,Female,Hispanic,07/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +16324,78838,71326,Probation,RODRIGUEZCUELLAR,SANDRA,PATRICIA,Female,Hispanic,07/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +16324,78838,71326,Probation,RODRIGUEZCUELLAR,SANDRA,PATRICIA,Female,Hispanic,07/20/88,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67877,78826,71314,PRETRIAL,smart,sylvester,NULL,Male,African-American,11/25/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.25,3,Low,New,1,0 +67877,78826,71314,PRETRIAL,smart,sylvester,NULL,Male,African-American,11/25/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +67877,78826,71314,PRETRIAL,smart,sylvester,NULL,Male,African-American,11/25/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +67878,78827,71315,PRETRIAL,weiner,michael,NULL,Male,Caucasian,08/21/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/19/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +67878,78827,71315,PRETRIAL,weiner,michael,NULL,Male,Caucasian,08/21/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/19/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +67878,78827,71315,PRETRIAL,weiner,michael,NULL,Male,Caucasian,08/21/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67884,78834,71322,Probation,Sales,Julio,NULL,Male,Hispanic,11/07/70,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Separated,11/19/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +67884,78834,71322,Probation,Sales,Julio,NULL,Male,Hispanic,11/07/70,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Separated,11/19/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +67884,78834,71322,Probation,Sales,Julio,NULL,Male,Hispanic,11/07/70,22,Risk and Prescreen,Intake,English,Pretrial,Probation,Separated,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67890,78842,71330,Probation,HYPPOLITE,LESSELY,NULL,Male,Other,03/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +67890,78842,71330,Probation,HYPPOLITE,LESSELY,NULL,Male,Other,03/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +67890,78842,71330,Probation,HYPPOLITE,LESSELY,NULL,Male,Other,03/06/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67880,78829,71317,Probation,Higuera,Jaime,NULL,Male,Hispanic,09/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,7,Risk of Violence,-3.39,1,Low,New,1,0 +67880,78829,71317,Probation,Higuera,Jaime,NULL,Male,Hispanic,09/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +67880,78829,71317,Probation,Higuera,Jaime,NULL,Male,Hispanic,09/20/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67873,78821,71310,PRETRIAL,ARBE,JOHN,NULL,Male,Caucasian,10/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +67873,78821,71310,PRETRIAL,ARBE,JOHN,NULL,Male,Caucasian,10/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +67873,78821,71310,PRETRIAL,ARBE,JOHN,NULL,Male,Caucasian,10/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/19/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +67917,78871,71356,Probation,HEBERT,CHARLES,NULL,Male,Caucasian,01/14/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +67917,78871,71356,Probation,HEBERT,CHARLES,NULL,Male,Caucasian,01/14/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +67917,78871,71356,Probation,HEBERT,CHARLES,NULL,Male,Caucasian,01/14/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67900,78850,71338,PRETRIAL,MONTI,KRISTY,MARIE,Female,Caucasian,11/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/20/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +67900,78850,71338,PRETRIAL,MONTI,KRISTY,MARIE,Female,Caucasian,11/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/20/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +67900,78850,71338,PRETRIAL,MONTI,KRISTY,MARIE,Female,Caucasian,11/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67914,78868,71353,Probation,Whetsel,Jonathan,NULL,Male,Caucasian,09/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/20/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +67914,78868,71353,Probation,Whetsel,Jonathan,NULL,Male,Caucasian,09/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/20/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +67914,78868,71353,Probation,Whetsel,Jonathan,NULL,Male,Caucasian,09/12/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67912,78863,71350,PRETRIAL,Salas,Juan,NULL,Male,Hispanic,01/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +67912,78863,71350,PRETRIAL,Salas,Juan,NULL,Male,Hispanic,01/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +67912,78863,71350,PRETRIAL,Salas,Juan,NULL,Male,Hispanic,01/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67921,78876,71361,Probation,Hewitt,Robert,NULL,Male,African-American,07/04/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,2,Medium,7,Risk of Violence,-1.46,7,Medium,New,1,0 +67921,78876,71361,Probation,Hewitt,Robert,NULL,Male,African-American,07/04/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +67921,78876,71361,Probation,Hewitt,Robert,NULL,Male,African-American,07/04/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67905,78855,71343,PRETRIAL,Lamothe,Immaculee,V,Female,Other,02/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +67905,78855,71343,PRETRIAL,Lamothe,Immaculee,V,Female,Other,02/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +67905,78855,71343,PRETRIAL,Lamothe,Immaculee,V,Female,Other,02/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67897,78847,71335,PRETRIAL,Smith,Shannell,Lerhonda,Female,African-American,02/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,7,Risk of Violence,-2.09,4,Low,New,1,0 +67897,78847,71335,PRETRIAL,Smith,Shannell,Lerhonda,Female,African-American,02/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,8,Risk of Recidivism,-0.82,4,Low,New,1,0 +67897,78847,71335,PRETRIAL,Smith,Shannell,Lerhonda,Female,African-American,02/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67919,78873,71358,PRETRIAL,Darville,Joseph,NULL,Male,African-American,11/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +67919,78873,71358,PRETRIAL,Darville,Joseph,NULL,Male,African-American,11/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +67919,78873,71358,PRETRIAL,Darville,Joseph,NULL,Male,African-American,11/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67902,78852,71340,PRETRIAL,Gauthier,Anderson,F,Male,Other,02/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +67902,78852,71340,PRETRIAL,Gauthier,Anderson,F,Male,Other,02/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,8,Risk of Recidivism,-1.24,2,Low,New,1,0 +67902,78852,71340,PRETRIAL,Gauthier,Anderson,F,Male,Other,02/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67910,78859,71347,Probation,Derosa,Glenn,NULL,Male,Caucasian,06/19/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/20/14 0:00,1,Low,7,Risk of Violence,-4.17,1,Low,New,1,0 +67910,78859,71347,Probation,Derosa,Glenn,NULL,Male,Caucasian,06/19/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/20/14 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +67910,78859,71347,Probation,Derosa,Glenn,NULL,Male,Caucasian,06/19/62,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67688,78866,71098,PRETRIAL,TAFT,WILLIAM,NULL,Male,Caucasian,12/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,Copy,1,0 +67688,78866,71098,PRETRIAL,TAFT,WILLIAM,NULL,Male,Caucasian,12/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,Copy,1,0 +67688,78866,71098,PRETRIAL,TAFT,WILLIAM,NULL,Male,Caucasian,12/27/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +67355,78861,70745,PRETRIAL,Clarke,Kamille,NULL,Female,African-American,09/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/14 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,Copy,1,0 +67355,78861,70745,PRETRIAL,Clarke,Kamille,NULL,Female,African-American,09/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.37,6,Medium,Copy,1,0 +67355,78861,70745,PRETRIAL,Clarke,Kamille,NULL,Female,African-American,09/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +67907,78857,71345,PRETRIAL,Stephens,Stacee,Lee,Female,Caucasian,03/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.91,2,Low,New,1,0 +67907,78857,71345,PRETRIAL,Stephens,Stacee,Lee,Female,Caucasian,03/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +67907,78857,71345,PRETRIAL,Stephens,Stacee,Lee,Female,Caucasian,03/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +67930,78878,71363,PRETRIAL,Falcon,Steven,Valentine,Male,Caucasian,11/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +67930,78878,71363,PRETRIAL,Falcon,Steven,Valentine,Male,Caucasian,11/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +67930,78878,71363,PRETRIAL,Falcon,Steven,Valentine,Male,Caucasian,11/11/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +51850,78874,71359,PRETRIAL,Butler,Reginald,Elsworth,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +51850,78874,71359,PRETRIAL,Butler,Reginald,Elsworth,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +51850,78874,71359,PRETRIAL,Butler,Reginald,Elsworth,Male,African-American,04/28/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51314,71821,65126,PRETRIAL,Gaskin,Russell,Bernard,Male,African-American,08/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,4,High,7,Risk of Violence,-0.94,9,High,New,1,0 +51314,71821,65126,PRETRIAL,Gaskin,Russell,Bernard,Male,African-American,08/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,4,High,8,Risk of Recidivism,0.2,8,High,New,1,0 +51314,71821,65126,PRETRIAL,Gaskin,Russell,Bernard,Male,African-American,08/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67901,78851,71339,PRETRIAL,Moss,Devonte,Keon,Male,African-American,01/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.05,8,High,New,1,0 +67901,78851,71339,PRETRIAL,Moss,Devonte,Keon,Male,African-American,01/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +67901,78851,71339,PRETRIAL,Moss,Devonte,Keon,Male,African-American,01/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67903,78853,71341,PRETRIAL,Farnan,Thomas,Scott,Male,Caucasian,01/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,7,Risk of Violence,-2.37,3,Low,New,1,0 +67903,78853,71341,PRETRIAL,Farnan,Thomas,Scott,Male,Caucasian,01/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +67903,78853,71341,PRETRIAL,Farnan,Thomas,Scott,Male,Caucasian,01/15/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67908,78858,71346,Probation,Butler,Kellie,Lynn,Female,Caucasian,07/22/72,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,11/20/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +67908,78858,71346,Probation,Butler,Kellie,Lynn,Female,Caucasian,07/22/72,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,11/20/14 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +67908,78858,71346,Probation,Butler,Kellie,Lynn,Female,Caucasian,07/22/72,22,Risk and Prescreen,Intake,English,Other,Probation,Widowed,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +54383,78879,56013,Probation,Simtatis,Jose,NULL,Male,Hispanic,06/21/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,1,Low,7,Risk of Violence,-4.06,1,Low,Copy,1,0 +54383,78879,56013,Probation,Simtatis,Jose,NULL,Male,Hispanic,06/21/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,1,Low,8,Risk of Recidivism,-2.28,1,Low,Copy,1,0 +54383,78879,56013,Probation,Simtatis,Jose,NULL,Male,Hispanic,06/21/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +67915,78869,71354,PRETRIAL,Thornton,Trevor,NULL,Male,African-American,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +67915,78869,71354,PRETRIAL,Thornton,Trevor,NULL,Male,African-American,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +67915,78869,71354,PRETRIAL,Thornton,Trevor,NULL,Male,African-American,11/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +67898,78848,71336,PRETRIAL,RAMOS,MICHAEL,ANTHONY,Male,Caucasian,08/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,4,High,7,Risk of Violence,-0.61,10,High,New,1,0 +67898,78848,71336,PRETRIAL,RAMOS,MICHAEL,ANTHONY,Male,Caucasian,08/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,4,High,8,Risk of Recidivism,0.23,8,High,New,1,0 +67898,78848,71336,PRETRIAL,RAMOS,MICHAEL,ANTHONY,Male,Caucasian,08/30/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,4,High,18,Risk of Failure to Appear,39,10,High,New,1,0 +51314,78865,65126,PRETRIAL,Gaskin,Russell,Bernard,Male,African-American,08/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,4,High,7,Risk of Violence,-0.94,9,High,Copy,1,0 +51314,78865,65126,PRETRIAL,Gaskin,Russell,Bernard,Male,African-American,08/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,4,High,8,Risk of Recidivism,0.28,8,High,Copy,1,0 +51314,78865,65126,PRETRIAL,Gaskin,Russell,Bernard,Male,African-American,08/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,4,High,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +67899,78849,71337,PRETRIAL,JENKINS,ARTHUR,NULL,Male,African-American,03/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/20/14 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +67899,78849,71337,PRETRIAL,JENKINS,ARTHUR,NULL,Male,African-American,03/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/20/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +67899,78849,71337,PRETRIAL,JENKINS,ARTHUR,NULL,Male,African-American,03/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67911,78862,71349,PRETRIAL,HINES,THOMAS,NULL,Male,Caucasian,11/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/14 0:00,1,Low,7,Risk of Violence,-4.05,1,Low,New,1,0 +67911,78862,71349,PRETRIAL,HINES,THOMAS,NULL,Male,Caucasian,11/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/14 0:00,1,Low,8,Risk of Recidivism,-2.73,1,Low,New,1,0 +67911,78862,71349,PRETRIAL,HINES,THOMAS,NULL,Male,Caucasian,11/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +67913,78864,71351,Probation,agnew,james,NULL,Male,Caucasian,12/19/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/20/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,New,1,0 +67913,78864,71351,Probation,agnew,james,NULL,Male,Caucasian,12/19/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/20/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +67913,78864,71351,Probation,agnew,james,NULL,Male,Caucasian,12/19/59,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +67906,78856,71344,PRETRIAL,Douglas,Jason,NULL,Male,Other,11/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/14 0:00,1,Low,7,Risk of Violence,-2.43,3,Low,New,1,0 +67906,78856,71344,PRETRIAL,Douglas,Jason,NULL,Male,Other,11/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +67906,78856,71344,PRETRIAL,Douglas,Jason,NULL,Male,Other,11/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +54383,61708,56013,Probation,Simtatis,Jose,NULL,Male,Hispanic,06/21/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +54383,61708,56013,Probation,Simtatis,Jose,NULL,Male,Hispanic,06/21/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +54383,61708,56013,Probation,Simtatis,Jose,NULL,Male,Hispanic,06/21/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67916,78870,71355,Probation,ellis,austin,NULL,Male,Caucasian,07/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +67916,78870,71355,Probation,ellis,austin,NULL,Male,Caucasian,07/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +67916,78870,71355,Probation,ellis,austin,NULL,Male,Caucasian,07/20/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67922,78877,71362,PRETRIAL,Robertson,Jerry,NULL,Male,African-American,11/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +67922,78877,71362,PRETRIAL,Robertson,Jerry,NULL,Male,African-American,11/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +67922,78877,71362,PRETRIAL,Robertson,Jerry,NULL,Male,African-American,11/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +61522,78867,71352,PRETRIAL,Dalo,Michael,NULL,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/20/14 0:00,2,Medium,7,Risk of Violence,-1.45,7,Medium,New,1,0 +61522,78867,71352,PRETRIAL,Dalo,Michael,NULL,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +61522,78867,71352,PRETRIAL,Dalo,Michael,NULL,Male,Caucasian,04/15/88,22,Risk and Prescreen,Intake,English,Other,Probation,Separated,11/20/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67896,78846,71334,PRETRIAL,Palomo,Jesus,E,Male,Hispanic,02/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +67896,78846,71334,PRETRIAL,Palomo,Jesus,E,Male,Hispanic,02/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +67896,78846,71334,PRETRIAL,Palomo,Jesus,E,Male,Hispanic,02/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67937,78880,71364,PRETRIAL,Mbilli,Jean,NULL,Male,African-American,05/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +67937,78880,71364,PRETRIAL,Mbilli,Jean,NULL,Male,African-American,05/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +67937,78880,71364,PRETRIAL,Mbilli,Jean,NULL,Male,African-American,05/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67920,78875,71360,Probation,Rangel Valencia,Jerremy,Emmanuel,Male,Hispanic,04/22/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/20/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +67920,78875,71360,Probation,Rangel Valencia,Jerremy,Emmanuel,Male,Hispanic,04/22/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/20/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +67920,78875,71360,Probation,Rangel Valencia,Jerremy,Emmanuel,Male,Hispanic,04/22/86,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/20/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67904,78854,71342,PRETRIAL,Ferry,Brittany,Nicole,Female,Caucasian,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +67904,78854,71342,PRETRIAL,Ferry,Brittany,Nicole,Female,Caucasian,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,7,Medium,New,1,0 +67904,78854,71342,PRETRIAL,Ferry,Brittany,Nicole,Female,Caucasian,10/01/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/20/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67918,78872,71357,PRETRIAL,Tigner,Quakiiya,s,Female,African-American,01/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/20/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.97,9,High,New,1,0 +67918,78872,71357,PRETRIAL,Tigner,Quakiiya,s,Female,African-American,01/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/20/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.38,6,Medium,New,1,0 +67918,78872,71357,PRETRIAL,Tigner,Quakiiya,s,Female,African-American,01/03/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/20/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67945,78893,71376,PRETRIAL,palgon,jason,NULL,Male,Caucasian,02/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +67945,78893,71376,PRETRIAL,palgon,jason,NULL,Male,Caucasian,02/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.47,9,High,New,1,0 +67945,78893,71376,PRETRIAL,palgon,jason,NULL,Male,Caucasian,02/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +67951,78901,71383,Probation,Moro,Zachary,NULL,Male,Hispanic,02/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +67951,78901,71383,Probation,Moro,Zachary,NULL,Male,Hispanic,02/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +67951,78901,71383,Probation,Moro,Zachary,NULL,Male,Hispanic,02/21/91,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +33089,78891,71375,Probation,Condra,Thomas,James,Male,Caucasian,10/04/56,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,11/21/14 0:00,1,Low,7,Risk of Violence,-3.72,1,Low,New,1,0 +33089,78891,71375,Probation,Condra,Thomas,James,Male,Caucasian,10/04/56,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,11/21/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +33089,78891,71375,Probation,Condra,Thomas,James,Male,Caucasian,10/04/56,22,Risk and Prescreen,Intake,English,Post Sentence,Jail Inmate,Divorced,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67949,78898,71381,PRETRIAL,martinez-vargas,clarissa,NULL,Female,Hispanic,10/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-2.08,4,Low,New,1,0 +67949,78898,71381,PRETRIAL,martinez-vargas,clarissa,NULL,Female,Hispanic,10/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-1.17,3,Low,New,1,0 +67949,78898,71381,PRETRIAL,martinez-vargas,clarissa,NULL,Female,Hispanic,10/29/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67938,78883,71367,PRETRIAL,Butler,Rickey,NULL,Male,African-American,02/25/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +67938,78883,71367,PRETRIAL,Butler,Rickey,NULL,Male,African-American,02/25/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +67938,78883,71367,PRETRIAL,Butler,Rickey,NULL,Male,African-American,02/25/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,2,Medium,18,Risk of Failure to Appear,35,10,High,New,1,0 +12417,78885,71369,PRETRIAL,MEDINA,JOSE,NULL,Male,Hispanic,08/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +12417,78885,71369,PRETRIAL,MEDINA,JOSE,NULL,Male,Hispanic,08/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +12417,78885,71369,PRETRIAL,MEDINA,JOSE,NULL,Male,Hispanic,08/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67944,78890,71374,PRETRIAL,correa,jorge,NULL,Male,Hispanic,01/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-2.54,3,Low,New,1,0 +67944,78890,71374,PRETRIAL,correa,jorge,NULL,Male,Hispanic,01/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +67944,78890,71374,PRETRIAL,correa,jorge,NULL,Male,Hispanic,01/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67953,78904,71385,PRETRIAL,Isaacs,Jerry,NULL,Male,African-American,05/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-4.15,1,Low,New,1,0 +67953,78904,71385,PRETRIAL,Isaacs,Jerry,NULL,Male,African-American,05/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +67953,78904,71385,PRETRIAL,Isaacs,Jerry,NULL,Male,African-American,05/12/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +59827,78907,71388,PRETRIAL,Wick,Daniel,D,Male,Caucasian,03/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/21/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +59827,78907,71388,PRETRIAL,Wick,Daniel,D,Male,Caucasian,03/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/21/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +59827,78907,71388,PRETRIAL,Wick,Daniel,D,Male,Caucasian,03/24/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67940,78886,71370,PRETRIAL,Herrera,Lissette,NULL,Female,Caucasian,07/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/21/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +67940,78886,71370,PRETRIAL,Herrera,Lissette,NULL,Female,Caucasian,07/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/21/14 0:00,1,Low,8,Risk of Recidivism,-0.76,5,Medium,New,1,0 +67940,78886,71370,PRETRIAL,Herrera,Lissette,NULL,Female,Caucasian,07/03/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +25511,78881,71365,PRETRIAL,HARRIGAN,JAMES,ANSON,Male,African-American,08/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.5,6,Medium,New,1,0 +25511,78881,71365,PRETRIAL,HARRIGAN,JAMES,ANSON,Male,African-American,08/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.39,9,High,New,1,0 +25511,78881,71365,PRETRIAL,HARRIGAN,JAMES,ANSON,Male,African-American,08/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +67942,78888,71372,PRETRIAL,longa,kurtland,NULL,Male,Caucasian,04/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +67942,78888,71372,PRETRIAL,longa,kurtland,NULL,Male,Caucasian,04/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +67942,78888,71372,PRETRIAL,longa,kurtland,NULL,Male,Caucasian,04/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67947,78895,71378,PRETRIAL,Vela,Sarah,NULL,Female,Caucasian,05/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +67947,78895,71378,PRETRIAL,Vela,Sarah,NULL,Female,Caucasian,05/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +67947,78895,71378,PRETRIAL,Vela,Sarah,NULL,Female,Caucasian,05/01/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +61819,78902,64417,PRETRIAL,EDELEN,KENNETH,ERIC,Male,Caucasian,11/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,2,Medium,7,Risk of Violence,-2.16,4,Low,Copy,1,0 +61819,78902,64417,PRETRIAL,EDELEN,KENNETH,ERIC,Male,Caucasian,11/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,Copy,1,0 +61819,78902,64417,PRETRIAL,EDELEN,KENNETH,ERIC,Male,Caucasian,11/09/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +67952,78903,71384,PRETRIAL,White,Robert,NULL,Male,African-American,11/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +67952,78903,71384,PRETRIAL,White,Robert,NULL,Male,African-American,11/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +67952,78903,71384,PRETRIAL,White,Robert,NULL,Male,African-American,11/05/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +67957,78908,71389,PRETRIAL,Maqueira,David,NULL,Male,Hispanic,12/29/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.92,9,High,New,1,0 +67957,78908,71389,PRETRIAL,Maqueira,David,NULL,Male,Hispanic,12/29/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.48,4,Low,New,1,0 +67957,78908,71389,PRETRIAL,Maqueira,David,NULL,Male,Hispanic,12/29/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +19460,78912,71392,PRETRIAL,Singletary,Mark,A,Male,African-American,12/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/14 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +19460,78912,71392,PRETRIAL,Singletary,Mark,A,Male,African-American,12/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +19460,78912,71392,PRETRIAL,Singletary,Mark,A,Male,African-American,12/31/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +40912,78882,71366,PRETRIAL,BURKE,DAVID,MARK,Male,Caucasian,10/17/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +40912,78882,71366,PRETRIAL,BURKE,DAVID,MARK,Male,Caucasian,10/17/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +40912,78882,71366,PRETRIAL,BURKE,DAVID,MARK,Male,Caucasian,10/17/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67950,78899,71382,PRETRIAL,Dang,Dung,NULL,Male,Asian,12/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/21/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +67950,78899,71382,PRETRIAL,Dang,Dung,NULL,Male,Asian,12/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/21/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +67950,78899,71382,PRETRIAL,Dang,Dung,NULL,Male,Asian,12/06/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/21/14 0:00,2,Medium,18,Risk of Failure to Appear,35,10,High,New,1,0 +56371,78896,71379,PRETRIAL,Chambers,Nadine,NULL,Female,Caucasian,08/08/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +56371,78896,71379,PRETRIAL,Chambers,Nadine,NULL,Female,Caucasian,08/08/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +56371,78896,71379,PRETRIAL,Chambers,Nadine,NULL,Female,Caucasian,08/08/65,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67941,78887,71371,Probation,Eloi,James,NULL,Male,African-American,05/14/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +67941,78887,71371,Probation,Eloi,James,NULL,Male,African-American,05/14/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +67941,78887,71371,Probation,Eloi,James,NULL,Male,African-American,05/14/88,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67946,78894,71377,Probation,WARREN,CAITLIN,M,Female,Caucasian,01/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +67946,78894,71377,Probation,WARREN,CAITLIN,M,Female,Caucasian,01/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +67946,78894,71377,Probation,WARREN,CAITLIN,M,Female,Caucasian,01/15/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67959,78913,71393,Probation,Shields,Angel,NULL,Female,African-American,10/28/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-2.17,4,Low,New,1,0 +67959,78913,71393,Probation,Shields,Angel,NULL,Female,African-American,10/28/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-0.6,5,Medium,New,1,0 +67959,78913,71393,Probation,Shields,Angel,NULL,Female,African-American,10/28/84,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +67954,78905,71386,PRETRIAL,Joseph,Samuel,NULL,Male,African-American,08/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +67954,78905,71386,PRETRIAL,Joseph,Samuel,NULL,Male,African-American,08/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +67954,78905,71386,PRETRIAL,Joseph,Samuel,NULL,Male,African-American,08/14/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67939,78884,71368,PRETRIAL,Sopcheck,Matthew,Peter,Male,Caucasian,09/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +67939,78884,71368,PRETRIAL,Sopcheck,Matthew,Peter,Male,Caucasian,09/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +67939,78884,71368,PRETRIAL,Sopcheck,Matthew,Peter,Male,Caucasian,09/29/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67958,78910,71391,Probation,Ramos,Enrique,NULL,Male,Hispanic,07/15/47,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/21/14 0:00,1,Low,7,Risk of Violence,-4.4,1,Low,New,1,0 +67958,78910,71391,Probation,Ramos,Enrique,NULL,Male,Hispanic,07/15/47,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/21/14 0:00,1,Low,8,Risk of Recidivism,-2.26,1,Low,New,1,0 +67958,78910,71391,Probation,Ramos,Enrique,NULL,Male,Hispanic,07/15/47,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/21/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67948,78897,71380,PRETRIAL,Edwards,Dahron,NULL,Male,African-American,03/31/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.59,10,High,New,1,0 +67948,78897,71380,PRETRIAL,Edwards,Dahron,NULL,Male,African-American,03/31/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,7,Medium,New,1,0 +67948,78897,71380,PRETRIAL,Edwards,Dahron,NULL,Male,African-American,03/31/91,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,6,Medium,New,1,0 +67943,78889,71373,PRETRIAL,Murphy,Darren,NULL,Male,African-American,09/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.33,7,Medium,New,1,0 +67943,78889,71373,PRETRIAL,Murphy,Darren,NULL,Male,African-American,09/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +67943,78889,71373,PRETRIAL,Murphy,Darren,NULL,Male,African-American,09/26/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +67962,78918,71396,PRETRIAL,Carr,Taneka,NULL,Female,African-American,08/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +67962,78918,71396,PRETRIAL,Carr,Taneka,NULL,Female,African-American,08/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +67962,78918,71396,PRETRIAL,Carr,Taneka,NULL,Female,African-American,08/24/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +62287,78936,64963,PRETRIAL,Thorpe,Shellene,NULL,Female,African-American,06/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,Copy,1,0 +62287,78936,64963,PRETRIAL,Thorpe,Shellene,NULL,Female,African-American,06/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,Copy,1,0 +62287,78936,64963,PRETRIAL,Thorpe,Shellene,NULL,Female,African-American,06/17/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +36212,78931,35471,PRETRIAL,Pino,Miyami,NULL,Male,Caucasian,09/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/22/14 0:00,1,Low,7,Risk of Violence,-3.16,1,Low,Copy,1,0 +36212,78931,35471,PRETRIAL,Pino,Miyami,NULL,Male,Caucasian,09/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/22/14 0:00,1,Low,8,Risk of Recidivism,-1.23,2,Low,Copy,1,0 +36212,78931,35471,PRETRIAL,Pino,Miyami,NULL,Male,Caucasian,09/15/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +67964,78920,71398,PRETRIAL,CEPRANO,NINA,MARIE,Female,Caucasian,03/26/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +67964,78920,71398,PRETRIAL,CEPRANO,NINA,MARIE,Female,Caucasian,03/26/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +67964,78920,71398,PRETRIAL,CEPRANO,NINA,MARIE,Female,Caucasian,03/26/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67973,78926,71404,PRETRIAL,kenney,jonathan,NULL,Male,Caucasian,07/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.41,3,Low,New,1,0 +67973,78926,71404,PRETRIAL,kenney,jonathan,NULL,Male,Caucasian,07/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.46,9,High,New,1,0 +67973,78926,71404,PRETRIAL,kenney,jonathan,NULL,Male,Caucasian,07/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,45,10,High,New,1,0 +38560,78917,38005,PRETRIAL,Burrows,Brittany,NULL,Female,African-American,02/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,Copy,1,0 +38560,78917,38005,PRETRIAL,Burrows,Brittany,NULL,Female,African-American,02/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,8,Risk of Recidivism,-1.08,3,Low,Copy,1,0 +38560,78917,38005,PRETRIAL,Burrows,Brittany,NULL,Female,African-American,02/16/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +67961,78915,71395,PRETRIAL,Velezlopez,Esteban,NULL,Male,Hispanic,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +67961,78915,71395,PRETRIAL,Velezlopez,Esteban,NULL,Male,Hispanic,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,8,Risk of Recidivism,-1.25,2,Low,New,1,0 +67961,78915,71395,PRETRIAL,Velezlopez,Esteban,NULL,Male,Hispanic,11/10/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67967,78924,71402,PRETRIAL,Gadson,Dominique,NULL,Male,African-American,07/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,7,Risk of Violence,-2.13,4,Low,New,1,0 +67967,78924,71402,PRETRIAL,Gadson,Dominique,NULL,Male,African-American,07/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +67967,78924,71402,PRETRIAL,Gadson,Dominique,NULL,Male,African-American,07/10/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67975,78929,71406,PRETRIAL,williams,Tracy,Nicole,Female,African-American,10/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,2,Medium,7,Risk of Violence,-2.6,2,Low,New,1,0 +67975,78929,71406,PRETRIAL,williams,Tracy,Nicole,Female,African-American,10/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +67975,78929,71406,PRETRIAL,williams,Tracy,Nicole,Female,African-American,10/07/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67978,78933,71409,PRETRIAL,francis,bruce,NULL,Male,African-American,11/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,4,High,7,Risk of Violence,-0.83,9,High,New,1,0 +67978,78933,71409,PRETRIAL,francis,bruce,NULL,Male,African-American,11/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,4,High,8,Risk of Recidivism,0.74,10,High,New,1,0 +67978,78933,71409,PRETRIAL,francis,bruce,NULL,Male,African-American,11/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67966,78923,71401,PRETRIAL,Knoche,Courtney,Diane,Female,Caucasian,04/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +67966,78923,71401,PRETRIAL,Knoche,Courtney,Diane,Female,Caucasian,04/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,8,Risk of Recidivism,-1.73,1,Low,New,1,0 +67966,78923,71401,PRETRIAL,Knoche,Courtney,Diane,Female,Caucasian,04/30/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67976,78930,71407,PRETRIAL,Booton,Jessica,Marie,Female,Caucasian,07/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +67976,78930,71407,PRETRIAL,Booton,Jessica,Marie,Female,Caucasian,07/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +67976,78930,71407,PRETRIAL,Booton,Jessica,Marie,Female,Caucasian,07/30/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67977,78932,71408,PRETRIAL,chico,christopher,NULL,Male,Caucasian,10/10/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,2,Medium,7,Risk of Violence,-1.53,6,Medium,New,1,0 +67977,78932,71408,PRETRIAL,chico,christopher,NULL,Male,Caucasian,10/10/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +67977,78932,71408,PRETRIAL,chico,christopher,NULL,Male,Caucasian,10/10/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67972,78925,71403,PRETRIAL,Riosquinones,Jermayne,NULL,Male,Hispanic,11/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/22/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +67972,78925,71403,PRETRIAL,Riosquinones,Jermayne,NULL,Male,Hispanic,11/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/22/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +67972,78925,71403,PRETRIAL,Riosquinones,Jermayne,NULL,Male,Hispanic,11/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +30293,78921,71399,PRETRIAL,Townsell,Marcelo,NULL,Male,Other,11/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +30293,78921,71399,PRETRIAL,Townsell,Marcelo,NULL,Male,Other,11/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +30293,78921,71399,PRETRIAL,Townsell,Marcelo,NULL,Male,Other,11/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +37293,78916,36636,Probation,Vassell,Hopeton,NULL,Male,African-American,06/05/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,7,Risk of Violence,-3.89,1,Low,Copy,1,0 +37293,78916,36636,Probation,Vassell,Hopeton,NULL,Male,African-American,06/05/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,Copy,1,0 +37293,78916,36636,Probation,Vassell,Hopeton,NULL,Male,African-American,06/05/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +67974,78937,71405,PRETRIAL,ARECHAVALETA,JUAN,NULL,Male,Hispanic,03/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,Copy,1,0 +67974,78937,71405,PRETRIAL,ARECHAVALETA,JUAN,NULL,Male,Hispanic,03/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,Copy,1,0 +67974,78937,71405,PRETRIAL,ARECHAVALETA,JUAN,NULL,Male,Hispanic,03/28/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +67963,78919,71397,PRETRIAL,SEENATHSINGH,SYLVAN,NULL,Male,Other,07/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/22/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +67963,78919,71397,PRETRIAL,SEENATHSINGH,SYLVAN,NULL,Male,Other,07/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/22/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +67963,78919,71397,PRETRIAL,SEENATHSINGH,SYLVAN,NULL,Male,Other,07/10/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +8588,78927,8129,PRETRIAL,LEBRECHT,JESSE,CHARLES,Male,Caucasian,12/08/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/14 0:00,4,High,7,Risk of Violence,-1.22,8,High,Copy,1,0 +8588,78927,8129,PRETRIAL,LEBRECHT,JESSE,CHARLES,Male,Caucasian,12/08/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/14 0:00,4,High,8,Risk of Recidivism,0.39,9,High,Copy,1,0 +8588,78927,8129,PRETRIAL,LEBRECHT,JESSE,CHARLES,Male,Caucasian,12/08/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +67980,78935,71411,PRETRIAL,Sanchez-Rodriguez,Jonathan,NULL,Male,Hispanic,07/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/14 0:00,2,Medium,7,Risk of Violence,-1.44,7,Medium,New,1,0 +67980,78935,71411,PRETRIAL,Sanchez-Rodriguez,Jonathan,NULL,Male,Hispanic,07/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +67980,78935,71411,PRETRIAL,Sanchez-Rodriguez,Jonathan,NULL,Male,Hispanic,07/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/22/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67960,78914,71394,PRETRIAL,Etienne,Amsterby,NULL,Male,African-American,12/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +67960,78914,71394,PRETRIAL,Etienne,Amsterby,NULL,Male,African-American,12/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.07,7,Medium,New,1,0 +67960,78914,71394,PRETRIAL,Etienne,Amsterby,NULL,Male,African-American,12/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67965,78922,71400,PRETRIAL,LETOHIC,JOSEPH,NULL,Male,Caucasian,07/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +67965,78922,71400,PRETRIAL,LETOHIC,JOSEPH,NULL,Male,Caucasian,07/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +67965,78922,71400,PRETRIAL,LETOHIC,JOSEPH,NULL,Male,Caucasian,07/11/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/22/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +43480,78940,43438,Probation,BORGES,JACKLYN,NULL,Female,Hispanic,01/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/23/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,Copy,1,0 +43480,78940,43438,Probation,BORGES,JACKLYN,NULL,Female,Hispanic,01/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/23/14 0:00,1,Low,8,Risk of Recidivism,-1.47,2,Low,Copy,1,0 +43480,78940,43438,Probation,BORGES,JACKLYN,NULL,Female,Hispanic,01/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +67983,78943,71415,PRETRIAL,WALLACE,CARL,NULL,Male,African-American,09/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +67983,78943,71415,PRETRIAL,WALLACE,CARL,NULL,Male,African-American,09/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +67983,78943,71415,PRETRIAL,WALLACE,CARL,NULL,Male,African-American,09/06/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67988,78948,71420,PRETRIAL,Spells,Ericka,NULL,Female,African-American,10/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +67988,78948,71420,PRETRIAL,Spells,Ericka,NULL,Female,African-American,10/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.81,5,Medium,New,1,0 +67988,78948,71420,PRETRIAL,Spells,Ericka,NULL,Female,African-American,10/01/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67982,78942,71414,PRETRIAL,King,Bradley,NULL,Male,Caucasian,03/14/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +67982,78942,71414,PRETRIAL,King,Bradley,NULL,Male,Caucasian,03/14/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,1,Low,8,Risk of Recidivism,-2.09,1,Low,New,1,0 +67982,78942,71414,PRETRIAL,King,Bradley,NULL,Male,Caucasian,03/14/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67986,78946,71418,PRETRIAL,STEPHENS,LARGOS,TRAMAINE,Male,African-American,01/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/23/14 0:00,1,Low,7,Risk of Violence,-2.76,2,Low,New,1,0 +67986,78946,71418,PRETRIAL,STEPHENS,LARGOS,TRAMAINE,Male,African-American,01/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/23/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +67986,78946,71418,PRETRIAL,STEPHENS,LARGOS,TRAMAINE,Male,African-American,01/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67990,78951,71422,PRETRIAL,lever,eric,NULL,Male,Caucasian,09/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.47,3,Low,New,1,0 +67990,78951,71422,PRETRIAL,lever,eric,NULL,Male,Caucasian,09/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +67990,78951,71422,PRETRIAL,lever,eric,NULL,Male,Caucasian,09/18/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +67992,78953,71424,PRETRIAL,zelada,erick,NULL,Male,Hispanic,08/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/23/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +67992,78953,71424,PRETRIAL,zelada,erick,NULL,Male,Hispanic,08/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/23/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +67992,78953,71424,PRETRIAL,zelada,erick,NULL,Male,Hispanic,08/19/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67982,78950,71414,PRETRIAL,King,Bradley,NULL,Male,Caucasian,03/14/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,Copy,1,0 +67982,78950,71414,PRETRIAL,King,Bradley,NULL,Male,Caucasian,03/14/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,Copy,1,0 +67982,78950,71414,PRETRIAL,King,Bradley,NULL,Male,Caucasian,03/14/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +13378,78938,12787,PRETRIAL,TUCKER,EUGENE,R,Male,African-American,02/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,Copy,1,0 +13378,78938,12787,PRETRIAL,TUCKER,EUGENE,R,Male,African-American,02/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,Copy,1,0 +13378,78938,12787,PRETRIAL,TUCKER,EUGENE,R,Male,African-American,02/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +67985,78945,71417,PRETRIAL,JACKSON,TAKESHA,NULL,Female,African-American,12/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/23/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +67985,78945,71417,PRETRIAL,JACKSON,TAKESHA,NULL,Female,African-American,12/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/23/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +67985,78945,71417,PRETRIAL,JACKSON,TAKESHA,NULL,Female,African-American,12/19/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/23/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67991,78952,71423,PRETRIAL,Boothe,Antwyn,Durrell,Male,African-American,06/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +67991,78952,71423,PRETRIAL,Boothe,Antwyn,Durrell,Male,African-American,06/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/14 0:00,1,Low,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +67991,78952,71423,PRETRIAL,Boothe,Antwyn,Durrell,Male,African-American,06/18/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +67987,78947,71419,PRETRIAL,HERNANDEZ,CARLOS,manuel,Male,Caucasian,08/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/23/14 0:00,1,Low,7,Risk of Violence,-4.09,1,Low,New,1,0 +67987,78947,71419,PRETRIAL,HERNANDEZ,CARLOS,manuel,Male,Caucasian,08/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/23/14 0:00,1,Low,8,Risk of Recidivism,-2.56,1,Low,New,1,0 +67987,78947,71419,PRETRIAL,HERNANDEZ,CARLOS,manuel,Male,Caucasian,08/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/23/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67989,78949,71421,PRETRIAL,WILLIAMS,THEDORE,NULL,Male,African-American,04/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/14 0:00,2,Medium,7,Risk of Violence,-3.03,1,Low,New,1,0 +67989,78949,71421,PRETRIAL,WILLIAMS,THEDORE,NULL,Male,African-American,04/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +67989,78949,71421,PRETRIAL,WILLIAMS,THEDORE,NULL,Male,African-American,04/16/56,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/23/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +1288,78941,71413,PRETRIAL,JUNIOR,PIERRELOUIS,NULL,Male,African-American,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,1,Low,7,Risk of Violence,-2.6,2,Low,New,1,0 +1288,78941,71413,PRETRIAL,JUNIOR,PIERRELOUIS,NULL,Male,African-American,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +1288,78941,71413,PRETRIAL,JUNIOR,PIERRELOUIS,NULL,Male,African-American,12/19/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +67984,78944,71416,PRETRIAL,Bailey,Kevin,NULL,Male,Other,12/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +67984,78944,71416,PRETRIAL,Bailey,Kevin,NULL,Male,Other,12/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +67984,78944,71416,PRETRIAL,Bailey,Kevin,NULL,Male,Other,12/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67981,78939,71412,PRETRIAL,Owens,Elonzo,NULL,Male,African-American,11/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.26,3,Low,New,1,0 +67981,78939,71412,PRETRIAL,Owens,Elonzo,NULL,Male,African-American,11/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,New,1,0 +67981,78939,71412,PRETRIAL,Owens,Elonzo,NULL,Male,African-American,11/04/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +67996,78957,71428,PRETRIAL,Pacifico,Frank,NULL,Male,Caucasian,05/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +67996,78957,71428,PRETRIAL,Pacifico,Frank,NULL,Male,Caucasian,05/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +67996,78957,71428,PRETRIAL,Pacifico,Frank,NULL,Male,Caucasian,05/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68024,78986,71454,DRRD,Tayor,Gary,Monte,Male,African-American,09/05/93,17,All Scales,Intake,English,Post Sentence,Probation,Married,11/24/14 0:00,4,High,7,Risk of Violence,-1.08,8,High,New,1,0 +68024,78986,71454,DRRD,Tayor,Gary,Monte,Male,African-American,09/05/93,17,All Scales,Intake,English,Post Sentence,Probation,Married,11/24/14 0:00,4,High,8,Risk of Recidivism,0.35,8,High,New,1,0 +68024,78986,71454,DRRD,Tayor,Gary,Monte,Male,African-American,09/05/93,17,All Scales,Intake,English,Post Sentence,Probation,Married,11/24/14 0:00,4,High,18,Risk of Failure to Appear,16,1,Low,New,1,0 +68018,78978,71447,Probation,Garcia,Jose,NULL,Male,Hispanic,03/19/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +68018,78978,71447,Probation,Garcia,Jose,NULL,Male,Hispanic,03/19/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +68018,78978,71447,Probation,Garcia,Jose,NULL,Male,Hispanic,03/19/77,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +19272,78965,71434,PRETRIAL,PERKINS,ROBERT,NULL,Male,Caucasian,10/16/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/24/14 0:00,2,Medium,7,Risk of Violence,-2.56,2,Low,New,1,0 +19272,78965,71434,PRETRIAL,PERKINS,ROBERT,NULL,Male,Caucasian,10/16/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +19272,78965,71434,PRETRIAL,PERKINS,ROBERT,NULL,Male,Caucasian,10/16/58,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,35,10,High,New,1,0 +53223,78999,71464,PRETRIAL,Bartron,Darren,NULL,Male,Caucasian,12/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,7,Risk of Violence,-2.2,4,Low,New,1,0 +53223,78999,71464,PRETRIAL,Bartron,Darren,NULL,Male,Caucasian,12/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +53223,78999,71464,PRETRIAL,Bartron,Darren,NULL,Male,Caucasian,12/05/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68025,78991,71455,PRETRIAL,Stunneck,Joseph,NULL,Male,Caucasian,07/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,Copy,1,0 +68025,78991,71455,PRETRIAL,Stunneck,Joseph,NULL,Male,Caucasian,07/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.03,7,Medium,Copy,1,0 +68025,78991,71455,PRETRIAL,Stunneck,Joseph,NULL,Male,Caucasian,07/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +68013,78970,71439,Probation,HYNES,AMANDA,NULL,Female,Caucasian,08/03/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +68013,78970,71439,Probation,HYNES,AMANDA,NULL,Female,Caucasian,08/03/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.44,2,Low,New,1,0 +68013,78970,71439,Probation,HYNES,AMANDA,NULL,Female,Caucasian,08/03/77,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68021,78983,71451,Probation,Meghani,Karim,NULL,Male,African-American,05/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +68021,78983,71451,Probation,Meghani,Karim,NULL,Male,African-American,05/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +68021,78983,71451,Probation,Meghani,Karim,NULL,Male,African-American,05/25/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68009,78962,71433,PRETRIAL,VICTOR,EDDYTE,NULL,Female,African-American,12/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +68009,78962,71433,PRETRIAL,VICTOR,EDDYTE,NULL,Female,African-American,12/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.13,8,High,New,1,0 +68009,78962,71433,PRETRIAL,VICTOR,EDDYTE,NULL,Female,African-American,12/12/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +68007,78959,71430,PRETRIAL,Tallis,Matthew,NULL,Male,Caucasian,02/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +68007,78959,71430,PRETRIAL,Tallis,Matthew,NULL,Male,Caucasian,02/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +68007,78959,71430,PRETRIAL,Tallis,Matthew,NULL,Male,Caucasian,02/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68015,78973,71442,Probation,Sanseviero,Nicolas,NULL,Male,Hispanic,11/30/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +68015,78973,71442,Probation,Sanseviero,Nicolas,NULL,Male,Hispanic,11/30/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +68015,78973,71442,Probation,Sanseviero,Nicolas,NULL,Male,Hispanic,11/30/70,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68032,78996,71461,Probation,Bejaranorincon,Fredy,Octavio,Male,Hispanic,07/04/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/24/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +68032,78996,71461,Probation,Bejaranorincon,Fredy,Octavio,Male,Hispanic,07/04/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +68032,78996,71461,Probation,Bejaranorincon,Fredy,Octavio,Male,Hispanic,07/04/75,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +58123,78968,71437,PRETRIAL,BERLANGA,MITCHELL,NULL,Male,Caucasian,12/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,7,Risk of Violence,-1.65,6,Medium,New,1,0 +58123,78968,71437,PRETRIAL,BERLANGA,MITCHELL,NULL,Male,Caucasian,12/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +58123,78968,71437,PRETRIAL,BERLANGA,MITCHELL,NULL,Male,Caucasian,12/01/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68016,78975,71444,PRETRIAL,engelke,barbara,NULL,Female,Caucasian,06/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-4.2,1,Low,New,1,0 +68016,78975,71444,PRETRIAL,engelke,barbara,NULL,Female,Caucasian,06/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +68016,78975,71444,PRETRIAL,engelke,barbara,NULL,Female,Caucasian,06/15/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +67993,78954,71425,PRETRIAL,Fisher,Amy,NULL,Female,Caucasian,06/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/24/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +67993,78954,71425,PRETRIAL,Fisher,Amy,NULL,Female,Caucasian,06/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +67993,78954,71425,PRETRIAL,Fisher,Amy,NULL,Female,Caucasian,06/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +47029,78971,71440,PRETRIAL,Galette,Hardy,NULL,Male,African-American,08/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,2,Medium,7,Risk of Violence,-1.39,7,Medium,New,1,0 +47029,78971,71440,PRETRIAL,Galette,Hardy,NULL,Male,African-American,08/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +47029,78971,71440,PRETRIAL,Galette,Hardy,NULL,Male,African-American,08/02/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +68026,78989,71456,Probation,kelbie,lena,NULL,Female,Caucasian,06/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,7,Risk of Violence,-2.35,3,Low,New,1,0 +68026,78989,71456,Probation,kelbie,lena,NULL,Female,Caucasian,06/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,6,Medium,New,1,0 +68026,78989,71456,Probation,kelbie,lena,NULL,Female,Caucasian,06/27/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68020,78980,71449,Probation,windle,samantha,NULL,Female,Caucasian,05/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,7,Risk of Violence,-2.18,4,Low,New,1,0 +68020,78980,71449,Probation,windle,samantha,NULL,Female,Caucasian,05/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +68020,78980,71449,Probation,windle,samantha,NULL,Female,Caucasian,05/10/92,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +67994,78960,71431,PRETRIAL,Kumar,Vick,NULL,Male,Other,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/24/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +67994,78960,71431,PRETRIAL,Kumar,Vick,NULL,Male,Other,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +67994,78960,71431,PRETRIAL,Kumar,Vick,NULL,Male,Other,06/21/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68019,78979,71448,Probation,GILES,LAMONDA,D,Male,African-American,09/19/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +68019,78979,71448,Probation,GILES,LAMONDA,D,Male,African-American,09/19/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.09,7,Medium,New,1,0 +68019,78979,71448,Probation,GILES,LAMONDA,D,Male,African-American,09/19/76,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +59949,78981,63815,PRETRIAL,Daniel,Miesha,NULL,Female,African-American,02/12/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,Copy,1,0 +59949,78981,63815,PRETRIAL,Daniel,Miesha,NULL,Female,African-American,02/12/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.32,7,Medium,Copy,1,0 +59949,78981,63815,PRETRIAL,Daniel,Miesha,NULL,Female,African-American,02/12/93,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +68031,78995,71460,Probation,Thomas,Kenton,NULL,Male,African-American,07/07/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +68031,78995,71460,Probation,Thomas,Kenton,NULL,Male,African-American,07/07/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +68031,78995,71460,Probation,Thomas,Kenton,NULL,Male,African-American,07/07/67,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +20177,78963,39471,PRETRIAL,HARRIS,VONETTA,MICHELLA,Female,African-American,04/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,Copy,1,0 +20177,78963,39471,PRETRIAL,HARRIS,VONETTA,MICHELLA,Female,African-American,04/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,Copy,1,0 +20177,78963,39471,PRETRIAL,HARRIS,VONETTA,MICHELLA,Female,African-American,04/15/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +68033,78997,71462,Probation,villalobos,christopher,NULL,Male,Caucasian,07/30/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/24/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +68033,78997,71462,Probation,villalobos,christopher,NULL,Male,Caucasian,07/30/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/24/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +68033,78997,71462,Probation,villalobos,christopher,NULL,Male,Caucasian,07/30/80,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68011,78967,71436,Probation,Gordon,Tarvell,NULL,Male,African-American,07/17/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/24/14 0:00,2,Medium,7,Risk of Violence,-2.15,4,Low,New,1,0 +68011,78967,71436,Probation,Gordon,Tarvell,NULL,Male,African-American,07/17/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +68011,78967,71436,Probation,Gordon,Tarvell,NULL,Male,African-American,07/17/76,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +24906,78976,71445,PRETRIAL,Doe,Paris,Verell,Female,African-American,04/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-2.18,4,Low,New,1,0 +24906,78976,71445,PRETRIAL,Doe,Paris,Verell,Female,African-American,04/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +24906,78976,71445,PRETRIAL,Doe,Paris,Verell,Female,African-American,04/09/90,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68006,78958,71429,PRETRIAL,Yauri,Carol,NULL,Female,Hispanic,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +68006,78958,71429,PRETRIAL,Yauri,Carol,NULL,Female,Hispanic,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.07,3,Low,New,1,0 +68006,78958,71429,PRETRIAL,Yauri,Carol,NULL,Female,Hispanic,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68014,78972,71441,PRETRIAL,Marshall,Zachary,NULL,Male,Caucasian,12/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +68014,78972,71441,PRETRIAL,Marshall,Zachary,NULL,Male,Caucasian,12/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-0.82,3,Low,New,1,0 +68014,78972,71441,PRETRIAL,Marshall,Zachary,NULL,Male,Caucasian,12/21/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68028,78993,71458,PRETRIAL,Vitale,Kevin,NULL,Male,Caucasian,05/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,2,Medium,7,Risk of Violence,-1.67,6,Medium,New,1,0 +68028,78993,71458,PRETRIAL,Vitale,Kevin,NULL,Male,Caucasian,05/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,New,1,0 +68028,78993,71458,PRETRIAL,Vitale,Kevin,NULL,Male,Caucasian,05/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +60929,78982,71450,PRETRIAL,Devaswamparambil,Veugoplalan,NULL,Male,Other,05/13/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/24/14 0:00,1,Low,7,Risk of Violence,-3.85,1,Low,New,1,0 +60929,78982,71450,PRETRIAL,Devaswamparambil,Veugoplalan,NULL,Male,Other,05/13/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +60929,78982,71450,PRETRIAL,Devaswamparambil,Veugoplalan,NULL,Male,Other,05/13/70,22,Risk and Prescreen,Intake,English,Other,Probation,Married,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68012,78969,71438,Probation,Mateo,Alejandro,Yupanquz,Male,Hispanic,02/13/75,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/24/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +68012,78969,71438,Probation,Mateo,Alejandro,Yupanquz,Male,Hispanic,02/13/75,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +68012,78969,71438,Probation,Mateo,Alejandro,Yupanquz,Male,Hispanic,02/13/75,22,Risk and Prescreen,Intake,English,Other,Probation,Divorced,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68008,78961,71432,PRETRIAL,JOSEPH,TAMEEKA,NULL,Female,African-American,12/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/24/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +68008,78961,71432,PRETRIAL,JOSEPH,TAMEEKA,NULL,Female,African-American,12/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +68008,78961,71432,PRETRIAL,JOSEPH,TAMEEKA,NULL,Female,African-American,12/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68035,79000,71465,Probation,rolle,Janet,NULL,Female,African-American,12/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/24/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +68035,79000,71465,Probation,rolle,Janet,NULL,Female,African-American,12/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.88,1,Low,New,1,0 +68035,79000,71465,Probation,rolle,Janet,NULL,Female,African-American,12/29/70,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +35086,78990,34271,PRETRIAL,Desir,Marvin,NULL,Male,Other,12/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-2.02,4,Low,Copy,1,0 +35086,78990,34271,PRETRIAL,Desir,Marvin,NULL,Male,Other,12/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,Copy,1,0 +35086,78990,34271,PRETRIAL,Desir,Marvin,NULL,Male,Other,12/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +68017,78977,71446,Probation,Monteiro,Tiago,NULL,Male,Caucasian,08/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +68017,78977,71446,Probation,Monteiro,Tiago,NULL,Male,Caucasian,08/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +68017,78977,71446,Probation,Monteiro,Tiago,NULL,Male,Caucasian,08/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68022,78984,71452,PRETRIAL,Patterson,Zachary,Todd,Male,Caucasian,08/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +68022,78984,71452,PRETRIAL,Patterson,Zachary,Todd,Male,Caucasian,08/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1,3,Low,New,1,0 +68022,78984,71452,PRETRIAL,Patterson,Zachary,Todd,Male,Caucasian,08/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +67995,78956,71427,PRETRIAL,KAARLSEN,DANIELLE,A,Female,Caucasian,08/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-1.93,5,Medium,New,1,0 +67995,78956,71427,PRETRIAL,KAARLSEN,DANIELLE,A,Female,Caucasian,08/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-0.88,4,Low,New,1,0 +67995,78956,71427,PRETRIAL,KAARLSEN,DANIELLE,A,Female,Caucasian,08/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68027,78992,71457,Probation,GIPSON,JARED,M,Male,African-American,07/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,7,Risk of Violence,-2.26,3,Low,New,1,0 +68027,78992,71457,Probation,GIPSON,JARED,M,Male,African-American,07/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +68027,78992,71457,Probation,GIPSON,JARED,M,Male,African-American,07/24/85,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +25243,78964,30645,PRETRIAL,BROWN,KEVIN,ALEXANDER,Male,African-American,02/17/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/24/14 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,Copy,1,0 +25243,78964,30645,PRETRIAL,BROWN,KEVIN,ALEXANDER,Male,African-American,02/17/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +25243,78964,30645,PRETRIAL,BROWN,KEVIN,ALEXANDER,Male,African-American,02/17/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/24/14 0:00,2,Medium,18,Risk of Failure to Appear,35,10,High,Copy,1,0 +68034,78998,71463,Probation,swans,keelan,NULL,Male,African-American,08/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +68034,78998,71463,Probation,swans,keelan,NULL,Male,African-American,08/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +68034,78998,71463,Probation,swans,keelan,NULL,Male,African-American,08/12/89,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68043,79013,71474,PRETRIAL,Davis,Aaron,R,Male,Caucasian,07/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/25/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,Copy,1,0 +68043,79013,71474,PRETRIAL,Davis,Aaron,R,Male,Caucasian,07/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/25/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,Copy,1,0 +68043,79013,71474,PRETRIAL,Davis,Aaron,R,Male,Caucasian,07/30/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Widowed,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +68048,79019,71480,Probation,thomas,zackterrus,NULL,Male,African-American,10/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-2.72,2,Low,New,1,0 +68048,79019,71480,Probation,thomas,zackterrus,NULL,Male,African-American,10/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-0.87,3,Low,New,1,0 +68048,79019,71480,Probation,thomas,zackterrus,NULL,Male,African-American,10/06/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +58469,79026,71487,Probation,Pryor,Tiara,NULL,Female,African-American,11/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,2,Medium,7,Risk of Violence,-1.94,5,Medium,New,1,0 +58469,79026,71487,Probation,Pryor,Tiara,NULL,Female,African-American,11/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.51,6,Medium,New,1,0 +58469,79026,71487,Probation,Pryor,Tiara,NULL,Female,African-American,11/17/79,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +68039,79005,71469,PRETRIAL,HARRIS,DENNIS,DARNELL,Male,African-American,09/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +68039,79005,71469,PRETRIAL,HARRIS,DENNIS,DARNELL,Male,African-American,09/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-0.67,4,Low,New,1,0 +68039,79005,71469,PRETRIAL,HARRIS,DENNIS,DARNELL,Male,African-American,09/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +12156,79006,71470,DRRD,kraft,thomas,NULL,Male,Caucasian,09/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +12156,79006,71470,DRRD,kraft,thomas,NULL,Male,Caucasian,09/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +12156,79006,71470,DRRD,kraft,thomas,NULL,Male,Caucasian,09/30/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +68059,79034,71494,Probation,Clarke,Reese,NULL,Male,African-American,10/25/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.34,7,Medium,New,1,0 +68059,79034,71494,Probation,Clarke,Reese,NULL,Male,African-American,10/25/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +68059,79034,71494,Probation,Clarke,Reese,NULL,Male,African-American,10/25/86,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68050,79021,71482,PRETRIAL,Lamour,Denny,NULL,Male,African-American,02/14/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/25/14 0:00,2,Medium,7,Risk of Violence,-1.64,6,Medium,New,1,0 +68050,79021,71482,PRETRIAL,Lamour,Denny,NULL,Male,African-American,02/14/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +68050,79021,71482,PRETRIAL,Lamour,Denny,NULL,Male,African-American,02/14/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/25/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68042,79011,71473,PRETRIAL,MILHOMME,JACQUELINE,NULL,Female,Caucasian,08/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/25/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +68042,79011,71473,PRETRIAL,MILHOMME,JACQUELINE,NULL,Female,Caucasian,08/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/25/14 0:00,1,Low,8,Risk of Recidivism,-0.67,5,Medium,New,1,0 +68042,79011,71473,PRETRIAL,MILHOMME,JACQUELINE,NULL,Female,Caucasian,08/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +59173,79029,71489,PRETRIAL,Denicola,Janel,NULL,Female,Caucasian,03/22/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-2.05,4,Low,New,1,0 +59173,79029,71489,PRETRIAL,Denicola,Janel,NULL,Female,Caucasian,03/22/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-0.71,5,Medium,New,1,0 +59173,79029,71489,PRETRIAL,Denicola,Janel,NULL,Female,Caucasian,03/22/95,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +27305,28932,26420,Probation,tyler,betty,NULL,Female,African-American,12/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-3.56,1,Low,New,1,0 +27305,28932,26420,Probation,tyler,betty,NULL,Female,African-American,12/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-1.63,2,Low,New,1,0 +27305,28932,26420,Probation,tyler,betty,NULL,Female,African-American,12/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68037,79003,71467,PRETRIAL,Diaz,Jose,Julian,Male,Hispanic,09/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +68037,79003,71467,PRETRIAL,Diaz,Jose,Julian,Male,Hispanic,09/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +68037,79003,71467,PRETRIAL,Diaz,Jose,Julian,Male,Hispanic,09/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68062,79037,71497,Probation,Cunningham,Jermaine,NULL,Male,African-American,07/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +68062,79037,71497,Probation,Cunningham,Jermaine,NULL,Male,African-American,07/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-0.5,5,Medium,New,1,0 +68062,79037,71497,Probation,Cunningham,Jermaine,NULL,Male,African-American,07/04/87,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +68046,79016,71477,Broward County,Graham,Maerethe,NULL,Female,African-American,07/23/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,2,Medium,7,Risk of Violence,-2.64,2,Low,New,1,0 +68046,79016,71477,Broward County,Graham,Maerethe,NULL,Female,African-American,07/23/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +68046,79016,71477,Broward County,Graham,Maerethe,NULL,Female,African-American,07/23/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,2,Medium,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +38357,79018,71479,PRETRIAL,Reyes,Santos,NULL,Male,Hispanic,09/26/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +38357,79018,71479,PRETRIAL,Reyes,Santos,NULL,Male,Hispanic,09/26/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +38357,79018,71479,PRETRIAL,Reyes,Santos,NULL,Male,Hispanic,09/26/85,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68060,79035,71495,Probation,smith,houston,NULL,Male,Caucasian,10/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +68060,79035,71495,Probation,smith,houston,NULL,Male,Caucasian,10/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +68060,79035,71495,Probation,smith,houston,NULL,Male,Caucasian,10/26/94,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68044,79014,71475,Probation,may,sarah,NULL,Female,African-American,03/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +68044,79014,71475,Probation,may,sarah,NULL,Female,African-American,03/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +68044,79014,71475,Probation,may,sarah,NULL,Female,African-American,03/11/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +61801,79002,64398,PRETRIAL,Haynes,Richard,NULL,Male,African-American,09/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,Copy,1,0 +61801,79002,64398,PRETRIAL,Haynes,Richard,NULL,Male,African-American,09/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,Copy,1,0 +61801,79002,64398,PRETRIAL,Haynes,Richard,NULL,Male,African-American,09/22/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +34500,79009,70685,PRETRIAL,Bonilla,Danny,R,Male,Hispanic,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,4,High,7,Risk of Violence,-1.15,8,High,Copy,1,0 +34500,79009,70685,PRETRIAL,Bonilla,Danny,R,Male,Hispanic,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,4,High,8,Risk of Recidivism,0.64,10,High,Copy,1,0 +34500,79009,70685,PRETRIAL,Bonilla,Danny,R,Male,Hispanic,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +34500,78102,70685,PRETRIAL,Bonilla,Danny,R,Male,Hispanic,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,4,High,7,Risk of Violence,-1.03,8,High,New,1,0 +34500,78102,70685,PRETRIAL,Bonilla,Danny,R,Male,Hispanic,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +34500,78102,70685,PRETRIAL,Bonilla,Danny,R,Male,Hispanic,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,4,High,18,Risk of Failure to Appear,32,9,High,New,1,0 +68052,79023,71484,Probation,Rodriguez,Rubisel,NULL,Female,Hispanic,07/27/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +68052,79023,71484,Probation,Rodriguez,Rubisel,NULL,Female,Hispanic,07/27/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +68052,79023,71484,Probation,Rodriguez,Rubisel,NULL,Female,Hispanic,07/27/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68056,79030,71490,PRETRIAL,SMITH,JOZIE,NULL,Male,Caucasian,07/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +68056,79030,71490,PRETRIAL,SMITH,JOZIE,NULL,Male,Caucasian,07/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +68056,79030,71490,PRETRIAL,SMITH,JOZIE,NULL,Male,Caucasian,07/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68058,79032,71492,Probation,DELGADO,DAVID,A,Male,Hispanic,06/23/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/25/14 0:00,1,Low,7,Risk of Violence,-3.3,1,Low,New,1,0 +68058,79032,71492,Probation,DELGADO,DAVID,A,Male,Hispanic,06/23/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/25/14 0:00,1,Low,8,Risk of Recidivism,-1.55,1,Low,New,1,0 +68058,79032,71492,Probation,DELGADO,DAVID,A,Male,Hispanic,06/23/81,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +56744,79031,71491,PRETRIAL,Miller,Barnabas,William,Male,Caucasian,07/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.49,3,Low,New,1,0 +56744,79031,71491,PRETRIAL,Miller,Barnabas,William,Male,Caucasian,07/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.44,9,High,New,1,0 +56744,79031,71491,PRETRIAL,Miller,Barnabas,William,Male,Caucasian,07/13/84,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +68036,79001,71466,PRETRIAL,LOY,ERIC,MILTON,Male,Caucasian,11/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.71,6,Medium,New,1,0 +68036,79001,71466,PRETRIAL,LOY,ERIC,MILTON,Male,Caucasian,11/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +68036,79001,71466,PRETRIAL,LOY,ERIC,MILTON,Male,Caucasian,11/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,New,1,0 +60620,79010,63082,Probation,Johnson,Chavalier,NULL,Male,African-American,04/09/96,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.45,10,High,New,1,0 +60620,79010,63082,Probation,Johnson,Chavalier,NULL,Male,African-American,04/09/96,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,7,Medium,New,1,0 +60620,79010,63082,Probation,Johnson,Chavalier,NULL,Male,African-American,04/09/96,17,All Scales,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,5,Medium,New,1,0 +68051,79022,71483,PRETRIAL,MACHESKY,NATHAN,NULL,Male,Caucasian,01/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +68051,79022,71483,PRETRIAL,MACHESKY,NATHAN,NULL,Male,Caucasian,01/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +68051,79022,71483,PRETRIAL,MACHESKY,NATHAN,NULL,Male,Caucasian,01/06/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68061,79036,71496,Probation,PARKS,JAMES,B,Male,Caucasian,05/20/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/25/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +68061,79036,71496,Probation,PARKS,JAMES,B,Male,Caucasian,05/20/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/25/14 0:00,1,Low,8,Risk of Recidivism,-1.42,1,Low,New,1,0 +68061,79036,71496,Probation,PARKS,JAMES,B,Male,Caucasian,05/20/54,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Separated,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68045,79015,71476,PRETRIAL,Bowles,Gregory,Gary,Male,African-American,05/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/25/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.24,3,Low,New,1,0 +68045,79015,71476,PRETRIAL,Bowles,Gregory,Gary,Male,African-American,05/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/25/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.32,9,High,New,1,0 +68045,79015,71476,PRETRIAL,Bowles,Gregory,Gary,Male,African-American,05/21/61,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,11/25/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +68047,79017,71478,Probation,dutherville,keitha,c,Male,African-American,10/27/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +68047,79017,71478,Probation,dutherville,keitha,c,Male,African-American,10/27/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.6,4,Low,New,1,0 +68047,79017,71478,Probation,dutherville,keitha,c,Male,African-American,10/27/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68053,79024,71485,PRETRIAL,SOLDIEW,ALBERTO,NULL,Male,African-American,01/27/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/25/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +68053,79024,71485,PRETRIAL,SOLDIEW,ALBERTO,NULL,Male,African-American,01/27/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/25/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +68053,79024,71485,PRETRIAL,SOLDIEW,ALBERTO,NULL,Male,African-American,01/27/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68063,79038,71498,Probation,Villalobos,Nelson,NULL,Male,Hispanic,09/03/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +68063,79038,71498,Probation,Villalobos,Nelson,NULL,Male,Hispanic,09/03/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +68063,79038,71498,Probation,Villalobos,Nelson,NULL,Male,Hispanic,09/03/86,22,Risk and Prescreen,Intake,English,Other,Probation,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +12156,12539,11658,DRRD,kraft,thomas,NULL,Male,Caucasian,09/30/79,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +12156,12539,11658,DRRD,kraft,thomas,NULL,Male,Caucasian,09/30/79,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-0.27,5,Medium,New,1,0 +12156,12539,11658,DRRD,kraft,thomas,NULL,Male,Caucasian,09/30/79,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68055,79028,71488,PRETRIAL,barnes,joseph,NULL,Male,Caucasian,03/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +68055,79028,71488,PRETRIAL,barnes,joseph,NULL,Male,Caucasian,03/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +68055,79028,71488,PRETRIAL,barnes,joseph,NULL,Male,Caucasian,03/23/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +68049,79020,71481,PRETRIAL,Chaney,Shetera,NULL,Female,African-American,11/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +68049,79020,71481,PRETRIAL,Chaney,Shetera,NULL,Female,African-American,11/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-1.25,3,Low,New,1,0 +68049,79020,71481,PRETRIAL,Chaney,Shetera,NULL,Female,African-American,11/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68057,79033,71493,Probation,Roldan,Carman,NULL,Female,Hispanic,12/09/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/25/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +68057,79033,71493,Probation,Roldan,Carman,NULL,Female,Hispanic,12/09/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/25/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +68057,79033,71493,Probation,Roldan,Carman,NULL,Female,Hispanic,12/09/61,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Married,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68038,79004,71468,PRETRIAL,STARR,JAMEL,NULL,Male,Caucasian,02/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +68038,79004,71468,PRETRIAL,STARR,JAMEL,NULL,Male,Caucasian,02/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +68038,79004,71468,PRETRIAL,STARR,JAMEL,NULL,Male,Caucasian,02/12/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +68054,79025,71486,Probation,Grier,Margaret,NULL,Female,African-American,07/14/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,1,Low,7,Risk of Violence,-4.26,1,Low,New,1,0 +68054,79025,71486,Probation,Grier,Margaret,NULL,Female,African-American,07/14/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,1,Low,8,Risk of Recidivism,-2.49,1,Low,New,1,0 +68054,79025,71486,Probation,Grier,Margaret,NULL,Female,African-American,07/14/56,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,11/25/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +24803,79054,23976,Probation,davisjr,dwight,NULL,Male,African-American,04/13/90,22,Risk and Prescreen,Intake,English,Conditional Release,Jail Inmate,Single,11/26/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,Copy,1,0 +24803,79054,23976,Probation,davisjr,dwight,NULL,Male,African-American,04/13/90,22,Risk and Prescreen,Intake,English,Conditional Release,Jail Inmate,Single,11/26/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,Copy,1,0 +24803,79054,23976,Probation,davisjr,dwight,NULL,Male,African-American,04/13/90,22,Risk and Prescreen,Intake,English,Conditional Release,Jail Inmate,Single,11/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +68070,79046,71506,PRETRIAL,BRAMHALL,DIANE,MARIE,Female,Caucasian,09/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/26/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +68070,79046,71506,PRETRIAL,BRAMHALL,DIANE,MARIE,Female,Caucasian,09/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/26/14 0:00,1,Low,8,Risk of Recidivism,-1.8,1,Low,New,1,0 +68070,79046,71506,PRETRIAL,BRAMHALL,DIANE,MARIE,Female,Caucasian,09/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/26/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68066,79041,71501,PRETRIAL,GYORFI,THOMAS,CHRISTIAN,Male,Caucasian,04/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +68066,79041,71501,PRETRIAL,GYORFI,THOMAS,CHRISTIAN,Male,Caucasian,04/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +68066,79041,71501,PRETRIAL,GYORFI,THOMAS,CHRISTIAN,Male,Caucasian,04/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68079,79056,71515,Probation,murphyquintana,amy,c,Female,Caucasian,08/16/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/26/14 0:00,2,Medium,7,Risk of Violence,-2.06,4,Low,New,1,0 +68079,79056,71515,Probation,murphyquintana,amy,c,Female,Caucasian,08/16/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.42,6,Medium,New,1,0 +68079,79056,71515,Probation,murphyquintana,amy,c,Female,Caucasian,08/16/83,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Divorced,11/26/14 0:00,2,Medium,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +24803,26175,23976,Probation,davisjr,dwight,NULL,Male,African-American,04/13/90,22,Risk and Prescreen,Intake,English,Conditional Release,Jail Inmate,Single,11/26/14 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +24803,26175,23976,Probation,davisjr,dwight,NULL,Male,African-American,04/13/90,22,Risk and Prescreen,Intake,English,Conditional Release,Jail Inmate,Single,11/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.26,6,Medium,New,1,0 +24803,26175,23976,Probation,davisjr,dwight,NULL,Male,African-American,04/13/90,22,Risk and Prescreen,Intake,English,Conditional Release,Jail Inmate,Single,11/26/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68073,79049,71509,PRETRIAL,shaw,gloria,NULL,Female,Caucasian,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,7,Risk of Violence,-2.79,2,Low,New,1,0 +68073,79049,71509,PRETRIAL,shaw,gloria,NULL,Female,Caucasian,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +68073,79049,71509,PRETRIAL,shaw,gloria,NULL,Female,Caucasian,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +68069,79045,71505,PRETRIAL,Henley,Constance,Madeline,Female,Caucasian,07/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/26/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +68069,79045,71505,PRETRIAL,Henley,Constance,Madeline,Female,Caucasian,07/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/26/14 0:00,1,Low,8,Risk of Recidivism,-2.25,1,Low,New,1,0 +68069,79045,71505,PRETRIAL,Henley,Constance,Madeline,Female,Caucasian,07/02/51,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/26/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68076,79052,71512,PRETRIAL,Hawthorne,Anthony,NULL,Male,African-American,09/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/26/14 0:00,2,Medium,7,Risk of Violence,-2.38,3,Low,New,1,0 +68076,79052,71512,PRETRIAL,Hawthorne,Anthony,NULL,Male,African-American,09/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +68076,79052,71512,PRETRIAL,Hawthorne,Anthony,NULL,Male,African-American,09/24/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/26/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68082,79059,71518,PRETRIAL,Villegasvillegas,Laura,Daniela,Female,Hispanic,03/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +68082,79059,71518,PRETRIAL,Villegasvillegas,Laura,Daniela,Female,Hispanic,03/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,8,Risk of Recidivism,-0.97,4,Low,New,1,0 +68082,79059,71518,PRETRIAL,Villegasvillegas,Laura,Daniela,Female,Hispanic,03/30/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +13030,79043,71503,PRETRIAL,BROWN,RODRICK,DWAYNE,Male,African-American,05/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,New,1,0 +13030,79043,71503,PRETRIAL,BROWN,RODRICK,DWAYNE,Male,African-American,05/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +13030,79043,71503,PRETRIAL,BROWN,RODRICK,DWAYNE,Male,African-American,05/26/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +68065,79040,71500,PRETRIAL,White,Donovan,NULL,Male,African-American,07/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +68065,79040,71500,PRETRIAL,White,Donovan,NULL,Male,African-American,07/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +68065,79040,71500,PRETRIAL,White,Donovan,NULL,Male,African-American,07/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68080,79057,71516,PRETRIAL,ROSAMELIA,ROBERT,ALLEN,Male,Caucasian,06/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/26/14 0:00,1,Low,7,Risk of Violence,-3.81,1,Low,New,1,0 +68080,79057,71516,PRETRIAL,ROSAMELIA,ROBERT,ALLEN,Male,Caucasian,06/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/26/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +68080,79057,71516,PRETRIAL,ROSAMELIA,ROBERT,ALLEN,Male,Caucasian,06/29/59,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,11/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68075,79051,71511,PRETRIAL,Lacruz,Joseph,A,Male,Caucasian,06/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/26/14 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +68075,79051,71511,PRETRIAL,Lacruz,Joseph,A,Male,Caucasian,06/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +68075,79051,71511,PRETRIAL,Lacruz,Joseph,A,Male,Caucasian,06/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,11/26/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68077,79053,71513,PRETRIAL,PIERCY,ALEXANDRIA,HAVEN,Female,Caucasian,03/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +68077,79053,71513,PRETRIAL,PIERCY,ALEXANDRIA,HAVEN,Female,Caucasian,03/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,4,High,8,Risk of Recidivism,0.49,10,High,New,1,0 +68077,79053,71513,PRETRIAL,PIERCY,ALEXANDRIA,HAVEN,Female,Caucasian,03/11/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68068,79044,71504,PRETRIAL,Collazos,Emely,NULL,Male,Hispanic,05/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +68068,79044,71504,PRETRIAL,Collazos,Emely,NULL,Male,Hispanic,05/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +68068,79044,71504,PRETRIAL,Collazos,Emely,NULL,Male,Hispanic,05/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68067,79042,71502,PRETRIAL,SCZEPANSKI,RICHARD,WILLIAM,Male,Caucasian,08/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/26/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +68067,79042,71502,PRETRIAL,SCZEPANSKI,RICHARD,WILLIAM,Male,Caucasian,08/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/26/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +68067,79042,71502,PRETRIAL,SCZEPANSKI,RICHARD,WILLIAM,Male,Caucasian,08/01/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,11/26/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68074,79050,71510,PRETRIAL,LINTON,AKEEM,NULL,Male,African-American,03/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +68074,79050,71510,PRETRIAL,LINTON,AKEEM,NULL,Male,African-American,03/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,8,Risk of Recidivism,-1.02,2,Low,New,1,0 +68074,79050,71510,PRETRIAL,LINTON,AKEEM,NULL,Male,African-American,03/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68081,79058,71517,PRETRIAL,SMITH,CONNOR,PATRICK,Male,Caucasian,07/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +68081,79058,71517,PRETRIAL,SMITH,CONNOR,PATRICK,Male,Caucasian,07/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +68081,79058,71517,PRETRIAL,SMITH,CONNOR,PATRICK,Male,Caucasian,07/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68071,79047,71507,PRETRIAL,James,Christopher,Bruce,Male,Caucasian,04/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +68071,79047,71507,PRETRIAL,James,Christopher,Bruce,Male,Caucasian,04/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +68071,79047,71507,PRETRIAL,James,Christopher,Bruce,Male,Caucasian,04/15/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/26/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +68089,79068,71527,PRETRIAL,Balog,Emily,Deanne,Female,Caucasian,06/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/27/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +68089,79068,71527,PRETRIAL,Balog,Emily,Deanne,Female,Caucasian,06/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/27/14 0:00,1,Low,8,Risk of Recidivism,-1.03,3,Low,New,1,0 +68089,79068,71527,PRETRIAL,Balog,Emily,Deanne,Female,Caucasian,06/24/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,11/27/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +9783,79063,71522,Probation,Washington,Marvin,NULL,Male,African-American,07/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.47,7,Medium,New,1,0 +9783,79063,71522,Probation,Washington,Marvin,NULL,Male,African-American,07/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +9783,79063,71522,Probation,Washington,Marvin,NULL,Male,African-American,07/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +68086,79065,71524,PRETRIAL,CRUZ,JOSHUA,CASADO,Male,Caucasian,06/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +68086,79065,71524,PRETRIAL,CRUZ,JOSHUA,CASADO,Male,Caucasian,06/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +68086,79065,71524,PRETRIAL,CRUZ,JOSHUA,CASADO,Male,Caucasian,06/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68083,79060,71519,PRETRIAL,Mahmud,Nina,NULL,Male,African-American,06/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +68083,79060,71519,PRETRIAL,Mahmud,Nina,NULL,Male,African-American,06/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +68083,79060,71519,PRETRIAL,Mahmud,Nina,NULL,Male,African-American,06/04/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68084,79061,71520,PRETRIAL,Jeanty,Wilder,NULL,Male,African-American,06/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,1,Low,7,Risk of Violence,-1.88,5,Medium,New,1,0 +68084,79061,71520,PRETRIAL,Jeanty,Wilder,NULL,Male,African-American,06/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,New,1,0 +68084,79061,71520,PRETRIAL,Jeanty,Wilder,NULL,Male,African-American,06/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68087,79066,71525,PRETRIAL,Williams,Andy,Dean,Male,African-American,08/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.61,6,Medium,New,1,0 +68087,79066,71525,PRETRIAL,Williams,Andy,Dean,Male,African-American,08/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,New,1,0 +68087,79066,71525,PRETRIAL,Williams,Andy,Dean,Male,African-American,08/19/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68085,79062,71521,PRETRIAL,Williams,Wendy,NULL,Female,Other,06/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +68085,79062,71521,PRETRIAL,Williams,Wendy,NULL,Female,Other,06/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +68085,79062,71521,PRETRIAL,Williams,Wendy,NULL,Female,Other,06/30/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68088,79067,71526,PRETRIAL,Traslavina,Michelle,NULL,Female,Caucasian,10/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +68088,79067,71526,PRETRIAL,Traslavina,Michelle,NULL,Female,Caucasian,10/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,1,Low,8,Risk of Recidivism,-1.72,1,Low,New,1,0 +68088,79067,71526,PRETRIAL,Traslavina,Michelle,NULL,Female,Caucasian,10/12/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68100,79080,71539,PRETRIAL,Richman,Amie,NULL,Female,Caucasian,06/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +68100,79080,71539,PRETRIAL,Richman,Amie,NULL,Female,Caucasian,06/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +68100,79080,71539,PRETRIAL,Richman,Amie,NULL,Female,Caucasian,06/20/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68093,79072,71531,PRETRIAL,Mcgill,Bruse,NULL,Male,African-American,07/31/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,2,Medium,7,Risk of Violence,-2.1,4,Low,New,1,0 +68093,79072,71531,PRETRIAL,Mcgill,Bruse,NULL,Male,African-American,07/31/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,6,Medium,New,1,0 +68093,79072,71531,PRETRIAL,Mcgill,Bruse,NULL,Male,African-American,07/31/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68096,79075,71534,PRETRIAL,Thomas,Denfield,NULL,Male,African-American,06/20/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +68096,79075,71534,PRETRIAL,Thomas,Denfield,NULL,Male,African-American,06/20/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +68096,79075,71534,PRETRIAL,Thomas,Denfield,NULL,Male,African-American,06/20/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68091,79070,71529,PRETRIAL,Dixon,Doyle,NULL,Male,Caucasian,11/23/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +68091,79070,71529,PRETRIAL,Dixon,Doyle,NULL,Male,Caucasian,11/23/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,8,Risk of Recidivism,-2.38,1,Low,New,1,0 +68091,79070,71529,PRETRIAL,Dixon,Doyle,NULL,Male,Caucasian,11/23/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +48526,79077,71536,PRETRIAL,Clarke,Devin,NULL,Male,African-American,10/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,New,1,0 +48526,79077,71536,PRETRIAL,Clarke,Devin,NULL,Male,African-American,10/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.45,9,High,New,1,0 +48526,79077,71536,PRETRIAL,Clarke,Devin,NULL,Male,African-American,10/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +68094,79073,71532,PRETRIAL,Stricklin,Tony,NULL,Male,African-American,08/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +68094,79073,71532,PRETRIAL,Stricklin,Tony,NULL,Male,African-American,08/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +68094,79073,71532,PRETRIAL,Stricklin,Tony,NULL,Male,African-American,08/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68098,79078,71537,PRETRIAL,Gonzalez,Miguel,David,Male,Caucasian,12/09/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/28/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +68098,79078,71537,PRETRIAL,Gonzalez,Miguel,David,Male,Caucasian,12/09/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/28/14 0:00,1,Low,8,Risk of Recidivism,-1.4,1,Low,New,1,0 +68098,79078,71537,PRETRIAL,Gonzalez,Miguel,David,Male,Caucasian,12/09/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/28/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +46418,79081,46831,PRETRIAL,adams,rashad,NULL,Male,African-American,06/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,Copy,1,0 +46418,79081,46831,PRETRIAL,adams,rashad,NULL,Male,African-American,06/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.93,10,High,Copy,1,0 +46418,79081,46831,PRETRIAL,adams,rashad,NULL,Male,African-American,06/21/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +68095,79074,71533,PRETRIAL,Elien,Frederick,NULL,Male,African-American,06/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +68095,79074,71533,PRETRIAL,Elien,Frederick,NULL,Male,African-American,06/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +68095,79074,71533,PRETRIAL,Elien,Frederick,NULL,Male,African-American,06/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68090,79069,71528,PRETRIAL,Allen,Steven,NULL,Male,African-American,10/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,2,Medium,7,Risk of Violence,-2.24,3,Low,New,1,0 +68090,79069,71528,PRETRIAL,Allen,Steven,NULL,Male,African-American,10/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.31,6,Medium,New,1,0 +68090,79069,71528,PRETRIAL,Allen,Steven,NULL,Male,African-American,10/09/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +68097,79076,71535,PRETRIAL,Salem,Julio,NULL,Male,Caucasian,09/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +68097,79076,71535,PRETRIAL,Salem,Julio,NULL,Male,Caucasian,09/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,8,Risk of Recidivism,-1.51,1,Low,New,1,0 +68097,79076,71535,PRETRIAL,Salem,Julio,NULL,Male,Caucasian,09/12/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68099,79079,71538,PRETRIAL,Donnelly,Joseph,NULL,Male,Caucasian,10/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/28/14 0:00,1,Low,7,Risk of Violence,-4,1,Low,New,1,0 +68099,79079,71538,PRETRIAL,Donnelly,Joseph,NULL,Male,Caucasian,10/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/28/14 0:00,1,Low,8,Risk of Recidivism,-2.44,1,Low,New,1,0 +68099,79079,71538,PRETRIAL,Donnelly,Joseph,NULL,Male,Caucasian,10/28/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68092,79071,71530,PRETRIAL,Smith,Dominique,NULL,Male,African-American,01/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,7,Risk of Violence,-2.45,3,Low,New,1,0 +68092,79071,71530,PRETRIAL,Smith,Dominique,NULL,Male,African-American,01/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +68092,79071,71530,PRETRIAL,Smith,Dominique,NULL,Male,African-American,01/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/28/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68107,79089,71547,PRETRIAL,blaise,stanley,NULL,Male,African-American,09/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +68107,79089,71547,PRETRIAL,blaise,stanley,NULL,Male,African-American,09/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +68107,79089,71547,PRETRIAL,blaise,stanley,NULL,Male,African-American,09/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68110,79092,71550,PRETRIAL,BROWN,JAMES,NULL,Male,African-American,10/14/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/14 0:00,1,Low,7,Risk of Violence,-4.31,1,Low,New,1,0 +68110,79092,71550,PRETRIAL,BROWN,JAMES,NULL,Male,African-American,10/14/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/14 0:00,1,Low,8,Risk of Recidivism,-2.66,1,Low,New,1,0 +68110,79092,71550,PRETRIAL,BROWN,JAMES,NULL,Male,African-American,10/14/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68103,79084,71542,PRETRIAL,White,Carnel,NULL,Male,Other,09/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/14 0:00,1,Low,7,Risk of Violence,-3.46,1,Low,New,1,0 +68103,79084,71542,PRETRIAL,White,Carnel,NULL,Male,Other,09/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +68103,79084,71542,PRETRIAL,White,Carnel,NULL,Male,Other,09/29/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68105,79086,71544,PRETRIAL,Taylor,Sabrina,NULL,Male,Caucasian,10/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +68105,79086,71544,PRETRIAL,Taylor,Sabrina,NULL,Male,Caucasian,10/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +68105,79086,71544,PRETRIAL,Taylor,Sabrina,NULL,Male,Caucasian,10/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68108,79090,71548,PRETRIAL,COLOSIMO,ROBERT,SCOTT,Male,Caucasian,10/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,7,Risk of Violence,-3.28,1,Low,New,1,0 +68108,79090,71548,PRETRIAL,COLOSIMO,ROBERT,SCOTT,Male,Caucasian,10/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,8,Risk of Recidivism,-1.08,2,Low,New,1,0 +68108,79090,71548,PRETRIAL,COLOSIMO,ROBERT,SCOTT,Male,Caucasian,10/15/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +1236,79088,71546,PRETRIAL,PICKLE,ANTHONY,NULL,Male,African-American,07/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.53,6,Medium,New,1,0 +1236,79088,71546,PRETRIAL,PICKLE,ANTHONY,NULL,Male,African-American,07/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +1236,79088,71546,PRETRIAL,PICKLE,ANTHONY,NULL,Male,African-American,07/02/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68101,79082,71540,PRETRIAL,Louis-Baptiste,Alain,NULL,Male,Other,10/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +68101,79082,71540,PRETRIAL,Louis-Baptiste,Alain,NULL,Male,Other,10/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +68101,79082,71540,PRETRIAL,Louis-Baptiste,Alain,NULL,Male,Other,10/15/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68106,79087,71545,PRETRIAL,CHUKWURAH,PATRICK,OBINNA,Male,African-American,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +68106,79087,71545,PRETRIAL,CHUKWURAH,PATRICK,OBINNA,Male,African-American,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +68106,79087,71545,PRETRIAL,CHUKWURAH,PATRICK,OBINNA,Male,African-American,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +68112,79094,71552,PRETRIAL,DOWNS,DAVID,DEWANN,Male,African-American,01/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/14 0:00,1,Low,7,Risk of Violence,-3.49,1,Low,New,1,0 +68112,79094,71552,PRETRIAL,DOWNS,DAVID,DEWANN,Male,African-American,01/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/14 0:00,1,Low,8,Risk of Recidivism,-1.98,1,Low,New,1,0 +68112,79094,71552,PRETRIAL,DOWNS,DAVID,DEWANN,Male,African-American,01/07/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68109,79091,71549,PRETRIAL,ATLI,IBRAHIM,NULL,Male,Other,08/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +68109,79091,71549,PRETRIAL,ATLI,IBRAHIM,NULL,Male,Other,08/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/14 0:00,1,Low,8,Risk of Recidivism,-1.2,2,Low,New,1,0 +68109,79091,71549,PRETRIAL,ATLI,IBRAHIM,NULL,Male,Other,08/01/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,11/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68104,79085,71543,PRETRIAL,Davenport,Stephen,NULL,Male,Caucasian,09/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +68104,79085,71543,PRETRIAL,Davenport,Stephen,NULL,Male,Caucasian,09/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +68104,79085,71543,PRETRIAL,Davenport,Stephen,NULL,Male,Caucasian,09/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,18,Risk of Failure to Appear,28,8,High,New,1,0 +68102,79083,71541,PRETRIAL,Johnson,Darrell,NULL,Male,African-American,03/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +68102,79083,71541,PRETRIAL,Johnson,Darrell,NULL,Male,African-American,03/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,8,Risk of Recidivism,-1.63,1,Low,New,1,0 +68102,79083,71541,PRETRIAL,Johnson,Darrell,NULL,Male,African-American,03/16/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68111,79093,71551,PRETRIAL,kane,igor,NULL,Male,Caucasian,05/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +68111,79093,71551,PRETRIAL,kane,igor,NULL,Male,Caucasian,05/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +68111,79093,71551,PRETRIAL,kane,igor,NULL,Male,Caucasian,05/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +11906,12284,11422,PRETRIAL,THOMPSON-HENRY,ZANE,DERON,Male,African-American,10/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,4,High,7,Risk of Violence,-0.39,10,High,New,1,0 +11906,12284,11422,PRETRIAL,THOMPSON-HENRY,ZANE,DERON,Male,African-American,10/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,4,High,8,Risk of Recidivism,0.82,10,High,New,1,0 +11906,12284,11422,PRETRIAL,THOMPSON-HENRY,ZANE,DERON,Male,African-American,10/31/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,11/29/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68121,79098,71556,PRETRIAL,Glazer,Michael,Wayne,Male,Caucasian,04/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/14 0:00,1,Low,7,Risk of Violence,-3.51,1,Low,New,1,0 +68121,79098,71556,PRETRIAL,Glazer,Michael,Wayne,Male,Caucasian,04/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +68121,79098,71556,PRETRIAL,Glazer,Michael,Wayne,Male,Caucasian,04/07/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/1/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68124,79095,71553,PRETRIAL,MCCUTCHEON,MARIA,NULL,Male,African-American,05/04/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/1/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.49,7,Medium,New,1,0 +68124,79095,71553,PRETRIAL,MCCUTCHEON,MARIA,NULL,Male,African-American,05/04/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/1/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.33,9,High,New,1,0 +68124,79095,71553,PRETRIAL,MCCUTCHEON,MARIA,NULL,Male,African-American,05/04/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/1/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +7066,79102,71559,PRETRIAL,Beaver,Stephon,Alexander,Male,African-American,02/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.56,6,Medium,New,1,0 +7066,79102,71559,PRETRIAL,Beaver,Stephon,Alexander,Male,African-American,02/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.3,8,High,New,1,0 +7066,79102,71559,PRETRIAL,Beaver,Stephon,Alexander,Male,African-American,02/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68133,79109,71566,PRETRIAL,Cooper,Roger,NULL,Male,African-American,12/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,2,Medium,7,Risk of Violence,-2.47,3,Low,New,1,0 +68133,79109,71566,PRETRIAL,Cooper,Roger,NULL,Male,African-American,12/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +68133,79109,71566,PRETRIAL,Cooper,Roger,NULL,Male,African-American,12/04/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68131,79107,71564,PRETRIAL,Campbell,Ezekiel,H,Male,Other,09/14/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/2/14 0:00,1,Low,7,Risk of Violence,-4.24,1,Low,New,1,0 +68131,79107,71564,PRETRIAL,Campbell,Ezekiel,H,Male,Other,09/14/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/2/14 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +68131,79107,71564,PRETRIAL,Campbell,Ezekiel,H,Male,Other,09/14/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/2/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +68128,79104,71561,PRETRIAL,SILVER,OSWALD,NULL,Male,African-American,11/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.86,9,High,New,1,0 +68128,79104,71561,PRETRIAL,SILVER,OSWALD,NULL,Male,African-American,11/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +68128,79104,71561,PRETRIAL,SILVER,OSWALD,NULL,Male,African-American,11/23/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68135,79111,71568,PRETRIAL,Gutierrez-Centurion,Alana,NULL,Female,Hispanic,11/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,2,Medium,7,Risk of Violence,-1.77,5,Medium,New,1,0 +68135,79111,71568,PRETRIAL,Gutierrez-Centurion,Alana,NULL,Female,Hispanic,11/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +68135,79111,71568,PRETRIAL,Gutierrez-Centurion,Alana,NULL,Female,Hispanic,11/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68129,79105,71562,PRETRIAL,House,Raysheuna,NULL,Female,African-American,05/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +68129,79105,71562,PRETRIAL,House,Raysheuna,NULL,Female,African-American,05/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +68129,79105,71562,PRETRIAL,House,Raysheuna,NULL,Female,African-American,05/20/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68126,79100,71558,PRETRIAL,CAVEY,CHARLES,NULL,Male,Caucasian,06/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/2/14 0:00,1,Low,7,Risk of Violence,-3.8,1,Low,New,1,0 +68126,79100,71558,PRETRIAL,CAVEY,CHARLES,NULL,Male,Caucasian,06/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/2/14 0:00,1,Low,8,Risk of Recidivism,-1.6,1,Low,New,1,0 +68126,79100,71558,PRETRIAL,CAVEY,CHARLES,NULL,Male,Caucasian,06/24/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/2/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +68137,79113,71570,PRETRIAL,Glueck,Bruce,NULL,Male,Caucasian,10/28/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +68137,79113,71570,PRETRIAL,Glueck,Bruce,NULL,Male,Caucasian,10/28/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +68137,79113,71570,PRETRIAL,Glueck,Bruce,NULL,Male,Caucasian,10/28/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68134,79110,71567,PRETRIAL,Michi,Roy,Thomas,Male,Caucasian,11/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/2/14 0:00,1,Low,7,Risk of Violence,-3.74,1,Low,New,1,0 +68134,79110,71567,PRETRIAL,Michi,Roy,Thomas,Male,Caucasian,11/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/2/14 0:00,1,Low,8,Risk of Recidivism,-1.94,1,Low,New,1,0 +68134,79110,71567,PRETRIAL,Michi,Roy,Thomas,Male,Caucasian,11/29/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/2/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68130,79106,71563,PRETRIAL,SYLVESTER,HAKIM,NULL,Male,African-American,04/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +68130,79106,71563,PRETRIAL,SYLVESTER,HAKIM,NULL,Male,African-American,04/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +68130,79106,71563,PRETRIAL,SYLVESTER,HAKIM,NULL,Male,African-American,04/12/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,1,Low,18,Risk of Failure to Appear,35,10,High,New,1,0 +16093,79114,71571,PRETRIAL,sutton,david,justin,Male,Caucasian,06/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,New,1,0 +16093,79114,71571,PRETRIAL,sutton,david,justin,Male,Caucasian,06/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +16093,79114,71571,PRETRIAL,sutton,david,justin,Male,Caucasian,06/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +51652,79101,55206,PRETRIAL,Wright,Byron,Moctavius,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.89,5,Medium,Copy,1,0 +51652,79101,55206,PRETRIAL,Wright,Byron,Moctavius,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,Copy,1,0 +51652,79101,55206,PRETRIAL,Wright,Byron,Moctavius,Male,African-American,06/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +29066,79099,71557,PRETRIAL,Donaldson,Dwayne,NULL,Male,African-American,08/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.12,8,High,New,1,0 +29066,79099,71557,PRETRIAL,Donaldson,Dwayne,NULL,Male,African-American,08/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +29066,79099,71557,PRETRIAL,Donaldson,Dwayne,NULL,Male,African-American,08/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68127,79103,71560,PRETRIAL,Parnell,Ledford,NULL,Male,Caucasian,02/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +68127,79103,71560,PRETRIAL,Parnell,Ledford,NULL,Male,Caucasian,02/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,1,Low,8,Risk of Recidivism,-1.49,1,Low,New,1,0 +68127,79103,71560,PRETRIAL,Parnell,Ledford,NULL,Male,Caucasian,02/21/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68136,79112,71569,PRETRIAL,MILNER,ANTHONY,NULL,Male,African-American,06/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/14 0:00,2,Medium,7,Risk of Violence,-2.96,1,Low,New,1,0 +68136,79112,71569,PRETRIAL,MILNER,ANTHONY,NULL,Male,African-American,06/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +68136,79112,71569,PRETRIAL,MILNER,ANTHONY,NULL,Male,African-American,06/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/2/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68132,79108,71565,PRETRIAL,THEOPHILE,FEGUENS,NULL,Male,Other,03/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/2/14 0:00,1,Low,7,Risk of Violence,-3.7,1,Low,New,1,0 +68132,79108,71565,PRETRIAL,THEOPHILE,FEGUENS,NULL,Male,Other,03/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/2/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +68132,79108,71565,PRETRIAL,THEOPHILE,FEGUENS,NULL,Male,Other,03/02/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/2/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68150,79129,71584,PRETRIAL,PAUL,FAITH,NULL,Female,African-American,01/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +68150,79129,71584,PRETRIAL,PAUL,FAITH,NULL,Female,African-American,01/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,8,Risk of Recidivism,-1.02,4,Low,New,1,0 +68150,79129,71584,PRETRIAL,PAUL,FAITH,NULL,Female,African-American,01/18/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +32123,34056,31138,PRETRIAL,WALKER,ZHIVAGO,DEAN,Male,Caucasian,12/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/3/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,New,1,0 +32123,34056,31138,PRETRIAL,WALKER,ZHIVAGO,DEAN,Male,Caucasian,12/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/3/14 0:00,4,High,8,Risk of Recidivism,0.64,10,High,New,1,0 +32123,34056,31138,PRETRIAL,WALKER,ZHIVAGO,DEAN,Male,Caucasian,12/25/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/3/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +68140,79117,71574,PRETRIAL,Owens,Leonard,NULL,Male,African-American,12/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +68140,79117,71574,PRETRIAL,Owens,Leonard,NULL,Male,African-American,12/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +68140,79117,71574,PRETRIAL,Owens,Leonard,NULL,Male,African-American,12/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68138,79115,71572,PRETRIAL,Sinclair,Donte,NULL,Male,African-American,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +68138,79115,71572,PRETRIAL,Sinclair,Donte,NULL,Male,African-American,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +68138,79115,71572,PRETRIAL,Sinclair,Donte,NULL,Male,African-American,06/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68156,79138,71590,PRETRIAL,Maddox,Fredrick,NULL,Male,African-American,10/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +68156,79138,71590,PRETRIAL,Maddox,Fredrick,NULL,Male,African-American,10/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +68156,79138,71590,PRETRIAL,Maddox,Fredrick,NULL,Male,African-American,10/27/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68155,79135,71589,PRETRIAL,Graham,Harry,NULL,Male,African-American,06/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.48,3,Low,New,1,0 +68155,79135,71589,PRETRIAL,Graham,Harry,NULL,Male,African-American,06/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.81,10,High,New,1,0 +68155,79135,71589,PRETRIAL,Graham,Harry,NULL,Male,African-American,06/30/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +68160,79143,71594,PRETRIAL,Ferdinand,Kaya,NULL,Female,Caucasian,06/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +68160,79143,71594,PRETRIAL,Ferdinand,Kaya,NULL,Female,Caucasian,06/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,8,Risk of Recidivism,-0.84,4,Low,New,1,0 +68160,79143,71594,PRETRIAL,Ferdinand,Kaya,NULL,Female,Caucasian,06/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68145,79122,71579,PRETRIAL,THOMPSON,STEVE,NULL,Male,Caucasian,12/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,7,Risk of Violence,-3.92,1,Low,New,1,0 +68145,79122,71579,PRETRIAL,THOMPSON,STEVE,NULL,Male,Caucasian,12/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,8,Risk of Recidivism,-2.32,1,Low,New,1,0 +68145,79122,71579,PRETRIAL,THOMPSON,STEVE,NULL,Male,Caucasian,12/13/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68148,79127,71582,PRETRIAL,Beyerlein,Alysha,NULL,Female,Caucasian,10/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,New,1,0 +68148,79127,71582,PRETRIAL,Beyerlein,Alysha,NULL,Female,Caucasian,10/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.17,9,High,New,1,0 +68148,79127,71582,PRETRIAL,Beyerlein,Alysha,NULL,Female,Caucasian,10/07/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68142,79119,71576,PRETRIAL,LITTLE,PHILO,NULL,Male,African-American,10/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +68142,79119,71576,PRETRIAL,LITTLE,PHILO,NULL,Male,African-American,10/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +68142,79119,71576,PRETRIAL,LITTLE,PHILO,NULL,Male,African-American,10/03/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68161,79144,71595,PRETRIAL,Rivera,Cynthia,NULL,Female,Hispanic,06/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +68161,79144,71595,PRETRIAL,Rivera,Cynthia,NULL,Female,Hispanic,06/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/14 0:00,1,Low,8,Risk of Recidivism,-1.84,1,Low,New,1,0 +68161,79144,71595,PRETRIAL,Rivera,Cynthia,NULL,Female,Hispanic,06/14/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +28515,79131,27560,PRETRIAL,AGOSTO,GIOVANNI,NULL,Male,Hispanic,06/11/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/3/14 0:00,4,High,7,Risk of Violence,-0.74,9,High,New,1,0 +28515,79131,27560,PRETRIAL,AGOSTO,GIOVANNI,NULL,Male,Hispanic,06/11/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/3/14 0:00,4,High,8,Risk of Recidivism,0.8,10,High,New,1,0 +28515,79131,27560,PRETRIAL,AGOSTO,GIOVANNI,NULL,Male,Hispanic,06/11/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/3/14 0:00,4,High,18,Risk of Failure to Appear,18,2,Low,New,1,0 +24868,69303,62826,Probation,Dennett,Pedro,NULL,Male,Hispanic,12/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/3/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +24868,69303,62826,Probation,Dennett,Pedro,NULL,Male,Hispanic,12/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/3/14 0:00,1,Low,8,Risk of Recidivism,-0.91,3,Low,New,1,0 +24868,69303,62826,Probation,Dennett,Pedro,NULL,Male,Hispanic,12/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +68141,79118,71575,PRETRIAL,SMITH,ANTHONY,NULL,Male,Caucasian,03/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +68141,79118,71575,PRETRIAL,SMITH,ANTHONY,NULL,Male,Caucasian,03/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +68141,79118,71575,PRETRIAL,SMITH,ANTHONY,NULL,Male,Caucasian,03/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68147,79126,71581,PRETRIAL,Passmsore,Lavarus,D,Male,African-American,09/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.72,6,Medium,Copy,1,0 +68147,79126,71581,PRETRIAL,Passmsore,Lavarus,D,Male,African-American,09/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.4,9,High,Copy,1,0 +68147,79126,71581,PRETRIAL,Passmsore,Lavarus,D,Male,African-American,09/22/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +68149,79128,71583,PRETRIAL,Cummings,John,NULL,Male,Caucasian,05/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +68149,79128,71583,PRETRIAL,Cummings,John,NULL,Male,Caucasian,05/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +68149,79128,71583,PRETRIAL,Cummings,John,NULL,Male,Caucasian,05/01/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68158,79141,71592,PRETRIAL,MORALES,TANAIRA,NULL,Female,Hispanic,08/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/3/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,New,1,0 +68158,79141,71592,PRETRIAL,MORALES,TANAIRA,NULL,Female,Hispanic,08/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/3/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +68158,79141,71592,PRETRIAL,MORALES,TANAIRA,NULL,Female,Hispanic,08/02/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68143,79120,71577,PRETRIAL,Registre,Kirby,NULL,Male,African-American,06/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,4,High,7,Risk of Violence,-0.84,9,High,New,1,0 +68143,79120,71577,PRETRIAL,Registre,Kirby,NULL,Male,African-American,06/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,4,High,8,Risk of Recidivism,0.62,10,High,New,1,0 +68143,79120,71577,PRETRIAL,Registre,Kirby,NULL,Male,African-American,06/21/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68154,79134,71588,PRETRIAL,HELLER,BREONTE,NULL,Male,African-American,09/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +68154,79134,71588,PRETRIAL,HELLER,BREONTE,NULL,Male,African-American,09/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,4,High,8,Risk of Recidivism,0.11,8,High,New,1,0 +68154,79134,71588,PRETRIAL,HELLER,BREONTE,NULL,Male,African-American,09/03/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,4,High,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68144,79121,71578,PRETRIAL,Weekes,Denis,B,Male,African-American,01/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,7,Risk of Violence,-1.87,5,Medium,New,1,0 +68144,79121,71578,PRETRIAL,Weekes,Denis,B,Male,African-American,01/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +68144,79121,71578,PRETRIAL,Weekes,Denis,B,Male,African-American,01/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +24868,79137,62826,Probation,Dennett,Pedro,NULL,Male,Hispanic,12/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/3/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,Copy,1,0 +24868,79137,62826,Probation,Dennett,Pedro,NULL,Male,Hispanic,12/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/3/14 0:00,1,Low,8,Risk of Recidivism,-0.93,3,Low,Copy,1,0 +24868,79137,62826,Probation,Dennett,Pedro,NULL,Male,Hispanic,12/27/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +68159,79142,71593,PRETRIAL,Jano,Bart,NULL,Male,Caucasian,10/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.9,9,High,New,1,0 +68159,79142,71593,PRETRIAL,Jano,Bart,NULL,Male,Caucasian,10/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +68159,79142,71593,PRETRIAL,Jano,Bart,NULL,Male,Caucasian,10/08/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +68139,79116,71573,PRETRIAL,Lorasantos,Luis,Davy,Male,Caucasian,11/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.98,9,High,New,1,0 +68139,79116,71573,PRETRIAL,Lorasantos,Luis,Davy,Male,Caucasian,11/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,7,Medium,New,1,0 +68139,79116,71573,PRETRIAL,Lorasantos,Luis,Davy,Male,Caucasian,11/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +68146,79123,71580,PRETRIAL,laporta,anthony,NULL,Male,Caucasian,07/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +68146,79123,71580,PRETRIAL,laporta,anthony,NULL,Male,Caucasian,07/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +68146,79123,71580,PRETRIAL,laporta,anthony,NULL,Male,Caucasian,07/07/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68151,79130,71585,PRETRIAL,GALLO,ROXANA,NULL,Female,Hispanic,02/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +68151,79130,71585,PRETRIAL,GALLO,ROXANA,NULL,Female,Hispanic,02/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +68151,79130,71585,PRETRIAL,GALLO,ROXANA,NULL,Female,Hispanic,02/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/3/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68173,79151,71602,PRETRIAL,Chi,Addison,NULL,Male,Caucasian,07/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +68173,79151,71602,PRETRIAL,Chi,Addison,NULL,Male,Caucasian,07/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +68173,79151,71602,PRETRIAL,Chi,Addison,NULL,Male,Caucasian,07/31/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68175,79153,71604,PRETRIAL,Andrews,Larry,Donnall,Male,African-American,11/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +68175,79153,71604,PRETRIAL,Andrews,Larry,Donnall,Male,African-American,11/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +68175,79153,71604,PRETRIAL,Andrews,Larry,Donnall,Male,African-American,11/23/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68183,79163,71612,PRETRIAL,Knight,Paul,NULL,Male,Caucasian,05/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/14 0:00,2,Medium,7,Risk of Violence,-1.43,7,Medium,New,1,0 +68183,79163,71612,PRETRIAL,Knight,Paul,NULL,Male,Caucasian,05/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.05,7,Medium,New,1,0 +68183,79163,71612,PRETRIAL,Knight,Paul,NULL,Male,Caucasian,05/01/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +68164,79146,71597,PRETRIAL,ROBERTS,CHRISTOHER,NULL,Male,African-American,07/26/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +68164,79146,71597,PRETRIAL,ROBERTS,CHRISTOHER,NULL,Male,African-American,07/26/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-1.03,2,Low,New,1,0 +68164,79146,71597,PRETRIAL,ROBERTS,CHRISTOHER,NULL,Male,African-American,07/26/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68179,79158,71608,PRETRIAL,Sargent,Christina,S,Female,Caucasian,12/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.21,4,Low,New,1,0 +68179,79158,71608,PRETRIAL,Sargent,Christina,S,Female,Caucasian,12/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.82,10,High,New,1,0 +68179,79158,71608,PRETRIAL,Sargent,Christina,S,Female,Caucasian,12/24/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +68064,79039,71499,PRETRIAL,Robinson,Yalera,NULL,Male,African-American,04/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-3.65,1,Low,New,1,0 +68064,79039,71499,PRETRIAL,Robinson,Yalera,NULL,Male,African-American,04/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +68064,79039,71499,PRETRIAL,Robinson,Yalera,NULL,Male,African-American,04/10/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68177,79155,71606,PRETRIAL,Johnson,Selisia,Michelle,Female,African-American,10/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +68177,79155,71606,PRETRIAL,Johnson,Selisia,Michelle,Female,African-American,10/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-0.68,5,Medium,New,1,0 +68177,79155,71606,PRETRIAL,Johnson,Selisia,Michelle,Female,African-American,10/07/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +68182,79162,71611,PRETRIAL,bell,jimmy,NULL,Male,African-American,04/02/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.18,4,Low,New,1,0 +68182,79162,71611,PRETRIAL,bell,jimmy,NULL,Male,African-American,04/02/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.54,9,High,New,1,0 +68182,79162,71611,PRETRIAL,bell,jimmy,NULL,Male,African-American,04/02/57,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,29,8,High,New,1,0 +68169,79147,71598,PRETRIAL,SMITH,FRANK,NULL,Male,Caucasian,07/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +68169,79147,71598,PRETRIAL,SMITH,FRANK,NULL,Male,Caucasian,07/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +68169,79147,71598,PRETRIAL,SMITH,FRANK,NULL,Male,Caucasian,07/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +68171,79149,71600,PRETRIAL,Desilvio,Dominic,A,Male,Caucasian,02/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +68171,79149,71600,PRETRIAL,Desilvio,Dominic,A,Male,Caucasian,02/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +68171,79149,71600,PRETRIAL,Desilvio,Dominic,A,Male,Caucasian,02/06/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68178,79156,71607,PRETRIAL,OSCAR,BRIANNA,NICOLE,Female,African-American,03/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-2.63,2,Low,New,1,0 +68178,79156,71607,PRETRIAL,OSCAR,BRIANNA,NICOLE,Female,African-American,03/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-1.42,2,Low,New,1,0 +68178,79156,71607,PRETRIAL,OSCAR,BRIANNA,NICOLE,Female,African-American,03/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +36453,79161,45393,PRETRIAL,Perry,Stephen,NULL,Male,African-American,08/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,Copy,1,0 +36453,79161,45393,PRETRIAL,Perry,Stephen,NULL,Male,African-American,08/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,Copy,1,0 +36453,79161,45393,PRETRIAL,Perry,Stephen,NULL,Male,African-American,08/03/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +68189,79169,71618,PRETRIAL,Zeitlin,Rochelle,NULL,Female,Caucasian,08/08/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +68189,79169,71618,PRETRIAL,Zeitlin,Rochelle,NULL,Female,Caucasian,08/08/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-1.2,3,Low,New,1,0 +68189,79169,71618,PRETRIAL,Zeitlin,Rochelle,NULL,Female,Caucasian,08/08/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,27,8,High,New,1,0 +68170,79148,71599,PRETRIAL,Colorado,Andres,NULL,Male,Hispanic,11/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-1.78,5,Medium,New,1,0 +68170,79148,71599,PRETRIAL,Colorado,Andres,NULL,Male,Hispanic,11/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +68170,79148,71599,PRETRIAL,Colorado,Andres,NULL,Male,Hispanic,11/24/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +43473,47586,43430,PRETRIAL,REID JR,NEVILLE,D,Male,African-American,12/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,2,Medium,7,Risk of Violence,-3.06,1,Low,New,1,0 +43473,47586,43430,PRETRIAL,REID JR,NEVILLE,D,Male,African-American,12/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +43473,47586,43430,PRETRIAL,REID JR,NEVILLE,D,Male,African-American,12/21/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,2,Medium,18,Risk of Failure to Appear,29,8,High,New,1,0 +68162,79145,71596,PRETRIAL,DORVAL,JEFFREY,NULL,Male,African-American,03/24/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,4,High,7,Risk of Violence,-0.73,9,High,New,1,0 +68162,79145,71596,PRETRIAL,DORVAL,JEFFREY,NULL,Male,African-American,03/24/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,4,High,8,Risk of Recidivism,0.83,10,High,New,1,0 +68162,79145,71596,PRETRIAL,DORVAL,JEFFREY,NULL,Male,African-American,03/24/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68172,79150,71601,PRETRIAL,Titus,Woodjerry,NULL,Male,Other,10/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-2.01,4,Low,New,1,0 +68172,79150,71601,PRETRIAL,Titus,Woodjerry,NULL,Male,Other,10/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +68172,79150,71601,PRETRIAL,Titus,Woodjerry,NULL,Male,Other,10/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68176,79154,71605,PRETRIAL,Thomas,George,Sylvester,Male,African-American,06/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/4/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +68176,79154,71605,PRETRIAL,Thomas,George,Sylvester,Male,African-American,06/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/4/14 0:00,1,Low,8,Risk of Recidivism,-2.36,1,Low,New,1,0 +68176,79154,71605,PRETRIAL,Thomas,George,Sylvester,Male,African-American,06/26/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68188,79168,71617,PRETRIAL,Anderson,Sylvia,NULL,Female,African-American,08/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +68188,79168,71617,PRETRIAL,Anderson,Sylvia,NULL,Female,African-American,08/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,8,Risk of Recidivism,-2.42,1,Low,New,1,0 +68188,79168,71617,PRETRIAL,Anderson,Sylvia,NULL,Female,African-American,08/27/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/4/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68192,79175,71621,PRETRIAL,Stanley,Steven,NULL,Male,Caucasian,06/12/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/5/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +68192,79175,71621,PRETRIAL,Stanley,Steven,NULL,Male,Caucasian,06/12/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/5/14 0:00,1,Low,8,Risk of Recidivism,-0.8,3,Low,New,1,0 +68192,79175,71621,PRETRIAL,Stanley,Steven,NULL,Male,Caucasian,06/12/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/5/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68205,79189,71635,PRETRIAL,FERRARA,KAYCIE,NULL,Female,Caucasian,11/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/14 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +68205,79189,71635,PRETRIAL,FERRARA,KAYCIE,NULL,Female,Caucasian,11/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.46,6,Medium,New,1,0 +68205,79189,71635,PRETRIAL,FERRARA,KAYCIE,NULL,Female,Caucasian,11/25/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/14 0:00,2,Medium,18,Risk of Failure to Appear,20,4,Low,New,1,0 +68197,79180,71626,PRETRIAL,Argueta,Maria,Elena,Female,Hispanic,09/01/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +68197,79180,71626,PRETRIAL,Argueta,Maria,Elena,Female,Hispanic,09/01/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,8,Risk of Recidivism,-2.62,1,Low,New,1,0 +68197,79180,71626,PRETRIAL,Argueta,Maria,Elena,Female,Hispanic,09/01/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +24543,79171,23725,PRETRIAL,HOLLIS,APRIL,D,Female,African-American,09/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,Copy,1,0 +24543,79171,23725,PRETRIAL,HOLLIS,APRIL,D,Female,African-American,09/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,10,High,Copy,1,0 +24543,79171,23725,PRETRIAL,HOLLIS,APRIL,D,Female,African-American,09/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +65192,79173,68273,PRETRIAL,Tillman,Storm,NULL,Male,African-American,04/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,Copy,1,0 +65192,79173,68273,PRETRIAL,Tillman,Storm,NULL,Male,African-American,04/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,Copy,1,0 +65192,79173,68273,PRETRIAL,Tillman,Storm,NULL,Male,African-American,04/07/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +68203,79187,71633,PRETRIAL,Golden,Corey,NULL,Male,Caucasian,02/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +68203,79187,71633,PRETRIAL,Golden,Corey,NULL,Male,Caucasian,02/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +68203,79187,71633,PRETRIAL,Golden,Corey,NULL,Male,Caucasian,02/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68199,79182,71628,PRETRIAL,DOHERTY,SHARON,M,Female,Caucasian,06/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,2,Medium,7,Risk of Violence,-3.17,1,Low,New,1,0 +68199,79182,71628,PRETRIAL,DOHERTY,SHARON,M,Female,Caucasian,06/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.55,6,Medium,New,1,0 +68199,79182,71628,PRETRIAL,DOHERTY,SHARON,M,Female,Caucasian,06/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68208,79192,71638,PRETRIAL,Karnell,Ivan,NULL,Male,Caucasian,04/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,12/5/14 0:00,1,Low,7,Risk of Violence,-3.84,1,Low,New,1,0 +68208,79192,71638,PRETRIAL,Karnell,Ivan,NULL,Male,Caucasian,04/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,12/5/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +68208,79192,71638,PRETRIAL,Karnell,Ivan,NULL,Male,Caucasian,04/29/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Unknown,12/5/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68194,79177,71623,PRETRIAL,Iacino,joshua,NULL,Male,Caucasian,02/19/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +68194,79177,71623,PRETRIAL,Iacino,joshua,NULL,Male,Caucasian,02/19/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +68194,79177,71623,PRETRIAL,Iacino,joshua,NULL,Male,Caucasian,02/19/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68201,79184,71630,PRETRIAL,Murphy,Glenn,NULL,Male,African-American,08/20/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +68201,79184,71630,PRETRIAL,Murphy,Glenn,NULL,Male,African-American,08/20/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,8,Risk of Recidivism,-0.66,4,Low,New,1,0 +68201,79184,71630,PRETRIAL,Murphy,Glenn,NULL,Male,African-American,08/20/57,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,18,Risk of Failure to Appear,34,10,High,New,1,0 +63084,79185,71631,PRETRIAL,Vitiello,Anthony,Frank,Male,Caucasian,10/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,New,1,0 +63084,79185,71631,PRETRIAL,Vitiello,Anthony,Frank,Male,Caucasian,10/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,8,Risk of Recidivism,-0.71,4,Low,New,1,0 +63084,79185,71631,PRETRIAL,Vitiello,Anthony,Frank,Male,Caucasian,10/10/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +6662,6649,6254,PRETRIAL,Duncan,Paula,NULL,Female,Caucasian,07/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +6662,6649,6254,PRETRIAL,Duncan,Paula,NULL,Female,Caucasian,07/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.78,10,High,New,1,0 +6662,6649,6254,PRETRIAL,Duncan,Paula,NULL,Female,Caucasian,07/16/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +68195,79178,71624,PRETRIAL,Cross,James,Kaden,Male,Caucasian,05/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +68195,79178,71624,PRETRIAL,Cross,James,Kaden,Male,Caucasian,05/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +68195,79178,71624,PRETRIAL,Cross,James,Kaden,Male,Caucasian,05/15/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +23645,79172,22844,PRETRIAL,JONES,CLINTON,NULL,Male,African-American,05/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,4,High,7,Risk of Violence,-0.92,9,High,Copy,1,0 +23645,79172,22844,PRETRIAL,JONES,CLINTON,NULL,Male,African-American,05/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,4,High,8,Risk of Recidivism,0.48,9,High,Copy,1,0 +23645,79172,22844,PRETRIAL,JONES,CLINTON,NULL,Male,African-American,05/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +68196,79179,71625,PRETRIAL,Ramos,Jacob,NULL,Male,Caucasian,11/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +68196,79179,71625,PRETRIAL,Ramos,Jacob,NULL,Male,Caucasian,11/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,8,Risk of Recidivism,-0.56,4,Low,New,1,0 +68196,79179,71625,PRETRIAL,Ramos,Jacob,NULL,Male,Caucasian,11/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +55016,79193,56793,Broward County,Newson,Anthony,NULL,Male,African-American,04/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,Copy,1,0 +55016,79193,56793,Broward County,Newson,Anthony,NULL,Male,African-American,04/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,Copy,1,0 +55016,79193,56793,Broward County,Newson,Anthony,NULL,Male,African-American,04/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/5/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +68193,79176,71622,PRETRIAL,Campbell,Georgia,Nicole,Female,Other,01/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/5/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +68193,79176,71622,PRETRIAL,Campbell,Georgia,Nicole,Female,Other,01/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/5/14 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +68193,79176,71622,PRETRIAL,Campbell,Georgia,Nicole,Female,Other,01/18/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68198,79181,71627,PRETRIAL,Dennis,Demario,NULL,Male,African-American,01/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +68198,79181,71627,PRETRIAL,Dennis,Demario,NULL,Male,African-American,01/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +68198,79181,71627,PRETRIAL,Dennis,Demario,NULL,Male,African-American,01/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68191,79174,71620,PRETRIAL,Rodriguez,Evan,NULL,Male,Caucasian,01/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,2,Medium,7,Risk of Violence,-1.52,6,Medium,New,1,0 +68191,79174,71620,PRETRIAL,Rodriguez,Evan,NULL,Male,Caucasian,01/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,2,Medium,8,Risk of Recidivism,-0.59,4,Low,New,1,0 +68191,79174,71620,PRETRIAL,Rodriguez,Evan,NULL,Male,Caucasian,01/05/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68204,79188,71634,PRETRIAL,LINDER,CHARVIS,DEMETRIUS,Male,African-American,03/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +68204,79188,71634,PRETRIAL,LINDER,CHARVIS,DEMETRIUS,Male,African-American,03/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +68204,79188,71634,PRETRIAL,LINDER,CHARVIS,DEMETRIUS,Male,African-American,03/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/5/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +50521,79195,51560,PRETRIAL,Stephens,Charles,NULL,Male,Caucasian,05/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,7,Risk of Violence,-2.07,4,Low,Copy,1,0 +50521,79195,51560,PRETRIAL,Stephens,Charles,NULL,Male,Caucasian,05/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,Copy,1,0 +50521,79195,51560,PRETRIAL,Stephens,Charles,NULL,Male,Caucasian,05/04/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,Copy,1,0 +68214,79202,71645,PRETRIAL,PierrePaul,Hattrina,NULL,Female,African-American,03/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,4,High,7,Risk of Violence,-1.13,8,High,New,1,0 +68214,79202,71645,PRETRIAL,PierrePaul,Hattrina,NULL,Female,African-American,03/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,4,High,8,Risk of Recidivism,0.75,10,High,New,1,0 +68214,79202,71645,PRETRIAL,PierrePaul,Hattrina,NULL,Female,African-American,03/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68211,79199,71642,PRETRIAL,Wolf,Nicholas,NULL,Male,Caucasian,08/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +68211,79199,71642,PRETRIAL,Wolf,Nicholas,NULL,Male,Caucasian,08/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +68211,79199,71642,PRETRIAL,Wolf,Nicholas,NULL,Male,Caucasian,08/07/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +62359,79204,65043,PRETRIAL,GODDARD,RODERICK,LOUIS,Male,African-American,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,7,Risk of Violence,-1.41,7,Medium,Copy,1,0 +62359,79204,65043,PRETRIAL,GODDARD,RODERICK,LOUIS,Male,African-American,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,Copy,1,0 +62359,79204,65043,PRETRIAL,GODDARD,RODERICK,LOUIS,Male,African-American,06/08/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +68210,79198,71641,PRETRIAL,Mercedes,Juan,NULL,Male,Hispanic,09/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,7,Risk of Violence,-1.38,7,Medium,New,1,0 +68210,79198,71641,PRETRIAL,Mercedes,Juan,NULL,Male,Hispanic,09/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +68210,79198,71641,PRETRIAL,Mercedes,Juan,NULL,Male,Hispanic,09/30/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68212,79200,71643,PRETRIAL,Haynes,Dezekiel,Armonrajan,Male,African-American,11/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,7,Risk of Violence,-2.08,4,Low,New,1,0 +68212,79200,71643,PRETRIAL,Haynes,Dezekiel,Armonrajan,Male,African-American,11/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +68212,79200,71643,PRETRIAL,Haynes,Dezekiel,Armonrajan,Male,African-American,11/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68216,79205,71647,PRETRIAL,Drummond,Ralston,NULL,Male,Other,06/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/6/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +68216,79205,71647,PRETRIAL,Drummond,Ralston,NULL,Male,Other,06/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/6/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +68216,79205,71647,PRETRIAL,Drummond,Ralston,NULL,Male,Other,06/20/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/6/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68215,79203,71646,PRETRIAL,Eubanks,Terry,NULL,Male,African-American,09/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,1,Low,7,Risk of Violence,-2.28,3,Low,New,1,0 +68215,79203,71646,PRETRIAL,Eubanks,Terry,NULL,Male,African-American,09/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +68215,79203,71646,PRETRIAL,Eubanks,Terry,NULL,Male,African-American,09/24/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64473,79196,71639,PRETRIAL,ARNDT,ANDREW,NULL,Male,Caucasian,04/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +64473,79196,71639,PRETRIAL,ARNDT,ANDREW,NULL,Male,Caucasian,04/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +64473,79196,71639,PRETRIAL,ARNDT,ANDREW,NULL,Male,Caucasian,04/08/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/6/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68213,79201,71644,PRETRIAL,zemo,dara,NULL,Female,Caucasian,12/22/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/6/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +68213,79201,71644,PRETRIAL,zemo,dara,NULL,Female,Caucasian,12/22/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/6/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +68213,79201,71644,PRETRIAL,zemo,dara,NULL,Female,Caucasian,12/22/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/6/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68220,79210,71652,PRETRIAL,Preston,John,NULL,Male,Caucasian,01/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,7,Risk of Violence,-4.02,1,Low,New,1,0 +68220,79210,71652,PRETRIAL,Preston,John,NULL,Male,Caucasian,01/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +68220,79210,71652,PRETRIAL,Preston,John,NULL,Male,Caucasian,01/25/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68229,79222,71662,PRETRIAL,Pena,Berglio,Oswaldo,Male,Caucasian,07/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,2,Medium,7,Risk of Violence,-2.47,3,Low,New,1,0 +68229,79222,71662,PRETRIAL,Pena,Berglio,Oswaldo,Male,Caucasian,07/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +68229,79222,71662,PRETRIAL,Pena,Berglio,Oswaldo,Male,Caucasian,07/02/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68224,79215,71656,PRETRIAL,FIGUEROA,BARRINGTON,NULL,Male,African-American,08/27/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,7,Risk of Violence,-4.33,1,Low,New,1,0 +68224,79215,71656,PRETRIAL,FIGUEROA,BARRINGTON,NULL,Male,African-American,08/27/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,8,Risk of Recidivism,-2.74,1,Low,New,1,0 +68224,79215,71656,PRETRIAL,FIGUEROA,BARRINGTON,NULL,Male,African-American,08/27/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68225,79217,71658,PRETRIAL,Honeyghan,Nancy,NULL,Female,Caucasian,04/22/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/7/14 0:00,2,Medium,7,Risk of Violence,-3.14,1,Low,New,1,0 +68225,79217,71658,PRETRIAL,Honeyghan,Nancy,NULL,Female,Caucasian,04/22/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +68225,79217,71658,PRETRIAL,Honeyghan,Nancy,NULL,Female,Caucasian,04/22/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/7/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +49373,79216,71657,PRETRIAL,Henry,Clyde,NULL,Male,African-American,06/30/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +49373,79216,71657,PRETRIAL,Henry,Clyde,NULL,Male,African-American,06/30/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +49373,79216,71657,PRETRIAL,Henry,Clyde,NULL,Male,African-American,06/30/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68221,79211,71653,PRETRIAL,Hew,Terrence,NULL,Male,Other,03/18/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/14 0:00,1,Low,7,Risk of Violence,-4.44,1,Low,New,1,0 +68221,79211,71653,PRETRIAL,Hew,Terrence,NULL,Male,Other,03/18/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/14 0:00,1,Low,8,Risk of Recidivism,-2.86,1,Low,New,1,0 +68221,79211,71653,PRETRIAL,Hew,Terrence,NULL,Male,Other,03/18/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68218,79208,71650,PRETRIAL,Thompkins,Sharikia,NULL,Female,African-American,04/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,7,Risk of Violence,-1.8,5,Medium,New,1,0 +68218,79208,71650,PRETRIAL,Thompkins,Sharikia,NULL,Female,African-American,04/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +68218,79208,71650,PRETRIAL,Thompkins,Sharikia,NULL,Female,African-American,04/26/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +68217,79206,71648,PRETRIAL,FLORES,NERY,ANSELMO,Male,Caucasian,07/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +68217,79206,71648,PRETRIAL,FLORES,NERY,ANSELMO,Male,Caucasian,07/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +68217,79206,71648,PRETRIAL,FLORES,NERY,ANSELMO,Male,Caucasian,07/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +1782,79213,1480,PRETRIAL,sanders,dwayne,russell,Male,African-American,06/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/7/14 0:00,2,Medium,7,Risk of Violence,-2.74,2,Low,Copy,1,0 +1782,79213,1480,PRETRIAL,sanders,dwayne,russell,Male,African-American,06/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/7/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,Copy,1,0 +1782,79213,1480,PRETRIAL,sanders,dwayne,russell,Male,African-American,06/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/7/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +68226,79219,71659,PRETRIAL,Aliyez,Araz,NULL,Male,Caucasian,07/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +68226,79219,71659,PRETRIAL,Aliyez,Araz,NULL,Male,Caucasian,07/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,8,Risk of Recidivism,-1.16,2,Low,New,1,0 +68226,79219,71659,PRETRIAL,Aliyez,Araz,NULL,Male,Caucasian,07/10/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68228,79221,71661,PRETRIAL,Garcia,Ivan,Javier,Male,Hispanic,09/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +68228,79221,71661,PRETRIAL,Garcia,Ivan,Javier,Male,Hispanic,09/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +68228,79221,71661,PRETRIAL,Garcia,Ivan,Javier,Male,Hispanic,09/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +53705,79207,71649,PRETRIAL,Gabriel,Renet,NULL,Male,African-American,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +53705,79207,71649,PRETRIAL,Gabriel,Renet,NULL,Male,African-American,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +53705,79207,71649,PRETRIAL,Gabriel,Renet,NULL,Male,African-American,01/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68222,79212,71654,PRETRIAL,Williams,Ricardo,NULL,Male,African-American,05/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +68222,79212,71654,PRETRIAL,Williams,Ricardo,NULL,Male,African-American,05/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +68222,79212,71654,PRETRIAL,Williams,Ricardo,NULL,Male,African-American,05/14/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68227,79220,71660,PRETRIAL,Idleburgh,David,Leon,Male,African-American,10/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/7/14 0:00,1,Low,7,Risk of Violence,-2.86,2,Low,New,1,0 +68227,79220,71660,PRETRIAL,Idleburgh,David,Leon,Male,African-American,10/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/7/14 0:00,1,Low,8,Risk of Recidivism,-1.45,1,Low,New,1,0 +68227,79220,71660,PRETRIAL,Idleburgh,David,Leon,Male,African-American,10/04/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68219,79209,71651,PRETRIAL,Nelson,Angela,NULL,Female,African-American,05/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,7,Risk of Violence,-3.17,1,Low,New,1,0 +68219,79209,71651,PRETRIAL,Nelson,Angela,NULL,Female,African-American,05/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +68219,79209,71651,PRETRIAL,Nelson,Angela,NULL,Female,African-American,05/03/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68230,79223,71663,PRETRIAL,Avila,Juan,Carlos,Male,Hispanic,08/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/7/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +68230,79223,71663,PRETRIAL,Avila,Juan,Carlos,Male,Hispanic,08/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/7/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +68230,79223,71663,PRETRIAL,Avila,Juan,Carlos,Male,Hispanic,08/25/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68223,79214,71655,PRETRIAL,Rhoden,Robert,NULL,Male,Other,12/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,7,Risk of Violence,-3.69,1,Low,New,1,0 +68223,79214,71655,PRETRIAL,Rhoden,Robert,NULL,Male,Other,12/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,8,Risk of Recidivism,-1.96,1,Low,New,1,0 +68223,79214,71655,PRETRIAL,Rhoden,Robert,NULL,Male,Other,12/04/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/7/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +64493,79218,67504,PRETRIAL,Foster,Reginald,NULL,Male,African-American,01/29/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/7/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.62,6,Medium,Copy,1,0 +64493,79218,67504,PRETRIAL,Foster,Reginald,NULL,Male,African-American,01/29/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/7/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.51,9,High,Copy,1,0 +64493,79218,67504,PRETRIAL,Foster,Reginald,NULL,Male,African-American,01/29/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/7/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,Copy,1,0 +33349,79235,32446,PRETRIAL,Williams,Alexander,NULL,Male,African-American,11/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/8/14 0:00,2,Medium,7,Risk of Violence,-3.38,1,Low,Copy,1,0 +33349,79235,32446,PRETRIAL,Williams,Alexander,NULL,Male,African-American,11/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,Copy,1,0 +33349,79235,32446,PRETRIAL,Williams,Alexander,NULL,Male,African-American,11/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/8/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +68246,79244,71678,PRETRIAL,Adoni,Guy,NULL,Male,Caucasian,01/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,7,Risk of Violence,-2.69,2,Low,New,1,0 +68246,79244,71678,PRETRIAL,Adoni,Guy,NULL,Male,Caucasian,01/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +68246,79244,71678,PRETRIAL,Adoni,Guy,NULL,Male,Caucasian,01/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +57521,79230,59631,Probation,Royster,Don,NULL,Male,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.14,4,Low,Copy,1,0 +57521,79230,59631,Probation,Royster,Don,NULL,Male,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.43,9,High,Copy,1,0 +57521,79230,59631,Probation,Royster,Don,NULL,Male,African-American,01/05/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +12554,79232,12037,PRETRIAL,BUTTERFIELD,MATTHEW,C,Male,African-American,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,Copy,1,0 +12554,79232,12037,PRETRIAL,BUTTERFIELD,MATTHEW,C,Male,African-American,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,4,High,8,Risk of Recidivism,0.21,8,High,Copy,1,0 +12554,79232,12037,PRETRIAL,BUTTERFIELD,MATTHEW,C,Male,African-American,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +68235,79228,71668,PRETRIAL,BURDICK,JUAN,NULL,Male,Other,08/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +68235,79228,71668,PRETRIAL,BURDICK,JUAN,NULL,Male,Other,08/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +68235,79228,71668,PRETRIAL,BURDICK,JUAN,NULL,Male,Other,08/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68238,79233,71671,PRETRIAL,Joffe,Broderick,David,Male,Caucasian,01/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +68238,79233,71671,PRETRIAL,Joffe,Broderick,David,Male,Caucasian,01/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,8,Risk of Recidivism,-0.7,4,Low,New,1,0 +68238,79233,71671,PRETRIAL,Joffe,Broderick,David,Male,Caucasian,01/24/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68232,79225,71665,PRETRIAL,MCKENZIE,TANESHA,NULL,Female,African-American,09/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/8/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,New,1,0 +68232,79225,71665,PRETRIAL,MCKENZIE,TANESHA,NULL,Female,African-American,09/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/8/14 0:00,1,Low,8,Risk of Recidivism,-2.02,1,Low,New,1,0 +68232,79225,71665,PRETRIAL,MCKENZIE,TANESHA,NULL,Female,African-American,09/05/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68157,79139,71591,PRETRIAL,clarke,julius,NULL,Male,African-American,08/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +68157,79139,71591,PRETRIAL,clarke,julius,NULL,Male,African-American,08/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,4,High,8,Risk of Recidivism,0.52,9,High,New,1,0 +68157,79139,71591,PRETRIAL,clarke,julius,NULL,Male,African-American,08/20/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68233,79226,71666,PRETRIAL,Bell,Andriette,NULL,Female,African-American,04/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,7,Risk of Violence,-4.08,1,Low,New,1,0 +68233,79226,71666,PRETRIAL,Bell,Andriette,NULL,Female,African-American,04/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,8,Risk of Recidivism,-2.53,1,Low,New,1,0 +68233,79226,71666,PRETRIAL,Bell,Andriette,NULL,Female,African-American,04/15/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68244,79242,71676,DRRD,Gray,Jermaine,Leonard,Male,Native American,09/12/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/8/14 0:00,4,High,7,Risk of Violence,-1.16,8,High,New,1,0 +68244,79242,71676,DRRD,Gray,Jermaine,Leonard,Male,Native American,09/12/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/8/14 0:00,4,High,8,Risk of Recidivism,0.77,10,High,New,1,0 +68244,79242,71676,DRRD,Gray,Jermaine,Leonard,Male,Native American,09/12/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/8/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,New,1,0 +68234,79227,71667,PRETRIAL,Malcolm,Ruel,NULL,Male,Other,04/24/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/8/14 0:00,1,Low,7,Risk of Violence,-3.64,1,Low,New,1,0 +68234,79227,71667,PRETRIAL,Malcolm,Ruel,NULL,Male,Other,04/24/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/8/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +68234,79227,71667,PRETRIAL,Malcolm,Ruel,NULL,Male,Other,04/24/52,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/8/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68239,79234,71672,PRETRIAL,Smith,Latoya,Denise,Female,African-American,11/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,2,Medium,7,Risk of Violence,-2.23,4,Low,New,1,0 +68239,79234,71672,PRETRIAL,Smith,Latoya,Denise,Female,African-American,11/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.5,6,Medium,New,1,0 +68239,79234,71672,PRETRIAL,Smith,Latoya,Denise,Female,African-American,11/06/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68236,79229,71669,PRETRIAL,BEL,CLEOMIN,NULL,Male,African-American,02/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/8/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +68236,79229,71669,PRETRIAL,BEL,CLEOMIN,NULL,Male,African-American,02/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/8/14 0:00,1,Low,8,Risk of Recidivism,-1.78,1,Low,New,1,0 +68236,79229,71669,PRETRIAL,BEL,CLEOMIN,NULL,Male,African-American,02/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/8/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +12554,12967,12037,PRETRIAL,BUTTERFIELD,MATTHEW,C,Male,African-American,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,4,High,7,Risk of Violence,-0.59,10,High,New,1,0 +12554,12967,12037,PRETRIAL,BUTTERFIELD,MATTHEW,C,Male,African-American,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,4,High,8,Risk of Recidivism,1.14,10,High,New,1,0 +12554,12967,12037,PRETRIAL,BUTTERFIELD,MATTHEW,C,Male,African-American,12/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68231,79224,71664,PRETRIAL,CHARLES,WILBERT,NULL,Male,African-American,03/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +68231,79224,71664,PRETRIAL,CHARLES,WILBERT,NULL,Male,African-American,03/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +68231,79224,71664,PRETRIAL,CHARLES,WILBERT,NULL,Male,African-American,03/19/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68242,79238,71675,PRETRIAL,Shafer,Parker,J,Male,Oriental,07/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,New,1,0 +68242,79238,71675,PRETRIAL,Shafer,Parker,J,Male,Oriental,07/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +68242,79238,71675,PRETRIAL,Shafer,Parker,J,Male,Oriental,07/11/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +50268,56376,51259,PRETRIAL,jones,morell,NULL,Male,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,4,High,7,Risk of Violence,0.18,10,High,New,1,0 +50268,56376,51259,PRETRIAL,jones,morell,NULL,Male,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,4,High,8,Risk of Recidivism,0.78,10,High,New,1,0 +50268,56376,51259,PRETRIAL,jones,morell,NULL,Male,African-American,11/22/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/8/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +68240,79236,71673,PRETRIAL,Hill,Stephen,NULL,Male,African-American,05/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/8/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +68240,79236,71673,PRETRIAL,Hill,Stephen,NULL,Male,African-American,05/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/8/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +68240,79236,71673,PRETRIAL,Hill,Stephen,NULL,Male,African-American,05/05/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/8/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +68237,79231,71670,PRETRIAL,Cross,Dwayne,NULL,Male,African-American,10/19/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/8/14 0:00,2,Medium,7,Risk of Violence,-1.49,7,Medium,New,1,0 +68237,79231,71670,PRETRIAL,Cross,Dwayne,NULL,Male,African-American,10/19/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.77,3,Low,New,1,0 +68237,79231,71670,PRETRIAL,Cross,Dwayne,NULL,Male,African-American,10/19/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/8/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +33349,35477,32446,PRETRIAL,Williams,Alexander,NULL,Male,African-American,11/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/8/14 0:00,2,Medium,7,Risk of Violence,-3.36,1,Low,New,1,0 +33349,35477,32446,PRETRIAL,Williams,Alexander,NULL,Male,African-American,11/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/8/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +33349,35477,32446,PRETRIAL,Williams,Alexander,NULL,Male,African-American,11/07/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/8/14 0:00,2,Medium,18,Risk of Failure to Appear,20,3,Low,New,1,0 +25289,79261,44472,PRETRIAL,STUBBS,ANTWANE,NULL,Male,African-American,01/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/14 0:00,2,Medium,7,Risk of Violence,-2.28,3,Low,Copy,1,0 +25289,79261,44472,PRETRIAL,STUBBS,ANTWANE,NULL,Male,African-American,01/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,Copy,1,0 +25289,79261,44472,PRETRIAL,STUBBS,ANTWANE,NULL,Male,African-American,01/10/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +68255,79257,71689,PRETRIAL,Stephens,Joshua,Daniel,Male,Caucasian,08/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.5,3,Low,New,1,0 +68255,79257,71689,PRETRIAL,Stephens,Joshua,Daniel,Male,Caucasian,08/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.36,9,High,New,1,0 +68255,79257,71689,PRETRIAL,Stephens,Joshua,Daniel,Male,Caucasian,08/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +42331,79273,71700,PRETRIAL,Merritt,Michelle,NULL,Female,Caucasian,01/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/9/14 0:00,2,Medium,7,Risk of Violence,-1.57,6,Medium,New,1,0 +42331,79273,71700,PRETRIAL,Merritt,Michelle,NULL,Female,Caucasian,01/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,7,Medium,New,1,0 +42331,79273,71700,PRETRIAL,Merritt,Michelle,NULL,Female,Caucasian,01/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/9/14 0:00,2,Medium,18,Risk of Failure to Appear,38,10,High,New,1,0 +68250,79252,71684,PRETRIAL,Raman,Steve,Hassan,Male,Caucasian,02/20/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +68250,79252,71684,PRETRIAL,Raman,Steve,Hassan,Male,Caucasian,02/20/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +68250,79252,71684,PRETRIAL,Raman,Steve,Hassan,Male,Caucasian,02/20/46,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68257,79259,71691,PRETRIAL,Carson,William,NULL,Male,Caucasian,08/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,7,Risk of Violence,-2.88,2,Low,New,1,0 +68257,79259,71691,PRETRIAL,Carson,William,NULL,Male,Caucasian,08/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +68257,79259,71691,PRETRIAL,Carson,William,NULL,Male,Caucasian,08/13/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68262,79266,71696,PRETRIAL,black,michael,NULL,Male,Caucasian,06/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +68262,79266,71696,PRETRIAL,black,michael,NULL,Male,Caucasian,06/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,8,Risk of Recidivism,-1.44,1,Low,New,1,0 +68262,79266,71696,PRETRIAL,black,michael,NULL,Male,Caucasian,06/23/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68256,79258,71690,PRETRIAL,Guignard,Stephanie,NULL,Female,Caucasian,04/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +68256,79258,71690,PRETRIAL,Guignard,Stephanie,NULL,Female,Caucasian,04/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,8,Risk of Recidivism,-1.19,3,Low,New,1,0 +68256,79258,71690,PRETRIAL,Guignard,Stephanie,NULL,Female,Caucasian,04/28/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68248,79250,71682,PRETRIAL,Missick,Justin,Jason,Male,African-American,08/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,2,Medium,7,Risk of Violence,-1.34,7,Medium,New,1,0 +68248,79250,71682,PRETRIAL,Missick,Justin,Jason,Male,African-American,08/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,2,Medium,8,Risk of Recidivism,0.06,7,Medium,New,1,0 +68248,79250,71682,PRETRIAL,Missick,Justin,Jason,Male,African-American,08/28/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68260,79263,71693,PRETRIAL,Bentivegna,Michael,NULL,Male,Caucasian,03/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +68260,79263,71693,PRETRIAL,Bentivegna,Michael,NULL,Male,Caucasian,03/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/14 0:00,1,Low,8,Risk of Recidivism,-0.9,3,Low,New,1,0 +68260,79263,71693,PRETRIAL,Bentivegna,Michael,NULL,Male,Caucasian,03/04/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68253,79255,71687,PRETRIAL,GUIGNARD,STACEY,NULL,Male,African-American,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,7,Risk of Violence,-1.96,5,Medium,New,1,0 +68253,79255,71687,PRETRIAL,GUIGNARD,STACEY,NULL,Male,African-American,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +68253,79255,71687,PRETRIAL,GUIGNARD,STACEY,NULL,Male,African-American,05/03/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +53081,79247,63346,PRETRIAL,Soto,Ruben,NULL,Male,Caucasian,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,4,High,7,Risk of Violence,-0.93,9,High,Copy,1,0 +53081,79247,63346,PRETRIAL,Soto,Ruben,NULL,Male,Caucasian,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,4,High,8,Risk of Recidivism,0.21,8,High,Copy,1,0 +53081,79247,63346,PRETRIAL,Soto,Ruben,NULL,Male,Caucasian,09/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,4,High,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +24543,79272,23725,PRETRIAL,HOLLIS,APRIL,D,Female,African-American,09/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.97,5,Medium,Copy,1,0 +24543,79272,23725,PRETRIAL,HOLLIS,APRIL,D,Female,African-American,09/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.56,10,High,Copy,1,0 +24543,79272,23725,PRETRIAL,HOLLIS,APRIL,D,Female,African-American,09/05/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,Copy,1,0 +68265,79275,71701,PRETRIAL,Rosado,Jennie,NULL,Male,Hispanic,10/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/9/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +68265,79275,71701,PRETRIAL,Rosado,Jennie,NULL,Male,Hispanic,10/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/9/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +68265,79275,71701,PRETRIAL,Rosado,Jennie,NULL,Male,Hispanic,10/31/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +68252,79254,71686,PRETRIAL,Louis,Camary,NULL,Male,African-American,10/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,7,Risk of Violence,-2.22,4,Low,New,1,0 +68252,79254,71686,PRETRIAL,Louis,Camary,NULL,Male,African-American,10/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +68252,79254,71686,PRETRIAL,Louis,Camary,NULL,Male,African-American,10/20/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68263,79267,71697,PRETRIAL,Smith,Frank,NULL,Male,Caucasian,07/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +68263,79267,71697,PRETRIAL,Smith,Frank,NULL,Male,Caucasian,07/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +68263,79267,71697,PRETRIAL,Smith,Frank,NULL,Male,Caucasian,07/11/87,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +17605,79246,71679,PRETRIAL,Green,Antoine,NULL,Male,African-American,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,New,1,0 +17605,79246,71679,PRETRIAL,Green,Antoine,NULL,Male,African-American,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +17605,79246,71679,PRETRIAL,Green,Antoine,NULL,Male,African-American,12/28/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68258,79262,71692,PRETRIAL,Welsh-Wesolowski,Mary,NULL,Female,Caucasian,11/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/9/14 0:00,1,Low,7,Risk of Violence,-2.07,4,Low,New,1,0 +68258,79262,71692,PRETRIAL,Welsh-Wesolowski,Mary,NULL,Female,Caucasian,11/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/9/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +68258,79262,71692,PRETRIAL,Welsh-Wesolowski,Mary,NULL,Female,Caucasian,11/06/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +24906,79249,71681,PRETRIAL,Doe,Paris,Verell,Female,African-American,04/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +24906,79249,71681,PRETRIAL,Doe,Paris,Verell,Female,African-American,04/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.02,8,High,New,1,0 +24906,79249,71681,PRETRIAL,Doe,Paris,Verell,Female,African-American,04/09/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,4,Low,New,1,0 +68259,79264,71694,PRETRIAL,Milgram,David,E,Male,Caucasian,12/21/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/14 0:00,1,Low,7,Risk of Violence,-4.36,1,Low,New,1,0 +68259,79264,71694,PRETRIAL,Milgram,David,E,Male,Caucasian,12/21/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/14 0:00,1,Low,8,Risk of Recidivism,-2.73,1,Low,New,1,0 +68259,79264,71694,PRETRIAL,Milgram,David,E,Male,Caucasian,12/21/47,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +6635,6620,6228,PRETRIAL,AHMADOIYA,NOOR,TALIB,Male,African-American,02/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,2,Medium,7,Risk of Violence,-2.74,2,Low,New,1,0 +6635,6620,6228,PRETRIAL,AHMADOIYA,NOOR,TALIB,Male,African-American,02/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.18,6,Medium,New,1,0 +6635,6620,6228,PRETRIAL,AHMADOIYA,NOOR,TALIB,Male,African-American,02/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68249,79251,71683,PRETRIAL,Lewis,Kevin,Obrien,Male,African-American,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.46,7,Medium,New,1,0 +68249,79251,71683,PRETRIAL,Lewis,Kevin,Obrien,Male,African-American,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +68249,79251,71683,PRETRIAL,Lewis,Kevin,Obrien,Male,African-American,09/15/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68251,79253,71685,PRETRIAL,Ospina,Jonathan,NULL,Male,Hispanic,08/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +68251,79253,71685,PRETRIAL,Ospina,Jonathan,NULL,Male,Hispanic,08/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +68251,79253,71685,PRETRIAL,Ospina,Jonathan,NULL,Male,Hispanic,08/19/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +6635,79274,6228,PRETRIAL,AHMADOIYA,NOOR,TALIB,Male,African-American,02/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,2,Medium,7,Risk of Violence,-3.06,1,Low,Copy,1,0 +6635,79274,6228,PRETRIAL,AHMADOIYA,NOOR,TALIB,Male,African-American,02/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,Copy,1,0 +6635,79274,6228,PRETRIAL,AHMADOIYA,NOOR,TALIB,Male,African-American,02/24/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/9/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +68247,79248,71680,PRETRIAL,JENNINGS,KENNETH,ALEXANDER,Male,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/9/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +68247,79248,71680,PRETRIAL,JENNINGS,KENNETH,ALEXANDER,Male,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/9/14 0:00,1,Low,8,Risk of Recidivism,-0.86,3,Low,New,1,0 +68247,79248,71680,PRETRIAL,JENNINGS,KENNETH,ALEXANDER,Male,African-American,09/08/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/9/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68275,79286,71711,PRETRIAL,mercado,carlos,NULL,Male,Hispanic,07/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +68275,79286,71711,PRETRIAL,mercado,carlos,NULL,Male,Hispanic,07/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +68275,79286,71711,PRETRIAL,mercado,carlos,NULL,Male,Hispanic,07/28/76,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68279,79290,71715,PRETRIAL,Amaya,Randolph,NULL,Male,Caucasian,01/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +68279,79290,71715,PRETRIAL,Amaya,Randolph,NULL,Male,Caucasian,01/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +68279,79290,71715,PRETRIAL,Amaya,Randolph,NULL,Male,Caucasian,01/30/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68277,79288,71713,PRETRIAL,COHN,JAIME,NULL,Female,Caucasian,07/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,7,Risk of Violence,-3.5,1,Low,New,1,0 +68277,79288,71713,PRETRIAL,COHN,JAIME,NULL,Female,Caucasian,07/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,8,Risk of Recidivism,-1.91,1,Low,New,1,0 +68277,79288,71713,PRETRIAL,COHN,JAIME,NULL,Female,Caucasian,07/27/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68270,79281,71706,PRETRIAL,Sommer,Fawnne,NULL,Female,Hispanic,11/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,7,Risk of Violence,-2.74,2,Low,New,1,0 +68270,79281,71706,PRETRIAL,Sommer,Fawnne,NULL,Female,Hispanic,11/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +68270,79281,71706,PRETRIAL,Sommer,Fawnne,NULL,Female,Hispanic,11/07/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68267,79277,71703,PRETRIAL,Perez,Valerio,Bernardino,Male,Caucasian,04/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,2,Medium,7,Risk of Violence,-2.7,2,Low,New,1,0 +68267,79277,71703,PRETRIAL,Perez,Valerio,Bernardino,Male,Caucasian,04/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.06,7,Medium,New,1,0 +68267,79277,71703,PRETRIAL,Perez,Valerio,Bernardino,Male,Caucasian,04/13/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +68280,79291,71716,PRETRIAL,oliver,thomas,NULL,Male,Caucasian,02/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/10/14 0:00,1,Low,7,Risk of Violence,-3.77,1,Low,New,1,0 +68280,79291,71716,PRETRIAL,oliver,thomas,NULL,Male,Caucasian,02/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/10/14 0:00,1,Low,8,Risk of Recidivism,-2.41,1,Low,New,1,0 +68280,79291,71716,PRETRIAL,oliver,thomas,NULL,Male,Caucasian,02/19/68,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68272,79283,71708,PRETRIAL,Brown,Marjorie,Yvonne,Female,Other,06/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,7,Risk of Violence,-3.76,1,Low,New,1,0 +68272,79283,71708,PRETRIAL,Brown,Marjorie,Yvonne,Female,Other,06/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,8,Risk of Recidivism,-2.15,1,Low,New,1,0 +68272,79283,71708,PRETRIAL,Brown,Marjorie,Yvonne,Female,Other,06/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68286,79298,71723,PRETRIAL,BROWDY,RYAN,NULL,Male,Caucasian,12/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +68286,79298,71723,PRETRIAL,BROWDY,RYAN,NULL,Male,Caucasian,12/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,8,Risk of Recidivism,-1.3,2,Low,New,1,0 +68286,79298,71723,PRETRIAL,BROWDY,RYAN,NULL,Male,Caucasian,12/31/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68274,79285,71710,PRETRIAL,Higgins,Melisa,Stephanie,Female,Other,11/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +68274,79285,71710,PRETRIAL,Higgins,Melisa,Stephanie,Female,Other,11/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,8,Risk of Recidivism,-1.39,2,Low,New,1,0 +68274,79285,71710,PRETRIAL,Higgins,Melisa,Stephanie,Female,Other,11/03/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +41434,79280,41136,PRETRIAL,GIBBONS,MARCUS,NULL,Male,African-American,08/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,4,High,7,Risk of Violence,-1.11,8,High,Copy,1,0 +41434,79280,41136,PRETRIAL,GIBBONS,MARCUS,NULL,Male,African-American,08/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,4,High,8,Risk of Recidivism,0.87,10,High,Copy,1,0 +41434,79280,41136,PRETRIAL,GIBBONS,MARCUS,NULL,Male,African-American,08/17/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +68282,79293,71718,PRETRIAL,Robertson,Jason,NULL,Male,African-American,11/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/10/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +68282,79293,71718,PRETRIAL,Robertson,Jason,NULL,Male,African-American,11/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/10/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +68282,79293,71718,PRETRIAL,Robertson,Jason,NULL,Male,African-American,11/13/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68281,79292,71717,PRETRIAL,BONILLA,VERONICA,NULL,Female,Hispanic,06/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +68281,79292,71717,PRETRIAL,BONILLA,VERONICA,NULL,Female,Hispanic,06/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,2,Medium,8,Risk of Recidivism,-0.64,5,Medium,New,1,0 +68281,79292,71717,PRETRIAL,BONILLA,VERONICA,NULL,Female,Hispanic,06/04/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68273,79284,71709,PRETRIAL,Reynolds,Donald,K,Male,Caucasian,08/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,7,Risk of Violence,-3.05,1,Low,New,1,0 +68273,79284,71709,PRETRIAL,Reynolds,Donald,K,Male,Caucasian,08/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,8,Risk of Recidivism,-0.38,5,Medium,New,1,0 +68273,79284,71709,PRETRIAL,Reynolds,Donald,K,Male,Caucasian,08/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,32,9,High,New,1,0 +68266,79276,71702,PRETRIAL,Barrett,Orville,NULL,Male,African-American,06/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +68266,79276,71702,PRETRIAL,Barrett,Orville,NULL,Male,African-American,06/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,8,Risk of Recidivism,-2.12,1,Low,New,1,0 +68266,79276,71702,PRETRIAL,Barrett,Orville,NULL,Male,African-American,06/21/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68278,79289,71714,PRETRIAL,Vanderburg,Shane,m,Male,Caucasian,03/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,7,Risk of Violence,-2.27,3,Low,New,1,0 +68278,79289,71714,PRETRIAL,Vanderburg,Shane,m,Male,Caucasian,03/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +68278,79289,71714,PRETRIAL,Vanderburg,Shane,m,Male,Caucasian,03/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +68269,79279,71705,PRETRIAL,ALVAREZ,VALENTIN,MICHEL,Male,Caucasian,01/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/10/14 0:00,1,Low,7,Risk of Violence,-3.45,1,Low,New,1,0 +68269,79279,71705,PRETRIAL,ALVAREZ,VALENTIN,MICHEL,Male,Caucasian,01/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/10/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +68269,79279,71705,PRETRIAL,ALVAREZ,VALENTIN,MICHEL,Male,Caucasian,01/24/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68276,79287,71712,PRETRIAL,Papa,Breon,NULL,Male,African-American,11/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +68276,79287,71712,PRETRIAL,Papa,Breon,NULL,Male,African-American,11/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +68276,79287,71712,PRETRIAL,Papa,Breon,NULL,Male,African-American,11/02/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +68283,79294,71719,PRETRIAL,Korn,Christopher,Douglas,Male,Caucasian,12/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/10/14 0:00,1,Low,7,Risk of Violence,-3.75,1,Low,New,1,0 +68283,79294,71719,PRETRIAL,Korn,Christopher,Douglas,Male,Caucasian,12/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/10/14 0:00,1,Low,8,Risk of Recidivism,-2.21,1,Low,New,1,0 +68283,79294,71719,PRETRIAL,Korn,Christopher,Douglas,Male,Caucasian,12/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68284,79296,71721,PRETRIAL,Johnson,Julian,NULL,Male,African-American,12/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +68284,79296,71721,PRETRIAL,Johnson,Julian,NULL,Male,African-American,12/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.26,8,High,New,1,0 +68284,79296,71721,PRETRIAL,Johnson,Julian,NULL,Male,African-American,12/23/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68271,79282,71707,PRETRIAL,Jackson,Keara,Marie,Female,African-American,09/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.23,8,High,New,1,0 +68271,79282,71707,PRETRIAL,Jackson,Keara,Marie,Female,African-American,09/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.27,7,Medium,New,1,0 +68271,79282,71707,PRETRIAL,Jackson,Keara,Marie,Female,African-American,09/28/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68268,79278,71704,PRETRIAL,RUFFIN,GELISSA,SHAQUANDA,Female,African-American,02/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,7,Risk of Violence,-3.29,1,Low,New,1,0 +68268,79278,71704,PRETRIAL,RUFFIN,GELISSA,SHAQUANDA,Female,African-American,02/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +68268,79278,71704,PRETRIAL,RUFFIN,GELISSA,SHAQUANDA,Female,African-American,02/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/10/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +51543,79303,52732,Probation,bohler,alexus,NULL,Female,African-American,07/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.67,6,Medium,Copy,1,0 +51543,79303,52732,Probation,bohler,alexus,NULL,Female,African-American,07/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.61,10,High,Copy,1,0 +51543,79303,52732,Probation,bohler,alexus,NULL,Female,African-American,07/09/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +68296,79312,71734,PRETRIAL,NEWTON,MICHAEL,NULL,Male,Caucasian,09/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +68296,79312,71734,PRETRIAL,NEWTON,MICHAEL,NULL,Male,Caucasian,09/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,1,Low,8,Risk of Recidivism,-1.83,1,Low,New,1,0 +68296,79312,71734,PRETRIAL,NEWTON,MICHAEL,NULL,Male,Caucasian,09/19/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68287,79299,71724,PRETRIAL,Turk,Sherif,NULL,Male,Hispanic,07/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,2,Medium,7,Risk of Violence,-1.66,6,Medium,New,1,0 +68287,79299,71724,PRETRIAL,Turk,Sherif,NULL,Male,Hispanic,07/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +68287,79299,71724,PRETRIAL,Turk,Sherif,NULL,Male,Hispanic,07/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68292,79308,71730,PRETRIAL,Young,Bernard,NULL,Male,African-American,07/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/14 0:00,2,Medium,7,Risk of Violence,-1.29,7,Medium,New,1,0 +68292,79308,71730,PRETRIAL,Young,Bernard,NULL,Male,African-American,07/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +68292,79308,71730,PRETRIAL,Young,Bernard,NULL,Male,African-American,07/06/96,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68298,79315,71735,PRETRIAL,Pantaleon,Jesus,NULL,Male,Caucasian,01/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +68298,79315,71735,PRETRIAL,Pantaleon,Jesus,NULL,Male,Caucasian,01/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.39,5,Medium,New,1,0 +68298,79315,71735,PRETRIAL,Pantaleon,Jesus,NULL,Male,Caucasian,01/12/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68289,79305,71727,PRETRIAL,BLACKOWICZ,CHERISSE,ELLEN,Female,Caucasian,04/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/14 0:00,1,Low,7,Risk of Violence,-3.6,1,Low,New,1,0 +68289,79305,71727,PRETRIAL,BLACKOWICZ,CHERISSE,ELLEN,Female,Caucasian,04/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +68289,79305,71727,PRETRIAL,BLACKOWICZ,CHERISSE,ELLEN,Female,Caucasian,04/04/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +12201,79300,71725,DRRD,Daniels,Brion,NULL,Male,African-American,02/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,4,High,7,Risk of Violence,-0.72,9,High,New,1,0 +12201,79300,71725,DRRD,Daniels,Brion,NULL,Male,African-American,02/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,4,High,8,Risk of Recidivism,0.44,9,High,New,1,0 +12201,79300,71725,DRRD,Daniels,Brion,NULL,Male,African-American,02/13/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,4,High,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +60954,79314,63454,PRETRIAL,Tilghman,Kenneth,NULL,Male,African-American,09/02/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/11/14 0:00,4,High,7,Risk of Violence,-1.18,8,High,Copy,1,0 +60954,79314,63454,PRETRIAL,Tilghman,Kenneth,NULL,Male,African-American,09/02/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/11/14 0:00,4,High,8,Risk of Recidivism,0.34,9,High,Copy,1,0 +60954,79314,63454,PRETRIAL,Tilghman,Kenneth,NULL,Male,African-American,09/02/94,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/11/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +68288,79301,71726,PRETRIAL,Guerra,Roger,NULL,Male,Hispanic,09/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,4,High,7,Risk of Violence,-0.78,9,High,New,1,0 +68288,79301,71726,PRETRIAL,Guerra,Roger,NULL,Male,Hispanic,09/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +68288,79301,71726,PRETRIAL,Guerra,Roger,NULL,Male,Hispanic,09/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68290,79306,71728,PRETRIAL,malletgonzales,jeffrey,NULL,Male,Hispanic,11/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,4,High,7,Risk of Violence,-0.81,9,High,New,1,0 +68290,79306,71728,PRETRIAL,malletgonzales,jeffrey,NULL,Male,Hispanic,11/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +68290,79306,71728,PRETRIAL,malletgonzales,jeffrey,NULL,Male,Hispanic,11/12/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +68291,79307,71729,PRETRIAL,gonzalez,andrew,NULL,Male,Caucasian,08/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.12,8,High,New,1,0 +68291,79307,71729,PRETRIAL,gonzalez,andrew,NULL,Male,Caucasian,08/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +68291,79307,71729,PRETRIAL,gonzalez,andrew,NULL,Male,Caucasian,08/12/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68295,79311,71733,PRETRIAL,Ellison,Charneshia,Dena,Female,African-American,05/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/11/14 0:00,2,Medium,7,Risk of Violence,-2.31,3,Low,New,1,0 +68295,79311,71733,PRETRIAL,Ellison,Charneshia,Dena,Female,African-American,05/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/11/14 0:00,2,Medium,8,Risk of Recidivism,-0.53,6,Medium,New,1,0 +68295,79311,71733,PRETRIAL,Ellison,Charneshia,Dena,Female,African-American,05/06/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/11/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +46270,51224,46660,PRETRIAL,Ryan,Timothy,NULL,Male,Caucasian,04/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.93,9,High,New,1,0 +46270,51224,46660,PRETRIAL,Ryan,Timothy,NULL,Male,Caucasian,04/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +46270,51224,46660,PRETRIAL,Ryan,Timothy,NULL,Male,Caucasian,04/02/63,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/11/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,38,10,High,New,1,0 +68299,79316,71736,PRETRIAL,Boone,Victoria,NULL,Female,Caucasian,10/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/14 0:00,1,Low,7,Risk of Violence,-3.36,1,Low,New,1,0 +68299,79316,71736,PRETRIAL,Boone,Victoria,NULL,Female,Caucasian,10/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/14 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +68299,79316,71736,PRETRIAL,Boone,Victoria,NULL,Female,Caucasian,10/22/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/11/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +26032,78495,25131,PRETRIAL,MCKAY,MARLON,ADRIAN,Male,African-American,11/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,4,High,7,Risk of Violence,-1.09,8,High,Copy,1,0 +26032,78495,25131,PRETRIAL,MCKAY,MARLON,ADRIAN,Male,African-American,11/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,4,High,8,Risk of Recidivism,0.2,8,High,Copy,1,0 +26032,78495,25131,PRETRIAL,MCKAY,MARLON,ADRIAN,Male,African-American,11/30/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/11/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +68319,79337,71755,PRETRIAL,Johnson,Charles,NULL,Male,African-American,04/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +68319,79337,71755,PRETRIAL,Johnson,Charles,NULL,Male,African-American,04/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +68319,79337,71755,PRETRIAL,Johnson,Charles,NULL,Male,African-American,04/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,20,3,Low,New,1,0 +67327,79325,71744,PRETRIAL,Ouzts,Eugene,NULL,Male,Caucasian,08/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,4,High,7,Risk of Violence,-1.05,8,High,New,1,0 +67327,79325,71744,PRETRIAL,Ouzts,Eugene,NULL,Male,Caucasian,08/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,4,High,8,Risk of Recidivism,0.51,9,High,New,1,0 +67327,79325,71744,PRETRIAL,Ouzts,Eugene,NULL,Male,Caucasian,08/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,4,High,18,Risk of Failure to Appear,28,8,High,New,1,0 +67189,79332,70540,Probation,Ogiste,Victory,NULL,Male,African-American,12/10/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/14 0:00,4,High,7,Risk of Violence,0.28,10,High,Copy,1,0 +67189,79332,70540,Probation,Ogiste,Victory,NULL,Male,African-American,12/10/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/14 0:00,4,High,8,Risk of Recidivism,0.88,10,High,Copy,1,0 +67189,79332,70540,Probation,Ogiste,Victory,NULL,Male,African-American,12/10/95,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/12/14 0:00,4,High,18,Risk of Failure to Appear,23,4,Low,Copy,1,0 +68305,79323,71742,PRETRIAL,FREEL,THOMAS,NULL,Male,Caucasian,06/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,7,Risk of Violence,-3.32,1,Low,New,1,0 +68305,79323,71742,PRETRIAL,FREEL,THOMAS,NULL,Male,Caucasian,06/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,New,1,0 +68305,79323,71742,PRETRIAL,FREEL,THOMAS,NULL,Male,Caucasian,06/02/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +67752,78655,71176,PRETRIAL,Lopez,Cesar,D,Male,Hispanic,03/21/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,4,High,7,Risk of Violence,-0.52,10,High,New,1,0 +67752,78655,71176,PRETRIAL,Lopez,Cesar,D,Male,Hispanic,03/21/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,4,High,8,Risk of Recidivism,1.08,10,High,New,1,0 +67752,78655,71176,PRETRIAL,Lopez,Cesar,D,Male,Hispanic,03/21/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68308,79327,71746,PRETRIAL,Vizuet,Gonzalo,NULL,Male,Caucasian,01/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +68308,79327,71746,PRETRIAL,Vizuet,Gonzalo,NULL,Male,Caucasian,01/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,1,Low,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +68308,79327,71746,PRETRIAL,Vizuet,Gonzalo,NULL,Male,Caucasian,01/03/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68302,79319,71739,PRETRIAL,Johnson,Nikesha,NULL,Female,African-American,02/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +68302,79319,71739,PRETRIAL,Johnson,Nikesha,NULL,Female,African-American,02/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,8,Risk of Recidivism,-0.93,4,Low,New,1,0 +68302,79319,71739,PRETRIAL,Johnson,Nikesha,NULL,Female,African-American,02/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +9698,9872,9225,PRETRIAL,KAYE,LOUIS,SETH,Male,Caucasian,02/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.94,5,Medium,New,1,0 +9698,9872,9225,PRETRIAL,KAYE,LOUIS,SETH,Male,Caucasian,02/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.21,8,High,New,1,0 +9698,9872,9225,PRETRIAL,KAYE,LOUIS,SETH,Male,Caucasian,02/10/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +68200,79183,71629,PRETRIAL,Henderson,Latwan,NULL,Male,African-American,03/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,2,Medium,7,Risk of Violence,-2.3,3,Low,New,1,0 +68200,79183,71629,PRETRIAL,Henderson,Latwan,NULL,Male,African-American,03/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,2,Medium,8,Risk of Recidivism,0.05,7,Medium,New,1,0 +68200,79183,71629,PRETRIAL,Henderson,Latwan,NULL,Male,African-American,03/02/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68317,79335,71753,PRETRIAL,JACKSON,kIRBY,LYNN,Male,African-American,07/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.19,4,Low,New,1,0 +68317,79335,71753,PRETRIAL,JACKSON,kIRBY,LYNN,Male,African-American,07/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +68317,79335,71753,PRETRIAL,JACKSON,kIRBY,LYNN,Male,African-American,07/28/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +68304,79322,71741,PRETRIAL,Carter,Breanna,Khahila,Female,African-American,03/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +68304,79322,71741,PRETRIAL,Carter,Breanna,Khahila,Female,African-American,03/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,8,Risk of Recidivism,-0.89,4,Low,New,1,0 +68304,79322,71741,PRETRIAL,Carter,Breanna,Khahila,Female,African-American,03/21/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68316,79334,71752,PRETRIAL,Murphy,Daniel,NULL,Male,Caucasian,04/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +68316,79334,71752,PRETRIAL,Murphy,Daniel,NULL,Male,Caucasian,04/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,8,Risk of Recidivism,-0.51,5,Medium,New,1,0 +68316,79334,71752,PRETRIAL,Murphy,Daniel,NULL,Male,Caucasian,04/11/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68303,79321,71740,PRETRIAL,Brantley,Tyrail,Kevice,Male,African-American,10/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +68303,79321,71740,PRETRIAL,Brantley,Tyrail,Kevice,Male,African-American,10/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +68303,79321,71740,PRETRIAL,Brantley,Tyrail,Kevice,Male,African-American,10/06/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +47203,52420,47725,PRETRIAL,Brown,Stephon,NULL,Male,African-American,01/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +47203,52420,47725,PRETRIAL,Brown,Stephon,NULL,Male,African-American,01/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +47203,52420,47725,PRETRIAL,Brown,Stephon,NULL,Male,African-American,01/13/86,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45331,79320,45563,PRETRIAL,CONFRERAS,MAYKER,NULL,Male,Caucasian,06/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/12/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,Copy,1,0 +45331,79320,45563,PRETRIAL,CONFRERAS,MAYKER,NULL,Male,Caucasian,06/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/12/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,Copy,1,0 +45331,79320,45563,PRETRIAL,CONFRERAS,MAYKER,NULL,Male,Caucasian,06/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +68301,79318,71738,PRETRIAL,Anaya,Brian,NULL,Male,Caucasian,03/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,7,Risk of Violence,-1.9,5,Medium,New,1,0 +68301,79318,71738,PRETRIAL,Anaya,Brian,NULL,Male,Caucasian,03/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +68301,79318,71738,PRETRIAL,Anaya,Brian,NULL,Male,Caucasian,03/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68318,79336,71754,PRETRIAL,Heller,Jeffrey,Stewart,Male,Caucasian,06/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/12/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +68318,79336,71754,PRETRIAL,Heller,Jeffrey,Stewart,Male,Caucasian,06/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/12/14 0:00,1,Low,8,Risk of Recidivism,-1.05,2,Low,New,1,0 +68318,79336,71754,PRETRIAL,Heller,Jeffrey,Stewart,Male,Caucasian,06/21/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68300,79317,71737,PRETRIAL,Henry,George,NULL,Male,African-American,12/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/12/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +68300,79317,71737,PRETRIAL,Henry,George,NULL,Male,African-American,12/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/12/14 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +68300,79317,71737,PRETRIAL,Henry,George,NULL,Male,African-American,12/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68320,79338,71756,PRETRIAL,MCGILL,TOCCARA,NULL,Female,African-American,11/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,1,Low,7,Risk of Violence,-3.21,1,Low,New,1,0 +68320,79338,71756,PRETRIAL,MCGILL,TOCCARA,NULL,Female,African-American,11/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +68320,79338,71756,PRETRIAL,MCGILL,TOCCARA,NULL,Female,African-American,11/05/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68306,79324,71743,PRETRIAL,CEGLAREK,VINT,WARREN,Male,Caucasian,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,4,High,7,Risk of Violence,-1.01,8,High,New,1,0 +68306,79324,71743,PRETRIAL,CEGLAREK,VINT,WARREN,Male,Caucasian,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,4,High,8,Risk of Recidivism,0.28,8,High,New,1,0 +68306,79324,71743,PRETRIAL,CEGLAREK,VINT,WARREN,Male,Caucasian,07/05/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,4,High,18,Risk of Failure to Appear,19,3,Low,New,1,0 +3890,3851,3607,PRETRIAL,WILLIAMS,GREGORY,NULL,Male,African-American,03/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/12/14 0:00,2,Medium,7,Risk of Violence,-1.59,6,Medium,New,1,0 +3890,3851,3607,PRETRIAL,WILLIAMS,GREGORY,NULL,Male,African-American,03/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/12/14 0:00,2,Medium,8,Risk of Recidivism,-0.78,3,Low,New,1,0 +3890,3851,3607,PRETRIAL,WILLIAMS,GREGORY,NULL,Male,African-American,03/30/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/12/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,New,1,0 +44972,62476,45143,PRETRIAL,Valencia,Andres,NULL,Male,Caucasian,01/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,2,Medium,7,Risk of Violence,-1.58,6,Medium,Copy,1,0 +44972,62476,45143,PRETRIAL,Valencia,Andres,NULL,Male,Caucasian,01/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,Copy,1,0 +44972,62476,45143,PRETRIAL,Valencia,Andres,NULL,Male,Caucasian,01/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/12/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +68310,79329,71748,PRETRIAL,GARDNER,SHAKEIA,RENEE,Female,African-American,11/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,7,Risk of Violence,-1.79,5,Medium,New,1,0 +68310,79329,71748,PRETRIAL,GARDNER,SHAKEIA,RENEE,Female,African-American,11/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,8,Risk of Recidivism,-0.85,4,Low,New,1,0 +68310,79329,71748,PRETRIAL,GARDNER,SHAKEIA,RENEE,Female,African-American,11/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,20,4,Low,New,1,0 +68315,79333,71751,DRRD,Gavilan,Jesenia,NULL,Female,Hispanic,10/02/88,17,All Scales,Intake,English,Probation Violator,Probation,Single,12/12/14 0:00,1,Low,7,Risk of Violence,-2.12,4,Low,New,1,0 +68315,79333,71751,DRRD,Gavilan,Jesenia,NULL,Female,Hispanic,10/02/88,17,All Scales,Intake,English,Probation Violator,Probation,Single,12/12/14 0:00,1,Low,8,Risk of Recidivism,-0.86,4,Low,New,1,0 +68315,79333,71751,DRRD,Gavilan,Jesenia,NULL,Female,Hispanic,10/02/88,17,All Scales,Intake,English,Probation Violator,Probation,Single,12/12/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +68331,79350,71768,PRETRIAL,RHOAT,JESSICA,NULL,Female,African-American,06/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +68331,79350,71768,PRETRIAL,RHOAT,JESSICA,NULL,Female,African-American,06/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.27,9,High,New,1,0 +68331,79350,71768,PRETRIAL,RHOAT,JESSICA,NULL,Female,African-American,06/28/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +68327,79345,71763,PRETRIAL,QUARLES,WILLIAM,CONARD,Male,African-American,08/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/13/14 0:00,1,Low,7,Risk of Violence,-2.29,3,Low,New,1,0 +68327,79345,71763,PRETRIAL,QUARLES,WILLIAM,CONARD,Male,African-American,08/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/13/14 0:00,1,Low,8,Risk of Recidivism,-0.37,5,Medium,New,1,0 +68327,79345,71763,PRETRIAL,QUARLES,WILLIAM,CONARD,Male,African-American,08/14/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/13/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68321,79339,71757,PRETRIAL,Wallacw,Caitlin,NULL,Male,Caucasian,03/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +68321,79339,71757,PRETRIAL,Wallacw,Caitlin,NULL,Male,Caucasian,03/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,1,Low,8,Risk of Recidivism,-1.13,2,Low,New,1,0 +68321,79339,71757,PRETRIAL,Wallacw,Caitlin,NULL,Male,Caucasian,03/11/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68326,79344,71762,PRETRIAL,SALAZAR,MARCOS,ANTONIO,Male,African-American,12/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/13/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +68326,79344,71762,PRETRIAL,SALAZAR,MARCOS,ANTONIO,Male,African-American,12/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/13/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +68326,79344,71762,PRETRIAL,SALAZAR,MARCOS,ANTONIO,Male,African-American,12/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/13/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68323,79341,71759,PRETRIAL,Cheri,Wilson,NULL,Male,Other,02/03/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +68323,79341,71759,PRETRIAL,Cheri,Wilson,NULL,Male,Other,02/03/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +68323,79341,71759,PRETRIAL,Cheri,Wilson,NULL,Male,Other,02/03/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68324,79342,71760,PRETRIAL,DEJESUS,RAFAEL,MAROCCI,Male,Hispanic,01/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/13/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +68324,79342,71760,PRETRIAL,DEJESUS,RAFAEL,MAROCCI,Male,Hispanic,01/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/13/14 0:00,1,Low,8,Risk of Recidivism,-1.39,1,Low,New,1,0 +68324,79342,71760,PRETRIAL,DEJESUS,RAFAEL,MAROCCI,Male,Hispanic,01/17/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/13/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68329,79347,71765,PRETRIAL,Gayle,Dennis,Peter,Male,Other,06/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/13/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +68329,79347,71765,PRETRIAL,Gayle,Dennis,Peter,Male,Other,06/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/13/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +68329,79347,71765,PRETRIAL,Gayle,Dennis,Peter,Male,Other,06/09/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +12252,79349,71767,PRETRIAL,VEACH,RICHARD,JAMES,Male,Caucasian,01/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,4,High,7,Risk of Violence,-0.91,9,High,New,1,0 +12252,79349,71767,PRETRIAL,VEACH,RICHARD,JAMES,Male,Caucasian,01/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,4,High,8,Risk of Recidivism,0.21,8,High,New,1,0 +12252,79349,71767,PRETRIAL,VEACH,RICHARD,JAMES,Male,Caucasian,01/20/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68322,79340,71758,PRETRIAL,JOHNSON,STIKKA,NULL,Female,African-American,11/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.45,3,Low,New,1,0 +68322,79340,71758,PRETRIAL,JOHNSON,STIKKA,NULL,Female,African-American,11/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.08,8,High,New,1,0 +68322,79340,71758,PRETRIAL,JOHNSON,STIKKA,NULL,Female,African-American,11/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68325,79343,71761,PRETRIAL,Bondanza,Tracy,NULL,Female,Caucasian,01/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.88,2,Low,New,1,0 +68325,79343,71761,PRETRIAL,Bondanza,Tracy,NULL,Female,Caucasian,01/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,8,High,New,1,0 +68325,79343,71761,PRETRIAL,Bondanza,Tracy,NULL,Female,Caucasian,01/29/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68330,79348,71766,PRETRIAL,Robinson,Anthony,NULL,Male,African-American,01/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,2,Medium,7,Risk of Violence,-1.56,6,Medium,New,1,0 +68330,79348,71766,PRETRIAL,Robinson,Anthony,NULL,Male,African-American,01/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,2,Medium,8,Risk of Recidivism,-0.52,4,Low,New,1,0 +68330,79348,71766,PRETRIAL,Robinson,Anthony,NULL,Male,African-American,01/22/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68328,79346,71764,PRETRIAL,SOLOMON,DETIA,NULL,Male,African-American,01/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +68328,79346,71764,PRETRIAL,SOLOMON,DETIA,NULL,Male,African-American,01/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,1,Low,8,Risk of Recidivism,-1.9,1,Low,New,1,0 +68328,79346,71764,PRETRIAL,SOLOMON,DETIA,NULL,Male,African-American,01/04/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/13/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68337,79358,71775,PRETRIAL,AVILA,MICHAEL,NULL,Male,African-American,09/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/14/14 0:00,1,Low,7,Risk of Violence,-2.25,3,Low,New,1,0 +68337,79358,71775,PRETRIAL,AVILA,MICHAEL,NULL,Male,African-American,09/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/14/14 0:00,1,Low,8,Risk of Recidivism,-0.43,5,Medium,New,1,0 +68337,79358,71775,PRETRIAL,AVILA,MICHAEL,NULL,Male,African-American,09/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/14/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68332,79351,71769,PRETRIAL,Burse,Dynesha,NULL,Female,African-American,05/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +68332,79351,71769,PRETRIAL,Burse,Dynesha,NULL,Female,African-American,05/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.28,7,Medium,New,1,0 +68332,79351,71769,PRETRIAL,Burse,Dynesha,NULL,Female,African-American,05/06/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68334,79353,71771,PRETRIAL,BRADLEY,STEVEN,LAWRENCE,Male,Caucasian,10/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/14/14 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +68334,79353,71771,PRETRIAL,BRADLEY,STEVEN,LAWRENCE,Male,Caucasian,10/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/14/14 0:00,1,Low,8,Risk of Recidivism,-1.18,2,Low,New,1,0 +68334,79353,71771,PRETRIAL,BRADLEY,STEVEN,LAWRENCE,Male,Caucasian,10/01/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/14/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68339,79360,71777,PRETRIAL,JOSEPH,DEAN,MANCINI,Male,Caucasian,03/28/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,New,1,0 +68339,79360,71777,PRETRIAL,JOSEPH,DEAN,MANCINI,Male,Caucasian,03/28/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +68339,79360,71777,PRETRIAL,JOSEPH,DEAN,MANCINI,Male,Caucasian,03/28/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,2,Medium,18,Risk of Failure to Appear,28,8,High,New,1,0 +68340,79361,71778,PRETRIAL,Miller,Jayson,NULL,Male,Caucasian,09/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,1,Low,7,Risk of Violence,-2.78,2,Low,New,1,0 +68340,79361,71778,PRETRIAL,Miller,Jayson,NULL,Male,Caucasian,09/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,1,Low,8,Risk of Recidivism,-0.99,3,Low,New,1,0 +68340,79361,71778,PRETRIAL,Miller,Jayson,NULL,Male,Caucasian,09/20/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68336,79356,71774,PRETRIAL,Boyd,Kanetra,NULL,Male,African-American,06/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,1,Low,7,Risk of Violence,-3.09,1,Low,New,1,0 +68336,79356,71774,PRETRIAL,Boyd,Kanetra,NULL,Male,African-American,06/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,1,Low,8,Risk of Recidivism,-1.59,1,Low,New,1,0 +68336,79356,71774,PRETRIAL,Boyd,Kanetra,NULL,Male,African-American,06/08/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68341,79362,71779,PRETRIAL,Graves,Christopher,A,Male,African-American,12/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +68341,79362,71779,PRETRIAL,Graves,Christopher,A,Male,African-American,12/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,1,Low,8,Risk of Recidivism,-0.74,4,Low,New,1,0 +68341,79362,71779,PRETRIAL,Graves,Christopher,A,Male,African-American,12/28/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +31817,79355,71773,PRETRIAL,BATTLE,TRAVIS,NULL,Male,African-American,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,4,High,7,Risk of Violence,-0.58,10,High,New,1,0 +31817,79355,71773,PRETRIAL,BATTLE,TRAVIS,NULL,Male,African-American,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,4,High,8,Risk of Recidivism,0.39,9,High,New,1,0 +31817,79355,71773,PRETRIAL,BATTLE,TRAVIS,NULL,Male,African-American,10/14/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +68342,79363,71780,PRETRIAL,Montesano,Rafael,NULL,Male,Caucasian,11/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/14/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +68342,79363,71780,PRETRIAL,Montesano,Rafael,NULL,Male,Caucasian,11/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/14/14 0:00,1,Low,8,Risk of Recidivism,-1.17,2,Low,New,1,0 +68342,79363,71780,PRETRIAL,Montesano,Rafael,NULL,Male,Caucasian,11/14/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +5991,79357,5607,Probation,Mornes,Nathaniel,Christian,Male,Caucasian,09/12/79,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Separated,12/14/14 0:00,1,Low,7,Risk of Violence,-3.25,1,Low,Copy,1,0 +5991,79357,5607,Probation,Mornes,Nathaniel,Christian,Male,Caucasian,09/12/79,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Separated,12/14/14 0:00,1,Low,8,Risk of Recidivism,-1.07,2,Low,Copy,1,0 +5991,79357,5607,Probation,Mornes,Nathaniel,Christian,Male,Caucasian,09/12/79,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Separated,12/14/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,Copy,1,0 +68333,79352,71770,PRETRIAL,ROLLE,SHAKERA,NULL,Female,African-American,07/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,4,High,7,Risk of Violence,-0.93,9,High,New,1,0 +68333,79352,71770,PRETRIAL,ROLLE,SHAKERA,NULL,Female,African-American,07/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,4,High,8,Risk of Recidivism,0.73,10,High,New,1,0 +68333,79352,71770,PRETRIAL,ROLLE,SHAKERA,NULL,Female,African-American,07/13/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68338,79359,71776,PRETRIAL,RENDER,SEDRICK,LAMAR,Male,African-American,08/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/14/14 0:00,2,Medium,7,Risk of Violence,-2.25,3,Low,New,1,0 +68338,79359,71776,PRETRIAL,RENDER,SEDRICK,LAMAR,Male,African-American,08/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/14/14 0:00,2,Medium,8,Risk of Recidivism,-0.24,6,Medium,New,1,0 +68338,79359,71776,PRETRIAL,RENDER,SEDRICK,LAMAR,Male,African-American,08/17/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/14/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68335,79354,71772,PRETRIAL,GOSSELIN,GATSON,ROMULUS,Male,Caucasian,02/06/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,1,Low,7,Risk of Violence,-4.11,1,Low,New,1,0 +68335,79354,71772,PRETRIAL,GOSSELIN,GATSON,ROMULUS,Male,Caucasian,02/06/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,1,Low,8,Risk of Recidivism,-2.52,1,Low,New,1,0 +68335,79354,71772,PRETRIAL,GOSSELIN,GATSON,ROMULUS,Male,Caucasian,02/06/61,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/14/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68347,79368,71785,PRETRIAL,Hall,David,NULL,Male,Caucasian,07/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +68347,79368,71785,PRETRIAL,Hall,David,NULL,Male,Caucasian,07/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +68347,79368,71785,PRETRIAL,Hall,David,NULL,Male,Caucasian,07/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +17687,79375,71792,PRETRIAL,ALEXANDER,LEONARD,A,Male,African-American,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/15/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +17687,79375,71792,PRETRIAL,ALEXANDER,LEONARD,A,Male,African-American,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/15/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +17687,79375,71792,PRETRIAL,ALEXANDER,LEONARD,A,Male,African-American,05/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/15/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68352,79373,71790,DRRD,Noel,Jerry,NULL,Male,African-American,11/12/81,17,All Scales,Intake,English,Probation Violator,Probation,Single,12/15/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +68352,79373,71790,DRRD,Noel,Jerry,NULL,Male,African-American,11/12/81,17,All Scales,Intake,English,Probation Violator,Probation,Single,12/15/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.1,7,Medium,New,1,0 +68352,79373,71790,DRRD,Noel,Jerry,NULL,Male,African-American,11/12/81,17,All Scales,Intake,English,Probation Violator,Probation,Single,12/15/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,4,Low,New,1,0 +68345,79366,71783,PRETRIAL,VALLEJO,luis,GUILLERMO,Male,Caucasian,07/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,7,Risk of Violence,-1.84,5,Medium,New,1,0 +68345,79366,71783,PRETRIAL,VALLEJO,luis,GUILLERMO,Male,Caucasian,07/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +68345,79366,71783,PRETRIAL,VALLEJO,luis,GUILLERMO,Male,Caucasian,07/05/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68344,79365,71782,PRETRIAL,Vasquez,Steven,NULL,Male,Caucasian,09/30/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,2,Medium,7,Risk of Violence,-1.69,6,Medium,New,1,0 +68344,79365,71782,PRETRIAL,Vasquez,Steven,NULL,Male,Caucasian,09/30/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,2,Medium,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +68344,79365,71782,PRETRIAL,Vasquez,Steven,NULL,Male,Caucasian,09/30/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68349,79370,71787,PRETRIAL,Sittif,Michael,Wilson,Male,Caucasian,05/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +68349,79370,71787,PRETRIAL,Sittif,Michael,Wilson,Male,Caucasian,05/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +68349,79370,71787,PRETRIAL,Sittif,Michael,Wilson,Male,Caucasian,05/17/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +35653,79377,34879,PRETRIAL,Robinson,Stephen,A,Male,African-American,03/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,Copy,1,0 +35653,79377,34879,PRETRIAL,Robinson,Stephen,A,Male,African-American,03/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,8,Risk of Recidivism,-0.59,4,Low,Copy,1,0 +35653,79377,34879,PRETRIAL,Robinson,Stephen,A,Male,African-American,03/16/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +68343,79364,71781,PRETRIAL,OQuinn,Tamara,NULL,Female,Caucasian,03/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +68343,79364,71781,PRETRIAL,OQuinn,Tamara,NULL,Female,Caucasian,03/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +68343,79364,71781,PRETRIAL,OQuinn,Tamara,NULL,Female,Caucasian,03/07/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68351,79372,71789,PRETRIAL,Alarcon,Jorge,NULL,Male,Hispanic,02/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,4,High,7,Risk of Violence,-1.11,8,High,New,1,0 +68351,79372,71789,PRETRIAL,Alarcon,Jorge,NULL,Male,Hispanic,02/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,4,High,8,Risk of Recidivism,0.09,8,High,New,1,0 +68351,79372,71789,PRETRIAL,Alarcon,Jorge,NULL,Male,Hispanic,02/04/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,4,High,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68354,79376,71793,PRETRIAL,claudio-nieves,shawn,NULL,Male,Hispanic,04/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,New,1,0 +68354,79376,71793,PRETRIAL,claudio-nieves,shawn,NULL,Male,Hispanic,04/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,New,1,0 +68354,79376,71793,PRETRIAL,claudio-nieves,shawn,NULL,Male,Hispanic,04/08/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/15/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68346,79367,71784,PRETRIAL,OREFICE,MICHAEL,JOHN,Male,Caucasian,05/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/15/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +68346,79367,71784,PRETRIAL,OREFICE,MICHAEL,JOHN,Male,Caucasian,05/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/15/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +68346,79367,71784,PRETRIAL,OREFICE,MICHAEL,JOHN,Male,Caucasian,05/28/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/15/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68370,79397,71811,PRETRIAL,BARRY,RAVEN,NULL,Female,Caucasian,05/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.74,5,Medium,New,1,0 +68370,79397,71811,PRETRIAL,BARRY,RAVEN,NULL,Female,Caucasian,05/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.01,8,High,New,1,0 +68370,79397,71811,PRETRIAL,BARRY,RAVEN,NULL,Female,Caucasian,05/02/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68356,79379,71795,PRETRIAL,Devallon,Gueldrine,D,Female,Other,10/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +68356,79379,71795,PRETRIAL,Devallon,Gueldrine,D,Female,Other,10/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +68356,79379,71795,PRETRIAL,Devallon,Gueldrine,D,Female,Other,10/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68358,79381,71797,PRETRIAL,Suddoo,Kadeem,A,Male,African-American,12/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +68358,79381,71797,PRETRIAL,Suddoo,Kadeem,A,Male,African-American,12/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.71,10,High,New,1,0 +68358,79381,71797,PRETRIAL,Suddoo,Kadeem,A,Male,African-American,12/24/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68363,79388,71803,PRETRIAL,JACKSON,CASSIDY,NICHOLE,Female,African-American,09/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +68363,79388,71803,PRETRIAL,JACKSON,CASSIDY,NICHOLE,Female,African-American,09/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,8,Risk of Recidivism,-0.7,5,Medium,New,1,0 +68363,79388,71803,PRETRIAL,JACKSON,CASSIDY,NICHOLE,Female,African-American,09/14/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +7436,79395,71809,PRETRIAL,DAMICO,DEREK,PATRICK,Male,Caucasian,05/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/14 0:00,1,Low,7,Risk of Violence,-2.67,2,Low,New,1,0 +7436,79395,71809,PRETRIAL,DAMICO,DEREK,PATRICK,Male,Caucasian,05/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/14 0:00,1,Low,8,Risk of Recidivism,-0.61,4,Low,New,1,0 +7436,79395,71809,PRETRIAL,DAMICO,DEREK,PATRICK,Male,Caucasian,05/17/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68374,79402,71815,Probation,Edinburg,Shanuce,NULL,Female,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +68374,79402,71815,Probation,Edinburg,Shanuce,NULL,Female,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/14 0:00,1,Low,8,Risk of Recidivism,-1.05,3,Low,New,1,0 +68374,79402,71815,Probation,Edinburg,Shanuce,NULL,Female,African-American,03/26/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68371,79398,71812,PRETRIAL,JONES,JENNIFER,NULL,Female,African-American,09/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.42,3,Low,New,1,0 +68371,79398,71812,PRETRIAL,JONES,JENNIFER,NULL,Female,African-American,09/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.66,10,High,New,1,0 +68371,79398,71812,PRETRIAL,JONES,JENNIFER,NULL,Female,African-American,09/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,34,10,High,New,1,0 +68361,79385,71800,PRETRIAL,Gegoire,Steve,NULL,Male,Other,06/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/16/14 0:00,1,Low,7,Risk of Violence,-2.94,2,Low,New,1,0 +68361,79385,71800,PRETRIAL,Gegoire,Steve,NULL,Male,Other,06/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/16/14 0:00,1,Low,8,Risk of Recidivism,-1.85,1,Low,New,1,0 +68361,79385,71800,PRETRIAL,Gegoire,Steve,NULL,Male,Other,06/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68367,79392,71807,PRETRIAL,NEWSOME,VANESHA,UIQUE,Female,African-American,09/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,4,High,7,Risk of Violence,-0.95,9,High,New,1,0 +68367,79392,71807,PRETRIAL,NEWSOME,VANESHA,UIQUE,Female,African-American,09/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,4,High,8,Risk of Recidivism,0.36,9,High,New,1,0 +68367,79392,71807,PRETRIAL,NEWSOME,VANESHA,UIQUE,Female,African-American,09/04/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,4,High,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68365,79390,71805,PRETRIAL,JOZEFYK,JESSICA,MICHELLE,Female,Caucasian,09/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.28,7,Medium,New,1,0 +68365,79390,71805,PRETRIAL,JOZEFYK,JESSICA,MICHELLE,Female,Caucasian,09/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.37,9,High,New,1,0 +68365,79390,71805,PRETRIAL,JOZEFYK,JESSICA,MICHELLE,Female,Caucasian,09/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +11978,79382,11493,PRETRIAL,REED,DEMETRIUS,R,Male,African-American,01/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,4,High,7,Risk of Violence,-1.11,8,High,Copy,1,0 +11978,79382,11493,PRETRIAL,REED,DEMETRIUS,R,Male,African-American,01/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,4,High,8,Risk of Recidivism,0.55,9,High,Copy,1,0 +11978,79382,11493,PRETRIAL,REED,DEMETRIUS,R,Male,African-American,01/12/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +68375,79403,71816,PRETRIAL,Frattura,Mario,NULL,Male,Caucasian,07/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/16/14 0:00,1,Low,7,Risk of Violence,-2.19,4,Low,New,1,0 +68375,79403,71816,PRETRIAL,Frattura,Mario,NULL,Male,Caucasian,07/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/16/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +68375,79403,71816,PRETRIAL,Frattura,Mario,NULL,Male,Caucasian,07/26/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Married,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +68366,79391,71806,PRETRIAL,Brown,Nigel,Okieve,Male,Other,09/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +68366,79391,71806,PRETRIAL,Brown,Nigel,Okieve,Male,Other,09/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +68366,79391,71806,PRETRIAL,Brown,Nigel,Okieve,Male,Other,09/05/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68359,79383,71798,PRETRIAL,TANIS,RICHEMOND,NULL,Male,Other,01/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/14 0:00,1,Low,7,Risk of Violence,-3.02,1,Low,New,1,0 +68359,79383,71798,PRETRIAL,TANIS,RICHEMOND,NULL,Male,Other,01/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +68359,79383,71798,PRETRIAL,TANIS,RICHEMOND,NULL,Male,Other,01/29/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +34467,79386,71801,PRETRIAL,Douze,Mike,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +34467,79386,71801,PRETRIAL,Douze,Mike,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +34467,79386,71801,PRETRIAL,Douze,Mike,NULL,Male,African-American,11/03/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68376,79404,71817,PRETRIAL,Littman,Lester,NULL,Male,Caucasian,08/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,7,Risk of Violence,-3,1,Low,New,1,0 +68376,79404,71817,PRETRIAL,Littman,Lester,NULL,Male,Caucasian,08/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +68376,79404,71817,PRETRIAL,Littman,Lester,NULL,Male,Caucasian,08/29/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68362,79387,71802,PRETRIAL,PHILMORE,MARCEL,NULL,Male,Native American,08/31/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,2,Medium,7,Risk of Violence,-2.41,3,Low,New,1,0 +68362,79387,71802,PRETRIAL,PHILMORE,MARCEL,NULL,Male,Native American,08/31/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.04,7,Medium,New,1,0 +68362,79387,71802,PRETRIAL,PHILMORE,MARCEL,NULL,Male,Native American,08/31/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68368,79394,71808,PRETRIAL,Tharp,Joshua,Carle,Male,Caucasian,07/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,7,Risk of Violence,-1.98,4,Low,Copy,1,0 +68368,79394,71808,PRETRIAL,Tharp,Joshua,Carle,Male,Caucasian,07/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,Copy,1,0 +68368,79394,71808,PRETRIAL,Tharp,Joshua,Carle,Male,Caucasian,07/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +68369,79396,71810,Probation,Broliath,Logan,NULL,Male,Caucasian,05/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +68369,79396,71810,Probation,Broliath,Logan,NULL,Male,Caucasian,05/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/14 0:00,1,Low,8,Risk of Recidivism,-1.75,1,Low,New,1,0 +68369,79396,71810,Probation,Broliath,Logan,NULL,Male,Caucasian,05/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +12254,12646,11745,PRETRIAL,CRAVEN,BRUCE,E,Male,Caucasian,05/16/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,2,Medium,7,Risk of Violence,-2.21,4,Low,New,1,0 +12254,12646,11745,PRETRIAL,CRAVEN,BRUCE,E,Male,Caucasian,05/16/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +12254,12646,11745,PRETRIAL,CRAVEN,BRUCE,E,Male,Caucasian,05/16/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,2,Medium,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +68364,79389,71804,PRETRIAL,BLAKENSHIP,ASHLEY,ASHLEY,Female,Caucasian,03/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/16/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +68364,79389,71804,PRETRIAL,BLAKENSHIP,ASHLEY,ASHLEY,Female,Caucasian,03/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/16/14 0:00,1,Low,8,Risk of Recidivism,-0.61,5,Medium,New,1,0 +68364,79389,71804,PRETRIAL,BLAKENSHIP,ASHLEY,ASHLEY,Female,Caucasian,03/16/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68360,79384,71799,PRETRIAL,Guyher,Kavair,NULL,Male,Other,01/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/16/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +68360,79384,71799,PRETRIAL,Guyher,Kavair,NULL,Male,Other,01/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/16/14 0:00,1,Low,8,Risk of Recidivism,-1.22,2,Low,New,1,0 +68360,79384,71799,PRETRIAL,Guyher,Kavair,NULL,Male,Other,01/22/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68357,79380,71796,PRETRIAL,MICHEL,JOSIANNE,NULL,Female,African-American,05/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,7,Risk of Violence,-3.82,1,Low,New,1,0 +68357,79380,71796,PRETRIAL,MICHEL,JOSIANNE,NULL,Female,African-American,05/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,8,Risk of Recidivism,-2.27,1,Low,New,1,0 +68357,79380,71796,PRETRIAL,MICHEL,JOSIANNE,NULL,Female,African-American,05/15/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68373,79401,71814,PRETRIAL,HAWALDAR,RIZWAAN,NULL,Male,Other,02/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/16/14 0:00,1,Low,7,Risk of Violence,-3.48,1,Low,Copy,1,0 +68373,79401,71814,PRETRIAL,HAWALDAR,RIZWAAN,NULL,Male,Other,02/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/16/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,Copy,1,0 +68373,79401,71814,PRETRIAL,HAWALDAR,RIZWAAN,NULL,Male,Other,02/19/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/16/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +68377,79405,71818,PRETRIAL,RILEY,LANCE,MATTHEW,Female,African-American,10/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,4,High,7,Risk of Violence,-1,8,High,New,1,0 +68377,79405,71818,PRETRIAL,RILEY,LANCE,MATTHEW,Female,African-American,10/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,4,High,8,Risk of Recidivism,0.45,10,High,New,1,0 +68377,79405,71818,PRETRIAL,RILEY,LANCE,MATTHEW,Female,African-American,10/29/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68382,79410,71823,PRETRIAL,Cooke,Rick,NULL,Male,Caucasian,04/30/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/17/14 0:00,1,Low,7,Risk of Violence,-3.91,1,Low,New,1,0 +68382,79410,71823,PRETRIAL,Cooke,Rick,NULL,Male,Caucasian,04/30/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/17/14 0:00,1,Low,8,Risk of Recidivism,-2,1,Low,New,1,0 +68382,79410,71823,PRETRIAL,Cooke,Rick,NULL,Male,Caucasian,04/30/55,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +67681,79431,71090,PRETRIAL,Doe,Tyrel,NULL,Male,African-American,11/14/92,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/17/14 0:00,4,High,7,Risk of Violence,-1.06,8,High,Copy,1,0 +67681,79431,71090,PRETRIAL,Doe,Tyrel,NULL,Male,African-American,11/14/92,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/17/14 0:00,4,High,8,Risk of Recidivism,0.29,8,High,Copy,1,0 +67681,79431,71090,PRETRIAL,Doe,Tyrel,NULL,Male,African-American,11/14/92,17,All Scales,Intake,English,Pretrial,Pretrial Defendant,Single,12/17/14 0:00,4,High,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +2978,2904,2693,PRETRIAL,KELLER,JOSEPH,PATRICK,Male,Caucasian,02/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,4,High,7,Risk of Violence,-1.18,8,High,New,1,0 +2978,2904,2693,PRETRIAL,KELLER,JOSEPH,PATRICK,Male,Caucasian,02/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,4,High,8,Risk of Recidivism,0.69,10,High,New,1,0 +2978,2904,2693,PRETRIAL,KELLER,JOSEPH,PATRICK,Male,Caucasian,02/17/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +68394,79422,71834,PRETRIAL,fields,qushondra,NULL,Female,African-American,12/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +68394,79422,71834,PRETRIAL,fields,qushondra,NULL,Female,African-American,12/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +68394,79422,71834,PRETRIAL,fields,qushondra,NULL,Female,African-American,12/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68387,79415,71828,PRETRIAL,Naira,Bernice,NULL,Female,Other,08/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/17/14 0:00,1,Low,7,Risk of Violence,-3.63,1,Low,New,1,0 +68387,79415,71828,PRETRIAL,Naira,Bernice,NULL,Female,Other,08/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/17/14 0:00,1,Low,8,Risk of Recidivism,-2.08,1,Low,New,1,0 +68387,79415,71828,PRETRIAL,Naira,Bernice,NULL,Female,Other,08/24/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68389,79417,71830,PRETRIAL,Wilkinson,Keva,NULL,Female,African-American,11/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,7,Risk of Violence,-3.14,1,Low,New,1,0 +68389,79417,71830,PRETRIAL,Wilkinson,Keva,NULL,Female,African-American,11/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,8,Risk of Recidivism,-1.59,2,Low,New,1,0 +68389,79417,71830,PRETRIAL,Wilkinson,Keva,NULL,Female,African-American,11/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68395,79424,71835,PRETRIAL,Horta,Rosa,Haydee,Male,Caucasian,11/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,Copy,1,0 +68395,79424,71835,PRETRIAL,Horta,Rosa,Haydee,Male,Caucasian,11/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,Copy,1,0 +68395,79424,71835,PRETRIAL,Horta,Rosa,Haydee,Male,Caucasian,11/05/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +68379,79407,71820,PRETRIAL,Mathieu,Meachnight,NULL,Male,African-American,12/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,7,Risk of Violence,-1.83,5,Medium,New,1,0 +68379,79407,71820,PRETRIAL,Mathieu,Meachnight,NULL,Male,African-American,12/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,8,Risk of Recidivism,-0.81,3,Low,New,1,0 +68379,79407,71820,PRETRIAL,Mathieu,Meachnight,NULL,Male,African-American,12/24/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +3073,3008,2788,PRETRIAL,Moore,Michael,Antonio,Male,African-American,02/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.79,5,Medium,New,1,0 +3073,3008,2788,PRETRIAL,Moore,Michael,Antonio,Male,African-American,02/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.62,10,High,New,1,0 +3073,3008,2788,PRETRIAL,Moore,Michael,Antonio,Male,African-American,02/01/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68384,79412,71825,PRETRIAL,Petitisse,Andre,NULL,Male,Other,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/17/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +68384,79412,71825,PRETRIAL,Petitisse,Andre,NULL,Male,Other,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/17/14 0:00,1,Low,8,Risk of Recidivism,-1.82,1,Low,New,1,0 +68384,79412,71825,PRETRIAL,Petitisse,Andre,NULL,Male,Other,11/13/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68399,79428,71839,PRETRIAL,GOLDFARB,JACK,NULL,Male,Caucasian,03/25/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/17/14 0:00,1,Low,7,Risk of Violence,-3.68,1,Low,New,1,0 +68399,79428,71839,PRETRIAL,GOLDFARB,JACK,NULL,Male,Caucasian,03/25/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/17/14 0:00,1,Low,8,Risk of Recidivism,-1.54,1,Low,New,1,0 +68399,79428,71839,PRETRIAL,GOLDFARB,JACK,NULL,Male,Caucasian,03/25/49,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68388,79416,71829,PRETRIAL,Credle,Shondayah,S,Female,African-American,08/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,New,1,0 +68388,79416,71829,PRETRIAL,Credle,Shondayah,S,Female,African-American,08/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,8,Risk of Recidivism,-1.12,3,Low,New,1,0 +68388,79416,71829,PRETRIAL,Credle,Shondayah,S,Female,African-American,08/22/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68380,79408,71821,PRETRIAL,Gordon,Andrew,NULL,Male,African-American,12/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +68380,79408,71821,PRETRIAL,Gordon,Andrew,NULL,Male,African-American,12/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,8,Risk of Recidivism,-2.03,1,Low,New,1,0 +68380,79408,71821,PRETRIAL,Gordon,Andrew,NULL,Male,African-American,12/18/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68383,79411,71824,PRETRIAL,Gaskin,Tylus,J,Male,African-American,06/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,7,Risk of Violence,-1.97,5,Medium,New,1,0 +68383,79411,71824,PRETRIAL,Gaskin,Tylus,J,Male,African-American,06/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +68383,79411,71824,PRETRIAL,Gaskin,Tylus,J,Male,African-American,06/16/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68378,79406,71819,PRETRIAL,Frank,Howard,NULL,Male,Caucasian,12/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +68378,79406,71819,PRETRIAL,Frank,Howard,NULL,Male,Caucasian,12/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,8,Risk of Recidivism,-1.09,2,Low,New,1,0 +68378,79406,71819,PRETRIAL,Frank,Howard,NULL,Male,Caucasian,12/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68385,79413,71826,PRETRIAL,NELSON,DAVID,LEE,Male,African-American,10/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,2,Medium,7,Risk of Violence,-2.47,3,Low,New,1,0 +68385,79413,71826,PRETRIAL,NELSON,DAVID,LEE,Male,African-American,10/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,2,Medium,8,Risk of Recidivism,-0.2,6,Medium,New,1,0 +68385,79413,71826,PRETRIAL,NELSON,DAVID,LEE,Male,African-American,10/07/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68398,79427,71838,PRETRIAL,Jennings,Jennifer,NULL,Female,African-American,02/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,7,Risk of Violence,-2.11,4,Low,New,1,0 +68398,79427,71838,PRETRIAL,Jennings,Jennifer,NULL,Female,African-American,02/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,8,Risk of Recidivism,-0.83,4,Low,New,1,0 +68398,79427,71838,PRETRIAL,Jennings,Jennifer,NULL,Female,African-American,02/12/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68392,79421,71833,PRETRIAL,pINEDA,GIOVANNY,NULL,Male,Hispanic,07/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,7,Risk of Violence,-3.52,1,Low,New,1,0 +68392,79421,71833,PRETRIAL,pINEDA,GIOVANNY,NULL,Male,Hispanic,07/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +68392,79421,71833,PRETRIAL,pINEDA,GIOVANNY,NULL,Male,Hispanic,07/18/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68397,79426,71837,PRETRIAL,Baribeault,Robert,NULL,Male,Caucasian,09/16/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +68397,79426,71837,PRETRIAL,Baribeault,Robert,NULL,Male,Caucasian,09/16/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,8,Risk of Recidivism,-2.07,1,Low,New,1,0 +68397,79426,71837,PRETRIAL,Baribeault,Robert,NULL,Male,Caucasian,09/16/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68381,79409,71822,PRETRIAL,JONES,CHRISTOPHER,MICHAEL,Male,Caucasian,07/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/17/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,New,1,0 +68381,79409,71822,PRETRIAL,JONES,CHRISTOPHER,MICHAEL,Male,Caucasian,07/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/17/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,New,1,0 +68381,79409,71822,PRETRIAL,JONES,CHRISTOPHER,MICHAEL,Male,Caucasian,07/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/17/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +57659,79430,71840,Probation,doctor,patrick,NULL,Male,Native American,01/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,4,High,7,Risk of Violence,-0.19,10,High,New,1,0 +57659,79430,71840,Probation,doctor,patrick,NULL,Male,Native American,01/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,4,High,8,Risk of Recidivism,1.37,10,High,New,1,0 +57659,79430,71840,Probation,doctor,patrick,NULL,Male,Native American,01/17/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,4,High,18,Risk of Failure to Appear,44,10,High,New,1,0 +68390,79418,71831,PRETRIAL,BURNS,ALISHA,LEE,Female,Caucasian,11/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.09,4,Low,New,1,0 +68390,79418,71831,PRETRIAL,BURNS,ALISHA,LEE,Female,Caucasian,11/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.71,10,High,New,1,0 +68390,79418,71831,PRETRIAL,BURNS,ALISHA,LEE,Female,Caucasian,11/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,28,8,High,New,1,0 +42121,45897,41897,PRETRIAL,RIDGLEY,MICHAEL,NULL,Male,Caucasian,09/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.05,4,Low,New,1,0 +42121,45897,41897,PRETRIAL,RIDGLEY,MICHAEL,NULL,Male,Caucasian,09/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.48,9,High,New,1,0 +42121,45897,41897,PRETRIAL,RIDGLEY,MICHAEL,NULL,Male,Caucasian,09/13/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68386,79414,71827,PRETRIAL,MCWHORTER,JASON,D,Male,African-American,07/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.02,4,Low,New,1,0 +68386,79414,71827,PRETRIAL,MCWHORTER,JASON,D,Male,African-American,07/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.31,9,High,New,1,0 +68386,79414,71827,PRETRIAL,MCWHORTER,JASON,D,Male,African-American,07/07/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/17/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +68403,79435,71844,PRETRIAL,King,Kenneth,NULL,Male,African-American,01/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,7,Risk of Violence,-3.08,1,Low,New,1,0 +68403,79435,71844,PRETRIAL,King,Kenneth,NULL,Male,African-American,01/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,8,Risk of Recidivism,-1.52,1,Low,New,1,0 +68403,79435,71844,PRETRIAL,King,Kenneth,NULL,Male,African-American,01/05/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68406,79439,71847,PRETRIAL,OUTEN,SHAQUILLA,SHAVAY,Female,African-American,06/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +68406,79439,71847,PRETRIAL,OUTEN,SHAQUILLA,SHAVAY,Female,African-American,06/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,8,Risk of Recidivism,-0.91,4,Low,New,1,0 +68406,79439,71847,PRETRIAL,OUTEN,SHAQUILLA,SHAVAY,Female,African-American,06/08/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +27188,49224,44882,PRETRIAL,SHEPPARD,TOMMY,FRANKLIN,Male,Caucasian,06/26/86,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,12/18/14 0:00,2,Medium,7,Risk of Violence,-2.52,3,Low,New,1,0 +27188,49224,44882,PRETRIAL,SHEPPARD,TOMMY,FRANKLIN,Male,Caucasian,06/26/86,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,12/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +27188,49224,44882,PRETRIAL,SHEPPARD,TOMMY,FRANKLIN,Male,Caucasian,06/26/86,22,Risk and Prescreen,Intake,English,Other,Jail Inmate,Single,12/18/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68400,79432,71841,PRETRIAL,Loden,John,NULL,Male,Caucasian,08/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.7,6,Medium,New,1,0 +68400,79432,71841,PRETRIAL,Loden,John,NULL,Male,Caucasian,08/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,New,1,0 +68400,79432,71841,PRETRIAL,Loden,John,NULL,Male,Caucasian,08/02/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,31,9,High,New,1,0 +68402,79434,71843,PRETRIAL,MCALILEY,ANDREW,THOMAS,Male,Caucasian,09/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,7,Risk of Violence,-2.7,2,Low,New,1,0 +68402,79434,71843,PRETRIAL,MCALILEY,ANDREW,THOMAS,Male,Caucasian,09/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +68402,79434,71843,PRETRIAL,MCALILEY,ANDREW,THOMAS,Male,Caucasian,09/24/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +30640,79447,29614,PRETRIAL,alford,malcolm,NULL,Male,African-American,04/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.1,4,Low,Copy,1,0 +30640,79447,29614,PRETRIAL,alford,malcolm,NULL,Male,African-American,04/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.18,8,High,Copy,1,0 +30640,79447,29614,PRETRIAL,alford,malcolm,NULL,Male,African-American,04/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +45021,61744,45205,PRETRIAL,MOULTRIE,RYAN,NULL,Male,African-American,11/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,4,High,7,Risk of Violence,-0.75,9,High,Copy,1,0 +45021,61744,45205,PRETRIAL,MOULTRIE,RYAN,NULL,Male,African-American,11/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,4,High,8,Risk of Recidivism,0.95,10,High,Copy,1,0 +45021,61744,45205,PRETRIAL,MOULTRIE,RYAN,NULL,Male,African-American,11/22/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,4,High,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +7396,67167,60903,PRETRIAL,Watson,Adam,NULL,Male,Caucasian,09/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,7,Risk of Violence,-2.24,3,Low,New,1,0 +7396,67167,60903,PRETRIAL,Watson,Adam,NULL,Male,Caucasian,09/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +7396,67167,60903,PRETRIAL,Watson,Adam,NULL,Male,Caucasian,09/09/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68405,79437,71846,PRETRIAL,Sullivan,Shannon,Dawn,Female,Caucasian,02/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.41,7,Medium,New,1,0 +68405,79437,71846,PRETRIAL,Sullivan,Shannon,Dawn,Female,Caucasian,02/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.69,10,High,New,1,0 +68405,79437,71846,PRETRIAL,Sullivan,Shannon,Dawn,Female,Caucasian,02/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68408,79441,71849,PRETRIAL,SALAZAR,DAYANIRA,COROMOTO,Female,Caucasian,01/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/18/14 0:00,1,Low,7,Risk of Violence,-2.85,2,Low,New,1,0 +68408,79441,71849,PRETRIAL,SALAZAR,DAYANIRA,COROMOTO,Female,Caucasian,01/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/18/14 0:00,1,Low,8,Risk of Recidivism,-0.69,5,Medium,New,1,0 +68408,79441,71849,PRETRIAL,SALAZAR,DAYANIRA,COROMOTO,Female,Caucasian,01/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/18/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68412,79446,71852,PRETRIAL,Robinson,Ollica,NULL,Female,African-American,06/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-0.88,9,High,New,1,0 +68412,79446,71852,PRETRIAL,Robinson,Ollica,NULL,Female,African-American,06/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.15,7,Medium,New,1,0 +68412,79446,71852,PRETRIAL,Robinson,Ollica,NULL,Female,African-American,06/18/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +68401,79433,71842,PRETRIAL,Slade,Josephine,Kenyaa,Female,Caucasian,05/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +68401,79433,71842,PRETRIAL,Slade,Josephine,Kenyaa,Female,Caucasian,05/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,2,Medium,8,Risk of Recidivism,-0.47,6,Medium,New,1,0 +68401,79433,71842,PRETRIAL,Slade,Josephine,Kenyaa,Female,Caucasian,05/01/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68407,79440,71848,PRETRIAL,RAPONE,TONI,NULL,Female,Caucasian,10/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +68407,79440,71848,PRETRIAL,RAPONE,TONI,NULL,Female,Caucasian,10/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,8,Risk of Recidivism,-0.87,4,Low,New,1,0 +68407,79440,71848,PRETRIAL,RAPONE,TONI,NULL,Female,Caucasian,10/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68404,79436,71845,PRETRIAL,BURKE,MARK,WILLIAM,Male,Caucasian,02/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,7,Risk of Violence,-4.03,1,Low,New,1,0 +68404,79436,71845,PRETRIAL,BURKE,MARK,WILLIAM,Male,Caucasian,02/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,8,Risk of Recidivism,-2.45,1,Low,New,1,0 +68404,79436,71845,PRETRIAL,BURKE,MARK,WILLIAM,Male,Caucasian,02/23/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/18/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68429,79461,71863,PRETRIAL,LIQUORI,THERESA,NULL,Female,Caucasian,10/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/19/14 0:00,1,Low,7,Risk of Violence,-3.13,1,Low,New,1,0 +68429,79461,71863,PRETRIAL,LIQUORI,THERESA,NULL,Female,Caucasian,10/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/19/14 0:00,1,Low,8,Risk of Recidivism,-1.58,2,Low,New,1,0 +68429,79461,71863,PRETRIAL,LIQUORI,THERESA,NULL,Female,Caucasian,10/10/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +66797,79457,70085,PRETRIAL,Barrett,Rohan,NULL,Male,African-American,04/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-3.19,1,Low,New,1,0 +66797,79457,70085,PRETRIAL,Barrett,Rohan,NULL,Male,African-American,04/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-1.29,2,Low,New,1,0 +66797,79457,70085,PRETRIAL,Barrett,Rohan,NULL,Male,African-American,04/26/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68428,79459,71862,PRETRIAL,WILSON,TRAVIS,KYLE,Male,Caucasian,04/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +68428,79459,71862,PRETRIAL,WILSON,TRAVIS,KYLE,Male,Caucasian,04/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-1.11,2,Low,New,1,0 +68428,79459,71862,PRETRIAL,WILSON,TRAVIS,KYLE,Male,Caucasian,04/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68424,79452,71856,PRETRIAL,Brown,Sandy,P,Female,African-American,07/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/19/14 0:00,1,Low,7,Risk of Violence,-2.92,2,Low,New,1,0 +68424,79452,71856,PRETRIAL,Brown,Sandy,P,Female,African-American,07/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/19/14 0:00,1,Low,8,Risk of Recidivism,-1.6,2,Low,New,1,0 +68424,79452,71856,PRETRIAL,Brown,Sandy,P,Female,African-American,07/16/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68434,79466,71867,PRETRIAL,Milling,James,NULL,Male,African-American,03/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +68434,79466,71867,PRETRIAL,Milling,James,NULL,Male,African-American,03/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-1.47,1,Low,New,1,0 +68434,79466,71867,PRETRIAL,Milling,James,NULL,Male,African-American,03/12/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68435,79467,71868,PRETRIAL,CORTEZ-AMAYA,JOSE,NULL,Male,Hispanic,12/15/83,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +68435,79467,71868,PRETRIAL,CORTEZ-AMAYA,JOSE,NULL,Male,Hispanic,12/15/83,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,New,1,0 +68435,79467,71868,PRETRIAL,CORTEZ-AMAYA,JOSE,NULL,Male,Hispanic,12/15/83,22,Risk and Prescreen,Intake,Spanish,Pretrial,Pretrial Defendant,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68426,79454,71858,PRETRIAL,Kiernan,Dakota,James,Male,Caucasian,11/20/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.32,7,Medium,New,1,0 +68426,79454,71858,PRETRIAL,Kiernan,Dakota,James,Male,Caucasian,11/20/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.11,8,High,New,1,0 +68426,79454,71858,PRETRIAL,Kiernan,Dakota,James,Male,Caucasian,11/20/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +67866,79456,71860,PRETRIAL,Bein,Carrie,NULL,Female,Caucasian,05/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,2,Medium,7,Risk of Violence,-1.9,5,Medium,New,1,0 +67866,79456,71860,PRETRIAL,Bein,Carrie,NULL,Female,Caucasian,05/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +67866,79456,71860,PRETRIAL,Bein,Carrie,NULL,Female,Caucasian,05/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68438,79470,71871,PRETRIAL,MARTIN,ARLEEN,NULL,Female,Caucasian,08/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +68438,79470,71871,PRETRIAL,MARTIN,ARLEEN,NULL,Female,Caucasian,08/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +68438,79470,71871,PRETRIAL,MARTIN,ARLEEN,NULL,Female,Caucasian,08/14/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68430,79462,71864,PRETRIAL,FUERTES,CARLOS,EDUARDO,Male,Caucasian,09/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/19/14 0:00,1,Low,7,Risk of Violence,-3.54,1,Low,New,1,0 +68430,79462,71864,PRETRIAL,FUERTES,CARLOS,EDUARDO,Male,Caucasian,09/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/19/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +68430,79462,71864,PRETRIAL,FUERTES,CARLOS,EDUARDO,Male,Caucasian,09/14/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68422,79449,71854,PRETRIAL,Stephens,Desmond,NULL,Male,African-American,08/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +68422,79449,71854,PRETRIAL,Stephens,Desmond,NULL,Male,African-American,08/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-0.69,4,Low,New,1,0 +68422,79449,71854,PRETRIAL,Stephens,Desmond,NULL,Male,African-American,08/01/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +68431,79464,71865,PRETRIAL,HUDSON,JON-MICHAEL,ANDRE,Male,African-American,02/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-2.59,2,Low,New,1,0 +68431,79464,71865,PRETRIAL,HUDSON,JON-MICHAEL,ANDRE,Male,African-American,02/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-1.27,2,Low,New,1,0 +68431,79464,71865,PRETRIAL,HUDSON,JON-MICHAEL,ANDRE,Male,African-American,02/01/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +68423,79450,71855,PRETRIAL,Kearns,Angelica,NULL,Female,Caucasian,07/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-2.33,3,Low,New,1,0 +68423,79450,71855,PRETRIAL,Kearns,Angelica,NULL,Female,Caucasian,07/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-1.15,3,Low,New,1,0 +68423,79450,71855,PRETRIAL,Kearns,Angelica,NULL,Female,Caucasian,07/04/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68427,79458,71861,PRETRIAL,CAMILLO,RONALD,NULL,Male,Caucasian,04/16/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-4.35,1,Low,New,1,0 +68427,79458,71861,PRETRIAL,CAMILLO,RONALD,NULL,Male,Caucasian,04/16/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-2.62,1,Low,New,1,0 +68427,79458,71861,PRETRIAL,CAMILLO,RONALD,NULL,Male,Caucasian,04/16/50,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +46598,79451,47022,PRETRIAL,Swift,Reuben,NULL,Male,African-American,11/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,Copy,1,0 +46598,79451,47022,PRETRIAL,Swift,Reuben,NULL,Male,African-American,11/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,Copy,1,0 +46598,79451,47022,PRETRIAL,Swift,Reuben,NULL,Male,African-American,11/27/62,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,Copy,1,0 +68425,79453,71857,PRETRIAL,Drew,Michael,Owen,Male,Caucasian,05/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +68425,79453,71857,PRETRIAL,Drew,Michael,Owen,Male,Caucasian,05/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-0.4,5,Medium,New,1,0 +68425,79453,71857,PRETRIAL,Drew,Michael,Owen,Male,Caucasian,05/12/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68117,79460,71859,PRETRIAL,Farquharson,Amanda,NULL,Female,African-American,11/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,Copy,1,0 +68117,79460,71859,PRETRIAL,Farquharson,Amanda,NULL,Female,African-American,11/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-1.55,2,Low,Copy,1,0 +68117,79460,71859,PRETRIAL,Farquharson,Amanda,NULL,Female,African-American,11/02/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,Copy,1,0 +68437,79469,71870,PRETRIAL,LEE,TRAVIS,NULL,Male,African-American,08/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/19/14 0:00,2,Medium,7,Risk of Violence,-1.86,5,Medium,New,1,0 +68437,79469,71870,PRETRIAL,LEE,TRAVIS,NULL,Male,African-American,08/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/19/14 0:00,2,Medium,8,Risk of Recidivism,-0.25,6,Medium,New,1,0 +68437,79469,71870,PRETRIAL,LEE,TRAVIS,NULL,Male,African-American,08/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/19/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68413,79448,71853,PRETRIAL,Shepard,Jermaine,NULL,Male,African-American,04/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,7,Risk of Violence,-3.33,1,Low,New,1,0 +68413,79448,71853,PRETRIAL,Shepard,Jermaine,NULL,Male,African-American,04/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,8,Risk of Recidivism,-1.93,1,Low,New,1,0 +68413,79448,71853,PRETRIAL,Shepard,Jermaine,NULL,Male,African-American,04/15/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/19/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68433,79465,71866,PRETRIAL,Marshall,Olivia,NULL,Female,Caucasian,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/19/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.2,4,Low,New,1,0 +68433,79465,71866,PRETRIAL,Marshall,Olivia,NULL,Female,Caucasian,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/19/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,9,High,New,1,0 +68433,79465,71866,PRETRIAL,Marshall,Olivia,NULL,Female,Caucasian,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/19/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,25,7,Medium,New,1,0 +68442,79474,71875,PRETRIAL,BROWN,WESLEY,NULL,Male,African-American,09/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +68442,79474,71875,PRETRIAL,BROWN,WESLEY,NULL,Male,African-American,09/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,1,Low,8,Risk of Recidivism,-0.84,3,Low,New,1,0 +68442,79474,71875,PRETRIAL,BROWN,WESLEY,NULL,Male,African-American,09/14/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68444,79476,71877,PRETRIAL,Frith,Charles,NULL,Male,African-American,09/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/20/14 0:00,4,High,7,Risk of Violence,0.04,10,High,New,1,0 +68444,79476,71877,PRETRIAL,Frith,Charles,NULL,Male,African-American,09/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/20/14 0:00,4,High,8,Risk of Recidivism,0.46,9,High,New,1,0 +68444,79476,71877,PRETRIAL,Frith,Charles,NULL,Male,African-American,09/18/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/20/14 0:00,4,High,18,Risk of Failure to Appear,40,10,High,New,1,0 +68447,79479,71880,PRETRIAL,Jones,Brandon,NULL,Male,African-American,08/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/20/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +68447,79479,71880,PRETRIAL,Jones,Brandon,NULL,Male,African-American,08/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/20/14 0:00,1,Low,8,Risk of Recidivism,-1.97,1,Low,New,1,0 +68447,79479,71880,PRETRIAL,Jones,Brandon,NULL,Male,African-American,08/05/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/20/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68439,79471,71872,PRETRIAL,Torresmarrero,Osbel,NULL,Male,Hispanic,02/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +68439,79471,71872,PRETRIAL,Torresmarrero,Osbel,NULL,Male,Hispanic,02/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,1,Low,8,Risk of Recidivism,-1.41,1,Low,New,1,0 +68439,79471,71872,PRETRIAL,Torresmarrero,Osbel,NULL,Male,Hispanic,02/28/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68445,79477,71878,PRETRIAL,Moody,Robert,Milt,Male,Caucasian,03/07/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/20/14 0:00,1,Low,7,Risk of Violence,-4.04,1,Low,New,1,0 +68445,79477,71878,PRETRIAL,Moody,Robert,Milt,Male,Caucasian,03/07/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/20/14 0:00,1,Low,8,Risk of Recidivism,-2.3,1,Low,New,1,0 +68445,79477,71878,PRETRIAL,Moody,Robert,Milt,Male,Caucasian,03/07/48,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/20/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68440,79472,71873,PRETRIAL,Gray,Derrick,Justin,Male,Caucasian,01/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +68440,79472,71873,PRETRIAL,Gray,Derrick,Justin,Male,Caucasian,01/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +68440,79472,71873,PRETRIAL,Gray,Derrick,Justin,Male,Caucasian,01/26/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68443,79475,71876,PRETRIAL,Ferch,Molly,Marie,Female,Caucasian,08/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/20/14 0:00,1,Low,7,Risk of Violence,-2,4,Low,New,1,0 +68443,79475,71876,PRETRIAL,Ferch,Molly,Marie,Female,Caucasian,08/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/20/14 0:00,1,Low,8,Risk of Recidivism,-0.95,4,Low,New,1,0 +68443,79475,71876,PRETRIAL,Ferch,Molly,Marie,Female,Caucasian,08/03/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/20/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68441,79473,71874,PRETRIAL,Williams,Alexander,NULL,Male,African-American,01/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,1,Low,7,Risk of Violence,-2.49,3,Low,New,1,0 +68441,79473,71874,PRETRIAL,Williams,Alexander,NULL,Male,African-American,01/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,1,Low,8,Risk of Recidivism,-0.85,3,Low,New,1,0 +68441,79473,71874,PRETRIAL,Williams,Alexander,NULL,Male,African-American,01/16/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,1,Low,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +68446,79478,71879,PRETRIAL,Garrison,Amanda,Brooke,Female,Caucasian,06/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,2,Medium,7,Risk of Violence,-2.69,2,Low,New,1,0 +68446,79478,71879,PRETRIAL,Garrison,Amanda,Brooke,Female,Caucasian,06/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +68446,79478,71879,PRETRIAL,Garrison,Amanda,Brooke,Female,Caucasian,06/05/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/20/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +9707,9881,9233,PRETRIAL,lerkins,derek,duane,Male,Hispanic,12/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.52,6,Medium,New,1,0 +9707,9881,9233,PRETRIAL,lerkins,derek,duane,Male,Hispanic,12/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.7,10,High,New,1,0 +9707,9881,9233,PRETRIAL,lerkins,derek,duane,Male,Hispanic,12/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68450,79482,71883,PRETRIAL,ROBLEJO,LATONYA,NULL,Female,African-American,12/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/21/14 0:00,1,Low,7,Risk of Violence,-3.22,1,Low,New,1,0 +68450,79482,71883,PRETRIAL,ROBLEJO,LATONYA,NULL,Female,African-American,12/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/21/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +68450,79482,71883,PRETRIAL,ROBLEJO,LATONYA,NULL,Female,African-American,12/10/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/21/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68453,79487,71887,PRETRIAL,SHIRDEL,ROSLYN,HARRIET,Female,Caucasian,10/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +68453,79487,71887,PRETRIAL,SHIRDEL,ROSLYN,HARRIET,Female,Caucasian,10/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/14 0:00,1,Low,8,Risk of Recidivism,-1.67,1,Low,New,1,0 +68453,79487,71887,PRETRIAL,SHIRDEL,ROSLYN,HARRIET,Female,Caucasian,10/08/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68456,79493,71890,PRETRIAL,Cabral,David,NULL,Male,African-American,06/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/21/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +68456,79493,71890,PRETRIAL,Cabral,David,NULL,Male,African-American,06/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/21/14 0:00,1,Low,8,Risk of Recidivism,-0.88,3,Low,New,1,0 +68456,79493,71890,PRETRIAL,Cabral,David,NULL,Male,African-American,06/20/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/21/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68448,79480,71881,PRETRIAL,Shaw,Paulette,NULL,Female,Caucasian,09/09/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/21/14 0:00,1,Low,7,Risk of Violence,-3.88,1,Low,New,1,0 +68448,79480,71881,PRETRIAL,Shaw,Paulette,NULL,Female,Caucasian,09/09/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/21/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +68448,79480,71881,PRETRIAL,Shaw,Paulette,NULL,Female,Caucasian,09/09/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +9707,79491,9233,PRETRIAL,lerkins,derek,duane,Male,Hispanic,12/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.76,5,Medium,Copy,1,0 +9707,79491,9233,PRETRIAL,lerkins,derek,duane,Male,Hispanic,12/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.58,9,High,Copy,1,0 +9707,79491,9233,PRETRIAL,lerkins,derek,duane,Male,Hispanic,12/10/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,Copy,1,0 +68451,79485,71885,PRETRIAL,Vicenty,Megan,NULL,Female,African-American,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/14 0:00,1,Low,7,Risk of Violence,-2.16,4,Low,New,1,0 +68451,79485,71885,PRETRIAL,Vicenty,Megan,NULL,Female,African-American,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/14 0:00,1,Low,8,Risk of Recidivism,-1.14,3,Low,New,1,0 +68451,79485,71885,PRETRIAL,Vicenty,Megan,NULL,Female,African-American,08/13/93,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +14367,79484,71884,PRETRIAL,Bryan,Kevin,NULL,Male,African-American,01/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,1,Low,7,Risk of Violence,-2.21,4,Low,New,1,0 +14367,79484,71884,PRETRIAL,Bryan,Kevin,NULL,Male,African-American,01/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,1,Low,8,Risk of Recidivism,-0.83,3,Low,New,1,0 +14367,79484,71884,PRETRIAL,Bryan,Kevin,NULL,Male,African-American,01/05/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +9059,9190,8591,PRETRIAL,BURKS,RAYMOND,LEE,Male,Caucasian,09/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,2,Medium,7,Risk of Violence,-1.51,6,Medium,New,1,0 +9059,9190,8591,PRETRIAL,BURKS,RAYMOND,LEE,Male,Caucasian,09/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,2,Medium,8,Risk of Recidivism,-0.79,3,Low,New,1,0 +9059,9190,8591,PRETRIAL,BURKS,RAYMOND,LEE,Male,Caucasian,09/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68454,79489,71888,PRETRIAL,Clark,Anthony,Lee,Male,African-American,08/24/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/14 0:00,1,Low,7,Risk of Violence,-3.44,1,Low,New,1,0 +68454,79489,71888,PRETRIAL,Clark,Anthony,Lee,Male,African-American,08/24/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +68454,79489,71888,PRETRIAL,Clark,Anthony,Lee,Male,African-American,08/24/59,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/21/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +68455,79492,71889,PRETRIAL,Vilbrun,Gaspard,NULL,Male,African-American,12/23/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/21/14 0:00,1,Low,7,Risk of Violence,-3.35,1,Low,New,1,0 +68455,79492,71889,PRETRIAL,Vilbrun,Gaspard,NULL,Male,African-American,12/23/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/21/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +68455,79492,71889,PRETRIAL,Vilbrun,Gaspard,NULL,Male,African-American,12/23/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +5121,79488,4800,PRETRIAL,GALLANDER,MICHELE,L,Female,Caucasian,07/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.85,5,Medium,Copy,1,0 +5121,79488,4800,PRETRIAL,GALLANDER,MICHELE,L,Female,Caucasian,07/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.98,10,High,Copy,1,0 +5121,79488,4800,PRETRIAL,GALLANDER,MICHELE,L,Female,Caucasian,07/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,9,High,Copy,1,0 +68449,79481,71882,PRETRIAL,DESPINASSE,KESNEL,NULL,Male,African-American,02/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +68449,79481,71882,PRETRIAL,DESPINASSE,KESNEL,NULL,Male,African-American,02/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,1,Low,8,Risk of Recidivism,-1.34,2,Low,New,1,0 +68449,79481,71882,PRETRIAL,DESPINASSE,KESNEL,NULL,Male,African-American,02/20/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +9059,79490,8591,PRETRIAL,BURKS,RAYMOND,LEE,Male,Caucasian,09/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +9059,79490,8591,PRETRIAL,BURKS,RAYMOND,LEE,Male,Caucasian,09/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,Copy,1,0 +9059,79490,8591,PRETRIAL,BURKS,RAYMOND,LEE,Male,Caucasian,09/26/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +68452,79486,71886,PRETRIAL,Aldio,Michael,NULL,Male,African-American,06/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +68452,79486,71886,PRETRIAL,Aldio,Michael,NULL,Male,African-American,06/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,New,1,0 +68452,79486,71886,PRETRIAL,Aldio,Michael,NULL,Male,African-American,06/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/21/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +16719,79504,16020,PRETRIAL,Guelce,Ralph,NULL,Male,Other,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.99,4,Low,Copy,1,0 +16719,79504,16020,PRETRIAL,Guelce,Ralph,NULL,Male,Other,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,8,High,Copy,1,0 +16719,79504,16020,PRETRIAL,Guelce,Ralph,NULL,Male,Other,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +68470,79511,71905,PRETRIAL,BATES,OFARRAH,NULL,Female,African-American,08/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-2.89,2,Low,New,1,0 +68470,79511,71905,PRETRIAL,BATES,OFARRAH,NULL,Female,African-American,08/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-1.51,2,Low,New,1,0 +68470,79511,71905,PRETRIAL,BATES,OFARRAH,NULL,Female,African-American,08/28/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68467,79507,71901,Probation,SOLOVYOV,SERGIY,NULL,Male,Caucasian,12/10/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,12/22/14 0:00,1,Low,7,Risk of Violence,-4.23,1,Low,New,1,0 +68467,79507,71901,Probation,SOLOVYOV,SERGIY,NULL,Male,Caucasian,12/10/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,12/22/14 0:00,1,Low,8,Risk of Recidivism,-2.58,1,Low,New,1,0 +68467,79507,71901,Probation,SOLOVYOV,SERGIY,NULL,Male,Caucasian,12/10/55,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Widowed,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68474,79516,71910,PRETRIAL,FARANDA,MATTHEW,DEAN,Male,Caucasian,01/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-2.9,2,Low,New,1,0 +68474,79516,71910,PRETRIAL,FARANDA,MATTHEW,DEAN,Male,Caucasian,01/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-1.14,2,Low,New,1,0 +68474,79516,71910,PRETRIAL,FARANDA,MATTHEW,DEAN,Male,Caucasian,01/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68458,79495,71892,PRETRIAL,RODRIGUEZ,KIMBERLY,LEE,Female,Hispanic,09/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-2.48,3,Low,New,1,0 +68458,79495,71892,PRETRIAL,RODRIGUEZ,KIMBERLY,LEE,Female,Hispanic,09/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-1.11,3,Low,New,1,0 +68458,79495,71892,PRETRIAL,RODRIGUEZ,KIMBERLY,LEE,Female,Hispanic,09/24/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +65711,79502,68873,PRETRIAL,guess,samuel,NULL,Male,African-American,06/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/22/14 0:00,1,Low,7,Risk of Violence,-3.4,1,Low,Copy,1,0 +65711,79502,68873,PRETRIAL,guess,samuel,NULL,Male,African-American,06/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/22/14 0:00,1,Low,8,Risk of Recidivism,-1.15,2,Low,Copy,1,0 +65711,79502,68873,PRETRIAL,guess,samuel,NULL,Male,African-American,06/28/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +68468,79509,71903,PRETRIAL,Cabrera,Alejandrina,NULL,Female,Hispanic,07/18/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/22/14 0:00,1,Low,7,Risk of Violence,-3.96,1,Low,New,1,0 +68468,79509,71903,PRETRIAL,Cabrera,Alejandrina,NULL,Female,Hispanic,07/18/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/22/14 0:00,1,Low,8,Risk of Recidivism,-2.31,1,Low,New,1,0 +68468,79509,71903,PRETRIAL,Cabrera,Alejandrina,NULL,Female,Hispanic,07/18/54,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68471,79513,71907,Probation,Stathakis,Christopher,NULL,Male,Caucasian,01/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-2.14,4,Low,New,1,0 +68471,79513,71907,Probation,Stathakis,Christopher,NULL,Male,Caucasian,01/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +68471,79513,71907,Probation,Stathakis,Christopher,NULL,Male,Caucasian,01/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68463,79500,71897,PRETRIAL,WAITE,RANIL,L,Male,African-American,06/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-2.41,3,Low,New,1,0 +68463,79500,71897,PRETRIAL,WAITE,RANIL,L,Male,African-American,06/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +68463,79500,71897,PRETRIAL,WAITE,RANIL,L,Male,African-American,06/08/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68460,79497,71894,PRETRIAL,SANTOSO,DON,BERNANDI,Male,Asian,12/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/22/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +68460,79497,71894,PRETRIAL,SANTOSO,DON,BERNANDI,Male,Asian,12/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/22/14 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +68460,79497,71894,PRETRIAL,SANTOSO,DON,BERNANDI,Male,Asian,12/09/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68465,79505,71899,PRETRIAL,salama,Yihad,NULL,Male,Caucasian,03/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-2.44,3,Low,New,1,0 +68465,79505,71899,PRETRIAL,salama,Yihad,NULL,Male,Caucasian,03/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +68465,79505,71899,PRETRIAL,salama,Yihad,NULL,Male,Caucasian,03/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68469,79510,71904,PRETRIAL,Ross,James,NULL,Male,Caucasian,05/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-3.62,1,Low,New,1,0 +68469,79510,71904,PRETRIAL,Ross,James,NULL,Male,Caucasian,05/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +68469,79510,71904,PRETRIAL,Ross,James,NULL,Male,Caucasian,05/13/75,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68461,79498,71895,PRETRIAL,GOMEZ,GERARDO,NULL,Male,Caucasian,04/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +68461,79498,71895,PRETRIAL,GOMEZ,GERARDO,NULL,Male,Caucasian,04/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-1.35,2,Low,New,1,0 +68461,79498,71895,PRETRIAL,GOMEZ,GERARDO,NULL,Male,Caucasian,04/15/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68464,79501,71898,PRETRIAL,Holder,Asmond,NULL,Male,African-American,01/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +68464,79501,71898,PRETRIAL,Holder,Asmond,NULL,Male,African-American,01/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-0.33,5,Medium,New,1,0 +68464,79501,71898,PRETRIAL,Holder,Asmond,NULL,Male,African-American,01/27/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68472,79514,71908,PRETRIAL,Ward,Coretta,NULL,Female,African-American,12/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-3.67,1,Low,New,1,0 +68472,79514,71908,PRETRIAL,Ward,Coretta,NULL,Female,African-American,12/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-2.17,1,Low,New,1,0 +68472,79514,71908,PRETRIAL,Ward,Coretta,NULL,Female,African-American,12/14/73,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68457,79494,71891,PRETRIAL,Black,Marcel,NULL,Male,Caucasian,08/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +68457,79494,71891,PRETRIAL,Black,Marcel,NULL,Male,Caucasian,08/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +68457,79494,71891,PRETRIAL,Black,Marcel,NULL,Male,Caucasian,08/31/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68459,79496,71893,PRETRIAL,WILLIAMSON,GARY,THOMAS,Male,Caucasian,05/12/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-4.07,1,Low,New,1,0 +68459,79496,71893,PRETRIAL,WILLIAMSON,GARY,THOMAS,Male,Caucasian,05/12/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-2.19,1,Low,New,1,0 +68459,79496,71893,PRETRIAL,WILLIAMSON,GARY,THOMAS,Male,Caucasian,05/12/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68462,79499,71896,PRETRIAL,Rocher,Billy,NULL,Male,African-American,08/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-2.58,2,Low,New,1,0 +68462,79499,71896,PRETRIAL,Rocher,Billy,NULL,Male,African-American,08/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-0.95,3,Low,New,1,0 +68462,79499,71896,PRETRIAL,Rocher,Billy,NULL,Male,African-American,08/27/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +16719,79503,16020,PRETRIAL,Guelce,Ralph,NULL,Male,Other,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,7,Risk of Violence,-2.1,4,Low,Copy,1,0 +16719,79503,16020,PRETRIAL,Guelce,Ralph,NULL,Male,Other,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,8,Risk of Recidivism,-1,-1,N/A,Copy,1,0 +16719,79503,16020,PRETRIAL,Guelce,Ralph,NULL,Male,Other,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/22/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +18110,79512,71906,PRETRIAL,FAHEY,MATTHEW,NULL,Male,Caucasian,07/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,2,Medium,7,Risk of Violence,-1.99,4,Low,New,1,0 +18110,79512,71906,PRETRIAL,FAHEY,MATTHEW,NULL,Male,Caucasian,07/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +18110,79512,71906,PRETRIAL,FAHEY,MATTHEW,NULL,Male,Caucasian,07/03/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/22/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68488,79533,71925,PRETRIAL,FRANCOIS,ELIUS,NULL,Male,Native American,03/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/23/14 0:00,1,Low,7,Risk of Violence,-3.03,1,Low,New,1,0 +68488,79533,71925,PRETRIAL,FRANCOIS,ELIUS,NULL,Male,Native American,03/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/23/14 0:00,1,Low,8,Risk of Recidivism,-2.43,1,Low,New,1,0 +68488,79533,71925,PRETRIAL,FRANCOIS,ELIUS,NULL,Male,Native American,03/05/70,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68484,79529,71921,PRETRIAL,HINES,ANIKA,NULL,Female,African-American,08/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,1,Low,7,Risk of Violence,-1.92,5,Medium,New,1,0 +68484,79529,71921,PRETRIAL,HINES,ANIKA,NULL,Female,African-American,08/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +68484,79529,71921,PRETRIAL,HINES,ANIKA,NULL,Female,African-American,08/18/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68479,79524,71916,PRETRIAL,Bunce,Ramelo,NULL,Male,African-American,12/12/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,2,Medium,7,Risk of Violence,-1.33,7,Medium,New,1,0 +68479,79524,71916,PRETRIAL,Bunce,Ramelo,NULL,Male,African-American,12/12/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.58,4,Low,New,1,0 +68479,79524,71916,PRETRIAL,Bunce,Ramelo,NULL,Male,African-American,12/12/96,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68490,79535,71927,Probation,Zaki,Rami,NULL,Male,Caucasian,11/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/23/14 0:00,1,Low,7,Risk of Violence,-2.91,2,Low,New,1,0 +68490,79535,71927,Probation,Zaki,Rami,NULL,Male,Caucasian,11/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/23/14 0:00,1,Low,8,Risk of Recidivism,-1.26,2,Low,New,1,0 +68490,79535,71927,Probation,Zaki,Rami,NULL,Male,Caucasian,11/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Divorced,12/23/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +33118,79522,71915,PRETRIAL,DUMASSAIS,JUNIOR,NULL,Male,African-American,06/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +33118,79522,71915,PRETRIAL,DUMASSAIS,JUNIOR,NULL,Male,African-American,06/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +33118,79522,71915,PRETRIAL,DUMASSAIS,JUNIOR,NULL,Male,African-American,06/04/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68476,79519,71912,PRETRIAL,WARD,SHANDRICA,SHENANE,Female,African-American,10/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,New,1,0 +68476,79519,71912,PRETRIAL,WARD,SHANDRICA,SHENANE,Female,African-American,10/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,6,Medium,New,1,0 +68476,79519,71912,PRETRIAL,WARD,SHANDRICA,SHENANE,Female,African-American,10/14/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,2,Medium,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68482,79527,71919,PRETRIAL,Demeo,Mark,A,Male,Caucasian,08/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,1,Low,7,Risk of Violence,-3.15,1,Low,New,1,0 +68482,79527,71919,PRETRIAL,Demeo,Mark,A,Male,Caucasian,08/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,1,Low,8,Risk of Recidivism,-1.19,2,Low,New,1,0 +68482,79527,71919,PRETRIAL,Demeo,Mark,A,Male,Caucasian,08/13/76,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +67980,79518,71411,PRETRIAL,Sanchez-Rodriguez,Jonathan,NULL,Male,Hispanic,07/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/23/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.4,7,Medium,Copy,1,0 +67980,79518,71411,PRETRIAL,Sanchez-Rodriguez,Jonathan,NULL,Male,Hispanic,07/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/23/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,Copy,1,0 +67980,79518,71411,PRETRIAL,Sanchez-Rodriguez,Jonathan,NULL,Male,Hispanic,07/07/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/23/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,22,5,Medium,Copy,1,0 +68491,79536,71928,PRETRIAL,MORGAN,NATHANIEL,NULL,Male,African-American,11/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/14 0:00,1,Low,7,Risk of Violence,-2.51,3,Low,New,1,0 +68491,79536,71928,PRETRIAL,MORGAN,NATHANIEL,NULL,Male,African-American,11/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/14 0:00,1,Low,8,Risk of Recidivism,-0.55,4,Low,New,1,0 +68491,79536,71928,PRETRIAL,MORGAN,NATHANIEL,NULL,Male,African-American,11/29/90,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68478,79521,71914,PRETRIAL,HERNANDEZ,ROBINSON,D,Male,Caucasian,04/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/23/14 0:00,1,Low,7,Risk of Violence,-3.24,1,Low,New,1,0 +68478,79521,71914,PRETRIAL,HERNANDEZ,ROBINSON,D,Male,Caucasian,04/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/23/14 0:00,1,Low,8,Risk of Recidivism,-1.38,2,Low,New,1,0 +68478,79521,71914,PRETRIAL,HERNANDEZ,ROBINSON,D,Male,Caucasian,04/27/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/23/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +68483,79528,71920,PRETRIAL,Martinezreyes,Rafael,NULL,Male,Hispanic,08/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/23/14 0:00,1,Low,7,Risk of Violence,-2.93,2,Low,New,1,0 +68483,79528,71920,PRETRIAL,Martinezreyes,Rafael,NULL,Male,Hispanic,08/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/23/14 0:00,1,Low,8,Risk of Recidivism,-0.76,3,Low,New,1,0 +68483,79528,71920,PRETRIAL,Martinezreyes,Rafael,NULL,Male,Hispanic,08/06/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/23/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68477,79520,71913,PRETRIAL,Brown,Edwin,NULL,Male,Hispanic,03/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/14 0:00,1,Low,7,Risk of Violence,-2.81,2,Low,New,1,0 +68477,79520,71913,PRETRIAL,Brown,Edwin,NULL,Male,Hispanic,03/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +68477,79520,71913,PRETRIAL,Brown,Edwin,NULL,Male,Hispanic,03/27/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +21705,79523,55819,PRETRIAL,TERRY,JAMAR,NULL,Male,African-American,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,4,High,7,Risk of Violence,-0.88,9,High,Copy,1,0 +21705,79523,55819,PRETRIAL,TERRY,JAMAR,NULL,Male,African-American,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,4,High,8,Risk of Recidivism,0.95,10,High,Copy,1,0 +21705,79523,55819,PRETRIAL,TERRY,JAMAR,NULL,Male,African-American,08/30/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,4,High,18,Risk of Failure to Appear,20,3,Low,Copy,1,0 +68487,79532,71924,PRETRIAL,Charles,Yvecken,NULL,Male,Other,10/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/14 0:00,1,Low,7,Risk of Violence,-2.26,3,Low,New,1,0 +68487,79532,71924,PRETRIAL,Charles,Yvecken,NULL,Male,Other,10/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +68487,79532,71924,PRETRIAL,Charles,Yvecken,NULL,Male,Other,10/01/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/23/14 0:00,1,Low,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68485,79530,71922,PRETRIAL,ISALE,ZOLYA,NULL,Female,African-American,11/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,2,Medium,7,Risk of Violence,-1.96,5,Medium,New,1,0 +68485,79530,71922,PRETRIAL,ISALE,ZOLYA,NULL,Female,African-American,11/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,7,Medium,New,1,0 +68485,79530,71922,PRETRIAL,ISALE,ZOLYA,NULL,Female,African-American,11/13/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68492,79537,71929,PRETRIAL,Trueblood,Christina,NULL,Female,Caucasian,11/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,1,Low,7,Risk of Violence,-2.34,3,Low,New,1,0 +68492,79537,71929,PRETRIAL,Trueblood,Christina,NULL,Female,Caucasian,11/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,1,Low,8,Risk of Recidivism,-1.31,2,Low,New,1,0 +68492,79537,71929,PRETRIAL,Trueblood,Christina,NULL,Female,Caucasian,11/24/79,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68480,79525,71917,PRETRIAL,ROBERTS,DARRELL,DEAN,Male,African-American,05/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,1,Low,7,Risk of Violence,-2.68,2,Low,New,1,0 +68480,79525,71917,PRETRIAL,ROBERTS,DARRELL,DEAN,Male,African-American,05/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,1,Low,8,Risk of Recidivism,-1.12,2,Low,New,1,0 +68480,79525,71917,PRETRIAL,ROBERTS,DARRELL,DEAN,Male,African-American,05/01/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/23/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68500,79546,71937,PRETRIAL,Mansell,Christian,NULL,Male,Caucasian,03/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,2,Medium,7,Risk of Violence,-2.89,2,Low,New,1,0 +68500,79546,71937,PRETRIAL,Mansell,Christian,NULL,Male,Caucasian,03/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,New,1,0 +68500,79546,71937,PRETRIAL,Mansell,Christian,NULL,Male,Caucasian,03/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,2,Medium,18,Risk of Failure to Appear,18,3,Low,New,1,0 +8393,49768,45374,PRETRIAL,MCDANIEL,MICHAEL,S,Male,Hispanic,05/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.19,4,Low,New,1,0 +8393,49768,45374,PRETRIAL,MCDANIEL,MICHAEL,S,Male,Hispanic,05/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +8393,49768,45374,PRETRIAL,MCDANIEL,MICHAEL,S,Male,Hispanic,05/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68503,79551,71941,PRETRIAL,Ordonez,Chester,Alexander,Male,Caucasian,06/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,7,Risk of Violence,-2.55,3,Low,New,1,0 +68503,79551,71941,PRETRIAL,Ordonez,Chester,Alexander,Male,Caucasian,06/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,8,Risk of Recidivism,-1.33,2,Low,New,1,0 +68503,79551,71941,PRETRIAL,Ordonez,Chester,Alexander,Male,Caucasian,06/08/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68495,79541,71932,PRETRIAL,UBANKS,JEFFREY,NULL,Male,African-American,12/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,2,Medium,7,Risk of Violence,-1.68,6,Medium,New,1,0 +68495,79541,71932,PRETRIAL,UBANKS,JEFFREY,NULL,Male,African-American,12/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,2,Medium,8,Risk of Recidivism,-0.35,5,Medium,New,1,0 +68495,79541,71932,PRETRIAL,UBANKS,JEFFREY,NULL,Male,African-American,12/21/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68496,79542,71933,PRETRIAL,Holder,Sean,Paul,Male,African-American,10/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,4,High,7,Risk of Violence,-1.12,8,High,New,1,0 +68496,79542,71933,PRETRIAL,Holder,Sean,Paul,Male,African-American,10/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,4,High,8,Risk of Recidivism,0.47,9,High,New,1,0 +68496,79542,71933,PRETRIAL,Holder,Sean,Paul,Male,African-American,10/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68502,79549,71939,PRETRIAL,SARGENT,MELISSA,NULL,Female,African-American,11/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,7,Risk of Violence,-2.46,3,Low,New,1,0 +68502,79549,71939,PRETRIAL,SARGENT,MELISSA,NULL,Female,African-American,11/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +68502,79549,71939,PRETRIAL,SARGENT,MELISSA,NULL,Female,African-American,11/11/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68493,79539,71930,PRETRIAL,Williams,Aaron,NULL,Male,African-American,11/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.04,4,Low,New,1,0 +68493,79539,71930,PRETRIAL,Williams,Aaron,NULL,Male,African-American,11/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.65,10,High,New,1,0 +68493,79539,71930,PRETRIAL,Williams,Aaron,NULL,Male,African-American,11/01/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68498,79544,71935,PRETRIAL,Brown,Jarrod,NULL,Male,African-American,12/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,7,Risk of Violence,-2.56,2,Low,New,1,0 +68498,79544,71935,PRETRIAL,Brown,Jarrod,NULL,Male,African-American,12/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,8,Risk of Recidivism,-1.21,2,Low,New,1,0 +68498,79544,71935,PRETRIAL,Brown,Jarrod,NULL,Male,African-American,12/05/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68497,79543,71934,PRETRIAL,Clark,Thomas,NULL,Male,African-American,11/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,2,Medium,7,Risk of Violence,-2.4,3,Low,New,1,0 +68497,79543,71934,PRETRIAL,Clark,Thomas,NULL,Male,African-American,11/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,New,1,0 +68497,79543,71934,PRETRIAL,Clark,Thomas,NULL,Male,African-American,11/29/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68494,79540,71931,PRETRIAL,JOHNSTON,DAUDET,NULL,Male,Caucasian,12/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,7,Risk of Violence,-2.65,2,Low,New,1,0 +68494,79540,71931,PRETRIAL,JOHNSTON,DAUDET,NULL,Male,Caucasian,12/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +68494,79540,71931,PRETRIAL,JOHNSTON,DAUDET,NULL,Male,Caucasian,12/01/58,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +2746,43180,39488,PRETRIAL,HARDING,EDWARD,LEE,Male,African-American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,4,High,7,Risk of Violence,-0.44,10,High,New,1,0 +2746,43180,39488,PRETRIAL,HARDING,EDWARD,LEE,Male,African-American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,4,High,8,Risk of Recidivism,1.55,10,High,New,1,0 +2746,43180,39488,PRETRIAL,HARDING,EDWARD,LEE,Male,African-American,03/11/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,4,High,18,Risk of Failure to Appear,25,6,Medium,New,1,0 +8393,79548,45374,PRETRIAL,MCDANIEL,MICHAEL,S,Male,Hispanic,05/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.44,3,Low,Copy,1,0 +8393,79548,45374,PRETRIAL,MCDANIEL,MICHAEL,S,Male,Hispanic,05/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.22,8,High,Copy,1,0 +8393,79548,45374,PRETRIAL,MCDANIEL,MICHAEL,S,Male,Hispanic,05/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +4697,79538,4387,PRETRIAL,Miller,Darrell,Bernard,Male,African-American,03/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,Copy,1,0 +4697,79538,4387,PRETRIAL,Miller,Darrell,Bernard,Male,African-American,03/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,Copy,1,0 +4697,79538,4387,PRETRIAL,Miller,Darrell,Bernard,Male,African-American,03/29/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +68499,79545,71936,PRETRIAL,Martin,Ivory,NULL,Male,African-American,04/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +68499,79545,71936,PRETRIAL,Martin,Ivory,NULL,Male,African-American,04/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,8,Risk of Recidivism,-1.01,2,Low,New,1,0 +68499,79545,71936,PRETRIAL,Martin,Ivory,NULL,Male,African-American,04/26/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/24/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +15726,79552,15049,PRETRIAL,HEWITT,HORACE,NULL,Male,African-American,12/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/24/14 0:00,1,Low,7,Risk of Violence,-2.04,4,Low,Copy,1,0 +15726,79552,15049,PRETRIAL,HEWITT,HORACE,NULL,Male,African-American,12/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/24/14 0:00,1,Low,8,Risk of Recidivism,-0.64,4,Low,Copy,1,0 +15726,79552,15049,PRETRIAL,HEWITT,HORACE,NULL,Male,African-American,12/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/24/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +15726,16225,15049,PRETRIAL,HEWITT,HORACE,NULL,Male,African-American,12/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/24/14 0:00,1,Low,7,Risk of Violence,-2.03,4,Low,New,1,0 +15726,16225,15049,PRETRIAL,HEWITT,HORACE,NULL,Male,African-American,12/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/24/14 0:00,1,Low,8,Risk of Recidivism,-0.47,5,Medium,New,1,0 +15726,16225,15049,PRETRIAL,HEWITT,HORACE,NULL,Male,African-American,12/16/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/24/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68505,79554,71943,PRETRIAL,Vargas,Mannix,NULL,Male,Caucasian,05/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,7,Risk of Violence,-3.06,1,Low,New,1,0 +68505,79554,71943,PRETRIAL,Vargas,Mannix,NULL,Male,Caucasian,05/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,8,Risk of Recidivism,-1.53,1,Low,New,1,0 +68505,79554,71943,PRETRIAL,Vargas,Mannix,NULL,Male,Caucasian,05/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68509,79559,71947,PRETRIAL,Johnson,Marc,NULL,Male,Caucasian,04/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,7,Risk of Violence,-2.61,2,Low,New,1,0 +68509,79559,71947,PRETRIAL,Johnson,Marc,NULL,Male,Caucasian,04/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,8,Risk of Recidivism,-0.63,4,Low,New,1,0 +68509,79559,71947,PRETRIAL,Johnson,Marc,NULL,Male,Caucasian,04/28/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68511,79561,71949,PRETRIAL,Jimenez,Gerinaldo,NULL,Male,Caucasian,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,7,Risk of Violence,-2.32,3,Low,New,1,0 +68511,79561,71949,PRETRIAL,Jimenez,Gerinaldo,NULL,Male,Caucasian,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,8,Risk of Recidivism,-0.57,4,Low,New,1,0 +68511,79561,71949,PRETRIAL,Jimenez,Gerinaldo,NULL,Male,Caucasian,12/03/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68506,79556,71944,PRETRIAL,Turner,Tahir,Kareem,Male,African-American,02/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,2,Medium,7,Risk of Violence,-1.88,5,Medium,New,1,0 +68506,79556,71944,PRETRIAL,Turner,Tahir,Kareem,Male,African-American,02/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.23,6,Medium,New,1,0 +68506,79556,71944,PRETRIAL,Turner,Tahir,Kareem,Male,African-American,02/10/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68507,79557,71945,PRETRIAL,Ford,Deon,Deontae,Male,African-American,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,2,Medium,7,Risk of Violence,-1.62,6,Medium,New,1,0 +68507,79557,71945,PRETRIAL,Ford,Deon,Deontae,Male,African-American,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.02,7,Medium,New,1,0 +68507,79557,71945,PRETRIAL,Ford,Deon,Deontae,Male,African-American,10/25/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +62172,79555,64826,Probation,Osceola,Jaime,Renee,Female,Native American,08/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,2,Medium,7,Risk of Violence,-2.91,2,Low,Copy,1,0 +62172,79555,64826,Probation,Osceola,Jaime,Renee,Female,Native American,08/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.41,6,Medium,Copy,1,0 +62172,79555,64826,Probation,Osceola,Jaime,Renee,Female,Native American,08/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,Copy,1,0 +68512,79562,71950,PRETRIAL,Carlo,Jenna,Marie,Female,Caucasian,07/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,2,Medium,7,Risk of Violence,-2.45,3,Low,New,1,0 +68512,79562,71950,PRETRIAL,Carlo,Jenna,Marie,Female,Caucasian,07/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,2,Medium,8,Risk of Recidivism,-0.54,6,Medium,New,1,0 +68512,79562,71950,PRETRIAL,Carlo,Jenna,Marie,Female,Caucasian,07/12/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68513,79563,71951,PRETRIAL,Leblanc,Christine,Faith,Female,Caucasian,12/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,7,Risk of Violence,-2.36,3,Low,New,1,0 +68513,79563,71951,PRETRIAL,Leblanc,Christine,Faith,Female,Caucasian,12/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,8,Risk of Recidivism,-0.77,5,Medium,New,1,0 +68513,79563,71951,PRETRIAL,Leblanc,Christine,Faith,Female,Caucasian,12/23/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68504,79553,71942,PRETRIAL,Gurley,Shawn,NULL,Male,African-American,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,7,Risk of Violence,-2.84,2,Low,New,1,0 +68504,79553,71942,PRETRIAL,Gurley,Shawn,NULL,Male,African-American,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,8,Risk of Recidivism,-1.5,1,Low,New,1,0 +68504,79553,71942,PRETRIAL,Gurley,Shawn,NULL,Male,African-American,09/04/86,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/25/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68508,79558,71946,PRETRIAL,Tilak,Ganeshwar,NULL,Male,Other,10/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/25/14 0:00,1,Low,7,Risk of Violence,-3.04,1,Low,New,1,0 +68508,79558,71946,PRETRIAL,Tilak,Ganeshwar,NULL,Male,Other,10/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/25/14 0:00,1,Low,8,Risk of Recidivism,-1.92,1,Low,New,1,0 +68508,79558,71946,PRETRIAL,Tilak,Ganeshwar,NULL,Male,Other,10/16/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/25/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68524,79576,71964,PRETRIAL,Ogren,Amber,NULL,Female,Caucasian,09/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/14 0:00,1,Low,7,Risk of Violence,-2.62,2,Low,New,1,0 +68524,79576,71964,PRETRIAL,Ogren,Amber,NULL,Female,Caucasian,09/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/14 0:00,1,Low,8,Risk of Recidivism,-0.79,5,Medium,New,1,0 +68524,79576,71964,PRETRIAL,Ogren,Amber,NULL,Female,Caucasian,09/17/77,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,18,3,Low,New,1,0 +7247,79572,71960,PRETRIAL,Duane,Kevin,Eldridge,Male,African-American,12/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,4,High,7,Risk of Violence,-1.25,8,High,New,1,0 +7247,79572,71960,PRETRIAL,Duane,Kevin,Eldridge,Male,African-American,12/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,4,High,8,Risk of Recidivism,0.36,9,High,New,1,0 +7247,79572,71960,PRETRIAL,Duane,Kevin,Eldridge,Male,African-American,12/29/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,4,High,18,Risk of Failure to Appear,42,10,High,New,1,0 +68527,79579,71967,PRETRIAL,Nardone,Joseph,John,Male,Caucasian,11/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +68527,79579,71967,PRETRIAL,Nardone,Joseph,John,Male,Caucasian,11/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.21,6,Medium,New,1,0 +68527,79579,71967,PRETRIAL,Nardone,Joseph,John,Male,Caucasian,11/07/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68516,79567,71955,PRETRIAL,Dinnall,Nichola,Marshanee,Female,Other,10/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,7,Risk of Violence,-2.95,1,Low,New,1,0 +68516,79567,71955,PRETRIAL,Dinnall,Nichola,Marshanee,Female,Other,10/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,8,Risk of Recidivism,-1.49,2,Low,New,1,0 +68516,79567,71955,PRETRIAL,Dinnall,Nichola,Marshanee,Female,Other,10/07/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68522,79574,71962,PRETRIAL,Powell,Fabian,Hakeen,Male,African-American,08/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/14 0:00,1,Low,7,Risk of Violence,-2.2,4,Low,New,1,0 +68522,79574,71962,PRETRIAL,Powell,Fabian,Hakeen,Male,African-American,08/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/14 0:00,1,Low,8,Risk of Recidivism,-0.97,3,Low,New,1,0 +68522,79574,71962,PRETRIAL,Powell,Fabian,Hakeen,Male,African-American,08/28/91,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68518,79570,71958,PRETRIAL,Smith,Edwin,NULL,Male,African-American,11/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,2,Medium,7,Risk of Violence,-2.68,2,Low,New,1,0 +68518,79570,71958,PRETRIAL,Smith,Edwin,NULL,Male,African-American,11/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +68518,79570,71958,PRETRIAL,Smith,Edwin,NULL,Male,African-American,11/19/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +40782,44224,40416,PRETRIAL,turner,james,NULL,Male,Caucasian,08/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.5,3,Low,New,1,0 +40782,44224,40416,PRETRIAL,turner,james,NULL,Male,Caucasian,08/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +40782,44224,40416,PRETRIAL,turner,james,NULL,Male,Caucasian,08/09/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +68529,79583,71969,PRETRIAL,Tue,Miguel,NULL,Male,Hispanic,07/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +68529,79583,71969,PRETRIAL,Tue,Miguel,NULL,Male,Hispanic,07/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,8,Risk of Recidivism,-0.96,3,Low,New,1,0 +68529,79583,71969,PRETRIAL,Tue,Miguel,NULL,Male,Hispanic,07/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +21210,22166,20385,Probation,Otero,David,NULL,Male,Hispanic,05/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,4,High,7,Risk of Violence,-0.76,9,High,New,1,0 +21210,22166,20385,Probation,Otero,David,NULL,Male,Hispanic,05/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,4,High,8,Risk of Recidivism,0.87,10,High,New,1,0 +21210,22166,20385,Probation,Otero,David,NULL,Male,Hispanic,05/14/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,4,High,18,Risk of Failure to Appear,33,9,High,New,1,0 +68526,79578,71966,PRETRIAL,Bennett,Anthony,NULL,Male,African-American,02/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/14 0:00,1,Low,7,Risk of Violence,-2.64,2,Low,New,1,0 +68526,79578,71966,PRETRIAL,Bennett,Anthony,NULL,Male,African-American,02/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/14 0:00,1,Low,8,Risk of Recidivism,-0.94,3,Low,New,1,0 +68526,79578,71966,PRETRIAL,Bennett,Anthony,NULL,Male,African-American,02/27/82,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68514,79565,71953,PRETRIAL,Sokol,Josh,NULL,Male,Caucasian,10/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,7,Risk of Violence,-2.99,1,Low,New,1,0 +68514,79565,71953,PRETRIAL,Sokol,Josh,NULL,Male,Caucasian,10/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,8,Risk of Recidivism,-1.65,1,Low,New,1,0 +68514,79565,71953,PRETRIAL,Sokol,Josh,NULL,Male,Caucasian,10/11/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68525,79577,71965,PRETRIAL,ROBINSON,RAYMOND,EVANDER,Male,African-American,12/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/26/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +68525,79577,71965,PRETRIAL,ROBINSON,RAYMOND,EVANDER,Male,African-American,12/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/26/14 0:00,1,Low,8,Risk of Recidivism,-1.74,1,Low,New,1,0 +68525,79577,71965,PRETRIAL,ROBINSON,RAYMOND,EVANDER,Male,African-American,12/04/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +34115,79564,71952,PRETRIAL,Austin,Eniee,NULL,Female,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,4,High,7,Risk of Violence,-0.19,10,High,New,1,0 +34115,79564,71952,PRETRIAL,Austin,Eniee,NULL,Female,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,4,High,8,Risk of Recidivism,0.46,10,High,New,1,0 +34115,79564,71952,PRETRIAL,Austin,Eniee,NULL,Female,African-American,05/01/90,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,4,High,18,Risk of Failure to Appear,31,9,High,New,1,0 +65314,79483,68401,PRETRIAL,HATCHER,LEON,ANTONIO,Male,African-American,01/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,Copy,1,0 +65314,79483,68401,PRETRIAL,HATCHER,LEON,ANTONIO,Male,African-American,01/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,2,Medium,8,Risk of Recidivism,0.01,7,Medium,Copy,1,0 +65314,79483,68401,PRETRIAL,HATCHER,LEON,ANTONIO,Male,African-American,01/08/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +45198,79582,45401,PRETRIAL,Griffies,Wayne,NULL,Male,Caucasian,10/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.6,2,Low,Copy,1,0 +45198,79582,45401,PRETRIAL,Griffies,Wayne,NULL,Male,Caucasian,10/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,Copy,1,0 +45198,79582,45401,PRETRIAL,Griffies,Wayne,NULL,Male,Caucasian,10/17/85,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/26/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +2251,79569,71957,PRETRIAL,MCCLOUD,ERNEST,TYRONE,Male,African-American,12/21/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,7,Risk of Violence,-2.96,1,Low,New,1,0 +2251,79569,71957,PRETRIAL,MCCLOUD,ERNEST,TYRONE,Male,African-American,12/21/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,8,Risk of Recidivism,-0.48,5,Medium,New,1,0 +2251,79569,71957,PRETRIAL,MCCLOUD,ERNEST,TYRONE,Male,African-American,12/21/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68521,79573,71961,PRETRIAL,McCall,Jearod,NULL,Male,African-American,07/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,7,Risk of Violence,-3.1,1,Low,New,1,0 +68521,79573,71961,PRETRIAL,McCall,Jearod,NULL,Male,African-American,07/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,8,Risk of Recidivism,-1.32,2,Low,New,1,0 +68521,79573,71961,PRETRIAL,McCall,Jearod,NULL,Male,African-American,07/22/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68515,79566,71954,PRETRIAL,Buendia,Mark,NULL,Male,Caucasian,02/12/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +68515,79566,71954,PRETRIAL,Buendia,Mark,NULL,Male,Caucasian,02/12/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +68515,79566,71954,PRETRIAL,Buendia,Mark,NULL,Male,Caucasian,02/12/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68517,79568,71956,PRETRIAL,Cromer,Roena,NULL,Female,African-American,08/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,7,Risk of Violence,-3.53,1,Low,New,1,0 +68517,79568,71956,PRETRIAL,Cromer,Roena,NULL,Female,African-American,08/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,8,Risk of Recidivism,-2.13,1,Low,New,1,0 +68517,79568,71956,PRETRIAL,Cromer,Roena,NULL,Female,African-American,08/01/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68530,79584,71970,PRETRIAL,Choquette,Mark,NULL,Male,Caucasian,03/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,7,Risk of Violence,-2.66,2,Low,New,1,0 +68530,79584,71970,PRETRIAL,Choquette,Mark,NULL,Male,Caucasian,03/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,8,Risk of Recidivism,-0.75,3,Low,New,1,0 +68530,79584,71970,PRETRIAL,Choquette,Mark,NULL,Male,Caucasian,03/17/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68519,79571,71959,PRETRIAL,NELSON,DANDRE,L,Male,African-American,04/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,4,High,7,Risk of Violence,-0.75,9,High,New,1,0 +68519,79571,71959,PRETRIAL,NELSON,DANDRE,L,Male,African-American,04/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,4,High,8,Risk of Recidivism,0.83,10,High,New,1,0 +68519,79571,71959,PRETRIAL,NELSON,DANDRE,L,Male,African-American,04/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,4,High,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +68528,79580,71968,PRETRIAL,Calder,Patrick,NULL,Male,African-American,03/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,7,Risk of Violence,-3.47,1,Low,New,1,0 +68528,79580,71968,PRETRIAL,Calder,Patrick,NULL,Male,African-American,03/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,8,Risk of Recidivism,-1.48,1,Low,New,1,0 +68528,79580,71968,PRETRIAL,Calder,Patrick,NULL,Male,African-American,03/20/73,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/26/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68535,79589,71975,PRETRIAL,Everett,Oscar,Johnny,Male,African-American,06/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +68535,79589,71975,PRETRIAL,Everett,Oscar,Johnny,Male,African-American,06/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,1,Low,8,Risk of Recidivism,-1.04,2,Low,New,1,0 +68535,79589,71975,PRETRIAL,Everett,Oscar,Johnny,Male,African-American,06/22/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68533,79587,71973,PRETRIAL,Soto,Manuel,NULL,Male,Hispanic,03/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,1,Low,7,Risk of Violence,-3.97,1,Low,New,1,0 +68533,79587,71973,PRETRIAL,Soto,Manuel,NULL,Male,Hispanic,03/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,1,Low,8,Risk of Recidivism,-1.95,1,Low,New,1,0 +68533,79587,71973,PRETRIAL,Soto,Manuel,NULL,Male,Hispanic,03/16/60,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68540,79594,71980,PRETRIAL,IVANOV,CAROLYN,ALANIS,Female,Caucasian,04/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,1,Low,7,Risk of Violence,-3.41,1,Low,New,1,0 +68540,79594,71980,PRETRIAL,IVANOV,CAROLYN,ALANIS,Female,Caucasian,04/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,1,Low,8,Risk of Recidivism,-1.54,2,Low,New,1,0 +68540,79594,71980,PRETRIAL,IVANOV,CAROLYN,ALANIS,Female,Caucasian,04/21/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68541,79596,71982,PRETRIAL,PERKINS,BRANDON,NULL,Male,African-American,11/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,7,Risk of Violence,-2.33,3,Low,New,1,0 +68541,79596,71982,PRETRIAL,PERKINS,BRANDON,NULL,Male,African-American,11/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,New,1,0 +68541,79596,71982,PRETRIAL,PERKINS,BRANDON,NULL,Male,African-American,11/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +68536,79590,71976,PRETRIAL,LEE,LAJUAN,SAMUEL,Male,African-American,01/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,7,Risk of Violence,-2.78,2,Low,New,1,0 +68536,79590,71976,PRETRIAL,LEE,LAJUAN,SAMUEL,Male,African-American,01/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.08,7,Medium,New,1,0 +68536,79590,71976,PRETRIAL,LEE,LAJUAN,SAMUEL,Male,African-American,01/03/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,18,Risk of Failure to Appear,22,5,Medium,New,1,0 +68542,79598,71983,PRETRIAL,BROCK,MARK,NULL,Male,Caucasian,06/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/14 0:00,2,Medium,7,Risk of Violence,-2.55,3,Low,Copy,1,0 +68542,79598,71983,PRETRIAL,BROCK,MARK,NULL,Male,Caucasian,06/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.3,6,Medium,Copy,1,0 +68542,79598,71983,PRETRIAL,BROCK,MARK,NULL,Male,Caucasian,06/05/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/14 0:00,2,Medium,18,Risk of Failure to Appear,23,5,Medium,Copy,1,0 +68538,79592,71978,PRETRIAL,DOBY,QUSHANNA,LASHAWN,Female,African-American,05/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,New,1,0 +68538,79592,71978,PRETRIAL,DOBY,QUSHANNA,LASHAWN,Female,African-American,05/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.14,7,Medium,New,1,0 +68538,79592,71978,PRETRIAL,DOBY,QUSHANNA,LASHAWN,Female,African-American,05/05/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +58796,79599,71984,PRETRIAL,Bowens,Jermaine,Rashard,Male,African-American,04/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,7,Risk of Violence,-1.37,7,Medium,New,1,0 +58796,79599,71984,PRETRIAL,Bowens,Jermaine,Rashard,Male,African-American,04/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.13,6,Medium,New,1,0 +58796,79599,71984,PRETRIAL,Bowens,Jermaine,Rashard,Male,African-American,04/02/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68532,79586,71972,PRETRIAL,Smith,Natasha,NULL,Female,African-American,06/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,1,Low,7,Risk of Violence,-3.34,1,Low,New,1,0 +68532,79586,71972,PRETRIAL,Smith,Natasha,NULL,Female,African-American,06/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,1,Low,8,Risk of Recidivism,-1.06,3,Low,New,1,0 +68532,79586,71972,PRETRIAL,Smith,Natasha,NULL,Female,African-American,06/23/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,1,Low,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +68537,79591,71977,PRETRIAL,Lihansky,Anna,NULL,Female,Caucasian,11/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/14 0:00,2,Medium,7,Risk of Violence,-2.12,4,Low,New,1,0 +68537,79591,71977,PRETRIAL,Lihansky,Anna,NULL,Female,Caucasian,11/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.48,6,Medium,New,1,0 +68537,79591,71977,PRETRIAL,Lihansky,Anna,NULL,Female,Caucasian,11/03/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/27/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68534,79588,71974,PRETRIAL,Jordan,Joel,Emmanuel,Male,African-American,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,7,Risk of Violence,-1.42,7,Medium,New,1,0 +68534,79588,71974,PRETRIAL,Jordan,Joel,Emmanuel,Male,African-American,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.44,5,Medium,New,1,0 +68534,79588,71974,PRETRIAL,Jordan,Joel,Emmanuel,Male,African-American,12/17/91,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68362,79595,71981,PRETRIAL,PHILMORE,MARCEL,NULL,Male,Native American,08/31/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,7,Risk of Violence,-2.49,3,Low,New,1,0 +68362,79595,71981,PRETRIAL,PHILMORE,MARCEL,NULL,Male,Native American,08/31/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,8,Risk of Recidivism,-0.1,7,Medium,New,1,0 +68362,79595,71981,PRETRIAL,PHILMORE,MARCEL,NULL,Male,Native American,08/31/44,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/27/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68539,79593,71979,PRETRIAL,STFLEUR,CHANTALLE,NULL,Female,African-American,02/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/27/14 0:00,1,Low,7,Risk of Violence,-2.52,3,Low,New,1,0 +68539,79593,71979,PRETRIAL,STFLEUR,CHANTALLE,NULL,Female,African-American,02/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/27/14 0:00,1,Low,8,Risk of Recidivism,-1.36,2,Low,New,1,0 +68539,79593,71979,PRETRIAL,STFLEUR,CHANTALLE,NULL,Female,African-American,02/09/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/27/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68544,79602,71987,PRETRIAL,Brown,Brandon,NULL,Male,African-American,07/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.44,7,Medium,New,1,0 +68544,79602,71987,PRETRIAL,Brown,Brandon,NULL,Male,African-American,07/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.57,9,High,New,1,0 +68544,79602,71987,PRETRIAL,Brown,Brandon,NULL,Male,African-American,07/05/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68546,79604,71989,PRETRIAL,Whitt,Tiffany,NULL,Female,African-American,04/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,1,Low,7,Risk of Violence,-2.06,4,Low,New,1,0 +68546,79604,71989,PRETRIAL,Whitt,Tiffany,NULL,Female,African-American,04/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,1,Low,8,Risk of Recidivism,-0.98,4,Low,New,1,0 +68546,79604,71989,PRETRIAL,Whitt,Tiffany,NULL,Female,African-American,04/19/94,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68552,79612,71995,PRETRIAL,Fletes,Irley,Aaron,Male,Caucasian,08/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/14 0:00,1,Low,7,Risk of Violence,-2.4,3,Low,New,1,0 +68552,79612,71995,PRETRIAL,Fletes,Irley,Aaron,Male,Caucasian,08/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/14 0:00,1,Low,8,Risk of Recidivism,-0.73,4,Low,New,1,0 +68552,79612,71995,PRETRIAL,Fletes,Irley,Aaron,Male,Caucasian,08/07/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68548,79606,71991,PRETRIAL,Jones,Lillie,NULL,Female,African-American,06/09/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.42,3,Low,New,1,0 +68548,79606,71991,PRETRIAL,Jones,Lillie,NULL,Female,African-American,06/09/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.34,9,High,New,1,0 +68548,79606,71991,PRETRIAL,Jones,Lillie,NULL,Female,African-American,06/09/66,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,23,6,Medium,New,1,0 +68553,79613,71996,PRETRIAL,Gonzalez,Almalinda,Priscilla,Female,Caucasian,01/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/28/14 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,New,1,0 +68553,79613,71996,PRETRIAL,Gonzalez,Almalinda,Priscilla,Female,Caucasian,01/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,6,Medium,New,1,0 +68553,79613,71996,PRETRIAL,Gonzalez,Almalinda,Priscilla,Female,Caucasian,01/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/28/14 0:00,2,Medium,18,Risk of Failure to Appear,15,1,Low,New,1,0 +44110,79600,71985,PRETRIAL,Roberts,Joshua,NULL,Male,African-American,03/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,2,Medium,7,Risk of Violence,-2,4,Low,New,1,0 +44110,79600,71985,PRETRIAL,Roberts,Joshua,NULL,Male,African-American,03/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.29,6,Medium,New,1,0 +44110,79600,71985,PRETRIAL,Roberts,Joshua,NULL,Male,African-American,03/30/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68549,79608,71992,PRETRIAL,ABITANTE,JOSEPH,NULL,Male,Caucasian,09/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/14 0:00,1,Low,7,Risk of Violence,-2.87,2,Low,Copy,1,0 +68549,79608,71992,PRETRIAL,ABITANTE,JOSEPH,NULL,Male,Caucasian,09/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/14 0:00,1,Low,8,Risk of Recidivism,-1.64,1,Low,Copy,1,0 +68549,79608,71992,PRETRIAL,ABITANTE,JOSEPH,NULL,Male,Caucasian,09/22/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +68551,79611,71994,PRETRIAL,Kuckenbaker,Jennifer,Ann,Female,Caucasian,03/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +68551,79611,71994,PRETRIAL,Kuckenbaker,Jennifer,Ann,Female,Caucasian,03/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/14 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +68551,79611,71994,PRETRIAL,Kuckenbaker,Jennifer,Ann,Female,Caucasian,03/28/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68545,79603,71988,PRETRIAL,Doss-Wellington,Toni,NULL,Female,African-American,07/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/14 0:00,2,Medium,7,Risk of Violence,-1.84,5,Medium,New,1,0 +68545,79603,71988,PRETRIAL,Doss-Wellington,Toni,NULL,Female,African-American,07/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,7,Medium,New,1,0 +68545,79603,71988,PRETRIAL,Doss-Wellington,Toni,NULL,Female,African-American,07/25/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/28/14 0:00,2,Medium,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68547,79605,71990,PRETRIAL,Armstrong,Dominic,Manuel,Male,African-American,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.89,2,Low,New,1,0 +68547,79605,71990,PRETRIAL,Armstrong,Dominic,Manuel,Male,African-American,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.29,8,High,New,1,0 +68547,79605,71990,PRETRIAL,Armstrong,Dominic,Manuel,Male,African-American,02/03/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68550,79610,71993,PRETRIAL,barrientos,rony,NULL,Male,Hispanic,09/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/28/14 0:00,1,Low,7,Risk of Violence,-3.42,1,Low,New,1,0 +68550,79610,71993,PRETRIAL,barrientos,rony,NULL,Male,Hispanic,09/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/28/14 0:00,1,Low,8,Risk of Recidivism,-2.01,1,Low,New,1,0 +68550,79610,71993,PRETRIAL,barrientos,rony,NULL,Male,Hispanic,09/23/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Divorced,12/28/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +68543,79601,71986,PRETRIAL,BUTCHER,BRIAN,A,Male,African-American,06/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,1,Low,7,Risk of Violence,-3.87,1,Low,New,1,0 +68543,79601,71986,PRETRIAL,BUTCHER,BRIAN,A,Male,African-American,06/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,1,Low,8,Risk of Recidivism,-1.87,1,Low,New,1,0 +68543,79601,71986,PRETRIAL,BUTCHER,BRIAN,A,Male,African-American,06/14/65,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/28/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +51678,79626,60987,PRETRIAL,Leal,Justin,NULL,Male,Caucasian,01/20/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.05,8,High,New,1,0 +51678,79626,60987,PRETRIAL,Leal,Justin,NULL,Male,Caucasian,01/20/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.19,7,Medium,New,1,0 +51678,79626,60987,PRETRIAL,Leal,Justin,NULL,Male,Caucasian,01/20/95,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68559,79622,72005,PRETRIAL,NEAL,CONRADA,PEACHES,Female,African-American,11/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/29/14 0:00,1,Low,7,Risk of Violence,-3.59,1,Low,New,1,0 +68559,79622,72005,PRETRIAL,NEAL,CONRADA,PEACHES,Female,African-American,11/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/29/14 0:00,1,Low,8,Risk of Recidivism,-2.1,1,Low,New,1,0 +68559,79622,72005,PRETRIAL,NEAL,CONRADA,PEACHES,Female,African-American,11/11/75,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/29/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68555,79615,71998,PRETRIAL,ARANGO,JOHN,DAVID,Male,Caucasian,07/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/29/14 0:00,1,Low,7,Risk of Violence,-3.61,1,Low,New,1,0 +68555,79615,71998,PRETRIAL,ARANGO,JOHN,DAVID,Male,Caucasian,07/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/29/14 0:00,1,Low,8,Risk of Recidivism,-2.18,1,Low,New,1,0 +68555,79615,71998,PRETRIAL,ARANGO,JOHN,DAVID,Male,Caucasian,07/01/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +68556,79617,72000,PRETRIAL,WHITNEY,ANDREW,NULL,Male,African-American,02/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,7,Risk of Violence,-2.42,3,Low,New,1,0 +68556,79617,72000,PRETRIAL,WHITNEY,ANDREW,NULL,Male,African-American,02/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,8,Risk of Recidivism,-0.72,4,Low,New,1,0 +68556,79617,72000,PRETRIAL,WHITNEY,ANDREW,NULL,Male,African-American,02/11/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,18,Risk of Failure to Appear,29,8,High,New,1,0 +68561,79624,72007,PRETRIAL,Masters,Amara,Anthony,Male,African-American,04/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/29/14 0:00,1,Low,7,Risk of Violence,-3.07,1,Low,New,1,0 +68561,79624,72007,PRETRIAL,Masters,Amara,Anthony,Male,African-American,04/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/29/14 0:00,1,Low,8,Risk of Recidivism,-1.71,1,Low,New,1,0 +68561,79624,72007,PRETRIAL,Masters,Amara,Anthony,Male,African-American,04/10/84,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/29/14 0:00,1,Low,18,Risk of Failure to Appear,20,3,Low,New,1,0 +68565,79629,72011,PRETRIAL,MCCLAIN,THERESA,NULL,Female,Caucasian,08/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-3.1,1,Low,New,1,0 +68565,79629,72011,PRETRIAL,MCCLAIN,THERESA,NULL,Female,Caucasian,08/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.07,8,High,New,1,0 +68565,79629,72011,PRETRIAL,MCCLAIN,THERESA,NULL,Female,Caucasian,08/17/62,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +68557,79619,72002,PRETRIAL,Jenkins,Lourdes,Milagro,Female,Caucasian,09/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/29/14 0:00,1,Low,7,Risk of Violence,-3.55,1,Low,New,1,0 +68557,79619,72002,PRETRIAL,Jenkins,Lourdes,Milagro,Female,Caucasian,09/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/29/14 0:00,1,Low,8,Risk of Recidivism,-2.11,1,Low,New,1,0 +68557,79619,72002,PRETRIAL,Jenkins,Lourdes,Milagro,Female,Caucasian,09/13/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/29/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +41943,79621,72004,PRETRIAL,Beauchamps,Alexsandra,NULL,Female,African-American,12/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,2,Medium,7,Risk of Violence,-2.09,4,Low,New,1,0 +41943,79621,72004,PRETRIAL,Beauchamps,Alexsandra,NULL,Female,African-American,12/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,2,Medium,8,Risk of Recidivism,-0.56,6,Medium,New,1,0 +41943,79621,72004,PRETRIAL,Beauchamps,Alexsandra,NULL,Female,African-American,12/21/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68563,79627,72009,PRETRIAL,groenewald,david,NULL,Male,Caucasian,09/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,7,Risk of Violence,-3.58,1,Low,New,1,0 +68563,79627,72009,PRETRIAL,groenewald,david,NULL,Male,Caucasian,09/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,8,Risk of Recidivism,-1.69,1,Low,New,1,0 +68563,79627,72009,PRETRIAL,groenewald,david,NULL,Male,Caucasian,09/15/77,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68562,79625,72008,PRETRIAL,cortes,edward,NULL,Male,Hispanic,12/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,7,Risk of Violence,-3.43,1,Low,New,1,0 +68562,79625,72008,PRETRIAL,cortes,edward,NULL,Male,Hispanic,12/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,8,Risk of Recidivism,-1.66,1,Low,New,1,0 +68562,79625,72008,PRETRIAL,cortes,edward,NULL,Male,Hispanic,12/30/67,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68558,79620,72003,PRETRIAL,CARSWELL,ARIANA,NULL,Female,African-American,10/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,7,Risk of Violence,-1.82,5,Medium,New,1,0 +68558,79620,72003,PRETRIAL,CARSWELL,ARIANA,NULL,Female,African-American,10/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,8,Risk of Recidivism,-1,4,Low,New,1,0 +68558,79620,72003,PRETRIAL,CARSWELL,ARIANA,NULL,Female,African-American,10/17/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68564,79628,72010,PRETRIAL,Shy,Brent,Wilmington,Male,African-American,05/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,New,1,0 +68564,79628,72010,PRETRIAL,Shy,Brent,Wilmington,Male,African-American,05/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,8,Risk of Recidivism,-0.89,3,Low,New,1,0 +68564,79628,72010,PRETRIAL,Shy,Brent,Wilmington,Male,African-American,05/07/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68560,79623,72006,PRETRIAL,Teran,Eduardo,NULL,Male,Hispanic,12/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/29/14 0:00,1,Low,7,Risk of Violence,-3.27,1,Low,New,1,0 +68560,79623,72006,PRETRIAL,Teran,Eduardo,NULL,Male,Hispanic,12/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/29/14 0:00,1,Low,8,Risk of Recidivism,-1.7,1,Low,New,1,0 +68560,79623,72006,PRETRIAL,Teran,Eduardo,NULL,Male,Hispanic,12/09/79,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/29/14 0:00,1,Low,18,Risk of Failure to Appear,19,3,Low,New,1,0 +23727,25002,22929,PRETRIAL,Russell,Ahmed,NULL,Male,Caucasian,01/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.13,4,Low,New,1,0 +23727,25002,22929,PRETRIAL,Russell,Ahmed,NULL,Male,Caucasian,01/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,9,High,New,1,0 +23727,25002,22929,PRETRIAL,Russell,Ahmed,NULL,Male,Caucasian,01/10/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,33,9,High,New,1,0 +68496,79618,72001,PRETRIAL,Holder,Sean,Paul,Male,African-American,10/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,4,High,7,Risk of Violence,-0.42,10,High,New,1,0 +68496,79618,72001,PRETRIAL,Holder,Sean,Paul,Male,African-American,10/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,4,High,8,Risk of Recidivism,0.67,10,High,New,1,0 +68496,79618,72001,PRETRIAL,Holder,Sean,Paul,Male,African-American,10/20/95,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/29/14 0:00,4,High,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68554,79614,71997,PRETRIAL,Hines,Harley,NULL,Male,Other,08/31/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/29/14 0:00,1,Low,7,Risk of Violence,-4.43,1,Low,New,1,0 +68554,79614,71997,PRETRIAL,Hines,Harley,NULL,Male,Other,08/31/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/29/14 0:00,1,Low,8,Risk of Recidivism,-2.86,1,Low,New,1,0 +68554,79614,71997,PRETRIAL,Hines,Harley,NULL,Male,Other,08/31/53,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/29/14 0:00,1,Low,18,Risk of Failure to Appear,12,1,Low,New,1,0 +34895,79635,34081,DRRD,Forbes,Shavorn,NULL,Male,African-American,12/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.9,5,Medium,Copy,1,0 +34895,79635,34081,DRRD,Forbes,Shavorn,NULL,Male,African-American,12/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.24,8,High,Copy,1,0 +34895,79635,34081,DRRD,Forbes,Shavorn,NULL,Male,African-American,12/07/92,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,2,Low,Copy,1,0 +68579,79639,72019,PRETRIAL,FROST,LATONYA,SHEREE,Female,African-American,12/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,7,Risk of Violence,-2.83,2,Low,New,1,0 +68579,79639,72019,PRETRIAL,FROST,LATONYA,SHEREE,Female,African-American,12/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,8,Risk of Recidivism,-1.37,2,Low,New,1,0 +68579,79639,72019,PRETRIAL,FROST,LATONYA,SHEREE,Female,African-American,12/14/78,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68589,79644,72023,PRETRIAL,BAKER,DOUGLAS,SCOTT,Male,Caucasian,05/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,2,Medium,7,Risk of Violence,-2.02,4,Low,New,1,0 +68589,79644,72023,PRETRIAL,BAKER,DOUGLAS,SCOTT,Male,Caucasian,05/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.16,6,Medium,New,1,0 +68589,79644,72023,PRETRIAL,BAKER,DOUGLAS,SCOTT,Male,Caucasian,05/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,2,Medium,18,Risk of Failure to Appear,27,7,Medium,New,1,0 +11106,11396,10623,PRETRIAL,brennen,dwayne,NULL,Male,African-American,05/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.51,6,Medium,New,1,0 +11106,11396,10623,PRETRIAL,brennen,dwayne,NULL,Male,African-American,05/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,New,1,0 +11106,11396,10623,PRETRIAL,brennen,dwayne,NULL,Male,African-American,05/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,New,1,0 +68566,79630,72012,PRETRIAL,JOHNSON,JERMIAH,JERMAINE,Male,African-American,05/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,7,Risk of Violence,-2.71,2,Low,New,1,0 +68566,79630,72012,PRETRIAL,JOHNSON,JERMIAH,JERMAINE,Male,African-American,05/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,8,Risk of Recidivism,-0.68,4,Low,New,1,0 +68566,79630,72012,PRETRIAL,JOHNSON,JERMIAH,JERMAINE,Male,African-American,05/09/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,18,Risk of Failure to Appear,23,5,Medium,New,1,0 +68567,79632,72013,PRETRIAL,Mitchell-Mejia,Freddy,NULL,Male,Caucasian,06/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/14 0:00,1,Low,7,Risk of Violence,-3.23,1,Low,New,1,0 +68567,79632,72013,PRETRIAL,Mitchell-Mejia,Freddy,NULL,Male,Caucasian,06/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +68567,79632,72013,PRETRIAL,Mitchell-Mejia,Freddy,NULL,Male,Caucasian,06/13/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +3691,79651,3406,PRETRIAL,Austin,Samuel,NULL,Male,African-American,04/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/30/14 0:00,2,Medium,7,Risk of Violence,-1.54,6,Medium,Copy,1,0 +3691,79651,3406,PRETRIAL,Austin,Samuel,NULL,Male,African-American,04/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/30/14 0:00,2,Medium,8,Risk of Recidivism,0.03,7,Medium,Copy,1,0 +3691,79651,3406,PRETRIAL,Austin,Samuel,NULL,Male,African-American,04/16/71,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Separated,12/30/14 0:00,2,Medium,18,Risk of Failure to Appear,36,10,High,Copy,1,0 +68591,79649,72026,PRETRIAL,Kennedy,Kendrick,NULL,Male,African-American,06/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.84,2,Low,New,1,0 +68591,79649,72026,PRETRIAL,Kennedy,Kendrick,NULL,Male,African-American,06/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.23,8,High,New,1,0 +68591,79649,72026,PRETRIAL,Kennedy,Kendrick,NULL,Male,African-American,06/04/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,18,3,Low,New,1,0 +11106,79646,10623,PRETRIAL,brennen,dwayne,NULL,Male,African-American,05/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.63,6,Medium,Copy,1,0 +11106,79646,10623,PRETRIAL,brennen,dwayne,NULL,Male,African-American,05/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.13,8,High,Copy,1,0 +11106,79646,10623,PRETRIAL,brennen,dwayne,NULL,Male,African-American,05/28/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Separated,12/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,17,2,Low,Copy,1,0 +42708,79633,72014,PRETRIAL,RODRIGUEZ,EMIGDIO,NULL,Male,Caucasian,02/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,2,Medium,7,Risk of Violence,-2.13,4,Low,New,1,0 +42708,79633,72014,PRETRIAL,RODRIGUEZ,EMIGDIO,NULL,Male,Caucasian,02/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.27,6,Medium,New,1,0 +42708,79633,72014,PRETRIAL,RODRIGUEZ,EMIGDIO,NULL,Male,Caucasian,02/10/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +39209,42309,38710,PRETRIAL,velazquezmontalvo,alex,NULL,Male,Hispanic,07/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,7,Risk of Violence,-2.39,3,Low,New,1,0 +39209,42309,38710,PRETRIAL,velazquezmontalvo,alex,NULL,Male,Hispanic,07/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,8,Risk of Recidivism,-0.62,4,Low,New,1,0 +39209,42309,38710,PRETRIAL,velazquezmontalvo,alex,NULL,Male,Hispanic,07/09/88,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 +68568,79634,72015,PRETRIAL,Cormier,Dwayne,E,Male,African-American,09/01/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.65,6,Medium,New,1,0 +68568,79634,72015,PRETRIAL,Cormier,Dwayne,E,Male,African-American,09/01/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,New,1,0 +68568,79634,72015,PRETRIAL,Cormier,Dwayne,E,Male,African-American,09/01/68,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +68577,79637,72017,PRETRIAL,LAGUERRE,RICOT,NULL,Male,African-American,10/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/14 0:00,1,Low,7,Risk of Violence,-3.11,1,Low,New,1,0 +68577,79637,72017,PRETRIAL,LAGUERRE,RICOT,NULL,Male,African-American,10/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/14 0:00,1,Low,8,Risk of Recidivism,-1.79,1,Low,New,1,0 +68577,79637,72017,PRETRIAL,LAGUERRE,RICOT,NULL,Male,African-American,10/12/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68578,79638,72018,PRETRIAL,HAWTHORNE,JUAN,NULL,Male,African-American,06/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,4,High,7,Risk of Violence,-0.92,9,High,New,1,0 +68578,79638,72018,PRETRIAL,HAWTHORNE,JUAN,NULL,Male,African-American,06/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,4,High,8,Risk of Recidivism,1.07,10,High,New,1,0 +68578,79638,72018,PRETRIAL,HAWTHORNE,JUAN,NULL,Male,African-American,06/22/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,4,High,18,Risk of Failure to Appear,18,3,Low,New,1,0 +68590,79645,72024,PRETRIAL,Taylor,Rufus,NULL,Male,African-American,02/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/30/14 0:00,2,Medium,7,Risk of Violence,-2.39,3,Low,New,1,0 +68590,79645,72024,PRETRIAL,Taylor,Rufus,NULL,Male,African-American,02/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.19,6,Medium,New,1,0 +68590,79645,72024,PRETRIAL,Taylor,Rufus,NULL,Male,African-American,02/05/63,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Unknown,12/30/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,New,1,0 +68593,79652,72028,PRETRIAL,BAZIAN,MAHMOUD,NULL,Male,Other,07/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/14 0:00,1,Low,7,Risk of Violence,-2.8,2,Low,New,1,0 +68593,79652,72028,PRETRIAL,BAZIAN,MAHMOUD,NULL,Male,Other,07/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/14 0:00,1,Low,8,Risk of Recidivism,-0.92,3,Low,New,1,0 +68593,79652,72028,PRETRIAL,BAZIAN,MAHMOUD,NULL,Male,Other,07/20/80,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68576,79636,72016,PRETRIAL,MICHAEL,STERN,NULL,Male,Caucasian,07/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/14 0:00,1,Low,7,Risk of Violence,-3.71,1,Low,New,1,0 +68576,79636,72016,PRETRIAL,MICHAEL,STERN,NULL,Male,Caucasian,07/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/14 0:00,1,Low,8,Risk of Recidivism,-2.2,1,Low,New,1,0 +68576,79636,72016,PRETRIAL,MICHAEL,STERN,NULL,Male,Caucasian,07/07/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Married,12/30/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +68553,79647,71996,PRETRIAL,Gonzalez,Almalinda,Priscilla,Female,Caucasian,01/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,12/30/14 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,Copy,1,0 +68553,79647,71996,PRETRIAL,Gonzalez,Almalinda,Priscilla,Female,Caucasian,01/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,12/30/14 0:00,2,Medium,8,Risk of Recidivism,-0.17,7,Medium,Copy,1,0 +68553,79647,71996,PRETRIAL,Gonzalez,Almalinda,Priscilla,Female,Caucasian,01/11/95,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Significant Other,12/30/14 0:00,2,Medium,18,Risk of Failure to Appear,13,1,Low,Copy,1,0 +68586,79640,72020,PRETRIAL,Garguilo,Jaclyn,Marie,Female,Caucasian,09/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.55,6,Medium,New,1,0 +68586,79640,72020,PRETRIAL,Garguilo,Jaclyn,Marie,Female,Caucasian,09/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.59,10,High,New,1,0 +68586,79640,72020,PRETRIAL,Garguilo,Jaclyn,Marie,Female,Caucasian,09/18/81,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/30/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,32,9,High,New,1,0 +68588,79643,72022,PRETRIAL,Solis,Carlos,Joel,Male,Hispanic,05/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,7,Risk of Violence,-3.26,1,Low,New,1,0 +68588,79643,72022,PRETRIAL,Solis,Carlos,Joel,Male,Hispanic,05/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,8,Risk of Recidivism,-1.77,1,Low,New,1,0 +68588,79643,72022,PRETRIAL,Solis,Carlos,Joel,Male,Hispanic,05/17/80,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +14995,79631,14341,PRETRIAL,DANIELS,GLENN,NULL,Male,Caucasian,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,7,Risk of Violence,-2.31,3,Low,Copy,1,0 +14995,79631,14341,PRETRIAL,DANIELS,GLENN,NULL,Male,Caucasian,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,8,Risk of Recidivism,-0.45,5,Medium,Copy,1,0 +14995,79631,14341,PRETRIAL,DANIELS,GLENN,NULL,Male,Caucasian,08/25/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/30/14 0:00,1,Low,18,Risk of Failure to Appear,21,4,Low,Copy,1,0 +54855,79678,56587,Probation,Allison,Brian,NULL,Male,Caucasian,05/31/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,2,Medium,7,Risk of Violence,-1.79,5,Medium,Copy,1,0 +54855,79678,56587,Probation,Allison,Brian,NULL,Male,Caucasian,05/31/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,2,Medium,8,Risk of Recidivism,0.08,7,Medium,Copy,1,0 +54855,79678,56587,Probation,Allison,Brian,NULL,Male,Caucasian,05/31/74,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,2,Medium,18,Risk of Failure to Appear,32,9,High,Copy,1,0 +68596,79657,72032,PRETRIAL,LOGAN,JAMES,MICHAEL,Male,Caucasian,08/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,7,Risk of Violence,-3.2,1,Low,New,1,0 +68596,79657,72032,PRETRIAL,LOGAN,JAMES,MICHAEL,Male,Caucasian,08/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,8,Risk of Recidivism,-1.28,2,Low,New,1,0 +68596,79657,72032,PRETRIAL,LOGAN,JAMES,MICHAEL,Male,Caucasian,08/07/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,18,Risk of Failure to Appear,17,2,Low,New,1,0 +51943,79661,72036,PRETRIAL,Wright,Franklin,NULL,Male,African-American,03/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.21,8,High,New,1,0 +51943,79661,72036,PRETRIAL,Wright,Franklin,NULL,Male,African-American,03/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.17,6,Medium,New,1,0 +51943,79661,72036,PRETRIAL,Wright,Franklin,NULL,Male,African-American,03/13/83,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,21,4,Low,New,1,0 +42658,79659,72034,PRETRIAL,Enck,Michael,NULL,Male,Caucasian,04/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.08,8,High,New,1,0 +42658,79659,72034,PRETRIAL,Enck,Michael,NULL,Male,Caucasian,04/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,-0.11,7,Medium,New,1,0 +42658,79659,72034,PRETRIAL,Enck,Michael,NULL,Male,Caucasian,04/13/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +16932,79673,69848,PRETRIAL,Allen,Wymaneka,J,Female,African-American,10/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,2,Medium,7,Risk of Violence,-1.74,5,Medium,Copy,1,0 +16932,79673,69848,PRETRIAL,Allen,Wymaneka,J,Female,African-American,10/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.34,7,Medium,Copy,1,0 +16932,79673,69848,PRETRIAL,Allen,Wymaneka,J,Female,African-American,10/01/88,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,2,Medium,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +68600,79666,72039,PRETRIAL,Curtis,Cheryl,A,Female,Caucasian,01/20/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,7,Risk of Violence,-3.66,1,Low,New,1,0 +68600,79666,72039,PRETRIAL,Curtis,Cheryl,A,Female,Caucasian,01/20/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,8,Risk of Recidivism,-2.06,1,Low,New,1,0 +68600,79666,72039,PRETRIAL,Curtis,Cheryl,A,Female,Caucasian,01/20/69,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,18,Risk of Failure to Appear,14,1,Low,New,1,0 +68602,79668,72041,PRETRIAL,Avery,Brittany,NULL,Female,Caucasian,06/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,1,Low,7,Risk of Violence,-1.94,5,Medium,New,1,0 +68602,79668,72041,PRETRIAL,Avery,Brittany,NULL,Female,Caucasian,06/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,1,Low,8,Risk of Recidivism,-0.73,5,Medium,New,1,0 +68602,79668,72041,PRETRIAL,Avery,Brittany,NULL,Female,Caucasian,06/26/94,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,1,Low,18,Risk of Failure to Appear,13,1,Low,New,1,0 +68604,79671,72043,PRETRIAL,Sookram,krishna,NULL,Male,Caucasian,08/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.96,5,Medium,New,1,0 +68604,79671,72043,PRETRIAL,Sookram,krishna,NULL,Male,Caucasian,08/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.25,8,High,New,1,0 +68604,79671,72043,PRETRIAL,Sookram,krishna,NULL,Male,Caucasian,08/15/84,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,24,6,Medium,New,1,0 +45932,63092,46275,PRETRIAL,Phillips,Tevin,NULL,Male,African-American,06/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,2,Medium,7,Risk of Violence,-1.63,6,Medium,Copy,1,0 +45932,63092,46275,PRETRIAL,Phillips,Tevin,NULL,Male,African-American,06/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.57,4,Low,Copy,1,0 +45932,63092,46275,PRETRIAL,Phillips,Tevin,NULL,Male,African-American,06/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,2,Medium,18,Risk of Failure to Appear,11,1,Low,Copy,1,0 +68597,79658,72033,PRETRIAL,WEBLEY,DESMOND,THEOPHILUS,Male,African-American,08/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,2,Medium,7,Risk of Violence,-2.53,3,Low,New,1,0 +68597,79658,72033,PRETRIAL,WEBLEY,DESMOND,THEOPHILUS,Male,African-American,08/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.12,7,Medium,New,1,0 +68597,79658,72033,PRETRIAL,WEBLEY,DESMOND,THEOPHILUS,Male,African-American,08/09/87,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,2,Medium,18,Risk of Failure to Appear,21,4,Low,New,1,0 +68381,79676,71822,PRETRIAL,JONES,CHRISTOPHER,MICHAEL,Male,Caucasian,07/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/31/14 0:00,1,Low,7,Risk of Violence,-3.01,1,Low,Copy,1,0 +68381,79676,71822,PRETRIAL,JONES,CHRISTOPHER,MICHAEL,Male,Caucasian,07/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/31/14 0:00,1,Low,8,Risk of Recidivism,-0.49,5,Medium,Copy,1,0 +68381,79676,71822,PRETRIAL,JONES,CHRISTOPHER,MICHAEL,Male,Caucasian,07/27/71,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Significant Other,12/31/14 0:00,1,Low,18,Risk of Failure to Appear,27,7,Medium,Copy,1,0 +62296,79655,72030,PRETRIAL,HARDEN,MARK,I,Male,African-American,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,7,Risk of Violence,-3.18,1,Low,New,1,0 +62296,79655,72030,PRETRIAL,HARDEN,MARK,I,Male,African-American,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,8,Risk of Recidivism,-1.58,1,Low,New,1,0 +62296,79655,72030,PRETRIAL,HARDEN,MARK,I,Male,African-American,07/19/72,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,18,Risk of Failure to Appear,15,1,Low,New,1,0 +45932,79663,46275,PRETRIAL,Phillips,Tevin,NULL,Male,African-American,06/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.92,5,Medium,Copy,1,0 +45932,79663,46275,PRETRIAL,Phillips,Tevin,NULL,Male,African-American,06/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.14,8,High,Copy,1,0 +45932,79663,46275,PRETRIAL,Phillips,Tevin,NULL,Male,African-American,06/02/93,22,Risk and Prescreen,Intake,English,Pretrial,Pretrial Defendant,Single,12/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,19,3,Low,Copy,1,0 +24873,79675,29620,PRETRIAL,Sime,Viki,NULL,Male,African-American,02/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,4,High,7,Risk of Violence,-1.07,8,High,Copy,1,0 +24873,79675,29620,PRETRIAL,Sime,Viki,NULL,Male,African-American,02/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,4,High,8,Risk of Recidivism,0.27,8,High,Copy,1,0 +24873,79675,29620,PRETRIAL,Sime,Viki,NULL,Male,African-American,02/09/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,4,High,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +34047,79654,33181,PRETRIAL,Lewis,Kurt,NULL,Male,Other,08/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.58,6,Medium,Copy,1,0 +34047,79654,33181,PRETRIAL,Lewis,Kurt,NULL,Male,Other,08/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.76,10,High,Copy,1,0 +34047,79654,33181,PRETRIAL,Lewis,Kurt,NULL,Male,Other,08/03/74,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,30,8,High,Copy,1,0 +44498,79672,45849,PRETRIAL,Breedlove,Leotis,NULL,Male,African-American,10/23/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-1.82,5,Medium,Copy,1,0 +44498,79672,45849,PRETRIAL,Breedlove,Leotis,NULL,Male,African-American,10/23/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.15,8,High,Copy,1,0 +44498,79672,45849,PRETRIAL,Breedlove,Leotis,NULL,Male,African-American,10/23/92,17,All Scales,Intake,English,Post Sentence,Probation,Single,12/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,15,1,Low,Copy,1,0 +68599,79662,72037,PRETRIAL,PENTO,MELISSA,SUE,Female,Caucasian,04/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.84,2,Low,New,1,0 +68599,79662,72037,PRETRIAL,PENTO,MELISSA,SUE,Female,Caucasian,04/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.06,8,High,New,1,0 +68599,79662,72037,PRETRIAL,PENTO,MELISSA,SUE,Female,Caucasian,04/08/82,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,27,8,High,New,1,0 +19968,79664,36500,PRETRIAL,BUTTERFIELD,JAMES,MICHAEL,Male,Caucasian,09/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/31/14 0:00,2,Medium,7,Risk of Violence,-2.44,3,Low,Copy,1,0 +19968,79664,36500,PRETRIAL,BUTTERFIELD,JAMES,MICHAEL,Male,Caucasian,09/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.22,6,Medium,Copy,1,0 +19968,79664,36500,PRETRIAL,BUTTERFIELD,JAMES,MICHAEL,Male,Caucasian,09/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/31/14 0:00,2,Medium,18,Risk of Failure to Appear,26,7,Medium,Copy,1,0 +68608,79677,72045,PRETRIAL,Hayes,Thomas,NULL,Male,Caucasian,08/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,7,Risk of Violence,-1.74,5,Medium,New,1,0 +68608,79677,72045,PRETRIAL,Hayes,Thomas,NULL,Male,Caucasian,08/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,8,Risk of Recidivism,-0.32,5,Medium,New,1,0 +68608,79677,72045,PRETRIAL,Hayes,Thomas,NULL,Male,Caucasian,08/13/89,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,18,Risk of Failure to Appear,26,7,Medium,New,1,0 +68595,79656,72031,PRETRIAL,PENA,ROLANDO,N,Male,Hispanic,06/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,2,Medium,7,Risk of Violence,-1.61,6,Medium,New,1,0 +68595,79656,72031,PRETRIAL,PENA,ROLANDO,N,Male,Hispanic,06/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,2,Medium,8,Risk of Recidivism,-0.42,5,Medium,New,1,0 +68595,79656,72031,PRETRIAL,PENA,ROLANDO,N,Male,Hispanic,06/13/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,2,Medium,18,Risk of Failure to Appear,17,2,Low,New,1,0 +19968,39866,36500,PRETRIAL,BUTTERFIELD,JAMES,MICHAEL,Male,Caucasian,09/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/31/14 0:00,1,Low,7,Risk of Violence,-2.5,3,Low,New,1,0 +19968,39866,36500,PRETRIAL,BUTTERFIELD,JAMES,MICHAEL,Male,Caucasian,09/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/31/14 0:00,1,Low,8,Risk of Recidivism,-0.36,5,Medium,New,1,0 +19968,39866,36500,PRETRIAL,BUTTERFIELD,JAMES,MICHAEL,Male,Caucasian,09/24/73,22,Risk and Prescreen,Intake,English,Post Sentence,Probation,Single,12/31/14 0:00,1,Low,18,Risk of Failure to Appear,30,8,High,New,1,0 +68598,79660,72035,PRETRIAL,SUAREZ,ANDERSON,NULL,Male,Caucasian,08/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,7,Risk of Violence,-3.12,1,Low,New,1,0 +68598,79660,72035,PRETRIAL,SUAREZ,ANDERSON,NULL,Male,Caucasian,08/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,8,Risk of Recidivism,-1.57,1,Low,New,1,0 +68598,79660,72035,PRETRIAL,SUAREZ,ANDERSON,NULL,Male,Caucasian,08/10/81,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,18,Risk of Failure to Appear,11,1,Low,New,1,0 +65667,79665,72038,Probation,West,James,NULL,Male,African-American,06/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,7,Risk of Violence,-2.03,4,Low,New,1,0 +65667,79665,72038,Probation,West,James,NULL,Male,African-American,06/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,8,Risk of Recidivism,0.16,8,High,New,1,0 +65667,79665,72038,Probation,West,James,NULL,Male,African-American,06/21/64,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,3,Medium with Override Consideration,18,Risk of Failure to Appear,35,10,High,New,1,0 +68603,79669,72042,PRETRIAL,Ryan,Michael,NULL,Male,Caucasian,02/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,7,Risk of Violence,-2.75,2,Low,New,1,0 +68603,79669,72042,PRETRIAL,Ryan,Michael,NULL,Male,Caucasian,02/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,8,Risk of Recidivism,-0.34,5,Medium,New,1,0 +68603,79669,72042,PRETRIAL,Ryan,Michael,NULL,Male,Caucasian,02/06/85,22,Risk and Prescreen,Intake,English,Pretrial,Jail Inmate,Single,12/31/14 0:00,1,Low,18,Risk of Failure to Appear,16,2,Low,New,1,0 \ No newline at end of file diff --git a/tests/fixtures/credit_customers.csv b/tests/fixtures/credit_customers.csv new file mode 100644 index 0000000..bc281a3 --- /dev/null +++ b/tests/fixtures/credit_customers.csv @@ -0,0 +1,1001 @@ +checking_status,duration,credit_history,purpose,credit_amount,savings_status,employment,installment_commitment,personal_status,other_parties,residence_since,property_magnitude,age,other_payment_plans,housing,existing_credits,job,num_dependents,own_telephone,foreign_worker,class +<0,6.0,critical/other existing credit,radio/tv,1169.0,no known savings,>=7,4.0,male single,none,4.0,real estate,67.0,none,own,2.0,skilled,1.0,yes,yes,good +0<=X<200,48.0,existing paid,radio/tv,5951.0,<100,1<=X<4,2.0,female div/dep/mar,none,2.0,real estate,22.0,none,own,1.0,skilled,1.0,none,yes,bad +no checking,12.0,critical/other existing credit,education,2096.0,<100,4<=X<7,2.0,male single,none,3.0,real estate,49.0,none,own,1.0,unskilled resident,2.0,none,yes,good +<0,42.0,existing paid,furniture/equipment,7882.0,<100,4<=X<7,2.0,male single,guarantor,4.0,life insurance,45.0,none,for free,1.0,skilled,2.0,none,yes,good +<0,24.0,delayed previously,new car,4870.0,<100,1<=X<4,3.0,male single,none,4.0,no known property,53.0,none,for free,2.0,skilled,2.0,none,yes,bad +no checking,36.0,existing paid,education,9055.0,no known savings,1<=X<4,2.0,male single,none,4.0,no known property,35.0,none,for free,1.0,unskilled resident,2.0,yes,yes,good +no checking,24.0,existing paid,furniture/equipment,2835.0,500<=X<1000,>=7,3.0,male single,none,4.0,life insurance,53.0,none,own,1.0,skilled,1.0,none,yes,good +0<=X<200,36.0,existing paid,used car,6948.0,<100,1<=X<4,2.0,male single,none,2.0,car,35.0,none,rent,1.0,high qualif/self emp/mgmt,1.0,yes,yes,good +no checking,12.0,existing paid,radio/tv,3059.0,>=1000,4<=X<7,2.0,male div/sep,none,4.0,real estate,61.0,none,own,1.0,unskilled resident,1.0,none,yes,good +0<=X<200,30.0,critical/other existing credit,new car,5234.0,<100,unemployed,4.0,male mar/wid,none,2.0,car,28.0,none,own,2.0,high qualif/self emp/mgmt,1.0,none,yes,bad +0<=X<200,12.0,existing paid,new car,1295.0,<100,<1,3.0,female div/dep/mar,none,1.0,car,25.0,none,rent,1.0,skilled,1.0,none,yes,bad +<0,48.0,existing paid,business,4308.0,<100,<1,3.0,female div/dep/mar,none,4.0,life insurance,24.0,none,rent,1.0,skilled,1.0,none,yes,bad +0<=X<200,12.0,existing paid,radio/tv,1567.0,<100,1<=X<4,1.0,female div/dep/mar,none,1.0,car,22.0,none,own,1.0,skilled,1.0,yes,yes,good +<0,24.0,critical/other existing credit,new car,1199.0,<100,>=7,4.0,male single,none,4.0,car,60.0,none,own,2.0,unskilled resident,1.0,none,yes,bad +<0,15.0,existing paid,new car,1403.0,<100,1<=X<4,2.0,female div/dep/mar,none,4.0,car,28.0,none,rent,1.0,skilled,1.0,none,yes,good +<0,24.0,existing paid,radio/tv,1282.0,100<=X<500,1<=X<4,4.0,female div/dep/mar,none,2.0,car,32.0,none,own,1.0,unskilled resident,1.0,none,yes,bad +no checking,24.0,critical/other existing credit,radio/tv,2424.0,no known savings,>=7,4.0,male single,none,4.0,life insurance,53.0,none,own,2.0,skilled,1.0,none,yes,good +<0,30.0,no credits/all paid,business,8072.0,no known savings,<1,2.0,male single,none,3.0,car,25.0,bank,own,3.0,skilled,1.0,none,yes,good +0<=X<200,24.0,existing paid,used car,12579.0,<100,>=7,4.0,female div/dep/mar,none,2.0,no known property,44.0,none,for free,1.0,high qualif/self emp/mgmt,1.0,yes,yes,bad +no checking,24.0,existing paid,radio/tv,3430.0,500<=X<1000,>=7,3.0,male single,none,2.0,car,31.0,none,own,1.0,skilled,2.0,yes,yes,good +no checking,9.0,critical/other existing credit,new car,2134.0,<100,1<=X<4,4.0,male single,none,4.0,car,48.0,none,own,3.0,skilled,1.0,yes,yes,good +<0,6.0,existing paid,radio/tv,2647.0,500<=X<1000,1<=X<4,2.0,male single,none,3.0,real estate,44.0,none,rent,1.0,skilled,2.0,none,yes,good +<0,10.0,critical/other existing credit,new car,2241.0,<100,<1,1.0,male single,none,3.0,real estate,48.0,none,rent,2.0,unskilled resident,2.0,none,no,good +0<=X<200,12.0,critical/other existing credit,used car,1804.0,100<=X<500,<1,3.0,male single,none,4.0,life insurance,44.0,none,own,1.0,skilled,1.0,none,yes,good +no checking,10.0,critical/other existing credit,furniture/equipment,2069.0,no known savings,1<=X<4,2.0,male mar/wid,none,1.0,car,26.0,none,own,2.0,skilled,1.0,none,no,good +<0,6.0,existing paid,furniture/equipment,1374.0,<100,1<=X<4,1.0,male single,none,2.0,real estate,36.0,bank,own,1.0,unskilled resident,1.0,yes,yes,good +no checking,6.0,no credits/all paid,radio/tv,426.0,<100,>=7,4.0,male mar/wid,none,4.0,car,39.0,none,own,1.0,unskilled resident,1.0,none,yes,good +>=200,12.0,all paid,radio/tv,409.0,>=1000,1<=X<4,3.0,female div/dep/mar,none,3.0,real estate,42.0,none,rent,2.0,skilled,1.0,none,yes,good +0<=X<200,7.0,existing paid,radio/tv,2415.0,<100,1<=X<4,3.0,male single,guarantor,2.0,real estate,34.0,none,own,1.0,skilled,1.0,none,yes,good +<0,60.0,delayed previously,business,6836.0,<100,>=7,3.0,male single,none,4.0,no known property,63.0,none,own,2.0,skilled,1.0,yes,yes,bad +0<=X<200,18.0,existing paid,business,1913.0,>=1000,<1,3.0,male mar/wid,none,3.0,real estate,36.0,bank,own,1.0,skilled,1.0,yes,yes,good +<0,24.0,existing paid,furniture/equipment,4020.0,<100,1<=X<4,2.0,male single,none,2.0,car,27.0,stores,own,1.0,skilled,1.0,none,yes,good +0<=X<200,18.0,existing paid,new car,5866.0,100<=X<500,1<=X<4,2.0,male single,none,2.0,car,30.0,none,own,2.0,skilled,1.0,yes,yes,good +no checking,12.0,critical/other existing credit,business,1264.0,no known savings,>=7,4.0,male single,none,4.0,no known property,57.0,none,rent,1.0,unskilled resident,1.0,none,yes,good +>=200,12.0,existing paid,furniture/equipment,1474.0,<100,<1,4.0,female div/dep/mar,none,1.0,life insurance,33.0,bank,own,1.0,high qualif/self emp/mgmt,1.0,yes,yes,good +0<=X<200,45.0,critical/other existing credit,radio/tv,4746.0,<100,<1,4.0,male single,none,2.0,life insurance,25.0,none,own,2.0,unskilled resident,1.0,none,yes,bad +no checking,48.0,critical/other existing credit,education,6110.0,<100,1<=X<4,1.0,male single,none,3.0,no known property,31.0,bank,for free,1.0,skilled,1.0,yes,yes,good +>=200,18.0,existing paid,radio/tv,2100.0,<100,1<=X<4,4.0,male single,co applicant,2.0,real estate,37.0,stores,own,1.0,skilled,1.0,none,yes,bad +>=200,10.0,existing paid,domestic appliance,1225.0,<100,1<=X<4,2.0,male single,none,2.0,car,37.0,none,own,1.0,skilled,1.0,yes,yes,good +0<=X<200,9.0,existing paid,radio/tv,458.0,<100,1<=X<4,4.0,male single,none,3.0,real estate,24.0,none,own,1.0,skilled,1.0,none,yes,good +no checking,30.0,existing paid,radio/tv,2333.0,500<=X<1000,>=7,4.0,male single,none,2.0,car,30.0,bank,own,1.0,high qualif/self emp/mgmt,1.0,none,yes,good +0<=X<200,12.0,existing paid,radio/tv,1158.0,500<=X<1000,1<=X<4,3.0,male div/sep,none,1.0,car,26.0,none,own,1.0,skilled,1.0,yes,yes,good +0<=X<200,18.0,delayed previously,repairs,6204.0,<100,1<=X<4,2.0,male single,none,4.0,real estate,44.0,none,own,1.0,unskilled resident,2.0,yes,yes,good +<0,30.0,critical/other existing credit,used car,6187.0,100<=X<500,4<=X<7,1.0,male mar/wid,none,4.0,car,24.0,none,rent,2.0,skilled,1.0,none,yes,good +<0,48.0,critical/other existing credit,used car,6143.0,<100,>=7,4.0,female div/dep/mar,none,4.0,no known property,58.0,stores,for free,2.0,unskilled resident,1.0,none,yes,bad +no checking,11.0,critical/other existing credit,new car,1393.0,<100,<1,4.0,female div/dep/mar,none,4.0,car,35.0,none,own,2.0,high qualif/self emp/mgmt,1.0,none,yes,good +no checking,36.0,existing paid,radio/tv,2299.0,500<=X<1000,>=7,4.0,male single,none,4.0,car,39.0,none,own,1.0,skilled,1.0,none,yes,good +<0,6.0,existing paid,used car,1352.0,500<=X<1000,unemployed,1.0,female div/dep/mar,none,2.0,life insurance,23.0,none,rent,1.0,unemp/unskilled non res,1.0,yes,yes,good +no checking,11.0,critical/other existing credit,new car,7228.0,<100,1<=X<4,1.0,male single,none,4.0,life insurance,39.0,none,own,2.0,unskilled resident,1.0,none,yes,good +no checking,12.0,existing paid,radio/tv,2073.0,100<=X<500,1<=X<4,4.0,female div/dep/mar,co applicant,2.0,real estate,28.0,none,own,1.0,skilled,1.0,none,yes,good +0<=X<200,24.0,delayed previously,furniture/equipment,2333.0,no known savings,<1,4.0,male single,none,2.0,life insurance,29.0,bank,own,1.0,unskilled resident,1.0,none,yes,good +0<=X<200,27.0,delayed previously,used car,5965.0,<100,>=7,1.0,male single,none,2.0,car,30.0,none,own,2.0,high qualif/self emp/mgmt,1.0,yes,yes,good +no checking,12.0,existing paid,radio/tv,1262.0,<100,1<=X<4,3.0,male single,none,2.0,car,25.0,none,own,1.0,skilled,1.0,none,yes,good +no checking,18.0,existing paid,used car,3378.0,no known savings,1<=X<4,2.0,male single,none,1.0,life insurance,31.0,none,own,1.0,skilled,1.0,yes,yes,good +0<=X<200,36.0,delayed previously,new car,2225.0,<100,>=7,4.0,male single,none,4.0,no known property,57.0,bank,for free,2.0,skilled,1.0,yes,yes,bad +no checking,6.0,all paid,new car,783.0,no known savings,1<=X<4,1.0,male single,guarantor,2.0,real estate,26.0,stores,own,1.0,unskilled resident,2.0,none,yes,good +0<=X<200,12.0,existing paid,radio/tv,6468.0,no known savings,unemployed,2.0,male single,none,1.0,no known property,52.0,none,own,1.0,high qualif/self emp/mgmt,1.0,yes,yes,bad +no checking,36.0,critical/other existing credit,radio/tv,9566.0,<100,1<=X<4,2.0,female div/dep/mar,none,2.0,car,31.0,stores,own,2.0,skilled,1.0,none,yes,good +>=200,18.0,existing paid,new car,1961.0,<100,>=7,3.0,female div/dep/mar,none,2.0,car,23.0,none,own,1.0,high qualif/self emp/mgmt,1.0,none,yes,good +<0,36.0,critical/other existing credit,furniture/equipment,6229.0,<100,<1,4.0,female div/dep/mar,co applicant,4.0,no known property,23.0,none,rent,2.0,unskilled resident,1.0,yes,yes,bad +0<=X<200,9.0,existing paid,business,1391.0,<100,1<=X<4,2.0,male mar/wid,none,1.0,real estate,27.0,bank,own,1.0,skilled,1.0,yes,yes,good +0<=X<200,15.0,critical/other existing credit,radio/tv,1537.0,no known savings,>=7,4.0,male single,guarantor,4.0,real estate,50.0,none,own,2.0,skilled,1.0,yes,yes,good +0<=X<200,36.0,no credits/all paid,business,1953.0,<100,>=7,4.0,male single,none,4.0,no known property,61.0,none,for free,1.0,high qualif/self emp/mgmt,1.0,yes,yes,bad +0<=X<200,48.0,no credits/all paid,business,14421.0,<100,1<=X<4,2.0,male single,none,2.0,car,25.0,none,own,1.0,skilled,1.0,yes,yes,bad +no checking,24.0,existing paid,radio/tv,3181.0,<100,<1,4.0,female div/dep/mar,none,4.0,life insurance,26.0,none,own,1.0,skilled,1.0,yes,yes,good +no checking,27.0,existing paid,repairs,5190.0,no known savings,>=7,4.0,male single,none,4.0,life insurance,48.0,none,own,4.0,skilled,2.0,yes,yes,good +no checking,12.0,existing paid,radio/tv,2171.0,<100,<1,2.0,female div/dep/mar,none,2.0,car,29.0,bank,own,1.0,skilled,1.0,none,yes,good +0<=X<200,12.0,existing paid,new car,1007.0,>=1000,1<=X<4,4.0,male mar/wid,none,1.0,real estate,22.0,none,own,1.0,skilled,1.0,none,yes,good +no checking,36.0,existing paid,education,1819.0,<100,1<=X<4,4.0,male single,none,4.0,no known property,37.0,stores,for free,1.0,skilled,1.0,yes,yes,bad +no checking,36.0,existing paid,radio/tv,2394.0,no known savings,1<=X<4,4.0,female div/dep/mar,none,4.0,car,25.0,none,own,1.0,skilled,1.0,none,yes,good +no checking,36.0,existing paid,used car,8133.0,<100,1<=X<4,1.0,female div/dep/mar,none,2.0,life insurance,30.0,bank,own,1.0,skilled,1.0,none,yes,good +no checking,7.0,critical/other existing credit,radio/tv,730.0,no known savings,>=7,4.0,male single,none,2.0,life insurance,46.0,none,rent,2.0,unskilled resident,1.0,yes,yes,good +<0,8.0,critical/other existing credit,other,1164.0,<100,>=7,3.0,male single,none,4.0,no known property,51.0,bank,for free,2.0,high qualif/self emp/mgmt,2.0,yes,yes,good +0<=X<200,42.0,critical/other existing credit,business,5954.0,<100,4<=X<7,2.0,female div/dep/mar,none,1.0,real estate,41.0,bank,own,2.0,unskilled resident,1.0,none,yes,good +<0,36.0,existing paid,education,1977.0,no known savings,>=7,4.0,male single,none,4.0,no known property,40.0,none,own,1.0,high qualif/self emp/mgmt,1.0,yes,yes,bad +<0,12.0,critical/other existing credit,used car,1526.0,<100,>=7,4.0,male single,none,4.0,no known property,66.0,none,for free,2.0,high qualif/self emp/mgmt,1.0,none,yes,good +<0,42.0,existing paid,radio/tv,3965.0,<100,<1,4.0,male single,none,3.0,car,34.0,none,own,1.0,skilled,1.0,none,yes,bad +0<=X<200,11.0,delayed previously,radio/tv,4771.0,<100,4<=X<7,2.0,male single,none,4.0,life insurance,51.0,none,own,1.0,skilled,1.0,none,yes,good +no checking,54.0,no credits/all paid,used car,9436.0,no known savings,1<=X<4,2.0,male single,none,2.0,life insurance,39.0,none,own,1.0,unskilled resident,2.0,none,yes,good +0<=X<200,30.0,existing paid,furniture/equipment,3832.0,<100,<1,2.0,male mar/wid,none,1.0,life insurance,22.0,none,own,1.0,skilled,1.0,none,yes,good +no checking,24.0,existing paid,radio/tv,5943.0,no known savings,<1,1.0,female div/dep/mar,none,1.0,car,44.0,none,own,2.0,skilled,1.0,yes,yes,bad +no checking,15.0,existing paid,radio/tv,1213.0,500<=X<1000,>=7,4.0,male single,none,3.0,life insurance,47.0,stores,own,1.0,skilled,1.0,yes,yes,good +no checking,18.0,existing paid,business,1568.0,100<=X<500,1<=X<4,3.0,female div/dep/mar,none,4.0,life insurance,24.0,none,rent,1.0,unskilled resident,1.0,none,yes,good +<0,24.0,existing paid,other,1755.0,<100,>=7,4.0,female div/dep/mar,guarantor,4.0,real estate,58.0,none,own,1.0,unskilled resident,1.0,yes,yes,good +<0,10.0,existing paid,radio/tv,2315.0,<100,>=7,3.0,male single,none,4.0,real estate,52.0,none,own,1.0,unskilled resident,1.0,none,yes,good +no checking,12.0,critical/other existing credit,business,1412.0,<100,1<=X<4,4.0,female div/dep/mar,guarantor,2.0,real estate,29.0,none,own,2.0,high qualif/self emp/mgmt,1.0,yes,yes,good +0<=X<200,18.0,critical/other existing credit,furniture/equipment,1295.0,<100,<1,4.0,female div/dep/mar,none,1.0,life insurance,27.0,none,own,2.0,skilled,1.0,none,yes,good +0<=X<200,36.0,existing paid,education,12612.0,100<=X<500,1<=X<4,1.0,male single,none,4.0,no known 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b/tests/test_js_parity.py new file mode 100644 index 0000000..ca82f7d --- /dev/null +++ b/tests/test_js_parity.py @@ -0,0 +1,52 @@ +"""Parity tests between the Python and JavaScript profiler implementations.""" + +from pathlib import Path +import json +import subprocess + +import pandas as pd +import pytest + +from faircode import profile + +FIXTURES = Path(__file__).resolve().parent / "fixtures" + + +@pytest.mark.parametrize( + "csv_name", + [ + "small.csv", + "adult.csv", + "compas-scores-raw.csv", + "credit_customers.csv", + "AI_Fair_Recruitment_Dataset.csv", + ], +) +def test_python_js_profiler_parity(csv_name): + """The Python and JavaScript profilers should produce equivalent structured JSON.""" + + csv = FIXTURES / csv_name + + python_result = profile(pd.read_csv(csv)) + + completed = subprocess.run( + ["node", "scripts/profile-js.js", str(csv)], + capture_output=True, + text=True, + encoding="utf-8", + check=True, + ) + + javascript_result = json.loads(completed.stdout) + + # Flags are human-readable messages. They duplicate information already + # present in the structured output and may differ because Python and + # JavaScript format floating-point values differently (e.g. 6.25 -> 6.2 + # vs 6.3). Compare the structured data instead. + python_result = dict(python_result) + javascript_result = dict(javascript_result) + + python_result.pop("flags", None) + javascript_result.pop("flags", None) + + assert javascript_result == python_result